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bigcomputer
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kaggle-notebooks-outputs-filtered-21

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train · ~8.02k rows (showing the first 4.72k)

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text stringlengths 2.76k 92.6M	id stringlengths 23 24	file_path stringclasses 49 values
{ "cells": [ { "cell_type": "markdown", "id": "bd2da987", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T14:14:55.524238Z", "iopub.status.busy": "2022-10-27T14:14:55.522989Z", "iopub.status.idle": "2022-10-27T14:14:55.532508Z", "shell.execute_reply": "2022-10-27T14:14:55.530678Z", "shell.execute_reply.started": "2022-10-27T14:14:55.524196Z" }, "papermill": { "duration": 0.012476, "end_time": "2022-10-27T19:14:34.366444", "exception": false, "start_time": "2022-10-27T19:14:34.353968", "status": "completed" }, "tags": [] }, "source": [ "# Optimal threshold searching.\n", "\n", " In this notebook, I wanted to show, that we can improve our model performance if we change only our threshold. Also, there is no super metric that will be suited for every task and it's important to understand the next steps when we are working on a real task. \n", "I didn't pay a lot of attention to data cleaning or stratified sampling and built only a logistic regression model. But before coding a short theoretical brief about classification evaluation metrics." ] }, { "cell_type": "markdown", "id": "42715e0a", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T17:35:11.076901Z", "iopub.status.busy": "2022-10-27T17:35:11.076540Z", "iopub.status.idle": "2022-10-27T17:35:11.081517Z", "shell.execute_reply": "2022-10-27T17:35:11.080571Z", "shell.execute_reply.started": "2022-10-27T17:35:11.076873Z" }, "papermill": { "duration": 0.010195, "end_time": "2022-10-27T19:14:34.387753", "exception": false, "start_time": "2022-10-27T19:14:34.377558", "status": "completed" }, "tags": [] }, "source": [ "## Confusion matrix \n", "A confusion matrix is a table that is used to define the performance of a classification algorithm. A confusion matrix visualizes and summarizes the performance of a classification algorithm." ] }, { "attachments": { "b7da9466-0632-4048-b346-23351eb5b274.png": { "image/png": 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" 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" 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" } }, "cell_type": "markdown", "id": "feaa5f4e", "metadata": { "papermill": { "duration": 0.010385, "end_time": "2022-10-27T19:14:34.431391", "exception": false, "start_time": "2022-10-27T19:14:34.421006", "status": "completed" }, "tags": [] }, "source": [ "We have an imbalanced data set with two classes - \n", "* majority class (class 0)\n", "* minority class (class 1)\n", "\n", "Let's calculate evaluation metrics for this confusion matrix.\n", "* \n", " * Total samples: 670\n", " * Accuracy: (TP + TN) / Total = 610/670 = 0.91\n", " * Precision: TP / (TP + FP) = 60/80 = 0.75\n", " * Recall: TP / (TP + FN) = 60/100 = 0.6\n", "\n", "Precision gives a measure of how many minority class predictions actually belong to the minority class. \n", "Recall or Sensitivity gives a measure of how many observations from the minority class are actually labeled correctly.\n", "\n", " F1 score: 2 * Precision * Recall / (Precision + Recall) = 2 * 0.75 * 0.6 / (0.75 + 0.6) = 0.67 \n", " \n", "F1 score - weighted harmonic mean of precision and recall\n", "\n", " TNR: TN / (TN + FP) = 550 / (550 + 20) = 0.96 \n", "True Negative Rate (TNR) or Specificity gives a measure of how many observations from the majority class are actually labeled correctly. (the same as recall but for majority class)\n", "\n", " Balanced Accuracy: (Recall + TNR)/2 = (0.6 + 0.96) / 2 = 0.78 \n", "Balanced Accuracy is the arithmetic mean of Recall and True Negative Rate (Sensitivity and Specificity )\n", "\n", " G-mean: sqrt(Recall * Specificity) = sqrt(0.6 * 0.96) = 0.76 \n", "G-mean is the Geometric Mean of Recall and True Negative Rate (Sensitivity and Specificity )\n", "\n", "### ROC Curve\n", "\n", "ROC curve is used to show in a graphical way the connection/trade-off between sensitivity (or Recall or True Positive Rate) and specificity (True Negative Rate) for every possible threshold.\n", "* x-axis - FPR\n", "* y-axis - TPR\n", "\n", "AUC - area under curve. \n", "NOTE: AUC is independent of the classification threshold. It measures the quality of model predictions, so we can use AUC for comparing different models. \n", "Let's see what the ideal situation looks like. We have two classes that do not overlap anywhere and before threshold = 0.5 we have only negative samples and after threshold only positive samples. You can see it in the chart below (I took them from [here](https://towardsdatascience.com/understanding-auc-roc-curve-68b2303cc9c5), great article): \n", "![image.png](attachment:cd0033f9-774f-4cfe-bce9-437dffb9ff6f.png) \n", "But usually, we have some mistakes in predictions and our charts will be overlapped. By the way - there are two types of mistakes:\n", "1. Type I error (false positive)\n", "2. Type II error (false negative) \n", "Let's see how it looks on the chart\n", "\n", "![image.png](attachment:e981ec2d-8281-4e3e-818e-d7bc21984f4b.png) \n", "If we move our threshold to 0.75 all negative class samples will be correctly labeled, but we will have a lot of mistakes in positive class samples, which means that our False Negative value (Type II errors) will increase. Our task is to find a threshold that would suit us for a specific task. Let's do it.\n", "\n" ] }, { "cell_type": "code", "execution_count": 1, "id": "24b2fdb5", "metadata": { "_kg_hide-input": true, "execution": { "iopub.execute_input": "2022-10-27T19:14:34.457331Z", "iopub.status.busy": "2022-10-27T19:14:34.456260Z", "iopub.status.idle": "2022-10-27T19:14:36.144985Z", "shell.execute_reply": "2022-10-27T19:14:36.143874Z" }, "papermill": { "duration": 1.705808, "end_time": "2022-10-27T19:14:36.147707", "exception": false, "start_time": "2022-10-27T19:14:34.441899", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "/kaggle/input/creditcardfraud/creditcard.csv\n" ] } ], "source": [ "import pandas as pd\n", "import numpy as np\n", "import scipy.stats as stats\n", "from sklearn.model_selection import train_test_split\n", "from sklearn.preprocessing import PowerTransformer\n", "from sklearn.linear_model import LogisticRegression\n", "from sklearn import metrics\n", "from sklearn.metrics import roc_curve, precision_recall_curve, confusion_matrix\n", "from sklearn.metrics import precision_score, recall_score, roc_auc_score, f1_score\n", "\n", "import matplotlib.pyplot as plt\n", "import matplotlib.backends.backend_pdf\n", "import seaborn as sns\n", "\n", "import os\n", "for dirname, _, filenames in os.walk('/kaggle/input'):\n", " for filename in filenames:\n", " print(os.path.join(dirname, filename))" ] }, { "cell_type": "markdown", "id": "22c4aab6", "metadata": { "papermill": { "duration": 0.010365, "end_time": "2022-10-27T19:14:36.168938", "exception": false, "start_time": "2022-10-27T19:14:36.158573", "status": "completed" }, "tags": [] }, "source": [ "#### 1. Read data" ] }, { "cell_type": "code", "execution_count": 2, "id": "4c46b7b8", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:14:36.192703Z", "iopub.status.busy": "2022-10-27T19:14:36.192080Z", "iopub.status.idle": "2022-10-27T19:14:41.158828Z", "shell.execute_reply": "2022-10-27T19:14:41.157489Z" }, "papermill": { "duration": 4.981911, "end_time": "2022-10-27T19:14:41.161674", "exception": false, "start_time": "2022-10-27T19:14:36.179763", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>Time</th>\n", " <th>V1</th>\n", " <th>V2</th>\n", " <th>V3</th>\n", " <th>V4</th>\n", " <th>V5</th>\n", " <th>V6</th>\n", " <th>V7</th>\n", " <th>V8</th>\n", " <th>V9</th>\n", " <th>...</th>\n", " <th>V21</th>\n", " <th>V22</th>\n", " <th>V23</th>\n", " <th>V24</th>\n", " <th>V25</th>\n", " <th>V26</th>\n", " <th>V27</th>\n", " <th>V28</th>\n", " <th>Amount</th>\n", " <th>Class</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>0</th>\n", " <td>0.0</td>\n", " <td>-1.359807</td>\n", " <td>-0.072781</td>\n", " <td>2.536347</td>\n", " <td>1.378155</td>\n", " <td>-0.338321</td>\n", " <td>0.462388</td>\n", " <td>0.239599</td>\n", " <td>0.098698</td>\n", " <td>0.363787</td>\n", " <td>...</td>\n", " <td>-0.018307</td>\n", " <td>0.277838</td>\n", " <td>-0.110474</td>\n", " <td>0.066928</td>\n", " <td>0.128539</td>\n", " <td>-0.189115</td>\n", " <td>0.133558</td>\n", " <td>-0.021053</td>\n", " <td>149.62</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>0.0</td>\n", " <td>1.191857</td>\n", " <td>0.266151</td>\n", " <td>0.166480</td>\n", " <td>0.448154</td>\n", " <td>0.060018</td>\n", " <td>-0.082361</td>\n", " <td>-0.078803</td>\n", " <td>0.085102</td>\n", " <td>-0.255425</td>\n", " <td>...</td>\n", " <td>-0.225775</td>\n", " <td>-0.638672</td>\n", " <td>0.101288</td>\n", " <td>-0.339846</td>\n", " <td>0.167170</td>\n", " <td>0.125895</td>\n", " <td>-0.008983</td>\n", " <td>0.014724</td>\n", " <td>2.69</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>2</th>\n", " <td>1.0</td>\n", " <td>-1.358354</td>\n", " <td>-1.340163</td>\n", " <td>1.773209</td>\n", " <td>0.379780</td>\n", " <td>-0.503198</td>\n", " <td>1.800499</td>\n", " <td>0.791461</td>\n", " <td>0.247676</td>\n", " <td>-1.514654</td>\n", " <td>...</td>\n", " <td>0.247998</td>\n", " <td>0.771679</td>\n", " <td>0.909412</td>\n", " <td>-0.689281</td>\n", " <td>-0.327642</td>\n", " <td>-0.139097</td>\n", " <td>-0.055353</td>\n", " <td>-0.059752</td>\n", " <td>378.66</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>3</th>\n", " <td>1.0</td>\n", " <td>-0.966272</td>\n", " <td>-0.185226</td>\n", " <td>1.792993</td>\n", " <td>-0.863291</td>\n", " <td>-0.010309</td>\n", " <td>1.247203</td>\n", " <td>0.237609</td>\n", " <td>0.377436</td>\n", " <td>-1.387024</td>\n", " <td>...</td>\n", " <td>-0.108300</td>\n", " <td>0.005274</td>\n", " <td>-0.190321</td>\n", " <td>-1.175575</td>\n", " <td>0.647376</td>\n", " <td>-0.221929</td>\n", " <td>0.062723</td>\n", " <td>0.061458</td>\n", " <td>123.50</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>4</th>\n", " <td>2.0</td>\n", " <td>-1.158233</td>\n", " <td>0.877737</td>\n", " <td>1.548718</td>\n", " <td>0.403034</td>\n", " <td>-0.407193</td>\n", " <td>0.095921</td>\n", " <td>0.592941</td>\n", " <td>-0.270533</td>\n", " <td>0.817739</td>\n", " <td>...</td>\n", " <td>-0.009431</td>\n", " <td>0.798278</td>\n", " <td>-0.137458</td>\n", " <td>0.141267</td>\n", " <td>-0.206010</td>\n", " <td>0.502292</td>\n", " <td>0.219422</td>\n", " <td>0.215153</td>\n", " <td>69.99</td>\n", " <td>0</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "<p>5 rows × 31 columns</p>\n", "</div>" ], "text/plain": [ " Time V1 V2 V3 V4 V5 V6 V7 \\\n", "0 0.0 -1.359807 -0.072781 2.536347 1.378155 -0.338321 0.462388 0.239599 \n", "1 0.0 1.191857 0.266151 0.166480 0.448154 0.060018 -0.082361 -0.078803 \n", "2 1.0 -1.358354 -1.340163 1.773209 0.379780 -0.503198 1.800499 0.791461 \n", "3 1.0 -0.966272 -0.185226 1.792993 -0.863291 -0.010309 1.247203 0.237609 \n", "4 2.0 -1.158233 0.877737 1.548718 0.403034 -0.407193 0.095921 0.592941 \n", "\n", " V8 V9 ... V21 V22 V23 V24 V25 \\\n", "0 0.098698 0.363787 ... -0.018307 0.277838 -0.110474 0.066928 0.128539 \n", "1 0.085102 -0.255425 ... -0.225775 -0.638672 0.101288 -0.339846 0.167170 \n", "2 0.247676 -1.514654 ... 0.247998 0.771679 0.909412 -0.689281 -0.327642 \n", "3 0.377436 -1.387024 ... -0.108300 0.005274 -0.190321 -1.175575 0.647376 \n", "4 -0.270533 0.817739 ... -0.009431 0.798278 -0.137458 0.141267 -0.206010 \n", "\n", " V26 V27 V28 Amount Class \n", "0 -0.189115 0.133558 -0.021053 149.62 0 \n", "1 0.125895 -0.008983 0.014724 2.69 0 \n", "2 -0.139097 -0.055353 -0.059752 378.66 0 \n", "3 -0.221929 0.062723 0.061458 123.50 0 \n", "4 0.502292 0.219422 0.215153 69.99 0 \n", "\n", "[5 rows x 31 columns]" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df = pd.read_csv(\"../input/creditcardfraud/creditcard.csv\")\n", "df.head()" ] }, { "cell_type": "markdown", "id": "9810a336", "metadata": { "papermill": { "duration": 0.011074, "end_time": "2022-10-27T19:14:41.184743", "exception": false, "start_time": "2022-10-27T19:14:41.173669", "status": "completed" }, "tags": [] }, "source": [ "#### 2. Checking the target classes" ] }, { "cell_type": "code", "execution_count": 3, "id": "31570405", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:14:41.209047Z", "iopub.status.busy": "2022-10-27T19:14:41.208644Z", "iopub.status.idle": "2022-10-27T19:14:41.226360Z", "shell.execute_reply": "2022-10-27T19:14:41.224803Z" }, "papermill": { "duration": 0.033336, "end_time": "2022-10-27T19:14:41.229415", "exception": false, "start_time": "2022-10-27T19:14:41.196079", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "Proportion: 577.876:1\n", "Class 0: 284315\n", "Class 1: 492\n" ] } ], "source": [ "print('')\n", "target_count = df['Class'].value_counts()\n", "print(f'Proportion: {target_count[0] / target_count[1] :.3f}:1')\n", "print(f'Class 0: {target_count[0]}')\n", "print(f'Class 1: {target_count[1]}')" ] }, { "cell_type": "markdown", "id": "479ad29a", "metadata": { "papermill": { "duration": 0.010747, "end_time": "2022-10-27T19:14:41.251466", "exception": false, "start_time": "2022-10-27T19:14:41.240719", "status": "completed" }, "tags": [] }, "source": [ "#### 3. Train-test split" ] }, { "cell_type": "code", "execution_count": 4, "id": "cf56fa44", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:14:41.275182Z", "iopub.status.busy": "2022-10-27T19:14:41.274752Z", "iopub.status.idle": "2022-10-27T19:14:41.506030Z", "shell.execute_reply": "2022-10-27T19:14:41.504696Z" }, "papermill": { "duration": 0.246882, "end_time": "2022-10-27T19:14:41.509386", "exception": false, "start_time": "2022-10-27T19:14:41.262504", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "((227845, 29), (56962, 29))" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "X_train, X_test, y_train, y_test = train_test_split(\n", " df.drop(labels=['Time', 'Class'], axis=1), # drop the target\n", " df['Class'], # just the target\n", " test_size=0.2,\n", " stratify=df['Class'],\n", " random_state=0)\n", "\n", "X_train.shape, X_test.shape" ] }, { "cell_type": "markdown", "id": "5ac96ae3", "metadata": { "papermill": { "duration": 0.014515, "end_time": "2022-10-27T19:14:41.535524", "exception": false, "start_time": "2022-10-27T19:14:41.521009", "status": "completed" }, "tags": [] }, "source": [ "Checking a minority class proportion in train and test sets." ] }, { "cell_type": "code", "execution_count": 5, "id": "eb507c19", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:14:41.564101Z", "iopub.status.busy": "2022-10-27T19:14:41.562675Z", "iopub.status.idle": "2022-10-27T19:14:41.598617Z", "shell.execute_reply": "2022-10-27T19:14:41.597154Z" }, "papermill": { "duration": 0.053011, "end_time": "2022-10-27T19:14:41.601295", "exception": false, "start_time": "2022-10-27T19:14:41.548284", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "y_train: 0.0017 \n", "y_test: 0.0017\n" ] } ], "source": [ "print(f'y_train: {sum(y_train)/len(y_train):.4f} \\ny_test: {sum(y_test)/len(y_test):.4f}')" ] }, { "cell_type": "markdown", "id": "44369209", "metadata": { "papermill": { "duration": 0.0138, "end_time": "2022-10-27T19:14:41.626601", "exception": false, "start_time": "2022-10-27T19:14:41.612801", "status": "completed" }, "tags": [] }, "source": [ "#### 4. Variable transformation" ] }, { "cell_type": "code", "execution_count": 6, "id": "c7a8f65b", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:14:41.652375Z", "iopub.status.busy": "2022-10-27T19:14:41.651868Z", "iopub.status.idle": "2022-10-27T19:14:42.071665Z", "shell.execute_reply": "2022-10-27T19:14:42.070404Z" }, "papermill": { "duration": 0.436559, "end_time": "2022-10-27T19:14:42.074513", "exception": false, "start_time": "2022-10-27T19:14:41.637954", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>V1</th>\n", " <th>V2</th>\n", " <th>V3</th>\n", " <th>V4</th>\n", " <th>V5</th>\n", " <th>V6</th>\n", " <th>V7</th>\n", " <th>V8</th>\n", " <th>V9</th>\n", " <th>V10</th>\n", " <th>...</th>\n", " <th>V20</th>\n", " <th>V21</th>\n", " <th>V22</th>\n", " <th>V23</th>\n", " <th>V24</th>\n", " <th>V25</th>\n", " <th>V26</th>\n", " <th>V27</th>\n", " <th>V28</th>\n", " <th>Amount</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>count</th>\n", " <td>227845.000000</td>\n", " <td>227845.000000</td>\n", " <td>227845.000000</td>\n", " <td>227845.000000</td>\n", " <td>227845.000000</td>\n", " <td>227845.000000</td>\n", " <td>227845.000000</td>\n", " <td>227845.000000</td>\n", " <td>227845.000000</td>\n", " <td>227845.000000</td>\n", " <td>...</td>\n", " <td>227845.000000</td>\n", " <td>227845.000000</td>\n", " <td>227845.000000</td>\n", " <td>227845.000000</td>\n", " <td>227845.000000</td>\n", " <td>227845.000000</td>\n", " <td>227845.000000</td>\n", " <td>227845.000000</td>\n", " <td>227845.000000</td>\n", " <td>227845.000000</td>\n", " </tr>\n", " <tr>\n", " <th>mean</th>\n", " <td>-0.003321</td>\n", " <td>-0.001652</td>\n", " <td>0.001066</td>\n", " <td>-0.000374</td>\n", " <td>0.000877</td>\n", " <td>0.000770</td>\n", " <td>-0.000035</td>\n", " <td>0.001625</td>\n", " <td>-0.000391</td>\n", " <td>-0.000794</td>\n", " <td>...</td>\n", " <td>0.000671</td>\n", " <td>0.000563</td>\n", " <td>0.001234</td>\n", " <td>-0.001002</td>\n", " <td>0.000254</td>\n", " <td>0.000218</td>\n", " <td>-0.001128</td>\n", " <td>-0.000346</td>\n", " <td>0.000498</td>\n", " <td>88.522327</td>\n", " </tr>\n", " <tr>\n", " <th>std</th>\n", " <td>1.963028</td>\n", " <td>1.661178</td>\n", " <td>1.516107</td>\n", " <td>1.415061</td>\n", " <td>1.367074</td>\n", " <td>1.325341</td>\n", " <td>1.220384</td>\n", " <td>1.192648</td>\n", " <td>1.097367</td>\n", " <td>1.087268</td>\n", " <td>...</td>\n", " <td>0.772535</td>\n", " <td>0.734187</td>\n", " <td>0.724544</td>\n", " <td>0.625165</td>\n", " <td>0.606012</td>\n", " <td>0.521348</td>\n", " <td>0.482314</td>\n", " <td>0.400286</td>\n", " <td>0.331184</td>\n", " <td>248.100141</td>\n", " </tr>\n", " <tr>\n", " <th>min</th>\n", " <td>-56.407510</td>\n", " <td>-72.715728</td>\n", " <td>-32.965346</td>\n", " <td>-5.683171</td>\n", " <td>-42.147898</td>\n", " <td>-26.160506</td>\n", " <td>-43.557242</td>\n", " <td>-73.216718</td>\n", " <td>-13.434066</td>\n", " <td>-24.588262</td>\n", " <td>...</td>\n", " <td>-28.009635</td>\n", " <td>-34.830382</td>\n", " <td>-10.933144</td>\n", " <td>-44.807735</td>\n", " <td>-2.836627</td>\n", " <td>-10.295397</td>\n", " <td>-2.604551</td>\n", " <td>-22.565679</td>\n", " <td>-11.710896</td>\n", " <td>0.000000</td>\n", " </tr>\n", " <tr>\n", " <th>25%</th>\n", " <td>-0.922851</td>\n", " <td>-0.598040</td>\n", " <td>-0.889246</td>\n", " <td>-0.848884</td>\n", " <td>-0.690811</td>\n", " <td>-0.767803</td>\n", " <td>-0.554761</td>\n", " <td>-0.207838</td>\n", " <td>-0.643365</td>\n", " <td>-0.535584</td>\n", " <td>...</td>\n", " <td>-0.211753</td>\n", " <td>-0.228031</td>\n", " <td>-0.540792</td>\n", " <td>-0.162264</td>\n", " <td>-0.354099</td>\n", " <td>-0.317450</td>\n", " <td>-0.327910</td>\n", " <td>-0.070986</td>\n", " <td>-0.053117</td>\n", " <td>5.590000</td>\n", " </tr>\n", " <tr>\n", " <th>50%</th>\n", " <td>0.012663</td>\n", " <td>0.066665</td>\n", " <td>0.182170</td>\n", " <td>-0.019309</td>\n", " <td>-0.055243</td>\n", " <td>-0.273025</td>\n", " <td>0.040409</td>\n", " <td>0.022928</td>\n", " <td>-0.050932</td>\n", " <td>-0.092068</td>\n", " <td>...</td>\n", " <td>-0.062660</td>\n", " <td>-0.028807</td>\n", " <td>0.008697</td>\n", " <td>-0.011614</td>\n", " <td>0.041212</td>\n", " <td>0.016221</td>\n", " <td>-0.053257</td>\n", " <td>0.001315</td>\n", " <td>0.011216</td>\n", " <td>22.000000</td>\n", " </tr>\n", " <tr>\n", " <th>75%</th>\n", " <td>1.314821</td>\n", " <td>0.804401</td>\n", " <td>1.029449</td>\n", " <td>0.744822</td>\n", " <td>0.610852</td>\n", " <td>0.400298</td>\n", " <td>0.570631</td>\n", " <td>0.327854</td>\n", " <td>0.596671</td>\n", " <td>0.454152</td>\n", " <td>...</td>\n", " <td>0.133600</td>\n", " <td>0.186852</td>\n", " <td>0.529535</td>\n", " <td>0.147067</td>\n", " <td>0.440051</td>\n", " <td>0.351214</td>\n", " <td>0.239885</td>\n", " <td>0.091105</td>\n", " <td>0.078458</td>\n", " <td>77.070000</td>\n", " </tr>\n", " <tr>\n", " <th>max</th>\n", " <td>2.454930</td>\n", " <td>22.057729</td>\n", " <td>9.382558</td>\n", " <td>16.875344</td>\n", " <td>34.801666</td>\n", " <td>22.529298</td>\n", " <td>36.877368</td>\n", " <td>20.007208</td>\n", " <td>15.594995</td>\n", " <td>23.745136</td>\n", " <td>...</td>\n", " <td>39.420904</td>\n", " <td>27.202839</td>\n", " <td>10.503090</td>\n", " <td>22.528412</td>\n", " <td>4.022866</td>\n", " <td>6.070850</td>\n", " <td>3.463246</td>\n", " <td>12.152401</td>\n", " <td>33.847808</td>\n", " <td>19656.530000</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "<p>8 rows × 29 columns</p>\n", "</div>" ], "text/plain": [ " V1 V2 V3 V4 \\\n", "count 227845.000000 227845.000000 227845.000000 227845.000000 \n", "mean -0.003321 -0.001652 0.001066 -0.000374 \n", "std 1.963028 1.661178 1.516107 1.415061 \n", "min -56.407510 -72.715728 -32.965346 -5.683171 \n", "25% -0.922851 -0.598040 -0.889246 -0.848884 \n", "50% 0.012663 0.066665 0.182170 -0.019309 \n", "75% 1.314821 0.804401 1.029449 0.744822 \n", "max 2.454930 22.057729 9.382558 16.875344 \n", "\n", " V5 V6 V7 V8 \\\n", "count 227845.000000 227845.000000 227845.000000 227845.000000 \n", "mean 0.000877 0.000770 -0.000035 0.001625 \n", "std 1.367074 1.325341 1.220384 1.192648 \n", "min -42.147898 -26.160506 -43.557242 -73.216718 \n", "25% -0.690811 -0.767803 -0.554761 -0.207838 \n", "50% -0.055243 -0.273025 0.040409 0.022928 \n", "75% 0.610852 0.400298 0.570631 0.327854 \n", "max 34.801666 22.529298 36.877368 20.007208 \n", "\n", " V9 V10 ... V20 V21 \\\n", "count 227845.000000 227845.000000 ... 227845.000000 227845.000000 \n", "mean -0.000391 -0.000794 ... 0.000671 0.000563 \n", "std 1.097367 1.087268 ... 0.772535 0.734187 \n", "min -13.434066 -24.588262 ... -28.009635 -34.830382 \n", "25% -0.643365 -0.535584 ... -0.211753 -0.228031 \n", "50% -0.050932 -0.092068 ... -0.062660 -0.028807 \n", "75% 0.596671 0.454152 ... 0.133600 0.186852 \n", "max 15.594995 23.745136 ... 39.420904 27.202839 \n", "\n", " V22 V23 V24 V25 \\\n", "count 227845.000000 227845.000000 227845.000000 227845.000000 \n", "mean 0.001234 -0.001002 0.000254 0.000218 \n", "std 0.724544 0.625165 0.606012 0.521348 \n", "min -10.933144 -44.807735 -2.836627 -10.295397 \n", "25% -0.540792 -0.162264 -0.354099 -0.317450 \n", "50% 0.008697 -0.011614 0.041212 0.016221 \n", "75% 0.529535 0.147067 0.440051 0.351214 \n", "max 10.503090 22.528412 4.022866 6.070850 \n", "\n", " V26 V27 V28 Amount \n", "count 227845.000000 227845.000000 227845.000000 227845.000000 \n", "mean -0.001128 -0.000346 0.000498 88.522327 \n", "std 0.482314 0.400286 0.331184 248.100141 \n", "min -2.604551 -22.565679 -11.710896 0.000000 \n", "25% -0.327910 -0.070986 -0.053117 5.590000 \n", "50% -0.053257 0.001315 0.011216 22.000000 \n", "75% 0.239885 0.091105 0.078458 77.070000 \n", "max 3.463246 12.152401 33.847808 19656.530000 \n", "\n", "[8 rows x 29 columns]" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "X_train.describe()" ] }, { "cell_type": "markdown", "id": "aeac5489", "metadata": { "papermill": { "duration": 0.011567, "end_time": "2022-10-27T19:14:42.098083", "exception": false, "start_time": "2022-10-27T19:14:42.086516", "status": "completed" }, "tags": [] }, "source": [ "All features are less or equal to zero, so I'll use the Yeo-Johnson transformation for whole data set. \n", "Note! Yeo-Johnson transformations need to learn their parameters from the data. We should fit it only on the training set. It helps us to avoid overfitting. " ] }, { "cell_type": "code", "execution_count": 7, "id": "6ded4813", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:14:42.125035Z", "iopub.status.busy": "2022-10-27T19:14:42.124238Z", "iopub.status.idle": "2022-10-27T19:14:51.753890Z", "shell.execute_reply": "2022-10-27T19:14:51.752627Z" }, "papermill": { "duration": 9.646865, "end_time": "2022-10-27T19:14:51.757389", "exception": false, "start_time": "2022-10-27T19:14:42.110524", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "trans_cols = X_train.columns\n", "transformer = PowerTransformer(method='yeo-johnson', standardize=False)\n", "\n", "# learn the lambda from the train set\n", "transformer.fit(X_train[trans_cols])\n", "\n", "# transform the data\n", "X_train_transform = transformer.transform(X_train[trans_cols])\n", "X_test_transform = transformer.transform(X_test[trans_cols])\n", "\n", "# capture data in a dataframe\n", "X_train_transform = pd.DataFrame(X_train_transform, columns = trans_cols)\n", "X_test_transform = pd.DataFrame(X_test_transform, columns = trans_cols)" ] }, { "cell_type": "markdown", "id": "826e18e7", "metadata": { "papermill": { "duration": 0.011658, "end_time": "2022-10-27T19:14:51.781311", "exception": false, "start_time": "2022-10-27T19:14:51.769653", "status": "completed" }, "tags": [] }, "source": [ "Let's check distributions before and after transformation. For each feature I build a histogram and Q-Q plot (shows the distribution of the data against the expected normal distribution)." ] }, { "cell_type": "code", "execution_count": 8, "id": "989776ed", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:14:51.807861Z", "iopub.status.busy": "2022-10-27T19:14:51.807039Z", "iopub.status.idle": "2022-10-27T19:15:08.246506Z", "shell.execute_reply": "2022-10-27T19:15:08.245220Z" }, "papermill": { "duration": 16.455043, "end_time": "2022-10-27T19:15:08.248996", "exception": false, "start_time": "2022-10-27T19:14:51.793953", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 1296x360 with 4 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 1296x360 with 4 Axes>" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 1296x360 with 4 Axes>" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 1296x360 with 4 Axes>" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 1296x360 with 4 Axes>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "### Here I'll run it only for 5 columns because the output is very long\n", "for col in trans_cols[:5]:\n", " fig, axes = plt.subplots(1, 4, figsize=(18,5))\n", " sns.set_style(\"whitegrid\")\n", " \n", " sns.histplot(X_train[col], binwidth = 0.5, ax=axes[0])\n", " q = stats.probplot(X_train[col], dist=\"norm\", plot=axes[1])\n", " sns.histplot(X_train_transform[col], binwidth = 0.5, ax=axes[2])\n", " q = stats.probplot(X_train_transform[col], dist=\"norm\", plot=axes[3])\n", " \n", " axes[0].set_title(f'Histogram of {col}')\n", " axes[1].set_title(f'Q-Q plot, {col}')\n", " axes[2].set_title(f'Histogram of {col}(yeo-johnson)')\n", " axes[3].set_title(f'Q-Q plot, {col}(yeo-johnson)')" ] }, { "cell_type": "markdown", "id": "d351e1f6", "metadata": { "papermill": { "duration": 0.016618, "end_time": "2022-10-27T19:15:08.282463", "exception": false, "start_time": "2022-10-27T19:15:08.265845", "status": "completed" }, "tags": [] }, "source": [ "The transformation didn't work excellently for all features, but after transformation, the distribution has a better shape. Also, there are some features with outliers, but now I don't handle them. " ] }, { "cell_type": "markdown", "id": "ba342aa2", "metadata": { "papermill": { "duration": 0.016834, "end_time": "2022-10-27T19:15:08.316471", "exception": false, "start_time": "2022-10-27T19:15:08.299637", "status": "completed" }, "tags": [] }, "source": [ "#### 5. The best model searching (Logistic Regression)\n", "\n", "Let's build a simple regression model. We have an unbalanced data set, so it makes sense to use the class_weight parameter and regularization. For different values of the C parameter I'll fit a model and to compare different models with ROC-AUC and Precision-Recall-AUC scores. " ] }, { "cell_type": "code", "execution_count": 9, "id": "86f0331c", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:15:08.352582Z", "iopub.status.busy": "2022-10-27T19:15:08.352206Z", "iopub.status.idle": "2022-10-27T19:15:08.357395Z", "shell.execute_reply": "2022-10-27T19:15:08.356284Z" }, "papermill": { "duration": 0.026261, "end_time": "2022-10-27T19:15:08.359723", "exception": false, "start_time": "2022-10-27T19:15:08.333462", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "C_param = [1, 0.1, 0.01, 0.001, 0.0001]" ] }, { "cell_type": "code", "execution_count": 10, "id": "97c05dee", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:15:08.395966Z", "iopub.status.busy": "2022-10-27T19:15:08.394894Z", "iopub.status.idle": "2022-10-27T19:15:20.437618Z", "shell.execute_reply": "2022-10-27T19:15:20.436299Z" }, "papermill": { "duration": 12.063566, "end_time": "2022-10-27T19:15:20.440270", "exception": false, "start_time": "2022-10-27T19:15:08.376704", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "for C in C_param:\n", " clf = LogisticRegression(random_state=0, C=C, penalty='l2', class_weight='balanced')\n", " clf.fit(X_train_transform, y_train)\n", " y_pred = clf.predict(X_test_transform)\n", " fpr, tpr, _ = roc_curve(y_test, y_pred)\n", " auc = roc_auc_score(y_test, y_pred)\n", " plt.plot(fpr,tpr,label=f'C: {C}, auc={auc:.3f}')\n", "plt.ylabel('True Positive Rate')\n", "plt.xlabel('False Positive Rate')\n", "plt.title('ROC-AUC Curve')\n", "plt.legend(loc='lower right')\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "fa6df25a", "metadata": { "papermill": { "duration": 0.023267, "end_time": "2022-10-27T19:15:20.483154", "exception": false, "start_time": "2022-10-27T19:15:20.459887", "status": "completed" }, "tags": [] }, "source": [ "Next, we can perform an analysis of the same models and evaluate the same data using the precision-recall curve and AUC (area under curve) score." ] }, { "cell_type": "code", "execution_count": 11, "id": "7242078d", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:15:20.531832Z", "iopub.status.busy": "2022-10-27T19:15:20.531434Z", "iopub.status.idle": "2022-10-27T19:15:32.177919Z", "shell.execute_reply": "2022-10-27T19:15:32.176824Z" }, "papermill": { "duration": 11.67291, "end_time": "2022-10-27T19:15:32.180222", "exception": false, "start_time": "2022-10-27T19:15:20.507312", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "for C in C_param:\n", " clf = LogisticRegression(random_state=0, C=C, penalty='l2', class_weight='balanced')\n", " clf.fit(X_train_transform, y_train)\n", " y_pred_proba = clf.predict_proba(X_test_transform)[:, 1]\n", "\n", " precision, recall, treshold = precision_recall_curve(y_test, y_pred_proba) \n", " auc_score = metrics.auc(recall, precision)\n", " plt.plot(recall, precision, label=f'C: {C}, auc={auc:.3f}')\n", "plt.ylabel('Precision (Positive label: 1)')\n", "plt.xlabel('Recall (Positive label: 1)')\n", "plt.title('Precision-Recall Curve')\n", "plt.legend(loc='lower left')\n", "plt.show()" ] }, { "cell_type": "markdown", "id": "9938363c", "metadata": { "papermill": { "duration": 0.017696, "end_time": "2022-10-27T19:15:32.216179", "exception": false, "start_time": "2022-10-27T19:15:32.198483", "status": "completed" }, "tags": [] }, "source": [ "Based on ROC AUC I'll use C = 0.001." ] }, { "cell_type": "code", "execution_count": 12, "id": "1114cf04", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:15:32.255169Z", "iopub.status.busy": "2022-10-27T19:15:32.254745Z", "iopub.status.idle": "2022-10-27T19:15:34.093757Z", "shell.execute_reply": "2022-10-27T19:15:34.092137Z" }, "papermill": { "duration": 1.863806, "end_time": "2022-10-27T19:15:34.098842", "exception": false, "start_time": "2022-10-27T19:15:32.235036", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "### Logistic regression model\n", "clf = LogisticRegression(random_state=0, C=0.001, penalty='l2', class_weight='balanced')\n", "clf.fit(X_train_transform, y_train)\n", "\n", "### Probability estimates\n", "y_pred_proba_train = clf.predict_proba(X_train_transform)[:, 1]\n", "y_pred_proba_test = clf.predict_proba(X_test_transform)[:, 1]\n", "\n", "### Predict class labels for samples\n", "y_pred_train = clf.predict(X_train_transform)\n", "y_pred_test = clf.predict(X_test_transform)" ] }, { "cell_type": "markdown", "id": "c5a86fb7", "metadata": { "papermill": { "duration": 0.044, "end_time": "2022-10-27T19:15:34.186948", "exception": false, "start_time": "2022-10-27T19:15:34.142948", "status": "completed" }, "tags": [] }, "source": [ "Now we can visualize how Precision and Recall are changed at different thresholds." ] }, { "cell_type": "code", "execution_count": 13, "id": "265b8a43", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:15:34.242430Z", "iopub.status.busy": "2022-10-27T19:15:34.241250Z", "iopub.status.idle": "2022-10-27T19:15:34.578290Z", "shell.execute_reply": "2022-10-27T19:15:34.577168Z" }, "papermill": { "duration": 0.359834, "end_time": "2022-10-27T19:15:34.580801", "exception": false, "start_time": "2022-10-27T19:15:34.220967", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "(0.0, 1.0)" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 720x432 with 1 Axes>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "### Chart for Precision and Recall vs Tresholds\n", "precision, recall, threshold = precision_recall_curve(y_test, y_pred_proba_test)\n", "fig, ax = plt.subplots(figsize=(10,6))\n", "plt.plot(threshold, precision[:-1], 'b:', label='Precision')\n", "plt.plot(threshold, recall[:-1], 'r:', label='Recall')\n", "plt.title('Precision and Recall at different thresholds.')\n", "plt.xlabel('Threshold')\n", "plt.legend(loc='lower left')\n", "plt.ylim([0,1])" ] }, { "cell_type": "markdown", "id": "19bb8f5f", "metadata": { "papermill": { "duration": 0.018665, "end_time": "2022-10-27T19:15:34.618545", "exception": false, "start_time": "2022-10-27T19:15:34.599880", "status": "completed" }, "tags": [] }, "source": [ "We can see that precision starts to increase very fast near threshold = 1, but Recall falls sharply. If we want a compromise threshold we can use a value near the middle. Now, let's try to find the best threshold (or not)." ] }, { "cell_type": "markdown", "id": "42650b4a", "metadata": { "papermill": { "duration": 0.018977, "end_time": "2022-10-27T19:15:34.657632", "exception": false, "start_time": "2022-10-27T19:15:34.638655", "status": "completed" }, "tags": [] }, "source": [ "#### 6. Best threshold\n", " This data set is dramatically imbalanced so as an evaluation metric it's not possible to use accuracy. There are metrics like F1-score or G-mean which measure the balance between classification performances on both the majority and minority classes. What to choose as a metric and threshold depend on the task. Also, it's important to understand feature reactions for I-type and II type errors (False Negative and False Positive). This task is a fraud prediction, so if we will block cards (hypothetically) after scoring we should minimize False Positive (Type I errors) prediction and False Negative (Type II errors) has less importance. If we will manually check cards after scoring it's important to find more suspicious cards. The best way - check the confusion matrix and make conclusions." ] }, { "cell_type": "code", "execution_count": 14, "id": "b09488cd", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:15:34.698314Z", "iopub.status.busy": "2022-10-27T19:15:34.697869Z", "iopub.status.idle": "2022-10-27T19:15:34.707922Z", "shell.execute_reply": "2022-10-27T19:15:34.706759Z" }, "papermill": { "duration": 0.033317, "end_time": "2022-10-27T19:15:34.710728", "exception": false, "start_time": "2022-10-27T19:15:34.677411", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "#functions for searching best threshold\n", "\n", "### class label based on a given threshold\n", "def to_labels(pos_probs, threshold):\n", " return (pos_probs >= threshold).astype('int')\n", "\n", "### G_mean\n", "def g_mean(y_test, y_pred):\n", " tn, fp, fn, tp = confusion_matrix(y_test, y_pred).ravel()\n", " return ((tp/(tp + fn))(tn/(tn+fp)))*(0.5)\n", "\n", "### return threshold where F1-score is the biggest\n", "def best_tresholds_f1(y_pred_proba, y_test):\n", " # define thresholds\n", " thresholds = np.arange(0, 1, 0.001)\n", " # evaluate each threshold\n", " scores = [f1_score(y_test, to_labels(y_pred_proba, t)) for t in thresholds]\n", " # get best threshold\n", " ix = np.argmax(scores)\n", " #print('Threshold=%.3f, F-Score=%.5f' % (thresholds[ix], scores[ix]))\n", " return thresholds[ix], scores[ix]\n", "\n", "### return threshold where G-mean is the biggest\n", "def best_tresholds_gmean(y_pred_proba, y_test):\n", " # define thresholds\n", " thresholds = np.arange(0, 1, 0.001)\n", " # evaluate each threshold\n", " scores = [g_mean(y_test, to_labels(y_pred_proba, t)) for t in thresholds]\n", " # get best threshold\n", " ix = np.argmax(scores)\n", " #print('Threshold=%.3f, F-Score=%.5f' % (thresholds[ix], scores[ix]))\n", " return thresholds[ix], scores[ix]" ] }, { "cell_type": "markdown", "id": "98238af1", "metadata": { "papermill": { "duration": 0.018728, "end_time": "2022-10-27T19:15:34.748832", "exception": false, "start_time": "2022-10-27T19:15:34.730104", "status": "completed" }, "tags": [] }, "source": [ "Let's find the best threshold for F1-score and G-mean. For searching I use train data set and then apply thresholds for test data set." ] }, { "cell_type": "code", "execution_count": 15, "id": "4ecc581c", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:15:34.789044Z", "iopub.status.busy": "2022-10-27T19:15:34.788628Z", "iopub.status.idle": "2022-10-27T19:17:40.077435Z", "shell.execute_reply": "2022-10-27T19:17:40.076205Z" }, "papermill": { "duration": 125.332254, "end_time": "2022-10-27T19:17:40.100098", "exception": false, "start_time": "2022-10-27T19:15:34.767844", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "G-mean score: 0.9520, treshold: 0.525\n", "F1 score: 0.7865, treshold: 0.999\n" ] } ], "source": [ "treshold_gmean = best_tresholds_gmean(y_pred_proba_train, y_train)\n", "print(f'G-mean score: {treshold_gmean[1]:.4f}, treshold: {treshold_gmean[0]}')\n", "treshold_f1 = best_tresholds_f1(y_pred_proba_train, y_train)\n", "print(f'F1 score: {treshold_f1[1]:.4f}, treshold: {treshold_f1[0]}')\n" ] }, { "cell_type": "markdown", "id": "f28d3d6c", "metadata": { "papermill": { "duration": 0.019175, "end_time": "2022-10-27T19:17:40.138885", "exception": false, "start_time": "2022-10-27T19:17:40.119710", "status": "completed" }, "tags": [] }, "source": [ "The model during fitting used a default threshold = 0.5 and G-mean (The Geometric Mean) best threshold is close to the default value. Because we use weights in the model it generalizes data pretty well near 0.5. " ] }, { "cell_type": "code", "execution_count": 16, "id": "5497392d", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:17:40.180544Z", "iopub.status.busy": "2022-10-27T19:17:40.180135Z", "iopub.status.idle": "2022-10-27T19:17:40.187374Z", "shell.execute_reply": "2022-10-27T19:17:40.186224Z" }, "papermill": { "duration": 0.031214, "end_time": "2022-10-27T19:17:40.189954", "exception": false, "start_time": "2022-10-27T19:17:40.158740", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "### Predicted y for different thresholds:\n", "y_pred_05 = to_labels(y_pred_test, 0.5) #threshold = 0.5\n", "y_pred_052 = to_labels(y_pred_proba_test, treshold_gmean[0]) #threshold = 0.525\n", "y_pred_99 = to_labels(y_pred_proba_test, treshold_f1[0]) #threshold = 0.999" ] }, { "cell_type": "code", "execution_count": 17, "id": "96eb9241", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:17:40.232303Z", "iopub.status.busy": "2022-10-27T19:17:40.231844Z", "iopub.status.idle": "2022-10-27T19:17:40.264989Z", "shell.execute_reply": "2022-10-27T19:17:40.263704Z" }, "papermill": { "duration": 0.058001, "end_time": "2022-10-27T19:17:40.267854", "exception": false, "start_time": "2022-10-27T19:17:40.209853", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "### Confusion matrices for each threshold\n", "cf_matrix_05 = confusion_matrix(y_test, y_pred_05)\n", "cf_matrix_052 = confusion_matrix(y_test, y_pred_052)\n", "cf_matrix_99 = confusion_matrix(y_test, y_pred_99)" ] }, { "cell_type": "code", "execution_count": 18, "id": "a4ac9af2", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:17:40.310881Z", "iopub.status.busy": "2022-10-27T19:17:40.310426Z", "iopub.status.idle": "2022-10-27T19:17:40.319173Z", "shell.execute_reply": "2022-10-27T19:17:40.317880Z" }, "papermill": { "duration": 0.033524, "end_time": "2022-10-27T19:17:40.321532", "exception": false, "start_time": "2022-10-27T19:17:40.288008", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "### Function for confusion matrix visualization\n", "def confusion_matrix_visualization(cf_matrix):\n", " group_names = ['True Neg','False Pos','False Neg','True Pos']\n", " group_counts = [f'{value:.0f}' for value in cf_matrix.flatten()]\n", " group_percentages = [f'{value:.2%}' for value in cf_matrix.flatten()/np.sum(cf_matrix)]\n", " labels = [f'{v1}\\n{v2}\\n{v3}' for v1, v2, v3 in\n", " zip(group_names,group_counts,group_percentages)]\n", " labels = np.asarray(labels).reshape(2,2)\n", " \n", " fig, ax = plt.subplots(figsize=(7,5))\n", " sns.heatmap(cf_matrix, annot=labels, fmt='', cmap='Blues')\n", " fig.show()" ] }, { "cell_type": "code", "execution_count": 19, "id": "e3bd7b61", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:17:40.364943Z", "iopub.status.busy": "2022-10-27T19:17:40.364559Z", "iopub.status.idle": "2022-10-27T19:17:40.370756Z", "shell.execute_reply": "2022-10-27T19:17:40.369312Z" }, "papermill": { "duration": 0.031284, "end_time": "2022-10-27T19:17:40.373074", "exception": false, "start_time": "2022-10-27T19:17:40.341790", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "def eval_report(y_test, y_pred):\n", " print(f' Accuracy score:{metrics.accuracy_score(y_test, y_pred):.4f}')\n", " print(f' Balanced accuracy score:{metrics.balanced_accuracy_score(y_test, y_pred):.4f}')\n", " print(f' F-1 score:{f1_score(y_test, y_pred):.4f}')\n", " print(f' G-mean score:{g_mean(y_test, y_pred):.4f}')\n", " print(f' ROC-AUC score:{roc_auc_score(y_test, y_pred):.4f}')" ] }, { "cell_type": "code", "execution_count": 20, "id": "ef527f94", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:17:40.414267Z", "iopub.status.busy": "2022-10-27T19:17:40.413825Z", "iopub.status.idle": "2022-10-27T19:17:40.736729Z", "shell.execute_reply": "2022-10-27T19:17:40.735450Z" }, "papermill": { "duration": 0.346966, "end_time": "2022-10-27T19:17:40.739461", "exception": false, "start_time": "2022-10-27T19:17:40.392495", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " THRESHOLD = 0.5\n", " Accuracy score:0.9792\n", " Balanced accuracy score:0.9285\n", " F-1 score:0.1269\n", " G-mean score:0.9271\n", " ROC-AUC score:0.9285\n", "\n", "\t CONFUSION MATRIX, THRESHOLD = 0.5\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 504x360 with 2 Axes>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "print(' THRESHOLD = 0.5')\n", "eval_report(y_test, y_pred_05)\n", "print('\\n\\t CONFUSION MATRIX, THRESHOLD = 0.5')\n", "confusion_matrix_visualization(cf_matrix_05)" ] }, { "cell_type": "code", "execution_count": 21, "id": "49a9fee1", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:17:40.781353Z", "iopub.status.busy": "2022-10-27T19:17:40.780918Z", "iopub.status.idle": "2022-10-27T19:17:41.104031Z", "shell.execute_reply": "2022-10-27T19:17:41.102749Z" }, "papermill": { "duration": 0.34764, "end_time": "2022-10-27T19:17:41.107032", "exception": false, "start_time": "2022-10-27T19:17:40.759392", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " THRESHOLD = 0.52\n", " Accuracy score:0.9810\n", " Balanced accuracy score:0.9294\n", " F-1 score:0.1372\n", " G-mean score:0.9279\n", " ROC-AUC score:0.9294\n", "\n", "\t CONFUSION MATRIX, THRESHOLD = 0.52\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 504x360 with 2 Axes>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "print(' THRESHOLD = 0.52')\n", "eval_report(y_test, y_pred_052)\n", "print('\\n\\t CONFUSION MATRIX, THRESHOLD = 0.52')\n", "confusion_matrix_visualization(cf_matrix_052)" ] }, { "cell_type": "markdown", "id": "d88530af", "metadata": { "papermill": { "duration": 0.020348, "end_time": "2022-10-27T19:17:41.148569", "exception": false, "start_time": "2022-10-27T19:17:41.128221", "status": "completed" }, "tags": [] }, "source": [ "In the charts above we can see that there are the same True Positive values for both thresholds but less Type I errors. For threshold = 0.52, which was found with the best G-mean score, the False Positive value is smaller, so this threshold works better for us." ] }, { "cell_type": "code", "execution_count": 22, "id": "3cb5cb27", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:17:41.193323Z", "iopub.status.busy": "2022-10-27T19:17:41.191965Z", "iopub.status.idle": "2022-10-27T19:17:41.516885Z", "shell.execute_reply": "2022-10-27T19:17:41.515755Z" }, "papermill": { "duration": 0.350033, "end_time": "2022-10-27T19:17:41.519647", "exception": false, "start_time": "2022-10-27T19:17:41.169614", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " THRESHOLD = 0.99\n", " Accuracy score:0.9992\n", " Balanced accuracy score:0.8621\n", " F-1 score:0.7594\n", " G-mean score:0.8510\n", " ROC-AUC score:0.8621\n", "\n", "\t CONFUSION MATRIX, THRESHOLD = 0.99\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 504x360 with 2 Axes>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "print(' THRESHOLD = 0.99')\n", "eval_report(y_test, y_pred_99)\n", "print('\\n\\t CONFUSION MATRIX, THRESHOLD = 0.99')\n", "confusion_matrix_visualization(cf_matrix_99)" ] }, { "cell_type": "markdown", "id": "b78c128d", "metadata": { "papermill": { "duration": 0.02184, "end_time": "2022-10-27T19:17:41.563216", "exception": false, "start_time": "2022-10-27T19:17:41.541376", "status": "completed" }, "tags": [] }, "source": [ "Here we lose in True positives but False positives values are much smaller than before. If we are going to block cards after scoring in this case we will have only 18 dissatisfied hypothetical cards owners :) " ] }, { "cell_type": "markdown", "id": "86ae837c", "metadata": { "papermill": { "duration": 0.021345, "end_time": "2022-10-27T19:17:41.606763", "exception": false, "start_time": "2022-10-27T19:17:41.585418", "status": "completed" }, "tags": [] }, "source": [ "## Conclusion" ] }, { "cell_type": "markdown", "id": "9f5ac73f", "metadata": { "papermill": { "duration": 0.021306, "end_time": "2022-10-27T19:17:41.649564", "exception": false, "start_time": "2022-10-27T19:17:41.628258", "status": "completed" }, "tags": [] }, "source": [ "I wanted to show that the importance of choosing a threshold should not be underestimated. I did not specifically use any techniques for unbalanced datasets (except for weights) and only with the help of a threshold, I increased f1-score several times ^_^ \n", "I hope this notebook was useful for you. I am always open to questions and suggestions and let's give some claps for each other 👏👏👏👏👏 " ] }, { "cell_type": "code", "execution_count": null, "id": "37c51fe3", "metadata": { "papermill": { "duration": 0.021231, "end_time": "2022-10-27T19:17:41.692422", "exception": false, "start_time": "2022-10-27T19:17:41.671191", "status": "completed" }, "tags": [] }, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.12" }, "papermill": { "default_parameters": {}, "duration": 197.253432, "end_time": "2022-10-27T19:17:42.641443", "environment_variables": {}, "exception": null, "input_path": "__notebook__.ipynb", "output_path": "__notebook__.ipynb", "parameters": {}, "start_time": "2022-10-27T19:14:25.388011", "version": "2.3.4" } }, "nbformat": 4, "nbformat_minor": 5 }	0109/324/109324907.ipynb	s3://data-agents/kaggle-outputs/sharded/011_00109.jsonl.gz
{ "cells": [ { "cell_type": "markdown", "id": "00d8cdc2", "metadata": { "execution": { "iopub.execute_input": "2022-05-28T07:48:44.457889Z", "iopub.status.busy": "2022-05-28T07:48:44.456768Z", "iopub.status.idle": "2022-05-28T07:48:44.471029Z", "shell.execute_reply": "2022-05-28T07:48:44.469597Z", "shell.execute_reply.started": "2022-05-28T07:48:44.457771Z" }, "papermill": { "duration": 0.008223, "end_time": "2022-10-27T19:18:02.321153", "exception": false, "start_time": "2022-10-27T19:18:02.312930", "status": "completed" }, "tags": [] }, "source": [ "<div style=\"border-radius:10px;\n", " border : #015a2c solid;\n", " background-color:#D7D9DB;\n", " font-size:110%;\n", " letter-spacing:0.5px;\n", " text-align: center\">\n", "\n", "<center><h1 style=\"padding: 25px 0px; color:#015a4c; font-weight: bold; font-family: Cursive\">\n", "Machine Learning Studying <br><br>💡💡💡💡💡 <br><br> Explore Your Data </h1></center>\n", "<center><h3 style=\"padding-bottom: 25px; color:#025b2c; font-weight: bold; font-style:italic; font-family: Cursive\">\n", "Using tutorial at kaggle\n", " </h3></center> \n", "\n", "</div>" ] }, { "cell_type": "markdown", "id": "d8766bb2", "metadata": { "papermill": { "duration": 0.006131, "end_time": "2022-10-27T19:18:02.333957", "exception": false, "start_time": "2022-10-27T19:18:02.327826", "status": "completed" }, "tags": [] }, "source": [ "\n", "### Let’s take a look at Studying SQL for data analysts from useful resources collection\n", "\n", ".\n", "\n", " ![SQL for data analysts](https://user-images.githubusercontent.com/36210723/196912866-876148b9-e6d6-4226-920a-301cc5d071fd.png)\n", "\n", " \n", " \n", ".\n", "\n", "> If you want to learn SQL, here are free (+ paid) resources👇. Also, you can use these contents to face SQL interviews 🔥\n", "\n", "\n", ".\n", "\n", "\n", "𝟭. 𝗦𝗤𝗟 𝗕𝗼𝗹𝘁\n", "👉 https://sqlbolt.com/\n", "\n", "From SELECT * to GROUP BY, SQL Bolt contains lessons and interactive exercises to help you grasp the essentials in SQL. With no SQL Experience, you can get the basics of SQL in just one week.\n", "\n", "𝟮. 𝗦𝘁𝗮𝗻𝗳𝗼𝗿𝗱 𝗗𝗕 & 𝗦𝗤𝗟 𝗰𝗼𝘂𝗿𝘀𝗲\n", "👉 https://lnkd.in/gFEc8ngA\n", "\n", "If you want a detailed explanation of SQL queries with a mixture of easy and hard SQL problems, I highly recommend you check out this course.\n", "\n", "𝟯. 𝗧𝗲𝗰𝗵𝗧𝗙𝗤 𝗬𝗼𝘂𝗧𝘂𝗯𝗲 𝗖𝗵𝗮𝗻𝗻𝗲𝗹\n", "👉 https://lnkd.in/gjm4JZ9D\n", "\n", "I have seen a number of YouTubers focused on SQL and DBs, and I’d have to say I love Thoufiq’s explanation style. He covers a broad sweep of knowledge in SQL with an easy-to-follow explanation style. \n", "\n", "𝟰. 𝗦𝗤𝗟-𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗲\n", "👉 https://lnkd.in/gg3RsFnQ\n", "\n", "Here’s another free resource on learning SQL. It’s has a simple browser IDE that will allow you to learn the basics and play around with SQL.\n", "\n", "𝟱. 𝗗𝗮𝘁𝗮𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄 𝗦𝗤𝗟 𝗣𝗮𝗱\n", "👉 https://lnkd.in/gAmR4eQM\n", "\n", "Here’s a SQL Pad designed for SQL interview prep. It has 100 FAANG-style curated and solved questions.\n", "\n", "\n", ".\n" ] }, { "attachments": { "7a221601-7827-47fd-961d-80d1eed3a5e3.png": { "image/png": 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" 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" } }, "cell_type": "markdown", "id": "d626cdee", "metadata": { "papermill": { "duration": 0.006107, "end_time": "2022-10-27T19:18:02.346492", "exception": false, "start_time": "2022-10-27T19:18:02.340385", "status": "completed" }, "tags": [] }, "source": [ "![x.png](attachment:ce83b02d-8e6b-40d5-98b5-4539f53ba390.png) > ![know.png](attachment:7a221601-7827-47fd-961d-80d1eed3a5e3.png)" ] }, { "cell_type": "markdown", "id": "09b3a1f6", "metadata": { "execution": { "iopub.execute_input": "2022-05-28T07:49:58.145662Z", "iopub.status.busy": "2022-05-28T07:49:58.145236Z", "iopub.status.idle": "2022-05-28T07:49:58.164157Z", "shell.execute_reply": "2022-05-28T07:49:58.163222Z", "shell.execute_reply.started": "2022-05-28T07:49:58.145629Z" }, "papermill": { "duration": 0.00598, "end_time": "2022-10-27T19:18:02.358793", "exception": false, "start_time": "2022-10-27T19:18:02.352813", "status": "completed" }, "tags": [] }, "source": [ "> ## This notebook is an exercise in the . [Machine Learning tutorial at kaggle and here is the Home Page](https://www.kaggle.com/learn/machine-learning) course.\n", "\n", "---" ] }, { "cell_type": "markdown", "id": "4f6708a0", "metadata": { "papermill": { "duration": 0.006017, "end_time": "2022-10-27T19:18:02.371197", "exception": false, "start_time": "2022-10-27T19:18:02.365180", "status": "completed" }, "tags": [] }, "source": [ "This exercise will test your ability to read a data file and understand statistics about the data.\n", "\n", "In later exercises, you will apply techniques to filter the data, build a machine learning model, and iteratively improve your model.\n", "\n", "The course examples use data from Melbourne. To ensure you can apply these techniques on your own, you will have to apply them to a new dataset (with house prices from Iowa).\n", "\n", "The exercises use a \"notebook\" coding environment. In case you are unfamiliar with notebooks, we have a [90-second intro video](https://www.youtube.com/watch?v=4C2qMnaIKL4).\n", "\n", "# Exercises\n", "\n", "Run the following cell to set up code-checking, which will verify your work as you go." ] }, { "cell_type": "code", "execution_count": 1, "id": "8dfe885e", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:18:02.386047Z", "iopub.status.busy": "2022-10-27T19:18:02.385552Z", "iopub.status.idle": "2022-10-27T19:18:02.439671Z", "shell.execute_reply": "2022-10-27T19:18:02.438343Z" }, "papermill": { "duration": 0.066125, "end_time": "2022-10-27T19:18:02.443705", "exception": false, "start_time": "2022-10-27T19:18:02.377580", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Setup Complete\n" ] } ], "source": [ "# Set up code checking\n", "from learntools.core import binder\n", "binder.bind(globals())\n", "from learntools.machine_learning.ex2 import \n", "print(\"Setup Complete\")" ] }, { "cell_type": "markdown", "id": "49b526d0", "metadata": { "papermill": { "duration": 0.006494, "end_time": "2022-10-27T19:18:02.457751", "exception": false, "start_time": "2022-10-27T19:18:02.451257", "status": "completed" }, "tags": [] }, "source": [ "## Step 1: Loading Data\n", "Read the Iowa data file into a Pandas DataFrame called `home_data`." ] }, { "cell_type": "code", "execution_count": 2, "id": "930fcb0e", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:18:02.473130Z", "iopub.status.busy": "2022-10-27T19:18:02.472700Z", "iopub.status.idle": "2022-10-27T19:18:02.530153Z", "shell.execute_reply": "2022-10-27T19:18:02.529009Z" }, "papermill": { "duration": 0.067937, "end_time": "2022-10-27T19:18:02.532543", "exception": false, "start_time": "2022-10-27T19:18:02.464606", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "application/javascript": [ "parent.postMessage({\"jupyterEvent\": \"custom.exercise_interaction\", \"data\": {\"outcomeType\": 1, \"valueTowardsCompletion\": 0.5, \"interactionType\": 1, \"questionType\": 1, \"questionId\": \"1_LoadHomeData\", \"learnToolsVersion\": \"0.3.4\", \"failureMessage\": \"\", \"exceptionClass\": \"\", \"trace\": \"\"}}, \"\")" ], "text/plain": [ "<IPython.core.display.Javascript object>" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/markdown": [ "<span style=\"color:#33cc33\">Correct</span>" ], "text/plain": [ "Correct" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import pandas as pd\n", "\n", "# Path of the file to read\n", "iowa_file_path = '../input/home-data-for-ml-course/train.csv'\n", "\n", "# Fill in the line below to read the file into a variable home_data\n", "\n", "home_data = pd.read_csv(iowa_file_path) ## I added this line to read the file .csv\n", "\n", "\n", "# Call line below with no argument to check that you've loaded the data correctly\n", "step_1.check()" ] }, { "cell_type": "markdown", "id": "a2437eb6", "metadata": { "papermill": { "duration": 0.006597, "end_time": "2022-10-27T19:18:02.546268", "exception": false, "start_time": "2022-10-27T19:18:02.539671", "status": "completed" }, "tags": [] }, "source": [] }, { "cell_type": "markdown", "id": "12a564d6", "metadata": { "papermill": { "duration": 0.006489, "end_time": "2022-10-27T19:18:02.559709", "exception": false, "start_time": "2022-10-27T19:18:02.553220", "status": "completed" }, "tags": [] }, "source": [ "## Think About Your Data\n", "\n", "The newest house in your data isn't that new. A few potential explanations for this:\n", "1. They haven't built new houses where this data was collected.\n", "1. The data was collected a long time ago. Houses built after the data publication wouldn't show up.\n", "\n", "If the reason is explanation #1 above, does that affect your trust in the model you build with this data? What about if it is reason #2?\n", "\n", "How could you dig into the data to see which explanation is more plausible?\n", "\n", "Check out this [discussion thread](https://www.kaggle.com/learn-forum/60581) to see what others think or to add your ideas.\n", "\n", "# Keep Going\n", "\n", "You are ready for [Your First Machine Learning Model](https://www.kaggle.com/dansbecker/your-first-machine-learning-model)." ] }, { "cell_type": "markdown", "id": "6eec47c7", "metadata": { "papermill": { "duration": 0.006424, "end_time": "2022-10-27T19:18:02.574598", "exception": false, "start_time": "2022-10-27T19:18:02.568174", "status": "completed" }, "tags": [] }, "source": [ "## Think About Your Data\n", "\n", "The newest house in your data isn't that new. A few potential explanations for this:\n", "1. They haven't built new houses where this data was collected.\n", "1. The data was collected a long time ago. Houses built after the data publication wouldn't show up.\n", "\n", "If the reason is explanation #1 above, does that affect your trust in the model you build with this data? What about if it is reason #2?\n", "\n", "How could you dig into the data to see which explanation is more plausible?\n", "\n", "Check out this [discussion thread](https://www.kaggle.com/learn-forum/60581) to see what others think or to add your ideas.\n", "\n", "# Keep Going\n", "\n", "You are ready for [Your First Machine Learning Model](https://www.kaggle.com/dansbecker/your-first-machine-learning-model).\n" ] }, { "cell_type": "markdown", "id": "caf566a3", "metadata": { "papermill": { "duration": 0.00658, "end_time": "2022-10-27T19:18:02.587916", "exception": false, "start_time": "2022-10-27T19:18:02.581336", "status": "completed" }, "tags": [] }, "source": [] }, { "cell_type": "code", "execution_count": 3, "id": "b85b1def", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:18:02.604224Z", "iopub.status.busy": "2022-10-27T19:18:02.603348Z", "iopub.status.idle": "2022-10-27T19:18:02.616836Z", "shell.execute_reply": "2022-10-27T19:18:02.615716Z" }, "papermill": { "duration": 0.023893, "end_time": "2022-10-27T19:18:02.618992", "exception": false, "start_time": "2022-10-27T19:18:02.595099", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "application/javascript": [ "parent.postMessage({\"jupyterEvent\": \"custom.exercise_interaction\", \"data\": {\"interactionType\": 2, \"questionType\": 1, \"questionId\": \"1_LoadHomeData\", \"learnToolsVersion\": \"0.3.4\", \"valueTowardsCompletion\": 0.0, \"failureMessage\": \"\", \"exceptionClass\": \"\", \"trace\": \"\", \"outcomeType\": 4}}, \"\")" ], "text/plain": [ "<IPython.core.display.Javascript object>" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/markdown": [ "<span style=\"color:#3366cc\">Hint:</span> Use the `pd.read_csv` function" ], "text/plain": [ "Hint: Use the `pd.read_csv` function" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "parent.postMessage({\"jupyterEvent\": \"custom.exercise_interaction\", \"data\": {\"interactionType\": 3, \"questionType\": 1, \"questionId\": \"1_LoadHomeData\", \"learnToolsVersion\": \"0.3.4\", \"valueTowardsCompletion\": 0.0, \"failureMessage\": \"\", \"exceptionClass\": \"\", \"trace\": \"\", \"outcomeType\": 4}}, \"\")" ], "text/plain": [ "<IPython.core.display.Javascript object>" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/markdown": [ "<span style=\"color:#33cc99\">Solution:</span> \n", "```python\n", "home_data = pd.read_csv(iowa_file_path)\n", "```" ], "text/plain": [ "Solution: \n", "```python\n", "home_data = pd.read_csv(iowa_file_path)\n", "```" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Lines below will give you a hint or solution code\n", "step_1.hint()\n", "step_1.solution()" ] }, { "cell_type": "markdown", "id": "ee1dd246", "metadata": { "papermill": { "duration": 0.007206, "end_time": "2022-10-27T19:18:02.633997", "exception": false, "start_time": "2022-10-27T19:18:02.626791", "status": "completed" }, "tags": [] }, "source": [ "## Step 2: Review The Data\n", "Use the command you learned to view summary statistics of the data. Then fill in variables to answer the following questions" ] }, { "cell_type": "code", "execution_count": 4, "id": "83950d23", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:18:02.650897Z", "iopub.status.busy": "2022-10-27T19:18:02.650487Z", "iopub.status.idle": "2022-10-27T19:18:02.656020Z", "shell.execute_reply": "2022-10-27T19:18:02.655206Z" }, "papermill": { "duration": 0.017032, "end_time": "2022-10-27T19:18:02.658428", "exception": false, "start_time": "2022-10-27T19:18:02.641396", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/markdown": [], "text/plain": [ "<learntools.core.constants.PlaceholderValue at 0x7f2c1d830290>" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Print summary statistics in next line\n", "____" ] }, { "cell_type": "code", "execution_count": 5, "id": "40c6cc66", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:18:02.675380Z", "iopub.status.busy": "2022-10-27T19:18:02.674503Z", "iopub.status.idle": "2022-10-27T19:18:02.682822Z", "shell.execute_reply": "2022-10-27T19:18:02.682066Z" }, "papermill": { "duration": 0.019238, "end_time": "2022-10-27T19:18:02.685098", "exception": false, "start_time": "2022-10-27T19:18:02.665860", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "application/javascript": [ "parent.postMessage({\"jupyterEvent\": \"custom.exercise_interaction\", \"data\": {\"outcomeType\": 1, \"valueTowardsCompletion\": 0.5, \"interactionType\": 1, \"questionType\": 1, \"questionId\": \"2_HomeDescription\", \"learnToolsVersion\": \"0.3.4\", \"failureMessage\": \"\", \"exceptionClass\": \"\", \"trace\": \"\"}}, \"\")" ], "text/plain": [ "<IPython.core.display.Javascript object>" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/markdown": [ "<span style=\"color:#33cc33\">Correct</span>" ], "text/plain": [ "Correct" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# What is the average lot size (rounded to nearest integer)?\n", "avg_lot_size = 10517\n", "\n", "# As of today, how old is the newest home (current year - the date in which it was built)\n", "newest_home_age = 12\n", "\n", "\n", "\n", "# Checks your answers\n", "step_2.check()" ] }, { "cell_type": "code", "execution_count": 6, "id": "e4395180", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:18:02.702766Z", "iopub.status.busy": "2022-10-27T19:18:02.701920Z", "iopub.status.idle": "2022-10-27T19:18:02.714991Z", "shell.execute_reply": "2022-10-27T19:18:02.713945Z" }, "papermill": { "duration": 0.024221, "end_time": "2022-10-27T19:18:02.717074", "exception": false, "start_time": "2022-10-27T19:18:02.692853", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "application/javascript": [ "parent.postMessage({\"jupyterEvent\": \"custom.exercise_interaction\", \"data\": {\"interactionType\": 2, \"questionType\": 1, \"questionId\": \"2_HomeDescription\", \"learnToolsVersion\": \"0.3.4\", \"valueTowardsCompletion\": 0.0, \"failureMessage\": \"\", \"exceptionClass\": \"\", \"trace\": \"\", \"outcomeType\": 4}}, \"\")" ], "text/plain": [ "<IPython.core.display.Javascript object>" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/markdown": [ "<span style=\"color:#3366cc\">Hint:</span> Run the describe command. Lot size is in the column called LotArea. Also look at YearBuilt. Remember to round lot size " ], "text/plain": [ "Hint: Run the describe command. Lot size is in the column called LotArea. Also look at YearBuilt. Remember to round lot size " ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "parent.postMessage({\"jupyterEvent\": \"custom.exercise_interaction\", \"data\": {\"interactionType\": 3, \"questionType\": 1, \"questionId\": \"2_HomeDescription\", \"learnToolsVersion\": \"0.3.4\", \"valueTowardsCompletion\": 0.0, \"failureMessage\": \"\", \"exceptionClass\": \"\", \"trace\": \"\", \"outcomeType\": 4}}, \"\")" ], "text/plain": [ "<IPython.core.display.Javascript object>" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/markdown": [ "<span style=\"color:#33cc99\">Solution:</span> \n", "```python\n", "# using data read from home_data.describe()\n", "avg_lot_size = 10517\n", "newest_home_age = 12\n", "\n", "```" ], "text/plain": [ "Solution: \n", "```python\n", "# using data read from home_data.describe()\n", "avg_lot_size = 10517\n", "newest_home_age = 12\n", "\n", "```" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "step_2.hint()\n", "step_2.solution()" ] }, { "cell_type": "markdown", "id": "7891ec70", "metadata": { "papermill": { "duration": 0.007707, "end_time": "2022-10-27T19:18:02.732962", "exception": false, "start_time": "2022-10-27T19:18:02.725255", "status": "completed" }, "tags": [] }, "source": [ "## Think About Your Data\n", "\n", "The newest house in your data isn't that new. A few potential explanations for this:\n", "1. They haven't built new houses where this data was collected.\n", "1. The data was collected a long time ago. Houses built after the data publication wouldn't show up.\n", "\n", "If the reason is explanation #1 above, does that affect your trust in the model you build with this data? What about if it is reason #2?\n", "\n", "How could you dig into the data to see which explanation is more plausible?\n", "\n", "Check out this [discussion thread](https://www.kaggle.com/learn-forum/60581)* to see what others think or to add your ideas.\n", "\n", "# Keep Going\n", "\n", "You are ready for [Your First Machine Learning Model](https://www.kaggle.com/dansbecker/your-first-machine-learning-model).\n" ] }, { "attachments": { "28b522ee-c6cf-4212-bb69-a6d86b7858a8.png": { "image/png": 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" } }, "cell_type": "markdown", "id": "f394a955", "metadata": { "papermill": { "duration": 0.007746, "end_time": "2022-10-27T19:18:02.748749", "exception": false, "start_time": "2022-10-27T19:18:02.741003", "status": "completed" }, "tags": [] }, "source": [ "![00000.png](attachment:28b522ee-c6cf-4212-bb69-a6d86b7858a8.png)" ] }, { "cell_type": "markdown", "id": "713d7c94", "metadata": { "papermill": { "duration": 0.007792, "end_time": "2022-10-27T19:18:02.764581", "exception": false, "start_time": "2022-10-27T19:18:02.756789", "status": "completed" }, "tags": [] }, "source": [ "---\n", "> ## [Machine Learning Course Home Page](https://www.kaggle.com/learn/machine-learning)\n", "\n" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.12" }, "papermill": { "default_parameters": {}, "duration": 11.458648, "end_time": "2022-10-27T19:18:03.392890", "environment_variables": {}, "exception": null, "input_path": "__notebook__.ipynb", "output_path": "__notebook__.ipynb", "parameters": {}, "start_time": "2022-10-27T19:17:51.934242", "version": "2.3.4" } }, "nbformat": 4, "nbformat_minor": 5 }	0109/325/109325139.ipynb	s3://data-agents/kaggle-outputs/sharded/011_00109.jsonl.gz
{ "cells": [ { "cell_type": "markdown", "id": "30b1547a", "metadata": { "papermill": { "duration": 0.00408, "end_time": "2022-10-27T19:18:40.572952", "exception": false, "start_time": "2022-10-27T19:18:40.568872", "status": "completed" }, "tags": [] }, "source": [ "# Iris Classification using Decision Trees" ] }, { "cell_type": "code", "execution_count": 1, "id": "d84bd8ec", "metadata": { "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19", "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5", "execution": { "iopub.execute_input": "2022-10-27T19:18:40.581473Z", "iopub.status.busy": "2022-10-27T19:18:40.580985Z", "iopub.status.idle": "2022-10-27T19:18:40.593662Z", "shell.execute_reply": "2022-10-27T19:18:40.592554Z" }, "papermill": { "duration": 0.020111, "end_time": "2022-10-27T19:18:40.596546", "exception": false, "start_time": "2022-10-27T19:18:40.576435", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "#Import libraries\n", "import numpy as np # linear algebra\n", "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n", "import matplotlib.pyplot as plt\n", "%matplotlib inline" ] }, { "cell_type": "markdown", "id": "0e9a0adc", "metadata": { "papermill": { "duration": 0.002835, "end_time": "2022-10-27T19:18:40.602679", "exception": false, "start_time": "2022-10-27T19:18:40.599844", "status": "completed" }, "tags": [] }, "source": [ "# Getting Data" ] }, { "cell_type": "code", "execution_count": 2, "id": "e0b69624", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:18:40.610987Z", "iopub.status.busy": "2022-10-27T19:18:40.610225Z", "iopub.status.idle": "2022-10-27T19:18:40.658946Z", "shell.execute_reply": "2022-10-27T19:18:40.658030Z" }, "papermill": { "duration": 0.055507, "end_time": "2022-10-27T19:18:40.661235", "exception": false, "start_time": "2022-10-27T19:18:40.605728", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>Id</th>\n", " <th>SepalLengthCm</th>\n", " <th>SepalWidthCm</th>\n", " <th>PetalLengthCm</th>\n", " <th>PetalWidthCm</th>\n", " <th>Species</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>0</th>\n", " <td>1</td>\n", " <td>5.1</td>\n", " <td>3.5</td>\n", " <td>1.4</td>\n", " <td>0.2</td>\n", " <td>Iris-setosa</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>2</td>\n", " <td>4.9</td>\n", " <td>3.0</td>\n", " <td>1.4</td>\n", " <td>0.2</td>\n", " <td>Iris-setosa</td>\n", " </tr>\n", " <tr>\n", " <th>2</th>\n", " <td>3</td>\n", " <td>4.7</td>\n", " <td>3.2</td>\n", " <td>1.3</td>\n", " <td>0.2</td>\n", " <td>Iris-setosa</td>\n", " </tr>\n", " <tr>\n", " <th>3</th>\n", " <td>4</td>\n", " <td>4.6</td>\n", " <td>3.1</td>\n", " <td>1.5</td>\n", " <td>0.2</td>\n", " <td>Iris-setosa</td>\n", " </tr>\n", " <tr>\n", " <th>4</th>\n", " <td>5</td>\n", " <td>5.0</td>\n", " <td>3.6</td>\n", " <td>1.4</td>\n", " <td>0.2</td>\n", " <td>Iris-setosa</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " Id SepalLengthCm SepalWidthCm PetalLengthCm PetalWidthCm Species\n", "0 1 5.1 3.5 1.4 0.2 Iris-setosa\n", "1 2 4.9 3.0 1.4 0.2 Iris-setosa\n", "2 3 4.7 3.2 1.3 0.2 Iris-setosa\n", "3 4 4.6 3.1 1.5 0.2 Iris-setosa\n", "4 5 5.0 3.6 1.4 0.2 Iris-setosa" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#getting Data\n", "df = pd.read_csv('../input/iris/Iris.csv')\n", "df.head()" ] }, { "cell_type": "code", "execution_count": 3, "id": "f66989f8", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:18:40.670264Z", "iopub.status.busy": "2022-10-27T19:18:40.669497Z", "iopub.status.idle": "2022-10-27T19:18:40.676256Z", "shell.execute_reply": "2022-10-27T19:18:40.675143Z" }, "papermill": { "duration": 0.014088, "end_time": "2022-10-27T19:18:40.678881", "exception": false, "start_time": "2022-10-27T19:18:40.664793", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "(150, 6)" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#getting size of dataframe\n", "df.shape" ] }, { "cell_type": "code", "execution_count": 4, "id": "334c6ca7", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:18:40.687692Z", "iopub.status.busy": "2022-10-27T19:18:40.687256Z", "iopub.status.idle": "2022-10-27T19:18:40.702049Z", "shell.execute_reply": "2022-10-27T19:18:40.700865Z" }, "papermill": { "duration": 0.022375, "end_time": "2022-10-27T19:18:40.704873", "exception": false, "start_time": "2022-10-27T19:18:40.682498", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "Iris-setosa 50\n", "Iris-versicolor 50\n", "Iris-virginica 50\n", "Name: Species, dtype: int64" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#getting kind of iris\n", "df.Species.value_counts()" ] }, { "cell_type": "markdown", "id": "d8435b07", "metadata": { "papermill": { "duration": 0.003293, "end_time": "2022-10-27T19:18:40.712047", "exception": false, "start_time": "2022-10-27T19:18:40.708754", "status": "completed" }, "tags": [] }, "source": [ "# Data visualization" ] }, { "cell_type": "code", "execution_count": 5, "id": "0bbe50c9", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:18:40.721435Z", "iopub.status.busy": "2022-10-27T19:18:40.720780Z", "iopub.status.idle": "2022-10-27T19:18:42.588513Z", "shell.execute_reply": "2022-10-27T19:18:42.587253Z" }, "papermill": { "duration": 1.875562, "end_time": "2022-10-27T19:18:42.591192", "exception": false, "start_time": "2022-10-27T19:18:40.715630", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 720x1080 with 4 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "#Show BoxPlots\n", "import seaborn as sns\n", "\n", "plt.figure(figsize=(10,15))\n", "\n", "def show_boxplot(feature):\n", " sns.boxplot(data = df, x = 'Species', y = feature)\n", " plt.title('Boxplot for ' + feature, fontsize = 20)\n", " plt.xlabel('Species', fontsize = 15)\n", " plt.ylabel(feature, fontsize = 15)\n", "\n", "plt.subplot(221)\n", "show_boxplot('SepalLengthCm')\n", " \n", "plt.subplot(222)\n", "show_boxplot('SepalWidthCm')\n", " \n", "plt.subplot(223)\n", "show_boxplot('PetalLengthCm')\n", " \n", "plt.subplot(224)\n", "show_boxplot('PetalWidthCm')\n", " \n", "plt.show()" ] }, { "cell_type": "code", "execution_count": 6, "id": "b5011bf3", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:18:42.601733Z", "iopub.status.busy": "2022-10-27T19:18:42.601321Z", "iopub.status.idle": "2022-10-27T19:18:47.863016Z", "shell.execute_reply": "2022-10-27T19:18:47.862069Z" }, "papermill": { "duration": 5.271932, "end_time": "2022-10-27T19:18:47.867572", "exception": false, "start_time": "2022-10-27T19:18:42.595640", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "<seaborn.axisgrid.PairGrid at 0x7f03e9baf1d0>" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 834.35x720 with 20 Axes>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#Show Paired plot\n", "sns.set()\n", "sns.pairplot(df[['SepalLengthCm', 'SepalWidthCm', 'PetalLengthCm', 'PetalWidthCm', 'Species']], hue='Species')" ] }, { "cell_type": "code", "execution_count": 7, "id": "051cdaf1", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:18:47.885979Z", "iopub.status.busy": "2022-10-27T19:18:47.885257Z", "iopub.status.idle": "2022-10-27T19:18:48.253736Z", "shell.execute_reply": "2022-10-27T19:18:48.252623Z" }, "papermill": { "duration": 0.380649, "end_time": "2022-10-27T19:18:48.256381", "exception": false, "start_time": "2022-10-27T19:18:47.875732", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 720x504 with 2 Axes>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#checking correlations\n", "plt.figure(figsize = (10, 7))\n", "corr = df.corr(method='pearson')\n", "sns.heatmap(corr, annot=True)\n", "plt.title(\"Visualizing Correlations\", size = 20)\n", "plt.show()" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.12" }, "papermill": { "default_parameters": {}, "duration": 17.353038, "end_time": "2022-10-27T19:18:49.087739", "environment_variables": {}, "exception": null, "input_path": "__notebook__.ipynb", "output_path": "__notebook__.ipynb", "parameters": {}, "start_time": "2022-10-27T19:18:31.734701", "version": "2.3.4" } }, "nbformat": 4, "nbformat_minor": 5 }	0109/325/109325188.ipynb	s3://data-agents/kaggle-outputs/sharded/011_00109.jsonl.gz
{ "cells": [ { "cell_type": "markdown", "id": "4a674976", "metadata": { "papermill": { "duration": 0.00524, "end_time": "2022-10-27T19:21:22.423169", "exception": false, "start_time": "2022-10-27T19:21:22.417929", "status": "completed" }, "tags": [] }, "source": [ "# Importing Libraries" ] }, { "cell_type": "code", "execution_count": 1, "id": "467e76cf", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:21:22.434113Z", "iopub.status.busy": "2022-10-27T19:21:22.433327Z", "iopub.status.idle": "2022-10-27T19:21:23.626954Z", "shell.execute_reply": "2022-10-27T19:21:23.625730Z" }, "papermill": { "duration": 1.202152, "end_time": "2022-10-27T19:21:23.629753", "exception": false, "start_time": "2022-10-27T19:21:22.427601", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "import numpy as np\n", "import pandas as pd\n", "import seaborn as sn\n", "import matplotlib.pyplot as plt\n", "from sklearn.model_selection import train_test_split\n", "from sklearn import metrics\n", "from sklearn.linear_model import LinearRegression" ] }, { "cell_type": "markdown", "id": "dc137bbc", "metadata": { "papermill": { "duration": 0.004301, "end_time": "2022-10-27T19:21:23.639378", "exception": false, "start_time": "2022-10-27T19:21:23.635077", "status": "completed" }, "tags": [] }, "source": [ "# Data Visualizing" ] }, { "cell_type": "code", "execution_count": 2, "id": "39c3f022", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:21:23.650929Z", "iopub.status.busy": "2022-10-27T19:21:23.649954Z", "iopub.status.idle": "2022-10-27T19:21:23.694225Z", "shell.execute_reply": "2022-10-27T19:21:23.692794Z" }, "papermill": { "duration": 0.0533, "end_time": "2022-10-27T19:21:23.697110", "exception": false, "start_time": "2022-10-27T19:21:23.643810", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "<class 'pandas.core.frame.DataFrame'>\n", "RangeIndex: 414 entries, 0 to 413\n", "Data columns (total 8 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 No 414 non-null int64 \n", " 1 X1 transaction date 414 non-null float64\n", " 2 X2 house age 414 non-null float64\n", " 3 X3 distance to the nearest MRT station 414 non-null float64\n", " 4 X4 number of convenience stores 414 non-null int64 \n", " 5 X5 latitude 414 non-null float64\n", " 6 X6 longitude 414 non-null float64\n", " 7 Y house price of unit area 414 non-null float64\n", "dtypes: float64(6), int64(2)\n", "memory usage: 26.0 KB\n" ] } ], "source": [ "data = pd.read_csv(\"../input/realestate/Real estate.csv\")\n", "data.info()" ] }, { "cell_type": "code", "execution_count": 3, "id": "13313044", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:21:23.709265Z", "iopub.status.busy": "2022-10-27T19:21:23.708099Z", "iopub.status.idle": "2022-10-27T19:21:23.717062Z", "shell.execute_reply": "2022-10-27T19:21:23.715740Z" }, "papermill": { "duration": 0.017056, "end_time": "2022-10-27T19:21:23.719188", "exception": false, "start_time": "2022-10-27T19:21:23.702132", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "(414, 8)" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data.shape" ] }, { "cell_type": "code", "execution_count": 4, "id": "dcd6be77", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:21:23.730995Z", "iopub.status.busy": "2022-10-27T19:21:23.730325Z", "iopub.status.idle": "2022-10-27T19:21:23.767658Z", "shell.execute_reply": "2022-10-27T19:21:23.766749Z" }, "papermill": { "duration": 0.045635, "end_time": "2022-10-27T19:21:23.769726", "exception": false, "start_time": "2022-10-27T19:21:23.724091", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>No</th>\n", " <th>X1 transaction date</th>\n", " <th>X2 house age</th>\n", " <th>X3 distance to the nearest MRT station</th>\n", " <th>X4 number of convenience stores</th>\n", " <th>X5 latitude</th>\n", " <th>X6 longitude</th>\n", " <th>Y house price of unit area</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>count</th>\n", " <td>414.000000</td>\n", " <td>414.000000</td>\n", " <td>414.000000</td>\n", " <td>414.000000</td>\n", " <td>414.000000</td>\n", " <td>414.000000</td>\n", " <td>414.000000</td>\n", " <td>414.000000</td>\n", " </tr>\n", " <tr>\n", " <th>mean</th>\n", " <td>207.500000</td>\n", " <td>2013.148971</td>\n", " <td>17.712560</td>\n", " <td>1083.885689</td>\n", " <td>4.094203</td>\n", " <td>24.969030</td>\n", " <td>121.533361</td>\n", " <td>37.980193</td>\n", " </tr>\n", " <tr>\n", " <th>std</th>\n", " <td>119.655756</td>\n", " <td>0.281967</td>\n", " <td>11.392485</td>\n", " <td>1262.109595</td>\n", " <td>2.945562</td>\n", " <td>0.012410</td>\n", " <td>0.015347</td>\n", " <td>13.606488</td>\n", " </tr>\n", " <tr>\n", " <th>min</th>\n", " <td>1.000000</td>\n", " <td>2012.667000</td>\n", " <td>0.000000</td>\n", " <td>23.382840</td>\n", " <td>0.000000</td>\n", " <td>24.932070</td>\n", " <td>121.473530</td>\n", " <td>7.600000</td>\n", " </tr>\n", " <tr>\n", " <th>25%</th>\n", " <td>104.250000</td>\n", " <td>2012.917000</td>\n", " <td>9.025000</td>\n", " <td>289.324800</td>\n", " <td>1.000000</td>\n", " <td>24.963000</td>\n", " <td>121.528085</td>\n", " <td>27.700000</td>\n", " </tr>\n", " <tr>\n", " <th>50%</th>\n", " <td>207.500000</td>\n", " <td>2013.167000</td>\n", " <td>16.100000</td>\n", " <td>492.231300</td>\n", " <td>4.000000</td>\n", " <td>24.971100</td>\n", " <td>121.538630</td>\n", " <td>38.450000</td>\n", " </tr>\n", " <tr>\n", " <th>75%</th>\n", " <td>310.750000</td>\n", " <td>2013.417000</td>\n", " <td>28.150000</td>\n", " <td>1454.279000</td>\n", " <td>6.000000</td>\n", " <td>24.977455</td>\n", " <td>121.543305</td>\n", " <td>46.600000</td>\n", " </tr>\n", " <tr>\n", " <th>max</th>\n", " <td>414.000000</td>\n", " <td>2013.583000</td>\n", " <td>43.800000</td>\n", " <td>6488.021000</td>\n", " <td>10.000000</td>\n", " <td>25.014590</td>\n", " <td>121.566270</td>\n", " <td>117.500000</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " No X1 transaction date X2 house age \\\n", "count 414.000000 414.000000 414.000000 \n", "mean 207.500000 2013.148971 17.712560 \n", "std 119.655756 0.281967 11.392485 \n", "min 1.000000 2012.667000 0.000000 \n", "25% 104.250000 2012.917000 9.025000 \n", "50% 207.500000 2013.167000 16.100000 \n", "75% 310.750000 2013.417000 28.150000 \n", "max 414.000000 2013.583000 43.800000 \n", "\n", " X3 distance to the nearest MRT station \\\n", "count 414.000000 \n", "mean 1083.885689 \n", "std 1262.109595 \n", "min 23.382840 \n", "25% 289.324800 \n", "50% 492.231300 \n", "75% 1454.279000 \n", "max 6488.021000 \n", "\n", " X4 number of convenience stores X5 latitude X6 longitude \\\n", "count 414.000000 414.000000 414.000000 \n", "mean 4.094203 24.969030 121.533361 \n", "std 2.945562 0.012410 0.015347 \n", "min 0.000000 24.932070 121.473530 \n", "25% 1.000000 24.963000 121.528085 \n", "50% 4.000000 24.971100 121.538630 \n", "75% 6.000000 24.977455 121.543305 \n", "max 10.000000 25.014590 121.566270 \n", "\n", " Y house price of unit area \n", "count 414.000000 \n", "mean 37.980193 \n", "std 13.606488 \n", "min 7.600000 \n", "25% 27.700000 \n", "50% 38.450000 \n", "75% 46.600000 \n", "max 117.500000 " ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data.describe()" ] }, { "cell_type": "code", "execution_count": 5, "id": "ce4823d5", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:21:23.781407Z", "iopub.status.busy": "2022-10-27T19:21:23.781013Z", "iopub.status.idle": "2022-10-27T19:21:24.088313Z", "shell.execute_reply": "2022-10-27T19:21:24.087660Z" }, "papermill": { "duration": 0.315719, "end_time": "2022-10-27T19:21:24.090548", "exception": false, "start_time": "2022-10-27T19:21:23.774829", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "<AxesSubplot:>" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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"text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "data.plot()" ] }, { "cell_type": "code", "execution_count": 6, "id": "4a138fd9", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:21:24.103807Z", "iopub.status.busy": "2022-10-27T19:21:24.103282Z", "iopub.status.idle": "2022-10-27T19:21:24.117333Z", "shell.execute_reply": "2022-10-27T19:21:24.116413Z" }, "papermill": { "duration": 0.022814, "end_time": "2022-10-27T19:21:24.119320", "exception": false, "start_time": "2022-10-27T19:21:24.096506", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" 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121.53951 42.2 \n", "2 24.98746 121.54391 47.3 \n", "3 24.98746 121.54391 54.8 \n", "4 24.97937 121.54245 43.1 " ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data.head(5)" ] }, { "cell_type": "code", "execution_count": 7, "id": "6cf06e86", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:21:24.134234Z", "iopub.status.busy": "2022-10-27T19:21:24.133689Z", "iopub.status.idle": "2022-10-27T19:21:24.147317Z", "shell.execute_reply": "2022-10-27T19:21:24.146493Z" }, "papermill": { "duration": 0.023732, "end_time": "2022-10-27T19:21:24.149143", "exception": false, "start_time": "2022-10-27T19:21:24.125411", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " 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<td>390.96960</td>\n", " <td>7</td>\n", " <td>24.97923</td>\n", " <td>121.53986</td>\n", " <td>40.6</td>\n", " </tr>\n", " <tr>\n", " <th>412</th>\n", " <td>413</td>\n", " <td>2013.000</td>\n", " <td>8.1</td>\n", " <td>104.81010</td>\n", " <td>5</td>\n", " <td>24.96674</td>\n", " <td>121.54067</td>\n", " <td>52.5</td>\n", " </tr>\n", " <tr>\n", " <th>413</th>\n", " <td>414</td>\n", " <td>2013.500</td>\n", " <td>6.5</td>\n", " <td>90.45606</td>\n", " <td>9</td>\n", " <td>24.97433</td>\n", " <td>121.54310</td>\n", " <td>63.9</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " No X1 transaction date X2 house age \\\n", "409 410 2013.000 13.7 \n", "410 411 2012.667 5.6 \n", "411 412 2013.250 18.8 \n", "412 413 2013.000 8.1 \n", "413 414 2013.500 6.5 \n", "\n", " X3 distance to the nearest MRT station X4 number of convenience stores \\\n", "409 4082.01500 0 \n", "410 90.45606 9 \n", "411 390.96960 7 \n", "412 104.81010 5 \n", "413 90.45606 9 \n", "\n", " X5 latitude X6 longitude Y house price of unit area \n", "409 24.94155 121.50381 15.4 \n", "410 24.97433 121.54310 50.0 \n", "411 24.97923 121.53986 40.6 \n", "412 24.96674 121.54067 52.5 \n", "413 24.97433 121.54310 63.9 " ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data.tail(5)" ] }, { "cell_type": "code", "execution_count": 8, "id": "10b80d59", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:21:24.162247Z", "iopub.status.busy": "2022-10-27T19:21:24.161881Z", "iopub.status.idle": "2022-10-27T19:21:24.645324Z", "shell.execute_reply": "2022-10-27T19:21:24.644141Z" }, "papermill": { "duration": 0.492222, "end_time": "2022-10-27T19:21:24.647405", "exception": false, "start_time": "2022-10-27T19:21:24.155183", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "<AxesSubplot:>" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 432x288 with 2 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sn.heatmap(data.corr(), annot=True, cmap=\"Greens\")" ] }, { "cell_type": "code", "execution_count": 9, "id": "a42bbf38", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:21:24.662609Z", "iopub.status.busy": "2022-10-27T19:21:24.662264Z", "iopub.status.idle": "2022-10-27T19:21:35.115987Z", "shell.execute_reply": "2022-10-27T19:21:35.114949Z" }, "papermill": { "duration": 10.467193, "end_time": "2022-10-27T19:21:35.121608", "exception": false, "start_time": "2022-10-27T19:21:24.654415", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "<seaborn.axisgrid.PairGrid at 0x7f5e68c2fd90>" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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"text/plain": [ "<Figure size 1440x1440 with 72 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sn.pairplot(data)" ] }, { "cell_type": "code", "execution_count": 10, "id": "23a33d12", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:21:35.150164Z", "iopub.status.busy": "2022-10-27T19:21:35.149787Z", "iopub.status.idle": "2022-10-27T19:21:35.165575Z", "shell.execute_reply": "2022-10-27T19:21:35.164902Z" }, "papermill": { "duration": 0.032357, "end_time": "2022-10-27T19:21:35.167162", "exception": false, "start_time": "2022-10-27T19:21:35.134805", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>No</th>\n", " <th>X1 transaction date</th>\n", " <th>X2 house age</th>\n", " <th>X3 distance to the nearest MRT station</th>\n", " <th>X4 number of convenience stores</th>\n", " <th>X5 latitude</th>\n", " <th>X6 longitude</th>\n", " <th>Y house price of unit area</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>No</th>\n", " <td>1.000000</td>\n", " <td>-0.048658</td>\n", " <td>-0.032808</td>\n", " <td>-0.013573</td>\n", " <td>-0.012699</td>\n", " <td>-0.010110</td>\n", " <td>-0.011059</td>\n", " <td>-0.028587</td>\n", " </tr>\n", " <tr>\n", " <th>X1 transaction date</th>\n", " <td>-0.048658</td>\n", " <td>1.000000</td>\n", " <td>0.017549</td>\n", " <td>0.060880</td>\n", " <td>0.009635</td>\n", " <td>0.035058</td>\n", " <td>-0.041082</td>\n", " <td>0.087491</td>\n", " </tr>\n", " <tr>\n", " <th>X2 house age</th>\n", " <td>-0.032808</td>\n", " <td>0.017549</td>\n", " <td>1.000000</td>\n", " <td>0.025622</td>\n", " <td>0.049593</td>\n", " <td>0.054420</td>\n", " <td>-0.048520</td>\n", " <td>-0.210567</td>\n", " </tr>\n", " <tr>\n", " <th>X3 distance to the nearest MRT station</th>\n", " <td>-0.013573</td>\n", " <td>0.060880</td>\n", " <td>0.025622</td>\n", " <td>1.000000</td>\n", " <td>-0.602519</td>\n", " <td>-0.591067</td>\n", " <td>-0.806317</td>\n", " <td>-0.673613</td>\n", " </tr>\n", " <tr>\n", " <th>X4 number of convenience stores</th>\n", " <td>-0.012699</td>\n", " <td>0.009635</td>\n", " <td>0.049593</td>\n", " <td>-0.602519</td>\n", " <td>1.000000</td>\n", " <td>0.444143</td>\n", " <td>0.449099</td>\n", " <td>0.571005</td>\n", " </tr>\n", " <tr>\n", " <th>X5 latitude</th>\n", " <td>-0.010110</td>\n", " <td>0.035058</td>\n", " <td>0.054420</td>\n", " <td>-0.591067</td>\n", " <td>0.444143</td>\n", " <td>1.000000</td>\n", " <td>0.412924</td>\n", " <td>0.546307</td>\n", " </tr>\n", " <tr>\n", " <th>X6 longitude</th>\n", " <td>-0.011059</td>\n", " <td>-0.041082</td>\n", " <td>-0.048520</td>\n", " <td>-0.806317</td>\n", " <td>0.449099</td>\n", " <td>0.412924</td>\n", " <td>1.000000</td>\n", " <td>0.523287</td>\n", " </tr>\n", " <tr>\n", " <th>Y house price of unit area</th>\n", " <td>-0.028587</td>\n", " <td>0.087491</td>\n", " <td>-0.210567</td>\n", " <td>-0.673613</td>\n", " <td>0.571005</td>\n", " <td>0.546307</td>\n", " <td>0.523287</td>\n", " <td>1.000000</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " No X1 transaction date \\\n", "No 1.000000 -0.048658 \n", "X1 transaction date -0.048658 1.000000 \n", "X2 house age -0.032808 0.017549 \n", "X3 distance to the nearest MRT station -0.013573 0.060880 \n", "X4 number of convenience stores -0.012699 0.009635 \n", "X5 latitude -0.010110 0.035058 \n", "X6 longitude -0.011059 -0.041082 \n", "Y house price of unit area -0.028587 0.087491 \n", "\n", " X2 house age \\\n", "No -0.032808 \n", "X1 transaction date 0.017549 \n", "X2 house age 1.000000 \n", "X3 distance to the nearest MRT station 0.025622 \n", "X4 number of convenience stores 0.049593 \n", "X5 latitude 0.054420 \n", "X6 longitude -0.048520 \n", "Y house price of unit area -0.210567 \n", "\n", " X3 distance to the nearest MRT station \\\n", "No -0.013573 \n", "X1 transaction date 0.060880 \n", "X2 house age 0.025622 \n", "X3 distance to the nearest MRT station 1.000000 \n", "X4 number of convenience stores -0.602519 \n", "X5 latitude -0.591067 \n", "X6 longitude -0.806317 \n", "Y house price of unit area -0.673613 \n", "\n", " X4 number of convenience stores \\\n", "No -0.012699 \n", "X1 transaction date 0.009635 \n", "X2 house age 0.049593 \n", "X3 distance to the nearest MRT station -0.602519 \n", "X4 number of convenience stores 1.000000 \n", "X5 latitude 0.444143 \n", "X6 longitude 0.449099 \n", "Y house price of unit area 0.571005 \n", "\n", " X5 latitude X6 longitude \\\n", "No -0.010110 -0.011059 \n", "X1 transaction date 0.035058 -0.041082 \n", "X2 house age 0.054420 -0.048520 \n", "X3 distance to the nearest MRT station -0.591067 -0.806317 \n", "X4 number of convenience stores 0.444143 0.449099 \n", "X5 latitude 1.000000 0.412924 \n", "X6 longitude 0.412924 1.000000 \n", "Y house price of unit area 0.546307 0.523287 \n", "\n", " Y house price of unit area \n", "No -0.028587 \n", "X1 transaction date 0.087491 \n", "X2 house age -0.210567 \n", "X3 distance to the nearest MRT station -0.673613 \n", "X4 number of convenience stores 0.571005 \n", "X5 latitude 0.546307 \n", "X6 longitude 0.523287 \n", "Y house price of unit area 1.000000 " ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "data.corr()" ] }, { "cell_type": "code", "execution_count": 11, "id": "18aeee01", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:21:35.195836Z", "iopub.status.busy": "2022-10-27T19:21:35.195166Z", "iopub.status.idle": "2022-10-27T19:21:46.397610Z", "shell.execute_reply": "2022-10-27T19:21:46.396712Z" }, "papermill": { "duration": 11.222794, "end_time": "2022-10-27T19:21:46.403189", "exception": false, "start_time": "2022-10-27T19:21:35.180395", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "<seaborn.axisgrid.PairGrid at 0x7f5e66467790>" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 1440x1440 with 72 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sn.pairplot(data)" ] }, { "cell_type": "markdown", "id": "bc75c2f1", "metadata": { "papermill": { "duration": 0.019083, "end_time": "2022-10-27T19:21:46.441812", "exception": false, "start_time": "2022-10-27T19:21:46.422729", "status": "completed" }, "tags": [] }, "source": [ "# Data Cleaning" ] }, { "cell_type": "code", "execution_count": 12, "id": "e7bcff82", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:21:46.482019Z", "iopub.status.busy": "2022-10-27T19:21:46.481644Z", "iopub.status.idle": "2022-10-27T19:21:58.103335Z", "shell.execute_reply": "2022-10-27T19:21:58.102141Z" }, "papermill": { "duration": 11.646985, "end_time": "2022-10-27T19:21:58.108011", "exception": false, "start_time": "2022-10-27T19:21:46.461026", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "<seaborn.axisgrid.PairGrid at 0x7f5e5df8de90>" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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bVkh2sMcLJElgfoGZOQSk1zmnL4DdCjnBgZidqtUkLl9UiLLcNHS6/MhP16OyID1uMzqdmuSd/9o418lt9CKXPBUiseM1H8qz6Hj9oTyLuOyCzWrkJdttVqPodbOyTLh5TYUsMkHOYZgcf2S8MZ6xVDRhIGcNE/N76LVITZIozU3Dtj2N6HD5md+xWY1o7hngjJGQTa+tKoTdMcgc2NHSKez7pQ89rEYt7l63ALe9+ik6XH488V4ztqwqw0N7T2BddSEznnxJAI98c7EgqR1tC3zP/uCGRbLm8nRAKsT9UnwqOfNDyH4XzVyYVLtg+9Q0Ir6mmnc/ebGhDfdcvhC3vhLxqZ//qBXXryzFnbuOMbb7q29UIRgK4/F3m+Out0LvcefVNah7toHXz0zGepMMJMNO4z0LSRKYkaHn2MGzH9jR4fLDqFPjM9cgL7m7tqqQ8z10pm80kZxj1uG/Pl+KX7w+On53fr0SO/efQVP3gKA9RxO7yWg2OFUST1IRU5YcBvA5AF8nCOKrAPQALAB+AyCDIAj1SPZwEYD2kd9vBzATQBtBEGoA6QAc0R9KUdROADsBoKamRqmnUTBlIWarg8EQU5ZGZ9waNSr4g/wZp3Igh+wUcwz4cNbhxQ+e/STm98UIA1ryIToQFJN8kLr5ywka5TgYBekG3qBPqEy4U0Bzssst7MiNd2f1eGuq0Aad6LuiHQcgUtbEfo5bXz0acwoebaNiQWKeRcexJacvAINGhY5+H2yZ2TGZOk5fAHPz0vDMtRfivTO9CIVHHaubXjyEelZWZ/TzCBEtnW6/JLuRMy+FrgmEwpLtSexZhAKKZHV6HwsS2fvDYQqzsgz43TeX4HBbP0Jh4M8fnsWW2rl4/Ds16HT7kZWmxS9eO8aQCXSAfsmcLJTkpAm+mxBFSSL1hQh9OvmStv8ba+fi51GHFf/93Ce4eU3FlCqt63D58fC+0zE/Px/ICSmIZ6ckScCs18AXCMGs1yQ0vnL2TEB+Zq1c8lSvkUdi2zJNKMtL4/hDZXlpsGWKf1+r04ffvnWKEwj/9q1TWGKzitqkXDJB7kGtXBKb/s7xCJDHO5YaayaYmN/T5R5diwrS9UxG9orSbCy1WWOI2W3rq/CV+fkxNs0mZ4MhivFP2OMaDlM41uFiDqAHg8P49aZqHO9wIxSOEC9XXWCDLdPIzA++e9/83EHs2boCf79hBRo73Wjq8uDZDyIHbNFzi+96oaqnVCydl4pUiPul+lRS5wffmrxlVRnTryNZdhHtU9N7jZokABAx3+X0BTAzU4/NXyzFjAwDDBoVnnjvDFN9t9hmxfMftuBzc3I567tWzb+GCb1HdrNoPj9zKmSeJstO4z1LlkmHJ95rjhnzNqcPmUZtzEHrPZcvwG/fOsX8Li3/8Jt9p5iEGpvViP7BAEIhCq8cbMX9GxbBHxhGfroBT73XjCPtbgBgDs8S2Y/GsneNd1LUdMeUJYcpivo5gJ8DwEjm8I8pivoWQRAvAdgA4AUA3wXw6sglr438/f2Rf3+LoqgpuQkoUDBWZJl0ePJAC9ZWFTJlhk8eaMFT11woeI2chVarJhLakGkIOQZCGTxi5e5CG5scyQdA2uZv7+MPGhfPtIqeaEp1MKSWCQtlgAmJ/QPys7+SgXgbtJR3xfccdscgCjP02C0SpIsFibOyYkkFk1aFGVYDKgssMYTqPZcvwH8/9wkuW1SIR97iEl3RWZ3RjogY0SLlXcQjJqSQ8UcFAoN42qBSSSOhMfj9t5ZMmWymcJjCgWYHbnv1KP7783OYaoaK/BIMDYfR0jOAe/9xEj/7yjysqy5kMmDpAD1a0y363Zzr88VknYsRZvHKn4GI/fd4/Lh/wyKc7vbEHFaMZ8mwlP0kHKYYzcPzkZxIFsJhCv/4tBM/emnUJh66shpfWSAe8GjVKkazlr3O6VTi83ws5bZSfQcAUKsJfmJBJX4tSRJYNS8PJdlpksjaLndEloh9OAskdmAhh0yQe1Arl8SezAA5maS0nM8S83vYa3R0xVGr08db+WE1arG6Io+XnN22vgq3vXo0Zlzn3bAC7f2DONM9wHzfo+804/qVJTBoVMg0avGT1eUwaCMZzPQziR0kXzgrCy2OAQDA+qVFvHNLKENTyv6jYGIh1aeSOidoH7Cwbhn2nehmfAUg9uBwLHbBd1Bn0qqw+fmDuPaSYl7JAjVJ4pG3T8Nq1OI7Fxfju5eUYDAwDLNeg1OdbpTlZeC+PScSSiKKd6hOY7plzUuxByHfkpbQu/aSYvz+m0vQ4xlCukGD7gE/hzB2+gIwaVXYsbEap7oHmOoLu2MQxVkG3LymAr7AMNr6B7HjzVNM9aXYIVr0vY517xrvpKjpjilLDovgZgAvEARxD4CDAJ4Y+fkTAJ4lCOI0gD4AV03S/SlQMO6wWY24YVVZwpkkchbasw4vNj93UFJWr9QMHiHCQKzL+ESUWNr7vLxBY7zy1uHhMI51uEZ04iIEo1jJr1pN4usLZ2BWlgmd7ojeUtUM4TJhl59fD8rjD/D+PiA/+ysZSOYGLfQcmSYd48jylXTGI8dXzcvD7Kw0tPZ5YdSqkWfRoSjDiFanDzlmLZMNbNSosKX+IKNxHC+rM/o5k6lrJkRMSCXj5WqDSn0WoTEw6aYOYXjW4UWDvQ92xyB27DvNZJNRFDA3zwT3UAh6DYmnD9hx9bJizjtLRNPthX+34ulrLxQ9yGAjmtA3aFTY8sJBjsyJXkPC5Q/B3eXhPawYr+BHyn5C/+62PY0xtqaQE9LQ3DPAEMNAZIx/9NIhzMtbjtI8s+B1WWlamA0a9HpH9wmzQYMss1b0++RmyMrxHQBABZKXxFYTiffOlpISMtF7o9yDWrkk9mQFyMnWpJfzWWJjK7Z/fdjiEMw8LLIaMCc3DbOzTZhfYMElc7KQa9bD4R1i/AL2Na19Xhw814+XGkbLrztcfjx5oAU/W1OBU90DGHYNoqooHTOtJoTDFFr7vBgaDvPee06aHkfb++POLb5nd/oCWGLLSHj/UTCxkOJTyZ0TJEnAFwjFVPA8874dD25YBN9IpifdJ0MO2Ad1dkfE/h/9VzM6XH64h0J4/XCsZMFXF+YzPtO2PScZn+l375xmEqD45qTd4Y2xYb73uG19Fba/cZJz/XQ6mJZqD9FyfUPDYdzx2qdMNdxwGPifVyJ/37yqFK8fbsf3LpnN2ZcB4K5dxxlN9CtrilCWa8apbg/u3nUcAHD1smKm+pIeB6FDNHZcHQ5TONreP6a9S2ivberyAICy9sVBSpDDFEW9A+Cdkf9vBhCTHklRlB/AlRN6YwoUTBKkZpLICRLkBDJSM3jcQmSnSJfxiWgeIFUeA4gQw3871I7bXh0l7O9etwBXVBcKkr3hMIU3T3YnvKlnmfSobzge41w9fNViwfuazGYLcjLDhU7AhZ7DZjWKOkbxCACSJDAnN41xTvgcrXuvWAizXs0EgHxaW9FZndFzZSJ0zaTOc7naoPSzzLthBYdUF4LQGOSZdVOmEUiX248wFbkvOpuMvs8HNixiOmg//NZoKd3sbBM6XX7YMg3M55Akga8tKIDVqEWDvY8pHb55TQVsmSaOTEqioCgg3aARLGtev7RoQkkuKXbG/l26aaSKBGrLc7GwMENx0CWgRUCTt8XhFSWHZ1pNOOvwQkNytf1nWhOfZ1JIV7kkqE7Dv08K/ZzGZMg1yIFcMlpOnwVg8qqGkklKy/0sMb9HaC8GhBMWQuFYMp6eE5lGnaC/GKYixCy7Ya5Jq8LMTAOsJg3nu/cc68SJTjdePdQe419sW1+FFscATnR44vpUgr6SzP1HwfhDin84lvkldHDQ2OkBQQC3v3YMf4/TADSRZ6EltthE9Msft/EerBdlGDEYHMaOjdVo7ByVW6lbOQc795/BZYsKeefXiU4PnL4gltgyGNvme482qxEaFTkl/MzxgBx7YCeL/PusA2urCmHLNKC9f5CpPgOA1w+3M+OwtqoQKhK4cHYm/MEQQ/zScnx/2H8GaxYUwOkLwB8Mo76hFTs2VkOvIVGcZRI8RONr6Hyi053wgQAfhPbao+1u3Fh/SJGYiIOUIIcVKFDAhdRMEjlBgtxARkq5pZwu43ydnCsL0pO6yEuVxwCATz9zMcQwEHm/t736Kcpy01Bts/JeI7U7e2WBhTdjXKxb/WQ2WxDMDBeQLYjXaZidyUsTx/EcI6nkON/n3fK3o/j9N5dwSlHZzevyLDr85C+HY7I6o+cKPTfo+/6wxZFUHUip83wsjZUA4GSXZ0zdtW2ZJtgyTZPeCASIEDCvH27HbWvn4+5dxzkE7NMHmhkHmSY3y/MteOyd0zjS7sZgMITWvkHm2dVqEstLs1FkNaDb48f6JYWwWY2SykD55sIj31zMNJpjZxLzHVaMZ/Ajxc7Yv8sm3S+ZIz876XyFXqPiXU/1IpU2QGTd+VxJDquqJbE9czyyNsUwGAzFkNAUBcTrpTDRcg1yUZRuwF3rFuB21gHyXesWoCjdIHrdRGtGjxXJJKXlflYijZnYfiq7woFvD6hvaMXq+bkYHg4n1Cxu+8Zq5Jp1nENFWr5i2/oqzB/x2Wg/wKhV4aYXD+H7K0pgdwxyyGSKArJMGnz/mY/xwIZFcX2qqdJgS4E0JBo7jWV+CVU20U3Hosk6ueCTkupw+VHf0Ir6umUYDIYY4nZvYxdOdLrxUkMbbvlqBU51e7C2qhD1H7ViU40N9Q2tMf7N1toyAMAtfzuKupUlKM+3YE1lJKlhLD1OUhFy7YFOxAmHgSfea4bVqI3J9t1UY0P9RxHbKM40ID/dgGWzIr7b7pHM4xBFobl7AE3dA+hhaRB3uv24a9dx7Ni0iLkPvrWrqcuDnDQdstN08A4FmXWQ73cPnuvHYDAc1wcRk2Uby2Hl+QKFHFagIAUh1emXEyRMRMapnC7jfJ2ck30KOMNiQKHVwCmjKbQaMMMiHMS19w/ybtDt/YOC5LC9T1p3dqkyFDQmq9mCkGxBQEC2QEqn4YtmRxyUeI6RVMdQ6POCYUqwed3CQosgyRqdCU07w+Nhv1LnuVCWRSIkZjK7a092IxAgQsDUrZyDv31yDts3VuNEVAZL/Uet+PHqcpwa0fa9e6Skjs4qE2twIlfWh68p0e4tK7CsJBvhMMXYHB10PfrtpQBFwZZpGnNwJwYpdjaZsjbTDVajhpcktBo0otfJ3TPHI2tTDHJ6KQDyKlTo6+RqDsvRwW3scuN3b3PJ6N+9fQrz8tKwaCa/jwDI77MwWVVDyZzzY/mseH4PewxpctYfDKP+o9aYPWBTjQ1bXjiIO7++gHdd/vN1F8UcXLf2eXHVBTa88O9W5lCxIt+C+TMiWf7sPWFLbSnzmXzVKxfNXjriT/oSkoKaCg22FIwP5M4J2t5tmQY89u2l+KTVybFvurliU5cH8wsssm1HTErq5jUVnIqh5p4Bhgx0+gK4d3cjJ7vY5Q/ijrWVaOn14v4Ni3C2NyK78sz7kYopfzCMMAUmqUYsYWG6zgc59jA8HMbfP+1g9NRjGsxlGtE5kgTT4fKjqXsA1y0vwe2vHWMkbNiNwq1GLR7YsIjxjx96o4nxj0kQONs7AJvVGKN7ThO2YQp4/N1m3HP5AviDYdHqTKcvENcHYcccTV0eHG13czKi5R5Wni9QyGEFClIQUssh5ZRPTkSGblGGEUVRJGyR1YCiDOH7mggdvcYuNx7ae5ITpD609ySKM42CQVxmmpZ3g840Ces6SpWvkCpDMdkQygz/XGkW7+/L6TSciGMkxTEU+rzmngGk6dS8zetsmSYUZRhj5gqAGFJw59U142a/csgAuSTmeHfXnmh0uPzw+IO4pDQHrX1elOaacbbXi3XVhXAPBnGk3Y17dzfiOxcXc8g5djaC0LMnU9aHXVZHS3vQDZJu+etRpnv97OzxI4Ck2NlkytpMN5j1auSn6zlrUH66HmaDuCsvd88cS4aanIZ0cisZhCpUDHEyqsdCssjJqO5w8ZPRnS4/Fs0Uv085fRYmK2MumXN+LJ8lRuBHjyGbnD3S7sbdu47jG0uKUJxpwNqqQoZY+KTVyTsn3m7qwePvNnMOrmlSn9avD4XBZNLRB4r0Z9GSRkKkyIkON/QaEgMCuq3xpKAUTB/ImRPR9l6cZcAvr1gIx0AA66oLGdKN9mcumZMl21cTlJKal4uFRVwpKXqPefnjNiZj/1lW9mnPwBCCYQoP7D0Zs05T1Oh/6aQavn2uMOrQZirGSmOBVL3q1j4vWhw+JnucXqfqVpZgYWE6ZmeZcLbPy+ELhPxcevw6XP4YYp++7icvH8ZVF9gwO9uExUXpjF/AbuhMj+G5Ph9zOMa2ndJcM+7b3ciQu1KaxgLAjfWHJO/z5zMUcliBghSE1HJIex//7y+eaRXUlpKbbSQlo6bV6cODUSTsg3tPonJGelK1kKVCThCXYVDjjssqcefrx5j3dcdllcgwCi+zuWZ++YpcM3/mdKp1YA2EQthUY0u44ZmcTsPJJp/4DlLoTr5aNYGframAezAIk06NWVlGpOnV+Li1D5/1+zmlets3VmNenjlmvNhEN9/zjAVSyYDouUpRSNi5nm4ZoXkWPZ4fKWP89Zuj9nrX1yvxu3ci64DTF0C+RY/f/sdiHG13MR2/6QwJIQ3QZMr6RJfVEQTw45cOc35PTJomGZBiZ9O9pHMi8Vm/H0+914Lvr5yDwcAwDFo1Ht9/BgVfq0BxlvBYd7rkZdbK1bqV25BO7oF0v2+Il1BzDQo3agXkE49y9+GCdAPv+8xPF3+fydjjpGhGjxXJnPNyPysegR89hjQ5S/+9w+XHE+8147rlJRw/MPr3AC5BFX1wLUTqR+8JbFL42ajSbLqXwW1r52Pn/jMxPpVy2HZ+Qc6ciLZ3u2MQ33+6AQ//R6RfyfqlRRyybix+nJCU1Nw8MxYWZXB+l95jOlz+mIz93759CptqbPjdW6d413daboLOeDZq1bz73L4T3Xh43+kpn0wjF4naA1vPFwDnXXW4IvrQW2pLEQxRkX34P5dh38nuGD+XAIHmngHMyjJx/FS23F5RhgH2vlH94t/sO4W6lSVIN2hQnm/hlXsAgBcbRg8J6DV4a20ZhxiWGmcoCQrSoZDDChSkIKSWQ9r7vLy/LyRfAMgLgKRm1Mgp65wIUkpOEFeWY0Fr3yAe3LCIafqjURMoy7GIfhdfd3YhyC2fnSxIbXg2K8sUU3ZEB0RssMc72eQTffCy+YulKLQa0NLr5WRV0B16AeC3/1GNn/zlCK5bXoIn3muOmSu//9aSmPESCi6TZb+JZujyzdX711cl7FzLdbjklGNPBGZlmfDTL1fg/n82ckqA3zjWgbvWLUCXyw/9CBnXMxCIySDeWluGFscAp7HGaMkyf2ZjPFkfPm3A6LI6oTUhGbqBYpCSCT7Vs8ZTBXkWPZq6B7Dl+YPMzxJZO3Rqktf+NHFEa+Vq3Y5FA1HOgTRJkrz7zD2XLxS9T7l7h9x9uLLAwlvBJdYzYCz3KTfDORlI5pyX81nx/FcxcpZ+V9vWV2H7Gyc5nyukS0+TG4kcXJMEQBJEDBld39CKBzcsgk5D4mi7iynNBiLz1T0YxNqqQpAkmBL7pcUZuGhWrH77VN1nFSQHUueE0JrV3DMAvVqV1MMGoRitqcuDinwLCCJyPwXperQ4Bpg95ki7G9v2NOLmNRU43T3A6LPbHYPoGQjguuUlMGhILC22ondgiJPxvH1jNfIs/I0h6eSSqZ5MMxYkYg/0mvj9FSUA+OMQuqLh7zesQI93CAaNirP/3/Slubix/hDzzldX5HHWOKcvAFumCQ/tPcnpweIPRuQ/3m924PJFM/DYt5ei2+1HW1QDPKcvAPdgkPHBV5Rmw+UPcnSQ+exTbL1TEhSkQyGHFShIQUjN6JEqXwDIC/CkEspyiF65HcalOMtygji1mkTtvDwc63Ch0+VH/kjWk5gecEuvF4/+q5lTdvjov5oxM9OI2TzvS2qDt8kGX5nwtvVVcHiHmH9njwFJElhiy+CUHdV/1BqjS71tfRVnvJMZiNIHFg/ubcLPvjIPoTBw46VlMV189RoSp7oH4A+GQRDgnSsmXex4vX64PYb0m4xTbL65eqZnQJJzLdXhmkyyIhFkmjT4yepyNHV7oFWR6Hb7sftYF95vcUbI4NdGqwKKrEZsrS2DNxBiNECdvgB2b1mBWVmmmBLO6PUkEbmPGRl6PLBhEU52eZisnuiyOrFALCdNhxyzTnGEpwnkHsi4/AHezCuPXzyzVq7WrdwDXKkNWmlYjRre3gVWo7gWMxtSMmvl7sMkSSDHrOUcIJsNKklzU8p9yn2f0wFi/uusLFPCzbIAcPZqukHTdctLUJxpiCE3aDmT98/0Is+ix+qKPOwe2SNz0iJk2JrfRDQ6o0nmTTU2/HJ3Ix7YsBAGjYpDiNy+dj7+d/8Z2B2DzPPoNSQe3LAIexu7OHvoVN9nFUw8hNYsjz+Ev37SxqzxK0qzccGszDHZCV+SB32AMjfPzFQ6baktxc79kUZo1y0vgS3TgPb+QSZr9Gdfmces6+ws0kPn+vHCv1vx8KbFuGROFuN7AhBsQkZDKIY9Hw5T2Gsiu1EmOxHnkbdOwx+MSHRsfu4gMzYEEUleCoUpZq276cVD2L1lBRMHdLn9CIYonOhwMWsXDb2GHLkeONEV0Znma4C3tbaM8aW31pYhx6zD0uJMZg3lizMSWe+UBAVpUMhhBQpSEFIzevIs/PIFYo3f5AR4UgllOcGunA7jUp1luY3f1GoSi2ZaRfUD2dBrSN6yQ63A90ht8DYVQGtPqkkSZblp+NWeRtgdg4JjUJRhxJycNG7GZF4aHv9uDT5q6UMoDGx/4yQ0KjLhYEfI8eP7OdvuB4ZCgl18aUeKBt9cyTPrYuz75jUVWF2Rh4WF6ZN6is03V9klXYk411Idrqksi3LW4cX7zQ681NDG6KZZjVqmOYdnMIittWUoSDegzzuEgnQ9bmBlcNLo9ow6zuwSzt++dYpDPNBrXHPPgGBAkmXS4b1TvXj83WbBdVgsEKObfCjEwPSBHC3fLJMe9Q3HYzJrH75qseh1crVu5ZLYUhu00ijPs6Cl1xvTu6A8T7xqRy6JJrQPC8kl0Tjr8OIHz34SM5fjyW3IvU+573M6QMh/zTbpEm6WBQAzMvS4bnkJdGoSpblp2DbivzR1D+Dna8ph0qo5fsE9ly/AlhcOxvg4JTlpaO4ZYORWaI17Pv1NjUoVcyjzwkeRxqjRe3Nbvw+/fvMUZw+dyvusgskB35pFE3G09INeQ+IbiwvH7CeQJIHFMzN4bbupy8PYZXhEioX+/oJ0PcfPfv6jVtxYO5ezrhs1Kjx5oAVXXWBDj3cIq+blAQDjx88vMEeyXgf8MGhU2PLCQU4GK9/+db4cptBr4ssfR3xcutpGRQLl+RY89s5pRjqCluhgy4IAwOZVpcz/s2OB6OZ0P7x0Lna82cSxNXrsKvLNzGfTusI6NYnqmek40eHG+qVFIAmgLC8NtkwTb5wh1EyUvi9lvRsbFHJYgYIUhNSMHlumCWV5aZxNll54hWCzGnH3ugW47dXRbLe714ln6EollOWUe8iRopDqLE9U4ze1iuAl7dUq/u+Q2uBtssHWnvzvL5bih3HGgC4r3v7GScZpWWKzwmY14Ku/fY9jV4lu/kKO3+qKPN4SZnaZ1Msft8V08Z2bZ0auWYdPWp2ME8tXkrp9YzVsmSbYMk289j3Zp9h8c5Vd0lVVaEF+uj4h5zpRTIReuFx0uf0IU5F3QDusBAHkmXWYmWmAvZdCllmNZw4044olM0GBElzr+J7T7hjEYDCEZSXZABILSGZlmbCwKD1mjYgm2uay1na+Jh/0XJmVZZr22THTGXK1fOflpOG/v1CG218b3cvv+voCzMsxi36fXJKXJAmsKsvBs9+7EJ3uIeRbdFiYgHawnAon+vssBjXm5polZeTKJdGkyiXRkLv+yb1Pue9zOoDPdrfWlqFnYIi/WVZ5bgwxDACZRh0jGVWQrse3LrIhP12P1j4fHtvfDK2awPaN1TjdPYDhcBh9A0NMdm/0OEWP/9MH7DENnOjyeL5DGa8/GGNza6sKY2xoKu+zCsYffEkP0WuWXk3CpFXFLdeX+/1negdiJAnuvWIhHvgnV6aFL3v/yWsuwAfNDoTCwFP/14IVc3Nh0JComWXFoXP9WFtVyGSX7tq8HE3dA7x+FICEGpyeL4cp7DXx2Q/suLKmCGW5adCrVbhn93HmQGtrbRn0Gn4pKnblSnQswG5O98cDZ/Hj1XORn24AKOCc04cnD7SgbuUctPX7mM9mH0zs2boCRVZjXC5ArJkoDWW9Gxumv4egQME0hNSMHpIk8IWyXOSk6RJu9HLW4cUjb3MzdB95+xQWz8xAaR5/UDkW4fdEyyUnIqN5wpwFQprmsFCDt6maOcx+70LSC+wxYJfB0rZN25DYtWIlYUJjWV+3jPfnT197ISf7IN+ix+r5+egZGHVYzjq8eP6jVoYQpp3aR765BMc/c2M4HGYy+qYCEcwHvrlKN95jyyMk4lwniqncxC7PoueU2tEO69baMvxyVyNWzM0FQQCXlObAPRjEQbsT912xED9nZeyy302850xkjSFJAqvm5aE0Jw1LbFb4AsOwZZo4usZ0FhzfusDWwexy+3Gi0zPts2OmM+SSPid7PHixwY77NyxiGtk9c6AZ8/LTsGimVfA6uVp9gUAIr33agdtZB8t3rVuAy6tmQCuyv8mpcALkZ+TKfZ9y10W565/c+5T7PqcDSJLA/AIz59DsmfftGAyGOGQU7WdcModft5etidrh8uORt0/j52vKMT/fwjTxupvVh4CdWQdwxyl6/Gm/4f4Ni3C624OVZTmoLooQ1NF78w8vnQudmsQT78Wu8dE2NJX3WQXjC6FD50vn5eKGVWUcaatbvlKOx79bAxVBJPWwmD7EjJYkmJuXxpEbYCdf0Pd0Y+08NHd7OMRyU3dkDroGh/Grf3DJZSHpHCnSZ+fLYQrffu7wDmHL84cYaUN6nZyTmxYzNndcVonH/sWNy9h7XnRzunv+fgLFWQb86htVONHlwdqqQnj8QU7sRH/2tvVVTJYwHWN92OLgtct4zUTp+1PWO/lQyGEFClIQUklYOY1eWnr5m9i19HoFyWGpwaScch45BLRUZ3minAUV+OUj1AT/z+VmDk+Wnlb0e483BkJlsGFKOEszng0JjWWHi//n757u5S3FZ5fh0uTAtj3c5mUPv9mEI+1u5v7ikROTCXquzrthBRo73Wjq8nCae9A2ksxGDlO5azDfmC6ckY5Otx9N3QM40u5mAvIX/h3J2AL82Hl1DTQqbnCVyHPGW2Oi5yyfDiDbSaaz4IR0MI1aFa7947+nfXbMRGEy1lS5pE+Hy48GuwsNdq4MSqfLn7AEkhSt2yOfuRhiGIjY2u2vfoqSbBNqZmUKXienwgmIPAffXIrXIE5q7wYactdFueuf3HGX+z6nCzpcfjy8j+u/ChEJbJ1geizZJBdN4IbCwGP7m7F+aRGv3E+0CbA/uyBdHzP+m2psuG93I0tLfghrKvMZ+2rq8uBouxt/PHAWALD5i6XIt+jR6vTF7Nc0pvI+OxUxnfRmxZIh+gaGOIclj/6rmZMIkKx3wM4gZcePF86yxjQvK4uSjPvzhy245nMlCFNDnHXLrFfD3jvA+R69hoQ2ai7TzyxF+ixVD1Pk2C3f++BLNAsEwzHVyc9/aMePV5fjVLeHU2lB34fDOxTTT+WqC2xw+4eZtZKWDmFLWiyemYHPlWRzEh7EOIFEmokq693YoJDDChSkKKRoD8rJhBUqK9FpxHV3pWRKyrkvOYGZVGd5opyFTJNW0s+FMofFtA4nU0+L3TyQL0sgegyEymDP9flitHDpa+PZkNBYFqTz/5xdii/UuIckCayuyEOaTo0Gex/Kcs24i5U9RN/HVM88IEkCc3LTMDvbhPkFFlxckgWjVoVAKKJLGQpH5FryLHpcyNMRXc73TdWuwSRJoCLfjHXVhbBlGmHSqnHP7uMIDFOM7nDnSKbXphobU9Jb92wD6uuWSe6OLLbGJDpn2U4yW7dv86rSmHLRQCic0IHXdAqUxwuTtabKbcZakG7gtbV8i/h+Jvc5OwUOPrrcfoErIqAz5Uuy0yStDzo1v6+iEWrCMAKpvRui71VqRQi9b9TXLUu4ggsYo7yHjPc5XcC3xvI1hBXSCWaTXE1dHk6PAT5C4o7LKhEIhpjv5PvsR765GPX/uQz7TnYjFB5tMqrXRBq/sn0X2rZurB/1bx7c24TiLAMeurIaF5dk8a7Rydhnz5d9YLrpzYolQ7iHQhwbpmF3eHHoXD+nb8FY3oGQb/PRWSeqitKZqrycND0Gg8PY8Nj7UffcjBtq5yLTpIN3aBh9vgBMOjXCYYozt7bWlmFo5P/HEqul4mFKsuxWqGdFW7+PlzQ+0enB794+zVRaRN9HcZYBO6+uQWA4hCPtLjzzvh05aVrc+fVK3PHaMaZa4va1lTjTM4D8dAN+8foxPHXNhSjJSUuIExCqwIju6ZGK83eqQCGHFShIQbT08msP/l2AzJKTCWvSqXkDp7Qk6tUJ3Ve8jB+pgZlUZ1muszA8HMaxDtdI4GdAZYFFtIkdIbB3Cf0808ivdfjlSmGtw8nU04puHghEgvHyfDMyTVoEQmGcdXiZsciz6HD72vm4K6rpygv/bsVVF9jw4IZFONHl4RyGxLNtobGsLEgX7WzsD4o37ml1+lD3bAP8wTCHjKORCpkHNOhs1xOdHlz7x3/DatTiOxcXxxD5yQiYpqrMRjhM4dhnbjy8L0KwXr+yBOuqCxGmAINGhVyzDp0uP9ZWFTIE8bMf2OEPhrHvRDfa+yPNUDpco8G02HOKrTGJzlkh3WivPxjjKJ91eOMGUdMtUB4vTNaaau/jb8a6eKZVtMFYhlGNOy6rxJ2vH+MQWRkmjej3yX3OAgFyIC8OGQ3IWx9c/gBvgziPPyB6ndTeDWOFnAouGnIaEQJTd72dCPCtsdENYemmVXw6wWKVTzQh8b9XL8W/zzpBUYBrMICnD9hjNPvZn735uYN44T8vwkyrkdPPg/Y9ov1yvmfYVGPDj146hJu+NA8XFMdWlABjG/fzaR+YbnqzYskQjR1u3n/zDoUYchAY+zsQkix79gM7du5vRn3dMtTYMrG3sQsnOt0x/nuD3YXGDjc8/hCzLj/1Xgu+v2J2THO6R946FUNu3nvFQpBExI4TsdepnLQghGTZLUkSWGKLbR6oVROCzanZfmO0rIfdMYi6Zxtw59crmaqNDpcfWUc7sPPqGnS6BqHXqvHoO6ewqjyfqZqwjxxE+VmyPzSiOQGhdZ1PM16BPCjksAIFKQipXajlZMJmpWmRn67nbMb56XpkmfmzWmlIyTgwCjVM0QjrEsqFFGdZjrMwPBzGK4fbY7K6Ll9UKEgQd7j8ePRfzYzeUygcKfWam2/mDU5VJHDVBTZJmU6Tqacl1DzwkW8uxn/9+YOYwMOWaYK9z4sdG6vR2OlGKBwhv795YTGe+8iOtVWFHC3i3TwBHP1vtG2LjSUtq9DU5UFjp5unFF94i2S/18kqa5KT3SN0gMF28r6xpIixMSD1A6ZEcNbhxaluD/QaEh0uPx7bH5mXKhIotBrx4D9Pom7lHDR1R7TT+DK+6laW4OF9pxMKpsXsUmjO2qPGWqjpUkluWoyjnMiB13QLlMcLk7Wm2h38Uk9ih1gA8Fm/H89/yNUcfnz/GczONqI4S7omb7zD24Uz0nHXugUxmsNVM9ITfFJpyDLpUd9wPObQ9OFNi0Wvk9q7YayQO7/kNiI83yG2xtK+4PtnehnylgY9ly+clcXbnJa26etXluKhf55kJIeuW16CDpcfT7zXjD98pwbdniHez27r9+ORt0/hgQ2LcGpEqoK9n7Dtj36Gwrpl2HeCm21888tHYDFoMDvLyOh1JgPn0z4w3fRmxZIhegaGYmz4pi/NRVu/T9Y6LwTaZrOuvRDvnu5lCEfat953ohuuwWHc9OIhfH9FCa//7guEYtZlnWbUH6flXZy+AObmpWHX5uU40eVBU5cHD/zzJCO3kuiBRqodoiXTbm2ZJpTnW2L8yPqPWrG1tgwF6QY09w4wMjb3XrEQNqsRdscAjn3m4r2P6Nj+7aZeNDu8uHvdAjTYnbioJIez5h0814+H953GI99czM8JsHoVpCKZn2pQyGEFClIQUrtQy8mELTAbYNR6OB3ANWoCBWaD4DVSMw7cQhk/Q0EJbyMxSCXSpDoLxzpcDDEMRDbIW1/5FGW5wk1/pAancjKd5OoqJgNCxG1Tl0cw8FhRmgu7wwuTToVOlx9XLp2J5z6yM5maNPgCOCHbFhpLkiRAEMC5Pi8MGm7n5niNe6KbLzz7gR11K0uweGYGikeIu/F0VhKZa9E2X5RuwGtHP+M9wGAfOCXSPDDRe0yV0tQutx8vNrQx2RJ0kL+1tgz37W6E0xdAn3cIBekGTgYmO+MrPKLLStv0vBtWgCAg+PxCdik0b2gHmj3W9AFHa58XRq0aeRYdL1GQiEM93QLl8cJkaRTqtfzyCVqR6hQgcr9N3QPY8vyo5nAi9yv38FarVeHyqhkoyTYxtl81I120Gd1YkG5Q4/rPl8ZkRqcbxTOj5cp0yIXc+SWXpFcQ348Tm8vRa2aeWY8LZ2WiudeLPIseD+8bJYa31kaaudL//9O/HMHGmiLezwYVybC7d3cjrl5WHPdQmSQJ+AKhGP1kfzCMg61OHGx1ojzfwutny9mDz6d9IFX1ZoUgts9HN7c16dTY+sIhrF/Kb6fBEJVw9i3ffeSYdby63KEw0GDvgz8Y5k2seOjKaoSpUbkI2s/63VunsGZBAed3b1s7H//93Ce4e91C/Pilw5zvmq4HGsDY7TZ6XVhdkYfdIzaTk6aHigTK8804eK4fT77XjBVzc7F+aRFIAqguSsc7p7oRHKZwpmeA9z7anL6Yca1bOQcP/vMk7xjScid81/FJJ6YamZ9qUMhhBQpSEHK6UEstS2zscuPe3Y1YW1XIEJG7jrQj/yq9INkp1DlWSLtVqMHa0uJFovcm1eGdiDI5oQZnYk1/5GghS810Gouu4ljB93z3XrEQD/yT23GYHXiQJIHZOWkozjLhaHs/2voH8ePV5Xhw7wmOpi/7ueWW3AKRQOipA3Zcv7KE8xlFViOKMoRJguhnc/oCKM+34PNzc5NOgPLZe7zsHj6bf+qaC3gPMGZlmWIOnMYaMKVaaSo9t+o/asX2jdU40emGVkVCRQA/+tJcdLojWf7fvaRYMOOL3bTLHwyjsdPNBCx6TaQj84wMPbJMOsmyNjT5QH82e6zn5KaJZo7SGAtRkiyIrd2pcpgwWRqFOpWKdy3Xq8VJV7n36x6Uf3ir1apEm88lE809Xt7M6DyzTlQeIlr2iJbpWGKzjkvQKXd+CZL040S2TwbGOvfZ1xu1agRCobjrLBB/bkSvmQQxgI/O9uGRt09hbVUhLinNwcIZ6VCRwC1frcCpbg+eeT+yJ7zYEJttfNva+Wjr9zEVKnQjURUJzM01C/ouQrYTCkcOc/mIMLl78HQjTMUwVfRm5cQ0Qr8vlgwxKzuNWRObewbg9AV4Cdotq8pw26tHGS1YOc9DEuDVs332AztDSEfPgdryXFj0Glzzx49w3fIS2DINaGc12O0ZCKBuZQkK0w1odQ7C4w/C7hhkyGY2puuBBiAcW5FEpDqw1enj2AYAxl4K0vU43uHhXRei39WJTg+nIfPW2jL4giEcaXMBAF5qiLUdtq9Kj2tprhmf9fvQ1D2Ang9GE5xIAnAPBpnYbmAohNcPt8dwAmsWCEsnKkg+FHJYgYIUhNQu1HLKEiM6QLElrGJkp1S5i1yzjlcmIdcsTHLLcXgnokxOTtMfqQ1q5DiyE62ryAZfFgNJQFCfNzrA63L7GQ1YoQybsZbc0qQgLSNAayN39Puwt7GLsSs+Z3wiSpuE7N1q1Ig6w3w239rHXz7Y3DMAW6aRCWQTaR4YD6lWmjory8Q0Krp713FcWVOE/HQ9Ol1+PPRGE0MAe/whPLj3BOpWzuHosbEdYoA/Q/7ml4/guuUleOK95rhZ3uxMDgIEbqw/NO4ND8c7UBZbuwGkzGHCZJU1Zhg1MGlVnH3fpFUhI06GrNz7VakI3sPbRTMXxr1Xqfr7Y4FOTfJmRsfLqBaSPUpkXskhM+XOr0AolFA2VapirAeJfNdvWVWG+oZW3LymIq68jxQfjPan2FJgt792DOuXFmFmhoGT3Uv/7s6rl2JoOIyj7S54/EE8/1ErM550hcpta+fjlyMVKny+C3t/in7GtVWFvPuB3D14qhCmE4GpUKIu1f6T2YyMHme68s1mNaLT7WfIWDk+Bvv+rEYtHtywCE1Rh+mvH26PqdLatr4KlQXp2H+6h1mXoxvsOn0B6NUq/HrfKTh9AVy3vCTyndTYExpSCWxZvMZONyOnoVUTuGFVGacaZvvGamjVBBMnbaktxc79zTHrQnQSl1DsODvbxFTJOX0BhtwnRvyRQqsBTl8A/mAYT7zXjC2rItV3wGii0u/ePs0kTGx/YzRZ6OWP23j7nQitPamSUJBqUMhhBQpSECRJ4AtluchJ0yXk0MopE5NDdkqVu6A3k+hgV6ghGyDP4Z2IMjk5TX/kNKiRmiU70bqK0YjOYgiHKd7Aw2Y1xji8OzZWC2YX0JqqYxnb6OwG2mHZsqoMTx2I6GuVb1mBWVkmQWd8vEubhOy9vu5i3rlm0Kjw/pleDPI0dhDKQNNr1bj5r0fw869UMLalIoDHv1sDFUFwnK5EnbFULE01aFSMk1uRb0GPx49H3j4dE4z/YOUc/PWTc8zv6tUkTFquLMnd6xZg+xtNnM/3B8OMZEe8LO/tG6sxv8AMigIMrM+mMR5zeLwDZbG1G0BKHSZMRlmjxz8s6edsyLlfnUrFe3gbL1NZjv7+WKBSEbwZ1WpV/L1RDqEgl5yRSkTSyDLxN6KdLtlUYz1I5Lv+4ZGM8HifI9UHE/KnKAow6mL3V6cvgP7BYTy09wRuWFWG3751CptqbMx4Rsq3LXjsndPM4R+fXAhJEvjaggJYjVo02PuYfgy03Baf3crdg6cCYTqRmOwSdan2n8xmZNF9N+iDcEC+j8G+vw6XH7/c3RhD+G2qsaH+o9E1bcnMDNy56xg0KhJZJi0zjzpcfnj8QWytLUNOmg6tTh+jfcuWI3j9cDt+ecVC/A8rS3k8JYKmAmhZPLacxn9/sTSmOpDuh0H/LEzxy8Y1droxO3t0ngutdQWWSHPDVw61M4dcdOx029r56PdGSPvZ2UZkmXT4xeufMskVZXlp+PsNK9AzEFlXbFYjNCqSU4EZ/TtCa0+qVSemEhRyWIGCFIQch1ZqECSH7JQqdyG1IRsgT39vIsrk5DT9kSrDISdLdqplgQgFHnwO76/2NMZkF2zfWM1ptpWMAJ/ObjjR5YlpntHtifyXb5wK65bBFwiN64m1kL0HQ6GYcb3n8gVMd/SttaUx7+XpA824e90CTpf0O9ZW4vH9Z2B3DCI7TYvLqwsFA0IpzliqlaaedXhx7DMXnngvklFRkK5npEbUJImSbBMoULjqAhvUJLB+qY2zNv58TTm21pYh06hFq3MQTu8QL6FLsXSJxbK82Q3uirMMMdqo4zWHxzNQFiMrKIGAZSofJkw02voHeffLW79WgWobv9QTDTkZNpkmLe/hbaZJvCmtHP39sdxnmk7Ne59pOvEQR67msFxyRs5hMBDZw29eUzFl9vBkY6wHiULX0wdxYp8jdSz5bIauGslJ0+KOtZW4c9cx3v31t2+dwsObFiMQDuPC2ZlwegM4+pmL8W+AEU1igFfrVa0msbw0G4UZBjR2uqEiCxmiLNoewmFK8DA4kT14sgnT8wlS7T+ZB++0jf1qTyM21dg4B9zb1lfJWmOi74/OQH362gvh9gdxtN3F+Ni0XMH9GxbB7hjETS8ewl+uv5gTRz7/USuu/3wpfjsi5XJlTREWFWXg0XdOMaTjTV+ah2ffb5kwiaCpguh3LdQvJExxr+NbF5q6PJhfYGHel5C8WffAEOYXWKDXqPDCv0cPueYXWOD2BfDIvyKNAutWlqBvYAhrqwqhIoGa4kxcUpIFtZrkxLdCB1HxpNJSrToxlaCQwwoUpCCS4dDGC4LkkJ1FGUYUWQ1R2q0GQe3WXDP/yaRYszQ5+ntyCFKpQaqcpj9SZTjkOIVTMQuEL/Dgeza7I6Ipdt3yElQVWlCWZ47JYHV4h2LKLRMJnKOzG050eXibZ+Sk6QXf+74T3TENwpL9XoVI1kyTDktsmcy4GjQqhhgGwKt3+L3lc3DpvFzMzjahuWcA+pE5TTvomSYdMy5ydI7ZmGqHEvFAN6Rjl/s+eaAFt62txOnuAQCAWa/GYDCEHW9GiABamzgUBp480IJNNTb8et8pJiuQPthgZx7TTRXZa4OQfdEOPU0s1Nctw2AwNCXmsByINcckiPOrLFQOCgQyefJEqnkA+Rk2QhU8YpU9gDz9/bHcZ3meBS29XvR6Rw9jrCYtyvMsovcpV3NYLjkjN5gdyx6eCmW3Y22aK7RHUpTwGkK/F7b0Dw2xsYy2GXbVSIfLD+0nrXjqmgvg8AYQpsDsr0BkHe/zBTA4Mu43XhrJwmcTcltWleFoWz9IItLQi6+J6exsE1QkkJOmw+KZGbBlmjgZf/Q82ranMUaOZCrvwecrpB6kJ7vJtL3PC7tjkCMPQFFAlkkjea0IhykMhyjeDPrsNB38w8MoSDdwbJ4+QAFG597sbBMnjsyzaPHzNRU4PuJv/ebNJqyYm4tLSnNQW56LQCiMBrsLDXYX536m++GykO1E/509jHyycbRvunhmBmevmF9gZsaBlpVw+gK46dIyVM9Mhy2zHBQFmA1qnOxwMxWXW2vLkGvR4cF/cjPRoxOZxrI/pWJ1YqpAIYcVKEhBSF0U7X38QdDimVbB0zk5ZGer04cH955kmtiFwsCDe0+ickY6733JaZYmR39PanAVDlP4x6ed+NFLo0HqQ1dW4ysLhINUOQS8VBkOudmYqZAFIvRsHn8IT7zXzHEqokmE4iwDdl5dA42KSNjBiJ5DfE05ttaWRRo88Di7ek2kGQwwvifWYiQre1zfP9PLEMMAN1uDAsWx+SU2K7o9Q4LErVydYzam4qGEGOgSumejmmWc6vJg256IJtpvrqpmNCU7XH7cves4vrGkCAsLLVCR3Ixzpy8A92DkYEOnJlGWm4Zf7WlkMl3Y71uM3KBhdwzCFwjh4jnZE/RGkg+x9d6WmVqHCZOBHIsWd369Ene8NpqZeOfXK5FrEc/klUtKClX2lOUJV/YAIpJU6eL71FjIU4tBjbm5ZngDwzBp1TAbVAntAXI0h+Xuw2MJZuXs4alSdjvWprl8eyQtAcS3hrDfy/dXlEgaSz6bKUjX4w/fqcFwKMwQtf8+24fvPvVRzOeqVSRu+vMn8AfDgs2X1lYV4t3TvXj8XX5ter4xnZ09+ozseSQkx6Vg6kDqQXqym0zTcUiHy8/YtV5D4pI5NbwZ7GI46/Di1lePxvjS29ZXgSSAHzz7CebmpuH+DYtAURRUBIGdrAMUvYbEx3YXdh1px93rFkKjIpBr1uMzlw+ftDoZGQkAzDWLZ2aMKUs+lRFtO68fbo+JQ2/60lzoVCTzfpy+AIozTdhaWwZvIMRUSzp9ARw8188kvGxbX4WcNB1HR52GeyiED5r78L/7RyvtvnWRDT+8tAzZaTqc7PKgxzMk2idjrPtTqlUnphIUcliBghSE1EWRPhmODoKEMlQBeZl/UoMtOc3SMo38+ntfrkxMf4+i4v9Oc88AQwwDkU3tRy8dwry85SjNM/NeIycLSaoMh9xszFTIHpIS4EWTCHbHIOqebUB93TJ0uf3M50npyN3h8qO+oRX3b1iEpi4P5uWZce/uRpTnm/GL14/xHkjQWaCANJ1jKWORKMnKtyY4fQHkmHWSiVshkuaZ710oad1JhUMJGmz7Y2tP003m9BoSKpKIsZkn3mvGw1cthkETmwFGd60HIgTCrzdVxxD10d/NXgeiG9wFQ5TkYG0qId56n0qHCZOBdqcfe4524H+vXop+XxAZRg3++F4LirOMsGUmP9PVqFXzZiobNeKaw5UFFt6D0sqCdNHrxpKR+4NnP4lZl+I1JZWbgSdXjmIswaycPTxVym7H2jSXvZ9FmtmqEAyFsWZBPu97Yr8XvkNhMZ9KaJ/9oLmPaapVnGkU9O18gdFeAC9/3IbNq0pjqkvYTeaixysRKTL2PGITfpfMyVLW0ykIqQfpyW4yLWSrx9pdcA0OSzpMomPA6Czkwgw9WhyRSskj7W5sef4g02i6aaQyi+1Xd7j8qHu2AU98twZH2lw46xiASqC66OC5frzEUyl3Phwu89mOzWocSQAZbWYMgDMeMzJ0AAFBn9MfjDRQfuqaCwQTF178uI3ZBztckf4cW1aVYcebpxhZCTai99ax7k/jUZ2YCrHyREAhhxUoSEFIXRSlZqgC8jL/pAY/cpqlqUjwNskROzWXekJJOzFs+INhtDi8guSwEDEupoVsyzShLC+NUz5VlpcGWyb/OMoZk1TJHiJJgilhUpMkZmWb8Fm/D+uqCzG/wMy512TIPPDNoU01Ntw30jH8uuUlcPoC0KrJGGd3Xp4ZD+49wTkVTyTIH0sjo3gkq9CaYLMa0dwzEOPsiH2m0Pv9pNU5bR1wulnUU9dcgI/tTpTkpGEbK9P3trXzsfNfZ3ilIpp7BzjBGp99sIl6PgeUPa+zTTo0dXliyObbXj2Kp665cEoRO1IQb71PpcOEyUCeRY/3W/rwdlMv8zO9hsRtl1XGvU4OKen2B3gPxTxDQdHr1GoSly8qRFluGjpdfuSPNF6L14xOLlkrpw8BID8DT64cxVgOd+XsG6lSdpuMprkkSTDvUSiw55OSYDe7jZau4oPQIfazH9gZQsVq1OKSkqwY386oUaGld4Cx8Q6XH/UftWLHxmo0jpTLs5vMAdzxCocpNPcO8I4pO9FDyahLPUjZ+5LdZJovDjFqVHhsfzPTlDnR9YK2vegs5PVLChEKc8lddkLGYGAYrX2DnOorfzCMtr5B3PH6MViNWly/siRmvb7pS3Px1P+dZQjzupUljNSKigQ+bHFMe5KPz3bovzf3DMDpC8AfDMeMR1WRlTlQC1MUfvzSkZhM36Nt/TGyffR65/QFUJJl4m0WeM/lC+D1DzPjrddEmjS3OAYYCRyh/cmeIDmb7OrEVImVJwIKOaxAQQpC6qIoNUM1Golk2wLSgx85wZKcU3OpJ5R6jYrXudaLZEzJ0UIeCxIdE6lN7yYTHS4/bwnTJXOyOGMrFPwIyTwInQbTnZqPfebC6Z4BxrGhs3fuuXwhky3KdnaLswzY/MUyTmM3ofJV9vdSFH9ju2RkcgllEMhpgCQm8fHXT9oYB7w4yzStnO5Wpw8/++sRbKqxYdueRqaRBt1Nvql7gJGKUJFAaa4Z9+1uxPqlRZxgrSBdH9Odm7YPMQe0JCcNs7JM2HOsE21OH2eNo4Om8SZ2xjNzItV0qKca5Gasyn3vWpWKt0pnafGiuPdKkgTMeg18gRDM+sS0K+WStYJ7b5wMZ7kZeHLlKOQGs3IzrFKFJEzGuhAvsBeTkqArQOJlmgPcMWzq8uBouzuG0Gqw96HIakBpThqOtLkw02pAa98gHtvfDACcA5em7gF0uyM9A0pz02Lkiejxou8/TPFLXLETPZR1dnoj2eNLkgS+UJYLg0aF95v7EAoDj+1v5jRlTtTnENujSCJ2ff/Byjl4aO8JXLaokGkGTEOvIWHUqZmDlMf2N+M7FxfjgQ2LoCYJZKVpsfWFQ8x90vHD8/95EU52ecaF5Eu1zFLR8Rg5UDvR6cHJTjdvA2WXP4T5MzTYtXk5TnR50NTl4TTBzDJHJK3YzQIr8i3o8UTGi723atUENj93kFlnhfanaGmLGRl6ZJli9deB5CYUpEqlzURAIYcVKEhRSFkUpWaoAvJO0aQGP3KCJTlN7KRm0Fh0at4g1SzS/VyOFnJLrxebnzsYszn+XYC4laOFLLXp3WQi0WBWLHuHBj2+NNkmZMdzRgKy0z0D+I8LbZyM5b4BP3oH/DG2cNUFNgwGhhmScGVZDpbYrDFZStHf++CGReOayRW9JjT3DMhydsTeL+2Av1B3EUc7rLXPiy73ELyBYRRHNchJFbBLIm9fOx/ewDBa+3y4e9dxpskG3ZBja20Z7tsdySyObvDh9AVQlpeGv9+wAj0D3HUt3pjQhznfX1HCGyyJETtjDVzGO3Mi1XSopxrk9A6goVUTnP1fq47/zk06FW+VjkknTrrKtSO5ZK17UF6Gs9wMvLGQrnKCWbkZwKlCEiZjXYgX2CcqJZHIGkqPIUUBN9YfirGDUDhCqFEU8PC+09i8qpSzlj/7QSTDsTDdgFbnIEPE/eX6ZSjPt3AqRuj7oveFGy8ti5vooayz0xtjHd9oG6eTCE52unmbMks5TBLbo2Znm1Cay41DCzP02Fo7F7/Z18S7hrf3+ziZ9tv2nIReQ6JuZQlqy/N4CU2jVoVr//jvpJN8qZhZKlblMivLhE/b+3HTi4dgNWp5q+LqG1pHEiRCWDM/H/MLLLhkThZy0vRQkUC3Zwizs01YV13INFCmKApP/F9LTPb4/SPxD71vxZNToysxrlse8YXH+12nSqXNRGDKksMEQegB7AegQ+Q+/0JR1B0EQcwG8AKALAAfA7iaoqgAQRA6AM8AWArAAWATRVFnJ+XmFSiYBhhLcxgpwY/U35eTXSQ1mAuDQr5Fz3Fi8i16AMLpulkmfi3kNQuEtZClErdytJDlSIpMJNiOakG6PqFgNto5NmhU2PLCQV6Zh0Ts2JZpQnm+JcZJeepAxEm5fmVJTMndo/8azayYX2AR1TWkv/dUt2dCM7mkODvRAcPqijzs3rICdocXB8/182Yz0de9dbILp7oGYjJlp7LTzAd2SeRdu47j+hHNtPVLi2DSqlCWl4ZvXWRDaU4autx+JjBx+gKYnW3iJYOj53G8MaHXBKlamMkIXMYzcyLavi6cpehfSoXdwd87wO4QP+g76+A/hIyXKTkYDMGoUcWsff5gSPQ+5VaryCVrVSqCd+9dNHOh6HVyydOJJl3H0oh2dUUe6uuWocMV2V8rC9Kn5LyL9gPDYYpXDkkI8dbVaB1eWkqiONOAeflmLCzMAABJa6iKBG5fOx938RAq65cUAoiMU/Ra7vQFYNCo8Ot9pzh7aqZJhyW2TF7Szz4idfb0AXuMP8KX6KFI9JwfSLSCkAafn7Dz6hqGIJTic/BBrL9NcaYxZu9w+4exuCgd66oLQZLA/RsWQUUAJ0cyVAEI9vu4cJaVdx0OhMLjQvKlUmYpW0JHSO7wRKcHHn+QId7rP4r0dznBI3Hj9AUYfyE64aamOB3/74tlOHSuH6Ew8Mqhc/jvL5bhdlZl5R1rK/H4/jPQa8hIhvqZXuRZ9KjINzNrGd3nJVragiAm5l2nSqXNRGBqsAP8GAKwiqKoAYIgNADeIwjiHwBuArCDoqgXCIJ4DMB1AB4d+a+ToqhSgiCuArANwKbJunkFCqYS5ASHU/UUTSi7qHqmcHaR1HLcdIMWf/7wOL5zSQkGA8MwaNV45kAz7t9QLXhfNqsRN6wqk1TyK5W4laOFPFZJkfEEn6P6yDcX85Js0WAHP+EwhZvXVPAG6x+2OETtmHaicsxa1Nctgy8QAklEmjjQTspj+5vxjSVFWDDDgsZON6fkTq8hYTVqMTwcRqvTxwSzfPPnxYY23HvFQtzyt6NTilQQIhZXV+SBJACnL8ibzQRE1pYjbS7s3N+cEk6zGGxWI+5etwC3vRppsPHkgRbcvrYSjR1uDAyFcPeu4/jWRcUIhMN48kALkzm+xGbFJbOzoNWqBMkv2s5IghAdE3bncHan+eVzslEzK5N3LoTDFI6OZICMZQzGa81PxYybqQidmuS1HW0cLV+545pl0uHJAy1YW1UIggBCYeDJAy146poLRb9PbrUKe/7RdnL3uviyGToVf4azXi2e4Sw3A2+iMzPHolUsR1ZosiFnvYi31/E1oH3ivUjZsy3LmFBVR/QBV5fbjxd4CJXNXyxjbPa+Kxbi5387ymQLz842wTEwBA1JcvbUe69YyNhQNKkbDlNQq0blrWh/JN6+wPdeU6kkXgE/5O6nQn5Cg72PIQjZvTVWlGbjggRti4ZYTHOsw4Wf/OVIzL/95fqLOckZNcXpuLLGxmjl1je04nffXIJT3QPw+IcZspJCpE9JdLxw1uEdF5JvqsbE0RCT0AEi70KjInHTi4fwwIZFzL8faXfj7l3HcWVNEcrzzQAKOUkhdCVmtA1dVJKD//fnT2LezVPXXIBuzxBUBIGd+8+gqXsA91y+AFteOAi7Y5CppqSlBDevKuXNBKcPQMb7XadKpc1EYMqSwxRFUQAGRv6qGflDAVgF4JsjP38awC8QIYfXjfw/APwFwCMEQRAjn6NAwbSDFEdPTsMWuc1hxhuCHdRFtH2lluPOyjLhe8vnSNok5DSpkUrcytFCliMpMlHgO4mnNamWlWQn/DliwbpY0CjkZM/LM3OcFDqQvPWr5SiwGDhB3Z1fr8SpLjd8wRD+608fM5/zh6trYr7X6QtgiS0Du8dAKkiZ94k6O0IZETuvrkHdsw2wGrWoW1mCuXlmVORbOJIRkWYWSAmnOR5anT6kGzXMXNGrSTg8fgRCkeyFddWF0KtJ9HsDDGFWXZSBO177FDevqRAMzth2ZjVqRZv6sdcE2u621pYh16IT/ewTne4xj8F4ZU6kUsbNVIZcTV654zoryyR46CYGudUqZx1ePPI2dw995O1TWDwzQ/DwEwCy0rQwabkZziatCllpWtHvY0NupDAREcZEaxVPNuTcd7y9blaWibexUn1DK1bPz8X7Z3oxGAwJrqF88lR/uLoGTd0DuHvXcXxjSRGzRzi9Q5Gsve4B9Hj8jD2HwpH98tdvnoLVqGV+ThLAEltGzHjSe32PZwgnOtyS9oVoKAd00wdy5oeYnxCmRhvF0VIAeg2JbywulGwbYjHNiU4P7/xqcw4y6xtdqbbnaAfTqG5GugEdLh9+/WYT5zM/bXfhP59piLHj8SL5UiWzNJ6Ezj2XL8AnIwcC7f2+GEk0g0aFjn4fr3Qjnw3Rmb1s7D3ei/9cWYo5OSY4fUHcUFuGXLOOIYaB2GpKvntlywWO97tW5HhGMWXJYQAgCEKFiHREKYDfATgDoJ+iqOGRX2kDUDjy/4UAzgEARVHDBEG4EJGe6I36zDoAdQBgs9nG+xEUKJANMVuV6ujJaZYmNxAdbwhp+wZEtH3FSp34yGE5m4ScJjVSiVurUcM7JlaDRvC+SJLAqnl5KMlOG5cNbyxrqtChRVOXBwAk3adQGaWYoyhU/vzy9RfzZviSBPD4u2ci2lmBYeSnG/CnD5pRlpeB7oEA53NuffVoTDC6fWM1bJmj2UFSIXXeJ2rHQuPAziihG0Ts3rKCc32uWQ8VgSnvNCdip11uP5p7BqBXq5j1pTjLgJ+tqcCp7gEMh8OgqNFmLXpNREfN7hgUDc7Yznp0V+3opn5S1wT6s4UyRKSMwXgFVamScTMVIGanWrWKlwTVqcQzZOWOq9xgyaRT8e5T8bSKWwRkM8QqYwCgKMMIq0mLXu/ogZ7VpEVRhnjG8Vgy8CaaaJtIreJEMJ6xlJz7jmerJEngawsKYDVq0WDvY7J8b1hVxhAWW2tLBddQPkLu1leP4p7LF+LWV44yhNqWVRE5qpmZJl7t+IJ0PTM36Gtov4CN6Oy/lz9ui5GTsGUaEz7kT9WDgmRgusX9cuaHmJ/w+uF2Xl9Vzr4v5r84BgK88yvLpMWHLY4R8lXFZJK+3RShbwrS9fjxl+fGyBs9NlKtFm3H40XyjXdmabLsVEhCp6rQgvx0Pba8cBCXLSqEXkPyytSY9WqEQqONL/WaSGM4FQlRXzP670PDYVz9xEfMZ9y/oYohhmmwqyk7XH7UN7Ri59U1UJMEAqEw7njtU8bXnogsXkWOJ4IpTQ5TFBUCUE0QRAaAvwEoT8Jn7gSwEwBqamqUrGIFUxZitirV0ZPTLE2OfAMgvXRN6u8LdVD/3JwswWvkZDJJ3STkZFpLJW7NejXy06O0kNP1MBsSW8rHI8tpLGuq0En80XY3bqw/FBNwyymLFHMUhcqfj33mxo43T8Vky4bDFPQaFT5pdSIUBn73zmlsqrGhvqEVa6sKOZ9jdwzCrFcxUhXJKOOUE+AlYsdC4xC9PEQHIOEwhRbHALJM4tmwUwHx7DQcpjAcojAYCOGVQ+3M+qJXkzjX58VMqwEWgwZ37TrGOKu0jhogHpxFB3N8Tf1oSF0T6M+WqlHMh/EKqlIl42YqQMxOM01amA0aDglqNmiQGSdDdizjKidYkqtVLKcyBohUBj249yRH/uLBvScxvyA9rhazHMJMrqbyWCBn7xvPeTeesdRYNJbFbFWtJnFJSRbSDWp0uPz44rwc/OilQwxh8WJDm+A+xidPZXcMYna2kbFzigJT8h4KU8y6/MNL52LHSNaj0xeASavC/169FFSYgkGrjqkU4yv/d/oCjJwEMTLsmabEM+PP5wO66Rb3y5kfYn7CzWsqsLoiDwsL08e874v5L8FwCHesrcSdu44x333H2kr0eYfwgz8dFK24c3iGMDfXjBBFoalrgCPtxmfH40HyjXdmabLsVEhCZ/eWFUwSE9sOHtvfjCtrijAr04g0nRp37joOAJwYuzBDjw4Xvw29frg9Zly31pbheLuLs0ee6R4QrKb8+w0r0NrnhVGrRn66Dsc+82DbnkasrSpkpNvSDWqcdXjP22zeicSUJodpUBTVTxDE2wAuBpBBEIR6JHu4CED7yK+1A5gJoI0gCDWAdEQa0ylQMO0g1dGT0yxNjnyD1IwaORk4bn8Am2pskjqTT4Tu7lgzrRMhbj/r9+Op91rw/ZVzGC3kx/efQcHXKlCcJV5ONhXLCflO4ukyouhAfSzPIeQoCh0aGLRqTrZsfd0yJrNhWXEmKIrCwXP9WFtViPqGVtStnIOdIyQh+3M+truYLrsXzR57Ay45AV4ipALfONx3RRV+ve9kzDOxAxBay9xq1OI7FxfjgZEywPJ8MxYUxpbJTmW09Hpx66tH8b1LZsfol/7w0rm4/58nkZOmxY9Wl4OiKEZH7Ui7G0Dk3RCI6FZGv2OpwZxYYBM9nvShVLRGcW15LhbKGIPxCKoULbfkITgcwtxcM7yBYZi0avgCwvseG3LHVQ4pKVerWLAyxihcGQMIN+qLp3EsR24LkK+pLBdy975UnXfjdd/RGsxbaks5mWx0QsSDGxbBpFNxqjqE1vAskxazskycKqMtq8rQ1u9j1uU/HjiLzV8sRa5Zh+w0HU52eXD7q59iXXUh42NsW1+Fry0oAEkSMaXbbDKGnaH8s78ewVPXXMg5rBWaq8oB3fSBnPnBbrYr5CfQzcbOOryMvyuHiBPaawiQePmTVkYugu7l8t1LIo1/6Wz86Kq9rbVl0KlV+OXuRtzy1QpOJj4wsXacCpml8eyDzw5Kc824b3cj1i8tYrSe6f2Ulhj5rH+Qc+3mL5YiP12P1j4fnv8oUg1nsxrR6Y6so+uXFnHu68WGNty2dj7uZjXw3L6xGkUZxph1me5hwr6H65aXMPHUVIhfpzOmLDlMEEQOgOAIMWwA8CVEmsy9DWADgBcAfBfAqyOXvDby9/dH/v0tRW9YwXSFVEdPjnagnGxjqRk1cjJ3hDKHlxYvEryvogwjiqwGTiZTkdUgWnYqNSgWyrRebBPOtJYa9OVZ9GjqHsCW5w8yP4vnGE3VcsJwmEJLrxdmvQrPXHsher1DOPaZh9MAwR8Mwz4yBkatKunPIXRo0Ob0Mb/jD4ax70Q3E8TtvLoGv3j9GNZWFcKWacC66kLUf9TKe2DBR3KPBVLnfaL2RXe133l1DVNy++cPW2IaLEavGTS50uHyY9ueUSL5hbqLUs5xo6VnHtvfzBDdvqFhzLAacOsrkZK3DpcfW54/iOIsA+pWzkFTd6QtAm03N9YfgtMXkKyBl+haI9TAkf5sOkNk+8ZqWcTweEHRcksOOlx+7HjzNJM9SFHAXz9pw45NJtFqHkAeySuXlJTTnBUAyvMsaOn1xuzT5XkW0ev0WnmN+uTIbQHyNZXlQu4enqrzLln3HW3zFAXOe2RrrdJw+gJo7PRgRVkW590KreGRf4vNHtaqCaZUv8PlxyNvn8aWVWXY8eYpxr8Jsxot3fzyEViNWhRmGGJKt2kypm5lCQrTDWh1DjJ+EruxrthcTdWDAgWxkDM/2OMv5CeMdyJJnkWH2op8/PQvhwX9bbtjEL0eP3ZsrIbHH4RBq0ab04fH9jfD6Qugo98XE5duW18Fm9WI5p4BpdkixO2Dzw62rCrDfbsb0eHy4/XD7UwTTbYNqEjg1lePMu+eXtN+vqYcFfmR/TkUBh56o4mprIt+/U5fAO7BYEzDw+j9TaiHCa1tPBXi1+mOKUsOAygA8PSI7jAJ4EWKonYRBHEcwAsEQdwD4CCAJ0Z+/wkAzxIEcRpAH4CrJuOmFSiYCEh19Gjyp75uGTpcfhSk61FZkC66ecrJNrY7pGXUyMmEzLPoeDuTi2UBtzr5y04rZ6QLZudJdZJyzXreTGsxWQmpQZ8cB3+yywn5SAkAMe93x6Zq3oyAg+f68fC+09hSW5r05+DTRzNpVXj0X82ce6DPQ/zBiA4vnaVWkK7H1cuKI41nRoK30pw0tPb5YkhuuqnNWLqFSx1/KfbV6vSh7tkGzjvuGTiF+rplGAyGeAOQ6ZSNRBM+bKJbryFx06VluHrZLDy49yTzzq+6wAarQYMfr54Lt38Yc3PN+OWIcw1AkgYe31pz7xULscSWwehT0xBq4PiPLSskre2TgVTIuJnqyLPw7zHx5pvcoF8uKSmnOSsQKfv/SmUBbJkudLr8yB+xZXUcklen4tc41qvFSV45/QsA+ZrKciE3wxlI3Xk31vvms/kHNyzivMeXP47NZKOb1K1fwpWJivahZ6Tr0T0whDW/eRdba8tg0Khi7GFRUTrq65ah0zWEYx0ujk+g15CcajHatxgOZ8AfjC3dphtF/XrfKc5n0HM/3lxN1YMCBfyQOj/EYkB248PxTCSxZZowO9sU1992+UN4atdxXL2sGA+/NSpV8MNL50KnJvHnAy1MxmtFvgUVBWZO5ulUqo6cLAjZB70OFNYtw7unelGSk4ZtexoZQrdu5Rz8+cOzePTbSwGKgi3ThOJMI/af7oHdMchkGxMEMC/PjAf3nkBgmBoZK64cj1ZNMPEBvbY+876d+a5lJZkA+Pc3vriCYh2mnQ9yOJOJKUsOUxR1BMBinp83A4ipTaMoyg/gygm4NQUKJh1Syd7ocrpENk852cZSM3jkkEtSGzYB0pvFyQmK5chKdLqkBX1yHPzJJPCESIm5uWkx7/dX/2iMCdS21kacCYA/y2eszxGtj5aTpkeLYwBOX4D5fHa33Oj7YGf00M3FSAL46UhjD/Z90p1+x+LARo9/TpoeKhKCJYBSDgb4ftfuGMRgMIRlJdm89zOdspFyzbFZ5HdcVongcAhP/F8Lfrx6LvLTDTDr1RgKhvHIW6fQ1D2Ae69YyCGGAWkaeHxrzS1/O4q6lSUoz7dw7ENoPI91uPHjlw7LtisFqQG5800uySv3YLHTxb/fJkJmqtUkFs20YtFM0V/jICtNy9uoLyuOFrOc/gWAfE1luZCb4Xw+g8/mT3V7OO+xw+XH3z45h0e+uQRH2vqZJnU3r6mImVN8khR06bM3EMLLH7fFVI3NzDTixy8dZmSX2H4F27ehfxYKAybd6CElu+y7It+Cbref8xnsuZ/IXE3VgwIFY4dQDLi6Io/5+fdXlIxrIglJEri0PA9GrRoN9j5oR4Ijtk3fvW4BHnn7FGP/D2xYBLvDy5CYgWEKV9YUYU5OGs71+XDXruO494oFU7I6cqqCJAn4AiE8uLcJBel6TiWSxx9Eg92F//rTx6hbWYIQReFklwcnO93MukTv63QF3d27jjNx0Nw8M8rzzFCrCPQMDOHFumX4zOUHRQG/YpHQtCZxgcUQs7+9/HGs9js7DkvVBJRUwpQlhxUoUCAMqWSv3EZWUolIqRk8NqsR91y+QFL5qdSGTYD0ZnFygmI5shI6NT+ZrhFhlKU6+JNJ4AnZ3Y6N1bxEpMcfZPT+jFo1bqw/xJBuY224JVRWTZdakQTQ5R6CTk2i/j+XwRcMwahVYcsLBznEX3RnZ6cvgDk5aUjTR7bTGRYDr02TBJLiwLK14eKRzVIOBuQcIkyXbKRwmMKZ3oEYgkkFCsMEgXXVhegfHIbb70FRhh7dngC+UJ6LH66eh9mZBia4oSHFeRVaa8JUbAay0Bg1dXmUwOg8gNz5JpfklXuwKGdfGwuKMoywmrScRn1Wk1ZUNgqQ178AADINWl5N5Se+c0Hce5Uj7yFH4ut8B5/Nv9jQhrvXLcBtr47uzavK8/Hwm01YMTcXKhJ4+KrFvJI88Uqf+TL66XWZ9g3rVpagIt+Csw4vci26mEPo+oZWXLm0kLfs+66oJlF0SbaiKawgEQj54vV1yzg/T4YN0ZJx9j4vTCMNF+kqKLWaxPLSbKQb1Nh3ohveQAibv1gK/3AYJAEMBoaZNbnD5ceDe0/g/32hlNOcbFFRBv70/lm83dTLyPmMJ6k9HcHWoI7W9QVGfdAjbS7s3N8Mq1EbswdtqrGh/qNWTnKMzRqrHwwALzW0cUhoWpO4sdONB/55IqZKYna2CVtryxAMUSjN5WY3p2oCykRCjp/BhkIOK1CQgpBK9o6lLBFIrFkaEOmezJfBI9RVWW75qVSCVGpWrxxHW46shMsf4A363P6A4DVSMZkEnpDdhSiK9/36AiFG7y/HrOOQbh0uP+obWkVlDoQgVlYNAG+d7MKproGYLuUXFGfGZM+zOzt3uf0IDIdx+2ufwu6INGvYeXUNr03fcVllUh3YRNYAKQcDfL+7bX0VHN4h5t/53vV0yEZiN9a75asVONXtQSgM7NgXmct3rJ2PgcAwejxDcHiDCITCqMi3oL3PC72alPXeaAitNRQVax98Y3TvFQvxwD+5jQOVwGj6Q0pHjdw0Ha+NZZvEG7LKPVgU2tc8SdzX2LD38ctGzS9IF20QJ6d/AQAMDod4pa38w+KZw3LlPeRIfJ3v4FtXnb4AnN4hXLe8BLZMA1r7RrV76cail8zhbxwrVvrMd3B929r5eOStUV+QbnC7pbYUD+87japCC7ZvrMaJTjcnY9mWaYIt04R5N6xA6wi59pOXDzMH1HRDum8sLuTc53Sq4lGQfAj54h2s6sWxJmAA/Gvc1toylOWlYdW8PCYhY2FhBtr7/THNqB/9VzO0agIPbliEE10eUBSw52gHfrK6HAQBZBg12PHGSTTYXUziRZpepRyMSITNauQkufBl51IUEMaonTBN6Cx6tDoj0nlOXwDXrSjB5+fmgiQJnO7yxByiAfyHZyQBNHV5OHIVdJPEyoJ0hmS2GrW4sqYIc/PMqMi3YHZ26iWgTCSSoR2ukMMKFKQgpGYCySlLlLPAEALrjtDPheQeEiWtE4XUrF45jrYcWYl0vZY36HvoyuokPPUoJovAEyK+zvX58MNL52LHm02cd2XUqPDkgRasX1LIOwY3r6mQ1WhLjEgFRk/Ho/9995YVDLFON8ULhMJodfpgsxrxmWsQP/jTx5zr2JrEbNDloslyYBMtI413MMA+YZ5fYMbfb4j8bjBE4bZXjzKk93SWKmA31rt3dyM2ryrlyJt0uf1QqQgMBkPMoVe324/H9jfjypoiXFFdiN0jNjI0HMYdrMOCROR7ou2cdtLpwyV2o5XVFXnYzRpPksCYMpcVpA7kOv2DwyHevSkemSn3YDHLpEd9w/GYfe3hq2KU4nifUWrGi93h5V1z7Q7+Xgc05PQvAIA25yCvP1GSbcKCwgzB6+TKe8iR+DrfIXaQ1uHyY/OqUt4eB0LrZnT1Gbv0mT643r6xGqe7BzA0HIbHH+Rdl+lk7yPtbty96zi+saQIxZkG/GR1OSryzYwG7MkRkoWWpIg+uI4e++lSxaNgfCDki+ewDg75ZNKk2hDfGvebfadQt7IEJdlpTPPEsw4vcsxa/Pn7F+Fcnw/NvV6GbPzhpXPR5x3C4+82MzZ/aWU+zDoVbvnbUaytKsSyOTlM4sW3LrSNmdQ+n0BXHm9/4ySuW14Cg4ZE5Yx0/OL1T5nsXNoH3VhTxLGPB/c2oTjLgB+tLsf6pUWgKKAwY0T3vHcATd0DMXHJ64fbeeM9W6YR9/y9EQA4GcyXzMmCWk0q65lMJKMJvUIOK1CQgpCa2SqnLLGll3+BmXfDCsGAq8Plx6P/ambKR0Jh4NF/NWNuvpmXhJ0oLT05Wb1aNcHJgNaqxTclObISwXAI168sxZ27Rpsu3LG2EqHw+GgXTjSEslG3v3ESgWGK0XEFBZxz+vDkgRbcvKYCJBHR0aXJyp6BsTkHYkQqRQl3x6WJ1llZJpzo9ODaP/6beY7//fZSdPJ8rpA2cp5Zl9TMnkTXALGDASGyaV6eGV/77bvnjVQB+112uPyo/6gVOzZWo3Ekq+vJAy1M0yFvIIRQGEz37FA44ox9fm4u2pyDuD7qsCBR+Z55N6xAY6cbTV0eJkjavrEaLY4BbH7uYAwZSH/e8HA4JgPk3isWgiQi46s409MHcp1+uWQmIO9gsSLPjP/+Qhluf220fP+ury9ARZ5F9Dq55LeQjIVQrwMacvoXAEBBuoHXn8i3iB/IyJX3UIg/6eB7Z+yDNKEsSZvVyDmMo99z9OG/0xeAUaNiSuLn5ZmxbU8j7I5BAEBBuj7mQObeKxbiN/uamHukZSPoeWnSqTA7J43je7MlKaqLMpCVpkUgFMZZhzfGBqZDFY+C8QGfL37XugW47x/HY0r6y/MtTCaoVIjJZNFNmdlr/JbaUrxzohvXf6EUV9YUIRQGnvvIju9dMpsjN+H1B2HRa3gPAd1Do5rfdOapnCSS8wVsP4J+l7d8ZR6uXDozJis406iNIXY31dhw3+5RmYdvLC7EnmOdONHpxtw8c8wh2ncuLsZzH0WyjnPNOuSn6zHTagQhkNhg0Kjw/pleZv1V1jNpSEYTeoUcVqAgBSE1s1VOWaK9z8u7wLT2CWfjSCVh5WrpSc0uIgn+rF6hS+gy8+hgc7dIEC6nkzwBEi9/0or7NyzCYGAYBq0azxxoxk++XCH6/KkCvsaJFXkWaFQkbnrxEO75+wkUZxlw97qFqE7LwOr5+WhxDGDNb96VXQ7Dh3hEqooQ11rjOyj5uNWJslxzzHWvH27HL69YiP/521Fu0DlSLpqsAD8ZZaRCZNPvv7VkzM5FKiH6XTZ1D6Db7YdWRcJPhXHVBTaYdGoA3GyWH146F899ZMclczJx1uFFg71PNvkzO9sEFQnkpOmweGYGbJmRv9Nzgf4sNhkYnQFCNy569J3TuOVvA9M62/t8hFynX5DMTB+f7PJWpw8vNthj9rUltgyU5pkFr5NLfqtUBO/+rlaJ2z1JEvhCWS5y0nQJNfalkWFU447LKnHn66xD3csqkWHSiF43Fl1YhfiTjuh3Fg5THD3f+oZW7Ly6BhoVgTyLPkYvk+1/sA//bZkGtPcP4rH9zYzcA7s5Ex95TBJAWW4abvrSvJhS7vqGVqyrLoRRq0ZzzwBOdXs4NkJLUjz6rSXYtPODpPpGCs4P0L74zqtr0GDvQ2muGQ/tPQG7YxDt/UOM/7B8TjZy41ROiEFojSOJSHzIp93d1D3AZNGb9WrcsbYSd+46xlRfba0tg0GrRnu/T1CCKzrzVJkTwuDzI9xDITz+bjMjrUYT9Y/tbwYA1K0sgS3TCJNWzWkst31jNVQkmIaGbU5fzCGaSavCAxsWIUxRnLiHvR7Ta9o9ly/AlhcOSq5YHKvG7nRCMvTnFXJYgYIUBB/pJhbUyClLNAlm9QovG1KlFeSQ1nKyi1ocXt7MqfJ8M2YnSaNZDlln0qlQW5GPn/7lMOd9maZJF3KxDsm7eUjS5p4BDimfrIzVeGOzsCg9xm4furIaJAG8f6YXA0PDvBnCHf2+mOuuusCG0mwT7/MBSFqALzebjO1EDQZDvHaebAmMqQ72u+xyx0pqbFlVhpc/bsV3LynBo99agh7PELo9Q3juIzu+dVEx9GoVutx+waxxsQoFQHhNsxo1omQgXwaIXhNpKnKk3T2ts70TxXQKGqQ2VqVRWWCJacR197oFqCxIH5f7bHF40WB3ocF+MObnYuSw3N4IBrWKt9eBUCNcGlIb+9L4rN+P5z/kkt+P7z+D2dlGFGeJy0MourATA6F5L7ZnNvcMCB5OGLVq5oClIF2Pq5cVcxrK0c2ZrlteAp2aZJoosfeQ98/0Yl6BGY99eyk+aXUyWsNXXWCDSatCmKLw1YffxQMbFvHO81CYOm+qeVIJqbLHtDp9qHu2Af5gGJtXlTJZ7mxiNUwBj7/bLPnggX4HDu8Q7l9fhZ+yDkBoCQGSAEfjGOBm8NN62nddNh//85X5GKbC0KtVsDu8+P07ZwDwx5fPvG9nPi+R/fB8gZBd8pGHrx9ux21r5+PuXcdx7+7GGCkbvVqFh/ZGqh6urCniyI582OJgPuv5j1rxvUtmc/divRoUqJg+CdHrsUGjYohhIPE1Lhkau9MJyfAzFHJYgYIURDhM4Z/Hu/Cjlw5xyKyvLOBfDOUQSXkWHe9GLKbHJ0fbVyppLSe7yMRy7GmIEd2Cchca4WBTzjt2eiPZJeyN1KhRoX9wfBr3TDSExurpay9EjlmHC2dxT/jjZcbJdcLjjc2qeXkozUnDEpsVvsAwZlqNONvnZbI2H/nmYl5n6idfLkffwBBn/Mx6NVSqicnySjSbjO24f9bvZzKXttaWTogERiqAJAnm+RzeITx81WJ81u9HMEyhx+3H5Ytt2PHGSdRW5GOm1YhZ2Wp89+JZUJMEstK0CFMRm+BrTCSmOw6IdRK/WJSkF5ovtMb7dM72TgTTLWiQo2sPRN6DxaDGgxsWwRsYhkmrhkYdydyJBzlrrl7D3yBIL7J/AvJlpsKgYNZr0Osd3TfNeg0A8eeTm6mcZ9GjqXsAW54fJb8TOTwbizxEqhBQUwHx5r3QninmfwRDYWZtZ2sME6AwI92ALfURUoNubEfrcjaNNNWqb2jF2qpC/ODZT/DPG1dATRL4rH8QP15djo5+H0x6NX7218i+3M5z6Ly1tgznnL6Ye0t2fw4F0pBKe0y0fQtl4Uo9eIh+B8VZBjz+3RoEgmGoVQROdLhxz98b4fQF8IerazjfS8+lF+uWodU5iKYuD3bsOw2nL4BHvrkY/uEwtv3zJPNuc0fiUm8gBL06EpOxD2kS2Q/PB4jZ5awsU4wU2aYaG/72yTncv2ERqDCFLvcgdmyshscfhJ3VuBMAHt53Gi/UXcTYBk02v/xxG665ZBaePNCCtVWFTCWbxx/A4dZ+3PuPkzHzg70ev3+mlyGGaSTiwyZDY3c6IRkyVAo5rEBBCqK5Z4AhhoHIYvijlw5hXt5ywcwcqWWJRRlGFFkNHOKryGpAUYZR8Bqp0gpyFjE5pbVSiW63ULf1oaDgfdHPI+Udq1QEs5HSGs1PHmjBvVcsTOj6qQ6hsXr3dC9vdoJYOcxYnXCxsSFJArOy05gDjOgM5uhSKTpD2B8IojjbhEyTDt6hYfT5AgiFKAwGp45mNPu9Xbe8hNOE58WGtpjnSoYERioSGXz2tfPqpah7NqIhXJCux7cusjG6om1OH3yBEOYXWBiN0q21c/GbfU1MiWZ5vgWPvXMac3Ii71PonQhmTHr8vONDk9hC84XO0JjO2d6JIJlBw1SwaTm69gBw5DMXtr5wKMZO/nTdRaiZlSl4ndw112rU8O63VqO47IJcmSmLXos/f3gc37mkhCNjsW19teh1cmU6xpKZI0ceIpUIqMlGOEzhaHu/pHlPz22SIAT9jx7PUEyV27Y9jfjJ6nL0eIdikhxuWFXGlO3TdvzsB3b4g2F81u+HTkOirX8QYSryWWEMMcTI0wfsuH5lCcf3np1twn3/aOTct15DIhiiFG35JEHOGp9KxBTbX+DT3KZtFJB2sBz9DuyOQXz/6Qb86bqL8O0nPuTMp1tfPRpDTN68pgILCjMwvyAdM60GzC+wMNWwAPDUNRfg/WYHQmHg6f87izULChh5r+IsA6cRZCL74XRFOEyhpdcLe58XaVq1qF1+bUEB0g0aTgXDphobHtp7Aj9eXY57/3ESm1eVAkDcxp3s/fCPB87iOxcXY2amEQSAc31e6DUqPHXAznsf7HsfDlGyKqOSobE73TBWGSqFHFagIAXR4uDXA45XtikF9j4fHtx7kkNcPrj3JOYXpAtqDtusRtxz+QLc+spo+eo9ly+AzSpMKNOILjkRghw9HalEt1al4pW7WFq8SPTepDqXOpWKt1t6vHLYVIEYecXnJIgF3RPphEc7G08fsOP/fWFOTNmydyiMZ/55Eivm5kJFgtFxu/PrC/Dvsw5kmXS8NjCRRBP7vREEt/EeTTbtvHopNCoy5l7kOBepSmTw2deJDjenI/0jb5/GLV8pR45Zj4GhECgKyErTMs+1xJaBddWFCFOR9fLuXcfh9AVAUcArh9pxS5QONf1OhObJp+0uvNTQxqxDJAHMLzAz38c3X+gyy/Mh2zsekhU0TBWbltNYFQBv40x/MIxOt1/0OrlrbnmeBS293pj9tjxOQzo5MlNAJKOaT54pXgbZWLT5pDasHQtSiYCaTNDz9ESnO+F5z57bVqOW/7DUaoQvMMzrq51z+vCbfaewZ+sKjpSUzWpEWW4a9p3oRigMJvOOrkA70eXBw/tG5/HmVaNVPB0uPx7b34wra4qw1BYp37ZZjRgaDsfoFd/26lE8dc2Fih2MEXLX+FQiptj+Ap2xu2NjNYKhMNr7I01L6exQKQfLQu+guWcg5ud2xyAKM/QxsmsAeCV+5uWZ8bO/HuHoebv8QWzfWA1fYBitfT7cves4576DIQqHz/WjssACdZympNMF0fa7pbZU0C5nZZlg7/NBryGw2GbFwVYn1lYVMgQxre0M8FfDbVtfxfEro5O8sk06+IdDaHMOorIwHT9+6QgzPuz7YM+Psw4vbn31qKzKu2Ro7CrgQiGHFShIQcgt25QCe5+XtzOsWEO6VqcPv33rFCe4++1bp7DEZhXM2JDqkMnJ2ml18hPdlTPSee8rz6LjDQTEJDXkPEumScurlZhp0gp+TyqBb6zEshOinYycND1UJPBhi0NQH7drhOBIJtEa7Wx0uPx4/L1mRmqAoiiY9Grc/uqnsDsGIyXGI5lCdSvn4I7XPsXaqkI88V5sdvREE03xSgmdvgAa7E58bk52Ur4vVYkMvgDnqQN2/M/XKjjzk6KAu0aCEb2GxBfn5TCdlW1WI8rzLTFk7aFz/cxaAsS+E755cs/lC/HQ3pMcPUAg0myFzooRmi+LbRljbng4HZCsoGGq2DQBijcjl4gjn5Bn1gnKx4hBLvGhVpP4ckU+CtJd6HT7kW/Ro2pGetxAXY7MFCA/o1ruYbachrU05BwMphIBNZmg5+n3V5QkPO/Zc5u2o7qVJYymJt2kbtueRnx/eUmMBNhj+5uZay+ek80Zj4WFGWjv93Ps+d4rFqLXNxQjofLyx9wqHqcvgPJ8Cz4/N5exjxkZeo6N04SzYgdjx1gkZlKFmKL9hXk3rEBrnxdGrRpqksCdrx/DmgUFHHmGe69YmPDBstA7MAjIBGWadDGJB0J637//5hLYHYPw+IPY/MVS5Fv0aHVGCGGtmsB/f7EsRlbip385AqcvgHsuX4DLFxWeFwQxX6M/oSzcf3zayVQeF2cZ8IvLKtHtGcK66kImNqMbZW6qsTEHtioSWGKzYvmc7Jg9i85UnZVl4sQ3W2tLmfGJvo/mngFmH+xy+2F3ROQr2Gucxx9Ep9svuo8rWv7Jh0IOK1CQgpBbtikFchrS0Qt8NKEs5LzKdcikZu1IvS9bpglleWmc7yjLS2PKx/kg51kogXRpoZ8DwPBwGMc6XCONCA1T+nScTV7ZHV4cPNfP0a7Sa0gQiDSio4NkMSeDzx6DoUgTl0SI1niBOVubl6/0Ld2gYbqFVxVacPOaCjT3DMCWZUJnvw83r6nAY++cht0xyGTpRtvARBNNiZYSym1EEo1UJTL4AhynLwCTToWKfAvO9AygJCfSZIgmhresKsMn9j6Oltql83JRX7cMna4hHOtw4Zn37Vi/tEj0nUR3Eg+Fgb4BP69TTQed0bbM1u8+H0sq+ZCsoGGq2PSZXv7GqqW5aSjJFa4Y0mlI3Pn1Stzx2jHmPdz59UomO0gIcomPcJjCmye7JR+AydXKk5tRLfUwm4Zce5B7MJhKBNRkgh4Xvn1OaN5Hj2WHy8/R1GSTVgNDw5iba0ZTtwehMPDY/mZmL1ARXD8G4JJxJ7rcIEHgV3sa8ePV5Xj6QDPuWFuJO3cdY8jgQqsBuzYvR693KMb2w2EK/kA4bom3AnmYDImZyQJBRBKMcsw6UGEKTd0D6GGRciQBVBcJNziPhlASyB/2n5E9D4HI+9drSeg1JAaGQnj83WZYjVp8Y0kR1i8tAkkAFxZn4LFvL4XHP4xT3R5O9vOtr3yKstw0LJppHftLm+KIfn9CayBJgCNJaXcM4tC5frxyqB2bamxw+gLwB8Oob2jFbWsrYe/14kery3G214uh4TBMOhVanT7BGKqllxvfCEnXtThGpfv0GpLRomYnQ+g1JOpWloyrlr8CfijksAIFKQi5ZZtSkGvm1+nNFck2khrEyHHIWnr5s3b+fsMKwYxmqfdFkgRWzctDSXbauGohn+n14tF/NeMbS4qYjOZH/9WMggwDb7A/PBzGK4fbYzKdpvLpOJvsHRwJgoDRU/4b6w/B6Qtg+8ZqrK7IYxwPo1YV18nYtr4Kt716NCGiVSwwD4cpnOhy40Snh3m3xVkG7Ly6BhoVwThB7K68R9rduHvXcdzy1QqcGgkWn2JllNL8frQNTDTRJFRKeGpEo+3ZD+yM9EEyiOpUJTKEApwde5vw3c/NQiAURmufFz9ZXY5AKIzP+geZJkPA6Lt77NtLcf2fPsb3V5Tgkbe4ZJXYO2F3EgeAgnS9oN7wVJE5mOpIVtAwVWxaP9J8J5oEjVcxlKbTYF9jB/736qXo9wWRYdTgzx+04AIRvWFAfmZtdIBIz415Ins0DTlaeXIb9Uk9NKaRa+a3h3hktNyDwbEQUFNBK3uiQM/TDpefyUBTkUBteS4WFmbwPne8uc3er72BEH65uxFXLyuOKX3+5JwTv37zVMw6TJIECAI42enBzpEs4/Z+H2or8vHyJ624f8Mi+APDKEg3ICtNg9M9AyhIN8BmNXLuV6js+r4rFiYk26ZAHHLX+FQipvj8hqeuuYBZO3/39mlm7ezyDGFWdprgc0QnqVw6L5eRijBoVNjyQqRBY89AIO48DIcpaFUk7/tXkQSTxUrbPn2f2zdWo8M9hOv/9DHuvKySI9MCjEgnufxYNDP573Kqga/asb6hFQ9uWASTToXiLBNmZZnwTlN3TPzxYkMbNq8qxc79Z5ixWmyz4ndvNaHB7mJ+T68hcdHsTHz1Cf5knHCYQnMvV0qErsb4w9U1UI/EUiQBptk3EBmnW189ivvXV+GnrIScrbVlKMtLE93nxJIkFMiHQg4rUJCCUKtJfKWyALZMFzpdfuSPiPeLEYRSgwRiROIgWvKAEFl3pQYxchwyu4DespjcRVG6AXetW4DbXx0Ncu9atwBF6QbhhxnBeGohSw32j3W4mEAdGNlUU+R0nC+LmH3Kf9OLh7Dz6hqGIIvWzKKdjKevvRAUKOSa9XB4h3i72/J18BYKzOduXo5Dbf1o7fMxwRsQOVGve7aBUyrM54A9OCIlQeuhRUtnRNvARBNNfNIDLY4B/P6d07z3O1aimm8N2La+asoHsOz31NTlwdF2N5Pl3uMZgkGjQrZJh6ZuD15qaIPTF8Bta+dzCGB/MIxPWp3M2IplbEevi3wZbM+8b8cDGxbhZJeHozcsVIKZde2FyDHz61yfrxhrYw5g6mSHWXRqXhLUrBN35WdlmXD5Yht+MNJcMdH7l5tZa++TvkfTkENmypWVkLsWj4WMlnMwSFcW1NctGyFjIv5evPdyvh0iRR+E0rJOQsRw9DXsd2SzGtHcMxDTpM7pC3BKn0kC8PqD8PhDgmR/l9uPMDWq9083nLukNAdNI2u7XqvCra8eZRrY0Yf+JEngrMOLpi4Pb9l1j8ePvY1d03ZMJwoT3WRyMsDnA7/f7OD0NaDXzsFgCHkWPe8ziSWplOSkIRymGHmgePOQXqPa+ry8VW0EAeYQniSB+zcsQqvDi2UlWchO0+KvB9vhD4Zh1PFXuuanT+2khGSBz36vusAGvZbkSNPwVQQ7fQF4/UE8dGVEf9qoVeHuXcewqjwfn37mYT7v7nULBJNx6EpPILapnNMXgGswiPkzLCjJScP7Z3pj9kG7YxAzMvT4O0vyJM+igy1TeP8/3/a3iYRCDitQkKJQq0ksmmlN6FRUziLa4fLzZrXOzTcLBlxSgxg5DhldZhTtBGhFiPHGLjd+9zY3yP3d26cwL4+fVJXzvuRkWUmVB+lwCTQWSpHTcdqJ7nL7eU/5G+x9zPPxaWY5fQHkmHUch1VIaiK6g7dQYN7S68Wtr3yK768oiRu426zGGLmJrbVz8cf/a8F1y0ugU5MozeVKD0Tbc7KIJikkSnTwMjvbhN0iUh9jIar5JBK2v3ESGhU55Z02+j0BwI31o0HU0wfs+M7Fxfjt26ewtqoQV9YUYVFRBh595xSn0YZeQyI0YkIvf9yGH146FzvebOJkbIdBoTzPgtnZ3PESkrU40elhDo9ovWEhW373dG9SpEGSjUTlXKZqduNUyQ7zBoLIt+g5B7b5Fj18gaDodXLJRbmZtXIkqYCxyS7wHbLGW8fkrsVCZHT1zPEho8NhirdZU7z3MlW0sscCqftctKaqWJ8I9jXlUc3k6PfNblLH1gVmZ1lmmXV46kATAP7D6TyLHipi1FeJbjhn1mvwo5cOMQfdzKF/ThraXX6OjnJ02fV1y0uwPcXGdCpistd4qXtgsrTLwxR4185QWHidj5ekIuVdsnXCXz/cHtOMdLEtHZtqbDGkMQUKHS4/Eyf8Yf8ZjkwLHX9VFqSLvpPpAvqdz928HC0OL/QaFTKNGhi1anzY4mBsJM+iw01fmovtbzRxYs4ssw4/eukQbl5TAQBosLvQ3j/EGQ+tiuBNxun2+EFRkQSf31y1mDemPef0IdusRUlOmuA+SGtRxztApjEd9repCoUcVqDgPICcRVSOjp/UIEaOQ6ZTqXg3H71auLS2w8Uf5AqRqnLel5wsK6nyIAXpBv7TcUv84HIqkS9CzkGI5bcmkm05K8sUQ9YKdfAW+k4d62digTtt29vfOMmUXtUUZ2Km1YBbugdwpN0NICIHcGVNEdPQJvpdJyMIkUuiRNvB50qy4fYPc6Q+kpERGS2RACClnLZZWSbcd0UVfv63iF05fQEYNSpcdYENmUYtWp2D+M2bTbjmc7Px6WdHmTG4be187Nx/BkBkzfnjgbPYWluG0tw0WPQamHQqDAZDvNUX8Zo3sm1RyJaTJQ0CJG/NiGerqZL9MRWyw0IUgT9/eBbfuaQEg4FhGLRqPHOgGVsvnSd6nVxyUS6ZKUeSCph42QW5a7FRq+b1jYxacXkPufcp971MFa1suZC6NoTDFFr7vDjc1o9b/nY0YVuPntvsygz6IODBDYvgCwyj3xfAj1fPhVmngVGnRke/D93uIc7harQdzMoyYWFRumDDub3HO3lJl3bXIG568bBg9Qm9P0zUmE41PzLZmKw1Xo6dy9kz+eRwXj/cPpIR+inHruobWvGNxYW8n5NIkgpJEsy6RjeN5rMXtk54tFzLllVl8AyFmIZobNL4c6VZyDJp8PrhdmZePP9RZJ5SoGCzGlGZQBPU6Yam7gHmUOs7Fxdz9uB7r1iIpcUZKMkxYWttGTKNWph0aui1JB5+8xTsjkHc9OIh1NddzHsQ9eCVi3j9gZw0PVMt1NI7gFyLLqZx55MHWvDlEQk/kgDuvWJhzBqdqr0gpiMUcliBgvMAchZROaWTY9EaTFS+IStNyyt3kZWmFbxGkFQVKDmS877kZFmRJAGLQY25uWZ4A8MwadUwG1SCDl6GUY07LqvEna+Pno7fcVklMkzCjQinEvki1vBt2/oqbH/jJPO7QppZ0URroh28+QLzrbVl0KgiZaPxyGh2gM52mP6xZQXnc/m6jEdjrEGIHLKAzw7uuXwBXvjIziG7LynJYkg7uYFgqjttJEmgOMuA7RurcaLTjVAYePJACzbV2PDrfaeYrPAltgz86bqLsP9UD0JhoP6jVk6Wi9MXQHGWCV+cm4u9jV347lPCc5BNVHW5/QiGKNz26lHeDPR4RPJY33Uy1wwhW6X3BCX7I3FYdGrUVuTjp385zFnD4slKTDTpKkeSChib7ILcA7dwmILHH0S/LwiDRh1TccKHQCjES9QFQ2HR6wDpzXQB+e9lqmhly0E4TOFoe3/CdkuvWSc63Rx5KDnrCZ/Ezy93N+LHX54LEAQe3DuadXfHZZV47F+j/gCfHdA9LEpz0rDEZoUvMAxbpompHhHyTzNNWuZntI7yAxsWMT0OaF9nIsZ0KvmR0w1S12e567mKBG5bO58jgbapxobdRz7Do99eioOtzogf09CKqy6wocUxEFPhBCQWTyVqL0I64aW5Zty3uxHfvaSYN3M4GApjVpYJN6+pwLY9jcx1FoMGl5RknVekMO2r93iGmPf9jSVFTOwORGzklr8dRd3KElQVpWP1/Hyc6o7Ip/31kzbmcMsfDCMYCvHGSj5/kKmGi+YE6GqhgaEQ3jxux/eWz+H4zjd9aR5sViNjE1ajFnUrS1CWG8kkjndwzIdU3t+mOhRyWIGC8wByFlE5On5StQZlyTdkmjDDOoBeb4D52QyrAbZM4YC1ssDCK/kgVHIkp+GMnGvOOrz4wbOfxFyzW8DJ+6zfj+c/tOP+DYuYzLHH95/B7GwjirP4x2SqkC/RYx3d8M1mNSIUpjinyZtqbPjl7kbs2LRI8F6zTDreDt4kCLx1ogvFrCCMT/PYpCthCPdnP7CjbmUJSrLTUJJjxIIZoxppQgH6sQ431szPZ5pxTEQ5olSyQCjQvvWVT3Hd8hIO2b2bpR8mNxBMdactHKYwNBzGtj2NWFtVCJ2aZIIQOhi/74qFKMowoijDGGkWNLK2uPxBPPqtJdBrVAypLjYHbVYjp7FLZYGF0e176poLeW2KtuWsay/EWYcX7f2DSZUGSeaaIWSrjZ1uzM42pfxBwkRCrqzERJOuciSpgLGtG3IO3OQ2eM0y6Xiz2dYsyBf9vrMO/ma6Qvs9DbnvZapoZUsFm+hN1G7Z5eljXU+EJH663UMAgB0bqzEcppCmU6Hd6cOVS2fCPxwWtQOSJDArO43X/vn80zvWVsIfDHHug+5xsLV2LsdPeujKavgCw9jzaQezhySbHJsqfuR0hNT1Wej3+XptsNHh8sPjDzL7B51M4fQF8KMvR6pPCAJYW1WIZ96P/JxvbeKz17vXLYBWTTA2aIpqKC1kL3w64VtWleG+3RFfazAQwiuHYuUm1izIH92f8s1TvhngeIEdV7HXPoIAr42EKWDzcwexe8sKzM0zc+TTgFF5hyW2TEaeR6smcazdhR0jUoDRBP5iWwbyzJEGyi/8O5IgQfvOKhL4xdcXoCTbyFlDOlwRaUFaGofWpZZy2JSq+1sqQCGHFSg4DyBnEZWj4ydVa1COw0lnYZRkpyXsEKjVJC5fVIiy3LSEGviRBH/WtNieJecaqU5hnkWPpu4BbHn+IPOzeGMi15FMNqLHmq/h2xJbBq/jKvZ8fLZ9x2WV+MnLh5nmLmynI1rz+NF3mvHD2lI8uGERk72t05Cw6LnZ2EIBelOXB/NHCL2Jep/xyAJ21m9Buh7HOzyCgTY7m4+2PQBx56VYZnGqO20tvV4cbevnZKwUZxlw85oKNPcMoLzAgsfeOYUQBSy1ZeDrC2eIri1ic/CTVqcgOSVmUyRJIMesw09fPoxNNTaONMi29VVjetfJJGzjzZtUP0iYSITC4JWV2FI7V/S6iSZdJ1oDGJBX8i63wSudsSb1PuXOq7G8FzmZypMNNtGbqN2y3+1Y1xOhpqrb3zjJkX8ozjKgbuUcPPL2ac7vSV171WoSX184A8WZRrT0eqEfOfT/alVBTIb6phobfENB5mA9J02Hxk43Njz2vqQDDqlQDvHGD1LXZ6NgnCUua5Nn0eP5qOom2mYHg6GYPiAAf+VjdDyVZ9Gjy+PHFb9/n/OZ8eyFloGhKAp1K0tgyzTCqFVzDuEzjVpc//lSTrUke+2bCnJPk4nouIptF3w2QkuPdXv8uHBWluC+QpIE5uRG9H/DYQquwYj8nD8Y5hD4Tl8AOWl6nBmRk1hXHWkc+JPV5QiEwvisfxAnO934rz99jO0bqwVjEDrGSKTKmMZ46YRPd/mcRKCQwwoUnCeQGiTII5T5tQaFmoKMJaNJqkMgpYFfi8PLmzVdnm/GbIHvbOmVfo3UbGM5YyLXkUw2EhlrW6YJ5fkWSc8XnRHsHQrhgb0nOM1doolNtjPe4fJjx77TuLKmCBX5FjR2uvFSQxucvgCHVJ6VZYrRyaJL+S+Zk8WxxfF2LoSCV4d3CCQBHO/wMP+2pbYUO/c3CwbabDkXOiCJN1Z8Gf/3XrEQS2wZTHfhqdDASw7CYQqNHW64h0JMgxSdmsSsbBPa+rywZZlwutuDBrsLn34WKdMrzUnDVxcUCBJKQsGfRkXKIqdo8JVVsqVB5CKZhG28eSMWoCjgwqBV8cpKGMZJ61YuJloDWG7Ju9wGr3LvU051EQ05JK/cTOXJBluHNF7fARr0miXlGiEINanTqEiOjW2qsaH+I24GeWGGPsYOwmEKLb1e2Pu8MI00yaP3Sfrf3zzZjROdbg5Bt3JeLm+TrrVVhbhnd+Rg3eMP4id/OSJ7D0kUyiHe+EHqeilX1kbMX2h1+iSNLzueOnzOia0vcJMJmnsGRD9veDiMv3/agTM9A4wMzOZVpXj9cDvWVhUy9v7kgRZcdYEN1y0vgS3TAJNWDZIAPm7tQ5ZJlzJ+5XiB7auz1z5288xov4seh0T3MXajz8ZON5q6PEzizvaN1VCRkWzkGy8tAwAMDIXQ2OnBXz+JxFHXLS8ZyVqmRGMQf1C4ylgIyT4cUORzIlDIYQUKzgPICRLkBEBFGUYUWQ0xDdaKMoy8vz+W7t3jSb6ZBBvOCC+Zeg3Je41WJHtDqq6znDEZiz5iMpHIWMd7PqFxZ2cEf9zaL9hRl7b1aGfc6QtgTk4afrWnkXMtm1QmSUIws9moUeHDZge8gWHMzjKhsdMzrs6FkD6t3THIkMH0ew6PZArwBc33XL4Av33rFDMW7IBEbKz4Mv5pPbPyfAsnS3sqkxDRoOU3TnV78Prh9pgMm9vWzsdDe09gbVWkUUvE4QV++vIRZBi1WF6azTvGQsGf2x+IS04ND4djZCfojLDxKqtMJpkoNm+kBCgKIshPj5KVSNcjkTclN4NUzl5LkgRWV+Shvm7ZiN1GsukTGVM564bckne5DV7l3qec6iJAPsmbqtmeQjqkteW5WFiYEXeNpeWh5uaZUZFv4dVNjQe+8RU6hKab0eo1JFaWZaO5Z4CZJ3xkw9baMpTlpaE0Jw0dLj+MIyX40Qe4L3/cFtNUKroJXb8vyDvG7f2Dgu9KDlK9GmgqQ+oeKFfWJtpfyEnTQ0UC/7b3oSBdzzu+NqsRzT0Dous/3yHbiw1tMdITtL2EwxQONDtw88tHOFIIQk3paImLupUlCIWBJ95rli1FMN0QnehCr32LZ2ZgdrYJX6rIw4kuD4fQpRNJgMi8jreP0T5At8ePBTMsqMi34JI5WYydftjigD8YxtMH7LzjR/fCaHP6BAlrIH6MPREZvYp8TgQTQg4TBFEE4LcAlgOgALwLYCtFUW0T8f0KFJzvGGuQkGizuFanDw/uPcmc/IbCwIN7T6JyRjrv98hxOCfiZM+kU/EGcSadcIaWWkXwXqNWiWcuSdV1ppHomGQa+R3JL1eKO5LJglgTOr6xjg7KwmEKzT0DcHiH8Fm/P+Z69rjnWfRQEfHLSvmccYd3KC6pzJfZfM/lC3DoXD/u/ccJTqbueDsX9HsCgK8+/G4MGcyGUKBdWZCOJTZrTEAilJlss0YOeYTWkzCFlHWk2DqXLzVEghR63qhIoDzfgiffO4NNNTaOM0uX6TXY+1BkNfA+t1Dwd7TdxU9OpY9m18TTRB0PEj7ZhG28ioBUPEiYDOg1KgSHQ5wGpr5AEHqNeOawXHJR7l4bDlPY29g1Ydk3cv0bOQ1exwI5FUmAfGmoVM325NMh3b6xWpTsnIhDJvYh9C1/+zSGCLlt7XzcWH+IU3XERzb8Zt8p1K0swZE2Fx7edxpbakt5D3CdvgByLTrs2FiNxpHmTtFN6Awa/sqwcBjYc6wzaXNOOcQbX0jZA+XK2rC/h6+vxCPfXIy/37ACPQOj2fKJrON8h2xOXwClOWl4+toLYxowNvcMoMHex/x+NLm5tbYMMzIMONMzwBCaW2vLYNSo8NiIb82WIkhFfzNZ4Et0iW6IXZKThvkFFlxcksVJJElkX07EB+A7zCvONKAtqhfG8x+1YkttGepWlkBNkijLjSTk0OsZHWO/f6Y3hvydqIzeVD1QTTYmKnP4KQDPAbhy5O/fHvnZlybo+xUoOK8hJ0iQsxh3uf2wOwY52bMAv24VIM/hbOnlP9mTolUUD4PBEIwabrd1o0YFfzAkfJFAh3YxSNVmlDMmKhK46gJbwtnJyUS8JnTxxpp9PZ0pIEa6zsoyYWFRegxJz3aco0+fL5yVBQDw+Iclk8qGkYzh7W+OdgXmI2f5nItknYLzOTPR2Uf0++ALtPkCEjrzb+fVNWiw9yEUBra/cRIaFYk1lfmC6wlNlNod3pQLHNk6l05fAM9+YMc3lhRBpyZRkm1CKBzG9V8ow927jjHOLLtMLxSG6HPzveuKPDPuXrcAt73KbexSkWcBIF8TNRlIJmGrEAvJQXmeBS29XjR1e5g9piw3DeUj9iIEueSi3Cyaic6+kSvXIKfB61ggpyIJkC8NlarZnnLXC741azyyzWi/jSZCCCIyF92DQYYIoe1d7CCVuUeK/wC3NNeMz/p9eP6jUzFVLPddsRAO7xByzTreZnY7959BU/dAUueccog3NZCM/ZRvjd783EE8fe2FzOcluo7zNai7a90C3PP3Y2iwu5h1Z3Z2ZN3pcvsZm+c7EAEAly8ArYrELV+tAAHgnNOHx/Y3M74XW4qgy+1nPvd804hNxBaEEknY40mPd/Q7FLKBwrpl8AVCTDPx6MO8n68pZ/Y7AIwMz9P/dxZfKM/FjAw9NGoCV11ggzcQAkkAhVYD/vu5T3iJ64nyKVL1QDXZmChyOIeiqKdYf/8jQRA3TtB3K1AwLSHF6bVZjTGb9z2XL2AyAfkgZzEey8KaaCas3eHldbbtDmlaRWLINOrw5IEWTgb0kwda8OR3LxS8RgV+tlVNCLOwUoM3OWMyluzksSKRJnSJXi/UfZdNutLNCktz0rDEZo3JWBAi17VqAnfvOi6oVcg310py0vD+mV64h0Ki5Cz9d/YcSOYpePSci9Yac/oCKMtL42SEJOI8tzp9qHu2gfMcbEcy2m7ZROnBc/0YDIZTqtyPT+fyd2+fZg5Tnnnfjpw0LW796ny4/EG09vmYrJYfXjoXz31kh4pEws9N60zW/ztCTvkDw8hPN+BPHzTDpFNjTWW+bE3UqQiFWBg71GoSX6ksgC3TlVBjVRqC5GKcjGO5WTSdAnY7Xk1Qpcoz0ZDT4HUskFORBIxNGioVG9IByVkvxivbjL3/0XsEXf5Og54nQj4xOeJXAlytUJpcoRs+AcB3Li7GC/8erWKpnpmB3799iiHe/vfqJXjm2gvR4vAyBxy01MX5lvF2vmCs80NobX/3dC8efzeSQGA1ahJa/6Mb1GWl6fCrfxxHg93FXMOOU/Iserx+uJ2xeVoKwWY1omdgCDMzjXjgnxHJloJ0vahUgV5DIhiiGNKTrnL72oKCpDZknMpI1BbEDolPREnh0e9Q6Jp9J7rx8L7TzJq6uiIPL9YtQ3OvF829Xjy2vxlaNYEdG6vhD4bQ4vAy/vI1n5uN3+xrQmCYwjeWFDFNsTv7BwV7xUxURm+qHqgmGxNFDjsIgvg2gOdH/v4fABxiFxAEMRPAMwDyEJGi2ElR1G8IgsgEUA9gFoCzADZSFOUkCIIA8BsAXwXgA3ANRVGfjMOzKFAw6ZDq9LY6ffjtW6c4BOFv3zqFJTar4MIqZzGWSkLLcd51apLX2RbT9pUKOdm2WWlaST8HRsjMshw8+70L0ekeQr5Fh4Ui2oxyxkRu5/hkYKwbevT1iRw8kCSBWdlpvMS3ELlet7IEdscgr74hAEEbzTXHyljwNYKIdi6SeQrOV1YmRAZLOTyJN3ZCDSpox93pCyQ1m3+8IaRzWZFvQe/AEJy+ADpcftyz+zjuuGw+ctKsKMowoNszhOc+sjNyE05fgBlHsQM8tg002CPklF5D4rrlJYwtCGqipp9fWQwKRkGSBMx6DXyBEMx6TUIkl3swwEsueoaCotfJPewV2qM141SuInQAWj1T/AB0ogNBWRVJkK8xmqoN6ZKFZFeZsdfz+QVmZo81aFTY8sJBJmsYiLxng0YFh3cI96+vwk9Zclhba8tg0qrw6L+aAUTst76hFfdvWAQ1CRi0avzitU+ZLEmjRoUrl85EcZYJBIA7Xz/GIVF+8OwnqK+7GHe8dkxy9ryC8xPxqr9uevEQ6usuTnj9Zzeoe/9ML0MM02D7jtGN8QwaElVFGTjV5cFgMIR+7xBu+tI83PzyEWZubN9YjdY+H2yZRmxjSRFsW1+F2149ypnjN798BFaRHhDnK4QOidmNNgHuOyxM57cT+mCLtpXdW1ZgQWEGujxDqMi34MqaIoTCwK/2NOL7y0ugVZFYv7QIFAX4hoKoWzkHd+86zhyu3XvFQjzwz5Oc+2XbzERl9CpVbhFMFDn8PUQ0h3cgQvQeAHBtnGuGAfyIoqhPCIIwA/iYIIg3AFwDYB9FUb8iCOJnAH4G4GYAXwFQNvLnIgCPjvxXgYJpB6nkklS5B0BeYCiVhJZDkqlkaPtKhZxsW1umCTOsA+j1BpifzbAaYMsUDjQDgRBe+7QDt7/KLce6vGoGtDwlo3LGZDJPQse6obOvT0YX8nglnh0uPzNHLi7JYvTRhALMFscAbFnGmExds16Np6+9EGGK4s3qF7oPOXIMYs6M3AC4pdcLCvydhemxoz9/drYJVqOG02yMDpKldh6eTPDpXG6tLcNdu44DADZ/sRS5Zh2y03Q42enBvsZO/PBL89DqHMTaqkLOc3e5/byafuyDLyEboDPkuz1+1NgyeQ/bKgvSJ/z9KJh8yM2EVKkIXnJx0cyFot8nd+9wCpDR/YMB0evkwigk1xAnM3osgaAcuQI5FUmAfI3R810/0d7HX2UmZ18SmnurK/LQ1u/D1tq5uOVvR5l/u3vdAmx54SDsjkEUZxnw+Hdq4PQFQQDo8fhh0seWXD+09wR+srocOWlarKsuZPbUx/Y3Mw25whR4eyMEQ6GYubq1tgwtjgFZDfkUTG+IVX8BwjaVyLoTz++n1910gxrvN/dhcISMpP2nzatKMa/Agj9ddxE+aHagJCcN20aaRRdnGXDb2kq4RhraDg6HeOdDg70PhRmGlPE/JwJCFShCjZEb7H3IrMgTbSJH/25TlwckARSk63HgdC/Kcs0AgDSdDb9/5wwztnQChFmvYhIwVpblIMukZdZDGmybmcg4VqlymyBymKIoO4CvS7ymA0DHyP97CIJoBFAIYB2AL4z82tMA3kGEHF4H4BmKoigAHxAEkUEQRMHI5yhQMK0g1emfKFJRKgktRwsxTafm1fZNi6PbJwW5Zv5sW7EsDJIk8IWyXOSk6RLu0H7kMxdDDAORZ7/91U9Rkm1CzazMmN+XMyaTeRI61g09mrCrb2iVrFnMDuCFtCmjP4Kt5yhUIt3aF8nKuvHSMgDAAxsWwTc0jJ6BIfzu7TO4sqYIl1cXSpqPcuUYkuXMsANgq1EbNwOa/m41SeLxd5tjnieeluZUAq2z/OQ1Neh2B9DhGoRRo4LTF3GcH3n7NLbWlmHHm6eYBikDQyHe5w6GKMGsNXZppVDmDr02R5drJiojMFmYiG7S5zPkVhzoVCreShi9Wpw8BeTJElj0Gl4y+oH1ixJ/WAlw++VlRgPy1k65JD1J8FckxZsicvfwqaKfOFnrgkkgU06rJnmbHolBaO7tvLoGdc82wGrUom5lCebmmZGVpsXPXj7CkFZ2xyD+fbYPrxxqZ7SD5+amcRrN1Te04qoLbDjn9CE/XRfTwPO2tfPxyFunsX5pEe8zZZoiB5f0XKUTGpy+wHmTKa5AGHxzkF5T7A4vDp7r5xxw0za1xJYped1JxO8X8xtJAvAOhfDIW03YsNSGbXsasbaqkKnk6vP4sWPfaVxZU4S5eWbBzNZUSk6YCAhVoGy/slrwHZ7t83ESpeblmfHg3hMxVRKnuwfQ0uvFC/9uxaYaG37yl8OwGrX4zsXFnEOwLavKUN/QirVVhZz4el6eOabCIrppsZLRO3EY18iNIIjbRf6Zoijq7gQ/ZxaAxQA+BJDHInw7EZGdACLE8TnWZW0jP+OQwwRB1AGoAwCbzZbI1ytQMCkQs1WpTv9EkYpS70tOoxWzXg2zQcPJ0DUbNDAbxJez4eEwjnW4RohbAyoLLIIkixwNQzkd2jsFyPFOt5/39wF5wfp4noSK2elYN/SxZnbxdWOOngf3XrEQnsEgY4e0AxMIhTE8HMbQcEjARtXwB8OCBGEoLHwoIpa1wZYlmGiwA2A6e75uZQmKMgyYlWVCrkXHe12eRcc7X/IEfl8I40kiJLL32/t8+KC5D68easfaqkLMyNDjwQ2L0NY/iDnZJrT0DmD90iKQBJBr0eEP+0/HkFK3rZ2P2149ijvWVooe4M3KMmHb+irczHKGacd52/oqZm1ml2tOZUxUN+npDjE7ldtYLitNy3ugKiZ5BMiXJciz6HD950tx5+vHGFu447JK5KVLWw8ShUal4g16lxaPDxktl6RvcXh5K5LK882YHWe9l7OHj2e2VaKx1GSuC0L70rF2F+79x0lJ9yI09xrsfcx+SWtw3vn1yphsxhcb2vCTL8/Db/Y1MaX0aXoVDBoVvIEQ1lUXwqhR4ckDLfhyZT6W2DIx74YVaO4dwNF2Fzz+IJy+gGgF1YctDjy8j5uYASi6w+d73C82B2lfZDAY5pB4tE3JWXcS9dtzzTrc9KW52P5GE2d+2jKNuOO1T7G2qhCP/us0framAh5/EAatGmdH1lCnL4BQGGhz+nDP5Qtx6ytHY/yolWXZSX2P443xtlOhChSSBG5bOx937zoe8w4vnL2AkyhVkK7Hdy4ujskkJggwP2PLsl1ckoX5Myz42O5kDsFoCTZgNFb60UuHcdOlZaLJP0pG78RhvNN6vDw/MwG4DkAWgLjkMEEQaQBeBnAjRVFughg1FIqiKIIgEmxjxVyzE8BOAKipqZF0rQIFEwkxW5Xq9Cez+7MYZmWZ8NCV1fjRS6P39dCVwvclp9HKZ/1+PPVeC76/cg6nw3jB1yoEO4wPD4fxyuH2mPLsyxcV8hLEcmQlZDXwM+t4icc8M38Q3dLLH6z/fRK1XeOtqWPd0KVeTxOMPZ4h3m7Me7auwG7WPCAJ4LtPfRRDLCwoTMexz1z4xevHYmz03isWQk0S0Gtiuy2zHav1SwoFn2lNZT6yrr0Q757ujZFjmKxgLjoApgPezatK0eocZBqVRAfTtkwTyvLSOORTWV6aqKRKNMabRIhnp+EwhcYON1O2+7u3T3OaoViNWlxZU4RZmUaYdGo88d4ZrCrPZ0gpFQlUFWXg4TebYHcMQq0i4pZWfm1BAaxGLY609cOWZUJnvw93r1uIS0YkTSYDcgl6sfVPqBO2gliI2amcw1RAnuQRIJ+Mnmk1YUaGFw9uWARvYBgmrRpmgwozreMjZWRQk7wZubpxyrCX+15MQvIX41RhMZ7ZVonGUsnQ15e7JvHtS2ytX/peEtEgFkp8iHZV/cEw7zx1+gJYYsvAk9+9kNHpf/LdFmy8wMZkDz95oAU3fWkeHN4hkARwssuDE51uPLwvshcJNfCaX2AGSRJTJlN8qmE6xv1S5kS8OTge60Q8vz0cpnCmdwB6dWStzjRqYdKpYTVp0NIzALtjEAQR8cXu2nUcm1eV4va/HI7xsddVFyIrTcObhR+mKITDVFJ9jfFMYJgIO51fYMbT114Itz+IdIMGuWYdQmHgb5+cw/aN1TjBeod1K+fA7vDGyOaZtCrs2FgNtz+I1r5Ir5b1S4sY+2LL8wHASw1t+J+vVuCsw8toTdOa0XRFhD8YhnsoJKlhuYLxw7iSwxRFPUT//4hu8FZEtIZfAPCQ0HWsazSIEMN/pijqryM/7qLlIgiCKADQPfLzdgDs3JqikZ8pUDDtIGczD4cpePxB9PuCMGjUSd806e8IU2GOMx6mwoLflWnkL3P5cqVwoxU5HcaPdbgYYhiIOEe3vvIpynLTsGimlfc7pDZxk6PvpxvJMqEbidBZJ3oNf1CbTA296Qg2wfj9FSWCWdnLSrKZMQmHKab5BdvxvO3Vo/jJl8s5jepoG1WTwObnDzJOExOsZRrROSJ/cfOaCs6hCJ9TmWPW8WYdj2cwJ+bcxuusLhTYkySBVfPyUJKdJju4SGaTPjk46/DiVLeH02CQbk5Xt7IE8wssCFPAtj2NCAxTTAd5utyxPN+Ch99swpF2N/QaEic63DGZwdEHeGo1ieWl2SjMMKC1z4u8mVbkWXSS1+VEApZEf0cuQS+lE7aSUSwPQ8P8h6kBkcNUQP78lEtGkySBi2dl48hnLnS6/ci36FE1Q1xiaSxw+IZ4G705fUPj8n1y34tJp+LNZDXFuW4smOxsq7HqHo9lTYq2ewIEbqw/xCmJ9gfDaOx0x9Xl5UvI2La+Ctvf4DZR0mtIdPT7YubptvVVKMow4liHCz9+6TDzTk50DeDKmiLUFGfgotmZuO3Vo7A7BrGlthQ79zfj+ytKIp8Z1Si1NNeM+3ZHSBY6aWEy+0somDhInRNSDrOoCaLO6aoUq1GLbywpgjcwCJIALphlRafn/7P35vFNXOf+/2dGu+Tdxgs2MhgbMMYL4FCaBtpAmtLUKUkJJLe3aZOml5v7K4E2bW/67S1NszQtWUhDkjblNvttG5KbNgtN06QkDcklm7MAYbPBRo6NN7xIlmRZ2/z+kGeYkc6MNONNss/79eIF2NLMmZkz5zznOc/zefzCGojv+3veayM6gK0GHe59pQkblpUAABgGQhT+j/98CI9es0L12CdnK6VydhSp7byDfXvDYlz7ufkS+Y6b1lXioX+eRK/bj+tXl0nmVo4Dbt17FBuWl+Dht86tX+Q2zzqdPvzipWP45mdLJedYVJiBh/55UnAU88UQZ3qmQzIw4YKADMPkALgRwL8iohG8jOO4gQS+xwB4GMAxjuN2in71AoBvAfjV6N/Pi36+hWGYpxApROekesOU6Ywao19t5KxWjnQ68aP/PRQzQdhzrEQnrI4la/ApyTdoMYA7ZXRjO50+Yrq2lnNoidpIMxmw71gnfnf1cgx6A8iyGvCHd1pxHkFvGJDX0EslbdeJJNrBKPc8oo2/2VlmifOXj+LNMOsF45TfKDAbWNx5Ra1EdqG6OBPzcm3Q6xh0uXy4pLpI4nxRKmYzmYu5eMYtqd9vW1sBq0GHh/afi7YiGW9jdUJMdfGkbpcPTze24/rVZYRICT1YlsEv/3pUKCYFRMYue44VJoMOt+2NVJDnje5HDzhw/7/USaLU5RxyJ7q1O0+DwTD++klnjBNa/P1EFzVjcdDLjX9Wow7XPvZ+zDETidajSNEx5MJyK+aR5wsxWt5PLZk9QKRPvnD4zITbGzy5NjNuefFoTKG3XVctHfdzAdrvy4DXT3RiT1ShvmRAazSrUgaQmk1Dcb9v6XUTix41dQ+hsjAj7ngULemVZdXHpGl//6IFMOlZ/OFAq+DIrS/Nwcq5OXjlWDeOd7mI2TmPXhPRLuZ/Fx51lIgzk/hCqVvXVAiOYbOBhcWgEzSUL64sSGjOoaQuaudpuXdwJBiRTmNZZtKdnry9Fx1luuffV+LFgx2C45Lv+4c6XPjVy8fw00sWY3A4gP/80iKYDCxu23sUjr5hOH2tuGldJU72uDESDOOh/S3odPpU249KttJUBzBoJRzmcLhjMKbtu0aLx2/540d45Fv1QhHMBfnpQgFAIFIQc2N9CZbbs5BjM2LrUx+h0+mTjE3PftCuWLiOXy/94rIlONrpwpLiTNz8wicSm/nJdxwxcwOtYzE1TLTm8F0AvoZImHw1x3FuFV//HICrARxmGObj0Z/9BBGn8NMMw1wHwAFg0+jvXgJwCYCTALyIRChTKNMWNYOm2shZrcg5YbtknLBa5Bv4wlF7Nq9MuPDbrDSyfENeGlm+QUtkthaH8txcGy5base/P/lBQt/JT4stErZtbQVmxdGOnCmIHYxy2nz2bGuM8fffV9dLdsCBSP84fdaDmxuqcMtekXZmQxV+v/8UgHMLu61ryxEIcVhXVUjst3JG5UtbV2lK55uI1H9xeuHCG1bhZI8bBh2Dkz1DgqHN35eJiGye6pRYPlvgof0t+OZnS3HXFbUY9geRbjbg1r1HMSvNiO9eWCEUkOR1VH/3xilcUlMkqS7Pa0fn2EyCY0LumY1lwREOczjQ0ic4huW+n+g5xuKglxv//KEw8ZjR0Xp0ERCfAa9fKGglXoAl4lzUcn/lCtisWyKf2QMAR87I2Buz0lBrV7Y3tLSzqigDN6ypiHFGVxVlKn5PK1rvi1EX0ZSNdmLfOUGF+pIBLXZRIhlApDEpXt+Zm2sj6pM++Y4DS+dkKTqH5SS9/rZ1FfZsXol9x3sQCgOPHTgNANhYX4Klc7JQmmsTZHX46yHNc0Y9G3Od0RHDFgMrOFV4x/Dtly3B1qc+EpwsYi1Z0n2lY2zykujzUStrI1ff4OYXPsFt66tRnGWZNOkX/nMsQ5bdKkg34cYvLsTOV0+goaYYehbYfXU9jne5MCfbijODw/jly8fhC4RRmmvBbeurYdAxsBp1wnsgPp5a+1HJVprqAIZEET+LokwzjnYOxWxKAZG2M0zk73da+wW98mhd4QGvH4sKM/D5BfkAIGyI8UXC791Uh+aeiHtvy4Xl8IfCWFWehx/+70FJlsaA1w+3P4S7X2nC/16/UiKxw9vM4rkhlSO1U52JDjf7AYARAD8F8F8ivWAGEcngDLkvchz31ujnSKwlfJ4D8N0xtZZCSRHUDppqnbbi86gxJosyLcQJvzCTPEFrkW8Ihzn8/Wh3jK7xl5fITxiBcIjo5AuFQ7LnURtppcWhrPY7Hn+IWFjI65e/jpmE2MEolgQgLdIkjovnD+O29UuwXeT427qmAr99owWz0oy484pa6JjI8X/1t6M41OESzsmnTikZ0/GMSrWaymreffE7PBwIyS4q+HYWZJgxL88GhgGufew9XFlvlxQqERdLG0+mOiVWfP4dL58Q+sC9/4hEbA14/ajItwk6qhlmA1gWaOpxo/eAI6ZIR6JG7lgWHKf7PEJBJKXvJ3qOsTjo5cay030e4jGbuoewuChDcJxH3587Lq/GMnsW7DnUgcGTZtYTnZI7NtQofk/rIkuugE28d7LDOUzsbx3OYdRC3jmstZ16PYvLaotRkZ+GLqcPhaMbxhMRpQxovy82k46YKWUzxZeVSFXHnha7KNEMIDGJZFCwLIN5uVbBfhJv5MXLvpKT9Drd58HnF+SjY9An6Q+LCjOwqnwW2ga8eLe1T5h75WoUHOlwSq5THInHRwzv3FSHC+bn4dFrVqBnyAeLQeoQU3LqUUdL8hIOc2jr9+DDtkH85C+H4z4ftbI2LMvIZsc1OvoRDGeNyemZaN8Sfy7bGhvocsfl1QCA2pJM/HhdJY51ueD0hbD9+cO4st6OW/ceBYAYm56XfNAyJkejZCtNdQBDIkQ/i2h5mui2c1ysdjoftPX4tSvAgYsZs/nxvNvlQ4jj0NLjxm/+eVJy35cUZuC7X6jAz14QBVOMBtaYDawQODEvz4bFRRk4f35uzHlSNVJ7OjDRmsMTY5lRKDMctYOmWqctoM2YrCrKwO2XLUk4gkeLQ6il1y04hvlr/8EzH2NhwQUoL0gnfocBi2c/bMOdo9GAFqMeTxxowY++VCl7Hi2MJbU+Ea2vtgEvfvtGC762rESIPPrtGy3Y3lCJJSVZst9LlYUl384+zwiMOhZef4jYXrnrie5P4h1v/vsk48/RNwyjjsF1F5TBnmNBx+CwYDx3On34z/89iJdGC2t9+4L5+OSMVLfryXccisb0eBqVat796Hd429pyYjsCIQ6X7HpT8g5eXFkgFI8Qp8eOpViaUj+cyOJJicBnJDy9eSU+HRgGwzCSwhlb11Tg/dZ+3PG3cxqTpbkWPHrNeQAi0RYXLy5Erzu27UrPbCx9o9vlQ5iL7zxJ9BxjddCTxr+5uTbccXm1ZNHLvzPnz89F2aw04v35yV8OY/PqMiwqzKAOjFGMOgbXf74ct7wo2uS8tAoGnfK90brI0vpO5sll6tjImTpjbSff1nSzAV5/COlmw4T2Fy3ZSwAwHAgRZSV8AeXN3VR37Km1ixLJAIrW808kgwIActOMsBh0MQ76ggzlvqkk6UV6T+zZVrxyrDtm7pXTDgYQI2dUUZCGvVsuwKcDXhj1LMx6HdoHvbBnWwEATd1DkkhJ/rpJdgh1tCQn/Lt9vMuF3ftbEno+WmRtcm0mYnZcKAzYTOS+nah9mmjfEn9OLMtWWZiBY10u3PX3Exjw+nH3FbX4xUvH8LVlJTDp2ZgiZiXZVliMrGTNNF72o5KtNNUBDIkQ/SzE8jTbGxbjtr1HJX1mT2Mbblu/BA+83iw5zoDXj1npJuLYwK+13L4ANu1+B9lWo7DxwDLAooI0vP/pIJ5udGDnxloEwhx0DIPd+0+hqceNOy6vjtQjGq1FJDc3yDnqj3e50Ds0goIMEw0emCCoUCWFkoKojTZT67QFtBmTaiN4tEzorWfJERytZz2yzuGCDBPWVhbiP0XVbhNZEKhFrRNW7aIvL81EjLRWWnSnysKSb+eOl4/FpE6L26t0PcC5arxefxD2HFtMoRnZomssi4ffakG21YirV5ZKomVvv6xaeJbrqgpRLEoj5Z3ISsa0GqMyXh+Se/ebuoeEc8k5JZ9ujNUF27GhBtufPxzznguSF4Xp4+KsTaQfTmXxpHCYEzQhGQDPfdwhpH/zEZoNNcWS7zj6hvF2Sx/W1xYLciKk1GSl8XrF3FxVCw5x/7Aa9YI+X3TxI/H3E+1/E+GgZ1kGy+xZxGg9/n2Ruz9hTjkif6YR5DjoGE6IXrcZ9fD6AwiGlXcWxxKdruWdTDfrcPOlVTFO7HSLcoSs2nRpnsme4/ixQu35cm0moqzEo9esUDxf61myLTZddbsTyQASy9Ec7hhMKIMCAOw5NlQUpEkc9BUFabDnKDt4CjJMREkv3oaMfk9aet2ycy9JOxiISKrddUUtTnQPgWWA+XlpOBZVzPPGLy5AUaYZP/rfQ7LRgCQ7JFVS4mcaYrmRRJ+PFlkbOWmJPY1t2Li8eExOz0T7VvTnxLJsvKQBADT3DEnWOUWZZmysL0FxpgVtA8N48PVmNNQUC9H0/Lgbb65KZH2mZCtNdQBDPPjri34W/KYUX9TvVK8b9lwbuga9+PG6SgSCQXx9RSnu/UdTwjboy0e6MOQLCGO0eE1aPTsTh8840ehwotHxEYoyzfjashKsXpiPzavn4xcvHRMkJJTmTLm12pEzQ3j4rYPYtrYCFQVpWLOwIGmewXSBOocplBREbbSZlrRLrcak2ggetYtPk4ElXrvJIH8tWhcEatCyQFW76CvIMBEX3QWZ8s7hqY4YSdRhzrfzugvKBEcXqb1y17PwhlXEwl7z8qTPWK7o2n/vPyXsrPOLUXu2Fb3uEczLtUocmNXFWTFppErGVKJGZSJ9SO7dP9zhwvf2fCxJxycZ49HpYn2eEcXoo/Fy1k51P4yHeJH27AftuHplqcThevtl1bj/tSbJd/jIm3jV7uWemcUQcZYluuCI7h+luRbcsKYC948WFpGL7lazqJkIB709x4ZFhRmy74vc/aHVq6XoELlH7YNDwjyWZzNCzygn6eWnk+/vrLSJSYd1j4SgQ5QTeyQAz4hyhKzadGmesThPtWTVaB3LtMpRyEkatPV7pqVzOJEMIEAadZlIBsVYKMmyoiTbIrEhS7ItKMmyEj+vNPd6/UF4RkK465XjMZqcx7uGBEfL0jlZMf1s56tN2Ly6TIgGjBdVzZMKKfEzEXE/SXSM1jKOsCyDrywpQrbViEZHP0LhiEP5pnWVsOfYInO0Rqdnon1L7nPRAc9PN7ZLgpkGvH6Y9Tr8enRjBYCglZuoDZmI7Ax/n5RspakMYFCCHwtPdLlk5WnERf1cvgAWFGagqcuFRw84YNQz+O2/LoPZoJPMg6T5kZ//7rqilvg8jQZWMh7zzmOzgcV1F5QJzzDesyOt1cSZmvfta8bm1WUoy9P2PFIlo3YqoM5hCiUF0ZLeotZpq8WYnIwIHotRR4zgsCgsIFmWwZqFBSjLS5uwHV8tC0YHYZfXFwjD0Ude9M3JtmF2lkey6E636DAnW/65T2XEiJr+wLeTN/rk2it3PW39id3/aONvVpoZrX1u3LfPLeysH+tyIRQG7n+9GVedZ0fuaME/sTGxuCgdf71hFVFGgEQiRmUifSiewSROx19YkB7zDpPSxSZj0ZjskUvi9g14/ULqL58ql5tmwObV84lpeTq2WNDPJSH3zLY+9RFuWlcpFBBKRGNY3D8cfcO4/7Vm7LpqKYYDoUl3+qpBKaJfLqqJVL16JiO3Aaq0MQpE+i9pzpyodVCuzYQfvnFQEnm/91BH3AhZLenSgHbnqVZ7ZSxjmVHPSByMRn38h6AkaTAdIc3ROhZ4t7WPWMzzO6vKEsqgACJjKKmw3EtxHExtA17c/coJSdT33a+cQNXsTMFhInYykOznAa8fuTYjeodG8IuXjsVsQPJjHt8mHcsQ+xmfKCCWqKgpzkBFQbrs+J8KKfEzEb6fkBz929ZWQEcY2rXK2uj1LC4oz0NJtgU9Qz5sWFYs6S9a7QOlvhVdHC36c3dcXo379kk33Qe8fmSYDbjugjJUzU7H8a4hIUMPOLdxDCSeWZKo7Aww9baSGvj72zs0Img5i/vRgNePeXk2bFtbAY8/BI4DfvbCEQx4/bjxogo4fSFsWF4CjgN+/uIRPHrNCuG65ebHbKsBvkAYHYNeol0xEgwTx+PtDYvxwGvnIowTmTMrC9Px8LfqMeAN4FintB/wY6GWNUSqZNROFdPTsqBQpjlqjQMtA6E920qUouD1zkhMRnSgURfRShYvsAozzTCycRbIEzzha1kwmvTkKGijQkR3IMShqedc5FhNiXJF9qmMGFET0cW3k2+fXHvlrsdq1BPvP8lwjO4L8/Js2LN5Jd5sPguDnoHFoIPHH8L6umLMy7OhJMuK02fdCRcM0bojnUgfEi+cm7qHcLjDRTSYbnz6Y7y8bVXcBeFkLRqTPXKJtEjjox1uW78EzV1DeOVoF3ZuqsPx0c2DPY1t2Lx6Ph547SSWzsmCPduKtgFvzHNXkiNRMz7K6WUPB0JYWZY3UbdmTMjNPeKIfr5gzpYLy1GYYUbbgFeQnrjj8mrqwBjFO7q4E8NxES1bJVr7PHjibYckDfmJtx1YVJiOeRMwH2qNkNWSLg1od55qtVe0jmVaHZPxJA2mI/wcPTfXFreYJ5/pwfcdJX18pTmW5OQV1ypw9A1L0qf5nx/vis1YuriygJih1OseEdLmeceuSc+iIj8Nv4rSuD/e6SL2M/El8RIV8fpQsqfEz1TE9pc4Y63LFYk0X2rPEiSreLTK2gATsw6S61sAYt7dB76+VNDRthr1yLCQi3Se6nXjwddP4ndXL4fFoJPIvEVvosTLLEm0cG+qIbateFkS8YYRwwCryvOw3J4d01/uuLwad/39hCRzAZA6WuXmxz2bPwuzgcXjBxy4fnVZjIb+A/uaccOaBbj/tSZhPK4pycJD/2yWnE9pziTVSyFpZrMMJrx2y0yEOocplBRErXGgZSBsG/AK6cr8Qu3+15qxzJ4t+x0tmoFqHWlZVgNMehYL8tOF6FmWBbJsBtnvaEFtu7QsGHU6hrjo08sUGNKyuJzKiBE1EV38ZsT9rzUrpkrKXY/NpEs4JZn0bL3+EO5+pUnQx+Kjg3LTjIIWbSIFQ8ayI51oH+INfAD43p6PYz7Pp+N3uXySysJWow7+UKTCerTjcqIXjckeuWTPtuIXl1fjv/5yWFikzcuzwazX4en32/DVumKsrSzEjpePoaGmGDoW+MmXF+PB15sx4PXjo08H0efx4/7XmuHoG4557izLwOsPSbT1gMQiX3iS3cFOItG5J9dmwgOvn0S21YivLSvBhuUlYBlgmT2LOjBG0TEMUbP2no11it+zGfVErfqJjDzVEiFrz7bihjUVqjakAcBmImcT2UzaNI7jOQy0jmVaNZUnQxYrWUmkmCfvEPnashLoWOCC+XnIzzARxw25MXRWmllx3pbflNbh2sfej2nfS1tXYXFRukRr/Ym3HRgOhPBMY+wG5J0bqrFx+Rz4gmFBlx0Afn5pFX4ukhHjNYf5tqiZR1MpInKmQNo4vufVJsU6Fsno2BL3rehoVnE7t/zxI+y+uh7/8YcP4QuEcfHiPDTUlMQ4GB/a3wIAaD3rhs0YKeKpZ2M3Ub5/0YK4mSWJFu5NNaL7AUnG4fK6YrQNeDEr3Yg9m1cKRb5ZBoLDnSf6fsjNV4FQSJj/Htrfgo31JZibE9nQeGh/Cwa8fvS7fbht/RK8d3oAoTCw6x9NWLekCJ+cGUpo3CLVS7nxiwuw89UmyRxfUZCmaQ2R7JmMUw11DlMoKYha40DLQCgXKaH0HbWagVocaXOyI9EdQ8PnoqVsJmVpBf5ciTp7tbRLy4LRotcJhg9vGNmMOpj15PuldULTslAfD9REdPGbEQ01xWBZ4M4ratHW58GqijxUF0sdRKQU9Q/a+hNKSZZ7trwEg7i4gtnA4uLKfMWCISd73ADOFYIbi+Gutg8pSUzwhh5fWfh415CwiCU5Lid60ZjskUttA170DfmEgkChcOR9G/aH8HZrP/o8fnx3TQVuvrQKI4EwOp3D+PmLkfQ8/p4PeP247oIyPPj6SWKUvJyDIRDihMrNSiS7g51Eog4x8bXxC5udm+pmhAMsUZw+f0yxzq1rKuDy+RW/N9mRp1ojZB395A3ppXOyFeUhhgMhWA26GAdDvIhqrZstWscyrZrKkyGLlWzw9lpT95CszSMu5slH0G5bW4Ftez6WLXhkz7bGSNjs3FQHHQvFeVtu7PWHwrLt4zjEbAaGObJskdmgxwOj8waP2cAi22bElgvLkZ9uQnG2BcVZEZ3jqtmZM6YvTHfU1rFIZscWKZpVjC8QlkTxNtTOwT2vHBc2PCvy03G3SIv78QMO/Mfny4Tv61gGt65fgh7XCLpdPvzxPQe+uLhAsU0FGeaEZWdSCXE/IMmS3HF5NZp7hoQAEv6a9ToGs9JMcW1Jufkx22rC4HAgEuWeY4XNqMevXj4mBEVsXVOBRw84sKm+BL9/81xATa/bL1tYVOnagEiGxKP/dxr3bqoTCvB2DnpRPitN09iXioEWkwl1DlMoKYha40DLQKjlO2o1A7U40liWwaryfJzu8yRsHKt19mopcKNFBywMDulmA856zi3u080GAOTq81oKC2ldqI8HapwScpsRVbMzBK1Be7aVGDE/L8+WcEqyXJ/729ZYCYZtayvQPTQSszPPYzaw8AXDuGTXmzGprmISNdzVOh34zy+8YRWOdbnQ1D0kOCnFht54RJqMR/GGZI5c6nb54BoJwdMzJBi0RZlmXL+6TOjD//7kBzAbWPzXJZWYnWkRtNrEsh6M6JZER8nLaetuf/4wdl21NGYTJJpkd7CTkBuzoh3iqXhtk02m2Ugc4+JFDk925KnWMdDR7yHOAfG0g406HTGietdVSxXbqUU6K5pomQ8ltGoqaz1fqhLtYJKzecRjhqPPg48+HcQTbzskBY8W3rAKDANB8/Ro5xB2vnoiRn7i/Thp53Lj0+k+j2z7GCbWZnjxYIcwB4g3wRiCLvj3L1qA1rNu3P1KRJN19zeWR97fJJ5HKdpQM//lp5mIfS7PNvUyM3LRrDxmg7QA3fBIUDLmF2WasWVNuVDbYcDrB8cBFoMOs9JNCIU5/Oz5TyTZWfZsK1p63bK2KS9ztOPlY3FlZ1IJ8Rqdz57YvLoMlYUZONblQrfLJ4wnQGQ8u+nZQ7jugjI8/FYLHvj6Utm6KeEwB5YB7ri8OkZKT8dCWFNuWVOOZz9ox08uqcSJ7iGJPfx0Yztu/WoVfvbCEeFZzs2NBPPwtofcc5PTbOfrwfD9pWZOrOxKIqRioMVkQp3DFEoKotZxq2Ug1PIdtZqBWheRao1jtc4xuUJxSotULTpgmRYj/vDuUXzz/DIM+4OwGPV44kAL7ryijnzdGgoLTWWUgRqnhJwT6aNPB7FrX2QRtfvqetnnmKjOpdz9ONLpQlVRRkwa6Kb6EpgN5IIhW9dU4MygV9KOse5Iq+3bLMtgfn4a5uXZsLgoA+fPz40x9LT2Ad4h3OcZwZlBX9xKz6kMH13y7fPnCe9Yp9OHRw604heXLcE9G2vh9gXR6x7Bb/55ChuWS6MiAGmhFP7/4ih5XltXPD7yhvS+4z3oGPTFvafJ7BggbSDoWGB7w+KYQn7bnz8sKX4CJPe1JQMjwSCuX12OW/aeSzO/uaEK/mBwqpsmQesYqFU72B8KESOq4zldtUhnAdqlg7RqKqdy8Rwtm4piey1eoS5+zOh2+YiSPce6XPjhMwfhC4SxdW25IA0lzg56KcF5mzQ+kezkbWsr0Nrnxur5s2I2A29aV4mq2bGZT239HrT2unHXFbXwjkTmmT++50BDTbHQFr2OkWxEJ/uzp6gj0flvOBgirgN8QeVMifHY4I9HItGs4gJ0VpN0zO90+vCXDz/FQ99Yjg/bBoSNvivr7bhndJPkVxuqMRIIoyDDhMqCjLjrLsHxXpg+rTaeo8eeAa8f82elCVG8W9aUE+1+vuj3lj9+hJe2roqpVyGeb7KtRmxeXYYFBemoLMzAvDwb3m3ti3HanugeirGHB7x+ZI5+f1FhBo53uXDX309gwOvHPRvrYDIwgpM5+rnJjatiyZGxRPrSYARlqHOYQklBtES8qJUW0DJ4qi1Eo3URqdbIUescMxvVF4rTEp05N9eGb18wP+H71XpWfWGhqUyfYVkGX6jIx6w0U0w0dXQV49Y+N9HgfeLtiPZedDoaj/g5JtJf5e5HU/cQrEZdzALz6cZ2Yfc8umDInsY2YfHGt0Oc6jqZO9JKCwstfUBsIPKRBmOJPE52xNElV51nx91X1AIM0OUcBscBPxh1MPC8eLADt19WjZ8+dy6q4uZLq/DQG+ecDqQo+VybiVhYIxRGSt9TpcrWQ74A0SGeDGmwqUSIY/Dsh22484payWbitosWKn5vsrNHtEblaJW/0Op01SKdBWjPxCjJtOC7F1bgZ8+fs9tuXb8EJZkWxXYmo8ZoImh1aovtNXGBJXuOBW39w8RCXUrzOv+z8KgWv5ixztssyxC1hQe8fuy+ul4SpXze3Bz4AiF86ddvxkTi9bpHUJBpwY/+92CM/cP/OxDmUubZUyaO9oFh4jqgLM+GJcVZxO9M1gaTXDRrVVEmCjNNyLQYJAXoHj/Qglu+WoWbXzi34bmx3o6yWVZkWwzYd6IHDTXFgs1gNrD4wBFxGj/8Vgse+sbyhMbG6bjxTFqj93lG4OgbFj5DGhP5AAa5NbA4c7bT6ROCc17auipGf53fANjT2EbcxGvpdWPXvpPYurZcsrb6wTMfY/PqspjnVizSRb64sgB/vWEV2vo9sBr1CHMcfvznQ0I/GOu6ajr2ifGCOocplBREbcRL61ny4vCvCjIJgLbBU40TWssiUouRo9Y5ZtKRC9zIaQED2qIz1UpRmI0ssbCQktN6KtNn5KKpL64skPycj+jJthqFPr2oIB2/eOmYpLptvKISifTXubm2mFQpXjP2c/PziKlMy+xZ+OsNq3C004nmHjfuebVJojUrbofYYJMrAjfZaOkDYocEH2kgZrKizycL/rllWvR4u6Ufx7qG8OcP29Hp9OF3Vy+PGQ+uOs+O3DSDsPApyjRhYNiP9XXFilHySjrRvkAYjgmO7JkolCpbD/tDRIc41XdTR4ZJj7WVhfjPKAdSuknZlNdaCE0rWiSWAO3yF/ZsK7ZcWIHtIqfrbevjy0No3TjVmolxrNuFB1+X2m0Pvt6MhQVpqJ2TPe7nm2q0OrWjnwuvJ8zruZOeEWlcvePyatz19xOSz8k9b7XBEOLN7eFAbKFRAGh09Es2H8SRy+L7sXl1GXbtO4nSXAt2X10PPcsgEA7jRKdLKMxZmGHGg681C99zTKE9QZlaijItxHVAYaayvJxS1t14RRSTolktBp1Qn+GBry+NGeMtegY7N9ZiaCRSYLx/NFOtMMOMggxzTNbRk+84sGF5CXyBMD5sG5jUuS3ZIK15oh230Rk10WsWMeEwh2OdLsX5RvyMO52RIJnbL6uGdySIu6+oRctZD4LhsBDlGy0lwh8vzMX+bN/xHsEZza/reR9FOMzh0WtW0EjfSYA6hymUFERtxIujX71MghbURihpiU7WGqGrxjmWYzMSC8Xl2Iyy7dKiB6xWikKL03oq02fkHUYrJT/nI3rExeC2rCmPqab74sEO/OLyavxXlAZWvM2EaMN3gcg45SMZB7x+gCDbIS6KdarXjVAY+JcVdpTnp2GHqGqyuB2JFIGbTLT0gWiHxFRFn08mLMuAYRCTHucQVcwWjwfHO4ewa99J3PjFBdi25yM88PWlWF9bjF63D7PSzNCxEPSy+fvNP4v86z6D/c29CIUhiYrxjIRw7WONKZU6DihXtq4uySS+V1TfTR3DwSAKM8ySfliYYcZIHFkJrYXQtKJFYgnQXnittc+DB6Kcrg+83oy6OVmoKEiX/Z72CGdtTuVOJ9lu63L6UDtn/M831Wh1asulFPNRtKRnRJrjvP6gxIZ49oN2xXEo0WCIcJjD3z7pwg+eibRv29py4vOJdojIRS7zThJH3zA2P9mIv96wCnpdpGBxr3sEHAfs3n8KhzpcwrE/+nQQw4FwyswPlPGjqiiDmDlaVZQp+x2lDcLjXUOqxmqlzM14OuBb/vgRXt62CmV5ESmYkWAYN7/wiaSY2Z7GNjzyrRXodPow5AsQbXU++lUuYGSi5rZkh+S43X11PQw6BoEQh+3PH1aMvD3d50Fzz5DiWjY6ACYQ4vDT5w7jmyvnYjgQwuxMM9oGvHhofwsGvH7cflk17n+tSXIes4GNkUMUj5mkdT2N9J08qHOYQklB1DoitWr5qUVr9KyaAV/rgkNNRDMj8yu5nwOAjiXrAevkg3pVO7pNBpbopDIpRA4DUzepyj2rTmfsz6P754sHO/DLy6vx/0SO4Cvr7fjTu6exZ/NKDAdCCUX3kKLMM8w6mPW6mB31g20DknQ9lgEqC9PBsgxaet04csYpREAWZZrxtWUl0LHA2kX5QjEx3nDuHRpJqlTgeH0g2uAXjzGkCITp6twjbcCYDTrkpJkkhSP5VE6zgcXcPBt8gXMabivm5sb0ux0bavCVJUXQ61mwLAMOHLEPtg96AUx9f1GLnAMrx2bCMnsOymelYZk9W6KzSZ0a6mDA4g/vno7RqP/RlyoVvzcehdDUMBYZBC1zVetZciG71rMeRecwoF5uC9DuVC7KtBDfEaWIv7Gcb6rR6tSOdvTyG21L7VmKc35033n/dJ+k3w94/bAadHjy2ysQ4jhNG+XhMIdPzgwKjmEgIj0VPWf88vIa/HqfNGpZRyhQJ07zBmJ1kktzLdhyYQWaetzC5/novwGvP2XmB8r4odezuKy2GBX5aehy+lA4mpmhV1gHyL2LVqNOCGAA4o/ViWRuxtMB73L5sLIsD2Wz0nD6rBs/XlcpFBrb09iGq86zg2Uibf7Te20xevLbGxbjgdcix33xYAexpsGQLyApeDtTUAoECYc5PPKtFYJMg1xh8KcbY+397Q2LJWtZ/hkDwCW7IjI5+Rlm/Oh/DyLbasTXlpUIWQ+5aVIpEbOBxY1fXIDcNKPQJ6OjmoHUyI6ZrlDnMIWSgqgtTJafTtbyy09X1vJTq+2rJXpWLVoWHGojmjudPvz2jRZ8bVmJUP38t2+0YEFhumxl1E6nj6gDFq2NJ0ato1u8Y87DccDgsD/ms8mA3LMqypT+nBTRs23tAhRlmYhapcOBUEwRBRJyToq7N9YSNSobaool0csAsHROFuaNGrpio4lPdb3j8mpUFWXGFG77zqoyVc9WDeNdWIRk8D/w9aWyEQipJnmgBlLWAADYTLpIxew0kyQqYnvDYpwROXR7hiIRMtH97qZnDyHbasQF5XlgWUZWJ5XXsBYfL5GigVMtRaHkwGJZBnPz0jRVlaacw2bSEWUlbHGipLRq8mplsmUQIhs4sfOM2aC8aToWuS0t2ThaIv7Gcr6pZixObWLxN5XjB6nfP3KgNaYQZqIEg2H89ZNOsAwj6TO87fe7q5djyBdEZWEGXD4/Nq+eL3Fa5ViNuPGLC7Dz1aaYiGges0Gqk+zoG8YDrzfjv6+ux7un+yV2ECDNFkyWuYAy8ej1LGrnZCtmHIghvYs7NtTAHwqrGqvVbPwlslZrOevBrXuPCmuthppiPPG2AxX5aagoSMMNaxbg/teaBN3u2pIs/PafzUL065X1dux5r034fXl+Ou555Th8wWK4fKEZGVmvtMF6ols5Srwgw4wBr1/QeeeDZFzDAbSe9cCeIx1TxHN9x6BXWB/x8j83N1ThwdeacWlNscSmNulY/OldB+68oha+0Y3uu185LpERTIXsmOkKdQ5TKClIa5+6wmTMaIRpdMSpUiSsFm1fLdGzatGy4FCruchPkNGaXkoTldbvqHF0G3U6PHKgFQ01xYLT+pEDrbhzQ63sOaYSuWdVVZQZo0tWUZCGvVsuwPHuITR1D+Guv5/ApvqSMWmVyj339gEvMRph9/5Tks+Ko+vljKalc7KEFOrowm0TkQqc6HupZqFIMvj59L+XNGgwyp0vVRevHAfc+0oTrlxhx/2vN6Ohphgb60uwqDADj7x1Cp8pmwXg3POV63eNjn6UZFsE3bbo4p0kR0GiRQMTHaMnilR1YKUSfOSjeB63GnRxNwfVFoodK5OxSSzGZtIT7Q5bnMyo8ZDbit6sVYJlGcxKN+LuK2rh8Uf0NdMtuoTekVRMqZ3qMWE8+304zOFASx9uevYQfvP1ZTH9e8DrRyjE4YfPHMRfb1iFTIsRf/nwU+zcVIfjo1GRjxxoxda1FdhyYTn8oTAWF2ag2+UTpC/MBrJOsqNvGE5fIEbuSDw/JNNcQEk+eB343VfXo9HRj1AY2PnqCdy+vlqVnapm4y/eWi0c5mA2kOuo6FgGh9td6Hf78MOLF6G5ZwihMHDfP5rwb6vn4wsLPSibFZF2c/QNo6nHja1rKnDPK8dxZb2dRtYTSMSxPzfXhh0banDTs4cEB+/WNRV46v02rK8rjpGyEc/17pEQXjzYIfFLPPthG755fhl6XT7Ul+bgUHtEDueRA624st6OX750DBuWl+DFgx0xa7IdG2pkx+pUXUukCtQ5TKGkIDajnjihyslEaImE1ZIaqiV6VgtqU0HVai7as63ECB+lAjdanNZqz2Mz6WLSc7atrYDNlJz6WnLpoe87+rG4KB1/vWEVet3nFo2n+zxCOiVATtdUs7iTc74P+UL484ftQgX0jsFh7CGkr21bWyGkXomfL2807dxUB4Y5FyUqLtw2UVIMibyXaheKcga/OP1PCdL5xDIKWto0FYTDHI6ccQlj5bw8K2xGPX41ugAxfvgpftZQhYPtgwiFgR0vH8NV59klWpgsA7AMQ+x3ofC5SC/Su9Ha55Y4CtQUDQSmXooiFR1YqYTWzcHJdtKNZZNYy6JPrwNmZ0m1mGdnmaEgxQ9Au9yW1rGs9awH//7kh6ojlVOZqRwTxrPfn+7zoNHRD18gjECYI/bvQJgTZCHWLS7Ety+Yjx0vH0NDTTF0LPDjdZX47T9PoqnHjW1rK3DL3qMAIEQ9rl2Uj0yLIabWgtnA4tN+b0z6vHh+SLa5gJJ8tA14sfnJRsn489PnDwvOwETsVDUBLXLvHwCcPuvGh22DODvkI75Lzd1DyLQY4RoJ4Q+jDl/elr77lePYcmGF8G5ZDCyW2rNxvNOFhppi2cj6mU4ijn2WZfCVJUXIthqFTYQ9jW2yDndxFvOzH7Tjm58tlTzLrWsq8MvRwuKluRb86OJF8PqDkuf04sEObF27ALv2nYsQry/Nwcq5OURbQG69MTvLjFybiTqKxwHqHKZQUpCCDLJMBElDKPJ59VGtWlJDtZxHLVpSQeU0F/0ymouOfi/uf01a4Ob+15qxdE627Dm0LETaBsjnWWbPJt7j4UCIGDnmC4SUbllSoGMZfHLGGWOEihfU0X2O32x4/NoV4KBeI9CebY0xfPnoTF4+ojTXghu/uBC797eg9x0HNq8ugz3bil73CCoK0oRidHLP993Wvpi+6AtEdJWfHD3e0jlZKM21jYvRksh7qbYy9VgLHpHOFy2jkAqLV74YBz+GFWWacf3qMqyvK0aYi2RbjIy+awwDXHWeHRUFafjhxQtQPisNvZ4RrLvvTWRbjfhZw2LcGqWDt6exDRuWnZONiHaczMuzJRypDUx++j5lainIMBE3B+XmfTGT6aTTukms1ekaDAIMONSXZmPAG0C21YBB7wiCcaZFm4lc4DWeTIfWsWyyCgNTzjFe/b7b5ROKXz34WjOu/dy8mMKQD77WLMhCLC7KwLqqQiwsSEdbvwc2kx5Wow7/75JKsAyD7+35WHBg8fbyZ8tyUVWUGVN0l4/cu+o8u+A8WVWeh6VzsmVtJ4DOBRQppD7i6BtGcZY5YbtDq1SMUEButFjp8S4Xdu9vQbbViOtXl0nepfwME+7+exN+ckmlEFHKy8PoWKBuThaeeu80fn7pEgAc7Dk26Fjgusff12zDzgQStfP1ehYXlOfBpGfx5smzMQ53R59H6CN8FvNdV9TiRPcQAGDLheUozDQjzaTHL/92rmg3ryXtC4SEDEv+58MjAdy2vlqQrbNnW2OK2vIOYKOOJa43+MzNZAs6SUWoc5hCSUHsOTZUFKRJJlSxIysaLRO6FoeRlohbtWhZYBl1OqLm4ufKc8nn6CMXuIm3iNNSXI90Hjm5i1ybiRg59ug1KxI632QjXuxHSy6QFtSkCO8Brx9mQ0RfTe25XznWjZ2vnhCMyhXzcuALhCTRmTetq8TFlQVYMjsTn44WanCNBFCRn4aq2ZkSA4N/vryD9d3WPkmbo6OFB7x+LCrMwOcX5I+boZLIe6m2MvXFlQVjKniUiIxCKixeeV1pPkKr0+nDIwda8fOvVqHf7Yej34uH3jiFLyzKx9zcSFTxbXuPoqGmGDk2o7Bp1en04an32nDvpjpJoZWb1lUq3lO148dYnfqU1KIky4qSbItk3i/JtqAka/zm1/FA6yZx61my03VhnMhak4HFoDeIk71e4b7k2Ywom6UcqqxVpkOtTBXPZBUGpow/BRnmSITb6Pz+6P+1YvPq+eDAQc+yQkQwX1Tp/Pm5mJtrI2p8LixIJ0YHB0IcHP1e/Ond0xI5Cj5yj9/UBoD5s9LQ6+4WnCB0LqDEQ6lobKJ2h5ogGNJm3+6r63Hj0x8LNTk6nT48tL8FP7mkUpCO6B0awYDXj//efwrXry7HQ/tPCtH3dSVZePLAabzedBb7m/uxeXUZhgPhMduwMwE1foCIBJKJKGXz0aeDgrwEn8V8ontI8tmiTDP+4/NluOo8O3KsRthMemRZ9Xji7VZ8bn5+zJz74D8jNTz4OkAtvW5ZB7COBXH+5TM3ky3oJBWhFgmFkoKwLIM1CwtQlpeW0G6vlqhWLQ5ltZGwQKTIx5FOJzqdPhRlWlBVlKFYdVfLAssfCsVIBihFDpuN5AI3RoV2aUGt3EVJpgXfvbACP3v+nPP91vVLUJJpGdd2jRfiCCux5AJPtHNQLsI7IPOcEj0376QwG1iiji4AtPa50dztlkSR3bOxDl9eEqvlKzZ4S3MtwobIRBRui06ztmdb476XcosAA2HH/canP8ZLW1eNKf1W7nxiGYVUWLzyTq0hX0AwXnm94SuWlwAAVi/MBwB4fEHc/1qzENWyuiJPcm2HOly4de9R/PrKOnDgsGFZcUL3VE1a/VgKPk0Vqa4VN5Xtbxvw4u5XTkg2B+9+5QSqZmcmJP0yWe3W2i+1RtZ6R0LEQq1ev3LosFaZDrXzNo/ajK+ZRLz+OdXjBq9fvOPlY4KDgmUZuEcCaB/wYfXCfKxakC+kXuenm2UjzF/etiomo2nrmgpsf/4wbr60Co0OJzoGI0W6lszOgI6VFqEzG1hkWQ349yc/EDZOUnEuSBWmuu+NV5uU+oia4yW6iU3q/7w0CyDNsrvjpWOCJEG21SiMk396z4EfXbwIIY6DUceifcCL15vOCscLcxgXGzaVCYc5tPV70O0agccfRGmODfPyYq9drR9gbq4N92ysww+e+VgyTonlJfg57an322ICYzgOCIU5dDiHsbpiFn7wzMdw9A3jcIcbP7mkEie6I5sBD+1viZEBkduAZRgIGRzR8y9vAyRb0EkqQp3DMhTPseNM+6eqvze7ZA46Pm2bgBaRoe0cX1KlnWISLYiiNipNi0NZLhJWbqAOBsN47mBHTKTxZbXFsg5iLQsstZHDJh053dQcR8RQrcGm1hl6rMuFB1+XOt8ffL0ZC/PTUGtXF1k7GURP8PGcg6Tq4nsa27BuSeGYzw3I6+i29LpxqN2J3fulkc0/eOZjzMleCY8/JDzPaIPX0TeM+19rxp7NKzEcCBHfE62LC7k064srCxTTAEmLgNvWL8GHIsNcfE/491Nr+q24iIWcjEIqLF7n5tpwx+XVuG9fU8xmEgAYdSz0OhaLizJwvNOJhppi7Glsw/fWLoDNpCNGvc9KNyV8T9Wm1U91wSe1pILutBJT3X61mSY8Y2m31rFLbV0AQHtkLcOA6OS9+wplJ69WmQ6tm5hqM75mCvH651S/d/w7MCvdiF1XLUWPawQjwTB2vHwM/iCHq1eWEmsLREtOAedskNlZZomdwzt/babIO8DLXt26fjGKMi2SbKebL62C46xHsnGSanNBqjDVfW8826SkATwR10iywXnHHinLzmrQ4YcXL0Bemgmu4QDuv2opDp9x4ljXEPYe6hDqO/DwDkFfIIymUUmDubm2aesUJM3FAPDaie6YwBa556fWD5BjM+DuK2pxvHtIMk4BkXX9irm5qChIw/q6YrAscPcVteDAoX1gGA/tj0QD79wUCZBw9A0DiMhORUcaA+fWg+EwJ7sBy3HAnz+MrefCO63Fx6FohzqHZTjT/imu/N0B1d/b8x+rwTDqB1OdwYRQYET19wDQdhKY9Hb++/mazqWVyTJYJjrN+UinU3AMA5FJ/qfPfYKK/DRZGQEtqbVykcNyi7ncNCNsRmm6qc2oQ26aUfYcWp6JWmdoh3OY6BzocA6jFvLO4amKfBD3h0QKtI2lunj0NYqr6PLI9UVeT5C0kDveNYT/fPaw0JZsqyHmc46+YQwHQlhZlkdsl9Z3VS7yiE+9knsvxYuAblfEkPvxnw/h0tpi2Xsylj4iV8RCLKOQCotXlmWwtCQTV51nR2muFXdfUYuWsx4YdAzSzQbc8bfjQrT4j9dVIme0sIbVpMd3//jhmAsQqtUyTcaIJiVSQXdaialuv9aIVa3t1jp2ne4j1wV4Kc75tEbWDgwHiPP74HBA8XtaZTrGcxOTEr9/TsV7x4+tfZ4RnBn0STY+77qiFne8dExwCvO1BebPSsOZwWFUFqYnJPUgltnif6dnGMlG68NvteInl1Ti7itq4fEHYTPq4R0JYNcbLTEbJ7Qg6Pgz1WP+eLeJLI2mm5BrJPX/Fw92CP37SVGNjy6XT4ggrSnOwPe+uAAnu4dQnp+Otj4PfnrJYrj9QckmCe8QNBtYHO5w4Xt7Pp5yx/1EITcXLyxIJwa2xHt+idiOp/s8eLulD2EOso5ccRZzt8sHq1GHMMfBnmNF3ZwsSVCNuC88+0FssfE7Lq+GjgWe+7gD9+1rknUA8xmad15Ri9NnPSjPT8OOl89pGydb0EkqQp3D4004qNm5OKlOSdpO2e+lAslosADqowM7nTLRnU4faueQz+HoJ6fWLi7KlE09VbuYs+fYMDvbjbOec7pws7MtihE+Wp6JPduKG9ZUJKzRnJdmIi428mzyi+epjHwQ94dEJBdYlsHFlQXYs3nlqMyIGVVFmXHbSbrG3129LK7+NW8gsQwDHUOObLaMLr7457ln82fJnzPoEA5zRANL67s6Fp1efhEARIwtR9+wrIPenm0dcx/hi1iUZFvQM+Qjyigk++I1HObQNRTZVHzkrRZ8+4L5CIbDGAkCf3j3NO7dVIfmHjeC4TB6RhczA14/7r6iFo6+YTz5jkNSeb66OEvx/kUb6Gqet1zF5q8sKVKU5ZlKUkF3Wompbr/WiFWt7dY6dmnV5NUaWZtrNeIXhPn9no11it/TKtOhdt7m0eo0n+7E659jee+0bKDFq5XAMJGsEH685+NXzAYddrx8AnNyrEIB2mh7eMeGGvR5RjArzRTzu21rK7DlTx/BqGfw0DeWw6SPbPzctvcIrrtgPnQsg6aeITzT2I4Br59KkkwCUz3mj3ebeAmCD9sG8ZPRoodb15ZPyDWS+r+4xgdfqPFH/3tQiCoFgKYeNywGFm5/CE3dQ1hYkI7bXzqKTLMB91+1FE5fAG39XkHe4PsXLcBjB04L81M8jfpURG4u/s2/LpMNbJF7fkoZiW0DXvR5RmDURbIXwhwkWutiRy7LQFjzzM214XjXEK597H3JMT8zL1f4vXjTi48U33JhOXzBMFgmolP87IcdgqObH18tBhZLijNx8wufCA7gK+vt+OVLEYdwaa4Fu65aKpu5SVEPdQ5TKCmIFuNAq5Gs5jtqowOLMi1ER1thpnxKiJZicWojUtVqOgPaFsSOfrJG89I52cRrKcgw4eZLq3DLi0eE67j50ioUZMovELQW+RkPWJbBRQvz8T/XfQZdLh8KM8yomZ0Jo0ykG19ETkukWvQ1fuAYxPMfd8jqX4sNpGyrET/60oKYnewbv7gA7QNe4Ty+QBiBUCjG4N26pgJbn/oIN62rjGnrWAz58dDpFVdZ73T6JA7MBfnpMOoZHO10jstmU7I7f+PBR0o809iOry0rQefgMOpLc3CofRBfWFgAp3cEpblWnOp1C47hW75ahd37TwGAkAoMAOfPz43rGI420P/76vqEnzepz9/07CFkW424oDwvKY3jVNCdVmKq2681YlUui2JWmnK7tTp5ZSOcDcoRzlrmXQCYlWHE//eFctz8wrl58ZavViE/Qz7Th78+NTJYPFpqK/Dn03I/pzvx3iut710ichUk+zZerYTdb5zCLV+tws0vHMGDr5+M2GENVXjwtWaYDSyauoewuCgDZbPSJBk8gRCH7c8fhqNvGGYDiwe+vhR/vWEV2vo9+OjTQUnBuev/5wPsvroeXn9I0CC+fnUZAGDD8hKwDGDPsc54SZKJZqrH/PFsE/8+HO9ySSJN5TRcx3qNSjIWfKHGBflpMWP3zQ1VaO5xY9e+yLhclGkWovR/9sIRXHt+KZbbs7G4KAMne9x47MBp4b3xBcI41uUiau6mMnJzh82klw1skXt+co7m3VfXY/vzh4UsnO+sKsOLBzuEuhr8uqGmJAu7/tGEn/zFLYyn8TaSWZYRpHRMelaI9uXHwh0baoTsRv4YYnv6f69fiUevWSEZR3lH8U3rKuMGYgCpl2k3lSS1c5hhmEcANADo4ThuyejPcgDsATAXwGkAmziOG2Ai2gP3AbgEgBfANRzHfTgV7aZQJhq1iz0t0aNj0bVK1EFUVZRBjO6sKsqU/Y6WYnFaUtrVOrq0pPw6+tU5uudk2zA7yyNJMUy36DAnW36BoLXIz3gQDIbxwuEzkud72/olKM+3IdNijHkG4xmpFuaguPAXn6vT6cNj/3ca2y6qiNzbkSD6vX6Y9Sx++0aL8F2zIVLZeZk9B8WbV2Lf8R6Ewud0uEhO97EsLsZDpze6ynqn04eH32rB9obF+MVLxwQHZ7JFx0wFvCN9wOsX+k1Rphkb60tQkmWBo38YRzu6cfnyOfj+RRUoyDTD0edBU49bchx+LG7pdcsaoqS+/tPnD8doN8s9b7nFQqOjHyXZlqR8bqmgO63EVLdfq+yOjgVRrkEXJ8Bcq4yFy+cnRjgPjSjLPIhJtJYCAHQM+PDy4U787urlGPQGkGU14LG3WlGaa4U9R/49kMvEyVXIxAG0O5W13s/pTrz3Sut7p2RPzM21ydq38WolNPW4MRII4d5NdQiGw2DAYPf+U2jqcQupz+fPzxWcInyfuGTXm5K2bPnjR9izeSXMBp3gCOPhx/K1iwqEjd2H9rfga8tKhI3dqtkZivY7dYSMnake88ezTfz78J1VZZL+nIjkmxpIfY9/B8JhDoc7BoW2H+pw4YpgSFjTWIx6/H7/KVy4KF947/ighs2ry1CcaYHNpMfRThd8gRB+tz9W7kC8OTNdkFtHFKSbUF2SGTO/Kz0/JduxoaZY6AfPftCOq1eWYk9jGxpqiqFjgcrCDOz6RxMOdbgAQBhP4wXBhMMcfP6wkIVRlGmWjGWZVr0QPU66zmyrSViPh8McHr1mhaoN5GTUDk9mkto5DOAxAA8AeEL0sx8D2Mdx3K8Yhvnx6P9vAvBlABWjfz4D4Lejf1Mo0w61iz0tTrfJiDjV61lcVluMivw0dDl9KByVEVBKi9ZaLG6ioxq1pPxqKcATCHFo6hkS0m5rSuQd6VrPMV6QNKW3P/8J7ryiFv/y3+/GTM6JRNmSDE+S4RRvNz36XIc6XPjpc0ewY0M1ctOMqJ+bg9Y+t0TjjJdgON3nQafTR1zQRUctjGVxoWZTQ24xSKqyvqgwAw/986QQbSHntEiViM7xIj894kjf3rAYt+09Cl8gkv5mM+rhC4QEw/bt1n5sXVOBe//RDADEhVVrn1tIIScZoqS+7ugbRnGWWbHYII/cYiEUju+kmipSQXdaialuv9bzdzp9eOJthyTS9Ym3Haibk4W5efL9RKuMhVwB2OWlygXitC7gCjLMeLu1X6hiD0Tehe2XVimezzMSJNoSnpGg4ve0bvhpvZ/A9Hb2xevXWvu9kj0BQNYmjlcrYeuaCvz2jYg+6u5vLscnHU6sXpiPVQvyhVT36L4g15Z9x3uw3J4tO5YP+fwSaa6H32rBtrUV0OsYWW1s6ggZP6Z6zB/PNon7oLi/8ZJvSkWVE0VJsqB90IsP2wZxuk8asPLbf7bEFHW8YnmJJEtywOuHWa/Db944KcgAPftBu8RW499N8ebMdEFuHWHPscGeY0P5rDQss2fD6w/CnmNTjJxWsh3FmRK8U/5ry0pgz7HAatTj1r1HhXUDcC7zJRjiFOfE030e/PT5w8Lz4seyrWsq8IuXjuHXV9bBbIgtVMjPya19buGaxGv5ROfFZJXiTFaS2jnMcdx+hmHmRv14PYAvjP77cQD/RMQ5vB7AExzHcQDeYRgmi2GYIo7jOiepuRTKpCG32FtqJy/2tKS2a404DQbDONLpHNWMtaCqKEPR2avXs6idky2rMRyNycASi8WZplhnU0vKb36akbg4nSVT+E6LZqHWIj/jgZym9LA/SJyc4y265QzPixbmx0RcVpdkKjplSeca8PrR6BjAZXXFKJuVhnl5Nomjzp5tFWQvvrOqjNjW6KiFsS4uEtnUiLcYXFdViEWF6XD0RdJXbxMZeGYDi/YB77hGjsi1MZmdG+Ewh9Y+Nzavno+/fPgpdm6qw/EuF0Jh4I/vOXDd5+bh3k11ONLpwnlzs/Gz5z8R7iEf1VJZmIEFBenQscC6+95UNETl+nqOzZTQJla0hhu/MNrT2IYNy4on6C6NnVSXHpnq9ms5v9Wol0TDA4lFrGqXsTDhqvPsMXNOfrrynKN1AWfPtuK29Uuw/Xlphko8DeD2gWGiHTUnx4o6u3yBV60bflrv50xw9sXr11r6vZI9oWQTr5ibG1Mr4aFvRJzAw4GwkClkNrA41eNGQYZZ4qAi9QUlh8zPXvgEv7i8Gv81qgErHstXV+RhXdUsLNhyAZp73AiFOXw64MUv/3YMYQ7EPkAdIePLVI/5JMbyPpAccImm5sdDSbKg0dGP3ftbYmxncYGxpu4hmPUsOA549oM2iR22p7FNkDhoqClGp9OHIV9AWAtyHGQ3Z1KdeOuIuXlpihu9YuS00He+eiKmaDXvxOXnLD5YhsdsiKy7f/r8YUVdYj7bRu55hTlOWKdGFyp84u3IZ/h1rlKxULl5MRm1w5OZpHYOy1Agcvh2ASgY/XcxgE9Fn2sf/Rl1DlOmHQUZZuJiT25C1BLpoiXiNBgM4y8fd8Qs0i6vKx63IkkDXn9MyinHAYPDfvIXNKLWmaUl5dfjDxEd3V5/iPh5LROc1iI/44GcprS4yJu47fEW3XLR7L//Vj12vnpCiIytL81Baa4FPUMj2LN5Jbz+UMwznJtrwx2XVwtFOUhRB9EGeEuvWzi/lqgFNanSakhE74uvUD08GoXBP4ttayvwxNsOAFBVTE0NqeDcaD0b2Xj53kUV2HbRQgx6/ViQn46Wsx6srysGxwG37j06GklcIXF+8VEtv3r5GB69ZoXspohDNJ7Ys61EAz2eQ4uHZRl8ZUkRsq1GNDr6hcXTTesqhfcl2R3yFPWo3XwFtEesapWxYEbnseh5jYnT9cZSOO+B16UawA+83oylc7JQXpAu+738DBPZjkpTdmJr3fDTej+nsm5AKhE93pHGWPH9lrOJ+ee7cFQP2GrUozDTBOdwIGYz7qn323DVeXah7y0qiOj4R0OybXh7odPpQ67NgHs31eGYyBF21Xl22Ew6IVru+6I+AJxL6Z6ba9Nc2JQyvRG/E0WZZqEP8g64BQXpqCzMGLNGL3+epu4hYt9rdPQLhdNIzumrzjtXYAwASnMtuHX9ErT0uIW6Dw01xYKD+Ml3Ijbrn95rw41fXJiQFFeqo2ZDIJ7tt7goHY9fu0KINC7NscKgY7Hj5WNEW4G/39GBRtsbFuNw+6CkIDM/B/cM+bDuvjexY0MNijIjPojHDzhiosR5vWF/kMN1F5TBnmNBW/8w7nm1SRKl3DPkk8gBkYqFym2CJaN2eDKTis5hAY7jOIZhVC23GYbZDGAzANjt9glpF4UyHij1VbWRK1oiXbREnH5yxik4hoFzMgIV+WmKkThqMOp0eORAq6TC+CMHWnHnBuWUVTVocWZpWTC2DXjx2zciOnL8tfz2jRZsb6jEkpKsmM9rmeC0FvlJFKV+StKUvrmhCr8fLeAV3fZ491Aumv3MwLBEA9JsYLF5dRl27TspPDu+aq74XMvsWaqiDsSLrkSjFhLpS2N14iW6GGRZBhdXFghRHEZdJAp/wOuHLxDRA9u5qW5cHcNAckQyxZv7+b7lHgnh2BknzAYdPP4QZmea0TbgFQrQ8Q6B//zSIqHSMv/sO50+9Az5ZN/Tjz4dlPTJixbmC88iFAZ2vnoCBh2bsNNcr2dxQXkeSrIt6BnyYcOyYqHvJINDnjqn1aPUT7VuvmqNWB2LjAVpXltQmK4Y3aS1cF6rTJHa1j6PonO4MNMkFBbj7+ctX61CYVb8rBotkXta7+dU1g2QI5nWUuEwh7Z+Dz5sG5Rs9vLp7CSZnkRsYr5oFv/73129TDJe844qvpCc2cAKDovobC7+2ZNqFZgNLI51DiF/1LZmGGB9XTGsBh18gUiggFIxw+Nd0naqKWw6E0imvjpW1MypJBuAL4LY6x6/tYD4PHIZdbxkgdkQWxj5okX56HGPSIIWrjrPjnv+fgLrlhRh+/OH0VBTDIuBxc8aqnDr3iOSYmQXVxagujgzaWQ/tDJe/VTJ9gNA/J2OBWalG7HrqqXwh8JCUE108TerQSfYvSwDuIYD8PhDwnMVr8GuuyCibX3Ts4ewbW1FTGRwRX4aCjLMGAmGBL3hB18/iS1ryiVOX/54+enmuMVC5TbBklE7PJlJRedwNy8XwTBMEYCe0Z93ABAnppeM/kwCx3G7AewGgPr6+gmK46JQxo5SX1W7yOCdQns2rxyNOIpo+ypNoCVZVpRkWyTRPyXZFlmdMwDoGBwmDtYdg8Pj5hwuyCCnrI6nTIJWZ5baBWNeGjlyKU+mII4920os4JdotOFERK7G66ez0o24+4paDAdCKMww4759J3CowxWTdiTWF5S7h3LR7JaoaHZfIIwwd+7fcs/OnmPDosKMhA2GaKff4wcc+OZnSxULQcTrS+PhxFOzadA24MXmJxuFzxZlmrF5dRmWzslCaa5tQgzrZIhkijf3833r2Q/aharww4EQznpGsCA/HT/+8iIYWAbtA17sunIpMq0G/OCZg8R7TjJExRHafB/Y828rJc8CiESDLdhygaJTS4zc+zLVDnlSv77j8moss2fBnpOai7fJQKmfat18tWdbccOaCk3zhtb0ZTWZTTxaC+eZDTri+Gc2KMtmlGTZMCfHi91XL8eAN4BsqwF6XeTnE4WW+zmVdQPkmMy1lJJDjB9njne5sHt/bBSZXOZQPBuaNH7++5Mf4uVtq1CSXYxulw/1c7Px8xc+ERwnfISdLxBGU/cQAMScs7o4C6d6PTEZS0+934Z/XWEXnGh80MOj16wAID/HWw06XPv0+5J2qilsOhOYLut+tXMqqQ9v+eNHeGnrKqwsyxu3dokzG0hRwdsbFmP3/lPwB7mYwsg7N9VhSXEWAOClravQ1D0UiTp1+dDU40bvOw5srC8RJAbu+0cT1tcVoyTLgoUF6aguyRI2e4CIrQkgJR3E49VP5Wy/4s0rkWYyEH8nDqbh+1T16HN59JoV6Hb5BEexo29YGLeeeNsBo54hSpzx0ca+QBgefwjPftAuFBXscA5jwOPHHS8dx6b6EsnY9uwH7bIF9t5t7YsZAxNZ9ySjdngyk4rO4RcAfAvAr0b/fl708y0MwzyFSCE6J9Ubpkxn1KaY8FqpiTqgHP1e3P3KCUmE7t2vnMDiokzZaJUcm5E4WOfYyBq6WrDn2FCeL5VJKM8fX5mEyXJmFWSYJEUXzAYWN19ahYJMsnO4bcCL+1+Tps/e/1ozltmzZds1lRGErWc9+PcnP5Q4IjfWl+C6C+bjWJcLd/39BAa8/oTbIxfN3jnolXzObGAljnC5Zyc2GLpdPliNOvhDYZzu80giMElpeb5ARE7AaogUSJyTYyWm58XrS4k4j+NFiqjZFY9uD19Y76nNn5kwp2EqpHSJ+9ZD+1tw7fmlWDonC8OBEBx9XkH3bHvDYnS6fKgszJC959GGKAMG39vzcUwhjw4neTOtucctyIFoRSnSjP/9REbzkvr1T/5yGJtXl2FRYUZSSYqkClo3Xx395Hlj6ZzsCYk81Rqlo7aWAk+21UCcF7KtBsXzsSyDlfNm4XSfB0a9ugWjFnkPreSnk+e9eBrO04F49gs/znxnVRnx3dh3vEeSrSEed5RsaLnxs8vlw8qyvMjcfdaNH128CE09QzGRwIc7XPjeno+J51xemhUjIfGvnylFbpoRO//xCfGdkXunXCOBmHY6+oaRazMkVNiUkjokOqfGk3gY73WMOLOBjwq+64panBh19O55LxJhv+u1ZkU5C75Nz3/cgec+7sB1F5RhXp4VaSY9fvm3Y4JT8svVRdDpGHS6fKgajQKZ6iypZEKp+OWC/HTi78TBNNF9Slz87ZFvrcCxLheauoeETEk+Q6O6OFOoa8KPhcC59Ri/1tiyphwPvHZSiC5+urEdP2tYjFtFRaD5ddWiwnRJ0Eq8YqFKdkYyaocnK0ntHGYY5k+IFJ/LYximHcDNiDiFn2YY5joADgCbRj/+EoBLAJwE4AVw7aQ3mEJJUrREkTn6yamaSqmMVqOO6Oy0KkTwqF1khcOckGrH4wuEJNGnY2WynFlzsm2YneXB3VfUwuMPwmbUI92iw5xs8uTGi/pHPxMlY28qIwij02F542Dr2nLs2nfuGhJtj5x+MnBuBzk6SpP/XbTUQ7Q24fGuIVz72PsSI+PiyoKYTZUHvr4Ue/5tJfadiKSGPrS/RVgQPn7tCjCMNGohXl9Sch6L9bWUjN5EdsX5a2YZZtIdtamQ0hXdt9z+ED7t98JsYFE+Kw3/ssKOkWAYQ74Abtt7FL/7xnIUZZoUI9N4Q7Sl100s5JFnM8mkYEae1VjeT7l+FwhxuGTXmxO+iJLr12Eu8fedIkXr5quWuXysGPWMZJwm6bBGozXieFFBBlrPemKynBYVZCTcXjVZNcFgGM8d7IiJxL6sdvxqK4jRquE8HYhnv4jHGbl0dvH3EtVpVpI4ERdE0usYWAw6ieP++xctwGMHTsvaWnOybfikwwXgnISEScfi8f87jcevXQEOXMwcLjfHv3+6n9hOg05HHSHTjETmVLHNKCfxMN62XnRmQ6fTh5M9Q/j9m+ci+Xvd/oQy1OzZVlQWZcA8+k5lW434j8+X4arz7MixGmEz6WE2stj1j2Y09bix++p6ZFn0Uy5blkwoFb9s7hki/i46mIZkp7Esg/n5kULdi4sycP78XMxKM0PHAu87+lGQYcbnyvLg8gUlEiHiKGLxuXyBiDREp9OHp95rwwNfX4ZD7YNC1sSNX1yIzy/Il/QT8VqCL2S4++p6GHQMlS4bR5LaOcxx3L/I/Got4bMcgO9ObIsolNRESySsllRGo55BpkUvcXayLGA0kAdrLYusI51O/Oh/D8W0y55jRe2c8ZGumCxnFssyWFWej9N9noQiPLRoMk5lSr9cH4qug5Roe+T0k4FISpqjz4PjXUOwGnQS42THhhpJka5oh+tvv7GcaFzu2bySmJb3m39dJnFu87978+RZ/P7NFonDLV5fUnIeq3HsK+2Ki68522qUTdlSIl4Es9LvUyGli+9b+WkmNPW4MSvdhJFAGKd63bj3HyclmpK+QBgftA3AqGPxwOsnccfl1SjKlH8H5fpAfnrss9i2tgKfDniRl25M+P0k3Xu5itTbnz88KYsouX7NcbQ4kla0bL4CY5Ml0KIbfbovUtwx+nzROqzRaJVN0utZfLmqCPYcJ7qcPhSOymbFc9Rqzao50ukU2giMpvI/F5H3GC8bRIxWDefpQDz7hR9nSFFkYqcE/71jXa6Eim/JSZz4AkE893GHIAtRmmvBzo11uPuKWnAAHH0ePHbgtBA1JzfW5Yo2dPhN5gGvHzqWgdw+BWmO11IbhJKaJDKnAlCUeNixoQZ9nhEA4ye9QOqDuTYjvn/RAtz7jyYhGnT+rIhjkX83orPz+jwjODPow85XT+Cq8+z4zdeX4ax7BJ6RIObm2nCk0wWOA/78YbtwjEZHP4qzLLJZUjPRxlAqfgkAt19WjZ8+d1gyXkQH0/B9qqXXjabuIUnglrjAdfT8eftlS/DUe5HsH4uBRVVxJlF6R3weAGjqcaO5e0iQ1WmoKUZxljmmf6bCWmI6kNTOYQqFMj5oiYTVksroHgnBPRyA1XQundM9HIB7JET8vJZFVqdTJt3P6UPtHOJXAKhb5E7mBKQm1YVlyAsWpWZpLfIzHpCMxp81LMbvRgvSiduTaDSDnL4Yb6wMB8LY8fIxodhFfWkOzi87V4yO5HD9qG2A2Kfk0rhtJrKzhTeooh1uSlF0Ss7jaH0t/vxqHWvia+ZTt/kojhybMUZKI5p4TpREnCypkNLFsgw8/hB++MwhFGWaY6oq84Ytv8ExK9MEPg1v29oKlObaiI4l0nhiz7aORluYJH3DaogU3PxSlXKxMB6lex99zj7PiFD4g2eiHLVKC5TJGn+mG1lWA3HzNcumLJ9gM+mI84bNqOxU1uo87ZKZo+Mt1rXIJvHo9Sxq52Qr2gDRaM2q0WqDANqc7VojX7SnbwABAABJREFUqrWeLxlINNNFPM6IU9bt2Rbc8NRHEikfs4FFU/cQKgsz4kYPy0mc5NqM+NloAUMgIuFwsteNm549jC1ryiXRktFt5Tnd58FNfz4kpNrz79b2hsX4wTMf48p6O/Y0tuGmdZXEdy1a6oqUTTWeMmuU5CDenJqfbo4pmswXfqsuzoDVqJdoxo5X1lB01pXNqEO2zYiHXzkhscM5hLHuPmnWkjg7jy/m6AuEsePlE4L8AADZdysUBqyym5/K89t0hbc3865dgbdOnY2RvCnJNgsZb/npZrT2uYmRvvw93fKnj4iBWy297pj586fPfYLrLigT5qqffHkhGmqKYdKzKM9Pw46Xjwnt4J3S4n+LpSguXpyPt0+dVczKo0wM1DlMocwAtETCakllNOp0ePCNU4JOMccBew91YNeVS4mf17LIKsq0EA2BQoXIPS2L3GScgFr7PMQFy6LCdMyTaacWh/J4QZKBKM4246Z1lZqjsuM9y3VVhVhUmC7r1CdFIoU5ckqq3M8L0k2KO/Nih1u8KDqljYjxkjeR0xl+4OtL8R9/eCfuOyEuOMJfn9iJMtXFz8aLcJgTFhr8wmrLheUoybag5axH0FjbuqYCexrb8MOLFwGIXG+O1ah4zdHjSUuvG2+39OGfx3tw/RfKcXxUf/KRA63YtnZBwu9DvHsfPYZNlqQI368X3rAqRqNu29oKtPa5E4rgo5yjODMifxMOn4st1LEMijOVI2t5Db/oTYjBYb/i97S+1yY9K5PqrhzJq0U2iUeLE1RrVo0WG4RvoxZnu9ZMpqmsNzAW1GS6yM2fAHDDmgWSCDl+jl46Jyuuc1jOIW8x6mP6jFVUzDQRDUy+n/OOO96WG/IF4Ogbxq7RDRLSu0Z6pg98fSnW1xaj1+0T0rzfbe1Lqc0ASnz4vr5gywU40unCqV63MKeKMyyiJR4efqsFezavxJW735kQG42U0WfPtqJqdqbwf5aB4BgWn/+pfzuXnccwiHm3+Gt59oN2bG9YjNtGdWn593lPYxvSTHZi1kAgOkVxBsGyDPIzTDGSN9vWVuCjtkHct68ZOzfV4TPzcqFjgV9vqoN7JIi2Aa/Ezm0frecSHbgVDnNo7nET50+xj8A1EhIc/kWZZnxtWQl0LLC4MAOtfR5sWF4Cs56FzSjN9rz9siXY+tRHMRsZAFJyszPVoM5hCmUGoCUSVi6VsaJAPpXR5fPHRENsXVOBoZEA8fNaFlmVBem4df0S/Oz5c6mnt65fgkoFfcFkdl6pWdTajHrigkUpPbj1rHqH8ngRbTTyC5de94isVms85ByVC29YhXl5trj3kuRwffFgB9Hw3P3GKeLC1J5jgz3HhkWjUhakAgyJaAqLtbxIGxHjJW8iFz0uLlgi906EwxyOdboUr2EqpUvGC37RvePlY5KK2g+8fhIP/MtSLC7KwMb6EqGA0FXn2dE+EDGczQYWVpNeVSpjt8uHMBdJp7tt71FhnF1fV4xl9qyE3wc1936ytZ95jTodCzR1D2HD8hJh/Bnw+uPKDFCktA14ccdLx2I2Xyvy0xXvo1EXiUYXF5d95EAr7txQq3g+re+10+cnLtZdPmVntNbNMK1OUK3nqyrKIMpfVBVlKn5vLHaIFg3nZLZ7lFDKdCHplcrNn/NyrcI94zgITo9E5FTkojQ7Br0xfebxAy2CTcpHL8+flYaqogxiYVF+Pu50+gRbzmyISBYB5xwsvkAYjih7hvRMt/zxI7y0dRVWzM1Nyc0ASuKwLAOWZbDz1UixcH5O5TMs5OZ4fyg8oTYa6R0U///tU2eJ52+Pys4Tv1vPftAu2N+dTh/+8uGnePDry3BwVJeWt8N4SQQ+Srk8Px33vHIc65Ykln01XSEF51gNOjy0v0UyF3S7fPik04UXD3ZI+tSexjY01BQLxxMHbp3u8yDEcbIZlDwvHuwQ5kp+o2Lnpjro9YxkXfXA15fi6c0rccbpQ16aCT945mMhy41va963V6DT6cNNzx6i49sEQ53DFMoMQW0krFXWESmfqmPU6bCnsU3iiNzT2IblpeRFqBZHb7tzGE+/78CdV9Ri2B+ExajHEwdaUF8qn3o6Wc4rtdFLahe1WqQ+zEaW+ByNE1RZPRolfaqdm+pwXmmOqnsWXeQOiDzLtn4PTnQPxb2XJOP5yno79rzXhs2ry1CcaUHbwLDg7O11+2WLxJTNSoM92xpTgCFRTeFE7t1Y5U3CYQ6tfe6YfnPH5dW46+8nYu5j9Dtxus8jW8SCvwala0yVtGbxopuP6OLTITsHPPAFIxYv78C1GXX47RstwjvYPuCNGR+Vrr0gw4wXD3YITrQHX49Ub96xoUZVSrCa/jVVem18pHo0qbR5kAxojawtyDDhqvPsqnVJtY5dmWYj0Q64Z2Od4ve0bl4obRgqRYiWZFqI9kdJpkXxfHo9i8tqi1GRn6ZK41irHaJVwzlVN+3kMl2e2vwZVe3OTTMSI+cS0eONHistBh22PvUR/EEuZuNjwzI7/nH0DO68ohY+fxBzcqxYPicbRhlbmaRnTNLiNBtYfPTpIHbtOym8C9lWg+wzBZCSmwEUdcSbB0hz/Ok+z6RlDZGQm0syzOckIaIj7we8fhRnmbFtbQU8/hA4DrjvH034wqJ82LMtuOo8O0pzbBjw+uELhPHwWy3YuqYC97xyHDd+cWFSFTyeCsTBOU3dQzjc4RIKaAPnxo389IgtGh3YRdIi5gO3ul0+tA94Y8axmy+twkNvnNvwurLejqfec+DuK2ph0LEozDShqigTLMvgpdE+OistIm2xaTSyfevacqL8WWuvBze/eISOb5MAdQ5TKBQi/lBIdaqO2kWoVkdvo8OJRsdHkp8rLXjGKz1fCS3RS2oXtVqkPkw6st6kWT+5elxyUUy7r67H5icbFe+Z2MlmNpBTlo16Fv/xhw8VDQf+OLPSjXh680qc7vPipCg178oVdvzmjZMSw2TA68esdBOxbwWDYfz1k07sfPWErMbxWKM1xypvwjsWsq1GwVnDMsCCgjTBoS2+j9HvRLfLh6cbY9Nl77i8WrgGuWu0Z1tTJpIpWquPX3htXVuOivx0/OaV44J2WmVhOlrPurFheYlEJ1g8PsYbD+bm2nDTukpFfexoSM5me7YVOzbUxERTyPWvqZDLmYzxdyagVT+eFEGUiC6p1rGLZYHrV5fjlr2iwnkNVUhkP1JLhKzShqGSc/hYtwsPvi7VOH7w9WYsLIhfWE6LxrHW56fVyZuq7914tVtrv+cRj5XBYBg3rKnAT587Fx1sz7HCZtTjVy8fg6NvGK8cPSu0Vclxz0dD/+7q5Tjc7kTZLKkWJ58uL3bO8PbMns2flb03qboZQFFHvPeDNMeTxvJ7NtaBZUDUdR1vSOe/4/JqnO7zSKKD9zS24d5NdfD4g2jr98Jk0GPHy9IghkMdLkGP+LFr6/HrK+twsscNe64NXYNe/HhdJaymyQl+SXb4vgAA39vzcUyfybOZ0NrnxlXn2fHU+20iWzQbzuFAjNQDnx1jNerxp/fa8O3z50nG19w0IzYunwNfMCxka3Q6fVg5fwgAsG3PuYLdfB9t6XVLNj/l5Pz47DwxfLYegKQPQEklqHOYQqEQybWZiNE/Sqk6JVlWlGRbJJNFSbYFJVlkTcTJcvRORjq1lhROR5+6Ra0WqQ+TgSU6lE2GyTWe5BYujY7+mHuWe+0KzEo3Cc9H7GT7yZcXyjq7lRZGJGfdY9ech5O97nNpVO+1xWxuyPWTcJjDgZY+wSknTg8VLwynurouf9/FDk8AWF2Rl9A7wWsvivURWQYS6QO5a0yltGa5cSUUBjoGvbj+8+W4ZTRqoTTXgh+vq4Q/FIKBZdE24EVDTbFkfIx37YnoY4uR05r0BznFzYlkINHxN1WizKcKUsThtrUViCPlC5Zl8IWKfMxKM6HTGSlixUfvxEOLszbDbMSzH7bFbPru2FCn+D2tEbI22YJEykucTic5Aq9zggrLaX1+Wp2lky0jM16MRWM5+plEa6GSnlM4zKGt34Nu1wg8/iBKc2wxeuiOfmmxxIr8dNzx0jFsWF6iusgnn5V3rNMFHctgx8sRqRiLgUVtSRacw37ccXk1fvjMIUlBPV8gjEAopHhvUnEzgKJuPNH6fkSP5WEujG89+t64F6gjIa5B0NbvgdWoh82kw3f/+GGMg7HH5cMjB1qxefV8tJ51y0oXmA0sPmwbhMWggz8URlP3EDgOeHTvUSpbFQWpz2xbW4GuIZ8QPMKvKwHgyBkX9h3rwqPXnAfncECwGfjsGH8ohCvr7YJclY4FFhVmoCDdhK1/ip3D2dH1KmkNEL02JGm3y0n6mA0sAiEOl+ySFjpMxgCUVII6hykUChE+sk2NAeLo9+LuV05ItA3vfuUEFhdlEp2dWhY99mwrUe+PL8ZAYjIcdFqiNsxG+ShYErJSHwb5KODhQEiiAQVEHP2+QCjeJY0rSs43Mb5AGG+ePIvfvxnZYV5YkC5xsj16wIH/+HxZTDRQbppRsS+RnHU3/fkQbvziQknU5QZDJNJ6To4VlYUZkkWi2IC3GnUSx7a4/dHPfKqKG4bDHIIhsi6YQcdiVrpRov1sz7bGLFDERiUvfcDrLoshXWMqRTLZs634xeXV+K+/SAsY8bprLCKF1HKsRqSZ9bAaWfT2+XDH344Tx0e5a4/WkEy0X5D676F2J3aP6sfJbU4kA4mMv6laPGsy4SMOo/Xjl9qzZDcHgci95SvCq7m3Wp21OhZYW1mI//zfg6qcoFrHCy1ySwAwK81EHBvz0pS/p7Wvan1+2iO4p3ZjUita2k16Jjs21OArS4oUx9hwmMNrJ7rR3O2O2RQWP09Hv0eykbBlTbkkqi4RG5a3H/o8PmxdUyFE3q2vK0aYA/yhMFp63Xhofwt+fVUdMbOHNG/z9yZVNwNmOmrHEy3vh9xYft0FZXjw9ZPjvnFPcnYDkEi/leZa8N0LK/Dg683C5khNSRaau4ewvq4YruEAnnjbQXQU7mlsw61frcK9/2jGhuUleOA1KlultMHAsgwWF6VLNNifeNuBjfUlxOCRLWvK0ehw4trH3ifO93zwmHitv+PlY3j82hVEJzSvdQzEzunRa0M+gpzfXO4YHBYkd6L7wo4NNdj+/OGUCEBJJahzmEKhyKI2aijagOaRi4TVYsxGR3DwxRiWzslWTCGdaAedFke3WskHl0yhH7mCf0BkEicVI3r0mhXaL1YDpGe9Y0MNdr4qTRnjowL4Sf43/7pMck/56OlfX1kn0QEGoNiXSI4HR98wirPM2LN5JfYd70EoDEGTi3eCiB3DYgN+69py2fSnZInUOd3nwU+fPxzTZ35xWbWkEvCODTVYPidb1oGk1cGQSmnNbQNeDI8EcO+mOhzrcgkFT66st2NPY2QR7wuGBc2z0lwLtjcsxj0ba+EZCWJRYTqWFJ+Lppa79mgNSaUKzGJjfzgQium/YS62uneyOt/jjb+pFGU+VeSnm4mbg/FkCbTeW63OWq1O0LGMF6TsmHiwLHBzQ5Vq+Qut91Pr8xuLk3eqNibHitp2Ezd/nz2EbKsRF5TnETd4CzLM4DhINtn470Y/z+jodL5Y1lPvt8XMr3JZEbz98J1VZULxpyybAblpJrSc9WAkGMZD+1sw4PWjIN0UY8/cftkSyby9c1MdPjMvV+IASsXNgJmOlvFE7fshN5aLJelIm9da+o6cszs60COyVmzGj9dVwjMSRNuAFzc9ewgDXj9u/eoSPPjPc1ITD359GU6f9WBWhhlnBr1YX1eMTKsx7gbNTMlGSmSDgVT7QW4NwwcUyc33csFjAFCUacJj156Htj4v8tJMONkzJNE6jp7TSWvDzavn455XjsMf5HD1ylJBV3pPYxt2X10Pg45BQYYZfZ4R1ZkblPhQ5zCFkqJM9KSnJWpIbXqnFmPW0Ud2QDv6lPUFJxotjm61kg9qC/4BkYhIXisv0UjriYD0rO3ZVhh0bExFcH6X2BcIw2aK7VNyOsBKfUnO8ZBjM6HbFWs0+QIRLSv+HNEGfJiDpKCY2OGtJf1VTmNZy7vNf7+pewiOvmGJJATHAX1un6QS8E3PHkJ+uklxgaLFwZBKkUzdLh8e/GcLrl8dqRhv0rP40cWLwIHDxuVz8ND+Fhj1TEQPb3Qhs/25Ixjw+nHPxjqJYxiQT+OL1pBceMMqYiHFiysLJM76bWvLY/qvjknuzQk1KEVaT9cFnVq0yhLI3Vvx+EZCq7NWqxN0LAXpSHJLc3KsmKdwfZkWsvzFnVfUKZ5Pq9Nc6/MDUtfJO5HE2zzzBSKyVSXZFllpqbuvqE1ok60gQxqdPuD1w2bU4f+Nygs9es15o58jz9di++HZD9px9cpS7HqtGdlWI7752VL85p8nJTaEPccGe44tpiCeeN4mORBpP0k9JiPDSm4sF2cVym1eq5175Zzd0YEeQMRBfKTThWc/aMfXlpVgw/ISrJibg/95pwU/uHgRhv1BpJv06HP7cNcrJyTrhAdfa1bcoEmlmhdjpaXXrWi/y2URvniwA9sbFuO2vUeJazC5+T56PccXlVt335uCxNmufSdRlGkWnLv88aLndHFUc3GWBW39w9jzXptQII/XeF9QkB6TzckfczrYwMkEdQ5TKCnIZKTgajFYog1ofvGjVB1arTFr0quTYpgstDi6vX6y5MOwjOSDlqrzbQPkSOtldvmifxMF6Vnz98zR58FHnw4KBQyAyHMlRdDIOQyU+pKS42HIF5TZ1DgXfUbSxbp6ZangrE9U7zXeuzvWdzs6QslsYCUpY3wqoRhfIIy2fq/i+y6V1NDDHwoh12ZS7OOpFMnEays/tD/iZNKzgI5l8KuXjwuRWlvXVODWvUdh1DO4df0SYUMn06pHW78H9hxpGp/42hkw+N6ej2M0JNv6yQupPZtXSn7+dGN7zNhaXZKZMs73eMgV6zreNYThQHhaLujUIheRWzdHOSLXKrdpqyBHBGh31o7FCapF49hsZInO6Hg2wdxcG759wXzV16fVaa41ohqgetzRRM+TP163kPhMQuFz6eUkp1Vzz1BCm2yk4nZAxC7go32jAyeCwTCOdDrR6fRBxzLC8TudPjz5jgNbLixHcbYFvS4ftlxYDn8oHGND8PbM26fO0gi5aUq+nLyNTVneRg2ksfz2y5bg/teahfORNq+1ZO7IrR1JgR68g5q3Uc0GFosK0vHK0bNCgUcAKMo0Szbm+SLSN+Sn4ZFvrcCAdyRGamWmZCNFxhmXov0ul0V4Zb0de95rw+bVZSjNscJi1EuKYyoFu4jXW6d6zhWVY5hzEcn8WMevkRbkpxPndD6qecuacjz8ViSLo9ftF763dlE+qqMCMMJhDiwD3HF5NX4ikoNLVRs4maDOYQolBdEy6aldXGjSAx5jdehE0OkY4sJTr5v6hZJaR7eOYYiSD/dsrCN+Xsv97XaRi+7EixqbbNLMesyflRazwxwdQaPVwajkqPSHQkS5joBIEFlOF+uejXUIhMIJL9hbz5Lf3YU3rML8fPICVo1BGx2hFH1d2xsWY/f+U5Lv8NH9pPfdYtAhGAzHSE7wum83ratUdNylSiQTSVv511fWYftXFmNwOIC2/nMLkm1rK3D0jEvQudu6thzvIVKQQ3wvxNfe0usmakhajeQKzJ1O6QKLdyw9fu2KGDmVZHe+JzL3yDkUAUzLBZ0WZDXn40goaJEjArRv7mh1YmvVOFYrzyS+vosrC7Bn80pVhfq0Os21RlTPdD1u0vgRPU9yAH7WsBi3RkXA7Wlsw4ZlxQDITqunG9vx069UxvQfUnTbFyrykZ9mQofTh2CIQ/uAF0+8fW4zW+yoDQbDeO5gh5CxFZ350en04YHXT2Lb2gq4R0JgGGBRQTr8oRDxmSZqj9NNhNRjOBgijl++oHxdELXPWS5zb5k9W3HzWsvmg1xfJQV68PIR/Ge2rqlAO6Hw2IDXj0/OuPDnDyMRxhvrS7AgPx2+QAh6HRAIccixGSQOxFSqeTEWjnQ60dJLLtw3K82Mll63JItwy4XlKMwwS5zs13xuHu76e0Tij8/A4TigOMsc45BtPeuBo98Dm1GPggwTSrKsOBblnBZnVXY6fXj4rRZsb1iMX7x0jLiRxvcZ8ZqF/96ODTUx87J4Tsy2GhUjiynqoc5hCiUFUTvpaVlcaFkAsSyTUHXo6LapMXIseh1RiiHeQjAZjeYBr19InREvaAaH/fG/nCBao8Ymg+h+WZprwW+/sRzgONijKoaPh4NRzlHJF1eIluv40qgeLEB+H66st+MHz3yMm9ZVSrT/lHD0e4jvLq/LPVaDVvx98a59TXEGCjPNuG3vEWxePT8mjezxAxEjTFycb+uaCmx96iPctr46xmG9azQafbo47uQWT/9s7oF3JAgA2LC8BCwDpJn0+M0/Iw52PjqNYZSdmHLjaUEGOWqoKDN2gSUnp5LMznelQlF6UWSnnENxw/KSabmg04LcJpY/uqpnFFrkiHi0bO5odWJrlb/IsRmJNkGOzah4Pq2F+rQ6zbVGVM+UCDgx54q3jeDMoE8yL+3cVIdsq0HSVzz+EP52uBM7N9XhuEgzftvaBYLNSnJaDXj9qJqdgarZGVhmz4bXH4yxPfj28H3lO6vK8Ps3W2LGbLGj9kinU3AMA+TMj61rKgTnMp/R8/BbLcTNkETs8Zm+iZCqtA8ME+e+sjwblhRnxXxe63MmjeXxNq+1pOfL9VWSVMrh9kGhICPHAU++44BRz8RIHdx8aRUeeuOk4DDcuqZCcDTefUUttvzpo5j7kEo1L8ZCp9OHpxtjA0FuW78EzT1D+N4eaRbh3a80oSjTjI31Jbjj8iUozbWBZSDo+oqzDPmNNYDc77atrUB1SSaae4aEe03KqlxUmIGH/nlS2Hxo6h7CkC8oZCDas61Cn+FlJOw5VnQ5fdj56gkYdKykf4vnRD7qmN9IpmPd2KHOYQolBZFLwZWLQNFa8GAsKeHRcgkktBg5YXBINxtw1nPOkEk3GxCJHRm/80wGaWY9cdG+Y0MN8fNaIqu0Ro1NBtH90tE3jP/4nw+weXUZhgNhzMubuNQg8WZBUaYZ//mlSvzgGanRc7JnCCwDdI1+xqhncPcVtWjqGUIoDEECQ81CPZ4u91gNWlKEM7/g5NOoH3nrVMwi+qZ1lbi4sgBzc61CcT7++hod/USnDcNMr0iM6MVTOBwZU3yBEOpKstDn8SMv3Yifv3BEWNDz0WkNNcWK90LO+dw+6CWmxVUVkSUjWAZ4+9TZpNngikeihaJ4WY9ohyLHTc8FnRbknLyfm5+r+D0tckQ8WjZVE8nEICG7kZlAcTktxMviUEKL01yrrMRMiYDjEdtrvMM0+hnt2fzZmL7S1OPGbXuPCpFv6+uKsXROlmSel3NasSwTN6pdKSMn2lErl/nx8Lfq8VHbIMpmpUnSt7c3LMYDr51UfK7xJFdSeRMhGYM3JouiTAtx7ivMJM95Yxm3eKLvt9g5J97E1VKbJN7aUSyV8uA/W7BlTXlMsMJfPvwUezavRL/Hj48+HcSf3nXg5oYqfPjpoOBE5h2NHn9Qch8WbLkA5QXpKVXzYizw/UdcW4RlgOJsM779WCNxzBrw+jF/VhrSzHqwo3NRtB0a/fxJ48t9+5pxy1erJM5pPqvypnWV8PqDaOv34ra9RyVygYc7XPjeno8lGYgXVxbgJZHE4D2vNAnfiR7HZtqcONlQ5zCFkoKojUDROpCqXQCpdcJqMWYzLUb84d2j+Ob5ZQkXkdFiTE2GsWrR63D958txy4uiaumXVsEiEwWtJbJqLFFjE43c9YS5iU0lJ/XTR685T1h48Yv2Aa8fm1eXYde+k9i6thy797fgO6vKBDkBcZsTNUri6XKP1aBV+r5gtBemo98zguKsfHj9IWxYViz83usPqapoLE5dm04Lu3CYw+GOQWEzZsuacvz+zRYsyE/DTesqJY71K+vtePIdR1wnpng8TSQtTq7gRzJtcMVD7h1vdPSjOMsijL+kfssvHKbjgk4LrmFypkm8jb6SLCtKsi0Sx1JJtgUlWcoLf62bqnKZGOuWFMp+B9DuVG7t01aQLl4WhxJa7AO5DZB4Gx8zJQKOR2wX8huQYnyBMAKhkGS8ePFgB26/bAl++twngizQzk11OHX2nBam2cDiga8vxV9vWIVet7qAB7mMnEWF6VhcFJvKXJRpIUYpu0dCyLYZsePlY2ioKY6JqpObT+UCA8Q6q6nqMEnW4I3JoqooQ+i7/PXfftkSVBVlEj8/lnELkL/fFy3Mx+6r69Ho6EcoDGLEZqLIrR2ja1cMeP3Y814bMeK/ujgL77b2Cfaoxx8iRuxbRAXPfYEwmnvcKJuVllI1L8aCuP/wY9/NDVU42eMmjlnVxRmwGvXY/vxh+IMcvvnZUty3r1mwQ+UiduXGF/458se351jQMTiM2/YeBYCYgnR8wTtfQJqBuGfzSlQXZyVUIHymzYmTDXUOUygpiNoIlMkoeACod/ZqMWa1FJFRa0xNlrGaaTVAx3C4+4paePxB2Ix6eP0BZFoNxM9riawaS9TYRKNUQTlePxiL857UT99u6YsxSICIY5T/m//8WIySeLrRcgYtgIQcsPz3F96wCm39HlhHdcHEv1fa8CE9kxcPduCXl1fj/4miCnjH3Y4NNWjtky7AU31hx7//x7vO6ag9+0E7vn/RAtz7jybctvcovvnZUhRlWrC+rljQbbv9smr0eUYAIG5/TCQtLlqzWOwcSJWoMLl3PBSGZPwV6792u0aQYzOCA4d1Swqn5YJOCzodQ3S61s6pVvyeo9+Lu185IdG2v/uVE1hclKnoTNAaiTg314ab1lWq3uDS6lS2ycpYKC9x4mVxyKHVPtC68TdTIuB4ou1C0jPKsZmwzJ4j2TzT64DHr10hSEPoWAibaUCk/27540d4aesqrCzLU9UmuYyczavLUDU7I+a5kxx+NzdU4cHXmnFJTRHW1xVDz7Ioz49EEPNFT+/ZWEecT6NlNPjr2Xe8R5g7/vvq+pR0mKRyxPN4oNez+Gr1bMzNtaHL5UNhhhk1szMlsktitI5bPHL3e8/mldj8ZKPkuOP5HEgycr+4vBr/9ZfDuG3vUWysL8G8XCuuOs+OZfYsAEAwxAnX+t/7T+HmhircslcaTPN7UQ2NiG0RWRvwDuJklt0aD/R6FpfVFqMiPw2fDgwjzAG/338KqxfmE8esPf+2Elf+9zvwBcL47oXlwtpQbIded0EZHH3DkucvZ8t1DnoFSboHXz+J0lwLblhTIchU7Glsw+6r6+ELhHCw3SmJ+hZvAO473oOOQR8WFqQTzzMSDOP9030xMhQzYU6cbKhzmEJJQdRGoAwHZAoeBOQLHmhBrbNX6+6f2ormao2pyTJW7Tk2nOx141C7U7iWmpJM2QJzWjQnJ6NIoFbkogXjRWGqXZxHO5JJ/VQpOlb8f1JKaXRFXyXHdSK63CR5A7XOiBPdQ5o2N0jP5KZ1lbhoYT5y00w41D4Ie64NXYNe3La+GqW5Fnzp129O+LsymfDvP6/TxhvOjx04jdvWL4bNZEA4DPR7RmAx6PDjLy+C2xdAv9uHHz5zMKH7rXasTNWosLm5tph0RX5jYXXFOQeNnP7rcnsOdQyPYtLpiBt98fT2Hf0eYlHSeJFmY8k40hKxpdWpnJ9OzsbIT1feALWZyIXsbCbl+6k1rVvrfZkpEXA8YrtQScKBnyfn5tqI86OcQ5Xvv2o2mOXGsSffceD8+bkx74PYYdMxOIxwGNi9/xQOdbjQ6/ZLovU21pfAnm1Fr3sEOTYDrn3s/Zi+9YfrPiO7ycZ/7qfPH46pG5AKDpNUndvGi3CYwz9O9CRsr8XLPouH3P2OlkLhfz5ezyF63HT0DeNP757GQ99Yjg/bBhAKA/e/3oxtaxeAYSKf/+nzhwX94UMdLhg/jDgau10+lOZacfqsG009bgAQ7sOnA17kpRtnRN/h0etZ1M7JRrrZgEt2RezxXnespODOTXXoHhoRnoFcZgbDnPs3//zn5tpixpdtaytgNuhQNycTL8kUO+Tnq9N9Hmx9Kjb7gc9ADIUjmxEvb1tFrH9y8wufoKGmGA+/1YKdm+oEGYqZMCdONtQ5TKGkIPZsKzENSU4fqm20qnJ0pHFprhVLSrLGrV1qnb1aImK06O6qNaa0FsZRi9oCflo0J7UUCZws+EXvgi0X4EinC6d63aIoTPn+rMZ5HwyG8ddPOiWGBinChhQdu21tpGAMEIkc5fuQUDAh24oul09S0TcRR67aaAa1mxVyzotEHLZKjogLyvNQkm1Bz5APS2ZnYG6uDe+29sm+KwBSUmqCf/9JOm29QwFkWPTItpoQ4jiU5hnwh3dasdSeK/SVRO633FjJgEFLrzvmfqVqGh3LMlhemoV7N9XhmCht9Krz7JLxd6ZHjyWCycASC6+ZDMoVzbRGmo2lz2mN2FK78QsAHMcR7wsXp/DBcCAEq0H6PatBF3fTfCxp3Vrvy0yIgOMR24W8fuXuq+th0DHEuUQ+EjJWl5jvv2o3XFmWwTJ7lkR6irdV5N4H3mFTXZyFl490CU6sAa8fVoMOWy4shy8YRkV+Ou54KaI/vHVtObFvfeDojynSxTuneRx9wyjOMqecwyRV57bxQu3cN9aAD7n7nSeTYTpez4E0bjY6nNCzQH1pDhod/WioKcZ9+5pw1Xl22HOscPQNx8hObH/+ML77hXLc+fIx/MtnSmPG70cOtEqKSc8k4o2dLAP85aMOyXNWCoqJfv6W0XFrVpoJVpMe7QNe/PaNFlQUpKMgwyx8jzRfKUmHiaUmulw+zM4yS9a5fLQx78y+8emPhTX/TJgTJxvqHKZQUpC2AS/uH9Xq4QfP+19rxjJ7NnGgzEszESONx1tWQouzV+1isEtmd1vJcavWmJrMwjjhMIchXwCD3gAsBj3CYU7WmHf5tGlOJvPCkmUZsCyDna9G0p43LC8R+nNFfpqgpyde5CQaaRIOczjQ0ic4hvnPkSJsxNGxjY5+GHURRwyvlSVe0PlDYZTnp+OXo9WSL6leJZxzIpxcaiJrwmEOxzpdCX+ehFx/If1cbqERCHFCBEOqSU3w1yTWadOxQHl+Ou555Tgaaorx5w+P42vLSqBjgW+snIebnj0spMoBicnjRI+V29ZW4Ht7PsaA1x9zvxKtVp+MRX3mZNvQPOoY4QtFRY+/Mz16LBGGA6GYQq8RCR5lZ6bWSDO1m9BitPTF1rPkjd+/xonIPXWWrDlclGVBWX667PdybSY8cqBVIrfxyIFWPHrNCsV2jjWtm6KM2khpubEjWpdYPGZqmadLsqyYPytNdWQufz3Fm1cKxV4f2t8iaAxfd0GZMHfIZTA5fSGEAcHmX1iQjrtfOS6Zc3i5jWS19eSYabIp0aid+7QEfEQXYI6+37dftgS/+tvRuIUWx4LcuMkwDDY/IZWzuG9fM+7eWAuzgcWhDpdQaFLHAj+6eBEMehaNDif8wdO4/gvlguP4kQOtuGld5YzpO9HEGzvfPnVWUjxOHPQSHRRjNrC44/JqsMy5/nPkjBO/2x+r+5yIvc+yDBYXpWPz6jLoWRa1czJxotOFhppiwfnLB0gYdTpJIVL+PLz9Q23DiYVaMhRKCtLt8hHTROXlG0y4+dKqmMJnBZnjrzurxtmrJQrYpGeJBoZBrhof1BtTWgvjqCUYDOO5gx0xi+/LaouJemPJXFxODSSZB1J/FuvpiY2NRCNNTvd50OjojzG8HX3DmC0TYcNHx/KRr//5pYXIMBvQNuDFQ/tbMOD1Y9vaCsExfMfl1fD6g4IW1kQ4udRE1pzu86C5Z2jSInFIC7sdG2qw/fnDKRUFGr14uv2yavz0ucOCTtvWNRW455XjuH51OR7af1L4+faGxTja6RI2EXjUyOMUZ1rQ4RzGE287ZKszxzP6k7moTyLj70yPHksErc5MrQXp1G5C82jti1ojcs0GHXHz22xQ3szVKmMhK0eRwOZxsm7gJBtqNrTlxo5sqwmDwwGiPap2nuZlb3a+ekLYLKwvzcH5ZblgWQbhMIe2fg+6XSPw+IMozbFJitSxLIPq4iyc7vPGpGXzGSeAvL7/k+84sGF5ieAwKco04+qVpRPmyJtMZppsSjRa5j417wdpPBYXZrQYdNj61Edw9A2jY3BE6N9rF+WjujhL83OIHuvk5H/Meh3xXWwf8MbYYdvWVqDPPYLhYEjWcZxItsl0Rqlv8JKU4uJxTq9fyGIw61noGOB7ayvQ4RxGt8uHdfe9Kcj0iB3L59as1UR7f+ENq8Aw0uxBXtcYgDCG8WOaOEDCqGdiNqbFmRLUNpxYqHOYQklB8tPJxsSsNPJgWZxpRY5tSFL4zKBnUJwZPwJIDWqdvVocaU5frI7S1jUVGPL5iZ/nUWNMaS2Mo5YjZ5zC5AeMRrU+9wkqZqWh1p4d83mtxeWmckEafW57tjVGW1SukIpYT0/sLEs00qTb5ZONxDHq2BhdX3HBt/x0M75y/5vCQuxry0qwsb4EFy3KR7rZgDk5VjR1D+Guv5/AgNcvpEfdvr563J1caiJrul0+ogF3x+XVY1o4yvUh0sKuzzMCR9+w5PvJvNNPWjw9ds15QoTD3Dwbel0+/HhdJR5+61RMlXmnL5CQ1qO0UrdOGCu3rCnHA6/FVmeOvl9KY1iyyzLEG39nevRYImh1ZmotSKd2E5pHa1/UGpGbbTUQnQ7ZMoVdecRFEDudkU2hqqLMuHPjgMdPlKMYHFa2QZJ5AyeVkRs7dCxk7VG1Djlxn+bfB/5Yc3NteO1EN5q73ZI+SJKTmp1lxl1X1KK5ZwhGHQur4Vx2ktnA4sp6O/IzjNizeSW8/hCsxojjrtPpk8gcJSK3EU0yb0wkc3bbRDPRcx9pPBYXZnz71FnBXut0+oT+ff783DE5hkkO6fL82AzO3DQj8V30+kNIN+uxbW0F5uXZEAxx+HQ0SAOAMOaLN/B/MRq0oRRgNJMR9zW+eNz1q8slRf62rqnAr0fv65Y15cL8vWfzZyWOZYaJPMPiLBPR3j/W5cIPnzko6dPiYnN8Zh4fIGEz6fGLUXkdILIR/T/XfQbvtPShbFakcCcfXRxd5yUeyTz2JSPUOUyhpCA6FsTFkFzwbNuAF3e8dExYHHIcsPdQByry08d1Ap2MgnS5NjP2NB6NcdzuumrpuF2HPduKG9ZUqE6nVTsBdTiHiferwzmMWsQ6h7VEgE3lgpR07t1X18cYqiSZh2g9Pb4f8Smhs9LPLaDk7nVBhhkvHuyIcZRub1gsiQIn6RLffUWt0MZogznNbBCMHp5doxF2ckVhWCaS0qXFMFETWRMdGcAbcMvs6iNA+P7c5xnBmUFfzDXxfYi0sEulKFDS4sk1EoTFoJOMsT/58iKsW1KELKsRbf1e3Lb3KAa8fmxvWIwsq16IxCE9n+h3IVpbcqz3S27sdaSIQTzTo8cSQes90lqQTu0mNI/W7AmtheUWFWSg9awnZl5cVJCh+D25Iojx5kadjiFGcN9xebXi+caygUMXt/LIvRdyevg9Qz6smJurSqZnOBAiHqupewhDvgAOtTuxW5RuLfdsc6wm/PCZg4I8WLbVKKlfsKexDSU5i3Dd4x9g56Y6nFeaI2wI8Q7hezfVobnHjWA4DH8ohAvKC+L2BboxkbxM5NzH92Gl8XgisnbkHNIPf6s+5rOzMyz41ddq8OM/SyPqbUYdWnrd2PHyCZTmWrB59XzJ3ECSeeMdi8kaiDDViPtaU/cQDne48Kf3HMKGVSgMicSDWMZBLNPz4OsnhbXU4XYnsf80dQ/FjIcvb1uFX15eg//3l8izHvD6Ydbr8Js3TqKhplgikxNxOHOCY5gPylhqz0ZZXuKBbXTsUw91DlMoKUin00csMFc3Jwtz88gRuloigNSidjGpZce8siAd372wAj97/pzj9tb1S1AZZyGoBi3ptFomILkCEHJa0G0D5AiwqtmZsu2ayohC0rnlZB7EhVT4NLdoPb1ZaWbiPf7MPHKEw9xcG2784kJJKuiiwgw88tYp3HlFHQB5XWIlaQY55wfDxEpW5NlMONnrxrr7xqa/m2hkTXRkAH8+sb5rIo4GcX++7oIyif5XvD6UalGgpOfZ0uuWFLmyGXUozbViwBtEj2sYRh2LjfUlQvRwU49biMQhEf0uiCPaowvfie9Xok4huQXeR58OEqVZkpGJiB6bbk41LfdIa0Su2k1onrE4G0iF5eLBsgwyLHosyE8XMqPSLbq4z1nr3GjS6YgZPGa9clu1Os3p4jY+0e9FOMzJ1o7ITzerlunZtraceKzDHS4c7XQhzCHusw2HObT2ufGvnynFH951YMuF5SjMNKOt34t7Xm3CgNePmy+twplBr9AX/3rDKiwuSsfj166AyxfA4Q4nbt17VLCNlDLzxCR7ZkkqMx5zzETNfS8f6cKJLpfsuqyl140+z0hCmU9qkBvr3m3tF2QF+Hbsvroe//NOK+6/aikGvH5YjHp0DnqFdS0QsauHfAHcu6kOHn8Qbf2xMm/idyJZAxGmAlL2JstE5Jh4u/6Ol47FyNREyzjk2EzISzNJinIO+QJ4/IAjxn699atVuPcfzZJ28NHCRVlGSYHBPY1t2Lx6PnbvPyX5PH/OZfYcLCxIx7EuF5q6h/CTPx8m1uWQg4596qHOYQolBbEa9USNPbmCaVoXa2qNHrWLSS075u3OYTz9vgN3XlGLYX8QFqMeTxxoQX2psg6iGrQ407VMQPlpRqIWdH66UVW7lIrxTWWhJ9K55WQexIVUwmEuJn36jsurMRwIEu9x8eaVRG00lmXwlSVFyLYa0ejoRygM7Hj5mKRghZwu8dON7bjj8mr8RKT9JzaYSdfAjV7bsD+MuXYb5uba8NbJs/jenskzTMZLm7b17Ln+zFcIFqPUh1ItCpQ0Pv7pvTb84OKFOOuJpPwOB0I4fdaLZz9sxxcW5aMiPx3Hu4Zwm2ihruY9TCRFGEDcZyWO7o5e4In1LGeiQUydahG0auTKbUIvtZM3oXm0FrJr7SMXlpuTY8W8ODIW//7khzHjcTynmdzcqPQeA0BumpHoxM5NI8/bPFrtMLq4VQf/3u94+ZhigS01Mj1PN8YWbhJrAeuY+NkfvOzatrUVuOo8O4qzLDAbdKgszMD3L6pAttWI3+0/ic+UzQIQec6fnHEKY/rWteUSxxr/mURsOVrwc2JI5jmG78PZVmPMe3Dnhhq09rkF2ZXSXIsqiZJ4yI110WVb+ICRRocTHS8cwdeWlaA0xwK3P4RHDzgkDl+vP4Rb9x7F9avLAAAblpfAZtRhdpZZIs2SzIEIk010/yzNteCGNRVo6/fi+Y87YmzQh76xHCZ9pMDc9ucPCxHEfPbj8a4hyRi0ZU05MVMx02ok1uEIhDh84OjHcx93CEFODTXF+MuHn2Lz6vm4be/RmLGaZRkwDGKyNROdA+nYpx7qHKZQUpCRILlgml+mYJqWSD4tRo+WxaTaHfNulw+NDicaHR9Jfj6eA72WRZyWCcjtD0HHcBItaK8/ALefXH1eLhJGblNA67WMF6Rzv3iwI26UAu9cXHjDKmG3+K6/n8DG+hLiPd53vAcdgz5i39TrWaHIXM+QDxuWFUsMXzld4gGvH8vsWcSidaT3idcc3rqmAtufP4xHvrUC7pEA0fE80YbJWLVpw2EOxzpdMX1GTR9KJQ3Bubm2mI2AK+vtGPT6kWUxIMdmQstZtxCp8o2Vc/H4gRY0OpzCMXjDNxzmEors5Y3xPZtXYjgQIjrQW3rdis+KZPjzCzyWYfC9PR9Lou9nmkFMnWoRBrzaNHJ5iZroTeh4c4ejn5x5s3ROtqKMhU1201t5qaLVyatlPgUi8k7ZNqOwcQQA2TZj3AJ/WjMq6OJWHeL3nndaqC2wFX3PeduWt9Xa+oeF9OtnP2jH9avLYpzHd0bpYvLH9PhDeOC1k6gpzsD1XygXIuge/OdJXFlvl0Trnep1E7NNeKLfx2AwjCOdzlENbQuqijKg17O04OcEkcxzDN/feG1XfjxeWJCOzkEvdv6jWWi3o28Ym59sHDetXtJYt71hMTE6lF+28vJtRZlm/ODiBRKH7/cvWoC89IjD8aH9LdhYX4K5OVb0ukfg9EaKTi6dk4XSXFtSByJMNtH9s6GmGD997hN8Z1UZHH3Dkn7BcUCaSYf6ubkIhzk8es0K9Az5MCvNjNa+SPbjd1aVScaRZz84t2nGZypuXVOBB19rJkYTb3/+MPxBjhilvOe9NslYXVWUGVfWJ5E5kI596pl2zmGGYdYBuA+ADsDvOY771RQ3iUIZd3QMQyyYtmJeDvHzWiL5NEXCppMXk/E0CtUwGQO9lkWclna1Dwzj3n+cFCKlOA7484ft+Pmli7GkOCvm8/6Quk0BQHsU13hAuo83ravExZUFqC7OVOyLpN1iucVRKKy8ixyvei9Jl/j2y6oxO8MCo1EX8z3x+3Syxw1fMIwzg1401BQLC0beqZ3Igm4yScSRcrrPI5HVUJI9mA6wLINl9ixJutyT7zhg1DPYvHo+/uedVnzz/DJ8/6IKFGVa8JcPP8WaRYX45MyQ5D3c/vxhPHrNioSlNm5aV6norIjnFIoeo8ULPADEyI2ZZBBTp1oEo05H1Mi9c0Ot4ve0OjO1ahwXZJA1h+MVXJVz8loMyk5eufk0oDCfAtrknQDtGRVatZ+B6Serkgji915rgS2SPTfg9eNY1xAYBhKZpU6nD48caMVPLlmMu66ohXckiF73CGZnmSXn448JRJ7foQ4Xbtt7FF9bVgKLgcUtX12Cm1/4RIjW296wWFKolDQP79hQI9hywWAYzx3siLH1LqstTjmpp1QhmecYcR/m3wOzgRXWjRPZ7uixzmLQ4ba9RwStbb4P3rZ+CR54XSo/MOD1o3doBL/5+jL0ukfQMTiMxw6cxqw0qRzB/a8348p6Ox7+v1bctK4Sn1+QP+3HNrVE90/xczcbWMn4aDaw2LCsGIB0zdTSey7CPHoMGvD6UVGQhj985zN4o6lXolns9AVw5xW1aOoeEqKJ+cJ1vFPapGexpDgDt7x4BI6+YTT1uLFzUx2qijIl9QDkZH0SsWfp2KeeaeUcZhhGB+BBAF8E0A7gfYZhXuA47ujUtoxCGV+cPn/MJLt1TQWGfPKRQFoidNUaDyxDlpUYz/l6MgZ6LYs4Le0qyrQQnemFmeQJz6jTETcFPleeK3sOLfrJ44XSfUykLyql4kendmo1bOfm2vC9tQvw631NMbrEFfk21M6JLQzIXxt/rkt2vRljtPCOYZLjWW2l3fFEbhNDHPXa7fLh6cZY2YPffmM5zKNRSNPNyVCSZYU9xypZWN9xeTX++O5pfGFhAfyBEPo8fgz7Q3jpSDeyWwckhYR4g3g8pTbibTgpjdGJFFya7tCIkQgFGSaiRm48p6tWZ6ZWjWN7jg0VBbHV7MV66SQGvSPEecEZJzI612YizqfrlhQqfm8sNRy0ZFRo1X5O5pT3iWQ83nu57CA+qje6v111nh0/f+GIJA3+kupVxGOK5S46nT48/FYLdm6qwwXz8/DoNStwtNOFY52RQnfiDT5+Hn782hX4v1NnEQoDO189AYOOxbqqQhzpdArzFzBa7Pe5T1CRn4baOdkpJfWUKiTzHKPUhzcsL5nwdovHunCYw7cvmI8dLx+T2NnPvN9GXMs+8bYDP7mkEr8ZjaYf8PrR6fRhx8vHcPOlVWjqduNHFy9CulmHR69ZQfuyDHL9U03AR/RmG+/YrSnOQHl+Olr7Ihlu0bIQV51nxy9fOoYBrx9b11Sg9aybuFlx40UV2HXVUkkGXSKyPonas6kmc5cMTCvnMIAVAE5yHNcCAAzDPAVgPQDqHKZMK3JtZuxpPBqzqNl11dJxO4cWo6e1z0OUlVhUmK6oGaiGyRro1S7itLSrqiiDGNVbVZRJ/Lw/FCIaUkqRTpNVjFCOscgLyKXi/891n8H+5t6YyrpaDFuWZZBp1UuiwHgd2S6nD7VzlL9PMsDvuLwad/39BADg6pWlggNCxwL1pTk4vyzxCKbxZm6uLUbWIzrqlU8nj9YRm5drVdQaTWVImyjekQDWLCoUqspvrC9BSbYFOzfWYjgQgmO0kFCihVDUvgvxNpyUxmhqENOIER6tTldA2/itNQKYZRmsWViAsrw0VX2WZVmik/f2y6oVvzc31xajbZ9I/5hsh5BW7edkTnmfSMbjvSdFPoqL5D75jkNIZbfn2NDa546reyocszAd/Z4R7Nm8El5/SLLZWjYrDUO+IH74zEGiVuyV9XYc/HRAovvJP9NOJ3mzkLdjUknqKVVI5jlG3IcdfR589OmgRApFq7NtTG0pTJe8T46+YRzvdgv2cXl+ulBcrmPQi6vOs+Op98/Zz5WFGWjv9+JXfzsOAPjdN5bR/qxAdP988WCHsObkx7AFBemoLMzAvLzEih3zG1p8hhofVTzkCwg2hlkf2bncWF8iPFMgdpNz65oKPHrAgZo5WZJiznKyPo9fuwIcONX2LB371DHdnMPFAD4V/b8dwGfEH2AYZjOAzQBgt9snr2UUikqU+mpVUQZuWFORsFNRC1qMHq2agWpJ1oFebbv0ehaX1RajIj8NXU4fCjPNqCrKhF5PDgnSEuk00QvZiRxT5VLx60qy0DM0Mm4Gea7NjIff+ijmHslFcIshOeFYJpIa5wtENA+/tqxEtebhRMGyDGZnmSV9KDrqVXzf+d39nZvqEnImJSvx+ilpE2XLmnK8eLAjUlU+w4y2AS/ueOk4Brx+/OTLi4TxDoj0l19eXj2pGQzxxuhkHScni1R0kE/EeKrV6aqVyXZGZ1sNxMjobKsh7rm09I/Jdghp1X6eyJT3ZF5Ljdd7Hx35KN5IGPD6sagwQ0hln5dnI9YnUDqmHOKgAd6BU5aXhrPuSNReQ02x5PP8My3KtBBtvUTsmOnMRPbVZJ9j+P42N9eG4dF+C0CQA/jrDavQ656cdsu9T7yzcceGGtzzynFhA+bxAw78x+fLsL6uGGEucowelw8P7W8BMP369kTN/dH9055txTJ79rhkxb7b2ieMN48fcMRoCd/cUCU8U7OBRWmODdvWVsDjDwlrjwGvP2Yuk5P1mZVumrH27GQy3ZzDceE4bjeA3QBQX1/PTXFzKBRZlPqqWqeiFrSlQWuLGJrJ6PUsaudkx41QBbRFOk30QnYix1SlPjieBrnaCG5SO8ULvnCYE+65OG10qh3DPLk2k0QzEZA6G5J9waOFeP1UrnjijV9ciJuePSREDv/XVyqxsCAdx7tcePiVE0JEy9I5WfhcWd6kZjBMx+c03qSag3yixtPJvA+T7YxeVJCB1rMeiTO6JNuCRQUZCbVV7X2Z7PdO6xw+kRvDyb6WGu/+Hu+Zj+f5BPt+VhraBobBANi9/xSaetzYsaEGO189Ifk8/0zl6kuMZ9BIKjLRfTUV5hil/qukAz+Z7eG1s/mstgGvHxwHWAw6VBamgwPw8xePCI7G6da3J3PuH6+s2Ghda3FGhY5lsWtfRJufz5pcOTcH/zjRE3cuS+aI/JnAdHMOdwAQu1hKRn9GoUw71DgVtaLW6BlLxBAlPloWpanuQJLrgxOyGBunzZZkv+eJGF6psOAZT9QWT5yXa4M9xzphm3OJMtOeEyU1mMx+qdez+HJVEew5zkl7Hyfb2Z4KEc7Tncnu07X2bFSXZOF0nwc/+Uql4EAz6FjiM2VZZsKDRiipS7LZCqT2fGVJEbKtRjQ6+oXCqTetq8TqBfkIhznsumop7dtTgFzfiZ5jxBkVQGSTVktgT7KvoaY70805/D6ACoZh5iHiFL4KwNentkkUysxhsiOGZiJaI52SyShMRsZ7syWZ7zk1vGJRuiek5zgZm3MUCiUxpvv7mAoRzpTxh/TclZ7pdH8PKNMbvZ7FBeV5glNxw7JioX+zLEP7dpIRb44ZS2BPMq+hpjvTyjnMcVyQYZgtAP4OQAfgEY7jjkxxsyiUGQUd0CmU5Ie+p7HQe0KhUKYTdEybftBnSpnO0P6dWtDnNf2YVs5hAOA47iUAL011OygUCoVCoVAoFAqFQqFQKBQKJZlhOC7p6ghMGgzD9AJwyPw6D8DZSWyOHLQdydUGQH07znIct24sJ4zTV9WSLPcxGtoudYx3uya6n071fZzK88/kax/v809kP53q+6SWVGrvTGzrmPpqko+nYmhbyKRKWyayn2olWe5dMrQjGdoATH07JmstNdXXSSIZ2wTQdpFItjV/okz1s6RrtMlFtp/OaOewEgzDNHIcV0/bkTztSIY2JFM7tJKs7aftUkeytkuOqW7vVJ5/Jl97Mpw/UVKlnTyp1F7a1vElmdpI20KGtkU7ydLeZGhHMrQhmdox0STjdSZjmwDarunEVN8zukZLnv5KyzxSKBQKhUKhUCgUCoVCoVAoFMoMhDqHKRQKhUKhUCgUCoVCoVAoFAplBkKdw/LsnuoGjELbcY5kaAOQPO3QSrK2n7ZLHcnaLjmmur1Tef6ZfO3JcP5ESZV28qRSe2lbx5dkaiNtCxnaFu0kS3uToR3J0AYgedox0STjdSZjmwDarunEVN8zukZLEqjmMIVCoVAoFAqFQqFQKBQKhUKhzEBo5DCFQqFQKBQKhUKhUCgUCoVCocxAqHOYQqFQKBQKhUKhUCgUCoVCoVBmINQ5TKFQKBQKhUKhUCgUCoVCoVAoMxDqHKZQKBQKhUKhUCgUCoVCoVAolBkIdQ5TKBQKhUKhUCgUCoVCoVAoFMoMhDqHKRQKhUKhUCgUCoVCoVAoFAplBkKdwxQKhUKhUCgUCoVCoVAoFAqFMgOhzmEKhUKhUCgUCoVCoVAoFAqFQpmBUOcwhUKhUCgUCoVCoVAoFAqFQqHMQKhzmEKhUCgUCoVCoVAoFAqFQqFQZiDUOUyhUCgUCoVCoVAoFAqFQqFQKDMQ6hymUCgUCoVCoVAoFAqFQqFQKJQZCHUOUygUCoVCoVAoFAqFQqFQKBTKDIQ6hykUCoVCoVAoFAqFQqFQKBQKZQZCncMUCoVCoVAoFAqFQqFQKBQKhTIDoc5hCoVCoVAoFAqFQqFQKBQKhUKZgVDnMIVCoVAoFAqFQqFQKBQKhUKhzECoc5hCoVAoFAqFQqFQKBQKhUKhUGYg1DlMoVAoFAqFQqFQKBQKhUKhUCgzEOocplAoFAqFQqFQKBQKhUKhUCiUGQh1DlMoFAqFQqFQKBQKhUKhUCgUygyEOocpFAqFQqFQKBQKhUKhUCgUCmUGMqOdw+vWreMA0D/0z0T/GTO0r9I/k/BnzNB+Sv9Mwp8xQ/sp/TNJf8YE7af0zyT9GRO0n9I/k/RnzNC+Sv9Mwp8xQ/sp/TMJf2SZMOcwwzBzGIZ5nWGYowzDHGEYZtvoz3MYhnmVYZjm0b+zR3++iGGYtxmGGWEY5oei45gZhnmPYZiDo8e5ReGcm0Tn+2O8Np49e3Y8LpVCmXBoX6WkArSfUlIB2k8pqQDtp5RUgPZTSqpA+yolFaD9lDKVTGTkcBDADziOWwxgJYDvMgyzGMCPAezjOK4CwL7R/wNAP4CtAO6OOs4IgDUcx9UCqAOwjmGYldEnYximAsD/A/A5juOqAHxv3K+IQqFQKBQKhUKhUCgUCoVCoVCmCRPmHOY4rpPjuA9H/z0E4BiAYgDrATw++rHHAVw2+pkejuPeBxCIOg7HcZx79L+G0T+kcOh/A/Agx3ED/PHG9YIoFAqFQqFQKBQKhUKhUCgUCmUaoZ+MkzAMMxfAUgDvAijgOK5z9FddAAoS+L4OwAcAyhFxAL9L+NiC0c/+HwAdgJ9zHPeylvaGwxxO93nQ7fKhIMMMe7YVbQNe4f9zc21gWYb4vbZ+D7pdI/CHQsgwGeANhCTH6POMwGLQYSQQhi8YwkggjNJcG0pz5M8hPq7HH0Rpjg3z8shtSOR65ubaACDmZ2qP1+cZgVHHwusPoSjTjFAY6BlSf7xE26zmfmh9hmraQaFQxk4wGMaRTic6nT4UZVpQWZCOduew7Lt/us+DLqcPJj0Lp8+PXJsZVUUZ0OvHtteZ6LseDnNoPeuBo8+DNIsODMfAPRJEjs0EfyiEXJtp0sYJtW0+4/TCpNPB4w/Cnm2FXs+gyxkZR+fl2hDmyGN4OMzhVK8brWc9MBtYZJoNqCzMgNGom/BrnEzEfXF2lgXpJj0Gh/1gwGBoJAhfIIS8NCMGvH6kmwwIhEPQMzqc9YygOMuq2A/Fzyo/3QwdC3Q6yfOT+P/iz5LmWUD7XD5ZTMd5dKquye8P4dAZJ7pcPhRlmFE9OzOh9zB6nE10zNT6veHhAA53udDtGkFBhgnVhRmwWAwTdj6tz2Oyz6f1e1qf+3R49xK9hni2hNw6QM08Gr32iTcOyx2bfz96hkaQn25CMBSCyaCH0xtApsUAg46BR+b4VqNe1taYDs97sknFezYe40+0PaF1nSx3DtJ7En28cJjDpwMedDtHcNYzgoJ0M1gWyLEZMegJoNPlw6x0E3QM0D7oQ2GGCUY9iwyzAaEw4PL5EQoDZ90jkvF7vHwAyUwifSAYDON4twsD3gB8gRDm5tpg0DGC7UkaW8JcGCzDCM9NadwUP7uSLCvSzXp0qRxHPSMhZFj08PpDcI9EfDqlOVa0D3olfp7SHCsc/V44+j2wGfXITzeBYSC5lrE+01QcCyaCCXcOMwyTBuBZAN/jOM7FMOduMsdxHMMwiqLIo58LAahjGCYLwF8YhlnCcdwnUR/TA6gA8AUAJQD2MwxTzXHcYFR7NgPYDAB2uz3mXOEwh5ePdOHGpz+GLxBGaa4FN6ypwE+f+wS+QBhmA4udm+qwrqowZkJ+7UQ3mrvdeOr9NlxZb8eu15olx7j/tWZ8+/x5YBjA4w/hvn3Ncc8BQDgu/3m5NpCIvh6zgcUDX18Kf5CT/Ezt8Xa8fEy4xmyrEd/8bKmm9iXaZjX3Q+szVNOOyRgs4vVVCiUZGEs/DQbDeO5gh/BuluZa8N0LK/Cz58ljYfT7uHVNBfY0HsUNaypwWW2xZgdxou+6+HOkcS/SnjbctK5ywscJtW0Wj9n852/5ahV+88+T8Ac52TEcAP72SRd+8My582xbWwHHgBfrKgtTxkEcr59G90WzgcWtX10Mg16HLqdPcm9+ePFCPPnOafx/XyjHb/55Eo6+YZgNLG5bvwSX18X2Q9Kz2ra2Ak+87cCA14/bL1uC+19rhqNvmDhfbVtbgb8d7sSXq4tinpFRz2DLHz+akjkqEaZ6Hp0IJvKalPqp3x/Cc4fOSMbHW9cvwWU1sxXfQ1Lfvv2yJXHHTK3fGx4O4MVPuvCzF8Tv0hJcuqRQ0UGs9Xxan8dkn0/r97Q+96nqp+NJoteQiC0hHmf541xcWYBXjnWPaR6VG4fljv2F8lzs/aRb8n7cfGkVHnpDfi6OPj7J1piOY+14oNRXU/Gejcf4Q7JfSe+H2vsQ7z0RHy8c5vDmyR6cGRzBLS8eOfe5jbU40eXGz0U/u/nSKvzpXQeaety49atVMBsYPPG2AxuW2XHL3iOSa/hq9Wz840TPmH0Ak42aMTWRPhAMhvG3I51oHxiWPGex7UnyB93cUIWH9p+UtUf5se3/Wnpjnp342ImOo3J90TsSxB1/Oy77DLetrYDNqMNv32iRPZ8aUnEsmCgmUnMYDMMYEHEM/4HjuD+P/ribYZii0d8XAUhY/mHU0fs6gHWEX7cDeIHjuADHca0AmhBxFkcfYzfHcfUcx9XPmjUr5iCn+zxCxwCAhppioTMCgC8Qxo1Pf4zTfZ6Y7x1qd+K+fc1oqCkWBkTxMRpqitHn9eOsxy+8BPHOIT5uvDaQiL4eXyCMQ+3OmJ+pPZ74Gr+2rERz+xJts5r7ofUZqmnHZBCvr1IoycBY+umRTqfk3WyoKRYWc0Dsux/9Pu56rVl4v490OjVfQ6LvuvhzpHGPb89kjBNq2xw9L/kCYdz8whE01BQrjuGn+zyCY5j/3X37mnGyx41DZ7Tf88kmXj+N7ou+QBhWowGtZz0x9+buV06goaZYuH/8z7c/T+6HpGd1375mfG1ZCXyBsGAfAOT56r59zfjO6vnEZ3So3Tllc1QiTPU8OhFM5DUp9dNDZ5wx4+PPnv8k7ntI6tuJjJlav3e4yyU4voR2vvAJDne5JuR8Wp/HZJ9P6/e0Pvep6qfjSaLXkIgtIR5n+eMc6UxsPaQ0j8qNw3LH/qRrKOb9uOVF5bk4+vgkW2M6jrXjgVJfTcV7Nh7jD6mfkd4Ptfch3nsiPt7pPg+GhkOCc5H/XJiD4Bjmf3bLi0fwndXzR+eSI8iymvDN88sEx7D4Gg6dkb53Wn0Ak42aMTWRPnCk04nmHnfMcxbbniR/0C17jyjao/zYRnp24mMnOo7K9cWzHr/iM7xvXzPOevyK51NDKo4FE8WEOYeZSIjwwwCOcRy3U/SrFwB8a/Tf3wLwfJzjzBqNGAbDMBYAXwRwnPDR5xCJGgbDMHmIyEy0qG13t8sndIzIsSD5PxD5f8+QL+Z7YS7yu+jv8P9nGCDMQfhcIucQHzdeGxK5HiD2/FqOJ25zovcoUUhtVnM/tD5DNe2gUChjp9OZ+Lsq9z7y3+lyan8vE33XxZ+Tayv/84keJ9S2Wam9Wu57mIsce7oQ3RcBwDMSlJ1vxPO6+OekfqjUd6P/LfcshkeCss8h+mfJNEdNx3l0qq6pS+a88d5DUt9OZMzU+r1u14hMO0cm6Hzansdkn0/r97Q+9+nw7iV6DYnaEtHjtVwfUDuPksZhuWPLvR9KczHp+NG2xnR43pNNKt6z8Rh/En0/1N6HeO+J+HjdLh88BLuG9DNfIIxhf1D494A3IGsTRY+X4+2jSAYS6QOdTnl/Cf+c4/1e7t51OsnPLtquTWQcTWTMU/qM0vnUkIpjwUQxkZHDnwNwNYA1DMN8PPrnEgC/AvBFhmGaAVw0+n8wDFPIMEw7gBsB/JRhmHaGYTIAFAF4nWGYQwDeB/Aqx3F7R79zK8MwXx09398B9DEMcxSR6OIfcRzXp7bRBRlmmA3S20L6f366OeZ7OubcZ+WOoWMg+Vy8c0QfV6kNiV7PeB1PfAytx0u0zWruh9ZnqKYdFApl7BRlWlSNhaTfcVzk78JM7e9lou969OeU2jPR44SWNsu1V+53SvedZSLHni6Q+qLNrJedb/jnzHHSn5P6oVLfjf43///oz1pNetnnEP2zZJqjpuM8OlXXVCRz3njvodw4G2/M1Pq9ggyTTDtNE3Q+bc9jss+nuZ0an/t0ePcSvYZEbYnocVbue2rnUdI4LHdsufdDaS4mHT/a1pgOz3uyScV7Nl7jTyLvh9r7EO89ER+vIMMMmznWriH9zGxgYTHqhX9nWw2yNpHceKnUllQjkT5QlGlRtF8BeX9QPHu0KJP87KLHsUTH0UTHPNJnlM6nhlQcCyaKCXMOcxz3FsdxDMdxNRzH1Y3+eYnjuD6O49ZyHFfBcdxFHMf1j36+i+O4Eo7jMjiOyxr9t4vjuEMcxy0dPc4SjuNuFZ3jZxzHvTD6b47juBs5jlvMcVw1x3FPaWn33Fwbdm6qEzrIiwc7cPtlSySdeeemOkHEW/y96pJMbFtbgRcPdmDrmoqYY7x4sAM5ViNybUZsWxv7e9I5xMeN14ZErsdsYFFdkhnzM7XHE1/jsx+0a25fom1Wcz+0PkM17aBQKGOnqihD8m6+eLADt66XHwuj38etayqw91Dk/a4qytTcjkTfdfHnSOMe357JGCfUtjl6XjIbIprDew91KI7hc3NtuGej9Dzb1lagPD8NNbO13/NkI7ovmg0svCMBzM2zxdybH168EHsPdQj3j//5bevJ/ZD0rLatrcCfP2yH2RDRV+OPQ5qvtq2twH/vP0V8RjUlmUk9R03HeXSqrql6dmbM+Hjr+iVx30NS305kzNT6verCDNz61ah2fnUJqgszJuR8Wp/HZJ9P6/e0Pvfp8O4leg2J2BLicZY/TlVRxpjnUblxWO7YSwrTY96Pmy9Vnoujj0+yNabD855sUvGejcf4Q+pnpPdD7X2I956Ijzc314Z0sw43X1ol+RwL4OdRP7v50ir8fv+p0bmkCoPeETx+oAU3N1TFXEP1bKmPQ6sPIJlJpA9UFWWgPD8t5jmLbU+SP+jmhipFezQytmUSn5342ImOo3J9Mc9mVHyG29ZWIM9mVDzfeN/TmQLDcVz8T01T6uvrucbGxpif89UKe4YilcL5So38/5UqMLb1e9DtGkEgFEK6yQBvQFrtsd8zArNBh5FAGL5gCP5gGPbRKoxy5xAf1+sPwp5jw7y8xCsoRl+PuDplvGtSOl6/ZwSG0UqkfNXTXrf64yXaZjX3Q+szVNMOFYxZyVyur1Io48iU9FO+wniX04fCTDMqCzLQ7hyWfff5SrIGHYshnx85NhOqijI1F6PjSfRdD4c5tJ71oK3fA6tJBxYMPCNBZFuNCITDyCFUEJ8o1La50+mFUaeDxx/EnGwrDHoGXc7IODo314YwRx7Dw2EOp3rdaD3rgdkQqRS9uDBjqorRTVg/FffFokwz0s0GOIf9ABgMjQTh84eQm2bE4LAf6SYDguEQdIwOfZ5Ipewls+X7ofhZzUozQ8dG0sVJ85P4/+LPFmbEzrOA9rl8shineTSpSPCaxnSRpH7q94dw6IxTqKZdMzszofcwepxNdMzU+r3h4QAOd7nQ7RpBQYYJ1YUZisXoxno+rX1sss+n9Xtan/tU9dPxJNF7Fs+WkFsHqJlHo9c+fEV7gDwOyx2bfz96h0YwK92EYCgEk0EPpzeATIsBBh0DD+H43S4frEYdAiGyrTEdx1oREzL3p+I9G4/xJ9qe0LpOljsH6T2JPl44zOHTAQ+6nSM46xlBfroZehbIthkx6Amg0+XDrDQTdCzQMehDfnok6j7dbEAoDAz5/AiGgbPuERSJxu/x8gFoZFLWUon0gWAwjOPdLgx4A/AFQpiba4NBxwi2J2ls4TgODMMIz01p3BQ/u+IsCzLMBnRrGEfTzXoM+0NwjwQFn1j7oFfi5ynNscLR742svYx65KebwDCQXMtYn2kqjgVjQPbCqHOYOtwoEw91DlNSAdpPKakA7aeUVCGpnW4Uyii0n1JSATr3U1IB2k8pqYBsP50wWQkKhUKhUCgUCoVCoVAoFAqFQqEkL9Q5TKFQKBQKhUKhUCgUCoVCoVAoMxDqHKZQKBQKhUKhUCgUCoVCoVAolBkIdQ5TKBQKhUKhUCgUCoVCoVAoFMoMRD/VDUhG+GqFfZ4RGHUs/KEwjFEVN8NhDkc6nejzjCDDbESY42DSx1blDIc5tPV70O0agT8UQobJAG8ghKJMMzgO6BkagccfxLzRSvE9Qz5JdUi+MrF8dUgrKgvS0e4clrTXYtBhJBBGkAsjGOIwEghjXp70HOIqlc5hP0KjFT9Lsi2wGnTodfvh8QdRmmPDvDxpRcvoyqP8Pet2+WKujf/+WKqe9nlGhGvyBUMYCYRRmis9rrgN0fdM3LZQGOj3Ro7nGQkR7z9/b0jPTu7YctVYKRRK4gSDYZw668KgN4SeoREUZppg0esiY4BRD38whHTCu8h/90inE51OH4oyLagqypBULubfU/H4ajXqEebCYMFgOBAAy+rQ7RpBcZYZBj2DoeEQbCY9/KEQcm0mlGRacLTLhS6XDzk24//P3r/HyXGVd/74p7q6q6vv0sxoplsa62JrZIu5YBQlAScLRLId841ua8AmkPUmJL8NCcEKApZNYiQka5MlgPgJyHchyW5idsNig1lZ0i4ORgphWQNBNtZoxrI1RrLkufTc1fe6n+8fPVVTXV1VXd0zPZqRzvv1mtd0d53Lc57znOd5zpGmDzIlGe3RIGRNQ1Yo+7sNLfb+2wk3P2J+Zshqukm4kbYBGH41GmSRK6lGPLHTWZibH3+tG4hXsi9UFA2DoxmMZgREeT/4AINQwI+cIKMkq4hwfmRKMiKcH1yAgd/nm7sxW8Z6mzhp1tv61eWblq/OFBDh/OiIB9G5qtpOzPW96FEQFFwYy2CmKKMlHEBOUBDl/QhzLHKCUvdcLGQerevPnJsEfD4IsgpZIxBlFZtaI9i0JlrRttP6XQg3g12auV4ScCldzks64kFsSUawKsTXrFcqybiQzhr1epNxhEKBpslZLEkYSOeM/nqSMYRDXNPq5UsCXjbp5U3JCKIe9CJJKvpHM0hnBaTiPHrXJsBxbM16jdpqo/bYqJw32v7Ne6B69gNmudujQZQUFcOzJVtdaxrBlakCrs0UEAn6ISoq1sZDYFkGk3mxav8GlHP7iZyITElGjA8gGmRRklW0hIPws0A6Uy2vdQ0lQiyuzghoCQUwU5QQ4vxoiQRwZ3ulfLZ+8XoRoxkBOUFBeywInw9IhLiKvcXV6QJGMyWjjJ9lICkEMwURHXF7m7PuX+32rV5sdqnt5kbb6UJYDNkVRcMr41nMFmUIsorbbeKjua9MSYKiknKO7MEf6GtkKl8Cx7LIiyryooJ1q0KI8X6kTfkKx7I1871G9aHnK+msiLUJHi2RAMazErKChDDnR4z3g2GAXEkBF/AhK8iIcn6wPgaTeQmxoB+xoB8lRcGaaAi3rQrhYjqLkUwJbdEgOuJB3LZ6cWVeyZj9SEFU0RrhoBICPsDCByAvKRAVFaGAH5M5EakEj2DAh5HZsj5lTUNRUhAK+JEXFGxojcDvY3BlupzHJhNBKCpQkGQIsobxrIhUIggfA0zlZUSDLIJ+Fi3hAAryvA8PBYDxnIyCqGDtqhBiQT+mCiIYMIZ/29oRw2i2ZPjpOB+oyptTCR6KSjCWLSHIsihIipGL3wzzd6Ogh8MWNI3g2cE0PvPsRTy8fT2ePHcND29fjy+eHYIga+ADPnz132zDZE7Cl84OOZY59tDduH9rB74/NIGh8Ty+8dP5MqvDHP7gHbejIKk4fqb8/pG3bcDxM+X6G1pD+MiOLjx2YqCqvf97eRKj10UcPjVolP3wr3Xhr/5pXpYP3rMJzNyacOqDD/jw5fe/BZJC8F9/+HO8e9t6HD49WCWbteyBp16qkOmB7iQA4NnBNA489ZJjfb1sPYvVPBf6mJzaNctg1dl3L44bsj3ytg34xk/LOirK7roBUDV3Tm0vZJwUCqWMomj4Pz+fwERWwqGTg8a6enxvD2RVxVd/cNl2LT7QnYSmEZw4P1LhN4/u68Ge3rX43qsTFev06L4efOnsEK5Ol7ChNYQPvX0znn7xWoUftPqER3d04ewraTy0fQMOnpzv46P3bsHY9RL+/Duv2LZfyy/ofq6Wb9X9/YfevhmHTw968jlObXN+Bo+ffhkffscdUMEY8cRNZ4/u6MKT567hkw9srerPbQwrxRcqilZlPwfu24I1sSD+/9+7VGV3+3d2Ye0qHseeu2TMs12c1O3mfb+0oartVILHJ77V7ynO2ulREBScvDCGv/p+Of7vt8j3tR9dxWxR8jwXC5lHO/0d2duD7708il+5o902fn/+vXfjXT3ltu3qH93Xg31vXtfwAfHNYJdmrpcEfHdgssL/HNnTg/t71rgeEJdKMk4NpKvq7e5JNuWAuFiScHpgvKq/XT0drge9jdbLlwT8bxu9/D89a1wPiCVJxYn+URx8ptJm9/WtdT1oadRWG7XHRuW80favaQRnXx3H0Hi+rv2Andxmf2bWtV3ZR3d04bFzA/j//avbURBVfOF7l6py+8uTBRx77lJF++EAi1P9I3j3L6yviInHHrob79zcWmWbj+/tASEaHv0fP6to5/JkAe/qTsHv99nayl++uw/prFDR/6d3d+NbL1zDB3/1joq9o3lf+Ifv3FyRF1ltzrp/NcerL7//LbhelD3Z7FLbzY2204WwGLIriobvDI5heLbkGB/NfZn37F78gbneb711I8YyQkU/B+7bgr/7v69jtigZeZ5+nmCX7zWqD0lScfLCmLGGNrSG8KF3bK44zzC/5wM+/MkDd0EhBJ/9x1cr1ti6VTy+/cIb2L5pTYVfPLS7G2tXFfCvNrcviszL3f7ccPK/j+7owktvTGPn1hS+eU7f97xo62sP3LcFQdaHv3j2Fdvnh3Z342dXp/ALG9sqfJO5zP6dXYjM2eV//ufL4PxMlS/703fdhZKsVfjqI3t74GMIHjsxWGGret5sPtNx2heu5Pm7kdCvlbDw+nQBB556Cbv61uGLZ4eM34KsAQAEWUOupOKxEwOuZQ489RIGxzLoH87g+JnKMg9u68RUQTIW64PbOo3XALCrb50RwK3t5Uqq4Tj1sgefqZRluihhqiC59iHIGvqHMzjw1Et45J7bjSBjlc1a1irT69MFQ2du9fWyjc6FPiands0yWHVmlk2fi+libd3YzZ1T2wsZJ4VCKTM4lgHL+IykASivq089M4B0VnRci69PFzA4lqnym4+dGED/aPU61f03UPahh08PVvlBq0/44tkhPHLP7UZiq3/+he9dwlRBcmy/ll9w8l12fk2X1avPcWq7fziDXX3rEA4GKuKJm870+GLXn9sYVgp29nPsuUu4MlWwtbvjZ4bw88lCxTzbxUndbuzaHprIe46zdlwYy+DgyQFH+R7c1lnXXCxkHu30d/CZAXzgrZsc4/fHvjnfttP6HRzL1Oy7GeNZjlxKF6r8z8GTA7iUdh/PhXTWtt6FdLYpcg6kc7b9DaRzTan3soNeXq6hl/7RjHGwYNR7puz/3GjUVhu1x0blvNH2//p0wcij65HBTm6zPzPr2q6sHqsmcqJx2KA/03N7/WDW3P50USrnAaeqY6ydbX7qmQEMXxeq2hmayBvy2dnKa5P5qv4/faqcg1j3jubYb82LrDZn3b9ax+3VZpfabm60nS6ExZB9cCyDoYm8a3w092XOVfWybv7AXO/yVKGqn2PPXTLWlvlMwynfa1Qfer5Skc9azjOsa2+6KBkHw/pnx88M4bXJAvZtW1/lFw+fGkSupC6azCsZJ//7xbND+MBbN+HQyUFbWzL72mPPXcJ0UXJ8fvjUIPZtW1/lm8xljp8ZMs6kHtzWaevLpgpSla8++MwAeL/fMW82n+k47QspjUEPhy2MZ8uBnmFQ8dtMQVRqlhFkDWMZARqpLsMwMD7X35vru7Wn920ta/6tkfkfpz6A+eclU5tW2axlrTJN5ARDZ2719bL1YJ4L63jcZLDqzKqDWvrXx2s3d05tL2ScFAqlzFhGwExBtl1XGnH2jRM5wXE9ph18g/7XFXqbVj9oV6ckKY6yObVvltEOJ99l59fcxl9P27ourfFEf+6mM7v+3MawUnCyHze705/pOMUor3ZTb+xMZ0XXGKXL5nUuFjKPTvq7XpBrxm+3+ulM4zZ0M9ilmfG5+TYjyOU/5WxGvUZZajkbrefk58az7vbRqK02ao+Nynmj7X88KzS0H3CS2+zPdF27lXXayzjJpBFU5AHmZ042Zhf7NQJDPjtbqRUnzHtHHScfb7Y56/7VS592NrvUdnOj7XQhLIbsdvNt147el7ONuueBJVFx7Me8tqznCvWMxU0facsa8nL24bZWp/L2a7IgKYsm80rGzf/Ozu2znGzJbA9u+xtB1jCVs58Haxt6vlzPPBckpeozXZ5aZ3Arff5uJPRw2EJHnAcfKKvF+lsnwvtrluEDPqQSIbCMfRnz50717doz920tq/9mmfkftz705+Gg31U2p8/4gA/tMb5CZ7XK1oO5XbvxuMmgP0slQrY68KIbp7lzarvRcVIolDKpRAgtkYDtutL/OshpzTmtx5SDbyCk8r3VD9rVCXP2/tf6l0t27Tv5BSff5ebX7MrW07Yur1M8SbrozK4/tzGsFJzsx83ufAwq5tkpRnm1m3pjZzIedI1Rumxe52Ih8+ikv1WRQM347VY/mWjchm4GuzTTYZpvHT7gQ0c82JR6jbLUcjZazyk2dMTd7aNRW23UHhuV80bbf0ecb2g/4CS32Z/punYr67SXcZLJx6AqD9CfOdmYXez3MTDks7MVp/5Dc3HCunc0l7G+N9uc3f61Vp92NrvUdnOj7XQhLIbsbvNtbkfvy9lG3fPAcNDv2I95bel5nlO+54abPpIOa8jtvdtaXRO1by/C+RdN5pWMm//V91lOtmS2B7f9DR/wYU3Mfh6sbZjzZa/zHOH8VZ+Z5XHLf1f6/N1I6OGwhY2tERx76G6cOj+CR3d0Gb/NBhjjWRzd1+Na5thDd6M7FUdvZwL7d1aWefqFYbRGOOzfOf9efw0Ap86P4Oi+Htv2YjyLQ7u7K8oe2VspS0uYQ2uEc+2DD/jQ25nAsYfuxhPPX8ahXd22slnLWmXa2BoxdOZWXy/b6FzoY3Jq1yyDVWdm2fS5aAnX1o3d3Dm1vZBxUiiUMt2pOFSi4fCe7op19fjeHiTjQce1uLE1gu5UvMpvHt3Xg9611b7r6L4enO4fAVD2oYd2dVf5QatPeHRHF554/jKO7Kns46P3bkFbhHNsv5ZfcPJddn5Nl9Wrz3Fqu68zgVPnR1AU5Ip4osveZ6OzR3d04XT/iG1/bmNYKdjZz4H7tmBTW8TW7vbv7MIdayIV82wXJ3W7sWu7qz3qOc7a0ZtK4MieHkf5vv3icF1zsZB5tNPfkb09+IcfX3GM359/73zbTuu3O5Wo2XczxrMc2ZKMVPmfI3t6sCXpPp7eZNy2Xm8y3hQ5e5Ix2/56krGm1HuTg17eVEsvaxM4srfaZvvWuttco7baqD02KueNtv+NrREjj65HBju5zf7MrGu7snqsWhML4qP3brHN7Q/ct6Wq/dYwV84DdlfHWDvbfHxvDzpX8VXtdLVHDfnsbOWONdGq/j+9uxtfe/5y1d7RHPuteZHV5qz7V+u4vdrsUtvNjbbThbAYsnen4tjcHnWNj+a+zLmqXtbNH5jrbWqLVPVz4L4txtrS145bvteoPvR8pSKftZxnWNdeS5jDJ379zqo1tnlNBP/zxWtVfvHQ7m7EQuyiybyScfK/j+7own//8RUc3tNta0tmX3vgvi1oDXOOzw/t7sb/fPFalW8yl9m/swttEQ5tEQ7ffnHY1pe1RrgqX31kbw8ERXHMm81nOk77QkpjMISQ2qVuUrZv307OnTtX9bl+a+VMQUSA9UFSNcdbX2cKImI8BwJSVUa/cVa/qVdWVcSCARRlFakED0KAiZyIoqSU2yTAZF5Ae4zH+tXl2xgncuX35vbemC1gPCOWb5dPhLA1GcdwplQhbyjAQpQ1KESDohJIilbVh/lm9GxJgqKV/0yjc3UI4QCLybyEounmR72sVSazziZyApLxyrEt5OZI81zwc2MSFBWSolW1a5bBqjOzbKoGzBbL7RVE1Vb/5huNrXNnnV8nnZhY8DeiO9kqhbKILAs7VRQNP5/K4npRxWSufCt4KMBiuiAixPkhKfZrUa87OJZBOiMgmeDRnUoYl9aY16nuX8ezAsIci3IcZCDIMnwMi4lc+SblQIBBXlAR5ljIqoaWSBCdiRBeTmeRzgpoCXPICDLWRINQNA05oezvNrTY+28n3PyI+RZlXVaGYapiTT1tAzD8aiTIIldSjXjSvbZSZ3q/+vid+vPoCxeDptmpomgYHM1gLCsgEvQj6GcQ5sq3NJdkBSHOj2xJQZhjwfkZBFgfVA3ICzJus8RJq97Wrw7j6kwR12YKCHP+iluX7ebGqx71279nizJWhwPIiwqiQT9CHIucoNR98/ZC5tG6/rZ2lHOT6YKIgM8HQVGhqASCrGJjawS3W25jd1q/C2EJ7dKOBXVkZ6fXSwIupct5SUc8iC3JiOtldDqlkowL6axRrzcZb8pldDrFkoSBdM7orycZc71UbqH18iUBL5v08qZkxPUyOh1JUtE/mjFuqe9bm3C95E2nUVtt1B4blXMpclS3uG/eA9WzHzDL3RYJQlBUjMyWbHWtaQRXpgq4NlNAhPNDUlUk4yH4WQZT+fK+yBwvgXJuP5kTcb0kI84HEAmyEGQVq8NB+FkgnamW17qGEiEWV2cEtIQCmCnKCHEsWsIB3NkRr5DP1i9eL2I0IyAvKmiLBsH6gESIq9hbXJ0uYDRTQl5Q0RbjEGAZSArBTEFCRzxoa3PW/avdvtWLzS6131zJe6nF0JWiaHhlPIvZogxBVrHJJj6a+8qUJCgqwURO9OQP9DUylS+BY1nkRRUFSUEqwSPOB5Cey1f0845a+V6j+tDzlfGsiGSCR2skgPGchGxJRphjEQv6wfiAfElBwO9DTpQR4fxgfQym8hKiQT+iQT9ERUFbNITbVoVwMZ3FSKaEtkgQHYkgblu9uDI3wLKxU7MfKYgqWiMcNBAEWR98DIO8pEBUVIQCfkzmxPJfDXI+jMwKaItykDUNJVFFkGNREBRsaI3A72Pw+nQ5j00mglBUoCCVv6ZiYs43sj5gKi8jEmTB+1msDpf3bCOzJXTEeYQ5BuM5GQVRwdoEjxgfwFRBBAPG8G9bO+IYzZYq/LQ1b07GeSgqQTpbtuvCAs+cbjEcFUQPh+mBG6X5LJtAQaG4QO2UshKgdkpZKTTt0I1CWUSonVJWAjT2U1YC1E4pKwFHO6VfK0GhUCgUCoVCoVAoFAqFQqFQKLcg9HCYQqFQKBQKhUKhUCgUCoVCoVBuQejhMIVCoVAoFAqFQqFQKBQKhUKh3ILUPBxmGGYLwzBnGIYZmHvfxzDMY80XjUKhUCgUCoVCoVAoFAqFQqFQKM3C76HM3wD4BICvAgAhpJ9hmK8DONpMwZYD+g2zYxkBnatDiHIsJnJS+Vb3VWF0p+JVN+ZemykgU5RRUlTkBQWrwhw0QhDmWIiyBkFRIcoaNrQ636ZovbV0c1sEYBhM5EQUJAUbWiLY0FK+rXG6IIIz3Ui7fnX5c/1GY+ut93bySYqGZKK67OvTBeRFGaKsYTwnIhXn0Tt3I6r5JvtUgoeqARM5oeI24DdmCxjPiIa+tnbEMJotYTovQVBUaBpBnA9A0jSEAmX9KESDohJbHZlvPdb1oD+v9cwsKyHARE4EgQa/j0VWkBDny/MU9PuM21rNt/z6fEyVPfB+FpN5se7b4CmUWwn9duJ0VkQyHkRvKgGenw891vWpqATXZorgAz74/QxY+NAa5bC+pXodphIhw6+MZ0UURAVtsSBERUVrJIjORAgXx7MYywhYEw0i4GdACFCU1ApfICkqwpwf0wUJfMCHaNCP1iiHVGy+fioRQncqDk0j6B/NYKYoYXUogOtFGXzAh9URDopKkBVkiIpWvkVX06BqwGRORGuUQzIRhKwA41kBQb8PGUFCa4S3jSW6Trz6F68+cO0qHtcLMsay8/obzpQwni3f/JsTZIyaxuubu5l4PFu+xZn1AWMZ+/hiJ3MjY7lRKIqGV9JZZEUZBUFFNORHSVbQFg6iIKuYzktoi3II+VnkpfLtyQVJxVROQirBY1U4YNwevn51GFdnirg6U0CE81fcsqzrwhqv9ffTBRGhAAtVJSgp5X7XxIJIJoLQNGAiOx9XW6J+pK+LmCpISPB+JMIBFKWy/S9E1zdy3haz75Vkf16o5U+dKJVkXEhnMT53m3hvMo5QKFCzXrEkYSCdM+r1JGMIh7ia9bIlAa+kC0a9u5IRxEN8zXqSpKJ/NIN0VqjIOWuRKwm4aOpvazKCmIf+Gh1fo/PQaH+Nzt/NjNva1p9Z90j6/qSWT7BrWxBlDKRzmC5IaI1wmC3KWB0OYFWIxVROQTDgQ1GWEQoEIMkaIrwfgqxgpiCjNcqhPcZhuiBjtighzgcwlReNnGdiLkcIBViM50SsjfNQNILRTAlt0SAkRUE46IeqArMlGQk+gKKkYL0lzl+ZKuDqTAEJPoAAy6BQ57gb1fetzGLopdm61TRS3pNnRUzmRLTFgojzLCayIhKhAGSVYDwnojXCIcyxKMkK1kRDjucUXsYyXRDB+XyYKUoIz+VAa+PVOTkApDMCwpwfsaAfeUlBUVIR4/0IBVgIsoqirGBViIMga5gulPOwCMdC0zQkwkFcL8oYywhojXKQFBWpRLhK9pvZfu3GBlSvdwC4MlXAZL4Ev4/FVF5EhGPREuEQ5vyYmss9i6KKTElGIhwAIQR5UUGMDyBTlBHhWfhZBn7GhxDnQ06YKxsKIBFikSmpZRub82c5QUFBUhAPBSDIKqJBP2RNQ66kIh4KIBpkUZJVcCyLkizDBx8KFt/mNFb9/GmmWO3nveyZblZ7WCheDofDhJB/YZgKhSlNkmfZoCgaTpwfwWMnBrA6zOGj926GShgcPjUIQdbAB3w4uq8H+968Dn6/D5pGcPbVcczkRaiEwVf++TU8vH09njx3DR+8ZxMYBihIKo6fGTLqH3vobjzQnawwRkXR8J3BMQzPlnD8zBBWhzn8wTtur6i7oTWEj+zowpfODuHh7evxxbOVnz92YqCqDwC28ul1rWWfHUzjxM+uYefWFA6dnB/zkb092NOTwtmhSRx46iWsDnN45G0bKsb15fe/BQGWweh10dDXhtYQPnb/nbhekFCQVHzjp9eq9AM460iXf2g8X/X8/q0d+P7QhOOz714cN2TVdXnmYhrv3rYeX/nB/DyZf1v1cu+d7Th5YdSwB+uY7eaSQrnVEQQFJy+M4eDJeZ90ZE8P9vSmwPN+aBrBs4NpR1+yf2cXInMHA2tX5/H2O9YY69DsV0bm/KVe76P3bsFzL4/hoV/cgIPPzPd9eE83vnnuGkaui4Yv0H2Rec3v39mFro4ofnJltqL+43t7EA/58ef/+2KV7/3je7cgnREq5Di8pxv/7/dfw9Xpku37R3d04clzL+MjO7oqYomuE6/+RY8/tXzglvYofvOXN1TEsSN7e/BX/zQESSFV+v/se/rgY3z42DdfqtDN1350FbNFqSpmWGU2973cfaUeeydyIj77j68a8n78/juRiSr4k29fMD47tLsba2IcRmZzOGiKj7puOD9TFYv/9F13IRz0V3x2dF8PvnR2yLCHo/t68I1/uYrdfesQ4nxVOceRPT2I8iwOPHXesLsPv7OrYn3t39mFaNCPv/3heXzyga0N6boRG1wsFrPvGzmOZlDLnzpRKsk4NZCuqre7J+l6wFgsSTg9MF5Vb1dPh+uBZrYk4NmByap6D/SscT0gliQVJ/pHK3zukb092Ne31vWAOFcS8B2b/t7Vs8b1gLjR8TU6D4321+j83cy4rW2gHI8+8+xF23ye8zP4o6//zNEn2LX9tQ9ux+tTQsUclOP3NfzhOzfj2QtjuDxdwIfevhmHT79oGy+P7OnGU+euYcddSXzx7JBtPD60uxuRoA+DY9mKvdfhPd3gAzKOPXfJdkzWvY7dvkxSSMO+8GbzpYvFYuil2brVNIL/89pExZ5ct7VkLIBL4/mKPObQ7m4keD8+94+v4oO/ekdDY7Fbe4/9xlYE/Sw+ZcnJ9Zx4Q2sIH3rH5goZP727G9964Roe+oXbkM5I1fInOLw6XqiQ/9EdXfizEwMV+c/NbL92Y3Na75yfwVe+/xoe2r6+KneN8X5wPgbXBQXHnrtkPDtw3xYEWR/+4tmfVZWP8X588ukLRj76h+/cbPgtu/n8kwfugqhqFe3v39mFcIDFqf4RvHvbehw+PejJN+t+zm4P52XPdLPaw2Lg5TuHpxiGuQMAAQCGYd4DYKxWJYZhbmMY5p8YhnmZYZhBhmH2z33ewjDMcwzDDM39Xj33+V0Mw/yIYRiRYZiPm9rhGYb5F4Zhzs+1c7hGv+9mGIYwDLPdw9gcGRzLGJu4B7d1IswFDAMHAEHW8NiJAQyOZQCU/3WmfzhjlNvVtw5fPDuEXX3rMF2UMFWQjECt1z/w1Et4fbpQ1e/QxPwG/8FtnVV1d/Wtw2MnBow+rJ/b9eEkn1PZA0+9hA+8dZOxyPUyB58ZwIWxjLGgHtzWWTWu/uEMciW1Ql+7+tbhtYm8MRY7/bjpSJff7vngWMb1mVlWvY9H7rkdh09XzpP5t7Wd/tFKe/AylxTKrc6FsYyxmQLmfMjJsg8BYPgap3V1/MyQ4Rv6hzMV6xCY9yvWel/43iU8cs/txiGD/vmhk4N45J7bK3yB3Zo/fmYIHOurqv+pZwYgK8TW916ZKlTJcehk2cc4vdd9jjWW6DrRy9XyL7X8o97e7739jqo4dvCZciyx0//QRN44GDbr5sFtnbYxw61vr2O5UeixVz8YBsryfu67r+LKVKHis8OnBsv2YYmPum7sYvFUQar6TI/j5veP3HM7pouSbc5x8OQANA0VdmddX8fPDGEyL2JX37qGdd2IDS4Wi9n3jRxHM6jlTx3rpbP29dJZ13oD6ZxtvYF0zrXeK+mCbb1X0u567x/NVPncg88MoH/UfXwXHfq7WKO/RsfX6Dw03F+D83cz47a29WeO+fxwxtUn2LWtakzVHOjx+9DJQfz2r27Crr51xsGGXsYcLw/O5R+6THbx+PCpQawKcVV7r0MnB/HzyYLjmKx7Hbt92UJ84c3mSxeLxdBLs3X7+nShak+u21o4yFXlMYdPDUIjwCP33N7wWOzsdCInGgfD+mfmnHhX37oqGT99qrxmwsHqfOjwqUGwTHUepq9Ls+w3s/3ajc1pvfcPZ8p7I5vcdSInIhwMGAe3+rNjz13CdFGyLf/zyfncWPeF5vfWOZsuSlXtHz8zhOmiZJzLePXNup9zO8+qR2c3iz0sBl4Ohz+M8ldK3MUwzAiAPwbwIQ/1FAAfI4S8CcBbAXyYYZg3AfgPAM4QQroAnJl7DwAzAB4F8DlLOyKAHYSQNwO4G8ADDMO81a5DhmFiAPYD+IkH+VwZywiG0TAMUBAV472OIGtIZwQA5T8T1sh8OYaB8Vsj5R+7+hM5oapfc1m9vrmuuW27z+36cJLPqawga5gtyPZjzooV8lnLmPsxy2bWg51+3HSky2/33Koz6zM7XZZs5slNL+ms4Dpmu7mkUG51zL5CR5A1jGdFADB8DeC8rsz+wbwO9TpOa78k2fvskqRU1HPqd8bB/xXm6nuVw/xHN07vrbGkXv9Syz/qn5cc4hjDOPtytzFZY4Zb317HcqNwiyMaQdVnTvGxUV3q70uSYhtD9ecFaf4Pt9zWjP6sEV03YoOLxWL2fSPH0Qxq+VMnxldIPat/n6/nPl9LL+fK0OfNjNva1p+5+Ue7em5tT+bs50Dv43pRduzPHC/NeYlTPHaKLWa/bn1m3et4jT9efeHN5ksXi8XQS7N1O54VHPOJiZx93wVJMWy1kbE0kgM52XZJUhzld8vDzLLfzPZrNza3XNbJ77jlnXY+U9+X6Xg5k2pELiffXOvcptae6Wa1h8XAy+EwIYTcC2ANgLsIIb/qpR4hZIwQ8uLc6xyAiwDWAdgL4Im5Yk8A2DdXZoIQ8lMAsrVzQkh+7m1g7sdipgaPA/gMgAXPbioRAh+YH2aE91e8BwA+4EMyUf6TtY44D5apLKf/Zpnyj1399ljln7ylEqGqsk51zb+tn1v7cJPPriwf8KElErAfczxY8bm1jLUf8+fmsVj146YjXX6753Y6Mz+z02U4WK0HN72k5nTiNGa7uaRQbnWsvgIor5WOeBAADF9jfmYt62Ng/FjXIeDsN8Kcvc8Ocf6qenblnPxfZK6+VzkIqf3eGkvq9S/u/nG+PbPfs5Op3jFZY4Zb317HcqNwiyPWvzLjAz6sdrCPRnWpvw9zfscYarY/82d28up21YiuG7HBxWIx+76R42gGtfypEx0rpJ6dfy/Xc5+vpZZzpczDzYzb2jY/8+rPzT7Bru01Mfs50P3sqnDAsT9zTDDnJU7x2Cm26HJ7ibVe449XX3iz+dLFYjH00mzddsR5x3yiPWbfd4TzIzRnq42OpdEcyPo8zPkd5XfLw8yy38z2azc2t1zWye/4XPJOO5+p78usn7u9b0QuN9/s5udr7ZluVntYDLwcDj8NAISQwtwhLwB8q55OGIbZCOAtKP+P3g5CiP61FGkAHR7qswzDvARgAsBzhJCq/xnMMMw2ALcRQv5XPbI50Z2K4+i+HvABH55+YRhFUcah3d0Vhnh0Xw+6UwkAwMbWCHo7E0a5U+dH8OiOLpw6P4KWMIfWCIf9O7sq6h976G7jC8LN/W5ujxpln35huKruqfMjOLqvx+jD+rldH07yOZU99tDd+O8/vjL3PVfzZY7s7UFvKoFjD91tyGcdV29nAjGerdDXqfMjuKM9aozFTj9uOtLlt3venYq7PjPLqvfxxPOXcWhX5TyZf1vb6V2bqLAHL3NJodzq9KYSOLKn0icd2VP2IQAMX+O0rvbv7EJbhENbhENfZ6JiHQLzfsVa76P3bsETz1/Gkb2VfR/e042vPX+5whfYrfn9O7sgqVpV/cf39iDgZ2x978a2SJUch/d043T/iOP7R3d04XT/SFUs0XWil6vlX9z947y//psf/Lwqjh3Z24PT/SO2+t/cHsXn33t3lW6+/eKwbcxw69vrWG4Ueuz9xK/fWSHvx++/E5vaIhWfHdrdXbYPS3zUdWMXi1sjXNVnR/f1VNjD0X09eOL5y2gJc7Y5x5E9PfD55hPhU+dHqtbX/p1dWBMN4nT/SMO6bsQGF4vF7PtGjqMZ1PKnjvWScft6ybhrvZ5kzLZeTzLmWu+uZMS23l1Jd733rk1U+dwje3vQt9Z9fFsd+ttao79Gx9foPDTcX4PzdzPjtrb1Z075fF9nwtUn2LXN+kjVHOjx+/Cebvz9D6/g1PkRHNplHxPKc9aNJ56/bMhkF48P7e7G9ZJUtfc6vKcbd6yJOI6p28O+bCG+8GbzpYvFYuil2brd2Bqp2pPrtlYUpao85tDubvgY4GvPX254LHZ2uiYWxOM2ObmeA506P1Il46d3l9dMUajOhw7t7oZKqvMwfV2aZb+Z7ddubE7rva8zUd4b2eSu7bEgioKMA/dtqXh24L4taA1ztuXvWDOfG586P1Lht+zmsyXMVbW/f2cXWsOccS7j1Tfrfs7tPKsend0s9rAYMITY/ydchmHuAtAN4C8BfML0KA7gE4SQbk8dMEwUwD8D+I+EkG8zDHOdELLK9HyWELLa9P7TAPKEEOvXS4BhmFUA/ieAjxBCBkyf+wCcBfDbhJDXGYb5PoCPE0LO2bTx7wD8OwBYv379L1y9etVRdkXRMDiWQTojYN3qEKIci4mcVL4lPBFC99pE1Q3z12YKyBRllBQVebF8uyYBQSjAQpQ1CIoKSdEcb2HU+31lPIvZogxBVnFHWwQMw2AiJxq3025oKd9qPlMQETDd0Kjfdj6RK98sb729104+WdUcb/otiOU/2RjPiUjGefTN3RytP5/IlW+4VzVgMj/fJ4DyzagZ0dDX1mQco9kSpvMSBEUFIQSxYACSphn6UYgGRSW2OtLlH8+Ktrf0uj0zy0oIMJETAWhgfSyygoQ4X54njvVBUjXbWy+t9sD7WUwVxCo929DQt5vXY6sUyiLQFDvVb3U3blm33OpuXZ+KSvDGbBGc32fciNsa5bC+pXodJhM8tnaU/Yq+9lsjHCRVQ0skiM7E/M3IbdEggn4GGgGKkopUYt4XyKqKUMCPmYKEYMCHKOdHa4xDKlaur/fVnUpA0wj6RzOYKUpYHQrgelFGcC7pUTSCrCBDlDV0JIJQNQJVA6byIlrCHJKrgpAVYCInIMD6kBMktESC6E5VxxJdJx78i1HHiw9MJXhcL8hIZ+f1N5wpYSInoCPGIyeUb33Wx+vzMUbdNVEerK/859928cVO5kbGUsvkGqrkwZ8qioZX0llkRRkFQUWU90NQFLSEgyjKKmbyElqjHHg/i6IkIxoMoCirmMpLSMZ5rA4HMJkvx4T1q8O4OlPEtZmCcVN356rK+GyN1/r7mYIIPsBCVQlKiorpvIQ1sSCSiSA0DZjIluPq2kQIrbEA0tdFTBckxHg/VoUCKMkqWiLBBem6CfN2Q/q+keNAA7a6UH/qRKkk40I6O18vGfd0mVmxJGEgnTPq9SRjrpen6WRLAl5JF4x6dyUjrpfR6UiSiv7RjHGDuJ5z1iJXEnDR1N/WZMT1MrqFjq/ReWi0v0bnzyOLbqdLgdva1p9Z90j6/qSWT7BrWxBlDKRzmClIaAlzmC3JWB0OYFWIxVReAef3QZBl8IEAJEVDhGMhKCpmijJaIxzaYxymCzJmixLifADTeRHJRDnnmciJaIlwCHMsxnMiUnEeqkYwmimhLRIs5ygcC1UDrpdkxPmAbZy/MlXAtZkC4nwAAZZBoc5xN6rvJWJZ7qUWQy/N1q2mkfKePCtiMidiTTSIKM9iMiciEQpAttigICtoi4Yczym8jGWmICLg82GmKBk50Np4dU5OAKQzIsIci1jQj7ykoCiW869woLyGSrKKRCgAQdYwUyjnYeEAC0I0JMJBXC+Wc9qWMAdJVZFKhKtkX0L7XXI7tRsbUL3eAeDKVAFT+RJYH4vpvIgQx6IlwiHC+TE9l3sWJRWZooxEOABCCAqSgmgwgExRRiTIgmUZcD4feM6HnKAiU5KRCAWQCLHIllRM5ES0RTmEAixyooKCqCIe8kOUVYSDfqgqQVZQEA8FEA2yKMkqOJ8PgqKAgQ8Fi29zGqt+/jRbrPbzXvZMN9if3WicD61cDof3ovyVD3sAnDQ9ygH4BiHk+Zq9MkwAwGkA/0gIOTb32asA3kkIGWMYJgXg+4SQO011Pg2Hw+G55wcBFM3PGYZJAPg5AP3rJ5Iof4fxHrsDYp3t27eTc+ccH1Moi8WCvQ21VcoSQO2UshKgdkpZKSzIVqmdUpYIaqeUlQCN/ZSVALVTykrA0U4d/5mbEPIMgGcYhnkbIeRHdffIMAyA/wLgon4wPMdJAP8WwH+a+/1MjXbWAJAJIdcZhgkBuA/l7xU2y5oB0Gaq8304/M9hCoVCoVAoFAqFQqFQKBQKhUKhuBwOm/gZwzAfRvkrJoy/0SKEfLBGvV8B8G8AXJj7vmAA+FOUD4WfYhjmdwFcBfAQADAMkwRwDuWvrdAYhvljAG8CkALwBMMwLMrfkfwUIeT0XJ0jAM4RQsz/s5lCoVAoFAqFQqFQKBQKhUKhUCg18HI4/N8AvALg1wEcAfABABdrVSKE/BDO/2V5p035NIBOm7L9KF9mZ9fHQYfP31lLPgqFQqFQKBQKhUKhUCgUCoVCuZXx1S6CzYSQTwEoEEKeAPAbAH65uWJRKBQKhUKhUCgUCoVCoVAoFAqlmXj5n8Py3O/rDMP0AEgDaG+eSMsL/TZD/ebkRm8zbLQdc71Uonwr40TOuQ1rP/rt59Z+a8nj9FzTCK7NlG88JdDA+/3IiQoEWcXmtgg0MBXyAfDcj3l8Tq+t7U4XRHCmGyrN4127isf1goyxrIBUIoTuVBx+v/u/h0iSipfTWWQFGYKsYVNbBHesiXrSDYVCqcZuvQDOfsFcvj3Gw8cAV6YLiMzddty5qrzG3dZ+mPNDUlW0RoKOPm/96jCuzhRxdWa+7fUtZdl0H1cQFayJBSEpGjKCjA0tEWxoqazXHuVQkFUMz5YMP+PzMQ3510b01ay5ao/xYH3AWMZ5DIaeJAUbLDcLr0Q/qSgaXh7LYCwrIMr5EeX9CPoZZOZuX26PBxFkAY0waItxkJXa8dhNR4qi4ZXxLGaLMgRZxcbWCAIsU6FzYGnmvtl4sQdF0TA4lsFYxnvMvtUolEQMpvMYz4roiAfRnYwiEgrWrCdJKvpHM0hnBaTiPHrXJsBxbM16i5G7LoXdFksSBtI5Qy89yRjCIa5mvUb10iiN9icICi6MZZDOikjGg+hNJcDztbdwK9EPA97l1stZ8wG9vNWnbO2IYThT8hx7rW2siQbh8wGJEOdpP6U/S2cE8AEfJFVDTlCwsSUCUZ3PG7Z2xDCaLWEiJyJTkhHnA0a+M3y9iPGsCNZHQAiD8ZyItiiHkJ9FIhwwciKn3Iey/NE0gitThap81Gn+FnNd15uPuq1Dp7MHp7MIwOQTMwLa40GsCrEYz0oIBlhkSzKifACrw6yRh62JBaGoKni/HxoIWkIcSrKKdE5AnA+gICpYb8m1bga8nttMF0QEWR+m8hIiQXtbssv1J/PzPtR8ftK5OoRwgMVkXirnsavDYE15qnUvlUwEoajl3Lg9GkRJKfu51ggHQVEQDgTg8wE+xgeNaAiwPhRE1ciRN7Q4206j/q2e9bJSY6aZhY7By+HwXzMMsxrAp1C+TC4KwPbrHG42NI3g2cE0Djz1EgRZAx/w4dhDd+OB7mRdSm60HXO91WEOj7xtA46fGXJsw9rPhtYQPrKjC4+dGKioc//WDnz34rijPE7y3r+1A98fmsDQeB5nLqbxgV/eiHQ2g+Nnhmzl+/L73wJJIZ76Mdd3em1t9zPPXsTD29fji2eHqsa7pT2K3/zlDTh8atCod3RfD/a9eZ3jZlOSVDx7MY2R2VJFf59/7914V4+7buq1CQrlVsBpvXB+Bn/09Z9VrSEAVeX37+zC1350FbNFCft3dqFzdQhPPH8FO+5KGmtfX99fOjuEq9Ml8AEfHt3RhSfPXcMnH9hq6/Os5ffv7MKb1sYgqwRD4/kKH3Dgvi34u//7Ojg/U+VT9+/sQoRj8Z//+TJmixI++54++BgfPvbN+vyr0/hr+dFmzpVZ99YxnH11vEpPbuNY7n5SUTScOD9SMbdffv9bMJ2XcOjkfBw5vKcbq0Isfj5ZwKeeGXCNx2460jSC7wyOYdgSb3Rbmy1KSzb3zcZL3LTTf62YfatRKIn4XwMTOHhyXkdH9vTgN3raXQ+IJUnFif5RHDTZ65G9PdjXt9b1YHIxctelsNtiScLpgfEqvezq6XA9IG5UL43SaH+CoODkhbGq8e3pTbkeEK/UfNWr3Ho5615AL3/vne04eWHU8CkbWkP48K91Vei/VsyytsEHfDi0qxtPv3gNH/zVO1z3U3ZtWvMZ/fVfvqcPkzkRn/3HVytiwYbWMC5PFvCza9PYuTVVEYsO7e4GyxBc4DL43Hdftc19lvtcU5xzr66OKHbc2WH7j86Lta7rzUfd1qHT2YPTWcQD3cly3Lf6xD3dYBjgU8+UbX37hgQe2r6hwv/pa3DHXUk8ee4aPvDLGxBkffijZ6v3FTeD/deac7MvfP8vbcAXvnfJ0Zbs2jpw3xYEWR/+4tlXKs5PVoc5/ME7bkdBUj3tiTa0hvChd2yuOHsx+7nyvA3h3dvW459eHcO7etYhnRWMtu1sxW1v52V+61kvKzVmmlmMMdTMuAkhf0sImSWE/DMh5HZCSDsh5CsLln4F8Pp0wVAuAAiyhgNPvYTXpwtL0o653oPbOo3F49SGtZ9dfeuMBWauMziWcZXHSd7BsQz6h8uHwY/cczuuTBcMmezk6x/23o+5vtNra7u7+tYZyaB1vL/39jsM56TXe+zEAAbHMo767h/N4LWJfFV/H/tmbd3UaxMUyq2A03rpH87YriG78sfPDOHBbZ3G66GJPB655/aKta+v711964z3Xzw7hF196xx9nrX88TNDyJVUw8eZyx577hIe3NZp61OPnxnCVEEyZByayBsHw9bxuenEafy1/Ggz58qse+sY7PTkNo7l7icHxzJVc8uxPmMzrn926OQg4qGgcTCsf24Xj910NDiWwZBNvNFtbSnnvtl4sQc7/deK2bcag+m8sUEGyjo6eHIAg+m8a73+0Yyx+TbqPTOA/lF33S5G7lpPvUYZSOds9TKQzrnWa1QvjdJofxfGMrbju1BjbaxEPwx4l1svZ90LGHnGaKVP2dW3rkr/tWKWtQ1B1nD49CAeuef2mvspL/mM/vq1ibxxMKyXPfbcJcgKwfEzQ/jAWzdVxaLDpwYR5gIYmsg75j7Lfa4pzrlX/3DGdv4Wc13Xm4+6rUOnswens4jXpwv2PvHkIEIBv/HZI/fcXuX/9DWo2/qx5y5huiitOF/nlVpzYfaF+sGwXs5qS3ZtmfVnPj95cFsnpgqS5z3Rrr51VWcvZj+nz9vh04P4wFs3VZwj6fXt8sCF+Ld61stKjZlmFmMMjofDDMMccPtZuPjLn/GsYChXR5A1TOSEJWnHXI9hULMNaz9OdcYy7vI4yTuWEaCR8uuSqBivnfoyP6/Vj7m+02tru9Zn5vclUbHtO51x1nk6K9Qls91zCoUyj9N60QiqPpvICY7lGaayrtP6Zpjq924+z1q+YPFr1rJOPlUjMNpaiA+xe1arvcXCi+7NY3CTayX6STsbmSnItuOYyoue4rGbjszx1Prcqy2tFLzYg9MadYvZtxrjWXu7G8+KrvXSDvofz3rPQc316sld66nXKEutl0ZptL90g+NbiX4Y8C63Xs4pLlv17baPcurTac5KklJzP+Ulptby9YW5fmYdYlFBUiryD3O7K2GuKe55st38Lea6rjcfdVuHOm57c2s7TuurICnGe6d8X1+DevtO+4qbgVpzUcsXmm2p1r7MrG+GcfZNdnsip/7NPq9k8mnWtmvVN7/3Or/1rJeVGjPNLMYY3P7ncGzuZzuAPwCwbu7nQwC21SvsSqQjzoMPVKqID/jQHuOXpB1rvVptOPVjfZ9KhFzbcmonlQiBZcqvw0G/8dqpL+vzWv14eW1t12m84aDf9lky4azzVJyvW2brcwqFMo/TerH+ZYu+hpzKE1JZ12l9E1L93s3nWctH+Gq/ZieD3Xj05wvxIXbParW3WHjRvXkMbnKtRD9pZyMtkYDtONqiQU/x2E1H5nhqfe7VllYKXuzBaY26xexbjY64vd11xN2/czjloP+OeH05qF6v3tzVa71GWWq9NEqj/SUbHN9K9MOAd7nN5Wx9h8c9kVvMcmojxPlr7qe8xNRavj4y149TLIpw/or8w9zuSphrinuebDd/i7mu681Ha61Dc7la79tjvKNPjHDzX5fjlO/ra1C3dad9xc1Arbmo5QvNtlRrX2bVdyN7Irey+rytjgQc23aqb37vdX7rWS8rNWaaWYwxOB4OE0IOE0IOA+gEsI0Q8jFCyMcA/AKA9Y2JvLLY2BrBsYfurlhwxx6627gkptntmOs9/cIw9u/scm3D2s+p8yM4uq+nqk53Ku4qj5O83ak4ejsT2L+zC088fxkbWyOGTHby9XYmPPdjru/02truqfMjeHRHl+14/+YHP8eh3d0V9Y7u60F3KuGo7961CdzRHq3q7/Pvra2bem2CQrkVcFovfZ0J2zVkV37/zi58+8Vh43VXexRPPH+5Yu3r6/t0/4jx/tEdXTjdP+Lo86zl9+/sQoxnDR9nLnvgvi349ovDtj51/84utEU4Q8bN7VF8/r31+1en8dfyo82cK7PurWOw05PbOJa7n+xOxavmVlI1HN5TGUcO7+lGtiTi8b3VsdUaj9101J2KY7NNvNFtbSnnvtl4sQc7/deK2bca3ckojuyp1NGRPT3oTkZd6/WuTeCIxV6P7O1B31p33S5G7lpPvUbpScZs9dKTjLnWa1QvjdJof72phO34emusjZXohwHvcuvlrHsBI89Ym6jwKafOj1Tpv1bMsrbBB8rfd/q15y/X3E95yWf013e0R/GJX7+zKhYE/Az27+zCf//xlapYdGh3N4qSjK72qGPus9znmuKce/V1JmznbzHXdb35qNs6dDp7cDqL2NgasfeJe7pRkhXjsyeev1zl//Q1qNv6gfu2oDXMrThf55Vac2H2hR+9d4urLdm1Zdaf+fzk6ReG0RrhPO+JTp0fqTp7Mfs5fd4O7erGP/z4SsU5kl7fLg9ciH+rZ72s1JhpZjHGwBBC3AswzKsA+ggh4tz7IIB+QsidDUu+TNi+fTs5d+6caxn9xr+JXPlGx0ZvLWy0HXO9ZJyHqgGTeec2rP3otzxa+60lj9Nz8+3rgIag34+cqECQVdzRFgEBUyEfAM/9mMfn9Nra7kxBRMB0Q7F5vKlE+bbNdFZAMsGjO5WoebGNJKl4OZ1FVij/CdemtgjuWBP1pBsXFvwt5l5slUJZIE2xU7v1Ajj7BXP5NVEePqZcNjx3g7N+M7fT2i/faMtCVjW0mG60tfONV2eKuDYz3/b6lrJsuo8rSgpaoxxkhSAryFg/d5Ouud6aKIeirGJktmT4GZ+Paci/NqKvxcSqe9ZX/lNopzGY9WS9HXqxYqcNTfOniqLh5bEM0lkRYY5FjPcj6GeQKamYnLslm/MDhDBoi3GQldrx2E1HiqLhlfEsZosyBFnFxtYIAixToXNgaea+2XixB0XRMDhWvrXca8xe5ixoouzstFASMZjOYzwroiMeRHcy6noZnY5+I7x+e3Xf2oSnS9cWI3ddCrstliQMpHOGXnqSMdfL6HQa1UujNNqfICi4MJYxxtebSrheRqfjcR4W3U4Xilf70ctZ8wG9vNWnbO2IYzhT8hx7zW2MZQS0RYPw+4B4iPO0nzLfGs/5fZBVDTlBwcaWCER1Pm/Y2hHHaLaEyZyI6yUZcT5g5DvD14sYz4rw+wg0wmAiJ6IlwiEcYJEIB4ycyCn3uYm4afdSmkZwZapQlY86zd9i+td681G3deh09uB0FgHM+8Ry3hPEqhCLiZwEzs8iW5IR5QNYHWaNPKwtGoSqqQj6/dBAsDrEQZBVpHMC4sEAipKC2yy51hKzZHspu33FTEEEx/owXZAcbcku15/Kz/vQtavmz0/WrQ4hHGAxmZfKul0dht+Up1r3UslEEIpazo3bIkEIiorh2RJaIxwERUEoEADrA3wMA0II/KwPBVE1cuQNLfa2sxD/Vs96WercpRksNO57ORz+MwAPAfifcx/tA/AkIeQvGhd7ebBcgwTlpuOmTWgoNxXUTikrAWqnlJXCsjt0o1BsoHZKWQnQ2E9ZCVA7pawEHO205j87E0L+I8Mw3wHwr+Y++h1CyM8WSzIKhUKhUCgUCoVCoVAoFAqFQqEsPbX/JgkAIeRFAC82WRYKhUKhUCgUCoVCoVAoFAqFQqEsESv6y9woFAqFQqFQKBQKhUKhUCgUCoXSGPRwmEKhUCgUCoVCoVAoFAqFQqFQbkHo4TCFQqFQKBQKhUKhUCgUCoVCodyC1PzOYYZhHgTwGQDtKN9sxwAghJB4k2VbVmgawevTBYxnBaQSPFQNmCmK4FgfipKKjjiPja0R+HyNX1Jp7qNWe5pGcG2mgOm8BEFRIcoaNrRGsKEljGuzRUNOQoCZQmWZTW3e5LQb80Su8vXaVTyuF2SMZQV0rg6B97OYzIu28usyj2dFSKqKeDCAojyvOwCexm8eu0I0KCrxPDY3HSuKhsGxDMYyAlKJELZ2xDCaLWE8K6IgKdjQUq1fXQ+LMf8Uys2Ikx/piPNYv3p+PelrSFE09I9mkM4KSMV59K5NwO/3GW20x3iwPmAsIzj6js5ECBfHsxVreThTcvUtXvyvJKll2TICkokgQhyLmbyEoJ9FQVKw3uIj3Pq6MlXA1ZkCIpwfHfEg1rd49x9eZNXLTBcq45Sdzu3q6r7azveZ63mNW/XEtxuJOQ6sCvsR8LFIZwVsaA2jKKmYzIlYEwtClBUEA35kBRlrojy6U3H4fIzjGM3jN9twezSIkqJiIicgznOQFA3JhDf9mp+FOT8kVUVrJLhsdUtZOIKg4MJYBumsiGQ8iN5UAjxf+/oQa37TnYrD72/e/w9ptL9Gx1coiRhM5zGeFdERD6I7GUUkFKxZr1iSMJDOGfV6kjGEQ1zNekYsMMUpjmObVq9RVorfXQzqjos+H2aKEsI2MVi33/GsgNZIEBpIlW9VFA2vjGcxW5ShaRrCnN/Y/7RGuDnb56GoBGPZEoJsZZ5wdaZYkQN0rirH2OmCiDjPIlNUMZETkUrwCAZ8uDZTRFs0CEVVwfn9Rqyw5jvNXtuUlY2e303kRGRKMuJ8AO2xIBimMq+ux0+Y/dptq0IIB/2Y8nAWkBVktIQ5KEQD0QiCfhY5UYEga2iLcijJCjiWxURORGuUQ8jPYjwnIBHmEOdZ3NFamdt7yW9vNZz8oqJoGBzNYCRTQjLOw88ymMpJiATn/SGAqhyTY1kwDIGkEEzlRaQSIawK+zF6vezvNI1gMi/ieklGKMAiEvTD72MwlReRCJVz3I54OQcezwmQFIKSpGBNLAhFm/ez5r7dcl8vezq7feOtbhdueLmQ7i8B7CaEXGy2MMsVTSN4djCNA0+9hNVhDo+8bQO+8dNreHj7enzx7BAEWQMf8OHYQ3fjge5kQwZn7qNWe5pGcPbVcYzOllCQVBw/U5ZhQ2sIH9nRhcdODGB1mMMfvON2AKgo41VOuzEfPzNU8XpLexS/+csbcPjUYMXndv3oMg+N52119+X3vwWSQmqO3zz2esfmpmNNIzhxfgSPnRgwdPmx++/EyGzJUb9u46VQKM5+xLqe9DX01X+zDeNZCQefmf/sL9/TB5bx4WPfnF+3+3d24Ws/uorZomTrO47s7cFf/dMQrk6XjPdP/fQqzl3N2K5VL/5XklSc6B+tkO3AfVsQZH34i2dfcRyTl7727+xCV0cUO+7sqOk/vMiql/nMsxerfO3RfT340tl53djV1X212b/Z1bt/awe+e3Hck9/2Gt9uJIqiVcQBfW6G0ln88h1tOHRy0Pj80R1dePJcOZY9fu5l/NGvdaE9zuH3/9uLVWMEYDvnug3P29HPKuq66deuTV2mTz6wddnplrJwBEHByQtjOHhy3j6P7OnBnt6U6wGqnV0f3deDfW9e15RDpEb7a3R8hZKI/zUwUVXvN3raXQ+IiyUJpwfGq+rt6ulwPSC2iwVH9vZgX99a14PeRus1ykrxu4vBQuOiOQZb9wN2vlXTCL4zOIbh2ZLtnubQ7m58d2AMb9vchn/4ydWK5xtaQ/ijX+vCp56pjDOdq0N44vkreOStG3BZIRXx5tDubvyPn1zFpYk8Du3qxld+8BquTpewoTWED/9aV4VNNXNtU1Y2en53ebKAY89dqrC/CMfiP//zZcwWpbr8hNmv1XMWYC5zZM+bEPCzSGeEis8f39uDL5tyefM6OLKnG0MTBfz7b/V7zr9vNZz84r13tuPkhVHH8wzdHwLAH339ZxV+8KU3prFza6rKP313YAw739QBUdHw2X98taKtZIKHLKv4sKmtv3iwF5M5scIOP37/nfhvP34dn3xgKzg/U9G3W+7rdZ+l59y3ul3UwkvkGL+VD4aB8r9c6Ab24LZOHD8zhF1964xADwCCrOHAUy/h9enCgvuo1d7r0wX0D2cwVZCMxQwAu/rWGU7xwW2dmCpIVWW8ymk3Zuvr33v7HTh8arDqc7t+dJmddNc/nPE0fvPY6x2bm44HxzKG7nRdvjaRd9VvI3qlUG4lnPwIULmegPIaypVUY5Ojf/baRN44GNY/O35mCA9u63T0HQefGcCuvnUV7x+553bjvXWtevG//aOZKtmOPXcJ00XJdUxe+jp+Zgj9wxlP/sOLrHoZO1/72IlK3djV1X11rXqDY979ttf4diOxxgF9bt7zi+uNRFj//Itn52PZrr51+NQzA8iVVNsxOs25bsNWO/KiX7s2dVmWo24pC+fCWMY4yATmfNvJAVwYy7jWs7Prx04MYLBGvUZptL+Gx5fO29YbTOdd6w2kc7b1BtI513p2seDgMwPoH3WXs9F6jbJS/O5isNC4aI7BdvZr9a2DYxkMze0R7No7fGoQv/2rm3DsuUtVz/V4Ye1/aCKPR+65Hasiwap4c/jUIH7v7XeUX58eNGLxrr51VTbVzLVNWdno+Z1+IAfM299UQTJyknr8hNmv1XMWYC4T5gK4MlWo+vxTllzevA4OnhzEaxP5uvLvWw0nv9g/mnE9z9D9Yf9wpsoPfuCtm2z902//6iZM5ETjYNjc1pWpAsLBQMXnV6YKVXb4ue++avhZa99uua/XfVYj9n0r4uVw+BzDME8yDPObDMM8qP80XbJlxHhWMAyMYcpGpv82I8gaJnLCgvuo1d54VoBGAI1UymCWiWFgW8arnHZjtr4uzf3ph/Vzu350mZ1051VO89jrHZubjscyQpUua+l3MeefQrkZcfIjdu8BoGDyKTpO65xhvD3X35ckpeK9ea168b9phzIamX/vxS849aURePIfXmTVyzjJY9WNta5XnVr9pl17XmVeDjiNZyonOurD/LtgsjG9zEROcBy/rk+rHemfuenXrc3lqFvKwkln7e1wPCu61nOyo3SmOTbSaH+Njm98ies5xYLxbK3xNVavUVaK310MFiMu6jHYyX7NvnUs476nEWQN14uy7XO3/kuSgpmCbPtcz2HMscOprWatbcrKxi2/0wgqchKvfiLtkudb23LqvyAqdefyjeTftxpOftHLnOnnLNbPZx380/WC7Gpb1vzYbb6dcmK33NfLPqsR+74V8XI4HAdQBHA/gN1zP7uaKdRyoyPOgw/Mq0p/bf5Mf98e4xelD7f2OuI8WAZgGXsZdNzK1JLTaczm1+Gg37GMtR9dZifdeZXTPPZ6x+am41Qi5FkmL+OlUCjufsTufYT3e16HhHh7rr8Pcf6K9+a16sX/phzKWP8qqVY7Tn35GHjyH15kNZfxohtrXa86tfObTn57JfhLp/GsiQUd9WH+HeH8VWXaY7zj+HV9OtmRm37d2lyOuqUsnGTc3g474u7fretkR8lEc2yk0f4aHV/HEtdzigUdcffxNVqvUVaK310MFiMu6jHYyX7NvjWVCLnuafiAD6vCAdfndv2HOT9aIgHb53oOYxeLrWWbtbYpKxu3/M7HoCIn8eonrH6tnrMAnQjvrzuXbyT/vtVw8ote5szHwFa/Tv5pVSTgalvW/Nhtvp3m1i339bLPasS+b0VqHg4TQn7H5ueDSyHccmFjawTHHrobfMCHp18Yxv6dXTh1fgSP7uiqCPzHHrrb+BLthfRRq72NrRH0dibQGuGwf+e8DKfOj+Dovh5DztYIV1XGq5x2Y7a+/psf/ByHdndXfW7Xjy6zk+56OxOexm8ee71jc9Nxdypu6E7X5R3tUVf9NqJXCuVWwsmPAJXrCSivoRjP4sjeys/uaI/i8++tXLf7d3bh2y8OO/qOI3t7cLp/pOL9156/bLy3rlUv/rd3baJKtgP3bUFrmHMdk5e+9u/sQl9nwpP/8CKrXsbO1x7dV6kbu7q6r65VrzsV9+y3vca3G4k1Duhz882fXsPhPd0Vnz+6owun+0eM34/v7UEsxNqO0WnOdRu22pEX/dq1qcuyHHVLWTi9qQSO7Km0zyN7etCbSrjWs7Pro/t60F2jXqM02l/D40tGbet1J6Ou9XqSMdt6PcmYu5w2seDI3h70ra0xvgbrNcpK8buLwULjojkG29mv1bd2p+LYPLdHsGvv0O5u/P0Pr+DAfVuqnp86X44X1v672qN44vnLuF4Qq+LNod3d+Nsf/Lz8ele3EYtPnR+psqlmrm3KykbP7w7ct6XK/toinJGT1OMnzH6tnrMAc5miKGNjW6Tq88ctubx5HRzZ043N7dG68u9bDSe/2Ls24XqeofvDvs5ElR/87z++Yuuf/v6HV7AmFsQnfv3OqrY2tUVQFOWKzze2Rars8OP332n4WWvfbrmv131WI/Z9K8IQQtwLMEwngC8B+JW5j/4PgP2EkOEa9W4D8DUAHQAIgL8mhBxnGKYFwJMANgJ4HcBDhJBZhmHuAvB3ALYB+DNCyOfm2uEB/ABAEOUL9L5FCDlk098BAL8HQAEwCeCDhJCrbjJu376dnDt3znX8OvqthxM5Ack4D1UDZosiAqZb4Bd6+6G5j/aYe3v6bZ/TeQmCokJSNOMG3GuzRUNOQoCZQmWZTW3e5LQb82S+8nUqweN6QUY6K2Dd6hB4P4upgmgrv/mGUllVEQsGUJTndQfA0/jNY1eIBkUlnsfmpmP9duJ0RkAywWNrRxyj2RLGsyKKphuGzfrV9VBjvhb8jef12CqF0iBNsVMnP9Iem79Z2LweFUVD/2jGuIW2b20Cfr/PaGNNtHzrbDo7Xweo9B367d3mtTycKbn6Fi/+13wjc0csiHCQxWxBAme5hdw6Jru+rkwVcG2mYHtTei28yKqXmSlUxik7ndvV1X21ne8z1/Mat+qJbzVoqj/V48BYRsCqUAAB1od0VsCGljCKsorJnIg10SBERUEw4EdWkLEmEkT32gR8PsZxjObxm224LRKEoKiYzAmI8RxkVavIJ9z0Zr6NOcyxkFUNLXM3PdOLNpYFC5oEOzsVBAUXxjIYz4roiAfRm0q4XtamY81vulOJpl5Y1Wh/jY6vUBIxmM4b9bqTUdfL6HSKJQkD6ZxRrycZc72MTkePBeY45eVSuUbrNYpHv7vodnojqDsu+nyYKUq2MVi33/GsiJYIBwKCVotvVRQNr4xnMVuUoWkawpwfk3kRHTEerVEO6Ww551FUgnS2VJUnXJ0pVuQAnavKMXamICLGs8gUVUzkRSTn/hfctZki2qJBKKoKzu83YoU132n22r6B0L3UIqDnd5M5EddLMuJ8AO2xIBimMq+uJ4cw+7V1q0KIBP2Y9nAWkBNkrApzUIkGohEE/Sxyc18v1xrhICoKAiyLiVx5HYYDLMZzIhKhAOIhFne0xipyey/57RKwrOzUyS8qiobB0QxGMiUkYzz8fgbT+Up/CKAix5RUDRxb/l+9okIwlReRivNYFQlgLFP2d5pW/vx6SQEfKP9Fnd/HYLooIj6X47bHyjnweE6ApBCUJBVtUQ4qmfezet+18mkvezq7fSPNkZ3t1Mvh8HMAvg7gv8199FsAPkAIua9GvRSAFCHkRYZhYgBeALAPwG8DmCGE/CeGYf4DgNWEkE8yDNMOYMNcmVnT4TADIEIIyTMMEwDwQ5QPp39s6e/XAPyEEFJkGOYPALyTEPKwm4w0SFCWiGUVKCgUB6idUlYC1E4pK4Wb4tCNctND7ZSyEqCxn7ISoHZKWQk42qmXf1pcQwj5O0KIMvfz9wDW1KpECBkjhLw49zoH4CKAdQD2AnhirtgTKB8GgxAyQQj5KQDZ0g4hhOhXDgfmfqpOtAkh/0QIKc69/TGATg9jo1AoFAqFQqFQKBQKhUKhUCiUWxIvh8PTDMP8FsMw7NzPbwGYrqcThmE2AngLgJ8A6CCEjM09SqP8tRO16rMMw7wEYALAc4SQn9So8rsAvlOPjBQKhUKhUCgUCoVCoVAoFAqFcivh5XD4gwAeQvkgdwzAewD8jtcOGIaJAngawB8TQrLmZ6T8nRbu32tRLqcSQu5G+X8D/xLDMD0u/f0WgO0APuvw/N8xDHOOYZhzk5OTXodBoSw51FYpKwFqp5SVALVTykqA2illJUDtlLJSoLZKWQlQO6UsF2oeDhNCrhJC9hBC1hBC2gkh+wgh17w0PvcdwU8D+AdCyLfnPh6f+z5i/XuJJ7wKSwi5DuCfADzg0N+9AP4MwB5CiOjQxl8TQrYTQravWVPz2zEolBsGtVXKSoDaKWUlQO2UshKgdkpZCVA7pawUqK1SVgLUTinLBccrgBmG+feEkL9kGOZLsP+O30fdGp67SO6/ALhICDlmenQSwL8F8J/mfj9To501AGRCyHWGYUIA7gPwGZtybwHwVQAPEEI8HzgvBubbzVOJELpTcdebYs03jJtvJfeKXn+6IIJjfcbtkfpv/VZ6623nTv1Z29MIgaqhfAulh/HU0oV+g7ve//rVYQxfL2I8K6IgKdjUGoFGgInc/PNrs0WMZwWkEjwIASZy5bIb5m751Z+7jafR5/XMwULaoFBuNcz+oXN1CLyfLd/uPbeGACz6urJbqwBwZaqAqzMFRDg/kokgJKVcLhRgEeFYZAQJq8N8hf9z8/X1+lmrn25kTF7aWkq5Ftrmjfar5lu0JUUFHyjbZyrOAwwwmZMQ5lhEgywKkgpZ1bAqxKEoqggGfJgtSYjzAXTEg1iXcI9Tizle3S7HswJaI0FomL/xebnEpXrzJIo9gqDgwlgG6ayIZDyI3lQCPO+Yyhs0amuNzttSyylJKvpHM0hnBaTiPHrXJsBxbNPGVyrJuJDOYjwroiMeRG8yjlAo0LTxNcpKXXeLJXe9+nYrb5WpJerH2KyIqYKIzlVhxHg/0tnqfYy5HUXRMDiawWhGQGuUg6Ao4HwsipKKtlgQoqKiJRwE6wPGMvY5SzToR5hjkRMUtMf4qrLLxedTmkcj62Ox8gRznqTvyze1eW/DvMbCnB+ioiLI+lBSFGRLClZFAvAzPkzkRIQ5FrGgH3e2R5HOS8a5gKpVnxksZg67knHyYXZ5eXuMh48p77siwfJcrE2Esamtcj8W5vyQVNXWXnS7ygoSeL8fBUlBmPNjOi+iNRpEXpSxKsTBzzLIl8q5ckaQ0BblEQvO+0y7vYl5n9YRD2J9y+Kf51CqccvULs79bvS6xF8B8G8AXJj7vmAA+FOUD4WfYhjmdwFcRfkrK8AwTHKurzgAjWGYPwbwJgApAE8wDMOi/D+dnyKEnJ6rcwTAOULISZS/RiIK4Jvlc2lcI4TsaVB2zyiKhhPnR/DYiQEIsgY+4MPRfT3Y9+Z1to5a0wieHUzjwFMvGeWPPXQ3HuhOejJovf5nnr2Ih7evx5PnrlX8/uLZoYp279/age9eHHfsz9re2VfSePe29Th8etDTeGrp4rPv6YOP8eFj3yz3v6E1hI/ffyeGZ0s4fmYIq8McHnnbBhw/M2Q8/8iOLjx2YgCrwxz+4B23oyCpts/dxlNrvI3qfzHmkEK5FTH7B+u619cQ52fwR1//2aKtK7u1+uX3vwWiTCp80h++czMOnZz3eft3diEcYHHo+ZfxkR1d2PfmdQDg6Ot9PsaT39H9rNVPN+J/vLTl1R8uhlyNyFdrrpbSr2oawdlXxzE0nsc3fjofT+1s9dDubjz9wjXsuCtZMb5Hd3ThyXPX8KF3bEZLJIc//98XcXW61NDceMUu7upyfPKBrcsiLtWbJ1HsEQQFJy+M4eDJeT0e2dODPb0p14PXRm2t0XlbajklScWJ/lEcfMbU394e7Otb63pA3Oj4SiUZpwbSVePb3ZN0PSBeah+3UtfdYsldr77dymsaqZBpQ2sIH37nZhy05A1f+9FVcH7Gdp9y753tOHlhtOLzQ7u68ZUfvGbEiY/euwVf/5ereN8vrsfXfnQVs0WpKmcx9zVblCpe073IzU8j62Ox8gRznmTN3720YbfGPnrvFoQCPvz5d17B6jCH3/mVjTj23KUKW39jtoT+N6bxvwYmq/Kxo/t68I1/uVqVj92Ka8HJh+lnQXZ5udl/PDrntz61602QFFLRjp296Hb1jX+5indvW4+v/GCwqv3y/Jbw5995xdLWyxV+rtZZzf6dXejqiGLHnR2Ldp5DsccxyhJCTs29LBJCnjD/ACjWapgQ8kNCCEMI6SOE3D33878JIdOEkJ2EkC5CyL2EkJm58mlCSCchJE4IWTX3OksI6SeEvGWunR5CyBFTHwfnDoYx11aHqa+mHwwDwOBYxnC2ACDIGh47MYDBsYxt+denC4Yh6+UPPPUSXp8ueOpPr7+rbx2+eHao6re13cGxjGt/1vYeued242DYy3hq6WJoIm8kNACwq28dhibmg8qD2zqN1/pzvY0Ht3ViqiA5PncbT6PP65mDhbRBodxqmP2Ddd3ra6h/OLOo68purfYPZ6p8kn4wrJc5fmYI00XJ8DeDYxlXX+/V7zj56Ub8j5e2llKuRuSzq3ej/Orr0wX0D2dw/ExlPLWz1cOnBvHIPbdXjU+PxYdPDUJWCHb1rXMcy2KN184udTmWS1yqN0+i2HNhLGMcSAJlPR48OYALNfTYqK01Om9LLWf/aMY4GDb6e2YA/aPu/TU8vnTWfnzprGu9pfZxK3XdLZbc9erbrbxVpl1964yDYb3s8TNDeHBbp+M+pX+0elyHTw9WxIkvfO8SdvWtM9qyy1nMfVlfLxefT2kejayPxcoTzHlSI37Mbo194XuXMFWQjHxLPxjWnx8/M4TXJvO4t3udbT722IkB23zsVlwLTj5MPwuyy8vN/kO3if7h6rMjO3vR7Uo/O7Jr3zy/1racfJfdOI6fGUL/cGZRz3Mo9nj5J9g/8fjZLclYRjAMU0eQNaQzgm358ax9+YmcfXmn+gwD29/Wdp3k0/uztlcSlbrGY8auL41UysUwlZ9Z5Ta/t5a1K+80nkafe2Ex2qBQbjXM/sFpHWuWLzBa6LqyW6tefYpG5p+lM4Krr/fqd2r5r3rG5KWtpZSrEfns6i2GDI0wnhUM27DGITu5SpJ9rNTLFyQFDFP5rJ658YqTXepyLIe4VG+eRLEnnRVt9Tietb1iw6BRW2t03pZazrRDvfFsc8Y3vsTja5SVuu4WS+569e1W3iqTU1xgGOdnTnZqjRPmfR1QnbNY61lfLwefT2kejayPxcoTzHmStS0vbTitMT33d8vHJ3NC3fnYrbYWnPSrz7+b3zK/dvM5Zr3q7epnR/Xs7ax+zstZjf4VpG5lbrU5bwaOh8MMw7xr7vuG1zEM80XTz98DUJZMwmVOKhECH6hUIx/wIZngbct3xHnb8u0x+/Ju9Z1+m9t1kk/vz9peOOivazxm7PpimWq5rJ/Z9edW3+t4GnnuhcVog0JZCOtuWw+GYer+WXfb+hsms9U/2K0h618CLXRd2a1Vrz7FxwCEzPs/N19fj99ZTP9Tq62llKsR+ZzqLVSGRuiI8xW2UctWw5x9rNRtJsL5QUjls3rmxitOdqnLsRziUr15EsWeZDxoq8eOeNC1XqO21ui8LbmcDvU64s0ZX8cSj69RVuq6Wyy569W3W3knmazvdZ9vux9zaN8aJ3TfrX/ulLOY+zK/Xg4+n9I8Glkfi5UnWPMkc1te2nBaY+bc3+n5mrn268nHbrW14KTfVMI9L7f6EjefY9arblfmsyOvezurn/NyVuNjsKjnORR73P7n8CjK3wEsAHjB9HMSwK83X7SVQXcqjqP7eioWxdF9PehOJWzLb2yN4NhDd1eUP/bQ3caFA7XQ6586P4JHd3RV/ba2252Ku/Znbe+J5y/j0K5uz+OppYvN7VF8/r3z/Z86P4LN7VHs31mW9ekXho3X+nO9jadfGEZrhHN87jaeRp/XMwcLaYNCWQijw2/g4a8+X/fP6PAbN0xms3+wrnt9DfV1JhZ1Xdmt1d7ORJVPOryn0uft39mF1jCH0/0jhv9z8/Ve/Y6Tn27E/3hpaynlakQ+u3o3yq9ubI2gtzOB/Tsr46mdrR7a3Y0nnr9cNb5Hd3ThdP8IDu3uRsDP4HT/iONYFmu8dnapy7Fc4lK9eRLFnt5UAkf2VOrxyJ4e9NbQY6O21ui8LbWcvWsTOLLX0t/eHvStde+v4fEl4/bjS8abMr5GWanrbrHkrlffbuWtMp06P4IjNnnDt18cdtyn9K5NVH1+aFd3RZz46L1bcLp/xGjLLmcx92V9vVx8PqV5NLI+FitPMOdJjfgxuzX20Xu3oC3CGfnWgfu2VNn65jVRfG9wxDYfO7qvxzYfuxXXgpMP604lHPNys//QbaK3M1HVjp296Halnx3ZtW+eX2tbTr7Lbhz7d3ahrzOxqOc5FHsYQoh7AYaJAygQQtS59yyAICGk5vcOL3e2b99Ozp1r9L69efSbGtMZAckEj+5UwvXSBP12xYmcgPZY/bcr6vVnCiICrA+SqoEz/bbe1FmrP2t7GiFQNWAqLyLlYTy1dOHzMRX9r18dxvD1IsazIoqSgo2tkfKfjOTnn1+bLWIiJyAZ50EIMJErl13fEsGGlvnnbuNp9Hk9c+CxjQV/M/pi2Srl5oBhGDz81efrrvfk798DF5/fdDs1+4d1q0Pg/SymCqKxhgAseG1asVurQPnm72szBYQ5P5KJICSlXC4UYBHhWGQEGavDXIX/c/P19frZhdyoXE9bSynXQtv06FebZqfmW7glRQUfYDGZF5GK8wADTOYkhDkWkWD5dnlZ1bAqxKEoqeD8PlwvSYgHA+hIBLEu4R6n6hhvTeZvIRfREuFAGryFvJnUmyfdJCxI+XZ2KggKLszNdUc8iN5UwvWSN51Gba3ReVtqOSVJRf9oxri1vG9twvUyuoWOr1SScSGdnR9fMu56Gd1Cx9coHse36Ha6UBbLX9Srb7fyFTLFebTEAhibFTFVELFuVQhxPoDxXPU+xtyOomgYHM1gLCugJcJBVBT4fSwEWUVrhIOkalgdDoL1lb8uxS5niQb9CHEscoKC9hhfVXa5+PwmQPdSczSyPhYrTzDnSfq+fFOb9zb0NTaeFRDmWEiqhoDPB0FRkS0pWBX2w+/zYSInIsyxiAX9uLM9inReMs4FVK36zGAxc9gFckPt1MmH2eXl7TEePqa874pwfkiqilQijE1t8/sxfZ5kVUOLjb3odpUTJAT9fhQlBSHOj+mCiNZIEAVRRoLn4PczyAvlXDknSGiNBBEz+Uy7vYl5n9YRD2J9y+Kf59zCOB9aeTgc/jGAewkh+bn3UQDfJYTcs6gi3gBuliBBWfbQhIayqKzUw2EKZRGgdkpZKSy7QzcKxQZqp5SVAI39lJUAtVPKSsDRTr38MyyvHwwDwNzr8GJIRaFQKBQKhUKhUCgUCoVCoVAolBuDl8PhAsMw2/Q3DMP8AoBS80SiUCgUCoVCoVAoFAqFQqFQKBRKs6n9BWDAHwP4JsMwoyj/F+QkgIebKRSFQqFQKBQKhUKhUCgUCoVCoVCaS83DYULITxmGuQvAnXMfvUoIkZsrFoVCoVAoFAqFQqFQKBQKhUKhUJqJl/85DJQPht8EgAewjWEYEEK+1jyxlg/mWzU74uVbMYevFzGdlyAoKkRZw4bW+Zs69fKZkgQGDARFhaISSEq53IaW8q2a1vbGsyIKkoINLfNlpgsiQgEWoqxBUFRoGkGcD6Aoq451rTdM2t3Yqd80minKkDUNsqpB1WDIaB3LeFbA2lU8rhdkZEUJvN+P6YKEVCKE7lS86oZU/ebK6YKIOM9BUjQkE/M37rrJZpVRH9umuboTuWo9jWcFpBLl20tniiI4D7eV2s2reV7M9cxl9X4mcu7yUyiUMro/GMsISCVCWBX2Y/T6/PoB5n2CfvP2WMZ+XZrf62Un8+U1XxBVRILl23bNNzA7rV9zX2tX8ZgtyBi5XkJrlEM4wCIvqEiuqvSzRUlBnA8gI0hojfDY2hHDWK6E8Yx+Y3nY1ida/c1i+o3Km5/L42+Zu+28rPNKn6XrcLow7yvNurDTka7joqQiGeeRE2SMzs3n1o4YhjMlo/+sIIFjWdubhRVFwyvjWcwWZQiyittbI9jQGnH0vUuNphFcnsxj9HoRfMCPrChjVYjDVL58a3YiFIAgq5gtyghzLKJBPyJBH7KCAlEmKEgKknEeoqIhL87HZKsdWm1/uiCC8/mQE2VwLIuCpGD96jBYlsHI9RJygoK1q0J4U3JpbYuy/BAEBRfGMkhnRSTjQfSmEuD52ql8sSRhIJ3DeFZERzyInmQM4RDXtP4KJRGD6bzRX3cyikgoWLOeJKnoH80gnRWQivPoXZsAx7E16+VKAi6mC0Z/W5MRxEJ80/prVC+N1rPGUbs4Q6md27u91+OnOX8wo9tKOf8IQiMafIwPHMsgJ6rICQpaoxwSIRZ3tMWhacSwrXWrePh9PoxnBcT4AHKCjDWxIAqigkxJQXssCD/LYHi2nIPEeT+ygoqipOC21WGIioqJnIBYMICipCDM+TFblNARp7ZA8YZTrqBpBD+fzOPKVAExnkWAZSHJGpKrGt9Dr43xGEhnDb/anYxjJCtgLFPOrabyIiIci5ZIOQZdmy1hdTgAjvWhJKkIcSxERUVGUNAeDUIjBCVJg0pUhLkAJnMi2mNBtEVZTOVVTBUkJHg/UokQNjjs32/W/MjrGPVzFfP51aa2CDQyn+8H/EA6I2IyJ2JNLIiSrGBVKFjhYxRFw6vjWcwUZQiSikR43idlSjIiQRYhP4vJvIhEmAMhBNmSglXhADriQcgKwbWZIoJ+H1iWQTTox10dlf4yleDRFuWQzsyd+awOw+9nMJ4VkSnJiPEBRIMsSnJ5v+NnMV/WlHdTGqNmRsIwzCEA70T5cPh/A3gXgB8CuOkPhzWN4NnBNA489RIEWcOG1hA+fv+dmC1IKEgqjp8ZgiBr4AM+HHvobty/tQPfvTiO//rDn+MDv7wROUGuKLehNYSP7OjCYycGKtobni1VlfnS2SF88J5NYBigIKn4xk+v4eHt6/HFs0OOdfmAD19+/1sgKcSQWZftge6kEQTOvjqOmbyIgJ9FriS7juXAUy9hS3sUv/nLG/D0C9fw7m3rcfj0i0bZo/t6sO/N6yqcxonzI/jS2aEKeb3IZtb72VfHMTSex/EzQ1gd5vAH77jdUZerwxweeduGKh25tW+dV/O8mOsBMMrq/Vh1ZW2fQqGU0f2BeW0d2t2N//GTq7g0kbf1Cft3duFrP7oKzs9Urcuj+3rwpbNDuDpdAh/w4U/fdRdKsoYvfO+SUebRHV148tw1fPKBrRV+zG797t/ZhX+5PI37e1I4fGrQVsbPvqcPYxkBx56z9vEyPrKjC6yPwZ98+4KjT7T6m8X0G3Zt6+N/3y+ux3cujOFdvamKMR/d14Nv/MtV7LgrWeEr9+/ssi1/4L4tCLI+/MWzr9jq8MjeHvzVP83Pibn/ro4odtzZAZ+PgaJo+M7gWFW8+6Nf68Knnqn2vUvtUzWN4DsDafzlP17Ew9vX48lz1/Bv3roRn/vuzwxZP/SOzRV2sn9nF9atCkGQFRw8+bJjjDDboflzzs/g8dMvG/1ZY7y1v6W0LcryQxAUnLwwhoMn59fLkT092NObcj1gLJYknB4Yr6q3q6fD9YC40f4KJRH/a2Ciqt5v9LS7HhBLkooT/aM4aPIHR/b2YF/fWtcD21xJwHcGJqv6e1fPGtcD4kb7a1Qvjdazi6NWX0Cx94fWnMH83i73N+cPZj9qZyuHdnXjn14dw6/dVZk/PL63B9dLEq5OixXlzfmKUz6i5z5/+M7NOHRysCoO/9fnX67a51BboNTCKVe4f2sH/vHlcXzsm973uLXW2f1vasO9W9dW+blzr09iS3IVPvfdVytsPsKx+NYLw1W5p74eZosSDu3uxtMvXKvKW4/s6cFffX9+fe/f2WXknQBu+vzIaw6on6uMzpaMsxTrfG/fkMB7t6+v8DuHdnXjS2eG8L5f2oB9b14HAFV5vF7uKz8YrJgHfe7Mrw/v6cb/+/3XKspFOBaTeQGTObnCX1rLfnp3N/7zP1fWDQdYnOofwbt/YX2FD77Z5nmp8RJJ3gNgJ4A0IeR3ALwZQKKpUi0TXp8uGAsOAHb1rcPQRB5TBclYFAAgyBoOPPUSBscyOPDUS3jknttxZbpQVW5X3zojCTG3Z1dmV986TBclo41dfesMh+hUV5A19A9nKmTWZXt9umCMqX84gzAXwJWpahmtYxFkDb/39jtw+NQgHrnndhw+PVhR9rETAxgcyxg6GxzLGPKb5fUim1nv/cMZQ64Ht3W66vLBbZ22OnJr3zqv5nkx1zOX1fup1T6FQimj+wPzmjl8ahC/9/Y7HH3C8TNDeHBbp+261H2L/n6qIBkHw/pnXzxb9gVWP2a3fo+fGcJv/+omI6mwk3FoIm8cDFv7eOzEAK5MFVx9otXfLKbfsGtbl+34mSH83tvvqBrzYycG8Mg9t1f5Sqfyx567hOmi5KjDg89Uzom5//7hjDHOwbGMbbzTD4YXWzf18vp0AR/75ktGHNnVt87YxOiyWu3k+JkhvDaZR5gLuMYIsx2aP+8fzlT0Z43x1v6W0rYoy48LYxljww3Mrb+TA7hgsgk7BtI523oD6VxT+htM523rDabzrvX6RzPG5tCo98wA+kfd+7uYLtj2dzHtvg4a7a9RvTSsT5s4avUFFHt/aM0ZzO/tcgxz/mD2o3a2cvj0ID7w1ur84VPPDACErSpvzlec8hE999EPaPRnehy22+dQW6DUwilXGBzL4GPfrG+PW2udfeCtm2z93L5t6ytyKt3mpwqSbe6prwc9J7fLWw+erFzf5rzzVsiPvI5RP1cxn6VY5/uRe26v8juHT5f1rvsYuzxeL2edB33uzK8PnawuN1WQwDK+Kn9pLfvpU9V1p4tS+WzK4oNvtnlearwcDpcIIRoAhWGYOIAJALc1V6zlwXhWMIwNABgG0Ej5x/w5UH4/limXL4mKbTmGqX7vVMbal5e6gLNsEznBGJNGgIKDjNaxAEBJVIxx2ZVNZwTjvV7PKq8X2XR0GfWybnqy6sxr+27zYq5nLuu1fQqFUsbsR3QEWUNJUgA4+wSGcV5vjOkfgt3qW/2YU3vXC3LDMgqyBo2g6pnZJ1r9jV5mMfyGU9u6bE4+2/Fzyf5zfYxe5sSqG32cYxmhZkzU698In6rr0imeOMmqEaAwZytOZZzWgUac45dTW0tlW5TlRzor2s73eFZ0rTfeYL2l78/ensez7va81P01qpdG6zn5D7MvoLjHQ7v3bvHM6kedbMUpf5jIVZe37mvqzX3M8cL6jNoCxQ2nteElR661h9bL6etq1mFNTOft/Z9G4JiT6m265afW9a3nnbdCfuR1jPq5ipsPqrUvSGcE2zxeL+fkZ51e6+81Asw42IxTm+a6TnLfTPO81Hg5HD7HMMwqAH8D4AUALwL4UTOFWi50xHnwgUoVsUz5x/o5H/AhlQiBD/gQDvpdy1nbcypjbcNLXaf22mO8MSaWASK8u4z6WAAgHPQb47Irm0zM/9meuV69sunoMprL1tKlU59O7deaF72etayX9ikUShmzP9DhAz6EuPKf0Dqta0LmXzs9q1W/7Mdqr99VkUDDMvIBH6x/tWT1iU7+ZjH8hlPbumxOPtvxc87+c/MYa82JVTf6OFOJkKeYeKN8qlmXbvHE+t7HABHO71rGaR3oeq2nv6WyLcryIxkP2s53R9z9u3w7Gqy31P2lHOy5I+5uz0vdX6N6abSek/8w+wKKezx0e29X3upHnWzFKX9oj9nvH2vlI265jzVemJ9RW6C44bQ2vOTIXvfQuu22OKyJ1qi9//MxcMxJzevBKT+1rmc977wV8iOvY9TPVdx8kNMchOb0nkzwrnm8k591eq2/9zHONlPLd7vZzs00z0tNzcNhQsgfEkKuE0K+AuA+AP927uslbno2tkZw7KG7DaM7dX4Em9ujaI1w2L+zq2JDd+yhu9GdiuPYQ3fjiecvY2NrpKrcqfMjOLqvp6o9uzKnzo+gJcwZbZw6P4JHd3S51uUDPvR2Jipk1mXTL7/Z2BpBb2cCRVHGxrZqGa1j4QM+/M0Pfo5Du7vxxPOXcWhXd0XZo/t60J2a/5aR7lTckN8srxfZzHrv7UwYcj39wrCrLp9+YdhWR27tW+fVPC/meuayej+12qdQKGV0f2BeM4d2d+Nvf/BzR5+wf2cXvv3isO26PLqvB6f7R4z3rREOH713S0WZR3d04XT/yJwfS7iu3/07u/D3P7yCQ7u7HWXc3B7Fgfvs+zi6rweb2iKuPtHqbxbTb9i1rcu2f2cX/uYHP68a89F9PXji+ctVvtKp/IH7tqA1zDnq8Mjeyjkx99/XmTDG2Z2K28a7x/fa+96lZmNrBJ9/791GHDl1fgQfv//OClmtdrJ/Zxc2r4miKMmuMcIcT82f93UmKvqzxnhrf0tpW5TlR28qgSN7KtfLkT096DXZhB09yZhtvZ5krCn9dSejtvW6k1H3/tYmcMTiD47s7UHfWvf+tiYjtv1tTbqvg0b7a1QvDevTJo5afQHF3h9acwbze7scw5w/mP2ona0c2tWNf/hxdf7w+N4egFGrypvzFad8RM99Du+pbFOPw3b7HGoLlFo45QrdqQQ+/9769ri11tl///EVWz934sVrFTmVbvNtEc4299TXg56T2+WtR/ZUrm9z3nkr5Edex6ifq5jPUqzz/cTzl6v8zqFd3fja85cNH2OXx+vlrPOgz5359eE91eXaIhxUolX5S2vZT++urtsa5spnUxYffLPN81LDEPMxvF0BhvkVAC8RQgoMw/wWgG0AjhNCri6FgM1k+/bt5Ny5c65l9Fsg9Zsc9Zvr9dseJUXDepsbybMlCQADQVGhqASSomFDawQbWso3elrbG8+KKEoK1rfMl5kpiOADLERZg6CoIISUb6qVVeN2UGvdTW3zN6DrfVhvrtRvrMwUZciaBlnVoGowZLSOZSJXvjnyekFGTpQQ9PsxXZCQSvDoTiWqLkHQb1WeKYiI8RxkVau6nd1JNquM+tj0uhO5aj1N5AQk4zxUDZgtigiwPhQlteatndZ5Nc+LuZ65rN7PZN5dfgsL/kZ0L7ZKWXmsu209RoffaKjuw199vu46T/7+PXDx+U2xU90fpDPl9bMqEsBYZn79APM+YU2UB+sr/wmn3bo0v9fLTuXn13yYYyGrGlpMt407rV9zX6kEj9mCjJHrJbREOEQ4FnlRRTJR7WfjfABZQUJLJIitHXGM5UoYz4iYKohYlwihe221T7T6m8W8Mdl8U7E+/tXhoDE2q8/SdThTmNdbe4y3LW+n42ScR06QMZYRkEzw2NoRx3CmVO4/wCInygiwLDriQaxvqRynomh4ZTyL2aIMQVaxaS6Bd/K9DjTNn2oaweXJPEYzRfB+P3KijESIw3ReRIhjkQgFIMoqZosKQpwP0aAfkaAPWUGBKJO5uBOEqGgoiIptbmAeJ1C2/ZmCiIDPh5wog2NZFOZuqPezDEaul5AXVKQSQbzJJt4207YoC2ZBE2Fnp4Kg4MJYBuNZER3xIHpTCdfLzHSKJQkD6ZxRrycZc72MbqH9FUoiBtN5o153Mup6GZ2OJKnoH80YN6/3rU24Xg6nkysJuJguGP1tTUZcL6NbaH+N6qXRehVx1CH3XgCLbqc3ilq5vdN7c/w05w9mzLbSHgtCIxp8jA8cyyAnqsgJClqjHBIhFne0xaFpxCifSvAIsD6M5wTEggHkBBlrYkEURAWZkoI1sSACLIPh2RJaoxzivB85QUVRUtC5OgxRUTExV7coKQhzfswW5fLaWlxbWM7QvdQCcMoVNI3g55N5XJkqIMazCLAsJEVDMtH4HnptjMdAOmv41Z5kHCNZAWOZIviAH9N5CSHOh5YwB4YB3pgtYVU4AI71QZBUBAMsJFVFtqSiLcYBhKAoaVCJhjDnx1ReRFs0iDVRFlN5FdMFCTHej7WJEDY47N+XMD9aUjv1Okb9XMV8frWxNQKNzOf7AT+Qzohl/UaCKCkKVvFcxb5GUTS8Op7FTFGGIKlIhOd9UrYkI8SxCAdYTOUlJEIBEBBkSgpWhQPoiAchKwTXZorg/D74WQbRoB93dVT6y2ScR1uMQzpT3nfdtjqMgJ/BRFbE9ZKMOB9AJMhCkFWsDgfhZ2GUNefdFFccFeTlcLgf5Uvo+gD8PYC/BfAQIeQdiyjgDeFWDhKUJaWpgaKRA8a1nbdh5I1rCxWLskAYhmn4kHelHA5TKIsMtVPKSuGmOXSj3NRQO6WsBGjsp6wEqJ1SVgKOdlr7n6sBhRBCGIbZC+DLhJD/wjDM7y6ebBQKZSGMDr9R90Hhk79/T5OkoVAoFAqFQqFQKBQKhUKhrBS8HA7nGIb5EwC/BeDtDMP4AASaKxaFQqFQKBQKhUKhUCgUCoVCoVCaiZcvKXoYgAjgdwkhaQCdAD7bVKkoFAqFQqFQKBQKhUKhUCgUCoXSVGr+z+G5A+FjpvfXAHytmUJRKBQKhUKhUCgUCoVCoVAoFAqludQ8HGYY5kEAnwHQjvKXFzMACCEkXqPebSgfIncAIAD+mhBynGGYFgBPAtgI4HWUL7ebZRjmLgB/B2AbgD8jhHxurh0ewA8ABOfk/RYh5JBNf8G5/n4BwDSAhwkhr9caX72Yb4bviFfe9mn3uVvd9avDGL5exHhWREFSsMHDDYv6jcVjGQGpRAjdqbinW2q9yGctl0qUb62fKYrg5m6qt6vr1rbXZ3pfE7nK126yusms1+1MhHBxPIuxjIDO1SHwfhaTebGmLIQAE7nyvGyau83TLA+Ails/RVnDhlZ6QyaF4oZXP9RIHXO5MOeHpKpodbh13NpmZyKES5M55EUFskqQFxW0R4PoTsarbpLXffB0QUSc5yDJGiK8HwVRAsP4UJQUrInyUFQN6ZyAdavCrn66EZ00gpfYod9mXE9McmKpxrWY6ONPZ0VkSzIiQRahAIvWKIdULISfT+eQF1WUpLLPb4ly0AhBi+W25JbI3E32YDBTlBDm/OiIB7G+pVoHjcb0WuNoVPeNrDcvfUiSiv7RDCZyAtqiQRQlGavD/KKMdym50XadLQl4JV1eox3xIO5KRhAP8TXrCYKCC2MZpLMikvEgelOJKt9mRzPssxn9lUoyLqSzhl56k3GEQrW/Aa/ZOfVi1WuUG2Wv9fZrnYctbREMjueQzgpIxXl0J+MYzQl1j8Pa7p1ronhtKo+ZooSSrGJtIoStSe9zfmWqgKvTBURDLBjCoCgpiPEBlGTv+wDdF+pj612bAMexjvqz7sUkVXPdk1nrr5T4u1xZjrps1N9ZacbYvO7722M8WB8wmS/bdUFUEeX9CPiAoqQhLykQ5XIenxEktEYq8wVzvlrOuzgIsoapvIjO1e55d6N6WI62oCgaXh7LYDQjIB7yY22cR1ZQMGqKaT4fY8idjAUxW5IxnhUR5/1Ym+CxoS0KTSOGr7Q7L9E0gsHRDEYyJbRFg+iIB9ER4TGQziKdFZCMB8EHWGRKMiRFQ0skiKwggWNZI/8192GOt7pepwvu502UpcHLdw7/JYDdhJCLdbatAPgYIeRFhmFiAF5gGOY5AL8N4Awh5D8xDPMfAPwHAJ8EMAPgUQD7LO2IAHYQQvIMwwQA/JBhmO8QQn5sKfe7AGYJIZsZhnkfygfaD9cpsyuaRvDsYBoHnnoJgqyBD/hw7KG7cf/WDnz34njV5w90JyscornuhtYQPn7/nRieLeH4mSHHemYURcOJ8yN47MSAUf7ovh7se/M6VwfoJLe1H3O51WEOj7xtA77x02t4ePt6fPGsvYxubQPw9Ezv6/iZoYrXXnRiJ7Ned/uGBB76xQ04+MyAa7tWWf7gHbejIKmO8nz5/W8BAIzOloxyXmSlUG5lvPqhRurYlXt0RxeePHcNn3xgq6sv3r4hgUfu2YTrBalqPT++twe7e1LGIYrug790dqjKLx7a1Y2v/OA1XJ0ugQ/4sH9nF772o6uYLUqOfroRnTSCl9ihaQRnXx3H0Hh+wT5tqca1mDiN/8B9W9AeC+KNWAGTORnpjFDxXLezD71jM77yz+X539AawofevhmHTw8a5fbv7EJXRxQ77uwwdNBoTK81jkZ1v5D15taHJKk40T+Kg88MWPT2Mj6yo2tB411KbrRdZ0sCnh2YxMGT83o8sqcHD/SscT0gFgQFJy+MVdXb05tyPSBuhn260Wh/pZKMUwPpqvHt7km6Hpg0O6derHqNcqPstd5+rfOwoTWED7+zq2o+nzp3FeeuZjyPw9ru9g0JPPK2TRi5Xrnv+o//uhd7+9Z6nnPz/uiD92xCUfa+D7DzhUf29mBf31rjgNhtL/bkOfc9WSP6pzizHHXZqL+z0oyx1XsmcOC+LQiyPvzFs68Ya/9j923ByPXKPOuj927B4X+Zzxd8PqYiX7Pbqz++twf/+u7asapZec9SYOc7P/SOzTh8arAipq0KB/BHX/+ZrZ727+zC5vYCBFnFJ77Vb1vm8++9GxrR8Ilv9Ruf/cWDvVA1UtH3H75zMw6dnO9bz4/f94vr8aa1MUzmpKp4u6d3Lb736gQ+8+zFmr6NsjR4ye7GGzgYBiFkjBDy4tzrHICLANYB2AvgibliT2DuMJgQMkEI+SkA2dIOIYTk594G5n6ITZfmdr8FYCfDMItqTa9PFwynAACCrOHAUy9hcCxj+/nr0wXHurv61mFoYn4T6lTPzOBYxlhUevnHTgxgcCzTkNzWfszlHtzWieNnhrCrb52xUO3qurXt9Znel/W1F504tQMAj9xzu5GAubVrbWOqILnK0z+cQf9wpqKcF1kplFsZr36okTp25b54tuy/avniR+65Ha9N5G3X86eeGcAFk3/VfbCdXzx8ehC7+tYZ74+fGcKD2zpd/XQjOmkEL7Hj9ekC+oczi+LTlmpci4nT+I89dwmXpwpgGRZXpgpVz3U7O3xqfv539a0zDob1csfPDKF/OFOhg0Zjeq1xNKr7haw3tz76RzNGLNbL63pb6HiXkhtt16+kC8aBgN7/wZMDeCXt3v+FsYxtvQs19N4M+2xGfxfSWfvxpbNN6a9RO1hq+7lR9lpvv9Z52NW3znY+H7nn9rrGYW33kXtux2uT1fuuP/ufF+qac/P+aLpY3z7AzhcefGYA/aOZmn3pPtNtT2atX4++KNUsR1026u+sNGNs9Z4JHHvuEqaLUsXaf22yOs/6wvcuVeQL1nzNbq/+qWe8xapm5T1LgZ3v1A+GdRkfOzGA/uGMo56OnxnChZEMhibyjmU+9s2XjOf6Z1emClV96wfDehndZx0/M4RcSbWNt/2j5TM0L76NsjR4ORw+xzDMkwzD/CbDMA/qP/V0wjDMRgBvAfATAB2EkLG5R2mUv3aiVn2WYZiXAEwAeI4Q8hObYusAvAEAhBAFQAZAq01b/45hmHMMw5ybnJysZxgYzwqG0eoIsoaxjP3nEznBsS7DABpBzXpmnPpJZ+zL15Lb2o+5HMOUy+i/neq6te31mbmPWv25jc1atyQqntq1tmGeF7t6Gpn/qUfWelmIrVIoS4VXO/Xqhxqp41ROX79uvrgkKq7reTwrGu91H+zkT8z/HGl+7+SnG9FJI3iJHeNZYdF82lKNqx5q2anb+DUCTOVFx+fmeFnuy7kdsw4ajeluLET3C11vTn2ka6zPhYx3KVkKu3az0/GsWNNH2ZFusF4z7LMZ/TWql2bn1ItVr1Ga2Z+7ndbXr3UenPxnSVI8tefUrh7rFzrnZn9fb8x08oXjWfscxboX87JHWo7x90bSjH3/jdRlo/6uup3FH1sjZwKa6b/7ua0pc75gzdec1oWXWNWsvKdeGrFTr75T17Hbcy9lzFjnyW1fJMgaCqYzGfNz3SfWe/5DaR5eDofjAIoA7gewe+5nl9cOGIaJAngawB8TQir+WYsQQmD/v4BhKacSQu4G0AnglxiG6fHav01bf00I2U4I2b5mzZq66nbEefCBSpXxAR9SiZDt5+0x3rUuy6BmPTNO/SQT7t835yS3tR9rOf21W123tut55vTaSdZaMgNAOOj31K61Deu82M2b/lOPrPWyEFulUJYKr3bq1Q81UsepHCG1fXE46Hddzx3xoPHe7IOd+rN77+SnG9FJI3iJHR1xftF82lKNqx5q2anb+H0M0BYNOj7X7cw6/3btmHXQaEx3YyG6X+h6c8xdaqzPhYx3KVkKu3az0454sKaPsiPZYL1m2Gcz+mtUL83OqRerXqM0sz93O63TPzjMg/V9iPNXvK81Dmu7eqxfjDnXX9e9j3PQTUfcOUex5hyN7DdvdPy9kTRj338jddmov6tuZ/HH1siZgPUbA2rlWckEb5uvNRqrmpX31EsjdurVd5p17PTcSxkzTvNkfa/PW4T328+RSa/Lba3dqtQ8HCaE/I7Nzwe9ND73HcFPA/gHQsi35z4eZxgmNfc8hfL/BvYEIeQ6gH8C8IDN4xEAt8216weQQPliukVjY2sExx66u8KIjz10N7pTcdvP9YvL7OqeOj+Cze1R7N/Z5VrPTHcqjqP7eirKH93Xg+5UoiG5rf2Yyz39wjD27+zCqfMjeHSHs4xubXt9pvdlfe1FJ07tAMATz1/Gkb09Ndu1ttEa4Vzl6e1MoLczUVHOi6wUyq2MVz/USB27co/u6MLp/pGavviJ5y/jjvao7Xp+fG8Pek3+VffBdn7x0K5unO4fMd7v39mFb7847OqnG9FJI3iJHRtbI+jtTCyKT1uqcS0mTuM/cN8W3N4WgUpUbGyLVD3X7ezQ7vn5P3V+BId2dVeU27+zC32diQodNBrTa42jUd0vZL259dG7NmHEYr28rreFjncpudF2fVcygiN7KvV4ZE8P7kq699+bStjW662h92bYZzP6603G7ceXjDelv0btYKnt50bZa739Wufh1PkR2/n82vOX6xqHtd0nnr+MO9ZU77v+47/urWvOzfujlnB9+wA7X3hkbw/61iZq9vXojtp7Mmv9evRFqWY56rJRf2elGWOr90zgwH1b0BrmKtb+HWuq86yP3rulIl+w5mt2e/XH93qLVc3Ke5YCO995aHdl7nl0Xw/6OhOOetq/swu96xLoao86lvn8e+82nuufbWyLVPV9eE9l33qet39nF2I8axtv+9YmcOyhuz35NsrSwBDi/h93GYbhUb7srRuAcXxf64B47vt+nwAwQwj5Y9PnnwUwbbqQroUQ8u9Nzz8NIE8I+dzc+zUAZELIdYZhQgC+C+AzhJDTlv4+DKCXEPKhuQvpHiSEPOQm4/bt28m5c+dcx29Fv1FxIle+aVO/SdHpc7e661eHMXy9aNy0ud7DzfD6zbvpjIBkgkd3KlHXzcpu8lnLJePlG3JniyICLrdHurXt9Zne12S+8rWbrG4y63U7EyFcHM8inRGwbu72zamCWFMWQoCJXHleNrZGoJFKeQDg2kwB03kJgqJCUjS3+Vvwd1+72SrDMHj4q8/X1d6Tv38Paq19SvNpZO6A8vw1Ws9l3ptqp4B3P9RIHfMtwmGOhayWb8v14os7EyFcmsyhICqQVYK8qKAtGkRPMl51YZPug2cKImI8B0nREOZYFCUZDONDUVKwJhqEohKkcwLWJULoXuvspxvRSSN4iR3W25+9xCQnmjiuptmpefyZkoxwkEXYz6I1xiEVC+Hn0znkRRUlqXwzfUuEgwaClnAQfhZIZ+ZuzQ5zICBgwGCmKCHM+Y3bmq06aDSmu7EQ3TeSK3jpQ5JU9I9mMJET0BYNoigpWB3mFmW8S0md416QrdrZabYk4JV0wbil/q5kxPUyOh1BUHBhLDN/u30q4XoZnU4z7LMZ/ZVKMi6ks/PjS8Y9Xc7U7Jx6seo1isf+Ft1O6x2ndR62tEUxOJ7DeFZAR5xHTzKO0ZxQt96s7d65JobXpvKYKUoQJA3JVUG8Kel9zq9MFXBtpoBwkIUPDIqSghgfQEmuuQ8w0H2hPra+tQnjMjo7/Vn3YpKqgXPZk1nrL4WdLRFNz1HtWI66bNTfWWnG2Lzu+9dEebC+8ld26WcMEY5FgGVQlDQUpPLXELREOGQFCa2RYIV/tuarLREOgqxhKi9i3aoQelzy7kb1sBT+FKjPThVFw8tjGYxlRER5FusSPLKCgjFTTPP5mHm5o0FcL8kYz4mIBf1Ym+CxsS0KTSOGr7Q7L9E0gsHRDEYyJbRFguhIBNER4TGQziKdFdARCyLMsbhekiEpGlaHOeRFGQGWNfJfcx/meKvrdabgft5EWVScE1cPh8PfBPAKgPcDOALgAwAuEkL216j3qwD+D4ALAPQvEflTlL93+CkA6wFcBfAQIWSGYZgkgHMof42FBiAP4E0ANqJ8yMyi/D+dnyKEHJnr4wiAc4SQk3OH2P8N5e82ngHwPkLIZTcZGwkSFEoD0MPhBll323qMDr9Rd721nbdh5I1rTZBocbnVDocplEWA2illpbDoh24UShOgdkpZCdDYT1kJUDulrAQc7bT2fxsANhNC3sswzF5CyBMMw3wd5UNfVwghP3TpeKdN+TTK3ylspR/lA1+7Pg6aXgsA3ltLLgqFsnIYHX6j4UNQCoVCoVAoFAqFQqFQKBSKO17+v7089/v63EVwCQDtzROJQqFQKBQKhUKhUCgUCoVCoVAozcbL/xz+a4ZhVgN4DMBJAFEAn2qqVBQKhUKhUCgUCoVCoVAoFAqFQmkqrofDDMP4AGQJIbMAfgDg9iWRikKhUCgUCoVCoVAoFAqFQqFQKE3F9XCYEKIxDPPvUb5A7pbAfPtlQVKwqTUCjQATufKtsutXh3FttmjcMmt9b71Z0drehpYINrSU60wXRIQCLAqiCklVsTrEAQAKkorJnIhUgkevzS22eruvTxds5Uglyjfb6jJvbI0AAF6fLmC6ILrecqvf7DuWEZBKhNCdihu3XJrHqLdn7m+maN92PbJ2JkK4NJnDbFGGIKu4vTWCTWuirrdVOrVfa6x2dd1uKLXOY60biSkUijN2vgZA1Wfm24bN6zXM+SGpKlojwQqf0h4r34BcbqPaF9r5gCtTBVydKSAa9CPMscgJSpU/EmUVa2I8JFUFx7LQiIaAz4eMICMvKoiHAkjGeNxmkkWXcU006Ooj3XDyUebPzWN287267748mceVqQL4AItIkEVRUpBKhKt8mlf/6DSfTnO3XG8hFgQFF8YymC3JWBUKIFuSEQ8FkBNkhDi2fHtzXkSc94P1+TBbLN+grYGgNRKsupX76nQBo5kScoKCtatCYBlg5HrJqNMSDsLPAlM5CYKiQpQ1bGh1ji1O8+kU2/VnTrF7qeah1tyvBNtYLjR6S32j9WqtayckSUX/aAbprIBU3DmXtaKvwXRWRDIeRG8qAZ6v/UeOxZKEgXTOGF9PMobwXE7tRqO2t9Tja7S/RudvOVFvnj6RE5EpyWgJc/CzDGYKEsKcHx3xINa3OO8DrD60MxHCxfEspgsi4jwHSdYQ5f0oKQpmCzLaY0H4WQY+hoEoaxAUFZpGEOcDKEgqIsH5HMUss6JoGBzNYOR6CS1RDqEAi8m8iFWhAFRCIMka4nwARVlFMs4jJ8gYzQjoXB0C72cxkRMR9PuQESS0Rnhs7YhhOFPyHBeob11+1OuH3Mqbn5lzYLMtpRIhrAr7MXp9cWKutU9FJbg2UwTP+RBkWbRGOXSuCmP4ehHT+fl857aWMCRFxXhOQCjgR0FUsDrCISdICAUCyAoy1iZ4AMBMUUZBUtAWCeJ6SUKcDyDGs5gtKIiH/BBkFbNFGXE+ULXWb4Ucw7on8LNAOiMiK8hIhMo6kZXyvER5FgCD60UZbdGynwQBpvKSMWdr4hxmCzLGsyLiIT9kRcPaVeGKMyyO9UGUNTAMMJkX0R4LIuj3YSxTruOfy5NbwhxUQhD0s5BUFS3hYNWeBYBxzpIVyjm4oKjoXBWGqhG8MVtEJOiHqKhYa7NfoSweXr5W4nsMw3wcwJMACvqHhJCZpkl1g9A0grOvjmNoPI/jZ4awOszhkbdtwPEzQxBkDRtaQ/jIji48dmLA9j0f8OHYQ3fjge6ksTE3t2eu86WzQ/jgPZtQlFV846fX8MF7NmF1RERJJjh0ctBo78jeHuzrW1uRBGoawbODaRx46qUqOawy8wEfvvz+t0BSCD7z7EU8vH09vnh2yFZeRdFw4vxIxXg++54++BgfPvbNl6raO/DUS0Z/3/jpNdu279/age9eHPck6/YNCTxyzyaMzJYq5P/8e+/Gu3qSjsmgnS6+dHbIdax2de3K2NmFW1kKhVIbO19zdF8Pgn4fPvGt/orP9r15Hfx+n+16fXRHF86+ksb7fmlDRVv7d3bhOxfG8K7elOuatWtz/84ufO1HVzFblPCX7+lDOiPg2HOXqvr8wC9vRDorVLR/4L4tSCV4fO67r+LqdAl8wIeP3rsFoYAP/+X/Xqnpk6w4+SirX7XK7VTmy+9/C0SZVPjz/Tu7EA6w+LMTA/jkA1sr4pcX/+g2n25zt9z8pyAoOHlhDH/1/erY8eiOLjx57hre94vrbe1Kf67rD4BtzDhw3xb83f99HbNFyajzx/duwWROrLAxpzhk1WGt2M75GfzR139W87NmzkOtuV8JtrFcKJVknBpI4+DJ+XV2ZE8PdvckXQ96G61Xa107IUkqTvSP4uAzpv5sclkr+hq0yrmnN+V6gFosSTg9MF5Vb1dPh+sBcaO2t9Tja7S/RudvOVFvnn55soBjz12y3Qvt39mFro4odtzZUZUD2PnQI3t78NRPr2LHXcmKz82x9vG9PSBEw3RBtt0HWWODppGqOTm0uxssCB4//TJ+91c2oSRr+ML3KsdgN55yLvIaHvrFDRW24XXPR1ke1OuH3MoDMJ7Vsp9Du7vxP35yFZcm8guyC7M8q8McfudXNlbkM/t3diHCsehI8JjMicgJSoUcj/3GVhREFV/43qWqdfPBezZhKifgeqmyzkfv3YKv/8tVfOgdm/HdgTH80u2tjmvdrJObdR3Y2cSh3d34yj+/ZuxFPr27G//5n1+DpJAqWziypxt/9f35sn/6rrsQmvLjUya/8uiOLhw/cwnv+6UNxhnLk+eqfd6h3d22c6LPqV7vfb+43vCjX37/WwCgKmf+s/9nKy6N5/HZf3y1op3HLPsVyuLiJTt4GMCHUf5aiRfmfs41U6gbxevTBfQPZwzDfHBbp/EaAHb1rTMCut17QdZw4KmX8Pp0wbY9c51dfeswXZRw/MyQ8XpVOGgcDOvtHXxmAP2jmSo5dQdglcMqsyBr6B/O4MBTL2FX3zpjAdvJOziWqRrP0ETeOEiwtmfuz6ntwbGMZ1kfued2vDaRr5L/Y9+cl9FuzuzarzVWu7p2ZZzm0akshUKpjZ2veezEAIYm8lWfDY6V/Z/dev3i2SE8cs/tVW0dPzOE33v7HTXXrF2bx88M4cFtnRBkDa9N5I0k19rnlelCVfvHnruEoYk8dvWtMz77wvcuYaogefJJVpx8lNWvWuV2KtM/nKny58fPDGG6WJbPGr+8+Ee3+XSbu+XmPy+MZXDwpH3s+OLZcoxzsiv9uT4mp5hx7LlLxhzpda5MFapszCkO2c2nW2zvH854+qyZ81Br7leCbSwXLqSzxsEiMJcjnhzAhXS2KfVqrWsn+kczxmGV0Z9NLlsl59warJKzRn8D6ZxtvYF0zrVeo7a31ONrtL9G5285UW+ervtSu73Q8TND6B/O2OYAdj704DMDeOSe26s+N8faTz0zgDAXcNwHWWOD3ZwcPjWIcDCAXX3rMFWQjEMy8xjsxqPnIlbb8LrnoywP6vVDbuXNz2rZz+FTg/i9t9+xYLuw9mnNZ46fGcJUQYKsEEzkxCo5JnKiYfP6Z/q6mS5KGMtW1/nC9y5hV986HD41iN/+1U2ua/1WyDHsxnj41GDFXuTTc+/tbOHgycqyUwXJOBjWPzPvt3TfYudjnObEXF7Pp3U/2j+csc2ZJ/OicTBsbedmm8PlhJfD4a2EkE3mHwBvarZgN4LxrACNwDBChpl/7eU9oDs6wbY9cx2GgfFMfz1TkG3bG88KVXI6yWEnk7kfN3nHMoJjXafPzOOxa9vappusJVGx7c8soxUnXdQaq11dp77s5rGWXBQKxRk7XyPIGjSCqs/SmXl/alenJCn2n4v2n3vxAczcP0Q7rXs3X6URGPWtn9XrQ5zkc9Kf3q9TmVoyW+OXV3md5Kk1d8vJf6azomvs0D93siuz/txihnmOzHmAtZxdHKo3ttutJ7vPmjkPteZ+JdjGcmF8zkbNlHNEsSn1aq1rJ9IOc2rNZavrLe34GrW9pR5fo/01On/LiUbzdDefaJcDOJV38/f668JcmVqxYyInOM5JQVKq4kGtvZ1T/uN1z0dZHtTrh9zKm595tZ9a/dUjv9u6KzjkzW65kkbcnwuyhusOZyf6Wr8Vcoxaexnzezc/peO495EqfZ1TW05zYq1n3mvVaxs32xwuJ7wcDj/v8bMVT0ecB8sAfGBeLebXXt+3x3jH9sx1zM9YBmiJBGzLdsT5Kjnd5LA+M/fjJm8qEXKt6/SZW9t2bTrJGg76HfWly2jFTRe12nGqa+3LbR6d5LpZWXfbejAMU/fPutvW32jRKcsIJ79g/esgPuBDMjHvT+3qhDm//edB+8+9+AAyd4DmtO7dfJWPgVHfOq56fYiTfE760/t1KlNLZmv88iqvkzy15m45+c9kPOgaO3T9ONmVWX9uMcM8R4Q4z4ldHKo3ttutJ7vPmjkPteZ+JdjGcqHDZKM65Rwx2JR6tda1Yz2HObXmslaSSzy+Rm1vqcfXaH+Nzt9yYiF5upNPdMoB6skjzH48wvtd2zDHBqc5iXB+23hQazx2+Y/XPR9leVCvH3Irb31Wy35CnL9mf/XK77TuIrx93uyWK7GM+3M+4MMqh7MTfa3fCjlGrb2M9X2tso57H67a19mVc5oTfc7Mv/X+6rWNm20OlxOOh8MMwyQZhvkFACGGYd7CMMy2uZ93AggvlYBLycbWCHo7E9i/swt8wIenXxg2XgPAqfMjOLqvx/E9Hyh/j43+xdrW9sx1Tp0fQUuYw/6dXcbr60URh/d0V7R3ZG8P+tYmquQ89tDdtnJYZeYDPvR2JnDsobtx6vwIHt3R5ShvdypeNZ7N7VF8/r1327Zn7s+p7e5U3LOsTzx/GXe0R6vk//x752W0mzO79muN1a6uXRmneXQqe7MzOvwGHv7q83X/jA6/caNFpywj7HzN0X096GqPVn3WnSr7P7v1+uiOLjzx/OWqtvbv7MLf/ODnNdesXZv7d3bh2y8Ogw/4cEd7FAfu22Lb58bWSFX7B+7bgq72KE73jxifffTeLWiLcJ58khUnH2X1q1a5ncr0diaq/Pn+nV1oDXM43T9SFb+8+Ee3+XSbu+XmP3tTCRzZYx87Ht3RhdP9I452pT/Xx+QUMw7ct8WYI73OxrZIlY05xSG7+XSL7X2dCU+fNXMeas39SrCN5UJvMo4jeyrX2ZE9PehNxptSr9a6duxvbQJH9lr6s8llq+rNrcEqOWv015OM2dbrScZc6zVqe0s9vkb7a3T+lhP15um6L7XbC+3f2YW+zoRtDmDnQ4/s7cETz1+u+twcax/f24OiKDvug6yxwW5ODu3uRlGUcbp/BK0RDh+9t3oMduPRcxGrbXjd81GWB/X6Ibfy5me17OfQ7m787Q9+vmC7sPZpzWf27+xCW4RDgGWwJhaskmNNLGjYvP6Zvm5awhyS8eo6H713C073j+DQ7m78/Q+vuK71WyHHsBvjod3dFXuRT8+9t7OFI3sqy7ZGODxu8Svm/ZbuW+x8jNOc6HNqzqd1P9rbmbDNmduiQXzi1+909amUxYch5n8qMD9gmH8L4LcBbAfwUwD6/zfJAniCEPLtpRCwmWzfvp2cO1f59cn6bbfjWRFFScHG1gg0Akzmy7c/rp+7iX4iZ//e7hZuc3vrWyLGTY8zBRF8gEVBVCGrKlbNXZxRkFRM5kUk4zz6HG4k1m+ltJMjGS/fTqrLbL65dqYgIuByc61+s3E6IyCZ4NGdSsDnYyr6Mrdn7m+2aN92PbJ2JkK4NJnDbFGGIKvY1BrB7Wuinm5ttbZfa6x2dWvdgmyexzpuylzwt6Xb2arROMPg4a/W95/5n/z9e+C09t1opK+V1N9Ss5DxNUEvTbVTK3a+BkDVZ+aLc8y38YY5FrKqoSUSrPApa6I8WF/5T3HtfKGdD7gyVcC1mQKiQT9CHIucoBi3lev+SJRVtEWDkDUNHOsDIQR+nw9ZQUZeUBEL+ZGM87htThazjG3RoKuPdMPJR5k/N4/ZqYzZd1+ezOPKVAE8xyISYFGUFaRsbv/16h+d5tNu7ry0VYOm2akgKLgwlsFsScYqPoCcKCMWDCAnyQj5WfABFlN5CXGeBavfwhwJgoBU3UivaQRXpwsYzZSQF1SkEkGwPgYj1wW0RDgQELSEg/CzwFSufHu3pGiuscVpPp1iu/7MKXYvcB48U2vuF9E2lhsLGoSdnZZKMi6ksxjPiuiIB9GbjLteKrfQerXWtROSpKJ/NGPcDu+Uy1rR16AhZyrhelmbTrEkYSCdM+r1JGOul9HpNGp7Sz2+RvvzOH+LbqeLSb15+mROxPWSjJYwBz/LYKYgIcz50REPYn2L8z7A6kM7EyFcHM9ipiAixnOQFA2RIAtBUXG9oKAtxoFjy38dJ8oaBEUFIQSxYABFWa3IUcwyK4qGwdEMRjIltEQ4hPwspgoi4nwAGghkRTPaSMZ55AQZYxkB61aHwPtZTObLcuaEcvzZ2hHHcKbkOS6sYN+6pDnqUlKvH3Irb35mzoE7YvO2lIzzWBUJYCyzODHX2qeiErwxW8T/x96bh8dRXXn/3+p9UXdrs6S2ZMkIy5sWG0chQDCZ2EBIYsBhMTNMIGHgdTIzxE7Iwm8I4AGcZMgEMxgySSC8CZDJYAiJwQz4JbGTQIYlmMUbNsjIlpCtXXK31K1eq35/tKpU3V3VXVW9S+fzPHokdddy695zzzn31L3nmgw6WAx6VJWZ0FBuQ99pP0YnZ/ydhgobQpEohiYCsBgN8AUjqLCZMBEMw2o0wBsIw+20gGGAMX8YU8EIKsvMOD0VgtNihMOix2l/BA6LAYFwFOP+MJwWY1Jfz7OPURA5TRwTGPTAgCcIbyCMcqsRNU4zwpFYu9jMejBgcNofRlVZTI9xHDAyGYLZGGuzeU4Txn1hDHqDcFoNiERZuF22uBiWUa9DMMKCATA8GcS8stjqmH5P7ByDTofT/hDKbTGf16TXIRxlUWEzJ41ZAAhxlolAGC6rEcFIFPXlNkTZWLntJgNC0ajkeIVQjWzlyQaHhQMY5kqO457JepGKgGI1EsSsg4LDJXK/fDOXg8MEoRGSU6JUKOqgG0FMQ3JKlAJk+4lSgOSUKAVk5TTt6//ZGhgmCIIgCIIgCIIgCIIgCIKYy6RfG0YQBEEQBEEQBEEQBEEQBEHMOig4TBAEQRAEQRAEQRAEQRAEMQfRFBxmGOaibBeEIAii0NQvaATDMKp/6hc0FrroBEEQBEEQBEEQBEEQqkm/Ra40jwKY1dEQftdHfmdgLTtbSl0DiO0gO+oLwjS9g6zbFdtNdMyf+jO5cqgpa+KxjRWxXSe1nCu1O2ridUd9QViNeviCUfhCETRN78QOzOxKKf5cagdzqboamkhdhvnlFpz2hdHvDcDtsmJZrQP9E1MY9AThDYZRbo3tPDy/XNn1EtsvE7koCnQGMEwJljvHnOr7SPNGb4Q0/O7sA94g6qZ3ZzeZ9JL9H5jRC/5QBJV2M4KRKPQMA08ghOoyCxxmAwZU9j9+x/Z+T0wftLqdwo7t/C7wA94A3E4LWuucODURSNJlA54AzAYdxqd3Sa51mrGgInb/SITF0UEvxv1hBMJRNFfZcca8spS6pFB6g2U5HB/xoWfMB3uaHdx7Rn045ZnCRCCC+eVWLK9zSu10P2vg5cQ7FYLZaMDQRBDVZSYYdQxYACadDuNTQZSZTdABiHIchiaCqHNa0D7fBYNBl7Kd5eSAZbmU9lCqzRrKZ2w3v6P9KQn5FqNEDnMhq5n4KMViY4ulXP6pEA4NTGDQG0St04y2OgdsVlPOzkulO1MxNRXGwQGvcL/2OiesVmPO7idlZyyW9EMcrffTKg/5vl+po/S5xcfZpne0n1dmTvLvgWQfnmU52TYRX7emzIxAJIrBidg9pkJRNEroavHxoWgUw5MhTIWjmO+yYkmNAyc9UxiZDGLMF4LVpEeZ2QB/KAK30wq9nkG/J71OlxufKLHthDSF6mNa7qtmPM5/F4mweK/fg1OeAJxWA+a7rEL/qHFYYNADAx75MblSIhEWh0/F7uOyGWAx6DE8GUSdMybHOh0jlE88pq9xWKDXAf2e+L/LbQZMBKIYmQyi3mVFhOUw7Aui3GpEOMJifrkNTZXKYxmZUMx6mGU5fDTuw6AniBFfEPXlNkFvSMVTxHXssBgwEYjAGwijpsyMKIfYmMhlQZXdJLQJLyOhaBROsxH+cFQYJ/WM+dEz5kO51QiOAwYnAqguM8Nh0WMyGEWNwxwXl5GyfbwvPDQRxFQoArNRD+9UBHUuS8bjj2Juu2JD1nNiGOY5ua8AVOWmOMUBy3LYfXgAtzz1LgJhFhajDts2rMQlrXWKBUnqGg9dexZCEQ737j6CazobsX1vFypsJlx/bhOefLM35Wdy5VBT1sRjm6qs+NqaFty+85Dqc8XHApC87oN7u/AP550BfziKB/Z0xdUDAHQNTsZ9Lr43fz+pupI6R1yGxTVl+LtPNOGuXYeF8tz2uWUY84Xx0z8fU329xPbLRC6KBjZCQVAi5wQCETx3sB93PjejY+6+rA2Laq14o/u0Ir2waU0LduyL6cId+97D3368EY+/1oNxf0hR/4tEWOzcfzJOz21d34b1K+rBshx2HjiFO5+NL9+P/9SFntEpSR3Jl+ern1qE+eU+nLuwGv/vyAD6xqfiyn3f1Svx2TZpXVIovSGlxzevbUFLbRnWLKmNsyt73x9Magu+3mZjgJiXkyf/2oMrP9aIu3a9LTz3lktboWc4hKIcolEOuw4cw5WrGnHX84dn5ObyNtQ6TfjKE2+ntGmJcnDxslr8qWtI1h4CyfKzeW0LGiqs+NFL7yMU4ZLsmFQ7KfEVsuH7JJKJj1IsNrZYyuWfCuH5Q4NJ+nRdW23KQK/W81LpzlQ6YGoqjF2HBpLud2lbXcoAsdb7ydmZy9rdKQPEWu+nVR7yfb9SR+lzSx33jQsXw2rU4fsvHk3pw9939UqwHItv/+ZAUpvodEzSdW/77FJMhVnc/4cPFI2FvvqpRcJYxGLU4d+v6sC4LxRXrs1rW2Az6vHdnYfwtx9vxIsH+/HZdresTperF5OBwc2/fielbSekKVQf03JfNeNx/rsLl9TguYOnBN0jJZtbLm3FT/98DD2jU5qfX0rHbV7bIvjsW9e3odxmxM2/fkdyDC4+dvPaFvy1exQXt7lx167DqLCZcMMnF2Lb72f63qY1Lbj92UNCzCGTsqejmPUwy3J45dgQTp0OxrXp1vVtuKx9Pv7w/lBcPEVc32J9I9UmWy5txX+/0YMPhiax5dJWPPNWL9YsrYu7ztb1bXhwb5ekP7rl0lZUWvU4NuRLKpvY9vHjju5hH/7rjZ6ksmYy/ijmtitGUtXwagA/A3CfxM9k7otWOE6M+gQBAoBAmMUtT72LE6O+jK5xoM+DW556F+s66gWBv2JVAx7Y05X2M7lyqClr4rHrOuoFBa72XPGxctdd11GPUX9IUBLiejjQ50n6XHxv/ppS9ZKuDDddcKaggPjyhCMc7tp1WNP1EtsvE7kgZinTM7HV/sx2DvZ7hAE7EOszdz53COEIo1gvbN87owvXddTjgT1duGJVg+L+d7jfk6Tnbt95CIf7PThwyiMEhsXlW9dRD0BaR/LluGvXYUxMxWYddw1NJpX7m0/L65JC6Q2psjywpwsH+jxJdkWqLfh6m43wcnL9ec1x9iMQZnHXrsOwmYwYmghi1B+KHfN8/DF3PnsIE1PRtDYt8fvD/antoVybdQ1NYl1HvaQdk2onJXKYC1nNxEcpFhtbLOU6NDAhqU8PDUzk5LxUujMVBwe8kvc7OODNzf1k7MzBNOdpvZ9Wecj3/Uodpc8tddz9f/gAI75QWh/+m0+/i66hSck2kbruiC8kBIYTyyQ1Fkq0JV1Dk0JgmP/sgT1dGPWHBP/mpgvOTKnT5erlQJ8nrW0npClUH9NyXzXjcUE2TsXrHinZ5MfISsshhZSOE/vst+88JMiplO8iPvaBPV348vlnCOW8YlWDEBjmj+f9cT7mkEnZ01HMevjEqA8TU9GkNr195yEcOJUce+K/T9Q3Um1y167DuOmCM4W/rz+vOek6fP3Lne+0mSXLJrZ9/Lhj2+8/kCxrJuOPYm67YiTVmqvXAfg5jvtz4hcMw7yfuyIVnkFvQBAgnkCYxdBEAM3zyjRfg+Vi12EYCN/xf6f7TK4casqaeKyS6yupE46D5HUZZuaZE+uBP1/u3vz9pOolXRmmgpGk8vimP9NyPXG5M5WLOctsT2NBM7ElGfAGZfuMGr2QqBN5UVLS//o90rprwBNAmOVk7wfI6wj+c18oggFvIKVukNIlhdIbcnqc5ZBkV+SeacATwIoFeSty3uDlJNF+ADNtzctoqmMSP0u0aYnf93u0yQ/LIa4fJH6f2E5KfIVs+D6JZOKjZOP+2aBYyjUoo08HvcGcnJdKd6bSAfm+n5ydyd3zaZOHfN+v1FH63Knsmhg5PZt4HN8m/lA06Xg1ulrKf0hVBv74qZC0feHlROnzStl2QppC9TEt91UzHue/G1A4/hcP07Q8v5yOE/sqvJymK0MgzOK0L5x2zJ44LtBa9nQUsx4e9AaEOIcYcdvL1Z9Y36Q6Rup48TGp/NHhSWkbLbZ94nGHXDm0jj+Kue2KEdngMMdxn03x3QW5KU5xUOu0wGLUxQmSxahDjcOS0TX0TOw6/PX475R+JlUONWWVOzaTc/ljpb4TP3NiPaS7N38/qXpJVwab2ZB0nN1i0Hw9cbkzlYs5CwVP5yR1TrNsn1GjFzgu+bf4Wqlwu6yS16xzWRCJcrL3E/8vVx67yQC304KuwQnV+rEQekNOj+sYJNkVOX1X55qd+o6XEyn7wbc1v/os1TFipGxa4jlulxVH+r2q5UfHAFE25swraSclvkI2fJ9EsuGjFNrGFku5amX0aa3TnJPzUunOYrqfnJ3J3fNpk4d836/UUfrcqeyaGDmblngc3yYOi1H1OCDdGCtVGaJs7G+bSdq+8HKi9HmlbDshTaH6mJb7ahmP1ykc/yf6vmqfX07HiX12sZymO7bcHt8H040PMil7OopZD9c6LRj1hVK2Pf9/4veJ+kbqGOu0b5tKP3GcvD86r0zaRottn3jcIVcOreOPYm67YkQ2rQTDMI0pvlud7sIMwyxgGOaPDMO8xzDMYYZhNk9/XskwzO8Zhuma/l0x/flShmFeYxgmyDDMt9JdR+J+LoZhdjEMs3/6uBvSlVGOhVV2bNuwMk5At21YKST813qN9gYXtm1YiV37T2LTmhZYjDo881YfNq9tSfuZXDnUlDXx2F37T2Lr+jZN54qPlbvurv0nUWkzYfPalqR6aG9wJX0uvjd/Tal6SVeGR17+EFsubY0rj1HPYMulrZqul9h+mcgFQcwl2t0u3H1ZvI65+7I2GA2cYr2waU0Lnj9wUvi9eW0Lfvt2n+L+1+p2Jum5revb0Op2oX2+C3dfnly+5w+cBCCtI/lybLm0FQ6rHu3zXVhUU5ZU7vuultclhdIbUmXZvLYFHQ2uJLsi1RZ8vc1GeDl57NXuOPthMcZypvlDYdQ4zKiymWLHrIs/5u7L2+Cw6tPatMTvW93OlPZQrs1aasrw/IGTknZMqp2UyGEuZDUTH6VYbGyxlKutziGpT9vqHDk5L5XuTEV7nVPyfu11ztzcT8bOtKc5T+v9tMpDvu9X6ih9bqnjvnHhYlTbTWl9+PuuXomWmjLJNpG6bpXdhG9cuFjxWCjRliyqKcNtn12apM+rbCbBv3nk5Q9T6nS5eulocKW17YQ0hepjWu6rZjwuyMZ8V5zukZLNLZe2Cr6v1ueX0nFin33r+jZBTqV8F/Gxm9e24Jd/OS6U85m3+nDLRfF9j/fHt65vy7js6ShmPbywyg6HRZ/UplvXt6FjfnLsif8+Ud9ItcmWS1vx85c/FP5+7NXupOvw9S93vtcflCyb2Pbx445bLlosWdZMxh/F3HbFCMNxnPQXDNMN4KcA7uM4Ljr9WS1iOYeXchzXmfLCDOMG4Ju47y0AAQAASURBVOY47m2GYRwA3gKwHsCXAYxxHPdvDMP8fwAqOI67lWGYGgBN08eMcxz3o1TX4TjuvYT73QbANX2teQDeB1DHcVxIroydnZ3cvn37JL/jdzXkd9DUsquh1DWAWO6TMV8QxukdI/ndOsf9qT9Lt7u4krImHttYEdvhU8u5UrujJl53zBeExaiHLxiFPxQRdvYFIOzOLv5camd3qboankxdBrfLgtO+MAa8AdS5LFhW60T/xBQGPUF4g2GUW00IR1nF10tsP5VykXE+hVSyyjCM6lm5O75ynuaZvCVx3j9eALCR9AdKUBLPl8F5cjofOZJTfhd5Ydd6twsmk16y/wPxeqHSZkKIZcGAwUQghCq7GQ6LEYMq9TK/Q/yAJ6YPWt0uYVODUCiWN5jfwbatzolTE4EkXTboDcCo1+H0VAhOsxG1LjMWVMzsAn100ItxfxiBcBRnVNnRPK8spS4p1CYILMvh+IgPvWM+2FLsaM6yHHpGfTjlmcJkIAq3y4zlonorIDnTp7yceAMhmA0GDE8EUWk3waRnwAIw6XQYnwqhzGycnunFYWgiiFqnBR3zY3WTqp3l5IDfoVnOHkq1WUP5jO2udcR2tu+XkG8xSuQwF7KaiY9SLDtKayxXRgWXklP/VAiHBiYEfdpW50i5qVym56XSnamYmgrj4IB3Ru/XOVNuRpfp/aTsTKrN6DK9n1Y5zff9FJJ1Oc0WSp9bvBO9zaRHOMqiusyc5N8DyT48y3KybSK+f7XdjGAkiqGJIKwmPaZCUUldLT4+HI1ieDKEQIhFXbkZS2ucOOmZwshkEOO+MCwmHcrMBkyFIqh1WmHQMxjwptfpcuMTJba9hMnpWKpQtkfLfdWMx/nvIhEW7/V70O8JosyiR325Vegf88osMOiBAY/8mFwpkQiLw6c86PcG4LAYYDXqMTIZQq3TjFa3CzodI5SvzmmJK4NeBwx4Z/7u9wRQbjNgIhDFyGQQ811WRFkOI74gXFYjIlEWbpcNTZXKYxmZoLCtciqnqcr20bgPg54gRnxB1LusaJ32S6XiKTWOmTp2mA2YCEYwMRXBPIcJUS7WDm6nBVVlJqFNeBkJR6NwmI3wh2OxqcYKG3rG/Ogd86HcagTLAYPTOtBhjcWA5jnMcXEZKdvH+8LDEzE5NBv18E5FUOfMfPxRrL5lAZF9+FTB4QoA/wbgPACbAbQDuAXADwH8hOM4VvJEuRsxzLMAHpr++RuO4/qnA79/4jhuiei4fwUwyQeH5a7DcdzvEz7/FwALAPwzgIUAfg9gcapy5tKhIQgRFBym84rmvHwHhwkiy5CcEqVC0QbdCEIEySlRCpDtJ0oBklOiFJCV01Q5h8cBfGU6jcMfAJwCcA7HcX2q784wCwGcBeANALUcx/VPfzUAoFbjdRJ5CMBz0+V0ALhGKjDMMMxGABsBoLFRNnMGQRQcklWiFCA5JUoBklOiFCA5JUoBklOiVCBZJUoBklOiWEiVc7icYZifAbgBwCUAfgPgRYZh1qi5AcMwZQCeAfB1juO84u+42BQ22WlsSq8zzWcAvAtgPoCVAB5iGCYpwRnHcQ9zHNfJcVznvHnz1DwKQeQVklWiFCA5JUoBklOiFCA5JUoBklOiVCBZJUoBklOiWEiVvONtAF0AOjmOe4njuK8DuA7AVoZh/lvJxRmGMSIW0P0vjuN+O/3x4HQ6CT6f8JDG6yRyA4DfcjGOATgOYKmSchIEQRAEQRAEQRAEQRAEQcw1UgWHL+A47kccxwm7OnEc9y7HcecB2JvuwgzDMAAeBXCE47htoq+eA/Cl6b+/BOBZjddJpBfA2ulzagEsAdCdrpwEQRAEQRAEQRAEQRAEQRBzkVQ5h2VzC3Mc94iCa38SsZnGBxmGeXf6s9sQ2+TuKYZhbgTQA2ADADAMUwdgHwAnAJZhmK8DWA6gQ+o6HMe9wDDMV6fL81MA9wD4JcMwBxFLsnwrx3EjCsqpCPFOuLXOmR1uxTvUL6q2gwUT2z3cqXwnRKlr8zuYS32u5BoNLiuODHrR7wnA7bKi1e0UdgiVux6/i7L4HKndcQe9AbhdsR1GE59VTZnF1xz1BWGa3kFT6npS3wMQdnj3hSJomt5dFUBSGaQ+S9wlPt015viulgShCX4X+QFvEHUpdpFXqzvEpNNdqY5dVutA77gfx0d9cFgMMOp1iEY56HQMxnxB1DqtWDKvDMdGJ+ELRhCOcvCFInC7rFhel16vFgKW5XB8xIeeMR/sCbuWK6lntW2hpv6LHX6n7ZOnp1DlMIPjogCnw0QwgnKrEQwDjPnCsBr1MBoYOMwGLKmNZbBSaj+l7JLNZEAoGkWV3Sy583im8pWt62hBLB/zy61wmA0YKKL+Ukr4p0I4NDCBQW8QtU4z2uocsFlNac9TqocT0So3+T5vaiqMgwNeoV7a65ywWo1pzwuFojhwyiPszN4+3wWTSZ+z87TqykL233yQ6vkyqTMpOwhAGFcwmLHzauyWuLzlNgMmAlGMTAZRX25Duc2AU6dj46RIlEPvuB8uixFGA4ORiRAsJh3Mej2qykxoKLehd9wvPHdjxcz/vE2YV2ZGlAXG/EGYdDqM+UOwmQyoc5kRicaPw/hnk6rH2S5Dcwmt+keOXMiG1Pja7TAJ9qvOaUaNw4ShyRCsBj08gTAmAhHML7dicXUZ3h+eQL8ngOoyEww6BhPBKAKhKMptRgQiUcx32dKO17U8Vyn1k3QxFPExg94AahwW6Bjg+OiMTpzvtOLooBenPAE4rQa4nVY0yTwz7x8P+4JwWozwBSNYWGmDPxzFuD8MfygKl9UAo04HfzgCh9mIMX8IdrMBwXAULpsJAIdQhMPIZDAuPpUoK02V8bqxmNthtpHeM9QIx3F/gfxOeGsljh8A0CBxrOx1poPC/N+nAFysvqTpYVkOuw8P4Jan3kUgzMJi1OFn162CdyqCvvEpPLCnCxU2E64/twkP7OkSjtm2YSUuaa1LGxxNvPa2DStx8bJavHRkMOlzqeslXqOzyYUNH2/Cnc8eEs7996s6oGN0+ObT0teLRFjs3H8St++cOWfr+jasX1EPg0EXdw+5Z1VTZnG57919BNd0NmL7XunrSX3/0LVnAQC6BifjyvHQtWchFOHiyiD1GX/9P3UNKbqGkrYkCCKeQCCC5w72487nZvTK3Ze14bJ2d1xgQk4PKulz6XRXqmObqqz42poW3L7zkKDXnnyzN0nf/PDKDninHVexrti6vg3zHCZ85Ym3i0ZXSNXl5rUtaKktw9+01KTV0WrbQk39FztS8vFPf7MIW547HFeXj7/Wg3F/CJvXtsBu0qPv9BQmg1F893cH09pPcZ2aDAxu/vU7wmeb1rRgx75e3HrJMlzSWgcAmvuFmEz6V6ZIyYe4DgvdX0oJ/1QIzx8aTNKn69pqUwaIlerhRLTKTb7Pm5oKY9ehgaTnu7StLmWAOBSKYueBU3G+8t2Xt2F9x/yUgRat52nVlYXsv/kg1fOxLJe1OuPtIADc8/x7SXZeqd0SX3txTRn+7hNNuGvXjI3YcmkrXjrUj3MXVWPb7z9Ahc2EGz65ENt+/0FcWewmPSrsJvzopffRMzoV54/wx33jwsWwGnV49H+PJ5V3y6Wt+Omfj6FndCrt2AXIji0hCo9W/SNHLvQLy3LY+/5g3Pj64uXVuHDZ/Dg9fddlrSi36NE9OiUc19nkwobOJuE4KT/sGxcuxu07D+GOdcuzKvOlpGvTxVDk6kDsf9322aWwmQ1J/llLbRnWLKlNmkC4c/9JPLi3S7hfhc2Ef/xUM3yhaNzY6PbPL4MvGMX9f5jReZvWtGDv0QFc3dkY15Zb17dhfrkZ+z/yJo2vHtzbJei3Ym2H2UhpjdwKxIlRn9CxACAQZjExFUXX0IzSu2JVg/A3f8wtT72LE6M+1de+5al3cbjfI/m51PUSr3H9ec2C0eDP7RqaFALDUtc73O8RlAP//e07D+FwvyfpHnLPqqbM4muu66gXlJrU9aS+P9DnwYE+T1I5DvQll0HqM/76Sq+hpC0JgojnYL9HcPCAWF+687lDODitV3jk9KCSPpdOd6U6dl1HvfA/r9ek9M2x4UkMTQSTdMXtOw9hYipaVLpCqi4f2NOFA30eRTpabVuoqf9iR0o+eCcWmKnLK1Y1CH+P+EIIRzghMMwfJ2c/+e9veepdHOjzxH22fW9M/vj6zqRfiMnWdbQgJR/iOix0fyklDg1MSOrTQwMTKc9TqocT0So3+T7v4IBX+vkGpPaunuHAKU+Sr3zns4dw4FTqetF6nlZdWcj+mw9SPV8264y3gwf6PJJ2XqndEl/7pgvOFALD/HXu2nUYXz7/DCEYfMWqBuFvcVlGfCF0DU1iXUc9gHh/hD/u/j98gBFfSLK8d+06LJybbuwy22VoLqFV/8iRC9k4MepLGl///TlnJOnpLc8dhtNmjjvu+vOa446T8sPu/8MHWNdRn3WZL6V+ki6GIlcHYv9rxBeS9M8O9HmSnpnXxeL7XbGqASO+UNLYaGgiKASG+c+27+3C9ec1J7Xl7TsPIRKF5PhKrN+KtR1mIxQcVsCgNyAILI8vGAHLQficYZB0TKyDBFRfOxBm0e+R/lzqeonXmApGks4Vl1XqenL3G/AEku4h96xqyiy+ZrrrSX3PctLPpPQz/vpqjk/XlgRBxDPgDUr2pUFvMO4zOT2opM+l012pjhXrFv5vNfomEGbhC0WSPiukrpCrS5aTrytxedW2hZr6L3ZSyQcPLyP83ywX8weU2k/x9yyHpM/4ew5NBDLqF2KydR0tyMmHuA7JtipjUKE+TUSpHk6+nza5yf95WutF+n6D3tT303qeVl1ZyP6bD1I9X7brjLflcrpdid0SX1tqvBUIszjtD6cdM4nLku64dLYISD12me0yNJfQqn/kyIVsDHqTx9fjvrDkfUYm4/V3Yp9KJfvZlvlS6ifpYiip6oDXG3L1x3JIemapmIxcG8hddyokrS/lZEOs34q1HWYjFBxWQK3TAosxvqrsFgP0DOI+TzzGYtShxmFRfW2LUQe3y6r4eonXsJkNSecmljXxenL3q3NZJO+RaZkTr5nuelLPI/VMSj/jr6/m+HRtSRBEPHVOs2RfqnWa4z6T04NK+lw63aXk2MS/leobi1EHu8mQ9FkhdYVcXeoY+ecXl1dtW6ip/2InnXzw/3PczN86JuYPqLGf4nOlrs3Xdyb9Qky2rqMFuToV1yHZVmXUKtSniSjVw8n30yY3+T9P2/O5Ze5X60x9P83nadSVhey/+SDV82W7znQMBL2r1W6Jry013rIYdSi3GdOOmfiycBzSHif3nfjcVGOX2S5Dcwmt+keOXMhGrdOSJI+VdqPkfarL4vW3XJ9K/J/jsi/zpdRP0sVQUtUBrzfk6k/HIOmZ5WIyauIoNpN021bIyEaibizGdpiNUHBYAQur7Ni2YWVcp3BY9FhUU4bNa1tgMerwzFt9wt/8Mds2rBQ2CFBz7W0bVqLV7ZT8XOp6idd47NVu3H15W9y5i2rKcN/V8tdrdTuxdX38OVvXt6HV7Uq6h9yzqimz+Jq79p/EpjXy15P6vr3BhfYGV1I52htcSWWQ+oy/vtJrKGlLgiDiaXe7cPdl8Xrl7sva0D6tV3jk9KCSPpdOd6U6dtf+k8L/vF6T0jdnzivDPIc5SVdsXd8Gh1VfVLpCqi43r21BR4NLkY5W2xZq6r/YkZKPuy5rTarL377dJ/xdbTfBqGfwvS+0K7Kf/PfbNqxER4Mr7rNNa1rw/IGTQn1n0i/EZOs6WpCSD3EdFrq/lBJtdQ5JfdpW50h5nlI9nIhWucn3ee11Tunnq3OmPm++K8lXvvvyNnTMT10vWs/TqisL2X/zQarny2ad8Xawo8ElaeeV2i3xtR95+UNsuTTeRmy5tBW//Mtx3HLRYsG34P8Wl6XabkJLTRmeP3ASQLw/wh/3jQsXo9pukizvlktbhXPTjV1muwzNJbTqHzlyIRsLq+xJ4+tfvX48SU/fdVkrvP5g3HGPvdodd5yUH/aNCxfj+QMnsy7zpdRP0sVQ5OpA7H9V2U2S/llHgyvpmXldLL7fM2/1ocpuShobzXOY8Y0L43XepjUteOzV7qS23Lq+DQY9JMdXYv1WrO0wG2E4cVh+jtHZ2cnt27dP0bH8bo9DE7HdHhdW2cGyHI4OejHuDyMQjuLMajs4MBienDlGze7M4muLd5VP/FzJNRpcVhwZ9GLAE0Cdy4JWtws6HZPyevyOwOJzpHZbH5oIoM5pQZRF0rOqKbP4mmO+IIwSO22m+h6AsLulPxRBY6U9budScRmkPuOvr/QaGSRBzzh7eipZZRgG1/zsVVXX2/GV81SfQ+fNjvNS6PycyGkgEMHBfs/MLvJul+QmSGp1h5h0uivVsctqnegd9+P4qA8OiwFGvQ5RloOOYTDmC6HWacaSeQ4cG52ELxhBOMrBH4qizmnGcgV6tRDwu7T3jvlgE+3SrlRHq20LNfWfBXKqT/ndmE96plBlN4NDFByngy8YgctqBMMAY74wrCY9jHoGZWYDltbGglBK7WeiXYrtTK9HOMqi0m6W3Gk6U/nK1nW0IJYPt8sCh8WIwSLqLzkkoweTklP/VEjY7b3WaUZbnSPlZnQ8SvVwIlrlJt/nTU2FcXDAO/N8dc6Um9HxhEJRHDjlEXZE75jvUrSpk9bztOrKHPffrMupWlI9XyZ1JmUHgZjeHfUFwWDGzquxW3x5B70BlNsMmAhEMTIZxHyXFRV2I/o9sXFSJMrho3E/nBYjjAYGIxMhmI06WAx6VJWZ0FBuQ++4X3juxorY/2KbUF1mRpQFxv1BGHU6jPlDsJkMqHOZEYnGj8P4Z5Oqx0LagCyRU9tfSmjVP3LkQjakxtduhynOftU6TBieDMFi0MMTCGMyEIXbZcbieQ68PzyBfk8AVdMv4CeCUQRCUZTbjAhGonC7bGnH61qeKwt1kTc5TRdDER8zNBHAvDILdEysvnidON9pxdFBL/o9QZRZ9JjvsqJJ5pl5/3jYF4TTbJxuVxumwlGM+8Pwh6Iotxpg0OngD0dQZjbi9LS+CkWjcFpiPnQwwmFkMgi3KD6VKCtNlfG6sQT1VbEjW5kUHJ4FRoIoeig4TOcVzXn5Dg4TRJYhOSVKhYIH3QhCASSnRClAtp8oBUhOiVJAVk4prQRBEARBEARBEARBEARBEMQchILDBEEQBEEQBEEQBEEQBEEQcxAKDhMEQRAEQRAEQRAEQRAEQcxBKDhMEARBEARBEARBEARBEAQxB0m/VfEchd8dt98TQEOFFRaDHuNTIZj0OoSiLEyiXSHFu8tK/Z/p7uJKriveFdQXiqBJtNPjoDe2Q3iUBYYmpM8V3yexvOm+V1qfRwe9GPeHEQhH0VxlxxnzyqDTMbLXV3PfVNdIrBfx7qZydSP+PrHu55dbcNoXxqg/CKfFhFCERZ2LdtIkCCnEfbPGYYFeBwxP8ruEB1HrtKLV7QQAQee6XbHPxDuHi3Wy22XFsloH+jxTGeklfjfznlEfLCYdzPrYDuLiHc0HvQHUlJkxFYmib3xKsmyK7jHmg120Y3omOjbV8VL3m++04oPhCVn92zvmw9BEEJ6pMJwWI2qdZjSU29B32p+kO5XajVIjEmHx4YgXnqkoRn0hOMwG6HWAxaBHZZkRIxNh+EIRRDgWDpMRY74QqsvMCLNRMNAJddY77seoLxjnI2Qkmynkhj9OysaptaGFRunzznUS9aBSXcTvbj/gDcDttKBd4e72Wu+X73IGAhEc7PdgwBtEndOMdrcLFkv6IU6+z8t3vZSSDsgULXWbzpaKv2twWXF00ItBbxAumzFmL61GOC16BMIsdAyDoYkgLEY9KmxGLK11QqdjcGLUh1FfzOcZ94VQaTfBaGAQjnAY9AZQ7TCj1mnGgooZvd09PInjoz5YjHpU2o2wmwwYnQwhwrEw6BiEoxzGJkOor7Cp8keI4iSVHc/0urwM1zktmAiEcSqhf+Tq3oB0n+T7xKA3AJvJAIbhEIpwGPMFUV1mBssB4/4Qysx66BgGdpMBk6EIRidDmOcwQ8cA4/4wmqvsaKqyJ8VFAMwZnccjbudU8R7x8WJ/q85lBssCQxPJsZLeMR9GJ0OYCkfhC0XgdlmxvG5GdsS6qsZhhHcqigFvEG6XGRaDHifG/ILNMhh06B3zYcAbhHcqDIdVjzKTEb5QFP5gBNUOM6IsiygLYXyYjbEeoQ4KDksQibDYuf8kbt95CBU2E64/twlPvtmLazobsWNf7Pf2vV0IhFk0VVnxtTUtuH3nIcn/LUYdtm1YiUta61QJM8ty2H14ALc89W7a6wLA3vcH0TU4iQf2JJeLfwb+u8RzxfdJLG9iObQ8TyTC4sXD/egbn4orw31Xr8RnltfipSODSde/eJn051L3lSvjxctq8aeuobh6sRh1eOjasxCKcLjlqXcl60b8fWJdLq4pw999ogk//fOxODnQ2s4EMZuR6pu3XLQYZr0OP9h9VPjse19oh0nP4Nu/OSB8tnV9G9avqIfBoIvTyfz3d1/ehqfe7MG+Ho+m/idVts1rW2A36dFU7YMvyCZ99/hrPRj3h+LKpuUeLbVlWLOkVpOOTXU8kKzPv/2ZJWiosKJ72Cepf//UNYTuYR+2/f6DuDI2z7OjZ9Qf97lSu1FqRCIsXvlwCCMTYdzx7KEkeSi3mRAIR/DjP32YpPe3rGvFM2/34rIV9bCZDXhwb1fGtkGJ3PDHJdp+LTa00Ch93rmOlB5UootCoSh2HjiFO5+N15/rO+anDDBqvV++yxkIRPDcwX7c+ZzovMvacFm7O2XANt/n5btesuG/lwpa6laNLW2qsuLmT7fE2YdNa1qwY18v/ulvFsFq1OE7zxyM018nT08hEgV++P+OJI0b/+lvFmHLc4dn7MilrZhf7sMnm+fh/703iG8+Ha8Lm6psGPOFYNIziHIM7tp1WJUMEcVLKjueSV8Vy7fUWHfr+jZc1j4fL384nPV7A/J9cp7DhK888bZsXxD72rd/fhnMBn1cv9tyaSv++40efDA0ia3r2/Dg3i70jE5Jjt9ns87jSdfOic8vpffuuqwVwXAU339xZlx239UrUWbRoWfED18oKik7vz86FKer7rqsFf/5p2NCe4jb6p7L21DjMOG9/om4WNVXP7UoTp9tubQVP/3zzDUyHesR6iFLIsHhfo+gzK5Y1YAH9nRhXUc9tu+d+R0IswCAdR31wrFS/wfCsQDDiVGfqjKcGPUJHTfddU+M+nCgzyN0tsTj+WeQO1d8n8TypvteaX12DU0mleGbT7+Lw/0eyevLfS51X7kyHu73JNVLIMziQN/MtaXqRvx9Yl3edMGZuGvX4SQ50NrOBDGbkeqb237/AUb9objPvvu7g+gamoz77Padh3C43wMgXifz39/57CFcf16z8L/a/idVtgf2dGHEF8LEVFTyuytWNSSVTcs9DvR5NOvYVMdLfffv/+99hCOcrP490OcRAsDiMoYjXNLnSu1GqXG43wM9oxMGIEC8PBwbnoTNZJTU+3c9fxjXn9eMEV8It+88lBXboERu+OOkbJxaG1polD7vXEdKDyrRRQdOeYTAIn/enc8ewoFTqc/Ter98l/Ngv0cI1ArnPXcIB9PcL9/n5bteZpueToWWulVjS9d11CfZB35MuOW5wzg27JO0od98+l3JcSMfDOOPv2vXYUxMRXG43yMEW8TX4mf12UxGIZCi9DmJ4iaVHc+kr4plWGqse/vOmA7Jxb0B+T45MRVN2RfEvvbQRDCp39216zBuuuBM4XrrOuqF7xLH77NZ5/Gka+fE55fSe1ueO4wRX/y47JtPv4uJqShGfCFZ2UnUVVueOxzXHuK2uuPZQ5gIRJNiVYn6jI+x8P9nOtYj1EPBYQn6PQFBUBkmJoyJv3nS/Q9gWsEFVJVh0BtQfN1BbwAsJ1+OdOemKm+675XQ70kuH38dcV0r+VzqvnJllLuv+DOpuklVl1PBiKQcpCofQcxV5Pomy0HRZwOeWH+S0wdToUjc/2r6X6qy+UIRye8YJrlsWu+hVcemOl7uO19Q+nlS6Wa5OlBiN0qNfk8AY76wbFvxMiGn96dCEaEes2EblMgNf5xa21qMbaT0eec6cm2aThcNyNTvoDf1eVrvl+9yDniDMucFi+q8fNfLbNPTqdBSt2psqZxe5z+X8l98MuMFuWv5QhHZ5/BN2xg5W67EHyGKk1R2PJO+KpZhOZkbyNG9Afk+6RP57an6FZA8Hue/531/8bGpjp+NOo9HSTsn+o1Kx2W+YES2TuXskrg9EtsqUX+la//Ea0g9D5F9KDgsgdtlhcU4UzX834m/E79P9X+Nw6KqDLVOi+Lr1jot0DOpy5Hq3FTlTfe9Etwuq2z5Eus63edS95Uro9x9Ez9L9734GJvZkFIO1LYzQcxm5Ppm4moguc/qXLH+JKcPrCZD3P9q+l+qstlNBsnvOC65bFrvoVXHpjpe7ju7Rfp53C552yFXB0rsRqnhdllRaTfKthUvE/xnicdYTYa4esy0bpTIDX+cvG0tnTZS+rxzHTk9mE4XuWXqt9aZ5jyt98tzOeucZpnzzEV1Xr7rZbbp6VRoqVsttjTxf46T91/EdlfJtewmg+xz2KdtjJwtV+KPEMVJKjueSV9NlGFJucnRvQH5Pmk3GZI+S/yf97XlymYV+WOcKKiZq2cpZpS0c6LfqHRcZrcY5H1MmeuI2yOxreT0l9JrSD0PkX0oOCxBq9uJrevbYDHq8Mxbfdi8tgW79p/EpjUzv3lh3rX/pHCs1P8WYyw/Cp8kXSkLq+zYtmGlousurLKjvcGFzWuly8U/g9y54vskljfd90rrc1FNWVIZ7rt6JVrdTsnry30udV+5Mra6nUn1YjHq0N7gEo6Xqhvx94l1+cjLH2LLpa1JcqC1nQliNiPVN2+5aDGqbKa4z773hXa01JTFfbZ1fRta3S4A8TqZ//7uy9vw+Kvdwv9q+59U2TavbUG13QSHVS/53W/f7ksqm5Z7dDS4NOvYVMdLffftzyyBUc/I6F8X2htcuOWixUllNBqYpM+V2o1So9XtRJRjcc/lbZLysGheGfyhsKTe37KuFY+/2o0quwlb17dlxTYokRv+OCkbF7N/rpJpI6XPO9eR0oNKdFH7fBfuvjxZf3bMT32e1vvlu5ztbhfuvizhvMva0J7ufnk+L9/1Mtv0dCq01K0aW7pr/8kk+7BpTQueP3ASd13WikXz7Mk2VM/gvqtXSo4b77qsNd6OXNoKh1WPVrcT912drAt1OmCewwx/MIwtl7aqliGieEllxzPpq2IZlhrrbl0f0yG5uDcg3ycdVn3KviD2tec5zEn9bsulrfj5yx8K13v+wEnhu8Tx+2zWeTzp2jnx+aX03l2XtaLaHj8uu+/qlXBY9KiymyRlp32+K0lX3XVZa1x7iNvqnsvb4DDrk2JVifpsy6Xx18h0rEeoh+E4Lv1Rs5TOzk5u3759kt/xO2wOeAKor7DCYtDj9FQIRr0OoSgbtxN5Y0Vsh/KhiQBqHMn/a91Zkd99Usl1xbuN+kMRNFba0VQ5c3ydM7Z75fCk9Lni+ySWN933SohEWBwd9GLcH0YgHMUZVXY0zyuL21E98fpq7pvqGon1wu/AyR8vVTfi7xPr3u2y4LQvjDF/EA6LCeEom24HzYyzpqeSVYZhcM3PXlV1vR1fOU/1OXTe7Dgvhc7PiZyK++a8Mgv0OmB4MrZz95gvhFqnWRjY8Dq3zmVBq9sVt8GKWCfXuSxYVutEn2cqI73E79jbO+aDyaCDxaBHVZkJjZXxOqDabkYgEsXJ8SnJsim9h81kQK3TjMbKzHRsquOl7jffacUHwxOy+rd3zIfhiSBOT4XhtBhR6zSjodyGvtP+JN2p1G7kkJzIaSTC4sMRLzxTUYz5QigzG6DXARaDHpVlRoxOhDEZiiDKsigzGzHuD6PSbkKUjQLQCXXWO+7HmC8Io8hHyFQ25eSGP07Kxqm1oYVG6fOWGBkVXk5OU+lJOUKhKA6c8gg7fnfMd6XczCzT++W7nIFABAf7PRj0BlHrNKPd7Uq5OVyhzst3vSjUAVmX00KgpW7T2VLxdw0uK44OejHoDcJlNcITCMNlMcJh1SMYZsEwDIYngjAb9aiwGbG01gmdjsGJUR9GfTGfZ9wXQoXdBJOBQTjCYXDav6h1mbGgYkZvdw9P4vioDxajHpU2I+xmA0YnQ4hwLAw6BuEohzFfCPUuK1rnK/dHSpycjqUKSSo7nul1eRmudVgwEQijP6F/5OregHSf5PvEoDcAm0kPHQMEIzF5riozARww5gvBbtZDr2NgNxkwGYpgdDKEeQ4zdAxw2h8WXuIkxkUAFNrvybucits5VbxHfLzY36pzmYW85omxkt4xH0YnQ5gKR+EPRVHnNGO5SHbEuqrGYYR3KirYRatRj54xv2CzDAadIGueqTAcFj3KzEb4Q1H4QxFU2U2IchyiLITxYTbGeoQkspVIweEiNBLErIOCw3Re0ZyX7+AwQWQZklOiVJgVQTdi1kNySpQCZPuJUoDklCgFZOV0TrxqJAiCIAiCIAiCIAiCIAiCIOKh4DBBEARBEARBEARBEARBEMQcZE6nlWAYZhhAj8zX1QBG8lgcOagcxVUGQH05RjiOuySTG6aRVbUUSz0mQuVSR7bLlWs5LXQ9FvL+c/nZs33/XMppoetJLaVU3rlY1oxktcj1qRgqizSlUpZcyqlWiqXuiqEcxVAGoPDlyNdYqtDPKUUxlgmgcklRbGN+pRS6LWmMll9k5XROB4dTwTDMPo7jOqkcxVOOYihDMZVDK8VafiqXOoq1XHIUuryFvP9cfvZiuL9SSqWcPKVUXiprdimmMlJZpKGyaKdYylsM5SiGMhRTOXJNMT5nMZYJoHLNJgpdZzRGKx55pbQSBEEQBEEQBEEQBEEQBEEQcxAKDhMEQRAEQRAEQRAEQRAEQcxBKDgsz8OFLsA0VI4ZiqEMQPGUQyvFWn4qlzqKtVxyFLq8hbz/XH72Yri/UkqlnDylVF4qa3YppjJSWaShsminWMpbDOUohjIAxVOOXFOMz1mMZQKoXLOJQtcZjdGKBMo5TBAEQRAEQRAEQRAEQRAEMQehmcMEQRAEQRAEQRAEQRAEQRBzEAoOEwRBEARBEARBEARBEARBzEEoOEwQBEEQBEEQBEEQBEEQBDEHoeAwQRAEQRAEQRAEQRAEQRDEHISCwwRBEARBEARBEARBEARBEHMQCg4TBEEQBEEQBEEQBEEQBEHMQSg4TBAEQRAEQRAEQRAEQRAEMQeh4DBBEARBEARBEARBEARBEMQchILDBEEQBEEQBEEQBEEQBEEQcxAKDhMEQRAEQRAEQRAEQRAEQcxBKDhMEARBEARBEARBEARBEAQxB6HgMEEQBEEQBEEQBEEQBEEQxByEgsMEQRAEQRAEQRAEQRAEQRBzEAoOEwRBEARBEARBEARBEARBzEEoOEwQBEEQBEEQBEEQBEEQBDEHoeAwQRAEQRAEQRAEQRAEQRDEHISCwwRBEARBEARBEARBEARBEHMQCg4TBEEQBEEQBEEQBEEQBEHMQSg4TBAEQRAEQRAEQRAEQRAEMQeh4DBBEARBEARBEARBEARBEMQchILDBEEQBEEQBEEQBEEQBEEQcxAKDhMEQRAEQRAEQRAEQRAEQcxB5nRw+JJLLuEA0A/95PonY0hW6ScPPxlDcko/efjJGJJT+snTT0aQnNJPnn4yguSUfvL0kzEkq/STh5+MITmlnzz8yDKng8MjIyOFLgJBKIJklSgFSE6JUoDklCgFSE6JUoDklCgVSFaJUoDklCgkczo4TBAEQRAEQRAEQRAEQRAEMVeh4DBBEARBEARBEARBEARBEMQcxFDoAhDFB8tyODHqw6A3gFqnBQur7NDpmEIXiyAyguSaIIhUkI4gCEIJpCsIMSQPBJE9qD+VPtSGpQsFh4k4WJbD7sMDuOWpdxEIs7AYddi2YSUuaa2jTk2ULCTXBEGkgnQEQRBKIF1BiCF5IIjsQf2p9KE2LG0orQQRx4lRn9CZASAQZnHLU+/ixKivwCUjCO2QXBMEkQrSEQRBKIF0BSGG5IEgsgf1p9KH2rC0oeAwEcegNyB0Zp5AmMXQRKBAJSo8LMuhe3gSr304gu7hSbAsV+gizXnUtgnJNUEQqVCiI8gWEMTsQkufJn+CEJMLeSBbQ8w1eJn/YHACN61uhttlEb4j/VpcpNNPZCNLG0orQcRR67TAYtTFdWqLUYcahyXFWbMXWhpRfGhpE5JrgiBSkU5HkC0giNmF1j5N/gQhJtvyQLaGmGtIyfymNS144vUe9HsCpF+LCCX6iWxkaUMzh4k4FlbZsW3DSliMMdHgO/3CKnuBS1YYaGlE8aGlTUiuCYJIRTodQbaAIGYXWvs0+ROEmGzLA9kaYq4hJfPb93bhilUNpF+LDCX6iWxkaUMzh4k4dDoGl7TWYemm1RiaCKDGMbd3mEy1NKJ5XlmBSjW30dImJNcEQaQinY4gW0AQswutfZr8CUJMtuWBbA0x15CT+Y56J17YtJr0axGhRD+RjSxtKDhc4rAshxOjPgx6A6h1qut8cufqdAya55XNaidEab3R0ojiQ2ubzAW5JghCOzodI8xsGPTGcqM1VtjQO+6HjmHIFhBEjsnEp1VLJv6dVn8in89H5Ac1barkWCUpjkiGiNmEnMyXWQzgROlsSfYLj1K7mcsxd6Ic8H46yUV2oOBwCZNJXqq5nNNKzbPzSyMSj6WlEYVjvsOCuy9rw53PHRLa5O7L2jCfgjQEQWRAom1oqrLia2tacPvOQ6iwmbB5bQse2NNFtoAgckC+/dLGChu2rm/D7TtnfImt69vQWGHL+r2Aue13z1bUtKnSY1ONO0iGiNmIlMxvXtuCbz19AOP+ELZtWImLl9XipSODJPsFJt92M5FUfjrJRXag4HCRoeatmFzel6WbVqd9U5PJuaWO2mdf7nbgsRvOhj8UQWOlHWdU0xupVOT6ze6hAS9+/Kcu3Hh+MxgG4Djgx3/qQvM8OzoXVmbtPvSGmiDmFidGfbh39xFBtyypdeBHLx1FIMyi3xPA46/1YOMFzah3WXHSM4XlbgfpBILIEpn4pVrsde+4Hw/ujfclHtzbhVWNFTnxgxP1CwDcu/sIltY5Zr3fPVs5PhKT2QqbCVesagDDAO8PeLHc7cDC6vg2VSrfqZZkdw9PztmxGzF74WW+fuM5eH9gAn2np/D4az0AgBvPb8bRAS9qHWbcu/sIyX6BSWc3cz12TtSj6zrqhcAwMCMXyzevBsuBxvAaoOBwEaH2jXAmeanmck4rpc8u1x5nVNNMMTnyMathwBtAz+gUfvzHY3Gf88vAswHNziCIuceoL4hrOhuxfe/M7GDxjtn9ngC27zmGm9cswkN7j+G8M6uSAgAEQWhDq1+q1V4PyvgSufKD5fTLmC846/3u2QjLcjjS70WFzYTrzmmKa9emKjsaK+ODEWrkW25J9lweuxGzG52OgT8URe/4FB7aewxulyWuXz38cnecPwaQ7BeCVHZzYZU952PnRB3IMEjSiRU2E97uPY3bfneQxvAa0BW6AFphGEbPMMw7DMM8P/3/GQzDvMEwzDGGYXYwDGMqdBnFsCyH7uFJvPbhCLqHJ8GyXNIxaneo5fO+iFGaLy2Tc0sdpc9OOwarJx915pZpv1pn9mQ3n22vRDcQBJF7THqdMBAB4nfM5rEYdeC4uWMvCSJfaPVLtdrrfPvBcvrFqC/Zodic5sSoD11DE7i6syGpXW/73cEk+ZOTt3llFsU+4FweuxGzH5vJAD0Tk+krViX3Kyl/jGQ/v6TSQXK2+ODJ01kb48rdX8zVnQ1CYFhcDorfKKOUPZLNAI6I/r8XwP0cxy0CMA7gxoKUSgJ+VsPntr+Cv3vkDXxu+yvYfXggqYOkeiMsBZ+jh+8UanIgZnKuHMUS5EpXDqXPrrY9iPzUWft8F+6+vC2u/e6+vA0d810pz1Mjn1qfQ20fUKobCILIPb5gVLLf87Ebi1GHO9Ytxxvdw9i2YSUaK2xFYfMIIlfk06/T6pdqtde58INTIadf/KFo2nOLxb8mZhj0BvDUvj4sqLApkj8pebvv6pUYmghg57sn8b8fjuKGX/41zgdMbPfGClteZZYgsk0qXcZyLNobXLhj3XLodckzQhP9MZL9/CBuM44DHrr2rCQd1Fhhw/BEEDetbsbNaxbB7YoF7QNhFnuODmVtjJuoR3ftP4mt6+NjAotrHBS/yYCSTCvBMEwDgM8D+B6AWxiGYQCsAXDt9CGPAfhXAD/J9r215FJRmmdK7c7JqfJSpSOTc6UolmX4Ssqh9Nkz2cl6rqKlztT2KZNJj/Ud89FcbRfO6ZjvgsmkT3kPNfKp9TnU9oG5nPubIIoNu9kg2e8/3lSJTWsXIcoCD7/8Ib6+djEaKiz4n0P9uPWZA7RsjZiV5Nuv0+kYXLysFjs2noN+TwBulwWtblfae2n11bLtB6dDTr/YUvguQPH410Q8tU4Lxv0hDE0EFMkfL29LvrYavWM+2M0GjEwEccMv34xLM8LnoZZbon3xslq8kCeZJYhskkqXsSyHEyNT+JffHUCFzYTvfn6ZZL9aVOPAprWLsHZpDdrry0n2c4xcm+3evBoD3pgOanBZk/xhPgXIuD+E6HQTZmOMK2W3GytsWNVYIfzPr+6j+I02SnXm8H8A+A4AvtWrAJzmOC4y/X8fgHqpExmG2cgwzD6GYfYNDw+ruqnWWX5KZzVomcXA56U6p7kazfPKVCnJTM5NJNWyvnzOeFC6vFDJs+d7VkkimchqoVBbZ1r7lMmkR+fCSny+Yz46F1amDAwD6pedaml7LUtbZ8Ps9FKUU2LuoUROQ9EovnHh4rh+f8e65bj92YPYvucYfvt2H9Z11OP4qA/j/rDgCAO0bI3IDsWkT/OdWotlObx0ZBDXPPw6vvqrt3HNw6/jpSODaf2BTHw1rX6wFr82FI1i05qWuHJuWtOCcJRNeV4xpjgrJjktFLzcPbXvo6R2TSV/7w9O4F93HcaAN4hbnt6ftGx+XUc9hiYCsu3eO+7P2thtLkCyWjzIyfTxER/e7BnD8dFJ3LS6GVd+rAEP//lDbF6brC9/8MIRbN9zDFPh6KyS/WKTU97G/emDIbw/EMutDsy0GcsB5zRXY2GVHa+fGEvyh7fv7cLVnQ3YtKYFv327T7huNsa4iXbbYNDF/X9GdWHjN6VOyc0cZhhmHYAhjuPeYhjmb9Sez3HcwwAeBoDOzk5VUUqts/yUzmrI9yyGbCIX5BrzBXF0YCJvMx6yuVlDodsjE1ktFGrrLF8zZ+XkYtArLRda2l6L7M2G2emlKKfE3EOJnFbZzfj1X3tw86cXYV6ZGTazASzHomd0KmlzlE1rF9HGQETWKSZ9mu/Nr7T6A/n21bTO5K2ym7FjX2/cLu879vXikra6lPcrxk3IiklOC4Ugd3UOjPmC2LHxHPhD0ZQr4E6M+nDv7iO4prMRx4YmZJfN1zgsRdnupQjJavEgJ9O9Yz6c8gTw8MvdcTNPXzzYj0e/1Ik3jo8hykLYjK7UxklKKCY5lbJx4s0AxXroxKgP+3rGJNu1vd6Frf/znrCBIJCfMW6h4zelTskFhwF8EsBlDMN8DoAFgBPAAwDKGYYxTM8ebgBwMts31mqo+bfLiY6k1BsMuR1qpWBZDr1jPgx6g/CFImiqtOOM6twIf7ql/3JBLqNel9dl89kOtqlpDyKGmjrT2qciERaH+z3TS0+taHU7YTDIL4SwmdQv51Tb9lpkb2GVHQ9dexYO9HnAcoCeAdobXPR2kyAKwMIqO269ZBlueepdVNhMuLqzAZ1NFZKbo7Ayy9ZsRj1e+3BEcdopgihWMvGntKRgG/QGUGEz4YpVDWCmD33mrT5FwbB8+mpag9hi/ZJuLCBmNrxEnq2olbtBbwDrOuqxfW8XblrdLNmuZ59RCY4DdAwj+f28Mmp3ojSR02UWox73PP9e0szTjRc0w6CLpfa6/dmDQmCYZoHmFikbt31vF248vxk//uMxWIw6MGDQPTyJUV9Q1h+uKTPjjnXLcfOv31Fl89Qg52tQ/EY7JRcc5jjuXwD8CwBMzxz+Fsdxf88wzNMArgLwJIAvAXg22/fOdl4zAOgenlTlPPOwLIe97w+ia3ASD+zpyums3EiETZtbUS4A7g9Jb8Ch9s230kC4mkD8XEPLYE0LagK3WvpUJMJi5/6TuH3nIaGNt65vw/oV9bL34Zdz8sEdpcs51aBV9kIRLu5t+bYNK1Men692JIi5Bm+rl29ejbd7T+O23x3E0zYTNq9twVQ4isU1ZbjpgjMxFYyg3G7Cty5egh+99L7QdzevbcG7H53GT/7cjXF/iPKCEllH7YvRTNBq07TOrHW7LLj+3KY4n3bz2hbUOYsrGKZ2JRKP1tlM5NeWNizL4fiIDz1jPliMOqxY4EKFzYRn3upL8kv/7YoOTIWi+PyDr6DCZsItFy3Gtt9/ENcfjo9O5mwiEEHkCpblYDQA3/tCO777u4NxMr2/77SkTm2stOHrO97FuD+Ee6/sQH25BZV2M417coycjWOY2Bj9ts8uxZsnxhCKsvhYYwWGPD7csW65EODnx9ibdryDWy9ZFpefOJttR/n4c0PJBYdTcCuAJxmG2QrgHQCPZvsGiQ5aU5UV91zejkFvQPheThgT32BkKtAnRn040OcRgkpAbmblsiyHV7tH43LJVNhMODrghcWow8Iqu/DcUk7viVGfpoC6OADmdllwbHhSUSCclhJIky8FqjZwq2XQc7jfgwen32Dys4se3NuFlpoyrFhQIXmOluWcaoOwWmRP7QwkMoQEkVt0OgYsB9w2PXjp9wTw+Gs9+MEVbXC7rPjOb/YLfe/eK9vxyxs+jp5RP4Yngnj8tdjmG/zsCtpcksgmWl6Mis/VElQ2GRhsvKAZLAfomNj/6Tg+Im3XlnxtNc6ske8LURaCj8ef98CeLly8PHXahXyjZSUSj5bZTOTXli4sy+HFQwP45tPvxgXD/vnTZ+LHf/wQT7zegxvPb4ZeByyuccBhNeDOZw8JtifKckL/4zgINuYFsitECcGyHF45NoQBTxD/+adjgsyvbCjHZCiEj8akN3Uc8ASElAS3PnOA5D5P1DikJ26tWlCOWy5swVSYxUN/PCbEwv750y348R+7hHbtaCjHqdN+hCIcbnnqXbywaTXOaa7OejlpU/fcUNLBYY7j/gTgT9N/dwM4O5f3EztoY74gTp4OYOMT+zQHdzMR6EFvACyHnOejSswlk5h3MfG5E51eLcG/xADYprWLAEBxIJyWEiSjdbCmlsP9HmHgyt/n9p2HZAO3WgY9o74grulsTJoFPOYLyp6jdjmn1iCsliWGavowGUKCyD2J/bLfE4A/GMVduw7H9b1bnzmIR67rxH/+6Riu6WwUPudfWlF+SCKbHD4lY1/nlWFFo/SLUUB7UPnEqE9YDspjMerSDtB7xnyyeSVT+RtDE9L2cHgykFU/JVPysRIpEfJrS5PjIz4hMAzMvPDYeEEzrj+3Cffufh+P/qUbm9a04HsvHMHVnQ1Y11GPH//xGADAF4riob3Hkq5LdoUoJU6M+jAxFcWW52I+FC/fFqMOj1zXiYCdxTcuXIz7//BBnE594vUe4RrkT+UPvQ7YvLYlbkLepjUt+GBoAhOBKB79y0w8Zl1HvfBCS9yuGy9oxnXnNOGJ13ty1m6Ulz03lHRwuBDwDhoAfPHRv2YU3M1EoGudFugZmRwvWcxDxgeh+fuI8y66XRZcsaoBRwe8qC+3or3elRQ4y8ZsSn4T6HwoALnZosW4lF9NmbQO1tTCJ6pPvM+AJ4AVC6TPUTvocVpMcbk/+VxIv7rxE7Ln5GujPLWzs9Sm1SBDSBC5x+2yYNPaRYLteeatPkwEI3F9j7d/Y74QvnXxUvzopaO4YlUDHv1LN+wmPf7504ug1wFWowEsyxXcXhClz0nPlKT+P+mZwgrIB4e1rLYBtNsbu+zM2tRDjlLJrat1YzlAe1qoYvRBifSc8vhx4/nNcFj0qC+34fiID6EoC5sp9v/NaxaB44Ddh/pxdWcD6l1W2C0GuF0WYcZkKfQJgkjFoDcAX4IPBWB6hvwU+jwBWI16bLygGa1uF+pcZmx68p3psVTM1xL7UwBk9SHpyszhV8z9+1Ur8P7gBOwmPaIshyqrGQ0VBlTYTIJ+clj0cb7FM2/1od8Tix3xeaNzpa9y4TOQ/FBwWDPZCO5mItALq+xob3AlvdnJdh6yWqcFu/afFGZJMAyEwLB4BvHDL3fLzqzMxmzKfATC5WaLXrysFi8dGSyqpfxqZ7ZqHaypxe2ySt6nzpW9dgpFWMm+l27WTq43ytMyO0vtzPpSGTwTRKnCshze65+IywO+eW0LmqpsQt+TWkGzaU0LDDrge19ow8hESJhZkco2EoQaqsvMkvq/2m5OeZ6W1TaAdntT6zQn+aab17ag1pm6nKWSW1frxnJaVyRROqnShGU5DE+E8PyBk7imsxHfFqUkumPdclTajfj5K92osJkkc20//loPdu0/ia3r2+L8ymLsEwSRilqnBaO+kPRmdCYDWA6YCkdhNeqxpK4MjZUxHXvv7iNxtuvhl7vx0LVnCekKEvUhANKVWaDWacG4P4T3Byewa39Mf/FpJMT6CQAcFiP+4w/xvsWOfb3gple3L6515ExfZdtnIFsbg+E4rtBlKBidnZ3cvn37NJ3bPTyJz21/JUnJ7d68GiyHtG8csiGA4k3a/KEIGmU2acsEvpz37j6CdR31WOZ24FtP78eN5zfHLSvgnz8b+YAS69btsuAfP9UMXygqm3M4G2965Np0x8ZzcM3Dr2fyrBk3SKKsypVVrkwnRibx4qGBJOfzs211WFidvRmnmeREVEr38CRu+OVfsa6jXnhTuWv/Sfziy2dnbfas2voFgP0fjUvKyY6N56ScncXLrpIZzTk2XFmXU4LIATmV01S2/c0T43joj1345sVLhdzD4mMeu+FsWE06bPhZRvaCmD1kJKuJctozOolXPxwT0ptYjDpsubQV551ZiaYqednad2IMX3z0jSSZ/NWNn0DnwkrZ8zIJZu59fxAH+jxCruKOBhfWLKlNa6fU2MNCoqWcWvyKTM5TQVbllIhxbHAC6x76i+x46cfXnoVwlEMkyuFbMvZknsOMxgobesf9Rd8n8gD5qCUKy3L40weDGJ4ICaklLEYdtqxrxTNv9+K8RfOwuMYBi0kn2AmW5XDw5Om4cZXbZcF3P7dMsr+8sGk1AORaVyqh5OVUHPsRvwjl4dNGRFlI6rYH//Ys3PncYYz7Q/ifLKevlCprtnyGPNjaYkK2kmjmsEak3lb87LpV2N/nETZvS+VIZ2ODCZ2OwcLqsqwG96TucUlrHZbWOTA0EUCd04JtG1bi6IA3Z8vbE+t23B/C/Aorzqwuw6rGiqRAeLYCZnKzReVSJRRyKb/ama2NlXa01JbFbSzTUht7O5tNDAYd1q+oR0tNGQY8AdS5LGh1u7K6m3qDK5b8ns9xZDHqcPflbWhwWbN2Dy1vI7Wk1BCj5D0dbUxDELlFTrcOeAP4fGts0HJsaELyGJbj4AtGi85eELODBRV2zC/34UdXrYAvFIHdZIDDqseCitR2PJPVNlrsjU7HYM2SWjRXl6m2U1pz6+Z7KaiWcg7I+AiD3tS6gdJJFQdqZCyWYiw2TuJXXIoJhFkc6Z/AUrcDJr1O8nsOnNC+lG+aKGV0OgYXLKrBwVOn8eiXOnFyfAoWkwGPv9qNtcvq0FBhg9tlQVWZKe4cf2jGn+JXbH0g438NTQSE2apS31H/UY449iPn7y6udYBlOcnvPIEwTAYG2zasxBnVuV3lkM18/GRrY1BwWAFyDoHYaa5zWtA7NoVtv38/LvfKvbuPYGmdI0mo8uHIZuseiR2vsdKO+nJr3AZxQPaWt6cakJyRw0265JZQyqVKKORSfrXLPTMZrKnFYNBhxYIKRQFRLRwZ9AqBYSDW3nc+ewhLalPnT1SDTsfg4mW12LHxHCHnVas7Oae2GC0pNbS82NBiCEOhKA6c8mDAG4DbaUH7fBdMCnZWJ4i5Rird2jXiw3d/dxA3rW6WPGZemRk6HVN09oKYHeh0DFYvqlE9S6bOJS3TtU7lMql2kSHLcpgIhHHaH8553u1CLAXV4l+bDTrJdjDqU788p3RShSedjCXKw2QgjO7hSViMsbaVar/VLdVodbtwuN8rY0+S25fyYRKlisGgw4qGCvSO+WDS63B6KoxvfWYZjDoGo74Qjg1N4s0TISyqLRNmD4t1H7/nkZz/xetD0pXZQbzHllSdHumfQHWZUfK73jE/7rt6JVY1VqRcCcvrMpvJgFA0iiq7uaB5+MnWxsjedL5ZCu8QfG77K/i7R97A57a/gt2HBwRHt3leGc5prgbLAUf7PbimsxGP/qUbD+09hp+/0o1rOhvj8rqxLIcTI5PY+e5JyWvmo9yZotMxaK93YduGlXGOTzbzYInrtnleWVKHZ1kO3cOTeO3DEZwYld5sbWgioOqe/GzRxGdqdTtz+qxakCtrqjKlq9NSIdUM3WzBshxeOjKIax5+HV/91du45uHX8dKRwZT9p9XtxNb1bXFtsnV9G1rdLtlz5F5snBj1Ze1ZQqEodh8ZwMtdwzg6MIGXu4ax+8gAQqFo1u5BELOFxgpbXD9uqrLiJ3+/CgOegKB7nnmrD5vWtMT19c1rW3BkwIsGl7Xo7AUxe9Bix7X4C4B2P5JPLzVjP1/Dzv0nEYmknqmslXzYUTFa68UTCCXpjU1rWjARCKU8b2GVHQ9dexY2rV2Em9cswua1i/DQtWeRTskjqWRMSh5OjPrx1L6YneD3bUkeW7jwp64hvNE9gi2XtibZk+Ojk3EylctxHUHkA37F88fPqMLapbXwh8I4OjiBTU++g1t/exD/sacL3cM+fDTuQ/fwJAY8Afzk71ehqcoqzMCX8r+2rm9DY4VNs60j5JGq001rWvDKB0PQgcEd65Ynfff0vj4MeAOCfkwkUZdd8/BrePP4OG745V8V6bRc6cLGChsevq5TsLVNVdY5KT80czgNSmelDnoDcJfbhA0H+GO37+3Cjo3nAJgR5qMD3rhZt1pnumaj3FIoeRtTyOXtiW/wN69dpOlNj9Rzyj1TsS3lL8Yy5Yv55dIzdN1Z3PROS//RklJj0BtAhc2EK1Y1xO30mmoJi9q3pe8NeHFyfCppg633BrxY2ZidmdYEMVvoHffjwb1dwg7zDosR//hfb8fZmn5PAE+83oObP70INQ4zal0WBMIsHnn5GJoqbXNWNxPFiVZ/Qasf+V6/R9h3gD/v9p2HsLimDB1ZWt0jJt9LQU+M+nDv7iOKVgmKqbJbsGPfe8J5HAfs2NeL7X97Vtp7hiJcnA3ftmFllp6GUEIqGQOQ1E8+HJ7EuD+EJ17vwRWrGqDTAT+6agUMegYtNQ6cUW1H75gPXYOTeGBPFzavbRHSvnEc8OLBfgBucBzgtBiFzRyzsUqSIIqBj8Z9sBkNcFlY3HVpK0Z8Qfzq9V781xs9qC4z47bfHRT03R3rlqPKborzv248vxl6HfCxpgrc+ewhrGqsQPO8MvK/sgzvPyz52mocG5pEKMri5Gk/Ptvuxg92H8XXL4zXXU+83oNxfwgnRnz4YHACi2scWOZ2xu2JJeVbbJ/2u5XotGytGBfDTwoTrw6598oOXLws/V4Jsw0KDqdBqdNZ67TgrZ5xyWP90zP0eGG+aXVzzh1Zrc5yJMLifw71S+ZN5p9BHJTKRx6sxGAYx8U7SE/t60vaGTvdm55US8SknimbOW2yTS73lIzlTfNMp1awotXtTJs/ONfL3hxmg+RO6A6LMWv30Np/1KbUcLsskrtU18ks99WyfNYbCAvX55/jgT1daJ3vVFZIgphDDHoDCEU4WI06LK5x4J9+/bakrQEAvY7BnQmbq3gD4aK2F8TcRo2/oNUOnpJZ3dPvCaIjjW3U4j/keynoqC+IazobsX1v/A7tY75gynpZVuvAzZ9uwR2i/RLuubwNy2pT2+JcDIQJdaSSMal+8tS+PnzvC+347u8O4sd/PCbIyI59vfjRVStwZMCLeQ4z9hwZQCDMwheK4pm3+nDFqgY4LHr83Sea4jae3Ly2BY2VNlTYTOgXrZKbi/kwidJErNvdLgsOn/Kid8wfN/75xoWLwXKcEBgGYjJ+z/Pv4ZHrPoZ7Lm/DHc8eQr8ngEf/0o2t69vwy78cR8/olNAPyP/KDCkbDADvD07EjT3vWLccFTYTHnu1B9ed0xRnD7eub4PNpMf7AxP43gtHMO4P4ftfaMeqxnI0VtplfQt+dng6nZaLF8JSdvbWZw6gvd4152SJgsMysCyH3jEfghFWkdO5sMqOsxrLU+Z1Ewtzrh3ZGoe0IyOVw4qHZTm82j0qBIbdLguuWNWAowNeNFZa0Ts2lRSUunhZLXrH/ZoCgUoGAVLBsB9dtUJ4Lr6MDAM8/g9nI8pySdeSuk+pO9tagoRqB1380lB+BhCv8NevqJcNEOcj99+AN4DHX+uJm33z+Gs9WLmgXDIntRZqnRZ0Nrlw/XnNmApGYDMb8Nir3Zpmo6d67igLycDtxcvrJI/XMmMpEJbejCjxM4IgYjZl09oW3LXrML5+YUtcX3vmrT48/loPHrm+E1GWw1d/9VZc373r+cN47IazC1j6zKGclsWNlvbRape1Bl2dVoPkeWWW1HnutZZzYZUdP7tuFSamovAFI7BbDHBY9IqWgmp5AW7S64SBMJC8SlCOvtN+BCPRuI2Bg5Eo+k770VzjkD2PNsnJPmr7UbpNisXy7nZZcMN5TbCb9HF+6hOv96DfE8Arx0bw9L4+XN3ZgC+ecwY+2xaE0cDg+nOb8OSbvfjmxUvxnYRVqA/s6cLGC5pxdWcDtu85JpQrsT9mS3+THZgb5KudE3X7prWLACBpFfX9f/gAP/3ix3DT6mY881af8CIkEGbxzkcevPzBIP7z2lV4t+80oizw4N4uXNPZiO5R35zLC5ttWJbD8REfjvR70TU0gaf29WHcH8K2DSuxpNaRFDO55/n3sPGCZmzfc0xYSVdfbkWl3YipEAvPVBgttQ58Y+0i3L/nGG773UHccmELlrpdiLIsHrr2LPSN+zEZjL0YG/eHwHHKfIxcvBAmOzsDBYclEKd/ePbdWK4o8RuRe6/skHQ6p8LRlDNYeWHm8+WIr5ntnCZ6HSRnV6ba9+LEqA/7esaEwLD4TRCQrMTv3X0E4SgrOcs4W4MVqSBu19AELEYdKmympLdV2zasxCfOqIoLDEvdp8JmLGklcHxEOri95GurcWZNcvm1DLq0LA3NR9DdZjJg3B/Cj/8Y7yDbsrjBWoPLig0fbxIcdItRh7svb0ODyyp7jpY6HpqQNkbDkwHJdtQyY+mMarukEc31DrIEUWqwLIeeUT/u2nUYFTYTXBYj/uMP8X1tx75eePxh2R2zR0V7DJQahdjYi1CO1vbRapfTBcTkcDutkv7n/BT2M5NysiyH4YlQ0ovsdJvgaXkBDgC+YFSy7/vT5PEf8Aaw9X+OJNni//ulzpTBYdokJ7to3QhYbrm6uJ9U2Ey4/twmTIaiONLvxaN/Sd6426TXJY1d7ly3HHuOnMQ1nY04JmNbWA5YWucQZCGxP2ZLf5MdmBvks50TdTufGlZKzvf1jOPnr3Rj05oW4YWKxajDopoy6BjEreYCgO17u/DwdZ1zLi9sNpGSBb7+b3nqXfzn36+SbKsz55UJqT5CURa+YBiBCBu36mHLpa34x0814yd/7obdYsTGJ/bF3WPX/pO4/twm2Ix6/N9XjyvyMbT6JqkgOzsDBYclEKd/6BmdEnLb8G9/68stSYrzxKgPN//6HVTYTMKxOgZY7nYIx4qF+YnXe7DxgmYsrnVgWV18LpZs0O+Rnl15VmM5FlZLO9mD3gDY6bc2V6xqwI59vcL59S5rkmJY11EvBIYBdYFANbmcE+/71L4+fP8L7Tgx6kuavZF4Dbn77Nh4btKb/qs7G+APRdE9PFn0b8l7xqQ34esd80kGFbUMurQsDdXy5k3tm+tQNIp/uWQpRv0hsBygZ4BKmwnhaPZmwh4Z9OLOZ+MD43c+ewhLasuwIouBcbXGSMuMpTPnleG+q1fim0/PGNH7rl6JM0vgJQhB5JMToz681TuOCpsJ//K5ZTg2NBE3g2X73i7cv2ElesZ8gq1M7Lu1JexIlvqKmtmO1vbROiNGa67ipio7WmrL4mbIttSWoSnNwE1rOQ/LvMhuqZG315mcZzcb0FRlxbqOemFVwa79J9O+oPYGIpLP5w1EUp6Xi4HwXEZrP5Jars7PPNcxwH/d+AkYdAyueeR1wW4kTgS6Y91yeKeSU33d/fx7+OFVK/Cd3+zHTaubJW2LjgGW1Tnxgkx/zJb+JjswN8hnO0vpdj0j7UNx3MzYZvPaFkyFo1hQYUPvqA8LKpJjEYEwC6OeKeoxe7GTKgfwj/94DHaz9GqgU6ensGPjOZgKRxEMR2HQ63DjY/vi9tIZ8EzhE82VuLqzAfc8/57kPR7Y04Un/uFs/OLLZyvyMXKx7xLZ2RkoOCxBYvqHfk9AmKVoMepw5ap62XPEx7pdFnzyzGr0e9JveJZtap0WydmVqd6A1Dotwq66Bh3iZihKbfqm10m/9VMy+1ZuEDA2PeuKDxRKpccY94ewqrEc5Wlm/8ZmgUkHUcPRaNKb/sQZ38X8ltxuklbUNpN0l9Yy6NKyNFRtsFPLm+t5ZWYEo2zc5iy3XLQY1WVm2XKppV8mMD7gCcjmE9ayudzCKrtk4FbOGPlD6mcs6XQMPttWh2Vu2qCBIFIx6A2g0mbE9efGrxq4Y91yTATCeOzVHnRNb8jx+ofDuGPdcsHZ5Wcdplqdkw1yuQyUltUVN1rbJxszYtTkKtbpGKxZUovm6jJVNkdrObXY60zOYxgO//Q3i7BFlG/8rstaka4bOmSCymXm1EOxubwBcS7Ilp6Tmnl+9+VtWDw9QYPfkI6fZOM061FlM8HAMJLL5gOh2MsDqaDy5rUtWDR9XTndP+oLJqVB6vcEVD8X2YG5gVw79+TAv4il61okzBh++f0hfPGcxiQfip+tCgAVNhOqy8xJOdqbqqzoGZ0Sri1O30koR+xLToWlx5YMw096MOP7X2iP2yRw05oWYdLh2QursPPdk9AzjOSq7oYKG85eWIE/HS3D6sU1cTqKzzMc5ThV+iXbuaXJzs5AwWEJtKR/SHRq+Y2mvvSLvyYFvbQIc7oBYeL3jRU21W9AFlbZcesly3Dv7iO4+/I2fOWJmXyKUpu+fbypUvOAQ2oQ0FRlxcnTAXzx0Zk6e+jas/DQtWfhQJ9HmCXa3uBCY6VdduZWjcMCluWw9/1BhKOc5DGVdjNWNVZi6abVGJ4ICu0ElMZb8lqnGbdctBjbfv9BXICU39E4+Xj1gy4tS0PVvnlTmx4DiOXp5Z+bP2fb7z/A2qW1suUC1AVV3C6rZH3VuVLUl8rN5fgysRwbN8OK5VjZ5bBy7ajUMcrl5oUEUerUOi3wBSO4+b/fidMvfG61689tgp4B/vDeEP7u7Cb89OVjwo7ZKxvKsfvQSaxqlJ9xmCm5XgZKy+qKGy17SQDaZ8RkIm9aBm6a01hosNeZnBeKcEJgGIjpiC3PHcavbvxEyvPml1vw1U8tSlpyW1+evn9pHQhT7thksqXnpGae3/nsIfzoqhX43gtHhPHjj/94DE1VVvzzp1vwdYll2/yy+YYKmzAhiQ8q63XAx5oqMOydwmQggs8/+IpkX2RZDqdOB4Q0FuI0SGqfi+zA3ECund/56DS27zmWNf+CZTm81z8RN6Hnts8uBcDgYZEPtazOiZ/86ZjwwuTqzgYhMAzE+tcdzx7Cf/79KvzTf70952d3ZkKibZeaAMivVti2YSUaK2P1y49V+Rzq4/4QahwWnBj14bbfHcT9G1bE8qInrHC949lD2Ly2JWmjzVsuWowoyxWNfqHNDGNQcFgCLekfEp3aqzsbkpYNaQ04pnPQ5b6/eFmt7PIj8bXFjuPFy2qxtM6RlPOKT1Px2A1ngwOHGkfqAHQ6h1RqEHDP5e1CLhq+zu55/j1886IlcUZl24aVstfg739i1IcDfR7ZnNGNFba0b8yGJgLCtYrNsW4ot6GpyoYfXbVC2IDFqGfQUG6TPF7LoEvL0lC1b97UpscA1OfpBdQPclvdTmxd35aUi7DV7ZJ9drWbywGxwcW3f3MgySA3Vtokl7UurLJLvixJ1Y6UP44glNHgsuLogFdSv9hMevhDUSytc2Ljp87Ev/+/o+gZnYpbVZTrvHe5XgZKy+qKGy17SQDaZ8Tke3m51nJqsdcAsKzWgbsvbxNSSPEzP5fVOlOeNzIZlNQRI5Op841PBCLCwJg/565dh/FUmo3sAG0b5/GTJBL9hTVLaue07c+WnpObec5hZtbwxgua0VbvQoXViFeOjSSlKbrx/GY8+pdubF3fhlOnfbjn8jbc8ewh9Htigd5Na1rw4J4P8M+fbsE/TgfExJuF15db0V7vwolRX1KaP625WMkOzA2k2nnz2thsUCB7+l7Kjoz4QsK4XuxDbbygGcOTIVzd2YAz55XFTbjjV2Ua9Qxe3LQag3N8dmcmJLaJ1ATA73+hHasay9FYGavfxko7ltY5JfXCW71juPH8WCrWjzVWoMJmEoL8QKzNK20mbJnez4NvS18wglWN5Xjo2rNIvxQRFByWQIuDmniO3PJvNQFHPsA6PBFM6aDLOfAvTH+fKterXNAISJ6VO+4PYZ7DHHc9qXoCoCgYtdztwGM3nA1/KILGSrtk0G9dRz2+kyKvsVw78fmTpXJGN1Va8dKRwbRvzOqcFuE5KmwmXN3ZgMU1DixzZz9HtFr6TvvRPexLGiQuqfVL5pTWKtNaloaqefOmNj0GoG32lNpBrsGgw/oV9WipKcOAJ4A6lwWtblfKwZiWoLXcsq5Bb/Y2taL8cQSRHpbl8OJ7A+genpRc1eKQ2JyOn/UF5CfvXa6X++Z6WR3NYswMLXtJJKJm9UghlpdrmbmjxV4DQJ9nCj/+Y1dcff74j13obKpIef95ZWZJHyRdaqsBmfoc8AbRkeI8rRvn9Y750DU4GTe5YvPaFiyaV6ZYXmYjOh2Di5fVYsfGc+KC7Up0kViHVdlNknIw32XB7s2rMegNIhSNYswXxqbp1SiJtmO524H/uukTOHzSg++/eBQVNhM2XtCMxkobzqi2g+M4fHJRFfYcHRICw+Il2w+/3I1tG1ZinsMkKVtabBItry4M+baPie3MgMHXd7ybFNTLVN9L2RGWk05L2TrfhQUX2XDHs4eE3NuJaQp+Pj3Ja76CFReENOI24QPv4SiHx//hbOgYoNJuFuI5iRMI+UmHdU4LoizwVu8Y+sam4lYt8C8ZeFmyGHWwmQ2SKSfuvqwVlWWmgtUFkQwFh2XQ4qCKz/lwKHmAmRhwTBU4FQdub1rdnNJB1+rApwoaKX1zzO/UC8SUDRBzsFMFo+SC0ktqHUl1li6vsVw71TotQrL7xJzRFy+vEQK+V6xqgNWkx53rluNuUd6jbRtWIspCOC5RmRV65uWgNyg5S3VVY4Ws05+pTCtFjYNT6zRLzoSSS48BaJs9JR+Ele8jBoMOKxZUpMw9GP8s6pfiVdmlB5mVdmlDqWWwp+XZ5zL1Cxpxqu8j1efNb1iAkx/15qBERD7gZ14trilLyoN36yXLUm7WAWSW906pzszHct9cLaujFQyZo2UvCUB73Wcib/kOdKi110DMNopn/4s/TyX/RgODuy5rTco5bDakfj45e18lY+95tG6cN+gN4sk3e+Py0D75Zm9KP3EuwLJc3AQRpf0hsR9tvXw5tqxrxV3Pi9KErGuFycDgvf4J3PLUu8LMYCnb8ehfumEzG9B/OoDvv3gUgXBs3xp+Sf9jN5yNjy+sxJ8+GALLxV5SfvPipUkbpcY22T4no5RjidDy6vxSKPuYGLcY94fivs+GfyFlR+Q2owtGYikIKmwm2E163LFuOQa9gaQ0Bbc+c0DoQ+RHqIdvE6n4xve/0I7qMnNKPbmwyi7Iq5SOe2BPFzZe0Czosk1rWnDytF9IOSGePXzy9BRO+0NoriZ9UyxQcDiBbDi0LMvh+OhkUgBLHHBMFTiVmi2cykHX6sCnCyoreXMsZdB+dNWKlNeVC0rv3rw6KSCtNq8xX3+jviCWuZ2SbeAPRZMUYlOVFT/54sdgMeiEdn/j+CgCYRZXrErOn1PomZfeQFiyjr2BcEHKw8OyHF48NJC0wdpn26QNd2OldOoKPr+RFP2eAF482I8fXrUCU8EIbGYDHnn5w5Szp2yyM5RT7y6uBi1L8VhwSWlPNq1pAQfp6V1aXgrIPrsxe88+mzjV9xGu+dmrqs/b8ZXzclAaIl/wG0pe0ubGwy9/KOTB62gox7HBSUl9y7+QUtLX5ZaFqxkUlvJyX1rBkDlqNzDl0Vr3hchVnE+0+gUcB/znn47FzTj+zz8dw/a/PSvleVPhiKS9nwpHUp6ndeO8UDQat7E0f79wVH4D21KGZTn0jvkw6A3CF4qgqdIuucpPa39IPG9gIoTXPxyO+aKhCKwmAx5/tRvL57cKx/GbLYnhbcfW9W341+cO4Z8+tUjymHA0it2HB/D+gBevfziMr16wKG6jVPEMZH8oWrK2gSi8fUwVt9AiQyzL4fiIDz1jPrgsRvzwyg5hFbDFqEN7gytJXjetacGJEZ8wPn9gTyyI+PULWyT7B9+35rofIRW3ApAylsXb9qMD3qT4xm2/O4iNFzSjs6lSViYBpNVxCyps+NFVHegd9+OJ13tgMjD4xoVLJAPSd6xbjjFfcM62YbFR0OAwwzA2AN8E0Mhx3P9hGKYFwBKO454vRHkSHdqmKivuubwdRj2jKlB8YtSHm3/9DhbXlAlOg91kQOt8B06dlg/Iit/EiGcLS22M99C1Z4HjgNc+HIHbZdHkFKQLKit5cyxl0LqGJuKu63ZZcHVnA8JRFvs/Gpd3dL2BpIC0mo31Etuvs8mFWz+7DI9c34lAOIozquxCcDoxYXrP6BT+8VdvCak4xPUjp/gKuXOvy2qUbLtyqzGr91H7sqR7eBK/+N8P4wK3v/jfD7GktgyLah1Jx2tJXeF2WfDZdneck5xu47dQNCo5KAtHWdlz1D67lqV4VXYz9h4dEPSEzWTAY69245I26TzFWl4KeAMhyWefCBb2RQJBFBM1DkucXRDPCP6/X+6U1LeLahy4ec0irF5UjY8vrJTt63LLwi9rn48+z5TiQWEpL/ctRIoCQFuu1mJF7QamPFrrvhC5ivM541iLXwAA/lBUcsaxP5Q66Goy6LFjX29cUHnHvl50Nq1IeZ7WjfOcZmPSwH/73i48+X/S5zguNfj8yt3DvriNmreub8PSOgeW1s70e639IfG8Z97qw3XnNMX5og9dexYCYRY3rW4GAFiNOsm262yqQNfgJHpGpzDiC0oe4zAbcdPjb6HCZsI969tw86/fTmpLftZejcOCT5xRVZK2odTJho0plH3k4eMWFTaToJ90TCz9o5YJcomThG7//DL8/Eud0DNMXACTl1cdGHz7mf24dEV9nB/W7wngo/Epyf7Bp0gq9Hi8kEi9iN26vg3zXRZs+/37+ETzvNimlo0VcFoNcFlNgl64pLUuqV6BWH2yHLCvZywujsPP9B2eDELHQJj9K7Xq22LU4cSoH799uw9XrGrANy5sQVOVHSzHSm5Yd8/z72GHgtz7RH4o9MzhXwB4C8C50/+fBPA0gIIEh8UOrdtlwTWdjcIGaWpmPohnIImdhu9/oR0rGsplA7KJDrX4OIYBfnTVCpiNOiyaV4YjAxNxu9Y+dO1Z+J+vrcbwpHKnIHFWCB8M59NDKLmGlEF7al8fvv+Fdtz2u4OosJlw/blNePLNXlgMemzf2yXkEZKqA6mAtNLBibj+Ouqd+MKqBbju0b/GtV/zvDIsrLJjcY0jrSHm6+f9AW/Ol/KqpcZhxi0XLY5zgm+5aDHmOeTTMagddGnZzGRoYgpXrmqMk/st61oxNDElGRwG1C9f07LxW5XdLDkokwvCap35pPZZGits+Nuz4wcXW9e3obFCemNBuZcCrhQvBUx66QHpx9IMSAliLqHXAY2VNkm7cKDPkzSj5hsXLsbJcT90DGCY3hhWTje8J7MsfEGFDTod4pbYAbGgQ6r9CUpxuW8+UmIkojVXa7GidgNTnhq5HLn21DlyxajNVSwn06nkNpMZx1qCymr9Ah45WU63hD8YkZ7JG0ozk1frxnlj/pCkPktcOj4bODEaS7mV6BvevvMQNl7QjKMDE1i/oh46HSM7YzydLkps935PADv29WLHxnMwFY6izmnB4VMTuPnXM+OO735uGb5x4WLc/4cZX/2ey9swFWZhNDCwGHX41eu9Scds27AS/unNsvs9gZSrV/i0aqVqG0qZbNmYQthHMaO+YFz6GT5lyXlnVqlOQdM9PCkEhoGYnG79nyPYvLYFn2mti1slzetrvQ7YeMGZePjlD3Hzp+NnCktNkNtyaSvCkShuXrMIegayk4Nm+z4HUi9ib995CJvXtuDKVY1xKW/uXLccLMuib9yPSJRDU5UdTZV22cA7i1gqm6s/tgC1Tgv6xv14al8ffv5KN/79qhXYtLYFd01vMJfoH4tXNTz6l2789Isfw8caYz7K8KS0XUr3cpXIH4UODp/Jcdw1DMP8HQBwHOdnGKZgvVYc6MwklUDiDCT+/Nt+dzApdYI4IDsVntnEjleGO/b14prORqHTNVVZ8W9XdCQpg5t//Q5e2LQa5zRXK35e8ayQMV8QJ08HVAfDxXlr+IGAngE+1lSOFzatxvBEEF/6xV9x4/nNQn1IKfpUM52VOjx8+7ldFnz1bxalnLmyzO1Ma4j5+lnudqCpyo7bfndQcxA92zRW2rGkrgw/umoFfMEI7BYDHBa9bDoGLYMuLflt9Tq9YIyAWL3f9fxhPHbD2bLPovatu9zGb0MT8hu/Layyx+UNTSdz+Vri1TPmlwwanbWgQvJZbCa95EuBVMtga51m3PjJMzDiC4HlAIMOuPGTZ6TM60wQc41+TwCD3oCkPeM3/tp4QTOW1DnQO+qHxaDDD3bH8kQ+/HJ3ygHhKZnVMkMTQZxRbcP15zYl5113KNufoFQoREoMrblaU1HIwaacHPWnSS8QiEQl8/QHI6kHY1qDtW6XRVKmU63uAbTbXa3lVOsXiM/TIsvzXTbcvvNQUjD6M63y/hEQ2zjvqTd74lZkPfZqd9qN8+TTZhR66KeedP1u0BtAdZlZdhbc7TsPYXFNGfpOB3Dv7iOqxiA8Uu1+y0VLhM0PPxxKDop974UjuO2zS/HwdZ3wTIXQNTSJbb//AOP+ELZc2oq7L12OO3e9h1++egIbL2jG4loHltXFNr0+MeoT2m8yFBH+5mfx6XXAuc1V+MELR1RtSkmoI5XsZcvGFDJlFMtyOHU6ELehGB9/0BKcPj7qk+yH1WXmpFXS4mddVGPH35/diDqXBZvWLgLLzQSpd+zrxQ+vWoEPBifAccBP/3wMl6+sx0N7Yzltl9Q50VgZrxNKJb1RJsjNOK+0mbBlV/xY/O7n38Mj13fi9p0H0TM6JUwslErv8cTrPagvN+PmT7fgDtFLSf67rqEJITbAb5S78YJmtNSUwWU14UDfaVz5sQbs2n8SX1+7GOefWS34xq1ul6aXq0T+KLSHEGIYxgrEEmwyDHMmgGChCiN+c5dJKoFUM5DEqRMSA7Kb1y4S7t/vCeCJ13vw3c8tw7emZxV21DtxzdmNeK17VFXZUhk2PvAKAF+cnmXLXy+dU86yHHQMcN/VK9A75o8bCCypc+KS1jpBcYnrk3+2G89vRke9Ey21jqwMsPj2u2JVA44OeFPW0RnVKjbcq47lwF25oFxzED0XTAZYQTYsxljuQTm0DLq05LcdmQxK1vvIpHS31vLWXUueQLXLY/O1xKtnTNqJ6h3zSQaHp8JRmPW6uGXFZr0OgbD8IL+h3IYyi1HY8IRfxdBQLj07mSDmIrVOC57a9xH+5ZKl8IejSbOEAWD7nmO4f8MKLJ/vxFeeeEvxgNBpldZZTqsB/mBUUs9+8syqWZWjtxApMbTmapWj0INNh1lajsrMqV35k6djgzdxUPLx13pw5rwytNbLn6c1WKtldQ+g3e5m8jLXZGDi7KkpzaZygHZZPqPaju98ZllSzugzqlMHgEZ9QaxZWpeUbzZdjsZap/QKs1J7Mayk37ldFgTCUdlZcLFx1cxeLvwYRK8D1i6tQXt9edr20+kYXLysFg9f14l9PWOIssC2378Po16HS1rrZP05d7kVlXajMG7guWvXYWy7ekVSUJgvhzhg+Mxbfdi8tgVPvtkbN/v84Ze7Fb14IbSRTvayZWMKmTKK34xXrD+37+3Cw9d1agpOW4166ZUqZSbUOZNXSVfYTDg64MV5zZUot5vxfx7fF6fn+ElyP3jhCPo9AeGarCithJS+L3Qe53xQ45CecW4zGyTl8s0TY7ims1GY1Xvzr9/B7s2r8T9fW40jA158MDiBJ17vwbg/hHuv7IjTWbxc3Hh+zF6Kr9/vCeDpfX245aLF+PZvZtrve19ox+fb3HHjean4y71XdggrZmf7bO9SoNDB4S0AdgNYwDDMfwH4JIAvpzuJYRgLgJcBmBF7ht9wHLeFYZgzADwJoAqxdBXXcRyneP2U2BADqTeBS4XcDCSnWQ+bUY83jo+i1mlBhc0cF5B9al9f3OwOfukX/6aYnw2bKi1DIqkMGzCTsFw8a5knXcCZv+7Nn16Eh/54TFIB8wHbxLxb/FKDFzQoaTnFIU6wznKp20+tIc4kiJ4Ljo/4kmYofPPpd7G0brVkUFHLoMsXikie4w/Jb57SUGGTrPf6cqvk8Vreuoei0aQleN+4cHHaPIFqltzVOi1oqrJiXUe9sMxq1/6TWV/iZVc5s6fKbsauAydx/XnNcTmKVy+eJ3uPE6M+YdY7MLOKoaPeJZvqgyDmGvwswgHPVFJg6/4/fCDkdjw+6sOHI9JBALkBodNiTJq5ece65QiEWUwEIqiwmeIGPYEwi1MebUvzi5l0OjjbgwKtuVrlKPRg02ExSAb7HGmCw06rAeP+UFyOXP7lRCq0poeQW90zPCm/ugfI3ebKcvB5NhPvp8Qv1bqE32yMD0abjenl26TXSeYOTpejsaHcBrfLEnc/t8tSci+GlfS7SJTDyXE/7li3HPc8/15ccOmJ13tiL1Es+rgxCN8fzjuzSrGe6R33445nDwq+4aUr6nHv7iNYWueQ9ecsRj36xqckZZQDsH5lvayuW+524Fc3no1TpwMY8Ezh1s8sxS1P71f94oXQRjrZy5aNKWRATC6lhFHPaMo3bDIwSf1w89oWdA1OoLHSHmcf3C4LvnzeQtz/hw8QZSHMXgZm9NzPrvsY7nz2UJyPxL/04ZHS94XO45wP+LQyiSkdTp72S640aKlx4EcvHcUVqxrw4+m4zfERH1Yvio0hbSY9PrmoGrUOs+yLD35FXaLcX93ZIMwy5o/97u8O4qwF5XH1neol28XLavHSkcFZPdu7FChocJjjuN8zDPM2gHMAMAA2cxw3ouDUIIA1HMdNMgxjBPAXhmFeBHALgPs5jnuSYZifArgRwE+UlicxzUJLTZnwNk3NEg+pGUh87t0ND78uXO9HV61IevPy+Gs9eOyGs8GBQ43DAm46yCmeDasmLYOcYVu+eTXe658QvhPPWuZJ5ZSLrxuIsLIK+OyFVXjo2rNwanxK8S6oqYxkure4l7TWoaHCiq/999tJdXTvlR1x99Pi3BeLselVOeNUy6BLLheRXOoKAGh1O7F1fVvSTOC2+S7J47W8dZ9XZobVGD971mrUobos9WwYNc5XY4UNX1vTkvQccrmAtVLjMEsu962RyR2tNkcxIL/E6/ioj4LDBDENbz/2HB2U7C+8E/74az248mMN0jM4LQZ0D08KuoXXOadOT2HRvDLccmELAhEOLTVl+LfdR4Slffx1+cGPxahDQ4VV09L8UiUXs3Ll7FGrW9oepaPQ9n8qFMG8MnOc7ZtXZkYgIv/CFgAiUVZy47VImheqWtND1DikX67OK0t9ntal1dkOKg96c9OeWoPR/pD05I10ORp7x/2SOapb57tKKjiipN/1e6bgC7H49V+PCzOCl9U58ZM/HcO4PzS9SZN0IE/NS/9RX1Ayb/SYL4hap7Q/d+ikB1KzmpuqrKh1WiRT1In14Q+vWoHvTI9Fb16zSNWLF5qFlxnpZC8bNqaQK1JSpZTQssy/d8yHdz/y4L/e6InrhxNTIdy/5xg6FpTDPZ02wqDT4awFLhzp9+Km1c0w6aU3R9v/kSepz/E+E49UPy50Hud8wMeNbv70ItQ5Legd9+OJ13tgMjC4+/I2/PiPXZL6qsyixz9/ehH0OiAYYfHi4X7BVvDyJ7fRnI4BKm0mfOviJfjRS+8L58itmJfyj3rH/UkrKW556l3s2HhO3N5ffOyrvtyK9noX6a48UdDgMMMwq6b/7J/+3cgwjAtAD8dxst4ux3EcgMnpf43TPxyANQCunf78MQD/ChXBYSA+YLiK5dBe75KdWZpqBuutlyxDz6hPcBKuWNWQNBupa2giqeON+0OY5zALHYlluaTZsOK0DC6LHquaKhGOsjgx6pPMwyXt/AbjgsaJs5bTOeWJ15VTwDodgzOqyhTvgprOSCqZQTA0EcDffrwRT77ZKxinzqZKnNesfHaAHMVibOwyy0vtMjNOtQy65FJvpFoCqdMxKLcZ4wav5TajbL1reeseZSGkSBCf88lF8rNn1TpfvePSuYBXNabO8acWhgHsJn1cfdlNeshlXtdSLovMEi+LUT4NB0HMRXQ6Bk6L9KaPnzijEt96+gD6PQHJF7Sb17bgW08fEJbjfXZ5Hf7w/lCczrlj3XI0lZmx+cl34vrwA3u6sPGCZmzfc0zQTRaDXtPS/FIlF7NyDQYd1q+oR0tNGQY8AdS5LEJ+UC0U2v7rGB3+RbQKhL//4yly+gOAw2KS3Hjtk2eelfI8rekhDHrgq59ahLt2zWyGs+XSVhjSmBytS6sbK2ySAZp0L3O1pKji0RJ00zoTW+sGeIV+mZEtlPQ7o0EnrCbjZwRbjDo8cn0nnBYDWt2xwEKmeV1TzeJurLSjpbYszp+zGfX46cvdAOJn+DVVWfHPn27BFx99I+1YJxSJJj27Eh1U6DQ4s4F0spcNG1PIFSnZTikx6A0KK1vE/fDmTy/CuD+EWocFB/o8cXvZbFrTgl37T+L/u2SZZF0HIyz+++0+3Hh+M1Y0uFDnNOOj8SlhdbVcPy5kHud8Ueu0YNwfwo9e+kAIpl7d2YALWuZBrwPuvrwtKQXajn29uPnTLXj0LzOpBjevbRFWsPHyl7hHlsUY20xz3BfET1/uxg3nNQm6juMgrJhXopvkbBN/f7fLguvOaYpLn0O6K38UOq3EfwJYBeAAYjOH2wAcBuBiGOYfOY57Se5EhmH0iKWOWATgxwA+BHBaFFTuA5Aim1p65GaWsiyH3jEf3u49LSzXFhtdYDrwKcqzK5XD+Kl9ffj+F9qTrpE4u/WS1jrUl1ux6cmZ2bD9ngCeP3ASN6dwLgB5w5aYMkBq1nIqZ1ec5ybdTGZ+CYl4GRcAyV1Q0xnJdM4uPzMj0QFvrLRmZXfyYjE2wUhUciZQql2v7WZd3AZ2dnPq+tAyUFM7M0bLW3ctS1bVOl/5mlHU7wngJ3/uFmQ1ygI/+XM3Ftc5JPM6axnsVdiSl7THHAFj1p6DIGYLcrO/jAadMBjhX9BuvKAZy+qcODLgjZv5e+szB1DjMCfpnHuefw//nrBiiP+ufb4Lv/hyJ2wmA2qd8kv60i3NL1VyFcgyGHRYsaBCU47hRApt/+VSPflSpHoCYqmYpGYPhdnUM4e1pocY8ASFwDB/zl27YhvTNlVlP11D77gfD07nQuSD3w/u7Ur7MjcUlfaj0qWoymSjvn/8VLOwOayeAf7xU81pZ2Lne0Z1saHk+b1T0n1jKhTF6paZiQOZ5nVNNYtbp2OwZkktmqvL8MHgBA6e9OKnL3cLduHx13rw6Jc6MRmIoKrMLIzd+Gvc8tS7WPK1WGo48Qbb1WUmxeMtMYVOgzMbUCJ7mdqYQr7Ekbu3lpQSgLyNCkVZbNuwEic9U8IseP47Po/tv+0+IpsWJjEVZVt9OZa5nSn7cSHzOOcLsXzydXTvlR1Y2VCO3nE//vdY8h5V6zrqk9I/PLAn1gZ8jIaP2STWX2OFDb3jfjRW2TERiOD7Lx4Qrut2WZJSPsrpJjnb5HbN7B2V+BKOdFf+KHRw+BSAGzmOOwwADMMsB3A3gO8A+C0A2eAwx3FRACsZhikH8DsAS5XckGGYjQA2AkBjY6PqAvNO4dEBr/DmC5BO15CYG1hqlvCqxnK8kEZx6XQM2utduPWSZbh39xFhNuy5zVW44Zdvpuw8coZNKmVA4qzlVHVwfHRSGEDzO4k+fF0njHomaRaFGgc1nZFMdy3+fCWB6HTPKDUrJJ/GJpWsznda8cDRD2K7V4tyz168vFbyWr1jPrx3aiIp4NFUaU9ZL2oHamqdHC1v3eUS8Kdasqq2XJnMKFID/9Y3MRek3OBNy2Bvaa0Tx0d8cbNZGiqsWFrrzMozZKpTCSIfKJVTqdlfLbVlqHOacc/lbXjoj11Y11EvLJcc8Exh+55jcdcIhFn0jvkldY5Jr5Psw1azHjc9NrORxyPXdc6KwI5StOj1fJMP+59KThs1pHoCgEqbWXLm8GdaU88A1tomWvYr4NE6I7dndCrOjgJIG1ypskvXyyVtqetFa9CN4wBfKBo3a27z2pa43JlSaJW7XL7MyKfdV/L8dbKzq81J19KSK5on3Sxu8f4kX9/xbtIYy+2yonlRGV77cESyjxwZ8KKp0gabSY9NaxfFAmDeQNJ46yd/vwrvD07CH4pIrsIEZs/M8UzJRFbzofMLafvk5Dkc5WKbzqt8Trl0hGuX1MBlM+K375yUlEmGAUIRDvPKzPjJ369CMMLCZtLjjulcw4m6S2k/zrS/5xMtcpouf++KhvKk9tDrkicr8m3Aw8sAgKT64/9+9t2TSdeusBlik9BCEdhN8pPQ5GxTq9slrJYn3VU4Ch0cXswHhgGA47j3GIZZynFcNyO3rjoBjuNOMwzzRwDnAihnGMYwPXu4AcBJieMfBvAwAHR2dqZxyZLhncKbVjfLzCycSdcgfsPL7zSbmLahsdIe50zIIRioOodgoJQYfjnDBkCz0yienStOE9FYaZUMNKpxUNMFv+Su1VhhQ/fwJHQMk/GAOt2skHwZm1SyajAwuPJjjXG5Z7dc2gqjzE7bg96g5PLQVY0VqoLm6dASvFT71l0qAf/mtS3Qp5gIrbZcWmcUqWVhlR0PXXsWDvR5hJlE7Q0u2X6oZbBnMOjw2VY3Gis9WVlanUimOpUg8oFSOeVnfy2aV4ZBbxC+UARNlXbMd9pQX+HHprWL8V3Rap871i1HU5UVPaNTwjViL5KkXzAtqilL6sM/vLJDuCYwnS7m2YO498oOTfselCJa9HohyLX9TyWnWlI9AbG6/duPN6quW61tomW/AkD7jFytM2QXVtlxx7rlgv016IA71i1P28e0Bt2GJuT9sDNyEOTIZWAr33Y/3fO7bAbcdVkrtjw3k8rkrstaUZ7lFVJKfbB0x4llVrxhlMmgwwuH+oXZlXyfe/Fgf9x4K8Jy+LcXjwKQn/wyW2aOZ0qmspprnV9I27ewyp7kZ2xa04I7nj2IX3z5bNXPLGej2hvK8cbxUdnN4u0mPa4/twmbplNuWYw63Hf1Sjx2w9kY8M7MWp3N+bO1yqlc/t4XNq3Guc1VSe378aZKyTbgq5L3a1PJwMIqO9obXHEzvW84rwmjvjDufO69OP/4fz8cRn25La69UtkmfrW8eAImX665prsKRaGDw4cZhvkJgCen/78GwHsMw5gBhOVOYhhmHoDwdGDYCuAiAPcC+COAq6av9yUAz2a7wGKnMF26BnFu4I56J5bUOXDx8joMT6Z20lLNWk00UEoMf+J5/PXnOUzYsfEc+ENRVYpW7excNQ5qOodK6lqNFTZhd8sKm0lV7mQpSmEpltplm5nM5FFDPpbd9nsCePFgf9ys6Ude/hBnNZbLBrrVlkvrjCItBMNc3Eyi+65eKXus1sFeNpdWE8RcQLxhq8UY29DU7bIkBXHvef69JN2yaU0LHnu1WzK4e0a1HWdU2+P68KgvGBdcBoCe0SnUl1vSriyaLfCprcQ69/HXelLq9bmGVv2vtW61nndGtR33Xb0S33z63Ti7li6IrdX3ysTvCEXi7e+2DSvTnqM16JYvP0xMKc2cy4RTpwP4r9d7BL/QajLg5y9/iKYqW9pUJmpQ2gdTHceyHHQMsHV9Gx7cG79h1Ka1i5JWpSYu+QaAe69oB5Ba7gqdBodQRiFtn07HYH65Je7efBoHLbM0U01Is5n0cJr1kqkjgOT89t98OrZB2dkLqwCA8mfLkO5l5aUd8+P2z2qssCXphW9dvAThaGzDSx0DeKfC6BmdkpQBPoZkNxnQ5p7ZIHdRjQP/9Ou3k/zjG89vxqN/eQv3XtmBz7e5hYlJcraJXy1PuqtwFDo4/GUA/wTg69P//y+AbyEWGP50ivPcAB6bzjusA/AUx3HPMwzzHoAnGYbZCuAdAI9mu8C8UyiX9ylxxoQ4Tw6v5FPlalMzc0KL4Ze7/ifOUL5ZmxbHWM0SkHSOV+K1uocnhefhjezGC5px1oJyNFXZVQ+oS2EpltpBhtaZPGrhl7js2HgO+j0BuKdnqWbTeLtdFny23R03azrdDupqB9X8ppK5NkzHR3zCABqYcYiW1q2W1RNzZbBHEIVCKkh16zMHZPMFdw9P4v4NK+ELRTAwvez31kuW4eJltbKb2ip50VtpN8+Zvq42xc5cRYv+11q3mbSJ2cjEpWYxG5VPPBCjxPfSGjTPdzC6qcIm2c8XpNk4j0hPrdOCD4Ymsem/3xE+y5X+yGRJu3gMVmEz4bufW4ZvTfuyAMByypZ8D08G08rdXMi5OhsotO2rspvx6F+yN0tTakKaOO7QVGXFz6/vxLsfnUZjlR2nTvtRYTVJyv37AxPwTkXgdlmKftJWoUgXk5HSQ7xeGPQGEI5yuOPZg+gZnRKC9Y+/1iMpA1Jt+bU1Lbh95yHcdWmrrO7ifegKmwnnL6pOq4NIdxWWggaHOY6bAnDf9E8ikynOOwAgaZtljuO6AaTetjlDxE4hvyHN4loHltU5hVkRmbztUOOsat0wjM9bzDsb9+4+gqV1DsUKVuvO0HJIzZTOJM9tvyeA7XuO4cmNn9BkNEphKZbaYK/W5ahqYVlOmMWdq7e7URZ48s3eOBl+8s3etDuo86TL7wfkzzD1jPkkjWnvmG9WbjpFEKWAXJDKbtJL6t2WGgf+dddhjPtDeOyGs/G5dregL5TYMprhRXWQS7TWrdbz1G5My5MN30uJfefRuvFs8ktwK1rdzrT+gV7PSC4fN+hpwJsp+dAfWvJhJ9I75sPRAS9uWt0MAOgeSfYB0y35/uGVHZhfbsHn2lenLQNNJih+Cm37cn3/xLhGz+gUvrvzIL5x4RJhks/mtYsk5d5qMuD2Zw/imxctKfpJW4VCS/uJ9QLLcvi/XzobRwa8+GBwAk+83oNxf0jyGlJt+eRfe/CrGz+BUDQq2Ya8TQ6EWezrGUNDhVVRm5HuKhwFDQ4zDNMC4AcAlgMQvD+O45oLVqg0KAkaZRJUUjtzQm3nGfUFJXetHvMFFV9D687QUmjNMSdGakDRVGWF1ajHax+OqHbiCm2olaA22JuvYGc+UnKM+aVleNwfBCB9Dy1ylg/DZJfd+C67qjkbgxqCmCsk2hS3y4KrOxswEQwnLYm8Y91yePxBADF9x4HL2lLMudRHqQ5yh9a61Xqe1hnAWn0vrX6kzWRAU5UV6zrqhRfNu/afTLvxrNaX4JQ6JXfkWn8kzvi9urMBi2scWOaOTQxSch+W5fB27+m4NCb3b1gZZ2uk9qe55aLFOO/MKpx3ZhXpxVlIoW1fru8vZQ96RqfQUDGTNqvOacGSOmecTr1j3XL0n/bj/7tkGYYnAkU/aatQZNp+Oh2DM2vKcEa1HcvdzpR6JrEtO+qd+Ifzz8TLXcOwmfS4+7JW3CnK+75pTQueeL0HQKy9omz6jWKJwlPotBK/ALAFwP2IpZG4AbE0EUVNuqBRJkGlXM9aNel1QlANiDnsO/b14uwzKhUHUuV2hh7zBYXvlQagshFMTBxQ8Mscrnn4dU0B50IbaiVoSd+Qj2DnoDeACpsJV6xqEAZbz7zVl1VjICXD2/d2YcfGc2TPKdY80rVOs+RMosQdtjMhGy9gCGIuIbYpFTYTrj+3SeijTVVWbNuwEt3Dk2issuMHLxzBuD80nVetO2tLMecSLMvh+IgPPWOxPHZ1TouwWS8RT6Yv+tTMrAW0p7HQ4sfmOz0Ey7H46gWLcNfzM4PZLetawaWpJK33K/Ty8bmCXsdgIhDGG8dHs/YynG/zCpsJ153TlJRSUIk/dWLUh9sSctb/2+4jcS8cx/0h2Ix63PzpRQhEWHAc8Iv/PYGOBhfOaa7O6BmI4objAH8oiuGJ4PQm7/kNEOfK/5CzB4lpsxor7ai58RN4vXsUzfPKcO/uI0Kqgy2XtuJ7X2jDd393KK7fFdOkrUKSOBP4xKgPo74gTHqd4n2llMhA4kaa15zdGL+58lUd2Ly2BeEoh0U1sTbs9wSEQPGOfb24clV9LqqAyCKFDg5bOY7bwzAMw3FcD4B/ZRjmLQB3FrhcBUNrHmGlgwV/KBqnoN0uC67pbMQXH31DsaMjN1P35OkAvvjoX1U5TNnI75s4oLAa9UJgmL+e2kCgnJIslhmY+UjfoAW3yxIXSFGSD1gtiTIM8PmWo7LnaJGzfLR1Y6UdLbVlcbkZW2rLspoLulgD4wRRrIhtSr9nCjc+NrMTdCjC4eiAF/UuK3htEAiz0OtAgxUNSL282ry2BS21ZVizpJYCxCK0vujL9wvCTFZfaQlSaH0prWMYITAMTG/s+/zhlC+a+fvlc2Y0kR5exu/dfSRpZVk2ZJ1v8ytWNSRNTlDqT4nlxu2yCPLaVGnD/3ztfBwZmAA44N9fOhq3QSm9QJjdzHYbqFTvsSyHYCSKeWVmvD/gRSgSe0kXCMc2XL9/w0ph1cXqRdX4+MLKkq+bbJNrPci35b27j+CbFy/FsaEJ3LS6Gc+81Yd+TwDf+c0BYfNMsY5btaAcdz1/GLdesozsXQlQ6OBwkGEYHYAuhmFuBnAScuvC5whqZ06odfoTA7taHB0pRX/P5e3Y+MQ+1Q5TuhkmSgN04gHFax+O5CQ3UTHNwCzWgF+UTd5x9oE9XYrzAStBTmZqUwSgaxzS58wrkz4nX22t0zFYs6QWzdVlimdKqQ1al8IGiwRRbPA2JXFAnzhrjJ8NsXZpDdrry2mwohIpW/bAni5svKAZzdVzcya1HFrtfr79hXyvvqpzSr+Urk0TUNPyohnI/8xoIj28jN94frPm4G0q+DbnN1cSo9Sf4q+ROPv459P7tlzWPh+nvFPYvHYxbvvdwbj0FRwX8/1IVmYfs90GKtF7kQiLnftPxu1lxKck6PfEfLCeMT9+/MdjsBh1uOKseuoLEuRaD/KrlsNRNm5TeHFbNVVa4XZZ0O8JCO31xD+cjV98+WyydyVCoVM4bAZgA7AJwMcAfBHAlwpaIoWwLIfu4Um89uEIuocnwbIq1+qlgB+UntNcjeZ5ZWk3mJNy+k+M+iSP5wO7FmOs6fU6eUcnVfkuaa3DC5tW48mNn8ALm1bDqGdUX0eqPOI3inyA7nPbX8HfPfIGPrf9Few+PJC2rnkHTEw23ryrretckirgV0iGJqTLNTyZvXKlkhk59Dpg89qWuHM2r22BXkYD5rOt1fR3LX0iV/2BIOYC/IslQPpl6va9XbjrsjYKDGtEzpaxXOw7Ygatdr8Q/oIau5YpE4Gw5EvpiUA45Xnivs2jxDZq8UF48lkvcwlexlMFbzOBb3M9A83+FH+NqzuT7cjtOw/hyKAXC6vLsH5lPXZvXo1vf2YJHn65Gzf/9zv4/IPKxj9E6ZHKBhZ6TJct0um9w/0eITAMzPhWV6xqAMBvuG4T0nrR7FNplOjBTONXveN+3PrMAcm2shh16Ds9hevPbYLbZRFs48eaKsnelRAFnTnMcdyb039OIpZvuCQophmkWjawi0/BYBA2R+BROgMicelftmdSdA9Pqp7twrIcdAzw/S+0C7m9srV0r5hmYOY6N7VW8lEuLbNv1G4Eo7Wtc52K4viIdNB6yddW48wa5TP9ybkiCGXwL5Ye2NMl63CHIiw5vRpJzGF3xaoG6HXA4loHAJotJ6bGYZHcQE1uBQxPsfoL2eKUR9pe93sC6Fggf564b4tnHMu9NOahGcDFBctyYABsWrsI9S4rNq9dhKf2xZY5A9mRdb7Nl7sdaKqyaxpf8NfQydiRAU8AKxbEjmM5JOUnLobVgUT2kdPrOgazRkeno19GhzPTL2M2rWnBvbuPYPvfnkUv4lNQ64zJ0pJaBzatXQSWg5DygV8tm2n8Sm58rNdBmEE87g/hsRvOxjyHmWxjCVLotBIlSTaX6KkNJiUeL7dcPpVBSUxcno3AUS5yzKkN0CXuJrzxgmYsrnVgWZ3y3YRTUUwDrGIN+OWrXGrzEqrdCEZLW+fjpVHPmE+yT/SO+WSDwzSQJQjtiF8sLal1yKS0ye4Gkrl8wVQsefN5xDnsEnPk3XLRYrhdFskXeHMRgx746qcW4a5dog3ULm2FQZ/6vEL4C5EIi8P9nukNc61odTthMORmsaLbZZXsl3Wu1L6Z2pfGYubyBpLFRu+YDwdOeoSJLnyQ//HXYkEKrbIupSsXVsf2hFi5oBxDEwHMK7NAr4Pize90OkaRvBbTZBQit8jp9VqnKWtym87GF9ovkOsTS2oduPH8ZiFlwVQ4SmOXFDRW2PC1NS34dkLKhx37enHLRUtg0ENV/EpKLuTGx4tqHPjBC0eEl3IcONJVJQoFhzWQLaOtNpgkdfxD156VkdOfrcBRLgJQagN04qB9vyeA7XtiuW5e2LQ6K8akmAKyxRzwMxmYuA3WTIbCl0lt22lp63zkdSwzGyT7RJk5tSqngSxBaEP8YsntsmDTmpa4AObW9W1odbuycq9cv2AqplVPPLwtqy4z4fr/+9c4/bnt9x9gRUP6QN1cYcATFAIIwMxGPY/dcDaaqlJsvJZnf0Eqf+TW9W1Yv6I+JwHiVrcTW9e3Jd0vXb9U+9KYKE4GvUFs+/0HSWlFfn59J+aXWzXJejpd2TyvDAur7Jr0qRJ5LabJKERukdPrT/zD2VmX22ydk22k+sTmtS34vijYSPKfnt5xv2R6jh9etQL3vXQUm9cuRoXNJNQpf4xU/EpOLi5eVps0Pt68tiUuMExtVdpQcFgD2TLaaoNJUsff/Ot3sHvzaryQgdOfrcBRtgNQagN0uX7TXmwB2WIM+J0Y9eHmX7+T1DdeKPBSOLVtp6Wt8zHTw2bSSy6DtZrSTB0jCEITYjvU7wlgx75e/PSLH0MowqLWaUar25W1gFeuXzAV60amOh2DyWBEUn/6Q5EClar48IW011E+/QWp/JG37zyElpoyrFhQkfX7GQw6rF9Rj5aaMgx4AqhzWRT1y2J64U9oR65fhKOsZnlXoiu16lMl8kqyOXeQk9/JoHrbp0Umi8EvSOwTbpcFQ5NBjPtDANTldZ/LyI1DPxicQM/oFG773UFsvKAZ2/ekfyEqJxcvbFodNz6utptxbHiS2moWUdDgMMMwiwH8BEAtx3FtDMN0ALiM47ithSxXOrJltNUGk+SOH/AGhCTvswm1Abp85bsttoBsMVHMS+HUtp2W1BW5lr+JQERyGezKBeVZuwdBEDPk86VgrvVnMevnpkq7pP5srKQBBk+p1JFc/kg+p2ouMBh0WLGgQtX1i+2FP6GNXPQLJboyE32aTl5JNucO2ZRfLTJZLH5BYp9gWS6jiW9zEblxKDe951wgzGKxKD1aqvhVOrkQj4+b55VRW80iCj1z+BEA3wbwMwDgOO4AwzC/BlDUweF0Rltp7h61waRsBp8KnV9IKWoCdPSmvfDM5aVwWuVPTV+UWwZb65z99UsQhSJfLwVzrT+LWT+fUW3HfVevxDefntGf3/9CO/Q62pSOR6qO7rt6Jc6oLi4fR2sO4EJAL/xLF5bl0Dvmw2l/CFvXt+P2nfGbxGXSL5ToylzrU5LNuYGUXr/3ig40VdpUX0uLTBarX0DyrxxeF477knUhv0kcEGvXZXVORYFcNXJBbTW7KHRw2MZx3F8ZJk4oS2INoVxHUJO7Jx95UKUohvxCuYDetBeeuR6gV5tvWW1fnOv1SxCzmVz372LXH2ZjvP6cmArjS7/4K269ZFnJ+yfZgGU5sBwbV0csxxZd8FxrDmCCUArLctj7/iC6BifxwJ6urG9CrURXFrs+JUqHMosO929YiSMDXkRZYNsf3ofRoFNt97TIJMlxaSOrC2scKLcb8d3fHUS/JxD30oyPYaWC5GLuwnD8XPNC3JxhXgRwM4CnOY5bxTDMVQBu5Djus/m4f2dnJ7dv376sXrN7eBKf2/6K4pyr/KxBpcFMtcdno4xExmQ8asuFrOaKbMhoKaKlX2k5J4f1O6fkVA6GYXDNz15Vfd6Or5yHQtrTOcSsltNc689i1c9yuvDG85vx6F+6S9U/yahiE+V0/0fjuObh15PqaMfGc3KSyzcTIhEWh/s9qnIAEwUjq3KaD7qHJ7Hz3ZN4+OXunI1llOjKYtWns5RZafuzLctaZJLkOKvkVU5Tyc//fG01GAaa25XkYlYj25CFnjn8zwAeBrCUYZiTAI4D+GJhi5QZanP3iHe9PTHqwxvHR1MuLc/G1P1iyS9UqhRLSo5iKUcic3V5Sb5zfVEckiCyT6H1aq71Zz71s5q6lNOFDEP+CU8hcvlqRUsO4EJQ6P5OaGPQGwDLQbI/DHqV64pU7a9EV85Vf5fIHqlkOdHuKdFXWmSykHJMOjgzUsnP8GT6Paky0YHUdrOTggaHOY7rBnAhwzB2ADqO4yYKWZ5soCV3T77TPCgtI3X6ZIolJUexlCMbzBY5y0eur9nU7gRRbGjtX7NFh2UTtXWZaiOVYsh/WAzML5fO5evOYS7f2SzbZE9Ll1qnBXoGkv0hHOUUpVoplfafzX2QSC3LYrtXKvKqhkyeifpFDKXyI0Wm9T/b5JGIUdA1XgzDbGYYxgnAD+B+hmHeZhjm4kKWKVP4HC0WY6xqleRoOTHqEzoXEHvbc8tT7+LEqK9gZeQ7/ee2v4K/e+QNfG77K9h9eAAsO7enK+a7rYq9HJkym+RMS99Xe85saXeCKEa09K/ZpMOyidq6lNKFm9a04PkDJynP3TQOswGb17bE1dHmtS1wWIw5ud9sl22yp6XLwio72htcuGPd8iSdccezBxW1YSm0/2zvg8SMLCfq9kS7Vwryqhatz0T9Ygal8iNFJjJ1fET63OMjpSuPRIxCp5X4B47jHmAY5jMAqgBcB+AJAC8Vtlja0bIpWr7TPCgpY6LCqLCZcHTAC4tRh4VV9jn7hq5YUnIUSzkyRc4wLS2C/JJq30pr6ftqz5kt7U4QxUiq/sWnfkrUB8WswwqJlhRbvC4c9AZgM+kRjrK4pK1uzvobiQx4A3j8tR7ceH4zGCaWWujx13pwVmM5zsiBrM122Z4L9nS2zq7T6RisWVKL//1wOK4/PPF6D/o9AUVtWArtL9UH7919BPXlFvhD0VnVpnMVXpYXzSvDqsYK+EMRNFbakzZVLAV5VYvWZ5rttkkNSuVHikxkqmfMJ3lu75gPZ9aoS4VCFBeFDg7z0vE5AI9zHHeYYZiSlhiW5dA75sPwRBD+UFRRXlAty9EzJV0eGbHCcLssuO6cJmzf2zWrl30oKWsh2kqKYilHphSrs8Pv/nqgzwOWA/QM0N7gwpoltYrkV00+YJblMBEI47Q/DKvRkHI55Gxpd4IoRuT617wyS9LyuR98oR0NlVZMBCIpdRhvV0Z9QZj0ujkzoNeiqyh/Z2pqnRbUl5uxpM6BqWAENrMB9eXmnOn/QtjnfPqMpWRPtdTLbF/2q9MxqC+34dG/vKWpDZW0P8tyOD7iQ8+YD3aTAbVOMxorlcmkXJtlkovd7bLgms5GYWPK2damcxWdjsHC6jIsrJbXq6Wkr5RS45B+pmq7WfJ4vu98MDiRZJsqbCaM+0J4Y2IUvlAETQoDpLMBJfIjho9VsRyHH17ZjuHJIH71ei/6PQHFMmU3GSTbzmYyxPm9/acD+M4zB0hflRCF3jr4LYZhXkIsOPz/GIZxAGDTnFO08AGlFw8N4Eu/+Cv+4Zf78PkH0y910LIcPdfwRggArljVIASGgcIv+2BZDt3Dk3jtwxF0D09mZRmJ0rIWS1sVSzkyRSxnPLlydtTITe+YD12Dk3j45W48tPcYfvZyN7oGJ9E7lt3l5ZEIi537T+Kah1/HV3/1Nq55+DXs3H8SkYi0Gpwt7U4QxYhc/9LrkLSS5vioD91DPvhDUTRVWeOuw+swXifc8Mu/4s3j47jm4dfnzBJI0lXZp8FlxYaPN+E7v9mPW397EN/+zX5s+HgTGlzW9CdrIJ/2GZjxoXe+exL/++Eonn33JPa+P5izflIqMqrVl56Ny9ATyaQN053L1/vnH3wF//DLffjSL/6KFw8NKJJJuTaLRFjBJvzl2GhM1o+NyPp8iX1Q63iMKH1KRV+pQa9DUjqEO9ctx/hUKKmPifvUoVPeuH7hdlnwj59qxl9PjKmKv8xFxLGqGx/bh+88cxAP7j2GL5+3EE1VVsUyVes0S6a5qnGYBR037A3i2PAkblrdDLfLQqknSgSGK+CW9wzD6ACsBNDNcdxphmGqANRzHHcgH/fv7Ozk9u3bl7XrdQ9PYue7J/Hwy91Jb1JeSLPUgX/LonQ5eq4Rzzi4aXUzHtp7LOmYJzd+Auc0V8teo3t4Ep/b/oqiulD6Jj1XMyHSlVVcPrfLgigLDE8qbquMG1JKVotNZhLLpWRWRL5mtqi9zxvdo/jSL/6aJA+P3XA2PtFcJXkPNfLOs/+jcWx68h2s66gHv2Zi1/6T2P63Z2HFggrZZ8lRu+dETksNhmFwzc9eVX3ejq+ch0La0zlETuVUqn+9cXwUf/fIGwBig5CvXtCMUX9IWFWwsNqO//jDB+gZnYrTLSdGffjc9ldw4/nNePQv6v0CpRTrCp1itVF5JKOHTZTT/R+NCzMGeSxGHXZsPEfWXmRCvjcLOjEyiZc/GMaIb6ZvVdlNuGDxPMUzotRSCjKqxbcAgNc+HBH0lhgJ3z2rcppvMmnDVOfK1fuPrlqBBZU2tNe7ZO8jd+6OjefgnucP4x/OPxNHB7xguZjPd8tFS3Bpx/yk6yX2wU1rF2H7HvXjsVnCnPdRsyHrxeQnvPbhCH7wwhF8bU0Lxv0hWE0G9J/2o8phxscaK+L0vrhPJa5o3rR2EQBoir/kgKKW01Sxqqc2ngO72YihCWXjd/EKWx0DdDS4sGheWSxAf94ZcX5ypc2En77cjX5PAL/4cic+vbQ2J89HKEZWTgudVuL86d8dJZ5NAkBs+Q/LQdMyvGJYTploOC5eVosXNq3G8GQQP38lWYmkmz2idEmimgFIrvIMpcs1WYxL84pBZhJRO5jUkqdXC2rlxheSXiruD0Vk76FlCe6oL4hrOhvjUrZsWtOCMV9Q9j7F2O4EMVuQ6l/i5ZzXn9sEfzgqONb8bIn7r16JEMvG6TBeJzCMNr9ACcW8dJx0VXbp90jbmAFPACsWZP9+Wu2zVpkcnQzBF0ruW6OTISzMUdyrFGRUa3qP2bgMXYpM2jDVuXL1fnRwAt/6zf6UMi137qgviC+sWhDXNzatacG237+P9npXUjkS+6DVaJAM6sy2NiWk0Srrxeon1DotWNfhxrHhSTywpyul3hf3qX5PAE+8Hsu/31HvhNGgw9u9p4syTWGxkSpWdWLUrzgFBJ/ruLm6LGkyxd9+vFHST77+3CY8sKcLNlOhw49EKgqdVuLbop87AOwC8K+FLJAYfhn6mydGsf+j8bTL0WudFugZKFqGJ7XEPd2y91ykUxBfO3EJ1EtHBrGwyo6PN1VqWsqidEmimqVvqZzkTEhV1mJdmpdLedB6Dy11xTs75zRXo3lemeJcbmrKJSc3g15puWmqtEvKQ2OlvMxrWYLrtJiSlghu39sFh8WU8nkIgsgPLMtBxwDf/0I7LEYdGipswiAGiPXZB/Z0wR9O3mNArBNytTw/1Y7RkQiL/R+NY/ehfuz/6LTs0mWiNHC7rJJyVOfKfWBIzaIIrbuYByJRyb4ViEQ1lzsd+fCjMkVreo/ZuAw9n9SUmSXrnePSy7RcmzktJtzz/HtJPt+6jnrJcUziPjZOi4HalFAM7wO81j2iSSfnmoVVdixxO2X1vlg/26Zz3PL0ewJ4/sBJ1LkssJsMiuMvc50ah3ys6tjwZMbj91qnBQtk/OQFFTbcsW45fKEw+aRFTEFD9xzHXSr+n2GYBQD+I9U508c8DqAWAAfgYY7jHmAYphLADgALAZwAsIHjuHGtZeODpffuPpI0s0/uTcrCKjvaG1zYvLYl7g1YouGWeoP30LVnIRThZN/q5fqtX7qZlVpmj/COaWKZE50YNTOMbTIJ0DNR/uLB/22/O5hU1jeOjxbd28hMN0xTeg+1MpcqCJututJSLjm5sZn0ksefUS0tu2dUyzvgSuVdTCjMosJmwhWrGoS0Es+81YcQGUyCKDhiXbO4pgz3b1iJKMtJ6rhTp6fwnWcOxukjXifcu/sINq1pSfIj5HSDmuWfPaM+SR3SM+rDOx+N4/adh4R7bl3fhvUr6mEwFHpeAKGFVrcTW9e3JbVpq9uVk/tp9Tt7Rn1YXFOGmy44U9g475GXP0zaxTyRYJiV7FvBcG7sYbHOpktEi28B5G9l1mwkEmHx3oAXt1y0GNt+/4FQ73esW46JQBg3r1mEZ976/9n78vCoyrP9+8y+TyYTspCQhJAEsrMERAu0glraxhVcaosblm4IFdvarz+Rqq1fcaGfiF1QatXWitZW1CrVghatuMSFfUkIJCRknUxmMvtyzu+PyTk5Z+Y9ZxZCEmDu6+pVmcyZs73v8z7v/TzP/bSj0+EBRSHGVou9s0CIPMblMhCTiHYe6UZTtzCrctONM/DPO+YnI22XxnkItqfJPa/sx32XVxH9BNYmj5XkhExGIRwm+1T+IC2wz0VWrWD9K7JqccfCMly/+UNYdCp8/8slcfmX8x00zeC4zYX8DA3WNlRygSpW6/nxIQnRPLOGGyu9Ln9S46HYqseRrtiGgRE7R2HzrmOcBFvaJx2fGG953e0AKuJ8JwTgLoZhPhtqYPcpRVFvA7gFwA6GYX5NUdTPAPwMwN2pXghLli6fV0IU/yeVo7Mp9qUTDJhZaIEnEEIhoVsmiYjd2+4QlApFnyfRsvhUDXw8gjaVUpZEHdNEOwazZH0ym+x44G8OLDoVViwoQXmOERW5Ju69jcfSPH7DNH7JRumExLuVxkMqEh7JkrCjdV2BcDhm3KxaWIZgmLzpTGVTlcoxJp2CK7Phv0eTdryZ5jTSOP/AtzV7O5y4//WDWHd5JdHGGTVK5Jk16HT4YgOruUb0u/3YumIuPIHwiOrqG7Ryog3Rq+X4wfP7BXbynlf2oyzbcEb0adM481AoZLiqLh9l2QZ0OXzINWtQlWc+YxurVGW8MvQKfPOCSOM8dkyuu7wq7rqWoVMS55ZZp4x7rSlpHJ8hmbKRxumQvGeDbMZ4xIFOB37yt72w6FRYeXEpSrMNYBjg19sPccTGmkvLMeAN4fZn3yPa6ssqcrB1xVx0OnzIM2tRlWdCm91DHOP1RZkx+5gTNjdxb7jy+c/xxqr554PGcBqngQOdDo5IzdCriH6CTi0f8yBZkVVPnBNZBhWu42nst9q8eHxnE7aumDu0d6Owq6kXt88vwcuftuN3/2nBrRcVYcvN9QiEaCL/cr7jhM2NB14/iBvnFOH5jyOyHHIZUJFrQq/LB7snEKPn/NR7LZLjgbT2lmcbiO/0hM2NVpsXQNonHc8YU6qeoqjHKYraOPS/TQDeA/CZ1DEMw3QyDPPZ0H8PAjgEIB/AlQCeGfraMwCuSvW62IHuC0prBZIgk1EozjLgghIrLp6WgynZsWXyJCJWSqtY7Jjo60i1ozFw5rpSJyIZkEjpG+vEt9q8nM7QqkWl2Lpi7mktYPzNQafDh407mvHjl/aAosD95ngszet2+oklG91Oca3a5M+RvIQHS8Lyn5UUCTta12XVq7G1sQ3L55Vg5cJSLJ9Xgq2NbcjUq0WPSUXuItljfEGRMtrgmSujTSONNBJDtK3pdPhw32sHOYkJIGLj7rykHL/efgjL5hZxHZlZe8TahPpiK+omWXDhFGnbkKw0D8VQRBvC/jcfvmBEnzaNsxcKhQx1kyz4anUe6iZZzmjGTaoyXqEwcN9rBwRj8r7XDiCeGzDgDeDOS8pj5pbTG5A8LlXf90zJlJ1JpHuejg5Yfe9Ohw+PvHUUDAPcObQHASLjZMPbR3G0e5Boq2mawVuHunH95g/xvT9/hus378Zbh7pRaNHF7CfWL6nFRSVW4l4x3t4wjTTEwNeop2mG6CfIQI25dCJbqcmfEw9eXQOHLxgz9lttXgTDNHoGA/j2lo+wcUcznnqvBcvmFgEAHnzzCOQySpR/Od/R7fShoTYfvxlqoPzEO83YuKMZd774BZzeEFYtLMO19QXEpEjSeBBbe4usejx6rfCd/vKqajy7u1VwfNonHZ8Y6/Q0fivGEIC/Mgzz30QPpiiqGMAMAB8ByGEYpnPoT12IyE6QjlkBYAUAFBYWxvydHehHupyCQR0d/cg1adDS60qpBIOUicrqv4hlpyaSvRovC0IqsyKZsrVkMjQS+W50hL3AooVGIcdHx23cMdFC9E+8Eyl9uGhKrEOVDBKRtBir0jypsZpKw7RkkUrGdKZumISlqMhGZmtjG75alSt6TCAQxt5TDnQ5fcgzaVAz0QyVRKZxKtdVbNXj7sUVSZdlJotks5fsnljnxxekYfcER+wcZxrxbGoaaYwHpDJOs43DtibPrMH3v1yC4iw9/CEaz902B/s7HLAaNTg14MHldfnY2tiGa2YWYMv7Lcg2alKaq8k2n3L5yWuB0xsi+y6joE+bRupIxEcdLfufatVUn8tPHJN9LungtVWvwX0fHxT4D89/3IqNN8yQPO6EzY0/vn8MDy2t42Qs/vj+MUzLNY67hm2pvL+xzuwj4Wxd90MhGgc6HYJsXlKAhdX3ZsdGU4+LOKaj4w984pa/H7PoVDg8tK+szDPi9ZXzcNLugU6lQI5JzckH8sdGLq+PzXiqXDzbcLaO1dMFfwyLjV+XP4SQiFTWaEonVuQaseXmes5vCdMM+l1BbLpxBjb/5xj2djgBAEVWLQAKh7ucXMZwp8OHjTubsHpRGbzBMDyBMFp6XWO+N0oWozFOc0waaKPsCRB534EwjZca2/GjS8qIf+92+sAwQGu/G/ohuwUM2zlWiuJwlxP5GVoYNDKsWFACmgFkFFBk1cHuiQR62e/KZUCWQR2R9zyL3tW5jrHWHH6GoigVgPKhj44keixFUQYALwP4EcMwTooaHlQMwzAURRHj6wzDbAawGQDq6+tjvsMSrBadCqsWlmFrY1tMOfqmG2fgYOdgyo4aiYitKTBLkrPxyFt+tjMfrIEvtuolnctECdBknNREv8tG2NnnHl36suG66ZiaYzwjDlKimwNSad6Z3qRJjVW2YVr0dUs1TEsWqejcyWXA8i9NRp87AJoBFEP/loskNwUCYbyy9xTu3TasoXj/ldW4qnaiKEGcynWlQvAn+35T2cCZtSJltFpyGe143CTGs6lppDEekMo4lcuA1YvK8MInbbjrkjLoNSo0ttpBM8Brezrwg6+U4tkPWtDY6uCqJBQyYMN101Fo0aU0V5MlrApF1oLiLP2o6tOmMTKQGqejbf9T1brNz9ARx+REs1byuIocI354cVmMP1CRY5I8zuENYMnMQqGMRUNV3IzjVO8PGF2SdzzKX5yN6z5fg5VvE0mal9H63mGaJo7p6NfG2mp+kC+6TJs97+M7mziJiui+M0VWLe6/oholWXr85vrp+PWbw3IWDy2pTeuoJoGzcayOBPhjOBAmj9/CTD2oMQxARNvEyyqzcMPsYuztcHB+1ve+XAp81AqHL4g7Fpbh21s+4ubRqoVleO7DSDaqWauM4Q7Gm368FEZjnBaYtajONxPfd3m2EUtmFUCvJstDBsMMvvH4sITO6kVlKMzUwaKLNFBnbRz778JMHdQKGf78YRs6HT580NzL2T1+L6/Nu6RlK9IYfVDMGNYoURT1FUQkIE4AoABMAnAzwzC74hynBPA6gH8xDLNh6LMjAL7CMEwnRVF5AN5lGGaq1O/U19czjY2Ngs92H+vDN5/8CMBwZMOokWPmJAvCDIMckwYMA26CsNAoZXgjCUeNdSz5RBWAmM+iSVTS3/nZzn/gaVPxrwsAvr7x9K4ZAFp6XQn/TqLf5X/vhxeXYsv7sfewffX80yLkAbIzDyAlZz0UovHP/Z24++W9iRx32tYueqyO1iYx0SwLFp+csOGz1gH85t/DDTzuvKQcs4oyUF9sjfl+44l+bqFnoVHK8OflF6C+OFP0PGJzYaSQyvNNZm6w2N8xgM9a7RyZLqcAq16FmUUWVOdnjMg5ksCIj9OzERRF4fo/fJD0cVu/exHGcj09jzBq43T3sT6seXEPfnFFFZzeINbySCs2eHzXZdOw6q+fAxi2XTMLLTje5yb6Cf+8Y75kU65kbU8oROODFhsaW/u5zdTdiyuwuCoXNM3gQKeD06etyDGh3eEdN1UH5wFO6+FGj9NjPa6UxtTpIJW1ttXmwhcnB3Cs182tayUT9Jg+KQNFVvHrbOl14dY/fYyG2nwuc/j1vR14+pY5kutbqn5EqveXqv+V6vrN35fw8cKKC0ZKd3ZEx+l4xZ6TdlzP0zAFIs9/64q5RM3LUIjG4W4n7J4gaJqG2x/5NzumswxqMAyDB988HDMOTtjccfc1y+eVcFWQqxaVctrCJDL5gSuroZJTOGn3Ym5JJtGfPg+Q9lETAH+vm21QwxsKo3fQB2+AxuHuwZgm5kBq++CRAN8m5pk1WHNpOdHPenhJHdRKGXH+srq5mwn8x5lcGyUwLscpTTN4v7kPa7ftE5CzGqUMv76mFqUT9Ggf8GJSphZ2TxAfHx/2KddcOhUb3j7CyeoAkee7YkEJACBMA1veb4FFp4qxXSyB3+nw4R/fvxAdAz78eCiQy/+tEdrHppE4RMfpWMtKPArgMoZhjgAARVHlAP4KYJbYAVQkRXgLgEMsMTyEVwHcDODXQ/+/LZUL4mftsPIF0YN297G+0y7BYLvZApEyUiCSxSDVOEKsscTxPmG2M6lZ20fHbSldM00zaOt3o9vphzsQAiT0r9jfYRemo92DxO6o0efkR9ijNZ6HyxQGUZlnTLlDr5QzL2waoeEyq8RkQ2iawQctNo4YZp/BaGZyjIbUBU0z+NfBbtz10vAze/Ta6fhatbjDoJLLOGIYiDyX3/z7KLaumEv8fpfTRxwj7JwQQypNVpLJ9EklUyfZcnAA8AbDCDMQNBa8e/E0eEU0h7tFnlci83g8SVGkkcZ4RPQ8yTNrYPcEQNMMt2EBIvN6484mLJ9XAi9PyscXpMEg8htHup1Ee8B2B2dBCsDxbfsEgwZyGQQyS/y1iK26Ye3H/15dg0umZnMVQXWTLKibND6rDs4mjAcb2tpPrg6LHlMk+Hwh7Ot0oMvpR65JjZo8MzSa+FuAVNbafncA/qGMIC4D+Ioq2N0BFElwWt1OH6eDyEe89S1VGQsgtftLNZM3FR8BOD35i/EwbscSfPsaFimf73T4YNTE+vsyGYW2fi+3v7r1S8WCMf3jy6bi1S86sOXmesgoCjqVHIEwjRM2NwrMWmxeVo/G1n7km7XE81LU8B4n36zlyuSvmRmr+bl2234sn1eCLe+3oKF2PnF/cr6/69PFufD8xNb5yypy8K+D3YLx++i109HW70anw3da+2upa4n3PPk28ZqZBUQ/a+XFpej3BGDWKmPmkUWnQkWuEQzI3EQia+O5BKlnHmlwOYBAiAFFAQ8vrYMnEMKgLwilnMLSP+wmVm8/eHUNJhiUAmIYGJbVmZZr5LTXSbZr484mPLy0Ds09g/CHw2AA3D4/QiqzsiDJcmhpnFmMNTmsZIlhAGAY5uhQVrAUvgRgGYB9FEV9MfTZzxEhhV+kKGo5gFYA16VyQfwyM4tOhWvrC1CebQSFSNZGz6APOhU55T6ZEoyR2qjRNINDnU7OwWGbtVEUML80C7OLMyGTUSk5lzTNYOeRbjR1uzhD8bPFU4m/M8GgibmvH11SFmNkfv61adAp5fjkhA0quQyBMA2VXCb4Tb7GY3QEKtXNrJgzX0nISI4u74o+7wmbG42t/acdIDhdJLupSdbxael1ccQwELm/u176AlNz5qE0x0g8xhMIE8lLT4BMdk7K0BI76OZnSJefnmnJh1Q2canMMbVChvXbDwue8frth/Hid8lkep5ZQ3xeuSbpeTweSKH8SYU41X4y6eMmFkxCx8m2M3BFaaQxDLF58odlM2F3k3V95TLAqB52o4qsWthcAbzX1Id8sxarF5XixcaI8wtE7IFONfx9qTLnkgkGFFv12HmkG3vbHTHZPuxaFL2u/c8/9sFqUGNeaZZgfo/H0vSzBePFhhrUChRZtVxmLRDJ6jGopV15ny+EV/d14t5XeXINV1Tjipq8hAjiZEHTwL2vChvS3fvqAfxl+QWSx6VKgkbrw7LH5Z0hfe1USd5sg5r4/rIkGuMCqctfjJdxO1aItq+bbpwhKuPFZi9GZ/+yz+6amQXY8LYw8eGRt45g9aIyqOQyOHxB7G6xcXa6cqIJLUOZ83pNZN5GZ93pVXJilp2YBqxcBlFZw8sqcmIChefTuz5dnCtzRWyd3/qducT93P9dNx37O50xvsXpItHnybf50clh7HXmmjWwGlTI1KoE9lOrlGGCQYWjPYMJ+VvnOuI9c5vbj4o8Y8wectONM7Hy+c84OxfduPDn/9iH3ww1DIy2nTIKmJZjRJ5Jg827WkTf4ZHuQby2pwMFFl1MZvhzH7bC7gmkddTHEcZ61jRSFPUUgD8P/ftbEDapiwHDMO9DPBV60eleEJuRWbl6Pj5rG8DP/7EvJpJSZNXGaPnFc9SiySyGgeRGLVHy64TNjaaeQWK28zUz8lNqOCf4bR4xDETIrNWLymLIKVZTlr8whcIMNr3TzB1r0angDoRxxwuf4/r6Quw83IWrZ07C5l3HuIznlz9t537/WxcUEjtmprKZFXPmu53+mPewt90hKE+JPi/bQXisNJpSQSqOz3ERDevjNrcoOSxGXopt0miQO+jOLZGWlJAiTEhIlhjhN6JiwQ+CkFA81J01OtNaao51O8gZT90OP1AQ+/0wDeLzuqxSvOHfCZsb67cf4oJGALB++6G4zXpGGqfaT6Ys15BGGmcaYjbihe/MxWetA0R7ML0gA/3u4Y3Ir6+pRVP3IADg5IAXcgr4/pdL8Lv/tMDuCWDNpeVcEw8AONDp4PwI9pz3vLIfZdkG1E2yoHVoDeZn+6xeVIYpWQZMHlqLSPajsbUfBRataIUO/7vpbI34II2N9dsPIT9DA08gPGpZZkaNHD+6pBzH+4blGn50STkMGvEGrgCwr9PBEcPs9d/76n5MztJh9mTp8vRUsum6RMZaV5yKoGKrHptunBGztscjQavyTHh4aS2aelzccaXZhjOmr50qiR2gw/jel0tx32sHuPm87vIqBGly8JxFqpVi53tAKNq+bv7PMay7vErw/B9aWovWPlcki84fQp/bz/lHUlWNAIb2gzoY1HI0tto5O11k1SLXrBX4wesur8Lv/9PM6Qb/8qpq9A76RbPsSONr0bRsGNRKgbQMR/6tmEv086x6FSYY1WdlFuxogaYZ7OsYiGlydjbOFbF1vsPhJX7u9AWxaWdzjG/BItVsaraiOXqclq2cB08gxFVKVeQYOW4CIO+r2/o9cHqDuHBKZoz9vO+KKhhUcqK/tbahUuBvnWuIfjcySppXUsllOBrF6UQ4j4G4ds4bDOMnX52Kh/91ROCLluUYcKLfjVN2L1YvKoMvGCa+Q4YBGmrziZnhKxaUYFquKa2jPo4w1uTw9wH8EMCqoX+/B+C3Y3c5EchkFGgG+Pk/9hEjKa02Lx7f2YStK+bCGwzHddRI+rSPLK0T3ajxm8fxs5cr8kyYnCU8T7fThxcb22PkJB68ukYw0eI5l6QFwOb2I8ug5q4zz6yBQaPE5rePCrpJP7u7FTMKM1CcJdys+kK04B6/dUFhpLHPZdPw6FuH8bPFFbhzyJCxGc9yGTC/LAuLq3Kxr8MxIptZmmYQCjMxBqvIqsWgLxhzDjqOdEaOSYPX9nTEPPP147hJRCqbBI1STjTyGqX4RjRMAy980iZwUF/4pE2UvGTLSfhggxwzRM7R1k8mTEonGFCcNTKSD2wjKrEgCAk0zYBmaEF3VpqhJbuwij5jkWZ8PYPi9yFWOmVz+2P0pVYtLEO/239WOb1ppHEmIWYj2ge8xDX2gSursX1/B66YPgl//c4FyDFpYHcH4A6EsXlXC7d269QKbLiuDvvaB5Br1mCiabgqgm//2PJiigIGfSHQNINTDi8xGFRbYMbkobWIZD/Kso0x8/t0StNHAmdzyW702Mgza3B9fSGnfzhaWWZuP40uhy9m7Ztk0Uke1zNIDkL2DErLLqSaTZdpUBHHWqZeFfcedSoZ6oss6HcHkalXQiHNewOI+LcyShZTMn2m3kWqmbx9riBHbACRd3Dfawfw5E31cc+ZivzF2RwQGgl7Ee1f7u1wAh+14ulbZsPpDSLfokWbzQO7N4RfvH6Ie5d3XlKOfrefs5kWnUq0KbZRo0S/Jyiw0w21+cT3/OxtcyCjgEy9GoUWHd492kN8P+qhQOPP/i7saVKTnyEqEdjtFPp5RVYt7l5cgZN2Dz441jeiWaHnEkg2jq+ROl7nitj8EFvnswxq4ufaocxa1reommgCAyTdkyf6etpEJJAOdzm5IN6hTifa+t34akUu/nnHfHQ6PCi2ChPv2Hfxo0vKMOAJxcyrda8ewIoFJQKC+6ElNfjwuB0TDOoRbdI+nkAatw9eXQOLTsVlTgOsbYj8u9PhgzsQJnIepOptFpHxo4JFr8Smb86AL0QjQ6tEgSXiy9789MdYeXEZfvefFtx5SSl+dXUN/t8Qf8Z/h0tmFRDHxPSCDHxlSAotjfGBMSWHGYbxA9gw9L9xheiIMalU3hsMc80gaJoR1YAi6dPys32ByGbj2voCeAJh7OsY4IjheLIKOaaIJiJfTkJGATMLM0Q1qKIXOrENQL5Zg3a7h7vOa2YWoN3ugd0TEGjC8TeY0QsTXyKi0KrD9fWFaO4ZxLWzJuFQ17AmI5vxDAAXTbFCp1LgWK+Lc8zYZy+nEFNCH8+JPGFz455t+wSb+yKrFnddNhVBOpY0llMQfTctvS4UWnS4e3EFF6WXy4D6okxcVGIdt8YtlU2CRackEqQWnbjyS7/HjxvnFMU0pOv3+DEFseeZIFJmOcEgHu3tdvqJhMnMQosoOZwsMXJqwIdnd7fGBEGmT8oQPceBTgceeesIdy80Azzy1hEUZuqIzU4AwKRREJ+xUaRMWKyLrF6ETAYiOtCk7BQxHeg00jgfIWYjGAbENdbu9mOCSY9gmMa8skhTl/86evHYjki35h98ZQp6XX6csHlwst+DLIMaj751BEU8e8CWw0ev9U8NrcEKGUW0225fJNOw0KIjOuKPvHUYay6dipm8wFSqhNZIwOcLYcfRHhwhNMMZr2smH9Fjg6SrNxpZZr5gmBh8rcmXzpCdYCQTAxOM0llVqWaeqmRUTIbmusuroJJLv+v2ATf6BgNoZhvZ9QFTJujRPuBGYab4+Y73uYkl09Nyz0wzolQzeX3B2I25L0jDJyK7dboY64BQqiBVh5XnGKFUyGDVqVAz0QyVhM/DgiQ3crTHBZ1KjgunZKGl14XD3YMxlYJsnww2k72p24VH3jocEyBcvagMGqUMNldAcA6x7Lv3m/swLdeEmYWRyjhFlKQeEHk/R7sGYdIoBIkGKsXwnk8s8MJeW55Zg9vnleBw13DzvC6HD239blH/9XwFycax/QS2vN8yLucKTTPYcbgb+zqG50d1vhmLpuWIrvM5JjXRJtvdwwFCX5DGxyfsWPHcp9hw3XRU5hkTsv8kDuH3355F3quohfPW4Q3iaO8gqvMzMCXbgBN9Lm7cMww4yYG2fi86BsjZzzQz/N+P7WjCb2+ciS3vt+C52+acFf5FKiCN25//Yx9WLCjBxh3NXLKBXAYwAG7908e4vC4/ht8AInvutQ2VeOD1g4Lqbb5PuXbbftwwuxDZJjU27mjCxhtmoDjLgN3H+nDD7EJolXKsmD8ZWpUCnQNePLy0DgDQbvfg2d2tAqmP6DGhkMq6SmNMMKbkMEVRXwLwCwBF/GthGKZkrK6JBX8BNqjloqXyLb0u2Nx+nBrwCTKD+ZpVJH3aFxvb8eDVNUTZih9fVs6RsaQNSOXq+aCZCOGXZ9ZwCwErJ7HhuukoyNDhRJ+Lk8aQivqJbQB+962ZgowpigIxg+rRa+vAMJFGffzr2XWkhzM418wsgAwUNu5swu3zSzDBqMZJu1fUcWUzov9n8TR4hjZEDbX50Kvl6HX50eX0wxMIYbJVj0Ndsfpb/Htkm5zwN/flOUY09wxi2xexGcAVeSaB7nSsPs8MVOQa8dCSiJh7YaY+JqN7vCGVTcK0HBOO97kFDmqBRYtpOSbRY2QURWxI95fbyVqDchmF7y0oxX2v8xyWhiooJDaRTkK2ty8YKY8SQ7LEiFohIwZBlBKLmM3tx20XTYbNE+Acttsumox+t3h2VpCmoVfJBc9Yr5IjRNPE74fCNH7+tWnocw+fw6pXIcR6RwS4/eQNqZgOdBppnI8g2YhVC8vQ1DWA3317Fj5vs3Odm6+vL8TTH7Ti2voCZOqGsyH9wUi1zIr5k+Hyh2IyPG+5sBhdDh/qJkW+X5Vnwi+vqkZbv0ew1lt0KhzucqIyz0TU0TNqI+5Sm92Dv350gmt8FKbBZTzd/fJeVE80c+TYaDUxjQ7UhkI0PjnZj44Br+B5rLm0HKUTzg6yInpsyGXS1UVnCoFwmFgFEghL23JvIBTj56xaWCZopkhCqg1QFXIZ9CoKm5fNgt0ThEWnxIDHH3cT2DcYQMdAbGZ0gSWAQnGlKbT2u1GebcDtC6bA6w9Bp1bgyV3HEmpGFAiEsfeUA11OH/JMmoSJx1QyecX8sDNV+jyWASEWqWQAt/W70dLrjrEXYZrBqh1NuP/KalxVOzHue2LtK5uJWGTV4heXV8HtD3N7N7FKwUiTOjeKM/VY+fzn8AWFFY7l2UbYXH64fEHkZ5A1r6P/HabBkWsAsO7V/THzcm1DJcJhmvPxAOClxnZs3tWC7avmod8dxPoltWjpdeHFxnbYPQFsuG46GAzrFIutP3Z3AMVZCb+68wJiiTNyGUZ9riSK430uHO+LnR/H+1yYkm0krvP7Owbw+/80CxJefv+fZty9eBryzBp0OnxcMJzlAJ65dU5C6xyJQ1j36n5u/89e4yNL69Dc444Zl27eOlSYqce0XJPAZt15STksOgXyLTo8dv10qBQUfvfuMeztcHLXzL++fk8A/7N4GoJhGruP9Z11lUqJQGzclmUbUGTVCvyEzbtasGphGbbv78SSmQXce2Gr20qzDdCp5Hj02jq4/CFkGVTYcG0dDncPCnzKx3ZEJCAaavO5/WOeWYOWPiV+/Lc9WL2oDO12L8fXyGVAXUEG8jPU6HT48NqeDqxrqBLs9yPEc0TTmGYApy8Ak0aFQCiiNU16b2dzFdrZgrGWldgC4E4AnwIYV0wF36mK1s71BWm88EkbJmZocffLe7Hy4tKYv7Mk7gmbm6hPa/cEMLMwA2+smo/eQT9ufvpjLuI7ZYIBGqWMGH226FQxhO+mG2dwXUZzh/SMX917Cidsbq68lXXuj3Q5UZlnFGzI+EaGX9qqVysEGVNTc4wxGVQmtRxhmsFtz3zMGYOLSqx44455+KLdgcd2RCQoCjO1aOmLlJnsOtKDNZdNxW/fbSbKYRRadOiwe2H3BDDoD+GlT09yGsXfvKAIjSfsHFm7alGppD4wMOyQ87OTVy0qBc0ghjRmGCDXpIZFr8Lzyy+AP0zj1j99Iti0N3W7OGeRdbYnZ40/B4KPVLT8FAoZvlqRizxzZOOUa9KgdqIZCoX4Bk+sa7jNFSB+X05R3ELBfve+1w9g63fEs1rNWiUx2zhDK57RLJNRuGRqNv68/ALBvYgtKA5fxLngE72ZOhWcPvJ9AECmTo0jXbFyFxad+MavZ9CP3/2nhZtzYRr43X9acG9DBfH7Tl8Q3qCwC/ydl5RjUIIYN2pEso3VCdTrppHGeQI+eXq0exD7OpzodXpQMdGC7//5U26+/fKqavxzzynYPQHUFmQgyAvkFGXqoFHKUGTV4wdDDT4AYUaL1TBMJisUMlxVl493eOXFpEasqxeV4dndrZxuMVs9Y3P7cUHJBHQN6eD//bNhEtkXpHGoyykIXKZCaIkh2kEvtOiIDZFyTGpQAFz+kKBD9Ya3j2KGRCXGeEI0sa5VKgR+BzA6GZkGtRI7D3fhoaV1HAn6zActqC8mrxfD16bA1sY2gZ+ztbENDy2pkzwulQaoAEAzDBhQaGy1c+tnyQQ9aEY8iAlExgipKmjzslmSx2XqVPjmBUX46d/2CLLi+IEbEgKBMF7Zewr38hrkJEo8pgKHN4AfXzYVj7w1rNv448umSga2TwejERASA00zON7nxqFOJ5p6BgVEZjxZkp5Bv6D5m0WngssfQmWeCf93/XQ89d4xlGTpUV8sETHAsH0tyzag3+3HgCeE7//lM+7Zr19SC4OKLO11vM+Ng51OlGUbBTq07B5i/TU1+OMHx3HD7EJMzmIEepyv7enALy6vwi9eE5Igz33YypFrjMj+I0zTkMuFEimrFpbhk+M2fNw6IBirD1xZjZmFGZicZcAJm5u7D7H1pyYB+ZLzDWIBm0XTslGTnzEuSadupw9/+ahVUEHyl49aUT3RhCnZRuI63zWUJMWOX3av7wmE8dCSWjT3DCLXrMXv3o38PZJAEkooqYhEVLbavJhgVAsSXyz6CIkYPS6f4o1L1mZNvWM+jnQ70dLrRp5JBXeQwfJnGrmx/4vLq6D6tA2LKnLx7O5WwfVZdEr0uwO4jff9s7G5oBSixy1b4RwIM3h4aR1+EvWcN+5swsqLS+EJhjE914A1l5QhQ6fCE+824/r6QmxtHCZ0swxqDHoDCNORKoglswo4+0czEdnFbGMkObJ30M8FAAosOjzy1uGYAPavrq7BJZU+DPrC+OvHkXFbnmPAyX4Pnvsw8u6O9bqx6Z2mmGPXL6nFxAwNrHp10lInaaSOsSaHHQzDvDnG10BE9EYx2vA11Obj7pf3wqJTIcekESVxW21uUX3awsyIk8Y3rNfMLMCvtx/CqoVl8Idihb2vrS/giGEgMulXPv853lg1H3OKrdh+oAuHu5zYvKsFt88vEZSrslGive0OhGlwm0a+rhZ/U/rang4u6v7EO82CRnxslvLmZfVYu21fTJTq99+exV3nE+80Y+XCUsipiM7vkpkFoMDghtmFXImkXAZU5JpQOdGINruHk4HwhcJoqM3H1sY23L24grs39v75UX8+sd3r8nNOMCl7YnZRJhpb+6FRColOs0aObqcfe9sdcAfC8EaVAZI6eZ4tTQv8QSZGk08KNM1g94k+DHrDcPtD6IIP7kAQ80vFtYGSJSL7PYGYueML0rB7xEnYbKOa2NRFqkQ2FKLx6r5TAi2rX15Vjavq8olkt1Wvjolwr7m0HFYJotcXokXlLsSQZVATM5StIrIaaoWcmJn99C2zRc8RDNFE6YpQSHqjnkYa5xvYTRUA/GjrF/jTrbNxy9OfCObbPa/sx2+um45LqnLRNeBBSdYEABF72e7wYN3lVURdN1+Qhi9ExzTJUihkmDLBwAW8Ci1anHJ4Oe041o48vLQOTT2DKJmgR5FVH9EkHvBhy/tCEoHN8tAoZTjaPYiKXNOIl9aTykjXL6nFhrePxKyNT98yC50OfwzZ8dyHrRjwnhlS7EyAv+GmaWZMMjJD4TCWzCwUkqANVQjFyRzOMalxw+zCmDUgXsZqKg1QgYiUUbfTT8gUlx6HHpF5441T5RIM00SN1+dumyN53N5TDo5sY4+7d9v+hIjHVKCSy/HchycEZOBzH56IS9KfDkYyIJQopHRcE/GXHd7h6jBSsOy+K6rg9idmOxQKGeomWdDS68L3/yJs5Hb3y3vx9C2zY/yj/1k8Db4QTbRZrG3tcHhx45wi/OmDE7B7Ali9qEzwXp//qBXP334BTg344B5qdAcIybXopBWNUoaHltZx85u9zo07m/Dksnp857lGwedrt+3Hc7fNwZRs4T5HbP1x+8dVDta4gFh2/XglhgGpChJyxSEQ2dOwezPSnFq1sAy/3n4IKxZMwdd9Qfz14zYUZiZWeSBGsE/JMqB0goELTJG4FF+Q5nos8IPYU7INoCjgcNcglAoF7vu7MDP5F0Ma3r2Dfm6/yCbLkJqunS379ETBH7ekCme+vQIizyDXpME92/bDolPh3oZK/Hr7Idx12TR0DXiwYsEUQZb3/VdW4/W9HVwDzVULy7C1sQ0yKiKjedwWSZK7fX4J95w9/hAaavNjKt7/3z/24eGldXjwjUPodPhwtCciHRKmI5Kidy+eirXb9mP5vJKYY+9+eS8n8ZKM1Ekap4cxIYcpipo59J/vUBT1MIC/A+BqrxmG+Wwsrisa/I1itOFjywq/dUGhQJeXBUvisoQrm7VB0qflG1aKGo4m33RhUUxZRnm2kWhcewYjBmDNi18IJuu19RFpivJsA66fUyj4LTbawhqZw11OwcRkG+/97XsXwu0Pwz0k48BmKbPyDyRj8FmbXXCdL3/aju8tKMG9DZXosHvRavNAr5Ljyun5XOmUUkFhkkWPj47buGfw869XoKlnEA21+Zx+Fvu7tfkmzC62EIntp95rEUSTorMnCi06+MNh/Pxr0+AOhAWZyAc6nQDAEez8dyumJTYWTQtCIRoHOh1c19eqPJNoVm9Lr4uoyTc1Zx5Kc4zEY07a3Tg14I8hYU/a3Siyku/VrCHrFJtFsnrFNHR1KnHT5PQGBeVRQKQ8qipPrIVdbNdqluQpyzYQ9YCDYUaQueIL0tjw9lH8eTlZHgMAPIEQcWx4JEp3Hd4gsdzXIZJJxN808c/hkCBZugbJ+slFVukmRmmkcb6CXROjtSSByHxjwCAcpmE1DGcznLS74Q3QsLn8KMnSEe1avllDtNGFFh3uWFgW04hl+/5OzC/PHup7oMQ1M/K5oHJLryumlwFfK5HdHMyYlDHi5DCpjJR14vmBLl+QhpySi3aoNmnEqz3GM8YqI1MhkxMrbZ69VZoELczUoyzHIMjiKssxxG3W0zPoI8o19LrEG6ACgNMXIq6fNfniQUwgUrVFzFSLQ2L3ilQs9bqkG+51iZTmsg18pJBKaWuqJP3ZBikd1yfeaY7rL5s0Sm4ckOT11r0an/iPhlgZNgB8rToXMwst6HP5cbBzEIP+UEw1KN+2rm2ohNMbxJ8+OMGRL95gWGD7iqxatNu9+ClPbnD1ojKU5Ri4NSOaePvlVdWwDfoEvi2bsScmp9bvDuCTEzZY9WpcVpGDN1bNh83tJ86jPPO5Nc5GAmOZXZ8qtEolsY/IMxLrAA2G22uQ5hQ7vh94/SBWLCjByovLIKPAjSmpZyNGsLMJaOxcd/nJmcgmrYKoh11s1WPKBAOCYZo49vtcflRNNOGNVfPR7fRBKZdh0BdAiB4/+/QzBZmMwmUVOdi8bBYc3hAxU5jvj2mUMrTZPfAFI5I5pwa8uL4+EmhePq8EG/4tHA/3DpG1TwzZwY07m/Cb66aDGkry++r/DQfa2Hfa5/aLSm419QxyXNiKBVMw6AsiP0OHIqsWRZk6jv8iHct+nozUSRqnh7HKHH406t/8WhcGwMJRvJa4EMs8LbJqkWPSYMPbR2MIntIJBm4SPvdhK5fR+qUpWZhdnCkwroUWHdYvqcXdL+8FMBxNXr/9CPLMGqxYUIIZkzJQZNWDIUhUsJFovvOjUcrw8qftWHNpOSw6Fb73lVLJaMviqlzB79bmm3D7gilgaBpHu12SusUkYxAtpdHp8OGPHxzHr66qQZ87ECN3AQClEwyCTOZOhw8PvnEI9zZU4hCvsUKEJDfgm3OKcO+2/VyGsVSDGFL2xMKpOdjfMYDrhjqOs9fNwhek8fKnQo1lkpj7aJSTRiMUovHKno6EM2GP28idY4/b3KLkcLfDT+64fOscUXLYFyRr6Pqjzs3CHwoTyVEpDcU+t58YNbdJaPtGd61mr5Wv/8lHl9j3JTaNRZl64tiQ2oBn6lTEcl+xrO5sscZCEg388jN0xOzkfLNW9Jg0zk3kTyrEqfaTSR83sWASOk62nYErGr9QKSgY1SrifLPq1Wjv96Ayz8Q1fv20dVjuqb7IjAeurOZIUdY+V00kNw5rs3tiglcbdzYJ/A62SR1rT8TIjsJMLZbPK+EauUgF2lKF2Lm1Shl+eHGpQO6ne5BM3E3O0p/VpNhYZGSKPcueOCSoTEZh4dQclGQZkiJAJmZoiHINeWZpf8cpEsQc9EprHFMUhfuvqMK9rw4HpO+/ogpySvo6+VlxLNh5KoU8UQ3gOLIZhIZpiTRYTJWkP9sgZZtWLyqNK0uSY1JzSQZihEE84j/2N8X7bhRnGVCcZcBHLTZseX+PIMGGf86afBP+vPwC3PXSF2i1eQW/M2dyJidXJ6eA2ZMzcfszwkzfx3Y04Z93zOfGSDQpWWDW4p/7O7H+X8OyI2zGntVAXouCYQafHLdz1ZWLq3JRaNEJtJbZ9acyj7z+nO8YC1t+OrC5ReT7JPZAEwxqKGTAlpvr0W4nN3Zj5xrNAGu37ceKBSWYlmvC4qpcyWeTKME+LdsY4xc9cGU1nvmgBd+ZX8qRw/zAW55ZgzChcTxr3wsydFAoZILraxlqZj/W+/QzjTa7B5+22sGAbCNZif/IOlqN3/z7KPf3bJOGI5SlSFn+vzVKGb5cno1P2/q5PeukDDXuv7Ia927bjz9/2IZ1l1cSn32YBjbubOKqzdmM5LUNlTBplVwVN+lYVo3KF0xc6iSN08OYkMMMw1w8FudNFXzD1+/2QymXIRCmcd8V1Tjc6SR2Mi/OGiaK2LIhjVKGa2bkCwwmTTN461A3Nrx9BMvnlcCklgu6j9s9AUzLNeHL5dkAIo0a2EZ2fLKWjUSzpDBLuPUM+nBtfQEOdzkloy2s/AKfeGUjSmzZKnsMn3QttuoxuygzZrK+tqeDI7zZ67x7cQUCIZrL/uWXUwHARVOskawoCtw9djp82PL+MaxcWI51r+7HbRdNxupFZZhk0XHaRc992IofLSpLOpokk1GC8qs8swZThxrVsc+SJfeXzyuBWSPHnMlWFFn1os9/tJBsJqxGSdZV0yjFdfX63H5iM5o+CQfE4Qvib5+2RzKNAiHoVJFMo0mZ5CzViWYd7nllfww5+tUq8Qi4WaMiRr3/IpHVS+parVHKkCuyyc0zkzcSUpuaokyyQ14kcu8AUDPRjJ9/vQLBEAO3PwS9RoHaggrUipBIlTkm3H9FNe59laeReEU1qnJNoueIbsoSj6hK49zFqfaTuP4PHyR93NbvXnQGrmb84oTNjZXPf47ffXsGMXjlCQShUcpxrM+FIqseJ2xugdxTY6sDQCv+sGwWBr0hTMrUoiovVq+d3QSJlVv2u3x4aGkdfMEwck1qtNnckcZ4YKBTkasuOga8nL9xprISxYiWqokmgabnL6+qRo5INmiuWXPOkWJnGmLPMltCUikacWR/BRhwB/HO4U78Ydks2N1BZOqV+POHx1GZa0SRVfw4o1ZEXkojrePbM+jHnz9sjWgqB0LQqhR4atcx3LGoTPI4d4BcgeMJSEsP1Ew0cxtbbj29slp0/WXR1u/GKbtX8Nkpu5eY/cZHqiT92QYx+9DW78WW91swNdfEVUCQwJLojyytA0QSMrLiEP8sWBtrc/vx0JLamEze4zYXT2IvQkr7grGSfmyFolWvwq+uqgLNUOgfmhMKeUTahA+Hhxwg4WfdR5OSLb0u/E+UbCAbJLS5AsQx3j7g4bIE+XszVmu5y+FDrllDXH/SODuRZSCvA1kiSSI0zeBg5yA2/LsJP7qkDEVWYSILq1ebb44EbzK0So4kTrRkPxGCvd3hxdZPhPb92Q9acEHJBAx4glyTyFMDPo47qC8y4/tfKSU3VA2G8G5TD75Slo02u0fQ/2CsG3GeCURXq3Q7fXixsR33NpAJ2dJsI1YtKsX80izQDAO7J8DJbzKIaBMf73NjcpYeRVZtTMCL7ytolDJk6lSgaQY2VwByWSSZTq9W4eG3DnN7+B6nD+surxJUHPP11htb+7nz+II0Hnj9IP50a0Ta54VP2ojvmdUljgQEVOfkux1vGGvN4bMGLHl6uGuQG5TrGiqgVcq5CDe7IXvw6hpU5poSGsD88iuWKC2yarF1xVx4g2HOeQSGRbgtOhVWLChBeY4RFbkmzrHhZzg/92ErViwoQVmOEb5gGEe740fS2ONpmuGI13gyCjIZhQtLrEQi+LKKHNTkmwVSDge7nKLZt7kmjeg9TsrQYs2lU/Hc7uP4zoJSBEPDZSadDh9ODniTjibRNINQmOGcvmVzi/DIW4dx20WTQVHg3munw4fX93bgjoVluOHJD0Wf/2ii00HuIi6WCauUU0S5B6VcKstFR2xGU2gRJzuLMnX4Wk2eINNo9aIyFIoQpJOz9Lh7cQWxHEkMYuV1Uk1dRAlSkUyKVDaNrf0ePD7kpLNE9+M7mzBjkkW0BFcmo+D0hmIi6WLj6dSgDy82thIaEllQoiGfg9+U5XzaKKSaJZtGGja3H8vnlUBByYiZ/TfMLoSMovDA6wdRkmUgZso1tjrwaasdX5qSRQzY8XU5o+WLAKC+yAylQh6jL/u/bx7Ewmm52Hm4i2jT+l1+rFxYekazEknVVOuX1HINmIDhgOUrP7gQ911RhXX8bNArq1Fg0ZxzpNiZRoZWHvMs77uiChlaadKVphm819zD9Q+wuQM4aXdL9g8AAG8oiEUVefjuc58KzucNSZOueSYt0d+YGKdaxaRR4miPC6v++jn3mUYpiys/YlArifP04aXSWr4KhQw5JhUeWVoHdyAEvUoBo1Yed220uQJwB8IxzWdtrgCKsyQPPeuyFFMByT7wCYJ4hBNLorf1u7Gvwxkzlu67ogo5CUgkRGsf//xrU7msbVZey+4J4I2ha2FJ6ZYeV4yk3+pFZfjR1i9Qk2/AJRV5Udnt1dAoIRgPv7l+uuiehE/y6FQKBMJhWPVq0Yzr5h4XVHKKOMYbavMFezV2b8ZqLZP2A2mc3cg1q4kVFrkic4LPMzzzQSvuXFTKEXgkvdpfXF6F+iIzGCa1kn3++M42aiCXRfas3mAYja0ONLZ+Lvj+RaUToFbK8PWN78UkpDW2OqBTy0X9MADQqxRc43h2D5mIHMbZBJKO+5PL6mH3BPC7d5tj7NWqhWV49K3DuHtxBWYVRfTzN904A03dLrzwSRv0KmH17bqGKvx+VzOX0cv+GwD3e6u2fo67Lp2KAU+As3WrFpUKGh0CkWDD5mWz0NhqR5iGQKs9WhbbF6QRDtOommjCjy+bBrVSht9cNx2t/R4UZuqwfvsh7lhWV/tsk4E5G5Emh5NAtI5WljGSlm/RqQRZw+U5kYU5kQEs1uXTGwxjbsmwl9nS6+LO3enwYeOOCBH9xqrhEiWx0o7jfW48+tYRYlO8aLK6Ms+I/aecMQ6NFOmqUMhwee1EARHM3iu/gcv2A11Yv/0Qbp9XEuPsbbhuOsI0RO9RpZLjG9V5AIDVL3yOh5fWCa7r5U/bib8pFU06YXMLGt+xz+blz9rxw4Vl0ClleOqmegRCNKx6Fa5/8kPJ5z+aKLBoicRtvoW8+TJqFDBqFIJyRqNGAaNa3ARoFHJiM5pLK3JEjxnwBonHzJlMbu6Sit6XWMacVPl0sgSpSiXHVbUTUZKl56K0tRPNkh3MW/vdCPCavFEUEAgxaOt3i5LDBzodMXqca7ftR3kOOQPc5vZj4bRcAWG0amEZ+t1+SeftfNwopLNk00gF/EZvf/9Mhe9/uQR97gBoBlDIgNvnleC37x6D3RPA8nkl6Bn0iWbKVeSaRDN3+f5EtHyRRinDmkun4bZnhM3w7nv9ANewaPm8Ejy+s0kQSC606NBm9xBtaSoaqWIg2W2b2y/IPGGv2e4JYVJmZLNg9wRh0UUy7fLN6UyPZGFzh7B9XySTd8ATRIZOiT+9f1w0+MripN2NfncQx/vcXNl7cZZesn8AAMgoOUdEA8N6r8/G0XstspLlE4riZPfw5QT4fk287He1PNLw7livm5unay4th1ouTfKesLnx3ec+i5m3b8TJlPOFwkQ/Z8vN9aLHnE+Ibui9r8MZ0xwpHuEkk1EozjKgIEOHT0/247c3zoQ7EIZSRkGrlmGSJb79aOt343CXE7fPLwEA0AA27miO+V63czjZhc3s7nf7sXXFXPS7A/j85ACe3R25/l8vqeGCJey93PvqfmxeNkvw2a/fPESs8iy06IjN+rY2tuGXV9YQ15EQTWNSph53XVqOZt4Yv+2iyfj9rhYuyy9dXn1+oCBDj4JMT8yaWpBBnhN8nqHT4cNvdjTjF1dUcZKVbLUPMNzsbfOyetz98t6kxxSJxFy9qAzP7m7FdfUFon7S4U6naEJaU7crxr7z/bBHltYJrn/Ni19wNrx4qLLro+O2hP2ekfSVRgokHfd7tu3jEvM27WzGigUlmJprRIFZiyBNY3F1ruDaJ1sNWPn858TGb/e9fgB/vHk2Tjm86HL48NePW3HXZdPQ3DMoIHh/+vJerFgwLLsTLSEKAHZPAHIZhWm5JsE4WNtQic27jgnuq8iqRZ87KEgu/PnXpiEUptHS68Ivr6zB0e5B9HuC2NrYhsXVuedFgHWskSaHk0A0kXu8z82RhfyoyYUlkXo7sQEcHTVOJONVLKIc7WCRzlmUqcOaS6dy0hX8pngAcKLPBZsrgOM2D+55ZZ+AeCVtWkmka7zJyjdsv333GG66sAiPLK2DWilDSZYBk7MijejYe2RLHygq0myk2KpHm93DGZAndx3DuoYqrjmL3RNAgUWL11fOQ5/bnxDJ2O30cY3vWFmKPLMGi6vzsPqFzwX36wmSu/+OlQh6ssTtlEwDjvW40TM4LAlh0igxRWJjKNbkpc/tRynIOsVS2r5iSNbQ55jUWHNpOdfwJkKklCdcPh2hb+Mv9CqVPKmO5WaNErd+qTjmuqSynpLVQlbJZURJja0r5iZ8nWmkkYY4TtjcgkZv3qCwa/2PL5sKYFjTjV1rojPl1jZUQqcW1xyP3rCx8kW1+SaU5RhFpSa8Q40v2ea10YFkMZ8jesMW3TsgWZDsNsmXYTdXx3pd3N/0SiVCIZoYbBuPG7PxgmyjBruP9+Odo33cZxqlDPc0VEkeZxsMoMvhi810HQxIykN0O0U0jp1nRuM4VU3eDL0SgR5GcH8PXFmNDL10xnGifnU0/EFyg6RAiNxb4XwEvxHVj7Z+EWMX4hFO/IbLBRYtrDq1pG8fbTcKLTp81jYgGBNrGyqJ5dPBMAOaZiCTUTF2bfexPgGhbHeTK9fsHmE2favNi2yjKiZ7UapZH5/s4V+z2xdEjkmFLkdAcD93XlIOlYLiyOWzubz6fLb7yd67TEahfpIVe0854PRF5PtqJ5pFj4kOXnc6fDhwyoGNO5qx/poa4njudvpg9wQSHlPsPfQO+mPG92M7IuP7xcbYJK61DZVQyCk8/UEr91vRfsSrX3TghjlFon6Y2y/UsmdteLFVn7TfcyZ8pZGAWCJhfoYmxsYA4MYTAO6z1qHeQ2IV4R+02PDUey1YvagMva4AmnsGY4JpviAt6M1E4oh+dXUNZhdGemv9efkFaOl1wahRwu7xY+XFZWi3e/BiYzvsngAeuLIGK54b1ma36FRwB8JcQ1A2ePb63g7cvbjirLVvZxvGjBymKMoEYALDMMeiPq9lGGbvGF2WJKINrFw2bMRYMlMui2Q2so5GNKINT5FVG1MaSjLG7LnZEpACi47TdGXPxdfWUsll8ATCyDNrIlpDbx9BQ20+zBo5agoywDBA+4AHzb0uNHW7AIAz2HzitdPhw9bGNvzuWzOhUcq5hQuIZDOLLWYkbRz+wrR++xEAwAsrLuCyKvn3uGxuEWdsnnqvBRuumw6LTsn9xt4OJ/BxKx67YQa0Shn8IRolVj2Khq6DbxTFDDpLzPNlKUhdXNe8+AW2rrgwZsEqsmqhVcqx+1jfqDszyRK3R3oHOa01FhqlDEUr5hIzVIHIRpS02Z9gEHfqU2nw4vOFsK/TgS6nH7kmNWryzNBoxE1TQYaOa9TIbiDzzBoUZIhnTyXbwC8VKBUUsUP7i98VJ26T1UJ2+8lBCk9AvIFfGmmkkTj4a9U1Mwvwm38L5/Qjbx3ByotLsemdZlwwORN5BjWXKTf1jvlo63dDp1Igx6Qm6mqya6M3GMbqRaV4sTHSjT6ir9/CZbwM+siNN7RD6xabKZZr0kiuxQA56yRRLcFEIdaxvNiqRyhE41CXE809LuiUClRONOKdph5k6dWo4VVkjNeN2bgBw+ChJdXI0Kk5vdMBjz+ukLArECIGkzcvmyV5XK6IxnEyOtbJaBynSioHQwyxAuf1lfMkj8sxaVBk1aKhNl/QRDEecRmt2QnEbz57vkLKLvARCISx95QDXU4f8kwaOP0BfN4Wafh3qNOJ0mwDvlaVR/TXSHZj87J6gQ68LxjRt9x040ysfH5YF33VwjKs3bYPT98yh2gL+fu+PLNGVPfbohMGIjRKGfLMupgAmlhAgg32mbUKbF0xF55AGDqVHMEwjUy9GjTN4LY/CTOWf/Pvo/jL8gvAgInJEjybcD7b/VTuPRSi8d/jvZBTMoTCDDyBEP57vBfzp2QT5wdpDtYVZEQqLtUiCWomNVYsKIFKEf/5R0tkiY3vTocPz+5uxTO3zoFniL/IMakhlwPrl9Sg3x1ElkGFiWY17n/90HAQ5NKpWB7V3JHvh/V7AoLzscEnMb8nf8Vc1ORnEJ/vaPhKqUCsOi1TrxZkSH/a1g+bK4CDnU6uSuiCEgsoyKCQU9AopRu/sb4BK8lE+h7/sbEc0V+WX4A+lx+5Jg0y9Eoc6HLA4Q3hszY7MnVKhBkI3ukvr6rBpEwNHJ6Q4PevmVkQ46uwCVBi7yyNkceYkMMURV0H4P8A9FAUpQRwC8Mwnwz9+U8AZo7FdbHgR6zzzFpU5BjR7vDC5vYLorpKGcWJaF9fP6zfsnlXCzbdOAOTrQb0e4aJ2hyTBgwDgeEJhBj0u/zYcnNEvqAwU0/UsC226rHpxhk4ZffCF6K5LpMapQyPXjsdX63MwVuHurF++yHBtaxaVMpF2/7+WTuWzS3itHlWLSqFVinHC5+0YeXFww3del0BBMNh/GHZLARCNCw6FQIhWkAMSy1mYto48fS32Od7rNeVMEHb5/JzOjtFVi3uWFgWQ7RfVpGDNrtHQJrnmDQIhMNcxIuVpfCKZAgHw2HB4sqe6/rNH46JMyPVeZkEMYe0WyIDSC4DscRTqlKzKpfcMK1apGGazxfCa/s7YzR3L6/OEyWI2+we/ORvsUR31USz6OJ9oNMh0AMGInrAYg38gOSj+X2DAeIztrkCIkcAFTnk7r0VOeTnZRJp9GOI0+jnfM7KSCONZMC3rWqFjDini6x6/O81NdjX7kC/O4Aiqw7lWUZQVKT55wRjLDFM0wxO9LlwcsCLbocPvS4/XvmiAzddWMRpX/JJk4ocY4zu+bqGKjz7QQtXnrfpxhk42DkYd2OZaoZkMpCSCDrU5USH3SvI/Fm1sAwPNh7CDy8uw1W1E6FSycftxmy8oM/jhTfI4KdRGsB9Hh+miFTzAJHnSHr/0Z9FoybPTFzPa0S0+lmcDtkTCtHodwfQ5wpAKZOhwKyVlHMCgLZ+D/H+2vo9KM0Rfy6FFl2Mz/jLq6ol+yoAkWq8h5bWornHxW3Ap2QbJJvPnq9IRDosEAjjlb2nOFtXZNXiB18pjcl0P9zlRHVBRsw5SHajsbWfOCb8wbBAu5Qtl2YTSqJ9JJZYY/dWT//3WKyG+hXVkMkYLthn9wTw6LXk3hlivjsb7HP6wvjenz/Ehuum44LJVu457TzcTbwfpy+Ii6cNVwxGk+z84JvU38YS57PdT+Xej/U50eMMxGjPH+tzYmpuRsz3+cHrQ11OHO0exGP/PorVi8rwzActgipc9rf+9P5xvHO0LyGZneh7EBvfAKBSUKAowOUPw6BWYIJeiR1H+tDcG7Glx/sitvTZ5bMRDgM5RjWOdLuIYz/bqMaj106HWklxiWXX1hegPNsIhgF6Bsl+z47DPegY8BHXo9HwlVKBVJCNv96uHmreyred+ZZq+AIhbPnvca7KQKrxmy9I43ifGxoFxSUvss92ygQDsvQqrgJDo5ThrksjWdxKuQxOfwgP/PMAvnlBEWyDfpRlR9bfDrsHFp2Kq5a955V9WHlxKYJhWjBexLKa+93i++g0Rh5jlTn8cwCzGIbppChqDoDnKIr6H4Zh/oFE6r3PIKIzDOuLzLhhTjHueWUf57RsXlYPpZyCNxjG//vHfvzP1ys4DVAgkhbf1O3CA68fFBC1GqVMoI2TZ9Zg2dwibPi3ULKB5FDIZBQmWw1o6nbFRFXueukLFHxnLtZvP4S7LpsmuBaaGZ5o0VmxOpUcVr0aDbX5aLd7BFm7D755WCBUzze6kyxa0cWs0KLDno4BSW0c/r0WmLV4be8p7vMiqxY/W1wRl6C16FT4/ldKcefQf18zswDTco0cac4e88f3j8EfDOP/dhyNeRdPLqsXiNwDQEWeibiwZRnUGPAGuWzVaTlGrmlf9DMYjQUk0WwMFlY9OdshU68SPQcb5eU70s/ubsWMwgzRjtynBn144l1hU7Yn3m0SbZi2v8tJzPiZnKUXlXToGvChPNuA2xdM4ZqyPbnrGLoc4ou33ePHbRdNhs0T4DZzt100GXYPecFJZXOrF4nAS2khdw56oVbKBFnQaqUMnYNeohZkIEQTCftgSDw963zOyhhVyBSgqOSf58SCSeg42XYGLiiNVFBg1uKhpbXosHsxLddInNNNQ+V2GmVEOsYfDMEbDMPtj/zvcJcTLZk6LJyawwVMdx7pFqzfbFnw8x+3YtM3Z0Ahp+AJhHHC5kahRYd/H+lBIBjCI0vrIprCJjVabW5cVDoB03KMePqWOWAY4BuPvxd3HUo2mJgqxCSCHL5YLXq2lPrebftRMmTvx+vGbLyAYkQ0gG+V1gC26JQJZTtGQ6GQYYJJKdC2DDN03GqbEzY31m8/JPCt1m8/hGm5Rsn3GE0SapSR5oVs8EAMGpWMeH9slpQY2uweztcHhnzVV/ZjZqFF8jpP2j0xMh1rLi3HSbsHk9PjNAbxpMP2nnJw7xwAGmrzY8b5YzuaUDWRHDQn2Q2SFqZGKUNBhhZ3vbQn5vNgmMHXN75H9JEWV+UiP0OD6zdHGlLfeIEKT98yGz2DfmTolPjLh8cxqygLr3zRgZULSzHBoIaMMPRomoGMAh67fjqCYQZufwh6jQIyAH/8bwseuLIaShmFh5fW4Y/vHxPMF30CvTak5g+AlObWaOB8tvup3PuAJ0xcB56RWAdksggp+2Pe2O91BXBtfQGKrBo8c+sctPV7oFbK8ewHLbi0Mg+Hu13odPiI18JPosvUq1CebcDeDid2HenB/15dg+M2ob790+8fR5FVix9+pQw3/fFjbgz+6uoaeAOhGFtaaNGhtjADn7b1Q6Ug2/dcswZzCjOhUsmxffV8HDjlxJHuQRzuHkRTzyDmTM4kHsf2NyLt10fLV0oWUkE2fk+qAosuhge5d9t+rFhQwsloXjOzAAoZ8MdbZqPL4cMJm1ugCa9RylCWbcCvtx/CbRdNxppLyqDXKAUN7355VTWCoTAmZmgRCDH4T1MvzBolJmXq8LOvVaC134MwA0Ei452XlONPH5zgCOJckwbP7j4h2NPKKbLd/vzkALxBOr1vHSWMFTksZximEwAYhvmYoqiLAbxOUdQksJKgY4QDnQ7OWcwza3DbvCkCorPV5sWK5xrxxqr5ACLC29HagGxaPEn0myVhfUFaVMJg2qr5XIkAP4rdM+hDpk5FXEh63X5cX1+I5p5YnUL2fNERmfwMHZp7BiGXAS82tsc0ZmPvI1rmYdWiUnIE2xvAm6cc8IdiM1JI2jiFFh0+aLEJ9B1bbV4c7nJyRDVfQkOlkHMdSHsH/fjvsT7u2rY2tqHQIrwu/vsjvYt7tu3DmkunCgjrTTfOIJKuYRp44PWDuGF2IQosOoRoZsydmQydHJuXzeLKSxUS/l2YZoiRQlqi5jPHpBGUFFFUJOortUh2O33Epmxsw49oiMpjuMQzmg0aOb55QZGgKdu6y6tgUIs/ALNGBU/QFZOJYhbRA04lmp9KM50uhx8/JWRBP3PrHCI5fGqATNhPytSJlluc9VkZKZKuow46lG6Adw7gaO8gAqEwJll06HUF8ORN9Xjs30fQ2Org5vSzu4czLDa8fRRP3jQLn7UOCOb+T746FW39bhRnGXDC5iYGdn/z76NYeXEpWvs9gsZFm5fVc0FQ/trLrkczCi2QySjsPtaX0DqUbDBxpOEJkCtyWJ+Ezdobrxuz8YLuQREN4EFpDWCVXIYN19WBpjFMSFGRz6VwsNOB7//585j38eKKuagVqbgBIo1To4PxiTROjSYJ2Y1tiUSwmL0/0tqrikNip0pKnXJ4iRJSVRNNaXI4BXRFvQex7DFfgJzpTrIbr+3pICakVE00x9jC9UtqsXbbPlEfSSajOBt2zcwCfNbm4HxJFrua+rF8XgkeeP0gNi+bhbXb9qMka5gQZ4P0/S4fMg1RPiEF/M/XK7DmxT1cNt66hio4vcPJC4n4l1LzB0BKc2s0cD7b/VTuvSfFdSDa3rHN1ed/dy6WDRG2LPafGuRkG6KvhSTTt+7yKuCjVnytJg9hhkZ5tpFba3zBENZdXoUww3DEMHvN/+8f+wQNzlhb+tRN9Thhc8PlC+H+1w/E7F8fuLIavhCNwz2DmF4YWYva+j2CPZ5Vr8JDS2o5SUV+hqyYnR9rX0kKYkE2/nv1+EPEscHqBPN7ZK1aVIosvQoTzVouUUqjlOGhpbU4YXPjB18uxSmHFxqlnCOG2d+755X9+MOyWehy+PDbd5vRUJsPhy+ISQBCYRqtNo/ARrL+7vJ5JXjinUhiRZvdg/nl2Xh2dyseXloHuQyozDNhalQjO/ad2T2Bs2ffepZjrMjhQYqiprB6w0MZxF8B8AoA6c4aZxj8BlHXzCzA4S6nqPM4p9iKDddNx5EhMpP9HuvYRDs4eWYNtEo5J0VRaNESf7vf7cfhrkFuc8hl7GbqoNeQo8cmjRIbdzbh9vklgr+zcgmP7Wjivsv+7XifGy82tuPehkrYPQFBYzb+fUST2GIR+RANNPW4QIH8d1Ybh53YLb0uYunXi43tePTaOthcfrgDYUHkiY3mdzt9oBng2voCbG2MyHpEjJiM+P7Ye+E3ugOAokwtUcw9Ojr3aVs/brtoMjzByPVEP2f2HkfLmTlpd6PV5sN9rw2XAq27vAr5GeTu4wo5JciSZhhga2MbLigRdwonGjX44VfKYkpKJ0rco1Gj4LLN+Q6sUUQiwiiSbWtQi5smdyDM3TcQea/3vXYAT98yW/IYkuZizU3k7uKpbBpTaaYj5uT1ijh5VqMKdk9A0ACTdYLEcNZnZaRJ1zRGEf5gGMEwcM8rw+vOfVdU4fZ5CgRp4ME3DnEZFkBkLg14YjVdH/7XEVRPNKM4ywCb248sg5o4D4usejT1DOL2+SV4+dOI/vDe9gH4grSgUR1FAfNLszC7OJPLnEh0Y5lIafeZxMQMsrY6W0rNatKP543ZeICY3ml2HA3gEEPD6Q3hFzx/4ReXVyHHRCbbWHSKrB1dTj9qJY5LtXGqWBlwz6B4Q1sA6HcHiEHTKXHWt1RJKVHtf39a+z8ViPWqiP53bgZ5nJPsxt2LK3BZRQ4q80yREmmlDGaNEjTNxNhCm9svaFIHxPpI7FhRK2QIhMkyLew+o7HVjuvrCwXBEDZI/+zy2TjW44nx3ScYVdw1+II07nv9AP68/ALu9xPxL+PNn1Tm1mjgfLb7qdx7qlrwYvbO4SU3Wcwza4jXwk+iY79732sH8MjSOug1cnQ5/AL/ad3lVVDIKHQNkMcnHZWjxNpSdu/CZrzy7bvN7cfabfvxy6uqMS3biE6HD95gWOBHPfjmYfxl+QXYumIudhzuQZgelpERs/Nj7SulAv577XP7ie84+vLZDOoH3zyMu786FcvnlUAuA75cNgEtfW7BHv7+K6o4SQgWviCN7iFiODoQ/MCV1dCp5MR3rR7KAl/bUIlNO5uxZFYB7J4AmnoG8aUpWSjOitg0661z8F5zn0D6B8DZs289yzEynZiSx/ejz80wzCCAxQBuG5MrGgLbIAqIkKMsEcoHa1RYI3LNzHw8eHUN9z02LZ79LotrZhbgf7cfxpv7OrFiwRTYPQHibyvlMkHW0OZdLVj518+x6oXPkKFVYPWiMsHvr15UBvdQtOjlT9vxP4unYdWiUqxcWIpbLyrCzKIMPHPrHMydbMH6JbXcsWGaht0TwO/ebcbaIYKYbczGv55okpvtTsl+j5Xa6BoibNksZP41Pnh1TcwCwxK80c/A7glgkkWLPncgZsO95sUvcMLmRo5Jg9f2dGCSRYeG2nxs3NkUc165TPj+iqxaLJtbhC3vt2DTzmY89V4LWvu9KLbqMbcki8sQYKNz/M9UchlsnuHriX4Go+3MdDv8RIK020EmFQNhGjfMLuTufcv7LbhhdiGCYfHN4f4uJ0cMs+e499X92N/lFD3GI0LCekUapinlFHE8K+XiC3G/m6ztK6VJJKYl7Q2Sr4tdbPlIZNOolFOc9Ep5tlHyPgBgopl8HrGGdGatAusurxI8r3WXV8GsFSfTU72XNNI4HxEIMzG2dd2rB6BVK9DcMxgjRaNRyqAXcYQ9gUgXbZVcxlUNRR/LSlQ89V4Lls0tQp5ZwzW8AoYzPZ56ryXi5PO8fHZjmcg6RFrXpEDTDFp6Xdh9rA8tvS7Q0Tu4JFCZa8KveD4Smw3y+t4O3H9lNWonmrlrXFyVizdWzccLKy7AG6vmp8sIeaCZMO67Qmj/77uiCjQjTUoGwwxHDAORsfmL1w4gGJZ+p4ahUnY+NEoZdHHK0MUyxeM1Tp1gUBPPNyE60zIKOpWCC5pu2tmMJ95pht0TiHudycwfPsxaJfE6TVppmY40yKiZaMb9V1Zzz/S1PR24/4pqwXv51dU1qMwla12L2Q2aZrCnfQCrXvgcN/3xE1z/5Id4dd8phEK0wBaysmt8RPtI7FgpmaAX7PH432eDXWEa2LizCUpeZj5LdIVCIPruwZDwnnxBYQUd26zxqun5mFdqxVXT8znZIhZS8yfVucXHSK4JfJzPdj+Ve68e6u3Cnx/3X1GNGpHeLizE7J1JxJ4VWHTEa+En0bHwBWnIZIBGISeOb08wjAlG8hgkEZdatRw5Jg0UsoieMOsHsfvXQV9kjXl8ZxP+ebALt/7pkxg/yheMaHLX5GdgWq4JW95v4YhhKTufrK801uC/1z9/2IY1l5YL3vEDV1YjS68SfHbnJeX4+2ft8AVp2DxBbHm/BQUWHT4+0R8j9XjvqwdwbX2B4JwaZaQ5Msu/8L+/dtt+FGToiO96+iQzNi+rhy8QxnX1BTCpIwmTWXoVF9yQyShMMKrx1HsteOKdZoHcRXrfOjoYq8xhO8MwMSKLDMMEKYoaU/HFqjwTJ8ANRJyU6HKG9UtqBUblwKlBPLbjKBd5mVtiRXmOCQ/965DgWLksMnHml2dj865juO2iyTFlQhuumy4oX+JPulabF//376O47UslxOgxOxF9oUhTPFaW4eY/fsJlIFdPNGPrd+bCEwwjz6zB1FwT1m8/BKc3iEeW1kGrkmH9NbW4++97uaxjXzAMjVLGaftSFKCQAS+umItAmEbHgA8rnmuMlAVQ4LKQ2SifjAJmFsZ2mWQJXtLzdQfCAr1kFmyke06xFXcvrkCbzc091+gsq3mlWfjJ3/ZwAux3L66IKa+/++W9qMkXb2TGwhN1Pfxz1eabUJZjHNXoYp9bRI7BTSaHB30hYmZNabb4fUeX+rHnYEuASXCJlLS4/CHi9/VqBfQquWA861Vy6CUyh/OHFp3oyGh+hlb0mGKR7uJizkEq0fy2fjcOnhqMyZouytSLajRnaJXEUkGLyCZTp5AjU6/EI0vr4A6EoFcpoFRQ0CnFN8Hnc1ZGGmkkC5tI8GnAE0SmToU7LynHb/59VDBfQwxDtC9sVpcnEOaCl/y1LlqigtXh7RzwEGWAooN5ZyrLZaR1yhUKGa6snYjSCXr0Dvph0iox4A3i0WunozaqKVI8fdLzGVqlCjsOHccfls3CgCfI6Z3+8CvlksfZXMk3SwUizRVJ65NWYr0BxDPU2AxxMTAMiOM+HgWlV5GvMx45nOr8CYTCIvMzfuZwujlsLFQqOa6qnYiSLD33XKpyjJiaa0CXw4dcswZVeWZJrWuS3dhPyHC855WIlMLMouGquUR8JHas/PdYLzJ1qpjxtu7yKvz+P82CsnV+MISdE2Lri80dG3TMMqix+1ifYJxE3yN/PCnlspj1adXCMoASn1uJdvk5070rzme7n+y9a7VKXF6di+IsHbqdfuSY1KjJNUEbJzglZu/+e6yXODYGvOT1gU2iI+3BTtq9osk7EwzqmPPceUk5sowq7vdY223SKMAwERnBNZeWczI+7LWxzdMaavPx//4hlIRh/agt77dwjYHPtmzgZBB9fzlGDeZOzkTnkO2syDHhlNOLKdkGdNi96Bn0c9q/GqUMc4otqM2fgWO9LlhFKtwKLTrBO1rbUInOAQ/Hv0R/n2aYGBt55yXlcPlDWPPicFb5L6+KNMvLzdAKqiD4jUAbavMhlwGzizLjNotNY2QwVuTwuxRF/R7AowwTSXmgKCoHwKMApgEg13qPAhQKGa6qy0dZtgH9bj+mZOnxfzzit74oExeVDHeQ5et5sqXem3e1YPvq+Xj6ljnod/uxdcVceAJh6FQKbN7VAoqKGLT/3R5p+sYnUSvzjFy2K0l3q7HVgZ99TY1peSaBkaNpBuuX1OJYr4tzDMQ0g9lF/YLJVhRk6BAM0zG6u/+8Yz56XT7kmjRgGKA8x4i2fk8Uka3H1Bwjvr0loiH05K5juPVLw4Q3qyvz6LXTiaX1xVY97l5cwTUu4T/fNrtHVJicn7Xd1u/GCduwjjMbXdQoZVg6M5/7/YbafHgCZOIykTKFHJMm5no6HT5seb8lbifXMwFRgtRMJkiLrXqiHIEUQShW6ie1wSvKJJOwYtIK5ROMaOlzo4/nGGfoVSifIN5h3KKPZM9Gl+VZ9OKOkUpBxXSYvu+KKoGmMh+pOBPdTj8xa3pmoUWUHG61e4ik/bRcI6YQuqx3Dwbw4BuR8cx+//W9HXhoSR2KJ5Cv61x3jNJIYySRZybbvUydCr9+8zAAcOtVebYRDBjQdGyjSH63+hyTJiZoOi3HiF8RJCq0Shkq8sy4Z9u+GBmgxdW5Mdd7JjbVZ0KnXKGQoU5CpzaN+MjQKXDxtDx897lPBWtfhsTaBwBWg4o8piXkiNjjSMFbq0H6uFQDkmqlnCh/9aVSq+RxmQYV8i1awXXmW7RxrxNIbf5MzNDhnm37Y67zq1XSjQHTzWHFoVLJY7Rv6yZZUDcp9d/sE+1pISS9EvWRZDIK+Rk63PPKftwwuxAPL62Dxx9CvycAq16Fhtp8Qdk631dm54RyKBMyei5mGYQE2f1XVuPXbx7ktO5J44Q0nn7+tWlYeXEpfCE6Zt0gzS3SmkLCWd+74hyDVqvEnMnSdpEEkr2baI6M6eixceX0fJRlxzYR5SfR8Um+qjwzQjQ5UJ5r0sCiV8WMwec/bsUvr6qOsd09g36uAeT3vxxJiMvP0KJjwCuQGRAjJ+UyYMN1wz7YuR58IN1fLc92snIN2w904V7ePnj9klps3HEUV8+chMd2xEqTApH31+X0Yfm8EhRbdThp98DtC0KtkKNQJPFKJZdBToGzkb0uP57/uBVXTs+PCdZtXTEXNfnCBEKZjMJlFTkx/FR6vRwdjBU5PAvArwF8QVHUagA1ANYAeAjATWN0TRz4mxiaZlA3KUPUYRDT8+xy+riSBDaya3P7sX5JLVp6XWCo4WxXPmF30RSrqJYxQNbupWkGbx3qxoa3j+AHXx5uyiamGcxf1AEIGsL5gjRWPv853lg1H3NLsrjz0gwEHX7Z3/jtt2Zyn+3tcOLp/x7HnZeV4+lbZqPfHUCBRYeqPBNxIrOTPz9Dg06HD3m87IBiqx41BWZiZjW7wZDJKBRnGVCQoSM2nijM1KMwU49puUb0DPqgVZL1bRMpU0jkekYToovzRHLZnUJG4SdfnYqH/3WE+/5PvjoVCgkDy5b6RXc3rhU5BwBMziJvCtkFOhrtDi+e/eA4brqoBN5ACFqVAs9+0ILqieLZ3KcGfHhrfyf+sGwW7O4gLHol/vT+cUzO0hH1loFI47ffvtsscEp++24ziq11osck60y4AyFBdj0QkWBhS8tJ0PPKYVlolMIO1NHnaLV5Bd8HIHmOVO4ljTTOV9Tkke2eJxiC3RPJ+tryfgvWNlTCalDif9+IEMZrL6/EkzfVwxcMY7JVLyhH5JNlbPDy99+eRZSomF2ciVmFFkGlC7emWXRo6XWd8azDs16n/BzFqQEf/vpRKx5aWsetl0/tOia59gGAWiEjBlSjyz6jUZipR16GSxC8zYvK8CEh5YzccJjYyE5K/goAgiEGj751hAuahmng0beOYMtN4n0ITgeTs/TE+Snm57BIE2yjC6NGSfT5ST0wEvWRCi063HXpVEGTq/+9ugbBcGRdiJd53NbvJq4vu5t78Oytc2D3BGA1qDliGBgeJ1PvmI8pvGo/0nh68M3DWLGgBJt2NsdcB2nMJrp/Sa8J5x5YbqLf48eqReVcBi6b5fmnD07goinWmPfLT6KLzuwX85+qck1QqeTEMTh7Uia0SgXn12TqlPj64+9zHMnv/tOCa+sLoFHIuEA7EJnLMydZiHP8S1OE/RnSGOZctq6Yy3EuNMPggpIJXMM5VjIzeg1mG8KtWFCCHJMGTm8Qf/zgOO6/siqGf/nlVdXINqvh9IcEPaMevLoGD//riOCafEEaJ+1e1ORnxFxvm90Tw0+l18vEcLoVSmNCDjMMYwfw3SFi+N8ATgGYyzBM+1hcjxT4DgPpYcdraBEd2S2yavHra2rhD9Fxs2Ir84wosuoFXcxJiznfQWA1g9nfFctAZhd1RkK6gT/5xBod6KMaivW6AjjcORhDoJIiPSypLZZFsXBqDkonGDCz0AJPIITCTD0mZ8UOcIVChstrJ6Im30zciPDfX6rl9clcz2hAanEm4bjNjafeOy4gR5967zhKsvSi3bVJpX7RJcDRSHZT2O30obHVgcbWzwWfSzmceWYN5pRYBdlTqxeVIVciozlVUjUZTLbqic34pMZXtpHcgTrbSNaBSzYzO4000kgOKpUcZdl6bLi2DkGagZyisHnXMTh8QWy6cSYOnnLCH6KxaWczfrSoDHs7nEOZxWrBxp0Pkl3sdJClI7zBUETnXkEJsmlUCgrvNvVg5fOfn/EsivO5e/x4Ro5Jg6M9Lqz66/B6mch78QRCMGsUAjkiGRV//aNpBr4oXX5fMAyaZuKOuVQCkla9OqXsxja7h7i+n7R7UEqowDldkDbZVXnmuM8kTbCNLvwi8h/+UGqNA2mawbtNPRgYIklY22zUKvCVsmxUrDLFzTwuzjJALgeeurkep+xeaIYSIhZV5GKCUY05JVbsPNzNEcMsfEEabf1uwRojNp5mTMrACysuiLmO06kgS68J5xb43IRFp8JPvlouGNMahQwqBSX6ftkkuujMfpVKjiuq81CQoY30WRga3wa1AourckXHIL9qYPexPsE463T4sHFHM1YuLMXLn7ZzQXizVglPICTpR6UxDBLnsn5JLbRRFdHb93fi8RtmwOELoq3fwxHDv7yqGtNyjfAHI1rOf7x5DhcQzTVpuAZyj751lFsXH1laB7VShpIsA+QyEBMijnYPojLPhGKrXsCxpdfL1DASFUpjQg5TFJUBYD2ACxBpQvd1AG9SFLWaYZidCRz/RwANAHoYhqke+iwTwFYAxQBOALhuiIQeEbAPe/32Q7hhdiEmWXQ40jWIaTkGScIxOrLbavPi1j99gn/9aD4x2zU6K7YwU4/pEpnLgNBB4Ed9ojWDxRb1RBZ8UQ05o1pw/9fWFxCbyJEiPfGyKNhnwC/JZxsiREdDEtmIcKT76vnodvrhDoRQJEGqkYIB0dczlhBbnElINkOVhUxGQSmnIJdRUMplCRmWZDaFqTicYRpE+YbLKsU3kKmQqslG3mgm+esCQCzbFcPkLD023TgDe9sdoJlI88uaAnPcjKU00kgjcZi1KnxyvB+uIa35BVOz8fKn7Vj5/GdYPq+Ey/7VDQVHE8kajLaLYZrB1sbYUs6nbpqNEzY3RwKz0ChlWLGgRHS9HCktU5pmwDDAI0vr0NQziBcb22H3BNI65eMAxVay/Y/3XvQqJX7z9lHcdFEJwAAMgD/+twX3fKNK8rgDnQ785G97Ceum7oxIhBRb9VjbUMndn0IGrG2oTOD+yFVh8fybVMGShOx1Hup0otflj2kQFo00wTa6yM/QYd2rBwQ2dufhLlw0xYrdx/qQbdRALosQInybKWZLT9jc2NvuwOZdLTHvkJWXS8TvDQSB//ePfVym+9wpE/DCJ22om2RGkVWf8HgWG09FQ5Ur0TidCrJ074pzBzTNYF/HAA53OXH7/BLoVXL8/B/7Y8bR5mX1Kb3fU4M+/M8/9grG9/rthzAt18iNP9IYZOedjCJLrzBMhFxkGAb7OhzQqeSoyjMRA4pPnaGqkbNZM57Eudz98l48t3wOVi0qBc0ABrUcRZl67DvlgFohg1Ypx5JZBZHeUZMyUJxlwAmbG4EwzVXI8hvI8d+Z3ROASavEvNIsyGQUQiEav/v2LHzeZgfNRHp6XV9fiOc+bMWFJVYc7hoU2Jcnl9Wn18sUMBIVSmMlK/EZgN8C+CHDMCEAb1EUNR3AbymKamUY5ptxjv8TgE0AnuV99jMAOxiG+TVFUT8b+vfdI3XBJ2xurN9+CLddNBmeYBg/5qXK8zV6owlcschHp8Mnme3Kgl3M2YjKR8dtyDFpUGjRoc3uQbfTB92QI8GWtMtkkY2dXi3H5Cw9GAaSGciJLPhijgEn3TAUCRTrUk2K9CQbFRopvbaDnYNxf+Nc04bLMZEzVNnuoCSEQjRe2dMRI11xVV2+ZGOQZBbPVBxOsSz2nkGfaObe5Cw9Hr12Ou56afg8fE1Q0j0k+/7FrqvXJX5dx21u/O3Tdty+YAq8gRB0KgWe3HUMkzJ1ohndgRDDbU7Y60ojjTRGDoUWHSx6NTb8e9j2saV11JD2/OpFZZho1uCNVfOJNi6eHZwywYCffrUixiZNmWDAR8dtRFsS3RzeolOhd9APm9uPUwO+09ZmI9m9B6+uwczCDK6xSxpjC39QaP8fvXZ63GOCNI2F03LxU57fumphGYK0tFyDWFf6LocvblA61U10KutbshU4p4u2fjdO2b2Cz07ZvWjrd0smD6QJttFFtI0tsmqx8uIy3PDkh4Jx8uzuVi4AdllFDjG77hvVeeh2+iQbZSe68e73+InyKQPuINr63cg1q7G2oZIr9Rbz10dzPKV7V5wbIK3x919RBYtOFdP/QCmniO83nm23ucnju9/tF50j0ZnM0facbSy/elEZGCbiCLn8YRzvc2P1onIBv8H6USONs50X4HMueWYNrplZAKNGjvZ+LzbvaoFFp8JNFxbhTt79rVpYhpc/bUenwxchcLtdxPsn2aL1S2oxtziTk1WN9lHXNlRi68dtsHsC8IdorN9+SEBo3rNtX0wS5YNX10BGIaHqpfMVI5FxPVbk8IJoCQmGYb4AcBFFUd+JdzDDMLsoiiqO+vhKAF8Z+u9nALyLESSHu50+NNTmw+YJCKLGviBZo5eFVKZAolFckjTFHQvLONKuyKrFw0tr0W73xsg5sBu6Iqt4BjJpwQcQk6Er5Riw99HS60o40pNsFsVIREMS/Y1zTRuuMFOPshyDIEO1LMcgmTl7QKTTc1m2QTRrKNnFMxWHUyeaVSHdmVytFJZpq5Xi50jl/aeSFWTWKLF0VgGaewa5TLClswpg0pAbDJ1r4zKNNMYj2uwerN0mtH0bdzZhxYISzCqyYJKlCgUWLeoKMoiBskTsoExG4WvVuajIi7V9YraEbxbzzBrcdGERbn76Y64z9+naBZJ9+fk/9uGNVfPTjvg4wPE+N0d0AZH3c9dLX2Ba7nzRACQAqOSymL4TG3c2YeuKuZLnE+tKn2uWztxJdROd6vpGUYBVr4zIZvhD0GsU8PiDXGbTSMPmCsAdCAtI7NWLymBzBVAcuw3gkCbYRhfRNlarlOP6zR/GVHex1SBrXvwCW1fMJWbXWXQqFGZqJRtlJwqx+fjksno4PEF0OHzYvOsY1/i0ItcEnTpS6RZNzF1WkYM3Rmk8pXtXnP0g2dh7Xz2AFQtKsHGHsLKU1Hw8EdueynrDv65Ohw/P7m7F6kVlmJSpAxigfcAz1CDPgEBoOEq+5b/HsfxLk/HcbXMQZpgzOgfO9v0X61dadCosm1uEjTsjtu///h0h1q+ZGVv5zX5ny/st0KnkuPWlWf9jAAEAAElEQVRPn4jef/TaVmjRcYE2ko/6wOsHsXpRGb5n1WN/hwM/vmwaHuQ1aW61eZGfocE/75iPQ11OHO0exMP/OsIF8s4WUn60MRIVStLdKM4QpLSFGYZ5MsWfzWEYpnPov7sA5KT4O+QfN0XKj6SixiSw0RSNMvKoU4nsRhukhtp8AWnXavMKiGH2mta8+AVO2NwAhhd1tkledFdI/t8AYPuBLnx943v45pMf4esb38P2A10AIPobqdxvss9GKhqSKBL9jZE413gCq5l81fR8zCu14qrp+XFLIKWyhsQgtniy41Ds2uKNKz4C4YiOHH/cxGtaw5Zpb9zRjE07myP6Vc9/Lnpdqbz/VOa6RinjNpmbdjbjD7ta4A6Eud8YietKI400koPYPJsywYB7t+3H3S/vw/JnGvHWoW7Q0em8SNwOitk+MVtSW2DmPuNLOEn1FRiJ+07bl/GB1n438f209YuvrwBEK7o8AWntVbbxLX8csl3ppZCKHwCkPv56XX7YPSH8+G97cPff9+HHL+2B3RNCn8sveVyq8IXCRAkpXwJatsn6O2mcHvjPW2wesEEElpgifaextR9hGlxj6tPZ04ldx572AXhDYax58QtOQ3vjjmbc+eIXKMiI/H703uytQ90oturT4ymNhCBmYwszdQmN6URseyrrTfR1dTp8WL/9CHJNalRONGH6pAxcMyMfTl8Id7wQ2cs99V4Lrq8vxJb/HkcgTJ/xOXC2+0esX3ltfQFH3vN9RzE/Ui6LVJgHwrTk/UevbW12DzdWxH4716zBmhe/wCNvHcVP/rYHy+YWIc88LHmaqVeDooAfv7QHG3c0c/Y5EX/ifMVI8I5jlTl8RsEwDENRVOyODQBFUSsArACAwsLChH+z2KrH7KJMNLb2J8XIJ5opQNMM2vrdAi1cttlZtEEiTTJ3EnIOUmC1iBKJjoldc6KZEclmUYxENCTR3xgP2nCpjlUxJBv1TyVrKJVyhmTLT1NpWpPsdeWYNKgvMuOmi0rg9YegUyvwzActku8/lSY1Lj95kzmzkJyZPR7GZTRGepymkcaZQDLjVGyenRrwotUWKSeXyhpJxt74fCHs63Sgy+lHrkmNmjwzNBqFaEXPGyISTiNhF8ajfTnfIDVOU9XWFe0ZIdHEFUi+8S2LVMsaUx1/KrkMv/n3UcE6+pt/H42bGZ0q/EHyJjkQkpbpOJdwNq77YuNLoxjeRIv5vWEa6HX5RqQxtdh1eIM0+t0B4tjqdflAUSDuzSpXzUOvKxCzhqQRwdk4Vs8UxMZel8OHZ26dAwbS2bditt3hDeCT4zZ0Of3IMamTXm/EritTrxZUJrPyEex52czW0bC9Z9o/OtPjlOVcjBo5wnRk/zw1xyi4J9L9LZqWjZr8DJywuUXvn7SPt7n93D49+jzsscf73MT3ueX9Fo7QFJNZSzemI2MkKpTGJHP4DKGboqg8ABj6/x7SlxiG2cwwTD3DMPUTJkxI+MdlMgoXllhRkWdKOmrMknJziq0AgI+O29DS6+Iyjmiawc4j3Xhzfxdufvpj3PanRnzj8Ui2Lk0znEHiI/rfbKlT9Hf4Rott5rb7WJ/g/Py/bz/QhR2He+JGx6SuGYifYRz9bBL57khEQxL9jZE41+ki1bE6UkglayjbSB6rEwzkxZMdc9FZ6qRsPBbFVj3uXlyBLe9Hsm23vN+CuxdXSL4bsTkktqgXmLW4bnYRfjqUifSTv+3BdbOLUGDWip6D7QR7/eYP8b0/f4brN38omlnIwh0IiUTYyV3ki60R7WT+O3n02rHVLBzrcZpGGokg0XEaCkXmX7TtW9tQiWd3twq+K5Y1kqi98flCeHVfJ5b98WPc8dfPseyPH+PVfZ3w+ULEtZH/WbFVz52DbUR7uutVoUVHtPmFFl1Sv5NG6pAap3lmFe6/okrwfu6/ogp5ZpXkb56OP8M2vv1qdR7qJlniEsNA8uvt6V5nqpnRqaKIN/dYaJTSDW7PNZyN6z5pfK1eVAajWoEiqxYbrpuOqjwT1i+pjalMe31vBycHWJxlwAUlVlw8LQdTsiPNQPectGP7/k7sOTmAUByiqtiqFz1HfoZOdO6QiLnybAM+PjFAXEPSiOBsHKtnCmJj76VPT2KCUR13L06y7fVFZjT1uLkx+JO/7cH9V1QnZcej52Z9kRlP3zIbR7sHuTklRkzLZRgV23um/aPRGqf97iC3f37krcNY1xDxKV7+tJ3Ib9XkZ0Tsnsj6XGjRxezjdx7pxqkBH/E87LFrGyrxUqNQSMAXpFGbb8Ibq+ZjcVUk4UunlGPVolKsXFgqyCpOJy2I43QrlM6l0OKrAG4G8Ouh/9820idQKGS4rDIXbf3upKPGUjo9pA64/KykaKHv1/Z04JdXVQsahdUUmCUbE0SLvV9bX4DybCMq8kzc9bPlIrfPL4kbHYt3zWcimsOPhvS7/VDKZfAEwjhhcyccFUk0opLWhksta0guA7ExjFzkkFQ0nFJ5N8k27jjU7cS9UZqj927bj6k54nrLbNNKNlIKQNChl4SiTD1xrok5OjTNgGZogXYyzdBpcf400hgBhEI03jzQiaYeF3QqOR5ZWodgmEbHgBduXxB2T0DwfTEHNVF7s6/TgXtfjbIzr+7H5CwdZk+2Eq+Rn6Hx5LJ63LNtH1ptXmxtbMPmZfVQyqmUu2i32T14fChzg63KeHxnpJIhnaEx9uhyBvDEu82C9/PEu80ozqpDIXm4AEitquV0kGqjrFT9rmyDGkVWLRpq87m197U9HZhgODMN6SZnke9PrMFtGuMDMhmFyjwj5z8xDLhmdFtXzOVIkG9U58GiU3FSElsb20QTEPhrBs0AhzqdaOt342tVeaK+stQ5qvJMknMn2l9csWAK1yAdSGwNSeP8RbLjOxok277m0mm47ZlhLdpWmxdPvNuEZ2+bAzpBHWC+7Xd6A2ize7G7xSaYU5W5JuJ+qb4oMyHbm2qTVBbngn90wubmGrwBkXf1+13NeObWyLvKM2twWWUuel2x66/Y+kzax7P8kEWnwjUzC0BRwKAvgC0318MbCGNvhwODIj51WU5kz0zizdjGhImO1zRSw1lJDlMU9VdEms9lURTVDmAdIqTwixRFLQfQCuC6M3FuNmos1ZGYBCkSjN8Bl+0gyTq4/W4/iq16VOYZ8cytczhCuihTh5mFlpiSUzGnmj0/X4g8mqRmo3JsFlL0d/gTkdS1l732o92DAHBGyFQ2enW4azDljqHx5BWiF5A5xVbR3z3dxWa8g80aiteZnEWnw4c393XioaV18AZC0KkUeHLXMcwozCDOmW6nT7B4AJEsuETLRRjxpFwBkt10djrI1yXVpT2VDr1FmTo8vLSW21jIKaA024CiTHIk+kCnAz/5214CmawTJa3TSCONxHC42wlvIITybCPc/hBAAcFwGLMnW5Bj1KAgU58Q4ZWovely+omZMN1OslYqyVlev6QWRZlaUBQFTyB8WutQt9PHaV3ykS7fGx/odvqJ70dsvLBgq1pGq8v6SATXE13bASBAh/GjS8pxvM/NraM/uqQcQfrMZA6PRfLAue5rjhY6HT5B4y0WnkCYe54KhQwXlVhh1irQ6fDhssocVOWZiM/7cLcTdreQ4LC7Azjc7UR1fobodSgUMswrzUKBRYueQR+WzMzn3qnY2GKJufXbD6GhNh9yGWDUKmDRqbgmToD0GpJGGjIZhfwMLUJ0BvRqBa6dlc81r0/k2OjxefCUM8aPabV50eP0o6FuYlLXVWzV4/OTAVAAyrONaOlzI0zTsLsDCNDhGGJ6/ZJaXFQivkdnkWqTVD7OBf8oOvs6z6xBQ20+TtjcmGjWoiBDB4VCJtrglsSfkDK6aQZEvunehkpMytQgTAOBEIPfXDcdv95+CK02b+SdXFuHTocXx3pdyDZqsH77oRjZiUeW1qEyz5he/84gzkpymGGYb4r8adGoXkgSkNJgyzFpIKeAIqs2hlyqnmgiGrTJWXoiwSlGerLnv2ZmQUwXUZakZstFOh0+PPdhK9cpl9Wb4U9E9prZKF6eWRNjBDbdOAOTrQbuHkfKmY2XbUpyotnj4jnW8RYQ/m/nmTU42Jk6ST3aCIVoHOh0DGUOaVGVZ0qoRDQZ5Jk1+FpNHn46lMnAZg7nimhN5Zk1uOnCophMY7HvA8OSJnvbHdxGsKbAHLfBXjKaywUWLfG68i3ishKpdOhtH/CgZ9Av6Hr+k69ORfuAh0imSzUJTJTATyONNMjwB8OgGYrLxNIoZfjF5VVQUJGgcGGmPqYbs9i6koi9yRXV5iNnPJLWvud2H8fKheX4rM0OmolkTN69uCKldSitOTy+Ia7lKJ0hO5Zd1pMheVPdwDu9IfS7AzHrqNN75krrk+3hcDoYCWIjjQh0orrdcu7fYsGUyypy0Gb3COy92x9CkGZixp7bHzv2SHsT0hgSG1tsBUAwTHPZf6xv+uzuVo4gTsQmpHH+gaYZHO9z41CnE009g3ixsR12TyAiDZCELEP0+LS5/CmtS6Tr236gC+u3H4rhQlh7LtaLoaXXJbm/H4k18Fzwj/j3QOJt/u/66SjLNibF2+SYNILKHa1ShrJsI6blGGOqGv6w6xh+tKgcW94ftpfrLq9CmKZRZNXhUOcg1rw07H+vWliG5z4ctm2+II3D3YPIMqqSTtJMI3GcS5rD4xpSGmzFVj1qCsz42eKKGHLpYKczpa7PYueX6mrO15PpdES0YqblmmKIYQDcNbP6NNGks0WnQlO3C994PHEt2UQhRbSTNGx3HulOWNdWqhNr9G///fOOEXk3o4FQiMYrezp4eri78cqejrjaaMkiTIPYYC0scppkvw8Abf1uNHW7sHlXRMvoD7ta0NTtituxPRloFHLidWkUctFjUtE97Bn04+F/HRGc5+F/HUHvIDnrg22WIrhWpXSTwDTSSCMxhGgGv3jtgGA+/uK1A2DNZLTm71uHupPSS49GTZ45Rpvv/iuqUSOi607K+rh65iR878+fCrp3r99+KKV1aDxo7achjppcE3m85JokjxvtLuup9BIApP0vKTAAcR09fW9zfCDV55JGLALhcIw++6qFZQjynE7S816//RD+ub8zZkxTVGJjL9U5EY02u0dQFs76ptfWF3D3I7WGpHF+gh1/33j8Paz86+f4w64WLJtbBItOddq2JFk/RgzsvGuozY/hQtg5Fa2lCiCheTUSa+C54B/x74HE2xzvcyfN2xRadLhjYRmnL/z4zmYc63WhfcAT88yvnTUJ/xPVVPC+1w6gPMeIT07YseFtYWPZjTubcM3MAu54jVIGGYWzipA/G3FWZg6PBuKVcCVb4iWlwSaTUVg4NQf/ORrbCC5augFIrUsje/4jXU7RyFcypXLsNbNde21uYXnsNTMLYsi1kcpUiY58XTOzAHIZoFUqcLxPXPsmkWuJt4Dwf3uk3k2qSGYMHuh0cBrV7HXe88p+lGWLa+imgp5B8vPrdfmIZSrJfh+IlNCSiNuZhZYRiyT2usjl3n1uP0phJB4THT0FIll8Uh16Hd4g8TwD3iDx+2yTQL7eeLwmgWmkkUZi6HWRO8X3ufxc1k1rvxt6lQJ6tfy0M1E0GgWuqMnD5Cwduoe6fEt1mo/OXLlmZgEeeP1gjDO9fF5JSutQWmt/fEOrVeLy6lwU88dLrglarVLyuNHOeEo1S0vK/5I6zuEhr6NOz7nRlCvV5wKk5SiiYdWrsbWxTaAburWxDYurc7nvkJ53Q21+DCm75sUv8Nj104nvxhE19sTmxNQ75oOikPD7ERsL1RPN2PTNGXHXkDTOT5DGH+srPPFO82ntW5P1Y6LB2qij3YPwBWnRJLboOUXTDPZ1DCS01ozEGngu+EfsPeSvmIvDXYMJ8zastjDJTrXZPTH8wmM7mvDw0rqYZz7BqCa+W5srgHyzlvg3tmcRWyUxOUufbpJ8hpFePQhIRFog2RIvdkJWrp4PmysAXygMf5DG8T431xCO7YDMnxx86QYWyRg0vmNYmWdERa4RRVY9HttxlNOsml2UyU20ZErl+PrLLb0uwXVKZSifLnHK193il55s3tWCR5bWnRbBLrWAkJwyEhk4GhGtZMfgaMkRJLsAp7Jgu/0hkQzdkdsIpnJdbPQ0mriVWsRMGiXxPCYNebOvUMhwRc1EFFv16HL6kGfSoGaidJNAYHQkRdIYXeRPKsSp9pNjfRnnFHJMaqxaVAo2UeLlTyNll5l6Fd7c34W7Xhq2t+suryJqPSa7xmk0ioQbB0UHmeUy8toml6WeWTGa5fJpJA+tVok5STaaSrVBXKoQI7C6ndJzI9UNvFYlJx6nUcVf484G8lQs8BzvuaTlKGJRaNFhzaVTBbIM0XOBNA7FbK3Y2NNGjT1S1cc1MwtwsNMJs1aBp98/jt3H++O+n2wjeY5MmWAQTahIIw0xm0xRIxMoTMaP4SMUovHP/Z24++W9uH1+iSArl73ePLMG19YXgGYYfHqin9vzbD/QhcNdsXrHJD9spNbAc8E/ksko1ORnwOkNJcTbdDt9kn2exMbW8T53TP+qPDPZfoVoBqccXuLfFpRNQGWeCTKKAgXA4Qvig5Y+TLLoUDS0Xp8N6/jZhDQ5TAA/wsYu4Ie7nMjP0KIm33xa2jXNvS40dbsEWqbsJOOTnjfMLsQkiw5alQzrr6nF3X8Xd2TEIOYYNlTnQS6jYpyjRBxGsQkYs2k9TVJbClzkK0OD6zd/KHgPTT2Dp0WwR99HkVWLB66sQbfTF6NVtutID7735VLcN1SGnAgZOFJIdgyycgTRz2Ck5QgKLTpiZqvYM0llwc4yknUXrXrVmN0HQI6e3vPKfslOtjkmNVYvKovRNhbT6qJpBv8+0pPUZi+VbtppjH+caj+J6//wQVLHbP3uRWfoas5+BAJhtPd7BdqRqxeVIdesgUGtwK1/+kQwt+977QBWLCgRNDcaDf25qTlG/PZbM6FXK6CUUYKqGPYaZhZazqpSxzTOLFit0q0r5goChGdq85SIrisJqW7gTRoFcR01qqW3OGcLeTrRqMEPv1KGe18d9kfuv6IaE+PYGlIlHZutej4QidH7lUKLDm8d6saGt49wPVXqizJjGlqRxuGsQgtxTBvV5LFn0Qn90Xhanw9cWQ0AcfeSMgrE842j4ZrGOISYTZZRGDNpBJpm8EGLjeMiXv60HasWlmFrYxtHKlp0qpj+Lw9cWY0LSixY8+IXHKGcyP6e7zvlGNUJN+E7FyGTUbiwxIr1S2q55y/GlehVcuxuseH2+SUAIkkTfDslFtT1h2j89bN2rFhQghmTMlBk1YMC2X612z14sbE95m8/vmwq7nrpCyz/0mQo5BS6nH7QDHCy34Nelx82tx+ZOhW+aHfg50NyFeN1HT+bkCaHCWCjINEL+OZdLdhw3XRYdMqUsmJP2NxxJQ4uq8iBjIo4dayQd5FVi83L6qGUU0lFRMQIxK0r5hLLo+KR2/EcaX65Ra5Jg6m5Jqx58QtYdCpcW1+A8mwjGCbyO1LXn0gESCajiBqvLza248GrawRGoqbAnPCGg38f/W4/OgZ8WPFcI/ce+IThV6Zlc8Qw+xzjkYEjhWTLDFOVI0g2Gtdm9+CFj1vx0NI6eP0h6NQKPPNBi+gzSaVMJ0zTWHd5lYCUX3d5FehkOt/EQZvdg8eHSq7Y0sPHdzZJvttUsqUmmrTIt2ixYkEJaCbi+OdbtJhoIje+SyUwdbjbiXZ7LOkVr5t2GmlwkClAUck7WRMLJqHjZNsZuKCRx/5OR4wW2mM7mvDkTfUY9JHlJqZMMHBO8ZnOxiStv49eW4c7LynHb/59lPtsbUMlMrSKtFOcBgexBltnavPE6rryya9oXVcSUi3blckoTMzQCNbRiRkaKOTSx41lo75kcLDbyRHDQOQ67311P0qz9ZhZlCl6XGu/m2i32vrd5zw5TLKX65fUYsPbR9Bq8+KJdyJBPY1Shjei3jdpHDq8AeKYVsgpog9XEaUDziecSY3B127bjz/eXI93jvZJ7iWP29x4dnerwDd9dncrpuUaMXkcjdk0xhdINnltQyWm5Rgxo9AyJv7CCZsbja393DzodPjw3IetWD6vGAUWHR5ZWgeKAu56aU/MXPnz8gsEhDL/vqL9MDHuIpkmfOciFAoZLq+diJp8cwxvw39OJ6P2j2yTONZOkYJpbJNMuycArVKOyVl6FGcZQNMMynIMAnupU8rx+10t6HT48OzuVjy5rB4D3iBUchmeeKcJgRCDbKMGrkAIFIYr+lYvKkOGVoldTX0JS4emkRjS5DABbBSEtIBHyNULU8qK7Xb64koctNk9ONjpFAz0VpsXK55rjHFg4kGMrBKTGEiE3JZypKPLLQoz9ahcPR+ftQ0kHNFJJpODFK2yewKYWZiBN3gkdZgG+j1+bF0xF55AmMsgiNdlHgC+veVjwXt4fGcTtq6YC28wDK9IA7LR0BzOMWlQX2TGTReVCEhYsTGoUMhwVV0+yrIN6HL4kGvWoCpPWo4glawam9uPhdNy8dO/CbuN9rv94pkQSZbpyCgKv/9Ps8A5/v1/mrHxhhkJHZ8Iup0+wQaChdS7TSVb6lC3E4++dYQrFw3TwKNvHUFRpo6oBZ2K9qDdEyRqNFfnp3WK00gQdCjpLGXg7MpU7hPRGfcHw1AryaXDGVoltx6caf050vp710t7sOaSMoEt3LzrGJ65dU7c7t1pnJ1IpXxytEnQRHRdxZBK2a5BrcQ/93bgW3MnY8ATRIZOib98eBw/+1qV5HGno+U7mhCzTX2ugORxelGf5Nzf+pHG/N0v78XyeSX4+2ftuGZmASfRQfJPo8dhS69LdEx/vSoPBzIdkr41n3A+IlIK7/KH4+4l9SoF7J6AwDc9X95pGqmDZJM37zqGp2+ZM2a+AcuJ8G1Up8OHR946iq3fmQtQQFu/lzhX+t0BaJQyHqEcqQRYNC0bNfkZgntKZP07X2UJ2MpvIPLsK/OM+Ocd89HrigTFZBSw+LH3BM9u484mrFhQwtkpvm072j2I5h4XAGDJrAIueDWjMAPFWQauX1VJlgGtNjc+PzmAl3n2WE4BrTYXOp0ByGXAHQvL0OX04Uc8HoIlpx/b0YRHltaNef+ncxHp1YQANgoipmUTDIeTKn1jjY6MouJKHCRCICcKsVR/MYmBRMjtZK5LJqNAM+CIYfb7UpuSZDYxYiWIbKlIsVVPJDdnF2USs2guq8hBm93DLQ6k+221eeENhlFfmIn/Hus7Y9IZ8VBg1uK62UUCEvb+K6tRYCZnnAIRgrhukiVhjeFUNpQquSwmoLJxiFAXQ7KLsicQJhK3nkA4sRtLAKlo/KWSLdXpIJPQYlrQYnpzEwzi1+ULkoMYvuDIPa800jjbkalXkQlgnRIyisI936hAz2CkpE1ORRpr6NTymI3ImYLY+jvRosOGl4bXgU03zkBzrwt72x3ctdYUmLFwas55sdk5l0HTDHYe6U763Y42CVps1ePuxRWjpnFcbNXjW3OLMegNwRcIY1BG4Vtzi+Oeb7Qb9aUKMduUqY/XiDA52apzCWJjXquU4XsLSmDzBLg51OcKxK1olBrTMhmVkG/NEs79br/o+9x04wwUW/WifSLO53eaRuoYbZucCHJMGry2p4OY0WzWKVGcZUCIZkTnypPL6nHPtn1otXmx5f1IZTfJH4u3/qW6rp6t4O+5s40aHLe5sPL5z4lJYLuP9RGfXXmOUTB2+El1P9r6heSayn43Yjsj44BtrMxWAr++twOtNq9ApodNbOQ3UnT7Q9w5xvs6fjYhTQ4TwOqz5RjVRD2/TL0aMwszEyp942dfWnQqfP/LJTELO99A55g0p6XXy5/0EzM0Aj0Z9lxVeaakdd1omkEoTDbSUteV7KYkme9LlSBKdTHdumJuzOfrtx9CMEwLntWTy+rJOr0mDT5oseHeV/fHLGrrl9SOymJ7qNuJe7dFlRlu24+pOQZixmkq6Hb6YNGpBBkWL3/aLrmhJEl9+IK0KHGbSnay2IYuxzRyC0EqzeWsejV2Hu6KSGoEQtCpItncUtlSyWpBU2CIGwMK4pIaJYRGlxqlDJPTmqRppMGBAVkLjQHw590ncGHpBEFp3QNXVqM6Z2R1W6UCZWKBoYpcE1cpk23UgAKw/UBXjIxM6YRI89g0zl609bvR1O1K+t2eDgmaSkbVaGsc0zSDHmcAa7ftF8zPeIRfKr0FxgJStkkKhZn6mBLeshzDeVFOLTbmLyjJROMJe8wcaut3S86hVCVPWPDnkUJOib7PQIhBKETj1X2nBOPygSurUZqth0mjQuVEI9ZcUoa8DB08gRAKLFoUZIyvMZvG+EK8/fIJmxs2tx8quYyrsD3T2bMsYb1++yEu87euIANaFYXCzEiAxBsMi86V7zzXiPVLapGfoUGmXi16vfHWv1TX1bMRpD13NPnK6tJTVKRSl/TspuUYE+o/xfIiDm8Ae07aBWMLACjIOGIYGO7nwZK/vmCk0pX9N/sdtpFivyeQkLRIGskhTQ4TwOqzrd9+SHTAJVr6xs++7HT48Lv/tODWi4qw5eZ6BEI0CjP1mJw1bNCKrXrUFJglCWSp6+YT0TddWIQXPmmLabygUMiSdnJO2Ny4Z9u+pMhQmmZES+1Jm5Jkvw+QSxDZ58DP/GYbC1IU0EkgoBtq82N0mO/Zto9IrodpoLG1H602L1fOwpbp5GdoRiXSKCYNIpZxmgpyTRp8/8sl6HMPZ1h8/8slyJHYUCZL3KaSnVxs1WPTjTNiorwjuRCk0lyu0KLDzRdNRlPPIHddN180WXKjmawW9LE+st5cWbYBJdlG4jGTJxjw6LXTcddLfK3S6elymzTS4KHH6SfOrWKrHg3T8/GDv3wmsAdrt+1HWbYB0wtHJhgnlb0CAMdtLqJfwPoP7Hz+qMVGlJGZWWg55zY65xu6nf6U3m2qjd5SbdhG0wzeberhxvKhTid6Xb4zlol14JSDI4aB4flZnm1AncT8TLZHwlhBzDYVZkoTgvwS3lQIzbMZYmOeYZCyfUxF8gSIte3Tcoyia8367YeQbVTH+J9rt+3Hb2+ciXeP9GJmUQZyzVr8hFc5mG7AlEY8iO2Xdx7pRkuPC3qNUpDBeabHFBtEtOiUsLkCcPtDaOoeRGlO5PoOnHLg4+P9eKmxPWauFFh0uH1+CTa8fQRP3zJHck7GW/9SXVfPRpD23CTy9VCXEz9+aQ8sOhXR7zzR7xbNNmb5pW6nD8Ewg407juDy2nxBtUZNgRmTrQaB5jQLX5BGoUWLlQtLAUSS0vgtTzTKSCPFH182FSo5BbsngOc+bMWKBSUotOjQ6/KjMs+YtoWngTQ5TAB/8vC1bC6rzIFWqcBHx20JR9WiM2E7HT48+OYRvLDiAlw8LSfm+6wzVzrBgJmFFngCoRgCOZHrvmZmATeZSY0X+Doz3U4fAEjeD6vBmigZym4qpAj20/l+Is+B7WJq0akEjQVXLyqNITDlslgpj1abF/kZGkFWVrFVj4+O2zidpE6HT/B8l8zMT/g6TwfJZpymAk8gBHcgHBNN9QRCosckuwlNtdw1EGIE17Xhuukp3aMYUrmu9gEPsfFb+4BH1MFQKGRoqMpDUaYOXU4/ck1q1EhoQWuUcqLenFoprmssk1H4WnUuKvJSy3hJI43zAQUWHXFuHepyiko9dTq8mI6RIYelsldoBlj5/Oew6FTc+iujEOMA0zQDpy8oUr0hbrfTODvgDoRSerepZj2mqlU82plYHQ6yLmWHw4s6ifmZSo8EFqOpUZln1hBtU24C1VKpEppnO8TG/LtHe1K2j6m+8+j58OSyWaJrzfX1haL+52cnB/DUey34zXXT8dMUmoqncf5CbOyyY9MbDGPDv2N7LJ3pMdU+4MG+Dgc2vD3cVHfNpeUoneBGh8MLmgFxrhzuGsSW91sSstfx1r9U19WzEWK2JZp8Pdo9yCU1Prs7QrzOmJSBIqueqENM6j8FAF/f+F6ENwgKuYR7Gyohp6gYzWn2/B0OLzbtbOZ8B7a3LJtAVTrBgCBNQwYKKy8uhS9ER3r2vH0UnQ4fp3GcRmpIk8ME8CcPS/7lmSPGJNHGaixSKeeTySgUZw070fEcEvbv7GQGAIqS1i1ONiOEvQ8xMjT6GhkGRIJ90bRsVOWZY+5HjJAnicuLIfo5sKUGvlAYG3c2cdnUJRMMuP+KKtz76gHu3i+YnMkRyXxh9CyDGsVZQsdaTCdptCQlgOQzTlNBvyfIZZ6zC8cLn7RJNjJLdhOayvwYjeY6qVxXt9NPfF5S0edQiMbbR7rR1OMCzQDNPYPocvrwtao8IkGsVlK47/JKdDh8XAR2olkDlSKxTSkTrw41jTTOU5Bs6ppLy/H6nlP4zoIpRHtg0avilq4nCqnsFZphOEedv0m6aIoVOXo1DnQ50eMKwKRRQKuUEa/1fCglP9dRlEmWCErk3aZCEqYavO12+vF5mw1/WDYLdncQmXol/vzh8TOWiZVlUBOfS5ZeWoc1lR4JQOraz+yxyRKMcorCusurcN9rwz7rusuroEgHeCVBGvNic8ikUeLztn7IKIpYVk/TDPad6oc/EGkQKJdRGPT7UTMxM4EkIaFtf3xnE35xeRV+wXufbJMluyeAZ2+bQ7xGhhnO6ktlXqZxfoKffLXm0jKEaAZHugYxwaiCUi7DYzuacPv8kjEZU/3uAMAweHhpHTz+EFz+EMI0jaPdg8gyqPHansNETeJNO5sTtteA9Pp3Ouvq2Qax6mwZj3x98OoadDt9XObugfYBlGYb4faHMegLYdAXSGissP5DgUXHVTmw373/9YP44y2ziVzKA1dWw+b2I8+sQafDhxc+acOGa6fj99+eKdBfB4ATfS4EwsO8F3sPab3h00OaHCaARAxdW1+QVGM1FqmW87GQInGBSET6s7YB/Pwf+7hMWfYapcit433JEWxS9xEtZ3FtfQHKso0xBDsALCjLIjaDs+iUxO9fNMUqmpnMd7ALLTrud9nnwHYx/dGQns73FkRIuwOnHNCp5HhkaR0oGVCZa8KxPhd+/rVpcAfCgvKJqbkmrsEd/1lE6ySxkh2jlY2pUMhwVV0+yrINkh2STwc0TeP6+sKYBms0Ld5gDUhuE5rK/Eh1w5rMpqzYqidKMUhdVyAcJj6vYFi88dvhbicx2/hwtxPV+Rkx388zqdHa543RPp1oFt8Ep1oanEYa5xvUCplAn1OrlGPJzAI88lbsBuXHl02FyxfCu0d7UGzVn3bmoFT2SpGIbvgEvRqvH+gSaK3+/GvT8MCV1YLPWPmJNM5uTM4ir5dn6t2mqlVMUTQWVeThu899yl3nfVdUgZJJ+w6pItesjgn4339FFXIzpMnhZHsksEg1MzrVtdjmCeCvH7Vy/Qy0KgWe2nUMd15aLnmd7DlHK8P5bABpDq1aWIb/ffMglswsxH2vHyC+m06nG0c63TFjLMugRn6GtK/rDoRi+nf8a38nnrypHh8d7wfDAM992IpOR6SKMxgKxwQD1jZUYtAXxMqFpdCp5CnNyzTOT5ywubF++yH88CtTcGrAj7tfFmpZl2dHxu9ojymaZtAx4EWYgUAiZfWiMqx79SBUCgo/+EopfvtuM7fXri3IwKkBD5bMKsDLn7aj0+FDvzuA3cf6UrZvo72ujiVIjdPvvKQc9UUWXDTFiiy9Goe7BjkepMiqxQ++UiqorvnlVdUosmrRavNyvxs9ViIyoXKsWlQKvUrOaRqz8AVp7G8fwJpLp2LD20e491uRa8Lv3m3G0R4XVi0sw/b9nVhcnYdvbflIkIhXmKmFnKLQ2u8FhYj0hN0TwJpLy1EyQZ/WGz5NpMlhAkiEVTmP7GSRaFStMs+IZ26dk5REBAuxLMnK1fNxsHMQh7ucnIPKF+V++dN2gU5MkVWLB66MRINkVEQDLpn7kcoIbel1ccQwK98QTVQDEeOhlMtEmsRdGPP9IqsWWqU8xuiTHOzNy+o5staglmNtQyUeeP0gOh0+nHJ4cW19AfyhMMIMYhz6SRlarHz+c6y8uBSbhgTQ+dcWTZhzzyLXOKZl+gqFLKEOyakiQ6siZtW88B3pKK1Yl2USUil3FWvMNMEg7sQkuykLhWiEGVpAFIUZGqEQDZWKLOFgUivJWUgSz8ueZHZ2pyNA1FZ89rY5mJRJPsdoZFqnkcbZjgOdDvzkb3tj7MqKBSUCSSW5DCjPNiJI03jgnwe5jsqbbpyBydaItmcqmxSp7BWxIJrdE2sPHnzzMNZcUoaHltbhaPcg5pdmYXZx/Oy2NMY/TrcpVrJIPblBhnVDJBoQGZfrXj2AZ2+bc0au0x9g8MQQgcBKnj3xbjNmTJoteZyYLxGPEElVozLVtbgoUx/ZLP/1c8F1xstsSweGY8HOofwVc7HjcA/CdISYvWZmAUcMA7HvpqPfzxHD7N/vffUAnr11TlxyeLJVj5suLIppqmXWKPHUe7FNz3PNOoQYBpuXzcKgLwQZReHX2w9xa82aS8vxq6ur8f/+sT/JeZnG+Yhupw8NtfloH/Bx+19geP/wyNI6/OqN05d0TBYnbG409bhiromvgfvbd5sjmaSuADL0Kvzi1f3cPFi1sAxbG9vw+ckBbNzRzPEcSjmVlA822uvqWMKqV2NrY5tgrXz+41ZcWpmDkgkG7Dlpx495Wb4Ntfkxa/k9r+zHphtnYuXzn3Fj5cGrayCjImsOAGLTu2d3DwfANEoZHL4wZhZp8PQtc9Bqc+PzkwO4f4i3AYCNO5vw0NI6jphmz3/3y3uJAb7nPmzFhreP4vWV887JdzeaSJPDBJAMBcPTRWGbm8llgFapQChEo83uiYnMizlmyUSjxLIku51+LkuWn3HLbmDri8yYYNRgZqEFwXAYNncQK55rhC9IY9WiUlBIPkoolhHKXuM1Mwu4hUWse6RYpkYwHBZM9iKrFncsLMP1mz+McWpJDvbhTocga7PIqsWG66ZDIaNQnmPA/g4nGCCmtOGxHU2YnKWHL0jDF6ITJszHg45bMiQskHwGiVvkXXmD4lk1oRCNV/Z0xMhdXFWXL0kQJ/Ms5TJy5265RNJ0spuyvacc+CmBKJq4XIv6YjIL6wmKZCFJPK9ks7O7nX5ReyCGVDOt00jjfELnAHmeDPm6goqWlQtL8dR7LdwGxqJToanbJdqgIxFIZa+IbV7+ua+TeM1OfxjO7kE89V4LrpmRn3aUzyGMpu+R6qZZbJ3qkVinTgfHbW602rwCyRX287JccqNWIDVfAoj0YyBnHEtrVIr789JrcaqZbenAMBkyWUQ6YuOO4fEiJsXHvpvuQRHfa1B8TLM+d5+LHEz4WnUuUR6uKFOHyVl67Otw4MApZ8yxG94+ih9fVi6pP59GGixyTBrIZRDtncCAETT1Ks8xoiLXlFQiWyroGpLHI10TmyzTavMiTDPIz9Dipqc/jkm++c1103H/6weRZ9bg+vpCjudI1gcbD3v60QBb+SwW8I1udi9mFwc8Aay8uBS5Jg3a7B48/K8jsHsC2HDddFTmGYlN71YsKMHGHc0CYn9BWRaASD8dvj1mj/OKrLWHedI67Fhg/fGTdg9Kc8TX/TTiI00OiyDaUNA0gw3XTcf67YcEZM62Lzpwx8Iy3PPKfk5SoTzbiIo8E4Bh3V2WUD7c5UR+hhY1+eaEDJZYWR+/BJX/906HD6/v7UB5jgHf/8tujgzmR+ZoBkTy9sGra1KKErLXyDcifKK6Nt+Eshwjpy1Mup9MvRrTCyzYumIuOh0+ZBnU+PZQGQEgdGpJDnZehlDTptXmHcpInoviLAPCNPCpSFdMkzaiwRP9LNl/j8dSrWRJ2FQySPRqsjaRTiRzFohk30V3Wb7nlf0oyzagbtLING5iBfKju9dKCdAnS5B2SWzixCA2V3MkmsYkm52dYyJrK+aYxMtnUy0NTiON8wmZBpWkFhv/M1b7kd3A8BvAAqmRMGznbnYNZAN+rH0mbV7E7AF7zelssjROF6lsmsXGZbbEOsUi2aA3+9uk87F+nRjEfInpk6Sb2Zg0SuL5TBql5PnE9B51Eg1lgdMh6dOBYTGI+UVi/m6yvhdflzrfrCW+h3a7F48PkRrs+Ht8ZyQDvWSCATX5kf4sRHLGG4rRn083YEqDhGKrHrOLMtHY2k8cw3lmbYzfMZIShWJQK2SQU+R5x/ZH0ShlKLLqcVCk2rmpx4VOhw8/vLg0Zi+VDoTFIt5aItbsPvrfKoUc3iCNe3iVa0CE83rm1jnEd1WeY8SqRaUI08DWxjbcMLsQP9r6BeyeAJ5cVk88T66ZbKfDUflTrD8esdlpavN0ceZn/zkCdkJtvGGGwAA11OZzxPCyuUXYvKsFK//6Ob7x+HucdEOeWYNlc4uw5f0WbNzRjOs378b2A11c+r0U2LI+Pnm54brpXAkqS/Ly//7AlTW4m9fJlhSZY6OEy+eVYOXCUqxYUIKZhYk1fhO7RtbIs+h0+LDl/RaU5Ri5DpZi91No0eHdph7sONyD/aecaOl1Ca45z6zB8nklONo9yDnYfLSKOFCsdtzkLD3yLdqY4zRKGfJMkSxjVhg9+trG4+ZajIQ90Okgfl8sg+SEzS16DlabiP88Ihq64rqB0VFH9lxdDnFSNVnkmIQN2CgKUCkoSbKT3QjwIUWQ5ol8X4roFRvbUuMn2ezsmlwT7r+iWnCO+6+oRk2uSfQcBWYt7r8y6pgrq1Fg1ooek0Ya5xs8gRDWNVTFzJOpOcYYG/j3z9oFGxipBrCJgqYZvHWoG9dv/hDf+/NnuH7zbrx1qFvST6jJNeGBqLm9elEZKnJNuGZG/nldPp7G2EFOIWYurWuo4jqOiyEUovHmgU7OD9x5uBtvHuhEKCStVWxUK7B6UVnMPDCqpTeJOpUCdk8AT7zTjE07m/HEO82wewKSAXAAcPgCRN/I6QtIHucUOW7QH5Q8Dhgm6eeWZHH+dDwk6/ecT4j2117b0xEzZvn+bnWukeh7TdCr8MkJG/actGP3sT609LpA04xAl/rkgJf4HjoGvFzGOzv+Wm1ebt2QySgUZJD3Lfzmwul3moYUZDIKF5ZYUZlnirGTv7yqGnZPICm/Y6Tg8AWQqVMRbTfrYz14dQ3kMvE9WWioynIkfLDzBVJrCduYmW8X779CaBfvu6IK//j0JOQy8jP3BELEd9Xl8KI824jKPCN+8tVpeHNfJ8cZ3LNtH9YvqY2xv4/+60jMmrm2oRKv7+2I+X0ZFakEkkqWSiMxpOn1JMCWIpFS7vmSCgAb0RqERikj/i3RiJZYlAcAV2YWXQpCyhbgR174esRPvNM8TNCm2JmTvcbKPCOKrHr8/B/7BFnUDAOuo7vY/bCO1LYvOtBQmw8dL2uVJdf5khHRpVh1BRmSWZsyGYULiq14aEktfjpEnHNEu1WPIqse03KN6Hf7sXXFXGK3Yj7GusmHFAlL0iBOJYOEpE20tbENi6tzRa8rz6xFkVWLhtp8LqvutT0dyDWPnONaaNFx2fr8rOlCi070mGKrHptunBHTXVyMuK0aImHvfXX4HPdfUY1qCRI2leyeZLOztVolLq/ORXGWDt1OP3JMatTkmqDVimcsHep24ol3hNkpT7zThKk5I5fNnUYaZzuMaiU2fdaEDdfWIUgzkFMUNu86BocviD/eUo9AiEG304c+lx8qBYX7r6jCE+9GMrfEsl8S3bDTNIN9HQM43OXE7fNLuEYrUn4CTTPodPkxJUuP526bgz5XAEaNAnkmDSYnSB6lcf5gNH0WhVyOlz9rEzRQe/aDFqxtqJI8LtkGrSzkcgoTMzSCHgETMzRQxGGjaYbGuoYqQROydQ1VYBhpYsSq12Dn4ebI/flD0KkVeOaDFnypVPr+VHI50aeaVVQneVyqON2G2Gc7pMY8669lL78AH7bYUGjVY8Djx0NL69Bmc6PQqsejbx3m/F2dVoWG6pxh38uohisQxC3PfBIjDbbhuunIMaq5ahJ+pSa7NyrM1EGvksdt7KRUULjviipO9zPiiw6vPefbO00jNSgUMlxamYuW3kHU5Jsx6Ashy6CCRadEw6b/jknGrVWvwX2vHcQNswvx8NI6ePwhhGgapdl6TLJUwO0Pocfpw3+O9GJihjam0e4vLq9CMEwLiMN0hWRq4NvKWYUWvMir4v7fNw8K1qzfvtuMX15VA71KLqhKB4YyvTN12LysHo2t/aCZCAdw45wiKGUyTs9Yo4w0wut1BdDp8KHV5kV+hgZbV8zFka5BtA94uSadva4AViwoQWGmDjqVAn98/1iMzV3bUAm3L4iSbEPKXFYaw0iTw0lCrBSJFLV6sbEdD15dI1oWxBJz8Zx2sbI+MdL41FCUmkQG+4I07J4AynIM+Ocd89HrGhnxdZmMQnFWZFLOLMzAZ20D+Pk/9hElDEj30+3044VP2rgJbxmKJj62oymGXG+1RUqxtq6YC28wjGyjBoUWXYwTvOnGGWAYCBraNdRORHW+mUjeJVo6OR6afIiVfoiRsKlIC6RCwk6dYMAPv1IWQ6pOnTBy+j9tdg8xa5otxRNDIMQINp0brpsu+t1Tgz682Ngas7mtL7agRBN/jMTZWw5fE6FzbLzsbK1WiTmTrYmdAOAW3mg9RrFAQhppnI+omWjGdbOLcLh7UODw5pk12N/hxIa3j3Jz9FdX12D/yX401OZDLgMqJ5pjNi6JbthJ6wnbXKPT4SMG8MTWoIumZKVJ4TRiMNo+SyAcxsJpuYIO56sWliEgsa4BkQatJG1WsQatLEwaJWQUUF9kgd0dhEWvhMMbgDGOzIOMovD7XcJGdr/f1YyNN8yQPK4ix4jrZhcJ7u/+K6tRkSMePAYi0gQ3zC6M0Tg+U5lO51OjpWgkMuZlMgrTCzJwwuaOGauPvnUYdy+uENhwjVqJPlcAP/nbHiyfV4It70d050nJP1turuc+Y2X2Vi8qQ5ZBLVgn7ruiCr99t5lrshXtYxvUSuw41Ik/LJuFAU8QmXoVepxe3PONyv/P3pvHt1Wd+f+fo83aLNmWN8WOt8TZvGTBhEAJ0yYtTdsAKeuUDlBKJ9Pvr5B0aDu0DEtZpm1amg4BptO0tAN0IUBattJMaUILTKE0LNlJnJjYOPGS2I5kS5Zk+Z7fH/K90XKv1itbsp/36+VXYln33HPPfc5zznnOc54HNpMeFYUFqCmZGe+UyJwj/Z6IPvHAlYunLPRMk9MWs8b8yXXn4J0uV4yO7Dg1guYqG7Zedw6GPGMosujxP69/gI4BD3509RIEBUFKRD8TN8IyQU5XbrqiFZ9pduLvnYPY3enC7s7IU8l/+2AQtgJtTMz+2z+1APtPuiOc8O5cuwjj46FkyeF68kd/OoKbPzYXv/pbF65qq4bbF0RtiQXFFgPGhFAcbCB00t1pN2E0MI6HdrVjbWsVdBrgF184F5wDlgItxsYFlFgKZsz4lm3IOJwCgsChYcB3PtsiGT5f2HMC969rxoeD3hjj25A3gGU1RZhTZpXdXSkvNGY0aZczsnacGsEdz+2LMDgNeQOoL7XIGoPnlKur/DUaBoFDah8g8U6kIHC4fWNY21ol1VmMBbf+ogYsqCyMGbw6B0YxOjaOFQ2l0mfhk+BKmxEHe4bxmYdei2nXTIPO50KSjyanDT+4shXt/SOSJ+zcciuanPKLqHQ8SDoHvbLx0JbOLlaUm8OnhiXDMCBmdN6P+ZXqeamm4wWd6jvrc/smBsR3Iz6Pd490+nI63tmpkupGAkHMRDQahqZZhSgs0EX0lc+fVyMZhoGQ7vj33+3DzR+bi4dfOYo71y7Cd146iAeuWpzWhusHp2N1k5hc49HXO2Q38HJhDCLyBzkZu/Wp9zD/lpWqzwEBZQ/Zj8yNv6npU0jq6ouT1BUIld895MM3njnrkLBxdSOaZ8WvpzcwLrtxKoYjU6LbNYq7noua5zy3H2218Teoa0osaKywRng4N1Zk19NppiRaiiZZmdfpNFi3uAqN5Vb0uf0osRjAwbGmuTJGh4frXdEhSOk4u8c/HjHv6nH5MDo2LhmGxe/d/fwBfP/KxTjSNxwTcxgIzd3XLa3BvzzxNorNBlx/fm2EMSaTU5/EzEJu3iCecJ4Kj1ux780rt6LH5YfVGDoxKbdB+KOrl+CEy487wwzJG1c34qPzy3Hs1AgenkgMHJ6kcWElJWlMBjm5uG37XhSbDagqkl8/cg64/ePY/nZ3xDjv9gVjjMD3vXgQP1DYhKh1mHHzqrkRRv3vX9GKqrCTQJwDW3a2w6Bj+MbFCwCGSUmYOJMh43CShBt+is2GiDAOtSVmdJ/xSiEV5AZtMZmd6Gl0bm0JaorNcRd5YgI3JY9iOY/jPnfIS1CMJyx22FKrAXPKraovBJTqEK0Eis0GnBr2xzyL2K5dA56Y+DU9Lh+27DyKbf+yIqnBK3wS3HFqJO12TUSuJPkYG4/0hP3OZ1sUv5uOB0nnoHwG8K5Bj6IcpRruAkj9uGs6XtCpvrN07pGOwSZR5lg1EGNIRXuAK20kEMRMIzzB5w+uXAyjXoNiswGXL6tGdbFZYVJrwU0XNsDjG8PNH2vE4llFMBi0KY+xnYPyJ4u0GuWEcrkyBhH5gZKMxRvLMyEwPh5z7DPRiRgAaHBYZMfd+gTjYf+wX9agsKymGPVx+kOFzSgbBitebgEgdOpGrj373PH7n0bDsGp+BRpKrTPOk3eySUXmdTpNUs4L0Xq31mHC/IkkS2Ki7x6XD0a9BsdOjeDey5qlTQSjXoPGcqtsnY70DePhXWfn2eF6PHzufmrYjxt+8RZtChJpITdvEE84R9suJsvjVqfToHV2MVon1oe73u+T7SMC55JhWPzswZ3tuPljc+ELCpJTWfh6densorj6nwihNJ/c3TmImpKqGMcy8WTbFedUSzH7RTasnitblkHLJD0JhHTlkDeAEksBvvHM3oj3+m/b9+KxG5djcbUde7pdEBDKK7Rx9Tw0V9nopMQkQMbhJAk3/IhGS6Neg5c2rIROp5FCKiyZXSQ76bt4YQXGxgUpUZyogIvNetmONOjx4/3eYUUvRCUvRTF5TriSNOo1uGJZleptkqgO4nM57UZcf36tNKkJfxaxXYvNBtx9ySL5uMGFBSl7vSopu0TtmgzpGA7V5mCPK8Y7+/bf7cPcMgtaFSa5qXqQWJQya8fJBJqql2o63rY1xWZZY2e8cBflVvlM06UW+eOc6dwjHYPNZBz7DPeM6XX5UGk3oslpn5RsxMQMR6MDY6nL8qzq2TjxYVcWKiRPeILPn756DN/9bAt63T48uLMdX1rZIKs7NAx49PUO/PKm87Ckuijt/qSkZy+cU4q2uhJZXZALYxCRP6QzlmdCuidi6sus+OFVS/C1p8/OB3541ZKEcxZvICg79noDwbjXVVoNsmGwKq2GuNcV6DSy7anXJtYBM9WTd7LJhsyH691XD/fjyxfNxTeiwlFs2x0Kj/f4G50w6Bh+edN5CAoCyguN4Fw+Lmqi5HKizCjNMRNtShAEID9vEE84v5QjoWdqS+Q3CE0GLYrNBvSEJTcPGY3PfmeyxrfphtJ8clwAet0+aY3aOeDBux+ekUKeRYcsNeo1OLe2RLYso14bk0ugutiEd7uGZHXa/x07DZNei6d3h4zIYpgLWrdODtTKSRLP8CMSLwNk15BXMgyL19761HswT0xgwhEnmXJeiMcHPACUvRRFbyOxzGzuAiZbh6vaqmO8OsRnEdu1x+XDf00c0Y2ue02JBWuaKvHShpV4cv15eGnDyoTGXKUszYnaNRmisxxPRWyjkwqeKz0uv2r3qLAVyGaRjRcfLzrTaSIvVSUZivc+uobOhru4edVc3HRhAx7a1Y6uIa/iNaPBcdln8QXlj4+mc490M4Onk4U8VUTPmE82O7F4djENsLnEhAE11Z+8QAjimp/8NeWfk90fTmo1w0887D3hxoDHH5NMKFp36LUhvb+sJrP+pKRny20FirogF8YgIn9IZyzPBPFEzKOvd+DhXUfx6OsdMfFb5dBoGD7VHDnX+1Rz4o37EkuB7NhbYo5v5N3fKx8Ga3/vcNzrXL5AjE7YsKoRw75A3OuIySMbMh+ud1fOK5cSGQJnwwF97eIFkvGkc2AUAyN+aW5XXxqrt+9f14wX956Qfo+nx5XWi0oJjAkiHKV5Q02JJetrkGSpL7XgPz7bEqNb73nhAK5qq474rlGvQUOpRTJSTtb4Nt2oc1iw6YrWmDZ/ce8JlBcapTXqP8wrx4JKW0QsYDF/lThen9/giJGxTVe0xoyzD+5sh16jgS8oyOq0cQFSzinfWMixMt76m1CXabetwhhbA+BBAFoAP+Ocf0+NcssLM/PUUTIuj42PS16xYhbbeeWFGBgJSPGlqovN8PqDOO3xY9Djj7uDLO7yLNq4En1uPzyBUIBvkWBQwIEeF3pcPjjtJjQ5bSktbMNDAIwqxIcL32nqH/bBGzj7PafdiMuXVYMx4NSIX2rXYrMBK+eVY9g3hgeuXAxLgRa1DktaCeOAyBi70e2q5FEMAAMePwxaDbyBcTjtRowLoSNe4eEOciHJh82kkz0OKcZsksPnC2Jfjwu9bj8qbQVocdphNCqrgJoSC85rKMJjNcul59TreNz4Zql6qabjbdvn9sFu1GN+ZaGUKfy1I/q413QPjeLxNyJDrTz+RicaSi2yWdDF8CzRITXi3aPOYcHD1y7F3m6XFAe6pdqecEGc6nshphkTBtRU2fYvF2ShMjOT6BMPDAw3XdiAAp0GjRVWGPUa/Ne1y+APCmAA3KMBmA0aXDCnLGO9n04c0lwYg4ipYXR0DPt63ehz+1FhK0BLpQ0mU/zEazUlFpxTZ8cvvnAuTg37UVZYAK02/lieCZnIZzqetYqJXYX4YSz63H4pfIw4j9r+djf63PE32R0WI7btPhjjGZ0okV0mZDp3n2kko1dTbdNwuT5w0i07dz1+2iPJk5YBDWUmvPXBgNRfPzrXIXlpOiwF8PqD+MYnF6DUasCsogL0ugL4/b4e2b6dTgJjghCZzHlDIDCOvSddODMagM2ol8YdpfEqvC8Wm3URulXcbJlbZsXtn5oPZ5EZo4Egym0FKCzQYvPViwEAG1c3whMYn5RY7tMJjYbhM81OFJsN2N05iHEhNJ5Fb+gqyQ8AMBZaNwOhk/KijiuzGtHj8qJzYDTinr4xAS7fGF7Yc0LSaaKtpr7UgpNnRjGv3Ipzaoqw6fIWmAt0cI8qb74mCk8ZDAo42OPCSZcPNpMOTpsJs4vN6Bryph1idDozrSwQjDEtgEcAfAJAN4C/M8ae55wfzKRcQeD4YGAkxn0+FU8dJbf9UmsBzoyO4daPN8Ji1EtBuW//1Hz8v39ogCcwHnFsafYVrQgGBQTHeVxj9cGe2NAJH59fjuf3nYw5Kr9ucVVSk8zoEAAbV89VrEN0/F/RAHzdilppYvOz1zrw8LVL8fC1S9HeNyLbtul2VFGJLdq4Eu90nZFCMHxzzfyYOtc6TDhxxoevPb1HipOnlPhB9Fie6qOBs+wmfPkf5uKeFw5I9bv7kiZUFZlkv+/zBfH8vp6Y45OXtjgVDZGBwDiO9o3GXLOofDyu8VL0UlWKMRxOOsejZxUZ8bnzIjOF331JE5xxEqw57aaY2Ejxwl0obQaVWeNvBgWCkXGgN1+9JO7303kvBEGoS3hc7nnlVtjNevzgj4cjjsA9/kYnhrwB3PqJeSgs0KKqyKzKRDLdOKRTPQYRk8/o6Bhe2N8bM15c0lwZ10AcDAo4ftoXEf/03suasWSWAEOWvA4nUz7TDWNRU2KKmedtXN2ImmL5eZRIk9OGW1Y1Tloc//CY6OnM3WciifRqum0qyvXpEb/sHLGx3Ip/nVgj1TpMqCoyy/bXarsJz+49KfXJWodJNsRJeN+ejATGxPRmMvRyIDCOZ/eexCOvtMfEnpcbr6L74sbVc/Ho6x0xfctm0uHEGUTYRO67rBlrmypRUKBDhc1Im+VpotNpcOHcUlQXm9A/7MMVy6pk2zBafuKFhqxzWLDrcB+gEE7H4w/imrYabNvdhY2rG2EznbWB1TpCNo7/79fvRLzr5lmxIdwShaeU0/W3fmIenHajFO84+pqZznSbVSwHcJRz3sE5DwB4EsBlmRZ6fMCDm3/9ruR5ePOquVh/UQMWOZPPhKl0nGNcAG7+9btw+calTgEAgXGO055ATDiGf9u+NxQf8bl9McfaNl3RKiVbkzuqv/fk2biK4ud3PLsfB3pcSbdDeLlP7Y49yiFnMBef/aq2ammQEO9/86/fRbm1QDHsRCZoNAwCR0RsXg7E1Pmbaxbitu17sba1Sqrf5cuUQ2HkAuMCJMMwEKrfPS8cgJIDwb4el+zxyX1x3n0616RKOsejz3jGZJ/9jGdM8ZpUw11oNbFysnF1I+KFFEwnRMZktDFBEPERTzxsW78C3/r0wphxMvx42+aXj6DH7cewT1nfpMpkhJYh8p99vW758aLXHfe6vSddkhFKuu65/dh7cnqMM+mGsRgLCrKJ7BJ5Yobri5/80zJsW78iq4ba8JjoYj1TmbvPVOLp1UzbtKXShnsvjZxT/se6FnxvxyGpzLWtVYr9NbpPxvuuSLpyThCTiSjb4WtqQHm8iu6LcraF//hsCw71DMfo6zufC5VHc6jMSacN4617jw94sLfbhY5TI7Lr6bnlVmzb3YW1rVWoLTFH2MDWtlbFrPPvfE5ePydae8vp+s0vH0F7/0jO2nimmunmmlYFIDxYYTeA88K/wBhbD2A9ANTU1CRVaHhc3HDPwwvmOFBXmtzum5I7/t8+GIBvTABjiNhV8QXPCmw4Yj06B0bxxJuRx+SrikIeu/FCTsh+7vIl5eUZXW6Py4fH3+jEYzcuBwdX3K0Tnz1650i8v1L8XDUyr0fX2RMYx/a3uyPaTVQQ4e8g+n2oWadkiSer/cPybXZqxCebfbzX7Zf9frzjk+lckyrpHHPqiSPfixWuSTXchSjb0WEoltYUKfb5dEJkTEYbZ5t0dCpBTDaJ5FQ88fDCnpOyfVI8du4bCyVB6XH5pAzbBKEW8eS0L83xQmnuJx4DzXfSPS7do9CePUmMv6mckMqUHoU5crJz92yQ7+N+pm1qMulxSXMl6krNUsiI0UAw4vi00jqiz+2P+Vu874pQOKH0yHdZzTfE8SYZmQZi+6K4/vrp9W044x2T+tYHpz15v16KRz7Kabx1L+eAwAG3P9bu8vgbnbjhgjp87/JWDHgC0nUiSrIjp58Trb2VdL3AoXjNTGe6GYcTwjnfCmArALS1tfEEXwegXmZwueMc4Umsou+hZfKu+GJ8xHBjtVGvwRXLquLW16nwudLR+miUMp2WFRYk7EwaDUOdQz4LaXS8R/FzNTKvK9U53MgvhscQ7yt+N1t1SpZ4spqqTFbaCmS/Hy9gfzrXpEOqx5yU5CWRHKca7kIuDEW895+OnpisNs4m6ehUgphskpXTCoU+ycOyYmsYkh43CSIV4o/76Y0XSnO/Ctv0keF0jkun256TTbpznmyS7+O+Gm1qMumxvN4h/b7nwzOyZcrJl5axpL8bDoUTSp18l9V8wxnHriEn03J9ccgbgM2ow8rGMgChvqVkE8k1fZ0u+Sinida92ol9K7n1tDcQhF6rwSKnDQd73EnpQzn9nKgOSro+ek9tsm08ucx0CytxAkC46ad64rOMyGZmcLFsMSi3eI8X9pzA3HKrbNiGJqctbn2U6tsyy57S0Xq120Hp+kTPkwnR93xhz4mYNmiptse8A7nsp7mUDT7Vd9HitMccgbv30ma0xHn36VwzGaQaIiId0pH1dK7J1TYmiJmK3HHhjasb8dt3umHUh2KVza8ozFp8UYJQQk427720GS2VtvjXzbLj3suirrusGa2zZrYMN1VaZduzqTK3DG+TMeeZaWSjTaPLfGHPCcX+Gt0n432XIPIJUbaj7RpKMp1MX2xy2jCvojBmXX7fZdRHppJ46946hwUt1XY4LIaY93brJ+ZhbrkVrbNCSdsLjVrcfUlTXH2opJ8Trb3l5OvWT8xDY7k1Z208Uw3jPC82J5KCMaYDcATAaoSMwn8HcC3n/IDc99va2vju3buTKlvMhJiNozxi2YMeP/RaDbyBcVTYjKgpNqP7jBd9bj+8gSBqSiyoLw3dN1F9lP4uZgRN5mh9NtpB6frJaF+x7JqJDJXR2Taj34HTbsS4AJwaybhOGT+InKym2mY+XxD7elxns5w77QmTnqVzzWSQqRwnQzoymc41OdTGWZFTqXDGcM1P/ppymdv+5QK6TqXr8qGO4nVx5iZZlVMglPhrf68bp0b8KLUWgHOOM94xFBp1sJv1mF8eP6s9QUyQkazKyeno6Bj29brPjhcK2d+jEbPHi5m5W2fZs5aMLp/wjPpxoHdEas+mSissptzzRMvynEd1Oc0HstGm0WXOLTVHyFd4f43ukwsqzDjY60m5b88gsj72E+ogyrZrNIBCox6nhv0oK1SW6WT6YjAo4HC/G4OeMYz4giizGtCUm31kRslpvHWvIHB0DXowMBKALzgOj38cZoMW1gIdFlXapDmIIHB8OORBn8uP0x4/quwmzC8vxOFTw0np50Rr72BQwMEeF3pcfliNWsyymzBbxhY0w0L0KD7s1Ft5VIRzHmSM3QzgfwFoAfxcyTCcKtk8yhOv7LpSq2yM00T1Ufp7pnHSMm0Hpesnu33l7qV0f7kYvrlAqm1mNOpwbtgRuGxdMxlMRry/dGQynWtytY0JYqZiMumpTxI5SfRR9mQxGLRoqyvJQo3yG4upAMvrc88YHM1kxjieKWSjTeXKVJIvuT65vJ6ONRP5T6rjTTJ9UafToGlWUeaVI1Ql3rpXo2ETdqzEZdQ6rKh1RJaRrH5OtPbW6TRonV0ckyeEQvTIM62MwwDAOX8JwEtTXQ+CIAiCIAiCIAiCIAiCIIhchs5FEgRBEARBEARBEARBEARBzECmVczhVGGMnQLQqfDnUgCnJ7E6SlA9cqsOQOr1OM05X5PJDRPIaqrkSjtGQ/VKDbXrlW05nep2nMr7z+RnV/v+2ZTTqW6nVMmn+s7EumYkqzmuT8OhusiTL3XJppymS660XS7UIxfqAEx9PSZrLTXVzylHLtYJoHrJkWtr/mSZ6ndJa7TJRVFOZ7RxOB6Msd2c8zaqR+7UIxfqkEv1SJdcrT/VKzVytV5KTHV9p/L+M/nZc+H+yZIv9RTJp/pSXdUll+pIdZGH6pI+uVLfXKhHLtQhl+qRbXLxOXOxTgDVazox1W1Ga7TckVcKK0EQBEEQBEEQBEEQBEEQBDEDIeMwQRAEQRAEQRAEQRAEQRDEDISMw8psneoKTED1OEsu1AHInXqkS67Wn+qVGrlaLyWmur5Tef+Z/Oy5cP9kyZd6iuRTfamu6pJLdaS6yEN1SZ9cqW8u1CMX6gDkTj2yTS4+Zy7WCaB6TSemus1ojZYjUMxhgiAIgiAIgiAIgiAIgiCIGQh5DhMEQRAEQRAEQRAEQRAEQcxAdGoVxBgrA/DPAOrCy+Wcf1GtexAEQRAEQRAEQRAEQRAEQRDqoJpxGMBzAF4D8CcA4yqWSxAEQRAEQRAEQRAEQRAEQaiMajGHGWPvcc6XqFIYQRAEQRAEQRAEQRAEQRAEkVXUjDn8ImPs0yqWRxAEQRAEQRAEQRAEQRAEQWQJNT2HhwFYAAQAjE18zDnnNlVuQBAEQRAEQRAEQRAEQRAEQaiGasZhgiAIgiAIgiAIgiAIgiAIIn9QMyEdGGOXArho4tc/c85fVLN8giAIgiAIgiAIgiAIgiAIQh3UDCvxPQDnAvjVxEefA7Cbc/4tVW5AEARBEARBEARBEARBEARBqIaaxuG9AJZwzoWJ37UA3uWct6pyA4IgCIIgCIIgCIIgCIIgCEI1NCqXVxT2f7vKZRMEQRAEQRAEQRAEQRAEQRAqoWbM4e8CeJcx9goAhlDs4W+qWD5BEARBEARBEARBEARBEAShEqqFlQAAxpgTobjDAPAW57xXtcIJgiAIgiAIgiAIgiAIgiAI1cjYOMwYW8A5f58xtkzu75zzdzK6AUEQBEEQBEEQBEEQBEEQBKE6ahiHt3LO10+Ek4iGc85XZXQDgiAIgiAIgiAIgiAIgiAIQnVUCyvBGDNyzn2JPiMIgiAIgiAIgiAIgiAIgiCmHo2KZf01yc8IgiAIgiAIgiAIgiAIgiCIKUaXaQGMsUoAVQBMjLGlANjEn2wAzJmWTxAEQRAEQRAEQRAEQRAEQahPxsZhAJ8E8AUA1QA2h30+DOB2FconCIIgCIIgCIIgCIIgCIIgVEbNmMNXcM63q1IYQRAEQRAEQRAEQRAEQRAEkVVUMw4DAGPsMwCaABjFzzjn96p2A4IgCIIgCIIgCIIgCIIgCEIVVEtIxxj7bwDXALgFobjDVwGoVat8giAIgiAIgiAIgiAIgiAIQj1UMw4DuIBzfj2AIc75PQDOBzBPxfJVZ82aNRwA/dBPtn8yhmSVfibhJ2NITulnEn4yhuSUfibpJyNITulnkn4yguSUfibpJ2NIVulnEn4yhuSUfibhRxE1jcOjE/96GWOzAIwBcKpYvuqcPn16qqtAEElBskrkAySnRD5AckrkAySnRD5AckrkCySrRD5AckpMJToVy3qRMVYE4AcA3kHIKv0zFcsnCIIgCIIgCIIgCIIgCIIgVEJN4/D3Oed+ANsZYy8ilJTOp2L5BEEQBEEQBEEQBEEQBEEQhEqoaRx+A8AyAJgwEvsZY++InxHEVCIIHMcHPOhz+1BhM6LOYYFGw6a6WgQxKZD8ZwdqV4Ig8gHSVQQhD/WNmQ29fyIfIbklskXGxmHGWCWAKgAmxthSAKJk2gCYMy2fiISUQeoIAseOA7249an34BsTYNRrsPnqJVjTVEltlwOQTGcXkv/skG/tSv2MIGYm+aarCCKabI1f1DdmNsm8f5o7EbmGnNx+57MtWFZThJoSkk8iM9RISPdJAA8AqAbww7CfWwHcrkL5xASiMvj0ltfwuZ/+DZ/e8hp2HOiFIMRNOjjjOT7gkRQoAPjGBNz61Hs4PuCZ4poRJNPZh+Q/O+RTu1I/I4iZywen5XXVB6dzT1cRRDTZHL/yaRwn1CfR+6e5E5GLyMnt7b/bh9++e4Lkk8iYjD2HOeePAXiMMXYF53y7CnUiFFAaxBZsWImGMusU106eXNhx7XP7pDYT8Y0J6B/25Wy75QrZfn/5KNP5Bsl/dlBq184BT855llA/S54rP38Dek4Nyf7NWVaMZ3712CTXiCAyo3PQI6urugY9mFNO/Z/IbbI5ftH8aGaTaB5HcyciF1GSW51Gg/d73TDqNahzWHJuLULkB2rGHK5mjNkADAP4KUKxhr/JOf+jiveY0eTbJCZXjmtV2Iww6jURbWfUa1BeaJy0OuQjk/H+8k2m8xGS/+yg1K7vfngGo2NCTh1LpX6WPD2nhjD7ym/J/u3DZ747ybUhiMyxFuhkdZW1QM0lAEFkh2yOX+WF8uN4mZXmRzOBRPO4skIDzZ2InENJbueWW6fc5kLkP2qElRD5IufcDeBiAA4A1wH4norlz3hEZRBOLht5cuW4Vp3Dgs1XL5HaTlSYdQ7LpNYj35iM95dvMp2PkPxnB7l23bCqEU/v7s65Y6nUzwhi5mI2aLFxdWOErtq4uhEmg3aKa0YQicnm+KXVQLZvaNVcHRM5S6J5nEGrobkTkXPIye2daxdh045DU25zIfIfNd0GxG2JTwN4nHN+gDFGWxUqIiqD6F2hXDXy5Iq3mkbDsKapEgs2rET/sA/lhZRQIBkm4/3lm0znIyT/2UFsV8eNy/Ha0dPgHHjizU70uHwAkFOeJdTPCGLmMuwL4vE3OnHThQ1gDOAcePyNTiyZXTTVVSOIhGRz/Opx+WT7xtKaItSV5sb4TWSPRPM4b2Cc5k5EziHK7fxbVuJQrxtH+oYx7BtD58BoxPfIy51IBzWNw28zxv4IoB7AtxhjhQCEBNcQKZBvRp5cOs6u0TA0lFlJQabAZLy/fJPpfIXkPztoNAxlhQX42WsdOaHnlKB+RhAzlwqbEUPeAB555aj0mVGvQYUtd3QUQSiRzfFLqW/k0vhNZJd487gKmxHn1Tto7kTkHBoNw5xyK+pLLVjktOHUiD9nbC5EfqPmwZmbAHwTwLmccy8AA4AbVSyfwFkjz4qGUjSUWXN6gKLj7PnNZL2/fJJpgogmX/Qc9TOCmJnki44iCCWyNX5R3yCA+HJAcycilxHl89zaEtJlhCqo5jnMORcAvBP2+wCAgWSuZYwVAfgZgGYAHMAXARwGsA1AHYDjAK7mnA9NhKp4EKHwFV4AX+CcvzNRzg0A7pgo9n7OOaUVn0LIWy2/ofdHEImhfkIQRC5DOoog5KG+QQAkB0T+QzJMqEWupCp+EMAOzvmVjDEDADOA2wHs5Jx/jzH2TYS8km8D8CkAjRM/5wH4MYDzGGMlAO4G0IaQgfltxtjznPOhyX8cQoSOs+c39P4IIjHUTwiCyGVIRxGEPNQ3CIDkgMh/SIYJNcjYOMwY03HOgxlcbwdwEYAvAADnPAAgwBi7DMBHJ772GIA/I2QcvgyhhHccwJuMsSLGmHPiuy9zzgcnyn0ZwBoAv0m3bgRBEARBEABw5PD7+MjFl8Z87iwrxjO/ooNKBEEQBEEQBEHkJ2p4Dr8FYFkG19cDOAXgF4yxxQDeBrARQAXnvGfiO70AKib+XwXgw7Druyc+U/qcIAiCIAgiI4Jcg9lXfivm8w+f+e4U1IYgCIIgCIIgCEId1EhIl2kwEx1CxuUfc86XAvAgFEJCYsJLmGd4HwAAY2w9Y2w3Y2z3qVOn1CiSILICySqRD5CcEvkAySmRD5CcEvkAySmRL5CsEvkAySmRK6hhHC5jjN2q9JPE9d0Aujnnf5v4/RmEjMV9E+EiMPFv/8TfTwCYHXZ99cRnSp9HwDnfyjlv45y3lZWVpfKcBDGpkKwS+QDJKZEPkJwS+QDJKZEPkJwS+QLJKpEPkJwSuYIaxmEtACuAQoWfuHDOewF8yBibP/HRagAHATwP4IaJz24A8NzE/58HcD0LsQKAayL8xP8CuJgxVswYKwZw8cRnBEEQBEEQBEEQBEEQBEEQRBRqxBzu4Zzfm2EZtwD4FWPMAKADwI0IGa6fYozdBKATwNUT330JwKcBHAXgnfguOOeDjLH7APx94nv3isnpCIIgCIIgCIIgCIIgCIIgiEjUMA4rxhxmjH2Ec/5/iQrgnL8HoE3mT6tlvssBfEWhnJ8D+Hmi+xEEQRAEQRAEQRAEQRAEQcx01DAOf5Ix9jkAVQB2cM73M8bWArgdgAnAUhXuQRAEQRAEQRAEQRAEQRAEQaiIGsbh7yOUCO4tAFsYYycR8gL+Juf8WRXKJwiCIAiCIAiCIAiCIAiCIFRGDePwuQBaOOcCY8wIoBfAHM75gAplTymCwHF8wIM+tw8VNiPqHBZoNIpRNIgEUHsSRCyp9gvqR0QmCALHB6c96Bz0wGLQocJWgJoSkiGCmM4EgwIO9LjQ4/LBaTehyWmDTqdGTmqCyD1I3onJgmSNyEXC14pmgw6B8XE4LAW0ZiQSooZx2M85FwCAc+5jjHVMF8PwjgO9uPWp9+AbE2DUa7D56iVY01RJnSoNqD0JIpZU+wX1IyIT5ORn4+pGNFZYsWp+BckQQUxDgkEBz+45gTue3S/1+/vXNWPd4ioyYhDTDpJ3YrIgWSNyEbm5/oZVjdi2uwu3rVlIa0YiLmporgWMsb0TP/vCft/HGNurQvlTwvEBj9SpAMA3JuDWp97D8QHPFNcsP6H2JIhYUu0X1I+ITJCTnwd3tmNvt4tkiCCmKQd6XJLxAgj1+zue3Y8DPa4prhlBqA/JOzFZkKwRuYjcXH/Lrnasba2iNSOREDWMwwsBXDLxszbs97UT/+YlfW6f1KlEfGMC+od9U1Sj/IbakyBiSbVfUD8iMkFJfgQOkiGCmKb0uOT7fa+L+jwx/SB5JyYLkjUiF1Ga6zNGa0YiMRmHleCcd6pRkVyjwmaEUa+J6FxGvQblhcYprFX+Qu1JELGk2i+oHxGZoCQ/GgaSIYKYpjjtJtl+X2mnPk9MP0jeicmCZI3IRZTm+pzTmpFITMaew4yxYcaYO+xnOPxfNSo5FdQ5LNh89RIY9aEmEmN71jksU1yz/ITakyBiSbVfUD8iMkFOfjaubkRrtZ1kiCCmKU1OG+5f1xzR7+9f14wmp32Ka0YQ6kPyTkwWJGtELiI319+wqhEv7j1Ba0YiIWokpNsJoBLAbwE8yTnvUqHMKUejYVjTVIkFG1aif9iH8kIjZXjMAGpPgogl1X5B/YjIBFF+5t+yEl2DHpgNOlTYClBTQjJEENMVnU6DdYur0FhuRa/Lh0q7EU1OOyVMIqYlJO/EZEGyRuQi4WvFPrcPZoMWY+MC1jRX0pqRSIgaYSXWMcbsAC4H8FPGmBHANoQMxYOZlj+VaDQMDWVWNJRZp7oq0wJqT4KIJdV+Qf2IyASNhmFOuRVzykl+CGKmoNNpsHh2MRbPnuqaEET2IXknJguSNSIXobUikS6qbG1xzl2c818A+BSAnwC4F8AX1CibIAiCIAiCIAiCIAiCIAiCUB81wkqAMXYBgM8BWAngdQCf5Zy/pkbZBEEQBEEQBEEQBEEQBEEQhPpkbBxmjB0HcAbAkwDWAwhOfL4MADjn72R6D4IgCIIgCIIgCIIgCIIgCEJd1PAcPg6AA/gkgIsBhEe55gBWqXAPgiAIgiAIgiAIgiAIgiAIQkXUSEj3URXqQRAEQRAEQRAEQRAEQRAEQUwiqiSkIwiCIAiCIAiCIAiCIAiCIPILMg4TBEEQBEEQBEEQBEEQBEHMQMg4TBAEQRAEQRAEQRAEQRAEMQNRzTjMGNuZzGcEQRAEQRAEQRAEQRAEQRDE1JNxQjrGmBGAGUApY6wYAJv4kw1AVablEwRBEARBEARBEARBEARBEOqTsXEYwL8A+CqAWQDexlnjsBvAwyqUn3cIAsfxAQ/63D5U2Iyoc1ig0bDEFxIEMeMgfUFEQzJBEIQcpBsIIgT1BWK6QLJMZALJD6EmGRuHOecPAniQMXYL5/whFeqU1wgCx44Dvbj1qffgGxNg1Guw+eolWNNUmZMdlRQKEQ+Sj+ySb/piJjDVMk8yQRCEHILAsetwH/Z2uyBwQMuAlmo7Vs2vIN1AzCiix8lahwn3XdYCvZbRXJXIK4JBAX/tGMDuzkEIHHhhzwnctmYhzfmIpEhmzTDV6xoiv1DDc1iklzFWyDkfZozdAWAZgPs55++oeI+cQamjHR/wYNOOQ7jpwgYwBlgLtOgc8ODPR/pR57DkTIcUBI6uQQ/e6TqD23+3b9oYIWaSAsz2s5KRKnWCQQEHelzocfngtJvQ5LRBp1MO7X58wCO1LwD4xgTc+tR7WLBhJRrKrKrcg0ieXJD5rkEP3u9140srGwAA29/uxqYdh1BlN2LAG4DFoEOFrQA1Jcr9PVw3OO1GjAtA//D014kEMZ3pGvSg1+WL+KzX5UPXoAd1pfLjhQiNG8R0Qpw7FZsNuP78WpTbCiTjmpYB8yts+PiCchgM2qmuKkEoIggcv9/fg80vH8ba1ipoNcC3L2mCe9SflF4nCNHutHF1I6qLzRAEAQzAX470o9ZhQU2xGX881Bexrvn+Fa2oKjLB5RtDbYkF9aW0LiDOoqZx+E7O+dOMsQsBfBzADwD8GMB5Kt4jJ4hnQBjw+HFNWw227GqXJi0P7mzPKeOaWP/3e93Y+mpHSoapXCYXDDuTxWQ8azqGy5lMMCjg2T0ncMez+6V3cv+6ZqxbXKW4CO9z+6T2FfGNCegf9sm2cTr3IJJnqmVeEDje6Toj6WWjXoNvrVkAX1DANT99U/ps4+pGNFZYZT0Gw3VDro5BBEGkzqAngGFfMEI/bFzdiEFPAHWlytfRuEFMN/rcPhSbDbhuRS20DOh3+2P6xVudA1hRX0oyTuQsxwc82PzyYcluIMrvnWsX4eBJd1wnAIIAgAGPH1+8oB7esXE88Mf3Y2Rp0xWt2Pzy4Yh1zb9t34v1FzVgy86jtC4gYlBzxByf+PczALZyzn8PwKBi+TmDkgHh+IAHBq1G6pSXL6uWFuXR35tKxPoLPFQnp92Ir3xsLm5eNRdfWtmAQY8/rXIFgaPj1AjeOHYaHadGIAhc5ZrHJ957mW6Ee6iL723TjkOqPms8w2U8ploOpooDPS5p8Q2E2uqOZ/fjQI9L8ZoKmxFGfaQaNuo1KC80qnYPInnSlXm1OD7gkU5yiPce8Abwoz8difjswZ3tCAY53ug4jV3v9+FY/9l+Fq4Hc3UMIggidbyB8Zj+/ODOdngD43GvO9DjwkO72iPmCw/taqdxg8hbKmxGXNVWjS272uEsMsv2i7Fxjj3dZ2bMHJTIP/rcPqxtrZLsBkBIfu978SA6B700VyMSYtBqMOAN4MGd7bKydNv2vfj6xQvgtJ9dV/rGBIhqkdYFRDRqeg6fYIz9BMAnAGxijBVAXeNzzhDPgMAnDK4AwBgUvzeVnpfh9a91mGJ2mRrLrVgm8JR2kHLBazdVL8x8JtxDXWzvDasaMejxq/asouEyvE3jGS6B3JCDqaLHJS9/vS4fFs+Wv6bOYcHmq5fEtFedw6LaPYjkSUfm1UROhwlcfhwZCQTxVZl+Fl5Gro5BBEGkzog/KNufPf5g3OvizRcIIh+pc1gwr7wQvjEBXoV+8XbXGfzstY4ZMwcl8o8KmxGmqDknEJLfCptR1TUdMT3xBsaldUKBTl6W2vuHcd2KWjzxZid6XD4Y9RpwHvkdWhcQImoab68G8L8APsk5PwOgBMA3VCw/Z4jn7Rf9t1S8AicLsY7b3+7GbWsWyu4ypbqDlAteu6l6YeYz4R7qQKi9t+xqh16rXpcWDZdimyYyXAK5IQdThdNukpW/Sruy/Gk0DGuaKvHShpV4cv15eGnDyriLmHTuQSRPOjKvJnI6TMvkx5GuQa9sP8uHMYggiNRxWA2y/bnEEv+Qns1okJ0vFBqn5eE+Ygag0TAsdNpg1Gtw2uOX7Reis85MmYMS+Uedw4JltcWy8mvQalRd0xHTkwqbUVon1JdaZGVpXAC27GrH5cuqpbA7v32nO+I7tC4gRFTTOpxzL4B+ABdOfBQE0K5W+blEPANC+N+2v92Njasbp8zQoIRYxyFvAEf7R1Q5Rj3Vx7GBqTfsTCbewLhseyc6XpoKqRougdyQg6miyWnD/euaI+Tv/nXNaHLa416n0TA0lFmxoqEUDWXWuO2b7j2I5EhH5tVEToe1VNvxw6siP7tz7SI8vbs74lqxn+XDGEQQROpwDmxYFdmfN6xqBBKop0BQkB2Xx8YFhSsIIvepLw2NdU/t/hB3rV0U0y9E48dMmYMS+YdGw6Bl8nq9+4xX1TUdMT2pc1jQUm3HxtWN6DnjlZWl377TDd+YgJYqG352QxssBi2GvAHpO7QuIMJRLawEY+xuAG0A5gP4BQA9gF8C+Iha98gVRAPCgg0r0T/sQ3lhZAb48L9V2oy4eFElTo3Efi8X6n9qxK/KMeqpPo4NJH4v0wml9q6wqdveouEy2aMmuSAHU4VOp8G6xVVoLLei1+VDpd2IJqdd1WQok3GPmU6qMq/2veV0GAAsqFyJrkEPLAU6vNc1JE3sRMR+Fl1GLo5BBEGkTqm1ANt2d+GmCxvAWMhYvG13F9Y0V8a9rtI+OfMFgphMpLGushBDngDWX9SAqiITTpwZlY5PAzNnDkrkJ2WFRlm9ftmSKtLRREI0GoZV8yswt8yK/mE/vvHMHvzgysVo7x/GuICIUBLzKgpR57CgusiE+ZU2eANB1JRYUF9K6wLiLGrGHP4sgKUA3gEAzvlJxlihiuXnFPEMCHJ/m1OujqFBEDiOD3jQ5/ahwpb+Ql+sY6oxT5VQq5xUiW6PmmIzAETE0pmOpNPeasmO2vUKBgUc6HGhx+WD025Ck9OWt8ZOnU6DxbOLsxr/dzLuMVMJBMax96QLvW4fnDYjWmbZYTBoJ7UOSmPLnHIr5pRbIQgcbt8YNq5ulJLwRPezbI5BBEFMDXUOC+69rAnDo+Pw+IOwGHVYXt+UcJ41VfMzgkiWdMdecawTHBx9w35s2nEI17TVkFcckTfUOSy4bc3CCP28cXUjGiusinKbC3NVIrcQeCjPyK2fmI8H/vi+lGeg2GzA7Z+ajwVOG46f9oDz0KmLulJaExDyqGkcDnDOOWOMAwBjjEZilclGsi+1vG2nwms3uj1qHSbcsqoRdzy7X/VkaJNhWE2FVNt7shLFpVqvYFDAs3tORLyz+9c1Y93iqrw1EGebXJPF6UIgMI5n957EXc+dlcV7L2vGutZZOTXpDvcSWFZTnPHOP8kTQeQHwaCAPncgRkcFg0JcHaXRMFy8sALb1q+I2ISlfk7kAmqMveFexIMeP7atXwFvYFxxTKNxj8gVRNlduGElTrpGMewLYlaRCYsq5XV0vsxViclBzhZy32UtMBk0eObL56NzwIuuQS/WP/G27PqfdCERjZrG4acYYz8BUMQY+2cAXwTwUxXLz0nETjXg8cOg1cSdjERfk2pHVEr2tWDDyrhHoBPdT6Nh0u5knzt0DCsV5SAIHF2DHvS5/fAEgqgtsaiqXJTqH90ea1urJCMjkHz7JHN/OcPqxQsr0DXknTKFmsrx92zJTqb1OtDjwkO72qXjVADw0K52NJZbsXh2ccLrU2EyPJSzPcgKAscf9vfia0+flcUfXrUEn2qmTNyZsvekC4+8EimLj7zSjoZSC9rqSgCE2v+D0x6cdHlRoNXC7RuDzaRHeWEBakomr/9rNAx1pdaMd/4na9OIIIjMSUZHySEIHH881Ef9nMhJ9p50SYYuIDQ/feSVdtQ5zOhz+1FhK4CWAcWWgrhzqmTnnjTu5R5koAIO9Q4nJZPpjgPJQO8h/+ga9OD9Xje+tLIB1gItbEYdBM4xMBJAkVmPE0Ne6ZQhcHb9P/+WlagvtcTowk1XtGJWkRGOBPqWmL6oYhxmjDEA2wAsAOBGKO7wXZzzl9UoP1cRJxibdhzCFy+ox4A3AIGHssu3VNuxan6F7G51uobGeMm+lCZDwaCA3+/vwW3b96LYbMBVbdWYV16IhU6b5GkWXiel78Rrg12H+9DeNxJzxFktj12lSVx0ezCGlNsn3n3FAdJs0MYYVjftOISxcQG3bd+bF5PLPrcPxWYDLl9WLU0mtr/dHbdt0p1ApzK5GPL6paMv4j02rGqMiaeaKZPhoTwZC46OUyOSYRgIyeLXnn4P8ysuxNwK5Sg+NOFLzKA3ICuLAx4/AoFx6HQa7Hy/D0f7R1BqLUD3kBdP7e7GkDeAWz8xD/WlFqxeEKvzc5l0N40Igph8hrwBXLu8Fj/60xFJR/3rx+fhzGj88ZL6OZHL9EbN5Z12I65pq8H1P38rYr62t9uFrjIrzq2xw2IqSPt+1B9yCzLWpyaT6Y4DiaD3kH8EgwLe6TqD5947gavOmY2qIhNG/OP48i/PegnfuXYRis0GKQY7EJKvI31uAIiRu9u278VNFzbg0dc76P3PUFSxinDOOYCXOOcvc86/wTn/eqqGYcaYljH2LmPsxYnf6xljf2OMHWWMbWOMGSY+L5j4/ejE3+vCyvjWxOeHGWOfVOPZ4iEq8388twbesXFsfbUDD+86ip+82oH2vhF0DXoUr4k2NP5+fw8+veU1fO6nf8Ont7yGHQd6IQiRgXPFZF/hxEu0IAgcf+0YkAzD162oxdZXO3Dzb97FZx46ew+xTvG+E68N9na7ZHeljg/EPn+qKA2Yxwc8iu0R/XuqiSjEAVJ8Hzvf748xOq9trZIMw9H1ykUqbUZcf34tHn09JKM/e60D159fi4o4bROv7ZWIbjslWRYxG/SSMU68x5Zd7TAb1DzUEPJQjvYqv+PZ/TjQ41LtHum0V6p8MOCR3QBR853MVIpM8rJo0mux96QLnQMeHO0PbYJ945m9+MmrHbhuRS2KzQZsfvkI9p1woePUyBQ/RWrE23AkCCK3KDLpJYMAEOqrP/rTEdiN+rjXUT8nchln1Fz+8mXVMWPxHc/ux2nPGL78y7fxh4On4M3AEEb9IbeYjLlzrpOKTKY7DiSC3kN+Idp4Htx5BNe01eDhV47i/d4R3PPCgYh3eN+LB3FVW3XEtUa9BgadFl2D8mtK0dmO3v/MRM0z1e8wxs7N4PqNAA6F/b4JwI8453MBDAG4aeLzmwAMTXz+o4nvgTG2CMA/AmgCsAbAfzHGshp8R1Tm1cXmGOPogzvb0ef2K14TztrWKmx++TBuurABN6+aiy+tbMCmHYdiOqSYVEScRCVKtHB8wIPdnYPwjQmyky2x04t1ivedeG0gcGWP3UyJN2BGt8cLe07g/nXNSbePEtEDpMBjjc5aTfaeORsM+8ZkZXTYN6Z4TToT6FQnF6dH/LL3OD0S23cyoccl/yy9LvXe12QsOEx6rewGiFGvrOpowpccrtEx2fd3sGcYfW4fTrpGY/rQll3tuHxZNXxjAgQeMt6ngyBwdJwawRvHTqPj1MikGe5T3XAkCGLqOO0JyOqoAU98Qxn1cyKXaZllx72XnZ27K82vRYPFHc/uw/7eYelvqY6f1B9yCzLWJy+TgsDTHgcSQe8hvxBtPGtbqyTbjdIJ6poSc4Rt5F8/Pg/3vngAlgKdrNxxfvZaev8zDzXd884D8HnGWCcADwCGkFNxa6ILGWPVAD4D4D8A3DoRpmIVgGsnvvIYgG8D+DGAyyb+DwDPAHh44vuXAXiSc+4H8AFj7CiA5QDeUOXpZBCVudcflO2M3kBQ8Zrw79uNWtnjzIMef8RxklSTfYmGW6NeEzfkglindMIyVNiM0DLEPJNaEy259hLLlmuPmmIzltUUZ5QUL3qA3P52Nzasaox4P+fWlmTtmbPBSQXjaI/Lh9bZ8tfEa3slUg19UlGY+j3SwWk3yd6n0q7efdJpr1TRaRg2rm6MCOGycXUjdFplGU8nHM1MpFxBFr2BICpsRsWNDDah/zQMcY30SkzlUT5xgy363pTZnSByD+vEQi5aR1kK4k/lqZ8TuYzBoMW61lloKLWgz+1DWWEBtr7aESPn4QYL0fkmnfGT+kNuMRlz51wnGZkUZb3QmN44kAh6D/mFaOOJ3kyTe4dWgw7/de0ynBr249SIH//z1+Pocfng9o3h/nXNESEX717bhN+81SldS+9/5qGm5/AnAcxByKh7CYC1E/8mw38C+DcAojQ7AJzhnIvW1W4AVRP/rwLwIQBM/N018X3pc5lrJBhj6xljuxlju0+dOpVk9eQRlfmQNyC781JTEjvRkPP+bakukj3OrNfGvh4x4cKKhlI0lFnjGg8qbEa8sOcENqxqlAy40XUUDaibr14S9zvx2qCl2o6Nqxsz9thVKj+et3R0e+h0mqTbR4noHdwelw/bdndh2/oVeHL9eXhpw0qc3+BIyYs7HdSUVdE4Gk4i42iqnupA6h4Z0R4jYtbd1ln2pJ4rWZqcthiv8vvXNaPJqd590mmvVDHptbAYtFh/UeiUwfqLGmAxaGHUKRsls+0lo6acTiVNThv+47MtEe9v4+pGzC23onWWHbOK5PuQhgF3X9KEUosBxebUj/VNpWe3uMH20oaVkm6brvHFpoucEtObeHJqN+li5lobVzfCZoxvFJhJ/ZyYHNTWpwaDFm11JfhM6yw0VVpx76WR87UNqxrx23e6pd8rbKGYw+mMn9Qfcotsz53zYexPRiZFWbcZtWmNA4mYjDUMoUyqciraeBZW2qR3JjqzRcuGdyyIe148gNt+uw8P/PEIelw+GPUaFJkMUlL4m1fNxU0XNuC/Xz2KlfPK6f3PYFTzHOacdwIAY6wcQNJWB8bYWgD9nPO3GWMfVas+SnDOtwLYCgBtbW0Znd0VlXnXoAflNiNu/92+iB2/+tLYDiXn7dqr4NXpDYynXTdB4NAwYOPqeXhw5xH847k1uHPtItz34sGYXUmxTouchah1WGKeI55i0GgYVs2vwNwyK5bVFMMbCKKmxJIwkV2ypOotrQZyO7i3rVmIlqqiiPtmu15qyqpoHI1OyBbPOJpO26fqkRHtMVJhM6J1lh0Gg7oRYXQ6DdYtrkJjuRW9Lh8q7UY0Oe2qJaMDJkdWA4IAxiLLY4xhTBAUrsi+l4yacjqV6HQaXNY6C41lFvS4fDAZtLAb9VhYaYPBoMWiypDx+N/D9OO9lzVjVlEBjp/yoNhiwIIKW8r3nWrP7mQzvOc700VOielNPDnVMIbqYhPWX9QAgQMaBlQXm+KeHJGunSH9nJgcktWn6STDtZgK8JnmctSVLsepET/MBh2+/fx+yaBx76XNaK4MJeBNd/yk/pA7ZHvunC9jfyKZFGX9sf87jo8trIgZBxplbA7hJOqLU7HeJs6SqpzWOSy4bc1CPPr6Mcm+Izqz/fjz52BsXIDJoMWJQQ/GxsbxlY814q7nIm0AWg3QOTCKR145GlF2a5UNL21Yqdr7p6To+YVqxmHG2KUAfghgFoB+ALUIxRBuSnDpRwBcyhj7NEJGZRuABwEUMcZ0E97B1QBOTHz/BIDZALoZYzoAdgADYZ+LhF+TNTQahrpSK2pKLFgyuygphSo3AMgdA6iwpefZF37MqthswFVt1ZhdYkaT04bf37ISp0Zi6xj9HIMeP/RaDbyBcRwf8CR8nrpSK+pKszPJmuxJXLIDZD5NLtM1jqb6jOlMLkSPkWyj02mweHYxFiuE0VCDbMtEmbUAH+hGMK+8EB5/EBajDl7/GMqsypm7acKXPDqdBq2ziyNCrYjxDPvcPiyrtuPxLy5Hn9sPS4EW4BwjvnG0VBelvdlAR/kIgkgGa4EO1gINPjKnVNLl3kAAFpUTuBKEGohrkU07DmFtaxW0GuDc2hKc3+BIOFZaTAVYXh+a13hHA/jBlYvR5/ajwlaA5spCmE0GADR+ThfyaT01VYiy/tv3egAAV55bg4ERPypsxog+IUcwKOCvHQPY3TkIgYdy9Ny2ZmGMdzK9h/xBWttVFmLQ48e29SvgDYxHGF+DQQEHjDr0unyocZjw5D+vQJ/7rA2ga8grqz/nVxZC4MDfPhjI2Jg7laHziPRQc0Z5H4AVAP7EOV/KGPsYgH9KdBHn/FsAvgUAE57DX+ecf54x9jSAKwE8CeAGAM9NXPL8xO9vTPx9F+ecM8aeB/BrxthmhAzUjQDeUu/x4pOJQlXbsy/8mFWPy4ctO4/CqNfgpQ0rMafcijnl8XfT6xwWvN87PKM78nQcICfDOApMz7bLFTgHBjxjuOv5sycANq5ulGLxKUHvJD3kJjUbVzfi8Tc60TORzFDUrel6oVP8Q4IgkoFz4P1eDx7cGamP6hyFU101gojh+IAHm3YcismpsumKVlzSOivp9YTZZMDyeofs32j8JGYK4bL+2/d68NKBPmy+egnaakvi9iVB4Pj9/h7ctn1vRF6jTTsOYUFlIa0L8phEa7tE6345/fnwtUtxsEc9G5BS6J8FG1aS7OUoahqHxzjnA4wxDWNMwzl/hTH2nxmUdxuAJxlj9wN4F8CjE58/CuCJiYRzgwD+EQA45wcYY08BOAggCOArnPP04zJMImp79mV6TJk6MkHkJv3DfikZHRDqmw/ubMeymmLUU99UHTld+ODOUHwu8RhWpiEgyLObIIhkIP1P5BN9bh/WtlbF5FS5bftetFTZVVlP0PhJzBTSlfXjAx7JMAyczWt004UNlJh6hiMnU5wDn3noNdVsQFMdOo9IHTWNw2cYY1YArwH4FWOsH0BKGXU4538G8OeJ/3cAWC7zHR+AqxSu/w8A/5FSrXMENT37Mj1mRR2ZIHITTyCoEJ88qHAFkQlKujA87LMaR1jJs5sgiESQ/ifyiQqbEVoNsr6eoPGTmCmkI+tK81itBhR+hYiRqTeOnVZVZ1Pon/xDvWxMwGUAvAC+CmAHgGMALlGxfCJJMs04KnbkcKgjE8TUU1tike2bNSV0hDIbKOlC0VGDjrASBDFZkP4n8ok6hwXn1pbQeoIgphCleWxbbQnNXYkY1LYBZWqTIiYf1TyHOecexlgtgEbO+WOMMTMArVrlE8mT6TGrmR7Di7JqTi7U3slTXyrfN+sTZCkm0kMpHle5tQCLnDY47SY0OW0krwRBZJ36UgsevnYp9na7IHBAy4CWajvpfyLnEOd1Wg3DT/7pHNz1/H50DozOuPUEQUw1cvPYTVe04oKGUBxvMeEyrb8IICQvcvOMdHU2hf7JP1QzDjPG/hnAegAlAOYAqALw3wBWq3UPInkyOWY1kzsyZdWcXKi9U2Mm982pILq9K21GHOwZxtVb3yR5JQhi0gkEOba+2hGhfwgil5Cb1226ohVVRUaUWApozkIQk4jSugEArb8IWdSeZ1Don/xCzbASXwHwEQBuAOCctwMoV7F8YhIRO/KKhlI0lFlnzEChlIzv+EBK4bOJJKH2Tp2Z2jenivD2FjhIXgmCmBJovCTyATk5vW37XpRYCmjOQhBTgNy6gcYTQg6SC0JN47Cfcx4Qf2GM6QBwFcsniKwTLxkfoT7U3kQ+QfJKEMRUQfqHyAdITgki96F+SshBckGoaRz+C2PsdgAmxtgnADwN4AUVyyeIrEPJ+CYXam8inyB5JQhiqiD9Q+QDJKcEkftQPyXkILkg1DQOfxPAKQD7APwLgJcA3KFi+QSRdSir5uRC7U3kEySvBEFMFaR/iHyA5JQgch/qp4QcJBeEagnpOOcCgJ9O/BBEXkIJvyYXam8inyB5JQhiqiD9Q+QDJKcEkftQPyXkILkgVDMOM8Y+AuDbAGonymUAOOe8Qa17ELmJIHAcH/Cgz+1DhS3/lQhl1ZxcZnp7T7f+ky+k2+4zXV4Jgph6OGX0IHIYGienHzRXnX6E91N6v4RItvQ3yVh+oJpxGMCjAP4VwNsAxlUsl8hhBIFjx4FeKbOlePxgTVMldXiCSAD1n6mB2p0giHyD9BZBEFMB6Z7pDb1fItuQjOUPahqHXZzzP6hYHjEFpLqrc3zAI3V0IJTR8tan3sOCDSuz4jGQzq4T7VSlz2S03Ux+P+n0n5ncXskg1z4AIj7TMEyq3spHSM4IIrc4PuDBz18/hu9fuRij/iDMBTr8/PVjWFBZSHqLIJJAEDg+OO1B56AHFoMOFbYC1JTQ2BZN9PhPc6bpifiejw94cLjXjWKzAT0uH71fBYJBAQd6XOhx+eC0m9DktEGnUzN9V/aJ7ts1xWZ0DXlVm+srrR0m215EpI+axuFXGGM/APBbAH7xQ875Oyreg8gi6ezq9Ll9UkcX8Y0J6B/2ZeU4Qqr1o52q9JmMtpvp7yfV/jPT2ysRcu3z8LVLEQjyiM++89kWaRIski29lY+QnBFE7uEaDeCKZTX4t2f2SP3y7rVNcI0GprpqBJHzyI1rG1c3orHCilXzK2hsm0CunWjONP2Qe88bVjXiiTc7JQMxvd+zBIMCnt1zAnc8u19qr/vXNWPd4qq8MRBHv/Nahwm3rGqMeKZM5vrx1g6TaS8iMkNNaT4PQBuA7wD44cTPAyqWT2QZpV2d4wMexWsqbEYpo6WIUa9BeaExJ+qXzjVEiMlou5n+flLtPzO9vRIh1z57u10xn93+u324qq064tps6a18hOSMIHKP4DjHPS8eiOiX97x4AMFxCkBMEImQG9ce3NmOvd0uGtvCkGsnmjNNP+Te85Zd7bh8Weg90/uN5ECPSzKiAqH2uuPZ/TjQ45rimiVP9Dtf21oV80yZzPXjrR0m015EZIZqxmHO+cdkflapVT6RfeLt6ihR57Bg89VLpA4v7hKJR7mnun7pXEOEmIy2m+nvJ9X+M9PbKxFy7SNwyLbZvIrCSdFb+QjJGUHkHv3DfoV+6Ve4giAIEaVxTeCgsS0MpXaiOdP0Quk9M0bvVw7Rmzoc35iAXlf+6I7od86Y/PooXX0Yb+0wmfYiIjPUDCtB5Dnirk54x060q6PRMKxpqsSCDSvRP+xDeWH2YlOmU790riFCTEbbzfT3k2r/mentlQi59tFOTHSj22xhpQ0vTYLeykdIzggi96hU6JcVNuqXBJEIpXFNw0BjWxhK7URzpumF0nteObcUly+tovcbhdNukm2vSnv+6A6ld67WXD/e2mEy7UVEZuRHkBRiUkh3V0ejYWgos2JFQykayqxZ6+jp1I92qtJnMtqO3k9q/YfaKz5y7dNSbZdts/pSy6TorXyE5Iwgco+WWXbce1lzRL+897JmtM6yT3HNCCL3kRvXNq5uRGu1nca2MJTGf5ozTS+U3vO5dSX0fmVoctpw/7rI8ff+dc1ocubP+Bv9zl/YcyLmmTKZ6ydaO0yWvYjIDMb5zI1V1tbWxnfv3j3V1cgpxCyTubqrk079cuCZMr7ZVMnqZLRdDryfvCKL7ZW3chqOXPsAIBlLkRzul1mV049cfClmX/kt2b/97/034pN3/CLm8w+f+S7+74/PZ1otYvqRkazKyWkgMI69J11SJvDWWXYYDNqMKknMeFSX01xFEDg+OO1B16AHZoMOFbYC1JTkzNiWM+To+D8t5qi5RI6+55wlGBRwoMeFXpcPlXYjmpx2uWR0OS2n0e+8ptiMriGvajJAMpU3KL4U1cJKMMbMAL4GoIZz/s+MsUYA8znnL6p1DyL7iLs6uZo5Mp365foz5TKT0Xb0flKD2is+Su1DbZYaJGcEkXsYDFq01ZVMdTUIIi/RaBjmlFsxp5zGtXjQ+D8zoPecGjqdBotnF2Px7KmuSfrIvXM1ZYBkKv9RM+bwLwC8DeD8id9PAHgaABmH4yDusIheILTDkj2orVMnnTajdiZmItmSe+pPBEHkG6KHVY/LB6fdhCanTc7DiiByFkHg6Br0oM/thycQRG2JBfWlNP4SuQ3pXkIk2fUDrTOIcNQ0Ds/hnF/DGPscAHDOvYwxkqw4CALHjgO9uPWp9+AbE6TYLGuaKqlTqgy1deqk02bUzsRMJFtyT/2JIIh8IxgU8OyeE7jj2f2S3rp/XTPWLa4iIwWRFwgCx67DfWjvG8GDO9tp/CXyAtK9hEiy6wdaZxDRqKkpAowxEwAOAIyxOQD8KpY/7Tg+4JE6IwD4xgTc+tR7OD7gmZL6CAJHx6kRvHHsNDpOjUAQpk886lxr66kg1febTptROxPTgcnoK8lA/YkgiHDyYZ52oMclGSeAkN6649n9ONDjmuKaEURyfej4gAd7u12SYRig8ZfIfUj3Zk4+jLHJoLR+6Br0RDzfB6dpnUFEoqbn8N0AdgCYzRj7FYCPAPiCiuVPO/rcPqkzivjGBPQP+yY9Vst03znKpbaeCtJ5v+m02UxvZyL/may+kgzUnwiCEMmXeVqPS15v9bp8eR2rkch/ku1DfW4fBA4af4m8gnRvZuTLGJsMcuuHYrMB73Sdwe2/2yc93wNXLiY9R0Sgmucw5/xlAJcjZBD+DYA2zvmf1Sp/OlJhM8Koj3wFRr0G5YXGSa/LdPdQy6W2ngrSeb/ptNlMb2ci/5msvpIM1J8IghDJl3ma026S1VuVdtJbxNSSbB+qsBmhZaDxl8grSPdmRr6Msckgt364qq1aMgwDoedr7x8mPUdEoHYAGiOAIQBuAIsYYxepXP6UkK0jBnUOCzZfvUTqlLUOE7Ze14Y+t2/SjzLE81CbDkS3tbgbWOewTHHN0icVuUzn/abTZnUOCx6+dik2rJ6Lm1fNxcbVc/HwtUvzup2JmUU2+kowKGDPh0PYsb8Hez48g2BQUCwrlXIJgpg55Ms8rclpw/3rmiP01v3rmtHktCe8Nl1dSRDJkGwfqnNYsKy2CHeuXUTjL5E3yOne/1jXgiGvn/RpEuTLGJsMcuuHeeWFMc/31O5u3L+uhfQcIaFaWAnG2CYA1wA4AECUPA7gVbXuMRVk84iBRsOwpqkSCzasxKDHjxNnfFj/xO4pOcog7jCFK43ptHMU3tb9wz5U2owYF4C/fTCQVmbOqc7smapcpvN+o9usvDC55wwEOba+2hFRr0TPQllSk2emtVf485oNOgTGx+GwFGTtudXuK5kkCEm3DxIEMf2osBnRVmvH9Rc0YNQfhLlAh8f+2pFz8zSdToN1i6vQWG5Fr8uHSrsRTU57Qn1HyZSIbJNsHxIEjlPDAWx99RhuurABWg2wdHYRPtJQSuMvkbOE694+tx96nQbffn4/OgdGSZ/GIRgUcKDHhSFvAA9fuxRb/3IMe0+4AeSvLURu/cAFjlqHCWtbq8Am1Nibx07BbtThR1cvQYnFgApbAWpKaJ0xk1Ez5vA6APM559MqCZ3SEYMFG1aqEotFo2FSOf/06FtZu08ixB2maGPjdNo5Etu6zmHJyOCfCzGJUpXLdN+v2GbJymCq9cqFtswnZlp7yT3vhlWN2La7C7etWZiV51a7ryglCGkst2Lx7OKE9Um1DxIEMT2ptptw9bm1+Ldn9ki66d7LmlFtN0111WLQ6TRYPLs4pTiXmepKgkhEsn0oXBYfeeUogJCRaNv6FSSLRE4j6t49Hw7hmq1vkj5NgNym5N2XNAF/68SR/pG8toVErx86B0bw5X+Yi3teOCA96z2XNuH+lw5KGwibr16CmpL8fF5CHdTcOuoAoFexvJxgso4YTPVRBnGH6aUNK/Hk+vPw0oaVWTM4pROmQ83QHpnGFMqFmESpystkvd9U6zWZbTkdMtDmguxNJnLPu2VXO9a2VmXtueP1FUHgOH56BH/rGMCu9/twrD+xHMVLEEIQBJEsh/rcuOu5SOPpXc/tx6E+9xTXLJZ0wkOQriSyTaI+JMpt1+AofnDlYrRW2aRrSRaJfEJJnw77AhS6Jwy5Tcl7XjiAOz6zKKu2kKmg1+WXDMNA6Fnvfv4A1rZWSb9P5zUlkRwZew4zxh5CKHyEF8B7jLGdACTvYc75hkzvMZWEHzF22o24fFk1tBrApNdBELhqCiMXwjpMhodaOp6PantLhhswxXfKGHBqxB9xZFvp+H48A+hkefele/Q92++3wmaMObLywp4TivWarLbMZY/bVMJE9Ll9KDYbJJkFgO1vd6PPPf2yyortIicfjKUmJ6mG4pDrK4LAsetwH9r7RvDgznb4xgTUOky477IW6LVMsVwxQUh0X6UEIQRBpEK+ZKJPNzyE026SPfJPupJQi3h9qMkZktuHJjagtRpg48fn4fd7TsBZbIFWA5RYDPj78YGshrYiCDWInns67Ub888p6jPgFnPGOouO0B4d63Oga9OBTTc4ZG2pCSScMeQNY3uCYolplB08gqLimAs7aRI70DWPEH8RYUIDLN4baEgvqS0nfzRTUCCuxe+LftwE8H/W3/HPNi0I8YrxpxyFc01aDLbtCRoGtr3ZkZFyKNlbUFJunPKxDprFMk7leyfNx0caVEDhkr1U7tIdoWC02G3Ddilps292Fta1V+L+jpxEYE3B+gwMaDVM0JuaCIV9M/La32wWBA1oGtFTbVZeXVGWiptiMW1Y1xiwKa4rNst+frLZMR4YmI7avaHCMfo+r5lfI3qvQqMP159dKxkmjXoONqxtRaFQzQtDUIxrzD/e6ZeWD80g5ifeu1NoYOD7gwd5ulxRP22k34pq2moRx4hdWFOLHn1+GAyfdmFNuhZYxBAUBZoO6G4wEQUxv8mWj6cBJFx7a1Y6bLmyQFp0P7WpHY5kVi2uUjzPPL7Pi6raoI/+XNmN+WeEk1ZyY7sTrQwd6QnIbvtYTw0488ko7AsHQknZOmRWCwHHaM4q2GopBTOQmYnK6O57dj2KzARtWzcGwL4gBTwD3vXgwYg3xfp8bzVVFU13lKSFfxlU1qC2xyD6rUaeB027EdStqI3TfxtWNePyNTgx5AznjUEVkn4wtCpzzxwCAMbaRc/5g+N8YYxszLX+qCDc2LHIWYss1S3HNT99My0ApZwj+46G+GGPFxQsr8JJM4qFERio1jFjBoIDf7+/Bbdv3pmVASfZ6Oc/HVw/3452uM7j9d/tirgWg6D2YqnepIHB0DXow5Ang/nUt6Br0YNvurpiJ4KYrWtE8y65oxNYw4IdXLcbhvuGsGmYT4R+LTPz2w6uWqFp+qoZLAOga8srGDFxWU6xqLORUZT5Vj9vJ8jTuGvTEHFPsdfnQNehBXWlsvbyBcckwDITa98Gd7WirjR8/LJ+S2I2OjuFQ/zAsBVosnm3HfZc1487nzm42iDGHN1+9BBoGvNs1CNdoEO90DUHgIU/18HjEqWwMxGunPrcPAodUzuXLqiW9IZa7acchlFoMGAkEUVtiQW2JGX863B8hRzTZIggiHcIX++Gbr01O+1RXLYLTHj82rp4Lg1YHjz8Ii1GHhtK5GPDGT0lyuH8Ydz0fdeT/+f2YXxHfqEwQyRKvD/3p/T6sba2KGdfvem4/bv7YXJRbDTAX6OHxB3FqJAC9luGEy4PZxdPr1BYxPRCT09U5LBgNjKHH5cMCpw09Lh9+cOVi/PTVUNK1B3e2o7kqt8aQySRfxlU1qC+14IdXLcHXno5ck1gMWnz+vBps292FjasbUV1shtcfxJA3gOvPr8WmHYdx61PvofSLy1Fo1OKMN5jza0kifdR0N7sBwINRn31B5rOcR84w9MCVi9MyUMqVtfW6NlljxUsTxoroo8w7DvRi045D0jGnc2tLcH6DAzqdRhUjliBw/LVjQDLshtcpWeN3stc77cYYz8cfXb0E/6pgiD3YM6zoPZiKd2n0kfBiswFf/Xij7ETwtu178V+fXxbzvovNBrzTdQYP7jyCa5fXRhhmN1+9JOm6qMEHpz2Schfr/bWn38OCypWYU67ORLVr0IP2vpGI59y4uhFzy6yyhktAOUyEkhFWLptqosEmHZlP1eP2+IAHm3YcivB82rTjEBZUFqoavmHQE8CwLxjTxkOeAOpKY78/4pM/EjTiDyreI5dDakQzOjqGlw/348SZ0YjQDQ9/bimOnvJg2ewiaDTAJ5sq8cHACG74xVtYf9GcCC+IDasapXdV57AkvbmUqJ0qbEbYCrTYsHouBA7MryhEsdmAngnjvuhJfP0v3orYaNr88uEYY/5NFzbgkVeOTmrSUYIg8pvwTPS9Lh8q7UY0Oe05dxy4otCI/uEAbv/dWQ/guy9pQrk1/pzthGtUVlefcI1iMcg4TGROvD7ktJtwsMctK4ONFVYMesbw9WciZdrlDYJyexG5ik6nwdh46KTaOGdY/8TbZ+V3bRPwVif2nnDDFxif6qpOGfkyrqpFiUWP9Rc1QOAA58Djb3TCoGO4a+0ifPGCenjHxvGNKD3ntBvR4/Lh9aOn4bSb8JuwZH25uJYkMiNjyWeMfY4x9gKAesbY82E/rwAYzLyKk4+cp1l7/zCM+sjmSsZAKVfW7s5BRWOF3PViSItHX+/Alp1H8c9P7Mbv9/dIXm6ZJqg6PuBJqU7JXO+0G3HThQ040jcckfxrXECM5+OhXvnJWJ/bj1ufeg9P7e7GhlWNUvunE3JDPBIu3rvH5cOHQ6PQaiB778ICXcz7vqqtGrf/bh/WtlbhR386klGbZ0rnoLzBq2tQvTr0uf2yXqp9bmXvH7Mhtt2Meg3MBq3iNWJ81xUNpWgosyYcZNKReSWP21GFCdGAxy/1uYd3HcXPXuvANW01GPTE93xKFaV6eRTqVWiUb19rgfI+X64msZNLELiv142jp0Yi2qRzYBQ3/+ZdeANBlBYWoK3OAcaAm3/9Lta2VkmGYSAyYV2f24cdB3qx58MzSenuRO1UU2xGibUAW18NycQ3ntmD68+vhXPi6JmcJ/Ft2/dKiR5EfGNn43slq2MJgiCAs5noP9nsxOLZxTm5gB0JBGOS3tzzwgGMBJQ3MQGg1Fogq6tLLQVZqysx81DqQ01OG5bOLpKVQZtJLyvTw774Mk0QU02FzYjAOI+V3xcP4EsXzYFRr4FOq5nRienyYVxVg+MDHrzRMYAtO4/i4V1H8cgrRwEA17TVYDQgYMAbiFmT3vPCAVy+rBpGvQbjAnDPCwfwtU/Ox5dWNmDTjkNTvpYk1EcN6f8rgB8CeH/iX/HnawA+mehixthsxtgrjLGDjLEDYigKxlgJY+xlxlj7xL/FE58zxtgWxthRxthextiysLJumPh+O2PshnQfSM778and3fjOZ1tSNlDKlSVMxMsMR8nQ3Of2KXq3isef0zXqht8jlTolul6MW/Po6x348i/fwae3vIYdB3ohCBz9w8m3hxg4vcflwxNvduKmCxtw86q5eOzG5SnvVEUfCQdCYQUWVtpk720yaLFxdaRBuqbELBl2Mm3zTLEoGmHVOwzgVQhc742zwAuMj8cY8jesasTYuHqTjnRkfsSfmsetQauJ6XNbdrVDr1V3wpBqvQa9Y7LtO+QdU7yHGjpCbUQv3U9veQ2f++nfJB3R5/bH9FMg9Pu8ikJJ34rPpNQXtRrAbNCmtLmUqJ3kQqY8uLMdV7VVA4DiRlO0yIgxk8X/T2ascoIgiGxzeiQgqwtPjwTiXldhK8DdlzRF6Oq7L2lChZ2Mw0T20ek0+EhDacxab8OqRnQPynu1D3gCkvMLQeQidQ4LBhR0si8QxIZVjfj2C/txoMc1RTUkJgs5e4/o2NJx2qO4/tJqgA2rGvHbd7rhGwsl8MyW0xQx9agRc7gTQCeA89MsIgjga5zzdxhjhQDeZoy9jFBIip2c8+8xxr4J4JsAbgPwKQCNEz/nAfgxgPMYYyUA7gbQhlAivLcZY89zzodSrZBckqwhbwDLaopkYwKnWtYLe05g0xWtMfF55QzNFTajotGhf9iXVkKv6Lia5YVGvLDnBDasaoyJvZuMd26FLfJ6OQ868fh0ovYoNhtwVVs15pUXwmEpkL7b4/LhkVeOwqjX4PKlVSkfYaiwGaFliLh3j8uHR18/hu9+tgXfiop3POwL4vE3OiNi71gM2ogJYyptrjYVtgJsXN0YEyahwqbeIqokrP1FjHoNSswGxWsclgJs290lhWPgHNi2uwtrmitVq1c6Mq8UhL+mRF6+vYFxBcO4ukevHBaDbL0cFvk2LjHr8R2Z9n3gysWK96iwGVHrMGFta5XksfrCnhNTapRU8tJ9/IvLcXTilEZ0myystAEAOk6NYHRsPBTTUqeR/e7SmmIEx7kU9kHcXGIMWDm3FOfWlcTokERypWQ8rrKbsOmKFlgmThtEX99WWyJ9Hh5zOJ0TENkmn2JTEwSRPMGggAM9LvS4fHDaTWhy2pLyjkpHJ5RaUxvXRGYXWzCryIMHrlwMTyAIi0GHQpMWs4tzR0cS+YOS7MaTaYNBixKLLmKO9cSbnbj90wsV5gcFOD7gyYnQUDR+E3KEwqLJr+cq7Eb86E/t6HH50OvyoaVqesqQIHB8cNqDzkEPLAYdKmwFqCmZHs+WCtH2GtHw6xsTEBgXYuwkQOj3c2qLsedDF644pxov7DkBk0EnOU1tW79iCp+IyAZTnuKec94DoGfi/8OMsUMAqgBcBuCjE197DMCfETIOXwbgcc45B/AmY6yIMeac+O7LnPNBAJgwMK8B8JtU66SUJEtUJNFxKuMpUrmybluzEBcvrEBLlT2hobnOYcG5YcYFEdFokWpCL7m4mg9fuxS3rVkoxVjVaoC22hJc0OBISnHWOSwR19eUmBSN2cvrHIrtsbjaHpGYrtZhigkSn64xpc5hQUu1Pcag+sUL54TuPbso4l0cH/DAoGPgHFLsnVqHCfdd1oyHX2mPMaRPtpGnpsSCxgqrFDdIw4DGCquisTMdRC/g8OfcsKoRY4KyF7AoC6kmmEuFdJLY1ZfKX1NfKn+NkqGwwqauQbWyqAD3XtosJeEx6kPZ2SuL5I38LU47vvLRxpjvt8RJnFBTbMYtqxpjki3UFJtVfZZUUDK06jQMc8qsMf30h1ctRm2JOUZ33f6pBfjXj8+TwrwY9RrcuXYRfvTHwzjSPyIZYsM3lz6xsBx/+2AgRl8ryZWGAW8cOy2FTImWiROuUTy9uxv/7x8aYuq9+eoluKDBgd/fshJdgx5YC3QQwLGgshA1JRbUl+bO5DSfYlMTBJE8waCAZ/eciBkD1i2uimsgFgSOP+zvjUhe88OrluBTzfF1gtWgxd2XNEnHmEUPYGuBcngpIGTEWDm3HMcHPCk5YRBENErj2cULK2QTgoePc8VmIx59/d2Isf6xv3bg3suacddzkXOv14/04YLG8ik3DtP4TcSjqbIwRn7vXtuEH/7vYfS4fDDqNai0G6elDMn1jY2rG9FYYY2bYH06UlNsxldXz8d/7jws2XtEG9P2t7vx5Yti1zH3TchN58AojHoN7rm0Cb97+0MA2XGaIqYexnnuHIdhjNUBeBVAM4AuznnRxOcMwBDnvIgx9iKA73HOX5/4206EjMYfBWDknN8/8fmdAEY55w9E3WM9gPUAUFNTc05nZ6dsXUSjb7wJajKDsZgIbW+3SzLitVbbU1JIwaCA3+/vifE0Fu+TTF1FOk6N4NNbXosxcOzYuBICR9oT8vA6mPQ6XLP1jZh7iAn3lOorV7dahwlb/nEpRsfGU6qXnNEeCCVZ63P74Q0E4xpnBIHj9aOnsf6J3bL1GRsXoNdq4A2MJ7O7mtbIk0hWU3nv6dBxagT/9sx7uP6CBowGgjAbdHjsrx34/pVLFCfCash7MqTz7KlcM1kT7fe6hrBx27uSVy/nwIt7T+DBa5ZiiUJ2dp8viH09LvS5/aiwFaDFaYdRIbEeoNznX4pNhJYVOU21Tk5rAQ71D2PYH4R/TECdwwSDTos+tx83TCR7C7/mVzedB52WYdATwLsfnsHTu7ulJHFGvQbrL2rAlp1HJYPIQ7vapUmOnL4WZaTMasQHAyO4+dfvSptD0Ub2zVcvwSJnIXrdPlTajOAc6B9OrF9ykRTkZKrJqpx+5OJLMfvKb8n+7X/vvxGfvOMXMZ9/+Mx38X9/fD6dahHTm5RlNR19mog9Hw7hmq1vxvTtbetXYHGcbFpH+4Zx0+N/jzl18uj152JuRaHidR+cGsG+E0PQMK3kASzwcbRUFaM+t3QJESIn5FRNlMazbetXyPaF8HFOaTPlvAYbeoaC6JuYQ/5fex+2vt6JF2++MG5/yAbRaxwNA9Y8mBfjdyZM2hx1OtI1MIyTLj9OjwRQbNbjRy8fxu5Ol7R5N6/Cgr8cOQ0xSsr2t7sx5A3kvQwp6YL1FzVg3ZKqbDxbTsqpuK79+evH8LWLF+CNjgGMC8BrR/qxptmJLbvaUWw24MYLajG/0obRsXGUWgvwtaffQ+fAqFSOUa/BzR+bi9EJr+PVC0LOjvmy1iEkFF+Yqp7DjDEDgHkTvx7mnCsHwoy91gpgO4Cvcs7djJ2tM+ecM8ZUsWJzzrcC2AoAbW1timWKHsLxlIbS0ejw7PPHBzyScUEk1QFbp9PgktZZip7GydRVRMljr9ftkxKCxUPJUzq8DoLA43p2KtVXrm6dA6MYHRvHiobShM8WXkclw15dqRV1pWfvGwwK2HfiTMxRS42GQa9lqtQnXRLJairvHUj9yFlNsRk3XFCP9v5hCBzQMuCGC+rjepyqIe/JkOqzp3qNRsOwpqkSC1IMI5NqG590jaJzYFRKChD++RKF7OxGow7n1jsSPoNIvFi6aryTZHVqOPG8vzUahmW1JQAi+/KXVjbIPseYIOCculK8cew0tuw8GvP3pbOL8OT682DSa7HhyXelSY6cvhZlpM5hwb4TZ7C324WvfrwRwXEOX1DA4IgfT61fAW/YZhUQipve4wq9c7mQFflAtuVkqklHTglissmGnPa4FOZ9Lh8Wz1a+7sQZL754QT0GvAFpDvDFC+px4ow3rjGs1mHBsdMjMZvEtTkUQofIjFzXp0rjmVJfCB/ndDoN1i2uQmO5Fb0uHyrtRjQ57Xi/z423u4bw5N+7sLa1ClqNFj+6ZgnGhMn1nJNb43znsy1SGC2l55qp5LqsThbVxVbsPzmCrz+9B8VmA64/vxY3XtgAs16LXtcojg94sfXVjoiTok+82YnOPA4zIa7J5Pq86BCXK/0j23J6fMCDTTsOYW1rFfqHQ/ldfvtONwCAMeAHVy6GXsvQWF4oOba8cex0hGEYCLVdpc2IOya80Le+2jEtPMyJs6hmHGaMfRSh8A/HEbJGz2aM3cA5fzWJa/UIGYZ/xTn/7cTHfYwxJ+e8ZyJsRP/E5ycAhE9nqyc+O4GzYSjEz/+c5uMASGzoibeYFkMTHOkbVmXBnY4xTI504rWKiBMSUbmIxxHOb3BEHE1MxrAm17ap1k3p/SRjtAcSH7XMpK1yjXQ8YbvPeNE9NBoxWdi4uhHdZ7wRBvZwJsvAlG78xHRI9nBFOm0sZmePljE1s7Pnohwna3yP7svxnkPpOWsdFjSUWRUnOdGyGf4exQn0w68cDVuEGXFp6yzodBrJU769bwQlZgMGPAH0ukbRVlMCgyH+EeqpQklv5qKcEASRObOKTLJ922mP37ctBTp4x8Zj5gCWgvhLB42G4cL6UtiNevS6/aicOOFCC0disigvlB/PnPbkxjmdToPFs4sjNk+6h0bxh309WH/RHNz34sGIdUN9sRX7e93odfvgtBnRMsuetTnAB6dj1zi3/26fdEoq/LnKrDR+EyHEebfjxuXodY9iNCDga0/tidDt4gaDGE924+pGvPvhGen0XT4ZAcW5/OFet2yf1zDMqPntgMePa5fXRoTh+9ePz4NRp8F3d7wvfbbpilYMev1wWApQrrBG7RryJrSxEPmLmp7DPwRwMef8MAAwxuYhFO/3nHgXTYSMeBTAIc755rA/PQ/gBgDfm/j3ubDPb2aMPYlQQjrXhAH5fwF8hzEmuttdDED+bGgSJGPoUVpMV9qMEd5uubTgTideq4i463RNW01M4rpLWmfFHM2ODunQcWoEfW4fnHYjDvYMy8YCS7Zu0e8nFA+4BXotw+hYZDIxp92Iy5dV40jfsNQGGg3DgR6XZBgGgGKzAV2DXrxypB9zyqyoKTZH1Ee8R5/bF1HOVJGKgTRZg3k4fW6/FHdIvObBne1YVlOsaByeDANTuvETUyEdQ286bVxeWICHr10Kg1aDQc8YSix6BMYFlKuYWLCm2BwTu3uqYw4DyW14hW82bH+7O26s70S6TS4x35vHTsGk1+KNY6fhtBsxLgCnR/xSGf/vHxpQYinAPZc0wVygw09fPYbbf7cPpdYCXDi3FF2DHnSc8sQkhhz0jmHNosqsbVikSrhODo5z3PHcvpjQGpmMDQRB5C5Wg1Y2ga01gZHXNyZg56FefP/KxRj1B2EuCIWWaqlSjnEPAIHAOJ7f3xMZn/WyZqxrnZWzm2bE9EKrgazM+4LjsrkBkhnnnHYTPrqgHL9758OYPlFiMeD/+9U7WZd3QeA41OOWdcKoKTFL82/xebW5MQUhcgSNhqGssADDvjHctj10yrO1yoYvXTQHo4EgNl+9GO39w/jxnzukteXPX+8AkH9GQHETpdhsiFk7iDGHZ8r8VhA4BAGSYVi0i3gCQVQVF0ZsCty2fS9uurABj77egR//0zL8x2db8O8TuaCMeg3uWrsID+2KPaWZS17YRGaoaRzWi4ZhAOCcH5nwCE7ERwBcB2AfY+y9ic9uR8go/BRj7CYAnQCunvjbSwA+DeAoAC+AGyfuN8gYuw/A3ye+d6+YnC4dkjH0KC2mxwVInyUyaEw26R6XB0KGmrWtVdKzAJAUSUuVXQopIZfwLhDk0mcbVs+VPFHEMm596j28tGFl0nULfz9OuxHXtNVI8YE3rp4rTZCcdiOuW1Eb0/5rmiojjpcpfe/ihRV4acNKDHr8OHHGJ91jqndQUzWQpuPR6wkEZa/xBoKK9ZoMA9PBKKO+b0zAHc/ux7xyK1rjxE9MhfSM6am3sVYLDI4EcNfzZxP33HtpE7SVqjwGAKBryIuHdrVHZN9+aFfIyJ/rA3n4ZkOPy4cn3uzE+osasHR2EWodlpjwOvH0R3RivlqHCV/5WCOu2fqm5CH84M52KXxFa5UNBXotvv7MWc+Ku9c24TdvdWJ35yCqi004NezH5pePxGygrL+oAbOLTXHjeU4WcjpZPC7Y4/JFyHW6YwNBELnL8UEvHn+jM2IMePyNTiyoLERDuXJ4CA3juGJZDf4tSgdqEkR523vSJRmGgZBevOu5/WgotaCtrkTVZyMIOXpcPlmZHx0bx9O7u6XPNQxY5CxMapxrctrg8vnhtJli+sSgxz8p8n58wIP2/mFZJ4xely/meZfWFCk6cxAzkzqHRTrV3Fplw+eW10bK8yVN+NfVc/HIX46h4/QIVs4rx94TbgD5ZQTsHPRErB3EvrG8rhg1JWbUlMyc+e3xAQ8+nPD2lbN3hK8JfGMCGAPmlVvR6/Ljv/9yVEpet7i6CGYDw5A3EFE+nTKcXqhpHN7NGPsZgF9O/P55ALsTXTSRWE6pd66W+T4H8BWFsn4O4OdJ1TYByRh6lIwRf/tgQLo2XCm1VtnQWFE45QvudENUVNiM0GoQt13kjGp7u10RxmCBxy9DqW6i99uAx48z3jGpjMuXVUcYrJ/a3S15BkT/LdzI57SfPWqp9L3wWLn/9OhbsuVMxSAZ7fUsGkgby62yBql0PHprSyyy19SUKBt6M9l8SJaTCjHjelx+tMaJn5gK6Rh602njniG/ZBgW73HX8wfw+I3LMbtYHbnqc/sQCJ5dzDMGBII8LyZ40ZsNQ94AFlTa8A/zymVlKp5u6xryRvSZta1VkgHj8mXVEV7yRr0GX7pojjRhBkLv5p4XD+CBKxfjUO8wjvQNw2bSycb5EzjQ6/KhpSq1GNTZQE4nb5nYLHhkIlyGKAtqhS8iCCJ3sBh0GPIGImLbG/UamA3xlwA6rRb3vHggRgc+fuPyuNf1un0oNhtw+bJq6ZTG9re7pVNXBJFtKmxGWZmfW16IK86pBhCSyR6XDxfMcSRlQNXpNDDqdLjnxXdi+sRjNy7HzavmSmX6xoSsyHuf24endsc6Hd2/rgUP7ToSkziKDDZENBoNg9mgVZ7nvhCa5965tgl3Prtf6i9A/siUIHBYC3QRziWPvBIKjbFy7vIZt2HS5/ahQBd653L2jvA1gVGvAeeIkA1Rjxr1Gvzo6iX47mdb8K0wb2I6ZTi9UNM4/P8QMtpumPj9NQCPqFj+pJKsoUduMR19bY/Lh0df71AlKVeiOMipJsRKhTqHBefWlsRtl3CjmnhsocpuijG0KYXjEENPRNc9PN7xNW018AfHpTIYizQ2ix4Dj924HEPegKKRr62mRDpuH11G+Pcayqw5l6wp1QQz6Xj01pfKX1NfGn8AyLaByWbSycqP1aje8b10DL3ptHH/sF9erkb8itek2seddqPkFSvWa+PqRlTacmOCl+h5FlYW4tEb2jDiG4fTXoBFacaujO7D4X0+/P/iaY9RBc/5cc7x4t4TAIBHX+/AxtWNePyNTslALMYyqyo2pRyaJJ32SfW5xecQjTb5MtknCCI9KmwFskfsKxKEL+pzK4xPw8rjEwDMLjLhxo/USacqjHoNbv3EPFQVmTJ+FoJIBrn52H2XNeOHf3xfCqm0YVUjtu3uSmn8U+4TPvzstQ7JA2/IG0BVkUla05RbCzAaHEf30GhGeTJEo3e4J6SGAefUFOG2NQspLBSRFHajHhtXK89zPYEgfMFxDHkD0ITNFfNBpsLtBXLhJBKNe9ORCpsR+7rPhN55VOhN4OyaINyL+KurG2W/5/aNoaHMgpfolOG0RU3j8JcnYgZLcYMZYxsBPKjiPSaNTI7HZ+tofaI4qOnESU0FjYbh/AYHNl3Ritu275V9NtGoVmw2SMcWouMub3+7O2ah8vC1S2XjEIt1F73fbrqwAVt2tUfEEAJijc1D3gDKCgtQVigfTL280BiRkXjYF8TP4hgDcy1ZU7jXc3h9KhUSzKTj0TsZXsDpMMtuwt2XNOGeF86GYrj7kiZVF57p9mGDjmH9RQ1ShnaDLn5bVdjk5bOiUH7ykk4fHxcgGzv64kUqxq5Ik3jPAyDmbxtXN6J/xI9V8ytSlkOlPhzuLRx+BG3TFS2y3zdoNbimrQZPvNkptaWYCEasY3WxCUadNuXQJKm0T7LPr/TcnOfPZJ8giPSpKbGgscIaMTY1VljjngIClMenRDHxTQZNTLidzS8fwfNfuSDzhyGIJIiev5r0Wmx48l3Js1b0ltt6XVtK459Sn3BYC6Qy11/UgLnlVpw448M//vTNiPnL42+EDMfp5skIn5uKXn6br16CWocFtQ5Lzs3XidxkYaUNnUNeFJsNsvJsmThVsvnqJVjkLMQFcxx5I1Php+XETRStBphXXgijIf7p1+lKncOChnIrBkf8cNrtsu98YWUhNl+9BJt2HEKPyweLUd4Ry2LQocRcQKcMpzFqGodvQKwh+Asyn+UF8QxjiTy5UjWqJesZligOajpxUlNFp9PgktZZaKmyyz6bOHF5v9ct7daFx10uNhtwVVs15pRZse2fV8A7No4KmxGcA5956LWIo4iHe91Y5CxEXelZz13Rwy88XIe1QIvvfLYFD+48grWtVdBqgHNrS1BTbIZGw+Ia+cSMxILA434v15I1NTltsknGmpzKiWLS8egVBI5h3xjOeMdg0usgCDzhxCCb3utAyNgpxkASY6v991+OYnld/KOuqaDRMFy8sALb1q+YSMpgRFMCj9XjAx7c/Ot3YwbSeCcGGOO459Im3B0Wc/ieS5VjOqbTx/uH5T1HT434MKd8agZ2QeDoGvSg3+3H+71ufGllg3QcU3weADHPKhpiG0pTn5RE9+EX9pyQ+lD0htWQNwAOHtPH7r2sGQwcHGffj29MQMssO352/Tko0GtRbNZjQYUNf+8czPi0Qbo6PbwPOu3GGN216YpWVBUZccWyqryY7BMEkT4aDcNFc8pQZDKg1+2D02ZEy6zEJzDMBi3uvbQpJia+pSD+KZ3jA17ZsBLHB0YxrzJ+Mrtszx+ImUP4/HVYE4wIuQCExlO9lqUkX82Vhbj30mbc9fz+iD7xzN+7pDKbZ9lRX2rBlx7/uzRPBYAn/96Fz59Xgwf+eEQKA9dSVZSSvCdaX5LBhkgGg0GLNQsr8X6fO0bH331JE/Q6hlKrAUtnl0CjYTkfhiE8QbtWwyJOboshEX7xhTbFkHTTHY2GYdX8Cuw/cQa3PPlujEf1nWsX4Sd/OYZTIwFcvqwaNSUmDI748e1LmvDtKEcsb2CMEl1OczI2DjPGPgfgWgD1jLHnw/5UCCDthHC5gJwxLVVPLh4nb4doIHmn60yMYfP8BkfMjnKi0AaZhj5QmpSL9exz++EJBFFbYkF9qUW2THHiEh1W44k3O7FxdSPKCgsijC2br16C8+od+NsHAxHexuLfax0W1JRYJO83INLDT9w5/9+vrsStn5gf49G8pqkyKUN9oglXrnnRhns997p8qJwwXsbzQkh10ZVq0jvxHql6OoYP6skct+sf9qFzYDQilpz4uVrGTkHg+OOhvpSeI53+Ny4w7DzUg59cdw7OeMdQZNbjV29+gDrHXNXukWte74LAsetwH9r7RiJOD4QnROgf9oErxCYXOOI+r5Kcy/XhmmIzltUUo8/tQ6FRh3Nqi+HxB1EzoeMEgaOx3Ioelw92kx4//OP72N3piqjvkDeAfSddqHdYoNEA40IoD6sa7Z7O+1ZKCvr7W1bi1IgPZdZQ7Pgelw/DviDe7hqEw1JARhiCyAPSMZ4GgwKe33cypbEcAEx6HXYfP42ff+FcDIz44bAW4Nl3unBObfwkW4VGnWwoo8IEoZ+yffqNmDlEz1/DE1WLGPUaVKQYXstsMmBtcwXqSs3oc/tRajXg6b934bfv9Uhl2k16nBkN4Jq2mpikT7NLTHDajehx+dDr8uHDwR609w/jqd3dGPIGkpL36LWpIHDFkHwEoYTBoEXX0CjAOH52fRsGPAEUmfX4cMCDU8MCyqwFScvRVG7qJdvXa2d4v9BoGEb84+gcGMWO/T2SI9+4AGx99Zh0IvLR1zuk05CtVTZsvmoxxgSOUqsBx/pHsOUvHfjRNZaMNgxoEzi3UcNz+K8AegCUAvhh2OfDAPaqUH5O8cHpWE+uTTsOoarICG8g5AVbU2xOaFgKBgX8fn8Pjp0awXPvncA1bTXYtrsLa1ur8PfOQQic4yNzSqWQCn1uH8wGeRf/6NAH4R4btgItzHot3jh2Om4HVJqUX7ywAn9u70d73wie/Huofu99eAbn1pbgvLoSnHSPxhiNNRqGOoclxkA8OjYek0RN9IKrsBlxVVtskPTbf7cPS2YXSV5/cjGENl+9BMFxSIbh6LLDk9zFU0iJPGtzLVmT6PUsF2M4GtEgt7fbBYEDWga0VNvjHs9PNekdIN8/bn3qPcy/ZaWs4TYdA7SlQOmoS+KFZ7KDUToemxU2I9pq7bj+ggaM+oMwF+jw2F874hoDK2wFuHBuOd7uHJLey4VzyxVjYqVjcKwpNst6mdcUmxWvySbHBzwxSSrF45g3XdiAR18/22Zyz6phUHxeUc5PDo2iutiMAyfdODXsx9LqIhgMWkk3AUDvGR9c3gBGx8ZxeiSANzsGIhZooi4rNOrhGxNwwy/eiqnv+osaYNRpJSNxqP7v4v51zbi0ZVbGpw3Sed9ysnvzr9/FSxtWYnmdI0bPi3EXb1uzkIwwBJHDCALHmx+cQnAcGPSMYWxcQK/bixX1ZXH77YEeFx6a0K+iF+NDu9rjjuUAoNUA9WU2fPF//h5h5E3kNaTXamRDGf3yi/FP90zG6TdiZiDOX8X1kFajwY+uWYLv/eGQFHM43dN/ZpMBy+sdOH56BH/Y34uXDvQBQERMU9fomGzSpweuXIzLl1Xj0dc7oNdq8MgrR3Ckf0TabE4n9FQ6OoEgAMBpM+Kt417c9dzumHnmE19cnvRp0amUwcP9bnQNevGllQ0AgFfe748JXUnh00LrbTFf08p55RFjLQBpTWMx6GDSa1DrMGHlvHK83zeMhZU2bPrD+9h7wi27BpFbXwMhm0DnoAcWgw4VtgIppAdtAuc2GRuHOeedADoBnJ95dXIbQeA41OOO6ExOuxHXtNXgmq1n40ptva4t7gRXEDj+2jGA27bvxZdWNmBtaxW27e6K2WX+z2uWQOBnj1bXOkwxRp7o0AcPX7tU8sgrNhtw/fm1uDqsbkodUGlSvm39CuztdkkGbLF+tQ4TvnbxfJwYGo1RwGuaKmXDMMwrL1T0glte54j794Yya8jrr7IQgx4/tq1fIRnj6xwW/O2DgYQedjPZK6Vr0IP2vhHJICdOYueWWRV3/1JNegcAnQMe2Wu6Bj2yxuF0DNDBcUE2uc64oOymn+q771V49j63ssfmrEIjrm6rlbK7ho4bNmNWHENedZEZ5gIdtv7h/QjDbXWRvOE2HUNv15A3wjDAecgwsKymeEoW3H1uHwQFr2CtBhE6LVqHbFzdiMYKq+Ikr2vQg16XD57AOP6/X78Ts+Gg0TBJDkT9KOe9LG5oHO4LxUH/0soG2fpW2U34z53tUjI6MeyNKMOZnjZIJ5xNPG9jIDZUh2iUJyMMQeQ23Wc8+HDQFxOGqLrYg5oS5X57xivvxXjGG4h7PzG5b/jY8fgbnVhaUxTXa+iMd0xWB50ZHYt7v1xL/EvkLz0un+xpxPvXtaDMqsfsEkvG3mrxYnkrrUk6Tnug1QAbVjXinhcP4GsXL8CG37wrjcOPvHI0JXlPVycQBAC0zLKj+8yo/FrP7cfxAU9CWZxKGRwZ9eHgyeGIte2GVY34w74e/PT6Nui1bMpP+uYKB3pc+PYLB7BhVSN8QfmkdOKapsxqwC2r5uGOZ/dFtKvLN4aNq+dFrEGUTiv6xzi+9nTs+m1umZU2gXMcNWMOT3uOD3jQ3j8c4cl1+bJYb9fdCWJNHh/wRHxHqwHWtlbFlHOwxx3hXdc5MIqHdrVj2/oVGB0blw19UO+wSnFPL19WLRmJ5eL4hqM0Ke9xhQw50fVb21qFo/0jMd5/4R082jAiJkCS84LTaBgWOm1xveREz906hwXHBzzwBsal7yXjYTeTvVL63H5ZT55lNcWKi7xUk94BgNGgkU/ipeAFnI4BesATkF2wzo0TUiLVd1+gC+2arm2tkjytXthzAvo4LlP7e91SHDrxHnc9vx8NZRa01ckfw+0a8soax5UMt+kYevvcPgSCZw3njAGBIJ+yBXeFzQgtk9cFqxeUo6WqSNJpa5oqMf+Wlega9MActvOsHNrDj/5hf4xeEo21hUa9JAeifpQzlD7yylF0DUbKjFx9u4ZGJcOwmORNLCskw5mdNkgnnE20LnTaQ6cyRgPj6HWPothskOos1lU0apMRhiByl94zfvzXn49GeAD/15+Pot6xOO4i3KjXyXoxPnZjfE/eCpsRQ95ARAinZELjGHSpzQPC75dLIZCI/CI8RJnDErn5C4hzgX34xRfOVWWcE+N4NpRaY8ZnJVkOCgLmlhfiuy+Fkj6NBoJS3RhLXd57z/glo5xYzt3PH8DjNy4n4zCREINBC6ddXlZLLPqk5oTRMlhsNuDEmVEcPDmMIU8wYajATDjY68Gdz+2PGdvWXxTyIl7RUJqV++YL4WFBTw37ccniKuzY34N/vmhO3DXNVW3VkmEYiDz50Fxli1iDyK2v5U6HijljCgv0tAmc41BI6RToc/vw1O5QcjUx/q1WE+sBJ0wYQcMJH/BFzzmjXoPtb3djYaVNsZzozzoHRjE6No4VDaVoKLPGGAnCk08xBmnn/NHXO/DwrqN49r0T+GDAizeOnUbHqREIE96W4TF9w+vstJugZbHPyZh8/cI91ERjrljX+tKQF1x47OBwL7hEfwfO7lB9estr+NxP/4ZPb3kNOw70oqbYnPDaRB510xlPICj77N6JiakcYtK78DZNlPSuQKvFrZ+YF3HNrZ+YB6NOPuSDaIAOJ5EB2mbUSwvWh3cdxSOvHMWQNwCbUa94Tarv3js2hi9fNFfqNz97rQNfvmgufGPKnk+9CvfocyvLV6r16nOfjbcsPnvnwGhcGXbajbj+/NqIZ7n+/FpUphhrTy3qHBa0VNuxcXVjTH8NNwwDIR0yp9yKjy2owHkNDtSVxuq8cDyBoKJe6nX5ItpbNIhGf09coFkMOhSbDQAgJdWM7gsv7j0h/b5hVSN++0639Hs8GU6FaD2ayPtB9DYO6e/Qu9/6agdu/J/d+OL/7Mb159fCGVY30ahNRhiCyG3OjI7hmraaCF1+TVsNzvjie+SeHvHL6roBjz/udeG6BJCfV8lhN+pj9PvG1Y1xx+hM7kcQYoiya7a+iS//8h1c9/O3MKvIpCD38T3mU0FpfJaT5Y2rG+EwGyTDsFGvgckQ8tGqdZiwoKIQD1y5GJxDWpslon9Yvm/3j8Tv2wQhUmjU4u5LmiJk9e5LmjA2LiQ1JwyXQafdiOtWhOacX/7lO7hm6xt4ds8JBINCglLSo88tL//1pRaUmM+ON2Jc7mjbx3RGDLP3h/29uOEXb+Hm37yLn73WgTXNTvz01WMxa5qNq0NrGKNeg9nFZtl2FTiXQkOIyK1jldZhAge8gWBcGxkx9ajqOcwYMwGo4ZwfVrPcqUaMpaJhDEPeAJ5486zX4ryKwpjdlxf2nMCmK1pjkqOJE9wKmxEv7Dkhxc798Z+PYuPH58WUo+RdFz+GaeQOYHgcXzEExv/75dsR9VIKA7H56iVoctpwasSHsXGecf3USPqm5AH60oaVCa/N1CslnwOo15ZYZJ89WsmHk07Su9JCA8oKCyKO2ZUVFqC00CD7fdEAHR0mIZ4BusJWIBtWQilOb+ia1N69Sa/HPS++EyFn97x4AL+86TzFezgV7hEv4UmFzSjroaxUr3RkeFyArNf4xYsqFa/JJqK3zdwyK5bVFMMbOJsALtP+VFtiwZ4Pzyh6vBca9RF/E//vtBsn4hKGdPq31izAN7bvwfXn1+LxNzqlpJrrL2rA0tlFoUSZYcnsfGPj+PYLB6QFXyIZzibhevTUsD8mVrK4e79l51HJqL1tdxcZYQgixyky62U9gB9PEMu3vLBAVieWWZXHTCD9RLwLK23oHPJGzAOqik1YVGlLeL+Pzy/HL286D71uH5w2I1pm2fNmnkVMHXIhyjpOjSjMl+LLvRqIfSf85NPY+Dj+/dn90jzh7kua8LNXj6HWYcJXPtaIr4eFJEs25J2S16fc5n+qyZ+JmUFjmQ1dg6N44MrF8ASCsBh00GhCDhTJzAnDZVDuNHV4qEC1ZbDCJj+2VdqNmF8RGm9makjJRPldtu3uwn9duwxnRsckJ6YrzqkG58DAiF/2BKJeq8EHp0ag1TL0uEK2kPLCWB2kZB/SsFA4nkzzsRDZRTXjMGPsEgAPADAAqGeMLQFwL+f8UrXuMRWEK5Vis0EySj3yylEprkq0kN+2ZiEuXliBxdX2iGRtInUOC25bsxCbdhzCTRc2QKsBbCYdNl3eis1/Ooy1rVXQaoDzGxyYV2GLiNmSqAOFG3m3v92Nr108T+qccko7PJneImehlNE+fBGwan4FPhzy4DufbcHtvwsdM3hhzwl8/eL5UnsUmw24qq0a88oLpV1vUenKGVWTTfoWnYU3UUw6sW1ERRe+kEkUvzOe8TffB5f60lA86uiEdPWl8ZWxmJDLGxhHoVGfOCv6OPCffzoiGTsFHvr95zfIL17TMUDXlFiwaFbIw8LjD8Ji1KHQqI1r6E41dmsgKESEYwFC3qNj48q73y2z7Lj3smbc9dxZQ/e9lzWjdZaykbCm2IxbVjUmHUO4ptiMH1zZivb+Eek9zi23xo053D/sk32WUyM+2TjQk4FGw1BXqhzvOl3qSy1orrLHbB6IxlqNhkXox42rG/Hk32PjvX/94vkIBHmEIXXIG8CCShv+YV651A9EXRUMCtjyj0uTluFsbzSJelRJXzaWW/Hrf16OcQEYDQTx8OeWYWGlLS90GUHMVFzeMcwrt+JLF82Rkp7+9NVjcHnjew47LDrcfUkT7nnhbEzIuy9pgsOSeAmQTiJeg0GLNQsrsdfuknRc6yw7DAmSxgaDAl7Y34N//93ZOIf/8dkWXNY6i4xYRFzEEGXiRi9jgMmgjXE+uPfSZiyqTN4IkclYLZ58EudZEfMEmxFFFj3qS80w6bVS3hogtZB3yc47g0EBz+09SX2LiEGn02D1/AocOOnCCdcoSi0FqLAXYHZxcrIeLoPiibzwfggAQ14/fL4gfn+wV1UZXFRpwb2XNksh/WodJtx9SRPGxwV0DXmlMJTTOaSkqKN6XT4U6DRw+QIotRrh8gYUPXgXOQvxqaZlGAkEcWZ0DPWlFnw3LFnnD65sxT2XNuHu5w/I5me5c+0iDPvG8KeDvfjaxQsi7ENGvQYt1Xb88KolsjGH60tDzkCZ5GMhsouansPfBrAcwJ8BgHP+HmOsXsXyp4RwpSIm5wj3HhONS9FCDgAHe4YVjYlicrXwa5ZWc4BB8jje+moHHr52qazBVoloTw+zQSft3kQfo5ZLpidn8NRoGGodVswutmDJ7CKpzjXFZnSf8WJ5XQk+GPBGBC4XywHSz0opZ5D96XVtip6TiQy48bxgEl07HQaXQJBHBO3ffPWSuN9PxyA+6PXLJr4Z9PoxB/LtpNNpsHh2sWKMYTk8fiHGyyIeqXpAzSoyxgyGG1c3RhzHj8Zg0GJd6yw0lFqSXhCnGnO4+4wXPS5fxHu89RPz0H3GGyd2tPyzTFVYiWyi0TCsXhDySm6ttmPENw6nvQCLwoy1ohz0unywFmjRWl2Emx77e8Q7eOCPh3Hzx+bigT8ewdLZRXhy/XlxZSYVGZ7MjSYlT3OTQYs9H7oiZOKHVy3Bp5rzY7OLIGYis0uM+Nx5kUlP776kCbNL4uvyvuEx/OZvnfj+lYsxGgjCZNDhZ68eQ33pQjSUZ6euBoNWMda+Egd7XZLhAAjp4n//3T40llvQWi2foJYgAGCW3YRahylm/vnAlYvxy5vOm/ByK8CiSguspuRPC6o5VsvNE2odVrxx7HRcp5d4JDvvpL5FxEOn02BxTTEWI3VZCJdBbyAo2w/rHM14u3tIdRm0moz4dHMZ6kqXY8g7Bo8/iP/vV+9E9NeyQkPa/SvXkdNRodOAB/EvF82Bw6KXXQMsctpwqDfSRvWdz7bAYdHDZAg5XPW4fLjpwgYsqCzENybmHECo7e578SDWX9SAK5bV4Ju/3YtAkGP9RQ2YV1GIhZU2yfFsQaVyzphM8rEQ2UXN7cIxzrkr6rO8D+oS7XnV4/Jhy86jMBm0UnwpuZhTSsbE4wMeAPJxqrqGvJJhWLzm5l+/C8aQdLzJ6LKbZ9lj4l6JyHkSh9cxXrkNZVbodBrUlVpRbDHEBC4Xy/ngdPx2iIdcG97x3D5suqJVNiZdojZXanele4Vfm+/xipNpGzWuYWCyx14Z1DM4pVMvILXYrUqhGOI4DgMITbBKLAbpJ9FueOoxh/3Y/PKRiHptfvkI+tzK8eXSfZZ8RaNhqC+z4iNzy/DJ5kq0zi6OeA+iHFwwtxRWo14xq3iZNXRcrdZhSUn/JiJd+U0HubiHd65dhPa+kRiZ+NrT2akDQRDqMOwbl7x/gYlwRy8cwLBvPO51FTYjjvSPYMNv3sVt2/dhw2/exZH+kZyL8ddzRiFB7RmKn0rER6sB7lzbFDP//PozewAAlyyeheX1jqQNw4DyWP3BaXXHSaWcL8n2T3Ej5jOts9BWVyLrkEB9i8gmogxe0FCKb1/SLBtawj0qn/smUxm0moxYXu/A3DKr5L0qln3rU+/BoNVM2xi3cjpqy652rG2twr0vHsSCSpts/P9h/1jMdbf/bh9ml1iwvN6Bhc4i1DmsePT1DhzuG5Z9bwIH7nnxANa2Vkm2sa8/vQeMQbKNpZIzhsgd1PQcPsAYuxaAljHWCGADgL+qWP6UkG6c2mijj3jE4kjfMADIeqAlCpkQD6WjT+Eek4MePxrLrZIBWi4JXvT9kjlSpVTvQY9fMVh8Ms8kV27nwCiqiox4ScYDVPx+9HGWQY8/rXuF1zPfs2inI1vpXDPo8cuGMBiMkwAk1WN7mfSTZAlP7Bh+j3ihGNLxMklVrtJJLJjOs8wUwpODRr8DS4EOm65ojRvGRxA4PjjtQeegB5aJnfFZNhMO9bkVY6opyW+fOzteDPMrCvFfn18GvVaD/SdcGPaNwRMYn7aeFPnElZ+/AT2nhmI+d5YV45lfPTYFNSJymV6F+VRvnM1BIPWwSlOF2aCV1cVGQ2I/lnzOCUFkzodDoxjxy8+P4iUFjofSWH24z42jp4bhtJmwSIW4vdnsn2K/MGXQtwgiWXQ6DUbH5Puhkn43G+OHG0qGQGAch3rcCuuj8bwY/9JBSUeJJ8W7h0bx+Btn82RxDrzVMYA6h0X2uvd73eA8FKJP1EuHe92y743zs/cKL4PWEfmPmsbhWwD8OwA/gF8D+F8A96tY/pSQ7qAdbvQRs3eGH7GQMxpFXyMmSDLpdRExfKMRjVKbdhyS4hWfW1uC8xsc0Ok0ETHjlgkcLVV29A/7YNLrIgKVA5GGqWSNXUoGLqNeC42GpW1UVSq3xFIgG5dYw5jscZbG8tBzR7df+GIiPPxGdD0FgUPDEBNTJ58Gl3SM2+lcU1Vswo0fqZO8W8WwB1VF8teI2VSjYyGvml+hmkE1/F7JLh7TuYeSl/z8W1YqGmFris2yCfmUYgink1gw3zc2MiXee49ODiq+gzvXLkKFvQBLq4sVZcTnC2LPyVBijRKLHo++fhSfaqnC38eHcOdzke9z3eIqaQGppGvMCeJxpvPc0fp74+pGAOklOyXUp+fUEGZf+a2Yzz985rtTUBsi11FKvhMvGSuQfmK5yabYYsA31yzA93a8L+msb65ZgBKzfEJbkXzPCUFkjtNuwodDXoX+kd64pjR3er93WEroGj2+p0N0/yyzGqHVAH/7YCDtjQ6fL4h9PS70uH3QMIbtuz+UTeScqG8RRDSJ1lIVMgnKjHoNDDqG2z+1AN/5w1n9/o1PzofbOxbXxpGIYFDAW50D0Grl7Q0VNiPOq3fk/PiXDko6ivOzdpghbwCPvHIUQMhR8eufnAcorAEOnBzGrU/tkcbPNU2VWOQsRK3DEmH/2LCqEU+82RlypDFo8ZWPzQVjQGWhAVrGsGN/D5x2ExZWFKLbNUqbtnmGasZhzrkXIePwv6tVZi6Q7qQ63KisFL4hOl6teM2mHYciDJxbX+2IO9E9PuCJucao12DTFa24pHVWTPxg0bAqCDyu4TvZOLtKBnSPfxzf+8OhGMPLdz7bkpRRNRnDfHTCwLvWLsK/RtX5tu170VJlj6hz9GKi1mGKMdJtvnoJaorNkuH9H8+twQNXLoZWw9BYblXtmHm6pGLsTGeTI51rxse5bNiDFfUrZL/fNehBe99IRAzdjasbMbdMOVlZOvVKdfGYzj06Bz2yO7Fdgx5F43D3GS+8/mBEVnevP6gYQ7i2RN6YXFuinJAuX7zGskGi9y6XHHRhpQ0Feoal1cWKC75AYBzP7+uRkmAY9Rrcc2kTxsfHcedzByPkPzxTMwAExsdjdOKGVY1xkx2mg5z+fnBnu7QgjF4o/vCq1GSCPPXOcuTw+/jIxfK5d8kLmFCLAi2TksSE650CbfL9judwsLeGEjM6TnkixsMSiwENDuXxDUh+rkpMX5qcNvS6R2MSLyZKChyPOoclxilk4+pGPP5GJwD58V2JROOluDarc1gy3ujw+YIx85O71zbhjwd6sP6iBlTZTTjhGkV1sQkLKm1ptQ0xM0lmLSWXJPHuS5pg0DEUWQyR+t1swM//rwMLnLa0dfWBHhfOeIP4wR/fn4i32yU5yi2rKUZNsTmtxKr5gNz6TmyDjasb8dNXj0XM9a9qq0bngBfPvRfrFHPfZc3S+j18/KwrtaK6yIw5pRZ0DY2CAdj66jEMeQP4/pWt6HX58OjrHZhXbsXnzqvFdT9/K0L/PvX3TuzudNGmbR6hmnGYMfYygKs452cmfi8G8CTn/JNq3WOqSEephBuVjyjEa4l2vRevqSoyppS5ts/tw9rWqhgDtJxRVKmOcobvZI/vR5dTaTNiXADa+4fROTCKJ948e6TBYtDCaTfibx8MwGkPfa9/WHmylMgwH50wsL1/JKk6Ry8mOgdG8dCudmxbvwKjY+PSvcIN7+GGlE1XtE7pIJOqsTOdTY50rjnpkpeZHpcfrTLJuvrcftl4uMtqihWNwxoNw8ULK7Bt/YqJo/tGNDntceuV6uIxnWe3KHqEKqvZPrdf2kUPv2Z+pU32+buGvHjyrYnEQhPZ6h/7a4diArt0n2W6kOi9i20zv6JQMWmCHHtPuqSFl1ju3c8fwOM3Lse8civ2nnBL3/WNCeh1+aQkNA5LAbbt7oo45rVtdxfWNFeq+uxK+ntBZSGsRh10jKHpunPgGxNQX2rBnBQ2u8hTL5Ig18h6AAPkBUyox0mXH++fPIP/uXE5Tk3o8h37TsBm0mNxnOvypb8e6B3Gv4Xl3QBC4+ETX1yOc+sditdNRqgpIrfR6TRYPb8C7f1u/OIL52LQE0ClzYiWBEmB46HRMCyrKZKMWYur7RA48NXVjTAX6PDTV49h7wl3xPguRyr9T42Njn09sfOTe148gO9fuRgbfvMuHrl2KVY7y9EUlqiXIJIhGfkUE9TNKbWg1+1DicWAIpMOI/5x/Nszsfr9+1cuTltXByZCpHEAX794AV451Iv1F83BfS8ezOmxTi3C13d9bh/0Wg2GfQE89I9LUWjUY2lNESptRly8qBLt/cNwecfw4ZnRGNsM54BBy9DjCoXgKTYbMDDix/EBD+xGPU6cGZXGZtHJb1lNEYLjXHqnX7pojpQsFwjJxl3P7cf3r1yM3Z3v0qZtHqFmWIlS0TAMAJzzIcZYlvIg5weiURlI/givRsPgTTIepLgTrWEsbvzgOocFXYMe9Ln98ASCqC2xoL70bExiJcN3KsfR5Xa9b1k1F0a9Bj0uHx555SicdiOuP78WN/7P3zGv3IprltckVOCJDPPRi4LAuJBUnZXiGY+OjWNFQ2nE99IxvGebdCaQmeycJuttZDPJG0itCjGlvGnE0BUEjj8e6ktpoZvJ4jHZZ6+wFcge24t35DfVGMIDHj9WLaiMyFa/YVVjwrja03XXPBHJvHcxaUK8+MuCwCUd6vaNwTcmyG+CuH343Hm1wN86JQOxUa9Bpf2s/hG9lbPtya2kv2sdlozlQEn/zL9lJRgDeRMTRBaoKjJinrMIX/jFWc+cuy9pQpU9/rH5fPGsVYqpHC/hKkChk4gQOp0GC2cVqVpmTYkFCypt+PnrxzC72BThtX/32iYY3umKGN/lSKX/iXOWj80rxRcurMeQZwwlFj08/rGk66zUj0YDQRj1GizMwEuTmNkku5YyGLQ4p64k4nsv7Dkpe60vEER5Yeoe7IHAOJ7dezLCQ/mRa5fhK79+J+fHOjWJt76rD/uMMeC5907AOhH7WbTNAKHx8usXzwMQCj1x40fqJA/gDavnRoQg9Y2FkteJDlri56MKMd9Hw9az2di0pVOM6qOmcVhgjNVwzrsAgDFWCyCHD7BlTrICmeqxbqWJbqXNiI5TI+hzh7wlD/YMnw2ncMkixWt2He6LyE6fyJgmPteAx49NV7RKCeySMWKEx1395Ztd+NePz8OP/nREOs7w4M52FJsN+PJH52a8WBEEHhG/02k3wmLQ4s61iySjc63DhPsua5ESUojvKNnFRIXNmFTivskmnaRWwaCAAz0uxURZ0aTjbeS0mWQNpLPsJtnvl1jkYyjGi4OWTmzfCpsRbbV2XH9BQ4THrdLiMZ1nrymxoLHCGnFkqrHCGjcecKoxhA1aTcxGxZYJj/fpgNqDfLL9PBAYx96TLvS6fCi3FaDSXoDqotC9BYHjtaP98PoFHOp1Q+DAefUlsuUWmfW4bftePHDlYtz8m3elsB8LK2yS7q6wGXHxwgrZpJpqUlNsTll/J4uS/jnU68bXn96TdJ8hCCJ5/EFBOjIPTHgEvnAAT3xxedzrMtkcFWOX9rr9qLQVoMVph9GYeOmQji532tOLqTwVoZNoQTozED3zyqwGyVgCnPXGffSGc9HkjB+2Qqn/HexxY8QfRGGBDj0uHwp0GgSC4/j1l5bj1EgA73QO4and3RjyBnDvpc3gACwGPbQaoMelLHeVCrHJLQbdjAkpRmQHcU49r9yKL100B6P+ICxGHZwJNkgAZbmsKjbDaY2v4+XYe9IlGYYBYF65NWnnuplIncOClmo7GCC7TheEkMnuqrbqiPCQApe3gex8vx9V9gI8/Lml8PiDqHGYZd9vYYEu4neTXos3jp1WZdzMl1NR+YaaxuF/B/A6Y+wvABiAlQDWq1h+TpGKQKZ6rFtuovvwtUslY3D0Tk6Py4cfv3I0wigq1mdcAPZ2u2J2fZQMsdExfG+8oBZbrzsH4wJHTZjHsVKbvN97Nltoj8uH//nrcdx0YQNaqmww6EJK4/Jl1RHfEwn3dE406Q5PwifG1xFDPxSbQzGNmqvsGA2MY/0Tu2PeUbKLiTqHBefWyhuCptIrJdWkVsGggGf3nIiJVRsvkUY63ka1DnkDaa3CZFTgAu5e24R7Xoz0xuBx9pW60ojtW2034foL6nG0f1hKfHf9BfWoVjBap+uZvWp+BRpKrUkb/VKNIaw08fEGxhXvkS9kY5BPpp/LeR/cc2kTZpd4saK+DF2DHnQP+SJ067wys2zsz/95/QP4xgSMCxyPXLsU1cUmLKyw4U+H+2WfS4z9rraRQfSu3/zyYdz8sbkoLyxApd2I2QqJDlNFyegeHkJpJnhsJEO8eMTtxzoQ5zQyQUTQp+RZO5wdz1q52KX3XtqMS1uccQ3E6epyk14rq1cTJeuc7NBJtCCdWWg0DH3D8n3vjDeQMDSDUv871DOMrz+9R4pjPOQN4O61TfjvV4+ic2BUOhn2xJuduOv5/fjJdedg56F+OCwG/PgvHRjyBmTlrsVpx72XNsf02+ZZhahxTG2uFCK/qXNY8JPrluHkGX/ECcb71zWjym6O2xeaKgtj5fKyZoz4/djX60ZbbUlKstkbtunSWmXD55bX4mj/cM6t13MFcY36lyP9ePyNyJASj7/Rids/vRDfv6IFhSZ9jK6Ta1ObUQfGtPj6hBy01dpx76VNuCv8dMUlTRjxj8FpN2LIG8D965qx4cl3Jf2WjKNivLVRvpyKyjfUTEi3gzG2DIDowvZVzvlptcrPNZQEctHGlRB47LHa8LALxwc8cbPQyk10OQc+89Brijs5e0+4cWrXUfzqpvMQFLgUPqJ/2Ke46yO3kyY+V7HZgOtW1GLzn9olI7FWw9A54EGtQ95IfHzAA46zSsRpN+LyZdXQaoAyawGKzAYY9RowFqq/kqdzMpPu8PZ/4s1OfOvTC6WBqsflw5adR2WPQoQrjWQWExoNw/kNjqx54KVLqkmtDvS4JAMkkFwijXS8jTQaho82lqPMWpBUPGANGP771aMRg9R/v3oUW65ZqvjspokjMdGyY4qzgDxyahgnhkZjEt8dOTWM5qoiVZ5dfP5Uwjd0DXnx0K72iOd/aFe7YgxhpUVGomzc+eDllO4gH+/ZkjEaRHsf+MZC8YO3XncOjg94cGrYLxmGxb//22/3495LF+GxG5ej1+1DkVmP/3n9A7xy5DSMeg20GoaFThvqHBbsO3EG7/e68aWVDdj+djd6XD7pudRIPhOvLYvNBmgYi5ispVO+IHB8cNqDzkEPLAYdKu0FMUb37362BeYCHTZd3hIRj3Gme2zEi0d88P4bJ7k2RD5TruB5VV6YHc9audildz2/H/Wl5rgxgNM53QMAHae9/z975x0eR3Xu/+/ZXrS76tJasmTLlpuKjRE1lGATArlyCRiTwIWEckkj9oV0Ajg2pBC4zoVAQkgFbgokBLD9Cw7BhhAu4QYbbFnCRW6SJauX3dX22ZnfH6sZbZnZplWz38/z6LF3Zs457zlz5pR33nlf7DzQhZ/dfC6GPUFpXDXrNKiRmacj4XkBLl8Qw54gjFoNeF6YsDmONqRnH/YM1l6JvsIUlb6+YDjOxu2XVOHJN45i844W6f++YPjLMPH3eyeH8It/HMfGldW45aJKPLzzsGy/Mxg0WF1nx9xCE3qcfpSkYfFPEIlQqRhyDTp8bvv7ae0nAaC1343XD56OGt9/++4JVJfk4pdvN+F7n6zDNYtLYDRqk8rBcTwKc8bmQ9HfbZ5JF7c3nur9+nRCpWKoLDBjyBOQXEoA4bHsULcLT75xFBtXzo8a617c2xFnaXx/4xJUFZpw62/2SNftaXMAaMevP3seep1+FFp0ONY3gqfePoH/vmFZeNwbVQwDqRsqKu1dxPGVLMWzT7ZnCj2AwdF8lzDGIAjCW1kuY1JIpkyRUx7lmXR4v304KrJtZGeOtcq9vqEcC4otWGy3RilbY8uuyDPhraN9Sd/k6DQMHcPeqAXIz29ugJqFr80z6XDt8nIwFracLJVZ1Ij1unZ5OR7fPeoC4rIqeIIh3PncXviCY64atGoW1TY9Th86hjxRlrziAP30W8fxxI3nYOv6ZTjc7cTLMpEyH76uHiEeKS26I9u/y+GLslgTfRuX55lSGjQifcrK3XeNRoVV9bNQV2abNgG90g1q1aUQKC5RII0SqwGVBUY01peBjVZ1+/7OhG9g0/UHPOgJoG3AGzVJiceV8AXlFeO+oLL17JAniD+8N9ZeAPCH99pRWyb/OWAmdRfrn44SttvhQ4Ab64CMAQFOUHQPkskmn+cF7D7cg6YOh2Q1XVduw4qFJdNKQZyJQj6VBUQyhX23QrlDniB0Gp+itXbHcDidUafB50bHRvFNucWoBgPwlwNdaO114Y+jn4aKG8Iuhw+9rrCrm2wpGSL7nooxabyPdUPy8M6DKLbo0T/iT+heRsxvxB/EiC+EzmEvSqx6tPY4MegxINekxo67LsGpIQ90GhUYgOZOB379zpgFVOnhrqx+QkYQZzO8EJK1rBWExF+OZBLEFcjcUrlNYcPWNqD8dQ8Q/uz4nycG8caRMbsSg1aFL14xP2F5HMfj1ZYutPaOgBeAg11OtA+6cU2NfUICbvU4fVHraSC8gU5lQ5quey9ielA3y4Yta2qjvjDasqYW9bOi15CR8zAXEvDYrsP46MISVBaY8MvPNKDb4cPxfo+0DgDCz0ZFvhF3rZiPF/d2gDFIxjWMAQtLLKgsMEIYNfR5bFcrHlm3VEor1+8MBk3CFzgEkSldCmvmRPtJnhfQ5fDhtQ/7caBzROrbyysLUJlvxh2XVqFtwI09HUM4tzwXJqOya0GeF/BBxxBGfEH88Lp6qFQMgiBIxmGRgdbOn5OHS+YX0bozArl9pLg3AYAX9nTge5+sw70vHZB0VeV5RvzqMw3ocfmRZ9LhSLcTvaPrg8ixCgAcniDUaoamDgce29U6argWgkoFSTEsksxQUWlvJO79Dnc7yVJ8Asiacpgx9jCAGwC0ABDvkgBgximHA4EQ/l9zF741quSVU4YWW8beIosPxuJSi2ReD8R35lir3Of3tKOxvgxHel04rzIfF1UVQKViUcqOygIjvryiGqcGPbJvcv7wXjgPtQq4qKoAt/7mvei3ea8cwLeuWYx7r1kEdyAU9eZnYakVFfnRm3WxXoyF0990QQUGPAHJ4tJuM+CGhgpZVw0lVgO8gRBe3teJr1y1KC5q5V2/+wA7N16KJXYLKgvMeGzXEdx+SRXUKqChMh8XVxXgvbZBWaV7n8sfpSw36+XdKkQqs4/2uhQVfHJKpSduPAcBTlBUNE2ngF4VeSZ8eUV1nDuCCoXPxu02o7yldgI/UemWAaRvUWPSaWTvkUmnPDTl6DWyivFH1ynHa+d5HjeeXyn5vzZoVbj7ygXgeXlL64o8E7561UJps6lmwFevWpiw7pl8amrWqXHLRZVxvp+MWmUraK2aRbnt0KoTL3raB91o7RmJs5qeX5SDOYXToz8DiBpTRQxaFYpylPtoNiy4lCyC8kxa6asNufNL7FZo1AyXzSvCguIcdDq8KDTrUWzV42jfCK55/B9xC6/Hd7di48pqeIMheAIh9I0utMRNoliHdN96y/W9e69ZBKNOEyW3OH7/+y//L+qZFt3LxG5st+8/hfOrinHfy2MvPDc11uCX/ziGT19QiX5XMCqC8caV1fj8ZVV46q3jeOqto9i4cgFuePrdrFpFEzOTdTd9Bl19Q7Ln7EV5+NNvn5lkiWYeRq0Ouw6eiLO8+tIVCxKmyySIK5DAUjmJf0idRiWbTpdECVpnt+GxG5YhGBLgHvVlqVUx1CXx6Xqox4kOmS+DDvU4Zb8MiiQTZW2p1SA7b5ck2ZBm4t6LmB7odGqsrZ+FqkKztBepn2WDLuKLtdh5uLLAiC9+dH7Uy5wH19RiR1Nn1Jxv0KrQPujFL98OWwWbdWrcfGFllAHEpsYavNbShS9dMR+MhdeO4qfakYqQTH2EE0SqpLufjFTkVRYYJcMxMTD93RHzUlluDT7UulBbGt9vxb7N8SGcGvJHvaj57to6VBYY0TbglQKtGbQqfHTBBbTejCHyi8q2ATc+ODUc9bJKp2GYX2TGz28+F70jAXx7VEkcO+c9uKYWDZU2rFhUGjVW3d+4BE+/dQxfuHw+Hr62Dmp1+GtKly+ILauXIM+sh8fPod/txwt7TsGgUeNk/0iUH/VkxkKR+jSyFM8+2Zwx1gJYKAhCYpOCaQ7H8fjf4/2SYri+zIobzo9Whj5xY/iT93uvWQRfMASzQYsHd3yIr121UFKgiparHj+HgRE/KvJMkjXFtcvL8fyedtx28VwMeALgBWBP2yDcAQ7VxZYoZUdjfRnue7k56gFYUJyDOy+bB7NBjY0rF0iWyjq1Srb8Eos+rBQY3aSLyuxD3U6U5RpRVzZmQaJWhR2V+4IhVBYYUWI1oG3QI8kjWqJFOqPnBQGnhtySs3ODVo2jvS7ZB7vb6cOFVYUozzVhXpEZA24/rAYdAhyP9iGPpCASrTIsBjWsBi0+Mxqdu7LAiK9etRBD7kDUZw7vHuvDdz9Zh7YBt6TMXlCcg89fNl/yZ1tZYMR3VtWg2+GDyxeMUypF+maObaMauxXtQ55p81l+x7AHOjXw9M3nYnA0mvGwx4+OYY+swq/GbsX3P1kn9WvxM/BEgTRODrhlXVEsK8/F/BKLbBolixolS9hSmx7/eeUCnOh3S0rY/7xyAUptypvPET+HL10+Dya9VtpAVubNgzsiImosuUadpBgW6/Kj14/g+f+QD+R2asgju9k8NeSJiv4a217pKipHApzUh8U0j+1qRX25/H053jeCL//+g7hF2Y67LlG8J91Ov2wZyyvypoVymON4tJx2YNAbkN5WR7b5iYERRV/nmbr/iFSC5ujVeHBNLZ54o1V60XbO7FzkmjQozdHBoNfGvWX/3ifrsNhuwey8sFxLK/KwFOHP6Y71juCu330Q1d7ip6H/ONKL6hILmjqG8X77MLbv78QtF1Xi2X+OLczSfevN80KU64q3Dvdi9bJZyDfrYTVqpAUzAFlL4vtebsacAjMECDg97Iv68uQnNy7HF2MiP2/e0YKf3XwuXF4u7mXoY7vCyu9rl5cDgHQvxfP06XVqJPJT3H7yOCrmVMUdn+4K1q6+IUX3Gqf+9P1JlmZmUmO3YtXScuxtG5Lmy1VLy5MGxMr0JZpeo5INXKPXJlZkiuvI2HTqJPpPlYqFI5ZEwpB0raX0ZVCdwpdBIpkqa12+oOyc+pF5iS01M3HvRUwfVCoGrZpBrWKwGVXY1zksuW1YXGpG3wgXt38TFcNA+H7f/0oznrzxHOyP+JIr36TDU6Nrzcd2tUrn77g0PM6/uLcDm3e04Ikbl+Ou0flYfKbK84yS0UKmPsIJIh1q7FbZWClK81CkIu/+xiXS/yMD09ttBtx0QQUEAC4fh70dQzivIh86nRocx+NQtxMHu114/r02fOWqRXGu4L798gH89Kbl+MJvx54POct+Ikykq1NvkMfQ6Ne6okHi+qffxe2XVOGXbx+X9Faxc979rzTjl59pwO3PjLmWyDPp0OP04YuXz4efC6Esz4jTw17YjFroNAxajRpfi/BV/eCaWjR1DEOlYnjyjWOSH/Xq4pyExkLi3i/WUvzS+YU4b056vquJeLI5WxwHoAUwo5XDLV0OfHBqWBqsIgcvINzxfQEev3nnOK47twL97gC2vt6Ki+bmY35xDioLjLjt4rnwBEPSAyA+bKK1K2PAp86rgCcYilM+6TXRD4NowSs+APdeswh6bdgBuPjgim90Fox+evSly+chKCDqAXx03VKpTuIb6TxT+LONHqcPJRY9PMEQvMEQnv1nG75weRU2rarB/lPDklsKX5AHY+GIoJ8+vzLKGf2WNWFn9CsWlmB+UQ56Xf4of79AeNAxatV47+QATg/78Nw/T+C6cyvwxd9+IH26UDvLhp/cdA66HGE/n7dfUoX/HvV7fMtFlVgyy4q9bUN4+q1wvW+/pAoWgxoWgxaP7zqCL14+H6eGvfAFeVy6oFhSDIsWc+LEsWHl/DilkuibObKNfEEe7xztw6cvmCO9PVNyBzKZODxBuAMCvv5i9OfsDk9Q9vpgMASTTo1H1y2FO8DBrNNAq2YIBkOKm6ATCp+GnhhwKyoiLQYNbv3IHCnSqUGrwj0fWxAVrTQSng+7Voh9DhQMegEANqMWQ54gjkQEl5tTaIYtgZ+qAXdAti4Dbnn3FacdXtnNZn25TVE5nImi0uXnZNOM+OQ/E24bdMsq39sGle+JyxeULcPpk+8rkwXPCzjeN4KWLid6HF4IYGAQJKtoMUjCkCeAvyj4pFIKzJjM9Umkdc+W1UtgMahx52XzooLO3fOxBWgb8OHKBUVYYrfgmVvPhyfARQXm5HkBJ/tH0OP0w+3nUGjRo9flw72fWIRCsx4uHyf537UY1Ljh/Iqozd2GFeGvP65vKMfju46m/NZbtHbrcfqg16jxwLZmtA14UVlgxBcun4/vbI8OCPHU38MBbtQqef/zb7X2IcRDWgiKx/d1DMteLyqn5M6V55lgHPVflsrzMBP8YU82yfwUy50jBeuZj0rFYDVosKDYIr0YtejVKbiHSO+lrUjnsFc2cM2cAlNCZaZGrYJZp476wsWsU0OTRDt8pM+FQXcQm2PGL6XYACI8z0cZW6gZcNvFcxFKtJAA8GGXI8rnPxD2+b+gOAf1Ceqn5Iqo2+lHfYLyuhXce/U4fEgWmZLGyewQCITQdNqBbqcPdqsBdTHWv0pEvki4aG4+rq6zR1kEb1ldi8oCg+z+LZKw8sSPV/Z1orG+DAIDSmwGFOWEvyDKM+kw6A5K59Uq4IHGJfjpm0fRFDEfR76MbR/yoKooJ2Mf4QSRDhqNCmuXlqG6OAfdDh9KbQYsLLIofoERqcjrd425rhQD09ttBnz24jn43b/a0Fhfhs5hL5aW5+KdE/3IM+ow6PXjg3YHXtnXiS9cPh/tEQZrIr4gj0F3EI+uW4qQIGCWzYClZbkpPdtnM5FWxINuPwAmfVkYOX7FjmX1ZVbccdk8DLqDeGTdUvz8rWPoGwlE6ZduuagS//Hsnqgx8sW97XEK5jsvq4JRq5b8qD+88yDu/7cl2LSqJmotsHl1DfpGvGAs+kvTSEvxa88po3kxC2RTOewBsI8xtgsRCmJBEDZksYwJp8vhk4KlRQ5eACSl4elhD267ZB7ueWEf7ri0Cr4gj89eMhenBtx4oLEG+zuGoxSjjfVl+PHuVnzlqoXYsKIaKgaU55lkra6eve38KHcVC0ssUcqPykIzPvfcXuSZdKjIM0ouKgBgy44W3N+4BEFOkD7TEPPuGPJIdRIf3NsvmYvn3j0Jg0aNDX8IW7ptXDkfOg2DN8jjaM8IXtjTgc9fViW5sFhYYsGikrD7jMjNRueQR/qEb05hDiryzXjixnPQ1OGASadGVWEOHN4gbhh9G7WjqRObGmvwxd+9L31a8uCOD5Fn0mHTqiXS/8U6iq4iIpUS4oDwpSvm479fDytyTw17JWV25GAWazEnFxAvZzTQWeS1dptButdiW4vnlHwvTwZeLiQNmuI93ry9Bb+59TzZ6w/2unC83x1nyVNk0WN5Zb5sGqNWIfBbApcH3kBIUgyLcm392xGcc9v5stf3KFi1nlORp6iEhSCvUJ6Tr+zyQZ/mZ67BEI87LqlC34hf2mzecUmVYsA/IDO3CPmjQRpj0+SZ5BXdeSadrPI9L4F/LptRK+u6w2ZIHvRhoohV0IrBI++4tApP7D4ad/2pQTc6h73wBUOoKjCjssCM1w724OGdBxN+UiS3oW4fdKNj0I1H1i2Fx8/BnmvAntEXTrH99s7LqmDWq/HFCGsE8cuRQY8fLl8QQ54g2gY8Uj9ZMsuCslwT9ncMgxfCbf35y+ejKEeHu34vb1FcnmvErz/bgMoCc9JxRM7a7f7GJXD5guBCgqQYFsvYvL0FP1q/DBwvwGaUV6aHePmNrFLgUPF6uXOHul345dvH8dS/n6s4fog+iCvyTBl97k7Ek8jaeLpbFROpcWrIjdMOf5zy9NSQG5UFykpeq1Ej6wbBmsSaMM+skw1ck2tSnm+A8FrKZtKiP+Llq82khTnJRt3l42TXNb/+rPy6RqqfQQt/iI9aE9zzsQWwJpnjBj2BqNgY4gu7RDEPgHDMB7k5Nd+cuF2U3KGZFF6ei2TisioyLSmVwwQCIbzcdDrqc/QfrqvH4lIr+kf8iu3D8wL2dQxLc+5tl1ThP57bE9VPH9jWHLV/E4n9fX1DOX721rG4fnd/4xL07T6K6xvK8cQbrVEvOw51O3HrJXPRHeGKQiy3yKLHoNuPqqKcjH2EE0S6aDQqLJ2dh6Wzk3+BIQbSXlCcg/I8k7Q/j9S1/O5fbbihoUJyt7m/YxjnzM5F2+AIcgw6LCq14CPXLcXXX9yPr161SPY502pUuOv3H+DxTy3DuZVnnvXoRIzlsa7k9scYhES2s/j/+jJrnIHgpsYaBEMhfO/VQ8gz6fCtTyzG0V5XVCDuB7Y144frlmJP2wdS/nkmHZZX5MHl41Bi1WNT42KYdBr4OB4v7o12H/mTN4+isb4Mv3x7LIZVukF2idTIpnJ42+jfjMZuM+IX/ziGTY01GHD74eN4aVD7yscX4nPP7cXW9UujlMYGrQpD7iBsJj0OdjmjLFCvXV6OirzwIvJY7wj+92gfPvuRuWAYuybSBYSKAVvXL8PDOw/ihoYKPPraoagAb92jb5ZvvrASQ54Arm8ox+5D3bjpwjloG/DCH+RxeDQ4m5h3VVEO/EFO8nXpC/L44uXz8N1XD+L2S6qilKYv7OnAltU1+PIfPsAj65ZiyBPAU28dx91XzseGlQvw6GuHcM/HFsYpSg1aFWbnm7CoJOx+YcDth8cfwiv7OnFDQwWaT4+5bJAspwOhqE9L8kw6PNC4BB92OSWFsNmgwfUN5ZKriDsurYqyZLbbDKjIM0ryv7h3TJntC4aiLJ4j70mOXo37G8eU0LdeXInSXGNUGwHATRdUSPc6Umks525kMpUagwqWsIMKlrAuv7z7gp/dfK5iGRa9RvbT0JwEGxkluYbc8laqTp/89U6vslWrUl1qEtRFq2W495pF6HePWRYVmHXQaeTvVa5Rh4N+V5wCOjeBElbFgG9evQg/2HlISvPNqxchUXcQEMLD19XhWN+YW42qIjMEJq+E9gZD+O3/tUVZOv32/9pQO8uqWAYXCsX5vdu8ugYcnziI0URycsCNh3celOpRXWxBnkmHPBlF9rvH+tDrCuD+iA3dD66th0HLsGVNLQZGAti6fik6Bj24oKoAdWW5cQFAI59RrZohFPFlxeOfWooym1G2H/ICcLTHJclp1KpwesiLu373ATaurMaCkhz0Ov3Slwy3XlwJpzeE+18ZWzRtWFGNp/5+FN/+xGLZMtQqwDhqyZ+KuwW5T5Mf3PEh7rysCnMLzbJluP0c7nsl7J4o9pn+1tWL4PJzKMrRY+PK+XhhT4fk4mL7/k5pnIysjxi4Qi4wpBiBfdO25ri0D66plaIVG7QqPH1zQ9YC8p3tJLI2JqviM4OeCMUwMKY8ffbW8xMqhz3+kOyXMA2ViV0Z5Bo1cdY7m1bVINeUeOugUavx3D9P4paLq+ANcDDqNHj2neP4/rXKcQEA5S98lNY1It6g/EvpX32mIWE6s04T52bn8d2teE7hZbZUPxXDXVdUR81JD66pTer/X6NismsqTZJ0JwfcePmDdvzs5nMxNOpG7H/ePYFFpZak7pP+0doLly8Et5/DgDuAU4NuXFpdfMYpTlKh6bQj6nP0PJMOnUNefP1PTVFrhMh1vLiOiLRyHPLI99NhTxAPrqmV+sX2/WEjmKfeOipZAdeV2TC/2BKnOHlwx4d4dN1SCBAUvyxdYrdIQeu6HL7wvivPhBAfAs8Lij7CC5K8tCCI8aDkLmdRiQUhIRxg+6l/PxchPuyWbMOKavi5cHyi+xuXoMfpQ2N9WVwge9GF20/eaEXnsB/XN5TjP69cAJNOhUfW1eNrEc/tpsYa/OKtYzBoVcg368648W08LwjTyfNH65dJY8iLezukNb4Y5+qxXa2447J5cTGlNu9owa8+ex7+88pq2Iy6KMXx3VcuwG/eOYkuhw9BbmzfKeqoPv8/Y19Af+3jC/Hfu1rDQa1X1SDfrMOwO4B+tx8BToDFoMbtl1TheO8Izq3Mx09vWg6zXgM/F8Ism7KBGJEeWVMOC4JwRpil1Nit+NIV1fjO9hYpMu2WVUsQAsPetqGwW4lRpUFlgRFmXVjJmG/Whj8Z43ioGSSn68/vacdXr1oEtSqseH1wbQ1ae0Zg0KokFxSMAa2jn8ifdnixvDIXj99wDm74+bvIM+nAGLBlTS0+99xePLJuKa5vGPNZXJZnxKJSqxSxccTHSbKJ7i1aRhWzeSYdHli1BJUFRhRa9FFKU5Euhw/D3vBn6J3DHkkxnWPQSQrcopywawXRAlm0HvYFOGxvOo1vvXRAcnkhKp+/+NH50sJqYYkl7FaOhd+iH+oeUwa7A2H5b724Ep5gCNv/9zhuunAOjvW5pcHq85dV4Z6PLcBv/y/8pvG0wxv1ecFTbx3Hlz5ahYuq8lFRYMa3XzoAIPqeNNaXQQXg2dvOR8eQFz1OH77+pybpJYDo91j0uRxpiSznbmSylRqlCkG0lAKi+CIU3mPHePiD8kpIAHD5gzBpoz8NNWnVcPuVFbc5BnnLGLNB3mJIyS2AKYGFkScgXxdvQLkuepUaeq06arG9eXUN9Gr5cpQU0Il8GA64fagsMEb5gQ7xPAbdPkUraA3ToH8kOljc1z6+EOW58pNcMCQfWC+QwKJZq1Zj18GuuI3lf1yaOAJ8tnB7/WjpHpF88xXn6NA57InbXH/t4wtRmW/C5y+fj6f+PraZuvtjC6N8WvmCPL755yZsXb8Mn3tub1Q7BEO8tFBS8rP56Lql0r212wxw+0Podvpk+2Gt3QqnL4itr48pRzaurMaC4hwsmWVFKCTgsV2t0suykUAIW1+PXiSL1sFGhb6+qNSKh3cexMaVC8DzQkqfiMv1/7JcI3oc8vVoH/JI4+Oz/2zDnZdVocxmRK5Zh7YBN55442hU/UR3Hp+/bD5efL8dd10xH8UWPcrzTPjWS02S8vi5d8N5VRdbcKjbFRXUom3AC5cvKAUdPa8yH/e9ckDyf+wL8tgjE4DUF0w/IB9BnA30u+UtA/vdiS0Dh71BWQvZ4QQvYQGgusiK9kFvtDsqDUN1kfLLSADoH/FjT5sjykIIAAbcflRD3v0RAJRYFALgWRIHwFN0z+RP/AJ02CPvcmlYwT2XSEgQpLlLTHP/K8343R0XJEyHUfcase42kjHiD+KqmllR891Da2sTrsUAoH1gRNbSvH1gBHOKlO/DmUqsO5BbLqqENxiK8u17zwv7UHbnhdJLZnEdccelVZKVo1LAxebTDrx5qHcsODIDdn/YLbmsyjPpUGo1YIvMy9Yuhw8nB9xYXpkHBib7ZelPblyOX/zjuLQvu/OyeXjkrwexvqECpdYRDMbEYhHXuXZr4ueHIMZDl4y7nDyTDge7XXEv0AKcgOfebcMtF1Xizsvmwe0LYkGJBUd6XGisL4t7WXfvSwfwo/XL0Ov04fsRhjdb1tTi2dvPR6/DB6tRi0f/ehhHekdwf+OShAZMM5VsBN9OJc8f7DwoGXV0OXx4fk87tq5fBk+AQ5/Lj7uumA8Iguy82THoARcS4l5g/+j1I7jrivl44o2jyDPrcO81C/Hrd9pwfUO8H+NH/noYT998LjyBEH7xj2O4eH6R5HLvvn9bDLVKhd//6yhuaKjATRGBte++cgEOnnZiVq5J1uUnx/H4sMuB0w4frEYN7FYjZueZ4mJJie1ytn9pk7XwuIyxasbYnxhjHzLGjot/2cp/slCpGLzBENoGvDjaM4IbGipgM+mxeXsL9BoVrm8oR6/Th3eP9eHzl83HY7ta8fy/2qFWASVWQ/jTMpMO37x6sfQW7Jl3jmNpeS6GPAH4Ryf5p986gW9evRh+LgR3IPyG+MW9HRAAOL0cekaj2N98YfhTwPdODsEX5PHzt46hqjAH1587G9/feQhqFcOhbifeONSLTY018AQ5bN/fiW9cvRgDngAe29Ua5RvS5QnggcYa6TN7ANK/IsZR9woj/hCe39OOb169WHprftMFFTjeN4KqwhxJvh1NnTDr1CjNNUkBz0TfyYyFJ4nFpWF/yDdfWIln3jkOxoCOIQ8q8k3gBUjWwacGPXj3WB8WlFrxh/fasWJRKXocPknhfstFlagoNMFuM+Jbo21s0IYV9GI9dBoGm0mH5tNODLh8eGTdUtTNsuA7q2ule7KjqRMOXwi9Tj9+938nMSs37L7i6lo7frzrCO5vXILrG8rRMeTB9v2d2LCiWrJYjrQmjkRUakwGDOGAL5H3cOPKakUr1XyTLuyP+or5uGtF+K+ywKjovgAAdBo1tjd1Yn6xBbNzjagutmB7Uye0GuXNjFGrxj0fWxAl1z0fW6DoikI8H3t9ooA31tFP42PzsSgooAHA4QvGBQbZtK1F0e/uiE9ps6kc9E6nVsPP8XB6OfiDITh9HPwcD62CAhoIuwd55K+H4yZHLye/qTXpNLKB9Uw65cVQSAhh5WI7PvfcXvzn8/tw53N7sXKxHSFh4i2H3V4//tLSi1t+9S98+fcf4JZf/QvvtQ0jGELc5lpsh6f+Hp74f/n2cTy+6yj+74S8AjHyGRTbQRvh0zJWiWq3GXD7JVXgeAF3XFolfUWweceHeGFPB+6+cqwfVhYY8dObliMkCBh0B5Bn0sFuM+CuK+ajIt+Ee/9tCZzeILSa8Fcl4lcFSn541arwi5WHr6uP6uv3Ny7BU2+G/QHf+9IBnBxwJ2xPnheg16hl+3/nsBdGrRrfWVUTV8Yf93REXS+9SxAQZ3H32K5WPHxdHX60fhlU4PGp8yux2G7Fk28exVf+uB+fOq9Cyn/IE0BFvhldwx788u3jcRHYXb4QnnzjKB7fdVR682+3GaRxqLrYIluXdALyEcTZQlmuSXYeL7MZE6bLNWrx/J6w5fBdK+bjjkur8PyeduQm8NMPhD8dXrmwBLPzjcg1ajE734iVC0sSBmsDIH1GHEkqz7UnyMWNX99ZFV7XJsKs08i2S6KXzACQb9bKyplnTtwuvS55JX2fK7GFs2F03b1gdE21YNRtnD6JL+ZgSJC1zAuEhITpupzyluZdzrPTzYD48gEI+8wszNHj6beO44ndR/GLfxzHzRdWIs+kw65DvdjZ0g2eF6R1hGhFZzOo0efyx62/N62qQWGODquXleGrf9qPu37/Ab76x/24qtYufT1z7fJySTEMjL08vnZ5OQxaFeYV5eBbf26SzkXiC/LwcSH87OZzMSvXiB9etxT72wewYlEpnnzzKLqdAfzn8/skH+F3rZiPOy+rwpwCEyoSfFVAEOPFbjPGjaNfuLwKp4Y8uOPScF/MM+lw/yvN+PYnFuO6c8vx7D/b8MTuo5hTmAM/F8LS8lzFmBgHu53wBENR89eTb7Ti7dZ+BEICco1aXLmkFHdeVoWKPCOWlCZ+eTkTSRTTJlt52m0GNNaXQa9R4ZF1S3HvNQvxjY8vwoM7PsTJAQ8e29WKR187glyT/Lxp0GlQlKOXlbPYosfdVy7A5u0tGAmE8OUV87HEbpW9dsgTABcS8JmL5+KS+YXYsmYJ7ri0Ch5/2O2U3EuE3/2rDbNyTTjU48K2/Z3YfbgHPB+eH0W3J+uffhef/5/3cdtv9uBvB3vwaksXPvH4P/Dpn/8fPvH4P7D7cA92tnRHHRPngZmGGNPnn8f6cbxvJO06ZPP1yq8BbALwIwBXALgVWVQ+TxYnB9w43O1CZYERs3KN+MHOg/jqVYvCFrNmHSxGHXqdPtx+yTzc/cI+yV/u7c/sxSdqSrBx5QI8tusINq5cEPWZxE/fbMX9jUvgHrVw6HL40No7grmFZnxt1H/vzRdWStf7uZBknesL8jBqw4vKvpEACsxacHw48EH7gBe8AHx0UTFefL8dn76gEjddUBnuDBGKCvGNd4fDh96RAKpLLJIf4W9dvSgqkEeRRSedu+3iuZI1b2WBUbKkzeMEyYL5hoYKeIMhHOoa++xqcenYpv/6hnKc6B/BN69ejB+Musvodfnw+ofduGvFAvx4dys2rlyA4/1uvLg3bF3t9nPSAJBn0uHulfPxn1cuQLfDhw/ah/HKvk585aqFuKGhAo/tCgcQER3R220GHOpywh0ISVZ9t1xUiRAvxH268p9XVuPzH52PYCi6Pk+/dQxfvHw+/ntXq3RfPnVeBb77yVoIAnBywKNg4TI5So3eEb9soJh5Cm8QjTo1vvTR+XggKoBGTUL/wVwohJsumIOjEYHfbrpgDriQslJx2BuAXq2KsozRq1VweOU3TVqVCkUWfdT1RRY9dCrloaPArMWW1TVxdSnIUd7QeRQsp5WsjfNzlHwBK3+eJwgChjxcnJWO3ao8KHsULJ48ChZPwwk+Z1RCxdSyivFnk3w6mw0Odo/IWliJATIj8QV5uANc3MSfyO9tbHpPYKzdIn1A15dZ8fmPzsehbieO9o1g+/5O3LViflQAUIMm3G9NunCAy8iox1+9aiH0GhV+8fZx3NBQga/8cX/UPY68j3KyLi3PRUuXA798+wR+8ZkGDLuDONjtwhO7j0oK1VQsZk8OuPHAtmZFdw5DngB+9dkG/Nf1S6FiDLkmLTRqJkUijg22KReY0xfk8a+TQ/jFP46PWhGHIwiLZYiWx0vsVtitBiwstuDNo31xFkvip2RiG5zod+PWiyvB8Yjx214bZV1CfsMIQp7FJRZ86YrqKJ+pW9bUYnGSzbAnwMlaDnsCiZWuQLRvyVSZU2DOyB9grlGPH+9qxQ/XLY1yR3H/v9UkTGczamRdJ9mMibc4Kibv5kHNElsKmXQK8Rh0ibc8Po4DYyrJKlSypgslvg99Csro/iTK6IGR9ALxnunoR/vFT948Kvv13+O7W3HnZVUI8ZCs8sQXHWJQ8B9cVyfFfRHX3yoWXpsBiLOE+7Br7CW2nF9/8eXx/Y1L8IOdB9E2EP6SUa5/GbTqKOvxzatrsOtgFxrry9Dr8ktuKiJ9hF9UVXBWWr4Rk0eN3YqH1tZKL7AaKm0w6jR4+tVDcWvUQz2uKOt3TyCER/96BN/8eDXOmZ2nuNYvytHjsV3NUfnpNSrc+9IB/OKWBvzkzaP43ifr0DA774wMQlei8LXweHQOkXnG7g3EvU3/iB9dDl/4q4qPLcDWvx3Br98+EbcHF916fO7yebJyFln08AZCCHACeAHYsuND/PrW8+KurSwwYsQfwoM7DkTJ8e6xPtxwXiUWFOfEjaN2mwE3NFREzasbV1ZjflEO5hTmyLo9EWPKRB5r6nDExZ6ZiW7usuGCJJvKW6MgCLsAMEEQ2gRB+A6Af8ti/pNCj9OHF/Z04BsRikybMez3tmN0E//9nYfQ2jsi+csV3wr/eV8XHvnrYaxZVoZZuQaoVZAUHXvaHHj+X+2YlTv2hi0Q4uHnQtIb5cd3t+L6c2fj8d2taDo1LFnnfuPqhSi1GbBxZTWubyhH82knTg16UFlgRGWBCdv3d6Ii34QLqorw7Zea8ev/PYl5xTmSpav4xlutCitafByPn791FKVWA/7jkrkwGzTS2/OX93WC54GKfBNuOr8CVcU5ODUYtp795tWL0THkgZoBz757EhX5JknesPLYDINWhVsuqkSXw4uNK6uxfX8nZueZ4PSH0No7IrXH02+dwO2XzMMTu4+M+hBSQ80gWVefGvRIbxG7HD44/RxOjAZU4wWMuoVgeHw0svQN54cHho1/2Ie3j/ajPM8kLdJuuiCsQPZxYSW7KLMvyKMs1wRfgMcPXj2I2XkmSb62AS/6ueplcgABAABJREFU3X4MeQJ47t02yQeq3WqQ2mPDimjLgYevq580pYZRq0ZZrh4LS8MWKItKLSjLHbOKiMUbCEkDOSAG0GiBN6is6NVp1AiGQpKVS3WJBcFQCLoElsM5ei1+9c4JSXHHC8Cv3jkBs05ecWszaWHSMlxUVYAFxTm4qKoAJi2DLYFFs8MbwpNvHpXeIt9+SRWefPMoHF7lukRajIiEJyx5Za9BE154R97fzatrYEhgMeUZtcqJtdLxxGwGIhFdDcTKpWTxZNDKW40q3XcA6FUIUtI7CUFK+kbCVreRFl15Jp0UGC0Sg1aFWbnGOOsBcfyKstJpXIIdTZ1x6UusYwsltSpsXV9ZYMQN51fgnhf24fFdYQsh8QWQXqNGQ6UNP7yuHjaTDg2VeVhYapHGdCAsy6OvHUbfiF/2jfXm7S2oLsmJGmsjZX1wTS2ef+8kepwBtA14cccze1BRYJK1tE220Otx+tA24MVz77bhkXVLpf4vfpbqC/J49/ggvvS7D3D3C/vQ5fBh6axcfP+TdagsMOJbn1gMHxeSLKdFxXtsOy4osYwGWw3hlosqoyycuhw+PL7rKGxGLSxGLT7oHMbCEguWV+bi0XVL8ci6evz035fjd/9qk/wiblhRjT/u6cBCuzWq/doGvHjijVY8f+eF+MOdF+AvGy6lYHQEoUCHw4sX3mvDD9ctxcPX1uGRdUvxwntt6HB4E6Yz6jTYfag7Kt3uQ90waifm81sxAvpfNlya1nNdY7fiMxfPxdFeF04NeXGs14XPXDwXNbOU3TkBgDsQkn0B6g4k/jqm2+mPsrS8/ZIqPPvPNnQnsazNGY3HEPvlVrLPmdVMLfuyVMUSKzMULaP1idOV2uTXPSVJ3HScqeTotdh1sAvfv7Ze8eu/ynwz/vx+h/SyVnzRISqID3Q4pH3Jn9/vgFmnRnWxBeV5JiyxW+MMCCK/0gTk59tauw0uX1ByufSLt09Efclk0IZ9r8auLzdta8FnPzIPNoMaVqNGsn622wxSusg1EUFMBBqNCmuXluH5Oy/Ez/59Ob6zuhZGrRqbV9Xgpzedg3uvWQQfF8K3/20xCkxaaT354JpaFOaEg54e6fNiYMSL736yLqrfb1hRjR1NnZJrNGDsRc78kpywUYk/hGdvOx+r62fBmORrmJlK5DgEICuGFJF5RsZUEr+y7HJ4Mb84B9+8ZiF0GoZcgwY/v6UBV9fZUVVkxqPrluLh6+rwi880IBgK4bKFxSgw62TnxhAv4Ps7D+H6hnIsLAnHmHF6gtgU86XQN65eLO2/IuX48soFeOKNVnzho/MlY0mRSNmBsS8ge0bncTm3J75g2D1sJEpffvY4J+eL8Gyh5IIk2ZepkWRzZehnjKkAtDLG7gLQCWDmqNpHKbGGgw0c7R2RNuHfu7YWVYU5ONo3gtbeEfiCPAIhXvKXG9mZxI3zstk2LC614uDo+foyKz7zkTn48LRDCvDx1uFeNFwV9m8rul8Q3RvceEFYwXrLRZUAgG+/1IwFxTn4j8vm4US/G28c6sUDjTXYsqMFt108F7lGbZRSJRjkUFVklqwinnu3DQ+uqcGBTgdeHg0S92pzJz51/hx8cdRCTnz7cutv3sOC4hx8+oJKvHdyEH/cE/bz6w2G8MLo/2//yFwU5YQXQWKZXaM+imfnmfDVUWvoa5eXw2LQQM2AEM9HKXxbe0fQOexHjk6Dn711FDddMAcbV1bD7efwzD/bsGnVktFP8HJQkKOHJ8BLZRm1Khzvd0cFtBPP6TUquEf90tptBpRYDcgz6WDWqbG8MhenBr3SOf/o5/ttA170unxQqyBZGhdb9dKbsj+/34EvXF6FbqcfbxzqxZ2XzcPTbx3DxpXh+qpUDAuLJ6+755t1uPmiaKvemy+ag3wFy9b+DCxIGICQwKLexm1aVYNE2zuHgm9Dh4L7htIcA5o4B/55fAC8ABzrG8G8ohyU5igvaHucfrQNeKOsI8TjSmjVKmxZXYsHtkVYXK2uhU5B2dvr8sOoYXh61E9vnlmLYbcfvSPKZWRipWPUqmQD5Sm51TArBAk0J3ArUaIQpGQyNoj5Zi1uuagyTl5OEOLqcX/jEjz2+mF84aPVUfKKfq9+uG4pGATkGDR4cndrVD+7akkh7rysGqeGPDjS40JRjg5MBbx6oAtfuWpRXPAE0Q+wNxjE+oZKKfK4+BJgQXEOmjqdUj3EhYSS5Y/DOxaIRvTDW5FvQrfDhyfeCMsqBnHzBXkEuFCUZV3YgrZOWoQo+bmKtGI6PGqBIWdlIZZz70sHsGx2Lq5ZUgoBiAoSsWFFNd47MRAXNG5TYw3+67VDUtC4+xuXwG4zoMvhk4JZhe9PCJ94/B9R9/XZf4YVwt+8ZiHWLCsDL4S/anju3TboNAy8gCj/jl2OsLLbGwzhwqrC8Xc4gjiDGXYHcN3yirgo4aLVohLBECebLjiBQUlVqnCAzXQsblQqBhVTRfng/6/rlyVVKve7AlHxL4Dw+NI/krhdbCZNVFBaxkbdkiWxOHb5gyi1GqK+eCq1GjCSxAdwv1tezmSWvCadCp+/fH7cV0mmBC+FAaC21IYfrqvH0d4RaX0xrzgHdfbEyvYzlTkFZqw9pwLvjq43xa/BxPuhZkBZnkF6qVlsMUgvOhZtuBS9Lh+MWk3Yd+ZonBRPMIRHXzuE68+djSKLHt/7ZC3aBtz42VsnAEQHdn5xbwe+9vGFkgstcd50B7goa/Quhw+/eeck7rysCguKLbAatfAEOEl5LBJ+GTyAygIzXhlVaItrm1++fZy+wiEmDfELk+rCAHY090TttTatqsGbh3rx9FvH8Z1VNagvs6Kp04kepx/FFi1+uK4eKjD4uBCKLVr89w3L0D7gRmmuCe0DbnxnVQ1+9LcjUeX5gjz6XP5RYxoV+lz+pO6OZjKx41CxZfz+cCPzjAy4GWlB/PToGPW1jy9Et8OPB54N75U2rJyPx3cdxRULCvHvF81BvzsAo1YFh08+VpE3GEKeSYeKPBOeeec4tqyugZ8L732evPEcjPhDONIzgq5hL26/pAp6jQrVxTnS1xTinuXUoBtaFYv6elLJHUkwFMLxvhGoVSwu2LZBq4pzwykaVMbuqYIhIaV4MNOFRC5IUl2PZVM5vBGACcAGAA8i7FrilizmPylU5Jnw8HX1ON43Ir2ZONTlQs0sK9T9YQWnaCF2z8cWSMHKYjtTgdmAB3c04wsfDVuubbiyGq09I/jDe2H3BI+uWwqrUYP7X2nG3VcugCfA4daLK2HUqXF9QzkGPQE4fRz+uPcU7rqiWvKHe7TXheoSCz66qBjHRhXYLj+HB//fh/jm1YulN0AqlRqPvHYInzqvAo+sWwqtaixq7afOq8Cug9348soF2Ns2JMkuvn3JM+nwhY/Ox92jQRiGPAG4/BwGPQHoNAyeYAi1ZTY0dzrgC4ak9nhg9LOor161SFrgPPnGUUkx7vZxKIr4jEFUsB847cAFVUX4711H8KnzKlCeb8SQJ4Dn/9WOH66rh1alwqFuJ6pH/bO9dbgXG69cgKaO4SgFvRj5stiqR35O2CfOTRdUYMjtlxRUj91wjmR1fUNDBU4NerDIboVBq8L/vNuO735yzNXC47tacdvFc6WAS629LpTmGnFNnR1Pv3UMt39kLnLNOhwZVdAe7nairtyGFQtLJnwQCXI8HDGuBByeIIIKgclyzfLBsBJtggIyjuU3b2/Brz97nmIam1ErG/1byYXBoV4Xup2+qM3gPR9bgEO9LiyrkI+krqjsTBB0w+kN4sk3W6PccDz5Ziu+/8k62esLzDrs6Xfj639ujpKrIV95oZ2JEtYb5KDTRAfK+86qGvgVfCzq1SpUFpjCAYL8HMwGTdh1R4JFkfgpZewnt4msjbOFijHZwH4/Wr9Mck9QnmtEjkGLp948iqZOJ55/7yR++u/n4oP2IfACsH1/+GXWs+8cxz0fW4gRfwhf+/hiuHxBPHvb+dCoBHQM+fHeycEoZfODa2rx7xdW4GS/W3aiDPuJN0qfaYrHN21rwaPrluKu348FUxIXEkouLnJNOjAm4Ombz4XLx6Esz4RgKBxBfM2ysqhAbQatCvlmPZZX5GPRhksx6Pajc9iHOyMU1EqfAEV+rh0ZPThS4SsqocX69Dh96BgK+zSOfS63rl+Gh3celILGnT83H99+KTpo3IM7PpQ2m4Iw5sf4OzFjw2O7ws/Xk28cxTPvtEUtMCsLjPj85fPxhYioxJGuMESLaZ4XKBgEQSjACQI274iZk3ckdxGkUWmwecf7cemeuXXiXQulw8kBN77yx2iLl6/8cR8W2xN/1lmWZ5B9CVlmS2w1adKq5ZWuST5LNmo1+O9dLdIXZSEe+O9dR/DIdUsTpss3aXHrR+ZIft7FdUWi2A8AwBjDi3vDL0i9fg4mvQbPvHMc3/rEkoTpNBoVVDGv81VgZ7QSJRGiMqQs14gNf3gf37p6ETzBUFS/qSww4yc3noM8sw7lo768I1908LyA/7p+GQ73ODHgCeCVfZ1xQYI3rqzG5y+rgp8L4XuvHopyQbHEbsGdl1WhMEeHygIzepx+aDUqVJpNUfP5kCcAu9WIR147BJtBi/tG46rIvQz+9ksHwoGi0CUZI/1lw6U0fxKTTnO3S1IMA2P7xh+uW4oNv/8A3xn9/9f/tB+nhjyoLMzHoJvD119qGjPcWbUEOQat9DKzssCI+0dfguo1avz8rWM40jsCgyYc46ZzyIP5JWeen+FYMnnhmmqe4tpeyQr30XVL8ehrY/FxRFejn6ifhS/9bswF3wONS7C9qRMXVBVJc+Ov3jmBNcvKcH1DOUKhEP7j0vk4cNoR3t+91onbPzIX84tz0ONQw2rU4pHXDsftE7ocPjy+uxXP3Ho+PEEOOXoNfnLjcpzod2PJLCte2dcpzccA8O6xPgy4g7jj2XgDliFPAPd8bAHstjF9lEGrQl25DQ9fV49vvNgUVf79rxzArz97/oxxLZENFyTZVA7PEQThPQAjCPsbBmPsegD/l8UyksIYuxrAYwDUAH4hCMIPUk3L8wJeO9iDrX87LPmX7XX6JZ+2t14yFy5vUJrAe10+yb1ApKXkw9fVo8Ye9nE5MOLD/Y018AVC+MN77ZKPXPHNS9uAF7955yRuuagSC0qteGL3Edxy0VwwxhAIedFYX4aOIY/kfzjPpMO3PrEIs/NM0ifmPo5H24AXP33zKO5vXIIepw9uf/gt88M7D8NuM+D+xiX418kh/HFP2AL2hvMqsbdtKErZIVov33xhJZy+cBRn8TNpHxfCm4d68fnL5mPzjpYo6y+x/j998yjuvGweOofGFOZ2mwFX19rx+K5WfOq8ClRoVfjuJ+vw7ZcO4MW9HfjKVQvQ4/TBP1qHZ//Zhs9rq3Dfvy2Gy8ehcyhsVfbHPR341icWSbKIFtNmgwYnB8aUvd5gCN9+qRkXzc3HD9fVI8Dxo9Z7R+EL8hj2BCSr6y/97n2pPUX/RxAY/vBeO+66ohqN9WVSdNS7VswHAIRCguTHeFaeEa09I1GKvUg/NxOJLyKQYWTZPoVAZnqVWtbiVJcgWNqAW94SdjCBlYuST1yHgmXTiJ+LC4i19W9H8ItbGhTL4PiQrLKTS2AFNTL6PMRaGytFM/cFQ7Jy/eozynJZjWpZ62SrUbmNtWp1nJLtO9tb8Jtb5RXwniCHjiFv3OayMEfZF7JFr4VRO2oF7Qkiz6TFsMePHP3Ef36lFLintXdE+sri4WvrpMi4dpsB51YWRikR729cgr8f7sb6hgp866UDcZbp3/1kHQZcvjgltOjbuKpIKztRLiq1okfB5UZIEKIWDXdfuQAGjQq/eudE3Hi/ZXUNPL4ATg76ojaIW9cvwwVV+dC0DUs+fyM/BRMXZQDw77/8V5TsSn6uYq0HSq0GXLWkFH0jPhg1amx4/oM4VxUmnRq7DvXK1vNQtzPquRDnpNjr1CrggcYlcPqC+MmNy3Gk1yV7nbgwE629/+f2C/BWax/OrcyLU8KL/h3nFeVgToE5K36yiJnJkcOH8JGrVsuesxfl4U+/fWaSJZqeKI1XvUncIPSNKARQS/AlzFSQqcWLIMT7en1sVysuuOOChOW5/CHZF+A/T7D+AMLrHLn1hFJsBREVY7LriueSKPe9waCs5bcvmNhS+VCPE6eGPHHrxEM9TtSW5SZMe6aiUjHUldnwnysXotvpjes39750QHoZ+tDaWqxdWhalTFepGK6pLQVjwIddTjTWl8UFCX5sV3huO7cyL8pQBgBm59bhzUO9+PT5lVH+g7esrsG8YjN+/KlzcLjHhYY5+fBzHL5/bT38wRAGXN64da+oOPEFeczKDSuyDVoVqkssM0aRQZxZKM1R3lH/9r4gD1+Aw/c+WYdzK3NxcsAjBbIXz3c4xgyGxC+a74pQQG5aVYN8kxbeQBDFFj1UKob6JK6HiMTMLQwbnii523EHouPjvLi3A/c3LolzX7Blx4dx8Qbub1yCJ3Yfxb2fWAS3P4SNz38gnfvW1Yvg43jc9swe3H5JFba+Hv1iQfwS4slRHc7/HuuH3WrEi++34uaL5kClYviv1w5JuqnIfeHWvx2OG5d/fksDVAyYZTNidp4JNbNsUZbYe9sHo4zIRMV0Ola3U02mMR8iyaZy+FsA/pjCsQmDMaYG8CSAjwHoAPAeY2ybIAgfppI+0k/HwzsP46tXLZCUin0jATg9Qfi5EKqKcvCTG5cDTMA9Vy7E1tcPS5ZXDZX5uLiqABqNCnMLcnDX7z7AFz86HyUWvWKgpS6HDw/vPIxH1tXjgqoiaDUqnBpwY7HdioNdTrywJ2ylLC4yTg16oGYMKgZsWFENPxe23m3qdKJv91Hc+4nFYBHm8dcuD1vX8kLYp2+PK4Bfvn0Id1xaFaXcBiApoR9Zt1SS7bl323DvJxYDQJTViugj+Ll3xwKjuX1BXFpdiGKrAfe+dCDqLdTDOw8DCL9tev7OC+ENhmAxaODxc6gqMkhvrb6/8xDuumI+nnjjqKSEHvIEcGrQgxf2nMIXLw8rMJ566zgeWLUE2/d34htXL8Y9o5bOviCPN4704yPVhXD5OAgY++Sg3+3HRxcV4+BokAixPV/YcwpfuWoR9nUMSwr52E8V1AxwjSrNr11eDl+Al92QLK/Im3DlMMfLb4aUlKrdTp9sALvKApNiGaKf3lilWlECS9hck3wgN5tRXnnpCSgEZEvgK1CjUmPXwS787OZzMewJItekxW/fPYE7LpmvmMask7ecVrIQcvrk5XL5lAPH9LmCeGFPW1wwnVm5C7GwVD6Ny6tQjle+HD8nyG4uE21mXb4gvv5ic1zdX7jzQsU02aJYoQ/5OV76f6fDKyk0r11eHrfRenDHh/j1Z8/Drb95D7dfUhX3VvvbLx3AIwkC3BVb9HhobR3ue3kswMF3P1mHX719DJ+5uEpWPp1ahR+tX4aWLicEAfjNOyeh0zA8fF09vAEOz9x6PgbcflgNWhzvG0Gvyy/NFWLZ97ywD3/ZcCnWLivDstm5ip+CpasQkbMemFcctmgSx8HIBUEgxKcc1E/puvnFFnz/Lwcx5Angh+uWYsQfkr1OrJZBG/YdJkCQXgDI1bHMZkRZbvjT3eN9I7J+smZaMAgifThBhdnrviV77tSfvj/J0kxflL5OKU7w1QygPJdPN9+zmVq8dA7Lj6Gdwz4sr1RO51VYf3iT+CpWXOckCFgLAIMKL9yH3ImVvJlafg95grLrxNqys1uRolIx/FttKV4/3CN7P0T3Ufe93Izq4hwsnZ0Xl74wRwc1AwQFV1O8EI71EdtPzAYN7rxsnuSuTbz+gW1ho4BvvNiEGxoq8I0X92PNsjJctaQE7Z4gPux2o6VjGM/cej7+91g/QvyY4kL8ci4TJQBBZBOlOco46vrOoFVhTqEZDZX5eL99CN0y/mAjfb/KWbJuHjWg0WpUKLbosaDIckYGoZtMIr+qiAzKBoTvWeweusvhw/G+Edmx72jvSFSwTqc3iCFPAGrG4oyhBjwBqTwlt32R7uxCfFgP9cN1S3G014Wn3zqO2y+pivui6tujL/kiX+D6gjy0ahblwi52L1Vg1uOXb8fXfzyB/yabbLggGfe3RYyxaxhjPwZQxhh7POLvNwCSh0LOLucDOCoIwnFBEAIA/gBgTaqJYzfpPo6PGqC+v/MQvvfqYXzuub247Zk9+OJvP8DS2Tb8+rPn49LqAqxdVoZL5hdKb5l7XeH8AqHwJ0LJAi0NjPihVgFtA27oNWq4vAEsLc/FkCeAXpdPuu5/3m2HUavG7AIznt/TDoNWjftHPznqcvjw6GuHoFUzydE3G/0cWlQEi3K8uLcDNzRU4Pk97bj9kipY9WrMK8oZXVR7JKfiYp5VhTmS/C/u7UC+Kex4fMgTwJNvhAM9leebsdhuw9plZfjLhktRV2aNe9gjfUwaNBp879VD+OkbYatnUbbIthflfmHPKdzQUIHTDq8k15btH+KGhoqoQUpsp2Evhxf2dGBxqTWq7SryTfBxfNSxGxoqxvz3qhCXTqxvvlkntanbr6TYnPhuP6JQ9ohfvuyyPJN0n57YfRRPvnEUQ54AykY/m5PDF+TinMVvWlUDP6dcP6cvGBeQa8OKajgVfPFZjbo49wYGrQrWBEEFvEEOy2YX4HPP7cXGP+zD557bi2WzC+BLIJdBq5Z1ki+6EIklMnBkpFz2BJ+pugMc9rQ5sOH3H+AbLx7Aht9/gD1tjoSK7hyDfIA5s0FerhEFpbVb4b4DwGkFZ/yRFqYTRW2pFVtW18a1+5/f74BBG3ahUWge6wNKvqNEawSlxYM3wMm3o06DfLMO155TFhUcaU39LPxw3TKU5xmwZU1tXB93B4II8jx+8Y/j0rNyz8cWQqNiqCzIwXlz8nF1jR1OH4fvvXooaryKlKvX5ZOUuRdWFaKqKCdughYVIrGyp7sYUQoCVWDWywbQfHBNbVxQv+37O6W5RLxu48pqSTG8aVU4IvH2/Z14aG10u21dvwzXnlMWV7ZBq0K/2y9bx06HF/nmsIIqkZKcIAigTmY83bK6FnWliT+prSm1yKarKbVMuMzpkGnQHVEhEYmoMEuE3SY/z5faEqcb9sqvc4a9iZW8Zr1CANokgeUytfxWWi8orRPPJnQ6NRYWW2TvhzAaqMgXDH95KEdtqQXzinKw2G6VzUPFgNPD3rjAxlo1Aw9B/n66wkFvn98Tdj9YXZyDRSVWlOcZoWbAP08MotvhhUGjlgLain3PFwzh/32ZAroSU0utzFwjrhsj5yuViqHb6YNJJii36PsVUI7z0ecKoKrQjNqyXFIMZwnxq4rYOXjjympYjOq4NX/NLPmxj+N5SSdk0Kjxh/fasXl1DY7LuPiLDQKnNB6L45wYLNQb4KS0Sn1EHaPhTGVfNRGB/6aCZPvOZGTDcvg0gD0AVgPYG3HcBeDuLOSfDmUATkX87gCQ+LuyCJSsFhJ1vm6nT2p8pfxe3BsO4jan0Bz35uX5Pe2SFW2p1YD2QS/2tg3i9/8KLw6KrAY8tLYOP959RLLw7XL48Kt3TuDR65di48oFuPelA8gz6cLBC0osWFxqRWW+CZ0OD5699Xz4uRDue6VZUgR/9apFUVbB1y4vh1oFXFBVgJzRgfqZd9rw+cuqopyKl1jHrCW6HD489dZx3HpxJX75mQYEOB4V+WbMLRx7OyG2SSJLEFGBHmn1HPlQvri3AzdfWInn97Sjsb4MGhVwXnUhKgvMuPelA1Ib/uDaeun6SEvoIU9Acrchfrre7/JHWUyLeXz/2np8689N+ObVi2XTiW3+/U/W4eSAG0OegGzdKhL4pc0WokIttux8s7zlSo3diofW1uK+l8dcHjy0tjZhFHCrUY8Xd7XGWcLe31ijmCbXqJVeNogWys/vacej6+R98ZVa9bLuLkoTbOrKbSY88EpLXBlXLVH2hVyQEw5IGNmfzTo1ChTcMSwptUruTyKtTZckCOQibjRj70miulgM2rgAJV/7+EJYFVw+lOXKl2FPEJFaUa4k/hizgdGoxaraUswpNKHH6YfdZgAv8HAHQhAE4Hf/14Zr6ux4ZN1S6NQMQV5Q6NfaqHEh3nLOENePHlxTC62GocZuk7W2Ff9fU2rDvEIzup0+5Jt10KkZ9Fo1FhRZULvBlvDNq/h2tm/ELxscLhUFbzY+ARKRq+ecAjO+cfXiKN/Cyyvy8Lv/OxHnouOGhgo8/6923HlZFRaWWqBTqdDl8OKb1yzC7Dwj8s06zC00odhiQEWeCcsr8uLaJ/KrCbFuD+88iK9etVDyWSY+59UlOVI9s+EniyDOZGLH0xKrHnWl1qQR2k1GHRprS6LS1ZZaYFL4omeqyNTiZUmpWdal05LSxGPo4lIrvvfJOskfu0Grwvc+WYclpYkta60Gjew65wfX1idMl2fSyq53cpPcPyXL7+Iklt8ltplhMT5VzC3Kwfc/WSd91i4qIES//YnWSSajDlcuLMLxQU/cWnHjymrkm7T4711H8aWPVuGXnzkPQ+4Aiq161JTm4GDPiPx9sRqgVjFcOLcOeWYtFpVYodGosKTUirYBNzaurJb2K7F9b+v6ZZg3iUGxCUKO2Lmm1KqHXqPCf1w2L26+slsN2Ns2GDcmVhSYsGlVDTZvbwEgv+YvsegnZa99tiHOwQu/fCnaB90w6TQosYbbmucFVBfnoNvhQ6nNgMUlVvzwunp8PcJH70Nra8FxITzx6XOQZ9bC4Q1izbIy/PbdNtx5+by4exkZBC5SfxO5jxty+3H7JVVRX0oYdZqolwhyfaShMl86nuq+aiIC/81EmCC+Ih1vRoxpBUEIjv4/D8BsQRCaspJ56jKsA3C1IAh3jP6+GcAFgiDcFXHNnQDuBICKiopz29rGgvfE+jysLDDiyyuqcd/Lzbjj0irZzf9fEnzyGplfnkmHL320Cka9NmoREetTkeN4vH6oByf63dJgKUayN+rCnzt7AiEpWA8QdoeRqBOLcjy88yAa68tgM6hRYDHIygEgSubrG8qjFM6vHexJyydkMj+Sx/tGpIj3AKSgcqJ/ZtHPcqQccwvj612RNyabeH1tmQ3eQAjfeLEpKo8auxUHu11Se4juQC6ck4/XD/fiV28fwyeXz8aDOz5ULLt90I2W0050Dkf7f/2v65fhmtq49shoVEnUVw93D6Opw4X7X2mOGkTryy1YWJormx/H8WjpckgDe43dljAwCcfxeHl/Z5xCOdYHWyQ+H4dtB7riNmmr6+wwGOLfRfG8gN2He9DU4ZCUtvVJgvrxvIBXm7ulwDUJ2n1c5UxGe3Ecj1dbutA6Gk1cxYDq4hxcU2OXTZNpGSmmyXo/lWP/qWHc8PQ/48bSF79wEY71udHt8EU9UxtXVmPpbCs6h/x44o3WOIXmN69ehAUlZhi1Grj8HLwBHgU5WuTo1ZhfZJ2U4Dvj9ZcrBmKbqMVIbP7iePnwzoO4/tzZKLUZ0D7owR/3dGDIE8DD19Vj2Wwbuhzjl0cse9Dth06twoA7ELXgFPNNow0ntJ9+5KrVii4O/vrQrfj4fb9O+Xim57Kd5tSfvo//fW2b7LnJIpN2BaaH7OMg7b6a7nhKhBnx+vBht1tSfi8pNSPHmPzFUrrzPBBef73f7owLZHdOhRWLFNZfYlnpzPciDq8Pf23ui1tXfby2CLYEdQwEQnil6XTcOnFN/axYa7uztp/6fBzeOTmAD087UVWUg4d3HkTbgDeltZWI0+vD4W43+kYCsOg16HZ4sfX1Vgx5Avif2y/A8oq8qDlM6X5eUGVBiNfIzrccx+NQjxPuAIdTg96o9ZzCPT0TmZQ1KjE5BAIh7DzYjWF3AP3uAHghHLSzyGLAo68dQmN9Gew2PQxaTZRbuC2ra3FVbRFyUxjfp4izpp9yHI93jg+gqWMYFQVmdA97sMhuk/QpkXqW8+fmY3AkEKVM/uG6egRDgqSPqiwwYlNjDT7scsIb5PF/x/tw3bkV0XNtYw1efL8dt1w0B4GQgB/vjt8Xbl2/DFctLkH7kOesVvImQbExsqkcfhNh62ENwhbEvQDeEQRh0qyHGWMXAfiOIAgfH/39LQAQBEHWaV1DQ4OwZ8+eqGNym+j2IY8UUT4yimEqm3+l/JIpc9sHw4tcT4CLs8jNhHTkSKSoyESJkSy/WIXAEzeeg7kFORjy+KGNUYan09aJlOdKMkUqMpKVncZ9GvdoFNtXOY7HP471Qs1UUpCxkMDj0nnFWVWGZbJx8vk4HOhyjFk22W2yimGRbPepbKZJl0zaKxMl9ASVkfV+qiSLkrKa5wV82O3EiJ+DJxCC1ahFacRb6+bTDvSNhH39Or1B2IwamPUaLCyZHCVwIiajf2WTSHlLrQaEeKBvZGplT7ENJ7SfknJ4YiDlcPqkMp4Skw/H8dh9pBeBYNivvVmngU6rwooFyddfmczfQFiheDhC+b2w1JxQMSwSCITQdNqBHqcPJVYD6mfZ5JSIZ3U/FdtoyBOAzaiFwxMMW/mmeG/EPLY3d0UZ3SRSLmd6PyPlTXJPz0QmZY1KTB6BQAgHu51w+ILwBkKw2wyYV2jCvk4nOoe8MOg0ONEzjAvnl6DXlf6zMkWcVf00mT4lVidzvG8Erb0jEAQBOq0KT715FBdUFUmGepUFRpwe9sHl5WA2qFFmM8Dp43DaEf660xPgYNJqoFYJKMgxwOEJYtDjh8WgQzDEp6QvIgAk6KfZDEhnEwTByRi7A8CzgiBsYoxNquUwgPcAVDPG5gLoBPApADemk4HS58dVRTlYzguoK0v8mXE6+SVKM6cwJ6tBzdKRQ+7aVM6lU3bkOWUT/vTqr1SO3DGla9Op30Tcp1TRaFS4dF4xWroc8AZCsBm1aS1k0yln6ew8LJ2dehqDQYPz5hakfH22+1Q206RLJu2VbprJKGMi0WhUWLu0LOrzpMi+u6wiTzadSsUUz00HJqN/ZROlwHZTyUxrw5nCkcOH8JGrVsueaz95HBVzquKO24vy8KffPpN2Wetu+gy6+obijrceO45pMPxkhFKdgMzbiZi5aDRhRXAmSt5M52Kb0YDz56avENHp1GiYk592urOJbLSRTqfGmvpZmF9kTqlPZHo/xbLonhJnAjqdGktl1vUXzClAiz48vn50sX1C9rdEdkhXnzK/xIKqohzJEO/+xpo4Q7zKgvg9QP1MXUDOQLKpHNYwxuwA1gP4dhbzTRlBEDjG2F0A/gpADeBXgiC0ZCt/2rhODNSumTGdFH4EkQ7Udwli8uAElaLV7ocP3Sp77tSfZD+4SkpX35Bsfh8+dGtG+WVCtpW5SnUCMm8nYmZDcxgRC/UJgsgO9Cyd2ZDeZ3qTTeXwFoSVsm8LgvAeY6wKQGsW808JQRD+AuAvk10uQRAEQRAEMbWQMpcgCIIgCIIg0iNrymFBEP4I4I8Rv48DuC5b+RMEQRAEQRATTyauKICZ7T6CIAiCIAiCIM5Wxh2QjjH2dUEQfsgY+zGAuMwEQdgwrgImEMZYHwClcJCFAPonURwlSI7pJQOQvhz9giBcPZ4Ck/TVdJku7RgLyZUe2ZZrovvpVLfjVJZ/Ntc92+VPZD+d6nZKl5kk79ko67j66jQfTyMhWeSZKbJMZD/NlOnSdtNBjukgAzD1ckzWXmqq6ynHdJQJILnkmG57/lSZ6ntJe7TJRbGfZsNy+ODovzMjrGIEgiAUKZ1jjO0RBKFhMuUhOaa/DFMlR6K+mi7TpR1jIbnSYzrKNZ3H1Kks/2yu+3QoPxalfjrd5EzGTJKXZE2f6TyeRkKyyHO2yJLN9anIdGm76SDHdJBhOskxHlLpq9OxntNRJoDkmigmYkxNxlS3Ge3Rpk9/HbdyWBCE7aP/UrhmgiAIgiAIgiAIgiAIgiCIGcK4lcOMse2QcSchIgiCvNM6giAIgiAIgiAIgiAIgiAIYsrIhluJR0f/vRZAKYD/Gf39aQA9Wch/qnh6qgUYheQYYzrIAEwfOTJluspPcqXHdJVLiamWdyrLP5vrPh3KT5WZIqfITJKXZM0u00lGkkUekiVzpou800GO6SADMH3kmGimYz2no0wAyXUmMdVtRnu0acK4A9JJGcn4y5huPjQIgiAIgiAIgiAIgiAIgiCIMKos5mVmjFWJPxhjcwGYs5g/QRAEQRAEQRAEQRAEQRAEkSWy4VZC5G4AbzLGjgNgACoB3JnF/AmCIAiCIAiCIAiCIAiCIIgskTW3EgDAGNMDWDT685AgCP6sZU4QBEEQBEEQBEEQBEEQBEFkjawqhwmCIAiCIAiCIAiCIAiCIIiZQTZ9DhMEQRAEQRAEQRAEQRAEQRAzBFIOEwRBEARBEARBEARBEARBnIVkRTnMGCtljJWO/r+IMXYtY6wmG3kTBEEQBEEQBEEQBEEQBEEQ2WfcymHG2OcA/BPAu4yxLwDYAeDfAPyZMXb7ePMnCIIgCIIgCIIgCIIgCIIgss+4A9Ixxg4AuACAEUAbgPmCIHQzxvIAvCEIwrJxS0kQBEEQBEEQBEEQBEEQBEFkFU0W8ggKguAB4GGMHRMEoRsABEEYYoyNT/NMEARBEARBEARBEARBEARBTAjZ8DksMMa0o///N/EgY8yQpfwJgiAIgiAIgiAIgiAIgiCILJMNtxIVAE4LgsDFHC8DsFgQhNfHVQBBEARBEARBEARBEARBEASRdbJi2RurGB491gnAn438CYIgCIIgCIIgCIIgCIIgiOySDeXwm4yxrzPG1OIBxlgJY+x/APwo1UwYY3mMsfosyEMQBEEQBEEQBEEQBEEQBEEkIRvK4XMBzAOwjzG2gjG2EcC/APwTwPmJEjLG3mSMWRlj+QDeB/BzxtjWLMhEEARBEARBEARBEARBEARBJGDcPoeljMJK4R8BOA3gQkEQOlJI84EgCOcwxu4AMFsQhE2MsSZBEMiCmCAIgiAIgiAIgiAIgiAIYgIZt+UwYyyXMfYzALcCuBrAnwC8yhhbkUJyDWPMDmA9gB3jlYUgCIIgCIIgCIIgCIIgCIJIjWy4lXgfQCuABkEQXhME4T8B3AzgIcbY75Ok3QLgrwCOCYLwHmOsajQvgiAIgiAIgiAIgiAIgiAIYgIZt1sJxli5kgsJxth/CILw83EVQBAEQRAEQRAEQRAEQRAEQWSdcVsOJ/ItnEwxzBhbwBjbxRhrHv1dzxi7b7wyEQRBEARBEARBEARBEARBEInJhluJ8fBzAN8CEAQAQRCaAHxqSiUiCIIgCIIgCIIgCIIgCII4C5hq5bBJEIR/xRzjpkQSgiAIgiAIgiAIgiAIgiCIs4ipVg73M8bmARAAgDG2DkDXZBV+9dVXC6Nl0x/9TeTfuKG+Sn+T8DduqJ/S3yT8jRvqp/Q3SX/jgvop/U3S37igfkp/k/Q3bqiv0t8k/I0b6qf0Nwl/imgSnZwEvgTgaQCLGGOdAE4AuGmyCu/v75+soghiXFBfJWYC1E+JmQD1U2ImQP2UmAlQPyVmCtRXiZkA9VNiKpky5TBjTA3gi4IgXMkYMwNQCYLgmip5CIIgCIIgCIIgCIIgCIIgziamTDksCEKIMXbJ6P/d6aRljP0KQCOAXkEQakeP5QN4HsAcACcBrBcEYShduXhewMkBN3qcPpRYDZhTYIZKxdLNZsrLyDZyMgNI6dh465aovTJtS54X0D7oRo/TD3eAQ2W+GXMLx5/vZDJdZeQ4Hi1dDnQ5fLDbjKixW6HRKHuwmax6TIZc03X8mK59JZZU5Uz2/E4F6bbxZN4TpfFbbENPgEO+WQ+nLwCdWo0Sqx4V+dOzj0wkgUAIzV0O9Dj9yDFokG/SYmFJeJzw+TgcGD1XaNGh1KJHRUHOWddGBEEQxOTCcTwO9Tgx5AlCEHgYtBr0uvwotuhRU5oDs1E/1SISREZ4vUEc6Haix+lHiVWPJaVmHOn1yK7DiOlHsr1M5PlZuQYMe4LocfphNWrgD4Zg0mng40KYZTNJ+7h09oIzYW8705hqtxIfMMa2AfgjAElBLAjCn5Ok+w2AJwA8G3HsmwB2CYLwA8bYN0d/fyMdYXhewM6Wbtzzwj74gjwMWhW2rl+Gq2tKs9bZJqOMbCMn8xM3noMAJyQ9Nt66JWovABm1Jc8L2H24B609I3hsV2vW8p1Mpms/4jgeL+/vxH0vN0tyPbS2FmuXlslO7JNVj8mQa7qOH9O1r8SSqpzJnt+pqFO6bTyZ90SpLLNehQ9Pu6LacMOKajy/px2fOq8C1SU5WLGwZFr1kYkkEAjhlabTuP+VsTFi48pqHO93Y+WCIuxo7sED28bObVpVg7ZBDy6tLj5r2oggCIKYXDiOx6stXegY8uIP77XjhoYKPL57bN7esroW/1ZbTApiYsbh9QaxvblbWls1VNpww3mVsuuwa2rspCCeZiTby0SeX1Ccg5surMSmbS1xe44bz6/EfS834xtXL8ZVi0vw2sGelPaCM2FvOxOZ6qfMAGAAwAoAq0b/GpMlEgThLQCDMYfXAHhm9P/PAFibrjAnB9xSJwMAX5DHPS/sw8mBtAybp7yMbCMnc1OHI6Vj461bovbKtC1PDrjR1OGQlCLZyncyma4ytnQ5JAWsKNd9Lzejpcshe/1k1WMy5Jqu48d07SuxpCpnsud3Kki3jSfzniiV5fKG4trw8d2taKwvw2O7WtHU4Zh2fWQiaTrtkDYkQLg9HtvVitbeETR3u6TNi3hu8/YWuHyhs6qNCIIgiMmlpcuB1t7wy/DG+jJJMQyE56IHtjWjpXtkiqUkiPQ50O2MWlvdcnGV4jpMab9GTB3J9jKR5++4bJ6kGBavFfccP3r9CBrry3DPC/vQ0pWaLmmm7G1nIlOqHBYE4VaZv9syzK5EEISu0f93AyiRu4gxdidjbA9jbE9fX1/UuR6nT+pkIr4gj16XL0OR4pmMMrKNnMy8gJSOjbduidor07bscfoSyjpd7tFU99VM6HLIy9XtkJdrsuoxGXJN1/FjouVK1E/TIVU5kz2/U0G6bTyZz69SWW4/J3ucsfC/vIApH0+ySbJ+2q3QTrwA9Dj98m0Y4M6oNiKmnmyNpwQxkVA/nTy6HGNrHnF+jsQX5NHj9E+RdNMf6qvTl9i1lVdhXcoLUNyvnSnMxH6abC8TeV7p3opjmviv0n5dbi84nfaBZxJTqhxmjJUzxl5ijPWO/r3IGCsfb76CIAgABIVzTwuC0CAIQkNRUVHUuRKrAQZtdJMYtCoUWwzjFWlSy8g2cjKrGVI6Nt66JWqvTNuyxGpIKOt0uUdT3VczwW4zyspVapOXa7LqMRlyTdfxY6LlStRP0yFVOZM9v1NBum08mc+vUllmg0b2uCCE/1UxTPl4kk2S9VO7QjupGFBi1cu3oU5zRrURMfVkazwliImE+unkYbcZo9Y8cnNRiZVcSihBfXX6Eru2Munl16UqBsX92pnCTOynyfYykeeV7q245xD/tdtS3wtOp33gmcRUu5X4NYBtAGaN/m0fPZYJPYwxOwCM/tubbgZzCszYun5Z1AS8df0yKXhPNpiMMrKNnMx15baUjo23bonaK9O2nFNgRl25DRtXVmc138lkuspYY7fiobW1UXI9tLYWNXab7PWTVY/JkGu6jh/Tta/EkqqcyZ7fqSDdNp7Me6JUlsWgjmvDDSuqsaOpExtXVqO+3Dbt+shEUjfLhgfXRI8RG1dWo7o4B7WlFmxZHX1u06oaWAzqs6qNCIIgiMmlxm7F/OIcbFxZje37O7FhRfS8vWV1LWpKc6ZYSoJIn7pSa9Ta6pl3jiuuw5T2a8TUkWwvE3n+528dw+bVNbJ7jruvXIAdTZ3Yun4Zauyp6ZJmyt52JsLCRrZTVDhj+wRBWJbsmELaOQB2CIJQO/r7EQADEQHp8gVB+HqiPBoaGoQ9e/ZEHRMjH/a6fCi2TEzkw8koI9vIyQwgpWPjrVui9sq0LXleQPugGz1OPzwBDhX5ZilK5njyVWDcN3eq+momcByPli4Huh0+lNoMqLHbEgYRmKx6TIZc03X8SDHNhPTTdEi1bsme36kg3fsymc+v0vgd2YZ5Jh1G/EFo1WqUWPWoyJ8e44kME9ZPA4EQmrsc6HH5kaPXIM+kxaLRKNk+H4cDo+cKzDrYrXpUFORM1zYipgfj6hzjHU8JIkWon05zOI7HoR4nhjxBCAIPg1aDPpcfRRY9akpzzpZgdFO+RiWyj9cbxIFuJ3qcfpRY9VhSasaRXo/sOmyGcFb102R7mcjzdpsBw54gepx+WI0a+IMhmHQa+LkQ7DaTtI9LZy84HfUgMwTFhppq5fAuhC2Ffz966NMAbhUEYWWSdL8H8FEAhQB6AGwC8DKAFwBUAGgDsF4QhNigdVHMpIePmNGcVRMFMWOhfkrMBKifEjMFUroRMwHqp8RMgOZ+YiZA/ZSYCSj2U81kSiHDbQB+DOBHCPsIfgfAZ5MlEgTh0wqnEiqVCYIgCIIgCIIgCIIgCIIgiDBTrRwuFwRhdeQBxthHAJyaInkIgiAIgiAIgiAIgiAIgiDOCqbagcuPUzxGEARBEARBEARBEARBEARBZJEpsRxmjF0E4GIARYyxeyJOWQGop0ImgiAIgiAIgiAIgiAIgiCIs4mpciuhA5AzWr4l4rgTwLopkYggCIIgCIIgCIIgCIIgCOIsYkqUw4Ig/B3A3xljvxEEoQ0AGGMqADmCIDinQiaCIAiCIAiCIAiCIAiCIIiziakOSPd9xtjnAYQAvAfAyhh7TBCER6ZSKJ4XcHLAjR6nD3abASEe6HX5UGI1YE6BGSoVSymt3PVy5wFEHavIM6Fj2IMepx/uAIfKfDPmFiYuN11ZxHMDbj90ahU8gVDa9Yttm4o8E9qHPHHlJWuT2LxTkSmVPHleQPugO64dY9s70T2Su/9i+gG3H0atGm5/aFz3KVMCgRCaTjvQ7fTBbjWgbpYNOp2yV5ZU78N406QrVyZwHI+WLge6HD7YbUbU2K3QaKbahTrg83E40OVAt9OPUqsedXYbDIbEw6zXG8SBbid6nH6UWPWoK7XCaNQqXp9J+07GPVFiPPcqMm1lgRH+oIC+ET+sBi2cviCsRg1y9BpUF1rQ4fCm1U8nmlTG38mUN7JMk06DQCiEArMeFXkmtA160DbohlmnQYlVj4r89OetVOa6qb4nyXB4fTjc7Uavy48iix5ciINBo4Wf46DTqOEL8nD5ORTl6FBs1aM8d/rXiSAIgpgcYtdaxTYdeh0B+LgQ/EEelQXhfYLL78fhbre07ltQakZbvzduncRxPA73ODHoCcLt5zDLZsSCohwc7nNNu/UvQWRC5Dp/ToERLl8IPU4/iq16aFQMeSY1+kc49Lj8KMjRQadiUDGG/BwdZufRGmwySLYHEHUlg56w/sbtC0GvVWHIG4DVoMWsPD26hwPodvowO9cIk16D/hG/pDsS9yA5eg0sBjWc3jG9SmV+WLfUPeyDVsMw7A3CatRC4HmUWI3ghbFyU9VlJarniX53wv3Q2cBUK4eXCILgZIzdBOBVAN8EsBfAlCmHeV7AzpZu3PPCPuSZdLjloko8tqsVviAPg1aFreuX4eqaUkXlpphW7nq580/ceA4CnCAdqyww4qtXLUTHkDflcpPVIzYPANjZ0o2Hdx7EDQ0VeHx3+vWLbZvKAiO+vKIa973cHJXXVYtL8NrBHsU2ic07FZmStbN4ze7DPWjtGYlqx9j2TnSP5O6/mP7hnQdx28Vz4QmGxnWfMiUQCOHlptN44JWx9t6yphZr62fJKv1SabNspElXrkzgOB4v7++M6msPra3F2qVlU7pA9vk4bDvQhQe2RdR9dS1W19kVFcRebxDbm7vj0qyqLZVVEGfSvpNxT5QYz72KTLugOAefvqAST/39aNz4cO81i3Csz42v/6lp0p9DJVIZf9N5riZCng0rqrH7UDc+dX5l1P3ZuLIa1SU5WLGwRHHe2rp+GXQahrt+90HKc91U35NkOLw+/LW5L+pZ3NRYgxffb8X6hgr4giF879VD0rkH19SiI8+DC+cWTds6EQRBEJOD3Frrh9fVoW8kgEf+elg69tS/L0evMxC37jvSPYRf/O8paZ3UWGPH3w73RO0HGyptWN9QGZV2Oqx/CSIT5Nb5m7e3RKwbl+Jobyh6XbaqBmomQD+kxskBNy6dX0xrsAkkme5K1JX84b32uP3ZhhXV2HdqAFcutuOBbS0p6Y42rarBU38/irYBrzS+/Xh3q/R7w4pqPL+nHZ+/fD7aBz148s1jaemy0qln7H7obGGqZxItY0wLYC2AbYIgBAEIUynQyQG31DGuXV4udWAA8AV53PPCPpwccCdNK3e93PmmDkfUscb6MrT2jqRVbrqyiOca68ukhynd+sW2TWN9mfRwR+bV0uVI2CaxeaciU7J2Fq9p6nDEtWNseye6R3L3X0zfWF+GAU9g3PcpU5pOO6QFqFj2A680o+m0Q/b6VNosG2nSlSsTWroccX3tvpeb0dKVvTIy4UCXQ1rAiHI9sK0ZBxLIdaDbKZ+mW967TibtOxn3RInx3KvItHdcNg+bt7fIjg/fe/UQjvaOTMlzqEQq4+9kyitX5uO7W3HLxVVx9+exXa1o6nAknLfueWEfmjocac11U31PknG42x33LG7e0YJbLq7CA9ta0O8ORJ27/5VmcCFM6zoRBEEQk4PcWuton1tSDIvHRnwh2XXflTVl0u/7Xg6vHWP3g+H5aPqtfwkiE+TW+ZF9m+cRvy7b3gKTTotjfW64vCFag00wyXRXoq5Ebn/2+O5W3HThXDywrSVl3ZG41xN/3/dyc9Tvx3eHyxL7Qbq6rHTqGbsfOluYauXwzwCcBGAG8BZjrBLhoHRTRo/TJ3UMxiD9X8QX5NHr8iVNK3e93HleiC6DsfhjycpNVxbx3HjqF5tWKa8uR+I2ic07FZmStbN4jVw7JmvbZPdfTJ+t+5Qp3Qpt0OPMrG9mK026cmWCUp/qdkx8uyei2+lXqLtfMU1Pmmkyad/JuCdKjOdeRab1+rmE4wMf80pxsp5DJVIZf+XOTbY83gCn2J6J5q1kbT4VdRwvSs+i2EZy9R3yBKd1nQiCIIjJQW6tJbdPcPvl592+iLnEF+TR7fTHpfcqpJ3q9S9BZILcOj8SpWfFHeDAC4A7wNEabIJJprsS92VK+7NhdzBt3RFjyX+L/SBdXVY69YzdD50tTKlyWBCExwVBKBME4ROCIAgA2gFcMZUylVgNMGjHmiXy/+LvYoshpbSx18udV7P4MuSOJSo3XVkiz42nfnJpY3/bbcaUykhHpmTtLF6TSdsmq2Nk+mzcp0yxK7RBiTWzvpmtNOnKlQlKfarUNvHtnohSq16h7nrFNCVppsmkfSfjniiWPY57FZnWpNckHB9iv/aZrOdQiVTH39hzky2PSadRbM9E81ayNp+KOo4XpWfRONpGcvXNM2mndZ0IgiCIyUFurSW3TzAb5Ofdooi5xKBVodSqj0sfuRaKunaK178EkQlK63wRpWfFrNNAxQCzTkNrsAkmFd1Vov1Zrlmbtu5IEJL/FvuBUh7p9otEe52zrY9NteVwFEIYbiplmFNgxtb1y2DQqvDi3g5sXFkd1em3rl8mOeJOlFbuernzdeW2qGPb93difnFOWuWmK4t4bvv+TmxYkVn9Yttm+/5OPLS2Ni6vGrs1YZvE5p2KTMnaWbymrtwW146x7Z3oHsndfzH99v2dyDfpxn2fMqVulg1b1kS395Y1taifZZO9PpU2y0aadOXKhBq7Na6vPbS2FjX27JWRCXV2G7asjqn76lrUJZCrrtQqn6bUKn99Bu07GfdEifHcq8i0P3/rGDatqpEdH+69ZhHmF+dMyXOoRCrj72TKK1fmhhXVeOad43H3Z+PKatSX2xLOW1vXL0N9uS2tuW6q70kyFpaa457FTY01ePad49iyugaFZl3UuQfX1EKjxrSuE0EQBDE5yK215hWZ8bWPL4w6lqNXy677Xm/plH4/tDa8dozdDz7zzvG4tNNh/UsQmSC3zo/s2yqG+HXZqhp4AkHMKzLDYlTTGmyCSaa7EnUlcvuzDSuq8dt3T2DL6pqUdUebVtVgR1P0WBj5e8OKauxo6pT6Qbq6rHTqGbsfOltggjClLn6nlIaGBmHPnj1xx8WojL0uH0qt4QiMfSM+FFuSR0CMTCt3vdx5AFHHKvJM6Bj2oMfphyfAoSI/HN02XWfYiWQRzw26/dCmEeExUdtU5IUjSsaWl6xNYvNORaZU8uR5Ae2D7rh2jG3vRPdI7v6L6Qfdfhi0arj9oWT3adxezOX6qhgVWYweWj/LljDAWKr3Ybxp0pUrE8Tott0OH0ptBtTYbdMiGIfPx+FAl0OKQF1ntykGoxPxeoM40O0cS1NqlQ1GJ5JJ+6aYZkL66XjuVWTaigIj/EEBfSN+WA1aOL1B2IwamPUaVBdZ0OHwptVPJ5pUxt/JlDcy2rBJp0YwxCPfrJciBbcPumFSiM6byryVylyXpTpOSD8FwkHpDne70evyoyhHD47noNdoEeA4aDVq+IM8RvwcCs06FNv0KM+d+n5GTGvG1TmU+ilBZBnqp1kidq1VYtOh1xGAjwshwPHSPsHl9+Nwt1ta9y0oNaOt3xu3TuI4Hod7nBj0BOH2c7DbDFhYZMHhPte0W/9OAhM29xNTR+w6f8QXQo/Lj2KLHlo1Q65Rjf4RDj0uPwrMOujUDCrGkJ+jw+y8abkGO+P6abI9gKgrGfKE9Tdufwg6jQrD3gCsei1m5evRPRxAj9OHslwjzHoNBtx+SXck7kFy9BrkGNRwesf0KpX5Yd1St8MHrZph2BuE1aAFwKPYYgQvjJWbqi4rUT1P9LsT7ofOIBQrRcrhafTwEWcsZ9xEQZyRUD8lZgLUT4mZAindiJkA9VNiJkBzPzEToH5KzAQU++mUvmpkjJkYY/czxn4++ruaMdY4lTIRBEEQBEEQBEEQBEEQBEGcDUz1dyi/BuAHcNHo704AD02dOARBEARBEARBEARBEARBEGcHU60cnicIwg8BBAFAEAQPsmCOTxAEQRAEQRAEQRAEQRAEQSRmqpXDAcaYEYAAAIyxeQhbEhMEQRAEQRAEQRAEQRAEQRATiGaKy98EYCeA2Yyx3wL4CIDPTqlEBEEQBEEQBEEQBEEQBEEQZwFTqhwWBOFvjLH3AVyIsDuJjYIg9I8nT8bY3QDuQNga+QCAWwVB8I1XVp4XcHLAjR6nDyVWA+YUmKFSxXvAiLzObjMgxAO9LuX/J8orUX5iOgBoH3Sjx+mHO8ChMt+MuYXxx+cWmMEL8uVX5JnQPuSRyhAEoNflRyAUQp5RB3cgFJXHoMcPo1YNtz8Ul3ekXOm2V7K2yOT+pHuc43i0dDnQ5fDBbjNicYkFHQ7vuOWbCGJlrbFbodEofwyQ7vWZpvH5OBzocqDb6UepVY86uw0Gg/JQk0kfSLeMTMoJBEJoOu1At9MHu9WAulk26HTqhGVkksbjDaC524Uepx8lVj1qSy0wGXVZq0emaSYbnhfQPujGwEgAPi4Ef5BHZUF4PMu2rNloj0h5AyEebj8Hq1ELPxdCea4pbkyc6PaOnSu4kID2IQ/MOg2KLXowBnQ54se7Qz1ODHmC8AVDqCo0w+3n0O30ocCsBwMQEgQMuAOw6DWYZTOgLNeEgz1OdDl8KM8zwqBRo2/Er1hPUa4Btx86tQpufwhmvQaBUAgFZv206ouR7eEJcMgz6eDnOGhVarj8HHJNWjAA3iAPxnhoVRr0j/hRZNGjxKrH7LzpUxeCIAgidTJZ78qlnZVrhM2oQb8rgEAoBI4HfIEQiq0G+IJBMKZC34gfBWYdSi16CGA4MeBGgUkHjhfQN+KX9h+nnV70uvwY9gSRb9aCF4D+ET/Kck2osVuhUjFp3i+2GKBWxc/zBDEdEfdxg54g8kxaOL1B2ExauP1BGHUaqMAw7A0i16jFkCcIg1aFEqsODm8IQ6NpghwPe66R+noWyFSP4vAGwPNA34gfFr0GRp0a/e4ArAYNjFo1hjwB6DVq+DgOJRYDtGo1OoY8MOs1GPYEUWDWRe2VY/cyok7K7edQaNHDz8XvHeRkBFLTQxHxTKlymDH2SQC7BUH4f6O/cxljawVBeDnD/MoAbACwRBAEL2PsBQCfAvCb8cjJ8wJ2tnTjnhf2wRfkYdCqsHX9MlxdUxrV0SKvyzPpcMtFlXhsV6vi/xPllSg/Md0TN54DAGjtGUl4PFH5lQVGfHlFNe57uRl5Jh2+cHkV3IEQ/vBeO267eC48QWdUurHjIcX6PHHjOQhwQlrtlawtMrk/Vy0uwWsHe1I+fuXCYmw7cBr3vdwstc2XrqjGA680j0u+iYDjeLy8v1OS1aBV4aG1tVi7tEx2MZvu9Zmm8fk4bDvQhQe2jaXZsroWq+vsssrbTPpAumVkUk4gEMLLTaej7v2WNbVYWz9LUdmbSRqPN4AdzT1xdWmsLZFVEGfSXtl6ziYSnhew+3APTg954Q6EUhofx1PWeNsjUl4fx2Pr345Ied195QKc6HPje68emrT2TjZXbFxZDbNOjZ/+/TiGPAFpvPvrwW50DHkVx/JNjTV46q2jaBvwwqBV4d5rFsGo0+D+V5pTmstEuR7eeRA3NFTg8d1j125YUY3n97TjG1cvnhZ9keN4vNrSJbWHKOd3VtXgp38fa4NNq2rwxqEuXLHQjs073h9rq1U1mJXrxqXzi6e8LgRBEETqZLLeTZT2wTW1EAQeA+5g9Jy6qgZPxcwnWjXw//Z34apaOzZvb5H2H1+5aiG6HT5s/dsRLCjOwacvqJTOi2UUW3X43HPvR831z/6zTZrnp8PcShCxiPu4J99sjVsb3n3lAhi1Kvzyf0/EnduyugYv7GnHikWlUcepr4+PTPUov3r7GNadW4HvRIxLG1dWw6RV47vvnMDnL58PNQQ8+fdjuO3iuWjtcUftlzasqMZ397TjS1dUY239LGg0qqi9jKiTihxD775yAX73rzZp7wAgTvZU9VCEPFPtc3iTIAgO8YcgCMMIu5oYDxoARsaYBoAJwOlx5oeTA26pgwGAL8jjnhf24eSAW/G6a5eXS51Z6f+J8kqUn5iuqcOBpg5H0uOJym+sL5MWNNcuL0e/O4DHdrWisb4MA55AXDql47Hlp9teydoik/vT0iUvh9LxptMOqS3EthEVfeORbyJo6YqW1Rfkcd/LzWjpcmTl+kzTHOhySIpOMc0D25pxQCFNJn0g3TIyKafptCPu3j/wSjOaTiuXkUma5m6XbF2au11ZqUemaSabkwNuNHU4pPFnImXNRntEyisudMS8fvT6EfS7A5Pa3snmisd2taLfHcC1y8ujxrvW3pGEY/nmHS1orC+Tfve7A7j/lWbF62PrKcrVWF8mLeTFax/fHZ5PpktfbOmKbg8gLOd3tke3webtLbjpwrnYvKMluq22t8DlDU2LuhAEQRCpk8l6N1Ha+19phkmnjZ9TZeYTg0aDz14yV1L8AuH9x9HeEWl9ccdl86LOi2W4vKG4uT5ynqf5iJiOiPs4ubWhuIaWO/fAthbccnFV3HHq6+MjUz3KLRdXSYph8fxju1ox4Anfv83bW2DSayXdUex+SdwHiHvl2L2M3J7wR68fido7yMmeqh6KkGeqlcNy5WdszSwIQieARwG0A+gC4BAE4bXIaxhjdzLG9jDG9vT19aWUb4/TJ3UwEV+QR6/Lp3gdY0j6/0R5JcpPhBfCf8mOJyo/9pyYLvL/kdcpHY8tP932StYWiVDKp8uR3vHumHzSuVcTQaK+qlgHh7xs6V6faZpup182TY9TPs5kJn0g3TIyKSe2L4yVkUiu9NP0TEJ7Zes5UyKTMTWWHqdPcTzL9jOXjfZIJi8vIO7YRI4byeYKUSbGxn53j9YhWToW8ZI9lesj6ynKlSjvyRpTk/XTLodP8X5GtoEvyGPIHZS9zh3gJm1+IM5MsjGeEsREc6b100zWu8nSugNcSvOJO8DFzSmxey2vXz4vd4BTzH8y9yvTmTOtr54JiPu4ZOtVuXNehedqpvf1qeynmepRlMalyPvnDnBx41nkteJ1PU5f3F4mWZpel09W9snYS57JTLVyeA9jbCtjbN7o31YAezPNjDGWB2ANgLkAZgEwM8b+PfIaQRCeFgShQRCEhqKiopTyLbEaYNBGN5VBq0KxxZDwulT+r5RXsvwAQM3Cf6kcT1Z+ZFrxt1IeifKWO69Ux1TbNRlK+dhtxvSOK+QzXvkyJVFfVapDqU1etnSvzzRNqVUvm6bEqpe9PpM+kG4ZmZSj1BdKrAnaK4M0JZPQXtl6zpTIZEyNpcRqUBzPsv3MZaM9kskb+9XSRI8byeYKUSZBGPttH61DsnRChKI7lesj6xkpl1LekzWmJuundptR8X5GtoFBq0K+WSt7Xdi/8+TMD8SZSTbGU4KYaM60fprJejdZWrNOk9J8YtZpZOeUyPnIpJfPy6zTxB2LnOdpPjrz+uqZQOQ+LtEaWu6cSeG5mul9fSr7qbIeJfFxpXFJ3G+IY5QgKO+XxOtKrIY4OZKlKbbEp0mUbqb3kcliqpXDXwYQAPD86J8fwJfGkd+VAE4IgtAnCEIQwJ8BXDxeIecUmLF1/bKogWzr+mWSw2u5617c24GNK6sT/j9RXonyE9PVldtQV25LejxR+dv3d+KhtbXSuQKzDhtXVmP7/k7km3Rx6ZSOx5afbnsla4tM7k+N3ZrW8bpZNqktxLbZsqZ23PJNBDV2a5SsBm3YP1qN3ZaV6zNNU2e3Ycvq6DRbVteiTiFNJn0g3TIyKaduli3u3m9ZU4v6WQnqnkGa2lKLbF1qSy1ZqUemaSabOQVm1JXbpPFnImXNRntEynvPxxZE5XX3lQtQaNZNansnmys2rqxGoVmHP7/fETXezS/OSTiWb2qswY6mTul3gVmHB9fUKl4fW09Rru37O7FhRfS1G1ZUY0dT57TpizV2a1R7AGE5v7Mqug02rarB/7x7Apsaa6LbalUNLEb1tKgLQRAEkTqZrHcTpX1wTS08gWD8nCozn/g4Dr9++wQ2rRqbU7bv78S84hxpffHzt45FnRfLsBjVcXN95DxP8xExHRH3cXJrQ3ENLXduy+oaPPPO8bjj1NfHh7IeRV6fIx5/5p3j+E7MuLRxZTUKTDrsaOrEplU18PiD2NEU1h3F7pfEfYC4V47dy8jtCe++ckHU3kFO9lT1UIQ8TBCE5FfNEBhjFwD4FYDzAHgRDkS3RxCEH8td39DQIOzZsyelvMVIiL2ucERYpaiHkdeVWg0I8UDfiPL/E+WVKD8xHQC0D7rR4/TDE+BQkW/G3ML443MKzOAF+fIr8kxoH/JIZYiRIYOhEHKNOrgDoag8hjx+GLRquP2huLwj5Uq3vZK1RSb3J93jYsThbocPpTYDFpdY0eHwjle+cXs/l+ursbLW2G0JA2eke32macQItD1OP0qsetTZbYqB4oDM+kC6ZWRSTiAQQtNphxTptD4immo203i8ATR3u6S61JZaZIPRZVqPNNJMSD9NFZ4X0D7oxsBIAD4uhADHS+NZtgMIZGPciZQ3EOLh9nOwGrQIhEIoyzXFjYkTHQQhdq7gQgJODXlg0mlQbNGDsbDrk9jx7lCPE0OeIHzBEKoKzXD7OXQ7/cg366BiQIgXMOgOwKzXYJbNgPJcEw72ONHt8KEszwiDRo1+t1+xnqJcg24/tGoVPIEQTDo1giEe+TERh1Nkwvqp2B7DniA8/hByzVr4OQ4alRojfg65Ri0YA7xBHioI0KjV6B/xo8iiR4lVj9l5FA2ZiGJcnWE84ylBpAH1U2S23pVLa7cZYDNpMeAKwB8KgeMBXyCEYosePo4DYyr0j4Tn2FKLHgIYTg64kW/SgeMF9I34YR/df5x2etHr8mPYE0S+WQteAPpH/CizGVEzywaViknzflGOAWpV/Dx/BjGla1Qiu4j7uCFPELkmLZy+IGwGLdwBDkadGiowDHuDyDVqMewJQq9VocSig8MXwpAniDyTFkGOhz3XON36+ozsp5nqUZzewKhOyY8cvQYmnRr97gAso/8f9gSg06jhD4ZQZNVDp1ajc9gDk1aDYV8Q+SZd1F45di8j6qQ8AQ4FZh0CMnsHORmB1PRQZzGKjTGlymHG2AIAXwUwBxG+hgVBWDGOPDcDuAEAB+ADAHcIgiDrwJMmCWKSmJETBXHWQf2UmAlQPyVmCqR0I2YC1E+JmQDN/cRMgPopMRNQ7KcZB3/LEn8E8BSAXwAIZSNDQRA2AdiUjbwIgiAIgiAIgiAIgiAIgiDOVKZaOcwJgvDTKZaBIAiCIAiCIAiCIAiCIAjirGOqA9JtZ4x9kTFmZ4zli39TLBNBEARBEARBEARBEARBEMQZz1RbDn9m9N+vRRwTAFRNgSwEQRAEQRAEQRAEQRAEQRBnDVOqHBYEYe5Ulk8QBEEQBEEQBEEQBEEQBHG2MqXKYcaYCcA9ACoEQbiTMVYNYKEgCDumUi4A4HkBJwfc6HH6UGI1YE6BGTwv4FCPE0OeIHzBEOYXmgHG0Ovywx3gUJlvxtxCM1QqljCf2PPtg270OJXzkMunIs+E9iEPBtx+6NQqeAKhuPxTKVvuvHg8Ud7J2i0yrd1mQIgHel1j5QCQyp6Va8CwO4gupw/leUYYNGr0jfijjtttRtTYrdBoVHFlxbaJUn0T3WM5GZOlTeW+TSQ+H4cDXQ50O/0otepRZ7fBYFB+pAOBEJpOO9Dt9MFuNaBulg06nTphGcn6UDbKyaSMdOsOAF5vEAe6nehx+lFi1aOu1AqjUZu1emRKunXhOB4tXQ50OeSfCzkyaeOJhOP4qLG0qsCMuUU54HkBLV0ODHn8MOu0GPIEUGJNrY5y8LyAE/1utA24YdCpoFerUZCjQ0V+9Dh5ot+N08Me6DRqOLxB5BjUsFuNqBwd91tOO9Dp8KIwR48Sqx6z85TbbzLbOlFZqcoReZ1JpwFjAgKcgP4RP4py9NBqGAQBcPtDMOs1CIRCKDDrE84n6Y6nqdRnouE4Hkf7nRhyc3D5OeQatRj2BJBr0sEd4JBn1GLEH4LLx6HIooOKCbAZ9XD7OZx2+DAr1wiLXoPuafKMEQRBEMkZz1pPXFf2Ov0oturhCXAwaNXIM2mgU8fPB5Hrt8IcPfwchxAP2IxaWPQa9Lj8KLEaMMtiQHO3Ez1OH4oteoR4HoypUGzRgzGMrv8ym2cJYqqIXOMVWwzQ64DTQ35pX5ZnUsPhDWHQHYRRq4Zex6BTqdHj8sGoVcNm1AICcGrYiwKzDjl6NaoLLUn3f4QyyXRBcjoWky5+LyCOoyEhBBVU6HH5UWDWwahVQaNWgRcECALgCYRQmKOHLxjCiD+IEA8EOB6V+Sao1Qx9I34YterR9XYQNqMWJVY9uFD8WDfd9rZnClP9NP0awF4AF4/+7gTwRwBTqhzmeQE7W7pxzwv74AvyMGhV+NnNy+H0cugY8uKxXa3IM+nwhcur4A6E8NiuVum6reuX4eqaUqnTxuYTe3734R609owo5iEnT2WBEV9eUY0f727FDQ0VeHx3fFoAScuWO3/V4hK8drAHD+88qJh3IqXIzpbuqLR5Jh1uuagyqn5P3HgOApyAe17YhwXFOfj0BZXYvL0l6trI42K6h9bWYu3SMmg0KsU2ue/l5pTkjUwvJ2OytKnct4nE5+Ow7UAXHtg2Vt8tq2uxus4uO0kGAiG83HQaD7wScf2aWqytn6W4CE7Wf+VIt5xMyki37kB4Ab+9uTsuzaraUlkFcSbtlQnp1oXjeLy8vzOqn0c+F3Jk0sYTCcfxeLWlSxpLRZn+6/ql4AUBj752OG7sSVZHOeTqvXFlNcw6NWbljWDFwhIAiBuzIq9dYregbyQQ1d6bVtVgVq4bl84vln2JN1ltnagssV7J5JAbR7/40fnYtG1s3N28ugY/efMo2ga8MGhV2LCiGs/vacc3rl4sO5+kO55ORdvFwnE8dh/pxcBIAE/9/WhUX6gsMOI/Vy7AoS5XVJ0eWluLUMiNTds/jOozz/6zDUOewJQ+YwRBEERyxrPWk1tXbmqswYvvt+O6cyugZgJ+9PpRaT64cmExth04Hb2eGL1+5eJSmHVq/PTvx1GWq8f6hkrZfMXr/rS3A9fU2adsD0IQ6RK7xlt/rh0Nc4qkfl5ZYMRdV1Tj/ohnUVyz//TvxzHkCcT93rSqBqeHfbh8fhEpiDMgmS4okY4lci+woroI25q7sOdEHxrmFkWNp5tW1cBm1ECtYvj5W8ewp80Bg1aF719bhz6XH1v/dkS69msfXwiLTo0BTzBqbNu0qgZP/X1sHyInI42B2WOqA9LNEwThhwCCACAIggfAlN/RkwNuqbMBgC/Iw+UNobV3TBl47fJy9LsD0m/xunte2IeTA27FfGLPN3U4EuYhl09jfRnue7kZjfVl0gY2Nm0qZcudb+ly4J4X9iXMO1m7Raa9dnl5XP2aOhxS2XdcNk9SAEdeG3lcTHffy81o6XIkbJNU5Y1MLydjsrSp3LeJ5ECXQ5pQxfIf2NaMA6PtE0vTaYc0WEvXv9KMptPy1wPJ+282ysmkjHTrDgAHup3yabqdWalHpqRbl5YuR1w/j3wu5MikjSeSli5H1FgqyvSVP+5Ha++I7NiTrI5yyNX7sV2t6HcH0NThiBon5cp8bFcrXL5QXHtv3t4Clzck236T2daJykpVDrlxVFQMi+k2bWtBY32Z9Pvx3a1orC9TnE/SHU9Tqc9E09LlQGD03sb2hcb6MpwYcMfV6b6Xm9Hp8MX1mWuXl0/5M0YQBEEkZzxrPbl15eYdLbjl4ips3t4Ck04bNR80nY5fv4nXi2uTa5eX45aLqxTzFa+747J5U7oHIYh0iV3jrV1eEdXPG+vLJMUwEL1mF5+j2N+bt7cgGBIS7v8IZZLpghLpWCL3Age6wuPo2uUVcePp5u0t4HkgyAm45eIq6fiJfrekGBaPPfLXwzDptXFjm7g2TyQjjYHZY6qVwwHGmBHhIHRgjM0D4J9akYAe59iGT8Tt58ALkI4zhqjfIr4gj16XTzGf2PPJ8pDLh7HwNeK/cmlTKVvufNfoZjdR3kqIeUamlcsnss5ePyd7beTxyPK7HfLypytvZPpM0qZy3yaSbqdftvwep/zj061wv3ucye9nbJpEdUy3nMzKSK/u4XImvr0yId26dDnk5RKfCzkyaeOJpMuh/PzwgvLzmKiOcijVmxfCY1DkOKlUpjsgPw65A5xs+01mWycqK1U5Uh1HGYv/rTSfZDJ3JKvPRNPl8ME9OufEyp9orucFxB0T22oqnzGCIAgiOeNZ6ymtK72j6wZ3gIuaD5TKEq8X1z9K+5/I67wKaxOac4jpSuwar9/lT2n9KT4XSr/dAS7h/o9QJpkuSCTR3iA8toXvZew9Fa9zBzi4Axy8AU46rrSudiuMf7H7EKX9MI2B42eqlcObAOwEMJsx9lsAuwB8fWpFAkqsBhi00U1jNmigZog6HvsbCP8uthgU84k9nyyPRPlE/hubNpWy5c7bbcakeSsRmWdk2th8Iuts0mtkr409Lp4rtSWWP1V5Y9OnmzaV+zaRlFr1suWXWPWy19sV2qvEmtr9jEyTqI7plpNJGenWPVzOxLdXJqR9HyOez8jrxedCjkzaeCKx24yKz4/4JVC6dZRDqd4qBqgY4sZJuWvNOvlxyKzTyLbfZLZ1orJSlSPVcVQQ4n8nmk8yaYOp7Kd2mxFmg0axLyTrr5HHxLaaymeMIAiCSM541npK60rj6LrBrNNEzQdKZYnXqxggCMr7n8jrTAprE5pziOlK7BqvyCL//MT+Fp8Lpd9mnSbh/o9QJhVdUOTx2N/iXkDcyyrdU7NOA7NOA6NuzPWH0ro6ci0eW1YqMtIYOH6mVDksCMLfAFwL4LMAfg+gQRCEN6dSJgCYU2DG1vXLojaKFoMa84tzsHFlNQxaFV7c24ECs076LV63df0yKeCaXD6x5+vKbQnzkMtn+/5OPLS2Ftv3d2LDCvm0qZQtd77GbsXW9csS5p2s3SLTvri3I65+deU2qeyfv3UMm1bVxF0beVxM99DaWtTYbQnbJFV5I9PLyZgsbSr3bSKps9uwZXV0fbesrkXdaPvEXT/Lhi1rYq5fU4v6WfLXA8n7bzbKyaiMNOsOAHWlVvk0pdas1CNT0q1Ljd0a188jnws5MmnjiaTGbo0aS0WZ/uv6paguzpEde5LVUQ65em9cWY1Csw715baocVKuzI0rq2ExqOPae9OqGliMatn2m8y2TlRWqnLIjaObV0ePu5tX12BHU6f0e8OKauxo6lScT9IdT1Opz0RTY7dCpwnf29i+sH1/J+YUmOPq9NDaWpTZDHF95s/vd0z5M0YQBEEkZzxrPbl15abGGjz7znFsWlUDTyAYNR/UzbLFrydGrxfXJn9+vwPPvHNcMV/xup+/dWxK9yAEkS6xa7yX3m+P6ufb93fiwZhnMfK5kPu9aVUNtGqWcP9HKJNMF5RIxxK5F6izh8fRl95vjxtPN62qgUoFaDUMz75zXDo+p9CMez62IOrar318ITy+YNzYtmlV9D5ETkYaA7MHEwQh+VXZLpSxRYIgHGKMLZc7LwjC+5MhR0NDg7Bnzx7Zc2IExF5XOKLmnNGo9Yd6nBjyBOELhjCv0AzGGHpdfngCHCryzZhbKB/BPTKf2PPtg270OJXzkMtHjBo56PZDq1bBEwgpRqtPVLbcefF4oryVkEsrRtTtGxkrB4BUtt1mwLA7iG6nD2V5Rhg0avS7/VHHS20G1NhtUQGplNpEqb6J7nGpNV7GZGlTuW+jjNuPtlxf9fk4HOhySFFe6+y2hA75xUiiYlTP+hQiMifrQ9koJ5My0q07MBZVWkpTapUNRpdpPTIl3bqI0a67HfLPhRwptvGE9FM5OI6PGkvnFphRVZQDnhfQ0uXAkCcAs06DIU8QJVZ9SnWUg+cFnOh3o33QDZ1GBYNGjYIcHSryo8fJE/1udDk80KrVcHqDMOnVmGUzonJ03G857UCnw4tCsx4lNj1m5yn30Uz6c6YkKitVOSKj/Zp0aqgY4OcE9I/4UZijh17DwI9GGDbp1AiGeORHRCiWkyXd8TSV+kQwIf2U43gc7XdiyM3B5eeQa9TC4QnAZtTBE+RgM2jhDoTg8nEozNFBrRJgM+rh9nNS5HiLQYueSbjvxIxhXB0g1fGUIMbJWd1Px7PWE9eVvS4/ii16eAIc9Bo18s0a6NSauPlAXL91OXwozNHDz3EI8YDNqIVFr0HviB/FFgNmWQxo7naix+lDsUUPXuABqFBs0YOxsDuMTOfZGcykrVGJiSFyjVeUY4BeB5we8of3PxY98sxqOLwhDLqDMOrU0GkY9Go1el1+6LUq5BrCe7ZTw14UmHUw69RYUGSZbsHoZlQ/TaYLitWxiHuF2L2AOI6GhBBUUKHH5UeBWQeDVgWtWgVBEKS9RGGOHr5gCCP+IEI8EOB4VOSboFEz9I/4YdCq4faH4PQFkWvUotiqBxeKH+smc791BqLYUFOlHH5aEIQ7GWNvyJwWBEFYMRly0CRBTBIzaqIgzlqonxIzAeqnxEzhrFa6ETMG6qfETIDmfmImQP2UmAko9tMpedUiCMKdo/9eMRXlEwRBEARBEARBEARBEARBnO1MuR0+Y+xiAHMQIYsgCM9OmUAEQRAEQRAEQRAEQRAEQRBnAVOqHGaMPQdgHoB9AEKjhwUApBwmCIIgCIIgCIIgCIIgCIKYQKbacrgBwBJhKhwfEwRBEARBEARBEARBEARBnMWkH/49uzQDKJ1iGQiCIAiCIAiCIAiCIAiCIM46ptpyuBDAh4yxfwHwiwcFQVidaYaMsVwAvwBQi7CLitsEQfjnOOUkCIIgCIIgCIIgCIIgCII4o5hq5fB3JiDPxwDsFARhHWNMB8CUaUY8L+DkgBs9Th/sNgNCPNDr8qHEasCcAjMA4OSAGwNuP3RqFQIhHjq1Cp5ASLpGpWJSPg5vACEe6B/xw24zosZuhUrFpDIi0wBAIBDCh91OOH1B+II85hWZATBJhoo8EzqGPehx+hEIhZBn1MEdCMEd4FCZb8bcwjEZxfwr8kxoH/LIlpdJ28jVSaNRxbVfbJvFls/zAtoH3ehx+uEOcJhbYAYvAIMef8I2VapXot9y91Jsg1RkzlYbjhefj8OBLge6nX6UWvWos9tgMCg/0oFACE2nHeh2+mC3GlA3ywadTp2wDI7j0dLlQJfDF3d/lZBrw0Ttk0kZk1EXjzeA5m4Xepx+lFj1qC21wGTUZV2udMuZrPuYLdxeP1q6R9Dj9MNu00OrUqF9yCvVtXskgB6nD8UWA9QqoG8kfjwVz4XlV35+x0uycWVOgRk8L+BQjxNDniB8wRCqCsyYW5SjKEMqz0M6z4zSvGTSacALPFSMyY6XkeOrOD9EjqXiPCa2t0YNdDvir89m+yaaE6YKjuPxYbcDvU4/rEYtfEEOOrUaTh8Hm1EDFWNweIMotujgDwkYGAlgVq4RS0on75kiCIIg0idyDiq1GuAJcBhMMpdHpomcG13+IKwGLfpcfhRa9DBp1bAYNKjIj5/DlNZgHMfjwy4HTjt8yM/RQiUw9I34UWwxIBAKweXjYNRpYNapUZCjw+y8xPNjuutvgphKxLVpr9OPYW8QFoMGfo5DnkmHEA+cHvah0KKDSavGoCeAfFNYzzEwEkCJVY9FpWYc7/dOyd5mspmKZ1tpTzTg9kOvVsHpC0KnUaPP5UexRQ+NmiFHr4UvGMKIP4gQj9H9iB4BjseQJwiTTg2tmkGjZuD58J7PbjVAANDr8qM8zwi9Ro1TQx6YdRqUWPVxY6rSmKy0X4kcZ61GDexWI2ZPE13OdGRKlcOCIPydMVYJoFoQhNcZYyYAibUcCWCM2QBcBuCzo/kHAAQyyYvnBexs6cY9L+xDnkmHWy6qxGO7WuEL8jBoVXjixnMQ4AQ8vPMgbmiowPN72nFDQwUe3z12zdb1y3DV4hK8drAHv3r7GK5bXoHNO1qk84+sq4eKqfCVP+6LSnN1TSk4jsfOg93oHPLisV2tcTJUFhjx1asWomPIiz+8147bLp4LT9ApK+M9L+yT0nx5RTXue7k5rrx0HgixbeTq9NDaWqxdWgaVikntpyRPZBu92dqL1p6RqLr+4b3EbapUr0S/5e6l2AYAksqcrTYcLz4fh20HuvDAtjE5tqyuxeo6u6yCOBAI4eWm03jglYjr19Ribf0sRcUix/F4eX9nVF3F+6s0+UY+N6m0TyZlTEZdPN4AdjT3xLVvY22JouI2E7nSLWey7mO2cHv9+H/NvVH127iyGs/+sw1DngC2rK7Fk2+2om3AC4NWhXuvWQRvkMfv/tUW9+xvXFmNVw904Zo6u+zzmw3FZWzffWhtLX68e0y+J248B95ACB2j47J43X9dvwzX1MbLkMrzkM4zk2xe2tRYg6feOirJKze+yo2l4jwmtndlgRGfv3w+Nm9vyVo7y9VTaU6Y7PFUhON4vNJ0Gt9+6UBcmwY4Ia69I/vyZD1TBEEQRPrEzp9fuLwK7kAo4VweO281VNqwvqECT755NG6Nsnl1DYxahqN9I1ixsETKQ2kN1lhjx46Wrri9idzcvnFlNUptBpwccOPS+cWy82O662+CmEp4XsDuwz043ufG1r8dkfrshhXVeH5POz51XoW0vtq0qgazbHq0dLmi1qVbVtfihT1t2NPmmNS9zWQzFc+20p7oD/9qw8eW2GX3aZsaa/DG4S5cU1eGbocv6Xj2368fiVpbK11bXZIjjamxciXbr8iNv/d8bAHsNgO+9qcmGitlmNKnhzH2HwD+BOBno4fKALw8jiznAugD8GvG2AeMsV8wxsyZZHRywC11vGuXl0sdFQB8QR5NHQ7c88I+NNaX4fHdrdK/kdfc88I+tHSFr7vl4ipJiSqeb+0dkRTDkWlODrjRdNqBo71jm/lYGRrry9A6er6xvgwDnoCijJFpxIcjtrxM2kauTve93IyWLkdU+ynJE9lGTR2OuLoma1OleiX6LXcvxTZIReZsteF4OdDlkBRuohwPbGvGgS6H7PVNpx2SQlG6/pVmNJ2Wvx4AWroccXUV768Scm2YqH0yKWMy6tLc7ZJt3+ZuV1blSrecybqP2aKleySufo/tasW1y8ulujbWl0nn+t0B/Oj1I7LP/mO7WnHHZfMUn9/xItd373s5Wr6mDoc07kZe95U/ysuQyvOQzjOTbF7avKMlSl658TX2XOQ8FjnOiQutZDKNp32V5oTJHk9FWrockmJYlEdsU7n2juzLk/VMEQRBEOkTO3/2u+P3TbFzeey8dcvFVXhgW4vsGmXTthbkmvRo6nBE5aG0BjsQcTxyflGaa070u+HyhhTnx3TX3wQxlZwccKOpwyEphoFwnxV1KpHrq83bW6DTqOPWpQ9sa8YtF1dJv8/UddhUPNtKe6JbLq5S3Kdt3tGCmy6cixP97pTGs9i1tdK1kWNqrFzJ9ity4+/Wvx1Ba+8IjZUKTPWrlS8B+P/s/Xl4HNd1541/b+97E3uDoLiJoCxhMa3Qia1JvJCWIifcrMRybE80iceTzY4Y00n8vhlFNGklv3EmpkdeMlk8ydhZxpIjj0QqsWKbiu34Jzsx7YggoA0SRVIA0QCxsJfqrqquqvv+0ahCdXVVb2igAeJ8nqcfdlfd5dxzzz333MtC3f8AIA0AnPNxAN3LKM8D4HYA/5Nz/gYAAoD/x5yAMfYrjLFzjLFz165dcyxoOi0aRsMYjO86Gi9e0+/ZpRELGqZSxXLykuJYhjXPTEZEMi2W3LeWz1ipDHZlWa85yTiTER31YIeuG7s2iQUNyZRYor9q7Z1K2be1mk6d2lXpdyUd1CJzs3RYC5VsNZmWbOWYTkuwI2nTtmJ6Z7mtetbzJFPOeex0WEk/jdSxGm2ZrlO/jcpVbz2r1Y/1UMlOndrHWPl3oNyvWvPlZXuf04zx52S7Vvkq+e1ayzSnrWfMVJuXrPLa+VfrPTt9r4Sfq2dOWG1/quM0Vhirru9mjili41JrjEoQrWQ92ql1/qxl/rHOW/q6x2k+WMgVoHGUlOEYg5nio1rWKRoHBFlxnB/rjb83CuvRVjcC02nn2NS8D6Bfu5axX0/kZaXk93qNwyqvpVZ/bDvVWc0HXl/0gbX4M2tsXSmt3larXNXWK07+V+NwzLPRafXmsLT46gcAAGPMg+Ihco0yAWCCc/6vi7//HsXNYgPO+Z9zzvdyzvd2dXU5FtQTCyDgXVKP+TsAuNnSNeu/5jy98SACXhdCfk/FMsx5uqMB9MYCZfcr5bcry6l8u/rqQdeNXZsCXhcS8UCZ/irJ0xsPOra1kk6rtcvpt5MO6pHZLn+zqWSriZjfVo6emN+2rF6bthXTO8vtpOdE3DmPnQ4r6aeROlajLT116rdRueqtZ7X6sR4q2alT+zgv/w7Y+1VzvpDP3uc0Y/w52a5Vvkp+u9YyzWnrGTPV5iWrvEV/WT6XLN0LVtR3LTLVSj3+dbX9qY7TWDHba6V7zRpTxMal1hiVIFrJerRT6xxUy/xjzWNe99jlbQt54WIoKcMxBrPER9XmdhcDwj6P4/xYb/y9UViPtroR6LHZ5wCW4iprfNUVtV9PBH2ekt/rNQ6rvJZa/bHtVGc1H7gp5K26f6X7M7vY2imt3lYnuay/9fRO/tf69gjylUu0enP424yx3wMQZIzdCeArAM40WhjnPAngNcbYLYuX9gN4rpGytneEcerePQh4XXjshxM4ur+/ZDAMbYnj1L17cOb8JO7f12/8a05z6t49GOiN4dS9e/DFZy7i+IGBkvu7uiP41Lv3lOXZ3hHG0OY4bu6OGPVaZThzfhK7Fu+fOT+J9pDPUUZznoeODNrW14hu7Nr00JFBDPTGS/TnJI9ZR0Nb4mVtraZTp3ZV+m3Xl7oOapG5WTpcLkO9cZw8VCrHyUODGOqN26ffHMfJw5b0hwcxvNk+PQAM9MbK2qr3rxN2Oqykn0bqWI22DCaitvodTESbKle99axWPzaLgUSkrH1H9/fjqz+aMNr65Mikca8j7MNH3rHbduwf3d+Pv/jOK47jd7nY2e5DR0rlG9oSN/yuOd2n3m0vQy3joZ4xU21eOn5goETeor+Ml/jX0nuxknnM7OeOHxxoqp7rmRNW25/qDPTG8AfvGrLVqZ2+zba8WmOKIAiCqB/r/NkRLl83Wedy67z1xWcu4uShAdsY5cShAVzPSRjeEi8pwykGG+qN265NnOaaHZ1hRINux/mx3vibIFrJ9o4whrbEcezO3SU2e/++fjw5MlkSXx0/OABZUcvi0pOHBvGlZy4av2/UOKwVY9tpTfTFZy46rtOOHxjA337/VWzvDNfkz6yxtVNas0+1ylVtvWLnf4/duRv93RHylQ4wzpfzoO4yK2fMBeA/A7gLAAPwTwC+wJchFGNsD4AvAPABuAjglznnC3Zp9+7dy8+dO+dYln4a4kymeKqtqgHXssWTEc2nrM8LErxuF2RVM057t54Uf2lOQDovQ9GA2ayE3ngAA71xuFzMqEMvV38ZtiyreC6ZRlosQCxouLkrDIAZMmxtC2Hieg7TaQkFVcWmYPEUz5ysYOviaY26jHr5+kmTdvXVQ6U26S+CN+vPqjNr/fqJpdNpCTlZwfaOMDQOLOSKunXSqVO7Kv2260vz4RPVZG5Ah8t+u7mdrYqiggtTKUynJfTE/BjqjdseRqcjyypGrqaMkzmHN8cdDzHT0U9YTqZEJCz964SdDivpp5E6VqMtubyM0WTG0O9gIup4GN1y5Kq3nhVs+4rYqZCXMJbMYjotoTfmh9ftwpWFvNHWZFbGTEZEVyQAt6voS6z+tDtavJdMVx6/y6WaX9neEYamcbwwncbC4gnnOzrC2GlzwrlTmXby1jNm7OalmYyIkM8NzjkYY7b+0uxft5pO89XL0+cxXd/66b/W9M3Ub6U5oQIrYqc6iqLhuWQKM2kJsYAXoqrA63IjKyqIBT1wMYZUvoCuqA+yyjGfLaA37sdtNfgtYsOxLFutFqMSRJPYMHZqnoN6ogHkZAXzVeZyc56uyNLcmJUKiPq9uCZI6Az7EfK5EQ14sLW9fA5zisEURcNzUylMpSS0hT1wgeGaIKE7EoCsqsiIKoI+N8JeNzqiPtzUVnl+rDf+Xmes6NxPrD56bDqTkZDKFRAJeCApKtqCXqgcuJoS0RH2IexzYz4noz1U3OeYE2R0R/24NRHGxdl8XevHVWBF7LQVY9tpTTQvSPC5XUiLBfjcbswKEroifnjcDBG/F2JBRVYqQNWAvKyiO+ZHQdUwLxQQ8rnhdTN43Aza4v5RIhYABzCTkbClLQi/x42JhRxCPg96Yv4yn+rkk53WK2Y/Gwm4sTkexE1N2g9bxzg2ttWbw/cA+AfOufOLPFcQmiSIVYICGmI9QHZKrAfITon1wobZdCPWNWSnxHqA5n5iPUB2SqwHHO201f+9chDAS4yxv2aMHVh85zBBEARBEARBEARBEARBEASxwrR0c5hz/ssAdqH4ruH3AniFMfaFVspEEARBEARBEARBEARBEASxEWj5k7qc8wJj7GsAOIAggCMAPthSoQiCIAiCIAiCIAiCIAiCIG5wWvrkMGPsnYyx/w1gHMDPoXiQXKKVMhEEQRAEQRAEQRAEQRAEQWwEWv3k8H0AHgHwq606lI4gCIIgCIIgCIIgCIIgCGIj0tLNYc75e1tZvxOKouGF6TQWcgVomoZNQR9yBRU9sQC2d4Shady4LxZU7OoMQwPDfE6Cz+1CTlbRGw+Ac2BekCEqKqSChh2dYQDATEaCICvY1h7Gjs4wXC5mW7dYULGzI4xtHWFcWchhOi2iJxbA5mgAo8k05nMy2oJecA6E/G5IBQ1gHG7GkC9omBdkbGkLYaA3BpeL4cq8gOm0BFlV0Rb0QZDVinKMTaUwJ0hoD/khKhoKqoqY34tcodg+VQNmMqKhF3N+ANA0jktzAqbTYkl6/XtalMHAkJGUEj3b6W5bRxjb2kOYuJ4z2hDzeyFrmqFza/9kJQWKyiErS7q3lqlfvzIvYC5bvKdpHLGAt6TP9bZpGjf0KMgKdnSEofHKelgpRFHBhakUkmkJiZgfQ71xBALOQzqfL+BCMo3ptISemB9DiRiCQW9T6wCAXF7GaDJj1DOYiCIU9DVVrkxexPNJwchzayKMaDBQMY8sqxi5mkIyLaI3FsDQ5jh8PrdjeiEvYSyZNeoYSEQQDvqb2vZG2pLNi3jOlP62RBiRKm03j8XVtlM7OeYECT6XC/M5GSGfBz0xP7ZsKo7veUFGQdUgqxxiQcX29jAUrmI2u+QTd3RFAMAoK+p3Q5A0CLKCnKyiI+xDNOjGzvYoJlJ5TKdFhHweyKqKrogfnJv8cFsIXi/DbFpGVlYgFjS0h72QFQ1iQcO29hA8HobrQgGSqiErFRD2eTEnSOiM+BEPunE9V+pLNY1jbCqFqZSIrogfLhcQD/qapnfdP0+lRGzeFETU70HSpm/t+l3XWzVbMNfRGw8a80ijdrRWbLAa1vHVE3NjOqViOlP8rXIVbubGvCCjPexDQVWgcRfaQl68ricGj2fpD7LWS5sJgiA2AnocOJ+T0RX2IV9QkZEUxINeRPwe5AsqOsJ+W19tnhNv7gpiIadiOi1ha3sQsqIZcXJH2IPpTAHd0QDcLmAqVfT/W9tCxlquNx7AXFZGMi2iK+pHQVUQ8fsx0FucQ8yxZG/cD6/bBVEpgMGN6bSE7pgfm4Ju7GiPlsSx1ph9MBHDVFaiOYhYE9jtcXTGvHgxKSCVL2BT0ItZQUZ7yAsXY7iWLcbZgAbAhZm0hK6oH9GAGxoHJq7nEQt4EPZ6IMgqEnGy8Vowx6bmtZF1XwcAXp0VcHleQMTvQcjnxlRKRGxxHyAjKtjaHoKkaFjIyZAKGjojPsgqx7wgoSPiRypfQDTgQcDjwvV8AVG/B6KiISMqSMT8i3soEuJBD8I+D7KSgrSoIOr3IOL3YFaQ4Pe44fMyeFwMHuZCKl+A3+OGICvYarOHRSyPlm4OM8buAfBJAN0A2OKHc85jrZJJUTR8bWwKEwt5fPkHV/CevVvxmafHIRY0BLwu/Nkv3o50XsHEQh4Pnx1HW8iH+968rSRtW8iHX3/rTgCAIKtGul9/607jt17eqXv34O6BBFwuVlK3nmZbRxAffns/fv+JUYgFDXfd1ol33LoZn//WON6zdyseOXcFH7hjBxgDAl4XIgEvUnkFJ86MGXX80c8PI+h14+WZLL78g2L6XCFdUY7Hz0/is0+P4wN37MCLyWxZ++578zbH/EDR8Tw1lsSxR58tSa9/P/t8Eu//ie1IpsWqutP18Nt33VLSL4+cc+6fBUEu0721zIDXhc+97w0AgKsLeQiyatvnetsA4OkXpzE+nS1pSyU9rBSiqOD0hSk8eHrUqPvkoUEcGuq13bzN5ws4M5osS39wMOG4EVtvHUBxc/TJ0emyPAcGe2w3SRuRK5MX8bXRa2V53jnY5bipKssqHh+5igefMOU5PIgjw5ttN4iFvIR/GJ0pq+NnB7sdN4jrbXsjbcnmRfyjTfqfGexy3CA2j8XVtlM7OT751PNlY+zo/n7s7ApjPiuhoPKysf9rb91V4tM+9e498HsZPvHkc/jw23fB43YhmRJLxuLJwwO4PJfH0S8vtfsj79iNtpAHc0LBSLt3Wxz3vXk7Jq+LjuP6E4cH4fMwnPrGS2Wynzw0gEfPXcG5yylDNo1r+J2/HzHSHD8wgMd+dAUf+Mmbl6133T8/8Phoif6+9L3LWMjJJf7K2u+fe98bICu8qi3Y1fHQkUF0RX341b/+Ud12tFZssBr242sAn//Wy7g8l0fA68KJQwP4E9NvvW/335rAq7MC3jnQC4/HtW7aTBAEsRHQ48DP/3NxbfPKTLZknj9252743S785TOv4mN331riq81z4pt3tOPuoV4cPz1mGy8cPziA//Ovl/HSTNaYm30eht/c148HHh/F7u4I3vsT20pimuI8Mo5f+PFtuPu2rrJ56KEjA1A14PjppTwnDg1gKiXhjh2d8PncZTH7to4gPvS2/pJyaA4iWoXTHseH3taPz39rHO/78W349Ddfsh1T1rjrxKEBdER8+JOnXy4ZZ+YYmGzcHrvY9CPv2I2g14U//NoLJesFqcDx0a88W7LW+NqFKbxzqLfM5/3pt1+GrPCyvrt/Xz8eOXcFv/bWXQh7GV6azuLUN8r7eVtHEL/xtl0lPu7o/n5E/B584bsX8f6f2IbuqB+f/mb5Ooz6vLm09J3DAP4IwCHOeZxzHuOcR1u5MQwAY1MpjC8GDAeG+wzjAwCxoCGTV437YkHDPbdvKUt7z+1bMCvImBXkknTm33p5xx59FpfmhLK69TQHhvuMjWEAeP+bduDB06NGfQeG+zCXK9YV8nmhaTACDr2Ol2eyuDCZMuScy1WX44HHR0vSWttXKT9QfDJNdzzm9Pr3++7YiVfnhJp0p+vB2i+V+sdO93b6H5lIYWQiZdyzK1Nv26U5ASMTqbK2VNLDSnFhKmUEfHrdD54exYWplH36ZNo+fTLdtDoAYDSZsc0zmsw0Ta7nk4JtnueTznofuZoyNoaNPE+MYuSqfVvGklnbOsaS2aa1vZG2POeQ/rkKbTePRT3PatmpnRx2Y+zhs+MoKBxTacl27Ft92ke/8ixGJlI4MNyHoNeDV2eFsrH44BNjKCi85Nqnv/kSQj5vSdr77tiJl68JFcf17z8xileuCbayP3h6DPfdsbNEtvGZbEmaE08W0zRD77p/turvntu3lPkra7+PTKRqsgW7Oh54fBSZvNqQHa0VG6yG/fgaw4HhPuP3cctvvW8fPjuO8Zksxhb943ppM7E+6btpKxhjdX/6btraatFXFNIL4YQeBzqtg0594yXM5WQcGO4r89XmOfGXfnKHsYFhFy+cODOGD77l5pK5+cBwn5H/g2+5uSym0eeRBx4ftZ2HAh6PUad+7fjpMbgYM+JYa8x+YLivrByag4hW4bTHoe9pfPqbLzmOKWvcdfz0GHxuV9k4Ixuvjl1s+ulvvoRZQS5bL+gbw/q1h8+O44NvudnW5x0Y7rPtO32/5sSZMWwK+3HqG/b9fGC4r8zHPXx2HNeyEg4M9+HUN17CxVn7dRj1eXNp9TuHpznnz7dYhhKmUiI0XjQ2xmAYn44gKcZ9AEYac1rGAI0X01uvWcsTCxpmMiJ2dkVK6taxyrAgFErqM9clSEpJnTpmWWqVw5rW2r5K+QFgOi3apte/5016rKY7q/7sdG7tHzvdV9KNWT9ObeMctn1fSQ8rRTIt2dY9nbZ/dfd0nekbqaORehqRq7G2iA55xJbKtTr6sm/7atipnRxO40aQy8cu4DzONF68Z/XJ1jLtrpnT5h18ulN9dvfypnr0tHZpmqF33T9by2ds6bvur+z8XS224FSHnT5rac9ascFqOI0vXbdOv/W+1TiQTIl4/U3rp83E+uTqxGt4z589U3e+R371jhWQZu1AeiGcSKbL1zZmrPO82Veb50R9HQZUjwmsczNQjDmc8ujxnN3axi7PQq6AjKgstq80XyvXKARhpdIeRy17DNa4S381hfU+2XhlnGJT67rFyUc6+S+rn7PeW+oz+36uZe1VaR1Gfd48Wv3k8DnG2COMsfcyxu7RP60UqDcehHvxFQ3A0r864YCn5L45jfmam6EsnfW3nqc7GrCt21o+ALSHvWX16XWFAx6EA56y/FZZapHDLq1dm+3yA0BPLOCYPuB1IeT3OJZtpzsnWZz6x073TmVa7zm1rScWcOx7Jz2sFImY37bunpj9Kw966kzfSB2N1NOIXI3k6bXY41Ie+75aLblWR1/2bV8NO3WSw06esM9+7Dql1/96yM4nm8u0u2ZOa/VF1eqzuxc01WNOa03TDL2b/bO5fM6Xvuv+qpIPNee1yuRUh50+a2nPWrHBajiNL84r/9b71sWARDywWNb6aDNBEMRGwBwHOs2FLgZwXu6rzXOieR2m57OWo8cE1rkZKMYcTnn0eM5ubWOXpy3kNeJYp5jd+pvmIKIVVNvjqDamrHFXW8jrOM7Ixp1xik2t6xanvnLyX1Y/Z72n91m1fraTS89faR1Gfd48Wr05HAOQA3AXgIOLnwOtFGigN4Zd3REc3d+PM+cncf++/hLHFQ24jfsBrwuP/XCiLO1jP5xAR9iHjrCvJJ35t17eqXv3GC/9NtetpzlzfhKfODxo/P6b77+Kk4cGjfrOnJ9Ee6hYV04qwMWA4wcHSuq4uTuCwb64IWd7qLocDx0ZLElrbV+l/ACwvSOMU/fuKUuvf//iMxexvSNck+50PVj7pVL/2OneTv9DW+IY2hI37tmVqbdte0cYQ1viZW2ppIeVYqg3jpOHBkvqPnloEEO9cfv0iZh9+kSsaXUAwGAiaptnMBFtmly3JsK2eW5NOOt9aHMcJw9b8hwexPBm+7YMJCK2dQwknP9Xst62N9KW2xzS31ah7eaxqOdZLTu1k8NujB3d3w+vhy0e5lI+9q0+7VPv3oPhLXGcOT+JvKxge2e4bCyePDwAr4eVXPvIO3YjJxdK0n7xmYu4uStccVx/4vAgbu4K28p+8tAAvvTMxRLZ+rsjJWmOHyimaYbedf9s1d9XfzRR5q+s/T60JV6TLdjV8dCRQUSD7obsaK3YYDXsx9cAnhyZNH6fsPzW+/bo/n70d0cwsOgf10ubCYIgNgJ6HOi0Djp25250hHx4cmSyzFeb58S/+u6rOHFowDFeOH5wAF/4zislc/OZ85NG/r/4zitlMY0+jzx0ZNB2HhILilGnfu3EoQFonBtxrDVmP3N+sqwcmoOIVuG0x6HvaXzkHbsdx5Q17jpxaACyqpWNM7Lx6tjFph95x250hn1l64VPvbs03dH9/fiL77xi6/OeHJm07bv79/XjyZHiOu66IOHYnfb9fOb8ZJmPO7q/H10RP54cmcSxO3djZ6f9Ooz6vLkwznn1VDcoe/fu5efOnSu7bj5NU9M0xIPFE2310xs1jZectnlzZxgcDAs5CV63CzlZRW88AM6BeUGGqKiQFc0w3JmMhJzDCYvWkzx3LC7yryzkMJMR0R0NYHM0gNFkGgs5GZuCXnAAIZ8bUkEDGIebMeQLGuYFGX2bghjcHIfLxXBlvngCe0FVsSnogyCrFeUYm0phXpDQFvJDUjQUVBVRvxe5QrF9qgZcyxZlsjsdVD8NcyYjIhFbSq9/z4gyAIaMpJTo2U53W9vD2NYewsT1nNGGqN8LWdPgW9S5tX+ykgJF5ZAVDTs6i7q3lqlfvzIvYC5bvMc5N9ppPd1X07ihx5ysFOvjlfWA4kGLy8LOVvVTiafTEnpifgz1xh0PigOKh79dSKaX0idijoe+NVoHgJJTlntifgwmoo4HsjUqVyYv4vmkYOS5NRF2PIxORz+lWj+1eXhz3PYwOh0hL2EsmTXqGEhEHA+ja7TtjbQlmxfxnCn9bYmw42F0OuaxuNp2aifHvCDB63JhPicj5POgJ+bHlk3F8b0gyJBVDbLKIRVUbGsPQ+EqZrNLPlH/0yG9rIjfDUEqvvYgJ6voCPsQDbixsyOKiVR+8UReNwqqhs6IH5wv+eGb2kLweRlm0zKysgKpoGFT2IuCokEsaNjaHoLXw3BdKEBSNQhSASGfF3NC8RTleNCN67lSX6pp3DjVvDPih8cFxIK+pp2irPvnZKp46nk04MW0Td/a9buutyq2UFJHIh7AQG9xHqklb6W+bySvhRW1U+v46om5MZ1SMZOR0B31Q4MKF9yYz8loD/ugqCpUztAW9OJ1ieJJ8zpNbDOxPllWZ1eyU8ZYw69PuJHjftJLQ6yYna419DhwISejM1xcc2RFFdGgB1G/B6Kioj3st/XV5jlxZ1cQCzkV02kJW9uDkBUNycU5ozPswUy2gK5IAG5X8XUW3dEAtraFjLVcIhbAXFZGMi2iK+pHQVUR8Xsx0BuHx+MqiSV7Y354PS5ISgGAG9Pp4ly0KeTGjvZoSRxrjdkHEzFMZaUbZQ5a8RiVWFns9ji6Yl68mBSQyhewKejFnCCjLeSFizFcyxbjbDAN4C7MZCR0RfyIBtzQODB5PY+I34OIz2O7Zm8Ra95O9djUujay7usAwKuzAq7MC4j4PQj63EimREQX9wEyooKt7SFIioaFnAypoKEz4oOscswLEjoifqTyhWJerwvX8wVE/R5IioaMqKA76gcHcC0jIxpwI+L3ICspSItKsV/9HsznJPjcbng9DB4Xg9flQloswOd2Q3DYwyJqwlFhLd0cZoxtAfBZAP9h8dK/ADjKOZ9YjfppkiBWiTU/URAEyE6J9QHZKbFeoM3hVYb00hAbZnOYWNfQ3E+sB8hOifWAo522+rUSfwXgNIDNi58zi9cIgiAIgiAIgiAIgiAIgiCIFaTVm8NdnPO/4pwri5//DaCrxTIRBEEQBEEQBEEQBEEQBEHc8LR6c3iOMfYfGWPuxc9/BDDXYpkIgiAIgiAIgiAIgiAIgiBueFq9OfwBAPcCSAKYAvDzAH65pRIRBEEQBEEQBEEQBEEQBEFsADytrJxzfhnAoVbKQBAEQRAEQRAEQRAEQRAEsRFp6eYwY+yLAI5yzq8v/m4D8CnO+QeWWa4bwDkAk5zzA8uVU1E0jE2lMJUSsaUtiIDHjYW8DJ/bhZysoicWwPaOMADg0pyAOUFyvDedFh2vbW0L4cpCDtNpEb3xAFQNmMkspXe5lg4W1DSOK/MCptMSBFnBtvYwdnSWpqmWFkDNZdSCpvGyNlrL0tPY6aiS7HNZGaKiQipo2NEZhsaXdGPWW6WyatWLy8VK7smqiragD5KiGTJs61ierpqBLKsYuZpCMi2iNxbA0OY4fD63Y/pa+seK2fZ740EM9Mbg8VT+gwNRVHBhKoVkWkIi5sdQbxyBgLOraaSOetsO1N/+etvRKPW2JZeXMZrMYDotoSfmx2AiilDQV7GORnS8WjTSl1aq9a31vtXXahrHVFpERlTQEfahO+bHTW1LZZj9QVosIB70YnObH8nrMq5lJEQDHkQDHsSDXmxtL/ftW+JBPD+dxpwgIR70IZUrIOBzwe92oyPiw9b25vmSenVRaRzUO2bM6bujAbhdwFTKec6r1VevNnbt1jSOsakU5gQJ7SE/spJStJeID51hL7Z3RiHLquEzdnaGkJNVw38MJKK4OJfDfE5GvqBiczyIWxNL47AR/2yW97UFAdMpCbOChL5NIQz0xgBgzY57giCItYimcbw6K+DynAC/xwW/1wXGGKSChkS89jnVKGdeQNjnQU/Mj63tYSiKhueSxXki5HMj6vfgdd1RBINeADDuT10XEfS5EQ94jbmi1vWTXfwKYFViWmLt4LR/wcAwL0joiRXjApeLrUpsls2LeC4pGOuXtpAbN8UjAIDRZHopng56ICsaOsL+ElkURcML02ks5AoQCyq2tRfjrInr+YbXDxsNs7+KBjzIySqyUnEPZFt7CJfnc7g8LyDi9yDkdeNaVkIs4AUYMJ+V0R72IV9Q4PO4oWgqgh4PspIKQVbQu8kPqcAxnZawpS0At4vh6nURXRE/XC4gHvTVtGdT7x7XelhXrCdaPSsM6xvDAMA5X2CMvaEJ5R4F8DyA2HILUhQNj5+fxAOPj6It5MN9b96GL//gCt6zdys+8/Q4xIKGgNeFz73vDZAVjk8+9bzjvWOPPut4bVtHEL+5r7+knofPLpVx6t49uHsgYQQcT784jfHprGMaHae0n3tfUc21lFELmsbx1FiypI3WsvQ0djqqJPvVhTwEWcXDZ8fLdGPWWz1tqKTDu27twbfGZzA+ncWXf3AFH7hjBxgTDBmWq6tmIMsqHh+5igefWGr3ycODODK82XZirKV/rJhtX8/z0JFBHHl9n+MGgygqOH1hCg+eNsl1aBCHhnptg9BG6qi37Y20v952NEq9bcnlZTw5Ol0m14HBHscN4kZ0vFo00pdWqvWt3f2Hjgzis0+PQ1Y4PvT2m5ERlZKxfeLQAC7FBfzUrm4AKPMVd93WiTtv24zfN8l9dH8/2kNevHwtCwD48N/9u+GjPvT2fnz+n8fxvh/fhk9/899L8oR9bmxuy2LfLT3L9iWN6MJpHNQ7ZuzSH93fjy997zIWcrLtPNhKH+qEXTs+9e490LiGP/76i/jgT+7Ei8lsmb1cWcgjnVfwu4+N4M072nH3UC+Onx4z0vzRzw1jXpDx3556wbj2B+8awuHhzXC5WN3+2Szvv7w8g6vXJZw4s1TfJw4PIhb04OiXn11z454gCGItYuf/jx8cwJ9++2VcnsvXPKfedWsPvv78dNl8eFtvFLNCAf/1/14ouf7aQh533tINr9eN0yNX8XuW+5fnc+iMevH/fnW06vrJLn79o58bhqxqJXHgSsS0xNqh1v2Lh44MYlPIa8SsKxWbZfMi/nH0mmX9MoBcQsFL0/myeDri9+AL3z2Pj919K+4eSEDTOL42NoWJhXxJ/PU7P30LvvAvr2IhJ9e9fthomP1VLfspR/f342sXpvDOod4Snd+/rx9Pv5DEL755O65eT+Phs+Mlca/dPtbxAwN47EdX8As/vg2ffXrc1p/qMtazx9Vo7Ew40+oVgmvxaWEAAGOsHcvcsGaMbQHwswC+sEzZABSfutEHyj23b8HDZ8dxYLjPcKwAIBY0jEykcOzRZyveq3TtwHBfWT3m9McefRaX5gQAxSevRiZSFdPoOKUdmUjVXEYtXJoTytpoLUtPY6ejSrLPCrIhp1U3Zr3V04ZKOhybWtLNgeE+zOXkEhmWq6tmMHI1ZWyo6fI8+MQoRq6mbNPX0j9WzLav53ng8VGMTdnXARSfStAnfkOu06O44JCnkTrqbXsj7a+3HY1Sb1tGkxlbuUaTGcc6GtHxatFIX1qp1rd29x94fBQHhvtwz+1bMJORysb28dNjyORVXJoTbH3F+9+0wwhk9TwPnx3HZEo0fKvZRz34RLG+T3/zpbI8s4KMkYlUU3xJI7pwGgf1jhm79A+fHcc9t29xnAdb6UOdsGvHR7/yLMZnsjgw3IdrWXt7yYoqXr6WhVjQ8Es/ucPYGNbTvHwta2wM69f+6/+9gLGpVEP+2SxvJq8aG8N6/t9/YhQFha/JcU8QBLEWsfPFJ86M4cBwn/G7ljl1bKp8vnv47DgyompsDJuvv3wtiwvJNMamUsbGsPW+oqKm9ZNd/PrytWxZHLgSMS2xdqh1/+KBx0dLYtaVis2eSwo265cxSAVmG09fy0o4MNxnyDI2lcL4TLYs/vrv//SiEWfWu37YaJj9VS37KQ+fHccH33Jzmc4/8/Q47rtjJ165Jhj3zHGv3T7WiSfHcN8dO431l37dbq+onj2u9bCuWG+0enP4UwC+xxj7BGPsEwCeAfBHyyzzfwD4XQCa3U3G2K8wxs4xxs5du3atamFTKdEwOsaKhqf/a0bj1e9VumbOZ1eGWNAwkxEBANNp0bZMcxodp7Qat5fLroxamE6LVcvS01Rrn1V2s5zWvLWWZSevU/unUmJJfzZbV7VSyVaTDvqeTtvLU0v/WDHbvjlPMuWcJ5mWHOSSmlhHfW0H6m9/ve1olPr7sX65GtFxPdTrU8000pdWqvWt033GYIxvu/uCrGAmI9r6igWhYJtH9xUaX7pead4w52mGL2lUF3Z11ztmKukZaI0PNVOrnTq1Q+PV7UXvdzv7cMqXTIkN+WezvIKkOMpkVx+xdlmOPyWI1eJGtdNq85j+u9qc6hR3OflqjRfjO6d8GgcWcoWa1jx28avT/NPsmHYtcqPaajVq3b/Q7ct6rdmxmeP6JVM55tJlMa/NrWn18Vnv+mEtsRp2avZXte6n5B18Vn4x5tXvmeNex7JkpaI/1WWsZ4+rleuKG5WWbg5zzr8E4B4A04ufezjnf91oeYyxAwBmOOc/rFDnn3PO93LO93Z1dVUtszceRMC7pCb9u/kaALhZbfcqXbOrx/y7OxoAAPTEAo759TQ6TmndzFkGaxm10BMLVC3LnKYe2a1yVtJbrW2opMPeeLDkXrN1VSuVbLXXQd89MXt5aukfK1bb1/Mk4s55EjG/g1z+ptVRb9uB+ttfbzsapf5+rF+uRnRcD/X61BLZGuhLK9X61uk+XwyGncZ22OdBdzRg6yvaw17bPC4G42O9Z/7XLk8zfEmjurCru94x06ieV9KHmqnVTp3aofdpJXvR09jZh1O+RDzQkH82yxsOeBxlsquPWLssx58SxGpxo9pptXlM/11tTu2N21938tUuVozvnOI1FwPaQl7jt/W+ea6wi1+d5p9mx7RrkRvVVqtR6/6FOb4xX2t2bOa8fnGOuThfksW6Njen1cdnveuHtcRq2KlV17Xsp4T89j4r5POU9Ic17rXLE/R5KvpTXcZ69rhaua64UWn1k8PgnD/HOf/c4ue5ZRb3HwAcYoxdAvBlAPsYY3+znAIHemN46MggAl4XHvvhBI7u78eZ85O4f19/iaMd2hLHqXv3VLxX6dqZ85Nl9ZjTn7p3j3Ggz/aOMIa2xCum0XFKO7QlXnMZtbC9I1zWRmtZeho7HVWSvSPsM+S06sast3raUEmHA70x496Z85NoD/lKZFiurprB0OY4Th4ubffJw4MY3hy3TV9L/1gx276e56Ejgxjota8DAIZ64zh5yCLXoUHjMIym1FFn2xtpf73taJR62zKYiNrKNZiIOtbRiI5Xi0b60kq1vrW7/9CRQTw5MonHfjiBrqi/bGyfODSAaNCN7R1hW1/xN99/FZ+wyH10fz/64gEMb4ljeEu8xEedPDyIM+cn8ZF37C7L0xn2YXhLvCm+pBFdOI2DeseMXfqj+/vx1R9NOM6DrfShTti141Pv3oP+7gjOnJ9EZ8TeXiIBN3Z1RRDwuvBX330VJw4NlKS5uSuC/+fu15Vc+4N3DWGgN96QfzbLGw24cfxgaX2fODwIr4etyXFPEASxFrHzxccPDuDJkUnjdy1z6kBv+Xx3dH8/on43/uBdQ2XXd3VFMJSIYaA3hj90uO9xo6b1k138enNXpCwOXImYllg71Lp/8dCRwZKYdaVis9sSYZv1ywD8Hm4bT3dF/HhyZNKQZaA3hl3dkbL463d++hYjzqx3/bDRMPurWvZTju7vx19855Uynd+/rx9ffOYidnaFjXvmuNduH+v4gQF86ZmLxvpLv263V1TPHtd6WFesNxjnvHqqdQhj7G0AfptzfsApzd69e/m5c+eqlqWf9plMiehbPO3zel6G13JaLFB8/8m8IDnem8kUT3G3u6af4DiTEZGIBaBqwLXsUnrrS7j1kxxzsoKtVU5ytEsLoOYyakE/MdLcRrtDjpx0VEn2uawMUVEhK1rx5Hi+pBuz3pzqdZLXqf3mewVVxaagD5KiGTLUqatlvxXdzlZlWcXI1ZRxQudwlVNaa+kfK2bbT8QDGOiNVz3MSD8lWT+NttqJyI3UUW/bgfrbX287GqXetuTyMkaTGUOuwUTU8TA6nRp1vCJ2Wo1G+tJKtb613rf6Wk3jmEqLyIgKOsI+dMf8uKktXHJAgu4P0mIBm4Je9Lb5kbwuL52u7PcgHvJia3u5b98SD+L56TTmBQmxoA+pXAF+rwsBjxsdER+2tjfvdN16dVFpHNQ7ZszpuyIBuF3FV4c4zXkNniq84nZq125N4xibSmFOkNAe8iMrKYa9dEa82N4ZhSyrhs/Y0Vk8RVsfpwOJKC7O5TCfkyHKGhKb/LgtsTQOG/HPZnlfWxAwnZIwK0joiwcxsLhAqte3Ek1lWbZayU4ZY3jPnz1Td5mP/OoduFHjfoD00iArZqfrEU3jeHVWwOU5AT6PCwGvC4wxyIpmu15x8t16OVfmBYR8HvTE/NjaHoaiaHgumcJ0WkbA50LU78Gt3VEEg8Ung/X7yesSAj4XYgEvbkvE4PG4al4/2cWvAFYlpl1BWhKjrmfs9i8W8jIYGOYFuRib9MbhcrFmxGZVyeZFPJcsxtI9UT/awm7cFI8AAEaT6aV4OuCBrGroCPtLZFEUDS9Mp7GQK0AsqNjWXoyzJq/nG14/rABr2k51fzWdFhENeJCXVWSl4h7ItvYQLs/ncGVeQMTvQdDrxrWshFjACzBgPiujLeyDpCjwutxQuIqgx4OsrCInqUjEfZAUjpm0hL5NAbjdDFevi+iM+OFxAbGgr6Y9m3r3uFbDdm9AHJXUks1hxpifc76iLzpq5uYwQSyTNT1REMQiZKfEeoDslFgv0ObwKkN6aQjaHCbWAzT3E+sBslNiPeBop616hOR7AMAYa/j9wtXgnH+r0sYwQRAEQRAEQRAEQRAEQRDERqZVf0/iY4y9D8AdjLF7rDc5519tgUwEQRAEQRAEQRAEQRAEQRAbhlZtDv8agPcD2ATgoOUeB0CbwwRBEARBEARBEARBEARBECtISzaHOeffBfBdxtg5zvn/aoUMBEEQBEEQBEEQBEEQBEEQG5lWH1v914yx+xljf7/4+U3GmLfFMhEEQRAEQRDEjYXLA8ZY3Z++m7Y2VF3fTVtXtT6CIAiCIAiiMVr1WgmdPwHgXfwXAH4RwP8E8MGWSUQQBEEQBEEQNxqagvf82TN1Z3vkV+9oqLqrE6+tan0EQRAEQRBEY7R6c/iNnPPXm34/zRg73zJpTGgax5V5AdNpCYKsYFt7GNvaQ7iykMN0WkRPLIDtHWG4XKws36U5AXOCBJ/bhZysojcegKoBMxnR+J4WZePfWMAHWdGQiBfLBIBLc4JRz9a2ECau5zCdliCrKmJ+L3IF1ZDBnN5cl1VGXTZzuXp7euMBAMBMWsKsIKFvUwgDvTF4PC5oGsdrCwKmU8V7W9tDCHjcuJaVbGWwyqzrb0dnURZF0fDCdBoLuQLEgoqdHWFs6wjbtlFvz3xOQtDrhiCpZeXpKIqGsakUplIieuNBQ37zfWu9O7oiZbLrOrPqy9xOc/862cJKU629VuzaU03mfL6AC8k0ptMSemJ+DCViCAYrP9wvyypGrqaQTIvojQUwtDkOn8/dUBudEPISxpJZQ66BRAThoL9iHlFUcGEqhWRaQiLmx1BvHIGAswusV79AYzpO50W8kBSMtrwuEUYsGHBMn8vLGE1mjPSDiShCQV/FOhrpx5XGyVcqqoY5QYascOQLCjojfmTEAgJeD3pifmxtLx2flcZirf1hThfyeSCrKjrC/rKyLs8JuJrKIyspiAW9SET8cLkZptMSCqqKgMcDQVYgKRoSsQAUTYPX7UJWUpERC2gP+aBwDYKoYltHuQ+zo1Y7dGqrNf+tPVFMpPIV22pXtt72jKhg86YgbkuU+9d6x8t6xKznrogPGVFBXlHhYgyqxiEVtJr7VkeWVTyXTCMnK8hICsI+D0I+N1L5ArZsCkGQFUxcz5f4U71P0nkZuUJxzHRGfAj73LielxHyest8r6ZxvDor4PK8gLCvdDwRBEFsdPR5bE6QEPV7sZCTsSnkg6yo2NLmx0xGMeKozW0edIcieH46jZm0hHjIi1S+OM8PbY4DQEksHA64cHk2j5DPjbawD/GQB7NpGRlJWYxf/PC4XLg8n1ux2Jm48bGLxVwuhum0gNcWJMN+/R4XZtISIkE3on4vMqKCOUFGT9SP3jY/NseaFxs4radfmcni1bksAl43gj43gh43dndHG7L7RtZfNzpWnWyOBjA+m4WoqCioGjKigqDXjfawD3lZxUKugM6IDzlZRUZU0B72Ihb0ICuqxto54nfj4mwO7REfOkIeZCUNV1PFfaSOsA9TqdrXFvXIbi2H+nvlaPXmsMoYu5lz/goAMMZ2AlBbLBM0jePpF6cxPp3Fw2fHIRY0bOsI4jf39eOBx0chFjQEvC6cuncP7h5IlGwePDWWxCefeh7v2bsVn3l6HG0hH+578zY8fHbp+9nnk/i527fiT7/zspFOL/Nz73sDZIXj2KPPGvX+9l23YGIhjy//4ErF9Oa6rDICwFNjyZJy9fa0hXz4yDt2QeUMJ86MGXkfOjKIQ0Ob8b1Ls7h6XcKJM2O2dVSS2SrLO27pxj89nyy5t60jiI/edQsmLW3U6/ryD67gA3fsQK6g2rZN3wB5/PxkSf88dGQQR17fB4/HBUXR8LWxqTKZPvveN6CgLsmul3vXrT34+vPTJdf1dpr718kWVppq7bWzaXP/1yJzPl/AmdEkHjy9VMfJQ4M4OJhw3FiUZRWPj1zFg0+Y8hwexJHhzU0LcoW8hH8YnSmT62cHux03iEVRwekLU2V5Dg312m4Q16tfoDEdp/Minhq9VibX3YNdthvEubyMJ0eny9IfGOxx3CBupB9XGidf+etv3QkAEOTSsf7bd92Cv/7+JfzCG7eivyeCt/V34+vPT1cciwBq6g+7frt/Xz8eOXcFH7v7VqMs65wQ8Lpw7M7d6I768Y8XJvHOwT4k0+mS+ycPDUAsqPjDr71Qkuev/v+XsJCTq9pHrXboZHvvuKUbpy9cLcl/8vAgPv/P47g8l7dtq91/eNq13epf6x0v6xGzns32CpTbbK1zgiyreOr5JK5lJPz3f3rRyH90fz++9L3LWMjJJd9PHh7EocFefPfVWWTyMkQFJfP28YMD2BT04OFvjuPeN24zfK+djRzd34/+ngj23dJDQTVBEBsafR777NPjZXHFH75rAFevS2Vx1LZOGf/pL8+VxQ6/9zO3IpVXSmLh4wcH8H/+9TJemsnigZ+9FbGgF5OWNcnJQwP4m+8X0zQ7diZufJxisTdsjeKHlzIl9mu2xxOHBvAn33rZiAtPHh7Erm4Re7Z0LDs2sIs9Pve+N0AqaPjoV86XxCOJeACT1/N4++7uuuy+kfXXjY5VJ3fd1omfu30rcgUV84JsxJvbOoL4jbftwp9862V84I4deOVaaaz/icOD+JxpzXDi0ACeujCFi3MCfuNtu3D89JitTVVbW9Qju7U/qb9Xllav2n4HwD8zxr7FGPs2gKcBfLTFMuHSnICRiZQxOADgwHCf4WwBQCxoOPbos7g0J5TkO/boszgw3GcEFffcvsUoR/9+3x07ceLJsZJ0epkjEynD2PV6x2eKA7VaenNdVhl12ezac8/tWxDyeY0Fpp73gcdHMXI1hUxeNe7Z1VFJZqssI1dTZfcODPfhZZs26nUdGO7DXE52bBsAjE2lyvrngcdHMTaVMu7byXRhslR2vdyxqfLrejvt+sFqCytNtfZasfZ/LTJfSKaNQELP8+DpUVxIph3zjFxNGcGwkeeJoh01i7Fk1lausWTWuS1TKfu2OOirXv0Cjen4haRgK9cLSfs8o8mMbfrRZMa57Q3040rj5CtnBRmzQvlY/+Ovv4gDw314+Ow4RiZSxvisNBZr7Q+7dJ95uuh3zGVZ5wSxoOHUN17CxVkB73/TDrw6J5Tdf/D0GGYFuSzPPbdvqck+arVDp7aOXC3P/+ATozgw3OfYVru+smu71b/WO17WI2Y9m+3VzmZrnRNGrqbw8kzWCNT1/A+fHTfsxPz9wSeKfmtkIgWv21M2b584MwZVA+67Y2eJ77WzEX08rebcRRAEsRbR5zG7uMLn9tjGUeAu29ihoPCyWPjEmTF88C03QyxomMlIxrrHGjPoaZodOxM3Pk6x2FxGLbNfsz0ePz1WEhc++MQoCgprSmxgF3uMTKSMjWH92sNnx/HqrICCyuu2+0bWXzc6Vp28/007UFCLfz1mjjcPDPcZ/W+31/L7ljXD8dNj+KWf3GHkc7KpamuLemS39if198rS0s1hzvlZAP0A7gfwmwBu4Zz/cytlAoDptAiNwzA6AGCs9DeAxQleLMknFrSStHbf85JSlk7Hrl79WrX0lWTUZbNrD2OAsCiTNW8yLZbcq1dmu/JqbaP+vVJ5uv6nUqJ9faml+3ZlOJVrV16lfrDawkpTrb1WrP2vp68k83Rass0znZYc8yQd6plON083jclVX5569VuUa+V13EjbG8mz0jj5So07j0k9rcaX+qcen2e+ZyeLU316WU5yaRxYEAoV79uV7SSPmVrt0KkNTuNRr9+urVYqtd3sX+sdL+sRs57N9lptfqqE3Zyo5zfbifl7Mi1B487ztiAryMtKie91shGNY1XnLoIgiLVIpbjCyddafaee3yl9XlYAVJ439DTNjp2JGx+nWGw6Y3/dbGvWuHAmIzYlNrCLPSrFy4Ks1G33jay/bnSsOlkQChAkxXF/q9Jei9U2rucKjusvq0010g/V+pP6e2Vp9ZPD4JxLnPORxU/rditM9MQCcDMg4C1Vj93v7migJJ+expzW+j3k99imA2Bbr/latfROMppls0sbDnhs7xffk+WpWEc1ma3l1dNG/btTebr+e+NB2/uJ+NL9uuS0Ka9SP1htYaWp1l4rTv1fSeaemN82T0/M+d2+vQ719MSap5tG5ErUmade/RblWnkdN9L2RvKsNE6+0s2cxyTnxX9dDOiN2+fXf1fyedb+cEqn16eX5SSXiwHtYW/F+3ZlO8ljplY7dGqD03jkvPy3kyyV2m72r/WOl/WIVc+6vVabnyrhNCda7cT8PRHzw82c5+2wz4Ogz1Pie51sxMWwqnMXQRDEWsQ8j1l9pZOvtfpO3Vc7pQ/6iq8xqzRv6GmaHTsTNz5OsZjT/G+2NWtc2B0NNCU2sKu7UrxcPA+hvnobWX/d6Fh10h72IhzwVNzfqhaL6r83hbwl+cz3rDbVSD9U60/q75Wl5ZvDa5HtHWEMbYnj6P5+w/jOnJ/EQ0cGSwKHU/fuMV6qruc7de8enDk/ifv3FfM+9sMJoxz9+xefuYjjBwZK0ullDm2J49S9e0rq3dUdwdH9/VXTm+uyyqjLZteex344gZxUwPGDAyV5HzoyiKHNcUQDbuOeXR2VZLbKMrQ5XnbvzPlJ3GzTRr2uM+cn0R7yObYNAAZ6Y2X989CRQQz0xo37djIN9pXKrpc70Bsru663064frLaw0lRrrxVr/9ci81AihpOHSus4eWgQQ4mYc57NcZw8bMlzeBDDm+3laoSBRMRWroFExFmu3rh9Wxz0Va9+gcZ0/LpE2Fau1yXs8wwmorbpBxNR57Y30I8rjZOv7Aj70BEuH+u/fdcteHJkEkf392N4SxwDvdXHYq39YZfu/n39eHJksqQs65wQ8BbfH7yzM4y/+f6r2N4RLrt/8tAAOsO+sjxf/dFETfZRqx06tXVoc7ws/8nDg3hyZNKxrXZ9Zdd2q3+td7ysR8x6Nturnc3WOicMbY7j5u4IfuenbynJf3R/v2En5u8nDxf91tCWOAqKUjZvHz84ALcL+NIzF0t8r52N6ONpNecugiCItYg+j9nFFbKi2MZRYJpt7OB1s7JY+PjBAXzhO68g4HWhK+o31j3WmEFP0+zYmbjxcYrFOiLuMvs12+OJQwMlceHJw4PwenhTYgO72GNoSxyfevfry+KRHZ1heN2sbrtvZP11o2PVyd98/1V4XQzbO8Ml8eaZ85M4cWjAca/lE5Y1w4lDA/jf333VyOdkU9XWFvXIbu1P6u+VhXHzfwesZsWMMQBbOOevtUQAAHv37uXnzp2zvadpHFfmBUynJeRkBVvbw9jWHsKVhRxmMiK6o/YnI+qnJ84LErxuF3Kyit54AKoGXMuKSMSK3zOiDEUD0qKMWMCHgqqVnOB5aU4w6tnaFsLE9Rym0xIKqoqo34tcQbVNr5d/LVsuoy6buVy9PYnF/6WbSUuYFST0xYMY2ByHx+OCpnG8tiBgOlW8t7UthIDXjVlBMuqoJLOuP/30dkXR8MJ0Ggu5AsSCih2Lmy92bdR1t5CTEPC6IUhqWXk6+gmtyZSIRDyAgd54yWFIdvXu7IqUya7rzKovczvN/VvDKZnLfju6na1Wa68Vu/ZUe3F7Pl/AhWTaON12KBGreoiZLKsYuZoyThAdXoETl4W8hLFk1pBrIBFxPIxORxQVXJhKLbWlN257GJ1OvfoFGtNxOi/ihaRgyPW6RNj2MDqdXF7GaDJjpB9MRB0Po9OpsR9XxE6dcPKViqphTpAhKxz5goqOiA9ZsYCA14OemB9b20vHZ6WxWGt/mE+9DfncKKga2i2n7Goax+U5AVdTeQiiimjQg56oH243M/xWwOOBICuQChp64n5oGofH7YIgqciIBWwK+aByDTlJtfVhdtRqh05ttea/tSeGiVS+YlvtytbbnhVV9Mb9uM3Gv9Y7XhpkVe3UilnPnWEfMqKCvKLCzRgUjUNWtJr7VkeWVTyXTCMnK8hKKkI+N0JeN9JSAX3xEARZweT1fIk/1fsknZeRKxTHTGfEh5DXjZQoI+j1lvleTSu+b+7KvICQr3Q8ESvCshRbyU4ZY3jPnz1Td5mP/OodDedrZL2wHDnXQ303CCtmp+sNfR6bEyRE/V4s5GRsCvogqyq2tPkxk1GKcVTUj83tHnSHInh+Oo2ZtIR4yItUvoC2kM/Y3DLHwpGAC1dmRQR8LrSFfNgU9mA2LSMjKcjJKrqjfnjdLlyZz61Y7LzOaencv16wi8VcLobptIDXFiTDfv1eF2bSEiIBN6IBLzKigjlBRk/Uj942PzbHmhcbOK2nX5nJ4tU5AQGvC0GfGwGPG7d0Rxuy+0bWXyvEmrFTq042RwMYn81CVFQUVA1ZUUXA60J7yId8QcVCvoDOsA85WUVGUtAe8iIW9CArqkgurh+jfjcuzubQHvahPeyBIBVfxZmIBdAR8WEqVfvaoh7ZreWsof5erzhvWrUyGGKMXeCcD7Wq/o0wSRBrgjUzURBEBchOifUA2SmxXqDNYdocXg/Q5jCxHqC5n1gPkJ0S6wFHO231ayV+xBh7Y4tlIAiCIAiCIAhiI+LygDFW96fvpq2tlpwgCIIgCKIpOP9N9erwEwDezxi7DEBAcRebc86HWysWQRAEQRAEQRA3PJrS8BPHBEEQBEEQNwKt3hz+6RbXTxAEQRAEQRAEQRAEQRAEsSFp6WslOOeXAdwEYN/i91yrZSIIgiAIgiAIglhL9N20lV5/QRAEQRDEitDSJ4cZY8cB7AVwC4C/AuAF8DcA/kMr5SIIgiAIgiAIglgrXJ14jV5/QRAEQRDEitDq10q8C8AbAPwIADjnVxlj0UYLY4zdBOBLAHoAcAB/zjl/eLlCahrHpTkB02kRPbEAtraFcGUhh+m0iN54AKoGzGSK97Z3hOFysYr59TRO153qnxMk+Nwu5GS1YvpmtdeuPgBVZbZrVy35KunKLk0qL0PVgNmshC1tQQQ8blzLSuiNB8A5MJORIKsq2oI+CLIKQVawrT2MHZ1LZZrrq9aXtfbXaqEoGsamUphKieiNBzHQG4PH4/zgfSPy11tHI3kaqUMUFVyYSiGZlpCI+THUG0cgUNmdNVJPvTSi41xexmgyg+m0hJ6YH4OJKEJBX1PlWo22rxTNHHdWPdzaE8VEKo85QULQ40ZKLCAjKti8KYjbEjFoGseFqykk0yI6Ij54XAwBrxvRgAdXr5fPB/XOAc1un1N9Zhm7owG4XcBUqj5Zqsm5HL+/3tA0jstzAmayImSFQ1ZUdEb8EAtacQ6KBTC0OQ6fz11Xmea5CJwjlVeQK6iYF2R0Rf1QVBUcDD6PCzlJwZZNIezoitwQOiUIglhJmjHXKoqGietpzKRVTGeKMdtAIoJw0F9z/ea1y+Z4EG438Np8HrGgB5vjwbJ1iKbxkrilLezBtbQMUVEhFTRs6yiua6zp1lOcR6wumsbx2oKA6ZQEUVEQ9Howk5HQHvbB52ZQwRHyerC7qxgjNyOG0zSOK/MC5rJF283JKuJBL7qjfmxtr69cvayZjIRUvoBYwIveTX4sZAuYSovYvCmIqN+D5A0Wey4XfQ00J0iI+r1YyBUQDXoQ9XlwLSshHHCDcYaspKA97EdBVaBxhmsZCe0RHzYFPQj5irbic7sgKRrcjOGaICEW8CDs9UCQVSTizd8fIlaPVm8Oy5xzzhjjAMAYCy+zPAXARznnP1rcZP4hY+wbnPPnGi1Q0zieGkvi2KPPQixo2NYRxG/u68cDj4+iLeTDfW/ehofPjkMsaAh4XTh17x7cPZAoWVCb8+tp7rq1B19/frrsujmvOf8nn3oe79m7FZ952rmuZlCpvs+97w2QFV5RZrv21pKvkq7syv/L776Cn7t9K048OVbSD20hH379rTshyCq+/IMr+MAdO5ArpG37CIBRX7W+rEW21URRNDx+fhIPPD5qyPPQkUEceX2fbTDYiPz11tFInkbqEEUFpy9M4cHTS3lOHhrEoaFexw3iRuqpl0Z0nMvLeHJ0uqwtBwZ7mrZBvBptXymaOe6setjWEcSH3t6Pz//z+KKfUEvG/8O/sAepvIIHn1jS2/GDA3AzDq/Hjb/67qt4aSaLh44M4rNPj+PyXL6uOcDqg5rlVyrNWXodR/f340vfu4yFnFyTLNXkXI7fX29oGsfTL07j6kIegqwa8451/jh5eBBHhjfXtEFs1l9byIeP3tWPkM+DVF7BiTNjS/Z3YACP/egK9t+aQMjrxoOnx/C7P30r3jm4vnVKEASxkjQjlihurMzjxWQOD54eK4nZfnawu+IGsd3axW4+Pn5wAH/67ZeNeOJT794DjWv4nb8fMebzY3fuxtXrYsl8Y023nuI8YnXRNI5/eXkGV69LeOyHVxbt8Udlca6sclycFfClZ17FucupZcVwdnGTXt+xO3djZ1cY+27pqalcvayL1wSc+sZLxrj4jbftwvHT9uPqRog9l4u+Bvrs0+Nl+ztH9/fjaxem8M6hXqNv9m6L4917t5bo9PjBAXRFfbg0m8Nff/+SbTlOOnfywT4Pw4f/7t9vqHXCeqfVM8ajjLE/A7CJMfZfAHwTwF80WhjnfIpzrj+FnAHwPIC+5Qh4aU4wDBkADgz3GYvse27fYgwiABALGo49+iwuzQmO+fU0Y1Mp2+vmvOb8B4b7jAFYKf1yqVTfyER1me3aW0u+SrqyK/++O3YawZW5H+65fQtmBRkPnx3HgeE+zOVkxz4y11etL2uRbTUZm0oZdqjL88DjoxibStmmb0T+eutoJE8jdVyYShmbqXqeB0+P4kIT5WqERnQ8mszYtmU0mWmaXKvR9pWimePOqocDw3148IlRRz9RULixMaxfO3FmDCGfF6/OCvjgW242dHlguM9RvkptWAm/UmnO0ut4+Ow47rl9S82yVJNzOX5/vXFpTsDIRMqYZ5zmjwefGMXI1drGmHUuCng80DQYG8N6mSeeHMN9d+zEw2fHMZeTcWC4Dx/9yvrXKUGU4fI09G7d9SInvQN4dWnGXDs2lYJUYMbGsF7Og6dHMZbM1lS/ee2i5zfPxyfOjJXEEx/9yrMYn8mWzOevXBPK5htruvUU5xGry6U5AZm8ihNnxmztUY9zZzISXp7J4r47dhr3Go3h7OImvcxT33gJIxOpmsvVy9I3hoHiuDh+2nlc3Qix53LR10B2+zsPnx3HB99yc0nf3HfHzjKdnjgzBp/bhT/++ouO5Tjp3MkHj0ykbrh1wnqnpU8Oc87/mDF2J4A0gN0AHuScf6MZZTPGtqP4yop/tVz/FQC/AgBbt1YPzqbTomG0xfwwfpu/64gFDTMZETu7Irb59TRTKfvr5rzm/LXU1Qwq1afxxtpbSz6nvE7l5yXFth8YW6rP/N2uTM5r78taZGs2lWzVyX6SKRGvv6m8rEbkr7eORvI0UkcyLdnmmU5L9hkarKdeGtHxdANtqZeVbnu9PrUemjnurHrQx7yTnxBMPsZctyAr0DiQlxXjmnlPotY5wOqDlts+nUpzlrkOXeZaZKkm53L8/mrRLDudTovQePF7tfljOi3WXKa5LEFasi1rmXm5aJcaX6q3VTolms9K+tN1haasj3frNirnr7+lNZvZTWK92WkzYomplIiCqjUUs9mtXcz5zfOxNZ7Q5xsAFdc15nT6tWbGuOuV9WarK810WjTiWyd71ONcYCnW1e81Em/YxU3mMjWOmsvVy2okzl3LcdJK26m+BnLSlR5b6jjZxkKuULEcJ507+WA7v7XW++pGp9WvlQCACwCCKL4j+EIzCmSMRQA8BuC3OOdp8z3O+Z8D+HMA2Lt3L7fJXkJPLICA11Vi0Obfdve6o4Gq+Xvjwap5zflrqasZVKrPzRprby35nPI6lR/yexz7Qa+vlrpr7ctaZGs2lWzVyX4ScXt5GpG/3joaydNIHYmY3zZPT8z5T/oaqadeGtFxTwNtqZeVbnu9PrUemjnunPQA2PuJcMBjmz7s88DFgKDPY1zjplbXOgfY+aDltK9afdbfusy1ylKvf6zV768WzbLTnlgA7sXgt9r80ROrra1W/YUDS7ZlLTPoK9qliwGq1lqdEs1nJf0psYZYL5vfDqw3O21GLNEbD0JS1IZiNqe1i57fPB9b4wnrX1c7za3WdM2Ocdcr681WV5qeWABzglzRHvU4F1iKdfV7jcQbTnGT/tvFUHO5elmNxrlrlZW2U30NBNjrKuQrtQUn22gLeSuW46RzJx9s57fWel/d6LT0tRKMsQ8C+DcA9wD4eQDfZ4x9YJllelHcGP5bzvlXlyvj9o4wTt27xxgIZ85P4qEjgwh4XXjshxM4ur+/ZJCcuneP8YJtu/x6moHemO11c15z/jPnJ3H/vsp1NYNK9Q1tiVeV2a69teSrpCu78r/4zEUcPzBQ1g+P/XACHWEfju7vx5nzk2gP+Rz7yFxftb6sRbbVZKA3ZtihLs9DRwYx0Bu3Td+I/PXW0UieRuoY6o3j5KHSPCcPDWKoiXI1QiM6HkxEbdsymGj4XM4yVqPtK0Uzx51VD2fOT+Lk4UFHP+F1M5w8XKq34wcHkJML2NEZxhe+84qhyydHJh3lq9SGlfArleYsvY6j+/vx1R9N1CxLNTmX4/fXG9s7whjaEjfmGaf54+ThQQxvrm2MWecisaDAxYDjBwdK7e/AAL70zEUc3d+PjpAPT45M4lPvXv86JQiCWEmaMdcO9Mbg93CcPFTql08eGsRAovJTbnZrFz2/eT4+fnCgJJ741Lv3oL87UjKf7+wKl8031nTrKc4jVpftHWFEA24cPzhga496nNsd9WNXdwRfeuaica/RGM4ubtLLPHbnbgxviddcrl7WsTt3l4yLE4ecx9WNEHsuF30NZLe/c3R/P/7iO6+U9M0Xn7lYptPjBwcgqxp++65bHMtx0rmTDx7eEr/h1gnrHcZ56/4TjTH2IoA7OOdzi787ADzDOb+lwfIYgC8CmOec/1a19Hv37uXnzp2rWq5+uuJMpnjSu37y+0xGRCIWgKoB17LFe5VOZ9Tz62mcrjvVPy9I8LpdyMnqip7oWKk+AFVltmtXLfkq6couTTovQ9GKJ/5uaQsi4HFjVpCQiAXAOTCTkVBQVWwK+iDIKnKygq3txVN9zS9I1+ur1pe19pcNy+4kO1vVTx1NpkQk4gEM9MYrHjzRiPz11tFInkbqEEUFF6ZSmE4XT4se6o07Hka3nHrqpREd5/IyRpMZoy2DiWjTDqPTqbHtK2Kny2UZ464Mqx5u7YlhIpXHvCAh4HEjJRaQFVX0xv24rTcOTeO4cDWFZFpEe9gHr5sh4HEjGvRgKlU+H9Q7BzS7fU71mWXsigTgdgHJdH2yVJNzOX6/Tlpup5rGcXlOwExWhKxwyIqKzrAfoqLhWrY4Bw1vjtd0GJ25TPNcBM6RyivIFVTMCzK6on4oqgoOBp/HhZykoG9TCDu7InRwx9plWR1TyU4ZYw0/edpovkbWC62Qk/LZ56vQfytmp2uJZsy1iqJh4noaM2kV05lizDaQiFQ8jM5av3nt0hsPwONmmJgXEQm40bcpWLYO0TS+FLfEAmiLeHEtLUNUVMiKZqxrStKtUIzbYlo+998oaBrHawsCplMSJFWB3+PBtYyE9rAPPjeDwjnCPg92d0Uxkco3JYbTNI4r8wLmskXbzUkqNoW86Ir6sbW9vnL1sq5lJFzPFxALeNG7yY+FbAHJtIjeeADRgBfTzY09a2XN2qm+BpoTJET9XlzPFRAJeBDxezCblRDyu+ECgyAp2BTyQdVUaJxhZtE2NgU9CPmLtuJ1uyCrGhgY5gQJEb8HEZ8HuYLzHtUqrhOI6jgqudWbw88AeBvnXF787QPwLc55Q383xRj7SQD/guLrKfTn1n+Pc/6PdulpkiBWiTU7URCECbJTYj1AdkqsF2hzmDaH10y+jb45TKx7aO4n1gNkp8R6wNFOW/LOYcbYscWvLwP4V8bYEyi+c/gwgJFGy+WcfxdNGJQEQRAEQRAEQRAEQRAEQRA3Oq06kE5/oeYrix+dJ1ogC0EQBEEQBEEQBEEQBEEQxIajJZvDnPMTraiXIAiCIAiCIIg6cHlQPNaDIAiCIAiCuBFp1ZPDAADG2F4A/xXANrMsnPPhlglFEARBEARBEEQRTWn4XbcEQRAEQRDE2qelm8MA/hbA76D0ADmCIAiCIAiCIAiCIAiCIAhihWn15vA1zvnpFsvgiKZxXJkXMJ2WIKsqYn4vZE2Dz+1CTlbRGw9A1YD5nGRc64kFsLUthInruZJ8uULx3vaOMFwutqyyryzkMJ0WS8qzyn1pTsB0WjTKmcmIZbIJsoJt7WFsa69cpl7enCAh6HVDKmgQFRVSQcO2jjB2dC61Sa9XLweAca2vLYCZtIxkWkRvLIChzXF4PC5DD4KsYEdHGBpfktdJFqc6qulEb4MgqUZ9ADAvyBXblMrLYGAQFRWKyiErpelagSyrGLmaKtGnz+d2TC+KCi5MpZBMS0jE/BjqjSMQqOwCcnkZo8kMptMSemJ+DCaiCAV9FfPk8wVcSKaNPEOJGIJBb8vlsrOdSn2nKBrGplKYSonojQcx0BuDx+OqWEe9fQLUr6960zfalmZhpxPruN/WXttYqtaHTvc1jePVWQGX5wWEfR6E/W7kJBVeN4PGOWSVY16Q0RnxwethcDMXZEXDQq6AoNeFsN+DjogPN7WV1qcoGsaupjCZyiMRC0AsqMhKKnZ0hnFzV2RFfUMlXdjNAfpcIikaXIzhWkZCR8SHRNyPgmLvc2utI+TzIC3K8Lnd6In5sbW9dX6xGeTyMsaSGUxnJHRF/VBUBV63BxmpgKjfi7RYQDzgRcjnRlpUGtZbT9SHOaGAmYyEzogfYkFBW8iP2xbHpzlO0OcrVeO4spBD2OdZd7quND4vzQlIpkT4PS6kRBkd4UBT/FSzfJ/V3jVeHEd6bFZtPiEIonFqid/0sT4nSGgP+cEYh1TgmFmc6yJ+N7Z2BLEgKJjLLsX8N7WHICkqJhbyKxIflfhxSUHvJj+yoloyv4C7EA95kC9o6Aj7yZ+sIlbfLqtqSR9Us71mzDGyrOK5ZBppsQCxoK1KDNlMzDro7w5iXijad0fYB5+bgTGgLeiDy82QTDnvjTRCNi/ihaSAa1kZEb8HbWEv/G43ZgUJ3RE/8oqK2ayIsM+LhVwBkYAbvbEgtq3zMWYXg4e8HnjdDIKsIhELICMWcDUloivih9fDwDmMPSbOgZmMBFVT4XW7MZOR0B72Ieh1FdcMgoxIwAOVqwh6vBAVFYKkIhJwI+z1QANHPOjDlngQz0+nMZUSsXlTEFG/B8m0iLDfAxeAXEHFnCBjU9CLkNeN6YyIntjSODHvz5j3u8gHNk69+x1WWr05fJwx9gUAZwFI+kXO+VdbJ1IRTeN4+sVpjE9n8eUfXMF79m7FI+eK/37m6XG0hXy4783bjHufeXocYkHDto4gfvuuWzCxkC+7F/C6cOrePbjr1h58a3ymobJ/c18/Hnh8tKS8uwcSJQvPp8aSOPbos0Y5D58tl818rVKZenmffOp5fOCOHWAMEGTVyG9u09efn8axR581rn/ufW+ArHAce/RZvHlHO+4e6sXx02PG/T/6+WEEvW68PJPFw2fHy+R1ksWpjmo60duQK6hGfb/+1p0AKrfpL7/7Ct7/E9uREQu26cx1rRayrOLxkat48Imlfjt5eBBHhjfbbkaKooLTF6bw4GlT+kODODTU67gRm8vLeHJ0uizPgcEex43YfL6AM6PJsjwHBxO2G5irJZed7VTqO0XR8Pj5yZJx8dCRQRx5fZ9j0FdvnzSir3rTN9qWZuGkk+2dAfzwUqqusVStD53u2/mmo/v70RHywuVmKKjAiTNLfunjBwcQC3pw7NHzJekT8QAuzQn4qV3dcLlYiV7tfNen3r0H7xxcGd9QSRcAyuYAu3lG9/+/8bZdJX7Zrpxa7t2/rx+PnLuCX3jjVvT3RLDvlp51GdjZ+ZfjBwbw2I/Gse91CUOHelu/9L3LWMjJdettd3cE7/2JbSW2V9ThGH5zXz8ODW3Gd165hvFp5/nx6P7+daPresZnUQ/P4Tf39S/LTzXL91ll39YRxK+9ZRdOPFk+btZ6PxDEeqOW+E0f6599ehwfuGMHsmIBYoHjQdPcdvzgAK6mRPg8DC9MZct8qe7LmxkfmdeSD58dt/X7xfnlCvbfmkBH2Ivf/sp5fOzuW8mfrAJ2tqXHMh+7+1bb+clse82YY2RZxVPPJzFpWpuvdAzZTMw6eO/ePqTFtpKY//jBAbgZh6pxBHwe/O33L2Hf6xJleyON2Hs2L+JrY9fw+4v1besI4tfeuqtkfB27czf8bhf+f0/9+7qMneyws9uPvGM3gl4X/vBrL9jGiycODeAr565g8rqEX3/rTgiyirPPJ/HzP7YVH1/Ul92a4OMHByArOfzh114o0WlXxI+vjY7jHbdtLulv3Zf6PAwffnu/0Td2fvbQ0GZ888UZfPKp5233y8gH1k+9+x12rM6jY878MoA9AO4GcHDxc6CVAulcmhMwMlHcvDgw3IfPPL30r1jQcM/tW0ruiYXiWzEODPdhfHGz03pPLGg49uizGJtKNVy2PgGZy7s0J5TIrRuEXo6dbLWWqZd3YLgPczkZs4Jckt/cJr1e/frIxNK1X/rJHYaz0e+/PJPFhcmlDSKrvE6yONVRTSd6G8z1zQrV23TfHTvx6pzgmM5c12oxcjVlOGNdlgefGMXI1ZRt+gtTKWOzw0h/ehQXpuzTA8BoMmObZzSZccxzIZm2ryeZbqlcdrZTqe/GplJl4+KBx0cxVkGuevsEaEBfdaZvtC3NwkknqsrqHkvV+tDpvp1vevjsOEJ+LwIejxFE6vc+fmYMmoay9K/OCsjkVaM+s17tfNdHv7JyvqGSLuzmALt5Bij6f6tftiunlnt6+Q+fHcfIRKolfrEZ2PmXE0+O4b47dpboUG/rPbdvaUhvH3zLzWW2p5f7wONFv6HHCU42tp50Xc/4NOthOX6qWb7PKvuB4T5jY9jclvXQDwSx3qglftPHuh7nbwr5jY1hPc+JM2MoKBwBj8fWl+q+vJnxkXkt6eT39fnl4bPjmLgu4sBwH/mTVaJSLOM0P5n7phlzzMjVlPGQ1GrFkM3ErIOfHuori/lPnBlDyOfFVFrCq7OCEUs1Y/58LikYm4/A4txsGV+nvvES5nLyuo2d7LCz209/8yXMCrJjvHj8dNHP6HsfD58dx3137DQ2hgH7NcHHz4wZ5erXTn3jJbw6J+D9b9pR1t+6Lz0w3FfSN3Z+duRqytifaZZNbHTq3e+wo9Wbw2/knO/lnP8nzvkvL34+0GKZAADTaREaLyqVsdJ/Adhe069b85kRCxqmUo2XbVfeTEYskdtajp1stZapl6fnteY3t8l63Zx2QSjY3jenqVUWpzqq6cTa/lrblJeUiunMda0WSRtdiAUN02l7WZJpySG9ZJseAKZXIc/qyWWvL6e+s7NnsaAhmXLu63r7pChXfW1ppO2NtKVZOOnkWta+HZXGUrU+dLrv1H5BViBIiuM96zWNA4KsGPWZy63FNzeTSrqwmwMamVNqrcN8Ty9PfzXQesRpjOVlxVaXjC2lqUdveQfb08tNmmIQwLmv1ouu6x2fhh6W4aea5fussq/2eCeIjUwt8Zs+1vW4ft5mzaHP7U7xh9mXNys+mrb4cSe/r88vGl/yL+RPVp5qsYzTHGIXB5rv12M/1rnerp61jFkH1zLO8ba+jtZt3ZqmkbZa47VKcZLdtfWgXzuc7FZvp5Me8rJSshdi9Uf16s9ub0cfP05llfhZ0/7MerX/tUa9+x12tHpz+BnG2G0tlsGWnlgAbgYEvEUVWf91ugbANp85T2882HDZdr+7o4ESue3KsZOtljLN5bmZc/7eeLBiXe1hr+19a3m1ylKtPU46saavpU0hv6diOnNdq0WvjS4CXhd6YvayJGJ+h/R+xzp6ViHP6sllry+nvrOz54DXhUTcua/r7ZOiXPW1pZG2N9KWZuGkk66IfTsqjaVqfeh036n9YZ8H4YDH8Z71mosBYZ/HqM9a7mr6hkq6cJoD6p1T6qlDv8f5kq5a4RebgdMYC/o8JW00/6unqUdvIb+97enlJiwxiH7fmn696Np5fFa2peX4qWb5PifZrb/XQz8QxHqjlvjNPNbdzH7Noc/tTvGH2Zc3Kz6yriWd/L4+v7gYDN9H/mTlqRbLOM1PTnGgfr8e++m1meut9axlzDrojtrrK+zzwMUAFwNCPvsx0EhbneI162/rX9Ovp9jJDie7NbfTyc8AS/sZTv6oUrnma20OftbsSyvdS5jasV7tf61R736HHa3eHH4TgGcZYy8yxkYYYxcYYyMtlgkAsL0jjKEtcRzd348z5ydx/76lfwNeFx774UTJPb0jzpyfxK7uiO29gLf43o+B3ljDZT90ZLCsPP1QNl3uU/fuKSnHTrZay9TLO3N+Eu0hHzrCvpL85jbp9erXh7bEjWt/9d1XceLQQMn9m7sjGOyLG+VZ5XWSxamOajrR22CuryNcvU1ffOYitneEHdOZ61othjbHcfJwab+dPDyI4c1x+/S9cZw8ZEl/aBBDvfbpAWAwEbXNM5iIOsuViNnXk4i1VC4726nUdwO9sbJx8dCRQQxUkKvePgEa0Fed6RttS7Nw0onbzeseS9X60Om+nW86ur8fOakAsaDg+MFSv/TxgwNwuVCWfkdnGNGg26jPrFc73/Wpd6+cb6ikC7s5wG6eAYr+3+qX7cqp5d79+/rx5Mgkju7vx/CWeEv8YjOw8y/HDwzgS89cNNpobutXfzTRkN7+4juvlNmeXu5DR4p+Q48TnGxsPenaeXyWz+FmPSzHTzXL91llP3N+EscP2I8bgiCaSy3xmz7W9Tj/ek7CScvcdvzgALweBlFRbH2p7subGR+Z15JOfl+fX47u78eWTQE8OTJJ/mSVqBTLOM1P5r5pxhwztDmOmy1r85WOIZuJWQdPXZgsi/mPHxxATi6gN+bHjs4wvrgYSzVj/rwtEcYnTPWdOT9ZNr6O3bkbHSHfuo2d7LCz24+8Yzc6wz7HePHEoaKf0fc+ju7vxxefuYiPm/Rltyb4+MEBo1z92rE7d2NHRxh/+/1Xy/pb96Vnzk+W9I2dnx3eHDf2Z5plExudevc77GCc8+qpVgjG2Da765zzy6tR/969e/m5c+cc75tPmC2oKqJ+L2RNM05T1E+BX8hJ8JpOWNzaFsLE9VxJPuuJnMsp+8pCDjMZEd1R+xMI9VMKZzIiErFiOdeyxfRm2XKygq3tYWxrr1ymXt68ICHgdUMqaBAVFbKiYWt7GDs6S090NZcDwLi2eVMAM2nZOD1xeHMcHo/L0ENOVrC9IwyNL8nrJItTHdV0ordBkFSjPqB4KmelNqXzMgAGUVGhqByyomFbx1K6Kiz7bep2tirLKkaupkr06XTwGQCIooILUylMpyX0xPwY6o07Hvqmk8vLGE1mjDyDiajjoW86+XwBF5LppXoSMcfD0lZTLjvbqdR3+um7yZSIRDyAgd541QMm6u0ToH591Zu+jrasmp1ax715zFWiWh863dc0jldnBVyZFxDyeRD2u5GTVXhdDBrnkFWOeUFGR8QHr5vBw1yQVQ0LuQICXhciPg86oj7c1GZzSvXVFCZTeSSiAYiKiqykrspJ05V0YTcH6HOJrGpgYJjNSmgP+ZDY5EdBsfe5tdQxnRYR8rqRkQrwut3oifmxtX1FTxleETs1k8vLGEtmiqfJR/xQFk9zzkoFRPxeZMQCYgEvQj430qJSdhpwrX3THfFiTij+mXNH2A+xoGBTyGeMT3OcoM9Xqsbx2kIOIZ9nNXTdVCqNT92WvG4XMqKM9rC/Jp9bjUb8eCXZiyeDu8E5B2Os2snay+qYSnbKGMN7/uyZust85FfvoHwbNF+F9d6K2WmzqCV+08f6vCChLeQHYxxSgWMmK6Ej7EPY58a2ziAWBAVz2aWYf0tbCJKiYnIhvywfUUl23Y8LkoLeuB9ZSS2ZXzhniAc9EBUNHWF/3afLbxBWZO63+vaCqqHd1AfVbK8Zc4wsq3gumUZaLP6Z/mrEkM3ErINd3UHMCypmMhLawz743AwMwKaQD243QzLlvDfSCNm8iBeSAq5lZUQCHrQFvfB73JjLSegM+yEqKmazEsI+DxZyBYT9bmyOB7Ft5cbYiseogH0MHvR64HUzCLKKRCyAjFjA1ZSIzogffg+DxmHsMXEOzGQkqIvxrd5fQa8LqlbcF4kEPNC4hoDHA1FRIUgqwn734l9XcsSCPmyJB/H8dBrJlIjeeADRgBfJtIiwzw0XY8gVVMwLMuJBL0JeN6YzxbWrOc7V92fM+13kAxunxv0OR+W2enN4q911zvmV1ah/NQIagsAqTRQEsUzITon1ANkpsV6gzWHKt2byrefNYYIAzf3E+oDslFgPONpp5cfzVp5/AMBRFDAAYAeAFwEMtFIogiAIgiAIgiAIgiAIgiCIG52Wbg5zzofMvxljtwP4jRaJQxAEQRAEQRAEQRAEQRAEsWFo9YF0JXDOfwTgJ1otB0EQBEEQBEEQBEEQBEEQxI1OS58cZowdM/10AbgdwNUWiUMQBEEQBEEQBEEQBEEQBLFhaPU7h6Om7wqK7yB+rEWyEARBEARBEARBEARBEARBbBha/c7hE80ukzF2N4CHAbgBfIFz/t+aXQdBEARBEARBEARBEARBEMR6p9WvldgN4LcBbDfLwjnf12B5bgCfB3AngAkAP2CMneacP7d8aUvRNI5LcwLmBAk+twsa51A1YDYrYUtbEAGPGwt5GT63CzlZRW88AFUDZjJiyfeeWADbO8JQFA3PJdPIFxSoGiArGrZ1hLGjMwyXiznWm5NV9MQC2NoWwsT1HKbTEgRZwc7OMFK5AuZyEroiAeRkFRmpgM6wH6KioaCqiPm9kDUNQa8bUkGDwjV4XAwFlSMrKtgU8kHjHH7PUj3bO5bk0TSOK/MCUrkCODjyBQ1ZSUEiVqxvTpCwozMERQWu5wsQCyp2dYahgTnqwVz2pTkB0+liOs6BeUGGwjUAgKJySAUNOzrD0PhSGZujAYwm00imRdy0KYiQ34OsVDD6pjcexEBvDC4XM8rX6wZg6FbXiaiokArlfaG3Xdf3tvbyvlppFEXD2FQKUynRaJfH4/wa8Vxexmgyg+m0hJ6YH4OJKEJBX8U6GsmTzxdwIZk28gwlYggGvY7p03kRLyQFI/3rEmHEgoGKdYiiggtTKSTTEhIxP4Z64wgEKruzevM0UoeQlzCWzBptGUhEEA76myrX9byIl0z62p0IY1MVfcmyipGrKSTTInpjAQxtjsPnc1fM0yzqtQcrZl8Q8nkgqyo6wv4Sf2FGllU8n0wjJRaQk1X0bQoiGvCUjVUARrmbNwVwXSggrxTgYm5DVg4VnaEgwJZ81rwgYzojIeL3wOdmCHhcKGgc02kJHREfemN+pPIKrlYYl9axe2tPFBOpvOHvFJXjykIOYZ8HPTE/tmwK4fJ8DpfnBYR9HiTifiiqve+spL+w34OCoiEnK4j4PchICsRFP3pzV6REJ5X8s7X8K/MC5rKyo79cb1ht1sMYNoV92BIP4vlkGpOpPDojfvTE/LipLQxN40Z/7ugMIiNqSKZFJGJ++NwuTF4XsTnuh6QW7SQR8yPkc+O1hTw2x4NQNQ0T18Wa/Uw17OYGuznPafyMXE1hOi2iO+qHx80QD/rK0pvtSi/PrAezXUuKAknWkJFUCLKCzogPC7kC2kM+wxdpGsel2SyupkRkJQWxoAcBjxvtYR+2tq9fWyKIjYjdvJMSC46xsjVG6e8JGXFhb9wPjXPMZQvoivpwW08xDtXnnpmMBEVV4fd6MJeVEQ14kJMVtId9GEiUxjqaxnFlLouptIS5rIxE3I/BhLPP1TSOV2cFXJ4XEPN74HYxTF4X0RH1oS3kwa7OynF3Pl/AaDKN6YyEzogPfo8Lc1kZOzrC2NEVMfRg9dmbQh5cvV59fgcai1WrYeffAdQ0hzSrvo3i8/W5L5kWkRYVhH1utIV9eF1PuW3pevJ6FExdV2teB5jtWI8rt7aXz9nxoAcXZ0vTWPtB0zheWxAwnZIwK0jo2xRCf2cIY8kMkmkJN7UF4HW7MJ8rgHMNAa8H1zISuqJ+uBkAMCzkZcQCXiOGarSvzX4jEfPD73FhIVcoiWtrKbvW8Vfvunul0ftiNiNDkBXkCyraw16AM8PntIc9yIraYryvoifqh6oB17IS4kEvCqqKoNeDhVwBsaAHbSEPFA3ISapRRiIWKLEF83iNBjwQCyrmhQJCPjfCfje0xfK7o34omoZ5oYCuiB+KpoLBBUFW0BHxQ1KW1nNAqX/ZEg/i+en0mtH1RqLVr5X4CoA/BfAFAGoTyvtxAC9zzi8CAGPsywAOA2jq5rCmcTw1lsQnn3oe79m7FU+/kMTP3b4VJ54cQ1vIh/vevA1f/sEVvGfvVnzm6XHj2sNnS7+LBQ0Brwt/+Us/htlsAdcFGYKsltw7de8e3D2QgMvFyur9zNPFdNs6gvjtu27BxEIeD58dx+7uCN77E9vwp99+GR96682YTsv402+/jA/csQPj01lDtkfOXcEH7tgBtug3A14XVM7wp99+2bhvrscsDwA8/eI05rMSIgEvUnnFqG82K+PEmTHs7o7gl39yB5Ipsaztdnowl/3UWBLHHn0WbSEffv2tO0v0r+vIWsZdt3XiHbduxoOnR417Z59f6hu9nv/+88NwMRc++pVnjWufe98bICscn3zqeUMnTn2ht318OuvYVyuNomh4/PwkHnh81Kj/oSODOPL6PlvnmcvLeHJ0Gg+eXkp/8tAgDgz2OG72NpInny/gzGiyLM/BwYTthmA6L+Kp0Wtl6e8e7HLcIBZFBacvTJXlOTTU6xgQ15unkTqEvIR/GJ0py/Ozg92OG8T11nM9L+LrNvq6a7DLMTCUZRWPj1zFg0+Y8hwexJHhzSu+QVyvPVjRfd6xR5fG6v37+vHIuSv42N23lo03WVbx1PNJTC76Qt0//vpbd+HjZ5Z8wKfevQd+L8OH/+7fDX/5zy9MYf+tvTh+eindiUMDmPZK+N3HRrG7O4L3v2lbyf2j+/sRXtTh//z2RSzkZJw4NICvnLuCc5dTtuPSbuyePDyIR39wGZPXpTK/+HvvfB1Cfk9J+uMHB/Cn334Zl+fyFX2Pnf6O3bkbmwIezOUKJfV89r1vQEHlht918s/WDcKnX5zG1YV8xblrPWFns8cPDOCxH13BvW/chs//87ih9+MHB7A5LiAtKvidvx/Bm3e04+6hUhs6fnAAL01dx+s2byq7/n/+9TJemsni6P5+fOl7l7GQk6v6mWo4zQ1dUR9+9a9/VLF/7HyF3vYP/OTNZbGI2a4+9e490LiG3/n7kRK7Tgs5dG+KlIzJgNeFj7xjNx76t+fwobf349BgL/7l4ixenimdU4/duRshnxuJeBb7bulZd7ZEEBsRO/9g9nFW32P1O9s6gvjQ2/pLfLA5/ycOD+JnBrrxvUsLuHhNwNfHpvCeN27D7z/xw7I44cNv78fhxVhH0zj+ZXwGV1MSTpjiASefW60dxw8O4Mq8iH27u23jbtu5xOT3P/XuPXjnYAKaxst8tjldpbm0kVi1kf47de8e+DzFmKnZc7xTfesxfqgXTeM4+8I0Xp0VcOobL5XY2cVZAT8z0GvYlq6nTUFgYqGAB0+X2rDTOsDJjl9/UwxXr0uOdnd0fz/6eyIlc6+mcfzLyzO4er18DD16rhjDfujtNyMjKqb194/K4ol9r0vgkXNX8Gtv3YXNmwT81K7uuvvazm/8xtt2lcRZ+hirVLZdzGQ3/uzGaaV190qj98W8ULDdZzH3DaDhwdPP2d7XfaW+7/Nb79gNVeNl+rg8X+wnoHSP5pf/w/YS27WuT6w+03zvI+/Yjb/7t8v4/QO3QVa4YaN7t8Vx7xu3lcSirdT1RqPVGlY45/+Tc/5vnPMf6p9llNcH4DXT74nFa03l0pyAY48+iwPDffjM0+O4746dxubjPbdvwcNnx4175mvW7wAgFjQoKvDyTBazglx279ijz+LSnGBbr57uwHAfxk2Lqg++5WacODOGA8N9CPm9xve5nFwim35tVih+Qr6ltPp9cz1meS7NCRiZSCHk80LTUFafLsers4Jt2+30YC5bdxD33L7FkE//OJXx/jftMAIk/Z65b/R6xmeyxsawfm1kImXoVtdJJflGJlIV+2qlGZtKGY5br/+Bx0cxNpWyTT+azBi60dM/eHoUo8mMYx2N5LmQTNvmuZBM26Z/ISnYpn8h6azHC1Mp+zoc2t5InkbqGEtmbfOMJbNNk+slB329VEFfI1dTxgRr5HliFCNXndvSLOq1BytmX6Dn132T3XgbuZoq2WACiv5R3xjWy/joV57FyESqxF++/007jKBST3f89Bg2hfxGOuv9h8+OG37pntu3GHnuu2OnkcY6Lu3G7oNPjOK+O3ba+sVZQS5Lr/tb/beT77HT36lvvISQ31tWz4XJVInfrcW/6b6w2ty1nrCz2RNPFvv0wSdGS/R+4swYMqKK8ZksxIKGX/rJchs6cWYMPz3UZ3v9g2+52bAj3X6q+ZlqOM0NmbxatX/sfIXedrtYxDqmdD3o1x58YhTDN3WWjUmxoOHT33wJB4b78OATxfZemCyfU0994yXMZCSMTKTWpS0RxEbEzj+YfZzV91j9zoHhvjIfbM7/+08U46qRiRROfeMl3HfHTvy+xW/pccLvm2KdS3MCMqJqrFH0tE4+t1o7TpwZg1zQHONu27nE5Pc/+pWiHux8tjldpbm0kVi1GnbtPvboUsxkvtYMv+xU30bw+ZfmBFyYTBmba8CSnb08ky2xLV1PHpfP2BjW01daBzjZsaKiot09fHa8bO69NCcgk7cfQ3oMO5ORHNffejyhj88TZ8aQyasN9bWd37DGWfoYq0St46/edfdKo/eF0z6LLuODp0cR8nkd75v3ew4M9+HVWcFWH3o/WfdorLZrXZ9Yfab5nh4H6nswejl6vL1WdL3RaPXm8BnG2G8wxnoZY+36ZyUrZIz9CmPsHGPs3LVr1xoqYzotQixoYKxosPnFP80tlo+Se+Zr1u8680IBGgc0Xn5PLGiYyYi29S61qTSvLg9jgGD6rqcxy6jXq/HStHb1mOWZTotGHsGmPl0Os1zV9GAu25zOLKNTeQCwIBTK7pn7RsdOz2bdVOsLve2V+qoZVLLVqZRoW38yZV//dFqyTT+dlhzrX408jdSRXIU8jdSxGm1prA57W5lON8dWK9lpI/KW5reXXR/f1vGWtBmbTr5G48Xvuo8w+w9zuoVcoSSdXTkah/EXGGJBQ15WStKYx6XT2M3Liq2sTr5Gr0//bed7nPQnVPGLlfyztfxa5q61QK1zv5PN5mXFVu+CrBi25GRD1zLOfa5/N9tPrePDDif7Ekw2qV+zGz+V2m6NRazpdD2Yr01nnOdL3c6SackxjW5fa8mWVpJmxKgEsdJUnved5239u3k8W/2O0/xj9ZG6z3Cam/Vy9FhnOi3azn1OPreWdgiyUnfcbfb7MxmxYkxgTmdHI7FqNerx783wy071Ncvnr2WfWmk9qXGU2Jaup2mHeMJ53WCfft4hXjHbnXXurTSG9Bi22rg0x1L6GGqkr2v1G9XKrnX81bvurpd67VTvi1pidz3+q+Rb9X+d7FHvJ+seTS3rE7PPtLtnrdPJdpqla6Iyrd4c/k8AfgfAMwB+uPg5t4zyJgHcZPq9ZfGaAef8zznneznne7u6uhqqpCcWQMBbVF3A60LI7zF+69fM/1b6DgDtYS/cDHCz8nsBrwvd0YBtvWbMec3yhANL381pzNf0jzmtUz26PD2xgJHHnM/8PeT3lLWpkh7MZZvvmWWsVF572Ft2z9o3Vj3YXavWF3rbK/VVM6hkq73xoG39ibh9/T0xv236npjz+3BXI08jdSRWIU8jdaxGWxqpo9cynpbyNMdWK9lpI/KW5reXnXP78dZbYWxaf+t/Zab7CKv/0NO1hbwl6ezKcTGA86VrQZ+nJI15XDqNXT1PLf5K14H5t53vcdKf2U871VOLf9N94Wr4w+VS69zvZLNBn8dW72Gfx7AlJxvqjtr3g7nPzfZT6/iww8m+wj5P2TW78VOp7XaxiDmd9S83dT9TyYYDXhcSMb9jGn18rSVbWkmaEaMSxEpTed53nrf17+bx7OR3KuXvMfkMp7lZ9y96rNMTC9jOfU4+t5Z2FM8AqC/uNvv97migppjAyf81EqtWox7/3gy/7FRfs3z+WvapleZHF0OJbel6ctKX87rBPr1TvGK2O+vcW2kM6fmqjUtzLKWPoUb6ula/Ua3sWsdfvevueqnXTvW+qCV2D1vWJNb7el9w7hzP6/1ktada1idmn2l3z1qnk+00S9dEZVq6Ocw532Hz2Vk9pyM/ANDPGNvBGPMB+AUAp5sj7RLbO8I4de8enDk/ifv39eOLz1zE8QMDCHhdeOyHEzi6v9+4Z75m/Q4Ujd3jBm7ujqAj7Cu7d+rePcaLuq316unOnJ/Eru6IkfcvvvMKjh8cwJnzk8iJBeN7e8hXIpt+rSNc/OSkpbT6fXM9Znm2d4QxtCWOnFSAi6GsPl2O7Z1h27bb6cFc9ql79xjpdPn0j1MZf/P9V3Hy0GDJPXPf6PXs6o7gU+/eU3JtaEvc0K2uk0ryDW2JV+yrlWagN4aHjgyW1P/QkUEM9MZt0w8mooZu9PQnDw1iMBF1rKORPEOJmG2eoUTMNv3rEmHb9K9LOOtxqDduX4dD2xvJ00gdA4mIbZ6BRKRpcu120NfuSvraHMfJw5Y8hwcxvNm5Lc2iXnuwYvYFev779/XjyZFJ2/E2tDmOm02+ECj6x48fLPUBn3r3HgxviZf4y7/5/qs4cag03YlDA7iek4x01vtH9/ejM+xDZ9iHr/5owsjzpWcuGmms49Ju7J48PIgvPXPR1i92hH1l6Y8fHMCTI5PGbyffY6e/Y3fuRk4slNUz2Bcv8bu1+DfdF1abu9YTdjZ7/ECxT08eHizR+/GDA4gG3OjvjiDgdeGvvltuQ8cPDuCpC5O217/wnVcMO9Ltp5qfqYbT3BANuqv2j52v0NtuF4tYx5SuB/3aycODGLkyWzYmA97iu+aeHJnEycPF9g72lc+px+7cje6oH8Nb4uvSlghiI2LnH8w+zup7rH7nzPnJMh9szv+Jw8W4amhLHMfu3I0vPnMRn7D4LT1O+IQp1tneEUbU7zbWKHpaJ59brR3HDw7A53U5xt22c4nJ73/q3UU92Plsc7pKc2kjsWo17Np96t6lmMl8rRl+2am+jeDzt3eEMdhXtGOrne3qjpTYlq4nRZVx8lC5DTutA5zs2ONGRbs7ur+/bO7d3hFGNGA/hvQYtivqd1x/6/GEPj6PHxxANOhuqK/t/IY1ztLHWCVqHX/1rrtXGr0vnPZZdBlPHhpETi443tf7Qv93e2fYVh96P1n3aKy2a12fWH2m+Z4eB+p7MHo5X1yMt9eKrjcajJu38G8AGGM/A+B/AHAD+EvO+R84pd27dy8/d66xB5X1kxrnBQletwsa51A1YDYrYUtbEAGPG9fzMrxuF3Kyapz8fi0rIhFb+t4dLZ6EqSgankumkS8oUDVAVuxPfLfWm5NV9MQC2NoWwsT1HKbTEnKygh2dYaRyBcznJHRGAsjLKtJSAZ1hPyRFQ0FVEfV7IWsagl43pIIGhWvwuBgKKkdWUrAp6AMHh89Uj/nUTv2k4FSuAA6OfEFDVlKQiBXrmxUk7OgIQdGA6/kCxIKKmzvD4GCOerCehDmTKabjHJgXZCi8+GcGisohK1rxhHS+VMbmaKB4MnBaRN+mIMJ+DwSpAGWxb3rjAQz0xo2T22cyS3UDMHQbWNSJqKiQFQ1bLScs623X9W29bzXLhozMhJ2t6qemJlMiEovtqvSi9lxexmgyY5xuO5iIOh4st5w8+XwBF5JpI89QIlbx8LF0XjROpe6J+fG6RNjxMDod/XRmo44aTmeuN08jdQh5CWPJrJFnIBFxPIyu0Xqu50W8ZNJXtVOKgaUTffVTYIc3x+0Oo1sRO63XHqyYT8UN+dwoqBraF0+3tRtvsqzi+WQaKbGAvKyid1MAsYC3bKwCMHxAbzyA60IBeaUAF3NjJl08ZZczDZ2hAMCWfNa8IGMmIyHs98DnZvB7XFA0jum0hI6ID70xP1J5BVMVxqV17N7aE8NEKm/4O0XleG0hh9DiidFbNoVweT6HK/MCQj4PEnE/FNXed1bSX9jnRkHlyMkKIn7P4unFS6c6m3VSyT9by78yL2AuKzv6yyazInZqRrfZmbSE7pgfHhfDppCveHpyMo3JVB6dYT964sWTtvUTv5MpEds7g8iIGpJpET3R4unZkykRm2N+SCo3xkHY58ZrC3lsjgegahyT18Wa/Uw17OYGuznPafzovqI76ofHzRAP+srSm+dovTyzHsx2LasKRElDRlKLp1SHfbieL6At5DN8kX5i+9WUiKykIBbwIOB1oz3ssz0xfZ2wLKEr2SljDO/5s2fqLvORX72D8m3QfBXWe023U7t5Jy0WHOcGa4yyuyeEF5ICZhb9JQfHXLaAzogPA4txqD73XMtIKKgq/B4P5gUZkYAH+UJxDTPYWxrraBrHlbksptIS5gQZPdHKPlfTOF6dFXBlXkDE74HHxTCZEtER9qEt5MGurljFuDufLxTXJBkJnREf/B4X5rIytneEsbMrYuihxGfHAtgU9mIqVX1+BxqLVath598B1DSHNKs+m7JXfO5vBfrcl0yLyIgqQj4XNoV8uDVRblu6nrweBVPX1ZrXAWY71uPKre2WOTsWQDzkxauzpWnsDjp+bUHAdErCrCChLx5Ef1cYY4trxb5NAfg8LsznCgA0+N0eXMtK6IoWn/bnYLielxHze40YqlE70v2GHm8FvC4s5AolcW0tZdc6/mpcd6+anep9MZeRIcgK8gUNbWEPwBlmMhLawz60hz0QJA0ZSYEka+iK+qDx4p5ILOhFQVUR9HqwkC8g6vegLeyBpgGCpGImU1zXJGKBElsw+/dowAOxoGJeKCDkcyPsd0PTUOzziB8qL77CpDPih6qpYHAZcaBsWs8Bpf5lSzyI56fTNe9xEHXjaKc33OZwPazFSYK4IbkhAxrihoPslFgPkJ0S6wXaHKZ8aybfam4OE8QKQHM/sR4gOyXWA452SlvwBEEQBEEQBEEQBEEQBEEQG5A18+QwY+wPOee/t8p1XgNw2eF2J4DZVRTHCZJjbckA1C/HLOf87uVUWMVW62Wt6NEKyVUfzZZrpe201XpsZf0bue3Nrn8l7bTVeqqX9STvRpR1Wba6xv2pGZLFnvUiy0raaaOsFd2tBTnWggxA6+VYrbVUq9tpx1qUCSC57Fhra/5aaXVf0hptdXG005ZsDjPGPmO9BOAXAXwJADjn96+6UBYYY+c453tJjrUjx1qQYS3J0ShrVX6Sqz7WqlxOtFreVta/kdu+FuqvlfUip856kpdkbS5rSUaSxR6SpXHWirxrQY61IMNakmOlWYvtXIsyASTXjUSrdUZrtLVjr8t7Y33jvAvAtwF8HUvvvPgFAD9skTwEQRAEQRAEQRAEQRAEQRAbila9c/g2FB+fvhvANzjnXwSQ4Zx/cfE7QRAEQRAEQRAEQRAEQRAEsYK05MlhznkGwG8xxn4MwN8yxv4Ba+9wvD9vtQCLkBxLrAUZgLUjR6OsVflJrvpYq3I50Wp5W1n/Rm77Wqi/VtaLnDrrSV6StbmsJRlJFntIlsZZK/KuBTnWggzA2pFjpVmL7VyLMgEk141Eq3VGa7Q1QssPpGOMMQC/AeDNnPP/2FJhCIIgCIIgCIIgCIIgCIIgNgitOpBuK+f8isO9n+Kc/8tqy0QQBEEQBEEQBEEQBEEQBLGRaNWrHL7FGPtdxphbv8AY62GM/Q2AT7dIJoIgCIIgCIIgCIIgCIIgiA1DqzaHfwzAzQCeZYztY4wdBfBvAL4H4MdbJBNBEARBEARBEARBEARBEMSGoaXvHF7cFP40gKsA3sQ5n2iZMARBEARBEARBEARBEARBEBuIljw5zBjbxBj7MwC/DOBuAH8P4GuMsX2tkIcgCIIgCIIgCIIgCIIgCGKj0aoD6S4C+BMA/4Nzrixe27N47TLn/L2rLhRBEARBEARBEARBEARBEMQGolWbw1ucXiHBGPsvnPO/WG2ZCIIgCIIgCIIgCIIgCIIgNhItfecwQRAEQRAEQRAEQRAEQRAE0Rpa8s5hgiAIgiAIgiAIgiAIgiAIorXQ5jBBEARBEARBEARBEARBEMQGhDaHCYIgCIIgCIIgCIIgCIIgNiC0OUwQBEEQBEEQBEEQBEEQBLEBoc1hgiAIgiAIgiAIgiAIgiCIDQhtDhMEQRAEQRAEQRAEQRAEQWxAaHOYIAiCIAiCIAiCIAiCIAhiA0KbwwRBEARBEARBEARBEARBEBsQ2hwmCIIgCIIgCIIgCIIgCILYgNDmMEEQBEEQBEEQBEEQBEEQxAaENocJgiAIgiAIgiAIgiAIgiA2ILQ5TBAEQRAEQRAEQRAEQRAEsQGhzWGCIAiCIAiCIAiCIAiCIIgNCG0OEwRBEARBEARBEARBEARBbEA29Obw3XffzQHQhz4r/Vk2ZKv0WYXPsiE7pc8qfJYN2Sl9VumzLMhO6bNKn2VBdkqfVfosG7JV+qzCZ9mQndJnFT6ObOjN4dnZ2VaLQBA1QbZKrAfITon1ANkpsR4gOyXWA2SnxHqBbJVYD5CdEq1kQ28OEwRBEARBEARBEARBEARBbFRoc5ggCIIgCIIgCIIgCIIgCGID4mm1AOsdTeO4NCdgOi2iJxbA9o4wXC7WarEIgrhBIZ+zspB+CaL50LhqDqRHgiAIYiWg+WVjQ/1PALQ5vCw0jeOpsSSOPfosxIKGgNeFU/fuwd0DCRpMBEE0HfI5KwvplyCaD42r5kB6JAiCIFYCml82NtT/hA69VmIZXJoTjEEEAGJBw7FHn8WlOaHFkhEEcSNCPmdlIf0SRPOhcdUcSI8EQRDESkDzy8aG+p/Qoc3hZTCdFo1BpCMWNMxkxBZJRBDEjQz5nJWF9EsQzYfGVXMgPRIEQRArAc0vGxvqf0KHNoeXQU8sgIC3VIUBrwvd0UCLJCII4kaGfM7KQvoliOZD46o5kB4JgiCIlYDml40N9T+hQ5vDy2B7Rxin7t1jDCb9/SzbO8ItlowgiBsR8jkrC+mXIJoPjavmQHokCIIgVgKaXzY21P+EDh1ItwxcLoa7BxJ43f0/hZmMiO4onexIEMTKQT5nZSH9EkTzoXHVHEiPBEEQxEpA88vGhvqf0KHN4WXicjHs7IpgZ1ek1aIQBLEBIJ+zspB+CaL50LhqDqRHgiAIYiWg+WVjQ/1PAPRaCYIgCIIgCIIgCIIgCIIgiA0JbQ4TBEEQBEEQBEEQBEEQBEFsQGhzmCAIgiAIgiAIgiAIgiAIYgNCm8MEQRAEQRAEQRAEQRAEQRAbENocJgiCIAiCIAiCIAiCIAiC2IDQ5jBBEARBEARBEARBEARBEMQGhDaHCYIgCIIgCIIgCIIgCIIgNiC0OUwQBEEQBEEQBEEQBEEQBLEBoc1hgiAIgiAIgiAIgiAIgiCIDQhtDhMEQRAEQRAEQRAEQRAEQWxAaHOYIAiCIAiCIAiCIAiCIAhiA0KbwwRBEARBEARBEARBEARBEBsQ2hwmCIIgCIIgCIIgCIIgCILYgNDmMEEQBEEQBEEQBEEQBEEQxAbE02oBiPWPpnFcmhMwnRbREwtge0cYLhdrtVgEsS6g8dMaSO8E4QyNj7UJ9QtBEATRbGhuIVYasrH1QUs2hxljNwH4EoAeABzAn3POH2aMfRzAfwFwbTHp73HO/9Em/90AHgbgBvAFzvl/W7y+A8CXAXQA+CGAX+ScyyvcnA2NpnE8NZbEsUefhVjQEPC6cOrePbh7IEEDniCqQOOnNZDeCcIZGh9rE+oXgiAIotnQ3EKsNGRj64dWvVZCAfBRzvltAN4E4EOMsdsW732ac75n8WO3MewG8HkA7wRwG4D3mvJ+cjH/LgALAP7zSjdko3NpTjAGOgCIBQ3HHn0Wl+aEFktGEGsfGj+tgfROEM7Q+FibUL8QBEEQzYbmFmKlIRtbP7Rkc5hzPsU5/9Hi9wyA5wH01Zj9xwG8zDm/uPhU8JcBHGaMMQD7APz9YrovAjjSVMGJMqbTojHQdcSChpmM2CKJCGL9QOOnNZDeCcIZGh9rE+oXgiAIotnQ3EKsNGRj64eWH0jHGNsO4A0A/nXx0ocZYyOMsb9kjLXZZOkD8Jrp98TitQ4A1znniuU6sYL0xAIIeEvNKOB1oTsaaJFEBLF+oPHTGkjvBOEMjY+1CfULQRAE0WxobiFWGrKx9UNLN4cZYxEAjwH4Lc55GsD/BHAzgD0ApgB8agXq/BXG2DnG2Llr165Vz0BUZHtHGKfu3WMMeP0dMts7wi2WbAlN47h4LYvvvTKLi9ey0DTeapFqgmz1xqeR8bPW7Hk92ul68FutZq3Z2XJZj3baCjSNg3Pgj3/+9Ti6fxd64wEaH6tIJTvd3hHG5973Bty/fxc+vG8Xju7fhc+97w3UL8SqQ/6UWC+QrTqjx3nTaRF/8Yt7sa0jCIBi4lZwo9ip09qB1l3rB8Z5axZ8jDEvgCcB/BPn/JTN/e0AnuScD1quvxnAxznnP734+/9dvPXfUDzILsE5V6zp7Ni7dy8/d+5cU9qzkdFPn5zJiOiOrq3TJ9fIC9CXXRHZ6o1LPeNnhe15Q9npWvZbrWaN+E0nNpSdriZ2/f6H7xrC7Vs3YWs7jY8GWJbCrHa6xsclsX5pqp0SxApBc38TsZtPPvlzw+jbFEB72E8xceNsWDutFqPQumtN4aj4ljw5vPh+4P8F4HnzxjBjrNeU7F0ARm2y/wBAP2NsB2PMB+AXAJzmxV3ufwbw84vp/hOAJ1ZCfqIUl4thZ1cEb9rZiZ1dkTU10OkF6MRap57xQ/bcPNay32o1ZGcbE7t+/73/ewEaB42PNQCNS4IgCKIZ2M0nH3tsBO1hP8XERENUi1Fo3bU+aNVrJf4DgF8EsI8x9uzi52cA/BFj7AJjbATA2wF8BAAYY5sZY/8IAIvvFP4wgH9C8SC7RznnY4vlfgzAMcbYyyi+g/h/rWqriDUHvQCduJEgeyZWA7KzjQn1+9qG+ocgCIJoBjSfEM2GbOrGwNOKSjnn34X948z/6JD+KoCfMf3+R7u0nPOLAH68SWISNwD6C9DNzopegE6sV8ieidWA7GxjQv2+tqH+IQiCIJoBzSdEsyGbujFo6YF0BLHS0AvQiRsJsmdiNSA725hQv69tqH8IgiCIZkDzCdFsyKZuDFry5DBBrBYuF8PdAwm87v6fohegE+sesmdiNSA725hQv69tqH8IgiCIZkDzCdFsyKZuDGhzmLjh0V+AvrMr0mpRCGLZkD0TqwHZ2caE+n1tQ/1DEARBNAOaT4hmQza1/qHXShAEQRAEQRAEQRAEQRAEQWxAaHOYIAiCIAiCIAiCIAiCIAhiA0KvlagBTeO4NCdgOi2iJ3ZjvT9lrbdtLcm3lmRphPUu/41Kvf2iKBrGplKYSonojQcx0BuDx0P/z9comsZxeU7A1VQeGVFBR9iH7pgfN7XR+CCah6JoeCGZxnxORr6gYnM8iFsTNHYJwowoKrgwlUIyLSER82OoN45AgJYqBEEQ6x3y7+sT8zo15PMgLcrwud1IxP1QVGAmQ/sKNxI0IqugaRxPjSVx7NFnIRY04+TFuwcS634ArPW2rSX51pIsjbDe5b9RqbdfFEXD4+cn8cDjo0b6h44M4sjr+2iTqQE0jePpF6cxPp3Fw2fHDZ2eODSAS3EBP7Wrm8YHsWwURcPXxqYwsZAvsbM/eNcQDg9vprFLEChuHJy+MIUHTy/NbycPDeLQUC9tIBAEQaxjyL+vT+zWqffv68cj567g1966C3/67ZdxeS5P+wo3ELQiqcKlOcEYEAAgFjQce/RZXJoTWizZ8lnrbVtL8q0lWRphvct/o1Jvv4xNpYyNYT39A4+PYmwqtWoy30hcmhMwMpEyNuyAok6Pnx5DJq/S+CCawthUCuMz2TI7+6//9wKNXYJY5MJUytg4AIpj5MHTo7hAY4QgCGJdQ/59fWK3Tv3M0+M4MNyHE2fGcGC4z7hO+wo3BrQ5XIXptGgMCB2xoGEmI7ZIouax1tvWqHyaxnHxWhbfe2UWF69loWm8ZbKsFVZT/pXQ/41Kvf0ylbJPn0ytDztca0ynRWgctjoVZGXdjG8naCy2Fl3/ry3k0RcP0tgliAok05LtGJlOS1Xzkq8jCIJYuzj595lMdf9ONJd65kundSpjS/+ar6/3dRNBr5WoSk8sgIDXVTIwAl4XuqOBFkrVHNZ62xqRb6Ven7DWdVWN1ZKfXl9RH/X2S288aJs+EV8fdrjW6IkF4Gaw1WnY51k349sOGoutxar/o/t30dgliAokYn7bMdIT81fMR76OIAhibePk30N+DzSNk69eJeqdL53WqZwv/Wu+vp7XTUQRenK4Cts7wjh17x4EvEVV6YNoe0d4RetdjacgWtW2WqlVPrOuLkxer/nP9GvVsaZxuBjwh+8aWrO6qsZq9XUjr6/YyE/81NsvA70xPHRksCT9Q0cGMdAbXzWZbyS2d4QxtCWOo/v7S3R64tAAokF3xfEhyyrOXZrHkyNX8YNX5zAysbCm7JdeJdNarswVbeHEwQF89r1vwMhr18vs7A/eNURjlyAWGeqN285vQ1XGCPk6giCItc1Qb7xsHf3bd92Cj58eJV+9itQ7X9qtU+/f148nRyZx/OAA/vXiNXzo7btw//5d+OIH3ogFQcZTo1M4/9p1KIpmWyaxtqEnh6vgcjHcPZDA6+7/KcxkRHRHV/40xtV6CqIVbauHWuSz6ur+/bsc/0x/Z1fEMZ+Tjs3p2kI+/MpbdmJ3TxS3JmLY0bl2dFWN1eprpz8/mU6X6l+HnvgBfB6GX3nLTmgccLHibydcLoZNIW9J+k0h74bRVbNxuRj23dKDmzsjGN4SR0ZU0BH2oTvmx01tzuNDllU8PnIVDz6xdLDGiUMDOPv8FI68YeuasN9KryyxG4tE8xBFBf926XrJwSvHDwzg62NT+PNf/DGIsobEJj9uS8TpMDqCMOFzu0rnQ3f18UG+jiAIYu3jcZWudzrCPsQDXvLVq0i986V5/2A6LSLkdSMjFfBj216P3k1+hLxufOyrI9jdHUFvPIgTZ8bowPR1zrI3hxlj2wD0c86/yRgLAvBwzjPLF611KIqGsakUplIieuNBDPTGsLMrUtVxaRrHpTkB02kRPTH7zbda0jj9r87r7v+ppjtPl4tVbFst8q4k1eSz6krj9n8ibv0zh1p1bE43lRLxmbMvI+B14R/v/6mWb/40Cq/jwcZ6+z/k89j/2ZDPbZt+NW19LXJpTsCH/+7fy/T1jw7trze9TqvH8VqHMcDtcsHFGAqahoyoVPwzt5GrKWNjGFg6xO7PfvHH8Kt//cM1Yb/LeZUM2UtlNI3jylwWU2kJc1kZibgfg4m4ceK23cErJ54cwx///OuxpS3UctsgiLXIhakUfvexkTKf1fuBH8cbd3Q45iNfRxAEsbZx8u9//POvr/q6yEtzAq7nZCgax0xaQk/Mj6HepZiLqJ1G5kt9L2Z7RxiX5gTkCiq6on4UFOBjXy326QffcjN+9+/Plx2Yvr0jjNu3tgGAMdeGfB7IqoqOsN9xzqW5uXUsa1Qxxv4LgF8B0A7gZgBbAPwpgP3LF601KIqGx89P4oHHR+v6n49anoCs9SnJev9XZ6UGkJ28n3vfG7CjI4KZzMoM1nrbYtXVYz+cwP37+vGZp8dLdGz98/BadXyjPJHSyBO6msbx9IvTGJlIQeOAmwFDW+LYd0uP8xOVqlqm//v39aOg2v9pyY2iX53l2i9Q+UnretPrMm30p7Od0G18fDqLh88u2eyxO3fj1VkB7xzotfX7SYd+SOcV/NY7+jEvSC23X/1Pwaz9XulVGZrG8eqsgOen0hifyeDRcxNYyMlkLygd2y4GXJrL4fjppSckTh4axKGhXgQCHseDVzh43a/ysfqUrW0hXFnIUcBMrAp2D0us1FNAjR5I1xvx4+ShwZIn9U8eGkRvZO29q5gWvARBrFVWMt6oJy4yy6GoHH/9/Yt4+y29OPGkfcxF1I7d2uCTPzeMrW0h2/TWvnjgiQu4PJc3Nvb1Ps1Lim3/XryWxfW8DFnhJXXev68fj5y7go/dfWvFv9qmdevqs9wR9SEAPw7gXwGAcz7OGOtetlQtZGwqZWwMA0v/89HfHcHrb2pzzFfLE5C1PiVZz//qrOQAssrbFvJhfDprPLnY7MHaSFusuppKiXjk3BU88itvQr6gOr4+oVYdr/eD6HQaeUL3yryA8eks/vw7F43+OLq/H7u6ItjeaZ+nI+zHI+eu4D//5E4wVnxK+ZFzV3D3YMI2/Y2iX6Ax+w377Z+0Djs8aV3vk9kAPZ1diUtzAkYmUoaNA0X9nPrGS/iVt+zE1vaUrd/vdbDbeNCDiQVgNiu3/ICNel8lY2e/9+/rx19///KGtxe71xdZbebB06PY0RnCG3d0OB68kogF6rIJa73bOoL4zX39Jf95TQEzsVI0+rBEozR6IN1oMo3Pf2u8JO74/LfGjfHoxGrPjbTgJQhirWLnnx46MojPPj1ubAYux1/VGhfZP5h2Oz78dz9yjLmI2nG5GO66tQd//ot7ce7yPFQNOPWNF+F1u2rapNXXBVMpEeMzGaNPQw7r2YDPY7vO+szTxTm72l9t6+k3+jpkNVludCdxzmX9B2PMA2BtnMbTIFMp+yfCkimxYr5KT0DWkkbTOC7NZvGvF+cweT2HT/7ccE2HVK3kQRxWee+5fYvxdB1Q3CyemBfwvYuzePqFabwys7zDmBppi92L0j92960Y6tuEN+3sxM6uiO0kVutBYGv90L5aqcU+y/NIJf0tFjQ8fHa84lM82zvC+Njdt+J/ffciPvf0y/hf372Ij919q6O+1rJ+FUXD+dcWan6x/qU5AZ986nn85yLmbzcAAQAASURBVP+PvS+Pj6K8/3/P3vdms7kTsklIQu5ACIcWUIkiWg7lEGvFC5ufVoV6V1uloNWiiBWxtXhVsCpavLBKraAiX0AMKGcCCYGEhNzHbvY+Zn5/7M5kZndmkyzh0n2/Xn1VNjs7z8w88zyf5/28P+/PpCzcPTUbt0/OworN1WH7r8dLhhSpWlKRA4+P/z2ildnBhQGElNlAZM/+QobXS+JQcy++re3A5oMt2B/m2bVZnCAp8N4fkoLguF+cosfy2dzCSctmFeKN7cfxwpZaHG6xnBcFNuhUsHBjIQ2+8Xf11lrMKUv7SfeXwYDPviicwrE4WY/ls7j9Y/ks/sJaTqcX3x/vwqZ9/sKGTqdX8LwzSlJDNq+jhbd+XgjXX4YbQmKJQy3mM3K+obw3bLRaXGjocuClr+qwZmsdXvqqDg1djgEVx2d7bowWzosiiijOV/CNT3/86CBmlKQy/xYarwYzLw12fOdrx/6m3oiySqLgR2OPHZXrq7B6S/98yfdsw60LAOC9qiamyOAr245h6czCkOcrEwGj02JgUMk4v+30kEiPVeL2yVnotnGf489t3Xq+4XSVw98QBPEoACVBEFcA+C2ATaffrHOHZL2Sf2dLH17JOBgFpNB3knSKkNRmk1GJtQvLIRUTYVM5hiMtXyjNLbi9BNG/IE7WK3DHlCzYPT4serNqWFQQkVxLpIXWBnvc+V60b7CIRKFrc/OniNjd4RejQy2wdrbu71DSOSNRTHXZXFhQnh5iqRHOYsDs9GDdzgaO4mndzgbkJWl5vz9UZTbw01JnDwSvl8Tnh1rQ1OPg2EQEPzu6Lzg8PuQlaXnvj4iA4Lgvk4lxTUkKMmJVaLE4EaOS4p/bj+Oro53+36dwwVmjCI2/BPHT7S/hwLWRIGBQydDC2iwIp3BUKCSYVZyMzDgV2sL44zmdXnxyoCUkHZ5OlQx+Juw5mPmNIc73UVy4GKi/DDfCiSVKRwz76Qb93gQjUsXx2Z4b2yxOGFQyzClLAxEIPTbuaYq+v1FEEcU5R7gYkP3v4PFqsPPSYMd3vnFSLhFFNMZHwY/Ttdakn0uP3Y2xphj8/cax+KGxBx6vD89fNxoeHwmDSoYXthxBVYOZET6t29nAxNEKqQiN3Q68tr0eOQkalLGyLem5md0PxASQpPt5rUPOFU43mvw9gEUADgD4fwA+A/Dq6TbqXKIwWYcnrykKIYUKBZQL9AKyy+bCirkleDhgts6ngBTygPSRCJHcN3Q5ULm+asBCU6cb3IZLcwtur5joXxDPKUtDl90dkiZwOrL/SK+Fr2jdYIjAgYrdDfV75zMi8R81xaphMioxoySVmQg27WtGeqzwMZEUTDsb93eo6ZyR2MvIxCKGGKaPWb21FhsqJwq2yxSrRo/djZe+qmM+U0hFgveYVmYP5TlG8uzPJwyF1D/UYkZtuzVkXGI/O75U/aUzCzkVdu+7IhfJegUz7vO1QSYTI04rx01v7OYlli80MlVo/BURuKD6y3CAb7xgB7Yb9zRhSUUOZwMiWAGjUEgGTHfkK1zHTpVkP5NkvQKjErVYXJENkvKTSi1m58+SuP+5YqD+MtxI1it5Y4CBxBKng8G8N8GgFWnB5MRAiuPTmRsj8Q5O1itw00UmzrixpCInuuCNIooozjmS9QomvgD8MUaP3c0pYs4XbwxlXhrM+M43Tj56VV4INzOYMT4KfpyutaZaJsbiimzkJmjRa/fiT58cREOXg/kOn/XaC1tqUTklC6u31HHsKZweEg9v3I/iVD3DA2QY1fjHwjI09TjxxKeHmWc+KkmH9NgLT6B3oeG0yGGKokgArwT+95OARCLCNaWpyEnQoNXsRFKAIOBTC/KRDOHUvkIqye+OdwmmqQ6kKDhd4mcgXxd2e5N0CoxK0uG+934EQQin1kaqghguEutM+7qdLwVFhtqOoSh6AcAUqwrxt3zymiKYYvlN64Hzt8DcUP2LIlFM2d0+AaW1T7BdmXH8fT4zjr/PR6K0vpDV70N9l1vMwjYR9LML7gsNXQ68/E0d1t06Hr0OD9RyMfRKKfIS/YWXhrKBRi/2cxI15x2ZOtB4wXctT11bjLL0mJ9dMNbQZUNNqwW3T84C4F8ksQPbHrsbmXFqrLt1PNqtLiRqI6ucPVABLvqZrNhcjQXl6XgwUAmaDqzpYh7nW1+L4swg0oJtkSI/UYu7LsvB4x+zFuSzi5CfqDsj54sUkSqOI50bI40xfSR4rbqmFQhn/rDPeT7EnVFEEcVPDyRJ4XBLX0iNmTSDEiu/OAJA2PZvOOclkqRgtnvg8Phw++QsZhP8qc9r8I8by/DPW8ej8zRirij8GCzfwve9vy4YDbvbh0c/PMCJR9fvagDgtyBN1Ss5zw/w94lUvRJrbhiD6pY+xreY/lswT0BAxBDD9HeivsNnBxG9VQRBHEAYb2GKokoibtE5BklSaOyxw+72ISdRGzYA4yMZBlL7ikQE8/K1WfwvRYJWwVHl0hisajZS4ocONsORebSqM8OoxokuG+K1MmyonAinh8SOY50hbTYZlVBKxdh5rHPIAWwkBZQau21os7hgc3thilUjM049KCIwXKAt9LsiEXHeFBQZajsiUfQ29th51bNl6QbBYyJRf0ey6BlqBfWhpnNGYi+TqFPwqqwSw6iC6MIAGyoncq5lILJ3qErrC0X9HtwXKAq87/KoeyZDLALzjmYa1SApQCwikJekhcmo5Oxis58d3wZGQ5cDJChMKwxdpLO9pOnnumJzNfKStMwG2qh7JqPFbIdMLIbN7Q2rrhe61jO52BcaLwqStYF+p4CPBAwqKTZUXgSPz4dYtXzY23S+Exxutw/VbRaO+pwOfOvaLPjFyDjkJGiRqJOjKEkLlVI28I+GwWDS4UclavHUtcWMfRPAzUooTo05r+5hFGcOkdonRIoms4MhhoGAIuzjgyg3CccAp4tIx4hIFMdAZHNjpMVy2vv4N507rE6MTBA+7nTiTpvDhUOtVoY0L0zSQK2MpmJHEUUU/eAb017YUotNd0/CG7eMD7smP915yen04kCLGd12D+wuLx5hkY5PXlOE/+w7ha+OduL7hl5s2teM1dePgd3tw6k+JzJk51cMeaFAiG8BgPoOK2f+Df4eRQG/fPHbkHh0SUUOKAoh1oo0CayQimBQyxCvlYGigD9fUwQKFJp7HOi0uaGUSphC3o3dNrSYHQOKzc73NcWFiki3XGYE/v+uwP+vD/z/jbiAC9IJBWDT8hPR2GMP6XyRqCT5q3COQXGaPiRNdbCq2UiCW7odR1otgj7I9ACRrFfgcEvfgG2mK6kvWLsLBpUM88vTkJugRX6yDqZYFe89jPRaSJIK8Wmm75lBJWXScG+6yIQ0gwp2lxddVhdzP4UCbQCCvzu9MOm8qaB5vJO/HaPumcy7yIikr0ZyTJpeieWzi0KURml6Je/3I1n0ROIHPNR0zvxELe91hFNMpRtUeGDaKNS2W/1EJQE8MG0U0g3CSmuSpPDfw224//3+639u/mhcVTS8mw3nywTKtuGRiUWwu31Me4DQ93LlvFLePljTZkFjlx0vbKmFQSULebZLZxbi5W/qmArLT15TBJ1CCpKkhryBMZCXtEhEIDNOjSNtfbjvvT2D6sdnY5OJ/cxVMjHveFE5JQtf17Rjwfh0TurWU9cWI04jF/y9SPrQ+bKxJgS324eP95/CyR47b1Xl124eh/871gmSAlZ+UYP7rxiFzHgVmnv8mzr5iVo0mR1Duj/h0uHZ9+v2yVm874HD4zsv7l0UZweR2idECqEYoM1yZjKBTmeMcLt92H/KjFaLE8k6BYpT9JDJxMPeRiDyDKlEnQLlJj1uujgLDpcXKrkEb+6oH1AEMtR4j4bN4cJ/DraH9JdfFiVECeIoooiCgdCYdqStD1cXJYcd14YyL7HjyGS9Am4vieqWPtR3WqFVSLDyi6MhgqSXbihDn8uDEXo5/nxNMY532hGrlmJHXQeqWywoTIlaDUSCYPHfnsZunOp1htijTi9M4vAyO4918vaVEQYVHghkt9Gfrd5ai0WTsvDa9no8Mj0PrWYHFr/7A3cdHhDubKlpQ4/dDZ1CAovTC7PdHXatdr6vKS5kREQOUxTVAAAEQVxBUdQY1p8eJghiL/xexBcc+Ii/FZur4fGRIS/LtPxEeH1UWMNsvsU03znufvsHbF4yGdnxGpSlG+Dx+aCVS2H3+HCiyxayyBxI2TqYBTzdDoNKhsVTczjEx5obxnDI4IenjwpJhQtus93tRaxKhgWv+InhhRNNzG/SpDFN5pmMSjwxuzhssb3gCcRHAt12F5RSMWwuH7wkGeLTTAfMGyovgsmoxG0XZ8Lu8XFScVddNxqjErXMtc8pS4NWIQZJUvjmaDti1TLB381bPPm8KSjSIKD4buy28S4WErT8qtZ4TXgl7FBVwNVtFrz3fQOemVfKWfyMSuT36o1k0ROJH7CPBN79vpGj/nz3+0bBdM4mswMvfVXLKfz20le1YRVTTb12ONxe5CZoYXN5oVZIYHd50NRrR0Yc/zH1HVaGGKav5f73f8SoxEnITuQvSjdU1fT5MoHS7aBT5NljDq1iDe4Lte19vH2QYqXnzilLCxmflm06hDduGYceuwcNXTY898VR9NjdzNgdLp0qeHzVK6TYUNXIGS/SYlTotLqx+3gXErRy+Eh+hbPQptGZ3mQKfuaLK7J5x4tMoxrjrszD9w3dnBSwRz88gMopWchL0jGbZqfbh86XjTUh7D9lxmMfHwwhYpP1Cr/Hvs2FcpMBb+06jtsuzkSrxYmHWHHB8tlFeOmrWmZDYjD3J1w6fH2HlXO/Tqe2QBQ/DURqnxApVDIJb79TSc8M6RrpGOF2+7DjeCdEBAGvj4LN7cWO4524ODPujBDECVr+2ChcPAX4N8+vG2fCQ6yYNNzmOY2G7qHFezQOtVp5vUAz4sZjfGaUHI4iiij8EFrvHW3rQ0GyLuz4O9h5iR2X8ok6hMQg+5p68diMQjg8fnu4WLUUb+06jsvykmFzefDFoVakxaqjpGAEYD8TmsTlm39p/qrN4oRMzF8cUCQiGGEemyMpStHh+QWjIRcT+C0rg9np6fchLkjS4fFPDvv7wfxSaOQSpBvVeOOWcTjQ1AuLy4dN+5px3xV+wVV9hxUdfa7zek1xIeN0I0qCIIhfUBT1f4F/XAxAmKU4z8G3czajJJUhhgE2ATkRf/z4AB6Znge7x8cZ4EYl6ZAWo8IX1W0hi2la1cqG00Oi1eLExKw4pMeqsflQK25fF6pAA4DGbhsOnbKgsdseomydlp/IOWc4Epa+1hazE+t3NTAk2OTsOMRp5Pjli98yg3eSXhHSZoNKhi6rG16SYghqOmVuTlkapzDXjJJUhsxL1iuwoDwdleureK+PVhXSu1d0G979vpEhe1/YUst4QfLdS4/PhydmF6OqoZuX5P3br8sYAntDVSMWlKczu10PTMsN66V8vhQUUUj5B2eZAEkoEQO/vTQbSz/pL7q1bFYhJGHWTZF4QHfZXJial8RZ/NAqSz5EsugRVjMJ+1t12wXUn3YXRiL0PK1mJxq6HJxCcfS5hSYds90DH0UwfYlWsJrtHsF2Cdm6nOiy8ZLDkaimB7JFOFugF/6LJmWFFO67770f8eat40PuxVc17fjztcX4AyvN7Klri9HUa2e+SxD876vT4+MEDoCfwP1s8WRB+xqhjIR7L8+FQiLC6zuOc8YLhVSEP80shFEjExwz+O6xUB9u4NkMjASN3VzP3AQNf9qfVinFb1hjMTsFjAxYeuQtnszcu9MJws5XP3Iaraz20fcqWa/gbHTS46aYoPD0xzVc0uXjg3h2XimOtPVh456mQd8foXR49v3auKcpZBP351YkMAo/IrVPiAQWpzuk3y2emoM+l/CcdjqIVKl8vLsPbRZXSHxzvLsPo5Jihr2dYhFCMv2WVORAPMDqp7rNwmvTIbR5TkMtRNLLwi/h2vv4vUA7+s6MR3UUUURxYSLDqMZT1xbz+shePNIYcRzDBnvzj0/UAQF7TaVUjKNtVjzGyuRcNqsQW6pbcOPETChlUhxptaAgWSsoxImCH+xnIrSWarM4UdPaLxh89KpRIXHBYzMKoFNIYDIqQ9baj80owNptx3Dv5aN4f5+kAIfXh+SAgvhkEL917+W52LSvGYsrcnFlXj/PJZRRd76sKS5knC45vAjA6wRB6AEQAHoA3HbarTpHCN45S9YrkB6r5CVGWwLkUZ/LizVf1fGSx3yL6Q2VF4VVAAkpJwqWTEZdhxVON4mj7X7TeINKhjsvyYIpTo1emwc/nOxhjg1HwopEhKCSdM6YVEYdu3CiCQ6PDyc6bSH35c5LsrD7RDeT1j2/PA3lJgMUUlHIAMP+dzBxzL4+Wq3M3r2iJ5BFk7LQZXdzyF4hn+ZYtRweH39hKoNKBo1cgvnlaUy6A7s9JqMadQJqxQSt4rQKigwnJGKCd3EiEfOTSuyFE+Bv99JPDmH9beNhMgr7Yw/Vz1qnkIU839Vba/HWogm8349k0WNQyXiPMaikgscQIIbULrlExPt+SMOs/uweH5Zt4t5jWsEqBLWc//rVcv7rPyygms5N0KBEYHE5kC3C2QK98BcKQOxuLycTQy4RISdRg9e+PYZFk7IgFgFjRsRgZIIaG/c0c+6bUB8KFzjw2dec6LLxZg48/+VRVE7JwoyS1JB+9KdNh7B24VjBMYMv00NIefbDyV44PORpKSBIksLexl7mGkxGJe6fNipkvHh8RgGe+PRQyDtBj78U1X+/qEEUHx0oayWSTISzieRA+9hELN98tfSTQ/jnreOZOICG0+NPwXz123rce3ku/rnjxGkFqez7RW/iVk7JwpgRMTAZ1VFvtSjOOOQSMTZUNXIyaDZUNWJcRukZOZ+gUnkA9W+v3ccb37x56/gBzxmJXU6L2Ynd9V34x8Kx6LF5EKuW4o3txzEmPSYsOSFU6LYlTKFbAEjQyHjjvXhNeM/zBC3/pmC8NqoajiKKKPohEhEoS49hipZTFLB+VwN67O5hi9HYm39yiShkLGzqsePxGQVYzrI4Wzw1BwAYYhjoH9/XLhyLVrMTD208AIVUBJNRjbQYVdhMyii4CN6QFZp/b/3n98zntIr37suykaRToLHHjjVb65AaI8fSmYX47b/2cp7VE58exqJJWTjeaeVXHBP+LOI5ZWkAQjmW5788ikWTsvCHDw8gw6hCTasFv7s8B/nJOiyuyAZJgcl6PJ/WFBcyTusNoihqD0VRpQBKAZRQFDWaoqi9Ax1HEMQIgiC+IgjiMEEQhwiCWBL09/sJgqAIgogTOH4FQRAHA/9bwPq8giCIvQRB/EgQxHaCILKHcj20UtJkVOLh6aNw99RsnOr1p4jSoJWj1S0Br14vKRjs8X3u8fmw6rrRzG8GK4CElBNdVjdq26w42t4HkvITZPdWZEMqEeP/rd+DJRt+xLd1/T4wQiTsiS4bSJJCU68Nd1ySjde212PN1jq8+m097pmag3SDCok6BUOekhTwXpV/sUy3eX55GjptboYYXjjRhLXb6rHyv0fw2IwChrRlg/638M6Ui3f3iv5vggCH7N24pwmxKn/AzHcvE3WKkHbQz+7Bf+/DCIOKl6hq7rXz/u5T1xYjw6gOW1DkbEMtE6NyShbunpqNyilZUIdZQJkdHt529zrCK4BoT6KJWXGMv2o4uD3874PbS/J+Xy0Xh9zrJRU5UMuFr8Xu9nL6Ix1A2N1ewWO6bfwKmm6bm/f7Lq8Xd0zhvh93TMmG2yt8ji6bm//dFTgHfR6+a3F5fbzfPyW4uBRWAsnEIl5iPBzRfSZAk10A//ggl4rw9Jxi3HSRCa9tr8eq/x3FvRt+xNS8JHywtwmrt9Thzn/tRY/Vw/id02Qe3ziQGCiSEXyecIFDm4V/U4ne3RYav9r7XHjq2uKQNohFwOcHW/D5wVbc/MZu3PbPKvzyxW9xvMsaMg8snpqD96uamHE6UpzosjHqD8CfufHQv/dj3U5/hgg9XmgVEk7RPvpaxCJg8dQcfLC3iblf7GdHg30v6dS0q1d/i1+98h2uXv0tth5pw7F2K3Ye60R9hxXpBlXYue9cozhFjyevKUKP3c0QsbmJGoH5yombLjIxSgcgYHdC9QezN11kOq0glY5H6PvVY3cjL0mHS3ITBjUWRxHF6UItE+P6cenMPPja9npcPy59QLI2Urh9Pt750OPjjx9oCClk2wdQyPKNW5sPtYIkw5dOSYlRYFpRMv7f+j343YYfUbl+D6YVJXPGAz7EaWS846hRHZ7ktXl8vPGe3cMfJ9Cwujy899N2hpTfUUQRxYWL9Fg18pJ0ePXberz0VR1jxTZcMRo7jsxOUIeMhe/sbkSMSornrxuNxRXZWDQpCxuqGpESEyrSc3pImB0e6FUy5t+PfngAO+q7Bhy/o+gH+5nQwojgGN3tI2FQyXDXZdm4e2o2lFIRbrs4E24fiT9+fBCrt9ShxexERX4Seu38XANB+LmkP80sDFnvG1UyvF/VBIIQXmPRn5/sduDjH5tBksD/W78Hq7f41+cLJ5pgMirPqzXFhYzTUg4TBPF40L8BABRFLR/gUC+A+ymK2ksQhBbAHoIg/kdR1GGCIEYAmAagUeCcvwRQBmA0ADmArwmC+JyiKAuAvwOYTVFUNUEQvwXwRwC3DPZ6RCIC0/IT4fGR6LK68MSnh0M8eeeXpzGkKE3i8O2EJOuVIZ+bjEpIxSLEa2XYUDmRU4yJXugJqauc3n47BTHhJ2hVcimT3pysVyAnQcscG/yC0R4wR9v60Of0YE9Db4g67o8fHURZugHpBhWyE/oXxfRieUlFDtIMKvhIyq9i9vRbSBhUMkwvSsbabcdw/bh0PDajgClwtGlfM568pgh//Ohg//V4+n1pxCLA4vSEXrOHhFIqYgYStlK4xezEy9vqcevFJrx2czncXhLpLO/lDKM6pGAe/exoxZvJqMSoRC2nPakxKqz8ogbXj0vHs/NKYXd54fL6kB2vxnfHuzjKFnb72VU2zwqGeBqdQsrbr3QKYbUtMHRVjVohoIQVWEw6PD6opGJmt1pEACqpGM4wix6VTIKtNa0hvsbjMoTTMhN1oe+jQipcTVciFmPj3saQczw0PV/wHEIqnYQwKh2tXNZ/LW4vVDL/eSZkxvJ+X6fkv78aRTgy3Seg1A2/sBxu0GTXis3VISlJK+aW4GCTGT4qdNeYroJrdflAEECfy4tLcxI4fucZRjWmFSShw8qtustni5JuUOFEp5XXs529qcS3u01SQt6vcsSqZfjPPZPRY3dBKhKhqdeBA80WnOqxC3q2v3nreHxb18moNGgl6kBFTcO9k8EbjPRc0GJ2cmxS1t02jvdachO0+PNn1eixu/H0tcWwujzweCk8O68UBAGs/eYYjrZbOUFYcMaLQSVDbZsVd7/9A+feT8tPxGeDqI58LohPmUyM/CQtllTkIFYlg0ouQbxWxjveJ2jlMNvduOvSLLRY3BCLgNK0GLzw5VEA/vudEVD3RopIMjeiiGI40WZxMZtKtHJ43c4G5CVpUXgGzmdUy3mVytOLwmdm0RuBg53faZzosuGjHxo5CuC3dh0f0HKp1+bBxj2h8UFBkhamARw/ls4sZDKMFFK/9RQxwCt9qteBv39Tz/g4+kjg79/UY9msQhSlCh+nkUt57+ezc8+M8juKKKK4cHGmYw62VaHHS2Lx1BxsqGrEjJJUiEVAucngX9oSBPKTdFDJxEiNkSNJYHzXK6U42tbHfOb0kKhq6EaaQRm1FRgk2M+kxezEhqpGrF1YzrEjbey2MfaeM0pS4fKSyE9WYlSyFjQPv+1IOwpSdLC5vLxZtxTl55LitTK8eP0Y9NjdUMok6Oxzwu7xYX55GnIStGjusfM+ayqw9qrvtPJmcK7eWosNlRNRnBoTjZGHAadrK8GWNykAzABQPdBBFEW1AGgJ/HcfQRDVAFIBHAbwPICHAHwscHgBgG0URXkBeAmC2A9gOoD3AFAAdIHv6QGcGuoFNfbYsX7ncdw4MZOTzkkHVwXJOs7nN11k4hCh9CK4MFnHISboomwL1u7ifG9CppHTkYV8Xl0BRebGPU24Y0oW1AoJbC4vs2hdONGElV/UMKQL0E9ilKTqcPMvMtDQZcfBUxZYHB5BdVy3zYWa1j6c6nFwUmw3VDWCooAH/72PIagV0n4LCbZSecXmI0jWKzgpsOkGFcrSDei2uZCToMH6ncdxbdkI5r4tqchm2ss+p0YmwZKKHMZzmE329tjdSItV46KsuJDBQCQiMHVUIodAYqdG//dgK+6Yks3cM9p7eOUXNVhQns6cg35u1wWem8moxJPXFOHFrbWcVP212+rPapEvMUS81ywh+NWgCVo5b1piOOKS9l/d32QGSfnJ+eI0PaaOShS8xqF6FMaq5Hh9x3FmIvGRwOs7juP1m4XTQZ1eL+aWpXN8jZfOKIQzjKq3MFnHbFDQxzx5TREKBaq8Ozz853B4hM+hV4qxfFYhHmf5Hi6fVQi9Upi4dXm9mF/OPc+yWYVwCVxLmkHJe44RscIFbYQ2nBLPsk82E3gmadFtc3E2yLpsLtS2WwHwW8HolFKm774qFeG5+aNxVVFSSApvsE91cKCbblDh69r2EE9h+t3l21SiMwckIuC5/x0N6d9LZxZi5X+P4Gi7FWtuGAO3l+KM34/NKOC1IGi1+Nv06rf1Ic9GSHE6mOKCghuMQf/usYW+q/ddkYuTPXbML0/DmBEx+PxAM5yeOCz7lNXfZhdhQqYBIwyhHvY0+PzkaL9ntp3H+VIskcaoRB0Ot/QxKYzTCuKwfFYRXvo6dLxfUpGDVIMSr2w/zhShu/fyXFxVnAyHxwejRgavlzytglh05kZ0oRPFuYBaLkGP3c3ZVPKnmZ6ZAngZRjWenlMErw/oDpC1v8g2DLjJIhVTvPOiVBxeQWZ1eVCR71cAs+ffgZS1FpebNz6wuISzhACg0+rGO981MJvBSpkEr247ht9eFj7J0aCS8T6HcFZagJ80v+OS7BAyOlEftZWIIoooQnEmYw56DVB072S0ml3oc3qwpCIXj354AAaVDHFqGWxubg2nP80sxGvbj2HpjEJOHLpsViHe2H4chWkxzO8rpCL4yPDiiii4GMyGAF3QnY6BDSoZlFIx5zktnVmIxz8+CL1CGjrnzCjExr2NuO+KXHT1udDr8ECtkOKlAN/CXoM8O68UD145Cs/+9wjz2b2X5+Lt3Q14bEYB1mytw9yxabz8lcPjixLDwwSCooZPfk8QhBzAfymKunQIx2QA2AagCMBlAKZSFLWEIIgTAMopiuoM+v40AEsBXAFABWA3gJcoinqOIIjJAD4C4ABgATAxoChmH18JoBIA0tPTxzY0NHDas/NYJzqsbhxr78M/toUu2jdUXoQFa3dylER6hRhlplh4fCRH+UQrvNr7nFBKxQwxzP69z3gK1rCPo1/U4502/PLFb5nzPj6zAD6SwgPv72M8IunibWkGFSiKhI8E/rrlKB6bUcAhQ5ZU+ANR/uubiAVrdzF2EfRA8Ier8zkq5d9eOhJWlxcEgL8GFM1rtnKLdwHAu5UTMDGL6w7i9ZLYfqwTd7y1hzl/cKG3cpMeD16Zj5vf2M14kGoVYmTFaaCWi+H2+pVZJOWfCAajOKvvsOLq1f57eNdl2YyvcbJegUeuzmcCfbotIwwqxKikuH1dVYgC/Ln5o3Hja98N6nliyDrfwEFh+mp1Sy+Od9pBkoDN5YVaIYGIADLjVMhPjgn5rROdVuw+3gWVTAqb2wu1TAK724PxmUZBj7wTnVZ8frA1hFDmI+VofFffhYc27mPIXooCPt3fjGfmlmJCVqikJpJzVJ3o5r33by2agPIMfsUt4K9ovv+UGa0WJ5J0CpSk6AWJm93Hu3DT67tDzrHutvEYL1B04fsTXWjpsSNGLUeP3QODSopemwspBhXKM/iPGep5qk504/73fwy5v8/NHy147UMg+Ye9nw4W9R1WfPxjM4DQcWlxRTYnywEI+66FgK20Vckk2HGsk0NcBv8e2yPY7vZihEGFbocTTjcFq9MLiUQEbYA00cqlON5lxd+/rkeL2SnY1sopWVi9pS7kfBlG9ZDIUfYYxv6t/9wzGQThJ2lTYhQ40WnHnsYekBSw61gH5palcwLrJ68pQppBiYc37mf6kkIigkxMICdRi1i1DE98egj3VOQyxAn7fBsqJ3IKKAW36+6p2YOaD4SuZ4Bne0b7qdvtww9NvWi1OCEmCOQkqmC2+3DTG6HvaeWULMjEIqz84ijz2cp5pahp68Omfc2469Ic5CVroJFLo6rfnyeG/MAH6qeReORGihOdVmw72oFOm5uZO4xqGabkxp+Rwj9utw+bD7eirsPKnG9kvAbTC5LCbrLsPt6FZzZX46aLsxjSdV0g00dovgaA7493YSHP/Lv+tvFhiytFEh8AwN6Gbtzwamjs8q9FEzA2TOzy9ZFWHD5lDdl0L0jR4tJRiYLHkSSFb+va0efwMXGfVinG5OyE0577h2PejyKKIeKcxahR9ON05iCn04sdJ7rw48le5CRo8WBg3X3XZdkQi8AbPy+alIVvj7bj9ikj4XR7kRarwivfHMPO491MbE2PiRuqGvHGLePPNTn8k+qnO491YntdF8OZsPkTGjSxKxERuDeoELhCKsKrN5Xj8CkzSABpMSpIJQQMShlvXL1u0XjYnF7Y3D4YVFIcaDajz+mDXiHGqi/9fBOfqObNW8cjXiuPxtqDh+BNGu7tfxWAtMF+mSAIDYCNAH4Hv9XEo/BbSgiCoqgvCIIYB2AHgA4AOwHQ+dH3AriaoqjvCIJ4EMAqALcHHb8WwFoAKC8vD2HGE3UKNHbbGZ9dOhgzGZX408xCuH0+rJhbglX/OxKy4xGsBGbvwO081snpyMDAVRWpQJr98U4buu0uPDO3BA9t3I8WsxOvfXsMv5kyEktnFqLF7GDIXDbJ9tz8UqxeMAYnexzM58l6BRRSMRJ0oUrSVdeNZlLQgxXTEjHBaT9JUtDKxdAF/HmdHn57jWAFHElSONRixt7GHs53W8xOrNvZgDdvHQ+xCGjudeL/AvcsOB363coJuCQ3YciKM7Yqm2270WJ24mhbH4cY1in9lh181TAbuhzotAp53A3fjmW4vupwk2josoeQqskCatAOqws9di8e/6Rf4X7v5bnotLoEF3ltFhdv8b2ydIPgMUl6fqVKkoBShX7uwWmr4Qq7DNXXGPD3uy+PtA+6v3QKeBh2WoU9DGNVcqz43L9Adbp9MBME1u1qwIq5owWP6RhiNfFWi78QJvt9APykYDi4vRQTdNHXPlwYaEx1ODw40GpBm8WFRJ0cxUk6KJVcxROt2G01O3HfFblY9b+jTFsz49QRv2t8ytQnZheF/T2RiEBGnIbpfyc6rahts3OyQ5bOKMTL2+oYxShd1VkoIyM9VsWMj/T9pwOYoaTxCXnSV7da8MD7+5gNQva48NiMAnx1pAVrbihDr90NmUSMV7cdw+MzC/Dw9PyQd+KS3ATsaezG1Lwk7Gno4T1fa1ABpeCMFyFrjuD5QOh6zoTyY6B+SkMmE2NsugFf1rSh0+pCfQcBL0nxtpOkgCSdAsl6BVNnoCZQlG7x1By89HUtls8uwnX/2HVOFdFRXDgI10/PttI+LUYFlVyCtZ/XcDeWYlQDHhsJgXC41YLmXgdnrlpSkYPDrRaMThe2jWrvc6GqwYyqhh84nwvNo+zj+Mef8McNdd6m4aMo3Ht5Lp7/sn9+u/fyXJAIL9IxqBTYUHU4xB5i9fVjwh4nEhGYnJ0QIjYZjr4y2PE0Cn7ccGslTnX08P4tJd6At99Ye5Zb9NNFtK8OHyKdg2jRxd7GXqYmxuKKbGYclUtEcPv413YEAexvtmDxOz8gWa/Ao1fno3hEDG7+RSaMav9awkf6x8SHp+dfsJ6z52s/TdQpIBaF1oJiw+khcbzThpQYBe/fDp6ywOujkGpQ4mh7H96vasL8cn4F8PbaTigkYqzf1eCvfxUg/x+Znof7rsjFv75r4M163NvYA4fHh3GmWFyUZeQUJvR6SRxuMeOU2QmdUoJknRIjDCo09tjPuaXd+YjT9Rw+ADBRjRhAPIAnBnmsFH5i+F8URX1AEEQxgEwA+wLexWkA9hIEMZ6iqFb2sRRF/RnAnwO/8zaAowRBxAMopSjqu8DXNgDYPNRryjCq0WZxMj67iyZlQasQQ6uQ4s5ABUaTUYm/zCnhVG90evxps3kCiqfgVN9kvb/om93tQ32HlaM2pgdeg0qGOy/JQqfNDZXMr5pdu3AsfCSFWJUMizf8gEW/yMRFAUVmsAfL/e/vw99+XcbYT5Sk6vCrCSYs23QIBpUMt15swhu3lIOkAJeHhMmoBiiKaSdNytKKafrzOWVpeHpzDe6+LBtPflbDEBKPzShgPIdHGFQQiwhQJMV48dLXVtNq4fXu9PvR+EnEG1/bjdsnZwkSDMEelwPdf4CbPtFhdYXsPJmMSiwoT4fD4+OQonxt4POUDpcOPtwIbiNN3JbcXM77fZlYxCxI6O8//+VRbKicKHgOu9vLO3CHK/zm9QEvf1PHWcS8/E0dxmfw20Qk6hS86ZLh7uNQfY0Bv7fgis3VTLsAYMXmakFvwViNjPccsWEKx0jEwNyxQammMwshCZNV7t+sCT1PkgDJnxyBRUQk78pwweHwYNPBVjz+Sb+dx/JZRZhZlMQhiGkbmMZuG3psbrx+czmsTh90Sgl+PNkb8bvGd+1NPJ5W5SY9JCIRNh9sQbxGDpEI0CtlgfnAxRDD9G8s+/QQFk3Kwktf1cHp8ftdLZqUJUiKxiilzNjN9kanr32waXxClhH05hafncMTnx7GynmleOyjg4y1hb8vy1GWHou8xZP9qmqpGBaXB9+f6IZETGD11lrBMdiokcPrJTmBVWGKlvEOV0jFISQIX6EIoes5H6oNJ+sUSNTKUd3ahzaLk7edIsJvRTWnLI2ZK2n7IrpP0AU66Hcuw6g+a8rPKH5aONFlw+vbj3G8bl/ffmxAj1wgMrK2scfOWDEB3NoU4c4XiSUV4K89wRfXFKboBI8BhP3+48PYZgFhvIoHOC4pQqsmo1qOt3dzN8Pf3t2AKwqE1b+A3xZrcUUu/hAgVRRSEf58bbGgLRYbUWua8xOnOnqQNOs+/r99suostyaKKAYHOqbOTdDg9ikj4XB5QVIUTvbYYDIK18mg1/5sZTCbB8iMU6OuvY93XKUT3NlF5dnribljUtBicWFuWargvHY2M25+SiBJCiICKEs3cJ4N33PKiFPjmMAzTIlRoq69D498cID3+bO/6yP9fFbllCxU5CXgoiwjVDIxPD4ScRo5KvIS0WP3WxN229yoae2DXCzC0//r38ReMbcEM0tSIBIR8HpJfLSvmWMred8VuUjWK/Dgv/eHbHIA+Nn3ldMtVz8DwMzA/6YBSKEo6sWBDiL87O9rAKopiloFABRFHaAoKoGiqAyKojIANAEoCyaGCYIQEwRhDPx3CYASAF8A6AGgJwgiN/DVKzAI/+NgiEQExo4w4InZRQxpZXf7OORAQ5cDO+u7BBVPfEg3qLBibkmAWPQPcGu31eO2f1ZxKiSzyYybLjLB5vYxlRkXv/sDbnr9e9z5r7042eNAQ5cDj39yGPe9tw8jDCre9tCecbR3Lq3obDE78caOBvx40oxFb1bhtjercNubu3G41YIlFaHVKmkPZYXU7zNsUMmQqFMwv7Vi8xFs2N2IxRU5AIAH/r0Pd/5rL365ZnvItZGU36A8uCrmirklDDnv9JCClTPZ36GRrFdg0aQsHG3rQ32HVbBaKR0ojzPFcirBb9rXjD/NLMTqrbUc9Z9QG9j3I7htZwO0BzUbTo+wejaSomSxajlzfTQUUhFiVcIEaRtL2bpmax1e+sqvrhR6L2jF4VDuo9fnxbJZ3Iqny2YVwksKX0uXzYUF5f1V11/9th4LytPRbeNX+sgkBJYGVVVdOrMQUrHwBNFqdjHvFxAgETcdQqtZWE1Etz34WpQy/qG5OEWP5bOLON9fPrsIJSnCi8RWM786cyC18XDgQKuFIYbp8z7+yUEcaLWEfJdW7I4xxeLi7HhMK0pCuSkWqQZlyJj03PzBvWt8ytT3qprw2IwC5vfKTXpcN86EG1/7Dne8tRe/fu071LRY8dC/f8TmQ62CmyTsIkJODwmxCMhO0OC5+dz+vKQiB16SwsVZcbgsLxEjEzQRBxp878tT1xbj/aomAH71BV9bQfg33+hj2MrlDKMaPXYPFryyCwtf+x43v7EbxzttgmPw0pmFWLutFh/ta8bVq7/Fr175Dlev/hZ7GnrxflUT1mytw4rNR/DPHSewaFIWXr6xDBsqJyJeK8OJLhtnbI7k/T/TcLt9+GhfMxZv+AEOL4nlnx7Ge1VNuPfy3JDnyq6yTCvIP9jrfxZ0n4gJ+II6PX5P/82HWjn3jZ4fo4hiIJgd/V63D39wAA/+ex/mlqXD4gjvdUsvzofa78Ip+8OhocuG2jYr1m7zz7f/2FaP2jYrGrpsYY9zePjjFKdbOCsIAIqStFg+K2henFWEoiRt2ON8FBUytyypyIFvACVvYZJO4HzhSew0vRJ3XZbDxCGvba/HXZflIE0vXDOAhkxMoHJKFu6emh2ws/l5LVajiCKKc482ixO5CRr8aryJmYceeH8fvjveA6/A+pO99meP7+z4srnXjthAJjJ7XH1idhE+3e+3nGMXlQf61xNtfW5MzIpjMv+CEen893MHfd+mv/AtVn1xhFk3bdzTFPKcFk/Nwane/qz74GeokYuQnaARfP7s3/lgbxOcHhK5iVoUp8bgopFxKB1hQHmG3wZzZIIG5RlGlI4wQCEVw+ry4enNNZx+8fDG/TgRiDcOtZhDNrlX/e8oatutIaKpxm5btK/g9G0lnqQoaiH7A4Ig1gd/xoNfAFgI4ABBED8GPnuUoqjP+L5MEEQ5gDsoirodgBTAtwF1sQXAjYHidCAI4jcANhIEQcJPFt8WyUXJZGJcOzoVuYkatJqdEIkIxveWIACNXIyRcRpBxV9w5XWSpPCfgy1Y9b8jWFKRg+JUPW5fV8X5zSOtFhQkaznBeJpBhQf/7fcUDlYF17J2Z1rMTrT39Sub2FXV1TIxshM1eOSqfHTb3Zz2BqvMZpSk4sF/74dBJWOUDSICKEzRorHHjnitDBsqJ8LpISEiEKLAm5ybgIYuO2dnkK2YYpO+CyeamCrK/iqlsbg4y2/JQavJ2NYWYhFQkZfAVKJkK87ognxsC5AnZhdzqm0CoTtBtIq42+aCVCzi3Hv2vV2/q4FTXC+SdPDhhsmo5u1/6bH8pEokRcncPh8emZ6HLnu/32CsSgYPKbxQk0tEvOeRivnJzkjuo48i8Levuerkv31dF7YCt0ws4lTtBvwpSL/I5vcHpEgCYoLCynmlHI9mUOFVT3wLW4tTuLjNqV4nRAT85wl4RzvcXpwyO1GQwnMdMjFmFSUj06hCq8WFJJ0cxcnC3snA0J/JcKLNwp9+22ZxDbiTT5IUGnvsMKrlSDeoUJKmR5/Ti2S9glFMBY+1wf2Gr9/32N0oTdPjzVvHw+72QquQcjysaWXwM/NKcd97P3KyJmiw1Qz0vwtT9KjvsKIgWYuV80pR32mDy0ti3c4G9Njdg/ZIDge+90UUIH6T9QrkJPDPS3mJWnzG846RJIUDzb0h6uqT3XbeMbjcZMCJThtyEmNCgq1HPzzA+O0C/sDv0/3NmJRtxJaadmZT8OHp+UwK4rkeR4NBkhT2nOxhCo7uDdhqtJid+OeOE3j+utHoc3qglEnQ1GPHy9vq0WN3o9xkQF5iKdZuO8ZRZ49Oi8E/tx9n/i0ViwRV/FFFcRQDwUeC8Q4H+seqtxZNCHvcUDNnaCTqFLyVxwdS9p8yO/Du99z59t3vG1GSpkdmmPOlCGRkJcWEV/KqlDJcXRSPjLjxjH1RQZIaKqXwRjYA9Ng8vLZWWXHhN6dO9TnxXhW3sNy6HfUozzAgSyF8fdWtFrz0VS3nfC99VYtRCRqUhrHNONRiZhRONPzxnorj/R5FFFFEEQkGq6xN1ClQOWUkU4MICJC0Hx/EqEQNZzzyekkcajHjZI8Dt0/OgkYuhkIq4nAfEhHwxi3j4PGReOzjg7h+XDqenVcKu8uLbrsb6UYlHpyWB6fXB4VELLie2HeyF4XJOo6VAI1zmT15ISG4D5AkxWSxT85NQJ/Tg5XzSuH2kdApJVhSkYM4jRwne+xYv6sBN05M52Td0xySTinFjyfNKE2LQblJj6oGMwC/reSGqka8clM5vj/RDR8JrN/l91leXJENlVSME102QQ4HAFQyCcfygga9iZ0Vr2Es34L/Hsz30n0p2ldOnxwuZP+DIAgJgLEDHURR1HYMYNgdUA/T/12FgHcwRVFOAAUCx3wI4MOBzj8YSCQilI4woHSE33PypotM/mD3F5mIUcvQYnaEePauuWEMDrf0cbx41twwBjKxGA9v9JOuKqkYrRYnp+Ab/d3cRC3SDP3elPaAHQSfv8tXNe146tpixrvnvaqTePKaImZRy66qvuaGMZBL/BWm2YE3/bs0mZxuUDILYTrNP1nvfwlf2HIUM0pSoVeIMcZkQHa8Bk9/XsPxfRGLIOi52d7nRIJGziEcaAKbTfoC/Srrh2l/5e31WHXdaM532B6Xc8rSmMJ5tF9w5foqzjNweylej6QMoxo1rX1YsbkaD0zLY3bF2NfVY3cjL0mHS3K5RTzOZbpeZpwaz80fjfvf77+m5+aPRqbAoibdoMKT1xRx0iqevKYI6QZh78B4jRwuH8nx/7vvilzEaYQXanaPJ6Sq7NIZhXB4hAnSod7HdosLbm//qE4Qfk/d9jB+wG4fiRvGm0K8/tw+fqLbqJHhWEfgHxSY0cqoEV5s6pVS3oVtjFK4orhBJUN9pw2P/e8Q5x5nCfgtkySFrbUdQ/L7MjvdIf5Mi6fmwOIMrzYbDgim7erkvL5l0/IT0dhjR5fNhVO9Tjy8sT/lZ0lFDkO0rrpuNGQSAne//UPY+8AeS+jvPTO3BHmJ/UHk5oMtvGOWTEzg2Xml6LE7Q35j+ewivPRVLXM9f762CN02N2c+WDw1B+/sbWLIwuHy0Q1+X0iSwoq5JTjWYcVfNleHPOulMwvREXg3ggum0ql+fOrq5bMK8fgnh5gxePHUHDy88QDmjk0T9ByjLWfEBHDv5dkQiUSM/RJ9T4JJqfMp7flElw2N3XbMKEnFhqpG/PHqAs5G4fJPD/s9nT85xOmXj3xwAD12Nx6bUYCrnR443D7kJGqx+WAzvjrayfRPoQyONosTNa19Z81LNooLE0K1DsJ54QP+zJm7Lh2Jpl4ns9F716Uj0WVzhX3vUrQK3HVpTogtUMoA5LDL68P9l+cgRi1Ht82DWLUUufGqsHUBACA/SceJa+nMiIKk8PYJXi+JzYc7QuKba0pTeckCGnEaOa+tlTFMjAP41XPNvS4cae1jyO/mXteAY3yz2cFbM6DZ7EAphEleocVtsPd7FFFEEcVQMRQf4QyjGodOhcaMBpUMZocHmw+2IFmvRHacErsbzfghUBh5075m3HFJNp66thBtFm6s/MTsIsRpZbz1ap7dXIOpeUlwen1QScX8ayyVFAvW7sSz80qQn6RDh9XFiXXPZm2LCxXBVlAamRgZcWperurP1xbhRKcNsSoZ4rQyGNUyaGRiGLX9taxom7WlMwvx1GeHmfosf762GMAJVDWYoZCKcMN4E57dXIMF49Oxdtsx/HpCOpL0CpzstuMPHx1Ej92Np64tRqpBgX2NvbC4fBATQJkpBjYXide3H8Odl+bw9gt6E1vIBjQ4tFZIRbAJZIr+3PpKROQwQRCPwF88TkkQBJ0fTABwI2Cm/VMBSVKwODx49/tG3HZxJuK1ClQHfHOCFbYJWjmu+8cuDuHqdJPY326G0+P3g+yyu9Ftd2N+eRpHyaiRi9Hc68Az/63BvZfn4u3dDdCppBy5Pd1hk/UKXFWcjBe2HMWiSVnQK8QoTouBWETgufmjQ1Rwd7/9AzZUXoTatk7mxTWoZMhL0jI+u0L+kv40jqNYUJ6ODVX+e/BtbScKknUhO0S5iVrUtoX6zZSb9FDLJDgUsKx4YUstWsxOfLq/GX+ZUwKnh8TXR9thilXDFKvC17XtaDM78GxAlZFiUGJiRn+hP3p3i1Yyt5j7yfZgL16DSganm+TschpUMtS0WvyLALUMKzZXY0F5OlZ+0U9202rh3EQt8pN0jEcoe2ctWa8ARfmLmtjcXpiCvETPNAxqMdYuHMssvsJ52zb22PHiVq5i5cWttWG9A70+Cv/6roGj/vnXdw2YOipB8DxyiQQb99ZyPBHfDFQNHy6MiFWGFN1aUpGDEQbh1Ey5gOfyewKey2kxKhyQmXG0vY9ZTGcnaMIW4knQyvHglaPw7H+PMO168MpRYX0PXV4fU3yNbteq/x3F6wLe0ZF4TmrlUmytaWVUTiqZ/5mMyxi+ZyKEgiQ1ls8qCiEXkvQyTrV3p4fEis3VcHp8ePTDA1g0KYtTDdfpIfHu9414dl4J7G4f9EopLE4P3rx1HJweH5774mjI7i5JUviiuo3J2Mg0qkEBUMnE+KGpG3FqBVotTsRrQglsk1GJPqcXj318kMlGWLuwHFIxgQStAhIxkGksRUO3HY3ddrT0OrEm4D9Mt5f2nKWDJDpQGQ7vM1qR0WJ2IlmvxJV5ifhKLMLqrjrOmExR/rmFTdDSQf/xTr+agm/c77G7kaCTM4p2lVyCV7YdQ4/dDYoCY6MQHGw19TqwZmsdTEYlnpxdjN8ENumC78n5GmiJRV5kxqmhkokxOacEFqeHswncY3cjTiPD89eNhi8gHV/7Tb9a+IlPDzN99y9zSnDnpbmYMzadUUSf6LLx3je1TIyd9V24fXIWAL/q+ueoVogiPIQWOcn68GStQiJCl80TUugtPzl89shBAVugrHg1yjNiBY9L1CrQ0efGQ+v3MOdbNqsQIwfw8pVIRLgyPx5phn4FcGGSJizBC/iVte/ubgiJO3ISNGGVtT6KDBF5LKnIAUmFJ7GTtHKmHggdH9x5SRYSBiCV43jmGoVUhDh1+OOS9Urc/osRuLwwFR2BDIv/HWpG0gDPPYoooohiINDKWr5s5uDC4CIRwSmwDPR7AVcGxnuTURnikb54ag5e/qYOf76mGI9+yM1+eezjg4Gsah3euGUcuqz++FMmpnD/tDw4vR6opDK097nwyk3leOHLIwy5uKQiBye7bTCoZGjqcfB6yJ7PtS3OFzR221DfYePECEtnFmLZrEIcPGXG7ZOzsHGP3zKt3eLCu983Yv7YERCLiUCmoRh/+PAghxfLS9Ti2S9q0NDlAOB/1n/48ABevnEsCPj7mI+iYHZ6kJOgwf1XjMKxDiue++IoeuxuptA3nZVo1CpQkCJHl80FqVgMpZTCnZdlo6vPiWfmlaCu3crMx/nJOkZdXJisCxHH0Z7DdL+g+4splj8r+0LrK6e7zoyIHKYo6mkATxME8TRFUY9E8hsXAtjKqhklqeiyu9Fld0Mi4hZsA/yDY3a830+lJFWHBePT8cSnh3H75Cwopf60broa58Y9TXjk6jyOwndxRTZDOBuUEiyuyMHJLhuWzizEy9/UcdRgbN+dD/b6LRroxT+7+icNp4eEx+dDVoIGp3oc+OPVeZBLJXj2vzWcavW0YnZDVSNmlKRCLPIrOXwlfnPwJRU5sHt8TDuDd4jW3DAGxWl6TrBN+3k2dNnxEMuyQqsQI14rx48ne/Hu9/7z/XiyF5Nz4lDbZg0J1tNilMiI08DrJfGfgy0cFd9rN5f7K1oGCG72hHXLxRk42t7H+Yy9C7a4IhszSlKZfwvZWJAkhYYuKw42W3CkrQ8qmRgtZjnaLC5OW8+W2utkjw0NXc6QXdbUGP6iAGwvYDbCkTStFgduuziTYytx28WZaLM4kJ3I7+XX5/TgurEjGDNzggCuGzsCVpewcjiY6BJKDaLh8VG8RWvGhVmsdlrdvO9Fl41fPdvUa0dTT2jV9KZee0iwRCNFp0S8Vs4U5RIRQLxWjhSdMGltdfHvUlpd/P7JZocb84KK3v1pZiHMYTwnKZCYX849ZtmsQlAIvwAeDtS02fHS10FptF/XIt1YEnLdM0pSGcVYsDI1Wa/AgvJ0/OGjA5xxUyEV4ffT83D75Ey8+u1xTn9mB7wigsDvWKqIJRU5UMvE+Ps39fhlUTzeuGUcOq1+4k8iBsQEgac+46ZhP/bxAbxxy3jm970+YGGA4L57Kv+4S5OotErf6yWxo74LVQ3djJrivitG4ZdFyQMSIDT4iis8eU0RxoyIYTIz6PdcIRWhckoW5125770fMeqeyahusTDjfnDxuEevykOXzcMJ7pdU5GBe4J7JJASWzSrE0iAF7bqdDcyz+r6hm/eeiEU4LwMts8OJ7+r7gjYyClGYosWjV+Wh3eqGTi6GlwTuZfWlx2YUALsb0WF1Mxk4t0/OwvNfHsEbt4zHxKw45hzsjBf2nHEyaKyhg+LzlUSP4tyAb5Hz5DVFAxYmMzu82FLdGkKeFqeGP47OcqMJA8C/cTGQX73V5WPGBsD/3i/95BDevJW/MC0Nh8ODLUc6UdfhX+TVtfeh1ezEFaMSOAVMQ8/X78XMxEMzCsPGHUA4W4nw75zF5YXN7QuJD/pcwsV6AYCkSPxpZiH+xIrb/jRz4LnYFKdAbpIBt7yxm7PJaoob2Ks4iiiiiCIc2gSymU1GNdJjQ0ml4Hko2Av4sV/mw+mhsGxmISMsoIUBp3odvHFhVrwaDd0Opr4TrSieOFKLnXV2PP5Jf8y0bFYhZo32oc3ixrqdDZg7Ng1zytJCrIzoLDWhuOtc1rY439De52KESsl6BX49IR0iApCICKhkYryzuxF3TMlCgk6Bk902VE4ZyXlWT15TjBVzitHU68BbuxrRYnbi91eN4lhSbdzjz6SsaujBq9/6sxF1CjHuviyHEQux41+2wOZElw0rvzjK/H3V/47it5dmgwCFl74+hhvGmzjz8VPXFjPXJpGIcE1pKnITNGgxu6BRiJGiV2KEQYXCFD3H0g7ABd9XhpIJIIRIlcN5FEXVAHifIIiy4L9TFLU3kt8930CTC7dPzmIsE5SBATPYNycvUYva9j6YjErccWk2x7NEKiL8ysZYFWrb+tBjd0MiIjg+wrQdw5yyNPQ6PPBRYBS+88vTMCJWiX8tmgC3j+QU7aAtFdi/Q+96sL2HpWIxLs0xoNlsR32nHXe+5d/hq2MZcreYndh8sIXz0i+pyGb8XNJjVbj//X0MMb5up19dW5isR06ihnl5suM1KEs3cPw8l80s5BDqd12WDbvbjo9/bOYQkH0OLy/xV5ZuQHqsGjvquxhiGPCrgI+1W5Ee21+Qj77+X09Ix/NfHuUo49gWFHPK0pCT4H9u7HtAEysXjzQyxPDWI20gADR2+z2VF03Kgt0t7K98phf0bQLFz9bdOp6XHI7EO1AlkzCbAewFkFImPGzEqeVo73MzSm2atDaq+JUxQkRXuHTQ9j7+1NqOPuHUWpWcPx1JIeWXW7NJf/r36X4oRA5Xt1nwEI8voKlS2BdQHWT1Qh+jEvAQ9pFgFpZ0u/60aSDPSRHvQn3dbeEX6sOBVoFNiS6rO+S6g32j2H+n31s+//W/bK5B5ZQsVE4ZyenPdCrZnLK0ENX4C1v8lXB/N3UkiCDrg6UzC6FXSnDbL7Jw3/v9/Xjx1Bx0s9Kw2/ucgu2l/z0qUYtFk7Lw4tZalJsM2Ndk5mxs+YOcIzCoZJiUHTeoiZuvuMIfPzqIf946DvddkcsEeAqpCI/PKMCLW7n33ukh0dhtY3zraT/duy/LRoJWjlSDElq5BNet3RVyz/52Qxnmjk2DiAA8Xh82VE6Ew+OD10fhwX/7bYDuuixbMBNFIRXhoiwjKArYeazzvPLWPdJq41FJHsLKeaWQisXYdqQdk3MTsOpL7rv0xKeH8fx1o9FucTJFMehnG5y2L+QZPf2Fbzm/SVdqPh9J9CjOHehFTk6Cvx5GUsB/fcCNJYLkJU8JInyRlREG/iydtDBZOkBkczQAVLf3obk3dFO2ur0PZSbhzV+pWIJln+7lxkOfDjzHpcQoeW0lkvXhlbzmQDZhsKdyYYou7HGJWiW6rS5OxpfV6UaCNvz9PMo7Nh1ERtx4jM+MjhFRRBFF5EjUKRiBFXuMefTDAxg9IiZkPRs8D9HfB4BbLxqBbpuXs8m+dEYh3tndALEIUPKseUxGJcQiEcM70L/32McH8eat4/E4z/rlmXmlePzjw1BI/fU/YlXSEOEIOwY7n2pbnI8wOzwMb3TLxRkcsciSihzcdclI9Dq9uPe9H7FoUhZWfcntK3/8qD/j897Lc/Gf/aegU0jx1y+5z2NDVSMoqj/OffPW8bj5jd0h8S9NCtMCm/QAv8T++9JAfD6jJDVkjRfcdyUSEUpGGFASZMPEZ2l3ofeV4fDYjrQi0X2B/3+O538rI/zN8w7sAmr5STro5GJo5RJQFIVHpufhpotMTNXho+19eK+qCQ9Pz2c8HJP1CqhlYsTrFFi3swE+H8lU46zvsIUEzwqpCAQBJMeomGC8xezE+1VNqG23Mj46tOwdQIjCjlb/moxKLJzob9/qLXVYsHYnvqhug9cH/NDYwxzj9pHMbyXrFbidRQwDfu/J/GQdTEYl80LTaDE7sXpLHWQSgqkSKhIRyIjTYEKWEZfkJjAEikouYc5Dt5ukgOvHpTME5JqtdYKeena3Fye6bKgKUqPNKUvDU5/XoM3iL8jHrn6ZqFMwz4/+jCDA7JC+tr0eT31WjfxkHadt9LOgF+YnumzY32SGw00yz0UuEYX1Vz7TEPQetPEvvtINKjwwbRToGmRiAnhg2qiwnsNWFz9Rbw2jjnF4fbyktcPLr4Q9dIqf6Dp0yix4jhiVhPd56ZXCpLXd7cUj0/OwuCIbd0/NxpKKbDwyPQ8OD/+1CPkO0Z6qfKDtTe66zH+Ou6dmw6CSMcETHxRSMW+1dKUAad0hsOgO5zkZ6UJ9OJAcSOdiQyH1F+5cc8MYzvMoTdMz3w2uYksTx0Jet6l6JSj4lV90VVk6lUzoGJIC0ozqkMBz2aZDIEmufzodkLCL+CWyrk2o6u5Tn1Xjpa/q0NDlQJvFxdnYon9zRkkqqhq6mcq6A0HIf3LHsS7IxSLcHeh/lVOyYAx4agbff7VMglSDCq8sLEe5SY8Ws98WQy2XQCuXoDFQQISdru70kLA4vdh1rANKqRhJMUoUp8ZgfIYRYhGY89D3m++e/HXBaHTbPPjli+dfJWCh4ok2txcvb6vD/VeOQnqskve+VLda0MUq+Eo/W4KntALtsUxX124x+6t/r/7VGKyYU4wXfzUGuQka5CZqLyi1QhRnByIRAa1CCp1SCq1COqhFi1Qk4S1kJxGF8aICgIBIITgGwACvK+01z4ZCKkKCLjzp2icQcwykyBWaFwea4wqS/Ao49hj15DVFKBhAiU1SFG67OJMTT912cSZIKvyNIUDB7CRRuX4PfrfhR1Su3wOzkwQxwA0NV9g1iiiiiOJ0kGFUoyw9Bs/MK2VikJJUXdj1LF2X6cqiZCQF7I4A4Mri1JCNrGWfHkLllJEYPSIGnX1OvHRDGUxG/4aYP/uqEPubepljkvUK3HVZNm6fnCW4fnG4vcx66duj7ShI0YWQ2+wYLDjuupDIvuGE10ti38kebD7Ygn0ne+EN1AHQKfw2pkJiGpVcyghPhNZU9Odv727AA1eOQqvFycTL9PN4eHo+PtjbxBwj9HxpUlhEAIun5uBUr533XDa3F3KJSGB+jIyLudD7SjiP7cEiUluJysB/XhUoEMeAIIifzDY2XcCtxezE37+uw73TcnHnW3txz9RsiAiCCWL9VeK16LG7Gc8T2sv3hS21uGdqNnrsbtR22LBpXzOuH5eOkgARQj/AjXuasKQiB06PDw4WMRVsg0DbN9CydyBUsSYRASvmluCWN74P2Tn426/LOOpitpXEgvJ01LFUtICfiHhvdyOWzizE0da+EMW0mADvApaWtdPnemXbMU6hMnHgXRthUHH8gDusLt5zZMapUd9pY36P/jtdRO+tXY0cv+D7Ls9BgpZbAG/RpCzkJWk5O6QtZif+/lUdHptRwEmRYKcRtFmckIhEsAUsAPzPW8P4FrPv19nypknU83soJQqcu6nXjp4gC4UemzusTQJboU7D6SHhdAunQHYL2Dd0C9g3NJv5U4zCFWhRyyS8PoFqufBwZlDKUOezhRTXMwhUMxfyHUqPFSZr0gRUVqlhVFY9DjdUUjHHikIlFaNXwCZCp+BXGmvCXDv9HgQfE84LebhQnKLH8tlFePxjVqr+7CIUJumwtbaD8zwemDYKj0zPw9Oba5gqti/fOBYURUEll2Dttnqm7cHX0mx2YPWWOk76DJ1KdkTgPRURQLfNI0gIBsO/OdC/ycFOVQtub01rHwBg7tg0AH6VvtCGg1jkV4QP1kJAyHfURwJPb65hdtwB4I1bxvIW03tw4z6mQASdogfK/87TimF2eleL2b/5Vt9pxYNX5iNRJ0dajAonumxo6LLBR1J49aZynOp1QKeUwmRUoqHLwbHpyU3QIkWvCFEkny/eukLFE7VyCRaUp+P/sfxTg++LjwSjIATAZO20WZyo77CGVR6kxCjwqwkmPPTvfUym0G2TspAa468WfaEFplGcOZAkhc8PtoYUor2qKHy6YIfAZnLHAIXsWgQWGS0WJ0rDHJdikPN6zacYws85kcQcAJAkEA8l6cLHYhKJCDMKk2GKVaHV4kKSTo7iQSixjWo5qlv6QhTOxgG8g1v7+DO+/nnrOGTE81t1AeELu0YRRRRRnA7cbh9j48MUj5uSDdnexkGtZ9k2Ex19/HMGCQqneuxY9mk1FFJ/YTK9UgKv11/Xib22Z3Mea24YI7AWU2HVdaXwkT787vJcNLPsKuj4y08g+qJxVAB0pu6LAVHK4RYLum0u/CIrDok6fzE5wTnY62MyZUYlanmfCUX1WwBWCsTLde1WpkaHQiqCUSMTXJ89NqOAqfk1oyQ15Fy00CUzbmgZuD91DIfHdqTKYRo7BvnZBQm3z8con/Y3W3Co2cIQkXEaOUMULpxoYoqZ+UgSm/Y14+Hp+czgRhOXm/Y1M4TxwxsPcBSDPXY3chI1uGZ0KhPoAqG2EU6Pv8BcYYoWGyonoixdj6evLQ6kwvlN4Vd9WYvdx3t4X3CtXIJN+5qZ66JJjaevLcHqrbXMAM1G8YgYHD5lwZs7G/CHq/Nx5yVZYAnocKzTGqL8oosdrf3GTwofbbfind0NWDmvFC/+ajQuz09EUaoeCNqBemtXI/5wdT5Hlf3Rj82oaujB0dY+bNrXzFFtn+x1hBDA88vTUGaKxZFAATyTUcnYayhlIuQkaDjn3N9swZqtdXjz1vF4t3ICPls8GdMLkwAAJzqtkEtEyEnUoMfuZnbW/rK5mlGBs1UnZ8ubRiomsHxWIefcy2cVQirhnwC7rG7GI2/N1jr8Y1s9bG4fuqzCXrWxKhmv+segFvb+SzWoeI9J1fMTpHSBluDvhyvQ0tHnYnwC756ajUWTsrBuZ0NYlZDTS/IWfnMKVE83xarwxGyuouiJ2UUwxQorreViMa/qSS4WnqB0Cile33EcvkAzfCTw+o7j0Cr473GKXoH7rsjltOu+K3KREqYwTXGSDstnFQX1lSIUJ4VPgR0OyGRiXF0Yj3W3jceLvxqDdbeNx9WF8TjV5wxJe1n5xRH4KAp/u6GM8QJf+slB1LT24eWv6vCnmYWcsYu+lgevHIX3q/p3ou9770ec6LIxKfzXjE7FnwNjJH3MkoocxKlliGEV/aRBBxzqIPsUOhuBBv37ny2ejHcrJ+CNW8ZjSk48JmfHI14rxwtbarFmax1e/bYe90zNgUng3chL0uHT/eEtXtigA/FglfIHe5uYHXX6c5NRg5klKUwb31o0AS99VcspEPG3r+uQYVQHvMTsMKhkzN9Wb63FnLI05hzvVzWh0+pCeqwaX1S34erV3+LWf1bh7nd+wOEWC7psbhxusWDpzEJGkfza9nooJGL8+bNqnBJQPZ+NbIuBMCpQPJF9X5fOKESn1cWrSGHfl0/3NzOVj+mY4LXt9bjr7R8GVEf32jxYtukQsyhau60ev9vwI371ynf4aF8zo+yIIor6Dive+L9jjMLr2XmleOP/jqG+wxr2uEQt/zybOMAGYbzQ/DxA4bUeqxciEYWV80qxYm4xVs4rhUhEoccaXgEs1M54Lf8mLg2jWoalM7nx0NKZhTBqwh/n9ZL49FALFr6+G/e88wMWvr4bnx5qGfCds7t9vHM9e/OQD922oW2e0+Abm5bPKsKopGhmQRRRRBE5vF4Snx1uxW//tRert/jj1QXl6f5sqWl5g1rP0jYTGyoncjLqaNBrujitglEk/+HDA3C6yUDqvpyJ7YPtLdZ+cyxkbF8+uwg769qxYnMNXF4Cv317L0502RkehI6/1mytw+3rqs6b7LRzjUMtZry4tRYLytOZrPI7/7UX/znYgrQYFXIS/RlrvOt+lYy5pyu/qMHSGYW8axA+zoodL3tJkjlmSUUO6tr7QniU5bOLoJGJsWF3IxweH+67fBS0cjFTQI6OuZfOLITd7UFLr503c9Pj+3nGzrRw6XS4qUg9h5MApAJQEgQxBmByJ3UAhNmTCwxGtRwbqvp9xWiv4RazE+19ToYoZBczu+kiEyqnjER9B9fLd/2uBswpS0N+sgYbKifC7vYhWa/AtIIkdFi5viYjDCo8M7cED23czyvfN6hk2NPQyxRvMhmVWLuwHHKJCDe/sRsGlQw5CZqQnQOTUYkumxvXj0tn/NLEIqA84OXGVhKzlcq5CVrUBLySvT4STi8ZopjIjtdwFKgN3X7bjP3NFoCuIu32IkkvR4xShg6rCzkJGlicXk47W8zOEDuDGSWpeHFrLW67OJOxoaD/zm4vTUSsum40PD4Sb+xowL0V2SHG6a/dXB5yb3rsbsRr5UxF+T2N3eiyunG805/q/e73jbjt4kzcd0UurC4vGroceHlbPW66yIRn55XC7vIiK16NsabYs7JD6fFReOnruqBCX3VYdd1o3u87vfyLmdduLhc8R7xGxls8JT7MgkuwYE4Kf5pmok7ur4gaVFgvMYznn1Yp5fUJFCJUAcDhFtgN9fAv5hq67VjzFbeQ2pqv/J7DIxP4FY4nAhVzg4v3nOi2ISdJuIAfn09Wn0AhndQYFZJ0Co7SOEmnQFqM8LCrVEoxoygRGXEqpgJ8UZI2bIGf4YLD4cFnBztCFGSpMQre55GsV+K3b+/l/O2FLf7n8PZ3DXj0qgIQIuDNW8fD4vBArRDj/vf2MzvR9O/QKlyRiEBmvAYmoxqj02LQ2G2DSiZBglYOgvDf/2Bl89KZhRCJ/EXp6HGCb3IVqgZ7osvGa5WyecnkkEIHj80owOvbj+Hh6fmDnrjpQDzDqMa22g74SHBUrPSOOt1eOkUqK16DzQdbGGIYGHiX3+khkR6rxJKKHPhICvPL05CglTObf8GbLUsqchgF95+vLcblBU70OX1Yv6sBPXa3oOr5fPDW1SsVuLIoHlnx49FidoIAgbXbjuHSvATevmqKVWLRpCxsqGrEHVNGQixCSExAfzecOppWZ950kQkOjw+3T84C4B87/vjRQeQkaAQ9y6P4eaG9z8HrHdzeJ1wkFgA0cjHvPKuRh1fWiETgZHzR5xvI4rjH7sYfPzoU8p6vXTg27HGxahlv/DAQydtiduKd7/rjTKVMgle3HUNmnEowMwoQ9m8f6J2LxHYK8G+G89V+GIhs18rlSNDJsHJeKWxuL9QyCTQKMbTyqHI4iiiiiByHWsx49MMDnLWLy+vD9ePSYXZ4Bl/AKmAzYXe4Q7JGls4sxF8+r8bRdiuWzigEdjdgf7MFR9v7oJSKcaLTinum5uDFrbX47SXc4s77my3Adw147eZyNPc4oJBJsG5HPa4oSMajVxfg0Ckzbp+chW1H2rF4ag6cXt+Q4q+fE1rMTswoSQ25P498eAClI2IwdVQiGrttePraYjzCKkb92IwCLGfZUvn5jzq8elM5umxuaOV+26oWszOkdgx9DrEIuPfyXJAUhReuH41jHVas29kAALhjShY3e1YmQoJGi5sulofEAiPj1Oi0ufHM3FIAJBK0SlicXix+dy9nvb6hqhHTi5KGfI+E1nUXEvhqmwz1OiIihwFcCeAWAGkAVrE+7wPwaIS/ed4hw6jGw9PzmUWwyahkAte3djWGSPBbzE58fqAFd03NQVacOoT0fG17PeaWhQ5QwWSTRCLCjJIUFKXq0WF14dVv6zkv2/zyNIYYBvwvauX6Kvzt12UwqGR45Op8vLb9WIhVwrJZRbjjrT3MJKBViJEWo4KPJKFXhlowiEVARV4CNHIpng0oo+O1Co4NBE0yBhfqYhfa2t9sweJ3foDJqMSSilzc+GF/Vco1N4zBc/NH4/73f2RSatMMKs71yiUizChJxdOba2BQyXD/tNwQ4n1JRQ7GpMfAR1JweUioZBL02N1ot7qx5qs6Tnsf/fBASKr1qutGI92gYio80te/dls9bp+cxSGDy00G5l6t2HwEgH/h89niyWdtEOm0ugQLffHBLkCO2l3CSheL04u/f8MloP/+TR0KkscIHjPUgjkjDGqkxNg4ix6tUowRBmGirM/hwb2X53IM8++9PFeQUAX6N3ZCU5P4z9PYbeO9v43dNkFyWKuQ8NpKaBXCw6xOIcXWmtAq8uMy8nm/X91mwUMs31r6OkxG4aJ3JEnh67qu06pcGikOtFp4C+msu208fxqQXMzbTwnCHyT+v7f24O6p2ZiUbcQVhUmo77DyeuoGk40iEYGRCRreZ6dVSPHCgjFw+0gY1TJIJMDRlj5MyonHZ6zJNd2gYoKGBK0Cx7usuPvtH0LuqZDf0/FOG6blJ+KzxZPRZnFCKhbB4nTjsRmFKEzWD23ilohQlm5Ae5+L81xXzC1BaowCc8tSmWCAHezQSkC6fUK7/LQ1hUIqgl4hhZekmLnk4x/9mTF81xivkSNZr0CL2Yk/fHgAlVP6f2fVdaNRmKw7rysB65UKUJQNb+44jpsuzsKvJ5oEU9ZVMglMsX6i5+Vt/mrJq6/39yMhdTTf4iRZr4TJqESCTo52iwuxKhnUCgmevKYQL3xZi1azE6UjQg6L4mcIiUjM6x287tbwhddazC5e8jRRm4v8FOHj9EoZNu5t5By3bkc9npk3Ouz5HB4fchM0uH3KSGZee2XbsQHtIVL1KtQo+jjxgFRCIFUfXnOSqFPgaLsVi9/5gflsMJtOQv7tA71zkdhOAQBFkbjjkuwQkp6iwt+X45023PHW3pDz/eeeyYLxSBRRRBHFQKBrHiy+PAdONwmby+sXS+nkAxYe5YNKKWPEKO19LoAC1m475id5ASz71F9M7qF/74OP9Is/np1XipZeO/4ypwSeQB0k9lh3tN2K7453Y/WW/vXYwVN9qJySxYgRFk/NweaDLfj1BNOQ4q+fE5L1ShxusTD3h22/0WF1IcOoRkacP0t61fxSeEgKcRoZzHYPR1QC+HmnvY290MrF0MjFmD06FSQF5CTwW05kJ2jx9GfV6LG78ey8Us6zfHlbPeaUpcEUq0RDtwN//k8NHrk6n3fjdkPlRFxRwCV9SZLicHWRritoO9RzsVYebrBFQZEgUs/hNwG8SRDEXIqiNkZ05gsAfOx7ukEVWJQ7kaRTwOzwMiraklQdfjXehCXv/gBDwHKATRQNpbPSD5bta8lW8vINfnqlFDddZEJrrx1T85KwdtsxhuTMS9LB4/UvWlvMTnywtwkLJ5oYopdNfLMVuIXJejT12rGkIhcvbDmKB6blDUoxQfvXsK//99PzcW/gOuhBqb7divGZRvxr0QQc77Ljjx8d4FS5p/19qwNF/lrMTsgl4pDBRy0T44fGXuZ89PU0dttD2tvQ5UBqjIJD/NCKYfo+0wXz6GPZZHCyXnFaz3Y4oBXwnlULKIEMgfT54O+Hs4hos/AT0AMVQaEL5tjdvgEL5ohEBCZnJ+BEl23QO1yJegVO9To4O41KqbDfMuD3rKY3Iehn9tz80ciM439marnA/ZUJD5lSsYhXnf2v2ycIHiMTizC/nKsEWzarEDIBMj2SxexwVC6NFEKFdHrsnpBxbfHUHBxp4fcHpuv8KKR+Lyp60c83Pg71XUyPVeNwSx8eZD2DVdeNRnpsv+qWL2hYUpHDWDDMKUtDTasFiVo5ZGIR7zX8cLIXDg+JafmJqGntO+0AZDC7w8HtNhmVHKW00C4/XQxi+ewiNHbbmMrEtNJYyMe5sceOOWVpeCmwITdmRAzerZzAadv5Xgm41eJCVYMZVQ1+oilZrwjZaF08NQd//qwac8emMePj818exeu3jEOiht8fVIioKkzW4c/XFOFwS1/IxtLNv8gI61kexc8LQsVb2gfwDlbLJbzkaTiffsA/vt42aeSQx9cMo5Lx0WaToOlx4cnapl476jtsIe/BqETh2giAv+Aun+I4XMFdQNi/PSmMTRMw9HiC+W2JhNdzeMNvJoY9rqErtIC100OG3ayOIoooohgIaQYlbv5FBmrbrJxx974rcqFKi8yzVaWUYXymEZv2ncI9rDkHoD3kvUyGmtPjLy5ndvrwf8e6sGlfM/58bbHfdsJDZxsW4vkva0N+h3aKYIsaTpkd52122rlGYbIO3bb+uk5sb+dXvw1wPilaHOvwczH0/X/phjLee+ryksiMU2Nfk5khe5P1ipDs8yUVOQwxvHRGIbqsTl7xJLteisPFn53Dt9YdrnXFuVwrn2+IVDkMAKAoaiNBEL8EUAhAwfp8+ek27HwBH/vO/jdJUgw5cfuUkUww3GJ2Yt3OBlROyUJxqh4jA0TvUDsrX6en04aDX1SpiGB24Wiig37RFFIR/rVoAnNcsGKsocuBF7fWYkPlRDg8PiRoFUjTK/Gfgy14eON+RtUrRDIGKybSY9XISdRwCDySohiCYeFEE1ME7/pXdmHRpCy8tt1PsrOtImh/399Pz2fO2xzwl6HbP788DZ02N0PSA4DbS8Hp9uIX2XGcz+n2xqrlIc81WPEnDhAkwVYbtD/0f+6ZHGIJcraQrFPyFmVLEfD2VUjFuO+KXMZ3l578FVLhyT9G4FnHqIQJZZKksPVIG/Y3mUFS/ntYnKbH1FGJgvdnqDtcHi+Jpz6vCWnX22FIWACQSwlOf5RLhZ+Xy+sLmeAWT82B2yestHZ5+BWD7jD+hR6SwtJPuIvFpZ8cwluL+K8lksVsuMqlZ3rCEyqkY1BJUW6KRWrlRGypaWesEQDw9ut1OxuY/85J1DDkxHAEBYP5Db6g4YUttbj7Mn9xUrqfrN1Wj3svz8WjV+UxfZRt1dBjd2ND5cRhC0AGeneC293Q5cCXh09h3W3j0RYowMQ3Pk7MjMUlOXF44N/7MLM0lfk7PW8YVDJewnT9rgamCJ9f0a4Oadvp7mifaSQF9dkWsxM2p4cZOygKzLOkWDZ2Tg+JXrsbKXrFkDYsJBIRJGJxiCf6C1tqUTklC6WpMWf6kqO4QCA0niYM4B3Mt1m/pCJnwIJmkY6vfU6SlwQVmtdotFlcvBuswZlpwWjsseNd2r6MlYFTlm4IO84I2mAl89tgsTGUeIKGILkfpl4CAChk/BuOQpvIUUQRRRSDgUIiRkOXnRMHOj1+m7DStBhkJUT+24KFNPUKPP9lLWOFZlDJ8NLXdZhRkoqGLge6+pycjNVuu5s3QzA4/hKLgJxEbcjG3fmUnXYuIZGI8IusODx9bTGOd9l47TdWzitliGHAb2N6rL0Py2cV4vFP+jNels8uwnvfNyAvScvUqqK5r/W7/NxXToIWDV02iAng/mm5aDU78fK2Olw/Lj0k+/epa4vxwpajTFtVAgItobXucKwrzuVa+XzDaZHDBEG8DL/H8GUAXgUwD8DuYWjXBQN28MyW6wP+ReXqLXX4x41lYTvWQB4nwZ2eTUizBz9bwDrgeCe/yoBE/3F8XsYNXQ44PD5MzIoDSVLYXtfJWC/Q12IyKhk/ZPa5gxUTIhGBqaMSkRWnCSG1aYJh0aQsZnBit4dtbZGfrMVLXznw96/rGDLC6vJh075mZvJI1StxMqhS6R1TstDn8uGhf+8LIfnW3DAGFAXsPNbJud/sCo8b9zThjilZzIKKHuxyE7XIT9IhM07NpKqfC5iMoeR7TqLfW5UPfU4v3vi/E5wJ943/O4HiVOFFkNPr5fUbdHqFffUau22obbMO6El9OhAqasX2nQ3GiS4bYwFAQyH1W4HwvZspOiX+WHUwxMNoWsE4wXMIpZ8nhqmY3tHn4vUp7hRQgkWymB2OyqWRojhJhydmF+ExlqfvE7P9xfBEIgJ2t4+TXgQA63Y24Nl5pTjS1odLcuIQp5EjL0kLlUyCRJ2cUfTSGI6gYKDfEAoa4jVyLA0iQZ7/8ijuviwblVOykKpXorHHwXj4AsLq7zMRgAS3uyRVh8tGJeOm1/3WPiajEstmFTIbFPT7KhYR+Lauk0klo/sPPU63mJ3oC0OYXqgBOUlSsLu9If6sCToF9F4y5D7RnmmA/5rFhAitFueQCTW7gIcpSQGdNheyIewnG8XPB4VJ2hA/x+WzilAk4GlPg2+zPidRM6ANAhDZ+NoqMF62WcIXnozUy7fL5sLUvCSOUnnx1Bx021xh2z1UGywaQ40nmO/IQrPeFFIRFANUVVdLJSHj9LJZhdCEyWSKIoooohgIHVYXJ0uWxmDG3YFAF8MOnq9e3HKUIYaXzizEP7bVYUF5OiMQ8ZAUIxYD/HFrcEzGF39Nyo5D2QgDRCIC+cnnb3bauYRM5reA+PpoO+8zZ8/BtJBv1Zd+QUjllCykG1RotTgxMk6JGyZkoLnHzhQTZAvoknQKUKDg9JJw+wCFywuHh8TM0lRkxqlhcbg58YhWIcEjV+Xjdxv8vNabO+pD6sEMduM2UpzLtfL5htONLC6mKKqEIIj9FEUtIwjiOQCfD0fDzjeQJIXGbhvaLC7Y3F6YYtUMQUgHz31BxdWAgVV9kXicCKk5TnTZoJCK4Obx7FFIRTCq5RibHou8xZN5vYzpl4AkKRxo7kVVQzcvgZzCY8nA11YhUrsmYBFBEw3JegVGJXJ9aug0gw2VF0EhFWF/swUdW/3+tzq5GL+ryGUM05dUZDMqX6fHr4rusvcridkeytMKEtHY7cAvX/w25H6zU9RbzE68vuM4Vs4vxbpbx6PT5kKqXonClIEXDmcDIhGBKSPjEaOUodXitzgpSRH2LU3QKniLuIUb9JRSKV7edohDkL68rQ7PzR8teEykyp+hIFlgAA9Hwg51R1AsJvCbyVlo7/MHThIR8JvJWZCIhQOMSCwOYtVSXp9ig4A6O5LF7HBYL0QKqVQMlUwcVGxADIIgsO9kD7wkFfIse+xu1LT24bXt9ZgzJhWZ8RpknuNdW6GgQS2X8PYrp5fEmq11WFyRHfLOJQtsIpyJACS43ezsFsA/nv/t6zr8Y+FYfH+iBxTlJ+cdHh+jBmBnTtBt9QdvDZy0NIVUhKevLUZarJLjeUxjMIUezmUxCK+XxL6mXhxp7UNmvAbPXzcacokIFCic6nXi1UDam1gEjEmPQXOPg1Gz0O8tEbA8GSqhJuRhyrZQiSIKtp8ju7ioShm+YBvfZv2ZfLcimaOByL18ZWIRr3f6hsrwdg1AfyGlofh6t1mcvJu6A23wSUTAo1flodPmZjKrjGrZgAX+JBICLo+PM4+6PD5IJFHCI4oooogciToFZ/1MYzDj7kBQKqWYWZQUMl+VZxjQZnFCJROjz+nBxdnxHAGFVEQwma5+UnIkOvqceGVhOfY19QLwW0kGx18qmZhZC53P2WnnGiIRgQyBOjwqVr0odoY5LRBUSEWonJIFH0kwhQxvuTgDb+/u51nyk3R4bfsxTMiKx0tf1SFZr8C9l+cwhD/9vN6vagLgz0g80GxGfrKOqeVVborF+HQDRiUObeOWjaGuJ87lWvl8w+mSw7RDtZ0giBQAXQCST/M3zxvQHavL5kKX1Y3jnbYQn1k2iRuJqo+v6vtgUoz5Fp90x16xuRqLp+ZgQ1UjZpSkQiwCxplikW5QhfUyZhdlq2m1cFIFaCikIsRp5IxabCigSe3UGCU+/rEZoxK1MBmVWFCejpWBgnfsNl+cZYRWLmbSDejP85P1mJARi9IRMYz3c12HlVH5BvsFt5idDEHzi5FxYe83m3RP0ilwuOX0vUHPBLxeEv+tbkVtuxUkBdS29aHF7MBVhcm8g6dYxJ+uLw4zzrq9JK/nsMcnbJMQqfJnKChO0fOqUUtShN+zBC3/YjVew79Y7bD60z/ZCugHpo1Cp9UlSHJHkoKrkIh5yfRwHoRDXcyKRASm5SdiQ+VEtJidSA5MsmejDx9qMeP+9/eF3Pe/3zgWdwaKYwYvlmNVMry+4/hZm5TZAYRKJoHb54NRLWeendfr7798Y7tMyp/uq5D4Py83xTJ/p8ePwmT9WQtAgsd5B8/72dDlQKvZiTVb+y2IfCTwwd5+UpjOnChM0TF+cC1mJzZUNeLvvy6DQioOG3wNZhP0XBaD8HpJfLSvGS9urcWC8nTc805/ocHHZhTg1e31nLGQHj/ZG2frdjbgjzPyI3qOfB6mtIVKilaBqhPdaLU4kaxToDhFD9kASsMofrqg/RyHirNp51Kcog9R/SwfYI4G/O/BmhvGhNhSDeTlK1hw1y1sA3U6SNLKce/l2VDJpLC5vFArJLj38mwkaMLbdKhkEsilYk5csWxWIVTS8EuxXruH10rrtZvLh+V6oogiip8f3G4fLA4PRiZoQtaHg/FQHwyUSmnIfJWllHFEYxanj0P0jkrSwkNSWH39GPTa3UxtJLZ9GQBOdt66nQ0YPSLmtNv7UwdJUjjeacMpsx1PX1vMiOzomPOVbceYuJ8vw9zpIZFpVMPs9DCk8T93nGA2SnMStPjL5mosKE/H5oMtuOuybOQnaZlnSP8Gny0f/Xzfr2rC2m31+Gzx5CFv3LKvc7iEl+ea7zkXOF1y+FOCIGIAPAtgLwAKfnuJCx7sjkXvhgR78gSTuAOp+oJ3MdINKkZFS6MkVYfbp4zE4RYL+pxeFCb706/p45L1CvhIoL2v/zcae+zMb07LT0RekhYWhxvJegXnxV9zwxhkGjXMsdPyEwWLst0+OQu7jnWE+Er+dcHo0yJMRSIChck63DM1Byu/qOFUmNx8sAWVU0biiU8Pw6CSQSn1E2e5CRpUThmJtduOYUZJKr5v6IZUTCBOIwdF+YngS3MSkB2vQVm6ARQo7DzWxSFtkvUKzC9PQ5eN3/Ot2+ZP46fv4/gM46DMyc+V0q2mzYKmHkeIfUNNmwVFPB6VLWYndtd34R8Lx6LH5kGsWoo3th/HmPQYQbIzEpsEk0HFe8yIMIVhvF4Sh1rMAeJSicJk3YC7g8ogNapyALJkqOS4TCzCyi+OcJ79yi+ODEqJBAx+46Tb7ubvj0H+Wmy43T7sP2UeNFlEkhS+qG47J6SbkIXCD409zOeOIBL+qWuL8eat40PsI8LB7fahutUCs9MDu9sHo1oGrVKM7LjwfYkvgKA3qR6eno/LRyXgkwOn8MePDjJpVSPjNciMU+Ged36AXiENSXdbOrMQYoLCmhvGYGJGLIuU7+/bQwlATmeMCQ52pCJ+MpsutKiQivDCgtGgKCDdkAO9SoqHrxyFHocHF2UZ8fsP9sPtpVA5JctvFWNUoWCQadh8Y+moeyYz1jznshjEoRYz/viR30ZmQ1UjQ/oC/krb88eOwMov+v3QnB4SDo8vRBWel6iL6J0SiQhcVZSEvKTJaOy2QSEVQy4Wwez0YMeJLizbdAgNXQ6GZLumJCVKEEdxXiNeK8XaQLxhUEvho4Q3ldlweynOfLDqutEDHpOoU6DcpMdNF2dxPIcHUioDkY2vNo8PUokYR9v7GBI7I04Nuyc8Ge0TqDEwUL2EPif/prvVeWbI7yiiiOKnDbfbh4/2n8LjH/tj27suzcLrN49jLAGKw2SiDieCY9QknQJ7G3ux61g75ow14eApM26fnIWNe5r86tWAJeVLX9Vh9ZY63D3Vn503mMyUnzvY6x2DSoY7L8li1tFqmRhpBiWOtlvRsasB912eg+K0GN4M8xiVFD+e7GXWErQATyEV4R8Lx+Ivc0rw4d5G3HFpNuo7rFDJxDCoZBzrR6eHxAiDCvWdVuZvTg+JDVWNWDm/BN02D7ptLqQbVGjotqOh2wY1y1oQQNh5O9L1xPleE+Vs4XQL0j0R+M+NBEF8CkBBUZT59Jt17sHuWMFKVBp8aelCqj4+EmLtwnJQ6FfnlqTq8Kvx/RWeTUYl/nxNEdr73Ix8n52CXm7S41cTMvCHwN/ml6chN0GL/GQdtAoZHvnwO6bNBpUMtW1WxieNTRDxFWXbdqQdvxpvwsvb6vpTaUfEIM2gwsw12zm/WxOoXJ9hVDNkdZfNBZlYBLvbF/LiNvbYGQVeXbuV+a1phUkMET2nLI25zsm5CVi77RgWlKczxZCUUjHe/Z6rjL4oy4j0WDW2HmmDUS1jyED2fbt9chZMRiVmlKQyi/9dxzrQ3OvEja/t5twbg0oa9pmfS6Vbj93DqzgtEvAQTolRYFpRMv7f+j0cEis5jOVJJCkWBMFPwgrdDlqxF6zIvKY0VZBwOtRqxgM8atR3fjMBY9JjeY9pMTvx+YEWTsGaV7YdEyTHhQrHdIQpHBNJfxD0IBQoFOh2+7C5uhV1LMV4s9mB6flJgmTRuSTdggvo0Zs0qXol7p6aDaNKihX/5ZLwj354AJ8tnjwkYnhzdSuaexycfrd8ViEauhyoGJUo2JfY9yZZr8CcsjQ4vT48MbsINS0WHAiQhnQARKdVrbt1PBq6HLjrslS8/E0d13rlmzrMHp2KwhQ9vjzSLtgfBhOADMcYwz6X10vyKqCL03R45zcToFNIcLilj6PKXzqzEKPjVPj9B/sZD2L6Pny2ePKg0ryEbF2qWy2MPdO5LAZBB6ZpMXJmnmFvFmTGqVCSqsP+ZgsA/zuan6QLUYWfjtJGJCKQGafG8S4rfjzZy+nLtFqmxezE4x8fRFacGuUZ/GNdFFGca1S3WlDTYg2JA2KVcpSmGwSPi3SuitNIcF25ieM5vHxWEeI04Zc4JEmhqqETPpJg5vZOqwPlpriw46vD40NHn4tDYt93RS7SDPwFgWl0Wvnjik6r8GYwAKTE8BeiTdaHVypHEUUUUfBh/ykzk9kBABanD7e9+f2g12HDCXaMWtfWh13H2jEuMx63vLGbNwaSB9qkkIou6BoXZxvs+XVOWVpINorJqMSGyonw+Eg09zrx+w/2h9RseuraYvxp0yG4vVSIeHBJRQ5+v/EAZBICd12Ww1m33HdFLnwkBVsgm2fTvmYcbbfite31HDX4gvJ0LHqzipNx9NJXtYw4YklFDgpStLC5yLDromhxudNDROQwQRBzwvwNFEV9EHmTzg/QHYv2w61r7xuST2SwGoEkqZCgt6qhGyqZmHn52H6QyXoFFpSnY/eJHiYApQnT3AQN7pqaA6mIwG/f3guDSoaFE03YWtOK7AQtDp7qhVwi5rSVTbbS5+cLummPysm5CUwhMnYq7d9+Xca076aLTNAppczgYDIqcc/UHCY1lz2gsF9c9ksrFvl/16CSIVGnYD5npzMQBDCjJJX5vTllaXj3+8aQc6yYW4KiFD3ufvsHhhB+dl4p1DIxc58SNDL89tJsTmGPv/+6DHf+a2/IvaH9joWe+bkk3Zwe/jRKl4Bypcfm4a0e/u5vJsIkkKEaSYrFsU4b1u1sCEm3zk7QICshtGjOoVP95Bvdrj9+dBA58RrBRWSbRaDit0V4gZWkU+Cq4mTO4nFJRQ4SBd5frYKftNUohIfMSPqDXCTiJdPlApLmw60WNPMoxg+3WjBa8H6du0mSbbUTvLlFL+D5dpSH0rb9p8yoa7eGZHY8/skhrJxXikMtZpSOCH9v6CKWXXa/vcWehh4Y1TJ0CmwSdNpcUEhFIAjwWq+QFNBt95z2+DDcY4xQdotIRODQqT50Wd0MMUyfb9mmQ1h323iGGGbfh8E+J7aPGQ2FVISjbX0oSNYhK15zTotB0JsYWfFa3BxYkAD93qUr55XizkuzsfzTw+ixu/HYjAKc6nXgjVvGQURQiNcqhyVr5ESXDfubzCF9ma2WcXoGLuwVRRTnEmYn/+Z1YYou7HGRzlU1rTam6BF9zOOfHERG3HiMzxQeP072WHGi08Gtwj6rEIk6K0xG4SJ/Lg+JVf87yjnfqv8dxas3hbd5SNTxk7yJuvAkb0ESv2VdwRkszhNFKG64tRKnOnpCPk+JN+DtN9aegxZFEUVkYBcNZXvLAqx1WIJGMHYeTvQ5nKhu9dd0MqikmFduYoom0+2hY6DXttcjI07NWH71OT1Yu3AsJmXH/yzT/4cC9vzKZxnR0OWAw+NDglbBiOXYNZvGmgww293MWqDP6cGiSVlINyjRbPZbe7SYnbjrsmzOxgM9P1ZOycKarX5hydIZhXhndwPn2QII6YePf3yQE/u+sMUfjwfbVASvi6LF5U4PkSqHZ4b5GwXggieHE3UKjh/ubRdnhpA4QjtVfGqv568bHfIikhTgcPvw0Y/NWDQpCyRJhQzWt0/O4rzMuQka/Gq8CYdO+QXaNFm6taYVc8vS8dwXNVhQng6X18d5MYS8Y4KDblotGmx3QX9fLZcw98Xh8XEWADNKUpnU3OAXfMXmaqTGKGB3+xiiwKCSQSOTMAbkTT12TpvZ/y0WCZPF9Dke3rifIa8BwOry4UhbH0bEKBkCvdPm5iy8DSoZoxKllYO0opiiSI5y1mRU4onZxczC/FySbsIDH/8i45TZwdvWU2YHRmPgyX+wNgkKqZi38J2QErZZoF3NZgdKBdqlElDbKmXCO9wWgcXqxSP5mXGZWMxL2srCmDRH0h/MTg+v3Ue+QPX5Ppd3SIpxoH8sY6vlN+1rPiuTJJuMtDi9+M26qpAFfOWULKzeMvhCicFotTgFMztsbi9azU5Bzyr6PbrpIhPsHl8I6a5RiPH3X5fB5SURq5biRJcNr20/jlS9EquuG40jgayJ4L4oIoQ3cIYyPgzUpwabEh38veLUGJSO6P9efYcV9733I5bNLOQnw62u0wq03D5fiMqAVgtcPNIY1gf/bKhB6E2MDoHNgPpOG7wkiaeuLQIFcG0eZhWhIFk7LAuTtqC+TNtMOT0+jDAokaiTocvqRmpMeIViFFEMF5xOLw60mNFqcSFJJ0dxsh6KMJukgLAHsGMAD+BIF3SRZPoAQJvZzRDD9DGPf3II624dL7hpDoSrrRD++iKpSwJEVog2iuHHqY4eJM26L/TzT1adg9ZEEUXkSGatC4pTtPjHwrFos7iglIrxyrZj2N9sCRs7Dxf6HE58frCD2dzzx32lvOOrWAQsnpoDUCSemVeKpz+rRo/djbcWTYgSw4MAey2YE6/Gml+NQX2nDW4fiY17mtBjd4OA38aUj6+yOPzrKXqOtrp8+HR/Mx6YlgeSAuaOTcPGPU2CfBNJ9f/3sk/9xe73N/u5JoJAYN0UehxBcP8tNP+y11bR4nKnh4jIYYqibh3uhpxvyDCq8cTsYlSu95MZL2+rx00XmbByXinkUhGy4jRMCml9h5WzOOdTe/koKiTo3bSvGQ9fmYfrx6XjhS21eHZeKfMdgvATl6MStZzjKqeMxAP/3ofbJ/t3WWj12k0XZ+Ghf+9jiFmDSsZJBxCqRhocdLOLxrFJVPr7iVo5c1/YxDXQT0DLJSIO2apViKFVSLFg7S6GZH3ymiI0dtvx9OYaGFQy/K4iB3/dUsu0eeOeJoac27inCY/PLBAkiwEw55KKRQx5TV/776ePwvzyULI9Wa/AwokmnOp1hByjkIqQk6DBL4uS8dniyei2udDc62T6g0IqwisLy8/ZzhRFUlgxtxjHOmyM511WvFqQxI3TyHnbGqcWVqxEktKuk0t4SVWtnH+oiaRdarmEqWRLn+O+K3IZ31Q+NPcKkNC9Dt6d8Razk1cBnR4r7J0cycI2SS/ntfsQUhLZBSbFcIvudIMK90zNCVmQpofxgR5O0FY7m/ad4m17Osunmk5bGsoEnqxToLaNP7NDLZMgiWWdEkySpumV+PuNY0GRFH77Njd7YEt1K4waOaeo0tKZhXj06nzoVVLYPT5cUZCIDKM6pKhDmkGJLIFqwEMZH8L1qcG+n3zfWzG3BL8s8hevpO+J00NCJedX+NJkeKSBllEth83Zw/ibURSwflcDeuxu5n6cy2IQNPmy92QP7/V7SdLv9W9xYemmYDJpYIXiYMGuHH51YSImjoznZDssnVGI/6vrQIZRjRiVdEi+3FFEMVQ4nV58cqCFs3BfPqsIs4qTwxLEwjYI4d+RSBd0CVr+OCJeYLOcRoeAzUOHNTyprJIKbFBLw5O1p0PyDrUQbRRRRBGFEAoStbjr0hy8V9WAtBglfvce15Kn6kQHJ3Y+U6jmyfogKX6+IjtBi+e+qGGELj1296AKnUbhB70W5MvuXlKRA7VMjN9t+BHXlacxAr5bLs7A81/2r7X/NLMQy2cV4PFPDmPbkXbccUk2HgwqGEghlO+iLUBosElfhVSEUYla5r/DHUev6wZaW0WLy50eTrcg3U8aPpJkOh9NFs0pS0Nxqs7vQxxU6IlWlgYTOMl6BZQybvq4yajE4zMKYHf7idtn55VCJgZT4VkjF/vJ6C9qOITp76/KY357075mLJ6aA5fXB1dApUYTtC1mJ5MOQBDAlJx4jErShQ262cRJsl6BVdeNxorN1Rxf37QYFafIVPALajIqkZuoQblJj2vLRmDttmO4f1oexy5jRkkquq0uFKfombZ22lzosbs5bRYTwHuVE2H3+JCsV2DF3BI8vHF/CFlMk7yrt9big71NeHxGAe5l+YgqpWLEaeUhZDutzs5N0OCxGYW4O4gcenjjfhSn6pmdqBtf2w2DSsYQ3g6PD09eU4w/fnRA8J6eKTh9PvQ5vZzP+pxeOH38JCFJkVg6o5CxCqGJBgok7/eByFLaCRGQGafCynmlsLm9UMskkIghWPiNiqBdKqkIOQlqrF04Ft0Bta2PJKEKoxweKgmdpFPwKqDDFTyIZGFrdfo4nrWA37N25bxS3u8LTYqqMMWp2B7fQH/KWFm64ax6LyXq+J9Bq8XJXL+IAMaaYphxSCWTwO3zwaiWh0zs9HilkIlQnmFAgo6rTF0+qxBSCcGosoJJUtoG548fHcRvL80OIQnoDTf2fVu2yW9V8cEPzYzv7is3lWHdbePRZnEhRa+ASAR0Wt1oszqxav5orPhv/xhalm5Aj92FrdU2mIxqxm9XCOH61GDfT77vPbxxPwwqGS7OMuKL6jZGAf3KtmMh7+OT1xShMEWP4rQYjLrHXzBNFSgMMVhkGNXIStCgts0aNvvmXBaDkEhEyE9S44nZRRzP5SUVOVBJxXh9x3E8MC0vpJ84PSTaLP1kUnDBSJlEhBNd9kGpLjOMahSn6fHkNYVI1isZ7zX6PMs+PYRn5pXioX/vw1+vG42mXgdUUjFIikKrxQWjWgaVTAy5lIBMLIkGwz9B2BwuHGq1os3iQqJOjsIkDdTKM+M9e6DFzGvXkBmnwrhMYWltQZIOr988FgQhQkefC/FaOSiKHNAGIdIFXZ/LE+KNuHhqDqwuT9jj4oVIZU34+6lTSPk3wRXSsMcBUZI3iiiiOPsgSQotFhuae1zM3PFl9SneOPfxTw7itZvLkStQrHw4wWcT2NRjDxlfF0/NYTKjN1Q14onZRbg0dwIKEjVMvJWolUMkAjr63EjRK1EwiOLmPyfQa0G+7O4XttTi7suyEa+RoSw9BmsXjoXN5UNDl41TMO5Pmw7h5RvH4o1byuEjgduDskFXb63FfZfnMFwWe35ct7OBaQtN+tLP9qnPqiGTECHx99KZhXj5m35r0yUVOdAqxYNaa0eLy0WOKDnMA5pEYKcMswlIujOuXVjOKWa0oDydUdSyj7u3Ihu9dg/UMjEqp2RBJfMrafcFeQsCQLlJj7cWTYDL62MWhpsP+gtpOd1epOj9SrKNe5qwcKIJG6oacdelI5Ea4/8c6Cds2RUk54xJxZh0A/ICKlhpoFjciS4bMoxqkCSF/xxswcMb9zPX94+FZbjvilGcz1ZdN5ohWDfuaWICcoNKBp1cjOWzi/DilqO489IcLP/0EBaUp6OuvY9zDzdUNeL6cekQiQhmd4q2l3hhSy3T5lXXjUZBsh6NPXac6nWiNE2P/9wzGR1WJ4csZvsltZidqGUVuZtTloanN9fg99NH4aaLTHhzRz2T3kyrs6cXJaOmhd9Gg05TaLM4GWuKDVV+v+PF7/q9jSunZCE3UYv8JN2AZM+wgfKTwcFp8BBQDsdrlFj53yP+gmxuL5QyCdbtqMeKuaMFT9Hay5/S3moWTosXEQRazS78ZXMN067fT89DmoBKVSmTYuPe0HY9PqNQsF0EAbRa3IyHMj2BhFMlJenlIZPOE7OLkBTDvwgsTtGHTG6D2aGWSQhGHSki/P8Oh16Hh7cAVq+Df1Ebo5TiL3OKUd/ZrxjPjFNDrxRelJ4vxvzFSTosn1XEUaHREz+dor/mhjE42GzBM/+tYQjVklQ9VnxejdsmjWRUsfQYvWJzNadQZeWULGTHa5ASo4BGLkZ2fH9weLyTS5LSNjhOD4nMuFCVr0NApW1ze5n0qNwEDZp6XFi2aS9yEzRYMD6dQ1A/eOUoPDAtj7OzTgdJPXb3gEr8cGSJ0HNts3Cfq9D3qhq6oVdKmMrF9Fj+zu4GrJxXCgpAukGJwhQ9ozA+0tYXUXE8kYjA1FGJyI7XoCzdALvbi/TYgcnxsw2tUoFphfHIjJuA9j4nSBI42WPH6zuOY0F5Opp77SH9xL9pJAdJUv4Cm4EK4Ow+/s53DTjabh1QdUnfpz0N3ajvDE3tc3pIpl9a3V68uv0Y5penczz0l84sRKxKiu+Pd6AsI/6sFEiN4uzA5nDhPwfbQ5S8vyxKOCMEcauAv3+rJbyy1u5xo6nHFdLOolQ3dJLwarRIFnRauRQbqho5mT4bqhrxrMAmKw2H28tLKjs83rDH5Sfp0NBj58z1qQYlCpJ0g25zFFFEEcXZAElSONzag8PNNs6YvGxWIeQSgneMb+5xQC4Rn/HCt3yikXd2N2JJRQ4qp2RBIhIhK04NChR+Pz0ff9lcjevHpcOokSEnThs23jqbRfUuBLQGCF46u5sNp4eEUS3FbZMycbilj0PM33t5Lv654wRDEHdZXajvtIdkcNO/E6uRI14jY+ZHhUQEVcByEvDHzI/NKECsSsZZDy2bVYjkGDn+/usyODwkGrpseOe7Bswe7c+2SdIpEK+VIz3WTwJHVcFnDlFymAe00oq9YOYzbK9q6OaQkPTf2aTpTReZoFXKcG/g9+aUpSE1RoUHA9YQwS9WVYMZXpKEiCAYQnV6UX8hrXJTP2m1flcDbr3YhDitAqv+dwRLZxTi5W11IcEuvaMiEhHIMKpR08pd4K+5YQxkYjFDAtPXt6ehN6Qwzn3v/YjNSyYzuzbrdzXgvstzYFDL8djHB/HE7CJMyIrHvqZexheYJsvnlKUxxKrD48PyTw9h8dQcOL0+xl6CrSAsTNFylNnBZMQIgxrFqXocbevj3Ee3j2QmG1pJbXX58P6ek1hQno61245h0aQs5CVpOXYT4dIUEnUK5rvsXbcWs5NREH62ePJZG5zcPorXe/YVgYIomXFq3DZpZMi9pK1R+CCVELz3RCoWvka724c3dhznKGHf2HEcBQKFaLxeEhX5SSGF4rw+YZNjs8PHW1xv3a3jBY/x+fwLQfZizuH2QkBoDZlMjGtKUpAVp2YsCEpS9JCFUeie6LLhiU8PMylPJAU88elhZMUJL3R1CmnIuLJ6ay3eFLgWhZRAO0+V9KIU4eI5CVp+a4J4zdk15lcqpZhZlISMOBW6rG5Ut1rwzncNzP0SEUC8Ro7F7/4QQpgvn1WIFZurkZekRVa8hhmjw72Lwfe8oZtLtrF9sZp77SHjZoqePzVaLZMwaU53Tc3BoVNm/PbSbIwZEYPfrOfuoj/73yOonJIV8p7SBRbue+9HpFZORHFqTFiCmI8sEbKc8PgokCTF/J7Q93wkmGAvONMkXivHuIxYTptOtzieSEQgI06DjLOgRjkd6JUKjE6ToabVAovTA5lEg9mjU5lqysH9ZNmsQvTYXWjstqHT6g4pxLFsk1/tu/idH/D4JweRFa8Ou+ASiQi09bkEi/gpA583dtvxm8kjsWTDjyHnWzmvFFcWpWLh67vPSoHUKM4ODrVawxReG35yWMiuQai2AY1IC8QBodY/g1n0jTDIcdel2SGF5UYYwrdTRBC8pPITs4vCHieTiTE9Pwn79eZBxwdRRBFFFOcCJ7pssDupkDF56SeH8Oat43nHeIVMclYK36YZ5Fg+q5Azdt8zNRdvf3cCE7LiQVIkqlv7GG/bGSWpWLezAaNHxGD/KXPYeOtsFtW7ECCXiKCQinjFMAqpCJnxWuw41hnC+zz/5VFmzaKQiqBXyRCr8qDH4RHIZJXgxa21uLZsBCOWMRmVeP660bC7vTBq5GjssuHvX9fh0rwEPDR9FFL0SiTHyHGq14kUowLpBhUae+wYkx4jSP5GVcFnDsNCDhMEkQlgDIDDFEXVDMdvnkvQSiv2gjndoAwhctm+OGyigX1cYYoOVQ09HCXv3VP7U5jDEZI0oUovRJP1CkzIiofb48X628ajy+ZGnEaObbUdqGoww+1twP3T8kBRJP6xcCzcHhIjEzScl4pvgb+/qb+4XfD18atGnBw1m1IqZvyEFVIxxCL/scrAtdFkudPr4xDGDV0OrN/VgN9V5HDuD41fjIwLS0bQpEnwfWT7FTN/85KYP3YEcy9f+qoOJak63DYpi2njvZfncrx12GkKGUY1chO0Ic+afV/OphJTSNUo5D0bSbpmj8MTck/uvTxXUNVKt4tPCetw8ytxWvv4vX1NRmE/3M4IfALb+1x46vOakHftzSQdMgWemUQiQqxaBo+PRKxaNuDuc5fNhRvGm0LuV7fNJVyQzuHmvRazwD1utbh5q6QXJOuQncjfLrEIvCmwYWrrnTEolVKMzzRi57FOpgjd/mYL8/f8JB1vscnHP/EXL2Ar+Yf6LgpZctCbR5v2NXP64fpd9SFB69KZhbC7PfhgbxOS9QqY7f0FLhdXhFpTOD39RRjYn2kVYtx1WTYIAjjZ40CH1YWpoxKHtLmUYVQz2RPsd+2xjw/gjVvGcwoz8H1vQ1UjphUkCmaaBLflfFGgnw1IJCIUpcUA8G9gWV1e9Nj97+qGqkasuaEMZrsbyTFKvPLNMew83o03bx0v6GHqcHsZX/xTZgeOtVvDqqaTdQo8/flhXsuddYHslzVb65BzdT7v+WxuL06ZqUDB1f7nEwnxFsX5A381dxmncO7GPU0cW5PhhFouxrJZhRxl+rJZhVDLw5OgfKnCTg85YDsjqXMAAI3dLnxZ3YJ/LByLXrsHMSop/rXrOExGNZJjhMcmnULK1Pxgz426QdhDyGRnXlUXRRRRRDFUBM/zXTYX2gSKdrZZnIJxxu+vKjjjbW3ocsLtcWPdrePR1udColYOivDiioJkzlqKth5oCRREU8nEONkTWkvGn4ksxt1TswGAUav+FHC68ZvZ6cYTs4vQwiOGeWxGAbptLkHehwjUwrj38lw88ekhLJ9dhN9vPMD7O69vP4YJWfHoc3rwzLxSNHbZMCEzFiAAo1qLdIMKDQYVRsSqGIs6un5Gemz/fB0lf88dIiKHCYL4iKKoawL/PRvAXwF8DeBpgiCepijqn8PUvnMCttKqxezEB3ub8Idf5ocQC5v2NTOLboBLULaYnXhtez1GjxgjaK7OVhjTOytPzC7meP7WtFoYYjjY1mLVdaPh8fWbt+9vtmDxOz8wv8+nnuNb4NPkRXAbwxWxY6vZdh7r5Cjw8pN1+Mvn1XhydjEUUhFDlj96dT5q2/tVvvTfTvY6eM8zmIqUQKgvZ4/djZxEDf5zz2T02F3ISdCgzexArEbO+b3JuQloNTv67TgkIkFLAJGIQH6yLsS6I/i+nC0kC6gak/TCSpmhpmsmauRo7XVw7olSGt6PTymV8CphhVS9qTEqXm/fVL1S8ByCPoFh1EzC1cX5SetIFqlysYgJZujff/7Lo3ivcqJgu2JUMt5riRGwiehz8l9HsP80G0LF9cakx5wzFaeQmlUjlwimKolF4Cj5h/ouJurkHJJ8075mLJ1ZiGWbDmHjnibcdJEpxOPs8wMteGVhObptbhjUUihkIpjtfqJw0aQsTqV7oXE+uLuYjEpoFVL89UsuIZEdPzRVrUhEICVGEURoN6DF7OSMkSIRgV8WJcOgkqGqoRs+0q+Oe3h6PgqTdYP2yY6k4OJPARKJCFflJyJGKcWPTb3wkcATAcuklV8cRYvZr66xu71IFrhHMQFLouD5W2g8KU7R47pxJrz3fQOemVcKl8eHEbFKtPc5mKC7x+6GUS0VVLcfbe/DTReZIBGJsPlgC9IMSjR0OXD/+0O3BYni/EBqjCJknFpSkYPUmDPzDmoVEiRoZVi7cCx67B4YVH5/f20Y32wASBDwlx9IcRxpdoLN7cUXhzvxxeFOzue/Gp8R9nyjErRo6A6yh4hRIi9BOBMniiiiiOJ8Bd/a5alri5Fm4F8zJugUcHq8+Oet43Cy2wG5VIx1O+px3TjTWSn0lqhT4PcfNGJBOTjx0SPT8/DQlaOQoFNARBBYsbmfGF48NQceHxkSbyXr/fMjXVxaIRUhK66Yk0l3oSLSjVM2jGoFrE4vkmNUeHNHPcMx+Uhg7bZjeHxGoSDvMypRG5gnKTR0OdDR50KL2YkNVY34x8Kx+P5Ejz/zZncjphclh8S6Y03cTMSRCRqMTIgSv+crItWOmVj//TCAqRRF3QrgFwDuDXcgQRAjCIL4iiCIwwRBHCIIYknQ3+8nCIIiCCJO4PgVBEEcDPxvAetzgiCIPxMEcZQgiGqCIBZHeG0M2aiQipjB5tn/+gvDsQmJh6fn45dFyfhs8WRcmhuHFXNLOH9fdd1oZBnVTOE4+m+b9jXjidlF6LG7sflgC1bOK8U/Fo7F7ypGoXJ9FX71yneY/sK3kEkIVOT5lV2/npAeQrrd996PUMkkIb+vkPqr0Ydb4LMhJsD7G/kB4iD4moJ/l/7NZL0CFOUv5Fc5ZSTq2vuY32wxO7HyixqUpsVwiHH6v5dU5IScxxSrDmkrHxlBq2I/WzwZ71ZOwGeLJ2PqqESMTNCgPMOImSUpmJhlxMluO+f3CAJ4c2cDFk/Nwfxyvzfx6i11WLO1Dqu31OGJTw/jQHMvdh7rRH2HFaZYFVZdN5r3Xp2tQnQ0RiVo8eQ1RZw2PHlNEfIShs/zTiWX4KnPuffkqc9roJYLLwyHSsIWJut4r6MwTFCSqJNj6cxCzjFLZxaGLZAl1Jdo76JgnOiyYcXmaiyalIW7p2bj9slZWLG5Gie6bILn6LTyq4C7bMI71/FqGZbN4l7LslmFiNfIeL9Pp/kGX0c4YjyRVVxvzdY6vPRVHXrs7nNK6rHHWKD/HdIpJJxNGBoKqQjlpliOkl/oXVwxtwTpAY9rkqRQ32HFzmOd8JFAQYo/wLl7ajZmj05FSowc/7lnMp5fUIrJOXFYUpGDu6dmY9GkLKzf1YCdx7ux63g3lmz4ETe9/j0efH8/ErVy/O3XZZiYaYBB1f+c2GMa3ZYnrylCdryG89nvp+czqVZAv9WEkKqOfQ31HVaQLCmyUS3Ha9vrmedKB8/Bz1YiEWFSdhyuGZ2KyTlGvHHLeEwvTIJEIgoZO4WCTaFndjbHvXOFFqsLyz49BB8JpMcqGZsJmhimxxLaqzx4bDrZbeOdv4XGE9rW5vdXFTC+4qNTYiARSfDa9nq8uaMBSyr8VaGDx4+lMwthd3nwflUTUmKUuPG173DHW3vxxeE2hhhmt+F4p/CYFsX5BZLit5MiKWEbptPBCIMa8qCxWC4VYYQh/DuvkYmxPKhfLp9VCM0AiuNWs7CPejgMdX6ncarPief+dwS+wCl9JPDc/47gVN+ZT6eOIoooohhu8G2wPfrhAXh9vpBYYfnsIpgdbqhkEnx56BTSY1UQEcDvryrANSUpZ8UmJ8OoxhOzi0Pio6c312CsyYD8RC1WbPYXdaZj8w1VjYhVy0PirfnlaSHz46MfHgi7brtQILRxOtC1sdcPOoUEMSoZVn5Rw9hMrt7iXzu4vRSOtfdhZLw6hI+59/JcPPVZNVZvqYPN7YNCKoJMIoZCKsL149JxpMXCrEH2N1uwoaoRGyonDrimiOL8RaS2EuxIVEJR1HEAoCiqkyAIUuAYGl4A91MUtZcgCC2APQRB/I+iqMMEQYwAMA1AI9+BBEH8EkAZgNEA5AC+Jgjic4qiLABuATACQB5FUSRBEAkRXhsnBb+jz4Wb39gNp4dkrCLEIqAiL4HxiaTVmGUkheJUPSdtHwAenp7PEE1iEVBuisXEjFiMyzBgb2MvHvj3PiyalIXXtnN9Xu5++wdsXjIZa24Yg167hzdo9vh8vL9/cZYx7AKfvftUnKbHqCSd4G8MZEWQYVRjzQ1jmEr0BpUMt15sQnFaDH7/wX6un9v3J/D0tcV45MMDWL+rgSnmVpisw7SCJHRYufdusKq2cKpYkYiAze3De1VcpbaY8KecsK0taCTrFbjt4kxsqWlnCn8Vp+kxLT8ReUladNtc2FA5EXa375yk5zaZHXgx4H9M39sXt9aiLN0wbGkYQvYNXTYXcsCvrIlV8yuGYlT8ZKdEIsI1pX6z+VazE0l6BQqT9WEtHEYY1EiJsWHlvFLY3F6oZRJoleKwC9bMuNB+H85zucvm4rXH6ApjEaGW89sWqGTCw+yIWDWOdlg51yKVEBghsKgtTNLhmXklqGu3Mv1yZIIGRWEK4fC98+ea1BOyOXG7fWi1OJmikXR7n5lbwhnTmOOTtLA43ChIGYu9jT3wkcCq/x2BVCzCtPxExrPcoJJhfnkachO0uDw/EW6vD7FqOfPejkzQgCQpNHY7OPdp8dQcxmuWLjp6HWOh019crsXsZHbRn5lXiqNtfaAoIF4jQ5JezhTWyEnQCFph8G2gDKQWGMqzFRojB5tREIk1zU8FbRYnGroceOmrOiaLh11cgx5LRCKC41WeoJXjSKsFWrl0yJYcfGnr7PufEqPAnhO9eD/Q51weH9JilbA4PKhrt0ImIXCso784q1C6YHWr5bwrDBgFPywRZI6cDkQiAhMz43GiywaZZPDvvNPjhVYh4cxr/oyQ8O1USEUwGZWMDz3gFy7IBrB0Gur8ToP9XrPxU7TKieLCxw23VuJUR0/I5ynxBrz9xtpz0KIozjcI2X/12L3YErDeMds9iNfJcaytDwe67di0rxn3TM3BmLSYs+6bLhIRkIr5i+I5PD4Up8bg4en5vDFucLxFCcQ4P4XxPBJbN771w/pF43HP1BzUs2JDOqZd9WUtchM0uHtqDv6xcCz6nF60mh14bfsJRngiIoBlswrRa3ehckoWsuLUEIv76xPRwslwdVSiOP8RKTlcShCEBQABQE4QRDJFUS0EQcgAhB1ZKIpqAdAS+O8+giCqAaQCOAzgeQAPAfhY4PACANsoivIC8BIEsR/AdADvAbgTwA0URZGB326P8NoA9C+Y2S8k2xP34pGh5KvQIpsmMYIX1CQFPPrhAdB+LnwvfqvFiUyjBp80NfMST7FqOcrSY3l/X+i6+Bb4AAR/YyDiQCQikGnU4O63f4DT47fieOrzIzAZlbjvilEcr8tV143G5aMSkBWvRovZb5/BJgOD0wzotnbbXJCKRbC7fTjRZRsyKUGrJ9lFl9QyMZ6ZW4KHNu4Psba46SIT7B4fp/AXnfp9PvjgnI1FTSRp5Banm7f6t9Ul7FMskYhQOsKA0hGDa5dIRGBydgJOdNkGTVKJRASm5SdiQ+VETr8TOoYAwWuP8daiCYLnCLYtoPtMOEVzY48dT31WzSyGKQr4dH8zchK0vM9RJhNDTBCcfvnc/NKwAd35SurxjZcKhQSXZMejus2CtQvHwukhkWlUY2SCRnC8re+w4vpXvuP00/ve+xEbKicyxDBfSn9ZOjfNKfg+KaViLH73B0YdyleU9IUttaicksUUwltQno6nWb5oc8sm42hbH+OvDAAPXpnL+17xqdwGSrM+2892qNY0PxUEW03RG5tjRsTAZFRz7jmb1CVJCh1WN460WobFkoN9//ed7MEjgfihubcaCyea8Biravfy2UXYVdfBOZ6vDUfb+lCQrPvZPdMLEbRCdjBjx3AhkneepAjc+96+kHauv024aKz/OAp3XJLNFJyllfDUAMroSMfBn6tVThQXJk519CBp1n2hn3+y6hy0JorzEUKFbBu77RhrisPjHx9E5ZSR+P/snXl4G9XV/78zWqzFlmzLm2LHdhzbWbxkwYTAm6QlAZq2gbAk0NKGNkDTviUkbWjLr5TlZSltKE1fAnQJpWxdCCUva2kKJLRA2WqWLM7mxIkdO15lW7Yka535/SHPRCPNyJK8yfb5PI8fiK3R3Llz77n3fu+55/zoCWkOiof31o9b8rZodngo2y7MtziOx7+Pd01ae57IWCW3fninvgtZRq14itvt48S1TYZBi5WVVmx69lPJGla4132XV2JWbhpMejVa7W4sKT2rH72WZOtLYngkJA7zPK+kRBgAfDvW72EYphjBRHYfDsYubuF5fh/DKDaqfQDuYhjml4P3uhBBURkAZgK4hmGYKwB0AtjE83y9zD03ANgAAIWFhUOWcSQmj0qT6/CdIKX7tPe5I7xedZpgHCGhEw41eZcLZB7++eEs+jv6I3e1Gm0DyE/XSYxGYYZB9OaLJW6O4B13pK1/WLF2Qj3shKRL266ej0vm5KIy34xuZzA28bY3jmJVdT5m5aaJcYuAs0LQwsKMMYvTGq2tjsWiJhGPU61Khb1H2vDAmnkY8Pph0Krx1HsNOKdoZCcc8S5YOY6Pq911O+W9prujhIgozDRi7rS0oLeUxw+jTo00nSrqwj1ekf9klxO3/HWfpF3e8td9mJ1nihq/aTRFvXhtajQ4jkebww1vgIef4zEzO3VIr0alHfXWwSPKcqKuUhzL0HriOF7isaAP62/Cd83JM+Ev3zoPvgCPO146IArDQl/pd/slffWPHzRhy8XlYmLBaF5usXgLTFXBNl5iaad+P4e6VvvgBpIeFVYT1GpWNq797DwTPleeM+Sm1MqKPMy1pqHIYhQ3g0fCe7815Ai+XBu/86WDePTahTje6cT+lj5JotZwz/gLZlqo/SQJ0dppoh6yY43NKR9iKdr4KXxGEIZD//3762qGvGcidnA8TtUo2ZiJxkiO+wQxmkyltuoNBGQddJ5+P3gC7hdrqnHj07URji83LClBm90ds5POSFJg1uOJb56Lpm6XuGa8fslM0Q7HYttZlsH5JZaI5MvjfUoyHqK100TGKqUcU11OL9460oB7VlfizpcOis6JSg4wT61fhOy0FInoW2QZOf1oKEL1K4NWDW8gAIsxhUToUSTRhHSFPM9HhH7geb6XYZiYvpNhmFQAuwB8D8FQE7chGFJCEZ7nX2cY5lwA7yEoAL8PIDD45xQAbp7naxiGuRLAHwAslfmOHQB2AEBNTc2QgdqGO3mMll0yVOALT04Xfp9wr1eWARYWxua2PxKBzIdCSazMNKZIjEZDpyPuhCOJJikJJdruo1C++f7g99+6az8KL62I+ej3aBGtrY7FoiYRb5w8cwquOqcQP3p+n8TzJ1qivESIN2trvG0o1ySfvCGaFzAAOD0cfhDy7Nuunh/18/GK/I3dTtl22dTtHLfg/vHaVCU4jsfeo+1ieJpYbZVSHVrNwd8rncoIF+Dl2lRo+9ewrOx9Drf14fL5+Si2GPHENxdF9BUhrvbtLx4UhUWrWYdXNy5Bl9MTtV+RZ9vIMVQ79fs5vLivRXxPgqfE5fPywbIM5lrT8NT6RXB5/SjMNMYcioFlGRRnpaIw04j509NHzLsiNCmpUhvf19yLDctmYuNfPkWPy4vpmQZsXlEGpzcgJjAc7/jjhJRo7TRZT4GEk2mUT7SaYZQPLyXg9XOy7djrHypaXWKZ3Me6PqPZmIkmEI/UuE8Qo81UaqsWYwp21jbhhiUlSFGzKM1JlSRzc3jkQxOpWCDPPPrzgHA7XWDW4+UDZyQ28d7VlbhoVvSNdznUahaXVk+LCO+ZbOOjEiM99sutH17Z14J7LqsEADz6VnBTYFZuWtS1Eg8+IeE3kTFZ7jvC9atNy8vEpNoUz3h0SDSsxD8ZhvktgF/yPB8AAIZhcgH8EsBsAFG3+RmG0SAoDP+J5/n/YximCsAMAILXcAGATxiGWcTzfFvotTzP/xTATwe/588Ajg3+qRnA/w3+/wsAnkjw2SQMZ/IYT7xIIV7ljnU10KgYSUdS8nqN9SjhSIirQ6EkVhZmGNDQ6RCNQzxxcwTDcqy9P2FxR3hPsRipph6XuOPY5fSM+fHNeBirRQ3H8eh3+9Dr8kGvUQ+Z9dUfgKznz99ujtinGVaZ4t3siDdeU7igJyziKqzKifIS6WfxivxGhSNj0eIaAyMzSI82p2xOiTAMnK3DWTcvVRS/leqwwmrGtqvnx3SkP1qbEjaP/nPKFhEL+fsXlYPjeRxr70e/2w9vIBDRF6PF1S5ViN091LNNFE+IiURdq13s70Cw7d3+4kGUZaeixe4etrfmSHt4h9ooQP7kUYALJl793dcXIs+sw5xcE9482kHtKQHCbWhhhgFNPa4xt6mJtqOx9Fh1eHxxh5cCgCKLfNiMoiHa53AcIBKtT683gP1n7Gjrc8Nq0qFqmnnIeJ2KNmacjnMTBDG5PBOLLUbJibciix53X1YJr59DrikFfQN+WRs7f3p61PXNSCBnp5++flGETbzjpYMoz03MJk7mk3ThzyYkmwudgwAQ23JOmg6PXLtADPkpxAM+f4YFdrdPkkdj0/IyePyBEXNGGc6YHMz/4kR7nwd+jotYVwue7lue+wxzNy8FxyOp17YTkUTF4XMA/BzAZwzDbAZQBWALgAcAXBftQiao/j4O4DDP89sAgOf5AwByQj5zCkANz/NdYdeqAKTzPG9jGKYaQDWA1wf//CKCYSZOAvgczorGwyZRY3OyS14sEoSOWAW+4QqBiQQyjxe5MsqFkHhsXU1MxkfwItzfbEdZTtqwxB0AMRmp0Hr64wdN+P5F5fjVm5FHv5NNaBulROUJebnIhRcR2tpIebaesjnF5IlCBJqtuw9jdp58nF4gfg/MRBLlJdLP4u3beeYU3HVpRURMxmie2WNxcmAksDk9yEpNka3DaEmzotVhrEf6YxH2LcYUON092LCsBBwP6NQsdGoWP9t9RPzeO1bNxQufHMb1S2ZK6neouNpKNmWieApOBjr6gqFkrGYdrlxYINqWbpdHjF0t/P5oWx/mWtPGLMSQHKE2qsflRUlWlaSNC94Vl8xdIFlkUXuKn3AbWmTR4+blZZKxMRltqsBYe6xajDrsrD0kTUZc24TtX1kQ9bpEw2YkMicQSGQ+5/UG8OL+M7gzLMb35dXTogrEoaFgBNw+btyOcxPEVGeyeSYONWc82NIbEV7qjlVzYTWljPrphXA7nWXUoNXulsytAGDXx81kE4dAaV2nVTMSMXjb1fOxe/NStPWFn2g0i2tiIY/G+guKxFATsToPKI2fiTolhp8gvXFpieyYyTBAhkGLT5p6I9Z2E63PJiOJxhzuAfDtQWH4TQBnACzmeb45hsv/C8A6AAcYhvls8He38Tz/mtyHGYapAfAdnudvBKAB8M6gd3EfgK8PJqcDgmL1nxiG+T4AB4AbE3m2WIh1MhnLEfBownMscYJjYayOJoc/i1wIidtfOiAbEyjcw5gBUN/uwI63G5Bh0EYMZoLBEuqos9+jaIgADGmkOI6XBPJvtbvx5HunIpIOAbEJzaNNIoJfvJ5DiXi5KCVDMIxgBlyb04NragojvJK6nZ4R89ANJai9D/1uE+1n8Ww++QPAro+bImI6LxpMgCXHWJwciFrmGNsdAwbNPS7ZOjzd7cIpmzOqyC5Xh8KR/oJ0A2aGJcFU2hgSCBf2iy1GlOSkipOWG5aU4JG3jkjq9d5XD2Hb1fNjFiaAofvyeHlCJNsm2GhjNmhQZNFH2JaSK6rwxDdr0O304XS3C0+9HwzFUGQxojBzfOtE2HQAgoJVhkGDT0/3IsAFxbibl5dFeANNZs+a0SLchq6qzo8YG8fSpsbLWHusVlhNEeL5UCdvgMQdIWxOD2763EwYUjRivP/C9JlR5wRA0Mb9/WAbbvnrWdv7y7Xz8cXK6PO5/Wfs4gIaOBvjuyTLKCajlCM0FIyATsOOyXFugiAikZsfh3omJqtNj0a0MX52rgknu5yikwPLACadGmU5plEvV/jabdOKUnj9HK47vygikXe6QYMT7f2YkR2ZjJpQXtdtWFYS8bvXNi3F4pIsyfUzsoz45dr54tjX4/JCp1GhIEOHJ9cvwoBC+LTQdYHVrMOhVvl8UKFrKsHhIkXNosvhgc3pkfXM5zgeB1p6YXN44fYFkGEIhqGSGzN5HlhbUyAKw6HPOxH7bLKRaMzhdABbAZwHYCWALwH4O8Mwm3me3xvtWp7n38UQSgvP88Uh/1+LQaGX53k3gLkK1/QC+HKsz5Ao8YhyiR4Bj/c+QzFeR5PlBJdYk9TtWHeOOFi02t14+v1gdvgKqxlluakRQq3S7lJHvxs8HxlHJ8OgRWe/R2Lgtu4+LDkKGZp0CIBEhB5vL7J4Bb9EPIcS8XJRSobgCyjHDIxXhNKq2Iig+dv31mPnhsWK18S76Eykvsain3W7PFg9vwDHO/rB8YCKAVbPL0CPywNAvv2NxckBJeKpx26nB8/VNkd4Rt/2xdmwmvU40eEQQzfEc+QvlmSEsQj7LMtg+axclGanYmFhBmwKSQuPtPVhVXV+zPU73uK9XP8DkmMTbCyxD/gkxzGB4Lu47YUD2LCsBNv3HBdDiTz53inc9sIBzJ+enjSTUK1WhaWl2cg0atHv9uLz5VmwOb2oa+1LmqRXE3XDIdyGxhrHfDRIJDzEWHtnJXLyRiCRzYtUrQoBMJJ4/3ddWgHjEJvSDZ0OcXEMBN/hLX/9DLNyl6A0VznkT5vCmNre5456v0TCVREEMXoozY8FGz8WNl1gLMZHtZrFFyusKMy0x22bh0v42o3jAW+AxyNvHZfY4If21GPjhaV45K3jMW3WjQQTLVGoUrvlwk4Sy7VhoZ0ZtCweXDsPLq8PVpMB3S4vup0+7PjXCRzrcESc2gnXpTatKMWOtxtk1y7CmirDoMW6xUURmkC4Z76SB//ug62ymsLO2ib88JLZ4zYPm+wkGlbiEwC/BnDToOfu6wzDzAfwa4ZhGnme/+pIFTDZiGchn2tKifB43byibMikVvHeZyjChbE8kw4BDvjwpE0yAIXGeXF6/SiKI+mOHMNJUtcWJky22t3Yvuc4/njDuQCCZTdoVZLrook7oX+zmnW47vwifOOJjyIMnJD0T8UCK2bnoCo/HYBUhJYzdmPtRRav4JeI55DVrEeRRY9V1fnigvKVfS1RvVxCkyGEHiddWZkn+/lENkFc3oDss7u8AdnPC8Sz6EykvhL1eopnQmjQqODw+MX2KtgUvUZ5ETyeSc3iqcdckx49Li8yjVrRq8GoVWHAx+HmZz+NmBjIHfmTs2EqFkMeOQ4X9ossety7ukpc7IeGeSjOSkVxVioaOh2KcV5VLGKu3/EU75X631xr2rgK1uNBpkGL9xtsUSfcbh+HX715DDcsKcGjbx0fl0loNHuhVrOosJoHN2Q+kQhQl1VNQ7N9YEg7M1qLpIkS3kYOJRs61jbV7+fwwmctuOMlafKeK+ZHDw9RkKGX9c7Kz9CPWlmHCqUzktjdftlcB0+uPzfqdSdt8qf7TtqcUcVhq0J7yDVFf//DEc0Jghh5lGw7z49t8t+xHB/H0jaHIrd28wbkk5C6B5OT3vLXzzDHOjLzTqW5k5wTy72rK1GaY4RZr5XMlZJFRFZqt+FNRS4EZ/hpmbsvq8DtLx1Ao20guLG6qgJ/+agxYs4frktxMo53wtplUbEF266ejyNtfbLOXOGe+dE8+J/5oFE8xZ1p1MIX4LCyMk/so+Oxtp3sJCoOLwsPIcHz/GcALmAY5lvDLlUSE+tCnhtcTRZmGiTHN8pyU2NKajZSgkG4MawpzJT1ortkTi7+Wd8hHpnOMGixtqYA5TlpmGM1JSQSx+pJGf6sVrMOaXpNRKcvsuhhc/rwkxc/wqrqfBRm6sW/7/q4OWJ3KfReoeVYW1MgSXoVauBa7W48+tZxAMAFMy1gWSZCvF5bUxBh7MbaiyxewU+pPbX3eRTvMSc3DTddWBYRV29OrvLxo/BkCEN5zw4VlzueZx9qYRYPw40NGGsc6HgnhL0DvoiEbQ/tqUd1gbLn0XgmNYunHgWvqvr2fmzfE+yDN11Yisffle5Mh04s8jcsRlV+uri5FRqrSnjWX66dh2sXFUnih4eHIQkV9rudHrT0urHhmVqJUCwkChUSUdmcHvzsimr8+IX9ku/dWduEn11Zhf4BH3YfbB1yAjnW4r00+YpKtv89tX7RlNuRr5pmht3tU1woCgheRToNC4tx6I3eRFBKkCN3yibcXihtyOSn67H+yf9EtTOjGZt2vD3kh0O4DX1lX0uEB+hY2NSDZ+yiMAwE6/COl4KbbfMLlcNDpKhVsuPGRXNyh7znRPD27nJ4Ze2VzeGNep1Oo5Lt77oom61A0FaEx2a8Z3UlqqcN7QE8XsIMQRCRyM2PhXncWCZrncjjY6yEz3V3fdyMOy+dG3XOJawX4q2D8DkUx3No6h6ICGm5siJPds50x0sH8cCaefjqYx+Kn+M4fkxj90dDaV2nVTNifYbPSziOx8EzvRGnZe56uU50eHD7ONz9ah0eWDMPm/7yqWTOb3N6sPHCUuSadLAYtdCqWfxe5t1lp+pwyuZEhkGDqnyz7Ngc7pkfzYM/9BR3uDMQJeweHRKNOawYW5jn+ccSL07yE8tCPlTwEUTW2XlpmJMXu8g6EoKBnPC0Y12N7AC0c8Ni7G+2izF+wz1jE9nBjNWTMift7LNazTqsW1yEn//9cERCuHtXV+GOlw6IMYtuXFoiXicEVA+PESzcK7QccruX0eo61Gjt+rgZWy4uH3fhJF7Bz2JMUfDi1ireo9k+IBtXr6YoY8QSrDUpxOU+HRKXO5zCDIPs0czCDIPis8TLtHT52IDWKF7Tiez8xzsh7Hf7ZevL4Y7uNa1VM5JNKq16bBb38cRYFLyq9jX3itcoHd8Wfr/nSAdaet1YWZGHUzanaMNC6/Noe3/E7+TCkAie5QDw9cc/Eu3RNTWFEqE4NJZmkUWP33xtIerO9GHAx2FnbRNuuXgWbA4vrn++NqYJ5FiK93LHwuTq1+WVz2g9mXfktVoVLii24P4rpIndNq8ow9PvN4qfE7wzNq8ow+G2PhRlGKImoYqXaAly7l1dNaS9UNqQOd3tGtLOjGZs2vH0kB8uSgl3FxZmjGliv5beAdk6bOkdiCoOh7770Ouae1woi+IhO1G8vaeZ5efLQ8XyzTRqZE/3ZRo0Ua/TalW4vHoaSrKMomhePc08onaAIIjRJ9S2CxvmgmfiWG6ETeTxMVbC57o9Li9YBvjpFVX4SVgy3Wc+CM65dBoWbn8AXm8gZvsqN27dsWoudrx9QnYOpDRnGvD6JZ/rd/vGNHZ/NJTW2gAkYTtDT4bvrmtDgOMV11Sh/x4YXAMIc36O49Ha6xZDgAgh/+6+rAJ3vVwnmR+ctDnEpHibV5TG5JmvpHmdX5KJK+bny2pnlLB79EjUc3jKEstCPlTwEcIh6DQsXtu0NOZGOxKCgZzwVNvYLWsYWu1u0YP2yoWRnrHDCWkx1FF+FQtxgh567yffOyUJ8eDyBrCqOl/8e7i3sNLuUng5wo+D7/q4WTHhHSA1Wq12Nzr63eMunMRrFDnwsnF7eCi7uCY6WYknfIMxJf643E09Ljw86D0qhK54eG89FhYqi9bxkpaill00pumUF42J7PzHW8fKorWyB+Mpm1McqEOveW0MPBLijbGoVrNYUJgh2j6hrEoTiwAHsY7b+9yyx5yUjj4phSEJfSfhtjA8EVWjbQD//adPsHPDYgz4ArhqYT5cXj/W/Pb9mCeQYznBkTsWJle/hZnj520+nuh0alw+Px/V+WYcbuuDTq1Cq30APa6gB6JOE4xl2uvy4unBxHTTbtBHTUIVL9GO1ymN36H2QmlDRhdmU+XszHBPTERjPMPbjARy49pYJ/bLNGrj3uQFAJ2Wlb1OO4S300TxZtOo2IhY9XddWgGtKvrzGTRqGLUqycapUauKKS+IVqsa0X5PTFyOHD6Ez69aK/u3adkZ+PMTO8a4REQ8JEOS1ok+PsZC+FxXr1Fh07OfwqzT4OGvLIDD44dOo8LPdx9Gqz24zv7+ReW4+5U6/HLt/Jjtrdy4de+rh0TvWAFhDqQ0Z9IPjgPC53pdvlGbHyWCUruV+51QJ7++duGQp+N0GhZGrVoy5z9lc+JHg17XQPC57//7EWy5qAwPrpkHY4oKRRYjWAZY+dA74ueeq43UV+Q885U0r/NLsqKuhZKh705GSBxOgLnWNDy1fhFcg9kcizINkmN3sQg+Qx3VE4zo3M1LJfEzY0H47mPt/bJCiby4pMfh1j7oNKyit163MxiCYKSPFwoJ525YUoLCjLOhIsJDPOSadFCx0hAQQozg6nwTynLThiwTx/FgGUi8w3pcXpTlpuJvNy9FpyNSnAk3Ws/Vnh6XI6XhxGMULcYU7D3ShgfWzMOA1w+DVo2n3mtQjAUMJD5ZiecYap/bJyta93l8it/f3ueG1392JGMYwOvnhxSt4ylXW9/ZNikI0E+/34gFhemYMUJCLxCsY7m4zkp1PDdPXmydGyWhzXh6JCQSYzE8xENZTqrkKJgwsRC8C4RnyTXpoGIi7Zvc73QaFgwYfNrYDac3AIfHj1xTCiryzJJ2H24LlWzjgC8gZgPefbA17gnkWE1wwtuCUjieGVnBePNTcUeeZRmUDo4lR9r6kKpT4bHrauBw+3Gi04Hte+rRaj+beGqoJFTRcAy4cagtGCM715SCuXnGqMfrlMbvUHshtyFz7+pKPP1eg+Q75Wx5PJ7+8TKe4W0mC2kpalkRNDUl+lQ+RaXCD78wC7/4x1Hxuh9+YRZ06uieWBPFm62x24W/fNgozm/0WjV+//YJfPtzM1FVkK54XVufG7/5V4OYqC/AAb/5VwPK89IUx3mCCMcHFnmXbZH925mXt41xaYiJyFQZH0Pnuu+f6EKjbQDAAO58uQ7XnV+EeQVm/OCS2XB5/Oh0ePDke6fQandHnWeFz6N4Xj6OcfheoTAHkjuNeteqCvz+7ROSz+k18s5MIzE/Gm2EsdzH8RFi7d2XVeDX/wxqLcK/reYUqFgW753ogtPrR5pOjQyDVjL3dfs49HkC6Gvvx5JSi/hOQ+tH0HeeWr8IHM8reuaTF3ByQeJwHMgdVXjk2gU42t4v+d1j62qiLuCE79m6+zBWVedDxQLnFmXi/BJLhGhyqLU/riN9oWW8eXmkO/8r+1qw9arqiLg7FVYTOh1ubF5RBrcvILnOatZh/QVFOGUbEI9bj+TxwlyTDj0uLx596zg2ypRZqLtiixHnFmVK/t5qd+Pxdxti8oIMD/exYVkJKvPNyE1NgcsXAMMAi4otETFtTtmcyE7TYueGxXB5A2Lc0bE+UjocCjMM+MYFM1Df0Q+ODwpm37hgRtRQDIlMVuI9hpqdqsO9tYciEthtv2aB4j2EhILhXr15UWIOx1uu0DYpMJQwnpMqH7ojK0pc0sIMgyRMwVAhMliWQXaaFg+umQen1w+jVo00vSpq24tXgB5pEomxGDqBXMjxqMo3o73PDa2ahc3hxXc/V4quwc2qUPtQVWCOmPhUFZgj2vHmFWW4/7VD+GKVVfLZ+y6vxKoKKx65dgH2N9uRb9Zj84pSPFfbLE6KlN7xvtM9aLW7YVHw7kuGCWT4hk+r3Y2dtU2i53O4LZvKO/JqNYvKQWGpodOB5h6XJKs2MLxY544BN1472Ik7X5bGLV0w3RQx/q6tKUC+WQ+PP4DHrqvBf051g+OD/fjWlXMkNlluQ2ZOrgnGFDUOnoluy+P19I8HmvwPn/KcNLTYByT2X6NmMCtHOTQEAOSla1DiNmDHunPQ4/Qhw6hBgOOQlx49fMJE8WazmnQ41uHApr98Kv4ulr6ZyDhPEPGg5FV8rP44lFwzErmGmNhMxfEx/FTu1t1H8fT15+KHz++LeZ4lN4+67/IqFFn0aLQNwGrW4cqFBTDrVKgqSIdWxcLt5yRzJ5ZlxDlTq90Ns16DX75+BPtb+iRzJY7jR21+NNoIdf3o3nqs/68Z4mmZCqsJbx1pxT2rK9Hr9CHdqMGfPjiJ6ZklONxsxy/+cVQMj3rLJeVo73Pjjx80iZ7dQvOMFh6ix+VFdlrKkGsJ8gJOHkgcjkK4pyHPI+KoglyMy9tfOiArwIa652/dfViMnZthCB4J7BnwosJqFmOrJHKkL/QalmEihJKvnFuI+dPNsjFpls/KRWl2KmwOL6ZnGnH7iweQYdDiuvOL4PAGsO3FA8M6XqjkuRkqQr59tAN3rJqLe189FFF3LMvg/BJL1LqNRni4j7/WNgePtfzlU1nBUElQPG+GZcIZseZeF5p7BsS2Kghkzb0uFGcpxw++ZE4udm5YPJiZNej1GW2yIrRtQewFgK27D2N2XppsXc3KTsVNny+TCiSXVUZd7AY4yCbXuWSu8rQ53r6UiDA+4A/IhqJw+5XjATf1uGRjWCmFyDhlc+Lbz3wSMXGKtjkSrwA9FnAcj6Zup+RUhFI8dqGvFVuMEf1x84oylOWmRtiwhYUZ4smOGVnBdzZ701I02pz49HQvnn6/EVcuLIhoR7e/eBCl2anw+vmIvvL0+414ZV8L7l1dKSaF0mlY/HLtfBxu68MPnw/apJoiM+65rDJsspocE8hii1EUvoVNojlW05De3FOdYosRbX2uiPhqsSahkuNQm1NsI8DZmO5PX78Iv1w7D7f8dZ84/gpJYq87vwjfevpsLOutV1Xjkjm5Ef1GbkMmloVnIp7+8TAe42ayZBcfCbRaFS4sy8H+M/a4Yt129fvR1ueN8DjONKYgP135uonizZZogriJ8nzExEXJq/jA1g0jeg0xfozUGDPR1pXDRc7+qlWIy5bLzaNuf/EAfvP1c/A/Lx/ENTWF2FnbhGtqCiUJecPnTqFzJo7j8cCa+RFzpVAReTTmRyNNqOZiTFGL88on/n0SG5bNBA8gz5yCmhnZ+PYzH0s8iZu6nKIwHJ6DSji9+ZVzC2HUqjAtQz9keAgaUycWJA4rICcMPrhmXsRRBbl4lo22AeSn62QFWCDo3i/Ezo2W/C2RI32h1zi9Aez6uFn2aPzikqyI72BZBsVZqSjOAhYUZmBhYTo6+z34xhMf4calJUOWJdqx/aE8N4UQGp809eKhPcfEWMM1RZm4oMQiMeCXVk9DVb457t3V8PqUE4dCBcOJEm8vFtr7PLKC6sLCDEVxmON4vH64PS7PdZvTg2sXFUkSCX7/onJ0Oz2ydXa0sx/P1UqPgz79XgNm5SkH+O/ol+8XnQ63YhK7ePtSIrv4zT0DsqEoSrKMqFRYgSuVq71Pvlzxfh6IX4AebTiOx96j7ahvd0TE+Y43ed9De+rxt5vPxnI/a8Min0vIiLt9T9BLTClERJ/bJ3ufX6yZhyNt/SjLMUpse3iM4dpGO4BGPHP9InQ7vaM2gYwnTEooHp9U+N5ycTn+Wd+B5bMiRUYiCMsyWDwjGwUZTjy9fhE6HB7kDTMJVXufR7b9vXu8C+U5aXh14xLYnF5844ngaR258erWXftRlW+OqR/HuvBMxNN/uCTalofC7+eSJrv4SJFIrFuXNyAKw0Cw7dz9Sh2e+Oa5Ua+bKN5siSaImyjPRxBEcjJSY8xojYHJjJL99U/nYrblSvOo/gEfHlwzD+v+8BFuWFISkUcp2twp2lxpPOZHiSCnufzgklnYclEZpmUYMCfPhG6XB8097ojE83e9XIdff22hOO8Mr7vte+vx5PpzoWFZWFK1KMyk8BCTDRKHFZATIuo7+mOOZ5lpTBF3SoRYOUIHCY2dGy35WyJH+sKvSfTInGAcQ8WoWEJlyAmJAHCgpTeq0MqyDDgeYhxgocxyXpGJ7q6G142SOCQIhhMl3l4sOAezrobi9nFwef2K1yQijqeoWFEYFq751ZvH8NyGxbKfb7W7UdtoR23jp5LfR4vPOhL9IpZr4m1nVrNetr9FCydg0Col5JOfCMX7eSD54kaesjllT1wkmrwv2qZAOOHtQK4u3T75eGVH2/vx+LsNuGphvqRdyMUYrm20o9vpxRcqrTGVK17iDZMicMrmxC1/lfbpbW8cw4++MAunbM4JZ9fGEpZlUJiZisLMxOqI43ic7HKisdsJo1YNq1k+DE2AA37w/D7s3LAYHM/HPF5NVBJty7FQ12pPmuziI0UiXmo2p1e27XQ7vUPeb6J4syWaIG6iPB9BEMnHSIwxozkGjhexjlNy9jceW55rkp9HHe90QKOSzx0CTI65UzihdZ6dmhKxfn/w9aPYeGEpfvDXfXht01JYjCk42emUrZuufg90GuUcVABwjsI7ojF14jMxXSfGADkh4rnaZtx/RRV0mmC1hcazDP3dI9cuAAPgxc9asP7Jj/DucRte/KwF/z7eBb+fk8TODe94VrMONywpwbH2frAMIr57KPd8waVfp2Gx6+Nglsgiix43XViKTStK8di6mojj5BzHo6HTgfdPdKGh0wGOO5vsSxBThMRFSmU52SUvJDZ1O7G7rg17jnQoGudodR7+maHKG+1voXUDnBX2QwkVDIVnV/r7eOP3c9h3uge7D7Zi3+le+P2c4meLMo2yz1IYJclhNC9VJZQWoTaFRaiQACm8XNEEVeFo/KYVpdi4vBSbV5TikWsXxNwvhHvEEj9ZqS3JIcTrDL3HUOEEvIFARL/atLwMvoD8u/QGAvj+ReWSz3//onLFzwPJ147b+9yyJy7k+nooI/EccvYx/H3NyJLvK4I9Dm8zibTh4aJkb0/ZnACkbbfR5sC+ph68XteK1t4BMYyR1azDTReW4salJZiZnQpnlCSQxPDgOB57jrTjpX0t+KSpF5829SDAcbh3dWVE3/+/T5rh9gUTGIa3+WTqxyOF0ibkp6d7oo5psdBqlx/D2uzKdiaZ8fs5vHWsA6e7B2B3+XC6x4W3jnUMWU9ZqVrZtpNp1I5mcQmCICY1IzHGKI2BJ7ucI1rWscLt9uODUzZxnHr/RBf+cagNbreyM1KizM0zys6j/lrbjFSdWvL7UCbD3EmA43jUt/fjbwdbsfdIB+5+5RD+Vd8ptqfQuX51gRnlOanodnrA80CeWX5d1dHvwZ2r5g6pkxCTE/IcVkApqPbCwnS8tmkpup0eaFQsXN4ASrN1+NvNS9HpcCPPpMOh1n688FkLXvqsRYwrLOwGbr2qGpdWTxNj5zZ0OsT7WM26iBATj1y7QPzuWNzzw136rWYdpqXrI2L0CjuSfj+Hvx1sVfx7aPyYZz5oxIZlJSjPTcOcPJMYI5TjeBxu7VMQEj3Y8txnuHFpyZCem7F4dw7lobz3aLsknmZVgVk8Lh1eN3kmHWblmRRj4yRz7Jx4jzLNyJJ/FiEeqxwGrVo2kVk0L1Vjirxnq1Erb2oSTYAUHhN229Xzo34+3qMuiezkq9UsLquaNhif1A2rSYeqadHDCViMKdhZ2xSRkG9lpXz85OzUFBhTVGIyAZYBjCkqZKUqJ70rMOtlY3gVmPVRamz0yDXpFE9cRJtwjER/DG0HbXY39BoWVdfVwOHxIyctBZWDMbXD45rff0UVFhamS45PCYxmEi+BUK/T1BQ1elzymzAd/W5JbObynFR89bwiSazRzSvK8PcDrVhZaZWMNT+7ogoV09InrKdKMnOqy4HjHY6IONZ/P9CKDctKUJhpQJvdjWc+aBQTfeSZdZI2L2xmhIdiSYbxaDiEbkIKyWMYBuh3+/Fxkw0LCjITDt0hbNyE25lkSA6ZCCe6+uDw+HGyyynOcYqzjDjR1YdZeemK1+nUwRjD4TGHwxd9BEEQROyMxBjT1utGhkErjn0AsOvjZhxu7VPMxZGs+P0c3jzagdM9LslcZcvF5fjP6W6cPyNrREM6pep1qJiWJq6JeB545oNG9Li8yDBosO3q+di6+zA2LS+LCN850edOgPxa9ccrZyPHpMOmFaVIUbNI1arxs91Hzq7/LquA0+PH1x//CBkGLe5cNRf3hOR5EmIK//TySpTmGDE90yBZ30yWuiOUIXFYASUhQvC0PNLWLyscCTuANy4tEeMKh+4Ghsa5ubR6Gpq6nSiyGPHQnmO45ZLZ+FFIlk63j8PGP3+K1zYtxeKSrJjLHurS39DpEEUO4TuF49vFFiPea7Ap/l0I9zCUqHbK5pQNuaHTsGI4A8HzOJpxjkX8iRbqgGWA+vbIBXhp9tkYpOHHHQozjYrPlsyxc+I9ypTIs3A8h+8sK8Xdr4YsKFdVgOeVPWgHvP6I97xpeRkGfPI7xokkQEo0FnQ8R10SuQfH8XjzaEdcgnKxxYhbV86JWfD0B3g89k6DKNhzPPDYOw1YPMOi+CyH2/vw6Fv1EgH60bfqMSt3fI5WF1uMqCowxy10jVR/jNYOhInWtjeORsQ9V2qTI5HEK9547XeumitmYxYQxPXQtnvjspkRY8pDe+rx4Jp5+EHY73/8wgHMm55OR8FGgTN2t2zM9xuWlGD7nuPQaVhsWFYiCsPC5oLchuYlc/Ni3iweb2KJoyhsCsvlX7hj1VzYHD6srLQm9JxjsXEzlvS5A2izuyPmOAUZ0Tf61CoWZr0aD66ZB6fXD6NWDZYFNCyJwwRBEIky3DGG43jwDC8mng2162d6XRHhvpI9NnFdqx3HOvojwsZte+MYHlwzD3Wt9hFfd5TnmHCotT/iHczONWGu1YzZeWnodnqwc8NiuLyBpKy3RAlfq2YYtHD5Avh+WOLuDINW9HK/8+U6PLauRvzdG3VtePTahdjX3IsAF3RQ2rBsJgI8j5oiC2qKgIWFGUmngxCjB4nDCkQTIho6HYrCUagXjBBXOJTQODdC8qSCdANULIPjHf0jHhdHKTRAt9ODfrcPtY3dQ95zKFGtvc+N52ojxd/7r6gSwxm0DnpFCYLLitk5qMqXeqnFIv5ECz3BgIk76dpQz5assXOiHWVSitUb77OwDCMKw8L33/1qHXYqxA8GAL1WLesJ++CaeYrXxBvgfyxi6CZyj0QE5XgFz9a+gYjTCJuWl6GtbwCluWny19jdaLQNSGIhA9HjOo8mLMtg+axclGanYmFhBlxePwozjTF5SIx2fwx9h9HinocznCQV4eJvkUWPe1dXQaMKxqfneUS0q3tePRSxkXb/FVUothjx4Umb+NkBj3ys8QDHj3ofIs7S75Z/D4KXkNvHYa7VhN99fWHE5oJcm481xvZ4Euvpi2KLEfdfUYVTNmfEZvq9rx7ChmUlmG01JdQuR2LjJpkY8AZk5zg71p0T9bqOfjecHj/0mrNTfqfHj07HxAyvQRAEkQwMd4wRcnDI2fWNF5ZGJH1P9tjErXblsHFOj39U1h1DvYNkXMOPFOFrVbnExYIjgrCmcfs4tNoHcOXCAvzfJ804d4YF97xah1XV+VCxwP9cVomSLAOmZ5xdk03mOiQiIXE4CkpCRDThKDRG752r5sZ0dLqpx4Vbd+2PKfRCvMiFaiiy6NHS68aJTgc4Pv7j3XL36HF5RfGXYYLH3YVj2IKI0Wp34/F3G7Dt6vkRwrDAUOJPtNATp2zygdWjJV2bqIzFcVmXN6BQnwHFa3LSUvC184qw7Y1jkuNE2WnKYQ/iJZHkcmNxj2gxmmMZVKM4ZIukqFSymWOfXr9I8ZpkPFotbIwpbdqMF+ORvC9UkLaadbimphAbnqkV+88Da6ply3S8wxFhb4WEp8L7NiiEeck0ake9DxFnUUqaIvR5nYaF1aybsEnS5Ih1s4xlGSwsTIcvIJ8IkuMRsw2VY6JkF4+FAZ/8mBz+u3AsRh3ufuWQeOKE54FX97dg+1cWjGZxCYIgJj3DGWPa+9xwKqy1vAEO2aln52SJnpocS6xmPQ639snOd7pdXsy2yjuxDJfJNM7HQ/haVSmBHBMit+g0LHRaNRgmKCYLa8pwh5hk2XAgxp6J6T4xzkRLjFSYYcB9l1eix+XFb/55HHcMCsTCZ+SOTguCxFBJ3xJBLhHXvaurcOuu/eD4YAzZ8Htuvao6rnsK9+hxefHoW8fx+3caMDvPJMbnXFmRh9c2LcWzG87Da5uWDmuXM1pisUSSrk1UEkl+Fi9K7TzXpCwgFWYaUZJtxIZlJdi4vBQblpWgJNs4ou8gkeRyY3EPg1YtW1/RYjQLngBf2v4OvvrYh/jS9newu65NMfmdEKYlFLePgzPKBshYtJXJwngk7wsVpEMnakDw3Z7ocMiWyc9xEfYWkLbdx94+IYktKhwx+8O7DTGNTcTIUGk1RyRN2bwimHxusvbHWBPMAsFxQ6nvsQzgC/BDJgSdCuSkpcjWUVZq9MRyFVYTbl5ehsffbcAje4/j8XcbcPPysknX5giCICYSoTk4QtFpWMzJM0EV8ut4xtTxosJqQmlOakSy5x9+YRYKMvQ05owwxRYjfrn27FpVqS0JkosQHvLp9xrAMspicjK1KWLsIc/hBIgWG/eUzYmH956N79k34MPmFWWYnZeGIosxasy9WEIvxIvcsfVQMXrd4iIxDEBofM147jnU0fiRPAoe7V6JJF2bqIzFcdlEEoAJIQNKslJHLT7RWMSCTuQe3kBANt6yL6Ds1RWvJ0Dh4AZI+I58NPF9sh2tHk3GIwll6M6/3ETtudpm3LFqLu4NSRix5eJyVOWbcX6JJSJ+mlxS0p3fWoz2fg8sqVqAB2bnpSEnLQXPXL8IDk/sYT2IxNBqVVhdPQ0zsoxo7wu+E62aRUmWcdL2x3hOX7AsA7NeHZEYZfOKMuSYUnDHSwfwxDcXJY131Hgx4PXLxrd0K8T0F6AxgCAIIvkothgxx2qKyMFx56q5+M0/j+O2L88RT9iNxanJ4aJWs/hihRVH2vtQlW+GyxtAaooKJr0Gs3NNNOaMMCzLoGJaGratnYdDbf3QaVT4wSWz8ODrR8W2tPXKauSl61CQrodOq8bT7zXgkgorAhyP6ZmGpG9TxNhD4nACRBOO2vvk43s+u+E8xYVNqCARS+iFRMobLs6GitFXLiwYthg9lrF5le6VzAnkRoPRPkaTaH2ORVtIxntYjCmy8ZZXVuYpXhNvGINEN0Cm6pGreBkPGxJq/4HIMD89Li/6Bnx4av0iuLx+GLRq5JpSxJMZSs8R2naLlPMVEmOEVqtCTXGm5HeV+enjU5gxIN6NFrNei9+9fQIbLyxFdmoKDClqtPa60NHnQaNtgOJhA1CrVHj2o0Y8sGYeBrx+6AcXereunDP0tTQGEARBJBUsy8CSqgXDMMGEoR4/Oh0ePLz3OHpcXolINx7OC4mgVrOTem6TbLTa3TjU1o/fv9MghqcLdzIEgOzUFHT0u7H1qvlQsUBbXzDJ8URoU8TYQuJwgigJR4ns7I21IDHaYvR4kqwJ5CYqVJ+xU2wx4taVc+IaZOO1F1NtA2Q8GOs2H/pOu50ezMwy4scvHJB4nz/7nyZ8oSIPJdmk8hITg3htlZz93LS8DM980EieLIPkpKXgkgorfvT8vlGL6U8QBEGMHRZjCn7w130RyabDQzzS/J+QI9ekE0OEbt9bL+o6W6+qlug64esawSO9MNNIbYqQQOLwCJPozl6sggTH8Thlc6K9zx1xnDhWaIAhkomRaNPJQCL9KtHQHSTYTy5C3+n8Ag6W1BTUNnYjwAW9z29dOWfYO/mTpZ8RE4d4bJVgP2fdvBSH2/pwrL0fz3zQiB6XN6k8WcazH4XG9Of4YCLKWGP6U/8nCIKIn9G2ncLG6Nbdh4cM8UjzfyKcwgwD7l1dhSOtdvxizTw02pyoLkiPOUQotSkiHBKHR4jQwWOuNQ1/u3kpOh2xC6+xDD5C8qpwISlagrfQ77WadQhwQEf/2XuEGwNaQASZjPXg93Ooa7Wj1e6G1axHhXV04j/FU3eJtOlkJt5BNhFBOZH3OBnb83jg93M41GrHGbsbaSlqGLUqdLm8yE7VjVh/UqtZLCnNQkGGHh39bly1MH/Y72uy9TNiYuEa8OJgWz/a+zzINaWgMi8NBn1kEjWWZTAzJxUzsoyYazXhgpmWpNq8Hu9+xLIMzi/OgEmnEeuyIi81pvkl9X+CIIj4GAvbKa4D8tJiXgfEOqYSkxu/n8N7DTYcabXDmm5Ao82JqnwzFhdnQq1mJevFIoseHh+Ptr7R1QCIiQ+JwyPAcAePWK+PN3lV6PdmGLS47vwiScD78HsM5zkmk/g0GRdSfj+HF/e1RCSyuXxeftTBId73Gm/dxdumJyPxCMqJvMfJ2J7HA7+fw0v7z+AnISEftlxcDr1GhXtfPYSbl5cN2Z9iZaR38qmfEeOFa8CLv9W1446Xztqse1dX4ssVuYqL2WT1ZBnvfuQa8OK1uo646jIZyk0QBDERGSvbGc+Yl8iYSkw+OI7H3w62YtsbR3FNTSF+GBJu6r7Lq3DOdDMOtvbhh8/vR3lOKr56XhHufqUuLg2AmJqQODwCJCLahgpuPI+Yro83eZVQrgyDFj/+0hwxTp3cPTiOx4GW3oQGQb+fw98OtuLWXftHRXwaa+E51vc5kQTxula7KCgCwWe6/cWDKMtJxbzpGbLXJCIqxtsX2vvcKM9JxY3LZmLA44chRY3H3j4xKsmHxsJzerTbRF2rHQ/vrReT3gHAw3vro75HEgZix+/ncKjNjtZeNwxaFTKMWjHD8qFWuygMA8F63PbGMWz/ygLc9qW5uP+1Q1Hfw3gS79hBECNFXVs/7njpIDIMWly5sAAMAzT3uFDf5cS86RNrITve/aiurR+PvCW1/4+8VY9iiwHnzlCORz7e5SYIgpiIJKPtTHQcICYXp2xO3LprPzZeWCrGqgaADIMWTd1OpKhZpOk0uG91BaZl6HH9k7VxaQDE1IXE4RFAafBo74scPOQEtwfXzItp8Ik3eVV7nxsZBi3WLS7C8Y5+xXsUW4zYXdeGI219cQ+CHMfjvQabKAwL14yU+DQeXo+xTAYmmjdmq13+mdrsbsXs5YmIivFOpKxmHb56XpEkwc5dl1YgzzSyyYcS9ZyOh7FoEzanJyJpxablZeh2ehSvScbJbTIi5xm8eUUZTnY58cUKK84o9KGDZ+ywmvW4/oIZUd/DeJJIolSCGAk6HV5xHhJqtwoyDCjNMsConzjJ1Ma7H/V7fLL23+HxRb1uvMtNEOPFtes34ExnT8Tvp2Vn4M9P7BiHEhETiWS0nYmOA8TkQtB4ck06sX1azbqIudbmFWVgWAYZBi1a7W7xerePQ2sUDYCYuoyLLznDMNMZhnmLYZhDDMPUMQyzOezvtzAMwzMMk6Vw/VaGYQ4O/lwj8/ftDMM4Rqv84Ri0aug00qrUaVgYtKqIz8oJbvUd/bLXhw8+QvIq4bNDJa/KNemwtqYA2/fWg+OheA+hTNE+o8QpmxO1jd2K4tNwURIoT9mcw/5uJYTJQCjh9TAe5RoOVrNe9pnyzMrvNpqoqEQsdReKzeEVj7kI33/3K3WwObxRnydelDyn61rtI3aPsWgTJp1WskPs9nHYvrceaTplD7x438lUpU7GM/ihPfWo73CgrtUOk17ezgc4BNusyxv1PYwn8Y4dBDFSmHRqcR4S2rfueOkg6trGbJo2Iox3PzJqNbL236DVRL1uvMtNEOPFmc4e5F22JeJHTjAmiHCS0XYmOg4QkwtB42nucYnt88qFkXOth/bUo9HmwtqaAsn1Og2LrNSJszlPjB3j5TnsB3ALz/OfMAyTBuBjhmHe4Hn+EMMw0wFcAqBJ7kKGYb4MYCGA+QBSAPyTYZi/8zzfN/j3GgBj6iPvDQSwaXlZxC6eL8BFfFZOcHuuthn3X1GF20I81uQGn3iTVxVbjCjPSYPbx2HXx80RZRTu8eFJ25CfUaK9zy2KyqOxszoeXo/CZCDcAzS0HiaaN2aF1YT7Lq+M8JytsJoVr0lkxzyWugulVaEe2/qGv7EguU8CntPxMhZtwuvnZO8hZ2sE4n0nUxWlNsLxQJvdjfLcNGxeUSaJ275peRme+aBR/Fy09zCeJJL4kCBGgjxTCmZkGRVOVyWnp70S492Puhwe2Xq0DXFiYbzLTRDJxpHDh/D5VWtl/0ZexYRAMtrORMcBYnIhaDw/fe2wqN0wDBTXMcWZBnFNr9OwuGtVBSjcMCHHuIjDPM+3Amgd/P9+hmEOA8gHcAjArwD8CMBLCpfPBfA2z/N+AH6GYfYDWAngOYZhVAB+AeBaAFeM7lOcxWJMwc7aJjH+D88DO2ubsLIyL+KzcoJbj8uLhYXpeC2GwSeeoPUsy2CO1QSdhkWr3Y1nPmjEDUtKoGKBFbNzUJWfDpZlxDJF+4wSuSYdXtnXEiEqb72qekTEp/E40hPLZCAZjxpFQ61mcfm8fJTlpKLN7kaeWYcKqzlqSIVERMV4J1JWhXrMHeGwEoLndPh9onlOx8tYtIk8c/z1lYyT22REqY2wTLDeiyxGzMgy4sE183Csox8BDnjmg0a02t3i50a63Y4kyZrki5jclGSnocvpVbBbE89rZTz7UU5aimw9xuL9Q/2fIM7iA4u8y7bI/u3My9vGuDREMpNstnM44wAxeRA0nh6XF8980IiNF5aiYppJcR3T1ucW9Z1zijLw8J5jeGDN/PF7ACJpGfc9A4ZhigEsAPAhwzCrAbTwPL8vyiX7AKxkGMYwGHbiQgCC799GAC8Pis9jRrHFiFtXzsHj7zbgkb3H8fi7Dbh15RxZEU3piEphphEl2alYXJKFkuxUReGG43g0dDrw/okuNHQ6wHF81LLNyDp7v1a7G4+/24DZeSaJ6BtaJqXPDPXsgji+aUUpdqyrwZcrrSMiPg11pCe8Pvx+Lq76UUKYDCi9j2Q8ajQULMsgTaeBSa9Bmk4z5PsRRMXXNi3FsxvOw2ublsYUP3eougulapoZ966ulNTjvasrUT1N2aM5EQTP6dD7DOU5HS9j0SYSvUc872SqUmE14WdXVEnq9odfmIWynFRUWM1gWQYXzc6FJTUY4+vxdxtEYXjLxeWoLjAndf8niPGAZRlUWlNxj4ydT1Gz8HoD41zCicPcvFT5cSwvOUQLgiAIYnShcYAQEDSeHpcXD75+DI++VY+fhq1jtlxcjpqidMzIMqIoU4+qaWY8vOcYrl8yk9YshCzjmpCOYZhUALsAfA/BUBO3IRhSQhGe519nGOZcAO8B6ATwPoAAwzDTAKwF8Pkh7rkBwAYAKCwsHN4DDBKPZ95wvPgSSXgVy/2GUybx2ry0UfFKjFa28Poosuhx8/IySeiE0UoSNxbemCPZVhNNljbaO+Ysy0CnYbFhWQk4HmCZwV3OEX5fiXhOx8tYtIlk9AIeDZs6HnAcD5WKkbTF7LQUXFSeI7YTtZrFeTMssJp1eGr9IvS5fUjXa5CdloLCTPLGTmYmSzudiKTqdfhyRQ5Kss5DS+8ATnQ6sO2NY+hxeXHP6kpcXj0NWpkcDVORaO1Uo1JDq5aOl1o1C42KcksTYwvZU2KiMNnaKo0Dk5NE2inLMrhkTi52rKtBbWM3Ahzwj4MteHL9ueh1+WDSqeH2BVB3pl8SEu+Bq6pxyZxcWrMQsoybJWEYRoOgMPwnnuf/j2GYKgAzAOxjGAYACgB8wjDMIp7n20Kv5Xn+pwB+Ovg9fwZwDEHv41IAxwevNzAMc5zn+dKwa3cA2AEANTU1ibmVyhBvuIdEBDelhFezNy2N+l2x3G84IuBYCIhy3x9eH6uq8yOSjsVSPyNdrpFiJNtqom1ntKlrteOHz++POAJTmGnAvOkjGzpcrWYxb3rGqGZmHYvjZ8l2xG20bOpYs/+MHT+SaYt/vOE81BRnir9jWQbFWakozkqO+idiY7K004mKUZ8CwIlbd0n72J0vHURJllHSx6Yy0dqpko2adoOe6o8YU8ieEhOFydZWaRyYnCTaTpt6XNjwTK2kPbxd343XNi0FALz4WQt2vN0gWf//aNd+VOabk2YdSSQX4yIOM0H19nEAh3me3wYAPM8fAJAT8plTAGp4nu8Ku1YFIJ3neRvDMNUAqgG8PhiDOC/kc45wYXiiM9GSoI024fWhFIh9qtZPKMnadsYiURxBxEKbQh9pH+HkiAQxVaE+Njyo/ghCnmvXb8CZzp6I3x+rP47I7C8EMXGhcYAIJdr6nucBjidthIiP8fIc/i8A6wAcYBjms8Hf3cbz/GtyH2YYpgbAd3ievxGABsA7g97BfQC+PigMT3omWhK00UapPqh+IknWtjMWieIIIhbGKjkiQUxVqI8ND6o/gpDnTGePbIK5A1s3xP1dRw4fwudXrY34PQnNRDJA4wARylDrexVD2ggRH+OSkI7n+Xd5nmd4nq/meX7+4M9rYZ8pFryGeZ6vHRSGwfO8m+f5uYM/i3me/0zhHpNuO2QiJkEbTcLr45V9LRFB+qdy/YSSrG1nLBLFEUQsVE0zRyTNumcUkiMSxFSF+tjwoPojpgLXrt+Az69aG/Fz7fr4hd5E8IFF3mVbIn48/inhh0QkOTQOEKFEW98XW4yoKjBj84qypFv/E8kLRS+fQCRjMqrxRK4+CjMMWFiYQfUTRrK2nbFIFEcQsaDVqnB59TSUZBnR3udGrkmH6mlmSpRFECME9bHhQfVHTAWUvIDPvLxtHEqT/Ch5OgPAtOwM/PmJHWNcImI0oXGACGWo9f3yWbkozU7FwsIMuLx+FGYaMSNr/Nf/RPJC4vAEI9mSUY03cvVB9SNPsradsUgURxCxoNWqKKEHQYwi1MeGB9UfQRChCJ7OcpCgPjmhcYAIJdr6npJoE/FC4jAhC8fxOGVziruSyeBlShAE9c2xhuqbIGKD+sroQ3VMEARBxAONG0Q8UHuZ2pA4PEkZTsfmOB6769qw5bnP4PZxYnyalRV5ZBwIYhyhvjm2KNX3XGsaWu00aSIIAbJNow/VMUEQBBEPcuPG1quq8eVKK4XwIyIYjXkGic0TCxKHJyHD7dinbE7xWgBw+zhsee4zzN60NOlCEhDEVOJkl3zfnHXzUszMob450ijZwg3LSrB9z3ESZwhiELJNow/VMUEQ8aAUj5hiEU8d5Oaxt+7ajwyDFktKs2juSkgYaQ2INrUnHiQOT0KG27Hb+9zitQJuH4eOfveUEIdph2tsofqOncZup2zfbOp2kjgwCsjZwgyDFmU5adi4vBQAsHX3YczOS5sStpEgBMLt9hm7i2zTKNPY7USGQYsrFxaAGRwid33cTHVMEIQsSvGIKRbx1EFpTV/b2I3CTD04HrT+IkTa+9yy84xENSByOJx4kDg8CRmuuJtr0kGnYSXfodOwyEnTjXhZkw3a4RpbqL7jw6hVy/ZNg5ZM+WgQbgutZh2uO78IP3x+n9heNy0vQ7fTQ5McYsogZ7fvv6IKRRY9Gm0D4ufINo0sZp0G151fhIf21Iv1vnlFGUw6zXgXjSAIgkhClNb0eo0KnzT14rYXDtD6ixAR1jnh84w8U2Ia0FR3OJyIULCZSYgwEIQSj7hbbDFi29Xzxe8QBoxii3HEy5psKO1wnbI5x7lkkxOq7/jINaVg84oySd/cvKIMuaaUcS7Z5CTcFq6tKRAnTECwvW7fWw+NioZSYuogZ7dve+EA/t/KOWSbRhGNiomwPw/tqYdGRQt5giAIIpJiixFbr6qWjM2blpcBgCgMA7T+IoIEOMjOMwLcEBcqMFxNihh7yKVjEiIIGuHemLGKuyzLYGVFHmZvWoqOfjdy0qbOURPa4RpbqL7jozDTiLLcVGxYVgKOB1gGKMtNRWHm5N+4GQ/CbaHLE5Btry5vYJxKSBBjj5Ld5sCTbRpFnF55++Mk+0MQBEHIwLIMvlxpRYZBi9rGbgQ4YGdtE354yWxafxERdPTLz+86He6EwlcNV5Mixh4ShychIyHusiyDkuzUKTdATOWQGuMB1Xd8sCyD5bNyUZKVOuU2bsaLUFvY0OmQba+5CR63IoiJiJLdnp1rwpw8E9mmUUKp3sn+EARBEEqo1SyWlGahIEOPjn43rlqYD54Hrb+ICEZ6XT6VHQ4nKnQWdpIiCBqLS7JQkp1KnTBGpnJIjfGA6jt+qG+PH9ReCUK5H8zIMpJtGkXI/hAEQRCJEL52mJFF4wkRyWjMM2jdOrEgz2GCCIF2uMYWqm9iIkHtlSCoH4wXVO/EROPa9RtwprNH9m+NJ4+jaEZpxO+P1R9H3mgXjCCmODSeEHJQuyBIHCaIMKZqSI3xguqbmEhQeyUI6gfjBdU7MZE409mDvMu2yP7twNYNsn87sHWD7OePHD6Ez69aK/s3EpQJIn5oPCHkoHYxtSFxmCAIgiAIgiAIgkhKfGCjCs3E8EnE03tadgb+/MSOEblPIt9FEARBjBwMz/PjXYZxg2GYTgCNCn/OAtA1hsVRgsqRXGUA4i9HF8/zK4dzwyHaarwkSz2GQ+WKj5Eu12i30/Gux/G8/1R+9pG+/2i20/Gup3iZSOWdimUdVltNcnsaCpVFnolSltFsp4mSLHWXDOVIhjIA41+OsVpLjfdzypGMZQKoXHIk25o/Vsb7XdIabWxRbKdTWhyOBsMwtTzP11A5kqccyVCGZCpHoiRr+alc8ZGs5VJivMs7nvefys+eDPePlYlSToGJVF4q68iSTGWksshDZUmcZClvMpQjGcqQTOUYbZLxOZOxTACVazIx3nVGa7Tkaa/seBeAIAiCIAiCIAiCIAiCIAiCGHtIHCYIgiAIgiAIgiAIgiAIgpiCkDisTLJExKdynCUZygAkTzkSJVnLT+WKj2QtlxLjXd7xvP9UfvZkuH+sTJRyCkyk8lJZR5ZkKiOVRR4qS+IkS3mToRzJUAYgecox2iTjcyZjmQAq12RivOuM1mhJAsUcJgiCIAiCIAiCIAiCIAiCmIKQ5zBBEARBEARBEARBEARBEMQUhMRhgiAIgiAIgiAIgiAIgiCIKQiJwwRBEARBEARBEARBEARBEFMQEocJgiAIgiAIgiAIgiAIgiCmICQOEwRBEARBEARBEARBEARBTEFIHCYIgiAIgiAIgiAIgiAIgpiCkDhMEARBEARBEARBEARBEAQxBSFxmCAIgiAIgiAIgiAIgiAIYgpC4jBBEARBEARBEARBEARBEMQUhMRhgiAIgiAIgiAIgiAIgiCIKQiJwwRBEARBEARBEARBEARBEFMQEocJgiAIgiAIgiAIgiAIgiCmICQOEwRBEARBEARBEARBEARBTEFIHCYIgiAIgiAIgiAIgiAIgpiCkDhMEARBEARBEARBEARBEAQxBSFxmCAIgiAIgiAIgiAIgiAIYgpC4jBBEARBEARBEARBEARBEMQUhMRhgiAIgiAIgiAIgiAIgiCIKQiJwwRBEARBEARBEARBEARBEFMQEocJgiAIgiAIgiAIgiAIgiCmICQOEwRBEARBEARBEARBEARBTEFIHCYIgiAIgiAIgiAIgiAIgpiCTGlxeOXKlTwA+qGf0f4ZNtRW6WcMfoYNtVP6GYOfYUPtlH7G6GdYUDulnzH6GRbUTulnjH6GDbVV+hmDn2FD7ZR+xuBHkSktDnd1dY13EQgiJqitEhMBaqfERIDaKTERoHZKTASonRITBWqrxESA2ikxnkxpcZggCIIgCIIgCIIgCIIgCGKqQuIwQRAEQRAEQRAEQRAEQRDEFEQ93gUgkguO43HK5kR7nxu5Jh2KLUawLDPexRJJ9vJNNsaivumdEiOJXHsCQG2MIGLA7+dQ12pHq90Nq1mPCqsJajX5ESQL9H4IInE4jsfJLicau50watXINaWgMJPmAwRBTA3C10iFGQY09bhofUSIkDhMiHAcj911bdjy3Gdw+zjoNCy2XT0fKyvyksJQJHv5JhtjUd/0TomRRK49PXLtAnj9PLUxghgCv5/Di/tacPuLB8W+ct/llbh8Xj4JkEkAvR+CSBy5+cHmFWUoy03F8lm5NB8gCGJSE24Diyx63Ly8TDKnoPURQbNJQuSUzSkaDABw+zhsee4znLI5x7lkQZK9fJONsahveqfESCLXnvY326mNEUQM1LXaxUUCEOwrt794EHWt9nEuGQHQ+yGI4SA3P3hoTz32N9tpPkAQxKQn3Aauqs6PmFPQ+oggcZgQae9ziwZCwO3j0NHvHqcSSUn28k02xqK+6Z0SI4lce+J4UBsjiBhotcvb4zY79ZVkgN4PQSSO0nyT40HzAYIgJj3hNpBhaH1ERELiMCGSa9JBp5E2CZ2GRU6abpxKJCXZyzfZGIv6pndKjCRy7UnFgNoYQcSA1ayX7St5ZuoryQC9H4JIHKX5JsuA5gMEQUx6lGxg+L/JHk5tSBwmRIotRmy7er5oKITYM0JCp/Em2cs32RiL+qZ3Sowkcu2pqsBMbYwgYqDCasJ9l1dK+sp9l1eiwmoe55IRAL0fghgOcvODzSvKUF1gpvkAQRCTnnAb+Mq+log5Ba2PCEpIR0iYa03DU+sXweX1ozDTiBlZyZO1kmUZrKzIw+xNS9HR70ZOGmXVjIfwDKVD1d1Y1De9U2IkUWpPAOJqY/H2FYJIdmJp02o1i8vn5aMsJxVtdjfyzDpUWM2U7CxJUKtZXFY1DcUWI9r63Mgz6VA9jd4PQcSCMD8o37gEJ21O6DQqZBg0mJ1rovGdIIhJD8syuGROLnZuWIxWuxtWsw5zck1YWJhBa3BChMRhAoB8Ft9tV8/HjKzk2j1iWQYl2akoyU4d76JMKJTe71AZSceivumdEiOJUnuKtY0l2lcIIlmJp02r1SzmTc/AvOnjVFhCEY7j8ebRDrJNBDEMjnU4qA8RBDHl4Dgerx9ul7V/tAYnBMjdgAAgn8WXMlZOHuj9EkRsUF8hJhvUpicH9B4JYnhQHyIIYqpC9o+IhVHzHGYY5g8AVgHo4Hm+cvB3vwBwKQAvgBMA1vM838swjAXA8wDOBfAkz/MbFb7zfwB8C0Dn4K9u43n+tcG/VQP4HQATAA7AuTzPU7rFGFHK4tvR756Uu0nDPTY+0Y6dJ/P7nWh1Od5MtfoKfV6DVg1vIACLMWXUnjuZ+wpBxILfz6Gu1T54bFAPjueoTU8C2vvcKM9JxY3LZmLA44chRY3H3j5B75EgYoT6EEEQU5X2PjcyDFpcubAAzODy6e2jHejs90yZNSUxNKMZVuJJAI8AeDrkd28A+DHP836GYbYC+DGAWwG4AdwBoHLwJxq/4nn+wdBfMAyjBvBHAOt4nt83KDb7RuQppghCBsvQBeRkzVg53GPjE/HYebK+34lYl+PJVKsvuefdtLwMO2ubcOvKOaPy3MnaVwgiFvx+Di/ua8HtLx4U+8y9qytRU2RGbaNd/By16YnHtHQdvnpeEX70/D7x3d51aQWsZnqPBBEL1IcIgpiqWM06XHd+ER7aUy+xfz/atQ+NtoFJv6YkYmPUwkrwPP82gO6w373O87x/8J8fACgY/L2T5/l3ERSJE+ESAPt5nt83+H02nucDCX7XlEQui+9kzVg53GMVE/FYRrK+34lYl+PJVKsvuefdvrceq6rzR+25k7WvEEQs1LXaRWEYCPaZO146iFsumU1teoLT6/Th7lfqJO/27lfq0OskXwiCiAXqQwRBTFUCHERhGDhr/1ZV54v/nsxrSiI2xjMh3fUAdiZw3UaGYa4DUAvgFp7newCUA+AZhvkHgGwAz/I8/4DcxQzDbACwAQAKCwsTKvhkRMjiO3vT0kmfsXK4x8bH6tj5SLbVZH2/dIQ/PpKxvkbTpio9L8OM3nMna18hhsdUGftb7fJ9xj7gw2vUppOeaO20VcEetvW5MW/MSkgQE9eeUh+aekzUtkpMLcainXb0K6+pQv9Na/CpzbgkpGMY5icA/AD+FOelvwEwE8B8AK0Afjn4ezWAJQC+NvjfKxiGWSH3BTzP7+B5vobn+Zrs7OwESj95YVkGJdmpWFyShZLs1Em7cBSOjYcSzxHb4V4fKyPdVpPx/Y5VXU4WkrG+RtOmKj0vz4/ucydjXyGGx1QZ+61mvWyfsZp11KYnANHaqdK7zaMj8cQYM1HtKfWhqcdEbavE1GIs2mm0NVXov2kNPrUZc3GYYZhvIpio7ms8H9och4bn+Xae5wM8z3MAHgOwaPBPzQDe5nm+i+d5F4DXACwcwWITk4jhHhunY+cjB9VlfEy1+pJ73k3Ly/Dq/pZJ/dwEkSgVVhPuu7xS0mfuu7wSFVbzOJeMGC70bglieFAfIghiqiK3prrv8kq8ur9F/DetrYgxDSvBMMxKAD8C8LlBETfe6608z7cO/vMKAAcH//8fAH7EMIwBgBfA5wD8agSKTExChntsnI6djxxUl/Ex1eor9Hnb+9wwaFXwBTisrMyb1M9NEImiVrO4fF4+ynJS0WZ3I8+sQ4XVDLV6XA6KESMIvVuCGB7UhwiCmKrIrSELMwxYWJgxJdaURGyMmjjMMMxfAHweQBbDMM0A7gLwYwApAN5gggFOPuB5/juDnz8FwARAyzDM5QAu4Xn+EMMwvwfwW57nawE8wDDMfAA8gFMAvg0APM/3MAyzDcB/Bv/2Gs/zfxutZ5vocByPUzYn2vvcyDVNTUMgHBtPNKbOcK8nzjLV6zLe/jjV6iue5yXbRkx2YmnjajWLedMzMG/6OBWSGDUSfbdkGwkiCMsySNNp4PIGkKbTUD8gCGLKIKypii1GnLI58Z/GbuSadFhUbCFbSAAYRXGY5/mvyvz68SifL1b4/Y0h/78uyvV/BPDHOIo4JeE4Hrvr2rDluc/g9nHiEYKVFXlkFAhijKH+OHJQXRKTHWrjRCJQuyGIINQXCIKY6pAdJKJB52imGCe7nKIxAIJZKbc89xlO2ZzjXLLkhON4NHQ68P6JLjR0OsBxcYXJnpJQncXOKdvY9MfJ8k6iPcdI1OVkqScieRlOG2vqduJIWx9uXFqCjctLkWHQ0vhNDMkpmxNbdx/GDUuC7ebGpSXYuvswtRtiUiNna8dqzjUSZSUIghgNYrWDHMfjVJcDHzbYsPdIO050kG2aCoxpzOGpRDIe4eM4Hodb+0RjIOD2cejod0+ZY+qxQjtr8TNWdZaM/SsR2vvco94fJ0s7Huo5hluXk6WehmKy9J2JSLxtLPRdWc06fNLUix1vN4jXblpehmc+aKTxm4iKzenBNTWF2L63XtJ2bE4PtRtiUqJka7PTtEm3Bpoqcw+CIMaP0PnkgC8wpB3kOB57j7ajvt2Bh/bUk22aQpDn8CggDPRf2v4OvvrYh/jS9newu65t3HdbTtmcqO/oF7NUCug0LHLSdONUqvFltD0Rk4mx8EwYizpL1v6VCLkm3aj3x8nSjod6juHWZej3W8063LCkBEfa+nCgxT4h25Yck6nvTETi6YvCu1r/5Ed497gNB1v6cNsLByTXbt9bj7U1BVN2/CZigwEjCsPA2bbDgBZ3xOREydb6A3zSrYEmyxyNIIjkJHzuv+90r2gHrWYdbrqwFJtWlEKvUYvrgVM2J/Y320VhGCDbNFUgcXgUSNaBvr3Pjedqm7FpeZloFHQaFvdfUYVii3FcyxYPIyVyDiWURPNEnGiMlSg0FnWWrP0rEYotRmy7er6kP267ev6I9sfJ0o6Heo7h1qXw/VazDusWF+Hxdxuwfc9xXLPjfUlfmcjHPydT35mIxNoXOY7HgZZeNHc7sWHZTDz+bgOOtPfLXluemzahxm9i7OlyeGTbjs3hGfLaiWzviKmLkq1ts7tx7+pKbF5RCqs5uKG89arqcbWhk2WORhBEchI+93+uthmbV5ShyKLHNy8oll3vtPe5wfEg2zQFobASo8BYHBVPhFyTDj0uL575oBE3LCkBwwAsAywsTJ8wxwNG8viVklAye9NSlGSnip6IgmB05cICqFiIO2vjXWfxHA8f6llHitA6Exhpr4xk7V+JwLIMVlbkYfampejodyMnbeSP+eekyb+T7NSJ5W04VNsabl0K33/lwoIILzuhrxRbjBP6+OdI9h0KT6GMUt3EYh9Dx7gblpRg25tn26LctXPyTFTvRFQyjVoUWfRYVZ0PZrCpvLKvBRkGbdTr6Lg7MVExaNWy9lKjYvH95z6FTsPijlVz0TfgQ366btTbc7TxcizmzQRBTF3C5/6tdjeefr8R278yH+v+8FHEemfWzUuRa9JBxQRtUYZBiysXFoBhABUD5JnINk1myHN4FBiLo+KJIHjW9bi8ePSt4/j9Ow2YnWdCYebE8ToaSc+3cGMpHCU/1t6Phk4HCjMM2Hb1fBRZ9FE9CceDeD2Bx8ozYSw8Yceqf42VxxTLMijJTsXikiyUZKeO+CJFxQKbV0hPC2xeUQbVBLP+sbSt4dSl8P0qVnmnfKTsz3h5441U36HwFMoo1Y3fz4HngQfXzJN4rYW34dA2xjBn2+KujyNP/Wy7ej5mZE2c8ZsYPonYDp7n8J1lpXj83QY8sjc49/vOslLw4KJeRycNiImKNxCIsJeblpehudcFINiW7331EAZ8AWQaUxS/ZyTG6qHGy7GYNxMEMXWRm/tr1Qw8fk5McGw1B9cBbh+Hpm4nii1GVBWYcdsXZ+O684vE+cPv3m7AodZ+mu9PYshzeBQQBvpwb4vRHOhj8eKK1bNuJD3C/H4Oda12tNrdsJr1qLCaoFYnrkpFEzmLLcaIcgOIabdeOEoemrBl29XzccmcXOSn63DNjg9G3es2HuL1BB4rzwSWZXDJnFzs3LB48J3rUGE1R20/8baRRPtXPO06UY+pRPrOaHtgCjvEwmkBngeefr8RCwrTUZyVXJ7W0epiNL2sOY7HyS4ndGoWF8y0iEm/BIS+Eovn7VDteTy98UZqbBqrkwgTCa83gP1n7HB5/bJ185uvn4P//uPHYr3ff0UVFhamozBT2obD25hgt1vtbjzzQSM2LCvBgunpKLIYyVt7isFxPP5+sA23/PVs//3l2vn4YmV026FTq3H3q3WSNnn3q3XY+a3FUe/X3ueWeAwBwU2KWE4a0MkCYjyxGFOws7ZJMu/ZWduEVdX54meGCssjN1ZvvaoapdlGnO4ZiHlNozRepl1XA7Neg7QUNTIMGuzccD58gaBYTf2FIIiRQpj7b919GF85txCzclPR7fLhxqdrRdsmJDjucXlh0KrBsgyWz8rFwZZeXK2ggRRmGFB3xo4W+wCyUlOQa0rB9AyyXRMdEodHATkRozDDoChc2pweaFUsXN5AQpPoeMQGwbNOaWIf/l1FFj1+fmU1WIaB0+tHUaYRM7JiK5/fz+HFfS24/cWDYrnuu7wSl8/LV5xMDbWgUBI580y6iDp45NoF8Pp5xXoJFUqUjpK/tmkpXN6hs3qONfEeDx8LQVX4/D/rO7C/2Q6OBw639qHT4cHyWbmy1/n9HF74rAV3vHS2jdy7uhJXzFduI4mIhPEKcomIX4mIfmMhFArhZB5967j4u/E+ycBxPJq6nWjv84h2pSjTgNcPt0eti6HsV6JlCbd5d11agbtfqZPtK3L2h+eBj07a4PD40OP04ycvHlC0eSe75NvWrJuXYmbO6NqTkRLYJ1Nol5HA6w3gxf1ncOdLB3Hj0hLZuvm0qUfyzm974QBe27QUHMfjcKsd3S4fnB4/slNTxDYmeAsLY1OPy4vZeSZ8rjyHJt9TkBOdDlEYBoLt6Ja/foby3CUoy01TvM6lkJnc5QtEvV+eSYfrzi+SZCrfvKIMuUOMHRSOghhvii1G/OgLcyQbKZtXlOHp9xvFzwwVlkduHnjrrv3YsKwE2/ccj2lNAyiPlx+e7Mbv32kQy9Xj8mLb1fOxsDCT+glBECOG4LjFMkBTtwufNdslTjBuXzBJ7YZlJdBrVEhRs/B6A9BqVXAqaCDtfW580tQj0XjuurQC09KdWFpKc9SJDInDcSInlgHy3qmCiCE3Uf7duoXodfmx7Y2juKamMMJjVZhExyLOhU9gMgxaHGnrg07DoiTLiAAHdPTHJu6FfpfVrMP1F8zAZ6d78dCeemQYtFhbU4DynDTMsZqGFInrzthFowEEjcntLx5EWU4q5k3PkK3boRYUSiJngEPEJG6/jPHbuvsw8tN1ohB/yZxcvLZpKY4pJPsR6i3Z4oHFW6ZEPHoTWeA1dTtR3+4Q612YkJdmp8p6qR48YxeFYSBY53e8FGwj8wsj20g4fIynWuIVexMRvxIR/U52ObF192HRuwUAtu4+jFm5aYrXxCvYj8dJhmhwHI+9R9tR3+6QiA471tUk5I2ayAbGKZsTbb1u6LUs3H4OR9r6cOPSEuz6uBmNtgH89l/H8eCaeTCmqJBp1MIb4HDK5hRDzYTW5ZaLy3GsrR8/230ENywpwePvNkS1eY3dTtm21dTtHHVxGBgZgT0ZbeJ4ILSljn437gyxY3J1Ewg7we/2cTjT60J7vxttdjdOdTnxXG0ztGoG96yuxJ0vHUSr3Y2dtU3Ysa4GGhVDHphTnJNd8rbjZJczqjicZUyRbZNZUY7TA0C/2xeRqfyhPfX4r5mWqNeNx8kC8lQmQuE4HhzPYfOKMmQatEjTqZGmU0OrDraJWMLyKM0DhdPUQ61pBJTGS54/26duWFKCR986PuVP4BAEMTo09bhwqLUPO95uUHRiKEjXw+0L4OAZOzodHhi1KnC8/JxWo2IjNJ67X6nDr66ejwMtvQk7PBLjD4nDcSAnlj1y7QIAwP5mOwxaFQrSDTjc2ofZeWfFUznx1uXhsO2No7jlktn40fP7ZCfR4cmPiix63Lu6KmKRGDqBCQ2PkGHQRnh9DCXuhX7X184rhM3lxY63G5Bh0MqGXZD7LsErsKnHFWF8Mgxa9Ln9eP9EF6xmnUS45vlIgTd8oiR4vs3dvFTiddjRHzmJC8+yaTXrcE1NoRgiIvQZAHnjJ3jWJZO4BsQv+HEcP6RXZjiJLPDa+zyyi8mFhRmy4nBL74DsANXSO6AoDgviouCdrGKAqgKzondysFzyk/z2PnmxNxHxq0lB9DsdRfRrtbsiNoc2LS9Dq90lew3H8XjneAf6BwJwevywOb043RN9l5ZlGVw0Kwd/vOE8tPW5kWfSoXpa9I2B0eSUzSm7cVPb2B3XOwLi38AI/bycfRSOVTXaBnCkvR+z89Lw33+S2gthQ6nR5sSnp3uRrlcjTafFz6+sRk6aFu8c68D+lj7JM7Ta3UjTOdDe54ZOw8q2LbWKRUOnY0JMpJLRJo4lXm8ARzv60enw4LPTvSjJShXfZ7i3r5D4aMfbJyTfodOw8AZ4fPfp/0S0v0ffqscfbzgPfo4blSSVxMREyXaExxIMx+MPRJyGuOvSCnj80T2Hz9jlx81WuxvV05WvG87JAiE8S1ufG1aTDlXTzNBqVVGvGY6n8kiHPiOSg7pWOx58Peh8c1dIu//pFVXIMmowPXPosDxK88CF09Px8FcX4LG3T2B/Sx/a7G7Mi9Ifii1G/HLtfIkXs2DrgWDfEJwD5PoJtVGCIIZLe59b1EX0SnMJrRq/erMeWjWDm5eX4ea/fIoMgxabV5RFaEl9bq/sOO8NcNj07KdYVZ0PFQucW5SJ80ssUKtZySauQauGNxCARSaMjtzp0lhPrRPDh8ThOAj3qr1yYQE4LnjU76XPWnBNTSF+MCj0hk5OwyfKVy4swOluJ66pKcTxDmWPVQCS+11TU4gNz9RGfH/oBOZr5xWKcbZm56XhhwrCs9IEXfiuDIMWuSYdGruDAq9S2IXw7xIm6Ufa+lCemyYxPlZz8Ijit56ulRVmHlwzL+YFxaHWfslC4LF1NRH3mp0nvX+0Z4gmdoxmrNPhoFUz2LCsBBwPsAxEjwg5EhN644832Of2yb7DPrdP9vPZafIeTdmpyh5NjTZ57+SZWamYoVAupczVBoVFZ2GGAfddXhkREqUww6BYLmOK0j2UzaxWrYpok9v31uPp9YtkP3+6x4kzvZ6IRf7pHieKLPLP7vdzePnAmbjCu4wmoROUUJR2p30BHhzHy25CHWjpjatdh/aDKxcWRGxkbN9bL3r/sgwkJwqE735t8Lvb+9z455EOfG1xEb4fYjfuurQC+LBRFIh1GhZGrRovfdaC52qbsf6CooiJ1uYVZTjYYse3nq4d9ePXI+Fhl6w2cbTx+zkcarPjTI8bXo7D8Q4HOB7INGpkYwOX5aTBoFXhb/taIjaB7r+iSuzHgLT9PfrWcdgcHnyh0jrOT0wkExkGDe6+rAJ3vXzW/t99WQUyDJqo1/W4fPjtv45L4q/+9l/Hcd/lVVGvm2bWy4fxMkc/IZDoyYLQ8CzC892zuhKXV0+LKhCfssmfwJmdlxZVjE4k9BkxMWi1u7GqOj9ifvWTFw7giW+eG5NnbrHFiK1XVePWXfslY/VPXjyIHpcXd62qgPaTJkl/CB1fc9J0ULFAp8MDgMeGZSXIT9ejpXcAz3zQiFZ7cJ0neBEL/x/aT6iNEgQxEuSadFAxQJFFj1StOmIdsml5GX722mG02t246cJS0eYIeWs2LCtBdb4ZJdmpKLYYcaDFLjvOa1VsxHx361XV+OLcPHxwqhu1jd3geOCVwXnxztom3LpyjuTEvNzp0geuqoY1XScrJhMjC4nDMSAM9oJQEOqd+4s188QjQUrCY7gwxTCANd2AHz6/DzcuLVGcRIeKyrEIm1t3H0ahxSB2SqVjA9HEPeG7jrT1obnHBRUTLE9o1vRo3yWILzcuLcGOf53AXasqxEQoa2vOijFywkx9R7/8QsSkQ0OnQxQz5DyMb3/pgDiJE4TnX/zjiMSDS8VGfwY5j2SB0Yh1OhxO2ZzY+OdPI+rqtREMk2A167D+v4qx7Y1jonHecnE58kzKC7wMg0b2HSotXrUqVlYo00aZ9J6xD8h6J1cXmBXFYSFzdbiHri/8rPcgTT0uPDwo1AiL6Yf3Bj2gownjP145GzaXV/Qch25MAAEAAElEQVRozjRo0eeRF8YBwOaQ33ntdnllP99u90QISne/Uoen1y9SFIfrWuML7zLa5Jp0SNWqItrJK/tacN/qStweIgxsWl6GO146gCe+uUhxEyqedh3aD5RsmooFNq8oQ2GmAff97bDid+eadNiwbKa4ISj8/e5X6vDgmnnY+JdPxfb8o1370ePyYtPyMry6vxVrzimQbOwYNCr8dnCzYzSPlSbiaR2+0G21nxWVBU/h9r7gIncyT9hCF+mbV5TBGCJWHTrTh61XVeHWXcFY0z0uL6wmPR57+wSOdTjwwJp5+OXrR/Crq+cjwPGYYzXheKcDjbYByT0ED7JYBDhi6uH2cfj1P6Ui76//GQyBEw2Hx49G24Ak7jwAONz+qNcJtjB8fFYP0ccTPVmw/4wdj75VLxF5H32rHiVZRtQUZype19XvkT2B0+XwRLWj4zE2UviLscFq1uNQq/z8wOaUn1+Fw7IMvlxpRYZBC/uAD/Ud/Xj6/bOi7t2v1uHxb5yLCqsZgPz4+tMrKpGTpsPR9n5wPPCnDxqxstKKnsE5XmgsZGEzpMCsF8ug1EYLMwzISiORhCCI2Ci2GFFVYMYcqwnf2xk8PXnDkhIUZko3rKxmHQoz9RLb2Wp3Y/ue49j+lbNOc+kGNe66tAK//ddx0Ut4fkE6uhzuCL3q1l37YdZr8J2QpMyblpeJSUK3PPcZLOsXITstBTwP2dOlP9q1X3TeoRwGowuJw0MQOtjfvLwURRa9JBSEy+MXF3RKIoWKZaQiJRP0fnT7IhPOhE+iBQEl/PsFz+Vj7f0AgEvm5CI/XYfT3QOSThmv94bgEabTsPjJCwfxnWUl2LyiDG5fIKbvChVfjnU48JePGvHAmnkY8Pph0KrFv6Wo2Yj6eq62GfdfUYXbXjibzOmRaxdEeAnLeRg32gaQn67Da5uWorPfg2888RHcPg7PfNCIG5aUwKxTYUFhhsTYyD1D+L2S1QDFK/Ym4snjD/D404eNkoXanz5sxPJZOYrX6DQq2cWkTiPv9dPRH9yRDF3sPv1+I2ZGWdD1u/2yz94fZaFrMaZg75G2YFv0+GFIUeOp9xqwsjJP9vPtfW7ZxXQ0MT24ieGUeDRvubgceVHqOMcUn+d0l9Mj++xdTo/iPVqjHA2OdhRytCi2GDFvenpEO/nKuYVI0bBiWzBqVQhwPC6dl4/Ofg9Y5qwwyTIQN6GitWuO43Gyy4lGmxM6LQsNKz1KJXft+SUWWAeFuZ4wkT70u4stRtSdkV98Bjgej167AEfbpYtJwTP0N/9qwP9eMx89Li8OtPTht283iJ8ZatNmOCidIMjfsDgiPpjcQjc0cc5QCT8nAwMDPhxo60N7nwe5phQ8PBiuqSrfhAMtfRF9/Y83nIcTnQ7otWr8fvDIMQAwAH54yWyk6VRYVGSBVquCzemRbX8sA9x3eaUoOBCEQHu/R3Zcau9Xtv8AkJ2mVRhntFGvO90zIDs+z8gyoiI/XfG6RE8WdLu8siJvuB2OgIH8CZzr5U/gCLTa5U9HDRUmAADcbj8OtNrR1udBnikFVVYzdLroSypK1Dd2VFhN6HF5FeYH0WNth6JWs1hSmoXXDrZi+x5pv3P7OPS6vKIHr1wIwY4+D37ygnTDe/fBVtywpARFmXoUWQywu/z43ooycV46K/fs5oTS/O2kzYnrnviI2g9BEDHBsgyWz8rFv451iGvAR986Ljo89ri84gnvM70DsrbzeKcDp2xOlGSn4kyvG68fbMXGC8skSeXvXDUXGQatuKYBgjbrk7CkzNtDHLDcvmCCTj/HoWKaGWU5abhxaQmA4JgMBJ0kCzP0uHFpieRkEG24jjwkDg+BMNifPyMTpTmp+M7nSiWhILoGF3hAsOOU56TixmUzMeDxw6hTY1q6Do1dA2Koh6BXkAozsozQaVi02t3YfbAVD6yZB7fXj5LsVMwvSAfLMhLvC+H73b6g5/I3LyjGr948JplgZhg0aBhMWGI162DUqnDHqrm499VDErGV5yEb81foUCzLoCjTiB6XF7s+acZNy8tg0LAoWF2JO146KElMx/OQHPkWRMhQ0XvToAedEPohw6BFWU6q+P/CxFzFADXF6WLStIIMPfwBHl957IMhPYxriswAGBxr74eKZcS/tdrd+L9PmrFucRF+8Py+qEJ8okcTx4Nckw5FFj1WVeeLZX1lX4ui2JuIJ09r34DsQq2tbwClCslv+gb8+KjBht+tOwc9Th8yjRo88e5JzJ+ervAcevS4vJLFrk7DItekPHm3GLWyz24xKi90CzMM+MqiInFTZ6gwEYmI6Tq1Km4xnWWAewf7lVCue1dXglVwnM5PN8iWa1qIp0k42akKyYiihO4YScIFtqo8EwBEiA5/P9CKH3xhFh5/92yM80feOg63j4vI6H3/FVXIMGijbq7JxabOT9eJ4UJ2fdwcIVD/9IoqLMhPh06nBsfx2Hb1fPzh3RO47oISDHj9KMw0SLx6pqXL90MVyyA7LQWH2/px1TkF2PVxs7jIYxiIi9YMg1aSwE54N4kmdhtqkqS0qbTnSIeYfV1YbMoJyQ/tqcetX5gFS5oOLBhsee5Tyd+H8nqeSJM414AXrx3qwMN7j2FVdT7qO/px92WV0KgAjmciTi9se+MYHruuRjzyLyCIEToNiwqrWRQS5uYZcc9llbjzZWnfnzstDbNyKKYkEYlVYVyKdpoHAGbnGmXHmdl50T15s1NTZMfnWMaORE5bZeg1siLvM0OIvJ398pumnUOI5tMz9bjpwpno6PeIY8RNF85EQYbyeAoEheF/He+EL8DD5fGjvR/odnbic6XZUQXi4STqm0i2MxlQq1ksLDThvsurcPuLZx1O7rmsEnOHaPfhsCyj2PdyB/ue2+2PCBM4VOiqx9adg89O28W1XJFFj/+5rBItvQPw+DlU5ZlgVQjtYjXr8cu189Dc7URTt1M2pwdBEEQoLMugyGKU2BQh8fH/Xj0fWjWL7/75E2QYtBH6kRAnfeH0dHAcD4fHj6vOmR5xevKeVw+J67VQfae6wAyrWSd6J1+5sAAzsgzITkvBbV+chYppZvzqzaPINekk9/3+ReXQqVn8bPcRSVm6nR4xN9fW3YdlYxwL+P0cDrXaccbuhkmvhtWkx/QMA5p6XDSmykDisAyhwf9VLIPynFR8/fxi7GvuxY63G3Dz8lKxY/3xgyZ8/6Jy/PmjRtxz6VwEwEgEqN98bSH+55U6UWQThNUUDYOfXVGF/91zDFctLMDxjuCRo5beAfQOeLF8Vi6As3FlDSFC79fOK8Sv3jwmEVaPtvVhxexcBLjgBOOamkI8tCd4v2Dsw1RUTjPjcFs/vvzwOyjPScU1iwolHTA0OdtJmwO3fXE2AKDuTFBcMaWo8NT156Klxy3x7g3duQ4VIYW4i+W5aaiwmsAwwD2rK9Hc48LPdx/Gj1fOhssXECdPRRY9pmcacPuLB8XQEAO+wJAexjVFZlx9bhG+/viHcPs4bF5RKhGeQ2Mv7z7Yioe+sgAaloGf4zEzJFOxzSl/NLHbGf1o4nhQmGHAzcvL4oqJG0+MYgBIUcUXDxcAMoxqXFJpxbefOXt05K5LK5BukDc1FVaTbGzfaF5zWakq3PT5Momocs9llchKVY5J2NTjkj2apxQmosCsxwNrqsWYoioGmJmTKhEGw+kZUPB6GlD2ejLrWJj0ajy4Zh6cgxtKGhUDk05eGBKO8YTHHM4wKsecZFlIwrvoNCzuWlWBsdCeBgZ8eLWuLUKUKMnS4ydfmoOGLie8AQ7vHOvAF6us2L7nGH56RSVSVCoc6+jHjUtLRGE1NKP3bS8cwIZlJdi+57h4OkDFAitm56AqP7i5dqrLIRub2mLU4JFrF6Kh04EFhWb85msL8enpXgQ4YPueY2AAzLGmoizbhItm5cDp8UdsKlxWNQ1vHu3Ai5824bufL42IAarTsvjh8/vQaBuQTKp6XF7RM3TTs5/C6+dlEz0kktgtFq+0nDT5Ba4QXSVUrJATkjMMWhhTNPjRYEikeE4vTCSvOY7j8WFTLx7eeyyiT//0iiqY9WrZZ+93+yJiwt6zuhILCtIjYqam6nX4UmU2irMWiRsnc/OMSNVTOAlCnqppZtyzujIiJm/1tOhe5ql6Hb5YkY0iS3xtbazHDq+fk+1XXr98+CeBPJMONUXm4CZeyMmg3CFEcwbBk0jhYwQzhDk61tmPbpcvYhw+1tmP6ijhKM70RiZpdvs4tPYORJ1jJpKIlgBMeh1Wzs1CYebwbWy0vud2+/HygVa09Lokm8XT0/Wy71vFAvddXgU/x4vCsJBX5r9Djl3fc1klvlyZgwfXzsOxwbAUFqMGc/JMaOoZgEGrQrpBg7ozfSjMDAobiXi0EwQxdZBzFrv1C0E95tBgqL5Wuxv9bp+oGfA8xDVMgAdWPfIu3D4Om1aUytq4ael6/PfnSnD/34+I+s68gnTcsWoO1CyLfo9PPFFRZNHj1pVzUHemDz/4wmx884n/SNbqv3rzGB5cMw8ZhqAD2JULC6Bmg2X617EONNmcuP6CGRLxeOtV1bi0ehpYlpGN277l4nJYzTr88Pn9Sb8eGQ9oxAgjvBH9v5WzsGHZTOxr7gXHBxfHoYG8W+1uvHGoFT+/shosA3wjpFFnGLToGDwGKIiSHp8fxzud+LjRDlOKCg+unYfaUz2Syek9l83FgeZeuHwB3PvqIayqzofDE8wqvXlFGWZkGUXPutBFa2lOGirzzZidZxITJAlxYnQaFjs3LMaW5z5DeU4qvn9JOf77j59EeDDM3bwU9gEfNv75U9z6hVlw+zm89FlLsAzeAPwBXhRlQ68L9XyYa03Dn244D25/AB4fh5JsI/Y128XEfTcvL0OjbQD9Hr/oGQgAq6rzRWH4zlVz8f2wY+PCcYfpGQak6VR4/tvnw+kNgAcvMSbP1Tbjti/OhtvP4U8fNqIwo1S8/qqFBWjolAY5f+TaBZhhSQXPQRTwBdFdzQIMw+D9E13izhIQ9ACxOT3Qa1RwegJjnk3zlM2JZ4WQHSGLofkF6bJevSe7nPjtP49LFk+//edxzLCkYmbOyCSXA4B+dwC7Pm6KKNfM7Dmyn1erWVw+Lx9lOalos7uRZ9ZJvOvk6HQERGFYKNOdLx/E09cvwoxs+WviDcNxwtYPj4+T9Mt7V1fihK0fc6zpsvdgwciGrjhvhnKsxN4BDg2dzogwHEphJc70utHa48BT6xeJHv/vHmvHmV6DYsxhk06LT5u68Idvnouufg+y01LwwidNWBSlXCNFXVufKAwDwTq/46WD+M3XF0qSd96xai5e+OQ0Lq3Oh83hlcS5Ds3qfW5xBnasOwdmvQZ9bh92bjgPbl8AD++tx/VLZorCMAC093lkY1P/Ys08HO/ox4LpGeA44L//9IloH65cWIBTNicKMw348JQNTk8ANodHnJR87bxCpKhZfNrcC4DHjUtL8cDuw5J73PVyHTavKBPjyQqbKhuWlaDYYkR5bipu+vMn4t+FRA8LpqejyDJ0BvVwBI+yzn7PkF5pKha47Yuz0eU8Gxc736xDh8OLjctLAQSPcAmZhMOF5LU1BZK+F4t3fTzlG2/sA24cbQtmSLYYNbjhv2bg5X0teGDNPHj9AeSkpeBEh0P0GA+NGazTsLAYU1CabcAfbzhP9EaonmZWTKaVqtdh0QwSg4nY0GpVuLx6GkqyjDG1r1ASaWtmvRa7PmkSQ4PptWo8/V4DHlgzP8EniI5OExmLXqdhkaIQlkogK02Fmy4shYoNZkM369W46cJSZKdFv87m9MmOEVX50cV2pzcgSfAHBBP8/fzK6qjXadXyz6cZQm0/3eMEeMCkV8PP8TDp1OB5PmoiWiLISNlYrVaFyyqtmGExSIRXANjfakdzrwtZqVrJZnG4o4rgQTd3mhlHWrqRn56Duy+tgCFFjR6nRxRSgLPz2pLs8zDgDWDH2w04f0Ym1i+ZgQ6HB1ZTCp754CQunG1Fj9ODUzYnpqXp8PKB1gjHicuqrCQQEwQBQD7sE88DX374HYnm8tR7jRE60x2r5uKewc1iq1mHspy0CBtnSlEhRcXCkKLGL9bMQ0efG9PS9bj71TrRYWbLxeXiuur6C2bgSFsfOB7ocnhRnpOKpeU5klBPPID/uXQuTHoN7ANe9LsDWPeHj8Ry3fbF2dh4YSncgxvJ2944iqrB5Hlycdu3vXEMG5aVJPV6ZDyh0SIMoRFlGLT478+VIN2oRYDnxYX02poC/Gz3EWQYtNi8ogyzrWmwOXz4f/+3H1suniU2NCGGy5neARRZ9FhZaUVjlwMBHhLB6TdfP0cyOS3PSYVGrcJ7DTbo1GyEx3FpTir0GhXW1kgT1GUYtLC7PGCMKXAPettW55vEEBfpRi3a+4Lx1TZdVCYmwhIEEYYBUlNU+KSpF6cG4yFnpenw4OtHxDKcPyMTM7NTJc8oXNvp8KAww4DXD7dj6+7DYgbKr5xbCA7Arbv248alJfD6eRgHRQeOl8ZRZpjgc3xnWQmc3mBcWeHY+M7aJlx/wQy4fAH84Pl9omfxQ3vqcfelFZLvabW74Q0EheFragpxxh40RlcuLIDN5ZXEHc4waFHf7sDGP3+K760ol4juGQYt1v9XMb72+w8lQrLXz2Pr7sNiecK9/sZi56mjfwBXLSyUeDTetaoCHf3yIR86FT7f5RhQFIfT9JHikE7DwhRlkjng88veZ8CnHA+YZRmk6TRweQNI02mGrDubQ/4IqS1K3F0lj8nsVPlFg8MdwM7/RIrvxRZ5kRsA3H75Z/f4lZ/d4fHLLk53rDtH9vNZqWoUZKaKMbWDk/8KZKUqvxONGlhSnosPGmzgeOBEpwNLynOhGQPr36GQcK+zzyN55ntfPYQHBkXb8CQE2/fW47YvzoZKxeKulw9GeHL+v5Wz8Y0LZuCiWVIvKsGGhN/b6w+gJCsVfo5Dr8sn2sHQfq/XqCT9+geXzEKKmsXv323ANTWFkt3muy+rQFpKK9461iXew+kNRNy3wmrGrLxUtNrdElFR2MB7dsN5cU9KQr1xY/Hk7XR4MBCy6VFk0eM7nysVN+mEzQmtisWjbx2N8IINtf9DxcsPL9/3LiqTiCmCR/hoxVeOF/uAG/842CldWK+uxA1LSvD958726U3Ly/D/du3Hdz9fil//87g42b37sgoYtCqU56WP96MQkxitVhU1OdtIUmwx4volM+NOLJcodrdXNnFsvzt6zGGHm0dnvxd3hnrsX1YxZHgeRwL5C4DguC13SsjhiX5dj0s+aW2PS3nDPVgmP9r6PBEnVPLMYxMaigiOZXvrO7Hluc/E9VjvgA/2AT9uf/GA6NRyuK1PPPEkOKo4vdJ1wgNXVcKakYb1T/5H8j7Lc1LFOPVAsC229bnR3OPClypycd7MLGwIOZV392UV2HO4FV9bPAONNidsDo+s48SMLAPOnWEZr6ojCCLJCA/79P6JLonmsn1vvRhuYtvV83G8wwGPP3g6rtE2IK6ZHnz9iOQUuKDNfC9kzrBpeRl+PqgLCUnvtr1xDBsvLIVJp4ZKxUp0MSHJnTC33ryiDD1ODxyeAHbWNuHWlXMkTkcZBi2c3oBkHbNpeRn6Brxo6HTgdM+A5BQqELSNHC+tE2G9VGwxTvkQThTULgwhQcV3lpUgO02HHz2/H1oVg1f2tSDToEVhpkFskAaNCm4vh9tfPDAY64SBThOs0isXBsXb52qbcevKOdi+tx7WdINECMowaOH0SCenNy6biZNdTjz7nyaU5qSJYsW6xUXY8XYDjrY5cLStTyyH1azDrStn4UcrZ8GSqsMP/roPp2wu1BSZ8dXBGKv/u6ceDZ0O1J3pw9qaAri9HE53B48/rVtchMffbcAje4/D5Q3gthcOgOMFj7AAVlXnY/veejG0RkOnYzDeVdAwvLq/BTwP/Pt4F/7T2I0tz32GVdX52FnbhGtqCjHgC2B/c6/4jGtrCsSQEmW5qWJ9CaytKYDLF8Dpbhd0mmBM5mc+aMQtlwQn1EL9hcbyMqSoI74nTacRy/5cbdDYqVhECNLC95TnpKIsN1Uiun/tvELRgxEIXre/2S4+Y2h5hL9vee4znLI5R7JJyqJiVeJRT+Hed79aBxUr7ynDMqzs55koJkDLBnf3hLoVdvs0KuVr9Bq17H30CkqkEBf2xc9a8O8TNrz0WQv2Hm0HF261Q7AMxtANRadhYTEoL5SErOuhz7J5RbBNyOEJEXpv/b8D+OHz+3DVwkJ4/QH5CwCo43wnAGTDprh9kUdrBXpcAXEBLHz2zpfr0ONSLpet34uWngHseDvYz3/3dgNaegZg648tY/dwSNNF9k2dhoVeK20Pbh8Ht9cf0T+BoJ2clmEQT1GEhzr5+e4jqO9w4HB7n+S6okyjfDtJTcGJTgdueKoWh9v6xY0j4Xvl4gQ++PpRdDo8sve/6+U6rF9SIiax02mCScXC77u/xY6VD70Df4CXLVcicYbDY1gO9b1aFSseYwWCpzWEo9HC8zy0px5+jsflC6ajMNOA7V9ZgK1XVWHzijIYtSrxHoJt3rCsBA9cVYUd62pQMS0NH560oaHTIXoMC4vpNJ1GHGt+/04D1i0uQpFFn3B85ZHmaJszcmH90kEEOEh+t31vPVZV5+Oul+tw3+oqbFpRih3rzsGfPmhEo801no9AECOK4GH02qaleHbDeXht09JR3fy2GHVifo6Ny0txw5IS7KxtQqYxugjq9MiPi06P8rgIQIwFHopOwyJ7iIRlZr1GUs4blwbLadYrh3cCgOxULTwBTjIWewLckIkBe10BSSxzYdzpjTLuEyNL6FgmrMc+O23Hw3uPYfOKMmxcXorvP/cZtu85O74BQJ870gGAZVQRY81dL9dhw7KZknvqNCwOt/bjd2834Mqa6bJt4GuLZ6DX5cOnp3vR3ifvODFUwkqCIKY2Qp4dYV5/w5ISbFpRigeumoetuw9j2xvH8Ohbx+HwBCRrJuEUuJw2A5ydM689Zzq2763HlQsLxN+X5aYhf3BtJ1k3v1KHVdX54r8f2lOP7DSdOPc+0iZNBK50z94BP760/R1s/POnok0eap2WZ9Jhd10bvrT9HXz1sQ/xpe3vYHddW1RNYjJC4nAYVrMea2uCHqaHBxvgb/55At9ZVopX9rcgb7ADCV6owmcYBtjxrxO4a1UFdBpWzL7YanfjeIdjUPAJRDTo5kERVGDAExRIVlXnY9+gqCp0wgyDFoUZejzxXiPMOo0o7gLBsAFCWXZ93IxNK2aJQpXQcZ6rbcb0DAOcHr9EtM4waHHThaXIN+vF63+8cjYyDBqo2OBz3DgYWkMQWq87v0j05hVE19PdLrEuBBGF4yGKzbs+Dt5fMCY///thbFpehiKLHjddWIq8NC1Ks1ORadCK9ymy6HHlwgIMhAlHQv0CwGNvn6134GwHF8ouGLuynDSoGAzGt5mF3607BxXWtOBmwOdLcc+rdZiecVb8z05NiZhoCWVgmEihGTi78zTadCp4z3Y55CeBSp/vVPh88Bovnvj3KclC7Yl/n0KnQ1lU7FCYnHYoTE6bup1iXFhhsVTf7kBTt7LAbh8Iet9sWlGKjctLsXlFKX68cjbsUcJdtNrdqG/rwx++eS62f2U+nvjmuahv60Nbn/y70qjkRW61SlnojfedAMriaWqK/H2UJv8dfcr3cIR4rQiff2hPPRze0V9YWoyaCFH+jlVzwfEcNi4vlQzU0zMNSA0RHwXW1hSIG0yh/V5A2AFus0vf5YysYFyt0Hvff0UVjrX14dn/BBf2qSkq3Lu6UrQVAKLeQ+lvbfYBXLmwADpNMFNvllErue+m5WX4v0+a4fZxuP2lA9h6VbXk7/F443Ecj4ZOB94/0YXO/mDIi9AEpHLfK1wTHl4lRc3KPs+/T3Thu3/6FOuf/A+Odzjw638eB88Hj07fu7pSvEePywudWoVfvVmPDc/UYtcnLZIJlc3pEceg8Ang9r31+PmV1VHjpI8lSn3L6fVH/E5oB70DPph0Gty66wCOdTiiJtIkiImI4GG0uCQLJdmpo+pBU2E14eblZeIm0uPvNuDm5WVRcxAAQIdCQrqOKGMvAGjVLO5ZLZ073rO6AilDhHnoc/twTU2hZLPrmppC9EeZgwAAx/MRDgfb3jgGjo++8FR8vhhEv9DxQti0I+JHGDtDN5IL0lOwYdlMDAyGAAwf365cWABvIHKzP9wpSLiGB684b2jpGZC9ptflQ44pBWqWhSVVKzufjJasmSAIQohDLAjEj7/bgJnZqfjFPw7j2kVFol15ZV8L7rq0QrJmcofkClBaI+WZdEENK1OPjctLUVNkhkmnFnWu8M+Hxv13+zgxzKWgvYTaOaV7ftLUI2uTBUe3spzUiPVSgINs+LuxcPpLJkbtYDHDMH8AsApAB8/zlYO/+wWASwF4AZwAsJ7n+V6GYSwAngdwLoAneZ7fqPCd/wPgWwA6B391G8/zr4X8vRDAIQD/w/P8g4mUe05uGk7ZnKjvcAAQPL76YKlrxTXnFuEnLx7ApuVlcPsDoku60LiOdTjwl8E4sKlalZiYYEaWEUUWPSyDgkFoJ3rq/UZ8/6Jy0Zsr06jFGfsANGoWbn/QPT5FzYq71WfsA+hxefHnDxtx16oKfPfPn+De1ZVo7HaJZWm1u9EWIgKEdpxUnRqNXU70uLw43uGQhFEQYs0AwLR0Pe792yH8+ItzoNOwomjd4/Ji98FWrF8yA185txAuX0A8DiDE1wIgMRyv7GsRjyl09LuDdeDnxFjMG5bNxI63T+CamkI4PAMoyDSI9xH+9oNLZkPFnI1xmaHXiP+/v6UP+KgRD66ZB5YFCjODYsMcq0lS3809LpTlpuJ7F5XD6fGjodMBty+AtTUFONLWh0bbgFi+DIMW2YNeJaFGRyiDXsPCO/h+Qv+eqAdgvOTIlC2ax4swaQz/fGaUSaNBq5LNVG6IEt8w1yxfrlyFcrX3ebDncGSc3oWFGYrZlzONWpzsckqOoWy5uByZBuVnyc/Q4cI50tAKF87JxbR0+XfVlYDQG+87AYIJcbZcXC6Jsbvl4nLFhDi5Jvl75EQRpZweP8pzUsUQM4YUNR57+wScQxyBHQnKc0w42eXChmUlULMsynJS8fPdh9FoC4bbuWPVXDR0OjAzOxW/fP0I1p1fHFEf0zMMaAzZRJNtxwYNctJS8PaxDri8AViMWqTpVbhoVg5eC4mrZXN60NHvlhwJvueyuSjPTZN8r9w92JBJSfjfdFo1ynONeGDNPKgYYHqGAX/ftBRH2/txoKVPPEoFAI22AeSn6yTlivXYUnhStyKLHnddOhcubwCNNif+fqBVTEA612rGjMGEm6GhJ4TyB+OFpco+T2iCuu176wdjeQWw9pxC5JlS8Kur56OutU9MUiE8mzAmChOqnRsWSzZLQ3H7OLzfYEOPyyd6IwrexmN9nMvv55Cj0LfMOo0khFJwDAhuYqQbNLj/tcPocXlx3+VVYgxKgiDiJ5EcBACQlaaVJAIDgvPOoUSxbpcHOjUrSdSrU7PodkUXXU26s57Dwv121jbhF2vmRb0uUZFXadwfajOK43jsOdKOAy12MYxFZb4ZK2bnTrljssNF8KwTwt9tWDoDuWY9vvunTxRDJqnYyHWI1ayDNV0+zFlumg6Pf6MGZ3rdOGVzScZWuRwAwinO52sb8dzHrSiy6COS5t11aQWstGlJEEQU5OIQ25we1Dba0dLrwcYLS5GdmgJDihqpOhUsRo3imkluLG7qcWFtTQG6nV5kGjRYd/4M2JxepKjZCPu4tqYA+eagiLzr42b0uLzQD9o/ngde3d+CO1bNFTfkBKcipXWMgNvHYa41DY9/owbTzHpMzzCgYppZsg77uKk7qcPfjRWjGXXySQCPAHg65HdvAPgxz/N+hmG2AvgxgFsBuAHcAaBy8Ccav4oi/G4D8PdEC8xxPN482gGH2wcVA7z42VlRc25+uhjj5JkPGnHbl+bgeEe/+JmdtU3iZzf95VPUFJlx04VluPOlYPzi+y6vQHOPSyJ8qJig2Prke0HvzFyTFgGeQ3GWEVnGFNz+0gH8eOVs5Ax2FsHLVxCnBXE3K1WL5h6XpLz6sMQeRRY9rqkpxM//fhg3LinBlouDAmloGAXBY9jlC8A+GFfm128dxx2r5sKoU4sir9sfwKkuJ8py0sT4v1cuLIBeq8Kdq+bid2+fwP9bOUf0Fl63uEicSGtYBj+9ogpNNid0GhZLy3Nw76uHsPHCUvH5fn5lJTavKMOALyCKxk+914CvnleEzSvKsOdwGzKNWjEpoNvH4ViHAwzD4JI5ufhnfQfO9AyIXorCdzy0JyhyqFhm8LsbkGHQYsvF5aL49McPmnDPpXPh44HjHf2Sewg78A9dMx/tfW6kZ6gjYnLed3nlmHjCGTRBj8c7QiaB966uhEEhcUtWqhr3XFYREZMvO0qs2oxBr8/wZGkZBuWjk9lGbUSd3H1ZheKxyQAXkI3TG+CUvVp9AU7W++bJ9ecqXtPj9KF5MLRC6LMUZhpQKBO+MSctRXaAiyb0alXAPZdVRiQDUXACBgBoVCzS9Wo8uGYenB4/jDo1XB6fYugOnTo42Q/Pkq6Lsngutujx1fOKpHV8aQWKLHrlgo0QajWLL8zNQ0GGHn1uP771dK0oTF5TUyiJZXnHqrlot7txXokFT60/F94AL54YEGxPqJ0Vrrv9y3OQn67DobZ+cbIgtO9G2wBWzMqVDOoF6QYxGR4A/OZfDbjpwpmibd71cXNEu7/v8kpoVAy2vXEs4v53XVqBV/edxudm5eHeVw+cjQ+fnQqLUYt5081451iHuMgLbsqkSOJ9xUpoGAmhDr+382wdfv+icjz53in0uLz4281LwbIMGjod4nFYnTpoJ5p7XNBpVPj57sOyMT6FBIDA2V3/20NszR2r5uKVfS0RCdlCHeDcPg4ubwDbrp4v2nu5yZuQBKLYYpQI38JO/ljEcK9rteOD+vYIm7p5RRm8HIf//lwJHv/3SayqzgfPBL3S77lsLtJSgvH/F0zPwHlF6ZT0hyCGSbw5CAAg06CWJAIT5h2Zxuj90aBR49u7PomwS89cvyjqdS6vD9dfMEMSO/j6C2bA5Y3uOZyVKi/yZikkoBXINalk5xa5pugJ9052OXC8wxEx7ynJMmJmTmRuiqmA1xvA/jN2tPW5MT1dD0OKGl0Oz5CbkcUWI7ZeVY12+wCuO78IPQM+9JzuFUMm/e+b0jF0Z20TynPSwIAX5xZCPM7te47hrlUV4uk0Yb7SM+DGgRYHVExQABE2JAHglX2nI4TfO1bNxWdNPbigNAdH2pzY39KHR9+qF/M3VBekw6BhUEhJC4kJznXf+i7OdPVG/H5aVjqefuzXY1+gSUh4HGLgrMPhg68fg9Wsw3XnF2F6hgFmvRo/vbwKP3nxgGTNVNfciy0Xl+NEp1McG7+3ohxP/PskvrWsBO19Hjzwj6OiDbv/ikr84JJZePD1o5JcUqHjVZ5Zh6ffaxDt6jU1hXjhk9P49bULcbLLiemZhog1m6BFhaLTsJhjNUmeL/R5OY7Hmd6g13S4LU+W8HdjRcwrGYZhDDzPxxxQj+f5txmGKQ773esh//wAwJrB3zsBvMswTGms3y9TvssBnASQsO/3KZtTTDRmMWrxlXMLxePHhZl6cUF+3flF0KpZzMw2ip9ZVZ0PNQs88c2gQGXQqnDNjg/g9gXDGrh9HO7/+9lEdgUZBmhUEAf7R986jke+ugDf27kP5Tmp2LiiDNfUBD1zf/73w9h4YZn4Xc980IjvrSiDIUWNtTUFqG/vjyiv3eURv3vXx824c9VcfH9QIOA4HuB5zJ1mhtt7NtRFq92Nfo8ff/34NP7n0grRa7pz73H89+dKxAQ83/1cKf53Tz1+8qU5kQncLijC3ZdVIi0leIT7thcOYPfBVvzwktngARRm6DEnz4QzfQMoshhxpncAGQYtck06sRxN3QMwalXINGol8Yu376nHV84txC2XzMb6J/+DDINW3OFhB8NFNPW4sL/ZLgq/151fhHtWV+Lbg0kc3H4O09P1ON07INZn34BPIj6l6bViXX1nWYnEq6QoywAVy+Lxv5/E/1s5B79847BYBp4HHt5bj4WFGaO+w+Tw+uHxByRl8/gDcHjlvUEdbh6P/vO4pKyP/vM4HrpmgeI9DBo1jFqV5B5GrQoGrbLZONXtgl7NYMe6c9Dj8iHDoEGv04NT3S4UZ0cuRtQq+Ti9T0dZnPUPKCSRGVD2hJWL+/bQnnpUKmQl9wYCsotNX0BZtGbA4rnaxojM7rd/uULxGrNeBYZhRbFSEPnNeoWwEv0eqMAHxWSvH0ZtUEyOFlPO7eMj4sre/Uodnv3WYsVrRhK1msW86Rl4Zd8ZsQyhRzOFMt376iFsWFaC5p4BMAwj8Y79zudK8dt/HRft7OPfOBcDXj9MOjVSNCqc6XVHHOu88+U6PLhmHupa7ajKT8cpmzOYtDDMi7XV7sajb53Ar66uxu/WnQOH249Mowa/+/o5GPAFkJqixv++eRSXzcvH/VdUwesP4Mn1i9DZ74aKYfCHfzeISZtC7WHo5Gb9khl44t2TONbhGFZCp9CwEHJ1+Ks3j+HWL8xCl9OHQ63BGMzdLo9sue5dXQmvnxfjizEMMCs3DQ++fkQUsoHghKqpxxXxrn7ztYX47z99InnOp98PisrCONnvDr6jC2ZaYDZoJZsagggd9JwL3k/uONdYZA9utbsxIzcdLrdXtHc8Dzz9fiN6XF5sHhyPQ+vvp1dUweUL4NLqXMywmIb0biQIIjpCDoL9zWc9XasKzFg+K7qna7+bk43H+qcbzot6vy6FhKldUUJnAUBqigYuX6ToakyJHnO4z+1TSLg3RDgKTgWTXiUZ99Wq4O+j0Wp3y857qvLNU1Ic9noDeHH/GdFpJ1yIiLYZybIMvlxpxcdNPfjGEx/hxqUlAIJhr+RCSvzm6+fA6+dw/2uH4PXzuGFJCc4pTMd3/xwcM73+4FzR7fWjyGKEWsXh7WPdeGVfC265pBw3Ly/H7S8ekMw/D7f04Kn1i3C6x4Wmbhce2XtcHJ82X1SGG576GI22ARxr78cje49Dp2HFTWKCmMic6epF1hdvjvz93x8eh9JMDQozDNixrga1jd3INGig16ola+LffX2hOF8GgFu/MAszc1JRd6YvYmxcVW2FimHw4OtHJbbythcO4tFrF2DjhaUothgljjvCePXotQtw3QUl6Oxz45ZLZiNFzaIwswT/++Yx7G/pEz2MQ/WNZz9qwuYV5bjthQMS+x5t7XXK5sStu/ZH2PId62pGLQlvsjKkOMwwzAUAfg8gFUAhwzDzAHyb5/nvDvPe1wPYmcB1GxmGuQ5ALYBbeJ7vYRgmFUEP5IsB/CDRArX3ubGqOh8/231EnDj84JLZGPD6MTM7FUUWfdA7wBfA5mc/FcXQe1dXIsDxKMw0isd4/3msQzLpDM2KzPPAD5/fhxuWlODV/S1ig/ZzPNy+YJiE/c12fHCiE9+4oEQS7kAQNE/3DsCUosL0DAO2vXEM31lWAhUDsbx5Zh0WFWZiVm7weJ6KZeD2BeNl/Wz3EbEsP/xCucSTwe3nsKo6H/XtZ71mW+1u3P/3I7jnsrnYtnY+BnwB9Li8aO9zSzya1y0uwrY3z2arfPY/Tdi8ogwmvUYifgkTsIJ0Az493QNvgIPN4YFOE4zl/NPXDiPDoMVtX5oDFQtJEqitu4/igTXVYj383yfNuHJhATgAvS4f+t1nYxO32t3YuvsoNi4vlbwLo04tCVHhDXCisH7LJbNxotMhXv/btxtw3flFKMlOhUGrgppl8H6DDauq83F4MBRFaNgFAGNy/IDjeNz3t8MRHih/+EaN7Ofb+tyyZW1XiLkrXPP8x80R4QjK89IwQ+H5UtQq/PLN+giP259fWS37+U6FY5adUcTONL1a1qs3Va9szpSykitlF9eqVLKLzWgeRd0uL2ob7aht/FTy+16X8kKz1xWQZF11+zjc8dJB/FHhPiadBjf/5dOI9/7UeuVytYXFmRXuoxRveaTx+znUtdqRbjh7DClaXN+j7f3ixAIIhmH47b+O4+dXVsPh8WOGxSiJffn2sQ4x3nr49zm9frTa3WjpPeuR+v9Wzorw3upxeZGdpoeKDYY6cXn9KMw0gud5rHrkXbh9HGob7QCCm1Dbr1mAdIMWHl8AP1o5B02D8dblBNuH9tRjw7IS/OALs5Bp1EKnVuGfRzug07JIUalgSdWiMDO28AnC0dYMgxaz89LEBapw9CnDoIUxRY2tITvzW6+qliyChXLd8dJBbFhWgu17jot2ociix4ZlMyUe2PeuroTN6YHVrJNk+tVpVGJojOxUHU7aHOhxeWE167D+v4oloUE2ryjD9Ew9tl09D0fa+hHgzoajKLLoodeocKy9Xzaj8FjYU6tZjyNtfWi2e/DI3uMRf880aHFX2AbLT144gB3rzkFHvw8FpgCJwwQxTBptzojY8W12NxptTsU5BxDcNJWz/0OFa0jTyc8l0oY4ASDY9XA7//vr5OdfAul6aTgKng+Go3hwiHAU7f0efG/nvohx/8n152KGzKa7QL/CvKffPfohpZKR/Wfsouft184rlE0oPevmpZiZI21roeGOHCHxgl/Z1yI67oTi9nFwefw42t4vnq559K3j2HpllfjZ/S192PSX4Fxxx7pzoFEDS8osKM1JhUbF4kfPSzdKgwnrSuD0+HH7iwcl93xoTz1+t+4cANITPG4fh06HO+J5CIKYeIx22LXQ789JC87pN/45uN7ctKIUO3afFXbLc1KhVrHIN+tFbeCSijz0Dcg7Yu1Ydw7q2x2ytnJfsx3zC9IV8/Z8etouzst1Gha/vnYhvv0X6TpbLgTmwsL0uML3hedkEe6vUTFTboMtFs/hXwH4AoCXAYDn+X0Mwywbzk0ZhvkJAD+AP8V56W8A3AuAH/zvLxEUmf8HwXATDkYpWOfZe28AsAEACgsLJX/LDUtitnX3UTHWYFaaFndfVolPmnpEr9QrFxagzxPAx409uGJBPgozjWjqduKTpl509LklAkSX04Miix63XDIbv3z9iOg9/OhbZwW7h7+6QLzm7aMd+OqiIhzv6IdOw+IfB9vEY0jlOamozjdDo2JwyhaMHyyImACQomFh1KpxoM0OrYqFSa+BMUUdEfuxOt+E0pw0SbgBFQPwDPDEe40Sr1lTigp5Zj28AQ4FGXo8cu0CtPUOYGZ2qkQUyTBo8eMvzRGPsDs8kcmwtjz3GeZuXopDrf1otw+gNCcVPQ4vbvvibKRoVGL93//aYdy5aq5E+LGadbCGCCTfvKBYjNf8ew2Lx9bVSIRfAeHzRq0KJp0alpCwFE5vALs+DorMXn8ARRaj5HqDRoWGTgee/U8TNl5YhhQ1C4+fU4w/OlLHD6K1VacnILbB0Ng4Stm5rWa9Qsw65bJazTp8scoqCUeweUUZ8qJc4/H7IzzsNi0vg8cvX65MY/yxkDmOw3eWlUqO5N21qgI8xylek6UQczlL4T5Or/yiKjw5VSjGFDVqisy47oISSfzkaJ7WXU4FzyWnvKDs8PgURG5lz6PsBI+yxkq0dur3c3hxXwtuf/GgeGrioT31YhnCy8TzgCFFFRHzqdE2AIfHjwvLc6BWs8FJTJdjUMgNKPZFo1aNrNQUfP3xD8W/PfV+Y8QRpIe/ugAOjw99bj9cg55Z/W4fupyRk5VG2wAG/AEsLcsGADR0OvDv411RY+sK8dq7HF7JTvbmFWXIMaWgy+FBul6LziGOtxZbjHjk2gWob3fghyH9UvDCXVtTINpy4d637tqP/71mvmy5ZmSdtXU6DYtragqx86MmbFhWgvLcNBxr78e2N46hx+UV79Fqdw/WrQrFg0I9EAy18Nqmpejs9+AbT3wkK5CnalXQqVWifSiy6LHxwjLxlE3oswj3GQt7WmE1wen140zvgHw7SlHL1l9tYw/0GhW6nT6U5hhQlk0exMTwiNZOJxKhx/etJh2qppmhjZKvAAjOk/vd/givoy6nJ6o4nG6Qj8dqjrJhDACZqRp876JynOwKOQJ7UTkyjdE9gB0KCcWUNpsF/ByPG/5rBrqcwXAUaha44b9mIDBEQjolD2fbEB7OieRBiJWJ2E6FjXKrWSeeVgyNJ6/XsOhyuFHf0Q+rWY8Kqwksy0jCHQm5Vd4+2oENy2aKji1y8yuWYSLWgXKfPXjGjukZBnh9HCxGLT5pkk/SVGwxwukNyP7N6fFHhIUayfFzIjMR2yox9YjWTsPzjYx02DW57w+GkdSi1e4Wne6AoHb01UVFuOGpWjGM3vVLSpBu0Cg6fLXZ3dAP5uIKD0cX4IJr7tM9CvNvrQo3XVgqxnA3aFlsXlGK52qbAUBMxh3q1LLt6vmi002sziWC8008OslkJaZVDM/zp8N+lXCae4Zhvolgorqv8fwQM6LIcrTzPB/geZ4D8BgAwV3uPAAPMAxzCsD3ANzGMIxsUjue53fwPF/D83xNdna25G/FFiPOLcqEThOsFqtZh3WLi/D4uw24/smPcXAwqYPgJStkKv7d2w2oO9OH3XVt+PvBNjy05xj0GhU2ryhDkUWPmy4shVmnxk0XlsHW78b1F8wAAFH4FXjs7RPB+KGaYCzeu1+tw3O1zdi0vAyfn52D3759HLd9cTa+trgIm579FL964xhKslOxeUUZtGoGPA88+PoRtPS4seWvn+E/J3uw6dlP8dnpXjR1O4MZJgeFU6Fzb37202Cm+WUleOgr87F63jScW5QpCs4BDshJ0yIvXY/axh78+4QNr9e1Bb0PPAG0Di6mhSQN6xYHBW2hcymJJe19HmzdfRh5Zj00LIs/vHcSAz5OXJwLdPa7sWB6uvi7KxcW4KE9R3HXqgpcd36RKAwDwfsfbrWjNCcNm1eUide8sq8Fv1hz1nvuwX8cFb2Hf7FmHhZOT0ePy4v/+6QZRq0arb0ubFpeJnoy21xePLQn6A3b4/QgLUWNOVaTGIpCuI/gpTdSxw+itdUMY9A7OzRb9nXnFymKqilqiG1LKGvw38qDSoCDGKZk4/JS3Li0BM/+pykiyHsoaTpthOfk9r31SNPJL7bSdMG4zaHluvuyCqSlKC/qDFqNbCgKg1Z5QadiGWy5uFxyny0Xl+P/s3fm8XGV1f//PLNllmQmyWRt0iRNk25ZuhCgYFu1BSx+C5QdUVAWKyq2X3FBlEUW0SLULwUVC4iCC60i6w8q0oIFAbHUbqFL2rRJk2Zptkkyk8ks9/n9Mbm3s9w7mZlkJjPJeb9eeSW5c+/cc597nu085zlHrdCpisk//NFrVWENvRoVx1V1vvjJt/9tH7731z24qq4EGrVyM2fWy99HyXNpepZR9vzpWcrxg/U6Xzw7/2e/7+IqGHXjY8QKp6f1bTbJy6XN5sSzHzRhzbJyLCqx4MFLawJkWru8Eu8e7oRZrw3Q6+sWl6LUasC+Vhte2tMKp9ODfx/rxr+OduPLz3yE1t4h2br4wOoaaDUsIDkmAEmO399wFp5fczZe/9YSDLm9eP9oN7767E587blduPnZnfjoeA+GXEJIbObgCVeZ1YSaYgvWraiU2tfg81UMyDalSYZh4LTRtHtgGIc6BrHq8ffwhSf/jc9vfBdb69tls8qrVAx56WkhC24btzfgyrpilGQbZdtbMelDsFwGjRq3frYCD19ZizXLyvHch0043DmIfLMeP//7QWzcdkQKi+Sf6XfdikrsbbVh+6EOSU5B4BhwuhVX/wUOZKenSZ5za1dU4GeX1YZ4zvvfZywhOIIJp6cajQq109Ixb5olpD368UVVMKbJl59X8HltNXQOoMfuxr8au+ByxTw8IoiwepoquFxevH24E+02J+xOD9r6nXj7cOeodUPJI3fYHWbQAcCoUQeM+cQ2yqCQg0GS083RbnNi047TY/l2mxMuT/ipiZhc2h+9VjVqAjyn24MhtxBwvyG3AKc7fLmIRt7g++WOssA7K9+I+y+pDiiX+y+pxuz8sefFSEU9FR1LLltUjJZeB0qthoC53GPbj2BXcx/uffUTXL3pA7y0pxUneu0B4Y627GzBg5dW48KaQmzacRQcwF2r5oWMrzL0ahjTVAGfbdl5Ag+srg4Z9/xlZwvuenk/Mo1p2NXcJzmo+KPXqmDQqmFN18p+lpehx6br6rB5Z7O0sDqe/Wcqk4q6Skw9wumpf74R4LSj3fHumCOpjvr9j27zjcVFxHbn5mUzce9r9ZLNZ9OORvzv5t245Q8fI8so3z51Dgzjvtc+wY8vDm3/XtvbCoNWLTuPe/DSGhRlGfD0e43YuO0Ivr15N/a09OOl3a0j4U5nYsjtxYDTjYevmI9ffnEh/t+3lsZkNC+zmrDhqgUB95+qbWgknsMnRkJLcMaYFsA6AAdiuRljbCWA7wP4dDTxi/2uL+Sct438eymA/QDAOV/qd86PAQxyzh+P9vtVKoZzyq1Yf3ktNvzjEL5zwRzJaxLwhVxQMwQkcQN8lehQxwBe3u3bYiSGppiVly5t0fWFkDiGBy6pwX+aeiTvY//4Y4c7BzEtMw2bv7o4ICauGGO4qXsImaY0Saa9rf04cHIAz37QJHnr3rSkHBu3N+CmJeVSrN4htxeHOwbx8u5WXHNmCe5aNQ8W/elQD202JzZu88Wn2rxmMc4uy8ZPL63BHS/uw992teCB1VU43HE6vtraFRU40ePAo9tOJ8gb9nilcrl5aXnA6ovcSozd5cGq2iL8bOsBrFsxC6tqi/CLt3wJG7593iz86aMmXF1Xggff8JWjuCrEGLCzyQaXpwm3fOZ0uAjRkC+Gtbjh3FJsuu4MKdwH5xzf++teqdwe/vth3HBuKbJNWgicY/3ltTh6ahA/23oAP1g5Fz/b6oslXJJ1Oj4xY4DLy7HhrdPvdtOOo7hpSTnUKqCuNBvnllsTsv2AMchOov54s3yMvePdQ/jzvwPj4T614yiyjZWYUyh/jx7HsKwXcK9jGL4oM6H0KnjC9ip4wgqc4y87m0Pi9M69SDlOb7eMN6fTLfjiySrQNTiMZ/51PGA75zP/Oq7Y6NuG5GMD2oaUPXQ9Agvx2rz7lfDxkw1adUCSStForTSpdbq9+PFFVfixX+zWH19UFVIe/gy5BGyRKePy3HmK14wXomHR//+N247gN19ahNULijC/OBMH2vtxuGNA8ny9TyZ+3y+vXYRH3zqMw52DyElPk3ZwON0CnnrvGG5aMgPPfXhcqouLSrIwzaJDeY4Zzb2OkDbIF0bClxRu5/GegKQ94n03/OMw1iwrxz0XVeEbfrF1H7y0JkBvVCqG5bPzUZGbju5BF6ZnGyWDuORtb9EHxHcXcboFFGYaJS9g8Vi4WLsnbfJbn4ozDcg0aGXbW7eXh6ys/+TSGui0DI+/fQRZRh2+eHYJ/ndFJUxpGhh0Kml139+z6qyyLOSYZmPTu8ekWIflOekoyTJKHuLB7b8og2okkdtDl8+XwnZ0Dsg/S22RGa+PJKlL1Hauxq4htPY68PsPAtuJX//zCB5YXYUHVlcHvFf/mMkC97UZLT0OgAOfmplDHsTElOVQ5wAcbm+AR25ZjgmHOgdQU5ypeJ1S+KfRwiC0Dwzj2Q+aAurtsx80oTwn/KTO5nTLjqOqppnDXpdpVIe0Bw+srkamMbwxOj1NG+DQ4HT74sSPlgDPoFXLJqI1jOKJfaDdjs3/Cc2DUGo14qwZU88bqqrAjPsurkZLnwNbdrbgrlXzZA0iNy0pxy/fPoI7X9qPZ284K2QMMz3LiB++6Hv34g7TNcvKMafAjCyjFgwCTGkaXPbrDwJyo5h0amTotfj5FfNxqGMAnJ8OrwT4wqzNzs/Asa5B2fGny+PFsEclm/RZp2ZYVJGDZ75yVsTbqAmCSA2UQh6MV9g1pe/338F55//MRefAMISREKiyuWP+3ychfdV3L5iNp987BqdbwLDbi19duwi7W/rgFXxhla5bXIaN2xp8OxdHnEfUKmBugRnttiEpTJ54j1+8dRg3LSmH0+2FlyNkp5G44yNaVCqGlVUFmBNFKIrJSiTG4VsAPAqgCEArgDcBfHO0ixhjfwbwGQA5jLEWAPcAuANAGoB/jIR/+JBzfsvI+ccBmAHoRpLLXcA5/4Qx9hSAJzjnO+HzDl4AX1iJ4wC+FuFzRoxGo8L/VPusZf4esICvctyyrBwmfegWU4H7YuO29DokT7Wls/KkyThjvs/3tPQFxMT1Twa0tCIHZ5Zl+7I1B03yjSNhIYb8trMVWvQotRrR63DhcMeAdB//+4nGWsC3HVocyNy+co5sQ9BjH8Zbhzrxf9t8lW9uQQaGXIHeHBa9FmaDNuAZrj+n1GcAcQt44eMWaWDjn8XS392/NNuE3Sf60NQ9hDbbUIB3n16jwvcumCMZr8WkeGuWlWNxeTaeeteXKM8rcKmM/BspX4zkQ9BrVdi6bikEDjR0hsa68QjATb/fCafb5x34g5VzsbH7CH79zhHJqH/z0vIAb0CXVwiQSTSafGrm6XeXCLoVvPOUthmaDRoc7hyUYpwBvmdK1ytPLnRqlawX8OY1yonMxPAlwYYhk4InsH3YKxunVyk8BnC6LgTfI5xXb4ZBIxuTSMlDN0OvkY0NuP7yWsV7dPZHH/fQ5nQjNz0tIOlfbnoabAoJamxOD379zyMhxqufrK5RlmvAKVvGYhKweKIUzqTAoodKxTAzLx0zckyYV2jG3AIz+p3yYTMOtPVj6aw87G3tx67m3oAtTm02J55+7xguW1SM2iIzKvMzAjp0cTU4eDuWaOBt7w/cMuV/X4ED9mFPQOLLRSWZIfVcpWIoy0lHWQ5gc7rw3QtmId9sgEmnhlvg+OX2Bnxv5RzZsnAohDBRGvQplenM3HTkZOikRKD+E8efjCTFWbOsHCVZRrT3O2HWa2DWa6WB3MNvHkap1YD7L6nBsMeLdSsq8PbBTqysLgyYpN6zqgq56b6tZtlGHXrsw+ixu9Dc48DNS8ux41Anvn3eLMkIIg7YirMMmF+UGWA0ZQohgCrzM+IeZziYkzYnehxuhdjsLmTotXj4ivk43BkYM1k0fB9sH4Beo8bdr+zHbefPxkW106bkoJJITmKNVxjLdUMer+SRG9wGhCM3QyH8U3p4j1yTTr5/DzcmAHyLrXJtr9MV3lO5f8gXU9a/33YMe9A/FP66Xod8/xZu0RkA2mzyi/u3Lq9ETbHydR39w7J9f0d/+FjMk5WTA068deAkbvjUTGza0YgjMvMCf4OI0y3IhoIIzuMgLno/9oWFUh3597FuaT4i5kaxu7zIMmrxryNdeOrdxhA9zzJpcezUIGbmZeC+1+pDxp/XLS6FSqXCsMeL31x3Bjr7h5GmVeOpHUexZtlM1E73JcNOdN9JEER8UQp5MF5hY5S+X+zqdRoGrVqFTTsa8fMr5ks7xoPbz6buIZh0vrjAXYPD6BwYxtPvHZPGymkaFQ62D6AyLwNqFWDQTpc+PzXowmWLijGnIAMNnQO477VPcPkZxYpttJxjzaPbGrCoJAtlObG1gWIYiqneho5qHOacdwH4YrRfzDn/gszhp8OcX6Zw/Ga/v6+L4L4/jkC8sDT3OnD7C3tDPKDabE789v1j+MWI27m/woqxerfsbMHdI9uIgiuOWnXa+1i8vs3mxC/f9nntXrawKMSgsX7rAVxdV4KH3zyItcsrYdKfNox98ewS/GzrAclz198VXrqfW4BBq4LLIwTcU61isg1Bhl6Hr//RF5/zl28fwa3LKzA90xBgkJ6Vn4GdTT0B37d+6yEp0ZO/0VutApZW5uCCeQU4NXh6JUYQOM4oyYJeq8IfPmyWykxMmPeNz1TIDr6WVS6WDD2tfQ7J8BwcS/nmZTPBBQG7mvvwwxf3hbzL4BWvpu4hHGzvh16rkgy/Ny0phzlNjeIsI9atqMTz/2nGD1bOHfXdJQKrST6WnFJYCbNeG2KkX7eiEhaFcA8A4FDwdHSE2Ro65PaEGIa+fd4sON3ynj95GdF3eEMu+XsMKdwDAIwaDX544Rwp1p+a+baGGhU8dA06Fb7xmYoQ7wyDVtkbsNAi/yzhYjSbdBp8/Q+7Qq5R8jZ2uDyyxqtw7yRHKeawaXxiDoejqtAs62FVVWiRzhE744bOAcWYU0MjgwFxK3+wUdFnIG7E6zLetqOtBhea9WjoGFAcGFkMWvxtVwtuOLcUcwrNaOgcROfAMPIy0mQTyVlNenzjj6FJA7OM2hAj9boVlcg2yhtElOqAUpnOL/YZXjmHZLSoKjTjRI8dF80vAgD8ZWcLeh0urFlWjt0nbHj6vUb839UL8NyNZ2HY40W33Y01z+2UvvcXVy3At4M8q+59rR4PXTEf3//rHmSZdOgadOGTtn6pXl2+qBgv7GrBrZ+twNzCDBh1GthHEgkGl9VohvtEYtSpFePVH+ty4LW9rfjuBbORnqYJSbZn1KrxxI5G9DpcuGlJOW5/YS8KLXrUFJjRNjgctwQixNQjFmNtrPEKBYFj+6EO7G2xSfW7ptiC5bPzw17ndIXmmhCT0oQjz5yG+y+plkLN6LW+MAj5lvB9VYZeLTu+yUgL71mbZZTfaZFpDD81srs8ePCNgyHXjfZ8ivczhI9xnG82yC7u55vDl0u+Wb7vH+26yUpHvxNvftKFfa2D+PZ5s+BweWTLRwx4qNf6Ei4F91HKsSnTpPGHf/LY6xaXYvPOZqyqLcLu5l5UjoS+89fX+y+pxtHOQeRbDFCpEJIYdt2KSpTlmKQEUf67V3odLsV3Gu8kVgRBxJ/xHisHtwslWUbZ77emayFwYF5BBm77i88Q++SOo7hnVRXa++Xna5lGHZweAW6B4/G3jwS0YQLnIf20iDiP+9W1i7BxW+BCr1wbPaTgWOMIkxuIiAzFERBj7DH4PHRl4ZyvjYtESYDoXi96wIqduloFnFmajepCCzZctQC/fe+oL/mUy4PyXBOGXL5YYr9+5wjuWjUPnf1OKRNyepoalSOrwTeeO0PWmza4ks8rzMDPL5+P60eS+zz3YRO+/uly3HtxFX71zhHkm/Vo6h6SPHfvWjUPm3YclWT+wcq5KLUakGvSQasNHDz//v1G3HdxNX75ToP0bAunZ8LlFkIqW6/DFeChu6elT4qF7O9RNj37dOMiVvINVy3AvEKL5CUI+BqlNw904LfvHZW2Ootl1tHvRJZRh8q8dJRaDbjmzBIUZxkhCALS9RoMewRk6NXY/NXFEMDR1ufEbedVYk6hGXqtCrPy0vGFs0qlEBtPv9cY4s3sdAshcUgBMZaYz+vOX/7zZufh8KkBLCzJhFbF8JNLa/AjP8+8iTBmaDVMdmtZmkZ+0Dfk9qLcasAzXzkTpwaGkZuRhn7HMJwKieKA2Ay3+WY9TvY5AzxqTGlqxWvUKsgabdVhdmTnm/XoGhjGw1fMh30keZjD5UZ+GLmGvYIU68/foOxSSGLn9kA23MUPLlQOxVAzzYL7LqmWsmHrtSrcd0k1aqdZFK+xD3tkEws6FBLbWBTCBpjDZFfPN6fJbkkdbcI9Hmg0KqyeX4TKvHS025wosOhRVWiR3XI/zWLAg68fCAl/ILZnlywowk8urcHGbYfh8vCQ9idcPQy3GlxVYIZb8KKmOBN7R3Z2vLqnFV88uxQFZj1m5Bpx3yVV8Hg5djb1Sp9/94JZ6OgfxqmBYeSZ0yBwLwxaHWbnpssab+fkmzGv0ILZ31qKpm471GqGQ239eGx7Q0T9QaRlKi6kFVr0KFxegQ1vNYRMJkuyjXjkTZ+B838378bra32RmW5+9t0Ag45/MlARn2edB3etmgerSYePjvdIIYumZxkBBqxdUYkn/nkE0zIN+KbfZDbYIJVM27gsBm1AolJR5p9eWoNskxZnlGbi+Y+O46ozS/F/Vy0Ahy8sTnOPA0/saJS2Bs/IMeLmpeXodTixq5WjpdcBo06DR948iBs/VQ6zUQv7sAfTLAbMLaAEdkTkCALHu0c6MTDkhX3Yg267Cyd67VhakRe2zijFK1QKXSPS3GNH4yl7QL952/mzUJFrD+uZo+iR65bvb0VyDWmYlW/AszechY4B36Q1TcORawjfV83INaK5dyhg3FGUZcCMvPCxdXPT9fje52bj5yPbVvVaFb73udnIHcUbayjG53N7BVkjtjtMMl0gskVWOWpGwijc/YrfmOTiatQUhA+bMVkRDbZtNid+9/5xrFk6I2Q8v25FJZ79oOl0GU+zoKY4E7O/tVQKgdXc1R+QyFss17kFp/ts0ZhzsL0f2w+2487Pz0OPwwWjToM+xzAWlmTi1186Aw6XB83dDinx6/2XVMOoU+Px7UdCwqRcWVccUIc3bvfliynONKImSBecTg/2tdnQ1u+EijFs+udR2Jxu/PjiajiGPcjLSENNoQX6MGNHgiCSg/EcK8stFj+wugaVuSZsWbMYdpdXWkg61mXHU+824n/PqwxIFP5mfRuuObs0ZDH3e5+bjSG3gP4hNyryTPj+52ajx+GGigEFFn1I2EAxWbUY2vShy2vR4hcKMNh24z8nvOt/5snOh7UjSctpESx2wvUKO0d+fwrAPACbR/6/EsAn8RRqovEfQPznWDdu/WxlgPJvuGoBllfmwj7skeL/6rUqPHrNAqy/rBa3/20vHt9+BN/8TDm++ZlKaWBWV2rBt5bPwmPbD+OaM0uw8ZqFMGjVcHsFlPoZAvwr7s1LywO84+5+5RPUFpnx88vn419HuyQ5xXARV9YVo7bYjE9VLITAOe69uBq7mnulyfvPr5gPx7AHPQ4XzqnIglY9C3f4DYyevK4uoLK98HELvv7pcikuKmM+7+dehysgJIaKAVXTzCjJNo3aePlPVFr7hiUP4/nFFngF3wDn6feO4n9XzEJ7vxMPv3kQN547AydtTmlQXWo14FvLK/H8R024dNF03PXyfqxdXomSbKMUjsLfm9jfm7m2yIzCTENAjFHAZwRfOD0Tr/vJX5JlxJsHOiQP7o3bfTGN1ywrx6z8DMwtMGNGTuKNGZwDv3oncPD4q3eOYOM1C2XPz0vXofGUHeu2/CfAmDynUHm7ploF2YlMOMOtTq3GA//vQEhj/eqtS2TPPzU4LGu07RocVpx8cgHotrtx9yuBXhXh0lumaVSysf6UQmT0Olyy2zH7HMrZwXU6NVbXTkN5jklaja0dJUO7xaCVEiUGeHQreBLlZygYesN4Ak3PMmFapj3AmJ5hUGN6VmIWNDQaFeZPz8L86eHPm1tgxtoVs/Dnfx+XJlViTKpvLa/EnIIMzMrN8MVp3rIbz33oS25XmZeOuQVmlOemR10PBYHjvWNdaOgYDHgHP7m0BhW5JszKSUeH3bc1yt9g/dBl1XC4BHx5ZOFOrE/bDhzDBVXTsKqqUNF4OzMvHTPz0iEIHNOzjKidnokCsz5kd0W4ZwlXpvl+SXful4nfvGZZOdptTsmY6XT7QlhwmdAaApdftZ+ebcSQ2wO3wPH8f5px47kz4HB7pbZXr1XhV19cJMVqFu8jZ5BKlm1cc/PNaOpxwOkews9HFoXyLXqcNT0LH53oAQPH1WeW4WjnACryMmB3eQO2tAG+stFp1Djc3oeSbCPWPX+6vf3ppTVo63dK3heinl1SO40MxEREnOi142TfcEj7f6LXjlKrcv1RiifY0R8+XmHnwLDkJS9es+Efh7FwemZY4/AMa7psuzFjlEX0ln47DrU7goxuVTDqNKg0ZCped6rfjUfePIRVtUVgzJdM95E3D2FewZmwGJQNvaVWE0qtxgCjcqnVGDAel2Napnxon8LM8EbsAadXNjbyzFzlHAtAdIus/hgMWlxUXYCyHCM6+oeRb05DTYEZhlE8lScr/t53bTYnfvfBcfzw83Pxi6sW4EB7P3RqFdQM+MGFc1Bo0WOBXxgk/xBYnQNOlGTr8eyNZ0nlOrfAhAw/XRONORl6NQotBnzr+f8GjPEOtw8gL0OP72wJ7EPuenk/Hr5yvmyYlOBk0E63gOpCC5bOtAYYeZ1OD17Z1xawKPDTS2vQbXfh63/4OMCgfXFNIRmICSIFGK+xstxi8Z0v7cOaZeUwaNWozE+XnFPUKuCRK+fDNuTG/wU5mjz4+if42rJy/PLaRegeHMbgiLPTOr+27r5LqjEzzwQVU2HY7ZVymYg43QLmFZrxzFfqUJJtQmm2Ee80dErz3DabE5t3NmPDVQvQeGoQi8utADg+V1WAlj57yHz42+fNwo9e3IdnvnLWhM8pUhnFHoFz/nsAYIx9HcASzrln5P8nALybGPEmBv+QDleeWSLrcfGHm84OybK+7vnd+Ost50jGRYNWjas3fSids7PJhlODh7HxmoVwewW09jmx9vlQr6pjXYEVN3gQerhzEIMuT4j3bq/DhTKrCefOzJUMCx8c7YLAT8cb9mdRSZZkGBaf4c6X92H95bW4/YW90ndOyzJgZk465hdnwssF3PG3fdJ9xbAK6y+vlbZYj9Z4+U9UxNAMAHDuTCvOKrPiRI8DXgE41u3zWLlpSTm6Ha4AY+6q2iLc+dJ+3LSkXDKAPPdhU0AsZYNWpbj1XMXkDZ+MATNyTsvfeGoQt23ZLSX6c7oDE/i9vnbphKxOOVzeqMILdAy4JC9jwPeu7xlJllaaI3+PNptTdiKzsER5YniixyE7CW3pdaAyPyPkfJ06OqMtAPQ4XFEnkYk2RIZZL++hmxEmDAfgm8Rlm3RwewVkm3SjTt445BMLnqWQWLDb7sYTQTGHn/jnEVTmLcAMhSTMKhXD0oo8HO+2T7h3Zjg0GhUuqZ2GilwTeuzDWFaZC7dXwOWLigLkHU9P0+PdduxtsYUko/vRi/vw8BXzpf+DjayZpjR8/7mPQ+rTb647A1977mNU5qWPahCXayvF3RWxIG4T67YP42eX1aKxSz6eoug1LOK/GyBY51/d0xrisXbfJdUoytKjONOEdw53YlVtUUj77HQL2H2iT/b+45VAY7zR6dRYObcAe0/aJKNZdYEZh04NoN02jEKLHj9+bT+auodw6/IKKbOyv0fDXavm4WSfA19cPANfC9IPsT8L1rOKXBPmT8+ayEcnUoQO23BA+w/42v+ZOfPDGoeNOoU4/QphlURsCjFy+xzhY+TOzEvHI1fOx3f8FkIeuXL+qO1br90rn9T1hvAJ245122XHQ8e67aiQGXeIiMlEy3PSo+pP0nUa/GDlHPxs60Hp+X6wcg7SdeHHBzNyTLJGvxmjJM4DIl9kDcZg0OKsGdboLpqkBHvfiXM0cfeWkwtweQHt4DBuf2FvSJiq4D57WmZ4fVapGMx6Le591dcXiMldh9xeTM82QqNhiuNlub5l046jAefqtSrsb7OhIj8d5X4G/31tNskwLH6nXP9z9yv7MSPHiDNJPwhiyqC0WCxwSJ68Fbnp+KRtALdt2Y1bP1shhYcQz924vQEbrloAtYrhm3/ahZuX+hzmvh8UA/jul/fjma+ciQ8au3FmWbbsOGRWUI6R5bPzcaLXjl9/6Qz8t7kXXgFYv/UAbl85F4tKsqT+eUaOCf86eipgPvy794+jzeZM2nlGqhDJcmEWfIniekb+Tx85NmkRBxBFmXpsO9gpW4mCExKIx1t7h/C56kKU56bjg6NdIec0dQ9hyO1FXoYeX3r6oxCj87x1S3Gg7fRWXjmXejGhm5z3bnCypHyzXjGOol0mXktT9xCKMvUB3rPiYHlGrs/b7faVc7F+6wHJ47euNBvnllsjNtCEC6yuUjHMLTTjcOeAlCSKMYQkjPJPvOdv/BVjKWcZdUjXaRS3a//7WHdEhk+xEZULvD6Rhg7lmGfyXjIdCsnSwiUmyTfrZScy4cJK6HUqWbl0CkbSWOIaOxS2dA6FSSITbXnlm9NkFw/CeejGEtfx1ID8ezmlkMSuzeaUnQS328Inl0sW78zRECfA4RjPZ+kIk4zO7vKg3eaEVqMK+bzHrmw0cboFtNucUU/ix0Kw7pVaDXhwdY2szhdYfPVa/F9sEwWBhxiCb/l0Bd5vOCWFVzHpNKgpNqMk21f2YmJRuTJU8joerwQa8UCnU6OuLBuAfH0Ww3K88HELbl1egU07jkr94JwCM3773lGcXZ6LXhn9UNKzROsKkbr0D7ulHUz+Otk/HN5Y2+90yW7NHBjlOpNeLW9UHiWWLwCkaVUBHrlp2tG94zsU+sOOMEldfTLJy6kfxfgNxNaftPc78ZsRxwVx/PibHY2YU5iBGWG+Z2ZuOh65cgG+85fTbcojVy7AzCTvlycT/u9bnKP5O6kAwK3LK8ZtfC+OcQstely3uDSgDv7k0hqUWg0B3nR6rQoDTi/+tqtF0q/Z+Rn4/fuNWLtiVkAIDLE/OnemNUDOdpnxvlL/M1WTExLEVEVpPizuHhS4z2Ygjn2dntCQSU63gCOdg8jPSJM+U4oBfKLHgY3bjqDUaggJvSgXQk+lYii1pmN6ls+TuHPAGeIkJJ5XlGnE0+99nFLzjFQgEuPwzwD8lzH2NgAGYBmAH8dTqGRApWJwuLzSBNc/LqiahUk+ZTmtkOGMoMrb/IbR0Hk6OZIYDmHNsnIsnJ6JUqtJmsiLHr6i9+6GqxagJNtXyfy9yOYWmiVDV5ZRhyvrijErLyNMUrM0xcGytPJekBG1556/TP7eycENxIwcE84szZaS3gFQNHCLv8XjT+44insuqkKbbQg/3XrQt8VhRSWKs4xwuDxStmx/w6e4mn9lXTEMWo0Uq0YQuORxE3wf/3c5EZRZTfjNdYuk2IMmvQYZerVinNJYEpOUWU14/NqFIclowsVXTlPLJ4bRa+QnadEabQEgV0FvrWEymkcbzL8k24TK/PSAyW1lfrpUv+SIJa5joUVhe6pF/vkLUjDBzNCQG/va+5NyW2u4xTOLXgtrehq8Ag/5PNsk71mem5GGtSsqkJOeltCYV8G619Q9hB++tC8kfvP6y2uxuMwqu/h3vNuOx7Y3hHilr6otCkiE9PyasyUvxRk5JpxRkoVdzb0KXsc1uPOliY3PHguizg443fj5FfPxt49PYF5RJpweL374+bl48PUD2PyRL67/gZHwJ2Looec+bML6y0MN80p6VqBQ1wkimEyDDtsPtvsWa4Y9MKZp8Pv3G3HWDOVY+IAv3NPuE934zXVnoNfuRrZJiz98eAxnlIZfiIu2Pxc53m2XEmeJiDutwhnbYk2glmWUT7ibZYxPPxPLwjngGz9fWF2AuYUTH2OdCG8kGa/xfYE5DY9/YSE8AodGzTArLx17W30OQD96cR+evP4M/Od4b0DOjV//szEg4fWaZeW46sxSnDUjUxqTcg4pGV2wnHLjRKX+J5nHjgRBjD9y82FxoUmvVWFOfga8XECWUSeFn5NrO4Y9AoxpGpRaDdBrVJieLT+fzbfocevyCgDAlv804dkbzoLd5UFJtikgLGdwkrxiiwEDTjf6HO4A28xoz5Iq84xkZlTjMOf8GcbYGwDEfc63c87b4ytWcpBv1uPVPa24Y+UcONzegIHnotLMURNEjKa0wZWo1OqrCErhIj49K08yWr55oAMb/nFI1ntXzovsZ5fV4o83nY1j3Q5psl5qNYQ8w2iVSinz7WgZceVk2nRdHQw6FXRqFRwuL45326Xrzim3wu7yYN2KSimmpf/gX9zu/Nj2hoCysjl9QdCzjVqpbDmHFBtSfMYL5uZLoUOuriuRkg5uO9iB/iE3zi7LxluHOrF+6wEp+Hk0CbDijSBwnBpwheifkkGqqiBdNjFJVYHyRE0QOPoc7oB4wOHuAQDWdB0y9JoAo2qGXqNouI2lYR9ye7D+smqoVWrJMO71euF0K2cojTaYfyzbTZUWfMJ5n8zOlX8vs3Plt8LWFFrkE8yMkphmojJWDw258Vp9e0j2+VVVBQk3EMuVQZnVhJpiS4hh4b6Lq+ASBHzp6X9LC0z+n3POZd5DFe742140dQ9h047GUb3GxxM53WvqHoLd6Q7oIxaXZaO514GOficy9Bp0DQ7jeLcdpdkmdA7Ie6UzP/GDJ8wqFcM5M6wYHPaElNEtn67AWTMyZQ3RyczQkBuv7m8PeLf3X1KNXvswnnnfNxkX+wSX14tcUxp6h9zSjpo2mxN/+PBYiH7MzEsPSd7xk0trRk0qRRAiDByXLyoJyHVxz6oqMOXc0QCAaVlpWDW/GB+PJNRUdwGr5hdjWlZ4w5A1XQeTTh2YYFanDrsQC8TWFwLAvAKTbP82ryD8OGtOvhnHuuwBchZnGTAnXznU1FgYy4Q0VXbxpCIej4CDHf3odbjhdHtRbjVhRphcBEpGEjHG5VjH90NDbvzneF+APt+zqgr4qAl7W/sxKy8dbu/puvvS7lZ84zMV0I0klhb7nsq8dMwbSV46p8A8qt7JjRNn5qZLCbejGTsSBJHcyM1tAEjHCi16eAWgc+D05yurCgKSbIoLTetWVOInrx+Q/n72gybZHez3rKrCEzuO4JNWE77xmQrc80o9ZuWlh8QAvvfiKtz9si8cm9i+7jrRi/97yxeWQgypJAgc2w91SM5oeek6GHSagPHyA6ursXp+UUC4xmRKap1MjHXOz3i4LE4AGGPL5I5zzndEJ2ryUVdXx3fu3Kn4uWjQbOq2B8QFBXyd9t//dyn6HG7FBBGCwNHcY0dH/zAcQaskcsbS714wGxq1Ct/evBuz8tJx87KZGBoxftUUmSVvrcZTg/j8xndD5BG9MpQ+37xmcUAMZMBnkN54zUIp1EU4BVLaNn/B3Hy8eaBDcTu9IHDsa+2Tvfdt58/Ghn/4EomoVcCZpdk4p9wKzUi2SbH83F4vMg06DHsEOD1eDLsFzMgxQeDAgNMFj+DbOmlzeHHHi3tx89JyPPWub9vf0+81yj6zyyuAgeE7f9kdslXziS+dgVv+EBgnrNCsQ9U0CwZd3ogGnn6MuZUK1tU9J3pDylN8x3Lb8vec6MUv3z6MLy6egT6HG5lGLf744TF887OzFLfx72nuxdrN/5WSvAA+b8CNVy/E/BL5azweAe8e7YSaqdAz4qHk5QKWzsxTjL/r8Qiob7OhzebrxEZLtNLUPYh/N/aEJK05uzw7bNzFeHO0cxD/81hovft/31qqGGtxz4lerH3+dBlzDry2txUbr1mo+F6i9cSNItzFuOvpzuM9+NLT/w4pkz/cdLa0fT8ReDwC3m/sxs6mHgjcp8e3r5yLlVUFcLm82N9mQ/vAMKwmHQxaFVQqhvtercfZ5blgDEhPU4NzYE5BhrR7w+MRsKe1D202X+f7/Rf2hGwPHc1TbrwI1+aLbbuYXPO2Lb7+5eqzSgK8ip+8rg5ffW5nyHf4ZxJWMni7XF78p7kHvXY37CMJTyvz07F8dn48Bmnjrqf+fHSsGw9tPYDrzy0P8M48tyIXeo1aGkT//oaz8PO/H8DOJhsASAlhqwotKLCkoTLHhPr2Aame9jrc+Mnrn0h93cLpmTi7NAtGQ3hDG5HSjElXg/X0o2PduP63H4XU0WdvPCtsXNk9J3pxqL0fRp1WWlB1DLsxu8AcNoxP8IRNxYDaYsuo9Xq0MWo4Boec+KTdLtWbeQUmpIdJKicijiOiSdg2FsTJ1ySZkI6rnk4EHo+AN+rb0GZzSkkUfWE75uPC6sKw8xpxEm3UqUfyRaSNy/tUqq+//tIiuNwChr0CVIxh0z+P4nDnoGSY/s4Fc3C4YwAqBly2sCgg1F2keud0erCvzXZ6nDhiBA4+lmLJ6OLa9xPJy3mXXoucC78Vcrzrjcfw1ot/mgCJwpIwPZWb3z2wuhrTLHrc8eI+uDw8JOl5sH3mWJcdjV2D2Ndqw192tgAAvnh2CXIz0pCbnobDnQN465N23HbBbAw6vUjTqqAd2V3v9nL8bOsBaQ6bZdBierZRyrvzgxGHGRG91peseldzH17d04rffvkszMgx4ZM2G/a02KQ5ydoVFQEx0sVrlWwcxGnGY84fSa/wPb+/9QDOAvAxgOUxSZ1CiCsS7xyWjzvcZnNicXmObLxApZcjrpLIJUbYdrATL+8+7an8/SBv1+lZvkHAaF4ZwZ+Lxs0TvUOy3mVDbi8WlytkJfNDadv85jWLFbfTl1lN2FrfjoPt/SH3XlVbhA3/OBRimF1/eS0uqp0GlYqhLCddGhiJZbp+pCHa3dKHc8ut6La78Z2/7A4wBIsrXU6PN6Qsrq4rkQyra1dUYFVtkXR/Uf5dzb3S/202J/62qwW3LCvHh8d6FBvZRNJmk9cBpfiVbTYn3vykC29+0hVw/PJFJYrxLrvsw7LxDbsdyjHKWm0OtNtcIdnUW20OWcOt6AUfXZxel2zSmj/cdDZKxzGvRrQrb2qVfJJDdZj5aUe/vLemUhw4QeB4+0hXVOUVS7iL8SLamMrxQBA4/t/+toAwNmuXV2L91gOYV5iBj473BsTAuueiKmjVwBfPLpMSdorXZOg1UpnpdGp4BI61z+/GrcsrZLPwJiomuZInW01RJgCfDuxoOIVD7T5vpVs+UxGarTgoGan4HfMKM3DuTGvYiahOp8Y55TnSpPXMjOyUNZY4XB5Z70y34MWDrx/ETUvK8cu3j6BrcBjXnl2G/Sf3STt85hSYcf6804YzMdHPx009UvJZsa7rtSo8eX0dzHotqgrNcTVkEZODWNtTj1eAlzN811+nL6qCx6scpx+IPWHbWDxr0w16nDUj+u38sSZsixXyAE4u6ttsODUwLBmGAV/d+M5f9mB2foZiYsJ4vke5XB+z8tJxqt8V4k3854+asHEkrNPhjgE89W5jQKjAaOXV6zWyieYo+RxBTB7k5nd3vrQfa5aV4+q6Ehi0Kvzug+MBSWzXbz2AOQW+JHAqFcPMPF//vnGbL8zmV84tkxLFi/PYb362Aif7nAG7le9ZVQWvIMjaCeYUpsM+7JGdF+1q7sNT7zZi7fJKdA0O4VDHAA629wcYgylHR+yMx5x/1NkI5/wiv5/zAVQD6B2L4KmESsVQZjVJcWdFRotHpfRyjnfbA767PDcdi8tzpPjGTd1DGBj2BHgqB18rxslSksf/czEJwtPvNeJg+0DUz+GPklFayVDZOeCUykGM3eyPWgVZw+ztL+wNKCeR4912KQzE0+81YuO2I3i/sVtK7hGcnO65D5tQmZcRcN/LFhUH3E/gPjmC5Q+W97JFxeh2uMK+l0Qixqr1J1z8ymjPB4AMvTbk3Wzc3hA2I3eHbVgyDIvX3PtqPTps8pPXSOpJMErJIDv6wydliwZxIeLzG9/FF578Nz6/8V1srW+HICjvtGizOaUkh7cur8BNS8rx7AdNaA8jlxj32x+9VoVsk7w3YSzlpRzffPzKS4n0NI3s86Un0FvleLddMngCp/V4VW0R2vudkmFY/OzeV+uh12hwrNseco02yNLv39aOpW0dK+Ji4+trl+L5NWfj9bVLsbKqAAAkPb7x9zvxmx2NuPqsEjSeGpRdKBSTkfp/R1mOr48qH2WXhH9/Ntq5yYxRp8G9rwW1Ya/Vo9RqkvoZX6xGPVYvKAopL7nn7lRICPrvYz24etMHeGlPKzye8IY6gshO10XVX4i4vFy2X3Z5w+8cBGKr10rtUaq2CUTy0+sYRpZJJ9vOHpuAMTpwOoa2P2uWzZQMw8Dp/uXmZTPhdAtQq4BzyrOpzhAEMSpK8zuBAxu3N6AiP12ymTy+/QieercRV9eVoMceOCcX5zKXLSqWDMPidz26rQH2YUEyDIvH732tHrMKMmTtBGa9Dhl6rex4RUx8t3F7AxhUko0o+DmitVkQPsI5kEZKLK4qLQDmxnBdyiJ6QfgbAUbzgoj25QQkRlLIDCleO5o8/p/7G0NFb9poniNYRrnKqmR49E+8J3fvM0uzZQ2zSuXU0e8MMSYHNyj+crTZnHj4zYNYf3mtdDz4fi983IK5BeYQ+V/d0xpyndJKVjQVbryoKjTjgdXVAeUZHPN6LOcDYbyU7MpeSl12+Wu6FK6JpRErVNDDcEnsoiUWI6x/kprHtx/BL98+IpssxB8BPKRerF1eCa4QQzKW8vJPqiii16pg1I2eyX2sWIwaXwIjv+dbt6IS5gQah5XKTK0CugZdsp/ZXR4ErwM43QIcLm/AMbGtfXVP65ja1vFAzogjp8f3v/YJShUWPMVkpKlu4B0LSobczv5h6LUqqBhw3yXVqJ1midhwZtbL10FxkHznS/tR32aL2zMRkwODxufx69/O+P+vRLdCO9dtd8VN1smyWESkBiadFse77LLtrF4b/7GOHDUFZtx3ceC4W+Bcti4OuTzQa1VYWJKFs8usVGcIghgVJbuMOLZ0e7is8TbY0UWcyyjZZOwuj/zcflB+vOz2Csg3p4XM/9Yur8TfdrWcvt7PZuD/HC983BJy7Wg2C8LHaA6kkTDqDJ0x9hggWSpUABYA2BXxHSYBsQS8VsqCq/RySrKMmD/dgrtWzUNnvzPstaPJ4//54Y6BEG/am5aUo7bIjMr8DMl40XhqcNTt88FbBcVEdx6vEDYrvV6rQpvNia3723xZtl0eVOSmo2aaRfo8knLKN+tlGy7xermg6bevnIsL5uajpsgyEr5DE7B1oc3mxNPvHcVPL60J2EIud932gx1RvdN4otGosHp+ESrz0iOKsRft+QCQp5A5PC9dOYlNUaZR9poii0H2/GjrCQDUTLPgvkuqA0IBiMaa8SKWhDqxbKW1mtKweWeztOWHc2DzzmasrC6QPT+W8nJ5vSH1Yu3ySrhH2VI8HszJM+N4tyMgUVBRlgFz45QoCPDFHjzU0Y8ehy/+bW66vB7XlWbDlKaW/cyk0yC4CVRagJidn4F7LqqCxaDFlorFsLu8CU36Fw7F3R59jhCd+OmlNZThF8rtnkGrxgOrq1GRY0Kf04UDHQMRh4OYZtGHhJwRs0MDvnfS3DMEl0dIxTiQRILocbigBsfDV8yH3eWBSeeLHdzrCG/kzVfqyzPCJ6QjiFSh1+EKSeat16pw16p5yDImNvmtiMGgxUXVBSjLMUpxflVMfs5j0mnw4KU1WFySFXWIITG+cHv/MApSM5YwQRAxoJRU87kPm6DXqtBtl18YDnZ0Ee1GRZkG2Vi/phEno+Dj+RnKc9JpZgNqiy34v6sWgAM40N6P5z5sQpvNKZ2XMzI/C7bf9DpcqMhLx5Y1i9GWoDwCk4WxhPUSiaT38I+I7QHwZ875v6IVNtWJNi5VNC9HEDjeaehE4yk7/vjvJlxzZgnuWjUvIFlQ8LWjySN+DgQORHzG0EYpMUgUgasDjM499mF0Dbqw+0QfHt3WgCyjDmuWlWNWfgbmFpilxHtiOazfegArqwtD4iifNztPNs6lXDmVWU04szQ74HnE1aVHtzWgzebE5p3N2HRdHbRqFmCgEctKEHjIe7lxyUxcMDcf86dnhhjb/a87NegMmeAn2jvQn2hj7EV7fk1BaMbj0bIbz83PkDXczi2QNwbG0ohpNCoUZ6Vh03VnoNfhRpZRC40a49pp5CgYFK2m8JNpnYYFGELFrNNKlFlNuH3l3IifPxEG6PFEp1Nj5dwC7LXYpMWn2mkW6OLktSwmpWnpHZLqaanVEKKT6y+vxbnlVggCD/nsnouq4PR4MGPEu1apnKNpOycKpcWE8rwM3P9aPW5aUi4lR/tUeU7SyD2RVBdkhLR7915chVyzDg6XB9c89W/puFz2ZDlKc9JRkWfHmmXlKMo0oLVvKGSQfLB9AN/76x7cd3E1Lq4ppMk9EUJOuh73vvpJSALTx65ZGPa6OQUm2b58bgEtBhGTg3yzAb0Ol+QAw5hvDFZqNWJOHBejR8Ng0AYki3QMuWT7l2yTBgPDXmij9HJ2Oj14ZV9bSN2mPoQgJj+iXWbWrUtQ39aPo6cGpaTJD15ao+hsKOfoolIx1BRZQuaY61ZUIsPgc47wjzn8wOpq1EyTP7+lz47/nujFY9sbcHVdCTbvbMbVdSXSQrZeq8Jt58/CA699ItlVnvuwSdaOVEsxhqMiFofWYBjn4WOOMcbWcc4fHe1YKhLvrKWRZpVtPDWIl3a3BqzWiJnPF07PRKnVFLMX2mgGjFizSsvJrHStIHDsa+2TksAFn1tmNUWc9dnjEUKSSz1+7ULMsKbj1GBklSDWLNOCwNHc48ui7XB5UJJtkhqvUUjZDLtyGY/DDTgbTw3i+3/djevPLceQywODToNn32/EQ1csUNSnaN/HWDKhR8ru5l580NgdklzunHIrFpTIZ0qNVa5onz+W88eauTRSJjoT9J4Tvdh2sDOkXSq1GvDIlQvgEYSQMnO5vNh30ob2fieyTToMe7w40DaAN/a1YemsPKhVwIo5eagpygwor0To4ViRe/drl1di+8F23Lp8Flwe39avFFuRj7ueOoZcqG8fQMfAMKwmHQoy0mB3e3HFEx+EvO9IsyeLWaHbbA6097sCdtqInh5tNt9A/rkbz6LEQZODMelqsJ7+t6kH/2nqlZJuiROsM0uzsLA0W/F79pzoxTsH2rC4Il/qNz480oHPzC2kzN8EMM56OhF4PAJe2tMaYLz4yeoa/E9VQdIZSR1DLuxvH0DnSP9yasCJn75xCL0OV8T9ich/jnXjut9+FNIvTdI+JOXHqERsnHfptci58Fshx7veeAxvvfinCZAoLBOipx6PgPo2m7Q7eG6+GTuOnkJDx2CIU1s4JxZxrNrcY4dRp0G+OQ0l2SYIAg/4fnHecLxrEH/7bysE7luw/tuuFlxZV4xNOxpx05JyPP2ebz5WaNHjskXFUKuAWXkZ+MnrB9Bmc46bvYuIGsVCjqTH/DKAYEPwV2SOEUFE6m3c0e8MiWfbZvNljnx+zdljMjSMtoIQy/Z5JZkBIMuoQ6/dhX8PdMPu8qB0xIDqcHnD3idSr2yNRoWLaqdJ4R78n2dmXoRZGGPMTqxSMZTlpKMsJzkMP4lAKeOxEh39TuxssmFn038DjofTp2jfR0e/E1lGHS5bVCxlX33h45ZRdVY0qo4WPgUAWvqGpORyoofWsx80oSTbqGgcjrUuRfv8sZw/1lXEVKHNJt8uNXUPoXtwGJ+rLgy5RqdTY35xJjRtNpzoHQLnwBv72rC3tR97W/sBAOfOtIaUV6zvO5H4v/uOfieMOjXcXgErqwsmrQ6MB0aDLqTd27q/TfZ9t9ucqCr0Dcp9A12DbLgJsY+amZcOj0dAZZ4JzT1DONg+EOBF7HQL6OhXjutOTF1a+pz44EgXfnPdGeizu5Fp0uJ37x3DNIsBC0uVr2uzOfGL7ceA7ccCjs+ZFvlOIoJIZmIJnTZRGA069NhduPVP/w35rLlnCACLOGRRu0KMfOpDCGJqIbc7ePnsfFTkpmNRSVbETm3+Y9Xg43K7j0V7lWj8/fK5pZhbaMY3PlOB/Iy0gJ3rv3z7CADg1uUV0ph3vOxdxPihaBxmjH0BwLUAZjDGXvH7KANAT7wFm0oEJKOLQzzbcMakWGKYKslcaNHj658ux0fHe0JWqWbnZ4zb88Vq3CXiT6z6FA2FFj2uP6c0xKu3IExCumhDABT6JZfzf45wSe8S8eyxMlXqTKHFgANt/bLvQSnLrZzH0T2rqoCPmrC3tT9sDPRkfd/+TJV3H2/ExKvB77swUx+iP6OFmxAH8S6PgO+NhFry/858M8WCJUIpzTbggupCfO25jwPC4JRky8f0F1HSXcr8TUwmog2dNpEo1UkxvFCkIYsKFOKJUx9CEEQinNryzXqUWg0B4SPEMcq6FRWy7ZNcTpdkmztNZcL1Ou8DeATAwZHf4s93AHwu/qJNHcqsJtQUW0IyM0Ybz1YQOBpPDeKDo11oPDUIQQgfMkS894arFkR9XzmZr6wrRpfdJRntAN8K9m1bdkOtQkz3IVKLWPUpGrwCQnTs0W0NCJdf7Xi3XTIMi9fctmU3jnfbZc8Xk975P8doSe8S8exEeKoKzajISw9pSx+8tAYuryDbLta32STDHuDTjXtfq8fNy2aOGgOd3vfUoarQjAdWB7YJD6yuhgosRH/ufGk/6k/aRu2PawotIdnsR4vrTkxdBA7c+2p9YFv1aj1GG+op6S5l/iaIiUGuTq5dXom/7WqR+pBdzb2jzuWoDyEIYiIps5pw/yU12Li9Aatqi6SkcgCwZWdLyHzskSsXoLbYQnOnJEbRc5hz3gSgCcA5iRNnaqJSsZhc//2JNTlSrFvO5WTmHNh1ok9+622/c8psbZ/KJCKEQeeA/Hb+U4NOxdAiSiEAOvrlQwDodGqsrp2G8hxTxInUplL4hmRFo1HhwqpCHOroR3WRBfZhD0xpGtz50j40dQ/JtottNnndUDNIMdHl3iG976mF0rbltw52yOpPc+8Qvvfkh2H7Y71eg4trCjHDL5s9ZZonlGhX6Mfa+51hr0ulLfcEMRXwr5NK4YWOddtx/TMfhZ3LUR9CEMREolIxaNUMTrcAxkJDpD77QRN+c90ZONQ+gDkFZpxb7gvT9zrNnZKWcGEl3uOcL2GMDQDwX7ZkADjnfOLSv05Cxur6r+QZOSeC5EjjFYO38dQg9rT0KW61pu3NU4N4v+dYtvMbdRrZa4xhjL06nRp1ZcpJfuQgHZ94NBoVqooyAYQmjZNrF5W2dxZnGeLWdhKpidy2ZSX9YUBE/XG0cd2JqUtuuvwW8pz00beQp9KWe4KYCoh1EmCy4YUMOk1EcznqQwiCmEjEeTkQGiK11+HCR8d68cu3jwQk7aa5U/Ki6DbAOV8y8juDc272+8kgw3DyES45UqIYr/AYBBGOWLbzu7xerF1eGbKFzx0uFgWR8kTSLtKWa2IsyOnPfZdUY9OOowHnJbo/JiYfKhVwz6qqAF27Z1UVyAGYIFIXuT7knlVVeGqkD6G+g5gqXP/Vb+C8S68N+Tl4uGGiRSPCIM7LX93TKjvX/tuuFgDUlqUKo+47YYzJuc4NcM7dcZCHiJFEJUcSBI7j3XZpq73/VoDxCI9BEKMRy3Z+qykNm3c246Yl5WAM4BzYvLMZK6sLxlW2cPWDSDyRtItj3XJN73xqI6c/mUYt7n55f8B5sfbHpF+EiMWgwwu7mvHQFfMx5PLAoNPg2fcb8dAVC+J2T9I/gogv/n1Ia98QBAHYtOMo9rb2A4i876C6SqQ6J7v6kHPht0KOu+q/MQHSEEBk7Yo0Ly/IQI99GJvXLEaP3YX/nugLCJdDiedSg0iCEu0CMB1AL3whJTIBtDPGOgB8lXP+sdxFjLHfAlgFoJNzXj1y7OcALgLgAnAUwA2c8z7GmBXAXwGcCeB3nPNbFb7zxwC+CuDUyKEfcs5fZ4ydD+BnAHQj3/09zvn2CJ5t0iCu2gTHHB5Pj91I4honIjMmQUS7nb/MasLtK+dOeP0gEkuk7WKsW67pnRNAqP4IAh+X/pj0i/CnzGrCjUtmxrUf84f0jyASg9iH1BRlYmt9Ow53DgKIfPcl1VWCIMabaNqV4Hm5IHAMuQX0OlwAaCd5KhGJcfgfAP7KOf87ADDGLgBwOYBnAPwKwNkK1/0OwOMAng36rjs45x7G2HoAdwC4HYATwF0Aqkd+wvELzvnDQce6AFzEOT/JGKsG8HcARRE826QhEcmRxhLXmCAmEqofU5N4v3d654Qc46V3pF+EP4lOgkn6RxCJJdY6TnWVIIjxZqz5rChpd2oSiXF4Mef8q+I/nPM3GWMPc86/xhhTzILBOd/BGCsLOvam378fArhi5LgdwHuMsYqopD/9vf/1+7cegIExlsY5H47l+1KVeCdHChe/kwYfRLJD9WNqEs/3Tu+cUGI89I70iwgmkUkwSf8IIvHEUseprhIEMd6MtV2hpN2pSSTG4TbG2O0Anh/5/2oAHYwxNYCxZHO6EcDmGK67lTF2PYCdAL7DOe8N+vxyALuUDMOMsTUA1gBASUlJDLcPZCrFeEpEXONoynOyl/146+pkIhnffaz1I9pnSbZnn2x6Kle+AGTLPFGx3hNFsunWeJKKelpo0WPtigoI3Pf/Cx+3QKdhMGjV+OBoV0q9o8msW+PJaHqayHLMN+tRV2rB9eeWY2jYA2OaBr9/vzFl2zdi/EjF9nSyINcG5Jv1KLUasKq2CGykOXh1T2vK1NV4tmukq0QqkGg9latzgsBR32ZDm82JQosBBZNsjkNERiTG4WsB3APgpZH//zVyTA3gqlhuyhj7EQAPgD9GeemvAdwPgI/8fgQ+I7P4vVUA1gO4QOkLOOebAGwCgLq6Oh7l/QGcrlDd9mGc7HPi9hf2hsRiAeSNCclMuM5ZEDhUDHjw0hr88MV9Ac9bkmVE46nBMT9rNLFtRjt3MkxEx0NX/YmlTJKxHAWB44397fjOX06/+0euXIALqyc2tloscb+jjRMXa1y5eL7H8dbTYOIlu//35mXooVYBbTYnPF6OO1/eh6buIei1Kjx+7UK4PFy2zBMR632szybXloufGXUauLxeWE1pKMky4s0DHZM2ZmG89XQsuFxe7D1pQ7vNiTxzGgosaZhmNuKTtgFs2tEIp1tAqdWAey6aB7dXwPaDndiyswW9Dlfc3tF41juKhxk54fRUEDi2H+rA3hYbBA6oGVBTbMHy2flxKcdiiwHXnzsDRzoHpPtdf+4MFFsMo14r6XS/E4VmPWqmWaDTqcddRmJiSOb2NFnxeIQAw0umUYOTfYH9cCTOAVvr27F+6wGsqi2CWgWcWZqNM0uy8K3llbjzpf1SG/vA6mqUZBnHTf54jsXi2T+QrhKpQCL0VGyDuu3DsDm8uOPF0/arx76wEP1OD37kZ+N5YHU1Hr92IW7903/Hxe6TjDYFIpRRjcOc8y4AoakjfRyJ9oaMsa/Al6huBec8KuXnnHf4fc+TAF7z+78YwIsAruecH41Wrkjx78RuWlKOp99rDInFMm/dUnzSNhCXjm4iOmcA0mdZRh3WLCvHrPwMzC0wozQ71KDw+LULMcOajs6B8IaJ4M9Gi20TaNRQB5ybZdShpceODxq7IHCOHrtbMtqXWg24/5IaaNVsUjVG0XpZRzv4StYJfeOpQckwDPj05Dt/2Y3Z+UtQkZ8xbveJtq7FEl/pWJcdv33vqC/7/Ihn1m/fO4rZ+RmYmRe6Ded4tx3rtx7ATUvKJe+Q9VsPYE5BhuK2nWR9j5Ew3rL7v1OPl+PRbYdwdnku1Cpg/nQLjp2yo9/pwQ9WzsWv3zmCva392Ntiw6Ydjcgy6nDZomIwBhxq78fcggxwAFlGLTavOQdurxfZQZO78WivY/Esj6QtFz9bu7wSm3c24/5Laihm4QTgcnnx0t6T2PKfJlx/bjmOddnh5Rz9Qx4IAse9F1XBYtTi1MAw/ndz4Ht77sOmuLyj8a53FA9zfGjusaOhY1BaMNBrVVi3ohIVufFJAny4cwD9Q+6AY/1DbhzuHEB1cabidS6XF283dMLt4bAPe9AGJ7rsw/hsZd6oBmKaPBLJTvDChylNhePdQyi0GFBVaIZGowLg0+VjXXY09dhh1Gng8Xrxo5f2SwvP91xUhT//uwmHOwelfvj2lXPDtrPiGPDquhJs3N4gtQM/vbQGj438D/ja2Dtf2o9FJVnj0sbGcxxJ/QNBxB+PR8BLe1px50v7cdOScry2tzVgLnns1CA2vBXYhjy2vQEPXzEf/3f1ApjSNMg2alGZmxGTI0kqz0WnGqMahxljswB8F0CZ//mc8+XR3owxthLA9wF8mnPuiOH6Qs5528i/lwLYP3I8E8D/A/ADzvm/ov3eaPDvxBiDbCyWjv7huHR0kVSsWAfW4TpnANJnbTYnNm47Ar1WhdfXLkVzryPESNvQMYhb//RfZBl1uLKuGLPyMlA1zQwA+O+JvhDPY1H+cLFtyqymgGdfu6JCOrfQoscty8rhcHtx0+93BhjtCy16XF1XgjXP7YzIG1n0CNepVXC4vAFlmEyTlmgb2VgGX8e65K+Z/a2lsobLsTxLNOV6vNsuqyfHu+3jZhweaycW6bLXqcEh3PipcmnbOGPAjZ8qR9fgkGwZd9uHQyYFa5dXosc+rPgek33gHe79K+lgLLIHv9NSqwG3LKvAva/VI8uog0GrxqPbTpfrXavmwVrfjjNKs3DfJdUoNOvx6LZDaO0bxpV1xdjbakNb3xB+/0GT5MG5qCQ7oC0e60Aolu+Qe9/rtx5AUaYe3XYXDrX3I8uoQ5vN195u3N6Am5aUY2dTD8UsnAD2nrRhy3+acPmiEnz/r3sk3fzmZyqwZWczrj+3HLYhN8pyTDhnRjbePtwV8N5++faRcX9HkbQZ0bTbFA9zfOjoH8bz/2kOmNA9/59mLCrJiotx2O72QKdmmJWXAfuwBya9Bo5hN+xuT9jrDncOoNfuxo9frZfarR9fVDWqUZkmj5OHZBovjydyCx8qBjzxzlEc7hzEA6ursXp+EVQqFrLD7bbzZ2HtikqcGhjG799vwr2v1uOhK+Zj7Z//K7Xno41vOvqdWFVbJI0BAV9beseL+6T+QGQ829h4jiOpfyCI+FPfZsOdL+1HllGHmmkZqJo2Fwfb+yFwXwiaNctmSnODQoseXzy7BEWZBnQMDKOl14EhlxdWkw79Tk9MbUGyz0WJ00QSVuIvAJ4A8BQAb6RfzBj7M4DPAMhhjLXAF5riDgBpAP7BfCPbDznnt4ycfxyAGYCOMbYawAWc808YY08BeIJzvhPAQ4yxBfCFlTgO4Gsjt7sVQAWAuxljd48cu4Bz3hmpvJES3InJxWKxuzxx6egi8ayNdWAdrnPmXN4ILvfZZYuK8ei2BmQZdbhucSk2bvf9ff05pRhyeyWPl2D5y6wmeLxcMbZN8LML/HTZX7aoGN0Ol/Td/kb7yxYVhwyi5LyRxRAhG/5xKMT4tuGqBbhgbn5SbbmO1nAby+Crqcce4C0J+GJeNvfYx804HIvOZhi0snqSodeOi0xAbJ1YLM9i0Gpgcw7hXr9J9D0XVaEoS37brk6twuadgcaBzTub8akKq+KzJPPAezQv1wNt/QoLcNHLHvxOV9UW4d7X6qU2RDQMi/d4cdcJXFlXgq8997Ek232XVMPj9eK+1w6M6sE5HgOhWL4j+H2LC2RXb/owRGbRQMxYYJsqXndlXTEcLi8aTw1Omsl9stHe78T155ZLhmHAp5tbdjYHGIz1WhXuu7gKn52bh1+/04g2mxOMxSfu/6mBYdy8tByAr80X9URsM6Jt6yZbbO6JwuX14tqzSvGLtw5L5f7t82bB7Y14aB4Vasbg5Qzf9dPBey6qgoaFbwcGXR7JMAz42q0fv1qP391wZtjraPI4OZjMRv7DnQPosbtDxmzfvmAWbnhmJ+58aT8q89KRnqYN2eG24R+HsW5FJYbcXly3uBTPfdiEIZdH+lycu4Qbm+WbfSGw5MZFalXguWNpY4ON+9324biNI6l/mHpc/9Vv4GRXX8jxg4cbsOTCxMszFWizOTErLx1rz6tEr92Nu17eHzAn2LTjKK6sK8ZfdrZI9hv/z1/a3YprzizBgDO8jUtpYTCZ56JEIJEYhz2c819H+8Wc8y/IHH46zPllCsdv9vv7OoVzHgDwQJQijopS0H+xE3vh4xbcsXIOuh2ugPhvpdmmcZ9ki7KEq1hjGViP1jkrPY/VlBbwmTi48TfKioaXm5eWB3yHaHQ8NTgMzoE7X96HtcsrAxqk9ZfXosxqwr+PdQfI9sLHLdK5omFDzmifplHJlllHf6A3suhtfNOScun+oowH2/uRl5GWVJOWph55XVAy3MYy+LLotbj+nNIAb8p1KyphHsUIG43HSEw6yznWragMkcu3ZjQ+dPT7OtGbl82Uwj08ueNo2E4slmdxuLzSJEO85t5X6/HMV+Qn0S6vIOs57PIq5wZN5kQlo+1YaOgckNVbY4SxK/11ccjtDfge/0UkuV0gwQY7p1vA3S/vx8NXzA8wnG3c3oCHrpiPwx0DaOl1wOHyYE6+eVwGQrF8R3Bdl1sg8/c61WtV4Bx4bW8r1l9ei9tf2Cst6PnXsckyuU82Cs16HDk1GKKbsvr3Sj0evmI+rltcis07m2FOU+OJL52BI50DGHB6ArY0x4KcUUdcSOh1uKQ2I9q2Llljc6caZr1WMgwDvnL/xVuHsXnN4rjczyNw2f5pNCNv16BLdmG5e9AV9jqaPE4OJoORPzg+sNi2Dgx7ZOvEb798pvR/u80Jrdolq8vZRh1O9A1h4/YGrFlWDoPONw0X++HRxuVlVhPOLM2WHRfV+R0fSxsr1w+sv7wWpVYDmrqHAu45HuNI6h+mHie7+pBzYWjEUlf9NyZAmqlBcZYBXzi7VAqVFzwneOiK+eCc40f/Mxc///tB2TnDo9sa8KtrFynaE8ItDNIiUOoQiXH4VcbYN+CL5zssHuSc98RNqiRAScEvmJsvdWIAMOwVAuK/bbhqAUqzjdI54zHJFmU51N4ftmKNZWA9Wues9DylVgMeWF0tJUFQj3gyKRle9FpVgFex0y3gqXcb8fAV89HUPYTnPmySvCI5B4oy9VCpWEij0mZzYvPOZmxesxhOj4D3j3QFGO1Fw/GMHJOicUkuRIj4u9CiD5BRLMtYyjYemHQaheeSr9KxDL60ahbiTfnotgZsCTMRjdZjJBadtQ978ewHgXry7AdNmD2O8YanZerxhbNLA7z27rmoCoUW5U4slmfptstPIHrs8pNonVola+gLZxwoyTLGPVFJrIy2Y2HLzpaQBaO7VvmSco1GsC6uW1EhW2f82yb/z4YUdoAc7hzA49uPBBjOjvgdW7eiEse67JhXYB7zQCiWwVRwXVfyMhK9Tv1jHV4wNx81RRacGhjGl5/5KKUn96lCzTQLhr3eiPXP7vJg4/YGbLruDJwadOGWP3wcUK9Xzy+K2UAsZ9QRjRhzCsxSfxFtWxdLPHYilO7B6PqLsdKlcL/RjLz55jTZheU8c9oo19HkcTKQ6kZ+/9ic/m3rqqpC5TGbw1cn9FoV6tv6cUZJlqwum9I00o7LmbnpeGrH0YB+eLRxuUrFcE65VVrI9R9nn1tuxevj0MbK9QO3v7AXm66rCwnRNx4GXOofCCL+pKnVuPfV+gBHPRGnW8CRzgEpbKj/7kLxc9E+0uNw4cFLa0JChJZZTWEXBmkRKHWIxDj85ZHf3/M7xgGUj784yYOSgr++dqnUiSlNoCM5J5atxVlGXYihxL9ijWVgPVrnrPQ8Td1DeGzEOOX2CtBr1Si1mtDZ7wwxvIhGW8YQYnQUPQTbbE4pZpZeq8Lli4oA+AxcwYOh21fORU1RJgBgwOmWvElFw/Gm6+rgEbwhZbZ2eSXcXkE2RIj4+7JFxQHb9yvzMpJq0pJvTpP1ns1XmHzFMviyu7yyHYjdpbyFNVqPkVh0ttRqQq/DFRBbTa9VoXSUDiYaj+Y+v22D4nPc+2o9Nn91MUoVIjjE8iz5GWkK18i/R4fLK+uR5QjzTpp7HdIkR3yW8UxUEiuCwGFUWOQQy6zX4QpYMFIxwO50I9uUFvJdwe/WXxcLLXpo1b4J3okeB7bsbMGre1px78VVuOeVerzwcUtIfSrJNsrKJtql/Q1n/sce3eY7NiNn7AOhWAZTwXXdoNUEeAmIz7G0Igfnz82D2ytgZXWBVB/Kc9NTfnKfSuh0aiyclomfrK7Bj17yDbZf3dOKn15aI6t/Bp0GTrcAgUPKKg344v039ziw7VAHjDoNsoxazMmPzpNY6b0vnJ6JT8/Kk9rLWNo6UbdIf2LHlBbdovBYyUnXyd4v26QLex2D/MLyH246O+x1ZVYTHr92Ifa22AJ249HkMbVIZSO/xyNgX2sfmnscATuE7nxpP0qzjbCa5OuERa8NMKqk69SyY3S9ToW/7WqBXqvC9CwD7vj8XBh16pB+OBwajQoX1U5DTZElZDw/Hm2sUj+gVbNxMT7LQf0DQcSX4347jpXmNuKOaafHix9+fi4efP0A2mzOgJ0NFr0WeRlp2LxmcUhuptHmDrQIlBqMOqLknM9IhCDJxmgKHskEWjxHzpjTYx+W7hNpMpc2mzPAULK0IgdnlmUDABpPDaLbPiy7mhzJwFoQOJp77Dg1MAyHyxuSUCuc0aCpewicc7T2OXH7C3sxKy8dX/5UmTQw8je8bN3fhptkVq3ePtgpuxJVkmXE8a5B7Gruw6PbDuOmJeVQq4C60mycW26Vymz57HxU5KZjUUkWHC4PSrJNmJHjMxDd++onuGlJOTL0aszISYfXK6DX4UZehl7yZDbp1Lhr1Txs2nEUa5dXQqNCwPb9UqsB96yqwhM7jmBVbREsejVqijPRPrKqlugGriTbhHnTMvDwFfOlRDEZejVKssMbjaIZfInlE80AX0nflYxKsRi/ZuTITyBn5ChfIwgc2w91hFyzfHa+7HtrU6jbbf1OzFe4RyzP4vJ68dDlNThyyi7JNTPXpBhDssCsxw2fKsOGf5yOOXnb+bNQYB5fj+Z4I3r1rt96IGTx5rEvLES/wwXbsAf/d/UCtNmGsGnHMfQ6XFi3ohLleekos5okg7BtyAXbkAe7mnulxAq3r5yL3AydZBgOjp9116p56B9y448fNuH3N5wFDo4Csx7nz83HiV4HjDoNTDq1ZDz2X1h67sOmgHIsz0nHb99rRKFFj+vPKUXxiEd2v9ONC+bmY+u6pejoH0a/041sow7/aeqG3elFqdXXRoVrN2L1qPGv64LAZfXyzLJsxe9J5cl9KmIwaPH5efnINunw3xO90KlVGBh24b5LqnG3X1y4e1ZVSZ5m9mGfZ3FtkRm3fHom3AKHWsXwy+1HcLhzUPJgv7CqMGIDsdJ7Lw3SOfIAmRiiXRQeKzoNwz0XVYXEV9Vpwrc/pwbkwzKdGnSGvU4QOPoc7oDdeA+sroYgcJpAphCp2j54PALeqG9Dv9MToINivy9wLzQqNR66vBYqFcOmf/qS0N1zURU8XMBNS8olb7tn3m/CHZ+fgzXLfAmHVQzIM6dh41sN6HW48MDqatQWZca8yyOexlSlfiDfrCcDLkGkKHqtWnLU+/Z5swJyF6xdXomt+9twy7JyDHu8KMw0YsjlwX0XV+E3O45g+ZwCbN7ZjAdWV8Pp8eCWP9ZLibjPnmGN2HGAFoFSg1GNw4wxLYCvA1g2cugdAL/hnLvjKNeEIgg8bHI0kUgm0KLBwH8w/8ML5+BknxNfevqjgIGT3Nb7YFlEz1q9VoXLFvq8av23TpdaDdh0XR0MOhV0ahUcLi+Od9vDGhREw1lDx+Co4S/knrnUakDfkEcySi+dlYcfvejLiCkastUM2LJmMdxejs7B4YDvKLTocWFNYYjxd3FZNt480IGD7f3SQM3fq/h1P29UlYqhLCc9JGN3mdWE21fOxfqtB3DjuTPQeGowICTGz6+oRUvvkJRE78q6YlTkpyPLoMV1vw30kH5hVzPWrZiFR7cdxtV1Jbjhd/8Z9f3FC1/SIFfItrfxnESpVZCdGAYnvfCn0KLH1z9dji776TjcX/90uaLxMlbjl8vDQ8K5hKOp246GjsGAa9atqMTMnHTMkOmkctPlPXpz0pUn4bE8S7ZRhzbbcMhkONMo75nV73RLhmHgdJKTs2dkK95Dycifmz5xhj5/r15xwUutAi6Ym4/Gbjs+ONYT0BY9eGmNz2snXSctgIjG5TXLZuL+1z4JGOSs33oAG69ZKO0CCA7Fcf9rvgWjw52DyM1IU0yy9dDl1Xjyujq02YaQb9Hj7pf3S9usAF856jUqXHdOGbJNWhw9Zcf3/EKRPHLlAqRpGW79038D9O7ZD5qkgdVo7cZYB1Ox6GWqTu5TGYNBi0+VW5Gh16Cj3wmrSY9Sqwq/uGoBXF4BasawaYfPGPGTS2twoseBulILLl9Ugtv+4hf+ZlUV/vxRk+TBXpJtw/zpWRHJEOl7V9IpwLdQHcmiNxE9JdkmVOanBxicKvPTwy4KjwWdWg2tGr5FaJcHJp0GTo8HaZrwMd9LrEbZsEzTRwllJGZTD97lUpmXHrEOExOPf/vQ0e+EUaeGyyuMOheZaOrbbGjoHJSNx3nn5+egqWc4YLHuvourUWDRYdjD8eNX6gPi8fY6XCjJMqJ6ms+7N8eUBqfHi29+tgIFFj2qCi1jig8fT6j/J4jJR5ZRi9vOn4U//rsJeo1KGkfMyc/Az988iGvOLAFjgJcjYB7z4KU1MOlUuPKM6XhsewO+/ukK5Kbr0GZz4rYtuzH7W0ulXEdKbUdJlpHGhilEJD3TrwGcAeBXIz9njBybtBzvtkvJ0fxDDfzf1QvAOfDB0S40nhpESZYvtrD/OcEdqFcIDaHQZXfh+yOGVPHYbVt243i3PWJZxERtwdv4m7qHcNfL+3Cyz4mrN32ILzz5b3x+47vYWt8OQZBP2HW82469LbYAObOMOhxs78c7hzvReGpQulas+P6y3H9JDXY190rXinFpREP249uP4ME3DsHh9sIjcPzsjQMBz3NlnS9hXVP3EH759hFs3HYEa57biQMd/bhty+6QZHNimXUOhPdCAU4PUjdesxDdDlfAM7o8HHqNWjrWZnNi47YjWPvn/2JwODTe49nlufjhi/uwqrYoxNik9P7ihdIkqr7NNm73aO0bwhP/PIKblpTj1uUVuGlJOZ745xG09g0pXsO5LxzFph2NeHz7EfxmRyPsMp7o/ojGr8XlOSjPTR+1w1AKXRGu/E/ahmS3uZ60yT+LSgXcs6oqQM/vWVWF0cby0T6L3SXIvkeHSz6m7sk+BY9mm3JdUKvg287o9yzrVlSGNfLHG39vZrGd2LjtCAaGPTjSORjyrn744j5kGnUoy/GVqagDq2qLJMOweO7G7Q1YVVsEh8uLDVctCJvZ27+9ltOr77+wH03dg9DrNBhyeXHrZytDdOKnWw/ge3/diz0tthDD/Xf+sht7W2whenfZouKEthvR6qXYbr6+dimeX3O2FCqJBnPxRadTo64sG/9TOw11Zdkoz87AwLAHG/5xCAfaB/CZOXn45bWL4HJ78PsPmvDt82fj3teCwt+8Vo+bl82E0y1Ao1JJu1siIZr3HqxTALD9UAde2t2Kfx3txsu7W7H9UIfiuIOIDa2aYVZeBqZnGTArLwNadfzq5Jx8M9I0ahzuHMCJ3iEc7hxAmkaNOfnmsNfZh+UTrYYLfwQo73Lp6B9WuIJIVlQqhjKrCb0ON9Y+/1+8c6jL1zYc6YLHM3rOgImgzeZUnG+U52ZIhmHx2N2v7Ideo4HVqMU3g8YG911SjXkFZqmNrMjPQHVRJj5XXYj507OS1jAMUP9PEJOROflmzCvMwPcumIOfbj2Ijdt89pmfvH4A15xZgulZRnTZXbLzr/q2AagYg8vD8eNXfWNM8fPmntNzGLm244K5+XjzQAc+v/HdiGxSxMQTSaCyMznn/juptzPG9sRLoGSgo98ZkBxNDEcw4HTjfx57N2A15IK5+WFjMHUOhA52lQYfcqEmgmUJTtQmN5heVVskefGK3x0u7mtHf+CASG4btr+HW7DHkHi9v3eikkf18W57yPMUWQyKBq/Rvi8SVCoGh8sbUu6XLSrGvpM22XsbZWL7iUYm/wR7/tckcpu+f9n4y9Buc2L+9PG5x4DTIxns/Rl0Kk/wOgeGZY2wi0qyZD10YyGWMAkDTvnkTkrPYjHo8MKuZjx0xXwMuTww6DR49v1GPHTFgnF5BpF2hWdp75c36KQrxJw0hYk52WZzyibwW1iSGeJpnyiUdl10D7oU28cD7f1SGAZRB5Tqolrlu8fZM6woyjTIxtxdMScPNUWZUnstp1dZRh30Oi2+/9c9uHlpOcxpamm1fVZ+Bh5586DkLaQkd/D4R5Rb/DtZ4/jS9q+JR6dTY3XtNJTn+MYCBWY9jDoV0jQq9Dpc6FFIjjTk8kCvVaE8x4Rskw5b97eh0GJAVeHoMYhjfe/NPfK7MypyQ3f0ELHR3GPHJycHQsJKlGab4lLGGo0KF1YVoiTbhnabM2KPx47+4ZiMvFaT/I6d0WIcE8nJ8W471m89EBCiTXRuuah2WtIZGwstBhxok0/8rZSIrmPAiappFqyelim10/lmPWqnWaDThfewT2ao/yeIyYVGo4KKqXCwYyCgLRPniHevmhd2HrNxewNuWlKOX759BEMuDwD5nAfBbUfjqcGochERE08kS5dexthM8R/GWDmA8Mv/KY5ouGizOfG3XS0QBKD+ZKin5m1bdqO51xHWI0v8Ln/UDCHHSq0GtPY5Q1ZWxC3h/l64T7/XKCVkkv1+BU85JU/bfLM+QCa5bdj+Hm7BHkP5Zj1e3dMqeQOLMYblPKpLs00hz3PSNhTyDHqtCoUWg/R9wZ7T0W5xCn5GwOfhLBq1g++dn5EW4iF9Zml2wP/B1yQyHue0TINCmY2fDMr3UA6t4HDJG2EdIx3JeCCn86OVf7TPUmY14cYlM/H9v+7B7S/sw/f/ugc3Lpk57tvqxIR0wXLlKySkS9erZb2A09OUJyH5Zr2UwO/x7Ufwy7ePoNfhmtD4sXI7EDZctQD55jTZ9lGvVeFwx4DUBvnrgNy5daXZ0kJdTZFF9l7+huHg7xS5sq4Yd44kCXvh4xakadQwaNV46t1GHO4YCNhGqiRL8PxXr1VJnvSJbjeI1MPfm/iMsmzMnZaJc2fmYMNVC5CTLt9+mHQa3LVqHjRqhvVbD+CWP+zC1Zs+wEt7WuPmtdfRL78wSF6f48dElLFGo8L86VlReTzmmxX6tVFiI3sFHjLWW7u8EkK4rUdE0tLR75TdaXf7C3sTutMuUqoKzajISw8ZY61dXolMo1ZhrOZz5Ane9ZHKhmGCICYncrYQwBcGJ9OoVZx/cX7asUWv9SVGFuefo/Xr4Ry6iOQkEuPw9wC8zRh7hzH2TwDbAXwnvmJNLP6GC9FQGmtoAzkjSE1xqLHi/ktqZL19xa3PSoZRue/3N2KKhDNClFlNqCm2SAOicJ6xStffvnIuNu9sxk1LynFlXTEWTM/Ea7cuCdmSNCMnsvLYcNUCVBWaseGqBeh1uPDch01Ys6wcj1+7EP/vW9FvcQp+RsBnpPc3aov3Xn95LUqyTSFbI84pt2LDVQtkr0l0PK6MNI2skTBDrx23e8wrMOOB1dUB93hgdTXmFVoUr8k2yU8KsxVi6MaCkmExXPlH+yyJ2laXplXh3osDw1f4/x+My+NFoUWPNct8oT7WLCtHoUUPl0ICOyC28oo3SuVbXWDGzNzQydmdn5+Lv+xskdog8ZmU6q9/sspI36VcOc3KywgIf/HEjkYAwK+uXYRF0zMD3pPcotgjVy7AnPyMkHoqZiuf6PdApCaiTk+zaHHfxdUh7UeGQY0Xd53Ayb4h7GzyhRqKR+ghf+wJWBic6qRKGRdnqUP08r6Lq1GcFd5gplYxaRwphrLavLMZKpZcHqZEZOSb9VE7q0wkoqf80socbLruDPz6i4vw1PV12LyzGb99tzFkrHbfxdWYnq1OOg9ogiAIOdQqwGrShcxVfnJpDVQqjpl5ppDPvn3eLGnOomLAvRdXoc8xjDXLyiPKeRCLQxcxsYwaVoJzvo0xVglg9sihQ5zzSe0K4h864bCf+73cVqPRlDtc4pY5a5eixz4MrVqlHCag3xk2mZDc94uxkCNNJqBSMSyfnY+K3HQsKsmClwt46t3In1WSoSAjRMYKZERVHsHXx5KsTEnGz1TmocCsR3WRBU63FzNzTJhdYMb6rQcCEuH5G5aCt1WJz9ljH8bmNYvhcHknJLh6e79yqIDxCt+g0ahwcc00lFlNaO93otCsR8208FtKXV4v1i6vDNhCuHZ5JdzC+HmrxaIXGo0Kq+cXoTIvPeLtsYnYVpeepsW2A234zXVnoM/hRqZRiz9+eAxnlsknmMtJN+Dnfz+E688tDwh3sf7yBYr3GM96NJ7Ila/BoMX5s/NwoHMAv7nuDDhdAhwuNx76++EAb2f/NieSuhjJu5QrJx4ULqfN5pQSff1lp88YLHry9TpcKM024ukv18Hh8mKG1YTy3HS8c7gDNy0pR5pGhco83+6S/11RieJsA84pzxn1PQgCx/FuOyVyIAJQqRhKcyzIMqVhRs5Z6BgYhlmvwfEuO+5+uR5rls3E49sDQwJlGXUYcHqw/WAHTDoN8s1pKMkeH30SdwUFjxvilSxtKpIqZex0azBvmh7P3nAWOgZ87ZZRJ8DpDj/lsDldISEI1i6vxIDTlSDJifGkzGqSnFViDQuXaDQaFaqLMrF1fxu+/sddqC0yS0lvAWDTdWfANuRGvlkPjcqDoVF0miAIYqIInj909Dvx63824vpzSvHIlfMhcECjYrAY1HC5AYNWg8UzslF13RkYHPagqduB371/HL0OF+6/pBoVuSbodSr0OTxYUhHZfIQSXKYeir0aY+wyhY8qGGPgnP8tTjIlBaIxAUBAaIPgOLyRKLeSYaLMasLB9gHctmU3bl5arjiAGs2wIfd5tMYglYqhLMcXG1AQeNQVORpDmtK5csfGy0AnCBxvHugIeaYL5ubLGrWjlT3R+IcKEBnvAbcgcLx1qDOkzMJ50GYb0yTPH9FovXlnMz5XVTBucgGxvQdxe+x4xWQeD8qsJqxeWIKvPfdxRHVtRo4v3EXwO5mRE74dSha9jQSDQYsF07Owtb49bBsUj2cK/k6ltnBeYQbOnWlFgVmPC+YVoHPACbeX466X96Gpe0g6rzw3HVaTHk+/99+Qtn3zmsURGYblyoGSwxAiZoMeZ87Qw+MR8H5jN7rsLqyqLYLd6Uav47RRrdCix/XnlOLmZ3cGxKutzE/H8tn5Y9YncVdQtG0TETmpUsbFFgNe2tsrJfDSa30JulbXyi96ilhNemze+UnI+GHjNQsTJDkxnqhUDOeUW7H+8lppZ2SqGAamZRpQajVgZXUhNu04KjmQuL0cT+5oxOHOQWy4agEWTE/u5yAIYmoiN3948ro69DpcWL/1kHReqdUgLYD599db/tOEs8tzcWVdMRZOz8SnynNiCpeTrA5KhDKMK8TyYow9E+Y6zjm/MT4iJY66ujq+c+fOsOf4V64sow5X1hVjVn4G5haYpeRIsdJ4ahCf3+hLcDdaErhEI642TZaK7F/WInqtCq8nJiD6mAsuWFcTYTSKpcyOdw3ijf3tIQlzLqwuoKRECkRb1+JYN8ddT8dCsrRBkcgRrq6UZBnx0p5WKWa9GNJk9fyiUeN3TnC7lawklZ4mE/66mp+hx8fNvZLerV1RIZuYcc2ycqxeUDQu+pQsdTaJGNPDy+lpKpTxnhO9uHrTh7ILYvOnZyle5/EIMbeVxJgYdz31JxV0NphjpwZxsH0A3/ZLpAT49Pj3N5yF3Iy0lHiOSQb1/ZOE8y69FjkXfivk+PaHv4Hl3/1VxMe73ngMb734p7jIOAaSQk/l5g+lVgNuO392yGLdbTLt3B9uOhvdg8MRJ6IlUg5FPVX0HOac3xAfWVKLeK54+AfpbrM58dyHvjABtUVmVOZnTOjAI5U8DSMhXED0VHzGRKzExVJmYtZTuXAXZByWJ9q6NtnqphLJ8pyRyDFaXYk2pEmk30sQ/gTr6vQso6R3KhVTzEI9XvqULHV2MpMKZawYJs3mDLtzJ5bwT0Tykwo6G0x7vxMNnYOyeszBU+pZCIKYesjNH5q6h1CUqcfra5eio98Jo06tOM/wCAI+V12YSJGJJIGCJUVAvAY2YpBufwPx0+81TnWvsLgQXNZAcsc9i4R4D7hjKbNEhLsgiGRjtLoSa0iTydhuEYnDX+8aTw3K6pKKgfSJGFcKLQZZXSuwjK5nyRj+iZh65Jv18AoC9b8EQaQkSvOHbFNagO1AaWxI7dzUhZbjJxAxSLd/VshUiMWVilBZR08sZUblTExF4qX3VJ+I8UJOl9atqERtsYX0iRhXqgrNeGB1dYCuPbC6GlWFlgmWjCAio8xqQk2xBetWVFL/SxBEyhHp/IHmGUQw5Dk8gVCQ7sRBZR09sZQZlTMxFYmX3lN9IsYLUZdmf2spmnvsMOo0yDenoSSb9IkYXyg8BJHqqFQMy2fnoyI3HYtKsuBweVCSbRpzrhmCIIhEEOn8geYZRDCKxmHGWAmATs65kzHGAHwFwCIAnwB4knPuSYyIqYHHI6C+zYY2mxOFFgOqCs2KA2ExOUNHvxP5Zl8lLLOacLzbjn8f65aOyVVMuWtHS17V3GNHR/8wXF4vzGlaONzekGvF7+22D0OnVsHhCj0nknvYXR6UjvMAKtwzB39WkmVEc69D9txowjBEUs7RvouJxuXyYu9JG9r7nSg061EzzRJx5lGFvJXjcs3QkBv72vvR0T+MfHMaagrMMBi00d9wFKKpo7GSCJ2I5T2mmq5OFP66mGdOQ5ZBjfKc03ricnmx76QNHQNOWE1pGHJ7oNOoYNJqMLfAHJcwL6kYr5FITlQqhpl56ZiZl1hdsg8No+GUAwNOD+wuD3LSdeh1uJFt1EXVDxFA35ATh9vtUn85q8CETEPybf+k8BBENASPayrzjTg4oueFljQInKN70I3cDB3m5WfAaNDFXSaViqEsJ53yZRAEkZSI9pfuQReG3F6f7SYjDUMeL/ocbmSkaZBp0kKrUqGl14GGzgGkp2mQrvPNWcSxF80zCH/CeQ6/DuCskb9/BmAmgJcALAdwJoAb4ypZChFNhmVB4Nha3y5lhtRrVXj82oVweXjAsQ1XLcDKqoIAA47ctXLn+Z+//VAHGjoG8fx/mnF1XQk2bm8IuRYAtta3Y/3WA4rnKBmS/O/x6LbIr4uUcM8syi1+Vmo14FvLKwPeQyxyRFLO0b6Licbl8uKlvSdx98uny+a+S6qxunaa4sQ8lmeM9pqhITde3d+Ou1/xk+vialxUXTCuBuJEZEFPhE4k6j1OReR08d6Lq9Bqc2LpzDwIAg8p+7XLK7F5ZzOuP6cMTb0OrJxbQIYugvDDPjSMbYe70No7FDBG+PZ5s/DAR5/gm5+tDNt+EafpG3Lizf2nQvrLC6pzk9JATBCREDyuKbUa8M3PVAbo+boVlXj2gyb0Oly4/5Jq/E9VfkIMxARBEMmIaH852TsEu8uLR7c1IMuow/XnlAaMte69uArDbi8efOOgdOy282fRnIVQJJxVRMU5d4z8fR6Aqzjnf+Cc3wjgjPiLljrUt9kkoxPgy/J450v7Ud9mCzn3eLddMtKI5+5tsWH91gO4aUk5bl1egZuXlmP91gM43m0f9drbtuwOOc///L0tNjy6rQGraosko2/wteL3hjtHCf97RHNdpIR75uDPVtUWhbyHWOSIpJyjfRcTzd6TNmngDfjkvfvl/dh7MlRHRWJ5xmiv2dfeL00AJLle2Y997f0xPacS0dTRWEmETiTqPU5F5HTxnlfqoWYq1LfZZMt+43Zf2/rzvx/Ckc7BsO8hHILA0XhqEB8c7ULjqUEIQgyu+gSRZAgCR337II50DoaMEX7x1mGsqi0atf0iTnO43S7bXx5up7acSF2C+9ZVtUUhev7otgZctqgYTreAu17ej/3tA9L11H8SBDHVEO0vXXaXNL66bFFxyFjrnlfq0WV3BRzb8I/D0pyF2k8imHCewycYY8s559sBHAcwHUATY8yaEMlSiDabMyDLI+CrfO02Z8iWuo7+0HONOnWIx+7a5ZXosQ8HuPjLXet0C+gccMpuBejod0LgvnMYg+K1PIJzlLYa+N8jmusiJdwz86D7xiJ/tPcUvyfadzHRtCvI29HvVLwmlmeMXkeHFeQaDvs80RJNHY2VROiE0j3G+z1ORZR0sdfhxpDLC7fAZT8X2x2BI+x7UII8u4nJiKjXXkFQHCOIdSeWejMVSVR/SRCJJHh8qjSWZ+z036LOU/9JEMRURLS/AKfbS6W2M9je6z9nofaTCCac5/DNAO5ijO0AoAOwmzH2NoC3AHwnEcKlCoUWg5TlUUSvVaHAErrNL9+sDzm3ONMY4rG7cXsDtGrVqNfqtSrkZchvJ8w366FmCMhAKXet//dG8/1y94j0ukgJ98xKn41VjkjKOdp3MdEUKsibbw7/bmPRh+h0NE1BrjTFe8RCNHU0VhKhE3kZ8uWVl6FcXqmmqxOFki5mGbUosOgV6xDnvt8qhrD1SQny7CYmI6Je52UojxHEuhNLvZmKJKq/JIhEotS3Bv8v5rHw13nqPwmCmIqI9pfg8ZVc2xls5xWP5WWkUftJhKBoHOacn+CcfxbA1wA8BZ+x+AcAzuCcvzXaFzPGfssY62SM7fc79nPG2EHG2F7G2IuMscyR41bG2NuMsUHG2ONhvvPHjLFWxtjukZ/P+312B2PsCGPsEGPsc5E8/HhRVWjGA6urAwysD6yuRlWhJeTcMqsJG65aEHCu0kqPw+Ud9doNVy1AmdUkK1eZ1YSaYgvWrajEq3tasXZ5pey14veGO0cJ/3tEc12khHvm4M9e3dMa8h5ikSOSco72XUw0NdMsuO+SwLK575Jq1E4L1VGRWJ4x2mtqCsy47+IguS6uRk2BOabnVCKaOhoridAJjZrhnlVVAfe4Z1UVNGrlFd5U09WJQk4X7724Cl4uoKrQIluH1i6vxGt7W/G9z81GRV562PqkRDjPboJIVUS93rqvFTPz0kPGCN8+bxZe29s6aj9EnKYwU437Lq4K6i+rUJhJMQOJ1CW4b311T2tIX7xuRSX+tqsFeq0K919SjeqCDADUfxIEMTUR7S9Wk04aX73wcUvIWOvei6uQY9IFHLvt/FmoyEuHRs2o/SRCUAwrwRgr4Zw3c84PADgQ9NlSzvm7o3z37wA8DuBZv2P/AHAH59zDGFsP4A4AtwNwArgLQPXITzh+wTl/OEieeQCuAVAFYBqAtxhjszjnXrkvGG80GhVWzy9CZV462m1OFFj0qCq0yCa6UqkYVlYVYM7apegccCIvQy95z/hXUDlvGrlry6wmRdd/lYph+ex8VOSmY1FJFtxeLzZ/dTEcbi/yzYHXrqwqwJyCDPTYh7F5zWJfxktz+O+Xu4fD5UFJtgkzcsJfFymjPXPwZyVZRiwqyYqofGK9Z6TnJBM6nRqra6ehPMeEjn4n8s161I6SJT6WZ4z2GoNBi4uqC1CWY5Syr9cUmMc1GR0QXR2NlUTohMWgwwu7mvHQFfMx5PLAoNPg2fcb8dAVCyZUrslAsC7mZaQh06jGzByzpCera6dhZo4JHQNOWE1pcLo9+OmlNTDqNJjnl/k3GkTP7uD2nzy7iVRG1OtnPjgBALh4QTGqr6uD3eWB1aRDn9ONR65cMGo/RJzG7dGgOEuLZ284Cx0DTuRn6OERXHB7wkWII4jkRm58OivfiLKcs9A5Mi7k4CizmpCTrkNVQYaUjI76T4IgpiKi/aW5x47uQReeur4OQy4v8jLSsLAkE30ON9L1GmQatBh2C3jyujMw5BZgTFMjfWTO0mIbovaTCCHciPIdxtgTAB4RjayMsXwAjwCYA6Au3BdzzncwxsqCjr3p9++HAK4YOW4H8B5jrCLqJ/BxCYDnOefDAI4xxo4AOAvABzF+X9RoNCrMn54VUfxSlYqhPDddivcpCBwbrloQEvNFzrMv+NpI7lWWk46ynPDnR/u9sdwjVsLJJvdZrM8R6T2jOSeZ0OnUqCvLjuqaWJ4x2msMBi3OmhH/UObR1NFYibdOlFlNuHHJzIjaikTKNVkYTRd1OjXOiLIOjYbo2R3tOyWIZMZfr5/54AT+vLOVYtmNkTKrCQfbB3Dblo8C2orF5dRWEKmN3Pj0rBmjGyio/yQIYqpy2v4S2/XUfhJyhDMOnwHgZ/DFGl4HoAbAbQAeAnD9ONz7RgCbY7juVsbY9QB2AvgO57wXQBF8xmaRlpFjITDG1gBYAwAlJSUx3H78Ic8+Qo5k1FViYknGtoL0dGwk4zudjJCeJhbS69gIp6dUpkSykCztKdUJYjSSRVcJIhwToafUfhJyKBqHR4yuXxsxDL8F4CSAxZzzlrHelDH2IwAeAH+M8tJfA7gfAB/5/Qh8RuaI4ZxvArAJAOrq6vgopycM8uwjgklWXSUmlmRrK0hPx06yvdPJCOlp4iG9jp7R9JTKlEgGkqk9pTpBhCOZdJUglJgoPaX2kwhGMeAmYyyTMfYbADcAWAngrwDeYIwtH8sNGWNfAbAKwBc551EpP+e8g3Pu5ZwLAJ6EL3QEALQC8N8sXjxyjCAIgiAIgiAIgiAIgiAIgpAhXFiJXQB+BeCbnHMPgDcZYwsA/Iox1sQ5/0K0N2OMrQTwfQCf5pw7Yri+kHPeNvLvpQD2j/z9CoA/McY2wJeQrhLAR9F+fzQIAsfxbruUPMHfDT/cZ8mCv4yFFj28AtA5MDZ5k+G54yVDMjxbKsiUzHIlAo9HQH2bDW02JwotBlQVmkdNehdtecVyDyJ1EASOY112NPXYYdJpkG9OQ3GmEU09DulYgSUNggB0DgzD7vKgdAxJQKdyfSUSi5KuiTp/ss8BrVqFviE3ctPToFL5knCSTp5maMiNfe39USdwpX6DmGwIAkdzjx0d/cNwebwwpWlwanAYZoMWGToNBoY9in0a9XsEkfoc+KQe5116bcjxaTmZePbJX02ARBODf1vIIUCjUqPHPgyrKQ0COKymtIDxln/bV5JlRHOvg9pCQiKccXhZcAgJzvluAOcyxr462hczxv4M4DMAchhjLQDuAXAHgDQA/2CMAcCHnPNbRs4/DsAMQMcYWw3gAs75J4yxpwA8wTnfCeChEQM1B3AcwNdG5KpnjG0B8Al84Sq+KSbRiweCwLG1vj0kgPfKqgIAwPZDHdjbYoPAAXOaGvOKLFAzljSVzl/+WXnpuPqsEtz/2ichzxKNnOHKJFHPGy8ZkuHZJkqmaAfQyVhWicLjEfDSnlbc+dJ+6dkfWF2N1fOLFCfh0ZZXLPcgomMiJ41y+vDDC+fAmKYJeOf3XlyFYbcXD75xUFZvIl38m8r1lUgsSrp2wdx8vHmgA+u3HsDVdSXYuL1B+vwnq2vw9/oGrF5YQjoJn2H41f3tuPuV023BfRdX46LqgrAGYo9HwIu7W3HXy6evu/+Saly6gPoNIjURBI7thzrQ0DGI5//TjOsWl+HhNw9J+r1uRSWe/aAJvQ5XSJ9G/R5BTA7cXIWcC78VcvzkG49NgDQTgyBwvHukEy29Try46wQuX1SCe1+rl9q2tcsrsXlnM247fzamZerhdAl4dNshnF2eC4teDWuGHj96cR+1hYSE4qgwXGxhzvmTo30x5/wLnPNCzrmWc17MOX+ac17BOZ/OOV8w8nOL3/llnPNsznn6yPmfjBy/ecQwDM75dZzzGs55Lef8Yj8vYnDOf8I5n8k5n805fyPSAoiF4912aVABAE63gNu27Mbxbjuae+xo6BjEph2NeOHjFng5cPPvd+ILT/4bn9/4LrbWt0MQJjbkkSh/llGHWz5TIRmGg58llu8c6/eMhXjJkAzPFsyxLnmZjnWNn0ziAPrzG9+NWH+TsawSRX2bTTLgAb5nv/Ol/ahvsyleE215faJwj0/C3IOInFh0fjyR04cuuyvknd/zSj267C5ZvfF/htu27MEb+9vxP4/JP89Urq9EYlHStfo2G27bshuraoskw7D4+Y9e2oerzyzD+q0HSCcB7G/vlwzDgK+M7n5lP/a394e/7qRNMgyL19318n7sP0n9BpGaHO+2Y2+LDY9ua8CVZ0yXDMOAT78f3daAyxYVy/Zp1O8RBDFZaO6xwzEs4P7XPsH155ZLhmHA17Zt3N6AVbVFuP2FvXjnUBe++txOXL6oBK/tbYXN6ZUMw+L51BYS5DIQAx39TqkiiTjdAjoHnOjoH8aj23wTnMsWFUt/i+ckQ6UT5b9sUTEOtvcrPkss3znW7xkL8ZIhGZ4tmKYeu6xMzT3jp1uxDKCTsawSRZtN/tnbbcrPHm15nVS4R5ttOEapCX8metIopw8Ch+w7D7ZXi3rj/wyj9UFTub4SiUVJ18R2kzF5Pd/T0odVtUWkkwA6+odly6hjIHz739o3JHtda9/QuMtIEImgo98p9Y256Wmy+s3Y6b/92w/q9wiCmCx09A/jwIgtZ2jYo9gW+v++97V6rKotUhx3UVs4tSHjcAzkm/XQawOLTq9VIS9DD7vrdMVM1konys+Yz/Cg9CyxfOdYv2csxEuGZHi2YEw6jaxMRl24SDHREcsAOhnLKlEUWgyyz15gUX72aMvLbJB/7+l6dYxSE/5M9KRRTh/UTL6NDt7xJeqN/zOM1gdN5fpKJBYlXSu0nD4u97lXANQqkE4CyMnQyZaR1aQLe112uvx12aNcRxDJSr5ZL/WNxjT5cZGY8jy4T6N+jyCIyYLd5ZFsOeHaQv820X/xjNpCIhgyDsdAmdWEDVctCJjQbLhqAcqsJpRmmwIqWjJWOlF+NQNe3dOKtcsrA55l/eW1KLOaYvpOuTJJFPGSIRmeLZh8cxrWrQh8b+tWVCLfnDaO94h+AJ2MZZUoqgrNeGB1dcCzP7C6GlWFFsVroi2vQrNB9r1PsxjG+WmmJhM9aZTTB6tJF6JX915chRyTTlZvgp8h3PNM5fpKJBYlXasqtGDDVQtkxyLfPm8WXtvbirrSbNJJAPkZabjnoqqAMrrnoioUjNLvZxo0stdlGsdvMZkgEkmZ1YSaYgvWrahEW58Dt50/K2Rc9LddLbJ9GvV7BEFMFkqzTdL46ffvN+KeVYF9/drllXhtr+/zv+1qkY5zDrzwcUvIuIvaQoJxPrHxbyeSuro6vnPnzpiuFRP+dA44kZcRmHVbTHSQZdTh+nNKpW29yRToW8xsuau5D49uO4xVtUVQq4C60mycW26NKUmJUpkkknjJMMbvHbMAwboqJuMQEx+qGFBbbMHy2fnjVuaxJu1IBj2YKMSM8O02JwoselQVWkatS9GUV5zf+7jraaqRDIlqBIHjWJcvfr1Rp0G+OQ3FmUY09TikYwWWNAgC0DkwDIfLg5JsE2bkxNYHpWB9nfJ6mqqEGzcdPTWI5l47DBoN2mxDaLM58ZePT+A758/G56sLUzVx2ph0Va7ff7ehEwNOL+wuD0w6DTL0aiytzAtbZz0eAdsOdcDt4dJ1Wg3Ditn5qVquxPgyrnqaKMR5TPegCydtTrT0OpBt1MFi0CLTqEW33YXZ+Rkoz00PqR8p2O8R1PdPGs679FrZRHLbH/4Gln/3V2M+3vXGY3jrxT+Nj7DRk1A9Fcf867cewKraIhSadajMN8M25Ea2SQcOjiGXgLte3oem7iEpIe3jbzegqXsIpVYD7r+kBlo1S3gSbmJCUXzJ5DYQIyoVQ3luOspz00OOr6wqwJy1S9E54ESBWY8L5hXg1GByDUBUKoaynHSUZJuwYHrmuAyQlMokkcRLhmR4Nn9UKobls/NRnpMet8FtsC5Heo9kK6tEotGoMH96FuZPj/yaaMorEe99KhOrzo+3DDPz0jEzL1Af5I7NkNGZaPugqVxficQSbtxUmZ+BGVYTDnb0w8v1MBu0ePr6M2UNO1MVlYphaWVe1EYtjUaFFbPzo164JIhkRpzHlOUACwWOxlODONZth16rRrpeg7rSbEUdp36PIIjJgDTmL8hQHBcIAsczXzlL+rwky4gzSrNoHknIQsbhOCA36Aie1CcLNEBKXRLx7kg/kg96J/FlMpRvKvVBBCGi0ahQXZQ50WIkNbG2T7EsXBJEqqBSMVTkZ6AiP2OiRSEIgkgoo40L5D5P9XkOET/IbYAgCIIgCIIgCIIgCIIgCGIKQp7DBEEQBEEQBEEQBEEQk5zrv/oNnOzqCzk+LScTzz4ZGseXIIipARmHCYIgCIIgCIIgCIIgJjknu/pkk8KdfOOxCZCGIIhkgYzDBEEQBEEQBEEQBEEQkwQlD+GDhxuw5MLEy0MQRHJDxmGCIAiCIAiCIAiCIIhJgpKHsKv+GxMgDUEQyQ4lpCMIgiAIgiAIgiAIgiAIgpiCkHGYIAiCIAiCIAiCIAiCIAhiCkJhJcIgCBzHu+3o6Hci36xHmdUElYpNtFgpC5UnQYQSbb2gekSMBUHgONZlR1OPHSadBvnmNJRkkw4RkxOPR0B9mw1tNicKLQZUFZqh0Uw9vwgqB2IqQfpOEMRUxn+uaNRp4PJ6YTWl0ZyRGBUyDisgCBxb69tx25bdcLoF6LUqbLhqAVZWFVCligEqT4IIJdp6QfWIGAty+rNuRSUq89OxfHY+6RAxqfB4BLy0pxV3vrRf0vcHVldj9fyiKWUoonIgphKk7wSRHFAyvIlBbqy/dnklNu9sxu0r59KckQgL9ZIKHO+2S5UKAJxuAbdt2Y3j3fYJliw1ofIkiFCirRdUj4ixIKc/j25rwN4WG+kQMemob7NJBiLAp+93vrQf9W22CZYssVA5EFMJ0neCSA7EZHjBPy63Z6JFm9TIjfU3bm/AqtoimjMSo0LGYQU6+p1SpRJxugV0DjgnSKLUhsqTIEKJtl5QPSLGgpL+CBykQ8Sko80mr+/ttqml61QOxFSC9J0giKmM0lifMZozEqNDxmEF8s166LWBxaPXqpCXoZ8giVIbKk+CCCXaekH1iBgLSvqjYiAdIiYdhRaDrL4XWKaWrlM5EFMJ0neCIKYySmN9zmnOSIwOGYcVKLOasOGqBVLlEmN7lllNEyxZakLlSRChRFsvqB4RY0FOf9atqERtsYV0iJh0VBWa8cDq6gB9f2B1NaoKLRMsWWKhciCmEqTvBEFMZeTG+muXV+K1va00ZyRGhRLSKaBSMaysKsCctUvROeBEXoaeMjyOASpPgggl2npB9YgYC6L+zP7WUjT32GHUaZBvTkNJNukQMfnQaFRYPb8IlXnpaLc5UWDRo6rQMuWSUlE5EFMJ0ndiMqOU5G1aTiaeffJXiReISDr854od/U4YdWq4vQJWVhfQnJEYlbgahxljvwWwCkAn57x65NjPAVwEwAXgKIAbOOd9jDErgL8COBPA7zjnt47y3d8B8DCAXM55F2PMAuAPAErge66HOefPjEV+lYqhPDcd5bnpY/kaYgQqT4IIJdp6QfWIGAsqFcPMvHTMzCP9ISY/Go0K86dnYf70iZZkYqFyIKYSpO/EZEVM8hZy/I3HJkAaIlmhuSIRK/FeRv0dgJVBx/4BoJpzXgvgMIA7Ro47AdwF4LujfSljbDqACwA0+x3+JoBPOOfzAXwGwCOMMd1YhCcIgiAIgiAIgiAIgiAIgpisxNVzmHO+gzFWFnTsTb9/PwRwxchxO4D3GGMVEXz1LwB8H8DL/l8NIIMxxgCkA+gB4Ild+uREEDiOd9vR0e9Evpm2lBOpD+k0QcQfqmcEMXZStR6lqtwEAZD+EgRByEFtIzHeTHTM4RsBbI7mAsbYJQBaOed7fHZgiccBvALgJIAMAFdzzgWZ69cAWAMAJSUlMYo9MQgCx9b6dty2ZTecbkFKRrWyqoAagklIKutqpJBOpz5TQU9THapnpKfE2ElEPYqHnlL9J8abRLanpL/EWKC+P/4oxUE+eLgBSy5MvDypSCx6Sm0jEQ8mLDo/Y+xH8Hn2/jGKa4wAfgjgbpmPPwdgN4BpABYAeJwxZg4+iXO+iXNexzmvy83NjUHyieN4t11qAADA6RZw25bdON5tn2DJiHiQyroaKaTTqc9U0NNUh+oZ6SkxdhJRj+Khp1T/ifEmke0p6S8xFqjvjz9iHOTgH5d70m3gjhux6Cm1jUQ8mBDjMGPsK/Alqvsi55xHcelMADMA7GGMHQdQDGAXY6wAwA0A/sZ9HAFwDMCccRV8gunod0oNgIjTLaBzwDlBEhHE2CCdJoj4Q/WMIMZOqtajVJWbIADSX4IgCDmobSTiQcKNw4yxlfDFC76Yc+6I5lrO+T7OeR7nvIxzXgagBcAiznk7fMnpVozcIx/AbACN4yr8BJNv1kOvDXxleq0KeRn6CZKIIMYG6TRBxB+qZwQxdlK1HqWq3AQBkP4SBEHIQW0jEQ/iahxmjP0ZwAcAZjPGWhhjN8EXGzgDwD8YY7sZY0/4nX8cwAYAXxk5f97I8acYY3Wj3O5+AOcyxvYB2Abgds551/g/1cRRZjVhw1ULpIZAjC1TZjVNsGTKCAJH46lBfHC0C42nBiEI0TiKExNNvN9fKuo0QQST7O0c1TOCGBuCwME58PAV87FuRQUKLfqUqUdlVhMev3Yh1q6owK3LK7BuRQUev3Zh0stNEED8+69k778JgiDkCG4bS60GbLquDh39TmrLiJiJa0I6zvkXZA4/Heb8MoXjN492Puf8JIALopMwtVCpGFZWFWDO2qXoHHAiLyO5s1JSoPTUJhHvL9V0miCCSYV2juoZQcSOXB1/8NIaLCrJREl2atQjl4dj047GgDaKIFKBePZfqdB/E5MbpWRu03Iy8eyTv0q8QETK4N829tiH0drnxJrndlJbRoyJuBqHifFHpWIoz01HeW76RIsyKkqB0uesXZpw+QWB43i3HR39TuSbyTASCYl6f6mk06kK6X98EASOfa19ONjej5uXluOFj1vQZnNOWDsXDqpnBBEbcn3ho9sOY+M1C/HvY91J36Ye77Zj/dYDuGlJOdiIiOu3HsCcggxqD4iUIF79F9UNYqIRk7mFHH/jsQmQhkgVgud1Oelp+NLTHyWFzYVIbcg4TMSNcIHSE9lQkWdAbCTL+yPGBul/fJAr17XLK/Hch01oszmpnhDEJCG4Lyy06HF1XQmu3vRhSrSp3fZhXF1Xgo3bGwLaqh77MLVRxJSG6gZBEKmG0m6mLKMObbbTyehozk7EQsIT0hFTh2QJlK7kAXu8255QOVKNZHl/xNgg/Y8PcuW6cXsDLltUTPWEICYRwX3hZYuKJWMSkPxtqk6tCpF34/YGaNU0BSCmNlQ3CIJINeTmHz98cR+urCsOOI/mIkQsUO9HxI1kSYIUzgOWUCZZ3h8xNkj/44NSuapVoHpCEJOI4L5QrUJKtakOl1dWXofLO0ESEURyQHWDICYfBz6px3mXXhvyc/1XvzHRoo0LSvOPWfkZNGcnxgyFlSDiRrIkQRK9fvwbUlpNG51keX/E2CD9jw9K5bpiTh5qijKpnhDEJCG4LzRoNVJyN5FkblOV2qp8c3LKSxCJguoGQUw+3Fw1qeM4K7VbcwvMeJ3m7MQYIc9hIq6ISSQWl+egPDd9Qhop8oCNnWR4f8TYIP2PD0rlSoZhgph8+PeFNUWWlGpTqQ8gCHmobhAEkWootVszckw0ZyfGDHkOE5Me8oAlpjKk//GBypUgpiapVvdTTV6CSBRUNwgiEDEkQzDTcjLx7JO/mgCJiGCo3SLiCRmHiSmB6PVDGTuJqQjpf3ygciWIqUmq1f1Uk5cgEgXVDYI4jVJIhm2P3CJrNAaAg4cbsOTCeEsWP67/6jdwsqsv5HgyG8Sp3SLiBRmHCYIgCIIgCIIgCIKYckRrIEw2g6KSx+94GW6VjMYA4KpP7URvJ7v6ojKIJ7PRmCDGChmHCYIgCIIgCIIgCIKYckRrIDx4uAFL1m0M/Z4JSnqmZLxNdcPteBKtAX2yJ7YjCDkY53yiZZgwGGOnADQpfJwDoCuB4ihBciSXDED0cnRxzleO5Yaj6Gq0JEs5BkNyRcd4yxVvPZ3ocpzI+0/lZx/v+8dTTye6nKIlleSdirKOSVeTvD31h2SRJ1VkiaeexkqylF0yyJEMMgATL0ei5lIT/ZxyJKNMAMklR7LN+SNlot8lzdESi6KeTmnjcDgYYzs553UkR/LIkQwyJJMcsZKs8pNc0ZGscikx0fJO5P2n8rMnw/0jJVXkFEkleUnW8SWZZCRZ5CFZYidZ5E0GOZJBhmSSI94k43Mmo0wAyTWZmOgyozla8uiraqIFIAiCIAiCIAiCIAiCIAiCIBIPGYcJgiAIgiAIgiAIgiAIgiCmIGQcVmbTRAswAslxmmSQAUgeOWIlWeUnuaIjWeVSYqLlncj7T+VnT4b7R0qqyCmSSvKSrONLMslIsshDssROssibDHIkgwxA8sgRb5LxOZNRJoDkmkxMdJnRHC1JoJjDBEEQBEEQBEEQBEEQBEEQUxDyHCYIgiAIgiAIgiAIgiAIgpiCkHGYIAiCIAiCIAiCIAiCIAhiCkLGYYIgCIIgCIIgCIIgCIIgiCkIGYcJgiAIgiAIgiAIgiAIgiCmIGQcJgiCIAiCIAiCIAiCIAiCmIKQcZggCIIgCIIgCIIgCIIgCGIKQsZhgiAIgiAIgiAIgiAIgiCIKQgZhwmCIAiCIAiCIAiCIAiCIKYgZBwmCIIgCIIgCIIgCIIgCIKYgpBxmCAIgiAIgiAIgiAIgiAIYgpCxmGCIAiCIAiCIAiCIAiCIIgpCBmHCYIgCIIgCIIgCIIgCIIgpiBkHCYIgiAIgiAIgiAIgiAIgpiCkHGYIAiCIAiCIAiCIAiCIAhiCkLGYYIgCIIgCIIgCIIgCIIgiCkIGYcJgiAIgiAIgiAIgiAIgiCmIGQcJgiCIAiCIAiCIAiCIAiCmIKQcZggCIIgCIIgCIIgCIIgCGIKQsZhgiAIgiAIgiAIgiAIgiCIKQgZhwmCIAiCIAiCIAiCIAiCIKYgZBwmCIIgCIIgCIIgCIIgCIKYgpBxmCAIgiAIgiAIgiAIgiAIYgqStMZhxthvGWOdjLH9fsd+zhg7yBjbyxh7kTGW6ffZHYyxI4yxQ4yxz0Vyj5UrV3IA9EM/8f4ZM6Sr9JOAnzFDeko/CfgZM6Sn9JOgnzFBeko/CfoZE6Sn9JOgnzFDuko/CfgZM6Sn9JOAH0WS1jgM4HcAVgYd+weAas55LYDDAO4AAMbYPADXAKgaueZXjDH1aDfo6uoaT3kJIm6QrhKpAOkpkQqQnhKpAOkpkQqQnhKpAukqkQqQnhITSdIahznnOwD0BB17k3PuGfn3QwDFI39fAuB5zvkw5/wYgCMAzkqYsARBEARBEARBEARBEARBEClG0hqHI+BGAG+M/F0E4ITfZy0jxwiCIAiCIAiCIAiCIAiCIAgZNBMtQCwwxn4EwAPgjzFcuwbAGgAoKSkZZ8mIaBEEjuPddnT0O5Fv1qPMaoJKxSZarKSAdDX1mIr6nCp6OhXfDXGaWPSUdIZINPFqT0mXifEkVfr9ZIXqY+IgXU08pN/RQ3pKJAspZxxmjH0FwCoAKzjnYkDlVgDT/U4rHjkWAud8E4BNAFBXVxc2IDMRXwSBY2t9O27bshtOtwC9VoUNVy3AyqoC6kRAuppqTFV9TgU9narvhjhNtHpKOkNMBPFoT0mXifEmFfr9ZIXqY2IhXU0spN+xQXpKJAspFVaCMbYSwPcBXMw5d/h99AqAaxhjaYyxGQAqAXw0ETISkXO82y51HgDgdAu4bctuHO+2T7BkBBE9pM/JC70bIlpIZ4jJAukyQSQPVB+JyQzpN0GkNklrHGaM/RnABwBmM8ZaGGM3AXgcQAaAfzDGdjPGngAAznk9gC0APgGwFcA3OefeCRKdiJCOfqfUeYg43QI6B5wTJBFBxA7pc/JC74aIFtIZYrJAukwQyQPVR2IyQ/pNEKlN0oaV4Jx/Qebw02HO/wmAn8RPImK8yTfrodeqAjoRvVaFvAz9BEpFELFB+py80LshooV0hpgskC4TRPJA9ZGYzJB+E0Rqk7Sew8Tkp8xqwoarFkCv9amhGJeozGqaYMkIInpIn5MXejdEtJDOEJMF0mWCSB6oPhKTGdJvgkhtktZzmJj8qFQMK6sKMGftUnQOOJGXQRlNidSF9Dl5oXdDRAvpDDFZIF0miOSB6iMxmSH9JojUJmHGYcZYHgBpTwHnvDlR9yaSF5WKoTw3HeW56RMtCkGMGdLn5IXeDREtpDPEZIF0mSCSB6qPxGSG9JsgUpe4h5VgjF3MGGsAcAzAPwEcB/BGvO9LEARBEARBEARBEARBEARBKJOImMP3A1gM4DDnfAaAFQA+TMB9CYIgCIIgCIIgCIIgCIIgCAUSYRx2c867AagYYyrO+dsA6hJwX4IgCIIgCIIgCIIgCIIgCEKBRMQc7mOMpQN4F8AfGWOdAOwJuC9BEARBEARBEARBEARBEAShQCI8hy8B4ADwvwC2AjgK4KIE3JcgCIIgCIIgCIIgCIIgCIJQIO6ew5xzO2OsFEAl5/z3jDEjAHW870sQBEEQBEEQBEEQBEEQBEEoE3fPYcbYVwH8FcBvRg4VAXgp3vclCIIgCIIgCIIgCIIgCIIglElEWIlvAvgUgH4A4Jw3AMhLwH0JgiAIgiAIgiAIgiAIgiAIBRJhHB7mnLvEfxhjGgA8AfclCIIgCIIgCIIgCIIgCIIgFEiEcfifjLEfAjAwxs4H8BcArybgvgRBEARBEARBEARBEARBEIQCiTAO3w7gFIB9AL4G4HUAdybgvgRBEARBEARBEARBEARBEIQCmnh+OWNMDaCecz4HwJPxvBdBEARBEARBEARBEARBEAQROXH1HOacewEcYoyVxPM+BEEQBEEQBEEQBEEQBEEQRHQkIqxEFoB6xtg2xtgr4k8kFzLGfssY62SM7fc7ls0Y+wdjrGHkd9bIccYY28gYO8IY28sYWxSn5yEIgiAIgiAIgiAIgiAIgkh54hpWYoS7xnDt7wA8DuBZv2M/ALCNc/4zxtgPRv6/HcCFACpHfs4G8OuR3wRBEARBEARBEARBEARBEEQQcTcOc87/OYZrdzDGyoIOXwLgMyN//x7AO/AZhy8B8CznnAP4kDGWyRgr5Jy3xXp/giAIgiAIgiAIgiAIgiCIyUrcw0owxhYzxv7DGBtkjLkYY17GWP8YvjLfz+DbDiB/5O8iACf8zmsZORYszxrG2E7G2M5Tp06NQQyCiC+kq0QqQHpKpAKkp0QqQHpKpAKkp0SqQLpKpAKkp0SykIiYw48D+AKABgAGADcD+OV4fPGIlzCP8ppNnPM6znldbm7ueIhBEHGBdJVIBUhPiVSA9JRIBUhPiVSA9JRIFUhXiVSA9JRIFhJhHAbn/AgANefcyzl/BsDKMXxdB2OsEABGfneOHG8FMN3vvOKRYwRBEARBEARBEARBEARBEEQQiTAOOxhjOgC7GWMPMca+Pcb7vgLgyyN/fxnAy37Hr2c+FgOwUbxhgiAIgiAIgiAIgiAIgiAIeRJhHL5u5D63ArDD5917eSQXMsb+DOADALMZYy2MsZsA/AzA+YyxBgDnjfwPAK8DaARwBMCTAL4xng9BEARBEARBEARBEARBEAQxmdDE+wac86aRP50A7o3y2i8ofLRC5lwO4JvRSUcQBEEQBEEQBEEQBEEQBDE1SUjMYYIgCIIgCIIgCIIgCIIgCCK5IOMwQRAEQRAEQRAEQRAEQRDEFCTuxmHG2JWRHCMIgiAIgiAIgiAIgiAIgiASRyI8h++I8BhBEARBEARBEARBEARBEASRIOKWkI4xdiGAzwMoYoxt9PvIDMATr/sSBEEQBEEQBEEQBEEQBEEQoxM34zCAkwB2ArgYwMd+xwcAfDuO9yUIgiAIgiAIgiAIgiAIgiBGIW7GYc75HgB7GGN/5JyTpzBBEARBEARBEARBEARBEEQSEc+wEls451cB+C9jjAd/zjmvjde9CYIgCIIgCIIgCIIgCIIgiPDEM6zEupHfq+J4D4IgCIIgCIIgCIIgCIIgCCIG4hlWom3kd1O87kEQBEEQBEEQBEEQBEEQBEHEhireN2CMXcYYa2CM2Rhj/YyxAcZYf7zvSxAEQRAEQRAEQRAEQRAEQSgTz7ASIg8BuIhzfiAB9yL+P3tXHh9Feb+fmb3vbDYnCZuwJOHIAYSAaAkqUIs2inKI1WKr2NRWBLW2VH8qItaKVawUrcVaq7RWbGlVUKkKKlrxAJUzAUJIQiD3sZu9j5nfH5uZ7OzOTJIlFzDP59NPzbKzc73H933e5/t8JUiQIEGCBAkSJEiQIEGCBAkSJEiQIKEPGHTlMIAmiRiWIEGCBAkSJEiQIEGCBAkSJEiQIEGChJGFoVAO7yUIYguANwD4mA9pmv73EJxbggQJEiRIkCBBggQJEiRIkCBBggQJEiTwYCjIYSMAN4ArIj6jAUjksAQJEiRIkCBBggQJEiRIkCBBggQJEiQMEwadHKZp+paB/k2CIO4GcBvCJPNBALcASAfwGgALgH0AltI07R/oc0uQIEGCBAkSJEiQIEGCBAkSJEiQIEHC+YBBJ4cJgngJYRKXA5qmb43z9zIArAAwkaZpD0EQrwO4AcBVAJ6mafo1giCeB7AMwB/jv3IJEiRIkCBBggQJEiRIkCBBggQJEiRIOH8xFLYS2yP+Ww3gOgBnzvI35QA0BEEEAGgBNACYDeDG7n9/GcDDkMjhQQVF0ahpc6HJ4UWqUY1siw4kSQz3ZUmQMGyQ+oSECwXnc1s/n+9NggQJ5x6kMen8hvR+JUjgh9Q3JEgYWgyFrcTWyL8JgvgHgE/P4vdOEwTxJIA6AB4A7yFsI9FJ03Sw+2v1ADL4jicIohxAOQBYrdZ4L+OCB0XR2HG4Efe8/i28AQpqBYn110/GvPy0IRm0L4TJQmqr5xaGu0/0dm2D1V+kdnr+I7r9WM1avFfRNCLbuhD62k6j+3GWRYO18wuhkBHn7VwjYeRAGk8lRIOiaOw62oQD9XZQNCAjgMJME2aPSx22sUhqp31DX2KvkRw7ng+Q2uq5h8h+EwzReODNg6ht85zXfUNqpxJGCgiajnF8GNwTEsQ4AG/TNJ0T5/FmAFsBLAHQCeCfAP4F4GHmNwmCGA3gXZqmC8R+q6SkhN67d288l3HBo7rFias2fAJvgGI/UytIvLOiFLZk/aCe+xwMpM76oqS2OvIxnH1CDP3oL1I7lRADvvazbmER1r9/FLVtHvZ7Q9jWB7WdRvbjdJMaS2dkYcOu4+fKXCNhZOGsGok0nkoAgJpWJ9491IhndvaMQyvn5OLKgjRkJw3IeCu100FAX2OvkRo7jkBIMeoFAL5+s2J2LjZ/XosGu/dc6BtSO5VwLkCwnZKDfmaC6CIIwsH8D8A2AKvO4ifnAjhJ03QLTdMBAP8G8B0ACQRBMEroTACnz+rCJYiiyeHlBDIA4A1QaO7yDvq5a9pc7KTBnPee179FTZtr0M8tQYIQhrNPiEHqLxLOBnztZ9XWAygr4ibnjIS2PhCI7McLijNZYhiQ+o4ECRKGHk0OH0sMA+Fx6Jmdx9Hk8A3zlUkQQ19jr5EaO0qQMBzg6zcbdh3HguJM9m+pb0iQMHgYdHKYpmkDTdPGiP/lRVtN9BN1AGYQBKElCIIAMAfAEQAfAljU/Z0fAXjz7K5cghhSjWqoFdzmo1aQSDGoB/3cUiAlYSRiOPuEGKT+IuFsINR+ZFHRw0ho6wOByH5MEJD6jgQJEoYVLn+Qdxxy+4MCR0gYCehr7DVSY0cJEoYDQv2G6NY5Sn1DgoTBxaCTwwMNmqa/QNhG4msABxG+h00Iq5HvIQiiCoAFwIvDdpEXALItOqy/fjIb0DDpUtkW3aCfWwqkJIxEDGefEIPUXyScDYTaT0lW4ohr6wMBvn4cCanvSJAgYSiRlajjHYesief+eHs+o6+x10iNHSVIGA4I9RualvqGBAlDgUEvSDcYoGl6NYDVUR9XA5g+DJdzTmGgClORJIF5+WkYv6IUzV1epBiGrlAPE0hF+3hJk4WE4US8fWKwiysOd3+5EIpHns8Qaj+X2Cx4ZxjG/8FGZD9ud/mQm6LHqq0HpLlGgoTzEOfC/DQmiX8MHpMkjUMjGX2NvZg5Z9ydpahrd0GrlCPVqBqmq5YgYXjB12/WLSxCRoIaC6ZkQEYCX5xsG7HjtQQJ5zoGjRwmCGIMTdMnB+v3JfQfA13IjSQJ2JL1Q24KP5zEtAQJYuhvnxiK4orD2V/OweKREqIg1n6GY/wfCjD3lm3RodPThPJZNlA0QBKAUi61WwkSzgecK/OTFPOem+jvezva1DXi26IECYMNoX4D4JwYryVIONcxmLYS/wIAgiB2DuI5JPQD51NhKmbxPsOWBFuyXpoYJJyTGKo+OVz95Xwacy5kXKjjbU2bC8tf/QYbdlZh464qbNhZheWvfiO1XwkSzgOcS/PThToGn+vo63s7l9qiBAmDDb5+I/URCRKGBoNJDpMEQdwPII8giHui/zeI5z2vQFE0qluc2HOiFdUtTlAUHfdvSYWpJPQXA9n+JMTifO+T5/v9STi/IbVfCRLOX0j9W8JIgdQWJUgQh9RHJEgYGgym5/ANAK7tPodhEM8zJBgOX7KBTnljTN4jB1epuI4EIZwrKZeDhaHo8+d7n0wx8N9fsv78uD8J5zek9itBwvkLqX9LGCmQ2qIECeKQ+ogECUODQSOHaZo+CmAdQRAHaJp+d7DOMxQYLpJMKIVi/IrSuHweh7sw1bmAc6E4yVBhoNvfuYR4+3x/28/53idJArj/yvFodflB0YCMACw6JS7QLiXhHIPUfiVIOH8h9W8JIwVSW5QgQRxSH5EgYWgwmMphBp8RBLEewKzuvz8G8AhN0/YhOPeAYLhIMrEUinjOKxW1EMeFrpSNxkC3v3MJ8fT5eNrP+d4n6zvd8AQobNpdzT6Tu+fm4XSnG2PO8zYk4dyH1H4lSDh/IfVvCSMFUluUIEEcUh+RIGFoMBTk8F8AHAJwffffSwG8BGDBEJx7QDBcJNlgpJyfzxXmzxZ8hOC6HRXISFDD7Q9dcEri893yQAxNDi/MWiUWFGeC6H7dW/fVi/b5eDeRzuc+qZLJ8PQHxzjP5OkPjuGVW6YP85VJGGqcK1kZkdepksvw6pe1UvuVIOE8xHDMT+fKOCihfzjb9yrFShIkxEKKx84d3HhLOc60dMR8PirZjFdf2jQMVyQhXgwFOTyWpumFEX+vIQji2yE474BhuEiy8z3lfKQhehMg3aTGkhIrlmz6/IJUEl/I7S/dpMbNF2fhmZ3H2XtfOScXaUbhPn8hK62F4PIHeZ+Jyx8cpiuSMBw4V7Iy+K5zxexcbP68Fg32cNETqf1KkHB+YKjnp3NlHJTQPwzEe5ViJQkSuJDisXMLZ1o6kHbNPbGfv7V+GK5GwtmAHIJzeAiCmMn8QRDEdwB4huC8AwaGJFMrwo9rqEgyJuX8nRWleK38IryzolQKIgcRzCYAgwXFmdiw63iMErSmzTVclzikuJDbX4gCSwwD4Xf/zM7jCFHCx0S3H+DCUVoLwZqo430m1sTzf4NBQg+EVPUjbSzlu84Nu45jQXEm+x2p/UqQcH5gqOenc2UclNA/DMR7lWIlCRK4kOIxCRKGB0NBDt8O4FmCIGoIgqgBsBHAT4fgvAOG4STJmJTzGbYk2JL1FwQxN1yI3gSQkRBUgl4ouFDbX3MXvwq4xSn87odrE2kkY0wS/zMZk3ThPpMLEWKq+pEEoeuUdUdKUvuVIOH8wVDPT+fKOCihfxiI9yrFShIkcCHFYxIkDA8G3VaCpun9ACYRBGHs/tsx2OccDJzPvqASwoguDqZRyFnjewYXuhL0QkE8VjLne3G5eCA9EwnAueNfLnSdc8an4JKxFqn9SpBwHmGo56dzZRyU0D8MxHuVYiUJEriQ4jEJEoYHQ6EcBhAmhc9VYljCwIGiaFS3OLHnRCuqW5ygKHpEXUekUrYww9SrEnSk3M+FhsF+7vGqgONRWvf3Xs7VNkcP0GWeq/d/IYOvPz12XSFIAiPq/VnNWmxaWoIVc3KwfHYOsiwaPLV4MmQkgU53AF3e4Ii6XgkSJAwMBmp+EsPZZBdJ897IRX/eK/Mev6ppw/5THbzvcyjaogQJIxkURYMkgMeuK0SWRYM7Ls/Bijk5eGFpCRK0CqmPSJAwiBiKgnQXPAarOvG5VvV4pBTj6Ot19LaTP1Lu50LDUDz3oVJx9PdezrU2N1DXy4x1bS4fznR6sWrrgXPi/i80CM1JTH8ad2cpKhodONbUhd/99yg63P4R8/4oisZ7FU2ctrpuQRHkMmDR83vYzx69tgDXTsqAXB67t36uzckSJIw0DGUfGo75VCknUD7LBooGSCL890i8Tgl9R1/jReY9rttRgSUlVramCbNZqlXKcNeWbzmfFVsTYE2U5hEJ5w96G+Mjx7u8FD3KZ43F2u1HOMXBX9lTO6LiRwkSzicQ9AW8/VJSUkLv3bt3UM8Rb1DXn8FzJAWLYtdd3eLEVRs+iUkReWdF6YDYdfR1UTFQ19GP3znrFzIUbfVcwYlmJ77/h9jn/vadpRibIvz+RiJx09+2GO+99xED3k77e3+RJLBSRsLtDyHFoMbJNieWv/oNls204cVPY61eBmoMkRA/+jInDdDYOyjjqdC1lc+yYcPOKs5nf1t2EYqt5nNiTpYwrDirF3+hzftD3YfOZj6NJ56Id/w7m3Gzj9d5QbfToYoNmfcoFMfwzTXls2wYn2bk9IGRGMsOEaS11DmO6DE+y6LBb64rhD9AQaeSI9WoQogCOy7fcXkOb19ZNtOGZz+sGsj1z0Digmynl5UtRto198R83vjWeny0/Z/DcEUSeoFgOx105TBBEFoAvwBgpWn6JwRB5AIYR9P09sE+93AgetKmafBWsR0vEtT1JUAWqo4r9ruDjd6uW6xow9lec38WFQN1HYN5PxKEUdvu4n3ude0uwQBhpBI3Qm2oycHfhuriuHdg+BYT/ekjYqqalXNyYdYqoZKT/XpeEgYOvbWhvsxJI3nMbLTzX1t09rY3QKG6xYnmLh+umJCKug43mhxeaJWyETcnS5AwXIhnzhnquDaeWAKIP56Id/zrb5xwttd5IWEonxHzHgmCv9g131xDda8hmT4gvVMJ5zIix/h0kxo3Ts/CbS/v5cT61kQt2z+E+gpB9Px3b+O1BAkS+oeh8Bx+CYAPwMXdf58G8OjZ/CBBEAkEQfyLIIhKgiAqCIK4mCCIRIIg3icI4nj3/5vP9sL7C2bSvmrDJ/jBC1/gqg2foKLB0e8qtkIBck2bi/0OE2Skm9S44/KwP+JtpTa0u3yDc3N9QG/XzZjLR2KginH05ZkB4XekVcoH5DoG834kCEMn8P60SuG9rr62j0gMhcefUFvUKmW839ep+L+vE7l3vnFpx+HGIfEs7E8fYd7RDdOs8AZDuK3UhuWzc2DWKvHMzuNYUJyJMUm6fj0vCQODvrShvlRsTzGM3DFTJSd5ry16va1WkEg1qbFuRwU+q25jn8nOyuazrlgvQcL5gHjnnL6MIWLn7O98HU8sAcQXTwDxx4z9jRPO9jovJAzEM+pr24t8/32da2gaMGuVaOnyYc+JVhw8bce6HRXSO5VwTiJyjF9QnImnPzjGacvP7DwOGtz+wddXxqUakG5S92m8liBBQv8wFOTwWJqmnwAQAACapt04e8n9MwB20DQ9HsAkABUAfg1gJ03TuQB2dv89pOALMo43d/U7GOwtQGYIziyLBktnZOHFT6uxcVcV/vxJNU53eoetUEVv1302xTjO9txAz4JlxWtfY8Xs3LO+jsG8HwnCSDOpsPrqfM5zX311PtJMKsFj+rvoHCpC1R8KxbTFFbNzEQhRvN/3Bfm/7w+FBM8xnAvE/vSRJocXZq0SRo0Cm3b3jGlLZ2TBrFWCIIDTne5+Pa/BwoVWHKgvbag34oOiaJxsc2LlnLMfewcDdq8/pm3dPTcPOSn6mPb20JuHsKTEisoGO/tMKJp/ETMSiG8JEoYSQ02exjtfxxNLAPGT2PHGjP2NE872Oi8knO0z6k/bY97/tv2neeeaLIs25h1/cqwZN1+chR+99CV+8MIXWLJpD5aUWJFu6ukT0juVcK4gcowXUgXXd7jxYNlEqBUktu6rj4kZV8zOxZPvVeLmi7Nw/5XjkWoUH68lSJDQPwzFdoufIAgNABoACIIYi7CSOC4QBGECMAvAjwGApml/9znmA7is+2svA/gIwKp4zxMP+IKM1/fW47HrCnH/fw6y/jpr5xeiydFDmEb7FgZDNNQKbvo0EyBHpl6vmjchJgBftfUACjNMA+VD1i8wgz7fdQODW+Srt3MD3AXL5s9rsWymDTISmDM+BYUZCf2+jqEqWiaBi2AI2LqvDk8smgSPPwitUo6XP6vG9OxEwWP60j4iMVTprYlaFbbsrcOymTYQRLhK9Za9dfhefhrv90cZNXhg76GY718xcZrgORjSdUFxJpuKtXVf/ZCk8venj6Qa1VhckskWngDCz33DruMon2UDAIQoGq/vPcVz/6mDeh+RuBDTOvuSDs0sfKOfC0N81LS5sPzVb2DWKtn3RxLAxHTDiHhuFp0aW/Ye4bStV7+sxbLvjMHLt0zH/060IkQBmz+vRYPdiw27juOJRZPY47fuq8eK2bkcO5SRQnxLkDCUiNc+obcxRAgnW/nn63G9eFEGQ8DzH1dx+vzzH1dhevZ00fP1N55gEG/M2N844Wyv80LC2T6j/sSKzPvPMKnxxck2PLFoEmpaXfAFKXau+cMNU+AJhFDV4sTmz2uxuCQTz+w8HhMTMZ6r/b1eCRKGE5FjPADevuf2h0DTYMc7GQHeGOyZncfx5x+VwJooxVgSJAwkhoIcXg1gB4DRBEH8HcB30E3sxokxAFoAvEQQxCQA+wCsBJBK03RD93caAfCyBQRBlAMoBwCr1drryfpDovIFGR1uP4qtCXhnRSnaXT6c7vSifPNeQVKhps2FB948GLPIXLewCNkWHScQqWp29svPk7mPdJMaVS1OHKi3g6LDA29hpgmzx6X2GqSKPY++BPYkScCWrB9wUqov545csDTYvWxgdclYS9zkxGDdD9D/tjpSMNj+tu1uH64uykBVcxfbfq8uykCH2weA/z30d9EZ7+K2v/cuI4EbplnZ4J/x3JIJ5HTIZATv9+Uy4XOkm9T42aU2tLr87PP62aU2pBkHZjHRWzvtax+xmrUYm6znfe55qQYUjDLC7g7AlqTHiRYnsiw6NHS68esrJ6DD4wdF0UNCMo5Ev/fBRl8W0L0RH0yfihx7gfD4m500+M+tt3Zq0shx5+xcPPDGIbZvrZo3Hn/8uBq//N44TqEgIPzeG+0e9u8Guxdb9tZhS/kMeAIhabNQQlw4V+f9SAw1eRqvF39zlxe1bR7OeAQALU6v6HHxktiR6E8tcJIA7rhsLLRKBVy+IHRqObISx8bYEAzGdQrhfGinAP8zeuy6QpAE+hRT9DdWJEkCRo0CCVoFSACpBhX7Pi16FR7ZfgQv3zIdBRkmXDLWAo8/xPv7TIwobUL2jvOlrZ4PiBzjz3S6kZGQjzXbDnPWM3qVHM99dAIN9rCIrijDiNGJOt4YTEYQ502MJbVTCSMFg04O0zT9PkEQXwOYgbCdxEqaplvP4iflAIoB3EnT9BcEQTyDKAsJmqZpgiB4Qy+apjcB2ASEq0GKnUhMIQYghgQSCsSsieHglqaBH774pSip0OQIB6uMspVRCWQkqDlF3dJNatZ/s7cAPPo+7r9yHEI0sGl3NWdAzknWiy7Se1PMDaeSti/n7suCZSRVAe5PWx0pGApVpUYhgzsQimm/aoWw/15/22Y8i1uKorHraFO/Nl0a7F68sofb11/ZU4sp1gTevtjf7wPh77j8sc+rP4tTMQxUO61td6Oh04MsiwZlRRmsynnb/tOYkGaENVGHN+pOs1kYTHrZ4+9WoHzWWCTpVMjq3kBj+q/VrGULhg1Ufx7JRdUGC30lGcQ2AoZbxdZbO211emFQyfDkokksASMngcIMPettF33thRkm9vMwmTwhriwUCRIYnIvzfjTOhpSMZ8Od8eKP7p9iXvzA2ZHYV0xIxZbyGWiwhwUX+emmPokr+hsjAECTw4MQTeDef+1nn+fqq/PR3OXBGJHnNJgx+fnQToGeZzTuzlKcaHXCH6BQ3epCbZurT+8mnjbE9z7XXJMPkgBWzZvArhltyXrsP9XJ+/tTs8xYPjsHpTlJmJadKM05Ijhf2ur5AqZtZ1t0+KSqGX/6YTFCVHidopARcHj87HeLMoz4wUVZqGx08PYDOUngq5o2WHSqc34zXmqnEkYKBp0cJgjiOgC7aJp+u/vvBIIgrqVp+o04f7IeQD1N0190//0vhMnhJoIg0mmabiAIIh1A89leu5BCLP+uUnx7yo5VWw/EEGBCgRhF0aLF6ZhAmAk0ItVVagWJhcUZ7L9nWTRYUmLFk+9V9imNNfo+0hO0+GV3UAKEix14AiFUNoaVmEIDbF8UcwOhpI2XoO3t3L0tWM61dPGRRGQzONnqwrodFSx5CQDrdlRgXKphwKrJOn2hmDS7Z3YeR7G1bzUo+0KKxrO4rWt34XiTs1+bLqlGNTrcfo5ySWxhkWLg/36yXngh0tzlE3xeYgvLoUZtmwvvHGzA7bNysGZ7j5LgkfkFyErUoqbNhWd2HuO0rS1761BWlIG1249g09KpqGjsYt9ZlkUTowQV29zra98ZbpJzODAQJMNgqtgGAiRI1LZ7sP79Y+z13fPdPNz6nbHo8gVx99w8tngKszHh9Afx9p2laHFKtkISJDAYaqGALxCKiYVXzM6FLyjsxQ/EPyZRFI33Kpr6HSvWtbtQ3eLixAj3fDcPOckuUWEGQZAc+wsgbH/xxMJJgscwGMzstvMFJElARgInmp0xWVm9iWasZi0evbaAE2c8em0BrGat4DF87/O5j6rw2HVFIElum2X8pqPbdkWDA3/+pBqLijNG3DpAgoS+gCQJWM067DjcGNPv7rjMhgaHH1OtCViz/TBumGbFg2UTWds5ph98U9eBIBVeC6yaN2HErtclSDiXMCS2EjRN/4f5g6bpToIgVgN4I54fo2m6kSCIUwRBjKNp+iiAOQCOdP/vRwAe7/7/N8/2wvkUYmatEtWtbpYYTjepsaA4E5WNDmQkaFi/3+hArKbNxRanEyMVegtWsy06rJ1fyFpT9MU7N1JtfPPFWZCTRA9RbFJj6YysGIKZb4AdCsXcYBK0vS1Yoslvs1bJ7lYyyvCRMunE85ziIZODQQqHG+zd6hgN8tONkMuF61iesbuxpMQaE8g22N0DRg53eQO87dDhDQge01/FTjyL2yaHMAkrtLjo7+JURgL3XzmeYxFh0SkFbSgAwOUP8j4vtz8ofNAAoi9tiKJoyGUELhufwhLDzHU+9OYhlGSZ0eby8bYtkgx/z+4J4sn3KtkF17hUA558rzJmM2viylIcaeiKu++km9QjmuSMxkBtIp0tyTDSPdpdgRBLDDPzutMXRCBE49G3j2DZd8Zg+eU58AYp1vNz/uQMjE3SY3q2BTVtLnxxsk1aoEsYVPR3Th5uDFSGihh0KjmvJ+9FYyaLHhfvmBSvtVBzl48dY5jj1r9/DFNGC2f+AIDDG+Cd+8RiHgn9QzzxGwDUdbjx2pe14RoYviC0qnANjGKrGbZkPW9/5XufD5ZNhNPrx+GGLow269h2JOQ3PX9yBjbeOAUH6u34FY9QSZp/JIwEiM1XFEWjRUC88txNxXj0nUoY5uZiSUnYSs+sVaJ8lg1WsxZJBhVWv3UIZUUZePHTaiybaTvv7d0kSBgqDAU5zBe1nu157wTwd4IglACqAdzSfZ7XCYJYBqAWwPXx/jizmCYJIobMXVySiW/qOtgFZCSxuml3tSix+vrecMEaRu0mI4Fiq5mzwxwZrLa7fFDIwubsNW0uNmhVyAjOApYgwpXSAyFKsNBTlkWDWy8ZA3cghNo2F3tfC4oz2esHxIPcoVDMRRYWiSbe89ONZ50iLkZwRJLf/SHNhwP9XZzEQyYHgxTe2H86RhFx7aQMwcWoSiaLaU8bdh3HK7eIF3jpD0waBa/1QIJGIXhMPKpeBn1d3MZDwvZ3cdri9MHTPdYw93H33Dy0On2C95GVyG8/MxRFHPja0Nr5BchJ0cGkUbKE6sHTnfAGKWRbdIIbUBoFf9t6YtEkqBUk1AqSdwHNFK9gjmly+ASLFxEEYsaXyL5j1iqxuCQT41IN2FJ+MQKhEBJHcDrbSMuGGMkqNnd3/+Ub+x8smwiXN4DsJB1+83YFOtx+rLkmHx1uP5q7vDh0WlqgSxh8xDMnDwfOZtyJZzOryxfA3XPzUN3qAkUDchK4e24enP6+k6f9IbGFirw2OcSFEnYP/8Z2p0f8OhM0Ct65b/OtvcdVIzHDbKSBomg4BEQHYvEbRdHocPlxXfFo/CrCImLF7Fy0u3ywmrW8/XVskg53Rr3PtduP4LmbiqFVyjiCGxkJ3HRRFta/f4yNP+6eOw6jzRoEKQrLX/0mJpbJKJ8Btz8kvW8Jwwqx+YokCew43IjqFv7aSd+e6oQ3QCGjO9OZGW8pGjjV4UaGWY0bp2fhr5/VwBugYE3U4LZSG9pdvhEZX0qQcC5hKMjhvQRBrAfwbPffdyBcRC5u0DT9LYASnn+acza/CyCGCFg5J5eT7pCXYkBlU1gBHE2s8ilNgTAx5QtS6HD7seNQA8pnjeWkRkQHzSRJINuiQ2Ujv7ot0loicgGbm6JHMU8BBUZtvLe2HZt2V8OsVbIpsgSBPquBhyItuLa7sEj0Av3Nb08LpoiLBT5MYNzm8kHZTbQLBUyR5Hd/SPPhgNDiREjFHY/S5UiDnX3ezDEPvHEIeSl6FI3mt3AQIkhdA6hSTTOpcMdlOXjorQjrgWvykWpSCR7TX1VIPIvbeEnY/hBmSpJkU9uZ+3j6g2PY8pMZgsdkJfKnPWYlCqc9DhQO87ShB988hCcWTcIPXvgC66+fDKWcwPJXv0Feih53zc3jfYYauQwUTXPSMLfuq0eD3Yu6NhdWX50PGQHeBXR0VW+hNlrR6MC9/9wf876ZvmPWKnk3jIqtI9fv70IsnhcvzFol77zOLNx/t2gSfvffSiyfnQOXNwClnMQ7BxrgjvDzZr4vPWMJgwG+8fSBNw4hN0WPSQJz8nAg3nEnXlLZqFLgaKMzxq6htzkuXg9gg1qOmy/OikmFNqjFl1RGtYJ3fjOqhTe2ASAQpHnjvUBInNEeaZuDIxHMMzoq4GkqFL8xx1U2OmLG/w27jmNL+QzB/vrij0rY92lQy5CRoMXJVhfc/hBsSXqO4KbF6YNKRuKeubnQqRWcteODZRNh1irZzW/mHDsrm7FhZ5X0viUMK8TmK4NagXU7KvDreRN4+12o+8+TrS7kpehx+2U5qGx0QKuUgaaB5i4/clP0SNYr0eH2o67dgxc/rUZein7IilNLkHC+YijI4TsBPAhgS/ff7yNMEI9IRAa1TPGn8lk2TBmdgCyLDjQN/K7b69cb7Kkiy6c22njjFPiDNCobHXjz29PsMczkDggHzXzB9bodFchIUMMforDmmgLc/rd9nH9ftfUAa2sRCUZtTNFg7+uvn9Vg2UwbxqUa+qwGjjcFL1q5IFYkSqeU8y7Qy4oy8MAbhzgB8tFGByamGwQVk0zwtm5HRQyRzhcwMeT3uh0VsJo1fSbNhwPpJjVu+U52jD9mmpFfxR2PJUijw8d7TKPDhyKB67LoVLztKVGn7PvN9YIOZ4Alhplreuitw9jykxmwJvIf019VbzyL2zFJOjbNL3KhOSapd//Cvip72t1+3vtod/t5vw+EC739oZskZdIS/7DrOKaMNg+Y1YcQGuz87c7T/T7uef1blM+ywRugUJoXtpTg89dbseUbLL88F9sPnEZtm4f9fMveOlgtOjz1XiV+feUE3nNFV/UWIvGPNXXxbvTplHKYtUrcdFF4DOnPGDTcEOr3vSncLkQYVDKsvjofDXaPYJt9qCwfW76qQW5qAtZ/cBBPLJrEaTeR3x8pc4WE8wdC42mj3YtJo4fpongQrwVZZOYYcwyT1SE2V7n8Ibx3uCEmtX9iulH0OuPNKPIG+OseTMsWJ+hTjaoYwcnKOblINQpvbAPAKLOal4welSCetSdtDvYOps2ZtUreGi5C8RvzbG8rtQnEliFBpbjLF8TNF2fhta/qsKTEytaAUStIrI3yK1bKSPx2R9gu670jjTFtfHFJJjbs5NagYIg16X1LGE6IzVdufwhlRRl4fEdFTL/7zXWF2LDzGABAKSewZLoV63ZUYPHU0UjSq3Cq3Y3H361Eh9uPB8smIhik8Hz3GP6rrQeQP8o06GsbCRLOZww6OUzTtAvhgnHnBKKD2ga7Fxt2VuG18otgSw7vSK2aNwHrdlTg3ivGiypND9TbsWl3NW4rtaG2zYPNn9firjm5okEzQxRFLzjTTWosKbFiyabP4Q1QuPeKvD79DkM4pRjUkBFgr5cpeJdl0WDdwqKY4np8auB40tMiCdqyogyY1DJYDGr8338O8hK1TPDsCYQ490cQ4FXuZVl0bGXfaDDB27KZtl5VwMy9pZtUuGtOHmoirDcY8JHmw5WyFwzRvN51s8el8H6fUZtHWzGIWYIYNfwVwI0a4WHDHQjg4avz8fC2HlXvw1fnwxsQT83rzzNsEFBNNzq8ECrP0l9Vb7yLW3+Q5iw0118/WfC7QP+VPVqlnPc9akWqste2u1Db5uEUsQPCC+PBDqDSTRre556sV2H57Bxs3VcPqlv8RBBgx8knFk1CVXMXQhRYW4gH3zzEqoAZdc6zNxbjmQ+OwR+kkWpQYcWcHPb3tu6rR4fbjznjU3DJWAu7mQUgJgPisesK8bv/Hu2+5tiNvnu+m4c0k7rfY9BwQ8gKKBCiJXVFFNrdATz/cRXuv2oibzuqbffgobcO49FrC5CgUYQLuXZvLl1oBQolDA+ExtM0U+9tbShjlXgtyJjMsUh4A1SvcxUNCjddlI2q5i52Y/ami7IBUILHAPH7zHa4+Um/Dre4PURmghaZZg3KZ9lA0QBJAJlmDTITxBXOwRDNe53fnZDay/0Nfp2Qcx1Mm2uwe9kaLgQBXGxLxMW2JME+Evls+WKyVKMaWiV/DJ2gVeKZnd+ya53bSm0AwnPNg28cwlSrGdkWHWraXGiwe3FbqQ1WswaZCVaOfcXqsnykGpXsORg18cZdPbGe9L4lDAcoikaynl8slGZSw6BWQEb2xPyR4hWjWo5l3xmDVpcfqQY1mhxe3HrJGPx2RyVHNLL581qs3X4Eyy/P4VjHDcXaRoKE8xmDRg4TBPF7mqbvIghiG4CY3Ceapq8ZrHOfDcSCWia4TjYoseGGKfCHKJZY5bNnkJM9v6NWkGiwe3Gq0yP6+wyRGkk8p5vUuO+qCWxQAADeIMU/6BrVqGl14uu6TtwfQcBuvHEKCjNNMaqFVfMm4IoJqSjMMImqgeNNT6tpc3GUu8tm2rD+g4OCRK01UYfcVD2CIZrX7zma5L3/PwcxeXSCqIdwb9YZkfe2bKYNL35aLagiiCTNhzNl71SHm/eeTnW4kZNqiPm+1ayNseXoraKyYAXwgHAFcBlB4o8RVZhpGvjjx1V4chE/bRvPM8w0a3hVNBlmjeB1jUnit0QRUoXEQ6bHo9Lp7zFpJhXumpuHk93eijICuGtuHtJELDV0cRDKA4VxyXo8ck0BHnqrp92tvjofv//gGI41O7FyTi5kEa+ZGSfPdLoRosKE8cKpmayFBBHxXW+AQkWDA1fkp8GoluObU50xCrDcVD0KMxIAgFMw7IoJqXgnIgOCJICObvU130bf+veP4clFkwTHoEmZCSMyGM226GI2/1bMzsWDbx7ESz+eLi0YI+D0BeEP0qhpdcW0I61CxipTHnjjEF6+ZTp+dqkNCVolfv/B8Zh5dSQXKJRw7mJCqgGPzC/AQ2/2jKePzC/AhFRxhexQxyrxWpDpBMi03uYqnVKBQ46umH6bZREnXeMt1hqvPURdhxtPvneUnYtDFPDke0eRPyo24y/6uP7EewyGok7IuQyKoqFXytnNwK376vHsh2E7htIcYWIY6Hm2u4824/ZLc7AmQhDxyPwCZJo0gAm8/dXtD8KsVcKoUXDmDYbwanJ4Ud/hwd7adlB0OF57YuEk/OilLzmxx5rth/HyLdNxz9xcJGiVSDGqsXHXMY7NhPS+JQw1IrmM6DUkM1/J5SSKrWY25mfEK1kWDWblWtCplGPTu5Wc8ZyxUGHEIaxYJNi/+UKCBAniGMwetLn7/58cxHMMOPiC2o03TgEB4I1vT3MI1/XXT8b3C9JRmGFCi9OHP3/S4zuVblIjN1UPtYLE1n09heh0ShkeLJvI8Y3aeOMU0DTwVU07S6Q+2W1dsWVvOO2oqpmrJGZ+M9rG4khDF68H1vJXv8GOlaXISdaj2GqG2x+ENVGHMUm6Pnmexpue1uTwoqwog73O3ohakiRwWW4KPqhs4iy4t+0/jXu+O65fKogUQzh4A8SVXZGpjMz1RasISnOSMC2b6y06nCl7OhX/IkonMCnWdbh5vZ+Yisp80Cj5K4ALEb0A0OkJ8KpU7QIFV+J5hiqZjFdFM3e8sIqmv5Yo8ZDpcVl3CKRdCaX9UxTQ0uWL8VakRARSaSZVzOJl9dX5ooTyQOFoSxee/YhrafH8x1VYPHU0SvMoeAIhXJSdiCyLBlv31eOe7+bh71/UwqBW4PcfcBdNW/bWcYoGqRUkPAEKWYkatLn8vG1i+/KZACBIjERmDjDjvtAYVd/pwWizlvffKhod7Fg6kkCSBEYlqDnPn1Fi91dNdL4XNjJqFFhckhnj6f3MzuMxypRWpw+tLj/8oXAtAZ1ShldunY4QRZ+Xz0bCyEC93YPXvwpnVnj8QWiUcrzyWTVKsoTnceDsYpV4+n28FmTx2i44fUHe8X/T0qmix2WZtbxx1GiReR4AUgz815liEL/OJoeXNz7qbSyOlzQfijoh5yr4NkyYOOOGadZe2xzzbGvbXGxsBXTbnL15CGMsWijlJG9//cUV47C4JDPGYnDDruMon2WDL0ixtoHMdYnFl7lpRoyxaJGZoIXbH8KhM9L7ljB8iFxTM+toGQlMzTLjDzuPsfPVmCQtVl+dz/afLIsGt1+ag/+daIvhMJ7Zya0fwqzX1QoSzLTS1/lCggQJ4hg0cpim6X0EQcgAlNM0fdNgnWegER3UphnVONLQhf98ezpmsGI8gN3+ENJNak4QtrgkE4+/27NrFlmIzqxVonyWDXmpBuSnG1HR2IXv/+ET3FZq4xCpmz+vZRXDt5XaOMFhg92LLXvrsKV8BjyBEFIMatA02N/hCyIaHV7MsCX1yR8zekEQb3paqlENGYmYoDby7yyLBhqFDHtOtCLVGL6Pu7aEPcAYUoMkAFtSrDVAlkUDjbznWGYBQlE0TraFlYmvfVUnqgKOLIIX6cHM7GaqFSQWTMmIWdgMZ8qeLxjC/101AS1OH6sgTdKr4A/xq3rj8R5NMajYKsmRRGSyyAJISFFjEFDUxHNdNQKppzXtLuSmCato+lP4ra6D69MLhH16xch0ZjMi+t6T9cKqDZWc5D1GIeOvPN/i9PHaiUwZnYAxAtcVCNIxi5c12w6zxOlgosHOvxhOM6k5xPvqq/Ph9gWRnaTF/VdOxMot3ArcW/bW4YlFRWjr8mPdgsIwIaeSw+MPwqBRQKOUCyqrXP4gKhsduK3UxiqQo4mRyHE/eqMPCL+TrEQtzghkfhxr6sLEdOOIVOJadCq8+Gns/fRHTXQhFDZKN6qRk6znbUfRyhSLXoVMfwAkQaJ8Vjgl2OEN9FrISoKEs0GTw4u9tXbsrf2G83lvMUe83uNn0+/7M98yYDLHIm0XclP1vRZ1jbYhY+4v+jO+a+QjeWW93BtBABadAk8umgSXP0DJzwAA3ZdJREFUPwidUg63P8DJbOFDvEreFIMK9185Hq0uPxvvWXTKXslokiRwxYRUbCmfgQa7F+kmDfLTjdIYBf4Nkw27juPJRZOgVvZeSBgI+6FmW3S8ba/V6cepdldMf003qdHuCiA3Rc9bYDcnWY/Vb3Hrq/iCIaQa+VP09WoFEjRydl0Xz6aMBAkDBYqiUdHg4HAVTPy/fHYO9tba2flqtFmHZIMT9185HplmLWQyAj/dvE+Qw7Amalg7ug63HyQBPHptAdqdPiyfndPn+UKCBAniGFTtPU3TIYIgsgiCUNI0LVwxaYQhMqitbnHyFh2I9gBmlLtv31mKFmfYbH3Dzip212x8moEtOsD4GKsVJLaUz+AEKJFEaoPdy3oP8ymFHyybCL1KAbc/TAg2d/UsANQKkhNcyAgIFiuLBt+C4IWlJbzErF4lxxfVbXD5g8iKUCIzyLboMC0rkT02+j6yLBrcOTuX8xyfXDSJQ84yuDQ3mRPIM7uMS174PGbhUtPmwvJXv2GfAUkCTy6aBJ1KhiyLLqYIXpZFw1Fsi9lJMM+Iz/piqFK4Rpu1ONPp5ShI11yTj0wBxYuQ95lWKRM8hzVRB1uyjrNQsyXrRCfe/ip/4rkutULGe4xaIXwM0D8FVJvLh6UzsvHke0fZ+7j3inFoc/kEF7skAd57F4vL3YEAVpflY832CFVvWT68AX6ltVCBk04BZTYQf0rqQEDIc6yuveeaGLJ6863TkWxQobqFS/6nm9S49ZIx+Lq2k/NsH7kmH3/+tA61bR6snJPDex4QBGdsYdI2+ZSzzLgvZMXw+I4K3DTdGpP5wfzmJWMtI5IczrbwF0rsj5qIsQeKXMyu21GB8WmGEXnP/QVF0ahqcUIpsFkTqUxZMTsXq7bux52z82C1qNHS5cMfP65Gh9uPd6TCPxIGEfGSi/HMs8DQZ0eRJIHZ41JhS9L3i9wyxVEfAQgr3F7Zw/W7fGVPLcanGQQ3W4HwJq3DG8JDbx3hxAetTp+o+CJeJS9JAiqFLCbeI/n3kFlQFI33KprO6029eCG0YaJTyXBpXkqvz6emzYXnP6rCvd8bz9v2KhodrD1ZbZuH/bfFJZl44r+VuH3WWHbTNlK1nKRXwh+kY2ob2JJ1+M11hZx6LStm5+Lhtw5hzTUFbA2BeDZlJEgYKNS0uXC8uYu3T9A0d75iMoXfOdSAn7/6NYdn4V83ePDip9XhLA2jCm1dPoxO1KClywerWYNxaQYUZiRc8GObBAlni6EwZqkG8D+CIN4C4GI+pGl6/RCc+6wRGUBEEq6RZG+6SY0FxZk4UG9Hsl6N6dkWtqAZQ3Aun50jqNxgfkOnlCEvQrnKgPkdhmg2qWWYPsaC6lYXvv+HT2II3K376nHfvPFwR1RUVitIjEsz9qlwErMgiCSXKxrseGJhEX619QDMWiVuuSQLaQkafHK8NcZrcV5+Gvs7TQ4vrBFF7xjF86alJVDICGiVMpa8YZ6J0MRi9wY4gXxeqoHrwxyxcGGeazTBzBQWBHrIQjlJ4NfzJuBunjSYOeNTeCebmjYXHnjzYAyRvG5h0ZCkcNndAax+i6sGXf3WYWz5yQze7/tD/P7BgRDF+30gvoVaf5U/8VyXWavgJWHNWmG/v/4qoGQEwRLDQPj5PvneUbx620WC5zjZ1v+FpkahwNavj7Nph1pluAL1r6+cyPv9eLwO9QIWJHrV4A//JIkY8vuRa/Lx9AfHOd/zBig4fUFY9KoYy5QFxZloc/tjMjceeuswm2b2+t76mDbxYNlEPPwW10plw66wRcDGD6t4i0vWtbvQ5PBBp5LxWjEkaJUwdWd+UHTPv3W4/ZzfG2kWDEKFEimKxslWF2rbXdAp5Ug1qti+Gnn9do+f9Y2P7KftIpsl5xJq2lw4UG/Hm9+ejhmPVl+dj0SdEivm5HAKJD7wxkG8cHMJ8lL1rC92PFkjI62tSBi5iJdcjGeeBYYnOyoecktOhrOaorOcelMA69QydLj9nBgxbM8lTpqrZCRvfPB6OX/8xYAkCczOTcbmW6ej0eFDmlGFwnRTr/290e7jjfdevmU6sizCz+lkK/+m3rhUw4j0yB9KCG20ZPVx/HX6AlhcYsWqrQd4+xYTF7ywtAQPvHkQ/iCNxSWZyE3Ro6woA2t4LCV+v2QydEo5b22DVVsP4oWbp3JixRd2n0Btmwdf13XArA0LhaQ5RMJwgIljjjV14fW9/GK2TbtPxMxXte1u/KpbiAGA5TCE+pQ30GP19eR7x3D/VeORbdHB4QlwMrwkSJAQP4aCHD7R/T8SwODK1AYIkYs1RnGx+2gzfntdIRodXjyz8zh+flkOS+pG7vBu2l2N9ddPxhUTUjlBvIzgt1NQyWWsavWZnceRl6LnKNM+P9HC7hY32L3YfuA07pydi11Hm3k8eY7it9cV4r7/HESXL4iNH1bFpfhocnhh1ipjdq6fWjwJ764oxTenOlHT5kJVszPmGu55/VtMXFmKIw1dMb7NjKo6kmTcc6I1ZvHx+t56PHZdYYy/c1aijhPICxHuzV3emMAv3aTG4pJMuP0hVLc4kWnS4N0jjVjVTXb/8nuxfsYUDcHJhvGOi66ympGgHpKgrEFg0dbg8ILPEdiiU2FXZWM4sPQFoVWFSch5BWmi5xlsFYJFp+L1NRa7rhyLHtWtLg4BnWHWIEdkkdRfBVSr08f7fFudwgkQOqWcd6Ep5gtI0TSuLsrgVFm/uigDdGwNTwBhZXakRxdDXol5bGmVMl4yXdPLAnggYNIosfXrOjyxaBLkJFDb5ka6Sc0Wf2OgVpCQkQSu2vAJzFol53plZHdf5HkfzII3Wa+ELVmP5384FV3eIFq6vDCo5RzFDnNMmkmNjTdOiSkuuetoE850eNDq8iM3xcBrxZBkUGHNtsMxROmj1xaAJMK/Awh7HA/Hgk2o7fON0w+WTUSj3QtfKISfbv6a/fy31xViy966mMXsll7IkHMFTQ4vKJq/cnaKQYlWpx8bdnKtUbwBCg2dHiQbVNi2/zRuvjirz9k5DC4Euw4JAwulnODMfUp57+0knnkWGJ6CZvFslrS7/HjpfzWc+3vpfzXItuSLHqcgSd65US5g68Sg1envd3wAAH5/CG8daogpUHZt0SgoRebjeAvnnbG7ceP0LNZHXa0gcffcPDTY3Rc8OXw2fswURcPtD7GE/Y5DDfjT0qlotHtZ0pbxqP+qth2rvhcW6zzwxiHcVmqLsdoDwn+HKBoBisaYJH6rinZXgF2zLC7JxC0zx0CjkKHZ4cXOymY2I3XdwiKMSlDDolNJRLGEQUdkHHNbqQ0dbj8njiIJYHyqAS/9eHpMe6xt68kUZIRtbW4/SBLYtHQqmhw+1LS52U15oMfqS60gkWnW4lS7C4+9e1SKnyRIGCAMOjlM0/QaACAIwhj+k+4a7HOeDSIHOUYhu3Z+AU51uFli2KxVIjclXGxuQXEmJ+gGetJto72Lx6UZOYHI2vmFePDNg1g1bwL7+YHTDrTsqkL5LBumZ5vR5gpg/ftHWcXwpNFm/OilL2NsLooyjLiueDR+v/MYls20IdmgilvxkWpUc3auGWX00aYupBrVuP8/B3FbqY39Tebfmftv6fLFkBHLX/0G76woxQxbUsy5ohcfHW4/iq0JeCfi2YUooN3t46R78xHuzMKFCfzW7ajADdOsMGoULOGeZdHg4avz2d9psHvRYPewyvClM7KwZW8dyooy8L+qVvgDFC62WSCXkzHXHalMVitILCzO6EszO2sIpesn6flJQqtZixumZ7FKa4bQEiuwFg8YO4/o6xJKt8626PDI/Hx0eUJw+YLQqeWYPiZfNECvanPC6w8iL8XAHuP2BVDV5kRBRgLvMcyGR2Q7FVP6aQTScMUIVZ2Kn4TVqYSP0SplcAdCMVXWNQIWGQ5PAM9/XBVT4C0/fYrgORyeIK+iefLoBMFjBgrZFh1unTkW97z+LdZcnY91O47i11eO431Old0+ZQ12L17ZU4vyWTZMGZ2ARJ0KuyqbBNPUijKM+MH0LKx87Rv299Zckw+PL8B7TEuXD7nJeuyra4dSRsLtD0GrlKOx0wOXP/wuoglqZsGllBFYt7AIvmAIL/14GlqcPlQ1O/HUe8eglBNYO78QwRCFo40OTmXle17/Fkm3TofTx2+/M5gQ9huNHafXbj+C8lk2jDZrsbpsAjo9Qbj8IdS0uXDDNCvW7TjK+Q3G0uhch1Yph14p4x3TC5dMxthkPW9bSjWp0ekKYNW88ahvd6O6xQWKRp8X5MNZ1LQ3SIrmkYeaNhfWbj+CsqIMEER402zt9iOwJYlv4GZbdJw4s69E2EBY0vQH8W6WJBtUvBuzSXql6PkaHV7euTHbIh4XCdnPKOXipPKBM3Y8+yG3lsGzHx6HLUmHkuxEwePiLZynlsvw6pe1nPO9+mWtaFHhCwXxFk0EgLp2Fzu3p5vUmFeQjp9u5haQa3H60eH2I0QBlU1dbIy3dV89HiqbyPs+ZSSBX/zzW/z6ygm8/36ixQmzVonbZ9nQ5vbjRIsLMgLITurpj2GV8QEsm2nDi59WDyhZJs0J5zfifb+RcUyk6pep2bP++smYYjXH/BZF0dCqZFgxJwcUDew+2owARePNb0+jrCgDe2s7MC07EQ++eSimL5AEsGJ2LtbtqMAj8wuwfHYOgPPL7kyChOHCoJPDBEGUAHgJ3aphgiDsAG6laXrfYJ87HkRaKiydkYX1H4TJ4Lvm5uJUhwfeAIUFxZl4fEe42JychGi6baTq0pqo4wQijPq0qtkZQ7JSdNhbddXWcMDx76/rsXRGFv7XrbTVKHqC03STGrdflsMOzv/+uh73X8UfXPQl9TnbokNeigHeAIWiDCOWTLfGVNUFAL2yR/Ucef95qfxFffiIuMjde2Y3PC/FgBAFjEkKewNHLhayLBrWkiLdFEu4MwsephBHIEThRIuTU8l68dTR+OZUJ+ca//Z5uGidNxjClr11Mfe0bmERri4axU5uw10FmgLFS7DR4Fc617a72QJgQPh9PPDGIUwZbRZVkASDFA432DnFTOQiC6D+krAURaOly88pTvbotT3+aXxw+oJocwU4fn8r5+TC6RNW0aQZ1bj54qxYL2QBBZRKTvCmqYqptAIhCmlGNUfVlWZUIyiSuuv0hnirrE+xmnm/f1qgwNsZuxdFo/nPoVMJKZoHXzkcmUYbpMIe3S9/VovbZ9lQPssGOUnClqSDXEbgdIcH6SY1qw4IUYAvSMGkkaMw0xTT3h+9tgB/2HUcv7hifIy9zOq3DmP94klskMqMLdZELUxqBda+fRizx6dx+vhvriuE2x9iC9cxBHXBKBPUChkefPMgats87BgvJ4H1H/RsoC0psaJ8817OPMCoHbwBCp9WtbLKnqFUNwip/4TUaBQNPPjmIZTPskGvkrPFPx4sm8h5P2oFidR+KmVHKvyhECaMMuCRawrw0FsRhRLL8vHnT07gru+Ow6PXFnDGqTXX5OOhNw+xbeKe7+bh/944hA63v8/vdziLmopBUjSPTLS5fLxK0N7sXUiSwNxxKfjbsovQ6PAi3ahG4aje7QwAYUuawUDcmyU0v99/b3eXrFdx5nSiW4kttMnOQEZCwMZC/HztLgF7Hre44lgm4y+cJ5eJ36HbH+Q9X2+K4wsNNH+iliCaHD7UtLqQZdHwxh8bdh1H+Swb1HIZNn9ei4VTM9l/b7B78cePqmIywB69tgCtXV7cOD2LU8y8R0xUgPXvH8PNF2fxCgpyu+N4Zh1pNWtwW6ltwMgyaU44v3E27zcyjmEsMFd9bxxyUg1w+4NI1quwr66do2QXOt+6HRWcMSvLosGaa/JZlT6TLdnp9uOVPeH4urXLBwDYtv80lpRYzxu7s/MFlRVHcFnZYt5/G5VsxqsvbRriK5LQG4bCVuIvAH5O0/QnAEAQxEyEyeKiITh3v8EMcguKe5SzDXYvTnV4WKUqQfSknz6+sJDdMQbE0235UvTVChL+EBVDsmZZNMhN6SFZmeu5rdQWLgSnlLPB4oLiTFQ2OliSYumMLLz8WTV+c10BatvcvIqP3iaCCenGcMG3CNIZYEjrsCfQ2mvzOV69zP2faHb2ORWR2b2fuLIUh884cLSpC5VNXTjT6cbEDBMUJMk5f22bB+Wb9+KdFaXITtLHEO6RO511HW6s2nqAo7JON6kx2qzB8RYX5xoZL+QHvj8RIQo8fl8HUJhhYt/d2agOBgIdLn416FiBCTEydYeBN0Chrt0lSA4HgxTe2H86hri9dlKGIEGcbuInYYXSrQ832HlJ69wUPSaN5idIgyGal1D9880lvN8HgC5vAK99xVX4v/ZVHb4z1sL7/RSDGskGL4foTTaoBMlkACAJAu8eOo2bZoxBpyuABJ0Cf//8JO64PE/wGIeXv8CcQ6DAnJB/sE7EPzhev8mBgN8fwntHm1DV7IRWIcempVNx+IwDdm8QE9ON8Ico3BuhZr97bh7ePnAG8wrSOaRufroRl9gsKLaa4fYHYU3UIStRi2KrGUciKiMz8AYodPmC2Px5Le6Zm4sErRIPRQSXjP9ZZBv6v/8cxLKZNmw/cBoPlk1EVbMT/hAFk1aOH/3lq5gx/rkbi1kiOXK+iPwO44msVpBgHvdQq0OFNrKyEnWCamyGJF7//jH2HhhVcSTBPVSbYYMNi06FFocPz350nKvK312FsqIMdLoDyExQ4883l8DhDSBJr8Iv/7WftS3xBiisf/8Y64PX1/c7HGn7fUG8JJ2kLBtcqGQkSwwD4ffy9AfHevW6DQYpvHXwTL/mcmDole3xbpa0OP39iocYkCRw19w8nGx1sXHyXXPzei30ZlApkGxQxcQHepWw9z8AJGgVvPPEK7dMFz2OyaaJvr8p1gTRAngqhYz3fH+9ZZr4DQ4gRuqYcDZkmMsfxIeVzbhrTh5IgM2k3LqvHkB4vWZL0uN0pxsAYrIcW5x+BIIhTvtxeYPwBUN4unvDObL2yfTsRLgDIXS4/cg0a9l6N0BP/PvcjcUxNofRYqWzwUjOcpHQN4j1xbN5v9FxTLJeCbVSjp+8whVLbNlbh1XzJrBF46PPV9noQFlRBmfMqm3z4LmPqrBp6VS4/SGYNAo0O7xo797RUStIVLe68eKn1ew5vpPDv66TEIsbbynHmZaOmM8HkrQNgETaNffw/tuZt86J8mMXHIaCHA4xxDAA0DT9KUEQI3bbmhnkCILrCbV1Xz1un2XDyjm58AZCbPrp/lP2mGDWrFXCG6Cw50QrOwADiBmUmUX7Xz49gQfL8rH81a/Z3yorykB1Sw/JylzP1n31eLBsIqu0XTbTBqtZg1OdHo7Nxa2XjEGb08/ZXX5q8WT2GsV8KCk6bOGw5poCfF3XwZLOC4ozoVfJWGKl0x3Amc7YYF7IM9hq1qK6xRkzMZEkAZoG6trdbEr3zRdn4baX98bYZzDXyiwWxDxxo4sJegMUfnapDXq1Atv2xxYeuue742BL0uPg6dh3yrdAGc6qwEaNglcNatLwL07Uyv6nQcZD3IYo8JKwV0zk9zZkVJWR8AYoNNq9mCSghPUHKd5j/CLFCFpdPl4FTZvLJ3gf9/37YMzzevvOUsFzUDSNy8dx0wtXl+WDEpGlGDUy3vdiVPMPzalGRcwu+ppr8pFqEF6Uxus3ORA40uhAo93L6dexhQR77Bee/uAYnlg0Cb/6135e3/NoQsOWrEeXNyhgARJWTOemGvCzv3/Nacdrtx9hSU8G3gCFRK0C5bPGchaM2RYde42R3/36VCe27Q8TyU4fvwqX6F4UMiriyH870+lGS5cPLv/gWk0IbWQBiCGNmeuMJImZfuwNUJgyOgGvlV/Ur82wkUoORCLbosPRxi5eVb6MBE61u3GqPUzIdLj9eKhsIvxBbr/2BigkdysO+0JoMecdzgwUIcRD0knKssFHm4vf67bNJa48jWcuB4Ze2Z5qVCPLomFtM4CwGqy3zRK9UGE5EUsnAAiEaHZ+ipyTRpnEz6dSyHjjg23LZ4oe5xKYJ9wB8SVRkp7fNsOiE1c4Ozz853N4hmYJNpLHhJo2/mJ9fVHZZiXqsGhqJms1GLm5rZaT+O2OSk57smgVuHtuHruxs7gkE4+9WxnTfp5ZMoX9jLE3SjepMSZJhyaHFytm58IjkPHj8ocEN6kHojbASM1ykdA39NYXz+b9RtsPTc82o5xHNLdspi2maDznGmnw+nHXtnnQ4Q7bxN3y168i1ux5sOiVePK/xzjnOF/szoYCZ1o6eIlbibS9sDEU5PDHBEH8CcA/ANAAlgD4iCCIYgCgafrrIbiGPoNZrNW1xSpL//LZSTx7YzF8AQqjE3V44I2D8IcozvcY5eSPXvqSHcA23jgF/iDNOygz1geVDQ5OOv7oBA1+v/M4S2ACYAlpxoaCCR6Wz87Btv2ncd+88VArZSgrykCb2x9TLO4X//wWE9JLkW3RoYZHSWrWKvF1XSdL6t57RR4oGhxVs1mrxB2X2bBiTh7q2lzsdUX+VrRncIpBDatZi/cqmnifAQCc6nCzQdaC4kyOMpSP+EkzqnmJ5kikGNSsypl5jllJOjz05iEsKbGyhJlJLUN+RgIIhCemaVmJI1LNFYk0o4o3zVCoMJlOIectZKYXKZYWD3Hb7uYnYTvcPgCxAUa6ScP/fkUWZ1mJWt4FpDVR2H/PqFbyBs1/W3YR7/fFAiUhpXWIAlt8LbLo36+vnCh4XTKhKusC6aJuH43nPuJ6Dj/3URWeWSLsORyv3+RAwOkLsvcW3a8ZxUskSesNUCC6/59vofPAG4eQm6zHpAjbjfx0Y0zK/9r5BbBZtHjupmJAoJhddAqwWkEiN9XAWkP0nPMgq5iN/K5OKcOSEitbhIOvHY9LNeDJRZPwu/cqOeRylkWD2nYPa9czEItmMRJWaCNrXn4a8pbPxJEGB6panGyF9WiSmLkfGUlieralz9c4ksmBSJAkgbwUfl/h/HQTnv3wOC4bn4K75uTiVKcHf9p9IuzLH9UmtN0K/r7OUYz90ZbyGRzrnuF+NvEomiVl2eBDp5Lzzn06kXkcELZ7anLwb44yGGplu9WsxZ2zc2MUzr3VRlDJ+OdRdS8ewPFkIQFiBWt9yE0VrrudKeAdnJEgfn8uX5A33nOJWGkBYVsrvvOJFbAdSIzkMaFNQDDQF5VtVqIWpyw63P43LgH29AfHUD7LFtOenr5+Mto9Aaz63jgkGdRsjAOAYyeoVpAoyTJhb62dPdfikkzUtIbXWm98exoPXMXvV5xpVseImphrGAiybKRmuUjoG3rri/15v9GxptWshS/QYz+0Yk64WHx0PaLcZB1uK7Whxelj1+eR59u2/zQeKsvnvY42pw+dngDn+te/fwzPLJnCKVQnI3He2J1JkDBcGApymKl8sDrq8ykIk8Wzh+Aa+gzGm+2DyiZOMJZl0WDt/EJ0eYNINaoxKTMBxdYEtLt8yE3Rs8XNIpVxDFGslJFY/uo+zmBZ2ehARoIGepUcq7YewF1zcznHrpyTw6n4ySh2124/EkNIb91XjzsuHwsgvHjQKEh4BdSV7S4fKhu7cLTRAbWCZNV8mWYtdEoZfv7q18hL0eO2WWOhV8qwZvthllhilHzNTj82vVMJs1aJn182NiZoXX/9ZFgTdSwhAQDVLU7BiQkAGiOISCbASTepoVP23Dfz+39aWoz99Xasf/8oyooyICOBS2wWJOlVaHH62MnqZJuTvTYmvbzLG2QtQRYUZ8KglsFiUOGLk21sWuFFNjOn8B1D8NM0OGrw4VzAWxN1mJgeJp5c/iB0SjkMahmsifyEH0ECW/fFEpf5VwtX8xYkbkUmXqWMjCnQKJbmw0fsPXptAfLTTYLnkMsJ3HF5Dh56s4fofmR+PhQifsD+QP/Uxio5ybsIV4iYCnoCASwstnKK/q0uy4cnwG8RAYQXfSoZyUkvVMlIuAUWfY0OL0exSBBhT8gmh5f3+8DwWqC4/aGYfh0Jb6BHmQqE2xfz/0Lfr+vwoDAzgb1+uZzENYWjkJGgwal2N9RKOV75rBrXFY+G1x9CXpqBtx2PTzOyY+DikkwUZZqgkBF4ZH4BNAoZXth9AgdOhy0rrOaeDQkZCUxIM6LR7sG6/x6FN0Bh99FmrC7Lx5rtPW1y7fwCpBgUCFDATRdlYf37x9jxNtuiQ4imcdfcXLz8Wdg37WwWzQwJu25HBXuN07ISYwppRoMkCeSkGmA1a/FVXTtsSXpUt/aQxKuvzsc/vqhlrTgqG+ywJmpEU5kj0V9yYDhVxmOS9XhiYRF+FTHuP1Q2Ef89dAa3X5aDykYHTnV6sG3/adx6yRjYUvR4YmEhWpw+vL73FG6YZkVrl5edL440dPVKilMUjY+ON7OKm4oGB1qcXswelzqs80s8imZJWTb4oGkKt1+aE7PJK1RrgEGqQchzX5wkHGple12HG699WRsTpxRbzaJtqMsXRJpBiU1Lp6LdFUCiToFOlw9dvZCnkfMTg76QaVqlHFdMTMJNM8ago/t8f/v8ZK8+/v5QiJfE9ofEz1ff6eG1lbAmajFZoD4BAJi0ct5MowStuP3FQGEkjwlKGSlo8VHd4hSde+o63IIbBFRUopg3QOFwgwPb9p/G7bNy8Mt/7cddc3OxYk4O5CSJ3BQ9Ht9RwXrX/+a6QgA12Ftrh1pBYmyyHo+/W4l7v5eHZd8Zg5OtTjx8dT4ejhgDfj1vPFq6/HB5g1g5Jwev760f8NoAIzXLRULf0Ftf7Ov75dvw37S0BL/4J9d+kq8e0YNlE7F1Xz3+/Ek1nlo8iY23zFolbrkkC3lpRnj8QTz/w6lY/VZPPYe75+bhjW9O4yezxrKF57buC7fxIE2xtTDCmyuJUpscZAhZURw7XoXBz0eVMBQYdHKYpunLB/scAwmKovF5TTvu+ed+tmK9LVkPu9vPKTbELPRsyXoUUzQKM0xod/lwJqKC7e2zbHAHQthb22PNEJkmvWl3NZ5cNAneAIVgiMbGD6vYwfX1vfUsscl4Vm68cQrevrMUHW4uIa2UE7Al67D/lB0vfFKNR+cXYm9tOy8hopCRLNF737zxIAjA5Q/hl//aj9tKbchL0eMH07PYtO6bL85CdYuTo+SLtHqgKBoyAvjdoknw+IMYZdZgRnaYCIxUTfFNTGatEi1dPnS4/Whx+jjXy0wsz+wMq5XLZ9mQm6JHwSgTTnV4sHnPSZTPGou124/ArFVCo5BxFj6blpZg+avfxLxDOUmwCuxnP6zCqnnj0OzwsdVRaQKwe0KYYjWxyuc0oxpHGrrw/T98wtkoUMiIYSOKg0EKzV1+toorQ0YFgxSUPAsUuzuA2ePTOMTlitm5gt62AGDWybF2fkHMOcx64YWFL0jxqjH8Av62JEkg2aDkktwamejzbOnyscQwEA5wHnrzMP62bDqyLPwLDoOG36tXr+ZfzLn8Afzs0hxOAP7w1eJEr1oux/O7D3OI8ed3V4lWBlcrZGwKYuR1CXkCZpo1uHtuDrRKBVy+IHRqOe6em4MMs0bwHMDwWaDoVVzbDL53wLxqpq38e98prL9+MpzeAO9Ch0CYdIy8l3q7h003Y3DoTBeWzbThgTcOxhC3v72uEKNMKvzrpxejsqkLr31Zi3SjBsu3f8Mh9vFlLY41O+EPhTjjzeKSTIxJ0uHO2Tn42+d1KM1LwfO7uYrujR8ex/zJGfjn3nrcckkWXvpxCc7Yffi/CLudlXNycfssG57fXY0GuzfuRTOTIttbIU0+UBSND442o7bNhde+qsMN06y4/6oJ8AVD0KnkWDE3F0oZiZc+PYk9J9uRZFCzm3+9oT/kwEhQGSfqw3ONLUkHOUmiyeHFtcWZOHzGwW4e3nHpWHR6gxw/vceuK4ROSSBIEdixshQhCux8wdwzHyle1+7C8SZnTFp7TrK+zwT8QIMh6M1aBbaUX4xAKITEiEIyQpCUZYMPGSnD8x9XceeYj6s4lmF8cAf4C59OHp0getxQbyzaPX7eDVaHR9w2I0GjQIc7gL21HeF+2gpkJ+mQIGCzxSBRp+Bts4k68ePkMqCsKBP7Is5XVpQJRS8F4pocXt7N4BaHDxglfFy6Uc1rK9Eb6Xem04u/f95NtvuD0Cjl+PPuE8iyaAVjpYHESB4ThDYGPj/Zjuc+qhKde9pcPrb+Q6QiX0YAuqj4m8m+WTx1NNZsPwyzVgkCBGfMjyxe+3//OYiNNxajttWF9AQN6tpc6HD74fIFYdAo0Orywxv04cnFkwCahlImQ4PdgxWvfcOZQxgLpL4o7/nAt1E7nHVWJJwdhPpiZIbTuFQDdqwsRaND+P3yegVH1f2ItL+M/F6kndsv/rkfz944BS/fOg2nOzxocvhYJT5DJHd5AwiGaChlBH4yywYC4U2dEEXh9lk2/OWzk9AqZHiobCIqGh2YajVjRnai1CYHAGJF5I4dr8KsXzwX8/nBdeWDfVkShghDoRweFBAEIQOwF8BpmqbLCIIYA+A1ABYA+wAspWlaPKLkQU2bC3tr21li1KhR4PAZe4xFQ+RCL1Ih+8nxVqgVYe9fxtqBSTlm/ICZwF6vkkEmC5OVjNI3Mg2DIIDNt05HiKajBmouIQ0QaLT3eF8da+pCYjcp+tpXdaySrNhqhssXDoga7F50+YLwhyjOvZXPGssWiGKKYPzf9ydArSChknNJngXFmbzE1n/vKsW3p+zYvOckbr7Ehrp2N7It3OJHRRlGLJluxa+27sevr5yA1/eeYj25tu6rx0NlE9lCdw12L1sEaUv5DFQ22HHrzB5fUL509b217ezfNA32Heal6Dn2CqPNWvzuvcoYUuWpxZMwPs0ImgYcngB7rnSTGktKrHjwzYO4YZoVo81aHG3sQl6KHmO628JQ4MAZOzZ+eJyzSNz44XGMSdKhJDsx5vsqOX9hErFCKC0OP4IhbtGMYCiEFocf1thTAAgXZeuPfUNduwu1rW60uvws+WLRKZGV6BIkR9pdft4U2XaXMHEbCFK4/8rxMecJRvmGMtAo5Pjjx1yi948fixO9Xb4ALzHe5RO+LkdEmhQDb0DYE1CvlCFEE5wibmF7EHHF0nBBJZexm1xb99XHZGM8ck0BfEEKm2+dhkNnHHj3YAPmFaRzCMLIhc7qsnxs3XcKyYYcTkobn00Oo0qubfPg+d1VeGLRJBxr6gJNA5mJGhg1SjTYPXjgjUOsz3Fku12z/TCeXDQJXb4gEjQK3B2RPRGthkjSq/Dvr+tZj8AFxZm4elIGclPCKcaPvXsUK+bkxMwjz+wMVzVfUJyJFz+t7veimVnAVTV34ZH5Bfjp5n2cvlHd4kRdu3BfAsJ9sLLRgQyTBv4gDZoGW/CGacNb9tbh55eFFRv3/+cgJmUmxNir8C0mIxckzHORkeH+RVE0Z7wc7hTkmjYXvjzZjn/urceKOblYs+0gGwcwpPlosza8oRoIcbyy7//PQfzxh1PR0u6C3ROEPxTiHaOiSfEmh4+XtCu2moeFHBYi6IutvS+4JGXZ4MPu9fPOMQ6veKhrF5hn7CKbwwzi3ViMJwsgRIHdxGOucc32w4LxA4MAxe8dnNnLpqlCRvLaNYhlCAFMJlIQeSkGdpPW7QvAF/WMo6FRyPGXz06yGUkUDfzls5N4fEGR6HGq7nk+WjHOZNoIIdWoxrFmJ1b84xv2s6EkZ0fimMC0S5IgeMkyX/daTGzuIQkCv323AvfNG8/ZeGGU2VkWDat6fLBsIkIUBa1SDm8gnF3q8gc5Rewii9d6AxSqm7swJcuMLk8QmYlabPzBFLS7fLxtPC9Vz1mHMXPIC0unosMTRF2bC4cbHCjMMA2IHdRw1VmRcHbg64t9zXCKBLPhH8lVFGaaOH2pwe5lRWWR8AYoGNQy3HF5DggC8AQo6FRATZubbdfpJjVuusgKOUlgfJoRIYrCHz+qwuzxaZx5b+WcXDxUNhEUTbNcASOI+H5BumjGnITeIVZETiKBz3+cs+QwgJUAKgAYu/9eB+BpmqZfIwjieQDLAPyxvz/a5PBCq5Th5ouz4Ome9HsrihZ57Ot7w/623mAIFN1TRG7F7FzISXC8e2++OAuPv1uBFbNz4QuGeNMwhJRfJEkg26JDZWMXqlucSNareoKDYAiv7z2FOy4bixVz8lilWpZFg8cXFLGDuDfYE0wA4SDl11eO59xrg92L37xdgd8tKoJcFi5qdri+E+sWFoZ/I2qS0KtkqG51Y/OekxwFCEMEPfTWIZi1Svzsshy8+OkJrJiTixaHFzdMs+LVL3uq8wqllDfYvUhP0KKysWenMvq76SY1clMMLIEdqXY+cNoBfBFWUtA0BYWciKmOatYqUdfuxi+61eO/uCKP/bfIgn/uQIhD0g2lyq3d7Q8XHXT3kJ23XjIG7W7+RaJLoIiF2y+cdukPUVizvSImeH7px8KVrjvc/AVzOgWuq83ph8sfigl425x+ZCfxn8OglvOmyBoEVMAA0On1wx+iOee594pxsAssqoWIXqcI0dtfX2MA0Cn5Fc1C6anNXX52gcicY822w3jllunIThY8zbDBoldCp5SxGwwyAvjDDVOgUZJocwXw0wilwMo5ubiyMJ2XLHvuxmI4/SH8Z98pTLdZWE/3LIsGd87ODdtJ8DxHxi+3ts2DY01d2LgrvMl00ZhEXPXiJ+y44BEoFBSiaXj9QTgIYR/ktduPoHyWDTdfnMWS29Hk8ZYv69j5IPocTBGOx64r7NeiOXoBt2JODi95PTpRh8wELUiSiCFrKIrG13Wd7Cbm4hL+gjbLZtqw+q3D2LS0BJVNTlQ0OtgCehRF42SrCxUNDhxv7sLre+vR4fZj/fWTMXdcCjYtLcGB+s5wemx3+uym3dUx4+VwpyA3Obyg6LDHI6POHJ9mwJPvVfKO93fPzcNfP6thCeIWhxdpCRqseO1r3HflBNxWOga/67YdYdLHoy154hmXBxNnQ9APp33NhQK9Us7bP4UyTRgk6pQCClllr+eMh+SlKBq7jjaxdimybgKhN7uUdoGCex29FNzz+PmV0ZuWThU9rsnh47VryOmlrQdpineTNkiLk8O+YBB3XDoWWlVP5o81YSx8QXFbiZo2N9471IA/LZ2KDlcAZp0Cf/30JIxqOQoyEgSPG25ydqSNCZFzJpNVGBlHRhaOFZp7KIrGmU4vats86PIFORmf3gDVPU9ORUOnFzqVHL95pwKLSzJBwI8siwZGjYL3nMwmYpZFA4tBhb01HZzv/ea6Qrz21YmYNv7ij0piCuaatUo0dflYu7aNH4oroaMx3Bu1EgYefH2RpvuW4RQJpmho5Ppo2/7TMdl5Y5NjazhkWTQwqhX4/QfcItNyskdAsGzmGDz5Xk/ctHJOLn5wURY28IzvTy2ehKNNXZzPV3XbVMzMSZJiDwkS4sQ5ubVCEEQmgO8D+HP33wTC3sX/6v7KywCujee3U43hAfOZncdB0eFJdlyqgd2hTzepccflOVgxJ4dVP0Uey/gET0g3Qkb0FJHb/HktxqUb2cGUUbsy/rdqhQwPluXHBP6rth5ATZsLFEWjusWJPSdaUd3iZAP2dTsqMDZZjw63H2oFiXSTGnqlHMu+MwYGtZIlhosyjCifNRa//vcBrJidy94Pc41AmAhWdiuZI+91cUkm0k0aPN69U/7Di7PQ5PDhTKcHWRYNls7IwoufVmPjriooZSS+qevAzZfYOAqQ2jYPnv0oTJT9fslknGp34daZY1Hb5sZj71bilT21HH/XUQmaGFVE+P40qG1zgaLB+ffIa146IwtPvleJFbNzOZVPme8cOO3Ab9+pwJlOL062uGKqo0YqkW+6yMoST0DYi5Yp+Be9GLnn9W9R012kb7CRrFPCHQiTqht3VeFPu6vhDoSQLLDYS9SpeJ9nglZ4cegUIMycIj5+Zq2yX+fxBvkXdV6RxZKcJHmPkZPCw5lRpWADDuaYJ987CoOKP31Uq+BfhKsVwvtpfgGf74CApQYAGDVyjgKIWWSa1PznaXH6wkUhL8/B8tnh/5m1SrQ4xQsL8Y0fQwFrog6jItRbTn8IBAmkm7SsLQ7Q8w5Hm7W8z/Db+k6s+Mc3KBydwHn3ZUUZeOCNQ+ymXORzXDE7F//+up79m+4eM9YtLMKGnUexbKaNHdu13SmikVArSBAEgQ5PADndga7QphXVPWeUzxrLSx7fflkO9EoZ7zlIIuxhXGxN6FcwG72AY4jN2CJ+B/FVbTt2HG7EVRs+wQ9e+AJXbfgEOw434qvadjyz8xiWzbRBKSMxZXQCzFF91Rug2PtutHuwuCQTx5q62Hlpx+FGfP8Pn2D5P77Bn3ZXY+mMLJi1SqzbUYG3DzWgfPNePPneMdz9+rdYUmJFuknNO14yKuPo5zNUKrdUoxrb9p/G+DQDlpRY8eKn1Tja1CU43j/9wTEsKM5kr7O+M5waecM0K062ulhimPn++vePIRji9rusRB3vPQt5xw82xAj6voBRmc6wJbFZVRIGDl1egTnZK76ZoFXIsHZ+AWd8XDu/AFqFeMYJ07+jx43e5o9IuxQmPjneFM5iEEOCVsHbH0y9eOR6AvwWAdGfRUOrlLF2DRt3VeHZD6vQ4fZD00smTjAE3k3aXjheWHQqhBAmlVf9+yDu/ed+hEDA0gtJPzpBg4tzkvDTzftw15Zv8dPN+3BxThIyEnq3k5qXn4Z3VpTitfKL8M6K0iEvBjqSxoTIOZPJjCyfZcMLN09F+Swba+0ACM89NW0utnicUG0XhzeI5z6uQkVjFxrsYcGRQhaO7Zj6Kcx3N+w6jsUlmWx88lBZPmrb3DHzzf/95yDKijJizvXFyXbcfHEW0iOKON98cRZLDDPfu+f1b3GytW/rk7OdBySMTET3xeau/r/nbIsOa+cXcuLMyOy85bNzsGymDS9+egIPlk3kzDn3XTkBj0S1/wfeOITc1HB8fdNF1ph1WpgncfO2fZcviOjllTcQzhweqrW4BAnnIwadHCYIQksQxIMEQbzQ/XcuQRBlZ/mzvwfwK4CtwmEB0EnTNBMh1wPI4DmuV1jNWmSYNfAGKOhVYQUxQzRGEqEbdlZhyaY9nECZ2aVXygk0272w6MI70wxBfLDezg56kSRDg92LdTuO4siZHjUsQ8zeVmpDh9vPG6A3ObwoK8rA4zsqoFHIcM9387C4JGz14PAGUdGtrk03qXH7ZTlYu/0IS0Yvm2mDUSXDuFQDe40A8OKn1Vg7vyDmXncfb2F3yj3+8EL3w8pmDqFdlGFEok4FigY8PIqo2jYP2pw+UDSNzMSw+pdR0zEewBt3VWHDzir4gyGsv34ysiwaloz/64+nwaCSoSDDhG37T7Nk0NZ99bj/yvFYMScH9181AVv2hq00SBIoyTIjy6JhC9sx97m4JEwAv7ynFhPTjZwFSWRBvFSjmkM8jUnSQUZCUAU4VMGTS0Ap4xIopNLl9ePuuXmcifruuXmiSlidAJklVnQlSFGc9sTs/AYp/kWaj2cB5w1QoumZHW4/L0HaIaBOBoAWAUVSq4AiKZ5FeJqJn9wS8wV0+0OsSpEJqp7/uAruAP97ZIpcMpsxf/6kOmZhEI14F/gDAZIkcFluCuaMT0HBKCPmjE/FZbkpgkGpSkHyPsM541PwWvlFmDw6gXNc5DhK0TTWXJ2PP/xgCv7y4xJs2VvHFqlYt7AIl49LwjsrSmFN1GD2+DS8+Gk1HnunAo/ML8DLn1VjdRmXpF9zTT5e6S6GNCkzAeuvn8zZTIu8Prp7PKDBPy5UNjowaXQCnlo8OaZvJOmUUMiJPhOCDNF/rKkLt5Xa2He/dV+9ILne5vTzKoHs7gBLhK5//xh+9vevY9pTJLGuVsoxPs0ApYzEkQYHvqnrwLodFRGqDxu8wRDuv2oCFk8djfu6NyeZc27YdZwlVKPHS2b+jHw+Q6lyy7bosGreBJg0Cs7CR2y8Z0iCh8om4p9767F2+xFMHGVEpsB7ONXh5nw2JkkX0yaeWjwZY5KGhxweboJegjj0agUbEzFzX5ZFA4NanDylaJq1oWLmmY0fHgdFi88BQgrC3hbeQnYpTQ7xTcxOT4B3k683+wujhn9zTyybCAj3bb54pRdXCbQJxBNtvSicnT7ufH9baXi+d/p6L4DHFLFjzrX+/WPQKfue/NnLq74gEE16MpZ1epUc49OMbAwpNvc0Obyo73CHxScC8YDdHbZ/+eRYMx65ZiKS9Gps/LAKX9d18rabMUk6GNQyLJtpQ0WDQ3C+iW6XagWJEBXemF5c0rNRKRQH9LY5w0CaBy4MxPOeSZKAnCR41/d1bS5s3FWFFz+txg8uysZ3xlqw+dbpeOHmqXjxRyUAhNo1gQfLJiLZoOL9dya7Lvo6syxafFHdEvN5iEJYRDZEIhgJEs43DIWtxEsIewBf3P33aQD/BLA9nh/rJpabaZreRxDEZXEcXw6gHACsVivn3yiKxnsVTTjTEfaKiiwSt+NQA+vpGB0oR6ZgKOUEfnnFeNwbUdCNKdYWnWYRnXIRosJpFNGpwSQBXs/jLeUXQ6Mgu3ftwiRRXqohrJgI9pxjQXEmr/+PwxdCqkmNCelGFFvNcPuDyLboUNXiZO8hUpXG7JS7fEGYtUrMK0jnGNHfNmssTjR3Ydv+03h0fiFvGmOaSQ2TRoEGu5dNN+T7XpJehWSDCivn5OH+/xzkFJ3LS9GjfNZY/OfrU3hi0SQoZYDHT+Gxdytx19xcTrrLFROTcMfluXjozUNsYbuxyXoYVHKWlH7uwyo8WDaRLTY1Pq3HkqK+w82qwVfOyYVSTqJwlAmHzth5r3sggyextursfgfRnpZCql6tUg6dSsbxD9apZNCKKGF1Sjmvz51eZEHi8ATxZXUbm/6YqFPgpU9PYqxAihKjFIp+jmJKoWS9Crd8Jzum4neyXrjyukElUJBOxX8vesECdsL3bjVr8ei1Baxig0mZEisG0uL0h1X1EYVmAKDVyb/IpGiad9H9t2XC3tGDnSLYlzE1Oq2VUexGP19bkp43DbYwI6yqrW5x8qaqRVuArL46HzdMs8ITCKEkKxGX2CysB9n+Ux3sdxvsXuSm6HDbzLEI0TRe+vE0dHmDoCgarU4vFk61IkETzhAxaeTIH2XCI9fk46GI6u9MWqhaQcIk0G5CFOANhPC9iakYf2cp6tpdUMpJqOUyWPRKZCZo+5S6zecFGFnMpi2qsCdzfpdAFkCAomOUxowPMuPzzngOry7Lx/b9p3BF/ih2XsyyaPDreRPgCYRg0ijwyPbDrNfio9cWCBKqzHVFjpeDnYIs1k4Z6FQk3P4Qm2auUZDISzEIjvfFoxNQPssGi16FZH14PO7sTvvm+76WZ+xUKQhugSrF8CnrhjsNXYJ4OzVrZfj5ZTlYHTH+rLkmHwlacRLU5Q/BH+GvTxCAP0gLbiYzaHJ4eeOMJoe41Uu8dilGtZxTl4OmgS1767BuYZHocUqSjBmXH7kmH8peWF6DSoEsizZcELfb5oEkAL1ARhGDVINKIP4TjkGA8KYznx1Yl0g2FgCc6nTzPs/6Tjdy0wyCxw1mkc++jKcjDXxFubIsGlbw0FsBToqioVXK4fGH8Ma3p3HDNGtMjLxyTi4StEp8fKwJC4vDWZd3dheLA/jXO05PEI+/exQAsHx2juC6aPLoBPbzyLnfG6CQmaDB8tk54farFrIr69uS/3ybB87FtjoUiPc96wTWU0WZJiyfnQOjSoZUowpnOrwIUBQefTssTNt44xTe4wgAOck69hqi/53Jrots+yvn5MLuCeKHM8Zg7gQPXt5TC6WcwKp5E1Dd4oTLH8Kuo029WhmNJEjtVMJIwVCQw2Npml5CEMQPAICmaXe3DUS8+A6AawiCuAqAGmHP4WcAJBAEIe9WD2ciTELHgKbpTQA2AUBJSQlnW4khUcxaJesbzCii5hWkY19th6Ba1JasR02bC8tf/Yb1sWQUwQze+PnFWLewCOvfP4oUvRJr5xdg44fH2YJxF9ssyEs14miTg7NgF9pFpmkKRd1G8EyK1EMR6lhGXSsngdHd6auRxLNZq4RRJcP4dCOCIRpZFh0oGrjzH9/E+Cwzvsm+YAgdbj+bvswU2/MGwr6dr++tx9IZWdj8eTXWXJPPWcQ8em0B8tNNqG13o7bNhW37T+PWS8bE+H4xJvmVjQ6WFL/pIiv7nQOnHcCXdVgy3Yqn3qvEqnkTcF83gTwh3cgWZfrZpTZkJmrx879/zb6PnsJ2F7PXfeC0Ay27qnDP3Fwk6tX43X8r2ffPqIa37K0DTQO1rU5oVXJWFR553QMdPIm1VUZBGu27K6QgDYQoPPp2rH/wKyJehQQBTmV0mg7//Ycbpggek2pUYl5hOruJwixeUw38aZMufyCmnay5Jh8ev7BSyBsM8apoXvpxieAxGgV/4Rmtgn/xmKZX4Z7v5sUQ0Kkii7/6TjfcviCH6HH7gqjvdAsWl0oXqSDMByFPRrFifEIL/IHycu3LmBpNTO9YWRoTlD52XSHkMiAvRY/nbiqGTiVHqkEFa2LPIi06mN22/zQevjofP+vu48w51mw7zBZ4UStIvBNBhEdWKU83qXGixcUh9FfOyUVGggZ5aQZ8W9cJs06JbYcaON7tf/lRCc7Yvahrd2Pz5+FieSvn5KLR7sHa+QV48M2e32PGDxkZLsAxLz+NU8wtGKTw9qEG1mZDbAEf/TzNWiW8wRDumpOLM3YPErWKmMXqitm5rO1Q7OaIjLc9jTZr8eD3J2DiKCNaurz4xRXj8cpn1Vg2cyxb/IMpznm3AFEt5gMtNF7GW/yqLxBrp0D42R5t6EKiXoUXP+3xJv+/qyYgO0kXM37cPTcPVc1dUMtleOydI7h9Vg6e312F2jYP7r9yHO94o1aQ2HOild0AYGKG6Gf0zjB5O440j9ALEWLt1O4OsXMl0ONxKlZYFgDSjPzxgtA8w8Co4ff3N4pskgJhu5SSLBNuvsQGjy8IrUqOlz+r7jU7QqeU4fZLc2I2pHW92F+EaODZj7ixyrMfiReQBQCNUoYGu5fjDf7L743DuFRhwhUAaFBsDY0eMroAPcmM/EjSK3GixRlTYyGpF1sJ4doE4u9hMDeGextPRyKi4wemZsGSTZ9z5l6+ApwM0b5uRwXuuHQsfj1vAioaHbB1rwVc/hBoGnj3YAMuG5+CBcVWkAQBu7enGOTWffVs4e3I969Xy1GUYcSB047wum1OLu9889yHYR/tvbUdCFFg51q1gkRte4/I4JFrJvLOP3q1DNUtzl43oc+3eeBcbKtDgXjfsz8UworZuTE1WY40OLB1X5gDuO3lvTFxYX2HO6Zd3n/leLQ6/bjzH9/ArFXGrLtWzsnF6EQt/hg1vr+ypzbMQ3Sv6R++Oh8qBclZU9zz3TzkJIsXZB5JkNqphJGCoSCH/QRBaADQAEAQxFgA4rllIqBp+j4A93X/1mUA7qVp+iaCIP4JYBGA1wD8CMCb/f1tJuWI8Qi+/6oJrII0mghlEKl+ikxZ4tudrm33YPOek1gxJxfNDh/e2n8a5bPGsh5Um3ZXY+ONUzA5k5s6zfd7akXYD7OywcEOtguKM/H4jgqWjFhSYsWWvXV49NpCPPDGQZbwZIjh22fZ4A6EUB5B5D25aBK8AQoaBck5Z4Pdiy176/DsD4pR2+5mPd4Y0njDruPQquSsynZBcSZ8wRA2LZ2KLm8QmWYN8tNNkMtJNHd5WRL5L5+dxA3TrHhy0SSQJIG8FD0IgsD3/9BTLCrdpMaoBA3n/kvzUrB2+xEsm2lDZaODJb0P1tth1ipx95wcJBrU+PYUfxpXIBTiBIkdbj/Gp5tQvjk8oTHvv8Pt56jG770iD4++XRGjCh+XZmDVjUMBt4CtxOTRCbzft3v4lTydHmHFSjxqo0CQ5l28/u1W/sWrTqnAcx8d5kz6z31Uhaevnyx4Dqc3xK+a9gpfVwg0EjRyDnGboJEjIJBrSZAEkvWKsKLIH4ROKUcgFBR9v00OHx57tzKmn45LMwoGJ8lGJa/iKdnIv1hUK2S8YwGzIcSHNIOKd4GfIqK0HigIedc1OryYl5+GcXeWoqLRgWNNXfjr/06iyZEes+ESraq9YkIq3okIZhvt/Odg2kbkBh7AVQ8tKM6M8eZjlLMmrQLpCRp0ugIsMQyE0+cOnbZD3U1YLJyaGVbiK2VI1Kvw+le1eO6mYnx7qhMhCuxYzJDIkQtziqLxWXVbjP+y0AI+slL0TRdZkWpUo77Djd/vPI4Otx+rr86HgqTx/A+n4uu6Dvb8y74zJmZRumJ2Lo43dfG2p5o2N579sArpJjUWl2Qiw6TBJTnJHG9PvuJ8kVXXX99bz2ZkMOf87XWFGJ2owcLiDHYREk/Bq8FAkyNc7PSXERkz3gCF37xTgWdvnAKTWo+nFk8CDcCkUaDD5UOiToUndlSits2DNdt7NiRe+qwWP7vUxs3UUMrwRXUbHnv3KNu2zVqF6IZzJIbqOQ0mQS/h7NDs9PG2l94857u8Ad544TtjLaLHuX38cca0LLPocRlGNa4vyWILEjPkaUYvZLQ7EIKMoDnzrtsfgLsXM1+7O8Abq3S6xe0o2lz+GG/w3/33KAozTBgrcpyMkGFvTQv+8uNpaHP6YNGr8MbXdbAlZ4uejylyHf08mZRrIaQYVLxkX29K5eEu8jnSEE2GaRQylhgGxOfeSPFQhyeIh7Yd4cylW/eF6xtEZn1u/MEUziZpOGOSRvksG+QkiewkHc50ulHT5sIds3Ox8rVvcPulOdj+7RlcPj4Ff1o6FZ3uABJ1SvxuRyUOnHbA7gmEN28jNqCZorcMXP4QpxAwM/90uANY+PKeXjehmWclzQPnPyLfc19jDItOxZvhUVaUIRoXvvxZLW6fxY2LIpX1DXYvXvpfDVbOyUWmWQsCgFpJot3pw7FmZ1gY1g0mI485x8PbDqN8lo1z3vXvH8OU0QnnDDksQcJIwVCQw6sB7AAwmiCIvyOs/P3xIJxnFYDXCIJ4FMA3AF7s7w9EkgYNdi8ee6cCK+fk8hKhkZMro35KMYSP5/ve2vmFKN+8F8tm2lDb5sam3dVYNtMWU5xg+avf4PWfXsxZsG/dV8+rUnX7Q3D4Qti6rx7LZtpgNWtYT+EFxZkgSeD+qyai0+1nP79rTi5LirS5/TF2Fcebw2SBViGLOecN06zQq+W4siCdTbNliPRlM22wu32sao5R7D16bQGunZTBpnQzzzmSRHb5QzjW3IUFUzKQnaTHnhOtHJL95ouzoFFySTHGa5QguIWYbiu14ZZLsmDQKHGgvrPHDiOK/EjUqVBsTeTsmEYG0sz7v2/eeLgDIeyr7YBZq4RJo2TbR6Qq/LXyi4aU0LB7Apx7AroLYQiQvTolP6ko5h/cX3Uy0H9v3zYXv62CmHdfgk7Be10JOuFUUBlIBKKKQQVCNOQEP6na4fbDFwTu+0/P4vbhq/PRKeJrHE8q7al2D6/iKcNcCGtibEBjUMl5F4kGAXsMAGj38BMD08ckCh4zUOBL42Q21EiSAEEA9/4z/IzvuDwn5jrX7ahAIETxqmojFy1CCtXI8zGIVA+JFZg72tiF2eNSUN3Kb8nz0me17AZFiAL++HE1fnFFHsanJ8CiVeI7Y5PwSVUryooyOIVuIhfmNW0u7K1t7/MCnq9SdKQyg1FMJ+hUCFGA1azB/MkZ+OPH1QCAJxZNQlVzF6s6AhDTnlaX5eP53eH+2OH2Y2yyHhadAqftHjTYPeyzFnp2DCnf4fbD5Q1g2UwbZCRQkpWIGdmJqLd70OQIPwurWctrOzLURZOA8LM91c6fvn34TBeyLVp0uv1w+UO4N0rR1eL0o8HuZe+9we7FHz+uxm+uLcDX3ZsEf/y4Ggun9vgtM9ZQYhvODAYzPVzCuYNkATuDpF42+s4IbKA12L0oGi18XEucZPShRgerqmWOeeitQ7Al61CSLTzvdLgCePqDKnZcpWng31/X4+Gr80XPZ1DLeGMCfS+ew3Y3fxxl74VULhxlwokxybj1r1/1kN/zC1A0yiR6nENgk76rl4KCRDe5F0329ZaDKTb/XuigaWHvaL65l1kfLCjOZDdZme8z5BcADjHm6s6mjFwPegIh/LNbHBO5ebJ2fgFWzsnF8x9X4YZpVjh9IU4G3orZubB7A5CTJN4/Uo8//nAqvuneAN60+wSWlFjZecgTCOGVPbHxyeKSzD4R4RIuPPQnxmDqM0R+d+WcXLyypxYLp2by9imCCMdFf/nsJFZ9bzy6vOGMkkhlPdBTg+mJhYWw6FX4254aTLdZYuJUJuaNPEe0xbA3QKGzF796CRIkxGLQyWGapt8nCOJrADMAEABW0jTdOkC//RGAj7r/uxqAeG5dL4hOOepw+5GbqkeKXo1Nu6s5RKiMBK6YmAqNQo4vTrYh3aRGfaeLVUpt/jxcBTcv1YAJaUa2ABNDZgotrs1aJU61c1MvlHICk0cn4OVbpsPtD8KaqMOYpHBKqowAW215+ewclrBlyLYVc3LCu2/dn5/qDC/uVXIS/lBsMbDX99bjqcWT4AmEsOm9YyxppVPKEKJoVDZ2gaKBiWlG9lk12L3hgkbXT8bccSnIS9Wj0e5FmknNqoWFnjNDIm+8cQpCFPBVTRuUMpIl2e+bNx6jE7VYs/0wJ8CKLASxbf9pLL88lyXwf3NdAb49FSaGGWuNSCJl3cIidkc0emc8Wi3t7lZ63FZqw+KSsAfxSAi2RyVoeK8j3cS/SNQLkIpCnrsA2EIX0aTiFRPTBI8xCXidGQTSUIWVsMKLOn+Q6rf6xqLnV+IKfR6igIejqpE/vO0w/rbsIsFzZJm1vPcyWsRzuMsb5CXHBVXQRDhFOHKRmGZUh0dWATQIEAON9sEvntibp1nkhgzfeFhWlNGrqpbvHEygymdfEKkeanH68OdPqmPeGUkAuakGZFt0aHB4Y95r5LgbeVxduxsahQwJOgU63QGQBDfROHqsaHJ4BTew+MaUbIsOa64pwO1/43rfRyp2ZSTg9VN48dNq3FZqw8ZdPdd4rKmL8zcQTs/73aJJONnqQnaSDolaGTYsmYJ2tx9apRypRhVryZNuUrPjKXOdfKS8WkFi3YIiTBptQqMjvPnGRwRvWloyqH7Y/UG2RcchvyPvKUhRUMlJtLpiN1Sf/uBYd3Xuak7Rp45uIpl53moFibxUA5bPzgEQ3vT1R2Ww8LVXYPB9wyWcGzCqZLx1AIy9kKDpJv54IU1koxcAkvT8ZLRFF59ildkUEkJY3Rg7rmqV4t7BCpmMNyb4u8h8DQh7s4rVFgAApVKGawrSMcaiRaPDhzSjCoXpJihFNtuBsK0E//MUt5VgNpuiyb68NIOoKu588449W1AUjV1Hm3Cg3g6KBltfpC9zLyP+EdoU5Stc2urysUIYZi2Vl2pgxSyR7fXBNw91i4c8yDTHZrBs2HUcT18/GY9sP4IFxZn4WUQMAICNAV78tBpTrWZs2l0d04+UMhJ3XJ4zKPZiEs5t9CfGiFbgJ+vVONnm5BR0FIoLb5hmxdq3K1ixxMo5Obzfr2334KG3DuOJRZNwrKmLFcERBDAu1YAn36tkf4M5JnqfXK0gYeylWKuE4UVlxRFcVrY45vNRyWa8+tKmYbgiCcAQkMMEQXwHwLc0Tb9NEMQPAdxPEMQzNE3X9nbsUIPPf8dq1uKj480ssdZg92L7gdN4fEERjjU5cX93uvH9V45DiAZe+6qOJY8npBkxcZQBWRY9W9UcAIfYjB4UF5dk4hf/3I+8FD2eWDQJNEXBH6JxS4RCYf314Wrm2RYdCjNN7LXxKYzzUgz4zTsV7IKe+c7oRC1vSnGH24/RZg12VjazQXq6SY2lM7LYIkTMNUSmd6cZ1QhRwL5THUg1hknhug43vqptj0lPiX7OaUY1jjR04daXv8SSEit2VTbiwbKJ2LT7BLxBCq1OH6t8ZiYHtUKG31xXiA07j+HWS8bA0B3kh4sy+VlimLHWYN5JsdWMmWOTeNOZrWZtTCDNVP3duq+e9UKKJpsfu65wyIPtiWlG3uJnE9P5lSveYAhaBVd5olXI4BdJ12Q2NDi/E6DQ4vRyPFMjkW5U85LQ6QLppEl6Ba+tQpJeeEJ3+UK81+USqfhtTdRhlNnJUTCPMmsEPRBbBRRTrSKKKZmM4PUplsuEmdtUowpZFg3KijLYgH3b/tNIFvBoNqqVePfQcdw0Yww63QEkaBX4++cnsWqesLJKyNc4tZcU34GAmKcZU9wl8tpiSFiSfyEWuaDhC1RlJDDFmsCeD0CM154tWc9bRHDlnFyMSlBDr5LhVIcbJ1ucseNqqgGr5o3Huh2V7GcPlk2EyxvAuHQDjjc72QWojABun2ULKybmTeCMFalGtegGFt/zVMpI3mfCzDHj04x4/qMqrJyTC28gxPvuo8f82jYX1r9/DGoFibfvLMXRpi6OL+PjC4qwYk4OKBrYcagBy2baYFSFx2DGcoN5Bl3damGNSgZroo4lL6pbnDGLj/6opgcbJEngomwLHl9QhF//+wCnPehVcpxsc4lWkX/02gK89mU4rGGOa+h0s3+vvjofT71XyRbsWzknF8EQHWOTwpfKKUS21XbPX1qlHP5QCBaBQkoSzg90eoL4xxe1eKLbzkqjlOPPu08g2zJB9LgJqQbeeGFCqlH0OH+Q31vSHxK3eUiLc84xqPu/iQ2ExzC+/tHhEc70AQCfwP35erGxoCgan55sZcf4quYu2L2BXosfpRhVvDUWUoziZDuTbRdN9vUmSjjfvGPPFnXtLpzp8LB/n+lwx7wPIfJcRgL3XzkeKQJtOyfFwApxmH/72+d1bEzICGHWLSyELUkvOoe7BbLQjjc70WD3CsZFhRlGbFpagg07j8bYSK1bWAS724+NH1Zy+laqpCK/oBAMUjjcYEeD3Yt0kwb56UbI5WS/LWiixVVjknR4Z0Up2l0+5KboOdl+j15bgHanDy/cXIJWp49DIo9LM8TEkZGFFj3dmZeR4x9fVuvqq/MRCPbEu2z77mVslTC8CIBE2jX3xHx+5q31w3A1EhgMha3EHwFMIghiEoB7ELZ7eAXApUNw7n6DGfCYYjH76jqw/NWwUfqymTYY1DIY1ArsqW7jKIgivQqZAUytIPHyLdORZdGzO/jrdlSwRdhe+6ouJjDNSzHArFViXkE6fvWv/exOcPRu3sSVpaDosPdhaW4Siq1muP1BZFt0uGJiGlqc4UCQphGzcy0jAINKhkRtbFG1x64rhMsf4qRC8XkI3fP6t2zRnGyLji3UUFaUAZNaBotBzRnso9NTIicWhjRYNtPG+nNu2n0Cv7hiPH71r/24k0cRrVaQeHdFKV6+ZTq+ruvEb9/tIcCbu7wcYpgp+McQw3I5KZhCE71QZ3Y7G+xeODyBmGdJEkCxdei8hhnI5SSuKRyFbIsOjY4wwV40KlalzYAkCPzls5MsCRmigL98dlK0YEuKgGooSUQ1RJAEDGqut69BLRd8Phq5DAo5yfm+Qk5CIxdW4CRoFbzXlaAVJpRJksDscamwJen7tEgSUloJkdxAWN2zff8ZduGuVcrxwu4TKMo0Cap7SILAXXPzcLLVxRKJd83Ng1zguuQy4PLx3IJ/q6/Oh8jjQuEoEx6ZX4CHIjzq+pICO1DgU+hHFneJ3riKHI8mpBt530OKQc3rjxZ5DuaZi6XL1ba78dqXtXjuxmLWpy9I06BpGuvercDd3x2Hx96tZMd/ps8r5SQ27a5G+SwbpoxOQKJOiUCIQqJOBQLAjsONMUWHnr2xGBPTTZw2x6TnrdtRwbFfuMRmEWybaSb+xSlJAA+WTcTzH1WFi2w6/dj4gynIsujYTcxt+0/HKA/v+W4eQhTNPhcZCfZZMUXnIjcnIz3tX/7fSbx8y3T870QrQhSwcVcVWyAnvPBUwe0PIdWoRpsrdsOlP6rpoYBcTmLehFSYl05FS5cPFp0Sx5u68NxHJ3B9SaZgFfmcFAOeeq8S5bPGYu7ENLj9IWQkqNHpDuClH5cgUavEii3fwB+kWeWWNxDC8aYupBrVvXo7CqWHf3Oqky3IwryXVfMmSHYT5ylSjWoca3ZixT++YT/rC+na0OWBjCQ486yMJNDQ5UGWRbjdGTVKXm/JmTnCRWkBQNVNekaToIwoQgj+EAWLrtvr3xeETi2H2xdAgKJEjzNo+GMCg0pcNRb2zjwcc39/+IH4/dW1u3C8KbawXE6yXlTJO9qsQ43JxfFUNmhkGG0WFxecjQJY8o7tQZsznM0R+d7uv3I8Xri5BF/VtIvOvS1OHwiCQLPDGxOnPDK/AE+9Vwl/kOb8W4fbD7WcxNPXT0ZFowMhCnjxk5O4a26e4By++up8jE7kjz9zU/TIsmgwIY0/Lko3qVkP5dOdPjammDM+BXKSwM9fPcq2dSAsZurNd1zC+QO/P4Q3D5zh+FUz1o9na0HDjDNWsxYN9gbOXKOUk9h+oAGZiVq8e/A0/rR0KjpcASTplTjV7sLzu6vxp6VTsY+n0KJGKce2/ac5a5gOtx9ahQzLL8+BP0QhJ8WAVz6rxo8uGcM5b26qvtciqBIkSIjFUJDDQZqmaYIg5gN4lqbpFwmCWDYE540bkWQCUxSNISbvuDwHv//gOPs5A7dP3G+U3cFPM6Dd5YNaIUOx1YxAKIQtP5kBdyC8gKYj/HOZneTo381L0ePruk52wc9HvjLKToqiYywc1l8/GZlmHR566zBumGbF7xZNgtsXRLvbj2JrAqgIQplRGYvtKNa0ubBuRwXrg7lspg3rP+gp4BSdnhJN6jA7lgQRTiNn7v1YUxe8AQp/+7wuZhd8/fWTkdVN4N//n4Mwa5UgCOB3iyaBpincPXccnv7gKEsMRwZ91S1OtHT5eFNoGMKbCaSDQQrrFhZh856TSNAp2MAv8lkOx+RDUTT21LSiyxOCyxdEI7xw+QMozUnhDWw7PAFen1IxPyZPMMSr4vGKqGrC/eQEJ/3x2Q9PICeFf9HU3OXHff8+GBOQvHLLdGQnC1yXPxjTHu6em8fuMPcGgRp0HJh1ct7FrVlE0ZxuUuPKwnSOj1xvFeG9wRAa7d6YReaoBP5jGu0+PP9xFSfAf/7jKtiSJgku8uNNgR1MRKawRVr1XGyzQCUPp9km6JRoc/rx+yWT8dt3K1Db5kGWRYO18wvRaPfidIcHD7x5kFViCvmjiaXLnbG78ZNZOWhweDmF01bOycX3C0ehq3tcj9yYAoB1CwrDxeXSjLg0L4WTiVDf6eFNcS62mmOuLXJe6Kuyi48oePTaQrQ7vSw5C4THcLNOiSlWMyZlJqCu3QWlnMTpdjcngFbJSFhTNHhnRSmyLTp8cbKNvXah4iJPLJqEP+8+gcvGp8DuCWBSZgIe2X6YDejvnpsHtZzkVIFft7AoXJi1rUe5tW3/aaxbWBTjKT2cac9HW7rYzZd0kxoLijNx00VWXGRLRIM9lhi4e24efvtOOE1y7fYj+N2iSVArSFQ1OzHarIU1UYd2tw/+IM0pVsQordtdPl7iJnKeTDep2c1lZk6bkG7EHz+sQlGGEbfNGguPP4i18wuwYecxjEs1CGZ3SDh3ES9J2GT34e+f1+DmS2zw+MJejy9/Vo0M0wRRctgXDGHpjGw8+d5R9nz3XjEO/pA4Wev0BbGzooElARJ1Cvzt85PIsghbLAGA2x9EhzuIh946wulfKSJFcAEANM0bq3TXwRaENxjCjy8Zw8kAWTVvPPxB8ftrcvgEx3gxcpgkCXzHlhyj3OvLRo5STkQRLtLmT2+IXmsE6VhLssfercRzNxazm2zvCFj1KEkSBGiYdSro1RRe+vE0tDh9IEEgxajgZH8tvzwH3iCFi22JoOhwhhRNG1DZ1IWbLspCVXNXTAz7yDX5aHP54fYFcbShi7c9n2p3YfnlufjPN7HConULizhWgZExyyVjLXD7g7xrgDZX3PXhJZxDoCga+051YMtX3ZknEfNAbooe+emmAYnFDjfY8ct/9VjBAeE13ZOLJqHV6cPl47jilpVzcuEP0njqv0fxg+lZWLM9Mou0AEoSuGGaFVazGs/dVIyv6zpB08Dz3VafAPDcTVPwxKLJsJq1yB/lRrvLB4WMhNsfQk2bi72HkVD4WIKEcwFDQQ53EQRxH4AfAphFEAQJYESbwESTCZG7aZFkbeTnrS4f765bJHHYlx18iqKRl2JgF6bjUrmeWEUZRqyYm4flr37NfmbWKlHZ6IBaQSLbouvVwiFEAe1uH+757riYiYC5XmYhqlXIICMJ9hqYxbKMBDQKOSiKRpPDyyF1hTy5mru8sJq1ePtQA+e8LywtCe8QKkj4glTMM2ywe/HXz2o4u+CFGWG1bpPDC7NWiaUzuCkmf/jBFGxYMgUNDi8yzRqo5TJ8U9+BM51erNp6IIbcZ55jS5ePYzPxXkUTNu85idsvy8XyV7+OURBOTDcMywRzqsOFM52+GO/BUx0u3sWeRavEb3gUQE8tnix4jvoOD9492MAJJF7YfQK2JB0KMhJ4j0kx8Kc/Juv5yc5WHjWhN0ChVSRgzUzQ4qG3uGqfV7+sxYs3TxM8pr8FnRo6fezittMVQIIubN+QbdHxFooD4vNoDobofvkn+0Mh3gA/IJLmS1E0dh1vGVHFrPhS2CgacAeC0CtlOGP3YtW/eza/HruuELYkLWrbPSjfvJdz74zKQMgfTShdrt3lQ0uXHzVtrhgf2Wd2Hsefby5Bok7B2ikAYY++DrcftmQddqwsRYgCvjjZBq1SjiaHF4fP2JFp5t9MEypM2Nu8wKeQ5rM/eq+iiZOuxwT2JElgbIoeY1P02H+qA89+fIJdyFJ0OIPgqcWTWT/Q9AhlstBYfqbTjSsL0zljLmMp0eUNgaJp/LabcGGOWbX1ADYtLeG8v1XzJuCKCakozDCNmLTnSI/uyAX2EwsL8bfPa3HH7Fw8d2MxvMEQqltc+OtnNewixRug0NDpRpJBzXk26xYWcdIgme+u3X4Er5fPABB+z3XtLjQ5fPAGgnD6Qjjd4UZ6ghan2t3Ismhx99xxHMuLe68YB4tOydmQWl2Wj1anRyKHz0PEaxPgCQaxsNga0048QfEN1WS9CqlGJTYtnYr2bpLX7vH3WgDPFwhhdlSGy8NX58MXECd5dUpFTLGvpz84hs23ipcTsXuCPbFKRNbO2F7UshadCm8fOM057uXPqnFpnsDOdDfiKT4LhPt4PAU4a9pcWP7qNzGxsRCRKYE/5nv02kKYtUqOV6k3QLEFkCNFL9HwBoNQyGW491/7YdYqsbgkE2OSdFAqSHS4g9h+4DRq2zycNZLDG0RjpweJemV34bgeEcB988azJDJNA+1uP57ZeRwbbyxGp9vPqflC02CLfa3/4BC7PovONqrvdPPGKykGNdpdft6NXrE6GhLOH9S0uWD3+HnnAdAh7KluQyBE4bkbixGkaRhUckzLChcPjbZkExurhGqc0AAStSrcG+Wl/czOnnoZ+DJMXNM0DYIg8OfdJ3DgtAMAsPHGKUjUKdgaIekmNe64PAcyEpzryrboUNnYFTPGKuUEO4aOhDWQBAkjGUNBDi8BcCOAZTRNNxIEYQXwuyE4b9yIJBO27qvnLYQW/fnre0/FeLox3sBC4Fv0kySBCelGtiL9k+9Vsucxa5X42WU5OFDfyV4f4wccSRYJWTgw9g+RXpKblpZAISNiBv15+WnISFBjZ2Uz/vLZSU4qMXOuTbvDRejGpRo4HlgaBckhtNNNaiwuyUQgROHTE60xBaYeePMgfr9kMpodXtiSe4iJyGccWfSOIYaB8KQQXdzBrFWiqtmJO/8RtgNhFuXLZtqw/cBpLJtpiyHdGQ+jH730JfscmWJJy2ba2GcerSC8ZKxFVCkyWGhy9BDDQPg5rtl2GK/cOp2XHC4cZcIdl+f2y1og06zhVcJmmDWCx5AEeBUPQvNvRgJ/EbcMk/A5xiTr8avvTcAv/tkz+T+1eLLoIolRt0cqbtftqMD4NAPvcf5QCJNHW2KqRYuRsEIezc1dwh7Nbj+/f7JbQCllUCl4A/zXfjJD9N5HWjErJoWN2dhh7unPn4RTMB/adoRzvff/5yC2lM+IGTsiC7EJLeyE0uUUMhLP7DyGn1+aI0Ae+9HoiFV156bqMWW0OWaR/2DZROiUMoxK4D9fPBkGYpsa0YRyX0gjf4ji3Vw4WN+JNdsr2N/feOMULH/1G/bao++leLQZN3ePlczzWrv9CMpnhd/F/VeO4/S1rfvq0WD3QiEjeP11R1Las6ClTIIGx5qd+OnmfUg3qfFQ2UTWhz/ye4WZCawNB9BDjD99/WTedna60wunrxU0aJxoduKxdyuxck5uuAgsDdauasWcnJhNjCffO4ryWTbOZ2u2h+cBCec3+pIBw0CrkGPN9q9j2klvpCtoGk4fhV/+i2tj1NvJtUo5Ht7GPd/D23o/X6c7wNtHOt3iFedTjSreWKU3v0mrWYsbpmdxjnv02gJYRYrIAkBWoi6uMT7eubi/fqAS+J/1A28cxMo5uVi34yj7PbWCZDdGxdLoCYLE6rcOx8QsTJ9YOz8fD755OGZ+DSt+PZy5whug8NsdlWzswnxvxexcrN1+GL/83nhekQXd7Xlf1exkN3i/MzYJ07LDJN6Rhi7eeCXbokOjAGkX6CULQML5gSaHFyaNEndt4ZKzz++uwso5eZxMZCb+SDGocLTJ2a/NLKH4yWrWoM3F7w3PxIkHTjvwq3/tR/ksGzbs5Lb9mlYXlDIDa8kZ2c/e/PY0Hr6mAKBpJGqVvGNsdJx0z+vfYtydpdImugQJPBh0cpim6UYA6yP+rkPYc3jEIpJMaLB7sfnzWpTPsmF6thkJWiXr4ch8npdqwIQ0I7IStSi2mvuk6AgGqRgFLTPojknSYe38QlZhxaRdT0gzoKLRwfFpjE77jVYRW81a1HW4u4vWyDiDZm1bWIUnpD5oc4ULuzHF4O67agIbRAM9A+yOlaWYlpXIkj3JOiUeLJuItduPcMjZEGXjLaTgD9Kw6JS4a8u3yEvRs8c22L3YsreOJbDTTWpWqceQ2dkWHau0ZrCgOJMlJyP/26CWsROKudtv+bWvwp7EE9IM7I4ms/PfYPewE9dI88Zs6eJX3LZ08StulUoZri0aBVuSjt2MKBolbi2glvNXAP/uhFTBY062unjVxuPTDBjD08by04343aIiHG92sp67OSl65IuQ1iRJ4LvjU/C3ZReh0eFFulGNwlEm0R3gNpePlxQTSuk2CpCwW0RI2OjiagBTaV3EP1nAKzFBw59cwefb6g1QoqmBI3FhyaRHVzY6Yp5zRaOD93pPdXhEA0uh/hiZis0ofvJSDHB0W62csXt43wFJEOxmH3OuZ3Yexzt3zsThBjsqGx24c3YOSIKAyx9Cs8OLiaNMePr9o6w/WuT5gDDZ2x+lQn8rSPdGsiplpKBNROTvv31nqWBxkfXXT0aIpnnfRYZJg19fOQ5mnQrrPzjE6Wtb9tb1yV93uJGfHlvs857v5uE/+3o2gBcUZ+LxCL/sSGKpXWABlKhT8razikYHm9K8ck4uzFolrIlaHG3q4pDBQsXwGJUYM28xfsY1rU5YEwdPhc23uQ1IqZuDCYqi8UlVM2sn1eby41SHS9BOikGLQIHVFpECqwDQ2MW/Cf3XW6YhO9kgeFyrk78PRBaE5YNQHzHr+Au0MvAFY+0Cntl5HFOzzKLH1XW4Y8b4B944hGKrWXSMykqMLWT66LUFyEoUJ5XjnYvP1g90OBA5PqQYwkViG+xDNy4IPetRCRrW3ogZ21/6X41oGj1F0fAGQritNCws+WXUOmjNtsN48UcleHxBUczG4DM7j2PN1fmCsQtzDRa9Ei//rwa1bR7Ud7hjRBZMlpS6O8OSIZUXTMlg7fKiY4Vndh7H23eWgiQJwVoFQ1GYWMLwY1SCGseanDGb9jdMs6KmzYXbSm3sZ8/sPI7yWTY2I68/m1l88dOj1xZgQpoRX9S0C8TaPf99z3fzoFHI2O8xmy8bdh7HXXNy8coeLhfB1MX42d/CG5gr5vCLPaio/UxvgEJdu0sihyVI4MGgk8MEQXShx/hLibClhJOm6aGphhQHon3dOtx+FGWa4PCGcNsre2DWKjmk8JiknkCnLwtfiqLxWXVbjAouctBVyIiYAc7lC4KiwaluH5n2y6iIt+ytQ4gCqpq6OIXhhAbN6MCUUasdbXSwSukGu5f1AI4+vtHhxcU2C9YtLEKT3YM2dwCvfVXHEtoM6aqSk/CHKF7F7idVrfAGqHAhpV09nqqlOUmYajWjvtMt6LMcXbQq8plE/rc1UYt7Xt/Pkv7vHmxA+ayxWLv9CGszEanEvq3UBrUiXECFeeZMgTuTWoaCjAQ0dqenDfUiONnAXywuWSTdU6mUoaRbYdAXtDh9yEvRh/0sI4jeVpcPOeBfGOo1Ml4Fj1bFT5CSJAGSIDlqh6cWTxZ9lsEghbcOnokJPq6dlCFYkE+IFNtSzk/2ugMCil6RtFihyudi/owObwD3zRuPNrefJccTtUo4vPxKKZ2Kn4DWiVRzH4kLSyY9Ovq6AEAlJ3mvlxbYoGE+F1rYMeeauLKUM4Zs/MEUbNh1HHkpepaoZsbXJSVW1He6Y67NrFViX10np6DHyjm5bPrmb64rwE9n5eBkqwt/vrkEHe4Au5CMJ5VtoIl9IaV6TauL83eL04sZtiRkW3RI0rvw8i3T4fYHYU3UYUxS2Oud713UdVeC//0Hh2L62qalJcPqJdxXkCSBZIOSUxRLIQvn9v6hW6luNWvYTdPI1F+1nAQZYcPEILwIV+Gx6wpjFDqv7KkF0LOYX355Dmianwzm+12jSoZ7r8hDqlGN+g43Xt9bjz9/Us2qxmaPSx3wuUlI0S6lbg4u6tr57aTq2l2iGUxJehWyLBqOL+q2/ad7tYcQJHmd4iSvSSvnPZ9RLb7kIEnEFMxcfXU+ZOJ17OAUqPnh8onbPMQ7vtZ1uNmxgOn7f9h1vFdSOd65+GwK0g0H+MYHZqzrcPuHZFwQetYnWpx4ZskUeIMhJOvDpHVRpklQ0BN5L2atEv931QQOkcak0bd2+XGi1cnbnqLjdSabMjfFgCcXT4LbG8CGncdRVpSBY81OdHlD+PfX9dh863Q0dflwrKkLmz8PPzvmOUa3AaG23OIMZ66da21IwsAhGKRwoN4OAJCRYNcad8/JQZAG7yYERQuPq2LjI1/8ZFDLcMYRrhESvUZiCiKvW1CI03YPXvpfDQBwLFOe/G8lGuxetLp86HD7UdPqYq8rWiAnJOSKHmrCwp2hSJ6XIOHcw1Aoh1kWiSAIAsB8AMLyuxEAPl83mga+/4dPWGKRUfrsWFnaq1ImWmFD08De2nbRQZcv7fq2UhtLXDAVpMen9dgjLCjO5Fg/RBeG66v6lVGrmbVK3D7Lxu5gM9/nO14uJ3F10SjsqW7FspfDiudnP6zC8tk9hPSYJB3HJsMboLC4JKzsvXN2DketzeyKLyrOwHsVTahsdMSk1K7bUYGMBDX8IYpjpB9dUZ55jt4A18+4NC+FLULFfC9yotl9tBkPlk3Ept0nsKTEil2Vjbj90hw8/3EVlpRYcevLXw3bIjjVqOJdRKWaxBd7/UG6SY0fXMRNuVx9db5ogTWCJngVPELppDVtLtYegvn+L/75LSakC+9MHz5jx2tf8hRVSNZjkpVfKdRf+wahhYWYykJGELyV3aePESbk9So5fCGKQ47f89086AXIXm8gyEsme0VIa6uZX+XUW+rsYIPxB4teNBlU8hjVzL1XjMMLu0/wFmHJStTgiokpnOITfP3Q7gmwComt++pR3eqCWavEvIJ0zoJp7fwCbN5Tg8vHp8S0gcUlmSwxDHA90/79dT2aHT78304uccx4HDIbgBnlM+D2h/qkoBpoYl/o93zB2N8XIgDHJOl4F5qry/Lx/O4qXD0pg7evKWTEOUES1rW7cORMV4w1TmGmCbVtHjz7YRV++b08dtOUSf1VK0i8fMs0/GrrgZh2+th1hWzKOVNUalyqAY91F7Jj4A1QSNarUN/hjpnHtu6rj+kXzyyZjC5fkNO3V1+dD7vHj398WYf5kzNgSxp4pbaQop0vdVOoEK2kKu4/Gh1eYSWvCDlMI4SfX5YTU2CVhnhKearAJnSKQTzOMKkVWH55LmcTbe38AsGMGAYygsDWfXUxHsAPleWLHhevzUO842uTw8uOBZHojVSOl6CL12t6uMA3PkR6iw6FrVW2RRcT9zDEV1GGCXMjakFE953IsUqrlGPdjgqYtUr8+JJsVuyiVoSLJf71sxp0uP1QyAjBNdbRpp4Cc5HZlJHzyw3TrPAEQuw1drj9sOhVmJqViInpRlwy1sKS2dOyzTEFt3pryyO9DUnzw+DhcIMdHS4/vEHuWmPt/AI4XT5OjLphV1g1DAAWnTKmiHBv46NQ/KRXKmI21NVyEhkJGvzin/txW6kNG3f1jKfM2HrvFXms7/DfPq/DA9+fAIu+Z16KrosRbfmpVpB4YmEROt1+jhq5L7ZDEiRcqBjSbROapmkAbxAEsRrAr4fy3P1FdIrunhOtHAJjQXEmDGqZoJoVCAdIbS4fWwSN+c6TiyaBosEqKwxqGTIStKhtc7FF3pggsrbNxQ6yW/fVs8pgpmK5RafEU4sn4xf//BYEAdHCcHyDJl9gyuxAN9i9eH53NX52qQ1/WjoVviCF315XhPv+w1/NlCSJmIJyQE+w1OzwcohtGRleIJu1SuiVsYTQ+usnI0QB97z+bUwBOSaVZMVr37BK3pd+PI39t3FpRtzz+rfsgtoTCKE2Su0W+XyYZ+MNhknEdJMa8wrSsWl3uHiTnAR+NW8Cbv7Ll1g20xajQh1qD9fRZh2yLG5sWjoVHe4AzFoF5LLw5wOFNqefdyH692UXITuJ/xihnWangIInHuVOp5e/qEKnV1jN1F+yN9uiw8Ybp+BAvZ0lYQszTaKLOLvXz2td0SVyXQRBYP373AI8698/JugZqlHwk8kahbB1Rbwqp8EEsxBoc/k4GzuLSzLx2LuVMYUfA6HurAKnH8tm2lCUYURuqoEtxCbmicZHcq6YnQuSRIxfuTdA4cE3D6F8lg2JWmXM4nK0QLE5guDa2TCfc4ptdH+2s7KZ3VzsbVMpXjJBaKHF93uPzC/Asx/2bP4xv1/X7kJlo4Ojkooc5yIXmhqFDGu3H0ZZUUaMnzvzu+dK+mqTw8f7Hl/68TQ8On8iTFoVu7iIXgCBAK+iOMWgBEkSsCbqML57brqt1MYWEGTAZAH8fudx3Dl7LOccHW4/Mswa/OXHJSAQrhPg9AWw8k+fx4zRK+fkYkmJFSTZO2EV3zPiH7f5Ujebu7wx9Q4kVXF8EFLytvWi5KUokiWGmWNWv3WYjZmEQBI01lyTH0Mqywhxz2GnLxSzifbgm4fw8i29FZYLYPb4NM7cvmJ2rmAmDYMxSTo2DmaOe2qxeM0PIP7xNV5SmSQJXDEhFVvKZ6DB7kW6SYP8dGOf+sBI82YXg9D4wKjIe4vxBgIkSWC0WcNuxtE0WNJVpZAJzpFC8YJSTuDJ92KLJa6ck4sErRLPf3wCLU4/b/YYkx1SPsuGaVmJ+Em3ZSDzO8/sPB4uBEbRWP3WYXS4/Vi3sIjXk5+iaBxpiC24dcWE1F7b8khtQ/0tGC2hf2iwe5GVpGNrqAA9Y/LKOblYOiOLLezsDVCwJmrh8Ydw77/2447Lc/Hsh8dZG5bexkeh+GnT0qlYOScHr++t52yo71hZirfvLEVTlwfb9sdmmxRlJrBjLVMM+r5/9yiQmd9hzsfYUf71lvDcxhRs/uh4MzsWkASQm6qPqw7IuYgbbynHmZYO3n87drwKwiXTJVyoGApbiQURf5IASgB4Bb4+YsGn5F0204bfRyhzGZJw4spSdvJeNtOGFz/lKl6PN3fhWGMnfn5ZDp77KKxCZVKPN35YxU6KV0xIxTuHGziD3ubPa7GgOJMlR5hBekJ6KVqcPvyvqjUmYI0eNLeUz4AnEIrZOWaCJZLoSYtN1ishk5H46eZ9MGuVuOWSLGxaOhUhimZTjCMn72gFB0PO7qxoRHaSDo90EwgEAWgUMshIAotLMvH/7Z13mFTl9fg/Z7bN9gbsLmV3WVmkg4ioiRgVNSRB0QimGjUm/FIUoymmaYz6tcSSaExijMaWYo3GGEM0lqixYqEoCEgTBBaWhe113t8ft+ydmXun7c7sAO/nefbZmTu3nHvvedt5z3vONUvX2HGAR5fm0d7dy+jS3KAkX87zhnpJWx2K686YxpFjy41BuGm4qCzys2FXG7/6z1o7nnFnT7CHsfVsf/KZiWEexFZDdt0ZU12N7tZ7TXUM16a2vrDBUCTinZnf7tHB397sXXyHFbh7GpUXuMcMHOGx/7B87xndXI/kOvdGGHimYkldeb6fB5a9F+Y5fMvnDvM8Zp9HAp59Hgl4Mnw+V2NypIzTXl5OO5uHJuawNRC4bulq5k8bRW6Wj7vOOYLMDKHRNH6EJn48/4RxAHZiSitOulucvdCJGjcvplueNZbvV5e5G3tHFefy2/+u50uzq/nFwumsb2ihLwBtXT2u2cCVwrNeEEcR82f5sKKMxDKplIi3j9tA69YvHsbY8gIaWjqZVFXIE+cfw5qdLazd2cKfXtnEghmjgsIkAby1ZW/QJITl0WTVc86BZiCg+Ooxh9grTtwm+vaX5att3e4TXK9saKSqKJcbnlrDKdNH8cibW8OyyVsreUI9ij8xfjYbdrVSW55vv89Nja1hhrcrFkyhsthPU3s3+zp6yRC4fuF02rt62dXaxY1Pvc8fz55tx8lbumq7q6xledn87B/vcsPC6UEGq8HyzvIyjrkt3RxR6E/LpJj7I5VFiXnytnZ6TNp2Rg67kOnL4KFl/Z68udmZ3PvyBn76mcievF5xt/e0RzZi52RmuIZ/itS228dmSdDgPycrNoNrIt6UA5m0izaZeSDgVT9YeQwHsvolVgIBRXamUF2WFzTB+/NTJ1Pkz/A0Rnr1F25YON1Vp8cOy+e3z623vRsfWLaFB75+FFuaOlizo8U2ugHc8sx6bv78DNfz7G7tok/BuR+rYUJVMR+rK3fVCa+69Mklc9LaMzgSun0YXELb+dGluZ45O6y+wvnHj+OGp9YaE9TZmdz41Fq27+vksr+v4k/nHUlvIBCTTnn1n7bv7eT3L2wICy9j5UWoKcvjghPqw1Y4HlVbZicxrizys2pbc9AEfEFORtC43p/l44IT6mnp7OUT44bbeXVOOLSCumEF+13ZGAw+2tVE5akXu/628rrFKZZGsz+QCs/hUxyfe4FNGKEl9ivcPHlzMo3OjzMRDBjJwqyGzjIYOPcpL8jm87Nr+daf37K9UEvzsu3f39/RzKSqQgIKPmhoDTPwOo0jFnXDjZhS3T39MX3dPIUvmTeRqaNKosbVspK1feO4cfa2s46q4ab/BA/4Qz0zxg4Lj9c8aWQhE6uK+Nnjq4KMuUvmjuOaf63m/OPr7ftTjuzs/iwffzhrFv4sn30vDyzbwuePqGZ0aR4wKmwgcckjK5g6qtg2Wjif0aemGp7A5x1TR7E/g2mjSxg3opB1DS22d2ihP4ObzpzBhl3BscOqiv0MNw2ZMPTJ6Tbudg/HMKHSPftqIKB49v2dYZ6wkeJRVnl08COFlQgElGu4C+WxerWjt8/VA6+z1ztMglcyvt0RkrIBZGcGDx6zM707Blv2tLFuZ2tY5udxwws8l++W5GXyjU+MC7v3knzvpbTFee4J6Yrz3I9pausOqivANFBGSPSTl+0e/zFSorxksqmxjeuWrnad2Bk7zH15sE/64/SNH1FoxGQNqJg8z7326e4LeCYE3NPezQ/nTWRdQysCPLRsKwDnfKw2TCfyszP43X83cOas0RENZk4Da6isteX5nka7eL19nGGBrBUuDc1dQbFgrztjGjc9/T6bGzvsRJ9rd7Ywxgw1sqmxzV4RY8lpLTd0q+dCjSyVRX5OnlTJrtb9ryPutUS9LwA/f+JdzjvG8KR2yyZfnp8dFlf44pPGc+H97wTF2qwbXkBXby9tXUb9N7wghy1N7fzy6bVkZ4o9EXnJIyuD+g6nTB/FnvYuDsEwyDsTtzjlyMvJtPsfVlkBYvLOisWA7GUcy87sn1i2tvkE1uxo4Wtz6njh/QbmjB9h10NeCUE17uRmZ7iGCMr3iOlvUe6R6K0sSqK3Pe3dLNu8j2Wb3w7avjeKkbfI7x4bvzBCbHzwNiy0dUc2Ym9qbLPrN+f1vJItO0nEmzLcA9jP5KrISXEtOQ8GI5hb/eAVK3cwcKuzrPjcu1q6+Pkpk43YpzkZ+MTI57J1T5s98ba7rYvrlq5mQmWhZ3+h0EOn87IzWNvQan+/ZN5EivOyWP9+Q5BjkPV7VoZ7TPqGli5ufW49NyycTnVZrmf+jGh9nnT0DI5GOiZNHgpiaXuj7ePmHHDjohkU53ror9lXqCzyU1Oey+dmVXOFmRAerJUpXXxySlVM9+DVf7KSot78zDruPHsWmT5fUFiHaMlBLWeQdQ0tYRPwNeW53H7WLJZt3kNfwFgZ+fU5daz4aB8KRbYZgqWiyM/sWvdJl1gnznX4k9SwZvV7HDd/Udj2kcNL+ctdtw+BRAcXqYg5fG6yr5FsrMqgqjiH3r6AbeytH1FgV6ZOI8f4ioKgijF0nyVzx9nLA0UI8ka2zlFTnk9VsZ8Hl4UbeK8+fapn4iUrMdwlj6ywPYVvP2sWWRkSsSJzdlq37+vk3lc285NPT2TNjmY6ewJhQd/dOrXWcxpemM0DjriaSsHfl2+zZ/ss7+C+gGJzYwcNLZ1h3rpgPJfV2/dx1WlT+eljK1m6ajtL5tbT0NzF+oYWMnyxe/D2BfqD7v/tLSM8xyV/W8EXZ9fYxp6a8lwOryljeGEmwwvK7AbOSlK3vqHFNprHEp4jmWze0+Z6717ZVzc3uhs7DxlWwFgvr0XB1XCbEaEdbO3u5bb/rg/yqLvtv+u5+vSprvtvberg3lc2h3ng1Q3LZ8qoEtdjvJLxRUqus3F3G1c+8Z5tIA0ouPKJ9xhbXuD6vLyWRs2sLvU0Dn+0t5O/vrY5yMvqjhc+oLY8j5py92PysjO4+KTxtjewZUzyMtyOKvW7xqsbWRrBYK8CfOPYcfz8CYfRev5klIq8NDhZ7GzuDAp/A/0TO/9aMifM+HHlgilMHWWskggN4eMVwmB4Qf/zGFHoPskxsbKIW55ZF6bjVy6YQk6Wj4tCBrZ9AcUv/7M2TCfuPHsWP/nMRD5qaueiE8fb+1hG2EOG5zO6JJe87Eyuf2qNbUz47MzRZPgMT/hn3985aIm8djZ3uqxwCX/WVpxkZ9tz+wsbuOnMGQwvzHatX8Y7VquE4mZk2R8zQYdOcDqN+p09AarLcmlq7w5711edNoUL7n+b7l7F4mPrmFRVxHvbm7nrf5vsd75mRzP+TB+1w/Lp6A7w/YeN93DzM/2DoqpiPzubu2jr6nXtXxwyLJ/Dq4229v0dza519NamdvxZPt7b3sJ3H1rO1adPZXxFQVTDVKzLe708LgHby2d4gZ+Nja3Mu/lFu30NrYfqRxQwM6D04CpGMnxGm3HDwum0dfeSn52Jz2ckcouEz4d7eIgoxxUkkAAVDCO2m15Gm5CsTjB2cKqNS4l6AB8sRrDQ+sGKlXtYdcmgTxZ61VmVRTls2dMepIM/O2Uyj7y5hS8cWUNfiCPKRSeO56O97VQV5brqYFdfwFWnlTLq+8PGlFBTbsTjf21jo+vY7arTpjKy2M81p0/lR46+jBW7uLMnwJqdLQwrzHbtZwYCit4+NeTOKYNNOiZNTjWxtL2x7OM2AfXdh97hr187MmJfYUtTO9d8dho/+tuKoDwI/iwflcWxvwe3/pOl32CM65vaelizsyXISSlWRw+3cnXBCeO59O8rbWeHLx1ZjT8rg2Wb9pCblcE1S9dEnRCPdeJchz9JDT34XL2dP3r8piGQ5uAjFWElRgO/Bj5ubnoRuFAptTXZ1x4MnJXBecfUkenrT1x27dLVXDJvYlhF7PT2feTNrVw6f1LQPgHH0ipwj3v540dX8sDio2lq7w4yqLZ39zIuwoDbSgw3dVSx5/IJt5mv0Ip5+75O1uxsseWMFkrBq9I8oqaMF9bvshM1gGEAvOGpNfzwU0YIhz+9usWO9+v0div0Z3HlE+9RmpfNxSfWM3V0Ca9saOT2FzZQmpfNZfMnBXUoLM/C9u4+ewmvdd/O8BSWEfq8Y+rswb0Vw3ixGQvsx5861G6ArP3Hjyjg7I/XsmDGKHw+uGHhdMQHEyqKwsJrJJv8bC8vBvci/dG+Dldj57TRxZ7G4YaWLlfD7SEREt+0d/e5hjDo8Ej8VlWcG+TBK6ZHb6TOSGVxjutAtzJCMr6P9rW7xgPevq/d1YDV7uHB1B7BgykvO5N9nT28v6PF9ozb19kTcUDc0dNHZWG2ETu6rYfS/Cz2tnXhlWCuozvg+h5n13onvfOJ2AYZ65ifP/EuDywemrygFUV+z4mdnS2dnDZ9FPUjCtixr5NK0yNrS1N7mCfrxQ++w9IL57h6KK3Z0UyGD0aX5NHR0+vaKd7U2GbHMf7tF2ey6qNmsjKEumH5fOnO1+x64bMzR9PR08dhY0rsxB1OmV/buIdRJblc/a/3qSr2B5WXUSV+Wjp72dLUERQz3qmLt7+wgYtPGh+WuC5Rb7KKIn9Qm+JVd2f4wjM9W9e+99zZngb1A70TbBk2Ri0+imfWNNAXwF4a7M/ysWVPB3e+tIEfzZvAhXPrmVBZSFl+NkvufzvIE7uzx4jBO7zASEBUlJsVtPTxqtOmUJqXHba6qLo0l4/2dfDcGiMh6oqt+4LiPv/o0ZWMKctjR3Mnd728mW8cWxe0IiIvK4M/vrwxyKD940dXei6Ldg6+4vFs9PK4dHr5OL05508bFVYPOVf6aKLT0tnH5sb2sLpseJSwEh09AX77fPCk7W+fX8+1n50W8bgAih9/agK72/oToJbnZxMg8sTi7tZu8rIywvRyd4QVLgBjSnK5csGUsER2Y0pyIx7nNQHonCQcTBL1AD6YjGBu9UOkpImJ4vUu7vjKrLC+0s//8a4dJio0wfUv/7PWnHRp5YoFU7js78GJ7G59Zh1nf7w2SKdHleaycXcbDy3byrH1RiKO1zY2kpedSVN7N0tXbbcTJ+f7M5k6qoia8gJK8rK5YeF01prhqu5+eZPdvvgET33Y1NjGT/++0jUxb215/n7r1ZiKsG/pTix1Siz7eBpZW7uoKva79hV+NG8CLV297Grp4vJTJrNuZwt3vWyEfrj69KlMriqO+T6cE0ObG9t4+8O9tn5XFRvOLc6kjtaKzFjqxooiv20TceYkKfRn2n2vUEc7t6TQ5efOZnhhjl0+Yq3PD5aVHxpNKsJK3AX8BbD8w79sbjspBdceMM7KQAR71qqz1zCCbWlsD6uIH1y21V5aCu6Gpn8s32aHSXCGVbDo7AnQ09fHTWfO4Lqlq8PCLUSarYq0TM4rHmVORvjy1AyBx94x5Ozq7YtYcbtVmtctXY1PoDeg7Pvt7O3jgWVb+OrHxrKrudM22tz36mZ+vmAyuVkZdhInp7dbbwBe2dBIQJnxi/Z18rvn19uxhpwZgEvzsu3l5xOrDMOts+GxBuPOQfmPPj3RToIC0NzVxz+Wb+O8Y+qoLs2lNC+beVOquOWZdcyfNgofUJqfjUBQTNFUkZ+T4Tpo81pe2uIZc9A7fENxXpbr0unCXO9qozg3yzWEQbFHlvKJFYV89+RDWd/Qat/Hd08+lIkVRZ7X6OnFNQ7irBpvA2lORnyxDIs8wg0U+b1DRCTioTs8P5v1DW38wEwUYXm3DPNY7rvDo+O3I0Ic6PbuPg9Dt/e7Tya15fkcUVPmWZ9kZvqYPqaU6WOM7YGAYldLV5CBzOro7Wg2Yug6k85Y8cwWH1tHdVkeO/Z18ufXtoRNcpxx+GjACA/w5pa9PLFiG98+vp7/rttl1wtuHc17X+mPIejPMsINWB52obFmT540gvwcYUJFIYtmjUah+MmnJrHkgbeDdPGmp9faMd+sbYl6k9WW5zN+RKF9D5OqCu04ydaz82f5mFVTxrLNe1x149WNe1zjBkdL8HSg4PMJU0eVsG1vp6cH8TVL13D7WbM4ZtwwXtvY6Do4qSnP5fJTjPis3/xzcJz0nz62ytZbNw/hH82bwK6Wbte4zy+sMyZcm9q7ue2FDXx25mhyMn3UDcsnN9vHOUfX0tbdZ+v4I29upa27N+rgazA9G0PPFUus/v3VuJEqOrr7uP+N/roM4P43tjB5pHd7CUYMYLdJ2z1RjLU9vQE6eoIToF504nh6ej3iRJmU5Wfxf0/2r9TpC8AfX97IDQunRzxu9c5mbn0uOHnqrc+tY3xFAdPHlHoel+HDtT8UzTM6URItJ9oINvh4vQuv5Mgd3b3kZWcElSGrXdy6twOlFBmCayK7huYucrMyGFWSy/pdrVzz5Bqa2ru5+KTx7G7t5st3vm7X+9cvnMbWpo6g5Io3nTmDMaX5VJfls35Xqz3esX6/+KTx1A3P99QHK39EaMLTUSVGHe7moHPyxAq2NLWndZ2aaOzvA4mBhEhz7uNlZPVnZfDIm1s475hxNLV309un2Lq3nc8fUU1nr5HvyNnP/d4nx9PY0kWhPzPu92DZIGrL8+noCdiJdxfNGm2P0a1QWZ09fTS2dnNYdWnUutFZf/7mOSOp8xULprBxV6vr6uPOHvek0C+u380dL26w7SjWarvQcH2h9fnBsvJDo0mFcXi4Uuoux/e7ReQ7KbjugLEGKs7KwJq1uuyUSdSU51JTnhdWETe1dzOzuoSlF87hrS17aWjuDNrnkTe38pWja7j/jS3MnzbKjmXlrJwyxEjuNbO6jFElfj53e3BG8kRnq9yMuCu27uPv72zjeycfyn2vbmL+tFFk+ODIsWWMryjiF/9ezXkfHxvm0eGsuN0qzXOOrmXj7jbuf8PwlHtg2Ra+9YlxzJ82isb2btsD2OrkBPqU3VFyM9x+bU5dUBK5Fdua2fXsehYfW8eRY8s4755lriE6QjP5Qr8XszUoX9/QEiS/5eV3y7Pr+NqcuiBPPGsp9nn3vBGTsT4Z9PQFyM7MCBq0XX7KZHr73AdtI0vcl8pVRfC2LcjOdPW4jBQ3sLI4h28fN47LnEmWTp1Mhcd1tu3rYFtTR1i4i237OiJ4NHe6xkHc1drpuYy9rbvXtfH3imW4r8M963SkrOmJeOjuau22YxTbx/zjXe776mxqh4fv7xVSI5LnmFdnsSJC7OhkEhr+JtIgubc3wD9XbQ/azzKQNbV3M6LQz/Z9ndzyzPqw64wqyeXDPe1MqCpyneRQ5mqGS+dPoi8Q4MoFU1i2uYn6EYURO5qLj63jlmfW28fe/sIHTBs9KSzMwEUnjufKJ97lzCNqgryQrvnsVNcO5nBHWBQ3b7JYDWc+nzCxqoia8ly+OLuGix9cHvTsHli2hYtPOpTcbB+fqB8e5EFlXburN8BfX98atlz2YBqsOQesa3e2sHJbc1Byoc6eAFkZgs8ndhlz6oy1GuWbf36Lr82pc33nNWV53PLsOtcVSFYbGTqhtfjYOvoC8Le3+pdXWgOlJSfU8+yaHZxxeDXX/fv9oDq1siiHy+ZP4gqH93JomRtMz0avc3mdWy/ZjE6fCriugAlECRFUkWAiO39WZlgonV/+J3ICVAB/ZgbfOm5c2Oqe3KzIYSW273NPnrpjX6c9WejGrtYuVyP27taupHirJlpOtBFs8PF6F9b/0O0ledn0BZTtfOJsF0eW5PKDh5e7jiOWnGBMDH925mh+YPZHLG56ei2Lj+2v4zc3drC1KXy13sUPvkPRV2ahgMoiP+MrCphZXUpzZw8luVkML8yxE3RFutfQSegzZo7ydNDp6QuE9bPSsU5NJPb3gUKs4UJiqXfcJqAunT+JPa2dnDRpJGff9XqQM9V5x9QFxcZ29nP7AnDBX9+OKXa7G6H1XUtnr2vZGlOWz2HVpVHrxtDz5WZlsMQM5WU5n7n1s0KTQisVbEexPJpDx7pZPl/QKuSDaeWH5uAmSfPqQTSKyJdFJMP8+zLQmILrDghroLL8w712R8NKipadKTTs6+SH8yZy7dLVLDmhPqgzct0Z0xhdkse+jh5ufmYtuVlG/DVrn6b2buorCvjj2bOZU1/OhMpCbv3iYXzl6BrufGkDtz67nt+/sIH3ththHbw8/xpaOoPk3bCrlVc+2M2GXa12AprQ7W5G3ICCYn8WI4v9LJlbT4bP2Pbaxj0U5Pi4+5zZFPizbI+OH3/qUO465whKcrPY1NhGIKDsStOiqthP7bB8bn5mnT3TPX/aKPL9mfb5O3sCdifn1mfXs2p7c5BsNeW5dqzfzh4jREeZmSzP+SwnVBbZSSa8lklvaWpn3uRKnlwyh+PGD+O6M6bxj+Xb+OmnJ3HLs+uCwl4AdrzmBxYfxXHjhzFuRH8caa9rbGpsS0jXEsEnwuUhRsXL//Eu4uHGPH5YAVcumBKkp1cumML44YWe12jp6uVfK41lcdd9dirXL5zOv1Zup6XLO7RCU1uPbRi25Lrs8XdpanM3qnqFu/hoX4fnNUY4EgNa+LN8DMv3HujWlucHla87XtzAV46u8fTQ8Gdl8MAyw0Pr/BPGcd4xdTywbAvZHklCIDEP3R3N7sn1djS7J9fr6OnlZ/MnB73Hn82fTEeP9zuxOovOY4baW8kKf/Pkkjncv/hIO9N2aPiblzc02gMb6DeQLZo12r6H0LoHjHvcsqeD37+wgfbuXi46cXzQ/V86fxLF/gx+eeYM/vPuDtq6+lh835vc8sx6bnhqjR2P0+3djCnNs3WirbOHz82qZuuedvyZPhYfa+jL4mPr8Gf6OO7QCtswbB2/aXebq7xWHE+392O1R5++5UW+8IfX+PQtL7L03R12PR/K2GH5XLlgaphh55Zn13HVgqnc9PT7LLrtVS5+6B2uOi24XlhyQj1/e2urbXTPzc6gbnhB2g0mU4E1YB1fUcidL20Ii8VnTbBYZcypM6HthGudVZjD2UfXEggo13bZTf/GVxTy4toGtu/r5L5XN3PTouksmWvo432vbubIuuFhE043P7OO7l7F782ErEvmjuP2s2Zx8sTghKTVpXlh+nDVaVOoNhMVxoOz3pk2qohpo4rD2iCnnm/c7b5kc+Pu1LWr6U5eVqbrCphoRtfevgCXnxLcblx+ymT6ApE9gD2Tv7ZGTv66p73bDmNh1ZW/fX49e6IksrMmsZ0Yk9iRB9/ZGT5XI3ZWklyHB9KmWnXKUXXDDtp6NV56ewMs/7CJpau2s/zDvfQ6PNfd3sWSE+r57XPrufik4Hb/ilMns62p3Z4gg/4y9MN5E/lob7s9Lrnv1c1cvzC4bt2+r9OzXxDaFLd59Adf3biHr9+7jBfX7Wb5h/s4vLqUkyZVcsTYcmqHRdaHSHrnNrabP21UWP8p1WMVTXQ27u4PFxJqS3DznLXa1Fu/cBjXL5xOS2evXSYsA+qTS+Zw1zmz+OWZM7j9hQ/YtrfLdu6y8gotPraOCZWFnvpsOWk5bQ3xElTfDStwDaP508dWsqmxLaa60bmPFcbQKq+WY4cTf1Z4Uui/vbXVvnZDS2dQTiJr+83PrOOVDY1Bfe3B7B9pNOlMKjyHv4oRc/iXgAJeBhJOUiciY4B7gQrzfLcrpW4WkTLgAaAW2AScqZRqSvQ6zozvlneOZTC89rPTOPfuN/jWceNcl/jUlOXy1OqdrNnRzPxpo7hm6ZogD9minAxGFOTQ0GJ4gFWX5dMXICg+n3NWK9pslZfHzckTK8KSZvzhrFlh5zKWUB3C1qZ2+hRhXpyledl2vE/La/bcu98Iu5ZztnLRrNFBAwvLCFxV7Ofq06fyzodNrnJY25yxmr82p86eLb/tBcOod8PC6eRk+agbVsDYYflsajQMLtGWrlp/MwOK6aOLWbF1n329UE/RS+ZNZOqoEnw+CYojHcvy2GQTryHy/V0tcS/XrCr286mpVUHL4i6cWx9xoNbgYexs8DB2eoW7aOn0NnZ29PS5ejR7xekFw9Di1vifPKnSdf+qolw+f0R1eOK3Yu/Yh4l46Hp5dDmz+DrxZ2XyyFvrwkJqfP+TEz2vAUYcZ2esMWec56EimqfIpsY2z7AHh40p4RPjR+DziaunhHP5/08eXcWFc+s575g6MnwwbkQh1zy52g6vcO+5s/nKXa8Hef389vn1XGEaskLfTX5OJo+8uZWm9m5+sXA6Nz61hu+fPMGOo+bc9+enTA6T/8FlW+1wOE7dqh2Wx/2Lj3T1mIg31pnPJ2RliOuze2PzHjY3dtj3+utn1/HA149iT3s3b3+4N8g7VntFGERbDm7HKS7JtdtPZzvh1r7cdOYMjq4tJy8rg5fW747YHlr4s3ys3dnCvClV7GrtZvu+Tlq6eoM8573ap5Uf7QvyyvRn+cI8grY0tfPrZ4PbiV8/u87OGB4P1jOZ/J05vLaxiSX3v01pXjaLj63jkOEFTKoq4hDHADDeJKsHI03tPa7PaG+794oWABEfD78ZHoopWrsxvDDbVQfLPcIeWXT0uOceCJU9lMIcj9VKEcI5QepDJ2kP4ORjrZTZ19HN+oa2oFWLV502hdOmjyIz04fPJ0yqKuSGhdNZs7PFDgOxfV8nu1q7uefc2TR39uDPymBEYRabGztcdWVdQyt9gYCt79v3dXL1k6vDPAonVha59wtCckt41d+W16LlnVldti9iyBQnkfTOrf8ZT9JuzdCxeU+bqy2hPD/L1XPWalOdsXtDy0Td8AKUgs/82kgIO7wgJ0gXrMn/W794mKue+sxwQIPZBxw7rD/kmZNEddKp81Z5DW0/rjptCkX+LG5YNI0te9pd+7de4SI6ewNBfW1g0PpHGk06k3TjsFJqM3DqIJ6yF/iuUuotESkE3hSRp4FzgGeUUteKyA+BHwKXJHoRq7KwZqSsymDOuGEElOHl090XcF3ic/KkEbZR02qcncbRs46q4UwzTIQ1SCzNy/KsMGfXlkccmHoZDh5YfFTY9p/+fWXQcu6a8lyOqitnd2sXVSV5dlxja/+bn1nH2GH59jYvr9mlF85hUlUh95w7m/buXpSC1TuawxqdpvZuxg7Lo6s33MA3dXSxfZ/b93WyYVdrmOF2+75O7n9jC1cumEpWhtjLRazB+xbTSOxlSLfw+YSAgg/MWEXO95zhg7kTRtiGYQjOwGqdM9o1kkm8hshElmt6zaZ6GVQBivI8YvV6xBwuz49/8Lmlqd01UV5NeR5TRpe4HuNMSGhhlS83w0NNeT6TRhYGZYUvzM2gJoJnUCLxBH0S4IpTJ4eF4cgQ90G0P8PHGYdXBxnsf3bKZPwRPJo3NbZx5RP98R8DCq584j3qhqX3Er6dzZ22R3+oftQ4BuJWh/nQC+bw3vZm1uxoCVv+39bdx50vbWDJCfW2Ydj6bU97t31+KymYZWALXYa/5IR6rlu6mkWzRuPPzODGp9Zw/vH19KmAq37l5YQnjmxq76aiKCfIWF9fUcCkqmJP40Iisc686oiJlUWcf8I4wDBabm7sYE97N58YPyIoPlw6eJinC7EYg4w4xcWu7YTVviw+to5JVUWMLPFTmJPFmx820RtQdvI554RBWV423zv5UG546v0g/bNCqljLQStjDN8QGnHITX+smJah7USixgSfT9jb3mN7z2/f18lDy7ayaJYRI9knYidztZKshobXihTn/WDDq70si2Kszc/JYO7EyrCJXq8cBRYKXI21RLGBFvndE+YW+CNfb0dzp2vbflh1iWeYKRia0EkH8zL4ZOAMmzSi0M/GRiOh5S8WTrcNw9Afr71+RL9jgxEvuJ3KwmzGlOdTP6KAnEzhzpc2MLwwhyPrygHYsKuVrAyfq67MGFNMdVke4yuK+O5DRh+uqb2bkSV+fvflmbR19bF2Zwu/e3592ETfhXPrGV9RYJ/X6sNec/pUfmQ61jjrb+s+Aip6yJRQvPTOrf8ZKbeDJn0o9mfZeSEA2/ng2PrwnCg+n7C3rYffOJx9wDBS1g8vYHp1/0SDc9zj1hf1Z/n4cE+7qz5byeoS6QM6y3JedibdfX2U5xsJ4CZWuU+uJKKToTrf1G4kQj3/+HF09gbwCZTlZfHVe960bS9e/VuviRzo7yspxaD2jzSadCXpxmERGQ58HcOj176eUuqriZxPKbUd2G5+bhGR1cAoYAFwnLnbPcDzDMA4HDojZcX0++xhowCj4nAaLZ1J0Bpbu22j5mXzJwVVOl7G1Qf/39GeFWa0gamX4cBK2uQ0eIDh2fzkkjnsaeti295Ozr37DW75/GHsdRhJnOcpyu1vVNy8kkrzsnlry17bu9jyUH5w2YdhcTh/ccY0qsuMhAxb9rQxs7qU9u5eqsvy7WRH/fGEMrn1ufVBhttifwbDC/0svm+Zbdy2DMWTRxbik/DBjFfjtrO5004waBme73xpA1efPjXIMAzBxoE9bV3UjyiIGi81mcRriKwqznVNFFcZyQs4ToMqQEtHj2us3pYud8+miuIcV+OoV4xiMGJxu8WQjRRWIi/bvWOUl+09WG3rCgTNzN905gzPfSExb6KsjCyWbfqQP55zBI2tXZQX5PDYW1s4tHKs6/572rt5atV2fn/W4ext66EkP4u7X9pIpYenMUBjW5drnMo9bV1p3aGpKPLbiSzdMnM78fnE1snvu3jwzhk3jJMmjmDJ/W+HhQaoKs61jVLnfKw2qL66fuG0IEOFZXSuH1HItr3tzJ82CkWAkjz3mN7b97bzs/mTg5IULjmhntueX8+l8yfT0dMXk54kEuustjyfGxfNsAe6Vqd/V0unPfiwYi3mZWdqb7goxGIMcj7DLXvaqC2fwk8fW2UPXEaV5PLUqu3UVxaFGdz6AoGgJEi3vbCB7Ezhd1+ayZtb9gbpH8D4igJ+eeYMyvKzgtq8fyzfxs9PnRwU79WKje3ETX+SEVPP6oeAMfkSWsasGJgVRTn8+FMTaOvuC3o2hwwv4LCASlgPD6Qkd1kZiitOncJlj69ytJdTyMqIHHO4o6ePvKyMsEz1kVbbALR09LoaaydUeoejMuT08f1PHsr1jrjX3//koVHDPFjZ6EPb9mj6pxO97d+4rX78/icP5cK59a4hdzp7AkFG1apiP9v2ZtPTB//Pkdz3igVTaO3qseOG7mzupLtPuU54lOVnUzusgOqyfCZWzWFzYxttXX1s3dvOR3s7qa8oIDcrg7UNrewyJ/qqS/PsCY0vzK4OKie/++8Grl84lSeXGOdyW5XjEyL2wePBrf2uLs3T5SIFDKSNCQQU2/aG513Jz87wXEG4q62LL86uCctxsasteIWmsz3ftrc9TO+tONqArbszq0vo7VN09vRy46IZzKwujau9dCvLVj/zknkTw1YZD0QnnTq/vqGVvoDi2qWr2dzYYT+TtQ2tAEF2hGmjiqivKLTfU6TVhxDcBunJFs3BQCrCSvwdeBH4DzCoa7xEpBY4DHgNqDANxwA7MMJOuB2zGFgMUF1d7XluK7aMNbCzlidUl+bh84ldkdz36mYuPrGe0vwce3b7wrnjbG/U3z2/PsgjKHSZjxUIfXNjW0SjZqSBqdeAzjIIhhqG6kcUcMo0Y3bxy3cawen3tnUxotgjaVlRbkSv2UWzRvPjR1cGefys3r6P7550KDc+/b7tjXt0XTnDC3J4bWOj3YC6JQux7jMQUEGexHe+tIHbz5plG4athD/W9yVzx4UlufMJTKoqdG3crIGI0zPcZzaOkWIdWWEppo4qTqoRJZKuxmvImVhRyLePrw9KjHXFgilMrCjyvH4iBtXhhX5u++96e/lqXnYm97y8gY8fMtl1/55e+I0Zm9DqVP/m+fUcXhM+Y25RUZTDz06ZbMfVtLxnIxmUu/v6XI3WPR4J/OJdxm8RrzfR5Koi5oyv4NUNjUaW9YZW5oyvYHJVsev+1WV5zK4rDxoAXTi3nuoy75hX2T6fa5zK+7/unSgvHmKtU+OltjyfS+ZN5Lqlq+06ZFZNGR+rK/fUc6eHv7MePaK2DCAo8Zf12+SqIm46cwabG9vC4laub2gNStYBRhlYs6PFNmBcOHccv3nugzD9uuLUyTS2dfPIW1u465wjeGVDI30B7E5y6ASUF4GAQim4YeF01jW08OAyw7B76xcPQyl45YPdrgMSn8+YMHMaHO99ZbMdDmPtzha6evu4bP4kAkoRMA1wB6o3XLL0NBTrGQLc+qwRAkYFFBk+4fYXPmDO+BGuKzIunFuPPzMjSIcumz+J93e0cMeL4Tr4wa5WJlQWMbGymJ0tXUGGv8riHJ44/xjW7Gxh7c4WHnh9S1iYnKtPn4pPsN87JMfIVuXoV3zpyOqwMnbxg+8w/vxjEBGGF/lp3N5MaV62bVT+wSMrmDKqOCGdDAQUz76/kxVb9xn1q8DU0cWccGhF2hqII+lpT5/wm+fXhbSX67hh4fSI5yzLy+F/HzTwpaPG0tTWQ1l+Fn96dSPH1LtkPXVQU57vaqytLousD+X52ZTlZwfpZFl+NsOieDgnqn96Yiv1DGZ96hZv/Pp/v8+Fc+tZv6vVtR/q9ArvC4A/M5OfPha88vGyv6/i9rMO5+X1jYyrKGBseQE3PvUOXzqyNkg3R5XmMsHsC1v1d215Pkvf3WEnrqspz+X7n5zADQuns7ahhb4A3Pj0Wjs8VW8gEFZOqorz7HO1dwevyrlwbj2jS3M9+3qJ4NZ+63KR3LZ/oG3MpsY2fvDIiqDxc2dPHzNrSjzr2ZLcLPdEoV+dbcu0qbGNxrYue6XwPS9v5pufqLP1fkJFIdc/tcaerLAc4BYfW0duVgajS3OZMTq2PqoTt7J8ixmK4eIH37HziwyWTjr7W+fe/brtAKUU/OX1zSyYMcre17IjhIbTcrYfO5s76elTXPr3lXbZdrZByZxsGaiefvHcxXy0Kzya6tp16/Fe76vRhJMK43CeUiphD14vRKQAeAT4jlKq2ZmISymlRMTVlUIpdTtwO8CsWbM83S2ixd4LzZj5OTNMBBgxJS1D74ptzex74QNuP2sWWRlCXnamPUNoLXPo6Onj+w+viNmoGYpXh3pyVRFXLphqG0/BqKgveWQFU0cV2x7Hn505msv+8R5Hjy0LM4jfdOYMasrzqSnP9/SaHT+i0DUD6Y2LpvPHs2ezq7WTyiI/721vCYtVHClrrlVhT7pwDjubu2jr7qW3r3/5dqgXdmiSO4uPHVLuaoR2PjerYbzpzBlRBz6WbMk2okTT1Xhk2LqvIywx1mV/X8WsGu9YSfEaVAEOHV7AmbNqgpavXnHqFA4d4e5p1NDivox5V6u3d/KY0nxGlrSFhXwYU+r93srzc+wEc1Z5fmDZFuZNcW8yE1nGD/F7EPh8gk98QV4DNy6a4XnM3o4eV8PS7LFlntfY1ZpYUqFYibVOjRe7w1ZZGHMnMpqRwOu3eZMreWbNzrDn9OCyrVy5YEpQvMMrF0zhgTc28+3jx5HhgykjixlWkMMdL22wjdgTK4v43fPrWdvQahina8qoKPLT0NLJGTNHxdwZdvPCuPr0qRxeU8K7H7XY8eS86lMrrlwo6xtauPXZ9fYk0e+eX88vFs44II3CFsnSUy9qy/P56jGH2CGmbn3WeA/HHjrCtTweMryArAz403lH0tMXYEShn6172+jtC4RNHF99+lRmVpfYme1POLSCumEFYXpdZ8b2/dgh5VQW+TlpYoVtML7+3+/T1N4dpDfJMLJlZ8JVp03h18+uo6Y83/Xe1zW0cpGL145lIE502eaWPW2s29ka5pU1bniBa58gHYikp7tbu13by92tkRO9ZWXC3IlVQZOKPz91MllRRgBek23WKi8vxpTms25XG+NHFNptdHaWL2IbDQMz8h7IE1vpyGDWp17xxkeX5rFxdxu/PHNGkEfgz06ZTE5Wv040tHTS1uWev+L1TU3c8eIGLj5pPPUjCvjqMYfwx5c+4Csfq6Ozu5cxZXkcPqaUTJfQXKG5GsryMxF8VHT6g0IA3bhoBjlZEhRWwllOfD7hU1MqObTiGDY2tuHPyqA0L4sJFUWu1x1MdLlIbts/0DZmZ3On6/i5pjyfI2rcj9nT5h57fk97T1ifsaY817Y/VBX76QsY46uKQj8XnFAfNN6/csEUqstzyc/OTFg3vcqyM7mdM//PYGE5k4S2VdmZ4eXSzZjrLCeBgOKuc2bHNYYYDAaqpx/taqLy1IvDtq+8bvHAhdMcVKTCOPyEiHxaKfXkYJ1QRLIwDMN/Vkr9zdy8U0SqlFLbRaQKaBjINaLF3nNWJK98sDuoMrQygd5z7mwUKqgCcXrDWsbNr82ps42af3trK5+dOZoAsLOlyx78RSJSh9orKZGVDM+f1Z/E7bm1u1mzszUovvIRtWX29b28ZpXCNQPpdx9azpNL5nBU3TA27GpNyBMT4L3tLfaxlle2s7Fx4hY6wWvJx8HkbZKIsTNegyoYie+sJa/WNS57fBWHVronvktkGbPPJ8wZN4JNjW0xv7fa8nwunT/Jnt3P9MGl8yd5zvgmIlciHgSbGtvsZf9glZt3mFjlXi6cS7QtOnuMJZZe5GRluN5LTpQM9+lAIgObSMd4/ebzCUX+8HjZTe3dFOdm8cDXj6Kj1wgB0drVw+dn1/LTx/rD6Fx04ng+f0Q11WV5TKgsIsMHP/7MxDBDXbydYWdiVMurZHNjG+MrCmKqT7302JrfsSaJzj9+nI6bNsg425ddrV1B3r9u76Q4N8uOjWkxdlg+NWVtNLZ2c+fZs+juDdghmEK9xL302rl9w65WvvdQcNiVUL0ZbGPC5sYOenr7WHzsIYhHkqY+c+m4FQKrs7ePH396Ilc/uZqm9u6El23ubO5ynUybWV2atsbhSBT4M137OAX+yF35HXu77DAjYDyHnz3+LveeO5vqstjCpMTTR9rS1M7//fO9IC+uJ1ZsY1wMeqWNWQcf+R6r1AS46em1dmic8vxsuvsUd7zwAWV545hYVQIY7VxLV69r3FYrAdxNT69l+uiSkAnnIk993tTYFpQkHOD2F3wsvXAOVcV+O7+KMyTek1Fi0o+rKGRcReSQLJr9i4G2MRVFfhbNGh001gK4+Zm1zBhT4loP+rPc42b7s3xhqx43N3aw+L5lPLlkji2P5XgzpjSP+hEF7NjXSWWxn8lVxQOerPAqy0olNwSDV1sFkcul17niHUNoNAcSSTMOi0gLRj4LAX4sIl1Aj/ldKaW817NHPq8AdwKrlVI3OX56HDgbuNb8//cBiB+XcWhEYfi+Te3dDCvICfN+dFZga3e2BA0WQ2cP73hxQ1TvWud53SosN9n8WT6GF/hdk7iFxleOFl4BDKOYVwbSPWYMJOe9On+PZpAIbeicXtnWvVi/vfB+A9/4xLigcANWKJB4n1ssDHUsw3iun2jM0ngMquBthN7Z7O6lWl2ax/ULp7GuodU2qI4bURDxnUFi7627VwXN7keKIZzI8tZEPAjiNdpXJZB4pzQvyzXGXmmeTvTkZEShEfN0d1u3rYvl+dnkZvuYPLK/07z8wybbMAz9S/puWDid7Exjsq26zD1kTrx4eZWMKcuzl95buOlNtFhq1nGVxX4qk5i86WDFqqecYaoeeXOra3l0iy/o8wm1wwqoHTY48iS6ImIgVBXnohRcu3Q1P5w3katOm8KHe9rt8CgXzq3nw6Z2eyVVaGKc+oqChJdttnW7exO2d/fGfa6hbu/BWE78nRPHs3F3m11HfefE8ZR4JHy12N3msXqkLfrqkUTa2sFObKg5sKkoygmrE3/8qQlk+MROnnr7Cx9wyScnsOSvb+PP8gXF6q0uzeOtLU1hfa+8rAxue2ED0F/u3fTZrWx71ZU7mjs5qm5YxJB4mv2TROr4gbYxteX5TBlZHBZSaskJ9TR65AUpyMl07asW5GTG1cZnZvqYPqY0roSI0XAry1bM4Wjj8YHi1VbpcqnRxEfSjMNKqWRNj34cOAtYKSLvmNt+jGEUflBEzgM2A2cO5CLxGIcyfO4Znb1ybzhj5Piz+hPbdfb2uSari8W71gsv2TIzDMNrVXEOqPAEDfHE0fH5hImVhWFGq5ryXLbt7eTLd77O1+bUJRTIPbShc3plZ/gICnFx3IQRtmEY+rMaW6FABhO35d6xGvKH4vqJxvLr6lFhIQ8iUZ6f4/qevbKpb93bzvZ9nUHXuPik8Wzd2z6onl3xxhBOxGMqEQ+CeI32U0cWc8WCKWGxo6eN9I5bN6GiiI2724KWR452xNjTGPh84M/O5PZ/rQl6tve9spFRJXn2cjMr4aiTzp4AaxtauOWZ9QOuC0IzPX/l6JowvfrpY6tYfGxdUMgIN72x9PjQC+awekczGSJcu3R1WFK+LXvaOczFs18zODjDVOVk+qivKODCufW0dffhE6ivKIgpnNFASUbCuWhMriqisa2Tz82qDgodcen8SbR19lBdns81/1rtmqz35mfW8c8L5iTcptaU5bveb7zPeqjbe4vOnl52hLSXRuzSyO9vdEme63MYVZKbFDmHQs80+y/VZfnUVxTYfZSinAyyMzPCQs1kZvqoKc/lghPq7Vi9gYDi3e377OXx0F93nH/8uKAEcG7l3qtsT6oKH9NoHT5wSbSOH2gb4/MJFYU5LLn/7SD9veXZddx1zhFBOQEsOnt6yc7MCGoHLj9lMp29vVQWudf1qdJbZ1nO9PmoG5aPQrHo8DFBoTk1Gk36koqwEoOKUuolDO9jN+YO1nXiMQ5ZBktrSciIgmyGFeSwtqGV3a3ddPcanlmhxzsNdve9upnvnFg/6F49obIpBf9auZ2KIj8/fnQl5x1Tx50vxZ7EzY1AQLFxT3hCPSvecWleNvnZGUGJ+WI1TroNMprauxlemBMW4qK9uy9lXlGJJiwbqusnYuzcuNs95MGEyjme8YADKH40bwKN7f0z2mV52SjcwyftbO7ipqeDEytYy/8G0ziciMdcvB5TXjHvInkQxGu0z87O4LRpI6kblm97N0wbWUx2hCSBmZk+PjW5iuqyfYO6fOxAY8e+Lte43OcdU0dDS6edoOb9Hc1RQzUkWhe4DVCuO2Oaq15Vl/YPAqz9LL0J9YAZO8xY+rplT1tYnLlL50/igde38LFDyj3LtWZg7GzupLvXqAO7+wK8v6MFnwhTRhYx3pE1O9kkI+FcNHw+IcfhFQWG/l75xHvcc+5sDq8upas3wAe7Wl31fMuetrAwGrGSaMzcUIa6vbfo7FWuE5B3fGVWxOMK/ZmuTgJF/uSsHhkKPdPsv4TGTReEs+96PcxYdsPC6Xxn7ng+M6WKzEwfvb0B/rlqu2fd0d3XvzLzxkXu5d6rbP/zgjlahw8iEq3jB6ONae9xH7u+ubmJEYV+lxXIPi4PcYS6/B/vcve5Rwx53WuV5dLcbD7aZ8QC393WxZ9f28L2fZ169YhGsx+w3xmHU0msxqGKIr+d0XnaqCK+MLuG6/69hs/Nqg5aJhI6CxlqsMvNco/V45zxi3fZi1M2iyVzx/HjR41l0Vbc3liTuLmxcbcRmyvUwNwXCNhLom9+Zh2leUb26nHDC5g8sjimAV+0hs75jjZ4ZDVOZMY02nMeiuW5TrzDN0S/vooxzP3mRvfEAlv2tHkakYYX5NDVFwjzBB5eEL5kGhJfkpVIOUj2bPqwQnev6fIoGdpDk55kZ0YuE9nZGcyq9U5A50Yylo8daHjpYobPCM+zqbGN65auZtHhY7hywRS2NvUvjXcL1ZBIXeA2QPGq13Y0dwZN+o0q8dtx7b08YKw6/ZdnzuDDPW1UluSxpbGNbx4/ToeVSCJVxX6++Yk6exlod2+A8vxsinOzUhqeYCji7G9qbOPdbc2uZau5owefTxhZ4scn4qrnnT0Blr67IyEv3cG636Fu7y06PNvLvojH7WgOdxK495XNzBhTwtgkyH8w5XPQDC5KQUune8Ktjp4+tja181FzB9Vl+by8oZFLHlnhuTJxVk0pv//yTOqGF3CImSsmFK+yvau1U+vwQUSidfxg1HUjCtzHDh0e462WDvd2oKWjNy3q3kBAsb25k3UNLbaT0DeOreOPL2/UnveaAbFm9XscN3+R628jh5fyl7tuT7FEBybJjDn8JPAtpdSmZF0jXXAaML927CH84OHlnHdMXUwhIkIzZEYyhCay7MUpW2leNotmjaY+JD7wQIxmgYBi9fZmVwPzA//vqKBEddv3ddrLrp9cEttS0XgaOmdcR+v5JBLjKJbnPNTLJvM8gv7neXiQJqI7/mz3pAfZETxO+wK4egLPnVDhuv+YUvclUKMjvLOBloNkzaZ39fZx0Ynj+eV/1trXuOjE8bb3ihtuSU+s8qFn11NLjYcuzqopo7Y8nze37Amb8Lt0/iTGVxTwvYeWh4VqSKQucBugPLhsa9iqiwvn1nPvK5uDlsyeMXMU4O0BM+nCOQQUbN/XwbVLV/O5WdX84OHl9jmvOX1qTAlQNfGjFLR194WFA1i3s4WKIn9Ky3qqE6o0tnUxpsy9bH3Y1M7Sd3dwaEUh33toOUtOqA8rX929fVzyt5UJe+kOxv16tfe5WRmuy36TRVl+tkfYpsgewHnZmWFOApH6C4OBTtyjiZXQPt3PTpnoquebGtu586UNjCnLRwSWbd5DZ0+AR94MbyOXnFDPpX9fxeePqGZUaW5C+Ti0Dh88RNKDaM4oA9WTjt4+rlwwhUsd4eKsOL3H1ocnHCjOC0+e7M8yktoOhjwDZc3OZj7c0x7W37n69Kna814zIHrwUXnqxa6/ffT4Ta7bNfGTzHXFdwFPichPROSAznxkGTCfXDIHn+mJa3nkOrFmIWM5z/2Lj+TJJXOCDF4bd7sP+jfubot6zqUXzuH7nzyU21/YwPs7W/BnGa/eindsfY/XaLapsY11Df3ns/Bn+agozPFMVBfpObjdQ93wAo6qG0adx+w/BMd1PP+EcZx3TB2/fnYdW5raCQQUG3a18soHu9mwq5VAwNt91su4sqmx/zlbxsZEn9tA6e7rC3tvS06op8fDEJmI7uRkZHDh3OBrXDi3Hn+m94CyocXbC8ONrp4+12t09Xh7QsXyfkKJVrYGg/L8HP7y+uYg/fvL65spy3f3mobI3gqDSTz6f7CSkSFhunjp/EnUlBsDy2yfz3VpfGd3gO+efCgXzh1HVbF/QHWBNUBx0tTeTXNHD/ecO5v7Fx/JPy+YQ31FAU3t3baczuu56VRpXjZvbdnLp295kVc27GH+tFFh9/KjR1dGLEOaxGlocY9HXpqfM+hlPd3I9vm4dunqsPbqygVT6Oo16m4jN8J4O2P7krnjuOnMGTz61of4fL6k1Inx4Nbe/2jeBF7+oJEnV27ng4bU1KkKXNvLaFcOqADXnD6VJXPHcf4J47hw7jiuOX0qKtZlRBpNEnHr04Xq+ZIT6vnbW1vp7Anw08dWsrmxnZxMw4Fh+75OHnh9C3eePYslc42+132vbmZzYwc3P7OOpvYez2vXludz6xcPCyobt37xMG3EOogIBBRKwQ0Lp4f146pL81j67g4+fcuLfOEPr/HpW15k6bs7BrW+39rUQUdPL788c4atvw8s28Lnj6h2TVSb5Qvvq144t56sjPSY2G9q73Ht7yiFdj7QaPYDkpmQ7iER+RdwKbBMRO4DAo7fDygTv2XAbOnsDaqw4/UsjTTjt3lP/Mv8rXMGFHYoCcsgfMuz64xO1bIt3H7WLLIyJO4s3DubO3lw2dYwj5+rTS+0vsDAPJPjwStD9p62LtbsaInZ0zSW5UVDvXSnPD/HHkhby0QfWLaFeVMqXfdPRHfKC4xY0c6QB/nZGZQXeIdJiNejektTu+ty15ryPKaMLnE9ZiDLv5I5m15bns8l8ybG5Z2cCg/0dEmmlO64xWe/9dn1HDI8n5ryAva0uyeie2PzHntFxNWnT2VmdUnCHri15flcd8Y0O8mmNSi+/40tfHJypa27Y4fl86RH3eOmU4tmjbbrfzASlabDMvmDBa+QJR3dvYwoPLATQ+5p72ZzYwf3vRpctpo7emgz8wTsaO7k8JoSfjhvIqt3NNMXgOuWrubzR1Sztak9paty3LDa+1GLj+KZNQ3kZmXQ2RsIS+Kb7Dp1Z3OXa3s5pizy6qisDB+7WrvCwj3VV+iyrhl6Qvt0bd19PPLmVs4/fhxjyvJYu7OV+17tXynT2RNgx75Osnxijz1WbGu2Vyc66ewJ0BnB2QCguzc48fJNZ84Y9HvUpCdu/WNnPy4V8earinO55l+r+erHxgIgAgtmjKKmLM81sd12jzBBNeV5HDYoEg2MTo8Yyh1RyqFGo0kPkh1zuBtoA3KAQhzG4QOVyVVFXHXaFH797Lowg+lAPUvzPUMJRH+Nzs7X9n2d9kBt2qgi6geQEMeKaewc+PkEZlaX4POJZ7D+ZMzKexnasjJ8cTXusRrshnLpTryGyER0p7osn5Glrexu67a3jSzNjZiFN97wDcMKclyXuw6L4G071CE9vEhkwiAV4S7SJZlSuuMWn92pV16hXJyJ6H786MqYQ+a44fMJn5lSRWleNss276EvYEz6XDJvYpBORKp73HTKuYLjkTe3ctn8SWlZhg5UvDKajyzNPeA91Kxy4ww75c/ysfjYOpTq17sxpfmsa2gF+gfHeVkZ/PHljWmRCMrnE9q7+7jlmfV8+/hx3PnShpTXqSMK3dvLEYXe7SVAW1efR+LX2UmTVaOJFa/E0zc8tZbvf3J8UFkDM6RLdiZ5OZlc/+81nHdMHblZPkaX5rrWs2Mj1B26f3Rw4/b+nf24VMSbn1xVxAUn1PPrZ9cxf9ooMnxw2JgSPl43zLUvWZaf7doOlEXJb5Iq6srd+zuRyqFGo0kfkhlzeB5wE/A4MFMp1Z6sa6UTmZk+Tps+ivoRBexp6+JP5x1JT18gbo9cNyqKclwzTrstOwk/NrjztX1fJ3e+tGHAsU2dhojfPLe+fylOWX/CuFR52HoZ2tq73WcxvRr3oc72GgvxPtdEdCc0g3Qs7y4RuX52ymR+bmbe9Wf5+Nkpk6ko9pYrnd9PvBMGqSgf6ZJMKd2JplcVRTlcfNJ428hiefUORiI6J5mZPo4ZN4zRpbk0tHRyxsxRcemEm05ZRrjOHiP2+++eXx8WozFdytCBiNsk6S/OmMZRteUHvPe+W7m5cG49I4pyuOWZdbbeOdubnc2d5GVn0NMX4K5zZqdNIiirHxUpbFgy69SKohyuOHUylz3e315ecerkqH3ARBO/ajSpILTt/cfybXb+kD+9usW177p9bztzJ1Zy1zmz7XZudHEuvzhjGj9wrLy5cdGMiGVS948ObqK9/1Q4ozjtBjv2dVJZ7GdyVTGZHvldKov8ruOmdEkqPHZ4ATcumsF3H3on5nKo0WjSh2R6Dv8EWKSUejeJ10hLMjN9TB9TOujnHV2Sx9hh+UHL/OsrCiJ6cloky6AWi3ErVR62XrJsamyLq3Ef6pARsRLPc60uy6e+oiBu3Unk3cVzzJjSfEaWtHHDwum0dfeSn51JYW4GY0q95Urn9xMtcYUbyS4f6eppnW646VV1aZ79PquK/dQNz+fCufWU5WVTVeLn0r+vGpREdG6yDEQnQo8PTXa6tqGViqIc/nnBHHa1plcZSlcSKdsW6VxnJZvqsvygcpOfk0lpfhb52Rlhht+hTqQTDasf9f6O5iGpU8eU5rOtrJ3bzzqcpvYeSvOyyMwgYnsJ3p7rsfQdD3QGUq41g4NX2zuzupSdzUb7euHcetq6++zwZiNLcxk7LN+uMyzmTxvJlFHFMdezsfSPtI4cuER7/6lyRrHsBtPHRN+3uiyfzXvCx03pUp/7fMKnplQysSr2/o4uYxpN+pDMmMNzknXug5FAQPHU6p1ct3S1vexkVk0ZH6uLzfMomYPTdBrQucmSSOOeTvc0GCTiBZwqueaMG8Gmxra45ErH95OusX3T2dM63XDqldv7vPWLh3HypEp2tXZSWeSPO8b0UBGp/o8Ur15jMBhlOx3rrFSQrm1PIljlaFJVITXl+XYc71SVfZ9POGrscDY1tpGdGfuz9ArvNXZY+tVVqSRd2+yDEbf60dkWjyj0s2VPG3nZmVQU5XjG9Y+3no3WP9I6cmAT7f2n48RuouOmVBJPOdRlTKNJL5Idc1gzSDjjIjnj9sUTFuJgHpymW+M+FKTr+09XueIlXWPXaf1PDLf3ef5f3ubJJXM4qm4YYHhw7C/P9UApZ0NBupbt/YUDSfd8PqF2mLHqZsaYkpSX/URX8+g2IBxdrvcPrEnMZExkRisbWkcObNJp9Ws8pKNMiaLLmEaTXmjj8H6Cjos1MA6khlSTnqRzGdX6Hz+xvE/9XA8O0rlsa4aG/a3s72/ypgJdrjUQuWxoHTnw0XXj0KLLmEaTXmjj8H6Cjhuq0aQ3uoweWOj3qbHQuqDRHHjocq2JhtYRjSa56DKmGQzWrH6P4+YvCts+cngpf7nr9iGQaP9FG4f3E3TcUI0mvdFl9MBCv0+NhdYFjebAQ5drTTS0jmg0yUWXsfj44rmL+WhXU9j2tevWUzkE8qQLPfioPPXisO3PXvc1bTSOE20c3k/QMeM0mvRGl9EDC/0+NRZaFzSaAw9drjXR0Dqi0SQXXcbi46NdTa5G0JXXLR4CadIfL6PxR4/fNATS7B9o4/B+hI6LpNGkN7qMHljo96mx0Lqg0Rx46HKtiYbWEY0muegyptGkD9o4rNFoNBqNRqPRaDQajUaj0WgOSrxCdxwsoSi0cVij0Wg0Go1Go9FoNBqNRqPRHLB4JbADI37zsd/9bdj2dA1FMdjGbFFKDYZc+yUisgvY7PHzMGB3CsXxQsuRXjJA/HLsVkrNG8gFo+hqvKTLcwxFyxUfgy1XsvV0qJ/jUF7/YL73wb5+MvV0qJ9TvOxP8h6Msg5IV9O8PnWiZXFnf5ElmXqaKOny7NJBjnSQAYZejlSNpYb6Pt1IR5lAy+VGuo35Y2Wo36Ueo6UWTz09qI3DkRCRZUqpWVqO9JEjHWRIJzkSJV3l13LFR7rK5cVQyzuU1z+Y7z0drh8r+4ucFvuTvFrWwSWdZNSyuKNlSZx0kTcd5EgHGdJJjmSTjveZjjKBlutAYqifmR6jpY+++oZaAI1Go9FoNBqNRqPRaDQajUaj0aQebRzWaDQajUaj0Wg0Go1Go9FoNJqDEG0c9iZd0hFqOfpJBxkgfeRIlHSVX8sVH+kqlxdDLe9QXv9gvvd0uH6s7C9yWuxP8mpZB5d0klHL4o6WJXHSRd50kCMdZID0kSPZpON9pqNMoOU6kBjqZ6bHaGmCjjms0Wg0Go1Go9FoNBqNRqPRaDQHIdpzWKPRaDQajUaj0Wg0Go1Go9FoDkK0cTgEEZknIu+LyHoR+WGSr/VHEWkQkVWObWUi8rSIrDP/l5rbRURuMeVaISIzB1GOMSLynIi8JyLvisiFQyGLiPhF5HURWW7K8XNz+1gRec283gMikm1uzzG/rzd/rx0MOcxzZ4jI2yLyxFDJ4JAl3vczQUReEZEuEfletPO4XO/7IvKO+bdKRPpEpMz8bZOIrDR/WzaIsrm+exfZPJ+3iPzI3P6+iHwpxXJdbF5rhYg8IyI1jt/6HM/zqRTLdY6I7HJc/2uO3842r7dORM52O34wkBTWqeb1Yq5Xk3T9uMpEEq4fVz2aJBliqj/TiVTrqYcMg9YWp7B8D7itlOC6+5NJkrNERB4WkTUislpEjk7n5+q4XkS9jPRcB1mOqP0HETlORPZJf3tzWTJkMa8V1Bdx+d3zHQ6yHIc67vcdEWkWke+E7JO05yIDaO9SocvR9EZEvisiSkSGeRx/nRj90FUi8jmX328RkdahksPUs/8TkbVmvbJkiOSYKyJvmfr1koiMS0QOEblcRLY5dPXTHse71ksyBG29Rxm4Xoy6foWIPCoiJeb2cvO+W0Xk1hjOHfQ+JL7x0aDLFen9iEc7GvKu3kiVTCJykoi8aT6TN0XkBMcxz5syWcf8JYVy1YpIh2P7bY5jDjflXS9G3SJe599fGWjZHyQZwtpvSd0YybXNTub9e9QFKbf3xYxSSv+Zf0AG8AFQB2QDy4FJSbzescBMYJVj2y+AH5qffwhcZ37+NPAvQICjgNcGUY4qYKb5uRBYC0xKtSzm+QrMz1nAa+b5HwQ+b26/Dfim+flbwG3m588DDwziM7kY+AvwhPk95TIM4P2MAI4A/g/4XrTzRLn2KcCzju+bgGFJkM313bvI4/q8zWsuB3KAsaacs1Io1/FAnvn5m049AFqH8HmdA9zqsr0M2GD+LzU/lyZBd1Nap5rXjLleTdL143rHSbh+XPVokmSIqf5Ml7+h0NPB0B082uJUle943jWx190fABlJkPMe4Gvm52ygJJ2fa6x66fVcU6WbIfscZ+lBsv8I6Yu4/J60PnOU97UDqEnVcyHB9i5VuhxJb4AxwL+BzW7vEvgM8DSQCeQDbwBFjt9nAffh6GOlWg7gXOBewGd+HzFEcqwFJpqfvwXcnYgcwOU4+poR9Ny1XmII2nqPMnAykGl+vo7+uj0fOAb4Bi5945DzRnsf0cZHgy6X1/vBox11eVfrgTNSJNNhwEjz8xRgm+O35zHHaEPwrGqd1wn57XWM9kIw2o9PJVt/U/3HAMr+IMoQVFbMbSkbpzmuabfZybx/D/1Oub0v1j/tORzMbGC9UmqDUqobuB9YkKyLKaVeAPaEbF6AMYjB/H+aY/u9yuBVoEREqgZJju1KqbfMzy3AamBUqmUxz2d5AGSZfwo4AXjYQw5LvoeBuYMxyyciozE6YXeY3yXVMjiJ9/0opRqUUm8APTGeJxJfAP6aAtm83n0oXs97AXC/UqpLKbUReN88R0rkUko9p5RqN7++Cox2kX0onpcXnwSeVkrtUUo1YQw45sVxfKyktE6FuOvVZFw/3vp0sK8fbz06qMRZf6YLKddTNwaxLU5J+R6ktjK07l6P8T4GU85ijM75nQBKqW6l1F7S9Lk6iEUvk94HgYT7D0NJ0vrMEZgLfKCU2pzk69gMoL1LiS5H0ZtfAj/Au+8yCXhBKdWrlGoDVlgyikgGcL15/JDJgeEMcIVSKmCeu2GI5FBAkfm5GPhoAHJEw7VeGqq23q0MKKWeUkr1ml/tPrlSqk0p9RLQGcOpo72PaOOjZMnlhlc7Gvqu7iSkfU2WTEqpt5VSlh6+C+SKSI7Hvql8Vq6Y7UORUupVpZTCmPQ5bTCvkQ6kcVuesnGag5S02XG200PRdwlCG4eDGQV86Pi+ldQXmAql1Hbz8w6gwvycEtnEWJJ4GIa3WcplEWOJ6jtAA0Zn9QNgr6OBcF7LlsP8fR9QPghi/AqjQxAwv5cPgQyuxPh+4j2P1z55GB3PRxybFfCUuURo8WDKFvrulVJusnk9b0+dTJFcTs7DmPWz8IuxxOxVETnNcd5UyXWGuTTlYREZY25LVV2XDnUqDKCsDITBKq8JXDeeenSw+RWx15/pQrroqc0A2+JU3c+vGHhbmQpZxwK7gLvECIFxh4jkk77P1SKW66W0DwJR+w9HixHS5l8iMjmJYnj2RUyGokx/Hm9jUaqeC8TW1qT8+Tj1RkQWYHgSLo9wyHJgnojkibGs/3gMb06A84HHHfc5VHIcAnzO7OP9S0Tqh0iOrwFPishW4Czg2kTkMDedb/YZ/+ixtNtLd9K1rf8qwX3yqER7H/GOjwZLLhO39xNPm1WZIpmcnAG8pZTqcmy7y1y+f2kME5qDLddYsy/wXxGZY24bhfF8LNJFf5NGAmV/sHArK0MxTgtts1N1/zDE9r5IaONwGmPOXMXjDTggRKQAo6H7jlKqeShkUUr1KaVmYMwQzgYmJPuaTkRkPtCglHozldeNhcF6P5HOE8IpwP+UUs7ZrmOUUjOBTwHfFpFjB0u20HcvIlNiuZ9IpFouEfkyxlLH6x2ba5RSs4AvAr8SkUNSKNc/gFql1DQMI+E9LvscVKSqLhvK+nSo6tF0rj/3J9KhLY7GfvauMzGW9P1OKXUY0IaxjM8mXZ5ruhOl//AWRns3Hfg18FgSRXHtiwwVYsRWPRV4yOXnVD6XINJFr516A/QCPwYixl5WSj0FPAm8jDGAfwXoE5GRwCKMZzlkcpg/5wCdZh/vD8Afh0iOi4BPK6VGA3cBN8Urh1mef4dh8J4BbAdujOU86YqI/ATj+f45jmPyiP4+Yh4fDZZcJkl7P8mSyZwMuw74f47NX1JKTQXmmH9npVCu7UC12Re4GPiLiBS5nuEAZojLfsSykop2y6XNHrK6L13aaQttHA5mG/2zsGAMrLelWIadYrqPm/+tJUpJlU1EsjAqiT8rpf42lLIAKGPJ53PA0Rgu9Zku17LlMH8vBhoHeOmPA6eKyCaMpVInADenWIYw4nw/8Z7HizAvGKXUNvN/A/AohlFyUGRzXGMvxrt3W+Lo9bzddHJHCuVCRE4EfgKc6pwddzyzDZhxtlIll1Kq0SHLHcDh5udU1XXpUKfCAJ5vIgx2mUiUGOvRwSTe+jNdSBc9Hay2OBX3M1htZSpk3QpsdayueBjDWJyOz9VJLNdLSR/EPH/E/oNSqlmZIW2UUk8CWeKRWGuguPVFQnZJ9bv6FIZn3M7QH1L5XExiaWtS9nxc9OYQDG/+5Wb9MRp4S0TCPBqVUv+nlJqhlDoJIwbjWgxPt3HAevP4PBFZPwRygFG3WGXhUWBaquUQkeHAdEf99gDwsQTkQCm105xcDmAYu91C/HjpTiNp1NaLyDnAfAxDZDyGl1jeR0zjo0GWK9L7iafN2pEimazQU48CX1FKfeA4xnpWLRg5C1L2rJQReqPR/Pwmxsq68RjPyhkSMB37qoPCAMr+oOBRVlI9Rgpqs1N5/yZDZmOLhjYOB/MGUC9GttVsjMr/8RTL8Dhwtvn5bODvju1fEYOjgH0qgeVUboiIYMQhWq2Ucs42p1QWERku/dlIc4GTMGLhPAcs9JDDkm8hRmKAAc28KKV+pJQarZSqxXj/zyqlvpRKGUJJ4P3Eex63fYuBTzjPKSL5IlJofcZIFrBqkGRze/drXHb1et6PA58XI3P7WKAeY5Y6JXKJyGHA7zEMww2O7aVixtgyB4Mfx/AgTpVczjhFp2KUJzCSbJxsyleK8S7/HemaCZIOdSrE+XwHwmCV1wFcP956dNBIoP5MF9JCTwexLU56+R7EttKt7n59kGXdAXwoIoeam+YC75GGzzWEWPQy6X0QiK3/ICKV5n6IyGyMMUYyJsu9+iJOktZn9sAz/miqnouDWNqalOiym94opVYqpUYopWrN+mMrRoKkHSHHZohIufl5Gobh9Sml1D+VUpWO49uVUuNSLYf582MY4R3A6DOvJQJJkqMJKBaR8eauVpsflxzmdmef8XTCyxV41EtmvZMWbb2IzMMIeXSq6s8HEhPR3kec46NBk8s83uv9eLWjbu/qP6mQyeyH/hMj6db/HPtnmuMhy0g5nxQ+K7OPnGF+rsN4VhvM9qFZRI4yy8dXSL++6oAZYNkfjOt7lZWUjdNMgtrsVN2/g5Tb+2JGpTgDXrr/YWQJXIsxk/STJF/rrxiu6z0Yjc95GDGbngHWYVTgZea+AvzGlGsljiyfgyDHMRju7CuAd8y/T6daFoyOztumHKuAy8ztdRiN3HoM9/8cc7vf/L7e/L1ukN/PcfRnYB8SGRJ8P5WmPjUDe83PRV7nMY/5BvANxzXPwUhu4JSjDiPm2XKM5AI/GUTZXN+9ecwVGJ2DiM/blOcDjGR0302xXP8Bdjqu9bi5/WMYZWS5+f+aFMt1jfmulmN02ic49vuq+RzXA+cmsZ5LWZ1qXi/mejVJ14+rTCTh+nHVo0l8DscRpf5Mp79U6+lg6A4R2uJUle9Y3zWx191JyQ6OsVRwmflsHwNK0/25euklMbaJKdJNu++AEQfWam9eBT6WJFnC+iLmdqcsSeszu8iTj2HsLXZsS8lzIb5xxCzgjlTqspfehOyzCTNzvVNGU7ffM/9eBWZ4XKN1qOQASjAMYCsxwjxMHyI5Tqe/r/k8UeoBLzmA+8zzrMAwUlSZ+48EnnQc79peMgRtPe5lYD1G3E7r3m4Leb57gFZz/0nm9jtwqSec78P8fg6xjY8GXS6v92P+5tqOhryr5amSCfgpRgindxx/IzDqyzfN/d/FWHF0fwrlOsO87jsYIX9OcZx3Fka/+QPgVkCSrb+p/iPOsp+E63u136kcp7m12Um7f9LE3hfrn5iCaDQajUaj0Wg0Go1Go9FoNBqN5iBCh5XQaDQajUaj0Wg0Go1Go9FoNJqDEG0c1mg0Go1Go9FoNBqNRqPRaDSagxBtHNZoNBqNRqPRaDQajUaj0Wg0moMQbRzWaDQajUaj0Wg0Go1Go9FoNJqDEG0c1mg0Go1Go9FoNBqNRqPRaDSagxBtHNa4IiJKRG50fP+eiFw+hCJpUoSIjBGRjSJSZn4vNb/Xmt+XisheEXkiwjnOEZGRKRI5JkRkhoh82vH9VBH5YRKuc7mIfC/KPqeJyKTBvrYmNiLpuKknr4jIuyKyQkQ+53GO50VkVmolPziJ8r5qROQtEXnHfGffiOF8x1n1V7R6ILTeSCXm/X1xIMeYdfGtgy9dahGR74hInsdvz4vIFhERx7bHRKTV/FwrIh2mjrwnIveKSIX5/R0R2SEi2xzfs2OQJ6Y2LnQ/EbnDWfdHa2/NbUUisjXV7zGWtmyQrjPHLLvviEhusq83EELf31Bi1mMfG2o5DhRi6Pv2OeqIxz3OcbeILIxyHc86QUR+nIDctSKyKt7jNPsHMehltYg8JSKrzfat1uUcUfUyQdleNv/H3Vcxjzsg+ifpgBi8JCKfcmxbJCJLQ/ZrTb10iSEis0TkliSef4JZn78tIocM8FwjReRh8/OQjRsGA20c1njRBXxWRIYNtSCa1KKU+hD4HXCtuela4Hal1Cbz+/XAWVFOcw7gOnAWkYyBS5kQMwC7slZKPa6UutZ796RyGpAWA8yDkSg63g58RSk1GZgH/EpESoZCTo1BlPe1HThaKTUDOBL4YSxGO8e5o9UDM3DUGymmFoh3wJXIMSnFHMTE2//8DuBqHDbZC3zcPH8JUBXy+wemjkwFRgMnKqVmmNtuA35pfVdKdccgzzl4tHGR9lNKfU0p9Z7je7T2FuBK4IUYrpU2xPmOvwRcYz77jmTKNVBC398QcxwQl3FYRDKTI8r+TwxlscNRR5w6gEudg3edELdxWHNgE4Ne3gtcr5SaCMwGGlIom1X/1JLm/Y4DHaWUAr4B3CQifhEpAK4Gvj20kiWGiGQqpZYppZYk8TKnAQ8rpQ5TSn0wkBMppT5SSlkTMDMYwLhhqNtpbRzWeNEL3A5cFPqDOUP4rBhedc+ISHXqxdMkmV8CR4nId4BjgBusH5RSzwAtXgeas9OzgD9bnkAisklErhORt4BFIvJ1EXlDRJaLyCNieoSZs9u3iMjLIrLBmukWkSoRecE83yoRmWNu/52ILDO9jn7ukOEI8xzLReR1ESkGrgA+Z57jc84Zay+d9pLH5Z5/IiJrReQl4FDH9rD7FMPT51TgelOWQ8y/pSLypoi8KCIT4n5jmnhx1XGl1Fql1Drz80cYHe3hHudYZOrXWodO+kXkLhFZac5GH29uD/KQEJEnxPD8yjD1bJV5zEXm71F1QkRmi+Hl/Lapo4ea2/NE5EExvEgeFZHXxPRyFpGTzWPeEpGHzA7k/oDX++pWSnWZ++Tg0a8RkXkissasgz7r2O6sBxaZ72G5Wd9kE15veD3zc0Tkb+Y7Wycivwi59lvmeZ8xt+WLyB9N/XlbRBa4iH0tMMe89kVeuhXpGHPbSA+5ouqCGF6517noeYaIXG/WbytE5P+Z2wvMOvQtU84F5vZaEXlfRO4FVgFjROT7juN/7ngu/zSf1SrzmS/BMKY8JyLPub1f4H7g8+bnzwJ/c9tJKdUHvA6M8jhP6P2HlU9xb+MuM+9llYjcLgZu+z3vKItfEJGVwFeA0xy6/RMR+T/zGawEqoGnIsi4SUR+7njmE8ztQZ6/pmy15t8a877WisifReREEfmfqSOzHaefburIOhH5uuNcbu8u7B2HyDnX1NuVpu7niMjXgDOBK0Xkzy739hXzGstF5D7HdWJur0XkfhH5jOOcd4vIwgg6fJz5nh42n9OfRQyv9JD351p+IryPAukvvytE5IxI5wl5DkvEqM9XmPdTi2EIuMjUrTlRnsttIvIa8AvxaFskpP7z0rcDHM++b7xInHWCiFwL5Jrb/ywhHsHiWMEpIoeb72k5DuOPl05r9ntc9VIMj/NMpdTTAEqpVqVUe6QTudXD5navemu4iDwtxjjrDhHZLKbjmPR7oYb2VVz7u+bnc8Vod17HnNB1XOcRU3ffEBH7N01sKKVWAf8ALgEuA+51M3pKf//iVRGpMLdFaj8WOo61VmR5jctj7Vfe7Dh2trn9chG5T0T+B9wnwav8BtJ+zjDvdYUYY6JSMTx7vwN8U1z6lQ7dRoz+wt2O5+HWz6g17yVs3BBy3lox2t23zL+PmduPM7c/DrznVZeLRx97UFFK6T/9F/YHtAJFwCagGPgecLn52z+As83PXwUeG2p59V9SdOCTgAJOcvntOOCJCMc+D8xyfN8E/MDxvdzx+SrgAvPz3cBDGAaeScB6c/t3gZ+YnzOAQvNzmWPb88A0IBvYABxh/lYEZGJ4a9zquK793UunveQJudfDgZUYXm1FwHrgezHc50LHb88A9ebnI4Fnh/r9Hwx/kXTc/H02sBrweej4jebnTwP/cejqH83PE4AtgN9F/54wy9HhwNOO7SWx6oSl2+bnE4FHzM/fA35vfp6CMdk3CxiG4YGYb/52CXDZUL+Hgb4vDCPUCgyv72+7HOcHPgTqAQEexKy/QuqBlcCokPcQ+t68nvk5GPVOsXm9zaZcw81rjzX3s+qsq4EvW9cC1lrvxXGt43DUs166FeUYL7li0gW89Xwx8FPzcw6wDBiLUdcWmduHYdSHguFZFACOMn87GWMCWjDq1yeAY4EzgD84rl9s/t8EDPPQi+cxysgKjLbgKfN6rebvtcAqhy48B0xzHH85Zp3tcm6v8vk8wW1cmePzfcApHvs9j1EWR5rvb7j5zN7B1G3z/ynmc9kC/IIQPQyRcRP9bcu3gDvc7gvDYFtr/vVieFH7gDeBP5rvYgH97d/lwHIg13yXH5pye727oHfsUQbHm9/vBb5jfr4bR3voOGYyRrkYFlJ24mqvgdOBe8zP2aYcuXjr8HHAPgwPcx/wCnBMyPvzLD8R3sd1wK8c91ca6Twhz+IjICdEB0Pfb6Tn8gSQYX53bVtwqf8Oxj+825leU0deBU7zONbWZeKsE8zPrY7ttZj1lvndOQ5bARxrfr6e/vrNVaeH+pnqv+ToJYbn4xMYk6Fvm7qQ4XLs3cBCItfDXvXWrcCPzM/zTBmsOtlqY48jvN/h1t+tor/dywb+R3//6y/017PVwOqhfub74x+QD7xv1uc5Lr8rR130C0d9Ean9cI5XrXceNi4nvn7lH8zPxzrqr8sx+iO5oXrFwNrPFcAnzM9XWOchct/PWRcvBO52PA+3fkat4z6C9D/kvHmY/XaMMckyx7220T9WiKuPPZg6pJcXaTxRSjWL4QGyBHAu9Tuafs+r+zAqF82Bx6cwlmxPAZ4ehPM94Pg8RUSuwjCKFAD/dvz2mFIqgDFzVmFuewP4o4hkmb+/Y24/U0QWY1SWVRgVtQK2K6XeAEOPAaQ/HKUbkXTaTR4nc4BHlTlbL8Gx6CLdJ+b+BRhLQx9yyJgTSVjNoOGp4yJShaELZ5vv3w3LO/FNjI4BGF4dvwZQSq0Rkc3A+AgybADqROTXwD+Bp+LQiWLgHhGpx9D7LIcMN5syrBKRFeb2ozDKyP/M82ZjGD72F1zflzKWXU4TI5zEYyLysFJqp+O4CcBGZXqEi8ifMDpeofwPuFtEHsTD8xTvZw7wjFJqn3mN94AajA7sC0qpjaase8x9TwZOlX7PTj/mgCjC/Xvp1ooIx3jJVULsuuCm5ydjPHPLo6QYo6O7FbhaRI7FMBSOAqx6c7NS6lXH8SdjDGjBqB/rgReBG0XkOoxBwYtR7s2iD3gJw3s4Vym1KaTOP0RE3sHoXP9TKRXtmVmElU+P/Y4XkR9gdPzLgHcxBlteHAE8r5TaBSAiuzAGBlOAbozB9LcxBj5lMcjpfEefjbSjyUal1Erz2u9i6IgSw1O51rHf35UR6qHD9K6ZjaGHbu9uC8Hv2Mmh5jXXmt/vMe/vVxFkPAF4SCm1G4LKTrzt9b+Am8XwkJuHUR47RMRLh7uB15VSW83n8475TF5yXCdaXer2Pk6k37sdpVSTiMyPch6LFRjepo8Bj7n8Hu25PKSU6ovStsRS/x0MePULapRS20SkDnhWRFaqyEuR460TYkKMsDklSinLu/s+U2bwrpc3DvS6miHHTS8zMcYgh2HUvw9gGKbu9DhHtHrYrd46BmOCDaXUUhFpGsA9HElwu/cA/f3jE4FJjnqpSEQKlFL7TYzcdEAp1WY+11bVv6rOidW/AOM9n2R+jte2EzYuF5FPEHu/8q+mvC+IkVehxNz+uHIPL5VQ+ynGyuESpdR/zU33YBh3B0I0u0AksoBbRWQGRr/VOT583RorEH8fe0dCd+KCNg5rovEr4C3griGWQ5NCzErrJIwB0Esicr9SavsAT9vm+Hw3hufFchE5B2PGzMLZmAnYjcexwGcwBi83YRgRvofhIdxkLvnwD1BGN8LkiYO78b5PCx+wVxmxLzUpIpKOi0gRhiHoJx6GDgtLN/qI3p72EhzywA92B2c6hlfINzCWWH+H2HTiSuA5pdTpYiwzfj7K/oLhBfmFKPulHbHUSUqpj8RYhjsHeDjeayilviEiR2LUM2+KyOEuu0V65s66IppOCHCGUur9eOVMADe54tEFNz0XDC+joAkvs54bDhyulOoRkU3018vONkAw4sz+PvRiIjITw0v5KhF5Ril1RQwyghFa4lEMb5BQPlBKzRBjOez/RORUpZRrUiknHuXzqyHy+oHfYnj/fSjG0u+Y2yJTtydhDJYuAnpNQ+3RGAOEXAwPsWwRaVVKuSVQdHtHrnVOyP5gDDC6HJ+deqtCrqPweHdmeWhjaHHrP3SKyPMY7/BzGHpi/e6mw8cRvSxHKz+xtg2xlsPPYHhYnYIRdmRqlP1Dsd6LZ3/Drf5TSjXGeZ39mkjtjFJqm/l/g6lPhwGuxuGB1gkmkcqv5y3gotOa/ZsIerkVeEcptcHc7zFzHy/jcDTi6dNGIhHd9WGsOukcwHU1BgHzz40eZbqdEufYRYw8AtngOS5vIvZ+pVvfAuLrQyRzTOOUL1R/B2IXuAjYCUzHeK5OfQ/tI8fbxx4UdMxhTURMT40HgfMcm1+mf/bmSxhGOs0BghjTb7/DWGq0BWOZUrxx11owlph4UQhsN2ccvxSDTDXATqXUH4A7gJkYy7vbgH3mzJ3lOfE+UCUiR5jHFooR3D2STAPR6Rcw4kXmikghxuDNwus+bVlMz+aNIrLIlFdMY4QmSUTScTHiRT2KEasrbgMjhu58yTzXeAxv0PcxluzNEBGfiIzB8MDDNFb5lFKPAD8FZsahE8XANvPzOY7t/8MwYlkx6SxDwqvAx0VknPlbviljWhPlfY0WkVzzcymGl0uowXUNUCv92YhdO5IicohS6jWl1GXALozwC6H1htcz9+JV4FgRGWtew/IC/TdwgXlviMhhLseGXttLtyIdE0mugejCvzFitWVZ8ohIPsbzaTA7rcdjeCl7Hf9V6Y/TOkpERojh/d2ulPoTxnueGcd9vQhcg+mR4obphfpD4Eex3KRb+XSRx+qY7zbvxxmb3kvu14FPmOf/HcZg4QmMe7YGX18Cvokx0fE9jDrJzTDsxSZLXtPgPjaOYy0WiBHruhxjcvMNPN5dlPO8j1EGx5nfzwL+G2F/gGcx4rqXm9exyk4i7fUDwLkYE0dW9nYvHY6FRMrP0wTHhy2N5TzmgHyMUuo5jGWzxRje2qG6FfW5RGpbPOq/g4Yo7Uyp9MdmHYYRKzVSYsJE6gSAHksfMeqEESJSbl57PoBSai+wV0SOMfdz9i0HotOaNCTKmOwNoERErLwYJxBZLxOph539yZMxVkOFEqrTm3Dp7wKvYbR75aaOLnIc8xRwgfXFNIhrUodX+7EJI7wWGPlyrLrFbVweT7v4OXOfY4B91uq2CCTUfprnbRIzJjKx6TzAThGZaLa/p8ewv5NIdXwxxurmgClLhsd+A+1jJ4w2Dmti4UaMuCYWFwDnirFU+SzgwiGRSpMsvg5sUWaCAwzvh4liLBdBRF7EWJIxV0S2isgnXc5xN3CbmAk3XH6/FKOT8D8Mw000jgOWi8jbGA3KzUqp5RjLWtdgxKr6HxgJqsx9fi1Gso6n6Y8zOUlcAsQzAJ1WSr2FMfBcjrF89Y0Y7vN+4PtiJIU4BKMhPs+U912MuI+a5BFJx8/E8NA6x9SVd+LspP4W8ImxPPsB4Bxzadf/MJZ2vgfcgrEiA4wlQc+LsXT5T/QbrWLRiV8A15jlwjn7/1tguBghBK4yj99nLuU7B/irqeuvYIRcSHciva+JwGvmc/ovcIO1XN7C9ERZDPxTjIR0Xtm8rxcjwcMqjI7ycsLrDa9n7or5zBcDfzNltMLrXInRyV4hxrL+K10OXwH0iZE45CK8dSvSMZHkOofEdeEODF1+y3xev8d4Hn8GZkl/ojXX+l0p9RRGvf2Kue/DGJ3pqcDrZnn4GYb+ghHjdql4J6RDGdxghSGIwGNAnmOwEAmv8nk3ZhuH4UXyB4yYvv8muA2w93O2habX1w8xYg1PwvB++Tv97/gTMcgWjUeAMlO/zseI3xsvKzDKwKvAlcrIyO317jwxy+C5GOEMVmJ4Nd0W5Zh3gf8D/muWnZvMnxJpr58CPoERM7vb3Oalw1FJsPxcBZSKmfQNOD7G82QAfzKf29vALaaB8B/A6aZuzSH25+LVtrjVfwcT0dqZZeYzew64VinlaYQz309cdYLJ7Rhtwp+VUj0Y8TFfx+jHOuvSc4HfmPWP03MtYZ3WpC2eeqmMBKvfA54x6wfB0DtXEqmHgZ8DJ5v6tAhj+XpoUvLQfodrf9ds9y7HqOf+R3AYrSUYfYcVZt/1G1Hk0gwuXu3HHzAM+ssxQk9Y3q3HET4uj6dd7DSPvY1gB0QvEm0/Ac7GaN9WADMw6tVo/BBjwv5ljHAu8RDJ3vBb4GzzHibg7Sk9oD72QJB+z3KNRqPRaDT7OyKSAWSZy6kPAf4DHOowimg0Go1Go9FoNJ6I4bXep5TqFSPU0e90GDzNQBAjLM/3lFLLhloWTTh6NlGj0Wg0mgOLPOA5czmSAN/ShmGNRqPRaDQaTRxUAw+ay+u7MTyZNRrNAYr2HNZoNBqNRqPRaDQajUaj0Wg0moMQHXNYo9FoNBqNRqPRaDQajUaj0WgOQrRxWKPRaDQajUaj0Wg0Go1Go9FoDkK0cVij0Wg0Go1Go9FoNBqNRqPRaA5CtHFYo9FoNBqNRqPRaDQajUaj0WgOQrRxWKPRaDQajUaj0Wg0Go1Go9FoDkK0cVij0Wg0Go1Go9FoNBqNRqPRaA5C/j9U/1XlOECINgAAAABJRU5ErkJggg==\n", "text/plain": [ "<Figure size 1440x1440 with 72 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "X=data.drop('Y house price of unit area', axis=1)\n", "Y=data['X4 number of convenience stores']\n", "sn.pairplot(data)" ] }, { "cell_type": "code", "execution_count": 13, "id": "21e9f3f7", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:21:58.162343Z", "iopub.status.busy": "2022-10-27T19:21:58.161324Z", "iopub.status.idle": "2022-10-27T19:21:58.167168Z", "shell.execute_reply": "2022-10-27T19:21:58.166520Z" }, "papermill": { "duration": 0.03499, "end_time": "2022-10-27T19:21:58.169487", "exception": false, "start_time": "2022-10-27T19:21:58.134497", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "(414, 7)" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "X.shape" ] }, { "cell_type": "markdown", "id": "1aede951", "metadata": { "papermill": { "duration": 0.026958, "end_time": "2022-10-27T19:21:58.222859", "exception": false, "start_time": "2022-10-27T19:21:58.195901", "status": "completed" }, "tags": [] }, "source": [ "# Model Implementation" ] }, { "cell_type": "code", "execution_count": 14, "id": "f1d6d255", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:21:58.277951Z", "iopub.status.busy": "2022-10-27T19:21:58.277337Z", "iopub.status.idle": "2022-10-27T19:21:58.304865Z", "shell.execute_reply": "2022-10-27T19:21:58.303141Z" }, "papermill": { "duration": 0.057372, "end_time": "2022-10-27T19:21:58.306847", "exception": false, "start_time": "2022-10-27T19:21:58.249475", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "LinearRegression()" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size=0.3, random_state=100)\n", "model = LinearRegression()\n", "model.fit(X_train, Y_train)" ] }, { "cell_type": "markdown", "id": "db8a7d45", "metadata": { "papermill": { "duration": 0.026387, "end_time": "2022-10-27T19:21:58.360283", "exception": false, "start_time": "2022-10-27T19:21:58.333896", "status": "completed" }, "tags": [] }, "source": [ "# Model Evaluation" ] }, { "cell_type": "code", "execution_count": 15, "id": "3de42ec3", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:21:58.416357Z", "iopub.status.busy": "2022-10-27T19:21:58.415928Z", "iopub.status.idle": "2022-10-27T19:21:58.425619Z", "shell.execute_reply": "2022-10-27T19:21:58.424083Z" }, "papermill": { "duration": 0.040586, "end_time": "2022-10-27T19:21:58.427717", "exception": false, "start_time": "2022-10-27T19:21:58.387131", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "Y_pred = model.predict(X_test)\n", "MAE = metrics.mean_absolute_error(Y_test, Y_pred)\n", "MSE = metrics.mean_squared_error(Y_test, Y_pred)\n", "RMSE = np.sqrt(MSE)" ] }, { "cell_type": "code", "execution_count": 16, "id": "59f17311", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:21:58.482531Z", "iopub.status.busy": "2022-10-27T19:21:58.482147Z", "iopub.status.idle": "2022-10-27T19:21:58.487622Z", "shell.execute_reply": "2022-10-27T19:21:58.486097Z" }, "papermill": { "duration": 0.035455, "end_time": "2022-10-27T19:21:58.489794", "exception": false, "start_time": "2022-10-27T19:21:58.454339", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "MAE: 4.845271510302443e-15\n", "MSE: 3.2199864769923063e-29\n", "RMSE: 5.674492468047082e-15\n" ] } ], "source": [ "print(\"MAE: \", MAE)\n", "print(\"MSE: \", MSE)\n", "print(\"RMSE: \", RMSE)" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.12" }, "papermill": { "default_parameters": {}, "duration": 46.495716, "end_time": "2022-10-27T19:22:00.042280", "environment_variables": {}, "exception": null, "input_path": "__notebook__.ipynb", "output_path": "__notebook__.ipynb", "parameters": {}, "start_time": "2022-10-27T19:21:13.546564", "version": "2.3.4" } }, "nbformat": 4, "nbformat_minor": 5 }	0109/325/109325340.ipynb	s3://data-agents/kaggle-outputs/sharded/011_00109.jsonl.gz
{ "cells": [ { "cell_type": "markdown", "id": "9d131cf3", "metadata": { "papermill": { "duration": 0.008664, "end_time": "2022-10-27T19:23:56.168587", "exception": false, "start_time": "2022-10-27T19:23:56.159923", "status": "completed" }, "tags": [] }, "source": [ "Coursework assignment two - rob \n", "\n", "In this assignment the aim is to create artificial data in a time series, process it so it can be analysed by different machine learning models.\n" ] }, { "cell_type": "code", "execution_count": 1, "id": "d874aeac", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:23:56.186112Z", "iopub.status.busy": "2022-10-27T19:23:56.185611Z", "iopub.status.idle": "2022-10-27T19:23:57.782767Z", "shell.execute_reply": "2022-10-27T19:23:57.781500Z" }, "papermill": { "duration": 1.609075, "end_time": "2022-10-27T19:23:57.785535", "exception": false, "start_time": "2022-10-27T19:23:56.176460", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "# imports here\n", "\n", "import datetime\n", "import pandas as pd\n", "import numpy as np\n", "import matplotlib.pylab as plt\n", "import random\n", "from sklearn.svm import SVR\n", "from sklearn.preprocessing import MinMaxScaler\n", "from matplotlib.pyplot import figure\n", "\n", "import xgboost as xgb\n", "from xgboost import plot_importance, plot_tree\n", "\n", "from statsmodels.graphics.tsaplots import plot_pacf,plot_acf\n", "from statsmodels.tsa.arima.model import ARIMA\n", "# ARMA model has been deprecated and removed so have to use ARIMA framework\n", "# from statsmodels.tsa.arima_model import ARMA\n", "\n" ] }, { "cell_type": "markdown", "id": "5f678e9d", "metadata": { "papermill": { "duration": 0.007661, "end_time": "2022-10-27T19:23:57.801128", "exception": false, "start_time": "2022-10-27T19:23:57.793467", "status": "completed" }, "tags": [] }, "source": [ "libraries" ] }, { "cell_type": "code", "execution_count": 2, "id": "75d30c1f", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:23:57.819897Z", "iopub.status.busy": "2022-10-27T19:23:57.818905Z", "iopub.status.idle": "2022-10-27T19:23:58.357462Z", "shell.execute_reply": "2022-10-27T19:23:58.356330Z" }, "papermill": { "duration": 0.551353, "end_time": "2022-10-27T19:23:58.360441", "exception": false, "start_time": "2022-10-27T19:23:57.809088", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "<function matplotlib.pyplot.show(close=None, block=None)>" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" }, { "data": { "text/plain": [ "<Figure size 1152x432 with 0 Axes>" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# create data frame\n", "\n", "# this is a frame containing entries for every day this year\n", "\n", "df = pd.DataFrame(columns=['index','date', 'values'])\n", "\n", "# remember American formatting of dates or you'll get an error\n", "df.date = pd.date_range(start='2022-01-01', end='2022-12-31', freq='D')\n", "df.values=(df.index+ random.randint(1,10))\n", "\n", "\n", "#lets generate some data that slowly increases for each day\n", "\n", "#first we get the length of the array\n", "numdays=len(df. index)\n", "\n", "#fill each day with a random number but add in an increasing value to create\n", "# upward trend + a modulo of the loop to add in more variety\n", "\n", "\n", "base = float(0.9)\n", "l = []\n", "for i in range(0,numdays):\n", " a = base + (float(i)/100)+(i4)\n", " a= (i % 14)+(np.random.randint(1,20))+ (i/8) \n", " l.append(a)\n", "\n", "#then copy the array into the values column\n", "df.values=pd.Series(l)\n", "\n", "#just add an index counter as well\n", "df['index'] = np.arange(len(df))\n", "\n", "df.head(20)\n", "#figure(figsize=(16, 6), dpi=100)\n", "fig = plt.figure(figsize=(16, 6))\n", "df.plot(x=\"date\",y=\"values\", color=\"blue\")\n", "plt.show" ] }, { "cell_type": "markdown", "id": "ba92ff35", "metadata": { "papermill": { "duration": 0.008038, "end_time": "2022-10-27T19:23:58.379228", "exception": false, "start_time": "2022-10-27T19:23:58.371190", "status": "completed" }, "tags": [] }, "source": [ "write up here" ] }, { "cell_type": "code", "execution_count": 3, "id": "d84a2ebe", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:23:58.399793Z", "iopub.status.busy": "2022-10-27T19:23:58.398905Z", "iopub.status.idle": "2022-10-27T19:23:58.439165Z", "shell.execute_reply": "2022-10-27T19:23:58.438069Z" }, "papermill": { "duration": 0.0549, "end_time": "2022-10-27T19:23:58.442385", "exception": false, "start_time": "2022-10-27T19:23:58.387485", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Observations of Dickey-fuller test\n", "Test Statistic -0.212272\n", "p-value 0.937043\n", "#lags used 13.000000\n", "number of observations used 351.000000\n", "critical value (1%) -3.449119\n", "critical value (5%) -2.869810\n", "critical value (10%) -2.571176\n", "dtype: float64\n" ] } ], "source": [ "from statsmodels.tsa.stattools import adfuller\n", "print(\"Observations of Dickey-fuller test\")\n", "dftest = adfuller(df['values'],autolag='AIC')\n", "dfoutput=pd.Series(dftest[0:4],index=['Test Statistic','p-value','#lags used','number of observations used'])\n", "for key,value in dftest[4].items():\n", " dfoutput['critical value (%s)'%key]= value\n", "print(dfoutput)\n", "\n", "#df.head(20)" ] }, { "cell_type": "markdown", "id": "30f2867d", "metadata": { "papermill": { "duration": 0.01016, "end_time": "2022-10-27T19:23:58.465384", "exception": false, "start_time": "2022-10-27T19:23:58.455224", "status": "completed" }, "tags": [] }, "source": [ "references on DF test:\n", "https://www.analyticsvidhya.com/blog/2021/04/how-to-check-stationarity-of-data-in-python/\n" ] }, { "cell_type": "code", "execution_count": 4, "id": "a5960ba9", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:23:58.484172Z", "iopub.status.busy": "2022-10-27T19:23:58.483755Z", "iopub.status.idle": "2022-10-27T19:23:58.752556Z", "shell.execute_reply": "2022-10-27T19:23:58.751670Z" }, "papermill": { "duration": 0.281132, "end_time": "2022-10-27T19:23:58.754856", "exception": false, "start_time": "2022-10-27T19:23:58.473724", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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slMO5tTLJcBPGj5l2BgD5RAgClqiZaV/troa0em1P1qmA/T6FEK1RnWYWxk0BFjYAqIaX8mwzgLnAw3QzAMBSEIKAJco67avd1ZDlWNvzwX/8YKapgI2mEDJVrj9VmgBEs+tnqutkqtWZ8oIpZiFlGQBAmxCCgAyyTPtqdzUk689LC3lZpwKmXcdUud4SRq5SUO1sFn8Fc80Bqo/LYUR1BgDQtQhBQAulBY9mqiFZKiXN/Lx6IS/rVMC065gq1z2iqBJgiuVIxTCshJ048BTLle80BQAA9ANCENBCacEjazVEUmqlpF6YWY7qS6OpgFmu6/due90kjFwz5VDFIFIxCGeDTeV7qFJAwAEA5AMhCGihtOCRtRoiqe6xtG5ty1V9yXqPqHrX9Xu3vXYKwigOOJUKTjGIA0+58rhMFQcAAEmEIKCl0oJH1mqIu9c9JtUPSNdeeG1PVF+4yeri1arkzCQqOkxVAwBgcQhBQAs1mi6WtRpS71ijMNML1ZesU+z6zex6nMQ6nNk1OQGVHAAAWokQBLRYlulijaohaceyhJluq75knWLXK6oBJ9lggIADAEDnEIKALtCoGlLvWNYwQ/WldcpxoKl+LybaR1dDDgEHAIDuQggCukRaNaTesWbCTK9UXzp1I1V3n1+xqfOY+3sCANB7CEFAj+uVMJPFct5ItVYntWolpxh0z80+wyjUvc9+RY8ffVgXrn+xrth89aJ+96zXAQCQB4QgAF2rUSvv9BvMntpJrZhoG90LndTCKNQ7v/Z6PXb4e5oJpjQyuFIXbXiJPnzV3amBJut1AADkBSEIQNdK6363/fztetWfv1rf3fddTZUnNbpipS553jZ99DV/rSBSX9z4895nv6LHDn9P00HlNZgOJvXY4e/p3me/oiu3vqZutafRdQAA5B0hCEDXumzTZRpbMaaJ8lz3u9HBlVo7eL7+9Duf171775v9oD9VntT3n9utLz/x933zQf/xow9rJpiat28mmNLjxx7RFZuvrlvtSbsuLTwBAJAXhCAAXSNy16HxoqZLoabKgTYOXaGfOf0yff/AboWa0ejgSr1ow0t02RlX6dOP3Jb6QV/q/XUxF65/sUYGV84GPUkaGVypC9f9bGq1J+26RlPlev01AwBgMQhBANquFESaLoWaLAWaKgWaLIY6OVOWJO05OJE40/Thq+7Wb33hDo2He7TjiqtmP5SnfdCX+mNdzBWbr9ZFG14yLwRetOElumLz1akh8IaL31n3urTwlFZd6pXXDACAxSAEAVhW5TDSZDHQRDHQVClU5K4Hnjq26OsLAwU9b8W/1vNW/GtdufXi2f1pAUFqvJ6mFxQGCplCYNp1aVPlJPX8awYAwGIQggC0TBBGCiNX6K4fPzeuiWKgmXI0dzyKUq5emrQP+lL6eppOrItJ+3lpx7KGwHrXpYWnRq8ZAAD9ghAEIBN317HJUjylLdREMVCxHGmyFEiSDk+Uln0M9T7oS+kf9ts9VS7t50nKNJZGIbCeRuEpbYohAAD9ghAEoKFiEGqyGM5OaxufCeRy/cuB8U4Pra60D/tZW083kqVltZR9ClpaCEy7pl54ahSQAADoF4QgALPcXdPlUFOlyg1Fw8j1wFNHT7nnjqv778GTdV1Mo+YA9YJOWrUndR2Oe9unoNULT1mrSwAA9JqWhCAzu0bSn0oqSPq4u9+64PhbJP0XSfviXX/m7h+Pj90o6ffi/e939ztbMSYA6crV9TuRa8/BcU2VQk2XQkVxvikGoaTevulolnUxWbunZW1ZXX3cLVPQslSXAADoNU2HIDMrSPqIpFdJ2ivpfjPb6e6PLTj1c+7+jgXXrpf0XknbJLmkB+JrF986CkBD1fU71Q5tE8VApWBu/c6h8eVfv9NNsraelupPXUur9qS1rJbUM1PQuIcQAKBftKIS9FJJe9z9CUkys7skXSdpYQiq5TWSvuzuR+NrvyzpGkmfbcG4gNyJItdUOdRUHHYmS72xfqfdsraeTgs6WVtWS+qJKWjcZDU7XhsA6D6tCEFbJD2T2N4r6fIa5/2Kmf28pMcl/ba7P1Pn2i21foiZ7ZC0Q5LOPvvsFgwb6G2lIKrcaLQUarocKoxc333yqHzB7LVeWL/TCVlbT9cLOllbVjc61i24yWq2MNMPN+0FgH7UrsYI/5+kz7p70cz+D0l3SrpqKU/g7rdLul2Stm3bxqc65Ia7a6YcqRxGilz64f6TmioF89bqlMMoPrdTo+wfWbun9XtTgbzfZDVrmOmHm/YCQD9qRQjaJ+msxPZWzTVAkCS5+5HE5scl/VHi2lcsuPYbLRgT0LPCyPXcyRlNxlPapkqVKs90udKo4PhUucMj7H9Zu6f1QkUnq7zfZDVrmMnDawMAvWigBc9xv6QLzOw8MxuSdL2knckTzGxTYvO1kn4YP94l6dVmts7M1kl6dbwP6HvurolioOdOzugnhyb00N7jOjlT1mQp0BOHJvXcyaLGZwKFEeWdblINOi8YuUFXbn1N31R6GqlWwQoalWQaHRybrYJVA1JSv91ktVElrJ48vDYA0IuargS5e2Bm71AlvBQk3eHuj5rZLZJ2u/tOSf/BzF4rKZB0VNJb4muPmtkfqBKkJOmWapMEoJ9Up7SNF8uaKYcK3fXdnx4V+Qa9op9uspplbU+jNuf1nrPRa0PTBADojJasCXL3eyTds2DfzYnH75b07jrX3iHpjlaMA+gWkVfuv/PUkUlNFANNFsPZik4pXr9DAEKv6YebrGZd25MWZho9Z73XhqYJANA57WqMAPQtd9dUKdT4TKDxmbJOzgSaKFbuv/Ps8ZkOjw5oj7T1UN1U7ci6tictzHxn767U56z32tA0AQA6hxAELJG7a7wYqBhECiPX7qeOKQgp6wC1LGe1I0u4atSoIO0564WZrM0PmhkLAKA5hCCggWoDg5MzgU5Ol2ebFRSDSrc2AhBQ33JVO7LevDVtbU/WwNZovVCW65gqBwDLqxXd4YC+M1MOVQojTZVC3f/kMT2y76SePjKl41NlurUBS7CYrmphFOo7e3fpkw/9sb6zd5fCKGx4LBmuXD4vXFUDxM3f3qGPP/Qh3fztHXrn116vMApTu9ylPWeatOfMel3WsQAAFodKECApilwnZ8o6NlXW8amSZsqRZuL78hB6gOwW01WtXsVDUt1jzdy8td7anqzT2rI2hki7jvsLAcDyIgQht4pBpdoThK77n6RdNbAcGrWITpsuJ9UPM83cvLXe2p6s09qk7DfKzToW1gsBQHMIQciVyWKgo5MlHZ8qa6IYzFZ7CEDA8mhUJUmt6LjXPXbDxe9MDVdZwkw33e+omZbcAIDGCEHoe2HkKoeRvvf0MRXLUaeHA+ROWpWkUcWj3rHluHlrN93vqJmW3FSJAKAxQhD60kw51OGJog5PlDRZqtyzhwAEdJ9GgSXt2HLcvDXrtLblkKUl9xWbr6ZKBACLQAhC33BJB0/O6NBEUSeng04PB8AiNAos/RBmWi2tesYNWNNRJQNQRQhCT4si1/HpsqbLoYIw0k8OTTa+CEBXSQss/Rxmskqrnn36kdvoKlcHa6kAJBGC0HPcXSenAx2aKOrYVElBWFnzAwB5kFY9a6bDXb+jSgYgiRCEnpFscFAKaOcGIL/qVcgarbHql+lgWX4P7r0EIIkQhK42Uw51aLyowxPF2QYHBCAAqC2tStQv08Ea/R71AhL3XgKQRAhC13FJB07M6PBEUeMzNDgAgKWoVyXql+lgab9HWnc87r0EIIkQhK4QhJGOTpY0VQoVRJF+epgGBwDQSss5HSxrFaXV09okpQa9rPdeAtB/CEHomCCMdHSqpCMTJZ2YLstdCiIaHADAcmi2aUK9wJK1ipL1urTfo1HQy3LvJW5AC/QnQhDaqtrcoBy6HnjqmCKW9wBAWzTTNCEtsGSdZtfounrjafR7ZAl6acGKqXJAfyIEYdm5u05Ml3V4oqijk5V7+kgiAAFAGzXTNCEtsGStoqRdl7a2J+33aBSQ6km7rl/WUgGYjxCEZRO668nDkzoyWaSjGwB0gaxNE9ICS9YqStp1jcZT7/dIC0iNXpd619Fae3kwxRCdRghCS1VbWk8UA0Xu2n9iptNDAgA00OiDflpgyVpFSbvu04/cljl41AtIjdS7jhvQth5TDNENBjo9APS+UhBp/4lpPbz3hB58+rj2HptW5FR+AKBXVD/oJyU/6FcDS0Gjkkyjg2OzgaVaRblk7GZdMPIbuuXlt89+mE0LV2nXNRpPO6X97lLlA/139u7SJx/6Y31n7y6FUdj2MfaaZDh2+bxwDLQLlSBkkmxw8L2nj4nMAwC9q9FamkbTzLJWUepdl3Vtz3LIww1o240phugGhCAsyYnpsg6NF3V0sjTb4IAABAC9bTFrabJMM8saZrKu7VkuWddS5X3dS73fnymG6AaEIDQUueuZo1M6NFFUscx9fACgH2VdS9PoObOGmeUYT6s10+Gu36VVybqp0of8IgShpihyHZksaaoUKIhce49Nd3pIAIAe1AthJqtmOtx1m6xVq3rXNfr9u6nSh3wiBGGeqVKg504WdXiiqCB0BdzMBwCAmparw127ZV3blHZdo3U//RyO0RsIQZAklcNIj+w7ofGZoNNDAQCgJ6RN92u07qXVlZfFHq8la9Uq7bpm1v3kfS0V2oMQlGPFINSBEzManwnkcgIQAABLlKXDXaPKS70QsJjrslR0snZrS7vuhovfmWndDx330C6EoByaLAbaf2JahydKcpdcTHkDAKCV0qpE39m7K/UmsvVCQKOKTdaKTtaqVdp1WZti9NpaKvQuQlCOBJHr0WdP6OQ0FR8AAJZbvSpRWgVFUt0Q0Khi0+h4vTCTtWq1mPtLLXXdD/cQQrsQgvqcu+vwREmTxUChOwEIAIAOS6ugpIWARhWbtOONppllqVotR5e35VpLBSw00IonMbNrzOxHZrbHzG6qcfw/mtljZvaQmX3VzM5JHAvN7Pvx185WjAeV8HNwfEY/2HtCew5OKOSOpgAAdIVqBaWgUUmm0cGx2QpKNQQkVUNA2nWNnjc5zczl88KMNFe1ecHIDbPd26TGVat61y3Ha1MNcjd/e4c+/tCHdPO3d+idX3u9wihs6mcin5quBJlZQdJHJL1K0l5J95vZTnd/LHHag5K2ufuUmf1fkv5I0hvjY9Pufmmz48Ccg+Mz2ndsWjPc2BQAgK6TVnlJm2LWaJ1N2vGs08ya6fLW6temUVUK2eS1utaK6XAvlbTH3Z+QJDO7S9J1kmZDkLt/PXH+vZLe3IKfiwXKYaRiEOknBycbnwwAADqm3nqZxQSdtHU29Y5nDTON1v0shyxrqQhB2eS5G18rpsNtkfRMYntvvK+et0n6UmJ7xMx2m9m9Zva6eheZ2Y74vN2HDh1qasD9ZqIY6JF9JzRdDhUx7Q0AgJ7W6ilmUvo0s0Zj+fBVd+uSsZt1wchv6JaX396xD8hpUwWRTaNpkv2srY0RzOzNkrZJ+oXE7nPcfZ+ZPV/S18zsYXf/ycJr3f12SbdL0rZt2/ikr0rl5+mjUzo0XhTZBwAA1JO1ZXX12qV2eVsOjapSeZ3WtRj1Xps8V9daEYL2STorsb013jePmV0t6T2SfsHdi9X97r4v/v6EmX1D0mWSTglBmO/AiRk9c2xKQUj6AQAAjXVLmMkqLchlvQFtHqS9Nu1e89VNWhGC7pd0gZmdp0r4uV7SryZPMLPLJH1M0jXufjCxf52kKXcvmtkGSVeq0jQBdYSRa6Yc6qeHWfcDAADypV6QS7vJatoNaPMQhBq9Nu1e89Utmg5B7h6Y2Tsk7ZJUkHSHuz9qZrdI2u3uOyX9F0mrJP2lmUnS0+7+WkkvkvQxM4tUWZ9064KucohFkevpo1OaLHGfHwAAgKSsN6BNu4lsr8k65S1tmmS/vDa1tGRNkLvfI+meBftuTjyuGSfd/Z8kvbgVY+hnJ2fK+snBCVpeAwAA1JD1BrSNqkS9EgKamfJWr7rW753j2toYAUtTrf4cODlD4wMAAIA6Gk3rqhcC+mUa3XJMeUt7znoVtF5CCOpSYeT6wd7jVH8AAAAayHoD2k8/clvmaXTLJUv1qZkpb1mes15AvPtX/i7bL90BhKAuVAwiFYOQAAQAALBIWW5Am3UaXaO1RI2CTL3jWbvcZZ3ylibtOetVib7+1D/orRt+ZbH/ZB1FCOoi7q6fHJpQMQg7PRQAAIC+US8EZJ1GlxZWJDUMMvWOZ52etxxd3rJU0B47/JAkQhCWIIxcPz44rmOT5U4PBQAAIBeyTqNLCytS+jS6tGub6XKX9Wa4WV6belWiizb8L5l/XrsRgrpAOYz0owPjGp+h/TUAAEA7ZZlGlxpW3FOn0aVd28z0vOW4Ge5SK2i/eM6rW/Jz24EQ1GHFINS/7B/XVIkpcAAAAN2kXghotAYn7VjatVmn57VbWkDsFQOdHkCeTZdCPbLvJAEIAACgh1TDSkGjkkyjg2OzYSXtWKNrq+HikrGbdcHIb+iWl98+u5ao0fO2WzUgvmDkhtlKVC+hEtQhYeR69NkTKofcAAgAAKCXNKqEpB1rdG2W6XlYOkJQBwSRa7oUEoAAAAB6VNoanEbrc7Ku31mOdT95RQhqs2ePT2uqRAMEAAAAoFMIQW3i7nryyJQOnJjp9FAAAACAXCMEtQH3AAIAAAC6ByFomRWDUD86MK7JIh3gAAAAgG5ACFpGkbse2XdSpSDq9FAAAAAAxAhBy6TaAY4ABAAAAHQXQtAyOHBihg5wAAAAQJciBLWQu+upI1PaTwc4AAAAoGsNdHoA/aQYRAQgAAAAoMsRggAAAADkCiEIAAAAQK4QggAAAADkCiEIAAAAQK4QggAAAADkCiEIAAAAQK4QggAAAADkCiEIAAAAQK4QggAAAADkCiEIAAAAQK4QggAAAADkCiEIAAAAQK60JASZ2TVm9iMz22NmN9U4Pmxmn4uP32dm5yaOvTve/yMze00rxgMAAAAA9TQdgsysIOkjkrZLukjSm8zsogWnvU3SMXc/X9Jtkj4UX3uRpOslXSzpGkn/b/x8AAAAALAsWlEJeqmkPe7+hLuXJN0l6boF51wn6c748d2SXmlmFu+/y92L7v5TSXvi5wMAAACAZWHu3twTmL1e0jXu/vZ4+9clXe7u70ic80h8zt54+yeSLpf0Pkn3uvtn4v2fkPQld7877WeuPm+1/9x7f66pcbfCY8+elCRdtHmNJCly18RMIEl68siUJOnc01eecl3asWau5Vj7jnXbeDjGv1MvH+u28XCMf6dePtZt4+FYvv6dhlcUNDzYPS0HvvnWbz7g7ttqHeuZEGRmOyTtkKThLcM/d8X7r2hq3MshGYIAAACAPOmlEDTYguffJ+msxPbWeF+tc/aa2aCktZKOLPJaSZK73y7pdknatm2bf+Mt32jB0FtrphzqwaePd3oYAAAAQNttXTeqs9bXrnx1gr3V6h5rRVS7X9IFZnaemQ2p0uhg54Jzdkq6MX78eklf80oJaqek6+PucedJukDSd1swJgAAAACoqelKkLsHZvYOSbskFSTd4e6Pmtktkna7+05Jn5D052a2R9JRVYKS4vM+L+kxSYGk33T3sNkxAQAAAEA9rZgOJ3e/R9I9C/bdnHg8I+nf1bn2A5I+0IpxAAAAAEAj3bNyCQAAAADagBAEAAAAIFcIQQAAAAByhRAEAAAAIFcIQQAAAAByhRAEAAAAIFcIQQAAAAByhRAEAAAAIFcIQQAAAAByhRAEAAAAIFcIQQAAAAByhRDUQoMDpqFBXlIAAACgm/GJvYUGCwP62S1rNDZc6PRQAAAAANRBCGqx4cGCLt68VuvGVnR6KAAAAABqIAQtg8KA6Wc2rtaZa0c6PRQAAAAACxCClomZ6bwNYzp3w0qZdXo0AAAAAKoIQcts09pRXbhxtQoDJCEAAACgGxCC2mD92JAu2rxGQ4MEIQAAAKDTCEFtsmp4UBdvXquVQ3SOAwAAADqJENRGIysKunjzGp22ks5xAAAAQKcQgtpssDCgF565Ws9bM9zpoQAAAAC5RAjqADPTC85Ypa3rRjs9FAAAACB3CEEddNb6lTp3w8pODwMAAADIFUJQh21aO6oLNq7iXkIAAABAmxCCusCGVcN64ZncSwgAAABoB0JQlzht5ZBetGm1VhQIQgAAAMByIgR1kdUjK3Tx5rUaXsE/CwAAALBc+LTdZUaHCnrxlrU6fdVQp4cCAAAA9CVCUBdaURjQhRtX68KNq5geBwAAALQYIaiLnb5qWJecdRpVIQAAAKCFCEFdjqoQAAAA0FqDnR4AFuf0VcNaM7pCTx6e1OGJUqeHAwAAAPSspipBZrbezL5sZj+Ov6+rcc6lZvbPZvaomT1kZm9MHPuUmf3UzL4ff13azHj63YrCgC7YuFoXbVqj0aFCp4cDAAAA9KRmp8PdJOmr7n6BpK/G2wtNSbrB3S+WdI2kD5vZaYnj/8ndL42/vt/keHJh7coVumTrWp1z+koNMkUOAAAAWJJmQ9B1ku6MH98p6XULT3D3x939x/HjZyUdlHRGkz8398xMm08b1SVbT9MZq4c7PRwAAACgZzQbgja6+/748QFJG9NONrOXShqS9JPE7g/E0+RuM7O6n+bNbIeZ7Taz3YcOHWpy2P1jaHBA5z9vlS7eskarhlniBQAAADTSMASZ2VfM7JEaX9clz3N3l+Qpz7NJ0p9Lequ7R/Hud0t6oaR/JWm9pHfVu97db3f3be6+7YwzKCQttGZkhV68da0u3LhKY8OsFwIAAADqaVg6cPer6x0zs+fMbJO7749DzsE6562R9HeS3uPu9yaeu1pFKprZJyX9zpJGj1OcvmpYp68a1tHJkvYdm9ZEMej0kAAAAICu0ux0uJ2Sbowf3yjpCwtPMLMhSX8j6dPufveCY5vi76bKeqJHmhwPYuvHhvTirWv1wjNXa/UI0+QAAACAqmZD0K2SXmVmP5Z0dbwtM9tmZh+Pz3mDpJ+X9JYarbD/wswelvSwpA2S3t/keLDAurEh/eyWtXrRptVaO7qi08MBAAAAOs4qS3l6y7Zt23z37t2dHkZPmiwG2n9iWocnSurBf3oAAAB0qa3rRnXW+pWdHsYsM3vA3bfVOsY8qZwZGx7U+c9brbPWh3ruRFHPjc8oCElDAAAAyA9CUE4NDxZ09ukrtWXdqA6NF/XcyRlNlcJODwsAAABYdoSgnCsMmM5cO6Iz145ofKas504WdXSypDCiOgQAAID+RAjCrNUjK7R6ZIWCMNKRyZIOnizSYhsAAAB9hxCEUwwWBrRxzYg2rhnRZDHQwfGijkwUVWbtEAAAAPoAIQipxoYHdd7woM49faWOTZV1aLyoY1N0lgMAAEDvIgRhUcxM68eGtH5sSOUw0uGJog6NFzVZpJkCAAAAegshCEu2ojCgTWtHtWntqKZKgY5MlHRooqhiOer00AAAAICGCEFoysqhQa1cP6iz1q/U+ExZhydKOjpZVClgvhwAAAC6EyEILVPtLnfu6St1YrqswxNFHZ0s024bAAAAXYUQhJYzM522ckinrRxSGLmOTpZ0eKKoE9NlGioAAACg4whBWFaFAdMZq4d1xuphlYJIRyaLOjxe4v5DAAAA6BhCENpmaHCuocJMOYyny5XoMAcAAIC2IgShI0ZWFLR13UptXbdS06VQRyaLOjJR0lSJQAQAAIDlRQhCx40OFbR1aC4QHZ4o6vBEUTO03AYAAMAyIAShq4wOFXTW+pXzWm4fmSiqHNJRAQAAAK1BCELXSrbcPj5V1pFJWm4DAACgeYQgdD0z07qxIa0bm2u5fWSyqONTtNwGAADA0hGC0FOSLbfLYTR7D6KT07TcBgAAwOIQgtCzVhQGtHHNiDauGVExCHVkoqRD40U6zAEAACAVIQh9YXiwoM2njWrzaaOaLAazHeZKAfPlAAAAMB8hCH1nbHhQY8ODOnv9Sp2YLsc3ZaWhAgAAACoIQehbZqbTVg7ptJWVhgonpss6OlnS8akSLbcBAAByjBCEXCgMmNaPDWn92JDcXePFQMcmSzo2VdY0a4gAAAByhRCE3DEzrRlZoTUjK3TO6dJ0KdTx6ZKOT5V1crosZs0BAAD0N0IQcm90qKDRoVFtWjuqMHKdnC7r+HRZx6dKmilHnR4eAAAAWowQBCQUBuZuzCqNaaYc6sR0pUJ0cqZMtzkAAIA+QAgCUoysKGhkRUEb14xIqkydOzlT1onpssYJRQAAAD2JEAQsQWXq3PxQND5T1smZQOMzZabPAQAA9ABCENCEaih63prKdimIND5T1vhMoIlioMliQKMFAACALkMIAlpoaHBAp68a1umrhiVJ7q6pUqjJYiUUTRQDTZVCOcEIAACgYwhBwDIyM40ND2pseFDPi/dFkWuyFGiyGGqiWNZEMeReRQAAAG3UVAgys/WSPifpXElPSnqDux+rcV4o6eF482l3f228/zxJd0k6XdIDkn7d3UvNjAnodgMDptUjK7R6ZIWkytqiIIw0WQorlaJioMlSqJkyFSMAAIDl0Gwl6CZJX3X3W83spnj7XTXOm3b3S2vs/5Ck29z9LjP7H5LeJumjTY4J6DmDhQGtHR3Q2tEVs/vCyDVVCman01W/s8YIAACgOc2GoOskvSJ+fKekb6h2CDqFmZmkqyT9auL694kQBEiq3LNormJU4e6aKUeaLAWaKoaV76WAVt0AAABL0GwI2uju++PHByRtrHPeiJntlhRIutXd/1aVKXDH3T2Iz9kraUu9H2RmOyTtkKSzzz67yWEDvcnMZjvSadXc/lIQzVaN5r4znQ4AAKCWhiHIzL4i6cwah96T3HB3N7N6H7nOcfd9ZvZ8SV8zs4clnVjKQN39dkm3S9K2bdv4aAckDA0OaGhwSKetnNtX7UxXDUaTceUoCPmfDwAAyLeGIcjdr653zMyeM7NN7r7fzDZJOljnOfbF358ws29IukzSX0k6zcwG42rQVkn7MvwOAGpIdqaThmf3z5Tn1hhVW3aXAm7yCgAA8qPZ6XA7Jd0o6db4+xcWnmBm6yRNuXvRzDZIulLSH8WVo69Ler0qHeJqXg+gtUZWFDSyoqDTE/vKYaSpUqVV92Qp0HRcQQrpwgAAAPpQsyHoVkmfN7O3SXpK0hskycy2Sfo/3f3tkl4k6WNmFkkaUGVN0GPx9e+SdJeZvV/Sg5I+0eR4AGSwokZ3OqlSNZooBrM3e50qhUynAwAAPa+pEOTuRyS9ssb+3ZLeHj/+J0kvrnP9E5Je2swYACyfatVow6q56XTTs9PoKuuMpkqBygQjAADQQ5qtBAHImdnudAvWGc27n1EpULHMOiMAANCdCEEAmlatGK0fG5rdVwqi2Wl01Sl1VIwAAEA3IAQBWBbVtt3rEsGousao2oBhskhnOgAA0H6EIABtU60YJZXDSFPxPYyqHeqmy3SmAwAAy4cQBKCjVhQGtHblgNaunOtM5+4qBtHsjV6rwWimHBGOAABA0whBALqOmdVcZyRJxaAShopxKJoJQs0QkAAAwBIQggD0lOHBgoYHC9KCexpJlal1M+VQxSCaDUbFoLJdCiI5GQkAAIgQBKCPrCgMaEVhQKtrHKtOsat8hSqW5x6X4pBEIQkAgHwgBAHIheQUO+nUKpJUaetdCitT7UphNBuOivH+MkEJAIC+QAgCgFilrfeAVg3Xf2ssJQJRNSgVg0jlamgKIwXcDwkAgK5GCAKAJagGJQ3XPyeMXOUwml2LVA1L5TBSsRypFIYqBQQlAAA6hRAEAC1WGDAVBk69J1JSdY1SsppUSn4RlAAAWDaEIADogPlrlGqLIq+EpLiCNNsenI53AAA0hRAEAF1qYMA0Uq0ojZx6fLbjXTlSMTy1412RkAQAQE2EIADoUY063rlXKkmzQYlKEgAAkghBANC3zGzu5rJ1KkmlcP56pOLs9zBu5kBKAgD0H0IQAOTUvJBUR3Vd0sIby5bDSgc87p8EAOhFhCAAQF3z1iXVucmsNNcWvBqKqiGp8jV3LAhdIYkJANBhhCAAQNMW0xa8KopcQeQKokpACiNXEEaVfWFlf/VxGLnKURSfQ3gCALQGIQgA0FYDA6ahAdOQBpZ0nXslPFWrTpXv87eTwWpun9MAAgAwDyEIANATzEwrCqYVBS2q4pQ0W2mKXGFYqS4F4anhKUgcY9oeAPQvQhAAoO8NFgaU0v+hJvdEpSmK5oWnIKw0jAjibdY7AUBvIQQBAFCDmWlo0CRJo1pcgoqi+UFp9vFspWmuQUQ5rk4xVQ8A2o8QBABAiwwMmIYHChpe5H9dq9WmZEiqVJ4qj2uteQpCpyU5ADSJEAQAQIdUq01LbRJRDURhYp1TtWlEcn+1E184e2zuMQDkGSEIAIAeU21JnpV7pZpUDUShV75H8ePIXVGkyuOosh1GlWsiT2xXz4nPq54DAN2OEAQAQM6YmQpWCVOtlgxYCwNT5PND1ly4qn9NMmRVzwGAZhGCAABAyyxnwKqKktWrBYEpua/6OEhUuRaey/RAIJ8IQQAAoKcMDJgGVLlnVKtU11PNC1PV6YGJAOXVaYTucneFiYqWJ6YLVqtbEVMEga5ECAIAALnX7DqrRqLEtL/I4zAVB6nIVf+75sKUpNnnSJ7n1f1R5XxP/Izq+Uo8j0u0ZkfuEYIAAACWWbV61S08EZKqIcpdC6pZkhZsV0PWvGvjKthsYEuEu+T6r4XPnTyHUIZ2IwQBAADkjJnJTF0TzLxGB8JTKl6JylatMOaJIDd7XHPVMvcFj3Xq+dJclazec8wenT029ztQZesdTYUgM1sv6XOSzpX0pKQ3uPuxBef8oqTbErteKOl6d/9bM/uUpF+QdCI+9hZ3/34zYwIAAEBvMTMNFrojkLWKJypc1SA197i6f34VrBrI5h4nnitxnWqct/D5vXLSqaFv4dgSx6J5P6e6b/7PqjXOqqHBpd3zrJOarQTdJOmr7n6rmd0Ub78reYK7f13SpdJsaNoj6R8Sp/wnd7+7yXEAAAAAXaNabUvs6dRQUEOzce06SXfGj++U9LoG579e0pfcfarJnwsAAAAAmTQbgja6+/748QFJGxucf72kzy7Y9wEze8jMbjOz4XoXmtkOM9ttZrsPHTrUxJABAAAA5FnDEGRmXzGzR2p8XZc8zysTEesuBTOzTZJeLGlXYve7VVkj9K8krdeCqXQLnv92d9/m7tvOOOOMRsMGAAAAgJoargly96vrHTOz58xsk7vvj0POwZSneoOkv3H3cuK5q1Wkopl9UtLvLHLcAAAAAJBJs9Phdkq6MX58o6QvpJz7Ji2YChcHJ5mZqbKe6JEmxwMAAAAAqZoNQbdKepWZ/VjS1fG2zGybmX28epKZnSvpLEnfXHD9X5jZw5IelrRB0vubHA8AAAAApGqqRba7H5H0yhr7d0t6e2L7SUlbapx3VTM/HwAAAACWqnfuaAQAAAAALUAIAgAAAJArhCAAAAAAuUIIAgAAAJArhCAAAAAAuUIIAgAAAJArhCAAAAAAuUIIAgAAAJArhCAAAAAAuUIIAgAAAJArhCAAAAAAuUIIAgAAAJArhCAAAAAAuUIIAgAAAJArhCAAAAAAuUIIAgAAAJArhCAAAAAAuUIIAgAAAJArhCAAAAAAuUIIAgAAAJArhCAAAAAAuUIIAgAAAJArhCAAAAAAuUIIAgAAAJArhCAAAAAAuUIIAgAAAJArhCAAAAAAuUIIAgAAAJArhCAAAAAAuUIIAgAAAJArhCAAAAAAudJUCDKzf2dmj5pZZGbbUs67xsx+ZGZ7zOymxP7zzOy+eP/nzGyomfEAAAAAQCPNVoIekfRvJX2r3glmVpD0EUnbJV0k6U1mdlF8+EOSbnP38yUdk/S2JscDAAAAAKmaCkHu/kN3/1GD014qaY+7P+HuJUl3SbrOzEzSVZLujs+7U9LrmhkPAAAAADTSjjVBWyQ9k9jeG+87XdJxdw8W7AcAAACAZTPY6AQz+4qkM2sceo+7f6H1Q6o7jh2SdsSbE2bWqALVLhskHe70INBz+LvBUvE3g6XibwZZ8HeDpermv5lz6h1oGILc/eomf/g+SWcltrfG+45IOs3MBuNqUHV/vXHcLun2JsfScma2293rNoUAauHvBkvF3wyWir8ZZMHfDZaqV/9m2jEd7n5JF8Sd4IYkXS9pp7u7pK9Len183o2S2lZZAgAAAJBPzbbI/t/MbK+kl0n6OzPbFe/fbGb3SFJc5XmHpF2Sfijp8+7+aPwU75L0H81sjyprhD7RzHgAAAAAoJGG0+HSuPvfSPqbGvuflfRLie17JN1T47wnVOke18u6booeegJ/N1gq/mawVPzNIAv+brBUPfk3Y5VZaQAAAACQD+1YEwQAAAAAXYMQ1AQzu8bMfmRme8zspk6PB93HzM4ys6+b2WNm9qiZ/Va8f72ZfdnMfhx/X9fpsaK7mFnBzB40sy/G2+eZ2X3x+83n4kYzwCwzO83M7jazfzGzH5rZy3ivQRoz++34v02PmNlnzWyE9xosZGZ3mNlBM3sksa/me4tV/Lf47+chM3tJ50aejhCUkZkVJH1E0nZJF0l6k5ld1NlRoQsFkv5vd79I0hWSfjP+O7lJ0lfd/QJJX423gaTfUqWZTNWHJN3m7udLOibpbR0ZFbrZn0r6e3d/oaRLVPn74b0GNZnZFkn/QdI2d/9ZSQVVOvjyXoOFPiXpmgX76r23bJd0Qfy1Q9JH2zTGJSMEZfdSSXvc/Ql3L0m6S9J1HR4Tuoy773f378WPx1X5ULJFlb+VO+PT7pT0uo4MEF3JzLZK+l8lfTzeNklXSbo7PoW/GcxjZmsl/bziLqvuXnL34+K9BukGJY2a2aCklZL2i/caLODu35J0dMHueu8t10n6tFfcq8o9QTe1ZaBLRAjKboukZxLbe+N9QE1mdq6kyyTdJ2mju++PDx2QtLFT40JX+rCk/ywpirdPl3Q8vuWAxPsNTnWepEOSPhlPo/y4mY2J9xrU4e77JP2xpKdVCT8nJD0g3muwOPXeW3rm8zEhCGgDM1sl6a8kvdPdTyaPxTcOpk0jJElmdq2kg+7+QKfHgp4yKOklkj7q7pdJmtSCqW+81yApXsNxnSoBerOkMZ065QloqFffWwhB2e2TdFZie2u8D5jHzFaoEoD+wt3/Ot79XLU8HH8/2KnxoetcKem1ZvakKtNsr1Jlrcdp8ZQVifcbnGqvpL3ufl+8fbcqoYj3GtRztaSfuvshdy9L+mtV3n94r8Fi1Htv6ZnPx4Sg7O6XdEHcRWVIlcWEOzs8JnSZeC3HJyT90N3/a+LQTkk3xo9vlPSFdo8N3cnd3+3uW939XFXeV77m7r8m6euSXh+fxt8M5nH3A5KeMbOfiXe9UtJj4r0G9T0t6QozWxn/t6r6N8N7DRaj3nvLTkk3xF3irpB0IjFtrqtws9QmmNkvqTJ3vyDpDnf/QGdHhG5jZi+X9I+SHtbc+o7fVWVd0OclnS3pKUlvcPeFiw6Rc2b2Ckm/4+7XmtnzVakMrZf0oKQ3u3uxg8NDlzGzS1VppjEk6QlJb1Xl/+zkvQY1mdnvS3qjKp1MH5T0dlXWb/Beg1lm9llJr5C0QdJzkt4r6W9V470lDtR/psrUyilJb3X33R0YdkOEIAAAAAC5wnQ4AAAAALlCCAIAAACQK4QgAAAAALlCCAIAAACQK4QgAAAAALlCCAIAAACQK4QgAAAAALlCCAIAAACQK/8/bZDGX+iGhIIAAAAASUVORK5CYII=\n", "text/plain": [ "<Figure size 1008x432 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "\n", "#plot autocorrelation with 100 values from dataset\n", "#dropna to remove nulls\n", "\n", "fig, ax = plt.subplots(figsize=(14, 6))\n", "\n", "\n", "plot_acf(df['values'].dropna(), color=\"green\", lags=100, ax=ax);\n", "\n", "\n", "\n" ] }, { "cell_type": "markdown", "id": "5debc4d7", "metadata": { "papermill": { "duration": 0.008264, "end_time": "2022-10-27T19:23:58.771849", "exception": false, "start_time": "2022-10-27T19:23:58.763585", "status": "completed" }, "tags": [] }, "source": [ "Couldn't get window to expand using this type of plot. Had to consult: https://stackoverflow.com/questions/28517276/changing-fig-size-with-statsmodel for help.\n" ] }, { "cell_type": "code", "execution_count": 5, "id": "824f77e5", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:23:58.791448Z", "iopub.status.busy": "2022-10-27T19:23:58.790345Z", "iopub.status.idle": "2022-10-27T19:23:59.151969Z", "shell.execute_reply": "2022-10-27T19:23:59.151186Z" }, "papermill": { "duration": 0.37386, "end_time": "2022-10-27T19:23:59.154238", "exception": false, "start_time": "2022-10-27T19:23:58.780378", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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apJXACtiyaJLtJOxWTLNyyOWSJEmSasQQNEhjwBr44Jl38vmT74FLcFAESZIkacAMQYM2Btcfs5Evvmw9nIQBSJIkSRowQ5AkSZKkWjEESZIkSaoVQ5AkSZKkWjEESZIkSaoVQ5AkSZKkWjEESZIkSaoVQ5AkSZKkWjEESZIkSaoVQ5AkSZKkWjEESZIkSaoVQ5AkSZKkWjEESZIkSaoVQ5AkSZKkWjEESZIkSaoVQ5AkSZKkWjEESZIkSaoVQ5AkSZKkWulJCIqIEyPiexGxNiLOmWH5X0TE7RFxc0RcFREHNSybjIgby5/VvSiPJEmSJDWzsNsHiIgx4MPAi4F1wLURsTozb29Y7QZgPDM3R8SfAv8LOK1ctiUzl3dbDkmSJEmajV60BB0HrM3MuzPzMeBS4JTGFTLzG5m5uZy8Gti/B88rSZIkSXPWixC0DLinYXpdOa+ZM4ErGqafEhETEXF1RJzabKOIOKtcb2LDhg1dFViSJElSfXXdHW4uIuKPgHHgBQ2zD8rM9RHxDODrEXFLZn5/+raZeQFwAcD4+HgOpMCSJEmS5p1etAStBw5omN6/nLeDiDgBeCtwcmZunZqfmevL33cD3wSO7UGZJEmSJGlGvQhB1wKHRcQhEbEzcDqwwyhvEXEs8FGKAPRAw/zdI2JR+fdewPOBxgEVJEmSJKmnuu4Ol5nbIuJsYA0wBlyYmbdFxLnARGauBv43sBvw+YgA+HFmngwcCXw0IrZTBLLzpo0qJ0mSJEk91ZN7gjLzcuDyafPe3vD3CU22+3fg13pRBkmSJEmajZ78s1RJkiRJGhUDHR1OammSYvD0GyiGx1hJ0cFSkiRJ6iFDkKphEngpcA2wCVgMrOCXd5pJkiRJPWJ3uFEyCXwFeFf5e3K4xempKygC0KNAlr+vYcd/qytJkiT1gC1Bo2K+t5TcQPG6Gm0CbgROarOt3egkSZI0B4agUdHYUgI7tpS0CwmD1kkoOZYi2D3aMG8xsHwWzzWfw6EkSZJ6zu5wo6JVS0mVTIWSVwLvKH+/lPZd91YCK2DLokm2k8V/lVpRzm/FbnSSJEmaI0PQqJhqKWk0m5aSQes0lIwBa+CDZ97J50++By5hdq05oxIOJUmSVBmGoFHRaUvJoHUTSsbg+mM28sWXrS+6+M2mO9uohENJkiRVhiFoVHTaUjJogw4loxIOJUmSVBmGoFHSSUvJoPUrlDQbHnxUwqEkSZIqw9Hh1FtToeT1d3LwusWc9toDux+yut0IcGU4vP6YjZx20oFdvgB1xeHKJUnSCDAEqfd6HUpGaXjwOnO48v4wWEqS1HOGIFVfN/9IVYNjWO09g6UkSX3hPUGqPkeAGw0OV957/h8sSZL6whCk6nMEuNFgWO09g6UkSX1hCFL1OQLcaDCs9p7BUtIoazayq1QB3hOk0eAIcIPVyc34/RgZsO6mguV3Jlm0dQELdguDpVR3ozJYivc0quIMQT323e8/CMDPf/H4DtONWi1rp5tte2oSln5rJxbfvpBNR21j4wse36FS67Scnb5vlXlf5oNJOPKMJSy5aScWbIHtu8Ajz3qcOy56ZFYnrm8evgEO38CBRy6GH/a9tPPf/4Gv/t29PGP9bhx36h7FZ+2Hwy7UALWpa6Ra6bJ+HqSlX9+Jw7+7hLHNUcx4FCa/m9x54SNsPP7x4RaujgZYlz7v0D3788A9Zgiqmiqd8JuVZYQq4drr4Hha+q2dWHLTTk+cuMY2w5KbdmLpt3byxDUMY/AfRz/Efxz9EIcfv2TYpRks6xppB6NUPy++fSELtuw4b8EWWHzHwsqVdd6zLp2RIahKqnSQtijLKFXCtdbh8eSJS1VhXaN5rYMvqUapft501Da271J8bqds3wU2HblteIWqKevSmTkwQoU0HqSRwdjmeOIg7cpk0Sy97EO7sPTrO83qxsRWZWlVCas6Oj2epk5cjTxxaRisazRQHZwru3muI89YwuFvWMIBH9iFw9+whCPPWPLL52xSllGqnze+4HEeedbjbNl5G9tJJndNHnnW40XY00BZl86s3q++YvryDU8fWgO6+nanSt395rlOj6epE9ei6xaw6LExclc8cWko5s03ydZ71Tfgnhgtv5l/weNNyzJS9fMY3HHRI0++p9Fjf+DmTV3aY4agCulHuOi0CbRVWTquhKvU3W9YBngx1PHx5IlLFTFSF3zNWO9VS4/PlZ1q9818q7KMVP1c53saK6RtXVrTL2oMQRXSj3DRl9aADi+Sa98ndcAXQ11dQHri6kxNTyR9Mw8C+VDqPY/DmfXhXNmpVl9StS3LfKmfPU4Hp1VdWuMvagxBVdKHcNG31oAOKuFRuqGzHwZ+MTQPLiBHSjcnEi8GmmtV13T6vg1wu77Ve47eOWd9OVd2qN2XVPO+65LH6eA1qUvr/AW1Iahqehwu1v/Jls6bQHv8bVPd+6QOJQTOl28MR0DHJ5KqXQyMSiDr9H0b8HZ9qfccvbMjXZ0re63Fl1TzohtoGx6nXehxHV3nL6gNQfNAy5NshZpA61Cxt1L3EDjfdXoiqdTFQNUCWQudvm+D3q4f9V6rsvT1gqZKAblVWZos6/hc2S/NvqSqQSv+SF14V+y473UdXedrE0PQPND2JFuVJtAaVOyt1D0EznednkiqdDHQVZ0w4AuFtu9bk/J0+n53vJ/6UO/1bfTOVqoUkFuVhebLOj1XDkWVytIHI3PhXaXjnv5ct9X52sQQNB90eJK1e9aA1TwEDsUAL8w7HX2nShcDHdcJQ7hQaPm+tShPp+93V/tpgF2L+3VBU6UWy1ZlgYqNrFalVoQKGZUL774e9/24x7CT463G1yaGoPmig5NslS6+aqMfIdCT7MwGPVBBh11Pq3Qx0GmdMIwL5FbvW7v/wdLJ+12l/dSP0TvbqVKLZcvhpZPqjKxWsVaEtgZ5LhmRC+++hA7ozz2G3RxvNf2CuichKCJOBD5A8TZ/LDPPm7Z8EfBJ4DnAg8BpmfnDctlbgDMp/h/y6zNzTS/KpPaqdFJXG/NhJKgBh7WhDFTQYdfTqnw73WmdMKxW5WbvW7vydPR+V+mirQ+jd7ZTpS/N2pWlKuWsUutZW8M4l4zAhXe/Qkc/7jEcqeOtIroOQRExBnwYeDGwDrg2IlZn5u0Nq50JPJyZz4yI04H3AadFxFHA6cDRwH7A1yLi8Myc7LZcmoUqndTVUdAZmUpvCCfYvg1U0I8uDBX6drqTOmFoF8hN3re25en0/a7SRduAy1KlL83alaUq5axS61k7I3Mu6UYHdXe/Qkc/7jEcpeOtKnrREnQcsDYz7waIiEuBU4DGEHQK8M7y78uAD0VElPMvzcytwA8iYm35eN/tQbk0G1U6qddZh0FnVCq9YZxg+zJQwQser84wyR1quy86qBOqdIFcxfLMC+0CcoW6UlXly70qfe7bGZVzScc6/SKuT6GjH/cY9nNQlPna5T4ys7sHiHg5cGJmvqac/mNgRWae3bDOreU668rp7wMrKILR1Zn5qXL+x4ErMvOyVs85vmQ8J54z0VW5e+G2n/wMgKP3e9oT8362pTjwf/TgJgAO2nPxk7ZrtaybbV3W/D2tkpnKuvDhYNfvjxHb44l5uSDZfOgkY5uDResXEDQsI9m6bDuTu2bT7bbtnk2fr9NydrrdovULmr6Grcu2z+nxZy1h1/8cY8GjwYIEFsC2xcnmIyZpKMaTtNoXQGfv9yzKMqjjezb7oqPnS3jonq3s8tgYS/bciW1Ls+X7PBcdvTdtylOFz0W3hlEntjq+F24K2M6sP2t9KUsfl81ZHz/3vd6/req9qbqtU1U4d7d9fQkLNwZjm4PJXXNW9UVX71mH56dW5enL8dbhZ/tpu+zU/kUMSHwrrsvM8RmXjUoIioizgLMAjll0zHNueu5NXZW7X6ZCkKqjXyeZXlbsrS5MWwadpdnVxcegLuhmc7Loy37q4MTWqtJf9JMuwlybsnSqbQjYOsaSvX4ZArq92OnXMVOlLzKqFJBGITz17fPd5Bgelk5fQz8+9+3042J3VI7TOX8Rt9/2zgJJl+9ZR+endnp8vM0mPM70GR2VENSL7nDrgQMapvcv5820zrqIWAg8jWKAhNlsC0BmXgBcADA+Pp58swcl74Pbv//zYRdB05z7ldsAePtJR/dsWbfbTrf06ztx+BuW7NiMvSv84B2b2nfBmmqqvmPhE0Pkzrapeq7lhOL5vvp393Lout3Y6XcXzO75ZtEVoV/7qZWm2zZ5T1vup2F0GWm2L8r3++kPPaXoDrYVHtmr/f9Rmc1x0+n73c3nadD69Ro72a4f70uvn2/Zh3Zh1w/ssuPMhAdPeoz1r9vS2XO2OoaH1BVn0PupGx2Vtc25ZFSO05mWtaq7gWJZlhf622HBJPzktVtm///ROnjP2qnCMdXys/0nW5p+Rp93+J7DKfBMWvX86MHDXwscFhGHUASY04E/mLbOamAVxb0+Lwe+npkZEauBz0TEP1AMjHAY8B89KJM0UqbuYZh+Ydo45G3TinYMNh7/+GAuwssLk+XXPa2o9L41t37VnYa1gWvynrbcT4PWYl88cd/PY2XtP8NodCOzL1R5/bgXod0xrD4Y5LlkwFrV3cs+skvn90PN4/cMWn+2W31GOXw45Z2rrkNQZm6LiLOBNRSn0Qsz87aIOBeYyMzVwMeBfyoHPniIIihRrvc5ikEUtgGvc2Q41VKVgk4LXV2YVOQ1dKVCYa7VvpjNaHQjvy/UmUk47rY9OHTdbizddaeeHL/9+HJg3t+o30+t9nEf9v9IaFF3j9IAFoPWaXgcFT0paWZeDlw+bd7bG/7+BfD7TbZ9D/CeXpRDGmkjcGHqhQmV2U+t9oUn9Xmi1xesnbbkttPNlwNNXqPHcIda7WP6tP9HJViNQgt/1czz8Dg6cU3S0FWu0huVk28ftNoXntSHYAQCS1+7mLX6cqDZe9PiNXoMd6ZlFyXo/f7vV7DuVCefw3618HdTJ1Tp3DaPw6MhSNKsVarSq9rJd8C6uo9MvTUigWUoLbneuzZQrfYxSc/3/1Du3eogVM8mCPW0hb+bsozKuW0enGcMQZJmr0KVXu1vnB6R+8jqYFQCyzBacr13bbDa7eNe7/+BB+suQvUgdVOWKr2Otkb8M2oIkmZSpaboqqlIpef9SQx+X/Trc1Glz1sHZenqWBzgPTHDaMn13rXBarePe73/B70PuwrVA9RNWar0OuY7Q5A03ag0RdecF1AD1q/PRZU+bx2WpeNjcdD3xAyhJdd71waszT7u9f4f9D4clVDdTVmq9DrmO0OQNM1INUV3o0rfvnfAC6jB6tfnokqft07L0umxOJR7Ygbcejhv7l0bpWGnW+3jXu//Ae/DUQnV3ZSlSq9jvjMESdPMqim6aie9uarSt++dGqULqHmgX100qtT1o+OydHgs1uKemPlw79owhp0eJQPchyMTqrspS5VexzxnCJKmadsUPQ8CRJW+fQc6D5XdnHxHPcgOWL+6aFSp60dXZengWKzSa++rUQg6LQx82Gk1N0qhupuyVOl1zGOGIGmadk3RbQPECFxcV+nb96GEynkQZAetX100qtT1Y9BlqdJrV3ODHna6kqp0XjMgqEcMQaqvZpV6m2+aWgaIFzw+EhfXVfoGehitUpVrCRsF3XTRaHUBVaWuH4MuS5VeO1TrQrdCBj3sdOUM6Ysqj0X1myFI9dSuUm/xTVOrE+KoXFxX6RvoYbRKVaolbJR08g3sbC6gqvTN7qDLUpXXbutoU4MedrpqBn5e81jUgBiCeux5h+457CJomqc+pei3vcO++QpwC/BYOb0Zlt6yM8+7c084qc0DHgx8FrgG2AQshrEVwZH/7anwXmDaxfXYluDI+58Kh3b9Unrr34ArgBthbDksXbkzzxsbwvH7IuBjwKO/nBWLgwOP35UDD90VaLIP+/yc6pFuPmsaHPdTa63qy6rUpf3yGQZ7XvNY1IAYgjS/TcKzb17KwfcshmXASopvkm6gCDCNNgE30r6SHQPW8MRJj+UNj3sssJgdLq5ZXK5TNWMUr3XYJ5WVwAp2CJWsKOfPp+esq24+axoc91NrrerLqtSl/TLo85rHogbEEKT5axJ4Kbz+O4ezaOsC+AbFhe4auq/Um530vLieu1ahcj49Z12N0hcDdeZ+UjODPq95LGpADEGav64AroFdtpZXto8W01xB/yp1L6470+qb1Gatef18TvWOXwyMBveTmhn0ec1jUQMSmTnsMszZ+Ph4TkxMDLsYqrp3Ae8AGg/xAM4F3kbRUmRYqbayNW/LdyZZtHUBC3aLX7bmua9Gh5+10eB+UlV4LKpHIuK6zByfaZktQZq/2jWp2xJQfa1a89xvo8PP2mhwP6kqPBY1AAuGXQCpb6aa1HejaAHaDZvUR02rG2QlSZI6ZEuQ5i/vzxl93iArSZL6wBCk+c0m9dHmDbKSJKkPDEGSqsvWPEmS1AeGIEnVZmueJEnqMQdGkCRJklQrhiBJkiRJtWIIkiRJklQrhiBJkiRJtWIIkiRJklQrhiBJkiRJtWIIkiRJklQrhiBJkiRJtWIIkiRJklQrhiBJkiRJtdJVCIqIPSLiyoi4q/y9+wzrLI+I70bEbRFxc0Sc1rDsooj4QUTcWP4s76Y8kiRJktROty1B5wBXZeZhwFXl9HSbgVdl5tHAicD7I2Jpw/K/yszl5c+NXZZHkiRJklrqNgSdAlxc/n0xcOr0FTLzzsy8q/z7J8ADwN5dPq8kSZIkdaTbELRPZt5b/n0fsE+rlSPiOGBn4PsNs99TdpM7PyIWtdj2rIiYiIiJDRs2dFlsSZIkSXXVNgRFxNci4tYZfk5pXC8zE8gWj7Mv8E/AqzNzezn7LcARwK8DewBvbrZ9Zl6QmeOZOb733jYkSZIkSerMwnYrZOYJzZZFxP0RsW9m3luGnAearPdU4F+At2bm1Q2PPdWKtDUiPgG8aU6llyRJkqQ56rY73GpgVfn3KuDL01eIiJ2BLwGfzMzLpi3bt/wdFPcT3dpleSRJkiSppW5D0HnAiyPiLuCEcpqIGI+Ij5XrvAL4TeCMGYbC/nRE3ALcAuwFvLvL8kiSJElSS1HcyjNaxsfHc2JiYtjFkCRJklRREXFdZo7PtKzbliBJkiRJGimGIEmSJEm1YgiSJEmSVCuGIEmSJEm1YgiSJEmSVCuGIEmSJEm1YgiSJEmSVCuGIEmSJEm1YgiSJEmSVCuGIEmSJEm1YgiSJEmSVCuGIEmSJEm1YgiSJEmSVCuGIEmSJEm1YgiSJEmSVCuGIEmSJEm1YgiSJEmSVCuGIEmSJEm1YgiSJEmSVCuGIEmSJEm1YgiSJEmSVCuGIEmSJEm1YgiSJEmSVCuGIEmSJEm1YgiSJEmSVCuGIEmSJEm1YgiSJEmSVCuGIEmSJEm1YgiSJEmSVCuGIEmSJEm1YgiSJEmSVCuGIEmSJEm10lUIiog9IuLKiLir/L17k/UmI+LG8md1w/xDIuKaiFgbEZ+NiJ27KY8kSZIktdNtS9A5wFWZeRhwVTk9ky2Zubz8Oblh/vuA8zPzmcDDwJldlkeSJEmSWuo2BJ0CXFz+fTFw6mw3jIgAjgcu62R7SZIkSepEtyFon8y8t/z7PmCfJus9JSImIuLqiDi1nLcnsDEzt5XT64BlzZ4oIs4qH2Niw4YNXRZbkiRJUl0tbLdCRHwNePoMi97aOJGZGRHZ5GEOysz1EfEM4OsRcQvws7kUNDMvAC4AGB8fb/Y8kiRJktRS2xCUmSc0WxYR90fEvpl5b0TsCzzQ5DHWl7/vjohvAscCXwCWRsTCsjVof2B9B69BkiRJkmat2+5wq4FV5d+rgC9PXyEido+IReXfewHPB27PzAS+Aby81faSJEmS1EvdhqDzgBdHxF3ACeU0ETEeER8r1zkSmIiImyhCz3mZeXu57M3AX0TEWop7hD7eZXkkSZIkqaUoGmRGy/j4eE5MTAy7GJIkSZIqKiKuy8zxmZZ12xIkSZIkSSPFECRJkiSpVgxBkiRJkmrFECRJkiSpVgxBkiRJkmrFECRJkiSpVgxBkiRJkmrFECRJkiSpVgxBkiRJkmrFECRJkiSpVgxBkiRJkmrFECRJkiSpVgxBkiRJkmrFECRJkiSpVgxBkiRJkmrFECRJkiSpVgxBkiRJkmrFECRJkiSpVgxBkiRJkmrFECRJkiSpVgxBkiRJkmrFECRJkiSpVgxBkiRJkmrFECRJkiSpVgxBkiRJkmrFECRJkiSpVgxBkiRJkmrFECRJkiSpVgxBkiRJkmrFECRJkiSpVgxBkiRJkmrFECRJkiSpVroKQRGxR0RcGRF3lb93n2Gd34qIGxt+fhERp5bLLoqIHzQsW95NeSRJkiSpnW5bgs4BrsrMw4CryukdZOY3MnN5Zi4Hjgc2A//asMpfTS3PzBu7LI8kSZIktdRtCDoFuLj8+2Lg1Dbrvxy4IjM3d/m8kiRJktSRbkPQPpl5b/n3fcA+bdY/Hbhk2rz3RMTNEXF+RCxqtmFEnBURExExsWHDhi6KLEmSJKnO2oagiPhaRNw6w88pjetlZgLZ4nH2BX4NWNMw+y3AEcCvA3sAb262fWZekJnjmTm+9957tyu2JEmSJM1oYbsVMvOEZssi4v6I2Dcz7y1DzgMtHuoVwJcy8/GGx55qRdoaEZ8A3jTLckuSJElSR7rtDrcaWFX+vQr4cot1X8m0rnBlcCIiguJ+olu7LI8kSZIktdRtCDoPeHFE3AWcUE4TEeMR8bGplSLiYOAA4FvTtv90RNwC3ALsBby7y/JIkiRJUkttu8O1kpkPAi+aYf4E8JqG6R8Cy2ZY7/hunl+SJEmS5qrbliBJkiRJGimGIEmSJEm1YgiSJEmSVCuGIEmSJEm1YgiSJEmSVCuGIEmSJEm1YgiSJEmSVCuGIEmSJEm1YgiSJEmSVCuGIEmSJEm1YgiSJEmSVCuGIEmSJEm1YgiSJEmSVCuGIEmSJEm1YgiSJEmSVCuGIEmSJEm1YgiSJEmSVCuGIEmSJEm1YgiSJEmSVCuGIEmSJEm1YgiSJEmSVCuGIEmSJEm1YgiSJEmSVCuGIEmSJEm1YgiSJEmSVCuGIEmSJEm1YgiSJEmSVCuGIEmSJEm1YgiSJEmSVCuGIEmSJEm1YgiSJEmSVCtdhaCI+P2IuC0itkfEeIv1ToyI70XE2og4p2H+IRFxTTn/sxGxczflkSRJkqR2um0JuhX4PeDbzVaIiDHgw8BK4CjglRFxVLn4fcD5mflM4GHgzC7LI0mSJEktdRWCMvOOzPxem9WOA9Zm5t2Z+RhwKXBKRARwPHBZud7FwKndlEeSJEmS2hnEPUHLgHsapteV8/YENmbmtmnzJUmSJKlvFrZbISK+Bjx9hkVvzcwv975ITctxFnBWOfloRLRrgRqUvYCfDrsQGjkeN5orjxnNlceMOuFxo7mq8jFzULMFbUNQZp7Q5ZOvBw5omN6/nPcgsDQiFpatQVPzm5XjAuCCLsvScxExkZlNB4WQZuJxo7nymNFcecyoEx43mqtRPWYG0R3uWuCwciS4nYHTgdWZmcA3gJeX660CBtayJEmSJKmeuh0i+3cjYh3wPOBfImJNOX+/iLgcoGzlORtYA9wBfC4zbysf4s3AX0TEWop7hD7eTXkkSZIkqZ223eFaycwvAV+aYf5PgJc1TF8OXD7DendTjB43yirXRU8jweNGc+Uxo7nymFEnPG40VyN5zETRK02SJEmS6mEQ9wRJkiRJUmUYgroQESdGxPciYm1EnDPs8qh6IuKAiPhGRNweEbdFxJ+X8/eIiCsj4q7y9+7DLquqJSLGIuKGiPhKOX1IRFxT1jefLQeakZ4QEUsj4rKI+M+IuCMinmddo1Yi4o3luenWiLgkIp5iXaPpIuLCiHggIm5tmDdj3RKFD5bHz80R8ezhlbw1Q1CHImIM+DCwEjgKeGVEHDXcUqmCtgF/mZlHAc8FXlceJ+cAV2XmYcBV5bTU6M8pBpOZ8j7g/Mx8JvAwcOZQSqUq+wDw1cw8AngWxfFjXaMZRcQy4PXAeGb+KjBGMYKvdY2muwg4cdq8ZnXLSuCw8ucs4CMDKuOcGYI6dxywNjPvzszHgEuBU4ZcJlVMZt6bmdeXfz9CcVGyjOJYubhc7WLg1KEUUJUUEfsDvw18rJwO4HjgsnIVjxntICKeBvwm5SirmflYZm7EukatLQR2iYiFwK7AvVjXaJrM/Dbw0LTZzeqWU4BPZuFqiv8Juu9ACjpHhqDOLQPuaZheV86TZhQRBwPHAtcA+2TmveWi+4B9hlUuVdL7gb8GtpfTewIby385ANY3erJDgA3AJ8pulB+LiMVY16iJzFwP/B3wY4rw8zPgOqxrNDvN6paRuT42BEkDEBG7AV8A3pCZP29cVv7jYIdpFAARcRLwQGZeN+yyaKQsBJ4NfCQzjwU2Ma3rm3WNGpX3cJxCEaD3Axbz5C5PUlujWrcYgjq3HjigYXr/cp60g4jYiSIAfTozv1jOvn+qebj8/cCwyqfKeT5wckT8kKKb7fEU93osLbusgPWNnmwdsC4zrymnL6MIRdY1auYE4AeZuSEzHwe+SFH/WNdoNprVLSNzfWwI6ty1wGHlKCo7U9xMuHrIZVLFlPdyfBy4IzP/oWHRamBV+fcq4MuDLpuqKTPfkpn7Z+bBFPXK1zPzD4FvAC8vV/OY0Q4y8z7gnoj4lXLWi4Dbsa5Rcz8GnhsRu5bnqqljxrpGs9GsblkNvKocJe65wM8aus1Viv8stQsR8TKKvvtjwIWZ+Z7hlkhVExG/AfwbcAu/vL/jbyjuC/occCDwI+AVmTn9pkPVXES8EHhTZp4UEc+gaBnaA7gB+KPM3DrE4qliImI5xWAaOwN3A6+m+LLTukYzioi/BU6jGMn0BuA1FPdvWNfoCRFxCfBCYC/gfuAdwD8zQ91SBuoPUXSt3Ay8OjMnhlDstgxBkiRJkmrF7nCSJEmSasUQJEmSJKlWDEGSJEmSasUQJEmSJKlWDEGSJEmSasUQJEmSJKlWDEGSJEmSasUQJEmSJKlW/j/4GG6hBVfMNgAAAABJRU5ErkJggg==\n", "text/plain": [ "<Figure size 1008x432 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "#partial autocorrelation of values column\n", "fig, ax = plt.subplots(figsize=(14, 6))\n", "plot_pacf(df['values'].dropna(), method=\"ywmle\", color=\"magenta\", lags=100,ax=ax);" ] }, { "cell_type": "markdown", "id": "5c3f0786", "metadata": { "papermill": { "duration": 0.00836, "end_time": "2022-10-27T19:23:59.171508", "exception": false, "start_time": "2022-10-27T19:23:59.163148", "status": "completed" }, "tags": [] }, "source": [ "Get an error here if trying to plot (\"FutureWarning: The default method 'yw' can produce PACF values outside of the [-1,1]\") using default method. Hence had to change to Yule-Walker without adjustment (ywmle)." ] }, { "cell_type": "code", "execution_count": 6, "id": "5ff48ca5", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:23:59.191340Z", "iopub.status.busy": "2022-10-27T19:23:59.190361Z", "iopub.status.idle": "2022-10-27T19:23:59.501873Z", "shell.execute_reply": "2022-10-27T19:23:59.500819Z" }, "papermill": { "duration": 0.324283, "end_time": "2022-10-27T19:23:59.504498", "exception": false, "start_time": "2022-10-27T19:23:59.180215", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 720x432 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "#create new data frame and get rid of index column\n", "\n", "newdf=df.drop(\"index\", axis='columns')\n", "#readcol=df.set_index(\"date\")\n", "\n", "readcol=newdf.set_index(\"date\")\n", "\n", "fig = plt.figure(figsize=(10, 6))\n", "#readcol=df. \n", "#rmean=df.values.rolling(window=16)\n", "\n", "rmean=readcol.rolling(window=16).mean()\n", "\n", "df2=df.rolling(window=16).std()\n", "\n", "rstd=readcol.rolling(window=16).std()\n", "#print(rmean,rstd)\n", "orig=plt.plot(readcol , color='blue',label='Original data')\n", "mean= plt.plot(rmean , color='red',label='Rolling Mean')\n", "std=plt.plot(rstd,color='green',label = 'Rolling Standard Deviation')\n", "plt.legend(loc='best')\n", "plt.title(\"Rolling mean and standard deviation\")\n", "\n", "\n", "\n", "plt.show(block=False)" ] }, { "cell_type": "markdown", "id": "e8ca04ef", "metadata": { "papermill": { "duration": 0.00997, "end_time": "2022-10-27T19:23:59.524503", "exception": false, "start_time": "2022-10-27T19:23:59.514533", "status": "completed" }, "tags": [] }, "source": [ "Image plot here showing mean and sd\n", "Had to drop the index column as the plotter kept trying to draw the axis via the index column, and if you changed the set_index it still messed up. Am assuming this is python getting confused with index column/set_index so binned index column.\n" ] }, { "cell_type": "code", "execution_count": 7, "id": "85c6c6ed", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:23:59.546923Z", "iopub.status.busy": "2022-10-27T19:23:59.546143Z", "iopub.status.idle": "2022-10-27T19:23:59.790147Z", "shell.execute_reply": "2022-10-27T19:23:59.788844Z" }, "papermill": { "duration": 0.258563, "end_time": "2022-10-27T19:23:59.793057", "exception": false, "start_time": "2022-10-27T19:23:59.534494", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 720x432 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "readcol2=newdf.set_index(\"values\")\n", "readcol3=df.values \n", "orig= df.loc[:,\"values\"]\n", "#print(zz)\n", "\n", "df_diff=orig.diff()\n", "df_diff2=orig.diff(periods=2)\n", "\n", "fig = plt.figure(figsize=(10, 6))\n", "\n", "# Plot original data alongside first differenced result\n", "\n", "#df_diff = readcol3.diff(periods=1, axis=0)\n", "newplot=plt.plot(df_diff , color='red',label='Difference')\n", "orig=plt.plot(orig, color='blue',label='Original data')\n", "#df.plot(x=\"date\",y=\"values\")\n", "plt.legend()\n", "plt.title(\"Original data and differenced data\")\n", "plt.show(block=False)\n", "\n", "#df_diff" ] }, { "cell_type": "markdown", "id": "cd2d9059", "metadata": { "papermill": { "duration": 0.010573, "end_time": "2022-10-27T19:23:59.814718", "exception": false, "start_time": "2022-10-27T19:23:59.804145", "status": "completed" }, "tags": [] }, "source": [ "Plots first order difference (default=1) and original data\n" ] }, { "cell_type": "code", "execution_count": 8, "id": "4ea629b6", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:23:59.837714Z", "iopub.status.busy": "2022-10-27T19:23:59.837343Z", "iopub.status.idle": "2022-10-27T19:24:00.072468Z", "shell.execute_reply": "2022-10-27T19:24:00.071392Z" }, "papermill": { "duration": 0.250715, "end_time": "2022-10-27T19:24:00.076326", "exception": false, "start_time": "2022-10-27T19:23:59.825611", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 720x432 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig = plt.figure(figsize=(10, 6))\n", "\n", "\n", "newplot=plt.plot(df_diff , color='red',label='First order')\n", "\n", "plt.legend()\n", "plt.title(\"Differenced data -1\")\n", "plt.show(block=False)" ] }, { "cell_type": "markdown", "id": "539c99c2", "metadata": { "papermill": { "duration": 0.013282, "end_time": "2022-10-27T19:24:00.103039", "exception": false, "start_time": "2022-10-27T19:24:00.089757", "status": "completed" }, "tags": [] }, "source": [ "First order difference on its own." ] }, { "cell_type": "code", "execution_count": 9, "id": "21867138", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:24:00.128890Z", "iopub.status.busy": "2022-10-27T19:24:00.128174Z", "iopub.status.idle": "2022-10-27T19:24:00.362774Z", "shell.execute_reply": "2022-10-27T19:24:00.361655Z" }, "papermill": { "duration": 0.250658, "end_time": "2022-10-27T19:24:00.365465", "exception": false, "start_time": "2022-10-27T19:24:00.114807", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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f+IEfwHw+x5Oe9CS8+MUvxmtf+1qPESN8//d/Px588EE87nGPwyte8Qo89alPBQBcdNFFeO1rX4tv+7Zvw9VXX41nPOMZ+OhHP9ryLs1bvj8hISEh4UBjvgvY/T13GMpYGwKuvfZaK2sz3XzzzXjc4x63pBYlVOHmmz6Ex33wycBT/zPwmB9adnMSEhISEs4V/Hmu4Hz1e5bbjp4wxrzXWnut9rfEYCX0h50tuwUJCQkJCecS7C72u/qRAqyECNjfD0lCQkJCQmTMp/teIkwBVkJ/JAYroQp3vQO4Z++3l0rYJ9j8AvDp31x2KxJiw+5/D9Y5EWANySeWkCH7TvLvJQVYCVV4378CPvzKZbci4VzFba8H3v3dwO7pZbckISbm030/dww+wFpfX8e9996bgqwBwVqLe++9F+sr9ML+XoUk9MT0DDA/t/bvTBgQqO/MUh/aV7BT7Hd7yeDLb19xxRW4/fbbcffddy+7KQkM6+vruOL8vCDqPl+FJPTE9GzqIwndQQs4G6cAc8JAcADKNAw+wFpZWcFVV1217GYkaLj3nuxnmjwTqjDbSJNjQg+kAGtfwiaTe0JCGG5lub8fkoSemJ7N/BYJCV0wzxdw893ltiMhLg4Ag5UCrITuIOYqMVgJIdg5MNtK7ENCD+STcArS9xfm+9+DlQKsIeMTvwZ8/FeX3YowHIOVAqyEAKYb2c80OdbjrncA1wd2RLjrr4H3fL/+t7vflf1tvyYCuXEmMVj7CqlMQ8JScetvAbe9YdmtCMMxWPv7IUnogenZ7GcKwutx55uBT/yqHijd+Wbgll/XZbI7/yL7G/ZrgEUSYQrS9xVSodGEpWK2g2FTqInBSqjBLGewkkRYj6oFC/2NAlb/j+HP7QckBmv/wdrc5L6/544UYA0Z8+1hD5pJIkyoAwUEiX2oR9Xz5AKsjYrPDXis6IXkwdp3cH18v/bZDCnAGjIGH2AliTChBk4iTJNjLdzzpNyrKgbLPX/79Dmsui8J5ybou9znc0cKsIaM2c6wO2BisBLqkCTC5qgqqEnP2EyTCPc5g0XXlco07B/Qd7lf+2yOFGANGfNtDHpVmso0JNQhmdybo8rMfZAlwlTJff/BfZf7tM/mSAHWkDHfHvbEtN+liYT+SGUamqMqkKD7dyAlwgPKYL3r24EbfmTZrVgMDgiDNfitcg40Bi8RJgYroQbJg9UcVc/Tgc4iPKBlGh74CHDo0mW3YjGYJw9WwrIxdJN7KtOQUIeURdgCFdlyzoN1ACVCN84cMAZr8ON/D9iDwWClAGuosBaYD7wO1r4f2BN6I5ncm6NvFuF+fQ5tReC5nzEbuEWkDxyDtU+vL0cKsIaKc0GjThJhQh2Syb05GpncK7IIh7wY6wN3Xw4agzXwBXYfJJN7wlIx385+DjrAShJhQg0Sg9Ucjco0HECJ8KBmEe5nifBcIBAiIAVYQ8V8J/vJO+DOA8ADH11OezTs10KjD34a2Lpn2a3YH3AM1nz/9ZPY6Gpy3+8BFhYQYM22gfs+GO94i8CsQ4B16r1x+sEDH83mm0UhFRpNWCpmOYPFKdR3fivwJ4/L9ygcAPYrg/WOFwEf/Illt2J/gAcE+62fxEYTBusgSoTzBUiEn34d8OfXLjaI6Iu2EuGZW7JruvMt/c4728nmmXe9pN9xquC+y33aZ3OkAGuocBIhm5QeuCn/eePet0fFPg2wdu8HthODFQW8MOZBMym3RaUHi+pgaRLhPi/TsIi9CDduz+7p7ul4x4wJa9tLhNunsp+7PYPG+z+U/XzgI/2OU4VUpiFhqdAkwguuzX7e+569b4+G/SoR2jkw21x2K/YHEoPVHJWFRhswWPvtOSS4+xKRwdq5L/s51Oe8i4Q238o/0/M5O3V99vPkU/sdpwr8u6QFwj5ECrCGiplicj/8RdnPe6/f+/Zo2K8SoZ0Nd+A918D3zjtoJuW2aJJFqO1FuO8ruS+g0CixPUN9zmeKgtH4Mz3vEy3gD1/R7zhV4N/lfl0YIAVYw8Vc8WBRxeZTQwmw9mmZBjsHZlvLbsX+QJIIW6BiwZL2IozMYFGANdDnvEsW+SwSg+UW8Atklrifbr/NHwwpwBoqNImQqNQHbgpIBXuM/TqwJwYrHqaJwWoMkgFToVGBBXiwdgbOYNH434aVjCER7j4InL45P84C+5PXx/drv00B1nChSYTca3HqfXvepBL2q0SI5MGKBl636SAEWLf+DnD/TR0/3HGrnH3vwVpAFuHQPVjq+N/0Mz3G4/vetzfjuk0SYcIyoUmEvCM++Ok9bY6K/SoRzhODFQ3Ts8D4UPb7QZAIb/gB4JZf7/bZzlvlWP89+w2LKDQ6eAZrSRLhg7cWvy8y8PEkwhRgJew1iCKes4fFkwuHMFntV3NtYrCiYXoWWDme/b5fAwCOPvvHVdbBojINB7AOVuwAy84LBms60Oe8k0SYB2XzHs/ZnNdYXGSAlSTChGVCKzTKTYdD2JdrvzJYdjbcgfdcApW7WDkv//8QFgULht3tEWA1qeR+EE3ukSXC3dPFvRrqQqqTRBiBwaJEgtHagiXCxGAlLBMaRWznWccHBhJgkWdkvwVYeWCwj+uz7Alo8iIGa79LhNZmz2XXCcM9Tx3LNOzXiarqvnQBsVfAcAOsXhJhj/tEu4SM1xYsESYPVsIyoWURYp51fCBuynJXuBXOPntA7AyAFXR5QmuQnOUkwv0eYFFxyL4MVkWANd9VFlf7XCJ0Jv5IYx75r4ABB1g0/rfoS9ruH21B93i8vuAswsRgJSwTmkRoLTBazV8eQoC1T7MInXww0Bo55wpIzjooARY9k50ZrAaFRoGyTJgYrHbY5gHWQJ/xZUmE1IdH64sd1z0Ga5/NHwwpwBoqghLhEAMs1sb3/ijwmd9dSnNq8cnXAB96Rf37nBwTYXW7dQ/wthcAm1/of6xzDZLBGqqUPN0E3v61wOmP9TtOF9aBo8lmz4BidI+8F+H7fwy49fX9j/PJ/wl88N/0P05sD9bQGKz7PgT83xcW8hwQKDRdgxhlGuZ7JRHy73KfLgyQAqzhIiQRDirAUky5t70euONPltOeOtzxx/XBn7VwE1aMwfeBm4DPvwW47/39j3Wugfrw5Ej2c6gM1tnbgDv/DLjnb/sdJxaDVWVyB8oBVmwG69bXA3e+uf9x7vgj4LMRFluxswiH5sG6513Zvdq+q3hNHf9rEKPQ6HwXMGPATLDQwCfVwUpYKlSJcJ51fDMayGSlSIR2PuAd6mf1gw9/2KMMvgdYbqR7TYkZg+izCsgP0tdz5wKsrhNcRSAxn2a+GKBcbDT2XoRNnpMmmG1HYi1jB1g5g7VyYhgBlhaYL1MiHK3kc0wqNNoXKcAaKrhE6LLZbNbxzcrAGCwRBE7PLKc9dbDTBj6OyAGWjciGnWug/kGJGUPNIpzHCrA61C7iqPNgkdS6aAbLzuIca74TJyiaR5YIt09lxW9XTwyjHIsmLXfpS7EkQrOSsVhJIuyNFGANFd5gzzwWZpStMAYRYGkM1gzYHWqANasf8D0pJiaDNYCBfK/hGKxc1h4qg0UBzbIZrDoP1uRY9nvJg7WAACvGpDffjvSdxy7TcApYPZkxgkN4LjUGq0uZBpII+9yn+S4wXs0ZrFSmoS8my25AQgBOIkQRWNk5AJMFWIMo07AfJUL29ygMVgqwColwoCb3WBKh7RtgNWSwziWJMMZx3DgTy+R+H7B2MrNbDOG5jCYRRirTYFYALFoiTGUaEjhieAnaHIMP9q4DkkQ4GQiDpUiEGJBE6MmryCauWgYrtkS4hwGWtXofm89QWTQ19Lne7TnHJMJZJImwb6HREIMVkghjZxHaafhYdt78PPOdON95VeDpva9h2xyDdaj6uZxPq5+bWKiSCNsEOVE8WDu5B2vREuHBYLBSgNUEm58H3ngEuOfvuh/jC38F/O7xLG2/Cebb/D/Zj3NCIpwPRyJ867OBD7E08dYMVgRjOt2jvfB6fPjfAm/9ivL53/RFwKdfF/7cja8C/uIZ8dtzzkiEAzG512UR7qkHK3ANb312s1InQC4R7iGD9cH/B/jL59Qfb+e+zH81PhR+xue7wB8+FPj0b7Rqaie4sXwoJvdcIlzoXoScwRoosx0BKcBqgs07ssHi7K3dj3H2toza37y92fulRAgg6/AkEQ5gstImBDvLGKwhbDPz4Key+06ws2arYELULMI9CLAevBU4/VFx+h1g83PAg58Of+7sp4AHb4nfnnMlizB6gNWTwQpJhOPD+d9FO/fS5H72tnIfCyGWyb2pB+vsp5uN0dMNYHykmsHavBPY+rw/fiwKVR6sLps9n2tZhMnkfsAxi2AepM7alN3RJEJisIaSRaht0UE0vfSJLAPzHRH8TZfgwdrDLEJKMPBkURq8K/rufHcx7aN+62q3DTTAch6sns9U70KjNVvlUJmGUiC4hx6sNkks0TxYDbMI5w2ebyALRMZrwKQqwPqcf+5FolIi3GsGa4cFWKkOVl+kAKsJYmyi2TbAmmkSoQUwJIlQkzTytg5BJpzv+A9voyzCc5jBouvj8rJjZ+oCrK34rKP0YA1VCoieRdh1wqirg3Uo/32BDJa11V4mYqibYL4dyYPVsA5WlXeMY7aVBatVDNbGHf65Fwkby+QeUyLcwzINKcA64HCdPUaA1TDDjk+SfFNl8mANOYsQGEYm4Xy3LF8uLYtwDwqNan1s3oCdce/ZDr+nT3sOnES4oCxCF2CJ7zJqgFXDhrXJEpYMct821fWfpgzWbDvrk5US4V4yWIoHa5kS4Z5kESaJMIEQo76IMzv3lAjJgzUIBksM7JwBGUIm4XwHvnzZwIPF3x/DmL6nWYQKS0oDWZ1ECMRv47mSRRitknukQqMhk/t4DYBR2knPXYwAq6IN9HoriTBCJl5TidDuNgsK5sRgrYef8U1isPZQIuSZvH0kwl51sJhEuGcm9xRgHWy4jtsjqNEmv7v+OvwwqCb3yGUa7v9w86xGDXIw5oNRF4lw9zRw6r3d28Mxn5UZq/kUgGUs24PAvdf7n4vNYO21RAj4wW0TBouCr9iZjgeNwepdB6umTIOZZPLNQiVCrfSK+HuTxZO16FQsUz1WQ5N7EwbLzrPvu7FEuCQGS6tptXU3cP+NFcdRPnPfB/y9F+tg90oiXJAH6+xngDOfjHe8nkgBVhMsQiI8exvw1mdlGxBrmCsBVuwyDW//GuAjP9vjAEIi5A9KlwDrE/8f8JYvR5SaTJqvQQaCn3pNdj41mMU5WAerQiJcJoM1dJP7YLIIAxIhbUBuxtm9lPW6ogZYxHiGGKxcIqxjpTwTc9/nuWGZhiZJLPSsk0QY2j5rGRKhl0WoMFgf+Tngr742fBzNg/WWZwEf+8/t2rInWYQLYrDe+yPA3/2jeMfriRRgNcE8osmdVn8UgEwfDJyTD6KKRBiDDdg9na2KumIuAyseYHXwYO0+kJutIwSPWmaOnMB2T2fvC9VkiVIHay+zCOm6uETYhMHaI4lwsCb3yBJhbAaLjmfG2TYmi8wibMJg2Vn9s+EtWnqOVY0LjTYIsGgsJwYL0K9lTyVChfl0C2xbjCHTB7MxUj0Gu3Z+v6ZnwnOMepxcIsRebpUT8R5vn2p3vQtGCrCagAaLmGUa3Eox0IlDdbBilmmwU2Dax4xewWB18WA5L0KEa5spK0C5Op8rq/VFZRHuRaFRTYYeBIM1cIkwmgcrEoMVCrBG4z2UCCs8WED9860m6XRtU0MGq4lESOPqeI0FWEq/31hGmQZFIsz+ULRlFkhE0e43XVer/QyXkEUY0+s121xsu1siBVhNEKVMg8iu0yZ3DlUitHElwvluv3IKMouwr0QYM8CqYrBKxm9FRgTOXYlw2jGLMHamY4nBGmiANbTNnqVETvfN1AVYEWtOBSephlnCXpJOXwaroQerkUSY9/HRelYHCyg/m7tnigByLwIsFzgqEiHgB9DzbV2e5c9uKcBqcQ1cIlykyX1RdbBmm4NiylOA1QQxC43Sg6sZGznmO2yLEVamAZHKNFibdfJeAZYYjD2TewdmbCEBVoUHix5yPqHtCw/WwLIIicEaqgcrdhZh3zINVRKhWQlnEcZksIJlGpQ+poEzLb09lRHLNNDC1ZMIRb8n/xWwxxKhVqYB5fFVuw+zWAzWTtbH9rKSe+wAa0BlH6IEWMaY1xhj7jLG3MheO2mMeYsx5hP5z/NjnGspmMc0uUuJMNCJZ9tF5WZvL8JIZRo0tqP1MVh2o7XwOnYfiXBRHizHVNBPhXFYWBbhXtbB0rIIK/ou9cVFm9wHy2DFquS+oEKjLsCa6B6svZIILcvAbSURxvJgNTG5z3WGh0DPYZVESBmE/NyLhDZWqYWm58rf6C2cwRJZwZ0YrD2QCM2Y/hPvuPtUInwtgK8Wr70cwF9aax8F4C/z/5+biFrJ/bR/rFBnmG8Xe4/xQAaRyjRohujWxxCBSV+JcLYABkuT/0qmWf4ddKiDtXsGuP4HgL/5LuDzf+n/bS8ZrLnoY0A7iXBhZRpWABh9oL/9/wCfe3Oc881n2UbEbRM3BlOmIWDmpu81JBHumcmdBS6tJMKa+/HJ12TPzodeoQdHbSq58/dr4BIhBViy38dmsD77B8Dn3xb+e1UWIX/d9Q8lwKqSCNv0C1emYQ9M7m7h1fI8n3tzNm5omA4rwJrEOIi19h3GmCvFyy8EcF3+++sA/BWAl8U4355jHtHk7iTCOg/WTjEAaGUa+q4K6aHutaUND17mIsDqIxFGYDraeLC095hx86Do1A3AJ34t+322BVzyXPbHPd6LENDrYC1DIvQCg4n+vd70M1l/vuyr+p/vzMeAG/89sHo+8Nh/3qKdkQKsmRLUt0GTLMJFm9yrxiXPAtBCIqwbq27898UmzY/9F8DqCXFe8mDtZgGYMfpxvLaPA+9hEqHJ+QXZ76lu1MrxOAHWjT8FrF8KXPKcQJvqJEIR9Gr9VJUIO2ydM+NZhAsu0zBa68Y4feRnsuu94hvKf5tvYd9JhAFcbK29M//98wAuXuC5FouoJvcGWYRUJJMkwkVUcnc08pnuA/NcBCb8gRyMRFiRRah9B3RNk6PNAw4eOIQmv/lOBC9KDVQP1gDKNJhxxrqGCmi2KYRYBfoeZPHY2s/R9UdisLp+zyF5rhRgLXKrnAoGq83zzZ+DugXT9GwhF03PVp+36hqbJBk0kQjpHKPVOEHGfKf62aqTCGUZHE0irDS5t2Ww9kIinGZyN9D+PNunAgsAm92HRY+zLbAnJndrqVJeGcaY7zPG3GCMueHuu3vUZFokYprcm2QRulXWIXohf2/EMg38WrRBrdlBil9jSIR7lUUovVjed5Bfw+RIc98UDxwkfe8Fbwv2YTnZd2CFRs04+xfaY2/nVKTzdQywXLJDpCzCLitoLo2VCo02ZLBiSoTasdow1G3KNEzPAmsXFb9Xnbdq8VXnawVYmYaqOlgUYK1ECrB2awKsmixCWQ5HkwjpNW5O75xFuLoHWYS7ShJXQ+wEAiz3PR4MBusLxphLASD/eZf2Jmvtq62111prr73ooosW2JwecCb3CFvlzLdzqruKwcofromQCBGxTAP/fFeZ0Gv7HF7HXnoWYVUl9wYS4eRIewZrfLjCH4PF18LSJEIXPCyxTEMVg4V5vACLvocHb8lWuY0/N4AsQq8PtgywFpFFuFcSobXAbANYz8f+2Ybypnkh5zVJ1qi6/7TIGVUxWHS/YwVY0+qxRNt1IrSTBxCQCImZO1IwOG0ZLGvh7UW4SIlwPi2yi9sGRDun9D7VhbFbMBYZYP0RgJfmv78UwJsWeK7FIiaDBWSDU9Vg4LZz0CTCWGUaOIPVNcCqMLl3kggjZXMB+mQnGau5EuTS720kQvouJofL9H30wqVV7ajIIqyc5BacRUgerNCkPduKtLE26zenbmj/uWUWGtWkbPn/vfBgNZUI6wKspiZ36nNrD8l+hiRCV6y2aqHQksEK1cGKLRHaOgYrIBGWLCKz4m8SNEdNDndnsHhguWiJ0HY0uU83890+tHlznwZYxpjXA3g3gMcYY243xvxDAD8H4PnGmE8AeF7+/3MTMfciBLLgQ81go5fyB86Z3Bltb0ycLEKPwepYqkF6l1xwcqSfRLiIMg1cpW7DYNXtuQYU3+XkaLVEuFcBVtvNnvdEIgx5sPL7E8OHxRdAbWTC6HsR9mSw2kqEMo2/DyoZrBYLKP4cVC1MKaBar5EIm+xn2Ugi1LbKCQVYK3H8PE0lQplFqCU5AdUS4eRI9wCL2jHeiyzCXVaAuMV5aJyoCrAGJBHGyiL8tsCfnht4/dzCPAaDJeSzqsHAPSzSg8Ukwt61ZdjnO0uEwrtE/185AWx9AZUZPxoWkkUoVn/8dzXAYgwWkH0Xrh5ZAHScyZGwfAPsIYM1QA9WKIuQ3rNzCjh8Wfnvp96fbeD6lW/OVueV52PHb8NgRZcIuzBYSv+U/x9Nqjd7XnSZBo/BqlmUaVlt6vtySdB5sBSJ0M6zyXgXNf24RYBVJREuwoPV5PnjgZSd5u27r2hPE4lwcqQ417Qlo0PHNXuRRdhRIiQ7gRb4dvGcLRipknsTxKyDBWQBjTNaV0iEcgXjVXKfdxvICZzR6CoRhkzuqyeye6WttCoPt4i9CEUwBaBscld8WhRUNWkL92BVSoSLNrlXZREG+i5V9AcWGGCNGjBYAc/UZ38PuPudfvHHEOgaRyvtfF08wGrCWNYdp9MAXyUR8kBVqeS+Z4VGu0qEDRiskMmdmGe3G0BPkzsv0zBayV8L1B2LlkW4Wy2BS7bdKRgtJEJ3XREYrL3YKofM9EBLBit/rrVrahtQ7gFSgNUEsSXC3TNQ958ilCRCnkVo2MDQx3TPGawIEqGdwV3Lynn5cVsGbouQCGUGDv+9isFqs0Gxx2ANQCKcb5eLtob6iufFW0CAZUa5rF2RRQiEJUKS+pr0CbqW0Wq7QZYfu8+EWvVM1352IBKhtuhw7egoEVbdU2KsnMldBljMDwVUP49tJMLRGtz0V7rWyAwWebBCwbvMIiwtsEVmZ1WhUU8ibJlVR/13TzZ7nsaXCElpSgHWOYbYJvfp6Wo6W5ZpkCZ3EyHAipJFKAITzmAB7ZmxRZRpmCsrcisZLCX4auL5kMdTJcIlBFiAUtA2cB38Xi+CwaL6RqOKOliAnvVnbRFgNekTLsBaazcxVtUxawPZ59qg0uReE2DtWZmGjhJhIw8WmdylRJi3Y1zDYPHxp5bBMoylUd5PxzGBxIy2mE8BWL3t81n2N37e4PgvGC6OGCZ3Ou5eZBHajgwWjRNVDNaAPFgpwGqCeSyJMPcjeVmESmfgmS5ZA+gghQcL6Mf0eHWwIpRpsLOi06+cyH62ZcYWEWC5VR+7XsdgaVlfNKC32D/PmdyXnEXIU59dQdsaBssLsBZQpoECrNBkVSURnrkF2L0/+72VVNs2wGLH7hVgRTK5yz5Xu1XOAMs0NM0irJUIacFTs2F4lYeNY7aVV3E3uT/UoDQhO+Z13D/IqJPgNfZUKhhN9iKk11STe1MPFpMIsRdb5RCD1eIeO4kwlWnYP6DO29fkvnI8+517sFQGq0oiHEWSCGNkEYpBzTFYPSXCRZRp0CSYJgxWk4e/qUS4F3WwVvM91R2DVWNy568vxIOVDzFVldwBPcA6xTIB20i1fSTCGAFWJ4lQZOR6f2NlGsZLrOTuivAerV+UNa2DRSb31RP59lSCwSpJ9qGFgrKAUs+3xczV0LPl7Lwojts7wKp5vrQ9B0Me3Moswq0iAO/twdoDiZAzWF1M7lVZhMnkPlBsfA544KPllXxTk7u1wO6Dgb/NmDeJZxFqHqyqBywv0wB0C0RmW9kDzAckCoRmO/rqKIRS/SjyYJ3wj9u4bRQUDSCLsG7F7J2Lmdwrswg3wvfEzsN9pynsrJBn3Y4BbRisBUuE6r0kBkvxYPFSC/PdLPCo2nXAfQ/r+4vB0iRC7udZSBahtvDLX1s90a6SexOJcHIk+1disASjHGSwFCbIzsvHk1nBqhRGVowIAVbd8+U9lyKAkoWm6yTC8brf5j4MVleJcLpRP2aSnLuoMg2JwRogzt4G/OEVwJ88Dnj3d/t/c5XcazrO598K/P5FwNY95b/ZWZ65spbv/1fBYEmJkPsiPImwQyDyN98FvOsl/mdpNfqe7wPe9eIWBwtlEbJAsg0WymDxFa5gsOR1AM1MtfJ4kyNZ27XCpQDwiV/P+pjGZH3md/O/dd22CCKIz4O1OgZroQHWnEmE42oGS/Ng3f9BVsF7F7j5F4A/eSKCZuHOHqxYAVafMg0NPFhUpgFWXxTsVaHRlfOya63au7GtRDgOBVhSImzCYOVt/8zvAn9wuf+8USBC0JiamBJhmwBLBlBqoWmEJcLRWl4jUUiSbT1YpkcW4Z9eDXz0l6rfI7/TWB6sFGANGBufA2Czh+/0R4vX7ZxN/DWT7cZnsgd4OxBgmVEWtc93mDxVkUXo6v7QA2bhyjQA7QMRa7MgcON2/7MUCG3cDpz5ZIvjBSRCmuS7mtwXsdmzJhFWMlgtTO50LydH/P/z4wHAfe/L7vVUYao2bgd2H8jqh3UFBfEAu7a6Mg0LZrBGzIOlZhFWeLCmm9nEC2T3dOOzwNlbgQcDfbSrROhNgktmsEYr5fskGSxABIKLCLC0ayA2iZiViue0rUQ4OZwxwCGTe11Wr7eAytt+9jPZM8XHodl2wZxkB0YpkIgpEdYGWIpEKBd5TfYinG1m3wtvc+s6WD0lwvlu9myeva35ebIXmp+jiUSYTO4DBD3oRx/p19zxsmFqJn43wGrvm7M6NqzwXJssQlfJvWOARabh+Y6/2neG6Fk71okkS/q9ZHJvEWBRcT0gEoMlJrvGEmEPBmucB8TeAKgF0Fo2Uf5an4rmdlb2js1FoBU6b5u9F9u0x8sirDBOq3WruIywW7T13vfo5+tqcvdqpPUIsNSkiaZggX2dRAgEJuYYAVZVmYa8HU1qxLVmsA7nfTAkEdYEWFVJLB5DuVUwQ0C26C153kgpiOzB0phrbTHm6nDlVhCZ2aktArQAq/VWOT0lwp37/fMGz8OeU6Bdv21UByt5sIYHetCPPSr7El1phoYrMaDa70KTzSg3qVZtlVOSCCOZ3Mk0PN8pPrt20g+w2rBOdsbkSs5gkZm/RbDmDYKLziKUJndF0nMPf4OHdT7N2UmqDK1s1OpWa9CDHbrmNpsUS6gBFpv0VbaUAqxjC6qDxbMIqxgsJbC0c18acgHW9eX30nuAbhKhCxoiSISwaF2w1E2qSttrGSw6V0QGq6pMQ5Oin208WOP1LJjpIxFqDJY2Hs+2fAbLjFFmsPLkjBhG71YSoWSwVvTXQwzWRAZYLetg8TINXbIIKfipG0ckg5U8WAcAPMACgM3PZT+54b02wNrxf3p/yycbs+IzSG2yCCEkwrZS2r08wMrPv3qyCKrsLC8h0XBysHM/wOIF+iZH2gVr3kAT0eSu1sFaAINlJqxWj2AXzMj3fWgrUPou21Qg9z5vRcBLgzIPXLUAJ39t5ThcOZJYkAFWVaFRtQ4WY7Dmu8V9PRUIsPpIhE7ejZFFiA6DPAvE20qEMRks7XmR52nCYDXdKme6UTC/mkQoFzxBqVsLsJTxeKaZ3BWJcBQri7CmDIrG9JXGIPH9NpUI+2YRtl0o0DNcx2C5HRc6bJVT6cFKhUaHC5IIKcDayAOspisxoCGDteKvxptkEXKPBW07EjpPFTiDRQ/+6vkF02Rn2UDVtB6SnRVyJWdIzChjRNpIhHygWQSDpXmwqso01A3oHBRguclPSoSGfZeoZrA6B1iCKZOreGpn6Lwrx/Nd6ntsFVNqEw+wQib3vN279ytSzcz33lBbT72vOlhsLRHuMq9XrACr5cTMJ9VSHSxWpsGx14uSCBuY3B2zXiMRugVilQfrbBHcVmURun7dokxDiMGSEuEyswi96xFjFY2tpTpYIYlw3Zc16XxNC9+WtspBuz610zDAomt2maFN2zfL6+KZfL4RY5U7bwcGeUFIARaBHuzjj85+buY+rFYMVl2ARfsI1niwqiRC8K1yWjA982k2MQFlBstJhPlrTZknyWC5gWGUTditJMIWAdaDnwbuv7H6PVV7EZYYLD6IyAG9YZmG0aQIBrzVu/XlQ0C/vi4erPs/nN0LgE3QQtqsk15dgHUsbzvr73e9E9i+13//dBO48y3Z75t3AvfeEG5fyYMVYLBccdQHZON8toQG5tkm8MBNyrX0yCKkhBJ+j7buAu7+mxbHUYznTcEDiSYerJlyrhjekyqTe1uJkO5pnQerKsCSJvdWDJbiiZ1vlyXCplmE938YePBT4WvRsFcS4bSCwQr1xbvfDWzdzdoiKrlXfVYDjV2LYrBofFg7mf2U/co7bwqwhgUpEW6IAGtypAGDVSEROpP7qh/gVGURlirdCg9WG4lw47O5Tn/En6xWTxTGUjpPY+ZJBljEYI2zCbuVRNgiwPrAy4G//d5mx1NN7lVZhIKeb8NgaRIhrYaPP6boW1r/oLa08WC9+6XAB35ctFsMym0YLKAYpGbbwNueA3z8V/333/Y7wNtfAGx+Abjp54C//nvh9pU8WNpEOy8GTKra7j4vPFiznSLg4pm+8vpGq2g1MYQkwo/9CvCXX9ncmxaDwRqvVUiEnCVVGKyoHiyUWYCSXFcjEZL0V7nZM5MIJ4eVQqOSUW7DYOX3iAejskxDMItQCbDe/d3F89YUrbIIhf/NmdzF9xsqNNpGIrRz4G3PBT7+n8ttNSvFc9uJwapRQLzntMU5KMBabRBgDcTongIswnQDgAHWL8k6qvNgUdG3o/VsRtW2JFIirMsiHK2VOzmxIV1M7nQdVMOGF2WUUllT5ol7fjBHMVD1lAjrAsfdB8oDceh4MjMHUFa4/G8Bqa3yXMRgEbsgTO5mBFz3Z8BTf8U/r3eMDhLh9j2+vKu128uQ0/olmdxFgLV5Z/Z+WTaCSpDMzmYBdFXdLslghTxYLjlA2WOPZxHa3axfAXqQ2ieLUAuwdk9n/7/vA82O08eD5X1/1v+8xmBZ5VwxJULteCWJsGI8nO8wVrDG5E73ftxEIozAYJUquUtpeq6Xadj6Qvs6dV0YLLc1klwsUeCk9H3HYOULGWurTd9bd2V/5543ast4tZtE2NqD1TLAKnmTqwKsYfiwUoBFoAfdGODQZYVEOGcMVlOJUAsQaLIxMsBSOsJsmxkNgSJwySXCLmUa3ER6BF4W4WgdIM2aOmwriZBN6NyDtXJscRLhbLv+AaoqNFryYCmTWV3dHY4Sg6UEWMYw9iFSgLV7pnydXtKBOFcbBov6v2wP30R6vlsdyDTNIqQBU9som98zT8oLeLDIo9g6i5COy/thjam+dJwdNjG1ZbAqAvtaiXABexHK3/n/m0qEjsHqIRG6+1JXpoEHUfTMBzxYtSb3GUoeLGuzAKJtAk7tVjkNJEJv/IfOYHGTOx2risGi55tfOy80ig79uLEHSywGG2c5UgAoC3CjfN4UYA0M3Gx5+HKdwWosEVYEWGMpEWoM1k42WctVRJ8yDa546VFfIuSdta1E6GWtyQDreA+JsOY+z7bqH/zeW+V0kAiD8s1IHLMqi7ChB8taYHq6GGxDg5Y38bQJsPL+LyVLvgWPnVZPONLkXpK+SHIKmKbnM38yn++wSVt7xvLvQZs0qxCSCOnehspClM6/Wxio+5jcAV3yGo2ZMZj6t7ZlTg9436cinQHNswjpntYVGqWgeXIYXjIDwFizDmUaKAj1sgibVHKnRRFjt2abWX9oux8tb69aB6sqi1AslpzJvUGANd/y5w0JSuLydrHgJne5uG+Aph4sJxEKhq4OLomlQYA1kGKjKcAicC/Aoct0D1Zjk3uoTMNIYbCqJEIZYPUo08ALSgLFw87pflr5NZYI50VGIy802kUi5Cvyuuvig0fwPaImUVsPVl1hQ+9cu2GTOxWHBaoD47Z1sGab+So1EGC5QbnG5M7LNABFf6f+LwM+lxCRM0pVE86cBViayd3d64BEyE3uNPFq1fLd26fF5NBKIgwEWHRvmzBY1sKrp9VaIhT+Ji1g0Mo0aAkafRCNwdppzmBRBqcbmxiL1ZjB0pJYFAZLSoRqvSdFIqyqv1SFup0SvHvY1OQeyCKcsACL72tayWCxv3llGnpkEdZ5Frt6sByDFZAIp4nBGi44VX0oZ7CsZRJhEwarwoMlK7lXFhrdyTuf7OS0sqIyDW2yCEWARcZ2XlCzrUTIJRzOYI3GeyARNmSwgDz44wNwlUTY0PPhnatKIsyDYqA6MG4rEVKgE00izL1NksEKSoS7HSRCxesChCXCUh0sLhFWMVgtAiwqL6IyWPnvpz9WVKkOHqdmdV3bjgppuirAgtJ3+6CRB4v54kLgWYS1HixWB4teKw6U/61CXgf0+xUsNFpTpkEzubsK4j0YrKYSIV2z9GCF6mCR34ozWDPlHnJsVEiEXpmGFv24sQcrkkQo+xWv45dM7gPDVEiEs80sq6mNyb2JREhZhHUMFpcIvTooppoJqWvb5Gj2k8yNIyXAaso8zYVEyE3uK8dzSr1hG1sFWAqDZS3wgZ/ItgOSx7MzlEzu1lYzWG1M7jZnTkL7xJkmEmHelqYBlgt0xEbkpeKENSZ3KRHSKtAxWFIilAFWU4mwisEKVFHnZUCkRBhksCbQWQmGrbuA9//rrE+UFh4KgwUAp97rH+PU+4Gbf4mdW0ruyvk/9l+y1HgVFdI03bc6BqsuwPrcnwGf/k3/NWuBD/4b4MFb8/9XMVhdJcKKZ2i24XuwAN94XWLNWjBYMqt7Ps3+JiVCrZK7DLAoeOgjEWrZdV6yQkAilMyWlAhd3cR1ncHS6kzRAkplsLgHq0XQvntf0Z6qz0mJsHWdrsAiJjFYAwb3AqxdmP3cvleUaaiTriokQhdg5XWwKss0kMm9xoPVSyI8m9PgjA2jjt+YeWIToFZoFGgRrLUIsOYKg7V5B/CRnwU++d+VY8zFQDIVE9PMfy/QsdCoVgeLB1gNJMLZVrOyAPQdSYlQbvHTmMHKN+imla8zud/v3yvPg5V/NjSY8QBLyyKsY7BKrC9jsKo8WHV7yN35ZuDm/xc483EWGGkm921g/eLs943P+se47beBD7yMvbfGgAsAH3w58KnX6G2qCuxdVpni82sjEX78vwIf/nf+a5t3ADe9Crjj/5TPG2KwGkuENYVGrc2CKRlgcfYlRhah+7nttx8ImNw1iXBRDJZSbmMuAqxSmQbxnNBxOYNFCzAzgdovVJN73lazArdJe5csQkD3iRG6mtydb1iWL6JzpgBruAh5AWZMIrRTVFaIbVWmYbd4XWK2IzxY9J4eZRpKK/UN38zY1eRuGIPlpIxRITk1lRvblGnQTO70cPPtgHg75QAcMvOWJrqGEuGoZqscoFmABTQzuockQv590HGd8VXrl/lrVFuGjksrXFi/AKjbVomZkYPFHzmDpVRyr2WwZsiyuSZwZRpcIBQIFptIhG5LDdYPJlqAtcPKQoh7N9vJPi8XVa5KuBjgZ9vZeBJ6tqoCCU8ilJXcW5jc5zvZxMrHML4PKf+pHU9+X5VlGmhLGhP+LmZbWfv5VjlAwIMl+rVEkzIN9L3XSYRaJXfnweqYRWgmET1YInhx13UIrnYWMViTI/o9I4aa91PKgh2N0TqL0NosCHXzS8UisavJvUkWIREGyeQ+MHj1WOhB3yg680ourVV1Blc9PBRgjQqJsI7BGq+hRNOSRNilTIOTCBkNbybwdmxv68HiEg73YJlx+w2f3epJyTaTmG2h9ADRCvPUDVk7Sh4sPnFM9QGZ3gvUSxIctVvlNJAIvQCrgUwoJUJa9Y6FRDjfrWYS6LxrF2Q/d09ng+XGHYzJZe3hEmGVzE2vV+5F2MCDRQsKJxHmk3bIg9VEIuSsX4nB2vXfR8+9PB+vKs//Hhr8aYIOPQ+SgdQkr74S4Xwne3Z4QVdXR418iRUSofu+GkqEozWduSRQINVIIqyR7CtN7lRwlKS0DpXcHYPV0tvDJfi6AEvuAxn0YDVhsCjAOqr3i5BESOdsW8l9eiY71qHL/TZpcNfXMuPX1c+qCLCcLJ0CrGHBSxdmVDVnsIDqFYwbdDWJUMgdtVmEgTpYvRms/DpKDNaUMVgdCo1yiRA9JMJGUqwiEfIJ7MwnFAZLTBx8QNYmlWhb5cyLLMKqwJgH5Y0YrIBEqGURVhnD+ZZJQDZQ7p7O+seJJ+Xt4QEWkwgdQ9CAwRopJncXFFZ4sNwzkzNmo5VCZteupQmDNWcMFs+cGq2UJcJJIMCi/5OcW5Iv5AIg/05Di5fGDFaFyb1uMqTPOPaCtcct+KrKNLSVCNd05pIwCwVYkRgsV6aBAq38e+d7EQYruQuJsK8Ha+VYjURoWDvomtnil9oFlOW3aVWApTBY000WMAqJkPpX20ru1L8PXZa3sSLA4ntravc/BK20kDvmLGecG/j+9hApwCLIgncAY7BMvZ8AKFPSHDTZNCo0KiVCWsGQREgPXosAixcaBXIP1qSnRCgYLJf9wiTCLgFWZXbS1GfLCDwIuPf6MoPlBVSCwdIyseoGdI7KrXKULMKQREhBThMGq41EWNV3eb8YrWbHJX/GeU/MfnIGy0mEPMBqyGCVzi8ZEc2DlZc2ofOZlWKRUjpfHuiaMVC14SstmubT4vopSaEkER4tfveaJhgsmsxDq2v6ToMSoQiQaxksxf/WtHQJD7AqJcK6gDjwnFLW7mhVzx4lEFPFt8oB9CxCI4INiSZlGuQer0DWv0qbjFO/y9ktkr+AZgsu71iMwVLrYLGgQUqBIZN7SSKsC7BEv9i6k7WPByk7xTnbZhHSGHG4BYM1astg0b1SyjTwguBAYrAGh+lZ3Qsw28omziYbLLfJIqwsNCqyCD2T44gxIW3KNCgS4WjFH7jaSoSYCw+WEmBNm0qEefvGNQyWLKxJoAd8tArc+55swuODRBWDJf/WthRGlUToebCqJMJpYahuUguLS4S8zpfMIpxPmQRXIRGOJkVpDZqAT+QBlisgyLJCOYPVyIPFtvDgfweKoKQUxOQeLE8iXC0WKaXzEYNVkwGlSYRagDVjDFapCCrJTlv+30NZhPSdBiVCyWApgU4MiRBg/jqUJcIqD5ZMAAkthPheqlWSf0ginCkSobY3IIeWjSf9cc6rJCRClakb+SwOPQOdGawaiZBvUB56luskwklIIhT3jAfYXv/ZZUFdyyxCCkBJIqxK1OFZsZ0CLGURQ+ejPpQ8WAPCfOrTi9LkPlpjgUgDBmu+A3z6t4C//vvF31yAJRgsrSOQRKh5sEzXMg3UOQMMFjFDQDPWyVrBYM39wVCTCP/mu4Bb/nugfRQAHq6+LjehKQyWmQAXfEnmw/KymDQPljIg03vNmLGELSRCCszqsgjp3Jt3An/6ZODsZ7LXKMDiDNb1P+SXAyDwiZrXoxorEqELsALMGZAFLVQclibg84RE6J2T3cOmEiFvF1B8h5NQ+6QHixisSeBapiixsho0idBoDFaFB0syWKHB/4M/Cbz3XzSQCIUHS6vbFi3AUhgsbcEn719TiZB7nTRp2L0vD6SkNUOTCLW9ATkqyzTQd0USYYssQjqexmB94v/LxjSvHTPgDx8G3PZG/9wTEWBt3ZM9+w/cCFDpnRCDJV+XEqHGYFWZ3F2ALRIQekmEFGBd6rcJAO6/Efiza5i9gBn/20iEpWeMfRczEWAlBmtAcA+6spKans1WAaMGjAZf3d/zriL1GSgm2lKZBmXAkBIh5mzln+9rZ8bhFWRV27wsQjEZUZsaebDy9qh7EY512efON2f3RW0fMVhNAyzFg7V2Ejj2KODsrSgM0dQ2MQB7A/Lc/xsYg9W0kju9X07SlpvcRWD8wM3A/R8CHrgpe41YP86Aff4vgLvfWT4nD1x5XbW2EuF8F9kAPy62N6INnY8/OvvpKjSzczaVCCndm3v9+N+BMIPlJrpJcY3Og6XJnVPfVxgauB2DxaTikEToWBjZNhlgUf8VDNanfwP43B/XS4SyDpbqwWL+S+fz5DJoBwaLZ4Xyc/FrkO0IFXokbN2V/Vy9oNqDxZkugFX0V9LtaxmsiixCyWRxBguBLEIz8sdGYiD5e7/wl9nzyXH6o8DGZ4APvNw/98pxvw7Wg5/Mnv27/or1WWKohNxftxehKhEydlB+j/S38SH/b30kQuqPq+fn/2fXeuoG4L73A2c/6x+TFqVN62C5Yr5KmQZ3vcfbtXvBSAEWwL4cxQuwezqb+BoxWGzFNNvKfzI5wkmEu2z1H2CwPIlwBjeQcjakbxbhaAWdswhLqyzmweIBiqzDpBXbk+2rS/8GdAZr9WS+j+Tns2PQgK3WwaqSCNnqtalESPdxvIZSFiF9ZzRoS8livpMHQsrERVviSPDviJv+RxNkK1MajHdrqp8zWYAkwp1TWTtXT2aLi20lOGhrctc8NCUGqyKLkCaRUYVE6BismslhpjBYo4kuEY7WimfWOwZ9hxUM1ubngY3bM0lm+978fduBJBjJDon+acb5wsr4ZvzeHqwWEqGrWxbYO5JAAdzhy6s9WPzeA/m1GxFg0Wfp2WnDYInAygV0q8V7Q5s9ywBLY7C2T5XHM9pW6eQ1/vulREht2bqrCLDctVKwzbYh837O/PvAtz2TldzHhxUmkgcqPMDaLQdYjQ3o+TlcEhW7VvLayS3KSCJsy2C5BRm7LurHq3k9v8RgDQjObJkHH8QeTc9mE9nK8WYBlguaWGDFTaS8jk2IiQGgFhp1HYZlpPXKIpQS4S5cENdIIhTmU7A2ekZ8bi5n90VixgKsLgzWdh5gHbq8uA5uOHYsQG62Dnqw5uH2h0DeHyDrO1IipO8M8ANjCsTI2zRSVmazTb2PcJaRbx0kpZRaBmta9EmSCHfuy+6lMdnPXaXEQNMyDY69UxhgGVRoexFSgOV2Hmhqcq9oF/fxeRKhkkU4XtXPFyrTwL9Dqsk228hYVYK2gJHbh8gFgGPlIALBNgEWSdPcg0USofD/yN/5/+skQpIgD10GPbmB2sOlImT9bbwuvEoNJUKVwRJlc9QAS/NgaRKh4sHaua88ntF3fuyR+fuJwTqmB1jUHh7ouWdZkQg1HydnsOg580gDcX2u3MGqWHj2kAjpHFodLGqLHC9IIoziwcr78cqJlu1eLFKABZTNlsZkkf90I5tUJsfaSYSzHTifB5m8SwEWpXcrHYEkQigBVmcGS0iEtFqRRSjH6+FVNodmyvXofG1CrWGwzCjPpmkQYGl1sFbPL9KEgYIZ4ZLgODeTegOykAjl4FoHHqRIFoSKwxJ4YOwYrO2CSZKFD6cBBqskEQYCLK84Z8CDRQP5yvGsv26fyuRWIPtZx2A1NbkD+n03k3JwQ5+npI6ZCLCqKrnXTQ48i7DK5E4SofaslTxYikTIN4m+/8PF7+oChtihgMk9FGB519jBg1UlEYbKNNRlEXoMVgXr5OTZSfHa+JC+5UkriZCxt97PpgyWkAjnO0WxXX6enVNwSSaEe9/jH4sk+MmRfLFk/TYB7Lmv8GDR55yfkgV2NNd4EiHL0AwxWKM1/9rnOyjVwWoqtdmKAIueXRoneJmG0bh5MFRVpoGeqdUT+QspwBoOpNkSyB+Is9kXxyXCutovQM5g5Z2+xGDlD7ejTQMMFtWQyV4AShJhxcpQg+uch4rXzIRdFxVUPZG3r4bFkoPAnLNELJCUDNa8IsAaBdgCjhmTCPnARqwLpQkDjMFiEuFoDZUSofNf5P/aZBECZYmQm9yBbAJVJULyD7HvlTZx1fpISCKUtPt8ygJNzbe0W0xwK8RgnQJWci/F6smAB4sFJ8FJb1704SoGi2fXlj4vGayKPsKTDara5VVyFwGWq52U9+fRWh4UywzH/P9TwWDxFPJ7ry/acvrm4rPas1UlEc5lgNVTItz6Akp+SysmP94mefw6BmvjjowpXzlePU5J3yBQZrCaBlhNCo26YFoGWBpTxwIs8iSOVgWDlT8XnIm+/4PlNoxWyoER70+GJMJQgMXGVq0or1oH62z2+3i13C/kYtO9ziTCtlmETiKsYrAES0pFgTub3BWJcCVJhMODZLDo9+lGIRE2kYz4iqkkEeZmZxpMKKgrrZ5sEWxoEqHz83TwYI1WfYOnx2CRSfGE3+7wAYtj0P/dtSgMFpUSCEmE7ppFhtjmF8T7eIDGA6ycdTnEAqyxIhHSoFJZpoGXFmiRRQjkAZwwuYcYLD4w21020HKJw0IdgPj3o0mEc/Jp2PoyDSWJkDFYq+cHsgjberAqTO58hwPv8/MiWOcMluwj7v1NswgblGlwG+iu5lJKDYOl7ZN26nrgomfl798p2qUlkZQY4QgS4c79/vM238kCZjvPgiygJoswwGC5+kUVEiExyZUm9wCDpXmw+kiElQyWwqC4wF4EWGsXsWNPy8V+7/8QeyYYi8YDLMl4uvawQE8GWHxsdcdh36tmcp9twCVoNGWwrCIRamPPzn1lhcMxWJoHS0qEwoMVow4WLVpo/mrKvC0YKcAC9ABrfLgwuU8Yg9W0TIOTCAMerNDqf84Gaq+ej/BgdZEIaRIh0Ma4QPHAUhZIXSZhlcmd2B8AJemhSiKU7MQ97wH+4NIs247g+ZuYz2j3dNb29YsYm8TLNPBBRTJYYpLiQUFrD9aqCCLzwJrA5S0uEXLJliQVN3kHPFj0Xc13is/wiUiylo0kwjOZIXuVB1j35+cUEmHVfpr0ussi1Bhg5q8pZV9agORVMymeUfJKhTIi20iE3IvnyjQIhqFWItwS78+D+o3bs/t4+dcXnzl8RfZTW7zwBQCAkrQelAgDexFaC7z56cCHXlH8f74LHHlY9v/NvNhklyxCKv5aJRESk1xlcuf79BFKAVZHBouuF6gOsFQPkPBgUYLC2gVFm+mZAIo+cP+H/DbQuc1KsdiT/QUoJEJXUFQsXjkDPxFMGJDdL2J6OYM1Xtevz42Fgt2aMzabxm9N3v3TJwMf/UXxopAIucwrJULuwWoTYNkpAFamiI8B9EwlBmuAkBWFgZzBYhJh20KjjsFiHqzRWDzcUAKs/HNNPFhtyzQYEWCNNInwePaTF/vTUBoEpAfL+AyQZG1K7WMBFn1m604ANkt9JvAAjc5Hg93qyezcVItFY7DI2FlXaBSAvn+egjYSoSdDscncBVjsnoVqfgHZxEh7BYYkwtKKr4bBojIRm3cUwRv/PkJlGpp4sOQEQ38HdAaLs6FNJUJncq+TCBmD5STCSWYRcJXZeS2nCokwlEVI92r94uJeUnCjSoRtGSy6/oAHa/OObMuojdv99rk0+rzdfHziP+XvvI2unl/ge9+4o2CSqwqNBhksvgjjrHgdg2WKdnvSV10WoSIRcg+Ws5AcLYI3XquOnmOqPQUU94qXFuHXXAqwFInQM7kLBkua3MeH4Mr3UJudzUTsahA0uU9R8mCVDPIzYOOzwJlPll+nY5oxPKVBMlhdt8qhAFBjqHdPZ6+nQqMDhNwTi37fOZV1isZlGrhEGPJgrcgPibZQgLUqOjmrgwV0YLB2CrmDYNiKx5VJyCdZb7sKBdogwCdMAN5GrzJoKLWPAowVlFaePK1cm6Apw4dYFxrctUKj4xoPlvQNNTa5V0iEMotQMlgzxmCN2CRSyWCxAGu2zValbC8+l9jQsEwDfffz3eJeculi90y2CBmtiO+hSYBFE4MSILsJmwcxLFgvSYQVHqyuhUZHK8WiCmALnVUR0NAxpMmd+VoA9hyvFP3xcB5gqRIhm6Bk2+3MD0JCJnf+GZfBSNeTv98toMT41EYipO9LTTSwGYNFEmHVM6QxWJOOEiHPgLMzvy9JBmvMx8AxSmOws3NQsMIkODo+D7A4E03v4wyW3POVtwUoxnovyGXBUhOJkF7nDNZoXaggdH2cCRKvOwYrwAJThfjSdl7seZWJCu6ZEnOBk5obynlEEmjP9/RMrjTVsNd7jBRgAWGJcOvz+evMg1XFaHBT5axGInSfkQwWK4Zn+IqMOnCPMg0qgyUCLBqAawOsKgZL8TBJSaXUPkUi1LKePHaIAqz8YSff0OF8cOcMllu1NcgiBGOwekuEIouQX5+XRciCg1KApQTh8x3GYAWyCBsxWCwDkhgsoLiXXLLcPZ2XLFkJ1CoS0AKsqTZ5jspBjBUBlmMfVhowWA0lQp5FaFYKWwCAWolQlmlwTBhJfDzAyvsjMVhVWYRtPVghkzsFWPJ6KIgujU9agKUwO1kDwt/B9r3ZuZxEWCGzt5YIKyZj/t3zvg+gukxDIItwxCRCule0ULFTf0N27qWka+AeLJ5M5J5tRSLkDJZjoiEWiLRYkgFWPtbReUgi1IIRngzifd9sHAuxwLQ4kAEWH/vld1iqg9VRIiwFq5zByr3Sddtk7TFSgAWEJUIygjZhsOYz/6FytDFR8PmqqCQRSgqWS4QoOiCXTAAEtwsJwTEkLMDjexHS4OACrA4SIUQbjcJgNZIIBYPF6/ZoEiGVESD5QzJYrtAoky29AbiCwWoiEXLvQhOJ0MlL+ftoEnQSYQ2DRRN0lUTIfWe1HizKIjxevL7KAiz6XqdMLuf9o5FEKEy+gGCwAhKhGcPLMpN9xLsWmiBaSISSwSKmjEuEVVmEIYmQ+oBZKYKNI1+U/dQCLCexVBQaJTQKsPJyAfQ9yQUUlRfYrQiwSjKL+E60/sRrYAGo9GC5ex/Jg2UCAZaT5POfvD+pQZtksFjgBGTv5/uFcl8VLRZCDFZIIuRSmZMoFYuIVpR3GmCwSpnoOSzzKnoeLO71CwQqFJDL/VL591QKsEgiJIZOSIRtyjSEAiwam+qe/T1GCrCAvAOYYnAE/IKXTQIsK1ZMnIJ3ht0WDBbP5rBMIuRZhG3KNLgsvTGcZMVN7iUJoaFE6BkxpU9sUg6W6hgsyhDjJlUuEVYxWBQU0ITmJrvckzGawKWNN/JgdTS5h7bKAfyJySVC8ACLnXMaYLCmIsAKFRp1E1heITtYpkFIhEARrPIJaPdMUROuK4MVqtJdyiIUDBahLoswNABzcInQigCrxGCt5qU16iRCwWC5fe+YRLh+cdYn1RIoHRkszYNl59n2JED5eoilnG3lf6O6TGIhROf1msglwsB3QM8qXXPVIkUWGgWUOlisj9R5sHhFdDkeA0WgxfuTmkVIY0D+3DqJkO20EJIIKXPPfRe0sBUMlvv+TDEuu2KvtMhTGCxKovCyQ7fKAdZ8R0iE0mulsEdcig55sCgg5wyed/xRWealucQtsjmDpdz/ECoZLEpGSwzW8DA9mw2uhnlleE0sXqYhOFiwB3q+UwQC0zNi8pMBVsCD5cop5CsbzeTehsFy0b8pBnGtTENTidBNgGzgKJWS6Mhg0fG0vdNUk7v0YJFEyBmsfHVGK2ov2BCTFJc452xQuPX1ULNq5jzAEpXc+VY5gJAIBYNF/oK6LEJiRZtKhDTAhxgsTSLkDJYLsE7niw3miQIqFh0sMJhUMFiU/OEFpjz44v6jnIVVg0XpwQpJhNvF+/k9Gh/O+ped+0yyURgz+lypDpaYAEeTQrJePZmXwqjwYJE/qI7BomBByyI8c0tWGNOMwwHWfFskLdDE38SDNdLvCeAXGQXqgyKgIYNV48Hi3/28woNFY6CDYrJ25UGEREgKh53qJvfZNkp+qjoP1qHL8udeMlhcImRjq/NTsjGGM1gj1k84gyWlQKpBFZQIA89QSCLk7GZIIpRzgWPpeJBngU++BvjIz2dZ5Bw2N+G7xKwKiTCZ3AeE+ZbPXgHC8N5EIhQPtGOwTrPVx9g3WALKKrFOIqQyDUrdoCrwidSxY1oWYT4A10qEUpKa+ZMiULBFAAtUdgNBigyw2OTHPViayd0VmcuDw5PXZjVrjj2ieJ8btMao34uQe7Dyv93xf4C/+XbgnneL+5Czi9TuVhIhMVi5cTQkEcrBgiYxYgmkREi0O2dnQoynLNNA4B4s6nuzjey5kBLhIhgsTxpSJMJYhUY5i8L36ZRZhLLuT10dLDqHWQEu+BJg/SHZRuQrxwNlGijYpDpaVQEWlywVifDMJ7Kfxx/LUuTJg0UM9ZbfjiZlGjAHwPdDVL4DslWsX5z9rPIxqh6s0FY5I1SyHe67VyRCnkUoLRpqFuG8OB8Ar1I6nYszOFwipKDG2UVEUMAZLDMCLr4OOPEkn02SARbmxX1wLJqSRQj4/WQcMLl7cqryOt0X3l4CBeWzTX2xWykRsj5mxlk/kizamU8Af/cPs82y3/8v/HNXMVgkESaT+wDBgw8C92OtHOvAYOUPwG5LBqskEVIHFOxQaVPhGvBtECjI44ZgN6EcAWCam9y9CV0yWCt+YOXaorRbBli8ztLu6SIFWm6kzI9Nnz3vccDfvws4cmXRVjvLBg/Kaqrci5B5sGhQuPfvsp/yvshUcy1QCDFYJYkwl2xdxmWAwbr3egAGuODp+fvqJEJisAIBlioRUoAlsptI5uYMVqsyDdrkOfZZGcDvX56kkweLvQqNVkiEQPZ98OdQLTQqgmSeRAHAM7mfvAb4e18ADl2cjSVVldy1bWg8bwx8JscbP8TzsHqSMVjM7kDt9grHNjS5u2cjELDvns7uAQWatKDR4O4Z+36DhUYbSIQhD5bHYMkAKyARcg8WsZR8RwTPg0XlVhQGS/qGuAdrtAp82f8CrvlF8Z2yxSBQjF8AvKxtd/6qAKuCwdJM7o5NDEhtPCjnQSb/nmSpDS2L0KkEIsDa+Gz2c/X8MtNLXldi6bw6WMSuJ4lweODUKIEzWE02e+YPNDESQC4R0pct/CRAecDQJEI7h5MCXIC1HvYzhdrnAisK3hSJ0Ix9L0oIqvmUrXABP0Dh900LsGbkwWIBFg9UiLXRGCy7W6yIOPgqjCYp8jhVZRF6DBYFWNfrbZer8JJEaIFgmQaSCPP+Iiu5h+pg3Xt9xk6sByTCkZhkaAVd5VsChER4ojieFmCpPhl5bIXBqswiDDBY0oNVxWDxAEuTCeZTn13wTO75omq24TPJ8nzWloNgJxEqHiyOWolQYShocUAIBViyjtLKcUUizBmskkTIAyzKXg55kxD+DpzZmNpaV6bB+AsQmpxpvGsqEZZM7iGJUGOwAhJhiMGys0wic1XLWbmVkWSw8qBAY7BC2Yx0nzWTu5dUlGO2WQR/HtMpaim665sWY40s0+ACn5BEyPoMDzK9LELGQlpbLMa8cYQHcjzAytWKY49SFrO7/pzlebDO5OxsMrkPDzxVnRCSCEO+J1deYd3vhFwipJW6/0HxX0Ui5BSxkwjXxUReAy4FjRiD5Zg55hnh2VQhaIyJZGu0Mg2AHhi6Ol08wGKfIZnQq+TOaXgRIFPb6H1uVSgZLBNmsJycyEzDpe1cRIDVSCIUhv86idBrn822YLngaT5b4hmGRRbhaBJmHHgWIW21MTlWfA/uHlp2D1cEy6D5oax/L+vqYI1lgMWDL0UiDG32XCcRygCdB6GcweL16GSNLn69XCL0JmXGYHE0lQhllmuIwdIkQh5gkdTuJML8GrlEuHKeH2Bptbjo+O7ZCARYlAhB4IysBK8fR5gcAmCL9jbNIgyVaRivF8fitbKKBirHFBLhTAZYuQeLChpTn3YSofBgmZUy61JqC/dg0X1mEqGzmQQCrBCDNVKCkVCZhkYSIVsc7CgBFozPQmrjBGdkZRtoIX3sUWWbSkgitJZJhInBGh40Bssr2XC0GAjqGCzaNZ0gJcLWWYTkb9IkwjYM1k5xbo3BmjEGi9cDCqFUn4aCGB5MKCZ3IBxg0TYoALxK4UCxspkrDJYm8dK10PvsrBiAuQdLbnhK8gC1304L0zBQDmrrJEJtqxy5353MIqRjagHWxu2Zz+WCpxeTcROJMMhgsXtnTDY5kv8K8Adax2BNhMldmfQ8CRmswnmgiGQoi5Dv31l3La7mEAU5SrtkFqpnclckwvGaHxQDfjs5g8UHf+on0hLQVCK0DQOsOgZLXs9oLWcYtgsmbfX84l7xAKtk/hYSoRpgnW7HYJXGXeHV83x6HSRCng3emMEiBom+S1FolDxYFGCVJELJYHEPlpAIXTs0iVBjsJTgV6uDBdQwWIoHi8ZIui9ZQ/17UykR5uoFzwTVyrl4BU3F/d+8Iwv41y4qz0GhMg2zjewY3IOVTO4DgrqSOlL8HLHAKOg3oRUTC8xGK+UsQrkar8sidB1QVHIfd2CwHHOleLCkRNiUweLp03yFC1QwWBUeLM4UznfgGDtVIqQJJcBgcbqY6G/yYDl2Z7U8yLjVVf5eqikENJMI7ZwNJpLVYxOTY7BEgFVisFj7qC0nn5b1SzNCbRZh3f59vE+uHCtKNNDx6L7MGYNVVweLtwfImai1cI2jSolQySKU5yTZjvdpbZCVFei5vNxUIvT6MguwvAULSYRyXAlJhMLEPBNsXl2AJbPQAJawcpaVKFjN2e8ttkHu+YzBYmy+6sHii4+QRHhctLWCwaoLsLzaW1US4S58BosC5MNFO0MerFAWofwuvUKjp4psZVUiZPYFL8BqKhGGAizlu9HqYAENC40qgRc/TqUHizFYPPvaY7BYkCRN7tkF+efYuCPLQJ0cyT4rt/jRAizHxB5PDNYgUeXBIrq7aRYhlxbXLipnEXqV1NfKA0ZJIhz7D5gb4Nb8yeLudwMf/vcV19gwi9CMs4FErh4+83vAp16b/X7zLwJf+Mvi/Z4HS0iEGoNFLNRn/wD45P/IX5MSYS5tTI5m3wExWNpmz3xS4FAlwnzAl5Xd3TFZQEQMHPmvqJ0cksFym/UyicPzmFRIhOSVovZMFQbr1PXZtZ7/5KL9PIuQgi47b8ZgcekYyAYpt00OxECbX4s0uasSoQiwgAoDs8Jged6bBhKhe3+NRFhisNizH5IIZaHRUIBFFbn5eTSJcPse4K++IWNGvXthCuZEMlg8/d4LNCx7TQRYlDE43WABx2rBftPE5AVYMzaJBwIPAI0lQjPRmUTAZzIIJQaroUQoPVh0/yZHGGPcxoNVIRHOc5P7OkmExGDlEiGXHasKjdYFWN4CUUqErM1aHSzAzyIsea2UMg2caKiq5L5yIvtderCcusKe86kSYM1FIOcxWJ/LsqMnh/MxjI8JtIgRwSr1Y68OVqCf7DFSgAXoKylardAqsKnJXQZYsy3WSYSfZLxWfrhL2znkK1NZpmG87stln/4N4KaKAEsr06BKGmPd5H7Lq4GP/5fs95t+Fvj0b+bvJzPmvBxMaGUa+Llu+W/Ax/5T/vftgi0A4CTC0UqeUUISncJg8UrqHCV5a1IEMFUSocdgTbOHfv0Sv+3u/YLBkl49K4NORSLkbIeaRchXePkARIEcmepVTxzPImzIYD3y+4CHfw9rryYRCgZLlQiVACu4zxwxWHzC5gxWA5M795tpq3YC7z8UxLssypYSoZmw70iwZ7xMA8flXwec/8XA5/4YuOv/+tfrAntxPslgeckjLLDkjC7gFw32Cqfm7DcF9ivH2UKISYRRTO5VDNZuedyVyRC8j9R5sBpJhOL7UMs05DYBKRE6SX4jO9/aBfn/eaFRIRGSoVwrNFopEQqTu3seFAaLH0ua3FUGi0npJQaLMUvu3AzTM8DhK7K2eR4s1jcoA3C+q48TJSlSSISHLvPlet5u7fkmJtar5J4YrOFAW0nRYEuDVNMyDVwiXL8o+0nBQWk1rjBYIYmw5MFaz85Jr2/eAVcBXW0fewg9BkuRCMdHFIPhju81oFVDH5P7fJtp9TnN7ZncqXQDY3W0Su40iElwqYiMlcRKeTvK84eRXQNNDrMtYPW88vn5dUlq3Q0aFl52o1doVHjRSlmEmsldmGPJHF7nwQoVGpXs32N+BLjqu1ib2GDGAyxY/xil4zZhsBhLVTKSc++N9GCt5O1R2lBXaFSa3Pn107M7VSRCzii5kgfH/UKjZgVuSA0xWBd/JfCsPxTXCD+I0kz1tRLhBGWJUPNgrRbs9/Qs3ObdKoOlSYSsjaEyDVwirNvsucRgiXIeTbMI6Xt0GbRMImxbpoHkLh4s0zjE2zZe85UEJxFKBov3SVo8ybZwBovOb5AtqLnJXXiwXDKJHH8gJEIRSNXuRVghEa4cz4Ioz4PF2M3DlwGwmVfUC5CYmsGtA26hPAM27ywkQqAcYHmZ7/nxeB3EVGh0gKgyufeVCIGiI5qxX2hU82CFCo3KrXK4wRkoJLRKjwIxWOynzCIkiVBulcNre813ilUDX1nSys9dH5vUNZP7fMfPNhkfKgIlqoPlMuum/mf5tTZmsJhEyDfnrWKw5tOMKSS5JZRFWKLW2WDp3RNWU0kGa00KjUrGSUqEzrsxF0EHk2s5NBbBb1TRBncPRdDQlMEKSYR1hUa1LEJqu7sO+h5WUCkTSImZX3/TLEIeYM3zkgIhk3uddM2vN8QOzWf+d+QFGuTN4QyWDLCYREgM1nyb7WDB+lwlg8Um0aDJXZEIqwqN1prcW0iEWhZhnUQYrOQuJELuo6LFJ7+XdHxXPZ2x66FCo1IilJXc6fUqD1bJ68iftzX9WfDKmdA5ZaBWJREey2wEpSzC/DNUAHnjDl0itDP/PHRt23dnfyOJEPCtCKEsQk8irFhcLQEpwALgac8Ex2Dlg0VTBksNsO7PfsrJScpTAFpJhEDxcJMJPFhGgnltmpjcSzVIdvKJPPf2eAwWGwQ8rwib1LVCo7PtbCClrL4Sg8UeqLkSYLlBLGBylx4sqkdD3htAkQj5JJK/d7adf6+mIoswb3dpYJKyKZusJYMVulaN3nefWW2WRdhUIpRw/YMzWOJeNzG5A/k+fCEGq2GA5cktXEbTGCxlMvayUKc+g+UGdc74rMBJdsSYuZpS5xXPg1sM1DBYdE2yfd6kKoIXKRGGGCzOBABhBotq6E03igDLkwgrGCy3kbsm084z2bEkEVYERU1N7k32IqyTCEusEbLvQnrEnETHJELe72Y8wGIMllZotMqDNRYBlicRygCLGKxAgOWymLlE2ITBmuvHCTFBlMSwer7Y8JmNc2T+37wDakHi0qbSTIWhz2sMViiLkEuEyeQ+QEQxuVdIhDzAKmURNpAI5zOAe1L432db2blpi4rQ9jmqRMgffBqAJ3mAFZAIXXCwUbQnZHL3pAeNwcoDLBpMJ4f8ydOTCKfFZ+QEZQNBgsdgTQWDRRPyihh8mJeAVt+z3ESqVc8vebDEgFbypa0Uk3UowCpJhBUM1ngtD36pHYEAq0mZBg28jg5dS12pEf6atzdajQfLzuBteOuuR2QROpaTJ05oHixNIqxgsJz/J5cIR2tw28Lw9lJg5zxOmwqDRR6smsDftYU9O9q+jDLAkvdppEmE+dg1lQFjHhTMzmZBJff9cQarskyD0p9oMuQBVtVmz1pyituzUiwu6iTCUKHR8eH8ebc6g8VZHNcuRSIcswxnWiRQRiZnsGSh0arNnkseLIXBkgtsaXK37LkH/P7mbZWjSIFeUFczjhGIoVw9WS7TQOeifSg3PhdmsLwyDXkbSIUJSoTTAIOVS4STYwCU610iUoAFBFZSZHLPB1FnXg4NFhUM1u79+TGk3LEGwMJPRd0uOj99Rt3smbwKW3lwRavrCgarZHJnWYTc5K7VwSKJsBTAcYmwoQeLD0izTUa5r/uTJ68h44KOreK7cSv2hgwWTdbzWXlAJkgGiyRCZ3YOSIQlaj0UYK0Wn5PHCkmEJQ+W6EOOwaIstFHBrABoVaahhCYSYRsPlsJAEoNF1+d9nj0zZuIHPB7Lw7+HKomwwoNlRkXfp417AXY+kpoCAZbbtBf9GCwpv1UxWFVZhK59IYlwI/Nbes9pC4lQZnLKPUFdu0KL0ohZhKFCozQek6dT7gXbNIuQy3whBmu2rRca9YICxmDx56iURTjyX3f3oa1EqARKPFDhY6h3nMAzREkMmkRIn127MDv+ppQIWTCnebDcHquX+X5I127xjEmJMJVpGCi0Vfx4PXvNbRlCX1xgsKA6M16AdWH205MI2YNLLJTX+UMrG6UOFpANlBT507XUXWOdyX1yJDsup85nuUQoJTIzztrkghjpwapgsOhYlAQwUSRCt80Lk81cPRoxiJUgPVg0ADNpqGT05DJI/t7Zdt4f1iokQpooFIlQsnqAv50SwTTIIpS7DlDQ58kKFPASg0UeLCnp2OK+hMBXi04ibMFg8WuvY7AAFnRyaUjxDgIISoSyevWnfgN42wuy30tZhGKSpxIlLuUe8HyBvI0reeLDbNOf4Pl52jBY3IPVttCol0WoSYTUF4TJvSQRsv6lSYRu4s+DwBt/Gnj392SvcS+Ma2uNyT2WB0uWHpALXs6IczTNIuRBkvRgVWURVm327AV73IPFghUpEdJnSgFWwOSuLTa0Mg3SS6oWKLWFyX3tZO6ZYlsa8aBw/dIsYHISoRESITuPF2CZbKNwt+OAlAjzRRZ9b2/9SuADL4PzDg/M5F7lbj040FZSxgBf/ntZSjX9PySzAOyBZhIhFWykKJ6v/maSiqeHl1XlBZQVDHmwmES4yQKsJhLhmK3MKVNFBlhA9nCMjhWfn22XJTIzgsvc4QMDIFbGAYkQKFZC3IPFB0Rj2HG2ywxWqNDoiE1kPIuQPFjS6EnvLZncc+q/jUToDZYsi5Ama5qMeNAhJUKtDpbdLdhLoGiTFmC5VWnOYMkK4tLXoaFJgNXYg1WVRZj3ydkOsML/xhgs+VM1uSsS4X3vA+56R/4+IRFa4WmjIrvkvQJY8Lfr/3QbJysM1oyYaLE/ZnbA4vy8LW58qJEIg2UaxGRJgc70LNwCzWOwDHDokuKZoHNVlmngLNsUuPtdwJmP5edhXhgC9xRKNPFg8UCdS6PasRyDxdhbGo/noQBrXL5OuVUOBU6aB4tvWUbjhBe47Pp9MlgHa+x/B1widPYLlBmsEvPE+8ka4PaVZPeN3yspKwezoVH0o8mxLAjaPZ1tznzki/yFKZDJfBt3AEcfnv1/5Rg8idAbq/JzUKIT2VTcOakpbCFN/f2+92Xbhj36R/zvLDFYA0Jogr7iG4EjDy3+zwc2Cc3kzil6wB9AAbhMQN75+b5S2ZvgSYTOp0ES4Xamdct2cDgDusJg0XXJLEJAdO4dOD8Sh+eNEGyNtzIOSIRAoeVXmdx5FqFksEKFRksM1rg4lpQU3L3iq3QKxojBUiRCyWCVKGrr3xO693wfOHe/QhJhhQeLS4TeoDxnq9KAB0v6NzTw6wkyWA0DrKo6WBT0l/agGyv9tqVEaOd5/2W+N1oBS0aQEjwo5R5gfbJGIvTMzNvhwFWbvLw6WG0kwgoPFu0t6SRCk/2fWJcZM7l7k1+AweLVuollm54pxglNImxdpkHWwWrIYJGXTivTAGT/n++WA6xgFuHYv+dqFuEKvC3LnETIGSzpwWKWidpCo+x1uRiSDNaIBSwEz4PFF5HMg0UBa3AcY/ebB9Ann5b97oowi8X1ocsKiZDGTu7H9SwVnO0jdadCIqTrtLPsnj/kOuCq7xDtTgHWcBAKsCRCqe4Ae6C1ACsfLPjgBDC6l3UGMlS7c9KDJ8o0OIlQMlhKgMXNzgAL8Fhn9TxY2uohvz4pbZkRigld+o1qGCw6Jw+wQmUa3Mpvu2ifN4hVSDHkH+JZhJrRk97LPVjO5B6QCIMeLDa5S5M7wAar4/7f+Ipf82BpWYQhiZAPmtriQK5aNXgMFk084v2qRMgCJEITBktKhCqDRX5IHrRzOVRIhHYGIN9Kh4J7Mj/L+zk+XJQ1GIsAy5XXoAArD46nm0Vf1eRgidZZhFMEA6wqidAlrJz12WDyDTmJkPU5O2PSlcZgiSBw93QxCaoS4bjc77zrkgGWqIOFOUB73DWRCOs8WI0kwvyZHYkAS9bB4kVbaUHDswidBB+QCBsFWDnLFDS5S+aJamcBwUKj/F65oLzGSwr4ZvLzn5y15dT1/j0jHLo8k/ymG9kzVcpU5Sb3efn1WgZrzNQFKbUi3E/2GCnAAqBKhBpCRmGgTEkD/gAMMGaEJooAgzVRAqxSmQYuEXIGS5EIZekHyWCZMXyJMFCDBFD2Uetgcp8JBovSfYkepvdTWrXbP9AGPFhTlIzXdC30PpqkqF4QLwDYJIvQSYQBBqtNFiHgGzP53/gk0qQOliYROsmW+5JWyosDKS9oKEmEI5QCh84SIZN/SjIcl4bo3koPFjtvVaFRJ0FsF8H95GhxjySDNTtbyEKA0jbyYOXf3XyrzGBRWzSoHizW76h4LP8bH5/453kWYWnSHTFGjmcRszpY48N+8M0ZLLV8gQgCd8/A7RmnSoQUWCiMgrYwGq0CMP7iwjN817BhpQCrTiIUJndrAWKdPQaLZRF6EmEerLoxltXB8rJ420qEIZO7CNQ0FtqxQIGtcrS9CEvZiEof5WPWeA048eRib1TeZiArNrp7OkvAmhzxmUxZMd6zeuSvayqKl5AyzhdLtpgL6X7J610iUoAF6CspDVVF81SJ8Gj2MygRagxWjUQoGayZMLlXMVilOliys+bXqK4e8gGEb/YJZJO5C7CEDh8yubvijFUerCk8Botn3blSGPRghhgsRd5yxlXyyEiJUDBY8134EqFksBhzkv1SHMf9VCRCNxkxiZBWySWJkLevQiIciUGLB39VEmHV4qKRRKgxWEK6APLV/iY8YyzQgsGqkAi9a5UsImMN+Ma9NBFLD1adRCjLNEw3iyBfC6YlVAaLe/8aSITu8zyLUPHweIwceTCpTENAIgyWaRDPBmyWoEISbIjBAgJBuDLuGuMH4t59qZIIKWmFSYRmXHyHlAEtvxN3L5U+WZII8/+XCo1uFYtGj8FiAVZtmQYeaPBrFhKhGfuBpraQcfuihjZ73i2ek5KXq6FECGTep1PvLQJATyK8PPv54C0BGTokEZJtJfeNaoVG6XpdoMsDLCUwXCIWHmAZY77aGPMxY8wtxpiXL/p8ndCYwRIS4XQT2BT1pyg4IUkJKB7IkkTYwIMVqoPlBo5cIpzkwVwriZA6+aTIghyNywEW9/PIAAsjf5UlC41KBov8H7ydFGBNhETIyzTMmbzjVqWcwaqQCD0PFjFkW+VBht7rVo/jYqB322JsZ+3auL04N10roAxMLRgsnuUIsFpAcvXJAyySCLmvQTJYI519bSURshVuKb28BYPFDcg8CJMBViOT+zZwz98Cd/11MfhrdXLcAJ4naZhJft/Ii8cZwQqJsGRy51mEwszMPyeh+mI4A9kiwPKYDUVicowcT3LJA93ZFpv85nCSlmZdcMdlEiFQyPvTs2EPFn1WIvTcTg75fZ8/j20kQp6oEGKwStlywvNF8AqN0pjAJEInPTMPlre7gHiOVGlL+f5KC+yxfx/myjPs+tFaoK+JhAA6JxBeKG7dkz1rQBFgnXxa9p2f/nh5IUnFRs98oiwRcq+VDBa98eIIm4NyiZ97sHig6679AHmwjDFjAL8K4GsAPB7AtxljHr/Ic3ZCVwbrIz8PvOXLst9lodHRWkHDhjxYTiKsYLBcHaxAmYbZNrD5+SyTAyhLWPy1EnMVkAilwZAP9lMhEXoPvHjIOGviMpuOwitYChQS4Wjdn2hdodE86JC72nsMliYRsofNyxpELvtpEiFfPU6KB3y0XkiEn3od8MePze4PN5LT/fDalntICE0lQmt1v1ITiZAHWLx2VFDebCAR8v7hnf9QNYMlAywARTV1uu8siNJM7qEyDZ/5PeAvngG89VlZuQBABDli8iCJcLyGIoFBPPvOs9REIswnGs/kzjwwmmxNKAX27NnhyRTWZu1RV+ls4SUlQh5gTUWANVov3ksSIX2Oy+0lb5KQCLMXsx/Ts1mQa8YiC1qYu73jBRa2HoPFWPE6BksGWJQ9C+SsOWfnqH0BtlMGWFwi5BO7KhGOijbQPaj1YAUYyBKDJcz+tRKhwmBVlWmQC0XqX3/z7cAHfyL7ff3i7OfJPMP+/g/5wTcAHHtEfq/OAusPQbmYrebBEv2BSqbw9o3YnMUXvw4Hy4P1dAC3WGs/Za3dAfA7AF644HO2R1eT+9YXigrqdheAKQYX+jla65BFyAcoCgBowhFb5cw2s6CHippqdbBsiMHSJEKFweITs2Sw+AOv+Y2kyX1yNB+QmNTGGSx3XVvFIOkkwql/7Z4HqyGD5VahxGBJiZAN6Pxh5xIhZcds31PBYFHwYMU9qZEIeeYioJSkYJk0ANQsQhq0ODM7YvV6vGuFPskRqO1ushAB1mgtIP9UBFiy/IQmEfIJJdRvNz5TvH721vz9mkRIwelOUdPM9VkhLxPjwyVCI4I/mUU43y76KrWZt1OD1u+I/eV1sM5+OmMJTjyJfZZY2CkLRFfYdYpsLGLkHIPFJiQyuQPZM8aDkBKDxSVCcW2zjaLKt1eWRDA3HJKNJXSRCEserFwSdUkltFBSyjRkjSnO514XY5nzYAmTO68PyOtg8XGXS6Vu78qmWYRcwRgXx6f3AvCVA/ruKwqNSpN7KYtQBGYPfhK45PnA13wQOHxF9ppTTbaz4/Bn/cjDgK/5APDctwHP+A145IRXaFRci1YyBSirMB6DpXiwDgKDBeByAJ9l/789f83BGPN9xpgbjDE33H333QtuTgBtJELPS7TDBt0dn5J2/o1VxmCJgVfL1pkqHizP5Cgkwp1T2d/WLsgP1UIi5GUaCDzAmjUNsIhlE6sYz4O1W6xuuWeBrgHIrpvXwZGV3PkGzYBY+VQxWFwilAyWIhG6lGceYDGJkB7snVPKykrxYHnG/yqJMB+I59Oiz5CPzwWTIiAgtmNewWAB5RIJdN/o/SG4iYECLG46nyCYhl8VYElvmeEmd+HB4uyWZF6J+Tz8UGDrruJvcnJw924763tuO5NpeZKftJAIyWtEiwHJYtYGWII5BRsf6Bz35CbiC57mf5auK2Ryr2Kw+AKOJEIgn/xnRbtVBisQPJJEyPszwI6t9ZHAwshLhugoEdJCxC1oQgGW5pnMXw9mEQoPFl8wOolw5o+7/DtzakdFgOWmZoXB8pgn5TnjDFao0OhopcweAfpC0drM53v+k4Hzry6fR1tcA9n7L/7KbMs4Xn5GFhrVyjQA/p64rn00Fkz878G1KZncPVhrX22tvdZae+1FF120pEZ0lAjJJ+RWJIySdkzWGssiFPR6kzpYzgQYkAi38qB09WTeJk0ibMBgufNpEiEPsCokQml09DxY+UPtPAvsmKU6WHkWEd+LkKpuA2XvWl2ZBpdCzah6tyVRxUTnlUNgEiE99NunygOTVoNJLdPwYPbTTUgGXsIA9RlXkoJdq9wwvKrQqAuihcGcH7OJB0uTCF3Zi5YMVqlKt8ZgcS8MM77ynzunss8euox5sCb+985/zrYLBstlpgqT+/gI3P6YpWQUKRFSEssWPJnaKP2nBM37xxhuOsep67NxwmOwlABLerB4ursLsMS4A+R7ETIZz5PRNA9WIHicbhTbqHiXWcFgVQVYnOVsEmB5hUZn5fG4NsASAYuaRTgurpVe0yRCl2TCkotc9XGWrBOUCJmXtZRFGJIINQ/WevlZ8O6VsFDwz3IP1s6pbIwh47o8j1vAVoQT3mJbYdvpdU81OFy2qWgMlpdFqFzvErHoAOsOAA9l/78if21YCFHVEtLkzvdNI8pXrhJHq2WJcCwHbt75A3Ww3APGapwAmUwF1DBYDco0uPPVSISyGrgs0yA9WOQncoUA11CWCCnAWoeXReQxWFP2kIkAi5sfZdvofZpEKMsi0Ht5oEJwexFuF8zezqkKap2bZqskwjzA4kGLnRVBiNvqI+DBGq3BSSJ80EIuUbiJlvxP7L438WBR27UAixi3NoVGgWYMlmpyFwuDnVMZi0R9H0CjLMIRZxkkg5Xf7537i35Gf6dEkBKDte0Hs10YrFCh0XuvB85/ivjOOUMX2IvQMViHi0KjGoNFexECeX+wjLGTDJbwJ3JMzxYSoXedNSb3Wg+WlAiVidMZoIVEOFotxgVa0JT2ItSeVxQLR4InEQoGy079DaA1BovuBbUNEGNWSCLMZTxvMcLGrLnynHkSYYDBkuVM5GKLB09UBuhwVYAlFtcSfJzgXivJooUYLC3AUrMID5ZEeD2ARxljrjLGrAJ4CYA/WvA520OuYkMoMVhMHnQSoVgljtbKWYT0YGlZhNO6OlicojfZflAAsNpAIgyWaRCrn/F6dmzqwDPOYIkAazRmD4lka9jgSg81eRY8BusUvIwXkrNcmYZcNqN7L/dwbFpolA+axGBJJkEWGiXwQqP00O/cV15BSoo6xGC5jKvzxOfzgagUYLFgUmYRAtn7qxgsxx4xH1YTDxZN5poHy2V4dpUImzBYIqDjP7dPZQEqsbd0LSWJkPoJmdzXiz5VKtOQs7c798HbUgpgCyqSePJK6XMhEXrPaABSmvYk3jzAms/yrUCeLj7bQiKkTKwqidDVnmM+ouwF/7yeP1F6sPIASzJYrq1tGKx1EWDVMFicxTPj7L7JLMIQgwXleQVQNrkzidAr05CPRfQ8u6BGeLBc+xmDJSVCLYtQmtz5gpbeS8d2x8qfGe8aOEtPARZfgFZYHagMEGUG8vO4z4uFpAT3L3teKxlYKn5IoJrBOqiFRq21UwA/BODNAG4G8EZr7U2LPGdj7J4GPv2/iuCliQdL1hLingyZtcIlwqZZhJQ5ptXBkmUaTG6oJ4lwrYtEqDFYk+zYPIOjSiKsKzQKFOzTaKVgsLgHa77rX/P4UEG7e4VGaRCQEmGAwXIGbRZsuFVoKIuQSxIiwHISIfNg1ZVpCGYRConQG4Q5g3WUblJxr2QWIZAFw5oHy/VHEdwALDisWXkCPoPFs/raMFiySrcbBA0LFIXJXfNgOdknn9Bpz0+gvDLnx6J0+hHLItQKjQL568xHCRTPkStpwiRvTyJsyGAFt8rJJcLTN2fPIPdf8eN75mchEToGiwIsZqqWEiFfdABsYVQhEcrnbbqRJduEPFgqgxVYGLXNIvQ2Ne8oEc5lwKJJhIrJnbYso+xqyY7ye0CLEVUiFL6qUoAlmDXpnfJ8tJPiO9bGI5rvpIXCayuNWfNip5CSRMjvneLB4pC7eki2Xb4O+BIhfcd8IaplEQ7Mg9UgqugHa+2fAvjTRZ+nNW79LeD6HwAuemb2/yYMVsnkLgKskETI6xHRa/wnlzBgRRbhCM7nxY8BZA9RIwZLPNAnngAcfURmDgbKqx/AH+SqJEIaiMggKwuNAgX7NMoZrK0voFSwcyIDrAqJUDJYwUKjFQwWFRodiUHby5TiHiwmEXIP1qE1/70lyaEui1AGWCQRKjW/5rkk5Hmw8r6ye6ZMu6sMFg+wGniwnETITO480AmZ3DXpQttnzozyxYLwOXn1iALMK5BLhIzBaiIROgZL1A8DgOOPy9o53y58T6USErvFQsRJ3poHqwWDJf1N892shhAAnPcE8VmFwaJaVvJYK8eza9y5r3jeQyZ3t13WpNw+QDwbMsA6GzC5U/DW0oPlmFYhEcJmYyHPVJRmcieZNwmwBMMjAxn3Pk0iXGHPHwVYq8W949s30TErPVh8QcBM7jR+AWhscqd2ldhc/syz50RaHXibaK/bQ5fCg9cPZ34bJMyEPT8zMVbxwFIwWK0lQjn+LhcLD7AGCyoUSZJXUwbLo/XZgEsSoTSwa1++YxUEE+Mi8kP+ZzyJkA0s4/UiwCIfilamQXbOE08CvvGW4u/aNhx8tciDtlIWYS7v2F145kyArV5JilnRJUJ5zeNDxXloYOMmd5XB0gIstpO8C7AYg6VJhFUMVkkiPAWsXei/ty6LMFQHS7IfVCuK1/wqVY1H4XnZfaA4lsdgiQBrygIsucLW4NrDJEJ3rSz4lWgkEXLJqYkHS5G0W0uEm1lJE7o/khG88EuAF2/416JlEXKmmiRCI77DPlmEdrcsE/PPAvDKNIQkQpJ1zt6aLaoApUyDkAjNOGuLymCFJMKNbMHBvwtqF31WIvTcjleLey0lQtcO9jk+bnoMFlvwugBLtLsqi1A+t17JEto4m7K5H8jbsFZ8t+4Z4P5K7iVtWqZBKBh1EuGIB1ji+njQx9ketZ5WPjZu3pGNc169Kfjfh5ZF6L13AsyJjZoq15e/zucPL8CisZ8HWDRGKlmEAwmwFu3BGi5IV3YG9CYB1thfifHCgyQRaBIh/zzAJgxhclcDLOUBI4zXig5IA9tMkQilF0C7Lvm7F2ApEiF/QJwpV+jwXvp3PtlrEiEgjLeHmKdhtRiYnPeF7ilnsCqujWcROk/RNpuMxUTnrZhz0F6EdloYZrkHq1QBmU/uSoDlGKxcApSTsxs8WM0vGSgDRVC1c1/5u7N1DFZHidDzYIVkm6oAS2EnShIh92BNivPxn0AuEUoGq0IipL0+iXkLTfIcWqFR/pxPNwBuDm+SRVhVHmSUBxjaeMCPG5IIudRCxuTpWcYA8meNZRHyDd+171WybBzbp7KxdE0EWHyRJREqNOoVWuXSqQicCVqAJcfjLlmEgN8/acNp/v+RZLDWiu/WjQ30XFKfUxgsj5ViC1V3LCkRssUlHdtd07hYhJYWG+z9nkSosdn53LNxR1kelMeuDbDGxbl5gCzlTumHnG0gS2IQPmIvw5sHfrSoTgHWckG68rRFgCXlkKYSIUFOJlIiVAdU0uBFmQZ+DqCGwdIeaAa5aqHXtABreiYbtMgbRJ6c+a7C1nAGi5VpoC1LOEoMFgVyzOejMVjE7oW+PzfgBhgsOZF4q3TJYOX3b/f+7KfnwRIBkgva5D2hY5zJj0n9hK1yAebzYHKoTFYAClPxzv3s3EwilFmEmkTYqNBooEyDzKyVx65jsKRsru1FWCURSg/WaAWlINcFHjuFx9GbiGuefa3QKPczUcAtZeI+DBZQsJylAItPbKEswrwt3JhcWweLB1jMG+PaqARYVFplM1cE+HfB26r1kVBw6wVYwoPlXmOYhhgsHmDRdxQwuWtZhPynZE9l0Va+ICwxWKxfzCskwtBWOd6xGprc3XcsGSweYDWQCDHPsgilwd0759z/njSEPFilLYKEREgBqSYRumNzEiPfSUFb9C0BBzjAynVlp+M2ZLDULEImEUr5LyQRehp/3sGmAQbLM7lzwzSjgSkbrUmh0dJ1MXmLjm/GhY9GFhodrRbeIIxySn/HnzD5+ea7cL4V2mi2ViJ8oDiGW/kpHiwXJISujQ1Q3j230AuNcgZLkQiBosClVwdr5P8MSYQubfxMwYoB5cnZ9YUaBoskQk67k6+Mrwipr3RmsJQsQhf8NmSwSmUaFAZLVnKvMrkDAQ+WXLVTP972A6w5C/yrUCcR0uTdppJ7ZR0sCrBIdqoIsPhWOQDcfoKSwQLgbfbsXjtUvLfEYEkWgMt1+flWjmUsGFku2kiEoQLBJQZLBDtNGCyXIFOTRSjHYC4R8r/LBdBYBKtuvKI6WLPy8+VY05DJXZMIKVjjjK4Ipr3roPfQuBJgsOpM7tSmeS4RyhIN/JzUDyvHEbYQ8xgsdt2ayR0okjQA9j3w92msZGKwlguSCNswWNKDxQsPOkM2PUyaRMjMr9pEUPLdgAUIAYkQyNikEgPAoDEf3nUpkliIwaIsLCqASQwDMViaRCgZLC4R0kPkBVjrvmmUWBIti1AaSbVr41KQN4AQg8WZBL5iFjQ03W9a6VMldzI80/1wxwGCWYTzXZ8VkwzYXEqEbBDUJEL+WXnNQDWD1cSD5ZhRzihF8GDJCUwtNErXteL/BAIerICvZrZT7JTgsgh3q68fYEwzK9PAvZbOx9nHg6WweY4VqWKwuEQIfzEBZPeH2GbJYI0PZ/1WlmkgBquJRDg5njENG5/N/i8DLNfWFib30YrPZGoeLI4ZW4wEGaw6iVAGLIpECKDMYGkSYf7dyo2YHRMfCLCAIkB2Y5AwuUOa3APMU1cGqxRgbWe7JFQxWPMGEiFXf7jXqqrQqNtRZKM5g0V/G4hEeDBN7tOzxYqjLYOlerBYmQaTp5w7ZiIgEWoTAbEWTepgAcVDtHIcrh5VVRahjPRlu+TDpQVYQHZt1PmJ0SCTuxekMQ9WqNDo6nnA5kZYIqRJHJYNTJzBEhJdCYLBkunMJQaGsyoBiZBAEqGWJFCXRUjXIYtZ0j1TGSz47wX8ukMlWUExufM6WI02e66SCFsyWHStao2jPJCifuEFWMafLKskQhfsMpmgxGBRFiElZjRlsPJ7MBM1pbY+77+vUYBVxZwSg3U6v27x/VQFWBABFpBNjmc+Dk/WBNgzTM8pL8XBJqnb3ghs3olSrS4gu//GAGfzACvowZLBWj6mVXmwHBsXCLBu/qVszzv6/jWJUBYarfVgiXG2JBGKgIvupScRBhgslyEckgjzdngMlvTgjuE9cyqDNSnmnxKbyxZpzhMVMrmPc6XH1jNYUr0ovZctxLzAWpjcPcY775/Ts1DLNBBK5nt2zCXjYAZYlHYKMAarZpAFUF2mYaeQ6Z7wk9nGmABUifCLvgU4dHG58zvfDfNIuNWKVqYhfx/JRMQkSdQxWGo9rFx/B8oBFpcIzSj7/2wHZb8RY7BIDpgcya7FFdo8kQ3ePMCaHPIHAulLGndgsGjQOv+LgSu+KRtwH/Zi4K7/ywYfKyZ98RB79YPyDJfZRjkwBXz2hN+TyRHgkf8k2zz14ueUgwYn18gAi7OYfJWnBFjumhuWaaj0YAmJcMSCVAqwmnqwqEq/q20jAoHxYb+EA//8E/4f4NIX5K+J6185XgyqXkq8mDQpsHcS4Xb5eBqkRMiTKsbrZQbLTc41DJaXXBGQCCV75T4LP8DitavkfT18uR9gUZ+SAdYswGB9+jeBBz8B7/kesQDLzouFalMPVhV7yr2pVRLhJ34ty4h+xD/Kr+sQnDw+yxdtk8PZOba+4B9btq+URSjOyTMB+XHoerfuzF9fK77bUvHOse/BCmW/eQtV8lO28GA96vvLZRrAghgAXlkPzpCNxFi2fW9+nSJwBvyFjFxcl97LxgkZQIY8WN6+tEoWIUH11aUAa3kggzvQksGSJndeyX27mPif9IriPVoW4UO+PPv3uTdn/5dZhJLB4lsleGUa8mMTi0HZRxK1HqwWEiGQDSJBBiskEeYMFgUEtMXP6onyNfNJhe8BRuyLZ/yuKTVgRvmgknuu1i8CnvUHxd/vfqfPNnn3IyARAllNodMfzQq9yswbgPUTKZsa4Om/7rdxtKoEWHStjMFyfhvuQTqCrE9YsbqzhQ8FiJtFyKU6YwC7Vf6cG7DFsSdHimdO9peVY0V2pZRq+DM1GhfXTMHV6vnZZODdAyH7cE/TaFIEWHUMFqXsqx6stbIHy2UD1gSuJeZUkQi5IZ1/Fsi/vxqJECjkHRfME4N12G+n63MTeMzCbLP4W0kiPOYHT009WJqp2n2G2R1CZRqA7PubbvjjJt1XqsllRln9po3P+McuTpYfkwUbQPmcFAxJiZDu7YOfKl53DJYIIqs8WLyivBqACMm8FGCx+/jwlxa/S4aO33ee1ad5sDBiWwwpgT7AFnNinJNwmeC0iOUeLNY2b8FFvtHtlhLhCOruEkvAwfRgbbAAy23E3EMitLtZJ5BfNKDTwO5vAQZLq4OllmlgEiEA37vA0DSLsGmA5UmEuQl5vgvPOwAUgycv07AiAixi/aRE6I6xUnw3rnQBzyJsEDxyg7b299JgRRMdDYxrcNIv4fAV+XXcBVUiDG2Vo2G0Vl4hl6oUz/VA2ZjinnqDMjJW0W3LpNTBauTBqpMIxaKjdGwlwCI/jAwEVo6xnQIUSZyDMyhAMbFrAzdNnjzAMmMWNDR49rnxmgeuo/VyFmEjBquJyf20PrF5W1CJRQExJzywpRT7kgfriP9Zz4PFn/+tfOsq7hOj+3/cHwtChUalB0tKPt718QCL+5HkeLmVbaWimdz5voiHLi+eHdUQjfAYIBksGWDR9U/P5s+DKcZsKcGbMTwPFu8fUm4LbvYs5Ns6mb/E0AXKNISyCGkxVBtgNZQIJVNW5cFyloItlMs0sPsjg3TJDi8RBzPAogxCoB+DZdmKlg+6HJpEWPwxP45gsFSTe6CSO1AMJMQkSdQGIQGJkFYBsrbWaLUwp5tx9n9aBQULjU6zh4MGYEc9n8iPKepguWMoAZZncm/AYPHgQPu7nIglg6VlhFJV7K27/HPXSYQaxmu+jAAoEiGTQ+XE7b5/EShTrS9AZ7CqWAR3PUIilFl9bSRCIJcBWYDFh6DJ8UJu05I6ODiDAhRSDZ8Y5fYnO/fnnxEBVh2DBcCT3yWD5a61j8ldkd9CAZYXaIQkQvadHhYBFmWQ1UmEPLt5uunLQDyLkJiw1fPL31fIg1X13JYYLLFw4AEWZ7A8D9Z2EXxz/1CbSu78p8widKZ3wxhC8j0JBss924LBCkqEPKiUbNhIjFmB56x0XIXB4n8LZRHSs1oXYDXJIlR9aew5kB4sx2BtKQyW+B68cw3Hg3VAAyzOYOUdqNEqduyvxGYBiZBD3SeJ/t+AwXKGZU0iJAZrwRKhK/BJkgJjsPiEO9uGL4dxBmtXMFh3Z/eDMpyCEmGFB8vzOVQxWBRgKd+x94DL1SsFJ7TiVxisLclgScnBwvvONIxWy5NzSSKsuFZewZ3/dBta558xo0AWYROJUCvTMClkDwn3mujzkyOFB0sOyp5EWBNgOZN1fu2rJ+Fnc/JVrMZgTRiz2+TZDwVY6/57eJtbmdw5g8UlwoYerEYSoUiwkBJhyOQ+22QMliIREhO2IvxXvK0lD1ZDibAqi5C2rZJ1sAjUN3gGnFychDJOg1mE4v9AmSHUnhn6GayDJQIs6cEqMVgiwKryoHrXx5hDjcHy5oBRsWfqpIFEWJdFOGcMFje5Bz1YLGs7JBFqqlEKsJaMjTuKib1VJfcKBquLROg6JFspAjV1sLpIhBV0PG9XnUTIAzkuC7hCjNt++7RCo9yDNVpjwUuVB6uKwaq7tjoGawzQ/mYy4JAPscdgkUQoPFje5KewjhpGa+WVWRWDVQqwKiRCt3rOq06rHqyWEmHXzZ6B3IOVL2rmQlbQJMJQ8KdJhDLQlZPQjpAI3Xt7SoSyTV0ZrFKh0ZoAa84CLHftuSHaC7BEAABk/aqURRgwuc82s++YL6D4/afjyAxC3i7ZRxozWKyP8Oue58/D9CxKZRoINNZotcAIIYkwmEWoMCd0fJm5Jxd2TTxYkg2ihQJvlxdg1UmEAQbLTNg5FUM+nYue1d4S4biYB3h7eTAkM7JHCoMl1RbV9pL33emGzq7vIQ5mgLV1J3Dkyux3Wk13KjTaUyLkAwaARnWwPI+TIhGGyjSQP0DDaOL/pLa5AXbHP894LfNOue0i8uuebfkPGZcIqd4QlwhHq8W1yjpYrm0r7D5JD1ZbBksbhDhNLu6xk9eo2joPsB6mt9cbtGp8RISVoywrU0iEPKMqFExOZIClMFhAtgptXaZBrMZLWYRs0XHXO4A/fFgm81VKhAEGa3KMSYQBBozgKtTn175+keJdlB6s+/M2iACriUTI5Xe+7yBnqCWDVZmZXMFgmYYBFpcIqxisI7mc7YoDI1tgkv8xuFWOsC7MzhbHpXatnmQSoRJgBcs0NGCwZlIiZNdNweBsQwRYImAH/G1eumYRliRC9t1qEiFQHnfIh6TuRShYyVIAUmdyDwVY8vpCEqFklvLPOu9aIMByRY0bSIScwVI9WBUSoRznXT8MMFiYA2+6Erjhh8Nt2gM0iCr2IaYbxdYyXRksy1YVjSXCQIDlMVjGf3hdB1TYkKYS4WzLX2mXrqsBg2VGBU08WgMe9QPARV+e/z8gETrpYbdgsLjJfe2CQIAVkggrGKwqipwmdC0ja8QGoBKDVSURXgZ82W8DZ2/LNgh25+OsZI3MRXj6fy+8aFwi5MGlDZjcgWYSIZDd17ZlGqBMFtyDZW0RqD1wU5attfl5xqwoDNbZW4vzexPi8Q4SYd6fHvevgCteyP6uSL/kwRqvi8VES4lQlmng76FzA9X3VWOw6FpdP7MdJEJiE9h9P3wF8Kw/BB5yXfHal/1Wwbzw/uL+LxgsIA8s8/eungCe9UfAQ54F3PwL+WtagFUjEWpB6JgzWAGJkNo6PZs/K2tF8EFoIhHWZRHy/SEBncEKSoRCgjZjeBvdqxJhgOEpSYTUF5XASL0+hcHi80/Ig0XQxk5qjwv0ayRCKtfDrw8jeApCFIlwXIyXTRZPC8TBDLDmO4VE2JbBog7KAxnHYHWUCPlANj4kmKaRGEh5VXAq00ATbEAipA1uq65Ltk8GWKNVJpWtZnW8Dj0//z9JhFviGPS6UqbBzsIMFm+rKhESq8O9A6EHaVSdaqxOVmKC1CTC8WHgym9TjqcwYnUB1oVPZ81lEqFZEe3rIRECSoDVgcHildzNCmDY6pcYkNnZ8MrayyJUPFgkETYyuZtCnjp8RSHb0ufqsgi9Y9UgJBHyicfzldQct8qDxfuy9tx6DJbIItQYLMAPPoGsTIxsd6kOlmCwqN3umN+QtzH/DmQNLH7skMm9tkzDDCW5zs6KsWC+kwXl9GxXSYRmXA74m2YRVkqEeQDnFtMVDNZ8ozrAciw13ecR/MVfbnKfy4CpjsESkqJksNQsQh5g9fRgOYO/COTcZ/KFmvdccgaLFmwywKowudvdgIS4dzjAAVY+KLRhsLihlwdYszzDplYiDJnc2UAmB1SiOzW5yRUMrJEIKXALIZhFyCYUs8ImFRFIhiRCtdDoUfb3tWYMlvQl8T0EbQ2DNRoXE7oaZGo0ecjkLgqNavAmuoYBlvb52SZcTR06XojBchKh+B6bMliVHiy6HsXkTtWg3SaueX+ZVgVYh1kdLMFgTY5lxyBpSPs8gfpSkOFSZBSXvdXFgxUwufPn272mBEpa+7xUciWLENCZZ/edTNnEwyXCafi+qW0RHizKMrTM6yTPzUEmd9WDxdrKUeX/K5ncFYmQgkEgsxtMlADLSYSKyZ8gVYRSvxNyrzaxOwarxoPlfEg7AEx5vPU+wxdLYixpJREKho4vSL2xauq/Xx6zkQerRiJUswjF+OuNV3nfn7PvWtaa01QjMs6TNWaJOJgerPlOMcg6BqtJqvakPJkAjCFpm0UYYLC895CU0FAi1Mo00PYgITRhsMarerkCoCxput9FgGUm2YNBwcl4rRgYQ1mEZqV4mHjdIkcD1xm1GYNVNVl5kp64H5y5IwQDLD6gKZmfdfACLMlgBdi6oESoMFi8DlabrXJmbOAvbZWTH4cmvelGdwYLyBgJGexKcLlZbbciERIoi5Afqw7BMg3r/nuyA9Yft0kWIaAvCrw6WGJlr22VU4fQXoSYF75H127luF08WJUMFjHfonixxmABWYClMVjUP1aOZcF7iO0AWF8JZREKD5ZnF5ASoWCwuMeVTO7kX5XtUE3gwkSuBVi1WYQNGCw5hvKFZu1OGXUMFo1rLIjn56Agz9vEmdXBaptFSAuDFGAtARTZjlZaerACEqGbwCskQm1gkp1fDbCkyV2r5F6TRTitY7A6SIQcoQCLFxrlnX3CAkJqV6gO1lhIhGacD0ySwaowuVcxWKrRs4HJnUpWlMCP1zCL0GsPu1YeYIUKjQJhiZAfD+jmwdJW1lwu4b5E7osJmtyPFIyvDASoH++eRhGcVniwZFFLD4pESJh0YbCYv9HLItRM7mJS1sADQGqjxmC1lbXpvjaxPLjjVZjceUAO6H3ZSYQVHqw+hUZVDxYPsO4JBFisfxy+vCbAEgFLKYuwwoO1fmn2M5hFyMZXO/X3siwuOj+/LO3Axn/vOCJgCjJY+XY22lY5tX2GPIE1c0eTAKsUxAu2XavfZvIgUM0iVL4H97mRLsMuAQc4wFrN/rXxYHk7grMAi2qFaJspS9rY/2N+LCYRljpzvpLUDNNyL0KSMbbuBja/ULyvTiIM7UVYCrBqJMLSMRiDxVdIjnFjZRqqGCwZdLjzNGCwzKi6WJ4bDJXJKiQRjtZQ8nLI4/HvrM1jFpQIKwz9oSxCoDxZd/VguUB2zAa3FbHoaCgR0vXx0gT8OnbP1MurI+bnC7W7NGnmKHmwmkqEJJk3Nbl3ZbBaBFiYA1xuCnmwqsAlZfo/tW8mAyyNwWrpwTr9CbYHbF2AxfpISCLcubf4Hnj7eP84FAiwgiZ3yWLLLEJe8mIVWLsIpSzCmQwmGINVKhchgzLOVpEHi98Hwc7WsdDS5E7bIdG1W43Byo9Z599tKhECfh/LGpL/VKRtY7J7Ot/OxyqDUjFlNYtwXATgyeS+BMxYwNCWwUK+l5ImEWoMllzVlI6HovNrTFMpi4RNOIcvz9rNKer5LvCef5wd6zlvzl6fb7VnsEZsgqIAKyQRepJVgMGiQqNAsbIcr+UV0Y2f6VNVaJSbI+dMNqtisKq2e+ABUciDJZm7SYi9Yp+N4cFaOc+fOEOV3EsMVoCdGcs6WE08WEIipDo8axdle7xRAUqAmdw3yveSQJMxBWFBibDm3h26rHrwHI3LkyaB9iJ0721ocvey6aoCLNF/NJQYrIBE2ITBMiP4E1VHiVCT4JsEWLSrwdGHh9tKE/v0LPCnTwIe9hL/3F57QpXcOYPFFrjb9xRld9zEKzJFz3tCUaZDvZ6GEmGIOTnvCdnz4F2zwmBRodFQwdPStl5sge3axNnZGbIAu0aek2UaiB2iY1RJhE0YrCZZhECFREh9WbRhvF4oF9pCPiQRuuA2BVh7D87IUOp20zINQPkBbyQRKp1P6v+aV0qWaeCd+OLnAN90e5bRBxSr7I3P+RT6dBM4dKLiugRjQ69xQ38XiVAyWJpEeOGXAi/6HHDokuJz3qQlJMISg1VXpqEmE0bN+qOHV0qEFGAF/FfB47UIsPhkt3ahOF7DMg1akAvkDJZWB6ulyd0Y4Otvzs77gZcXg7aUCKvYjukGvEmDXweXCEOBwjN+M9xmAL5EWMNgNZUIKcORMxBeEotggisDN8lgsQmqtURo/LGkNYOVt5vGwpVjRftKAZbSl09eA7zoTv8ZJshCo7uns35Cmy93kgjnvvF5xhaQ9B4pHz/l53T7RMmDJW0CUiJUgmAAePab/MUftd/7TM5gzbb0cR4oB1h1EqHMvNPgMVhKJXdt/0repsoAawQ/0A+9Twbx7Pp4u+Q4Pl7PgyXjL2xD30P2YtE/UhbhHsNaP8BqtRchW41pAVZbiVAyWLOtoj5XcQDBhnBjpCmCKwDOiGtP+xNp0yxCbx/BrhJhyOS+W/yfS4RAeWAuZRHSfd/yB7Eq4ze/Du248u/cgyUliTGj/kcrNQEWl2piSIQKgxXyYEn6HPAnsEkoi7CBOVUO/NRPPQ+WkAi1Pk/eNe09XCKci+9CYuWo/jpvt+bBMmO4LDlC00KjdWUaWm2Vw9oH+PfCtAiwYOFS94FuARaNfTv3ZT8nx4qJvQmDBejBFeAvSoHieHSurlvl8PENKAdYUj6eHAJQs8ACyousJhIh4Ad0nMEyI3jbN9lpNvmXAqzAc+YCLBFo8n02awMshcHS9iIMSYR1CVLShB96H1D2YCEQWBJGa3mZhpk/7lZKhCNW0icxWHsLGpR4wAA0XMVyBiuGRMhofaDC5M7YkEoaNpcI59stAyxtYm4hEXqdWGFPKO3eba/BJEINExFgcVaH+8W8oCP0/XEGqyrlfa4MrjSYCkYtaHCHWBErQXEd+EBrVvxBsLZMQ51EqHiwiJEKtiewGuftJSZMSoSVDNbZ8qqXS4RNi7QG2z0ujsEDGTcRCzNtHagOlst2UhYb0oNVJU94Eib8e8EXalV1sObTskRImbWdGKxT2c+VY8Xz3zTACh5bSoT58bZP+efmaCIR1gVYVRmmWvvqsghdmYYKc3VxAUX7ZT+jtpdsFhUSYaXJvUkwrXiwNJN76btoKBGSf7WqHSUZWjJYgf1ix+vZwtru+uNupUQ4TgHW0sB3Mvc2P23BYFnJYOUm6oVkEdJE0SAjjVbZu2d8iTBaoVGSRaokQmVyl6sWLhFqqDK5G8YSkHdAtsFrWx2DxVdxUh4QEiEAf6Nr9YTseF2yCAWz4g2CdWUahEQBKBKhYLCayAtAOMDyasMxiZC8WhLO5K4EYTQp7p7WGds2II8e4AcyWrZZm0KjcpsTHnybFgxWk61y5PHdeTgrlEuLfLHW1eQuGSw0zCKsAl+UAmUGq1GApTBYXCIEynWwqhIgOEISYZsswtIxOYMlxtT5VJcIS1mEzG/lvlPeJsZI1c1dtQxWHpTL4zT1YLk6XW0kwho5lTBayxduVmewglmEw5AIOy4Pz2HwAbItg1XnwWotESoeLK3QaEgiLJ0rD7CmZ+A2oKbjVm2V0ziLML+WphKh20Jn0/+/lAi16zDj7Fg8a222KRgs5kuq2yoCaJiRxV5zWYS8PENNgMV9DZ2yCLn5erX4bFUWYWOTe+7BosBPkwXUNo3Zylpci5kAMvGjUiKsYLBkFmFX9orarHmwXFmQwD0KYUzssAiwOmcRskkSgCeF8c+pdbC4rJ1/riQRtlg7u4XQTsYSjMbFpNykDlblsdmiFCjGAtoSSbtHNI7OGlRyJ9D45hgs4cEKQkiEkjltKhFy8MQQ73mmLMIqiVApNOoUjJH/GrW7ySJJY7C8xWCVRNg0i7BBgOUCnwCDpXqwtrLxgo+7I2VsLv44GAbrAAZYrD5GVwaLMkEIVKahUiJUbnUjBksEWHUSIa0MgcKU25fBmrWQCDUPFg2qzoNVIxECuRFZDGrS5N6k0CgfqLSHTdLk/BpUBquFRNgnixDwGSxu6JfXWlmmQQRYANtmpKGUZEZhjwR/JmSh0VqJcFZu6/hQUWi07WReapeQfQDGdHTIIpzv+OMHoEuEbiKsyc6MUaYhGGC1YbAUmZbaV2Kw2gZYIwCmzGARGnmw6L7wAEswWH0lwlAld/mdNA6eoTBYkyyQaSMRuiSnHhKhZLyo/Xzs08aCtlmEVe2gv5VKVwQCS8J4PQvKphstJMIRy1ZMAdbegg+QnHFqks7pebA0BqurREgM1rbSYXKKuIknhbYuce06A1fRtrcHayUsEZpAgEX3ayoYrDqJEMhT6cW9mzGTO0ksIV+SvLbSHo+ukdkPLYtwcizb0Prk04q3X/L8bIPbEPpmEZYCLBp482s1k/J1rBwDLv5K4ORTy+eTDBZQTHJ21nxhUSUR0rFodTo7mzEf2vMgJUI5BK0cyxisurTv2jaLVT5BlQhbeLBKAZayF2HTSTjkwTIjv99qnwVYH8sL7wJwclKoTpvaFlNe/FD7ZEDU5TshaQwoM09VEqHNGUPJsNtZmVmLLRGWGKw2EiFjZby9/fL7oDJY9BlZyX3MgmbWJi+LsE4i5M9CoEyDJjW2CbC6FhotmdxFG8jkPjvbUiIkKTJ5sPYWvRgskRVHcCb3roVGK1YjjsFq6MHi4F6sRnsRisGgqUToBarj8u+u6Fsgi1DD+BAb7KhdtsxgcU+Bem01g4QntygM1vP/2n//l/y3cJupXUCx6swOVP0Zrz1CIuQrbBvY+sGMgOe+rdwGQARYtHkqBVhNGSwuEQYYLMtY3enZ7HWtsnfJ5C6ONzmeMa8rx9sFplqbpewD6AFWG5O7DLDUSu4NPFhVDBZ9djbbmyxCIOt3sykLTPL29TW507FDDJZ27x3zveNLQ5pESIUoOzNYcgwWz2yJyWrrwVIkwpm2+JAerDF7vafJXQZk1BZvbFFkZResRpQIa03uCoO19YW8HygMVqjQqOsfyYO1twgFWI0LjcKfTICi87bNInSTOz3UyoQjB4Cqfe1kZ9o9XbBHnRisvF1dC43SwN9JIlxHyffAj9G2TEPVZqWAkAh7SFP0/USTCIUHq9G+eeIYBCkRNvbqjMIDIPclcolw+1RNgLWhD8rEYEXxYDFWwi0OYkuEzPvD0/Hrjuu1T6lx546/BxIhP6YnETIGa+W8vF0dng0zRsmDRdAWRsYU93t6tvDteQFWXhtpNW9XXR2sqrYB7LtQJMLRCvtue5rcnURY58HifiuNwWJ9uzbAGrH3tyg02nqrnIp21BUaDdbBWiskQpXBShLhsOAGyBX/5jdayRPNyaQpb9+8lhKhymDJr0RSqFWrBIXBmvUJsBiDxbMumxYaBbJ7Jg2HrSVCLcDKfQVNC40Ga7lUSIRd4O39RRNnhzINAEo73vNirZXHUGRaoFiJuorkDTKQqE0yu0m2l6QPIJsUd07pW6dQP5yehbqgWDlWVHLv9T1wWWRerH61LVXaMFg0cI9FgKU9A1XyhCZhaoFx5fZOUxRSKu/HXQIskeFLzxf1FfdddpEIWzJYQHb98+1MSqbvTkqE4/Ui+KqrgxWEkAg1k7u2ENcSmtx7QhJhlcm9xoPlMVhC8muURShN7mOxuOwhEc4pQaiFyd1j6FBhQWAm93FDiRAjeF6zJeIAB1gsYOCrzyp4DFb+IHDaUpUIqyq5c4rW6pOKW2WQt6qFRDhtGGCpWYTsIZaV3JtmEQJ+gBUqNKphfEhnsLgMw8s09GawFImwK/iqru3xPElv1V9l8mKtdedXj6d4sJpMxLxmU2kA5B4sJhHunALWFAbLjPJsxkCm4eRYXqZB8We1gZRR6Nq1LMKmDBbAChOLxYZRFmuNGSyln2hb8bi/iUWBx2A12F9Sg9zGip4vKngrZbo2IO8RUDbNh4KD0WrBZDrmgl03lTqYiACLvtfOEqHiwVK/264MVkAiDAVYXCLksmVriZD62m4x33msZ5XJvUmh0RrG2d0TaXKv8WBRFuGsjUSoMMFLwsELsGZagNXQiqZNJjyqVulKI7w0/G8N2BPPb4HqQFCTCGkyjVEHy0mEFQyW7FKjSUWZhorOP2EBlrey52Ua5mFmxV1HzSrMW8VFYLDonDEkQo/B6igRVgZYDcs0eLJvqH+yLMLZRpbNqkmEQDYpTjf0QXnleGFyjyERkvwmA6wuhUaBwm/Ja16NVnUGq5JZqGOwKiRCarMWYIW8cnWQix+6fxTIaMxfU4wmYYkwyGCxjGjKHpNZhLwmnWxfY4mQ+liNRMivhdoXBGNltH423ago06AwWHPhcWobYMlCo9JgHpII6xanri0NgvqmhUY1iZDq4jWWCFsunhaIgxdgaQxWE5kE8CcTx2CxLz3kKQoGWHxyD/h/+jBYXCKsqoPVNMAKbpVTIbWqDFbLMg3eIKUwWFpmnWxPcKIS0kp2QeF2NUGb0hqlz4rBwZMI2SbDded3x1ACrGlLBkv2C+9vShbhzn0ZixUKsMaHw7WyVo4B09P1K+JajPzvtBRgdWSwqCQLl4jkxsLueWpaB0sJxJ2cXrEwoPR4vhdhiAmoQynAYgzW+BC7b5ElwkoG6/7s95DJfbzOpN+uWYTs+eI/PYmQj28tPFizbdHPGIsTKtMgTe4mZ7AqyzTUfNecgeZSoJx/OkuEwjemvk8EWCMR5LnyDWI8GK8XrDEv01AV6GrP0ZKQsgiB5oORVmi0TiIEskCijsEKbW5bSt/tKBFWMljUWWsCrIufAzzmR4HznqR/XmufxmAdfijw+B8HLv/6cJse9YPF1h0yE8e1ryKzrvhA9qOVRNiTwXIrxg4MlswilIVGYzJYbTxY2u/8/zzxo+TbEZgc0QuNUhtnW/0DLCddNAiwGjFY+X3XMoZHa2gvEfbwYNF77Sxj6AzzYHVmsCgwEWUapjLA6igROgarQZkGwGewtABrvp2Nq9KDdfJa4DH/DHjIVzRsm/BgyUXWw78XuOjLWLuaBFgVHixCqJK79Nq6cS5gcm9Uyy7AYMkyDSbQptoAq4k/WJjc5TMyF4tw1wTWpqZ7EWrJIktCCrCA9gwWLzTqvnRTMViEAixtcg+Y3NtIhGacnbN1FqFSpoFvjr12Enjqf1A+b7IHZb5bbr9Z0bdHeMrPhNsDAJd/LbsuLeNLMFh111bFBAAofA7oyZyADYoxsgj5KrNLFmEED5bnDVI8dgC8QqOEKokwtF8h9aMuRm3vOOI7oO9fKzTa5PuREuFIMFheW0kirGGw5lUBVj4+BaVvzmBxD1bHAEuWUOFlGnoHWJPiWksMVuAejVaBnfuz3zWTO2Xi0fjrvt/DwFP/Y4vGifFVLnQvfnb2j18LtS+EKg8WoVUl9whlGrStdfjY10cibBLUh+pguedqQz8GD6DaZBG68yaJcG/hsv96erBoIHMrqLVw8MOZCA88pb+JRFhjxOdZepTu3iuLkGfp1awE5D5srk0Kg9UWoSxCl/1SwxQA7STCGB4sHrB1zSLsWqbB80wpq2ZXpqHFVjna7/z/jlVg91kzuQPZJEgMVsmzl2fr9S00WpIIhZREbC1Pwa88XEWANVrTZfKmW+VogfhopV2Bx+gerHxijyIRcgarhQcrJBHOKyTCLm3LDpr9qFsUue+2IYMV8vq12ey5tBchN6cr0p7WHp51KMfquizCOv+uK1nUxuQuGCiSATWTO0EzuddJhEsuNHoAAyyNwWr4JfBCo1IirCw5EGKwTNH56wKs+bR+cKPOtHI8+zc9U0ymrbMI6YFoWLAtVI7C8ACrI2GqSSfOg7VbfVz3IAc8aE18cK3bSwNal82ehURYt8rUENpnT5MI+3qw3Mo03zeOy4JBD9aRog6WrKtkVornIYZESBNnSCJsvLiiAOus/3/Ar9kGsImwh0RoagKsUR60OClVmIU7M1hMIqQyDZND5UrpbY8dLNMQOB5nsLQ6WCQRyizCtghJhKG+17fQKKFLmQZtT8YmxYKlpChrUIWO09SDVZdoBBT3QXqwKNAkBkuOB6MaBitUaNR9PmUR7i16ebAUidCtiCsM26O1cscp/pgzRaHJnTFYdRMOGW9XjhXp7n0YLKC8zU0Ich829zo3uXdcTaiFRsdsYOjDYGkybd8AK6ZEyAfBnhKhrIPVxCALsPabMtvDM6MAEWBVeLBmeR2sUn/Jr2+23TPAYit/IJxF2HRxNa4JsFQPVk3gX1WmoQ2DxSVCN751ZLAmnMGKZXIXDBYP4kLs4Xi1+O6aSIS9AywKdmsyiZv0G35M6WsllBgsmlua1MESY1ZtgCUZrIDJfS8kQrkXoSx/UsVgqXWwkkQ4LGh7EXYq05BPdqHMOu9zgSxCoLzSLjEE9BA0kAhpkI8lEQKMfapjsAISYXQGiw8O8xYM1h5LhF23ypH0Nh8Eu0iEaiV3VqahjcldZWGpn1CAxVirWolQ82DRgLuFXsMTeZycBytQaLQ1g6V5sNbEIoCYhqp+WWdyX62pPzQpxg2jZRG2DbDy95fKNETyYNE1TjeB9YuL10Pg9zdocl9n0m/FvapsG3u++M+gRNiCweLvl7+HGKwSG6RJhDWBkdYezxQvMvjIy1oaCxowWCMmEbZhsCQDFfRgdZAIQ+PfEnCwA6y+ZRoMqwZf9cCtHPdTTL1jipV2yOTeRCIcaRJhiyxCNcASVdiD5w4UVPUCrK4eLLZCV8s01Hld0KwOVpesPxUk+3ZhsIw/eEgPVqMyDYEBnkzzrU3uFQGW29BbMlim2F5FoiqL0GUVbTdrW1WbedC8eiL7SW1q4pPy2lURYE2OA5Ojxf/Hh7NrrPJ2aQwWH45Xjobvn/s8yyIsMSBdyzTIQqMR6mCZcZEFPdsE1i7Kfq8ad+sCLCrWuXp+1lZ+/1u1LSARhqbGyREAxp/sy41nxw8wWLVZhJLBmpWfQzf+1X0ngsFSyzRoJncKsGpK/FCb21RyL0mEZ/33uaYHJEL6XSso6zFYKYtwbxGtTAPVhqIAq4LBuvZXw4OtW2k3MbnXBVhMIhyt9a+DBbTwYFVIhDav1XPs0dXHqIKZAHbHHxzmO7lsVsMUAM0kwqBM27atObvWNSuRJk+tDlaTAoqhAAvI7sOUM1gNVv7SXKudayYCLJr4NEyOZYHK5KjCYJFEuNUv0JWJBkcfATz7T4BLnpefh/pRSwZrVwmwnvof2cQM4NE/CFz6groDVjNYX/yL5axMDho3ZBZhVwaL7gffKkdjsLqsyb1Co1vA2gXZ+NSUwRpXSIQPfylw3hOKPQnbN644JoCgkkB42EuAo1dm1xA8ZGiBU2Vyp/FWySIEfIuIZN3rvmtZB0sr06AxWG0lwipZmtcA48cu7ZBQJRGyoPbSr8qe5/Mep7fJnTfVwdpbeHsR9inT0EIiPO+xNcdskkXYwPTLK6VTmYbZZt7Ois5fKREKzbzu3CXTcv65449tvn1FZRsDhUbrPrcMibBLFiE//2gF3gTQ2IPFV3BKgOVM7jNg3JPBCnmwQv4rIOsHsy14G8669jKJMGYdLDP2S3/0ZrDY546LhcP6Rdm/uvbBZgyUxpwee2T953kWoesnkbIIY5dp4Cb38aF8oTAPf4bf36o6WCvHgUue075Nrm10PQ0lwpWjRZAeRAcGiycz8fdy1aTkncr7d+38xYJ5bqlw10gMVmDuqfS3jQAom5VLlCTC/P91EmGIwRqt+M+z1m6ufCwJB1wiVCqFV0GWaeAbRnelIuuyCLlE2LhMA5MIqVBg5ecm/k/ejrYSocZgAcAFT6v+fB2MaCOtsGt9SXl76upgDSWLEGDXyiXCFlmEdQzWQj1YFGAF/FdAwZJMHwwzWPO+JncWgADlY8X0YHVqH/9eO/Q7GWDF8mBxkzuUQqNtzfN0bC4Rjg9lgVwTBmu0qkhaTLrsi7ZZhI2OyRmUkAerTSV3+BYRL8BqmkVIAVYbk3uDAMsba5oEWJLBqpEIQx6sSuTtWLI8CBzEAGumMFhtswjtNDvOaLVgVKokwrpjVu2Dp1HEIXCJcJKzBNMz9QGWNoFKSre21kqFyR0ATvYMsFwQKAqN1tVycg9yXZmGgWQR8vO7Gk2mJYMVGOABuM1TgeYeLJke7v2JGKx8gKTAKmRwB3yZs9TfuUTYx4PFvCvqeZRFRRWiB1icOemYbWqniCoRjtZY4k9siZAxWJND2fjUJMDishB/FmbbkQOshlmEbY4pj9PEgzWThnH+vYZM7g0CLF5oNFjJPSARNtnH1muzAlfORZrcZRahuBa6T5zMqEOTMil7hIMXYFFtEjPqIBFqDFYDibDymJLBkgFKF5P7sYLq37qrW4AlGay6zhrKIqTXYzFYXQuNBgcJPsDGNLl3zCIE4BXBBIoBsvFWOXyAr2Gw2jBiVQxWSSKsCrCYVCzv9ZhJhH2zCPl3Ko/VVSLcfTAfOyKwnED3wN5jsAyKibhjHSwzKX8vs+2sj0TdKmczW+ysHKu+93S/uSzkjjXLJuqui1p5PIAxWB1lfe2YgP98eR4sEWC5bPEAg8WZKrkorM0iHBUsacjk3jWLMBRAlt7HGCwzgvMkl+pgyfEq//tY9IMq0D1bsv8KOKgBFqefgeYMlovCuQerr0Q4RrU8xU3uLcs0AA0DrIoswqYMVkgiNJPs3/lPrv58HaQp2Xmw+pZpWJBE2MvkLlLBvWvty2DxAKtpFmGVyZ0GzhYeLL4Rb4jBiiURhuS3thLhmDFYMaQHr991ZbDyLMIYDJaZlL8X+k77FhqVHqw2DJYWYM22s3sWg8Hiu2kAeTuVem+tDhmSCDmDJYPDwPfHv1fN5N4ki5AzWHO+IK1jsEa+TUGDt9CokgjZfKJVtA8xWBSIyn5QBbd4Wr5EeABN7rvlAKsx9chNli2yCCtR48FyHVPZ509i7cKsHUcfUUyiG7cBh66o/lwTBqtpoVHZ/kOXZRuv9h0MJeNAg0ZdJlxtFuEiTO41/p8mnweKYIP7zfqUaQCyya3rZs+qREjMzuns58ox4NCl1RmjXiZkgPHsW2hUsoglZlVKzjWg+x4twOrZ77jspnmw2tacO3x5Id/w9gHZ93XkYdlrhy5pd1wAzoNlbe6dOpSZ+GlS1eACLOG74YFfFAYrlx0d06mUDml9zJBEyD1YDSu5e4WmQwxWXYA1EgHuBeI4cz1QO3x59r1XHrutRLgLrJxgr4+zzwU9WPl33Nh/xdoxAAbrAAZYO8VqtHOZBqUOVmeJkAKFwCBLbW2yol+/EPj7d2Wrw7O3Za9t3QUce1T150ZVAVbLLELZxqf9WnFtfVAyuTNWp6oGTmMGK2aZBikR9skiRHGtXbIINYmQgqEmBlneHu29VF9q6668zWvAN3yiOuhdqWCwYhYabbJw6bJVTlWKfpv2AX4bWxWkJQmUiowGTNJN8dRf8Z9T/vkTTwHOfwrwzfc1KxMiQcEgseHjQ8AX/z/V40IVg0WTcRQGC34Awiumdz5eIKiq8mDxhTT/v8pgtQ2wxsVib/NO4MQT/WO7hap4Fh77L4FH/3D9sbXfS+9jx5ZqxmitvtBoGwaryWbre4SDGWCVGKwOJndZpqFPFiGvOF2acIhC3USjAZgGwCMPyxit7Xv6SYQyrTaEUKHRcSSa1rVRsjqRtsqpCnJbt5UM1n2zCPm1Uq2a2BJhEwarwuROXqvNO/Pjr9YPhlUerFiFRkc1LGJbD5brx3aBEmEHDxby4KqvRFh6TtkkRRNil+DKtXXq7ypRNy44b6smEeaTcbQAiwUgWvHb1scLMFiVdbBkgCzkQDXACgRGWntoAbn1+UxVAOBk0JCXazRpcOyGDBY/tvTjjtbq62CFCnWr56K+u3yJMHmwgPYM1jyiRFhisGSAQgHWFlr5AowpMvfqiklqq/mSB6uhRLioLiVLSXisTh8P1h5IhG3vifQQeBJhyzIN8nvjhUZjSISTI9k5tj6fn6/Bc1CVRegCrJ2eEx0FuTVZhG0ZLPl7Z0QyuZOk1TfAKh0/P96Jq7uz8+5YkywQmLIAqw4hiXDEGKwYEiHAGGewoLXP8UIerIoAK+jBYov6zhJhPn5s35W9/9Dl/t+6Vv/nbQFqAiz2N5lRPl5lyRkyyCOJMJnczw3wAGvcksHi+wISg2X6SoQ1HiwnmTRksDgueHr2syrNlp9T25i0bZmGvtlVweNXsDqVAwMxWA3KNCwqi7Dt8UpZhJElws5b5Wgmd5MZ2inAavIcTKoYrNXw39qgJBFGyiKUv3eFG0v6mtzzLMLYARbJ2n3LqwD5JD5rti8qYRyQCDEq5KRYDJZXVT+CRFhXaNRMyuOkG28Dldy9Mg0iOK9tb359G3dk/z3MA6xRYQPpsldsY4mQbQFG85JrHhszQgpOF5N7KtOwBMRgsLQyDb2yCKsCLM5gtQ2w8sGxl0RIHqwlM1iSZaNVWW2ZhqYerCFmEcpgskMWoVa4z9XBalqmoUIiBDKZ0CVDNHgORpPw3nb8+qIEWKH6ci09WHJPx96IwGDNpwDyLMK+ZRokHvxU9vOCa/sdBygYLBdgNQiMtDpYAHwPViwGi0mEUUzuIQ9W/rt2/V1N7k2KD5NKsvm57P8kEdLf+vQZ7zM1981MMtuKNM7zAEsGeaNx9ry1kQhTodElYr7DZL0ehUajSYQ1UgaXCNuapZsGWJUmd5o4O3qwYkFmfXGTe2W6d34dwUrui5AIR2Jy7ykRYsQG3mWUaaiQCAG/5lXT58CrGM7Pxa+vT4A1AmDDBnJt94LK45n+iynveMz717nQKDFYTCLsanKXuO+92c/zr+l3HADO5N6Gwaos00ASYUSTO5hEuDAPFi32WgRYUUzuuc93M2ewuESIUViea4KmEiGQ9YOTT0PJ6sL9eNq1jNaSRHjOoJfJnTFYUetgNZQI2z746w/JNid9yLNr3ndp9p6TbLUqJcKuhUZjIVRodL5dbZi94EuBy74unGnorQZjerAiZBFyQ7/btLvJoBEY4IFscptvswSBnh4swA+wmrIK5MMK9feq8zWB67+BgKOtRMjbNoQyDVRbigIsug7yOfXtw9f8xyxz8MST+h2H2sIZrDrLAlAdYFEWbJvU/cr2LTCLUPNgaYsQNw4JkzsxN7NNhcFqWcl9447suOsPYX9jAdYiJUIAuPwbgau+s/y6JxEqbXjo3wMufk6LNg0nwDrgWYQt9yJ0gzYv09C3kjtJXaF6PWtFu7sEL898ff17JoeA5/1VuV1Ac31+r0zu7rsaFaviqiq/lzynejNYT/YdahbhqF3mFF/9ynPT5Dbbyq63iWeuViJkRUWbBh98U2GOmBIhUExYIc9Lm1X7Ihisvh4s2iqHJuLpmbyNPYf2y746+xcDFAwSG96IwaKiyYpEuJVnrMYol0HH3IssQmdXaMFgHb6s/B6PwWqSRZj3lc3PAeuXiKBvvHcM1jN/W3+9yoMFAM94Xbc2JYlwCZj1YbDYqpPqaS260KgXuO3h1+Ue+LZlGvoaREPtUXxJmGd+jFY1UuRxWdDspJoeVZwBFKbZiFmEbYy9biBWvjOa3GabLTxYQq6Q4PsONh3UnES4KA+WmLD6bpUDDIvB4mUozKgIRHbPtD/WokF+sS4SoVamgb7Tqt0CWrVvgVmEqgdLmysCAdYhYUjn721baHTjDt9/RX9rmsikHruFByuEOomwLQbEYB28AEs1uTet5mzgDJuy0OiitsrxJJO+E3/LdgGMwVq2REgTIivTMNvKvosYAVbjjJymx+xhcteyCFsxWHl16toAK7IHa7TS/FqbSIR9C40CFRLhCMF7FMKiGawuhUbtHKBio7yI7JACLPJgdSrTIJ5tzkTGCrB4FiFiSIScwVJK32jeMbcgEIZzaUgHinvQtkzD5h1+BiH9bRbJ5N41g5zICTOKNMelAGt5sNpWOS0GWVqNURbhwss0rPnv3StIk3ttpspeebAYgzV9MPu9jxdjJCTCWCuortIPoLN1bjPUhv3MjPV+TZPblAKsJn2/oUTYJvAgiTBUaLTqfE3gAiyaPJTvwIy7MVhRiudGyCK0MwC2uLbJYWA6wABLerD61MFyMtvhuIVGEVMiDPiS6HlUJUIKmqb+/1eOsrpxUiKc5u1tWGh083PC4J7/LZZE2DWccAFWJMfSfik0aoz5FmPMTcaYuTHmWvG3HzfG3GKM+Zgx5qv6NTMi+pRpAIrVGEmNrpbWorbKWZZEKEzudRMR3YeFZxHyQqP5oNiLwaKJbho5wIpZaLQlg0XHqGKwKDjtW2gUYAxWi2dgryVCre2hexRCX7baO1YED9Z86gcE4yPDZLDMpLtEqJncAV+W7t0+IRHGqIPnflUYLG0xXpK0GZNDQZF8DpvWPDPjzEqxc58iEe6hByuEcYd5uArOInHuM1g3Avh7AN7BXzTGPB7ASwA8AcBXA/ivxgzkieceLDMGYNozWJYxWDG2yqlK6V+6RNiwTANnlhbSHs2DlaPK5N7o2OMiizCWROgVGu27F2EXBmukB8UywGpyvVoZDw6a7NqwuE4irOrvMSVC5VhNtgLR2jakSu52XhxrciRiodGIoLZ2qYMVCrCiyYMoxmAgfhah5sdSy0uwMUJKZW5rG8FgzQMJHFp76HmXAZZXpqGnRNj1vjkGK1Kf7eKvXBB6hYzW2psBwJQnkBcC+B1r7TaATxtjbgHwdADv7nO+KOCbPRsDXPufgYu/svnn3WpsK+sYxx8PPPHfAJd1JOlcunVoS48RnO9rmQzWsguNyixCPmH2Tdem7yBGkUEAcNu02OL/bdvDfyImg5V/3gVYbSTCwHU4BquLRCj7O1/xR8wi1Abva34ZuOBLmh9ziHWweJ/lz8GQAqwRFRptkUV44TOAJ/wkcOEz/dddgBWRwXI7L8APWLsi5MFyEqHGYBng8BXAxu3l7458U9Lk7sbmmmf4yu8Edu7PznvZ15bb2mfz7CgMVn4/+ma+OgxHIlxUmYbLAfwt+//t+WvLB5cIAeDRP9ju82ZcTHaTQ9nq4eqf6t4eMhlWrWLHa8B0ujj5LdQuYDiFRjVWh9BHIqRjzSNLhF0nTmrPaKVYxXIGq02AVeXBapNtVisRkgeri0Qos/tYIknvQqOoZrAe+X3tjjmOGWD1ZbBEHSzAfw5iyS0xQG1pU8ttcgh48quUYy0gwHKMM+JIhJRkAqszPKFn+IKn6wGWY7DEc9jUnH7hl2T/1LaOi9IeXcbRKB6syBno51IWoTHmrcaYG5V/L4zRAGPM9xljbjDG3HD33XfHOGQ1ZIDVFqNJsfpvshJrcjzy/wB6J1t08KLBPcTbUOspSex1oVHedVtto6Ade4y4Jncu36D9PRmNfcbQjJi80kIi1CbZyQI9WJ0kwqr+HsPkHlEyk/Xz+sC1r2OBW6+P5YE4l8qHxGBRW6Zns+Cij9VhUR4sV1Ilxl6EYAvChlvlAMW+j7SoJThjOgUO1HcibItkRsViq1OANdJ/b4OFmdyXH2DVXpG19nkdjnsHgIey/1+Rv6Yd/9UAXg0A1157rdXeExV9AywzBnYjBlh1EiHAmIElebCadPyF70UoTe4RGazRJHKAFSGLMJRN13R7kKgMVl0W4Ym8bR0kQq2/jFaAGboP2AALYHbC52mLJBF2A/XD6dnm/TeEPfFgRegrZgRY6AxWiOmlrc0kSCKUXsg+5nTepj6V8WN4sMaL8mAtXyJcFCXyRwBeYoxZM8ZcBeBRAN6zoHO1A9+LsAvMpKBUYzFYlA0E6A+364BL8mA1CrAWXGjUBVYLkgijZxHyrXK6SISB4nuxswhjbJUzmgAr58XJIgQisaENsghbH3JIEiExWLxMw9AZrAf7b9B8LkiEdEwAugcrxGA9VX/dGdOlyZ22uOnJYJGXq0uyUAwPVpdySVUYEIPVt0zDi4wxtwN4BoA/Mca8GQCstTcBeCOAjwD4cwA/aK2r5LY8zPPBrBeDFVkiJL9JE4lwWSb3Jh11GYVGCb1N7lwijDS4ehJhhyzCULmCvhKhC7C6eLAq7s3q+XGyCIE4/b1kch8og9VrqxzafYDKNLDnoM+kGxuGMVh9a1ctJMCKbHKnYwLQyzQE7gExwRLO5E7fKS0eIkiE/Fr7erB6S4Sx+uxwyjT0zSL8AwB/EPjbTwP46T7Hjw63L1kfD9a4kFf2LMCiDrgkibBJgLVyXvazL5sUbE9FmYbeDBY3DMd4yMnT0TGLcOUYKy6IBUmEbTxYNRIhABy6tOgDTbB+UfZT24Q7RrDe1gjcBINksEIm9yEFWMyD1XlLMXGsmB4sXsk91higsb5mkgVXKycqmrJWMEqE9Uuyz9H3yxe/dNy+7QQGIBFGZrCiFATuhwGlmuwBHKXal8G6L/s9RiVhnsFG/5dYBoNFK+DZdjMT+SXPA577duC8xy2oPRVlGmLUwYqdRdjHg/WkV2ZFAfnxCI0ZrJBE2KFMQ51ECADP+I12lPzxx2T95aKvUM4XoaYaDa5uL82hBVgKg9Xm+ZZ7EQLDDbBGi2CwYnqwmEQYs1QL4D9fxgDP+2vg2KPCH/umzwCbd4pDTYDnvxM4+vCivUCcxYOJyGANLYvwXGewzjnMIzBYsU3u3GBNx5dYtgerKctx8XULbE+AwZJyWqdjc4kw0uq1TxbhoUuzf/x4hMYT1Ej/3kYTX+ZuJRFWvPfYIxu2iyHUX2LsCkCDq9vqaWASYe9Co4x1peQXz+Q+oKHdBQRn+4+Zi5IIEdmDFSrOe8G15fdyrD8k+yfB/VlRswjJerHSbRyNKRFG82Cxa1oy9nDGHgBiMVi8DlZfOImwYhU7WmKABQxiJRBksCZH+kuni84i7P2Y0Yos4KtS2zAOf2/jQ4XMHUsijIkY+1rSM07lLWIyWDGkB85gxcoiHGyZhryP7T4YTyKM7sGKLBG6kgoLCHSjZhEq/r024F6/oUmE+ziLcJiIEmBxNiFmFmH+gGvmVNfeJXiwgMUMEm1RMrnn/4/h+Ypuch91nzjV49G1rzUPJk2AwQKyhUEXk/teDRcxSn5QEBSVwYq4FyH3YHWugzU/NyRCj8GKJBFGrYPFswhjlWlowPp2hjC598oi7DmOxswijG1yTwzWHmMWIcDik9ZemdyXKRECw5AbHHMlJt++RUYBFGUaIhpc+2QRlo5H19picgp5sICs33bxYO1VZpqWyND6GDLAGqgHq08dLMCveO8kQtO/z8UEzyLszWCNsmunMh8xIDd7jplFuIixs8RgRcgiXGqAdYALje4rUIfsQ/HHZrAamdyXHGANoKMGC41GYbAGlkUowRmsNp+pCrDaFBqV9XcWjRg7F8gAK2ah0RiSeYwsQiAb0ySDNST2CmAm9404DNbq+ZEDSCYRxq7kvojvopRFGMHk3nWhGjOLMNYCLkmES0IsDxZhz+tgLUkiHAKDdfTKzPgtJ99YEuF8gR6s3hJhBwbryMOyfxomR4ssxUZFZBcpd2jnO2AerK51sIAsaKH7NdQAy7XH9g+wjlwJnPf4vi3y4ZncI1ZyBxbrwZpFquQOxGGwemcR7j+T+wBmzj3EeU8AXngbsHZB92PElghHE19O0jrpsiXCAXRUXPXSbFd4abiOKRHKzVk7H2/UL4uwdDy61haT07PeFF7lH7oUOHVD9nuTVeNC/STa+SJ4sEoSYYRnZ1CbPdMkuwms5xmn9CwMLsDiY2ZPifApP8vGykgw42LxvchK7rFAz6yNsEtB34VqVIkwsgdrAMlZByvAGq8CR76o3zFcJzBxAo82hUaXUckdGIjJ3fiDVUwGi4JcWMTxX5BpNlIWoVsNt5icqgInt/UGGk4AI/FzwYhRpmGRDFbUOlg1i6u6zwNFpe/BM1hA/70IR/EXmrKSe8wswkWa3GcxJEJisJYoEUZnsIYjEQ5g5jzH4HZEPxTHByCzCKu2DjnIZRokFpFFCBvJBxBbIuzAYFXh0OXlYzc5/56XaYhpch9YHSxPIuzAYPFFzyERYA1hQcThsf6R+nBUiDINUfx6C2SwpMm9z/etlfjo0hZ+rLaIvtlzMrmfu3ATewR50B3PZkVQzUgP2hytfoDLNEg4BiumRGjiSYTgdbD6fm80CPaUVwiHeYAVqZJ7TAzdgzWIQqOcwcoZycFKhDwxKFIfjgmvTEMkiXCRDNZCsggjMFidPVip0GgCYcQYrBigCW6+E35Qlp1FOGQGq+82OQCKLMKBVHLXjgf0l1cIXCJsU2h0z8o0LCCLcGgM1ogzWD1M7kCZwRpcgMX6WKw+HBPc5B47i3BPCo3GkAgjMFhdx4d9LBGmAKst3MQeKcAaNQmwliERGjjmZZAMVmSJcBFZhFSmYWgS4eGBS4RRC42eKwxWy9pVvHQH7cs3SQxWJ5QquQ+80GgpwIogES4zizC2RJgKjZ7DMItisLYR/DqWIRECxcM3hDINJSxAIoxZZNBGlAidTyLS5NTW5O4mnD2u5B51L8IIg/cFTwcueUGx6W4fuPbkyRBtr5U+f/jyIjAzoywIH1qANXQPlicRTiPaBLAgD5ao5B6DwYpSB2sgEuHJpwKXPL/b/qiRMcSZc9iIzWDRAzjbHpZECBRS1wBWAiWMIjJYPIswpkSIfCPe3pXcI0uEqyezPjWv6HPa+feMwYqwdYb0YMVYnBx7BPCcN/c/DlA8y12laXo/T1gA8r05BxZgeQzWEAMslkU4342bxLAQBitXF6JkEQ6hTEPkrXKOXgk85y/iHKsnEoPVFtE9WET3Vkx2MdLWu2CRtVx6I3Kh0UVUco9dtDAWg2VMIRM28mCdiyb3cf55i2DyyDLhZRH2YLA4GwlknsTBBVjcgzVAiZBnEc53IpXfWWChUQBe7a5eWYQRPVhd+13szZ4HhBRgtUVsPwz3YIVMgsuogwUw5mSADFZfalseiyTCGEZuTyKMMLHH7nNAMTE3YrD2eKscEyHAAhgTMcBhrjeDlY8bhyWDdXh4nslzQSIEZ7BiBFgLXpTwACsGgxVDIuybRTi0hUEEDHDkGTgW5cGaNcki3GsP1gIzYfoi6lY5C8giBCJWhe6wVU4dSFoa5GbPkQKj2NJDTEgGq+210ndxrkmEQ2SwpEQYc6/JRbEysQKs3ps9j/TfWzUhv99DnGd6IgVYbRE7wBo1MbkvaSXuVmEHgMGiLMJYJncgN8xGzEiKOTm1YrCWJRH2PN8ysm+bIpoHS0qEhwcYYA2dwZISYUQP1l5IhEPZi7BrvzMmu+dD67cRMMCRZ+BwHXIBWYRDNLkDw1xZ0H1bORrhWEwijJlBNJ8iziO2AAbLebCaBM/nYBYhcG4xWK09WPk9KkmER4fnZRm8yX3MAqxIEuFCt8pB1l+imtxjZBH2UFjG68NcyPfEwJ7EcwCLMrk3ySLc8zINA2awHvIs4Mk/m6XO98WITO7jyBLhblwGK+bkRBtnr19c/97RXjNYkZinITNYsg5W23t7yXOy/n/hM/zXn/ATwO7pOE2MhdHATe5kEQCyZzaqB2uBDNbuA9nvVAet63GA/gxW32fsab8GnHhyv2MMECnAaotlFBpddhbhEBmsySHgCS+Pc6zYHiwwBiumByuqRHgx8Nh/3vD8S5IID4QHKy/n0bafTI7o/f8hX967adExdAZrtJqNv9ZGLNOwaAaLBUYrx3scJ9JehH2v88pv7/f5gWKIS7thY2GFRge2VQ6w+FXYULCILEIg399woAxWK+xxFmF0iXCAw5xr0zxiYD9QeB6sATJYo9UsychO8/9HZLAW6cECsiSHPtJcNIlwgM/YAJDuSlsstNBoTSX3pTFYA5QIY8LVwYplcqfaZtN+g5873gIYrFbnX1IWYTST+wCDF9dHYtZfGyiGzmCNcwZrvpv9P2YdrEUzWDLJoetxli0R7lOku9IWzoMVuw5WlQeLKOtlebD2O4M1ib8XIRA/i3BZk9Ner1IPRB0suqfEYA2wjbEw9M2eSSJ0hTtjVnJfFIOV9xeZ5NAakSq57+cFQg/s46d6QYjOYNFKdoBZhKODxGBFzCJEbIlwAVmEXc5/zkmEkco9LALEbEb1/g0Uo3NAIrRTVvbgXGKwegZYZpwFgV3HeHedKZTQkO5KWyys0GjVVjnLruS+zxksl0UYSarhZRqGWgery/n3OotwP5vcgTyw71ho9FzC0CVC6ifTs/n/I3mwFrlFUyyJcOU4sH5Rj3aYfIzbx/23B/b5zLkAULARqw5WkyxCN1GkMg0LwaIquc8jlWlYRB2sNlhaodF9bHIH4ApcxkquGCqGvhehC7Ae9P/f76CLtVbQs9hXInz8vwYe/tL+bdnP/bcHUoDVFosyuc93whPB0vci3OfdhJvcY5ZViCUR0uC1LHllaRJhz/ONE4M1CPAAfYhjycIYrAX2u1gS4eqJ7F/vtuzj/tsD6a60xaIkwir2ZNlZhPve5D6OzGBxk/tAN3vucv696n8HotAoAIwOlgdriPIgsMAAa5EMFpnce0qEMUByaEIJ6a60RfRCo3yrgTqJMJVpWAgci7gbWSKMvFXOsjKwUqHRxYAYrC6FRs8lLLvMSB2ov8WUCM1obxis9UsXd46mWDRbdw5jHz/VC0L0rXLYKifUSc0EgMn/7SEOCoNFQa6dxs8ijFqm4YBIhLHLNAw1eCEP1nyfM1hANoYcNAZrkXKoGQPrDylk8GUiMVhBpLvSFovyYPFjl95jssk1MViLgWnAIrY63oK2ylm6RLhHQUAs79S5wGDhADBYQHat50qAFatMw6IZrL4ZhLGQPFhB7HNqYgE4+khg9SRw6JI4x+OrnKpB9vjjgKOPiHPOpjgwJvcGQW6r4zWobdYGxx4JrF8CrJzof6wuOHQ5MDkGHL1q7863cl7/8w250CjgZxEONQiMhdFkwBKhCLBisELHHgUcf0z/41Qdf+XY4o7fBkkiDGKfz5wLwMXPBr753njHazq5f8374p2zKQ5MmQbOYEVknHbPdK+QzHH51wN/787+x+mKw5cB33p67863fhHwLff3P865wGBR/bWhBoGxcNAYrCf8ePZvUXjmby/u2G2RJMIg0l1ZNmLLUzFxYBisBUmE00gBVkI3nBMerPn+r4MFZAvJoTJY4wV4sA4SUoAVRLory8YosjwVEweFwYr9HdAxYjFYCd2QGKzhYHQumNxjFho9QEgBVhDpriwbsf0/MZEYrI7IH6vZBjA5HOF4CZ0wHjqDNS4YrKE9+7FxLkmEicFqh+TBCmKgI88Bgmlocl8GXHp+CrDaHY99j+PEYC0NJlJF+IXhAJnczWSYGz0DKcDqi7QXYRDpriwb54JEuN8HnNhBLv8ek0S4PAzeg8W2yhlqG2PBjJdXKLcOpQArSYStkCTCIPY5NXEO4FyQCBOD1fJ4bLBJEuHyMPi9CA8Qg/Xw7wGOP3bZrdBR8mDt8wVlbCSJMIh9PnOeAzgnsgj3+YCzKA8WkBisZeJcMLkflEKjT/q3y25BGIso03CQkBisINJdWTbOCYlwn8fhsb+DUZIIB4FUaDShCWgBOYtYaPQgIVVyDyLdlWUjdpHLmDgoZRoWyWCNk0S4NJwLDNZB8WANGdRPdnOJcL+Pd7GRJMIg0lO9bJgRy9YbWCc9KAzWoiq5A4nBWiYGb3JPDNYgQP1klrIIOyFJhEGkuzIEkIl8aIPsgfFgxS40mgKsQeBcYrDSULw8pDIN/ZACrCD2OTVxjsBJcQObCFIWYf/jJYlweRg6g3WQ6mANGY7B2krBQheMVgFjlt2KQWKfz5znCIbOYKUAqyUSgzUInEsMVprUl4dRHlTZeWKvuuDJr1p2CwaLfT5zniMgj9PQBtmDIhFG34swBViDwNAZrOTBGg5GqxmDlYqMtsdFz1x2CwaLgY48BwxDZ7CSyb378VKh0eVh8IVG882eD0IdrKGDAqv9vphM2FOkp3oIGA08wNrvactpL8L9CddvBzrMmRGAA7LZ89Dh2M59PtYl7CkGOvIcMAzV5D46KAxWkgj3Jc4JD9Ys92ANtI0HBY7BShJhQjykAGsIGLpEmEzu3Y+XJMLlYTx0DxaZ3GfDbeNBQZIIExaA9FQPAWagJvfVk8Dq+fs/BTdlEe5PnAsM1nyaJMIhIAVYCQvAPqcmzhEM1YP16B8Cvuhblt2KxcPLIoxYyX20kgbsZWLoAdZ4DZhvpUKjQwA9p0kiTIiI9FQPAUOVCCeHgaNXLbsVi8eiJMJUZHS5GHqZhvGhrDRAYrCWj8RgJSwAAx15DhiGanI/KFhUFmGSB5eLwTNYh4DZZio0OgSkLMKEBSA91UPAUCXCg4JFZREmBmu5OCcYrM3EYA0B1FfGSSJMiIeBjjwHDEOVCA8KFiURJgZruTBjAGa4z9X4EDDdRCo0OgAkBithAej1VBtj/l9jzEeNMR8yxvyBMeYE+9uPG2NuMcZ8zBjzVb1bup8x1K1yDgpiV3JHkggHAWPyiXOgz1VisIaD5MFKWAD6jjxvAfBEa+3VAD4O4McBwBjzeAAvAfAEAF8N4L8ak0aQIBKDtVwsai/CVANr+bjgWuC8xy+7FTomhwBYYL6bFlfLxjgVGk2Ij15lGqy1f8H++7cAvjn//YUAfsdauw3g08aYWwA8HcC7+5xv3yKZ3JeLJBHuXzz/nctuQRjjQ8Xv6dlfLhKDlbAAxFw2/QMAf5b/fjmAz7K/3Z6/VoIx5vuMMTcYY264++67IzbnHEJisJaLRWURpn0IE6owXmf/SQzWUpECrIQFoJbBMsa8FcAlyp9+0lr7pvw9PwlgCuC32jbAWvtqAK8GgGuvvda2/fy+QMoiXC5iZxEiSYQJDZAYrOEg7UWYsADUBljW2udV/d0Y8z0Avh7Ac621FCDdAeCh7G1X5K8laBjqVjkHBbFN7qkOVkITeAFWevaXisRgJSwAfbMIvxrAvwbwjdbaDfanPwLwEmPMmjHmKgCPAvCePufa10gM1nKRPFgJy0BisIaDVKYhYQHouxfhfwGwBuAtJtsQ+G+ttf/UWnuTMeaNAD6CTDr8QWvtrOe59i+SyX25WFQWYSo0mlCFFGANB0kiTFgA+mYRPrLibz8N4Kf7HP/AIJncl4vYDNbkKPCoHwQu+9r+x0rYv0gS4XDgNntODFZCPPRlsBJiIAVYywWf3KIwWAZ42n/pf5yE/Y1JYrAGg+TBSlgA0rJpCHASVfo6loaUaJCw10gM1nCQJMKEBSA91UMATe6jtIpdGpIPLmGvwetgpX63XCQGK2EBSAHWEJAm9+UjfQcJe43EYA0HKcBKWADSUz0EpDINy0f6DhL2GimLcDgYpzINCfGRAqwhIJncl4/EYCXsNXiAlYbi5SJ5sBIWgPRUDwHJ5L58uAArfQcJe4TRKgCT/Z4C++UiSYQJC0CaTYaAxGAtH+k7SNhrGFOwWCmwXy5SgJWwAKSneghIWYTLR5IIE5YBqoWV+t1ykSTChAUgBVhDQJrcl4/0HSQsA4nBGgYSg5WwAKSneghIGWzLR/oOEpaBUV4LK/W75SIFWAkLQAqwhgCTTO5Lh5vgzFKbkXDAkCTCYcDtRZgkwoR4SDP6EJDYk+XDjDOZxqQAK2EPkSTCYWD94uzn2kOW246EfYW02fMQkDLYlg8zSfc/Ye8xTgzWIHDe44Bv/DRw9MpltyRhHyEtm4YAGlxTFuHyYMZpkkvYe7hio2koXjpScJUQGempHgKSRLh8pAArYRlIDFZCwr5FCrCGgGRyXz5GSSJMWAKSByshYd8iPdVDQPJgLR9mjPQ4JOw5UhZhQsK+RZpRhoAkES4fZpw8cAl7D1cHKw3FCQn7DempHgLOeyJw/DHAoUuX3ZKDi5RFmLAMJAYrIWHfIpVpGAJOfjHw9R9ddisONpLJPWEZSB6shIR9i/RUJyQAKcBKWA5SFmFCwr5FCrASEoDcB5ceh4Q9RqqDlZCwb5Ge6oQEIDFYCctBYrASEvYtUoCVkACkACthOUgerISEfYv0VCckAFkWYSrTkLDXSFmECQn7FimLMCEBAB7+PcDGZ5fdioSDhodcBzzynwDnPX7ZLUlISIiMFGAlJADA5V+37BYkHESsXwQ8/deX3YqEhIQFIEmECQkJCQkJCQmRkQKshISEhISEhITISAFWQkJCQkJCQkJkpAArISEhISEhISEyUoCVkJCQkJCQkBAZKcBKSEhISEhISIiMFGAlJCQkJCQkJERGCrASEhISEhISEiIjBVgJCQkJCQkJCZGRAqyEhISEhISEhMhIAVZCQkJCQkJCQmSkACshISEhISEhITJSgJWQkJCQkJCQEBnGWrvsNjgYY+4GcNuCDn8hgHsWdOxzGem+6Ej3RUe6LzrSfdGR7ouOdF90nIv35WHW2ou0PwwqwFokjDE3WGuvXXY7hoZ0X3Sk+6Ij3Rcd6b7oSPdFR7ovOvbbfUkSYUJCQkJCQkJCZKQAKyEhISEhISEhMg5SgPXqZTdgoEj3RUe6LzrSfdGR7ouOdF90pPuiY1/dlwPjwUpISEhISEhI2CscJAYrISEhISEhIWFPsO8DLGPMVxtjPmaMucUY8/Jlt2eZMMbcaoz5sDHmA8aYG/LXThpj3mKM+UT+8/xlt3MvYIx5jTHmLmPMjew19V6YDL+S96EPGWOuWV7LF4vAfXmlMeaOvN98wBjztexvP57fl48ZY75qOa1eLIwxDzXGvN0Y8xFjzE3GmH+Wv36g+0vFfTnQ/QUAjDHrxpj3GGM+mN+bf5e/fpUx5u/ye/AGY8xq/vpa/v9b8r9fudQLWBAq7strjTGfZn3mKfnr5/azZK3dt/8AjAF8EsDDAawC+CCAxy+7XUu8H7cCuFC89gsAXp7//nIAP7/sdu7RvXgWgGsA3Fh3LwB8LYA/A2AAfCmAv1t2+/f4vrwSwL9S3vv4/JlaA3BV/qyNl30NC7gnlwK4Jv/9GICP59d+oPtLxX050P0lv1YD4Gj++wqAv8v7whsBvCR//dcBfH/++w8A+PX895cAeMOyr2GP78trAXyz8v5z+lna7wzW0wHcYq39lLV2B8DvAHjhkts0NLwQwOvy318H4JuW15S9g7X2HQBOiZdD9+KFAH7DZvhbACeMMZfuSUP3GIH7EsILAfyOtXbbWvtpALcge+b2Fay1d1pr35f/fgbAzQAuxwHvLxX3JYQD0V8AIP/uH8z/u5L/swCeA+D38tdln6G+9HsAnmuMMXvT2r1DxX0J4Zx+lvZ7gHU5gM+y/9+O6gFgv8MC+AtjzHuNMd+Xv3axtfbO/PfPA7h4OU0bBEL3IvUj4Idyiv41TEY+cPcll26+GNnKO/WXHOK+AKm/wBgzNsZ8AMBdAN6CjLG731o7zd/Cr9/dm/zvDwC4YE8bvEeQ98VaS33mp/M+8x+MMWv5a+d0n9nvAVaCjy+31l4D4GsA/KAx5ln8jzbjZFNaKdK9EPg1AI8A8BQAdwL4paW2ZkkwxhwF8L8B/Ki19jT/20HuL8p9Sf0FgLV2Zq19CoArkDF1j11ui4YBeV+MMU8E8OPI7s/TAJwE8LLltTAe9nuAdQeAh7L/X5G/diBhrb0j/3kXgD9A9tB/gSjX/Oddy2vh0hG6Fwe6H1lrv5APinMA/w2FrHNg7osxZgVZEPFb1trfz18+8P1Fuy+pv/iw1t4P4O0AnoFM4prkf+LX7+5N/vfzANy7ty3dW7D78tW53GyttdsA/if2SZ/Z7wHW9QAelWdurCIzD/7Rktu0FBhjjhhjjtHvAF4A4EZk9+Ol+dteCuBNy2nhIBC6F38E4LvzjJYvBfAAk4b2PYTn4UXI+g2Q3ZeX5BlQVwF4FID37HX7Fo3cC/M/ANxsrf1l9qcD3V9C9+Wg9xcAMMZcZIw5kf9+CMDzkXnU3g7gm/O3yT5DfembAbwtZ0X3FQL35aNsoWKQ+dJ4nzlnn6VJ/VvOXVhrp8aYHwLwZmQZha+x1t605GYtCxcD+IPcNzkB8NvW2j83xlwP4I3GmH8I4DYA37rENu4ZjDGvB3AdgAuNMbcD+LcAfg76vfhTZNkstwDYAPC9e97gPULgvlyXp01bZJmo/wQArLU3GWPeCOAjAKYAftBaO1tCsxeNZwL4LgAfzr0jAPATSP0ldF++7YD3FyDLsHydMWaMjMh4o7X2j40xHwHwO8aYVwF4P7IAFfnP3zTG3IIsyeQly2j0HiB0X95mjLkIWbbgBwD80/z95/SzlCq5JyQkJCQkJCRExn6XCBMSEhISEhIS9hwpwEpISEhISEhIiIwUYCUkJCQkJCQkREYKsBISEhISEhISIiMFWAkJCQkJCQkJkZECrISEhISEhISEyEgBVkJCQkJCQkJCZKQAKyEhISEhISEhMv5/D8PYRHPHxdkAAAAASUVORK5CYII=\n", "text/plain": [ "<Figure size 720x432 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig = plt.figure(figsize=(10, 6))\n", "\n", "\n", "newplot=plt.plot(df_diff2 , color='orange',label='Second order')\n", "\n", "plt.legend()\n", "plt.title(\"Differenced data -2\")\n", "plt.show(block=False)" ] }, { "cell_type": "markdown", "id": "7870f5aa", "metadata": { "papermill": { "duration": 0.01278, "end_time": "2022-10-27T19:24:00.393159", "exception": false, "start_time": "2022-10-27T19:24:00.380379", "status": "completed" }, "tags": [] }, "source": [ "Second order" ] }, { "cell_type": "code", "execution_count": 10, "id": "444df9b9", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:24:00.422694Z", "iopub.status.busy": "2022-10-27T19:24:00.421405Z", "iopub.status.idle": "2022-10-27T19:24:00.682488Z", "shell.execute_reply": "2022-10-27T19:24:00.681311Z" }, "papermill": { "duration": 0.2797, "end_time": "2022-10-27T19:24:00.685949", "exception": false, "start_time": "2022-10-27T19:24:00.406249", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 720x432 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig = plt.figure(figsize=(10, 6))\n", "\n", "\n", "newplot=plt.plot(df_diff2 , color='orange',label='Second order')\n", "newplot=plt.plot(df_diff , color='red',label='First order')\n", "\n", "plt.legend()\n", "plt.title(\"First and second order differences overlaid\")\n", "plt.show(block=False)" ] }, { "cell_type": "markdown", "id": "9e6b816a", "metadata": { "papermill": { "duration": 0.014622, "end_time": "2022-10-27T19:24:00.715231", "exception": false, "start_time": "2022-10-27T19:24:00.700609", "status": "completed" }, "tags": [] }, "source": [] }, { "cell_type": "code", "execution_count": 11, "id": "23c2cf07", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:24:00.745455Z", "iopub.status.busy": "2022-10-27T19:24:00.745063Z", "iopub.status.idle": "2022-10-27T19:24:01.003417Z", "shell.execute_reply": "2022-10-27T19:24:01.002259Z" }, "papermill": { "duration": 0.27648, "end_time": "2022-10-27T19:24:01.006024", "exception": false, "start_time": "2022-10-27T19:24:00.729544", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 1008x432 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots(figsize=(14, 6))\n", "\n", "\n", "plot_acf(df_diff.dropna(), color=\"green\", lags=100, ax=ax);\n", "\n" ] }, { "cell_type": "code", "execution_count": 12, "id": "beedcd15", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:24:01.039434Z", "iopub.status.busy": "2022-10-27T19:24:01.038742Z", "iopub.status.idle": "2022-10-27T19:24:01.417887Z", "shell.execute_reply": "2022-10-27T19:24:01.416536Z" }, "papermill": { "duration": 0.398873, "end_time": "2022-10-27T19:24:01.420219", "exception": false, "start_time": "2022-10-27T19:24:01.021346", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 1008x432 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, ax = plt.subplots(figsize=(14, 6))\n", "\n", "\n", "#plot_acf(df_diff.dropna(), color=\"green\", lags=100, ax=ax);\n", "plot_pacf(df_diff.dropna(), method=\"ywmle\", color=\"magenta\", lags=100,ax=ax);" ] }, { "cell_type": "markdown", "id": "1f50b8e2", "metadata": { "papermill": { "duration": 0.016297, "end_time": "2022-10-27T19:24:01.451616", "exception": false, "start_time": "2022-10-27T19:24:01.435319", "status": "completed" }, "tags": [] }, "source": [ "No idea whether this is correct. There's less spikiness than in the original data. The jumps at the start are probably to do with the first few numbers being random before the loop division is added in." ] }, { "cell_type": "code", "execution_count": 13, "id": "f6f71210", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:24:01.484391Z", "iopub.status.busy": "2022-10-27T19:24:01.483858Z", "iopub.status.idle": "2022-10-27T19:24:02.575358Z", "shell.execute_reply": "2022-10-27T19:24:02.574134Z" }, "papermill": { "duration": 1.111362, "end_time": "2022-10-27T19:24:02.578910", "exception": false, "start_time": "2022-10-27T19:24:01.467548", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " SARIMAX Results \n", "==============================================================================\n", "Dep. Variable: values No. Observations: 365\n", "Model: ARIMA(0, 0, 2) Log Likelihood -1204.698\n", "Date: Thu, 27 Oct 2022 AIC 2417.396\n", "Time: 19:24:02 BIC 2432.996\n", "Sample: 0 HQIC 2423.596\n", " - 365 \n", "Covariance Type: opg \n", "==============================================================================\n", " coef std err z P>\|z\| [0.025 0.975]\n", "------------------------------------------------------------------------------\n", "const 0.1268 0.004 31.401 0.000 0.119 0.135\n", "ma.L1 -0.8473 0.285 -2.969 0.003 -1.407 -0.288\n", "ma.L2 -0.1524 0.080 -1.916 0.055 -0.308 0.003\n", "sigma2 43.2102 13.335 3.240 0.001 17.075 69.346\n", "===================================================================================\n", "Ljung-Box (L1) (Q): 0.23 Jarque-Bera (JB): 7.97\n", "Prob(Q): 0.63 Prob(JB): 0.02\n", "Heteroskedasticity (H): 0.88 Skew: -0.13\n", "Prob(H) (two-sided): 0.49 Kurtosis: 2.32\n", "===================================================================================\n", "\n", "Warnings:\n", "[1] Covariance matrix calculated using the outer product of gradients (complex-step).\n" ] }, { "data": { "text/plain": [ "<function matplotlib.pyplot.show(close=None, block=None)>" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 1008x432 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "\n", "\n", "#so we need training and test data. This has to be selected via a discrete chunk over time\n", "#and not randomly, so will split the data into two pieces\n", "\n", "#two thirds train\n", "# on third test\n", "\n", "\n", "x=len(df_diff)\n", "y=int(x/3)\n", "\n", "y=y2\n", "\n", "#z=y2\n", "#y=y3\n", "\n", "\n", "#train=df_diff[:y]\n", "test=df_diff[y: x]\n", "\n", "train=df_diff[:x]\n", "\n", "model = ARIMA(train, order=(0,0,2))\n", "model_fit = model.fit()\n", "\n", "s=model_fit.summary()\n", "model.update(test)\n", "\n", "print(s)\n", "\n", "fig = plt.figure(figsize=(14, 6))\n", "prediction = model_fit.predict(start=0, end=x, dynamic=False)\n", "\n", "plt.plot(train, color='blue', label='training')\n", "plt.plot(test, color='red', label='test')\n", "\n", "plt.plot(prediction, label='prediction')\n", "plt.legend()\n", "plt.show" ] }, { "cell_type": "markdown", "id": "83e15deb", "metadata": { "papermill": { "duration": 0.016817, "end_time": "2022-10-27T19:24:02.613506", "exception": false, "start_time": "2022-10-27T19:24:02.596689", "status": "completed" }, "tags": [] }, "source": [ "So originally the idea was to split it into test and train components. Which I did and the model was completely unable to predict within the test area. if we had, say, training on 250 days and test for the other 100+ days of the year then the model would make predictions for the 250 days and then flatline. Playing with parameters made it worse, until eventually fed the entire year series to the model then it would be able to give the relatively closely fitting plot as seen above.\n", "\n", "The plot still has train (2/3) and test (1/3) displayed in different colours. Have kept this to show initial approach.\n" ] }, { "cell_type": "code", "execution_count": 14, "id": "e554a42f", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:24:02.650017Z", "iopub.status.busy": "2022-10-27T19:24:02.649095Z", "iopub.status.idle": "2022-10-27T19:24:03.060468Z", "shell.execute_reply": "2022-10-27T19:24:03.059309Z" }, "papermill": { "duration": 0.432134, "end_time": "2022-10-27T19:24:03.062791", "exception": false, "start_time": "2022-10-27T19:24:02.630657", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "<function matplotlib.pyplot.show(close=None, block=None)>" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 1008x432 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig = plt.figure(figsize=(14, 6))\n", "\n", "plt.plot(prediction, label='Prediction only')\n", "plt.legend()\n", "plt.show" ] }, { "cell_type": "markdown", "id": "45b3ac98", "metadata": { "papermill": { "duration": 0.019878, "end_time": "2022-10-27T19:24:03.103180", "exception": false, "start_time": "2022-10-27T19:24:03.083302", "status": "completed" }, "tags": [] }, "source": [ "Eventually this worked when training was extended to the full dataset, otherwise the end third would be entirely flat. Clearly there is a way of doing this with test and train but am not sure what mistakes am making." ] }, { "cell_type": "code", "execution_count": null, "id": "d33c60b4", "metadata": { "papermill": { "duration": 0.019118, "end_time": "2022-10-27T19:24:03.142148", "exception": false, "start_time": "2022-10-27T19:24:03.123030", "status": "completed" }, "tags": [] }, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": 15, "id": "b25a88f9", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:24:03.182036Z", "iopub.status.busy": "2022-10-27T19:24:03.181610Z", "iopub.status.idle": "2022-10-27T19:24:04.157501Z", "shell.execute_reply": "2022-10-27T19:24:04.156239Z" }, "papermill": { "duration": 0.999701, "end_time": "2022-10-27T19:24:04.160949", "exception": false, "start_time": "2022-10-27T19:24:03.161248", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "<function matplotlib.pyplot.show(close=None, block=None)>" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 1008x432 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "model2=ARIMA(df_diff, order=(0,1,1)) \n", "model_fit2= model.fit()\n", "\n", "x=len(df_diff)\n", "\n", "\n", "train2=df_diff2[0:x]\n", "#test2=df_diff[y: x]\n", "\n", "\n", "fig = plt.figure(figsize=(14, 6))\n", "prediction2 = model_fit2.predict(start=0, end=x, dynamic=False)\n", "\n", "plt.plot(train2, color='green', label='training -1')\n", "\n", "\n", "plt.plot(prediction2, label='prediction', color=\"orange\")\n", "plt.legend()\n", "plt.show\n", "\n", "\n" ] }, { "cell_type": "markdown", "id": "fad2488a", "metadata": { "papermill": { "duration": 0.020789, "end_time": "2022-10-27T19:24:04.203369", "exception": false, "start_time": "2022-10-27T19:24:04.182580", "status": "completed" }, "tags": [] }, "source": [ "Here is where it gets weird. Because I can't use the ARMA model package, tried an ARIMA model with different parameters. Despite this being a different model with different name and the training data composed of 100% of the values dataset - the prediction kept failing and going flat two thirds of the way in. Thought at first I'd put in a wrong variable from the previous plot, but it turns out that Kaggle seems to only be running one incidence of the ARIMA model.Once I set the train data to full in the previous code the predictions in this one also started working on the entire 365 day set.\n", "\n", "Assume that it is possible to instantiate multiple identical models in a piece of code independently, tho could not get round this problem. Suggestions welcome, especially funny ones mocking me for poor Python skills or chuckling at the really obvious thing I totally forgot. At present am so bewildered I can even cope with someone using the word lol unironically." ] }, { "cell_type": "code", "execution_count": 16, "id": "614eb4a9", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:24:04.247381Z", "iopub.status.busy": "2022-10-27T19:24:04.246997Z", "iopub.status.idle": "2022-10-27T19:24:04.515163Z", "shell.execute_reply": "2022-10-27T19:24:04.514005Z" }, "papermill": { "duration": 0.294122, "end_time": "2022-10-27T19:24:04.518657", "exception": false, "start_time": "2022-10-27T19:24:04.224535", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "<function matplotlib.pyplot.show(close=None, block=None)>" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 1008x432 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig = plt.figure(figsize=(14, 6))\n", "\n", "plt.plot(prediction2, label='prediction only')\n", "plt.legend()\n", "plt.show" ] }, { "cell_type": "markdown", "id": "b2f7bdce", "metadata": { "papermill": { "duration": 0.022155, "end_time": "2022-10-27T19:24:04.563320", "exception": false, "start_time": "2022-10-27T19:24:04.541165", "status": "completed" }, "tags": [] }, "source": [ "Predicting based on information you already have and being unable to extrapolate it into the future isn't ideal. The shame envelops me in a cloud of doom. Which also funnily enough describes the weather today." ] }, { "cell_type": "code", "execution_count": 17, "id": "32b603aa", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:24:04.610761Z", "iopub.status.busy": "2022-10-27T19:24:04.609757Z", "iopub.status.idle": "2022-10-27T19:24:04.881388Z", "shell.execute_reply": "2022-10-27T19:24:04.880341Z" }, "papermill": { "duration": 0.298172, "end_time": "2022-10-27T19:24:04.883982", "exception": false, "start_time": "2022-10-27T19:24:04.585810", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "1 1\n", "2 2\n", "3 3\n", "4 4\n", "5 5\n", " ... \n", "359 359\n", "360 360\n", "361 361\n", "362 362\n", "363 363\n", "Name: index, Length: 363, dtype: int64\n", "1 1.125\n", "2 -12.875\n", "3 10.125\n", "4 -10.875\n", "5 1.125\n", " ... \n", "359 13.125\n", "360 -11.875\n", "361 17.125\n", "362 -5.875\n", "363 -6.875\n", "Name: values, Length: 363, dtype: float64\n", "(123,)\n", "(365,)\n" ] }, { "data": { "text/plain": [ "<function matplotlib.pyplot.show(close=None, block=None)>" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "ff=df['index']\n", "\n", "\n", "gg=ff[1:364]\n", "gg=gg.dropna()\n", "\n", "print(gg)\n", "#ff=ff.drop(0)\n", "#ff.pop(0)\n", "\n", "from sklearn.linear_model import LinearRegression\n", "\n", "\n", "\n", "\n", "zz=df_diff[1:364]\n", "print(zz)\n", "x=len(df_diff)\n", "zz=zz.array.reshape(-1, 1)\n", "test2=df_diff[y: x]\n", "\n", "train2=df_diff[:x]\n", "\n", "newff=gg.array.reshape(-1, 1)\n", "\n", "#print (newff)\n", "\n", "model = LinearRegression()\n", "model.fit(newff, zz.dropna())\n", "\n", "y_pred = model.predict(zz)\n", "\n", "print (test2.shape)\n", "print (train2.shape)\n", "\n", "plt.plot(zz, label='data')\n", "plt.plot(y_pred, label='prediction only')\n", "plt.legend()\n", "plt.show" ] }, { "cell_type": "code", "execution_count": 18, "id": "4175238d", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:24:04.935543Z", "iopub.status.busy": "2022-10-27T19:24:04.935163Z", "iopub.status.idle": "2022-10-27T19:24:05.206281Z", "shell.execute_reply": "2022-10-27T19:24:05.205017Z" }, "papermill": { "duration": 0.300071, "end_time": "2022-10-27T19:24:05.208755", "exception": false, "start_time": "2022-10-27T19:24:04.908684", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "<function matplotlib.pyplot.show(close=None, block=None)>" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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PvRfX9tNOtt+jHm0xNz8D4C9bP/teAO8uiuJlAN5d/r9Hj04hLCMBHRAc/tmATmGVzM0qm3iuan89DjcoUZEfoew1JRHObx/NTC+NXSuVpUUh1juWpfGxuDcUaA9ZLvDGf/tu/NYnn+p0P7uTDPc8vYWLO+0nFS5sTzDNBHY6lkX2cKOV4KYoivcDuGz9+GsA/Gz5/c8C+No29tWjRx1ovWMHOUfDUGB19UOr7HNT9MFNjzmwStfAVYGCm2d75mZp0D6SKMTmMMJuh/2z+DO4ypqbIx7bYJwJXNie4N5ntjvdT1revw892L6jHq05jhLDfJjQZc3NjUVRUAvpZwDc6PpQEAR/JwiCO4MguPPChQsdHk6P5wLsAEAthI4Aj38QfW56WVo7OL89PrJZ+VVDvdtHaNEwLWVpR7XmhgxKVsHc0Ng1KGtu9jrMnOc5D25WwNw8RwwF6B2/0rHTHT2XH3rgYgfbPjpmRocRKzEUKGRq1nmHi6L48aIo3lAUxRvOnj27isPpcYShraDNr0chy0unsIoMoXZLW7Es7Yg28vxnv/YpfM87P3Ug+/79zz6Dt/3h/Qey7y7QMzeHD/kKJbW0j7isuemSueGNO7sOOIqi0FbQR0iS6QKx+V0336ZE4QcfbD+4oWfjKI1ThwldBjfPBkFwEwCUX893uK8ePQBUm3geJWelVS7qdM3N6qyg5f6OZnDz+OU9PH3tYLLyv/vpp/GO9z5wZK6tbfN+FEBuaReOKLunmniuwlCAydLICrqrwnTOonfNqE8yoWTXR0CIUAvF3HRsjU7z3OOX9/H45b1Wt02s3lEPRK9XdBnc/BaAby2//1YAv9nhvnr0AMD63Fhfj4IsbZVW0NotbQVNPNkidb/DLOtB4uLOBFsH5JozTgUyUeAzT147kP23jewIZkQnSpZ2NJkbscqam9wMbjJRdCaH42xN15K7CUs05UddllZQcNPtmJnlAq+66TgA4EMtszdpL0s7ULRlBf1LAD4M4BVBEDwRBMH/CuAHAHxFEASfB/CXyv/36NEptCzN7nNz+AeYg6i5WQVzw8f+8QoWP6vGJMuxPc6wNT4Y1xxaON/9+NUD2X/boHXdUcqI0sL4ws7kSC6GVlnDR2O9rLmJAAB7HfW6WSVzs8+Y1yOQq6sFveNd19xkosCrnncMZ48N8eGWTQUoAD2K7/NhQNzGRoqi+EbPr97cxvZ79GgKb5+bI5DpKqzA7a5HryAOA7zmBSdb3xftYxU1MEfdCvrSjpygdyYZslwgjlbbO5kC1E88dnWl++0Kmo09OouGSSoQBPK9u7Q7wbljo4M+pFYhxOpY54zX3AzlEmdnkuHUxqD9fa2w5sYIbo5QYO+CZm6mEKJAGAad7CfLC8RRgNvObLQuG1aW9X1wcyBY7Szbo0fHsJmbVbIdXUPZWpeT6Pe/6x788B/c18m+VKZ1JcyNvjeTIxzcAMD2AbA3R4+5OZp9bp53XAY0R7GRp6q5WUFwY8jSBjK42etI7mpaQXfM3Ew5c3P4k3V1oHdcFMDWuDtpWiYKxFGI46OkdWY9O4Lj1GFCH9wcAvzKnz7WerHbUYUyErD63RwFfb6dsd5P88407DR5rqLmht+a/SMY3Fzc1YvVg+hWTVKgJ6/u4/wRsBrOxNHLiE6yHC84tQ7gaDbyXKmhAJelDaUsbXfaTVLBlKWtkLk52rGN8W53WXeTCYE4DHB8LW69JpKeh6NkfHKY0Ac31zkmWY7v+fVP4zc+8eRBH8qhgMr4VJibwz8bFJahQJqLzhZ4mWriuVrm5ij2ubm4rYObLrOQPozTHDedkKzAJ44Ae3PU+kcURYFJJvCCG2RwcxRMBYQo8L/85EfxvvukSeoqm3jS+JjEgWJudjvqdcNldl1L7sbpc4e54WxHl3bQeV4gDkOcWEvaD26O2Dh12NAHN9c5aDJYRQb9KEDJ0iy3tPQIDDC2ScI0E50xUqrmZgVMCmftj2TNDZucD4q5ed2LTiGJgiNRd2M36j3syESBogCef2oNwNGQpaVC4E8+fxGfekI69ClJ7SrMUKjmJgyxQcxNR4YC+YHJ0jrd1YGDsx1dmgqkQiCOAhwfJdieZK2OKarmppelHQj64OY6Bw2Yq8h4HQXYRgLCYm6EKPDA+Z2DObglQeMuncs0E505RvFAqmvWi/a1lkRHkrm5tMOYm/3V19yMU4HjowSvvuk47n78ysr33zaOGnNDssFjwxinNwZ49gjI0ohYoOTLaq2gtSxN19x0xdwwWVrHbAo3dznqC2aDuemw100uilKWlgAAdlqsu+mZm4NFH9xc50jZQrbHbNCYqI0F5FfKorzn3vP4yn//x3j62v4BHN3i4JksxdzkojOjBM4IdW3fSguf9UF0NGtudqYYxHKoPRjmJscwDvH8U2uGucFhxZELbspnfpiEOHtseCTqojS7VvYkyvWY1VVDTQKXpemam64MBZhb2iqZmyNO3fB3+2pHwU1RFEhzMhSQQXCbsuGst4I+UPTBzXUOLUs72oNZW7AlKzS5kizt8t4UogCu7B5MQ8VFwRmajLF5XQ2cfLtdS8VoV6MkWolb2u995hk8fHG38/0QLu5McOtpWU9xEDU3k0xglESIw/BITLTq3T4i2Wsa24dxiBuPj45GzY1l5MLHr67lW2mm3dI2h93W3KzSLc2ouTkaj74XnAS73NFcTbcuDgOcKJmbNpNPrme/x+rQBzfXOXrmZj7YLmm5lUGk67mK/i1tgi/kyAp6movOpBCZEKDWAl031hSiQBgAa4NoJfflu9/5Sfzshx7pfD+ESztTvODUOpIoWDlzI0SBaSYwjEPEYXCkXAOPQqAG8OAmwtljQ1zcOQLBDTVadbBsXdtBUyIrDgOM4ghBAOx1FdzkPLhZpVva0V4P8Pmuq5qblPVDIllam6YCJOc+4iTbdYs+uLnOQdmgSf+GNEKVuZE/p+tIWb3DVrjO5zLO3HS1vstFofTqXbMpoigQhQFGSbiSmps0LzrL5LpwcWeCM5tDHB8lKw9uaCE5SiJEYXAkXANdC+bDDEpcDeIQSRSupOi+a9jMDV+sdp2oS3OBJAoQBAHCMMB6EnUnS2PvU+dNPKd6+0fgNa6FaQXdTXCTsSD4+KgMblpk1o+afPawoQ9urnNQdmEVzRSPAgqLsVGTrLJPLoPFQ8aEmbI0gSyXgU13zE2h9OpdBxyiAIJAZllXEXTmosDeioJbIQpc3p3i9OagE7vRWaDrOYxDxNHRYm6OwrkA2gmT2LWjkJWvJJnyFQY3mUAS6aXNxjA+ErK0/TRHULLpR13qROcXBDK4ubaX4ut+9EO495mt1vZBz2Qchjix3r4sjZ6HPrg5GPTBzXUOyryuorPzUQCNIzT2V+yTVbB4uJgbnvnMRKEHzo4m1DwvsFHq1buWiolCytJGyWoMBTIhjOLcLrE1TpGJAqc3hzi2tnrmhoJ4Ym6OwkRL53BUmuNxWdqRuUc1zE3X8i3J3FjBzUoMBbrvc0NsetfmBQcNegdOrQ9weXeKDz54EXc+egWffbK94Ibk3dIKujQUaNHN8qjVBh429MHNdQ6SUU07WmD+1Acexj/+5U8ciQkVcMnSSjkaa3wJHL5mkYUlS6PsZ1cDZyYKVYzbNWsoRIEoCDBagRV0URQQRXfWsDaofuIMMTctWo02gcHchOGRYDuO2qKB3q9hEiIMgs6kpquESi7l1UC0a9Z8mhdGcLM+iDqruaEk0zAOK73UvvfXP4W3/eH9re1rnOZYH0g2/ag8+z7Q83J6Y4Areyk+9vBlAO0GxjSOxKG0DA+DdmVpdKxHJQlz2NAHN9c5upZRfejBi/jNu5/Cf3z35zvZ/qqhLaBtWZoZ5By2mhvbUGCSy+PvKijNhFATaffMDRAGsuama0aNrteqmJuLpfWyrLmJVy5LU6xAQpKnwz/RHjUtuyFLi4LOazdWgYqhywprbrKy5oawMYix21EyQ/XoGkQqEUn4+GNXcPfjV1vb134Z3ERhcKAL5vPbY3zPOz/VaWNxel7ObA5xdW+Kjzx0CUC7wY0yFAhlbdaxUbuy4aM2Th029MHNdY6u3dJIBvQf3/N5/MnnL3Syj1l4z73P4v/3R+1kuAqr1saWpVGweNiCG9sKmp6HrjLxJnPTvSwtKGVpXd8XmjRX1U+H+socVM0NsQKjOEIUBZ1LglYB+91eNf7pr34Sf/DZZ1rbHjcUCIMARyC2qSzszNqUVcvSIuxOujUUGMVRZSyeZqLVsXN/mkt5aXCwtXMffegyfuXOx/HQhe7s9Om5OXNsCFEA9z6zDaDduibF3JSB8ImWZcPpEWOYDxv64OY6x7Tr4Gaa4/UvOoVbT2/g//6D9ij0efATf/Iwfu7Dj7ayLZ8sjbKhh7VvkNnEU3RarChEgaKAqrlZRRNPckvrOuig67W3MuaGZGlDHC8nz66bGHIQ69YVc3N5d4rv/MWPr7R/z0F3/v4fn3oKHy1lMm3ArLk5GoshOgXV62OVVtB5YTA368PumBsah9cGUSVoS/OiVRv9/TTHGjE3B/iM2GqILvdxZnNg/Lxd5kbuIyp7Hhxfi1uVDed9E88DRR/cXOdQbmkdLTDHqcCp9QG+/OVn8cD5nZUuvAAZbHz8sSsVSn9R6D438qsKbiqytEMW3LDbkvKamw4GTlqQKEOBFTA3YRBgbQU1N3Ruq5KlXdqZIAhkYeyJtQSZKFbGGgGMuUkiRGXNTZvv+N2PX8H/+NTTuPfp7da2OQsHbQWdi6LVfXNZWlQ2Wl31ONw2dJKp2uuja1na1GZuBhH2OmJulCwtiSqL/WneLnMzTnOsKUv3g3s+VB1rhxQjPS9nNocAdADSRc0NPSvHW5alZb1b2oGiD26uc3QtSxuX2aAXn93AziTD+e3VNpD79JPXME5Fa318hC1LKzyGAoe4iWcuupWl0WC8MViNFXQuSivoRDbx7HJhJ1bN3OxOccP6ABHrpbBKxzRuKJCUC4Q2HxnqvbHKOhEaKg5i0VAUBTJRtJo518xNiCho/x4dBGzmnNtbr6bmZjVW0LTAHyVh5R2YZqLVpOR+KmVpYXCwVtCZlTDsAvTcnC2Dm9fccgJAu7I0Wgso5qblPmSKtTzkiYrDij64uc6RZvLF6IrK309zjOIQLzm7CQB48PxOJ/vxgbugtLGotS2gaTF76GtuLM36tDQU6KKwlCbpVTE3RVEgCiW7UBTdylYUc5PmKynKvbQzwQ0bUlpxQnXBXp1jmiF5KqU6bQYi9Gyssk7EVaS+KtiMcBvQbmmR0v8f9myvfZ0MQ4EVy9LIUKCLpEnGZGlTa+Gd5qLVsXN/KpmbOAoP9PnQc2p391HJ0o7JsfOLX3waScs1g5q50TU3bcprqR7rsL/LhxV9cHOdo+u+LMTcqODmwqqDG+mCUhTtDALCCmpovqFJaNqxzK8rVA0FdNDW9qRN92FzhTU3YRBgGMvhaDztcNJcoSUt7YNc5yi4WSVzQ5KnUVlzA7Q72ZLEbpXMjVhB5tgHOs82s7E0Jg0iaSgAHP4FEY1Juj5K/27VsrT1YQRRdPO+0/mN4qjS56bt4GacipK5OVhDgVUyN7ecWsc/evPL8NYvfiGSKGw1uKF3OQpLWdpa3Gri6aBrA5/r6IOb6xw0EXTJ3KwlEW48PsTGIMKDHTqg2MhFgTsfvaK6LrdxjrrmxmZuSlladkitoC1DAX6t2h47aVAexCGSKFhBzY20gl5bgfU0XxSsotdNLgqjYBVYtSyNF6vL4b5NaQc9G6ucwA9S7tGFveuk7DyfRAFoTX7YTQUUu+YyFOg4uElzgUGslzaUpNnpQJqW5QJxGCCJQmOxL4RstNympFcmIkNE4cH2TlGGAitgbqIwwP/2FS/HLafWEYdBq2MX3a+EydL207y157OvuTlY9MHNdQ5dK1K0PqAVhRx8h0mEIAjwknObK2Vu7n1mC9vjDLc/v9TTZi0wN3Z/BY+hQNeNKduGz1AAaH+SoWsWhQGGcfdF/kIUCEOZ/QS6DTxzI7jpPsBNc4G4DCq0LO3oMDdjxdysbgIXFiuwSriYiGUxyQSGcYggCFQAetgXRDQk0bibiQLl49eJFfRvf/IpZc+dVZp4yuCmC1OBrExexFFgFNjT95MWawgpEXnQzXh1Y+zumRuqQQNksq1d5kbPcwBwYr0cn1uSpqmx4pAnKg4r+uDmOgd/mdtmb4imX0vkovLFZzY69a63QfU2d7z0DIB2zk/1uaGi44qhwCGtueGyNCGM4KbtBBoNynFpz9xlszZAy9JGSfcGBnzRuArXMoO5ORBDAc7cdFFzs3pduYsNWNm+8/ZZIxncyGefSkUOfXBjJZlEUah5pgsVwk984GH89AcfAUAJBV5zI/fbhR00BVI2c5Oq56SdIKAoChXchGG3rOXeNMP/49+/H3c9esX5+1U0p8ytwAOADOraZG5Unxvtlga0l3xSEtZD/i4fVvTBzXUOXqTYtmaY7HDXEvkYvOTsJp68ur8SuQ4APHB+ByfXE9x6eh1Au7K0CnMjjlbNDQ96W2dulP9/uBrmppSljcrnsMugI1sxc5OJQhWJHxvJDPIqe8Jwm+Gkg2L1/QNgblyNIVeFLnT0kyxXMqqoA3aNcH5rjK//zx/ChRU4Yrr6jZHstAtZWi4E9spncZoLJDGvuSmZmy6CGyEQR0EpmXI7wrUhs51kAkVRmk6E3RoKXNqZ4r5nt3HvM1vO32vmpntZWsiCmyRu11CAaqRiSzbcVq+bXMnSWtlcjznRBzfXOXwDZhughQllzF9yTpoKrIq9Ob89wfOOj5SEoI1eN94mnpU+N4eLuckZm5IJU5bW9kRHwVIcBhgmYee22XlRIAg0g9jlveFB4ip63eSiUJNnHIXYHMYrZ24GUYgw1JKnNrOf+6rmZpVW0N0yN49e2sXDF91joMv9a1mQLA1Ap7K0+5/dwZ8+cgWff7b7nkR0+FyaQ/NMF4mlXAD7ZfCS5vKZJ2wO5X53OpKlxWGAOAoNhobP221IoGlMXCutoLsMbujYfeMEPfvdGgrIr1yWlkRhq6yfZm66YdZJmtjL0g4GfXBznYMv+Num89WAWWbUyDHtIc/E3jbOb41x9thQZS3byMrwMb8odD8KGmgOa58bWjsO4hBZbvYFanui45KAURx15tRHKIoCUSADKaBbVo1PyPtp9wxlmhdqwQqUdqMrtYLO1cI5VrK0DmpuVuhclndcc/N9v/VZ/L//+2ecv+tCamIGN/JnXSyIaCxsq6dYk32pJp65Dm66yPgLUSgmNs1MK2hdc9OVoUCIQRQYDLrB3LQwfu6zuToKg5VIwnz3KVd1VB3KhxVzo3+WtC1LI0OBqJuaSFePpx6rQx/cXOcwM0DtLjJt5uZFp9cRBqvrdXN+e4JzxzRz08ailhdv8k7iZDVNpgVdS63aBi0WhrHMEKadMjc06FPNTdeGAlKWNoi6k60QXIYCv/3Jp3BxpxupTi5M/f+xUbxiWZo0DAG45Kn9PjerrBERHbAnHHuT3Ous1Y1bmq65ISvoLlgpul5du5UBVbvuvCgZjjDoZP+ZEIqJlVIx1sSzDG52O2Bqs1zKTmOr5oYnItuoWaT5ai2RroddSjLTvD550HVyAdDPj8HctC1LU1bQJEtrz1CgKAp1HXtZ2sGgD26uc0w9A2YbGFvBzSiJcMup9ZU4pglR4ML2BOeOD5WEoB3mhgU3RWEsQjIhDq8srTyvQRxWrKDbnmQ0cxNilESdXyuSpRGD12lwU5jBzbW9FN/1S5/Af/v4E53sLxOFap4JyOB0FYtLwjjtmrkRrW9zFrouaLbHDY4ubKgnWa5Yyzhq/x4RilUGNwV91RLCOJKWyV3sXxQ6WTHNTFnaRilL2+2CuRHSUCC2Gkzy79tIpFHgNkoiaQXdodRJMTee+2RLvbs8Bm4o0LosTVlBm4YCbcjS+Ot7EJb1Pfrg5rpHlzU3PBtEOHtsiCt701b348LlvSkyUeBGQ5a2/CBgDCrC0fzykBoKFIq5icomnt0zN3EoG2t2zXIVhXQUU8FN3qUVtD6X/WmunvWuzAVyUag+CgBab0Q3C5NMKKMGyma3WnMzXT1zw81Cuug6n4vCL8npxFBAL8a7bOJJj/5qghszu5+X0tO27XwJuZBuYtRfhsvSNobE3HRjKBCFAZLQPC/e1qAN5saUpXVrKKAk3D7m5qAMBVp3SyuZm/JZGSUhBlHYimw47VA23qMZ+uDmOochS+vMLU0HN4MobKXfzCyc35IyoHPMUKCNSbeWuWEuY4eOuSkvzTAOOzcUyBldP0qiFVhBl7K0VTA3bNP7qQ5uugp2M6vmJo6CldanTNJcSZ466XOTHUBww/bVxW5FDXOjDQXa29/UIR3sIturZGmrqLmxgsBcFAjLBEYX+6f9TDLJzvM+N7KHUDd9btKcDAUCiEKfN0/QtJEcUiqLOETUsaGAZmY8Af4KZGmuPjfty9KIuZH7CIIAx9fakQ3z+9MHNweDPri5zrEatzT9GCRxuJKC0/PbYwDAuWNDlWVrZeCy6GC+CEmFUOzQ4WviyWRpuUDaoSyNFt9xGdx0zdzkQjb4G7QY5PrAi2D3pjmulhKEroLdzKq5aVtaMQucuemiz82BMDcdLxx4rZ5v310ZCijpoCd6urQzWXjxdRCyNN6lPQoCDKJuavjovuxOs9J+Xc9pQSCNUboKqqjPDaBZjylLELZiKDBdnaGAckvzvQPsnnYFCqDsPjc+NmkWppmo1NHRs8n3sTmMsd2CFTR/f/vg5mDQBzdz4MruFF/znz6Axy7trWyffJBsX5Zm1twAwCAKnFrbOx+5rAKSNnC+7LVwI2duWq65EaIwZEgZK8Sf5uJQDTq0mBrEcoDnC4S2s7yGW1oSds5yiUJndYFuJYNGE89phmt7FNx0s8/cqrlJorBTlyEbvFh91sJ5oe1nq6+5Md5x9n1RFPjgAxeXlqrlojC6zXPQebZ5D7mjnTIU8JzD3/35u/D/+e3PLbQfukWrkEWqWhsmISTpaZN5bH+a43NPufusuED3hZyuBuydAyAt7TsYx9K8lKVF5rvVtuKCm/9EYdCpvfBMt7Si/vdtgOa70LKCXrRdxDve9wC+9u0fNH5mN/Gk79swXOHjQ28FfTDog5s58NDFXXzyiWu4x9PcqgukuWCLvnYHZ9sKGoBXE/0dP3cnvv9d97a27/NbMlA6e2yoJva2raBlBlb/P81lIT6Nl6ss7F4WylAgksyNYSjQssyJ+/8P46jz+qSilKUN4/aCXB9stzQtS+uKubFrboKVyD4JY1as3kWDSM3crO5dMk1C9PcfevAS3voTH8Wdns7q82w/97xTubKCXmoXBngAOusend+e4MKCzn5cutU1bOmSCm4a1py9867H8bVv/2DjgISCKCoG57I0QErTumDrs7K+J7Z6SLVtBU3bG8XdMzd0Dt4+NysxFJBfOasyWEKW9tTVfTy7ZSZn7Sae9H0btb98XOqqH1ePevTBzRyY1dyqq31ulgWRrdfcOJgbn2xmP83xvvvOtzaont+e4PgoxiiJOq254QMLFQpvltagh6nuhk5jmEQQhXns3fW5CTvLeNr7W5UszWRuclwtmZuuZIp5peYm9LICXWCSCoyIuSFDgTaDG+pzcx3I0u57RjanvLi9nK13XhTe8+HWxm1hkukElpYOurc/TvOF30exQllawRgboDQUmIO52RpnmOai8XtJ+6Hu8tXgppvaQdmkN1TMDc2dbbul0faSOOjcUICevVmmGl2OY6rPDSPg4iUssCeZqKzb7Cae9H0b1zbzjFE9Voc+uJkDqTVwFUWBJ650K1FLc6GsLFuvuZlSNojV3HioXyGAK3spPvXE1Vb2fX5rgnPHR3KfLTI3fM1RFOYiZJIJiEL2GgEOVyNPJUsrJ+195u7VNu3N3dJGJXPThSsVQRQFwiBA2GEfDIIR3KQ5rnbM3KRCGJNn08x1W+DMTSeGAgfQ58YX3Dx0UVrYL2vlKoQ/uOnCLW3KZGmzDAUmmVg4yUWbXI2hgPxK2XEhCmUa0mT/St7VcAFN90MzN6Ysrat+XfR+JypxoGXPhDbGFhXcRN0bCmRqnePeh3LC6zDJK8qEV2DJ0hadG8ZpXpGS6tpSlnwK2xmfuRlDH9wcDPrgZg7QQ08D10ceuow3/dB7O+0LM80LbA6l/3rbg/M4yzGIQkNzKpmb6stIC+j33nehlX0/uz3GjceHAFjGvhUraHPhI4S2Bd0rrUCPlX72h6mRJ2/iCZjWxW1LgrhbGi2Mu5SykCwNQOPM7qKgiWYYh5ahQIc1N5YsbbVuaZq5oeNoK7gSrPZrpcyNJT0lPHh+F8DyTfjyovA6RXXT50Y0lg5K5max+0fbXAVzkzuYm7isTWmyfxqDmr4r1eCmytx0wUBnyi2tTpa2/PWmuTGJwu5laTPqyrIVGQrwcRNYTpY2yURljMqFlKjb43PrzE1fc3Mg6IObOUDF/fSCXdyZoCiAB893F9ykmcBmZ8yNzuoSZJPB6iRAL/wf33e+lX2f35rg3DHJ3LQpR7KDm7wo1OKO2I7NEcn8Dg9zQ9ef5Cucuems5qbUyPOfdQFpKCC/79pNjM7j2Cgp+9yUsrQV1dzEK+9zU20Q2daihAe8q8xO2lJTQnvMTY1TVMvMTVEUpVtaGYDW9Lmhz04OkyyNZfmlaUjUKIk1r3ED7Werruamg/MmZzbb8ZOzHm0EVbTdQRncdNkYMpsRWK7KUICbCQBLytJSIZUc7O9TURj1NoAMdNqYT3u3tINHH9zMAbvmhv7/1NX9TvdJTcjaXvSN09zocQOUBc/Wy02LifVBhE8+cQ0XltS0F0WBC9sTnDsmmZskbi+jzMcR6lcxsNgOJUs7VMyN/ErMDW9I113NTaAG/0VdahrtryhWxtzQouDYKMZemuFaKUvr4lkQokBRwKi5GXTUod2HceqwGW7pedlPuwuw65A7sqLb4xTPlr2zlg1uMlHN8urftRvc0Jhuy9Jc26fF+dKytBVaQSvr7EJbQTfZvwpuFmVuYiu46UiWluXS6l0ZCih2jPW5aUOWlpEsLZAL8BUYCsyquenWUKDK3Czjlkb3wG6uySVptI82nBD5NroMRHv40Qc3c8CuuaGvT3Yc3ChDgZYXYOM0N5zSAHcHdVpAvOllZwAA779/OWna1b0U01zg7DFTltbGArpwyNKUlCul4IZkaYeHuXHJ0tRCqO2aG6ZFVvVQHRaPCi5L63jxT+e2OYwNWVoXzA1dM6NgteOFCYfM9OfKMIQm8rYW5qapxcG4pZGr2cMXd9XPlu0wngv/NVJuaS29c7TgrgQ3ju3T+L/ouLWKjLval2JedDAoDQUCpzLAhnLsmrPmxmcFPerIUICYG3rHaeyiBGEYtDNvp7mWUIVB0KkD1/ViKBAFdnATLJzgpXtgMDe5cDM3bcjSeubmwNEHN3PArrkhev2pq+31f6nus8Ba6W3Pux63gX0HczOIJfXrkn584S0nEQTAI5d2sQx4jxtADihB0FafG/P7TBSq+/e4wtwcnuDGlqXtTTOsl+fV9mJZMTdRgCQks4fuBuiiKJQrzrDjJrK0wNscxhhPc1zZ7Y654QwYIfFYrXeBNC8giurCuRPmZqU1N1Xm5qELckzaHMbLy9JKxtdlotE6c+MLbhzvG2Wfl3VLW0WTZtpXUUgGUxRgVtCzrx0FkU0+y+cqqreyM/LS9bELWZpA4pDv0lx2bJS0ElRNc9ksNAiCzhMkmRWY2uC9i7qCEFLGyCFZlcX2Se+OHXTEUVX61rYVdB/cHAz64GYOUDBDfSqIaeiSuZnmAkkcdpLR3k+FWvgTXA01aTAjmdKyLys1AyVZWhAErdVa2A3+RMGYGzIU6Mhau0to5kber72JZt18PTkWBa+5Icmgr8C6DeRidbI0enaPjWJsTzJlHdtVVhcw+ygkZR+FLt3nCHROirlRNTftXF++yF6l9MJ0S5Pn8uCFHYQB8GduPr68oUDN4k7LrJbahYJmbuQ9ovfAxdzQ9V503KJj9r1f0iCinfeAH34mCmRCzGUFnc4RRPL75JWltcjc7E4y1cg7yyUjFUfmOEnnuDmMW7OCpgAq7LzPjalMqf5+BbI0h6FAEoVKjTEviLnhbFNq2fQDKNc314db2uXdKbaXHMsAve55rqEPbuYABTOZMF/+Lmtuppkc1IZJ+4s+WXNjPgJKIuZ4OaMgaKU78vlSG09W0AAwjMJWmhvycUQ28XTJ0g4fc0OLxwGruVHBTcsLS+6WFofV56FtiAIqS9d1cMMNBbbLwCYMOmJuckdwswKDBgKdk80KtMXCjQ+o5sY0DZFfH7qwixfcsI4zx4atWEHLbTuYm5adosgcwDZ9cC3g6H5mwu/mVgfapu/9+vWPP4E7fuA9rSQy+PURRQEhMJcVdD6j7oODPw+1VtAz3vGtcYp/+Rufxu6kfjH4E3/yML72HR8sj6+UpVkMd5oLJFGAtUE7QRVtD5DjSZfJhFk1NWIF8sZcoGooQKYNCwQflBAwGgCza8r30cZYZtYFLraN7/i5O/FvfueepY7jrkev4DX/+g86b1lyPaIPbuaALUuj/5/fnnTXJ6N8AQdR+wWRLkMBWjzzBRCNJVEYIAqCpZkCkqURcwPITFsbsju75kYGN6ZbGtXcdNW4kR/LT/zJQ7hcSp+WAd0Duj+igLp3bWfxDOYmWq0sres+MEIFN7H62dljw04CXZqEI261HpuWsV2CxqRhRzU31CerzW02Ab92GWNuXnJ2E8dHydI1N3U1B227pdGYTkklqjOgY/gv738Ib/uD+8rP8iL1BYKbGW5pT1zZx8Wd6ULb9u0LkOcia26a9yqZJY1yfRbQ9VaDiltaNHP+/PijV/CLH30Mn3jsau3nLu1OcHl3iiwXyIWcn6tuaQJJFGLUkhyOtge0Vxfi3xfV1Lj3Mc+9WRRFIZ8XjsEScxElESqGAlF70jcOunZB4E5UNMEz18a4uLPc2uGJK3tI8wIPeBx9t8Yp7n92e6l9XK/og5s5oAaujHS1+qF95lo3dTc0qHWR0d6f6mJjgpKlcZtXJktrY2AlmnSdmRkkUdASc2PL0nRWtOKW1rEV9FPXxvj//s49+MPPPbP0tuge8EmbmJvOam7C6qTdBVYpS8scwc3zjo86aVSasyCRQN+vopGiXayupDMdGAqssuZGMMmKEHLx8PDFXbz4zAZOrCXY2k+Xupd2jxaOtvvcqHuUaMkR3/4f338Bf3iPtN/ni+RF7KCVLM3bw8eUVC0DfnnyXDZFjcKwOXNjqSPqP1tlbuJKcBPOTGDQovnqfv2CkpJiu5OcydKsJp6ZnLfb6q8zzQo1N3duKKDWOTPc0jo8hly4DQXqjqsOLuZGWkGbz4m0gm6DudRJi0UTITuTbGmJHD2rvvXpT33gYfzNH/vwUvu4XtEHN3NgalHlfODtou6mKAqkZSFhF4XW48xtBQ24ZWlhOYgvO7FPM2lPy7sPD1oqtOZjgShgytKoz81wNbI0GoTbYD1oscb7ElFw2PZEp5mbcCXMjexzw4KbFTA39AwA2tiibWaUGAauHR8o5qb74Iaeb2IuKbBqq+aGDAWCjjum28iFbsybCYEnr+5jkgm85NwmTqwlmOZiqXtJz4jrmadr176hgH2PaAEpsF8mg/h4tRBzM0OWRs9rGyqE3GBuRBmQSvnxtEEiYZ6aG5ehgC03oj43dful+efqXr2skZJiO9MMqZBBjJ43deJzEEvmpo1xJc2FGjviFqThdZjVY4jm/2XHsHue3lK1SzbyomooQAHkvLK0XBRMbcOVHVW3tCRqhxWj/QzjxYObvWm29LHQu/zMlju42R5n2BkfzZqcPriZAxUraDZodeGYRi/IIA4xiKPWZVT7U4HRwC1LcxoKBNKGcvkXTg/UhCRqJ3hzNfGkhcM4Xa0src0sL10aOhdAy9K6ZG7iFTA3RbFCK2gKbkbdBzd0HRPDCrr7YJFA5zNKunFLo/dpYxC30huiKfKiUAymKAol+zx3bIjja/K+LlN3s1rmhgJQnZXn+8lFoZIy/PlcJDEzq1ZCLczbbqZcus9FZc0N35cPJH1uIt/kzzPttiJLK8fKusQJnfesZ0czN1nZK0XLd3mPmEEUYtQSc8NrbsJweWl4HWY18WzLUOC73/kp/NDv3+v8nRBVQ4FFZWn8ec4qhgLdWEFrd9NooUB0mgmkebH0NaYx41lPcJPlsqfXKgxuVo0+uJkDdiY+zYXKnj95pX3mhiahJGpeiDkPxmmOUWwFNy5ZmlrsllmjFl64oRXcDJZo0MXB31FZyFp1S1sfSGvtrmVpbTY7U7I0dt1GquamG8bBNWl3gZzX3HTulia3TQEuADzvRBnctMzkZeq9YTU3KwgWCVXmpt17qYKbYbRS5kaIAoPynLK80N3b4xAn1uR93VowuCmKQo0hroCt9ZobZfogz0fL7TR7RLWCfJG8SGJmllsanW8bQb5t7ELWvpoJrt/HrF4r5r6q9yJxyNKA+nObKuZmhiytnDe2x5k0FGDNjk1ZWoBR0mZws1rmxseQqCB5yXlnP8295g15gYosLV5QlsaZSNsK2n5O4jBshVWn53ZR5obWKssmjejZ88nSdLJmqd1cl+iDmzlgMzfTvMDGMMbZY8NOHNN0cCNlaU2an80D2cSzyqDwfQNMltaSW5qUpVUZo1ZkaRZzI/vcmLK0JAoxirvpe8BB59PGQogyKzwjSYF12+vkXMiGcfMsRpYBdS8H5HPQpUU3nQbZgQcBVDNZ1363xyn+j9/8zEJ2mjQxudzSVhHc2MwNHUZ7zI3c/sYwXmnNTcYSFnmhJSdJFOJ4GbQuytyYbkp+5qZ1QwEmObL3s5fmKIrCkqUtztz43i81r7UR3FjXMSsZDqUMmLEPxR40uM6ue2EXiqteZzWBRmNZWvncq546UVipVSUZ2bCleYb63AByXO60z80MZqatd0CUsnvn74S7z43c/3zXk19/ft3SXFSYm7Z6CNG1GSaLyfh3p2SA0A5z80zpUGuDy1+PGvrgZg64am4GUYibT67hqWvtBzdTK7hpc9GXlnSk3y3NIUsrDQWWHdQmWe6UpbXV5yaJTN267ZY2iAMMW8qo1aHNwkt9LsxQoCvmplyIAHqx1a2DGVT91bDjmhu6VhtlcHNiLVHX0fU8fOzhy/i5Dz+KTz1xbe59uWpuFq1hev/9F+Z+72xWgBoAtl1zszmMV87c8HecrmUSaeZm0eCGv6ur6XNjydIsQwFyGpvmwqizWUiWRjU3M2RpbdTcuOTBIQ9uZrzj84ydrmev6pZWMjc1gQYxAldnydLK63Ntj4KboGLWQUzLMJnt0tYEaSYMR70uDQVydQ7+wKPu900hWC2M6xiqhgIUQM45DhrMjZm0rVpBh60w27SNYbwYq02M1vJrrRmytJaTNdcT+uBmDlRqbkod7C0n1zoxFFA1N1H7TTxpYeJzS5tk1WwHNfFcdrE+dcjS2nNL0/IbGjhtQwFibrpu4tmmPp8uuRHcDGJjP20hZ3rnphr5ZSAsK+iua27iMFCs18m1RL0DrueBFsmLLCacNTcLyNIeOL+Db/mpj+H9n78w1/51E0/9zMQtFcwCcoGdRAGGcTsLgqbIi0I9l7ko1KJ0EIU4TrK0BZvfmRbG1XvUdp8bZSiQ6IUr3z4txvanuSGbXGTssmVpuSjwwHltA0v7aluWlpWytCgIKgyHD5o9mH0sur6Byz/N+aXuHSfQfHFtBnND21DObIZ8V19DsoJuQ+6a5kI1VO5aluYyTOKgfS8r3xJF/T6qzI0p/WsKH3NDTncccn2z/POfsWdymeBm2aQiPXuXd6fOpAXdw1Uy76tC58FNEASPBEHw6SAI7g6C4M6u99cl9EtvZmduPjnCU1f3Wy/Kokk7iYPWm3iOp+7gZhBXG/3Rwi4MAoTh8lmjae42FGgjY18UBesWbbIdFNDJSad75kYNHC0s/IRjAu+yzw0FiLaWvAvI4GY1VtDU+ZpstE+uD9Tz4XoeaAGzyGLCVXPjapI7CySJ25vM97wq5oa943EYtlaMvJ9KK/k2pKrzIBe835OuuUniQDM3Mxao/m3Xy9KUW1rbVtBUc2OxzvR1b5obC/NFFsx0zPR+/eHnnsFX/vv34/y2zOqSQ1krwQ27jqIo1Hs3bMjczCpq56DzOsYcEJPYw9zUsFJNraBpnCD5WhyGSBxNPKUsLWqltpPX3IRhgKJo3yWTYAfWNlTgueT+JevqqesR1T43i0p6fTU3mRCVIDiOAogWri09v4vX3OTldpY7Dh7YnXdI0xRzs8Lk1KqwKubmfyqK4rVFUbxhRfvrBJWam9J7/uaTaxinApdaaNbo2l9SMjdtMg300FetoMsBxNPnpo3MxiQVTtlAOy49VSkVLe72GXMjZWndMjd6gdJeLZHhljYwmzJ+9qlreLoFeSRnbppmWpeBKLAyK+i8zNYp5mZdMzeu54GCm0UmGVocuGpu5tmemoDmXFCPLckT0G4DQGoCHIeL250uglzo8SPL7ZobucDdWtDelL+qtW5prdXcmPeowtyw4MaouVlg7KLkG12v89sTiEI3vlSsQwvjImfApPWzfPZchjUuzCpq56BrxR0QXVbQQP11o2OaVXND8zAFQYkhS9MJ0EHJ3KR5YTxLl3en+OHfvw9v/Dd/hN/99NMzzw8wa26UXXhHCYVZTTxnue41hSgKr1ojL9qUpenj5M9TJqrMzSLjsws8sbrIfWpPlqbHDJcd9Cp6Fh0UelnaHKCXypClxaGykr244y7aWnh/PLhpOaPtk6W5am4qhgItMDe8Xwsgz7EtQ4HYyvDQhEoZcJp02tCW16HNTs4utzRblvadv/gJ/Md3P7D0vjLm/9/WYF8HIbgsTWqUu1osK+amfO5PMebG9TzQwm8ZWRqfQBdx/MkXXFDTInVkMDftyC4AuVAk5qbryfFX73wcD16QXba5yxEvSh5EIeIoxMYgWtxQYIYsTSUs2mJuyntE73VkLVy5LM1wS1vCUIDer32VHTYVCe3UPurvaXvcCnrWXDaPKx19hjfmTazmjFqW1sBQYEYTWAqQ6BmLwpDJTTU7Rm5p9n6/7kc/hLe/7wGc357gnmeadYen+l5AJ4I6GyMVa+Zhblqq0+Csa/UY2pSl6WvPGYosdzfxXGQfNjRzEy00d+xOW5KlZdo04WmHY1pfc7McCgB/EATBXUEQ/B37l0EQ/J0gCO4MguDOCxfm05SvGtwljf4/iAKcXJdSiCu7i/dWcO9PT9rDOGo1o03Bjc8tzehzU37blqHANKsyN+0FN0BCXeDLCZSOW8nSYimP6L7PTXsSFpcsbd2SpW2Ps4VcvWyYzM0KDAWYLI105V0xRXRuJEs7sdaMuVnkmaeJg2eRXe/XzO0sWOdhswIAWnl/CftTYm7aMynw4V/8t0/jnXc9AUC+46oZKpO20ALzxFqysBU0X9S4ZWnyZ0WBVmTIlB2nZIIKbizpz940s/rczH+9+SOX5kJJX1IraddGjYjN3ADzuS/qfjHNgxtqzBuFQWVh3MgKOhPqa931dRkKaFmaTnySWxqg71eaCzx0cRff+T+9FKMkbCyN5n1ubHavbdAzKQr3PpoaCrzvvvP4T+/5vPf3ufCPg6KGuZlblmbU3Jjf2008bbfCRUF/P4zDhba1W0qQl73H4zTHLafWAADPuoIbVXMjv/7yxx7Dv/7tzy61z+sFqwhuvqwoitcB+CsA/mEQBH+e/7Ioih8viuINRVG84ezZsys4nMVBL1XGBrAkCnHDxgAAcGWGP/6i+yPmps0+HGMfc+Pqc6Nkae3IWlxuaW0xU4XB3JhyOu6qNEra0ULXQS1K26i5KTfBF6ojK7jJhGglg57lzC1tQXeveSAKvahrKltZFMqSNgrxqpuO4/bnn1AF966s7jLBjWZuqn1u5qnD4hn3eTBOZdaO68qTltyAACl7GyWhHBO67INUMg3EduWCWUGz4IbO8/hasjBz01SW5vv9/PuTrCW5BaqFq3XP91LJ3BA7sUi9IA/GJplQyZ6pmtdaZG7YtaF3eSEr6DkMBah3lS1JA7Sct9Ytje2rru5Gy9JStb+wTKDxa0jzDKDvF8mNTq4PsD6IFXs2C2mm60Nsdq9t8PnKFUgoVnFGQuNdn34aP/bHD3l/X8zJ3FDyYl5ZGp/n+TyWiaJiGa6CmyXHMy5LW4S52VPMzbJrLYEzm0OsJZFTlmYzNx944CL+6J5nl9rn9YLOg5uiKJ4sv54H8BsA3tj1PruCq89NEoU4tS6Dm8tt19yQoUAHTTxny9Kqk3hYWsku6/7l6nMjDQXaCAKKiiNVaC3w4jBorXN0HbqwguZB4SAOjUx8molWAqlcFKqweZEC+HkhigKUpFMZ1rybe0Odr4MgwO/+4zfh//n6W9Sz6MrWbi1hKKAYhSX73CxaczPJ8oor4TzMTZaLWnZifyoNBeKoPTbIBXvctd3Splk1uFnULY1fY1fNAT/PNhaXJJMkhGGAIODZcXlu42mOcSqUYcJibmlmwLFnSV9UE89Wam7095xBH6j3u1nNTSMraMtQwC4SB7QbXZ0sjc8/vrobwZ43LksD5HtONR2kTtCJE/nznTK42RxGWEsiNQ/PwjQvlEmCze61jcyqS7GhWMUZ+88FsD3Jah3R/HbT1Saeqs5uTpaYP8+2YUiFuVlwHzY0a79ozY0pGV0Uk0xglIR43olRo5ob2XB3qV1eN+g0uAmCYCMIgmP0PYCvBPCZLvfZJaYWVU7ZFJKlzepsPP/+ykm7pLfTvGitkJXc0nyGArxhKO9zEwbLZ2knWdUtbRAFrcnSbEOBKNAFn4MoRBAEpSSg27dY0/vL3zNaZPKJexCHiALNpKV50ZqNpXJLU0xDh8GNMN3SgG6ZG3vSrGNuaJG8HHPDg5vy2Zxje8qha85juLafGnUIQPMmdUIU+LIffC9+5U8f935mnFHNTbeGAlOWTALMmhve54YWP8dHCa7tL2oowJM61WeQX7s2FgEysDefR/5Oc7e0cZpjYxAjiYKFEjP8FZ4yWZotAWsjicYXdLS9MGhuKJBbwV2Tz5KhgCu4UbUvDQwFAH9ww68Nzfckg+asKMnSRrHJ3NA13xjGGCVh4+CG19x0bShg2iUvztzQ+1MXKPpqD6UVtPmzxd3S9Of532a5UMEMoT3mRkreoijAIq8TJR6WDWDHaY5RHOHG40O3LM0aZ6iv1lFA18zNjQA+EATBJwF8DMDvFEXxex3vszOkTJML0AAWYBhH2BzGuNxhzY3d/OzaXoqvffsH8VBZZDsviKqtBjdVK2i1SCuDhDZqbuyMcluyNFHohbkqZA117xs6v2EcmU4i18Z4z73t0rGqMLMN5qbM8HLJxSCSzI0oChRlp/a2WCJakNNg3war5oMhS+s4uBGMlSLUMTdd1dzMYyhAE+28QfKzWxNldkKIGhoKjLMcz2yNa/t3jcuamyjo1nAiZeMtIO/FwAhuNMMNLFdzw++zK6vMA562aunsYDtk1toUBO+lucrCDuPFnB5t5oYW3F0wN4W1LwBGrdus4GyeOjO75sYtS2tiBa3P+5pHlsaPW1lBRzoRxNtFSFdO02aemJuNYYy1QaSSjLPAa25Uo9eO3jm+sHe/Aw2Zm/LXPrm+KPyBdM4SXgRtxjKvPJdZQfPATdQwN0vOd3kpeYuCxZQuOyVz08QtsA6TTJo3Pe/4DOaG9ZVapa1/l+g0uCmK4qGiKF5T/vszRVH8my731zXsSYB7z59cT7qtubGaa95/fht3P34Vn3t6a6Ft70/ldnyyNNNQoJSllczNsg//1MHctGUoUBQsQMsocx5q969yvzZz84sfewzf8XN3tZq1aLvmJgxguLsMYnleWV5oGUcb3ZVZoWUQyICqU+aGydIGkXweu7KDdjE3dQuftmtuFpE9zOMcxfHs1hjnjjmCmwbPCC3C6oKW/TTH2qB75iZlEy+NRfQe56VuPwh0gHx8LV7CUKCa1PH+vqX32tVIUFj3fH+aYZzmGCbRwk6PdsBBLAK9azReTluQhLoMBbgF+96MRb3t4Fa7rwbMTRNDgTQXStrmYxtcza25s6TplqaZG/o7qrnZGMRzydL4WoPGr64SCnbRvQ2e5a+TrVIi4IpHrl/nliaKqk2zkkjPK0tz3DP63q65WdSRzUZaOrHJ8Xb+bRFzs7xKJscwjnDjiRHOb00q9ytjCSMAquHuUUBvBT0Hqk08tTziho1BZ8HNIA5Vrxbbi3/RDLdyS7OZm7CaOadgJi4L85f3XncHN228WNwKmgaoKNRZH7pfdhPPSZYjF8XChcgutGkFTdItnmkaRGFJe4tK4L0MOHMDtBd4+mA38QS6d0vjCEuDATsbzh2lFnnm3TU38zNhi9p1Xtie4MbjQ+NnSdQsEKGGoXXv4ziVhgJt2ku7wMddZYnOmBsq3iZ514m1BNuTbKF7xhflznqDtmtuhA7sCSRLKwotEdmb5hiXjPeizE3uCW7U9W2RueHDBdXXyOBGBg+0yPf/vQ5oZ4HuEwUmthMnwNnZeubmbPm+XPXMA3RtXPbuCVvITnNRNt92GwpsDCOMGgY3RVmbUjEUWAVz42BJclH/jtjbueIJFHNReB3ZckcSahHWG7CYG1uW5rWCXpa5EYgjmQxeZFO65qY+gJwFadcvmZtpLip14XqNooOcnrl5DoLX2gDaEQWQ7ie+DMWi0IWyAYaRmV2mQGrRRadyS7OsoEPlLFYtwpOOMMu5LZF8yjYUUEYGSy6SeMaHa73pPtHEN0wiTDJdME1Z2DZNIVTDvzbkK+V5SfZM/oxqbnLWDK2NCc+m67nTXBcQhc5GriK4sSc0QBYc2wsfnv1fZMB31dzo5pPdMjfTTDYVdsvSZm+H+izMYm5GSVQG2N09H1O2YKT9GG5pWWEsaKnofnsBUwGz4Li+5qYVtzRHhjosmRu+r/1pjkl5vYdJuJDTIz/caS50nxurQLyNZtFOWVrQnLlRbF0TWRoZCpRuaXY2HigdzYL6c5tkAsdHCQZR6GVu6LqTiRAAVp8YqsVomgsMo6oVNC1aN4clc9NAlqbk6bahQGfMDQtuapibWcdA855flkZJYvc+fG5p8wYeBnNju6VVWNN2ZGlpue0oXOw+8ZYOy9znSSqZG3L0tZO39tyS5X3NzXMSfJIFdJ8bALhhPcHljgwFjJobxdxMjf/Pi3GaIwjcWa5BbGbqlaFAIF/WZRbrdE6VmpuWLICFcMnSAiYdoJobU6ZAA2abphB5bm57qW0JKHaDmCnuljZl2e3l92UuuOznoW1I5qbc1wJ9YOZB5pg0AarBMvfJJ4JFGEVbtgKg0mB2nu3ME2BdKBsKnztmMjdNmdcmjNWkbOLZBptbB27Bb7sGUs0Nr7M4Xi5yF2FhZ2WluRSttaSFXVtQ1tzwY9mbUs1NhFEcLcSuVGVpcgE1ZdeXfrcs6vrcDKJwZnDD7e0B4EMPXsTb/vB+974qNTfVOS0IAuc7zkEmACfWE2/NDV33M5ssuIkC9TUt6x6lPDqsNPGkpIGquWnA3Ohm3lYvpM4MBdzBACFn43XdOEbvT13NDeAe6+v63Mw7N0yynDmt2bI0j6HAkknWXMnSFnVL08HNMuuHScn20nNoM4W2uiQTopelPRdhW5Jy7/lTGwNcbdtQgFmcDq1aGCVLW3AxSw34bKce2p8hSyu/lUHCYk2pCDS5VJt4Vo0MFkFhGArIF1kaIZChgJalAXqyosm4C+amjQaHPAAgdx5ec8OLrZeF3bk5XpKtq0NRyIVAsCLmRhpOVJ/5UVLtI8UXx4s883Qv+AS6yHNOk808k86zZfGoi7lpEljR5Op7niigXkuiVnpf1UE3mdSSCdMtTRgLWnKI2x7P75jGF+Wr6HOTC1TG4LAMFjMruJHOR+HCNTf8eDlzo2VpxNwsX3NjyNLK7dF7tz6MZjYb1n1u5DH9/meewU994GHPZ8vgpqbmBnCzsxxpLhnAk2vJTObmNA9uKHEWyiSQqpWNmRV0Oc/sLFBzw9cBgA5uVmMo4GZVaP7M8gJ3PXoFf/tn76wwnfS8+a4lb2Hg+p3NaGpZ2nznPU4F1od0vLYsrR12yEYqRNk8fLH7tMuC/0WPpSiK0lAgUuUH9vNv19z0srTnKOglJJ1oyrznT60PsD3JWl2UqaaTcZW5ubJkzc04yyv1NgS75wzvc7Nsh3M6XnKRIQxKmdqyDIEoqsxNyFzGaIC0i8izGQPxImizyF8UmnHQgVqgFkK65qZ95iaJ27HpdoEOl1ipYcfBjY+5GSX1zM0yNTfGtQwXZ27mubfny+DmnFVz09TtUNkEez6rmwCHnTM3lKSYMkMBGg8zURjyYECbDSzyzM6SpRluaW3I0kQBey0eBWVww/a/n5KhANXcLClLY008bTe6Vpp4FtUFMr13G4NYybN8cNlT+7LpNnPjUiMAmMl4kdHNyXV/cEN/f3pDv1f07CVxmWgq551BFOpaH2JuJhnCQL43o8ayNCu46dxQoFBrA1/d2ZDJyD/28GX80T3PVpIJ9H645PqF8XxU9yEKVMbpqJRkz93nJpMW6vJ4daJIFFUJo0uWVhQFfuj37sVnnrwGQI59f/PHPozPPnXNu09pVx8Ytu7zYI8zNwu+jzSfDeNQuRSSkZTatjW3yHYjC+3uukMf3MyB1Mpo8En1VKlpbFPWxOnogSWjItp88Zqbqh0zwe45w/vcLBvczGJulpalMeaG9MIRK8SnhY/dK0DV3LQpS6OBtKXCY5rU6NiHUaQkLFy6syyyshiSkIThXH1Z5oF+tuT/XW59bSIX1WwdICcAe8G4bHCjmBurSWNT9kRvp0yqzMXcSFmazdw0ZV6JufHtkxuSREuyubMwVcwNk6WVD4wok0zcoIQCyGXYNt/fG31uOpKlyTEWFeZmkgmMYnJLm//9qDbxNANYVXPTlRV0eZ7rgwj7qZ+5KQrm/kgmB5nwvoPKZKJMArpqbgCZUJtlBZ1EAU6sDfyGAuXfUw0DoJMXcTlOUgNiztxoQ4EcG8MYQRCUsrTZ15rL0/n+ukoo5KJQi2F7PikKGRRQ0JaLomIpTqiTpZmW6x7mxnEbZeJ1zuCmLKqXSRgzCehnbvQ+0rzAO973IP7wc7JVxLNbY3zs4cv49BP+4CbLdY0sMD97szvNlzY3MIIbjyxNMzaawemZm+cYqBB+XUXA8iHRNTdysPM5gywClbEJdQZIMTe7yzE3wpPBBqo1Frower4O5y74mZt2FrWigOpjQsEoyekAfb/UwGEVrrbpeNcmmyKYdEs1JC1rbjJRqAVgO1IZh1tahwX+AJOltVR7Vbc/W+4AuJmbLZaJXGTAz4R+/jhISjjvduY5hme3xojDQI1LfN/tMjerrLnRdSgJY24yq+ZG98NYlrlxZ61d3y+K3NXEs1yE2TU349JQwHZ6bAq+wBqXfXMAs4aU/38Z2M5sgE5grA+iWuaGX1azQbEnuGHv2fog8svS4vqgkJKVJ9cTXPPMA2PF3Oj3SqsCpFua7k8XVOTPu5NMsQhrSSQZqRnXWys4rJqbjt65tJSbAtVnQRl6JJrhIFbK/qxQc2p1TWSwiA0NBQCai+Y7b7JD5jb4Lsmw3L65LuCf5S1A+FcXMiGfJQro5xm7i6LA7iTD8VJmuajygwJxGjOAmpqbXJ9jbyjwHAM9BMrKstQMK+ZmXRaxtlmzkZaa0DAMqoYCZWZpUeaGmkK6UK25YbK0oJ3ghvqZEJSH/ZITa1EUqiYlVZNqULGCpv/b7EqbdVOL9idxgctXVKBGhgJ5u7K0ilta1J3VL435K7WCdtSZuZibrSUNBdRC3JpAB3NmH/Vz1Hzf57cnOHds6JR2zOOW5qsX48ENJTyWsSytA19McFv6MNC9MgxZGgU3i9yzGVbQrTM3jmA7CgPkhTkWbu2nEAXKJp5V2/JG+yr0+8VZSVos0rm1wdzwSzdR47Dc9/ogrq25MQvay4Ary1EU7vdQBTdBgPWkLripDwrJUODkWjKTuTm9qWVpyi2trE2keWcQh3KBGwZaljbNsFHWf6g6iBljnS1Lo3e6qwy7rKlxu4bRPodM+knPiy0vq0sYumSL9u9d43SywFxEzW95HyJSddjMTaRYX/YMWvVfqfXVBWJuomj+QJSacZPr46JrIrovQ84gTutrbpTD6xEIcPrgpiHoAbOZG1uW1m7mX3vb6yaecr8kf1vUtlMUcA4eQLWvCc+MRdFyxcN0/K4+N0BLsjQrUJLBjWkoEFnSFfrapiyt7Zobul9kaxqV1txty9JczM2ixhWPX97DVo0l7+pladXGbYC/5sblstMU9Dd2DiGOFmRu5pjUn90a46wlSdP7nr0dZSjgOUzSbq+VzI08vm6DG24FHZX1f7LmpjAWtFo3v0AAwP7Edb1N5mbuzVf3V1SZPRdzQ/PKMI7KZ3WRmpsCo/L9umqYZchaJtrfpIUTK5hxh83cbAzrmRvDrtdaSLoW9Hx+Or05xPG12LndWXK+aSakocB6UsoAq8dIf++UpUUBpqVcHTDrO8fKUCBXtUEjay1Rd1x8e3Rdu1qApjkzDLDeAbrWI1aTQwGjz1DAVXNjBDeeXjqu5OsiPdfGqWZulPwq98jSQj9zo5sJm0yOC+TERnP2PIkQ6jFGwc2i4yo9v9xQYKZbWs17dtjQBzcNQS8gBTfkZsENBYB2gxvZ5bisryDXFauJJ3/Rx2mOd9/zLH7mgw/PzKIKUW0eRxjElqFAoZkbrltdBFOmA+VYpgiYQxTVzG0YBIrNsScIW3PaZs2Uyoq0UXPD5CsxswYnSdA8fSFmQTI3ZiZ80aDprT/xUXz/u+71/p4/W8BqmJuwIXNzbS/FifUEQbCgFXTJvNqyo3kn6IWYm60JbrRsoAEZ1DeZLGnx6XvXqch/EIcqO9lV3c2ULSrocGRxsewHk5aLUkJsyVLnQW5klOuZm/ZkaebPiB3n/U1IhkyF6IsxN3rRylnJaS6Mfia2a+AiyEVRSVTQe7c2iGtdwsw+K/J7Gg9c15wHN+946+vwL/7Kq5zbnW0FLYPkE+vuniCAZiy5W5oOYiQzZAcjPBjdm2TYGGpZGt+m/7ismpuODQVyoWVp9jtg95nKch3c+CRs1/bTyvhpO/fZ4AY6HFJVMq8sjZibQD1Pqh7XtoJ2jGWpFcykSp5Ww9yUtZ2L1M0Qa368DG4WVU2MGXNDNVT2s1bpcyP879lhgzvF0aOCqcXcUGaTajhOlrK0Nht5Ek0u96MXfeM0V5MDDaQPnN/G1779Q8pq8k0vP4uXnN30btuXGaF9TVnWSrDJI2xLllZhbijLt9xLZRgKOGRpg1K3HKoJwqScu7GCble+EoeBeh7CMnvdphW0s+ZmweDm/PYYH3v4kvf3RblZu+amjUaCLrgatwG+mpsUJ9YSXNmdLlyc7s8+Nt/eIsYUz26P8cbbbqj8PG4oSyPZkI9houOPS0cgfpxtg7t50ftKvavIKZDX8CWKbVuk5qbKWPt+35oszWkFrfd/fBTj4k7J3CSRMxBvti+dcedJnDQrjPvcTp8bOJgbckuLjD4eNkx2jGRpftltXuj56eaTa97tDuMQVz39awDd2oEy5tf2Upw7ZrKfNEbwmhuaW05vDPDpJ6/qYKSc40YGc5PhlvV1APBm0yvHRTU3K7SC5lbPHPT4Uw1wJoQ6N18gJAo5lp5k9X/81fQbCrQjSyPmRsoGzXkyqTA3VaZeMze2PK2GucmLUjo7/72iesfjSpa2HHNDvbGA2cxNm1L6g0bP3DQEPciUdaHBmWdnNgZR64YCVetiYeqly+N68MIudiYZvvoLbzJ+7oNsxOWRpcVmR3o+eSxbPDzxBDd2H59FUTCZB20rClGRpdnMjaq5afH+2TrWZSAKLW+Ko0BZZ8dhmb1uUOTYFJR1IsRzLsbVdnI58T14YdfbUFE3iJX/PyhDAZ9b2om1pKyBWEyW5tL/J9F8bmnzBsnjNMfVvRQ3Hq8yN03fX2KmfQt47QQXLu3qMwv82abjCctaRArsTVlaVVrSFPy2uLqzk5ZefraN97r6PBI7Tou4Y2VTUkDOM8MyEJ+3xkkyN46am1wY18qXWHjwwo6yw22yL9vhk85T1tyY71qaC3zwgYsATHkTt4IGYDRRJXDmpg6yz02NLK1MJtoNnjk0c8NrbsrgZnOASzvTiiPosVGirvfuNMMm1dwM5O9nydJ0zY1lKNBVjZsQKripOqCZyouUGQr4PgtUTQVm1dz4xul4gUSb7PWizXcAPTa43j35+2rNTWoFNXXjS1bKnxcZKyhBfXJZWRpjbsIwwDAOq8GNCvbM5EEvS3sOoVJzk5o1NwBwcn3QMnOjF0cUVF3bTw3pGw36NKC++ubjAGZP7EWNocDAGkAo6xAGbdTceGRpkcm2LArepFH1V+BW0JT9sgr9ePFjWxkxGgzb2F7O+9yEoeH6lgndOK4V5iY3nw3bGrwpeCOyTz1x1fkZvlilr3EYdFpz43NLqwtuFjUUaEM3rnTiDSecC9vSBvqcr+amQeaT+iz43nU6/jgKKomCtqFqbjKhgg+ydxdFteZGjSULPEMGa+BZSNOitRW5qfA08Sz0GE5NSQGzOHhedpNY7SgMKjU3hizNs91/93v34V/+xqeb7YtdJ9sKemMYYXeaGcHZu+95Fm/9iY/isUt7xjOXsXtPx2qD12HVYRT7a5XIDXXAmEhXYD8ppeLHhvqeUOLsho0BMlHgUsmy0XN45tgAF3fkO0lW0AC8DlY2VA1PbBoK8Ov04Qcv4T+95/O122kKbgVtv0PKUEAZDgivFbQo9LNrKyLyGcGNTOYtz3oDpRV0HJXyanO+t5NPLlmaWiNYCURX8oNA0u5FAlG75mZhQwFrrbU2iAxDAer1Q8cL6DGnNxR4DkExN+SWNqkGNzdsDFotSJ8yi9ONYYwzm0M8emnXYBdIxkU6aTq+WQGIr/YA8LulRaEc+JeRY9BA7Q1ulq65KVSzLy6HILrZX3OjKfRFOpu7YGdDlkHBmDbe94j0+VNr0F4GlHUikAvQvODSk7sfu+r8DA36fIE3iMPumBtPUD90FBur4GbBRmzkdmhjXiZMZdMa/s2zZQNPu8cNAMMOtQ4UmPoCFtpGEoZKt95VcMOfbduWnpgbV83NIveMj22+Bob07rWxAJDjlfkzYmNp/zy4GSWRkgT5XM2mmcC3/fTHKiyLKIAwlMmra9YcQvdzGJuSZI7dadao6STtK7HYeHrv1gYRisIMosh2fWeSmXbcVHNTk7xRbp4NmBvfNZNuf1DuZr590UI5LG2nAT2XnCnZnGfK94+ekzObQxbcZMpQoLEszWKCXIYCv/XJJ/Gf//ihyt/+6p8+jv/6kUdrt89RFLLWa42CF0+tzCjmhgJuWVomBM6WdX92LavZc8l9T12md4sk2saZbH4bRyGToZvPJEFJWo2ehiVjYwUAtcxNbtbcCEHXdvax2zU3i46r3NESkM8bf9Z4wHUUa2764KYh6AWkjAZp0qmGA5COaa3K0jJTbnHbmXU8cnFPDRTcUpa+UlZoVtF/XvgngyQ2rWrpHaZs6VLMTUr9gSwr6Bb73ATMSQmQAxgFiZU+Nw7JT1sB6iIuVz5wDXIcMkOBsuN8WqNJX2hfvOYmXqzmhtu9fuLxq87PFOzZInQa3HhlaVWpz7X9FMdHMaKoXeZm3gmagpqm2b/zxNw4DAWaNvHcU1bQnuCGvVurYm64LC0qs6IkyUysYBxYzC3NXFg7ZGksuGlNlmb3uQkCo9/EcS5LM5gb96L48u4U773vAj768GXnvgZxaDA3aa6Z381h7GVupploPL64kkw03+gEoR4feM8d/m7Y9Q2+gBOoOl/ZqDMU0L1k6oMbWigDeq6l/ZKD2tNX9+W2Ih30XNqZIssFJplQ7SRUkfdMWZrJMoQOQ4Gt/cw5Zv76x5/Ar3/8idrtc9Amdc2NxdwIi7kRrImntX8hdMBXkaXNqrnxGAosJEtLherHZbvv8XED4OuCanI3tdjDuvGFXDkjVtv7y3/6ON70g+9Vc8zPf/gRfOcvfrzytzT2nli65sZibpII+2n1vOS5mOugXpb2HEK15qbK3JxaTzozFACAW09v4GHG3Jw9NlQvHGWk1gdulxMbspDV/buhT5YWykWFr99AEyjmxm7i2VKthWQ4ZIBjWkHbbmnmAoVPFG053tkU+DIQLBiNOXPDiqoBykAut7+KW1oY1FLwPuyU78iZzSHufvyq87iULI09i4Oou+CG10xw2FIfIQrsTLKlmBtfzQ3PIDbdDh1TE8xibposykka4TtvOv4kCpwLgjahDQUKFlRB3Zc0E0YzPuWWuMCiQDiymRzty9KqTTzDUC7+aPHkY2589SN0XDsWA037GsShqgHZGERGcLMxjDHN3fU8aS4av5eiZJqjMFB/Q0HAukoQ6kX9VN1j4Qwwa93SWE1oHWTNjTuQmDJ2ZBZzQ9efGBj6PDmoPU3MTaSZm71pjgsle2P3uZltKKDfNUAzk3w82BqnzvtmB4uzQJ/1uaVVDAXKgI3/LSETAmfKa2Kvi2b2uRF+Q4F53uuikDVBwzgsJbnmIj4KzfE5CavMTWYpMIhJrmuPIFn7UM3ZQgCPXd7DM1tjtZ1PPH4VH3nocuVvdyxZ2qLjKreCBuTYwZlXu90HsXZ0vIcdfXDTEHbNzV5qGgoA0g66q5obALj1zAYubE/wZJkZOnd8WKm5oeObtYChyceFiiyNTR50OItO7BSEDaxFn5alLbdgIK1uFATaLS1gsjQWFAAmc0M66rbuYT7norQOQhQqAPj6N7wAb/3iFwHQ7ldGtnPJ/Tnd0hZwsaPM7B0vPY3Lu1M8fnnfuS/A1FcP4vmaXM4DXpPFYUt9tscZikJKA6JwMSmmv+YmmOt6zptNe+rqPoZxqBoLczStuSFphO/Zpck/jsKVMTeAZn6p/k8IR5+bJdzSXD1WjN8L7czWxgLAbSgge1dpWZq+j8OENeTzMDd0z3YmZra8KGQSYRBpO/ATa4kRNG4MYxSFexyeMre6mecloHpx2VbQxFy4ghvODvEaiTrmRjjGEBdc7Cw/N0DOD7Qd1/tmMjeyjoOCU2Ipnr1my9LkAv/RS3sAUJGl2eYK3mOzrKD58ZG1tz1uTjMxl6RYMzNzGAoQc+OQsJ1YGyAKg0rCkI8VPuamjXrFNJdyQ8nc6L9VTTxt5iaqJmqqbmlzMDdsvaTqxpiszfU+Ub2jDm4WG1cp+THiNTdclmbJP/lueubmOQQl+6KB2cncDLA9yVpxrKJ9ctr0tjMbAIC7H7+KQWlZmargpqy5Gc5Rc+OVpVluaWzyiCzGY154mRvV32S5HguiZG7kpEqMk5al2XaavC7mzDE3hb4o7IzPMuCD/V9/zc34xje+EACUNffUcb8WRdUtbX77TUC7vnzZS88AAD7x+JXKZ2gM5euSLmVpmSfgsKU+lNlWbmkLXFNfzU0ShXMxYTTRNH2OHrywi9vObFQYAWAOt7SZzI2WAnXtlsabSlI3d6r/0zU3XJa2OHOja8B8Eii0ytwIUS2EJxc4tyxN27rW1Y8A1dpBCqR4vePxcg7RsjS5bVdywbaMrj2vMnkWhyFsK+j1IfWK47I03SuF13XQezJRzI1bKgg0kaX5pc+6l4xm+WcxNxuD2BhLqNfd02Vwow0F5Lzy6KVd+XdWE8/GfW4sQwF+fFSzZMvuppmYK1FE95cCL/sdoCSP6nMjhFeWlosCSRRIRcteNdBWx2g9U0VRlIH48sGNYi/i0Bj7fFLG2DGW2cX2TRQZaakQ4OslO7DKhDvwpHpHYmwXbQJeZW5MtzTTNMFMXPSGAs8h0ERpD8x8oqBeNz7b2/n3adbc3HpaBzcn1xNDvjPNhNH/ZJbe3KX1JshMffVBjzlzs2hwYxVH6n0uviAh0KAYBFLrrWRpQaCyubQIsu1ihSi8FPqisHWsy0AUVVclgNXcdMzc2MFGylxyfCDm5oteeApJFODeZ7YrnxGMFSQMovpO4stACH/NDaCzXTy4CR2ytM8/u41/9Rufrp0EWnNLm9PB5sELO3jJOXePq6hBzU1RFGp88xsK6MynLfFsG5zlomcuKoOqvKhaQbuKgpuCrvEwdl+nXAg15rflglht4gnD3r0iS5vB3NBxb0/csjRduyFZBG4FTayKq5HnPBInLkuzraDtBCFgMjepSoBF6tmv63OjZdPNghvX2MIDCMXcuIKbLFeJkGOjWMmY6G+Pj2IlC6XrfHaTghvJ3FRkabNqbqymoC6mlMYre5yeZPPJ0miBS4YCVebGZHZywQ0Fqp+NwgAn1wcVQwHDLc0RFAFumSFn85qAN7KMHUxgbMnSXDbyOpgxg5PaPjdCSLMV9izZzE2auw0G9iYZ1gcRG8cWlKWxcwfKmpupn7nJWkyQXg/og5uGSC3Zl4u5UXKBFjo8A/Ll4cHTrWdk86/tcSaDGybfmWTys02zqKLwa5RtWZApS3O7qDTFJMsRBjA08oC+jsvIkWi8pEnVqLkJ3cyNYFnxE2sDxA4KfVHYDbKWga9GijrO8wli0cFQ/b0wpVuJw/773/3+ffim//KR2u3sMnrdZbUMuGVpww5laZlHy20zN+RudObYELHDUOB9913AL3z0MVyqCYSl61x1iJ1XljZPn5txmuPxy3veBr5xGKAo6rc1ToV6l3yfIwmK0edmSUmpD3wBoIKb8h3PywVCwsbJKAxK5mX+Z0hZ3caR8z1q3VDAEQDTO03bN4ObUBV7++YZGtPsmhslSyuPf30Qq0CbGwoA7gBgPkMBWTsUh4Fi43Wfmypz46q5GSWh7iifmwtDjtwjNbVRd92mLICw5wYOydxoQwFb1nR6c6iuEV3n05YsjYK7pJR0Nm/iKfdlGwoURaFlaQ7mZp73UkkC4xBhUL3eSrbWoM8N1c2cWk+qVtA1srS6Gqo4mm9u4OwFZ8xp/35DAb7wLwNvm7mpua65KBBFZjJYBzf6WXcFN7vTrHw3l2PEJ5kozZTkQYySyEiI2DU3BpPTy9KeO9A1N6WhwJRqbvTLoQfPdhZmaWZqydcHsWrMd3J9YDA3kyxXLzAwe+KVWTz378iFjbTJovxsECzvjDTNNK1v75N+vyh4cXrIDAVk7xS3FTR3NEsimWVqK7hptebGUyMVlfKZtpgbIYqyEaqZCbcH4ccv76naLx+IXt8cykWUazKgQ7Vlaa5+R+M0x30O9mceSDalOuyNLOaGsq/njg2dhgK0IKlLZOTCveiK55WllZ9tUvfz6KU9iAJ4ydkN5++bFP/zRafvPc9V5nN1bmmAzkZSokU++1XjhiRcrPGsYAvTWVbQrcjSHLUFUWguNsgSFjC7jXsNBcq/25m4ZWl0/KMkKp0QdSExsQqucXiaN18okzIgZDU3lFRQveJYFnnCmBs671EiA8wsF2qccD1jmfBLrDkUc+O4bryupa4J7CTL1fx188k1VWdDOF06pgF6Tju9UTI3l01ZGlC153WhUnOjitTl8e2nubpmFVnanIYCKrgJQ+c4pQwFFOuUqURI1QpaLvAlc2PL0vzBDe3DNd8NPPOID5y54fJiXxNPWuNk1sJf/o3J2NRd1zQvkISBOgdRFEpeO2WBuiiq64PdSY7NYaRdHxcs7hunuZEcX0vMPjdV5qaXpT0nYdfc0MDMJ1UtbWmPubEnbZKmnSqZG97gjjM3swY016RKSKLQyO7mTMLm0vvOg2lmOsARqHnjMvVKdEjUvZwGWylLK5kby1CAa3DDsNQH7y4uKxynuRoY6opg54WvRoqyvL6am6Io8L//90/j009ca7QfpV/nNQxlXxY+Ie2n+cxAdHeSIQxkBjbx2B8Xjiydz1DgnXc9gb/2Ix9o3GvDBSr0tGFLfchO+eyxodNQgN7xOvlcmguPFfR8srR5GMAHL+wAgJe5SWrqCQhcLuSbWPlz4irCbRP8WaD7E5YSWcrMDqx7KiUo8x+Pkt3EoXchTYvWdmRpVbkpye3oenLmZhCF6ln1WUHrmhtzHMvLBAkd//ogUrbktK+NGuYmzYXXSc11DLRQtGtulOOoh7mhhecokQtZfv99srRZDTwBvSB3n1sZ1EahsSC1McmEYnn/8Ztfhl/9u19q/J5YGkC/a4NY1sc+epFkaYyJG7gZbfPYPLK08vi29qvXkf9/noQh7/+ShFUJmG0owKWPFQamTO4cG8bGvebHDlRrbjRzUz0+3zziA70j2lDAHEvdbpZBZeEPmHIyoGqgYJxDmUTj64y0IkszZW6EvZK5WZYRJzUPYW0Q1dTcFMY598zNcwjVmptyUmUPz6z+A/Ni6ghuyFTg5NrAqIWYlEFD0yxqXjMhDBjlLD/LbIiXDG4mnuAGmL8WwQZNRkFgFum6+tzEluUjDcSyV9FizI0QBd70Q+/FL//p42qb/OsyKAp3B24qkuTXjX+/O83xXz/yGN533/lG+3HpnQcOenx/Oju42Zlk2BjE5SLHnUnPFdtm1ty4tn1tX9qdzsp01iEXbgaMWNcJY25OrScYxpHTUGBfBTcLMDeORcOsY+Zf6/DgeRncvNjL3MyWldJCZBCF8H2M997onrnR2zVladrat8LcRM36+digc+CJI/v3rTI3oio3jcJQNvEsz5sMBQaxtJadxdz4ZGmiDKS0LE07SNG+KHnnev9ocdbkPpMETiYG5M9oDrGl3YAOYCVzI78fxVFp9e1O3BBsGa0PuubGL0sblLUZcl/VbchsuLbWPcWYGgC4oWRpbOn1mc2BCgSIHQOqdRAuUJKExmQ7wbg15g1Zq8HNIg2D4yhw9jezDQX4M+aSl0VB4Azg6vrcuKTKhHn73HDmJmEJD18TT6DK+qpgxOpvU5c8od5bEQtEFWNjGQ3Zc8HuJC+d+JYvAeAqmUoTT2Geox3sHHb0wU1DVKygp1Ur6LZlaZLlMF++Wym42SDmpqSjSy1w0+7cUhPtZ25o//KzOhBatqfF1MomcCzrkmXX3BAihywtsjLYVPwonV0WC24mmSituvfUNuXX5Z8H2dSs+nNyVrL1swQagH3FxzboWE23tGqB9jjNZxb9704ylaX0LRa1BEH/zPcccJZyUfj0+fRM0iR8fnui+sSQIx0HveN177rPmW3epqiqz02DxfQDF3bw/JNrSj5rQwUiNQuePdUhO/Y+uySVI9cy+bOOght2v8dclhboILMa3CzGAtM15nbJhKIoyuCmmd1+0/3ZiziSmipZWhnckKXrrNpOxdxM7JobGUhRcLM2kLK0jBU2a+bGbSgANFtskTLAGEdUcFO1gtZuaTqDPEoiZEJgktcziaKhLK1ufubsiK5pqX7OzobbIFMa+3nk8rXNOWVpaV4YBjx2MmGLGRhN2bWSNun19t1f/SN/gp//yKPq/8riPQydCSn6PS2aeSNWzsBwebMrgDP63FSaf7olYwCx3vpv96YZ/sv7H/K+i5y5MWRpirlxqCEsd1Aa6zTT4g5KOMhMhjM3mp2kvzeZHH5OJnOzqCxNs4xAWXOTCnV9TQMBU3La97l5DkEN/gO7iaer5qZ7WVqVuZFRus1I+MD7ptigTD3XhtKLRguZRR/+WcxNXWOsWeA1N3y9EAVVK+hqzQ0VPw4WtoKeqMJKM6hpY6DwMQ5xKZkyMk1soFeGEw0Dbhdz4zJ7IJ133QKPMlByG+7FpnAxN3HklKXZdP68oMWpayE0siQr57fGOFtauNoyBYDL0uqZG5fsIQnna0Qn2DM6C3VOaYC+r3U1PzS2HR8l3mc3VYsgcwLvAk5DgTJhQQvVxBpT4nA+bT6BdjVMIvUe/dgfP4h3ffppzeqQLK2lJp728xiWizBVezKQ8hZ6RlVPJk+Qz2tuuISMxhAuS0uioKzLkJ/b9NTc8AZ/Td4/kqXxcSRkCbJhHKogmu+PMw2jRC5kjZ5rjmfM1xPFRi1zo4Ibfcyu+ztOc3UfXKCaG9sNlOygg0C7pAEkFaq/ntPMbAlRx9zwcZ7OyZYUc9z79LZiewGW3IoCg+kgKMONpCpL45/lzXZHSYix1V+orolnnaGAPY/8yecv4t+86x7c8/SW8/zoHZHMTWjYMMt9OGRplqNk1Qq6fFY970FR9qiKI9MtzTbF0M1Aze3sTDLVQ4nvf15UmJuBOW7wAE4mU9h71svSnjugAVYXQ1aZm7UlmZuf+JOH8HufeUb931UoS4XCpzcGqjahKClPXnPj6gfAUTchaFmaZm7oo5oZWuwcJx5DAQBK/70o+ELZmFRDPYhpG1TzOlEtxtrALLqbB3TfK826WohuCp+hQFn8aBgK5HzikN83Z270opWgBlkruAHqWZSdSaaylD5ZmjO48cjS7J4X88LX2wCYzdxUDAXKZ6QuaMw8NTfzyi8VczPjT4Qo8OD5Xa+ZANBMVkrZ2GNrSU3NjbSeD1g9W1d9boyaG8bchKG+D66am3lMGwhcdkPP+3/96KP47U8+VXHBasMdzmXJTwkLMm1IwhDrzAJ62JC5KQotn5b7MmVpa0lcSnBm19xMPeOLD1yWRuDfb1h1GLzLvXLkcsynPpOH+YIbx9jCZWnqHaluYxZzc0PJ0NgJPLKDJpkuwS7ydiHNzYSgzZTymhveE4rfM9fYm+WisqjNWNIidrhk0kdJGumTpWmLf8ncyMW9W/ZkJzTrmrLasjS9UPcwNyn1uYmkhNtyOvPLhqsBtR3c+1ltvW0KRAVjbnTS2L2dvWmOjUHsVEzMg0kmjH6Cyno8rfYwq9Tc9LK05w7owabod88hh1jWCvpnP/wIfvR9DwCQk/beNMPGwAwEXnpuE//hf34tvuoLb1ITepoXmKRyAGwa7QsPE8DPiV5GPnksm6Wd5n7mxpYjZbmYq2iXPhoEQaXmhhZgJPOzF3l0jvM2WOTgjej4tkWBRkW4dfAFo0S1m25p5jUEmgfcmrkx3dIAc4KkRWVdcMNlaT4pltbj658NYnefm2WZm7qMIElldiYZhChwfnuCc8TcuAwFstnMja8WgKRAjY+7obzxma0x9tPcayYAuCWGNmhBfHwUe9/zzBgT2rNGdsFczJSGAmUdFz0nzpqbBRYFWnajZWnjVGCSsUU39blpxS0NFblpVEpNef3DaKBd0rTrlye4YcfFF59FUSAKNasgZWmB5ZbmDm5SI2Ey+/0jWRofR/iYvD6IjJob0y1Nfk/nyxkel5yyrn6Uw66r46AxexCFjBlxy9LqmJszGz5Zmvw5r7cBqkXeLtgKDl7HAfhrbvj3rns2sZJwAK+5CVXgy0H3hubwHcNQwLEdxjjy8+RDxXzMjWluo9co7meSznGUhGXCg8ZS/W7ZsIM6W4mRWgGSDcNshd0rfb3NgKxacyPnTdWMeAm3tJFVcwPo+2CbJvD718bYdtDog5uGSNngNyjdxLimEmCytAUNBbK8wGee2sLOJMOdj16GKIDX33qD8ZkgCPA1r30+NoaxwbBU+tzMkqV5mACAL2bLgaOoytIWpS0naY6hywYF1Yz2d/3SJ/C//erdjbddKBbArCcKHbK0yAoC5UI0nLvYm6PC3LSYCRECThlhHOpGhq59pSq4WZy50R3fGXNDzEXu3+7uNFdBg4+VczE3wzhUvTGMY1uy5sYluSOc2RxgYxDhoQs7uLQ7RS4Kzdy4DAXo/GuOxZdRTsKgsesUoCfVWY/lLKc0oBlzo2puRok/uGGssqurd5tI84Ixa5y5CdQC315MxmEwMxh0IWfMjWI90xxjZrer+9wscDIWXEmmMJB9lfS7GGJ9EKn5JQikrMv37PHT3pnoha+SpZGhAPX+yIV6t0h2bQftxkK5wX0mZzY+jkSRFdwwxsLnlgaYtTlu5sbfs42jTpbGa240M1L9TC6KGcxNGdxYtbJUc8Od0oDmNTfO4CYn5mZ2cOO2ta7Kq1Rz3jIh6DMUIAt4s+amOgeFYaASwmMjuPEHy2qcdqxPEmusqet/xPc5LN3S7MDCbuJJ52bXowCa3dNBjo/V1tfIqLmx9u2ylC6KAnvTvDT7mF0fWQebuaHvae6ym3b2zM1zFGkupAsXYwHsYrRZLjazQDUMdz16BR984BLiMMCfvfWU9/OcYanU3Mx4OJvI0uhl5BPwsvaE09x84Th4cCNEgQ98/iKeujpuvG3FAriYG0+fG8MKOggQly5LizAtuuamSjcvu/Dz9rkpF97TjE8W1e8bMzcO/39bplgUhXYLq9nu7iRTGn5fDUThCG6oDsCGT6PcFHWytCAI8NIbj+Hz53dwflv3uAHkJOuruakLGjPhqbmZ0wVHMYAzPv/QBdlHo06W1qTJr6q5WYu9n8tyocbBplLYRZHmQi0K6XrT4spnKED25fOCenrFoWZuJqnAOM0rNTdt6NJd43BcMjc8GF9LIkdx8GzmZpsxNzSGcEMBsiWngIWYhSpzU10A14EkcIYszWBuYqcV9DTnTTyr/XCcNTfCLf+0MaxhbsiRLeHSbuv+qvoNz/wF6J42ds3N6TK42bSCm1EDt7Rpbtbc2AnGrXFV3gdYgY7jntHz4+pMH5cqhooVNJsf4ijw1tzw7aw57iMfy7x9bjysN/8bri5xQTE3pdmSZkt0EGcjtsxEVDBiMS11Y6Pctrvmxv7KtzMp+zxtDLWhQJNkggu84SzAyyZIlmauT/j/+z43zyGQLXMQ6I6v9oQ6Sws9C/RSfPShS/jwgxfxRS886XU9AsxFJ/WP0TaW9ROQZAI8wY0lQ3LJ0halLaeZqAz8hIRlIx+5tIvtSTYXJcuZm1mGAvYij2puKDO0yMLIZm5yx6SxKOqCmzq3NPp5U3tyXlBKsAPmaa6b6tUFGrYszfVZ+pFpKOCuuVFN1JZkbnzP/cvPbcrgZkv2uDlXMjduQwG6rvMzN1wa9pMfeBgfe/hy7XHzZ7QOJBHhTR8r+1bPvf+496YZgkAuQOtkafRcdM3cTDOhah1pbA3DwKiFsl0lXcXQTUBueuSYRBnXcarlUjTudtWcNwwlc5OyBdgtp9bxvBNr6jOjJPQmLPhxcdlQUchtG1bQUSlLK59jel9dlsIE19h47zNb+MHfuxefeOxKuS/pzGbXPhI2hpHbLY018aTFGA+CXM9tXizP3FCtyiBiwY31/NCzVydLO7WeIAj8srT1gS1LC2euF9LMlKWFYYAg0Pd5az9VrD6/TxPjntUEN+ya0kI6joKyiad5r3UtjUwYmjU3PCDQDKtL0WL0ucl8+6gcckUiPauXHAWykrnRjIyquXHJ0sLAOZ/aRgK+ecgpSxO65sY+Bn7P6J3YGESqT9SiSaNx2didYDNoprJEmP8/ArI0/8q5h4E003aM9ILZi/RhHCII/FroWaCH/d33nMfnz2/jO//iy2o/T8cxyZgsLWi2OBel/rpuu2qRXjiYm0WzCTVuaUPG3Hz6yWty33Pshz7KM4ZBKVE7sSYnl5PrcuEXW3UCtBBVC08hMJgz9reZGz4x+K6Xr6mpDd9COQoDFIU5YfNFHbcKbwK3W1qgjhUAxlM2gdZslxsKJB6ZEHe4IwyiCKIgdkBfG9WFe0Hmpk5nDQAvu3ETv3bXE7j/2W0AmrlxWUHvN2Bu0ly4a26YG+Hb/uA+/LXX3Iw33nZD5XOEpn1u7GZ/LjRhXncnVNBaPW9Clut6oq7d0qa5YHKpctFkSZ7csrTFmJswKBsYikK9V+OMMTexOXYsA1eSiaSmkk2W49d//MbXIoB5vrNkMYDJ3OSlMQx3SyOGSDWpbmIoYL3H//RXP4lf//gTAGQvqi964SnFhPuYm7UkxqWdvcr2pfSrzLY7ZGmua17n/MlRawVNhgLsObJfEe685UMchTi5llTG9DMe5qaZLK06R0QssN8ap7hhY4iLOxNDztu05sYs9NesQxI63NLK/xJzQ8Gz3XhZsM+5mRvz/Ix9ONh8Ao2dqRVo+N5FFZDGYanKaCBLs5t4ltdHFDD6T/kYFW6nzRvCcukl/8rfV5L5rZMRT+SXyb/r00/jjbfdYNiMc/iYG1VzY/XycTF4hxk9c9MQ1JQJ0M489oRKWujxgpllesjve3YbogD+3EtO135+yJgb0lfKjObsh9NnLQxUBxDBFtZ2UDAv6vrcUHErAHymDG7mkb8Rc0PyQUBPqF/y4hvwrn/0JlWPQJMh70UjqfjlmRuaNPg1cmV573r0Mr7g//x9JYOqgyjcND0t8MapngDNYsgyIFnKLc3cLp+MfcxNVj6TirmJQqMZnz6vciJzyODsbS/b56aufwIAvOzcMQDABx+8BAA4d1wbCtiZrHEDWZ635ibS2ufdaT5zcaOCmxnZtCwvKg5Vvn3Pqrkhzbfvc6nQsrSm9vOLIs2Fap6smRu3XTlh3mZ/BN2fQkpy1Dud6lqQtq2g7ViUeldxdmx9EKvMK1AfvPF7tlMrS4uNZxEANj1NPH1ujADwwQcu4o6XnsaZzYFaMJEszai5Yd9vDM1FvcsKmlw192fU3Mixe/ZSxsUE2eeXxIGqDbLHbO68VYfTm8NK4pNs5X01N3UyaJdrasTGpK39TDFDhiyN1UO65jMtS6smwyh4qcjSyuCADD0o8Dw2jA0mw8Xc7DtqboLAJUvzj9NqLrJYD9+7MM5ylbRMQocszcnchFZikjNbmsH1McO8V5xO/LC6MrXmMI8F4MxNvcvoRx+6hH/wCx/Hz33oEecxAFVnWlvmSfun9aKxXjkCzE0f3DQEdyyhbLJdNAjUa6FnIRMCr7rpeLmdEF/0wpO1n+f9RyasczLVjdRBFP7GZ/biktP+NIcsGtxMsry2z43N3MxTFEyHFAaBCtzoHIMgwKtvPq4+S+xOLmRhtyhowKbM9vwLo0rNDcvcu+7H45f3Mc0ELu3MbhrK7bg5QhXc5GryXsZQoN4tTW7LtSixQXUbJMPwuqV5ZGmubS/rlqZ6L3iC+pfdKAPfjz18CSfXE/U+SUMB87OKuZnlllZTc3NxR8rfZmnum9bcyICjfkhvVHMzzaXm22GBTeCGAnZD3LaRZoWa7Ol6x2FYG9wkNRnPOmSiUKxQLgqjn1EnzI2ziWdpKMDqmmzwLLRrmwReE0EskXJLSyL1PT3P66rmxm8oYCcddqcZXnbuGIax7g1Ezmxq3ghgWCCvD2I1Rsj9aRZB1dwMqsGIu+bG35Cag1iEPcf75jIUsJ99CnRHNTU3APCK5x3D80+tGT8bJRGOj2LVkFX9fBCVzLt/TLNrbuhcKJC8tp+q4GkeWZrLRpmubxKFZd85K/BghgL8mI6NYud2osBtKECB2SiO/G5pnr5u/HyU6ZHnXbi6l+JEKdONQmkExXtINbGCtp3TZrqlMckbr9/yNe/kwcuOYm4itQ3Xuf2n90pX3c95+vsA8h3mzyrdh31Ljjgqe3rxEgD7cfm377oHP/bHD3r3dT2il6U1xJQFN3b9BscoXiy4oSZpX/LiG3DfM1v4s7feMDNDpGpjssKwWLZfThfq7DNtWRqn/dthbnx9bmSthRAFPvukfGnnkZZwiZPN3LgQlYtWXvyoZWmLMzc8mzRKIuxMMuf10gPz7H357hcNzvupdFi5tp86s6xNDQWcbmkWk7fv0Mrb2CkXJFyW5qqfcsrSfMGNWI65qXNLA4CbT6wpF6cX3aCL8qWhgLnPpsyNu2BV/uzCdhnczBgvVM1NA+YmmbHIa+SWVjaRowDX1QGes1Ldu6UJtkDSsjTD9KIiSwuxI+YfhynpE5c1N9o4QmvS2zQUcCWZiCnkdts26lwd65kbGDU39P5SnZVc1AaNmRtyd9oYRsZCTBm0WNJFwsYgcjbxpIJqQEqJgNnMjSjc75kLG8PIcPji+5dGEtr23c5e07WaNS//h294rfPnP/rNr8cLb1g3fsaLvH21PGkuKnI2g7kZp7jtzAaCwAw8Z8nS6Nnmv6PvqS2CHUBzQwF+T4+NEmedShxxWZr+PTFVw6TauJv+NnDMd3bidRZzc3FnolgtPo9lpQmFax+2FbQp39LOgl7VgqheoywXRlN06k1Ix0PYs+ZNm0UCgLsfv4o/+fxFjJIQ9zy97TwGgGRpVStouu/c2j4XRW2N8PvuO49zx0b4u1/+Eu/+rjf0zE1DZHmhXixfzQ1QX+hZB3qWTq0P8L1/5ZX4+w0eIjqecZYbdqlUZD5rf02beLoMBRZdyNTVmAziEFf2pnjwwg62J1kjeR2HproDtViuk+hQsZ4ajKKgIsmbB5q50bSzloo5dN4zXFc4isI92NMC1Mfc0ADanLnRkxvBLuJswtzslQuIRWRpZBVe1f0vx9zMCm7CMMBLz0n2hiRpgHwuTA22ls7UZVzT3O3iROOGCm4aMjezmAi7RskF/f76j3tnkmG9rLmRn3UH5pWam46kDLLmZoYsbQ5DgaIovCyYqr0rx1Aayw23tBYNBVxJi7Cso/PVbAHVBRiHwdywHigutzR6t/emOZJyLBnGUeW55v/n15X6/6wPYmPeoX3Z8wZhvezvQtfQtILWGWUABsNjF/kD8vlswtzI/cZO5mZaMpFBEHgTeGNVnF7/jsVR6HwP73jpGbzAE9zUJTjSvGrCE4WBYShwYi0pLfTnZ25czTWTKHAG0NxQQDfEls8S37ft9GefIx3OKI4qhfm8XseGLUvjpkcuXNyZqpqUhDHM9YmDsBlz42O1RZUFNO6FEOZ8wsZiW/HgSlT/p/c8gBNrCb7jTS/Gk1f3cXWvqvwQQjd2J9i1T7qnV4SMye2AamA/zYRhTnIY0Ac3DWHU3FhBDseisjSeMfk7f/4l+HMvPTPzb2j/lJ2jKD2xrAxdIMtTF7RbGsnSCrWIVm5pC8vS/MHNX739Jjy7NcF3/dInAAAvv/HYnDU38qshS6uZ82gy5hT6rPqB3/nU03jvveedv6u4pQkdcLrWkrModQ6XNh9gzM1UZ/4yYyE+exHO4ercrBrDOgIlX3BDA6FibuJZhgKza26W7XPDM2o+UN3NuWMj9TPbCprX1NW96z7mht7bC6UszbXYMo+7ZFBnBA+pKCryFRsqYKl5r2SH7Mgohq0eE5Olkd3pgkHnLMiaG7KC1uMkDwrsmguf9TgA/NePPoYv/+H3On/Hm09meaFkcNxcoNU+N0V1jFILotQfrEahX3psMDdcllaUbmnMUEDJ0qa5Mb9VmRu2wGPb5+5OvEaLnNl8DPr6MEZRaKMG5cTImBsaO/dT7pbmSJAI6czWBOsDN3PDAwi6H/a+mjI380BJhWrGgDRz1NyUktGiKLA1znB8LcYgMnsfzXK4c9XccGbGZVphGAqUF2qUaEtx9TkmLXM1NxeMufE38axeC1uWxtkQFyRzU1r6s7m9juWuGAoYlsnCSPq6aqX4NaRhid/fNBOVgIlAzI2qubGSGEVR4D33Pou3vO75eEPZA9HF3tB1GTplaaZiZJiExjvIf6e2lwnne3M9ow9uGoLX3NjyNI5hEi1kKEAP1qzFCQdNsqSrNpmbGbK0okaWZsmCBFtYLyNBocZ0PkOBv3r7TfjWL30R7n1mG4M4xKtvOj5nzY2WOPkyhhw0GfOOyDpb7d7vf/7jB/FTH3zY+Ttec1OUbkc64HAxN/UDs31uLgMIXXOj7XKNAsiFa25czI3clmnh6r5OlIHaYPS6KyjRNTf6Z7NqbpoGapV9Kb24f9ijuhuDuQlNQ4H9BucP+GtubFnarHuTz8hOqv3lswuroway0t1phnXWIdtdxM3Y3BqGpw2keaGYGyrqDoPANKGoGAq4ZZAA8OjFXTxxZd/5O2JSEkuWBuhnWpkytCFLc7AOdD2nNcyNy8mKwIMDs+amKkujZ3FvmqtnVTYI9dfc8P1yd6eI9QYiZzZ6Hu1zpPu5O8kr8ilyiaN5aJZbWlNDAUCORz5DAbouxPxXDAUauKXNC1exvevYEmufUSmf25vK4PD4KMHAYtwWcUtLGevgYgcpEUc94egcEuuzfIE/ctTc0LV11tyIasKLkFiJL+7o6sLF7UmFuSHmxJc4sIv4jUAkK7yBif35hNXc8Ptrt27g8//u1Kx9s9kzUch/J9cGeNVNMhF3j6PuRrvE6UBcJwvKdQrV3MTaNZFQCW7ynrk5siDaGtALfHfNzWzfehfyfPbCywZN6CQ9MGtu6iden5MTwK1q9UQVKSaEqN35F5g0INVZH/+rr3o1/uytp/CGF53CaBAtZAVtyiH8+6LsZ87YCluCZUNmcN3nzt3S7Oyju+bGvWi969HL+D9+8zNGVshnAEHP4pTVJfB7T9d8kolGjUlddsm2g1ydLO3pa/u4uDNRAyE1BRzEbtcXJ3NT3oNHL+0an6XBeBEnO4BPuP7PvKyUpd14zAxu+OPO3+9FmJuKLK1hzc0s5ibLC28BOqFJcmJvIpkbuxO6uS/NZDep41kU5OKzVjEUsKygK7I0P3MzznIUhZt9pqCNmuPymipayMeRe/G7CFxJJs7ceKUzdbK08ucn1hKnW9rNJ0eIwgA3Hh9pt7TUZG7qmniaNQKly1oZDOfsWa2XpcXl32cVswIyxiCZHJeluZkbs4dOHTaGppGB2m9mFu3HYeh1SKzrczMv7DoIF7yGAqLAVjn3H3fI0qaee0agRAFPhvHklov95PWpdEyjuDQfmCVL41bQ5WYlc2Pug0vfbNDYaZvLuMYecqM8c2xgbC8vgwuv5DM0mZvcCv5MyVr1umpptzY94fc3tWyXTVmaVXNj1T3xPnTnjo1wZnPgNBVwNZwNShatUnNTMjcueSLfXh/cHFGkrPkkLc5di/RREi3U5yZlD21T0P61LE0zN7MWGr4aDgAYRnIwIi1szrKLuklo48NUoIWCr4knIM/pF7/jS/Cz3/7GuXtVcHtJOre6hWwcSscZXXMTMrc0n+RDeIMbztzwYj3AnVnyNSD7zbufws99+FE8dU1bRIvCbY7AJ4CRo+aGn0cTxkNPXvrC2czNuMZQ4O/+/F347nd+Sg3S2tKyuSztDbeewq2n1/GPfulu/Nqdj1fOpaks7f/1K3fjX/3Gpyv7qgt4X/OCk3je8RG+8AUn1c+kBMQtRfNdU2Lu3E08TeZmliyNjnvWu5CKqnzFt++65MTuNFM1FID72ZV9bkypahfMDT1zoyREGJhWtbVW0DXMBiUhfBKnMCQr6cIIPCnjTxavXRkK0HlNstx7P+26AA46rhNriVVzI7f9+hfdgI//71+BW06tG1bQsaq5ccnS3BIn5e5UBsMqEBem+6S9kCSWeW+aG2PINBPIyx5K9KxyWZrTLa3wJ+ps2EYGar+53SjTvcAD2mVu1th18MFXc5OJAlv7ZePeUVJh3IxAx1HvqNzS+OK9/D4JQwzioCoNJlaFvX+jJKq4YXI1RFLOq0bNDXNLs/fBZeI2KrK0GkMBcqM8szFU50R/K5kbf+IgNQIKcz41mC7HddXXUEtnDVOMXBjXymjiOZHGHsS4VJgbpXSQ233VTcedzI1qXmpJKNeSyFFzI4NYPifYYxvJ0pokSK8X9MFNQ0hq2GRs3DU3ixkK8MZPTUGZE5pgqBttElUdNmzkdU08Y80GAKUOvdLEc/5znJS++8MZmS+yoeR2l01QsIUyjVuz3NIyUehFbxAo2tsnaclF4V1c04AyZYMXDS6uYMmXdXr4omQsPlvaYdNnXPM3Pz9aMPB7zwfRJowir/0ixFa2bN+zuE9zgXue3sLHH7uiFoKGoUBe1Sgrto09iyfXB/jv//AOvP5Fp/Ddv/4pPH1t3zi2poYCD5zfwQPnd9T/dc2N/2/ObA7xkX/5ZrzuhafUz6ShgP6Mef7ua1pnNWrX3DR2S2skS1ueuZmksmdW3bueOfrcdMHc0L0elGMCoJMXM/vceI7H1YeKkBdmg1CuM6dxNgplTV8bzI2riSed19RjSAFU6wLMbTLmxpKl0a5OlM2MBzHJ0jI17ruYG8NQgD0Pe+w9rzI3Wo5mnyPVUO1NM6s3i1DsGd2DvRluafLzzeZN24KakOaFEUDYdXaAvgZdMDe1NTeePjfCYG7iSq3U1HPPCGNLngTopEccBc4A2rCCpmA4iaQbpiPzT2OD3ayUnlFXzY1gAZQNNT9bc4Gr3k8FN8dMtzQKUHxrLZu5sWXeRqDvZG6qCRh+7qkovA2+d6c51pPISCZnjmOhd+PVNx3H55/dqVxDYrht2/I1VhOuE7BRpeaGj23k7CaK5q6r1wP64KYhzJqbwPjKMUqixg0TObIlmJttJ3NT/xA2sYJ2MTeqeHiBiZ0G2+GM7DI/Dl+Q4YJLllbnokO6Zb4QpQG7zmbVt6BVzE3GmJtktizNnrBVcPOUzsi4tPmA+bwotzSPHGEu5sYhS6Ng19fE8+GLu0jzAlf3Utz3jCxyJHpdO/B5JAjWs3hyfYBv/XMvQlEAV3ZT41x8Fpw2qLmtPjctF5gHURAYkjBe1O4b7PV1rO6LrufFkrmZZqL2fVKNEWcxN7lfR06IZjzfNJENYyZL8ywoY7Vw1T9rGyoLyoIbO9ECVNngOre0sUOOQ6CGxZEjuNmb6B47dQ1O54EryaSYm7ReOuOTZ9JxnVx3y9LM7ei6Fu6WNs0EPv3ENbzzricA+Jkb7u7Eaz1pX3VW0ACwM8nV+xyFgcqqJ8xxbG+SYxDRNffcs4bT5sbQw9xY/ddc6gfVxHOGW9o8aFRzk4lqcBMQcyPHxhNriQxujPGeS6EcsrQa5sbXxNMwFCBZWhKWMtBqHQkNtaNBZIyVylDA4ZbGWR8b9J7TsU89cyggndIAMEMBndjJxYweUh6JVpqLCpNjg651HIVGTayxDeNamcmCdWb7HVvGIXZN7KtvPo5pLvDgBZ3EA/zMzWgQVWtuEil9M865MPdJ/z1M0rQ+uGkIo+amjrlZsM+Ny6VqFnTNjXzgmtbcKIajZuLknYN5IFS34JkFGpDqam44msjrOLihQOhYANkg2VtuDegAvAujzNLhc3Dmxq658dnpAqZEaJLleOqqZCqM4MZjKOCSpfkKHps8ly7GQQd8ZXDDZWnsWtz7jHZt+ejDlxEGOnOkGQO3BKGup4Et32sqS5vmwtKBo3JuTRBZEieaHE6uJd6AsQlzw4u96xY3jfvciKo238Ys5ka57MRh7bvOAynqRL9IHd4s8OaKdG6uOg77vOvc0uzMJQdJCW1WHNCyNOmC1KIszbaCZvax3gVY6HfEpNM+sTYwDQWK6njIa25oX9J1K8fb/vA+/F+//VkAtqGA3i93d+LjtShM6VKFuSnlqvvTTI0hm8O4dEsTJnOTZhiUz6Prua2rH7WxPohV0TaHzY645h56brqQpc2subFqyigxp5ibkaPmhrPqDvmUq8+NtoIOnclFp6FALGVpvF+Nbd7Caz34fkaOmps6QwG69nRu08z/LivmRhkK0FwskNY8M3EZZBPM+pjCCvT9zE3MZWnc8S8XxjmbMs9cBf7ymM25xw5uqOm7LU3Tzn41zA2zgq5jbnjAfJgc0/rgpiG47tX+yjFKwpl9K1zQzM0chgJUczORAxw9yHXFpkD94AHIxYrsTqzlMPQyac3+EsxNw8lh7pqb8h3kkpXZTTy1vztf1PgkLULUGAqwPje2LM1VDO6quXn88h5EIZ+jzz3FZGkeXblLlmYGN1yW1py54exGYrEusuFc2eyPbf/+Z7bVouSB8zvYGMYqaNFsoHkdtH139VhUM1nLVW4e5oZ/NmMT8zyQCwn9f5ocTqwn3vo6mpCcNTcO5qhuzFALxhmnXVckq/Y9o+aG3lHKlPP9m8dk7su38FwWdDxJpM0+7Hc7CFyLdr9bmqszOyFXhfA0tnK3NLPmZllZWlHIjGiVTSmZ0kx4Wcao5vzo3pIsjZJZeVG1/9eyNFZzk4TYneT42MOX1ZiROt4jwHR3MmtuyC3NnDcIxOhy5mZzGKtia27usjeRrArVSFbPt3lwszmUrJS9KOWtHoCqQyIdaxIFtTWj88LVqNSGr+YmF6zmpmRu+Nw0mSGfcrml0bhF987H3HBDj1ESVqygbdt9XusB6HF/WNbc2OY5/G85aD61j93J3JTM+Glq4kmJnVwmNBOfLM2SfFaYm1w7vrqCGzqmmLulcSvovHCaBADUQFkzN5F1D+zg5gWnZN+kp67q+lxAJ8tsCSWXB6qmxHGo2CzXOfMguWdujiD44Ke/ug0FlrKCniOrrPrcKCto+SDX9UAA6mlfwoC5n+QFqrK0BbKWizA3RdE8kHIxN7NkaVleGINpbLEUNjJRqGyRDc5i0GCmmBsnfa2DR8JDF6Qk7c2vvBFPXRvjyu60PDc4+xLxe+hq4pkZwc1izI0q4hRalrZW9jawmZsXn9nAy26UFpW8qza34eSom8hseaRdRDoL00wY0gza9TzSTzo2l6FAI+bGsa9BbC6igPrFDe17Vp1bM1naDOaGvaN1n82sffkWnstC1dzEflkaNV/kcElqCJMGzI275iZX+42C5Zkbl+06oMesSZZ754OkhtWmV/7EWoKi0AFI4WCJVAKBuYUN4xD3PbuN3akMPDKLAbULoAHJ3Ljd0sx7RiCrW+6WdmwUK4kmXxjulT14vMzNHIYCyqXNqruxm0u7gtftcYpjo8RrxLMIfD29CLkoIIrqWiMMKLiRic1jo9iYswGbualu39nnRsheWUHJzFAvHX08ZfDD3pFhHFXYDuEKblyGAklV2aCkby7mJiFZWm6co4+5OT6K1bqINyWeZHmFDSNIK+hqoAZQvY4wEolZLvBTH3i4ciwxc0szraCFkeQzZJ7TTJnwAKXro8PcgK792iDCsVGM81tmcKOD3tj4+dpAB5l8rKu4pbHL2Qc3Rxxc96q+Ol6OYSIzQ/Nm9bgvfFP43NJmSURsxw3ftukF55rmZWRpmrlpVpDJaeQmMJp4NmBuKEPDBwwaAOv07LOYG0APZvU1N1XN8yOl/fFXfeFNALQ0TQh3jZRRc+O0gp5PlpYzFotgsy77UxncDJMI01xv8/5nt/Hy5x3D7c+XVPm6Qa+7M12C3TMb9sRP96mpoUCam+YPSzE3bJc0OZxcH3jrr3wLV8BcqJDltE+WVhSFukaiQK1bTZY3kaXVF/9PHMGNayxLhTAW3p0xN4ahgJmwoONzZdJJq+66XnVuaWrCd8jSSIIVR6UsbUkVnn72zZ/zrua++SCqkd1RwuBEubCh+UEU1fHQ5Yo4iE0L/nEmjHHELoAOArl45cdEEji6NdU+N8TcZOod2hzGpRW0LPam+72flsxN5JbiSZao2TtN1vR2rxvbLY1qWji2xxmOjczF4rLw9fQicFkmB81dV/ZSbAwiJFHoNBSg4ME1nyn2Q5j3Vr9X1bkwL3StHR3TKAmRxGFFvgWAsTuWoQCrueHnCTBliWN1SmucicUo+mpuzjBLf5643J3kRvKNo85QgJp4UiIxzQU+/thV/F//43P4yEOXjGNKIi1L46qJLC+MJJ9trU6BP1AdV/W10c/7uWNDnC9ZKsK1fS1X5JD3ge67UGseu88NH/P5eqeXpR1BTPNCyXNmuaUB8zca1I2fmt8SGjhsQ4G6YlOAZ8v9204inYkxZGkzCpLrMF2AuaH9N4FibkJUgjH39sMy86IXorMCqrwovD1j3MzN7Cae/PwevriHGzYG+NIXnwYAfLaUpglPdpJP6sNY2uUagzFnbho8ky7mRrpD6e3upzlGZXdzuqe7kwyPXd7DK288hi94/gkANnPjlqXRIOpamwwic+Kn7GNT5ibNbEOB6rk1gZ2l58yNT+qnmVjHwpu9eDedXAPgD27omOla1L0KmfA7ABHoGfKND1w6Wlefk+fm8xhH4cw+PIuAnhfDUMAKblwBXcKytI9f3sP3/+496lmjxbSLaaL3jM7dqLnhsrQW3NL0eFVlnQB5L3wsIzUZdYGeGXJEI9myy3GRs4gxY2449qYZ0lyod9Ru4knuTnGojTfImc3H3JC19x5r4rlBNTelSxx/TwaRv+aGm1vMAu+vw2FLv0IPc2MvFpeFPcbZmLKFMkdYBl9X96Y4tSFlV8M4MpItk0yoMdjFDDmZGybXih1zYS5QaQshm3iGhrwstxJJawOzRYZq4plU54U6Np9kVtpQgObQ6vld2NENPPnxpnmB7UmGzaH7XtpOi0aysGziOWKJRHqW6HrydY42FDBNeIxA0LJW58yN3VDUNYedOzbyBjcn1sxztGtulK19yUCp/bCxnD87PXNzBMEHP9XszGMoADTvCE+o0+j7EAQBBqwLNadfa92XHL1FbPCmXLzoldZOiyxkaOBtGtw0sa3l0H1ugkp217d9ahJIn53Z56am7oMzN3uWLM11vWgfmRHc7OC2Mxs4tTHAzSdG+OxTWyp775JD2JlX213FcEtrxNy4JxaavAD5bEvmRmu8P19aLr/8eTq44dphNbF4ZGnObtSK7SmMv13cUGB+dhRAmaXXLABlvk6sJ34r6Jr3mS9UbjoxAlBdbKntMF00PwcXXJaxNnQdTf1iahCHrGGvi7kxZWldMzdJXBfc+APILC/wR/c8ix/744fUAoACUpesjMxTaFHutoIOnTUZ88LXz8MwFPDV3DjqIezt0sJme6zrbuwxhF87zdzIr2fKWoXxVL5H6ypbrffL3Z0iVus5yy0tCAJsDGLsTLQsbbNkReR5W01aa9zSuJvnLCjmxpKlpZn57rjqPbc6YG5oDp845hN5XO6EIAWSl/emuKEMblzMDQVzrmdlouZ3HWxkQiCymvOai2uhnldtFhAplkfb1pfHqRp92swN1N8C5nxa1+dGu6WZgYSvz83ZzSpzk4sCu5MMm0O3gqTSxFMU6vqTq9haopOW49QMtHQxv+5VY9iZ52YgwefEvUmunlFAzhW5Q5bG36dzx4c4v23J0sYp4jAw1BOA1edGydKk052LIQLM+dZlo369og9uGsKsualjbsrgZk47aF6ENg8GUahlaQlN/vU1N8pHvk6WFukB18ncLCVLmzO4acgScYlTpIKxGuam1C3bDccAv/SJPuti5jhzYwc3rnNwZZ0eubiHW09vAABeffMJfPapa+q8ZjXxpN5AfOA0ZGlNmBtPvyXe8X1vqmtu6J7e94yUz73yecfw6puOIwoDI7gZeK6rOjfHfdKyNLPpWBNDAbI0djE38wY39BzSsdIkfXyUIM0L5+K/ruaGszkU3PiSIYq5aRDcNJKlWYsQG4ahQI15iL2vKJA1N2ku8Dnm8rcsuMSDmHO9uKoJbmhhxhYfKsOqHJb8C2XulkYL2l1lBR0gDGdbc8+CL7CnY59kuZeRSCL/GE8MDbEM2+PM+57ZdVOAHrP+4ivPAZDPe5oL5lhmLnbI3cmsuTH7fLjeuY1hLGtuynt8jPW+kX1WTFbaF0CLYn7mxpbXTHOz5sblhidrbtoNbgDZGsEvS3MrOijhcmV3ipPrLLjJzeBmVParcs1nfMyhBTZnf5WKwQg8mEkEPS+Jtu3WMjEzubM2sGpuBMnSqvOCj9Gkn0k3P1OW5mJhL25PVIAOmAm2nUmmgmkblBymhEAmWDBTSsooaJhmujUEzf92bXEY6gamg7KGxjC6sWpu1gd+QwEXq3Xu2BDntyaGmuTafooTa9X6sFESqmPJywQVMTc5Y0ANt7Relna0Yfa5mS1Lm7fZEbdgnAeDODReHEAWm/oK4vm+6hZ53Lc+Z120aV22UM1Nbr70sxDNXXNDiwVmBV0z5/GXGij7V8xY/NXZEY+znBUQmo1Va2tuBAUNGZ7ZGuO2M9IB5bYz63jiyr5hlOA6B0Icaf2sOt45DQXUs2FdOC5T3E9zrA0iw53nvmd2sJZEeMGpdYySCH/xlefwhSWDI//eHeTlKqNcPRZlQpDJiWYeK2jy5ud0O+1rEStoQD+HkzTHMA5VjZOLvamtuYl5cFPK0qb18jZ6t+vYgkzMNhRQ2UtfsT1jV6OaRAbX5gOaufndzzyDr/qRP1F25svCaOJpLZTpHXeNJ/x5o+eexsnJrJob5ra4M8lwspR37Srmph1DAVX7aD0j9P809xfK20kM4xxKaR0t3rbHGXPIND/LA1R6dk6sSVvhP//yswDkdZuWNae2g9YeW4zxwIec2dS9cpzH+jDC7jQ3rKABKemNwtB4ljVzM/tZrAPtw7aDpvMjuGSHsuamXVkaUGVcOHw1N5SYu7KX4gZqyBqZbmnUr4qP3RxmA+ZyIc8cF131p4KtBTgrY7PsNvsySiJjjKM5bZT4a2589bLDWBvZ+JibSZZja5wZsjTew25nXCNLsxQjmRBsXZejKIA1YsSEMFpAyH2bSdwoCNQYtD6MlCMggc69KArsTW3mJrTmc7csbZIJbLGeVhTc2OB9bjKhGVJpca0Zql6W1gBBEPzlIAjuC4LggSAIvrfr/XWBoigMyQc9AC5DAcXczClLS61MR1PwyUkzN/WyNM1w1Gw31nU7vJh9mW7kNAg0tdKss6J1gTM3jWRppW6dNxyb5ZZGx+JjbiizV2FuaoIb2uYjF/cAALed2QQgKeQJa/DoWiDw8xs4FgBpLlRmtYkszdefJY609nd/mmOUREZfhc+f38ZLz22qY/wv3/IGfNebX8b+Xv7cZl0KT/YaMA0FfFI7H/iEPLWuc1MJC0EX1sv/U3BHNq6uRIaPAZM/0/u/+WS9LG0e5ibNxUy3Rfq1L3jXE3Ok3nmfpNKQ8ZTyifNbYxSFtDRvA2afG8qE6n3K3znkmmphptm7/WmOoigUc+NiUykwoPu2M85wck1mf6kIXTI3yzfxVIyxdfh8UedLdsVRUGtXHwaBksVM89yQ7HLwsZi+/7Y7bsN//4d34PSGXBgSuzKIpeWv2fdCL8a4Yx45s2nb7upxbg5j7E4ypRDYGOqxM2bsGQDGGjmYG9HcUIAy7s6aG8vF0GUo0HbNDVAf3PhqbpShwC6ruUms4KZ0gEuse0Ywi9wZc2MpVGwb8KqhQMTMB8yxlruljQ1Zmp+5mZV8leep2y7wvyFcogaezFBAu+/J59nHwsVWIi7Li0qz1bVEf2ZsSeQ4+037pXPfGMSlBKwaWNJcv27U3JhJDM3c6Pf23HF5jheYNG1rP8VxR3CzxgyvyHKdnqVc6AD/KDA37XOsDEEQRADeDuArADwB4E+DIPitoig+1+V+l8U0E/g3vyMPMQpDfOufexEAs0km4O9zAyxSc1MyN3N2T+dZSzqeWX1u6mhfQsJ867nV5qzFUR1oEmva4Xl+WZpmAZRLz8w+N9oKmjv0uAqui0KzPK5AYZzmOLGe4OpeWrGCdve50bQ3oJ3Sbi2Zm6EVKLvOxdalR1YBYioKbI5k47pmfW7cQXbCpA1Uc8Mn5Wv7qeon4IKSpVmTuLIMrdFXyyJjdybJB1uesT5wZ72awLY/525xQD1zU9fEE9DMjW+8oElQPUe1srRipqyVGm762FBeDKuyoo53gS9yAL0YpMzeM5Y16aKYckMBS5ZG74MrAKBxNM2FwdzIomf5GZ/zlm0FvVaaZ+xaVtDLGij4xmHOmvoWeD4WA6jaWWe57jDuqqVT2yz3e2ItwYm1BHc/fhWAfDanmVBSRZu5IVkUDwhEIe+TljBV79H6IDIMBXhi6IaNgZm4iWU9oYtxnMdQgAKoSs2NZShgW0Hn5bPdhSzNlpPZxwVU1xphEGCcCmxPMpwqrz/J24qiQBAE6p5xSTEHn8NStpDXwUtVxWAYCoTEyoSVQEiNfxHJ0kJLlobyb7W8izBrfSKNE0y2xF6P2A08+flQsf3GwF9zA8iE8xqkc+BaJbjRjBONL6oOqHyWQrZmouu7PojKPnhVdQUFDptWrartZgeYZlBnywDu/NYELz13TJ0jPRcca6xsIhcFoihQZQypKJTlusHcHFIr6E6DGwBvBPBAURQPAUAQBL8M4GsAXNfBTS4K/OYnnwIgI+DLu/JFaVRzowwF5pWlyc/PW3NDxyAjcPo+9DIPcl/1tC8gFwfaClovJKhB5iLdyK+WPVu4G0gdZknEbHANu90Lw7n9cjLmRXouhxi9ff29k7nJBI4NEwD7OrhhWl0b9kTw9DW5ILzlZBnclIs5YoFcSVyj5iYOKwWIaemY8ywm3uJ3jszzbEirTyZLSyIM4whX9+Q93ZlkeMEN697t6utqy9Lk13pDAVEJVmaBf4buVZP+Ti7QJEULq3EmMEoi7YzoeNcVE+t4n8l9ThTcUKBZzU3du5AJ0agJcF3xP6+Lo337pEB2L6RcFKr+75lr7QQ3us9NUJGl1dbc0NiRa0383jQ33tu6nil033YZS7mjmButU18GvtpH/u75Fu1xGKq6AJuNyQtTWsfrCu3N8fnGDkCI5difClVzE0dm343daY5bTmlZGn9mQkOWVj2HzWGMp66ODStoQAZTcRQYiT5VT+hjbhq+0z7mxpalxdYCj57rToKbupobFtxzxGGAS+W65BQzFABQyosCTLIcJ9cHjWRpSk7IpK0uFQM3FKB3ZJREuuamPF7NSmrmRvZSkddZy9JczA2Mv7UxjMNSHqat/u31iGJujJobua8ruzK42fSwcLE13mei0InGcpwmWVqaF9pQICPZslm/xcfk9WEsG4E6TAJoDuAmAPSeE3TykTE3x+Qcwh3Tru2nqnaXY02907mqrzKbBpeSW3Y5J31w48TzATzO/v8EgC/ueJ9LY20Q4e7/4ysBAP/s1z6J37z7SQC8v40/uBkuaygw58KLMjrGy1SzeAEaMjdxoF2FrIWMnMTmOkwAssnjC25YMwrN6xApCVzTmhv5NQwCNeHXW0FrOhaA4dDjYm74gGRPRkVpEa2yj6nJ3DTpc2NbZVNWiwY9VwBgGgpUG92lucDaIEIYNAu4aVFSsacNtUxxf1qtudkZZ9isCVopMeCTpQWOxc+ASRYMd5kGTF7qCIaWNRTgzM2oDO4A97s+y3aaJvjTm/V9buzgpo4tSPOiURPgJHJnwAGzLs4OCvkxFYU5aVP2jya/p1sOblxW0PSMOvvcsCQFPff709xgyFzvZF4mcvjCehSHGCaRcqWMokA1UVwGvmDbrqNzgdcF2JIlWuzz59ZnXmAGEObveLaaZNlJaLYZ2J1kajFm9xYKAr9bGiCL+3kTTy5Li0KZ+aYkgAysPG5phbsHmAvrrL8OR8paPQCoyA63xu6+IW2gkSzNqisLw0At4G9Y11bQgGQQ6P2tl6XlGCUhxqlmxtNcVJgb0y2NuRQqtzTtrJgK91jLZV1JFKrAfuiquWEtHVygczNqUax38YKDuaHzurovr5u3zw0Faqx58ubQlJvrJp6cuSE2KTdMk/g7t55EspdTpoM7ujcke+XrI9sMwhX4kSyNO6Z5a27YfaB1Hd0jcmcMQ3OeoeNbS6JDJUs7cEOBIAj+ThAEdwZBcOeFCxcO+nAqeOsXv7DiWDKIzJefQ2dz55SlKeZmMVkaf5lm1tyUL8gsK2iXoQBAWdr5o5t7nt7Cq2863vjzi1pB84xhPXNT0+fG1QPDk83g/6eCU7vPjav4mPaRqwnBZO/onu7XBDd88eySIGSiwCAKMbI0zz74eqVwmeI4FSq4UQNzjfsM/T3gkKVZGT7XuU2tiawJc2NYYCt3rOWYG2UokOVYS8JKQzmOupobQN6rE2tSejOMw5nBDV2/WW5pyzI3vC7OZxtN19bM+ssxhwKAZ1uSpRnBDbkP2W5pjtpHCvJSy1CA3ysXO5sLgSg0nxHO0gFQrAi/F7uTDH/pbX+Mux690vjcfLWPplGDr+bGP05RgT1nbgrPmM+DIDuQUguhMgBRzI1Rc5OpxZiW+erzsM0fODaGUi4rWZPAXACrYyrntxrmJivlNU0QhQFGSWgwpeSsaBsK8PtLveTsju9toIkszV5r8Cajp8hQwGoIKg0FZJ2Ur4knLdq5ioCeA+2MatZ8RNbzMoqjihum3ZR8ZDEfdGlpDOXnXydVBmRANMncNv+Ey6VK5LTDLe3angxUvTU37L2hc1GJxoosbTZzQ49VEknb7ywXKnBaSyImS6syN4klA7Vd6ADpMjhKQpzfkgGdEAW2PMGNkqWVDohcvjopGVP72afzumFj0FtBMzwJ4AXs/7eUP1MoiuLHi6J4Q1EUbzh79mzHhzM/XvuCk2pBrmpawipbQtAPz3yL/0XrAeiYaBENmMXfLuiMoX+7cRgqG2GpQ9e/s2nLJtidZHj40i5efdOJxn/jq7m5ujd1SqzofQwCXsjqv57UqI3bK0ZhgCBwL3z4z+z906Lp+Eg7/gC6vsg1Kdt6YZu908yNdmmy4bKCtgemmIKbBmwit/3moOAmKyVia6VUZ5LK4sTdaV7LyOnmqDYLIL+6Fj9BEJQFzIVeUIdBo5obM7ixdOBz1rVpe0z5f2Ju6sxDbM15ZZtRoBYlawPde8AGXa86BpCQitk1N0B9vQZd22FpIQs4HO4crJSquRm3y9xMWWKJFnjz9rmh+y9labOYm7JehV3HURKqe037lVbB+u+evjbGA+d3cG9pid4EXlmalUhyQSd+XPJZ0xQhy/2yNMAvs1YSlrJWKSndGGmcInendcsKmjuzUXDmOo+NgcwET1RtiPk88b8jtzQXc8kNb5qAjAwI9jtG+3cxN524pUWhM0EC+GtueDBny9LoHdYBqdtZb5zmKrhRc5Ao1D1LYjNgoc+5DAXsJs22ZbFds0LPI61bXI0qvYYCcYhJuTjnx2WfG6DLBAA97l8ppdS++cpOHOSi0OUGSpZGcnOh5lVeB2QEN+TqWD7j3C1NBjfye3omzf5wtiytOq8EQWA08tyZSuv3uuBmfypUIEvXeUyyNMcaAgBObSSHSpbWdXDzpwBeFgTBbUEQDAD8zwB+q+N9toogCPDWL3khAObOUyNLW9Qtra4vRh1sBzdgNrOSeyZVjkEcGMwNnzwijzygDvc+s42iAF5107HGf+OruXnLOz6Et7/3wcrnOXOjm47WMTdmzY0atEN3cMhfeHsyokWTV5bmmFzsmhsq0iZJnaq5UYYC1XOwgxu7WFwxN3HYKODmBaUcSWlSQb1yKLiZ5kLR6b6maPT3/JwJ3ATCBZJs0ASwPoga1tywe2XZhc6zEOKfV7I0VXMUGtvnmOV+mEShshjmjdVs2P0g6mRpWS4aGZI0qbmhjvCufbpYqbhMFChDgbZkaex4EmuhXB/caJkMjcXj1DTVcPdMkQty/g6M2L2m/UeBae5ACQibmayDbxzm/68LjgGP41u52KcFMDdNcY2HtjsWgS+EqCZlwBhccjGsMjcNZWnDWAWcgzi06hTM4Ea5pdU43DWFlMOxjvFZlR2xF3jbXdbc1DXxVCypFdywZ0Q18WQGLPR1WMrS7HE3s+4dr11J1DxYlaXx+iazz03JslsJOxojeKAMkJsec0tj781sQwEpSzMaf1rPBcnrbMUJAFwtDQW8sjRLMZILKVmMQt2vRllYi6LS32aSClOWphhmaYqR5kLdj9EgUoYBNIZsWG5pvMmnb8y4kTXyJGbKGdyw+5CVgazB3JTBjSFLK9c2p9YHaq4/DOg0uCmKIgPwnQB+H8A9AH61KIrPdrnPLvA3vuj5+MY3vhBf/OLTALgsrcXgRmWm25Gl1Um5Ciur4oLhlmYVbHJKvCk+97TMaL765uayNF/NzZNX93GBFc8RuK0w3Zq6hazd54b797syXUZwYy1iaNGkZWlln5uYtLl+WZry07f6WgzV4iI3js8+B8IgDipuRmkuEEeBovJnIWcdqjnisuiVjmU0kDUnkzRXVLWvbwDAzQHM6zDrWaRiWHoWN4Zxs+DGUXOj5A5zJhAqhgJpjtFAMzeu65rPYGKTUpYGVBvccdC9nGUoIEo5UFPmxmc4wuu+fLJQmmztxWAmhMo+XtiZ1JqaNIWS5cSBkp8pm3flluYIxhlrQWPx3jQza268gYE5DnOWLgjk/quyNNOatglcDfkA85mZzdy4zkE7utFnfDU3AFckVBkk6qOWlhIn7sS5Z8loKLHCndnqZGmUDLmyl2LIpE1yW2YCUbmlWecryvqv+YIbs3bA1UvGdoza7pC5Gcb+hI1P0cH/T0kSUgmoRTZzS5tazyV9psLc5Fx2VpU+ZtxQgCkMBuqzZsKOXiNb0SJrO91Ns2f3uanK0ipjlGVVL89Hbm+mLE0lDnSgRvW4ds1NmnHmhrmlWckQQDdG5gnV9UFVlsb73MRhiKLQc5evlpMzN+QG57KCtmtukjBQ/QSp5qbC3JTHd3pjcKhqbro2FEBRFO8C8K6u99Ml1gcxvv8tt6v/axq/+vIpK+g5MniAfjlndRi3QcfC7ZVtnaaNvGaiI8SMvaBMIMGO7Jvgnqe3cHwU4/kn1xr/jStzlOWi9IN3yDGYxCm0BmAXaDK2BwyfIYP5wluyNJu5aWQFbTM35oBMfVTqDAX4IoysoE1DAblNcpiZBZ+t6iCSi5wx0xyTVnxH0el1zE11EgPqZWmAXNTI4EZPBq7A1oZLlrYoc2MbCoxTgVGss/mu62pnLm186UtOK7lrE+aGFg8+K2gdcDRgbiK/LI038VRBXUVKSItyM9M+zYTKcOeiwMWdKZ5XusEtCp1VZ4YC1rtd75amDQUauaWViRyj5iYO1bges8U6X/xS1rWJZJLgtYLmwY3nfta7OhYIWd1QLkRtnaVy3HTsSz6bGWviqZNeu1amOQpDiEIfUxjo++AzFACAK7vTKnPDEk10jK6kne3K1QSy1kcv0qae4Ia/a6rmpgPmRvYLq3//7etHz8zGQBubuJgb6k1kM4q6RrQMbthcRIEIZz/18VTfu1EcqeO0+87Q+DeyEnVUx+sympnlajkq+9yYUjbz/OjcOeh4Z8rSrMQBNTZNolAdPzcUoPpqVXOT5UaZgDI+iTXzSfdjPYnV+0RjiNHnht2DYRgZzq4cZ48N8f775by4te9nbmgc259Wa27GqWRQw8BmbkiWNlDvwWFA17K0IwltLOBgbuJFmZvZbIoLQ8XccE14NcPF0VSWxhfftg68ae8Zwuee2sKrbz5esS2tQ+RYXFFnaWfBP5M4NZGlUYbCHjBcND5gLoZsWZrN3FBAMqqruVGL7vJrybIQNHNT1tw4rh1fO7u6eKe5LtZt8kz6am7ikkGh81ors3XTTAc3PppfHhsFqm5Zmu82JeU+6BqtD2KZiZ7BHPLJXDE3y1pBl8cgm3iG9czNDJnpD3/9a/DtX3YbgHIBOaPPjatzNMc8bouJFQBzcFmar4muy1CAu6W94AaZwHj62v7MY5kFXmtF463doNfZ50YtCnSTvXE62y1NlBLcxHoPaVzn9T7CMS41YRX1vuRX+5YZsjTP/fTVQwE6GaXvX/17Rvdx4HhW6dkkK2ieONOZZgpu5N/QszgryUTjxZW9VLl62efH61tdtWJq8T9HUlAyN1VZml0nwd8RWjB2UnNTYyjgddQrryvV29B2ALP2YxhHqlk1B70H2lBAL+RtNzT+jDkNBRx9bjJhPm92/7+ikL9zMfq+WjSCVAzMYm5EZVyg4762nyIIpHOZC7F13tTYNI4csjRmKDDhQaVlTgEw5iYvlBRtmOgkMo0hJnNjvufCE9ycOz7E9iTD/jRX9WGzDAXsmhtlBW0zN+V5nVwbSJe6Fhj5VaAPbhbAK593DK9/0Sm87MZq/UhYTsLzGgrMk3nlSCL94hDqmvQBmuFoKksTllvavN25c1Hg3me28Ko5nNIAd80NZTd8enmAZGkkXanZfpkJtLNMtJB3nQeh6pZmMjc0iCu3NI+rEd9uKkynMpoQ9mpkaTZzIy2b9bHRID9K/EWr9jH53dIK3cRsINkgUWgavC64iR2TGADDNtYF6ojOmRtgdoac/35idaSf17SDLxKBUpY2k7mpr7nhWBtE3j43upN3+RwJ2dvhV+983FhcK1lrQ7c0L3NTLmK5KYf9rqmGwzy4CeTPdyYZXnp2E0A7jmnTvFDHo1iAJswN69Ex8TI37gQGl1MBZc2NYm5CtW+DuZnMz9z45Ddm0Oh+flwNFvl2w1DWGwRBydzU1DHo5s/V67g+iLCfCoO5oetG7Mf6kAI/c4EbzrSCLmVpu1MMIrvmRo/F8hirNvd0rsB8zM3mMDb63NDYwudQe47bnmTSecxhIrQs6vrc+JgbCuZ4o0bulkZya20F7ZalbShZmg5K1Jqi3B71+aPf07G84NQ6NgYRTm8OtbMlrRnKz9G4btfcUADO7f71OcN5zoRhImtuXFI2ggwwrPeq3J4ogM1B7E182owVJfySKKw08eSyV6PWibsrMuaG+kRxNki9T5MMQaC3LY/FTI7a9cEE3etmrObjE+v+mpuxo+ZmnOZIwrC0udd/Q3MCBV2HxTGtD24WwLnjI/z63/9zqjOsjWHSTALEMUuj74OquUn4xBBAFH4Jy6xsuTwOvyzNbnA2C49c2sU4FXPZQNMxyP3rN41eLNfiTNXchDzD6n/Eo7LjtcoyhXq/vowowXZL08yNW5bmWoTYtpk04BFoQatlaa5z0D+kzFBuLHqLMrgx3dJyUeDH3/9gRQ7ld0uTQZOquSllaYCe/Orc0myrUIIo6gMAkqXR4l0VwM4KbhzMDT1HTRv+ESiDSE0TJXOj5SAu5maeQGqthlWza25yUeCDD1zEd7/zU/j0k9fU51JHwOED1ce4MM0EhpFewAPVcUQznXwCD7E7yZCLAi89J4ObNhzTeOf4xFrwqkWDs0aMmELdxLNJnxsqmDbkoUlYYW7CwGRuiL1cyFDAlhyxsdaX7HKNjXy7tsS2kSzN8ayOSskkBZlJrBfKVHNDsjRu3S73xcZhZ82N/LvLe1MMk7CSoONffX1uFmnMuz6IjQWaq+bGdmbbHqedsDZAfZ8bX/DmYm54nxvORiUOWZpibpQsrVBf6Vq++OwGXnpuE//x3Q+oWgvB5oc3vewMPvl9X4kTa4muCWRsB78na5YsTRQ1NTcz1ifSUCA35gAnc2MFotzgoq5tgX63GHMTyh5P+2xeDwO5H5pXtSzNZG7onRvEchvU2oAcIDkTujGIjUSfZm5MCXuFuTlGvW4mOripc0vjNTfltiaMubFlaYMoVO/rziExFeiDmw4wSqJG3eA5Us9DOwuq5sahV/ZJT/KaLJ7abilLKwpZqGwYCjgyaHW4pzQTmJe5oWvBs/2auXFpzeVX2cSTtlG3/bLBncXcJFGg7gdHXa8VzdyYsrQ4CstGdFXGwtYnZ7lp5auZm4ZW0HFQqbkhC1e75uazT13Dv33XvfjAAxcr5+h2SwvL+gWduaJnjprJNZGl2ZR2Xrrm+P8uVJMBwJibGYtI/szwZpTzJg8AUx45yWTBNM/mu951LUubPcSu1xgKuPrc0D3YMexsmzO/tukEB9eqe5kb2ldoTsLkQvTCG9YxiMJWHNNIVgnoc1NSp8D8OYe2HmdNPBu4pdEzYtbcREoiypkIs+aGDAWaBze86TBHZI21LtQ1G87LhaM6TlHUJrTIqMF1HaXZRaaCzCTUZhSKuRmYgR8tOsNQs22uuWadOXXZzI3Nyg0c9YSATgrOM29uDCODuXHJ0kJrjtsaZ530uKH9zs3chMTc6AXskDE3qnYuCg2JOUEZCgzMPjep0L2ykijE97/ldjx5dR///g/vB2AaCkg21Uw8aCm7MAIyJYcqj0snEcyAWP0u8LP5tqFAGLiks1VDAX7d6hJxOjGi5eJRKM+Vxuk4kixMysaXCQtyhgb7QkkYYm6KskVDULbt0DU3vMcN/1tb5WE/Dzcel8zN09ckcxOFATYGVdkdNxTQNTdazkgyNVuWJpkbec0Oi6lAH9x0AOr6Ow9yywa4KbRbmllzI7fpYW4aUPlU+EabsA0FfB3OXbhYFoDfNGdxMb3YLleiupqbMKhKV1ygydKuubEb1dnbB/xuabTA32cBSeyYlA2TBJYh4gMy3VMaUF3PBl+sUwdxwwpaydJMtzSaGGzGQDYxdO3HlqVFGMTkdlQGNzXZML3wMa+DKIraZ576AtCCacOajH3gv9e1TcXcrA1gGgqQxInbA7vedZ98wIU6WRpth95zUehrwf9mHqbItUgkTDJtYxoF1ffP2BfXlUeByhgeGyW48cSwNebGNnDhdS9AtXs7YGrVtVtasz43XE4FmE08OXPDH8HdBQwFfP3GGrmlRf4xnmfXqXakrt6My3FtkNkFNdrkgfGe1VHdXhRKebCfFeLW8XbNTcXu21dz0wJzs5/qbDwhspi5rf2OmRtfzc3M4MYhS8uFEbC55p8Kc8MWz/xe/dlbb8A3ffEL8VMffBgPXtiBEO5rbRsD5MK856OBzdxASb0Aq8/NDGvvYRkM0jlSHSbHNBfOmmjaX62EOjTHPV5zQ898EgVloM9kaXk9c0OmKFleIBNCzde85sYOulTd04zg5kWn1xGFAe5/ZhvX9lMcH8XOeXUYhwgC2a+n0uemtIIOA7O2s8Lc9MHNcxejuFnxNodtA9wU9BLxrJMupp1vwOSIS+cbmqj4OBGF4VyytC3VI2C+ycHFQNXX3Mif8XqBekc4soI26yNiNuBwZA42QP9fGwgM4lD1pkkcmRB5/FXtP/W5Idg1N65g1DZ6iELbClpS6vYzyQdi+xxdzwVl//a5oYCSpc1mbqghpx2UFMWMINvqc7PWkLnxWUEvwtxwQwGuuQ6CQEkkbMxTczNKItUczobd5yYXeiFg1g00Z24Sx/NI4MyNLc8guAI3vvDcHMa46fganmmj5iYrWHBjMTdWdp+DfkbacoBkafXMDQUGPHAbJaFKNOhFt9XnZkJZ2+bjorfPTZPgRjE3DlkaWxzazI1rwWPL/jjWypobMhSgbDXADAUs5oYaOYaBtqN2MjfMFWoYR8YcpmtuOHNTZRxnFZ+7sDGIjACA3Be5zNyWXm+Ps06c0gBKJLpNUryGAuX/bzBkaWUGPhVqXFc1N+X/f/z9D+J3PvV0peaGS6TtmstveuMLIQrgwfM73sDDydxwFYJltESMvUuWJkRRez+JMadF9iiJnG5prqQHHXtdvyJXE08yNKHxIw5DlQTl/W2AMrhxsJBkyJEKofrJ8UTq7qTK3GjjEK0+oP1zjJIILz27ic89vYVr+5lTkgbI959MQnKr5oZqcOzkNVlbUyDcMzfPYTR1puLw0aiz4OtzA7iL2AEt36qbD0iqQC+sPeHOYyiwPU6NxXBT8KJgAjmKuGtu5NemVtC2WxrvvOySvZlNPN01N9Svwe71YE/KKVsE0e9SK7BQzE1dzQ1zYqGi64osLQ4qbCItkO0ggbI5NsgCdt8jS4vCwHgGXXD1D8pFA1maUXPTVJamf68MBTz1RLOgGQw9Oa8N9HvnMmqYh0mpk6XZ3dMzoQtpeb3UPE2AZ9XcKFmagzkFuHmBWz61OYrxvBOj1mRpdDx2bUiTmhueZeRW5gCcjXV9hgKKuVHNJc0EzyLMDe/LZRw7l6X5am4894Z+RtukDudaslvdlpaluZmbvWmmawTCKnND8jK7qDwM6mtuNozgJjT2rxsq64Wha96ZhyElrCt2XT4LZHxB0h6gNBTIeXCTdtLAEzAZFxs+dyyXLM1gbnKaj0xZ2s99+FH8yp2Pq/fgmO2WZiXYAB0A7ZbPQV1wowICq/E3JfnMJp6Betdsc4B65kbOAdR7aG1QrZGVMko/w8SfPRt8sV8UhS68j8zzIfl6lbnJKywgoFm0opABEDE5vImnfVy2LM2uD+Z49c3H8dmnruHafuoNbgDtgJhRzY11XrbNvZKllce2c0jsoPvgpgMsLEubs8cNoLNuXJY2q+ZGSRTq5EDl20MaWf7Zed3StvYX0yu7NP/kSuTKWBqytIbMDaAXylqW5u+ETZjF3Oh9hJUCPcDy9Vc1N6Z9paTtg1q3NHJESviii12vrKTn7YA7YwMxBw3kNohOp22MBjpYvbI3xebQTYPb27AZMSos9WFIfW5Uzc0yhgILBjdMpqCsQMv3beipr2vCjhLWkkjpsKvbMesBhNDPPg+ItGXykjU3LJjgTSA5tO10VUYESObmeSdGeGZrrBbwi4LX3NBYV5Gl1bilGcGN5ZbmugT0PNoM6kjV3JTsURg4mZtFDAXsZ2QeK2hnzY0wmRtDllZrKOBgbpJI2SATC0Bjxw418Uw8bmkhc7hzMTeWLG1gjX2AWa9Q55Y2j9yU5HAUkJ7fniCJAiNQiAIXc9ONLE0xLi5jEo+E3GkFHemaGxpLhpYsbWeS4Zlr+7rmxupzY9d9AjqhtDPJDckjh231b4+1ijGY6t9ruVZQ6XNTtzah60U9V9aSqLIecVlBA/oZrzUUYPWhvAee7UxKRg2KsSm/Tpm0F9CBCBn+ADKQoQApY8mqNYu5qQSNNeP8n7n5OJ7dmuDhizvOBp6EUXkfVC0RT6aUwSYf23pZWg8F25mqCdIFJTNEvZpuaTrL60KThRcNVvTC2vKnuYKbcbrQxOCsualhbnR2MlAZylrmhs6RghsabEN3nxtOfdsLUc7c0LULAqjBw74XpizN1PZyDGPd4NE34MdhoJ4Dvi/K2MZhWMqnhFps0vk5mRvP5DXJhJKgGczN7rRWkqa3UdWWF8UMYwsyFFA1N4swN/p6LGsosM+CO8CfyNBNeWcPsbzI0wadBi1c8kIHQa6amyZuaS55IGGS5ZUgwg7M6fmy+9wQjo1inDs2xDQT2NpfbiLkixS7OL1eliZ/RxIKYiBIVw7UO40Z/abiSDXU1UwEnMzNPIYCvmbK9ljrAjeYcJ0Dl9jmrFGxu27PrGniWBtESlZMBdHaLU3KaEK2L4C7pQWVQNQ+B648CFh/IZ6sAThzY17fJok6G5QgIebp/NYEZzeHxrWRjW7132ytgrmp6ZdVcdQjWZrHCtrlllYUBXYnGZ65Nq72ueFzkLWvTVZInnkkY/Q8TlmQZN/zEevnlQvz/eVKBjIb8KFJcDOdYShQX3Oj61w4I24wi2UNDmfJpqUBk+wvFFa2xwP4/VQaN3Bn1r1pbthA8+NVQWNh/pyD3Ggfv7xfz9wMIiXX5TU38lhLGT1nbipW0H1w85zFMI7mZm6kDfACsjSmSSZonWY9c1PvlmYyN3xAk0Wqzc9va5zWZhJ84IMMgZib+pqb6gLIvX09GfO/SWK3G1yTmhveC0F1M3cEg3ww525pifUMjJIQe2lWbsd9HtxSk0vgVB1GHCj3Ft3grXCeR+YxFLjjpWeQCYH/8icPgfz5ec0NbzzmA89S8XOfJUuTVtAlc2PJKADgqav7+AyzRea/H5U9EfS+lghuCsZcEXMTu5kbOs8mzA0ttmxbbkAHEpq50S57piyNAo7ZYwi5Dbkgs45mfYk9jvhqbgibw1j3U5gzyVM5nrxac0NrjFpDgchkbm7YGGA/lYYCuru4eV7cGdLsN1V1S7PfaQo055Olya/2I2IsNjzBqlr0OF0jC8NQRcpr3PsCZD0d4GFuBnrhqJp4qj43uVE3E1oLsTCYbexCi0x6vnVgbQa0g9jtljaPHJPAmQhA9gY5e9w0u4kCHUiluXTE6sxQwAoMOGhOswMO+v/JdbcVtKq5iSIksVyEy94wBbbGGa7umXWSmrkRlTFE1hfKRa2vblHVzmRMlmZ9bm0QKjl3URRKFm8nW2YaCiR0/8rgZhBVaoBTq+5FH6fcbm3NjVKMmMwND5akRDM0FvqTNEeay3fNdt6j86TndDzNy21q1mpvmldqbhIrwWvXB3NwN9q64GaUhKzmxhzrpLvrDLc0T33o9YY+uOkAsmHinIYCnlqHWXAyN6H5QtgQnoyhsV2SpZXnwV8mSVs2P8at/WyhrJft8Q7oF8sVXHENe1O3NEC+vOZCze2WZsrSqjU3gyg0emSY2VO/LM0wFHAwNyR58d0v3r2drCYBFtyEWlZDTBzJZ+zz8LEbf/7lZ/F//83XIBOFyi5RdurqXlprrUlYRJYm+9xohzBuBV0UBX79rifwFW/7Y/z9X7jL+DvKXG4OYzXR+2yuZ0EzN8wKmzE3zpobj5zEBarfcTM3emFJ/0/ZZEhQfW4anN+QBXw2eM2NMlIon/v//oknsT1OGUtUTagAUvKhFlpzJnlspFm1z43NFDhrbsrfUXb35HqCNC+wM8nVgs6uSaRXNGLML0CyNJu5MaUbtMiZxShyzHLCkt+7p2gan111lVXmpt4tTQWPjsUgzyQnlUxz5uymnrLAfpY8mN7ngXUMus+Nvvd2Dy9gMUMBxdxMNHNzo9WzjpvAbCtDnG6YG5q7Xc+O7eTJjw8wDQW4rTJnbih44AvxRy/tAXD0uXGMkUEQYGMQY2eSeQOPKAxU3xfAPY+sceaGbSexgxtRfz81c5Oq7doJGJ9bGgVuzayguZNqaAR9xO4Sq6lMKlStE3OvpSAu1tvYT3P1TNM+xmlVlhapBK+ew2j/Nk5tDHBz6Ug7s+Zmmqv+PS7mRljMzTAOS4lj0MvSnstYxFCA3DPmBTXcM2puZsrS5NfamhsyFMiqmYI4mo+52V5QluYqaFZuaU4raPk1DALN3NScIw06kyw3zo/sh22YTTyrzA1NUmqiZt3Mfb1C+HZtQwFATny6iac/ixtH5mKGtkfnQ4uzcWYGh/aEWld0/ze+6Ba8/Zteh7/9phfLY2PPXDNZWrXfAmXK/X8jF+JalkY1Nzl+8WOP4Z/+2icxzUWlazJNbsM4MtzSogUSCNxQgDTjOsBzS1CJkWpSC7CW1DE3ZXCj3mkd3OynrM+Nw57ZB2mC4B6fbKcfkgI9c22Mf/Ird+N3PvW0k5XSgYa85vbztijS0hAD4AwD7YsCzCprSAt2ztwAwNW9qWL/vN3uQxgSqVESKabO1+dmGSto+xkxCrE9z4+uR3QlYfQ2qV+Lz5kNYAGEY192cMPf4d2JydzQMdHYSAYn8nfO01Djhj128vEMIObGUXOzgBU0jSGUKDu/Pca549XghnZFi+iuam7oOXYFN77g7fkn13Bmc2AEN0EQYBCHmOQC01wrCcj5dGtcDW6UWxpbPLuSrBvDSDXp9V3rhDnpuWz3uSxNFPo5H7E5js657naOXMyNs+bGn/RoIkvL2XsTh4HZ16usuaHi+uNrMnlCY7ivZxNtY2+alVI3WSNbFIWbuVEJA3kcPoMJwqtvPgFgFnMj5yxqGl6puXExN6Vh0cYw7mVpz2WMkhDjOTJ4AGXt578deuKvMjfeJp5Kx1uzXWalCpgvk01bzsKiDdBsj3dA24+6a25oItADZ93ikpyIJpnZcEwWYPqzaFS/wjFOtZzHdptyMTeGW5qinKs64WEc1TbxBPRAS5/hzccAmQ21rTh9srRZdSl/9fab8I//0suM8wSaBjfVWo9ZExkZCtA10lbQBT75+FWc2RzirV/8okohd5rp5qWGW9oysjTBZGmJrhXwMTdN32c6Jx6sEGzmRrDmrwZz46iD8aFWlpZXbUwzUahncKfU3QNmjQY965QJbou5mfKaG5YsAIAX3LCGt/3N1+ArXn1j5e+iUBpt7CjmRi4Cr+xNMUpCIzNPsOsbaD/SLc20O5ayNP23ylCgBbc0myV3IYnMRQ+HEIVK3MShdP2iU3U9/ipodDyvI7bYkplnHWBIdycXc6PHYR0Mut8FzdxE5XlZzA1vgOi4ZxTUzxPckJHB3jTDJMtxZS/FuWOWLC3UCTyqGzuYmhv51R6Tv+a1N+Mj/+LNFenVMJLjkVFzU95f6kcGAI9c2kUQaDOINJMLbLIHtrExjLE7zWuDmwGrnXHJ10aJrh8VQsvSbtgYqFpOoFmfG4DX3FT73KSZx1CgiSyNGQrwRA4fW6n+jAIsCibo/4YsjbulEXMzzZUpASDn4f20WnNj97OapQh49c3HjeNxgTM3kVVzk0QhwhCGMoez+ZvD+NAwN928rc9xLNrnZhHmhiYFlxW0r+bGN6lyxEqWZhbby98FjfvcFEWBrf0FmRuHvK6+z438GgSBCtzqFrN0vSepWWfic5OirMn6oLo4nGS5WvAOrAna7nYNmHapmmmp2nCSPlael/s8eM1NwqQbtA8uSxtbsrQKc5O7JzcX+DPXlSyNMsX0dxvMLe3qXoozmwMps7IWlTLjHxrdv2dNmj7w55DuOy3eR0mErTKzy0FNeZuAJjRihTh0QB2pY3DJ0pRUrMG9cwXnhEkqKmOJYOctJ8UykGL7oveMZEraAWrJmpuMN/EsZWnlvoIgwFted4v3b5NQLz7ICevKboqbToxqWQBtQxxiDIFRHCpmQQVYgSndUIYCc/W5gdoWxzw1N64kD2dfqSdZ0UCW5trXOltsDVimWQhZnH6C1XzYxc8Ra+LpG4c3rJob1UA2NO85MTeU5abi/0UMBWguurw7VT1ubrSYmzDQ0mtibrps4glAsS0cVGNhJ+k4K8YxTEJVX0PbpvnoCgsgnrq6j1EcIY5kU8dM6ASSi8HbLDP2dXWLMWP1XK6boyTCtTLAEmwsvmFjiCeu7KnPzexzYwc3g7Da5yYvPM199SLdB54c5okcQ5ZWNvGk8YWeKXpWDEMBVjdGSQkpS9OsiWahzOOqGAqUQaEvaUumAk0MBVzmKSQlNZpgs4TX//plt+Hmk2vebV9P6JmbDkCytHlsUBeuuSn/hr9M9DMvc9OAyh8oWVrVhpgXrc8C+akvZihgvthA05ob3ujPv306/6lVRMnpdY5MBTdxRdbDF4V2E8Q4DCoN2uicuF6YeklwDGMdENS5pVHdAS+6VQveWPegoaCbrt+8zA3HvMwNn/wIophR+2W7pQ0p0yiDmxNridKUF4ZOWF5LvpDPF2yUyw0FuHEEfXWxEy6JoQ+UveZNOQlk/WkyN/JnLmvvRsxN4m48CqDi9ENBAF3DvbJoln5H0HIP+Z7bwfSiSJl2nsakptc1jgIW3GhZ2iiJnM5btnQrKh2S4kg38eTuX7rIt1DnOZcszcOg89Pzmcy4mh8SuF2vblTsT2ip4NFjKEAg5y1AMoU7k0zZKvNjpWMKjNpH52moZAU9c3agxeWOrlpSJSWcY+48sznAyfUE9z2zjfNlcGMzNzyBt9Vxzc2AZe9tzJuQGZTjpTYU0Pfsyp5OwohCSwGlOyiTYDlu1sZABzd1Dn507+UzaB9bYKgU6Fk8szkvc6NlaVToX7Wr99TchJSEadbEU0tVTatyCgpUcLNm9oBxMjeRTkLupzmoESgAZbfuMxTgDUXrAvkve9kZ/M033II33naD9zPSOVLX3NjGME5DgfI4v/3LbsNf/oLnebd9PaEPbjrA2iCCKNyDlQ/pom5papHFCtiUZtRXczObudGyNKJl9e9ckg4flqH0qYeLwdyUg4mrkJbrk7l8xAfF3Fg1N7EneMtVcBNVGA/ZuMuUVvDsaaXmRrl5ab0w+c5z8HoC34AfhSZzQwtd3vtEGQpk9DuSpdl9bkTjhQIf7BeWpRVFrTxyEMtrR4tGJUvLBa7uT3FyPVFNU/lzQpMbZ258PXxmgRsKqP4R5cJglLglXvMEiXVW0JUmnrnHUMAhFfNhGEfGYoaDT2SAftenjLnJ1b745+T31BSwLeYmzYtKsqBp8TgvfiXmZncqG+y5mBtbzx6HgZJzEiur7KiZoQAPSucxFPAx6AEbv2b1uXFaQReFEYTJPje07eq26JxIvsRRNRTQi61dZs7Aj0lbQeugwytLG5pSXttpUh9byIqrHcHNHMxNEAR41fOO456nt3B+SwY3Zy1DAXLDK4pCZePrsuHLoE6WNm/jYRrvjD435TUkhzR6v1UdWTln6Pmiur+NYYydSY688Ns0c2beNdbypChPap0ugxt6n2Y28UyIuUnVM1kx7PG4pdG1mJe54bUpcRiUNXl6biHmhgJhcz2mmRvaxjiVsmlKSm6Ndf2QeSzmMz/r2mwOY/zQ170GpzeH3s+MkkjVzUgDAZNlqhgKeK7l9Y7Dd8SHAM8rbSWfnqNDt6y3mD+rrJt4mlkFYLYVdL1Nss4wAJYV9ByytGWLMRMrMCDmJnVM6vQjwy2tzlCATcaG7M4hnwJYcMMcuAjjVGhZWmwuhJw1N+VEMkoixaKkjgZq/L76mmTy4IYKYQULCJJIuz2pmhuPLG2eRfmQLXyayNIGC8nS5HHvldaZvFHd1b0Up9YHSn7As+Y0IA9YzY0oFnRLY4YCPCMKyPvjkqAuUnPj2g69q8otrSgwzRw1N1lVKuZDXeBhT2T07NJn96aZkyVSi4aRWSDeBnOje5+YC99Z4AW/vNmhZm7csjQdWITqGbdrbqJQf57uQxAs1ufG6T4V0OLefT+Vo5NrHGRZcWKoihr5lpbRVvc1soMbltWWzI0e17nLFJ1XzK6XC7YVdKKCIX0P6BhrmZs53+tX3XQc9z27jaev7QNA1VBAyd60ZKjJGLcIhjXBjZizTpDGOx3cROq9IXbktjMb8neJfp84O8udVwncUMD3/g1inbzKWd0XQTp5lswOS2rdsDFEJgol75Vzgv8c6XrtjDOvRbjPUICuRSMr6ErNjcku8uQOKVNovWPULSrmJjT+hjM33PnNOBalwmGGDwvMYRxrg0ito6LINhQI3YYCfXDTA4DSJD51db/x37iaXjXBrWc2cPOJEV58dkP9bJahABE6dbtTsjSHocA8TTxpwFpElkb75bbMlCWtMxQIQh0INAngppnJmPBeDhwquHFk6zlzM0/NDXd6yYWrz81s5sZu4gnIhRMFt4M4YDKhelnaPJlCg7lpwMzFUbXPzSxZ2kAFN9Jdhmc5r+6lOLGeVHosAHpyG8aRbiwn6pvD+UDZZ1Eu8vlE52dumtfcUF3DXgO3NMFqbvYZY+BqrOmDCm4cgcckyyuGArko1Gf3U13/ZLvsAHqxOmI9N5YBb+I5ryyNy1VOGf1A3Auiiiwt1C6DKrhhRiX0+V2mu19IluZ4/lXNoPedL4Ndj2U9Z66zvPA6swEwWF8bVVlamRDKq7I0Og9XE0+/FbTJ9Okgx0wQDeJQHbuTuZk7uDmGcSrwp49cRhQGOL1hBje8gTRnQbrAwJGcIfBml01A7pC0LaPmppSlvfTcJgD9jhKjTsX+LvfBDVZzUzcPmVbQYeX3BgPBZGmAbAYNyPVJE1nablmUb69HRMm41DXxrAtUVZ2LVXOjGstakkmABzfE3DBZmmJuImN8ThiTc80jS7MD+nzBOYyDB1Bk/cz/b/fwmuR9cNOjxC2nZHDz5JXmwU0q3O4es3DzyTV86F+8GS86zYKbhjU3TTLmygqafdbVlBIAzm+NcccPvAcPXdhRPyNZ2vEF9cp8QAS0W5qrD41uVFffGZtAl3uSmf1leC8HDl1zU23c6GRuampuaPtrSaRrZJx9brh213cemt7mmVVTllZm0iuytMWZmyQKlMxls1ETT93dnDArS0fXcs9yl7m2n2KaC5xcGzgXB7QoHkS6JsbXgG4W6NnPyoUOvyde5maOZIV2S3MUFKsAVTM3dX1uXDpzG3ZDV33MQmrxjR4NgSEL3J9mTm2+qrmxmJt5pLkupMxoxe5zMwv8XTKCG2JucndwwyVRtNDThe6aERYWc3NyPam49tWhrrEmHzvqzs01xvOFo+5z49+XDiSqzw5fbA2s9w8wkxp2jWQQyFqNjUGEc1aTTMKmZUBhS3pVYOtjbhawggZ0w8M/+fxFnNkcVP4+DPS+VL+wBebnJlA1N45kQ+5pquzdViwNBQy3tHL7JEujROiQSS2zvFDjj73ABkpDgWm9oQCXHbuCID6vCmYKQYHlpR15fPkMNp8zS4NSRkUSQkA7Rzrd0hoYCgRBoBhPXnNjMzYGc1O+B9uOmhs9flmNQJnigtZJPlkaje/zzM8+mMGNVXMTBcbYVhTlnNfRs98lDt8RHwLceHyEIACenIO5maWlnAezam5meaUD+qUi5oYvKHzMzSOX9vDk1X088P9v783jLbuus8Bvn+ne++aaSyWVZM2yZFuDJyUeIssjiYkJBMdxSIhj7IZ2CBkIhGbu7tBAQ9wQEroDZAIy/aDd0BAIkARIB4jjxA6ecKzgQVIkVUmqqldV793hDP3HOWvvdfbZ595z7xnuu7f29/vp91T33Xfms/de6/vWty6w4KYmc6M3bpvulkZBmwpcpgc3agGW6y1hKHwHmFuaQZaWr7nJB1bcVpSgZGkOc0sz22cSygb8V99+HA/fegwAZ+1Uht1nBdG6LM3M3FQbFoRQMrHNoErNjYG5mTJZ0rEDKrih/ZHL0bENXwZ2OVkaGQpk7kHpucVzSTwIeUOBfBaLDAu4mcFvPXkZ/+Yzz+H8sY1K2+95qWPRl54/KJiQSOaGgpscc2MyFFhclsazvQTXFZKxAtL7IG2nDczNtsbczOsaqSNi8j76WfUe8oXE3oYaf8gKupS5kZKoInPjsXdbZ272NoKFmBvTGEUflTFx09h5nt0lCfG0xs1K9mdgbvw8c0P7pYXypqHmhjfxHAQufvX7Hsc7X36T8TyIudHd0ng/Ifq9y8Y2fq5l5zUNd5/ZgucIXB2GBTMBvv+IWa8vIhuvgqnMzQKGAmQFTc5X9AxdOhhjq+fhpt00+aozNxSkm4KbzcDDcBJn5jslwY3Ha26KQZnH5sG8W1rG3FxLx/R4xlqIJ5f4MyldQqcwbcTAzGLhKODL1dxojA2/DruDcrc0hz3D/BnyXLVNWidtaPMot6UGFq8b5eiz4JBqbOS/HZEb2yZacm2VYK2gW0DgOTi93ZtLlpYubJt5gPR+AzpoPqziljY0MDemhQHA6jjYIE2FcovW3HD5SBwncgCeZgXtCCEnu+l21+nvRpMoN0nzXg4c9NlmZijALUlNzI0MckQxuBnL4IYxN1Gx11GeuTGfy1/5upfL/+eFxirjKAqZdPqd7vo2b2YoyBb3VWRppYYC02RpkrkJJWXuuwIXrqb1bHsbvsw48qz5OJNXcebGJJWoArqmcSbPyjE3vjI46HkuPv/cVXzLj34UxzZ9fPgbHqq0fSEE3vHAWfzsx57ExWsjfPjdD2E3W4xT0sNlmWRivw4yR0Yh1PNatc8NUAxsZbZX04UTYwWkwU1okKXpzfGaY27iXOYTmMMtjRYVrpPL1PYyeYie/NFthT1H9YfqaxbFjkhr26j5HpAG2pMob1U8DdMYdL3mpHhuxNBON7OQzM2UIOD88Q3sDnxs94pjtF5zoztvbWnjJqDuOe1rj7FmOmTNjdbnhs7/3jPbuP+mnVz9jqnmZt5sds9zceepLXzuuasFG2hALUhpHE1Z6paDm5I+N3PJ0nwH17P+PdJlkO7Z9UkW3PTldwFyB1W9rMyyNNVotGy8DlhSMEqKx81bLMQxCrK0568r5mbq2oSzH64jZcNpnSNyST0driOw1fNm3ksa93jNDUnGp9fcFGVpdJ7UUFXug71PZW5pOkNrcqGbF7rUPXdMTir/pFfMlPBaFazeEa8Ibt4bzMncmAvgFgHXCxv3RbUpU3Y3rYmna5BZAcqnn9Pr9NIuaqOZOpeR3j/r/us6xnOL2XlVk6WpjH8+e6G6BnPQYog7dhGmuaXp7BOQl6XxBl364rRKzQ0HBUeTKJEBle866GldsGn/erbQ5Ng2DXTO1d3SdFnadJkRvRPXR1FuUnkuczna2wiMtriTKEGgMTeR4fpWQU6WFsU52Zay2E738ZP/+UsYhzF+6o88irO7ZimOCT/03kfw5995P37pv13Az37sy/JzqoHKLbZCdT50PeWEPo+hwKQkuNGkkMRYpecZqUZyuTEhk3s03MST37NAe69mgd6Fnu/k5B6zmBs+dijGxsk5JvEkAhWc72ULnLKkkg7plmY4H9kfpkyWNoW5iRPO3KRSIJ740fG2+8/gN/7cWwqSGKBYc8NZACA/rptkabNAbmm9QmIo/fn7Hr4ZP/8n3pCdC2Wx69fcAGndDQCcMjA3NEyo4Ka9pdI0Q4FoTraZrKDHYZwLXoD0nm32XJzJJIL0jtIcO5SytOJYngtiS59JLksr1hzmam4S1cSTzD5eJFnaDDZfCMW8mJibaTLC45uBPP9poPpQE3NjYjolczPKDAXc4rydGnKov/EdVcejGpKWuKUx5qZuEnygNd7l7qieK2RCBDAnvFYFq3fEK4Jze4NODAVMmG0okM9QGreh6YDzsrRiMS5gljrtDycIPMeYDaoCvgihRnk7A98YfHBrVVkUXLGJZ27Q0Vx/CNwKGlDnGWWMUlnNjck6O+eWxgYufXFapebGdE5pIazKYNExkbxIMTeL19zw46vWxNPQ5yaeUXOTPYeH4yhXXHzxGgU3ylCAP3eUbQ1cV7JTsybNMuiGAnzxryy2031cH4c4sRXg/PFqkjSC4wh82+teAkD1SkiPOc4tqnmfG0BJ0+btc8OPmTAyyDk8x0EUKUOBlLkpZrJ15sbNJu5hDUOBJElyMgw9aTAL9B73fVdK/+jfRrc0TZb2pvtO4avuOSV/TxbS/BiiRGW8iaGoKk0ra+KZbj9/DjocR8ARZkdMc80NnVtxW2lDSPNSIG8FrbK8VzLmhstR6T7xJp6zcPvJTQSuI9mEaffYlLSbJrebBaq7Ob1dZG5cl8tA69c5TEOThgLSCpr1efFZQLrV9wvMDbmDTpOlbbDxvdQK2lM1lVFc/J7nOnKcShg747sO9jZ8vHA9k6VVkOLxGi3dIpzWIaZ350++/V78xLe9Zuq2gSxQi/O9f/TaNB5kbGs1N7wuSPa58ZwC6yTfpywJXKi50ZmbBRtRc0yruXGdfJ8blfBabP22TFhZWku4eW+Af/Pp59LFW4WHcVFDAROmSRaAatkuGhhocZIzFBDmmpuRDG7Ugmb/MFxYkkbHQfs6yMwEdgYenr82yhxR1HEZZWkVmBu95kYW5ccxAhb/8yaeQBoYPD08xHf97CdwdRji3rPpZCnd0phG12RVCSjmJkkSY91VruamwnPEde9clqZLH2giLTA3cTJXQzyaZLbr9LmpIEu7Pg5zExrps/cGAZ7xUolarqty1tk+x9zUtIIOTbI0jQXRfz8PKCPJgzRa3CimIH+eB5MQu/ClJXCV8yuTpY1MzI2TNxSg5m/6cyprbvp5+Vcd5oZeGTqnge/iTfeewsPn9yr9Pf1dGtgI2byu1C1Nk6V979vvy/1+EHhyvKFnNo6VyQnV9UzCGChvM1HYnyng8GYwN0C2WCypuZFBWOb8OE2WNg2uI+SCOe0blWduzIYC5YyUjgfO7eKz/8s7crU1fFv5Y8kvYvn/L8LIyuDGIEtTVtBJrkN7G5jWxHPexezJrR6evHQAfIG3JFBs/lbPTXuDeQ6ruUmfEQpudPYAyBvGlAWtAaupNDI3bt4trcf6Kh3fDJShQDzb/rrvu9gfhkajCRofTfdsp+9XWo8MAgfDcZ6l9tl8TucDpNePrpk0FODSXsY850xYGJOjam7MbmnKdKjh4EarufEdB66jkgYmNn9VYIOblnDzsQHGUYznr4+MBYs6ogazQ672QuhQ8q0pi0pNlsYnYJPMClCD81hjbqh77yJIraA15qav6hH4OCzPC1xaUr5tGliKsrSqzE2EP/ITH8OTLx7gb/zBB/EHHrkZQFE+YwoGaduDIK25KStaNWl3p8Fn2U0uSyPNui5La6LmBqjK3BRd6GbL0hRzo/T5jlz4UhNPIH+/JlEMP8uUTaK05iCMFrSCdvILHVPNDQX0ozBamKUEVA0TgRYJyr0pzjnOHTDmhprLzUK/hLkxFeJ6TuqcQ8/JcJLW3OgMo2qOpxYOPdZjaBHQ88ttjX/sfbOzruqY0mOk+7ERuBnD6sJ1irLdWUmfv/J1L5OulDSu5JibTJpSlbkpa+IJqPF2mgSFS3Y54gQ55jrvljb/8z/wXdnrgo5HytLY/eYy33Rf1bbPr3egZcc5ptXcLHJer7ztGL765WfxhrtOFX5Huw8zGWibsjQyZmmiied3vuVufPzLl/BbT12Rrmh6s2UhBL7x1efxypccB0DPUSJZYJM8kTN0pYYCLHllst3nST593D+52cPz0lDAHPBzcBmjbjTB+7stis2A3OGUeYqnMcj0s++5ch6UhgIlzA2fW7l7Gsn3+950Wdq87nkm9IO8ZE6vp+ZKEyo1sMGNhcS5Xep1M6wU3EwWrAcwYVbNTaUmnlo2SX8Byrqb878B0kxGHeYmlcCprDGg9K2TKM4tJOmQ0pobOtbyl5JPiHwRQQOOvnCgTCsN9IfjCL/93FV86E134etfeYv6ey37aAoGaRLoZW5pJnvd9Pez3dI4eHaT+r5wORfdIylLY/dKlwFVQZDJfUxSBh2eKwoLv1lW0HQvro9DnHPTd4oW330/lTvSd/jiYByl9pU0yYyjeGEbTV5fMZrks7hUaE41N8MazA2Qnhu/RrS40ZmbVOKnFiSmeq3yfZjrYYxuaU6+wd/BODRaltOzuckyvH3frdXE02RcMA+ULC09H1q0pTU3RdaD/AXKxsW3PXBW/j+3Ck77bQgZ4JsWqSbIYMokSxNq7CiDiREGyKlKfYe7pS2y3hv4Lq4cTnI1A5dJltbL6/cBZeyxSMAxnbnJL2IBNZct8oxs9jz88De90vg7GgOpr1SbwQ2QH5s5Zsl2dextBPhHf+S1+MBPfkwqDHzGkNAz+pff9TL5mZcFJdOsoHnyquy+8ubXJtt9Xsuqj/sntgLpsholxeSJDu5MWmBusnmvTp0IJUJ4Q1q91oZ+9nxXHo+JuVES02ITT/r31WGIvu8YA0IAOcarWStoISWucZKONw6zgtabVq8SbHDTEm5mvW4eqiCjSDOvXcnS0p/TmAApSzMZChjcvwAe3HBZ2mRhG2ggHxjIZnkDxdxwJFmRohAqgz295obLb/L7BIrMV8TYFgB46tIh4gTSWpOgZx9dp2iAMIliCAH0MmmJyV4X0C0lS0+FnZNaANA2pWsOWzjzn+TupMuAqqDnOdgKZrvP0HEsKksbsroomhD2BkHuOzlDgTDJWUePJvHctqoE+pMwq7nZ03qmAOqZH07qMTe6lIskRnQM1Odmd+Dj+WtjGfBPoriSmUC6D7MMZiQNO/KZvSiO5XfjJJVh6QHwXae3cP74INdvqz5zYw74q4Leb8qG0qTe86jmxpy8qLI77qB3MAqx2fOMz+E06DU+pu1Pexd5x3eOtAmiYo+jKKnE1pdhI3AhRHosvDgdyMvS6DwUczP/vqY54pmYm5AtPpuEZObiBBNN/twG0rHZ0OdqgQLy7b6Pn/7Ao7KPEl9Qm+TDgevgYBzKsURnD4BqhgK+y5QBBsaJL9TjJC89O74ZyCaeVWojuaGAbjQhmZsaSSbetDQ9NyUp02tu+r7DmJswVUnw4Ia7pfHaXk8FZvvDidHIQa+tW7RulEOvuaGf42wNmmNuWm5g2yZW74hXBOf2iLmpZiowT+Z1FmYaCkzRehNooTQ0GAq4jrJB5SiTpS3qlAbks5M0+FLDrELmlS2UaUCZtlDRHdIIdO76IoU38QSAL75wHQBkgab8e525MWRYx1k2UDduWKTPDYfHBnrKoNI+uPSBBsskUXIuXQZUBYHnVJKkpceWysny3aSny1dyBZiOmtAAVePAu6YTUlmaUMFHFC3cS0oIIR0CR1oTT2JuZM1NGNeWpenMjec4uWMIo0QG+LLvUzQHc1MmS2NsIoEmOt0kRF/svfSmHfzKn3pc9qygc6ljBb2ozS+BGwoAac1M+u/8BK7vrxpDmi20k5S52Qw8+axWl6Uh21/59qey6yUMehrEZ9/J6hzqFN4TO0rNDYGUuQlc1T+LjgdQ4+ZiwQ1JfqYxNwZDgYaDGzr2LmRpAKbK0hY5NyGUwyJPepjGanpGDsdm9kD/u7LjCViwbaqb4Q2mdcOBE1s9XDoYS/OLeQwFdKUKrzVdFMTc5Gtu8s+mblgCpI6uOsuR73OTn894U1xTrROQMWKxChrrrhO57NDVkgllhgJtP/9tYPWOeEWw0/ew1fMq20GHTdbczJKlVZjEnUwKUyZLM23f6JZW01AgV3OTMTckSzPWb2SHSR3Jp/VY4INELtCRjbNMwZNaLH3x+TS40S1/qZvvtJqbMLMqpu8QQzatz001K2h1b/Q6HpMsDVCLsUUWkz3PzUlTpoHkEXzfs7pR5zo9a5MKBTdyUanJ0lILbPW7Oo1y3ayXDNUeECh4GjLmpk6WK13kqKAjVxwuVHE/vQP03KRSsarMzTx9bkTmvMelppNKE2wqS8sHUM/tD/Gpp6/If//wv38C3/8vP2P8+0WCbQ5KWND9GPj07+luaVX2pwwF0pqbjUDJI0kWMwvRFHkwbX/aosJzhNF2mi8sKYiTkrtFam4CV75Hqtv9pPDeSzOTcHbyrAz0bpmksXQ/8zU39LtmgxvaF7kTtl1zUCpLS+r3NeGyNFM/stTCOcHhJDKyB0Beflj26nOrf5PtPlcV6HK7k1sBkgQywJn1nNIYFhjc0qShQC1ZmoeDcZSruVGGAnkGp+/nXdB4coj+FiBZWn6dQddoOIlLpd1+xr4CzTR77/vFhAT/SclrwPa5sTBACDFXr5t5FiezoJiHBP/piefxTX//vxQWlMDsic53hZSq6H1u0mPW2QhDn5uahgJceiGZGwpuNElGkijZxa0nNvDv/+RjeO3tx0u3bTIRoH2atk9UOy2WvvjCAQBVX0WgyURaRxoWUpOs07O0o84WtHq2iQ9EVdYlaqBXsjQ6jsBzMIqKwc1oouo20m1UHzzf/arzeP/r76j0XVX4n6/zmRbc8OvBzwNQAaxJDkTuTryZ5CiMF57w0gGfmJtin5ummJuen1/khExj7ThqsbUrmRuSpSXwK963efrcqJobFaRcHYaVpDK68xsA/J1fegIf/MmPyX//6hPP41996lnj39dlbjyNudnQmJtZfW6mIcfcjCJs9DzJ2JrkRSZMY4o8LaNqgucW5a4yceWohRhnbhZRtAx8V54bl6XpC2V6JkY1mJuAjZk6zH1uFt/XNORkaS1bQQPlLGcTHel5gGzqR+ZnLmcH46iUPRj4rgxG3JIx1HNFrgdXQZbGkoY6O0OM7wvX0uBmFlvFDQV0uWITbEPK3IS5mhtlKJAPCPqeC8cRhaapBM7c6E08+XdNRg60b15zs0iCgqOvMfOASoiTe1rRCnr1QgVbc9Mizu3155KlVV2czIJiVmL8+hcv4VefeAHPXB7i1hNp7w19AiyD7zjGmhvec4NDLfBUFnscxjUNBVRvFJNbGkeiFSm+5OQmpoFPWPxa0H0Yh8XFTxrcpIPQl188wMB3C8Eb1Szk7ViLwQ25mAFK/qcvGud2S8vJ0pReOD0utXDmjluyX88CBdzveNnZ2V/K4BkWJ3EyQx7JaXzJQKXXV8nSDDU3WbaV98l54drI2NOiCrg8i2fm+i0wN3yRE7NFAhXkTtg7lXNLq8zcmGVpJitoLscj7A8nRl1+YT9ZITrH/nCS++xwHOG5/aHRMr9uPQU9Fz3NUKCMuYkrJn34MUVxguujEJuByxjEaszNNLc03qemDHxsJOiJK2KN68i3BoGrFnQuJWPinIMWwJmbBgwFDPSAySinThPPaeCGEcQCt4kyWVocJ6VMSVXMCm7IUvxwHJUusIUQ2Aw8XB2FU6yg87b7BVkaS4pGWZ0n4cRmOi6/cG1UqMcxgcvSlIQwn7irsyBPa24iZvTDm3jmk2w0B5CkWN8vjQs9L8/c+I7IPedlgaXuQlf3WQ9cRxoI+FoywXPS60njiG3iaWHEOY25+d9/4b/hvX/vvxS+lzqITHf2mgd8EKGA4KlLB/L3cVJtMvBZNqkac5MvVifnkDqGAi6TXlwfpcV6RJEXu93PV2w3L3NDxZ20WHryxQPctNsvFOnqmZ3UjjW/rUkmS9OZG31S5yzAXBnlOLWCdoT6jGfSQ43lSM83Wyi0NJD5BoZlVoGk3lASSPspAMBuZiigu6WR9S31uQHS5z9OgLMay1YVjsjc0sK8plpnQeoaCujylJBZf9IxTKJEMjfkljaP26KXBdVlsjTdCprkeISrw7BSINX3nILV+ME4wsEkkgt7ciR6MStQ56DncdGFpcysUs2Nr7mllVi9V3rPeJ+bcSrnCQyyy2mQxi4mWVomD5lmAGByYdRNCjzqc5Pkj3sebPc9Gcjw+g29lpLLjoDFnNkePn8Mb7j7ZK52i2ByS1uEba6CvLy3I1masYln/Y70fEFtqrnxsyD5YBxNdb2kvy03FFAOhFFUZJz4vJok+Wfx5FZ6v5+/Pq4kvZKyNBNzE9UbN4CUuTnMkrNAOvfoRkG67FX/SfjaB8/hr3/9K7Dd92XtJB0fv7dl154zKXEDNTfU84u2rf90HZUAX2VZmmVuWsSp7R4uH0xkVvVzz17DF7I6DQ6aDJsyFOAOGxRgPMWCrGiG/S7Bd4Xsls4XoNwpiEPW3GQLPWpMtVPTUEC5paWDr0l7DeT7O1SBKWAD1H0w9blxhMpihHFSqLcBitlHkwSGZGkUSFRhbqo4HcljzzKOfBGaLpyZu1ZmJzxiQUF6DO1IMKRckl2L2bI0TuMreh8AjlHNjZQD6QWljmTRvpRJCHXzh6ogCVAZc6Ma2MYFzfU8CDwH17LaMkCrucnehXEUS7ZQytLC6m5pgFkyNjJMZJT5H4WRfF6uDkOcPzb7Gen5bmEfw0mEJFHyPWKGn70yxMmtPKsW1a25IU28p/rcAFNqbuZgN7gs7WAcYrPnymetshW0ZG4Mx+6ImeftOo5xjKK/p+OMY1Z4v8Cl/M433yODTz5H6SyA4wgIoc5/EWe2l9+yi3/4/tcaf2dyS6vS1mAR5AwFOmBuTO8jkM05dWtuZrilUf+xw0m5LA1QdTdl74efjZFhFGcMQ/73nLmnuZRAweyL10Yze58BeeaGJFWy5qYBtoGCeRqLPcaykDpCl73SuBlorPbpnT7e/arz8t/UmNxzRS7wLKt38hkjFsYJBg1IMAeBi+vjKMfY0LFRbSeg5jXrlmaRw3YmHaEXZH84KR3AgGYXlaS1piL8py+p4CaekS3n2zicIksrMDeaoQA1pqolS2PZoINxiM3AM2bwgHSim+e9LwtuaJFY6HMTJ/AYGwAUbaABrhtXlG8cJ7h0fYxv/ge/hmevDOWESddSGQrUY25U4BdjEiYay+AyQ4Gk0JejbgH3LEhDAS67SqYvuLidp948TTcUmGjMoe8Kea+oPsoUjFaBk9mfj0tqboYZG6HX5MyLnufkamF4zU3Ktqgu4oHr4GASyu/xwuFq+ylp4smsoIkdGIexZMpMxcImmJgbYproJwVnz1wZFv4+rDkuqj4UmSxNMjduJhXV3m+SwVUYRBy20E6TLp7RMGMauHV9YftCzJQp+6Zz0Bb7KfMWy0TUIgHHrSc2ZDsDbwYLwE0O6tYG6DApBqq0NaizrzhJ3Qk7sYI2rQ0WtK/n4O+P0VDATZmbwxnMDQWzZTEDBT+Hkyg7bp25UfcvTvIy1L2NAI4AXiDmZsYpT6u5kcmtOcZDHSTPozWM66qaG93YpieNSszMjQ7fUfMYTz6WSQIDz8lZQTexTuxPYW7ovlCPJzqGVcPqHfEKgRgLYk/2Dydmu0eqdWgwO0T9KWRww5mbirrNwHOMcgZHG0wIKnudLlj2pSytLnNDNTcRNnpK/63LSpI5mRvOkhjd0rTzU4YCahAyMQF6Izqqufnk01fwK59/Hh//8qW0AJzV3NC10yfRXJ+bCqfGi27DOM5tj0sfJpHSzNP9ap25MdTGzLL9zFlBE3OTfbar9bmR9USsdoS+++UXM2e7ncWCG9dRjCS/J7xnDN3Dfi3mxs3JU3Tmhhg+33UwCFwlS5uzT1bPK7IqpuJRxdzEMpgEUIkl6vkOhto+KFmi/3z2SrE2sW7NTaHPDTE3vjOVuZlLlpYxN1s91kx2jj43ZYtytxJzY6gb0kwKyPmoKfkWfx9NFv+OELX63EyD2S2tnYQMl/d2UXPTKwtuGjAUEEIxBEZZWlbTcTAOSxfYgGIWyo6H/jZ1GTM38QTSpGGsPfuuI3Bmp48nXzyoZigg3dJEbs4DeHKrTs1NFtxk6pOcW5qWZCsyN9P3S+sLvk1gWs2Nqq1r4nng+zLV3NB9iZLE1txYmEG1JlRAe3UYGgcw5WrVIHNDEhITc1MxCODHk2tyOSO4oXMkSdtWrxkr6IORztyknz916QCjMJrZ7d60bQIfiOm8C8W6cQxXiNzi1sQE0IAhPeSzBSI1vrt8OJGyMJ250QeuufvcsMBsosvS3LwVNC1OZB1OS/p1eWzMxY8QxcnUbHLeOjM/eZAszc1kmBMWuAHIuaV98fkD9Dwnt0Cf99iJZcjVpGTs23ASseCnRs2NVlicWsRnz5MQ8jnxXSfVhUtDgfmyyz3fIEvLgtyc/baTFpeOwlheb6DaM5I2JNWYm0mesaHzmcrcLDguqj4U6fm8+iXH8di9p7CVjSGFPlnz1NxklyiMkqxWgfW5mUOWVvZOu46YmezynWJTXL1uSDfxqPtq82MyFqc7gsnS6u1Lx1TmpunghhkKTKLFXRarYlrNTRPLApqTTLI0qqsbTmIM/PJEJAVGZQE5l3KZApR8E8/ifPbAuR188ukrcxsK6EFvEw5fFMjtH5IsTfWk0ZUZfS8f3MxibnhwxJNEpVbQzFAgMsj9FgEFojpz47kil7xeZbe01TviFQLJsSj63x9OMI7iQq1KG44vlJk0MTdVg4AyZsM1ZNAAlTGhRRM1GJxGdc8CL1K8Pi7W3IzDGG//8H/Ez/36k3MbCniGc0o/pwyTfp/S68Bf9CrMDS0QLx+kz8Hlg4mUpeluaboUpadl0Wefk6oHItMCflzTZGmKuWlnWDAVXCczZGlCKItNujZKlqaKjrkumbvE0d8+c+XQaP5QFY6j3Pr0yYv08hQc1GFu0qDD3OfGcYRkQnwvZW4OeJ+buWtuirI0vdaDCu+5LA2oFnD0DQHUkAU1kyiWge6zhuBGZeUXu566Jv51d53Ej7/vNXAcUZu5oXeRJMcbgcssyau6pZU7BbqOwCwG1cTc6HVD9JPejUWffwI/JhMLkBrAtMOmqKQaYzZr1BJNA2duJmFzDbbLUOaW1kRfE0CNmeYmnk4WpIczZGn5BbEO+ltKahaYG1fNq1FSDH5edvMu/vvz13FtGM48Z86W6DJ1ev+aqLnhzA1nXIBi8oSSWrOCm4AFN1QfDZTL0nzmoBkl9Q0m0mNO98Ulz/RvLsm0wY2FESTH2j8MEceJnAj1DI3UiDa4qHS1mpvfvXwoJ8KqAyavd8hTyOnPYs1N1ucmVM5RQPlLWwV8Ak8Ldz3GTsQYhhGujyNcvDZGnMw3eecXcepzvn2OKFa9aehPTTU3vpbZcR0HSZLaXALA5cNxJktTOt6yJp7EDOjHWwa+ACDTAoLexJMmOlrk1pUBzQJdF35dq3Sj1uUAPY25AfLnJmUJniObbMbJ4vU2QFZ/Ni4yG0A6UYzCSAaodZkbHhBEiVpYuY6QwUHgihxzM4nmW4ClrEpRlqafm+sol7icLK3CwqHnuQizAmMCZ24OGatjZG7I9aiuLM0QbNL4CAC/+Nnn8H/+h9+Z2nem+Pfpd168nrKxuwOfMTfV+9yUytLE7OCG2Hl9m/T3gBoP6N2o+25XsRWetCRLK+tzM8tVrs6+oqQbQ4HpTTybCW6EMCcafVdgEmd9biq4pZUdD/2eAgL9e9OaeALAK27ZRZIAV0fhXIYCpTU3ddzSeqrmRog0SSDnde2nDLTcfJBTBhkkafNaWWAZaMzNInbuOnS3NH4snLUcRzGEaE+q3iZscNMiOHNzbRyC2sLo2Uzupd4UqDHXtVEkaecLV9MFRNUixSAnS5vN3MiaG01PP82BZRZ4L4eDUTr4cqnFhEnh9D43Vbat/j8v3wKKGdgwW4wIoepuTMxNT2dusut48VomS7tuYG5KrKD59iqxbczpTZ+U9ZobysR15ZZG15j3AdH7HZhAQbbulsYtxvkEoHTCIpe9MwWiVeEIMFla/nnueQ6Gk1jew1rMTcEKmtXcCCH34bsONnxPsqNpfdV8zM1QZ24Mlreu40hZGmcnqsnSVD0SgdfaUGAGAM/um5ibesG2LPg1LDY4c/PPPvG7+Pu/8t/nct6i8fBilrA4vhkwq/NqzM00G3TXEVLWWgYj+1RwS8snFOq+2mkgkf6/qeaGW/c3PYyY+9w0byYAsOAm6qjPTYksrYm+JkD6LmwFnnGs9bLk2yiMp87VswwFaHFONcaF4EYzFNB//7Kbd+X/V5Wl5ZkbJUtzRL1AnpibK4eTnAIDUOMKJV0kc8NMDqZB3w7NUaU1N556p1KGvrngRkromfmRMhRQzbCbTh50ARvctAgKbq4OQ+m6ARQ12ZMWMubEeFwbTXDHqbSZJdXdJBUWlIAmS+PMjShOMgAKmXNaDNbp+8F7ORyMI2wGbqHYE0jZhzhuygq6yDAA+Sxaz3dKazj0mhs6pudzzE3eLW0kraCLx9/33VJXJR1cskemBQRiBagPzFZPr7mJc8fdNMpladP3p2Rp6c+vffAc/vw77889V77rSDkad3jhznZ1mBvXEXJhbmZuYnkPqzS4LEMvW+RQH5iITWapoYAKbgZazc08k17PdwrMzWhSrC2gBTRNcrSAqVLfo9tkx5muHwAOx6E89pNbPTxz5VCeM6FuzY3KrJqYGyEZpXEYZ1LR6sE9jYHPX2XBqZjqWQAAUmRJREFUTXacVQ0FEoM0hx/fLCafsyQEGrIcbUFGY3MTbAodV5lbGqGJDDOHqeamKWZDh2zimXTU58Z1zcxNRWfTWfBdx+iUBuRdxabJ0mYZCtDzcJVJuTjoPk2i2BjYn97u48xOL/fdMvQYW6IHvU0wbXQd9ochs0nWfsoamzxzM0sOpys76PgHJVbQPHEXx82sE2lM1GvzXEfIGi9Kaq2iJA2wwU2roMFk/3AiC9OA4uQXSkOB5m6H56RN+oaTGPec2Qag6m6mySE4uCzNMQQC+uJf73NzmHVrr/Myek7eCnoj8Ji8KZEL2lEYz20oIISSl5nMBQrMTcSCG8/Bub2BMeCgwcBn2RCABTcHE0zCVJZGgYRkbgwTR89zKmcnlXQjlqYFfDujMJYDJRk9dM3c6LK0WbvTJ5W7z2zj/a+/PfcdnZWi7+eZmzrBjSNZEl1THXgOhpNI3sO6fW6SRD17YaQWAbpb2kbgqj43c07oRre0qNijh4IA6t8zkFrtKrK0vORSZ3AoWLzj5CaGk1garxDCujU3MhExnbkZhRHCOJEJqHn63NA7fWwzWMhQoGxsfPNLz+CdD56b+vfT64byx6nYlGZYAMAsS+Pn04VbGh+TG92XS9nr7qyg9Ro4IG8FXwe+K4zBKIBKRe2AchArm4tkQHBY7I2XHoO6f2VJrZdn7M2sZ2eaLM3EQM+LDWYFrZiWfDCimgQTc6PcGKehIEtzpsvSfFaPFWamRnVB8sNCzQ1zn6Pk8Sr2uAFscNMqXEdgu+dhfziR2QwABQehcI6MYVV4riMXC/dmwc1Tlyi4qRb9c1maafGvxTa5RoZAWjxcp96G9kuD1mHW/Z0v4MdRtnCaxHPX3AC8Lkb9nQyeDHp2+l7gOaW2wjt9D2+69xQevnUvt21aCF05nGASm5kb0yTa993KCwWfUf+hxtyQ5Gksg5t808G23dKkVS6XpVUItPWmqOZtKwtabgWac7Zb0AYaSBeLpbI0nbmpwVSqhqQq4PQYA6iYm7TLNB1TGM9bc2M2FNCzjq6TXtcoTtDz3MKkOHUffl6WxmtsDsexPPbbT6bMsl53U3dclFatBiaN7Nn58VH9TKU+Nxobe3wjkJa7VfvcRHG5dOvrX3kLvvut90z9e94DTG0zH8RI5kbWwVQ6tJn7Bcrd0ghNDyNlzE0bwxU9A5M4SXtIdSBLm0SJ0WyoCQbMdx3j/QLy4+q0sWtrRs0NMTuSudHGo1wTz5L7RtK0WZe7xxzKdJl8E+52FAiGcSITkKqJZz7ZptfcVGVulLEAMTdlsjTNLa2BQFvvc8OtoKUsLUmMc8KqYPEGJBaVsDPwsX8Yyp4vgIm5ab7mxnMELh+mk/Wp7R6ObfiSuUnlEFW2USJLm8HckKzmYBxho8ZCj85jkrEQkyjJ3NLUJEcL5XEUw3fE3N2cXUcAkVZ/U2YokKgs2iO3HsOdp7bMx+w6+LH3vSa/DwAXMwnLpYMxAs/R3NLMhgJAOoBXPS8968LPixbOJAfSDQWW5ZY2KyDVJwETUllavubGz7TCQeakVqfmxp1mKEDMzaRoFT0vctn/Xr6vgUmWRv/mltFVYOqInkoQ8u+rx9iiwFOytGpNPEmWlq/BA1IWlo6dZLPPXhnipTftyO/UrUVUbmnF68JZD3peXshq4qpcRpWwGMMRqaEAUO56ZUIyp7ujDmrQyaHXKdHPRmVpxNyU1NwQmpalqaQaY27i2Dhm1oWjjctd9LkB0nms76h3sIotctXtm2qkgPycs1EijQJmGwpwKZfpe9zJs0xO+IpbMuZmlizNU3OC3lQ8VUXUu189z4EjUiMa2v5238MdJzdx15l03j+3N8AtxwZSGdPTam/KIBUdGhNUVnOTytKUGVQ7NTdqvMgZCqywLM0GNy1ju58yN9Nqbkj73eSi0nWEZG62+h5uPjZQzE3FSTUvS8tvG4AswCXwoG0UxinTUpO5oZobWhhtBK4cFHI1N5MIblCd4ZDb1xYBgBp8TE5E9L2/9Z6HK+9Dt3u+fDDBsY0g55ZGC03TwNWbg7nhvWRC5ogGqEU5OejpVtBd9bmZW5bm5el7E6hWBShagdLvatXcCHV9ClbQvosrhxNmKFCj5sbPBwRcluI6zAraKEubh7kxuKUZ5Bx8kdHzUhMDwByEF8+FZGlUZ6OCm+Ekms3c1JRJ0ntsMhQgt7Qk05UDwAvX0+RDlcUknf7FqyMc2wjkdeJZ1lmoa/PrOcLILgPqHHidA9BMwEHvYdeytLI+N03vB1DP3IgxpW0iF9yw8WNeRrYM3/v2+0qNTrgb4TRZGtWXliVvSIIu3dK0+yKThlGc1scankXJ3MySpbHifZXQU8lVXke0CIQQ2Aw8XB0pW+qe5+KX/uRj8jvHNwP8f3/6cflvxdxUdEvT5G7lsjTFBocN1WAd2wgQeA5jbOhYin1ubHBjYcRO38dVXZamBzdtMDeugytZX5XNnoeb9wZ44sI1AHPU3HBZGvu+3hiOMA5T20ByXjkcR7Wc0gC1CDlk5gQem7DppR+F8VzyLbl91miTwAdhjkX13XxxttXzcG0U4tooLGFuitvvz1Fzo4orY6OhAABcHykGwncFq7kpD7CagHST0mVpM/ZXmbnRm3gyRx0/FDixGZT+/SzwY9Qzc33PwQXWxLOOoYBet8Gvj+uoBomBJzAIPBxOorQuYF5Zml+UpY0mEXoGQwF5bJ4jkxVVnhHJ3EzyDTuBvBX0bSc24Qjg2SuHub9XLMRikyvZuZoy1pIFSNS1fj5jbubpc/P8tRHO7SlGkPdbmoWqSaYyeK6hEWliZm7S2q2Fd1XYL1AW3LCEWMPDiKnPTRw309RQB92Xw46YGylH1dYGTRkKvP7uk6W/44mKaYmZr7zzJH7wGx+W7IoOIVJ7eqq5KbeCTkqTWqe3+/iOx+/Cm196pvQ4gLQh7x9//C48cusxmTiWbmkNudsNAhdXR2HlpDMFfbNrbvKyNr9CzQ2XpTUxP7/3tbfiK+48IY+FqwNorREnSSP1S8vCah71CmFn4BVlaQXmpnk5kOcIuc+tnoeb9zbwu5fTzGg8xaWHgxcamuQGRSvoiDlwpYuXOg086TwAZS+5obulyTqfCHGSzN0VW2bF2cKQW1ZyVLXQ1sH/hrLUFNx4enBjMhTw3coZVxqY0iaeuizNlfsG0oU0z+C33ueGgtIcczNblqYbCpR9h/fwST+jjJuDMzv9Wllrfk10DTLV3DRlKADkgxv5jLLrRMwNkJpRpPe6nizNZCjAF1Y9z5Uy00qGAtNqbiaR7Nmz1fdwertfYG4mUb1g+633n8GPfuurcP74RuF3XFpLQZ6suamwP/rOwTjCcdZMNpWlJbh8MMb7fuyj0n7fhGlNPKvAc5xCAkaXpXFmuCmGg57/mW5pHTA3KbPZ/DKG5gBu4NEmyswouBS6LfCk0bT52nUEfu+D56aO15uBJxO5RStoxdxHU+R23/22e/Hg+b2px9z3XXzP2+7N1eDKmpuG6kTo+a6aNJL21LNqbujd1Gp5ytzS+NzWVM3NZs/LWW/zmht9fbWqNTeredQrhJ2+X5Cl6RlTWuw1ydzwgWWr52FnkGZ5ozjJLJNnb4OoXUfkF6Ayg8ZkaXFmPUz212OSpdWtuXEpuEmv38B3c8GHLCIP40q2wjr0gjqAy9KKC4dFJlJ+L16SBTdAOqnokjWjoUCm/60C6ngcUp8blnWhhTO5fvmuk7mMaTU3LUkwaIEwYRN4ld5EylCg/Nqn55GvoZCFm55TyykN0JmbYp+bUUPMjd4bhve54I8eD24OxtHcjk5GtzTDRMbfi543nxU0ycEocOeytMNxJJ/Dge/izG6/0Oumbp+bnufi8fvMGWDusCRlaZk5wDzMDQAc28w3k51EMT759BX88ucu4lNPXyndRlUGvQwm5obGZArkuSytqRoYzxXo+45xwd+mLE0IkTOYAShR1+huAKhEAj27bS/wypibKGrGUGAa+H2sm4zc6LnlfW7ks5hUqrWsCil3jpihQANsA12LquMPVwpMg56sk008y2puvHzNTSt9ndy0f5XrqDWJNBSwzI2FCamhwETqUAHzAAZgZl+DecAXH1s9ZZ88ieLqNTdasRmBBls+sVKQQRIQkqU1xdwQ25A28aTBLGbMzfxW0ICaxPj14AECR7igc42JuQEyG8vsPo1kE08zczPPAo9clCZRktNT0yBF19JzRbYwz9fctC5L4x3GK7BhcxsKaLK0e89u45Fbjy1+4MjLbXTNed93MGyYueFSQT0LD2SGAtlkeDiO5i6s7nkOojjJZf5NExnPEnJZWpXnsT+DuTnMnruNIGWE9BqgNuS6BBP7ez0LvqqMjfz8j2/qzE3aNwdQSQsTasvSDDU3VGxP4xqX8DYmS3OmOG/lgptm9sfhOkKruWlnsacMBbJESc0ajlnQXRIJ0xiOpsDvWV13083Ak2sdPRFI7zG9b00pBGiMUm5pzbjbUSPPqvMhJXNmGcpI1zXZxJOYm/KamzGruWljfvYcZcygxsZUFVA3Qb0s2JqblrHTT4vSqNNtyDKFBNXPoUnmRr1gmz1PLhAnUZzplKsHN/oELLOe0ZTgZpIyN03U3ABclubl5Am85iZeYLEgbR4NFPpEb+K54MDCB/k7WHDj5WRp5RKcge/MdV6pE1SMUNMe0zPAZWm8P0zdGocqxwVosrQKmnK96ZkJgacmgInG3Pxf3/yqxQ86A19f6wFAKu2L5D2s5ZamZXDzzA0LNFwHO5lDFzWgnKvPDQs8KCgyNWxzc7I0R8nSqhgKaMwNd5M7GEc4ZH2DAs/BZa3PTZvufTy40cfjeWRpQD64SbuJx/JcTL1LCNOaeFaB5zoFabBuCuKyBWVTTIrvitLghl+XVvrPaMxNXVOGafsBVP+xpcnSGpIhTQM/t7rz9SBw8aUXSJaW/13Rua/WriR0t7RxOJ+5ShmoZq/q+DMvcyObeDoOhCifN/zsPae1ThvzM2dsZAPbrNa5v2uDGwsDtvs+kiR1AjqxFeC5/VFhMqVMdpOOLHyRvNlzVf+TzGO+WnCTj+QJcmHAZGmUdd3uU2PIKDUUqJkJ8g2yNJ9laqT9dFizz402EvuGrGi44ERaJksLXCEHKtXEs7j9b370JXjdXeUFoab9HYwjjKMktwilwZPc0qgPTFfMTZDt78WscBsgK+jpf0eMz7QMPu/iLN3SGqTTc7I0A3MzCtPajcBzasktepp9cr7mRn3P9wRObafdvEnO5c9x39R+YgRejJ/56Jfx7P6wUEeRP29XydIq7EuX2JEs7fhmgGHWxHPgu1l/GCcnVwTade/L28lrwc0cfW6A1HmIQIYCVw7SZ3wqc1NXluYIYwKGH5/s1xI10/wPSIOqsoaQ/B1tSnbE4WrjclvBjW4F3ZY9PkFnbAltMVMc/J5Ns4Kugs3AlckzfRFOyhTZc6kp5kYmKhRzv+3XX9rOY3sPMEOBGbJk7kxG29/IxkETKBiiZ7GNONtzhLw/XJY2DOuv4ZaF1oIbIcRfAvABABezj/6nJEl+vq39HVXsDNJL/PSlQ5zd7eO5/ZExOwM0O4nTC0RF40oSVD0IkLI07bt6AR9QZG7G0i2t3iNG+yLmZsAMBfjCZBRGleo3yrZvYm6KxbqLLRCmytKy31GAYXoGXn7LLl5e4lBjwmtvP46PfPxpRHGSa8Sqghtlb5rWXtBCuvnaLw7HEbjz1BY+n7n2AdVkF1Wao5lkaU0mC6YaCnguwjjB9VGIfs2AqmdkboryUN91cGorDW6eyVzG5pGlKclYhD/705/Ev/rUs3j0juP4Y191Z+57ulsaFb1WySYrW+u8LO34ZiDd0mgBEXjF5pfKIr+NRbIaD7kUSIhqi67qsrRy5iaKZwf20+A5DpIkYz+1hJNuNzuO5jdbKcO5vUGhDQCBrmtbZSLEShPqSvvKUKi56UqWZjAUaMvghcADtzK76KrY6HmgZUFxTtVkaQ3dN26iA6TvdB32nECB3rw1N7P27WcWzLQGS3uWla+TaHvDSZvMjaOcY7PNR3GC4SSu/UwsC20zNx9OkuRvtLyPIw0qsH/h+li6UxSZm+YdWWgg2ezlmzWNSZZW4X2VsrSSwsBczU1oqLmZRBgE9c6J9rXP3NJ4AWFeljZ/EavJiQrIvOUN3aIXkQjQPjYDF7sDXzpV6VbQvisayXb+xd/7AN764f8g90HQ+9x4miyt7T43AHDPmS189Asvyn9Xce6jhcVU5oadhzQUaLhvFO1Hv0c0+ewfhrX1ybr2nksh9eBmazt918gFcV5DASANqn/tCy/iXQ+dw//xDQ8Vzk1nrAbZRFfl2qpJOd/E8/hmgBeujXEwjnLdvcuaG7fJ3ByM88FH1QUX/94xHtx4Dq6PQlw6IFlaOXOT1Fy40vswiWP0ssaPkc7c8Jqbhq7jD7z7QZTENnJeaWsModYAhKihPjDF/dC43I1bWk9774H03U+SdsdjQI0bgynsQVVssix/cd2QD+CaCkqpRjZiwU0zNTfVbe+B6jU3viNyz6zniKnrJJ25aSPZ89D5XVzJmr5LWVqSYDiJZjJRRxWrGZKtEEgXDwAns0xrwQq6hcJZiu5JPqBqbpLKVH65LC3dFu8UTdl/kqVdH4UI46TBmhslS3Od1NkjimO5eBhNFjQUMCwcgXKb1UUGFtr2XiZfoWZovLvyKIwbm8TOH9/Ad7/1HgD5bL4MbsbcClrJ0tqscSDcfWYbv3tlKO9nXEGWRs/utOPSraA9RzTqMkTPoWniogX6lcNJLTMBIK+9T5IkJ4XMBzcCfd/Fds9TzM1csjRVy/bi9THuOLllXNi4WlaXsplVxipdljYcRxAC2B34qRU0Y25MsjR6HttYWNK1PNSCm6rPDH8UC1bQUSwXClOZm7rBjYFB1/vcyACoQVkauSyaQM9LG5I0oKTmpiX5G6DuX/s1N/meUIBi4dqWpc1qIjkPuKytlLlpWJaW7sthzE0zhgIbvcWYm1ly6NtPbuLOU1vy36+94wQeu+d06ffpXCg51IZ73je8+lb88De9EgCTpcUJRpPYGgqU4NuFEN8C4GMAvidJkkv6F4QQHwTwQQC49dZbWz6c7kHMDQCc3E4nwbLgpskMDWniqfCTu6VVLbz3pMRAC240GhgoMjdUUDuNbq0CVXOjZGnpsaXMCtVXjOeQ23F42iJAfu6W1NzUkKWRfGVvkNZe6cxN3UCQ49tedzu+8Px1PHbvKflZoMvSPIHAc6RGuu0+NwBw9+l0UP/8hWt45NZjmZRw+v6UdeZ05mYSNZu546Bdm7JYtIi/fDipZQMN5Av9dXkHv050fqe2e7I/zFxuadl+nrp0AAA4u9szfi8nS3Pd3Ps3C0JkbnyhYm4Gflq3k1pBKz23z6y8CaFkISqfVmXQ+04s5onNAC9cH1dnbkpkaWmQllRzS4uTWkGAYmX4Yj/7nWRusnE/jFsLODjUs9rO9nW3NKpza3w/miytsyaeLKEmWbi2ZWkz3LrmASlFgHIjoqYNBYA02UDXaxw2y9xU3dYjt+7hna+4CffdtDP1e9/6utvxra+7Xf77/a+/fcq31bzXJnPDQc/+OJPsrqosrdZRCyH+nRDiU4b/3gXg7wK4E8BDAJ4B8DdN20iS5EeSJHlVkiSvOnXqlOkrKw3eHXtvEMBzRMFBhxiCNmQ0KrhRA0vV4IbqdAquJ66K7AkquFEOTkB99xVVczOBI9RCkvod8OZWk3B+u1PHsHAEskWK3v27pqEAMTaKuXGUxK5heYXnOvjffv8r8OgdJ+RnxApIWZpTxty0KUvbBgA88dw1uc9ZC0plKFD+fnBZ0yRKGl/w0HMyjbm52jBzI10UDQwq3aOTWz3J3CwiS/vSi2lwc3rH3AeIL6x6vsOKbKudJ3++VHDj4WAcpk48TJZW7CsV57TpTUI24cwWDHT+Vd/vcre09Dms5paGSvLgMtCiK8wtiCkrnv5b1dw0ZwU9DfJZbSmQ0vvcPH9tLBURTcLJ1AEUnLbd50avtQO6GY8B9Rw1kVzLMTfaw019iojJbbbG2JHJuXEUN1IjNZiz5ubEVg9/572PlDoJLgqay4hlblumSGM+7e+GZG6SJHlLle8JIf4egH9RZ1+rCi5L2xl4aW1Aifyi2cVtuq1NA3MTxQl6FV7+oGSimlZzs0PMTeYW1FSfm6vDMKcJ9rPBjC+IDifR3BOB6sxbPEddlrZoAELbPqbJ0jxX5Gp45sm8LwK9zw2ZTdACrIuam/PHN9DzHPz2c1cBIKuTmv43SpZW/kWyy4yyxq5NZ1q9KcENfXblcJJb6C4CXlgsjUY056vAVXU/p7Z7+PiTl7JjnIO5yfbz5Sy4ObNtDm7yzI3qrVP1Pev76vk6HKcSh77vYjiJMZxEsl7FNC6GUXvF1LLmJmMxz+z08Nln5ghu6F6wxqaAMhSQUrxZbmk1zs9k7CKZG03KOA7jUoezJmFiGZvePp93LuwP8bo7T0z5i8XhCqGsoFs2FOCGP4QoaX88BtQ9a0aWprZhOm6XJXebTFqkQa+SJTcRjM5bc9MWdFla288DbZ/6fjWpKOkSra2mhBA3sX9+HYBPtbWvowzO3Oz0VTE5B8kKmqx1oG1t9fXgJkGUVKO6pSxN+67yQVfnMdJlaRlzUzfq92TNTZiTuLmuQBjnnY6Gk2j+PjdlNTduKnO6cjDBhaup7Ceq0JNl2j64LA1IF0J84Gx7ENVrbkiWptiv9typCK4jcNfpLfz2hWtIssl71iRXRctMi49J1tg1aDBRAOQNBXQQW9NEzQ23gi70LMl+cobm5Fagxo8FmJsnKbjZMWe/deZmMKdUo+cr5mY4SWVoG4GLcRTLhAWdU8EtraWGdYCSa9G7QMHdvMzN8Y0g9/xSvyWquRnNqLmps8Cj54AzzNItTXtmJlE7rmI6aH9t7YovYoeTCPvDUFqiNw3HERiOu7GClsoKJjGMO0g2pfvOmJsmZGl8jjY8BL4jGndLA/JB76QhWdq8NTdtQRkKNM94mUDjxEGWBL0hZWkz8NeFEJ8UQvxXAG8C8F0t7uvIwndVZm9n4JdkKJu34JWytCAvS5tEcWXLZJ9JwDhMhawjTZZ2Rdbc1JSlsT43PCtEgxm/lsNJNPekKhtpadfez4KnP/VPfwt/7B/9JoB04VDPUKAoS8tJjVpu1tbLilap5kbK0pjtMD/etnDPmW18/rmrlS3QZT+AKd+Tcq4oTmtuGpal0TEaZWlZoBDGSe2aGy4fjSLzQpWfG1/YLdLE80svHMB3RSnjpDM3uxkTXTVp0fNcmf0mWRoFNC8ejFlwkxYExzkWImmNzaTzIukFBXdVAwAK+o5p1y1wHVzJmqoCFdzSatXcpNcmMiyITW5pHcQ2Rme/JsH73Dx/bQQArQU3niMwDDuSpWVjMzfV6Go8pnmnbo8bQDW+BMqZGxncNHhJuVxx3ND4vzmnBLct6DU3bRtM0H27JoOb1WRuWuOpkyT55ra2vWrY6fs4GEfY7ns5y1pCG80Tpf0wydJYwWJVh5kyWRpN7LyjuN7n5lILsjSurfYcB1GUYIy8LG1R5sZU/DgOY/zGly7hRLaAiSLVc2SRfShZWvrTc0Xu2jZZc2WCSZaWZ26SzImu3cHz7jNb+MjHn5YBcFVZ2rTFO53bJIxbMhSg4MZgKMAyW3UnAiFSNm0UxUqWolmy83PjC7tF3NKevnyIszv90nvOWSPPdXDHqS38yDe/Eo/dW+7uw9FnzE3a90qZElw+mMj/5wXVfYeCxbhF5oakFxlzs0vMTcW/z67XCS24oSaehOl9bqrJg8ugmJtinYbev2vRBsTzwi0xoWkKnqsWsRevthvcuEIoQ4HWZWkqCCXogWpr+26w5ibH3BieN/5+NDnPULIzSZLm3NLIGXLJzE2gydLaToLS2EZJUGsFbVEKauSZytLcoqFAHDe+qKRsA8nSpBV0puWvI0vb6Xt45NY9/NAvP4Ff+PSzAFTNzYbvwRGMuWlKljYKcyyQ66TduXmm63AcYd74QNXc5P/Qcx189pl9XB2Gkg5OFwjznwMVGFJ2mJibwHWkR3+6z45kaSMlS0ufR35+7Q/kd59OTQV+OzMVmPXcb2Vs4DQWkMsux2HSeKZVGgoYKHo++DfRPI6K8PWCYl5zQ+AB/1zMjaf6opRJ0vg++Xm97YGzlQ0b+PN1MInQD9zcmDBghgKAVnPQ4vNYqLkhWdqcbmk6c6NnjIdTDAWiCjboVY4hMsjSdOaGf9Ym6Lq2lSDhfW5kcLNlrherC8cRckHZtlua7EPHDQWS5pOexn07zcnSdHWFDs9tR5bmZkEvMaZNyJLpXJYuS+vcUCD9eTC2sjSLGSCp1s7AkwWnHGHUvLactrelNfEM4wRxRTmElKVp3xVC4Mfe9xo8cG4XH/rHv4mPf/mSDNh6flqk3ljNDZPp5AbObDDLZ0njxmpufFfIRny0QEn7Usz/ytx2YhM//YFH8db7zwIA9jJpj3QBkx3o230dXSftq3MwzsvSqLHron185sU9Z1I76M8+sy+Paxre+Yqb8FMfeO1UVyTuMtaULIGDrospaOKDf6+B7Cfdkyo1NznmZq6aG3XMZ0qc0gAlC100aOt5jsx+D8cRNjIraIJew8NtjSctjIsE6ZaWvQsnt3twBCo36aVx5viGn/ucPx++KyRrZULtJp6OOSAEOHOjjqcLWZp6VtvZPu9zc6Fl5sZzhGxW2nZwQ885v5ckv+vKCroJQwFuWmF6tj1HrX+anO6ozw1dvybcMsnWetnMTcFQoCNZGrHa1lDAohTkILbT99MCW0Ofm8ZlNLosjdXcxEm1gYX+xjS47g58/Mi3vBJhnOA3vnRJDliB66DnO7h82IwsjQ+Q/CUjGppPBuNo/l4ONLCbmngSaHFWZ/H/FXeekPt45LZjeOM9p2TPF9OitS3wQd93RU4O1KY7Fcf5YxvY7nv4racuA5gtS+v7Lr7yzpNTv8Nll1eHE/nONYUumRtKgNA7pTfTLZelzV9zA0wPbmRQt+B5pW5pzAo6cNE3BDfcJY4QxUnlYGNe0HvPs5O7A7/ywsFzBDYDFzcfG+Q+59fp9HZ/OnOzoEEJPwbaDt8mYE7atL0o4vtriyVK+9ykz8jFqyMIAZzYqudQWAY+77Vdc0Ny1JyhQEdNPGWfmwYWsbq6wrQv2cSzBbc0Wg80KUtrO+k4C4Wam5bnaHreiNW2NTcWpdgZ+LIbfOAagpuoue70BHoh9Cae4zDN0lfqc+MSo2D+/cnNNNt5+WAia216fnqOTfW54cHEIEd5OwijODexA/M3BjPJN4B8oDHKusVXlfPNwpmdPn7y214j/11mR90GAs/BwTiC7wrZZBFIzzFqscaBw3EEHjq/h9/8cmph3MQkF7Dg/crBBDfvDWb8xXzoquYGSO/RKIyxn0k7qYjfFNyc2OSytOrXkS/WpjI3U867CvQmnn3fxYZBluYbZGlhnLRWh0YLFmJuep6LvY2gMrvhOAL/4jvegJt289cuf1172M+aD5uQ2qDXCG7kM29YEBuCmy5laW1aQdMzcvHaCMc3gtZYlVw9ZBeJJ63XUxstIkzwHQd7G37hWV4Es2puXEexmU0+I15mNKESQk0YCuQTw8sCzdHDjmpuaI2z6oYClrnpALed2MRtJzZUdka3go6Txl8gmrwpuJEF11GSyavmCW7Mj4njCOxtBLh0MJYBGzE3hLo6Xp6N1j30U1lakluQzDtglve5Sfd7aruHJFE2jG0s/ik73YUri16cTzKqtGnkYrK7RfDgLXt48sW0+WQjwQ3L/F8+nMi6pqYwTZbGF/5N6JN7notxGEnDjt3MOpyuE5fcBZ6Tc9+rCo/ZkE+tuSHGqpYsLbPu1QwFAPVOKyvcfEPK1mtuMuaml13HebLkt5/cLEz8fBw/u9uf2sQzXrCGj0BjlJG5MSRtupSltTWMuI7I1dy0JUmjfZn+vy3oduh0L9sOSh1H4Be/+6vwTY/eVntb3C3NxCT7jjIUaPKaqvVAc+52g6NSc6PJ0tp+HiRzI5t4rmaYsJpHvWL444/fhY986HUA8gW2hKgFOVDBLY1lRivX3Ei3tPLv7A18XD6cYBymHbC9rDEkkE6mdWU6PEvBWaDUqjnBOIxyHYHnvYyurHfRgptsv6+/K5VDURajjYGua+aG76vnEnMTdVZzAwAPnd+T/9/ELn15HjEuH4wl29EUpsnScjU3DTjLUAKEGuHSudC98bULdiqrRZo3o0fv5tlpsjS3CVkas4IO8k0vKTjoeWp8IrQpk5S68kx6EXgOTmz2amv1KfDseanMbWoTz6SmLC27N6FpQWwYU7pYpHXB3EQdBze8aW6b8LV63K6aeALAia1eM1IuNkebAlxuBd3kaSmZenrNmnC3Czyltlkm9D43bfdc0mtuVpW5sbK0DuC7jsqUew7GWjZvEseNP7BeQZamZDtxXM3NRjE35d/d2/Bx+WCM8d5ALgxooTLw3dqTQq7mRqO8iYbe7nm4msk/5q65KTEU6HkuNgMXD9+6h498/GmZ4W0nuMkCji6YG60hJi3WR2GMSUc1NwDw0K178v+bkPrRBHTpYIw4UY1Sm4IMBg2L33TxAyRJM1kusosnx0FiZkxW0EDqmPb5C9fmXpz0fBfXxxFOTwluHFF+3pX2kUnsJplBwsB3c5OlLkvji7swTlqTYEjmZkKyNAff+/Z7ZRJjUdBzuLeROmNOs4KOk3oyV27zzLcJLE+W1rYVtOs4stD+4tUR7ji52cp+0n3R+9bNmKjbiNN5Lps5mAeeq3qnGZkbV8jkbvM1N8xQwG1mQf633vMQ7r9pt5FtLYqCoUDLzwONSbLmZkWtoG1w0zF400RCGDUvS1NuaVrNDfW5qWQoMHuiOrYR4JkrQ4zDWGataeHchPuKXyJLS91R0gX5dt8HrgyzY51v+1ISpv3hB954O77mFWfx4vV0gakaX7YgSyvJyLcBXZbGXcaiOG5dz0s4udXDLccGeOrSYSNZUcqYkz3sbsOyNBrwTZl9ql0aTuJGmBuygr5yoNXcGGRpgDIVmPfZpIBlmiyNFiiLMho9P13g08Tc991cs8CNoMgsE9qUSdI7dyhlaS7uPbtde7t0nfYGQc5MwYS4Yr+xMlAyJIzz1wxQz4qXC24W3tUcx0TMTUvbzxaxSZJ0xtw07bxYhp7nmOunutATNojNnodRODYed8rcNL9Ip/WAbsJSF+942U2NbKcOaI4edmQFLfvcEHMTrKbAazWPeoVhqrlpo5/DfTft4N4z27JYWC4ewnlqbsysBsfeRoDLB2OMwqjA3DRBZ7olsjRpBR3GspcPsHjNjX6O953dweP3nZHncr1N5kbW3LQ/idH50L44c9NVnxsCSdOamLxpAqDgZq9hWdqswnr6vEnm5vLhBJuBWzD20Hs40AJvbubGSyViXNapg2KLRYO2fpbMoR4NA73PTZAPtschrx+JWwv4Pc1QoKnFED2Huxt+xtLHshmjjlSWtvi+JHPDF8RSlpb+O8fcdPBut+6W5qZuafuHIcZR3G5wQ8mEjmRJvuvk+rbpznerAtkfxvBOeYydaoO5oW13FZB2AZLYDVsICk2gseP6KIQQ7TsFtoXVPOoVBi1cONroqP7qlxzHL3zXG3NFcY5I95UkSWOytGMbPi4dTDAKY/kS0EKoCeamzC3NdQQmUUpD52tu5nvxy/rcEChAu95izY2pJ0VboHvja/dqNOm25gZQwU0Tu6TA+uK1LLjZaFaWNquwvuflr2cdkBX05YNJ7jyIxTDJ0oBFam5cnN3pTx0L6JlcVJZGhhxfeP46AGSyNLUter+4JTmh1ZobaQUdoec1V1NB92Zv4MtzK2Nv4rhewCFrbnKGAtnvsvsmhGoS3IksTXRTc3PxWsrUtxncSLa2q+DGMxsKrGpwY5pLfNbEs8lg28tqcCdhc4YCRwVSljZuTz3CoZibCH2vfmnBsrA+T8CKgCQnHG1qyzn8zGoyqiiHqCRL2wxwOIlwbRiyBZ6quakLPrDr3Y+jOMFIY27mfQ9NrkIctBAjWVqrhgId9rmhwZ8CxoNJ1KlbGgA8nNXdNLEQomf1wn4mS2uauZkiSwPUIr0Rt7RMznTlMG+MQPO1Hty84e6TePy+0zlb6CrY6Lk4O8P+ddZ5z8K9Z3cAAB//8mUAqg6PxgaSpQWSWc4v7tquubk+Chtp+EegjPHehi+fhTLHtKrGLmWgACYX3CTksFX8XhdrZOWW1lbNTbqIbbuBJ8AMPJZUc7O6wU36TpvGdddxQI9rk6elam4yQ4E1Cm7oOTycNO8yZwJtfxzGK+uUBtiam85hYm66WlQG2eBZVQZXRZZGi6/nro4KxepNyNJ4zU1elqY6Em/XYW5kzc30RSsxN+3U3JCDWXeGArRoJC//g1H3zM2Dt+zhO99yNx6771TtbdGzqpibdqygy2VpzT3zxNxcOZzkghunRCbzspt38aPf+uq59/MX3nn/zIW9O+O8Z4HqWD6e9TSiBp6DwE3d08hQIJNe8Mz1JE6w0XLNzSiM05q9hqAMBQJ5zcoc05pq4snd0tIeZnljFdcRQNRRn5uWa26ObwS4sD/CJ5+6AgA43QFz04XRC6Dee0KXbmlNYrM3hbnh7n0t9LmRhgJrJEsTQiBwnc6aePLExKo6pQGWuekcPc9FFCe5CSmM2tOWc/he6jRTtXlcVUMBALiwPyxIc5qQpeVqbjTmJoxijKMYAbNrnPcyltXcEPSamzYWCF1mCHVDAbpH18dh5zU3nuvgO99yD05v128eR5PZ81fbYW6mGQoARUvjOqAmnqksjTM3dAzN3KOHbz2GB85NdwKSQd2CGbzdgY+b9wb4+JOXAagEhfyZPX/S2ELrc9NWsM2328Q9I9C92R0o5qbMMS1OWpClGeop27Zn5mi75uYPf+VLAAA/+EtPAABObdUfO8qgxuWOghvP3MRz1YKbjcCDEOZnO993qdmamzhhNTdLbrzZNHxXdCZLy5UC2ODGoiqM2vLOZGlC9rmp8n7ohcwmHMsWXxcYc0MLoboNPIH8i7ahWUFHmcY2yOwngUVqbqbXFdGilQqP27hPs+p+mgTdI7q3VK90fRS2uphsG9xQoO87jWeclKHA9JqbJvabOipGhWakbseLLb7POhr2+85uS6MHPaiZagUdtcckum0FN5kFLVlBA1NqbpJmmnhyQwETG0QJoi4UpzKQaum+nT++gT/06G24lskJdwbtiU/ondcNPNpCKhsvNmTtIihtEpuBW8rK8LGrebe0RI4f61RzA6SJadnEs23mht27ng1uLKoiME7izfe5McGfU5ZGJgSz3NKAdCDW6zmaWOiVZRH8TJY2jmL4niMDqqb63BDI41018Wz+PnWZIdTvEXWUPhhHrRZwtw1udd50jxuggqGAX6/wPretzGXrysEEO4OjEdwsytwAwH03KYtlCmo2AheuI2SGlZ5LfXHXVtKHP+dNSliObfoQArh5bzCTuaktS8uuTRTns/3LZW7ar+/59sfvwlbPw6mtXqvFzjTUd+eWljcUICvoVUs4bfS80nmEf97kZdX73KxTzQ2AnCytdUOBnCxtda+jrbnpGNx6l9AVcxNkmaF5msd5rjPDUEAtvihTSefYiCxtiltaGKV9blLmJv3d3IYC0qmsjLnJLGMpuGlhMp11DE1Cr7kJXAeeIzLmJqm1iF0m+AK1aUkaUMFQQFpBN1Bzw3ph8UCta2taoH7NDaBMBQCVoOj7LjZYk19pKBDpC/V2a26AZpmbW45t4Je/5zHcdmID/+l3XgAwTZbWTM2NHhDqC8u2pWKmY2pzX8c3A/y1P/AKvHh91No+AMWMdWkFrTOXwOrJ0m7eG5QaPfB1TpOBqeeIrO/d+llBA+mzQXNCV31ugNVt4AnY4KZzmJibcdi8FbQJ5KMfJ9UX6YHrzLCCDnLfBdRCqAm9phBCZmV0tzSiaQPPkYvOed/7B2/Zw+vuOlG6KCVa9nqLDbRUn5tuTCUANWELIbARuClz02IBd9vggWHTDTyB2Yt8ydw00eeGPQdclqasabtb7MyS41XBS1lzzL6vmJs+e59pMTLWkz6t1dyo82nCvpvjJSc3s+0WE1kccc0aN1MTz9hQc6PsmRfeVWVIiW3LgdTXvKL95or0vnW1UNbNhuJkNWVpH3jDHfhDr73N+Dv+Pjf5jLiOQBQl8l1bN1kaT6p1ayiwutfRBjcdoyd7H6hs3iiMO3GlIB/9KK7ePM5zxdRBqO+7WY1AXGjiOQiaebzI9llv4kl1MHVqbl5/90m8/u6Tpb+n7R6Mu3BLa38So8U3H/y3eh6uZczNqkkgCOQok8rSWgxuSgZ7ynA1sVDm++DnIrvOdzhx0/t9fHNxqd/tJzflveGyNJ6sIHnaWDNaaWsi55tti62kMb1UltZUE89YY25Kam66YADomFZsPW4E5RC6SiYEbt5QgO5rF6qOJsGTjTr42NVk0EZ9bi5eHcF1hKwFXhdwg4Qu3mNKKK+yW5oNbjoGLSp5Nm84idDvIDvEqc2qsjTfdWZ+99hGgGf3h8XgpqEXw3MERtDd0tS5+K6Q+2xag502+AOurUmfm56bl6UBqUb6YAluaU2DMp9N20ADKmjZLAnYaYHcRKaLB55cYkf3rEtZ2iBw8a+/8404t7e4K5XnOrj7zBY+/bv7cpz74BvvxIX9ofwOWb7ri7u2XI+EEJmUJWktyytrbkoNBWq6pVFww2RpJskxb+jZNmjfq8Y2mNClRT+wPoYC08CTZ01eVkeki/GnLx3i7E6/0wRQF8gZMXTUjDdCstJuaTa46Rg9g/zicBJ1w9xwr/SKL8h7X3MrHji3M/U7exs+ns1ZQVNw08wAQ8YGvRJqNvBcufhsem0uRBo4XZeGAu3V3HRpKMD3tRm4uD6KVtotDVDZrTZqbr7qnlP429/4MO45s2X8fc9zIUQzcoiAsT9cYqf63HR7j27PZFZ1cO/ZbXz+uWty0fHQ+b3c753MXGAcTi+ObxLUELIt5ka6pZXV3FRsplwG18DchJGBuZEBx8K7qoxZBi2rBNk0tyNZml5zE69on5tp4IFio8xN9i4/dfkQN+8NGtvuUQGfr7sIth0HQLTabmk2uOkYJh32cBI1Yps8C4Hr4Mp4AqB6xvC73nrPzO9Q3Y1ibvLdx+vCcx3Z2Vx9xoMbXnPT/ETQ991WgxvJ3CzBChpI79P10XowN4By8Gt621/74LnS399ybIBbjg0ayY7zIJ6fyyxTg6OM97/+djx867Gp3/ENspw2J3JihNtibnozmJuopqGAZJ+4CcOUPjddyVnSY2t9V61DJZ06kqVpNTfEyK1ywklHW/Iq13Ekc/Oa2483tt2jAj5GuR08j5QgsTU3FpURaMxNkiQYTuJOZGmeKyRz02QQQI5pep+bfkMBm+cIOFqgxAd8LktrYx7oeY6s72mTuemkz400FFD72ux5ePry4UrX3AAqYGuDuZmF973udvyhR81FtPOizPlNMTerN+E8cG53ZsNQkyynbeYGaN5QgEBsvIm5SZIESU1ZGqC08QSTSYEKOLqouWkvydQ1SJbWVXF6kFlBJ0kCIYQyFFjhMVkHfzabPC0vY32f3R+uJ3PDGjd3IUujZ87W3FhURqAxN/SzC/rPdx0MQ1qkN7ddyi5TPQdNBk3W3OgaWjfndrR4n5sq6Psurg3bMxTots9NvmkiAGz23LTmJmrPercL0HPXRs3NLLiOgOs087xLu25HYFNzCARWM7ipAm6BDaT1N20G2zSmtCdLK3dLo3ik7kKlEBAmxSRJl1bQXSZq2gblf7q0gk4S1d+JSJxVTjjpaMtQwHWEZL3OrWNw01Lz0zLQPlbZCno9Z8kjDMoSEnMzmqQ/u4iQA9eR+2tyYCFHJwrQmuxzA6Q0rB4o+TnmxmE1Ny0EN56L65lbWhtZNFm42kWvo1JZWrTyzI2UpbXQxLNLKHmdnwvWu5bJdA3dLaor5qatzHzgpmYkJrc0VSxebx/HNn1cvKb6vcQGJ0xlz1xvX1VAY9gKDyMSTsfJBKrtoWCVmrOuAwtGyFlBN/iQ8O3efGy9g5su5mhKugyC1Q0RVvfIVxRSlhalEx71aulC2+i7QrmlNSlLo5qb7AW8/eQWTm4FuO3ERiPb9x2nUJPk6jU3bnuytL7vYJgFha0yNx2wJvT8cXvTrZ6ram5WeOG8TFlak6CM/452Hk7Li/Flg3doT5Ika27cbs0N0B5zI4RA33ONwU1TkqO7Tm3hiQvX5L9NAWEXjTUJXUrg2obXcTKBxi9KfFIAvA4sGIEn8JpmbgjrKEvjY34XMkUrS7OYG1KqkC2WaeLrwnIv55bW4AtCMiBaON9+chMf+3NvbWz7riMKLJCnMzfZAqWNF59LBlupuZFNPLurufE05uZwEsF3xUozN7QIWYYsrUn0JAOVPw93hWtuqiDwlFsUybbafB4Vc9Pe2NvznRJZWjML17tOb+E//c4LMqgJ46JJQbc1N8QSre44QujSxRLgic8suCHp4gqPyTryVtAtMTdrGNzQ3NbV/CwNBawszaIq9AGMamC6aeI5f5+bKtDd0ppGz3ew2dMNBdS+As9hfW5a2H/L3YG7dDOiIFCvuQGAa6NwpSdSev52Vzy4ocW27vomF1sr6JZWBdwtLcwkOW0+j20zNwBKmZumZGl3nd7CKIzx9KVDAGnQVGRu0vPrYo1OgdUKl+5JdG3gQWw6vQNRB+9A18hbQTe3XZJ2n9gMOnGe7Ro0t3X1LMxqWr0KsMxNxwgKzA3V3HQgSWqpERS5pfVaWnT9z+96WaF5Ys4Kuu2aG79Y1N0kuswQkukDl1qQZXecrHbxqu86cB2B7d5qD2s0oejyuvPHBzi+GeC2483IPY8afNfBOEtXd2GDq9zS2nvvekzSykHMVN3x6q7Tad+lz1+4iltPbBjr5ro0FKBxea1kaV4350Ljvwpu0s/XgQUj8Hm7yfOie7WO9TaAeja6Cm4oBrWyNIvK6OnMDdXcdED/+Tm9a3PbPX98Az3Pwa0tLboeMfTHyDfx5H1umt9/PydLa34htOw+N1ssGFh1t7Tdgb/yC6ugpHbolmMb+M0/35zc86gh8BxMQmJu2q83oCxym32D+p6LUWiouWno/O46tQ0AeOLCNbz5pWcQJ0mBladxxcrS5kPXNW7F4Ga9mZsmn0e6RusoSQO6D25Unxsb3FhUBA2UJA+j4KYrK2hCk7K009t9fOovv73TWgBefJ+6pbXYxNNrh/GS23SKAUdbMLultctMdYVB4OL45mo7pQF5t7QbCYHrSIMVkm21+U603ecGyJuRcERkKFBzPNnd8HFyqydNBaI4KYxRNNZ3MTy7TntJpq7RdY2b3iZCMjfrcDEzeC018aTtrqMNNJBvD9AFaMzooha8LdjgpmMIIbJ+Dukk3rWhAKHpRXrXRc46c6NqbtqVpbXhJtZlzY0KbtS+NnPMzepOpN/11ntw5XCy7MOoja2+B98VuGm3v+xD6RS+K7A/7LDmJnsH2mRuei27pQHAXac38cRFFdyUMTedyNI63FfboLG+u5obzQo6aaYu6yghZwVtmZvKoPm6e+ZmdZUcNrhZAnqucgXqtObG48xN67trFTwD5LtCMl9tvPtck99mzU0XbmnHNwN4jsCp7Z78bF2YmztPbS37EBrBTt/Hv/yON+AlJzaXfSidwmfjIjE361BzczVrAMwRN1hPcffpbfw/n3gaSZIgipPCYnwZTTy7sKttG3RvuhiXAbMszXXEystsObhLp2jwtbM1N81CNvG0zI3FPOCduGXNTSfMDa+5We0Bk2t3e67L+ty0y9y0sf0uO8+f3u7jV7/vcZxmwU2u5maF+9ysE+45s73sQ+gcgefIWkQyFOjELa3NmhvfxcWro8LnTWbl7zq9havDEBevjhAlCfpHgrlpfVeto+0mrzpofp4wWdo61C5xtMfcpPdofZkbkqV18yzSWLHKVtA2uFkCeh5nbroMbtq1NO4S/Ph9T6g+N60YCrTM3HTsYX9mJy932mDBzSozNxarjSBnBZ0xNy0G23Lx2qosraTPTdykLI0c064hNjTx7LIOpkuWqG103eeGLN5HEfV6SlZeYaEj1+emwWfksXtP4TvefDdeetNOY9s8SpDJ246eB8XcrO4DaIObJYA3qxuG3cnSvBZrbroGHyS5FfQq19x0lZXRsRm06wZnYVEFvutgEmb1Bpluq813grbdrqGAi9G0mpsGxisKbp64cA2Rsc9Nd1IxuqbrJEvzO2KzZc1NqNjLZc0JbYEnK5o8tZNbPXz3W+9pboNHDKqJZ0fMDQU3K9wzaL3enBVBj9mDHo67s4IO2MCy6jpe1U8hzTK06ZbW68gtrSttt46NwDI3FstHTpa2JjU3fd+RCSyOSFpB19/H6e0eBr6LL71wgCgujoFOh2wKrb3WYRih69ZV01xiEMlQIE6StbiOHPkmnmt2ci2CnsHuDAXSn6ssS7PBzRKQZ24iBJ7TSaZrnWRpskeF60gHOqAlQ4Fcn5s2a26Wc08Cz5FZw1V/LixWFylzs141N+VuaenPJhZ4Qgic3e3jwtVhVoSe/32XdTCSuVmDhStdt+X1uUlyaot1QFs1N+sOaSjQ0TVzHQFHLG9N0gTW681ZEXBDgdEkzvVRaRP54KaTXbYGXS/fap8bv103MXfJsjQA2Oi52TGs7mBmsdrwPVFkbjqouWm7z42x5qZBWRqQsjcX9kdpn5tCzc0S3NLWYOHaec1N9qzzd2AdriMHD9bWQbrYFXpdMzeOQN93V1rhs+JL3NWEbijQld1eronnCj+0gJoIKKumam6a31euiWcLg4vU0y4xS7KZSdMsc2OxLPSYoYDqzt5izU0HfW76nosoTuR5EZQsrZn37cxOH89dHSJOimN7tzU36xPc0Dl0NS7Tc0hrg9QcopNddwa6lnaamQ/LsIJeZRtowAY3S4FuBd3VQxR47TiVLAMF5sZvn7lxRDu1Sm956Rn82a9+6VJtLDeJuVlhGtpiteG7DuIECKNYytL8FidzGiva7nMDoCBNa5q5ObPTw3P7w1TKpDM3HS4oHUdAiPVYvHpaAq1tBLosLVlDQ4EOG1avE7oObhwhOlMUtYXVPvoVxWbg4WCcNnY7nESd2e2tY82N7+qytOb3Rdtua6I5sdXDB954x1Ip4A3J3NghwWI58FlBddPMhgmeliBpA5QY0aVp1MSzqdM7s9PHcBLj0sG4wNB0zaZ4jlj5+QVQ16s7WVqx5mbdhmOaQ1dZ7rQM+B23i3AdsdJOaYANbpaCnYGHK4dpcDOcxBhYWdrc0CUltDhvowBTMjdr/LZs2pobiyWDxqdxFHdUc5NPjLQB2rbO3FATzyZlaQBwdRgWio7p310FHG974Cweue1YJ/tqE10bvajghuzQk7Uruqf3ed3Oq22oPjfdXLetnoe9gd/JvtqC7XOzBOwMfOwPJwDSSa+3lOCmk122BjXxpOd0fDPAD733Ebz+rpON74uCm3WTCHBs2JobiyWD1xyEXdTcZAxDm45UNHYMJxpzkzTXxBPIN+Yta+LZ1Xryh977SDc7ahnbfR+OALb63SyTpKFAqJibdRuPu3TuWyf4Uj3SzYX7c19zv3wOVxU2uFkCdvo+xmGM4STCMIyx21GEHKyRLM3UXfxrXnFTK/si2eCqX7Np2OplzNcan6PF0Qb14ZqwmptW+9y4ovV6CjI6ob5mhDhuvuaGUJClyZob+27Pg7c9cAb/7x9/PU5v92d/uQEIkT6P42idg5v1afLaJbquuTm7280z3ybWNxV9hLGTBTP7hxOMJlF3VtDcUGDFBxd62YMOJAO0QFm3iYZjI1j/c7Q42uA1B1EHsrRjGz6ObwatbR9Qi4S/8M8+jScuXJWfy5qixqygGXOjy9KoiNsGN3PBdx08cG63430K2espStbRCtoG2ouAWD07P1eHDW6WAGJq9oeTzFCge1naqk90JuamLdwIzM2mZG7skGCxHORlae0zN3/ssbvwc3/0K1rbPgA8dH4PP/DuB/E7F6/h9/7gr+Li1REA1sSzoddtELjY6ZulpXQNV3zIvyHge47WxHO9bpp1S1sMxDBbZUV12JXMEkCT0JXDCYaTqDNDgWCdDAU6bLCmam5W+5pNg+1zY7FscEMB5ZbW3vu91fM6sV///Y/cgr/9nodxOInwxIVrAJq3ggZU3c0ym3ha1IPvOhivtaFAey0b1hldy9LWATa4WQIkc3MYYjiJO7OC5lmgVU/Qe1KW1v6JKJvp9R1YbJ8bi2UjYG5RlL1el4TCuSyIunB1CKD5Jp6AksCVMTd2YXT0EbiqwXecrGHNjW3iuRDIUGDdnoc2seJL3NUE1dwQc7MUWdqKvyR0/H4HsjQhBHqes9YLf+uWZrFsBF6x5mZdnkcKPJ69kgY3bTA3VHejb9Nx7IJyVRAwWVoYrWFwYwPthRBI5sYu2aui1pUSQvxBIcSnhRCxEOJV2u/+jBDiCSHE54QQb693mOuFnb4KbkZhvBQr6FWnu2mQ7HXUYK3nOWs9INs+NxbLhpSlhd30uekSWz0Pm4GL5/ap5oaCm+b2QY5p+pCoam7W41quM3xXqJqbdTQUcNZfBdEGbM3N/Ki7MvwUgN8P4D/yD4UQ9wN4D4AHALwDwA8LIVa73WmD2BmkWXIqLu1KlsYlXKs+0dGip6vu0X3fXfmAcBruPbuN09s93LTbfg2ChYUJss8Hd0tbo0zlmZ0+ntsnWVr6WZMJE1lzU3BLs5KWVYHvKuYmXmNDgTV6rTsBOd3aoLA6avW5SZLks4BxofwuAD+TJMkIwBeEEE8AeA2A/1xnf+uCnuei7ztyouvKUIB3Wl71iY4WPV24pQFZcLPi12wa7ju7g4/+2bcs+zAsbmBIWRpjbtbpnePBTTuGAsTc5MdE2zhxdcANBcI4wWDNFrOOI+AIu0ifF75lbuZGWyvDmwE8yf79VPZZAUKIDwohPiaE+NjFixdbOpyjh92Bj+ckc9NNcOM6QtqBrjoLQe94d8zNetfcWFgsGwFzSwvXzFAASIOPZym4abiJJwCclm5p+c9dK0tbGQSeg3HW8HUdDQWANDG56uuPriFrlewapDJmrgyFEP9OCPEpw3/vauIAkiT5kSRJXpUkyatOnTrVxCZXAjt9Hxeyia4rWZoQQgYDqz62CCGwGbjY6tciHyuj5623LM3CYtngTTzXkrnZ7ePC/ghJkiBKWnBLy4IbvUGzXBjZ8evII3AdTIi5iZK1Cu4JnitWvol41xBCIHBtUDgPZq4MkyRZRKvyNIDz7N+3ZJ9ZZNgZ+PjC89cBAH2vu3Iksppch0XDT77/NXjJic1O9tX3HVkHYGFh0Tx8KUtL5LvWFTPbBc5s9zGOYlw+mMgmnk2e3untHh694zhefvNu7nPH1jmsDHxXYH+orKDXUb7lZtI0i/kQrLmpUdNoK+39zwH8lBDiBwCcA3A3gI+2tK+VxO7Ax4vXxwC6k6UBqu5mHV6SV952vLN9vem+05iENrixsGgLJEsbMeZmDYYpCSr4f3Z/KGVpTUrFPNfBz3zwK4qf2yaeKwOf9bmJ4vWUpfmuY5/FBfAX3nk/XqYlLizKUSu4EUJ8HYAfBHAKwL8UQnwiSZK3J0nyaSHEzwH4DIAQwIeSJInqH+76YIfJqboNbqwV4yL4Hx+7a9mHYGGx1pBNPMMYURzDc8Ra1Ymc3U0L/p/bH6o+Ph2cn2uDm5UB73OzrsGN5wj7LC6Ad7/6/OwvWUjUdUv7CICPlPzu+wF8f53trzN2s0aeQHc1NwAPbjrbpYWFhcVMkN3pJIrXsoEhNdl8bn8oF3ddnKPtLbI6CFwHY9bnZt3eASANbtbxvCyOFqwKd0nYyQU3HdbceLbngYWFxdFDoDXxXLdi6tM7xNyMpBV0F/GGYm7a35dFPfiuI+XPUZysZQG55zr2WbRoHTa4WRJ2lxTcqCZadnSxsLA4OiCr+knWxNNbIzMBIHVcPL4Z4Nn9YStNPMtAFvZ2zD/68D1xY8jS1vC8LI4W1mv2WCHs9JcrS1vHjJCFhcXqgqzqx1GCMKu5WTec2enjwv5QMje25saCw+eytHUNblxh1x8WrcMGN0vCzkCVOw26NBTwrP7awsLiaKLnOpK5WceFHTXyVLK09s/x2EaQ/fRnfNNi2UibeCor6HV8B1zHuqVZtI9uOiBaFLC0mhspUehslxYWFhaV4GeLu8maNjA8s93Hp393X1pBd7F4vf3kJn7lT70JtxwbtL4vi3oIXOWWFq5pgO+7wq4/LFqHDW6WBC5L63lWlmZhYWHhu0IxN+76jVFndvt4/tpINnDuahw+f3yjk/1Y1IPvOoiTVJIWxevZxNO6pVl0ARvcLAlkKNDznE57Odg+NxYWFkcVVHMQxgn8NUzv3np8A0kC/MR//hIC10Gvw3pLi6MPmp+lqcYaBgEfetNda2cWYnH0YIObJYFkaV1K0gAW3KzhoGlhYbHaoJqDda03eNdD53BuN+13c9PeoPPx3+Jog1o1jNe47uzNLz2z7EOwuAFgg5slYbvnQYhundIAIPAsJWxhYXE0EbgOhpMIjljPccp3HXzlXSeXfRgWRxRUE0sBvk1CWlgsBssNLgmOI7Dd8zp1SgPSydXW21hYWBxFnD++gS88fz1t4rmGNTcWFtPAZWnr2MjWwqIr2OBmidgZ+EuRpdnYxsLC4ijivrPb+OILB7g+CuGuYc2NhcU0UHAzDmMkia2NtbBYFHb2WCJ2Bz56y2BubDbIwsLiCOLes9uI4gSfe+4qfDtOWdxgoD50w0lqB23naguLxWBrbpaIe85sI8mauXWFwHYHtrCwOKK47+w2AODywcQu7CxuOAQZc3M4iQDY4MbCYlHY4GaJ+IF3P9j5Pr/2oXM4t2ebuVlYWBw93HZiE0FmB21rbixuNARe+swPbXBjYVELNrhZIrrsb0N45W3H8crbjne+XwsLC4tZ8F0Hd57ewmef2bc1NxY3HHyNubGGAhYWi8HOHhYWFhYWRwYkTbMLO4sbDRTcDMdpcGMNBSwsFoMNbiwsLCwsjgzuzYIbK8mxuNFATTyHoZWlWVjUgQ1uLCwsLCyODCi48W3NjcUNBjIUuDaywY2FRR3Y4MbCwsLC4sjgPsnc2OnJ4sYCmf184eJ1ADa4sbBYFHb2sLCwsLA4Mji708fuwLfMjcUNh+ObAU5t9/CZZ64AgG3bYGGxIKxbmoWFhYXFkYEQAh/+hgdx0661rLe48XDf2W381pOXAVjmxsJiUVjmxsLCwsLiSOHx+87gpTftLPswLCw6xz1ntrE/DAHY4MbCYlHY4MbCwsLCwsLC4gjg3jPb8v8dG9xYWCwEG9xYWFhYWFhYWBwBkFsgYHs9WVgsChvcWFhYWFhYWFgcAdx9ZgvkI2CbeFpYLAYb3FhYWFhYWFhYHAFsBB5uPb4BwNbcWFgsChvcWFhYWFhYWFgcEdyT1d1YWZqFxWKwwY2FhYWFhYWFxREBmQpYQwELi8VggxsLCwsLCwsLiyMCMhWwTTwtLBaDDW4sLCwsLCwsLI4I3njPKbzn1efxivO7yz4UC4uVhLfsA7CwsLCwsLCwsEixO/DxV//AK5Z9GBYWKwvL3FhYWFhYWFhYWFhYrAVscGNhYWFhYWFhYWFhsRawwY2FhYWFhYWFhYWFxVrABjcWFhYWFhYWFhYWFmsBG9xYWFhYWFhYWFhYWKwFbHBjYWFhYWFhYWFhYbEWsMGNhYWFhYWFhYWFhcVawAY3FhYWFhYWFhYWFhZrARvcWFhYWFhYWFhYWFisBWxwY2FhYWFhYWFhYWGxFrDBjYWFhYWFhYWFhYXFWsAGNxYWFhYWFhYWFhYWawEb3FhYWFhYWFhYWFhYrAVEkiTLPgYJIcRFAF9a9nEwnATw/LIP4gaHvQfLh70HRwP2Piwf9h4sH/YeLB/2HhwN3Oj34bYkSU6ZfnGkgpujBiHEx5IkedWyj+NGhr0Hy4e9B0cD9j4sH/YeLB/2Hiwf9h4cDdj7UA4rS7OwsLCwsLCwsLCwWAvY4MbCwsLCwsLCwsLCYi1gg5vp+JFlH4CFvQdHAPYeHA3Y+7B82HuwfNh7sHzYe3A0YO9DCWzNjYWFhYWFhYWFhYXFWsAyNxYWFhYWFhYWFhYWawEb3BgghHiHEOJzQognhBDft+zjuVEghPiiEOKTQohPCCE+ln12XAjxb4UQn89+Hlv2ca4bhBA/KoS4IIT4FPvMeN1Fir+dvRv/VQjxyPKOfH1Qcg/+khDi6ex9+IQQ4qvZ7/5Mdg8+J4R4+3KOer0ghDgvhPhlIcRnhBCfFkL8iexz+y50hCn3wL4LHUII0RdCfFQI8VvZffjL2ee3CyF+LbvePyuECLLPe9m/n8h+/5KlnsAaYMo9+HEhxBfYu/BQ9rkdjxhscKNBCOEC+CEAvwfA/QC+UQhx/3KP6obCm5IkeYjZG34fgF9MkuRuAL+Y/duiWfw4gHdon5Vd998D4O7svw8C+LsdHeO648dRvAcA8OHsfXgoSZKfB4BsPHoPgAeyv/nhbNyyqIcQwPckSXI/gEcBfCi71vZd6A5l9wCw70KXGAF4PEmSBwE8BOAdQohHAfw1pPfhLgCXALw/+/77AVzKPv9w9j2Leii7BwDwvexd+ET2mR2PGGxwU8RrADyRJMl/T5JkDOBnALxrycd0I+NdAH4i+/+fAPD7lnco64kkSf4jgBe1j8uu+7sA/GSS4r8A2BNC3NTJga4xSu5BGd4F4GeSJBklSfIFAE8gHbcsaiBJkmeSJPnN7P+vAvgsgJth34XOMOUelMG+Cy0ge6avZf/0s/8SAI8D+CfZ5/q7QO/IPwHwZiGE6OZo1xNT7kEZ7HjEYIObIm4G8CT791OYPrhaNIcEwL8RQvyGEOKD2WdnkiR5Jvv/ZwGcWc6h3XAou+72/egW355JDH6USTLtPWgZmazmYQC/BvsuLAXaPQDsu9AphBCuEOITAC4A+LcAfgfA5SRJwuwr/FrL+5D9/gqAE50e8BpCvwdJktC78P3Zu/BhIUQv+8y+Cww2uLE4Snh9kiSPIKVXPySEeCP/ZZJa+1l7v45hr/vS8HcB3IlUkvAMgL+51KO5QSCE2ALwTwF8Z5Ik+/x39l3oBoZ7YN+FjpEkSZQkyUMAbkHKht233CO68aDfAyHEywD8GaT34tUAjgP408s7wqMLG9wU8TSA8+zft2SfWbSMJEmezn5eAPARpAPqc0StZj8vLO8IbyiUXXf7fnSEJEmeyya3GMDfg5Lb2HvQEoQQPtJF9T9OkuT/zj6270KHMN0D+y4sD0mSXAbwywC+AqnUyct+xa+1vA/Z73cBvNDtka4v2D14RybdTJIkGQH4Mdh3wQgb3BTx6wDuzlxBAqTFiv98yce09hBCbAohtun/AbwNwKeQXvs/nH3tDwP4Z8s5whsOZdf9nwP4lsyZ5VEAV5hkx6JBaHrpr0P6PgDpPXhP5lB0O9IC0o92fXzrhqxG4B8A+GySJD/AfmXfhY5Qdg/su9AthBCnhBB72f8PALwVaf3TLwP4+uxr+rtA78jXA/ilxDZRrIWSe/DfWKJFIK154u+CHY8yeLO/cmMhSZJQCPHtAH4BgAvgR5Mk+fSSD+tGwBkAH8lqED0AP5Ukyb8WQvw6gJ8TQrwfwJcAvHuJx7iWEEL8NIDHAJwUQjwF4C8C+KswX/efB/DVSAt3DwC8r/MDXkOU3IPHMpvPBMAXAfwPAJAkyaeFED8H4DNI3aU+lCRJtITDXje8DsA3A/hkpnMHgP8J9l3oEmX34Bvtu9ApbgLwE5nznAPg55Ik+RdCiM8A+BkhxP8K4ONIA1FkP/+hEOIJpMYo71nGQa8Zyu7BLwkhTgEQAD4B4I9m37fjEYOwwbWFhYWFhYWFhYWFxTrAytIsLCwsLCwsLCwsLNYCNrixsLCwsLCwsLCwsFgL2ODGwsLCwsLCwsLCwmItYIMbCwsLCwsLCwsLC4u1gA1uLCwsLCwsLCwsLCzWAja4sbCwsLCwsLCwsLBYC9jgxsLCwsLCwsLCwsJiLWCDGwsLCwsLCwsLCwuLtcD/Dy8fHgreYm/yAAAAAElFTkSuQmCC\n", "text/plain": [ "<Figure size 1008x432 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig = plt.figure(figsize=(14, 6))\n", "\n", "plt.plot(prediction2, label='prediction only')\n", "plt.legend()\n", "plt.show" ] }, { "cell_type": "markdown", "id": "f91d8f47", "metadata": { "papermill": { "duration": 0.028552, "end_time": "2022-10-27T19:24:05.264150", "exception": false, "start_time": "2022-10-27T19:24:05.235598", "status": "completed" }, "tags": [] }, "source": [ "Predicting based on information you already have and being unable to extrapolate it into the future isn't ideal. The shame envelops me in a cloud of doom. Which also funnily enough describes the weather today." ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.12" }, "papermill": { "default_parameters": {}, "duration": 18.151182, "end_time": "2022-10-27T19:24:06.113303", "environment_variables": {}, "exception": null, "input_path": "__notebook__.ipynb", "output_path": "__notebook__.ipynb", "parameters": {}, "start_time": "2022-10-27T19:23:47.962121", "version": "2.3.4" } }, "nbformat": 4, "nbformat_minor": 5 }	0109/325/109325493.ipynb	s3://data-agents/kaggle-outputs/sharded/011_00109.jsonl.gz
{ "cells": [ { "cell_type": "markdown", "id": "068eb183", "metadata": { "papermill": { "duration": 0.013516, "end_time": "2022-10-27T19:25:52.276751", "exception": false, "start_time": "2022-10-27T19:25:52.263235", "status": "completed" }, "tags": [] }, "source": [ "# Introduction" ] }, { "cell_type": "code", "execution_count": 1, "id": "532eeaf5", "metadata": { "_kg_hide-input": true, "_kg_hide-output": true, "execution": { "iopub.execute_input": "2022-10-27T19:25:52.302784Z", "iopub.status.busy": "2022-10-27T19:25:52.302179Z", "iopub.status.idle": "2022-10-27T19:26:06.699856Z", "shell.execute_reply": "2022-10-27T19:26:06.698244Z" }, "papermill": { "duration": 14.414317, "end_time": "2022-10-27T19:26:06.702969", "exception": false, "start_time": "2022-10-27T19:25:52.288652", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Collecting textstat\r\n", " Downloading textstat-0.7.3-py3-none-any.whl (105 kB)\r\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m105.1/105.1 kB\u001b[0m \u001b[31m1.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\r\n", "\u001b[?25hCollecting pyphen\r\n", " Downloading pyphen-0.13.0-py3-none-any.whl (2.0 MB)\r\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.0/2.0 MB\u001b[0m \u001b[31m8.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\r\n", "\u001b[?25hInstalling collected packages: pyphen, textstat\r\n", "Successfully installed pyphen-0.13.0 textstat-0.7.3\r\n", "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\r\n", "\u001b[0m" ] } ], "source": [ "!pip install textstat" ] }, { "cell_type": "code", "execution_count": 2, "id": "9d7d3131", "metadata": { "_kg_hide-output": true, "execution": { "iopub.execute_input": "2022-10-27T19:26:06.732022Z", "iopub.status.busy": "2022-10-27T19:26:06.731512Z", "iopub.status.idle": "2022-10-27T19:26:18.834540Z", "shell.execute_reply": "2022-10-27T19:26:18.833159Z" }, "papermill": { "duration": 12.121137, "end_time": "2022-10-27T19:26:18.837550", "exception": false, "start_time": "2022-10-27T19:26:06.716413", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Collecting featdist\r\n", " Downloading featdist-0.1.3-py3-none-any.whl (5.9 kB)\r\n", "Requirement already satisfied: numpy in /opt/conda/lib/python3.7/site-packages (from featdist) (1.21.6)\r\n", "Requirement already satisfied: pandas in /opt/conda/lib/python3.7/site-packages (from featdist) (1.3.5)\r\n", "Requirement already satisfied: matplotlib in /opt/conda/lib/python3.7/site-packages (from featdist) (3.5.3)\r\n", "Requirement already satisfied: fonttools>=4.22.0 in /opt/conda/lib/python3.7/site-packages (from matplotlib->featdist) (4.33.3)\r\n", "Requirement already satisfied: packaging>=20.0 in /opt/conda/lib/python3.7/site-packages (from matplotlib->featdist) (21.3)\r\n", "Requirement already satisfied: python-dateutil>=2.7 in /opt/conda/lib/python3.7/site-packages (from matplotlib->featdist) (2.8.2)\r\n", "Requirement already satisfied: cycler>=0.10 in /opt/conda/lib/python3.7/site-packages (from matplotlib->featdist) (0.11.0)\r\n", "Requirement already satisfied: pillow>=6.2.0 in /opt/conda/lib/python3.7/site-packages (from matplotlib->featdist) (9.1.1)\r\n", "Requirement already satisfied: pyparsing>=2.2.1 in /opt/conda/lib/python3.7/site-packages (from matplotlib->featdist) (3.0.9)\r\n", "Requirement already satisfied: kiwisolver>=1.0.1 in /opt/conda/lib/python3.7/site-packages (from matplotlib->featdist) (1.4.3)\r\n", "Requirement already satisfied: pytz>=2017.3 in /opt/conda/lib/python3.7/site-packages (from pandas->featdist) (2022.1)\r\n", "Requirement already satisfied: typing-extensions in /opt/conda/lib/python3.7/site-packages (from kiwisolver>=1.0.1->matplotlib->featdist) (4.3.0)\r\n", "Requirement already satisfied: six>=1.5 in /opt/conda/lib/python3.7/site-packages (from python-dateutil>=2.7->matplotlib->featdist) (1.15.0)\r\n", "Installing collected packages: featdist\r\n", "Successfully installed featdist-0.1.3\r\n", "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\r\n", "\u001b[0m" ] } ], "source": [ "!pip install featdist" ] }, { "cell_type": "code", "execution_count": 3, "id": "64e4c82c", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:26:18.869245Z", "iopub.status.busy": "2022-10-27T19:26:18.868773Z", "iopub.status.idle": "2022-10-27T19:26:31.357284Z", "shell.execute_reply": "2022-10-27T19:26:31.356073Z" }, "papermill": { "duration": 12.50924, "end_time": "2022-10-27T19:26:31.360307", "exception": false, "start_time": "2022-10-27T19:26:18.851067", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "import pandas as pd\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "import seaborn as sns\n", "import gc\n", "import warnings\n", "import datetime as dt\n", "import math\n", "\n", "from featdist import numerical_ttt_dist\n", "import re\n", "import spacy\n", "import textstat\n", "\n", "from sklearn.feature_extraction.text import TfidfVectorizer\n", "\n", "np.random.seed(0)\n", "warnings.simplefilter(\"ignore\")" ] }, { "cell_type": "code", "execution_count": 4, "id": "41e71f7d", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:26:31.391257Z", "iopub.status.busy": "2022-10-27T19:26:31.389564Z", "iopub.status.idle": "2022-10-27T19:26:32.231304Z", "shell.execute_reply": "2022-10-27T19:26:32.229891Z" }, "papermill": { "duration": 0.859944, "end_time": "2022-10-27T19:26:32.233869", "exception": false, "start_time": "2022-10-27T19:26:31.373925", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>text_id</th>\n", " <th>full_text</th>\n", " <th>cohesion</th>\n", " <th>syntax</th>\n", " <th>vocabulary</th>\n", " <th>phraseology</th>\n", " <th>grammar</th>\n", " <th>conventions</th>\n", " <th>POS</th>\n", " <th>LEMMA</th>\n", " <th>...</th>\n", " <th>difficult_words</th>\n", " <th>linsear_write_formula</th>\n", " <th>gunning_fog</th>\n", " <th>text_standard</th>\n", " <th>fernandez_huerta</th>\n", " <th>szigriszt_pazos</th>\n", " <th>gutierrez_polini</th>\n", " <th>crawford</th>\n", " <th>gulpease_index</th>\n", " <th>osman</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>0</th>\n", " <td>0016926B079C</td>\n", " <td>I think that students would benefit from learn...</td>\n", " <td>3.5</td>\n", " <td>3.5</td>\n", " <td>3.0</td>\n", " <td>3.0</td>\n", " <td>4.0</td>\n", " <td>3.0</td>\n", " <td>PRON VERB SCONJ NOUN AUX VERB ADP VERB ADP NOU...</td>\n", " <td>I think that student would benefit from learn 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"output_type": "display_data" }, { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>text_id</th>\n", " <th>cohesion</th>\n", " <th>syntax</th>\n", " <th>vocabulary</th>\n", " <th>phraseology</th>\n", " <th>grammar</th>\n", " <th>conventions</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>0</th>\n", " <td>0000C359D63E</td>\n", " <td>3.0</td>\n", " <td>3.0</td>\n", " <td>3.0</td>\n", " <td>3.0</td>\n", " <td>3.0</td>\n", " <td>3.0</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " text_id cohesion syntax vocabulary phraseology grammar \\\n", "0 0000C359D63E 3.0 3.0 3.0 3.0 3.0 \n", "\n", " conventions \n", "0 3.0 " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "train = pd.read_csv(\"../input/advanced-dataset/fb3/train_fe.csv\")\n", "test = pd.read_csv(\"../input/advanced-dataset/fb3/test_fe.csv\")\n", "sub = pd.read_csv(\"../input/feedback-prize-english-language-learning/sample_submission.csv\")\n", "\n", "train[\"LABEL\"].fillna(\"NONE\", inplace=True)\n", "\n", "labels = ['conventions', 'grammar', 'syntax', 'vocabulary', 'phraseology', 'cohesion']\n", "stat_features = [\"flesch_reading_ease\", \"flesch_kincaid_grade\", \"smog_index\", \"coleman_liau_index\", \"automated_readability_index\", \n", " \"dale_chall_readability_score\", \"difficult_words\", \"linsear_write_formula\", \"gunning_fog\", \"text_standard\", \n", " \"fernandez_huerta\", \"szigriszt_pazos\", \"gutierrez_polini\", \"crawford\", \"gulpease_index\", \"osman\"]\n", "\n", "display(train.head(1))\n", "display(sub.head(1))" ] }, { "cell_type": "code", "execution_count": 5, "id": "40e81b54", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:26:32.264838Z", "iopub.status.busy": "2022-10-27T19:26:32.263731Z", "iopub.status.idle": "2022-10-27T19:26:32.272506Z", "shell.execute_reply": "2022-10-27T19:26:32.270763Z" }, "papermill": { "duration": 0.027388, "end_time": "2022-10-27T19:26:32.275543", "exception": false, "start_time": "2022-10-27T19:26:32.248155", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "train shape: (3911, 27)\n", "test shape: (3, 21)\n", "sub shape: (3, 7)\n" ] } ], "source": [ "print(\"train shape:\", train.shape)\n", "print(\"test shape:\", test.shape)\n", "print(\"sub shape:\", sub.shape)" ] }, { "cell_type": "code", "execution_count": 6, "id": "cd4d7906", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:26:32.307718Z", "iopub.status.busy": "2022-10-27T19:26:32.306900Z", "iopub.status.idle": "2022-10-27T19:26:32.321278Z", "shell.execute_reply": "2022-10-27T19:26:32.319582Z" }, "papermill": { "duration": 0.032989, "end_time": "2022-10-27T19:26:32.323720", "exception": false, "start_time": "2022-10-27T19:26:32.290731", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "train nan value sum: 0\n", "test nan value sum: 0\n" ] } ], "source": [ "print(\"train nan value sum:\", train.isna().sum().sum())\n", "print(\"test nan value sum:\", test.isna().sum().sum())" ] }, { "cell_type": "code", "execution_count": 7, "id": "c5ef7b0e", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:26:32.355125Z", "iopub.status.busy": "2022-10-27T19:26:32.354233Z", "iopub.status.idle": "2022-10-27T19:26:32.446239Z", "shell.execute_reply": "2022-10-27T19:26:32.444769Z" }, "papermill": { "duration": 0.110781, "end_time": "2022-10-27T19:26:32.449030", "exception": false, "start_time": "2022-10-27T19:26:32.338249", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "train dublicated value sum: 0\n", "test dublicated value sum: 0\n" ] } ], "source": [ "print(\"train dublicated value sum:\", train.duplicated().sum().sum())\n", "print(\"test dublicated value sum:\", test.duplicated().sum().sum())" ] }, { "cell_type": "markdown", "id": "52acf205", "metadata": { "papermill": { "duration": 0.013912, "end_time": "2022-10-27T19:26:32.477382", "exception": false, "start_time": "2022-10-27T19:26:32.463470", "status": "completed" }, "tags": [] }, "source": [ "# Exploratory Data Analysis" ] }, { "cell_type": "markdown", "id": "3eaa864d", "metadata": { "papermill": { "duration": 0.014047, "end_time": "2022-10-27T19:26:32.505833", "exception": false, "start_time": "2022-10-27T19:26:32.491786", "status": "completed" }, "tags": [] }, "source": [ "## Distributions" ] }, { "cell_type": "code", "execution_count": 8, "id": "cd85afad", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:26:32.536348Z", "iopub.status.busy": "2022-10-27T19:26:32.535968Z", "iopub.status.idle": "2022-10-27T19:26:34.056794Z", "shell.execute_reply": "2022-10-27T19:26:34.055458Z" }, "papermill": { "duration": 1.539105, "end_time": "2022-10-27T19:26:34.059391", "exception": false, "start_time": "2022-10-27T19:26:32.520286", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 1152x576 with 6 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "fig, axes = plt.subplots(2, 3, figsize=(16,8))\n", "for ax, label in zip(axes.ravel(), labels):\n", " sns.histplot(data=train, x=label, ax=ax, label=label);\n", " ax.legend()" ] }, { "cell_type": "code", "execution_count": 9, "id": "9b6f278c", "metadata": { "_kg_hide-input": true, "execution": { "iopub.execute_input": "2022-10-27T19:26:34.092537Z", "iopub.status.busy": "2022-10-27T19:26:34.092132Z", "iopub.status.idle": "2022-10-27T19:26:34.104647Z", "shell.execute_reply": "2022-10-27T19:26:34.103489Z" }, "papermill": { "duration": 0.032421, "end_time": "2022-10-27T19:26:34.107061", "exception": false, "start_time": "2022-10-27T19:26:34.074640", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "def plot_important_words(data=None, feature='', n_important=10):\n", " from sklearn.linear_model import LinearRegression\n", " \n", " vectorizer = TfidfVectorizer(stop_words=\"english\")\n", " X = vectorizer.fit_transform(data[feature])\n", " \n", " fig, axes = plt.subplots(6, 2, figsize=(16,3n_important))\n", " fig.suptitle(feature, fontsize=32, y=0.9)\n", " for index, label in enumerate(labels):\n", " model = LinearRegression().fit(X.toarray(), data[label])\n", " df = pd.DataFrame()\n", " df['word'] = vectorizer.get_feature_names_out()\n", " df['coef_'] = model.coef_\n", " df.sort_values('coef_', inplace=True, ascending=False)\n", " df.reset_index(inplace=True, drop=True)\n", " df_poz = df.loc[:n_important, :].copy()\n", " df_poz.sort_values('coef_', inplace=True, ascending=True)\n", " axes[index][0].barh(df_poz.loc[:, 'word'].values, df_poz.loc[:, 'coef_'].values)\n", " axes[index][0].set_title(label + ' pozitive')\n", " axes[index][1].barh(df.loc[df.shape[0]-n_important:, 'word'].values, df.loc[df.shape[0]-n_important:, 'coef_'].values)\n", " axes[index][1].set_title(label + ' negative')\n", " \n", " del X\n", " gc.collect()" ] }, { "cell_type": "code", "execution_count": 10, "id": "8a45e706", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:26:34.139311Z", "iopub.status.busy": "2022-10-27T19:26:34.138914Z", "iopub.status.idle": "2022-10-27T19:32:14.044502Z", "shell.execute_reply": "2022-10-27T19:32:14.042804Z" }, "papermill": { "duration": 339.943086, "end_time": "2022-10-27T19:32:14.065372", "exception": false, "start_time": "2022-10-27T19:26:34.122286", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 1152x2160 with 12 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plot_important_words(data=train, feature='full_text', n_important=10)" ] }, { "cell_type": "markdown", "id": "e02e80f5", "metadata": { "papermill": { "duration": 0.01681, "end_time": "2022-10-27T19:32:14.099671", "exception": false, "start_time": "2022-10-27T19:32:14.082861", "status": "completed" }, "tags": [] }, "source": [ "## Feature Engineering" ] }, { "cell_type": "code", "execution_count": 11, "id": "61bba371", "metadata": { "_kg_hide-input": true, "execution": { "iopub.execute_input": "2022-10-27T19:32:14.138816Z", "iopub.status.busy": "2022-10-27T19:32:14.137259Z", "iopub.status.idle": "2022-10-27T19:32:14.149677Z", "shell.execute_reply": "2022-10-27T19:32:14.148031Z" }, "papermill": { "duration": 0.035102, "end_time": "2022-10-27T19:32:14.152560", "exception": false, "start_time": "2022-10-27T19:32:14.117458", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "def add_new_features(df):\n", " def get_pos(text, model=None):\n", " # Create doc object\n", " doc = model(text)\n", " # Generate list of POS tags\n", " pos = [token.pos_ for token in doc]\n", " return pos\n", " def get_lemma(text, model=None):\n", " # Create doc object\n", " doc = model(text)\n", " # Generate list of lemmas\n", " lemma = [token.lemma_ for token in doc]\n", " return lemma\n", " def get_label(text, model=None):\n", " # Create doc object\n", " doc = model(text)\n", " # Generate list of all named entities and their labels\n", " label = [ent.label_ for ent in doc.ents]\n", " return label\n", " \n", " nlp = spacy.load('en_core_web_sm')\n", " \n", " df[\"POS\"] = ''\n", " df[\"LEMMA\"] = ''\n", " df[\"LABEL\"] = ''\n", " for index, text in df[['full_text']].iterrows():\n", " pos = get_pos(text.values[0], model=nlp)\n", " lemma = get_lemma(text.values[0], model=nlp)\n", " label = get_label(text.values[0], model=nlp)\n", " \n", " df.loc[index, 'POS'] = ' '.join(pos)\n", " df.loc[index, 'LEMMA'] = ' '.join(lemma)\n", " df.loc[index, 'LABEL'] = ' '.join(label)" ] }, { "cell_type": "code", "execution_count": 12, "id": "2bb3ac2b", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:32:14.190240Z", "iopub.status.busy": "2022-10-27T19:32:14.189834Z", "iopub.status.idle": "2022-10-27T19:32:14.195633Z", "shell.execute_reply": "2022-10-27T19:32:14.194312Z" }, "papermill": { "duration": 0.027889, "end_time": "2022-10-27T19:32:14.198283", "exception": false, "start_time": "2022-10-27T19:32:14.170394", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "'''\n", "add_new_features(train)\n", "add_new_features(test)\n", "\n", "end_mem = train.memory_usage().sum() / 10242\n", "print('Memory usage after optimization is: {:.2f} MB'.format(end_mem))\n", "''';" ] }, { "cell_type": "code", "execution_count": 13, "id": "8bcc7154", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:32:14.235761Z", "iopub.status.busy": "2022-10-27T19:32:14.235361Z", "iopub.status.idle": "2022-10-27T19:32:18.071627Z", "shell.execute_reply": "2022-10-27T19:32:18.070316Z" }, "papermill": { "duration": 3.858617, "end_time": "2022-10-27T19:32:18.074889", "exception": false, "start_time": "2022-10-27T19:32:14.216272", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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vmMRKkiRJkvqGSawkSZIkqW+YxEqSJEmS+oZJrCRJkiSpb5jESpIkSZL6hkmsJEmSJKlvrNvrAKaDgSMW9joESVKHlh+7f69D0CSwLpakzlgP2hIrSZIkSeojJrGSJEmSpL5hEitJkiRJ6hs9T2KTvCTJ9r2OQ5IkSZI0/fU8iQVeApjESpI0iZL8uIMyb0+yQdv6N5NsOqmBSZK0lsZMYpMMJLkmyalJliU5K8kGSZYn2bwpMy/Jomb5qCQnJVmU5NdJDm871+uT/CzJVUm+mOTpwIuB45NcmWSbSbpPSZJmtap6egfF3g78JYmtqv2q6o7JikmSpPHo9BM7TwLeVFUXJTkJ+Mcxym8HPAfYGLg2yWeAJwJHAk+vqluTPKqqbktyLvCNqjpruBMlmQ/MB5g7d26H4UqSpHZJ7q6qjZLsAxwF3ArsAFwGvBb4Z2AL4MIkt1bVc5IsB+ZV1a09CVqSpGF02p34xqq6qFk+Bdh7jPILq2p1U+n9L/Bo4LnAmYMVYVXd1smFq2pBVc2rqnlz5szpMFxJkjSKXWi1um4PPB54RlV9ArgZeE5VPWe0g5PMT7I4yeIVK1ZMerCSJLXrNImtYdbvbTt+vSH7V7ctr6HzFl9JkjT5Lq2q31TVfcCVwMDaHOwLZklSL3WaxM5Nslez/GrgR8ByYLdm28s7OMcFwIFJNgNI8qhm+120uh1LkqSp4ctmSVLf6jSJvRb4pyTLgEcCnwE+AHw8yWJaFeCoqmopcAzw/SRXAR9tdp0O/N8kVzixkyRJPeWLZUnStNfpm9d7q+q1Q7b9kNZkTQ9QVUcNWd+hbfkLwBeG7L8IP7EjSdJ0sAA4L8nNbeNihw4pkiSpp+w+JEnSLFBVGzV/LgIWtW1/a9vyCcAJAEnWodUqe+dUxilJ0ljGTGKrajmtKfglSdLssRT4XFXd0+tAJElqZ0sssPzY/XsdgiRJ00pVbdfrGCRJGk6nEztJkiRJktRztsRKkqSes1eUJKlTtsRKkiRJkvqGLbHAwBELex2CJE0LtoZJkqTpzpZYSZIkSVLfsCVWkiRJmkbsJajR2GvKllhJkiRJUh+ZsiQ2ySFJPjlV15MkSZIkzTy2xEqSJEmS+kbXktgk5yS5LMnSJPObbYcmuS7JpcAz2sqenOTEJIub/S/sVhySJEmSpJmrmxM7vbGqbkuyPvDTJAuBDwC7ASuBC4Er2soPAHsA2wAXJnlCVf2pi/FIkiRJkmaYbnYnPjzJVcAlwFbA64BFVbWiqv4MnDGk/Jer6r6q+gXwa2C74U6aZH7TYrt4xYoVXQxXkiRJktRvupLEJtkH2BfYq6p2otXies0Yh9UY662NVQuqal5VzZszZ85EQ5Ukqa8l2TDJwiRXJbk6yUFJlif5UJIlSS5N8oSm7IuS/CTJFUm+m+TRzfaNkny+Kf+zJC9vtv9tkouTXJ7kzCQb9fJeJUkaTrdaYjcBbq+qVUm2A/YE1geenWSzJA8FDhxyzIFJHpJkG+DxwLVdikWSpJns+cDNVbVTVe0AnNdsX1lVOwKfBP6j2fYjYM+q2gU4HXh3s/3fBstX1VOBC5JsDhwJ7FtVuwKLgXdMyR1JkrQWujUm9jzgsCTLaCWjlwC3AEcBFwN3AFcOOeZ/gEuBRwCHOR5WkqSOLAE+kuQ44BtV9cMkAKc1+08DPtYsPxY4I8ljgIcB1zfb9wUOHjxhVd3eTLK4PXBRc76H0arDH6SZwHE+wNy5c7t3Z5IkdaArSWxVrQZeMMyuRcDnRzjsu1V1WDeuL0nSbFFV1yXZFdgPODrJ9wZ3tRdr/jwB+GhVndsM/TlqlFMH+E5VvaqDGBYACwDmzZs37HAgSZImi9+JlSSpjyTZAlhVVacAxwO7NrsOavtzsAV1E+CmZvkNbaf5DvBPbed8JK1eVM9oG0+7YZInTspNSJI0Ad38xE7HquqQXlxXkqQZYEfg+CT3AfcAbwHOAh6Z5GfAamCwNfUo4MwktwMXAI9rth8NfCrJ1cAa4ANV9dUkhwCnJXl4U+5I4LrJvyVJkjrXkyRWkiSNT1V9G/h2+7ZmDOvxVfWeIWW/BnxtmHPczQNbZge3XwDs3s14JUnqNpNYYPmx+/c6BEmSJElSB0xiJUnqc1U10OsYJEmaKk7sJEmSJEnqG7bESpIkSdOIQ92k0ZnEAgNHLOx1CJJGYWUuSZKkQXYnliRJkiT1DZNYSZIkSVLfMImVJEmSJPWNnoyJTXJ3VW3Ui2tLkiRJ6j7nmZkazhUyxUlskgCZymtKkiRJkmaOcSWxSY4FbqyqTzXrRwF300pQXwk8HDi7qt6fZAD4NvATYDdgv+aYjwF/C/wWOLiqVkzoTiRJkiRJM954x8SeQStZHfRKYAWwLbAHsDOwW5JnNfu3BT5dVU+pqhuADYHFVfUU4PvA+8cZhyRJkiRpFhlXS2xVXZHkr5JsAcwBbgd2pNWyekVTbCNayev/ADdU1SVtp7iPViIMcArw1ZGulWQ+MB9g7ty54wlXkiRJkjRDTGRM7JnAK4C/ppWQbg38f1X1n+2Fmu7EfxjjXDXijqoFwAKAefPmjVhOkiRJkjTzTeQTO2cAB9NKZM+kNe71jUk2AkiyZZK/GuW6r2iWXw38aAJxSJKkIZKs0+sYJEmaDONOYqtqKbAxcFNV3VJV5wNfAi5OsgQ4q9k/nD8AeyS5Gngu8MHxxiFJ0myTZCDJNUlOTbIsyVlJNkiyPMlxSS4HDkzyqiRLklyd5Li24+9O8rEkS5N8L8mcZvui5vhLk1yX5Jk9u0lJkkYwoU/sVNWOQ9Y/Dnx8mKI7DCnnN2IlSZqYJwFvqqqLkpwE/GOz/fdVtWszb8UltL4McDtwfpKXVNU53D/B4v9J8j5aEyy+tTl+3araI8l+zfZ9h17Y+SokSb00ke7EkiSpd26sqoua5VOAvZvlwYkTdwcWVdWKqroXOBUY/GrA0AkWB4+F+ydbvAwYGO7CVbWgquZV1bw5c+ZM+EYkSVobJrGSJPWnoZMdDq6PNZniWOda3fy5hgn22JIkaTJYOQHLj92/1yFIkrS25ibZq6ou5v5JEndp238p8Ikkm9PqTvwq4IRm3+AEi6fjBIuSpD5jS6wkSf3pWuCfkiwDHgl8pn1nVd0CHAFcCFwFXFZVX2t2O8GiJKlv2RIrSVJ/ureqXjtk20D7SlWdBpw23MFV9Y5htu3Ttnzr0PNJkjQd2BIrSZIkSeobtsQCA0cs7HUIUlc5zlua2apqOUM+X7eWx/upO0lS37IlVpIkSZLUN2yJlSRJkjRh9gTTVLElVpIkSZLUN0xiJUmSJEl9wyRWkiRJktQ3HBMrSZIkSRMwlV87cezxBFtik2yYZGGSq5JcneSgJOe07X9ekrOb5buTHJ9kaZLvJtkjyaIkv07y4gnehyRJkiRpFphod+LnAzdX1U5VtQNwHrBdkjnN/kOBk5rlDYELquopwF3A0cDzgJcCHxzpAknmJ1mcZPGKFSsmGK4kSZIkqZ9NNIldAjwvyXFJnllVK4EvAq9NsimwF/CtpuyfaSW5g8d9v6ruaZYHRrpAVS2oqnlVNW/OnDkjFZMkSZIkzQITGhNbVdcl2RXYDzg6yfeAzwFfB/4EnFlV9zbF76mqapbvA1Y357gviWNzJUmSJEljmlDymGQL4LaqOiXJHcCbq+rmJDcDRwL7diFGSZI0xZJ8EPhBVX2317FIktRuoi2gOwLHJ7kPuAd4S7P9VGBOVS2b4PklSVIPVNX7eh2DJEnDmdCY2Kr6dlU9tap2rqrdq2pxs2tv4LNDym7UtnxUVX14uH2SJKlzSV6f5GfNlwK+mOTRSc5u1q9K8vSm3DuaLwlcneTtzbaBJMuSfLb5esD5SdZv9p2c5BU9vDVJkobV9bGoSS4D/gC8s9vnliRJ90vyFFrDd55eVbcmeRTwGVqTJ740yTrARkl2o/XFgKcBAX6S5PvA7cC2wKuq6u+TfBl4OXBKL+5HkqROTHR24gepqt2q6llVtbrb55YkSQ/wXFqTKN4KUFW3Nds+06yvab4csDdwdlX9oaruBr4KPLM5x/VVdWWzfBmjfDFgkJ+/kyT1krMCA8uP3b/XIUiS1CvtL53XAOuPdUBVLQAWAMybN6/GKC5JUld1vSVWkiRNmQuAA5NsBtB0J/4ezUSLSdZJsgnwQ+AlSTZIsiHw0mabJEl9x5ZYSZL6VFUtTXIM8P0ka4ArgLcBC5K8iVbL6luq6uIkJwOXNod+rqquSDIw1iUmKXRJksbNJFaSpD5WVV8AvjBk8wHDlPso8NEh25YDO7Stf7ht92bAbV0LVJKkLjGJBQaOWNjrEKRxcTy3pMmQ5CRgA+BHvY5FkqShTGIlSdIDVNUbex2DJEkjcWInSZIkSVLfMImVJEmSJPWNKe1OnOQQYF5VvXUqrytJkiRJk8V5SqaWLbGSJEmSpL7R1SQ2yTlJLkuyNMn8ZtuhSa5LcinwjGbbJkluSPKQZn3DJDcmeWg345EkSZIkzSzdbol9Y1XtBswDDk+yJfABWsnr3sD2AFW1ErgSeHZz3AuBb1fVPV2OR5IkSZI0g3R7TOzhSV7aLG8FvA5YVFUrAJKcATyx2X8GcBBwIXAw8OnhTti06M4HmDt3bpfDlSRJkqSpMXDEwgmfw/G3XWyJTbIPsC+wV1XtBFwBXDPKIecCz0/yKGA34ILhClXVgqqaV1Xz5syZ061wJUmSJEl9qJvdiTcBbq+qVUm2A/YE1geenWSzZrzrgYOFq+pu4KfAx4FvVNWaLsYiSZIkSZqButmd+DzgsCTLgGuBS4BbgKOAi4E7aI2DbXcGcCawTxfjkCRJkiTNUF1LYqtqNfCCYXYtAj4/wjFnAelWDJIkSZKkmc3vxEqSJEmS+oZJrCRJs0iSdXodgyRJE2ESK0nSDJFkIMk1SU5NsizJWUk2SLI8yXFJLgcOTPKqJEuSXJ3kuLbj705yTJKrklyS5NE9vB1JkobV7e/E9iW/tSRJmkGeBLypqi5KchLwj83231fVrkm2oDX54m7A7cD5SV5SVecAGwKXVNV7k3wI+Hvg6Km/BUmSRmZLrCRJM8uNVXVRs3wKsHezfEbz5+7AoqpaUVX3AqcCz2r2/Rn4RrN8GTAw3AWSzE+yOMniFStWdDt+SZJGZRIrSdLMUiOs/6GDY++pqsHyaxihx1ZVLaiqeVU1b86cOeMMU5Kk8TGJlSRpZpmbZK9m+dXAj4bsvxR4dpLNm0meXgV8fyoDlCRpIhwTCwwcsbDXIUhrzbHckkZwLfBPzXjYnwOfAf55cGdV3ZLkCOBCWt9qX1hVX+tJpJIkjYNJrCRJM8u9VfXaIdsG2leq6jTgtKEHVtVGbctnAWdNRoCSJE2E3YklSZIkSX3DllhJkmaIqloO7NDrOCRJmky2xEqSJEmS+oYtsZIkSZI0BZyYszu62hKb5JwklyVZmmR+s+3utv2vSHJys/y1JK9vlv8hyandjEWSJEmSNPN0uyX2jVV1W5L1gZ8m+cooZecDFyW5HngnsOdwhZpkeD7A3LlzuxyuJEmSJKmfdHtM7OFJrgIuAbYCth2pYFX9Dngfre/UvbOqbhuh3IKqmldV8+bMmdPlcCVJkiRJ/aRrLbFJ9gH2BfaqqlVJFgHrAdVWbL0hh+0I/B7YoltxSJIkSZJmrm62xG4C3N4ksNtxf/fg3yV5cpKHAC8dLJxkD+AFwC7Au5I8rouxSJIkSdKMMXDEQgaOWNjrMKaFbiax5wHrJlkGHEurSzHAEcA3gB8DtwAkeTjwWVpjaG+mNSb2pCTpYjySJEmSpBmma92Jq2o1rZbV4Zw1zLad2o49Fzi3W7FIkiRJkmambk/sJEmSJEnSpDGJlSRJkiT1jW5/J7YvLT92/16HIEnSlElyFHB3VX14hP0vAa6rqp9PZVySJHXCllhJkjTUS4Dtex2EJEnDMYmVJGkWSPLeJNcl+RHwpGbbNknOS3JZkh8m2S7J04EXA8cnuTLJNj0NXJKkIexOLEnSDJdkN+BgYGdadf/lwGXAAuCwqvpFkqcBn66q5yY5F/hGVQ33dQGSzAfmA8ydO3cK7kCSpPuZxIIfDZ5GHJ8sSZPimcDZVbUKoElS1wOeDpzZ9pn2h3dysqpaQCsBZt68edX1aCVJGoVJrCRJs9NDgDuqaudeByJJ0tpwTKwkSTPfD4CXJFk/ycbAi4BVwPVJDgRIy05N+buAjXsTqiRJozOJlSRphquqy4EzgKuAbwE/bXa9BnhTkquApcABzfbTgf+b5AondpIkTTfTojtxkm8Cr66qO3odiyRJM1FVHQMcM8yu5w9T9iL8xI4kaZqaFklsVe3X6xgkSZIkSdNfx92Jk2yYZGGSq5JcneSgJLsn+XGz7dIkGydZL8nnkyxpuiE9pzn+kCRfbb5H94skH2o79/Ikm0/GDUqSJEmSZo61aYl9PnBzVe0PkGQT4ArgoKr6aZJHAH8E3gZUVe2YZDvg/CRPbM6xM7ALsBq4NskJVXVjl+5FkiRJkjTDrU0SuwT4SJLjgG8AdwC3VNVPAarqToAkewMnNNuuSXIDMJjEfq+qVjblfg5sDYyaxPpBdUmSJEmz3fJj9+91CNNGx92Jq+o6YFdayezRwMvGcb3Vbctr6CCJrqoFVTWvqubNmTNnHJeUJEmSJM0UazMmdgtgVVWdAhwPPA14TJLdm/0bJ1kX+CGtKftpuhHPBa7tduCSJEmSpNlnbboT7wgcn+Q+4B7gLUCAE5KsT2s87L7Ap4HPJFkC3AscUlWrk4x1/lrb4CVJkiRJs0vHSWxVfRv49jC79hxm26HDHH8ycHLb+gsBkqwDbAzc2WkskiRJkjQbDRyxcMR9s2XcbMfdiSfRUuBzVXVPrwORJEmSJE1va9OdeFJU1Xa9jkGSJEmS1B+mQ0usJEmSJEkd6XlL7HQwW/qOS5IkSVK/syVWkiRJktQ3TGIlSZIkSX3DJFaSpBkiyUCSZUk+m2RpkvOTrJ9kUZJ5TZnNkyxvlg9Jck6S7yRZnuStSd6R5IoklyR5VE9vSJKkYTgmltG/tTQbOUZYkvratsCrqurvk3wZePkY5XcAdgHWA34JvKeqdknyMeD1wH9MZrCSJK0tW2IlSZpZrq+qK5vly4CBMcpfWFV3VdUKYCXw9Wb7kpGOTTI/yeIki1esWDHxiCVJWgsmsZIkzSyr25bX0Op1dS/31/nrjVL+vrb1+xihx1ZVLaiqeVU1b86cOROPWJKktWASK0nSzLcc2K1ZfkUP45AkacJMYiVJmvk+DLwlyRXA5r0ORpKkiXBiJ0mSZoiqWk5roqbB9Q+37X5q2/KRzf6TgZPbyg+0LT9gnyRJ08VatcSOMnX/zs1U/D9LcnaSRzblR5vS/6tJzkvyiyQf6vqdSZIkSZJmnPF0J94W+FRVPQW4g9bU/f9Na0r+p9KazfD9HZxnZ+AgYEfgoCRbjSMWSZIkSdIsMp4kdujU/dsAm1bV95ttXwCe1cF5vldVK6vqT8DPga2HK+Q0/pIkSZKkQeNJYodO3b/pKGU7ndJ/8BMAD+I0/pIkSZKkQd2Y2GklcHuSZ1bVD4HXAYOtsstpTel/KU7pL0mSJEkTsvzY/XsdQs91a3biNwAnJtkA+DVwaLP9w8CXk8wHFnbpWpIkSZKkWWqtktgxpu7fc5jy19DZlP4vXJs4JEmSJEmz03jGxEqSJEmS1BPd6k4sSZIkSZpkA0dMfJRmv4+rtSVWkiRJktQ3bIml/99ESJIkSdJsYUusJEmSJKlvmMRKkiRJkvqG3YnpzuDoXrAbtCSpm5IcAsyrqrcmOQxYVVX/3eOwJEl6AJNYSZL0IFV1Yq9jkCRpOHYnliRplkhyTpLLkixNMr/ZdmiS65JcCjyjrexRSd7Vs2AlSRqBLbGSJM0eb6yq25KsD/w0yULgA8BuwErgQuCKXgYoSdJYbImVJGn2ODzJVcAlwFbA64BFVbWiqv4MnNHJSZLMT7I4yeIVK1ZMYriSJD1Yz5LYJIck+WSzfFiS1/cqFkmSZrok+wD7AntV1U60WlyvGc+5qmpBVc2rqnlz5szpXpCSJHVgWnQndvIISZIm3SbA7VW1Ksl2wJ7A+sCzk2wG3AkcCFzVwxglSRrTpLXEOnmEJEnTynnAukmWAcfS6lJ8C3AUcDFwEbBsyDE1lQFKktSJyWyJ7crkEU0CPB9g7ty5kxiuJEkzV1WtBl4wzK5FwOeH2b4ZcMNkxiRJ0nhM5pjYrkwe4bgbSZKmVpJ/B54GnNvrWCRJGmpSkthuTh4hSZKmVlX9W1XtUVW/73UskiQNNVktsaNOHpHkobQmj5AkSZIkqWOTNSb2POCwZvKIa3nw5BF3AFcOOcbJIyRJkiRpFMuP3b/XIfTcpCSxTh4hSZIkSZoMkzmxU0ecPEKSJEmS1KmeJ7FOHiFJkiRJ6tRkfie2b9ivXJIkSVI/GDhi4aRfY7rnRz1viZUkSZIkqVMmsZIkSZKkvmESK0mSJEnqG46Jpfv9yqd7H3JJkiRJ6le2xEqSJEmS+oZJrCRJkiSpb5jESpIkSZL6hkmsJEl9LMlAkmVJPptkaZLzk6yfZOcklyT5WZKzkzyyKb8oybxmefMky5vlQ5J8Ncl5SX6R5EM9vC1JkkZkEitJUv/bFvhUVT0FuAN4OfDfwHuq6qnAEuD9HZxnZ+AgYEfgoCRbDVcoyfwki5MsXrFiRRfClySpc+NOYkd58zvaG95zknwnyfIkb03yjiRXNG+KH9Wle5Ikaba5vqqubJYvA7YBNq2q7zfbvgA8q4PzfK+qVlbVn4CfA1sPV6iqFlTVvKqaN2fOnAmGLknS2ploS+xwb35HswPwMmB34BhgVVXtAlwMvH6CsUiSNFutblteA2w6Stl7ub/+X2+M8/gpPknStDPRJHbom9+BMcpfWFV3VdUKYCXw9Wb7kpGOtcuSJElrbSVwe5JnNuuvAwZbZZcDuzXLr5jiuCRJmrCJJrHDvbHt9A3vfW3r9zHC2167LEmSNC5vAI5P8jNaY10/2Gz/MPCWJFcAm/coNkmSxm0yugktp/WG91J8wytJ0qSqquW0husMrn+4bfeew5S/Bnhq26Yjm+0nAye3lXthdyOVJKk7JmN2Yt/wSpIkSZImxbhbYsd489vJG96BtuUH7JMkSZIkaTh+J1aSJEmS1DecOl+SJEmS+sTyY/fvdQg9Z0usJEmSJKlv2BKLbzMkSZIkqV/YEitJkiRJ6hu2xEqSJElSnxg4YmGvQ3iQqe7ZakusJEmSJKlvzMqW2KFvLxwTK0mSJEn9wZZYSZIkSVLfMImVJEmSJPUNk1hJkvQgSb6ZZNNexyFJ0lCTnsQmOSrJu0bZ/5Ik2092HJIkqXNVtV9V3dHrOCRJGmo6tMS+BDCJlSRpLSXZMMnCJFcluTrJQUl2T/LjZtulSTZOsl6SzydZkuSKJM9pjj8kyVeTnJfkF0k+1Hbu5Uk2793dSZI0vEmZnTjJe4E3AP8L3AhclmQb4FPAHGAV8PfAo4AXA89OciTw8qr61WTEJEnSDPR84Oaq2h8gySbAFcBBVfXTJI8A/gi8Daiq2jHJdsD5SZ7YnGNnYBdgNXBtkhOq6sapvhFJkjrV9SQ2yW7AwbQqxXWBy4HLgAXAYVX1iyRPAz5dVc9Nci7wjao6q9uxSJI0wy0BPpLkOOAbwB3ALVX1U4CquhMgyd7ACc22a5LcAAwmsd+rqpVNuZ8DW9N6AT2iJPOB+QBz587t8i1JkjS6yWiJfSZwdlWtAmiS1PWApwNnJhks9/BOTmZFKUnS8KrquiS7AvsBRwMXjOM0q9uW19DBvw2qagGtl9PMmzevxnFNSZLGbarGxD4EuKOqdm77eXInB1bVgqqaV1Xz5syZM8lhSpLUP5JsAayqqlOA44GnAY9Jsnuzf+Mk6wI/BF7TbHsiMBe4tjdRS5I0MZORxP4AeEmS9ZNsDLyI1hjY65McCJCWnZrydwEbT0IckiTNdDsClya5Eng/8D7gIOCEJFcB36HVG+rTwEOSLAHOAA6pqtXDn/IBbGWVJE07Xe9OXFWXJzkDuIrWxE4/bXa9BvhMM4HTQ4HTmzKnA59NcjjwCid2kiSpM1X1beDbw+zac5hthw5z/MnAyW3rLwRIsg6tF8x3diNOSZK6aVJmJ66qY4Bjhtn1/GHKXoSf2JEkaTpZCnyuqu7pdSCSJA01KUmsJEnqX1W1Xa9jkCRpJFM1sZMkSZIkSRM2K1tilx+7f69DkCRJkqS1Zi5jS6wkSZIkqY+YxEqSJEmS+oZJrCRJkiSpb5jESpIkSZL6hkmsJEmSJKlvmMRKkiRJkvqGSawkSZIkqW+YxEqSJEmS+oZJrCRJkiSpb5jESpIkSZL6Rqqq1zF0LMkK4IZJOPXmwK2TcN7ZxGfYHT7HifMZTtxseYZbV9WcXgfR7yaxbp5Ms+V3vJ33PDt4z7PDTL7njurmvkpiJ0uSxVU1r9dx9DOfYXf4HCfOZzhxPkPNdLPxd9x7nh2859lhNt7zUHYnliRJkiT1DZNYSZIkSVLfMIltWdDrAGYAn2F3+Bwnzmc4cT5DzXSz8Xfce54dvOfZYTbe8wM4JlaSJEmS1DdsiZUkSZIk9Y1ZlcQmeX6Sa5P8MskRw+x/eJIzmv0/STLQgzCntQ6e4SFJViS5svl5cy/inM6SnJTkf5NcPcL+JPlE84x/lmTXqY5xuuvgGe6TZGXb7+H7pjrG6SzJVkkuTPLzJEuTvG2YMv4easZKclSSm9r+jtiv1zFNlSTvTFJJNu91LFMhyb83f4ddmeT8JFv0OqbJluT4JNc09312kk17HdNkS3JgU5/dl2TGzto71r/DZ5NZk8QmWQf4FPACYHvgVUm2H1LsTcDtVfUE4GPAcVMb5fTW4TMEOKOqdm5+PjelQfaHk4Hnj7L/BcC2zc984DNTEFO/OZnRnyHAD9t+Dz84BTH1k3uBd1bV9sCewD8N8/+yv4ea6T7W9nfEN3sdzFRIshXwt8D/9DqWKXR8VT21qnYGvgHMhpea3wF2qKqnAtcB/9LjeKbC1cDLgB/0OpDJshb/Dp8VZk0SC+wB/LKqfl1VfwZOBw4YUuYA4AvN8lnA3yTJFMY43XXyDDWGqvoBcNsoRQ4A/rtaLgE2TfKYqYmuP3TwDDWKqrqlqi5vlu8ClgFbDinm76E083wMeDcwayZEqao721Y3ZBbce1WdX1X3NquXAI/tZTxToaqWVdW1vY5jkvnv8DazKYndErixbf03PPgfbX8p0/zPvxLYbEqi6w+dPEOAlzddWM5q3vpq7XT6nDW6vZJcleRbSZ7S62Cmq2bYxC7AT4bs8vdQM91bm7rqpCSP7HUwky3JAcBNVXVVr2OZakmOSXIj8BpmR0tsuzcC3+p1EOoK6+U26/Y6AM04XwdOq6rVSf6BVsv2c3sck2afy4Gtq+ruZqzbObS6xapNko2ArwBvH9JaIfW9JN8F/nqYXe+l1T3+32m1yv078BFa/9jva2Pc87/S6ko844x231X1tap6L/DeJP8CvBV4/5QGOAnGuuemzHtpDR85dSpjmyyd3LNmj9mUxN4EtLcKPrbZNlyZ3yRZF9gE+P3UhNcXxnyGVdX+vD4HfGgK4pppOvld1SjaE7Kq+maSTyfZvKpu7WVc00mSh9JKYE+tqq8OU8TfQ/W1qtq3k3JJPktrrGTfG+mek+wIPA64qhkl9Vjg8iR7VNVvpzDESdHpf2taydw3mQFJ7Fj3nOQQ4IXA39QM+Z7mWvx3nqmsl9vMpu7EPwW2TfK4JA8DDgbOHVLmXOANzfIrgAtmyv/4XTLmMxwyZu7FtMbaae2cC7y+mR12T2BlVd3S66D6SZK/HhzPnmQPWn/X+UKq0Tyb/wKWVdVHRyjm76FmrCF11UtpTQozY1XVkqr6q6oaqKoBWt0Qd50JCexYkrT3wjkAuKZXsUyVJM+nNfb5xVW1qtfxqGs6yWVmjVnTEltV9yZ5K/BtYB3gpKpamuSDwOKqOpfWP+q+mOSXtCaNObh3EU8/HT7Dw5O8mFb3lduAQ3oW8DSV5DRgH2DzJL+h9Ub4oQBVdSKtt8T7Ab8EVgGH9ibS6auDZ/gK4C1J7gX+CBzsC6kHeAbwOmBJkiubbf8KzAV/DzUrfCjJzrS6Ey8H/qGn0WgyHZvkScB9wA3AYT2OZyp8Eng48J3mfe4lVTWj7zvJS4ETgDnAwiRXVtXf9Tisrhrp3+E9Dqtn4r/rJEmSJEn9YjZ1J5YkSZIk9TmTWEmSJElS3zCJlSRJkiT1DZNYSZIkSVLfMImVJEmSJPUNk1hJkiRJUt8wiZUkSZIk9Q2TWEmSJElS3zCJlSRJkiT1DZNYSZIkSVLfMImVJEmSJPUNk1hJkiRJUt8wiZUkSZIk9Q2TWEmSJElS3zCJlSRJkiT1DZNYSROW5FtJ3jDK/hOT/NtUxiRJkjqT5O4kj+91HFKnUlW9jkHSDJLkEODNVbV3r2ORJEkPlGQRcEpVfa7XsUjjZUustBaSrNvrGDqVFv8flyTNONbH0uzm/1Ca9ZLsmuSKJHclOTPJGUmObvbtk+Q3Sd6T5LfA55M8Msk3kqxIcnuz/Ni28y1KcnSSHzfdc76eZLMkpya5M8lPkwy0la8k/5jkF00M/55km+b4O5N8OcnDmrKdXPuYJBcBq4AHdQ1KsjzJvyT5eXOOzydZr23/3yf5ZZLbkpybZItm+7ub+xn8uSfJyW3XfXOSJwMnAns1Ze5o9p/c9kyXJXlh2/XWbe5n12Z9z+be70hyVZJ9JvZfWJLUD2ZpffyuJD9LsrK53/b6+IVJrmzqwx8neWqHz2rE2JIcAzwT+GTzTD7Zdu9PSPK0JL9Nsk7btV6a5GfN8kOSHJHkV0l+3zyTR03sv7y09kxiNas1ldHZwMnAo4DTgJcOKfbXzb6tgfm0/r/5fLM+F/gj8MkhxxwMvA7YEtgGuLg55lHAMuD9Q8r/HbAbsCfwbmAB8FpgK2AH4FVNuU6u/bomzo2BG0a49dc019wGeCJwZPM8ngv8f8Argcc0x58OUFUfqqqNqmoj4MnACuCM9pNW1TLgMODipuymw1z7tLb7Gbz3W6vq8iRbAguBo2k9q3cBX0kyZ4T7kCTNALO4Pn4l8HzgccBTgUOa57ELcBLwD8BmwH8C5yZ5eAfPasTYquq9wA+Btzb19Fvbg6mqnwB/AJ7btvnVwJea5X8GXgI8G9gCuB341Aj3Jk0ak1jNdnsC6wKfqKp7quqrwKVDytwHvL+qVlfVH6vq91X1lapaVVV3AcfQ+su83eer6ldVtRL4FvCrqvpuVd0LnAnsMqT8h6rqzqpaClwNnF9Vv247fheADq99clUtrap7q+qeEe77k1V1Y1Xd1pxjsFJ+DXBSVV1eVauBf6HVqjoweGCS9YFzgI9X1bdGOP9ovgS8OMkGzfqraVXA0PqHwjer6ptVdV9VfQdYDOw3jutIkvrHbK2PP1FVNzf18deBnZvt84H/rKqfVNWaqvoCsLp5TqM+qw5jG81fXjYn2ZhWHTxYTx8GvLeqftP8O+Eo4BXpo+7dmhlMYjXbbQHcVA+c4ezGIWVWVNWfBleSbJDkP5PckORO4AfApu1db4DftS3/cZj1jYZco6PyHV57aPzDaS9zA63nQPPnX94WV9XdwO9pvcEe9F/AtVV1XAfXeZCq+iWtt98vahLZF3P/G96tgQObrlN3pNUdeW9arcKSpJlrttbHv21bXtUWz9bAO4fUh1vRek6jPqsOYxvNl4CXJXk48DLg8qoa/LfB1sDZbTEtA9YAj+7w3FJXmMRqtrsF2DJJ2rZtNaTM0Cm83wk8CXhaVT0CeFazPUy+Tq7dyZTj7fc4F7i5Wb6ZVgXVOmmyIa1uTDc160fQ6n78plHO3cn1B9/yHgD8vElsoVUJf7GqNm372bCqju3gnJKk/jVb6+OR3AgcM6Q+3KCqTmPsZzVWbKPGVVU/p/VC+wU8sCvxYFwvGBLXelV103hvVBoPk1jNdhfTeoP41rQmGDoA2GOMYzam9Tb2jmYyg6HjaSZTt679T0ke25zjvdw/tvU04NAkOzdvYP8f8JOqWp7kBcDhwEur6o+jnPt3wGMHJ78YwenA3wJv4YGV4ym0Wmj/Lsk6SdZLazKPxw57FknSTDFb6+ORfBY4rJloKUk2TLJ/0713rGc1Vmy/Y5iJpob4EvA2WgnwmW3bTwSOSbI1QJI5zfWlKWUSq1mtqv5Mq6vMm4A7aI3J/AatcScj+Q9gfeBW4BLgvEkNcnKu/SXgfODXwK9oTaREVX0X+DfgK7Te9G5Da1IMgIOAOcCy3D9D8YnDnPsCYCnw2yS3DnfxqrqFViX8dNomh6qqG2m1zv4rrYmjbgT+L/5dJUkz2iyuj4dVVYuBv6c1IdPtwC9pJn3q4FmNFdvHaY1jvT3JJ0YI4TRa42gvqKr2uvzjwLnA+Unuas7/tHHepjRueWB3eklJfgKcWFWf73UskyHJcuDNTcIqSdK0NNPr427yWWm2sXVDs16SZyf566ZLzhtoTXE/lW9zJUma9ayPO+ez0mzndNhSa/KDLwMb0upe+4qmu6skSZo61sed81lpVrM7sSRJkiSpb9idWJIkSZLUN0xiJUmSJEl9o6/GxG6++eY1MDDQ6zAkSTPAZZdddmtVzel1HP3OulmS1C2d1s19lcQODAywePHiXochSZoBktzQ6xhmAutmSVK3dFo3251YkiRJktQ3TGIlSZIkSX3DJFaSJEmS1DdMYiVJkiRJfcMkVpIkSZLUN0xiJUmSJEl9wyRWkiRJktQ3TGIlSZIkSX1j3V4HsDaW3LSSgSMW9joMSVKPLD92/16HoEli/S5Ja2c214m2xEqSJEmS+oZJrCRJkiSpb5jESpIkSZL6xpQlsUkOSfLJqbqeJEmSJGnmsSVWkqRZIMmPOyjz9iQbtK1/M8mmkxqYJElrqWtJbJJzklyWZGmS+c22Q5Ncl+RS4BltZU9OcmKSxc3+F3YrDkmS9GBV9fQOir0d+EsSW1X7VdUdkxWTJEnj0c2W2DdW1W7APODwJFsCH6CVvO4NbD+k/ACwB7A/cGKS9boYiyRJapPk7ubPfZIsSnJWkmuSnJqWw4EtgAuTXNiUXZ5k817GLUnSUN1MYg9PchVwCbAV8DpgUVWtqKo/A2cMKf/lqrqvqn4B/BrYbriTJpnftNguXrNqZRfDlSRp1tqFVqvr9sDjgWdU1SeAm4HnVNVzehibJEmj6koSm2QfYF9gr6raCbgCuGaMw2qM9dbGqgVVNa+q5q2zwSYTDVWSJMGlVfWbqroPuJJW76iOtb9gXrFixWTEJ0nSiLrVErsJcHtVrUqyHbAnsD7w7CSbJXkocOCQYw5M8pAk29B6C3xtl2KRJEmjW922vAZYd20Obn/BPGfOnO5GJknSGNaq0hrFecBhSZbRSkYvAW4BjgIuBu6g9aa33f8AlwKPAA6rqj91KRZJkjQ+dwEbA7f2OhBJkkbSlSS2qlYDLxhm1yLg8yMc9t2qOqwb15ckSV2xADgvyc1t42KHHe4jSVKvdKslVpIkTWNVtVHz5yJaL5kHt7+1bfkE4ASAJOvQapW9cyrjlCRpLD1JYqvqkF5cV5IkdWwp8LmquqfXgUiS1M6WWEmS9CBVNeyn7yRJ6rW+SmJ33HITFh+7f6/DkCRJkiT1SF8lsZIkaWZa7ktqSVKHuvWdWEmSJEmSJp1JrCRJkiSpb/RVd+IlN61k4IiFvQ5DkqYNu2BKkqTZxpZYSZIkSVLf6KuWWEmSJM1O9saTHmg298ayJVaSJEmS1DemNIlNckiST07lNSVJkiRJM4ctsZIkSZKkvtHVJDbJOUkuS7I0yfxm26FJrktyKfCMZtsmSW5I8pBmfcMkNyZ5aDfjkSRJkiTNLN1uiX1jVe0GzAMOT7Il8AFayevewPYAVbUSuBJ4dnPcC4FvV9U9XY5HkiRJkjSDdDuJPTzJVcAlwFbA64BFVbWiqv4MnNFW9gzgoGb54CH7/iLJ/CSLkyxes2pll8OVJEmSJPWTriWxSfYB9gX2qqqdgCuAa0Y55Fzg+UkeBewGXDBcoapaUFXzqmreOhts0q1wJUnqS80QnIVJrkpydZKDkixP8qEkS5JcmuQJTdkXJflJkiuSfDfJo5vtGyX5fFP+Z0le3mz/2yQXJ7k8yZlJNurlvUqSNJxutsRuAtxeVauSbAfsCawPPDvJZs141wMHC1fV3cBPgY8D36iqNV2MRZKkmer5wM1VtVNV7QCc12xfWVU7Ap8E/qPZ9iNgz6raBTgdeHez/d8Gy1fVU4ELkmwOHAnsW1W7AouBdwwXQHsvqRUrVkzCLUqSNLJ1u3iu84DDkiwDrqXVpfgW4CjgYuAOWuNg250BnAns08U4JEmayZYAH0lyHK2XwD9MAnBas/804GPN8mOBM5I8BngYcH2zfV9aQ3kAqKrbk7yQ1twVFzXnexit+vtBqmoBsABg3rx51b1bkyRpbF1LYqtqNfCCYXYtAj4/wjFnAelWDJIkzXRVdV2SXYH9gKOTfG9wV3ux5s8TgI9W1bnNsJ+jRjl1gO9U1au6G7EkSd3ld2IlSeojSbYAVlXVKcDxwK7NroPa/hxsQd0EuKlZfkPbab4D/FPbOR9JqwfVM9rG026Y5ImTchOSJE2ASawkSf1lR+DSJFcC7weObrY/MsnPgLcB/6fZdhRwZpLLgFvbznF0U/7q5qsCz6mqFcAhwGnNeS4Gtpvke5Ekaa11c0zspNtxy01YfOz+vQ5DkqSeqapvA99u39aMYT2+qt4zpOzXgK8Nc467eWDL7OD2C4DduxmvJEndZkusJEmSJKlv9FVLrCRJerCqGuh1DJIkTRVbYiVJkiRJfaOvWmKX3LSSgSMW9joMSerIcsfwS1LX+HeqpEG2xEqSJEmS+oZJrCRJkiSpb5jESpIkSZL6Rl+NiZUkSZKktTUT59WZzePEe9ISm+TuXlxXkiRJktTfprQlNkmATOU1JUmSJEkzx7iS2CTHAjdW1aea9aOAu2klqK8EHg6cXVXvTzIAfBv4CbAbsF9zzMeAvwV+CxxcVSsmdCeSJEmSpBlvvN2Jz6CVrA56JbAC2BbYA9gZ2C3Js5r92wKfrqqnVNUNwIbA4qp6CvB94P0jXSjJ/CSLkyxes2rlOMOVJEmSJM0E42qJraorkvxVki2AOcDtwI60WlavaIptRCt5/R/ghqq6pO0U99FKhAFOAb46yrUWAAsAHv6YbWs88UqSJEmSZoaJjIk9E3gF8Ne0EtKtgf+vqv6zvVDTnfgPY5zL5FSSpC5Ksk5Vrel1HJIkddtEZic+AziYViJ7Jq1xr29MshFAki2T/NUo131Fs/xq4EcTiEOSpFklyUCSa5KcmmRZkrOSbJBkeZLjklwOHJjkVUmWJLk6yXFtx9+d5GNJlib5XpI5zfZFzfGXJrkuyTN7dpOSJI1g3ElsVS0FNgZuqqpbqup84EvAxUmWAGc1+4fzB2CPJFcDzwU+ON44JEmapZ5Ea76JJwN3Av/YbP99Ve0K/AA4jlY9uzOwe5KXNGVGm5ti3araA3g7o8xZIUlSr0zoEztVteOQ9Y8DHx+m6A5Dym00ketKkiRurKqLmuVTgMOb5cE5J3YHFg3O/p/kVOBZwDmMPjfF4PJlwMBwF04yH5gPMHfu3AnehiRJa2ci3YklSVLvDJ1PYnB9rHkoxjrX6ubPNYzwsruqFlTVvKqaN2fOnHFcTpKk8TOJlSSpP81NslezPNz8EpcCz06yeZJ1gFfR6joMzk0hSepjE+pOPNV23HITFh+7f6/DkCRpOrgW+KckJwE/Bz4D/PPgzqq6JckRwIVAgIVV9bVm9+DcFEcC/wscNKWRS5I0AX2VxEqSpL+4t6peO2TbQPtKVZ0GnDbcwVX1jmG27dO2fOvQ80mSNB3YnViSJEmS1DdsiZUkqc9U1XKGzPy/lsf7lQBJUt/qqyR2yU0rGThiYa/DkDRDLXfMvSRJ0rRnd2JJkiRJUt/oq5ZYSZIkSVpb9raaWWyJlSRJkiT1jZ4nsUlekmT7XschSZIkSZr+ep7EAi8BTGIlSZIkSWMac0xskgHgPOAyYFdgKfB64OfAvKq6Nck84MNVtU+So4C5wOObP/+jqj7RnOv1wLuAAn4GfAZ4MfDsJEcCL6+qX3X1DiVJkiRpGujml1Zm8zjfTid2ehLwpqq6KMlJwD+OUX474DnAxsC1ST4DPBE4Enh6k/g+qqpuS3Iu8I2qOmuc9yBJkiRJmiU67U58Y1Vd1CyfAuw9RvmFVbW6qm4F/hd4NPBc4MxmG1V1WycXTjI/yeIki9esWtlhuJIkSZKkmajTJLaGWb+37fj1huxf3ba8hgl8yqeqFlTVvKqat84Gm4z3NJIkSZKkGaDTJHZukr2a5VcDPwKWA7s1217ewTkuAA5MshlAkkc12++i1e1YkiRJkqRRdZrEXgv8U5JlwCNpTcj0AeDjSRbTam0dVVUtBY4Bvp/kKuCjza7Tgf+b5Iok26ztDUiSpLWT5Kgk7xplv5+/kyRNW5128723ql47ZNsPaU3W9ABVddSQ9R3alr8AfGHI/ovwEzuSJE0nLwG+QetLBJIkTSvT4TuxkiRpkiV5b5LrkvyI1lcHSLJNkvOSXJbkh0m2S/J0Wp+/Oz7JlfaSkiRNN2O2xFbVcmCHscpJkqTpKcluwMHAzrTq/stpff99AXBYVf0iydOAT1fVc/38nSRpOhv3rMGSJKlvPBM4u6pWATRJ6nrA04EzkwyWe3gnJ0syH5gPMHfu3K4HK0nSaPoqid1xy01YfOz+vQ5DkqSZ4CHAHVW189oeWFULaLXiMm/evKGf4ZMkaVI5JlaSpJnvB8BLkqyfZGPgRcAq4PokBwKkZaemvJ+/kyRNWyaxkiTNcFV1OXAGcBXwLeCnza7XAG9qPn23FDig2e7n7yRJ01ZfdSeWJEnjU1XH0Ppe+1DPH6asn7+TJE1bfZXELrlpJQNHLOx1GJL62HLH1UuSJPU1uxNLkiRJkvqGSawkSZIkqW/0VXdiSZIkSepXDmvqDltiJUmSJEl9wyRWkiRJktQ3uprEJjknyWVJliaZ32y7u23/K5Kc3Cx/Lcnrm+V/SHJqN2ORJEmSJM083R4T+8aqui3J+sBPk3xllLLzgYuSXA+8E9hzuEJNMjwfYJ1HzOlyuJIkSZKkftLtJPbwJC9tlrcCth2pYFX9Lsn7gAuBl1bVbSOUWwAsAHj4Y7atLscrSZIkSdPGwBELOyo3myeJ6loSm2QfYF9gr6palWQRsB7QnniuN+SwHYHfA1t0Kw5JkiRJ0szVzTGxmwC3NwnsdtzfPfh3SZ6c5CHAYCstSfYAXgDsArwryeO6GIskSZIkaQbqZhJ7HrBukmXAscAlzfYjgG8APwZuAUjycOCztMbQ3kxrTOxJSdLFeCRJkiRJM0zXuhNX1WpaLavDOWuYbTu1HXsucG63YpEkSZIkzUx+J1aSJD1Ikg8m2bfXcUiSNFS3ZyeWJEkzQFW9r9cxSJI0nL5KYnfcchMWz+KppCVJGirJ64F30foawM+a5ROBxzdF3lJVP07yDuCNzbbPVdV/JBkAvgX8CHg6cBNwQFX9McnJwDeqarghQZIk9UxfJbGSJOl+SZ4CHAk8vapuTfIo4DPA96vqpUnWATZKshtwKPA0IMBPknwfuJ3WN91fVVV/n+TLwMuBU8a47nxgPsDcuXMn6e4kSRqeY2IlSepfzwXOrKpbAarqtmbbZ5r1NVW1EtgbOLuq/lBVdwNfBZ7ZnOP6qrqyWb4MGBjrolW1oKrmVdW8OXPmdPN+JEkak0msJEmz2+q25TXYS0uSNM31VUW15KaVDByxsNdhSCx3bLak6eEC4OwkH62q3zfdib8HvAX4j8HuxMAPgZOTHEurO/FLgdf1KmhJkiair5JYSZJ0v6pamuQY4PtJ1gBXAG8DFiR5E62W1bdU1cXNRE2XNod+rqquaCZ2GvUSkxS6JEnjZhIrSVIfq6ovAF8YsvmAYcp9FPjokG3LgR3a1j/ctnsz4LauBSpJUpc4JlaSJD1AkpOADWh9ekeSpGnFllhJkvQAVfXGsUtJktQbtsRKkiRJkvrGWrXENhNAfItW96KnAzfRGnfzJOBEWl2PfgW8sapuT7IIeFdVLU6yObC4qgaSHAK8uCm/Da1v1727K3ckSZIkSX3Kr2CMbTwtsdsCn6qqpwB3AC8H/ht4T1U9FVgCvL+D8+wMHATsCByUZKtxxCJJkiRJmkXGk8ReX1VXNsuX0WpJ3bSqvt9s+wLwrA7O872qWllVfwJ+Dmw9XKEk85MsTrJ4zaqV4whXkiRJkjRTjCeJXd22vAbYdJSy97ZdY70xzjNs1+aqWlBV86pq3jobbLKWoUqSJEmSZpJuTOy0Erg9yTOb9dcBg62yy4HdmuVXdOFakiRJkqRZrFuf2HkDcGKSDYBfA4c22z8MfDnJfGBhl64lSZIkSZql1iqJrarlwA5t6x9u273nMOWvAZ7atunIZvvJwMlt5V64NnFIkiRJkmYnvxMrSZIkSeobJrGSJEmSpL5hEitJkiRJ6hvdmthpSuy45SYsPnb/XochSZIkSeoRW2IlSZohkgwkWZbks0mWJjk/yfpJFiWZ15TZPMnyZvmQJOck+U6S5UnemuQdSa5IckmSR/X0hiRJGoZJrCRJM8u2wKeq6inAHcDLxyi/A/AyYHfgGGBVVe0CXAy8fhLjlCRpXExiJUmaWa6vqiub5cuAgTHKX1hVd1XVCmAl8PVm+5KRjk0yP8niJItXrFgx8YglSVoLfTUmdslNKxk4YmGvw+gryx1DLEmzzeq25TXA+sC93P/ier1Ryt/Xtn4fI/w7oaoWAAsA5s2bVxOMV5KktWJLrCRJM99yYLdm+RU9jEOSpAkziZUkaeb7MPCWJFcAm/c6GEmSJqKvuhNLkqSRVdVyWhM1Da5/uG33U9uWj2z2nwyc3FZ+oG35AfskSZouetYS20zr/8lm+bAkzoAoSZIkSRrVtGiJraoTex2DJEmSJGn6m7SW2Obj6Zc1H1uf32w7NMl1SS4FntFW9qgk75qsWCRJkiRJM8NktsS+sapuS7I+8NMkC4EP0JodcSVwIXDFJF5fkiRJkjTDTOaY2MOTXAVcAmwFvA5YVFUrqurPwBmdnKT9g+prVq2cxHAlSZIkSdPdpCSxSfYB9gX2qqqdaLW4XjOec1XVgqqaV1Xz1tlgk+4FKUmSJEnqO5PVErsJcHtVrUqyHbAnsD7w7CSbJXkocOAkXVuSJEmSNENN1pjY84DDkiwDrqXVpfgW4CjgYuAO4Mohx9QkxSJJkiRJmiEmJYmtqtXAC4bZtQj4/DDbNwNumIxYJEmSJGmmGThiIQDLj92/x5FMvcmc2KkjSf4deBpwbq9jkSRJkiRNbz1PYqvq36pqj6r6fa9jkSRJkiRNbz1PYiVJkiRJ6tRkTew0KXbcchMWz8I+35IkSZKkFltiJUnSgyT5ZpJNex2HJElD9VVLrCRJmhpVtV+vY5AkaTh9lcQuuWnlX6aS7oXZOH21JGn6SrIh8GXgscA6wL8DvwY+DmwIrAb+BrgH+AwwD7gXeEdVXZjkEODFwAbANsDZVfXu5tzLgXlVdesU3pIkSWPqqyRWkiQ9wPOBm6tqf4AkmwBXAAdV1U+TPAL4I/A2oKpqxyTbAecneWJzjp2BXWglvNcmOaGqbhztoknmA/MB5s6dOwm3JUnSyBwTK0lS/1oCPC/JcUmeCcwFbqmqnwJU1Z1VdS+wN3BKs+0a4AZgMIn9XlWtrKo/AT8Hth7rolW1oKrmVdW8OXPmdP+uJEkahUmsJEl9qqquA3allcweDbxsHKdZ3ba8BntpSZKmOZNYSZL6VJItgFVVdQpwPPA04DFJdm/2b5xkXeCHwGuabU+k1WJ7bW+iliRpYnzbKklS/9oROD7JfbQmb3oLEOCEJOvTGg+7L/Bp4DNJltCa2OmQqlqdZKzz16RFLknSOJnESpLUp6rq28C3h9m15zDbDh3m+JOBk9vWXwiQZB1gY+DObsQpSVI3Tag7cZINkyxMclWSq5MclOSctv3PS3J2s3x3kuOTLE3y3SR7JFmU5NdJXjzB+5AkSd2zFPhcVd3T60AkSRpqomNiB6f236mqdgDOA7ZLMjhV4aHASc3yhsAFVfUU4C5aE1A8D3gp8MGRLpBkfpLFSRavWbVyguFKkqSxVNV2VfWeXschSdJwJprEPmBq/6paCXwReG2STYG9gG81Zf9MK8kdPO77zRveJcDASBdon8Z/nQ02mWC4kiRJkqR+NqExsVV1XZJdgf2Ao5N8D/gc8HXgT8CZzffpAO6pqsEJIu6jmdK/qu5rZk6UJEmSJHVg+bH79zqEnplQ8thM7X9bVZ2S5A7gzVV1c5KbgSNpzYgoSZIkSVJXTLQFdLip/QFOBeZU1bIJnl+SJEmSpL+YaHfikab23xv47JCyG7UtHzXSPkmSJEmSRtL1sahJLgP+ALyz2+eWJEmSJMHAEQvHddxMGEvb9SS2qnbr9jklSZIkSYJJSGIn045bbsLiGfDmQJIkSZI0PhP9TqwkSZIkSVPGJFaSJEmS1DdMYiVJkiRJfaOvxsQuuWnluGfhmqiZMIuXJElJ1qmqNb2OQ5Kk8bIlVpKkGSLJQJJrkpyaZFmSs5JskGR5kuOSXA4cmORVSZYkuTrJcW3H353kmCRXJbkkyaN7eDuSJA3LJFaSpJnlScCnq+rJwJ3APzbbf19VuwI/AI4DngvsDOye5CVNmQ2BS6pqp6bc309h3JIkdcQkVpKkmeXGqrqoWT4F2LtZPqP5c3dgUVWtqKp7gVOBZzX7/gx8o1m+DBgY7gJJ5idZnGTxihUruh2/JEmjMomVJGlmqRHW/9DBsfdU1WD5NYwwd0ZVLaiqeVU1b86cOeMMU5Kk8ZnUJDbJOpN5fkmS9CBzk+zVLL8a+NGQ/ZcCz06yeVNPvwr4/lQGKEnSRIw7iXXyCEmSpqVrgX9Ksgx4JPCZ9p1VdQtwBHAhcBVwWVV9bcqjlCRpnCbaEuvkEZIkTS/3VtVrq+rJVfXyqlpVVQNVdetggao6rap2rKodquo9bds3als+q6oOmeLYJUka00ST2CmdPGLNqpUTDFeSJEmS1M8mmsRO6eQR62ywyTjDlCRp5quq5VW1Q6/jkCRpMk00iXXyCEmSJEnSlJloEuvkEZIkSZKkKTNsF961cG9VvXbItoH2lao6DTht6IFDJ48AzppgLJIkSZI0Kyw/dv9eh9Azk/qdWEmSJEmSumncLbFVtRxw8ghJkiRJ0pSxJVaSJEmS1DcmOiZ2Su245SYsnsV9vyVJkiQJYOCIheM+tt/H09oSK0mSJEnqGyaxkiRJkqS+YRIrSZIkSeobfTUmdslNKx/U97vf+3NLkiRJkjpnS6wkSZIkqW+YxEqSJEmS+oZJrCRJM0iSDZMsTHJVkquTHJTknLb9z0tydrN8d5LjkyxN8t0keyRZlOTXSV7cs5uQJGkU0yKJTfLNJJv2Og5JkmaA5wM3V9VOVbUDcB6wXZI5zf5DgZOa5Q2BC6rqKcBdwNHA84CXAh+c2rAlSerMtEhiq2q/qrqj13FIkjQDLAGel+S4JM+sqpXAF4HXNi+M9wK+1ZT9M60kd/C471fVPc3ywEgXSDI/yeIki1esWDFJtyFJ0vA6TmJH6J60e5IfN9suTbJxkvWSfD7JkiRXJHlOc/whSb6a5Lwkv0jyobZzL0+y+WTcoCRJs0lVXQfsSisRPTrJ+4DPA68FXgWcWVX3NsXvqapqlu8DVjfnuI9RvmBQVQuqal5VzZszZ85IxSRJmhRr84mdwe5J+wMk2QS4Ajioqn6a5BHAH4G3AVVVOybZDjg/yRObc+wM7EKrkrw2yQlVdeNoF00yH5gPsM4jrCglSRpNki2A26rqlCR3AG+uqpuT3AwcCezb0wAlSZqgtUlilwAfSXIc8A3gDuCWqvopQFXdCZBkb+CEZts1SW4ABpPY7zXdmkjyc2BrYNQktqoWAAsAHv6YbWu0spIkiR2B45PcB9wDvKXZfiowp6qW9SwySZK6oOMktqquS7IrsB+tiR8uGMf1Vrctr1mb60uSpLFV1beBbw+za2/gs0PKbtS2fNRI+yRJmk7WZkzsFsCqqjoFOB54GvCYJLs3+zdOsi7wQ+A1zbYnAnOBa7sduCRJ6kySy4CnAqf0OhZJkiZqbVpCh+ueFOCEJOvTGg+7L/Bp4DNJlgD3AodU1eokY53frsKSJE2Cqtqt1zFIktQta9OdeKTuSXsOs+3QYY4/GTi5bf2FAEnWATYG7uw0FkmSJEnS7DQdxqQuBT7XfJdOkiRJkjSG5cfu3+sQeqbnSWxVbdfrGCRJkiRJ/aHnSeza2HHLTVg8i984SJIkSdJs1/HsxJIkSZIk9ZpJrCRJkiSpb/RVd2JJkiRJEgwcsbDXIfzFVE8y1VctsUtuWtnrECRJkiRJPdRXSawkSZIkaXYziZUkSZIk9Q2TWEmSJElS3zCJlSRJACQ5JMknm+XDkry+1zFJkjSUsxNLkqQHqaoTex2DJEnDsSVWkqRZIsk5SS5LsjTJ/GbboUmuS3Ip8Iy2skcleVfPgpUkaQTjTmKTDCRZluSzTWV4fpL1kyxKMq8ps3mS5c3yIU3l+Z0ky5O8Nck7klyR5JIkj+rSPUmSpOG9sap2A+YBhyfZEvgAreR1b2D7Tk6SZH6SxUkWr1ixYvKilSRpGBNtid0W+FRVPQW4A3j5GOV3AF4G7A4cA6yqql2Ai4Fhx920V5RrVvmdWEmSJuDwJFcBlwBbAa8DFlXViqr6M3BGJyepqgVVNa+q5s2ZM2cSw5Uk6cEmmsReX1VXNsuXAQNjlL+wqu6qqhXASuDrzfYlIx3bXlGus8EmEwxXkqTZKck+wL7AXlW1E3AFcE0vY5IkaTwmmsSublteQ2uiqHvbzrveKOXva1u/DyeZkiRpMm0C3F5Vq5JsB+wJrA88O8lmSR4KHNjTCCVJ6sBkTOy0HNitWX7FJJxfkiStvfOAdZMsA46l1aX4FuAoWsN6LgKWDTmmpjJASZI6MRmtnx8GvtzMerhwEs4vSZLWUlWtBl4wzK5FwOeH2b4ZcMNkxiRJ0niMO4mtquW0JmoaXP9w2+6nti0f2ew/GTi5rfxA2/ID9kmSpN5J8u/A02i10kqSNK34nVhJkvQAVfVvVbVHVf2+17FIkjSUSawkSZIkqW/01YzAO27pJ3YkSZIkafmx+/c6hJ6xJVaSJEmS1DdMYiVJkiRJfcMkVpIkSZLUN0xiJUmSJEl9wyRWkiRJktQ3TGIlSZIkSX3DJFaSJEmS1DdMYiVJkiRJfcMkVpIkSZLUN0xiJUmSJEl9I1XV6xg6luQu4NpexzFDbQ7c2usgZiif7eTy+U6emf5st66qOb0Oot8lWQHc0Os4mPm/r5PJZzcxPr/x89lNzEx8fh3Vzf2WxC6uqnm9jmMm8tlOHp/t5PL5Th6frfqJv6/j57ObGJ/f+PnsJmY2Pz+7E0uSJEmS+oZJrCRJkiSpb/RbErug1wHMYD7byeOznVw+38njs1U/8fd1/Hx2E+PzGz+f3cTM2ufXV2NiJUmSJEmzW7+1xEqSJEmSZrFpl8QmeX6Sa5P8MskRw+x/eJIzmv0/STLQgzD7VgfP95AkK5Jc2fy8uRdx9pskJyX53yRXj7A/ST7RPPefJdl1qmPsZx08332SrGz7vX3fVMfYr5JsleTCJD9PsjTJ24Yp4++v+kaSdyapJJv3OpZ+kuTfm/+/r0xyfpIteh1Tv0hyfJJrmud3dpJNex1TP0lyYFP/3JdkVs60u7bG+vf8bDCtktgk6wCfAl4AbA+8Ksn2Q4q9Cbi9qp4AfAw4bmqj7F8dPl+AM6pq5+bnc1MaZP86GXj+KPtfAGzb/MwHPjMFMc0kJzP68wX4Ydvv7QenIKaZ4l7gnVW1PbAn8E/D/L3g76/6QpKtgL8F/qfXsfSh46vqqVW1M/ANwJeBnfsOsENVPRW4DviXHsfTb64GXgb8oNeB9IO1+Pf8jDatklhgD+CXVfXrqvozcDpwwJAyBwBfaJbPAv4mSaYwxn7WyfPVOFTVD4DbRilyAPDf1XIJsGmSx0xNdP2vg+ercaqqW6rq8mb5LmAZsOWQYv7+ql98DHg34IQfa6mq7mxb3RCfYceq6vyqurdZvQR4bC/j6TdVtayqru11HH3Ef88z/ZLYLYEb29Z/w4P/MfWXMs1fGCuBzaYkuv7XyfMFeHnTJeas5q22Jq7TZ6/x2yvJVUm+leQpvQ6mHzXDM3YBfjJkl7+/mvaSHADcVFVX9TqWfpXkmCQ3Aq/BltjxeiPwrV4HoRnNOhlYt9cBaNr5OnBaVa1O8g+0Wr2f2+OYpLFcDmxdVXcn2Q84h1bXV3UoyUbAV4C3D2mRkaaNJN8F/nqYXe8F/pVWV2KNYLTnV1Vfq6r3Au9N8i/AW4H3T2mA09hYz64p815aQzROncrY+kEnz09aG9Mtib0JaG/5e2yzbbgyv0myLrAJ8PupCa/vjfl8q6r9WX4O+NAUxDUbdPK7rXFqT7qq6ptJPp1k86q6tZdx9YskD6WVwJ5aVV8dpoi/v5oWqmrf4bYn2RF4HHBVM8LoscDlSfaoqt9OYYjT2kjPbxinAt/EJPYvxnp2SQ4BXgj8Tfn9ygdZi989jc06menXnfinwLZJHpfkYcDBwLlDypwLvKFZfgVwgX9ZdGzM5ztknNuLaY2P08SdC7y+meV1T2BlVd3S66BmiiR/PTg2PsketP5u8+VWB5rn9l/Asqr66AjF/P3VtFZVS6rqr6pqoKoGaHWv29UEtnNJ2nuvHABc06tY+k2S59Mai/3iqlrV63g043WSL81406oltqruTfJW4NvAOsBJVbU0yQeBxVV1Lq1/bH0xyS9pTfRycO8i7i8dPt/Dk7yYVneY24BDehZwH0lyGrAPsHmS39B6e/1QgKo6kdYb7f2AXwKrgEN7E2l/6uD5vgJ4S5J7gT8CB/tyq2PPAF4HLElyZbPtX4G54O+vNIscm+RJwH3ADcBhPY6nn3wSeDjwneZ96iVV5fPrUJKXAicAc4CFSa6sqr/rcVjT1kj/nu9xWFMu/jtPkiRJktQvplt3YkmSJEmSRmQSK0mSJEnqGyaxkiRJkqS+YRIrSZIkSeobJrGSJEmSpL5hEitJkiRJ6hsmsZIkSZKkvmESK0mSJEnqGyaxkiRJkqS+YRIrSZIkSeobJrGSJEmSpL5hEitJkiRJ6hsmsZIkSZKkvmESK0mSJEnqGyaxkiRJkqS+YRIraUxJXpPk/FH2PzPJtVMZkyRJ6kySE5P8W6/jkLolVdXrGKRZJ8ki4JSq+lyvYxmPJAVsW1W/7HUskiSNV7/Xx8NJcgjw5qrau9exSJPFllhJkiRJUt8wiZXGkOQ9SW5KcleSa5P8TZK/TrIqyWZt5XZNsiLJQ5MckuRHST6c5PYk1yd5QVPuGOCZwCeT3J3kk832jye5McmdSS5L8sy2c38zyUfa1k9PctII8R6V5KwkZzQxX55kp7b9T06yKMkdSZYmeXGzfYsmnsGfVU2LK4P30yz/oDnVVU25g5Lsk+Q3bc/rrCExfTzJJ5rlTZL8V5Jbmud6dJJ1xv0fSJI0K/RpffzlJP/dxLw0yby2/Vsk+UoT6/VJDm/bt36SLzQxL0vy7sF6ttl/RJJfNef9eZKXNtufDJwI7NXc0x3N9pOTHN0sL0vywrZzrdvEsGuzvmeSHzf/TrgqyT7j+M8lTSqTWGkUSZ4EvBXYvao2Bv4OWF5VvwUWAa9sK/464PSquqdZfxpwLbA58CHgv5Kkqt4L/BB4a1VtVFVvbcr/FNgZeBTwJeDMJOs1+94IvC7Jc5O8BtgDeNsooR8AnNl2rnOayvyhwNeB84G/Av4ZODXJk6rq5iaejapqI+Bs4PShJ66qZzWLOzVlzxhS5HRgvyQbN89wneY5fanZfzJwL/AEYBfgb4E3j3IvkqRZro/r4xfTqhc3Bc4FBhPlh9Cqj68CtgT+Bnh7kr9rjns/MAA8Hnge8Noh5/0VrQR8E+ADwClJHlNVy4DDgIube9p0mJhOA17Vtv53wK1VdXmSLYGFwNHN/b8L+EqSOaPcozTlTGKl0a0BHg5sn+ShVbW8qn7V7PsCTaXSJGqvAr7YduwNVfXZqlrTlH0M8OiRLlRVp1TV76vq3qr6SHPdJzX7fgu8pTnPx4HXV9Vdo8R9WVWd1VTgHwXWA/ZsfjYCjq2qP1fVBcA3eGBlRpL3ANvRqqzXSlXdAFwOvLTZ9FxgVVVdkuTRwH7A26vqD1X1v8DHgIPX9jqSpFmlX+vjH1XVN5trfxEY7Bm1OzCnqj7Y1Me/Bj7L/fXhK4H/V1W3V9VvgE8MifHM5uXzfc3L5F/QSqg78SXgxUk2aNZfTSuxhdZz/GYT831V9R1gMa26W5o2TGKlUTQTF70dOAr436bb0BbN7q/RqkwfR+st6cqqurTt8N+2nWdVs7jRSNdK8q6mi8/KpvvPJrTeGg/6OrAOcG1V/WiM0G9su/Z9wG+ALZqfG5ttg26g9RZ4MI4X0Hqr/JKq+uMY1xnJl7g/MX4197fCbg08FLil6aZ0B/CftFqFJUkaVh/Xx79tW14FrJdkXVr14RaDdWFznX/l/uR6C9rq8iHLJHl9kivbjt1hSIwjap7lMuBFTSL7Yh5YTx84JK69aSX+0rRhEiuNoaq+1MzwtzVQwHHN9j8BX6b11vJ1PPCt75inbV9pxtu8m9ab10c23X9WAmkrdgytSucxSR7QcjqMrdrO/RDgscDNzc9WzbZBc4GbmrJPovV2+ZVV9YAKcy2dCeyT5LG0WmQHK8cbgdXA5lW1afPziKp6ygSuJUmaBfq0Ph7JjcD1bXXhplW1cVUNtnjeQqvuHtRer29Nq9X2rcBmTYxXt8XYyadHBrsUHwD8vO1rAzcCXxwS14ZVdew471OaFCax0iiSPKkZ9/Jw4E/AH4H2Vsz/Bg6h9RZzbSrN39Ea5zJoY1rjRFcA6yZ5H/CItjieBRwKvB54A3BCM25lJLsleVnztvfttBLHS4Cf0HoT/O5mjOw+wIuA05M8gtbb7Pd28GZ5aPwPUFUraI1R+jytSnpZs/0WWuNxP5LkEUkekmSbJM8e43qSpFmsj+vjkVwK3JXWZFXrJ1knyQ5Jdm/2fxn4lySPbM7/1rZjN6SVqK5oYjqUVkts+z09NsnDRrn+6bTmpHgL979oBjiFVgvt3zUxrZfW5I2PHfYsUo+YxEqjezhwLHArrS5BfwX8y+DOqrqIViV6eTMWtFMfB16R1qyDnwC+DZwHXEere++faLoONcnlf9OaeOKmqvoh8F/A55Nk2LO3ktGDgNtpvZV+WVXdU1V/ppW0vqC5p0/TGs9zDbArrTE/H0vbLMUjnP8o4AtNV6NXjlDmS8C+PLByhFbF/zDg5018Z2E3JUnS6Pq1Ph5WM0b2hbQmkLq+ua/P0eq6DPBBWkOBrge+S6uuXN0c+3PgI8DFtBLWHYGL2k5/AbAU+G2SW0e4/i3N8U8HzmjbfiOt1tl/pZUk3wj8X8wZNM2kqpMeB5JGkuQC4EvT5UPpSY4CnlBVQ2cylCRpxppu9XE3JXkLcHBV2XNJwrcq0oQ03X52pe0tpiRJmlozrT5O8pgkz2iG3TwJeCetT99JwiRWGrckX6DVxeftY0yvL0mSJskMrY8fRmv2/rtodQ/+Gq0hQJKwO7EkSZIkqY/YEitJkiRJ6hvr9jqAtbH55pvXwMBAr8OQJM0Al1122a1VNafXcfQ762ZJUrd0Wjf3VRI7MDDA4sWLex2GJGkGSLI2n+HQCKybJUnd0mndbHdiSZIkSVLfMImVJEmSJPUNk1hJkiRJUt8wiZUkSZIk9Q2TWEmSJElS3zCJlSRJkiT1DZNYSZIkSVLfMImVJEmSJPUNk1hJkiRJUt9Yt9cBrI0lN61k4IiFvQ5DktQjy4/dv9chaJJYv0vS8Kz7HsyWWEmSJElS3zCJlSRJkiT1DZNYSZIkSVLfmLIkNskhST45VdeTJEmSJM08tsRKkjQLJPlxB2XenmSDtvVvJtl0UgOTJGktdS2JTXJOksuSLE0yv9l2aJLrklwKPKOt7MlJTkyyuNn/wm7FIUmSHqyqnt5BsbcDf0liq2q/qrpjsmKSJGk8utkS+8aq2g2YBxyeZEvgA7SS172B7YeUHwD2APYHTkyyXhdjkSRJbZLc3fy5T5JFSc5Kck2SU9NyOLAFcGGSC5uyy5Ns3su4JUkaqptJ7OFJrgIuAbYCXgcsqqoVVfVn4Iwh5b9cVfdV1S+AXwPbDXfSJPObFtvFa1at7GK4kiTNWrvQanXdHng88Iyq+gRwM/CcqnrOaAe3180rVqyY9GAlSWrXlSQ2yT7AvsBeVbUTcAVwzRiH1RjrrY1VC6pqXlXNW2eDTSYaqiRJgkur6jdVdR9wJa3eUR1rr5vnzJkzGfFJkjSibrXEbgLcXlWrkmwH7AmsDzw7yWZJHgocOOSYA5M8JMk2tN4CX9ulWCRJ0uhWty2vAdbtVSCSJK2tblVa5wGHJVlGKxm9BLgFOAq4GLiD1pvedv8DXAo8Ajisqv7UpVgkSdL43AVsDNza60AkSRpJV5LYqloNvGCYXYuAz49w2Her6rBuXF+SJHXFAuC8JDe3jYsddriPJEm9YvchSZJmgaraqPlzEa2XzIPb39q2fAJwAkCSdWi1yt45lXFKkjSWniSxVXVIL64rSZI6thT4XFXd0+tAJElq11ctsTtuuQmLj92/12FIkjTjVdWwn76TJKnXuvmdWEmSJEmSJlVftcRKkqSZabk9rSRJHbIlVpIkSZLUN/qqJXbJTSsZOGJhr8OQJPWALXWSJP3/7N17mF1leffx789gORsV4gEExioVgQhCRFAsaNEieMAKBawieEg9vWitVvpKFRXfglit9dhoESuICBWkpoIHiAqCOAFiwAC1GkWgNQhEkBoh3O8fa41shpnMJLNn9uyZ7+e69jVrP8+z1rr3Ysiaez+HJbAnVpIkSZLUR/qqJ1aSJEnd4wg3afpzJNKD2RMrSZIkSeobJrGSJEmSpL7R8yQ2ySFJdu51HJIkSZKk6a/nSSxwCGASK0mSJEka05hJbJKBJNclOSPJiiTnJNksycokW7dtFiRZ0m6fkOTUJEuS/CTJsR3HOirJD5MsS/L5JM8AXgSckuTqJE+YpM8pSZIkSZoBxrs68ZOAV1fVpUlOBd4wRvudgGcDWwLXJ/kk8EfA8cAzqurWJI+sqtuSnA98tarOGelASRYCCwHmPGzeOMOVJEmSJM1E4x1OfGNVXdpunw7sO0b7xVW1pqpuBX4JPBp4DnB2W0ZV3TaeE1fVoqpaUFUL5mw2d5zhSpI0MyXZPMnidlTTNUkOb0dHfSDJ8iRXJHli2/aFSb6f5Kok30zy6LZ8iySfbdv/MMlL2/LnJbksyZVJzk6yRS8/qyRJIxlvElsjvL+3Y/9NhtWv6dhei8+jlSSpWw4Ebq6q3apqV+CCtnx1Vc0HPgb8Y1t2CbB3VT0V+CLwN2353w21r6qnABe1U4SOBw6oqj2AQeCtU/KJJElaD+NNYrdPsk+7/TKam+JKYM+27KXjOMZFwGFJtgJI8si2/E6aYceSJGlsy4HnJjk5ybOqanVbfmbHz6F79uOAC5MsB94O7NKWHwB8fOiAVXU7sDfNQouXJrkaeCWww0gBJFmYZDDJ4KpVq7r3ySRJGofxJrHXA29MsgJ4BPBJ4D3AR5IM0vS2rlNVXQu8H/h2kmXAh9qqLwJvb4c6ubCTJEnrUFU3AHvQJLMnJnnXUFVns/bnR4GPtT20f8mDR051CvCNqtq9fe1cVa8eJYbfT/WZN8/1KiRJU2u8w3zvraqXDyv7Ls1iTQ9QVScMe79rx/bngM8Nq78UH7EjSdK4JNkGuK2qTk9yB/Catupw4KT252Vt2Vzgpnb7lR2H+QbwRuAt7TEfAVwOfDzJE6vqx0k2B7Ztk2ZJkqaN6fCcWEmSNH7zgSvaIb/vBk5syx+R5IfAm4G/astOAM5OshS4teMYJ7btr2lHRz27qlYBRwNntse5jOZpA5IkTStj9sRW1Upg17HaSZKkyVdVFwIXdpYlATilqt4xrO1XgK+McIy7eGDP7FD5RcDTuhmvJEnd1lerBs/fdi6DJx3c6zAkSZIkST3SV0msJEl6sKoa6HUMkiRNFefESpIkSZL6hkmsJEmSJKlv9NVw4uU3rWbguMW9DkOSJmyl8/slTQP+WySpH9kTK0mSJEnqGyaxkiRJkqS+YRIrSZIkSeobPZkTm+SuqtqiF+eWJEmSNLv087o6zl1/sClNYpMEyFSeU5IkSZI0c2xQEpvkJODGqvp4+/4E4C6aBPXPgY2Bc6vq3UkGgAuB7wN7Age1+3wYeB7w38ARVbVqQp9EkiRJkjTjbeic2LNoktUhfw6sAnYE9gJ2B/ZM8sdt/Y7AJ6pql6r6GbA5MFhVuwDfBt69gXFIkiRJkmaRDeqJraqrkjwqyTbAPOB2YD5Nz+pVbbMtaJLXnwM/q6rLOw5xH00iDHA68OXRzpVkIbAQYM7D5m1IuJIkSZKkGWIic2LPBg4FHkOTkO4A/H1V/XNno3Y48W/GOFaNWlG1CFgEsPFjdxy1nSRJkiRp5pvII3bOAo6gSWTPppn3+qokWwAk2TbJo9Zx3kPb7ZcBl0wgDkmSNEySOb2OQZKkybDBSWxVXQtsCdxUVbdU1deBLwCXJVkOnNPWj+Q3wF5JrgGeA7x3Q+OQJGm2STKQ5LokZyRZkeScJJslWZnk5CRXAoclOTLJ8iTXJDm5Y/+7knw4ybVJvpVkXlu+pN3/iiQ3JHlWzz6kJEmjmNAjdqpq/rD3HwE+MkLTXYe18xmxkiRNzJOAV1fVpUlOBd7Qlv+qqvZo1624nObJALcDX09ySFWdx/0LLP5VknfRLLD4pnb/japqryQHteUHTOFnkiRpTBMZTixJknrnxqq6tN0+Hdi33R5aOPFpwJKqWlVV9wJnAENPDRi+wOLQvnD/YotLgYGRTpxkYZLBJIOrVvmEPEnS1DKJlSSpPw1f7HDo/ViLKY51rDXtz7WMMmKrqhZV1YKqWjBvnk8OkCRNLZNYSZL60/ZJ9mm3R1ok8QpgvyRbt4s8HUnzbHZwgUVJUh+b0JzYqTZ/27kMnnRwr8OQJGk6uB54Yzsf9kfAJ4H/M1RZVbckOQ64GAiwuKq+0lYPLbB4PPBL4PApjVySpAnoqyRWkiT93r1V9fJhZQOdb6rqTODMkXauqreOULZ/x/atw48nSdJ04HBiSZIkSVLfsCdWkqQ+U1UrGfb4uvXc30fdSZL6Vl8lsctvWs3AcYt7HYakPrLSefSSJEkzSl8lsZIkSZK0vvxSe2ZxTqwkSZIkqW+YxEqSJEmS+saUJrFJjk7ysak8pyRJkiRp5rAnVpIkSZLUN7q6sFOS84DtgE2Aj1TVoiTHAH8L3AEsA9YkmQv8EHh8Vd2XZHPgOuAPq+qebsYkSZIkSRtiOjwZxUWpHqzbPbGvqqo9gQXAsUm2Bd4DPBPYF9gZoKpWA1cD+7X7vQC4cKQENsnCJINJBtfevbrL4UqSJEmS+km3k9hjkywDLqfpkX0FsKSqVlXV74CzOtqeBRzebh8xrO73qmpRVS2oqgVzNpvb5XAlSZIkSf2ka0lskv2BA4B9qmo34CqaIcKjOR84MMkjgT2Bi7oViyRJkiRpZupmT+xc4PaqujvJTsDewKbAfkm2SvJQ4LChxlV1F/AD4CPAV6tqbRdjkSRJkiTNQN1MYi8ANkqyAjiJZkjxLcAJwGXApcCKYfucBbycUYYSS5Kk3kjy3iQH9DoOSZKG69rqxFW1Bnj+CFVLgM+Oss85QLoVgyRJ6o6qelevY5AkaSQ+J1aSpD6W5KgkP0yyLMnnkzw6ybnt+2VJntG2e2uSa9rXW9qygSQrknw6ybVJvp5k07butCSH9vCjSZI0oq4+J1aSJE2dJLsAxwPPqKpb28USPwl8u6pekmQOsEWSPYFjgKfTjID6fpJvA7cDOwJHVtVrk3wJeClw+hjnXQgsBNh+++0n6dNJkjSyvkpi5287l0Ef9itJ0pDnAGdX1a0AVXVbkucAR7Xv1wKrk+wLnFtVvwFI8mXgWTRPCvhpVV3dHm8pMDDWSatqEbAIYMGCBdXNDyRJ0lgcTixJ0uy2pmN7LX32BbckafYxiZUkqX9dBByWZCuAdjjxt4DXt+/nJJkLfBc4JMlmSTYHXtKWSZLUd/y2VZKkPlVV1yZ5P/DtJGuBq4A3A4uSvJqmZ/X1VXVZktOAK9pdP1NVVyUZGOsUkxS6JEkbrK+S2OU3rWbguMW9DkNSa6Vz1KWeq6rPAZ8bVvziEdp9CPjQsLKVwK4d7z/YUb0VcFvXApUkqUscTixJkh4gyanAZsAlvY5FkqTh+qonVpIkTb6qelWvY5AkaTT2xEqSJEmS+oY9sZIkSZI0Atf/mJ7siZUkSZIk9Y2uJrFJzkuyNMm1SRa2ZXd11B/aLvFPkq8kOard/sskZ3QzFkmSJEnSzNPt4cSvqqrbkmwK/CDJv62j7ULg0iQ/Bf4a2LvLsUiSJEmSZphuJ7HHJnlJu70dsONoDavqf5K8C7gYeElVjfgsurZHdyHAnIfN63K4kiRJkjR5Bo5bPKH9nZf7YF0bTpxkf+AAYJ+q2g24CtgEqI5mmwzbbT7wK2Cb0Y5bVYuqakFVLZiz2dxuhStJkiRJ6kPdnBM7F7i9qu5OshP3Dw/+nyRPTvIQYKiXliR7Ac8Hngq8LcnjuxiLJEmSJGkG6mYSewGwUZIVwEnA5W35ccBXge8BtwAk2Rj4NM0c2ptp5sSemiRdjEeSJEmSNMN0bU5sVa2h6VkdyTkjlO3Wse/5wPndikWSJEmSNDP5nFhJkiRJUt8wiZUkSZIk9Q2TWEmSZogkA0lWJPl0kmuTfD3JpkmWJFnQttk6ycp2++gk5yX5RpKVSd6U5K1JrkpyeZJH9vQDSZI0gm4/J3ZSzd92LoM+J0mSpHXZETiyql6b5EvAS8dovyvNkwI2AX4MvKOqnprkw8BRwD9OZrCSJK0ve2IlSZpZflpVV7fbS4GBMdpfXFV3VtUqYDXw72358tH2TbIwyWCSwVWrVk08YkmS1oNJrCRJM8uaju21NKOu7uX+e/4m62h/X8f7+xhlxFZVLaqqBVW1YN68eROPWJKk9WASK0nSzLcS2LPdPrSHcUiSNGF9NSd2+U2rGThuca/DkGaMlc4xl2aLDwJfSrIQ8EYqSeprfZXESpKk0VXVSpqFmobef7Cj+ikd28e39acBp3W0H+jYfkCdJEnThcOJJUmSJEl9wyRWkiRJktQ3TGIlSZIkSX3DObGSJEmSNElcSLP71qsnNslAkhVJPp3k2iRfT7Jpkt2TXJ7kh0nOTfKItv2SJAva7a2TrGy3j07y5SQXJPnPJB/o+ieTJEmSJM04GzKceEfg41W1C3AH8FLgX4F3VNVTgOXAu8dxnN2Bw4H5wOFJttuAWCRJkiRJs8iGJLE/raqr2+2lwBOAh1fVt9uyzwF/PI7jfKuqVlfVb4EfATuM1CjJwiSDSQbX3r16A8KVJEmSJM0UG5LErunYXgs8fB1t7+04xyZjHGfE+blVtaiqFlTVgjmbzV3PUCVJkiRJM0k3FnZaDdye5FlV9V3gFcBQr+xKYE/gCuDQLpxLkiRJkmaNgeMWr7N+Ni4c1a3ViV8JfCrJZsBPgGPa8g8CX0qyEFj31ZckSZIkaQzrlcRW1Upg1473H+yo3nuE9tcBT+koOr4tPw04raPdC9YnDkmSJEnS7LQhc2IlSZIkSeoJk1hJkiRJUt/o1pzYKTF/27kMzsKJy5IkSZKkhj2xkiRJkqS+YRIrSdIMkmTzJIuTLEtyTZLDk5zXUf/cJOe223clOSXJtUm+mWSvJEuS/CTJi3r2ISRJWgeTWEmSZpYDgZurareq2hW4ANgpyby2/hjg1HZ7c+CiqtoFuBM4EXgu8BLgvaOdIMnCJINJBletWjVZn0OSpBH11ZzY5TetHvNhv5o6s/HBypLUB5YD/5DkZOCrVfXdJJ8HXp7ks8A+wFFt29/RJLlD+62pqnuSLAcGRjtBVS0CFgEsWLCgJudjSJI0sr5KYiVJ0rpV1Q1J9gAOAk5M8i3gM8C/A78Fzq6qe9vm91TVUBJ6H7CmPcZ9SfwbQZI0LXmDkiRpBkmyDXBbVZ2e5A7gNVV1c5KbgeOBA3oaoCRJE2QSK0nSzDIfOCXJfcA9wOvb8jOAeVW1omeRSZLUBSaxkiTNIFV1IXDhCFX7Ap8e1naLju0TRquTJGk66dnqxEmOTvKxdvt1SY4aax9JkrT+kiwFngKc3utYJEmaqGnRE1tVn+p1DJIkzVRVtWevY5AkqVsmrSc2yXlJlrYPUF/Ylh2T5IYkVwDP7Gh7QpK3TVYskiRJkqSZYTJ7Yl9VVbcl2RT4QZLFwHuAPYHVwMXAVWMdpE2AFwLMedi8MVpLkiRJ0syx8qSDex3CtDOZc2KPTbIMuBzYDngFsKSqVlXV74CzxnOQqlpUVQuqasGczeZOYriSJEmSpOluUpLYJPvTPIdun6rajabH9brJOJckSZIkafaYrJ7YucDtVXV3kp2AvYFNgf2SbJXkocBhk3RuSZIkSdIMNVlzYi8AXpdkBXA9zZDiW4ATgMuAO4Crh+1TkxSLJEmSJPWlgeMWr7N+Ns6ZnZQktqrWAM8foWoJ8NkRyrcCfjYZsUiSJEmSZo7JXNhpXJK8D3g6cH6vY5EkSZIkTW89T2Kr6u+qaq+q+lWvY5EkSZIkTW+T+ZzYrpu/7VwGZ+GYb0mSJElSo+c9sZIkaWolOSHJ29ZRf0iSnacyJkmSxsskVpIkDXcIYBIrSZqWTGIlSZoFkrwzyQ1JLgGe1JY9IckFSZYm+W6SnZI8A3gRcEqSq5M8oaeBS5I0TF/NiV1+0+oxn5M0W8zG50FJkjZMkj2BI4Ddae79VwJLgUXA66rqP5M8HfhEVT0nyfnAV6vqnF7FLEnSaPoqiZUkSRvkWcC5VXU3QJukbgI8Azg7yVC7jcdzsCQLgYUA22+/fdeDlSRpXUxiJUmanR4C3FFVu6/vjlW1iKYXlwULFlSX45IkaZ2cEytJ0sz3HeCQJJsm2RJ4IXA38NMkhwGksVvb/k5gy96EKknSupnESpI0w1XVlcBZwDLga8AP2qq/AF6dZBlwLfDitvyLwNuTXOXCTpKk6WZShxMnmVNVayfzHJIkaWxV9X7g/SNUHThC20vxETuSpGlqg3tikwwkuS7JGUlWJDknyWZJViY5OcmVwGFJjkyyPMk1SU7u2P+uJO9PsizJ5Uke3ZVPJEmSJEmasSY6nPhJNMvxPxn4NfCGtvxXVbUHzRyck4Hn0Czr/7Qkh7RtNgcur6rd2navnWAskiRJkqQZbqJJ7I3tkCOA04F92+2z2p9PA5ZU1aqquhc4A/jjtu53wFfb7aXAwEgnSLIwyWCSwbV3r55guJIkSZKkfjbRJHb4svpD738zjn3vqaqh9msZZX5uVS2qqgVVtWDOZnM3MExJkiRJ0kww0YWdtk+yT1VdBrwMuAR4akf9FcA/JdkauB04EvjoBM8pSZIkSbPCypMO7nUI085Ee2KvB96YZAXwCOCTnZVVdQtwHHAxzbL+S6vqKxM8pyRJkiRplppoT+y9VfXyYWUDnW+q6kzgzOE7VtUWHdvnAOdMMBZJkiRJ0gw30Z5YSZIkSZKmzAb3xFbVSmDX7oUiSZIkSeo0cNzirh5vJsyxtSdWkiRJktQ3JjondkrN33YugzPgmwNJkiRJ0oaxJ1aSJEmS1DdMYiVJkiRJfcMkVpIkPUiS/0jy8F7HIUnScH01J3b5Tau7vjrXVJoJK4FJkmaHqjqo1zFIkjQSe2IlSepTSTZPsjjJsiTXJDk8ydOSfK8tuyLJlkk2SfLZJMuTXJXk2e3+Ryf5cpILkvxnkg90HHtlkq179+kkSRpZX/XESpKkBzgQuLmqDgZIMhe4Cji8qn6Q5GHA/wJvBqqq5ifZCfh6kj9qj7E78FRgDXB9ko9W1Y1T/UEkSRove2IlSepfy4HnJjk5ybOA7YFbquoHAFX166q6F9gXOL0tuw74GTCUxH6rqlZX1W+BHwE7jHXSJAuTDCYZXLVqVfc/lSRJ6zAtklgXj5Akaf1V1Q3AHjTJ7InAn23AYdZ0bK9lHKO0qmpRVS2oqgXz5s3bgFNKkrThpkUSW1UHVdUdvY5DkqR+kmQb4O6qOh04BXg68NgkT2vrt0yyEfBd4C/asj+i6bG9vjdRS5I0MeOeE5tkc+BLwOOAOcD7gJ8AHwE2p/km90+Ae4BPAguAe4G3VtXFSY4GXgRsBjwBOLeq/qY99kpgQVXd2pVPJUnS7DAfOCXJfTT339cDAT6aZFOa+bAHAJ8APplkOc29+eiqWpNkrOPXpEUuSdIGWp+FnXqyeESShcBCgDkPc8iSJElDqupC4MIRqvYeoeyYEfY/DTit4/0LAJLMAbYEft2NOCVJ6qb1GU7ck8UjOufdzNls7nqEK0mSNtC1wGeq6p5eByJJ0nDj7omtqhuS7AEcRLN4xEUbcL71XjxCkiRNraraqdcxSJI0mnH3xLp4hCRJkiSp19anJ9TFIyRJkiRpCq086eBehzDtrM9wYhePkCRJkiT11HR4TqyLR0iSJEmSxqXnCyu5eIQkSZIkabx6nsSuj/nbzmXQMeGSJEmSNGv1VRIrSZIkSbPJwHGLp+xc/bKI1HSYEytJkiRJ0riYxEqSJEmS+kZfDSdeftPqrnWn90tXuSRJkiTpfvbESpIkSZL6hkmsJEmSJKlvmMRKkjSLJJnT6xgkSZqISU9ik5yQ5G3rqD8kyc6THYckSTNdkoEk1yU5I8mKJOck2SzJyiQnJ7kSOCzJkUmWJ7kmyckd+9+V5P1JliW5PMmje/hxJEka0XToiT0EMImVJKk7ngR8oqqeDPwaeENb/quq2gP4DnAy8Bxgd+BpSQ5p22wOXF5Vu7XtXjvSCZIsTDKYZHDVqlWT9kEkSRrJpCSxSd6Z5IYkl9DcTEnyhCQXJFma5LtJdkryDOBFwClJrk7yhMmIR5KkWeTGqrq03T4d2LfdPqv9+TRgSVWtqqp7gTOAP27rfgd8td1eCgyMdIKqWlRVC6pqwbx587odvyRJ69T1R+wk2RM4gubb3Y2AK2luhIuA11XVfyZ5Os23xM9Jcj7w1ao6p9uxSJI0C9Uo738zjn3vqaqh9mvps0fxSZJmh8noiX0WcG5V3V1VvwbOBzYBngGcneRq4J+Bx47nYJ1DltbevXoSwpUkaUbZPsk+7fbLgEuG1V8B7Jdk63aRpyOBb09lgJIkTcRUzYl9CHBHVe3e8XryeHbsHLI0Z7O5kxymJEl973rgjUlWAI8APtlZWVW3AMcBFwPLgKVV9ZUpj1KSpA00GUnsd4BDkmyaZEvghcDdwE+THAaQxm5t+zuBLSchDkmSZqN7q+rlVfXkqnppOzJqoKpuHWpQVWdW1fyq2rWq3tFRvkXH9jlVdfQUxy5J0pi6nsRW1ZU0i0csA74G/KCt+gvg1UmWAdcCL27Lvwi8PclVLuwkSZIkSVqXSVmwoareD7x/hKoDR2h7KT5iR5KkCauqlcCuvY5DkqTJNB2eEytJkiRJ0ri4dL4kSZIkTVMrTzq41yFMO/bESpIkSZL6Rl/1xM7fdi6DfhMhSZIkSbOWPbGSJEmSpL7RVz2xkiRJkjSbDBy3uNchjGmq5+3aEytJkiRJ6ht91RO7/KbVXfkmwhW+JEmSJKk/2RMrSZIkSeobJrGSJEmSpL5hEitJkgBIcnSSj7Xbr0tyVK9jkiRpuL6aEytJkqZGVX2q1zFIkjQSe2IlSZolkpyXZGmSa5MsbMuOSXJDkiuAZ3a0PSHJ23oWrCRJo5hQEptk8ySLkyxLck2Sw5Oc11H/3CTnttt3JTmlvXF+M8leSZYk+UmSF03wc0iSpLG9qqr2BBYAxybZFngPTfK6L7BzL4OTJGk8JtoTeyBwc1XtVlW7AhcAOyWZ19YfA5zabm8OXFRVuwB3AicCzwVeArx3gnFIkqSxHZtkGXA5sB3wCmBJVa2qqt8BZ43nIEkWJhlMMrhq1apJDFeSpAebaBK7HHhukpOTPKuqVgOfB16e5OHAPsDX2ra/o0lyh/b7dlXd024PjHaCzhvl2rtXTzBcSZJmpyT7AwcA+1TVbsBVwHUbcqyqWlRVC6pqwbx588beQZKkLprQwk5VdUOSPYCDgBOTfAv4DPDvwG+Bs6vq3rb5PVVV7fZ9wJr2GPclGTWOqloELALY+LE71mjtJEnSOs0Fbq+qu5PsBOwNbArsl2Qr4NfAYcCyHsYoSdKYJpTEJtkGuK2qTk9yB/Caqro5yc3A8TTf+EqSpN67AHhdkhXA9TRDim8BTgAuA+4Arh62j18eS5KmnYk+Ymc+cEqS+4B7gNe35WcA86pqxQSPL0mSuqCq1gDPH6FqCfDZEcq3An42mTFJkrQhJjqc+ELgwhGq9gU+PaztFh3bJ4xWJ0mSeivJ+4Cn0/TSSpI0rXT9ObFJlgJPAU7v9rElSdLkq6q/q6q9qupXvY5FkqThJjqc+EHa589JkiRJktR1Xe+JlSRJkiRpsnS9J3Yyzd92LoMnHdzrMCRJkiRpSqw0/3kQe2IlSZIkSX3DJFaSJEmS1DdMYiVJkiRJfcMkVpIkSZLUN0xiJUmSJEl9wyRWkiRJktQ3TGIlSZIkSX3DJFaSJEmS1DdMYiVJkiRJfSNV1esYxi3JncD1vY5jhtoauLXXQcxgXt/J5fWdXDP1+u5QVfN6HUS/S7IK+Fmv45hCM/X/h27x+ozOa7NuXp/RzaZrM657c78lsYNVtaDXccxEXtvJ5fWdXF7fyeX1le7n/w/r5vUZnddm3bw+o/PaPJjDiSVJkiRJfcMkVpIkSZLUN/otiV3U6wBmMK/t5PL6Ti6v7+Ty+kr38/+HdfP6jM5rs25en9F5bYbpqzmxkiRJkqTZrd96YiVJkiRJs5hJrCRJkiSpb0y7JDbJgUmuT/LjJMeNUL9xkrPa+u8nGehBmH1rHNf36CSrklzdvl7Tizj7UZJTk/wyyTWj1CfJP7XX/odJ9pjqGPvZOK7v/klWd/zuvmuqY+xnSbZLcnGSHyW5NsmbR2jj77DUIclfJ6kkW/c6lukkyfvafyOuTvL1JNv0OqbpIskpSa5rr8+5SR7e65imiySHtfef+5L4OJnWWH+7z1bTKolNMgf4OPB8YGfgyCQ7D2v2auD2qnoi8GHg5KmNsn+N8/oCnFVVu7evz0xpkP3tNODAddQ/H9ixfS0EPjkFMc0kp7Hu6wvw3Y7f3fdOQUwzyb3AX1fVzsDewBtH+PfB32GplWQ74HnAz3sdyzR0SlU9pap2B74K+KXi/b4B7FpVTwFuAP62x/FMJ9cAfwZ8p9eBTBfr8bf7rDOtklhgL+DHVfWTqvod8EXgxcPavBj4XLt9DvAnSTKFMfaz8VxfbaCq+g5w2zqavBj412pcDjw8yWOnJrr+N47rqwmoqluq6sp2+05gBbDtsGb+Dkv3+zDwN4ArZA5TVb/ueLs5XqPfq6qvV9W97dvLgcf1Mp7ppKpWVNX1vY5jmvFv91FMtyR2W+DGjve/4MF/RP2+TfuPwGpgqymJrv+N5/oCvLQd5nJO+02zumO8118bbp8ky5J8LckuvQ6mX7XTNJ4KfH9Ylb/DEpDkxcBNVbWs17FMV0nen+RG4C+wJ3Y0rwK+1usgNK153x3FRr0OQNPOvwNnVtWaJH9J0+v9nB7HJI3HlcAOVXVXkoOA82iGvWo9JNkC+DfgLcN6U6RZJck3gceMUPVO4P/SDCWetdZ1farqK1X1TuCdSf4WeBPw7ikNsIfGujZtm3fSTOM4Yypj67XxXBtpPKZbEnsT0Nnz97i2bKQ2v0iyETAX+NXUhNf3xry+VdV5LT8DfGAK4potxvP7rQ3UmXBV1X8k+USSravq1l7G1U+SPJQmgT2jqr48QhN/hzVrVNUBI5UnmQ88HljWzmZ6HHBlkr2q6r+nMMSeGu36jOAM4D+YRUnsWNcmydHAC4A/qapZNdR6PX5v1PC+O4rpNpz4B8COSR6f5A+AI4Dzh7U5H3hlu30ocNFs+wdgAsa8vsPmt72IZl6cuuN84Kh2hde9gdVVdUuvg5opkjxmaH58kr1o/n3zC65xaq/dvwArqupDozTzd1izXlUtr6pHVdVAVQ3QDO/bYzYlsGNJ0jkK5sXAdb2KZbpJciDNXOoXVdXdvY5H0954cqNZaVr1xFbVvUneBFwIzAFOraprk7wXGKyq82n+yPp8kh/TLPJyRO8i7i/jvL7HJnkRzRCX24CjexZwn0lyJrA/sHWSX9B86/xQgKr6FM030QcBPwbuBo7pTaT9aRzX91Dg9UnuBf4XOMIvuNbLM4FXAMuTXN2W/V9ge/B3WNJ6OSnJk4D7gJ8Br+txPNPJx4CNgW+037teXlVeHyDJS4CPAvOAxUmurqo/7XFYPTXa3+49DmtaiH/jSZIkSZL6xXQbTixJkiRJ0qhMYiVJkiRJfcMkVpIkSZLUN0xiJUmSJEl9wyRWkiRJktQ3TGIlSZIkSX3DJFaSJEmS1DdMYiVJkiRJfcMkVpIkSZLUN0xiJUmSJEl9wyRWkiRJktQ3TGIlSZIkSX3DJFaSJEmS1DdMYiVJkiRJfcMkVppESU5IcvoG7rt/kl90O6apkuRZSa5fR/32Se5KMmcq45IkzT6z+X68oZL83ySf6XUc0khMYiVNiqr6blU9aeh9kpVJDuio/3lVbVFVa3sToSRJgpET9ar6f1X1ml7FJK2LSaw0AyXZqNcxSJI023k/liaHSaxmjSTvSHLOsLKPJPmndnubJOcnuS3Jj5O8tqPdnHZYzX8luTPJ0iTbdRzjxiS/bsufNezUmyQ5q93vyiS7dRy3kjyx4/1pSU4cJf7jOs7/oyQv6ag7OsmlST6c5FfAe9vPMb+jzaOS3J1k3gjHHtr/Y0lWJ7kuyZ901K/r2tzRDgu+K8lv2s800PmtbpLPA9sD/962+5u2TSXZKMnhSQaHxfRXSc5vtzdO8sEkP0/yP0k+lWTTka6TJGl683485v34kvaed3uSnyZ5fkf93CT/kuSWJDclOTHttJz22vxDklvb/d40dJ9t649JsqKN+ydJ/rIt3xz4GrBNx/18m3QMwU7ytSRvGhbrsiR/1m7vlOQb7We9Psmfj3TtpG4xidVs8kXgoCRbQvOPPfDnwBc66n8BbAMcCvy/JM9p694KHAkcBDwMeBVwd1v3A2B34JHtsc5OsknHeV8MnN1Rf16Sh25A/P8FPAuYC7wHOD3JYzvqnw78BHg08L7287y8o/5I4FtVtWqU4z+9PcfWwLuBLyd5ZFs36rWpqoe3w4K3AD4CfBe4qfPAVfUK4OfAC9u2Hxh27n8HnpRkx46yl3H/f5uTgD+iuc5PBLYF3jXK55AkTW/ej8e+H19Pcz/+APAvSdLWnQbcS3MvfCrwPGBoyO9rgefTXIM9gEOGHfeXwAtortsxwIeT7FFVv2n3u3nofl5VNw/b98w2bgCS7AzsACxuk+Bv0FzTRwFHAJ9o20iTo6p8+Zo1L+AS4Kh2+7nAf7Xb2wFrgS072v49cFq7fT3w4nGe43Zgt3b7BODyjrqHALcAz2rfF/DEjvrTgBPb7f2BX6zjPFcPxQQcDfx8WP3TaRLHtO8HgT8f5VhHAzcPtW3LrgBeMda16Sg7HFgJzBsp/rbugI73A+3n36h9fzrwrnZ7R+BOYDMgwG+AJ3Tsuw/w017/Pvny5cuXrw17eT9e5/34xx3vN2tjewxNUrwG2LSj/kjg4nb7IuAvO+oO6LzPjnCu84A3j/YZ22t2eru9ZXsv3qF9/37g1Hb7cOC7w/b9Z+Ddvf498zVzX/bEarb5Avd/k9jZ07cNcFtV3dnR9mc0PX7Q3FT/a6QDJnlbOzxndZI7aL6Z3bqjyY1DG1V1H/d/u7xekhyV5Oo0w3fvAHYd7Tztub5P8+30/kl2ovnW9vx1nOKmqqqO9z9r4xzr2pDkqcDHgJfU6N8sj2X4f5vzqupuYB7NTXxpx2e/oC2XJPUn78ej+++OfYd6mbeg6fl8KHBLx7n/mab3k/azdJ77AXEkeX6Sy9shv3fQ9GZ3xj2q9r/HYppeVmj+253Rbu8APH0opvbYf0GTeEuTwsnmmm3OBv4hyeOAl9D06EHTC/nIJFt23Di35/5hsTcCTwCu6TxYO9/mb4A/Aa6tqvuS3E7Tezhku472DwEe154PmpvaZh1tH0NzU32AJDsAn27Pc1lVrU1y9bDz1PD9gM/RDGH6b+CcqvrtCG2GbJskHYns9jQ32XVemySPovk2941VddU6jj9SfJ2+AcxLsjvNzfGv2vJbgf8Fdqmqm0bZV5LUX7wfr78baXpit66qe0eov4XmMw3p/LwbA/8GHAV8paruSXJeR9xj3aOhGVL87iTfATYBLu6I69tV9dz1+CzShNgTq1ml7SVcAnyWZjjqirb8RuB7wN8n2STJU4BX0wxxBfgM8L4kO6bxlCRb0QyvuRdYBWyU5F00c0067Znkz9qFFd5CcwO6vK27GnhZuxjDgcB+o4S+Oc0NZhU0izPQfPM7ltNp/jh4OfCvY7R9FHBskocmOQx4MvAf67o27Wc6h2a40ZfGOP7/AH84WmVV3UPzR80pNPOVvtGW30fzB8OH24SZJNsm+dMxzidJmqa8H6+/qroF+DpN8v+wJA9J8oQkQ7F+CXhze498OPCOjt3/ANi4jfveNItFPa+j/n+ArZLMXUcI/0HT6/pe4Kz2/gzwVeCPkryi/RvioUmeluTJG/I5pfEwidVs9AWaeSJfGFZ+JM08zZuBc2nmcnyzrfsQzc3h68CvgX8BNgUupBnaegPNcKffMmz4DvAVmvkit9PMMf2zNmEDeDPwQuAOmqE3540UcFX9CPgH4DKaG8184NKxPmj7x8CVNDfc747R/Ps0c1FvpZnrcmhV/aqtG+3aPI5mcYu35P4VDe9Ksv0Ix/974Ph2qNHbRolh6L/N2cO+ZX4H8GPg8iS/Br4JPGmE/SVJ/cP78fo7iiYh/RHN5zgHGFpU6tM01+WHwFU0See9wNq2V/tYmmt3O80Q7t8Paa6q62h6Wn/S3qcfNMy6qtYAX2bYf7P22M+jGWp8M01v88k0SbM0KYYmmEuaoZKcSrPi4PHraHM08Jqq2nfKApMkaRYZz/24y+d7PvCpqtphKs4nTSXnxEozWJIB4M9oluGXJEk9MBX34zTPT382TW/so2kel3fuZJ1P6iWHE0szVJL30Sx8cUpV/bTX8UiSNBtN4f04NM+tvZ1mOPEKfKa6ZiiHE0uSJEmS+oY9sZIkSZKkvmESK0mSJEnqG321sNPWW29dAwMDvQ5DkjQDLF269NaqmtfrOPqd92ZJUreM997cV0nswMAAg4ODvQ5DkjQDJPlZr2OYCbw3S5K6Zbz3ZocTS5IkSZL6hkmsJEmSJKlvmMRKkiRJkvqGSawkSZIkqW+YxEqSJEmS+oZJrCRJkiSpb5jESpIkSZL6hkmsJEmSJKlvbNTrANbH8ptWM3Dc4l6HIUnqkZUnHdzrEDRJvL9Lmgm8T00Ne2IlSZIkSX3DJFaSJEmS1DdMYiVJkiRJfcMkVpIkSZLUN6YsiU1ydJKPTdX5JEnS/ZJ8bxxt3pJks473/5Hk4ZMamCRJ68meWEmSZoGqesY4mr0F+H0SW1UHVdUdkxWTJEkbomtJbJLzkixNcm2ShW3ZMUluSHIF8MyOtqcl+VSSwbb+Bd2KQ5IkPViSu9qf+ydZkuScJNclOSONY4FtgIuTXNy2XZlk617GLUnScN18Tuyrquq2JJsCP0iyGHgPsCewGrgYuKqj/QCwF/AEmhvmE6vqt8MP2ibECwHmPGxeF8OVJGnWeiqwC3AzcCnwzKr6pyRvBZ5dVbf2NDpJktahm8OJj02yDLgc2A54BbCkqlZV1e+As4a1/1JV3VdV/wn8BNhppINW1aKqWlBVC+ZsNreL4UqSNGtdUVW/qKr7gKtpvlgetyQL29FUg6tWrZqM+CRJGlVXktgk+wMHAPtU1W40Pa7XjbFbjfFekiRNjjUd22tZz5FZnV8wz5vnKClJ0tTqVk/sXOD2qro7yU7A3sCmwH5JtkryUOCwYfscluQhSZ4A/CFwfZdikSRJG+ZOYMteByFJ0rp0a07sBcDrkqygSUYvB24BTgAuA+6gGa7U6efAFcDDgNeNNB9WkiRNqUXABUlurqpnt2WOlJIkTStdSWKrag3w/BGqlgCfHWW3b1bV67pxfkmStG5VtUX7cwnN/Xmo/E0d2x8FPgqQZA5Nr+yvpzJOSZLG4nNiJUnSSK4FPlNV9/Q6EEmSOnXzETvjVlVH9+K8kiRpfKpqxKcGSJLUaz1JYjfU/G3nMnjSwb0OQ5IkSZLUIw4nliRJkiT1jb7qiZUkSTPTSkdaSZLGyZ5YSZIkSVLf6Kue2OU3rWbguMW9DkOShD1nkiSpN+yJlSRJkiT1jb7qiZUkSep3jiqTZi5HKU0Ne2IlSZIkSX2j50lskkOS7NzrOCRJkiRJ01/Pk1jgEMAkVpIkSZI0pjGT2CQDSa5LckaSFUnOSbJZkpVJtm7bLEiypN0+IcmpSZYk+UmSYzuOdVSSHyZZluTzSZ4BvAg4JcnVSZ4wSZ9TkiRJkjQDjHdhpycBr66qS5OcCrxhjPY7Ac8GtgSuT/JJ4I+A44FnVNWtSR5ZVbclOR/4alWds4GfQZIkSZI0S4x3OPGNVXVpu306sO8Y7RdX1ZqquhX4JfBo4DnA2W0ZVXXbeE6cZGGSwSSDa+9ePc5wJUmSJEkz0XiT2Brh/b0d+28yrH5Nx/ZaJvAon6paVFULqmrBnM3mbuhhJEmaEZJsnmRxOzXnmiSHt1N8PpBkeZIrkjyxbfvCJN9PclWSbyZ5dFu+RZLPtu1/mOSlbfnzklyW5MokZyfZopefVZKkkYw3id0+yT7t9suAS4CVwJ5t2UvHcYyLgMOSbAWQ5JFt+Z00w44lSdLYDgRurqrdqmpX4IK2fHVVzQc+BvxjW3YJsHdVPRX4IvA3bfnfDbWvqqcAF7XrXBwPHFBVewCDwFun5BNJkrQexpvEXg+8MckK4BHAJ4H3AB9JMkjT27pOVXUt8H7g20mWAR9qq74IvL39ltiFnSRJWrflwHOTnJzkWVU1NNfmzI6fQ188Pw64MMly4O3ALm35AcDHhw5YVbcDe9M8LeDSJFcDrwR2GCmAzqk+q1at6t4nkyRpHMY7zPfeqnr5sLLv0izW9ABVdcKw97t2bH8O+Nyw+kvxETuSJI1LVd2QZA/gIODEJN8aqups1v78KPChqjo/yf7ACes4dIBvVNWR44hhEbAIYMGCBcOnHEmSNKmmw3NiJUnSOCXZBri7qk4HTgH2aKsO7/h5Wbs9F7ip3X5lx2G+Abyx45iPAC4Hntkxn3bzJA/6slqSpF4bM4mtqpWdvamSJKmn5gNXtEN+3w2c2JY/IskPgTcDf9WWnQCcnWQpcGvHMU5s21/TTvF5dlWtAo4GzmyPcxnNI/MkSZpWNnjVYEmSNPWq6kLgws6yJACnVNU7hrX9CvCVEY5xFw/smR0qvwh4WjfjlSSp2/oqiZ2/7VwGTzq412FIkiRJknqkr5JYSZL0YFU10OsYJEmaKi7sJEmSJEnqG/bESpIkTaGVTo2SpAnpqyR2+U2rGThuca/DkKQN4h+ukiRJE+dwYkmSJElS3zCJlSRJkiT1DZNYSZIkSVLf6Mmc2CR3VdUWvTi3JEmSpOmrn9fAcf2LqTGlSWySAJnKc0qSJEmSZo4NSmKTnATcWFUfb9+fANxFk6D+ObAxcG5VvTvJAHAh8H1gT+Cgdp8PA88D/hs4oqpWTeiTSJIkSZJmvA2dE3sWTbI65M+BVcCOwF7A7sCeSf64rd8R+ERV7VJVPwM2Bwarahfg28C7RztRkoVJBpMMrr179QaGK0mSJEmaCTaoJ7aqrkryqCTbAPOA24H5ND2rV7XNtqBJXn8O/KyqLu84xH00iTDA6cCX13GuRcAigI0fu2NtSLySJEmSpJlhInNizwYOBR5Dk5DuAPx9Vf1zZ6N2OPFvxjiWyakkSZIkaUwTecTOWcARNIns2TTzXl+VZAuAJNsmedQ6zntou/0y4JIJxCFJkiRJmiU2uCe2qq5NsiVwU1XdAtyS5MnAZc0ixNwFvBxYO8LuvwH2SnI88Evg8A2NQ5IkNdrRT1+j+XL4GcBNwIvbsrdV1WCSrWnWpRhIcjRwCM1aFTsCHwT+AHgFsAY4qKpum+KPIUnSOk3oETtVNX/Y+48AHxmh6a7D2vmMWEmSJseOwJFV9dokXwJeOkb7XYGnApsAPwbeUVVPbZ8icBTwj8N3SLIQWAiw/fbbdzF0SZLGNpHhxJIkafr5aVVd3W4vBQbGaH9xVd3ZPupuNfDvbfny0fatqkVVtaCqFsybN2/iEUuStB5MYiVJmlnWdGyvpRl1dS/33/M3WUf7+zre38cER2xJkjQZ+urmNH/buQyedHCvw5Akqd+sBPYEruD+hRUlSepL9sRKkjTzfRB4fZKrgK17HYwkSRPRVz2xkiRpdFW1ko7FFKvqgx3VT+nYPr6tPw04raP9QMf2A+okSZou7ImVJEmSJPWNvuqJXX7TagaOW9zrMCRNopXOe5ckSdI62BMrSZIkSeobfdUTK0mSJGlmc1SWxmJPrCRJkiSpb0xpEpvk6CQfm8pzSpIkSZJmDntiJUmSJEl9o6tzYpOcB2wHbAJ8pKoWJTkG+FvgDmAZsCbJXOCHwOOr6r4kmwPXAX9YVfd0MyZJkiRJGm4ynnrifN6p0e2e2FdV1Z7AAuDYJNsC7wGeCewL7AxQVauBq4H92v1eAFxoAitJkiRJWpduJ7HHJlkGXE7TI/sKYElVraqq3wFndbQ9Czi83T5iWN3vJVmYZDDJ4Nq7V3c5XEmSJElSP+laEptkf+AAYJ+q2g24imaI8GjOBw5M8khgT+CikRpV1aKqWlBVC+ZsNrdb4UqSJEmS+lA3e2LnArdX1d1JdgL2BjYF9kuyVZKHAocNNa6qu4AfAB8BvlpVa7sYiyRJkiRpBurmwk4XAK9LsgK4nmZI8S3ACcBlNAs7XT1sn7OAs4H9uxiHJEmSJGmG6loSW1VrgOePULUE+Owo+5wDpFsxSJKkRpI5jnKSJM1EPidWkqQ+k2QgyXVJzkiyIsk5STZLsjLJyUmuBA5LcmSS5UmuSXJyx/53JflwkmuTfCvJvLZ8Sbv/FUluSPKsnn1ISZJGYRIrSVJ/ehLwiap6MvBr4A1t+a+qag/gO8DJwHOA3YGnJTmkbbM5MFhVuwDfBt7dcdyNqmov4C3DyiVJmhZMYiVJ6k83VtWl7fbpNM9jh/sfWfc07n/M3b3AGcAft3X3dbTr3Bfgy+3PpcDASCfufPzdqlWrJvxBJElaH91c2GnSzd92LoMnHdzrMCRJmg5qlPe/meCx1rQ/1zLK3wlVtQhYBLBgwYLhcUiSNKnsiZUkqT9tn2SfdvtlwCXD6q+geczd1knmAEfSDB2G5v5/6Dr2lSRp2jKJlSSpP10PvLF9tN0jgE92VlbVLcBxwMXAMmBpVX2lrf4NsFeSa2jmzL53yqKWJGmC+mo4sSRJ+r17q+rlw8oGOt9U1ZnAmSPtXFVvHaFs/47tW4cfT5Kk6aCvktjlN61m4LjFvQ5D0ghWOl9dkiRJU6CvklhJkgRVtRLYdQL7b9G9aCRJmlrOiZUkSZIk9Q17YiVJkiTNOk6F6l/2xEqSJEmS+oZJrCRJkiSpb6xXEptkIMmKJJ9Ocm2SryfZNMnuSS5P8sMk5yZ5RNt+SZIF7fbWSVa220cn+XKSC5L8Z5IPdP2TSZIkSZJmnA3pid0R+HhV7QLcAbwU+FfgHVX1FGA58O5xHGd34HBgPnB4ku02IBZJkiRJ0iyyIUnsT6vq6nZ7KfAE4OFV9e227HPAH4/jON+qqtVV9VvgR8AOIzVKsjDJYJLBtXev3oBwJUmSJGnyDRy3mIHjFvc6jBlvQ5LYNR3ba4GHr6PtvR3n2GSM44y4UnJVLaqqBVW1YM5mc9czVEmSJEnSTNKNhZ1WA7cneVb7/hXAUK/sSmDPdvvQLpxLkiRJkjSLdes5sa8EPpVkM+AnwDFt+QeBLyVZCNivLkmSJEmakPVKYqtqJbBrx/sPdlTvPUL764CndBQd35afBpzW0e4F6xOHJEmSJGl28jmxkiTpQZL8R5KH9zoOSZKG69ZwYkmSNINU1UG9jkGSpJH0VRI7f9u5DJ50cK/DkCRpWkiyOfAl4HHAHOB9NGtTfATYnOZJAH8C3AN8ElhA8+SAt1bVxUmOBl4EbEbzyLxzq+pv2mOvBBZU1a1T+JEkSRpTXyWxkiTpAQ4Ebq6qgwGSzAWuAg6vqh8keRjwv8Cbgaqq+Ul2Ar6e5I/aY+wOPJUm4b0+yUer6sZ1nbRdsHEhwPbbbz8JH0uSpNE5J1aSpP61HHhukpPbR91tD9xSVT8AqKpfV9W9wL7A6W3ZdcDPgKEk9ltVtbqqfgv8CNhhrJN2PsN93rx53f9UkiStg0msJEl9qqpuAPagSWZPBP5sAw6zpmN7LY7SkiRNc311o1p+02oGjvNxs+o/K53LLWkSJNkGuK2qTk9yB/AG4LFJntYOJ96SZjjxd4G/AC5qhxFvD1xPkwBLktRX+iqJlSRJDzAfOCXJfTSLN70eCPDRJJvSJLAHAJ8APplkOc3CTkdX1ZokYx2/Ji1ySZI2kEmsJEl9qqouBC4coWrvEcqOGWH/04DTOt6/ACDJHGBL4NfdiFOSpG5yTqwkSRruWuAzVXVPrwORJGk4e2IlSdIDVNVOvY5BkqTR2BMrSZIkSeob9sRKkiRJUhf4RIqp0dWe2CTnJVma5NokC9uyuzrqD01yWrv9lSRHtdt/meSMbsYiSZIkSZp5ut0T+6qquq1d1v8HSf5tHW0XApcm+Snw14y8kiJtMrwQYM7D5nU5XEmSJElSP+l2Entskpe029sBO47WsKr+J8m7gIuBl1TVbaO0WwQsAtj4sTv6vDpJkiRJmsW6lsQm2Z/mger7VNXdSZYAm/DAB6VvMmy3+cCvgG26FYckSZIk9cLAcYun/JyzcR5uN+fEzgVubxPYnbh/ePD/JHlykocAQ720JNkLeD7wVOBtSR7fxVgkSZIkSTNQN5PYC4CNkqwATgIub8uPA74KfA+4BSDJxsCnaebQ3kwzJ/bUJOliPJIkSZKkGaZrw4mrag1Nz+pIzhmhbLeOfc8Hzu9WLJIkSZKkmamrj9iRJEmSJGkymcRKkjTLJDkhydvWUX9Ikp2nMiZJksar24/YmVTzt53L4CxcfUuSpCl2CM16Fj/qcRySJD2IPbGSJM0CSd6Z5IYklwBPasuekOSCJEuTfDfJTkmeAbwIOCXJ1Ume0NPAJUkapq96YiVJ0vpLsidwBLA7zb3/SmApsAh4XVX9Z5KnA5+oquckOR/4alWNtDCjJEk9ZRIrSdLM9yzg3Kq6G6BNUjcBngGc3fGEu43Hc7AkC4GFANtvv33Xg5UkaV36KoldftNqBo5b3Osw1OdWOq9akqCZUnRHVe2+vjtW1SKaXlwWLFhQXY5LkqR1ck6sJEkz33eAQ5JsmmRL4IXA3cBPkxwGkMbQM9zvBLbsTaiSJK2bSawkSTNcVV0JnAUsA74G/KCt+gvg1UmWAdcCL27Lvwi8PclVLuwkSZpu+mo4sSRJ2jBV9X7g/SNUHThC20sBnxMrSZqW7ImVJEmSJPUNk1hJkiRJUt+YUBKbZPMki5MsS3JNksOTnNdR/9wk57bbdyU5Jcm1Sb6ZZK8kS5L8JMmLJvg5JEmSJEmzwER7Yg8Ebq6q3apqV+ACYKck89r6Y4BT2+3NgYuqaheaVQ9PBJ4LvAR47wTjkCRJkiTNAhNd2Gk58A9JTga+WlXfTfJ54OVJPgvsAxzVtv0dTZI7tN+aqronyXJgYLQTdD5Qfc7D5o3WTJIkSZJ6auVJB/c6hFlhQklsVd2QZA/gIODEJN8CPgP8O/Bb4Oyqurdtfk9VDT0Q/T5gTXuM+5KMGkfnA9U3fuyOPlBdkiRJkmaxCSWxSbYBbquq05PcAbymqm5OcjNwPHBAF2KUJEmSJAmY+HDi+cApSe4D7gFe35afAcyrqhUTPL4kSZIkSb830eHEFwIXjlC1L/DpYW236Ng+YbQ6SZIkSepHA8ct7sl5Z9tc3In2xD5IkqXAb4C/7vaxJUmSJEmzW9eT2Kras9vHlCRJkiQJJv6cWEmSJEmSpkzXe2In0/xt5zI4y8Z7S5IkSZLuZ0+sJEl6kCTvTeKj8iRJ005f9cRKkqSpUVXv6nUMkiSNxJ5YSZL6WJKjkvwwybIkn0/y6CTntu+XJXlG2+6tSa5pX29pywaSrEjy6STXJvl6kk3butOSHNrDjyZJ0oj6qid2+U2re/bsJfXGbHvmlSStjyS7AMcDz6iqW5M8Evgk8O2qekmSOcAWSfYEjgGeDgT4fpJvA7cDOwJHVtVrk3wJeClwei8+jyRJ42FPrCRJ/es5wNlVdStAVd3Wln2yfb+2qlYD+wLnVtVvquou4MvAs9pj/LSqrm63lwIDY500ycIkg0kGV61a1c3PI0nSmExiJUma3dZ0bK9lHKO0qmpRVS2oqgXz5s2bvMgkSRqBSawkSf3rIuCwJFsBtMOJvwW8vn0/J8lc4LvAIUk2S7I58JK2TJKkvtOzJDbJ0Uk+1m6/LslRvYpFkqR+VFXXAu8Hvp1kGfAh4M3As5MspxkevHNVXQmcBlwBfB/4TFVdNZ5TTErgkiRNwLRY2KmqPtXrGCRJ6kdV9Tngc8OKXzxCuw/RJLmdZSuBXTvef7Cjeivgtq4FKklSl0xaT2yS85IsbZfsX9iWHZPkhiRXAM/saHtCkrdNViySJGn8kpwKbAZc0utYJEkabjJ7Yl9VVbe1z5v7QZLFwHuAPYHVwMXAmEOZ2gR4IcCch7l4hCRJk62qXtXrGCRJGs1kzok9tp2fczmwHfAKYElVraqq3wFnjecgnSsgztls7iSGK0mSJEma7ialJzbJ/sABwD5VdXeSJcB1wM6TcT5JkiRJ6rWVJx3c6xBmhcnqiZ0L3N4msDsBewObAvsl2SrJQ4HDJunckiRJkqQZarLmxF4AvC7JCuB6miHFtwAnAJcBdwBXD9vHZfwlSZIkSes0KUlsVa0Bnj9C1RLgsyOUbwX8bDJikSRJkiTNHJO5sNO4JHkf8HTg/F7HIkmSJEma3ibzETvjUlV/B/xdr+OQJEmSpIkYOG5xr0Poqum6UFXPk9j1MX/buQxO0wspSZIkSZp8PR9OLEmSJEnSeJnESpIkSZL6hkmsJEmSJKlv9NWc2OU3rZ5xk6X1YNN1ArkkSZKk3rMnVpKkWSTJnF7HIEnSRJjESpI0QyQZSHJdkjOSrEhyTpLNkqxMcnKSK4HDkhyZZHmSa5Kc3LH/XUnen2RZksuTPLqHH0eSpBGZxEqSNLM8CfhEVT0Z+DXwhrb8V1W1B/Ad4GTgOcDuwNOSHNK22Ry4vKp2a9u9dqQTJFmYZDDJ4KpVqybtg0iSNBKTWEmSZpYbq+rSdvt0YN92+6z259OAJVW1qqruBc4A/rit+x3w1XZ7KTAw0gmqalFVLaiqBfPmzet2/JIkrdOkJrHOu5EkacrVKO9/M45976mqofZr6bMFICVJs8MGJ7HOu5EkaVraPsk+7fbLgEuG1V8B7Jdk6/bL5iOBb09lgJIkTcREe2Infd6NJElaL9cDb0yyAngE8MnOyqq6BTgOuBhYBiytqq9MeZSSJG2giQ4TGj7v5th2+0HzbgCSDM27OY8Hz7t57kgnSLIQWAgw52HOu5EkaQz3VtXLh5UNdL6pqjOBM4fvWFVbdGyfA5wzGQFKkjQRE+2JnfR5N52LR8zZbO4GhilJkiRJmgkmmsQ670aSpGmiqlZW1a69jkOSpMk00STWeTeSJEmSpCkz0TmxzruRJEmSJGDlSQf3OoRZYVKfEytJkiRJUjdtcE9sVa0EnHcjSZIkSZoy9sRKkiRJkvrGROfETqn5285l0HHmkiRJkqahgeMW9zqErpuO83ztiZUkSZIk9Q2TWEmSJElS3zCJlSRJkiT1jb6aE7v8ptUzcpx5t0zH8eqSJEmS1E32xEqSJACSHJ3kY+3265Ic1euYJEkarq96YiVJ0tSoqk/1OgZJkkZiT6wkSbNEkvOSLE1ybZKFbdkxSW5IcgXwzI62JyR5W8+ClSRpFNOiJzbJe4HvVNU3ex2LJEkz2Kuq6rYkmwI/SLIYeA+wJ7AauBi4qpcBSpI0lmmRxFbVu3odgyRJs8CxSV7Sbm8HvAJYUlWrAJKcBfzRWAdpe3EXAmy//faTFKokSSNbr+HESY5K8sMky5J8Psmjk5zbvl+W5Bltu7cmuaZ9vaUtG0iyIsmn22FMX2+/CSbJaUkO7fqnkyRJACTZHzgA2KeqdqPpcb1uQ45VVYuqakFVLZg3b173gpQkaRzGncQm2QU4HnhOe/N7M/BPwLfb93sA1ybZEzgGeDqwN/DaJE9tD7Mj8PGq2gW4A3hptz6IJElap7nA7VV1d5KdaO7RmwL7JdkqyUOBw3oaoSRJ47A+PbHPAc6uqlsBquq2tuyT7fu1VbUa2Bc4t6p+U1V3AV8GntUe46dVdXW7vRQYGOukSRYmGUwyuPbu1esRriRJ6nABsFGSFcBJwOXALcAJwGXApcCKYfvUVAYoSdJ4TPWc2DUd22tpvgFep6paBCwC2PixO3ozlSRpA1TVGuD5I1QtAT47QvlWwM8mMyZJkjbE+vTEXgQclmQrgCSPBL4FvL59PyfJXOC7wCFJNkuyOfCStkySJPWBJO+jmRZ0fq9jkSRpuHEnsVV1LfB+4NtJlgEfopkX++wky2mGB+9cVVcCpwFXAN8HPlNV41mu315WSZKmgar6u6raq6p+1etYJEkabr2GE1fV54DPDSt+8QjtPkST5HaWrQR27Xj/wY7qrYDb1icWSZIkSdLs0/PnxCY5FdgMuKTXsUiSJEnShlp50sG9DmFW6HkSW1Wv6nUMkiRJkqT+0PMkdn3M33Yug367IUmSJEmz1vqsTixJkiRJUk+ZxEqSJEmS+kZfDSeWJEmSpOlq4LjFvQ6hJ6Z6Qau+SmKX37R61v5ijMTVzyRJkiTNNg4nliRJkiT1DZNYSZIkSVLfMImVJEmSJPUNk1hJkiRJUt+Y9CQ2yQlJ3raO+kOS7DzZcUiSJEmS+t906Ik9BDCJlSSpC5JsnmRxkmVJrklyeJLzOuqfm+TcdvuuJKckuTbJN5PslWRJkp8keVHPPoQkSeswKUlskncmuSHJJcCT2rInJLkgydIk302yU5JnAC8CTklydZInTEY8kiTNIgcCN1fVblW1K3ABsFOSeW39McCp7fbmwEVVtQtwJ3Ai8FzgJcB7RztBkoVJBpMMrlq1arI+hyRJI+p6EptkT+AIYHfgIOBpbdUi4P9U1Z7A24BPVNX3gPOBt1fV7lX1XyMc7/c3yrV3r+52uJIkzTTLgecmOTnJs6pqNfB54OVJHg7sA3ytbfs7miR3aL9vV9U97fbAaCeoqkVVtaCqFsybN2+0ZpIkTYqNJuGYzwLOraq7AZKcD2wCPAM4O8lQu43Hc7CqWkSTALPxY3esrkcrSdIMUlU3JNmD5ovkE5N8C/gM8O/Ab4Gzq+retvk9VTV0b70PWNMe474kk/E3giRJEzZVN6iHAHdU1e5TdD5JkmalJNsAt1XV6UnuAF5TVTcnuRk4HjigpwFKkjRBkzEn9jvAIUk2TbIl8ELgbuCnSQ4DSGO3tv2dwJaTEIckSbPRfOCKJFcD76aZ5wpwBnBjVa3oVWCSJHVD13tiq+rKJGcBy4BfAj9oq/4C+GSS44GHAl9s23wR+HSSY4FDR5oXK0mSxqeqLgQuHKFqX+DTw9pu0bF9wmh1kiRNJ5MynLiq3g+8f4SqA0doeyk+YkeSpEmTZCnwG+Cvex2LJEkT5aINkiTNcO2TASRJmhEm5TmxkiRJkiRNhr7qiZ2/7VwGTzq412FIkiRJ0oOsNFeZEvbESpIkSZL6hkmsJEmSJKlvmMRKkiRJkvqGSawkSZIkqW+YxEqSJEmS+oZJrCRJkiSpb5jESpIkSZL6hkmsJEmSJKlvmMRKkiRJkvqGSawkSZIkqW+kqnodw7gluRO4vtdxbKCtgVt7HcQGMvbeMPbe6ef4jX38dqiqeVN4vhkpySrgZ+3bfv79my68hhPj9ZsYr9/EeQ0n5klVteVYjTaaiki66PqqWtDrIDZEkkFjn3rG3hv9HDv0d/zGrqnW+UWA/w0nzms4MV6/ifH6TZzXcGKSDI6nncOJJUmSJEl9wyRWkiRJktQ3+i2JXdTrACbA2HvD2Hujn2OH/o7f2NVL/jecOK/hxHj9JsbrN3Few4kZ1/Xrq4WdJEmSJEmzW7/1xEqSJEmSZrFpkcQmOTDJ9Ul+nOS4Eeo3TnJWW//9JAMddX/bll+f5E+nNHDGFftbk/woyQ+TfCvJDh11a5Nc3b7On9rIxxX70UlWdcT4mo66Vyb5z/b1yqmN/PcxjBX/hztivyHJHR11Pbv2SU5N8ssk14xSnyT/1H6uHybZo6Oup9d9HLH/RRvz8iTfS7JbR93Ktvzq8a48123jiH//JKs7fjfe1VG3zt+3yTaO2N/eEfc17e/4I9u6nl77JNslubj9t/DaJG8eoc20/b3Xhkny10kqyda9jqWfJHlf+//A1Um+nmSbXsfUb5KckuS69jqem+ThvY6pnyQ5rP23+r4krrI7Tr3+O6HfjfV3zoNUVU9fwBzgv4A/BP4AWAbsPKzNG4BPtdtHAGe12zu37TcGHt8eZ840i/3ZwGbt9uuHYm/f3zXNr/vRwMdG2PeRwE/an49otx8x3eIf1v7/AKdOk2v/x8AewDWj1B8EfA0IsDfw/Wl03ceK/RlDMQHPH4q9fb8S2LpX132c8e8PfHWiv2+9iH1Y2xcCF02Xaw88Ftij3d4SuGGEf2+m7e+9rw36b74dcCHN82N7+v99v72Ah3VsH0v794+v9bqGzwM2ardPBk7udUz99AKeDDwJWAIs6HU8/fCaDn8n9Ptrff7Oqapp0RO7F/DjqvpJVf0O+CLw4mFtXgx8rt0+B/iTJGnLv1hVa6rqp8CP2+NNlTFjr6qLq+ru9u3lwOOmML51Gc91H82fAt+oqtuq6nbgG8CBkxTnaNY3/iOBM6cksjFU1XeA29bR5MXAv1bjcuDhSR7LNLjuY8VeVd9rY4Pp9fsOjOvaj2Yi/790xXrGPm1+3wGq6paqurLdvhNYAWw7rNm0/b3XBvkw8DeAC2+sp6r6dcfbzfEarreq+npV3du+nXb3oumuqlZU1fW9jqPP9PzvhH63vn+jTYckdlvgxo73v+DBf9z8vk37j9JqYKtx7juZ1vf8r6bpaRiySZLBJJcnOWQS4luX8cb+0nY4zjlJtlvPfSfTuGNIM4T78cBFHcW9vPZjGe2zTYfrvj6G/74X8PUkS5Ms7FFM47FPkmVJvpZkl7asb659ks1okrx/6yieNtc+zXSQpwLfH1Y1U37vZ70kLwZuqqplvY6lXyV5f5Ibgb8A3jVWe63Tq3jgvUiaDN6rpthGvQ5gtkjycmABsF9H8Q5VdVOSPwQuSrK8qv6rNxGO6N+BM6tqTZK/pOkNf06PY9oQRwDnVNXajrLpfu37WpJn0ySx+3YU79te80cB30hyXfut23RyJc3vxl1JDgLOA3bsbUjr7YXApVXV+W3mtLj2SbagSa7fMqy3SX0myTeBx4xQ9U7g/9IM59Qo1nX9quorVfVO4J1J/hZ4E/DuKQ2wD4x1Dds27wTuBc6Yytj6wXiunzSdTYck9iaauTNDHteWjdTmF0k2AuYCvxrnvpNpXOdPcgDNjX2/qlozVF5VN7U/f5JkCU3vxFQlUmPGXlW/6nj7GeADHfvuP2zfJV2PcN3W57/9EcAbOwt6fO3HMtpnmw7XfUxJnkLz+/L8zt+hjmv+yyTn0gy9mVZJbGdiVVX/keQT7aI0vf63Zn0cwbChxNPh2id5KE0Ce0ZVfXmEJn39ez/bVNUBI5UnmU8z8mVZM+uHxwFXJtmrqv57CkOc1ka7fiM4A/gPTGIfZKxrmORo4AXAn1Q74U73W4/fQY1PP/2dMCNMh+HEPwB2TPL4JH9A8wfY8NVizweGVqQ8lGbBkmrLj0izevHjaXpMrpiiuGEcsSd5KvDPwIuq6pcd5Y9IsnG7vTXwTOBHUxb5+GJ/bMfbF9HMY4NmsY7ntZ/hETTfuF84BTF3Gs/vDUl2olkM5rKOsl5f+7GcDxzVrta6N7C6qm5helz3dUqyPfBl4BVVdUNH+eZJthzapol9fKvPTaEkj2nn25NkL5p/I3/FOH/fei3JXJrRHl/pKOv5tW+v6b8AK6rqQ6M069vfe92vqpZX1aOqaqCqBmiG1O1hAjt+STpHf7wYuK5XsfSrJAfSzMl+Uce6JNJk6ou/E2aSnvfEVtW9Sd5E80fJHJoVZK9N8l5gsKrOp/nj5/NJfkwz4feIdt9rk3yJJgG5F3jjsCGj0yH2U4AtgLPbv41/XlUvoln57Z+T3Efzh/JJVTVlidQ4Yz82yYtoru1tNKsVU1W3JXkfzf+wAO8dNnRxusQPze/KF4d9C9vTa5/kTJqepa2T/ILmG/aHAlTVp2i+dT+IZqGyu4Fj2rqeX/dxxP4umvnqn2h/3++tqgXAo4Fz27KNgC9U1QVTGfs44z8UeH2Se4H/BY5of3dG/H2bZrEDvAT4elX9pmPX6XDtnwm8Alie5Oq27P8C28P0/72XpthJSZ4E3EezuvPrehxPP/oYzZMrvtH+23d5VXkdxynJS4CPAvOAxUmurqopf4xlPxnt79Ieh9VXRvo7p6r+ZdT2jrCQJEmSJPWL6TCcWJIkSZKkcTGJlSRJkiT1DZNYSZIkSVLfMImVJEmSJPUNk1hJkiRJUt8wiZUkSZIk9Q2TWEmSJElS3zCJlSRJkiT1DZNYSZIkSVLfMImVJEmSJPUNk1hJkiRJUt8wiZUkSZIk9Q2TWEmSJElS3zCJlSRJkiT1DZNYSZIkSVLfMInVrJVk/yS/6HUc65JkIEkl2ajXsUxUkq8leeU66j+V5O+mMiZJUu95P+4PSe5K8oe9jkMCmLX/I0qaWlX1/KHtJEcDr6mqfTvqX9eLuCRJ0gMlWQKcXlWfGSqrqi16F5H0QPbESuOUZE6vY5AkabbzfizJJFYzWpKVSf42yY+S3J7ks0k2Gdbmr5P8MsktSY7pKD8tySeT/EeS3wDPTnJwkquS/DrJjUlO6Gi/SZLTk/wqyR1JfpDk0W3d3CT/0p7jpiQnDt2EkzwkyfFJftbG8a9J5o7yebZJcn6S25L8OMlrO+o2TfK59nOuSPI3Q8Ozkrw9yb8NO9Y/JfnIhly3JK9tz39bG882bfnftMONhl73JDmtrVuS5DVJngx8CtinbXNHx/U+sd1ekeQFHefbKMmqJHu07/dO8r32Oi9Lsv9In0OSND14P57Q/fhtSX6YZHWSs4bdj1+Q5Or2c34vyVM66vZor9GdSc5u9x26zz4iyVfbe+vt7fbj2rr3A88CPtbepz/WlleSJyZ5epL/TseXCUlekuSHHdfxuCT/1f43+FKSR470+aQNZRKr2eAvgD8FngD8EXB8R91jgLnAtsCrgY8neURH/cuA9wNbApcAvwGOAh4OHAy8PskhbdtXtsfaDtgKeB3wv23dacC9wBOBpwLPA17T1h3dvp4N/CGwBfCxUT7LF4FfANsAhwL/L8lz2rp3AwPtMZ4LvLxjv9OBA5M8HJqkEDgC+NdRzgOjXLf2fH8P/DnwWOBnbVxU1Qeqaot2yNGTgVXAWZ0HraoV7bW5rG378BHOfSZwZMf7PwVuraork2wLLAZOBB4JvA34tyTz1vFZJEm95/14w+7Hfw4cCDweeEobI0meCpwK/GX7Of8ZOD/Jxkn+ADi3/byPpLmvvqTjmA8BPgvsAGxPc30+BlBV7wS+C7ypvU+/qTOYqvo+zfV/Tkfxy4AvtNv/BzgE2K+9PrcDH1/H55PWX1X58jVjX8BK4HUd7w8C/qvd3p/mH+2NOup/Cezdbp8G/OsYx/9H4MPt9quA7wFPGdbm0cAaYNOOsiOBi9vtbwFv6Kh7EnAPzZz1AaDa7e2AtcCWHW3/Hjit3f4J8Kcdda8BftHx/mvAa9vtFwA/2sDr9i/ABzrqtmjjHego2xRYCryjo2wJzTxYaG7Alww752nAie32E4E7gc3a92cA72q33wF8fti+FwKv7PXvmy9fvnz5Gvnl/XhC9+OXd7z/APCpdvuTwPuGtb+eJnn8Y+AmIB11lwzdZ0c4z+7A7R3vf3/P7igr4Int9onAqe32ljRJ7Q7t+xXAn3Ts99ih69jr30NfM+dlT6xmgxs7tn9G863gkF9V1b0d7++mScpG2pd2CM3F7fCb1TTf7m7dVn+eJpn6YpKbk3wgyUNpvuV8KHBLO9znDppvSx/V7rdNG1dnjBvR3Gw7bQPcVlV3Dmu7bUd9Z7wPiB34HPd/G/zyNt51Ge26PSDeqroL+FVHHNAkutdX1cljnGNEVfVjmpvgC5NsBryI+7/h3QE4bOhattdzX5qbpCRp+vJ+3Fjf+/F/d2x3XpcdgL8edj/crj3/NsBNVVUjxZFksyT/3A6d/jXwHeDhGf984y8Af5ZkY+DPgCurauja7QCc2xHTCpqkf/h1lDaYSaxmg+06trcHbl6PfWvY+y8A5wPbVdVcmrmdAaiqe6rqPVW1M/AMmm9Xj6K5aawBtq6qh7evh1XVLu0xb6b5B78zxnuB/xl27puBRybZcljbm9rtW4DHddR1fm6A84CnJNm1je2MMT77aNftAfEm2ZxmGNNN7fvjaIaJvXodxx5+XUcyNKT4xTTfUv+4Lb+Rpif24R2vzavqpHEcU5LUO96PG+exfvfj0dwIvH/Y/XCzqjqzjWHbJBkljr+m6Wl+elU9jKbnFtpryBj36ar6EU3i/nweOJR4KK7nD4trk6q6aaRjSRvCJFazwRuTPK5dVOCdDJujuZ62pPn29bdJ9qL5hxuAJM9OMr/9FvPXNENn7quqW4CvA/+Q5GHtggdPSLJfu+uZwF8leXySLYD/B5w17BtpqupGmuFRf59m0Yqn0CSKp7dNvgT8bbtYw7bA8DksvwXOobnRXFFVPx/js4523c4Ejkmye/sN7P8Dvl9VK5M8HzgWeElV/e/IhwWaPwge187ZGc0XaeYqvZ4H3hxPp+mh/dMkc9prsf/QghSSpGnL+zEbdD8ezaeB17W90kmyeZoFr7YELqPp/XxTmsURXwzsNez6/S9wR/vf493Djv0/NHN61+ULwJtpEuCzO8o/Bbw/yQ4ASea155e6xiRWs8EXaG5aPwH+i2Yex4Z6A/DeJHcC76K5UQ15DM1N6dc0Q2e+zf1DhI4C/gD4Ec0CB+dw//DXU9t23wF+CvyWZlGEkRxJMy/nZpoFG95dVd9s695Ls8jET4FvtudYM2z/zwHzGXvoEoxy3drz/R3wbzTf9D6BZlEKgMOBecCK3L9C8adGOPZFwLXAfye5daSTt39sXEbzLfpZHeU30vTO/l+ahaNuBN6O/55J0nTn/fh+63M/HlFVDQKvpVmQ6Xbgx7SLPlXV72iG+b4auINm2PJXO+L4R5r1K24FLgcuGHb4jwCHplm5+J9GCeFMmvm3F1VV5738IzS95F9v//tcDjx9Az+mNKI8cKi8NLMkWUmzMME3x2o70yR5PXBEVe3XUbY9cB3wmKr69Tr2XcksvW6SpO6bzfeVidyPuxzH92kWhfrsVJxPmkz2XEgzRJLHJnlmOzzqSTTzXc7tqH8I8Fbgi1N1w5QkabaZLvfjJPsleUw7nPiVNI/nGd7jKvWljXodgKSu+QOaVRYfTzN06IvAJ+D3iy/9D80iDAf2KD5JkmaD6XI/fhLNMOvNaYZwH9pO1ZH6nsOJJUmSJEl9w+HEkiRJkqS+0VfDibfeeusaGBjodRiSpBlg6dKlt1bVvF7H0e+8N0uSumW89+a+SmIHBgYYHBzsdRiSpBkgyc96HcNM4L1ZktQt4703O5xYkiRJktQ3TGIlSZIkSX3DJFaSJEmS1DdMYiVJkiRJfcMkVpIkSZLUN0xiJUmSJEl9wyRWkiRJktQ3TGIlSZIkSX3DJFaSJEmS1Dc26nUA62P5TasZOG5xr8OQJPXIypMO7nUImiTe3yXNFt7LJs6eWEmSJElS3zCJlSRJkiT1DZNYSZIkSVLfmLIkNsnRST42VeeTJEmSJM089sRKkjQLJPneONq8JclmHe//I8nDJzUwSZLWU9eS2CTnJVma5NokC9uyY5LckOQK4JkdbU9L8qkkg239C7oVhyRJerCqesY4mr0F+H0SW1UHVdUdkxWTJEkbops9sa+qqj2BBcCxSbYF3kOTvO4L7Dys/QCwF3Aw8Kkkm3QxFkmS1CHJXe3P/ZMsSXJOkuuSnJHGscA2wMVJLm7brkyydS/jliRpuG4msccmWQZcDmwHvAJYUlWrqup3wFnD2n+pqu6rqv8EfgLsNNJBkyxse2wH1969uovhSpI0az2Vptd1Z+APgWdW1T8BNwPPrqpnr2vnznvzqlWrJj1YSZI6dSWJTbI/cACwT1XtBlwFXDfGbjXG+6awalFVLaiqBXM2mzvRUCVJElxRVb+oqvuAq2lGR41b57153rx5kxGfJEmj6lZP7Fzg9qq6O8lOwN7ApsB+SbZK8lDgsGH7HJbkIUmeQPMt8PVdikWSJK3bmo7ttcBGvQpEkqT11a2b1gXA65KsoElGLwduAU4ALgPuoPmmt9PPgSuAhwGvq6rfdikWSZK0Ye4EtgRu7XUgkiSNpitJbFWtAZ4/QtUS4LOj7PbNqnpdN84vSZK6YhFwQZKbO+bFjjjdR5KkXnH4kCRJs0BVbdH+XELzJfNQ+Zs6tj8KfBQgyRyaXtlfT2WckiSNpSdJbFUd3YvzSpKkcbsW+ExV3dPrQCRJ6mRPrCRJepCqGvHRd5Ik9VpfJbHzt53L4EkH9zoMSZIkSVKP9FUSK0mSZqaVfkktSRqnbj0nVpIkSZKkSddXPbHLb1rNwHGLex2GJE0ae6MkSZLWzZ5YSZIkSVLf6KueWEmSJM1MjrbTbOGoq4mzJ1aSJEmS1DdMYiVJkiRJfWNKk9gkRyf52FSeU5IkSZI0c9gTK0mSJEnqG11NYpOcl2RpkmuTLGzLjklyQ5IrgGe2ZXOT/CzJQ9r3mye5MclDuxmPJEmSJGlm6XZP7Kuqak9gAXBskm2B99Akr/sCOwNU1WrgamC/dr8XABdW1T3DD5hkYZLBJINr717d5XAlSZIkSf2k20nssUmWAZcD2wGvAJZU1aqq+h1wVkfbs4DD2+0jhtX9XlUtqqoFVbVgzmZzuxyuJEmSJKmfdC2JTbI/cACwT1XtBlwFXLeOXc4HDkzySGBP4KJuxSJJ0kzVTsFZnGRZkmuSHJ5kZZIPJFme5IokT2zbvjDJ95NcleSbSR7dlm+R5LNt+x8meWlb/rwklyW5MsnZSbbo5WeVJGkk3eyJnQvcXlV3J9kJ2BvYFNgvyVbtfNfDhhpX1V3AD4CPAF+tqrVdjEWSpJnqQODmqtqtqnYFLmjLV1fVfOBjwD+2ZZcAe1fVU4EvAn/Tlv/dUPuqegpwUZKtgeOBA6pqD2AQeOtIAXRO9Vm1atUkfERJkka3URePdQHwuiQrgOtphhTfApwAXAbcQTMPttNZwNnA/l2MQ5KkmWw58A9JTqb5Evi7SQDObOvPBD7cbj8OOCvJY4E/AH7alh9AM5UHgKq6PckLaNauuLQ93h/Q3L8fpKoWAYsAFixYUN37aJIkja1rSWxVrQGeP0LVEuCzo+xzDpBuxSBJ0kxXVTck2QM4CDgxybeGqjqbtT8/Cnyoqs5vp/2csI5DB/hGVR3Z3YglSeounxMrSVIfSbINcHdVnQ6cAuzRVh3e8XOoB3UucFO7/cqOw3wDeGPHMR9BM4LqmR3zaTdP8keT8iEkSZoAk1hJkvrLfOCKJFcD7wZObMsfkeSHwJuBv2rLTgDOTrIUuLXjGCe27a9pnyrw7KpaBRwNnNke5zJgp0n+LJIkrbduzomddPO3ncvgSQf3OgxJknqmqi4ELuwsa+ewnlJV7xjW9ivAV0Y4xl08sGd2qPwi4GndjFeSpG6zJ1aSJEmS1Df6qidWkiQ9WFUN9DoGSZKmij2xkiRJkqS+0Vc9sctvWs3AcYt7HYakWWalc/EladL5b62k8bInVpIkSZLUN0xiJUmSJEl9wyRWkiRJktQ3ejInNsldVbVFL84tSZIkafqa6WvgOP974qY0iU3zNPZM5TklSZIkSTPHBiWxSU4Cbqyqj7fvTwDuoklQ/xzYGDi3qt6dZAC4EPg+sCdwULvPh4HnAf8NHFFVqyb0SSRJkiRJM96Gzok9iyZZHfLnwCpgR2AvYHdgzyR/3NbvCHyiqnapqp8BmwODVbUL8G3g3RsYhyRJkiRpFtmgntiquirJo5JsA8wDbgfm0/SsXtU224Imef058LOqurzjEPfRJMIApwNfHu1cSRYCCwHmPGzehoQrSZIkSZohJjIn9mzgUOAxNAnpDsDfV9U/dzZqhxP/Zoxj1agVVYuARQAbP3bHUdtJkiRJkma+iTxi5yzgCJpE9myaea+vSrIFQJJtkzxqHec9tN1+GXDJBOKQJEnDJJnT6xgkSZoMG5zEVtW1wJbATVV1S1V9HfgCcFmS5cA5bf1IfgPsleQa4DnAezc0DkmSZpskA0muS3JGkhVJzkmyWZKVSU5OciVwWJIjkyxPck2Skzv2vyvJh5Ncm+RbSea15Uva/a9IckOSZ/XsQ0qSNIoJPWKnquYPe/8R4CMjNN11WDufEStJ0sQ8CXh1VV2a5FTgDW35r6pqj3bdistpngxwO/D1JIdU1Xncv8DiXyV5F80Ci29q99+oqvZKclBbfsAUfiZJksY0keHEkiSpd26sqkvb7dOBfdvtoYUTnwYsqapVVXUvcAYw9NSA4QssDu0L9y+2uBQYGOnESRYmGUwyuGqVT8iTJE0tk1hJkvrT8MUOh96PtZjiWMda0/5cyygjtqpqUVUtqKoF8+b55ABJ0tQyiZUkqT9tn2SfdnukRRKvAPZLsnW7yNORNM9mBxdYlCT1sQnNiZ1q87edy+BJB/c6DEmSpoPrgTe282F/BHwS+D9DlVV1S5LjgIuBAIur6itt9dACi8cDvwQOn9LIJUmagL5KYiVJ0u/dW1UvH1Y20Pmmqs4Ezhxp56p66whl+3ds3zr8eJIkTQcOJ5YkSZIk9Q17YiVJ6jNVtZJhj69bz/191J0kqW/1VRK7/KbVDBy3uNdhSJoBVjq/XpIkqS/1VRIrSZIkaWbzi2aNxTmxkiRJkqS+YRIrSZIkSeobPU9ikxySZOdexyFJkiRJmv56nsQChwAmsZIkSZKkMY25sFOSAeACYCmwB3AtcBTwI2BBVd2aZAHwwaraP8kJwPbAH7Y//7Gq/qk91lHA24ACfgh8EngRsF+S44GXVtV/dfUTSpIkSdI0MfxpKy5ktf7Guzrxk4BXV9WlSU4F3jBG+52AZwNbAtcn+STwR8DxwDPaxPeRVXVbkvOBr1bVORv4GSRJkiRJs8R4hxPfWFWXttunA/uO0X5xVa2pqluBXwKPBp4DnN2WUVW3jefESRYmGUwyuPbu1eMMV5IkSZI0E403ia0R3t/bsf8mw+rXdGyvZQLPo62qRVW1oKoWzNls7oYeRpIkSZI0A4w3id0+yT7t9suAS4CVwJ5t2UvHcYyLgMOSbAWQ5JFt+Z00w44lSZIkSVqn8Sax1wNvTLICeATNgkzvAT6SZJCmt3Wdqupa4P3At5MsAz7UVn0ReHuSq5I8YX0/gCRJkiRp9hjvMN97q+rlw8q+S7NY0wNU1QnD3u/asf054HPD6i/FR+xIkiRJksZhOjwnVpIkdUGSgSQrknw6ybVJvp5k0yRL2sfhkWTrJCvb7aOTnJfkG0lWJnlTkre2o6Mu75j6I0nStDFmEltVKzt7UyVJ0rS2I/DxqtoFuIOx163YFfgz4Gk0037urqqnApfRPBf+QTqfHLBq1aquBS5J0nhs8KrBvTB/27kM+jBgSZLW5adVdXW7vRQYGKP9xVV1J3BnktXAv7fly4GnjLRDVS0CFgEsWLBg+BMMJEmaVA4nliRpZhnpMXfjfSzefR3v76PPvuyWJM0OJrGSJM18K7n/sXiH9jAOSZImzCRWkqSZ74PA65NcBWzd62AkSZqIvhomtPym1Qwct7jXYUh9aaXzyaUZr6pW0izUNPT+gx3VnfNbj2/rTwNO62g/0LH9gDpJkqYLe2IlSZIkSX3DJFaSJEmS1DdMYiVJkiRJfaOv5sRKkiRJUj9znZKJsydWkiRJktQ3TGIlSZIkSX2jq0lskvOSLE1ybZKFbdldHfWHJjmt3f5KkqPa7b9MckY3Y5EkSZIkzTzdnhP7qqq6LcmmwA+S/Ns62i4ELk3y/9u793C7yvLe+9+fwXI2KKRWKHFZi1IkihCOQkWL3QhWYCtF6wlsm0Lrxr5qW1qt4oH3hWJ1tx5wRzZihSJCRZEoeALEA0I4xIActBKKQNsgEMBoJHC/f8wRnSzmyjrNteYaa30/15UrYz7jGWPc88nMGuuez2HcBrwV2KdXpSYZXgIw70kL+hyuJEmSJE2foROWPa7MebLj0+8k9vgkRzTbOwI7jVSxqv4ryTuBS4EjqureEeotBZYCbPq0narP8UqSJEmSWqRvSWySA4GDgH2ram2Sy4DNgO7Ec7Nhhy0CfgJs3684JEmSJEmzVz/nxM4H7msS2J351fDg/0ryO0meAGzopSXJXsBLgecDb0vyjD7GIkmSJEmahfqZxF4MbJLkJuBk4Mqm/ATgIuDbwN0ASTYFPk5nDu1ddObEnpEkfYxHkiRJkjTL9G04cVWto9Oz2sv5Pcqe13XshcCF/YpFkiSNLMmJwENV9f4R9h8O3FpV35/OuCRJGgufEytJkoY7HNhl0EFIktSLSawkSXNAkrcnuTXJN4FnN2XPTHJx84z3K5LsnGQ/4OXAqUmuT/LMgQYuSdIw/X7EzpRatMN8lvsMJUmSxiXJHsCrgN3o3PuvBa6h8wi7Y6vqB0n2Bj5aVS9OciFwUVX1mg4kSdJAtSqJlSRJE3IAcEFVrQVoktTNgP2A87rWVdx0LCdLsgRYArBw4cK+BytJ0saYxEqSNDc9Abi/qnYb74FVtZROLy6LFy+uUapLktRXzomVJGn2+wZweJLNk2wN/AGwFrgtyZEA6djw5IAHga0HE6okSRvXqp7YlXeuYeiEZYMOQ5p2q5wLLmkSquraJOcCK4D/Bq5udr0GOC3JO4AnAp9u6nwa+HiS44FXVtW/DyBsSZJ6alUSK0mSJqaqTgJO6rHr4B51v4WP2JEkzVAOJ5YkSZIktYZJrCRJkiSpNUxiJUmSJEmtYRIrSZIkSWqNcS3slGQI+BLwTToPSL8TOAx4NvAxYAvg34E3VtV9SS4D3lZVy5NsByyvqqEkRwMvb+o/k84D2P+6L+9IkiRJkmYonzoxeRPpid0J+EhVPQe4H3gF8C/A31TVc4GVwLvGcJ7dgKOARcBRSXacQCySJEmSpDlkIknsbVV1fbN9DZ2e1G2q6vKm7JPA747hPF+rqjVV9XPg+8DTe1VKsiTJ8iTLH1m7ZgLhSpIkSZJmi4kkseu6th8BttlI3fVd19hslPP0HNpcVUuranFVLZ63xfxxhipJkiRJmk3GNSd2BGuA+5IcUFVXAK8DNvTKrgL2AK4CXtmHa0mSJElSaw2dsGzEfc6XHZt+JLEAbwA+lmQL4EfAMU35+4HPJFkCjPyvJUmSJEnSGIwria2qVcCuXa/f37V7nx71bwae21X0jqb8TODMrnovG08ckiRJkqS5yefESpIkSZJawyRWkiRJktQaJrGSJOlxknwxyTaDjkOSpOH6tbDTtFi0w3yWu2KXJElTrqoOGXQMkiT1Yk+sJEktlWTLJMuSrEhyQ5KjkuyZ5NtN2VVJtk6yWZJPJFmZ5LokL2qOPzrJZ5NcnOQHSf6h69yrkmw3uHcnSVJvreqJlSRJj3EwcFdVHQqQZD5wHXBUVV2d5EnAz4A3A1VVi5LsDHw5ybOac+wGPB9YB9yS5ENVdcd0vxFJksbKnlhJktprJfCSJKckOQBYCNxdVVcDVNUDVbUe2B84qym7Gbgd2JDEfq2q1lTVz4HvA08f7aJJliRZnmT56tWr+/+uJEnaiFb1xK68cw1DJywbdBiaJquc/yxJG1VVtybZHTgEeB/w9QmcZl3X9iOM4XeDqloKLAVYvHhxTeCakiRNmD2xkiS1VJLtgbVVdRZwKrA38LQkezb7t06yCXAF8Jqm7Fl0emxvGUzUkiRNTqt6YiVJ0mMsAk5N8ijwMHAcEOBDSTanMx/2IOCjwGlJVgLrgaOral2S0c5vL6skacYxiZUkqaWq6hLgkh679ulRdkyP488Ezux6/TKAJPOArYEH+hGnJEn95HBiSZI03I3A6VX18KADkSRpOHtiJUnSY1TVzoOOQZKkkUyqJ3aEh6x/rmv/S5Jc0Gw/lOTUJDcm+WqSvZJcluRHSV4+yfchSZIkSZoDJtsT2+sh6+9OsqCqVtOZf3NGU3dL4OtV9VdNYvs+4CXALsAngQt7XSDJEmAJwLwnLZhkuJIkSZI0OD5GcvImOyf2MQ9Zr6o1wKeA1ybZBtgX+FJT9xfAxV3HXd7MtVkJDI10gapaWlWLq2rxvC3mTzJcSZIkSVKbTaondvhD1pN8DTgd+ALwc+C8qlrfVH+4qjYs1f8ozcPVq+rR5hl2kiRJkiRt1KSSx+Yh6/dW1VlJ7gf+pKruSnIX8A46z6aTJEmSJKkvJtsD2ush6wBnAwuq6qZJnl+SJEmSpF+a7HDikR6yvj/w8WF1t+raPnGkfZIkSZI0Ww2dsGxSx7sw1BQ8JzbJNcBPgbf2+9ySJEmSpLmt70lsVe3R73NKkiRJkgRTkMROpUU7zGe53eeSJEmSNGdN9jmxkiRJkiRNG5NYSZL0OEnek8RH5UmSZpxWDSeWJEnTo6reOegYJEnqpVVJ7Mo710x6SWoNnsuCS1L/JHk98DaggO812x8DfqupclxVfTvJW4A3NmWnV9X/TjIEfAn4JrAfcCdwWFX9LMmZwEVVdf60vRlJksagVUmsJEn6lSTPAd4B7FdV9yR5CnAacHlVHZFkHrBVkj2AY4C9gQDfTXI5cB+wE/DqqvrTJJ8BXgGcNcp1lwBLABYuXDhF706SpN6cEytJUnu9GDivqu4BqKp7m7LTmtePVNUaYH/ggqr6aVU9BHwWOKA5x21VdX2zfQ0wNNpFq2ppVS2uqsULFizo5/uRJGlUJrGSJM1t67q2H8FRWpKkGW5gSWySo5N8uNk+tpnTI0mSxu7rwJFJtgVohhN/DTiueT0vyXzgCuDwJFsk2RI4oimTJKl1ZsS3rVX1sUHHIElS21TVjUlOAi5P8ghwHfBmYGmSP6bTs3pcVX2nWajpqubQ06vqumZhp41eYopClyRpwqYsiU3yOWBHYDPgn6pqaZJjgL8F7gdW0AxhSnIi8FBVvX+q4pEkaTaqqk8CnxxWfFiPeh8APjCsbBWwa9fr7vvwtsC9fQtUkqQ+mcqe2DdW1b1JNgeuTrIMeDewB7AGuJTON8aSJGkGSXIGsAWdR+9IkjSjTGUSe3ySI5rtHYHXAZdV1WqAJOcCzxrtJN3L+M97kisgSpI01arqjaPXkiRpMKZkYackBwIHAftW1fPo9LjePJFzdS/jP2+L+f0LUpIkSZLUOlPVEzsfuK+q1ibZGdgH2Bx4YbOC4gPAkXTmxUqSJEnSnLDq5EMHHULrTVUSezFwbJKbgFuAK4G7gROB79BZ2On6Yce4AqIkSZIkaaOmJImtqnXAS3vsugz4RI/ybYHbpyIWSZIkSdLsMSVzYscjyXuBvYELBx2LJEmSJGlmm8rVicekqv4e+PtBxyFJkiRJU23ohGWDDmHcZto83oH3xEqSJEmSNFYD74kdj0U7zGf5DPsWQJIkSZI0feyJlSRJkiS1hkmsJEmSJKk1TGIlSZIkSa3RqjmxK+9c08rVvOaambZ6mSTpV5LMq6pHBh2HJEkTZU+sJEmzRJKhJDcnOTvJTUnOT7JFklVJTklyLXBkklcnWZnkhiSndB3/UJKTkqxIcmWSpw7w7UiS1JNJrCRJs8uzgY9W1e8ADwB/3pT/pKp2B74BnAK8GNgN2DPJ4U2dLYErq+p5Tb0/nca4JUkaE5NYSZJmlzuq6lvN9lnA/s32uc3fewKXVdXqqloPnA38brPvF8BFzfY1wFCvCyRZkmR5kuWrV6/ud/ySJG2USawkSbNLjfD6p2M49uGq2lD/EUZYO6OqllbV4qpavGDBggmGKUnSxExpEptk3lSeX5IkPc7CJPs2238EfHPY/quAFybZrrlPvxq4fDoDlCRpMiacxLp4hCRJM9ItwF8kuQl4MnBa986quhs4AbgUWAFcU1Wfn/YoJUmaoMn2xLp4hCRJM8v6qnptVf1OVb2iqtZW1VBV3bOhQlWdU1WLqmrXqvqbrvKturbPr6qjpzl2SZJGNdkkdloXj3hk7ZpJhitJkiRJarPJJrHTunjEvC3mTzBMSZJmv6paVVW7DjoOSZKm0mSTWBePkCRJkiRNm569n+OwYfGIM4Dv01k84n9t2FlVdyfZsHhEgGUuHiFJkiRprlp18qGDDqH1JpvErq+q1w4rG+p+UVXnAOcMP3D44hHA+ZOMRZIkSZI0y03pc2IlSZIkSeqnCffEVtUqwMUjJEmSJEnTZrLDiafVoh3ms9wx5JIkSZI0Z7UqiZUkSZKkNhs6YdmgQ5iUmbAwlXNiJUmSJEmtYRIrSZIkSWqNVg0nXnnnmhnX/T4TutMlSZIkaa6wJ1aSJEmS1BomsZIkCYAkRyf5cLN9bJLXDzomSZKGa9VwYkmSND2q6mODjkGSpF7siZUkaY5I8rkk1yS5McmSpuyYJLcmuQp4QVfdE5O8bWDBSpI0ghmRxCZ5T5KDBh2HJEmz3Burag9gMXB8kh2Ad9NJXvcHdhnLSZIsSbI8yfLVq1dPXbSSJPUwI5LYqnpnVX110HFIkjTLHZ9kBXAlsCPwOuCyqlpdVb8Azh3LSapqaVUtrqrFCxYsmMJwJUl6vHElsUlen+R7SVYk+VSSpya5oHm9Isl+Tb23JLmh+fOXTdlQkpuSfLwZxvTlJJs3+85M8sq+vztJkgRAkgOBg4B9q+p5wHXAzYOMSZKkiRhzEpvkOcA7gBc3N783A/8MXN683h24MckewDHA3sA+wJ8meX5zmp2Aj1TVc4D7gVeM4bq/HLL0yNo1Y39nkiSp23zgvqpam2RnOvfozYEXJtk2yROBIwcaoSRJYzCentgXA+dV1T0AVXVvU3Za8/qRqlpDZ07NBVX106p6CPgscEBzjtuq6vpm+xpgaLSLdg9ZmrfF/HGEK0mSulwMbJLkJuBkOkOK7wZOBL4DfAu4adgxNZ0BSpI0FtP9iJ11XduP0PkGWJIkTbGqWge8tMeuy4BP9CjfFrh9KmOSJGkixtMT+3XgyCTbAiR5CvA14Ljm9bwk84ErgMOTbJFkS+CIpkySJLVAkvfSmRZ04aBjkSRpuDEnsVV1I3AScHmzsuEH6MyLfVGSlXSGB+9SVdcCZwJXAd8FTq+q68ZyiXHGLkmSpkBV/X1V7VVVPxl0LJIkDTeu4cRV9Ungk8OKD+tR7wN0ktzuslXArl2v39+1e1vg3vHEIkmSJEmae6Z7TuzjJDkD2AL45qBjkSRJkqSptOrkQwcdQusNPImtqjcOOgZJkiRJUjsMPIkdj0U7zGe531xIkiRJ0pw1ntWJJUmSJEkaqFb1xEqSJElSmw2dsGzQIfTddM/ztSdWkiRJktQareqJXXnnmgl/c+EqYJIkSZLUfvbESpIkSZJawyRWkiRJktQaJrGSJEmSpNaYEUlski8m2WbQcUiSJEmSZrYZkcRW1SFVdf+g45Akqe2SbJlkWZIVSW5IclSSz3Xtf0mSC5rth5KcmuTGJF9NsleSy5L8KMnLB/YmJEnaiDEnsSPcFPdM8u2m7KokWyfZLMknkqxMcl2SFzXHH53ks0kuTvKDJP/Qde5VSbabijcoSdIcczBwV1U9r6p2BS4Gdk6yoNl/DHBGs70l8PWqeg7wIPA+4CXAEcB7pjdsSZLGZjyP2NlwUzwUIMl84DrgqKq6OsmTgJ8BbwaqqhYl2Rn4cpJnNefYDXg+sA64JcmHquqOPr0XSZIEK4F/THIKcFFVXZHkU8Brk3wC2Bd4fVP3F3SS3A3Hrauqh5OsBIZGukCSJcASgIULF07Nu5AkaQTjGU68EnhJklOSHAAsBO6uqqsBquqBqloP7A+c1ZTdDNwObEhiv1ZVa6rq58D3gaePdtEkS5IsT7L8kbVrxhGuJElzT1XdCuxO5779viTvBD4BvBZ4NXBec78GeLiqqtl+lM6XzFTVo2zki+6qWlpVi6tq8YIFC0aqJknSlBhzT2xV3Zpkd+AQOsONvj6B663r2n5kLNevqqXAUoBNn7ZTjVJdkqQ5Lcn2wL1VdVaS+4E/qaq7ktwFvAM4aKABSpI0SeOZE7s9sLaqzgJOBfYGnpZkz2b/1kk2Aa4AXtOUPYtOj+0t/Q5ckiT1tAi4Ksn1wLvofPEMcDZwR1XdNKjAJEnqh/HMiV0EnJrkUeBh4DggwIeSbE5nPuxBwEeB05r5NOuBo6tqXZLRzm8vqyRJk1RVlwCX9Ni1P/DxYXW36to+caR9kiTNJOMZTjzSTXGfHmXH9Dj+TODMrtcvA0gyD9gaeGCssUiSpLFLcg3wU+Ctg45FkqTJGk9P7FS5ETi9qh4edCCSJM1GVbXHoGOQJKlfBp7EVtXOg45BkiRJktQO43nEjiRJkiRJAzXwntjxWLTDfJaffOigw5AkSZKkCVllPjNp9sRKkiRJklrDJFaSJEmS1BomsZIkSZKk1jCJlSRJkiS1hkmsJEmSJKk1TGIlSZIkSa1hEitJkiRJag2TWEmSJElSa5jESpIkSZJaI1U16BjGLMmDwC2DjqNltgPuGXQQLWObjZ9tNjG22/j1s82eXlUL+nSuOSvJauD2Uar5WbcNwDYA2wBsA7ANYOQ2GNO9uW1J7PKqWjzoONrENhs/22z8bLOJsd3GzzZrJ//dbAOwDcA2ANsAbAOYfBs4nFiSJEmS1BomsZIkSZKk1mhbErt00AG0kG02frbZ+NlmE2O7jZ9t1k7+u9kGYBuAbQC2AdgGMMk2aNWcWEmSJEnS3Na2nlhJkiRJ0hxmEitJkiRJao0Zl8QmOTjJLUl+mOSEHvs3TXJus/+7SYYGEOaMM4Z2OzrJ6iTXN3/+ZBBxzhRJzkjy30luGGF/kvxz057fS7L7dMc4E42h3Q5Msqbrc/bO6Y5xpkmyY5JLk3w/yY1J3tyjjp+3LmNsMz9rLZLkxCR3dv17HTLomAYlyVuTVJLtBh3LICR5b/Nz7vokX06y/aBjmm5JTk1yc9MOFyTZZtAxTbckRzY/3x9NMqceNTPa7+yz3Wi/S47VjEpik8wDPgK8FNgFeHWSXYZV+2Pgvqr6beCDwCnTG+XMM8Z2Azi3qnZr/pw+rUHOPGcCB29k/0uBnZo/S4DTpiGmNjiTjbcbwBVdn7P3TENMM9164K1VtQuwD/AXPf5/+nl7rLG0GfhZa5sPdv17fXHQwQxCkh2B3wf+Y9CxDNCpVfXcqtoNuAiYi19AfQXYtaqeC9wK/O2A4xmEG4D/CXxj0IFMp3H8zj6bncnov0uOakYlscBewA+r6kdV9Qvg08Bhw+ocBnyy2T4f+L0kmcYYZ6KxtJu6VNU3gHs3UuUw4F+q40pgmyRPm57oZq4xtJuGqaq7q+raZvtB4CZgh2HV/Lx1GWObSW30QeCvgTm7qmZVPdD1ckvmYFtU1Zeran3z8krgNwcZzyBU1U1Vdcug4xiAOf87e79+l5xpSewOwB1dr3/M439x+WWd5gfAGmDbaYlu5hpLuwG8ohm6cn7zbbBGNtY21ePtm2RFki8lec6gg5lJmukPzwe+O2yXn7cRbKTNwM9a27ypuQedkeTJgw5muiU5DLizqlYMOpZBS3JSkjuA1zA3e2K7vRH40qCD0LTxft8nmww6AE2bLwDnVNW6JH9Gpzf7xQOOSbPPtcDTq+qhZs7b5+gMkZ3zkmwF/Bvwl8N6IjSCUdrMz9oMk+SrwG/02PV2OkPk30un1+29wD/S+eV9VhmlDf6OzlDiWW9j7VBVn6+qtwNvT/K3wJuAd01rgNNgtDZo6rydzvSJs6cztukyljaQJmqmJbF3At09hL/ZlPWq8+MkmwDzgZ9MT3gz1qjtVlXdbXQ68A/TEFebjeWzqGG6E42q+mKSjybZrqruGWRcg5bkiXSSsbOr6rM9qvh5G2a0NvOzNvNU1UFjqZfk43TmQs46I7VBkkXAM4AVzQyo3wSuTbJXVf3nNIY4Lcb6WaCTvH2RWZjEjtYGSY4GXgb8XlXNyiHV4/gczCXe7/tkpg0nvhrYKckzkvwa8CrgwmF1LgTe0Gy/Evj6bP3PPw6jttuw+XUvpzPHTCO7EHh9s2rsPsCaqrp70EHNdEl+Y8Mc9SR70fkZM6e/ZGra4/8CN1XVB0ao5uety1jazM9auwy7Bx1BZ1GXOaOqVlbVr1fVUFUN0RlCuPtsTGBHk6R7xMRhwM2DimVQkhxMZ270y6tq7aDj0bQaS66jMZhRPbFVtT7Jm4BLgHnAGVV1Y5L3AMur6kI6v9h8KskP6UwKftXgIp4Zxthuxyd5OZ1hK/cCRw8s4BkgyTnAgcB2SX5M51vgJwJU1cfofDN8CPBDYC1wzGAinVnG0G6vBI5Lsh74GfAqv2TiBcDrgJVJrm/K/g5YCH7eRjCWNvOz1i7/kGQ3OsOJVwF/NtBoNEgnJ3k28ChwO3DsgOMZhA8DmwJfab6Lu7Kq5lQ7JDkC+BCwAFiW5Pqq+h8DDmvKjfQ7+4DDmla9fpesqv877vN4z5ckSZIktcVMG04sSZIkSdKITGIlSZIkSa1hEitJkiRJag2TWEmSJElSa5jESpIkSZJawyRWkiRJktQaJrGSJEmSpNYwiZUkSZIktYZJrCRJkiSpNUxiJUmSJEmtYRIrSZIkSWoNk1hJkiRJUmuYxEqSJEmSWsMkVpIkSZLUGiax0gQlGUpSSTbp83m/lOQN/TznVEnyd0lO38j+1yT58nTGJEmaW7wfT9xceI+anVJVg45BaqUkQ8BtwBOrav2Awxk420OSNAjef8YmyYnAb1fVawcdizRZ9sRKkiRJklrDJFYCkuyY5LNJVif5SZIPN+VPSPKOJLcn+e8k/5Jk/rDDX5PkP5Lck+TtXed8QpITkvx7c87PJHlKs2+zJGc15fcnuTrJU5t9lyX5k9Gu3zV86g29rt/jPZ6Z5GNJvpLkwSSXJ3l61/79mjjWNH/v15Tvm+Shrj8/T7Kq2XdikrOaU3yj+fv+pt6+SY5O8s2m7mlJ3j8sps8neUuzvX2Sf2v+DW5Lcvx4/g0lSe03h+7HH0myrLkffzfJM7v279zcq+9NckuSP+zat22SLyR5oIn1fRvus83+f0pyR7P/miQHNOUHA38HHNXco1d0v8ckmzbvf9eucy1I8rMkv968flmS65t6307y3HH+80p9YxKrOS/JPOAi4HZgCNgB+HSz++jmz4uA3wK2Aj487BT7A88Gfg94Z5Lfacr/F3A48EJge+A+4CPNvjcA84EdgW2BY4Gf9QhvMtfv5TXAe4HtgOuBs5s2eAqwDPjnJp4PAMuSbFtV36mqrapqK+DJwHeBc3qc+3ebv7dp6n9n2P5z6Nw801zzycDvA59O8gTgC8AKOu3/e8BfJvkfG3kvkqRZZI7dj18FvJvOffWHwElNG2wJfAX4V+DXm3ofTbJLc9xHgJ8Cv9HEPnw+69XAbsBTmnOcl2SzqroY+H+Bc5t79PO6D6qqdcBngVd3Ff8hcHlV/XeS5wNnAH9Gp53+D3Bhkk038h6lKWMSK8FedG5qf1VVP62qn1fVhm81XwN8oKp+VFUPAX8LvCqPXTzi3VX1s6paQScJ23BjOBZ4e1X9uLk5nAi8sjn2YTo3gd+uqkeq6pqqeqBHbJO5fi/LquobTTxvB/ZNsiNwKPCDqvpUVa2vqnOAm4E/GHb8PwMPNseO1xVAAQc0r18JfKeq7gL2BBZU1Xuq6hdV9SPg43Ru3pKkuWEu3Y8vqKqrmjm8Z9NJPAFeBqyqqk809+PrgH8DjmyS/FcA76qqtVX1feCT3SetqrOq6ifNsf8IbEonsR6Lf+Wx990/asoAlgD/p6q+27TTJ4F1wD5jPLfUV31dxU1qqR2B20dYDGJ7Ot8Ib3A7nf83T+0q+8+u7bV0vp0FeDpwQZJHu/Y/0hz7qea6n06yDXAWnRvsw328fi93bNioqoeS3NtcY/h1Nlxrhw0vkvwZcCCwd1U9yjhVVSX5NJ1veb9B5+a4YSjy04Htk9zfdcg8OomvJGlumEv3443Fuvew++EmTZwLmu07uvZ1b5PkbcAfN/EW8CQ6o6/G4lJgiyR7A/9FJ7G+oCuuNyT5X131f625jjTt7ImVOjeAhem9NP9ddH5wb7AQWE/nh/tYzvvSqtqm689mVXVnVT1cVe+uql2A/eh88/r6Pl+/lx03bCTZis5wo7t6XGfDte5s6h5AZxjyYSN8Qw2dm+VozqHz7ffTgb3pfLsMnba6bVhbbV1Vh4zxfUmS2m8u3Y83Fuvlw2LdqqqOA1Y31/zNrvrd9/UDgL+mMwz4yVW1DbAGSFNlo/fpqnoE+AydL5tfDVxUVQ92xXXSsLi2aEZuSdPOJFaCq4C7gZOTbNks8vCCZt85wP+T5BlN0rdhPslYlvD/GHBSk7BtWCDhsGb7RUkWNUODHqAznKlX7+Zkrt/LIUn2T/JrdJLSK6vqDuCLwLOS/FGSTZIcBewCXNQMN/4M8PqqunUj517dvIffGqlCMyzqHuB04JKqur/ZdRXwYJK/SbJ5knlJdk2y5wTfpySpfebS/XgkF9G5H78uyRObP3sm+Z0myfwscGKSLZLszGMT7q3pJLmrgU2SvJNOT+wG/wUMNetQjORfgaPoDJ/+167yjwPHJtk7HVsmOTTJ1pN+x9IEmMRqzmtuCn8A/DbwH8CP6fwAh84iBp+iM/z1NuDndBaIGIt/Ai4EvpzkQeBKOr2P0FmQ4Xw6N8ybgMub6ww3mev38q/Au4B7gT2A1wJU1U/ofPv8VuAndL7JfVlV3UNngYqnAufnVysU3zj8xFW1ls7CFN9qVi4caZ7MvwIH0XVzbP4NXkZn6NJt/CrRHb7ypCRplppj9+Oemp7P36czN/UuOsOOT6EztxXgTXTujf/ZxHMOnbmpAJcAFwO30hnu/HMeO9z4vObvnyS5doTrf5fOwlHbA1/qKl8O/Cmdxazuo7MY1dETfqPSJKVqLCMAJbVdkjOBH1fVOwYdiyRJmrwkpwC/UVXDVymWZjV7YiVJkqQWSOcZss9thvTuRWcRpwtGO06abVydWJIkSWqHrekMId6ezhzXfwQ+P9CIpAFwOLEkSZIkqTUcTixJkiRJag2TWEmSJElSa7RqTux2221XQ0NDgw5DkjQLXHPNNfdU1YJBx9F23pslSf0y1ntzq5LYoaEhli9fPugwJEmzQJLbBx3DbOC9WZLUL2O9NzucWJIkSZLUGiaxkiRJkqTWMImVJEmSJLWGSawkSZIkqTVMYiVJkiRJrWESK0mSJElqDZNYSZIkSVJrmMRKkiRJklpjk0EHMB4r71zD0AnLBh2GJGlAVp186KBD0BTx/i5prvLeNn72xEqSJEmSWsMkVpIkSZLUGiaxkiRJkqTWMImVJEmSJLXGwJPYJIcn2WXQcUiSNJsl+fYY6vxlki26Xn8xyTZTGpgkSeM08CQWOBwwiZUkaQpV1X5jqPaXwC+T2Ko6pKrun6qYJEmaiFGT2CRDSW5OcnaSm5Kcn2SLJKuSbNfUWZzksmb7xCRnJLksyY+SHN91rtcn+V6SFUk+lWQ/4OXAqUmuT/LMKXqfkiTNaUkeav4+sLlHn991f09zv94euDTJpU3dX97rJUmaKcb6nNhnA39cVd9Kcgbw56PU3xl4EbA1cEuS04BnAe8A9quqe5I8paruTXIhcFFVnd/rREmWAEsA5j1pwRjDlSRJG/F84DnAXcC3gBdU1T8neQvwoqq6Z6DRSZK0EWMdTnxHVX2r2T4L2H+U+suqal1zE/xv4KnAi4HzNtwYq+resVy4qpZW1eKqWjxvi/ljDFeSJG3EVVX146p6FLgeGBrPwUmWJFmeZPnq1aunIj5JkkY01iS2erxe33X8ZsP2r+vafoSx9/hKkqSpN6n7dPcXzAsWOEpKkjS9xprELkyyb7P9R8A3gVXAHk3ZK8Zwjq8DRybZFiDJU5ryB+kMO5YkSYPlPVmSNOONNYm9BfiLJDcBTwZOA94N/FOS5XS+xd2oqroROAm4PMkK4APNrk8Df5XkOhd2kiRpoJYCF29Y2KkxfDSWJEkDNdbhQ+ur6rXDyq6gs1jTY1TVicNe79q1/Ungk8P2fwsfsSNJ0pSqqq2avy8DLusqf1PX9oeADwEkmUenV/aB6YxTkqTRzITnxEqSpJnnRuD0qnp40IFIktRt1J7YqloF7DpaPUmSNHtU1c6DjkGSpF5atWrwoh3ms/zkQwcdhiRJkiRpQBxOLEmSJElqjVb1xEqSpNlplSOtJEljZE+sJEmSJKk1WtUTu/LONQydsGzQYUjSnGIPmSRJmknsiZUkSZIktUaremIlSZI0vRwFJ00tRzyNnz2xkiRJkqTWmLYkNsnRST48XdeTJEmSJM0+9sRKkiRJklqjb0lsks8luSbJjUmWNGXHJLk1yVXAC7rqnpnkY0mWN/tf1q84JEmSJEmzVz8XdnpjVd2bZHPg6iTLgHcDewBrgEuB67rqDwF7Ac8ELk3y21X18z7GI0mSJEmaZfo5nPj4JCuAK4EdgdcBl1XV6qr6BXDusPqfqapHq+oHwI+AnXudNMmSpsd2+SNr1/QxXEmSJElS2/QliU1yIHAQsG9VPY9Oj+vNoxxWo7zuFFYtrarFVbV43hbzJxuqJEmtlmTLJMuSrEhyQ5KjkqxK8g9JVia5KslvN3X/IMl3k1yX5KtJntqUb5XkE0397yV5RVP++0m+k+TaJOcl2WqQ71WSpF761RM7H7ivqtYm2RnYB9gceGGSbZM8EThy2DFHJnlCkmcCvwXc0qdYJEmazQ4G7qqq51XVrsDFTfmaqloEfBj4303ZN4F9qur5wKeBv27K/35D/ap6LvD1JNsB7wAOqqrdgeXAW6blHUmSNA79mhN7MXBskpvoJKNXAncDJwLfAe4Hrh92zH8AVwFPAo51PqwkSWOyEvjHJKcAF1XVFUkAzmn2nwN8sNn+TeDcJE8Dfg24rSk/CHjVhhNW1X3NIou7AN9qzvdrdO7hj9Ms4LgEYOHChf17Z5IkjUFfktiqWge8tMeuy4BPjHDYV6vq2H5cX5KkuaKqbk2yO3AI8L4kX9uwq7ta8/eHgA9U1YXN1J8TN3LqAF+pqlePIYalwFKAxYsX95wOJEnSVPE5sZIktUiS7YG1VXUWcCqwe7PrqK6/N/SgzgfubLbf0HWarwB/0XXOJ9MZRfWCrvm0WyZ51pS8CUmSJqGfj9gZs6o6ehDXlSRpFlgEnJrkUeBh4DjgfODJSb4HrAM29KaeCJyX5D7g68AzmvL3AR9JcgPwCPDuqvpskqOBc5Js2tR7B3Dr1L8lSZLGbiBJrCRJmpiqugS4pLusmcN6alX9zbC6nwc+3+McD/HYntkN5V8H9uxnvJIk9VurkthFO8xn+cmHDjoMSZIkSdKAtCqJlSRJj1dVQ4OOQZKk6eLCTpIkSZKk1rAnVpIkSSNa5VQuSTNMq5LYlXeuYeiEZYMOQ9KA+QuVJEnS3OVwYkmSJElSa5jESpIkSZJawyRWkiRJktQaA5kTm+ShqtpqENeWJEmSNBiub/N4rvUxftOaxCYJkOm8piRJkiRp9phQEpvkZOCOqvpI8/pE4CE6CeofApsCF1TVu5IMAZcA3wX2AA5pjvkg8PvAfwKvqqrVk3onkiRJkqRZb6JzYs+lk6xu8IfAamAnYC9gN2CPJL/b7N8J+GhVPaeqbge2BJZX1XOAy4F3jXShJEuSLE+y/JG1ayYYriRJkiRpNphQT2xVXZfk15NsDywA7gMW0elZva6pthWd5PU/gNur6squUzxKJxEGOAv47EautRRYCrDp03aqicQrSZIkSZodJjMn9jzglcBv0ElInw78f1X1f7orNcOJfzrKuUxOJUmSJEmjmswjds4FXkUnkT2PzrzXNybZCiDJDkl+fSPXfWWz/UfANycRhyRJGibJvEHHIEnSVJhwEltVNwJbA3dW1d1V9WXgX4HvJFkJnN/s7+WnwF5JbgBeDLxnonFIkjTXJBlKcnOSs5PclOT8JFskWZXklCTXAkcmeXWSlUluSHJK1/EPJflgkhuTfC3Jgqb8sub4q5LcmuSAgb1JSZJGMKlH7FTVomGv/wn4px5Vdx1Wz2fESpI0Oc8G/riqvpXkDODPm/KfVNXuzboVV9J5MsB9wJeTHF5Vn+NXCyz+P0neSWeBxTc1x29SVXslOaQpP2j4hZMsAZYALFy4cOreoSRJPUxmOLEkSRqcO6rqW832WcD+zfaGhRP3BC6rqtVVtR44G9jw1IDhCyxuOBZ+tdjiNcBQrwtX1dKqWlxVixcsWDDpNyJJ0niYxEqS1E7DF0Xc8Hq0xRRHO9e65u9HmOSILUmSpkKrbk6LdpjP8pMPHXQYkiTNBAuT7FtV3+FXiyQ+v2v/VcA/J9mOznDiVwMfavZtWGDx07jAoiSpZeyJlSSpnW4B/iLJTcCTgdO6d1bV3cAJwKXACuCaqvp8s9sFFiVJrdWqnlhJkvRL66vqtcPKhrpfVNU5wDm9Dq6qt/QoO7Br+57h55MkaSawJ1aSJEmS1Bqt6oldeecahk5YNugwpDlhlfPPpRmrqlYx7PF14zzeR91JklrLnlhJkiRJUmu0qidWkiRJUns50kv9YE+sJEmSJKk1TGIlSZIkSa1hEitJkiRJao1xzYlNMgR8CfgmsB9wJ3AY8GzgY8AWwL8Db6yq+5JcBrytqpYn2Q5YXlVDSY4GXt7UfyZwQVX9dV/ekSRJkiSNwyCfgOI84fGbSE/sTsBHquo5wP3AK4B/Af6mqp4LrATeNYbz7AYcBSwCjkqy4wRikSRJkiTNIRNJYm+rquub7Wvo9KRuU1WXN2WfBH53DOf5WlWtqaqfA98Hnt6rUpIlSZYnWf7I2jUTCFeSJEmSNFtMJIld17X9CLDNRuqu77rGZqOcp+fQ5qpaWlWLq2rxvC3mjzNUSZIkSdJs0o+FndYA9yU5oHn9OmBDr+wqYI9m+5V9uJYkSZIkaQ7r1+rEbwBOTfI9OnNd39OUvx84Lsl1wHZ9upYkSZpiSd6T5KBBxyFJ0nDjWp24qlYBu3a9fn/X7n161L8ZeG5X0Tua8jOBM7vqvWw8cUiSpKlVVe8cdAySJPXic2IlSWqxJK9P8r0kK5J8KslTk1zQvF6RZL+m3luS3ND8+cumbCjJTUk+nuTGJF9Osnmz78wkTgWSJM044+qJlSRJM0eS59AZ5bRfVd2T5CnAacDlVXVEknnAVkn2AI4B9gYCfDfJ5cB9dB6d9+qq+tMkn6Hz6LyzBvF+JEkaC3tiJUlqrxcD51XVPQBVdW9Tdlrz+pGqWgPsD1xQVT+tqoeAzwIbFmQc/ui8odEu2v34u9WrV/fz/UiSNKpW9cQu2mE+y08+dNBhSJI0mwx/5N3mox1QVUuBpQCLFy+uKYpLkqSe7ImVJKm9vg4cmWRbgGY48deA45rX85LMB64ADk+yRZItgSOaMkmSWqdVPbGSJOlXqurGJCcBlyd5BLgOeDOwNMkf0+lZPa6qvpPkTOCq5tDTq+q6JEOjXWKKQpckacJMYiVJarGq+iTwyWHFh/Wo9wHgA8PKVjHyo/O2Be7tW6CSJPVJq5LYlXeuYeiEZYMOQ5oVVjm/XNIIkpwBbAF8ZxrEbwAAGDFJREFUc9CxSJI0XKuSWEmSNPWq6o2DjkGSpJG4sJMkSZIkqTVMYiVJkiRJrTGtw4mTHA0srqo3Ted1JUmSJGkkrhXSLvbESpIkSZJao69JbJLPJbkmyY1JljRlxyS5NclVwAuasvlJbk/yhOb1lknuSPLEfsYjSZIkSZpd+t0T+8aq2gNYDByfZAfg3XSS1/2BXQCqag1wPfDC5riXAZdU1cN9jkeSJEmSNIv0e07s8UmOaLZ3BF4HXFZVqwGSnAs8q9l/LnAUcCnwKuCjvU7Y9OguAZj3pAV9DleSJEmSBmfohGVjque83V/pW09skgOBg4B9q+p5wHXAzRs55ELg4CRPAfYAvt6rUlUtrarFVbV43hbz+xWuJEmSJKmF+jmceD5wX1WtTbIzsA+wOfDCJNs2812P3FC5qh4Crgb+Cbioqh7pYyySJEmSpFmon8OJLwaOTXITcAtwJXA3cCLwHeB+OvNgu50LnAcc2Mc4JEmSJEmzVN+S2KpaB7y0x67LgE+McMz5QPoVgyRJkiRpdvM5sZIkSZKk1jCJlSRJkiS1hkmsJEmzSJItkyxLsiLJDUmOSvK5rv0vSXJBs/1QklOT3Jjkq0n2SnJZkh8lefnA3oQkSRvR7+fETqlFO8xnuc9HkiRpYw4G7qqqQwGSzAfenWRB89z2Y4AzmrpbAl+vqr9qEtv3AS8BdgE+SedxeJIkzSj2xEqSNLusBF6S5JQkB1TVGuBTwGuTbAPsC3ypqfsLOk8X2HDc5VX1cLM9NNIFkixJsjzJ8tWrV0/R25AkqbdW9cRKkqSNq6pbk+wOHAK8L8nXgNOBLwA/B86rqvVN9YerqprtR4F1zTkeTTLi7whVtRRYCrB48eIaqZ4kSVOhVUnsyjvXMHTCskGHIY3ZKoe/S5pmSbYH7q2qs5LcD/xJVd2V5C7gHcBBAw1QkqRJalUSK0mSRrUIODXJo8DDwHFN+dnAgqq6aWCRSZLUByaxkiTNIlV1CXBJj137Ax8fVnerru0TR9onSdJMYhIrSdIsl+Qa4KfAWwcdiyRJk2USK0nSLFdVeww6BkmS+sVH7EiSJEmSWsOeWEmSJEkaEJ9mMX597YlN8rkk1yS5McmSpuyhrv2vTHJms/35JK9vtv8sydn9jEWSJEmSNPv0uyf2jVV1b5LNgauT/NtG6i4BvpXkNjoLTezTq1KTDC8BmPekBX0OV5IkSZLUJv1OYo9PckSzvSOw00gVq+q/krwTuBQ4oqruHaHeUmApwKZP26n6HK8kSZIkqUX6lsQmORA4CNi3qtYmuQzYDOhOPDcbdtgi4CfA9v2KQ5IkSZLaYuiEZZM+x1ybV9vPObHzgfuaBHZnfjU8+L+S/E6SJwAbemlJshfwUuD5wNuSPKOPsUiSJEmSZqF+JrEXA5skuQk4GbiyKT8BuAj4NnA3QJJNgY/TmUN7F505sWckSR/jkSRJkiTNMn0bTlxV6+j0rPZyfo+y53UdeyFwYb9ikSRJkiTNTn19xI4kSZIkSVPJJFaSJEmS1Br9fsTOlFq0w3yWz7GVtyRJ6rckJwIPVdX7R9h/OHBrVX1/OuOSJGks7ImVJEnDHQ7sMuggJEnqxSRWkqQ5IMnbk9ya5JvAs5uyZya5OMk1Sa5IsnOS/YCXA6cmuT7JMwcauCRJw7RqOLEkSRq/JHsArwJ2o3Pvvxa4BlgKHFtVP0iyN/DRqnpxkguBi6qq19MFSLIEWAKwcOHCaXgHkiT9SquS2JV3rmHohGWDDkPjtMp5zJI0aAcAF1TVWoAmSd0M2A84r+sx7ZuO5WRVtZROAszixYur79FKkrQRrUpiJUlS3zwBuL+qdht0IJIkjYdzYiVJmv2+ARyeZPMkWwN/AKwFbktyJEA6ntfUfxDYejChSpK0cSaxkiTNclV1LXAusAL4EnB1s+s1wB8nWQHcCBzWlH8a+Ksk17mwkyRpphnYcOIkRwOLq+pNSY4F1lbVvwwqHkmSZrOqOgk4qceug3vU/RY+YkeSNEPNiDmxVfWxQccgSZIkSZr5pmw4cZLPNc+du7FZip8kxzTPqLsKeEFX3ROTvG2qYpEkSZIkzQ5T2RP7xqq6N8nmwNVJlgHvBvYA1gCXAtdN4fUlSZIkSbPMVCaxxyc5otneEXgdcFlVrQZIci7wrNFO0v1A9XlPWjBFoUqSJEnS9Ft18qGDDqF1pmQ4cZIDgYOAfavqeXR6XG+eyLmqamlVLa6qxfO2mN+/ICVJkiRJrTNVc2LnA/dV1dokOwP7AJsDL0yybZInAkdO0bUlSZIkSbPUVA0nvhg4NslNwC3AlcDdwInAd4D7geuHHVNTFIskSZIkaZaYkiS2qtYBL+2x6zLgEz3KtwVun4pYJEmSJGmmGjph2bRcZzbNvZ2yR+yMVZL3AnsDFw46FkmSJEnSzDbwJLaq/r6q9qqqnww6FkmSJEnSzDbwJFaSJEmSpLGayufE9t2iHeazfBaN5ZYkSZIkjY89sZIkSZKk1jCJlSRJkiS1hkmsJEmzRJKhJDcl+XiSG5N8OcnmSS5Lsrips12SVc320Uk+l+QrSVYleVOStyS5LsmVSZ4y0DckSVIPrZoTu/LONdP2HKW5aDY9O0qS5rCdgFdX1Z8m+QzwilHq7wo8H9gM+CHwN1X1/CQfBF4P/O+pDFaSpPGyJ1aSpNnltqq6vtm+Bhgapf6lVfVgVa0G1gBfaMpXjnRskiVJlidZvnr16slHLEnSOJjESpI0u6zr2n6Ezqir9fzqnr/ZRuo/2vX6UUYYsVVVS6tqcVUtXrBgweQjliRpHExiJUma/VYBezTbrxxgHJIkTdqMSGKTfDHJNoOOQ5KkWer9wHFJrgO2G3QwkiRNxoxY2KmqDhl0DJIktV1VraKzUNOG1+/v2v3cru13NPvPBM7sqj/Utf2YfZIkzRRj7olNsmWSZUlWJLkhyVFJ9kzy7absqiRbJ9ksySeSrGyW6H9Rc/zRST6b5OIkP0jyD13nXpXEb4YlSZIkSRs1np7Yg4G7qupQgCTzgeuAo6rq6iRPAn4GvBmoqlqUZGfgy0me1ZxjNzrL+K8Dbknyoaq6o0/vRZIkSZI0y41nTuxK4CVJTklyALAQuLuqrgaoqgeqaj2wP3BWU3YzcDuwIYn9WlWtqaqfA98Hnj7aRbuX8X9k7ZpxhCtJkiRJmm3G3BNbVbcm2R04BHgf8PUJXK/Xsv+jXXcpsBRg06ftVBO4piRJkiTNSKtOPnTQIbTOeObEbg+sraqzgFOBvYGnJdmz2b91kk2AK4DXNGXPotNje0u/A5ckSZIkzT3jmRO7CDg1yaPAw8BxQIAPJdmcznzYg4CPAqclWUnn4epHV9W6JKOd315WSZIkSdJGjWc48SXAJT127dOj7Jgex5/JY5fxfxlAknnA1sADY41FkiRJkjQ3jWdhp6lyI3B6VT086EAkSZIkSTPbeIYTT4mq2nnQMUiSJEnSIAydsGzQIfxSWxaZGngSOx6LdpjP8pY0rCRJkiSp/2bCcGJJkiRJksbEJFaSJEmS1BomsZIkSZKk1mjVnNiVd66ZUROf26Qtk7QlSZIkaWPsiZUkaQ5pns8uSVJrmcRKkjRLJBlKcnOSs5PclOT8JFskWZXklCTXAkcmeXWSlUluSHJK1/EPJTkpyYokVyZ56gDfjiRJPZnESpI0uzwb+GhV/Q7wAPDnTflPqmp34BvAKcCLgd2APZMc3tTZEriyqp7X1PvTXhdIsiTJ8iTLV69ePWVvRJKkXkxiJUmaXe6oqm8122cB+zfb5zZ/7wlcVlWrq2o9cDbwu82+XwAXNdvXAEO9LlBVS6tqcVUtXrBgQb/jlyRpo0xiJUmaXWqE1z8dw7EPV9WG+o/QsgUgJUlzw5QmsS4eIUnStFuYZN9m+4+Abw7bfxXwwiTbNffpVwOXT2eAkiRNxoSTWBePkCRpRroF+IskNwFPBk7r3llVdwMnAJcCK4Brqurz0x6lJEkTNNme2GldPOKRtWsmGa4kSbPe+qp6bVX9TlW9oqrWVtVQVd2zoUJVnVNVi6pq16r6m67yrbq2z6+qo6c5dkmSRjXZJHZaF4+Yt8X8SYYrSZIkSWqzyS7Y4OIRkiTNEFW1Cth10HFIkjSVJtsT6+IRkiRJkqRpM9nezw2LR5wBfJ/O4hH/a8POqro7yYbFIwIsc/EISZIkSepYdfKhgw6hdSabxK6vqtcOKxvqflFV5wDnDD9w+OIRwPmTjEWSJEmSNMtN6XNiJUmSJEnqpwn3xLp4hCRJkiRpurVqReBFO8xnuWPGJUmSJM0SQycsG3QII5qp83UdTixJkiRJag2TWEmSJElSa5jESpIkSZJao1VzYlfeuWZGjxnvp5k6/lySJEmSBsmeWEmS9DhJvphkm0HHIUnScK3qiZUkSdOjqg4ZdAySJPViT6wkSS2VZMsky5KsSHJDkqOS7Jnk203ZVUm2TrJZkk8kWZnkuiQvao4/Oslnk1yc5AdJ/qHr3KuSbDe4dydJUm/2xEqS1F4HA3dV1aEASeYD1wFHVdXVSZ4E/Ax4M1BVtSjJzsCXkzyrOcduwPOBdcAtST5UVXdM9xuRJGms7ImVJKm9VgIvSXJKkgOAhcDdVXU1QFU9UFXrgf2Bs5qym4HbgQ1J7Neqak1V/Rz4PvD00S6aZEmS5UmWr169uv/vSpKkjZhwEptkKMlNST6e5MYkX06yeZLLkixu6myXZFWzfXSSzyX5SjNE6U1J3tIMa7oyyVP69J4kSZoTqupWYHc6yez7gP85gdOs69p+hDGM0qqqpVW1uKoWL1iwYAKXlCRp4ibbE7sT8JGqeg5wP/CKUervSucGuydwErC2qp4PfAd4/SRjkSRpTkmyPZ176VnAqcDewNOS7Nns3zrJJsAVwGuasmfR6bG9ZTBRS5I0OZOdE3tbVV3fbF8DDI1S/9KqehB4MMka4AtN+Urgub0OSLIEWAIw70l+2ytJUpdFwKlJHgUeBo4DAnwoyeZ05sMeBHwUOC3JSmA9cHRVrUsy2vlryiKXJGmCJpvEDh+CtDmdm+OGHt7NNlL/0a7Xj44US1UtBZYCbPq0nbyZSpLUqKpLgEt67NqnR9kxPY4/Eziz6/XLAJLMA7YGHuhHnJIk9dNULOy0Ctij2X7lFJxfkiRNrRuB06vq4UEHIknScFPxiJ33A59phgEvm4LzS5KkKVRVOw86BkmSRjLhJLaqVtFZqGnD6/d37e6e3/qOZv+ZPHbI0lDX9mP2SZIkSZLUi8+JlSRJkiS1xlQMJ5YkSZIkjcGqkw8ddAitY0+sJEmSJKk1WtUTu2iH+Sz3mwpJkiRJmrPsiZUkSZIktUaremIlSZIkaTYZOqH9TyWd7nm99sRKkiRJklqjVT2xK+9cMyO/qXBFMUmSJEmaHvbESpIkSZJawyRWkiRJktQaJrGSJAmAJEcn+XCzfWyS1w86JkmShpvyObFJTgQeqqr3j7D/cODWqvr+VMciSZLGpqo+NugYJEnqZSb0xB4O7DLoICRJmu2SfC7JNUluTLKkKTsmya1JrgJe0FX3xCRvG1iwkiSNYEqS2CRvb26I3wSe3ZQ9M8nFzc3ziiQ7J9kPeDlwapLrkzxzKuKRJEkAvLGq9gAWA8cn2QF4N53kdX/8UlmS1AJ9H06cZA/gVcBuzfmvBa4BlgLHVtUPkuwNfLSqXpzkQuCiqjp/hPMtAZYAzHvSgn6HK0nSXHJ8kiOa7R2B1wGXVdVqgCTnAs8a7STd9+aFCxdOUaiSJPU2FXNiDwAuqKq1AE2SuhmwH3Bekg31Nh3LyapqKZ0EmE2ftlP1PVpJkuaAJAcCBwH7VtXaJJcBNzOB3tfue/PixYu9N0uSptWUL+zUeAJwf1XtNk3XkyRJjzUfuK9JYHcG9gE2B16YZFvgAeBIYMUAY5QkaVRTMSf2G8DhSTZPsjXwB8Ba4LYkRwKk43lN/QeBracgDkmS9CsXA5skuQk4GbgSuBs4EfgO8C3gpmHH2MsqSZpx+t4TW1XXNnNqVgD/DVzd7HoNcFqSdwBPBD7d1Pk08PEkxwOvrKp/73dMkiTNdVW1Dnhpj12XAZ/oUb4tcPtUxiRJ0kRMyXDiqjoJOKnHroN71P0WroYoSdKMkeS9wN50emklSZpRZsJzYiVJ0gxSVX9fVXtV1U8GHYskScOZxEqSJEmSWmO6Vifui0U7zGf5yYcOOgxJkiRJ6otV5jfjZk+sJEmSJKk1TGIlSZIkSa1hEitJkiRJag2TWEmSJElSa5jESpIkSZJawyRWkiRJktQaJrGSJEmSpNYwiZUkSZIktYZJrCRJkiSpNUxiJUmSJEmtkaoadAxjluRB4JZBx9Ey2wH3DDqIFrLdJsZ2mxjbbfz60WZPr6oF/QhmLkuyGrh90HFMI/+/9ma7PJ5t8ni2SW+2y6+M6d7ctiR2eVUtHnQcbWKbTYztNjG228TYbuNnm2lQ/Oz1Zrs8nm3yeLZJb7bL+DmcWJIkSZLUGiaxkiRJkqTWaFsSu3TQAbSQbTYxttvE2G4TY7uNn22mQfGz15vt8ni2yePZJr3ZLuPUqjmxkiRJkqS5rW09sZIkSZKkOWzGJbFJDk5yS5IfJjmhx/5Nk5zb7P9ukqEBhDnjjKHdjk6yOsn1zZ8/GUScM0mSM5L8d5IbRtifJP/ctOn3kuw+3THORGNotwOTrOn6rL1zumOciZLsmOTSJN9PcmOSN/eo42euyxjbzM+bBibJW5NUku0GHctMkOS9zc+u65N8Ocn2g45p0JKcmuTmpl0uSLLNoGMatCRHNj/TH00yp1fkHe33d41sRiWxSeYBHwFeCuwCvDrJLsOq/TFwX1X9NvBB4JTpjXLmGWO7AZxbVbs1f06f1iBnpjOBgzey/6XATs2fJcBp0xBTG5zJxtsN4Iquz9p7piGmNlgPvLWqdgH2Af6ix/9TP3OPNZY2Az9vGoAkOwK/D/zHoGOZQU6tqudW1W7ARYBfKsFXgF2r6rnArcDfDjiemeAG4H8C3xh0IIM0jt/f1cOMSmKBvYAfVtWPquoXwKeBw4bVOQz4ZLN9PvB7STKNMc5EY2k3DVNV3wDu3UiVw4B/qY4rgW2SPG16opu5xtBu6qGq7q6qa5vtB4GbgB2GVfMz12WMbSYNygeBvwZcXKRRVQ90vdwS24aq+nJVrW9eXgn85iDjmQmq6qaqumXQccwA/v4+CTMtid0BuKPr9Y95/C8sv6zT/FBYA2w7LdHNXGNpN4BXNMNZzm++QdbGjbVd9Xj7JlmR5EtJnjPoYGaaZhrE84HvDtvlZ24EG2kz8POmaZbkMODOqlox6FhmmiQnJbkDeA32xA73RuBLgw5CM4b3/EnYZNABaNp8ATinqtYl+TM6vdkvHnBMmp2uBZ5eVQ8lOQT4HJ3hsQKSbAX8G/CXw3otNIJR2szPm6ZEkq8Cv9Fj19uBv6MzlHjO2Vi7VNXnq+rtwNuT/C3wJuBd0xrgAIzWJk2dt9OZInH2dMY2KGNpE2kyZloSeyfQ3UP4m01Zrzo/TrIJMB/4yfSEN2ON2m5V1d1GpwP/MA1xtd1YPo8apjvJqKovJvloku2q6p5BxjUTJHkinWTs7Kr6bI8qfuaGGa3N/LxpqlTVQb3KkywCngGsaGYz/SZwbZK9quo/pzHEgRipXXo4G/gicyCJHa1NkhwNvAz4vZojz7Ycx+dkLvOePwkzbTjx1cBOSZ6R5NeAVwEXDqtzIfCGZvuVwNfnyg+EjRi13YbNq3s5nbll2rgLgdc3K8buA6ypqrsHHdRMl+Q3NsxTT7IXnZ8zc/2LJpo2+b/ATVX1gRGq+ZnrMpY28/Om6VZVK6vq16tqqKqG6AwB3H0uJLCjSdI9CuIw4OZBxTJTJDmYztzpl1fV2kHHoxllLHmPRjCjemKran2SNwGXAPOAM6rqxiTvAZZX1YV0fqH5VJIf0llc5lWDi3hmGGO7HZ/k5XSGstwLHD2wgGeIJOcABwLbJfkxnW+LnwhQVR+j8w3yIcAPgbXAMYOJdGYZQ7u9EjguyXrgZ8Cr/KIJgBcArwNWJrm+Kfs7YCH4mRvBWNrMz5s0c5yc5NnAo8DtwLEDjmcm+DCwKfCV5vu2K6tqTrdLkiOADwELgGVJrq+q/zHgsKbdSL+/Dzis1oj3ekmSJElSW8y04cSSJEmSJI3IJFaSJEmS1BomsZIkSZKk1jCJlSRJkiS1hkmsJEmSJKk1TGIlSZIkSa1hEitJkiRJag2TWEmSJElSa/z/W7JDKfqYlr0AAAAASUVORK5CYII=\n", "text/plain": [ "<Figure size 1152x2160 with 12 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plot_important_words(data=train, feature='POS', n_important=10)" ] }, { "cell_type": "code", "execution_count": 14, "id": "4b421178", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:32:18.114128Z", "iopub.status.busy": "2022-10-27T19:32:18.113744Z", "iopub.status.idle": "2022-10-27T19:37:12.283879Z", "shell.execute_reply": "2022-10-27T19:37:12.282605Z" }, "papermill": { "duration": 294.216645, "end_time": "2022-10-27T19:37:12.310346", "exception": false, "start_time": "2022-10-27T19:32:18.093701", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 1152x2160 with 12 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plot_important_words(data=train, feature='LEMMA', n_important=10)" ] }, { "cell_type": "code", "execution_count": 15, "id": "aed8c3c5", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:37:12.356072Z", "iopub.status.busy": "2022-10-27T19:37:12.355071Z", "iopub.status.idle": "2022-10-27T19:37:15.052134Z", "shell.execute_reply": "2022-10-27T19:37:15.048681Z" }, "papermill": { "duration": 2.722517, "end_time": "2022-10-27T19:37:15.055014", "exception": false, "start_time": "2022-10-27T19:37:12.332497", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 1152x2160 with 12 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plot_important_words(data=train, feature='LABEL', n_important=10)" ] }, { "cell_type": "code", "execution_count": 16, "id": "2619c186", "metadata": { "_kg_hide-input": true, "execution": { "iopub.execute_input": "2022-10-27T19:37:15.105376Z", "iopub.status.busy": "2022-10-27T19:37:15.104957Z", "iopub.status.idle": "2022-10-27T19:37:15.117430Z", "shell.execute_reply": "2022-10-27T19:37:15.116293Z" }, "papermill": { "duration": 0.040804, "end_time": "2022-10-27T19:37:15.120310", "exception": false, "start_time": "2022-10-27T19:37:15.079506", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "def add_stat_features(df):\n", " df[\"flesch_reading_ease\"] = train[\"full_text\"].apply(textstat.flesch_reading_ease)\n", " df[\"flesch_kincaid_grade\"] = train[\"full_text\"].apply(textstat.flesch_kincaid_grade)\n", " df[\"smog_index\"] = train[\"full_text\"].apply(textstat.smog_index)\n", " df[\"coleman_liau_index\"] = train[\"full_text\"].apply(textstat.coleman_liau_index)\n", " df[\"automated_readability_index\"] = train[\"full_text\"].apply(textstat.automated_readability_index)\n", " df[\"dale_chall_readability_score\"] = train[\"full_text\"].apply(textstat.dale_chall_readability_score)\n", " df[\"difficult_words\"] = train[\"full_text\"].apply(textstat.difficult_words)\n", " df[\"linsear_write_formula\"] = train[\"full_text\"].apply(textstat.linsear_write_formula)\n", " df[\"gunning_fog\"] = train[\"full_text\"].apply(textstat.gunning_fog)\n", " df[\"text_standard\"] = train[\"full_text\"].apply(textstat.text_standard)\n", " df[\"text_standard\"] = df[\"text_standard\"].str.extract('(\\d+)').astype(int)\n", " df[\"fernandez_huerta\"] = train[\"full_text\"].apply(textstat.fernandez_huerta)\n", " df[\"szigriszt_pazos\"] = train[\"full_text\"].apply(textstat.szigriszt_pazos)\n", " df[\"gutierrez_polini\"] = train[\"full_text\"].apply(textstat.gutierrez_polini)\n", " df[\"crawford\"] = train[\"full_text\"].apply(textstat.crawford)\n", " df[\"gulpease_index\"] = train[\"full_text\"].apply(textstat.gulpease_index)\n", " df[\"osman\"] = train[\"full_text\"].apply(textstat.osman)\n", " \n", " stat_features = [\"flesch_reading_ease\", \"flesch_kincaid_grade\", \"smog_index\", \"coleman_liau_index\", \n", " \"automated_readability_index\", \"dale_chall_readability_score\", \"difficult_words\", \"linsear_write_formula\", \"gunning_fog\", \n", " \"text_standard\", \"fernandez_huerta\", \"szigriszt_pazos\", \"gutierrez_polini\", \"crawford\", \n", " \"gulpease_index\", \"osman\"]\n", " return stat_features" ] }, { "cell_type": "code", "execution_count": 17, "id": "9ac3a546", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:37:15.167494Z", "iopub.status.busy": "2022-10-27T19:37:15.166716Z", "iopub.status.idle": "2022-10-27T19:37:15.171631Z", "shell.execute_reply": "2022-10-27T19:37:15.170854Z" }, "papermill": { "duration": 0.031382, "end_time": "2022-10-27T19:37:15.174163", "exception": false, "start_time": "2022-10-27T19:37:15.142781", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "'''\n", "stat_features = add_stat_features(train)\n", "_ = add_stat_features(test)\n", "\n", "end_mem = train.memory_usage().sum() / 10242\n", "print('Memory usage after optimization is: {:.2f} MB'.format(end_mem))\n", "''';" ] }, { "cell_type": "code", "execution_count": 18, "id": "99c8152d", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:37:15.220263Z", "iopub.status.busy": "2022-10-27T19:37:15.219807Z", "iopub.status.idle": "2022-10-27T19:37:48.108395Z", "shell.execute_reply": "2022-10-27T19:37:48.107155Z" }, "papermill": { "duration": 32.956974, "end_time": "2022-10-27T19:37:48.153189", "exception": false, "start_time": "2022-10-27T19:37:15.196215", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "---------------------------------------- conventions ----------------------------------------\n" ] }, { "data": { "image/png": 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5S6KS8kol5LNMnkXLOqpS8orH4LGK1l0qdwCefvppJk6cSETQv39/pk6dWu6QzMzMzMzMrEq4gsesQhxwwAHMmjWr3GF0RV1WU8MpETElq0wA90kK4Dc51puZZWsvtzivmFlH+ZzFzAqtIvKKK3isZCLC06zWgDaazzZFxOh2Nv90RCyU9HHgfkkvRsSjhY3QzGpMe7nFecXMOsrnLGZWaBWRV7pP/xcrqz59+rBo0aKK6ltrHRcRLFq0iD59+nR2+4Xpz3eAO4B9ChiemXVDzitmVgzOLWZWaKXIK27Bk2W77bYrSyuT7bbbruTHLKUhQ4bQ2NjYMkWiVYY17+c3zXqP9xa1PO/Tpw9Dhgzp8LEk9QU2iogP0ueHARd2eEdVqFx5JVccZrWkO+cVqIzc4rxitag75xZfC5kVR6nySlEreCSNAX4J9ACuiYiLs9b3Bm4A9gIWAcdFxAJJhwIXA72Aj4BzIuLBdJu9gOuAjYHpwFkREZI+BvweGAosAL4UEYs7GvOCBQs6/D6tfT179mTYsGHlDsOylHiGgK2AO9KThjrg5oi4pxA7rnS58sqlr76V17bnDBtU4GjMakq3zSvgcxazIuq2ucV5xaxoSpJXilbBI6kHcCVwKNAIzJBUHxFzM4qdAiyOiOGSxgOXAMcB7wKfj4g3Je0C3AsMTrf5NXAq8HeSCp4xwN3AJOCvEXGxpEnp6+8W6/2ZWcdExCvA7uWOw8xqh/OKmRWDc4uZFVqp8koxx+DZB5gfEa9ExEfANGBcVplxwPXp89uAQyQpIp6NiDfT5XOAjSX1ljQI2CwinoxkMJcbgKNz7Ov6jOVmZmZmZmZmZjWtmBU8g4E3Ml43sq4VzgZlIqIJWAoMzCrzReCZiFiVlm9sZZ9bRURzn4f/I2kCtQFJEyQ1SGpoamrq2DsyMzMzMzMzM6tAFT3IsqSdSbptHdaR7dIxeXJO15TONT8FoG/fvp7SyczMzMzMzMyqXjFb8CwEtsl4PSRdlrOMpDpgc5LBlpE0hGTqsBMj4uWM8pnT92Tu8+20Cxfpz3cK9k7MzMzMMkgaI+klSfPTsf+y139b0lxJsyX9VdJ2GetOkjQvfZxU2sjNzMysVhWzgmcGMELSMEm9gPFAfVaZeqD5xOYY4MG09U1/4C/ApIh4rLlw2gXrfUn7KRl++kTgzhz7OiljuZl1c3lciPWW9Pt0/d8lDc1Yt5ukJyTNkfScpD4lDd7MKk7GRBJHACOB4yWNzCr2LDA6InYjGWfwZ+m2HwN+COxLMl7hDyUNKFXsZmZmVruKVsGTjqkzkWQGrBeAWyNijqQLJY1Ni10LDJQ0H/g2ycxXpNsNB86XNDN9fDxddxpwDTAfeJlkBi1IplU/VNI84LPpazPr5vK8EGuZ0Q/4BUnX0OaWhTcB34iInYGDgNUlCt3MKle7E0lExEMRsSJ9+STrWiAfDtwfEe9FxGLgfpIZQc3MzMy6pKhj8ETEdJKpzDOXnZ/xfCVwbI7tfgL8pJV9NgC75Fi+CDikiyGbWe1puRADkNR8ITY3o8w44IL0+W3A5LSV4GHA7IiYBS15xsws10QS+7ZR/hTW3ZDKZxIKIJkYApgA0KtXr87GamZmZt1EMbtomZlVgq7M6PcJICTdK+kZSefmOoBn5zOz1kj6MjAauLSj20bElIgYHRGj6+oqel4MMzMzqwCu4DEza10d8GngP9KfX5C0QUtBX4SZdTv5TCSBpM8C3wPGRsSqjmxrZmZm1lGu4DGzWteVGf0agUcj4t10LI3pwJ5Fj9jMKl27E0lI2gP4DUnlTubMnvcCh0kakA6ufFi6zMzMzKxLXMFjZrWu0zP6kVx07Sppk7Ti599Yf+weM+uG8pxI4lKgH/CHdLKI+nTb94Afk+SmGcCF6TIzMzOzLnFfAjOraRHRJKn5QqwHMLX5QgxoiIh6khn9bkxn9HuPpBKIiFgs6TKSi7AApkfEX8ryRsysouQxkcRn29h2KjC1eNGZmZlZd+QKHjOreZ2d0S9ddxPJVOlmZmZmZmYVy120zMzMzMzMKpSkqZLekfR8K+v/Q9JsSc9JelzS7qWO0cwqgyt4zMzMzMzMKtd1wJg21r8K/FtE7EoyxteUUgRlZpXHXbTMzMzMzMwqVEQ8KmloG+sfz3j5JMmMoWbWDbkFj5mZmZmZWW04Bbi73EGYWXm4BY+ZmZmZmVmVk3QwSQXPp9soMwGYANCrV68SRWZmpeIWPGZmZmZmZlVM0m7ANcC4iFjUWrmImBIRoyNidF2d7/Wb1Rp/qs3MyuATN12XX8EfnFfUOMzMzKy6SdoW+CPwlYj4R7njMbPycQWPmZmZmZlZhZJ0C3AQsIWkRuCHQE+AiLgaOB8YCFwlCaApIkaXJ1ozKydX8JiZmZmZmVWoiDi+nfVfA75WonDMrIJ5DB4zMzMzMzMzsyrnFjxmZmZmVpUeX/JBXuX+tf+mRY7EzMys/IragkfSGEkvSZovaVKO9b0l/T5d/3dJQ9PlAyU9JGmZpMkZ5TeVNDPj8a6ky9N1J0v6Z8Y6N1M0MzMzMzMzs26haC14JPUArgQOBRqBGZLqI2JuRrFTgMURMVzSeOAS4DhgJfADYJf0AUBEfACMyjjG0yQjxjf7fURMLM47MjMzMzMzMzOrTMVswbMPMD8iXomIj4BpwLisMuOA69PntwGHSFJELI+I/yWp6MlJ0ieAjwN/K3zoZmZmZmZmZmbVo5gVPIOBNzJeN6bLcpaJiCZgKckUf/kYT9JiJzKWfVHSbEm3Sdom10aSJkhqkNTQ1NSU56HMzMzMzMzMzCpXNc+iNR64JeP1XcDQiNgNuJ91LYPWExFTImJ0RIyuq/MY02ZmZmZmZmZW/YpZwbMQyGxFMyRdlrOMpDpgc2BRezuWtDtQFxFPNy+LiEURsSp9eQ2wV+dDNzMzMzMzMzOrHsWs4JkBjJA0TFIvkhY39Vll6oGT0ufHAA9mdblqzfGs33oHSYMyXo4FXuhU1GZmZmZmZmZmVaZofZQioknSROBeoAcwNSLmSLoQaIiIeuBa4EZJ84H3SCqBAJC0ANgM6CXpaOCwjBm4vgQcmXXIMyWNBZrSfZ1crPdmZmZmZmZmZlZJijoITURMB6ZnLTs/4/lK4NhWth3axn63z7HsPOC8zsZqZmZmZmZmZlatqnmQZTMzMzMzMzMzwxU8ZmZmZmZmZmZVzxU8ZmZmZmZmZmZVzhU8ZmZmZmZmZmZVzhU8ZmZmZmZmZmZVzhU8ZmZmZmZmZmZVzhU8ZlbzJI2R9JKk+ZIm5VjfW9Lv0/V/lzQ0XT5U0oeSZqaPq0sevJmZmZmZWR7qyh2AmVkxSeoBXAkcCjQCMyTVR8TcjGKnAIsjYrik8cAlwHHpupcjYlQpYzYzMzMzM+sot+Axs5KS1EPSs5L+XKJD7gPMj4hXIuIjYBowLqvMOOD69PltwCGSVKL4zKyLypBXzKzGOa+YWTEUO7e4gsfMSu0s4IUSHm8w8EbG68Z0Wc4yEdEELAUGpuuGpUn4EUkH5DqApAmSGiQ1NDU1FTZ6M8tHqfOKmdU+5xUzK4ai5hZX8JhZyUgaAnwOuKbcseTpLWDbiNgD+DZws6TNsgtFxJSIGB0Ro+vq3PPVrJSqMK+YWYVzXjGzYihFbnEFj5kVSl1zK5b0MSFHmcuBc4G1JYxrIbBNxush6bKcZSTVAZsDiyJiVUQsAoiIp4GXgU8UPWIzy9Rebrmc0ucVM6tuzitmVmgVcS3kW81mVihNETG6tZWSjgLeiYinJR1UsqhgBjBC0jCSipzxwAlZZeqBk4AngGOAByMiJG0JvBcRayRtD4wAXild6GZGG7mljHnFzKqb84qZFVpFXAu5BY+Zlcr+wFhJC0gGOv6MpJuKfdB0TJ2JwL0k/V1vjYg5ki6UNDYtdi0wUNJ8kq5YzVOpHwjMljSTZPDlb0TEe8WO2czyVpa8YmY1reLyiqSpkt6R9Hwr6yXpCknzJc2WtGepYzSzdpUkt7gFj5mVREScB5wHkNZanx0RXy7RsacD07OWnZ/xfCVwbI7tbgduL3qAZtYp5cwrZlabKjSvXAdMBm5oZf0RJK2MRwD7Ar9Of5pZhShVbnELHjMzMzMzswoVEY8CbbUgHgfcEIkngf6SBpUmOjOrJG7BY2YlFxEPAw+XOQwzqyHOK2ZWaFWUVwYDb2S8bkyXvVWecMysLcXMLa7gMTMzMzMz6wbSmX0mAPTq1avM0ZhZoRW1gkfSGOCXQA/gmoi4OGt9b5K+pHsBi4DjImKBpIEkA5ruDVwXERMztnkYGAR8mC46LCLeaW1fRXx7ZlXv8SUf5FVuXJHjMDMzM7NOWwhsk/F6SLpsAxExBZgC0Ldv3yh+aGZWSkUbg0dSD+BKkkG/RgLHSxqZVewUYHFEDAd+AVySLl8J/AA4u5Xd/0dEjEof77SzLzMzMzMzs1pVD5yYzqa1H7A0Itw9y6wbKuYgy/sA8yPilYj4iGQqsOyGAOOA69PntwGHSFJELI+I/yWp6MlXzn11PnwzMzMzM7PyknQL8ASwo6RGSadI+oakb6RFpgOvAPOB3wKnlSlUMyuzYnbRyjXYV/Z0fS1lIqJJ0lJgIPBuO/v+H0lrSKYv/klERL77cr9TMzMzMzOrFhFxfDvrAzi9ROGYWQWrxmnS/yMidgUOSB9f6cjGETElIkZHxOi6Oo8xbWZmZh0naYyklyTNlzQpx/oDJT0jqUnSMVnr1kiamT7qSxe1mZmZ1bJiVvDkM9hXSxlJdcDmJAMktyoiFqY/PwBuJukK1ql9mZmZmXVUnuMMvg6cTHKuku3DjLEExxY1WDMzM+s2ilnBMwMYIWmYpF7AeJIBwDLVAyelz48BHkybGOYkqU7SFunznsBRwPOd2ZeZmZlZJ7U7zmBELIiI2cDacgRoZmZm3U/R+iil4+BMBO4lmSZ9akTMkXQh0BAR9cC1wI2S5gPvkVQCASBpAbAZ0EvS0cBhwGvAvWnlTg/gAZKBxGhrX2bdyaWv5j9pwieKGIeZWQ3LZ5zBtvSR1AA0ARdHxJ9yFfK4gWZmZtYRRR2EJiKmk4zqnrns/IznK4FjW9l2aCu73auV8q3uy8zMzKyCbBcRCyVtDzwo6bmIeDm7UERMAaYA9O3b162SzczMrE3VOMiymZmZWTnlM85gqzLGE3wFeBjYo5DBmZmZWffkCh4zMzOzjslnnMGcJA2Q1Dt9vgWwPzC3aJGamZlZt+F5ws3MzMw6IJ9xBiXtDdwBDAA+L+lHEbEzsBPwG0lrSW60XRwRruDJku94ch5LzszMbB1X8JiZmZl1UB7jDM4g6bqVvd3jwK5FD9DMzMy6HXfRMjMzMzMzMzOrcq7gMTMzMzMzMzOrcq7gMTMzMzMzMzOrcq7gMTMzMzMzMzOrEJI2lrRjR7dzBY+ZmZmZmZmZWQWQ9HlgJnBP+nqUpPp8tnUFj5mZmZmZmZl1yprVa7vVcUvgAmAfYAlARMwEhuWzoadJNzMzMzMzM7MOWbRwGXdNnsXyJavo1783R52xOwO37lezxy2h1RGxVFLmsshnQ7fgMTMzMzMzM7MOuWvyLJYvXgUByxav4s+/mlXTxy2hOZJOAHpIGiHpV8Dj+WzoCh4zMzMzMzMzy9ua1WtZvmTVesuWLVlVkG5Tbe2jmMetIGcAOwOrgJuBpcBZ+WzoCh4zq3mSxkh6SdJ8SZNyrO8t6ffp+r9LGpq1fltJyySdXbKgzczMzMwqVI+eG9Gvf+/1lvXr35sePTtfxbBo4TKuO+8xrj7zYa4/7zEWvbmsJMetQJ+LiO9FxN7p4/vA2Hw2rKnfgplZNkk9gCuBI4CRwPGSRmYVOwVYHBHDgV8Al2Stvwy4u9ixmpmZmZlVi6PO2J1+A3qDoN+AZCycrsi361Whj1uBzstz2QY8yLKZ1bp9gPkR8QqApGnAOGBuRplxJKPVA9wGTJakiAhJRwOvAstLFrGZmZmZWYUbuHU/Tvrp/qxZvbbLLWja6nqVve9CHreSSDoCOBIYLOmKjFWbAU357KN2fhtmZrkNBt7IeN2YLstZJiKaSPq5DpTUD/gu8KO2DiBpgqQGSQ1NTXnlXjMzMzOzmlCISpbOdL2qpcqd1JtAA7ASeDrjUQ8cns8O3ILHzKx1FwC/iIhlWdMUricipgBTAPr27ZvXFIZmZmZmZrbOUWfszp9/NYtlGdOfdycRMQuYJenmiFjdmX0UtYJH0hjgl0AP4JqIuDhrfW/gBmAvYBFwXEQskDSQpJvE3sB1ETExLb8J8AdgB2ANcFdETErXnQxcCixMdz85Iq4p5vszs6qwENgm4/UQ1uWJ7DKNkuqAzUly0r7AMZJ+BvQH1kpaGRGTix61mZkVzONLPsi77LgixmFmZq2r1a5XnTBU0k9Jxg/t07wwIrZvb8Oi/da6OLDpSuAHQK4Za34eEZ8E9gD2T/upNft9RIxKH67cMTOAGcAIScMk9QLGkzRzzFQPnJQ+PwZ4MBIHRMTQiBgKXA78f67cMTMzs1LLY0bQbSU9JOlZSbMlHVmOOK22lGvq8W5euQPwP8CvScbdOZikUcxN+WxYzBY8XRnYdDnwv5KGZ+4wIlYAD6XPP5L0DMndeDOznCKiSdJE4F6S1oRTI2KOpAuBhoioB64FbpQ0H3iPpBLIzMzMrOwybpwfSjKW4AxJ9RGReV31feDWiPh1elN9OjC05MFaxcundcyihcuSGa0yukoN3LpfiSI0YOOI+GtaN/IacIGkp4Hz29uwmBU8uQY23be1MulF2FJgIPBuezuX1B/4PEkXsGZflHQg8A/g/0XEGzm2mwBMAOjVq1e+78XMqlhETCc50clcdn7G85XAse3s44KiBGdmZmbWtnxunAfJTDuQdDV/s6QRWsXrSKVNy3TlrJuu/KSf7t/lGNz1Km+rJG0EzEtvVC8E8qphy+u3K2mDv2auZaWSjpFxC3BFc6ID7gKGRsRuwP3A9bm2jYgpETE6IkbX1XmMaTMzMzMzq2j5zAh6AfBlSY0kN7XOyLUjz/zZfbVU2sS6Sptc2pquvLMWLVzGdec9xtVnPsz15z3GojeXdXpf3cRZwCbAmSTjFX8FODGfDfOtPvtVnssydWRg0+ZKm+aBTdszBZgXEZc3L4iIRRHR/J94DckvwsysakS0PlOXmZmZWRuOJ5mcZghwJEnX8w2u9Xyzu3a1VQHTkUqbzkxX3p58K5csEREzImJZRDRGxH+S9DQY3t520E4XLUmfAv4V2FLStzNWbUYylkVbWgY2JanIGQ+ckFWmeWDTJ8gY2LSdmH5CUhH0tazlgyLirfTlWOCFduIzsxwihOSZvktp9eqNeffdHVmzthc9NvqILbZ4iZ49Pyx3WGZmlaVpLdS1f4Hh7zGrQfncOD8FGAMQEU9I6gNsAbxTkgitbPLpetVcabNs8bpKnrYqbQo5XXlblUvurrU+SZsBp5O00Ksn6Zl0OvAdYDbwu/b20V61bS+Svl51wKYZy98nqZBpVVcHNpW0gKQiqZeko4HD0uN+D3gReEYSrJsO/UxJY0lGmn4POLm9N29m67iSoXyaf+8g1qztxbvv7sigQTPLHZaZWUXQP1fS+w9voGVNRL86Vh27LbFl7w3KdfR7zBVBVkXyuXH+OnAIcJ2knUimVv5nSaO0omivIiTf8XI6UmlTyOnKO1q51M3dCCwmaQDzNeC/AAFfiIiZ+eygzQqeiHgEeETSdenozR3SlYFN02mJc8nZhyEizgPO62iMZpZwJUN5RKjl955IXvvCw8ws0fsPb6APmpIs+UETvf/wOitPG7FBuXy/x3xDw6pNnjfOvwP8VtL/Ixlw+eT2ekZYZcunZU5HWsd0ptKmUJUwhWwRVOO2j4hdASRdA7wFbJvWm+Ql346XvSVNIZlqr2WbiPhM/rGaWdm006zdlQzlIwU9Nvoo4/efvPbv3cwMaFqLljVlfDsBHzRt8L3Wke8x39CwapTHjfO5QNkmwbGOK0TLnM60jilHy5lCtgiqcaubn0TEGkmNHancgfwreP4AXE0yePGajhzAzMon32btrmQory22eGmDu8lmZgbUbUT0q4O0BU8AsWndBjct8v0e8w0NMyu3QrfMqabWMa7cadfukt5PnwvYOH0tICJis/Z2kG8FT1NE/LqTQZpZmeTbrB1cyVBOPXt+yKBBM32BYWbd0pq1osdGree+VcduS+8/vA4ZNytyyed7zDc0zKzcCt0yx61jakdEtDeRVbvyreC5S9JpwB1Ay39ZRLzX1QDMrEjybNbezJUM5effu5l1J0tX9ubR17blw6Y6Nq5r4sDtXmfzPqs2KBdb9k5uTrTT3Tjf77HO3NDwhZOZ5autfFHMljnOUQb5V/CclP48J2NZANsXNhwzK5g8m7VnK1YlQzpd56NAb5Lcc1tE/LAoBzOzbsF5pbo1V+6A+LCpjkdf25bP7ziv9Q3ymCId2v8e68gNjXy6UljtcW6xzij0dOVumVM4+f4Oi/m7LlVeySv6iBiW4+HKHbMKt+rYbYlN6wgllTutNWsvVTjAZyJid2AUMEbSfuUMyMyqnvNKlVqzVi2VO4nk9Zq1OSdLLYp8bmi0dKWIdV0prFtwbrENtJef8s0XR52xO/0G9AZBvwFumVNMixYu47rzHuPqMx/m+vMeY9Gby7pUrotKklfyasEj6cRcyyPihsKGY2aFlG+z9pLEkkzV2Zwte6YP90kys05zXqlePTYKNq5ryqjkSV63NRZPqXWkK0XmNr4Yq37OLdWvkJ/FfLqTFnu6cuucfMY76ki5ruhIXpF0SUR8t71lueT7H7V3xuMA4AJgbJ7bmlm5laZyp05SQ8ZjQnYBST0kzQTeAe6PiL+XIjAzq2pt5hbnlep14Havs3FdE82VOwdu93q5Q1pPc1eKTK11pSjR3V8rHJ+z1KhifBZzdSfN1pF8kbmNFU9blW6dKZeHQuaVQ3MsOyKvIPIpFBFnZAXWH5iWz7Zm1m00RcTotgpExBpgVJpD7pC0S0Q8X5LozKxatZlbnFeq1+Z9VvH5Hee1O4tWOeU7yGkp7v5aQfmcpUYV+rPYVnfS7LxVTdOVdwf5jnfUkXGR2tHlvCLpm8BpwPaSZmdsuinwWD5B5DvIcrblwLBObmtm3VxELJH0EDAG8MmSmXWZ80r1qtTKHcivK0VnunJZ9XBuqSyl/ix2pDupu15Vnnwr3UpdOddGXrkZuBv4KTApY/kH+c5gnu8YPHexrn9YD2An4NZ8tjUzA5C0JbA6TWgbkzQ9vKTMYZlZFXNesVJpr5tFge7+WoVwbqk8hZ6hqlk+lTEHbvf6BmPwtMWf/cqRb6VbKSrn8skrEbEUWAocL+nTwIiI+B9JW0gaFhGvtnecfFvw/DzjeRPwWkQ05rmtmRnAIOB6ST1Ixv+6NSL+XOaYzKy6Oa9UsO50F9tdM2qOc0uFybfrVb6fxXwqjJpVQ3dSa1u+30VF/s7KO69I+iEwGtgR+B+gF3AT0G5/w3zH4HlE0lYkgywDzMtnOzOzZhExG9ij3HGYWe1wXqlMHblwqhXumlFbnFsqSzFmqOrMWD2u3LGu6GBe+UJa9pl02zclbZrPhvl20foScCnwMEnnw19JOicibsszQDMrkU/cdF25Q7Ai8wWEmVWy7jzgsHOzWeF1putVe92yPG6WVbiPIiIkBYCkvvlumG8Xre8Be0fEO+kBtgQeAFzBY2ZWIt3xrriZVRdfOBWWf29miUJ2g/S4WVYFbpX0G6C/pFOBrwK/zWfDfCt4Nmqu3EktIuk3ZmZl5BO/7qU73xU3s+rgC6fCcIW+2foK3Q3S42ZZJYuIn0s6FHifZBye8yPi/ny2zbeC5x5J9wK3pK+PA6Z3OFIzKwif+HU/vituZtXCF05d5wp9s9wKdc7jcbOs0qUVOnlV6mRq879Z0nBJ+0fEOcBvgN3SxxPAlPZ2LmmMpJckzZc0Kcf63pJ+n67/u6Sh6fKBkh6StEzS5Kxt9pL0XLrNFZKULv+YpPslzUt/Dsj3l9AZa1avLebuzdrUcuIX6078rLY13xXP5LviZlaJmi+cvnHFQZz00/19A6KD2qrQb2ubcvE5sbWl0v8/fB5llUjSB5Lez3q8IekOSdu3tW17LXguB84DiIg/An9MD7hruu7zbQTVA7iSZH73RmCGpPqImJtR7BRgcUQMlzSeZB7444CVwA+AXdJHpl8DpwJ/J2lFNAa4G5gE/DUiLk4rkyYB323n/XWYW05YubklR/flu+JmVk38ndS6tr6zO9LNrZznpT4ntrb4/8OsSy4nqUO5mWSSq/HADiSzak0FDmptw/a+ebeKiOeyF6bLhraz7T7A/Ih4JSI+AqYB47LKjAOuT5/fBhwiSRGxPCL+l6Sip4WkQcBmEfFkRARwA3B0jn1dn7G8oNxywsrNLTm6L98VNzOrbosWLuO68x7j6jMf5vrzHmPRm8tyljvqjN3pN6A3CPoNaL1Cv5znpT4ntrb4/8OsS8ZGxG8i4oOIeD8ipgCHR8TvgTZ7KrV3Rdi/jXUbt7PtYOCNjNeN6bKcZSKiCVgKDGxnn42t7HOriHgrff5/wFa5diBpgqQGSQ1NTU3tvIX1dabJrFkx5HviZ7Up38o85yaz4smjG/qBkp6R1CTpmKx1J6VdyudJOql0UVu55XvRm0+FfjnPS31ObG3x/4dZl62Q9CVJG6WPL7Gu8Uu0tWF7XbQaJJ0aEetNySXpa8DTnY+3uDLnjM+xbgrp+EF9+/Zt85eTzTNDWKXwwHAdI2kM8EugB3BNRFyctb43SYvAvUhmCTwuIhZI2od1440JuCAi7ihd5J3jZtFmxZVnN/TXgZOBs7O2/RjwQ2A0yUna0+m2i0sRu5VPZ7pYt/UdX87zUp8TW1v8/2HWZf9Bcu1yFcm5wpPAlyVtDExsa8P2PmXfAv5T0sOS/jt9PEIyds5Z7Wy7ENgm4/WQdFnOMpLqgM1JLq7a2ueQVvb5dtqFq7kr1zsUgVtOWCXxF2X7Mi7EjgBGAsdLGplVrGU8MOAXJOOBATwPjI6IUSTjff0mzVUVzc2izYqu3W7oEbEgImYD2besDwfuj4j30kqd+0nyi9W4YnSxLud5qc+JrS3+/zDrnPTa5bSI+HxEbBERW6bP50fEh+lQNq1q80IlIt4G/lXSwawb7PgvEfFgHrHNAEZIGkZSCTMeOCGrTD1wEsmsXMcAD6Zj67QWz1vpCNL7kQyyfCLwq6x9XZz+vDOPGDvMLSfMqk7LhRiApOYLscw77eOAC9LntwGT0/HAVmSU6UM7TSIrgQfhNiuJXN3Q9+3Cttld2IGkWzkwAaBXr14dj9IqTqEHyy/neanPia0t/v8w65yIWCPp053dPq870RHxEPBQR3YcEU2SJgL3knSLmBoRcyRdCDRERD1wLXCjpPnAeySVQABIWgBsBvSSdDRwWNr0+TTgOpIxgO5OH5BU7Nwq6RTgNeBLHYm3o5yorJj8ZVhQ+VyIrTcemKTm8cDelbQvyWj12wFfSccLW08lXYS5WbRZ7ehKt3KrTMW66C1njvf3i7XF/x9mnfKspHrgD8Dy5oXpzOZtKmpXg4iYTjKVeeay8zOerwSObWXboa0sb2DDqdOJiEXAIV0I16zsPHZK5YmIvwM7S9oJuF7S3WnuyixTURdhnk7drOjy6Ybe1rYHZW37cEGisqrhi17rqPbGE0zLfImkRXIAsyIiu/eEmVWHPiRD13wmY1kA5a3gMbOOaRk7hXVjp5z00/3LHFXV68h4YI2tjQcWES9IWkZSwdxQvHC7zs2izYoun27orbkX+P8kNU9zehhwXuFDNLNakc/A7pJGkOSS/SNisaSPlyfazvE5i9k6EfGfnd3WFTxmFcJjpxRNp8cDS7d5I+22tR3wSWBBySLvIv/fmBVHPt3QJe0N3AEMAD4v6UcRsXNEvCfpxyS5CeDCiHivLG/EzKpFPuMJngpc2TwjX0QUZcKZQnPrdbMNSepDMgnMziSteQCIiK+2t63P/s0qRDFm17DkQoxkOsF7gReAW5svxCSNTYtdCwxMxwP7NjApXf5pYJakmSQXaqdFxLslfQMlsmZ19kQ/ZtaWiJgeEZ+IiB0i4qJ02fnpGINExIyIGBIRfSNiYETsnLHt1IgYnj7+p1zvwcyqRj6Ds38C+ISkxyQ9mXbp2oCkCZIaJDU0NW0wrGDJeeZPs5xuBP6FZObNR0h6IHyQz4ZuwWNWQTx2SnF0djywiLiRJMHWLN85s1JwS8Ta4r+nWUWqA0aQjPE1BHhU0q4RsSSzUKHGDSxEHnDrdbP1SapLb04Pj4hjJY2LiOsl3Qz8LZ99uILHrIJ47BTL9s9fTc6r3JZnTOzU/j3ukxWTKxBri/+eZmWTz3iCjcDfI2I18Kqkf5BU+MyggAqZBzzzp9kGngL2BFanr5dI2gX4PyCvcbX86TGrQP5is1Jo686ZWSG46X1t8d/TrGxaxhOU1ItkPMH6rDJ/Ip2hT9IWJF22Xil0IIXOA0edsTv9BvQGQb8Bbr1ulpqSTsbwfZLP+lzgknw2dAseM7NuynfOrJjc9L62+O9ZG/z3qk75DOyerjtM0lxgDXBORCxqfa8dV4w84NbrZuv5uKRvp8+bZ9K6Mv3ZN58duILHzKwb87hPViyuQKwt/ntWN3evq355jCcYJBNFfJsiKWYecC4xA5IK3H6AcqzLa8wsV/CYmXVjvnNmxeQKxNriv2f18nhrVijOA2ZF9VZEXNiVHbiCx8zMXLljReEKxNriv2d1cvc6KyTnAbOiytVyp0P8qbSa4YFhzcwqky8Caov/ntWluVtNJnevs67y/49ZURzS1R24BY9VPfcrNzMzM2udu9WYmVW+iHivq/twBY9VPfcrN7NmbjJuZrYhd6sxM+seXMFjVc39ys0M3JLPzCwfPjcyM6ttzvJW1dyv3MwgoyVfrGvJZ2ZmZmbWnfgq2KreUWfsTr8BvUHQb4D7lZt1N2215DMzMzMz6y7cRcuqnvuVm3VvzS35li1eV8njlnxmZl3j8yozs+rjCh6rGcU4CfHJjVl18AwxZmaF4THNzMyqV1EreCSNAX4J9ACuiYiLs9b3Bm4A9gIWAcdFxIJ03XnAKcAa4MyIuFfSjsDvM3axPXB+RFwu6QLgVOCf6br/iojpxXpvVtt8cmNWGoWqRHVLPjOzwvDspGZm1atoFTySegBXAocCjcAMSfURMTej2CnA4ogYLmk8cAlwnKSRwHhgZ2Br4AFJn4iIl4BRGftfCNyRsb9fRMTPi/WerPvwyY1ZcRWrEtWVO2ZmnefZSc3MqlsxM/U+wPyIeCUiPgKmAeOyyowDrk+f3wYcIknp8mkRsSoiXgXmp/vLdAjwckS8VrR3YN2SB2w1K76Oznrlz5+ZWfF5dlIzs+pWzGw9GHgj43VjuixnmYhoApYCA/PcdjxwS9ayiZJmS5oqaUCuoCRNkNQgqaGpqakj78e6ic6c3Pji02x9bX0mOlKJumjhMq477zGuPvNhrj/vMRa9uazgsZqZ2TqendTMrHpV5SDLknoBY4HzMhb/GvgxEOnP/wa+mr1tREwBpgD07ds3ih6sVaV8B2z1WD1m68vnM9GRWa/cXdKsa9y1xjrKY5qZmVWvYlbwLAS2yXg9JF2Wq0yjpDpgc5LBltvb9gjgmYh4u3lB5nNJvwX+XID3YN1Uvic3vvg0W1++n4l8KlE9FoRZ5/kGhHWV86yZWfUpZgXPDGCEpGEklTPjgROyytQDJwFPAMcAD0ZESKoHbpZ0GckgyyOApzK2O56s7lmSBkXEW+nLLwDPF/j9WDfUXrcsX3yardORz0Q+lagdaeljZuvzDQgzM7Pup2hnyemYOhOBe4EXgFsjYo6kCyWNTYtdCwyUNB/4NjAp3XYOcCswF7gHOD0i1gBI6ksyM9cfsw75M0nPSZoNHAz8v2K9NzPwWD1m2TrzmWivssZjQZh1nCcLMDMz656KOgZPREwHpmctOz/j+Urg2Fa2vQi4KMfy5SQDMWcv/0pX4zXrKI/VY7a+fD8T+fJYEGYd59ZvZmZm3VNVDrJsVik8Vo/Z+opVIeMLU7OOKXRlq5mZmVU+V/BYt1TKi0+P1ZOQtA1wA7AVyWx3UyLil+WNyjoq3//bavjf7m6fwVrkvNI6t34z6zznFjMrtFLlFVfwWLdSjq5Sbirfogn4TkQ8I2lT4GlJ90fE3GIfWNIY4JdAD+CaiLg4a31vkoS7F8lMfsdFxAJJhwIXA72Aj4BzIuLBYsdbiWqpm2EtvRcrX16pFt3wu8asEJxbzKzQSpJX/K1v3UpLV6lY11WqFDxQLETEWxHxTPr8A5LB1wcX+7iSegBXAkcAI4HjJY3MKnYKsDgihgO/AC5Jl78LfD4idiWZ8e/GYsdbqcr12SmGWnov3V258oqZ1TbnFjMrtFLlFbfgsW6jnF2luklT+TpJDRmvp0TElFwFJQ0F9gD+XoK49gHmR8Qr6bGnAeNIZulrNg64IH1+GzBZkiLi2Ywyc4CNJfWOiPX/kWpcLXUzrKX30o3klVtKnFeshl366lt5lTtn2KAiR2JFVKnnLGZWvSoir7iCx7qNSugqVeMXkE0RMbq9QpL6AbcD34qI94sfFoOBNzJeNwL7tlYmIpokLSWZre/djDJfBJ7JVbkjaQIwAaBXr16Fi7xCVMJnp1Bq6b10I+3mljLkFTOrbpV6ztJWLG12N88o90WSm1V7R0RDrjJmVhQVkVd8RmvdirtKlZekniQJ7XcR8cdyx5MvSTuTdNv6eq71ETElIkZHxOi6utqsN6+lz04tvRer3rxiZpWtknJLnt3NScf1OAu3NjKrSKXIK7V5JWLWim7SVaoiSRJwLfBCRFxWwkMvBLbJeD0kXZarTKOkOmBzksGWkTQEuAM4MSJeLn64lamWPju19F66uzLmFTOrYRWYW/Lpbg7wY5IbUueUNjwza0+p8orPbK1b8kVdWewPfAX4jKSZ6ePIEhx3BjBC0jBJvYDxQH1WmXqSQZQBjgEejIiQ1B/4CzApIh4rQawVr5Y+O7X0XrqxcuUVM6ttlZZbcnU3X29wVkl7AttExF/a2pGkCZIaJDU0NTUVPlIza01J8opb8JhZSUTE/wIqw3GbJE0E7iXptz41IuZIuhBoiIh6ktr0GyXNB94jqQQCmAgMB86XdH667LCIeKe078LMcilXXjGz2lZtuUXSRsBlwMntlU0HfZ0C0Ldv3yhuZGbWrFR5xRU8ZlbzImI6MD1r2fkZz1cCx+bY7ifAT4oeoJmZmVnr2utuvimwC/Bw0guEfwHqJY31QMtm3YsreMzMzMysJB5f8kG5QzCrRi3dzUkqdsYDJzSvjIilwBbNryU9DJztyh2z7scDEJiZmZmZmVWoiGgi6TZ+L/ACcGtzd3NJY8sbnZlVErfgMTMzMzMzq2DtdTfPWn5QKWIys8rjFjxW8dasXlvuEMzMzMzMzMwqmlvwWMVatHAZd02exfIlq+jXvzdHnbE7A7fuV+6wzMzMzMzMzCqOW/BYxbpr8iyWL14FAcsWr+LPv5pV7pDMzMzMzMzMKpIreKwirVm9luVLVq23bNmSVe6uZWZmZmZmZpZDUSt4JI2R9JKk+ZIm5VjfW9Lv0/V/lzQ0Y9156fKXJB2esXyBpOckzZTUkLH8Y5LulzQv/TmgmO/NiqtHz43o17/3esv69e9Nj56ukzQzMzMzMzPLVrSrZUk9gCuBI4CRwPGSRmYVOwVYHBHDgV8Al6TbjgTGAzsDY4Cr0v01OzgiRkXE6Ixlk4C/RsQI4K/pa6tiR52xO/0G9AZBvwHJGDxmZmaVoLM3sSQNlfRheqNqpqSrSx68mZmZ1aRiDrK8DzA/Il4BkDQNGAfMzSgzDrggfX4bMFmS0uXTImIV8Kqk+en+nmjjeOOAg9Ln1wMPA98txBux8hi4dT9O+un+rFm91i13zMysYmTcxDoUaARmSKqPiMxznJabWJLGk9zEOi5d93JEjCplzGZmZlb7innVPBh4I+N1Y7osZ5mIaAKWAgPb2TaA+yQ9LWlCRpmtIuKt9Pn/AVvlCkrSBEkNkhqampo6/q6s5Fy5Y2ZmFablJlZEfAQ038TKNI7khhMkN7EOSW9imZmZmRVFNU6T/umIWCjp48D9kl6MiEczC0RESIpcG0fEFGAKQN++fXOWMTOrFI8v+SCvctlXlmZWVLluRO3bWpmIaJLUfBMLYJikZ4H3ge9HxN9yHSS9kTUBoFevXoWL3szMzGpSMZtGLAS2yXg9JF2Ws4ykOmBzYFFb20ZE8893gDtI7qIBvC1pULqvQcA7BXwvZmZmZoXwFrBtROwBfBu4WdJmuQpGxJSIGB0Ro+vqqvGenJmZmZVSMSt4ZgAjJA2T1Itk0OT6rDL1wEnp82OAByMi0uXj0wEKhwEjgKck9ZW0KYCkvsBhwPM59nUScGeR3peZmZl1b52+iRURqyJiEUBEPA28DHyi6BGbmZlZzSva7aC0OfJE4F6gBzA1IuZIuhBoiIh64FrgxnQQ5fdIKoFIy91KMiBzE3B6RKyRtBVwR9qFvQ64OSLuSQ95MXCrpFOA14AvFeu9mZmZWbfWchOLpCJnPHBCVpnmG09PkHETS9KWwHvpec32JDexXild6GZmZlaritreNyKmA9Ozlp2f8XwlcGwr214EXJS17BUg51zZ6d2wQ7oYspmZmVmbunITCzgQuFDSamAt8I2IeK/078LMzMxqjTt0m5mZmXVQZ29iRcTtwO1FD9DMzMy6Hc8/bWZmZmZmZmZW5VzBY2ZmZmZmZmZW5VzBY2ZmZmZmZmZW5TwGj5mZmZmZmVmRXPrqW3mVO2fYoCJHYrXOLXjMzMzMzMzMzKqcK3jMzMzMzMzMzKqcK3jMzMzMzMzMzKqcx+AxMzMzMzMzKzOP1WNd5QqeLKtXr6axsZGVK1eWO5Si6tOnD0OGDKFnz57lDsXMzMzMzMzMusgVPFkaGxvZdNNNGTp0KJLKHU5RRASLFi2isbGRYcOGlTscs6KTNAb4JdADuCYiLs5a3xu4AdgLWAQcFxELJA0EbgP2Bq6LiImljdzMzMzMKlW+LW7MSsVj8GRZuXIlAwcOrNnKHQBJDBw4sOZbKZkBSOoBXAkcAYwEjpc0MqvYKcDiiBgO/AK4JF2+EvgBcHaJwjUzMzPbgKQxkl6SNF/SpBzrvy1prqTZkv4qabtyxGlm5eUKnhxquXKnWXd4j2apfYD5EfFKRHwETAPGZZUZB1yfPr8NOESSImJ5RPwvSUWPmZmZWcnlebPqWWB0ROxGci7zs9JGaWaVwBU8ZlbrBgNvZLxuTJflLBMRTcBSYGC+B5A0QVKDpIampqYuhmtmZma2nnZvVkXEQxGxIn35JDCkxDGaWQXwGDztKHS/yvZGPF+yZAk333wzp512Wof2e+SRR3LzzTfTv3//LkRnZp0REVOAKQB9+/aNModjZmZmtSXXzap92yh/CnB3rhWSJgATAHr16lWo+MysQrgFT4VZsmQJV1111QbL22sVMH36dFfumOW2ENgm4/WQdFnOMpLqgM1JBls2MzMzqxqSvgyMBi7NtT4ipkTE6IgYXVfne/1mtcYVPBVm0qRJvPzyy4waNYq9996bAw44gLFjxzJyZNLN9uijj2avvfZi5513ZsqUKS3bDR06lHfffZcFCxaw0047ceqpp7Lzzjtz2GGH8eGHH5br7ZhVghnACEnDJPUCxgP1WWXqgZPS58cAD0aEW+KYmZlZJcjnZhWSPgt8DxgbEatKFJuZVZCiVtt2dmridN15JM0L1wBnRsS9krZJy28FBDAlIn6Zlr8AOBX4Z7r7/4qI6cV8f8Vw8cUX8/zzzzNz5kwefvhhPve5z/H888+3TGc+depUPvaxj/Hhhx+y995788UvfpGBA9cfKmTevHnccsst/Pa3v+VLX/oSt99+O1/+8pfL8XbMyi4imiRNBO4lyUVTI2KOpAuBhoioB64FbpQ0H3iPpBIIAEkLgM2AXpKOBg6LiLklfhtmZlZh8u3G3173fLM8tNysIqnYGQ+ckFlA0h7Ab4AxEfFO6UM0s0pQtAqejNHeDyXpJzpDUn3WhVHL1MSSxpNMTXxcOir8eGBnYGvgAUmfAJqA70TEM5I2BZ6WdH/GPn8RET8v1nsqh3322aelcgfgiiuu4I477gDgjTfeYN68eRtU8AwbNoxRo0YBsNdee7FgwYJShWtWkdLK3ulZy87PeL4SOLaVbYcWNTgzMzOzNuR5s+pSoB/wh3S23NcjYmzZgjazsihmC56W0d4BJDWP9p5ZwTMOuCB9fhswWUlGGgdMS5sWvpreVd8nIp4A3gKIiA8kvUAy6FjN3k3v27dvy/OHH36YBx54gCeeeIJNNtmEgw46iJUrN5y9uXfv3i3Pe/To4S5aZmZmZmZVLI+bVZ8teVBWNm5BaK0p5hg8XZmauN1tJQ0F9gD+nrF4oqTZkqZKGlCA91Bym266KR988EHOdUuXLmXAgAFssskmvPjiizz55JMljs7MzMzMzMzMKlFVDp0uqR9wO/CtiHg/Xfxr4MckY/P8GPhv4Ks5tu3Q1IClrvUcOHAg+++/P7vssgsbb7wxW221Vcu6MWPGcPXVV7PTTjux4447st9++5U0NjMzMzMzs1r3+JLcN9zNKl0xK3g6MjVxY9bUxK1uK6knSeXO7yLij80FIuLt5ueSfgv8OVdQETEFmALQt2/fipwl5+abb865vHfv3tx999051zWPs7PFFlvw/PPPtyw/++yzCx6fmZmZmZmZmVWWYnbR6srUxPXAeEm909HiRwBPpePzXAu8EBGXZe5IUmZTmy8Az2NmZmZmZmZm1g0UrYInHVOnebT3F4Bbm0d7l9Q8ovu1wMB0EOVvA5PSbecAt5IMnnwPcHpErAH2B74CfEbSzPRxZLqvn0l6TtJs4GDg/xXrvZlZx6VjY70jyZWvVlXWrF5b7hCsDc4tZlZozitmVmilyitFHYOni1MTXwRclLXsfwG1Uv4rXY3XzIrqOmAycEOZ4zDLy6KFy7hr8iyWL1lFv/69OeqM3Rm4db9yh2Ubug7nFjMrrOtwXjGzwrqOEuSVYnbRMjNrERGPAu+VOw6zfN01eRbLF6+CgGWLV/HnX80qd0iWg3OLmRWa84qZFVqp8kpVzqJlZhWpTlJDxusp6aDmZlVnzeq1LF+yar1ly5asYs3qtfTo6XsjJebcYmaF5rxiZoVWEXnFFTxmVihNETG63EGYFUKPnhvRr39vli1eV8nTr39vV+6Uh3OLmRWa84qZFVpF5BVX8LTjn7+aXND9bXnGxDbXL1myhJtvvpnTTjutw/u+/PLLmTBhAptssklnwzMzs9RRZ+zOn381i2UZY/CYmZmZmVUq34qsMEuWLOGqq67q1LaXX345K1asKHBEZmbd08Ct+3HST/fnG1ccxEk/3d8DLJuZmZlZRXMFT4WZNGkSL7/8MqNGjeKcc87h0ksvZe+992a33Xbjhz/8IQDLly/nc5/7HLvvvju77LILv//977niiit48803Ofjggzn44IPL/C7MNiTpFuAJYEdJjZJOKXdMZvlwt6zK5txiZoXmvGJmhVaqvOIuWhXm4osv5vnnn2fmzJncd9993HbbbTz11FNEBGPHjuXRRx/ln//8J1tvvTV/+ctfAFi6dCmbb745l112GQ899BBbbLFFmd+FFcOlr76VV7lPFDmOzoqI48sdg5nVHucWMys05xWrFfleP5wzbFCRI7FS5RVX8FSw++67j/vuu4899tgDgGXLljFv3jwOOOAAvvOd7/Dd736Xo446igMOOKDMkZqZmZmZmVWufCs7oHJvmJq1xxU8FSwiOO+88/j617++wbpnnnmG6dOn8/3vf59DDjmE888/vwwRmpmZmZmZmVkl8MACFWbTTTflgw8+AODwww9n6tSpLFu2DICFCxfyzjvv8Oabb7LJJpvw5S9/mXPOOYdnnnlmg23NzMzMzMzMrPtwC552tDeteaENHDiQ/fffn1122YUjjjiCE044gU996lMA9OvXj5tuuon58+dzzjnnsNFGG9GzZ09+/etfAzBhwgTGjBnD1ltvzUMPPVTSuM3MzMxsQx4Dw8zMSsUVPBXo5ptvXu/1WWedtd7rHXbYgcMPP3yD7c444wzOOOOMosZmZmZmZmZmZpXHFTxmZmZm1iXVPtOjmZlZLXAFj5mZmVkNcFcgMzOz7s0VPDlEBJLKHUZRRUS5QzCzAvKFnZmZmXVHHZn+3HLryO/Q55KVzbNoZenTpw+LFi2q6QqQiGDRokX06dOn3KGYmZmZmZmZWQG4BU+WIUOG0NjYyD//+c9yh1JUffr0YciQIeUOw8zMzMxwS0wzM+s6V/Bk6dmzJ8OGDSt3GNaNuFmpmZmZ5csVQWZm1pqiVvBIGgP8EugBXBMRF2et7w3cAOwFLAKOi4gF6brzgFOANcCZEXFvW/uUNAyYBgwEnga+EhEfFfP9mVl1KEYuqlbuY21WGM4rZlZKXck5ZoXkSubKVrQKHkk9gCuBQ4FGYIak+oiYm1HsFGBxRAyXNB64BDhO0khgPLAzsDXwgKTmmTVb2+clwC8iYpqkq9N9/7pY78/MqkMxclFErCntuzCzSuK8Ymal1JWcU/poC8et3KubK4LKo5gtePYB5kfEKwCSpgHjgMxENA64IH1+GzBZyfRV44BpEbEKeFXS/HR/5NqnpBeAzwAnpGWuT/frCh7LW6GTkL+UKkYxctETJYq9rPzFbNaqbpNX/F1WvZzDa0qnc05U4MwxziuWybmqsIpZwTMYeCPjdSOwb2tlIqJJ0lKSLlaDgSezth2cPs+1z4HAkohoylF+PZImABPSlyHpwxzF6oCmHMtLyTGU//g5Yzi3zMcvgzrO/698Yti46JF0TrFyUYs880qmwv9dz/+vgu4uQ7uxlvgz0ZZK+Lzky7HmrxJzS9HzChQvt5TgM9v1/5mu57TOx1C4fFruz06zNuMoUQ6vtN9FJeaVtnQl57ybWagTeaWrKuVv36yw8XQtX1TS76biYynT+WZHfi8VkVe63SDLETEFmNJWGUkNETG6RCE5hgo9fiXEUO7jV0oMlS6fvJKpmn6njrU4HKvlo1pzSyXE4RgqK45KiKGS4iinjuaVrqq033klxeNYcnMsXbNREfe9ENgm4/WQdFnOMpLqgM1JBgVrbdvWli8C+qf7aO1YZtY9FSMXmVn35rxiZqXUlZxjZt1IMSt4ZgAjJA2T1ItkQMH6rDL1wEnp82OAB9N+ovXAeEm909mxRgBPtbbPdJuH0n2Q7vPOIr43M6sexchFZta9Oa+YWSl1JeeYWTdStC5aad/PicC9JNP5TY2IOZIuBBoioh64FrgxHWDwPZJkRVruVpKBw5qA05tnl8i1z/SQ3wWmSfoJ8Gy6784qWbPFNjiG8h8fyh9DuY8PlRFDpxUrF3VRNf1OHWtxONYqVqF5BSrnb1UJcTiGdSohjkqIASonjg7pSs6pAJX2O6+keBxLbo6lC+SKXTMzMzMzMzOz6lbMLlpmZmZmZmZmZlYCruAxMzMzMzMzM6ty3b6CR9IFkhZKmpk+jsxYd56k+ZJeknR4xvIx6bL5kiYVMJbvSApJW6SvJemK9DizJe2ZUfYkSfPSx0mt7zWv4/443f9MSfdJ2rqUx0/3d6mkF9Pj3CGpf8a6ov8dJB0raY6ktZJGZ60r6f9BqfafcZypkt6R9HzGso9Juj/9+94vaUC6vNX/CWtfqf6mnSVpgaTn0lzQkC7L+b9Qpviq5n+1lVg7/H1Toli3kfSQpLlpHjwrXV6Rv1vLrRLyS64cUqLj5p0bShxDq5/5IsXQoc9yGeIo2e9DUh9JT0malcbwo3T5MEl/Tz8nv1cyYLF1UWt/86wyB0lamvH3P7+I8bSZi0r5PSZpx4z3PFPS+5K+lVWmaL+bruRHFf56L1csrV4DZm1b0O+XruTsSvi+bVNEdOsHcAFwdo7lI4FZQG9gGPAyyaBmPdLn2wO90jIjCxDHNiQDp70GbJEuOxK4GxCwH/D3dPnHgFfSnwPS5wO6cOzNMp6fCVxdyuOn+zwMqEufXwJcUsq/A7ATsCPwMDC6XP8HGcct6v6zjnUgsCfwfMaynwGT0ueTMv4eOf8n/Kisv2kXYlzQnH/a+18oU3xV87/aSqwX0IHvmxLGOgjYM32+KfCPNKaK/N36kfNvWBH5JVcOKdFx884NJY4h52e+iDF06LNchjhK9vtI81O/9HlP4O9pvroVGJ8uvxr4Zqn+PrX8aO1vnlXmIODPJYqnzVxUru+xNFf/H7BdqX43nc2PFOd6L1csOa8BO/o3LVAs7eYoKuT7tq1Ht2/B04ZxwLSIWBURrwLzgX3Sx/yIeCUiPgKmpWW76hfAuUDmqNfjgBsi8STQX9Ig4HDg/oh4LyIWA/cDYzp74Ih4P+Nl34wYSnL8NIb7IqIpffkkMCQjhqL/HSLihYh4KceqUv8fNCv2/ltExKMksy1kGgdcnz6/Hjg6Y3mu/wlrX8n+pgXW2v9CyVXT/2orsbamtTxTEhHxVkQ8kz7/AHgBGEyF/m4tp2rNLwXRwdxQyhhKqhOf5VLHUTJpflqWvuyZPgL4DHBburys32m1pBL+5h1Uru+xQ4CXI+K1EhwL6FJ+LMb13gaxtHENWFRdyNkV/33rCp7ExLRZ2NSMJmqDgTcyyjSmy1pb3mmSxgELI2JW1qpSxnCRpDeA/wCamwWW7PhZvkpSq17OGJqV6/ilen+t2Soi3kqf/x+wVYXEVc2q4XcXwH2SnpY0IV3W2v9Cpai2/9WOfN+UnKShwB4kd7ur7XfbnVXK3yRXDimXSslduT7zRZfnZ7nUcUAJfx+SekiaCbxDcnH6MrAk42LSuasIcvzNM30q7TZ3t6SdixhGe7moXDlzPHBLK+tK9buB/HJCOX5HmdeA2Ur1/dJejqqU79tWdYsKHkkPSHo+x2Mc8GtgB2AU8Bbw32WI4b9YV6lSFO0cn4j4XkRsA/wOmFiOGNIy3wOa0jhKfnzbUEQE67css9r16YjYEzgCOF3SgZkrK/1/odLjo0TfN50lqR9wO/CtrJad1fC7tcrQZg4plzL+/5blM18pn+UccZT09xERayJiFEmLgH2ATxbzeNb2/x7wDEnXpN2BXwF/KmIoFZeLlIz3NBb4Q47VpfzdrKdSvt/zuAYsxd+0os/T8lVX7gBKISI+m085Sb8F/py+XEgyLk6zIeky2lje4Rgk7Uoy5sIsSc37e0bSPm3EsJCkr2bm8oc7c/wcfgdMB35YyOPnE4Okk4GjgEPSZEMbMdDG8k4dvxUF/T8o0HFL4W1JgyLirbTJ6jsVElc1q/jfXUQsTH++I+kOkhPi1v4XKkXV/K9GxNvNzzvwfVMSknqSnJT/LiL+mC6umt+tVcbfpJUc8mip40iVPXe18Zkvmg5+lksaRzl+H+lxl0h6CPgUSVecurQVj3NXAbXyv9cis8InIqZLukrSFhHxbqFjySMXlSNnHgE8k/k5aFbK300qn5zQqeu9zmjlGnA9pfh+yTNHVcT3bVu6RQuetmT1t/wC0DySdj0wXlJvScOAEcBTwAxghJJR+HuRNLWr7+zxI+K5iPh4RAyNiKEkzbz2jIj/S/d7ohL7AUvT5nT3AodJGpA2HTssXdYpkkZkvBwHvJg+L8nx0xjGkIxBNDYiVmSsKsnfoQ3lOn6p3l9r6oGT0ucnAXdmLM/1P2HtK/fftE2S+kratPk5yef6eVr/X6gUVfO/2onvm1LFJeBa4IWIuCxjVdX8bq38+aWNHFIuZc9dbXzmi3W8jn6WSxpHKX8fkrZUOhuPpI2BQ0nGhXkIOCYtVonfaVWpjf+9zDL/kpYjvZG9EbCoCLHkk4vK8T12PK10zyrV7yZDPjmh4Nd7ubRxDZhZpiTfL3nmqLJ/37YrKmCk53I+gBuB54DZJH+cQRnrvkfSX/cl4IiM5UeSjA7/MvC9AsezgHWzaAm4Mj3Oc6w/u9NXSQbinA/8ZxePeTvJP/Bs4C5gcCmPn+5vPkl/xpnp4+pS/h1IPsSNwCrgbeDecv4flGL/Gce5haQZ4ur0d3AKMBD4KzAPeAD4WHv/E35Uzt+0k7FtTzITwCxgTnN8rf0vlCnGqvlfbSXWDn/flCjWT5M0z56dkYOPrNTfrR+t/h3Lml9ayyElOnbeuaHEMbT6mS9SDB36LJchjpL9PoDdgGfTYz0PnJ/xf/oUyXnnH4Depfo/reVHG3/zbwDfSMtMTHPDLJLBdP+1SLG0dj6TGUtJv8dIJrFZBGyesawkv5uO5EdgNHBNxraFvt7LFUvOa0Bga2B6W3/TIsSSM0dlxpK+rtjz+YhAaZBmZmZmZmZmZlalun0XLTMzMzMzMzOzaucKHjMzMzMzMzOzKucKHjMzMzMzMzOzKucKHjMzMzMzMzOzKucKHjMzMzMzMzOzKucKHjMzMzMzMzOzKucKnhon6UxJL0haKGlyAff7sKTRhdpfB499naRj0ufXSBpZjjjMuptKyCeSTs51bEnfkHRioWJK93mhpM/mWH6QpD8X8ljtxFHS45lZYXTmHEXSsmLFY2Ztk3SBpLPLHUezzHOeQp/nSNpa0m2djccqV125A7CiOw34bPooS4VMJkl1EdFUqP1FxNcKtS8za1dF5ZNMEXF1EfZ5fqH32UySAEXE2mIdw8zKy+coZlYohT7PiYg3gWMKuU+rDG7BU8MkXQ1sD9wNDMhYvqWk2yXNSB/7p8v/TdLM9PGspE3T5d+V9JykWZIuzjjEsZKekvQPSQe0EcfJkuolPQj8VVJfSVPTbZ+VNC4tN1TS3yQ9kz7+NV0uSZMlvSTpAeDjGftuufMvaZmki9I4n5S0Vbp8h/T1c5J+0t7dMUnnpL+X2ZJ+lLH8T5KeljRH0oR0WY+0RdHz6f7/X8Yx70nL/03SJ9v/i5lVrkrJJ1kxfU7SE5K2yLzrluaFS7L3l35ef55+XmdLOiNdfn4a+/OSpqSVL9mtBcdIelHSM8C/txPXlpLuT3PFNZJeS2McmuaxG4DngW0k/VpSQ1o2M9/kPF5r+dPMNpR+Xv6S5pvnJR0naYGkn6a5qUHSnpLulfSypG+k20nSpRnf7celyzeSdFX62bxf0vTmHNHK8fM5RxmW5rHnJP0ka/sNzkckfUHSX9MYB6U57l+K9Ts0qwWSTkw/R7Mk3Zh+Hz+YLvurpG1zbJPzXD49N/h1+jl+RUkr26lKWjhfl7F9a9/vCyT9SMm1znPK8xpB65/nnJrmhllKzsE2yYjtmIxtWr3mSX8Hz6fPT5b0x/T9zpP0s4xy/5nmmaeA/TOWt3b+d6fSlkaSvi7pd/m8PyugiPCjhh/AAmAL4GRgcrrsZuDT6fNtgRfS53cB+6fP+5G08DoCeBzYJF3+sfTnw8B/p8+PBB5oI4aTgcaMbf8/4Mvp8/7AP4C+wCZAn3T5CKAhff7vwP1AD2BrYAlwTEYco9PnAXw+ff4z4Pvp8z8Dx6fPvwEsayPWw4ApgEgqQP8MHJj13jcmuTgbCOwF3J+xff/051+BEenzfYEHy/2/4IcfXX1UUD6ZDHwB+BswIF1+AXB2W/sDvgncBtRlHf9jGfu/MSOPXEdyd6sP8EaalwTcCvy5jRgnA+elz8ekuWkLYCiwFtgvo2xzDD3SuHdr63i0kj/L/b/hhx+V+AC+CPw24/XmaR77Zvr6F8BsYFNgS+DtjO2azzu2Al4HBqX5YDrJ+cG/AItJz0daOf7DtH+OUg+cmD4/nfQchbbPR24CJpJxfuOHH37kfgA7p9+VW6SvP0ZyjnJS+vqrwJ/S5xew7lwi57l8em4wLf1sjgPeB3ZNP6dPA6Oaj5P+bPl+T18vAM5In58GXNNG7Cez7nwrM7aBGWV+krG/6zJzEm1f8wwFns84zitpjuwDvAZsk+a919P82At4jPbP/7YC5gMHpL/3j7UWgx/FebiLVvf0WWCkkpvUAJtJ6kfyob0srWn9Y0Q0Khl/4n8iYgVARLyXsZ8/pj+fJkkSbbk/Y9vDgLFa18e1D0lieBOYLGkUsAb4RLr+QOCWiFgDvKmkJVAuH5Gc7DTHdGj6/FPA0enzm4GftxHnYenj2fR1P5KLrEeBMyV9IV2+Tbr8JWB7Sb8C/gLcl/4u/xX4Q8bvuHcbxzSrZuXIJ58h6SJ2WES830qZXPv7LHB1pN1EM45/sKRzSSqZPwbMITn5a/ZJ4NWImAcg6SZgQhvxfZqkAoqIuEfS4ox1r0XEkxmvv6SkRWAdyYnUSJKTxNaO11r+fKGNeMy6q+eA/5Z0CUkl6d/SXFWfsb5fRHwAfCBplaT+JJ/h5vOOtyU9AuydLv9DJF0r/0/SQx2IpbVzlP1JKpQgqWC+JH3e1vnIGSQ3mp6MiFs6EINZd/QZks/tu5B890v6FOtax95IUunaIo9z+bsiIiQ9R1Ix/Fy63RySc46Z5P5+n51un3mO0mar4Fbskrb460+SG+7txD6y/TUilgJImgtsR3Jz6uGI+Ge6/Pesuz7Lef4XEW9LOh94CPhC1rmelYAreLqnjUjuIK/MWn6xpL+Q3PF+TNLh7exnVfpzDe3/Ly3PeC7gixHxUmYBSRcAbwO7pzFmx9ee1RFJ1XGeMeUi4KcR8Zus2A4iSWSfiogVkh4maW20WNLuwOEkrYO+BHwLWBIRozpxfLNqU4588jJJd7FPAA1d2Z+kPsBVJHfZ30jzUJ92jt8VLblQ0jDgbGDvNJdcl8exc+ZPM9tQRPxD0p4keegnkv6armrOD2sznje/Lta5cVvnKJGjfM7zkdQQkli3krRReCwvs0LbiLbP5dvMIXl8v3fknCeX64CjI2KWpJOBg9LlTWnsSNqIpNVNvjLfRz5xtXb+B0mLpkUkPS+sxDwGT/d0H8ndHwDSFjNI2iEinouIS4AZJHet7wf+M6Nv58cKcPx7gTOklnEu9kiXbw68lZ6ofIWkSSMkd6uOUzJ+xiDg4A4e70nW3R0bn0dsX01r7pE0WNLH09gWp5U7nwT2S9dvAWwUEbcD3wf2TFsUvCrp2LSM0kogs1pUjnzyGsln+gZJO3dgu/uBr0uqyzh+8wnXu+nnPtd4Gi8CQyXtkL4+vp3jPEZS2Yukw8gYsyjLZiQVPkuVjMdxRB7Hay1/mlkWSVsDKyLiJuBSYM88N/0b6847tiRpSfwUyWf7i0rG4tmKdRdVXfEY685N/iNjec7zkTR/TSXJCy8A3y5ADGa17EGScf4GQst3/+Os/7n7W+YGBTiXb+37vVA2Bd6S1JP188YCkuEjAMYCPbt4nL8D/yZpYHqsYzPWtXb+tw/J+90DODut7LIScgVP93QmMFrJwGJzSVqeAHxL6eCjwGrg7oi4h6Qpc4OkmSS10V31Y5KEMzttyvjjdPlVwEmSZpFcDDbf6b4DmAfMBW4Anujg8b4FfDt9X8OBpa0VjIj7SLpxPZE2u7yNJIneQ1Ij/wJwMUmlEcBg4OH0d3MTcF66/D+AU9L3Moekj65ZLSpLPomIF0k+Z3/IqAhpzzUkfclnp5/NEyJiCfBbku4O95JURmUfayVJF6m/KBn0+J12jvMj4DAlgxceC/wf8EGO/c4i6X7xIkneeSyP47WWP81sQ7sCT6X55ockY1Xk4w6SrhSzSC4Oz42I/wNuJxlTcC7Jd/4ztHFOkaezgNPTc47BzQvbOB/5L+BvEfG/JJU7X5O0UxdjMKtZETEHuAh4JP3uv4ykYuI/03OUr5B8DrN1+ly+te/3AvoBSeXLY+kxmv2WpEJmFskQFctzbJu3iHiLZOyfJ9JjZXYH3+D8T1LvNIavRjJL13eAqc03paw0tK61qFltSlsLfJj2lR1PMiChK1zMrCjSE5w1EdGkpJ//r91l06w2pGNMLEtbAzxFMpj8/5U7LjMzM/AYPNY97EUyeLNIZuD6annDMbMaty1wa9r//SPg1DLHY2aF82clAzH3An7syh0zM6skbsFjBZMOonpJ1uJXI+ILucqXk6RdSUbNz7QqIvYtRzxmtr5qyCeS/pMNm3U/FhGnlyMeMysPSXcA2eNMfDciCjGzjZnVuGKeT/iap/txBY+ZmZmZmZmZWZXzIMtmZmZmZmZmZlXOFTxmZmZmZmZmZlXOFTxmZmZmZmZmZlXOFTxmZmZmZmZmZlXOFTxmZmZmZmZmZlXOFTxmZmZmZmZmZlXOFTxmZmZmZmZmZlXOFTxmZmZmZmZmZlXOFTxmZmZmZmZmZlXOFTxmZmZmHSRpjKSXJM2XNCnH+gMlPSOpSdIxGctHSXpC0hxJsyUdV9rIzczMrFYpIsodg5mZmVnVkNQD+AdwKNAIzACOj4i5GWWGApsBZwP1EXFbuvwTQETEPElbA08DO0XEkpK+CTMzM6s5deUOwMzMzKzK7APMj4hXACRNA8YBLRU8EbEgXbc2c8OI+EfG8zclvQNsCSwpetRmZmZW07p1Bc9GG20UG2+8cbnDMKsJK1asiIjo9t0+nVfMCqtCc8tg4I2M143Avh3diaR9gF7Ay62snwBMSF/utckmm3T0EGaWQ4XmlZLzOYtZ4VRKXunWFTwbb7wxy5cvL3cYZjVB0ofljqESOK+YFVat5hZJg4AbgZMiYm2uMhExBZgC0Ldv33BuMSuMWs0rHeVzFrPCqZS8UvYaJjMzM7MqsxDYJuP1kHRZXiRtBvwF+F5EPFng2MzMzKybcgWPmZmZWcfMAEZIGiapFzAeqM9nw7T8HcANzQMvm5mZmRWCK3jMrOa1N51xRrkvSgpJozOWnZdu95Kkw0sTsZlVsohoAiYC9wIvALdGxBxJF0oaCyBpb0mNwLHAbyTNSTf/EnAgcLKkmeljVOnfhZmZmdWabj1Neq7+7EOHDuW1114rU0TrbLfddixYsKDcYZjlTdKKiOhb7jiy5TOdcVpuU5IuE72AiRHRIGkkcAvJjDlbAw8An4iINa0dz3nFrLAqNbeUWiXlFucSq3bOK4lKyivZnGes2lRKXunWgyzn8tprr1EJlV6Syh2CWa1odzrj1I+BS4BzMpaNA6ZFxCrgVUnz0/090ZEAnFfMrBjKlVucS8xql89ZzKqbu2iZWa3LNZ3x4MwCkvYEtomIv3R023T7CZIaJDU0NTUVJmozMzMzM7MOcAseM+vWJG0EXAac3Nl9ZE9lXJjIzMzMzMzM8ucWPB0UEZx55pkMHz6c3XbbjWeeeWaDMitWrOBzn/scn/zkJ9l5552ZNGndmK6XXXYZI0eOZLfdduOQQw6piD6uZjWuvemMNwV2AR6WtADYD6hPB1ru0lTI+conrwB873vfY5tttqFfv37rLX/99dc5+OCD2WOPPdhtt92YPn16oUM0sypxzz33sOOOOzJ8+HAuvvjiDda3dx7y/vvvM2TIECZOnFiqkM2sSnT1Oujqq69m1113ZdSoUXz6059m7tzs3vJm1lWu4Omgu+++m3nz5jFv3jymTJnCN7/5zZzlzj77bF588UWeffZZHnvsMe6++24A9thjDxoaGpg9ezbHHHMM5557binDN+uO2pzOOCKWRsQWETE0IoYCTwJjI6IhLTdeUm9Jw4ARwFOFDjDfvPL5z3+ep57a8PA/+clP+NKXvsSzzz7LtGnTOO200wodoplVgTVr1nD66adz9913M3fuXG655ZYNLqDaOw/5wQ9+wIEHHljKsM2sSnT1OuiEE07gueeeY+bMmZx77rl8+9vfLmX4Zt2CK3g66M477+TEE09EEvvttx9LlizhrbfeWq/MJptswsEHHwxAr1692HPPPWlsbATg4IMPZpNNNgFgv/32a1luZsWRz3TGbWw7B7iVZEDme4DT25pBq7PyySuQ5IxBgwZtsFwS77//PgBLly5l6623LnSIZlYFnnrqKYYPH872229Pr169GD9+PHfeeed6Zdo6D3n66ad5++23Oeyww0oat5lVh65eB2222WYt5ZYvX+6BlM2KwBU8HbRw4UK22WZdj40hQ4awcGHrPTaWLFnCXXfdxSGHHLLBumuvvZYjjjiiKHGa2ToRMT0iPhERO0TERemy8yOiPkfZg9LWO82vL0q32zEi7i5GfB3NK9kuuOACbrrpJoYMGcKRRx7Jr371q2KEaWYVrqO5JPM8ZO3atXznO9/h5z//edHjNLPqVIjroCuvvJIddtiBc889lyuuuKKo8Zp1R67gKaKmpiaOP/54zjzzTLbffvv11t100000NDRwzjnntLK1mVl+brnlFk4++WQaGxuZPn06X/nKV1i7dm25wzKzCpZ9HnLVVVdx5JFHMmTIkDJHZma1oLXroNNPP52XX36ZSy65hJ/85CdljNCsNnkWrTxceeWV/Pa3vwVg77335o031s2a3NjYyODBG8yaDMCECRMYMWIE3/rWt9Zb/sADD3DRRRfxyCOP0Lt376LFbWaVq7N5JZdrr72We+65B4BPfepTrFy5knfffZePf/zjhQ3azCra4MGD88oluc5DnnjiCf72t79x1VVXsWzZMj766CP69euXc6BmM+s+Cn0d1Gz8+PGtjuFjZp3nFjx5OP3005k5cyYzZ87k6KOP5oYbbiAiePLJJ9l8881zjonx/e9/n6VLl3L55Zevt/zZZ5/l61//OvX19b74MuvGOpNXWrPtttvy17/+FYAXXniBlStXsuWWWxYrdDOrUHvvvTfz5s3j1Vdf5aOPPmLatGmMHbv+UGOtnYf87ne/4/XXX2fBggX8/Oc/58QTT3TljpkV9Dpo3rx5Lc//8pe/MGLEiGKHb9btuAVPBx155JFMnz6d4cOHs8kmm/A///M/LetGjRrFzJkzaWxs5KKLLuKTn/wke+65JwATJ07ka1/7Gueccw7Lli3j2GOPBZILs/r6DYYBMatJ6TTkHwBrgKaIGF3eiCpDPnkF4Nxzz+Xmm29mxYoVDBkyhK997WtccMEF/Pd//zennnoqv/jFL5DEdddd54ELrdtwXlmnrq6OyZMnc/jhh7NmzRq++tWvsvPOO3P++eczevRoxo4d6/MQszw5t2yoq9dBkydP5oEHHqBnz54MGDCA66+/vlxvxawsSpFXFBGF3mfV6Nu3byxfvny9ZZKohN9JpcRhli9JKyKibztlFgCjI+Ld0kRVes4rZoXVXm7pDnkFKiu3OJd0D2tWr6VHz9ps7O9zlkQl5ZVslRKHWb4qJa+4BY+ZmZmZmQGwaOEy7po8i+VLVtGvf2+OOmN3Bm7dr9xhmZlZHmqzWt7MKlUA90l6WtKEcgdjZjXBecWsgO6aPIvli1dBwLLFq/jzr2aVO6RyKVpukTRG0kuS5kualGP9tyXNlTRb0l8lbZex7iRJ89LHSRnL95L0XLrPK+S+2maVqOjnLG7BY2aFUiepIeP1lIiYklXm0xGxUNLHgfslvRgRj5YwRjOrPu3lFucVswJZs3oty5esWm/ZsiWrarG7VtnOWST1AK4EDgUagRmS6iNibkaxZ0m6cayQ9E3gZ8Bxkj4G/BAYTXKh+HS67WLg18CpwN+B6cAY4O6uxmtmeauIayFX8JhZobQ7UFhELEx/viPpDmAfwBdiZtaWNnOL84pZ4fTouRH9+vdm2eJ1lTz9+veutcodKO85yz7A/Ih4BUDSNGAc0FLBExEPZZR/Evhy+vxw4P6IeC/d9n5gjKSHgc0i4sl0+Q3A0biCx6yUKuJaqOaytZlVJkl9JW3a/Bw4DHi+vFGZWTVzXjErvKPO2J1+A3qDoN+AZAye7qbIuWUw8EbG68Z0WWtOYV1FTWvbDk6ft7tPSRMkNUhqaGpq6mDoZtZZpTpncQueLNttt11FTC+83XbbtV/IrLpsBdyRfr7qgJsj4p7yhlQalZJXttlyy3KHYFZo3TavQPlyi89RatvArftx0k/3r8VuWR1REblF0pdJumP9W6H2mXYZmQLJLFrZ6yvlnMV5xmpQSfKKK3iyLFiwYINl//zV5Ly23fKMiQWOxqx2pE2Ru99tQHLnlULLN0+Z1ZLunFeg87mlI/nC5zbdVzeu3Cl2blkIbJPxeki6bD2SPgt8D/i3iFiVse1BWds+nC4f0t4+89GVcxZfM5m1rlTnLN03c5uZmZmZmZXWDGCEpGGSegHjgfrMApL2AH4DjI2IdzJW3QscJmmApAEkXTzujYi3gPcl7ZfOnnUicGcp3oyZVRa34DEzMzMzMyuBiGiSNJGksqYHMDUi5ki6EGiIiHrgUqAf8Ie0O8frETE2It6T9GOSSiKAC5sHXAZOA64DNiYZs8cDLJt1Q67gMTMzMzMzK5GImE4ylXnmsvMznn+2jW2nAlNzLG8AdilgmGZWhdxFy8zMzMzMzMysyrmCx8zMzMzMzMysylVcBY+kMZJekjRf0qQc63tL+n26/u+Shmas203SE5LmSHpOUp+SBm9mZmZmZmZmVgYVVcEjqQdwJXAEMBI4XtLIrGKnAIsjYjjwC+CSdNs64CbgGxGxM8kUgqtLFLqZmZmZmZmZWdlUVAUPsA8wPyJeiYiPgGnAuKwy44Dr0+e3AYek0wEeBsyOiFkAEbEoItaUKG4zMzMzMzMzs7KptAqewcAbGa8b02U5y0REE7AUGAh8AghJ90p6RtK5uQ4gaYKkBkkNTU1NBX8DZlZ58uj6+Y20W+dMSf/b3HJQ0lBJH6bLZ0q6uvTRm5mZmZmZta+WpkmvAz4N7A2sAP4q6emI+GtmoYiYAkwB6Nu3b5Q8SjMrqYyun4eSVBrPkFQfEXMzit0cEVen5ccClwFj0nUvR8SoEoZsZmZmZmbWYZXWgmchsE3G6yHpspxl0nF3NgcWkVy4PRoR70bECmA6sGfRIzazStdu18+IeD/jZV/Alb9mZmZmZlZVKq2CZwYwQtIwSb2A8UB9Vpl64KT0+THAgxERwL3ArpI2SSt+/g2Yi5l1d/l0/UTS6ZJeBn4GnJmxapikZyU9IumAXAdw108zMzMzMyu3iqrgScfUmUhSWfMCcGtEzJF0YdptAuBaYKCk+cC3gUnptotJulXMAGYCz0TEX0r8FsysSkXElRGxA/Bd4Pvp4reAbSNiD5J8c7OkzXJsOyUiRkfE6Lq6Wur5amatyWNsrwPTMQGbJB2Tte4kSfPSx0nZ25qZmZl1RsVdiUTEdJLuVZnLzs94vhI4tpVtbyKZKt3MrFk+XT8zTQN+DRARq4BV6fOn0xY+nwAaihOqmVWDPMf2eh04GTg7a9uPAT8ERpN0B3063XZxKWI3MzOz2lVRLXjMzIqg3a6fkkZkvPwcMC9dvmV6IYek7YERwCslidrMKlk+Y3stiIjZwNqsbQ8H7o+I99JKnftZN6i7mZmZWadVXAseM7NCiogmSc1dP3sAU5u7fgINEVEPTJT0WWA1sJh143wdCFwoaTXJRdo3IuK90r8LM6swucb22rcL224wLhgk43sBEwB69erV8SjNzMysW3EFj5nVvDy6fp7Vyna3A7cXN7rSuvTVt/Iue86wQUWMxMzaExFTgCkAffv29ex+ZmZm1iZ30TIzMzPrmI6O7VWobc26ZM3q7B6DZmZWS9yCx8zMzKxjWsb2IqmcGQ+ckOe29wL/n6QB6evDgPMKH6LZOosWLuOuybNYvmQV/fr35qgzdmfg1v3KHZaZmRWYW/CYmZmZdUBENAHNY3u9ANzaPLaXpLEAkvaW1Egy8+dvJM1Jt30P+DFJJdEM4EKP7WXFdtfkWSxfvAoCli1exZ9/NavcIZmZWRG4BY+ZmZlZB+UxttcMku5XubadCkwtaoBmqTWr17J8yar1li1bsoo1q9fSo6fv9ZqZ1RJndTMzMzOzGtWj50b06997vWX9+vd25U4ZSRoj6SVJ8yVNyrH+QEnPSGqSdEzG8oMlzcx4rJR0dLruOkmvZqwbVbp3ZGaVwpndzMzMzKyGHXXG7vQb0BsE/QYkY/BYeUjqAVwJHAGMBI6XNDKr2OvAycDNmQsj4qGIGBURo4DPACuA+zKKnNO8PiJmFucdmFklcxctMzMzM7MaNnDrfpz00/3dLasy7APMj4hXACRNA8YBc5sLRMSCdF1b054dA9wdESuKF6qZVRtneDMzMzOzbsCVOxVhMPBGxuvGdFlHjQduyVp2kaTZkn4hqXeujSRNkNQgqaGpqakThzWzSuYsb2ZmZmZmViUkDQJ2JZnJr9l5wCeBvYGPAd/NtW1ETImI0RExuq7OnTnMao0reMzMzMzMzEpjIbBNxush6bKO+BJwR0Ssbl4QEW9FYhXwPyRdwcysm3EFj5mZmZmZWWnMAEZIGiapF0lXq/oO7uN4srpnpa16kCTgaOD5rodqZtXGFTxmZmZmZmYlEBFNwESS7lUvALdGxBxJF0oaCyBpb0mNwLHAbyTNad5e0lCSFkCPZO36d5KeA54DtgB+UvQ3Y2YVxx0vzczMzMzMSiQipgPTs5adn/F8BknXrVzbLiDHoMwR8ZnCRmlm1cgteMzMzMzMzMzMqpwreMzMzMzMzMzMqpwreMzMzMzMzMzMqpwreMzMzMzMzMzMqpwHWc7D40s+yKvcuCLHYWZmZmZmZmaWi1vwmJmZmZmZmZlVOVfwmJmZmZmZmZlVOVfwmFnNkzRG0kuS5kualGP9NyQ9J2mmpP+VNDJj3Xnpdi9JOry0kZuZmZmZmeXHFTxmVtMk9QCuBI4ARgLHZ1bgpG6OiF0jYhTwM+CydNuRwHhgZ2AMcFW6PzMzMzMzs4pScRU8edxp7y3p9+n6v0sami4fKunD9A78TElXlzx4M6tE+wDzI+KViPgImEbWmOgR8X7Gy75ApM/HAdMiYlVEvArMT/dnZmZmZmZWUSpqFq2MO+2HAo3ADEn1ETE3o9gpwOKIGC5pPHAJcFy67uX0DryZWbPBwBsZrxuBfbMLSTod+DbQC/hMxrZPZm07OMe2E4AJAL169SpI0GZmZmZmZh1RaS142r3Tnr6+Pn1+G3CIJJUwRjPrAkk9JD0r6c/ljiVTRFwZETsA3wW+38Ftp0TE6IgYXVdXUfXmZt1CpeYVM6tezitmVgzFzi2VVsGT60579t3yljIR0QQsBQam64alv6xHJB1Q7GDNrFPOAl4o4fEWAttkvB6SLmvNNODoTm5rZuVR6rxiZrXPecXMiqGouaXSKni64i1g24jYg6Sbxc2SNssuJGmCpAZJDU1NTSUP0qw7kzQE+BxwTQkPOwMYIWmYpF4kgybXZ8U1IuPl54B56fN6YHw69tcwYATwVAliNrM8lSmvmFkNc14xs2IoRW6ptL4E+dwtby7TKKkO2BxYFBEBrAKIiKclvQx8AmjI3DgipgBTAPr27RuYWSldDpwLbFqqA0ZEk6SJwL1AD2BqRMyRdCHQEBH1wERJnwVWA4uBk9Jt50i6FZgLNAGnR8SaUsVuZnm5nBLnFTOreZfjvGJmhXc5Rc4tlVbB03KnnaQiZzxwQlaZepKLryeAY4AHIyIkbQm8FxFrJG1Pcqf9ldKFbtbt1UnKrFCdklaoAiDpKOCdtAL2oFIGFhHTgelZy87PeH5WG9teBFxUvOjMrB2t5pZy5hUzq2rOK2ZWaBVxLVRRFTx53mm/FrhR0nzgPZJKIIADgQslrQbWAt+IiPdK/y7Muq2miBjdxvr9gbGSjgT6AJtJuikivlya8MysSrWVW5xXzIA1q9fSo2ctjbxQdM4rZlZoFXEtVFEVPJDXnfaVwLE5trsduL3oAZpZp0TEecB5AGmt9dk+WTKzrnBese5u0cJl3DV5FsuXrKJf/94cdcbuDNy6X7nDqmrOK2ZWDKXKLa7qNzMzMzOrQndNnsXyxasgYNniVfz5V7PKHZLlQdIYSS9Jmi9pUo71B0p6RlKTpGOy1q2RNDN91GcsHybp7+k+f59OLGFm3YwreMys5CLi4Yg4qtxxmFntcF6x7mbN6rUsX7JqvWXLlqxizeq1ZYqo9hQjr0jqAVwJHAGMBI6XNDKr2OvAycDNOXbxYUSMSh9jM5ZfAvwiIoaTTBhxSiHjNrPCKeY5iyt4zMzMzMyqTI+eG9Gvf+/1lvXr39tj8VS+fYD5EfFKRHwETAPGZRaIiAURMZtkXNF2SRLwGeC2dNH1wNEFi9jMqoa/AczMzMzMqtBRZ+xOvwG9QdBvQDIGj1W8wcAbGa8b02X56iOpQdKTko5Olw0ElkREUyf3aWY1ouIGWTYzMzOrdJLGAL8kmfXzmoi4OGt9b+AGYC9gEXBcRCyQ1BO4BtiT5Dzshoj4aUmDt7Ir1KxXA7fux0k/3d+zaHUv20XEQknbAw9Keg5Ymu/GkiYAEwB69fIwPWa1xhU8ZmZmZh2QMYbGoSR3ymdIqo+IuRnFTgEWR8RwSeNJxsc4jmQm0N4RsaukTYC5km6JiAWlfRdWDsWa9cqVO1VlIbBNxush6bK8RMTC9Ocrkh4G9iCZSbi/pLq0FU+r+4yIKcAUgL59+0Zn3oCZVS5/G5iZmZl1TLtjaKSvr0+f3wYcko6TEUBfSXXAxsBHwPulCdvKzbNeGTADGJHOetULGA/Ut7MNAJIGpK0DkbQFsD8wNyICeAhonnHrJODOgkduZhXPFTxmZmZmHZPPGBotZdI76ktJxsm4DVgOvEUyU87PI+K9XAeRNCEda6OhqakpVxGrIp71yqAlH0wE7gVeAG6NiDmSLpQ0FkDS3pIaSVr8/UbSnHTznYAGSbNIKnQuzmg5+F3g25Lmk+Saa0v3rsysUriLlpmZmVnp7AOsAbYGBgB/k/RARLySXdBdKWpL86xXyxavq+TxrFfdU0RMB6ZnLTs/4/kMkm5W2ds9Duzayj5fIckvZtaN+RvFzMzMrGPyGUOjpUzaHWtzksGWTwDuiYjVEfEO8BgwuugRW0Xo6KxXbt1jZmYd4RY8ZmZmZh3TMoYGSUXOeJKKm0z1JONgPEEyLsaDERGSXgc+A9woqS+wH3B5qQK38sp31qtiDcZsZma1zS14zMzMzDognzE0SMa/GJiOh/FtYFK6/EqgXzqmxgzgfyJidmnfgZVbe92yPBizmZl1hlvwmJmZmXVQHmNorCQZIDV7u2W5llttaK9lTr77aG0wZo/XY2ZmbXEFj5mZmZlZFxSyS5UHYzYzs87yN4WZmZmZWRcUuktVRwdjNjMzA7fgMTMzMzPrtGJ0qcp3MGYzM7NM/sYwMzMzM+uk5i5VmQrVpcqVO2Zm1hH+1jAzMzMz6wJ3qTIzs0rgLlpmVvMkjQF+CfQAromIi7PWfxv4GtAE/BP4akS8lq5bAzyXFn09IsZiZmaWwV2qzMysEriCx8xqmqQewJXAoUAjMENSfUTMzSj2LDA6IlZI+ibwM+C4dN2HETGqlDGbmVl1cuWOmZmVk7+FzKzW7QPMj4hXIuIjYBowLrNARDwUESvSl08CQ0oco5mZmZmZGQCSNpa0Y0e3cwWPmdW6wcAbGa8b02WtOQW4O+N1H0kNkp6UdHSuDSRNSMs0NDU1dTlgMzMzMzPrniR9HpgJ3JO+HiWpPp9t3UXLzCwl6cvAaODfMhZvFxELJW0PPCjpuYh4OXO7iJgCTAHo27dvlCxgMzMzMzOrNReQ9EJ4GCAiZkoals+GbsFjZrVuIbBNxush6bL1SPos8D1gbESsal4eEQvTn6+QJNk9ihmsmZl1zZrVa6tin2ZmZq1YHRFLs5bldRPZLXjMrNbNAEaktd4LgfHACZkFJO0B/AYYExHvZCwfAKyIiFWStgD2JxmA2czMKsyihcu4a/Isli9ZRb/+yVTlA7fuV3H7NDMza8ccSScAPSSNAM4EHs9nQ7fgMbOaFhFNwETgXuAF4NaImCPpQknNU55fCvQD/iBpZkYf152ABkmzgIeAi7Nm3zIzswpx1+RZ/z97dx8nV13e///1JktCTIRAUH+QoAkmakEFJYAWpArlziLBb0GCVqJFU6ug1ooFb2JKtYq2ohK8SQEDKIKi1AWiiCDeIMQkkACBUsKNkEBFQgIETGCT6/fH+Wwymczuzu7OmXNm5v18POaxZ86cm2tmZ64555rP53N4Zs0GCFi3ZgNXn7uslNs0MzMbwGnA3sAG4FLgSeAj9axYuhY8ko4CvgaMAM6PiC9WPT4KuBjYD1gNnBgRD1Y8/lLgLmBORPxHs+I2s/KKiAXAgqp5syum/7qP9X4HvCbf6MzMbLg2Pr+JZ9Zu2GreurUb2Pj8piFfujyPbZqZmdXhbyLiU2TDRwAg6QTghwOtWKpvJ0kjgPOAo4G9gJMk7VW12CnAmoiYApwDnF31+FfY+go4ZmZmZtbGRmy/HWPHjdpq3thxo4ZViMljm2ZmZnU4s8552yjbN9QBwIqIuD8ingMuA6ZXLTMduChNXwEcJkkA6RLGDwDLmxOumZmZmZXBMaftw9idR4Fg7M7ZeDll3KaZpKMk3SNphaQzajx+iKRbJfVIOr5i/r6Sbpa0XNLtkk6seGy+pAdSV/OlkvZt0tMxswaRdLSkc4EJkr5ecZsP9NSzjbJ10ZoAPFxxfyVwYF/LRESPpCeB8ZLWA/8CHA58vK8dSJoFzAIYOXJk4yI3MzMzs8KM330sM79wUEO7UOWxTetsFT0WDic711kkqbtqjL+HgPew7TnNs8DJEXGvpN2BJZKujYi16fHTI+KKXJ+AmeXpEWAxcCywpGL+08A/1bOBshV4hmMOcE5ErEsNemqKiHnAPIAxY8bUdakxMzMzM2sNeRRiXNyxBtrcYwFAUm+Phc0Fnt7xRSVtqlwxIv63YvoRSY8BLwLW5h61meUuIpYByyRdGhHPD2UbZfu2WgXsUXF/YppXcxlJXcBOZIMtHwh8SdKDwEeBT0o6Ned4zczMzKwJNj6/aeCFrOn8fxm0Wj0WJgx2I5IOAEYC91XM/nzqunVOujBNrfVmSVosaXFPT109Psys+SZJukLSXZLu773Vs2LZWvAsAqZKmkxWyJkBvLNqmW5gJnAzcDxwQ0QE8KbeBSTNAdZFxNxmBG1mVkYbN4kR27mhopm1ttWr1mWXK1+7gbHjsnFwxu8+tuiwOp7/L8WRtBtwCTAzInorbGcC/0dW9JlHNnTFWdXrujeDWUv4DvBZsotKvQV4L3U2zilVC56I6AFOBa4F7gZ+EBHLJZ0l6di02AVkY+6sAD4GbDMwmZlZJ3ty/SiuumcqP7r7VVx1z1SeXF/zRzwzs1IYqAXIVXOX8cyaDRCwbs0Grj53WZMis/74/zJk9fRY6JOkHYFrgE9FxC298yPi0chsIDs5PKBB8Q7Lxk19D51hZn0aHRHXA4qIP0TEHOBv6lkxlxY8kg6KiJsGmldLRCwAFlTNm10xvR44YYBtzBlUwGZmbeTXf3gpf+7pAsSfe7r49R9eytteeW/RYZmZbaWeFiAbn9/EM2s3bDVv3doNDRn02AMnD12e/5cOUE+PhZokjQSuBC6uHkxZ0m4R8Wi6uvBxwJ0NjXqQnlw/avPxyOiuHg552UPstMOGgVc0M4ANkrYD7k3DzqwC6moimVcGPrfOeS0rwtVoMyufjZu0ubiTye77FzQzK5t6WoCM2H47xo7buhXi2HGjhlVEWL1qHfPPvIlvffhGLjrzJlY/sm7I2+pUefxfOkU9PRYk7S9pJdmP2t+WtDyt/g7gEOA9NS6H/j1JdwB3ALsCn2ves9pWrR+bzKxuHwFeAHwY2A94N3ByPSs2tAWPpDcCfwm8SNLHKh7aERjRyH0V5fnnR/P4469k46aRjNjuOXbd9R623/7PRYdlZgbAiO2C0V09FUWe7L7H4jGzMhlMC5BjTtuHq89dxrqKlj7DsbmwxJbC0swvHDSsbXaiRv9fOkkdPRYWkXXdql7vu8B3+9jmoQ0Os1/9tdbq78emvo5H3PrLbIuUAwDWAe+VNIKstd/CgdZtdBetkWRNh7qAF1bMf4psQOSW11vcAbFx00gef/yV7Lbb0qLDMjPb7JCXPbRNs2gzs2br74SttwXIujVbijx9tQAZv/tYZn7hoIZ1y3LXosZo5P/FWkc9XSsH82OTB+s22yKNsfUhsivrdQPXpfv/DNwOfG+gbTS0wBMRvwJ+JWl+RPyhkdsugwhtLu5ksvsRQvKv42ZWDjvtsIG3vfJeX0XLzApR7wnbYFuANKKIMJjCktXHr11nqbcFXL0/NrlFndlWLgHWkF0x/H3AJ8mKD2+PiKX1bCCvy6SPkjQPmFS5j2Y3HWw0KRix3XMVRZ7svos7ZlZGLu6YWRHqPWErqgWIuxaZDc1gWsDV82PTUFrUucWYtbk9I+I1AJLOBx4FXpouNFWXvAo8PwS+BZwPbMxpH4XYddd7thmDx8ys5fVsgi4fMJnZ8AzlhK3ZJ2vuWmQ2NENpAdffj02D2Z67clmHeL53IiI2Slo5mOIO5HcVrZ6I+GZE/D4ilvTectpXU22//Z/ZbbelTNh9EbvtttQDLJtZS9Of1rPDN+5l9FfuYYdv3Iv+5EuYmtnQtdLVlcoYk1nZHXPaPozdeRQIxu48/BZw9W6vnqvumbWBfSQ9lW5PA6/tnZb0VD0byKsFz1WSPghcCWw+W4iIJ3LaX9O5W5aZFaWRvzqP+uHD6OmebGSxp3sY9cOHWP/BqQ3Ztpm1p4FykLtAmbWvRreAq2d7nT44eqc8T4OIGPaVx/Mq8MxMf0+vmBfAnjntz8xKTtIOwK+BUWS554qI+GyxUbWWhjdP7tmE1vVUDBsPPN3j7lrWMpxXmqveHOQuUNbqnFsG1ujPdr/dvDp0cHR3S2svzcoruXwqImJyjZuLO2adbQNwaETsA+wLHCXpDcWG1Foa3jy5aztibBe97REDiBd2ubhjraSwvCLpKEn3SFoh6Ywaj4+SdHl6fKGkSRWPvVbSzZKWS7ojHfSV3mBzULuffFlb8zFLyTS6a1grcLe0ttOUvJJLCx5JJ9eaHxEX57E/Myu/iAhgXbq7fbq5r2Od8mqevOGElzLqhw/Buh5ibBcbTnjpcEM1a5qi8oqkEcB5wOHASmCRpO6IuKtisVOANRExRdIM4GzgREldwHeBd0fEMknjqRhUsaw6vYuEdRYfs5RPXi0Dy5rDnHPbT7PySl5dtPavmN4BOAy4FXCBx6yDpZOiJcAU4LyIWFhwSKUy0FVm8mieHC8alY25425Z1qIKyisHACsi4v4Uw2XAdKCywDMdmJOmrwDmShJwBHB7RCwDiIjVTYh32Dq1i4R1Lh+zlFOjck7Zuz8557anevOKpLMj4l8GmldLXl20Tqu4vR94PVCeT4yZ5aFL0uKK26zqBSJiY0TsC0wEDpD06mYEVkdXio9JukvS7ZKul/SyisdmSro33WZWr9sIq1etY/6ZN/GtD9/IRWfexOpH1tVcLtfmyS7uWHn1m1sKyisTgIcr7q9M82ouExE9wJPAeOAVQEi6VtKtkj7R104kzep93j09PQ19AkPRiV0krG2V9pjFmmMo3Z82Pr+pCZFt4ZzbchqZVw6vMe/ouoKoO9zheQaY3KR9mVkxeiJiWj0LRsRaSb8EjgLuzDOoOrtS3AZMi4hnJf0j8CWyrhS7AJ8FppE1oVyS1l3TyBg3H2Sw5SBj5hcO2mY5D1xqHaqu3NLMvDJMXcDBZK2dnwWul7QkIq6vXjAi5gHzAMaMGZN795CNm8SI7frejXOQtZFSHrNY4zTyqlxFtfZxzm05w84r6Tzkg8Cekm6vWOWFwE31bDuXd4qkqyR1p9s1wD1kl0w3sw4l6UWSxqXp0WQFl/9pwq43d6WIiOeA3q4Um0XELyPi2XT3FrKqOsCRwHUR8UQq6lxHlogbpr+DjL74S94sU2BeWQXsUXF/YppXc5k07s5OwGqyQvOvI+LxlHcWkLV0LsyT60dx1T1T+dHdr+Kqe6by5PpR/S7vHGTtrsDcYsNUT6vo3u5Plfrr/lT0YMfOue2hzrxyKfA2oDv97b3tFxF/V89+8nq3/Afwn+n278AhEbFNtwgz6yi7Ab9M1ehFZIWTq5uw33q6UlQ6BfjpYNYdTjeKwR5kmNlWisori4CpkiZLGgnMIDsYq9QN9HbrPB64IQ2weC3wGkkvSIWfv2LrsXua7td/eCl/7ukCxJ97uvj1HzzYunW8onKLDVO9xZh6uz8N5Yc4sz4MmFci4smIeDAiTiL7kejQiPgDsJ2kunpE5dJFKyJ+JeklbBls+d489mNmrSMibgdeV3Qc/ZH0d2Tdsf5qMOsNtxvFMaftw9XnLmNdRdNfMxtYUXklInoknUpWrBkBXBgRyyWdBSyOiG7gAuASSSuAJ8iKQETEGklfITu4C2BBRFzT7OfQa+MmbS7uZLL7A3XXMmtnrXDMYtsaTNerers/ebBja5TB5BVJvUNEvBL4DjCS7Aqc247hUCWvy6S/A/gycCPZEcO5kk6PiCvy2F+Zuc+kWeHq6UqBpL8GPgX8VURsqFj3zVXr3tiIoP507tyt7r91d9j4/2UnVJt+dBt/SvNfdNqpjdidmTVYRCwg615VOW92xfR64IQ+1v0u2YFa4UZsF4zu6qko8mT3Xdwxs7xUHwP1ZbDHQEMpxtRznuYf4qwAbycrBt0KEBGPSHphPSvmNcjyp4D9I+IxyPqbAb8gu0xoRyj7pffMOsjmrhRkBZsZwDsrF5D0OuDbwFG9eSu5Fvh3STun+0cAZ+YVqE+ozKzR6vmh6ZCXPbS5m9borh4OedlDTYrOzKyx8ijGeLBjK8BzERGSAkDSmHpXzKvAs13VSdJq8hvvp5TqvSqOmeWrzq4UXwbGAj+UBPBQRBwbEU9I+jeyIhHAWRHxRAFPw8xsUAbzQ9NOO2zgba+8192yzKzl5VmMcXHHmugHkr4NjJP0fuDvgf+qZ8W83qU/k3StpPdIeg9wDVXNmNuZB+MyK5eIWBARr4iIl0fE59O82am4Q0T8dUS8JCL2TbdjK9a9MCKmpNt3inoOZeE8ZtYahnLVFxd3zJpD0lGS7pG0QtI2F6KRdIikWyX1SDq+6rGZku5Nt5kV8/eTdEfa5teVfrHqVC7GWCuLiP8g6/30I7JxeGZHxLn1rNvQFjySpgAviYjTJf0/4OD00M3A9xq5rzLzYFxm1m7c7dSsdQxmoFEzay5JI4DzyC6RvBJYJKk7IiqvpvcQ8B7g41Xr7gL0Dr4awJK07hrgm8D7gYVkP6wfxZargppZi4mI64DrBrteo7/lvwo8lQL6cUR8LCI+BlyZHusY9V56z8ysFQylNYCZFaP3h6ZK/qHJrDQOAFZExP0R8RxwGTC9coF0meTbgepms0eSXVr5iVTUuQ44StJuwI4RcUtEBHAxcFzeT8SGx62irS+Snpb0VNXtYUlXStqzv3UbPQbPSyLijuqZEXGHpEkN3lepeTAuM2sXbg1g1np81Rez0poAPFxxfyVw4DDWnZBuK2vM34akWcAsgJEjR9a5W2skt4q2OnyV7HN8KdklLmcALye7qtaFbH2V3600usAzrp/HRjd4Xy3BJz9m1urc7dSs9fiHJjOrJSLmAfMAxowZ44G3CuCL8Vgdjo2Iyl9m5klaGhH/IumT/a3Y6G/8xWmU561Ieh+wpJ4N1DHo2ChJl6fHF/a2DJJ0gKSl6bZM0tuH+2TMzCzjbqdmrcnFHbPSWQXsUXF/Ypo3nHVXpemhbLNhfrf26bpu7a6/rle+GI/V6VlJ75C0Xbq9A1ifHuu3MNvoFjwfBa6U9C62FHSmASOBAQsudQ46dgqwJiKmSJoBnA2cCNwJTEuXRN4NWCbpqojoadBzy5V/YTOzMnNrADMzs4ZYBEyVNJmsCDMDeGed614L/LukndP9I4AzI+KJNEbHG8gGWT4ZqOuKO9Y49XS9cqtoq9O7gK8B3yAr6NwC/J2k0cCp/a3Y0HdSRPwxIv4S+FfgwXT714h4Y0T8Xx2bGHDQsXT/ojR9BXCYJEXEsxXFnB0YoLJVFqtXrWP+mTfxrQ/fyEVn3sTqR9YVHZKZWZ98AGJmZjZ06XzlVLJizd3ADyJiuaSzJB0LIGl/SSuBE4BvS1qe1n0C+DeyItEi4Kw0D+CDwPnACuA+fAWtpqv3ghRuFW39SY1ePhgRb4uIXSPiRWl6RUT8OSJ+29/6jW7BA0BE/BL45RBWrWfQsc3LpNY6TwLjgcclHUg26NDLgHfXar1TtoHF3AfTzMzMzKxzRMQCskuZV86bXTG9iK27XFUudyHZ+U71/MXAqxsbqdVrMBekcKto609EbJR08FDXz6XAU5SIWAjsLekvgIsk/TQi1lctU5qBxXxlGjNrlE7o025mZmZWRkPpeuXzPevHbZK6gR8Cz/TOjIgfD7Ri2d5V9Qw6tnkZSV3ATsDqygUi4m5gHSWvYvcmgkrug2lmZmZmZtZa3PXKGmgHshrHocDb0u2YelYsWwueegYd6wZmAjcDxwM3RESkdR5O3bZeBryKbAygUjvmtH24+txlrKsYjMvMrNW5JaKZmZl1Ene9skaJiPcOdd1SFXhScaZ30LERwIW9g44BiyOiG7gAuETSCuAJsiIQwMHAGZKeBzaRDUz0ePOfxeA4EZhZO6nnChJmZmZm7crndDZcknYgu3r43mSteQCIiL8faN1SFXigrkHH1pONKF+93iXAJbkHmJN6E4ELQWZWZh443szMzMxsWC4B/gc4EjiL7LLpd9ezYukKPFabfxW3ZnER0YbKA8e3D//PzMzMWksrfHeXPcai45PUla4EPiUiTpA0PSIuknQp8Jt6tuECT4vwr+KWNxcRbbiGcgUJKxfnATMzs9bSCt/dZY+xRPH9Hng98Hy6v1bSq4H/A15czwZ81N0C+vtV3KxRNhcRY0sR0WywfAWJ1uY8YGZm1lpa4bu77DGWML55knYGPk12kam7gLPrWdEteFqAfxW3vLlrjTWKB45vXc4DZmZmraUVvrvLHmPJ4nuxpI+l6d4raZ2X/o6pZwPFv6JWF/8qbnnqLSJWchHRhsPvndbjPGBmZtZaWuG7u+wxliy+EcBY4IUVt7EVtwG5BU+L8K/ilrdjTtuHq89dxrqKvqdm1lmcB8zMzFpLK3x3DzbGZp/zlug1fDQizhrOBlzgaTEu7lheXES0TuP3+racB8zMzFpLK3x31xtjUYMdl+g11HA3UM53gJkVpqxfDMMh6ShJ90haIemMGo8fIulWST2Sjq96bKOkpenW3byoLS+rV61j/pk38a0P38hFZ97E6kfWFR1S6bRjHjAzM2tnrfDdPVCMeQ12XO/FiUrwGh423A24BY8VpgQVUusAkkaQDU52OLASWCSpOyLuqljsIeA9wMdrbOLPEbFv3nFa82w+eGDLwcPMLxxUcFRmZmZmnWsogx2XtUXQUEXEE8Pdhgs81nSt9kGzlncAsCIi7geQdBkwnexygwBExIPpsfrK+9aySnalBDMzMzNjcFeOrvd8shN/1PPRrDVdXk3vzPowAXi44v7KNK9eO0haLOkWScfVWkDSrLTM4p6enmGEankr2ZUSzMzMzCyp98rR9ZxP9vejXjtzCx5rKv96bi3oZRGxStKewA2S7oiI+yoXiIh5wDyAMWPGRBFBWv1KdKUEMzMzM0vqGey43vPJwbQIaicu8FjdGlGE6dQPmhVqFbBHxf2JaV5dImJV+nu/pBuB1wH39buSlVqJrpRgZmZmZlX6Oz4bzPlkJ/6o5wKPDajRY+Z04gfNCrUImCppMllhZwbwznpWlLQz8GxEbJC0K3AQ8KXcIrWmcnHHzMyKIOko4GvACOD8iPhi1eOjgIuB/YDVwIkR8aCkdwGnVyz6WuD1EbE0/Qi1G/Dn9NgREfFYvs/ErBj1nk924o96LvDYgBo9OFUnftCsOBHRI+lU4FqyA6kLI2K5pLOAxRHRLWl/4EpgZ+Btkv41IvYG/gL4dhp8eTvgi1VX3zKzDjXUE7SKx19KNtj7nIj4j2bFbWbFqvPqnqcAayJiiqQZwNlkOeR7wPfSdl4D/HdELK1Y710RsbgZz8OsSIM9n+ykc04XeKxfeY6Z00kfNCtWRCwAFlTNm10xvYis61b1er8DXpN7gGbWUoZzglbx+FeAnzYrZjMrjQGv7pnuz0nTVwBzJSkiKsf5Owm4LP9wzcrL55Pb8iti/fIVZ8zMzLax+QQtIp4jO8maXrXMdOCiNH0FcJgkAaQr8j0ALG9OuGZWIvVc3XPzMhHRAzwJjK9a5kTg+1XzviNpqaTP9Oabar7yp1l781m6DXipuHovV2dmZtYhhnyCJmks8C/AvzYhTjNrQ5IOJBsj8M6K2e+KiNcAb0q3d9daNyLmRcS0iJjW1eXOHGbtxp/qDlbv4MmD7ePosXXMzMz6NAc4JyLW9fED+2aSZgGzAEaOHJl/ZGbWDPVc3bN3mZWSuoCdyMby6jWDqtY7FVf9fFrSpWQtDS9ubOhmVnYu8HSwwQ6ePFDRptFX2zIzMyup4ZygHQgcL+lLwDhgk6T1ETG3eicRMQ+YBzBmzJioftzMWlI9V/fsBmYCNwPHAzf0jr8jaTvgHWStdEjzuoBxEfG4pO2BY4Bf5P1EzKx83MyiQ/U3ePJQbS4YxZaCkZmZWRvafIImaSTZCVp31TK9J2hQcYIWEW+KiEkRMQn4KvDvtYo7ZtaeUpfN3qt73g38oPfqnpKOTYtdQNalcwXwMeCMik0cAjzcO0hzMgq4VtLtwFKywtF/5ftMzKyM3IKnQ/UOnrxuzZYiz3AGT87zaltmZvVyzrFmiIgeSb0naCOAC3tP0IDFEdFNdoJ2STpBe4KsCGRmVs/VPdcDJ/Sx7o3AG6rmPQPs1/BAzazluMDTpuo5yTnmtH24+txlrKvoUjVUjS4YmZkNhruIWrMN5wStYpk5uQRnZlZiv1v7dF3LVV+a0MwG5gJPmxnMSc5gB08eSCMLRmbWGRqVfwY7ppiZmZmZWbtxgafNDOUkp1GtbBpdMLL2ImkPsqs5vAQIYF5EfK3YqKwog21x019eybuLqHNaeTmvmFkenFvMrNGalVdc4GkjZRkHxydC1oce4J8j4lZJLwSWSLouIu4qOjBrvnqL0fUUgvLqIupuXy3BecXM8uDcYmaN1pS8UrozcUlHSbpH0gpJZ9R4fJSky9PjCyVNSvMPl7RE0h3p76FND75gvSc5lTwOjpVFRDwaEbem6afJrhwxodiorAiDuYpfvVfnO+a0fRi78ygQjN25MV1EfWXA8nNeMbM8OLeYWaM1K6+UqgWPpBHAecDhwEpgkaTuqqrWKcCaiJgiaQZwNnAi8Djwtoh4RNKrya5s0XGJ2OPgWIG6JC2uuD8vIubVWjAVZl8HLGxGYFYu9ba4GUyrxEZ3ES1Li0gD6swtzitmNgg+ZjGzRitFXilVgQc4AFgREfcDSLqMbAD1ygLPdGBOmr4CmCtJEXFbxTLLgdGSRkXE1kfobc7j4FiBeiJi2kALSRoL/Aj4aEQ8lX9YVkb1FKOH0vWqUXnPVwYslQFzi/OKmQ2Sj1nMrNFKkVfKVuCZADxccX8lcGBfy0REj6QngfFkLXh6/S1wa63ijqRZwCyAkSNHNi7ykvFJiJWRpO3JEtr3IuLHRcdjxam3GF1kq0S3iGwNzitmlgfnFjNrtGbklbIVeIZN0t5k3baOqPV4aiY1D2DMmDHRxNDMOpokARcAd0fEV4qOx8phoGJ0ka0S3SKy/JxXzCwPzi1m1mjNyitlO2JdBexRcX9imldzGUldwE7A6nR/InAlcHJE3Jd7tGY2GAcB7wYOlbQ03d5adFDWGoossLi4U2rOK2aWB+cWM2u0puSVsrXgWQRMlTSZrJAzA3hn1TLdwEzgZuB44IaICEnjgGuAMyLipuaFbGb1iIjfAio6DjNrH84rZpYH5xYza7Rm5ZVSFXjSmDqnkl0BawRwYUQsl3QWsDgiusmaNV0iaQXwBFkRCOBUYAowW9LsNO+IiHisuc/CzMzMzMzMhuPLDzxa13KnT94t50jMWkepCjwAEbEAWFA1b3bF9HrghBrrfQ74XO4BmpmZmZmZmZmVjAcWMDMzMzMzMzNrcS7wmFnbk3SUpHskrZB0Ro3HD5F0q6QeScdXPTZT0r3pNrN5UZuZmZmZmdWvdF20zMwaSdII4DzgcGAlsEhSd0TcVbHYQ8B7gI9XrbsL8FlgGhDAkrTummbEbmZWNI+BYWZm1jrcgsfM2t0BwIqIuD8ingMuA6ZXLhARD0bE7cCmqnWPBK6LiCdSUec64KhmBG1mZmZmZjYYLvCYWbubADxccX9lmtewdSXNkrRY0uKenp4hB2pmZmZmZjZULvCYmQ1TRMyLiGkRMa2ryz1fzczMrG91jA04StLl6fGFkial+ZMk/VnS0nT7VsU6+0m6I63zdUlq4lMys5JwgcdKb+Pz1b1mzAZlFbBHxf2JaV7e65qZmZltpWJswKOBvYCTJO1VtdgpwJqImAKcA5xd8dh9EbFvun2gYv43gfcDU9PNXcrNOpB/arbSWr1qHVfNXcYzazcwdtwojjltH8bvPrbosKz1LAKmSppMVpyZAbyzznWvBf5d0s7p/hHAmY0P0czMzDrE5rEBAST1jg1YefGH6cCcNH0FMLe/FjmSdgN2jIhb0v2LgeOAnzY6eDMrN7fgsdK6au4ynlmzAQLWrdnA1ecuKzoka0ER0QOcSlasuRv4QUQsl3SWpGMBJO0vaSVwAvBtScvTuk8A/0ZWJFoEnJXmmZmZmQ1FPeP7bV4mHcc8CYxPj02WdJukX0l6U8XyKwfYJuBxA83anVvwWCltfH4Tz6zdsNW8dWs3sPH5TYzY3nVJG5yIWAAsqJo3u2J6EVn3q1rrXghcmGuAZmZmZgN7FHhpRKyWtB/w35L2HswGImIeMA9gzJgxkUOMZlYgnylbKY3YfjvGjhu11byx40a5uGNmZmZmraye8f02LyOpC9gJWB0RGyJiNUBELAHuA16Rlq/8ocpjBpp1KJ8tW2kdc9o+jN15FAjG7pyNwWNmZmZm1sI2jw0oaSTZ2IDdVct0AzPT9PHADRERkl6UBmlG0p5kgynfHxGPAk9JekMaq+dk4CfNeDJmVi7uomWlNX73scz8wkHulmVmZmZmbSEieiT1jg04Ariwd2xAYHFEdAMXAJdIWgE8QVYEAjgEOEvS88Am4AMVYwN+EJgPjCYbXNkDLJt1IBd4rPRc3DEzM2uc3619uugQzDpaHWMDrie78EP1ej8CftTHNhcDr25spGbWanzmbGZmZmZmZmbW4lzgMTMzMzMzMzNrcS7wmJmZmZmZmZm1OBd4zMzMzMzMzMxanAs8ZmZmZmZmZmYtzgUeMzMzs0GSdJSkeyStkHRGjcdHSbo8Pb5Q0qQ0/3BJSyTdkf4e2vTgzczMrC35MulmZmZmgyBpBHAecDiwElgkqTsi7qpY7BRgTURMkTQDOBs4EXgceFtEPCLp1cC1wITmPoPG+/IDj9a13OmTd8s5EjMzs87lFjxmZmZmg3MAsCIi7o+I54DLgOlVy0wHLkrTVwCHSVJE3BYRj6T5y4HRkkY1JWozMzNray7wmJmZmQ3OBODhivsr2bYVzuZlIqIHeBIYX7XM3wK3RsSGnOI0MzOzDuIuWmZmZmZNJmlvsm5bR/SzzCxgFsDIkSObFJmZmZm1Khd4Gsj9z83MzDrCKmCPivsT07xay6yU1AXsBKwGkDQRuBI4OSLu62snETEPmAcwZsyYaFj0ZmZm1pZK10VrGFelGC/pl5LWSZrb9MDNzMysUywCpkqaLGkkMAPorlqmG5iZpo8HboiIkDQOuAY4IyJualbAZmZm1v5KVeCpuCrF0cBewEmS9qpabPNVKYBzyJo3A6wHPgN8vEnhmpmZWQdKY+qcSnYFrLuBH0TEcklnSTo2LXYBMF7SCuBjQO+PVqcCU4DZkpam24ub/BTMzMysDZWti9bmq1IASOq9KkXlZUenA3PS9BXA3HRVimeA30qa0sR4zczMrANFxAJgQdW82RXT64ETaqz3OeBzuQdoZmZmHadULXho3FUp+iRplqTFkhb39PQMM1wzMzMzMzMzs+KVrcCTu4iYFxHTImJaV1fZGjCZmZmZmZmZmQ1e2Qo8g7kqBdVXpTAzq2UYg7dPkvTninEyvtX04M3MzMzMzOpQtiYsm69KQVbImQG8s2qZ3qtS3EzFVSmaGqWZtYyKwdsPJ+v2uUhSd0RUju21efB2STPIBm8/MT12X0Ts28yYzcza1ZcfeLSu5U6fvFvOkZiZmbWfUrXgGeZVKZD0IPAV4D2SVta4ApeZdZ7Ng7dHxHNA7+DtlaYDF6XpK4DDJKmJMZqZmVmHGEbL4sMlLZF0R/p7aMU6N6Zt+up8Zh2sbC14hnxVivTYpFyDM7NWVGvw9gP7WiYieiRVDt4+WdJtwFPApyPiN9U7kDQLmAUwcuTIxkZvZmZmbWOYLYsfB94WEY9IejXZj+KVF6R5V0QsbsoTMbNSKlULHjOzknkUeGlEvI6sxeClknasXsiDt5uZmVmdhtyyOCJui4hH0vzlwGhJo5oStZm1BBd4zKzdDXnw9ojYEBGrASJiCXAf8IrcIzYzM7N2Vatl8YS+lklDWFS2LO71t8CtEbGhYt53Uvesz/TV1VzSLEmLJS3u6ekZzvMwsxLyT81m1u6GPHi7pBcBT0TERkl7AlOB+5sXupmZmdnWJO1N1m3riIrZ74qIVZJeCPwIeDdwcfW6ETEPmAcwZsyYtrhQjQdvN9vCLXjMrK0Nc/D2Q4DbJS0layL9gYh4oqlPwMzMzNrJkFsWp/sTgSuBkyPivt4VImJV+vs0cClZVzAz6zBuwWNmbW+og7dHxI/IfgUzMzMza4ThtCweB1wDnBERN/UunIpA4yLicUnbA8cAv8j9mZhZ6bgFj5k1haQLJT0m6c6iYzEr0sbnNxUdQltxbjGzRsszrwyzZfGpwBRgdtXl0EcB10q6HVhKVjj6r0bHbmZD16zjFbfgMbNmmQ/MpUZ/cCsn92lvrNWr1nHV3GU8s3YDY8eN4pjT9mH87mOLDqsdzMe5xcwaaz455pVhtCz+HPC5Pja7XyNjbEf1HteAj20sF/NpwvGKW/CYWVNExK8Bj19jHeuquct4Zs0GCFi3ZgNXn7us6JDagnOLmTWa84qZNVqz8opb8JhZo3RJWlxxf166UoNZx9v4/CaeWbthq3nr1m5g4/ObGLG9f2sZgHOLmTWa84qZNVop8ooLPGbWKD0RMa3oIMzKaMT22zF23CjWrdlS5Bk7bpSLO/VxbjGzRnNeMbNGK0VecYHHzMysCY45bR+uPncZ6yrG4DEzMyu7eseueUXOcZjZwFzgMTMza4Lxu49l5hcOcrcsMzMzM8uFCzxm1hSSvg+8GdhV0krgsxFxQbFRmTWfizuN5dzSnnwVPyuS84qZNVqz8ooLPGbWFBFxUtExmFn7cW4xs0ZzXjGzRmtWXvHPiGZmZmZmZmZmLc4FHjMzMzMzMzOzFucuWmZmZmZmZmaD5PHCrGzcgsfMzMzMzMzMrMW5wGNmZmZmZmZm1uLcRcvMzMzMWpK7R5iZmW3hAo+ZWQF+t/bpupabnnMcZtY+6i12vCLnOMzMzKwY7qJlZmZmZmZmZtbi3ILHzMzMzMzMLCfuTmrN4gJPAfwBNzMzMzMzM7NGcoHHzMyGxUVrMyu7evMUOFeZmVnrKt0YPJKOknSPpBWSzqjx+ChJl6fHF0qaVPHYmWn+PZKObGrgZlZazitm1mjOK+3ryw88WtfNbKjyyB8DbdPMOkOpWvBIGgGcBxwOrAQWSeqOiLsqFjsFWBMRUyTNAM4GTpS0FzAD2BvYHfiFpFdExMbmPovG8a/iZsPnvGJmjea8YmZDlUf+SOsMtE2zUmp0wbzTz41LVeABDgBWRMT9AJIuI7tKcGVymg7MSdNXAHMlKc2/LCI2AA9IWpG2d3OTYjezcmrpvNJOlz120draSEvnFTMrVB75gzq2aS3Ax0rD1+mvYdkKPBOAhyvurwQO7GuZiOiR9CQwPs2/pWrdCdU7kDQLmJXuhqQ/DxBTF9BTV/SzP1nXYkPUZxyfyHOvdcbQZI5ja2WIowsYXXAMfSkyrwz/f9PovFJQnhqMJua04SrDZ6+Zinq+ZcwtuecVGPQxSz7/n3xzxlCU5nOXc64qzfNsgiKea5F5Ja/8MdA2gZp55XmKfa/1/f9vTv6puf+yn181ML6ic01h+/9E4/dfiuOVshV4chcR84B59S4vaXFETMsxpJaJowwxOI5yxlGGGIrUV17ptNfFz7e9ddrzLYPBHLN0yv/Hz7P9dNJzLYPqvFL06+/9e/+dvP88lG2Q5VXAHhX3J6Z5NZeR1AXsBKyuc10z6zzOK2bWaM4rZjZUeeQP5xUzA8pX4FkETJU0WdJIskHEuquW6QZmpunjgRsiItL8GWnU+cnAVOD3TYrbzMrLecXMGs15xcyGKo/8Uc82zawDlKqLVupjeipwLTACuDAilks6C1gcEd3ABcAlaVCxJ8gSGGm5H5ANJtYDfKhBV6SouztXzsoQRxliAMdRrQxxlCGGmgrOK6V9XXLi59veOu359snHK4Xy82w/nfRcc8sftbZZZ0hFv/7ev/ffyftvOGXFYDMzMzMzMzMza1Vl66JlZmZmZmZmZmaD5AKPmZmZmZmZmVmLc4GnD5KOknSPpBWSzmjyvh+UdIekpZIWp3m7SLpO0r3p78457PdCSY9JurNiXs39KvP19PrcLun1OccxR9Kq9JoslfTWisfOTHHcI+nIBsWwh6RfSrpL0nJJH0nzm/p69BNHs1+PHST9XtKyFMe/pvmTJS1M+7s8DexHGvzv8jR/oaRJjYijlRSZQ5phMPmiHQw2J7S6wX7mrVjtnG+KOibKW1mOufJWhmM6q62IvFHksUPR3+Nl+V6VNELSbZKubvb+i87nksZJukLS/0i6W9Ib2+H7pJoLPDVIGgGcBxwN7AWcJGmvJofxlojYNyKmpftnANdHxFTg+nS/0eYDR1XN62u/R5ON3D8VmAV8M+c4AM5Jr8m+EbEAIP1fZgB7p3W+kf5/w9UD/HNE7AW8AfhQ2lezX4++4oDmvh4bgEMjYh9gX+AoSW8Azk5xTAHWAKek5U8B1qT556TlOkZJckje5lN/vmgHg80JrW6wn3krSIfkmyKOifI2n3Icc+VtPsUf01mVAvPGfIo7dij6e7ws36sfAe6uuN/s/ReZz78G/CwiXgXsQ/Y6tMP3yVZc4KntAGBFRNwfEc8BlwHTC45pOnBRmr4IOK7RO4iIX5ON1F/PfqcDF0fmFmCcpN1yjKMv04HLImJDRDwArCD7/w03hkcj4tY0/TRZAphAk1+PfuLoS16vR0TEunR3+3QL4FDgijS/+vXofZ2uAA6TpOHG0ULKmEMaapD5ouUNISe0tCF85q04bZ9vamj5z11ZjrnyVoZjOqupkLxR5LFD0d/jZfhelTQR+Bvg/HRfzdx/H5ry+kvaCTiE7Ap1RMRzEbG2WftvJhd4apsAPFxxfyX9n1Q3WgA/l7RE0qw07yUR8Wia/j/gJU2Kpa/9FvEanZqaJl9Y0Xwu9ziUdS96HbCQAl+Pqjigya9HatK5FHgMuA64D1gbET019rU5jvT4k8D4RsTRIorOIUUpKk81VZ05oeUN8jNvxWn3fFOmY6K8lemYK2+FHNPZZmV6rZv+eS7qe7wE36tfBT4BbEr3xzd5/0Xm88nAn4DvpC5q50sa08T9N40LPOV0cES8nqzZ5IckHVL5YEQE2QekqYrab/JN4OVkTRofBf6zGTuVNBb4EfDRiHiq8rFmvh414mj66xERGyNiX2Ai2S8/r8p7n9a6Cs4XuSlLTmgGf+atJEp5TJS3dn1eSSHHdFZ+zXjfF/k9XuT3qqRjgMciYkmz9llDkfm8C3g98M2IeB3wDFXdsdol77rAU9sqYI+K+xPTvKaIiFXp72PAlWQJ4I+9zXHT38eaFE5f+23qaxQRf0xJcRPwX2xpsptbHJK2J/sC+F5E/DjNbvrrUSuOIl6PXqk54y+BN5I1E++qsa/NcaTHdwJWNzKOkis0hxSoqDzVFIPMCW2jzs+8Faet803JjonyVopjrrwVeQxjm5XptW7a57ks3+MFfa8eBBwr6UGyLnmHko1J07Tv9YLz+UpgZUT09oS4gqzg03bfJy7w1LYImJpGFR9JNuBbdzN2LGmMpBf2TgNHAHem/c9Mi80EftKMePrZbzdwsjJvAJ6saN7WcFV9zd9O9pr0xjFD2VWbJpMNQPj7BuxPZH00746Ir1Q81NTXo684Cng9XiRpXJoeDRxO1nf5l8DxabHq16P3dToeuCFVxTtFYTmkYEXlqdwNISe0tCF85q04bZtvSnhMlLdSHHPlrdnHMFZTmfJGUz7PRX+PF/29GhFnRsTEiJhE9v++ISLe1az9F53PI+L/gIclvTLNOgy4q1n7b6qI8K3GDXgr8L9kfSM/1cT97gksS7flvfsm6yN5PXAv8Atglxz2/X2yprLPk1U5T+lrv4DIRt+/D7gDmJZzHJek/dxO9kHcrWL5T6U47gGOblAMB5M10bsdWJpub23269FPHM1+PV4L3Jb2dycwu+L9+nuygRB/CIxK83dI91ekx/ds1meoLLeickgTn1/d+aIdboPNCa1+G+xn3rfC/19tmW8o8JioCc+tFMdcBT3Pph7D+Nbn/6bpeaPIY4eiv8fL9L0KvBm4upn7L0M+J+sWujj9D/4b2Lkdvk+qb0pP1szMzMzMzMzMWpS7aJmZmZmZmZmZtTgXeMzMzMzMzMzMWpwLPGZmZmZmZmZmLc4FHjMzMzMzMzOzFucCj5mZmZmZmZlZi3OBx8zMzMzMzMysxbnA04IkHSdprybs55NDWOc9kubmEU8f+3tQ0q4DLLOuj/lnSfrrNH2jpGlpeoGkcen2wSHGNU3S1we5zhxJHx/K/swGY6D3WiPfi5ImSbpzkOts3r+k+ZKOb0Qsdex3wFglvVnS1X08tkDSuDS9Lv3dXdIVaXpfSW9tcNhmVqE3f1R9x79J0nJJSyWNlvTldP/Lkj4g6eQh7qvy2GHQx0yN0OzjLrOyq/X926ok/S79nSTpncPYzuac17joBtynz2sK0lV0ADYkxwFXA3flvJ9PAv+e18YldUVET17bH0hEzO5j/lshS6bAB4FvDGHbi4HFw4nPzAZH0oiI2FjU/ntzR9W8R4DeAtW+wDRgQRPDqqno18osb1Xf8e8CvhAR3wWQNAvYpcGfgVyPmXr5s2tWn6rv36ZpxPlN7zYi4i/TrEnAO4FLh7jJQeW8os/RbHjcgqckJP23pCWpujorzVtX8fjx6ZfsvwSOBb6cfol6efpV+BZJt0u6UtLOaZ0bJZ0jabGkuyXtL+nHku6V9LkB9v1FYHTax/fSvL+T9Ps079uSRqT575X0v5J+Dxw0wPOcL+lbkhYCX0rx/yzt/zeSXpWWe5ukhZJuk/QLSS9J88dL+nmK9XxA/T2PisfOSfOvl/Siili2Sfza0iroi8DL0/P9sqSLJR1Xsdz3JE3v43lu/pU/VbAvTP+P+yV9uGK5T6XX7rfAKyvmb/O6SOqStEjSm9MyX5D0+f5eb7Netd5rkt6f3lPLJP1I0gtqrFfzM9rHPl6SctCydOs9MBkh6b/SZ/DnkkbXu/86nteDks6WdCtwgqQjJN0s6VZJP5Q0Ni03O+3rTknzJCnN3683XuBDFdudlJ7vren2lxW73VHSNZLuSflsu4pYtmpRmLZzp6SRwFnAiSmnnKgsF/fmo+0krei9X+N5npC2s0zSr9O8EZL+I82/XdJpaf5hKXfekXLPqMG8Vmatpo/8Nl/ZsdP7gHcA/5a+t7uBscCS9DmsbDE4Rdkxx7L0uXi5qlrtSZor6T1V+9/mmKlGjKcrff8rOya5IU0fqi3HWSelz+2dks6uWHedpP9MeeqN6uO4q1aeMOtUqmiVq6yl24+VHc/cK+lLaf6IlCvuTJ+9f0rzB3t+MkfSJZJuAi7pI55rJL02Td8maXaaPkvZ8dCb0766ST/ia8u54BeBN6Uc808p7i8rO665XdI/9PM6VOe8SZJuSOtdL+mlabnqc7T5kr6p7Bzz/hTfhcrOKedXbH+b89UaMQz7eM8GISJ8K8GNrKoKMBq4ExgPrKt4/HhgfpqeDxxf8djtwF+l6bOAr6bpG4Gz0/RHgEeA3YBRwEpgfF/7Tvcr9/8XwFXA9un+N4CT0/YeAl4EjARuAub28zznk7U+GpHuXw9MTdMHAjek6Z0Bpen3Af+Zpr8OzE7TfwMEsOsAzyOAd6Xp2b3xVb6O6bWalqYfBHYlq5bfWRH7XwH/naZ3Ah4Auvp4nm8Grk7Tc4Dfpdd9V2A1sD2wH3AH8AJgR2AF8PEBXpe9gbuBvwZuA0YW/d71rfy3vt5rvZ+RtMzngNPS9JyB3ot97Ody4KNpekT6nEwCeoB90/wfAH+XpuvZ/+bPaR/7fBD4RJreFfg1MCbd/5eKfLFLxTqXAG9L07cDh6TpL/d+5tNrtUOangosTtNvBtYDe6bneB1b8siDbMlH69LfSRXbfA8V+RH4bMXrdQTwo36e5x3AhDQ9Lv39R+AKUh4CdgF2AB4GXpHmXVyxj7peK998a6Ubfee3zbmjOo+w9fFNZb5ZCLw9Te+Qtvlm0vd5mj8XeE+avpEtxw7rBojzDcAP0/RvgN+THQt8FvgHYHe2HE91ATcAx6XlA3hHmu7zuKtWnvDNt0679fP9ez/ZcckOwB+APVL+uK5i3XHp72DPT+YAS4DR/cR1BtkPSTsBi4Br0/xfkhWm3ww8A0yu8Vyq89As4NNpehRZr4HJA70mafoqYGaa/nu2nNvMZ+tztPnAZWQ/pk8HngJeQ9ZAZAlbjuv6Ol+dw5bcWvN4z7d8bu6iVR4flvT2NL0H2QnFgCTtRJaMfpVmXQT8sGKR7vT3DmB5RDya1rs/7Wd1H/teXbWrw8iS4CJlP3yPBh4jS3o3RsSf0nYvB14xQNg/jIiN6dfivwR+mLYJWZICmAhcLmk3sgOYB9L8Q4D/BxAR10haU7Hdvp7HJrITT4DvAj8eIL6aIuJXkr6h7Bf2vyU7Gau3+eI1EbEB2CDpMeAlwJuAKyPiWdhcYae/1yUilku6hCwBvzEinhvKc7GOU/O9BrxaWWu+cWS/7lxbudIAn9FaDiUr/BJZM+AnlbUofCAilqZllpAddA24/0Ho/Xy/AdgLuCnFOxK4OT32FkmfIDth2wVYLuk3ZPmz95fuS4Cj0/T2wFxJ+wIb2Tqv/T4i7geQ9H3gYLJCy2BdCPwE+CrZQdZ3+ln2JmC+pB+wJYf9NfCt3jwUEU9I2ofs9f7ftMxFZAeUX03363mtzFpJX/ltUCS9kKw4ciVARKxP8xsV5xJgP0k7AhuAW8m6bL4J+DCwP1sfT32P7Jjnv8ly0I/Sdvo77qqVJ8wsc31EPAkg6S7gZcByYE9J5wLXAD8f4vkJQHdE/Lmf/f+G7LP+QNrX4akly+SIuCdt8/cR8UA/2+h1BPBabemJsBPZeU89676RdC5FdtzzpYrHfhhbd+O6KiJC0h3AHyPiDgBJy8mO5ZbWsT9o3PGe1cEFnhJQ1uXmr8lO2J+VdCNZdTkqFtthiJvfkP5uqpjuvd/Vz763CRO4KCLOrIr9uCHE9Ez6ux2wNiL2rbHMucBXIqI7xTinvw0O4nnA1q/rYF0M/B0wA3jvINarfO030v9nr7/XBbLq+VrgxYPYv1kt88l+IV6mrMvBm6seH+i9WK/q9//oOvdfr96cIrJf4k6qfFDSDmStDqdFxMOS5jBwTv0n4I/APmSvw/qKx6pzyJBySorlj5IOBQ4gGyekr2U/IOlAspaLSyTtN5R9MsBrZWbb6GHrIQ2GdDwWEc9LeoCsJcHvyFoPvgWYQtYyt78f9tZHHWNn1MoTEVH9g51Zp9rmWDwi1qQfRo4EPkDWnfOjDO385Jkay1daRFbUvZ+s9e+uwPvJir/1bqOXyFrBNLpQUr3/fs8j03Q956vzaczxntXBY/CUw07AmlSYeBXZL6sAf5T0F8rGd3h7xfJPAy8ESJXoNZLelB57N/Ar6tfXvgGel7R9mr4eOF7SiwEk7SLpZWTNmf9K2dg42wMn1LvjiHgKeEDSCWmbSkm2N65VaXpmxWq/JhtkDElHkzWVHOh5bMeWQdbeCfy2zhA3v84V5pMlfiJiuINc/xo4TtkVPV4IvC1tt8/XRdL/I2t9cAhwrtIVe8wGUPO9Rvb+fjR9drcpLgzwGa3lerJuQ7392ncaIK5+9z8EtwAHSZqSYhgj6RVsOeB4PP0ydzxARKwF1ko6OD1eGcNOwKMRsYksr46oeOwASZNTbj6R4eWU88laFlb/arYVSS+PiIWRDRz7J7JWitcB/yCpKy2zC3APMKn3NaDv74S+XiuzVtNXfhuUiHgaWNn7w5WkUenX9T8Ae6X748haNNdSeczUl9+QdR/7dZr+AHBbRARZl62/krSrsjEOT6L2Z7fP464+8oSZ9UHZuHnbRcSPgE8Drx/i+cmAUqv7h8k+szezdT4YSPXxw7XAP/bmHEmvkDSmzlB+R/ZDNWTHPb+pc72+9HW+WqnRx3vWDxd4yuFnZK1p7iYbROuWNP8Msq44vwMerVj+MuB0ZQN0vZwswXxZ0u1kV2k5qwH7BpgH3C7pe6mY8Wmypou3k51Y7Ja6fM0hS1Q3kf0KNRjvAk5RNnDgcrI+nqRt/lDSEuDxiuX/FTgkNQ38f2T90Ad6Hs+QnZDdSdaFpK7XJ/3qdZOygde+nOb9MT3H/rpS1CUibiXrLrEM+ClZZb/XNq+Ltgz8/L7U/WIu8LXhxmHtr5/32mfIThZuAv6nj9X7+ozW8hGyrlB3kP0itdcAodWz/7qlLgvvAb6f8tTNwKtSIee/yMbmupatP2vvBc6TtJSKQdvJWvzMTM/7VWz9q9Yiss/f3WTNoa+sM8Rfkp0oLpV0YprXO/jhQDnly0qDr5J9JywjKw49RJanlwHvTN1K3kuWP+8g+5XtW9Ub6+u1qvN5mJXGAN+lg/Vusu7et5N9zv6/iHiYbOywO9Pf2/pYd/MxUz/b/w3ZGDo3p+OJ9Wke6XjqDLI8sQxYEhE/qd7AAMddtfKEmfVtAnBjOgb4LtDbU2Gw5yf1+g3wWOrK9RuyLl/1FFhuBzYqG6T4n8i+/+8Cbk2f929Tf8+c04D3pjz3brJjt+Ho63y1UkOP96x/vYNEmVkd0q95d5BV+J8sOh4za22SpgHnRMSbBlzYzMzMzKwfbsFjVidJf032S9m5Lu6Y2XBJOoNs4NQzB1rWzMzMzGwgbsFjuZD0KbYdj+eHEfH5IuLJi6QjgbOrZj8QEX31QTVreUV8viVdCUyumv0vOQwwWKhOyZ1m7UrSeLLxyKod5gGPzdpfUecGkl5DdlWsShsi4sA892vl4wKPmZmZmZmZmVmLcxctMzMzMzMzM7MW5wKPmZmZmZmZmVmLc4HHzMzMzMzMzKzFucBjZmZmZmZmZtbiXOAxMzMzMzMzM2txLvCYmZmZmZmZmbU4F3jMzMzMzMzMzFqcCzxmZmZmZmZmZi3OBR4zMzMzMzMzsxbnAo+ZmZmZmZmZWYtzgcfMzMzMzMzMrMW5wGNmZmZmZmZm1uK6ig6gSNttt12MHj266DDM2sKzzz4bEdHxRWPnFbPGcm7JOLeYNY7zSsZ5xaxxypJXOrrAM3r0aJ555pmiwzBrC5L+XHQMZeC8YtZYzi0Z5xazxnFeyTivmDVOWfJK4RUmMzMzMzMzMzMbHhd4zMzMzMzMzMxanAs8ZmZmZmZmZmYtzgWeKpMmTUJS4bdJkyYV/VKYWYM4r5hZHorKLc4lZu3LecWstXX0IMu1/OEPfyAiig4DSUWHYGYN4rxiZnkoKrc4l5i1L+cVs9bmFjxmZmZmZmZmZi3OBR4zMzMzMzMzsxbnAo+ZmZmZmZmZWYtzgWeQIoIPf/jDTJkyhde+9rXceuut2yzz7LPP8jd/8ze86lWvYu+99+aMM87Y/Ni3vvUtXvOa17Dvvvty8MEHc9dddzUzfDMroXryCsCnPvUp9thjD8aOHbvV/Iceeoi3vOUtvO51r+O1r30tCxYsaEbYZlZCP/vZz3jlK1/JlClT+OIXv7jN41/5ylfYa6+9eO1rX8thhx3GH/7wh82PXXTRRUydOpWpU6dy0UUXNTNsMys55xaz1qAyDPxZlDFjxsQzzzyz1TxJ/Q4stmDBAs4991wWLFjAwoUL+chHPsLChQu3WubZZ59l4cKFvOUtb+G5557jsMMO45Of/CRHH300Tz31FDvuuCMA3d3dfOMb3+BnP/vZNvsZKA6zspH0bESMKTqOouWVVwBuueUWXvaylzF16lTWrVu3ef6sWbN43etexz/+4z9y11138da3vpUHH3xwm/WdV6wVObdk6sktGzdu5BWveAXXXXcdEydOZP/99+f73/8+e+211+ZlfvnLX3LggQfyghe8gG9+85vceOONXH755TzxxBNMmzaNxYsXI4n99tuPJUuWsPPOO28Ti3OJNdufzp1b13IvOu3UupZzXsnUe8zSjNzivGLNVm9egfpyS1nyilvwDNJPfvITTj75ZCTxhje8gbVr1/Loo49utcwLXvAC3vKWtwAwcuRIXv/617Ny5UqAzcUdgGeeecYjxptZXXkF4A1veAO77bbbNvMl8dRTTwHw5JNPsvvuu+ces5mVz+9//3umTJnCnnvuyciRI5kxYwY/+clPtlrmLW95Cy94wQuALKf0Hp9ce+21HH744eyyyy7svPPOHH744TV/gDKzzuPcYtY6XOAZpFWrVrHHHntsvj9x4kRWrVrV5/Jr167lqquu4rDDDts877zzzuPlL385n/jEJ/j617+ea7xmVn6DzSvV5syZw3e/+10mTpzIW9/6Vs4999w8wjSzkhtsLrngggs4+uijh7SumXUO5xaz1uECT456eno46aST+PCHP8yee+65ef6HPvQh7rvvPs4++2w+97nPFRihmbWD73//+7znPe9h5cqVLFiwgHe/+91s2rSp6LDMrMS++93vsnjxYk4//fSiQzGzNuLcYlYsF3jqcN5557Hvvvuy7777sttuu/Hwww9vfmzlypVMmDCh5nqzZs1i6tSpfPSjH635+IwZM/jv//7vHCI2s7Ibal6p5YILLuAd73gHAG984xtZv349jz/+eMNjNrNymzBhQl255Be/+AWf//zn6e7uZtSoUYNa18w6j3OLWetwgacOH/rQh1i6dClLly7luOOO4+KLLyYiuOWWW9hpp51qjonx6U9/mieffJKvfvWrW82/9957N09fc801TJ06Ne/wzayEhpJX+vLSl76U66+/HoC7776b9evX86IXvSiv0M2spPbff3/uvfdeHnjgAZ577jkuu+wyjj322K2Wue222/iHf/gHuru7efGLX7x5/pFHHsnPf/5z1qxZw5o1a/j5z3/OkUce2eynYGYl5Nxi1jq6ig6g1bz1rW9lwYIFTJkyhRe84AV85zvf2fzYvvvuy9KlS1m5ciWf//znedWrXsXrX/96AE499VTe9773MXfuXH7xi1+w/fbbs/POO/tSgdZRJD0IPA1sBHoiYlqxEZVDPXkF4BOf+ASXXnopzz77LBMnTuR973sfc+bM4T//8z95//vfzznnnIMk5s+f7wHcrWM4r2zR1dXF3LlzOfLII9m4cSN///d/z957783s2bOZNm0axx57LKeffjrr1q3jhBNOALICcXd3N7vssguf+cxn2H///QGYPXs2u+yyS5FPx2yz3619uq7lpjdwn84tWzi3mDVGM/KKL5M+yMsZN0tZ4jCrVz2XBkxJbVpEtG3/IecVs8YaKLd0Ql6BcuUW5xJrtp/82xfqWm76Z86sazkfs2ScV6yTFXGZ9GbkFbfgMTMzMzMzM7OOUW/LQGhs68C8eQweM2uULkmLK26zaiwTwM8lLenjcTOzagPlFucVMxssH7OYWaOVIq+4BY+ZNUo9/UgPjohVkl4MXCfpfyLi180Izsxa1kC5xXnFzAbLxyxm1milyCtuwWNmTRMRq9Lfx4ArgQOKjcjMWp3zipnlwbnFzBqtGXnFLXiqvOxlLyvF1Wde9rKXFR2CWUNJGgNsFxFPp+kjgLMKDqspnFfM8tHJeQWKyy3OJdbuOjm3OK+Y5aNZecUFnioPPvjgNvO+/MCjda17+uTdGhyNWVt5CXBlOmjoAi6NiJ81Y8eSjgK+BowAzo+IL1Y9fgjwVeC1wIyIuKLisZnAp9Pdz0XERYPdf628Uu/I/fWM2m/WwXLPK3Xkj1HAxcB+wGrgxIh4UNLhwBeBkcBzwOkRcUNaZz9gPjAaWAB8JIZw+ZhaucXMGqKwY5aiOa+Y5aYpecUFHjNrioi4H9in2fuVNAI4DzgcWAksktQdEXdVLPYQ8B7g41Xr7gJ8FphGNijakrTummbEbmb9yzuv1Jk/TgHWRMQUSTOAs4ETgceBt0XEI5JeDVwLTEjrfBN4P7CQrMBzFPDTvJ6HmQ1OUccsZta+mpVXPAaPmbW7A4AVEXF/RDwHXEbV1Q4j4sGIuB3YVLXukcB1EfFEKupcR3YiZmadYcD8ke73tuy7AjhMkiLitoh4JM1fDoyWNErSbsCOEXFLarVzMXBc7s/EzMzM2p4LPGbW7iYAD1fcX8mWX9Ebsq6kWb2XROzp6RlyoGZWOvXkgM3LREQP8CQwvmqZvwVujYgNafmVA2wTcG4xMzOzwXEXLTOzYYqIecA8gDFjxgx6HA0za1+S9ibrtnXEYNd1bjEzM7PBKF0LHklHSbpH0gpJZ9R4fJSky9PjCyVNqnjstZJulrRc0h2Sdmhq8GZWRquAPSruT0zz8l7XzFpfPTlg8zKSuoCdyAZbRtJEssugnhwR91UsP3GAbZpZGxvq+Y6kwyUtSec5SyQdWrHOfmn+CklfVxku32lmTVeqAk/FYIZHA3sBJ0naq2qxzYMZAueQ/SrWe1D1XeADEbE38Gbg+SaFbmbltQiYKmmypJHADKC7znWvBY6QtLOkncl+gb82pzjNrHzqyR/dwMw0fTxwQ0SEpHHANcAZEXFT78IR8SjwlKQ3pBOwk4Gf5Pw8zKwkhnO+w5bB219DlncuqVind/D2qenmMQPNOlCpCjwMYzBDshOv2yNiGUBErI6IjU2K28xKKo2JcSpZYeZu4AcRsVzSWZKOBZC0v6SVwAnAtyUtT+s+Afwb2UneIuCsNM/MOkA9+QO4ABgvaQXwMaD31/hTgSnAbElL0+3F6bEPAucDK4D78BW0zDqJB283s9yUbQyeWoMZHtjXMhHRI6l3MMNXACHpWuBFwGUR8aXqHUiaBcwCGDlyZMOfgJmVT0QsILsUceW82RXTi9i6y0TlchcCF+YaoJmVVh35Yz1Zcbh6vc8Bn+tjm4uBVzc2UjNrEcM533m8YpnNg7dLGtTg7fhcyKxtla3AMxxdwMHA/sCzwPWSlkTE9ZULecBCMzMzMzNrVR683cz6UrYuWsMZzHAl8OuIeDwiniX7te31uUdsZmZmZmZWHw/ebma5KVuBZ8iDGZL1j3+NpBekRPhXwF1NitvMzMzMzGwgHrzdzHJTqgLPcAYzjIg1wFfIkuZSsj6p1zT5KZiZmZmZmdXkwdvNLE+lG4NnqIMZpse+S3apdDMzMzMzs9Lx4O1mlpdSteAxMzMzMzMzM7PBc4HHzMzMzMzMzKzFucBjZmZmZmZmZtbiXOAxMzMzMzMzM2txLvCYmZmZmZmZmbU4F3jMzMzMzMzMzFqcCzxmZmZmZmZmZi3OBR4zMzMzMzMzsxbnAo+ZmZmZmZmZWYtzgcfMzMzMzMzMrMW5wGNmZmZmZmZm1uK6ig6gFbziu/PrW/AzZ+Yah5mZmZmZmZlZLW7BY2ZmZmZmZmbW4lzgMTMzMzMzMzNrcS7wmJmZmZmZmZm1OBd4zMzMzMzMzMxanAs8ZmZmZmZmZmYtzgUeMzMzMzMzM7MW5wKPmZmZmZmZmVmLc4HHzMzMzMzMzKzFucBjZmZmZmZmZtbiXOAxMzMzMzMzM2txLvCYmZmZmZmZmbU4F3jMzMzMzMzMzFqcCzxmZmZmZmZmZi3OBR4zMzMzMzMzsxZXugKPpKMk3SNphaQzajw+StLl6fGFkial+ZMk/VnS0nT7VtODNzMzMzMzMzMrQFfRAVSSNAI4DzgcWAksktQdEXdVLHYKsCYipkiaAZwNnJgeuy8i9m1mzGZmZmZmZmZmRStbC54DgBURcX9EPAdcBkyvWmY6cFGavgI4TJKaGKOZtZhhtAzcXtJFku6QdLekM5sevJmZmZmZWR3KVuCZADxccX9lmldzmYjoAZ4ExqfHJku6TdKvJL2p1g4kzZK0WNLinp6exkZvZgOSNCJ9Tq9u1v7IWgYeDewFnCRpr6rFNrcMBM4haxkIcAIwKiJeA+wH/ENv8cfMyqPZecXM2p/zipnlIe/cUrYCz3A8Crw0Il4HfAy4VNKO1QtFxLyImBYR07q6StVDzaxTfAS4u4n7G07LwADGSOoCRgPPAU81J2wzG4Rm5xUza3/OK2aWh1xzS9kKPKuAPSruT0zzai6TTrp2AlZHxIaIWA0QEUuA+4BX5B6xmdVN0kTgb4Dzm7jb4bQMvAJ4hqyA/BDwHxHxRPUO3DLQrDgF5RUza2POK2aWh2bklrIVeBYBUyVNljQSmAF0Vy3TDcxM08cDN0RESHpR6oqBpD2BqcD9TYrbzKCrt8iRbrNqLPNV4BPApuaGNmQHABuB3YHJwD+n/LIVtww0y9VAueWrtFZeMbPiOa+YWaOV4lyoVGciEdEj6VTgWmAEcGFELJd0FrA4IrqBC4BLJK0AniArAgEcApwl6XmyF+wDtX5pN7Pc9ETEtL4elHQM8FhELJH05qZFNbiWgSsrWwYC7wR+FhHPA49JugmYhovHZs3UZ24pMK+YWWtzXjGzRivFuVCpCjwAEbEAWFA1b3bF9HqygU+r1/sR8KPcAzSzoToIOFbSW4EdgB0lfTci/i7n/W5uGUhWyJlBVrip1Nsy8Ga2bhn4EHAoWVF5DPAGssq7mZVDUXnFzNqX84qZ5aEpuaVsXbTMrE1FxJkRMTEiJpEVWW5oxsFSGlOnt2Xg3cAPelsGSjo2LXYBMD61DPwY0Hsp9fOAsZKWkxWKvhMRt+cds5nVp6i8Ymbty3nFzPLQrNxSuhY8ZmaNNoyWgetqzTczMzMzMysbF3jMrOki4kbgxoLDMLM24rxiZo3mvGJmecgzt7iLlpmZmZmZmZlZi3OBx8zMzKwPko6SdI+kFZLOqPH4KEmXp8cXSpqU5o+X9EtJ6yTNrVrnxrTNpen24iY9HTMzM2tj7qJlZmZmVoOkEWSDrR8OrAQWSeqOiLsqFjsFWBMRUyTNAM4GTgTWA58BXp1u1d4VEYtzfQJmZmbWUdyCx8zMzKy2A4AVEXF/RDwHXAZMr1pmOnBRmr4COEySIuKZiPgtWaHHzMzMLHcu8JiZmZnVNgF4uOL+yjSv5jIR0QM8CYyvY9vfSd2zPiNJtRaQNEvSYkmLe3p6Bh+9mZmZdRQXeMzMzMya610R8RrgTen27loLRcS8iJgWEdO6utyr3qxdeGwvM8uLCzxmZmZmta0C9qi4PzHNq7mMpC5gJ2B1fxuNiFXp79PApWRdwcysA1SM7XU0sBdwkqS9qhbbPLYXcA7Z2F6wZWyvj/ex+XdFxL7p9ljjozezsnOBx8zMzKy2RcBUSZMljQRmAN1Vy3QDM9P08cANERF9bVBSl6Rd0/T2wDHAnQ2P3MzKymN7mVlu3N7XzMzMrIaI6JF0KnAtMAK4MCKWSzoLWBwR3cAFwCWSVgBPkBWBAJD0ILAjMFLSccARwB+Aa1NxZwTwC+C/mveszKxgtcb2OrCvZVIe6h3b6/EBtv0dSRuBHwGfq1VsljQLmAUwcuTIIT0BMysvF3jMzMzM+hARC4AFVfNmV0yvB07oY91JfWx2v0bFZ2aWvCsiVkl6IVmB593AxdULRcQ8YB7AmDFj+mxtaGatyV20zMzMzMzMmsNje5lZblzgMTMzMzMzaw6P7WVmuXEXLTMzMzMzsybw2F5mlicXeMzMCvC7tU/XtVz1ZTXMzMystXlsLzPLiws8ZmYl9uUHHq1rudMn75ZzJGZmZmZmVmYeg8fMzMzMzMzMrMW5wGNmZmZmZmZm1uJc4DEzMzMzMzMzKwlJoyW9crDrucBjZmZmZmZmZlYCkt4GLAV+lu7vK6m7nnVd4DEzMzMzMzMzK4c5wAHAWoCIWApMrmdFF3jMzMzMzMzMzMrh+Yh4smpe1LOiL5NuZmZmZmZmZlYOyyW9ExghaSrwYeB39axYuhY8ko6SdI+kFZLOqPH4KEmXp8cXSppU9fhLJa2T9PGmBW1mZmZmZmZmNnynAXsDG4BLgSeBj9SzYqkKPJJGAOcBRwN7ASdJ2qtqsVOANRExBTgHOLvq8a8AP807VjMzMzMzMzOzBvubiPhUROyfbp8Gjq1nxVIVeMgGEloREfdHxHPAZcD0qmWmAxel6SuAwyQJQNJxwAPA8uaEa2ZmZmZmZmbWMGfWOW8bZRuDZwLwcMX9lcCBfS0TET2SngTGS1oP/AtwOODuWWZmZmZmZmbWEiQdDbwVmCDp6xUP7Qj01LONshV4hmMOcE5ErEsNemqSNAuYBTBy5MjmRGZmZmZmZmZm1rdHgMVk3bGWVMx/GvinejZQtgLPKmCPivsT07xay6yU1AXsBKwma+lzvKQvAeOATZLWR8TcypUjYh4wD2DMmDF1XWrMzMzMzMzMzCwvEbEMWCbp0oh4fijbKFuBZxEwVdJkskLODOCdVct0AzOBm4HjgRsiIoA39S4gaQ6wrrq4Y2ZmZmZmZmZWYpMkfYHswlM79M6MiD0HWrFUgyxHRA9wKnAtcDfwg4hYLuksSb2jRl9ANubOCuBjwDaXUjczMzMzMzMza0HfAb5JNu7OW4CLge/Ws2LZWvAQEQuABVXzZldMrwdOGGAbc3IJzszMzMzMzMwsP6Mj4npJiog/AHMkLQFmD7RiLi14JB1UzzwzMzMzMzMzM9tsg6TtgHslnSrp7cDYelbMq4vWuXXOa1kRfV+py8zMzMzM8uNjcTNrtBLllY8ALwA+DOwHvBs4uZ4VG9pFS9Ibgb8EXiTpYxUP7QiMaOS+ivL886N5/PFXsnHTSEZs9xy77noP22//56LDMrN+SDoK+BpZHjo/Ir5Y9fgosr6t+5Fdle/EiHgwPfZa4NtkeWwTsH/qKlqcnk3QVaoh1MzMzJrCx+Jm1mhlyysRsShNrgPeK2kE2QWoFg60bqPPEEaSNR3qAl5YcXuK7IpXLa/3Hw9i46aRPP74K4sOycz6kRLiecDRZCPRnyRpr6rFTgHWRMQU4Bzg7LRuF9mAZh+IiL2BNwNDumRhI+hP69nhG/cy+iv3sMM37kV/2lBUKGZmZoXwsbiZNVpZ8oqkHSWdKWmupCOUORVYAbyjnm00tAVPRPwK+JWk+WkwoLYSoc3/+Ex2P0JIUWRoZta3A4AVEXE/gKTLgOnAXRXLTAfmpOkrgLmSBBwB3B4RywAiYnWzgq5l1A8fRk/3ZBno6R5G/fAh1n9wapEhmZmZNY2Pxc2s0UqWVy4B1gA3A+8DPpkCe3tELK1nA3ldRWuUpHnApMp9RMShOe2vKaRgxHbPVbwBsvv+QjErtQnAwxX3VwIH9rVMRPRIehIYD7wCCEnXAi8CLouIL1XvQNIsYBbAyJEjhxxov18kPZvQup6Krx7g6R531zIzs47hY3Eza7SS5ZU9I+I1WVw6H3gUeOlghofIq8DzQ+BbwPnAxpz2UYhdd71nm/55Zta2uoCDgf2BZ4HrJS2JiOsrF4qIecA8gDFjxgz626Cufr9d2xFjuyC14AkgXtjl4o6ZmXUUH4ubWaOVKK9sHgoiIjZKWjnYsT/zKvD0RMQ3c9p2obbf/s/stttSNwU1ax2rgD0q7k9M82otszKNu7MT2WDLK4FfR8TjAJIWAK8HrqeBavX73W23pdsst+GElzLqhw/Buh5ibBcbTnhpI8MwMzMrPR+Lm1mjlSiv7CPpqTQtYHS6LyAiYseBNpBXgecqSR8ErgQ2jwIaEU/ktL+m8xeKWctYBEyVNJmskDMDeGfVMt3ATLL+rscDN0REb9esT0h6AfAc8FdkgzA3zGD6/caLRmVj7rhblpmZdTgfi5tZoxWdVyJi2Fcez6vAMzP9Pb1iXgB75rQ/M7Oa0pg6pwLXkl0m/cKIWC7pLGBxRHQDFwCXSFoBPEFWBCIi1kj6ClmRKIAFEXFNI+MbUr9fF3fMzMzMzKxKLgWeiJicx3bNrHVJ2gH4NTCKLPdcERGfbca+I2IBsKBq3uyK6fXACX2s+12yS6XnpkT9fq2NbXx+EyO2b6/iYJF5xczal3OLmTVas/JKLgUeSSfXmh8RF+exPzNrCRuAQyNinaTtgd9K+mlE3FJ0YEUrUb9fa0OrV63jqrnLeGbtBsaOG8Uxp+3D+N3HFh1WozivmLWZkhSjnVvM2kgn5ZW8umjtXzG9A3AYcCvgAo9Zh4qIANalu9unm6sZFVzcsTxcNXcZz6zJhsNbt2YDV5+7jJlfOKjgqBrDecWsfZSpGO3cYtYeWjWvSDo7Iv5loHm15FLGiojTKm7vJ7vqTNv8XGhmNXVJWlxxm1W9gKQRkpYCjwHXRcTCpkdp1kE2Pr+JZ9Zu2GreurUb2Pj8poIiGpJ+c4vzill72FyMji3F6Bz5mMWsA7RwXjm8xryj6wqi7nCH5xnA4/KYtbeeiJjW3wIRsRHYV9I44EpJr46IO5sSnVkHGrH9dowdN4p1a7YUecaOG1WGZsqD0W9ucV4xa339FaNzylc+ZjFrc62YVyT9I/BBYE9Jt1es+kLgpnqCyOWZSbpKUne6XQPcQ3bJdDMzImIt8EvgqIJDMWt7x5y2D2N3HgWCsTtnzZPbkfOKWevqLUZXKksx2rnFrDW1aF65FHgb0J3+9t72i4i/q2fbebXg+Y+K6R7gDxGxMqd9mVkLkPQi4PmIWCtpNFnTw7MLDqutlWRAOSvY+N3HMvMLB7Xl+8F5xax9HHPaPlx97jLWVYyVURTnFrP20Gp5JSKeBJ4ETpJ0MDA1Ir4jaVdJkyPigYH2k9dl0n8l6SVsGWz53jz2Y2YtZTfgIkkjyFoP/iAiri44prZUpgHlrDzarbiTOK+YtYmSFaOdW8zaQKvmFUmfBaYBrwS+A4wEvgsMeJWMvC6T/g7gy8CNgIBzJZ0eEVfksT8zK7+IuB14XdFxtJpXfHd+fQt+5szNk+181SSzSs4rZq3tT+fOLTqEmpxbzFpXm+SVt6dlb03rPiLphfWsmFcXrU8B+0fEY7C5OdIvgI4r8JSkWmhmHaKAAeXMzMzMzKxxnouIkBQAksbUu2JeBZ7teos7yWpyGtC5rNxFwsyK0CZXTTIzMzMz61Q/kPRtYJyk9wN/D/xXPSvmdcT/M0nXSnqPpPcA1wALctpXKW3uIhFbukiYmTVDp1w1yczMzMys3UTEf5D1fvoR2Tg8syPi3HrWbWgLHklTgJdExOmS/h9wcHroZuB7jdxXmbmLhJkVqQwDyjnfmZWDP4tWFn4vthf/P60M2vl9GBHXAdcNdr1Gd9H6KnBmCujHwI8BJL0mPfa2Bu+vlNxFwszKoIic4+6p1m4kHQV8DRgBnB8RX6x6fBRwMbAfWZf0EyPiQUnjyX592x+YHxGnVqyzHzAfGE3WwvkjERGNjNufRSsLvxfbi/+fVgbt/j6U9DRQfVzwJLAY+OeIuL+vdRt99P+SiLijemaaN6nB+yo1d5Ews1ay8flNDdmOu6daO0mXMj0POBrYCzhJ0l5Vi50CrImIKcA5wNlp/nrgM8DHa2z6m8D7ganpdlSjY/dn0crC78X24v+nlUEHvA+/CpwOTAAmkh1LXApcBlzY34qNbsEzrp/HRjd4X6VWhi4SZmYDaeQvIO6eam3oAGBF7y9lki4DpgN3VSwzHZiTpq8A5kpSRDwD/DZ1X99M0m7AjhFxS7p/MXAc8NNGBe3PopWF34vtxf9PK4MOeR8eGxGVLUTmSVoaEf8i6ZP9rdjoV2BxGuV5K5LeByypZwOSjpJ0j6QVks6o8fgoSZenxxdKmpTmHyBpabotk/T24T6ZRmijN5mZtaFG/gLS2z21krunWoubADxccX9lmldzmYjoIWtCPX6Aba4cYJsASJolabGkxT09PXUH7c+ilYXfi7UN43xnvKRfSlonaW7VOvtJuiOt83VJanTc/n9aGXTI+/BZSe+QtF26vYOsZTBs23VrK41+FT4KvFfSjZL+M91+RdZ8+SMDrTzMptB3AtMiYl+yps7flpTXZeDNzFpef7+ADJW7p5o1TkTMi4hpETGtq2twhzT+LFpZ+L24tVbu+gn+f1o5dMD78F3Au4HHgD+m6b+TNBo4tb8VG1oAiYg/An8p6S3Aq9PsayLihjo3MZym0M9WLLMDA1S2yqbNmpSZWQvIY0B4d0+1NrMK2KPi/sQ0r9YyK9MPSzuRDbbc3zYnDrDNYfNn0crC78VttGTXz17+f1oZtPP7MBWBPxgRfV2g6rf9rZ/LqxERv4yIc9Ot3uIODLMptKQDJS0H7gA+kB7fylCbO+dl9ap1zD/zJr714Ru56MybWP3IuqJDMrMOMthfQOpt3dNuX7bWsRYBUyVNljQSmAF0Vy3TDcxM08cDN/R3RayIeBR4StIbUheKk4GfND70jD+LVhZ+L27Wkl0/q/n/aWXQju/DiNgIHDzU9duqC1NELAT2lvQXwEWSfhoR66uWmQfMAxgzZkzhrXw2j3/BlvEvZn7hoIKjMrNOUe8vIO1+OUqzWiKiR9KpwLVkl0m/MCKWSzoLWBwR3cAFwCWSVgBPkBWBAJD0ILAjMFLSccAREXEX8EG2XCb9p+TwK7tZs7TjL+jtrGznQmaN9ru1TxcdQiPcJqkb+CHwTO/MiPjxQCuWrcDTkKbQEXG3pHVk3cQW5xfu8HTICOBm1gIGyjkuRluniogFwIKqebMrptcDJ/Sx7qQ+5i9mS1d2s5bUiMJ/m5yIDVbLdv00s6bZgewzf2jFvAAGLPCUrYow5KbQaZ0uAEkvA14FPNicsIemQ0YAN7MWl8dgzGZm1toaeRXGDtPyXT/N8tbpx5gR8d4at7+vZ91SteAZZlPog4EzJD0PbCIbmOjx5j+LwTnmtH24+txlrKv49cPMrEzyGIzZzMxal1uhD527fpr1zUMCZCTtQHY1vb3JWvMAUE+Rp1QFHhh6U+iIuAS4JPcAG2ywI4D7i9PMiuBitJmZ9XLhf3jc9dOsNg8JsNklwP8ARwJnkV02/e56VixdgadTDfSF6GqmNYuLiFZLXpej9Ptt+PwamlkRXPg3s0Zyy0CQ1JWunDclIk6QND0iLpJ0KfCberbhAk+LcDXT8uYiotWjUV+wfr8Nn19DMytSXoV/M+tMbhkIwO+B1wPPp/trJb0a+D/gxfVswAWeBvrTuXPrWu5Fp506qO26mmnN4CKiNZPfb8Pn19DMysDHombWKG4ZuNk8STsDnyYbdH0s8Jl6VnSBpwW4mml5cxHRmsnvt+Hza2hmZmbtxi0DebGkj6Xp96a/56W/Y+rZQEe+aq3omNP2YezOo0AwdueOrmZaDnqLiJVcRLS8+P02fH4NzczMrF118PHMCLLWOi+suI2tuA3ILXhahKuZljc3ibRmGuz7zblvW/7MmpmZmbWVRyPirOFswAWeFuMTHMuLi4jWTPW+3zyQcN/8mTVrXf7cmplZDRruBlzgMbOt+IDTmmmg95sHEh6YP7NmrcNFazMz68dhw92AjwrNzKyU+htI2MysFW0uWseWorWZmRlARDwx3G24wGNmbU/SUZLukbRC0hk1Hh8l6fL0+EJJk6oef6mkdZI+3rSgzQMJm1lbcdHazMzy5qNkM2trkkaQXV7waGAv4CRJe1UtdgqwJiKmAOcAZ1c9/hXgp3nHatvyFQTNrF24aG1meXKx2MBj8JhZ+zsAWBER9wNIugyYDtxVscx0YE6avgKYK0kREZKOAx4AnmlaxLaZBxI2s3biq9+ZWaN5bC+r5AKP1c0nWNaiJgAPV9xfCRzY1zIR0SPpSWC8pPXAvwCHA+6eVaA8ck9ROc251KxzuWhtZo3mC1JYJRd4bECuClsHmwOcExHrpL6vWihpFjALYOTIkc2JzIasqJzmXGpmvVzcMbNG6G9sL+eZzuT/ug3IV3ywFrcK2KPi/sQ0r+YykrqAnYDVZC19viTpQeCjwCclnVq9g4iYFxHTImJaV5fr5mVXVE5zLjWzvHjsDbPOlPfYXs4trcdnItavPKvCrixbkywCpkqaTFbImQG8s2qZbmAmcDNwPHBDRATwpt4FJM0B1kXE3GYEbfko6pcu/8JmZnlwy0Azy2NsL+eW1uUCj/Wrtyq8bs2WE5OBqsIDnbA4YVgzpTF1TgWuBUYAF0bEcklnAYsjohu4ALhE0grgCbIikLWhoeS0Vt6vmbU3j71hZnmM7ZVXbvEPW/lzgccGVG9VuN7CjQ9GrNkiYgGwoGre7Irp9cAJA2xjTi7BWdMVdRUbXz3HzBrJLQPNrFIju2U1Orf4B/7mcYHHBvyw1lsVrqdw44MRMytaUVex8dVzzKyR3DLQzPKQR27xD/zN42+ADrZ61Trmn3kT3/rwjVx05k2sfmRdv8sP1C2rr8JN9TbyHAjMzKxeReUd5zsza5RjTtuHsTuPAsHYnd0y0Mwao5G5pd7zRGsMt+DpYI2spA6m0utuCmZmZmbDN9iWgYNpQejWhmadq5G5xa0Nm8sFng6VR1epegs37qZgZmZm1jgDHU8NZvwLj5VhZr0alVv8A3/zuMDTofKopA62cOPijpmZmVn+BtNq22NlmFm96s0X/oG/efzqdrC8+m37Q2tmZmZWDoMZ/8JjZZhZvYaSL3yemD+34OlgrqSamZmZtbfBtNr2WBlmVi/ni3Iq3asv6ShJ90haIemMGo+PknR5enyhpElp/uGSlki6I/09tOnBl8hgfmkp+4fQvxq1B0l7SPqlpLskLZf0kaJjMmukdspV9T6Xop+z84q1u0Z9xgbTattX5nJusfbWyO9u54v6NSuvlKoFj6QRwHnA4cBKYJGk7oi4q2KxU4A1ETFF0gzgbOBE4HHgbRHxiKRXA9cCE5r7DIrXTgPjtdNzMQB6gH+OiFslvRBYIum6qs+3Wctpp1xV73Mp0XN2XrG21OjP2GBabbuFN+DcYm0oj+9u54tBaUpeKdt/4QBgRUTcHxHPAZcB06uWmQ5clKavAA6TpIi4LSIeSfOXA6MljWpK1CWyeaCr2DLQVatqp+diEBGPRsStafpp4G46sAhr7aedclW9z6Usz9l5xdpVXp+xwZyAdfLJmnOLtaM8v7s7OV/Uq1l5pWz/iQnAwxX3V7Ltk968TET0AE8C46uW+Vvg1ojYQAdpp4Hx2um5dJAuSYsrbrP6WjB1rXwdsLBp0ZnloJ1yVb3PpYDnXFducV6xdtFOeaXEfMxiHcV5pSlKkVdK1UWrESTtTdZt64g+Hp8FzAIYOXJkEyPLXzsNdNVOz6WD9ETEtIEWkjQW+BHw0Yh4Kv+wzPLTTrmq3udSwHMeMLc4r1g7aae8UmI+ZrGO4rzSFKXIK2X7j64C9qi4PzHNq7mMpC5gJ2B1uj8RuBI4OSLuq7WDiJgXEdMiYlpXV9vVt9pqoKt2ei6WkbQ9WUL7XkT8uOh4zBqhnXJVvc+lTM/ZecXaUZk+Y53KucXajfNK8ZqRV8pW4VgETJU0mayQMwN4Z9Uy3cBM4GbgeOCGiAhJ44BrgDMi4qbmhVwu7TTQVTs9FwNJAi4A7o6IrxQdj1mjtFOuqve5lOU5O69YuyrLZ6xTObdYO3JeKVaz8kqp/rNpTJ1Tya6AdTfwg4hYLuksScemxS4AxktaAXwM6L2U+qnAFGC2pKXp9uImP4XSaKcPbTs9lw53EPBu4NCKz+hbiw7KrFHaKVfV+1xK8JydV6ytleAz1qmcW6xtOa8Upil5pWwteIiIBcCCqnmzK6bXAyfUWO9zwOdyD9DMhiQifguo6DjMrH04r5hZHpxbzKzRmpVXXL4zMzMzMzMzM2txLvCYmVnb8OU+zczMzKxTla6LlpmZ2WCtXrWOq+Yu45m1Gxg7LrsyxPjdxxYdlpmZmZlZ07gFj5mZtbyr5i7jmTUbIGDdmg1cfe6yokMysw7kVoRmZlYkt+AxM7OWtvH5TTyzdsNW89at3eDLgJpZ07gVoZmZlYGPfM3MrKWN2H47xo4btdW8seNGubhjZk3jVoRmZlYGPvo1M7OWd8xp+zB251EgGLtz9uu5mVkz9NeK0MzMrJncRcvMzFre+N3HMvMLB7lbljWcpKOArwEjgPMj4otVj48CLgb2A1YDJ0bEg+mxM4FTgI3AhyPi2jT/QeDpNL8nIqY15clYLnpbEa5bs6XI41aEZtYoPraxwXCBx8zM2oYPgKyRJI0AzgMOB1YCiyR1R8RdFYudAqyJiCmSZgBnAydK2guYAewN7A78QtIrImJjWu8tEfF4056M5eqY0/bh6nOXsa5iDB4zs+Hw2F42FD4SNjMz64e7WXS0A4AVEXF/RDwHXAZMr1pmOnBRmr4COEyS0vzLImJDRDwArEjbszbU24rwA19/MzO/cJBPwqxfko6SdI+kFZLOqPH4KEmXp8cXSppU8diZaf49ko6smP+gpDskLZW0uElPxXLksb1sKNyCx8zMrAb/cmbABODhivsrgQP7WiYieiQ9CYxP82+pWndCmg7g55IC+HZEzKu1c0mzgFkAI0eOHN4zsaZwK0IbiFsGWj18hVAbKr87zMzMavAvZ5ajgyPi9cDRwIckHVJroYiYFxHTImJaV5d/kzNrE24ZaAPyFUJtqPwOMTMzq+Kr4liyCtij4v7ENK/mMpK6gJ3IBlvuc92I6P37GHAlPkEz6yS1WgZO6GuZiOgBKlsG9rVub8vAJan1X02SZklaLGlxT0/PsJ6I5ctXCLWh8M9BZmZmVXxVHEsWAVMlTSYrzswA3lm1TDcwE7gZOB64ISJCUjdwqaSvkHWlmAr8XtIYYLuIeDpNHwGc1ZynY2Zt7OCIWCXpxcB1kv4nIn5dvVDqEjoPYMyYMdHsIK1+vkKoDYXfKWZmZjX4lzNLv5yfClwL3A38ICKWSzpL0rFpsQuA8ZJWAB8DzkjrLgd+ANwF/Az4UBon4yXAbyUtA34PXBMRP2vm8zKzQrlloA2Kizs2GG7BY2ZmVoN/OTOAiFgALKiaN7tiej1wQh/rfh74fNW8+wFXC806l1sGmlluXOAxMzPrh4s7ZmbWKOlqe70tA0cAF/a2DAQWR0Q3WcvAS1LLwCfIikCk5XpbBvaQWgZKeglwZTYOM13ApW4ZaNaZXOAxMzMzMzNrErcMNLO8uMDTQL9b+3Rdy1VfB9HM8iXpKOBrZL+UnR8RX6x6fBRwMbAfWR/3EyPiQUmHA18ERgLPAadHxA1NDd7MzMzMzKwObnduZm1N0gjgPOBoYC/gJEl7VS12CrAmIqYA5wBnp/mPA2+LiNeQ9YW/pDlRm5mZmZmZDY4LPGbW7g4AVkTE/RHxHHAZ2zakmw5clKavAA6TpIi4LSIeSfOXA6NTax8zMzMzM7NScYHHzNrdBODhivsr07yay6TLIj8JjK9a5m+BWyNiQ/UOJM2StFjS4p6enoYFbmZmZmZmVi+PwWNmNgBJe5N12zqi1uMRMQ+YBzBmzJhoYmhmZmZmZmaAW/CYWftbBexRcX9imldzGUldwE5kgy0jaSJwJXByRNyXe7RmZmZmZmZD4AKPmbW7RcBUSZMljQRmAN1Vy3STDaIMcDxwQ0SEpHHANcAZEXFTswI2MzMzMzMbLBd4zKytpTF1TgWuBe4GfhARyyWdJenYtNgFwHhJK4CPAWek+acCU4DZkpam24ub/BTMzMzMzMwGVLoxeCQdBXwNGAGcHxFfrHp8FHAxsB9ZF4oTI+JBSePJrn6zPzA/Ik5tbuRmVlYRsQBYUDVvdsX0euCEGut9Dvhc7gGamZmZmZkNU6la8EgaAZwHHA3sBZwkaa+qxU4B1kTEFOAcsoFPAdYDnwE+3qRwzczMzMzMzMxKoVQFHuAAYEVE3B8RzwGXAdOrlpkOXJSmrwAOk6SIeCYifktW6DEzMzMzMzMz6xhlK/BMAB6uuL8yzau5TBpb40lgfL07kDRL0mJJi3t6eoYZrpmZmZmZmZlZ8cpW4MldRMyLiGkRMa2rq3RDEJmZmZmZmZmZDVrZCjyrgD0q7k9M82ouI6kL2IlssGUzMzMzMzMzs45UtgLPImCqpMmSRgIzgO6qZbqBmWn6eOCGiIgmxmhmZmZmZmZmViql6qMUET2STgWuJbtM+oURsVzSWcDiiOgGLgAukbQCeIKsCASApAeBHYGRko4DjoiIu5r8NMzMzMzMzMzMmqpUBR6AiFgALKiaN7tiej1wQh/rTso1ODMzMzMzMzOzEipbFy0zMzMzMzMzMxuk0rXgMTOzwfvyA4/Wtdzpk3fLORIzMzMzMyuCW/CYmZmZmZmZmbU4F3jMzMzMzMzMzFqcCzxmZmZmZmZmZi3OBR4zawpJF0p6TNKdRcdiZu3DucXMGs15xcwarVl5xQUeaxsbn99UdAjWv/nAUUUHYWZtZz7OLWbWWPNxXjGzxppPE/KKr6JlLW/1qnVcNXcZz6zdwNhxozjmtH0Yv/vYosOyKhHxa0mTio7DzNqLc4uZNZrzipk1WrPyilvwWMu7au4ynlmzAQLWrdnA1ecuKzokMzMzMzMzs6ZyCx5raRuf38QzazdsNW/d2g1sfH4TI7Z3/bLJuiQtrrg/LyLmFRaNmbUL5xYzazTnFTNrtFLkFRd4rKWN2H47xo4bxbo1W4o8Y8eNcnGnGD0RMa3oIMys7Ti3mFmjOa+YWaOVIq/4LNha3jGn7cPYnUeBYOzO2Rg8ZmZmZmZmZp3ELXis5Y3ffSwzv3CQu2WVnKTvA28GdpW0EvhsRFxQbFRm1uqcW8ys0ZxXzKzRmpVXXOCxtuHiTrlFxElFx2Bm7ce5xcwazXnFzBqtWXnFZ8RmZmZmZmZmZi3OBR4zMzMzMzMzsxbnAo+ZmZmZmZmZWYvzGDxmZmZmZmZmVlpffuDRupZ7Rc5xlJ0LPGZmZmZm1jA+ETMzK4a7aJmZmZmZmZmZtTgXeMzMzMzMzMzMWpwLPGZmZmZmZmZmLc5j8BSg3n7Jp0/eLedIzMzMzMzMzKwduMBjZtZB6i0wg4vMZmZmZmatxF20zMzMzMzMzMxaXOla8Eg6CvgaMAI4PyK+WPX4KOBiYD9gNXBiRDyYHjsTOAXYCHw4Iq5tYuhmVlLOK0Pj7qRm+eSPgbZpVlaDaQVqfXNeMdvCeaWxSlXgkTQCOA84HFgJLJLUHRF3VSx2CrAmIqZImgGcDZwoaS9gBrA3sDvwC0mviIiNzX0WjeOTK7Phc14xs6HKI3+kdQbappm1KecVM8tTqQo8wAHAioi4H0DSZcB0oDI5TQfmpOkrgLmSlOZfFhEbgAckrUjbu7lJsZtZOTmv5MzFaGtjeeQP6timWdP41/Omc16xjuDcUoyyFXgmAA9X3F8JHNjXMhHRI+lJYHyaf0vVuhPyC7U82unD4xNAy4HzSkl0Yq5qheJXK8RYoLzyx0DbHBL/L5ur0Tmt0XnFSqul8go4tzST84oNV9kKPLmTNAuYle6GpD/3sWgX0JNLELM/2cit5RdnY9UV5yeaEMgA2ur1bLLRRQdQlEHkFcjrfze4vFKG909Lx9CgXLV5/wXmvrpfgxxjHCgG55bMQLmlboP4X7b057TVYujn/9Ixr8GwY6j/u9B5JdOwvAKlfw9DOeJoagwl/5+UIQZoXG4pRV4pW4FnFbBHxf2JaV6tZVZK6gJ2Iht8rJ51iYh5wLyBApG0OCKmDSr6AjjOxnKcbak0eQXK8b9zDOWIoej9O4a65JU/BswrMLjckocy/G8cQ/H7dwwN13F5pSz/uzLEUYYYyhJHGWIoUxyNUrbLpC8CpkqaLGkk2SBi3VXLdAMz0/TxwA0REWn+DEmjJE0GpgK/b1LcZlZezitmNlR55I96tmlm7ct5xcxyU6oWPKmP6anAtWSX+LswIpZLOgtYHBHdwAXAJWlQsSfIEhhpuR+QDSbWA3zIV7oxM+cVMxuqvPJHrW02+7mZWTGcV8wsT8qKwVZN0qzUhLHUHGdjOU7LWxn+d46hHDEUvX/HYAMpw//GMRS/f8dgw1WW/10Z4ihDDGWJowwxlCmORnGBx8zMzMzMzMysxZVtDB4zMzMzMzMzMxskF3iqSDpK0j2SVkg6o+h4qkl6UNIdkpZKWpzm7SLpOkn3pr87FxDXhZIek3RnxbyacSnz9fQa3y7p9QXHOUfSqvSaLpX01orHzkxx3iPpyCbGuYekX0q6S9JySR9J80v3mlr9isgvg30v5RjHCEm3Sbo63Z8saWF6LS5Pg0Lmuf9xkq6Q9D+S7pb0xgJeg39K/4M7JX1f0g55vw5F5+Y+9v/l9H+4XdKVksZVPFZIzrUtJP2zpJC0a7rf5/tC0sz0PrpX0sy+t1rXfv8tbX+ppJ9L2r2Z+0/bG/R7s9F5XdIJKU9skjSt6rGmxFAjpty/u4rOVdZ4ReWStL3C80napnNK33E17Zi44/JLRPiWbmSDkt0H7AmMBJYBexUdV1WMDwK7Vs37EnBGmj4DOLuAuA4BXg/cOVBcwFuBnwIC3gAsLDjOOcDHayy7V3oPjAImp/fGiCbFuRvw+jT9QuB/Uzyle019q/t/Wkh+Gex7Kcc4PgZcClyd7v8AmJGmvwX8Y877vwh4X5oeCYxr5msATAAeAEZXPP/35P06FJ2b+9j/EUBXmj67Yv+F5VzfNv9v9iAbpPUPpGONvt4XwC7A/envzml652Hse8eK6Q8D32rm/ofy3iSHvA78BfBK4EZgWsX8psVQFU9TvruKzlW+Nfz/WVguSdssPJ+k7Tqn1I6pqcfEnZZf3IJnawcAKyLi/oh4DrgMmF5wTPWYTnbyQvp7XLMDiIhfk43yX6mvuKYDF0fmFmCcpN0KjLMv04HLImJDRDwArCB7j+QuIh6NiFvT9NPA3WQniKV7Ta1uheSXIbyXGk7SROBvgPPTfQGHAlc0af87kX25XwAQEc9FxFqanzu7gNGSuoAXAI+S8+tQdG6utf+I+HlE9KS7twATK/ZfSM61zc4BPgFUDtDY1/viSOC6iHgiItYA1wFHDXXHEfFUxd0xFTE0Zf8phsG+Nxue1yPi7oi4p8ZDTYuhSlO+u4rOVdZwheUSKEc+SXE4p9TW1GPiTssvLvBsbQLwcMX9lWlemQTwc0lLJM1K814SEY+m6f8DXlJMaNvoK64yvs6npmZ4F2pLN41SxClpEvA6YCGt9Zra1gr/H9X5XsrDV8kO9Dal++OBtRUHPXm/FpOBPwHfUdZN7HxJY2jiaxARq4D/AB4iK+w8CSyhua9DrzLlkb8n+6WsqP1bImk6sCoillU91Nf/peH/L0mfl/Qw8C5gdrP3X6We92Yz37NFxVDk57JMucrqVIZckuIoUz4B55R69t1MbZtfuooOwAbt4IhYJenFwHWS/qfywYgISdHHuoUpa1zJN4F/Iyue/Rvwn2RJuHCSxgI/Aj4aEU9lDR8yJX9NrWSKei9JOgZ4LCKWSHpzHvuoQxdZ09zTImKhpK+RNcfdLO/PUyocTycrNq0FfkgDfh0criLziKRPAT3A94rYfyeS9Avg/6vx0KeAT5J1Jyhk/xHxk4j4FPApSWcCpwKfbXYMaZlc35v1xGBb8zFPuRSdSwaKoVn5pJ440jLOKSXWbvnFBZ6trSLrM9prYppXGulXYCLiMUlXkjVx+6Ok3SLi0dSE7LFCg9yir7hK9TpHxB97pyX9F3B1ultonJK2Jzsh/15E/DjNbonX1Goq7H80yPdSox0EHKts8PIdgB2Br5E1ee1KrVfyfi1WAisjYmG6fwVZgaeZufOvgQci4k8Akn5M9to083XoVXgekfQe4BjgsIjoPahyHstZRPx1rfmSXkNWfFyWir8TgVslHUDf/5dVwJur5t84lP3X8D1gAdkJWcP2X08MQ3hvDvo9O4jXoVJDY2jQfvNWeK6y2orOJf3FUENu+aSeOJxTBr3vZmnb/OIuWltbBExVdlWTkcAMoLvgmDaTNEbSC3unyarjd5LFODMtNhMoS6W2r7i6gZPTKOVvAJ6saCLXdFX9Kt9O9ppCFucMSaMkTQamAr9vUkwiGy/k7oj4SsVDLfGaWk2F5JchvJcaKiLOjIiJETGJ7DnfEBHvAn4JHJ/3/lMM/wc8LOmVadZhwF00N3c+BLxB0gvS/6Q3hqa9DhUKzSOSjiLrsndsRDxbFVchObfTRcQdEfHiiJiUPqsryQZn/z/6fl9cCxwhaefUQu2ING9IJE2tuDsd6G2h3JT9pxgG+95sZl4vKoYij419zNNiypBLoBz5JMXhnFJbGc652ze/RAlGei7TjWzk7P8lG9n7U0XHUxXbnmSjjC8DlvfGRzaexfXAvcAvgF0KiO37ZONKPE+WzE/pKy6yUcnPS6/xHVSM6F5QnJekOG4n+1DvVrH8p1Kc9wBHNzHOg8m6jN0OLE23t5bxNfVtUP/XpueXwb6Xco7lzWy5itaeZAcSK8i6K43Ked/7AovT6/DfZFfJaOprAPwr2UHmnSnvjMr7dSg6N/ex/xVk/dt734/fqli+kJzr2zb/twfZcuWbPt8XZN2ZV6Tbe4e5zx+lz8btwFXAhGbuP21v0O9NGpzXyX5oWglsAP4IXNvsGGrElPt3V9G5yrd8bkXkkrS9wvNJ2qZzSt9xNe2YuNPyi9ITMTMzMzMzMzOzFuUuWmZmZmZmZmZmLc4FHjMzMzOz/7+9e4+3oqz7//96yxZUSFGsfgYmGGhhqSlq3VpZpmJ3SX7zgJWHbsv6lnYwu9PbOyKrb1rd2kHvitQ8paSUuVMTLTXLPIBn0UwUTMgyEUkw0A2f3x9zbRgWa+299t7rMGuv9/PxWA9mzVwz8xn2Wte65jPXXGNmZtbinOAxMzMzMzMzM2txTvCYmZmZmZmZmbU4J3jMzMzMzMzMzFqcEzxmZmZmZmZmZi3OCR4rFEmfkHR0jbd5mKRHJN1cy+2aWd9JGinpk/1cd1dJ7+nHemMlfbA/+6ywvX0lXTPAbdwiaVKtYjIbzCR9Ov2O/7QAsSyUtHXRtlVm25+VtFk9tm1mIOl0Se/u4zqTJH2vj+v0u91k7ckJHiuUiPhhRFxc480eB3wsIt5Z4+2aWd+NBPrbUNkV6HOCBxgL1CzB01eSOpq1b7NB4pPA/hHxod4K+vsGkoYAnwWc4DGrk4iYFhG/qba8pI6ImBsRn+7jrkbS/3aTtSEneKxPJH1J0qOS/iDpckkn569ES9pa0sI0faykX0i6XtJjkr6Z285ySV+XdL+kOyS9Os2fLunkNH2LpDMl3SXpz5LeluZvJukKSQ9LukrSnZWuhEuaBuwDnC/pW5I2kfQTSQ9KulfSO/u6TTMbkDOA10m6L30nvyBpjqQHJH0FQNIhkn6rzDbp+/9a4HTgiLTuEeU2Lukdafl96Tv+irTPt6V5n0s9en4v6Z70+re07r6p3pkl6U+SfipJadnkNO8e4P/k9renpNvTvv4oacc0/1hJnZJuAn4raVNJM1MvhKuATev3X2w2eEj6IbA98GtJp0m6ILUL7pU0JZUp/b711P74gaS5kuZ11zlp/kJJX0l1woOSXp/mj5J0Qyp/HqDcOh9Osdwn6UeShkg6OFcHPSppQS+HeGKZfa5tC6X3D0kaW2mfaf5ySf8j6X7gNOA1wM1KvZcrHbeZrU/ScEnXKjtHeUjSF3Pf6QclRSp3oaRD0/R7UhvhbknfU+rlm77Ll0i6DbhEuR7A5dorynoFdc9bLOknlLSbKsS8r6RbU9yPSvqhpI3Ssg2++8p6EpU7pl2VnZc9oOx8aMs0/9PKzpEekDSzrn8AG7iI8Muvql7AHsB9wCbAK4DHgJOBW4BJqczWwMI0fSzwBLBFWudJYNu0LID3pelvAv+dpqcDJ6fpW4D/SdPvAX6Tpk8GfpSm3wh0de+/Qtz5+D4PXJCmXw/8JcXWp2365Zdf/XuR9aZ5KE0fAMwgO2HaCLgGeHtadilwQpp3ZJp3LHBOL9v/FbB3mh4BdAD7AtfkymwGbJKmJwBz0/S+wDJgTIrndrIE8SbAU6msgCu6twdsDnSk6XcDP8/FugjYKr0/KVf37Ow6xi+/qn8BC1P74v8BH07zRgJ/BoaX+b4dS+X2R3eZIal9sHNuHyem6U8C56Xp7wHT0vS/k7VftgbekOqbjdOy/wWOLon7CuBTvRxXuX1OJ7WF0vuHyOrOivtMcR1e+n+We1/2uP3yy6/1X8AHgB/n3m+Rm/4W8K00fSFwaK6NMC7NvzzXRpgO3A1smt7vm1u2QXslt5+RwIPA7uTaTT3EvC+wkiwZPgS4ETg0Levxu19yTA8A70jT4ImlBQAAWg5JREFUpwPfSdN/BYZ1x9bsv5FfPb/cg8f6Ym/g6ohYGREvkFVMvfltRCyLiJXAw8B2af5LZCdukFV8Yyus/4syZfYBZgJExENklVG19iE7cSQi/kTW6NthgNs0s/45IL3uBe4hS7pOSMtOBE4FVkXE5X3Y5m3AWZI+TdYI6SpTZmPgx5IeBK4EJuaW3RURiyJiDVlCe2yKa0FEPBZZ6+bSXPktgCslPQScDeyUW3ZjRDyXpt/OurrnAVzHmPXHAcApku4jO1HZBHhtWpb/vkHl9sfhynri3Uv2fc1//8u1OfLf3WuBpWn+fmQnX3NSPPuRnVwBIOk/gX9FxLm9HFO5fVbS0z5XAz/vYd2ejtvM1nkQ2F/ZXQRvi4hlAMp6Du8GnFJS/vXAExHR3VuvtM3SGRH/KrOfsu0VSSKrc86KiLv7EPddEfFERKxOMeyT5lf87uePSdIWKY7fpcUXkdV/kLVZfirpw2QXqKzA2v4+ZauJLtbd7rdJybJVuenVrPvMvZxOlErnl1pVRRkza00CvhERPyqzbAywBni1pI1SwqVXEXGGpGvJev3dJunAMsU+B/wd2IWs7lqZW1apzqrkq8DNEXFIuoXiltyyFdXEbGZVE/CBiHh0vZnSXmz4fdvguyxpHFmP3T0iYqmkC1m/3dKXNoeAiyLi1A0WZAOvHsa6k6OelNtnvl1FLsaK+wRWphO7DQPt/bjNLImIP0vajawd8TVJvyVLxE4n62Vc9nvWg7JtgXLtlXTxeTqwKCJ+0tfQS9/39N2X9EZyx5TllSr6d7L67H3AaZLeVOECmhWAe/BYX9wGvE/ZODYjgPem+QvJrihB1lWxEXEcDiBpIvCmPqz7e+BDad0dyK78PTrAbZpZ9V4gu8UTYDbwH6k+QdJoSa9SNkjqBcCRwCNktzeVrluWpNdFxIMRcSYwh+zKWul6WwBPp6TRUWTdlnvyJ2CspNel90eWbGtxmj62h23cShroOTWqdu5ln2a2odlkY9Z0j4315j6uvznZydYyZWP/HVTFOvnv7kHAlmn+b4FDJb0qLdtK0naStgPOBQ6rcNW+GgvJrqqTTjTH9bTPCtvI13v9OW6ztiTpNcCLEXEp2e1Lu5H1iDk6Iv5RZpVHge3TRR6AsmMEltnPBu0VSe8ju907PxBzr22fZE9J49LYO0cAf6DCd1/SyNJjSj2VliqNeUrWPvpd2t62EXEz8EWyds+Iao7RmsM9IqxqETFHUidZN72/k3VhXAZ8G7hC0vHAtQ0I5X+BiyQ9THbiNS/FUe26P0i3ZnQBx0bEKkkD2aaZVSkilki6Ld3S9GvgMuD2dL62HPgw8Ang9xHxB2UDhs5JV7luZt3tGd+IiJ+V2cVnlQ2evobse/zrNL06betCsnrg55KOBq6nl542EbGyu36T9CJZori7sfVNsrrjv+m5/vsB8BNJj5AlrfrS7drMMl8FvgM8kE46FrDuYlOvIuJ+SfeS/c4/RXZxpzdfAS6XNA/4I9nYfUTEw+l7f0OK5WXgU8CBwCjgl6le+2tE9PXpfz8Hjk77vJNsrKGe9vlkmW3MAK6X9NeIeGc/jtusXb0J+JakNWTfsWuAd5Hd2g1AROzaXTgi/qXsMebXS1pBlqypRrn2yvXAaOCutK/OiJiWbzdFxBcqbG8OcA4wnqy9dFVErKnw3Z9Cdttq6TEdA/xQ0mZk45h9hOwi2KXpFi4B34uI56s8RmsCrbtLxqx3kkZExPL0xb8VOD4i7mlwDEPIBhhcma6o/wbYMSJeKtI2zczMzMxscMudH4msB99jEXF2A/e/L9nA7FUnvG3wcg8e66sZ6RamTcjuA29ocifZjOzRnxuTZZI/WYNETD22aWZmZmZmg9vHJB0DDCUbzLjc2IJmDeEePDZoSLoTGFYy+6iIeLAZ8ZhZ/Uj6CPCZktm3RcSnmhGPmVklkq5i3Tg63b4YEbObEY+ZtSZJbwIuKZm9KiL2akY8VkxO8JiZmZmZmZmZtTg/RcvMzMzMzMzMrMU5wWNmZmZmZmZm1uKc4DEzMzMzMzMza3FO8JiZmZmZmZmZtTgneMzMzMzMzMzMWpwTPGZmZmZmZmZmLc4JHjMzMzMzMzOzFucEj5mZmZmZmZlZi3OCx8zMzMzMzMysxTnBY2ZmZmZmZmbW4pzgMTMzMzMzMzNrcU7wmJmZmZmZmZm1uI5mB9BMG220UWy66abNDsNsUHjxxRcjIto+aex6xay2XLdkXLeY1Y7rlYzrFbPaKUq90tYJnk033ZQVK1Y0OwyzQUHSv5odQxG4XjGrLdctGdctZrXjeiXjesWsdopSrzQ9w2RmZmZmZmZmZgPjBI+ZmZmZmZmZWYtzgsfMzMzMzMzMrMU5wVNi7NixSGr4a+zYsc0+dDOrE9crZlYPrlvMrNZcr5i1trYeZLmcJ598koho+H4lNXyfZtYYrlfMrB5ct5hZrbleMWtt7sFjZmZmZmZmZtbinOAxMzMzMzMzM2txTvCYmZmZmZmZmbU4J3iqdP3117Pjjjsyfvx4zjjjjA2W33rrrey22250dHQwa9astfNvvvlmdt1117WvTTbZhF/+8pcNjNzMiqq3emXVqlUcccQRjB8/nr322ouFCxeuXfaNb3yD8ePHs+OOOzJ79uwGRm1mRdbf9grARRddxIQJE5gwYQIXXXRRo0I2sxbgcyGzFhERbfvabLPNolT2X7K+rq6u2H777ePxxx+PVatWxc477xzz5s1br8yCBQvi/vvvj6OOOiquvPLKDbYREbFkyZLYcsstY8WKFVXt16yVACuiAN/rZr9qWa+ce+658fGPfzwiIi6//PI4/PDDIyJi3rx5sfPOO8fKlSvjiSeeiO233z66urqq2q9Zq3HdUn3dMpD2ypIlS2LcuHGxZMmSeO6552LcuHHx3HPPVfqblJ1v1ipcr9S+zeJzIWt3RalX/BStKtx1112MHz+e7bffHoCpU6dy9dVXM3HixLVluh/tt9FGlTtFzZo1i4MOOojNNtusrvGaVesf3z+nqnKvPPGEOkfSfqqpV66++mqmT58OwKGHHsoJJ5xARHD11VczdepUhg0bxrhx4xg/fjx33XUXb33rW5txKDX/HDVre33ZppmkycB3gSHAeRFxRsnytwPfAXYGpkbErJLlmwMPA7+MiJp88AbSXpk9ezb7778/W221FQD7778/119/PUceeWQtQmu6ZtYDfdl3NVxPWaP5XMgGo8HaPvQtWlVYvHgx22677dr3Y8aMYfHixX3ezsyZMwdNQ8nMBqaaeiVfpqOjgy222IIlS5bUrE4ys/6RNAQ4FzgImAgcKWliSbG/AMcCl1XYzFeBW2sZ10DqBtcrZlaJz4XMWocTPA3y9NNP8+CDD3LggQc2OxQzMzMbmD2B+RHxRES8BMwEpuQLRMTCiHgAWFO6sqTdgVcDNzQiWDOzZvO5kFljFC7BI2mypEclzZd0SpnlwyT9LC2/U9LY3LKdJd0uaZ6kByVtUouYRo8ezVNPPbX2/aJFixg9enSftnHFFVdwyCGHsPHGG9ciJDNrcdXUK/kyXV1dLFu2jFGjRtWkTjKzARkNPJV7vyjN65WkjYD/AU6uouzxkuZKmtvV1dV7UAOoG1yvmFklPhcyax2FSvBU2eX5OGBpRIwHzgbOTOt2AJcCn4iInYB9gZdrEdcee+zBY489xoIFC3jppZeYOXMmBx98cJ+2cfnll7tLopmtVU29cvDBB699ks2sWbN417vehSQOPvhgZs6cyapVq1iwYAGPPfYYe+65ZzMOw8z67pPAdRGxqLeCETEjIiZFxKSOjt6HTRxIe+XAAw/khhtuYOnSpSxdupQbbrjBV9rNDPC5kFkrKVSChyq6PKf33c/unAXsJ0nAAcADEXE/QEQsiYjVtQiqo6ODc845hwMPPJA3vOENHH744ey0005MmzaNzs5OAObMmcOYMWO48sor+fjHP85OO+20dv2FCxfy1FNP8Y53vKMW4Zi1LEkLU++6+yTNbXY8zVRNvXLcccexZMkSxo8fz1lnnbX2saQ77bQThx9+OBMnTmTy5Mmce+65DBkypJmHY9Y0TapXFgPb5t6PSfOq8VbgBEkLgW8DR0va8JnD/TCQ9spWW23Fl770JfbYYw/22GMPpk2btnbAZbN25DbLOj4XMquNRtQryp7oVQySDgUmR8RH0/ujgL3yT5eQ9FAqsyi9fxzYC/gwsDvwKuCVwMyI+GZP+xs+fHisWLGiNAaa8X/SrP1ae6vl04okvRgRw3spsxCYFBHPVrXjFtSO9YqfomX11Fvd0ox6JfUa/jOwH1liZw7wwYiYV6bshcA1pU/RSsuOJYu91w9eO9YtteSnaFme2ywZ1yvWzmr9u1CUeqVoPXgGogPYB/hQ+vcQSfuVFurr/exmZmZmeRHRBZwAzAYeAa6IiHmSTpd0MICkPSQtAg4DfiRpg+SPmZmZWS0VLcFTTZfntWXSFbQtgCVkAxzeGhHPRsSLwHXAbqU76Ov97GZWtY7u5Gl6HV+mTAA3SLq7wvKGknSBpGdSz8Byyz8k6YHUlfKPknZpdIxm1mvd0pR6JSKui4gdIuJ1EfH1NG9aRHSm6TkRMSYihkfEqDQ+YOk2Lqym946Z1VzLtVnMrPAKUa8ULcMxB5ggaRxZImcq8MGSMp3AMcDtwKHATRERkmYD/ylpM+Al4B1kgzCbWWN0RcSkXsrsExGLJb0KuFHSnyLi1kYEV8GFwDnAxRWWLwDeERFLJR0EzCC7JdTMGqe3uqVo9YqZFV8rtlnMrNgKUa8UqgdPNV2egfOBUZLmAycBp6R1lwJnkSWJ7gPuiYhrG3wIZtaDiFic/n0GuIpsYPVmxnMr8FwPy/+Y6haAO8h6FZpZgRStXjGzwcF1i5nVWiPqlaL14CEiriO7vSo/b1pueiXZ/ezl1r2U7FHp/bbddtuRPZSrsbbbbruG79OskSQNBzaKiBfS9AHA6U0Oqy+OA37dnxVdr5jVxyCoVwbEdYtZfdSqbpE0GfguMAQ4LyLOKFk+jKwX8e5kQ04cERELJe0PnAEMJbsz4QsRcVNaZ3eyHsibkp0zfSbdzbAV8DNgLLAQODx3kapqrlfM6qNRbZbCJXiabeHChc0OwWywejVwVWo0dACXRcT1zQ2pOpLeSZbg2afC8uOB4wGGDh26wXLXK2Z107L1Si24bjGrmwHXLZKGAOcC+5ONFTpHUmdEPJwrdhywNCLGS5oKnAkcATwLvC8i/irpjWR3N4xO6/wA+BhwJ1mCZzLZBahTgN9GxBmSTknvv9jXA3e9YlY3DWmzOMFjZg0REU8ALTdIsaSdgfOAgyJiSbkyETGDbHwehg8f7md8mjVIq9YrZlZsNapb9gTmp20haSYwBcgneKYA09P0LOAcSYqIe3Nl5gGbpt4+WwGbR8QdaZsXA+8nS/BMAfZN61wE3EI/Ejxmre5bC56uqtyx9Q1jA41qszjBYzbIVFupQeMrtlYj6bXAL4CjIuLPzY7HzMzMWsZo4Knc+0Vs+KCGtWUiokvSMmAUWQ+ebh8gG1t0laTRaTv5bXb37Hl1RHQ3Av9G1ltgA731Ojaz1uYEj5m1LUmXk13t2lrSIuDLwMYAEfFDYBpZQ+t/U3fKakbHNzMzMxswSTuR3bZ1QF/WS2PylO1R7F7HZoObEzxm1rYi4sheln8U+GiDwjEzM7PBYzGwbe79mDSvXJlFkjqALcgGW0bSGLKn7BwdEY/nyuef6Jnf5t8lbRMRT0vaBnimlgdjZq2hUI9JNzMzMzMzGwTmABMkjZM0FJgKdJaU6QSOSdOHAjel3jcjgWuBUyLitu7C6Rasf0p6i7KuxUcDV5fZ1jG5+WbWRpzgMTMzMzMzq6GI6AJOIHsC1iPAFRExT9Lpkg5Oxc4HRkmaD5xE9uQr0nrjgWmS7kuvV6VlnyR7+MN84HGyAZYhe6z6/pIeA96d3ptZm/EtWmZmZmZmZjUWEdeRPco8P29abnolcFiZ9b4GfK3CNucCbywzfwmw3wBDNrMW5x48ZmZmZmZmZmYtzgkeMzMzMzMzM7MW5wSPmZmZmZmZmVmLc4LHzMzMzMzMzKzFOcFjZmZmZmZmZtbinOAxMzMzMzMzM2txTvCYmZmZmZmZmbU4J3jMzMzMzMzMzFqcEzxmZmZmZmZmZi3OCR4zMzMzMzMzsxbnBI+ZmZmZmZmZWYtzgsfMzMzMzMzMrMU5wWNmZmbWR5ImS3pU0nxJp5RZ/nZJ90jqknRobv6ukm6XNE/SA5KOaGzkZmZmNlg5wWNmZmbWB5KGAOcCBwETgSMlTSwp9hfgWOCykvkvAkdHxE7AZOA7kkbWNWAzMzNrCx3NDsDMzMysxewJzI+IJwAkzQSmAA93F4iIhWnZmvyKEfHn3PRfJT0DvBJ4vu5Rm5mZ2aDmHjxmZmZmfTMaeCr3flGa1yeS9gSGAo9XWH68pLmS5nZ1dfUrUDMzM2sfTvCYmZmZNZikbYBLgI9ExJpyZSJiRkRMiohJHR3udG1mZmY9c4LHzMzMrG8WA9vm3o9J86oiaXPgWuC0iLijxrGZmZlZm3KCx8zMzKxv5gATJI2TNBSYCnRWs2IqfxVwcUTMqmOMZtZkVTxtb5ikn6Xld0oam+aPknSzpOWSzsmVf4Wk+3KvZyV9Jy07VtI/css+2qjjNLPicILHzMzMrA8iogs4AZgNPAJcERHzJJ0u6WAASXtIWgQcBvxI0ry0+uHA24Fjcydiuzb+KMysnqp82t5xwNKIGA+cDZyZ5q8EvgScnC8cES9ExK7dL+BJ4Be5Ij/LLT+v5gdlZoVXuBu6JU0GvgsMAc6LiDNKlg8DLgZ2B5YAR0TEwpTxfgR4NBW9IyI+0bDAzczMrG1ExHXAdSXzpuWm55DdulW63qXApXUP0Myarden7aX309P0LOAcSYqIFcAfJI2vtHFJOwCvAn5fh9jNrEUVqgfPADPdAI/nstZO7piZmZmZWTNU87S9tWVSz8BlwKgqtz+VrMdO5OZ9QNIDkmZJ2rbcSn46n9ngVqgED7lMd0S8BHRnuvOmABel6VnAfpLUwBjNzMzMzMyaaSpwee79r4CxEbEzcCPrzpfW46fzmQ1uRUvwDDTTPU7SvZJ+J+lt5XbgrLWZmZmZmdVZNU/bW1tGUgewBdkQFD2StAvQERF3d8+LiCURsSq9PY9sOAszazNFS/AMxNPAayPizcBJwGXpMaTrcdbazLpJukDSM5IeqrBckr6Xnm7xgKTdGh2jmZmZtaRqnrbXCRyTpg8Fbiq55aqSI1m/9w6Stsm9PZhsbFIzazNFy3D0JdO9KJ/pTpXhKoCIuFvS48AOwNy6R21mrepC4ByygdvLOQiYkF57AT9I/5qZmZlVFBFdkrqftjcEuKD7aXvA3IjoBM4HLpE0H3iOLAkEgKSFwObAUEnvBw6IiO4Bmg8H3lOyy0+np/h1pW0dW69jM7PiKlqCZ22mmyyRMxX4YEmZ7kz37eQy3ZJeCTwXEaslbU92QvZE40I3s1YTEbemJ/BVMgW4OCWQ75A0UtI2EfF0YyI0MzOzVlXF0/ZWAodVWHdsD9vdvsy8U4FT+xurmQ0OhUrwDDDT/XbgdEkvA2uAT0TEc40/CjMbRCqNC+YEj5mZmZmZFUqhEjzQ/0x3RPwc+HndAzQzKyHpeOB4gKFDhzY5GjMzMzMza0eDaZBlM7Naq2ZcMA/ebmZmZmZmTecEj5lZZZ3A0elpWm8Blnn8HTMzMzMzKyJfajaztiXpcmBfYGtJi4AvAxsDRMQPyW4XfQ8wH3gR+EhzIjUzMzMzM+uZEzxm1rYi4shelgfwqQaFY2ZmZmZm1m++RcvMzMzMzMzMrMU5wWNmZmZmZmZm1uKc4DGzhpI0RNK9kq5pdixmNji4XjGzWnO9Ymb1UO+6xQkeM2u0zwCPNDsIMxtUXK+YWa25XjGzeqhr3eIEj5k1jKQxwL8D5zU7FjMbHFyvmFmtuV4xs3poRN3iBI+Z1UqHpLm51/FlynwH+E9gTWNDM7MW1lvd8h1cr5hZ37heMbNaK8S5kB+Tbma10hURkyotlPRe4JmIuFvSvg2LysxaXcW6xfWKmfWT6xUzq7VCnAu5B4+ZNcrewMGSFgIzgXdJurS5IZlZi3O9Yma15nrFzOqhIXWLEzxm1hARcWpEjImIscBU4KaI+HCTwzKzFuZ6xcxqzfWKmdVDo+oWJ3jMzMzMzMzMzFqcx+Axs4aLiFuAW5ochpkNIq5XzKzWXK+YWT3Us25xDx4zMzOzPpI0WdKjkuZLOqXM8rdLukdSl6RDS5YdI+mx9DqmcVGbWSNVUU8Mk/SztPxOSWPT/FGSbpa0XNI5JevckrZ5X3q9qqdtmVl7cYLHzMzMrA8kDQHOBQ4CJgJHSppYUuwvwLHAZSXrbgV8GdgL2BP4sqQt6x2zmTVWlfXEccDSiBgPnA2cmeavBL4EnFxh8x+KiF3T65letmVmbcQJHjMzM7O+2ROYHxFPRMRLZE/DmJIvEBELI+IBYE3JugcCN0bEcxGxFLgRmNyIoM2soXqtJ9L7i9L0LGA/SYqIFRHxB7JET7XKbqv/4ZtZK3KCx8zMzKxvRgNP5d4vSvNquq6k4yXNlTS3q6urX4GaWdNU811fWyYiuoBlwKgqtv2TdHvWl3JJnP5uy8wGESd4zMzMzAooImZExKSImNTR4edimBmQ3Z71JuBt6XVUX1Z24thscHNrwczMBrU/Pv9C1WVL+86bVbAY2Db3fkyaV+26+5ase0tNojKzIqmmnugus0hSB7AFsKSnjUbE4vTvC5IuI7sV7OJqtxURM4AZAMOHD4++H5aZFZl78JiZmZn1zRxggqRxkoYCU4HOKtedDRwgacs0uPIBaZ6ZDS7V1BOdQPeT9A4FboqIikkXSR2Stk7TGwPvBR7qz7bMbHByDx4zMzOzPoiILkknkCVmhgAXRMQ8SacDcyOiU9IewFXAlsD7JH0lInaKiOckfZXs5A/g9Ih4rikHYmZ1U009AZwPXCJpPvAcWRIIAEkLgc2BoZLeT5YMfhKYnZI7Q4DfAD9Oq1Tclpm1Dyd4zMzMzPooIq4DriuZNy03PYfsloxy614AXFDXAM2s6aqoJ1YCh1VYd2yFze5eoXzFbZlZ+/AtWmZmZmZmZmZmLc4JHjMzMzMzMzOzFucEj5mZmZmZmZlZi3OCx8zMzMzMzMysxRUuwSNpsqRHJc2XdEqZ5cMk/Swtv1PS2JLlr5W0XNLJDQvazMzMzMzMzKyJCpXgkTQEOBc4CJgIHClpYkmx44ClETEeOBs4s2T5WcCv6x2rmZmZmZmZmVlRFCrBA+wJzI+IJyLiJWAmMKWkzBTgojQ9C9hPkgAkvR9YAMxrTLhmZmZmZmZmZs1XtATPaOCp3PtFaV7ZMhHRBSwDRkkaAXwR+EpPO5B0vKS5kuZ2dXXVLHAzaz1V3BL6Wkk3S7pX0gOS3tOMOM3MzMzMzHpTtATPQEwHzo6I5T0ViogZETEpIiZ1dHQ0JjIzK5wqbwn9b+CKiHgzMBX438ZGaWZmZmZm7UbSppJ27Ot6RUvwLAa2zb0fk+aVLSOpA9gCWALsBXxT0kLgs8B/STqhzvGaWeuq5pbQADZP01sAf21gfGZmZmZm1mYkvQ+4D7g+vd9VUmc16xatC8scYIKkcWSJnKnAB0vKdALHALcDhwI3RUQAb+suIGk6sDwizmlE0GbWksrdErpXSZnpwA2STgSGA+9uTGhmZmZmZtamppNdjL4FICLuSzmSXhWqB08aU+cEYDbwCNmtEfMknS7p4FTsfLIxd+YDJwEbjJthZlYjRwIXRsQY4D3AJZI2qDc9tpeZmZmZmdXIyxGxrGReVLNi0XrwEBHXAdeVzJuWm14JHNbLNqbXJTgzG0yquSX0OGAyQETcLmkTYGvgmXyhiJgBzAAYPnx4VZWvmZmZmZlZGfMkfRAYImkC8Gngj9WsWKgePGZmDbT2llBJQ8luCS29t/UvwH4Akt4AbAL8o6FRmpmZmZlZOzkR2AlYBVxG9uTwz1SzYuF68JiZNUJEdKWB2GcDQ4ALum8JBeZGRCfweeDHkj5H1i3y2DTml5mZmZmZWT38e0ScBpzWPUPSYcCVva3oBI+Zta0qbgl9GNi70XGZmZmZmVnbOpUNkznl5m3ACR4zMzMzMzMzsyaSdBDZg11GS/pebtHmQFVPcnGCx8zMzMzMzMysuf4KzAUOBu7OzX8B+Fw1G/Agy2ZmZmZmZjUmabKkRyXNl3RKmeXDJP0sLb9T0tg0f5SkmyUtl3ROrvxmkq6V9CdJ8ySdkVt2rKR/SLovvT7akIM0s5qJiPsj4iJgfERclHv9IiKWVrMNJ3jMzMzMzMxqSNIQ4FzgIGAicKSkiSXFjgOWRsR44GzgzDR/JfAl4OQym/52RLweeDOwd7qlo9vPImLX9DqvhodjZo01VtIsSQ9LeqL7Vc2KTvCYmZm1gdUvr2l2CGZm7WRPYH5EPBERLwEzgSklZaYAF6XpWcB+khQRKyLiD2SJnrUi4sWIuDlNvwTcA4yp50GYWVP8BPgB2bg77wQuBi6tZkWPwWNmZjaILVm8nF+dcz8rnl/FiJHDeO+JuzDqNSOaHZaZ2WA3Gngq934RsFelMhHRJWkZMAp4treNSxoJvA/4bm72ByS9Hfgz8LmIeKrMescDxwMMHTq02mMxs8baNCJ+mxK+TwLTJd0NTOttRffgMTMzG8R+dc79rFi6CgKWL13FNd+/v9khmZnZAEjqAC4HvhcR3bdt/AoYGxE7AzeyrmfQeiJiRkRMiohJHR2+1m9WUKskbQQ8JukESYcAVV2dq0uCR9Le1cwzMzNrN428VWr1y2tY8fyq9eYtf36Vb9eqgQEMnrqxpIskPSjpEUmnNjx467NqvzPN+m75O11Ii4Ftc+/HpHlly6SkzRbAkiq2PQN4LCK+0z0jIpZERHeFfx6we//CNrMC+AywGfBpsu/yUcDR1axYr7Tt94HdqphnZmbWFppxq9SQjTdixMhhLF+6LskzYuQwhmzsDrwDkRs8dX+y2y7mSOqMiIdzxdYOnippKtngqUcAhwHDIuJNkjYDHpZ0eUQsbOxRWDWq/d4261ZI34JZaHOACZLGkSVypgIfLCnTCRwD3A4cCtwUEdHTRiV9jSwR9NGS+dtExNPp7cHAIwM+AjNrioiYkyaXAx9J7Y6pwJ29rVvTFp6kt0r6PPBKSSflXtOBIbXcl5mZWStp1q1S7z1xF0ZsOQwEI7bMTgBtwPo9eCoQwPB0tX5T4CXgn40J2/qq2u9tX7/fq9eoofFZ40VEF3ACMJss2XJFRMyTdLqkg1Ox84FRkuYDJwFrewNKWgicBRwraZGkiZLGAKeRPZXrnpLHoX86PTr9frKr/sfW/yjNrJYkbS7pVEnnSDpAmROA+cDh1Wyj1j14hpLdG9YBvCI3/59kWWkza4auNdDhK/bWulavEUM26vGiZlbu5TWF7J3S061S9Y531GtGcMw39i7s/02LGsjgqbPIkj9Pk3W//lxEPFf3iK3Pqv3e9uX7vWzlMG598rX8q6uDTTu6ePt2f2GLTdZft9bxWfNExHXAdSXzpuWmV5L16iu37tgKmy2bHYyIUwHf8mlWTuucC10CLCXr1fdR4L/IvvOHRMR91WygpgmeiPgd8DtJF6bRns2sifSPlQy78im0vIsY0cGqw15LvHJYj+tUeyJt1gjVngwV/TaFItwq5RO+wtgTWA28BtgS+L2k3+QGSl3LT7upr95+76r93vbl+91dn4H4V1cHtz75Wt6342P9irEI9YqZWZH19VyoAOdB20fEmwAknUd2Mei1KRlclXr9AgyTNEPSDZJu6n7VaV9mVsGwK59CL3ShAL3QxbAr/1Kx7LKVw/jVoxP4+SOv51ePTmDZyp4TQWa10NvAoOVOhspphdsUfKvUoDKQwVM/CFwfES9HxDPAbcCkcjvx027qoy+/d9V+b6spt3qN1tZnmex9udu1qo2xr/WKB2M2s3ZS7blQgc6DXu6eiIjVwKK+JHegfoMsXwn8kGwE99V12oeZ9aRrDVrelWtGAi90Veyi2NerimYDUU2Pm55OhvJXV/p7m0KEkBp3laavt0rVupzVVL8HT5X0F+BdwCWShgNvAb7TqMCtb7931X5vqyk3ZKNg046uXL2WvS93tbjaGKuNr+i9HM3Maq4P50IFOg/aRVL3uHwCNk3vBUREbN7bBuqV4OmKiB/UadtmVo2OjYgRHfBCF92jesYrOsomd6o9kTarVm+fnbU9bljX4+aYb+y9XplqT4b6epvCyy9vyrPP7sjqNUMZstFLbL31o2y88b/6d6A51SZaeitT9Kf22NoxdboHTx0CXNA9eCowNyI6yQZPvSQNnvocWRIIsqdv/UTSPLIP9k8i4oHGH8Xg1dN3sb+/d9UmUXsr9/bt/rLBbae1iLG3/VZT55qZDSpVngsV6TwoIgb8YKp6JXh+JemTwFXA2ha3BxE0a6xVh70264qYu++0nL5cVbT21lsSo5oxc3rrcfPH519YO3/zrR7hpVwyZvOtHuWPz2fJmPwji9574i5c8/37WZ5LdlTSndwBsXrNUJ59dke22ea+fh9zrRMt1Z6I+YStufo7eGpELC833waup+9ivl4ZstFLa+sACIZs9BJ3/nPdg8xKH4dWS1tssor37fhYz8maGv8mezBmM2tX1ZwLDbbzoHoleI5J/34hNy+A7eu0PzMrI145jJWfnFDVyPHVXFUcCEmbALcCw8jqnlkR8eWa7sTqptokRjVdXPvS42bjjf/FNtvc1+vtVNXephCh3IkddCd5ym2/2mOuZaKlHk/tGcxcr/SunT4T1X4Xt9760Q168TVabycOtfxNLspgzLX+LNbzs+26xWxwqPZcqN7nQdC4eqUuCZ6IGFeP7ZpZP1XxWMBqrioO0CrgXRGxXNLGwB8k/Toi7qjHzqy2qjlx6ksX1770uAGqHiunt8a+FGWv3pfbflXHXONESz2e2jPIuV6poN1u4evLd7HaxHEz1fo3ua91bi3V+rPYoM+26xazwaSXc6EGnAdBg+qVurQEJR1d7lWPfZlZbdWrUovM8vR24/QqZsva1tPTiVNedxfXdX/Wyl1cu3vcfOJ7+3LMN/Zu6Inn1ls/ypCNXqI7uVPu6n3Vx5wSLXkDTbTU8qk9g53rlcpa4cly3WrxZKf+fBeLmtzJq9Vvcn/q3Fo9cavWn8VGfLZdt5i1p3reltWXekXSmdXMK6det2jtkZveBNgPuAe4uE77M7Pm65A0N/d+RkTMyBeQNAS4GxgPnBsRdzYyQOufvvQW6WsX12b0OKnm6n1fjrnWV8Zr+dSeQaLHusX1yoZa5Ra+WvfEaGYvlVZRzd+/ln+XWn8Wa7g9t1nMrNZqWa/sD3yxZN5BZeZtGET18VYvIk7Mv5c0EphZj32ZWWF0RcSkngpExGpg11QnXCXpjRHxUEOiswGp9sSpQV1ca6K3q/fVHnO9Ei21emrPINBj3eJ6ZUP1voWvVp/1vo5f5aRnY9RyXLFafxZruD23Wcys1gZcr0j6v8Ange0l5Z+w+QrgtmqCqFcPnlIrAI/LY2YARMTzkm4GJgNuLBVArU+cip7cqUafj9knlE3lemV99ejN0qyeHX3dr7+L/VeP3l+1/iw2uqeW6xYzq7Ue6pXLgF8D3wBOyc1/odonktclwSPpV6y7n2wI8Abginrsy8xag6RXAi+nCm1Tsq6HVd1LavXjE6feteMxtwrXK5XVozdLs3p21HK/1rN69P6q9WexET21XLeYWa1VU69ExDJgGXCkpH2ACRHxE0lbSxoXEQt620+9evB8OzfdBTwZEYvqtC8zaw3bABele083Aq6IiGuaHFPb84mTtTjXK72o5W1ZzejZ0YzxhL614Omqyn1h3DZ12X+z1auHTK3/XnVOvrtuMbNaq7pekfRlYBKwI/ATYChwKdBrI71eY/D8TtKrWTfY8mP12I+ZtY6IeAB4c7PjGAxqdWLTKgOxmlXieqVxmtWzo97jCdmGPJaR6xYzq70+1iuHpLL3pHX/KukV1axYr1u0Dge+BdwCCPi+pC9ExKwq1p0MfJfs1q7zIuKMkuXDyJ7GtTuwBDgiIhZK2hPoHqVawPSIuKpGh2TWMna49MLqC4+sqp6wgqj1E2d84mRmfdGsnh1+OlZz+LfAzFpR1edCxT4PeikiQumJIJKGV7tivW7ROg3YIyKeSQG9EvgN0GOCJ3VXOpfsfrRFwBxJnRHxcK7YccDSiBgvaSrZfWtHkA1ONCkiuiRtA9wv6VcR0VXrgzMza4Z63E7lEyczq1azena4R4mZmbWZKyT9CBgp6WPAfwA/rmbFeiV4NupO7iRLyO4z682ewPyIeAJA0kxgCpBP8EwBpqfpWcA5khQRL+bKbMK6QZ7NzFpevW6n8omTmfVVs+oK11FmZtYOIuLbkvYH/kk2Ds+0iLixmnXr9Ut5vaTZko6VdCxwLXBdFeuNBp7KvV+U5pUtk3rnLANGAUjaS9I84EHgE+V670g6XtJcSXO7uvrfuWf1y2v6va6ZFYOkyZIelTRf0ikVyhwu6WFJ8yRd1ugYu3XfTpVXy9upfOJkZm7bmFm1XF+Y1VdE3BgRX4iIk6tN7kCNe/BIGg+8OiK+IOn/APukRbcDP63lvsqJiDuBnSS9gWyE6l9HxMqSMjNIY/UMHz68z718aj0GhtlAuNdF/1VzS6ikCcCpwN4RsVTSq5oTbca3U5lZPbhtY1YfAxhbdBTZnQp7ABdGxAm5dXYHLgQ2JbuA/pk0VsdWwM+AscBC4PCIWFrrY3J9YUUyWM+FJL3AhnckLQPmAp/vvuOpnFrfovUdspMhIuIXwC9SgG9Ky97Xy/qLgW1z78ekeeXKLJLUAWxBViGuFRGPSFoOvJHsP6Fm/EhhKwL/uNZENbeEfgw4t7uBVHLracP5dqr1Vfso4x3qHIdZq3Pbxqz2Bji26ErgS2TnMm8s2fQPyNond5IleCYDvwZOAX4bEWekXsmnAF+s9XG5vrAiaINzoe+Q1RuXkT1AairwOrKnal0A7FtpxVqfIbw6Ih4snZnmja1i/TnABEnjJA0lO5DOkjKdwDFp+lDgppS1HpcSPkjaDng9Wfa6ZnoaA8Oskdb+uMa6H1frs2puCd0B2EHSbZLuSFfiNlCrWz+r5eSOmdWK2zZmdbP2QlJEvAR0X0jKmwJclKZnAfulsUVXRMQfyBI9a6UHyWweEXdERJD1/nl/mW1dlJtfM64vrCja4Fzo4Ij4UUS8EBH/THchHRgRPwO27GnFWp8ljOxh2aa9rZzGzDkBmA08AlwREfMknS7p4FTsfGCUpPnASWTZachuB7tf0n3AVcAnI+LZfh1FBfUeA8OsGv5xbagOYAJZlvxI4MeSRpYWiogZETEpIiZ1dNRr7Hozs9qrZ9vGv0vW5gY0tmgP21xUYZuvjojurq1/A15dbgMDuSjlcyErgjY5F3oxjQO6UXodzrqEb4/DzNT62zg3PcZrPZI+CtxdzQYi4rqI2CEiXhcRX0/zpkVEZ5peGRGHRcT4iNiz+/aKiLgkInaKiF0jYreI+GXtDmud9564CyO2HAaCEVt6DAyrj54qKP+41kw1t4QuAjoj4uWIWAD8mSzhY2Y2aNS6bbNk8XIuPPU2fvjpW7jo1NtY8tflNYrUzKqReveUPQkc6EUpnwtZI/hciA8BRwHPAH9P0x+WtClZh5iKan2p+bPAVZI+xLqEziRgKHBIjffVFB4Dw+qp2vtJPdhuTay9JZQssTMV+GBJmV+S9dz5iaStyW7ZqjiomZlZK6p128ZjdJgBNRpbtEz5MRW2+XdJ20TE0+lWrrqMG+hzIasnnwutHb/rkxFRafziP/S0fk0TPBHxd+DfJL2TdQOCXRsRN9VyP0XgCs3qodpGsX9cBy4iuiR13xI6BLig+5ZQYG7qNTgbOEDSw8Bq4AsR0VPDy8ysZdXqtqxKXef9ezU4+W9bUTUXkrrHFr2d3NiilTaYkjf/lPQWskGWjwa+X7KtM9K/V9fwWDbgv7nVg8+FICJWS9qn95Ll1WWwiIi4Gbi5Hts2G6z60ygebBVao0XEdWRPoMjPm5abDrKxvk5qcGhmZi2pu+v88qXrfs8GYdd5oy2eYjMgVV5IOh+4JI0t+hxZEggASQuBzYGhkt4PHJCewPVJ1j0m/dfpBVli5wpJxwFPAofX/SDNasjnQuu5V1IncCWwontmelJ5jzwaqFlBuFFsZmaDwWDuOm/r+Fa83lVxIWklcFiFdcdWmD+XDR+dTuphvN8AwjVrKp8LrWcTsts135WbF4ATPGatxI1iMzNrdYO567xlfCuemdWDz4UyEfGR/q7rBI9ZgTS6UfzH51+oqtyUOsdhZtZqJE0Gvkt268V5EXFGyfJhwMXA7mRX4Y6IiIVp2c7Aj8huv1gD7JGu5A8qjfgd+9aCp3svRDZCvtWOr7SbWT34AkFG0ibAccBOZL15AIiI/+htXSd4zAqonSs0M7OiS0+4OBfYH1gEzJHUmcbH6HYcsDQixkuaCpwJHJGelHMpcFRE3C9pFPBygw/BbMB8pd3M6qVIF7qhKRe7LwH+BBwInE722PRHqlnRCR4zs4Jo96sVZi1kT2B+RDwBIGkmWfsvn+CZAkxP07OAcyQJOAB4ICLuh7XjZpi1nHpdafdvoZm1K0kdEdEFjI+IwyRNiYiLJF0G/L6abTjBY2bWZH4SiVnLGQ08lXu/CNirUpn0NJ1lwCiyu4VC0mzglcDMiPhm/UM2q49aJWP8W2hmxl3Abqzr2fu8pDcCfwNeVc0GnB43M2uytU8iiXVPIjGzQasD2Iesu/U+wCGSyj75RtLxkuZKmtvV1dXIGM0azr+FZmZrzZC0JfDfQCdZD+Ezq1nRPXjMzJrITyIxa0mLgW1z78ekeeXKLErj7mxBNtjyIuDWiHgWQNJ1ZFfrflu6k4iYAcwAGD58eNT4GMwKw7+FZmYAvErSSWm6+0la56Z/h1ezAdeYZmZN1P0kkjw/icSs8OYAEySNkzQUmEp2hS2vEzgmTR8K3BQRAcwG3iRps5T4eQfrj91j1nb8W2hmBmRP5hwBvCL3GpF79co9eMzMmsxPIjFrLWlMnRPIkjVDgAsiYp6k04G5EdEJnA9cImk+8BxZEoiIWCrpLLIkUQDXRcS1TTkQswLxb6GZGU9HxOkD2YATPDZouBuvtSo/icSs9UTEdcB1JfOm5aZXAodVWPdSskelm1lSr99Cs3bh786goIFuwAkea3l+6oINFn4SiZlZ6/jWgqerKndsfcMYdHyCatY3bvcNKmUfutAXrkGt5fmpC2br83fCzMzMrD243Td4RMRzA92GEzzW0np66oJZO/J3wszMzKw9uN1npZzgsZbmpy6Yrc/fCTMzM7P24HaflfJf3lree0/chRFbDgPBiC1r+9QFZ7+tFdXzO2FmZmZmxeFzIcvzIMvW8urx1AUPVmatzE8iMTMzM2sPPheyPLf8bdCo5YmsByuzwcDJHTMzM7P24HMhAyd4zDbgwcrMzMzMzKwd+VyotTnBY1ainoOVuWI0MzMzaw+SJkt6VNJ8SaeUWT5M0s/S8jsljc0tOzXNf1TSgWnejpLuy73+Kemzadl0SYtzy97TqOO0wcXnQq3NY/CYlfHeE3fhmu/fz/LcfacD4ftYzczMzNqHpCHAucD+wCJgjqTOiHg4V+w4YGlEjJc0FTgTOELSRGAqsBPwGuA3knaIiEeBXXPbXwxcldve2RHx7TofmrUBnwu1Lid4rC31NghZrQcrW3sfK+vuYz3mG3sPeLtmZmZmVkh7AvMj4gkASTOBKUA+wTMFmJ6mZwHnSFKaPzMiVgELJM1P27s9t+5+wOMR8WRdj8IGnWrOb3wu1Lqc4LG20tfsca26Ila6j9WD4JqZmZkNSqOBp3LvFwF7VSoTEV2SlgGj0vw7StYdXbLuVODyknknSDoamAt8PiKWlgYl6XjgeIChQ4f25XisxfWnF43PhVqP/0etrTRjRPh63sdqZmZmZu1F0lDgYODK3OwfAK8ju4XraeB/yq0bETMiYlJETOro8LX+dtKsJ2P5XKix/K22ttHM7HGt72M1s/r41oKnqyr3hXHb1DkSMzNrcYuBbXPvx6R55cosktQBbAEsqWLdg4B7IuLv3TPy05J+DFxTg2OwQaLZvWh8LtQ4hUvwSJoMfBcYApwXEWeULB8GXAzsTlYBHhERCyXtD5wBDAVeAr4QETc1NHgrtO7s8fKl6yq3RmWPa30fq5mZmZkV2hxggqRxZMmZqcAHS8p0AseQja1zKHBTRISkTuAySWeRDbI8Abgrt96RlNyeJWmbiOi+SnEI8FCNj8daWDPPg8DnQo1UqP/d3GjzBwETgSPTKPJ5a0ebB84mG20e4FngfRHxJrKK8pLGRG2t5L0n7sKILYeBYMSWjc8eu0IzMzMzG/wiogs4AZgNPAJcERHzJJ0u6eBU7HxgVBpE+STglLTuPOAKsgGZrwc+FRGrASQNJ3sy1y9KdvlNSQ9KegB4J/C5uh6gtZxmnweBz4UaoWg9ePo92nxE3JsrMw/YVNKwNPq8GeDssa2vtx6DuXIfIKtv9oiIuQ0M0czMzFpURFwHXFcyb1pueiVwWIV1vw58vcz8FWQDMZfOP2qg8drg5vOg9lC0BM9ARpt/NlfmA2T3pW6Q3PHI8QbOHtt6PQb3J6tr5kjqjIiHS8q9AvgMcGfjo7Si8lg9ZmZm1op8HjS4Dbq/rqSdyG7b+ni55R453uph9ctrmh1C4UnaVtLNkh6WNE/SZ5oc0toegxHxEtDdY7DUV8nqlJWNDM7MelfAesXMBgHXLWZ943Oh3jWqXilahmMgo80jaQxwFXB0RDxe/3Ct3S1ZvDx75GBuRPhRrxnR7LCKqgv4fETck3rF3C3pxtIeMw3Ua49BSbsB20bEtZK+UGlD7hlo1jRFq1esRqrtJWdWJ65bzKrgc6E+aUi9UrQePGtHm5c0lGy0+c6SMt2jzcP6o82PBK4FTomI2xoVsLW3X51zPyuWroKA5UtXcc337292SIUVEU9HxD1p+gWyAQdHNzeqyiRtBJwFfL63su4ZaNYcrVavmFlrcN1iVh2fC1WvUfVKoRI8AxltPq03Hpgm6b70elWDD8HayOqX17Di+fWHeVr+/Kp27qLYIWlu7nV8pYKSxgJvprnj2vTWY/AVwBuBWyQtBN4CdEqa1LAIzQyqrFsKUq+YWWtotTaLWeH4XGgDhahXCnepub+jzUfE14Cv1T1As2TIxhsxYuQwli9dV7GNGDmsnQcu64qIXpMfkkYAPwc+GxH/rH9YFa3tMUiW2JkKfLB7YUQsA7bufi/pFuBkP0XLrOF6rVsKVK+YWWtotTaLWeH4XGgDhahX2vZ/36wW3nviLozYchgIRmyZ3XdqlUnamKxC+2lE/KKZsVTZY9DMCq5I9YqZDR6uW8x653OhvmlEvVK4HjxmrWTUa0ZwzDf2ZvXLa9o5W10VSSK7xfKRiDir2fFA7z0GS+bv24iYzKx6zaxXJE0GvgsMAc6LiDNKlg8DLgZ2J3sYxBERsTC3/LXAw8D0iPh2o+I2s94Vsc1iVkQ+F6peo+oV/xXMasAVWlX2Bo4C3pUbJ+s9zQ7KzFpaU+oVSUOAc4GDgInAkZImlhQ7DlgaEeOBs4EzS5afBfy63rGaWb+4zWLWBz4XqkpD6hX34DGzhoiIPwBqdhzWPNU+9niHOsdhg0cT65U9gfkR8QSApJnAFLIeOd2mANPT9CzgHElKT/58P7AAWNGwiM2sam6zmFmtNapecarNzMzMrG9GA0/l3i9iw0edri2TxvxaRvYU0BHAF4Gv9LYTScd3P42jq6urJoGbmZnZ4OUEjxVeGz9qz8zMBp/pwNkRsby3ghExIyImRcSkjg53ujYza0c+F7K+cGvBCmvJ4uX86pz7WfH8KkaMzEZlH/WaEc0Oy8zMbDGwbe79mDSvXJlFkjqALcgGW94LOFTSN4GRwBpJKyPinLpHbWZmLcPnQtYf7sFjhfWrc+5nxdJVELB86Squ+f79zQ7JzMwMYA4wQdI4SUOBqUBnSZlO4Jg0fShwU2TeFhFjI2Is8B3g/zm5Y2ZmpXwuZP3hHjxWSKtfXsOK51etN2/586v8CD4zM2u6iOiSdAIwm+wx6RdExDxJpwNzI6KT7FGol0iaDzxHlgQyMzPrlc+FrL+c4LFCGrLxRowYOYzlS9dVbCNGDnOFZmZmhRAR1wHXlcyblpteCRzWyzam1yU4MzNraT4Xsv7yJ8QK670n7sKILYeBYMSW2X2nZmZmZmZmg53Phaw/3IPHCmvUa0ZwzDf2dldEMzMzM2s5kiYD3yW7lfO8iDijZPkw4GJgd7JB2I+IiIVp2anAccBq4NMRMTvNXwi8kOZ3RcSkNH8r4GfAWGAhcHhELK3rAVpd+VzI+sOfFCs8V2hmZmZm1kokDQHOBQ4CJgJHSppYUuw4YGlEjAfOBs5M604kG7drJ2Ay8L9pe93eGRG7did3klOA30bEBOC36b0NAj4Xsr7wp8XMzMzMzKy29gTmR8QTEfESMBOYUlJmCnBRmp4F7CdJaf7MiFgVEQuA+Wl7Pclv6yLg/QM/BDNrNb5Fy8zMzMysTv74/AtVlfu3ka+ocyTWYKOBp3LvFwF7VSqTns63DBiV5t9Rsu7oNB3ADZIC+FFEzEjzXx0RT6fpvwGvLheUpOOB4wGGDh3aj8MysyJzgsfMzMzMzKw17BMRiyW9CrhR0p8i4tZ8gYiIlADaQEoIzQAYPnx42TJm1rp8i5aZmZmZmVltLQa2zb0fk+aVLSOpA9iCbLDliutGRPe/zwBXse7Wrb9L2iZtaxvgmRoei5m1CCd4zMzMzMzMamsOMEHSOElDyQZN7iwp0wkck6YPBW6KiEjzp0oaJmkcMAG4S9JwSa8AkDQcOAB4qMy2jgGurtNxmVmB+RYtMzMzMzOzGkpj6pwAzCZ7TPoFETFP0unA3IjoBM4HLpE0H3iOLAlEKncF8DDQBXwqIlZLejVwVTYOMx3AZRFxfdrlGcAVko4DngQOb9jBmllhOMFjZmZmZmZWYxFxHXBdybxpuemVwGEV1v068PWSeU8Au1QovwTYb4Ahm1mL8y1aZmZmZmZmZmYtzgkeMzMzMzMzM7MW5wSPmZmZmZmZmVmLc4LHzMzMzMzMzKzFOcFjZmZmZmZmZtbinOAxMzMzMzMzM2txTvCYmZmZmZmZmbW4jmYHYGZmZmbt4VsLnm52CGZmZoNW4XrwSJos6VFJ8yWdUmb5MEk/S8vvlDQ2zR8l6WZJyyWd0/DAzczMzMzMzMyapFAJHklDgHOBg4CJwJGSJpYUOw5YGhHjgbOBM9P8lcCXgJMbFK6ZtbgqEsonSXpY0gOSfitpu2bEaWZmZmZm1ptCJXiAPYH5EfFERLwEzASmlJSZAlyUpmcB+0lSRKyIiD+QJXrMzHpUZUL5XmBSROxMVt98s7FRmpmZmZmZVadoCZ7RwFO594vSvLJlIqILWAaMqnYHko6XNFfS3K6urgGGa2YtrNeEckTcHBEvprd3AGMaHKOZmZmZmVlV2m6Q5YiYAcwAGD58eDQ5HDNrnnIJ5b16KH8c8OtyCyQdDxwPMHTo0FrFZ2ZmbeSPz79QVbnSru1mZmbditaDZzGwbe79mDSvbBlJHcAWwJKGRGdmbUnSh4FJwLfKLY+IGRExKSImdXS0Xd7crC0N4KEQ+0u6W9KD6d93NTx4MzMzG5SKluCZA0yQNE7SUGAq0FlSphM4Jk0fCtwUEe6JY2Z9VU1CGUnvBk4DDo6IVQ2KzcwKbIAPhXgWeF9EvImsPXNJY6I2MzOzwa5QCZ40ps4JwGzgEeCKiJgn6XRJB6di5wOjJM0HTgLWXjWTtBA4CzhW0qIyjS0zs269JpQlvRn4EVly55kmxGhmxTSQh0LcGxF/TfPnAZtKGtaQqM3MzGxQK9y9BBFxHXBdybxpuemVwGEV1h1b1+DMbNCIiC5J3QnlIcAF3QllYG5EdJLdkjUCuFISwF8i4uCKGzWzdlHNGF7rPRRCUvdDIZ7NlfkAcE+l3oEe38vMzMz6onAJHjOzRqkiofzuhgdlZm1B0k5kt20dUKmMHwxhZmZmfVGoW7TMzMzMWsCAHgohaQxwFXB0RDxe92jNrCn6Oxh7WnZqmv+opAPTvG0l3SzpYUnzJH0mV366pMWS7kuv9zTkIM2sUJzgMTMzM+ubfj8UQtJI4FrglIi4rVEBm1ljDWQw9lRuKrATMBn437S9LuDzETEReAvwqZJtnh0Ru6bXej2Uzaw9OMFjZmZm1gcDfCjECcB4YFruSvurGnwIZlZ//R6MPc2fGRGrImIBMB/YMyKejoh7ACLiBbL6Z3QDjsXMWoTH4DEzMzPro/4+FCIivgZ8re4BmlmzDWQw9tHAHSXrrpfISbdzvRm4Mzf7BElHA3PJevosLQ3Kg7ebDW7uwWNmZmZmZtYiJI0Afg58NiL+mWb/AHgdsCvwNPA/5daNiBkRMSkiJnV0+Fq/2WDjBI+ZmZmZmVltDWQw9orrStqYLLnz04j4RXeBiPh7RKyOiDXAj8luETOzNuO0rZmZWZ18a8HTVZX7wrht6hyJmZk12NrB2MmSM1OBD5aU6R6M/XbWH4y9E7hM0lnAa4AJwF1pfJ7zgUci4qz8hiRtExHdPzqHAA/V6bjMrMCc4DGzhpB0AfBe4JmIeGOz47Ha+ePzLzQ7BGtjrlvMrNZqUa+kMXW6B2MfAlzQPRg7MDciOsmSNZekwdifI0sCkcpdATxM9uSsT0XEakn7AEcBD0q6L+3qv9KYYN+UtCsQwELg4/2J28zqo1HtFSd4zKxRLgTOAS5uchxmNrhciOsWM6utC6lBvdLfwdjTsq8DXy+Z9wdAFcofNZBYzazuLqQB7RWPwWNmDRERt5JdnTIzqxnXLWZWa65XzKzWGlWvuAePWYuodiyPHeocRw86JM3NvZ8RETOaFo2ZDRauW8ys1lyvmLUYnwtVGUSjd2hmg1ZXRExqdhBmNui4bjGzWnO9Yma1Voh6xQkeMzMzM7MW4afzmZlZJR6Dx8zMzMzMzMysxTnBY2YNIely4HZgR0mLJB3X7JjMrPW5bjGzWnO9Yma11qh6xbdomVlDRMSRzY7BzAYf1y1mVmuuV8ys1hpVr7gHj5mZmZmZmZlZi3MPHjMzMzMbkGoH/jUzM7P6cYLHzMzKqvaEbYc6x2FmZmZmZr3zLVpmZmZmZmZmZi3OCR4zMzMzMzMzsxbnW7TMzMyarNrb4b4wbps6R2Jmg4XrFTOz9uMePGZmZmZmZmZmLc4JHjMzMzMzMzOzFucEj5mZmZmZmZlZi/MYPGZNVu098mZmZmZmZoOJz4VqywkeM7M24h9RMzPL68vvggdkNjMrtsIleCRNBr4LDAHOi4gzSpYPAy4GdgeWAEdExMK07FTgOGA18OmImN3A0M2sxQykvjFrBj8Vpzjapb3ipLBZ/9Wjnqi0TUnjgJnAKOBu4KiIeKnex2hmxVKoBI+kIcC5wP7AImCOpM6IeDhX7DhgaUSMlzQVOBM4QtJEYCqwE/Aa4DeSdoiI1Y09CrOMG8XFNpD6pvHRmvWNr8jXl9srZj1zMro+9URap9I2zwTOjoiZkn6Ytv2D+h+pWXk+F2qOQiV4gD2B+RHxBICkmcAUIF8RTgGmp+lZwDmSlObPjIhVwAJJ89P2bm9Q7FYDzWwQuDHSdvpd30RENCpI/ziaFZLbK9aWav2bNMjbXvWoJyi3TUmPAO8CPpjKXJS26wRPi2nWd8IXhgaPoiV4RgNP5d4vAvaqVCYiuiQtI+uKOBq4o2Td0aU7kHQ8cHx6G5L+VSGWDqCrrwdQEIM+9v9sQCD92Pfg/X+f9l/VbGPTWgXTIAOpb57NF+pDvdIXRf089T+u6j5HA9newP/Pah3jOoX9e/5nMeOCdf9nRaxb6t5egX7XLUX9rFVSvHgr1wPFiLW6eqoYsVavx3jr0O5rRL1Sr3qi3DZHAc9HRFeZ8uupsl4pwuen2TE0e/89xtCgc6Gy+2/weViz/w7Z/lvoXKhoCZ66i4gZwIzeykmaGxGTGhBSzTn25nDs7avaeqUvivo3KWpc4Nj6o6hxQbFja5T+1C2t9v/WSvE61vpptXhbWTX1ShH+Hs2Oodn7L0IMzd5/EWJo9v77Y6NmB1BiMbBt7v2YNK9sGUkdwBZkg5JVs66ZWbeB1Ddm1t7cXjGz3tSjnqg0fwkwMm2j0r7MrA0ULcEzB5ggaZykoWSDi3WWlOkEjknThwI3pfEwOoGpkoalUeQnAHc1KG4zaz0DqW/MrL25vWJmvalHPVF2m2mdm9M2SNu8uo7HZmYFVahbtNK9pycAs8ke/XdBRMyTdDowNyI6gfOBS9JgY8+RVWykcleQDVzWBXxqgE+kqOntFg3m2JvDsbeQgdQ3DVLUv0lR4wLH1h9FjQsKHFvB2iulCvv/VkErxetY66fV4u1VveqJcttMu/wiMFPS14B707b7qwh/j2bH0Oz9Q/NjaPb+ofkxNHv/fSZfjDYzMzMzMzMza21Fu0XLzMzMzMzMzMz6yAkeMzMzMzMzM7MW1/YJHkmHSZonaY2kSbn5YyX9S9J96fXD3LLdJT0oab6k70lSkWJPy05N8T0q6cDc/Mlp3nxJpzQ+6g1Jmi5pce7/+j25ZWWPo2iK+P/aE0kL02f4Pklz07ytJN0o6bH075bNjrMdFfWzJOkCSc9IeqjZseRJ2lbSzZIeTvXhZ5odUzdJm0i6S9L9KbavNDumPElDJN0r6Zpmx5JXrn6yykr/jmnw1TtTHfKzNBBrIbTSb4+kkZJmSfqTpEckvbXAse6Ya0PdJ+mfkj5b4Hg/l+rEhyRdnurKwn5uB7v+tMPr0VaR9HlJIWnr9F7KzrPmS3pA0m65ssekz/Vjko6pvNWq9/3VtI/7JN0g6TWNjEHSt1Jd84CkqySNzC1ryN9ABTuvrOe2S/azQfu2Ut3Z0+ehUCKirV/AG4AdgVuASbn5Y4GHKqxzF/AWQMCvgYMKFvtE4H5gGDAOeJxsILYhaXp7YGgqM7EAf4PpwMll5pc9jmbHWybOQv6/9hLzQmDrknnfBE5J06cAZzY7znZ7FfmzBLwd2K1SvdjEuLYBdkvTrwD+XKD/MwEj0vTGwJ3AW5odVy6+k4DLgGuaHUtJXBvUT35V/3cErgCmpukfAv+32TH29Lct6m8PcBHw0TQ9FBhZ1FhL4h4C/A3YrojxAqOBBcCm6f0VwLFF/twO9ldf2+H1aKuQPfp9NvBkdx0BvIfsPEtk5113pvlbAU+kf7dM01sOcP+b56Y/DfywkTEABwAdafrM7u9qg/8GhTmvrOe2y+xrg/Ztpbqz0uehaK+278ETEY9ExKPVlpe0DVklcEdkf+mLgffXK76e9BD7FGBmRKyKiAXAfGDP9JofEU9ExEvAzFS2qCodR9G02v9rJVPIGrSkf9/fvFDaVmE/SxFxK9kTPgolIp6OiHvS9AvAI2QnEE0XmeXp7cbpVYgnG0gaA/w7cF6zY7H+K/07ShLwLmBWKtIKdXnhfnskbUHW6D8fICJeiojnKWCsZewHPB4RT1LceDuATSV1AJsBT9N6n9t20MjzibOB/2T938gpwMXpt/QOYGQ6DzsQuDEinouIpcCNwOSB7Dwi/pl7OzwXR0NiiIgbIqIrvb0DGJPbf0P+BgU7r2xYe7hC+7ZS3Vnp81AobZ/g6cU4Zd2efyfpbWneaGBRrswiCnIykTMaeCr3vjvGSvOL4ITU1e2CXBfiIseb1ypx5gVwg6S7JR2f5r06Ip5O038DXt2c0NpaK36WCkPSWODNZD1lCkHZ7TP3Ac+QNQaLEtt3yBrTa5ocRznl6icr7zus/3ccBTyfO1EoWh3SKr8944B/AD9J7cDzJA2nmLGWmgpcnqYLF29ELAa+DfyFLLGzDLibYn9u20Ff2uE1batImgIsjoj7SxY19HxG0tclPQV8CJjWjBiS/yDrJdKs/ZdqRgzNbg9XqjubHVdVOpodQCNI+g3w/5VZdFpEXF1htaeB10bEEkm7A7+UtFPdgqygn7EXTk/HAfwA+CpZw++rwP+QVW5WP/tExGJJrwJulPSn/MKICEmF6GlgVg1JI4CfA58tuRLXVBGxGtg13U9/laQ3RkRTxzGS9F7gmYi4W9K+zYylgg3qp3SFzXJa4O9YTqv89nSQddk/MSLulPRdsm76axUo1rWUjVtzMHBq6bKixJuSB1PIkmjPA1cywN4X1rtmt8N72f9/kd2iVFe9nVNFxGnAaZJOBU4AvtzI/acypwFdwE9rue++xGDrK0rd2RdtkeCJiHf3Y51VwKo0fbekx4EdgMWs6zZHml5cizgrxNHn2Mni2Tb3Ph9jpfl1Ve1xSPox0D3gZ0/HUSStEuda6QoaEfGMpKvIukL+XdI2EfF06m74TFODbE8t91kqAkkbkyV3fhoRv2h2POVExPOSbiY7kWn2QNV7AwcrG0hzE2BzSZdGxIebHBdQsX5ygmdDG/wdge+SdRnvSL0hClWHtNBvzyJgUa7H3SyyBE8RY807CLgnIv6e3hcx3ncDCyLiHwCSfkH2WS7s53YwqEM7vE9tlUr7l/QmsmTf/dkdpowB7pG0Zw/7XwzsWzL/lp7231MMZfwUuI4swVOzGHrbv6RjgfcC+0VEd0Khpud0LXRe2ez2cKW6s9lxVcW3aFUg6ZWShqTp7YEJwBOpu9Y/Jb0l3et+NFC0jGcnMFXSMEnjyGK/C5gDTFD2pIKhZN14O5sYJ7B2XKNuh7Du5KfScRRNIf9fK5E0XNIruqfJrpo8RBZz91MAjqF4n+t20FKfpSJI9fD5wCMRcVaz48lLvyMj0/SmwP7An3pcqQEi4tSIGBMRY8k+YzcVJbnTQ/1kJSr8HT8E3AwcmooVpi5vpd+eiPgb8JSkHdOs/YCHKWCsJY5k3e1ZUMx4/wK8RdJmqf7u/r8t5Oe2HfSjHV6ztkpEPBgRr4qIsakuW0T24IS/pW0ercxbgGXpPGw2cICkLVOPsAPSvH6TNCH3dgrrfqsbEoOkyWS32x4cES/mFhXhnK4ZMTS7PVyp7qz0eSiWKMBIz818kVVki8h66/wdmJ3mfwCYB9wH3AO8L7fOJLLK73HgHEBFij0tOy3F9yi5p3yRjf7957TstGb//6eYLgEeBB4g++Js09txFO1VxP/XHmLdnmw0+vvTZ/y0NH8U8FvgMeA3wFbNjrUdX0X9LJGdNDwNvJzqneOaHVOKax+ybuUPpPr6PuA9zY4rxbYzcG+K7SFgWrNjKhPjvhToKVqV6ie/qv87pv/Du8gGwrwSGNbs+Hr62xb1twfYFZibvr+/JHtSTiFjTfEOB5YAW+TmFTJe4CtkJ9APpTbgsKJ+btvh1Z92eL3aKuSetEf2pKJz0z4eZP0nO/1H+qzMBz5Sg/3+PH0eHwB+BYxuZAxpG0/l2jE/bPTfgIKdV9Zz2yX72aB9W6nu7OnzUKSXUrBmZmZmZmZmZtaifIuWmZmZmZmZmVmLc4LHzMzMzMzMzKzFOcFjZmZmZmZmZtbinOAxMzMzMzMzM2txTvCYmZmZmZmZmbU4J3jMzKytSfqWpHmSvjWAbSyvZUxmZmZmZn3lBI/1m6RdJb0n9/5gSac0M6b+6D4xk/QaSbOqKH+dpJF1D8zMqiKpY4CbOB7YOSK+0KD9mVkDSdpX0jXNjqOUpE9IOrqP69wiaVK9YjIzs9bmBI8NxK7A2gRPRHRGxBnVrlx6ktTsk6aI+GtEHFpFufdExPMNCMnMEklHS3pA0v2SLpF0oaQfSroT+KakPSXdLuleSX+UtGNa71pJO6fpeyVNS9OnS/qYpE5gBHC3pCMkjZV0U9rXbyW9NpUv3d+4tL8HJX2tOf8rZtbKIuKHEXFxs+Mws/qTdJKkh9Lrs5KGpzbK/WneEancQknfkHSfpLmSdpM0W9Ljkj6RyoxIbZR7UjtkSpo/VtIjkn6ceibfIGnTZh63NZ4TPLYeSV+S9KikP0i6XNLJ+atFkrZOFc9Q4HTgiFQBHSHpWEnnpHKvlPRzSXPSa+80f3o6ObsNuKTM+0rrXZf2c5+kZZKOqRD/sZKuTjE/JunLuWXrVaxl1h0r6aHcdn4h6fq0nW/myi2UtHWN/svNrBeSdgL+G3hXROwCfCYtGgP8W0ScBPwJeFtEvBmYBvy/VOb3wNskbQF0AXun+W8Dbo2Ig4F/RcSuEfEz4PvARRGxM/BT4Hu5UPL7+y7wg4h4E/B0XQ7czCqqtr1SZr3udsft6ff9Y7llX0htjwckfSU3/5eS7k4nTMeneUNS4vehdIL1uTT/dantcLek30t6fQ/HMF3SyWn6FklnSrpL0p8lvS3N31TSzHTSdhWwaW79A9Jx3CPpynTSt106rq0lbZRiOGCg/99m1n+Sdgc+AuwFvAX4GPAJ4K8RsUtEvBG4PrfKXyJiV7I2zIXAoWm97nppJXBIROwGvBP4H0lKyyYA50bETsDzwAfqd2RWRO5mbmtJ2oOsEtgF2Bi4B7i7XNmIeEnZlfBJEXFCWv/YXJHvAmdHxB+UXQGfDbwhLZsI7BMR/5I0veT9ZeXWi4j3pH3sDvwE+GUPh7In8EbgRWCOpGuBYF3FKuBOSb+LiHt72M6uwJuBVcCjkr4fEU/1UN7M6uNdwJUR8SxARDyX2jFXRsTqVGYL4CJJE8i+7xun+b8HPg0sAK4F9pe0GTAuIh4ts6+3Av8nTV8CfDO3LL+/vVnXaLoEOHNgh2hm1epLe6WCnclOloYD96Z2whvJToz2JGsndEp6e0TcCvxHqnc2JWtX/BwYC4xOJ2Zo3a3bM4BPRMRjkvYC/pesDqtGR0Tsqez29y8D7wb+L/BiRLxBWW/Ee9L+tiZLfL87IlZI+iJwUkScLulM4AfAXcDDEXFDH/5vzKz29gGuiogVAJJ+AbxM1iY5E7gmIn6fK9+Z/n0QGBERLwAvSFqV6poVwP+T9HZgDTAaeHVaZ0FE3Jem7yarq6yNOMFjeXsDV0fESmClpF8NYFvvBiauSyazuaQRabozIv6VK5t/X3a9iFieGjOXAIdHxLIe9n1jRCyBtRXoPmQnfKUV69uAnhI8v+3ej6SHge0AJ3jMimNFbvqrwM0RcYikscAtaf4cYBLwBHAjsDXZlbO+nAyW2x9k9YqZNd5A2ytXp3bHvyTdTJbU2Qc4gHXtghFkCZ9bgU9LOiTN3zbNfxTYXtL3yZLHN6R2zr8BV+baMcP6ENcv0r/5k7K3k3oSRsQDkh5I899CdoHstrSvocDtqdx5kg4j6yGwax/2b2aNtRvZcBdfk/TbiDg9zV+V/l2Tm+5+3wF8CHglsHtEvJx6K25Ssi7AanK9/qw9OMFj1ehi3e18m/RUMGcj4C2p8bVWaoSUniTl31dabwgwEzg9Ih7qZd+lJ139PQkrrSD9fTFrjpuAqySdFRFLJG1VpswWwOI0fWz3zNTb8CngMLLbSl8JfDu9yvkjMJUsmfwhsh5A5dyWyl2ayplZ81XbXinXThDwjYj4UX6BpH3JLj69NSJelHQLsElELJW0C3AgWSLlcOCzwPPp1or+6G53VNPmENkFrSM3WJD1UhyT3o4AXuhnPGZWG78HLpR0Btl39xDg42S98y6V9Dzw0T5sbwvgmZTceSfZRWgzwGPw2PpuA94naZN0Feq9af5CYPc0nR+E+AXgFRW2dQNwYvcbSbtWGUOl9c4AHoiImVVsY39JW6Wu1O8nO67fA++XtJmk4WQVa6UTNzMrkIiYB3wd+J2k+4GzyhT7JvANSfey4YnR78kaQv9K02Oo/P0/EfhIukp+FOvG+yn1GeBTkh4k6xptZo3T1/ZKqSlp3VHAvmQ9/WYD/9Hd21jSaEmvIjuRWpqSO68n6znTfYvURhHxc7JbpXaLiH8CC1LvGZTZZYDHeivwwbS9N5LdXgZwB7C3pPFp2XBJO6RlZ5KNITYN+PEA929mAxQR95CNpXMXcCdwHlny9S5J95HdktmXBzb8FJiU2iBHk41DaAa4R4LlRMQcZU+UeQD4O9l9n8vIrnRfoWxgwWtzq9wMnJIqpm+UbO7TwLnpJKmDrIHyiSrCqLTeycC8tC+AaRHRWX4T3AX8nOwk7tKImAvZU3DSMoDzehl/x8wKJCIuAi7qYfntwA65Wf+dW/Yl4Etp+q9kV8/y647ITT9JmfEyIuLYkvcLyMbr2WB/ZlZf/WivlHqArA2zNfDVVC/8VdIbgNtTb+PlwIfJBj79hKRHyG7LuiNtYzTwE0ndF0tPTf9+CPiBpP8mGx9oJnD/AA73B2k/jwCPkG4vjYh/pLEPL5fUfRvYf0vaBtgD2DsiVkv6gKSPRMRPBhCDmQ1QRJzFhheoZpcpNzY3fSFZYmiDZazfBsl7Y658pd7KNogpwkMI2Dq58W42I0uuHJ+yzi0hNXbWDvxsZmZmg09/2yvp4Q7LfeJjZmaDkXvwWKkZkiaS3bt+USsld8zMzKxtuL1iZmZWwj14rCVJOpANH0u8ICIOKVfezMzMrBkknUY20HvelRHx9WbEY2Zmg5cTPGZmZmZmZmZmLc5P0TIzMzMzMzMza3FO8JiZmZmZmZmZtTgneMzMzMzMzMzMWpwTPGZmZmZmZmZmLe7/BxHGFGoTGvmPAAAAAElFTkSuQmCC\n", "text/plain": [ "<Figure size 1152x1152 with 32 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>feature</th>\n", " <th>train_trend_changes</th>\n", " <th>test_trend_changes</th>\n", " <th>train_test_trend_corr</th>\n", " <th>train_target_trend_changes</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>11</th>\n", " <td>szigriszt_pazos</td>\n", " <td>5</td>\n", " <td>1</td>\n", " <td>0.998387</td>\n", " <td>5</td>\n", " </tr>\n", " <tr>\n", " <th>10</th>\n", " <td>fernandez_huerta</td>\n", " <td>5</td>\n", " <td>1</td>\n", " <td>0.998137</td>\n", " <td>5</td>\n", " </tr>\n", " <tr>\n", " <th>4</th>\n", " <td>automated_readability_index</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>0.977265</td>\n", " <td>4</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>flesch_kincaid_grade</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>0.968130</td>\n", " <td>4</td>\n", " </tr>\n", " <tr>\n", " <th>8</th>\n", " <td>gunning_fog</td>\n", " <td>3</td>\n", " <td>0</td>\n", " <td>0.961693</td>\n", " <td>4</td>\n", " </tr>\n", " <tr>\n", " <th>0</th>\n", " <td>flesch_reading_ease</td>\n", " <td>5</td>\n", " <td>1</td>\n", " <td>0.947991</td>\n", " <td>5</td>\n", " </tr>\n", " <tr>\n", " <th>9</th>\n", " <td>text_standard</td>\n", " <td>8</td>\n", " <td>0</td>\n", " <td>0.935383</td>\n", " <td>9</td>\n", " </tr>\n", " <tr>\n", " <th>7</th>\n", " <td>linsear_write_formula</td>\n", " <td>5</td>\n", " <td>1</td>\n", " <td>0.849062</td>\n", " <td>6</td>\n", " </tr>\n", " <tr>\n", " <th>12</th>\n", " <td>gutierrez_polini</td>\n", " <td>6</td>\n", " <td>1</td>\n", " <td>0.756861</td>\n", " <td>6</td>\n", " </tr>\n", " <tr>\n", " <th>15</th>\n", " <td>osman</td>\n", " <td>6</td>\n", " <td>1</td>\n", " <td>0.751823</td>\n", " <td>6</td>\n", " </tr>\n", " <tr>\n", " <th>2</th>\n", " <td>smog_index</td>\n", " <td>2</td>\n", " <td>4</td>\n", " <td>0.703572</td>\n", " <td>6</td>\n", " </tr>\n", " <tr>\n", " <th>13</th>\n", " <td>crawford</td>\n", " <td>3</td>\n", " <td>6</td>\n", " <td>0.588342</td>\n", " <td>7</td>\n", " </tr>\n", " <tr>\n", " <th>6</th>\n", " <td>difficult_words</td>\n", " <td>5</td>\n", " <td>1</td>\n", " <td>0.474954</td>\n", " <td>5</td>\n", " </tr>\n", " <tr>\n", " <th>14</th>\n", " <td>gulpease_index</td>\n", " <td>3</td>\n", " <td>4</td>\n", " <td>0.359054</td>\n", " <td>11</td>\n", " </tr>\n", " <tr>\n", " <th>5</th>\n", " <td>dale_chall_readability_score</td>\n", " <td>8</td>\n", " <td>2</td>\n", " <td>0.357135</td>\n", " <td>3</td>\n", " </tr>\n", " <tr>\n", " <th>3</th>\n", " <td>coleman_liau_index</td>\n", " <td>2</td>\n", " <td>2</td>\n", " <td>0.230895</td>\n", " <td>7</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " feature train_trend_changes test_trend_changes \\\n", "11 szigriszt_pazos 5 1 \n", "10 fernandez_huerta 5 1 \n", "4 automated_readability_index 1 0 \n", "1 flesch_kincaid_grade 1 0 \n", "8 gunning_fog 3 0 \n", "0 flesch_reading_ease 5 1 \n", "9 text_standard 8 0 \n", "7 linsear_write_formula 5 1 \n", "12 gutierrez_polini 6 1 \n", "15 osman 6 1 \n", "2 smog_index 2 4 \n", "13 crawford 3 6 \n", "6 difficult_words 5 1 \n", "14 gulpease_index 3 4 \n", "5 dale_chall_readability_score 8 2 \n", "3 coleman_liau_index 2 2 \n", "\n", " train_test_trend_corr train_target_trend_changes \n", "11 0.998387 5 \n", "10 0.998137 5 \n", "4 0.977265 4 \n", "1 0.968130 4 \n", "8 0.961693 4 \n", "0 0.947991 5 \n", "9 0.935383 9 \n", "7 0.849062 6 \n", "12 0.756861 6 \n", "15 0.751823 6 \n", "2 0.703572 6 \n", "13 0.588342 7 \n", "6 0.474954 5 \n", "14 0.359054 11 \n", "5 0.357135 3 \n", "3 0.230895 7 " ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "---------------------------------------- grammar ----------------------------------------\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 1152x1152 with 32 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>feature</th>\n", " <th>train_trend_changes</th>\n", " <th>test_trend_changes</th>\n", " <th>train_test_trend_corr</th>\n", " <th>train_target_trend_changes</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>11</th>\n", " <td>szigriszt_pazos</td>\n", " <td>5</td>\n", " <td>1</td>\n", " <td>0.998387</td>\n", " <td>3</td>\n", " </tr>\n", " <tr>\n", " <th>10</th>\n", " <td>fernandez_huerta</td>\n", " <td>5</td>\n", " <td>1</td>\n", " <td>0.998137</td>\n", " <td>3</td>\n", " </tr>\n", " <tr>\n", " <th>4</th>\n", " <td>automated_readability_index</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>0.977265</td>\n", " <td>4</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>flesch_kincaid_grade</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>0.968130</td>\n", " <td>6</td>\n", " </tr>\n", " <tr>\n", " <th>8</th>\n", " <td>gunning_fog</td>\n", " <td>3</td>\n", " <td>0</td>\n", " <td>0.961693</td>\n", " <td>4</td>\n", " </tr>\n", " <tr>\n", " <th>0</th>\n", " <td>flesch_reading_ease</td>\n", " <td>5</td>\n", " <td>1</td>\n", " <td>0.947991</td>\n", " <td>3</td>\n", " </tr>\n", " <tr>\n", " <th>9</th>\n", " <td>text_standard</td>\n", " <td>8</td>\n", " <td>0</td>\n", " <td>0.935383</td>\n", " <td>11</td>\n", " </tr>\n", " <tr>\n", " <th>7</th>\n", " <td>linsear_write_formula</td>\n", " <td>5</td>\n", " <td>1</td>\n", " <td>0.849062</td>\n", " <td>5</td>\n", " </tr>\n", " <tr>\n", " <th>12</th>\n", " <td>gutierrez_polini</td>\n", " <td>6</td>\n", " <td>1</td>\n", " <td>0.756861</td>\n", " <td>5</td>\n", " </tr>\n", " <tr>\n", " <th>15</th>\n", " <td>osman</td>\n", " <td>6</td>\n", " <td>1</td>\n", " <td>0.751823</td>\n", " <td>5</td>\n", " </tr>\n", " <tr>\n", " <th>2</th>\n", " <td>smog_index</td>\n", " <td>2</td>\n", " <td>4</td>\n", " <td>0.703572</td>\n", " <td>8</td>\n", " </tr>\n", " <tr>\n", " <th>13</th>\n", " <td>crawford</td>\n", " <td>3</td>\n", " <td>6</td>\n", " <td>0.588342</td>\n", " <td>8</td>\n", " </tr>\n", " <tr>\n", " <th>6</th>\n", " <td>difficult_words</td>\n", " <td>5</td>\n", " <td>1</td>\n", " <td>0.474954</td>\n", " <td>7</td>\n", " </tr>\n", " <tr>\n", " <th>14</th>\n", " <td>gulpease_index</td>\n", " <td>3</td>\n", " <td>4</td>\n", " <td>0.359054</td>\n", " <td>6</td>\n", " </tr>\n", " <tr>\n", " <th>5</th>\n", " <td>dale_chall_readability_score</td>\n", " <td>8</td>\n", " <td>2</td>\n", " <td>0.357135</td>\n", " <td>4</td>\n", " </tr>\n", " <tr>\n", " <th>3</th>\n", " <td>coleman_liau_index</td>\n", " <td>2</td>\n", " <td>2</td>\n", " <td>0.230895</td>\n", " <td>11</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " feature train_trend_changes test_trend_changes \\\n", "11 szigriszt_pazos 5 1 \n", "10 fernandez_huerta 5 1 \n", "4 automated_readability_index 1 0 \n", "1 flesch_kincaid_grade 1 0 \n", "8 gunning_fog 3 0 \n", "0 flesch_reading_ease 5 1 \n", "9 text_standard 8 0 \n", "7 linsear_write_formula 5 1 \n", "12 gutierrez_polini 6 1 \n", "15 osman 6 1 \n", "2 smog_index 2 4 \n", "13 crawford 3 6 \n", "6 difficult_words 5 1 \n", "14 gulpease_index 3 4 \n", "5 dale_chall_readability_score 8 2 \n", "3 coleman_liau_index 2 2 \n", "\n", " train_test_trend_corr train_target_trend_changes \n", "11 0.998387 3 \n", "10 0.998137 3 \n", "4 0.977265 4 \n", "1 0.968130 6 \n", "8 0.961693 4 \n", "0 0.947991 3 \n", "9 0.935383 11 \n", "7 0.849062 5 \n", "12 0.756861 5 \n", "15 0.751823 5 \n", "2 0.703572 8 \n", "13 0.588342 8 \n", "6 0.474954 7 \n", "14 0.359054 6 \n", "5 0.357135 4 \n", "3 0.230895 11 " ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "---------------------------------------- syntax ----------------------------------------\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 1152x1152 with 32 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>feature</th>\n", " <th>train_trend_changes</th>\n", " <th>test_trend_changes</th>\n", " <th>train_test_trend_corr</th>\n", " <th>train_target_trend_changes</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>11</th>\n", " <td>szigriszt_pazos</td>\n", " <td>5</td>\n", " <td>1</td>\n", " <td>0.998387</td>\n", " <td>3</td>\n", " </tr>\n", " <tr>\n", " <th>10</th>\n", " <td>fernandez_huerta</td>\n", " <td>5</td>\n", " <td>1</td>\n", " <td>0.998137</td>\n", " <td>3</td>\n", " </tr>\n", " <tr>\n", " <th>4</th>\n", " <td>automated_readability_index</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>0.977265</td>\n", " <td>8</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>flesch_kincaid_grade</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>0.968130</td>\n", " <td>8</td>\n", " </tr>\n", " <tr>\n", " <th>8</th>\n", " <td>gunning_fog</td>\n", " <td>3</td>\n", " <td>0</td>\n", " <td>0.961693</td>\n", " <td>8</td>\n", " </tr>\n", " <tr>\n", " <th>0</th>\n", " <td>flesch_reading_ease</td>\n", " <td>5</td>\n", " <td>1</td>\n", " <td>0.947991</td>\n", " <td>3</td>\n", " </tr>\n", " <tr>\n", " <th>9</th>\n", " <td>text_standard</td>\n", " <td>8</td>\n", " <td>0</td>\n", " <td>0.935383</td>\n", " <td>9</td>\n", " </tr>\n", " <tr>\n", " <th>7</th>\n", " <td>linsear_write_formula</td>\n", " <td>5</td>\n", " <td>1</td>\n", " <td>0.849062</td>\n", " <td>7</td>\n", " </tr>\n", " <tr>\n", " <th>12</th>\n", " <td>gutierrez_polini</td>\n", " <td>6</td>\n", " <td>1</td>\n", " <td>0.756861</td>\n", " <td>4</td>\n", " </tr>\n", " <tr>\n", " <th>15</th>\n", " <td>osman</td>\n", " <td>6</td>\n", " <td>1</td>\n", " <td>0.751823</td>\n", " <td>4</td>\n", " </tr>\n", " <tr>\n", " <th>2</th>\n", " <td>smog_index</td>\n", " <td>2</td>\n", " <td>4</td>\n", " <td>0.703572</td>\n", " <td>6</td>\n", " </tr>\n", " <tr>\n", " <th>13</th>\n", " <td>crawford</td>\n", " <td>3</td>\n", " <td>6</td>\n", " <td>0.588342</td>\n", " <td>7</td>\n", " </tr>\n", " <tr>\n", " <th>6</th>\n", " <td>difficult_words</td>\n", " <td>5</td>\n", " <td>1</td>\n", " <td>0.474954</td>\n", " <td>5</td>\n", " </tr>\n", " <tr>\n", " <th>14</th>\n", " <td>gulpease_index</td>\n", " <td>3</td>\n", " <td>4</td>\n", " <td>0.359054</td>\n", " <td>6</td>\n", " </tr>\n", " <tr>\n", " <th>5</th>\n", " <td>dale_chall_readability_score</td>\n", " <td>8</td>\n", " <td>2</td>\n", " <td>0.357135</td>\n", " <td>6</td>\n", " </tr>\n", " <tr>\n", " <th>3</th>\n", " <td>coleman_liau_index</td>\n", " <td>2</td>\n", " <td>2</td>\n", " <td>0.230895</td>\n", " <td>8</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " feature train_trend_changes test_trend_changes \\\n", "11 szigriszt_pazos 5 1 \n", "10 fernandez_huerta 5 1 \n", "4 automated_readability_index 1 0 \n", "1 flesch_kincaid_grade 1 0 \n", "8 gunning_fog 3 0 \n", "0 flesch_reading_ease 5 1 \n", "9 text_standard 8 0 \n", "7 linsear_write_formula 5 1 \n", "12 gutierrez_polini 6 1 \n", "15 osman 6 1 \n", "2 smog_index 2 4 \n", "13 crawford 3 6 \n", "6 difficult_words 5 1 \n", "14 gulpease_index 3 4 \n", "5 dale_chall_readability_score 8 2 \n", "3 coleman_liau_index 2 2 \n", "\n", " train_test_trend_corr train_target_trend_changes \n", "11 0.998387 3 \n", "10 0.998137 3 \n", "4 0.977265 8 \n", "1 0.968130 8 \n", "8 0.961693 8 \n", "0 0.947991 3 \n", "9 0.935383 9 \n", "7 0.849062 7 \n", "12 0.756861 4 \n", "15 0.751823 4 \n", "2 0.703572 6 \n", "13 0.588342 7 \n", "6 0.474954 5 \n", "14 0.359054 6 \n", "5 0.357135 6 \n", "3 0.230895 8 " ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "---------------------------------------- vocabulary ----------------------------------------\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 1152x1152 with 32 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>feature</th>\n", " <th>train_trend_changes</th>\n", " <th>test_trend_changes</th>\n", " <th>train_test_trend_corr</th>\n", " <th>train_target_trend_changes</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>11</th>\n", " <td>szigriszt_pazos</td>\n", " <td>5</td>\n", " <td>1</td>\n", " <td>0.998387</td>\n", " <td>5</td>\n", " </tr>\n", " <tr>\n", " <th>10</th>\n", " <td>fernandez_huerta</td>\n", " <td>5</td>\n", " <td>1</td>\n", " <td>0.998137</td>\n", " <td>5</td>\n", " </tr>\n", " <tr>\n", " <th>4</th>\n", " <td>automated_readability_index</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>0.977265</td>\n", " <td>2</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>flesch_kincaid_grade</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>0.968130</td>\n", " <td>4</td>\n", " </tr>\n", " <tr>\n", " <th>8</th>\n", " <td>gunning_fog</td>\n", " <td>3</td>\n", " <td>0</td>\n", " <td>0.961693</td>\n", " <td>4</td>\n", " </tr>\n", " <tr>\n", " <th>0</th>\n", " <td>flesch_reading_ease</td>\n", " <td>5</td>\n", " <td>1</td>\n", " <td>0.947991</td>\n", " <td>6</td>\n", " </tr>\n", " <tr>\n", " <th>9</th>\n", " <td>text_standard</td>\n", " <td>8</td>\n", " <td>0</td>\n", " <td>0.935383</td>\n", " <td>11</td>\n", " </tr>\n", " <tr>\n", " <th>7</th>\n", " <td>linsear_write_formula</td>\n", " <td>5</td>\n", " <td>1</td>\n", " <td>0.849062</td>\n", " <td>6</td>\n", " </tr>\n", " <tr>\n", " <th>12</th>\n", " <td>gutierrez_polini</td>\n", " <td>6</td>\n", " <td>1</td>\n", " <td>0.756861</td>\n", " <td>4</td>\n", " </tr>\n", " <tr>\n", " <th>15</th>\n", " <td>osman</td>\n", " <td>6</td>\n", " <td>1</td>\n", " <td>0.751823</td>\n", " <td>4</td>\n", " </tr>\n", " <tr>\n", " <th>2</th>\n", " <td>smog_index</td>\n", " <td>2</td>\n", " <td>4</td>\n", " <td>0.703572</td>\n", " <td>6</td>\n", " </tr>\n", " <tr>\n", " <th>13</th>\n", " <td>crawford</td>\n", " <td>3</td>\n", " <td>6</td>\n", " <td>0.588342</td>\n", " <td>9</td>\n", " </tr>\n", " <tr>\n", " <th>6</th>\n", " <td>difficult_words</td>\n", " <td>5</td>\n", " <td>1</td>\n", " <td>0.474954</td>\n", " <td>5</td>\n", " </tr>\n", " <tr>\n", " <th>14</th>\n", " <td>gulpease_index</td>\n", " <td>3</td>\n", " <td>4</td>\n", " <td>0.359054</td>\n", " <td>11</td>\n", " </tr>\n", " <tr>\n", " <th>5</th>\n", " <td>dale_chall_readability_score</td>\n", " <td>8</td>\n", " <td>2</td>\n", " <td>0.357135</td>\n", " <td>4</td>\n", " </tr>\n", " <tr>\n", " <th>3</th>\n", " <td>coleman_liau_index</td>\n", " <td>2</td>\n", " <td>2</td>\n", " <td>0.230895</td>\n", " <td>7</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " feature train_trend_changes test_trend_changes \\\n", "11 szigriszt_pazos 5 1 \n", "10 fernandez_huerta 5 1 \n", "4 automated_readability_index 1 0 \n", "1 flesch_kincaid_grade 1 0 \n", "8 gunning_fog 3 0 \n", "0 flesch_reading_ease 5 1 \n", "9 text_standard 8 0 \n", "7 linsear_write_formula 5 1 \n", "12 gutierrez_polini 6 1 \n", "15 osman 6 1 \n", "2 smog_index 2 4 \n", "13 crawford 3 6 \n", "6 difficult_words 5 1 \n", "14 gulpease_index 3 4 \n", "5 dale_chall_readability_score 8 2 \n", "3 coleman_liau_index 2 2 \n", "\n", " train_test_trend_corr train_target_trend_changes \n", "11 0.998387 5 \n", "10 0.998137 5 \n", "4 0.977265 2 \n", "1 0.968130 4 \n", "8 0.961693 4 \n", "0 0.947991 6 \n", "9 0.935383 11 \n", "7 0.849062 6 \n", "12 0.756861 4 \n", "15 0.751823 4 \n", "2 0.703572 6 \n", "13 0.588342 9 \n", "6 0.474954 5 \n", "14 0.359054 11 \n", "5 0.357135 4 \n", "3 0.230895 7 " ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "---------------------------------------- phraseology ----------------------------------------\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 1152x1152 with 32 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>feature</th>\n", " <th>train_trend_changes</th>\n", " <th>test_trend_changes</th>\n", " <th>train_test_trend_corr</th>\n", " <th>train_target_trend_changes</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>11</th>\n", " <td>szigriszt_pazos</td>\n", " <td>5</td>\n", " <td>1</td>\n", " <td>0.998387</td>\n", " <td>5</td>\n", " </tr>\n", " <tr>\n", " <th>10</th>\n", " <td>fernandez_huerta</td>\n", " <td>5</td>\n", " <td>1</td>\n", " <td>0.998137</td>\n", " <td>3</td>\n", " </tr>\n", " <tr>\n", " <th>4</th>\n", " <td>automated_readability_index</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>0.977265</td>\n", " <td>6</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>flesch_kincaid_grade</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>0.968130</td>\n", " <td>6</td>\n", " </tr>\n", " <tr>\n", " <th>8</th>\n", " <td>gunning_fog</td>\n", " <td>3</td>\n", " <td>0</td>\n", " <td>0.961693</td>\n", " <td>6</td>\n", " </tr>\n", " <tr>\n", " <th>0</th>\n", " <td>flesch_reading_ease</td>\n", " <td>5</td>\n", " <td>1</td>\n", " <td>0.947991</td>\n", " <td>3</td>\n", " </tr>\n", " <tr>\n", " <th>9</th>\n", " <td>text_standard</td>\n", " <td>8</td>\n", " <td>0</td>\n", " <td>0.935383</td>\n", " <td>11</td>\n", " </tr>\n", " <tr>\n", " <th>7</th>\n", " <td>linsear_write_formula</td>\n", " <td>5</td>\n", " <td>1</td>\n", " <td>0.849062</td>\n", " <td>7</td>\n", " </tr>\n", " <tr>\n", " <th>12</th>\n", " <td>gutierrez_polini</td>\n", " <td>6</td>\n", " <td>1</td>\n", " <td>0.756861</td>\n", " <td>4</td>\n", " </tr>\n", " <tr>\n", " <th>15</th>\n", " <td>osman</td>\n", " <td>6</td>\n", " <td>1</td>\n", " <td>0.751823</td>\n", " <td>4</td>\n", " </tr>\n", " <tr>\n", " <th>2</th>\n", " <td>smog_index</td>\n", " <td>2</td>\n", " <td>4</td>\n", " <td>0.703572</td>\n", " <td>6</td>\n", " </tr>\n", " <tr>\n", " <th>13</th>\n", " <td>crawford</td>\n", " <td>3</td>\n", " <td>6</td>\n", " <td>0.588342</td>\n", " <td>9</td>\n", " </tr>\n", " <tr>\n", " <th>6</th>\n", " <td>difficult_words</td>\n", " <td>5</td>\n", " <td>1</td>\n", " <td>0.474954</td>\n", " <td>5</td>\n", " </tr>\n", " <tr>\n", " <th>14</th>\n", " <td>gulpease_index</td>\n", " <td>3</td>\n", " <td>4</td>\n", " <td>0.359054</td>\n", " <td>13</td>\n", " </tr>\n", " <tr>\n", " <th>5</th>\n", " <td>dale_chall_readability_score</td>\n", " <td>8</td>\n", " <td>2</td>\n", " <td>0.357135</td>\n", " <td>6</td>\n", " </tr>\n", " <tr>\n", " <th>3</th>\n", " <td>coleman_liau_index</td>\n", " <td>2</td>\n", " <td>2</td>\n", " <td>0.230895</td>\n", " <td>9</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " feature train_trend_changes test_trend_changes \\\n", "11 szigriszt_pazos 5 1 \n", "10 fernandez_huerta 5 1 \n", "4 automated_readability_index 1 0 \n", "1 flesch_kincaid_grade 1 0 \n", "8 gunning_fog 3 0 \n", "0 flesch_reading_ease 5 1 \n", "9 text_standard 8 0 \n", "7 linsear_write_formula 5 1 \n", "12 gutierrez_polini 6 1 \n", "15 osman 6 1 \n", "2 smog_index 2 4 \n", "13 crawford 3 6 \n", "6 difficult_words 5 1 \n", "14 gulpease_index 3 4 \n", "5 dale_chall_readability_score 8 2 \n", "3 coleman_liau_index 2 2 \n", "\n", " train_test_trend_corr train_target_trend_changes \n", "11 0.998387 5 \n", "10 0.998137 3 \n", "4 0.977265 6 \n", "1 0.968130 6 \n", "8 0.961693 6 \n", "0 0.947991 3 \n", "9 0.935383 11 \n", "7 0.849062 7 \n", "12 0.756861 4 \n", "15 0.751823 4 \n", "2 0.703572 6 \n", "13 0.588342 9 \n", "6 0.474954 5 \n", "14 0.359054 13 \n", "5 0.357135 6 \n", "3 0.230895 9 " ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "---------------------------------------- cohesion ----------------------------------------\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 1152x1152 with 32 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>feature</th>\n", " <th>train_trend_changes</th>\n", " <th>test_trend_changes</th>\n", " <th>train_test_trend_corr</th>\n", " <th>train_target_trend_changes</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>11</th>\n", " <td>szigriszt_pazos</td>\n", " <td>5</td>\n", " <td>1</td>\n", " <td>0.998387</td>\n", " <td>3</td>\n", " </tr>\n", " <tr>\n", " <th>10</th>\n", " <td>fernandez_huerta</td>\n", " <td>5</td>\n", " <td>1</td>\n", " <td>0.998137</td>\n", " <td>3</td>\n", " </tr>\n", " <tr>\n", " <th>4</th>\n", " <td>automated_readability_index</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>0.977265</td>\n", " <td>6</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>flesch_kincaid_grade</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>0.968130</td>\n", " <td>8</td>\n", " </tr>\n", " <tr>\n", " <th>8</th>\n", " <td>gunning_fog</td>\n", " <td>3</td>\n", " <td>0</td>\n", " <td>0.961693</td>\n", " <td>4</td>\n", " </tr>\n", " <tr>\n", " <th>0</th>\n", " <td>flesch_reading_ease</td>\n", " <td>5</td>\n", " <td>1</td>\n", " <td>0.947991</td>\n", " <td>5</td>\n", " </tr>\n", " <tr>\n", " <th>9</th>\n", " <td>text_standard</td>\n", " <td>8</td>\n", " <td>0</td>\n", " <td>0.935383</td>\n", " <td>11</td>\n", " </tr>\n", " <tr>\n", " <th>7</th>\n", " <td>linsear_write_formula</td>\n", " <td>5</td>\n", " <td>1</td>\n", " <td>0.849062</td>\n", " <td>8</td>\n", " </tr>\n", " <tr>\n", " <th>12</th>\n", " <td>gutierrez_polini</td>\n", " <td>6</td>\n", " <td>1</td>\n", " <td>0.756861</td>\n", " <td>6</td>\n", " </tr>\n", " <tr>\n", " <th>15</th>\n", " <td>osman</td>\n", " <td>6</td>\n", " <td>1</td>\n", " <td>0.751823</td>\n", " <td>6</td>\n", " </tr>\n", " <tr>\n", " <th>2</th>\n", " <td>smog_index</td>\n", " <td>2</td>\n", " <td>4</td>\n", " <td>0.703572</td>\n", " <td>6</td>\n", " </tr>\n", " <tr>\n", " <th>13</th>\n", " <td>crawford</td>\n", " <td>3</td>\n", " <td>6</td>\n", " <td>0.588342</td>\n", " <td>9</td>\n", " </tr>\n", " <tr>\n", " <th>6</th>\n", " <td>difficult_words</td>\n", " <td>5</td>\n", " <td>1</td>\n", " <td>0.474954</td>\n", " <td>7</td>\n", " </tr>\n", " <tr>\n", " <th>14</th>\n", " <td>gulpease_index</td>\n", " <td>3</td>\n", " <td>4</td>\n", " <td>0.359054</td>\n", " <td>7</td>\n", " </tr>\n", " <tr>\n", " <th>5</th>\n", " <td>dale_chall_readability_score</td>\n", " <td>8</td>\n", " <td>2</td>\n", " <td>0.357135</td>\n", " <td>4</td>\n", " </tr>\n", " <tr>\n", " <th>3</th>\n", " <td>coleman_liau_index</td>\n", " <td>2</td>\n", " <td>2</td>\n", " <td>0.230895</td>\n", " <td>8</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " feature train_trend_changes test_trend_changes \\\n", "11 szigriszt_pazos 5 1 \n", "10 fernandez_huerta 5 1 \n", "4 automated_readability_index 1 0 \n", "1 flesch_kincaid_grade 1 0 \n", "8 gunning_fog 3 0 \n", "0 flesch_reading_ease 5 1 \n", "9 text_standard 8 0 \n", "7 linsear_write_formula 5 1 \n", "12 gutierrez_polini 6 1 \n", "15 osman 6 1 \n", "2 smog_index 2 4 \n", "13 crawford 3 6 \n", "6 difficult_words 5 1 \n", "14 gulpease_index 3 4 \n", "5 dale_chall_readability_score 8 2 \n", "3 coleman_liau_index 2 2 \n", "\n", " train_test_trend_corr train_target_trend_changes \n", "11 0.998387 3 \n", "10 0.998137 3 \n", "4 0.977265 6 \n", "1 0.968130 8 \n", "8 0.961693 4 \n", "0 0.947991 5 \n", "9 0.935383 11 \n", "7 0.849062 8 \n", "12 0.756861 6 \n", "15 0.751823 6 \n", "2 0.703572 6 \n", "13 0.588342 9 \n", "6 0.474954 7 \n", "14 0.359054 7 \n", "5 0.357135 4 \n", "3 0.230895 8 " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "for label in labels:\n", " print('-'40,label,'-'*40)\n", " df_stats = numerical_ttt_dist(train=train, test=test, features=stat_features, target=label, ncols=4, nbins=20)\n", " display(df_stats)" ] }, { "cell_type": "code", "execution_count": 19, "id": "70216d57", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:37:48.235084Z", "iopub.status.busy": "2022-10-27T19:37:48.234622Z", "iopub.status.idle": "2022-10-27T19:37:52.938334Z", "shell.execute_reply": "2022-10-27T19:37:52.936647Z" }, "papermill": { "duration": 4.748474, "end_time": "2022-10-27T19:37:52.941292", "exception": false, "start_time": "2022-10-27T19:37:48.192818", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 1152x144 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 1152x144 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 1152x144 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 1152x144 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 1152x144 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 1152x144 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 1152x144 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "image/png": "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\n", "text/plain": [ "<Figure size 1152x144 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "image/png": 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8zbWYORBWX3YoycVL6xdNbTBrY4xD0/eRJPdl8XjZ80cfz5m+j2xehXBSVhqzrs1sCWOM58cY3x1j/L8kH8/Lj/oaw8xS2z+bRVD9zTHGb0/NrsXMirD6soeT7Gx7SdvXZTEZwv2bXBO8prbf2/b7ji4neUeSx7MYuzdM3W5I8snNqRBO2kpj9v4k75tmorwyybeWHlGD2Tjm/b33ZHEtThZj+Pq257a9JIsJar6w0fXBsrZN8utJvjTG+NdLm1yLmZVtm13AXIwxXmp7U5JPJzknyR1jjCc2uSw4kQuS3Lf4NyfbkvzWGONTbR9Ocm/bDyR5Nsl1m1gjvELbu5NcleT8tgeT3Jzklhx/zO5Lcm0Wk9K8mOT9G14wHGOFMXxV211ZPDb5TJIPJskY44m29yZ5MosZWG8cY3x3E8qGZX8lyU8l+WLbR6e2fxrXYmami8fRAQAAYD48BgwAAMDsCKsAAADMjrAKAADA7AirAAAAzI6wCgAAwOwIqwAAAMyOsAoAAMDsCKsAAADMzv8HctUL96OrmqkAAAAASUVORK5CYII=\n", "text/plain": [ "<Figure size 1152x144 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 1152x144 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "image/png": "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\n", "text/plain": [ "<Figure size 1152x144 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 1152x144 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "image/png": 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YBryk7baVCTHafnMWEyndOd2y/6e2z5lmAX5VEnehOFnsTfLytl/b9vws+sVfJrkpyc6257d9YhaTy+zdwDrhhJv+g7HipVlMTJas3k/gZOD7ACZtn9T2G1aWkzw/i++KvUl2TbvtiiyxJlv2zurjafvSJL+aZFuSa9veOsZ4QZL/mOSNbf8tySNJXjPGeHA67CeSvDvJ1yf54PSCLWO1fjHGuK3tVUn+NsnDSV47xvjKdMzrknw4ySlJrhhj3LZB5cN6eUvbC7IYBnxXkv+UJI/XT2CrG2M87PsAHrU9ydXTr1yemuS9Y4wPtb0pyVVtL01yd5KXbWCNm0YXk9sCAADAfBgGDAAAwOwIqwAAAMyOsAoAAMDsCKsAAADMjrAKAADA7AirAAAAzI6wCgAAwOwIqwAAAMzO/wMTivC8t3btLwAAAABJRU5ErkJggg==\n", "text/plain": [ "<Figure size 1152x144 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "image/png": 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"text/plain": [ "<Figure size 1152x144 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "image/png": "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\n", "text/plain": [ "<Figure size 1152x144 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "image/png": 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"text/plain": [ "<Figure size 1152x144 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "for feature in stat_features:\n", " fig, ax = plt.subplots(figsize=(16, 2))\n", " ax.hist(train[feature], bins=50)\n", " ax.set_title(feature)" ] }, { "cell_type": "markdown", "id": "71482fe7", "metadata": { "papermill": { "duration": 0.039931, "end_time": "2022-10-27T19:37:53.023268", "exception": false, "start_time": "2022-10-27T19:37:52.983337", "status": "completed" }, "tags": [] }, "source": [ "# Validation" ] }, { "cell_type": "code", "execution_count": 20, "id": "00aab615", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:37:53.107757Z", "iopub.status.busy": "2022-10-27T19:37:53.107299Z", "iopub.status.idle": "2022-10-27T19:37:54.424086Z", "shell.execute_reply": "2022-10-27T19:37:54.422758Z" }, "papermill": { "duration": 1.362837, "end_time": "2022-10-27T19:37:54.426727", "exception": false, "start_time": "2022-10-27T19:37:53.063890", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<style type='text/css'>\n", ".datatable table.frame { margin-bottom: 0; }\n", ".datatable table.frame thead { border-bottom: none; }\n", ".datatable table.frame tr.coltypes td { color: #FFFFFF; line-height: 6px; padding: 0 0.5em;}\n", ".datatable .bool { background: #DDDD99; }\n", ".datatable .object { background: #565656; }\n", ".datatable .int { background: #5D9E5D; }\n", ".datatable .float { background: #4040CC; }\n", ".datatable .str { background: #CC4040; }\n", ".datatable .time { background: #40CC40; }\n", ".datatable .row_index { background: var(--jp-border-color3); border-right: 1px solid var(--jp-border-color0); color: var(--jp-ui-font-color3); font-size: 9px;}\n", ".datatable .frame tbody td { text-align: left; }\n", ".datatable .frame tr.coltypes .row_index { background: var(--jp-border-color0);}\n", ".datatable th:nth-child(2) { padding-left: 12px; }\n", ".datatable .hellipsis { color: var(--jp-cell-editor-border-color);}\n", ".datatable .vellipsis { background: var(--jp-layout-color0); color: var(--jp-cell-editor-border-color);}\n", ".datatable .na { color: var(--jp-cell-editor-border-color); font-size: 80%;}\n", ".datatable .sp { opacity: 0.25;}\n", ".datatable .footer { font-size: 9px; }\n", ".datatable .frame_dimensions { background: var(--jp-border-color3); border-top: 1px solid var(--jp-border-color0); color: var(--jp-ui-font-color3); display: inline-block; opacity: 0.6; padding: 1px 10px 1px 5px;}\n", "</style>\n" ], "text/plain": [ "<IPython.core.display.HTML object>" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [ "83556" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from sklearn.linear_model import Ridge\n", "from sklearn.neighbors import KNeighborsRegressor\n", "from sklearn.tree import DecisionTreeRegressor\n", "from sklearn.ensemble import RandomForestRegressor\n", "from lightgbm import LGBMRegressor\n", "import lightgbm as lgb\n", "from sklearn.multioutput import MultiOutputRegressor\n", "\n", "from sklearn.model_selection import KFold\n", "from sklearn.metrics import mean_squared_error\n", "from sklearn.metrics import r2_score\n", "\n", "from sklearn.preprocessing import StandardScaler\n", "from sklearn.feature_extraction.text import TfidfVectorizer\n", "import pickle\n", "\n", "def mc_rmse(y_true, y_pred):\n", " rmse_score_all = 0\n", " for i in range(0, 6):\n", " rmse_score = mean_squared_error(y_true[:,0], y_pred[:,0], squared=False)\n", " rmse_score_all += rmse_score\n", " return rmse_score_all / 6\n", "\n", "gc.collect()" ] }, { "cell_type": "code", "execution_count": 21, "id": "2e14fc01", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:37:54.507492Z", "iopub.status.busy": "2022-10-27T19:37:54.507116Z", "iopub.status.idle": "2022-10-27T19:37:59.627412Z", "shell.execute_reply": "2022-10-27T19:37:59.625770Z" }, "papermill": { "duration": 5.163809, "end_time": "2022-10-27T19:37:59.630019", "exception": false, "start_time": "2022-10-27T19:37:54.466210", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "X_full_text_n1.shape: (3911, 21069)\n", "X_pos_n1.shape: (3911, 17)\n", "X_lemma_n1.shape: (3911, 17438)\n", "X_label_n1.shape: (3911, 19)\n", "X_stats.shape: (3911, 16)\n", "X_all.shape: (3911, 38559)\n" ] } ], "source": [ "vectorizer_full_text_n1 = TfidfVectorizer(stop_words=\"english\", ngram_range=(1, 1))\n", "X_full_text_n1 = vectorizer_full_text_n1.fit_transform(train[\"full_text\"]).toarray()\n", "X_test_full_text_n1 = vectorizer_full_text_n1.transform(test[\"full_text\"]).toarray()\n", "\n", "vectorizer_pos_n1 = TfidfVectorizer(ngram_range=(1, 1))\n", "X_pos_n1 = vectorizer_pos_n1.fit_transform(train[\"POS\"]).toarray()\n", "X_test_pos_n1 = vectorizer_pos_n1.transform(test[\"POS\"]).toarray()\n", "\n", "vectorizer_lemma_n1 = TfidfVectorizer(stop_words=\"english\", ngram_range=(1, 1))\n", "X_lemma_n1 = vectorizer_lemma_n1.fit_transform(train[\"LEMMA\"]).toarray()\n", "X_test_lemma_n1 = vectorizer_lemma_n1.transform(test[\"LEMMA\"]).toarray()\n", "\n", "vectorizer_label_n1 = TfidfVectorizer(ngram_range=(1, 1))\n", "X_label_n1 = vectorizer_label_n1.fit_transform(train[\"LABEL\"]).toarray()\n", "X_test_label_n1 = vectorizer_label_n1.transform(test[\"LABEL\"]).toarray()\n", "\n", "X_stats = train[stat_features].to_numpy()\n", "X_text_stats = test[stat_features].to_numpy()\n", "\n", "X_all = np.hstack((X_full_text_n1, X_pos_n1, X_lemma_n1, X_stats, X_label_n1))\n", "X_test_all = np.hstack((X_test_full_text_n1, X_test_pos_n1, X_test_lemma_n1, X_text_stats, X_test_label_n1))\n", "\n", "y = train[labels].to_numpy()\n", "\n", "train_dict = {\n", " \"full_text_n1\": X_full_text_n1,\n", " \"pos_n1\": X_pos_n1,\n", " \"lemma_n1\": X_lemma_n1,\n", " \"label_n1\": X_label_n1,\n", " \"stats\": X_stats,\n", " \"all_n1\": X_all,\n", "}\n", "\n", "test_dict = {\n", " \"full_text_n1\": X_test_full_text_n1,\n", " \"pos_n1\": X_test_pos_n1,\n", " \"lemma_n1\": X_test_lemma_n1,\n", " \"label_n1\": X_test_label_n1,\n", " \"stats\": X_text_stats,\n", " \"all_n1\": X_test_all,\n", "}\n", "\n", "print(\"X_full_text_n1.shape:\", X_full_text_n1.shape)\n", "print(\"X_pos_n1.shape:\", X_pos_n1.shape)\n", "print(\"X_lemma_n1.shape:\", X_lemma_n1.shape)\n", "print(\"X_label_n1.shape:\", X_label_n1.shape)\n", "print(\"X_stats.shape:\", X_stats.shape)\n", "print(\"X_all.shape:\", X_all.shape)" ] }, { "cell_type": "code", "execution_count": 22, "id": "5c150761", "metadata": { "_kg_hide-input": true, "execution": { "iopub.execute_input": "2022-10-27T19:37:59.720888Z", "iopub.status.busy": "2022-10-27T19:37:59.719995Z", "iopub.status.idle": "2022-10-27T19:37:59.728311Z", "shell.execute_reply": "2022-10-27T19:37:59.726752Z" }, "papermill": { "duration": 0.060272, "end_time": "2022-10-27T19:37:59.730969", "exception": false, "start_time": "2022-10-27T19:37:59.670697", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "'''\n", "NFOLD=5\n", "kf = KFold(n_splits=NFOLD, shuffle=True, random_state=0)\n", "selected_stat_features = ['difficult_words', 'coleman_liau_index', 'crawford', 'smog_index',\n", " 'gulpease_index', 'dale_chall_readability_score']\n", "score_details_r2 = {key:0 for key in stat_features}\n", "score_details_rmse = {key:0 for key in stat_features}\n", "for fold, (train_index, val_index) in enumerate(kf.split(X_full_text_n1)):\n", " X_train, X_val = X_full_text_n1[train_index], X_full_text_n1[val_index]\n", " y_train, y_val = X_stats[train_index], X_stats[val_index]\n", " \n", " scaler = StandardScaler().fit(X_stats)\n", " y_train = scaler.transform(y_train)\n", " y_val = scaler.transform(y_val)\n", " \n", " model_lgbm = MultiOutputRegressor(LGBMRegressor(), n_jobs=-1).fit(X_train, y_train)\n", " val_preds_lgbm = model_lgbm.predict(X_val)\n", " ms_rmse_lgbm = mc_rmse(y_val, val_preds_lgbm)\n", " \n", " print(f\"fold {fold}, score: {ms_rmse_lgbm}\")\n", " for i in range(16):\n", " r_square = r2_score(y_val[:, i], val_preds_lgbm[:, i])\n", " rmse = mean_squared_error(y_val[:,i], val_preds_lgbm[:,i], squared=False)\n", " score_details_r2[stat_features[i]] += r_square/NFOLD\n", " score_details_rmse[stat_features[i]] += rmse/NFOLD\n", " \n", " del X_train, X_val, y_train, y_val\n", " gc.collect()\n", "''';" ] }, { "cell_type": "code", "execution_count": 23, "id": "15641330", "metadata": { "_kg_hide-input": true, "execution": { "iopub.execute_input": "2022-10-27T19:37:59.836446Z", "iopub.status.busy": "2022-10-27T19:37:59.835522Z", "iopub.status.idle": "2022-10-27T19:37:59.848258Z", "shell.execute_reply": "2022-10-27T19:37:59.846705Z" }, "papermill": { "duration": 0.06924, "end_time": "2022-10-27T19:37:59.850754", "exception": false, "start_time": "2022-10-27T19:37:59.781514", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "values = [['difficult_words', 0.5384438792921359, 0.7089487973147242],\n", " ['coleman_liau_index', 0.6895924750313855, 0.5226910999827121],\n", " ['crawford', 0.811208552901785, 0.3406058995044606],\n", " ['smog_index', 0.8661168439374631, 0.24789673496235784],\n", " ['gulpease_index', 0.9611410381066687, 0.07475228352665779],\n", " ['dale_chall_readability_score', 0.9840829546206842,\n", " 0.0031449149760098835],\n", " ['linsear_write_formula', 1.032164898629809, -0.06838537800144114],\n", " ['osman', 1.0024250425735577, -0.07605820772382624],\n", " ['flesch_reading_ease', 1.0059407058399736, -0.07815090692870719],\n", " ['gutierrez_polini', 1.0071147228791597, -0.0831228369714935],\n", " ['gunning_fog', 1.0059338892132892, -0.08481962059538001],\n", " ['szigriszt_pazos', 1.006124665202933, -0.08677813136123906],\n", " ['fernandez_huerta', 1.009898070092174, -0.09286688100582485],\n", " ['automated_readability_index', 1.0074979352332347,\n", " -0.09476267029511928],\n", " ['flesch_kincaid_grade', 1.0108127947382344, -0.09686693846586399],\n", " ['text_standard', 1.0300002916286095, -0.11601953173037179]]" ] }, { "cell_type": "code", "execution_count": 24, "id": "a68d7a00", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:37:59.932820Z", "iopub.status.busy": "2022-10-27T19:37:59.931850Z", "iopub.status.idle": "2022-10-27T19:37:59.948417Z", "shell.execute_reply": "2022-10-27T19:37:59.947170Z" }, "papermill": { "duration": 0.061234, "end_time": "2022-10-27T19:37:59.951676", "exception": false, "start_time": "2022-10-27T19:37:59.890442", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>feature</th>\n", " <th>rmse</th>\n", " <th>r2</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>0</th>\n", " <td>difficult_words</td>\n", " <td>0.538444</td>\n", " <td>0.708949</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>coleman_liau_index</td>\n", " <td>0.689592</td>\n", " <td>0.522691</td>\n", " </tr>\n", " <tr>\n", " <th>2</th>\n", " <td>crawford</td>\n", " <td>0.811209</td>\n", " <td>0.340606</td>\n", " </tr>\n", " <tr>\n", " <th>3</th>\n", " <td>smog_index</td>\n", " <td>0.866117</td>\n", " <td>0.247897</td>\n", " </tr>\n", " <tr>\n", " <th>4</th>\n", " <td>gulpease_index</td>\n", " <td>0.961141</td>\n", " <td>0.074752</td>\n", " </tr>\n", " <tr>\n", " <th>5</th>\n", " <td>dale_chall_readability_score</td>\n", " <td>0.984083</td>\n", " <td>0.003145</td>\n", " </tr>\n", " <tr>\n", " <th>6</th>\n", " <td>linsear_write_formula</td>\n", " <td>1.032165</td>\n", " <td>-0.068385</td>\n", " </tr>\n", " <tr>\n", " <th>7</th>\n", " <td>osman</td>\n", " <td>1.002425</td>\n", " <td>-0.076058</td>\n", " </tr>\n", " <tr>\n", " <th>8</th>\n", " <td>flesch_reading_ease</td>\n", " <td>1.005941</td>\n", " <td>-0.078151</td>\n", " </tr>\n", " <tr>\n", " <th>9</th>\n", " <td>gutierrez_polini</td>\n", " <td>1.007115</td>\n", " <td>-0.083123</td>\n", " </tr>\n", " <tr>\n", " <th>10</th>\n", " <td>gunning_fog</td>\n", " <td>1.005934</td>\n", " <td>-0.084820</td>\n", " </tr>\n", " <tr>\n", " <th>11</th>\n", " <td>szigriszt_pazos</td>\n", " <td>1.006125</td>\n", " <td>-0.086778</td>\n", " </tr>\n", " <tr>\n", " <th>12</th>\n", " <td>fernandez_huerta</td>\n", " <td>1.009898</td>\n", " <td>-0.092867</td>\n", " </tr>\n", " <tr>\n", " <th>13</th>\n", " <td>automated_readability_index</td>\n", " <td>1.007498</td>\n", " <td>-0.094763</td>\n", " </tr>\n", " <tr>\n", " <th>14</th>\n", " <td>flesch_kincaid_grade</td>\n", " <td>1.010813</td>\n", " <td>-0.096867</td>\n", " </tr>\n", " <tr>\n", " <th>15</th>\n", " <td>text_standard</td>\n", " <td>1.030000</td>\n", " <td>-0.116020</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " feature rmse r2\n", "0 difficult_words 0.538444 0.708949\n", "1 coleman_liau_index 0.689592 0.522691\n", "2 crawford 0.811209 0.340606\n", "3 smog_index 0.866117 0.247897\n", "4 gulpease_index 0.961141 0.074752\n", "5 dale_chall_readability_score 0.984083 0.003145\n", "6 linsear_write_formula 1.032165 -0.068385\n", "7 osman 1.002425 -0.076058\n", "8 flesch_reading_ease 1.005941 -0.078151\n", "9 gutierrez_polini 1.007115 -0.083123\n", "10 gunning_fog 1.005934 -0.084820\n", "11 szigriszt_pazos 1.006125 -0.086778\n", "12 fernandez_huerta 1.009898 -0.092867\n", "13 automated_readability_index 1.007498 -0.094763\n", "14 flesch_kincaid_grade 1.010813 -0.096867\n", "15 text_standard 1.030000 -0.116020" ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df_scores = pd.DataFrame(values,columns=[\"feature\", \"rmse\", \"r2\"])\n", "df_scores" ] }, { "cell_type": "code", "execution_count": 25, "id": "41554891", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:38:00.039465Z", "iopub.status.busy": "2022-10-27T19:38:00.038926Z", "iopub.status.idle": "2022-10-27T19:38:00.468388Z", "shell.execute_reply": "2022-10-27T19:38:00.466623Z" }, "papermill": { "duration": 0.473666, "end_time": "2022-10-27T19:38:00.471238", "exception": true, "start_time": "2022-10-27T19:37:59.997572", "status": "failed" }, "tags": [] }, "outputs": [ { "ename": "NameError", "evalue": "name 'kf' is not defined", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m/tmp/ipykernel_19/3385937402.py\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 20\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 21\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mf_index\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfeature\u001b[0m \u001b[0;32min\u001b[0m \u001b[0menumerate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mselected_stat_features\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 22\u001b[0;31m \u001b[0;32mfor\u001b[0m \u001b[0mfold\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mtrain_index\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mval_index\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32min\u001b[0m \u001b[0menumerate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkf\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msplit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mX_full_text_n1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 23\u001b[0m \u001b[0mX_train\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mX_val\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mX_full_text_n1\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mtrain_index\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mX_full_text_n1\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mval_index\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 24\u001b[0m \u001b[0my_train\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_val\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mX_stats\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mtrain_index\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mf_index\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mX_stats\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mval_index\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mf_index\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;31mNameError\u001b[0m: name 'kf' is not defined" ] } ], "source": [ "NFOLD=5\n", "selected_stat_features = ['difficult_words', 'coleman_liau_index', 'crawford', 'smog_index',\n", " 'gulpease_index', 'dale_chall_readability_score']\n", "\n", "X_stats = train[selected_stat_features].to_numpy()\n", "X_text_stats = test[selected_stat_features].to_numpy()\n", "\n", "scaler = StandardScaler().fit(X_stats)\n", "X_stats = scaler.transform(X_stats)\n", "X_text_stats = scaler.transform(X_text_stats)\n", "\n", "lgbm_params = {\n", " 'objective':'regression',\n", " 'metric':'rmse',\n", " 'learning_rate': 0.1,\n", " 'force_col_wise':True,\n", "}\n", "\n", "np_val = np.zeros_like(X_stats)\n", "\n", "for f_index, feature in enumerate(selected_stat_features):\n", " for fold, (train_index, val_index) in enumerate(kf.split(X_full_text_n1)):\n", " X_train, X_val = X_full_text_n1[train_index], X_full_text_n1[val_index]\n", " y_train, y_val = X_stats[train_index, f_index], X_stats[val_index, f_index]\n", " \n", " if f_index in [\"difficult_words\", \"gulpease_index\", 'dale_chall_readability_score']:\n", " dtrain = lgb.Dataset(X_train, y_train)\n", " dval = lgb.Dataset(X_val, y_val)\n", "\n", " model = lgb.train(params=lgbm_params, train_set=dtrain, valid_sets=[dval], num_boost_round=2000, \n", " early_stopping_rounds=100, verbose_eval=100)\n", " preds = model.predict(X_val)\n", "\n", " model.save_model(f'lgbm_{feature}_fold{fold}.txt')\n", " else:\n", " model = Ridge(alpha=0.7).fit(X_train, y_train)\n", " preds = model.predict(X_val)\n", " \n", " filename = f'ridge_{feature}_fold{fold}.sav'\n", " pickle.dump(model, open(filename, 'wb'))\n", " \n", " np_val[val_index, f_index] = preds\n", " \n", "df_meta = pd.DataFrame(np_val, columns=selected_stat_features)\n", "df_meta.to_csv(\"train_meta_csv\", index=False)" ] }, { "cell_type": "markdown", "id": "30e9aec2", "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "source": [ "## Sklearn Models" ] }, { "cell_type": "code", "execution_count": null, "id": "9b03f848", "metadata": { "_kg_hide-input": true, "execution": { "iopub.execute_input": "2022-10-27T13:22:56.139756Z", "iopub.status.busy": "2022-10-27T13:22:56.139322Z", "iopub.status.idle": "2022-10-27T13:22:56.159865Z", "shell.execute_reply": "2022-10-27T13:22:56.158384Z", "shell.execute_reply.started": "2022-10-27T13:22:56.139721Z" }, "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "outputs": [], "source": [ "def get_cross_val_score(train_dict, y, test_dict, nfolds=5):\n", " sub_copy = sub.copy()\n", " score_details = {\n", " \"model_name\": ['ridge', 'knn', 'dt', 'lgbm'],\n", " \"full_text_n1\": [],\n", " \"pos_n1\": [],\n", " \"lemma_n1\": [],\n", " \"label_n1\": [],\n", " \"stats\": [],\n", " \"all_n1\": [],\n", " }\n", " for key in train_dict.keys():\n", " X = train_dict[key]\n", " X_test = test_dict[key]\n", " kf = KFold(n_splits=nfolds, shuffle=True, random_state=0)\n", " test_ridge, test_knn, test_dt, test_lgbm = (np.zeros((X_test.shape[0], y.shape[1])), np.zeros((X_test.shape[0], y.shape[1])), \n", " np.zeros((X_test.shape[0], y.shape[1])), np.zeros((X_test.shape[0], y.shape[1])))\n", " val_ridge, val_knn, val_dt, val_lgbm = 0, 0, 0, 0\n", " for train_index, val_index in kf.split(X):\n", " X_train, X_val = X[train_index], X[val_index]\n", " y_train, y_val = y[train_index], y[val_index]\n", " \n", " model_ridge = Ridge().fit(X_train, y_train)\n", " model_knn = KNeighborsRegressor().fit(X_train, y_train)\n", " model_dt = DecisionTreeRegressor().fit(X_train, y_train)\n", " model_lgbm = MultiOutputRegressor(LGBMRegressor(), n_jobs=-1).fit(X_train, y_train)\n", " \n", " val_preds_ridge = model_ridge.predict(X_val)\n", " val_preds_knn = model_knn.predict(X_val)\n", " val_preds_dt = model_dt.predict(X_val)\n", " val_preds_lgbm = model_lgbm.predict(X_val)\n", " \n", " test_preds_ridge = model_ridge.predict(X_test)\n", " test_preds_knn = model_knn.predict(X_test)\n", " test_preds_dt = model_dt.predict(X_test)\n", " test_preds_lgbm = model_lgbm.predict(X_test)\n", " \n", " ms_rmse_ridge = mc_rmse(y_val, val_preds_ridge)\n", " ms_rmse_knn = mc_rmse(y_val, val_preds_knn)\n", " ms_rmse_dt = mc_rmse(y_val, val_preds_dt)\n", " ms_rmse_lgbm = mc_rmse(y_val, val_preds_lgbm)\n", " \n", " val_ridge += ms_rmse_ridge / nfolds\n", " val_knn += ms_rmse_knn / nfolds\n", " val_dt += ms_rmse_dt / nfolds\n", " val_lgbm += ms_rmse_lgbm / nfolds\n", " \n", " test_ridge += test_preds_ridge / nfolds\n", " test_knn += test_preds_knn / nfolds\n", " test_dt += test_preds_dt / nfolds\n", " test_lgbm += test_preds_lgbm / nfolds\n", " \n", " del X_train, X_val\n", " gc.collect()\n", " \n", " score_details[key] = [val_ridge, val_knn, val_dt, val_lgbm]\n", " sub_copy.iloc[:, 1:] = test_ridge\n", " sub_copy.to_csv(f\"sub_{key}_ridge_f{nfolds}.csv\", index=False)\n", " sub_copy.iloc[:, 1:] = test_knn\n", " sub_copy.to_csv(f\"sub_{key}_knn_f{nfolds}.csv\", index=False)\n", " sub_copy.iloc[:, 1:] = test_dt\n", " sub_copy.to_csv(f\"sub_{key}_dt_f{nfolds}.csv\", index=False)\n", " sub_copy.iloc[:, 1:] = test_lgbm\n", " sub_copy.to_csv(f\"sub_{key}_lgbm_f{nfolds}.csv\", index=False)\n", " \n", " del X, X_test\n", " gc.collect()\n", " \n", " return pd.DataFrame(score_details)" ] }, { "cell_type": "code", "execution_count": null, "id": "43468b51", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T13:23:18.265763Z", "iopub.status.busy": "2022-10-27T13:23:18.265283Z", "iopub.status.idle": "2022-10-27T13:32:43.955061Z", "shell.execute_reply": "2022-10-27T13:32:43.954064Z", "shell.execute_reply.started": "2022-10-27T13:23:18.265724Z" }, "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "outputs": [], "source": [ "df_scores = get_cross_val_score(train_dict, y, test_dict, nfolds=5)\n", "df_scores" ] }, { "cell_type": "code", "execution_count": null, "id": "f5c17859", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T09:32:33.749655Z", "iopub.status.busy": "2022-10-27T09:32:33.749190Z", "iopub.status.idle": "2022-10-27T09:32:33.756386Z", "shell.execute_reply": "2022-10-27T09:32:33.754918Z", "shell.execute_reply.started": "2022-10-27T09:32:33.749607Z" }, "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "outputs": [], "source": [ "df_scores_lb = {\n", " \"model_name\": ['ridge', 'knn', 'dt', 'lgbm'],\n", " \"full_text_n1\": [0.55],\n", " \"pos_n1\": [0.59],\n", " \"lemma_n1\": [0.56],\n", " \"label_n1\": [0.62],\n", " \"stats\": [],\n", " \"all_n1\": [],\n", "}" ] }, { "cell_type": "markdown", "id": "3774bf26", "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "source": [ "## CosineSimilarity Model" ] }, { "cell_type": "code", "execution_count": null, "id": "19129a8b", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T09:32:27.576104Z", "iopub.status.busy": "2022-10-27T09:32:27.575569Z", "iopub.status.idle": "2022-10-27T09:32:27.583162Z", "shell.execute_reply": "2022-10-27T09:32:27.581828Z", "shell.execute_reply.started": "2022-10-27T09:32:27.576065Z" }, "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "outputs": [], "source": [] }, { "cell_type": "markdown", "id": "08a7c67d", "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "source": [ "## Tensorflow Embedding with LSTM" ] }, { "cell_type": "code", "execution_count": null, "id": "124b83a9", "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "outputs": [], "source": [] }, { "cell_type": "markdown", "id": "ba61e173", "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "source": [ "## Transformers" ] }, { "cell_type": "code", "execution_count": null, "id": "5a8c7d97", "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "outputs": [], "source": [] }, { "attachments": { "2ef725fb-ab8f-4061-979a-7c88dbd376ae.jpg": { "image/jpeg": 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"__notebook__.ipynb", "output_path": "__notebook__.ipynb", "parameters": {}, "start_time": "2022-10-27T19:25:43.006875", "version": "2.3.4" } }, "nbformat": 4, "nbformat_minor": 5 }	0109/325/109325638.ipynb	s3://data-agents/kaggle-outputs/sharded/011_00109.jsonl.gz
{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.7.12","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"# This Python 3 environment comes with many helpful analytics libraries installed\n# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n# For example, here's several helpful packages to load\n\nimport numpy as np # linear algebra\nimport pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n\n# Input data files are available in the read-only \"../input/\" directory\n# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n\nimport os\nfor dirname, _, filenames in os.walk('/kaggle/input'):\n for filename in filenames:\n print(os.path.join(dirname, filename))\n\n# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","trusted":true},"execution_count":null,"outputs":[]},{"cell_type":"markdown","source":"Importing Libraries","metadata":{}},{"cell_type":"code","source":"import numpy as np \nimport pandas as pd\nfrom sklearn.impute import KNNImputer\nfrom sklearn.model_selection import train_test_split, StratifiedKFold\nfrom sklearn.ensemble import RandomForestClassifier\nfrom xgboost import XGBClassifier\nfrom sklearn.datasets import make_classification\nfrom sklearn.impute import SimpleImputer\nimport plotly.graph_objs as go\nimport plotly.offline as py\nimport seaborn as sns\nimport matplotlib.pyplot as plt\nfrom sklearn.metrics import f1_score\nfrom sklearn.metrics import mean_squared_error\nfrom sklearn import metrics\nfrom sklearn.metrics import roc_auc_score\nfrom sklearn.metrics import accuracy_score\nfrom sklearn.metrics import mean_absolute_error\nfrom sklearn.metrics import precision_score\nfrom imblearn.under_sampling import RandomUnderSampler","metadata":{"execution":{"iopub.status.busy":"2022-10-27T16:55:08.414578Z","iopub.execute_input":"2022-10-27T16:55:08.415085Z","iopub.status.idle":"2022-10-27T16:55:10.332093Z","shell.execute_reply.started":"2022-10-27T16:55:08.414984Z","shell.execute_reply":"2022-10-27T16:55:10.330721Z"},"trusted":true},"execution_count":1,"outputs":[]},{"cell_type":"code","source":"data = pd.read_csv(\"../input/sepsis-train-eda/final_Sepsis_EDA.csv\")\ndata.head()","metadata":{"execution":{"iopub.status.busy":"2022-10-27T16:55:10.336551Z","iopub.execute_input":"2022-10-27T16:55:10.336896Z","iopub.status.idle":"2022-10-27T16:55:15.527732Z","shell.execute_reply.started":"2022-10-27T16:55:10.336853Z","shell.execute_reply":"2022-10-27T16:55:15.526611Z"},"trusted":true},"execution_count":2,"outputs":[{"execution_count":2,"output_type":"execute_result","data":{"text/plain":" Unnamed: 0 Hour HR O2Sat Temp SBP MAP DBP Resp EtCO2 ... \\\n0 12 12 69.0 99.0 36.11 107.0 67.0 NaN 22.0 NaN ... \n1 21 21 93.0 100.0 36.80 103.0 62.0 52.0 18.0 NaN ... \n2 4 4 76.0 100.0 36.70 137.0 81.0 48.0 16.0 NaN ... \n3 2 2 82.0 100.0 38.80 113.0 85.0 66.0 13.0 NaN ... \n4 33 33 94.0 96.0 36.50 154.0 102.0 NaN 26.0 NaN ... \n\n WBC Fibrinogen Platelets Age Gender HospAdmTime ICULOS \\\n0 NaN NaN NaN 83.95 1 -2.87 14 \n1 NaN NaN NaN 61.00 1 0.00 22 \n2 NaN NaN NaN 74.00 0 0.00 5 \n3 NaN NaN NaN 63.00 1 0.00 3 \n4 NaN NaN NaN 54.88 1 -0.02 34 \n\n SepsisLabel Patient_ID ICU_Type \n0 0 7461 0.0 \n1 0 105529 0.0 \n2 0 114196 1.0 \n3 0 108059 2.0 \n4 0 18919 0.0 \n\n[5 rows x 43 columns]","text/html":"<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>Unnamed: 0</th>\n <th>Hour</th>\n <th>HR</th>\n <th>O2Sat</th>\n <th>Temp</th>\n <th>SBP</th>\n <th>MAP</th>\n <th>DBP</th>\n <th>Resp</th>\n <th>EtCO2</th>\n <th>...</th>\n <th>WBC</th>\n <th>Fibrinogen</th>\n <th>Platelets</th>\n <th>Age</th>\n <th>Gender</th>\n <th>HospAdmTime</th>\n <th>ICULOS</th>\n <th>SepsisLabel</th>\n <th>Patient_ID</th>\n <th>ICU_Type</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\n <td>12</td>\n <td>12</td>\n <td>69.0</td>\n <td>99.0</td>\n <td>36.11</td>\n <td>107.0</td>\n <td>67.0</td>\n <td>NaN</td>\n <td>22.0</td>\n <td>NaN</td>\n <td>...</td>\n <td>NaN</td>\n <td>NaN</td>\n <td>NaN</td>\n <td>83.95</td>\n <td>1</td>\n <td>-2.87</td>\n <td>14</td>\n <td>0</td>\n <td>7461</td>\n <td>0.0</td>\n </tr>\n <tr>\n <th>1</th>\n <td>21</td>\n <td>21</td>\n <td>93.0</td>\n <td>100.0</td>\n <td>36.80</td>\n <td>103.0</td>\n <td>62.0</td>\n <td>52.0</td>\n <td>18.0</td>\n <td>NaN</td>\n <td>...</td>\n <td>NaN</td>\n <td>NaN</td>\n <td>NaN</td>\n <td>61.00</td>\n <td>1</td>\n <td>0.00</td>\n <td>22</td>\n <td>0</td>\n <td>105529</td>\n <td>0.0</td>\n </tr>\n <tr>\n <th>2</th>\n <td>4</td>\n <td>4</td>\n <td>76.0</td>\n <td>100.0</td>\n <td>36.70</td>\n <td>137.0</td>\n <td>81.0</td>\n <td>48.0</td>\n <td>16.0</td>\n <td>NaN</td>\n <td>...</td>\n <td>NaN</td>\n <td>NaN</td>\n <td>NaN</td>\n <td>74.00</td>\n <td>0</td>\n <td>0.00</td>\n <td>5</td>\n <td>0</td>\n <td>114196</td>\n <td>1.0</td>\n </tr>\n <tr>\n <th>3</th>\n <td>2</td>\n <td>2</td>\n <td>82.0</td>\n <td>100.0</td>\n <td>38.80</td>\n <td>113.0</td>\n <td>85.0</td>\n <td>66.0</td>\n <td>13.0</td>\n <td>NaN</td>\n <td>...</td>\n <td>NaN</td>\n <td>NaN</td>\n <td>NaN</td>\n <td>63.00</td>\n <td>1</td>\n <td>0.00</td>\n <td>3</td>\n <td>0</td>\n <td>108059</td>\n <td>2.0</td>\n </tr>\n <tr>\n <th>4</th>\n <td>33</td>\n <td>33</td>\n <td>94.0</td>\n <td>96.0</td>\n <td>36.50</td>\n <td>154.0</td>\n <td>102.0</td>\n <td>NaN</td>\n <td>26.0</td>\n <td>NaN</td>\n <td>...</td>\n <td>NaN</td>\n <td>NaN</td>\n <td>NaN</td>\n <td>54.88</td>\n <td>1</td>\n <td>-0.02</td>\n <td>34</td>\n <td>0</td>\n <td>18919</td>\n <td>0.0</td>\n </tr>\n </tbody>\n</table>\n<p>5 rows × 43 columns</p>\n</div>"},"metadata":{}}]},{"cell_type":"code","source":"df = data[['Patient_ID','Hour', 'HR', 'O2Sat', 'Temp','MAP','Resp','BaseExcess','FiO2', 'pH', 'PaCO2','Calcium','Creatinine','Platelets','BUN','Glucose', 'Magnesium','Potassium','Hct','WBC',\n 'Age', 'Gender', 'HospAdmTime', 'ICU_Type', 'SepsisLabel']].copy()","metadata":{"execution":{"iopub.status.busy":"2022-10-27T16:55:15.529929Z","iopub.execute_input":"2022-10-27T16:55:15.531091Z","iopub.status.idle":"2022-10-27T16:55:15.680178Z","shell.execute_reply.started":"2022-10-27T16:55:15.531053Z","shell.execute_reply":"2022-10-27T16:55:15.679120Z"},"trusted":true},"execution_count":3,"outputs":[]},{"cell_type":"code","source":"df.columns","metadata":{"execution":{"iopub.status.busy":"2022-10-27T17:03:55.858703Z","iopub.execute_input":"2022-10-27T17:03:55.859132Z","iopub.status.idle":"2022-10-27T17:03:55.866849Z","shell.execute_reply.started":"2022-10-27T17:03:55.859097Z","shell.execute_reply":"2022-10-27T17:03:55.865384Z"},"trusted":true},"execution_count":11,"outputs":[{"execution_count":11,"output_type":"execute_result","data":{"text/plain":"Index(['Patient_ID', 'Hour', 'HR', 'O2Sat', 'Temp', 'MAP', 'Resp',\n 'BaseExcess', 'FiO2', 'pH', 'PaCO2', 'Calcium', 'Creatinine',\n 'Platelets', 'BUN', 'Glucose', 'Magnesium', 'Potassium', 'Hct', 'WBC',\n 'Age', 'Gender', 'HospAdmTime', 'ICU_Type', 'SepsisLabel'],\n dtype='object')"},"metadata":{}}]},{"cell_type":"code","source":"df['BaseExcess']=df.groupby('Patient_ID')['BaseExcess'].apply(lambda group: group.interpolate(method='linear',limit_direction = 'both'))\ndf['FiO2']=df.groupby('Patient_ID')['FiO2'].apply(lambda group: group.interpolate(method='linear',limit_direction = 'both'))\ndf['pH']=df.groupby('Patient_ID')['pH'].apply(lambda group: group.interpolate(method='linear',limit_direction = 'both'))\ndf['PaCO2']=df.groupby('Patient_ID')['PaCO2'].apply(lambda group: group.interpolate(method='linear',limit_direction = 'both'))\ndf['BUN']=df.groupby('Patient_ID')['BUN'].apply(lambda group: group.interpolate(method='linear',limit_direction = 'both'))\ndf['Calcium']=df.groupby('Patient_ID')['Calcium'].apply(lambda group: group.interpolate(method='linear',limit_direction = 'both'))\ndf['Creatinine']=df.groupby('Patient_ID')['Creatinine'].apply(lambda group: group.interpolate(method='linear',limit_direction = 'both'))\ndf['Glucose']=df.groupby('Patient_ID')['Glucose'].apply(lambda group: group.interpolate(method='linear',limit_direction = 'both'))\ndf['Magnesium']=df.groupby('Patient_ID')['Magnesium'].apply(lambda group: group.interpolate(method='linear',limit_direction = 'both'))\ndf['Potassium']=df.groupby('Patient_ID')['Potassium'].apply(lambda group: group.interpolate(method='linear',limit_direction = 'both'))\ndf['Hct']=df.groupby('Patient_ID')['Hct'].apply(lambda group: group.interpolate(method='linear',limit_direction = 'both'))\ndf['WBC']=df.groupby('Patient_ID')['WBC'].apply(lambda group: group.interpolate(method='linear',limit_direction = 'both'))\ndf['Platelets']=df.groupby('Patient_ID')['Platelets'].apply(lambda group: group.interpolate(method='linear',limit_direction = 'both'))","metadata":{"execution":{"iopub.status.busy":"2022-10-27T16:55:15.682368Z","iopub.execute_input":"2022-10-27T16:55:15.682711Z","iopub.status.idle":"2022-10-27T16:58:35.380604Z","shell.execute_reply.started":"2022-10-27T16:55:15.682678Z","shell.execute_reply":"2022-10-27T16:58:35.379594Z"},"trusted":true},"execution_count":4,"outputs":[]},{"cell_type":"code","source":"df.isna().sum(axis=0).sort_values(ascending=False)/len(df) * 100","metadata":{"execution":{"iopub.status.busy":"2022-10-27T03:45:56.117072Z","iopub.execute_input":"2022-10-27T03:45:56.117410Z","iopub.status.idle":"2022-10-27T03:45:56.153891Z","shell.execute_reply.started":"2022-10-27T03:45:56.117383Z","shell.execute_reply":"2022-10-27T03:45:56.152995Z"},"trusted":true},"execution_count":7,"outputs":[{"execution_count":7,"output_type":"execute_result","data":{"text/plain":"BaseExcess 65.774189\nFiO2 53.480541\nPaCO2 53.265815\npH 51.598274\nCalcium 18.002053\nMagnesium 16.546079\nPlatelets 12.743820\nWBC 12.468699\nCreatinine 11.468750\nBUN 10.765200\nHct 10.237444\nPotassium 8.791039\nGlucose 6.528100\nTemp 0.027317\nResp 0.004646\nO2Sat 0.000650\nHospAdmTime 0.000000\nAge 0.000000\nGender 0.000000\nICU_Type 0.000000\nPatient_ID 0.000000\nHour 0.000000\nMAP 0.000000\nHR 0.000000\nSepsisLabel 0.000000\ndtype: float64"},"metadata":{}}]},{"cell_type":"code","source":"df = df[df['Temp'].notna()]\ndf = df[df['O2Sat'].notna()]\ndf = df[df['Resp'].notna()]","metadata":{"execution":{"iopub.status.busy":"2022-10-27T16:59:33.002295Z","iopub.execute_input":"2022-10-27T16:59:33.003103Z","iopub.status.idle":"2022-10-27T16:59:33.461501Z","shell.execute_reply.started":"2022-10-27T16:59:33.003065Z","shell.execute_reply":"2022-10-27T16:59:33.460626Z"},"trusted":true},"execution_count":5,"outputs":[]},{"cell_type":"code","source":"df.head()","metadata":{"execution":{"iopub.status.busy":"2022-10-27T17:05:30.672659Z","iopub.execute_input":"2022-10-27T17:05:30.674221Z","iopub.status.idle":"2022-10-27T17:05:30.713985Z","shell.execute_reply.started":"2022-10-27T17:05:30.674159Z","shell.execute_reply":"2022-10-27T17:05:30.712715Z"},"trusted":true},"execution_count":12,"outputs":[{"execution_count":12,"output_type":"execute_result","data":{"text/plain":" Patient_ID Hour HR O2Sat Temp MAP Resp BaseExcess FiO2 pH \\\n0 7461 12 69.0 99.0 36.11 67.0 22.0 NaN NaN NaN \n1 105529 21 93.0 100.0 36.80 62.0 18.0 NaN NaN NaN \n2 114196 4 76.0 100.0 36.70 81.0 16.0 NaN NaN NaN \n3 108059 2 82.0 100.0 38.80 85.0 13.0 NaN 0.35 7.43 \n4 18919 33 94.0 96.0 36.50 102.0 26.0 NaN 0.95 NaN \n\n ... Glucose Magnesium Potassium Hct WBC Age Gender HospAdmTime \\\n0 ... 153.0 2.3 5.6 24.5 13.2 83.95 1 -2.87 \n1 ... 178.0 NaN 3.3 35.5 4.7 61.00 1 0.00 \n2 ... 106.0 2.0 4.4 36.6 7.5 74.00 0 0.00 \n3 ... 157.0 NaN 4.2 NaN NaN 63.00 1 0.00 \n4 ... 155.0 2.1 3.5 37.4 33.4 54.88 1 -0.02 \n\n ICU_Type SepsisLabel \n0 0.0 0 \n1 0.0 0 \n2 1.0 0 \n3 2.0 0 \n4 0.0 0 \n\n[5 rows x 25 columns]","text/html":"<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>Patient_ID</th>\n <th>Hour</th>\n <th>HR</th>\n <th>O2Sat</th>\n <th>Temp</th>\n <th>MAP</th>\n <th>Resp</th>\n <th>BaseExcess</th>\n <th>FiO2</th>\n <th>pH</th>\n <th>...</th>\n <th>Glucose</th>\n <th>Magnesium</th>\n <th>Potassium</th>\n <th>Hct</th>\n <th>WBC</th>\n <th>Age</th>\n <th>Gender</th>\n <th>HospAdmTime</th>\n <th>ICU_Type</th>\n <th>SepsisLabel</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\n <td>7461</td>\n <td>12</td>\n <td>69.0</td>\n <td>99.0</td>\n <td>36.11</td>\n <td>67.0</td>\n <td>22.0</td>\n <td>NaN</td>\n <td>NaN</td>\n <td>NaN</td>\n <td>...</td>\n <td>153.0</td>\n <td>2.3</td>\n <td>5.6</td>\n <td>24.5</td>\n <td>13.2</td>\n <td>83.95</td>\n <td>1</td>\n <td>-2.87</td>\n <td>0.0</td>\n <td>0</td>\n </tr>\n <tr>\n <th>1</th>\n <td>105529</td>\n <td>21</td>\n <td>93.0</td>\n <td>100.0</td>\n <td>36.80</td>\n <td>62.0</td>\n <td>18.0</td>\n <td>NaN</td>\n <td>NaN</td>\n <td>NaN</td>\n <td>...</td>\n <td>178.0</td>\n <td>NaN</td>\n <td>3.3</td>\n <td>35.5</td>\n <td>4.7</td>\n <td>61.00</td>\n <td>1</td>\n <td>0.00</td>\n <td>0.0</td>\n <td>0</td>\n </tr>\n <tr>\n <th>2</th>\n <td>114196</td>\n <td>4</td>\n <td>76.0</td>\n <td>100.0</td>\n <td>36.70</td>\n <td>81.0</td>\n <td>16.0</td>\n <td>NaN</td>\n <td>NaN</td>\n <td>NaN</td>\n <td>...</td>\n <td>106.0</td>\n <td>2.0</td>\n <td>4.4</td>\n <td>36.6</td>\n <td>7.5</td>\n <td>74.00</td>\n <td>0</td>\n <td>0.00</td>\n <td>1.0</td>\n <td>0</td>\n </tr>\n <tr>\n <th>3</th>\n <td>108059</td>\n <td>2</td>\n <td>82.0</td>\n <td>100.0</td>\n <td>38.80</td>\n <td>85.0</td>\n <td>13.0</td>\n <td>NaN</td>\n <td>0.35</td>\n <td>7.43</td>\n <td>...</td>\n <td>157.0</td>\n <td>NaN</td>\n <td>4.2</td>\n <td>NaN</td>\n <td>NaN</td>\n <td>63.00</td>\n <td>1</td>\n <td>0.00</td>\n <td>2.0</td>\n <td>0</td>\n </tr>\n <tr>\n <th>4</th>\n <td>18919</td>\n <td>33</td>\n <td>94.0</td>\n <td>96.0</td>\n <td>36.50</td>\n <td>102.0</td>\n <td>26.0</td>\n <td>NaN</td>\n <td>0.95</td>\n <td>NaN</td>\n <td>...</td>\n <td>155.0</td>\n <td>2.1</td>\n <td>3.5</td>\n <td>37.4</td>\n <td>33.4</td>\n <td>54.88</td>\n <td>1</td>\n <td>-0.02</td>\n <td>0.0</td>\n <td>0</td>\n </tr>\n </tbody>\n</table>\n<p>5 rows × 25 columns</p>\n</div>"},"metadata":{}}]},{"cell_type":"markdown","source":"Sampling","metadata":{}},{"cell_type":"code","source":"Sep0=df.loc[(df['SepsisLabel']==0) ]\nSep1 =df.loc[(df['SepsisLabel']==1) ]","metadata":{"execution":{"iopub.status.busy":"2022-10-27T16:59:42.307290Z","iopub.execute_input":"2022-10-27T16:59:42.307706Z","iopub.status.idle":"2022-10-27T16:59:42.458610Z","shell.execute_reply.started":"2022-10-27T16:59:42.307673Z","shell.execute_reply":"2022-10-27T16:59:42.457441Z"},"trusted":true},"execution_count":6,"outputs":[]},{"cell_type":"code","source":"len(Sep1)","metadata":{"execution":{"iopub.status.busy":"2022-10-27T16:59:42.800305Z","iopub.execute_input":"2022-10-27T16:59:42.800730Z","iopub.status.idle":"2022-10-27T16:59:42.808285Z","shell.execute_reply.started":"2022-10-27T16:59:42.800696Z","shell.execute_reply":"2022-10-27T16:59:42.806941Z"},"trusted":true},"execution_count":7,"outputs":[{"execution_count":7,"output_type":"execute_result","data":{"text/plain":"18935"},"metadata":{}}]},{"cell_type":"code","source":"len(Sep0)","metadata":{"execution":{"iopub.status.busy":"2022-10-27T16:59:43.608293Z","iopub.execute_input":"2022-10-27T16:59:43.608722Z","iopub.status.idle":"2022-10-27T16:59:43.616450Z","shell.execute_reply.started":"2022-10-27T16:59:43.608689Z","shell.execute_reply":"2022-10-27T16:59:43.615209Z"},"trusted":true},"execution_count":8,"outputs":[{"execution_count":8,"output_type":"execute_result","data":{"text/plain":"1056980"},"metadata":{}}]},{"cell_type":"code","source":"X= Sep0.drop(['SepsisLabel'],axis = 1)\ny = Sep0['SepsisLabel']","metadata":{"execution":{"iopub.status.busy":"2022-10-27T04:09:17.308644Z","iopub.execute_input":"2022-10-27T04:09:17.308997Z","iopub.status.idle":"2022-10-27T04:09:17.348931Z","shell.execute_reply.started":"2022-10-27T04:09:17.308969Z","shell.execute_reply":"2022-10-27T04:09:17.347972Z"},"trusted":true},"execution_count":19,"outputs":[]},{"cell_type":"code","source":"from sklearn.datasets import make_classification\n\nX, y = make_classification(n_samples=50000, n_features=25, n_informative=24,\n n_redundant=0, n_repeated=0,n_classes=2,\n n_clusters_per_class=1,\n random_state=0)\n","metadata":{"execution":{"iopub.status.busy":"2022-10-27T17:08:33.170733Z","iopub.execute_input":"2022-10-27T17:08:33.171179Z","iopub.status.idle":"2022-10-27T17:08:33.273705Z","shell.execute_reply.started":"2022-10-27T17:08:33.171143Z","shell.execute_reply":"2022-10-27T17:08:33.271974Z"},"trusted":true},"execution_count":13,"outputs":[]},{"cell_type":"code","source":"rus = RandomUnderSampler(random_state=0)\nrus.fit(X, y)\nX_resampled, y_resampled = rus.fit_resample(X, y)","metadata":{"execution":{"iopub.status.busy":"2022-10-27T18:13:01.445769Z","iopub.execute_input":"2022-10-27T18:13:01.446191Z","iopub.status.idle":"2022-10-27T18:13:01.478852Z","shell.execute_reply.started":"2022-10-27T18:13:01.446155Z","shell.execute_reply":"2022-10-27T18:13:01.477927Z"},"trusted":true},"execution_count":20,"outputs":[]},{"cell_type":"code","source":"print(X_resampled)","metadata":{"execution":{"iopub.status.busy":"2022-10-27T17:53:28.783504Z","iopub.execute_input":"2022-10-27T17:53:28.783914Z","iopub.status.idle":"2022-10-27T17:53:28.790394Z","shell.execute_reply.started":"2022-10-27T17:53:28.783879Z","shell.execute_reply":"2022-10-27T17:53:28.789071Z"},"trusted":true},"execution_count":18,"outputs":[{"name":"stdout","text":"[[-2.92883868 -2.34500783 0.75938345 ... -1.44057272 2.55484772\n -0.85360485]\n [ 1.40049788 -1.56384767 3.35085223 ... 2.05048374 1.32804195\n -2.00287498]\n [ 0.660329 0.21991275 1.35918781 ... -0.9889733 -0.72878511\n 0.3490803 ]\n ...\n [-3.94250579 2.84997832 3.54439077 ... 1.583228 -3.69622141\n -1.07981827]\n [-1.54718568 -2.54977063 -0.90715934 ... 2.51195846 -2.73391815\n -2.73985634]\n [ 1.69611856 -1.54332061 -1.26189913 ... 0.44439909 3.40161495\n -4.23414253]]\n","output_type":"stream"}]},{"cell_type":"code","source":"df1 = pd.DataFrame(X_resampled)\ndf1","metadata":{"execution":{"iopub.status.busy":"2022-10-27T18:13:47.595067Z","iopub.execute_input":"2022-10-27T18:13:47.595510Z","iopub.status.idle":"2022-10-27T18:13:47.649097Z","shell.execute_reply.started":"2022-10-27T18:13:47.595475Z","shell.execute_reply":"2022-10-27T18:13:47.647689Z"},"trusted":true},"execution_count":21,"outputs":[{"execution_count":21,"output_type":"execute_result","data":{"text/plain":" 0 1 2 3 4 5 6 \\\n0 -2.928839 -2.345008 0.759383 2.769413 1.089959 -0.694917 -3.648652 \n1 1.400498 -1.563848 3.350852 1.166694 5.786960 -4.551359 -2.270792 \n2 0.660329 0.219913 1.359188 -0.860015 2.232439 -3.063134 -1.889419 \n3 0.162166 6.859671 1.192628 1.635488 2.710302 -3.612925 -0.891918 \n4 -3.045220 1.032010 0.461564 -3.990741 1.103141 2.617638 -0.367998 \n... ... ... ... ... ... ... ... \n49975 1.752055 0.793041 4.446170 -1.172375 1.183033 -1.117922 -2.410851 \n49976 0.667696 1.404571 -0.747331 2.481867 1.100730 1.951693 2.427095 \n49977 -3.942506 2.849978 3.544391 7.283262 -0.685431 -3.000169 2.616386 \n49978 -1.547186 -2.549771 -0.907159 0.370923 2.903038 -4.722659 0.813451 \n49979 1.696119 -1.543321 -1.261899 1.403397 2.619160 0.912821 4.253015 \n\n 7 8 9 ... 15 16 17 \\\n0 1.187393 -0.396709 0.422570 ... -0.662187 0.082782 -2.646799 \n1 2.256506 -0.056216 1.955314 ... 1.586601 5.659941 1.459374 \n2 0.021365 -0.391175 1.887698 ... 2.188487 4.478132 -0.393927 \n3 0.424200 -6.023653 0.618309 ... 2.707585 -1.273260 0.220403 \n4 -0.227598 3.139862 3.947338 ... 0.902729 -4.303863 1.842884 \n... ... ... ... ... ... ... ... \n49975 -4.160490 -0.212244 -5.415652 ... -2.586864 2.079586 6.067314 \n49976 -4.820272 0.198704 2.076123 ... -0.874020 -2.253887 2.721895 \n49977 0.282595 -0.416623 1.211812 ... -4.191266 -2.780676 3.220323 \n49978 3.490076 0.291218 -2.650012 ... -0.071897 3.297932 3.622839 \n49979 3.781952 3.094525 -0.306866 ... -1.083855 2.853787 5.173252 \n\n 18 19 20 21 22 23 24 \n0 -1.839073 0.551557 -0.923028 0.276704 -1.440573 2.554848 -0.853605 \n1 -1.900422 2.626839 -0.501087 -2.075163 2.050484 1.328042 -2.002875 \n2 2.201543 -3.529522 -4.044893 -3.656676 -0.988973 -0.728785 0.349080 \n3 -0.772826 1.372742 1.053407 -0.894290 4.753714 -5.314489 -3.048451 \n4 -0.200097 1.177124 -4.382551 2.398384 3.356508 -2.869137 -4.724928 \n... ... ... ... ... ... ... ... \n49975 -4.433519 -0.045579 0.844620 4.622501 2.350095 -3.945312 2.891969 \n49976 -0.614366 1.627054 0.328617 0.538429 3.180807 3.257126 -1.555196 \n49977 2.106951 -3.689466 -2.771002 4.725590 1.583228 -3.696221 -1.079818 \n49978 -0.662559 -5.824940 -1.912048 -5.557300 2.511958 -2.733918 -2.739856 \n49979 4.382314 -7.835657 -2.020280 -12.532003 0.444399 3.401615 -4.234143 \n\n[49980 rows x 25 columns]","text/html":"<div>\n<style scoped>\n .dataframe tbody tr th:only-of-type {\n vertical-align: middle;\n }\n\n .dataframe tbody tr th {\n vertical-align: top;\n }\n\n .dataframe thead th {\n text-align: right;\n }\n</style>\n<table border=\"1\" class=\"dataframe\">\n <thead>\n <tr style=\"text-align: right;\">\n <th></th>\n <th>0</th>\n <th>1</th>\n <th>2</th>\n <th>3</th>\n <th>4</th>\n <th>5</th>\n <th>6</th>\n <th>7</th>\n <th>8</th>\n <th>9</th>\n <th>...</th>\n <th>15</th>\n <th>16</th>\n <th>17</th>\n <th>18</th>\n <th>19</th>\n <th>20</th>\n <th>21</th>\n <th>22</th>\n <th>23</th>\n <th>24</th>\n </tr>\n </thead>\n <tbody>\n <tr>\n <th>0</th>\n <td>-2.928839</td>\n <td>-2.345008</td>\n <td>0.759383</td>\n <td>2.769413</td>\n <td>1.089959</td>\n <td>-0.694917</td>\n <td>-3.648652</td>\n <td>1.187393</td>\n <td>-0.396709</td>\n <td>0.422570</td>\n <td>...</td>\n <td>-0.662187</td>\n <td>0.082782</td>\n <td>-2.646799</td>\n <td>-1.839073</td>\n <td>0.551557</td>\n <td>-0.923028</td>\n <td>0.276704</td>\n <td>-1.440573</td>\n <td>2.554848</td>\n <td>-0.853605</td>\n </tr>\n <tr>\n <th>1</th>\n <td>1.400498</td>\n <td>-1.563848</td>\n <td>3.350852</td>\n <td>1.166694</td>\n <td>5.786960</td>\n <td>-4.551359</td>\n <td>-2.270792</td>\n <td>2.256506</td>\n <td>-0.056216</td>\n <td>1.955314</td>\n <td>...</td>\n <td>1.586601</td>\n <td>5.659941</td>\n <td>1.459374</td>\n <td>-1.900422</td>\n <td>2.626839</td>\n <td>-0.501087</td>\n <td>-2.075163</td>\n <td>2.050484</td>\n <td>1.328042</td>\n <td>-2.002875</td>\n </tr>\n <tr>\n <th>2</th>\n <td>0.660329</td>\n <td>0.219913</td>\n <td>1.359188</td>\n <td>-0.860015</td>\n <td>2.232439</td>\n <td>-3.063134</td>\n <td>-1.889419</td>\n <td>0.021365</td>\n <td>-0.391175</td>\n <td>1.887698</td>\n <td>...</td>\n <td>2.188487</td>\n <td>4.478132</td>\n <td>-0.393927</td>\n <td>2.201543</td>\n <td>-3.529522</td>\n <td>-4.044893</td>\n <td>-3.656676</td>\n <td>-0.988973</td>\n <td>-0.728785</td>\n <td>0.349080</td>\n </tr>\n <tr>\n <th>3</th>\n <td>0.162166</td>\n <td>6.859671</td>\n <td>1.192628</td>\n <td>1.635488</td>\n <td>2.710302</td>\n <td>-3.612925</td>\n <td>-0.891918</td>\n <td>0.424200</td>\n <td>-6.023653</td>\n <td>0.618309</td>\n <td>...</td>\n <td>2.707585</td>\n <td>-1.273260</td>\n <td>0.220403</td>\n <td>-0.772826</td>\n <td>1.372742</td>\n <td>1.053407</td>\n <td>-0.894290</td>\n <td>4.753714</td>\n <td>-5.314489</td>\n <td>-3.048451</td>\n </tr>\n <tr>\n <th>4</th>\n <td>-3.045220</td>\n <td>1.032010</td>\n <td>0.461564</td>\n <td>-3.990741</td>\n <td>1.103141</td>\n <td>2.617638</td>\n <td>-0.367998</td>\n <td>-0.227598</td>\n <td>3.139862</td>\n <td>3.947338</td>\n <td>...</td>\n <td>0.902729</td>\n <td>-4.303863</td>\n <td>1.842884</td>\n <td>-0.200097</td>\n <td>1.177124</td>\n <td>-4.382551</td>\n <td>2.398384</td>\n <td>3.356508</td>\n <td>-2.869137</td>\n <td>-4.724928</td>\n </tr>\n <tr>\n <th>...</th>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n <td>...</td>\n </tr>\n <tr>\n <th>49975</th>\n <td>1.752055</td>\n <td>0.793041</td>\n <td>4.446170</td>\n <td>-1.172375</td>\n <td>1.183033</td>\n <td>-1.117922</td>\n <td>-2.410851</td>\n <td>-4.160490</td>\n <td>-0.212244</td>\n <td>-5.415652</td>\n <td>...</td>\n <td>-2.586864</td>\n <td>2.079586</td>\n <td>6.067314</td>\n <td>-4.433519</td>\n <td>-0.045579</td>\n <td>0.844620</td>\n <td>4.622501</td>\n <td>2.350095</td>\n <td>-3.945312</td>\n <td>2.891969</td>\n </tr>\n <tr>\n <th>49976</th>\n <td>0.667696</td>\n <td>1.404571</td>\n <td>-0.747331</td>\n <td>2.481867</td>\n <td>1.100730</td>\n <td>1.951693</td>\n <td>2.427095</td>\n <td>-4.820272</td>\n <td>0.198704</td>\n <td>2.076123</td>\n <td>...</td>\n <td>-0.874020</td>\n <td>-2.253887</td>\n <td>2.721895</td>\n <td>-0.614366</td>\n <td>1.627054</td>\n <td>0.328617</td>\n <td>0.538429</td>\n <td>3.180807</td>\n <td>3.257126</td>\n <td>-1.555196</td>\n </tr>\n <tr>\n <th>49977</th>\n <td>-3.942506</td>\n <td>2.849978</td>\n <td>3.544391</td>\n <td>7.283262</td>\n <td>-0.685431</td>\n <td>-3.000169</td>\n <td>2.616386</td>\n <td>0.282595</td>\n <td>-0.416623</td>\n <td>1.211812</td>\n <td>...</td>\n <td>-4.191266</td>\n <td>-2.780676</td>\n <td>3.220323</td>\n <td>2.106951</td>\n <td>-3.689466</td>\n <td>-2.771002</td>\n <td>4.725590</td>\n <td>1.583228</td>\n <td>-3.696221</td>\n <td>-1.079818</td>\n </tr>\n <tr>\n <th>49978</th>\n <td>-1.547186</td>\n <td>-2.549771</td>\n <td>-0.907159</td>\n <td>0.370923</td>\n <td>2.903038</td>\n <td>-4.722659</td>\n <td>0.813451</td>\n <td>3.490076</td>\n <td>0.291218</td>\n <td>-2.650012</td>\n <td>...</td>\n <td>-0.071897</td>\n <td>3.297932</td>\n <td>3.622839</td>\n <td>-0.662559</td>\n <td>-5.824940</td>\n <td>-1.912048</td>\n <td>-5.557300</td>\n <td>2.511958</td>\n <td>-2.733918</td>\n <td>-2.739856</td>\n </tr>\n <tr>\n <th>49979</th>\n <td>1.696119</td>\n <td>-1.543321</td>\n <td>-1.261899</td>\n <td>1.403397</td>\n <td>2.619160</td>\n <td>0.912821</td>\n <td>4.253015</td>\n <td>3.781952</td>\n <td>3.094525</td>\n <td>-0.306866</td>\n <td>...</td>\n <td>-1.083855</td>\n <td>2.853787</td>\n <td>5.173252</td>\n <td>4.382314</td>\n <td>-7.835657</td>\n <td>-2.020280</td>\n <td>-12.532003</td>\n <td>0.444399</td>\n <td>3.401615</td>\n <td>-4.234143</td>\n </tr>\n </tbody>\n</table>\n<p>49980 rows × 25 columns</p>\n</div>"},"metadata":{}}]},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]}]}	0109/326/109326116.ipynb	s3://data-agents/kaggle-outputs/sharded/011_00109.jsonl.gz
{ "cells": [ { "cell_type": "markdown", "id": "8ec76cb0", "metadata": { "papermill": { "duration": 0.013677, "end_time": "2022-10-27T19:39:21.822079", "exception": false, "start_time": "2022-10-27T19:39:21.808402", "status": "completed" }, "tags": [] }, "source": [ "# Kaggle Survey 2022 Analysis " ] }, { "cell_type": "markdown", "id": "d67e51d8", "metadata": { "papermill": { "duration": 0.013599, "end_time": "2022-10-27T19:39:21.847735", "exception": false, "start_time": "2022-10-27T19:39:21.834136", "status": "completed" }, "tags": [] }, "source": [ "# Table of Contents\n", "1. [Importing Libraries](#Importing-Libraries)\n", "2. [Reading and Cleaning Data](#Reading-and-Cleaning-Data) \n", " 2.1 [Algorithm to clean this data](#Algorithm-to-clean-this-data) \n", "3. [Exploratory Data Analysis](#Exploratory-Data-Analysis) \n", " 3.1 [Age Group Distribution](#Age-Group-Distribution-(Pie-Chart)) \n", " 3.2 [Survey Response Time Statstics](#Survey-Response-Time-Statstics) \n", " 3.3 [Gender Distribution](#Gender-Distribution-in-Kaggle) \n", " 3.4 [Are you studying?](#Are-you-studying?) \n", " 3.5 [Coding Experience of Kaggle Users](#Kaggle-User-Coding-Experience) \n", " 3.6 [Qualification of Kaggle Users](#Kaggle-User-Qualification) \n", " 3.7 [ML Experience](#Kaggle-User-ML-Experience) \n", " 3.8 [Occupation of Kaggle Users](#Kaggle-User-Occupation) \n", " 3.9 [Top 10 Industries Kaggle Users Work In](#Top-10-Industries-Worked-in-by-Kaggle-Users) \n", " 3.10 [Yearly Compensation (in \\$)](#Kaggle-Users-Yearly-Compensation) \n", " 3.11 [Top 5 Programming languages used by Kaggle Users](#Top-5-Programming-languages-used-by-Kaggle-Users) \n", " 3.12 [Top 5 Data Viz Libraries used by Kaggle Users](#Top-5-Data-Viz-Libraries-used-by-Kaggle-Users) \n", " 3.13 [Top 5 ML Framework used by Kaggle Users](#Top-5-ML-Framework-used-by-Kaggle-Users) \n", " 3.14 [Top 10 ML Algorithms used by Kaggle Users](#Top-10-ML-Algorithms-used-by-Kaggle-Users) \n", " 3.15 [Top 5 BI Tools preferred by Kaggle Users](#Top-5-BI-Tools-preffered-by-Kaggle-Users) \n", " 3.16 [Top 10 Relational Databases used by Kaggle Users](#Top-10-Relational-Databases-used-by-Kaggle-Users) \n", " 3.17 [Top 5 Learning Platforms preffered by Kaggle Users](#Top-5-Learning-Platforms-preffered-by-Kaggle-Users)\n" ] }, { "cell_type": "markdown", "id": "b4c18f3a", "metadata": { "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19", "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5", "papermill": { "duration": 0.011475, "end_time": "2022-10-27T19:39:21.871110", "exception": false, "start_time": "2022-10-27T19:39:21.859635", "status": "completed" }, "tags": [] }, "source": [ "# Importing Libraries " ] }, { "cell_type": "code", "execution_count": 1, "id": "21f6ddc0", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:39:21.897694Z", "iopub.status.busy": "2022-10-27T19:39:21.896714Z", "iopub.status.idle": "2022-10-27T19:39:24.196330Z", "shell.execute_reply": "2022-10-27T19:39:24.195200Z" }, "papermill": { "duration": 2.316812, "end_time": "2022-10-27T19:39:24.199694", "exception": false, "start_time": "2022-10-27T19:39:21.882882", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "import numpy as np\n", "import pandas as pd\n", "import plotly.express as px\n", "import matplotlib.pyplot as plt\n", "import seaborn as sns\n", "import plotly.io as pio\n" ] }, { "cell_type": "code", "execution_count": 2, "id": "2c2ca675", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:39:24.231120Z", "iopub.status.busy": "2022-10-27T19:39:24.230047Z", "iopub.status.idle": "2022-10-27T19:39:25.119745Z", "shell.execute_reply": "2022-10-27T19:39:25.118606Z" }, "papermill": { "duration": 0.911291, "end_time": "2022-10-27T19:39:25.122949", "exception": false, "start_time": "2022-10-27T19:39:24.211658", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "pd.set_option('display.max_rows', None)\n", "pd.set_option('max_columns', None)\n", "sns.set_style('darkgrid')\n", "sns.set_context(font_scale=1.5)\n", "plt.style.use('dark_background')\n", "pio.templates.default = 'plotly_dark'" ] }, { "cell_type": "markdown", "id": "2db398c5", "metadata": { "papermill": { "duration": 0.011597, "end_time": "2022-10-27T19:39:25.146517", "exception": false, "start_time": "2022-10-27T19:39:25.134920", "status": "completed" }, "tags": [] }, "source": [ "# Reading and Cleaning Data" ] }, { "cell_type": "code", "execution_count": 3, "id": "05429ba4", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:39:25.172588Z", "iopub.status.busy": "2022-10-27T19:39:25.171950Z", "iopub.status.idle": "2022-10-27T19:39:26.342905Z", "shell.execute_reply": "2022-10-27T19:39:26.341840Z" }, 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importan...</td>\n", " <td>What is your current yearly compensation (appr...</td>\n", " <td>Approximately how much money have you spent on...</td>\n", " <td>Which of the following cloud computing platfor...</td>\n", " <td>Which of the following cloud computing platfor...</td>\n", " <td>Which of the following cloud computing platfor...</td>\n", " <td>Which of the following cloud computing platfor...</td>\n", " <td>Which of the following cloud computing platfor...</td>\n", " <td>Which of the following cloud computing platfor...</td>\n", " <td>Which of the following cloud computing platfor...</td>\n", " <td>Which of the following cloud computing platfor...</td>\n", " <td>Which of the following cloud computing platfor...</td>\n", " <td>Which of the following cloud computing platfor...</td>\n", " <td>Which of the following cloud computing platfor...</td>\n", " <td>Which of the following cloud computing platfor...</td>\n", " <td>Of the cloud platforms that you are familiar w...</td>\n", " <td>Do you use any of the following cloud computin...</td>\n", " <td>Do you use any of the following cloud computin...</td>\n", " <td>Do you use any of the following cloud computin...</td>\n", " <td>Do you use any of the following cloud computin...</td>\n", " <td>Do you use any of the following cloud computin...</td>\n", " <td>Do you use any of the following data storage p...</td>\n", " <td>Do you use any of the following data storage p...</td>\n", " <td>Do you use any of the following data storage p...</td>\n", " <td>Do you use any of the following data storage p...</td>\n", " <td>Do you use any of the following data storage p...</td>\n", " <td>Do you use any of the following data storage p...</td>\n", " <td>Do you use any of the following data storage p...</td>\n", " <td>Do you use any of the following data storage p...</td>\n", " <td>Do you use any of the following data products ...</td>\n", " <td>Do you use any of the following data products ...</td>\n", " <td>Do you use any of the following data products ...</td>\n", " <td>Do you use any of the following data products ...</td>\n", " <td>Do you use any of the following data products ...</td>\n", " <td>Do you use any of the following data products ...</td>\n", " <td>Do you use any of the following data products ...</td>\n", " <td>Do you use any of the following data products ...</td>\n", " <td>Do you use any of the following data products ...</td>\n", " <td>Do you use any of the following data products ...</td>\n", " <td>Do you use any of the following data products ...</td>\n", " <td>Do you use any of the following data products ...</td>\n", " <td>Do you use any of the following data products ...</td>\n", " <td>Do you use any of the following data products ...</td>\n", " <td>Do you use any of the following data products ...</td>\n", " <td>Do you use any of the following data products ...</td>\n", " <td>Do you use any of the following business intel...</td>\n", " <td>Do you use any of the following business intel...</td>\n", " <td>Do you use any of the following business intel...</td>\n", " <td>Do you use any of the following business intel...</td>\n", " <td>Do you use any of the following business intel...</td>\n", " <td>Do you use any of the following business intel...</td>\n", " <td>Do you use any of the following business intel...</td>\n", " <td>Do you use any of the following business intel...</td>\n", " <td>Do you use any of the following business intel...</td>\n", " <td>Do you use any of the following business intel...</td>\n", " <td>Do you use any of the following business intel...</td>\n", " <td>Do you use any of the following business intel...</td>\n", " <td>Do you use any of the following business intel...</td>\n", " <td>Do you use any of the following business intel...</td>\n", " <td>Do you use any of the following business intel...</td>\n", " <td>Do you use any of the following managed machin...</td>\n", " <td>Do you use any of the following managed machin...</td>\n", " <td>Do you use any of the following managed machin...</td>\n", " <td>Do you use any of the following managed machin...</td>\n", " <td>Do you use any of the following managed machin...</td>\n", " <td>Do you use any of the following managed machin...</td>\n", " <td>Do you use any of the following managed machin...</td>\n", " <td>Do you use any of the following managed machin...</td>\n", " <td>Do you use any of the following managed machin...</td>\n", " <td>Do you use any of the following managed machin...</td>\n", " <td>Do you use any of the following managed machin...</td>\n", " <td>Do you use any of the following managed machin...</td>\n", " <td>Do you use any of the following managed machin...</td>\n", " <td>Do you use any of the following automated mach...</td>\n", " <td>Do you use any of the following automated mach...</td>\n", " <td>Do you use any of the following automated mach...</td>\n", " <td>Do you use any of the following automated mach...</td>\n", " <td>Do you use any of the following automated mach...</td>\n", " <td>Do you use any of the following automated mach...</td>\n", " <td>Do you use any of the following automated mach...</td>\n", " <td>Do you use any of the following automated mach...</td>\n", " <td>Do you use any of the following products to se...</td>\n", " <td>Do you use any of the following products to se...</td>\n", " <td>Do you use any of the following products to se...</td>\n", " <td>Do you use any of the following products to se...</td>\n", " <td>Do you use any of the following products to se...</td>\n", " <td>Do you use any of the following products to se...</td>\n", " <td>Do you use any of the following products to se...</td>\n", " <td>Do you use any of the following products to se...</td>\n", " <td>Do you use any of the following products to se...</td>\n", " <td>Do you use any of the following products to se...</td>\n", " <td>Do you use any of the following products to se...</td>\n", " <td>Do you use any of the following products to se...</td>\n", " <td>Do you use any tools to help monitor your mach...</td>\n", " <td>Do you use any tools to help monitor your mach...</td>\n", " <td>Do you use any tools to help monitor your mach...</td>\n", " <td>Do you use any tools to help monitor your mach...</td>\n", " <td>Do you use any tools to help monitor your mach...</td>\n", " <td>Do you use any tools to help monitor your mach...</td>\n", " <td>Do you use any tools to help monitor your mach...</td>\n", " <td>Do you use any tools to help monitor your mach...</td>\n", " <td>Do you use any tools to help monitor your mach...</td>\n", " <td>Do you use any tools to help monitor your mach...</td>\n", " <td>Do you use any tools to help monitor your mach...</td>\n", " <td>Do you use any tools to help monitor your mach...</td>\n", " <td>Do you use any tools to help monitor your mach...</td>\n", " <td>Do you use any tools to help monitor your mach...</td>\n", " <td>Do you use any tools to help monitor your mach...</td>\n", " <td>Do you use any of the following responsible or...</td>\n", " <td>Do you use any of the following responsible or...</td>\n", " <td>Do you use any of the following responsible or...</td>\n", " <td>Do you use any of the following responsible or...</td>\n", " <td>Do you use any of the following responsible or...</td>\n", " <td>Do you use any of the following responsible or...</td>\n", " <td>Do you use any of the following responsible or...</td>\n", " <td>Do you use any of the following responsible or...</td>\n", " <td>Do you use any of the following responsible or...</td>\n", " <td>Do you use any of the following types of speci...</td>\n", " <td>Do you use any of the following types of speci...</td>\n", " <td>Do you use any of the following types of speci...</td>\n", " <td>Do you use any of the following types of speci...</td>\n", " <td>Do you use any of the following types of speci...</td>\n", " <td>Do you use any of the following types of speci...</td>\n", " <td>Do you use any of the following types of speci...</td>\n", " <td>Do you use any of the following types of speci...</td>\n", " <td>Do you use any of the following types of speci...</td>\n", " <td>Approximately how many times have you used a T...</td>\n", " <td>Who/what are your favorite media sources that ...</td>\n", " <td>Who/what are your favorite media sources that ...</td>\n", " <td>Who/what are your favorite media sources that ...</td>\n", " <td>Who/what are your favorite media sources that ...</td>\n", " <td>Who/what are your favorite media sources that ...</td>\n", " <td>Who/what are your favorite media sources that ...</td>\n", " <td>Who/what are your favorite media sources that ...</td>\n", " <td>Who/what are your favorite media sources that ...</td>\n", " <td>Who/what are your favorite media sources that ...</td>\n", " <td>Who/what are your favorite media sources that ...</td>\n", " <td>Who/what are your favorite media sources that ...</td>\n", " <td>Who/what are your favorite media sources that ...</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>121</td>\n", " <td>30-34</td>\n", " <td>Man</td>\n", " <td>India</td>\n", " <td>No</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>Other</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " 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<td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " Duration (in seconds) Q2 \\\n", "0 Duration (in seconds) What is your age (# years)? \n", "1 121 30-34 \n", "\n", " Q3 \\\n", "0 What is your gender? - Selected Choice \n", "1 Man \n", "\n", " Q4 \\\n", "0 In which country do you currently reside? \n", "1 India \n", "\n", " Q5 \\\n", "0 Are you currently a student? (high school, uni... \n", "1 No \n", "\n", " Q6_1 \\\n", "0 On which platforms have you begun or completed... \n", "1 NaN \n", "\n", " Q6_2 \\\n", "0 On which platforms have you begun or completed... \n", "1 NaN \n", "\n", " Q6_3 \\\n", "0 On which platforms have you begun or completed... \n", "1 NaN \n", "\n", " Q6_4 \\\n", "0 On which platforms have you begun or completed... \n", "1 NaN \n", "\n", " Q6_5 \\\n", "0 On which platforms have you begun or completed... \n", "1 NaN \n", "\n", " Q6_6 \\\n", "0 On which platforms have you begun or completed... \n", "1 NaN \n", "\n", " Q6_7 \\\n", "0 On which platforms have you begun or completed... \n", "1 NaN \n", "\n", " Q6_8 \\\n", "0 On which platforms have you begun or completed... \n", "1 NaN \n", "\n", " Q6_9 \\\n", "0 On which platforms have you begun or completed... \n", "1 NaN \n", "\n", " Q6_10 \\\n", "0 On which platforms have you begun or completed... \n", "1 NaN \n", "\n", " Q6_11 \\\n", "0 On which platforms have you begun or completed... \n", "1 NaN \n", "\n", " Q6_12 \\\n", "0 On which platforms have you begun or completed... \n", "1 Other \n", "\n", " Q7_1 \\\n", "0 What products or platforms did you find to be ... \n", "1 NaN \n", "\n", " Q7_2 \\\n", "0 What products or platforms did you find to be ... \n", "1 NaN \n", "\n", " Q7_3 \\\n", "0 What products or platforms did you find to be ... \n", "1 NaN \n", "\n", " Q7_4 \\\n", "0 What products or platforms did you find to be ... \n", "1 NaN \n", "\n", " Q7_5 \\\n", "0 What products or platforms did you find to be ... \n", "1 NaN \n", "\n", " Q7_6 \\\n", "0 What products or platforms did you find to be ... \n", "1 NaN \n", "\n", " Q7_7 \\\n", "0 What products or platforms did you find to be ... \n", "1 NaN \n", "\n", " Q8 \\\n", "0 What is the highest level of formal education ... \n", "1 NaN \n", "\n", " Q9 \\\n", "0 Have you ever published any academic research ... \n", "1 NaN \n", "\n", " Q10_1 \\\n", "0 Did your research make use of machine 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on a reg... \n", "1 NaN \n", "\n", " Q12_9 \\\n", "0 What programming languages do you use on a reg... \n", "1 NaN \n", "\n", " Q12_10 \\\n", "0 What programming languages do you use on a reg... \n", "1 NaN \n", "\n", " Q12_11 \\\n", "0 What programming languages do you use on a reg... \n", "1 NaN \n", "\n", " Q12_12 \\\n", "0 What programming languages do you use on a reg... \n", "1 NaN \n", "\n", " Q12_13 \\\n", "0 What programming languages do you use on a reg... \n", "1 NaN \n", "\n", " Q12_14 \\\n", "0 What programming languages do you use on a reg... \n", "1 NaN \n", "\n", " Q12_15 \\\n", "0 What programming languages do you use on a reg... \n", "1 NaN \n", "\n", " Q13_1 \\\n", "0 Which of the following integrated development ... \n", "1 NaN \n", "\n", " Q13_2 \\\n", "0 Which of the following integrated development ... \n", "1 NaN \n", "\n", " Q13_3 \\\n", "0 Which of the following integrated development ... \n", "1 NaN \n", "\n", " Q13_4 \\\n", "0 Which of the following integrated development ... \n", "1 NaN \n", "\n", " Q13_5 \\\n", "0 Which of the following integrated development ... \n", "1 NaN \n", "\n", " Q13_6 \\\n", "0 Which of the following integrated development ... \n", "1 NaN \n", "\n", " Q13_7 \\\n", "0 Which of the following integrated development ... \n", "1 NaN \n", "\n", " Q13_8 \\\n", "0 Which of the following integrated development ... \n", "1 NaN \n", "\n", " Q13_9 \\\n", "0 Which of the following integrated development ... \n", "1 NaN \n", "\n", " Q13_10 \\\n", "0 Which of the following integrated development ... \n", "1 NaN \n", "\n", " Q13_11 \\\n", "0 Which of the following integrated development ... \n", "1 NaN \n", "\n", " Q13_12 \\\n", "0 Which of the following integrated development ... \n", "1 NaN \n", "\n", " Q13_13 \\\n", "0 Which of the following integrated development ... \n", "1 NaN \n", "\n", " Q13_14 \\\n", "0 Which of the following integrated development ... \n", "1 NaN \n", "\n", " Q14_1 \\\n", "0 Do you use any of the following hosted noteboo... \n", "1 NaN \n", "\n", " Q14_2 \\\n", "0 Do you use any of the following hosted noteboo... \n", "1 NaN \n", "\n", " Q14_3 \\\n", "0 Do you use any of the following hosted noteboo... \n", "1 NaN \n", "\n", " Q14_4 \\\n", "0 Do you use any of the following hosted noteboo... \n", "1 NaN \n", "\n", " Q14_5 \\\n", "0 Do you use any of the following hosted noteboo... \n", "1 NaN \n", "\n", " Q14_6 \\\n", "0 Do you use any of the following hosted noteboo... \n", "1 NaN \n", "\n", " Q14_7 \\\n", "0 Do you use any of the following hosted noteboo... \n", "1 NaN \n", "\n", " Q14_8 \\\n", "0 Do you use any of the following hosted noteboo... \n", "1 NaN \n", "\n", " Q14_9 \\\n", "0 Do you use any of the following hosted noteboo... \n", "1 NaN \n", "\n", " Q14_10 \\\n", "0 Do you use any of the following hosted noteboo... \n", "1 NaN \n", "\n", " Q14_11 \\\n", "0 Do you use any of the following hosted noteboo... \n", "1 NaN \n", "\n", " Q14_12 \\\n", "0 Do you use any of the following hosted noteboo... \n", "1 NaN \n", "\n", " Q14_13 \\\n", "0 Do you use any of the following hosted noteboo... \n", "1 NaN \n", "\n", " Q14_14 \\\n", "0 Do you use any of the following hosted noteboo... \n", "1 NaN \n", "\n", " Q14_15 \\\n", "0 Do you use any of the following hosted noteboo... \n", "1 NaN \n", "\n", " Q14_16 \\\n", "0 Do you use any of the following hosted noteboo... \n", "1 NaN \n", "\n", " Q15_1 \\\n", "0 Do you use any of the following data visualiza... \n", "1 NaN \n", "\n", " Q15_2 \\\n", "0 Do you use any of the following data visualiza... \n", "1 NaN \n", "\n", " Q15_3 \\\n", "0 Do you use any of the following data visualiza... \n", "1 NaN \n", "\n", " Q15_4 \\\n", "0 Do you use any of the following data visualiza... \n", "1 NaN \n", "\n", " Q15_5 \\\n", "0 Do you use any of the following data visualiza... \n", "1 NaN \n", "\n", " Q15_6 \\\n", "0 Do you use any of the following data visualiza... \n", "1 NaN \n", "\n", " Q15_7 \\\n", "0 Do you use any of the following data visualiza... \n", "1 NaN \n", "\n", " Q15_8 \\\n", "0 Do you use any of the following data visualiza... \n", "1 NaN \n", "\n", " Q15_9 \\\n", "0 Do you use any of the following data visualiza... \n", "1 NaN \n", "\n", " Q15_10 \\\n", "0 Do you use any of the following data visualiza... \n", "1 NaN \n", "\n", " Q15_11 \\\n", "0 Do you use any of the following data visualiza... \n", "1 NaN \n", "\n", " Q15_12 \\\n", "0 Do you use any of the following data visualiza... \n", "1 NaN \n", "\n", " Q15_13 \\\n", "0 Do you use any of the following data visualiza... \n", "1 NaN \n", "\n", " Q15_14 \\\n", "0 Do you use any of the following data visualiza... \n", "1 NaN \n", "\n", " Q15_15 \\\n", "0 Do you use any of the following data visualiza... \n", "1 NaN \n", "\n", " Q16 \\\n", "0 For how many years have you used machine learn... \n", "1 NaN \n", "\n", " Q17_1 \\\n", "0 Which of the following machine learning framew... \n", "1 NaN \n", "\n", " Q17_2 \\\n", "0 Which of the following machine learning framew... \n", "1 NaN \n", "\n", " Q17_3 \\\n", "0 Which of the following machine learning framew... \n", "1 NaN \n", "\n", " Q17_4 \\\n", "0 Which of the following machine learning framew... \n", "1 NaN \n", "\n", " Q17_5 \\\n", "0 Which of the following machine learning framew... \n", "1 NaN \n", "\n", " Q17_6 \\\n", "0 Which of the following machine learning framew... \n", "1 NaN \n", "\n", " Q17_7 \\\n", "0 Which of the following machine learning framew... \n", "1 NaN \n", "\n", " Q17_8 \\\n", "0 Which of the following machine learning framew... \n", "1 NaN \n", "\n", " Q17_9 \\\n", "0 Which of the following machine learning framew... \n", "1 NaN \n", "\n", " Q17_10 \\\n", "0 Which of the following machine learning framew... \n", "1 NaN \n", "\n", " Q17_11 \\\n", "0 Which of the following machine learning framew... \n", "1 NaN \n", "\n", " Q17_12 \\\n", "0 Which of the following machine learning framew... \n", "1 NaN \n", "\n", " Q17_13 \\\n", "0 Which of the following machine learning framew... \n", "1 NaN \n", "\n", " Q17_14 \\\n", "0 Which of the following machine learning framew... \n", "1 NaN \n", "\n", " Q17_15 \\\n", "0 Which of the following machine learning framew... \n", "1 NaN \n", "\n", " Q18_1 \\\n", "0 Which of the following ML algorithms do you us... \n", "1 NaN \n", "\n", " Q18_2 \\\n", "0 Which of the following ML algorithms do you us... \n", "1 NaN \n", "\n", " Q18_3 \\\n", "0 Which of the following ML algorithms do you us... \n", "1 NaN \n", "\n", " Q18_4 \\\n", "0 Which of the following ML algorithms do you us... \n", "1 NaN \n", "\n", " Q18_5 \\\n", "0 Which of the following ML algorithms do you us... \n", "1 NaN \n", "\n", " Q18_6 \\\n", "0 Which of the following ML algorithms do you us... \n", "1 NaN \n", "\n", " Q18_7 \\\n", "0 Which of the following ML algorithms do you us... \n", "1 NaN \n", "\n", " Q18_8 \\\n", "0 Which of the following ML algorithms do you us... \n", "1 NaN \n", "\n", " Q18_9 \\\n", "0 Which of the following ML algorithms do you us... \n", "1 NaN \n", "\n", " Q18_10 \\\n", "0 Which of the following ML algorithms do you us... \n", "1 NaN \n", "\n", " Q18_11 \\\n", "0 Which of the following ML algorithms do you us... \n", "1 NaN \n", "\n", " Q18_12 \\\n", "0 Which of the following ML algorithms do you us... \n", "1 NaN \n", "\n", " Q18_13 \\\n", "0 Which of the following ML algorithms do you us... \n", "1 NaN \n", "\n", " Q18_14 \\\n", "0 Which of the following ML algorithms do you us... \n", "1 NaN \n", "\n", " Q19_1 \\\n", "0 Which categories of computer vision methods do... \n", "1 NaN \n", "\n", " Q19_2 \\\n", "0 Which categories of computer vision methods do... \n", "1 NaN \n", "\n", " Q19_3 \\\n", "0 Which categories of computer vision methods do... \n", "1 NaN \n", "\n", " Q19_4 \\\n", "0 Which categories of computer vision methods do... \n", "1 NaN \n", "\n", " Q19_5 \\\n", "0 Which categories of computer vision methods do... \n", "1 NaN \n", "\n", " Q19_6 \\\n", "0 Which categories of computer vision methods do... \n", "1 NaN \n", "\n", " Q19_7 \\\n", "0 Which categories of computer vision methods do... \n", "1 NaN \n", "\n", " Q19_8 \\\n", "0 Which categories of computer vision methods do... \n", "1 NaN \n", "\n", " Q20_1 \\\n", "0 Which of the following natural language proces... \n", "1 NaN \n", "\n", " Q20_2 \\\n", "0 Which of the following natural language proces... \n", "1 NaN \n", "\n", " Q20_3 \\\n", "0 Which of the following natural language proces... \n", "1 NaN \n", "\n", " Q20_4 \\\n", "0 Which of the following natural language proces... \n", "1 NaN \n", "\n", " Q20_5 \\\n", "0 Which of the following natural language proces... \n", "1 NaN \n", "\n", " Q20_6 \\\n", "0 Which of the following natural language proces... \n", "1 NaN \n", "\n", " Q21_1 \\\n", "0 Do you download pre-trained model weights from... \n", "1 NaN \n", "\n", " Q21_2 \\\n", "0 Do you download pre-trained model weights from... \n", "1 NaN \n", "\n", " Q21_3 \\\n", "0 Do you download pre-trained model weights from... \n", "1 NaN \n", "\n", " Q21_4 \\\n", "0 Do you download pre-trained model weights from... \n", "1 NaN \n", "\n", " Q21_5 \\\n", "0 Do you download pre-trained model weights from... \n", "1 NaN \n", "\n", " Q21_6 \\\n", "0 Do you download pre-trained model weights from... \n", "1 NaN \n", "\n", " Q21_7 \\\n", "0 Do you download pre-trained model weights from... \n", "1 NaN \n", "\n", " Q21_8 \\\n", "0 Do you download pre-trained model weights from... \n", "1 NaN \n", "\n", " Q21_9 \\\n", "0 Do you download pre-trained model weights from... \n", "1 NaN \n", "\n", " Q21_10 \\\n", "0 Do you download pre-trained model weights from... \n", "1 NaN \n", "\n", " Q22 \\\n", "0 Which of the following ML model hubs/repositor... \n", "1 NaN \n", "\n", " Q23 \\\n", "0 Select the title most similar to your current ... \n", "1 NaN \n", "\n", " Q24 \\\n", "0 In what industry is your current employer/cont... \n", "1 NaN \n", "\n", " Q25 \\\n", "0 What is the size of the company where you are ... \n", "1 NaN \n", "\n", " Q26 \\\n", "0 Approximately how many individuals are respons... \n", "1 NaN \n", "\n", " Q27 \\\n", "0 Does your current employer incorporate machine... \n", "1 NaN \n", "\n", " Q28_1 \\\n", "0 Select any activities that make up an importan... \n", "1 NaN \n", "\n", " Q28_2 \\\n", "0 Select any activities that make up an importan... \n", "1 NaN \n", "\n", " Q28_3 \\\n", "0 Select any activities that make up an importan... \n", "1 NaN \n", "\n", " Q28_4 \\\n", "0 Select any activities that make up an importan... \n", "1 NaN \n", "\n", " Q28_5 \\\n", "0 Select any activities that make up an importan... \n", "1 NaN \n", "\n", " Q28_6 \\\n", "0 Select any activities that make up an importan... \n", "1 NaN \n", "\n", " Q28_7 \\\n", "0 Select any activities that make up an importan... \n", "1 NaN \n", "\n", " Q28_8 \\\n", "0 Select any activities that make up an importan... \n", "1 NaN \n", "\n", " Q29 \\\n", "0 What is your current yearly compensation (appr... \n", "1 NaN \n", "\n", " Q30 \\\n", "0 Approximately how much money have you spent on... \n", "1 NaN \n", "\n", " Q31_1 \\\n", "0 Which of the following cloud computing platfor... \n", "1 NaN \n", "\n", " Q31_2 \\\n", "0 Which of the following cloud computing platfor... \n", "1 NaN \n", "\n", " Q31_3 \\\n", "0 Which of the following cloud computing platfor... \n", "1 NaN \n", "\n", " Q31_4 \\\n", "0 Which of the following cloud computing platfor... \n", "1 NaN \n", "\n", " Q31_5 \\\n", "0 Which of the following cloud computing platfor... \n", "1 NaN \n", "\n", " Q31_6 \\\n", "0 Which of the following cloud computing platfor... \n", "1 NaN \n", "\n", " Q31_7 \\\n", "0 Which of the following cloud computing platfor... \n", "1 NaN \n", "\n", " Q31_8 \\\n", "0 Which of the following cloud computing platfor... \n", "1 NaN \n", "\n", " Q31_9 \\\n", "0 Which of the following cloud computing platfor... \n", "1 NaN \n", "\n", " Q31_10 \\\n", "0 Which of the following cloud computing platfor... \n", "1 NaN \n", "\n", " Q31_11 \\\n", "0 Which of the following cloud computing platfor... \n", "1 NaN \n", "\n", " Q31_12 \\\n", "0 Which of the following cloud computing platfor... \n", "1 NaN \n", "\n", " Q32 \\\n", "0 Of the cloud platforms that you are familiar w... \n", "1 NaN \n", "\n", " Q33_1 \\\n", "0 Do you use any of the following cloud computin... \n", "1 NaN \n", "\n", " Q33_2 \\\n", "0 Do you use any of the following cloud computin... \n", "1 NaN \n", "\n", " Q33_3 \\\n", "0 Do you use any of the following cloud computin... \n", "1 NaN \n", "\n", " Q33_4 \\\n", "0 Do you use any of the following cloud computin... \n", "1 NaN \n", "\n", " Q33_5 \\\n", "0 Do you use any of the following cloud computin... \n", "1 NaN \n", "\n", " Q34_1 \\\n", "0 Do you use any of the following data storage p... \n", "1 NaN \n", "\n", " Q34_2 \\\n", "0 Do you use any of the following data storage p... \n", "1 NaN \n", "\n", " Q34_3 \\\n", "0 Do you use any of the following data storage p... \n", "1 NaN \n", "\n", " Q34_4 \\\n", "0 Do you use any of the following data storage p... \n", "1 NaN \n", "\n", " Q34_5 \\\n", "0 Do you use any of the following data storage p... \n", "1 NaN \n", "\n", " Q34_6 \\\n", "0 Do you use any of the following data storage p... \n", "1 NaN \n", "\n", " Q34_7 \\\n", "0 Do you use any of the following data storage p... \n", "1 NaN \n", "\n", " Q34_8 \\\n", "0 Do you use any of the following data storage p... \n", "1 NaN \n", "\n", " Q35_1 \\\n", "0 Do you use any of the following data products ... \n", "1 NaN \n", "\n", " Q35_2 \\\n", "0 Do you use any of the following data products ... \n", "1 NaN \n", "\n", " Q35_3 \\\n", "0 Do you use any of the following data products ... \n", "1 NaN \n", "\n", " Q35_4 \\\n", "0 Do you use any of the following data products ... \n", "1 NaN \n", "\n", " Q35_5 \\\n", "0 Do you use any of the following data products ... \n", "1 NaN \n", "\n", " Q35_6 \\\n", "0 Do you use any of the following data products ... \n", "1 NaN \n", "\n", " Q35_7 \\\n", "0 Do you use any of the following data products ... \n", "1 NaN \n", "\n", " Q35_8 \\\n", "0 Do you use any of the following data products ... \n", "1 NaN \n", "\n", " Q35_9 \\\n", "0 Do you use any of the following data products ... \n", "1 NaN \n", "\n", " Q35_10 \\\n", "0 Do you use any of the following data products ... \n", "1 NaN \n", "\n", " Q35_11 \\\n", "0 Do you use any of the following data products ... \n", "1 NaN \n", "\n", " Q35_12 \\\n", "0 Do you use any of the following data products ... \n", "1 NaN \n", "\n", " Q35_13 \\\n", "0 Do you use any of the following data products ... \n", "1 NaN \n", "\n", " Q35_14 \\\n", "0 Do you use any of the following data products ... \n", "1 NaN \n", "\n", " Q35_15 \\\n", "0 Do you use any of the following data products ... \n", "1 NaN \n", "\n", " Q35_16 \\\n", "0 Do you use any of the following data products ... \n", "1 NaN \n", "\n", " Q36_1 \\\n", "0 Do you use any of the following business intel... \n", "1 NaN \n", "\n", " Q36_2 \\\n", "0 Do you use any of the following business intel... \n", "1 NaN \n", "\n", " Q36_3 \\\n", "0 Do you use any of the following business intel... \n", "1 NaN \n", "\n", " Q36_4 \\\n", "0 Do you use any of the following business intel... \n", "1 NaN \n", "\n", " Q36_5 \\\n", "0 Do you use any of the following business intel... \n", "1 NaN \n", "\n", " Q36_6 \\\n", "0 Do you use any of the following business intel... \n", "1 NaN \n", "\n", " Q36_7 \\\n", "0 Do you use any of the following business intel... \n", "1 NaN \n", "\n", " Q36_8 \\\n", "0 Do you use any of the following business intel... \n", "1 NaN \n", "\n", " Q36_9 \\\n", "0 Do you use any of the following business intel... \n", "1 NaN \n", "\n", " Q36_10 \\\n", "0 Do you use any of the following business intel... \n", "1 NaN \n", "\n", " Q36_11 \\\n", "0 Do you use any of the following business intel... \n", "1 NaN \n", "\n", " Q36_12 \\\n", "0 Do you use any of the following business intel... \n", "1 NaN \n", "\n", " Q36_13 \\\n", "0 Do you use any of the following business intel... \n", "1 NaN \n", "\n", " Q36_14 \\\n", "0 Do you use any of the following business intel... \n", "1 NaN \n", "\n", " Q36_15 \\\n", "0 Do you use any of the following business intel... \n", "1 NaN \n", "\n", " Q37_1 \\\n", "0 Do you use any of the following managed machin... \n", "1 NaN \n", "\n", " Q37_2 \\\n", "0 Do you use any of the following managed machin... \n", "1 NaN \n", "\n", " Q37_3 \\\n", "0 Do you use any of the following managed machin... \n", "1 NaN \n", "\n", " Q37_4 \\\n", "0 Do you use any of the following managed machin... \n", "1 NaN \n", "\n", " Q37_5 \\\n", "0 Do you use any of the following managed machin... \n", "1 NaN \n", "\n", " Q37_6 \\\n", "0 Do you use any of the following managed machin... \n", "1 NaN \n", "\n", " Q37_7 \\\n", "0 Do you use any of the following managed machin... \n", "1 NaN \n", "\n", " Q37_8 \\\n", "0 Do you use any of the following managed machin... \n", "1 NaN \n", "\n", " Q37_9 \\\n", "0 Do you use any of the following managed machin... \n", "1 NaN \n", "\n", " Q37_10 \\\n", "0 Do you use any of the following managed machin... \n", "1 NaN \n", "\n", " Q37_11 \\\n", "0 Do you use any of the following managed machin... \n", "1 NaN \n", "\n", " Q37_12 \\\n", "0 Do you use any of the following managed machin... \n", "1 NaN \n", "\n", " Q37_13 \\\n", "0 Do you use any of the following managed machin... \n", "1 NaN \n", "\n", " Q38_1 \\\n", "0 Do you use any of the following automated mach... \n", "1 NaN \n", "\n", " Q38_2 \\\n", "0 Do you use any of the following automated mach... \n", "1 NaN \n", "\n", " Q38_3 \\\n", "0 Do you use any of the following automated mach... \n", "1 NaN \n", "\n", " Q38_4 \\\n", "0 Do you use any of the following automated mach... \n", "1 NaN \n", "\n", " Q38_5 \\\n", "0 Do you use any of the following automated mach... \n", "1 NaN \n", "\n", " Q38_6 \\\n", "0 Do you use any of the following automated mach... \n", "1 NaN \n", "\n", " Q38_7 \\\n", "0 Do you use any of the following automated mach... \n", "1 NaN \n", "\n", " Q38_8 \\\n", "0 Do you use any of the following automated mach... \n", "1 NaN \n", "\n", " Q39_1 \\\n", "0 Do you use any of the following products to se... \n", "1 NaN \n", "\n", " Q39_2 \\\n", "0 Do you use any of the following products to se... \n", "1 NaN \n", "\n", " Q39_3 \\\n", "0 Do you use any of the following products to se... \n", "1 NaN \n", "\n", " Q39_4 \\\n", "0 Do you use any of the following products to se... \n", "1 NaN \n", "\n", " Q39_5 \\\n", "0 Do you use any of the following products to se... \n", "1 NaN \n", "\n", " Q39_6 \\\n", "0 Do you use any of the following products to se... \n", "1 NaN \n", "\n", " Q39_7 \\\n", "0 Do you use any of the following products to se... \n", "1 NaN \n", "\n", " Q39_8 \\\n", "0 Do you use any of the following products to se... \n", "1 NaN \n", "\n", " Q39_9 \\\n", "0 Do you use any of the following products to se... \n", "1 NaN \n", "\n", " Q39_10 \\\n", "0 Do you use any of the following products to se... \n", "1 NaN \n", "\n", " Q39_11 \\\n", "0 Do you use any of the following products to se... \n", "1 NaN \n", "\n", " Q39_12 \\\n", "0 Do you use any of the following products to se... \n", "1 NaN \n", "\n", " Q40_1 \\\n", "0 Do you use any tools to help monitor your mach... \n", "1 NaN \n", "\n", " Q40_2 \\\n", "0 Do you use any tools to help monitor your mach... \n", "1 NaN \n", "\n", " Q40_3 \\\n", "0 Do you use any tools to help monitor your mach... \n", "1 NaN \n", "\n", " Q40_4 \\\n", "0 Do you use any tools to help monitor your mach... \n", "1 NaN \n", "\n", " Q40_5 \\\n", "0 Do you use any tools to help monitor your mach... \n", "1 NaN \n", "\n", " Q40_6 \\\n", "0 Do you use any tools to help monitor your mach... \n", "1 NaN \n", "\n", " Q40_7 \\\n", "0 Do you use any tools to help monitor your mach... \n", "1 NaN \n", "\n", " Q40_8 \\\n", "0 Do you use any tools to help monitor your mach... \n", "1 NaN \n", "\n", " Q40_9 \\\n", "0 Do you use any tools to help monitor your mach... \n", "1 NaN \n", "\n", " Q40_10 \\\n", "0 Do you use any tools to help monitor your mach... \n", "1 NaN \n", "\n", " Q40_11 \\\n", "0 Do you use any tools to help monitor your mach... \n", "1 NaN \n", "\n", " Q40_12 \\\n", "0 Do you use any tools to help monitor your mach... \n", "1 NaN \n", "\n", " Q40_13 \\\n", "0 Do you use any tools to help monitor your mach... \n", "1 NaN \n", "\n", " Q40_14 \\\n", "0 Do you use any tools to help monitor your mach... \n", "1 NaN \n", "\n", " Q40_15 \\\n", "0 Do you use any tools to help monitor your mach... \n", "1 NaN \n", "\n", " Q41_1 \\\n", "0 Do you use any of the following responsible or... \n", "1 NaN \n", "\n", " Q41_2 \\\n", "0 Do you use any of the following responsible or... \n", "1 NaN \n", "\n", " Q41_3 \\\n", "0 Do you use any of the following responsible or... \n", "1 NaN \n", "\n", " Q41_4 \\\n", "0 Do you use any of the following responsible or... \n", "1 NaN \n", "\n", " Q41_5 \\\n", "0 Do you use any of the following responsible or... \n", "1 NaN \n", "\n", " Q41_6 \\\n", "0 Do you use any of the following responsible or... \n", "1 NaN \n", "\n", " Q41_7 \\\n", "0 Do you use any of the following responsible or... \n", "1 NaN \n", "\n", " Q41_8 \\\n", "0 Do you use any of the following responsible or... \n", "1 NaN \n", "\n", " Q41_9 \\\n", "0 Do you use any of the following responsible or... \n", "1 NaN \n", "\n", " Q42_1 \\\n", "0 Do you use any of the following types of speci... \n", "1 NaN \n", "\n", " Q42_2 \\\n", "0 Do you use any of the following types of speci... \n", "1 NaN \n", "\n", " Q42_3 \\\n", "0 Do you use any of the following types of speci... \n", "1 NaN \n", "\n", " Q42_4 \\\n", "0 Do you use any of the following types of speci... \n", "1 NaN \n", "\n", " Q42_5 \\\n", "0 Do you use any of the following types of speci... \n", "1 NaN \n", "\n", " Q42_6 \\\n", "0 Do you use any of the following types of speci... \n", "1 NaN \n", "\n", " Q42_7 \\\n", "0 Do you use any of the following types of speci... \n", "1 NaN \n", "\n", " Q42_8 \\\n", "0 Do you use any of the following types of speci... \n", "1 NaN \n", "\n", " Q42_9 \\\n", "0 Do you use any of the following types of speci... \n", "1 NaN \n", "\n", " Q43 \\\n", "0 Approximately how many times have you used a T... \n", "1 NaN \n", "\n", " Q44_1 \\\n", "0 Who/what are your favorite media sources that ... \n", "1 NaN \n", "\n", " Q44_2 \\\n", "0 Who/what are your favorite media sources that ... \n", "1 NaN \n", "\n", " Q44_3 \\\n", "0 Who/what are your favorite media sources that ... \n", "1 NaN \n", "\n", " Q44_4 \\\n", "0 Who/what are your favorite media sources that ... \n", "1 NaN \n", "\n", " Q44_5 \\\n", "0 Who/what are your favorite media sources that ... \n", "1 NaN \n", "\n", " Q44_6 \\\n", "0 Who/what are your favorite media sources that ... 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"duration": 0.311872, "end_time": "2022-10-27T19:39:26.892484", "exception": false, "start_time": "2022-10-27T19:39:26.580612", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>Duration (in seconds)</th>\n", " <th>Q2 What is your age (# years)?</th>\n", " <th>Q3 What is your gender? - Selected Choice</th>\n", " <th>Q4 In which country do you currently reside?</th>\n", " <th>Q5 Are you currently a student? (high school, university, or graduate)</th>\n", " <th>Q6_1 On which platforms have you begun or completed data science courses? (Select all that apply) - Selected Choice - Coursera</th>\n", " <th>Q6_2 On which platforms have you begun or completed data science courses? (Select all that apply) - Selected Choice - edX</th>\n", " <th>Q6_3 On which platforms have you begun or completed data science courses? (Select all that apply) - Selected Choice - Kaggle Learn Courses</th>\n", " <th>Q6_4 On which platforms have you begun or completed data science courses? (Select all that apply) - Selected Choice - DataCamp</th>\n", " <th>Q6_5 On which platforms have you begun or completed data science courses? (Select all that apply) - Selected Choice - Fast.ai</th>\n", " <th>Q6_6 On which platforms have you begun or completed data science courses? (Select all that apply) - Selected Choice - Udacity</th>\n", " <th>Q6_7 On which platforms have you begun or completed data science courses? (Select all that apply) - Selected Choice - Udemy</th>\n", " <th>Q6_8 On which platforms have you begun or completed data science courses? (Select all that apply) - Selected Choice - LinkedIn Learning</th>\n", " <th>Q6_9 On which platforms have you begun or completed data science courses? (Select all that apply) - Selected Choice - Cloud-certification programs (direct from AWS, Azure, GCP, or similar)</th>\n", " <th>Q6_10 On which platforms have you begun or completed data science courses? (Select all that apply) - Selected Choice - University Courses (resulting in a university degree)</th>\n", " <th>Q6_11 On which platforms have you begun or completed data science courses? (Select all that apply) - Selected Choice - None</th>\n", " <th>Q6_12 On which platforms have you begun or completed data science courses? (Select all that apply) - Selected Choice - Other</th>\n", " <th>Q7_1 What products or platforms did you find to be most helpful when you first started studying data science? (Select all that apply) - Selected Choice - University courses</th>\n", " <th>Q7_2 What products or platforms did you find to be most helpful when you first started studying data science? (Select all that apply) - Selected Choice - Online courses (Coursera, EdX, etc)</th>\n", " <th>Q7_3 What products or platforms did you find to be most helpful when you first started studying data science? (Select all that apply) - Selected Choice - Social media platforms (Reddit, Twitter, etc)</th>\n", " <th>Q7_4 What products or platforms did you find to be most helpful when you first started studying data science? (Select all that apply) - Selected Choice - Video platforms (YouTube, Twitch, etc)</th>\n", " <th>Q7_5 What products or platforms did you find to be most helpful when you first started studying data science? (Select all that apply) - Selected Choice - Kaggle (notebooks, competitions, etc)</th>\n", " <th>Q7_6 What products or platforms did you find to be most helpful when you first started studying data science? (Select all that apply) - Selected Choice - None / I do not study data science</th>\n", " <th>Q7_7 What products or platforms did you find to be most helpful when you first started studying data science? (Select all that apply) - Selected Choice - Other</th>\n", " <th>Q8 What is the highest level of formal education that you have attained or plan to attain within the next 2 years?</th>\n", " <th>Q9 Have you ever published any academic research (papers, preprints, conference proceedings, etc)?</th>\n", " <th>Q10_1 Did your research make use of machine learning? - Yes, the research made advances related to some novel machine learning method (theoretical research)</th>\n", " <th>Q10_2 Did your research make use of machine learning? - Yes, the research made use of machine learning as a tool (applied research)</th>\n", " <th>Q10_3 Did your research make use of machine learning? - No</th>\n", " <th>Q11 For how many years have you been writing code and/or programming?</th>\n", " <th>Q12_1 What programming languages do you use on a regular basis? (Select all that apply) - Selected Choice - Python</th>\n", " <th>Q12_2 What programming languages do you use on a regular basis? (Select all that apply) - Selected Choice - R</th>\n", " <th>Q12_3 What programming languages do you use on a regular basis? (Select all that apply) - Selected Choice - SQL</th>\n", " <th>Q12_4 What programming languages do you use on a regular basis? (Select all that apply) - Selected Choice - C</th>\n", " <th>Q12_5 What programming languages do you use on a regular basis? (Select all that apply) - Selected Choice - C#</th>\n", " <th>Q12_6 What programming languages do you use on a regular basis? (Select all that apply) - Selected Choice - C++</th>\n", " <th>Q12_7 What programming languages do you use on a regular basis? (Select all that apply) - Selected Choice - Java</th>\n", " <th>Q12_8 What programming languages do you use on a regular basis? (Select all that apply) - Selected Choice - Javascript</th>\n", " <th>Q12_9 What programming languages do you use on a regular basis? (Select all that apply) - Selected Choice - Bash</th>\n", " <th>Q12_10 What programming languages do you use on a regular basis? (Select all that apply) - Selected Choice - PHP</th>\n", " <th>Q12_11 What programming languages do you use on a regular basis? (Select all that apply) - Selected Choice - MATLAB</th>\n", " <th>Q12_12 What programming languages do you use on a regular basis? (Select all that apply) - Selected Choice - Julia</th>\n", " <th>Q12_13 What programming languages do you use on a regular basis? (Select all that apply) - Selected Choice - Go</th>\n", " <th>Q12_14 What programming languages do you use on a regular basis? (Select all that apply) - Selected Choice - None</th>\n", " <th>Q12_15 What programming languages do you use on a regular basis? (Select all that apply) - Selected Choice - Other</th>\n", " <th>Q13_1 Which of the following integrated development environments (IDE's) do you use on a regular basis? (Select all that apply) - Selected Choice - JupyterLab</th>\n", " <th>Q13_2 Which of the following integrated development environments (IDE's) do you use on a regular basis? (Select all that apply) - Selected Choice - RStudio</th>\n", " <th>Q13_3 Which of the following integrated development environments (IDE's) do you use on a regular basis? (Select all that apply) - Selected Choice - Visual Studio</th>\n", " <th>Q13_4 Which of the following integrated development environments (IDE's) do you use on a regular basis? (Select all that apply) - Selected Choice - Visual Studio Code (VSCode)</th>\n", " <th>Q13_5 Which of the following integrated development environments (IDE's) do you use on a regular basis? (Select all that apply) - Selected Choice - PyCharm</th>\n", " <th>Q13_6 Which of the following integrated development environments (IDE's) do you use on a regular basis? (Select all that apply) - Selected Choice - Spyder</th>\n", " <th>Q13_7 Which of the following integrated development environments (IDE's) do you use on a regular basis? (Select all that apply) - Selected Choice - Notepad++</th>\n", " <th>Q13_8 Which of the following integrated development environments (IDE's) do you use on a regular basis? (Select all that apply) - Selected Choice - Sublime Text</th>\n", " <th>Q13_9 Which of the following integrated development environments (IDE's) do you use on a regular basis? (Select all that apply) - Selected Choice - Vim / Emacs</th>\n", " <th>Q13_10 Which of the following integrated development environments (IDE's) do you use on a regular basis? (Select all that apply) - Selected Choice - MATLAB</th>\n", " <th>Q13_11 Which of the following integrated development environments (IDE's) do you use on a regular basis? (Select all that apply) - Selected Choice - Jupyter Notebook</th>\n", " <th>Q13_12 Which of the following integrated development environments (IDE's) do you use on a regular basis? (Select all that apply) - Selected Choice - IntelliJ</th>\n", " <th>Q13_13 Which of the following integrated development environments (IDE's) do you use on a regular basis? (Select all that apply) - Selected Choice - None</th>\n", " <th>Q13_14 Which of the following integrated development environments (IDE's) do you use on a regular basis? (Select all that apply) - Selected Choice - Other</th>\n", " <th>Q14_1 Do you use any of the following hosted notebook products? (Select all that apply) - Selected Choice - Kaggle Notebooks</th>\n", " <th>Q14_2 Do you use any of the following hosted notebook products? (Select all that apply) - Selected Choice - Colab Notebooks</th>\n", " <th>Q14_3 Do you use any of the following hosted notebook products? (Select all that apply) - Selected Choice - Azure Notebooks</th>\n", " <th>Q14_4 Do you use any of the following hosted notebook products? (Select all that apply) - Selected Choice - Code Ocean</th>\n", " <th>Q14_5 Do you use any of the following hosted notebook products? (Select all that apply) - Selected Choice - IBM Watson Studio</th>\n", " <th>Q14_6 Do you use any of the following hosted notebook products? (Select all that apply) - Selected Choice - Amazon Sagemaker Studio</th>\n", " <th>Q14_7 Do you use any of the following hosted notebook products? (Select all that apply) - Selected Choice - Amazon Sagemaker Studio Lab</th>\n", " <th>Q14_8 Do you use any of the following hosted notebook products? (Select all that apply) - Selected Choice - Amazon EMR Notebooks</th>\n", " <th>Q14_9 Do you use any of the following hosted notebook products? (Select all that apply) - Selected Choice - Google Cloud Vertex AI Workbench</th>\n", " <th>Q14_10 Do you use any of the following hosted notebook products? (Select all that apply) - Selected Choice - Hex Workspaces</th>\n", " <th>Q14_11 Do you use any of the following hosted notebook products? (Select all that apply) - Selected Choice - Noteable Notebooks</th>\n", " <th>Q14_12 Do you use any of the following hosted notebook products? (Select all that apply) - Selected Choice - Databricks Collaborative Notebooks</th>\n", " <th>Q14_13 Do you use any of the following hosted notebook products? (Select all that apply) - Selected Choice - Deepnote Notebooks</th>\n", " <th>Q14_14 Do you use any of the following hosted notebook products? (Select all that apply) - Selected Choice - Gradient Notebooks</th>\n", " <th>Q14_15 Do you use any of the following hosted notebook products? (Select all that apply) - Selected Choice - None</th>\n", " <th>Q14_16 Do you use any of the following hosted notebook products? (Select all that apply) - Selected Choice - Other</th>\n", " <th>Q15_1 Do you use any of the following data visualization libraries on a regular basis? (Select all that apply) - Selected Choice - Matplotlib</th>\n", " <th>Q15_2 Do you use any of the following data visualization libraries on a regular basis? (Select all that apply) - Selected Choice - Seaborn</th>\n", " <th>Q15_3 Do you use any of the following data visualization libraries on a regular basis? (Select all that apply) - Selected Choice - Plotly / Plotly Express</th>\n", " <th>Q15_4 Do you use any of the following data visualization libraries on a regular basis? (Select all that apply) - Selected Choice - Ggplot / ggplot2</th>\n", " <th>Q15_5 Do you use any of the following data visualization libraries on a regular basis? (Select all that apply) - Selected Choice - Shiny</th>\n", " <th>Q15_6 Do you use any of the following data visualization libraries on a regular basis? (Select all that apply) - Selected Choice - D3 js</th>\n", " <th>Q15_7 Do you use any of the following data visualization libraries on a regular basis? (Select all that apply) - Selected Choice - Altair</th>\n", " <th>Q15_8 Do you use any of the following data visualization libraries on a regular basis? (Select all that apply) - Selected Choice - Bokeh</th>\n", " <th>Q15_9 Do you use any of the following data visualization libraries on a regular basis? (Select all that apply) - Selected Choice - Geoplotlib</th>\n", " <th>Q15_10 Do you use any of the following data visualization libraries on a regular basis? (Select all that apply) - Selected Choice - Leaflet / Folium</th>\n", " <th>Q15_11 Do you use any of the following data visualization libraries on a regular basis? (Select all that apply) - Selected Choice - Pygal</th>\n", " <th>Q15_12 Do you use any of the following data visualization libraries on a regular basis? (Select all that apply) - Selected Choice - Dygraphs</th>\n", " <th>Q15_13 Do you use any of the following data visualization libraries on a regular basis? (Select all that apply) - Selected Choice - Highcharter</th>\n", " <th>Q15_14 Do you use any of the following data visualization libraries on a regular basis? (Select all that apply) - Selected Choice - None</th>\n", " <th>Q15_15 Do you use any of the following data visualization libraries on a regular basis? (Select all that apply) - Selected Choice - Other</th>\n", " <th>Q16 For how many years have you used machine learning methods?</th>\n", " <th>Q17_1 Which of the following machine learning frameworks do you use on a regular basis? (Select all that apply) - Selected Choice - Scikit-learn</th>\n", " <th>Q17_2 Which of the following machine learning frameworks do you use on a regular basis? (Select all that apply) - Selected Choice - TensorFlow</th>\n", " <th>Q17_3 Which of the following machine learning frameworks do you use on a regular basis? (Select all that apply) - Selected Choice - Keras</th>\n", " <th>Q17_4 Which of the following machine learning frameworks do you use on a regular basis? (Select all that apply) - Selected Choice - PyTorch</th>\n", " <th>Q17_5 Which of the following machine learning frameworks do you use on a regular basis? (Select all that apply) - Selected Choice - Fast.ai</th>\n", " <th>Q17_6 Which of the following machine learning frameworks do you use on a regular basis? (Select all that apply) - Selected Choice - Xgboost</th>\n", " <th>Q17_7 Which of the following machine learning frameworks do you use on a regular basis? (Select all that apply) - Selected Choice - LightGBM</th>\n", " <th>Q17_8 Which of the following machine learning frameworks do you use on a regular basis? (Select all that apply) - Selected Choice - CatBoost</th>\n", " <th>Q17_9 Which of the following machine learning frameworks do you use on a regular basis? (Select all that apply) - Selected Choice - Caret</th>\n", " <th>Q17_10 Which of the following machine learning frameworks do you use on a regular basis? (Select all that apply) - Selected Choice - Tidymodels</th>\n", " <th>Q17_11 Which of the following machine learning frameworks do you use on a regular basis? (Select all that apply) - Selected Choice - JAX</th>\n", " <th>Q17_12 Which of the following machine learning frameworks do you use on a regular basis? (Select all that apply) - Selected Choice - PyTorch Lightning</th>\n", " <th>Q17_13 Which of the following machine learning frameworks do you use on a regular basis? (Select all that apply) - Selected Choice - Huggingface</th>\n", " <th>Q17_14 Which of the following machine learning frameworks do you use on a regular basis? (Select all that apply) - Selected Choice - None</th>\n", " <th>Q17_15 Which of the following machine learning frameworks do you use on a regular basis? (Select all that apply) - Selected Choice - Other</th>\n", " <th>Q18_1 Which of the following ML algorithms do you use on a regular basis? (Select all that apply): - Selected Choice - Linear or Logistic Regression</th>\n", " <th>Q18_2 Which of the following ML algorithms do you use on a regular basis? (Select all that apply): - Selected Choice - Decision Trees or Random Forests</th>\n", " <th>Q18_3 Which of the following ML algorithms do you use on a regular basis? (Select all that apply): - Selected Choice - Gradient Boosting Machines (xgboost, lightgbm, etc)</th>\n", " <th>Q18_4 Which of the following ML algorithms do you use on a regular basis? (Select all that apply): - Selected Choice - Bayesian Approaches</th>\n", " <th>Q18_5 Which of the following ML algorithms do you use on a regular basis? (Select all that apply): - Selected Choice - Evolutionary Approaches</th>\n", " <th>Q18_6 Which of the following ML algorithms do you use on a regular basis? (Select all that apply): - Selected Choice - Dense Neural Networks (MLPs, etc)</th>\n", " <th>Q18_7 Which of the following ML algorithms do you use on a regular basis? (Select all that apply): - Selected Choice - Convolutional Neural Networks</th>\n", " <th>Q18_8 Which of the following ML algorithms do you use on a regular basis? (Select all that apply): - Selected Choice - Generative Adversarial Networks</th>\n", " <th>Q18_9 Which of the following ML algorithms do you use on a regular basis? (Select all that apply): - Selected Choice - Recurrent Neural Networks</th>\n", " <th>Q18_10 Which of the following ML algorithms do you use on a regular basis? (Select all that apply): - Selected Choice - Transformer Networks (BERT, gpt-3, etc)</th>\n", " <th>Q18_11 Which of the following ML algorithms do you use on a regular basis? (Select all that apply): - Selected Choice - Autoencoder Networks (DAE, VAE, etc)</th>\n", " <th>Q18_12 Which of the following ML algorithms do you use on a regular basis? (Select all that apply): - Selected Choice - Graph Neural Networks</th>\n", " <th>Q18_13 Which of the following ML algorithms do you use on a regular basis? (Select all that apply): - Selected Choice - None</th>\n", " <th>Q18_14 Which of the following ML algorithms do you use on a regular basis? (Select all that apply): - Selected Choice - Other</th>\n", " <th>Q19_1 Which categories of computer vision methods do you use on a regular basis? (Select all that apply) - Selected Choice - General purpose image/video tools (PIL, cv2, skimage, etc)</th>\n", " <th>Q19_2 Which categories of computer vision methods do you use on a regular basis? (Select all that apply) - Selected Choice - Image segmentation methods (U-Net, Mask R-CNN, etc)</th>\n", " <th>Q19_3 Which categories of computer vision methods do you use on a regular basis? (Select all that apply) - Selected Choice - Object detection methods (YOLOv6, RetinaNet, etc)</th>\n", " <th>Q19_4 Which categories of computer vision methods do you use on a regular basis? (Select all that apply) - Selected Choice - Image classification and other general purpose networks (VGG, Inception, ResNet, ResNeXt, NASNet, EfficientNet, etc)</th>\n", " <th>Q19_5 Which categories of computer vision methods do you use on a regular basis? (Select all that apply) - Selected Choice - Generative Networks (GAN, VAE, etc)</th>\n", " <th>Q19_6 Which categories of computer vision methods do you use on a regular basis? (Select all that apply) - Selected Choice - Vision transformer networks (ViT, DeiT, BiT, BEiT, Swin, etc)</th>\n", " <th>Q19_7 Which categories of computer vision methods do you use on a regular basis? (Select all that apply) - Selected Choice - None</th>\n", " <th>Q19_8 Which categories of computer vision methods do you use on a regular basis? (Select all that apply) - Selected Choice - Other</th>\n", " <th>Q20_1 Which of the following natural language processing (NLP) methods do you use on a regular basis? (Select all that apply) - Selected Choice - Word embeddings/vectors (GLoVe, fastText, word2vec)</th>\n", " <th>Q20_2 Which of the following natural language processing (NLP) methods do you use on a regular basis? (Select all that apply) - Selected Choice - Encoder-decoder models (seq2seq, vanilla transformers)</th>\n", " <th>Q20_3 Which of the following natural language processing (NLP) methods do you use on a regular basis? (Select all that apply) - Selected Choice - Contextualized embeddings (ELMo, CoVe)</th>\n", " <th>Q20_4 Which of the following natural language processing (NLP) methods do you use on a regular basis? (Select all that apply) - Selected Choice - Transformer language models (GPT-3, BERT, XLnet, etc)</th>\n", " <th>Q20_5 Which of the following natural language processing (NLP) methods do you use on a regular basis? (Select all that apply) - Selected Choice - None</th>\n", " <th>Q20_6 Which of the following natural language processing (NLP) methods do you use on a regular basis? (Select all that apply) - Selected Choice - Other</th>\n", " <th>Q21_1 Do you download pre-trained model weights from any of the following services? (Select all that apply) - Selected Choice - TensorFlow Hub</th>\n", " <th>Q21_2 Do you download pre-trained model weights from any of the following services? (Select all that apply) - Selected Choice - PyTorch Hub</th>\n", " <th>Q21_3 Do you download pre-trained model weights from any of the following services? (Select all that apply) - Selected Choice - Huggingface Models</th>\n", " <th>Q21_4 Do you download pre-trained model weights from any of the following services? (Select all that apply) - Selected Choice - Timm</th>\n", " <th>Q21_5 Do you download pre-trained model weights from any of the following services? (Select all that apply) - Selected Choice - Jumpstart</th>\n", " <th>Q21_6 Do you download pre-trained model weights from any of the following services? (Select all that apply) - Selected Choice - ONNX models</th>\n", " <th>Q21_7 Do you download pre-trained model weights from any of the following services? (Select all that apply) - Selected Choice - NVIDIA NGC models</th>\n", " <th>Q21_8 Do you download pre-trained model weights from any of the following services? (Select all that apply) - Selected Choice - Kaggle datasets</th>\n", " <th>Q21_9 Do you download pre-trained model weights from any of the following services? (Select all that apply) - Selected Choice - No, I do not download pre-trained model weights on a regular basis</th>\n", " <th>Q21_10 Do you download pre-trained model weights from any of the following services? (Select all that apply) - Selected Choice - Other storage services (i.e. google drive)</th>\n", " <th>Q22 Which of the following ML model hubs/repositories do you use most often? - Selected Choice</th>\n", " <th>Q23 Select the title most similar to your current role (or most recent title if retired): - Selected Choice</th>\n", " <th>Q24 In what industry is your current employer/contract (or your most recent employer if retired)? - Selected Choice</th>\n", " <th>Q25 What is the size of the company where you are employed?</th>\n", " <th>Q26 Approximately how many individuals are responsible for data science workloads at your place of business?</th>\n", " <th>Q27 Does your current employer incorporate machine learning methods into their business?</th>\n", " <th>Q28_1 Select any activities that make up an important part of your role at work: (Select all that apply) - Analyze and understand data to influence product or business decisions</th>\n", " <th>Q28_2 Select any activities that make up an important part of your role at work: (Select all that apply) - Build and/or run the data infrastructure that my business uses for storing, analyzing, and operationalizing data</th>\n", " <th>Q28_3 Select any activities that make up an important part of your role at work: (Select all that apply) - Build prototypes to explore applying machine learning to new areas</th>\n", " <th>Q28_4 Select any activities that make up an important part of your role at work: (Select all that apply) - Build and/or run a machine learning service that operationally improves my product or workflows</th>\n", " <th>Q28_5 Select any activities that make up an important part of your role at work: (Select all that apply) - Experimentation and iteration to improve existing ML models</th>\n", " <th>Q28_6 Select any activities that make up an important part of your role at work: (Select all that apply) - Do research that advances the state of the art of machine learning</th>\n", " <th>Q28_7 Select any activities that make up an important part of your role at work: (Select all that apply) - None of these activities are an important part of my role at work</th>\n", " <th>Q28_8 Select any activities that make up an important part of your role at work: (Select all that apply) - Other</th>\n", " <th>Q29 What is your current yearly compensation (approximate $USD)?</th>\n", " <th>Q30 Approximately how much money have you spent on machine learning and/or cloud computing services at home or at work in the past 5 years (approximate $USD)?\\n (approximate $USD)?</th>\n", " <th>Q31_1 Which of the following cloud computing platforms do you use? (Select all that apply) - Selected Choice - Amazon Web Services (AWS)</th>\n", " <th>Q31_2 Which of the following cloud computing platforms do you use? (Select all that apply) - Selected Choice - Microsoft Azure</th>\n", " <th>Q31_3 Which of the following cloud computing platforms do you use? (Select all that apply) - Selected Choice - Google Cloud Platform (GCP)</th>\n", " <th>Q31_4 Which of the following cloud computing platforms do you use? (Select all that apply) - Selected Choice - IBM Cloud / Red Hat</th>\n", " <th>Q31_5 Which of the following cloud computing platforms do you use? (Select all that apply) - Selected Choice - Oracle Cloud</th>\n", " <th>Q31_6 Which of the following cloud computing platforms do you use? (Select all that apply) - Selected Choice - SAP Cloud</th>\n", " <th>Q31_7 Which of the following cloud computing platforms do you use? (Select all that apply) - Selected Choice - VMware Cloud</th>\n", " <th>Q31_8 Which of the following cloud computing platforms do you use? (Select all that apply) - Selected Choice - Alibaba Cloud</th>\n", " <th>Q31_9 Which of the following cloud computing platforms do you use? (Select all that apply) - Selected Choice - Tencent Cloud</th>\n", " <th>Q31_10 Which of the following cloud computing platforms do you use? (Select all that apply) - Selected Choice - Huawei Cloud</th>\n", " <th>Q31_11 Which of the following cloud computing platforms do you use? (Select all that apply) - Selected Choice - None</th>\n", " <th>Q31_12 Which of the following cloud computing platforms do you use? (Select all that apply) - Selected Choice - Other</th>\n", " <th>Q32 Of the cloud platforms that you are familiar with, which has the best developer experience (most enjoyable to use)? - Selected Choice</th>\n", " <th>Q33_1 Do you use any of the following cloud computing products? (Select all that apply) - Selected Choice - Amazon Elastic Compute Cloud (EC2)</th>\n", " <th>Q33_2 Do you use any of the following cloud computing products? (Select all that apply) - Selected Choice - Microsoft Azure Virtual Machines</th>\n", " <th>Q33_3 Do you use any of the following cloud computing products? (Select all that apply) - Selected Choice - Google Cloud Compute Engine</th>\n", " <th>Q33_4 Do you use any of the following cloud computing products? (Select all that apply) - Selected Choice - No / None</th>\n", " <th>Q33_5 Do you use any of the following cloud computing products? (Select all that apply) - Selected Choice - Other</th>\n", " <th>Q34_1 Do you use any of the following data storage products? (Select all that apply) - Selected Choice - Microsoft Azure Blob Storage</th>\n", " <th>Q34_2 Do you use any of the following data storage products? (Select all that apply) - Selected Choice - Microsoft Azure Files</th>\n", " <th>Q34_3 Do you use any of the following data storage products? (Select all that apply) - Selected Choice - Amazon Simple Storage Service (S3)</th>\n", " <th>Q34_4 Do you use any of the following data storage products? (Select all that apply) - Selected Choice - Amazon Elastic File System (EFS)</th>\n", " <th>Q34_5 Do you use any of the following data storage products? (Select all that apply) - Selected Choice - Google Cloud Storage (GCS)</th>\n", " <th>Q34_6 Do you use any of the following data storage products? (Select all that apply) - Selected Choice - Google Cloud Filestore</th>\n", " <th>Q34_7 Do you use any of the following data storage products? (Select all that apply) - Selected Choice - No / None</th>\n", " <th>Q34_8 Do you use any of the following data storage products? (Select all that apply) - Selected Choice - Other</th>\n", " <th>Q35_1 Do you use any of the following data products (relational databases, data warehouses, data lakes, or similar)? (Select all that apply) - Selected Choice - MySQL</th>\n", " <th>Q35_2 Do you use any of the following data products (relational databases, data warehouses, data lakes, or similar)? (Select all that apply) - Selected Choice - PostgreSQL</th>\n", " <th>Q35_3 Do you use any of the following data products (relational databases, data warehouses, data lakes, or similar)? (Select all that apply) - Selected Choice - SQLite</th>\n", " <th>Q35_4 Do you use any of the following data products (relational databases, data warehouses, data lakes, or similar)? (Select all that apply) - Selected Choice - Oracle Database</th>\n", " <th>Q35_5 Do you use any of the following data products (relational databases, data warehouses, data lakes, or similar)? (Select all that apply) - Selected Choice - MongoDB</th>\n", " <th>Q35_6 Do you use any of the following data products (relational databases, data warehouses, data lakes, or similar)? (Select all that apply) - Selected Choice - Snowflake</th>\n", " <th>Q35_7 Do you use any of the following data products (relational databases, data warehouses, data lakes, or similar)? (Select all that apply) - Selected Choice - IBM Db2</th>\n", " <th>Q35_8 Do you use any of the following data products (relational databases, data warehouses, data lakes, or similar)? (Select all that apply) - Selected Choice - Microsoft SQL Server</th>\n", " <th>Q35_9 Do you use any of the following data products (relational databases, data warehouses, data lakes, or similar)? (Select all that apply) - Selected Choice - Microsoft Azure SQL Database</th>\n", " <th>Q35_10 Do you use any of the following data products (relational databases, data warehouses, data lakes, or similar)? (Select all that apply) - Selected Choice - Amazon Redshift</th>\n", " <th>Q35_11 Do you use any of the following data products (relational databases, data warehouses, data lakes, or similar)? (Select all that apply) - Selected Choice - Amazon RDS</th>\n", " <th>Q35_12 Do you use any of the following data products (relational databases, data warehouses, data lakes, or similar)? (Select all that apply) - Selected Choice - Amazon DynamoDB</th>\n", " <th>Q35_13 Do you use any of the following data products (relational databases, data warehouses, data lakes, or similar)? (Select all that apply) - Selected Choice - Google Cloud BigQuery</th>\n", " <th>Q35_14 Do you use any of the following data products (relational databases, data warehouses, data lakes, or similar)? (Select all that apply) - Selected Choice - Google Cloud SQL</th>\n", " <th>Q35_15 Do you use any of the following data products (relational databases, data warehouses, data lakes, or similar)? (Select all that apply) - Selected Choice - None</th>\n", " <th>Q35_16 Do you use any of the following data products (relational databases, data warehouses, data lakes, or similar)? (Select all that apply) - Selected Choice - Other</th>\n", " <th>Q36_1 Do you use any of the following business intelligence tools? (Select all that apply) - Selected Choice - Amazon QuickSight</th>\n", " <th>Q36_2 Do you use any of the following business intelligence tools? (Select all that apply) - Selected Choice - Microsoft Power BI</th>\n", " <th>Q36_3 Do you use any of the following business intelligence tools? (Select all that apply) - Selected Choice - Google Data Studio</th>\n", " <th>Q36_4 Do you use any of the following business intelligence tools? (Select all that apply) - Selected Choice - Looker</th>\n", " <th>Q36_5 Do you use any of the following business intelligence tools? (Select all that apply) - Selected Choice - Tableau</th>\n", " <th>Q36_6 Do you use any of the following business intelligence tools? (Select all that apply) - Selected Choice - Qlik Sense</th>\n", " <th>Q36_7 Do you use any of the following business intelligence tools? (Select all that apply) - Selected Choice - Domo</th>\n", " <th>Q36_8 Do you use any of the following business intelligence tools? (Select all that apply) - Selected Choice - TIBCO Spotfire</th>\n", " <th>Q36_9 Do you use any of the following business intelligence tools? (Select all that apply) - Selected Choice - Alteryx</th>\n", " <th>Q36_10 Do you use any of the following business intelligence tools? (Select all that apply) - Selected Choice - Sisense</th>\n", " <th>Q36_11 Do you use any of the following business intelligence tools? (Select all that apply) - Selected Choice - SAP Analytics Cloud</th>\n", " <th>Q36_12 Do you use any of the following business intelligence tools? (Select all that apply) - Selected Choice - Microsoft Azure Synapse</th>\n", " <th>Q36_13 Do you use any of the following business intelligence tools? (Select all that apply) - Selected Choice - Thoughtspot</th>\n", " <th>Q36_14 Do you use any of the following business intelligence tools? (Select all that apply) - Selected Choice - None</th>\n", " <th>Q36_15 Do you use any of the following business intelligence tools? (Select all that apply) - Selected Choice - Other</th>\n", " <th>Q37_1 Do you use any of the following managed machine learning products on a regular basis? (Select all that apply) - Selected Choice - Amazon SageMaker</th>\n", " <th>Q37_2 Do you use any of the following managed machine learning products on a regular basis? (Select all that apply) - Selected Choice - Azure Machine Learning Studio</th>\n", " <th>Q37_3 Do you use any of the following managed machine learning products on a regular basis? (Select all that apply) - Selected Choice - Google Cloud Vertex AI</th>\n", " <th>Q37_4 Do you use any of the following managed machine learning products on a regular basis? (Select all that apply) - Selected Choice - DataRobot</th>\n", " <th>Q37_5 Do you use any of the following managed machine learning products on a regular basis? (Select all that apply) - Selected Choice - Databricks</th>\n", " <th>Q37_6 Do you use any of the following managed machine learning products on a regular basis? (Select all that apply) - Selected Choice - Dataiku</th>\n", " <th>Q37_7 Do you use any of the following managed machine learning products on a regular basis? (Select all that apply) - Selected Choice - Alteryx</th>\n", " <th>Q37_8 Do you use any of the following managed machine learning products on a regular basis? (Select all that apply) - Selected Choice - Rapidminer</th>\n", " <th>Q37_9 Do you use any of the following managed machine learning products on a regular basis? (Select all that apply) - Selected Choice - C3.ai</th>\n", " <th>Q37_10 Do you use any of the following managed machine learning products on a regular basis? (Select all that apply) - Selected Choice - Domino Data Lab</th>\n", " <th>Q37_11 Do you use any of the following managed machine learning products on a regular basis? (Select all that apply) - Selected Choice - H2O AI Cloud</th>\n", " <th>Q37_12 Do you use any of the following managed machine learning products on a regular basis? (Select all that apply) - Selected Choice - No / None</th>\n", " <th>Q37_13 Do you use any of the following managed machine learning products on a regular basis? (Select all that apply) - Selected Choice - Other</th>\n", " <th>Q38_1 Do you use any of the following automated machine learning tools? (Select all that apply) - Selected Choice - Google Cloud AutoML</th>\n", " <th>Q38_2 Do you use any of the following automated machine learning tools? (Select all that apply) - Selected Choice - H2O Driverless AI</th>\n", " <th>Q38_3 Do you use any of the following automated machine learning tools? (Select all that apply) - Selected Choice - Databricks AutoML</th>\n", " <th>Q38_4 Do you use any of the following automated machine learning tools? (Select all that apply) - Selected Choice - DataRobot AutoML</th>\n", " <th>Q38_5 Do you use any of the following automated machine learning tools? (Select all that apply) - Selected Choice - Amazon Sagemaker Autopilot</th>\n", " <th>Q38_6 Do you use any of the following automated machine learning tools? (Select all that apply) - Selected Choice - Azure Automated Machine Learning</th>\n", " <th>Q38_7 Do you use any of the following automated machine learning tools? (Select all that apply) - Selected Choice - No / None</th>\n", " <th>Q38_8 Do you use any of the following automated machine learning tools? (Select all that apply) - Selected Choice - Other</th>\n", " <th>Q39_1 Do you use any of the following products to serve your machine learning models? (Select all that apply) - Selected Choice - TensorFlow Extended (TFX)</th>\n", " <th>Q39_2 Do you use any of the following products to serve your machine learning models? (Select all that apply) - Selected Choice - TorchServe</th>\n", " <th>Q39_3 Do you use any of the following products to serve your machine learning models? (Select all that apply) - Selected Choice - ONNX Runtime</th>\n", " <th>Q39_4 Do you use any of the following products to serve your machine learning models? (Select all that apply) - Selected Choice - Triton Inference Server</th>\n", " <th>Q39_5 Do you use any of the following products to serve your machine learning models? (Select all that apply) - Selected Choice - OpenVINO Model Server</th>\n", " <th>Q39_6 Do you use any of the following products to serve your machine learning models? (Select all that apply) - Selected Choice - KServe</th>\n", " <th>Q39_7 Do you use any of the following products to serve your machine learning models? (Select all that apply) - Selected Choice - BentoML</th>\n", " <th>Q39_8 Do you use any of the following products to serve your machine learning models? (Select all that apply) - Selected Choice - Multi Model Server (MMS)</th>\n", " <th>Q39_9 Do you use any of the following products to serve your machine learning models? (Select all that apply) - Selected Choice - Seldon Core</th>\n", " <th>Q39_10 Do you use any of the following products to serve your machine learning models? (Select all that apply) - Selected Choice - MLflow</th>\n", " <th>Q39_11 Do you use any of the following products to serve your machine learning models? (Select all that apply) - Selected Choice - None</th>\n", " <th>Q39_12 Do you use any of the following products to serve your machine learning models? (Select all that apply) - Selected Choice - Other</th>\n", " <th>Q40_1 Do you use any tools to help monitor your machine learning models and/or experiments? (Select all that apply) - Selected Choice - Neptune.ai</th>\n", " <th>Q40_2 Do you use any tools to help monitor your machine learning models and/or experiments? (Select all that apply) - Selected Choice - Weights & Biases</th>\n", " <th>Q40_3 Do you use any tools to help monitor your machine learning models and/or experiments? (Select all that apply) - Selected Choice - Comet.ml</th>\n", " <th>Q40_4 Do you use any tools to help monitor your machine learning models and/or experiments? (Select all that apply) - Selected Choice - TensorBoard</th>\n", " <th>Q40_5 Do you use any tools to help monitor your machine learning models and/or experiments? (Select all that apply) - Selected Choice - Guild.ai</th>\n", " <th>Q40_6 Do you use any tools to help monitor your machine learning models and/or experiments? (Select all that apply) - Selected Choice - ClearML</th>\n", " <th>Q40_7 Do you use any tools to help monitor your machine learning models and/or experiments? (Select all that apply) - Selected Choice - MLflow</th>\n", " <th>Q40_8 Do you use any tools to help monitor your machine learning models and/or experiments? (Select all that apply) - Selected Choice - Aporia</th>\n", " <th>Q40_9 Do you use any tools to help monitor your machine learning models and/or experiments? (Select all that apply) - Selected Choice - Evidently AI</th>\n", " <th>Q40_10 Do you use any tools to help monitor your machine learning models and/or experiments? (Select all that apply) - Selected Choice - Arize</th>\n", " <th>Q40_11 Do you use any tools to help monitor your machine learning models and/or experiments? (Select all that apply) - Selected Choice - WhyLabs</th>\n", " <th>Q40_12 Do you use any tools to help monitor your machine learning models and/or experiments? (Select all that apply) - Selected Choice - Fiddler</th>\n", " <th>Q40_13 Do you use any tools to help monitor your machine learning models and/or experiments? (Select all that apply) - Selected Choice - DVC</th>\n", " <th>Q40_14 Do you use any tools to help monitor your machine learning models and/or experiments? (Select all that apply) - Selected Choice - No / None</th>\n", " <th>Q40_15 Do you use any tools to help monitor your machine learning models and/or experiments? (Select all that apply) - Selected Choice - Other</th>\n", " <th>Q41_1 Do you use any of the following responsible or ethical AI products in your machine learning practices? (Select all that apply) - Selected Choice - Google Responsible AI Toolkit (LIT, What-if, Fairness Indicator, etc)</th>\n", " <th>Q41_2 Do you use any of the following responsible or ethical AI products in your machine learning practices? (Select all that apply) - Selected Choice - Microsoft Responsible AI Resources (Fairlearn, Counterfit, InterpretML, etc)</th>\n", " <th>Q41_3 Do you use any of the following responsible or ethical AI products in your machine learning practices? (Select all that apply) - Selected Choice - IBM AI Ethics tools (AI Fairness 360, Adversarial Robustness Toolbox, etc</th>\n", " <th>Q41_4 Do you use any of the following responsible or ethical AI products in your machine learning practices? (Select all that apply) - Selected Choice - Amazon AI Ethics Tools (Clarify, A2I, etc)</th>\n", " <th>Q41_5 Do you use any of the following responsible or ethical AI products in your machine learning practices? (Select all that apply) - Selected Choice - The LinkedIn Fairness Toolkit (LiFT)</th>\n", " <th>Q41_6 Do you use any of the following responsible or ethical AI products in your machine learning practices? (Select all that apply) - Selected Choice - Audit-AI</th>\n", " <th>Q41_7 Do you use any of the following responsible or ethical AI products in your machine learning practices? (Select all that apply) - Selected Choice - Aequitas</th>\n", " <th>Q41_8 Do you use any of the following responsible or ethical AI products in your machine learning practices? (Select all that apply) - Selected Choice - None</th>\n", " <th>Q41_9 Do you use any of the following responsible or ethical AI products in your machine learning practices? (Select all that apply) - Selected Choice - Other</th>\n", " <th>Q42_1 Do you use any of the following types of specialized hardware when training machine learning models? (Select all that apply) - Selected Choice - GPUs</th>\n", " <th>Q42_2 Do you use any of the following types of specialized hardware when training machine learning models? (Select all that apply) - Selected Choice - TPUs</th>\n", " <th>Q42_3 Do you use any of the following types of specialized hardware when training machine learning models? (Select all that apply) - Selected Choice - IPUs</th>\n", " <th>Q42_4 Do you use any of the following types of specialized hardware when training machine learning models? (Select all that apply) - Selected Choice - RDUs</th>\n", " <th>Q42_5 Do you use any of the following types of specialized hardware when training machine learning models? (Select all that apply) - Selected Choice - WSEs</th>\n", " <th>Q42_6 Do you use any of the following types of specialized hardware when training machine learning models? (Select all that apply) - Selected Choice - Trainium Chips</th>\n", " <th>Q42_7 Do you use any of the following types of specialized hardware when training machine learning models? (Select all that apply) - Selected Choice - Inferentia Chips</th>\n", " <th>Q42_8 Do you use any of the following types of specialized hardware when training machine learning models? (Select all that apply) - Selected Choice - None</th>\n", " <th>Q42_9 Do you use any of the following types of specialized hardware when training machine learning models? (Select all that apply) - Selected Choice - Other</th>\n", " <th>Q43 Approximately how many times have you used a TPU (tensor processing unit)?</th>\n", " <th>Q44_1 Who/what are your favorite media sources that report on data science topics? (Select all that apply) - Selected Choice - Twitter (data science influencers)</th>\n", " <th>Q44_2 Who/what are your favorite media sources that report on data science topics? (Select all that apply) - Selected Choice - Email newsletters (Data Elixir, O'Reilly Data & AI, etc)</th>\n", " <th>Q44_3 Who/what are your favorite media sources that report on data science topics? (Select all that apply) - Selected Choice - Reddit (r/machinelearning, etc)</th>\n", " <th>Q44_4 Who/what are your favorite media sources that report on data science topics? (Select all that apply) - Selected Choice - Kaggle (notebooks, forums, etc)</th>\n", " <th>Q44_5 Who/what are your favorite media sources that report on data science topics? (Select all that apply) - Selected Choice - Course Forums (forums.fast.ai, Coursera forums, etc)</th>\n", " <th>Q44_6 Who/what are your favorite media sources that report on data science topics? (Select all that apply) - Selected Choice - YouTube (Kaggle YouTube, Cloud AI Adventures, etc)</th>\n", " <th>Q44_7 Who/what are your favorite media sources that report on data science topics? (Select all that apply) - Selected Choice - Podcasts (Chai Time Data Science, O’Reilly Data Show, etc)</th>\n", " <th>Q44_8 Who/what are your favorite media sources that report on data science topics? (Select all that apply) - Selected Choice - Blogs (Towards Data Science, Analytics Vidhya, etc)</th>\n", " <th>Q44_9 Who/what are your favorite media sources that report on data science topics? (Select all that apply) - Selected Choice - Journal Publications (peer-reviewed journals, conference proceedings, etc)</th>\n", " <th>Q44_10 Who/what are your favorite media sources that report on data science topics? (Select all that apply) - Selected Choice - Slack Communities (ods.ai, kagglenoobs, etc)</th>\n", " <th>Q44_11 Who/what are your favorite media sources that report on data science topics? (Select all that apply) - Selected Choice - None</th>\n", " <th>Q44_12 Who/what are your favorite media sources that report on data science topics? (Select all that apply) - Selected Choice - Other</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>1</th>\n", " <td>121</td>\n", " <td>30-34</td>\n", " <td>Man</td>\n", " <td>India</td>\n", " <td>No</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>Other</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " </tr>\n", " <tr>\n", " <th>2</th>\n", " <td>462</td>\n", " <td>30-34</td>\n", " <td>Man</td>\n", " <td>Algeria</td>\n", " <td>No</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>University Courses (resulting in a university ...</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>University courses</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>Kaggle (notebooks, competitions, etc)</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>Master’s degree</td>\n", " <td>Yes</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>No</td>\n", " <td>1-3 years</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>Java</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>Notepad++</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>Other</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>None</td>\n", " <td>NaN</td>\n", " <td>Matplotlib</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>Under 1 year</td>\n", " <td>Scikit-learn</td>\n", " <td>TensorFlow</td>\n", " <td>NaN</td>\n", " <td>PyTorch</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>Bayesian Approaches</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>No, I do not download pre-trained model weight...</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " Duration (in seconds) Q2 What is your age (# years)? \\\n", "1 121 30-34 \n", "2 462 30-34 \n", "\n", " Q3 What is your gender? - Selected Choice \\\n", "1 Man \n", "2 Man \n", "\n", " Q4 In which country do you currently reside? \\\n", "1 India \n", "2 Algeria \n", "\n", " Q5 Are you currently a student? (high school, university, or graduate) \\\n", "1 No \n", "2 No \n", "\n", " Q6_1 On which platforms have you begun or completed data science courses? (Select all that apply) - Selected Choice - Coursera \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q6_2 On which platforms have you begun or completed data science courses? (Select all that apply) - Selected Choice - edX \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q6_3 On which platforms have you begun or completed data science courses? (Select all that apply) - Selected Choice - Kaggle Learn Courses \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q6_4 On which platforms have you begun or completed data science courses? (Select all that apply) - Selected Choice - DataCamp \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q6_5 On which platforms have you begun or completed data science courses? (Select all that apply) - Selected Choice - Fast.ai \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q6_6 On which platforms have you begun or completed data science courses? (Select all that apply) - Selected Choice - Udacity \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q6_7 On which platforms have you begun or completed data science courses? (Select all that apply) - Selected Choice - Udemy \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q6_8 On which platforms have you begun or completed data science courses? (Select all that apply) - Selected Choice - LinkedIn Learning \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q6_9 On which platforms have you begun or completed data science courses? (Select all that apply) - Selected Choice - Cloud-certification programs (direct from AWS, Azure, GCP, or similar) \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q6_10 On which platforms have you begun or completed data science courses? (Select all that apply) - Selected Choice - University Courses (resulting in a university degree) \\\n", "1 NaN \n", "2 University Courses (resulting in a university ... \n", "\n", " Q6_11 On which platforms have you begun or completed data science courses? (Select all that apply) - Selected Choice - None \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q6_12 On which platforms have you begun or completed data science courses? (Select all that apply) - Selected Choice - Other \\\n", "1 Other \n", "2 NaN \n", "\n", " Q7_1 What products or platforms did you find to be most helpful when you first started studying data science? (Select all that apply) - Selected Choice - University courses \\\n", "1 NaN \n", "2 University courses \n", "\n", " Q7_2 What products or platforms did you find to be most helpful when you first started studying data science? (Select all that apply) - Selected Choice - Online courses (Coursera, EdX, etc) \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q7_3 What products or platforms did you find to be most helpful when you first started studying data science? (Select all that apply) - Selected Choice - Social media platforms (Reddit, Twitter, etc) \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q7_4 What products or platforms did you find to be most helpful when you first started studying data science? (Select all that apply) - Selected Choice - Video platforms (YouTube, Twitch, etc) \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q7_5 What products or platforms did you find to be most helpful when you first started studying data science? (Select all that apply) - Selected Choice - Kaggle (notebooks, competitions, etc) \\\n", "1 NaN \n", "2 Kaggle (notebooks, competitions, etc) \n", "\n", " Q7_6 What products or platforms did you find to be most helpful when you first started studying data science? (Select all that apply) - Selected Choice - None / I do not study data science \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q7_7 What products or platforms did you find to be most helpful when you first started studying data science? (Select all that apply) - Selected Choice - Other \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q8 What is the highest level of formal education that you have attained or plan to attain within the next 2 years? \\\n", "1 NaN \n", "2 Master’s degree \n", "\n", " Q9 Have you ever published any academic research (papers, preprints, conference proceedings, etc)? \\\n", "1 NaN \n", "2 Yes \n", "\n", " Q10_1 Did your research make use of machine learning? - Yes, the research made advances related to some novel machine learning method (theoretical research) \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q10_2 Did your research make use of machine learning? - Yes, the research made use of machine learning as a tool (applied research) \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q10_3 Did your research make use of machine learning? - No \\\n", "1 NaN \n", "2 No \n", "\n", " Q11 For how many years have you been writing code and/or programming? \\\n", "1 NaN \n", "2 1-3 years \n", "\n", " Q12_1 What programming languages do you use on a regular basis? (Select all that apply) - Selected Choice - Python \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q12_2 What programming languages do you use on a regular basis? (Select all that apply) - Selected Choice - R \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q12_3 What programming languages do you use on a regular basis? (Select all that apply) - Selected Choice - SQL \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q12_4 What programming languages do you use on a regular basis? (Select all that apply) - Selected Choice - C \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q12_5 What programming languages do you use on a regular basis? (Select all that apply) - Selected Choice - C# \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q12_6 What programming languages do you use on a regular basis? (Select all that apply) - Selected Choice - C++ \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q12_7 What programming languages do you use on a regular basis? (Select all that apply) - Selected Choice - Java \\\n", "1 NaN \n", "2 Java \n", "\n", " Q12_8 What programming languages do you use on a regular basis? (Select all that apply) - Selected Choice - Javascript \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q12_9 What programming languages do you use on a regular basis? (Select all that apply) - Selected Choice - Bash \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q12_10 What programming languages do you use on a regular basis? (Select all that apply) - Selected Choice - PHP \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q12_11 What programming languages do you use on a regular basis? (Select all that apply) - Selected Choice - MATLAB \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q12_12 What programming languages do you use on a regular basis? (Select all that apply) - Selected Choice - Julia \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q12_13 What programming languages do you use on a regular basis? (Select all that apply) - Selected Choice - Go \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q12_14 What programming languages do you use on a regular basis? (Select all that apply) - Selected Choice - None \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q12_15 What programming languages do you use on a regular basis? (Select all that apply) - Selected Choice - Other \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q13_1 Which of the following integrated development environments (IDE's) do you use on a regular basis? (Select all that apply) - Selected Choice - JupyterLab \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q13_2 Which of the following integrated development environments (IDE's) do you use on a regular basis? (Select all that apply) - Selected Choice - RStudio \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q13_3 Which of the following integrated development environments (IDE's) do you use on a regular basis? (Select all that apply) - Selected Choice - Visual Studio \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q13_4 Which of the following integrated development environments (IDE's) do you use on a regular basis? (Select all that apply) - Selected Choice - Visual Studio Code (VSCode) \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q13_5 Which of the following integrated development environments (IDE's) do you use on a regular basis? (Select all that apply) - Selected Choice - PyCharm \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q13_6 Which of the following integrated development environments (IDE's) do you use on a regular basis? (Select all that apply) - Selected Choice - Spyder \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q13_7 Which of the following integrated development environments (IDE's) do you use on a regular basis? (Select all that apply) - Selected Choice - Notepad++ \\\n", "1 NaN \n", "2 Notepad++ \n", "\n", " Q13_8 Which of the following integrated development environments (IDE's) do you use on a regular basis? (Select all that apply) - Selected Choice - Sublime Text \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q13_9 Which of the following integrated development environments (IDE's) do you use on a regular basis? (Select all that apply) - Selected Choice - Vim / Emacs \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q13_10 Which of the following integrated development environments (IDE's) do you use on a regular basis? (Select all that apply) - Selected Choice - MATLAB \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q13_11 Which of the following integrated development environments (IDE's) do you use on a regular basis? (Select all that apply) - Selected Choice - Jupyter Notebook \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q13_12 Which of the following integrated development environments (IDE's) do you use on a regular basis? (Select all that apply) - Selected Choice - IntelliJ \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q13_13 Which of the following integrated development environments (IDE's) do you use on a regular basis? (Select all that apply) - Selected Choice - None \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q13_14 Which of the following integrated development environments (IDE's) do you use on a regular basis? (Select all that apply) - Selected Choice - Other \\\n", "1 NaN \n", "2 Other \n", "\n", " Q14_1 Do you use any of the following hosted notebook products? (Select all that apply) - Selected Choice - Kaggle Notebooks \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q14_2 Do you use any of the following hosted notebook products? (Select all that apply) - Selected Choice - Colab Notebooks \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q14_3 Do you use any of the following hosted notebook products? (Select all that apply) - Selected Choice - Azure Notebooks \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q14_4 Do you use any of the following hosted notebook products? (Select all that apply) - Selected Choice - Code Ocean \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q14_5 Do you use any of the following hosted notebook products? (Select all that apply) - Selected Choice - IBM Watson Studio \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q14_6 Do you use any of the following hosted notebook products? (Select all that apply) - Selected Choice - Amazon Sagemaker Studio \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q14_7 Do you use any of the following hosted notebook products? (Select all that apply) - Selected Choice - Amazon Sagemaker Studio Lab \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q14_8 Do you use any of the following hosted notebook products? (Select all that apply) - Selected Choice - Amazon EMR Notebooks \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q14_9 Do you use any of the following hosted notebook products? (Select all that apply) - Selected Choice - Google Cloud Vertex AI Workbench \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q14_10 Do you use any of the following hosted notebook products? (Select all that apply) - Selected Choice - Hex Workspaces \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q14_11 Do you use any of the following hosted notebook products? (Select all that apply) - Selected Choice - Noteable Notebooks \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q14_12 Do you use any of the following hosted notebook products? (Select all that apply) - Selected Choice - Databricks Collaborative Notebooks \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q14_13 Do you use any of the following hosted notebook products? (Select all that apply) - Selected Choice - Deepnote Notebooks \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q14_14 Do you use any of the following hosted notebook products? (Select all that apply) - Selected Choice - Gradient Notebooks \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q14_15 Do you use any of the following hosted notebook products? (Select all that apply) - Selected Choice - None \\\n", "1 NaN \n", "2 None \n", "\n", " Q14_16 Do you use any of the following hosted notebook products? (Select all that apply) - Selected Choice - Other \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q15_1 Do you use any of the following data visualization libraries on a regular basis? (Select all that apply) - Selected Choice - Matplotlib \\\n", "1 NaN \n", "2 Matplotlib \n", "\n", " Q15_2 Do you use any of the following data visualization libraries on a regular basis? (Select all that apply) - Selected Choice - Seaborn \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q15_3 Do you use any of the following data visualization libraries on a regular basis? (Select all that apply) - Selected Choice - Plotly / Plotly Express \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q15_4 Do you use any of the following data visualization libraries on a regular basis? (Select all that apply) - Selected Choice - Ggplot / ggplot2 \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q15_5 Do you use any of the following data visualization libraries on a regular basis? (Select all that apply) - Selected Choice - Shiny \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q15_6 Do you use any of the following data visualization libraries on a regular basis? (Select all that apply) - Selected Choice - D3 js \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q15_7 Do you use any of the following data visualization libraries on a regular basis? (Select all that apply) - Selected Choice - Altair \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q15_8 Do you use any of the following data visualization libraries on a regular basis? (Select all that apply) - Selected Choice - Bokeh \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q15_9 Do you use any of the following data visualization libraries on a regular basis? (Select all that apply) - Selected Choice - Geoplotlib \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q15_10 Do you use any of the following data visualization libraries on a regular basis? (Select all that apply) - Selected Choice - Leaflet / Folium \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q15_11 Do you use any of the following data visualization libraries on a regular basis? (Select all that apply) - Selected Choice - Pygal \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q15_12 Do you use any of the following data visualization libraries on a regular basis? (Select all that apply) - Selected Choice - Dygraphs \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q15_13 Do you use any of the following data visualization libraries on a regular basis? (Select all that apply) - Selected Choice - Highcharter \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q15_14 Do you use any of the following data visualization libraries on a regular basis? (Select all that apply) - Selected Choice - None \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q15_15 Do you use any of the following data visualization libraries on a regular basis? (Select all that apply) - Selected Choice - Other \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q16 For how many years have you used machine learning methods? \\\n", "1 NaN \n", "2 Under 1 year \n", "\n", " Q17_1 Which of the following machine learning frameworks do you use on a regular basis? (Select all that apply) - Selected Choice - Scikit-learn \\\n", "1 NaN \n", "2 Scikit-learn \n", "\n", " Q17_2 Which of the following machine learning frameworks do you use on a regular basis? (Select all that apply) - Selected Choice - TensorFlow \\\n", "1 NaN \n", "2 TensorFlow \n", "\n", " Q17_3 Which of the following machine learning frameworks do you use on a regular basis? (Select all that apply) - Selected Choice - Keras \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q17_4 Which of the following machine learning frameworks do you use on a regular basis? (Select all that apply) - Selected Choice - PyTorch \\\n", "1 NaN \n", "2 PyTorch \n", "\n", " Q17_5 Which of the following machine learning frameworks do you use on a regular basis? (Select all that apply) - Selected Choice - Fast.ai \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q17_6 Which of the following machine learning frameworks do you use on a regular basis? (Select all that apply) - Selected Choice - Xgboost \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q17_7 Which of the following machine learning frameworks do you use on a regular basis? (Select all that apply) - Selected Choice - LightGBM \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q17_8 Which of the following machine learning frameworks do you use on a regular basis? (Select all that apply) - Selected Choice - CatBoost \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q17_9 Which of the following machine learning frameworks do you use on a regular basis? (Select all that apply) - Selected Choice - Caret \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q17_10 Which of the following machine learning frameworks do you use on a regular basis? (Select all that apply) - Selected Choice - Tidymodels \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q17_11 Which of the following machine learning frameworks do you use on a regular basis? (Select all that apply) - Selected Choice - JAX \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q17_12 Which of the following machine learning frameworks do you use on a regular basis? (Select all that apply) - Selected Choice - PyTorch Lightning \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q17_13 Which of the following machine learning frameworks do you use on a regular basis? (Select all that apply) - Selected Choice - Huggingface \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q17_14 Which of the following machine learning frameworks do you use on a regular basis? (Select all that apply) - Selected Choice - None \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q17_15 Which of the following machine learning frameworks do you use on a regular basis? (Select all that apply) - Selected Choice - Other \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q18_1 Which of the following ML algorithms do you use on a regular basis? (Select all that apply): - Selected Choice - Linear or Logistic Regression \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q18_2 Which of the following ML algorithms do you use on a regular basis? (Select all that apply): - Selected Choice - Decision Trees or Random Forests \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q18_3 Which of the following ML algorithms do you use on a regular basis? (Select all that apply): - Selected Choice - Gradient Boosting Machines (xgboost, lightgbm, etc) \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q18_4 Which of the following ML algorithms do you use on a regular basis? (Select all that apply): - Selected Choice - Bayesian Approaches \\\n", "1 NaN \n", "2 Bayesian Approaches \n", "\n", " Q18_5 Which of the following ML algorithms do you use on a regular basis? (Select all that apply): - Selected Choice - Evolutionary Approaches \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q18_6 Which of the following ML algorithms do you use on a regular basis? (Select all that apply): - Selected Choice - Dense Neural Networks (MLPs, etc) \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q18_7 Which of the following ML algorithms do you use on a regular basis? (Select all that apply): - Selected Choice - Convolutional Neural Networks \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q18_8 Which of the following ML algorithms do you use on a regular basis? (Select all that apply): - Selected Choice - Generative Adversarial Networks \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q18_9 Which of the following ML algorithms do you use on a regular basis? (Select all that apply): - Selected Choice - Recurrent Neural Networks \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q18_10 Which of the following ML algorithms do you use on a regular basis? (Select all that apply): - Selected Choice - Transformer Networks (BERT, gpt-3, etc) \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q18_11 Which of the following ML algorithms do you use on a regular basis? (Select all that apply): - Selected Choice - Autoencoder Networks (DAE, VAE, etc) \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q18_12 Which of the following ML algorithms do you use on a regular basis? (Select all that apply): - Selected Choice - Graph Neural Networks \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q18_13 Which of the following ML algorithms do you use on a regular basis? (Select all that apply): - Selected Choice - None \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q18_14 Which of the following ML algorithms do you use on a regular basis? (Select all that apply): - Selected Choice - Other \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q19_1 Which categories of computer vision methods do you use on a regular basis? (Select all that apply) - Selected Choice - General purpose image/video tools (PIL, cv2, skimage, etc) \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q19_2 Which categories of computer vision methods do you use on a regular basis? (Select all that apply) - Selected Choice - Image segmentation methods (U-Net, Mask R-CNN, etc) \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q19_3 Which categories of computer vision methods do you use on a regular basis? (Select all that apply) - Selected Choice - Object detection methods (YOLOv6, RetinaNet, etc) \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q19_4 Which categories of computer vision methods do you use on a regular basis? (Select all that apply) - Selected Choice - Image classification and other general purpose networks (VGG, Inception, ResNet, ResNeXt, NASNet, EfficientNet, etc) \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q19_5 Which categories of computer vision methods do you use on a regular basis? (Select all that apply) - Selected Choice - Generative Networks (GAN, VAE, etc) \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q19_6 Which categories of computer vision methods do you use on a regular basis? (Select all that apply) - Selected Choice - Vision transformer networks (ViT, DeiT, BiT, BEiT, Swin, etc) \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q19_7 Which categories of computer vision methods do you use on a regular basis? (Select all that apply) - Selected Choice - None \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q19_8 Which categories of computer vision methods do you use on a regular basis? (Select all that apply) - Selected Choice - Other \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q20_1 Which of the following natural language processing (NLP) methods do you use on a regular basis? (Select all that apply) - Selected Choice - Word embeddings/vectors (GLoVe, fastText, word2vec) \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q20_2 Which of the following natural language processing (NLP) methods do you use on a regular basis? (Select all that apply) - Selected Choice - Encoder-decoder models (seq2seq, vanilla transformers) \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q20_3 Which of the following natural language processing (NLP) methods do you use on a regular basis? (Select all that apply) - Selected Choice - Contextualized embeddings (ELMo, CoVe) \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q20_4 Which of the following natural language processing (NLP) methods do you use on a regular basis? (Select all that apply) - Selected Choice - Transformer language models (GPT-3, BERT, XLnet, etc) \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q20_5 Which of the following natural language processing (NLP) methods do you use on a regular basis? (Select all that apply) - Selected Choice - None \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q20_6 Which of the following natural language processing (NLP) methods do you use on a regular basis? (Select all that apply) - Selected Choice - Other \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q21_1 Do you download pre-trained model weights from any of the following services? (Select all that apply) - Selected Choice - TensorFlow Hub \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q21_2 Do you download pre-trained model weights from any of the following services? (Select all that apply) - Selected Choice - PyTorch Hub \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q21_3 Do you download pre-trained model weights from any of the following services? (Select all that apply) - Selected Choice - Huggingface Models \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q21_4 Do you download pre-trained model weights from any of the following services? (Select all that apply) - Selected Choice - Timm \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q21_5 Do you download pre-trained model weights from any of the following services? (Select all that apply) - Selected Choice - Jumpstart \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q21_6 Do you download pre-trained model weights from any of the following services? (Select all that apply) - Selected Choice - ONNX models \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q21_7 Do you download pre-trained model weights from any of the following services? (Select all that apply) - Selected Choice - NVIDIA NGC models \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q21_8 Do you download pre-trained model weights from any of the following services? (Select all that apply) - Selected Choice - Kaggle datasets \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q21_9 Do you download pre-trained model weights from any of the following services? (Select all that apply) - Selected Choice - No, I do not download pre-trained model weights on a regular basis \\\n", "1 NaN \n", "2 No, I do not download pre-trained model weight... \n", "\n", " Q21_10 Do you download pre-trained model weights from any of the following services? (Select all that apply) - Selected Choice - Other storage services (i.e. google drive) \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q22 Which of the following ML model hubs/repositories do you use most often? - Selected Choice \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q23 Select the title most similar to your current role (or most recent title if retired): - Selected Choice \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q24 In what industry is your current employer/contract (or your most recent employer if retired)? - Selected Choice \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q25 What is the size of the company where you are employed? \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q26 Approximately how many individuals are responsible for data science workloads at your place of business? \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q27 Does your current employer incorporate machine learning methods into their business? \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q28_1 Select any activities that make up an important part of your role at work: (Select all that apply) - Analyze and understand data to influence product or business decisions \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q28_2 Select any activities that make up an important part of your role at work: (Select all that apply) - Build and/or run the data infrastructure that my business uses for storing, analyzing, and operationalizing data \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q28_3 Select any activities that make up an important part of your role at work: (Select all that apply) - Build prototypes to explore applying machine learning to new areas \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q28_4 Select any activities that make up an important part of your role at work: (Select all that apply) - Build and/or run a machine learning service that operationally improves my product or workflows \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q28_5 Select any activities that make up an important part of your role at work: (Select all that apply) - Experimentation and iteration to improve existing ML models \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q28_6 Select any activities that make up an important part of your role at work: (Select all that apply) - Do research that advances the state of the art of machine learning \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q28_7 Select any activities that make up an important part of your role at work: (Select all that apply) - None of these activities are an important part of my role at work \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q28_8 Select any activities that make up an important part of your role at work: (Select all that apply) - Other \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q29 What is your current yearly compensation (approximate $USD)? \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q30 Approximately how much money have you spent on machine learning and/or cloud computing services at home or at work in the past 5 years (approximate $USD)?\\n (approximate $USD)? \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q31_1 Which of the following cloud computing platforms do you use? (Select all that apply) - Selected Choice - Amazon Web Services (AWS) \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q31_2 Which of the following cloud computing platforms do you use? (Select all that apply) - Selected Choice - Microsoft Azure \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q31_3 Which of the following cloud computing platforms do you use? (Select all that apply) - Selected Choice - Google Cloud Platform (GCP) \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q31_4 Which of the following cloud computing platforms do you use? (Select all that apply) - Selected Choice - IBM Cloud / Red Hat \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q31_5 Which of the following cloud computing platforms do you use? (Select all that apply) - Selected Choice - Oracle Cloud \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q31_6 Which of the following cloud computing platforms do you use? (Select all that apply) - Selected Choice - SAP Cloud \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q31_7 Which of the following cloud computing platforms do you use? (Select all that apply) - Selected Choice - VMware Cloud \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q31_8 Which of the following cloud computing platforms do you use? (Select all that apply) - Selected Choice - Alibaba Cloud \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q31_9 Which of the following cloud computing platforms do you use? (Select all that apply) - Selected Choice - Tencent Cloud \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q31_10 Which of the following cloud computing platforms do you use? (Select all that apply) - Selected Choice - Huawei Cloud \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q31_11 Which of the following cloud computing platforms do you use? (Select all that apply) - Selected Choice - None \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q31_12 Which of the following cloud computing platforms do you use? (Select all that apply) - Selected Choice - Other \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q32 Of the cloud platforms that you are familiar with, which has the best developer experience (most enjoyable to use)? - Selected Choice \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q33_1 Do you use any of the following cloud computing products? (Select all that apply) - Selected Choice - Amazon Elastic Compute Cloud (EC2) \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q33_2 Do you use any of the following cloud computing products? (Select all that apply) - Selected Choice - Microsoft Azure Virtual Machines \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q33_3 Do you use any of the following cloud computing products? (Select all that apply) - Selected Choice - Google Cloud Compute Engine \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q33_4 Do you use any of the following cloud computing products? (Select all that apply) - Selected Choice - No / None \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q33_5 Do you use any of the following cloud computing products? (Select all that apply) - Selected Choice - Other \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q34_1 Do you use any of the following data storage products? (Select all that apply) - Selected Choice - Microsoft Azure Blob Storage \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q34_2 Do you use any of the following data storage products? (Select all that apply) - Selected Choice - Microsoft Azure Files \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q34_3 Do you use any of the following data storage products? (Select all that apply) - Selected Choice - Amazon Simple Storage Service (S3) \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q34_4 Do you use any of the following data storage products? (Select all that apply) - Selected Choice - Amazon Elastic File System (EFS) \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q34_5 Do you use any of the following data storage products? (Select all that apply) - Selected Choice - Google Cloud Storage (GCS) \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q34_6 Do you use any of the following data storage products? (Select all that apply) - Selected Choice - Google Cloud Filestore \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q34_7 Do you use any of the following data storage products? (Select all that apply) - Selected Choice - No / None \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q34_8 Do you use any of the following data storage products? (Select all that apply) - Selected Choice - Other \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q35_1 Do you use any of the following data products (relational databases, data warehouses, data lakes, or similar)? (Select all that apply) - Selected Choice - MySQL \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q35_2 Do you use any of the following data products (relational databases, data warehouses, data lakes, or similar)? (Select all that apply) - Selected Choice - PostgreSQL \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q35_3 Do you use any of the following data products (relational databases, data warehouses, data lakes, or similar)? (Select all that apply) - Selected Choice - SQLite \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q35_4 Do you use any of the following data products (relational databases, data warehouses, data lakes, or similar)? (Select all that apply) - Selected Choice - Oracle Database \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q35_5 Do you use any of the following data products (relational databases, data warehouses, data lakes, or similar)? (Select all that apply) - Selected Choice - MongoDB \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q35_6 Do you use any of the following data products (relational databases, data warehouses, data lakes, or similar)? (Select all that apply) - Selected Choice - Snowflake \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q35_7 Do you use any of the following data products (relational databases, data warehouses, data lakes, or similar)? (Select all that apply) - Selected Choice - IBM Db2 \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q35_8 Do you use any of the following data products (relational databases, data warehouses, data lakes, or similar)? (Select all that apply) - Selected Choice - Microsoft SQL Server \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q35_9 Do you use any of the following data products (relational databases, data warehouses, data lakes, or similar)? (Select all that apply) - Selected Choice - Microsoft Azure SQL Database \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q35_10 Do you use any of the following data products (relational databases, data warehouses, data lakes, or similar)? (Select all that apply) - Selected Choice - Amazon Redshift \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q35_11 Do you use any of the following data products (relational databases, data warehouses, data lakes, or similar)? (Select all that apply) - Selected Choice - Amazon RDS \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q35_12 Do you use any of the following data products (relational databases, data warehouses, data lakes, or similar)? (Select all that apply) - Selected Choice - Amazon DynamoDB \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q35_13 Do you use any of the following data products (relational databases, data warehouses, data lakes, or similar)? (Select all that apply) - Selected Choice - Google Cloud BigQuery \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q35_14 Do you use any of the following data products (relational databases, data warehouses, data lakes, or similar)? (Select all that apply) - Selected Choice - Google Cloud SQL \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q35_15 Do you use any of the following data products (relational databases, data warehouses, data lakes, or similar)? (Select all that apply) - Selected Choice - None \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q35_16 Do you use any of the following data products (relational databases, data warehouses, data lakes, or similar)? (Select all that apply) - Selected Choice - Other \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q36_1 Do you use any of the following business intelligence tools? (Select all that apply) - Selected Choice - Amazon QuickSight \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q36_2 Do you use any of the following business intelligence tools? (Select all that apply) - Selected Choice - Microsoft Power BI \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q36_3 Do you use any of the following business intelligence tools? (Select all that apply) - Selected Choice - Google Data Studio \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q36_4 Do you use any of the following business intelligence tools? (Select all that apply) - Selected Choice - Looker \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q36_5 Do you use any of the following business intelligence tools? (Select all that apply) - Selected Choice - Tableau \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q36_6 Do you use any of the following business intelligence tools? (Select all that apply) - Selected Choice - Qlik Sense \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q36_7 Do you use any of the following business intelligence tools? (Select all that apply) - Selected Choice - Domo \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q36_8 Do you use any of the following business intelligence tools? (Select all that apply) - Selected Choice - TIBCO Spotfire \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q36_9 Do you use any of the following business intelligence tools? (Select all that apply) - Selected Choice - Alteryx \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q36_10 Do you use any of the following business intelligence tools? (Select all that apply) - Selected Choice - Sisense \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q36_11 Do you use any of the following business intelligence tools? (Select all that apply) - Selected Choice - SAP Analytics Cloud \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q36_12 Do you use any of the following business intelligence tools? (Select all that apply) - Selected Choice - Microsoft Azure Synapse \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q36_13 Do you use any of the following business intelligence tools? (Select all that apply) - Selected Choice - Thoughtspot \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q36_14 Do you use any of the following business intelligence tools? (Select all that apply) - Selected Choice - None \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q36_15 Do you use any of the following business intelligence tools? (Select all that apply) - Selected Choice - Other \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q37_1 Do you use any of the following managed machine learning products on a regular basis? (Select all that apply) - Selected Choice - Amazon SageMaker \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q37_2 Do you use any of the following managed machine learning products on a regular basis? (Select all that apply) - Selected Choice - Azure Machine Learning Studio \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q37_3 Do you use any of the following managed machine learning products on a regular basis? (Select all that apply) - Selected Choice - Google Cloud Vertex AI \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q37_4 Do you use any of the following managed machine learning products on a regular basis? (Select all that apply) - Selected Choice - DataRobot \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q37_5 Do you use any of the following managed machine learning products on a regular basis? (Select all that apply) - Selected Choice - Databricks \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q37_6 Do you use any of the following managed machine learning products on a regular basis? (Select all that apply) - Selected Choice - Dataiku \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q37_7 Do you use any of the following managed machine learning products on a regular basis? (Select all that apply) - Selected Choice - Alteryx \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q37_8 Do you use any of the following managed machine learning products on a regular basis? (Select all that apply) - Selected Choice - Rapidminer \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q37_9 Do you use any of the following managed machine learning products on a regular basis? (Select all that apply) - Selected Choice - C3.ai \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q37_10 Do you use any of the following managed machine learning products on a regular basis? (Select all that apply) - Selected Choice - Domino Data Lab \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q37_11 Do you use any of the following managed machine learning products on a regular basis? (Select all that apply) - Selected Choice - H2O AI Cloud \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q37_12 Do you use any of the following managed machine learning products on a regular basis? (Select all that apply) - Selected Choice - No / None \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q37_13 Do you use any of the following managed machine learning products on a regular basis? (Select all that apply) - Selected Choice - Other \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q38_1 Do you use any of the following automated machine learning tools? (Select all that apply) - Selected Choice - Google Cloud AutoML \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q38_2 Do you use any of the following automated machine learning tools? (Select all that apply) - Selected Choice - H2O Driverless AI \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q38_3 Do you use any of the following automated machine learning tools? (Select all that apply) - Selected Choice - Databricks AutoML \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q38_4 Do you use any of the following automated machine learning tools? (Select all that apply) - Selected Choice - DataRobot AutoML \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q38_5 Do you use any of the following automated machine learning tools? (Select all that apply) - Selected Choice - Amazon Sagemaker Autopilot \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q38_6 Do you use any of the following automated machine learning tools? (Select all that apply) - Selected Choice - Azure Automated Machine Learning \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q38_7 Do you use any of the following automated machine learning tools? (Select all that apply) - Selected Choice - No / None \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q38_8 Do you use any of the following automated machine learning tools? (Select all that apply) - Selected Choice - Other \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q39_1 Do you use any of the following products to serve your machine learning models? (Select all that apply) - Selected Choice - TensorFlow Extended (TFX) \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q39_2 Do you use any of the following products to serve your machine learning models? (Select all that apply) - Selected Choice - TorchServe \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q39_3 Do you use any of the following products to serve your machine learning models? (Select all that apply) - Selected Choice - ONNX Runtime \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q39_4 Do you use any of the following products to serve your machine learning models? (Select all that apply) - Selected Choice - Triton Inference Server \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q39_5 Do you use any of the following products to serve your machine learning models? (Select all that apply) - Selected Choice - OpenVINO Model Server \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q39_6 Do you use any of the following products to serve your machine learning models? (Select all that apply) - Selected Choice - KServe \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q39_7 Do you use any of the following products to serve your machine learning models? (Select all that apply) - Selected Choice - BentoML \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q39_8 Do you use any of the following products to serve your machine learning models? (Select all that apply) - Selected Choice - Multi Model Server (MMS) \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q39_9 Do you use any of the following products to serve your machine learning models? (Select all that apply) - Selected Choice - Seldon Core \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q39_10 Do you use any of the following products to serve your machine learning models? (Select all that apply) - Selected Choice - MLflow \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q39_11 Do you use any of the following products to serve your machine learning models? (Select all that apply) - Selected Choice - None \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q39_12 Do you use any of the following products to serve your machine learning models? (Select all that apply) - Selected Choice - Other \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q40_1 Do you use any tools to help monitor your machine learning models and/or experiments? (Select all that apply) - Selected Choice - Neptune.ai \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q40_2 Do you use any tools to help monitor your machine learning models and/or experiments? (Select all that apply) - Selected Choice - Weights & Biases \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q40_3 Do you use any tools to help monitor your machine learning models and/or experiments? (Select all that apply) - Selected Choice - Comet.ml \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q40_4 Do you use any tools to help monitor your machine learning models and/or experiments? (Select all that apply) - Selected Choice - TensorBoard \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q40_5 Do you use any tools to help monitor your machine learning models and/or experiments? (Select all that apply) - Selected Choice - Guild.ai \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q40_6 Do you use any tools to help monitor your machine learning models and/or experiments? (Select all that apply) - Selected Choice - ClearML \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q40_7 Do you use any tools to help monitor your machine learning models and/or experiments? (Select all that apply) - Selected Choice - MLflow \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q40_8 Do you use any tools to help monitor your machine learning models and/or experiments? (Select all that apply) - Selected Choice - Aporia \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q40_9 Do you use any tools to help monitor your machine learning models and/or experiments? (Select all that apply) - Selected Choice - Evidently AI \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q40_10 Do you use any tools to help monitor your machine learning models and/or experiments? (Select all that apply) - Selected Choice - Arize \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q40_11 Do you use any tools to help monitor your machine learning models and/or experiments? (Select all that apply) - Selected Choice - WhyLabs \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q40_12 Do you use any tools to help monitor your machine learning models and/or experiments? (Select all that apply) - Selected Choice - Fiddler \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q40_13 Do you use any tools to help monitor your machine learning models and/or experiments? (Select all that apply) - Selected Choice - DVC \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q40_14 Do you use any tools to help monitor your machine learning models and/or experiments? (Select all that apply) - Selected Choice - No / None \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q40_15 Do you use any tools to help monitor your machine learning models and/or experiments? (Select all that apply) - Selected Choice - Other \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q41_1 Do you use any of the following responsible or ethical AI products in your machine learning practices? (Select all that apply) - Selected Choice - Google Responsible AI Toolkit (LIT, What-if, Fairness Indicator, etc) \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q41_2 Do you use any of the following responsible or ethical AI products in your machine learning practices? (Select all that apply) - Selected Choice - Microsoft Responsible AI Resources (Fairlearn, Counterfit, InterpretML, etc) \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q41_3 Do you use any of the following responsible or ethical AI products in your machine learning practices? (Select all that apply) - Selected Choice - IBM AI Ethics tools (AI Fairness 360, Adversarial Robustness Toolbox, etc \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q41_4 Do you use any of the following responsible or ethical AI products in your machine learning practices? (Select all that apply) - Selected Choice - Amazon AI Ethics Tools (Clarify, A2I, etc) \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q41_5 Do you use any of the following responsible or ethical AI products in your machine learning practices? (Select all that apply) - Selected Choice - The LinkedIn Fairness Toolkit (LiFT) \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q41_6 Do you use any of the following responsible or ethical AI products in your machine learning practices? (Select all that apply) - Selected Choice - Audit-AI \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q41_7 Do you use any of the following responsible or ethical AI products in your machine learning practices? (Select all that apply) - Selected Choice - Aequitas \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q41_8 Do you use any of the following responsible or ethical AI products in your machine learning practices? (Select all that apply) - Selected Choice - None \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q41_9 Do you use any of the following responsible or ethical AI products in your machine learning practices? (Select all that apply) - Selected Choice - Other \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q42_1 Do you use any of the following types of specialized hardware when training machine learning models? (Select all that apply) - Selected Choice - GPUs \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q42_2 Do you use any of the following types of specialized hardware when training machine learning models? (Select all that apply) - Selected Choice - TPUs \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q42_3 Do you use any of the following types of specialized hardware when training machine learning models? (Select all that apply) - Selected Choice - IPUs \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q42_4 Do you use any of the following types of specialized hardware when training machine learning models? (Select all that apply) - Selected Choice - RDUs \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q42_5 Do you use any of the following types of specialized hardware when training machine learning models? (Select all that apply) - Selected Choice - WSEs \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q42_6 Do you use any of the following types of specialized hardware when training machine learning models? (Select all that apply) - Selected Choice - Trainium Chips \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q42_7 Do you use any of the following types of specialized hardware when training machine learning models? (Select all that apply) - Selected Choice - Inferentia Chips \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q42_8 Do you use any of the following types of specialized hardware when training machine learning models? (Select all that apply) - Selected Choice - None \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q42_9 Do you use any of the following types of specialized hardware when training machine learning models? (Select all that apply) - Selected Choice - Other \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q43 Approximately how many times have you used a TPU (tensor processing unit)? \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q44_1 Who/what are your favorite media sources that report on data science topics? (Select all that apply) - Selected Choice - Twitter (data science influencers) \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q44_2 Who/what are your favorite media sources that report on data science topics? (Select all that apply) - Selected Choice - Email newsletters (Data Elixir, O'Reilly Data & AI, etc) \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q44_3 Who/what are your favorite media sources that report on data science topics? (Select all that apply) - Selected Choice - Reddit (r/machinelearning, etc) \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q44_4 Who/what are your favorite media sources that report on data science topics? (Select all that apply) - Selected Choice - Kaggle (notebooks, forums, etc) \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q44_5 Who/what are your favorite media sources that report on data science topics? (Select all that apply) - Selected Choice - Course Forums (forums.fast.ai, Coursera forums, etc) \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q44_6 Who/what are your favorite media sources that report on data science topics? (Select all that apply) - Selected Choice - YouTube (Kaggle YouTube, Cloud AI Adventures, etc) \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q44_7 Who/what are your favorite media sources that report on data science topics? (Select all that apply) - Selected Choice - Podcasts (Chai Time Data Science, O’Reilly Data Show, etc) \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q44_8 Who/what are your favorite media sources that report on data science topics? (Select all that apply) - Selected Choice - Blogs (Towards Data Science, Analytics Vidhya, etc) \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q44_9 Who/what are your favorite media sources that report on data science topics? (Select all that apply) - Selected Choice - Journal Publications (peer-reviewed journals, conference proceedings, etc) \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q44_10 Who/what are your favorite media sources that report on data science topics? (Select all that apply) - Selected Choice - Slack Communities (ods.ai, kagglenoobs, etc) \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q44_11 Who/what are your favorite media sources that report on data science topics? (Select all that apply) - Selected Choice - None \\\n", "1 NaN \n", "2 NaN \n", "\n", " Q44_12 Who/what are your favorite media sources that report on data science topics? (Select all that apply) - Selected Choice - Other \n", "1 NaN \n", "2 NaN " ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Correcting the column names\n", "questions = data.iloc[0,1:].values.tolist()\n", "question_num = data.iloc[0,1:].index.tolist()\n", "header_str = [question_num[i] + \" \" + questions[i] for i in range(len(questions))]\n", "header_str.insert(0, data.iloc[0,0])\n", "data.columns = header_str\n", "data = data.drop(0, axis = 0)\n", "data.head(2)" ] }, { "cell_type": "code", "execution_count": 6, "id": "a81aa65b", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:39:26.934285Z", "iopub.status.busy": "2022-10-27T19:39:26.933877Z", "iopub.status.idle": "2022-10-27T19:39:26.943610Z", "shell.execute_reply": "2022-10-27T19:39:26.942464Z" }, "papermill": { "duration": 0.03331, "end_time": "2022-10-27T19:39:26.945873", "exception": false, "start_time": "2022-10-27T19:39:26.912563", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "# Finding questions with choices / multiple choices\n", "select_questions = []\n", "for header in header_str:\n", " if 'select' in header.lower():\n", " select_questions.append(header)\n", "\n", "# Filtering the questions to their unique question\n", "unique_select_questions = []\n", "question_numbers = []\n", "for col in select_questions[1:]:\n", " if '_' in col:\n", " question = col.split('(S')[0]\n", " question_number = question.split('_')[0]\n", " question = question.split()[1:]\n", " question = \" \".join(question)\n", " if question not in unique_select_questions:\n", " unique_select_questions.append(question)\n", " if question_number not in question_numbers:\n", " question_numbers.append(question_number)\n", "\n", "unique_select_questions_cleaned = [question_numbers[i] + \\\n", " \" \" + \\\n", " unique_select_questions[i] \\\n", " for i in range(len(question_numbers))]" ] }, { "cell_type": "markdown", "id": "bd0195b7", "metadata": { "papermill": { "duration": 0.019002, "end_time": "2022-10-27T19:39:26.984407", "exception": false, "start_time": "2022-10-27T19:39:26.965405", "status": "completed" }, "tags": [] }, "source": [ "## Algorithm to clean this data\n", "Initialize an empty dataframe \n", "\n", "For each question with choice / multiple choices: \n", "\n", "    > Filter all the subquestions / choices. \n", "\n", "    > Filter the dataframe with subquestions / choices and store the answers values in a list \n", "\n", "    > For each answser in the list of answers: \n", "\n", "        > For each element in the answer: \n", "\n", "        > If the element is not NaN then append the element to a temporary list. \n", "\n", "        > Try to join the elements for temporary list using join function \n", "\n", "        > If there's a exception then try to convert the element into a string and then join them \n", "\n", "    > Store the cleaned answer values with respect to each question with a choice / multiple choices in a dataframe." ] }, { "cell_type": "code", "execution_count": 7, "id": "ffbf597d", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:39:27.026169Z", "iopub.status.busy": "2022-10-27T19:39:27.025280Z", "iopub.status.idle": "2022-10-27T19:39:29.620332Z", "shell.execute_reply": "2022-10-27T19:39:29.619148Z" }, "papermill": { "duration": 2.619182, "end_time": "2022-10-27T19:39:29.623026", "exception": false, "start_time": "2022-10-27T19:39:27.003844", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "# Applying the above algorithm to clean the data\n", "cleaned_df = pd.DataFrame()\n", "for i in range(len(unique_select_questions)):\n", " sub_questions = [col for col in data.columns if unique_select_questions[i] in col]\n", " answers = data[sub_questions].values.tolist()\n", " cleaned = []\n", " for answer in answers:\n", " temp = []\n", " for element in answer:\n", " if element is not np.nan:\n", " temp.append(element)\n", " try:\n", " temp = \", \".join(temp)\n", " cleaned.append(temp)\n", " except:\n", " temp = [str(j) for j in temp]\n", " temp = \", \".join(temp)\n", " cleaned.append(temp)\n", " cleaned_df[unique_select_questions[i]] = cleaned" ] }, { "cell_type": "code", "execution_count": 8, "id": "6e5aebb6", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:39:29.664262Z", "iopub.status.busy": "2022-10-27T19:39:29.663342Z", "iopub.status.idle": "2022-10-27T19:39:29.668247Z", "shell.execute_reply": "2022-10-27T19:39:29.667518Z" }, "papermill": { "duration": 0.0277, "end_time": "2022-10-27T19:39:29.670216", "exception": false, "start_time": "2022-10-27T19:39:29.642516", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "# Naming the columns correctly\n", "cleaned_df.columns = unique_select_questions_cleaned" ] }, { "cell_type": "code", "execution_count": 9, "id": "743b17a4", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:39:29.711784Z", "iopub.status.busy": "2022-10-27T19:39:29.710976Z", "iopub.status.idle": "2022-10-27T19:39:29.716662Z", "shell.execute_reply": "2022-10-27T19:39:29.715601Z" }, "papermill": { "duration": 0.029497, "end_time": "2022-10-27T19:39:29.719069", "exception": false, "start_time": "2022-10-27T19:39:29.689572", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "# Get column names for all questions without multiple sub questions / choices\n", "unique_questions = []\n", "for col in data.columns:\n", " if '_' not in col:\n", " unique_questions.append(col)" ] }, { "cell_type": "code", "execution_count": 10, "id": "d13238c8", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:39:29.760289Z", "iopub.status.busy": "2022-10-27T19:39:29.759894Z", "iopub.status.idle": "2022-10-27T19:39:29.843601Z", "shell.execute_reply": "2022-10-27T19:39:29.842371Z" }, "papermill": { "duration": 0.107186, "end_time": "2022-10-27T19:39:29.846300", "exception": false, "start_time": "2022-10-27T19:39:29.739114", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>Q6 On which platforms have you begun or completed data science courses?</th>\n", " <th>Q7 What products or platforms did you find to be most helpful when you first started studying data science?</th>\n", " <th>Q12 What programming languages do you use on a regular basis?</th>\n", " <th>Q13 Which of the following integrated development environments (IDE's) do you use on a regular basis?</th>\n", " <th>Q14 Do you use any of the following hosted notebook products?</th>\n", " <th>Q15 Do you use any of the following data visualization libraries on a regular basis?</th>\n", " <th>Q17 Which of the following machine learning frameworks do you use on a regular basis?</th>\n", " <th>Q18 Which of the following ML algorithms do you use on a regular basis?</th>\n", " <th>Q19 Which categories of computer vision methods do you use on a regular basis?</th>\n", " <th>Q20 Which of the following natural language processing (NLP) methods do you use on a regular basis?</th>\n", " <th>Q21 Do you download pre-trained model weights from any of the following services?</th>\n", " <th>Q28 Select any activities that make up an important part of your role at work:</th>\n", " <th>Q31 Which of the following cloud computing platforms do you use?</th>\n", " <th>Q33 Do you use any of the following cloud computing products?</th>\n", " <th>Q34 Do you use any of the following data storage products?</th>\n", " <th>Q35 Do you use any of the following data products (relational databases, data warehouses, data lakes, or 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you currently reside?</th>\n", " <th>Q5 Are you currently a student? (high school, university, or graduate)</th>\n", " <th>Q8 What is the highest level of formal education that you have attained or plan to attain within the next 2 years?</th>\n", " <th>Q9 Have you ever published any academic research (papers, preprints, conference proceedings, etc)?</th>\n", " <th>Q11 For how many years have you been writing code and/or programming?</th>\n", " <th>Q16 For how many years have you used machine learning methods?</th>\n", " <th>Q22 Which of the following ML model hubs/repositories do you use most often? - Selected Choice</th>\n", " <th>Q23 Select the title most similar to your current role (or most recent title if retired): - Selected Choice</th>\n", " <th>Q24 In what industry is your current employer/contract (or your most recent employer if retired)? - Selected Choice</th>\n", " <th>Q25 What is the size of the company where you are employed?</th>\n", " <th>Q26 Approximately how many individuals are responsible for data science workloads at your place of business?</th>\n", " <th>Q27 Does your current employer incorporate machine learning methods into their business?</th>\n", " <th>Q29 What is your current yearly compensation (approximate $USD)?</th>\n", " <th>Q30 Approximately how much money have you spent on machine learning and/or cloud computing services at home or at work in the past 5 years (approximate $USD)?\\n (approximate $USD)?</th>\n", " <th>Q32 Of the cloud platforms that you are familiar with, which has the best developer experience (most enjoyable to use)? 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\\\n", "0 Other \n", "1 University Courses (resulting in a university ... \n", "\n", " Q7 What products or platforms did you find to be most helpful when you first started studying data science? \\\n", "0 \n", "1 University courses, Kaggle (notebooks, competi... \n", "\n", " Q12 What programming languages do you use on a regular basis? \\\n", "0 \n", "1 Java \n", "\n", " Q13 Which of the following integrated development environments (IDE's) do you use on a regular basis? \\\n", "0 \n", "1 Notepad++ , Other \n", "\n", " Q14 Do you use any of the following hosted notebook products? \\\n", "0 \n", "1 None \n", "\n", " Q15 Do you use any of the following data visualization libraries on a regular basis? \\\n", "0 \n", "1 Matplotlib \n", "\n", " Q17 Which of the following machine learning frameworks do you use on a regular basis? \\\n", "0 \n", "1 Scikit-learn , TensorFlow , PyTorch \n", "\n", " Q18 Which of the following ML algorithms do you use on a regular basis? \\\n", "0 \n", "1 Bayesian Approaches \n", "\n", " Q19 Which categories of computer vision methods do you use on a regular basis? \\\n", "0 \n", "1 \n", "\n", " Q20 Which of the following natural language processing (NLP) methods do you use on a regular basis? \\\n", "0 \n", "1 \n", "\n", " Q21 Do you download pre-trained model weights from any of the following services? \\\n", "0 \n", "1 No, I do not download pre-trained model weight... \n", "\n", " Q28 Select any activities that make up an important part of your role at work: \\\n", "0 \n", "1 \n", "\n", " Q31 Which of the following cloud computing platforms do you use? \\\n", "0 \n", "1 \n", "\n", " Q33 Do you use any of the following cloud computing products? \\\n", "0 \n", "1 \n", "\n", " Q34 Do you use any of the following data storage products? \\\n", "0 \n", "1 \n", "\n", " Q35 Do you use any of the following data products (relational databases, data warehouses, data lakes, or similar)? \\\n", "0 \n", "1 \n", "\n", " Q36 Do you use any of the following business intelligence tools? \\\n", "0 \n", "1 \n", "\n", " Q37 Do you use any of the following managed machine learning products on a regular basis? \\\n", "0 \n", "1 \n", "\n", " Q38 Do you use any of the following automated machine learning tools? \\\n", "0 \n", "1 \n", "\n", " Q39 Do you use any of the following products to serve your machine learning models? \\\n", "0 \n", "1 \n", "\n", " Q40 Do you use any tools to help monitor your machine learning models and/or experiments? \\\n", "0 \n", "1 \n", "\n", " Q41 Do you use any of the following responsible or ethical AI products in your machine learning practices? \\\n", "0 \n", "1 \n", "\n", " Q42 Do you use any of the following types of specialized hardware when training machine learning models? \\\n", "0 \n", "1 \n", "\n", " Q44 Who/what are your favorite media sources that report on data science topics? \\\n", "0 \n", "1 \n", "\n", " Duration (in seconds) Q2 What is your age (# years)? \\\n", "0 NaN NaN \n", "1 121 30-34 \n", "\n", " Q3 What is your gender? - Selected Choice \\\n", "0 NaN \n", "1 Man \n", "\n", " Q4 In which country do you currently reside? \\\n", "0 NaN \n", "1 India \n", "\n", " Q5 Are you currently a student? (high school, university, or graduate) \\\n", "0 NaN \n", "1 No \n", "\n", " Q8 What is the highest level of formal education that you have attained or plan to attain within the next 2 years? \\\n", "0 NaN \n", "1 NaN \n", "\n", " Q9 Have you ever published any academic research (papers, preprints, conference proceedings, etc)? \\\n", "0 NaN \n", "1 NaN \n", "\n", " Q11 For how many years have you been writing code and/or programming? \\\n", "0 NaN \n", "1 NaN \n", "\n", " Q16 For how many years have you used machine learning methods? \\\n", "0 NaN \n", "1 NaN \n", "\n", " Q22 Which of the following ML model hubs/repositories do you use most often? - Selected Choice \\\n", "0 NaN \n", "1 NaN \n", "\n", " Q23 Select the title most similar to your current role (or most recent title if retired): - Selected Choice \\\n", "0 NaN \n", "1 NaN \n", "\n", " Q24 In what industry is your current employer/contract (or your most recent employer if retired)? - Selected Choice \\\n", "0 NaN \n", "1 NaN \n", "\n", " Q25 What is the size of the company where you are employed? \\\n", "0 NaN \n", "1 NaN \n", "\n", " Q26 Approximately how many individuals are responsible for data science workloads at your place of business? \\\n", "0 NaN \n", "1 NaN \n", "\n", " Q27 Does your current employer incorporate machine learning methods into their business? \\\n", "0 NaN \n", "1 NaN \n", "\n", " Q29 What is your current yearly compensation (approximate $USD)? \\\n", "0 NaN \n", "1 NaN \n", "\n", " Q30 Approximately how much money have you spent on machine learning and/or cloud computing services at home or at work in the past 5 years (approximate $USD)?\\n (approximate $USD)? \\\n", "0 NaN \n", "1 NaN \n", "\n", " Q32 Of the cloud platforms that you are familiar with, which has the best developer experience (most enjoyable to use)? - Selected Choice \\\n", "0 NaN \n", "1 NaN \n", "\n", " Q43 Approximately how many times have you used a TPU (tensor processing unit)? \n", "0 NaN \n", "1 NaN " ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Concatenate the two dataframe\n", "unique_df = data[unique_questions]\n", "final_df = pd.concat([cleaned_df, unique_df], axis = 1)\n", "final_df.head(2)" ] }, { "cell_type": "code", "execution_count": 11, "id": "204e042e", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:39:29.888387Z", "iopub.status.busy": "2022-10-27T19:39:29.888015Z", "iopub.status.idle": "2022-10-27T19:39:29.989752Z", "shell.execute_reply": "2022-10-27T19:39:29.988483Z" }, "papermill": { "duration": 0.125717, "end_time": "2022-10-27T19:39:29.992324", "exception": false, "start_time": "2022-10-27T19:39:29.866607", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "# Replace \"\" with None\n", "final_df = final_df.replace('', 'None')" ] }, { "cell_type": "code", "execution_count": 12, "id": "113cdfea", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:39:30.033831Z", "iopub.status.busy": "2022-10-27T19:39:30.033408Z", "iopub.status.idle": "2022-10-27T19:39:30.038438Z", "shell.execute_reply": "2022-10-27T19:39:30.037295Z" }, "papermill": { "duration": 0.028573, "end_time": "2022-10-27T19:39:30.040837", "exception": false, "start_time": "2022-10-27T19:39:30.012264", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "# Store all the column names to a list\n", "columns = final_df.columns.tolist()" ] }, { "cell_type": "markdown", "id": "a2a8c89a", "metadata": { "papermill": { "duration": 0.019399, "end_time": "2022-10-27T19:39:30.080118", "exception": false, "start_time": "2022-10-27T19:39:30.060719", "status": "completed" }, "tags": [] }, "source": [ "# Exploratory Data Analysis" ] }, { "cell_type": "markdown", "id": "583b8021", "metadata": { "papermill": { "duration": 0.01935, "end_time": "2022-10-27T19:39:30.120402", "exception": false, "start_time": "2022-10-27T19:39:30.101052", "status": "completed" }, "tags": [] }, "source": [ "### Age Group Distribution (Pie Chart)" ] }, { "cell_type": "code", "execution_count": 13, "id": "11f692a6", "metadata": { "_kg_hide-input": true, "execution": { "iopub.execute_input": "2022-10-27T19:39:30.161901Z", "iopub.status.busy": "2022-10-27T19:39:30.161507Z", "iopub.status.idle": "2022-10-27T19:39:30.402810Z", "shell.execute_reply": "2022-10-27T19:39:30.401683Z" }, "papermill": { "duration": 0.26535, "end_time": "2022-10-27T19:39:30.405576", "exception": false, "start_time": "2022-10-27T19:39:30.140226", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ " <script type=\"text/javascript\">\n", " window.PlotlyConfig = {MathJaxConfig: 'local'};\n", " if (window.MathJax && window.MathJax.Hub && window.MathJax.Hub.Config) {window.MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n", " if (typeof require !== 'undefined') {\n", " require.undef(\"plotly\");\n", " requirejs.config({\n", " paths: {\n", " 'plotly': ['https://cdn.plot.ly/plotly-2.14.0.min']\n", " 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seconds into float value and plotting statistics of the Response Time\n", "final_df['Duration (in seconds)'] = final_df['Duration (in seconds)'].apply(lambda x: float(x))\n", "median = final_df['Duration (in seconds)'].median()\n", "final_df['Duration (in seconds)'] = final_df['Duration (in seconds)'].fillna(median)\n", "duration = final_df['Duration (in seconds)'].apply(lambda x: round((x / 60), 2))\n", "duration.name = 'Duration (in minutes)'\n", "stats = duration.describe().to_frame()\n", "stats = stats['Duration (in minutes)'].apply(lambda x: int(x))\n", "stats = stats.drop(['std', '25%', '75%'], axis=0)\n", "stats.index = ['Total Number of Responses', 'Mean Response Time (in minutes)',\n", " 'Fastest Response Time (in minutes)', 'Median Response Time (in minutes)',\n", " 'Longest Response Time (in minutes)']\n", "fig = px.scatter(stats, x=stats.index, y='Duration (in minutes)',\n", " text='Duration (in minutes)', size='Duration (in minutes)',\n", " title='Survey Response Time Statistics')\n", "fig.update_traces(hovertemplate='%{x} <br>%{y}')\n", "fig.update_layout(font_size=14)\n", "fig.update_xaxes(title='')\n", "fig.update_yaxes(title='')\n", "fig.show()" ] }, { "cell_type": "markdown", "id": "ff8f1e7b", "metadata": { "papermill": { "duration": 0.020784, "end_time": "2022-10-27T19:39:30.665137", "exception": false, "start_time": "2022-10-27T19:39:30.644353", "status": "completed" }, "tags": [] }, "source": [ "### Gender Distribution in Kaggle" ] }, { "cell_type": "code", "execution_count": 15, "id": "dbb1f941", "metadata": { "_kg_hide-input": true, "execution": { "iopub.execute_input": "2022-10-27T19:39:30.708701Z", "iopub.status.busy": "2022-10-27T19:39:30.707745Z", "iopub.status.idle": "2022-10-27T19:39:30.823955Z", "shell.execute_reply": "2022-10-27T19:39:30.823082Z" }, "papermill": { "duration": 0.140207, "end_time": "2022-10-27T19:39:30.825974", "exception": false, "start_time": "2022-10-27T19:39:30.685767", "status": "completed" }, "tags": [] }, 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"2726b694", "metadata": { "papermill": { "duration": 0.021361, "end_time": "2022-10-27T19:39:30.868647", "exception": false, "start_time": "2022-10-27T19:39:30.847286", "status": "completed" }, "tags": [] }, "source": [ "### Top 10 Countries of Kaggle Users" ] }, { "cell_type": "code", "execution_count": 16, "id": "5c4d3993", "metadata": { "_kg_hide-input": true, "execution": { "iopub.execute_input": "2022-10-27T19:39:30.912855Z", "iopub.status.busy": "2022-10-27T19:39:30.912413Z", "iopub.status.idle": "2022-10-27T19:39:31.031294Z", "shell.execute_reply": "2022-10-27T19:39:31.030235Z" }, "papermill": { "duration": 0.144101, "end_time": "2022-10-27T19:39:31.033883", "exception": false, "start_time": "2022-10-27T19:39:30.889782", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div> <div id=\"a04cef58-5e00-4bb8-b6ff-7690b5dcbb89\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div> <script type=\"text/javascript\"> require([\"plotly\"], 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"completed" }, "tags": [] }, "source": [ "### Are you studying?" ] }, { "cell_type": "code", "execution_count": 17, "id": "8607061a", "metadata": { "_kg_hide-input": true, "execution": { "iopub.execute_input": "2022-10-27T19:39:31.124197Z", "iopub.status.busy": "2022-10-27T19:39:31.123781Z", "iopub.status.idle": "2022-10-27T19:39:31.206010Z", "shell.execute_reply": "2022-10-27T19:39:31.205193Z" }, "papermill": { "duration": 0.108041, "end_time": "2022-10-27T19:39:31.208218", "exception": false, "start_time": "2022-10-27T19:39:31.100177", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div> <div id=\"8ee1a2bc-7c31-437e-8fe7-843fdf5205a9\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div> <script type=\"text/javascript\"> require([\"plotly\"], function(Plotly) { window.PLOTLYENV=window.PLOTLYENV \|\| {}; if (document.getElementById(\"8ee1a2bc-7c31-437e-8fe7-843fdf5205a9\")) { Plotly.newPlot( \"8ee1a2bc-7c31-437e-8fe7-843fdf5205a9\", 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"output_type": "display_data" } ], "source": [ "student = data['Q5 Are you currently a student? (high school, university, or graduate)'].value_counts()\n", "percentage = 100 data['Q5 Are you currently a student? (high school, university, or graduate)'].value_counts(normalize=True)\n", "percentage = [str(i) + ' %' for i in round(percentage, 2).values.tolist()]\n", "fig = px.bar(student, color=student.index,\n", " text=percentage,\n", " title='Are you studying?')\n", "fig.update_yaxes(visible=False)\n", "fig.update_xaxes(title='Student',visible=True)\n", "fig.update_layout(font_family='Noto Sans',\n", " font_size=16,\n", " showlegend=False)\n", "fig.update_traces(hovertemplate='%{x} <br>Count: %{y} <br>Percentage: %{text}')\n", "fig.show()" ] }, { "cell_type": "markdown", "id": "4d5c7ee9", "metadata": { "papermill": { "duration": 0.022812, "end_time": "2022-10-27T19:39:31.253705", "exception": false, "start_time": "2022-10-27T19:39:31.230893", "status": "completed" }, "tags": [] }, "source": [ "### Kaggle User Coding Experience" ] }, { "cell_type": "code", "execution_count": 18, "id": "888aebb5", "metadata": { "_kg_hide-input": true, "execution": { "iopub.execute_input": "2022-10-27T19:39:31.300692Z", "iopub.status.busy": "2022-10-27T19:39:31.300301Z", "iopub.status.idle": "2022-10-27T19:39:31.403650Z", "shell.execute_reply": "2022-10-27T19:39:31.402441Z" }, "papermill": { "duration": 0.130385, "end_time": "2022-10-27T19:39:31.406228", "exception": false, "start_time": "2022-10-27T19:39:31.275843", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div> <div id=\"f1b5dd03-44f1-4c2f-95d6-c30a9273d610\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div> <script type=\"text/javascript\"> require([\"plotly\"], function(Plotly) { window.PLOTLYENV=window.PLOTLYENV \|\| {}; if (document.getElementById(\"f1b5dd03-44f1-4c2f-95d6-c30a9273d610\")) { Plotly.newPlot( \"f1b5dd03-44f1-4c2f-95d6-c30a9273d610\", [{\"alignmentgroup\":\"True\",\"hovertemplate\":\"Experience: %{y} <br>Count: %{x} <br>Percentage: %{text}\",\"legendgroup\":\"1-3 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formal education past high school\",\"Professional doctorate\",\"I prefer not to answer\",\"Some college/university study without earning a bachelor’s degree\",\"Doctoral degree\",\"Bachelor’s degree\",\"Master’s degree\"],\"visible\":true},\"legend\":{\"title\":{\"text\":\"index\"},\"tracegroupgap\":0},\"title\":{\"text\":\"Kaggle User Qualification\"},\"barmode\":\"relative\",\"showlegend\":false}, {\"responsive\": true} ).then(function(){\n", " \n", "var gd = document.getElementById('1c15f772-14db-4523-ba62-0a3f47e23c7a');\n", "var x = new MutationObserver(function (mutations, observer) {{\n", " var display = window.getComputedStyle(gd).display;\n", " if (!display \|\| display === 'none') {{\n", " console.log([gd, 'removed!']);\n", " Plotly.purge(gd);\n", " observer.disconnect();\n", " }}\n", "}});\n", "\n", "// Listen for the removal of the full notebook cells\n", "var notebookContainer = gd.closest('#notebook-container');\n", "if (notebookContainer) {{\n", " x.observe(notebookContainer, {childList: true});\n", "}}\n", "\n", "// Listen for the clearing of the current output cell\n", "var outputEl = gd.closest('.output');\n", "if (outputEl) {{\n", " x.observe(outputEl, {childList: true});\n", "}}\n", "\n", " }) }; }); </script> </div>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "qualification = final_df['Q8 What is the highest level of formal education that you have attained or plan to attain within the next 2 years?'].value_counts()\n", "percentage = 100(final_df['Q8 What is the highest level of formal education that you have attained or plan to attain within the next 2 years?'].value_counts(normalize=True))\n", "percentage = [str(i) + ' %' for i in round(percentage, 2).values.tolist()]\n", "fig = px.bar(qualification, color=qualification.index, orientation='h', \n", " text=percentage,\n", " title='Kaggle User Qualification')\n", "fig.update_yaxes(title='Qualification', visible=True)\n", "fig.update_xaxes(visible=False)\n", "fig.update_layout(showlegend=False)\n", "fig.update_traces(hovertemplate='%{y} <br>Count: %{x} <br>Percentage: %{text}')\n", "fig.show()" ] }, { "cell_type": "markdown", "id": "1d42f1ac", "metadata": { "papermill": { "duration": 0.022538, "end_time": "2022-10-27T19:39:31.645123", "exception": false, "start_time": "2022-10-27T19:39:31.622585", "status": "completed" }, "tags": [] }, "source": [ "### Kaggle User ML Experience" ] }, { "cell_type": "code", "execution_count": 20, "id": "489839fe", "metadata": { "_kg_hide-input": true, "execution": { "iopub.execute_input": "2022-10-27T19:39:31.693351Z", "iopub.status.busy": "2022-10-27T19:39:31.692969Z", "iopub.status.idle": "2022-10-27T19:39:31.802609Z", "shell.execute_reply": "2022-10-27T19:39:31.801339Z" }, "papermill": { "duration": 0.137411, "end_time": "2022-10-27T19:39:31.805251", "exception": false, "start_time": "2022-10-27T19:39:31.667840", "status": "completed" }, "tags": [] }, "outputs": [ { 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x.observe(notebookContainer, {childList: true});\n", "}}\n", "\n", "// Listen for the clearing of the current output cell\n", "var outputEl = gd.closest('.output');\n", "if (outputEl) {{\n", " x.observe(outputEl, {childList: true});\n", "}}\n", "\n", " }) }; }); </script> </div>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "ml_exp = final_df['Q16 For how many years have you used machine learning methods?'].value_counts()\n", "percentage = 100(final_df['Q16 For how many years have you used machine learning methods?'].value_counts(normalize=True))\n", "percentage = [str(i) + ' %' for i in round(percentage, 2).values.tolist()]\n", "fig = px.bar(ml_exp, color=ml_exp.index, orientation='h', \n", " text=percentage,title='Kaggle User Machine Learning Experience')\n", "fig.update_yaxes(title='ML Experience', visible=True)\n", "fig.update_xaxes(visible=False)\n", "fig.update_layout(showlegend=False)\n", "fig.update_traces(hovertemplate='%{y} <br>Count: %{x} <br>Percentage: %{text}')\n", "fig.show()" ] }, { "cell_type": "markdown", "id": "661c17e8", "metadata": { "papermill": { "duration": 0.022622, "end_time": "2022-10-27T19:39:31.851129", "exception": false, "start_time": "2022-10-27T19:39:31.828507", "status": "completed" }, "tags": [] }, "source": [ "### Kaggle User Occupation" ] }, { "cell_type": "code", "execution_count": 21, "id": "26c53a23", "metadata": { "_kg_hide-input": true, "execution": { "iopub.execute_input": "2022-10-27T19:39:31.898931Z", "iopub.status.busy": "2022-10-27T19:39:31.898536Z", "iopub.status.idle": "2022-10-27T19:39:32.014790Z", "shell.execute_reply": "2022-10-27T19:39:32.013590Z" }, "papermill": { "duration": 0.143356, "end_time": "2022-10-27T19:39:32.017398", "exception": false, "start_time": "2022-10-27T19:39:31.874042", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div> <div id=\"e266ce84-6f4d-4573-a4b1-5da93441c95f\" class=\"plotly-graph-div\" style=\"height:900px; 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(non-software)\",\"Machine Learning/ MLops Engineer\",\"Research Scientist\",\"Other\",\"Manager (Program, Project, Operations, Executive-level, etc)\",\"Teacher / professor\",\"Software Engineer\",\"Currently not employed\",\"Data Analyst (Business, Marketing, Financial, Quantitative, etc)\",\"Data Scientist\"],\"visible\":true},\"legend\":{\"title\":{\"text\":\"index\"},\"tracegroupgap\":0},\"title\":{\"text\":\"Top 10 Occupation of Kaggle User\"},\"barmode\":\"relative\",\"height\":900,\"showlegend\":false}, {\"responsive\": true} ).then(function(){\n", " \n", "var gd = document.getElementById('e266ce84-6f4d-4573-a4b1-5da93441c95f');\n", "var x = new MutationObserver(function (mutations, observer) {{\n", " var display = window.getComputedStyle(gd).display;\n", " if (!display \|\| display === 'none') {{\n", " console.log([gd, 'removed!']);\n", " Plotly.purge(gd);\n", " observer.disconnect();\n", " }}\n", "}});\n", "\n", "// Listen for the removal of the full notebook cells\n", "var 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Kaggle User')\n", "fig.update_yaxes(title='Occupation', visible=True)\n", "fig.update_xaxes(visible=False)\n", "fig.update_traces(hovertemplate='%{y} <br>Count: %{x} <br>Percentage: %{text}')\n", "fig.update_layout(showlegend=False)\n", "fig.show()" ] }, { "cell_type": "markdown", "id": "2e99026f", "metadata": { "papermill": { "duration": 0.022979, "end_time": "2022-10-27T19:39:32.063770", "exception": false, "start_time": "2022-10-27T19:39:32.040791", "status": "completed" }, "tags": [] }, "source": [ "### Top 10 Industries Worked in by Kaggle Users" ] }, { "cell_type": "code", "execution_count": 22, "id": "fc6a14b3", "metadata": { "_kg_hide-input": true, "execution": { "iopub.execute_input": "2022-10-27T19:39:32.111295Z", "iopub.status.busy": "2022-10-27T19:39:32.110924Z", "iopub.status.idle": "2022-10-27T19:39:32.235247Z", "shell.execute_reply": "2022-10-27T19:39:32.234418Z" }, "papermill": { "duration": 0.150911, "end_time": "2022-10-27T19:39:32.237586", "exception": false, 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"fig.update_xaxes(title='Industry',visible=True, tickangle=-45)\n", "fig.update_layout(showlegend=False)\n", "fig.update_traces(hovertemplate='%{x} <br>Count: %{y} <br>Percentage: %{text}')\n", "fig.show()" ] }, { "cell_type": "markdown", "id": "053d6745", "metadata": { "execution": { "iopub.execute_input": "2022-10-25T19:44:46.067664Z", "iopub.status.busy": "2022-10-25T19:44:46.066711Z", "iopub.status.idle": "2022-10-25T19:44:46.074413Z", "shell.execute_reply": "2022-10-25T19:44:46.073035Z", "shell.execute_reply.started": "2022-10-25T19:44:46.067611Z" }, "papermill": { "duration": 0.023027, "end_time": "2022-10-27T19:39:32.284148", "exception": false, "start_time": "2022-10-27T19:39:32.261121", "status": "completed" }, "tags": [] }, "source": [ "### Kaggle Users Yearly Compensation" ] }, { "cell_type": "code", "execution_count": 23, "id": "0bee3d80", "metadata": { "_kg_hide-input": true, "execution": { "iopub.execute_input": "2022-10-27T19:39:32.332772Z", "iopub.status.busy": 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round(percentage, 2).values.tolist()]\n", "fig = px.bar(compensation, color=compensation.index,\n", " color_discrete_sequence=px.colors.sequential.Purp_r,\n", " orientation='h',\n", " text = percentage,\n", " height=900)\n", "fig.update_traces(hovertemplate='Compensation Range: %{y} <br>Count: %{x} <br>Percentage: %{text}')\n", "fig.update_layout(title='Bar Chart of Compensation Range of Kaggle Users',\n", " showlegend=False)\n", "fig.update_yaxes(title='Compensation (in $)', visible=True)\n", "fig.update_xaxes(visible=False)\n", "fig.show()" ] }, { "cell_type": "code", "execution_count": 25, "id": "5b7b51fd", "metadata": { "_kg_hide-input": true, "execution": { "iopub.execute_input": "2022-10-27T19:39:32.815701Z", "iopub.status.busy": "2022-10-27T19:39:32.815040Z", "iopub.status.idle": "2022-10-27T19:39:32.822444Z", "shell.execute_reply": "2022-10-27T19:39:32.821650Z" }, "papermill": { "duration": 0.039281, "end_time": "2022-10-27T19:39:32.825098", "exception": false, "start_time": "2022-10-27T19:39:32.785817", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "def clean_dict(d):\n", " init = 0\n", " cntr = 0\n", " name = ''\n", " new_name = ''\n", " new_dict = {}\n", " for key, val in d.items():\n", " if (init == val) and (cntr != 1):\n", " cntr = 1\n", " new_name = name + \", \" + key\n", " new_dict[new_name] = new_dict.pop(name)\n", " elif (cntr == 1) and (val == init):\n", " temp = new_name + \", \" + key\n", " new_dict[temp] = new_dict[new_name]\n", " del new_dict[new_name]\n", " new_name = temp\n", " elif (cntr == 1) and (val != init):\n", " cntr = 0\n", " new_dict[new_name] = init\n", " else:\n", " name = key\n", " init = val\n", " new_dict[name] = val\n", "\n", " return new_dict" ] }, { "cell_type": "code", "execution_count": 26, "id": "bebbcac4", "metadata": { "_kg_hide-input": true, "execution": { "iopub.execute_input": "2022-10-27T19:39:32.883649Z", "iopub.status.busy": "2022-10-27T19:39:32.883182Z", "iopub.status.idle": "2022-10-27T19:39:32.889294Z", "shell.execute_reply": "2022-10-27T19:39:32.888526Z" }, "papermill": { "duration": 0.037041, "end_time": "2022-10-27T19:39:32.891324", "exception": false, "start_time": "2022-10-27T19:39:32.854283", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "def get_unique_vals(final_df, col=''):\n", " vals = final_df[col].values.tolist()\n", " val_dict = {}\n", " for element in vals:\n", " try:\n", " keys = element.split(', ') \n", " except:\n", " pass\n", " for key in keys:\n", " key = key.strip()\n", " if key in val_dict:\n", " val_dict[key] += 1\n", " else:\n", " val_dict[key] = 1\n", "\n", " return val_dict" ] }, { "cell_type": "markdown", "id": "223f3535", "metadata": { "papermill": { "duration": 0.02686, "end_time": "2022-10-27T19:39:32.945159", "exception": false, "start_time": "2022-10-27T19:39:32.918299", "status": "completed" }, "tags": [] }, "source": [ "### Top 5 Programming languages used by Kaggle Users" ] }, { "cell_type": "code", "execution_count": 27, "id": "307a014f", "metadata": { "_kg_hide-input": true, "execution": { "iopub.execute_input": "2022-10-27T19:39:33.000742Z", "iopub.status.busy": "2022-10-27T19:39:33.000049Z", "iopub.status.idle": "2022-10-27T19:39:33.082895Z", "shell.execute_reply": "2022-10-27T19:39:33.082104Z" }, "papermill": { "duration": 0.113513, "end_time": "2022-10-27T19:39:33.085274", "exception": false, "start_time": "2022-10-27T19:39:32.971761", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div> <div id=\"e0d44bd7-8e98-4f2e-96b0-90b627a4be3d\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div> <script type=\"text/javascript\"> require([\"plotly\"], function(Plotly) { window.PLOTLYENV=window.PLOTLYENV \|\| {}; if (document.getElementById(\"e0d44bd7-8e98-4f2e-96b0-90b627a4be3d\")) { Plotly.newPlot( \"e0d44bd7-8e98-4f2e-96b0-90b627a4be3d\", 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color='ML Framework')\n", "fig.update_layout(showlegend=False)\n", "fig.update_traces(hovertemplate='<br>Count: %{y} <br>Percentage: %{text}')\n", "fig.show()" ] }, { "cell_type": "markdown", "id": "a067003d", "metadata": { "papermill": { "duration": 0.027038, "end_time": "2022-10-27T19:39:33.578798", "exception": false, "start_time": "2022-10-27T19:39:33.551760", "status": "completed" }, "tags": [] }, "source": [ "### Top 10 ML Algorithms used by Kaggle Users" ] }, { "cell_type": "code", "execution_count": 30, "id": "0f3ba339", "metadata": { "_kg_hide-input": true, "execution": { "iopub.execute_input": "2022-10-27T19:39:33.636003Z", "iopub.status.busy": "2022-10-27T19:39:33.635417Z", "iopub.status.idle": "2022-10-27T19:39:33.777703Z", "shell.execute_reply": "2022-10-27T19:39:33.776435Z" }, "papermill": { "duration": 0.17392, "end_time": "2022-10-27T19:39:33.780300", "exception": false, "start_time": "2022-10-27T19:39:33.606380", "status": "completed" }, "tags": [] }, "outputs": [ { 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"source": [ "bi_tools = clean_dict(get_unique_vals(final_df,'Q36 Do you use any of the following business intelligence tools?'))\n", "bi_tools = pd.DataFrame(list(bi_tools.items()),\n", " columns=['BI Tool', 'Count'])\n", "bi_tools = bi_tools.set_index('BI Tool')\n", "bi_tools = bi_tools.drop(['None', 'nan'], axis=0)\n", "bi_tools = bi_tools.reset_index()\n", "bi_tools = bi_tools.sort_values(by='Count', ascending=False)[:5]\n", "fig = px.pie(bi_tools, values='Count', names='BI Tool',\n", " color='BI Tool',\n", " hole=0.5,\n", " title='Top 5 BI Tools preferred by Kaggle Users')\n", "fig.update_traces(textposition='outside', textinfo='percent+label',\n", " hovertemplate='%{customdata[0]}<br>Count:%{value}')\n", "\n", "fig.update_layout(showlegend=False, font_size=14)\n", "fig.show()" ] }, { "cell_type": "markdown", "id": "677b6b48", "metadata": { "papermill": { "duration": 0.028806, "end_time": "2022-10-27T19:39:34.024493", "exception": false, "start_time": "2022-10-27T19:39:33.995687", "status": "completed" }, "tags": [] }, "source": [ "### Top 10 Relational Databases used by Kaggle Users" ] }, { "cell_type": "code", "execution_count": 32, "id": "39ddf802", "metadata": { "_kg_hide-input": true, "execution": { "iopub.execute_input": "2022-10-27T19:39:34.084277Z", "iopub.status.busy": "2022-10-27T19:39:34.083888Z", "iopub.status.idle": "2022-10-27T19:39:34.155561Z", "shell.execute_reply": "2022-10-27T19:39:34.154497Z" }, "papermill": { "duration": 0.104295, "end_time": "2022-10-27T19:39:34.158162", "exception": false, "start_time": "2022-10-27T19:39:34.053867", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div> <div id=\"fbab1868-c6ec-44ab-a527-cff5193ae1f2\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div> <script type=\"text/javascript\"> require([\"plotly\"], function(Plotly) { window.PLOTLYENV=window.PLOTLYENV \|\| {}; if (document.getElementById(\"fbab1868-c6ec-44ab-a527-cff5193ae1f2\")) { Plotly.newPlot( 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y='Count',\n", " color='Learning Platforms', \n", " height=900,\n", " text=percentage,\n", " title='Top 5 Learning Platforms preffered by Kaggle Users')\n", "fig.update_yaxes(visible=True)\n", "fig.update_xaxes(title='',visible=True)\n", "fig.update_traces(hovertemplate='%{x} <br>Count: %{y} <br>Percentage: %{text}')\n", "fig.update_layout(showlegend=False, font_size=14)\n", "fig.show()" ] }, { "cell_type": "markdown", "id": "82131390", "metadata": { "papermill": { "duration": 0.028324, "end_time": "2022-10-27T19:39:34.470141", "exception": false, "start_time": "2022-10-27T19:39:34.441817", "status": "completed" }, "tags": [] }, "source": [ "### Work in Progress" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": 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}, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "Sheet.shape" ] }, { "cell_type": "code", "execution_count": 11, "id": "1d453bd4", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:53:31.908487Z", "iopub.status.busy": "2022-10-27T19:53:31.907954Z", "iopub.status.idle": "2022-10-27T19:53:31.914337Z", "shell.execute_reply": "2022-10-27T19:53:31.913127Z" }, "papermill": { "duration": 0.021424, "end_time": "2022-10-27T19:53:31.917024", "exception": false, "start_time": "2022-10-27T19:53:31.895600", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "X = Sheet.iloc[:,2]\n", "\n", "Y = Sheet.iloc[:,1] " ] }, { "cell_type": "code", "execution_count": 12, "id": "80dc7c27", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:53:31.941309Z", "iopub.status.busy": "2022-10-27T19:53:31.940797Z", "iopub.status.idle": "2022-10-27T19:53:31.950990Z", "shell.execute_reply": "2022-10-27T19:53:31.949709Z" }, "papermill": { "duration": 0.025757, "end_time": "2022-10-27T19:53:31.953423", "exception": false, "start_time": "2022-10-27T19:53:31.927666", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "0 I try and avoid this sort of conflict\n", "1 Had a friend open up to me about his mental ad...\n", "2 I saved a girl from suicide once. She was goin...\n", "3 i cant think of one really...i think i may hav...\n", "4 Only really one friend who doesn't fit into th...\n", " ... \n", "75 Now that I've been through it, although i'm no...\n", "76 when my best friends mom past away from od'ing...\n", "77 As a camp counselor I provide stability in kid...\n", "78 My now girlfriend used to have serious addicti...\n", "79 The one person I ever talked to it was because...\n", "Name: response_text, Length: 80, dtype: object" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "X" ] }, { "cell_type": "code", "execution_count": 13, "id": "5214c263", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:53:31.977406Z", "iopub.status.busy": "2022-10-27T19:53:31.976912Z", "iopub.status.idle": "2022-10-27T19:53:31.983265Z", "shell.execute_reply": "2022-10-27T19:53:31.981942Z" }, "papermill": { "duration": 0.021282, "end_time": "2022-10-27T19:53:31.985559", "exception": false, "start_time": "2022-10-27T19:53:31.964277", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "X1 = Sheet1.iloc[:,2]\n", "\n", "Y1 = Sheet1.iloc[:,1] " ] }, { "cell_type": "code", "execution_count": 14, "id": "1699304b", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:53:32.010789Z", "iopub.status.busy": "2022-10-27T19:53:32.009922Z", "iopub.status.idle": "2022-10-27T19:53:37.916672Z", "shell.execute_reply": "2022-10-27T19:53:37.915306Z" }, "papermill": { "duration": 5.922568, "end_time": "2022-10-27T19:53:37.919697", "exception": false, "start_time": "2022-10-27T19:53:31.997129", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "import tensorflow as tf" ] }, { "cell_type": "code", "execution_count": 15, "id": "3e64cac0", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:53:37.944743Z", "iopub.status.busy": "2022-10-27T19:53:37.943433Z", "iopub.status.idle": "2022-10-27T19:53:39.158495Z", "shell.execute_reply": "2022-10-27T19:53:39.157065Z" }, "papermill": { "duration": 1.231023, "end_time": "2022-10-27T19:53:39.161665", "exception": false, "start_time": "2022-10-27T19:53:37.930642", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "from tensorflow.keras.preprocessing.text import Tokenizer" ] }, { "cell_type": "code", "execution_count": 16, "id": "786c71ac", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:53:39.186256Z", "iopub.status.busy": "2022-10-27T19:53:39.185408Z", "iopub.status.idle": "2022-10-27T19:53:39.190137Z", "shell.execute_reply": "2022-10-27T19:53:39.189300Z" }, "papermill": { "duration": 0.019772, "end_time": "2022-10-27T19:53:39.192514", "exception": false, "start_time": "2022-10-27T19:53:39.172742", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "vocab_size = 10000\n", "embedding_dim = 16\n", "max_length = 100" ] }, { "cell_type": "code", "execution_count": 17, "id": "2718da0e", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:53:39.216338Z", "iopub.status.busy": "2022-10-27T19:53:39.215790Z", "iopub.status.idle": "2022-10-27T19:53:39.221101Z", "shell.execute_reply": "2022-10-27T19:53:39.219923Z" }, "papermill": { "duration": 0.020259, "end_time": "2022-10-27T19:53:39.223639", "exception": false, "start_time": "2022-10-27T19:53:39.203380", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "nlp = Tokenizer(num_words=vocab_size,oov_token='<OOV>')" ] }, { "cell_type": "code", "execution_count": 18, "id": "b2030981", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:53:39.247376Z", "iopub.status.busy": "2022-10-27T19:53:39.246400Z", "iopub.status.idle": "2022-10-27T19:53:39.257418Z", "shell.execute_reply": "2022-10-27T19:53:39.256243Z" }, "papermill": { "duration": 0.025653, "end_time": "2022-10-27T19:53:39.259915", "exception": false, "start_time": "2022-10-27T19:53:39.234262", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "nlp.fit_on_texts(X)" ] }, { "cell_type": "code", "execution_count": 19, "id": "75007f14", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:53:39.283546Z", "iopub.status.busy": "2022-10-27T19:53:39.282626Z", "iopub.status.idle": "2022-10-27T19:53:39.309820Z", "shell.execute_reply": "2022-10-27T19:53:39.308593Z" }, "papermill": { "duration": 0.042149, "end_time": "2022-10-27T19:53:39.312570", "exception": false, "start_time": "2022-10-27T19:53:39.270421", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "{1: '<OOV>',\n", " 2: 'to',\n", " 3: 'i',\n", " 4: 'and',\n", " 5: 'a',\n", " 6: 'the',\n", " 7: 'of',\n", " 8: 'her',\n", " 9: 'my',\n", " 10: 'was',\n", " 11: 'it',\n", " 12: 'with',\n", " 13: 'for',\n", " 14: 'him',\n", " 15: 'me',\n", " 16: 'as',\n", " 17: 'she',\n", " 18: 'in',\n", " 19: 'friends',\n", " 20: 'friend',\n", " 21: 'that',\n", " 22: 'have',\n", " 23: 'when',\n", " 24: 'through',\n", " 25: 'people',\n", " 26: 'he',\n", " 27: 'but',\n", " 28: 'about',\n", " 29: 'be',\n", " 30: 'helped',\n", " 31: 'them',\n", " 32: 'had',\n", " 33: 'up',\n", " 34: 'they',\n", " 35: 'some',\n", " 36: 'help',\n", " 37: 'talk',\n", " 38: 'there',\n", " 39: 'so',\n", " 40: 'going',\n", " 41: 'on',\n", " 42: 'out',\n", " 43: 'who',\n", " 44: 'just',\n", " 45: 'try',\n", " 46: 'one',\n", " 47: 'would',\n", " 48: 'their',\n", " 49: 'been',\n", " 50: 'his',\n", " 51: 'life',\n", " 52: 'from',\n", " 53: 'talked',\n", " 54: 'school',\n", " 55: 'get',\n", " 56: 'always',\n", " 57: 'being',\n", " 58: 'at',\n", " 59: 'think',\n", " 60: 'is',\n", " 61: 'if',\n", " 62: 'or',\n", " 63: 'not',\n", " 64: 'too',\n", " 65: 'depression',\n", " 66: 'problems',\n", " 67: 'someone',\n", " 68: 'issues',\n", " 69: 'can',\n", " 70: 'what',\n", " 71: 'best',\n", " 72: 'this',\n", " 73: 'how',\n", " 74: 'girl',\n", " 75: 'much',\n", " 76: 'because',\n", " 77: 'shit',\n", " 78: \"i've\",\n", " 79: 'you',\n", " 80: 'more',\n", " 81: 'listen',\n", " 82: 'same',\n", " 83: 'know',\n", " 84: 'go',\n", " 85: 'come',\n", " 86: 'lot',\n", " 87: \"i'm\",\n", " 88: 'open',\n", " 89: 'addiction',\n", " 90: 'over',\n", " 91: 'way',\n", " 92: 'really',\n", " 93: 'any',\n", " 94: 'by',\n", " 95: 'before',\n", " 96: 'years',\n", " 97: 'while',\n", " 98: 'advice',\n", " 99: 'went',\n", " 100: 'feel',\n", " 101: 'got',\n", " 102: 'better',\n", " 103: 'are',\n", " 104: 'down',\n", " 105: 'anxiety',\n", " 106: 'stuff',\n", " 107: 'well',\n", " 108: 'other',\n", " 109: 'all',\n", " 110: 'even',\n", " 111: 'back',\n", " 112: 'many',\n", " 113: 'time',\n", " 114: 'now',\n", " 115: 'did',\n", " 116: 'could',\n", " 117: 'personal',\n", " 118: 'experience',\n", " 119: 'will',\n", " 120: 'himself',\n", " 121: 'simply',\n", " 122: 'were',\n", " 123: 'never',\n", " 124: 'own',\n", " 125: 'make',\n", " 126: 'dealing',\n", " 127: 'after',\n", " 128: 'having',\n", " 129: 'myself',\n", " 130: 'sometimes',\n", " 131: 'helpful',\n", " 132: 'tried',\n", " 133: 'an',\n", " 134: 'used',\n", " 135: \"that's\",\n", " 136: \"don't\",\n", " 137: 'want',\n", " 138: 'like',\n", " 139: 'need',\n", " 140: 'though',\n", " 141: 'talking',\n", " 142: 'suicide',\n", " 143: 'may',\n", " 144: 'into',\n", " 145: 'pretty',\n", " 146: \"it's\",\n", " 147: \"didn't\",\n", " 148: 'self',\n", " 149: 'gf',\n", " 150: 'anything',\n", " 151: 'severe',\n", " 152: 'both',\n", " 153: 'listened',\n", " 154: 'troubles',\n", " 155: 'week',\n", " 156: 'off',\n", " 157: 'others',\n", " 158: 'give',\n", " 159: 'support',\n", " 160: 'alone',\n", " 161: 'girlfriend',\n", " 162: 'similar',\n", " 163: 'letting',\n", " 164: 'listening',\n", " 165: 'few',\n", " 166: 'has',\n", " 167: 'themselves',\n", " 168: 'dont',\n", " 169: 'see',\n", " 170: 'last',\n", " 171: 'year',\n", " 172: 'helping',\n", " 173: 'grade',\n", " 174: 'am',\n", " 175: 'often',\n", " 176: \"they're\",\n", " 177: 'told',\n", " 178: 'let',\n", " 179: 'everything',\n", " 180: 'times',\n", " 181: 'look',\n", " 182: 'lives',\n", " 183: 'feeling',\n", " 184: 'person',\n", " 185: 'situation',\n", " 186: \"i'll\",\n", " 187: 'little',\n", " 188: 'happens',\n", " 189: 'tough',\n", " 190: 'needed',\n", " 191: 'find',\n", " 192: 'we',\n", " 193: 'mental',\n", " 194: 'making',\n", " 195: 'depressed',\n", " 196: 'once',\n", " 197: 'very',\n", " 198: 'calm',\n", " 199: 'cant',\n", " 200: 'only',\n", " 201: \"doesn't\",\n", " 202: 'calls',\n", " 203: 'something',\n", " 204: 'boyfriend',\n", " 205: 'ask',\n", " 206: 'call',\n", " 207: 'ok',\n", " 208: 'say',\n", " 209: 'please',\n", " 210: 'said',\n", " 211: 'couple',\n", " 212: 'low',\n", " 213: 'esteem',\n", " 214: 'than',\n", " 215: 'emotional',\n", " 216: 'started',\n", " 217: 'our',\n", " 218: 'relationship',\n", " 219: 'sister',\n", " 220: 'night',\n", " 221: 'then',\n", " 222: 'parents',\n", " 223: 'found',\n", " 224: 'part',\n", " 225: 'bring',\n", " 226: 'work',\n", " 227: 'big',\n", " 228: 'problem',\n", " 229: 'away',\n", " 230: 'every',\n", " 231: 'day',\n", " 232: 'around',\n", " 233: \"he's\",\n", " 234: 'needs',\n", " 235: 'mom',\n", " 236: 'ex',\n", " 237: 'faced',\n", " 238: 'gone',\n", " 239: 'understand',\n", " 240: 'struggles',\n", " 241: 'internet',\n", " 242: 'important',\n", " 243: 'offer',\n", " 244: 'good',\n", " 245: 'honest',\n", " 246: 'guess',\n", " 247: 'diagnosed',\n", " 248: 'summer',\n", " 249: 'alcoholic',\n", " 250: 'high',\n", " 251: 'almost',\n", " 252: 'camp',\n", " 253: 'kids',\n", " 254: 'kid',\n", " 255: 'wanted',\n", " 256: 'care',\n", " 257: 'head',\n", " 258: \"you're\",\n", " 259: 'ended',\n", " 260: 'together',\n", " 261: 'months',\n", " 262: '5',\n", " 263: 'came',\n", " 264: 'serious',\n", " 265: 'resource',\n", " 266: 'else',\n", " 267: 'hard',\n", " 268: 'girls',\n", " 269: 'side',\n", " 270: 'bad',\n", " 271: 'kill',\n", " 272: 'hospital',\n", " 273: 'also',\n", " 274: 'called',\n", " 275: 'knew',\n", " 276: 'hold',\n", " 277: 'still',\n", " 278: 'bit',\n", " 279: 'basically',\n", " 280: 'keep',\n", " 281: 'struggling',\n", " 282: 'its',\n", " 283: 'irl',\n", " 284: 'dealt',\n", " 285: 'desire',\n", " 286: 'perfect',\n", " 287: 'describes',\n", " 288: 'caring',\n", " 289: 'either',\n", " 290: \"wouldn't\",\n", " 291: 'blunt',\n", " 292: \"they've\",\n", " 293: 'killed',\n", " 294: 'comfort',\n", " 295: 'past',\n", " 296: \"i'd\",\n", " 297: \"haven't\",\n", " 298: 'situations',\n", " 299: 'felt',\n", " 300: 'avoid',\n", " 301: 'sort',\n", " 302: 'conflict',\n", " 303: 'weed',\n", " 304: 'taking',\n", " 305: 'saved',\n", " 306: 'swallow',\n", " 307: 'bunch',\n", " 308: 'pills',\n", " 309: 'loving',\n", " 310: 'indirectly',\n", " 311: 'fit',\n", " 312: 'above',\n", " 313: 'categories',\n", " 314: 'therapist',\n", " 315: 'spiraling',\n", " 316: 'anyway',\n", " 317: 'frustrated',\n", " 318: 'logical',\n", " 319: 'fight',\n", " 320: 'crazy',\n", " 321: 'asks',\n", " 322: 'hand',\n", " 323: 'remote',\n", " 324: 'ago',\n", " 325: 'switch',\n", " 326: 'overcome',\n", " 327: 'roommate',\n", " 328: 'death',\n", " 329: 'loss',\n", " 330: 'bedroom',\n", " 331: 'quite',\n", " 332: 'eventually',\n", " 333: 'relationships',\n", " 334: 'suffer',\n", " 335: 'result',\n", " 336: 'offered',\n", " 337: 'comforted',\n", " 338: 'lost',\n", " 339: 'virgity',\n", " 340: 'walked',\n", " 341: 'cutting',\n", " 342: 'threw',\n", " 343: 'house',\n", " 344: 'supportive',\n", " 345: 'focus',\n", " 346: 'took',\n", " 347: 'packed',\n", " 348: 'car',\n", " 349: 'picked',\n", " 350: 'verge',\n", " 351: 'losing',\n", " 352: 'camping',\n", " 353: 'surfing',\n", " 354: 'physical',\n", " 355: 'activity',\n", " 356: 'memorial',\n", " 357: 'anniversary',\n", " 358: 'father',\n", " 359: 'remind',\n", " 360: 'anxious',\n", " 361: 'cutter',\n", " 362: 'suicidal',\n", " 363: 'slowly',\n", " 364: 'dying',\n", " 365: 'inside',\n", " 366: 'advise',\n", " 367: 'circumstances',\n", " 368: 'mine',\n", " 369: 'tryin',\n", " 370: 'expressing',\n", " 371: 'concern',\n", " 372: 'openness',\n", " 373: 'fell',\n", " 374: 'dialog',\n", " 375: \"girlfriend's\",\n", " 376: 'thinking',\n", " 377: 'days',\n", " 378: 'managed',\n", " 379: 'methods',\n", " 380: 'cope',\n", " 381: 'hits',\n", " 382: 'knowledge',\n", " 383: 'allowed',\n", " 384: 'several',\n", " 385: 'experiences',\n", " 386: 'face',\n", " 387: 'adequate',\n", " 388: 'normal',\n", " 389: 'kind',\n", " 390: 'guy',\n", " 391: 'disorder',\n", " 392: 'commit',\n", " 393: 'entire',\n", " 394: 'throughout',\n", " 395: 'recovery',\n", " 396: 'cleaning',\n", " 397: \"friend's\",\n", " 398: 'campsite',\n", " 399: 'slightly',\n", " 400: 'living',\n", " 401: 'mt',\n", " 402: 'hood',\n", " 403: 'woods',\n", " 404: 'damn',\n", " 405: 'apposed',\n", " 406: 'telling',\n", " 407: 'story',\n", " 408: 'mother',\n", " 409: 'tutor',\n", " 410: 'homeless',\n", " 411: 'men',\n", " 412: 'shelter',\n", " 413: 'obtain',\n", " 414: \"ged's\",\n", " 415: 'age',\n", " 416: '50',\n", " 417: 'reading',\n", " 418: 'first',\n", " 419: 'level',\n", " 420: 'teacher',\n", " 421: 'everyday',\n", " 422: 'facing',\n", " 423: 'countless',\n", " 424: 'issue',\n", " 425: 'tell',\n", " 426: 'restless',\n", " 427: 'haha',\n", " 428: 'eight',\n", " 429: 'rejected',\n", " 430: 'twice',\n", " 431: 'sign',\n", " 432: 'yearbook',\n", " 433: 'nervous',\n", " 434: 'rejecting',\n", " 435: 'thinks',\n", " 436: 'no',\n", " 437: 'less',\n", " 438: 'probably',\n", " 439: 'comes',\n", " 440: 'top',\n", " 441: 'specific',\n", " 442: 'example',\n", " 443: 'type',\n", " 444: 'struggle',\n", " 445: 'yourself',\n", " 446: 'truth',\n", " 447: 'hurts',\n", " 448: 'start',\n", " 449: 'completely',\n", " 450: 'isolated',\n", " 451: 'skipped',\n", " 452: 'convinced',\n", " 453: 'doc',\n", " 454: 'promised',\n", " 455: 'rehab',\n", " 456: 'clean',\n", " 457: 'complete',\n", " 458: 'lack',\n", " 459: 'family',\n", " 460: 'changed',\n", " 461: 'late',\n", " 462: \"he'll\",\n", " 463: 'listener',\n", " 464: 'heard',\n", " 465: 'necessarily',\n", " 466: 'fixed',\n", " 467: 'express',\n", " 468: 'relief',\n", " 469: 'thoughts',\n", " 470: 'trapped',\n", " 471: 'within',\n", " 472: 'confines',\n", " 473: 'lent',\n", " 474: 'ear',\n", " 475: 'speak',\n", " 476: 'cancer',\n", " 477: 'during',\n", " 478: 'visited',\n", " 479: 'treatment',\n", " 480: 'caught',\n", " 481: 'qualified',\n", " 482: 'drugs',\n", " 483: 'cocaine',\n", " 484: 'dumps',\n", " 485: 'positive',\n", " 486: 'reflect',\n", " 487: \"friends'\",\n", " 488: 'theripist',\n", " 489: 'describe',\n", " 490: 'nah',\n", " 491: 'brother',\n", " 492: 'able',\n", " 493: 'set',\n", " 494: 'path',\n", " 495: 'healing',\n", " 496: 'dumped',\n", " 497: '2',\n", " 498: 'stayed',\n", " 499: 'until',\n", " 500: 'stopped',\n", " 501: 'super',\n", " 502: 'drove',\n", " 503: '1n',\n", " 504: 'hour',\n", " 505: 'half',\n", " 506: 'cops',\n", " 507: 'already',\n", " 508: 'taken',\n", " 509: 'hung',\n", " 510: 'another',\n", " 511: 'hadnt',\n", " 512: 'cause',\n", " 513: 'blue',\n", " 514: 'thankgiving',\n", " 515: 'number',\n", " 516: 'huge',\n", " 517: 'douche',\n", " 518: 'psych',\n", " 519: 'ward',\n", " 520: 'trying',\n", " 521: 'whenever',\n", " 522: 'answer',\n", " 523: 'earlier',\n", " 524: 'mind',\n", " 525: 'might',\n", " 526: 'goal',\n", " 527: 'purpose',\n", " 528: 'sustained',\n", " 529: 'survival',\n", " 530: 'peoples',\n", " 531: 'laugh',\n", " 532: 'sad',\n", " 533: 'nobody',\n", " 534: 'treat',\n", " 535: 'humans',\n", " 536: 'strangers',\n", " 537: 'respect',\n", " 538: 'kindness',\n", " 539: 'sometime',\n", " 540: 'swimming',\n", " 541: 'enough',\n", " 542: 'light',\n", " 543: 'end',\n", " 544: 'tunnel',\n", " 545: 'switched',\n", " 546: 'idk',\n", " 547: 'long',\n", " 548: 'here',\n", " 549: 'till',\n", " 550: 'flickers',\n", " 551: 'acted',\n", " 552: 'schoolwork',\n", " 553: 'period',\n", " 554: 'intense',\n", " 555: 'made',\n", " 556: 'sure',\n", " 557: 'major',\n", " 558: 'blows',\n", " 559: 'girlfriends',\n", " 560: 'break',\n", " 561: 'write',\n", " 562: 'related',\n", " 563: 'nice',\n", " 564: 'rant',\n", " 565: 'objective',\n", " 566: 'guys',\n", " 567: 'innermost',\n", " 568: 'feelings',\n", " 569: 'thats',\n", " 570: 'least',\n", " 571: 'jokingly',\n", " 572: 'refers',\n", " 573: 'agony',\n", " 574: 'aunt',\n", " 575: 'possibly',\n", " 576: 'change',\n", " 577: 'subject',\n", " 578: 'drag',\n", " 579: 'due',\n", " 580: 'fact',\n", " 581: 'reality',\n", " 582: 'unless',\n", " 583: 'pulled',\n", " 584: 'giving',\n", " 585: 'hear',\n", " 586: 'such',\n", " 587: 'oh',\n", " 588: \"you'll\",\n", " 589: 'blow',\n", " 590: 'along',\n", " 591: 'lines',\n", " 592: 'rude',\n", " 593: 'essential',\n", " 594: 'progress',\n", " 595: 'y',\n", " 596: 'somebody',\n", " 597: \"who's\",\n", " 598: 'saying',\n", " 599: 'acquaintances',\n", " 600: 'known',\n", " 601: 'junior',\n", " 602: 'hoping',\n", " 603: 'answers',\n", " 604: 'peace',\n", " 605: 'turmoil',\n", " 606: 'calling',\n", " 607: 'sense',\n", " 608: 'maybe',\n", " 609: 'facebook',\n", " 610: 'chat',\n", " 611: 'harmed',\n", " 612: 'shared',\n", " 613: 'hopes',\n", " 614: 'swaying',\n", " 615: 'those',\n", " 616: 'actions',\n", " 617: 'worked',\n", " 618: 'admit',\n", " 619: 'brought',\n", " 620: 'initiated',\n", " 621: 'health',\n", " 622: 'encourage',\n", " 623: 'therapy',\n", " 624: 'met',\n", " 625: 'anyone',\n", " 626: 'attention',\n", " 627: 'chance',\n", " 628: 'unfortunately',\n", " 629: 'remember',\n", " 630: 'specifically',\n", " 631: 'rational',\n", " 632: 'possible',\n", " 633: 'fairly',\n", " 634: 'common',\n", " 635: 'occurrence',\n", " 636: 'gave',\n", " 637: 'input',\n", " 638: 'absolutely',\n", " 639: 'horrable',\n", " 640: 'judge',\n", " 641: 'most',\n", " 642: 'naturally',\n", " 643: 'grandmother',\n", " 644: 'shortly',\n", " 645: 'difficulties',\n", " 646: 'using',\n", " 647: 'relate',\n", " 648: 'share',\n", " 649: 'although',\n", " 650: 'where',\n", " 651: 'extremely',\n", " 652: 'sharing',\n", " 653: 'questions',\n", " 654: 'hesitate',\n", " 655: 'email',\n", " 656: 'book',\n", " 657: 'excited',\n", " 658: \"od'ing\",\n", " 659: 'counselor',\n", " 660: 'provide',\n", " 661: 'stability',\n", " 662: 'troubled',\n", " 663: 'home',\n", " 664: 'dating',\n", " 665: 'defined',\n", " 666: 'thought',\n", " 667: 'saw',\n", " 668: 'looked',\n", " 669: 'spent',\n", " 670: 'nights',\n", " 671: 'vent',\n", " 672: 'supporting',\n", " 673: 'spot',\n", " 674: 'ever',\n", " 675: 'thing',\n", " 676: 'us',\n", " 677: 'realize',\n", " 678: \"aren't\"}" ] }, "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ "nlp.index_word" ] }, { "cell_type": "code", "execution_count": 20, "id": "3405e57b", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:53:39.337046Z", "iopub.status.busy": "2022-10-27T19:53:39.336515Z", "iopub.status.idle": "2022-10-27T19:53:39.344628Z", "shell.execute_reply": "2022-10-27T19:53:39.343426Z" }, "papermill": { "duration": 0.023059, "end_time": "2022-10-27T19:53:39.347021", "exception": false, "start_time": "2022-10-27T19:53:39.323962", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "arr = nlp.texts_to_sequences(X)\n" ] }, { "cell_type": "code", "execution_count": 21, "id": "be7033b7", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:53:39.371740Z", "iopub.status.busy": "2022-10-27T19:53:39.370785Z", "iopub.status.idle": "2022-10-27T19:53:39.377235Z", "shell.execute_reply": "2022-10-27T19:53:39.376042Z" }, "papermill": { "duration": 0.021539, "end_time": "2022-10-27T19:53:39.379661", "exception": false, "start_time": "2022-10-27T19:53:39.358122", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "from tensorflow.keras.preprocessing.sequence import pad_sequences" ] }, { "cell_type": "code", "execution_count": 22, "id": "6689c0ad", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:53:39.404955Z", "iopub.status.busy": "2022-10-27T19:53:39.404327Z", "iopub.status.idle": "2022-10-27T19:53:39.414409Z", "shell.execute_reply": "2022-10-27T19:53:39.412672Z" }, "papermill": { "duration": 0.025536, "end_time": "2022-10-27T19:53:39.416631", "exception": false, "start_time": "2022-10-27T19:53:39.391095", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "100" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "X = pad_sequences(arr, maxlen=max_length)\n", "len(X[0])" ] }, { "cell_type": "code", "execution_count": 23, "id": "2cf39138", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:53:39.441623Z", "iopub.status.busy": "2022-10-27T19:53:39.441082Z", "iopub.status.idle": "2022-10-27T19:53:40.424893Z", "shell.execute_reply": "2022-10-27T19:53:40.423398Z" }, "papermill": { "duration": 1.000049, "end_time": "2022-10-27T19:53:40.428138", "exception": false, "start_time": "2022-10-27T19:53:39.428089", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "from sklearn.preprocessing import LabelEncoder" ] }, { "cell_type": "code", "execution_count": 24, "id": "4f09b212", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:53:40.454579Z", "iopub.status.busy": "2022-10-27T19:53:40.454030Z", "iopub.status.idle": "2022-10-27T19:53:40.459464Z", "shell.execute_reply": "2022-10-27T19:53:40.458459Z" }, "papermill": { "duration": 0.021147, "end_time": "2022-10-27T19:53:40.461637", "exception": false, "start_time": "2022-10-27T19:53:40.440490", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "l = LabelEncoder()" ] }, { "cell_type": "code", "execution_count": 25, "id": "8911cd22", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:53:40.486710Z", "iopub.status.busy": "2022-10-27T19:53:40.486181Z", "iopub.status.idle": "2022-10-27T19:53:40.495109Z", "shell.execute_reply": "2022-10-27T19:53:40.493900Z" }, "papermill": { "duration": 0.024306, "end_time": "2022-10-27T19:53:40.497408", "exception": false, "start_time": "2022-10-27T19:53:40.473102", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "array([1, 0, 0, 1, 1, 1, 0, 0, 1, 0, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0,\n", " 0, 1, 1, 0, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 0, 1, 1, 1,\n", " 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 0, 1, 0, 1, 0, 1, 1, 0, 1,\n", " 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 0, 1, 0, 1])" ] }, "execution_count": 25, "metadata": {}, "output_type": "execute_result" } ], "source": [ "Y = l.fit_transform(Y)\n", "Y" ] }, { "cell_type": "code", "execution_count": 26, "id": "38018fd0", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:53:40.522258Z", "iopub.status.busy": "2022-10-27T19:53:40.521719Z", "iopub.status.idle": "2022-10-27T19:53:40.869180Z", "shell.execute_reply": "2022-10-27T19:53:40.868254Z" }, "papermill": { "duration": 0.366922, "end_time": "2022-10-27T19:53:40.875663", "exception": false, "start_time": "2022-10-27T19:53:40.508741", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/opt/conda/lib/python3.7/site-packages/seaborn/_decorators.py:43: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n", " FutureWarning\n" ] }, { "data": { "text/plain": [ "<AxesSubplot:ylabel='count'>" ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "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\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "import seaborn as sns\n", "sns.countplot(Y)" ] }, { "cell_type": "code", "execution_count": 27, "id": "df64039f", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:53:40.915969Z", "iopub.status.busy": "2022-10-27T19:53:40.915117Z", "iopub.status.idle": "2022-10-27T19:53:40.922745Z", "shell.execute_reply": "2022-10-27T19:53:40.921877Z" }, "papermill": { "duration": 0.024345, "end_time": "2022-10-27T19:53:40.925042", "exception": false, "start_time": "2022-10-27T19:53:40.900697", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "import numpy as np\n", "h=[]\n", "d = []\n", "m0=0\n", "m1=0\n", "for i,j in zip(X,Y):\n", " if m1>=24 and m0>=24:\n", " break\n", " else: \n", " if j==1:\n", " #print(f\"m1 = {m1}\")\n", " h.append(i)\n", " d.append(j)\n", " m1=1+m1\n", "\n", " if j==0:\n", " #print(f\"m0 = {m0}\")\n", " h.append(i)\n", " d.append(j)\n", " m0=1+m0\n", "X2 = np.array(h) \n", "Y2 = np.array(d) " ] }, { "cell_type": "code", "execution_count": 28, "id": "5863b436", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:53:40.952105Z", "iopub.status.busy": "2022-10-27T19:53:40.951205Z", "iopub.status.idle": "2022-10-27T19:53:41.022358Z", "shell.execute_reply": "2022-10-27T19:53:41.021162Z" }, "papermill": { "duration": 0.088522, "end_time": "2022-10-27T19:53:41.025485", "exception": false, "start_time": "2022-10-27T19:53:40.936963", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "from sklearn.model_selection import train_test_split" ] }, { "cell_type": "code", "execution_count": 29, "id": "4a21d79f", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:53:41.052786Z", "iopub.status.busy": "2022-10-27T19:53:41.052266Z", "iopub.status.idle": "2022-10-27T19:53:41.059432Z", "shell.execute_reply": "2022-10-27T19:53:41.058100Z" }, "papermill": { "duration": 0.024498, "end_time": "2022-10-27T19:53:41.062050", "exception": false, "start_time": "2022-10-27T19:53:41.037552", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "X_train, X_test, y_train, y_test = train_test_split(X2, Y2, test_size=0.3)" ] }, { "cell_type": "code", "execution_count": 30, "id": "a6e30f3d", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:53:41.088892Z", "iopub.status.busy": "2022-10-27T19:53:41.087923Z", "iopub.status.idle": "2022-10-27T19:53:41.249002Z", "shell.execute_reply": "2022-10-27T19:53:41.247596Z" }, "papermill": { "duration": 0.178368, "end_time": "2022-10-27T19:53:41.252528", "exception": false, "start_time": "2022-10-27T19:53:41.074160", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "2022-10-27 19:53:41.139303: I tensorflow/core/common_runtime/process_util.cc:146] Creating new thread pool with default inter op setting: 2. Tune using inter_op_parallelism_threads for best performance.\n" ] } ], "source": [ "model = tf.keras.Sequential([\n", " tf.keras.layers.Embedding(vocab_size, embedding_dim, input_length=max_length),\n", " tf.keras.layers.GlobalAveragePooling1D(),\n", " tf.keras.layers.Dense(24, activation='relu'),\n", " tf.keras.layers.Dense(1, activation='sigmoid')\n", "])\n", "model.compile(loss='binary_crossentropy',optimizer='adam',metrics=['accuracy'])" ] }, { "cell_type": "code", "execution_count": 31, "id": "37534f4d", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:53:41.279336Z", "iopub.status.busy": "2022-10-27T19:53:41.278828Z", "iopub.status.idle": "2022-10-27T19:53:41.285783Z", "shell.execute_reply": "2022-10-27T19:53:41.284335Z" }, "papermill": { "duration": 0.024647, "end_time": "2022-10-27T19:53:41.289435", "exception": false, "start_time": "2022-10-27T19:53:41.264788", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Model: \"sequential\"\n", "_________________________________________________________________\n", "Layer (type) Output Shape Param # \n", "=================================================================\n", "embedding (Embedding) (None, 100, 16) 160000 \n", "_________________________________________________________________\n", "global_average_pooling1d (Gl (None, 16) 0 \n", "_________________________________________________________________\n", "dense (Dense) (None, 24) 408 \n", "_________________________________________________________________\n", "dense_1 (Dense) (None, 1) 25 \n", "=================================================================\n", "Total params: 160,433\n", "Trainable params: 160,433\n", "Non-trainable params: 0\n", "_________________________________________________________________\n" ] } ], "source": [ "model.summary()" ] }, { "cell_type": "code", "execution_count": 32, "id": "8e692a16", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:53:41.316996Z", "iopub.status.busy": "2022-10-27T19:53:41.316043Z", "iopub.status.idle": "2022-10-27T19:53:44.208474Z", "shell.execute_reply": "2022-10-27T19:53:44.206561Z" }, "papermill": { "duration": 2.910488, "end_time": "2022-10-27T19:53:44.212284", "exception": false, "start_time": "2022-10-27T19:53:41.301796", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "2022-10-27 19:53:41.415602: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:185] None of the MLIR Optimization Passes are enabled (registered 2)\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Epoch 1/30\n", "2/2 - 1s - loss: 0.6858 - accuracy: 0.6981 - val_loss: 0.6860 - val_accuracy: 0.6667\n", "Epoch 2/30\n", "2/2 - 0s - loss: 0.6827 - accuracy: 0.6981 - val_loss: 0.6842 - val_accuracy: 0.6667\n", "Epoch 3/30\n", "2/2 - 0s - loss: 0.6797 - accuracy: 0.6981 - val_loss: 0.6824 - val_accuracy: 0.6667\n", "Epoch 4/30\n", "2/2 - 0s - loss: 0.6775 - accuracy: 0.6981 - val_loss: 0.6807 - val_accuracy: 0.6667\n", "Epoch 5/30\n", "2/2 - 0s - loss: 0.6751 - accuracy: 0.6981 - val_loss: 0.6791 - val_accuracy: 0.6667\n", "Epoch 6/30\n", "2/2 - 0s - loss: 0.6727 - accuracy: 0.6981 - val_loss: 0.6774 - val_accuracy: 0.6667\n", "Epoch 7/30\n", "2/2 - 0s - loss: 0.6702 - accuracy: 0.6981 - val_loss: 0.6757 - val_accuracy: 0.6667\n", "Epoch 8/30\n", "2/2 - 0s - loss: 0.6679 - accuracy: 0.6981 - val_loss: 0.6740 - val_accuracy: 0.6667\n", "Epoch 9/30\n", "2/2 - 0s - loss: 0.6650 - accuracy: 0.6981 - val_loss: 0.6723 - val_accuracy: 0.6667\n", "Epoch 10/30\n", "2/2 - 0s - loss: 0.6624 - accuracy: 0.6981 - val_loss: 0.6705 - val_accuracy: 0.6667\n", "Epoch 11/30\n", "2/2 - 0s - loss: 0.6598 - accuracy: 0.6981 - val_loss: 0.6688 - val_accuracy: 0.6667\n", "Epoch 12/30\n", "2/2 - 0s - loss: 0.6569 - accuracy: 0.6981 - val_loss: 0.6670 - val_accuracy: 0.6667\n", "Epoch 13/30\n", "2/2 - 0s - loss: 0.6542 - accuracy: 0.6981 - val_loss: 0.6652 - val_accuracy: 0.6667\n", "Epoch 14/30\n", "2/2 - 0s - loss: 0.6517 - accuracy: 0.6981 - val_loss: 0.6635 - val_accuracy: 0.6667\n", "Epoch 15/30\n", "2/2 - 0s - loss: 0.6486 - accuracy: 0.6981 - val_loss: 0.6618 - val_accuracy: 0.6667\n", "Epoch 16/30\n", "2/2 - 0s - loss: 0.6457 - accuracy: 0.6981 - val_loss: 0.6600 - val_accuracy: 0.6667\n", "Epoch 17/30\n", "2/2 - 0s - loss: 0.6425 - accuracy: 0.6981 - val_loss: 0.6583 - val_accuracy: 0.6667\n", "Epoch 18/30\n", "2/2 - 0s - loss: 0.6400 - accuracy: 0.6981 - val_loss: 0.6565 - val_accuracy: 0.6667\n", "Epoch 19/30\n", "2/2 - 0s - loss: 0.6369 - accuracy: 0.6981 - val_loss: 0.6548 - val_accuracy: 0.6667\n", "Epoch 20/30\n", "2/2 - 0s - loss: 0.6339 - accuracy: 0.6981 - val_loss: 0.6531 - val_accuracy: 0.6667\n", "Epoch 21/30\n", "2/2 - 0s - loss: 0.6308 - accuracy: 0.6981 - val_loss: 0.6514 - val_accuracy: 0.6667\n", "Epoch 22/30\n", "2/2 - 0s - loss: 0.6274 - accuracy: 0.6981 - val_loss: 0.6497 - val_accuracy: 0.6667\n", "Epoch 23/30\n", "2/2 - 0s - loss: 0.6241 - accuracy: 0.6981 - val_loss: 0.6480 - val_accuracy: 0.6667\n", "Epoch 24/30\n", "2/2 - 0s - loss: 0.6210 - accuracy: 0.6981 - val_loss: 0.6463 - val_accuracy: 0.6667\n", "Epoch 25/30\n", "2/2 - 0s - loss: 0.6179 - accuracy: 0.6981 - val_loss: 0.6447 - val_accuracy: 0.6667\n", "Epoch 26/30\n", "2/2 - 0s - loss: 0.6148 - accuracy: 0.6981 - val_loss: 0.6430 - val_accuracy: 0.6667\n", "Epoch 27/30\n", "2/2 - 0s - loss: 0.6113 - accuracy: 0.6981 - val_loss: 0.6415 - val_accuracy: 0.6667\n", "Epoch 28/30\n", "2/2 - 0s - loss: 0.6085 - accuracy: 0.6981 - val_loss: 0.6399 - val_accuracy: 0.6667\n", "Epoch 29/30\n", "2/2 - 0s - loss: 0.6049 - accuracy: 0.6981 - val_loss: 0.6385 - val_accuracy: 0.6667\n", "Epoch 30/30\n", "2/2 - 0s - loss: 0.6013 - accuracy: 0.6981 - val_loss: 0.6371 - val_accuracy: 0.6667\n" ] } ], "source": [ "num_epochs = 30\n", "history = model.fit(X_train, y_train, epochs=num_epochs, validation_data=(X_test, y_test), verbose=2)" ] }, { "cell_type": "code", "execution_count": 33, "id": "9f8722a3", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:53:44.247064Z", "iopub.status.busy": "2022-10-27T19:53:44.245341Z", "iopub.status.idle": "2022-10-27T19:53:44.696298Z", "shell.execute_reply": "2022-10-27T19:53:44.694968Z" }, "papermill": { "duration": 0.470765, "end_time": "2022-10-27T19:53:44.698782", "exception": false, "start_time": "2022-10-27T19:53:44.228017", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "\n", "\n", "def plot_graphs(history, string):\n", " \n", " \n", " plt.plot(history.history[string])\n", " plt.plot(history.history[string])\n", " plt.xlabel(\"Epochs\")\n", " plt.ylabel(string)\n", " plt.legend([string, 'val_'+string])\n", " plt.show()\n", " \n", "\n", "plot_graphs(history, \"loss\")\n", "plot_graphs(history, \"accuracy\")" ] }, { "cell_type": "code", "execution_count": 34, "id": "a226a5fd", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:53:44.733857Z", "iopub.status.busy": "2022-10-27T19:53:44.732569Z", "iopub.status.idle": "2022-10-27T19:53:44.888082Z", "shell.execute_reply": "2022-10-27T19:53:44.886691Z" }, "papermill": { "duration": 0.176034, "end_time": "2022-10-27T19:53:44.890915", "exception": false, "start_time": "2022-10-27T19:53:44.714881", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "0.6666666666666666" ] }, "execution_count": 34, "metadata": {}, "output_type": "execute_result" } ], "source": [ "y_pred = model.predict(X_test)\n", "\n", "y_pred = y_pred > 0.5 \n", "from sklearn.metrics import accuracy_score\n", "accuracy_score(y_pred,y_test)" ] }, { "cell_type": "code", "execution_count": 35, "id": "861da088", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:53:44.926211Z", "iopub.status.busy": "2022-10-27T19:53:44.925213Z", "iopub.status.idle": "2022-10-27T19:53:45.031862Z", "shell.execute_reply": "2022-10-27T19:53:45.030726Z" }, "papermill": { "duration": 0.127855, "end_time": "2022-10-27T19:53:45.034939", "exception": false, "start_time": "2022-10-27T19:53:44.907084", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "X1 = nlp.texts_to_sequences(X1)\n", "X1 = pad_sequences(X1, maxlen=max_length)\n", "k = LabelEncoder()\n", "Y1 = k.fit_transform(Y1)" ] }, { "cell_type": "code", "execution_count": 36, "id": "788a24ee", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T19:53:45.069453Z", "iopub.status.busy": "2022-10-27T19:53:45.068964Z", "iopub.status.idle": "2022-10-27T19:53:45.146923Z", "shell.execute_reply": "2022-10-27T19:53:45.145897Z" }, "papermill": { "duration": 0.098633, "end_time": "2022-10-27T19:53:45.149794", "exception": false, "start_time": "2022-10-27T19:53:45.051161", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "0.736" ] }, "execution_count": 36, "metadata": {}, "output_type": "execute_result" } ], "source": [ "y_pred = model.predict(X1)\n", "\n", "y_pred = y_pred > 0.5 \n", "from sklearn.metrics import accuracy_score\n", "accuracy_score(y_pred,Y1)" ] }, { "cell_type": "code", "execution_count": null, "id": "23eb08b2", "metadata": { "papermill": { "duration": 0.01606, "end_time": "2022-10-27T19:53:45.182298", "exception": false, "start_time": "2022-10-27T19:53:45.166238", "status": "completed" }, "tags": [] }, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "26884d11", "metadata": { "papermill": { "duration": 0.015525, "end_time": "2022-10-27T19:53:45.213741", "exception": false, "start_time": "2022-10-27T19:53:45.198216", "status": "completed" }, "tags": [] }, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "id": "b5fe13f1", "metadata": { "papermill": { "duration": 0.015613, "end_time": "2022-10-27T19:53:45.245538", "exception": false, "start_time": "2022-10-27T19:53:45.229925", "status": "completed" }, "tags": [] }, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.12" }, "papermill": { "default_parameters": {}, "duration": 26.288164, "end_time": "2022-10-27T19:53:48.419870", "environment_variables": {}, "exception": null, "input_path": "__notebook__.ipynb", "output_path": "__notebook__.ipynb", "parameters": {}, "start_time": "2022-10-27T19:53:22.131706", "version": "2.3.4" } }, "nbformat": 4, "nbformat_minor": 5 }	0109/327/109327257.ipynb	s3://data-agents/kaggle-outputs/sharded/011_00109.jsonl.gz
{ "cells": [ { "cell_type": "markdown", "id": "25fc9e9b", "metadata": { "papermill": { "duration": 0.012576, "end_time": "2022-10-27T20:00:24.630842", "exception": false, "start_time": "2022-10-27T20:00:24.618266", "status": "completed" }, "tags": [] }, "source": [ "### Importing Library" ] }, { "cell_type": "code", "execution_count": 1, "id": "27554476", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:00:24.655020Z", "iopub.status.busy": "2022-10-27T20:00:24.654551Z", "iopub.status.idle": "2022-10-27T20:00:27.297692Z", "shell.execute_reply": "2022-10-27T20:00:27.295607Z" }, "papermill": { "duration": 2.659634, "end_time": "2022-10-27T20:00:27.301685", "exception": false, "start_time": "2022-10-27T20:00:24.642051", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "/kaggle/input/black-friday-sales-eda/train.csv\n" ] }, { "data": { "text/html": [ "<style type='text/css'>\n", ".datatable table.frame { margin-bottom: 0; }\n", ".datatable table.frame thead { border-bottom: none; }\n", ".datatable table.frame tr.coltypes td { color: #FFFFFF; line-height: 6px; padding: 0 0.5em;}\n", ".datatable .bool { background: #DDDD99; }\n", ".datatable .object { background: #565656; }\n", ".datatable .int { background: #5D9E5D; }\n", ".datatable .float { background: #4040CC; }\n", ".datatable .str { background: #CC4040; }\n", ".datatable .time { background: #40CC40; }\n", ".datatable .row_index { background: var(--jp-border-color3); border-right: 1px solid var(--jp-border-color0); color: var(--jp-ui-font-color3); font-size: 9px;}\n", ".datatable .frame tbody td { text-align: left; }\n", ".datatable .frame tr.coltypes .row_index { background: var(--jp-border-color0);}\n", ".datatable th:nth-child(2) { padding-left: 12px; }\n", ".datatable .hellipsis { color: var(--jp-cell-editor-border-color);}\n", ".datatable .vellipsis { background: var(--jp-layout-color0); color: var(--jp-cell-editor-border-color);}\n", ".datatable .na { color: var(--jp-cell-editor-border-color); font-size: 80%;}\n", ".datatable .sp { opacity: 0.25;}\n", ".datatable .footer { font-size: 9px; }\n", ".datatable .frame_dimensions { background: var(--jp-border-color3); border-top: 1px solid var(--jp-border-color0); color: var(--jp-ui-font-color3); display: inline-block; opacity: 0.6; padding: 1px 10px 1px 5px;}\n", "</style>\n" ], "text/plain": [ "<IPython.core.display.HTML object>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import numpy as np \n", "import pandas as pd \n", "\n", "import os\n", "for dirname, _, filenames in os.walk('/kaggle/input'):\n", " for filename in filenames:\n", " print(os.path.join(dirname, filename))\n", " \n", "import warnings # To ignore any warnings \n", "warnings.filterwarnings(\"ignore\")\n", "\n", "from sklearn.preprocessing import LabelEncoder\n", "from sklearn.model_selection import train_test_split,GridSearchCV\n", "\n", "from sklearn.neighbors import KNeighborsRegressor\n", "from sklearn.svm import SVR\n", "from sklearn.tree import DecisionTreeRegressor\n", "from sklearn.ensemble import RandomForestRegressor, AdaBoostRegressor\n", "from sklearn.linear_model import LinearRegression\n", "from xgboost import XGBRegressor\n", "from lightgbm import LGBMRegressor\n", "from catboost import CatBoostRegressor\n", "\n", "from sklearn.pipeline import Pipeline\n", "from sklearn.preprocessing import StandardScaler" ] }, { "cell_type": "code", "execution_count": 2, "id": "179c65b3", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:00:27.333488Z", "iopub.status.busy": "2022-10-27T20:00:27.332901Z", "iopub.status.idle": "2022-10-27T20:00:27.422237Z", "shell.execute_reply": "2022-10-27T20:00:27.421034Z" }, "papermill": { "duration": 0.107738, "end_time": "2022-10-27T20:00:27.425943", "exception": false, "start_time": "2022-10-27T20:00:27.318205", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "import seaborn as sns\n", "import matplotlib.pyplot as plt" ] }, { "cell_type": "markdown", "id": "bfb7887a", "metadata": { "papermill": { "duration": 0.017182, "end_time": "2022-10-27T20:00:27.463235", "exception": false, "start_time": "2022-10-27T20:00:27.446053", "status": "completed" }, "tags": [] }, "source": [ "### Reading CSV File" ] }, { "cell_type": "code", "execution_count": 3, "id": "f949737a", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:00:27.496540Z", "iopub.status.busy": "2022-10-27T20:00:27.496124Z", "iopub.status.idle": "2022-10-27T20:00:28.668275Z", "shell.execute_reply": "2022-10-27T20:00:28.667415Z" }, "papermill": { "duration": 1.187311, "end_time": "2022-10-27T20:00:28.670565", "exception": false, "start_time": "2022-10-27T20:00:27.483254", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>User_ID</th>\n", " <th>Product_ID</th>\n", " <th>Gender</th>\n", " <th>Age</th>\n", " <th>Occupation</th>\n", " <th>City_Category</th>\n", " <th>Stay_In_Current_City_Years</th>\n", " <th>Marital_Status</th>\n", " <th>Product_Category_1</th>\n", " <th>Product_Category_2</th>\n", " <th>Product_Category_3</th>\n", " <th>Purchase</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>0</th>\n", " <td>1000001</td>\n", " <td>P00069042</td>\n", " <td>F</td>\n", " <td>0-17</td>\n", " <td>10</td>\n", " <td>A</td>\n", " <td>2</td>\n", " <td>0</td>\n", " <td>3</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>8370</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>1000001</td>\n", " <td>P00248942</td>\n", " <td>F</td>\n", " <td>0-17</td>\n", " <td>10</td>\n", " <td>A</td>\n", " <td>2</td>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>6.0</td>\n", " <td>14.0</td>\n", " <td>15200</td>\n", " </tr>\n", " <tr>\n", " <th>2</th>\n", " <td>1000001</td>\n", " <td>P00087842</td>\n", " <td>F</td>\n", " <td>0-17</td>\n", " <td>10</td>\n", " <td>A</td>\n", " <td>2</td>\n", " <td>0</td>\n", " <td>12</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>1422</td>\n", " </tr>\n", " <tr>\n", " <th>3</th>\n", " <td>1000001</td>\n", " <td>P00085442</td>\n", " <td>F</td>\n", " <td>0-17</td>\n", " <td>10</td>\n", " <td>A</td>\n", " <td>2</td>\n", " <td>0</td>\n", " <td>12</td>\n", " <td>14.0</td>\n", " <td>NaN</td>\n", " <td>1057</td>\n", " </tr>\n", " <tr>\n", " <th>4</th>\n", " <td>1000002</td>\n", " <td>P00285442</td>\n", " <td>M</td>\n", " <td>55+</td>\n", " <td>16</td>\n", " <td>C</td>\n", " <td>4+</td>\n", " <td>0</td>\n", " <td>8</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>7969</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " User_ID Product_ID Gender Age Occupation City_Category \\\n", "0 1000001 P00069042 F 0-17 10 A \n", "1 1000001 P00248942 F 0-17 10 A \n", "2 1000001 P00087842 F 0-17 10 A \n", "3 1000001 P00085442 F 0-17 10 A \n", "4 1000002 P00285442 M 55+ 16 C \n", "\n", " Stay_In_Current_City_Years Marital_Status Product_Category_1 \\\n", "0 2 0 3 \n", "1 2 0 1 \n", "2 2 0 12 \n", "3 2 0 12 \n", "4 4+ 0 8 \n", "\n", " Product_Category_2 Product_Category_3 Purchase \n", "0 NaN NaN 8370 \n", "1 6.0 14.0 15200 \n", "2 NaN NaN 1422 \n", "3 14.0 NaN 1057 \n", "4 NaN NaN 7969 " ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df = pd.read_csv('/kaggle/input/black-friday-sales-eda/train.csv')\n", "df.head()" ] }, { "cell_type": "markdown", "id": "05ec8f69", "metadata": { "papermill": { "duration": 0.012192, "end_time": "2022-10-27T20:00:28.695062", "exception": false, "start_time": "2022-10-27T20:00:28.682870", "status": "completed" }, "tags": [] }, "source": [ "# About Dataset\n", "\n", "## Dataset History\n", "\n", "A retail company “ABC Private Limited” wants to understand the customer purchase behaviour (specifically, purchase amount) against various products of different categories. They have shared purchase summary of various customers for selected high volume products from last month.\n", "The data set also contains customer demographics (age, gender, marital status, citytype, stayincurrentcity), product details (productid and product category) and Total purchaseamount from last month.\n", "\n", "Now, they want to build a model to predict the purchase amount of customer against various products which will help them to create personalized offer for customers against different products.\n", "\n" ] }, { "cell_type": "markdown", "id": "dbe38dd9", "metadata": { "papermill": { "duration": 0.011511, "end_time": "2022-10-27T20:00:28.718376", "exception": false, "start_time": "2022-10-27T20:00:28.706865", "status": "completed" }, "tags": [] }, "source": [ "### DATA PREPROCESSING\n" ] }, { "cell_type": "markdown", "id": "35d35c21", "metadata": { "papermill": { "duration": 0.011408, "end_time": "2022-10-27T20:00:28.741565", "exception": false, "start_time": "2022-10-27T20:00:28.730157", "status": "completed" }, "tags": [] }, "source": [ "#### Checking Data Types of each Column" ] }, { "cell_type": "code", "execution_count": 4, "id": "c8bbf72c", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:00:28.768341Z", "iopub.status.busy": "2022-10-27T20:00:28.767687Z", "iopub.status.idle": "2022-10-27T20:00:28.913766Z", "shell.execute_reply": "2022-10-27T20:00:28.912237Z" }, "papermill": { "duration": 0.162681, "end_time": "2022-10-27T20:00:28.916770", "exception": false, "start_time": "2022-10-27T20:00:28.754089", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "<class 'pandas.core.frame.DataFrame'>\n", "RangeIndex: 550068 entries, 0 to 550067\n", "Data columns (total 12 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 User_ID 550068 non-null int64 \n", " 1 Product_ID 550068 non-null object \n", " 2 Gender 550068 non-null object \n", " 3 Age 550068 non-null object \n", " 4 Occupation 550068 non-null int64 \n", " 5 City_Category 550068 non-null object \n", " 6 Stay_In_Current_City_Years 550068 non-null object \n", " 7 Marital_Status 550068 non-null int64 \n", " 8 Product_Category_1 550068 non-null int64 \n", " 9 Product_Category_2 376430 non-null float64\n", " 10 Product_Category_3 166821 non-null float64\n", " 11 Purchase 550068 non-null int64 \n", "dtypes: float64(2), int64(5), object(5)\n", "memory usage: 50.4+ MB\n" ] } ], "source": [ "df.info()" ] }, { "cell_type": "code", "execution_count": 5, "id": "db6901b7", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:00:28.943325Z", "iopub.status.busy": "2022-10-27T20:00:28.942901Z", "iopub.status.idle": "2022-10-27T20:00:28.950354Z", "shell.execute_reply": "2022-10-27T20:00:28.949184Z" }, "papermill": { "duration": 0.024023, "end_time": "2022-10-27T20:00:28.952912", "exception": false, "start_time": "2022-10-27T20:00:28.928889", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "(550068, 12)" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.shape" ] }, { "cell_type": "markdown", "id": "432555f9", "metadata": { "papermill": { "duration": 0.012675, "end_time": "2022-10-27T20:00:28.977704", "exception": false, "start_time": "2022-10-27T20:00:28.965029", "status": "completed" }, "tags": [] }, "source": [ "Droping unnecessary Column" ] }, { "cell_type": "code", "execution_count": 6, "id": "007411c5", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:00:29.004715Z", "iopub.status.busy": "2022-10-27T20:00:29.004301Z", "iopub.status.idle": "2022-10-27T20:00:29.013987Z", "shell.execute_reply": "2022-10-27T20:00:29.012542Z" }, "papermill": { "duration": 0.026671, "end_time": "2022-10-27T20:00:29.016570", "exception": false, "start_time": "2022-10-27T20:00:28.989899", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "383247" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df['Product_Category_3'].isnull().sum()" ] }, { "cell_type": "code", "execution_count": 7, "id": "87e8a0ec", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:00:29.044496Z", "iopub.status.busy": "2022-10-27T20:00:29.044096Z", "iopub.status.idle": "2022-10-27T20:00:29.080133Z", "shell.execute_reply": "2022-10-27T20:00:29.078622Z" }, "papermill": { "duration": 0.052592, "end_time": "2022-10-27T20:00:29.082981", "exception": false, "start_time": "2022-10-27T20:00:29.030389", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "# Product_Category_3 has lots of Nan values, so we can drop the column instead of filling it because it would not effect the analysis that much.\n", "df = df.drop(columns =['User_ID','Product_ID','Product_Category_3'])" ] }, { "cell_type": "markdown", "id": "986bd191", "metadata": { "papermill": { "duration": 0.01252, "end_time": "2022-10-27T20:00:29.108615", "exception": false, "start_time": "2022-10-27T20:00:29.096095", "status": "completed" }, "tags": [] }, "source": [ "Renaming Columns for better understanding" ] }, { "cell_type": "markdown", "id": "87cc0a28", "metadata": { "papermill": { "duration": 0.013426, "end_time": "2022-10-27T20:00:29.134844", "exception": false, "start_time": "2022-10-27T20:00:29.121418", "status": "completed" }, "tags": [] }, "source": [ "##### Column 'City_Category'and 'Stay_In_Current_City_Years' can be renamed as 'City' and 'Years_in_City' respectively." ] }, { "cell_type": "code", "execution_count": 8, "id": "8544d99b", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:00:29.161715Z", "iopub.status.busy": "2022-10-27T20:00:29.161266Z", "iopub.status.idle": "2022-10-27T20:00:29.167338Z", "shell.execute_reply": "2022-10-27T20:00:29.166133Z" }, "papermill": { "duration": 0.022138, "end_time": "2022-10-27T20:00:29.169511", "exception": false, "start_time": "2022-10-27T20:00:29.147373", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "df.rename(columns = {'City_Category':'City', 'Stay_In_Current_City_Years':'Years_in_City'}, inplace = True)" ] }, { "cell_type": "markdown", "id": "1830e778", "metadata": { "papermill": { "duration": 0.011974, "end_time": "2022-10-27T20:00:29.194217", "exception": false, "start_time": "2022-10-27T20:00:29.182243", "status": "completed" }, "tags": [] }, "source": [ "Categorizing Columns" ] }, { "cell_type": "code", "execution_count": 9, "id": "4886278d", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:00:29.221354Z", "iopub.status.busy": "2022-10-27T20:00:29.220732Z", "iopub.status.idle": "2022-10-27T20:00:29.267370Z", "shell.execute_reply": "2022-10-27T20:00:29.266115Z" }, "papermill": { "duration": 0.063169, "end_time": "2022-10-27T20:00:29.269808", "exception": false, "start_time": "2022-10-27T20:00:29.206639", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "array(['0-17', '55+', '26-35', '46-50', '51-55', '36-45', '18-25'],\n", " dtype=object)" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.Age.unique()" ] }, { "cell_type": "code", "execution_count": 10, "id": "a70279ff", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:00:29.298646Z", "iopub.status.busy": "2022-10-27T20:00:29.298235Z", "iopub.status.idle": "2022-10-27T20:00:29.357365Z", "shell.execute_reply": "2022-10-27T20:00:29.355796Z" }, "papermill": { "duration": 0.077826, "end_time": "2022-10-27T20:00:29.360096", "exception": false, "start_time": "2022-10-27T20:00:29.282270", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "# Classifying Age into Categorical Data\n", "\n", "df['Age']=df['Age'].map({'0-17':'Child','18-25':'Teenage','26-35':'Adult','36-45':'Adult','46-50':'Adult','51-55':'Old','55+':'Old'})\n", "\n", "# Age Group 0-17 into Child Group\n", "# Age Group 18-25 into Teenagers Group \n", "# Age Group 26-35 into Adult Group\n", "# Age Group 36-45 into Adult Group\n", "# Age Group 46-50 into Adult Group\n", "# Age Group 51-55 into Old Group\n", "# Age Group 55+ into Old Group" ] }, { "cell_type": "code", "execution_count": 11, "id": "690a6eca", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:00:29.386640Z", "iopub.status.busy": "2022-10-27T20:00:29.386227Z", "iopub.status.idle": "2022-10-27T20:00:29.399983Z", "shell.execute_reply": "2022-10-27T20:00:29.399108Z" }, "papermill": { "duration": 0.029762, "end_time": "2022-10-27T20:00:29.402260", "exception": false, "start_time": "2022-10-27T20:00:29.372498", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>Gender</th>\n", " <th>Age</th>\n", " <th>Occupation</th>\n", " <th>City</th>\n", " <th>Years_in_City</th>\n", " <th>Marital_Status</th>\n", " <th>Product_Category_1</th>\n", " <th>Product_Category_2</th>\n", " <th>Purchase</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>0</th>\n", " <td>F</td>\n", " <td>Child</td>\n", " <td>10</td>\n", " <td>A</td>\n", " <td>2</td>\n", " <td>0</td>\n", " <td>3</td>\n", " <td>NaN</td>\n", " <td>8370</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>F</td>\n", " <td>Child</td>\n", " <td>10</td>\n", " <td>A</td>\n", " <td>2</td>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>6.0</td>\n", " <td>15200</td>\n", " </tr>\n", " <tr>\n", " <th>2</th>\n", " <td>F</td>\n", " <td>Child</td>\n", " <td>10</td>\n", " <td>A</td>\n", " <td>2</td>\n", " <td>0</td>\n", " <td>12</td>\n", " <td>NaN</td>\n", " <td>1422</td>\n", " </tr>\n", " <tr>\n", " <th>3</th>\n", " <td>F</td>\n", " <td>Child</td>\n", " <td>10</td>\n", " <td>A</td>\n", " <td>2</td>\n", " <td>0</td>\n", " <td>12</td>\n", " <td>14.0</td>\n", " <td>1057</td>\n", " </tr>\n", " <tr>\n", " <th>4</th>\n", " <td>M</td>\n", " <td>Old</td>\n", " <td>16</td>\n", " <td>C</td>\n", " <td>4+</td>\n", " <td>0</td>\n", " <td>8</td>\n", " <td>NaN</td>\n", " <td>7969</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " Gender Age Occupation City Years_in_City Marital_Status \\\n", "0 F Child 10 A 2 0 \n", "1 F Child 10 A 2 0 \n", "2 F Child 10 A 2 0 \n", "3 F Child 10 A 2 0 \n", "4 M Old 16 C 4+ 0 \n", "\n", " Product_Category_1 Product_Category_2 Purchase \n", "0 3 NaN 8370 \n", "1 1 6.0 15200 \n", "2 12 NaN 1422 \n", "3 12 14.0 1057 \n", "4 8 NaN 7969 " ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.head()" ] }, { "cell_type": "markdown", "id": "b415b5f3", "metadata": { "papermill": { "duration": 0.0129, "end_time": "2022-10-27T20:00:29.428130", "exception": false, "start_time": "2022-10-27T20:00:29.415230", "status": "completed" }, "tags": [] }, "source": [ "Filling Nan Values" ] }, { "cell_type": "markdown", "id": "90a9c4fe", "metadata": { "papermill": { "duration": 0.012341, "end_time": "2022-10-27T20:00:29.453147", "exception": false, "start_time": "2022-10-27T20:00:29.440806", "status": "completed" }, "tags": [] }, "source": [ "#### Filling Nan values in Product_Category_2 Column." ] }, { "cell_type": "code", "execution_count": 12, "id": "3c7182e0", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:00:29.480365Z", "iopub.status.busy": "2022-10-27T20:00:29.479682Z", "iopub.status.idle": "2022-10-27T20:00:29.570442Z", "shell.execute_reply": "2022-10-27T20:00:29.569281Z" }, "papermill": { "duration": 0.107078, "end_time": "2022-10-27T20:00:29.572809", "exception": false, "start_time": "2022-10-27T20:00:29.465731", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "Age\n", "Adult 8.0\n", "Child 4.0\n", "Old 8.0\n", "Teenage 8.0\n", "Name: Product_Category_2, dtype: float64" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# from statistics import mode\n", "a = df.groupby(['Age'])['Product_Category_2'].agg(pd.Series.mode)\n", "a" ] }, { "cell_type": "code", "execution_count": 13, "id": "7f6162ea", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:00:29.599914Z", "iopub.status.busy": "2022-10-27T20:00:29.599474Z", "iopub.status.idle": "2022-10-27T20:00:29.692746Z", "shell.execute_reply": "2022-10-27T20:00:29.691595Z" }, "papermill": { "duration": 0.10957, "end_time": "2022-10-27T20:00:29.695355", "exception": false, "start_time": "2022-10-27T20:00:29.585785", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "0 4.0\n", "1 6.0\n", "2 4.0\n", "3 14.0\n", "4 NaN\n", " ... \n", "550063 NaN\n", "550064 NaN\n", "550065 NaN\n", "550066 NaN\n", "550067 NaN\n", "Name: Product_Category_2, Length: 550068, dtype: float64" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "child = df.loc[df['Age'] == 'Child' ,'Product_Category_2'].fillna(a['Child'])\n", "df.loc[df['Age']=='Child','Product_Category_2'] = child\n", "df['Product_Category_2']" ] }, { "cell_type": "code", "execution_count": 14, "id": "c12e02ae", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:00:29.723325Z", "iopub.status.busy": "2022-10-27T20:00:29.722938Z", "iopub.status.idle": "2022-10-27T20:00:29.818867Z", "shell.execute_reply": "2022-10-27T20:00:29.817598Z" }, "papermill": { "duration": 0.113613, "end_time": "2022-10-27T20:00:29.821714", "exception": false, "start_time": "2022-10-27T20:00:29.708101", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "0 4.0\n", "1 6.0\n", "2 4.0\n", "3 14.0\n", "4 NaN\n", " ... \n", "550063 NaN\n", "550064 8.0\n", "550065 8.0\n", "550066 NaN\n", "550067 8.0\n", "Name: Product_Category_2, Length: 550068, dtype: float64" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "adult=df.loc[df['Age'] == 'Adult' ,'Product_Category_2'].fillna(a['Adult'])\n", "df.loc[df['Age']=='Adult','Product_Category_2'] = adult\n", "df['Product_Category_2']" ] }, { "cell_type": "code", "execution_count": 15, "id": "94124531", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:00:29.848741Z", "iopub.status.busy": "2022-10-27T20:00:29.848302Z", "iopub.status.idle": "2022-10-27T20:00:29.938705Z", "shell.execute_reply": "2022-10-27T20:00:29.937714Z" }, "papermill": { "duration": 0.106937, "end_time": "2022-10-27T20:00:29.941376", "exception": false, "start_time": "2022-10-27T20:00:29.834439", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "0 4.0\n", "1 6.0\n", "2 4.0\n", "3 14.0\n", "4 NaN\n", " ... \n", "550063 NaN\n", "550064 8.0\n", "550065 8.0\n", "550066 NaN\n", "550067 8.0\n", "Name: Product_Category_2, Length: 550068, dtype: float64" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "teenage=df.loc[df['Age'] == 'Teenage' ,'Product_Category_2'].fillna(a['Teenage'])\n", "df.loc[df['Age']=='Teenage','Product_Category_2'] = teenage\n", "df['Product_Category_2']" ] }, { "cell_type": "code", "execution_count": 16, "id": "8a7e44e1", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:00:29.969902Z", "iopub.status.busy": "2022-10-27T20:00:29.969464Z", "iopub.status.idle": "2022-10-27T20:00:30.057095Z", "shell.execute_reply": "2022-10-27T20:00:30.055942Z" }, "papermill": { "duration": 0.104781, "end_time": "2022-10-27T20:00:30.059703", "exception": false, "start_time": "2022-10-27T20:00:29.954922", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "0 4.0\n", "1 6.0\n", "2 4.0\n", "3 14.0\n", "4 8.0\n", " ... \n", "550063 8.0\n", "550064 8.0\n", "550065 8.0\n", "550066 8.0\n", "550067 8.0\n", "Name: Product_Category_2, Length: 550068, dtype: float64" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "old=df.loc[df['Age'] == 'Old' ,'Product_Category_2'].fillna(a['Old'])\n", "df.loc[df['Age']=='Old','Product_Category_2'] = old\n", "df['Product_Category_2']" ] }, { "cell_type": "code", "execution_count": 17, "id": "4bc48150", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:00:30.087303Z", "iopub.status.busy": "2022-10-27T20:00:30.086669Z", "iopub.status.idle": "2022-10-27T20:00:30.100300Z", "shell.execute_reply": "2022-10-27T20:00:30.099139Z" }, "papermill": { "duration": 0.030034, "end_time": "2022-10-27T20:00:30.102634", "exception": false, "start_time": "2022-10-27T20:00:30.072600", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "False 550068\n", "Name: Product_Category_2, dtype: int64" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df['Product_Category_2'].isnull().value_counts()" ] }, { "cell_type": "markdown", "id": "c61fc239", "metadata": { "papermill": { "duration": 0.012537, "end_time": "2022-10-27T20:00:30.128135", "exception": false, "start_time": "2022-10-27T20:00:30.115598", "status": "completed" }, "tags": [] }, "source": [ "Convert categorical data into integer using map function (e.g 'Gender' column)" ] }, { "cell_type": "code", "execution_count": 18, "id": "4d5d19e3", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:00:30.156031Z", "iopub.status.busy": "2022-10-27T20:00:30.155389Z", "iopub.status.idle": "2022-10-27T20:00:30.192616Z", "shell.execute_reply": "2022-10-27T20:00:30.191351Z" }, "papermill": { "duration": 0.054201, "end_time": "2022-10-27T20:00:30.195290", "exception": false, "start_time": "2022-10-27T20:00:30.141089", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "# Denoting Male And Female by 0 & 1 respectively\n", "# to convert them into integer\n", "# Male = 0 and Female = 1\n", "df['Gender']=df['Gender'].map({'M':0 , 'F':1})" ] }, { "cell_type": "code", "execution_count": 19, "id": "9a891686", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:00:30.223491Z", "iopub.status.busy": "2022-10-27T20:00:30.222879Z", "iopub.status.idle": "2022-10-27T20:00:30.230776Z", "shell.execute_reply": "2022-10-27T20:00:30.229676Z" }, "papermill": { "duration": 0.024421, "end_time": "2022-10-27T20:00:30.232932", "exception": false, "start_time": "2022-10-27T20:00:30.208511", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "Gender int64\n", "Age object\n", "Occupation int64\n", "City object\n", "Years_in_City object\n", "Marital_Status int64\n", "Product_Category_1 int64\n", "Product_Category_2 float64\n", "Purchase int64\n", "dtype: object" ] }, "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.dtypes" ] }, { "cell_type": "code", "execution_count": 20, "id": "f67a4c9e", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:00:30.260750Z", "iopub.status.busy": "2022-10-27T20:00:30.260346Z", "iopub.status.idle": "2022-10-27T20:00:30.275185Z", "shell.execute_reply": "2022-10-27T20:00:30.274030Z" }, "papermill": { "duration": 0.031588, "end_time": "2022-10-27T20:00:30.277692", "exception": false, "start_time": "2022-10-27T20:00:30.246104", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>Gender</th>\n", " <th>Age</th>\n", " <th>Occupation</th>\n", " <th>City</th>\n", " <th>Years_in_City</th>\n", " <th>Marital_Status</th>\n", " <th>Product_Category_1</th>\n", " <th>Product_Category_2</th>\n", " <th>Purchase</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>0</th>\n", " <td>1</td>\n", " <td>Child</td>\n", " <td>10</td>\n", " <td>A</td>\n", " <td>2</td>\n", " <td>0</td>\n", " <td>3</td>\n", " <td>4.0</td>\n", " <td>8370</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>1</td>\n", " <td>Child</td>\n", " <td>10</td>\n", " <td>A</td>\n", " <td>2</td>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>6.0</td>\n", " <td>15200</td>\n", " </tr>\n", " <tr>\n", " <th>2</th>\n", " <td>1</td>\n", " <td>Child</td>\n", " <td>10</td>\n", " <td>A</td>\n", " <td>2</td>\n", " <td>0</td>\n", " <td>12</td>\n", " <td>4.0</td>\n", " <td>1422</td>\n", " </tr>\n", " <tr>\n", " <th>3</th>\n", " <td>1</td>\n", " <td>Child</td>\n", " <td>10</td>\n", " <td>A</td>\n", " <td>2</td>\n", " <td>0</td>\n", " <td>12</td>\n", " <td>14.0</td>\n", " <td>1057</td>\n", " </tr>\n", " <tr>\n", " <th>4</th>\n", " <td>0</td>\n", " <td>Old</td>\n", " <td>16</td>\n", " <td>C</td>\n", " <td>4+</td>\n", " <td>0</td>\n", " <td>8</td>\n", " <td>8.0</td>\n", " <td>7969</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " Gender Age Occupation City Years_in_City Marital_Status \\\n", "0 1 Child 10 A 2 0 \n", "1 1 Child 10 A 2 0 \n", "2 1 Child 10 A 2 0 \n", "3 1 Child 10 A 2 0 \n", "4 0 Old 16 C 4+ 0 \n", "\n", " Product_Category_1 Product_Category_2 Purchase \n", "0 3 4.0 8370 \n", "1 1 6.0 15200 \n", "2 12 4.0 1422 \n", "3 12 14.0 1057 \n", "4 8 8.0 7969 " ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.head()" ] }, { "cell_type": "markdown", "id": "9b71c4b8", "metadata": { "papermill": { "duration": 0.012989, "end_time": "2022-10-27T20:00:30.304395", "exception": false, "start_time": "2022-10-27T20:00:30.291406", "status": "completed" }, "tags": [] }, "source": [ "# Data Visualisation" ] }, { "cell_type": "markdown", "id": "70c3f2f9", "metadata": { "papermill": { "duration": 0.013124, "end_time": "2022-10-27T20:00:30.331429", "exception": false, "start_time": "2022-10-27T20:00:30.318305", "status": "completed" }, "tags": [] }, "source": [ "#### Data is clean , now we can start our Visualization." ] }, { "cell_type": "markdown", "id": "2c8a45d8", "metadata": { "papermill": { "duration": 0.012891, "end_time": "2022-10-27T20:00:30.357992", "exception": false, "start_time": "2022-10-27T20:00:30.345101", "status": "completed" }, "tags": [] }, "source": [ "#### Checking relation between each columns." ] }, { "cell_type": "code", "execution_count": 21, "id": "48766978", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:00:30.386726Z", "iopub.status.busy": "2022-10-27T20:00:30.386314Z", "iopub.status.idle": "2022-10-27T20:00:30.987416Z", "shell.execute_reply": "2022-10-27T20:00:30.986473Z" }, "papermill": { "duration": 0.618439, "end_time": "2022-10-27T20:00:30.989537", "exception": false, "start_time": "2022-10-27T20:00:30.371098", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "<AxesSubplot:>" ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 432x288 with 2 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sns.heatmap(df.corr(), cmap='coolwarm', annot=True)" ] }, { "cell_type": "markdown", "id": "bee2be47", "metadata": { "papermill": { "duration": 0.013566, "end_time": "2022-10-27T20:00:31.017271", "exception": false, "start_time": "2022-10-27T20:00:31.003705", "status": "completed" }, "tags": [] }, "source": [ "### Independent Variables (Categorical variables)" ] }, { "cell_type": "code", "execution_count": 22, "id": "32469da6", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:00:31.047567Z", "iopub.status.busy": "2022-10-27T20:00:31.046565Z", "iopub.status.idle": "2022-10-27T20:00:32.347640Z", "shell.execute_reply": "2022-10-27T20:00:32.346359Z" }, "papermill": { "duration": 1.318786, "end_time": "2022-10-27T20:00:32.349976", "exception": false, "start_time": "2022-10-27T20:00:31.031190", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "Text(0.5, 1.0, 'Marital_Status')" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" }, { "data": { "text/plain": [ "<Figure size 432x288 with 0 Axes>" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 1440x1080 with 6 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.figure(1)\n", "plt.figure(figsize=(20,15))\n", "\n", "# Column (Gender)\n", "plt.subplot(321)\n", "df['Gender'].value_counts().plot(kind='bar',color='crimson',rot=0)\n", "plt.title('Gender')\n", "\n", "# Column (Age)\n", "plt.subplot(322)\n", "df['Age'].value_counts().plot(kind='bar',color='orange',rot=0)\n", "plt.title('Age')\n", "\n", "# Column (Occupation)\n", "plt.subplot(323)\n", "df['Occupation'].value_counts().plot(kind='bar',color='lime',rot=0)\n", "plt.title('Occupation')\n", "\n", "# Column (City)\n", "plt.subplot(324)\n", "df['City'].value_counts().plot(kind='bar',color='royalblue',rot=0)\n", "plt.title('City')\n", "\n", "# Column (Years_in_City)\n", "plt.subplot(325)\n", "df['Years_in_City'].value_counts().plot(kind='bar',color='olive',rot=0)\n", "plt.title('Years_in_City')\n", "\n", "# Column (Marital_Status)\n", "plt.subplot(326)\n", "df['Marital_Status'].value_counts().plot(kind='bar',color='magenta',rot=0)\n", "plt.title('Marital_Status')" ] }, { "cell_type": "markdown", "id": "f3b86c06", "metadata": { "papermill": { "duration": 0.015608, "end_time": "2022-10-27T20:00:32.380888", "exception": false, "start_time": "2022-10-27T20:00:32.365280", "status": "completed" }, "tags": [] }, "source": [ "Insights from above plot\n", "* Male count is almost 3 times more than females.\n", "* Customers are mostly of adult age group and least of child age group.\n", "* Occupation 8 customers are lowest and occupation 4 are more.\n", "* City B has most of the customers.\n", "* Most of the people are leaving for a year in the respective cities.\n", "* Customers with martial status 0 are more than 1." ] }, { "cell_type": "markdown", "id": "5427305e", "metadata": { "papermill": { "duration": 0.015528, "end_time": "2022-10-27T20:00:32.411689", "exception": false, "start_time": "2022-10-27T20:00:32.396161", "status": "completed" }, "tags": [] }, "source": [ "### Independent Variables (Continous variables)" ] }, { "cell_type": "code", "execution_count": 23, "id": "61cbdbbd", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:00:32.444677Z", "iopub.status.busy": "2022-10-27T20:00:32.444248Z", "iopub.status.idle": "2022-10-27T20:00:33.053605Z", "shell.execute_reply": "2022-10-27T20:00:33.052321Z" }, "papermill": { "duration": 0.629467, "end_time": "2022-10-27T20:00:33.056729", "exception": false, "start_time": "2022-10-27T20:00:32.427262", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "Text(0.5, 1.0, 'Product_Category_2')" ] }, "execution_count": 23, "metadata": {}, "output_type": "execute_result" }, { "data": { "text/plain": [ "<Figure size 432x288 with 0 Axes>" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 1440x1080 with 2 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.figure(1)\n", "plt.figure(figsize=(20,15))\n", "\n", "# Column (Product_Category_1)\n", "plt.subplot(211)\n", "df['Product_Category_1'].value_counts().plot(kind='bar',color='darkcyan',rot=0)\n", "plt.title('Product_Category_1')\n", "\n", "# Column (Product_Category_2)\n", "plt.subplot(212)\n", "df['Product_Category_2'].value_counts().plot(kind='bar',color='darkviolet',rot=0)\n", "plt.title('Product_Category_2')" ] }, { "cell_type": "markdown", "id": "314876bb", "metadata": { "papermill": { "duration": 0.015597, "end_time": "2022-10-27T20:00:33.088459", "exception": false, "start_time": "2022-10-27T20:00:33.072862", "status": "completed" }, "tags": [] }, "source": [ "### Target Column --> [Purchase]" ] }, { "cell_type": "code", "execution_count": 24, "id": "49fe269f", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:00:33.123116Z", "iopub.status.busy": "2022-10-27T20:00:33.121975Z", "iopub.status.idle": "2022-10-27T20:00:35.633609Z", "shell.execute_reply": "2022-10-27T20:00:35.632296Z" }, "papermill": { "duration": 2.532189, "end_time": "2022-10-27T20:00:35.636423", "exception": false, "start_time": "2022-10-27T20:00:33.104234", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "<AxesSubplot:xlabel='Purchase', ylabel='Density'>" ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sns.distplot(df['Purchase'])" ] }, { "cell_type": "code", "execution_count": 25, "id": "2814b0b3", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:00:35.672980Z", "iopub.status.busy": "2022-10-27T20:00:35.672581Z", "iopub.status.idle": "2022-10-27T20:00:36.030702Z", "shell.execute_reply": "2022-10-27T20:00:36.029331Z" }, "papermill": { "duration": 0.380226, "end_time": "2022-10-27T20:00:36.033316", "exception": false, "start_time": "2022-10-27T20:00:35.653090", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "<AxesSubplot:>" ] }, "execution_count": 25, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "df['Purchase'].hist(bins = 100)" ] }, { "cell_type": "markdown", "id": "b45a5df3", "metadata": { "papermill": { "duration": 0.016387, "end_time": "2022-10-27T20:00:36.066566", "exception": false, "start_time": "2022-10-27T20:00:36.050179", "status": "completed" }, "tags": [] }, "source": [ "## Categorical Column vs Target Column\n" ] }, { "cell_type": "code", "execution_count": 26, "id": "942884e9", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:00:36.102772Z", "iopub.status.busy": "2022-10-27T20:00:36.101384Z", "iopub.status.idle": "2022-10-27T20:01:28.261164Z", "shell.execute_reply": "2022-10-27T20:01:28.259877Z" }, "papermill": { "duration": 52.180414, "end_time": "2022-10-27T20:01:28.263695", "exception": false, "start_time": "2022-10-27T20:00:36.083281", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "Text(0.5, 1.0, 'Marital_Status vs Purchase')" ] }, "execution_count": 26, "metadata": {}, "output_type": "execute_result" }, { "data": { "text/plain": [ "<Figure size 432x288 with 0 Axes>" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 1440x1296 with 6 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.figure(1)\n", "plt.figure(figsize = (20, 18))\n", "\n", "# Column (Gender vs Purchase)\n", "plt.subplot(321)\n", "sns.barplot(x = df['Gender'], y = df['Purchase'], color = \"crimson\")\n", "plt.title('Gender vs Purchase')\n", "\n", "# Column (Age vs Purchase)\n", "plt.subplot(322)\n", "sns.barplot(x = df['Age'], y = df['Purchase'], color = \"orange\")\n", "plt.title('Age vs Purchase')\n", "\n", "# Column (Occupation vs Purchase)\n", "plt.subplot(323)\n", "sns.barplot(x = df['Occupation'], y = df['Purchase'], color = \"lime\")\n", "plt.title('Occupation vs Purchase')\n", "\n", "# Column (City vs Purchase)\n", "plt.subplot(324)\n", "sns.barplot(x = df['City'], y = df['Purchase'], color = \"royalblue\")\n", "plt.title('City vs Purchase')\n", "\n", "# Column (Years_in_City vs Purchase)\n", "plt.subplot(325)\n", "sns.barplot(x = df['Years_in_City'], y = df['Purchase'], color = \"olive\")\n", "plt.title('Years_in_City vs Purchase')\n", "\n", "# Column (Marital_Status vs Purchase)\n", "plt.subplot(326)\n", "sns.barplot(x = df['Marital_Status'], y = df['Purchase'], color = \"magenta\")\n", "plt.title('Marital_Status vs Purchase')" ] }, { "cell_type": "markdown", "id": "52bca574", "metadata": { "papermill": { "duration": 0.017489, "end_time": "2022-10-27T20:01:28.299497", "exception": false, "start_time": "2022-10-27T20:01:28.282008", "status": "completed" }, "tags": [] }, "source": [ "## Continous Column vs Target Column\n" ] }, { "cell_type": "code", "execution_count": 27, "id": "4e125fb7", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:01:28.337885Z", "iopub.status.busy": "2022-10-27T20:01:28.336836Z", "iopub.status.idle": "2022-10-27T20:01:44.178837Z", "shell.execute_reply": "2022-10-27T20:01:44.177662Z" }, "papermill": { "duration": 15.864208, "end_time": "2022-10-27T20:01:44.181472", "exception": false, "start_time": "2022-10-27T20:01:28.317264", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "Text(0.5, 1.0, 'Product_Category_2 vs Purchase')" ] }, "execution_count": 27, "metadata": {}, "output_type": "execute_result" }, { "data": { "text/plain": [ "<Figure size 432x288 with 0 Axes>" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 1440x1080 with 2 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.figure(1)\n", "plt.figure(figsize = (20, 15))\n", "\n", "# Column (Product_Category_1 vs Purchase)\n", "plt.subplot(211)\n", "sns.barplot(x = df['Product_Category_1'], y = df['Purchase'], color = \"darkcyan\")\n", "plt.title('Product_Category_1 vs Purchase')\n", "\n", "# Column (Product_Category_2 vs Purchase)\n", "plt.subplot(212)\n", "sns.barplot(x = df['Product_Category_2'], y = df['Purchase'], color = \"darkviolet\")\n", "plt.title('Product_Category_2 vs Purchase')" ] }, { "cell_type": "code", "execution_count": 28, "id": "72d26d1a", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:01:44.220659Z", "iopub.status.busy": "2022-10-27T20:01:44.220227Z", "iopub.status.idle": "2022-10-27T20:01:48.414597Z", "shell.execute_reply": "2022-10-27T20:01:48.413429Z" }, "papermill": { "duration": 4.21701, "end_time": "2022-10-27T20:01:48.417258", "exception": false, "start_time": "2022-10-27T20:01:44.200248", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "Text(0, 0.5, 'Purchase')" ] }, "execution_count": 28, "metadata": {}, "output_type": "execute_result" }, { "data": { "text/plain": [ "<Figure size 432x288 with 0 Axes>" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "image/png": 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EnQHjYqFzPO0YMX9Kkne21j5bM05xB8DyYWQQALAnXHz1rXPWjXoCFmKhI56uq6oPZyp4urKqHp3kgf7agvE21xd8X/xZCkYGAQAAy8VCRzz9UpKjknyptfadqnpckpf21hVMACETAAAAQ7eg4Km19kBVfTnJU6pqv557AgAAAGACLPSsdv8xySuSHJzkhiTHJvl4kp/qrTMAAAAAxtpC53h6RZIfS/KV1tpPJjk6yT19NQUAAADA+Fto8PTd1tp3k6SqHtFa+0KSI/prCwAAAPrhZECwdBY6ufjtVbUqycYkm6rqG0m+0ldTzG0ST5G+ZcOpE7leAADA8uX7BiyNhU4u/rzu6uuq6qNJfiDJh3rrilnNd4r0cX/THPf+AQAAgJ0tdMRTqmpFkoOSfLkr/Yskt/bRFAAAAADjb0FzPFXVrye5M8mmJJd3lw/22BcAAMBYMW8QwM4WOuLpFUmOaK19vc9mAAAAxpmQCeChFnpWu9uSfLPPRgAAAACYLPOOeKqqV3dXv5TkY1V1eZL7dtzfWntTj70BwIOcARNg8nhfB5h8uzrU7tHdv7d2l327CwAsOV9GACbHJJ+xeZL4ww+wu+YNnlprr1+qRgDYM+wgAgB7kn0IYHcsaHLxqtqU5Odba/d0tx+b5NLW2kk99gbAw2QHEQAAWA4WOrn4gTtCpyRprX0jyRN66QgAAACAibDQ4Gl7VR2640ZV/WCS1k9LAAAAAEyCBR1ql+R3kvxdVf11kkryE0nO7q0rmADm2AEAAGDodjniqar2SvIDSZ6Z5LIklyb50dbalT33BmNrvrO0AAAAwFDscsRTa+2Bqvqt1tq7k3xwCXoCAAAAYAIsdI6n/1NVv1lVh1TVATsuvXbGTuY6TMvhWwAAAMBytNA5nl7Q/fuyabWW5P/as+2wK0ImAACA3WdOVlgaCxrx1Fp78iwXoRMAAABjx5yssHQWNOKpql4yW7219s492w4AAAAAk2Khh9r92LTr+yV5dpJPJRE8AQAAADCrBQVPrbVfn367qlYlubSPhgAAgMm3ZcOp5tgBGICFjnia6dtJnrwnGwEAAIZFyAQw+RY6x9NfZOosdsnUhORPS/LuvppiePy1CwAAACbPQkc8/f606/cn+Upr7fYe+mGA5jujhPAJmHSC9/HhtQIAWLy95ruzqvarqlcm+fkkT01yVWvtqoWETlV1UVXdVVWfmVY7oKo2VdXN3b+P7epVVW+uqluq6saqeua0x5zZLX9zVZ05rf6jVbW5e8ybq6oWv/rQj7m+iPiCAkznVM7jw2sFAPDw7GrE0zuSfD/J3yZ5bqYOsXvFAp/77Un+f3nome/WJ/lIa21DVa3vbv9299yHd5djkrwlyTFVdUCS85KszdShftdV1Qdaa9/oljkryTVJrkhycpK/XGBv0DshEzBkP/Say3N/++fbe1dyyxu9LwIADM28I56SPK21dkZr7X8neX6Sn1joE7fW/ibJ3TPKp2UqzEr377pp9Xe2KVcnWVVVT0xyUpJNrbW7u7BpU5KTu/se01q7urXWMhVurQsAMHIzQ6ckub9N1QEAGJZdBU/f33GltXb/Hvh5B7XW7uiu/0OSg7rrq5PcNm2527vafPXbZ6nPqqrOrqprq+rar33ta7u3BgDAvGaGTruqAwAwuXYVPP1IVd3bXb6V5Bk7rlfVvbvzg7uRSkuyC9pae2trbW1rbe2BBx64FD8SAACAZcqcrLB05p3jqbW2Yg//vDur6omttTu6w+Xu6upbkxwybbmDu9rWJCfMqH+sqx88y/IAAACwS0ImWBq7GvG0p30gyY4z052Z5P3T6i/pzm53bJJvdofkXZnkOVX12O4MeM9JcmV3371VdWx3NruXTHsuAAAAAJaBXZ3V7mGrqndlarTS46vq9kydnW5DkndX1S8l+UqSX+gWvyLJKUluSfKdJC9Nktba3VX1e0k+2S33u621HROW/1qmzpy3MlNns3NGOwAAAIBlpLfgqbV2+hx3PXuWZVuSl83xPBcluWiW+rVJnr47PQIAAADQn6U+1A4AAACAgehtxBMAML8tG07NmvWXz1oHYDx5Xwd4KMETAIyQLyMAk2O20GlH3fs9MFSCJ0bOX/wZNdvf+HjGeR/Kvfdtf/D2Yx6xIje+/uQRdgQAAMxH8MSy4Es+o+Ivk+NjZuiUJPfetz3POO9DwicA6JE/0gG7Q/AEMIEmcQdxZui0qzoAsPv8kQ7YXc5qBzBh5ttBBB6eub5c+dIFADA/I54AgD3q+MMOyFVfvHvW+jgTMgEALJ4RTwDAHnXJWcftFDIdf9gBueSs40bUEQAAo2LEE/RkEufYAVgoIRMAAIngaewIM8aDSRgBAADAoXZjxYTBAAAAwDgx4gkARshIVgAYDZ/BsDSMeAIGzSnSGSUjWQFgNHwGw9Ix4gkYPCETAIyGEScAk8+IJwAAYMkZcQIwDIInAACAPcAh/AA7c6gdAADAHiJkAngowRMAY2HLhlPNBQJ7mN8pAKBvgicAxoYvxLDnzDe/jt81YAd/+AF2l+AJYMLYQQQA9iT7EMDuEDxBD3zxZ9RsawAAwHIgeIKe+OIP7IqQGgCASSd4AgbPF39GybYGAEvvD19wVF552Q2z1oE9a69RN8DCzfXlxJcWePjmm1wXAIDJtO7o1fnDFxyV1atWppKsXrUyf/iCo7Lu6NWjbg0mjhFPY2ZSQyYjTgAAgKW07ujVgiZYAkY8MXJGnAAAAMBkEjwBAAyQQ/gZtcc8YsWi6gCMJ4faAQAMlJCJUbrx9SfnGed9KPfet/3B2mMesSI3vv7kEXYFwJ4meAIAAEZCyAQw+RxqBwAAAEAvBE8AAAAA9ELwBAAAAEAvBE/AoDmrEwAAQH9MLg4MnpCJUVqz/vKdarZJlortDwDomxFPADAis33pn68Oe5LtDwBYCoInAAAAAHoheAIAAACgF+Z4YuS2bDh1IueYmMR1AgAAgMUQPLEsTFogM9+8GZO2rgAAADAXh9oBAAAA0AsjngAAABicY96wKXd+63sP3j7o0fvmmnNPHGFHMJkET8DgmY8LWIhnnPeh3Hvf9gdvP+YRK3Lj608eYUcAPFwzQ6ckufNb38sxb9gkfII9zKF2wKDNNx8X8PC96MKPZ836yx+8vOjCj4+6pd0yM3RKknvv255nnPehEXW0++YK2AXvwBDMDJ12VQcePiOeAGBEJvWsni+68OO56ot3P6R21Rfvzosu/HguOeu4EXW1e2aGTruqj4tx39YAgOVP8AQAIzSJX/xnhk67qgMAMLkcagcAAABAL0YSPFXVlqraXFU3VNW1Xe2AqtpUVTd3/z62q1dVvbmqbqmqG6vqmdOe58xu+Zur6sxRrAsAAAAAsxvloXY/2Vr7x2m31yf5SGttQ1Wt727/dpLnJjm8uxyT5C1JjqmqA5Kcl2Rtkpbkuqr6QGvtG0u5EgAAADtM4tx9ALtjOc3xdFqSE7rr70jysUwFT6cleWdrrSW5uqpWVdUTu2U3tdbuTpKq2pTk5CTvWtq2AVgqT15/edq025Xky3bmAVgm5jtb7jiHT8I0YHeMao6nluTDVXVdVZ3d1Q5qrd3RXf+HJAd111cnuW3aY2/vanPVd1JVZ1fVtVV17de+9rU9tQ4wJ6eoZtSmn8Z+x2XczQydkqkPkydPwLoBwHI1X5gGsBCjGvH04621rVX1hCSbquoL0+9srbWqmvn94mFrrb01yVuTZO3atXvseWE+QiZGZVL/2jrXm7c3dXj4jGIAhuoxj1iRe+/bPmsd2LNGMuKptba1+/euJO9L8qwkd3aH0KX7965u8a1JDpn28IO72lx1gAUzOg0YKqMYgCG78fUn7xQyPeYRK3Lj608eUUcwuZZ8xFNV7Z9kr9bat7rrz0nyu0k+kOTMJBu6f9/fPeQDSV5eVZdmanLxb7bW7qiqK5P8lx1nv+ue5zVLuCoj4S+TsOf5HQIAGB4hEyyNUYx4OijJ31XVp5N8IsnlrbUPZSpwOrGqbk7y093tJLkiyZeS3JLkwiS/liTdpOK/l+ST3eV3d0w0Pqn8ZRIAAAAYJ0s+4qm19qUkPzJL/etJnj1LvSV52RzPdVGSi/Z0jwAAQP+M5geYfKOaXBwAiC9dwHBN6skwAHiokUwuDgA4hHqcHH/YAYuqAwAwRfAEAOxRZxx76KLq4+CSs47bKWQ6/rADcslZx42oIwCA8eBQOwBgjzp/3ZFJknddc1u2t5YVVTn9mEMerI8rIRMAwOIJngCAPe78dUeOfdA06bZsONUcYwATxvs6y5HgiWXBGySjZPsDhsp7HcDkMGE/y5U5nhg5k+sySrY/AACA/gieABgLtcg6ACy1uUaVGG0CDJlD7YBFcVgao/LlDafmyesvT5tWq64OAMvFpO0XmQ8O2F2CJ2DBHDc+HiZ5B1HIBABLbxL2IYDRETwBTCA7iONhkkNCAABIBE9jxRcUgMnjPZxRsl8BAPRN8DRm7AyODzvzACxnDp9m1M449tBcfPWts9aBxTNQgeXKWe2gB/PtzAMAkJy/7sicceyhWVFT5yddUZUzjj005687csSdwXjyHYTlyognAABgJM5fd6SgCWDCGfEELNhcw3THefjuJK4TAAC79tqNm3PYa67ImvWX57DXXJHXbtw86pZgIhnxBCzYpM4HMs69AwCweK/duPkhc4xtb+3B20bhwZ5lxBMAAACD8qfX7Dyx/Xx14OETPDFyDnUCAACW0gNtcXXg4XOoHcuCkAkAAAAmjxFPAAAAMOYcScJyJXgCABggX1AAgKXgUDsAGKHZzhbpiz9LxbYGMDkm9QzUjD8jnoAF89dx2LPm20EEAPpz/GEHLKoOPHyCJ+jBpAY0viQDADAJLjnruJ1CpuMPOyCXnHXciDqCyeVQO+jJuIdMQ+JQJwCA4REywdIw4gkYNKO4AAAA+iN4AgAAAKAXDrUDABioST3UeFLXC2A+Wzac6v2PZcmIJwCAAZrUQ40ndb0AYFwJngAAAGDMCd5ZrgRPwILNNUzX8F0AAABmI3gCFsxfUWDPEuYCADDpTC4OACMkZAIAYJIZ8QQMmhEnAAAA/THiCRg8IRMAAEA/jHgCAAAAoBdGPAEADNCWDafOenIIo0CXJ68VsCve11muBE/AgvkwA5gs3r/Hw3xnlfUaArDcOdQOAAAAxtx8ITWMkuAJWDAfZgAAACyGQ+0AAAAAltCQpjAx4gkAAABgiQztSBLBEwAAAAC9EDwBAAAA0AvBEwAAAIy5ueYHmtR5gxgfJhcHFmzLhlMHNQkeAACME/vlLEeCJ2BRfJgBAABLyR+/x9vYH2pXVSdX1U1VdUtVrR91PwAAAMCeMbQzwE2isQ6eqmpFkv+Z5LlJnpbk9Kp62mi7AgAAACAZ8+ApybOS3NJa+1Jr7XtJLk1y2oh7AgBgREyuCwDLy7jP8bQ6yW3Tbt+e5JiZC1XV2UnOTpJDDz10aToDAGAkhEwAsHyM+4inBWmtvbW1tra1tvbAAw8cdTsAALBgRnEBTJahva+P+4inrUkOmXb74K4GAAATY1K/jAAM1ZDe18d9xNMnkxxeVU+uqn2TvDDJB0bcEwAAALAHDG100CQa6xFPrbX7q+rlSa5MsiLJRa21z464LQAAAGAPETKNt7EOnpKktXZFkitG3QcAAAAADzXuh9oBAAAAsEwJngAAAADoheAJAAAAgF4IngAAAADoheAJAAAAgF4IngAAAADoheAJAAAAgF5Ua23UPSypqvpakq+Mug+Whccn+cdRN8GyYptgNrYLZrJNMJNtgtnYLpjJNsFsJmm7+MHW2oEzi4MLnmCHqrq2tbZ21H2wfNgmmI3tgplsE8xkm2A2tgtmsk0wmyFsFw61AwAAAKAXgicAAAAAeiF4YsjeOuoGWHZsE8zGdsFMtglmsk0wG9sFM9kmmM3EbxfmeAIAAACgF0Y8AQAAANALwRMAAAAAvRA8MbGq6pCq+mhVfa6qPltVr5hlmROq6ptVdUN3+c+j6JWlVVVbqmpz95pfO8v9VVVvrqpbqurGqnrmKPpkaVTVEdPeA26oqnur6pUzlvFeMQBVdVFV3VVVn5lWO6CqNlXVzd2/j53jsWd2y9xcVWcuXdf0aY5t4oKq+kL3+fC+qlo1x2Pn/axhfM2xXbyuqrZO+5w4ZY7HnlxVN3X7GOuXrmv6NMc2cdm07WFLVd0wx2O9V0youb6PDnHfwhxPTKyqemKSJ7bWPlVVj05yXZJ1rbXPTVvmhCS/2Vr7mdF0yShU1ZYka1tr/zjH/ack+fUkpyQ5Jsn/aK0ds3QdMipVtSLJ1iTHtNa+Mq1+QrxXTLyq+tdJ/inJO1trT+9q/y3J3a21Dd2XxMe21n57xuMOSHJtkrVJWqY+b360tfaNJV0B9rg5tonnJPmr1tr9VfVfk2TmNtEttyXzfNYwvubYLl6X5J9aa78/z+NWJPn7JCcmuT3JJ5OcPn3flPE02zYx4/4/SPLN1trvznLflnivmEhzfR9N8u8zsH0LI56YWK21O1prn+qufyvJ55OsHm1XjInTMrXj0FprVydZ1X1wMPmeneSL00MnhqO19jdJ7p5RPi3JO7rr78jUDuNMJyXZ1Fq7u9sh3JTk5L76ZOnMtk201j7cWru/u3l1koOXvDFGao73ioV4VpJbWmtfaq19L8mlmXqPYczNt01UVSX5hSTvWtKmGLl5vo8Obt9C8MQgVNWaJEcnuWaWu4+rqk9X1V9W1Q8vbWeMSEvy4aq6rqrOnuX+1Ulum3b79ggth+KFmXvH0HvFMB3UWruju/4PSQ6aZRnvGcP1H5L85Rz37eqzhsnz8u4QzIvmOHTGe8Uw/USSO1trN89xv/eKAZjxfXRw+xaCJyZeVT0qyZ8neWVr7d4Zd38qyQ+21n4kyf+TZOMSt8do/Hhr7ZlJnpvkZd3waAauqvZN8rNJ3jPL3d4rSJuan8AcBSRJqurcJPcnuWSORXzWDMtbkhyW5KgkdyT5g5F2w3JyeuYf7eS9YsLN9310KPsWgicmWlXtk6lf8ktaa++deX9r7d7W2j91169Isk9VPX6J22SJtda2dv/eleR9mRr6Pt3WJIdMu31wV2OyPTfJp1prd868w3vFoN2541Db7t+7ZlnGe8bAVNW/T/IzSV7U5pgwdQGfNUyQ1tqdrbXtrbUHklyY2V9v7xUDU1V7J/m5JJfNtYz3isk2x/fRwe1bCJ6YWN3x1G9L8vnW2pvmWOZfdMulqp6Vqd+Jry9dlyy1qtq/m9wvVbV/kuck+cyMxT6Q5CU15dhMTQZ5R5h0c/5F0nvFoH0gyY4zyZyZ5P2zLHNlkudU1WO7w2ue09WYQFV1cpLfSvKzrbXvzLHMQj5rmCAz5oJ8XmZ/vT+Z5PCqenI3yvaFmXqPYXL9dJIvtNZun+1O7xWTbZ7vo4Pbt9h71A1Aj45P8uIkm6edvvR3khyaJK21/5Xk+Ul+taruT7ItyQvn+sslE+OgJO/rMoS9k/xpa+1DVfUryYPbxRWZOqPdLUm+k+SlI+qVJdLt7J2Y5Jen1aZvE94rBqCq3pXkhCSPr6rbk5yXZEOSd1fVLyX5SqYmiE1VrU3yK621/9hau7uqfi9TXyqT5Hdbaw9n4mGWmTm2idckeUSSTd1nydWttV+pqicl+ePW2imZ47NmBKtAD+bYLk6oqqMydcjMlnSfJ9O3i+5MiC/P1JfHFUkuaq19dunXgD1ttm2itfa2zDJ3pPeKQZnr++jg9i3KfjMAAAAAfXCoHQAAAAC9EDwBAAAA0AvBEwAAAAC9EDwBAAAA0AvBEwAAAAC9EDwBAAAA0AvBEwAwkapqe1XdUFWfqar3VNUjd+O5PlZVax/G41ZV1a8tYLmnVNUVVXVzVX2qqt5dVQfNs/yaqvrFxfbTt6p6eVXdUlWtqh4/6n4AgNETPAEAk2pba+2o1trTk3wvya9Mv7Oq9l6CHlYlmTd4qqr9klye5C2ttcNba89M8kdJDpznYWuS9B48VdWKRT7kqiQ/neQrPbQDAIwhwRMAMAR/m+SHquqEqvrbqvpAks9V1X5V9SdVtbmqrq+qn0ySqlpZVZdW1eer6n1JVu54oqr6p2nXn19Vb++uH1RV76uqT3eXf5VkQ5LDupFXF8zR2y8m+Xhr7S92FFprH2utfaYb2fS33SioT3XPme55f6J73ldV1YqquqCqPllVN1bVL3c97VVVf1RVX6iqTd2oqud39z27W+fNVXVRVT2iq2+pqv9aVZ9Ksr77d8f6Hj799kyttetba1sW9pIAAEOwFH/pAwAYmW5k03OTfKgrPTPJ01trX66q30jSWmtHVtVTk3y4qp6S5FeTfKe19i+r6hlJ5gxbpnlzkr9urT2vGyn0qCTru5911DyPe3qS6+a4764kJ7bWvltVhyd5V5K13fP+ZmvtZ7p1PDvJN1trP9YFSFdV1YeT/GimRkc9LckTknw+yUXdKKu3J3l2a+3vq+qd3Tr/Yfdzv96NvEpV/XRVHdVauyHJS5P8yQL+LwAAkhjxBABMrpVVdUOSa5PcmuRtXf0TrbUvd9d/PMnFSdJa+0KmDhF7SpJ/Pa1+Y5IbF/DzfirJW7rHbG+tfXMPrMM+SS6sqs1J3pOpAGk2z0nykm59r0nyuCSHZ2r93tNae6C19g9JPtotf0SSL7fW/r67/Y5MrfMOl027/sdJXtqFaS9I8qe7vVYAwGAY8QQATKptM0caVVWSfHs3n7dNu77fbj5Xknw2yb+Z475XJbkzyY9k6g+G351juUry6621Kx9SrDrlYfY0/f/oz5Ocl+SvklzXWvv6w3xOAGCAjHgCAIbsb5O8KJk6s1ySQ5PclORv0k3eXVVPT/KMaY+5s6r+ZVXtleR50+ofydThaunmXPqBJN9K8uhd9PCnSf5VVZ26o1BV/7r7uT+Q5I7W2gNJXpxkx2TfM5/3yiS/WlX77FiXqto/U5N9/7turqeDkpzQLX9TkjVV9UPd7Rcn+evZmmutfbd7/rfEYXYAwCIJngCAIfujJHt1h7JdluTft9buy1TI8qiq+nyS381D52Ban+SDSf6/JHdMq78iyU92z3Vdkqd1o4OuqqrPzDW5eGttW5KfSfLrVXVzVX0uU2fC+1rX35lV9ekkT80/j0S6Mcn2bhLzV2XqcLjPJflUVX0myf/O1Mj2P09ye3ffxZmaq+qbXZj00iTv6fp9IMn/muf/6ZJumQ/Ps0yq6v+uqtuTHJzkxqr64/mWBwAmX7XWdr0UAABjqaoe1Vr7p6p6XJJPJDm+m+9pMc/xm0l+oLX2n3ppEgCYWOZ4AgCYbB+sqlVJ9k3yew8jdHpfksMyNXk6AMCiGPEEALAEqurIJP/vjPJ9rbVjRtHP7ujCqCfPKP/2zMnNAQAETwAAAAD0wuTiAAAAAPRC8AQAAABALwRPAAAAAPRC8AQAAABALwRPAAAAAPRC8AQAAABALwRPAAAAAPRC8AQAAABALwRPAAAAAPRC8AQAAABALwRPAAAAAPRC8AQAAABALwRPAAAAAPRC8AQAAABALwRPAAAAAPRC8AQAAABALwRPAAAAAPRC8AQAAABALwRPAAAAAPRC8AQAAABALwRPAAAAAPRC8AQAAABALwRPAAAAAPSit+Cpqg6pqo9W1eeq6rNV9Yqu/rqq2lpVN3SXU6Y95jVVdUtV3VRVJ02rn9zVbqmq9dPqT66qa7r6ZVW1b1/rAwAAAMDiVGutnyeuemKSJ7bWPlVVj05yXZJ1SX4hyT+11n5/xvJPS/KuJM9K8qQk/yfJU7q7/z7JiUluT/LJJKe31j5XVe9O8t7W2qVV9b+SfLq19pb5+nr84x/f1qxZs4fWEgAAAIDrrrvuH1trB86s793XD2yt3ZHkju76t6rq80lWz/OQ05Jc2lq7L8mXq+qWTIVQSXJLa+1LSVJVlyY5rXu+n0ryi90y70jyuiTzBk9r1qzJtdde+/BWCgAAAICdVNVXZqsvyRxPVbUmydFJrulKL6+qG6vqoqp6bFdbneS2aQ+7vavNVX9ckntaa/fPqM/288+uqmur6tqvfe1re2KVAAAAANiF3oOnqnpUkj9P8srW2r2ZGpF0WJKjMjUi6g/67qG19tbW2trW2toDD9xp1BcAAAAAPejtULskqap9MhU6XdJae2+StNbunHb/hUk+2N3cmuSQaQ8/uKtljvrXk6yqqr27UU/TlwcAAABgxPo8q10leVuSz7fW3jSt/sRpiz0vyWe66x9I8sKqekRVPTnJ4Uk+kanJxA/vzmC3b5IXJvlAm5oV/aNJnt89/swk7+9rfQAAAABYnD5HPB2f5MVJNlfVDV3td5KcXlVHJWlJtiT55SRprX22O0vd55Lcn+RlrbXtSVJVL09yZZIVSS5qrX22e77fTnJpVZ2f5PpMBV0AAAAALAM1NXBoONauXduc1Q4AAABgz6mq61pra2fWl+SsdgAAAAAMj+AJAAAAgF4IngAAAADoRZ+TiwN70Mbrt+aCK2/KV+/ZlietWplzTjoi645ePeq2gB6tWX/5TrUtG04dQScA/Rvye94zzvtQ7r1v+4O3H/OIFbnx9SePsKOlNeTXfsjrznAY8QRjYOP1W/Oa927O1nu2pSXZes+2vOa9m7Px+q2jbg3oyWw7ovPVAcbZkN/zZoZOSXLvfdvzjPM+NKKOltaQX/shrzvDIniCMXDBlTdl2/cfukOy7fvbc8GVN42oIwAA9oSZodOu6gDjRvAEY2DrPdsWVQcAAIDlQPAEY6AWWQcAAIDlQPAEY6Atsg4AAADLgeAJAAAAgF4InmAMPPaR+yyqDgAAAMuB4AnGwHn/9oezYq+Hzui0Yq/Kef/2h0fUEQAAAOya4AnGxMxfVr+8AAAALHe+u8IYuODKm/L9Bx46lfj3H2i54MqbRtQRAAAA7JrgCcbAV+/Ztqg6AAAALAeCJxgDT1q1clF1AAAAWA4ETzAGzjnpiKzcZ8VDaiv3WZFzTjpiRB0BAADAru096gaAXVt39OokU3M9ffWebXnSqpU556QjHqwDAADAciR4gjGx7ujVgiYAgAmz34rKd7e3WesAk8ChdgCwDG3ZcOqi6gDjbMjveV94wyk7hUz7rah84Q2njKgjlsqQt3uGpVrbOV2fZGvXrm3XXnvtqNsAAAAYvDXrL5/zPgEMjJequq61tnZm3YgnAAAAAHoheAIAAACgF4InAAAARuKMYw9dVB0YP85qBwAAwEicv+7IJMm7rrkt21vLiqqcfswhD9aB8WdycQAAAAB2i8nFAQAAAFhSgicAAAAAeiF4AgAAAKAXgicAAAAAeuGsdjAmNl6/NRdceVO+es+2PGnVypxz0hFZd/TqUbcF9GjN+st3qm3ZcOoIOgEA+jD0z/qhr/9QGPEEY2Dj9VvzqstuyNZ7tqUl2XrPtrzqshuy8fqto24N6MlsO2Lz1QGA8TL0z/qhr/+QCJ5gDPzmez6dNqPWujoAAAAsV4InGAP3PzAzdpq/DgAAAMuB4AkAAACAXgieAAAAAOiFs9oBAMAy4Sy2AEwawRMAACwDG6/fmle/+4bsmMJx6z3b8up335AkwicAxpZD7QAAYBn47T+/MTPPG/JAm6oDwLgSPAEAwDJw3/0PLKoOAOPAoXYAAMvMmvWX71TbsuHUEXSy9Ia87kNnfiuAyWTEEwDAMjJb8DJffZIMed2HbuP1W/Oa927O1nu2pWVqfqvXvHdzNl6/ddStAbCbBE8AAMBIXXDlTdn2/e0PqW37/vZccOVNI+oIgD1F8AQAAIzU1nu2LaoOwPgQPAEAAADQC8ETAAAAAL0QPAEAAADQi96Cp6o6pKo+WlWfq6rPVtUruvoBVbWpqm7u/n1sV6+qenNV3VJVN1bVM6c915nd8jdX1ZnT6j9aVZu7x7y5qqqv9QEAAABgcfoc8XR/kt9orT0tybFJXlZVT0uyPslHWmuHJ/lIdztJnpvk8O5ydpK3JFNBVZLzkhyT5FlJztsRVnXLnDXtcSf3uD4AANCb4w87YFF1ABgHvQVPrbU7Wmuf6q5/K8nnk6xOclqSd3SLvSPJuu76aUne2aZcnWRVVT0xyUlJNrXW7m6tfSPJpiQnd/c9prV2dWutJXnntOcCAICxcslZx+0UMh1/2AG55KzjRtQRQH/OOPbQRdUZX3svxQ+pqjVJjk5yTZKDWmt3dHf9Q5KDuuurk9w27WG3d7X56rfPUp/t55+dqVFUOfRQGzEAAMuTkAkYivPXHZkkedc1t2V7a1lRldOPOeTBOpOj9+Cpqh6V5M+TvLK1du/0aZhaa62qWt89tNbemuStSbJ27dref16f1qy/fKfalg2njqATltLqVSuz9Z5ts9aHYsjb/pDXHYBhGPq+ztA/64e+/kN28dW3Pnh9e2u5+OpbBxM8DWm77/WsdlW1T6ZCp0taa+/tynd2h8ml+/eurr41ySHTHn5wV5uvfvAs9Yk124Y5X30Snfimj2XN+ssfvJz4po+NuqUl8ch9Z/9Vnas+aYa87Q953QEYjq9/67uLqk+SoX/WD339h2zIr/3Q1r3Ps9pVkrcl+Xxr7U3T7vpAkh1npjszyfun1V/Snd3u2CTf7A7JuzLJc6rqsd2k4s9JcmV3371VdWz3s14y7bmYQCe+6WO5+a5vP6R2813fHkT4NHO9d1UHABgn390++0EJc9UBGB99Hmp3fJIXJ9lcVTd0td9JsiHJu6vql5J8JckvdPddkeSUJLck+U6SlyZJa+3uqvq9JJ/slvvd1trd3fVfS/L2JCuT/GV3YUIJXwAAAGC89BY8tdb+LknNcfezZ1m+JXnZHM91UZKLZqlfm+Tpu9EmAMCysmXDqYOa9wEAmGxLclY7AAAWTsgEAEyKYcxMDAAAAMCSEzwBAAAA0AvBEwAAAAC9EDwBAAAA0AvBEwAAAAC9EDwBAAAA0AvBEwAAAAC9EDwxNg569L6LqgMAAACjJXgaI1s2nLqo+qS55twTdwqZDnr0vrnm3BNH1BFLZcjb/pDXHRge73kAMHn2HnUDLM7Qd7yGGjKtXrUyW+/ZNmt9KIa87Q953YHh8Z4HAJPFiCcYA2seN3vANFcdAAAAlgPBE4yBq7/0jUXVAQAAYDkQPMEY2N7aouoAAACwHAieAAAARuTwJ+y/qDrAuBE8AQAAIzXkMxpuevUJO4VMhz9h/2x69QmjaQhgD3NWOxgDzmoHAEy6IYRMcxEyMUT777si3/7e9lnrk27Vyn1yz7bvz1qfREY8wRg456QjsnKfh74Br9xnRc456YgRdQT0bch//QeAITjo0fsuqj5p3vC8I7Nir3pIbcVelTc878gRdbR0XvezP5x9Zqz7PntVXvezPzyijvplxBOMgXVHr06SXHDlTfnqPdvypFUrc85JRzxYByaTkAmASfeYR6zIvfftPOrlMY+Y/FEv15x7Yo55w6bc+a3vPVg76NH75ppzTxxhV0tnyN9xhrbu1QZ2Vqy1a9e2a6+9dtRtAAAAkOQZ533oIeHTYx6xIje+/uQRdgQ8HFV1XWtt7cy6EU8AsEy9duPmvOua27K9tayoyunHHJLz103+8HMAhmXIIdOLLvx4rvri3Q/ePv6wA3LJWceNsCPY8wRPMCZ8AYVhee3Gzbn46lsfvL29tQdv+90HgPE3M3RKkqu+eHdedOHHBxM+rVl/+U41Uw1MHpOLwxjY8QV0e3do7I4voK/duHnEnQF9mR46LaQOAIyXmaHTruqTZrbQab4640vwBGPAF1AAAADGkeAJAAAAgF6Y4wkAAJaJp557Rb67/Z/POr3fisoX3nDKCDsCgN1jxBMAACwDM0OnJPnu9pannnvFiDoCgN0neAIAgGVgZui0qzoAjAOH2gEALDMbr9+aC668KV+9Z1uetGplzjnpiKw7evWo21oSQ153AJhEgicAgGVk4/Vb88rLbnjw9tZ7tj14e9IDmCGvO0JHgEnlUDsAgGVkevCykPokGfK6D93G67fmnD/7dLbesy0tU6HjOX/26Wy8fuuoWwNgNxnxxFhZs/7ynWpbNpw6gk5YakN+7f0FmCEa8u88DNHr/+Kz+f6Muay+v73l9X/x2UF85r124+a865rbsr21rKjK6ccckvPXHTnqtpaM93yG6EUXfjxXffHuB28ff9gBueSs40bYUX+MeGJszPaBNF+dyTHk137HYSfT/wL8ystu8BdgJtqQf+dhqL7xne8vqj5JXrtxcy6++tZsb1PB2/bWcvHVt+a1GzePuLOl4T2fIZoZOiXJVV+8Oy+68OMj6qhfgieAZeyc99ywqDoAMF4uvvrWRdWB8TczdNpVfdwJngCWse8/sLg6AADAciJ4AgAARmqvWlwdgPEheAIAAEbqgba4OgDjw1ntxowzPgAAAADjwoinMeKMDwAAAMA4ETwBAAAA0AvBEwAAAAC9EDwBAAAA0AvBEwAAAAC9EDwBACwjc52t1llsJ9/xhx2wqDoAjIO9R90AAMB0WzacOusZW4cUvAxpXflnl5x1XF504cdz1RfvfrB2/GEH5JKzjhthVwCwewRPAMCyI3hhqIRMAEwah9oBAAAA0AvBEwAAAAC96C14qqqLququqvrMtNrrqmprVd3QXU6Zdt9rquqWqrqpqk6aVj+5q91SVeun1Z9cVdd09cuqat++1gUAAACAxetzxNPbk5w8S/2/t9aO6i5XJElVPS3JC5P8cPeYP6qqFVW1Isn/TPLcJE9Lcnq3bJL81+65fijJN5L8Uo/rAgAAAMAi9RY8tdb+Jsndu1xwymlJLm2t3dda+3KSW5I8q7vc0lr7Umvte0kuTXJaVVWSn0ryZ93j35Fk3Z7sHwAAAIDdM4o5nl5eVTd2h+I9tqutTnLbtGVu72pz1R+X5J7W2v0z6rOqqrOr6tqquvZrX/vanloPltgZxx66qDoAAAAwWksdPL0lyWFJjkpyR5I/WIof2lp7a2ttbWtt7YEHHrgUP7IXc51aeiinnD5/3ZE549hDs6IqSbKiKmcce2jOX3fkiDvrXy2yPmmGvO0Ped2B4fGexxAd/oT9F1UHGDd7L+UPa63dueN6VV2Y5IPdza1JDpm26MFdLXPUv55kVVXt3Y16mr78RBv6jtf5644cRNA0U1tkfRINedsf8roDw+M9j6G5+a5vL6oOMG6WdMRTVT1x2s3nJdlxxrsPJHlhVT2iqp6c5PAkn0jyySSHd2ew2zdTE5B/oLXWknw0yfO7x5+Z5P1LsQ4AAAAALExvI56q6l1JTkjy+Kq6Pcl5SU6oqqMyNVBjS5JfTpLW2mer6t1JPpfk/iQva61t757n5UmuTLIiyUWttc92P+K3k1xaVecnuT7J2/paFwAAAAAWr7fgqbV2+izlOcOh1tobkrxhlvoVSa6Ypf6lTJ31DgAAAGAsrF61Mlvv2TZrfRKN4qx2wCIdf9gBi6oDAAAsZ0OeWP+ck47Iyn1WPKS2cp8VOeekI0bUUb8ETzAGPnfHtxZVBwAAWM42vfqEnUKmw5+wfza9+oTRNLSE1h29Om/8uSOzetXKVKZGOr3x547MuqNXj7q1XizpWe2Ah+cb3/n+ouoAAADL3RBCprmsO3r1xAZNMxnxBAAAAEAvBE8AAAAA9MKhdjAGHvvIfWY9rO6xj9xnBN2Mxpr1l+9U27Lh1BF0AgD9ecZ5H8q9921/8PZjHrEiN77+5BF2BAC7x4gnGANDn+NpttBpvjoAjKOZoVOS3Hvf9jzjvA+NqCMA2H2CJwAAWAZmhk67qgPAOFhQ8FRVT6mqj1TVZ7rbz6iq1/bbGgAAAADjbKEjni5M8pok30+S1tqNSV7YV1MAAABDcMaxhy6qDjBuFjq5+CNba5+oqum1+3voB+ZlgmmGyHbPENnugaE4f92RufjqW2etM9m2bDh18J93Q17/Ia37Qkc8/WNVHZakJUlVPT/JHb11BbMwwTRDZLtniGz3wJB4zxuuob/2Q17/oa37Qkc8vSzJW5M8taq2JvlykjN66woAAACAsbeg4Km19qUkP11V+yfZq7X2rX7bAgAAAGDcLfSsdq+oqsck+U6S/15Vn6qq5/TbGgAAMATHH3bAouoAjI+FzvH0H1pr9yZ5TpLHJXlxkg29dQUAAAzGJWcdt1PIdPxhB+SSs44bUUcA7CkLneNpx+nsTknyztbaZ2vGKe4AANgzhnSmm5l+6DWX5/72z7f3ruSWNw5j3Yfu59cemi1f35av3rMtT1q1Mj+/9tBRtwTAHrDQEU/XVdWHMxU8XVlVj07yQH9tAQAM09DOdDPdzNApSe5vU3Um28brt+Y33vPpbL1nW1qSrfdsy2+859PZeP3WUbcGwG5aaPD0S0nWJ/mx1tp3kuyb5KW9dQUAwODMDJ12VWdynPu+zdn+wENf6O0PtJz7vs0j6giAPWWhZ7V7oKq+nOQpVbVfzz0BAAAD8u3vbV9UHYDxsaDgqar+Y5JXJDk4yQ1Jjk3y8SQ/1VtnAAAAAIy1hR5q94okP5bkK621n0xydJJ7+moKAAAAYBLtt2L2c7XNVR93Cw2evtta+26SVNUjWmtfSHJEf20BkCR/+IKjFlWHSTC0nTFg2I4/7IBF1YHx94U3nLLTfs1+KypfeMMpI+qoXwsNnm6vqlVJNibZVFXvT/KVvppibmvWX77TZSjmOo30UE4vPWRDfu3XHb16UXWYBEPbGQOG7ZKzjltUfdIMeT+PYbtve5v39iRZUPDUWntea+2e1trrkvynJG9Lsq7HvpjFkE+vnCSv3Tj7WU3mqjM5hrztD3ndGbYvvOGUbNlw6oMXoRMwqYb+WT/09WeYnrz+8syMmVpXn0QLHfGUqlpRVU9K8uVMTTD+L/pqCmZz8dW3LqoOAAAAy81cY5smdczTQs9q9+tJzktyZ5IHunJL8oye+gIAAABgzC0oeMrUWe2OaK19vc9mAABgqPZdUfneLHN87GtifQDG2EIPtbstyTf7bAQAAIbsvz3/RzIzYqquDgDjat4RT1X16u7ql5J8rKouT3Lfjvtba2/qsTcAABiMHWcsveDKm/LVe7blSatW5pyTjnAmUwDG2q4OtXt09++t3WXf7gIAAOxh645eLWgCYKLMGzy11l6/VI0AAJBs2XDqrKcR37Lh1BF0AwCwexZ6VrtNSX6+tXZPd/uxSS5trZ3UY28AAIMkZAIAJsVCJxc/cEfolCSttW8keUIvHQEAAAAwERYaPG2vqkN33KiqH0yy87leAQAAAKCzoEPtkvxOkr+rqr/O1FldfyLJ2b11BQAAA2R+LwAmzS5HPFXVXkl+IMkzk1yW5NIkP9pau7Ln3uAhzjj20EXVAQDGyWyh03x1ABgHuwyeWmsPJPmt1to/ttY+2F3+cQl6g4c4f92ROePYQ7OiKkmyoipnHHtozl935Ig7AwBgdxz+hP0XVQdgfCx0jqf/U1W/WVWHVNUBOy69dsZO5hpmPaTh1+evOzJffOMp2bLh1HzxjacInZh4fu+BIfGeN1z/+E/fW1R9ktjugUm30DmeXtD9+7JptZbk/9qz7bArPoBgePzeA0PiPW+YvvGd7y+qPmls98AkW1Dw1Fp7ct+NAAAAADBZFhQ8VdVLZqu31t65Z9sBAAAAJt1eSR6Yoz7pHvvIfWYd0fnYR+4zgm76t9DX9MemXX4iyeuS/GxPPQEAAMBE+8MXHLWo+qR50xzrOVd9kpz3b384+6yoh9T2WVE579/+8Ig66tdCD7X79em3q2pVkkv7aAgAAAAm3bqjVydJLrjypnz1nm150qqVOeekIx6sT7ohr//Q1n2hk4vP9O0k5n0CAACAh2nd0asnNmxYiCGv/5DWfaFzPP1Fps5il0wdnve0JO/uqymYy5r1l+9UcxYQJt1rN27Ou665Ldtby4qqnH7MITl/3ZGjbgt65f0ehmX1qpXZes+2WetD8NRzr8h3t7cHb++3ovKFN5wywo5YKie+6WO5+a5vP3j78Cfsn02vPmF0DS2xIe/nDmndFzri6fenXb8/yVdaa7f30A/MabYvITvqvowwqV67cXMuvvrWB29vb+3B25P6wQTe74cdvA153YfsJ5964EM+76bXJ93M0ClJvru95annXiF8mnAzQ6ckufmub+fEN31sEOHTkPdzh7bu804uXlX7VdUrk/x8kqcmuaq1dtVCQqequqiq7qqqz0yrHVBVm6rq5u7fx3b1qqo3V9UtVXVjVT1z2mPO7Ja/uarOnFb/0ara3D3mzVX10Jm5ACbAbDvh89WB8Tdf8DbphrzuQzfkz7uZodOu6kyOmaHTruqTZsi/90Nb912d1e4dSdYm2ZzkuUn+YBHP/fYkJ8+orU/ykdba4Uk+0t1O99yHd5ezk7wlmQqqkpyX5Jgkz0py3o6wqlvmrGmPm/mzAAAAABihXQVPT2utndFa+99Jnp/kJxb6xK21v0ly94zyaZkKs9L9u25a/Z1tytVJVlXVE5OclGRTa+3u1to3kmxKcnJ332Naa1e31lqSd057LgAAAACWgV0FT9/fcaW1dv8e+HkHtdbu6K7/Q5KDuuurk9w2bbnbu9p89dtnqc+qqs6uqmur6tqvfe1ru7cGAAAAACzIroKnH6mqe7vLt5I8Y8f1qrp3d35wN1JpSQ5cbq29tbW2trW29sADJ3+CQgAAAIDlYN6z2rXWVuzhn3dnVT2xtXZHd7jcXV19a5JDpi13cFfbmuSEGfWPdfWDZ1keAAAAgGViVyOe9rQPJNlxZrozk7x/Wv0l3dntjk3yze6QvCuTPKeqHttNKv6cJFd2991bVcd2Z7N7ybTnAgAAAGAZmHfE0+6oqndlarTS46vq9kydnW5DkndX1S8l+UqSX+gWvyLJKUluSfKdJC9Nktba3VX1e0k+2S33u621HROW/1qmzpy3MslfdhcAAAAAlonegqfW2ulz3PXsWZZtSV42x/NclOSiWerXJnn67vQIAAAAQH+W+lA7AADmsWXDqYuqT5IhrzsATKreRjwBsPvOOPbQXHz1rbPWgck15KBlyOt+0KP3zZ3f+t6sdQAYV0Y8MTaG/FfQP3zBUYuqT5ohv/bnrzsyZxx7aFZUJUlWVOWMYw/N+euOHHFn0J8h/84zbNece+JOIdNBj94315x74og6AujPXH9IHcIfWIe2r2PEE2NlUn8R2bUhv/bTRzxtby0XX33rYIKnNesv36k25G0BhmDov/czRzzNNgIKYBJcMsuo/h31oezrDoURTzAGXnnZDYuqMzlm+wI2X32SDHndh85rP1xDf+2Hvv7AsLRF1ifJ0N7vjXgCAFhmTnzTx3LzXd9+8PbhT9g/m159wugaAgB4mIx4AgBYRmaGTkly813fzolv+thoGgIA2A2CJwCAZWRm6LSrOgDAciZ4AgAAAKAX5ngCxsLQz3IEAAAwjgRPY2boX743Xr81F1x5U756z7Y8adXKnHPSEVl39OpRt0XP5jvrw5C2fwAAgHHjULsxMrRTLs608fqteeVlN2TrPdvSkmy9Z1teedkN2Xj91lG3BgAAAMxC8MTYeNVlNyyqDgAAAIyW4Imx0RZZB8bbXIdROrwSAADGhzmeAFi2hEwAADDejHgCAAAAoBeCJwAAAAB6IXgCAAAAoBeCJwAAAAB6IXgCAAAAoBeCJwAAAAB6IXgCAAAAoBeCJwBgWdmy4dRF1SfN0Nd/yLz2AEyivUfdACzU8YcdkKu+ePesdWAyrVl/+U41X8AYAts5AEyuP3zBUXnlZTfMWp9ERjyNkaH/FeySs47bKWQ6/rADcslZx42oI5bK0Lf9oZotdJqvzuTw2jNUtn2AYZgtdJqvPu6MeBozQ/+iPXPE02wjoAAAAIDlwYgnxoa/Ag6X1x4AAGA8CZ4AAAAA6IXgCQAAAIBeCJ4AAAAA6IXgCQAAAIBeCJ4AAAAA6IXgCYBlacuGUxdVB8af3/vh8toDTK69R90AAMzFFw4YHr/3w+W1B5hMgicAgGVmzfrLd6oN5Uv5kNd96Lz2AJPJoXYAAMvIbF++56tPkiGv+9B57QEml+AJAAAAgF4IngCWseMPO2BRdQAAgOVE8MTYcLaT4Rrya3/JWcftFDIdf9gBueSs40bUEQAAwMKZXJyxMoSggZ099dwr5qx/4Q2nLHE3S0/IBAAAjCsjnoBl77vb26LqAAAALA+CJwAAAAB64VA7gGVutlNJD+Ww0yGvOwAATAIjngCWsdmCl/nqk2TI686w7V2LqwMALGeCJwCAZeSWN56amRlTdXUAgHEjeAIAWEY2Xr81++2z4iG1/fZZkY3Xbx1RRwAAD5/gCQBgGbngypuy7fvbH1Lb9v3tueDKm0bUEQDAwzeS4KmqtlTV5qq6oaqu7WoHVNWmqrq5+/exXb2q6s1VdUtV3VhVz5z2PGd2y99cVWeOYl0AAPakr96zbVF1AIDlbJQjnn6ytXZUa21td3t9ko+01g5P8pHudpI8N8nh3eXsJG9JpoKqJOclOSbJs5KctyOsAgAYV09atXJRdQCA5Ww5HWp3WpJ3dNffkWTdtPo725Srk6yqqicmOSnJptba3a21byTZlOTkJe4ZWAL7rZj9VE5z1QHG2TknHZGVM+Z4WrnPipxz0hEj6ggA4OEbVfDUkny4qq6rqrO72kGttTu66/+Q5KDu+uokt0177O1dba76Tqrq7Kq6tqqu/drXvran1gFYIl94wyk7hUz7rah84Q2njKgjgP6sO3p1/t2Prs6KmnrfW1GVf/ejq7Pu6Fl3cwAAlrW9R/Rzf7y1trWqnpBkU1V9YfqdrbVWVW1P/bDW2luTvDVJ1q5du8eeF1g6QiZgKDZevzUXX33rg7e3t5aLr741a3/wAOETADB2RhI8tda2dv/eVVXvy9QcTXdW1RNba3d0h9Ld1S2+Nckh0x5+cFfbmuSEGfWP9dz6yK1Zf/lOtS0bTh1BJ7C0hrrtb9lwqnWfpc5kG/pr/8rLbpizLngCYFKsXrUyW2c5ccbqAcxpOLR9nSUPnqpq/yR7tda+1V1/TpLfTfKBJGcm2dD9+/7uIR9I8vKqujRTE4l/swunrkzyX6ZNKP6cJK9ZwlVZcrNtmDvqk7qBzvSiCz+eq75494O3jz/sgFxy1nEj7IilMORt/xnnfWjO+o2vn/xp7Sb99WVuXnuGaK9KHphlbP5epjQEJtBsodN89UlzxrGH5l3X3JbtrWVFVU4/5pBdP2hMjWKOp4OS/F1VfTrJJ5Jc3lr7UKYCpxOr6uYkP93dTpIrknwpyS1JLkzya0nSWrs7ye8l+WR3+d2uxoSaGTolyVVfvDsvuvDjI+oI+nfvfdsXVQdgfM0WOs1XB2A8vXbj5lx89a3Z3qbe4HccVv/ajZtH3Fk/lnzEU2vtS0l+ZJb615M8e5Z6S/KyOZ7roiQX7ekeWZ5mhk67qgMAAMByc8k1t85ZP3/dkUvcTf9GNbk4AMCcfug1l+f+aaM89q7kljc6/A4AGH9tjpGsc9XH3SgOtQMAmNPM0ClJ7m9TdQAAxovgCQBYVmaGTruqAwCwfAmeAAAAAOiF4AkAAACAXphcHIBl68Q3fSw33/XtB28f/oT9s+nVJ4yuIQAAYFGMeAJgWZoZOiXJzXd9Oye+6WOjaQgAAFg0wRMAy9LM0GlXdQAAYPkRPAEALCOP3Gf23bO56gAAy5k9GACAZeS//Nwzslc9tLZXTdUBAMaNycUBAJaRdUevTpJccOVN+eo92/KkVStzzklHPFgHABgngqcxsmXDqVmz/vJZ6wDA5Fh39GpBEwAwEQRPY0bIBAAAAIwLczwBAAAA0AvBEwDL0hnHHrqoOgAAsPwIngCWsVpkfZKcv+7InHHsoVlRU2u7oipnHHtozl935Ig7A/oy15QCphoAmDxDfs8f2rqb4wlgGXvRsYfm4qtvnbU+BOevO1LQBAPy1HOvmLP+hTecssTdANC3SQ1aFmJI6y54AljGdoQu77rmtmxvLSuqcvoxhwhjgIn03e1tUXUAYPkTPDE2tmw4NWvWXz5rHSaZUT8AAMC4EjwxVoRMAAAAMD5MLg4AAIzU0CbanW7I6z50XnuGwognAABg5CpJm3EbmGzPOO9Dufe+7Q/efswjVuTG1588wo6Wzsbrt+aCK2/KV+/ZlietWplzTjoi645ePeq2emHEEwDAMrPx+q05fsNf5cnrL8/xG/4qG6/fOuqWoFdPXn95Zk4h37r6pJttDtP56kyOob/2M0OnJLn3vu15xnkfGlFHS2fj9VvzG+/5dLbesy0tydZ7tuU33vPpif28FzwBy97hT9h/UXVgvO2/74pF1SfNxuu35lWX3fCQndFXXXbDxO6MQpKdQqdd1YHxNzN02lV9kpz7vs3Z/sBD3+G2P9By7vs2j6ijfjnUDlj2br7r24uqTxpnc2Rovv292Xc456pPmt/6s0/POvLjt/7s0xM7BB8AhmRo+zqCJ4BlbL4h2EMIn455w6bc+a3vPXj7oEfvm2vOPXGEHUH/vrd99jEec9UBAJYzh9oBsCzNDJ2S5M5vfS/HvGHTiDoCAAAWS/AEwLI0M3TaVR0AAFh+BE8AAMvII/aeffdsrjoAwHJmDwYAYBn53v0PLKoOALCcCZ6AZW+uSbSHMLk2MDxPWrVyUXUAgOVM8AQAsIycc9IRWbnPiofUVu6zIuecdMSIOgIAePgET8Cyt2b95YuqA4yzdUevzht/7sisXrUylWT1qpV5488dmXVHrx51awAAi7b3qBsAgNkc9Oh9Zz2D3UGP3ncE3cDSWnf0akETADARjHgCWMaGPL/VNeeeuFPIdNCj98015544oo4AAGD3DW0f34gngGVuUj+AFkLIBADAJBrSPr4RTwAAAAD0QvAEAMCycPgT9l9UfdLst6IWVZ8kQzvshH8219Y9+Vu97Z7hEDwBy54PZRgWv/PDtenVJ+wUMh3+hP2z6dUnjKahJfaFN5ySvWd82967pupDsGXDqTtdmHxtkfVJ4szNDIU5noBlb74PZTulMHk2Xr91zrozvU2+oYRMs9l4/dbcP+Pb9v3Ntg/AeDPiCQBYVl552Q2LqjNZNl6/Ncdv+Ks8ef3lOX7DX80ZRE4i2z4Ak8iIJwAAloWN12/Na967Odu+vz1JsvWebXnNezcniRE/ADCmjHgCAGBZuODKmx4MnXbY9v3tueDKm0bUEQCwuwRPAAAsC1+9Z9ui6gDA8id4AgBgWXjSqpWLqgMAy5/gCQBYVs449tBF1Zkc55x0RFbus+IhtZX7rMg5Jx0xoo6W1kGP3ndRdQAYB4InYNnbsuHURdWB8Xb+uiNzxrGHZkVVkmRFVc449tCcv+7IEXdG39YdvTpv/Lkjs3rVylSS1atW5o0/d+RgJha/5twTdwqZDnr0vrnm3BNH1BEA7L6xP6tdVZ2c5H8kWZHkj1trG0bcEtADIRMMy/nrjhQ0DdS6o1cPJmiajZAJgEkz1iOeqmpFkv+Z5LlJnpbk9Kp62mi7AgAAACAZ8+ApybOS3NJa+1Jr7XtJLk1y2oh7AgAAAObxhy84alF1xte4H2q3Oslt027fnuSYEfUCAAAALMCOw6ovuPKmfPWebXnSqpU556QjBn249aQa9+BpQarq7CRnJ8mhhzojDgAAsDxs2XBq1qy/fNb6EAx5/Ye87jsMfV6/oRj34GlrkkOm3T64qz1Ea+2tSd6aJGvXrm1L0xoAAMCuDSlomM2Q13/I685wjPscT59McnhVPbmq9k3ywiQfGHFPsMfN9YHkgwoml997AAAmwViPeGqt3V9VL09yZZIVSS5qrX12xG1BL3zZhOHxew8AwLgb6+ApSVprVyS5YtR9AAAAAPBQ436oHQAAAADLlOAJAAAAgF4IngAAAADoheAJAAAAgF4IngAAAADoheAJAAAAgF4IngAAAADoheAJAAAAgF5Ua23UPSypqvpakq+Muo894PFJ/nHUTTASXvvh8toPl9d+uLz2w+W1Hyav+3B57Ydrkl77H2ytHTizOLjgaVJU1bWttbWj7oOl57UfLq/9cHnth8trP1xe+2Hyug+X1364hvDaO9QOAAAAgF4IngAAAADoheBpfL111A0wMl774fLaD5fXfri89sPltR8mr/twee2Ha+Jfe3M8AQAAANALI54AAAAA6IXgCQAAAIBeCJ7GTFUdUlUfrarPVdVnq+oVo+6JpVVVK6rq+qr64Kh7YelU1aqq+rOq+kJVfb6qjht1T/Svql7Vvdd/pqreVVX7jbon+lNVF1XVXVX1mWm1A6pqU1Xd3P372FH2yJ43x+t+Qfd+f2NVva+qVo2wRXoy22s/7b7fqKpWVY8fRW/0a67Xvqp+vfvd/2xV/bdR9Ud/5njPP6qqrq6qG6rq2qp61ih77IPgafzcn+Q3WmtPS3JskpdV1dNG3BNL6xVJPj/qJlhy/yPJh1prT03yI7ENTLyqWp3k/06ytrX29CQrkrxwtF3Rs7cnOXlGbX2Sj7TWDk/yke42k+Xt2fl135Tk6a21ZyT5+ySvWeqmWBJvz86vfarqkCTPSXLrUjfEknl7Zrz2VfWTSU5L8iOttR9O8vsj6Iv+vT07/97/tySvb60dleQ/d7cniuBpzLTW7mitfaq7/q1MfflcPdquWCpVdXCSU5P88ah7YelU1Q8k+ddJ3pYkrbXvtdbuGWlTLJW9k6ysqr2TPDLJV0fcDz1qrf1NkrtnlE9L8o7u+juSrFvKnujfbK97a+3DrbX7u5tXJzl4yRujd3P8zifJf0/yW0mcBWpCzfHa/2qSDa21+7pl7lryxujdHK99S/KY7voPZAL39wRPY6yq1iQ5Osk1I26FpfOHmdoReWDEfbC0npzka0n+pDvM8o+rav9RN0W/WmtbM/XXzluT3JHkm621D4+2K0bgoNbaHd31f0hy0CibYST+Q5K/HHUTLI2qOi3J1tbap0fdC0vuKUl+oqquqaq/rqofG3VDLJlXJrmgqm7L1L7fxI1yFTyNqap6VJI/T/LK1tq9o+6H/lXVzyS5q7V23ah7YcntneSZSd7SWjs6ybfjcJuJ183lc1qmgscnJdm/qs4YbVeMUmutxQiIQamqczM1zcIlo+6F/lXVI5P8TqYOtWF49k5yQKamUzknyburqkbbEkvkV5O8qrV2SJJXpTvKYZIInsZQVe2TqdDpktbae0fdD0vm+CQ/W1Vbklya5Keq6uLRtsQSuT3J7a21HaMb/yxTQRST7aeTfLm19rXW2veTvDfJvxpxTyy9O6vqiUnS/evQi4Goqn+f5GeSvKgLHZl8h2Xqjw2f7vb3Dk7yqar6FyPtiqVye5L3timfyNQRDiaXH4YzM7WflyTvSWJycUarS73fluTzrbU3jboflk5r7TWttYNba2syNcHwX7XWjH4YgNbaPyS5raqO6ErPTvK5EbbE0rg1ybFV9cjuvf/ZMan8EH0gUzuk6f59/wh7YYlU1cmZOrT+Z1tr3xl1PyyN1trm1toTWmtruv2925M8s9sPYPJtTPKTSVJVT0myb5J/HGVDLJmvJvk33fWfSnLzCHvpxd6jboBFOz7Ji5NsrqobutrvtNauGF1LwBL49SSXVNW+Sb6U5KUj7oeetdauqao/S/KpTB1qc32St462K/pUVe9KckKSx1fV7UnOS7IhU4db/FKSryT5hdF1SB/meN1fk+QRSTZ1R9pc3Vr7lZE1SS9me+1baxN3iA07m+P3/qIkF1XVZ5J8L8mZRjtOnjle+7OS/I/uZDLfTXL26DrsR9mWAQAAAOiDQ+0AAAAA6IXgCQAAAIBeCJ4AAAAA6IXgCQAAAIBeCJ4AAAAA6IXgCQAAAIBeCJ4AgIlUVdur6oaq+kxVvaeqHrkbz/Wxqlr7MB63qqp+bQHLPaWqrqiqm6vqU1X17qo6aJ7l11TVLy62n75V1SVVdVP3f35RVe0z6p4AgNESPAEAk2pba+2o1trTk3wvya9Mv7Oq9l6CHlYlmTd4qqr9klye5C2ttcNba89M8kdJDpznYWuS9B48VdWKRT7kkiRPTXJkkpVJ/uMebwoAGCuCJwBgCP42yQ9V1QlV9bdV9YEkn6uq/arqT6pqc1VdX1U/mSRVtbKqLq2qz1fV+zIVoqS775+mXX9+Vb29u35QVb2vqj7dXf5Vkg1JDutGXl0wR2+/mOTjrbW/2FForX2stfaZbmTT33ajoD7VPWe65/2J7nlfVVUrquqCqvpkVd1YVb/c9bRXVf1RVX2hqjZ1o6qe39337G6dN3ejkx7R1bdU1X+tqk8lWd/9u2N9D59+e6bW2hWtk+QTSQ5e0KsDAEyspfhLHwDAyHQjm56b5ENd6ZlJnt5a+3JV/UaS1lo7sqqemuTDVfWUJL+a5DuttX9ZVc9IMmfYMs2bk/x1a+153UihRyVZ3/2so+Z53NOTXDfHfXclObG19t2qOjzJu5Ks7Z73N1trP9Ot49lJvtla+7EuQLqqqj6c5EczNTrqaUmekOTzSS7qRlm9PcmzW2t/X1Xv7Nb5D7uf+/Vu5FWq6qer6qjW2g1JXprkT3b1H9EdYvfiJK/Y1bIAwGQz4gkAmFQrq+qGJNcmuTXJ27r6J1prX+6u/3iSi5OktfaFJF9J8pQk/3pa/cYkNy7g5/1Ukrd0j9neWvvmHliHfZJcWFWbk7wnUwHSbJ6T5CXd+l6T5HFJDs/U+r2ntfZAa+0fkny0W/6IJF9urf19d/sdmVrnHS6bdv2Pk7y0C9NekORPF9D3HyX5m9ba3y5gWQBgghnxBABMqm0zRxpVVZJ8ezeft027vt9uPleSfDbJv5njvlcluTPJj2TqD4bfnWO5SvLrrbUrH1KsOuVh9jT9/+jPk5yX5K+SXNda+/p8D6yq8zI1P9UvP8yfDQBMECOeAIAh+9skL0qmziyX5NAkNyX5m3STd1fV05M8Y9pj7qyqf1lVeyV53rT6RzJ1uFq6OZd+IMm3kjx6Fz38aZJ/VVWn7ihU1b/ufu4PJLmjtfZApg5d2zHZ98znvTLJr+44i1x3lrz9k1yV5N91cz0dlOSEbvmbkqypqh/qbr84yV/P1lxr7bvd878luzjMrqr+Y5KTkpze9QwADJzgCQAYsj9Ksld3KNtlSf59a+2+TIUsj6qqzyf53Tx0Dqb1ST6Y5P9Lcse0+iuS/GT3XNcleVo3OuiqqvrMXJOLt9a2JfmZJL9eVTdX1ecydSa8r3X9nVlVn87U2eJ2jES6Mcn2bhLzV2XqcLjPJflUVX0myf/O1Mj2P09ye3ffxZmaq+qbXZj00iTv6fp9IMn/muf/6ZJumQ/Ps0y65zgoyce7ic//8y6WBwAmXE2ddAQAgElUVY9qrf1TVT0uU2eaO76b72kxz/GbSX6gtfafemkSAJhY5ngCAJhsH6yqVUn2TfJ7DyN0el+SwzI1eToAwKIY8QQAsASq6sgk/++M8n2ttWNG0c/u6MKoJ88o//bMyc0BAARPAAAAAPTC5OIAAAAA9ELwBAAAAEAvBE8AAAAA9ELwBAAAAEAv/v9sUW/xfNO+3gAAAABJRU5ErkJggg==\n", "text/plain": [ "<Figure size 1440x864 with 2 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.figure(1)\n", "plt.figure(figsize = (20, 12))\n", "\n", "# Column (Product_Category_1 vs Purchase)\n", "plt.subplot(211)\n", "plt.ticklabel_format(style = 'plain')\n", "plt.scatter(df['Product_Category_1'], df['Purchase'])\n", "plt.xlabel('Product_Category_1')\n", "plt.ylabel('Purchase')\n", "\n", "# Column (Product_Category_2 vs Purchase)\n", "plt.subplot(212)\n", "plt.ticklabel_format(style = 'plain')\n", "plt.scatter(df['Product_Category_2'], df['Purchase'])\n", "plt.xlabel('Product_Category_2')\n", "plt.ylabel('Purchase')" ] }, { "cell_type": "markdown", "id": "768db036", "metadata": { "papermill": { "duration": 0.01961, "end_time": "2022-10-27T20:01:48.456178", "exception": false, "start_time": "2022-10-27T20:01:48.436568", "status": "completed" }, "tags": [] }, "source": [ "# Classification Models" ] }, { "cell_type": "code", "execution_count": 29, "id": "cf68f484", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:01:48.498180Z", "iopub.status.busy": "2022-10-27T20:01:48.497794Z", "iopub.status.idle": "2022-10-27T20:01:48.548251Z", "shell.execute_reply": "2022-10-27T20:01:48.547239Z" }, "papermill": { "duration": 0.073983, "end_time": "2022-10-27T20:01:48.550898", "exception": false, "start_time": "2022-10-27T20:01:48.476915", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "X = df.drop(['Purchase'],axis=1)\n", "Y = df['Purchase']" ] }, { "cell_type": "code", "execution_count": 30, "id": "fd95a615", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:01:48.591294Z", "iopub.status.busy": "2022-10-27T20:01:48.590903Z", "iopub.status.idle": "2022-10-27T20:01:49.015943Z", "shell.execute_reply": "2022-10-27T20:01:49.014662Z" }, "papermill": { "duration": 0.448448, "end_time": "2022-10-27T20:01:49.018651", "exception": false, "start_time": "2022-10-27T20:01:48.570203", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>Gender</th>\n", " <th>Age</th>\n", " <th>Occupation</th>\n", " <th>City</th>\n", " <th>Years_in_City</th>\n", " <th>Marital_Status</th>\n", " <th>Product_Category_1</th>\n", " <th>Product_Category_2</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>0</th>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>10</td>\n", " <td>0</td>\n", " <td>2</td>\n", " <td>0</td>\n", " <td>3</td>\n", " <td>4.0</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>10</td>\n", " <td>0</td>\n", " <td>2</td>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>6.0</td>\n", " </tr>\n", " <tr>\n", " <th>2</th>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>10</td>\n", " <td>0</td>\n", " <td>2</td>\n", " <td>0</td>\n", " <td>12</td>\n", " <td>4.0</td>\n", " </tr>\n", " <tr>\n", " <th>3</th>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>10</td>\n", " <td>0</td>\n", " <td>2</td>\n", " <td>0</td>\n", " <td>12</td>\n", " <td>14.0</td>\n", " </tr>\n", " <tr>\n", " <th>4</th>\n", " <td>0</td>\n", " <td>2</td>\n", " <td>16</td>\n", " <td>2</td>\n", " <td>4</td>\n", " <td>0</td>\n", " <td>8</td>\n", " <td>8.0</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " Gender Age Occupation City Years_in_City Marital_Status \\\n", "0 1 1 10 0 2 0 \n", "1 1 1 10 0 2 0 \n", "2 1 1 10 0 2 0 \n", "3 1 1 10 0 2 0 \n", "4 0 2 16 2 4 0 \n", "\n", " Product_Category_1 Product_Category_2 \n", "0 3 4.0 \n", "1 1 6.0 \n", "2 12 4.0 \n", "3 12 14.0 \n", "4 8 8.0 " ] }, "execution_count": 30, "metadata": {}, "output_type": "execute_result" } ], "source": [ "X1 = X.select_dtypes('O')\n", "\n", "for col in X1.columns:\n", " lb = LabelEncoder()\n", " X[col] = lb.fit_transform(X1[col].values)\n", "X.head()" ] }, { "cell_type": "code", "execution_count": 31, "id": "9f64b470", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:01:49.060174Z", "iopub.status.busy": "2022-10-27T20:01:49.059794Z", "iopub.status.idle": "2022-10-27T20:01:49.198336Z", "shell.execute_reply": "2022-10-27T20:01:49.197267Z" }, "papermill": { "duration": 0.162254, "end_time": "2022-10-27T20:01:49.200947", "exception": false, "start_time": "2022-10-27T20:01:49.038693", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "X_train, X_test, Y_train, Y_test = train_test_split(X, Y)" ] }, { "cell_type": "code", "execution_count": 32, "id": "17a1941d", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:01:49.244078Z", "iopub.status.busy": "2022-10-27T20:01:49.243624Z", "iopub.status.idle": "2022-10-27T20:01:50.298925Z", "shell.execute_reply": "2022-10-27T20:01:50.297476Z" }, "papermill": { "duration": 1.080078, "end_time": "2022-10-27T20:01:50.301335", "exception": false, "start_time": "2022-10-27T20:01:49.221257", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "DecisionTreeRegressor()" ] }, "execution_count": 32, "metadata": {}, "output_type": "execute_result" } ], "source": [ "dt = DecisionTreeRegressor()\n", "dt.fit(X_train, Y_train)" ] }, { "cell_type": "code", "execution_count": 33, "id": "8711209f", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:01:50.343510Z", "iopub.status.busy": "2022-10-27T20:01:50.342309Z", "iopub.status.idle": "2022-10-27T20:01:50.580569Z", "shell.execute_reply": "2022-10-27T20:01:50.578950Z" }, "papermill": { "duration": 0.262223, "end_time": "2022-10-27T20:01:50.583329", "exception": false, "start_time": "2022-10-27T20:01:50.321106", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "(0.7254013035696869, 0.6158894165451075)" ] }, "execution_count": 33, "metadata": {}, "output_type": "execute_result" } ], "source": [ "dt.score(X_train,Y_train), dt.score(X_test,Y_test)" ] }, { "cell_type": "code", "execution_count": null, "id": "d1aa2cc2", "metadata": { "papermill": { "duration": 0.019406, "end_time": "2022-10-27T20:01:50.622778", "exception": false, "start_time": "2022-10-27T20:01:50.603372", "status": "completed" }, "tags": [] }, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.12" }, "papermill": { "default_parameters": {}, "duration": 95.710559, "end_time": "2022-10-27T20:01:51.666255", "environment_variables": {}, "exception": null, "input_path": "__notebook__.ipynb", "output_path": "__notebook__.ipynb", "parameters": {}, "start_time": "2022-10-27T20:00:15.955696", "version": "2.3.4" } }, "nbformat": 4, "nbformat_minor": 5 }	0109/327/109327648.ipynb	s3://data-agents/kaggle-outputs/sharded/011_00109.jsonl.gz
{ "cells": [ { "cell_type": "code", "execution_count": 1, "id": "655bb815", "metadata": { "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19", "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5", "execution": { "iopub.execute_input": "2022-10-27T20:04:39.770819Z", "iopub.status.busy": "2022-10-27T20:04:39.770178Z", "iopub.status.idle": "2022-10-27T20:04:39.797156Z", "shell.execute_reply": "2022-10-27T20:04:39.795652Z" }, "papermill": { "duration": 0.040173, "end_time": "2022-10-27T20:04:39.800700", "exception": false, "start_time": "2022-10-27T20:04:39.760527", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "/kaggle/input/ramen-ratings/ramen-ratings.csv\n" ] } ], "source": [ "# This Python 3 environment comes with many helpful analytics libraries installed\n", "# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n", "# For example, here's several helpful packages to load\n", "\n", "import numpy as np # linear algebra\n", "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n", "\n", "# Input data files are available in the read-only \"../input/\" directory\n", "# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n", "\n", "import os\n", "for dirname, _, filenames in os.walk('/kaggle/input'):\n", " for filename in filenames:\n", " print(os.path.join(dirname, filename))\n", "\n", "# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n", "# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session" ] }, { "cell_type": "code", "execution_count": 2, "id": "65e15073", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:04:39.817409Z", "iopub.status.busy": "2022-10-27T20:04:39.816970Z", "iopub.status.idle": "2022-10-27T20:04:41.053007Z", "shell.execute_reply": "2022-10-27T20:04:41.051635Z" }, "papermill": { "duration": 1.247822, "end_time": "2022-10-27T20:04:41.056248", "exception": false, "start_time": "2022-10-27T20:04:39.808426", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "import pandas as pd\n", "import numpy as np\n", "import seaborn as sns\n", "import matplotlib.pyplot as plt\n", "%matplotlib inline\n", "sns.set(color_codes=True)" ] }, { "cell_type": "code", "execution_count": 3, "id": "83c7cdac", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:04:41.070887Z", "iopub.status.busy": "2022-10-27T20:04:41.070483Z", "iopub.status.idle": "2022-10-27T20:04:41.098835Z", "shell.execute_reply": "2022-10-27T20:04:41.097620Z" }, "papermill": { "duration": 0.038847, "end_time": "2022-10-27T20:04:41.101493", "exception": false, "start_time": "2022-10-27T20:04:41.062646", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "ramen=pd.read_csv('../input/ramen-ratings/ramen-ratings.csv')" ] }, { "cell_type": "code", "execution_count": 4, "id": "a32407e2", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:04:41.116678Z", "iopub.status.busy": "2022-10-27T20:04:41.116262Z", "iopub.status.idle": "2022-10-27T20:04:41.143977Z", "shell.execute_reply": "2022-10-27T20:04:41.142618Z" }, "papermill": { "duration": 0.038994, "end_time": "2022-10-27T20:04:41.147240", "exception": false, "start_time": "2022-10-27T20:04:41.108246", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>Review #</th>\n", " <th>Brand</th>\n", " <th>Variety</th>\n", " <th>Style</th>\n", " <th>Country</th>\n", " <th>Stars</th>\n", " <th>Top Ten</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>0</th>\n", " <td>2580</td>\n", " <td>New Touch</td>\n", " <td>T's Restaurant Tantanmen</td>\n", " <td>Cup</td>\n", " <td>Japan</td>\n", " <td>3.75</td>\n", " <td>NaN</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>2579</td>\n", " <td>Just Way</td>\n", " <td>Noodles Spicy Hot Sesame Spicy Hot Sesame Guan...</td>\n", " <td>Pack</td>\n", " <td>Taiwan</td>\n", " <td>1</td>\n", " <td>NaN</td>\n", " </tr>\n", " <tr>\n", " <th>2</th>\n", " <td>2578</td>\n", " <td>Nissin</td>\n", " <td>Cup Noodles Chicken Vegetable</td>\n", " <td>Cup</td>\n", " <td>USA</td>\n", " <td>2.25</td>\n", " <td>NaN</td>\n", " </tr>\n", " <tr>\n", " <th>3</th>\n", " <td>2577</td>\n", " <td>Wei Lih</td>\n", " <td>GGE Ramen Snack Tomato Flavor</td>\n", " <td>Pack</td>\n", " <td>Taiwan</td>\n", " <td>2.75</td>\n", " <td>NaN</td>\n", " </tr>\n", " <tr>\n", " <th>4</th>\n", " <td>2576</td>\n", " <td>Ching's Secret</td>\n", " <td>Singapore Curry</td>\n", " <td>Pack</td>\n", " <td>India</td>\n", " <td>3.75</td>\n", " <td>NaN</td>\n", " </tr>\n", " <tr>\n", " <th>...</th>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " </tr>\n", " <tr>\n", " <th>2575</th>\n", " <td>5</td>\n", " <td>Vifon</td>\n", " <td>Hu Tiu Nam Vang [\"Phnom Penh\" style] Asian Sty...</td>\n", " <td>Bowl</td>\n", " <td>Vietnam</td>\n", " <td>3.5</td>\n", " <td>NaN</td>\n", " </tr>\n", " <tr>\n", " <th>2576</th>\n", " <td>4</td>\n", " <td>Wai Wai</td>\n", " <td>Oriental Style Instant Noodles</td>\n", " <td>Pack</td>\n", " <td>Thailand</td>\n", " <td>1</td>\n", " <td>NaN</td>\n", " </tr>\n", " <tr>\n", " <th>2577</th>\n", " <td>3</td>\n", " <td>Wai Wai</td>\n", " <td>Tom Yum Shrimp</td>\n", " <td>Pack</td>\n", " <td>Thailand</td>\n", " <td>2</td>\n", " <td>NaN</td>\n", " </tr>\n", " <tr>\n", " <th>2578</th>\n", " <td>2</td>\n", " <td>Wai Wai</td>\n", " <td>Tom Yum Chili Flavor</td>\n", " <td>Pack</td>\n", " <td>Thailand</td>\n", " <td>2</td>\n", " <td>NaN</td>\n", " </tr>\n", " <tr>\n", " <th>2579</th>\n", " <td>1</td>\n", " <td>Westbrae</td>\n", " <td>Miso Ramen</td>\n", " <td>Pack</td>\n", " <td>USA</td>\n", " <td>0.5</td>\n", " <td>NaN</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "<p>2580 rows × 7 columns</p>\n", "</div>" ], "text/plain": [ " Review # Brand \\\n", "0 2580 New Touch \n", "1 2579 Just Way \n", "2 2578 Nissin \n", "3 2577 Wei Lih \n", "4 2576 Ching's Secret \n", "... ... ... \n", "2575 5 Vifon \n", "2576 4 Wai Wai \n", "2577 3 Wai Wai \n", "2578 2 Wai Wai \n", "2579 1 Westbrae \n", "\n", " Variety Style Country Stars \\\n", "0 T's Restaurant Tantanmen Cup Japan 3.75 \n", "1 Noodles Spicy Hot Sesame Spicy Hot Sesame Guan... Pack Taiwan 1 \n", "2 Cup Noodles Chicken Vegetable Cup USA 2.25 \n", "3 GGE Ramen Snack Tomato Flavor Pack Taiwan 2.75 \n", "4 Singapore Curry Pack India 3.75 \n", "... ... ... ... ... \n", "2575 Hu Tiu Nam Vang [\"Phnom Penh\" style] Asian Sty... Bowl Vietnam 3.5 \n", "2576 Oriental Style Instant Noodles Pack Thailand 1 \n", "2577 Tom Yum Shrimp Pack Thailand 2 \n", "2578 Tom Yum Chili Flavor Pack Thailand 2 \n", "2579 Miso Ramen Pack USA 0.5 \n", "\n", " Top Ten \n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN \n", "... ... \n", "2575 NaN \n", "2576 NaN \n", "2577 NaN \n", "2578 NaN \n", "2579 NaN \n", "\n", "[2580 rows x 7 columns]" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "ramen" ] }, { "cell_type": "code", "execution_count": 5, "id": "07b84e2d", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:04:41.162997Z", "iopub.status.busy": "2022-10-27T20:04:41.162566Z", "iopub.status.idle": "2022-10-27T20:04:41.177325Z", "shell.execute_reply": "2022-10-27T20:04:41.176092Z" }, "papermill": { "duration": 0.02577, "end_time": "2022-10-27T20:04:41.179940", "exception": false, "start_time": "2022-10-27T20:04:41.154170", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>Review #</th>\n", " <th>Brand</th>\n", " <th>Variety</th>\n", " <th>Style</th>\n", " <th>Country</th>\n", " <th>Stars</th>\n", " <th>Top Ten</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>0</th>\n", " <td>2580</td>\n", " <td>New Touch</td>\n", " <td>T's Restaurant Tantanmen</td>\n", " <td>Cup</td>\n", " <td>Japan</td>\n", " <td>3.75</td>\n", " <td>NaN</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>2579</td>\n", " <td>Just Way</td>\n", " <td>Noodles Spicy Hot Sesame Spicy Hot Sesame Guan...</td>\n", " <td>Pack</td>\n", " <td>Taiwan</td>\n", " <td>1</td>\n", " <td>NaN</td>\n", " </tr>\n", " <tr>\n", " <th>2</th>\n", " <td>2578</td>\n", " <td>Nissin</td>\n", " <td>Cup Noodles Chicken Vegetable</td>\n", " <td>Cup</td>\n", " <td>USA</td>\n", " <td>2.25</td>\n", " <td>NaN</td>\n", " </tr>\n", " <tr>\n", " <th>3</th>\n", " <td>2577</td>\n", " <td>Wei Lih</td>\n", " <td>GGE Ramen Snack Tomato Flavor</td>\n", " <td>Pack</td>\n", " <td>Taiwan</td>\n", " <td>2.75</td>\n", " <td>NaN</td>\n", " </tr>\n", " <tr>\n", " <th>4</th>\n", " <td>2576</td>\n", " <td>Ching's Secret</td>\n", " <td>Singapore Curry</td>\n", " <td>Pack</td>\n", " <td>India</td>\n", " <td>3.75</td>\n", " <td>NaN</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " Review # Brand \\\n", "0 2580 New Touch \n", "1 2579 Just Way \n", "2 2578 Nissin \n", "3 2577 Wei Lih \n", "4 2576 Ching's Secret \n", "\n", " Variety Style Country Stars \\\n", "0 T's Restaurant Tantanmen Cup Japan 3.75 \n", "1 Noodles Spicy Hot Sesame Spicy Hot Sesame Guan... Pack Taiwan 1 \n", "2 Cup Noodles Chicken Vegetable Cup USA 2.25 \n", "3 GGE Ramen Snack Tomato Flavor Pack Taiwan 2.75 \n", "4 Singapore Curry Pack India 3.75 \n", "\n", " Top Ten \n", "0 NaN \n", "1 NaN \n", "2 NaN \n", "3 NaN \n", "4 NaN " ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "ramen.head()" ] }, { "cell_type": "code", "execution_count": 6, "id": "23d485d8", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:04:41.195630Z", "iopub.status.busy": "2022-10-27T20:04:41.195235Z", "iopub.status.idle": "2022-10-27T20:04:41.218847Z", "shell.execute_reply": "2022-10-27T20:04:41.217338Z" }, "papermill": { "duration": 0.034803, "end_time": "2022-10-27T20:04:41.221809", "exception": false, "start_time": "2022-10-27T20:04:41.187006", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "Variety\n", "\"A\" Series Artificial Chicken 1\n", "\"A\" Series Artificial Hot Beef 1\n", "\"A\" Series Vegetarian 1\n", "1 Step-1 Minute Asian Noodles Kung Pao 1\n", "1 Step-1 Minute Asian Noodles Lemongrass Ginger 1\n", " ..\n", "chicken 1\n", "dried Mix Noodles Soya Bean Paste 1\n", "spicy Pad Thai Instant Noodles & Sauce 1\n", "ДОШИРАК (Dosirac) Beef Flavor 1\n", "三養라면 (Samyang Ramyun) (South Korean Version) 1\n", "Length: 2413, dtype: int64" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "ramen.groupby('Variety').size()" ] }, { "cell_type": "code", "execution_count": 7, "id": "a721c6a2", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:04:41.238214Z", "iopub.status.busy": "2022-10-27T20:04:41.237773Z", "iopub.status.idle": "2022-10-27T20:04:41.260686Z", "shell.execute_reply": "2022-10-27T20:04:41.259156Z" }, "papermill": { "duration": 0.035507, "end_time": "2022-10-27T20:04:41.264762", "exception": false, "start_time": "2022-10-27T20:04:41.229255", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>Review #</th>\n", " <th>Brand</th>\n", " <th>Style</th>\n", " <th>Country</th>\n", " <th>Stars</th>\n", " <th>Top Ten</th>\n", " </tr>\n", " <tr>\n", " <th>Variety</th>\n", " <th></th>\n", " <th></th>\n", " <th></th>\n", " <th></th>\n", " <th></th>\n", " <th></th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>\"A\" Series Artificial Chicken</th>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>\"A\" Series Artificial Hot Beef</th>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>\"A\" Series Vegetarian</th>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>1 Step-1 Minute Asian Noodles Kung Pao</th>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>1 Step-1 Minute Asian Noodles Lemongrass Ginger</th>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>...</th>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " </tr>\n", " <tr>\n", " <th>chicken</th>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>dried Mix Noodles Soya Bean Paste</th>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>spicy Pad Thai Instant Noodles & Sauce</th>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>ДОШИРАК (Dosirac) Beef Flavor</th>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>三養라면 (Samyang Ramyun) (South Korean Version)</th>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "<p>2413 rows × 6 columns</p>\n", "</div>" ], "text/plain": [ " Review # Brand Style \\\n", "Variety \n", "\"A\" Series Artificial Chicken 1 1 1 \n", "\"A\" Series Artificial Hot Beef 1 1 1 \n", "\"A\" Series Vegetarian 1 1 1 \n", "1 Step-1 Minute Asian Noodles Kung Pao 1 1 1 \n", "1 Step-1 Minute Asian Noodles Lemongrass Ginger 1 1 1 \n", "... ... ... ... \n", "chicken 1 1 1 \n", "dried Mix Noodles Soya Bean Paste 1 1 1 \n", "spicy Pad Thai Instant Noodles & Sauce 1 1 1 \n", "ДОШИРАК (Dosirac) Beef Flavor 1 1 1 \n", "三養라면 (Samyang Ramyun) (South Korean Version) 1 1 1 \n", "\n", " Country Stars Top Ten \n", "Variety \n", "\"A\" Series Artificial Chicken 1 1 0 \n", "\"A\" Series Artificial Hot Beef 1 1 0 \n", "\"A\" Series Vegetarian 1 1 0 \n", "1 Step-1 Minute Asian Noodles Kung Pao 1 1 0 \n", "1 Step-1 Minute Asian Noodles Lemongrass Ginger 1 1 0 \n", "... ... ... ... \n", "chicken 1 1 0 \n", "dried Mix Noodles Soya Bean Paste 1 1 0 \n", "spicy Pad Thai Instant Noodles & Sauce 1 1 0 \n", "ДОШИРАК (Dosirac) Beef Flavor 1 1 0 \n", "三養라면 (Samyang Ramyun) (South Korean Version) 1 1 0 \n", "\n", "[2413 rows x 6 columns]" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "ramen.groupby('Variety').count()" ] }, { "cell_type": "code", "execution_count": 8, "id": "ed622cbf", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:04:41.287246Z", "iopub.status.busy": "2022-10-27T20:04:41.286799Z", "iopub.status.idle": "2022-10-27T20:04:41.300439Z", "shell.execute_reply": "2022-10-27T20:04:41.299213Z" }, "papermill": { "duration": 0.027703, "end_time": "2022-10-27T20:04:41.303210", "exception": false, "start_time": "2022-10-27T20:04:41.275507", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "Nissin 381\n", "Nongshim 98\n", "Maruchan 76\n", "Mama 71\n", "Paldo 66\n", " ... \n", "Golden Wonder 1\n", "Peyang 1\n", "Sanrio 1\n", "China Best 1\n", "Westbrae 1\n", "Name: Brand, Length: 355, dtype: int64" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "ramen['Brand'].value_counts()" ] }, { "cell_type": "code", "execution_count": 9, "id": "c9549db6", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:04:41.324816Z", "iopub.status.busy": "2022-10-27T20:04:41.324392Z", "iopub.status.idle": "2022-10-27T20:04:41.578881Z", "shell.execute_reply": "2022-10-27T20:04:41.577761Z" }, "papermill": { "duration": 0.266742, "end_time": "2022-10-27T20:04:41.581458", "exception": false, "start_time": "2022-10-27T20:04:41.314716", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "<AxesSubplot:>" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "ramen['Brand'].value_counts().nlargest(5).plot(kind=\"bar\")" ] }, { "cell_type": "markdown", "id": "92565fac", "metadata": { "papermill": { "duration": 0.007722, "end_time": "2022-10-27T20:04:41.597146", "exception": false, "start_time": "2022-10-27T20:04:41.589424", "status": "completed" }, "tags": [] }, "source": [ "HERE WE CAN SEE THAT \"NISSIN' HAS THE MOST VARIETY OF RAMENS (MORE THAN 350)" ] }, { "cell_type": "code", "execution_count": 10, "id": "8fa599dc", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:04:41.614454Z", "iopub.status.busy": "2022-10-27T20:04:41.614066Z", "iopub.status.idle": "2022-10-27T20:04:41.815082Z", "shell.execute_reply": "2022-10-27T20:04:41.813938Z" }, "papermill": { "duration": 0.212935, "end_time": "2022-10-27T20:04:41.817822", "exception": false, "start_time": "2022-10-27T20:04:41.604887", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "<AxesSubplot:title={'center':'the sale among the countries'}, ylabel='Country'>" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "ramen['Country'].value_counts().nlargest(15).plot(kind=\"pie\",title=\"the sale among the countries\")" ] }, { "cell_type": "markdown", "id": "9029f0d9", "metadata": { "papermill": { "duration": 0.008366, "end_time": "2022-10-27T20:04:41.835090", "exception": false, "start_time": "2022-10-27T20:04:41.826724", "status": "completed" }, "tags": [] }, "source": [] }, { "cell_type": "markdown", "id": "59b8bf28", "metadata": { "papermill": { "duration": 0.00834, "end_time": "2022-10-27T20:04:41.852168", "exception": false, "start_time": "2022-10-27T20:04:41.843828", "status": "completed" }, "tags": [] }, "source": [ "HERE WE CAN SEE THE SALE OF RAMEN AMONG THE TOP TEN COUNTRIES" ] }, { "cell_type": "code", "execution_count": 11, "id": "78eccaed", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:04:41.872111Z", "iopub.status.busy": "2022-10-27T20:04:41.871212Z", "iopub.status.idle": "2022-10-27T20:04:42.347077Z", "shell.execute_reply": "2022-10-27T20:04:42.345994Z" }, "papermill": { "duration": 0.488622, "end_time": "2022-10-27T20:04:42.349564", "exception": false, "start_time": "2022-10-27T20:04:41.860942", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "Text(0, 0.5, 'Countries')" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 864x720 with 1 Axes>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(12,10))\n", "sns.countplot(data=ramen, y=\"Country\", order=ramen['Country'].value_counts().index)\n", "plt.title('Countries X brands')\n", "plt.xlabel('Number of brands')\n", "plt.ylabel(\"Countries\")" ] }, { "cell_type": "code", "execution_count": 12, "id": "b3a123e2", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:04:42.371228Z", "iopub.status.busy": "2022-10-27T20:04:42.370146Z", "iopub.status.idle": "2022-10-27T20:04:42.380007Z", "shell.execute_reply": "2022-10-27T20:04:42.378907Z" }, "papermill": { "duration": 0.022893, "end_time": "2022-10-27T20:04:42.382273", "exception": false, "start_time": "2022-10-27T20:04:42.359380", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "Japan 352\n", "USA 323\n", "South Korea 309\n", "Taiwan 224\n", "Thailand 191\n", "China 169\n", "Malaysia 156\n", "Hong Kong 137\n", "Indonesia 126\n", "Singapore 109\n", "Vietnam 108\n", "UK 69\n", "Philippines 47\n", "Canada 41\n", "India 31\n", "Germany 27\n", "Mexico 25\n", "Australia 22\n", "Netherlands 15\n", "Myanmar 14\n", "Nepal 14\n", "Pakistan 9\n", "Hungary 9\n", "Bangladesh 7\n", "Colombia 6\n", "Brazil 5\n", "Cambodia 5\n", "Fiji 4\n", "Holland 4\n", "Poland 4\n", "Finland 3\n", "Sarawak 3\n", "Sweden 3\n", "Dubai 3\n", "Ghana 2\n", "Estonia 2\n", "Nigeria 1\n", "United States 1\n", "Name: Country, dtype: int64" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "ramen['Country'].value_counts(ascending=False)" ] }, { "cell_type": "markdown", "id": "c1210a20", "metadata": { "papermill": { "duration": 0.010259, "end_time": "2022-10-27T20:04:42.402516", "exception": false, "start_time": "2022-10-27T20:04:42.392257", "status": "completed" }, "tags": [] }, "source": [] }, { "cell_type": "markdown", "id": "0240d736", "metadata": { "papermill": { "duration": 0.010107, "end_time": "2022-10-27T20:04:42.423046", "exception": false, "start_time": "2022-10-27T20:04:42.412939", "status": "completed" }, "tags": [] }, "source": [ "JAPAN HAS THE MOST SALE OF RAMEN COMPARED TO OTHER COUNTRIES " ] }, { "cell_type": "code", "execution_count": 13, "id": "77a9a723", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:04:42.444980Z", "iopub.status.busy": "2022-10-27T20:04:42.443853Z", "iopub.status.idle": "2022-10-27T20:04:42.567993Z", "shell.execute_reply": "2022-10-27T20:04:42.565880Z" }, "papermill": { "duration": 0.142468, "end_time": "2022-10-27T20:04:42.575269", "exception": false, "start_time": "2022-10-27T20:04:42.432801", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "<AxesSubplot:title={'center':'Style mostly liked by comsumers'}, ylabel='Style'>" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "ramen['Style'].value_counts().plot(kind=\"pie\",title=\"Style mostly liked by comsumers\")" ] }, { "cell_type": "markdown", "id": "06af43e9", "metadata": { "papermill": { "duration": 0.019005, "end_time": "2022-10-27T20:04:42.619290", "exception": false, "start_time": "2022-10-27T20:04:42.600285", "status": "completed" }, "tags": [] }, "source": [ "HERE WE SEE THAT WHEN THE STYLE OF PACKAGING WAS \"PACK\" IT WAS MOST LIKED BY THE CONSUMERS AND \"BOX\" PACKAGING IS THE LEAST LIKED STYLE." ] }, { "cell_type": "markdown", "id": "4a28ab1d", "metadata": { "papermill": { "duration": 0.022679, "end_time": "2022-10-27T20:04:42.663024", "exception": false, "start_time": "2022-10-27T20:04:42.640345", "status": "completed" }, "tags": [] }, "source": [] }, { "cell_type": "code", "execution_count": 14, "id": "c00227f0", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:04:42.694027Z", "iopub.status.busy": "2022-10-27T20:04:42.692806Z", "iopub.status.idle": "2022-10-27T20:04:42.713635Z", "shell.execute_reply": "2022-10-27T20:04:42.712334Z" }, "papermill": { "duration": 0.04063, "end_time": "2022-10-27T20:04:42.716515", "exception": false, "start_time": "2022-10-27T20:04:42.675885", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>Review #</th>\n", " <th>Brand</th>\n", " <th>Style</th>\n", " <th>Country</th>\n", " <th>Stars</th>\n", " <th>Top Ten</th>\n", " </tr>\n", " <tr>\n", " <th>Variety</th>\n", " <th></th>\n", " <th></th>\n", " <th></th>\n", " <th></th>\n", " <th></th>\n", " <th></th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>\"A\" Series Artificial Chicken</th>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>\"A\" Series Artificial Hot Beef</th>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>\"A\" Series Vegetarian</th>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>1 Step-1 Minute Asian Noodles Kung Pao</th>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>1 Step-1 Minute Asian Noodles Lemongrass Ginger</th>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>...</th>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " </tr>\n", " <tr>\n", " <th>chicken</th>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>dried Mix Noodles Soya Bean Paste</th>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>spicy Pad Thai Instant Noodles & Sauce</th>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>ДОШИРАК (Dosirac) Beef Flavor</th>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>三養라면 (Samyang Ramyun) (South Korean Version)</th>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "<p>2413 rows × 6 columns</p>\n", "</div>" ], "text/plain": [ " Review # Brand Style \\\n", "Variety \n", "\"A\" Series Artificial Chicken 1 1 1 \n", "\"A\" Series Artificial Hot Beef 1 1 1 \n", "\"A\" Series Vegetarian 1 1 1 \n", "1 Step-1 Minute Asian Noodles Kung Pao 1 1 1 \n", "1 Step-1 Minute Asian Noodles Lemongrass Ginger 1 1 1 \n", "... ... ... ... \n", "chicken 1 1 1 \n", "dried Mix Noodles Soya Bean Paste 1 1 1 \n", "spicy Pad Thai Instant Noodles & Sauce 1 1 1 \n", "ДОШИРАК (Dosirac) Beef Flavor 1 1 1 \n", "三養라면 (Samyang Ramyun) (South Korean Version) 1 1 1 \n", "\n", " Country Stars Top Ten \n", "Variety \n", "\"A\" Series Artificial Chicken 1 1 0 \n", "\"A\" Series Artificial Hot Beef 1 1 0 \n", "\"A\" Series Vegetarian 1 1 0 \n", "1 Step-1 Minute Asian Noodles Kung Pao 1 1 0 \n", "1 Step-1 Minute Asian Noodles Lemongrass Ginger 1 1 0 \n", "... ... ... ... \n", "chicken 1 1 0 \n", "dried Mix Noodles Soya Bean Paste 1 1 0 \n", "spicy Pad Thai Instant Noodles & Sauce 1 1 0 \n", "ДОШИРАК (Dosirac) Beef Flavor 1 1 0 \n", "三養라면 (Samyang Ramyun) (South Korean Version) 1 1 0 \n", "\n", "[2413 rows x 6 columns]" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "ramen.groupby('Variety').count()" ] }, { "cell_type": "code", "execution_count": 15, "id": "3e971483", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:04:42.740867Z", "iopub.status.busy": "2022-10-27T20:04:42.740172Z", "iopub.status.idle": "2022-10-27T20:04:42.765318Z", "shell.execute_reply": "2022-10-27T20:04:42.764079Z" }, "papermill": { "duration": 0.040314, "end_time": "2022-10-27T20:04:42.767784", "exception": false, "start_time": "2022-10-27T20:04:42.727470", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th></th>\n", " <th>Review #</th>\n", " <th>Brand</th>\n", " <th>Style</th>\n", " <th>Stars</th>\n", " <th>Top Ten</th>\n", " </tr>\n", " <tr>\n", " <th>Country</th>\n", " <th>Variety</th>\n", " <th></th>\n", " <th></th>\n", " <th></th>\n", " <th></th>\n", " <th></th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th rowspan=\"5\" valign=\"top\">Australia</th>\n", " <th>2 Minute Laksa Flavour Noodles</th>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>Chow Mein Soft Noodles</th>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>Fusian Special Edition Ow... Ow... Spicy Cow Mi Goreng</th>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>Hot & Spicy 2 Minute Noodles</th>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>Instant Noodles Beef Flavour</th>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>...</th>\n", " <th>...</th>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " </tr>\n", " <tr>\n", " <th rowspan=\"5\" valign=\"top\">Vietnam</th>\n", " <th>Tu Quy Spicy Beef</th>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>Tu quy Chicken</th>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>Viet Cuisine Bun Rieu Cua Sour Crab Soup Instant Rice Vermicelli</th>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>Viet Rice Noodles Chicken</th>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>Xi Gon Satay Onion Flavor</th>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "<p>2486 rows × 5 columns</p>\n", "</div>" ], "text/plain": [ " Review # Brand \\\n", "Country Variety \n", "Australia 2 Minute Laksa Flavour Noodles 1 1 \n", " Chow Mein Soft Noodles 1 1 \n", " Fusian Special Edition Ow... Ow... Spicy Cow Mi... 1 1 \n", " Hot & Spicy 2 Minute Noodles 1 1 \n", " Instant Noodles Beef Flavour 1 1 \n", "... ... ... \n", "Vietnam Tu Quy Spicy Beef 1 1 \n", " Tu quy Chicken 1 1 \n", " Viet Cuisine Bun Rieu Cua Sour Crab Soup Instan... 1 1 \n", " Viet Rice Noodles Chicken 1 1 \n", " Xi Gon Satay Onion Flavor 1 1 \n", "\n", " Style Stars \\\n", "Country Variety \n", "Australia 2 Minute Laksa Flavour Noodles 1 1 \n", " Chow Mein Soft Noodles 1 1 \n", " Fusian Special Edition Ow... Ow... Spicy Cow Mi... 1 1 \n", " Hot & Spicy 2 Minute Noodles 1 1 \n", " Instant Noodles Beef Flavour 1 1 \n", "... ... ... \n", "Vietnam Tu Quy Spicy Beef 1 1 \n", " Tu quy Chicken 1 1 \n", " Viet Cuisine Bun Rieu Cua Sour Crab Soup Instan... 1 1 \n", " Viet Rice Noodles Chicken 1 1 \n", " Xi Gon Satay Onion Flavor 1 1 \n", "\n", " Top Ten \n", "Country Variety \n", "Australia 2 Minute Laksa Flavour Noodles 0 \n", " Chow Mein Soft Noodles 0 \n", " Fusian Special Edition Ow... Ow... Spicy Cow Mi... 0 \n", " Hot & Spicy 2 Minute Noodles 0 \n", " Instant Noodles Beef Flavour 0 \n", "... ... \n", "Vietnam Tu Quy Spicy Beef 0 \n", " Tu quy Chicken 0 \n", " Viet Cuisine Bun Rieu Cua Sour Crab Soup Instan... 0 \n", " Viet Rice Noodles Chicken 0 \n", " Xi Gon Satay Onion Flavor 0 \n", "\n", "[2486 rows x 5 columns]" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "ramen.groupby(['Country','Variety']).count()" ] }, { "cell_type": "code", "execution_count": 16, "id": "ddffb950", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:04:42.792148Z", "iopub.status.busy": "2022-10-27T20:04:42.791717Z", "iopub.status.idle": "2022-10-27T20:04:42.816145Z", "shell.execute_reply": "2022-10-27T20:04:42.814780Z" }, "papermill": { "duration": 0.039623, "end_time": "2022-10-27T20:04:42.818482", "exception": false, "start_time": "2022-10-27T20:04:42.778859", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th></th>\n", " <th>Review #</th>\n", " <th>Style</th>\n", " <th>Country</th>\n", " <th>Stars</th>\n", " <th>Top Ten</th>\n", " </tr>\n", " <tr>\n", " <th>Brand</th>\n", " <th>Variety</th>\n", " <th></th>\n", " <th></th>\n", " <th></th>\n", " <th></th>\n", " <th></th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>1 To 3 Noodles</th>\n", " <th>Chatpat Masala</th>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th rowspan=\"2\" valign=\"top\">7 Select</th>\n", " <th>Nissin Instant Noodles Shrimp Ma Nao Lui Suan Flavour King Cup</th>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>Nissin Instant Noodles Tom Yum Seafood Creamy Flavour King Cup</th>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>7 Select/Nissin</th>\n", " <th>Super Tom Yum Shrimp</th>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>A-One</th>\n", " <th>Mi Ly Instant Noodles Mi Bo Beef Flavor</th>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>...</th>\n", " <th>...</th>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " </tr>\n", " <tr>\n", " <th rowspan=\"3\" valign=\"top\">iMee</th>\n", " <th>Instant Noodles Creamy Tom Yum Shrimp Flavour</th>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>Instant Noodles Vegetable Flavour</th>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>Instant Noodles chicken Flavour</th>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th rowspan=\"2\" valign=\"top\">iNoodle</th>\n", " <th>Taiwan Style Chow Mein</th>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>Udon Noodle Soup Oriental</th>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "<p>2520 rows × 5 columns</p>\n", "</div>" ], "text/plain": [ " Review # \\\n", "Brand Variety \n", "1 To 3 Noodles Chatpat Masala 1 \n", "7 Select Nissin Instant Noodles Shrimp Ma Nao Lui Suan F... 1 \n", " Nissin Instant Noodles Tom Yum Seafood Creamy F... 1 \n", "7 Select/Nissin Super Tom Yum Shrimp 1 \n", "A-One Mi Ly Instant Noodles Mi Bo Beef Flavor 1 \n", "... ... \n", "iMee Instant Noodles Creamy Tom Yum Shrimp Flavour 1 \n", " Instant Noodles Vegetable Flavour 1 \n", " Instant Noodles chicken Flavour 1 \n", "iNoodle Taiwan Style Chow Mein 1 \n", " Udon Noodle Soup Oriental 1 \n", "\n", " Style \\\n", "Brand Variety \n", "1 To 3 Noodles Chatpat Masala 1 \n", "7 Select Nissin Instant Noodles Shrimp Ma Nao Lui Suan F... 1 \n", " Nissin Instant Noodles Tom Yum Seafood Creamy F... 1 \n", "7 Select/Nissin Super Tom Yum Shrimp 1 \n", "A-One Mi Ly Instant Noodles Mi Bo Beef Flavor 1 \n", "... ... \n", "iMee Instant Noodles Creamy Tom Yum Shrimp Flavour 1 \n", " Instant Noodles Vegetable Flavour 1 \n", " Instant Noodles chicken Flavour 1 \n", "iNoodle Taiwan Style Chow Mein 1 \n", " Udon Noodle Soup Oriental 1 \n", "\n", " Country \\\n", "Brand Variety \n", "1 To 3 Noodles Chatpat Masala 1 \n", "7 Select Nissin Instant Noodles Shrimp Ma Nao Lui Suan F... 1 \n", " Nissin Instant Noodles Tom Yum Seafood Creamy F... 1 \n", "7 Select/Nissin Super Tom Yum Shrimp 1 \n", "A-One Mi Ly Instant Noodles Mi Bo Beef Flavor 1 \n", "... ... \n", "iMee Instant Noodles Creamy Tom Yum Shrimp Flavour 1 \n", " Instant Noodles Vegetable Flavour 1 \n", " Instant Noodles chicken Flavour 1 \n", "iNoodle Taiwan Style Chow Mein 1 \n", " Udon Noodle Soup Oriental 1 \n", "\n", " Stars \\\n", "Brand Variety \n", "1 To 3 Noodles Chatpat Masala 1 \n", "7 Select Nissin Instant Noodles Shrimp Ma Nao Lui Suan F... 1 \n", " Nissin Instant Noodles Tom Yum Seafood Creamy F... 1 \n", "7 Select/Nissin Super Tom Yum Shrimp 1 \n", "A-One Mi Ly Instant Noodles Mi Bo Beef Flavor 1 \n", "... ... \n", "iMee Instant Noodles Creamy Tom Yum Shrimp Flavour 1 \n", " Instant Noodles Vegetable Flavour 1 \n", " Instant Noodles chicken Flavour 1 \n", "iNoodle Taiwan Style Chow Mein 1 \n", " Udon Noodle Soup Oriental 1 \n", "\n", " Top Ten \n", "Brand Variety \n", "1 To 3 Noodles Chatpat Masala 0 \n", "7 Select Nissin Instant Noodles Shrimp Ma Nao Lui Suan F... 0 \n", " Nissin Instant Noodles Tom Yum Seafood Creamy F... 0 \n", "7 Select/Nissin Super Tom Yum Shrimp 0 \n", "A-One Mi Ly Instant Noodles Mi Bo Beef Flavor 0 \n", "... ... \n", "iMee Instant Noodles Creamy Tom Yum Shrimp Flavour 0 \n", " Instant Noodles Vegetable Flavour 0 \n", " Instant Noodles chicken Flavour 0 \n", "iNoodle Taiwan Style Chow Mein 0 \n", " Udon Noodle Soup Oriental 0 \n", "\n", "[2520 rows x 5 columns]" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "ramen.groupby(['Brand','Variety']).count()" ] }, { "cell_type": "code", "execution_count": 17, "id": "838108cc", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:04:42.843392Z", "iopub.status.busy": "2022-10-27T20:04:42.842994Z", "iopub.status.idle": "2022-10-27T20:04:42.862320Z", "shell.execute_reply": "2022-10-27T20:04:42.861455Z" }, "papermill": { "duration": 0.034374, "end_time": "2022-10-27T20:04:42.864414", "exception": false, "start_time": "2022-10-27T20:04:42.830040", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "Brand 41\n", "Variety 41\n", "dtype: int64" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "ramen.groupby(['Review #','Style','Country','Stars','Top Ten']).nunique().count()" ] }, { "cell_type": "code", "execution_count": 18, "id": "494f842c", "metadata": { "execution": { "iopub.execute_input": "2022-10-27T20:04:42.891480Z", "iopub.status.busy": "2022-10-27T20:04:42.890636Z", "iopub.status.idle": "2022-10-27T20:04:42.905560Z", "shell.execute_reply": "2022-10-27T20:04:42.904089Z" }, "papermill": { "duration": 0.030279, "end_time": "2022-10-27T20:04:42.908270", "exception": false, "start_time": "2022-10-27T20:04:42.877991", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "Review # 37\n", "Variety 37\n", "Style 37\n", "Country 37\n", "Stars 37\n", "Top Ten 6\n", "dtype: int64" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "ramen.groupby('Brand').count().nunique()" ] }, { "cell_type": "code", "execution_count": null, "id": "120a5173", "metadata": { "papermill": { "duration": 0.011244, "end_time": "2022-10-27T20:04:42.931215", "exception": false, "start_time": "2022-10-27T20:04:42.919971", "status": "completed" }, "tags": [] }, "outputs": [], "source": [] }, { "cell_type": "markdown", "id": "a4523991", "metadata": { "papermill": { "duration": 0.011128, "end_time": "2022-10-27T20:04:42.953850", "exception": false, "start_time": "2022-10-27T20:04:42.942722", "status": "completed" }, "tags": [] }, "source": [ "CONCLUSION:\n", "* 1. FROM THE ABOVE ANALYSIS WE CAME TO A CONCLUSION THAT :\n", " (a) THE SALE OF RAMEN IS LARGEST IN ASIAN COUNTRIES ESPECIALLY IN JAPAN.\n", " (b) THE SECOND LARGEST RAMEN SELLING COUNTRY IS USA\n", " 2. THE TYPE OF PACKAGING OF RAMEN THAT IS:\n", " (a) MOST LIKED BY THE CONSUMER IS \"PACK\".\n", " (b) LEAST LIKED BY THE CONSUMER IS \"BOX\".\n", " *3. IF WE TALK ABOUT THE BRAND THAT SELL THE MOST VARIETY OF RAMEN IS \"NISSIN\"" ] }, { "cell_type": "code", "execution_count": null, "id": "6efd6d2b", "metadata": { "papermill": { "duration": 0.011043, "end_time": "2022-10-27T20:04:42.976524", "exception": false, "start_time": "2022-10-27T20:04:42.965481", "status": "completed" }, "tags": [] }, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.12" }, "papermill": { "default_parameters": {}, "duration": 12.922338, "end_time": "2022-10-27T20:04:43.711843", "environment_variables": {}, "exception": null, "input_path": "__notebook__.ipynb", "output_path": "__notebook__.ipynb", "parameters": {}, "start_time": "2022-10-27T20:04:30.789505", "version": "2.3.4" } }, "nbformat": 4, "nbformat_minor": 5 }	0109/327/109327898.ipynb	s3://data-agents/kaggle-outputs/sharded/011_00109.jsonl.gz
{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:34:24.377100Z", "iopub.status.busy": "2021-02-26T23:34:24.355120Z", "iopub.status.idle": "2021-02-27T00:08:03.666011Z", "shell.execute_reply": "2021-02-27T00:08:03.666588Z" }, "papermill": { "duration": 2019.348579, "end_time": "2021-02-27T00:08:03.666925", "exception": false, "start_time": "2021-02-26T23:34:24.318346", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Fold0:\n", "FOLD0 EPOCH: 0 train_loss=0.69229 valid_u_score=1705.18159 valid_auc=0.54655 time: 0.86min\n", "FOLD0 EPOCH: 1 train_loss=0.68979 valid_u_score=1775.34960 valid_auc=0.54931 time: 1.67min\n", "FOLD0 EPOCH: 2 train_loss=0.68913 valid_u_score=1981.09315 valid_auc=0.55046 time: 2.46min\n", "FOLD0 EPOCH: 3 train_loss=0.68872 valid_u_score=1987.40307 valid_auc=0.54843 time: 3.26min\n", "FOLD0 EPOCH: 4 train_loss=0.68839 valid_u_score=1978.15193 valid_auc=0.55057 time: 4.06min\n", "FOLD0 EPOCH: 5 train_loss=0.68808 valid_u_score=1872.87273 valid_auc=0.55126 time: 4.86min\n", "FOLD0 EPOCH: 6 train_loss=0.68782 valid_u_score=1877.99167 valid_auc=0.54984 time: 5.65min\n", "FOLD0 EPOCH: 7 train_loss=0.68751 valid_u_score=2011.69693 valid_auc=0.55051 time: 6.45min\n", "FOLD0 EPOCH: 8 train_loss=0.68725 valid_u_score=2204.02717 valid_auc=0.55119 time: 7.25min\n", "Early stopping\n", "Fold1:\n", "FOLD1 EPOCH: 0 train_loss=0.69264 valid_u_score=1914.27808 valid_auc=0.54819 time: 8.03min\n", "FOLD1 EPOCH: 1 train_loss=0.68973 valid_u_score=1911.46245 valid_auc=0.54947 time: 8.84min\n", "FOLD1 EPOCH: 2 train_loss=0.68915 valid_u_score=1671.56933 valid_auc=0.54801 time: 9.62min\n", "FOLD1 EPOCH: 3 train_loss=0.68880 valid_u_score=2195.71693 valid_auc=0.55246 time: 10.43min\n", "FOLD1 EPOCH: 4 train_loss=0.68843 valid_u_score=2382.53796 valid_auc=0.55144 time: 11.23min\n", "FOLD1 EPOCH: 5 train_loss=0.68806 valid_u_score=2063.93941 valid_auc=0.55045 time: 12.02min\n", "FOLD1 EPOCH: 6 train_loss=0.68788 valid_u_score=1867.98310 valid_auc=0.55093 time: 12.83min\n", "Early stopping\n", "Fold2:\n", "FOLD2 EPOCH: 0 train_loss=0.69223 valid_u_score=1970.49936 valid_auc=0.54852 time: 13.64min\n", "FOLD2 EPOCH: 1 train_loss=0.68970 valid_u_score=2103.07937 valid_auc=0.54971 time: 14.44min\n", "FOLD2 EPOCH: 2 train_loss=0.68918 valid_u_score=2394.89241 valid_auc=0.55060 time: 15.26min\n", "FOLD2 EPOCH: 3 train_loss=0.68879 valid_u_score=2200.45590 valid_auc=0.55189 time: 16.04min\n", "FOLD2 EPOCH: 4 train_loss=0.68841 valid_u_score=2229.41881 valid_auc=0.55071 time: 16.84min\n", "FOLD2 EPOCH: 5 train_loss=0.68808 valid_u_score=2101.30786 valid_auc=0.55161 time: 17.64min\n", "FOLD2 EPOCH: 6 train_loss=0.68782 valid_u_score=1894.94072 valid_auc=0.55114 time: 18.44min\n", "Early stopping\n", "Fold3:\n", "FOLD3 EPOCH: 0 train_loss=0.69253 valid_u_score=2209.80698 valid_auc=0.54581 time: 19.25min\n", "FOLD3 EPOCH: 1 train_loss=0.68979 valid_u_score=1865.45308 valid_auc=0.54858 time: 20.04min\n", "FOLD3 EPOCH: 2 train_loss=0.68913 valid_u_score=1904.09006 valid_auc=0.54990 time: 20.85min\n", "FOLD3 EPOCH: 3 train_loss=0.68878 valid_u_score=2085.33115 valid_auc=0.54994 time: 21.64min\n", "FOLD3 EPOCH: 4 train_loss=0.68842 valid_u_score=2067.05807 valid_auc=0.55275 time: 22.45min\n", "FOLD3 EPOCH: 5 train_loss=0.68809 valid_u_score=1983.13798 valid_auc=0.54950 time: 23.25min\n", "FOLD3 EPOCH: 6 train_loss=0.68783 valid_u_score=2104.66113 valid_auc=0.55254 time: 24.05min\n", "FOLD3 EPOCH: 7 train_loss=0.68756 valid_u_score=2307.02448 valid_auc=0.55101 time: 24.85min\n", "Early stopping\n", "Fold4:\n", "FOLD4 EPOCH: 0 train_loss=0.69224 valid_u_score=1931.65508 valid_auc=0.54873 time: 25.67min\n", "FOLD4 EPOCH: 1 train_loss=0.68971 valid_u_score=2067.32400 valid_auc=0.55065 time: 26.48min\n", "FOLD4 EPOCH: 2 train_loss=0.68913 valid_u_score=1932.62970 valid_auc=0.55034 time: 27.29min\n", "FOLD4 EPOCH: 3 train_loss=0.68875 valid_u_score=2199.77980 valid_auc=0.55116 time: 28.11min\n", "FOLD4 EPOCH: 4 train_loss=0.68837 valid_u_score=1827.35485 valid_auc=0.54987 time: 28.93min\n", "FOLD4 EPOCH: 5 train_loss=0.68807 valid_u_score=1950.97677 valid_auc=0.55005 time: 29.74min\n", "FOLD4 EPOCH: 6 train_loss=0.68776 valid_u_score=2091.65092 valid_auc=0.55112 time: 30.56min\n", "Early stopping\n", "5 models valid score: 2227.345577419398\tauc_score: 0.5540\tlogloss_score:4.0700\n" ] } ], "source": [ "import os\n", "import time\n", "import pickle\n", "import random\n", "import numpy as np\n", "import pandas as pd\n", "from tqdm import tqdm\n", "from sklearn.metrics import log_loss, roc_auc_score\n", "\n", "import torch\n", "import torch.nn as nn\n", "from torch.autograd import Variable\n", "from torch.utils.data import DataLoader\n", "from torch.nn import CrossEntropyLoss, MSELoss\n", "from torch.nn.modules.loss import _WeightedLoss\n", "import torch.nn.functional as F\n", "\n", "pd.set_option('display.max_columns', 100)\n", "pd.set_option('display.max_rows', 100)\n", "\n", "DATA_PATH = '../input/jane-street-market-prediction/'\n", "\n", "# GPU_NUM = 8\n", "BATCH_SIZE = 8192# * GPU_NUM\n", "EPOCHS = 200\n", "LEARNING_RATE = 1e-3\n", "WEIGHT_DECAY = 1e-5\n", "EARLYSTOP_NUM = 3\n", "NFOLDS = 5\n", "\n", "TRAIN = True\n", "CACHE_PATH = './'\n", "\n", "train = pd.read_csv(f'{DATA_PATH}/train.csv')\n", "\n", "def save_pickle(dic, save_path):\n", " with open(save_path, 'wb') as f:\n", " # with gzip.open(save_path, 'wb') as f:\n", " pickle.dump(dic, f)\n", "\n", "def load_pickle(load_path):\n", " with open(load_path, 'rb') as f:\n", " # with gzip.open(load_path, 'rb') as f:\n", " message_dict = pickle.load(f)\n", " return message_dict\n", "\n", "class EarlyStopping:\n", " def __init__(self, patience=7, mode=\"max\", delta=0.001):\n", " self.patience = patience\n", " self.counter = 0\n", " self.mode = mode\n", " self.best_score = None\n", " self.early_stop = False\n", " self.delta = delta\n", " if self.mode == \"min\":\n", " self.val_score = np.Inf\n", " else:\n", " self.val_score = -np.Inf\n", "\n", " def __call__(self, epoch_score, model, model_path):\n", "\n", " if self.mode == \"min\":\n", " score = -1.0 * epoch_score\n", " else:\n", " score = np.copy(epoch_score)\n", "\n", " if self.best_score is None:\n", " self.best_score = score\n", " self.save_checkpoint(epoch_score, model, model_path)\n", " elif score < self.best_score: # + self.delta\n", " self.counter += 1\n", " # print('EarlyStopping counter: {} out of {}'.format(self.counter, self.patience))\n", " if self.counter >= self.patience:\n", " self.early_stop = True\n", " else:\n", " self.best_score = score\n", " # ema.apply_shadow()\n", " self.save_checkpoint(epoch_score, model, model_path)\n", " # ema.restore()\n", " self.counter = 0\n", " \n", " def save_checkpoint(self, epoch_score, model, model_path):\n", " if epoch_score not in [-np.inf, np.inf, -np.nan, np.nan]:\n", " # print('Validation score improved ({} --> {}). Saving model!'.format(self.val_score, epoch_score))\n", " # if not DEBUG:\n", " torch.save(model.state_dict(), model_path)\n", " self.val_score = epoch_score\n", "\n", "def seed_everything(seed=42):\n", " random.seed(seed)\n", " os.environ['PYTHONHASHSEED'] = str(seed)\n", " np.random.seed(seed)\n", " torch.manual_seed(seed)\n", " torch.cuda.manual_seed(seed)\n", " torch.backends.cudnn.deterministic = True\n", "seed_everything(seed=42)\n", "\n", "feat_cols = [f'feature_{i}' for i in range(130)]\n", "\n", "\n", "if TRAIN:\n", " train = train.loc[train.date > 85].reset_index(drop=True)\n", "\n", " train['action'] = (train['resp'] > 0).astype('int')\n", " train['action_1'] = (train['resp_1'] > 0).astype('int')\n", " train['action_2'] = (train['resp_2'] > 0).astype('int')\n", " train['action_3'] = (train['resp_3'] > 0).astype('int')\n", " train['action_4'] = (train['resp_4'] > 0).astype('int')\n", " valid = train.loc[(train.date >= 450) & (train.date < 500)].reset_index(drop=True)\n", " train = train.loc[train.date < 450].reset_index(drop=True)\n", "target_cols = ['action', 'action_1', 'action_2', 'action_3', 'action_4']\n", "\n", "if TRAIN:\n", " df = pd.concat([train[feat_cols], valid[feat_cols]]).reset_index(drop=True)\n", " f_mean = df.mean()\n", " f_mean = f_mean.values\n", " np.save(f'{CACHE_PATH}/f_mean_online.npy', f_mean)\n", "\n", " train.fillna(df.mean(), inplace=True)\n", " valid.fillna(df.mean(), inplace=True)\n", "else:\n", " f_mean = np.load(f'{CACHE_PATH}/f_mean_online.npy')\n", "\n", "##### Making features\n", "# https://www.kaggle.com/lucasmorin/running-algos-fe-for-fast-inference/data\n", "# eda:https://www.kaggle.com/carlmcbrideellis/jane-street-eda-of-day-0-and-feature-importance\n", "# his example:https://www.kaggle.com/gracewan/plot-model\n", "def fillna_npwhere_njit(array, values):\n", " if np.isnan(array.sum()):\n", " array = np.where(np.isnan(array), values, array)\n", " return array\n", "\n", "\n", "\n", "\n", "class RunningEWMean:\n", " def __init__(self, WIN_SIZE=20, n_size=1, lt_mean=None):\n", " if lt_mean is not None:\n", " self.s = lt_mean\n", " else:\n", " self.s = np.zeros(n_size)\n", " self.past_value = np.zeros(n_size)\n", " self.alpha = 2 / (WIN_SIZE + 1)\n", "\n", " def clear(self):\n", " self.s = 0\n", "\n", " def push(self, x):\n", "\n", " x = fillna_npwhere_njit(x, self.past_value)\n", " self.past_value = x\n", " self.s = self.alpha * x + (1 - self.alpha) * self.s\n", "\n", " def get_mean(self):\n", " return self.s\n", "\n", "if TRAIN:\n", " all_feat_cols = [col for col in feat_cols]\n", "\n", " train['cross_41_42_43'] = train['feature_41'] + train['feature_42'] + train['feature_43']\n", " train['cross_1_2'] = train['feature_1'] / (train['feature_2'] + 1e-5)\n", " valid['cross_41_42_43'] = valid['feature_41'] + valid['feature_42'] + valid['feature_43']\n", " valid['cross_1_2'] = valid['feature_1'] / (valid['feature_2'] + 1e-5)\n", "\n", " all_feat_cols.extend(['cross_41_42_43', 'cross_1_2'])\n", "\n", "##### Model&Data fnc\n", "class SmoothBCEwLogits(_WeightedLoss):\n", " def __init__(self, weight=None, reduction='mean', smoothing=0.0):\n", " super().__init__(weight=weight, reduction=reduction)\n", " self.smoothing = smoothing\n", " self.weight = weight\n", " self.reduction = reduction\n", "\n", " @staticmethod\n", " def _smooth(targets:torch.Tensor, n_labels:int, smoothing=0.0):\n", " assert 0 <= smoothing < 1\n", " with torch.no_grad():\n", " targets = targets * (1.0 - smoothing) + 0.5 * smoothing\n", " return targets\n", "\n", " def forward(self, inputs, targets):\n", " targets = SmoothBCEwLogits._smooth(targets, inputs.size(-1),\n", " self.smoothing)\n", " loss = F.binary_cross_entropy_with_logits(inputs, targets,self.weight)\n", "\n", " if self.reduction == 'sum':\n", " loss = loss.sum()\n", " elif self.reduction == 'mean':\n", " loss = loss.mean()\n", "\n", " return loss\n", "\n", "\n", "class MarketDataset:\n", " def __init__(self, df):\n", " self.features = df[all_feat_cols].values\n", "\n", " self.label = df[target_cols].values.reshape(-1, len(target_cols))\n", "\n", " def __len__(self):\n", " return len(self.label)\n", "\n", " def __getitem__(self, idx):\n", " return {\n", " 'features': torch.tensor(self.features[idx], dtype=torch.float),\n", " 'label': torch.tensor(self.label[idx], dtype=torch.float)\n", " }\n", "\n", "class Model(nn.Module):\n", " def __init__(self):\n", " super(Model, self).__init__()\n", " self.batch_norm0 = nn.BatchNorm1d(len(all_feat_cols))\n", " self.dropout0 = nn.Dropout(0.2)\n", "\n", " dropout_rate = 0.2\n", " hidden_size = 256\n", " self.dense1 = nn.Linear(len(all_feat_cols), hidden_size)\n", " self.batch_norm1 = nn.BatchNorm1d(hidden_size)\n", " self.dropout1 = nn.Dropout(dropout_rate)\n", "\n", " self.dense2 = nn.Linear(hidden_size+len(all_feat_cols), hidden_size)\n", " self.batch_norm2 = nn.BatchNorm1d(hidden_size)\n", " self.dropout2 = nn.Dropout(dropout_rate)\n", "\n", " self.dense3 = nn.Linear(hidden_size+hidden_size, hidden_size)\n", " self.batch_norm3 = nn.BatchNorm1d(hidden_size)\n", " self.dropout3 = nn.Dropout(dropout_rate)\n", "\n", " self.dense4 = nn.Linear(hidden_size+hidden_size, hidden_size)\n", " self.batch_norm4 = nn.BatchNorm1d(hidden_size)\n", " self.dropout4 = nn.Dropout(dropout_rate)\n", "\n", " self.dense5 = nn.Linear(hidden_size+hidden_size, len(target_cols))\n", "\n", " self.Relu = nn.ReLU(inplace=True)\n", " self.PReLU = nn.PReLU()\n", " self.LeakyReLU = nn.LeakyReLU(negative_slope=0.01, inplace=True)\n", " # self.GeLU = nn.GELU()\n", " self.RReLU = nn.RReLU()\n", " \n", "\n", " def forward(self, x):\n", " x = self.batch_norm0(x)\n", " x = self.dropout0(x)\n", "\n", " x1 = self.dense1(x)\n", " x1 = self.batch_norm1(x1)\n", " # x = F.relu(x)\n", " # x = self.PReLU(x)\n", " x1 = self.LeakyReLU(x1)\n", " x1 = self.dropout1(x1)\n", "\n", " x = torch.cat([x, x1], 1)\n", "\n", " x2 = self.dense2(x)\n", " x2 = self.batch_norm2(x2)\n", " # x = F.relu(x)\n", " # x = self.PReLU(x)\n", " x2 = self.LeakyReLU(x2)\n", " x2 = self.dropout2(x2)\n", "\n", " x = torch.cat([x1, x2], 1)\n", "\n", " x3 = self.dense3(x)\n", " x3 = self.batch_norm3(x3)\n", " # x = F.relu(x)\n", " # x = self.PReLU(x)\n", " x3 = self.LeakyReLU(x3)\n", " x3 = self.dropout3(x3)\n", "\n", " x = torch.cat([x2, x3], 1)\n", "\n", " x4 = self.dense4(x)\n", " x4 = self.batch_norm4(x4)\n", " # x = F.relu(x)\n", " # x = self.PReLU(x)\n", " x4 = self.LeakyReLU(x4)\n", " x4 = self.dropout4(x4)\n", "\n", " x = torch.cat([x3, x4], 1)\n", "\n", " x = self.dense5(x)\n", " \n", " return x\n", "\n", "def train_fn(model, optimizer, scheduler, loss_fn, dataloader, device):\n", " model.train()\n", " final_loss = 0\n", "\n", " for data in dataloader:\n", " optimizer.zero_grad()\n", " features = data['features'].to(device)\n", " label = data['label'].to(device)\n", " outputs = model(features)\n", " loss = loss_fn(outputs, label)\n", " loss.backward()\n", " optimizer.step()\n", " if scheduler:\n", " scheduler.step()\n", "\n", " final_loss += loss.item()\n", "\n", " final_loss /= len(dataloader)\n", "\n", " return final_loss\n", "\n", "def inference_fn(model, dataloader, device):\n", " model.eval()\n", " preds = []\n", "\n", " for data in dataloader:\n", " features = data['features'].to(device)\n", "\n", " with torch.no_grad():\n", " outputs = model(features)\n", "\n", " preds.append(outputs.sigmoid().detach().cpu().numpy())\n", "\n", " preds = np.concatenate(preds).reshape(-1, len(target_cols))\n", "\n", " return preds\n", "\n", "def utility_score_bincount(date, weight, resp, action):\n", " count_i = len(np.unique(date))\n", " # print('weight: ', weight)\n", " # print('resp: ', resp)\n", " # print('action: ', action)\n", " # print('weight * resp * action: ', weight * resp * action)\n", " Pi = np.bincount(date, weight * resp * action)\n", " t = np.sum(Pi) / np.sqrt(np.sum(Pi ** 2)) * np.sqrt(250 / count_i)\n", " u = np.clip(t, 0, 6) * np.sum(Pi)\n", " return u\n", "\n", "\n", "if TRAIN:\n", " train_set = MarketDataset(train)\n", " train_loader = DataLoader(train_set, batch_size=BATCH_SIZE, shuffle=True, num_workers=4)\n", " valid_set = MarketDataset(valid)\n", " valid_loader = DataLoader(valid_set, batch_size=BATCH_SIZE, shuffle=False, num_workers=4)\n", "\n", " start_time = time.time()\n", " for _fold in range(NFOLDS):\n", " print(f'Fold{_fold}:')\n", " seed_everything(seed=42+_fold)\n", " torch.cuda.empty_cache()\n", " device = torch.device(\"cuda:0\")\n", " model = Model()\n", " model.to(device)\n", " # model = nn.DataParallel(model)\n", "\n", " optimizer = torch.optim.Adam(model.parameters(), lr=LEARNING_RATE, weight_decay=WEIGHT_DECAY)\n", " # optimizer = Nadam(model.parameters(), lr=LEARNING_RATE, weight_decay=WEIGHT_DECAY)\n", " # optimizer = Lookahead(optimizer=optimizer, k=10, alpha=0.5)\n", " scheduler = None\n", " # scheduler = torch.optim.lr_scheduler.OneCycleLR(optimizer=optimizer, pct_start=0.1, div_factor=1e3,\n", " # max_lr=1e-2, epochs=EPOCHS, steps_per_epoch=len(train_loader))\n", " # loss_fn = nn.BCEWithLogitsLoss()\n", " loss_fn = SmoothBCEwLogits(smoothing=0.005)\n", "\n", " model_weights = f\"{CACHE_PATH}/online_model{_fold}.pth\"\n", " es = EarlyStopping(patience=EARLYSTOP_NUM, mode=\"max\")\n", " for epoch in range(EPOCHS):\n", " train_loss = train_fn(model, optimizer, scheduler, loss_fn, train_loader, device)\n", "\n", " valid_pred = inference_fn(model, valid_loader, device)\n", " valid_auc = roc_auc_score(valid[target_cols].values, valid_pred)\n", " valid_logloss = log_loss(valid[target_cols].values, valid_pred)\n", " valid_pred = np.median(valid_pred, axis=1)\n", " valid_pred = np.where(valid_pred >= 0.5, 1, 0).astype(int)\n", " valid_u_score = utility_score_bincount(date=valid.date.values, weight=valid.weight.values,\n", " resp=valid.resp.values, action=valid_pred)\n", " print(f\"FOLD{_fold} EPOCH:{epoch:3} train_loss={train_loss:.5f} \"\n", " f\"valid_u_score={valid_u_score:.5f} valid_auc={valid_auc:.5f} \"\n", " f\"time: {(time.time() - start_time) / 60:.2f}min\")\n", " es(valid_auc, model, model_path=model_weights)\n", " if es.early_stop:\n", " print(\"Early stopping\")\n", " break\n", " # torch.save(model.state_dict(), model_weights)\n", " if True:\n", " valid_pred = np.zeros((len(valid), len(target_cols)))\n", " for _fold in range(NFOLDS):\n", " torch.cuda.empty_cache()\n", " device = torch.device(\"cuda:0\")\n", " model = Model()\n", " model.to(device)\n", " model_weights = f\"{CACHE_PATH}/online_model{_fold}.pth\"\n", " model.load_state_dict(torch.load(model_weights))\n", "\n", " valid_pred += inference_fn(model, valid_loader, device) / NFOLDS\n", " auc_score = roc_auc_score(valid[target_cols].values, valid_pred)\n", " logloss_score = log_loss(valid[target_cols].values, valid_pred)\n", " \n", " \n", " valid_pred = np.median(valid_pred, axis=1)\n", " valid_pred = np.where(valid_pred >= 0.5, 1, 0).astype(int)\n", " valid_score = utility_score_bincount(date=valid.date.values, weight=valid.weight.values, resp=valid.resp.values,\n", " action=valid_pred)\n", " print(f'{NFOLDS} models valid score: {valid_score}\\tauc_score: {auc_score:.4f}\\tlogloss_score:{logloss_score:.4f}')\n", " \n", " " ] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": 0.020857, "end_time": "2021-02-27T00:08:03.709139", "exception": false, "start_time": "2021-02-27T00:08:03.688282", "status": "completed" }, "tags": [] }, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": 0.021165, "end_time": "2021-02-27T00:08:03.751904", "exception": false, "start_time": "2021-02-27T00:08:03.730739", "status": "completed" }, "tags": [] }, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": 0.021256, "end_time": "2021-02-27T00:08:03.794912", "exception": false, "start_time": "2021-02-27T00:08:03.773656", "status": "completed" }, "tags": [] }, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": 0.020107, "end_time": "2021-02-27T00:08:03.835990", "exception": false, "start_time": "2021-02-27T00:08:03.815883", "status": "completed" }, "tags": [] }, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": 0.020778, "end_time": "2021-02-27T00:08:03.877789", "exception": false, "start_time": "2021-02-27T00:08:03.857011", "status": "completed" }, "tags": [] }, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.9" }, "papermill": { "default_parameters": {}, "duration": 2026.215651, "end_time": "2021-02-27T00:08:05.212824", "environment_variables": {}, "exception": null, "input_path": "__notebook__.ipynb", "output_path": "__notebook__.ipynb", "parameters": {}, "start_time": "2021-02-26T23:34:18.997173", "version": "2.2.2" } }, "nbformat": 4, "nbformat_minor": 4 }	0055/327/55327361.ipynb	s3://data-agents/kaggle-outputs/sharded/012_00055.jsonl.gz
{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": { "_kg_hide-input": true, "_kg_hide-output": true, "execution": { "iopub.execute_input": "2021-02-26T23:41:14.314004Z", "iopub.status.busy": "2021-02-26T23:41:14.313241Z", "iopub.status.idle": "2021-02-26T23:41:18.535544Z", "shell.execute_reply": "2021-02-26T23:41:18.536059Z" }, "papermill": { "duration": 4.273352, "end_time": "2021-02-26T23:41:18.536507", "exception": false, "start_time": "2021-02-26T23:41:14.263155", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "['Iris.csv', 'database.sqlite']\n" ] }, { "data": { "text/html": [ " <script type=\"text/javascript\">\n", " window.PlotlyConfig = {MathJaxConfig: 'local'};\n", " if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}\n", " if (typeof require !== 'undefined') {\n", " require.undef(\"plotly\");\n", " requirejs.config({\n", " paths: {\n", " 'plotly': ['https://cdn.plot.ly/plotly-latest.min']\n", " }\n", " });\n", " require(['plotly'], function(Plotly) {\n", " window._Plotly = Plotly;\n", " });\n", " }\n", " </script>\n", " " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "\n", "import numpy as np # linear algebra\n", "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n", "import os\n", "print(os.listdir(\"../input\"))\n", "import cufflinks as cf\n", "cf.set_config_file(offline=True)\n", "from sklearn.model_selection import train_test_split\n", "from sklearn.metrics import accuracy_score\n", "from sklearn.neighbors import KNeighborsClassifier\n", "from sklearn.ensemble import RandomForestClassifier\n", "from sklearn.linear_model import LogisticRegression, SGDClassifier\n", "from xgboost import XGBClassifier\n", "from vecstack import stacking\n", "df = pd.read_csv(\"../input/Iris.csv\")\n", "df.sample(5)\n", "import seaborn as sns\n", "import matplotlib.pyplot as plt\n" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.039858, "end_time": "2021-02-26T23:41:18.618130", "exception": false, "start_time": "2021-02-26T23:41:18.578272", "status": "completed" }, "tags": [] }, "source": [ "https://towardsdatascience.com/sweetviz-automated-eda-in-python-a97e4cabacde" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "_kg_hide-output": true, "execution": { "iopub.execute_input": "2021-02-26T23:41:18.702595Z", "iopub.status.busy": "2021-02-26T23:41:18.701872Z", "iopub.status.idle": "2021-02-26T23:43:48.872484Z", "shell.execute_reply": "2021-02-26T23:43:48.873181Z" }, "papermill": { "duration": 150.215024, "end_time": "2021-02-26T23:43:48.873420", "exception": false, "start_time": "2021-02-26T23:41:18.658396", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[33mWARNING: Retrying (Retry(total=4, connect=None, read=None, redirect=None, status=None)) after connection broken by 'NewConnectionError('<pip._vendor.urllib3.connection.HTTPSConnection object at 0x7f353f099b50>: Failed to establish a new connection: [Errno -3] Temporary failure in name resolution')': /simple/sweetviz/\u001b[0m\r\n", "\u001b[33mWARNING: Retrying (Retry(total=3, connect=None, read=None, redirect=None, status=None)) after connection broken by 'NewConnectionError('<pip._vendor.urllib3.connection.HTTPSConnection object at 0x7f353f099f10>: Failed to establish a new connection: [Errno -3] Temporary failure in name resolution')': /simple/sweetviz/\u001b[0m\r\n", "\u001b[33mWARNING: Retrying (Retry(total=2, connect=None, read=None, redirect=None, status=None)) after connection broken by 'NewConnectionError('<pip._vendor.urllib3.connection.HTTPSConnection object at 0x7f353f0a1290>: Failed to establish a new connection: [Errno -3] Temporary failure in name resolution')': /simple/sweetviz/\u001b[0m\r\n", "\u001b[33mWARNING: Retrying (Retry(total=1, connect=None, read=None, redirect=None, status=None)) after connection broken by 'NewConnectionError('<pip._vendor.urllib3.connection.HTTPSConnection object at 0x7f353f0a15d0>: Failed to establish a new connection: [Errno -3] Temporary failure in name resolution')': /simple/sweetviz/\u001b[0m\r\n", "\u001b[33mWARNING: Retrying (Retry(total=0, connect=None, read=None, redirect=None, status=None)) after connection broken by 'NewConnectionError('<pip._vendor.urllib3.connection.HTTPSConnection object at 0x7f353f0a1910>: Failed to establish a new connection: [Errno -3] Temporary failure in name resolution')': /simple/sweetviz/\u001b[0m\r\n", "\u001b[31mERROR: Could not find a version that satisfies the requirement sweetviz\u001b[0m\r\n", "\u001b[31mERROR: No matching distribution found for sweetviz\u001b[0m\r\n" ] }, { "ename": "ModuleNotFoundError", "evalue": "No module named 'sweetviz'", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m<ipython-input-2-d3a0bfeafdce>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0mget_ipython\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msystem\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'pip install sweetviz'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0;32mimport\u001b[0m \u001b[0msweetviz\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0msv\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'sweetviz'" ] } ], "source": [ "\n", "!pip install sweetviz\n", "import sweetviz as sv" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:43:48.975913Z", "iopub.status.busy": "2021-02-26T23:43:48.975087Z", "iopub.status.idle": "2021-02-26T23:43:48.979390Z", "shell.execute_reply": "2021-02-26T23:43:48.978759Z" }, "papermill": { "duration": 0.063493, "end_time": "2021-02-26T23:43:48.979535", "exception": false, "start_time": "2021-02-26T23:43:48.916042", "status": "completed" }, "tags": [] }, "outputs": [ { "ename": "NameError", "evalue": "name 'sv' is not defined", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m<ipython-input-3-852301991a03>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0miris_report\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msv\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0manalyze\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdf\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 2\u001b[0m \u001b[0miris_report\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mshow_html\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'iris.html'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;31mNameError\u001b[0m: name 'sv' is not defined" ] } ], "source": [ "iris_report = sv.analyze(df)\n", "iris_report.show_html('iris.html')" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:43:49.077364Z", "iopub.status.busy": "2021-02-26T23:43:49.076630Z", "iopub.status.idle": "2021-02-26T23:43:49.800976Z", "shell.execute_reply": "2021-02-26T23:43:49.800253Z" }, "papermill": { "duration": 0.778511, "end_time": "2021-02-26T23:43:49.801138", "exception": false, "start_time": "2021-02-26T23:43:49.022627", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "__notebook__.ipynb\r\n" ] } ], "source": [ "!ls" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.043101, "end_time": "2021-02-26T23:43:49.889121", "exception": false, "start_time": "2021-02-26T23:43:49.846020", "status": "completed" }, "tags": [] }, "source": [ "https://pypi.org/project/dtale/" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "_kg_hide-output": true, "execution": { "iopub.execute_input": "2021-02-26T23:43:49.986587Z", "iopub.status.busy": "2021-02-26T23:43:49.981206Z", "iopub.status.idle": "2021-02-26T23:45:42.772211Z", "shell.execute_reply": "2021-02-26T23:45:42.772752Z" }, "papermill": { "duration": 112.840408, "end_time": "2021-02-26T23:45:42.772956", "exception": false, "start_time": "2021-02-26T23:43:49.932548", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Collecting package metadata (current_repodata.json): - \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\b\| \b\b/ \b\b- \b\b\\ \b\bfailed\r\n", "\r\n", "CondaHTTPError: HTTP 000 CONNECTION FAILED for url <https://conda.anaconda.org/conda-forge/linux-64/current_repodata.json>\r\n", "Elapsed: -\r\n", "\r\n", "An HTTP error occurred when trying to retrieve this URL.\r\n", "HTTP errors are often intermittent, and a simple retry will get you on your way.\r\n", "'https://conda.anaconda.org/conda-forge/linux-64'\r\n", "\r\n", "\r\n" ] } ], "source": [ "!conda install dtale -c conda-forge -y" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "_kg_hide-output": true, "execution": { "iopub.execute_input": "2021-02-26T23:45:43.376880Z", "iopub.status.busy": "2021-02-26T23:45:43.376103Z", "iopub.status.idle": "2021-02-26T23:48:12.829874Z", "shell.execute_reply": "2021-02-26T23:48:12.829154Z" }, "papermill": { "duration": 149.760459, "end_time": "2021-02-26T23:48:12.830024", "exception": false, "start_time": "2021-02-26T23:45:43.069565", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[33mWARNING: Retrying (Retry(total=4, connect=None, read=None, redirect=None, status=None)) after connection broken by 'NewConnectionError('<pip._vendor.urllib3.connection.HTTPSConnection object at 0x7fe40e761050>: Failed to establish a new connection: [Errno -3] Temporary failure in name resolution')': /simple/flask-ngrok/\u001b[0m\r\n", "\u001b[33mWARNING: Retrying (Retry(total=3, connect=None, read=None, redirect=None, status=None)) after connection broken by 'NewConnectionError('<pip._vendor.urllib3.connection.HTTPSConnection object at 0x7fe40d395c10>: Failed to establish a new connection: [Errno -3] Temporary failure in name resolution')': /simple/flask-ngrok/\u001b[0m\r\n", "\u001b[33mWARNING: Retrying (Retry(total=2, connect=None, read=None, redirect=None, status=None)) after connection broken by 'NewConnectionError('<pip._vendor.urllib3.connection.HTTPSConnection object at 0x7fe40d3a1910>: Failed to establish a new connection: [Errno -3] Temporary failure in name resolution')': /simple/flask-ngrok/\u001b[0m\r\n", "\u001b[33mWARNING: Retrying (Retry(total=1, connect=None, read=None, redirect=None, status=None)) after connection broken by 'NewConnectionError('<pip._vendor.urllib3.connection.HTTPSConnection object at 0x7fe40d3a16d0>: Failed to establish a new connection: [Errno -3] Temporary failure in name resolution')': /simple/flask-ngrok/\u001b[0m\r\n", "\u001b[33mWARNING: Retrying (Retry(total=0, connect=None, read=None, redirect=None, status=None)) after connection broken by 'NewConnectionError('<pip._vendor.urllib3.connection.HTTPSConnection object at 0x7fe40d3a1a90>: Failed to establish a new connection: [Errno -3] Temporary failure in name resolution')': /simple/flask-ngrok/\u001b[0m\r\n", "\u001b[31mERROR: Could not find a version that satisfies the requirement flask_ngrok\u001b[0m\r\n", "\u001b[31mERROR: No matching distribution found for flask_ngrok\u001b[0m\r\n" ] } ], "source": [ "!pip install flask_ngrok" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:48:13.441742Z", "iopub.status.busy": "2021-02-26T23:48:13.430629Z", "iopub.status.idle": "2021-02-26T23:48:13.454109Z", "shell.execute_reply": "2021-02-26T23:48:13.454679Z" }, "papermill": { "duration": 0.32632, "end_time": "2021-02-26T23:48:13.454862", "exception": false, "start_time": "2021-02-26T23:48:13.128542", "status": "completed" }, "tags": [] }, "outputs": [ { "ename": "ModuleNotFoundError", "evalue": "No module named 'dtale'", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mModuleNotFoundError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m<ipython-input-7-5442b09ef9d6>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mpandas\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m \u001b[0;32mimport\u001b[0m \u001b[0mdtale\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 5\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mdtale\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapp\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mdtale_app\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 6\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'dtale'" ] } ], "source": [ "#https://www.youtube.com/watch?v=8Il-2HHs2Mg\n", "import pandas as pd\n", "\n", "import dtale\n", "import dtale.app as dtale_app\n", "\n", "dtale_app.USE_NGROK = True\n", "d=dtale.show(df)\n", "d.main_url()" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:48:14.063060Z", "iopub.status.busy": "2021-02-26T23:48:14.062041Z", "iopub.status.idle": "2021-02-26T23:48:14.067288Z", "shell.execute_reply": "2021-02-26T23:48:14.067929Z" }, "papermill": { "duration": 0.316553, "end_time": "2021-02-26T23:48:14.068089", "exception": false, "start_time": "2021-02-26T23:48:13.751536", "status": "completed" }, "tags": [] }, "outputs": [ { "ename": "NameError", "evalue": "name 'dtale' is not defined", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m<ipython-input-8-fa8608b83391>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mdtale\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minstances\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", "\u001b[0;31mNameError\u001b[0m: name 'dtale' is not defined" ] } ], "source": [ "dtale.instances()" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:48:14.688822Z", "iopub.status.busy": "2021-02-26T23:48:14.680587Z", "iopub.status.idle": "2021-02-26T23:48:14.693175Z", "shell.execute_reply": "2021-02-26T23:48:14.692645Z" }, "papermill": { "duration": 0.326698, "end_time": "2021-02-26T23:48:14.693366", "exception": false, "start_time": "2021-02-26T23:48:14.366668", "status": "completed" }, "tags": [] }, "outputs": [ { "ename": "NameError", "evalue": "name 'dtale' is not defined", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m<ipython-input-9-b9f0cc5fe694>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mdtale\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_instance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkill\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", "\u001b[0;31mNameError\u001b[0m: name 'dtale' is not defined" ] } ], "source": [ "dtale.get_instance(1).kill()" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "_kg_hide-input": false, "_kg_hide-output": true, "execution": { "iopub.execute_input": "2021-02-26T23:48:15.416599Z", "iopub.status.busy": "2021-02-26T23:48:15.415426Z", "iopub.status.idle": "2021-02-26T23:49:09.369231Z", "shell.execute_reply": "2021-02-26T23:49:09.368666Z" }, "papermill": { "duration": 54.340305, "end_time": "2021-02-26T23:49:09.369426", "exception": false, "start_time": "2021-02-26T23:48:15.029121", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Requirement already satisfied: plotly in /opt/conda/lib/python3.7/site-packages (4.14.3)\r\n", "Requirement already satisfied: six in /opt/conda/lib/python3.7/site-packages (from plotly) (1.15.0)\r\n", "Requirement already satisfied: retrying>=1.3.3 in /opt/conda/lib/python3.7/site-packages (from plotly) (1.3.3)\r\n", "Requirement already satisfied: cufflinks in /opt/conda/lib/python3.7/site-packages (0.17.3)\r\n", "Requirement already satisfied: numpy>=1.9.2 in /opt/conda/lib/python3.7/site-packages (from 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/opt/conda/lib/python3.7/site-packages (from packaging->bleach->nbconvert->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets>=7.0.0->cufflinks) (2.4.7)\r\n" ] } ], "source": [ "#https://github.com/santosjorge/cufflinks/issues/185\n", "!pip install plotly\n", "!pip install cufflinks" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "_kg_hide-input": true, "_kg_hide-output": true, "execution": { "iopub.execute_input": "2021-02-26T23:49:09.999081Z", "iopub.status.busy": "2021-02-26T23:49:09.998023Z", "iopub.status.idle": "2021-02-26T23:49:10.002232Z", "shell.execute_reply": "2021-02-26T23:49:10.001613Z" }, "papermill": { "duration": 0.330402, "end_time": "2021-02-26T23:49:10.002389", "exception": false, "start_time": "2021-02-26T23:49:09.671987", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "<class 'pandas.core.frame.DataFrame'>\n", "RangeIndex: 150 entries, 0 to 149\n", "Data columns (total 6 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 Id 150 non-null int64 \n", " 1 SepalLengthCm 150 non-null float64\n", " 2 SepalWidthCm 150 non-null float64\n", " 3 PetalLengthCm 150 non-null float64\n", " 4 PetalWidthCm 150 non-null float64\n", " 5 Species 150 non-null object \n", "dtypes: float64(4), int64(1), object(1)\n", "memory usage: 7.2+ KB\n" ] } ], "source": [ "df.info()" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "_kg_hide-output": true, "execution": { "iopub.execute_input": "2021-02-26T23:49:10.714812Z", "iopub.status.busy": "2021-02-26T23:49:10.714083Z", "iopub.status.idle": "2021-02-26T23:49:10.778006Z", "shell.execute_reply": "2021-02-26T23:49:10.777488Z" }, "papermill": { "duration": 0.382282, "end_time": "2021-02-26T23:49:10.778156", "exception": false, "start_time": "2021-02-26T23:49:10.395874", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>Species</th>\n", " <th>Iris-setosa</th>\n", " <th>Iris-versicolor</th>\n", " <th>Iris-virginica</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th rowspan=\"8\" valign=\"top\">Id</th>\n", " <th>count</th>\n", " <td>50.000000</td>\n", " <td>50.000000</td>\n", " <td>50.000000</td>\n", " </tr>\n", " <tr>\n", " <th>mean</th>\n", " <td>25.500000</td>\n", " <td>75.500000</td>\n", " <td>125.500000</td>\n", " </tr>\n", " <tr>\n", " <th>std</th>\n", " <td>14.577380</td>\n", " <td>14.577380</td>\n", " <td>14.577380</td>\n", " </tr>\n", " <tr>\n", " <th>min</th>\n", " <td>1.000000</td>\n", " <td>51.000000</td>\n", " <td>101.000000</td>\n", " </tr>\n", " <tr>\n", " <th>25%</th>\n", " <td>13.250000</td>\n", " <td>63.250000</td>\n", " <td>113.250000</td>\n", " </tr>\n", " <tr>\n", " <th>50%</th>\n", " <td>25.500000</td>\n", " <td>75.500000</td>\n", " <td>125.500000</td>\n", " </tr>\n", " <tr>\n", " <th>75%</th>\n", " <td>37.750000</td>\n", " <td>87.750000</td>\n", " <td>137.750000</td>\n", " </tr>\n", " <tr>\n", " <th>max</th>\n", " <td>50.000000</td>\n", " <td>100.000000</td>\n", " <td>150.000000</td>\n", " </tr>\n", " <tr>\n", " <th rowspan=\"8\" valign=\"top\">SepalLengthCm</th>\n", " <th>count</th>\n", " <td>50.000000</td>\n", " <td>50.000000</td>\n", " <td>50.000000</td>\n", " </tr>\n", " <tr>\n", " <th>mean</th>\n", " <td>5.006000</td>\n", " <td>5.936000</td>\n", " <td>6.588000</td>\n", " </tr>\n", " <tr>\n", " <th>std</th>\n", " <td>0.352490</td>\n", " <td>0.516171</td>\n", " <td>0.635880</td>\n", " </tr>\n", " <tr>\n", " <th>min</th>\n", " <td>4.300000</td>\n", " <td>4.900000</td>\n", " <td>4.900000</td>\n", " </tr>\n", " <tr>\n", " <th>25%</th>\n", " <td>4.800000</td>\n", " <td>5.600000</td>\n", " <td>6.225000</td>\n", " </tr>\n", " <tr>\n", " <th>50%</th>\n", " <td>5.000000</td>\n", " <td>5.900000</td>\n", " <td>6.500000</td>\n", " </tr>\n", " <tr>\n", " <th>75%</th>\n", " <td>5.200000</td>\n", " <td>6.300000</td>\n", " <td>6.900000</td>\n", " </tr>\n", " <tr>\n", " <th>max</th>\n", " <td>5.800000</td>\n", " <td>7.000000</td>\n", " <td>7.900000</td>\n", " </tr>\n", " <tr>\n", " <th rowspan=\"8\" valign=\"top\">SepalWidthCm</th>\n", " <th>count</th>\n", " <td>50.000000</td>\n", " <td>50.000000</td>\n", " <td>50.000000</td>\n", " </tr>\n", " <tr>\n", " <th>mean</th>\n", " <td>3.418000</td>\n", " <td>2.770000</td>\n", " <td>2.974000</td>\n", " </tr>\n", " <tr>\n", " <th>std</th>\n", " <td>0.381024</td>\n", " <td>0.313798</td>\n", " <td>0.322497</td>\n", " </tr>\n", " <tr>\n", " <th>min</th>\n", " <td>2.300000</td>\n", " <td>2.000000</td>\n", " <td>2.200000</td>\n", " </tr>\n", " <tr>\n", " <th>25%</th>\n", " <td>3.125000</td>\n", " <td>2.525000</td>\n", " <td>2.800000</td>\n", " </tr>\n", " <tr>\n", " <th>50%</th>\n", " <td>3.400000</td>\n", " <td>2.800000</td>\n", " <td>3.000000</td>\n", " </tr>\n", " <tr>\n", " <th>75%</th>\n", " <td>3.675000</td>\n", " <td>3.000000</td>\n", " <td>3.175000</td>\n", " </tr>\n", " <tr>\n", " <th>max</th>\n", " <td>4.400000</td>\n", " <td>3.400000</td>\n", " <td>3.800000</td>\n", " </tr>\n", " <tr>\n", " <th rowspan=\"8\" valign=\"top\">PetalLengthCm</th>\n", " <th>count</th>\n", " <td>50.000000</td>\n", " <td>50.000000</td>\n", " <td>50.000000</td>\n", " </tr>\n", " <tr>\n", " <th>mean</th>\n", " <td>1.464000</td>\n", " <td>4.260000</td>\n", " <td>5.552000</td>\n", " </tr>\n", " <tr>\n", " <th>std</th>\n", " <td>0.173511</td>\n", " <td>0.469911</td>\n", " <td>0.551895</td>\n", " </tr>\n", " <tr>\n", " <th>min</th>\n", " <td>1.000000</td>\n", " <td>3.000000</td>\n", " <td>4.500000</td>\n", " </tr>\n", " <tr>\n", " <th>25%</th>\n", " <td>1.400000</td>\n", " <td>4.000000</td>\n", " <td>5.100000</td>\n", " </tr>\n", " <tr>\n", " <th>50%</th>\n", " <td>1.500000</td>\n", " <td>4.350000</td>\n", " <td>5.550000</td>\n", " </tr>\n", " <tr>\n", " <th>75%</th>\n", " <td>1.575000</td>\n", " <td>4.600000</td>\n", " <td>5.875000</td>\n", " </tr>\n", " <tr>\n", " <th>max</th>\n", " <td>1.900000</td>\n", " <td>5.100000</td>\n", " <td>6.900000</td>\n", " </tr>\n", " <tr>\n", " <th rowspan=\"8\" valign=\"top\">PetalWidthCm</th>\n", " <th>count</th>\n", " <td>50.000000</td>\n", " <td>50.000000</td>\n", " <td>50.000000</td>\n", " </tr>\n", " <tr>\n", " <th>mean</th>\n", " <td>0.244000</td>\n", " <td>1.326000</td>\n", " <td>2.026000</td>\n", " </tr>\n", " <tr>\n", " <th>std</th>\n", " <td>0.107210</td>\n", " <td>0.197753</td>\n", " <td>0.274650</td>\n", " </tr>\n", " <tr>\n", " <th>min</th>\n", " <td>0.100000</td>\n", " <td>1.000000</td>\n", " <td>1.400000</td>\n", " </tr>\n", " <tr>\n", " <th>25%</th>\n", " <td>0.200000</td>\n", " <td>1.200000</td>\n", " <td>1.800000</td>\n", " </tr>\n", " <tr>\n", " <th>50%</th>\n", " <td>0.200000</td>\n", " <td>1.300000</td>\n", " <td>2.000000</td>\n", " </tr>\n", " <tr>\n", " <th>75%</th>\n", " <td>0.300000</td>\n", " <td>1.500000</td>\n", " <td>2.300000</td>\n", " </tr>\n", " <tr>\n", " <th>max</th>\n", " <td>0.600000</td>\n", " <td>1.800000</td>\n", " <td>2.500000</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ "Species Iris-setosa Iris-versicolor Iris-virginica\n", "Id count 50.000000 50.000000 50.000000\n", " mean 25.500000 75.500000 125.500000\n", " std 14.577380 14.577380 14.577380\n", " min 1.000000 51.000000 101.000000\n", " 25% 13.250000 63.250000 113.250000\n", " 50% 25.500000 75.500000 125.500000\n", " 75% 37.750000 87.750000 137.750000\n", " max 50.000000 100.000000 150.000000\n", "SepalLengthCm count 50.000000 50.000000 50.000000\n", " mean 5.006000 5.936000 6.588000\n", " std 0.352490 0.516171 0.635880\n", " min 4.300000 4.900000 4.900000\n", " 25% 4.800000 5.600000 6.225000\n", " 50% 5.000000 5.900000 6.500000\n", " 75% 5.200000 6.300000 6.900000\n", " max 5.800000 7.000000 7.900000\n", "SepalWidthCm count 50.000000 50.000000 50.000000\n", " mean 3.418000 2.770000 2.974000\n", " std 0.381024 0.313798 0.322497\n", " min 2.300000 2.000000 2.200000\n", " 25% 3.125000 2.525000 2.800000\n", " 50% 3.400000 2.800000 3.000000\n", " 75% 3.675000 3.000000 3.175000\n", " max 4.400000 3.400000 3.800000\n", "PetalLengthCm count 50.000000 50.000000 50.000000\n", " mean 1.464000 4.260000 5.552000\n", " std 0.173511 0.469911 0.551895\n", " min 1.000000 3.000000 4.500000\n", " 25% 1.400000 4.000000 5.100000\n", " 50% 1.500000 4.350000 5.550000\n", " 75% 1.575000 4.600000 5.875000\n", " max 1.900000 5.100000 6.900000\n", "PetalWidthCm count 50.000000 50.000000 50.000000\n", " mean 0.244000 1.326000 2.026000\n", " std 0.107210 0.197753 0.274650\n", " min 0.100000 1.000000 1.400000\n", " 25% 0.200000 1.200000 1.800000\n", " 50% 0.200000 1.300000 2.000000\n", " 75% 0.300000 1.500000 2.300000\n", " max 0.600000 1.800000 2.500000" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.groupby(by='Species').describe().T" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:49:11.416442Z", "iopub.status.busy": "2021-02-26T23:49:11.408837Z", "iopub.status.idle": "2021-02-26T23:49:18.062074Z", "shell.execute_reply": "2021-02-26T23:49:18.062644Z" }, "papermill": { "duration": 6.979796, "end_time": "2021-02-26T23:49:18.062830", "exception": false, "start_time": "2021-02-26T23:49:11.083034", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 1003.25x900 with 30 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# https://seaborn.pydata.org/examples/scatterplot_matrix.html\n", "ax = sns.pairplot(df, hue=\"Species\")" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:49:18.697742Z", "iopub.status.busy": "2021-02-26T23:49:18.696675Z", "iopub.status.idle": "2021-02-26T23:49:18.856021Z", "shell.execute_reply": "2021-02-26T23:49:18.855436Z" }, "papermill": { "duration": 0.478637, "end_time": "2021-02-26T23:49:18.856164", "exception": false, "start_time": "2021-02-26T23:49:18.377527", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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P3Ys3s9mSZw/+VOA3gbMkbUp/LsjxeHVptPc+3nMzs7zkdppkRHwHUF71N4r29vYDknp7e3thsZjZ3OIrWXO2YsWKA55/9KMfLSgSM5trnOBzdswxx/yy197e3k5HR0exAZnZnOEEPwtWrFjBwoUL3Xs3s1mV51QFDae3tzeX0xiHhoZoaWmht7e35nUDdHR00NPTk0vdZta4nOBnwa5du4oOwczmICf4Cnn1gkfrzasHb2ZWjcfgzcxKygnezKykGnKIJq8vQ/OydetWIL8hoLz4y1uzxtaQCX5gYICNDz3C/kOOKDqUTPSLAGDDv/+k4Eiym/fCz4oOwcxmqCET/NDQEBBFh5FZLDis6BCmIdLX2cwalcfgzcxKqiF78G1tbfx0TzO7j3tn0aGU1oJH7qKt7ZVFh2FmM+AevJlZSTVkDx6SLwEXPHJX0WFkot3JnQobaSw++ZLVPXizRtaQCb7RZmTcunU7AEtf30gJ85UN9zqb2YEaMsE32rnZnqrAzIrgMXgzs5JygjczKykneDOzkmrIMfi85DXHTd5z0XjOGDOrxj34WXDwwQezZ88eRkZGig7FzOYQ9+Ar5NUL/tSnPsWdd97J0qVLufrqq3M5hpnZWO7B52zbtm2sXr2aiGD16tU888wzRYdkZnOEE3zO+vr62L9/PwD79u2jr6+v4IjMbK7ILcFL+pKkpyVtzusYjWDt2rXs3bsXgL1797JmzZqCIzKzuSLPHvzNwPk51t8QTjvttAOen3766QVFYmZzTW4JPiLWA74tkJlZQQofg5e0XFK/pP7h4eGiw6m5e+6554Dn69evLygSM5trCk/wEbEqIjojorO1tbXocGru3HPPpbk5ORu1ubmZ8847r+CIzGyuKDzBl113dzfz5iUvc1NTE93d3QVHZGZzhRN8zpYsWUJXVxeS6OrqYvHixUWHZGZzRJ6nSd4G/CtwrKQhSf85r2PVu+7ubk444QT33s1sVikiio7hlzo7O6O/v7/oMMzMGoakDRHRWW2dh2jMzErKCd7MrKSc4M3MSsoJ3syspOrqS1ZJw8ATRceRkyXAtqKDsGlz+zW2MrffayOi6lWidZXgy0xS/3jfdFv9c/s1trnafh6iMTMrKSd4M7OScoKfPauKDsBmxO3X2OZk+3kM3syspNyDNzMrKSd4M7OScoJPSdoxwbrv5njcP8mr7rIoqm2ykPRqSV+Z5r7rJM2pU/fybktJ10o6Z4r7XCjpjyfZZtrtXCSPwack7YiIRWPKmiJi32wf1w5UVNuMOV5zROytcZ3rgN+PiExTqM7275yHAt9nDf/aTYd78GNIOkPStyXdCjyUlu1IH18lab2kTZI2Szqtyv5vknRfus2Dkpam5ZdVlH9BUpOkvwBa0rJb0u2uTuveLOmqtGyhpH+U9P20/OK0/KOS7k/LVknSrLxIBZlJ20h6maRBSfPS54dI+qGk+ZJeL+luSRsk3SPpDek2N0v6tKRvA9dJenta/yZJGyUdKqld0uZ0+yZJn5T0UNr2V6TlZ6fbPyTpS5IOrvK7XZKu3yzpuoryHWmv9F7glFxe2ALk2JY3S7ooLR9M3yPfAX5D0gWSHpP0HUm9ku5Kt/ugpM+myzen674r6fGKurK0c/29HyPCP8mnmB3p4xnATuB1VdZ9GPhIutwEHFqlnhuAS9Plg4AW4I3AN4D5afnngQ9U1p0uv4Xkj30hsAh4GHgz8B7gixXbvSx9PKKi7O+AdxX9OtZ523wdODNdvhi4MV3+JrA0XX4b8K10+WbgLqApff4N4NR0eRHQDLQDm9Oy3wO+CjSPtg+wAPghcExa9r+Aq9LldUAn8GrgSaA1rfNbwLvTbQJ4b9Ft0EBteTNwUbo8CPxhujzaDq9Ln98G3JUufxD4bMX+t5N0fo8DBtLyCdu58jFdrov3o3vw1d0XET+oUn4/cLmkjwHHR8T2Ktv8K/Ankv6IZI6IXcDZJMn7fkmb0udHV9n314A7ImJnROwAvgacRpL0z5F0naTTIuK5dPszJd0r6SHgLOBN0/2FG8hM2ubLJMkA4H3AlyUtAv4jcHvaNl8AXlWxz+3x4kf7/wd8WlIPcHi8dMjmHOBvRssj4mfAscAPImJLuk0fcPqY/d4KrIuI4XTfWyq22UeSTMqopm05zjFGy98APF5xvNsmiOv/RMT+iHgEeEWV9dXaGerw/egEX93OaoURsZ7kjfcj4O8kfUDSr1d8bO+MiFuBC4FdwP+VdBYgoC8ilqU/x0bEx6ocoupHujQ5jPbu/zz9KLiA5JPARRFxPPBFkl5K2U27bYA7gS5JR5C8nt8ieQ88W9E2yyLijdWOFxF/Afw2yaey740O5VQQSY97bNlkJtpmd5R37LjWbTnRMaYyXLKnYrnafi9p53p9PzrBT4Gk1wJPR8QXgb8FToqIOyoSQ7+ko0l6Cr0kf4QnkAwBXCTp5Wk9R6R1AYxImp8urwfenY4pLgR+HbhH0quBFyLi74FPAifx4h/PtrQXelHuL0Ady9I26aei+4DrST6e74uI54EfSPqNtB5JOnGcY7w+Ih6KiOuAfpJeYaU1wO9Kak63PwJ4DGiX1JFu85vAv4zZ717g7ZKWSGoCLqmyzZwx3bacpNrHgKMltafPL55g28lUa+e6fD82Fx1AgzkD+ANJI8AO4ANVtrkYuCzd5ifAtRHxM0krgDXpF0MjwH8jmRp5FfCgpAci4lJJN5P84UIyrrhR0juAv5S0P9339yLiWUlfJOnVD5J8rJ3LzmDytoHkI/vt6fajLgX+Om2j+cD/Br5fZd+rJJ1JMmzyCLCaA4dzbgSOIWnPEZLvTT4r6XKSIaBmknb6m8pKI+LHkq4Bvk3SO/yniPh61l+8hM5g+m1ZVUTskvRfgbslbePF99h0jNfOdfd+9GmSZjYnSFoUETvSs1s+B2yNiM8UHVeePERjZnPF76RfpD8MvIzkC/VScw/ezKyk3IM3MyspJ3gzs5JygjczKykneCs1SR+R9HA6Z8gmSW+rYd3/JOnwWtVnVms+D95KS9IpwDtJLpTZI2kJyfxANRERF9SqLrM8uAdvZfYqYFtE7AGIiG0R8ZSSWQavUzK7532jV5lKapX01XRGwPslnZqWL5J0k16cPfA9aflg+k9jvNlCm5TMTrg53fe/F/Q62BzlBG9ltgZ4jaQtkj4v6e0V656PiJOBzwJ/lZZdD3wmIt5KMoPnjWn5nwLPRcTxEXECY+Y9kfRGkiuYT42IZSRXul4KLAOOjIhfTecnuSmH39FsXB6isdJKr1p8C8mMnGeSzB45euee2yoeR69mPAc4Ti9O432YpEPT8vdV1PvzMYeqnC0UksnIniaZXvhoSTcA/0jyD8ds1jjBW6mlk1CtA9al07h2j66q3Cx9nAeckk7x/Evppe0TXRE4OlvoNS9ZkUxc9g6SuYfeC/zWNH4Ns2nxEI2VlqRjld5RK7WMZII3eHE2wYtJ5vCHpIf9oYr9l41T/itjDlV1ttB0fH5eRHyVZJjnpJn+TmZT4R68ldki4Ib0VMa9wACwnOTMmoOV3AZvHsn0vAA9wOckPUjy3lgP/C6wMi3fTDK+/nGSm7EAEBGPjDNb6C7gprQM4CU9fLM8eS4am3MkDQKdEbGt6FjM8uQhGjOzknIP3syspNyDNzMrKSd4M7OScoI3MyspJ3gzs5JygjczK6n/DwDwsaneIUiuAAAAAElFTkSuQmCC\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# https://seaborn.pydata.org/generated/seaborn.boxplot.html\n", "_ = sns.boxplot(x=\"Species\", y=\"PetalLengthCm\", data=df)" ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:49:19.498807Z", "iopub.status.busy": "2021-02-26T23:49:19.492299Z", "iopub.status.idle": "2021-02-26T23:49:19.644563Z", "shell.execute_reply": "2021-02-26T23:49:19.643993Z" }, "papermill": { "duration": 0.473215, "end_time": "2021-02-26T23:49:19.644708", "exception": false, "start_time": "2021-02-26T23:49:19.171493", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# https://seaborn.pydata.org/generated/seaborn.boxplot.html\n", "_ = sns.boxplot(x=\"Species\", y=\"PetalWidthCm\", data=df)" ] }, { "cell_type": "code", "execution_count": 16, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:49:20.294353Z", "iopub.status.busy": "2021-02-26T23:49:20.293343Z", "iopub.status.idle": "2021-02-26T23:49:20.449643Z", "shell.execute_reply": "2021-02-26T23:49:20.449030Z" }, "papermill": { "duration": 0.489654, "end_time": "2021-02-26T23:49:20.449781", "exception": false, "start_time": "2021-02-26T23:49:19.960127", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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tTNKRwLoc6wVwq6QlkmZtp85R6QK1RZIOqVVB0ixJHZI6uru7c4ZsZmZ55O0augC4CXiHpP8EJgGn5ljv6Ih4RtJewG2SHo6IOyqWLwUOiIgNkk4CbgR6nXIREfOB+QBtbW3bvXWmmZn1X597BJLeL2mfdJ3Ah4EvAq8BtwJd9RqPiGfS8/PADcDhVcvXR8SGNL0QGCtp4kDeiJmZDUy9rqHvAa+n6Q+QHSz+DvB70i/07ZG0i6TdeqaBE4FVVXX2kaQ0fXiK54V+vgczM9sB9bqGRkfEi2n6NGB+RFwPXC9peZ119wZuSN/zY4AfRcQtkmYDRMQ8su6lcyRtATYBMyLCXT9mZg1UNxFIGpPOEjoOqDzgW+/G948Bh9Yon1cxPReYmz9cMzMbbPUSwTXAryWtJfvF3jP6aCv5zhoyM7Mhrt6v+m9K+iWwL3BrRbfNKOC8ooMzM7Pi1T19NCLurlH2aDHhmJlZo+W9oMzMzEYoJwIzs5JzIjAzKzknAjOzknMiMDMrOScCM7OSyzv66LBT1E2ui1T0DbSLMtRvzG1mfRuxiaCzs5NlKx9k6/g9mh1Kbno9u15vyW9/1+RI8hu18cX6lcxsSBuxiQBg6/g9ePVg3wWzSDs/eHOzQzCzHeRjBGZmJedEYGZWck4EZmYl50RgZlZyTgRmZiXnRGBmVnKFJgJJayStlLRcUkeN5ZLULqlT0gpJU4uMx8zMemvEdQTHRsTa7SybDkxJjyOAS9OzmZk1SLMvKPsYcFW6BebdkiZI2jcint3Rhru6uhi1cZ0veCrYqI0v0NW1pdlhmNkOKPoYQQC3SloiaVaN5fsBT1XMd6WybUiaJalDUkd3d3dBoZqZlVPRewRHR8QzkvYCbpP0cETcUbFcNdaJXgUR84H5AG1tbb2W19LS0sJzr43xEBMF2/nBm2lp2afZYZjZDih0jyAinknPzwM3AIdXVekC9q+YbwGeKTImM7Nqa9eu5bzzzuOFF15odihNUVgikLSLpN16poETgVVV1W4CzkpnDx0JrBuM4wNmZv2xYMECVqxYwYIFC5odSlMUuUewN3CXpPuBe4FfRMQtkmZLmp3qLAQeAzqBy4BPFxiPmVkva9euZdGiRUQEixYtKuVeQWHHCCLiMeDQGuXzKqYDOLeoGMyqFXnDoiJvLOSb/xRnwYIFZF9FsHXrVhYsWMAFF1zQ5Kgay1cWmw2ScePGMW7cuGaHYf102223sXnzZgA2b97Mrbfe2uSIGq/Z1xGYNZR/VVu1E044gYULF7J582bGjh3LiSee2OyQGs57BGZWajNnzkTKzmQfNWoUM2fObHJEjedEYGalNnHiRKZPn44kpk+fzp577tnskBpuRHcNjdr44rAaYkKvrgcgdt69yZHkl9283heU2fA2c+ZM1qxZU8q9ARjBiaC1tbXZIfTb6tUvAzDlHcPpi3WfYfm3Nqs0ceJELrnkkmaH0TQjNhEMx4OCPTG3t7c3ORIzKxMfIzAzKzknAjOzknMiMDMrOScCM7OScyIwMys5JwIzs5JzIjAzKzknAjOzknMiMDMrOScCM7OScyIwMys5JwIzs5IrPBFIGi1pmaRe40FLmiZpnaTl6XFh0fGYmdm2GjH66GeBh4DtDbJ/Z0Sc3IA4zMyshkL3CCS1AP8duLzI1zEzs4Erumvo34C/A7b2UecoSfdLWiTpkFoVJM2S1CGpo7u7u4g4zcxKq7BEIOlk4PmIWNJHtaXAARFxKHAJcGOtShExPyLaIqJt0qRJgx+smVmJFblHcDRwiqQ1wI+Bj0j698oKEbE+Ijak6YXAWEkTC4zJzMyqFJYIIuILEdESEZOBGcDtEXFmZR1J+0hSmj48xfNCUTGZmVlvDb9nsaTZABExDzgVOEfSFmATMCMiotExmZmVWUMSQUQsBhan6XkV5XOBuY2IwczMavOVxWZmJedEYGZWck4EZmYl50RgZlZyDT9raCRob2+ns7Nz0NtdvXo1AHPmzBn0tltbWwtp18yGPyeCIWTcuHHNDsHMSsiJYAD8y9rMRhIfIzAzKzknAjOzknMiMDMrOScCM7OScyIwMys5JwIzs5JzIjAzKzknAjOzktNwuw+MpG7giWbHUaCJwNpmB2ED5u03fI30bXdARNS86fuwSwQjnaSOiGhrdhw2MN5+w1eZt527hszMSs6JwMys5JwIhp75zQ7Adoi33/BV2m3nYwRmZiXnPQIzs5JzIjAzKzkngn6QtKGPZb8p8HW/WFTbI0mztk8ekt4q6boBrrtYUqlOayx6W0r6uqTj+7nOKZI+X6fOgLdzM/kYQT9I2hARu1aVjY6INxr9utZbs7ZP1euNiYgtg9zmYuB/RURHzvoNfc9FaOJnbdj/7QbCewQDIGmapF9J+hGwMpVtSM/7SrpD0nJJqyR9qMb6h0i6N9VZIWlKKj+zovx7kkZL+mdgXCq7OtW7ILW9StL5qWwXSb+QdH8qPy2VXyjpvlQ2X5Ia8kdqoh3ZPpLeImmNpFFpfrykpySNlfQOSbdIWiLpTknvSnWulPRtSb8CLpL04dT+cknLJO0mabKkVan+aEnfkrQybf/zUvlxqf5KST+Q9Ac13tvpafkqSRdVlG9Iv3LvAY4q5A/bBAVuyyslnZrK16TPyV3An0s6SdLDku6S1C7p5lTvU5Lmpukr07LfSHqsoq0823nofSYjwo+cD2BDep4GvAK8vcayzwFfStOjgd1qtHMJcEaa3gkYB7wb+DkwNpV/Fzirsu00/T6yD8QuwK7AA8AfA38GXFZR7y3peY+Ksh8CH23233EYbJ+fAcem6dOAy9P0L4EpafoI4PY0fSVwMzA6zf8cODpN70p2b/DJwKpUdg5wPTCmZxsBOwNPAe9MZVcB56fpxUAb8FbgSWBSavN24OOpTgCfaPY2GEbb8krg1DS9Bvi7NN2zHd6e5q8Bbk7TnwLmVqx/LdmP6YOBzlTe53aufE7TQ+Iz6T2Cgbs3Ih6vUX4fcLakrwHviYiXa9T5f8AXJf092fgfm4DjyL7k75O0PM0fWGPdDwI3RMQrEbEB+CnwIbLkcLykiyR9KCLWpfrHSrpH0krgI8AhA33Dw8yObJ+fkH1pAMwAfiJpV+ADwLVp+3wP2LdinWvjzS6F/wS+LWkOMCF6dxUdD8zrKY+IF4GDgMcj4tFUZwFwTNV67wcWR0R3WvfqijpvkH3pjESDui238xo95e8CHqt4vWv6iOvGiNgaEQ8Ce9dYXms7wxD8TDoRDNwrtQoj4g6yD+fTwA8lnSXpTyu6Ctoi4kfAKcAm4P9K+gggYEFEHJYeB0XE12q8RM3dyPQF0rO38E9p93Nnsj2LUyPiPcBlZL94ymDA2we4CZguaQ+yv+ntZJ+Vlyq2z2ER8e5arxcR/wz8T7I9vbt7upAqiOwXfHVZPX3VeTVGbt/2YG/Lvl6jP900r1VM11qv13Yeqp9JJ4JBJukA4PmIuAz4PjA1Im6o+PLokHQg2a+OdrJ/1PeSdTucKmmv1M4eqS2AzZLGpuk7gI+n/s5dgD8F7pT0VmBjRPw78C1gKm/+g61Nv2hPLfwPMMTl2T5pT+te4GKyboE3ImI98LikP0/tSNKh23mNd0TEyoi4COgg+5VZ6VZgtqQxqf4ewMPAZEmtqc4ngV9XrXcP8GFJEyWNBk6vUac0Brot6zT7MHCgpMlp/rQ+6tZTazsPyc/kmGYHMAJNA/5W0mZgA3BWjTqnAWemOr8Dvh4RL0r6MnBrOri1GTiXbMjt+cAKSUsj4gxJV5L9c0PW57lM0p8A/yJpa1r3nIh4SdJlZHsJa8h2pctuGvW3D2RdBdem+j3OAC5N22ks8GPg/hrrni/pWLLumgeBRWzbjXQ58E6ybbqZ7NjOXElnk3U9jSHbVvMqG42IZyV9AfgV2a/NhRHxs7xvfASaxsC3ZU0RsUnSp4FbJK3lzc/ZQGxvOw+5z6RPHzUzqyBp14jYkM7m+Q6wOiL+tdlxFcldQ2Zm2/qrdELAA8BbyE4MGNG8R2BmVnLeIzAzKzknAjOzknMiMDMrOScCM0DSlyQ9kMaEWS7piEFse6GkCYPVntlg83UEVnqSjgJOJrsg6TVJE8nGgBoUEXHSYLVlVgTvEZhlF3utjYjXACJibUQ8o2xUyouUjQh7b89Vv5ImSbo+jSB5n6SjU/mukq7Qm6NN/lkqX5OSy/ZGmB2tbDTLVWndv2nS38FKyonALBsKYH9Jj0r6rqQPVyxbHxGHA3OBf0tlFwP/GhHvJxv19fJU/hVgXUS8JyLeS9W4NpLeTXZV+dERcRjZlcdnAIcB+0XEH6XxZ64o4D2abZe7hqz00lWk7yMbxfVYstFGe+5EdU3Fc8/VpccDB+vNYeR3l7RbKp9R0e7vq16qcoRZyAale55s2OoDJV0C/IIsMZk1jBOBGZAGI1sMLE7DA8/sWVRZLT2PAo5Kw4f/lzQkQV9XaPaMMPuFXguyAez+hGx8qU8AfzmAt2E2IO4astKTdJDSXeKSw8gG+4M3R588jew+EpD9Yv9MxfqHbaf8D6tequYIs+n4waiIuJ6se2nqjr4ns/7wHoFZdhexS9IpnluATmAW2ZlEf6Ds9o+jyIZ9BpgDfEfSCrLP0B3AbOAbqXwVWf//P5DdOAiAiHhwOyPMbgKuSGUAvfYYzIrksYbMtkPSGqAtItY2OxazIrlryMys5LxHYGZWct4jMDMrOScCM7OScyIwMys5JwIzs5JzIjAzK7n/DzC+/4wS9ghuAAAAAElFTkSuQmCC\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# https://seaborn.pydata.org/generated/seaborn.boxplot.html\n", "_ = sns.boxplot(x=\"Species\", y=\"SepalLengthCm\", data=df)" ] }, { "cell_type": "code", "execution_count": 17, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:49:21.152737Z", "iopub.status.busy": "2021-02-26T23:49:21.149899Z", "iopub.status.idle": "2021-02-26T23:49:21.326702Z", "shell.execute_reply": "2021-02-26T23:49:21.325942Z" }, "papermill": { "duration": 0.547069, "end_time": "2021-02-26T23:49:21.326899", "exception": false, "start_time": "2021-02-26T23:49:20.779830", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# https://seaborn.pydata.org/generated/seaborn.boxplot.html\n", "_ = sns.boxplot(x=\"Species\", y=\"SepalWidthCm\", data=df)" ] }, { "cell_type": "code", "execution_count": 18, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:49:21.968879Z", "iopub.status.busy": "2021-02-26T23:49:21.967877Z", "iopub.status.idle": "2021-02-26T23:49:22.837235Z", "shell.execute_reply": "2021-02-26T23:49:22.836682Z" }, "papermill": { "duration": 1.189171, "end_time": "2021-02-26T23:49:22.837390", "exception": false, "start_time": "2021-02-26T23:49:21.648219", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 751.25x216 with 3 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# https://seaborn.pydata.org/tutorial/axis_grids.html\n", "g = sns.FacetGrid(df, col=\"Species\", hue=\"Species\")\n", "_=g.map(sns.kdeplot, \"PetalLengthCm\", \"PetalWidthCm\", alpha=.7)\n", "_=g.add_legend()" ] }, { "cell_type": "code", "execution_count": 19, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:49:23.498356Z", "iopub.status.busy": "2021-02-26T23:49:23.497616Z", "iopub.status.idle": "2021-02-26T23:49:24.414080Z", "shell.execute_reply": "2021-02-26T23:49:24.413587Z" }, "papermill": { "duration": 1.260421, "end_time": "2021-02-26T23:49:24.414232", "exception": false, "start_time": "2021-02-26T23:49:23.153811", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 751.25x216 with 3 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# https://seaborn.pydata.org/tutorial/axis_grids.html\n", "g = sns.FacetGrid(df, col=\"Species\", hue=\"Species\")\n", "_=g.map(sns.kdeplot, \"SepalLengthCm\", \"SepalWidthCm\", alpha=.7)\n", "_=g.add_legend()" ] }, { "cell_type": "code", "execution_count": 20, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:49:25.082391Z", "iopub.status.busy": "2021-02-26T23:49:25.080414Z", "iopub.status.idle": "2021-02-26T23:49:25.937773Z", "shell.execute_reply": "2021-02-26T23:49:25.938271Z" }, "papermill": { "duration": 1.20349, "end_time": "2021-02-26T23:49:25.938459", "exception": false, "start_time": "2021-02-26T23:49:24.734969", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 751.25x216 with 3 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# https://seaborn.pydata.org/tutorial/axis_grids.html\n", "g = sns.FacetGrid(df, col=\"Species\", hue=\"Species\")\n", "_=g.map(sns.kdeplot, \"PetalLengthCm\", \"SepalWidthCm\", alpha=.7)\n", "_=g.add_legend()" ] }, { "cell_type": "code", "execution_count": 21, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:49:26.625702Z", "iopub.status.busy": "2021-02-26T23:49:26.605146Z", "iopub.status.idle": "2021-02-26T23:49:27.640252Z", "shell.execute_reply": "2021-02-26T23:49:27.639768Z" }, "papermill": { "duration": 1.379887, "end_time": "2021-02-26T23:49:27.640417", "exception": false, "start_time": "2021-02-26T23:49:26.260530", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 751.25x216 with 3 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# https://seaborn.pydata.org/tutorial/axis_grids.html\n", "g = sns.FacetGrid(df, col=\"Species\", hue=\"Species\")\n", "_=g.map(sns.kdeplot, \"PetalWidthCm\", \"SepalLengthCm\", alpha=.7)\n", "_=g.add_legend()" ] }, { "cell_type": "code", "execution_count": 22, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:49:28.297433Z", "iopub.status.busy": "2021-02-26T23:49:28.296380Z", "iopub.status.idle": "2021-02-26T23:49:28.300978Z", "shell.execute_reply": "2021-02-26T23:49:28.300481Z" }, "papermill": { "duration": 0.337606, "end_time": "2021-02-26T23:49:28.301115", "exception": false, "start_time": "2021-02-26T23:49:27.963509", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "Iris-setosa 50\n", "Iris-versicolor 50\n", "Iris-virginica 50\n", "Name: Species, dtype: int64" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.Species.value_counts()" ] }, { "cell_type": "code", "execution_count": 23, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:49:28.953370Z", "iopub.status.busy": "2021-02-26T23:49:28.952729Z", "iopub.status.idle": "2021-02-26T23:49:29.593233Z", "shell.execute_reply": "2021-02-26T23:49:29.593796Z" }, "papermill": { "duration": 0.969371, "end_time": "2021-02-26T23:49:29.593991", "exception": false, "start_time": "2021-02-26T23:49:28.624620", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "application/vnd.plotly.v1+json": { "config": { "linkText": "Export to plot.ly", "plotlyServerURL": "https://plot.ly", "showLink": true }, "data": [ { "histfunc": "count", "histnorm": "", "marker": { "color": "rgba(255, 153, 51, 1.0)", "line": { "color": "#4D5663", "width": 1.3 } }, "name": "SepalLengthCm", "opacity": 0.8, "orientation": "v", "type": "histogram", "x": [ 5.1, 4.9, 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(!display \|\| display === 'none') {{\n", " console.log([gd, 'removed!']);\n", " Plotly.purge(gd);\n", " observer.disconnect();\n", " }}\n", "}});\n", "\n", "// Listen for the removal of the full notebook cells\n", "var notebookContainer = gd.closest('#notebook-container');\n", "if (notebookContainer) {{\n", " x.observe(notebookContainer, {childList: true});\n", "}}\n", "\n", "// Listen for the clearing of the current output cell\n", "var outputEl = gd.closest('.output');\n", "if (outputEl) {{\n", " x.observe(outputEl, {childList: true});\n", "}}\n", "\n", " }) }; }); </script> </div>" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "for s in df.Species.unique():\n", " df.loc[df.Species==s, df.columns[1:5]].iplot(kind='box', title=s)" ] }, { "cell_type": "code", "execution_count": 29, "metadata": { "_kg_hide-input": true, "execution": { "iopub.execute_input": "2021-02-26T23:49:35.324431Z", "iopub.status.busy": "2021-02-26T23:49:35.323758Z", "iopub.status.idle": "2021-02-26T23:49:35.327299Z", "shell.execute_reply": "2021-02-26T23:49:35.326170Z" }, "papermill": { "duration": 0.431893, "end_time": "2021-02-26T23:49:35.327475", "exception": false, "start_time": "2021-02-26T23:49:34.895582", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "#df['colors'] = df['Species']\n", "#https://stackoverflow.com/questions/21131707/multiple-data-in-scatter-matrix?rq=1\n", "#df.colors.replace({'Iris-versicolor' : '#0392cf', 'Iris-virginica' : '#7bc043', 'Iris-setosa' : '#ee4035' }, inplace=True)" ] }, { "cell_type": "code", "execution_count": 30, "metadata": { "_kg_hide-input": true, "execution": { "iopub.execute_input": "2021-02-26T23:49:36.215264Z", "iopub.status.busy": "2021-02-26T23:49:36.214468Z", "iopub.status.idle": "2021-02-26T23:49:36.216963Z", "shell.execute_reply": "2021-02-26T23:49:36.217455Z" }, "papermill": { "duration": 0.430394, "end_time": "2021-02-26T23:49:36.217628", "exception": false, "start_time": "2021-02-26T23:49:35.787234", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "# color_wheel = {'Iris-versicolor': \"#0392cf\", \n", "# 'Iris-virginica': \"#7bc043\", \n", "# 'Iris-setosa': \"#ee4035\"}\n", "# colors = df[\"Species\"].map(lambda x: color_wheel.get(x))\n", "#https://stackoverflow.com/questions/22943894/class-labels-in-pandas-scattermatrix\n", "#df[df.columns[1:5]].scatter_matrix(color=colors)" ] }, { "cell_type": "code", "execution_count": 31, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:49:37.075609Z", "iopub.status.busy": "2021-02-26T23:49:37.074526Z", "iopub.status.idle": "2021-02-26T23:49:37.078403Z", "shell.execute_reply": "2021-02-26T23:49:37.078849Z" }, "papermill": { "duration": 0.440178, "end_time": "2021-02-26T23:49:37.079022", "exception": false, "start_time": "2021-02-26T23:49:36.638844", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>Id</th>\n", " <th>SepalLengthCm</th>\n", " <th>SepalWidthCm</th>\n", " <th>PetalLengthCm</th>\n", " <th>PetalWidthCm</th>\n", " <th>Species</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>0</th>\n", " <td>1</td>\n", " <td>5.1</td>\n", " <td>3.5</td>\n", " <td>1.4</td>\n", " <td>0.2</td>\n", " <td>1</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>2</td>\n", " <td>4.9</td>\n", " <td>3.0</td>\n", " <td>1.4</td>\n", " <td>0.2</td>\n", " <td>1</td>\n", " </tr>\n", " <tr>\n", " <th>2</th>\n", " <td>3</td>\n", " <td>4.7</td>\n", " <td>3.2</td>\n", " <td>1.3</td>\n", " <td>0.2</td>\n", " <td>1</td>\n", " </tr>\n", " <tr>\n", " <th>3</th>\n", " <td>4</td>\n", " <td>4.6</td>\n", " <td>3.1</td>\n", " <td>1.5</td>\n", " <td>0.2</td>\n", " <td>1</td>\n", " </tr>\n", " <tr>\n", " <th>4</th>\n", " <td>5</td>\n", " <td>5.0</td>\n", " <td>3.6</td>\n", " <td>1.4</td>\n", " <td>0.2</td>\n", " <td>1</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " Id SepalLengthCm SepalWidthCm PetalLengthCm PetalWidthCm Species\n", "0 1 5.1 3.5 1.4 0.2 1\n", "1 2 4.9 3.0 1.4 0.2 1\n", "2 3 4.7 3.2 1.3 0.2 1\n", "3 4 4.6 3.1 1.5 0.2 1\n", "4 5 5.0 3.6 1.4 0.2 1" ] }, "execution_count": 31, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.Species.replace({'Iris-versicolor' : 3, 'Iris-virginica' : 2, 'Iris-setosa' : 1 }, inplace=True)\n", "df.head()" ] }, { "cell_type": "code", "execution_count": 32, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:49:37.922583Z", "iopub.status.busy": "2021-02-26T23:49:37.921902Z", "iopub.status.idle": "2021-02-26T23:49:37.929696Z", "shell.execute_reply": "2021-02-26T23:49:37.930198Z" }, "papermill": { "duration": 0.431122, "end_time": "2021-02-26T23:49:37.930403", "exception": false, "start_time": "2021-02-26T23:49:37.499281", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "y = df[['Species']]\n", "X = df.loc[:,df.columns[1:5]]\n", "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=0)" ] }, { "cell_type": "code", "execution_count": 33, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:49:38.784128Z", "iopub.status.busy": "2021-02-26T23:49:38.773965Z", "iopub.status.idle": "2021-02-26T23:49:38.975805Z", "shell.execute_reply": "2021-02-26T23:49:38.975127Z" }, "papermill": { "duration": 0.624615, "end_time": "2021-02-26T23:49:38.975949", "exception": false, "start_time": "2021-02-26T23:49:38.351334", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "clf = RandomForestClassifier(max_depth=4, n_estimators=100, random_state=0)\n", "clf.fit(X_train, np.ravel(y_train))\n", "y_pred = clf.predict(X_test)" ] }, { "cell_type": "code", "execution_count": 34, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:49:39.825273Z", "iopub.status.busy": "2021-02-26T23:49:39.824623Z", "iopub.status.idle": "2021-02-26T23:49:39.831834Z", "shell.execute_reply": "2021-02-26T23:49:39.832477Z" }, "papermill": { "duration": 0.43407, "end_time": "2021-02-26T23:49:39.832647", "exception": false, "start_time": "2021-02-26T23:49:39.398577", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " precision recall f1-score support\n", "\n", " 1 1.00 1.00 1.00 11\n", " 2 1.00 1.00 1.00 6\n", " 3 1.00 1.00 1.00 13\n", "\n", " accuracy 1.00 30\n", " macro avg 1.00 1.00 1.00 30\n", "weighted avg 1.00 1.00 1.00 30\n", "\n" ] } ], "source": [ "from sklearn.metrics import classification_report\n", "print(classification_report(y_test, y_pred))" ] }, { "cell_type": "code", "execution_count": 35, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:49:40.721990Z", "iopub.status.busy": "2021-02-26T23:49:40.721387Z", "iopub.status.idle": "2021-02-26T23:49:40.726465Z", "shell.execute_reply": "2021-02-26T23:49:40.726939Z" }, "papermill": { "duration": 0.430427, "end_time": "2021-02-26T23:49:40.727096", "exception": false, "start_time": "2021-02-26T23:49:40.296669", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "Index(['SepalLengthCm', 'SepalWidthCm', 'PetalLengthCm', 'PetalWidthCm'], dtype='object')" ] }, "execution_count": 35, "metadata": {}, "output_type": "execute_result" } ], "source": [ "X.columns" ] }, { "cell_type": "code", "execution_count": 36, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:49:41.576980Z", "iopub.status.busy": "2021-02-26T23:49:41.576272Z", "iopub.status.idle": "2021-02-26T23:50:04.615788Z", "shell.execute_reply": "2021-02-26T23:50:04.616387Z" }, "papermill": { "duration": 23.466942, "end_time": "2021-02-26T23:50:04.616591", "exception": false, "start_time": "2021-02-26T23:49:41.149649", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 576x288 with 5 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "from sklearn.inspection import plot_partial_dependence\n", "features = [2, 3, (0, 3), (1,2)]\n", "plot_partial_dependence(clf, X, features, target=1, n_cols=4) \n", "# fig.set_figwidth(8)\n", "# fig.set_figheight(15)\n", "# fig.tight_layout()\n", "plt.gcf().set_figwidth(8)" ] }, { "cell_type": "code", "execution_count": 37, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:50:05.512437Z", "iopub.status.busy": "2021-02-26T23:50:05.511736Z", "iopub.status.idle": "2021-02-26T23:50:28.434616Z", "shell.execute_reply": "2021-02-26T23:50:28.434064Z" }, "papermill": { "duration": 23.394321, "end_time": "2021-02-26T23:50:28.434756", "exception": false, "start_time": "2021-02-26T23:50:05.040435", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 576x288 with 5 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "from sklearn.inspection import plot_partial_dependence\n", "features = [2, 3, (0, 3), (1,2)]\n", "plot_partial_dependence(clf, X, features, target=2, n_cols=4) \n", "# fig.set_figwidth(8)\n", "# fig.set_figheight(15)\n", "# fig.tight_layout()\n", "plt.gcf().set_figwidth(8)" ] }, { "cell_type": "code", "execution_count": 38, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:50:29.298547Z", "iopub.status.busy": "2021-02-26T23:50:29.296593Z", "iopub.status.idle": "2021-02-26T23:50:52.457417Z", "shell.execute_reply": "2021-02-26T23:50:52.457928Z" }, "papermill": { "duration": 23.599076, "end_time": "2021-02-26T23:50:52.458101", "exception": false, "start_time": "2021-02-26T23:50:28.859025", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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"text/plain": [ "<Figure size 576x288 with 5 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "from sklearn.inspection import plot_partial_dependence\n", "features = [2, 3, (0, 3), (1,2)]\n", "plot_partial_dependence(clf, X, features, target=3, n_cols=4) \n", "# fig.set_figwidth(8)\n", "# fig.set_figheight(15)\n", "# fig.tight_layout()\n", "plt.gcf().set_figwidth(8)" ] }, { "cell_type": "code", "execution_count": 39, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:50:53.351285Z", "iopub.status.busy": "2021-02-26T23:50:53.350365Z", "iopub.status.idle": "2021-02-26T23:50:53.353892Z", "shell.execute_reply": "2021-02-26T23:50:53.354504Z" }, "papermill": { "duration": 0.474043, "end_time": "2021-02-26T23:50:53.354681", "exception": false, "start_time": "2021-02-26T23:50:52.880638", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "array([1, 2, 3])" ] }, "execution_count": 39, "metadata": {}, "output_type": "execute_result" } ], "source": [ "clf.classes_" ] }, { "cell_type": "code", "execution_count": 40, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:50:54.207554Z", "iopub.status.busy": "2021-02-26T23:50:54.206622Z", "iopub.status.idle": "2021-02-26T23:50:54.215746Z", "shell.execute_reply": "2021-02-26T23:50:54.215101Z" }, "papermill": { "duration": 0.437096, "end_time": "2021-02-26T23:50:54.215887", "exception": false, "start_time": "2021-02-26T23:50:53.778791", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>Species</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>114</th>\n", " <td>2</td>\n", " </tr>\n", " <tr>\n", " <th>62</th>\n", " <td>3</td>\n", " </tr>\n", " <tr>\n", " <th>33</th>\n", " <td>1</td>\n", " </tr>\n", " <tr>\n", " <th>107</th>\n", " <td>2</td>\n", " </tr>\n", " <tr>\n", " <th>7</th>\n", " <td>1</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " Species\n", "114 2\n", "62 3\n", "33 1\n", "107 2\n", "7 1" ] }, "execution_count": 40, "metadata": {}, "output_type": "execute_result" } ], "source": [ "y_test[:5]" ] }, { "cell_type": "code", "execution_count": 41, "metadata": { "_kg_hide-output": true, "execution": { "iopub.execute_input": "2021-02-26T23:50:55.070458Z", "iopub.status.busy": "2021-02-26T23:50:55.069812Z", "iopub.status.idle": "2021-02-26T23:51:04.164532Z", "shell.execute_reply": "2021-02-26T23:51:04.165021Z" }, "papermill": { "duration": 9.524579, "end_time": "2021-02-26T23:51:04.165199", "exception": false, "start_time": 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e=this._instance;if(e.componentWillUnmount&&!e._calledComponentWillUnmount)if(e._calledComponentWillUnmount=!0,t){var n=this.getName()+\".componentWillUnmount()\";p.invokeGuardedCallback(n,e.componentWillUnmount.bind(e))}else e.componentWillUnmount();this._renderedComponent&&(v.unmountComponent(this._renderedComponent,t),this._renderedNodeType=null,this._renderedComponent=null,this._instance=null),this._pendingStateQueue=null,this._pendingReplaceState=!1,this._pendingForceUpdate=!1,this._pendingCallbacks=null,this._pendingElement=null,this._context=null,this._rootNodeID=0,this._topLevelWrapper=null,h.remove(e)}},_maskContext:function(t){var e=this._currentElement.type,n=e.contextTypes;if(!n)return g;var r={};for(var i in n)r[i]=t[i];return r},_processContext:function(t){var e=this._maskContext(t);return e},_processChildContext:function(t){var e,n=this._currentElement.type,r=this._instance;if(r.getChildContext&&(e=r.getChildContext()),e){\"object\"!=typeof n.childContextTypes?u(\"107\",this.getName()\|\|\"ReactCompositeComponent\"):void 0;for(var i in e)i in n.childContextTypes?void 0:u(\"108\",this.getName()\|\|\"ReactCompositeComponent\",i);return c({},t,e)}return t},_checkContextTypes:function(t,e,n){},receiveComponent:function(t,e,n){var r=this._currentElement,i=this._context;this._pendingElement=null,this.updateComponent(e,r,t,i,n)},performUpdateIfNecessary:function(t){null!=this._pendingElement?v.receiveComponent(this,this._pendingElement,t,this._context):null!==this._pendingStateQueue\|\|this._pendingForceUpdate?this.updateComponent(t,this._currentElement,this._currentElement,this._context,this._context):this._updateBatchNumber=null},updateComponent:function(t,e,n,r,i){var o=this._instance;null==o?u(\"136\",this.getName()\|\|\"ReactCompositeComponent\"):void 0;var a,c=!1;this._context===i?a=o.context:(a=this._processContext(i),c=!0);var s=e.props,l=n.props;e!==n&&(c=!0),c&&o.componentWillReceiveProps&&o.componentWillReceiveProps(l,a);var f=this._processPendingState(l,a),p=!0;this._pendingForceUpdate\|\|(o.shouldComponentUpdate?p=o.shouldComponentUpdate(l,f,a):this._compositeType===_.PureClass&&(p=!m(s,l)\|\|!m(o.state,f))),this._updateBatchNumber=null,p?(this._pendingForceUpdate=!1,this._performComponentUpdate(n,l,f,a,t,i)):(this._currentElement=n,this._context=i,o.props=l,o.state=f,o.context=a)},_processPendingState:function(t,e){var n=this._instance,r=this._pendingStateQueue,i=this._pendingReplaceState;if(this._pendingReplaceState=!1,this._pendingStateQueue=null,!r)return n.state;if(i&&1===r.length)return r[0];for(var o=c({},i?r[0]:n.state),a=i?1:0;a<r.length;a++){var u=r[a];c(o,\"function\"==typeof u?u.call(n,o,t,e):u)}return o},_performComponentUpdate:function(t,e,n,r,i,o){var a,u,c,s=this._instance,l=Boolean(s.componentDidUpdate);l&&(a=s.props,u=s.state,c=s.context),s.componentWillUpdate&&s.componentWillUpdate(e,n,r),this._currentElement=t,this._context=o,s.props=e,s.state=n,s.context=r,this._updateRenderedComponent(i,o),l&&i.getReactMountReady().enqueue(s.componentDidUpdate.bind(s,a,u,c),s)},_updateRenderedComponent:function(t,e){var n=this._renderedComponent,r=n._currentElement,i=this._renderValidatedComponent(),o=0;if(y(r,i))v.receiveComponent(n,i,t,this._processChildContext(e));else{var a=v.getHostNode(n);v.unmountComponent(n,!1);var u=d.getType(i);this._renderedNodeType=u;var c=this._instantiateReactComponent(i,u!==d.EMPTY);this._renderedComponent=c;var s=v.mountComponent(c,t,this._hostParent,this._hostContainerInfo,this._processChildContext(e),o);this._replaceNodeWithMarkup(a,s,n)}},_replaceNodeWithMarkup:function(t,e,n){l.replaceNodeWithMarkup(t,e,n)},_renderValidatedComponentWithoutOwnerOrContext:function(){var t,e=this._instance;return t=e.render()},_renderValidatedComponent:function(){var t;if(this._compositeType!==_.StatelessFunctional){f.current=this;try{t=this._renderValidatedComponentWithoutOwnerOrContext()}finally{f.current=null}}else t=this._renderValidatedComponentWithoutOwnerOrContext();return null===t\|\|t===!1\|\|s.isValidElement(t)?void 0:u(\"109\",this.getName()\|\|\"ReactCompositeComponent\"),t},attachRef:function(t,e){var n=this.getPublicInstance();null==n?u(\"110\"):void 0;var r=e.getPublicInstance(),i=n.refs===g?n.refs={}:n.refs;i[t]=r},detachRef:function(t){var e=this.getPublicInstance().refs;delete e[t]},getName:function(){var t=this._currentElement.type,e=this._instance&&this._instance.constructor;return t.displayName\|\|e&&e.displayName\|\|t.name\|\|e&&e.name\|\|null},getPublicInstance:function(){var t=this._instance;return this._compositeType===_.StatelessFunctional?null:t},_instantiateReactComponent:null};t.exports=x},function(t,e,n){\"use strict\";var r=n(4),i=n(358),o=n(163),a=n(24),u=n(11),c=n(371),s=n(387),l=n(167),f=n(395);n(1);i.inject();var p={findDOMNode:s,render:o.render,unmountComponentAtNode:o.unmountComponentAtNode,version:c,unstable_batchedUpdates:u.batchedUpdates,unstable_renderSubtreeIntoContainer:f};\"undefined\"!=typeof __REACT_DEVTOOLS_GLOBAL_HOOK__&&\"function\"==typeof __REACT_DEVTOOLS_GLOBAL_HOOK__.inject&&__REACT_DEVTOOLS_GLOBAL_HOOK__.inject({ComponentTree:{getClosestInstanceFromNode:r.getClosestInstanceFromNode,getNodeFromInstance:function(t){return t._renderedComponent&&(t=l(t)),t?r.getNodeFromInstance(t):null}},Mount:o,Reconciler:a});t.exports=p},function(t,e,n){\"use strict\";function r(t){if(t){var e=t._currentElement._owner\|\|null;if(e){var n=e.getName();if(n)return\" This DOM node was rendered by `\"+n+\"`.\"}}return\"\"}function i(t,e){e&&(G[t._tag]&&(null!=e.children\|\|null!=e.dangerouslySetInnerHTML?v(\"137\",t._tag,t._currentElement._owner?\" Check the render method of \"+t._currentElement._owner.getName()+\".\":\"\"):void 0),null!=e.dangerouslySetInnerHTML&&(null!=e.children?v(\"60\"):void 0,\"object\"==typeof e.dangerouslySetInnerHTML&&V in e.dangerouslySetInnerHTML?void 0:v(\"61\")),null!=e.style&&\"object\"!=typeof e.style?v(\"62\",r(t)):void 0)}function o(t,e,n,r){if(!(r instanceof I)){var i=t._hostContainerInfo,o=i._node&&i._node.nodeType===H,u=o?i._node:i._ownerDocument;F(e,u),r.getReactMountReady().enqueue(a,{inst:t,registrationName:e,listener:n})}}function a(){var t=this;C.putListener(t.inst,t.registrationName,t.listener)}function u(){var t=this;S.postMountWrapper(t)}function c(){var t=this;A.postMountWrapper(t)}function s(){var t=this;P.postMountWrapper(t)}function l(){var t=this;t._rootNodeID?void 0:v(\"63\");var e=U(t);switch(e?void 0:v(\"64\"),t._tag){case\"iframe\":case\"object\":t._wrapperState.listeners=[k.trapBubbledEvent(\"topLoad\",\"load\",e)];break;case\"video\":case\"audio\":t._wrapperState.listeners=[];for(var n in q)q.hasOwnProperty(n)&&t._wrapperState.listeners.push(k.trapBubbledEvent(n,q[n],e));break;case\"source\":t._wrapperState.listeners=[k.trapBubbledEvent(\"topError\",\"error\",e)];break;case\"img\":t._wrapperState.listeners=[k.trapBubbledEvent(\"topError\",\"error\",e),k.trapBubbledEvent(\"topLoad\",\"load\",e)];break;case\"form\":t._wrapperState.listeners=[k.trapBubbledEvent(\"topReset\",\"reset\",e),k.trapBubbledEvent(\"topSubmit\",\"submit\",e)];break;case\"input\":case\"select\":case\"textarea\":t._wrapperState.listeners=[k.trapBubbledEvent(\"topInvalid\",\"invalid\",e)]}}function f(){N.postUpdateWrapper(this)}function p(t){Z.call(X,t)\|\|($.test(t)?void 0:v(\"65\",t),X[t]=!0)}function h(t,e){return t.indexOf(\"-\")>=0\|\|null!=e.is}function d(t){var e=t.type;p(e),this._currentElement=t,this._tag=e.toLowerCase(),this._namespaceURI=null,this._renderedChildren=null,this._previousStyle=null,this._previousStyleCopy=null,this._hostNode=null,this._hostParent=null,this._rootNodeID=0,this._domID=0,this._hostContainerInfo=null,this._wrapperState=null,this._topLevelWrapper=null,this._flags=0}var v=n(2),g=n(3),m=n(332),y=n(334),_=n(20),b=n(82),x=n(21),w=n(156),C=n(22),M=n(83),k=n(51),E=n(157),T=n(4),S=n(351),P=n(352),N=n(158),A=n(355),O=(n(9),n(364)),I=n(369),D=(n(8),n(54)),R=(n(0),n(94),n(80),n(96),n(1),E),L=C.deleteListener,U=T.getNodeFromInstance,F=k.listenTo,j=M.registrationNameModules,B={string:!0,number:!0},W=\"style\",V=\"__html\",z={children:null,dangerouslySetInnerHTML:null,suppressContentEditableWarning:null},H=11,q={topAbort:\"abort\",topCanPlay:\"canplay\",topCanPlayThrough:\"canplaythrough\",topDurationChange:\"durationchange\",topEmptied:\"emptied\",topEncrypted:\"encrypted\",topEnded:\"ended\",topError:\"error\",topLoadedData:\"loadeddata\",topLoadedMetadata:\"loadedmetadata\",topLoadStart:\"loadstart\",topPause:\"pause\",topPlay:\"play\",topPlaying:\"playing\",topProgress:\"progress\",topRateChange:\"ratechange\",topSeeked:\"seeked\",topSeeking:\"seeking\",topStalled:\"stalled\",topSuspend:\"suspend\",topTimeUpdate:\"timeupdate\",topVolumeChange:\"volumechange\",topWaiting:\"waiting\"},Y={area:!0,base:!0,br:!0,col:!0,embed:!0,hr:!0,img:!0,input:!0,keygen:!0,link:!0,meta:!0,param:!0,source:!0,track:!0,wbr:!0},K={listing:!0,pre:!0,textarea:!0},G=g({menuitem:!0},Y),$=/^[a-zA-Z][a-zA-Z:_\\.\\-\\d]$/,X={},Z={}.hasOwnProperty,Q=1;d.displayName=\"ReactDOMComponent\",d.Mixin={mountComponent:function(t,e,n,r){this._rootNodeID=Q++,this._domID=n._idCounter++,this._hostParent=e,this._hostContainerInfo=n;var o=this._currentElement.props;switch(this._tag){case\"audio\":case\"form\":case\"iframe\":case\"img\":case\"link\":case\"object\":case\"source\":case\"video\":this._wrapperState={listeners:null},t.getReactMountReady().enqueue(l,this);break;case\"input\":S.mountWrapper(this,o,e),o=S.getHostProps(this,o),t.getReactMountReady().enqueue(l,this);break;case\"option\":P.mountWrapper(this,o,e),o=P.getHostProps(this,o);break;case\"select\":N.mountWrapper(this,o,e),o=N.getHostProps(this,o),t.getReactMountReady().enqueue(l,this);break;case\"textarea\":A.mountWrapper(this,o,e),o=A.getHostProps(this,o),t.getReactMountReady().enqueue(l,this)}i(this,o);var a,f;null!=e?(a=e._namespaceURI,f=e._tag):n._tag&&(a=n._namespaceURI,f=n._tag),(null==a\|\|a===b.svg&&\"foreignobject\"===f)&&(a=b.html),a===b.html&&(\"svg\"===this._tag?a=b.svg:\"math\"===this._tag&&(a=b.mathml)),this._namespaceURI=a;var p;if(t.useCreateElement){var h,d=n._ownerDocument;if(a===b.html)if(\"script\"===this._tag){var v=d.createElement(\"div\"),g=this._currentElement.type;v.innerHTML=\"<\"+g+\"></\"+g+\">\",h=v.removeChild(v.firstChild)}else h=o.is?d.createElement(this._currentElement.type,o.is):d.createElement(this._currentElement.type);else h=d.createElementNS(a,this._currentElement.type);T.precacheNode(this,h),this._flags\|=R.hasCachedChildNodes,this._hostParent\|\|w.setAttributeForRoot(h),this._updateDOMProperties(null,o,t);var y=_(h);this._createInitialChildren(t,o,r,y),p=y}else{var x=this._createOpenTagMarkupAndPutListeners(t,o),C=this._createContentMarkup(t,o,r);p=!C&&Y[this._tag]?x+\"/>\":x+\">\"+C+\"</\"+this._currentElement.type+\">\"}switch(this._tag){case\"input\":t.getReactMountReady().enqueue(u,this),o.autoFocus&&t.getReactMountReady().enqueue(m.focusDOMComponent,this);break;case\"textarea\":t.getReactMountReady().enqueue(c,this),o.autoFocus&&t.getReactMountReady().enqueue(m.focusDOMComponent,this);break;case\"select\":o.autoFocus&&t.getReactMountReady().enqueue(m.focusDOMComponent,this);break;case\"button\":o.autoFocus&&t.getReactMountReady().enqueue(m.focusDOMComponent,this);break;case\"option\":t.getReactMountReady().enqueue(s,this)}return p},_createOpenTagMarkupAndPutListeners:function(t,e){var n=\"<\"+this._currentElement.type;for(var r in e)if(e.hasOwnProperty(r)){var i=e[r];if(null!=i)if(j.hasOwnProperty(r))i&&o(this,r,i,t);else{r===W&&(i&&(i=this._previousStyleCopy=g({},e.style)),i=y.createMarkupForStyles(i,this));var a=null;null!=this._tag&&h(this._tag,e)?z.hasOwnProperty(r)\|\|(a=w.createMarkupForCustomAttribute(r,i)):a=w.createMarkupForProperty(r,i),a&&(n+=\" \"+a)}}return t.renderToStaticMarkup?n:(this._hostParent\|\|(n+=\" \"+w.createMarkupForRoot()),n+=\" \"+w.createMarkupForID(this._domID))},_createContentMarkup:function(t,e,n){var r=\"\",i=e.dangerouslySetInnerHTML;if(null!=i)null!=i.__html&&(r=i.__html);else{var o=B[typeof e.children]?e.children:null,a=null!=o?null:e.children;if(null!=o)r=D(o);else if(null!=a){var u=this.mountChildren(a,t,n);r=u.join(\"\")}}return K[this._tag]&&\"\\n\"===r.charAt(0)?\"\\n\"+r:r},_createInitialChildren:function(t,e,n,r){var i=e.dangerouslySetInnerHTML;if(null!=i)null!=i.__html&&_.queueHTML(r,i.__html);else{var o=B[typeof e.children]?e.children:null,a=null!=o?null:e.children;if(null!=o)\"\"!==o&&_.queueText(r,o);else if(null!=a)for(var u=this.mountChildren(a,t,n),c=0;c<u.length;c++)_.queueChild(r,u[c])}},receiveComponent:function(t,e,n){var r=this._currentElement;this._currentElement=t,this.updateComponent(e,r,t,n)},updateComponent:function(t,e,n,r){var o=e.props,a=this._currentElement.props;switch(this._tag){case\"input\":o=S.getHostProps(this,o),a=S.getHostProps(this,a);break;case\"option\":o=P.getHostProps(this,o),a=P.getHostProps(this,a);break;case\"select\":o=N.getHostProps(this,o),a=N.getHostProps(this,a);break;case\"textarea\":o=A.getHostProps(this,o),a=A.getHostProps(this,a)}switch(i(this,a),this._updateDOMProperties(o,a,t),this._updateDOMChildren(o,a,t,r),this._tag){case\"input\":S.updateWrapper(this);break;case\"textarea\":A.updateWrapper(this);break;case\"select\":t.getReactMountReady().enqueue(f,this)}},_updateDOMProperties:function(t,e,n){var r,i,a;for(r in t)if(!e.hasOwnProperty(r)&&t.hasOwnProperty(r)&&null!=t[r])if(r===W){var u=this._previousStyleCopy;for(i in u)u.hasOwnProperty(i)&&(a=a\|\|{},a[i]=\"\");this._previousStyleCopy=null}else j.hasOwnProperty(r)?t[r]&&L(this,r):h(this._tag,t)?z.hasOwnProperty(r)\|\|w.deleteValueForAttribute(U(this),r):(x.properties[r]\|\|x.isCustomAttribute(r))&&w.deleteValueForProperty(U(this),r);for(r in e){var c=e[r],s=r===W?this._previousStyleCopy:null!=t?t[r]:void 0;if(e.hasOwnProperty(r)&&c!==s&&(null!=c\|\|null!=s))if(r===W)if(c?c=this._previousStyleCopy=g({},c):this._previousStyleCopy=null,s){for(i in s)!s.hasOwnProperty(i)\|\|c&&c.hasOwnProperty(i)\|\|(a=a\|\|{},a[i]=\"\");for(i in c)c.hasOwnProperty(i)&&s[i]!==c[i]&&(a=a\|\|{},a[i]=c[i])}else a=c;else if(j.hasOwnProperty(r))c?o(this,r,c,n):s&&L(this,r);else if(h(this._tag,e))z.hasOwnProperty(r)\|\|w.setValueForAttribute(U(this),r,c);else if(x.properties[r]\|\|x.isCustomAttribute(r)){var l=U(this);null!=c?w.setValueForProperty(l,r,c):w.deleteValueForProperty(l,r)}}a&&y.setValueForStyles(U(this),a,this)},_updateDOMChildren:function(t,e,n,r){var i=B[typeof t.children]?t.children:null,o=B[typeof e.children]?e.children:null,a=t.dangerouslySetInnerHTML&&t.dangerouslySetInnerHTML.__html,u=e.dangerouslySetInnerHTML&&e.dangerouslySetInnerHTML.__html,c=null!=i?null:t.children,s=null!=o?null:e.children,l=null!=i\|\|null!=a,f=null!=o\|\|null!=u;null!=c&&null==s?this.updateChildren(null,n,r):l&&!f&&this.updateTextContent(\"\"),null!=o?i!==o&&this.updateTextContent(\"\"+o):null!=u?a!==u&&this.updateMarkup(\"\"+u):null!=s&&this.updateChildren(s,n,r)},getHostNode:function(){return U(this)},unmountComponent:function(t){switch(this._tag){case\"audio\":case\"form\":case\"iframe\":case\"img\":case\"link\":case\"object\":case\"source\":case\"video\":var e=this._wrapperState.listeners;if(e)for(var n=0;n<e.length;n++)e[n].remove();break;case\"html\":case\"head\":case\"body\":v(\"66\",this._tag)}this.unmountChildren(t),T.uncacheNode(this),C.deleteAllListeners(this),this._rootNodeID=0,this._domID=0,this._wrapperState=null},getPublicInstance:function(){return U(this)}},g(d.prototype,d.Mixin,O.Mixin),t.exports=d},function(t,e,n){\"use strict\";function r(t,e){var n={_topLevelWrapper:t,_idCounter:1,_ownerDocument:e?e.nodeType===i?e:e.ownerDocument:null,_node:e,_tag:e?e.nodeName.toLowerCase():null,_namespaceURI:e?e.namespaceURI:null};return n}var i=(n(96),9);t.exports=r},function(t,e,n){\"use strict\";var r=n(3),i=n(20),o=n(4),a=function(t){this._currentElement=null,this._hostNode=null,this._hostParent=null,this._hostContainerInfo=null,this._domID=0};r(a.prototype,{mountComponent:function(t,e,n,r){var a=n._idCounter++;this._domID=a,this._hostParent=e,this._hostContainerInfo=n;var u=\" react-empty: \"+this._domID+\" \";if(t.useCreateElement){var c=n._ownerDocument,s=c.createComment(u);return o.precacheNode(this,s),i(s)}return t.renderToStaticMarkup?\"\":\"<!--\"+u+\"-->\"},receiveComponent:function(){},getHostNode:function(){return o.getNodeFromInstance(this)},unmountComponent:function(){o.uncacheNode(this)}}),t.exports=a},function(t,e,n){\"use strict\";var r={useCreateElement:!0,useFiber:!1};t.exports=r},function(t,e,n){\"use strict\";var r=n(81),i=n(4),o={dangerouslyProcessChildrenUpdates:function(t,e){var n=i.getNodeFromInstance(t);r.processUpdates(n,e)}};t.exports=o},function(t,e,n){\"use strict\";function r(){this._rootNodeID&&f.updateWrapper(this)}function i(t){var e=this._currentElement.props,n=c.executeOnChange(e,t);l.asap(r,this);var i=e.name;if(\"radio\"===e.type&&null!=i){for(var a=s.getNodeFromInstance(this),u=a;u.parentNode;)u=u.parentNode;for(var f=u.querySelectorAll(\"input[name=\"+JSON.stringify(\"\"+i)+'][type=\"radio\"]'),p=0;p<f.length;p++){var h=f[p];if(h!==a&&h.form===a.form){var d=s.getInstanceFromNode(h);d?void 0:o(\"90\"),l.asap(r,d)}}}return n}var o=n(2),a=n(3),u=n(156),c=n(85),s=n(4),l=n(11),f=(n(0),n(1),{getHostProps:function(t,e){var n=c.getValue(e),r=c.getChecked(e),i=a({type:void 0,step:void 0,min:void 0,max:void 0},e,{defaultChecked:void 0,defaultValue:void 0,value:null!=n?n:t._wrapperState.initialValue,checked:null!=r?r:t._wrapperState.initialChecked,onChange:t._wrapperState.onChange});return i},mountWrapper:function(t,e){var n=e.defaultValue;t._wrapperState={initialChecked:null!=e.checked?e.checked:e.defaultChecked,initialValue:null!=e.value?e.value:n,listeners:null,onChange:i.bind(t)}},updateWrapper:function(t){var e=t._currentElement.props,n=e.checked;null!=n&&u.setValueForProperty(s.getNodeFromInstance(t),\"checked\",n\|\|!1);var r=s.getNodeFromInstance(t),i=c.getValue(e);if(null!=i){var o=\"\"+i;o!==r.value&&(r.value=o)}else null==e.value&&null!=e.defaultValue&&r.defaultValue!==\"\"+e.defaultValue&&(r.defaultValue=\"\"+e.defaultValue),null==e.checked&&null!=e.defaultChecked&&(r.defaultChecked=!!e.defaultChecked)},postMountWrapper:function(t){var e=t._currentElement.props,n=s.getNodeFromInstance(t);switch(e.type){case\"submit\":case\"reset\":break;case\"color\":case\"date\":case\"datetime\":case\"datetime-local\":case\"month\":case\"time\":case\"week\":n.value=\"\",n.value=n.defaultValue;break;default:n.value=n.value}var r=n.name;\"\"!==r&&(n.name=\"\"),n.defaultChecked=!n.defaultChecked,n.defaultChecked=!n.defaultChecked,\"\"!==r&&(n.name=r)}});t.exports=f},function(t,e,n){\"use strict\";function r(t){var e=\"\";return o.Children.forEach(t,function(t){null!=t&&(\"string\"==typeof t\|\|\"number\"==typeof t?e+=t:c\|\|(c=!0))}),e}var i=n(3),o=n(26),a=n(4),u=n(158),c=(n(1),!1),s={mountWrapper:function(t,e,n){var i=null;if(null!=n){var o=n;\"optgroup\"===o._tag&&(o=o._hostParent),null!=o&&\"select\"===o._tag&&(i=u.getSelectValueContext(o))}var a=null;if(null!=i){var c;if(c=null!=e.value?e.value+\"\":r(e.children),a=!1,Array.isArray(i)){for(var s=0;s<i.length;s++)if(\"\"+i[s]===c){a=!0;break}}else a=\"\"+i===c}t._wrapperState={selected:a}},postMountWrapper:function(t){var e=t._currentElement.props;if(null!=e.value){var n=a.getNodeFromInstance(t);n.setAttribute(\"value\",e.value)}},getHostProps:function(t,e){var n=i({selected:void 0,children:void 0},e);null!=t._wrapperState.selected&&(n.selected=t._wrapperState.selected);var o=r(e.children);return o&&(n.children=o),n}};t.exports=s},function(t,e,n){\"use strict\";function r(t,e,n,r){return t===n&&e===r}function i(t){var e=document.selection,n=e.createRange(),r=n.text.length,i=n.duplicate();i.moveToElementText(t),i.setEndPoint(\"EndToStart\",n);var o=i.text.length,a=o+r;return{start:o,end:a}}function o(t){var e=window.getSelection&&window.getSelection();if(!e\|\|0===e.rangeCount)return null;var n=e.anchorNode,i=e.anchorOffset,o=e.focusNode,a=e.focusOffset,u=e.getRangeAt(0);try{u.startContainer.nodeType,u.endContainer.nodeType}catch(t){return null}var c=r(e.anchorNode,e.anchorOffset,e.focusNode,e.focusOffset),s=c?0:u.toString().length,l=u.cloneRange();l.selectNodeContents(t),l.setEnd(u.startContainer,u.startOffset);var f=r(l.startContainer,l.startOffset,l.endContainer,l.endOffset),p=f?0:l.toString().length,h=p+s,d=document.createRange();d.setStart(n,i),d.setEnd(o,a);var v=d.collapsed;return{start:v?h:p,end:v?p:h}}function a(t,e){var n,r,i=document.selection.createRange().duplicate();void 0===e.end?(n=e.start,r=n):e.start>e.end?(n=e.end,r=e.start):(n=e.start,r=e.end),i.moveToElementText(t),i.moveStart(\"character\",n),i.setEndPoint(\"EndToStart\",i),i.moveEnd(\"character\",r-n),i.select()}function u(t,e){if(window.getSelection){var n=window.getSelection(),r=t[l()].length,i=Math.min(e.start,r),o=void 0===e.end?i:Math.min(e.end,r);if(!n.extend&&i>o){var a=o;o=i,i=a}var u=s(t,i),c=s(t,o);if(u&&c){var f=document.createRange();f.setStart(u.node,u.offset),n.removeAllRanges(),i>o?(n.addRange(f),n.extend(c.node,c.offset)):(f.setEnd(c.node,c.offset),n.addRange(f))}}}var c=n(6),s=n(392),l=n(168),f=c.canUseDOM&&\"selection\"in document&&!(\"getSelection\"in window),p={getOffsets:f?i:o,setOffsets:f?a:u};t.exports=p},function(t,e,n){\"use strict\";var r=n(2),i=n(3),o=n(81),a=n(20),u=n(4),c=n(54),s=(n(0),n(96),function(t){this._currentElement=t,this._stringText=\"\"+t,this._hostNode=null,this._hostParent=null,this._domID=0,this._mountIndex=0,this._closingComment=null,this._commentNodes=null});i(s.prototype,{mountComponent:function(t,e,n,r){var i=n._idCounter++,o=\" react-text: \"+i+\" \",s=\" /react-text \";if(this._domID=i,this._hostParent=e,t.useCreateElement){var l=n._ownerDocument,f=l.createComment(o),p=l.createComment(s),h=a(l.createDocumentFragment());return a.queueChild(h,a(f)),this._stringText&&a.queueChild(h,a(l.createTextNode(this._stringText))),a.queueChild(h,a(p)),u.precacheNode(this,f),this._closingComment=p,h}var d=c(this._stringText);return t.renderToStaticMarkup?d:\"<!--\"+o+\"-->\"+d+\"<!--\"+s+\"-->\"},receiveComponent:function(t,e){if(t!==this._currentElement){this._currentElement=t;var n=\"\"+t;if(n!==this._stringText){this._stringText=n;var r=this.getHostNode();o.replaceDelimitedText(r[0],r[1],n)}}},getHostNode:function(){var t=this._commentNodes;if(t)return t;if(!this._closingComment)for(var e=u.getNodeFromInstance(this),n=e.nextSibling;;){if(null==n?r(\"67\",this._domID):void 0,8===n.nodeType&&\" /react-text \"===n.nodeValue){this._closingComment=n;break}n=n.nextSibling}return t=[this._hostNode,this._closingComment],this._commentNodes=t,t},unmountComponent:function(){this._closingComment=null,this._commentNodes=null,u.uncacheNode(this)}}),t.exports=s},function(t,e,n){\"use strict\";function r(){this._rootNodeID&&l.updateWrapper(this)}function i(t){var e=this._currentElement.props,n=u.executeOnChange(e,t);return s.asap(r,this),n}var o=n(2),a=n(3),u=n(85),c=n(4),s=n(11),l=(n(0),n(1),{getHostProps:function(t,e){null!=e.dangerouslySetInnerHTML?o(\"91\"):void 0;var n=a({},e,{value:void 0,defaultValue:void 0,children:\"\"+t._wrapperState.initialValue,onChange:t._wrapperState.onChange});return n},mountWrapper:function(t,e){var n=u.getValue(e),r=n;if(null==n){var a=e.defaultValue,c=e.children;null!=c&&(null!=a?o(\"92\"):void 0,Array.isArray(c)&&(c.length<=1?void 0:o(\"93\"),c=c[0]),a=\"\"+c),null==a&&(a=\"\"),r=a}t._wrapperState={initialValue:\"\"+r,listeners:null,onChange:i.bind(t)}},updateWrapper:function(t){var e=t._currentElement.props,n=c.getNodeFromInstance(t),r=u.getValue(e);if(null!=r){var i=\"\"+r;i!==n.value&&(n.value=i),null==e.defaultValue&&(n.defaultValue=i)}null!=e.defaultValue&&(n.defaultValue=e.defaultValue)},postMountWrapper:function(t){var e=c.getNodeFromInstance(t),n=e.textContent;\n", "n===t._wrapperState.initialValue&&(e.value=n)}});t.exports=l},function(t,e,n){\"use strict\";function r(t,e){\"_hostNode\"in t?void 0:c(\"33\"),\"_hostNode\"in e?void 0:c(\"33\");for(var n=0,r=t;r;r=r._hostParent)n++;for(var i=0,o=e;o;o=o._hostParent)i++;for(;n-i>0;)t=t._hostParent,n--;for(;i-n>0;)e=e._hostParent,i--;for(var a=n;a--;){if(t===e)return t;t=t._hostParent,e=e._hostParent}return null}function i(t,e){\"_hostNode\"in t?void 0:c(\"35\"),\"_hostNode\"in e?void 0:c(\"35\");for(;e;){if(e===t)return!0;e=e._hostParent}return!1}function o(t){return\"_hostNode\"in t?void 0:c(\"36\"),t._hostParent}function a(t,e,n){for(var r=[];t;)r.push(t),t=t._hostParent;var i;for(i=r.length;i-- >0;)e(r[i],\"captured\",n);for(i=0;i<r.length;i++)e(r[i],\"bubbled\",n)}function u(t,e,n,i,o){for(var a=t&&e?r(t,e):null,u=[];t&&t!==a;)u.push(t),t=t._hostParent;for(var c=[];e&&e!==a;)c.push(e),e=e._hostParent;var s;for(s=0;s<u.length;s++)n(u[s],\"bubbled\",i);for(s=c.length;s-- >0;)n(c[s],\"captured\",o)}var c=n(2);n(0);t.exports={isAncestor:i,getLowestCommonAncestor:r,getParentInstance:o,traverseTwoPhase:a,traverseEnterLeave:u}},function(t,e,n){\"use strict\";function r(){this.reinitializeTransaction()}var i=n(3),o=n(11),a=n(53),u=n(8),c={initialize:u,close:function(){p.isBatchingUpdates=!1}},s={initialize:u,close:o.flushBatchedUpdates.bind(o)},l=[s,c];i(r.prototype,a,{getTransactionWrappers:function(){return l}});var f=new r,p={isBatchingUpdates:!1,batchedUpdates:function(t,e,n,r,i,o){var a=p.isBatchingUpdates;return p.isBatchingUpdates=!0,a?t(e,n,r,i,o):f.perform(t,null,e,n,r,i,o)}};t.exports=p},function(t,e,n){\"use strict\";function r(){C\|\|(C=!0,y.EventEmitter.injectReactEventListener(m),y.EventPluginHub.injectEventPluginOrder(u),y.EventPluginUtils.injectComponentTree(p),y.EventPluginUtils.injectTreeTraversal(d),y.EventPluginHub.injectEventPluginsByName({SimpleEventPlugin:w,EnterLeaveEventPlugin:c,ChangeEventPlugin:a,SelectEventPlugin:x,BeforeInputEventPlugin:o}),y.HostComponent.injectGenericComponentClass(f),y.HostComponent.injectTextComponentClass(v),y.DOMProperty.injectDOMPropertyConfig(i),y.DOMProperty.injectDOMPropertyConfig(s),y.DOMProperty.injectDOMPropertyConfig(b),y.EmptyComponent.injectEmptyComponentFactory(function(t){return new h(t)}),y.Updates.injectReconcileTransaction(_),y.Updates.injectBatchingStrategy(g),y.Component.injectEnvironment(l))}var i=n(331),o=n(333),a=n(335),u=n(337),c=n(338),s=n(341),l=n(343),f=n(346),p=n(4),h=n(348),d=n(356),v=n(354),g=n(357),m=n(361),y=n(362),_=n(367),b=n(372),x=n(373),w=n(374),C=!1;t.exports={inject:r}},function(t,e,n){\"use strict\";var r=\"function\"==typeof Symbol&&Symbol.for&&Symbol.for(\"react.element\")\|\|60103;t.exports=r},function(t,e,n){\"use strict\";function r(t){i.enqueueEvents(t),i.processEventQueue(!1)}var i=n(22),o={handleTopLevel:function(t,e,n,o){var a=i.extractEvents(t,e,n,o);r(a)}};t.exports=o},function(t,e,n){\"use strict\";function r(t){for(;t._hostParent;)t=t._hostParent;var e=f.getNodeFromInstance(t),n=e.parentNode;return f.getClosestInstanceFromNode(n)}function i(t,e){this.topLevelType=t,this.nativeEvent=e,this.ancestors=[]}function o(t){var e=h(t.nativeEvent),n=f.getClosestInstanceFromNode(e),i=n;do t.ancestors.push(i),i=i&&r(i);while(i);for(var o=0;o<t.ancestors.length;o++)n=t.ancestors[o],v._handleTopLevel(t.topLevelType,n,t.nativeEvent,h(t.nativeEvent))}function a(t){var e=d(window);t(e)}var u=n(3),c=n(150),s=n(6),l=n(17),f=n(4),p=n(11),h=n(93),d=n(324);u(i.prototype,{destructor:function(){this.topLevelType=null,this.nativeEvent=null,this.ancestors.length=0}}),l.addPoolingTo(i,l.twoArgumentPooler);var v={_enabled:!0,_handleTopLevel:null,WINDOW_HANDLE:s.canUseDOM?window:null,setHandleTopLevel:function(t){v._handleTopLevel=t},setEnabled:function(t){v._enabled=!!t},isEnabled:function(){return v._enabled},trapBubbledEvent:function(t,e,n){return n?c.listen(n,e,v.dispatchEvent.bind(null,t)):null},trapCapturedEvent:function(t,e,n){return n?c.capture(n,e,v.dispatchEvent.bind(null,t)):null},monitorScrollValue:function(t){var e=a.bind(null,t);c.listen(window,\"scroll\",e)},dispatchEvent:function(t,e){if(v._enabled){var n=i.getPooled(t,e);try{p.batchedUpdates(o,n)}finally{i.release(n)}}}};t.exports=v},function(t,e,n){\"use strict\";var r=n(21),i=n(22),o=n(50),a=n(86),u=n(159),c=n(51),s=n(161),l=n(11),f={Component:a.injection,DOMProperty:r.injection,EmptyComponent:u.injection,EventPluginHub:i.injection,EventPluginUtils:o.injection,EventEmitter:c.injection,HostComponent:s.injection,Updates:l.injection};t.exports=f},function(t,e,n){\"use strict\";var r=n(385),i=/\\/?>/,o=/^<\\!\\-\\-/,a={CHECKSUM_ATTR_NAME:\"data-react-checksum\",addChecksumToMarkup:function(t){var e=r(t);return o.test(t)?t:t.replace(i,\" \"+a.CHECKSUM_ATTR_NAME+'=\"'+e+'\"$&')},canReuseMarkup:function(t,e){var n=e.getAttribute(a.CHECKSUM_ATTR_NAME);n=n&&parseInt(n,10);var i=r(t);return i===n}};t.exports=a},function(t,e,n){\"use strict\";function r(t,e,n){return{type:\"INSERT_MARKUP\",content:t,fromIndex:null,fromNode:null,toIndex:n,afterNode:e}}function i(t,e,n){return{type:\"MOVE_EXISTING\",content:null,fromIndex:t._mountIndex,fromNode:p.getHostNode(t),toIndex:n,afterNode:e}}function o(t,e){return{type:\"REMOVE_NODE\",content:null,fromIndex:t._mountIndex,fromNode:e,toIndex:null,afterNode:null}}function a(t){return{type:\"SET_MARKUP\",content:t,fromIndex:null,fromNode:null,toIndex:null,afterNode:null}}function u(t){return{type:\"TEXT_CONTENT\",content:t,fromIndex:null,fromNode:null,toIndex:null,afterNode:null}}function c(t,e){return e&&(t=t\|\|[],t.push(e)),t}function s(t,e){f.processChildrenUpdates(t,e)}var l=n(2),f=n(86),p=(n(40),n(9),n(15),n(24)),h=n(342),d=(n(8),n(388)),v=(n(0),{Mixin:{_reconcilerInstantiateChildren:function(t,e,n){return h.instantiateChildren(t,e,n)},_reconcilerUpdateChildren:function(t,e,n,r,i,o){var a,u=0;return a=d(e,u),h.updateChildren(t,a,n,r,i,this,this._hostContainerInfo,o,u),a},mountChildren:function(t,e,n){var r=this._reconcilerInstantiateChildren(t,e,n);this._renderedChildren=r;var i=[],o=0;for(var a in r)if(r.hasOwnProperty(a)){var u=r[a],c=0,s=p.mountComponent(u,e,this,this._hostContainerInfo,n,c);u._mountIndex=o++,i.push(s)}return i},updateTextContent:function(t){var e=this._renderedChildren;h.unmountChildren(e,!1);for(var n in e)e.hasOwnProperty(n)&&l(\"118\");var r=[u(t)];s(this,r)},updateMarkup:function(t){var e=this._renderedChildren;h.unmountChildren(e,!1);for(var n in e)e.hasOwnProperty(n)&&l(\"118\");var r=[a(t)];s(this,r)},updateChildren:function(t,e,n){this._updateChildren(t,e,n)},_updateChildren:function(t,e,n){var r=this._renderedChildren,i={},o=[],a=this._reconcilerUpdateChildren(r,t,o,i,e,n);if(a\|\|r){var u,l=null,f=0,h=0,d=0,v=null;for(u in a)if(a.hasOwnProperty(u)){var g=r&&r[u],m=a[u];g===m?(l=c(l,this.moveChild(g,v,f,h)),h=Math.max(g._mountIndex,h),g._mountIndex=f):(g&&(h=Math.max(g._mountIndex,h)),l=c(l,this._mountChildAtIndex(m,o[d],v,f,e,n)),d++),f++,v=p.getHostNode(m)}for(u in i)i.hasOwnProperty(u)&&(l=c(l,this._unmountChild(r[u],i[u])));l&&s(this,l),this._renderedChildren=a}},unmountChildren:function(t){var e=this._renderedChildren;h.unmountChildren(e,t),this._renderedChildren=null},moveChild:function(t,e,n,r){if(t._mountIndex<r)return i(t,e,n)},createChild:function(t,e,n){return r(n,e,t._mountIndex)},removeChild:function(t,e){return o(t,e)},_mountChildAtIndex:function(t,e,n,r,i,o){return t._mountIndex=r,this.createChild(t,n,e)},_unmountChild:function(t,e){var n=this.removeChild(t,e);return t._mountIndex=null,n}}});t.exports=v},function(t,e,n){\"use strict\";function r(t){return!(!t\|\|\"function\"!=typeof t.attachRef\|\|\"function\"!=typeof t.detachRef)}var i=n(2),o=(n(0),{addComponentAsRefTo:function(t,e,n){r(n)?void 0:i(\"119\"),n.attachRef(e,t)},removeComponentAsRefFrom:function(t,e,n){r(n)?void 0:i(\"120\");var o=n.getPublicInstance();o&&o.refs[e]===t.getPublicInstance()&&n.detachRef(e)}});t.exports=o},function(t,e,n){\"use strict\";var r=\"SECRET_DO_NOT_PASS_THIS_OR_YOU_WILL_BE_FIRED\";t.exports=r},function(t,e,n){\"use strict\";function r(t){this.reinitializeTransaction(),this.renderToStaticMarkup=!1,this.reactMountReady=o.getPooled(null),this.useCreateElement=t}var i=n(3),o=n(155),a=n(17),u=n(51),c=n(162),s=(n(9),n(53)),l=n(88),f={initialize:c.getSelectionInformation,close:c.restoreSelection},p={initialize:function(){var t=u.isEnabled();return u.setEnabled(!1),t},close:function(t){u.setEnabled(t)}},h={initialize:function(){this.reactMountReady.reset()},close:function(){this.reactMountReady.notifyAll()}},d=[f,p,h],v={getTransactionWrappers:function(){return d},getReactMountReady:function(){return this.reactMountReady},getUpdateQueue:function(){return l},checkpoint:function(){return this.reactMountReady.checkpoint()},rollback:function(t){this.reactMountReady.rollback(t)},destructor:function(){o.release(this.reactMountReady),this.reactMountReady=null}};i(r.prototype,s,v),a.addPoolingTo(r),t.exports=r},function(t,e,n){\"use strict\";function r(t,e,n){\"function\"==typeof t?t(e.getPublicInstance()):o.addComponentAsRefTo(e,t,n)}function i(t,e,n){\"function\"==typeof t?t(null):o.removeComponentAsRefFrom(e,t,n)}var o=n(365),a={};a.attachRefs=function(t,e){if(null!==e&&\"object\"==typeof e){var n=e.ref;null!=n&&r(n,t,e._owner)}},a.shouldUpdateRefs=function(t,e){var n=null,r=null;null!==t&&\"object\"==typeof 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a=n(28),u=(n(15),n(174)),c=n(177),s=(n(0),n(399)),l=(n(1),\".\"),f=\":\";t.exports=o},function(t,e,n){\"use strict\";function r(t){return t&&t.__esModule?t:{default:t}}var i=n(41),o=r(i),a=n(182),u=r(a),c=n(183),s=r(c),l=n(181),f=r(l),p=n(180),h=r(p),d=n(179),v=r(d);(0,s.default)(),window.SHAP={SimpleListVisualizer:f.default,AdditiveForceVisualizer:h.default,AdditiveForceArrayVisualizer:v.default,React:o.default,ReactDom:u.default}}]);</script>" ], "text/plain": [ "<IPython.core.display.HTML object>" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "482c68559f734981a782c5a51425b91d", "version_major": 2, "version_minor": 0 }, "text/plain": [ " 0%\| \| 0/30 [00:00<?, ?it/s]" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import shap\n", "\n", "# load JS visualization code to notebook\n", "shap.initjs()\n", "\n", "explainer = shap.KernelExplainer(clf.predict_proba, X_train)\n", "shap_values = explainer.shap_values(X_test)\n", "\n" ] }, { "cell_type": "code", "execution_count": 42, "metadata": { "_kg_hide-output": false, "execution": { "iopub.execute_input": "2021-02-26T23:51:05.063403Z", "iopub.status.busy": "2021-02-26T23:51:05.062433Z", "iopub.status.idle": "2021-02-26T23:51:05.067068Z", "shell.execute_reply": "2021-02-26T23:51:05.066571Z" }, "papermill": { "duration": 0.457753, "end_time": "2021-02-26T23:51:05.067202", "exception": false, "start_time": "2021-02-26T23:51:04.609449", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "\n", "<div id='iNYOMUHUIYWCG89UREFQU'>\n", "<div style='color: #900; text-align: center;'>\n", " <b>Visualization omitted, Javascript library not loaded!</b><br>\n", " Have you run `initjs()` in this notebook? If this notebook was from another\n", " user you must also trust this notebook (File -> Trust notebook). If you are viewing\n", " this notebook on github the Javascript has been stripped for security. If you are using\n", " JupyterLab this error is because a JupyterLab extension has not yet been written.\n", "</div></div>\n", " <script>\n", " if (window.SHAP) SHAP.ReactDom.render(\n", " SHAP.React.createElement(SHAP.AdditiveForceVisualizer, {\"outNames\": [\"f(x)\"], \"baseValue\": 0.3246666666666668, \"outValue\": 0.0, \"link\": \"identity\", \"featureNames\": [\"SepalLengthCm\", \"SepalWidthCm\", \"PetalLengthCm\", \"PetalWidthCm\"], \"features\": {\"0\": {\"effect\": -0.010680555555555638, \"value\": 5.8}, \"1\": {\"effect\": -0.007222222222222255, \"value\": 2.8}, \"2\": {\"effect\": -0.15001388888888895, \"value\": 5.1}, \"3\": {\"effect\": -0.15675, \"value\": 2.4}}, \"plot_cmap\": \"RdBu\", \"labelMargin\": 20}),\n", " document.getElementById('iNYOMUHUIYWCG89UREFQU')\n", " );\n", "</script>" ], "text/plain": [ "<shap.plots._force.AdditiveForceVisualizer at 0x7f255a8839d0>" ] }, "execution_count": 42, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# plot the SHAP values for the Setosa output of the first instance\n", "shap.force_plot(explainer.expected_value[0], shap_values[0][0,:], X_test.iloc[0,:])" ] }, { "cell_type": "code", "execution_count": 43, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:51:05.974923Z", "iopub.status.busy": "2021-02-26T23:51:05.974273Z", "iopub.status.idle": "2021-02-26T23:51:05.979182Z", "shell.execute_reply": "2021-02-26T23:51:05.979680Z" }, "papermill": { "duration": 0.459479, "end_time": "2021-02-26T23:51:05.979861", "exception": false, "start_time": "2021-02-26T23:51:05.520382", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "\n", "<div id='iWNSTLZ1P1GKY5ZIBEKBE'>\n", "<div style='color: #900; text-align: center;'>\n", " <b>Visualization omitted, Javascript library not loaded!</b><br>\n", " Have you run `initjs()` in this notebook? If this notebook was from another\n", " user you must also trust this notebook (File -> Trust notebook). If you are viewing\n", " this notebook on github the Javascript has been stripped for security. If you are using\n", " JupyterLab this error is because a JupyterLab extension has not yet been written.\n", "</div></div>\n", " <script>\n", " if (window.SHAP) SHAP.ReactDom.render(\n", " SHAP.React.createElement(SHAP.AdditiveForceVisualizer, {\"outNames\": [\"f(x)\"], \"baseValue\": 0.36233832706178315, \"outValue\": 0.9689166666666666, \"link\": \"identity\", \"featureNames\": [\"SepalLengthCm\", \"SepalWidthCm\", \"PetalLengthCm\", \"PetalWidthCm\"], \"features\": {\"0\": {\"effect\": -0.0049028000249441706, \"value\": 5.8}, \"1\": {\"effect\": 0.026460663050506705, \"value\": 2.8}, \"2\": {\"effect\": 0.26595842466122455, \"value\": 5.1}, \"3\": {\"effect\": 0.31906205191809645, \"value\": 2.4}}, \"plot_cmap\": \"RdBu\", \"labelMargin\": 20}),\n", " document.getElementById('iWNSTLZ1P1GKY5ZIBEKBE')\n", " );\n", "</script>" ], "text/plain": [ "<shap.plots._force.AdditiveForceVisualizer at 0x7f255b0d6fd0>" ] }, "execution_count": 43, "metadata": {}, "output_type": "execute_result" } ], "source": [ "shap.force_plot(explainer.expected_value[1], shap_values[1][0,:], X_test.iloc[0,:])" ] }, { "cell_type": "code", "execution_count": 44, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:51:06.933582Z", "iopub.status.busy": "2021-02-26T23:51:06.932564Z", "iopub.status.idle": "2021-02-26T23:51:06.936729Z", "shell.execute_reply": "2021-02-26T23:51:06.936163Z" }, "papermill": { "duration": 0.46348, "end_time": "2021-02-26T23:51:06.936882", "exception": false, "start_time": "2021-02-26T23:51:06.473402", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "\n", "<div id='iDKHAQLNTPPM7JYGCWWGP'>\n", "<div style='color: #900; text-align: center;'>\n", " <b>Visualization omitted, Javascript library not loaded!</b><br>\n", " Have you run `initjs()` in this notebook? If this notebook was from another\n", " user you must also trust this notebook (File -> Trust notebook). If you are viewing\n", " this notebook on github the Javascript has been stripped for security. If you are using\n", " JupyterLab this error is because a JupyterLab extension has not yet been written.\n", "</div></div>\n", " <script>\n", " if (window.SHAP) SHAP.ReactDom.render(\n", " SHAP.React.createElement(SHAP.AdditiveForceVisualizer, {\"outNames\": [\"f(x)\"], \"baseValue\": 0.31299500627155036, \"outValue\": 0.03108333333333335, \"link\": \"identity\", \"featureNames\": [\"SepalLengthCm\", \"SepalWidthCm\", \"PetalLengthCm\", \"PetalWidthCm\"], \"features\": {\"0\": {\"effect\": 0.015583355580499704, \"value\": 5.8}, \"1\": {\"effect\": -0.01923844082828443, \"value\": 2.8}, \"2\": {\"effect\": -0.11594453577233592, \"value\": 5.1}, \"3\": {\"effect\": -0.16231205191809636, \"value\": 2.4}}, \"plot_cmap\": \"RdBu\", \"labelMargin\": 20}),\n", " document.getElementById('iDKHAQLNTPPM7JYGCWWGP')\n", " );\n", "</script>" ], "text/plain": [ "<shap.plots._force.AdditiveForceVisualizer at 0x7f255a883910>" ] }, "execution_count": 44, "metadata": {}, "output_type": "execute_result" } ], "source": [ "shap.force_plot(explainer.expected_value[2], shap_values[2][0,:], X_test.iloc[0,:])" ] }, { "cell_type": "code", "execution_count": 45, "metadata": { "_kg_hide-output": true, "execution": { "iopub.execute_input": "2021-02-26T23:51:07.877947Z", "iopub.status.busy": "2021-02-26T23:51:07.870927Z", "iopub.status.idle": "2021-02-26T23:51:09.930631Z", "shell.execute_reply": "2021-02-26T23:51:09.931154Z" }, "papermill": { "duration": 2.540097, "end_time": "2021-02-26T23:51:09.931354", "exception": false, "start_time": "2021-02-26T23:51:07.391257", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "6643326dd69f48d2aa3ff4a8487fefd0", "version_major": 2, "version_minor": 0 }, "text/plain": [ " 0%\| \| 0/30 [00:00<?, ?it/s]" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "shap_values = explainer.shap_values(X_test)" ] }, { "cell_type": "code", "execution_count": 46, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:51:10.831204Z", "iopub.status.busy": "2021-02-26T23:51:10.830515Z", "iopub.status.idle": "2021-02-26T23:51:10.841686Z", "shell.execute_reply": "2021-02-26T23:51:10.840994Z" }, "papermill": { "duration": 0.463647, "end_time": "2021-02-26T23:51:10.841830", "exception": false, "start_time": "2021-02-26T23:51:10.378183", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "\n", "<div id='iN4O02J22VCXY4MIF6UTH'>\n", "<div style='color: #900; text-align: center;'>\n", " <b>Visualization omitted, Javascript library not loaded!</b><br>\n", " Have you run `initjs()` in this notebook? If this notebook was from another\n", " user you must also trust this notebook (File -> Trust notebook). If you are viewing\n", " this notebook on github the Javascript has been stripped for security. If you are using\n", " JupyterLab this error is because a JupyterLab extension has not yet been written.\n", "</div></div>\n", " <script>\n", " if (window.SHAP) SHAP.ReactDom.render(\n", " SHAP.React.createElement(SHAP.AdditiveForceArrayVisualizer, {\"outNames\": [\"f(x)\"], \"baseValue\": 0.3246666666666668, \"link\": \"identity\", \"featureNames\": [\"SepalLengthCm\", \"SepalWidthCm\", \"PetalLengthCm\", \"PetalWidthCm\"], \"explanations\": [{\"outValue\": 0.0, \"simIndex\": 17.0, \"features\": {\"0\": {\"effect\": -0.010680555555555638, \"value\": 5.8}, \"1\": {\"effect\": -0.007222222222222255, \"value\": 2.8}, \"2\": {\"effect\": -0.15001388888888895, \"value\": 5.1}, \"3\": {\"effect\": -0.15675, \"value\": 2.4}}}, {\"outValue\": 0.0, \"simIndex\": 5.0, \"features\": {\"0\": {\"effect\": -0.012347222222222176, \"value\": 6.0}, \"1\": {\"effect\": -0.009722222222222215, \"value\": 2.2}, \"2\": {\"effect\": -0.14279166666666676, \"value\": 4.0}, \"3\": {\"effect\": 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0.03288888888888916, \"value\": 4.8}, \"1\": {\"effect\": 0.007055555555555648, \"value\": 3.4}, \"2\": {\"effect\": 0.3065555555555554, \"value\": 1.9}, \"3\": {\"effect\": 0.32883333333333287, \"value\": 0.2}}}, {\"outValue\": 0.99, \"simIndex\": 30.0, \"features\": {\"0\": {\"effect\": 0.03343055555555591, \"value\": 4.4}, \"1\": {\"effect\": -0.0031944444444446107, \"value\": 2.9}, \"2\": {\"effect\": 0.3085277777777776, \"value\": 1.4}, \"3\": {\"effect\": 0.3265694444444442, \"value\": 0.2}}}, {\"outValue\": 0.0, \"simIndex\": 12.0, \"features\": {\"0\": {\"effect\": -0.016347222222222277, \"value\": 6.2}, \"1\": {\"effect\": -0.004736111111111191, \"value\": 2.8}, \"2\": {\"effect\": -0.14236111111111113, \"value\": 4.8}, \"3\": {\"effect\": -0.1612222222222222, \"value\": 1.8}}}, {\"outValue\": 1.0, \"simIndex\": 23.0, \"features\": {\"0\": {\"effect\": 0.024722222222222257, \"value\": 4.6}, \"1\": {\"effect\": 0.013513888888889103, \"value\": 3.6}, \"2\": {\"effect\": 0.30655555555555547, \"value\": 1.0}, \"3\": {\"effect\": 0.3305416666666663, \"value\": 0.2}}}, {\"outValue\": 1.0, \"simIndex\": 22.0, \"features\": {\"0\": {\"effect\": 0.019819444444444445, \"value\": 5.1}, \"1\": {\"effect\": 0.017402777777778072, \"value\": 3.8}, \"2\": {\"effect\": 0.30713888888888874, \"value\": 1.9}, \"3\": {\"effect\": 0.3309722222222219, \"value\": 0.4}}}, {\"outValue\": 0.0, \"simIndex\": 9.0, \"features\": {\"0\": {\"effect\": -0.015541666666666717, \"value\": 6.2}, \"1\": {\"effect\": -0.006666666666666696, \"value\": 2.9}, \"2\": {\"effect\": -0.14279166666666673, \"value\": 4.3}, \"3\": {\"effect\": -0.15966666666666668, \"value\": 1.3}}}, {\"outValue\": 0.0, \"simIndex\": 1.0, \"features\": {\"0\": {\"effect\": 0.00323611111111112, \"value\": 5.0}, \"1\": {\"effect\": -0.013847222222222247, \"value\": 2.3}, \"2\": {\"effect\": -0.15055555555555555, \"value\": 3.3}, \"3\": {\"effect\": -0.16350000000000015, \"value\": 1.0}}}, {\"outValue\": 1.0, \"simIndex\": 25.0, \"features\": {\"0\": {\"effect\": 0.03288888888888916, \"value\": 5.0}, \"1\": {\"effect\": 0.007055555555555648, \"value\": 3.4}, \"2\": {\"effect\": 0.3065555555555554, \"value\": 1.6}, \"3\": {\"effect\": 0.32883333333333287, \"value\": 0.4}}}], \"plot_cmap\": \"RdBu\", \"ordering_keys\": null, \"ordering_keys_time_format\": null}),\n", " document.getElementById('iN4O02J22VCXY4MIF6UTH')\n", " );\n", "</script>" ], "text/plain": [ "<shap.plots._force.AdditiveForceArrayVisualizer at 0x7f259d3a3f50>" ] }, "execution_count": 46, "metadata": {}, "output_type": "execute_result" } ], "source": [ "\n", "shap.force_plot(explainer.expected_value[0], shap_values[0], X_test)" ] }, { "cell_type": "code", "execution_count": 47, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:51:11.788383Z", "iopub.status.busy": "2021-02-26T23:51:11.784443Z", "iopub.status.idle": "2021-02-26T23:51:11.793154Z", "shell.execute_reply": "2021-02-26T23:51:11.793665Z" }, "papermill": { "duration": 0.460316, "end_time": "2021-02-26T23:51:11.793833", "exception": false, "start_time": "2021-02-26T23:51:11.333517", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "\n", "<div id='iVWZACAQD7XEPNIKHIQ3Q'>\n", "<div style='color: #900; text-align: center;'>\n", " <b>Visualization omitted, Javascript library not loaded!</b><br>\n", " Have you run `initjs()` in this notebook? 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\n", "text/plain": [ "<Figure size 540x360 with 2 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "shap.dependence_plot(\"PetalLengthCm\", shap_values[0], X_test)" ] }, { "cell_type": "code", "execution_count": 50, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:51:14.784957Z", "iopub.status.busy": "2021-02-26T23:51:14.784368Z", "iopub.status.idle": "2021-02-26T23:51:15.029925Z", "shell.execute_reply": "2021-02-26T23:51:15.030469Z" }, "papermill": { "duration": 0.69563, "end_time": "2021-02-26T23:51:15.030648", "exception": false, "start_time": "2021-02-26T23:51:14.335018", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 540x360 with 2 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "shap.dependence_plot(\"PetalWidthCm\", shap_values[0], X_test)" ] }, { "cell_type": "code", "execution_count": 51, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:51:15.928838Z", "iopub.status.busy": "2021-02-26T23:51:15.928156Z", "iopub.status.idle": "2021-02-26T23:51:16.180660Z", "shell.execute_reply": "2021-02-26T23:51:16.181193Z" }, "papermill": { "duration": 0.701357, "end_time": "2021-02-26T23:51:16.181395", "exception": false, "start_time": "2021-02-26T23:51:15.480038", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 540x360 with 2 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "shap.dependence_plot(\"PetalLengthCm\", shap_values[1], X_test)" ] }, { "cell_type": "code", "execution_count": 52, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:51:17.090860Z", "iopub.status.busy": "2021-02-26T23:51:17.089837Z", "iopub.status.idle": "2021-02-26T23:51:17.341056Z", "shell.execute_reply": "2021-02-26T23:51:17.340407Z" }, "papermill": { "duration": 0.709916, "end_time": "2021-02-26T23:51:17.341198", "exception": false, "start_time": "2021-02-26T23:51:16.631282", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 540x360 with 2 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "shap.dependence_plot(\"PetalWidthCm\", shap_values[1], X_test)" ] }, { "cell_type": "code", "execution_count": 53, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:51:18.277157Z", "iopub.status.busy": "2021-02-26T23:51:18.258837Z", "iopub.status.idle": "2021-02-26T23:51:18.496174Z", "shell.execute_reply": "2021-02-26T23:51:18.495559Z" }, "papermill": { "duration": 0.698934, "end_time": "2021-02-26T23:51:18.496331", "exception": false, "start_time": "2021-02-26T23:51:17.797397", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 540x360 with 2 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "shap.dependence_plot(\"PetalLengthCm\", shap_values[2], X_test)" ] }, { "cell_type": "code", "execution_count": 54, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:51:19.447075Z", "iopub.status.busy": "2021-02-26T23:51:19.445992Z", "iopub.status.idle": "2021-02-26T23:51:19.686163Z", "shell.execute_reply": "2021-02-26T23:51:19.685622Z" }, "papermill": { "duration": 0.737729, "end_time": "2021-02-26T23:51:19.686298", "exception": false, "start_time": "2021-02-26T23:51:18.948569", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 540x360 with 2 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "shap.dependence_plot(\"PetalWidthCm\", shap_values[2], X_test)" ] }, { "cell_type": "code", "execution_count": 55, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:51:20.606487Z", "iopub.status.busy": "2021-02-26T23:51:20.605460Z", "iopub.status.idle": "2021-02-26T23:51:20.827028Z", "shell.execute_reply": "2021-02-26T23:51:20.826500Z" }, "papermill": { "duration": 0.691558, "end_time": "2021-02-26T23:51:20.827178", "exception": false, "start_time": "2021-02-26T23:51:20.135620", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 576x223.2 with 2 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "shap.summary_plot(shap_values[0], X_test)" ] }, { "cell_type": "code", "execution_count": 56, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:51:21.744212Z", "iopub.status.busy": "2021-02-26T23:51:21.737351Z", "iopub.status.idle": "2021-02-26T23:51:21.976272Z", "shell.execute_reply": "2021-02-26T23:51:21.975643Z" }, "papermill": { "duration": 0.697671, "end_time": "2021-02-26T23:51:21.976431", "exception": false, "start_time": "2021-02-26T23:51:21.278760", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 576x223.2 with 2 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "shap.summary_plot(shap_values[1], X_test)" ] }, { "cell_type": "code", "execution_count": 57, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:51:22.945835Z", "iopub.status.busy": "2021-02-26T23:51:22.944781Z", "iopub.status.idle": "2021-02-26T23:51:23.164115Z", "shell.execute_reply": "2021-02-26T23:51:23.163267Z" }, "papermill": { "duration": 0.699583, "end_time": "2021-02-26T23:51:23.164283", "exception": false, "start_time": "2021-02-26T23:51:22.464700", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 576x223.2 with 2 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "shap.summary_plot(shap_values[2], X_test)" ] }, { "cell_type": "code", "execution_count": 58, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:51:24.096467Z", "iopub.status.busy": "2021-02-26T23:51:24.093366Z", "iopub.status.idle": "2021-02-26T23:51:24.268278Z", "shell.execute_reply": "2021-02-26T23:51:24.267776Z" }, "papermill": { "duration": 0.65164, "end_time": "2021-02-26T23:51:24.268439", "exception": false, "start_time": "2021-02-26T23:51:23.616799", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 576x223.2 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "shap.summary_plot(shap_values, X_test, plot_type=\"bar\")" ] }, { "cell_type": "code", "execution_count": 59, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:51:25.229375Z", "iopub.status.busy": "2021-02-26T23:51:25.228692Z", "iopub.status.idle": "2021-02-26T23:51:25.241028Z", "shell.execute_reply": "2021-02-26T23:51:25.241539Z" }, "papermill": { "duration": 0.523486, "end_time": "2021-02-26T23:51:25.241708", "exception": false, "start_time": "2021-02-26T23:51:24.718222", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " precision recall f1-score support\n", "\n", " 1 0.58 1.00 0.73 11\n", " 2 0.55 1.00 0.71 6\n", " 3 0.00 0.00 0.00 13\n", "\n", " accuracy 0.57 30\n", " macro avg 0.37 0.67 0.48 30\n", "weighted avg 0.32 0.57 0.41 30\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n", "Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n", "Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n" ] } ], "source": [ "sgd_clf = SGDClassifier(random_state=0)\n", "sgd_clf.fit(X_train, np.ravel(y_train))\n", "y_pred = sgd_clf.predict(X_test)\n", "print(classification_report(y_test, y_pred))" ] }, { "cell_type": "code", "execution_count": 60, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:51:26.168904Z", "iopub.status.busy": "2021-02-26T23:51:26.159515Z", "iopub.status.idle": "2021-02-26T23:51:26.192405Z", "shell.execute_reply": "2021-02-26T23:51:26.191576Z" }, "papermill": { "duration": 0.496755, "end_time": "2021-02-26T23:51:26.192549", "exception": false, "start_time": "2021-02-26T23:51:25.695794", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " precision recall f1-score support\n", "\n", " 1 1.00 1.00 1.00 11\n", " 2 0.86 1.00 0.92 6\n", " 3 1.00 0.92 0.96 13\n", "\n", " accuracy 0.97 30\n", " macro avg 0.95 0.97 0.96 30\n", "weighted avg 0.97 0.97 0.97 30\n", "\n" ] } ], "source": [ "log_clf = LogisticRegression(multi_class='ovr', solver='lbfgs')\n", "log_clf.fit(X_train, np.ravel(y_train))\n", "y_pred = log_clf.predict(X_test)\n", "print(classification_report(y_test, y_pred))" ] }, { "cell_type": "code", "execution_count": 61, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:51:27.114581Z", "iopub.status.busy": "2021-02-26T23:51:27.113912Z", "iopub.status.idle": "2021-02-26T23:51:27.209888Z", "shell.execute_reply": "2021-02-26T23:51:27.210768Z" }, "papermill": { "duration": 0.562682, "end_time": "2021-02-26T23:51:27.210962", "exception": false, "start_time": "2021-02-26T23:51:26.648280", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[23:51:27] WARNING: ../src/learner.cc:1061: Starting in XGBoost 1.3.0, the default evaluation metric used with the objective 'multi:softprob' was changed from 'merror' to 'mlogloss'. Explicitly set eval_metric if you'd like to restore the old behavior.\n", " precision recall f1-score support\n", "\n", " 1 1.00 1.00 1.00 11\n", " 2 1.00 1.00 1.00 6\n", " 3 1.00 1.00 1.00 13\n", "\n", " accuracy 1.00 30\n", " macro avg 1.00 1.00 1.00 30\n", "weighted avg 1.00 1.00 1.00 30\n", "\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "The use of label encoder in XGBClassifier is deprecated and will be removed in a future release. To remove this warning, do the following: 1) Pass option use_label_encoder=False when constructing XGBClassifier object; and 2) Encode your labels (y) as integers starting with 0, i.e. 0, 1, 2, ..., [num_class - 1].\n" ] } ], "source": [ "xgb_clf = XGBClassifier(random_state=0, n_jobs=-1, learning_rate=0.1, \n", " n_estimators=100, max_depth=3)\n", "xgb_clf.fit(X_train, np.ravel(y_train))\n", "y_pred = xgb_clf.predict(X_test)\n", "print(classification_report(y_test, y_pred))" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.4575, "end_time": "2021-02-26T23:51:28.126356", "exception": false, "start_time": "2021-02-26T23:51:27.668856", "status": "completed" }, "tags": [] }, "source": [ "https://towardsdatascience.com/automate-stacking-in-python-fc3e7834772e\n", "\n", "https://github.com/vecxoz/vecstack/blob/master/examples/00_stacking_concept_pictures_code.ipynb" ] }, { "cell_type": "code", "execution_count": 62, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:51:29.047413Z", "iopub.status.busy": "2021-02-26T23:51:29.046736Z", "iopub.status.idle": "2021-02-26T23:51:29.049775Z", "shell.execute_reply": "2021-02-26T23:51:29.049230Z" }, "papermill": { "duration": 0.466585, "end_time": "2021-02-26T23:51:29.049925", "exception": false, "start_time": "2021-02-26T23:51:28.583340", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "models = [\n", "# KNeighborsClassifier(n_neighbors=5,\n", "# n_jobs=-1),\n", " SGDClassifier(random_state=0),\n", " \n", "# RandomForestClassifier(random_state=0, n_jobs=-1, \n", "# n_estimators=100, max_depth=3),\n", " RandomForestClassifier(random_state=0), \n", "# XGBClassifier(random_state=0, n_jobs=-1, learning_rate=0.1, \n", "# n_estimators=100, max_depth=3)\n", " LogisticRegression(random_state=0,multi_class='ovr', solver='lbfgs')\n", "]\n" ] }, { "cell_type": "code", "execution_count": 63, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:51:30.015955Z", "iopub.status.busy": "2021-02-26T23:51:30.015235Z", "iopub.status.idle": "2021-02-26T23:51:30.934848Z", "shell.execute_reply": "2021-02-26T23:51:30.935348Z" }, "papermill": { "duration": 1.38779, "end_time": "2021-02-26T23:51:30.935533", "exception": false, "start_time": "2021-02-26T23:51:29.547743", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "task: [classification]\n", "n_classes: [3]\n", "metric: [accuracy_score]\n", "mode: [oof_pred_bag]\n", "n_models: [3]\n", "\n", "model 0: [SGDClassifier]\n", " fold 0: [0.66666667]\n", " fold 1: [0.76666667]\n", " fold 2: [0.93333333]\n", " fold 3: [0.83333333]\n", " ----\n", " MEAN: [0.80000000] + [0.09718253]\n", " FULL: [0.80000000]\n", "\n", "model 1: [RandomForestClassifier]\n", " fold 0: [0.96666667]\n", " fold 1: [0.90000000]\n", " fold 2: [1.00000000]\n", " fold 3: [0.86666667]\n", " ----\n", " MEAN: [0.93333333] + [0.05270463]\n", " FULL: [0.93333333]\n", "\n", "model 2: [LogisticRegression]\n", " fold 0: [0.93333333]\n", " fold 1: [0.90000000]\n", " fold 2: [0.96666667]\n", " fold 3: [0.90000000]\n", " ----\n", " MEAN: [0.92500000] + [0.02763854]\n", " FULL: [0.92500000]\n", "\n" ] } ], "source": [ "S_train, S_test = stacking(models, \n", " X_train, np.ravel(y_train), X_test, \n", " regression=False, \n", " \n", " mode='oof_pred_bag', \n", " \n", " needs_proba=False,\n", " \n", " save_dir=None, \n", " \n", " metric=accuracy_score, \n", " \n", " n_folds=4, \n", " \n", " stratified=True,\n", " \n", " shuffle=True, \n", " \n", " random_state=0, \n", " \n", " verbose=2)" ] }, { "cell_type": "code", "execution_count": 64, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:51:31.868876Z", "iopub.status.busy": "2021-02-26T23:51:31.868226Z", "iopub.status.idle": "2021-02-26T23:51:31.872432Z", "shell.execute_reply": "2021-02-26T23:51:31.871813Z" }, "papermill": { "duration": 0.47346, "end_time": "2021-02-26T23:51:31.872569", "exception": false, "start_time": "2021-02-26T23:51:31.399109", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "array([[2, 2, 2],\n", " [3, 3, 3],\n", " [1, 1, 1],\n", " [3, 2, 2],\n", " [2, 2, 2],\n", " [3, 3, 3],\n", " [1, 1, 1],\n", " [3, 2, 2],\n", " [3, 3, 3],\n", " [2, 3, 3],\n", " [2, 2, 2],\n", " [1, 1, 1],\n", " [2, 2, 2],\n", " [1, 1, 1],\n", " [1, 1, 1],\n", " [3, 3, 3],\n", " [2, 2, 2],\n", " [2, 2, 2],\n", " [2, 3, 3],\n", " [2, 2, 2],\n", " [3, 3, 3],\n", " [2, 2, 2],\n", " [3, 3, 2],\n", " [2, 3, 3],\n", " [3, 2, 2],\n", " [2, 3, 2],\n", " [2, 3, 3],\n", " [2, 2, 2],\n", " [2, 3, 2],\n", " [3, 2, 2],\n", " [2, 3, 2],\n", " [1, 1, 1],\n", " [2, 2, 2],\n", " [2, 3, 3],\n", " [2, 3, 3],\n", " [3, 3, 3],\n", " [3, 3, 3],\n", " [2, 2, 2],\n", " [1, 1, 1],\n", " [1, 1, 1],\n", " [2, 2, 2],\n", " [3, 3, 3],\n", " [1, 1, 1],\n", " [1, 1, 1],\n", " [2, 3, 2],\n", " [1, 1, 1],\n", " [2, 2, 2],\n", " [3, 3, 3],\n", " 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1]])" ] }, "execution_count": 66, "metadata": {}, "output_type": "execute_result" } ], "source": [ "S_test" ] }, { "cell_type": "code", "execution_count": 67, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:51:34.778475Z", "iopub.status.busy": "2021-02-26T23:51:34.777811Z", "iopub.status.idle": "2021-02-26T23:51:34.782385Z", "shell.execute_reply": "2021-02-26T23:51:34.782860Z" }, "papermill": { "duration": 0.512933, "end_time": "2021-02-26T23:51:34.783019", "exception": false, "start_time": "2021-02-26T23:51:34.270086", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "(30, 3)" ] }, "execution_count": 67, "metadata": {}, "output_type": "execute_result" } ], "source": [ "S_test.shape" ] }, { "cell_type": "code", "execution_count": 68, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:51:35.714163Z", "iopub.status.busy": "2021-02-26T23:51:35.713521Z", "iopub.status.idle": "2021-02-26T23:51:35.734995Z", "shell.execute_reply": "2021-02-26T23:51:35.734490Z" }, "papermill": { "duration": 0.483947, "end_time": "2021-02-26T23:51:35.735134", "exception": false, "start_time": "2021-02-26T23:51:35.251187", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Final prediction score: [1.00000000]\n" ] } ], "source": [ "# model = XGBClassifier(random_state=0, n_jobs=-1, learning_rate=0.1, \n", "# n_estimators=100, max_depth=3)\n", "model = LogisticRegression(multi_class='ovr', solver='lbfgs') \n", "model = model.fit(S_train, np.ravel(y_train))\n", "y_pred = model.predict(S_test)\n", "print('Final prediction score: [%.8f]' % accuracy_score(y_test.values, y_pred))" ] }, { "cell_type": "code", "execution_count": 69, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:51:36.666072Z", "iopub.status.busy": "2021-02-26T23:51:36.665032Z", "iopub.status.idle": "2021-02-26T23:51:36.671996Z", "shell.execute_reply": "2021-02-26T23:51:36.672536Z" }, "papermill": { "duration": 0.476576, "end_time": "2021-02-26T23:51:36.672713", "exception": false, "start_time": "2021-02-26T23:51:36.196137", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " precision recall f1-score support\n", "\n", " 1 1.00 1.00 1.00 11\n", " 2 1.00 1.00 1.00 6\n", " 3 1.00 1.00 1.00 13\n", "\n", " accuracy 1.00 30\n", " macro avg 1.00 1.00 1.00 30\n", "weighted avg 1.00 1.00 1.00 30\n", "\n" ] } ], "source": [ "from sklearn.metrics import classification_report\n", "print(classification_report(y_test, y_pred))" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.9" }, "papermill": { 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{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:50:31.695889Z", "iopub.status.busy": "2021-02-26T23:50:31.694802Z", "iopub.status.idle": "2021-02-26T23:50:31.739081Z", "shell.execute_reply": "2021-02-26T23:50:31.739659Z" }, "papermill": { "duration": 0.058647, "end_time": "2021-02-26T23:50:31.740000", "exception": false, "start_time": "2021-02-26T23:50:31.681353", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "import pandas as pd\n", "\n", "iowa_file_path = '../input/home-data-for-ml-course/train.csv'\n", "\n", "home_data = pd.read_csv(iowa_file_path)" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:50:31.760266Z", "iopub.status.busy": "2021-02-26T23:50:31.759542Z", "iopub.status.idle": "2021-02-26T23:50:31.892271Z", "shell.execute_reply": "2021-02-26T23:50:31.892785Z" }, "papermill": { "duration": 0.145896, "end_time": "2021-02-26T23:50:31.892955", "exception": false, "start_time": "2021-02-26T23:50:31.747059", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>Id</th>\n", " <th>MSSubClass</th>\n", " <th>LotFrontage</th>\n", " <th>LotArea</th>\n", " <th>OverallQual</th>\n", " <th>OverallCond</th>\n", " <th>YearBuilt</th>\n", " <th>YearRemodAdd</th>\n", " <th>MasVnrArea</th>\n", " <th>BsmtFinSF1</th>\n", " <th>...</th>\n", " <th>WoodDeckSF</th>\n", " <th>OpenPorchSF</th>\n", " <th>EnclosedPorch</th>\n", " <th>3SsnPorch</th>\n", " <th>ScreenPorch</th>\n", " <th>PoolArea</th>\n", " <th>MiscVal</th>\n", " <th>MoSold</th>\n", " <th>YrSold</th>\n", " <th>SalePrice</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>count</th>\n", " <td>1460.000000</td>\n", " <td>1460.000000</td>\n", " <td>1201.000000</td>\n", " <td>1460.000000</td>\n", " <td>1460.000000</td>\n", " <td>1460.000000</td>\n", " <td>1460.000000</td>\n", " <td>1460.000000</td>\n", " <td>1452.000000</td>\n", " <td>1460.000000</td>\n", " <td>...</td>\n", " <td>1460.000000</td>\n", " <td>1460.000000</td>\n", " <td>1460.000000</td>\n", " <td>1460.000000</td>\n", " <td>1460.000000</td>\n", " <td>1460.000000</td>\n", " <td>1460.000000</td>\n", " <td>1460.000000</td>\n", " <td>1460.000000</td>\n", " <td>1460.000000</td>\n", " </tr>\n", " <tr>\n", " <th>mean</th>\n", " <td>730.500000</td>\n", " <td>56.897260</td>\n", " <td>70.049958</td>\n", " <td>10516.828082</td>\n", " <td>6.099315</td>\n", " <td>5.575342</td>\n", " <td>1971.267808</td>\n", " <td>1984.865753</td>\n", " <td>103.685262</td>\n", " <td>443.639726</td>\n", " <td>...</td>\n", " <td>94.244521</td>\n", " <td>46.660274</td>\n", " <td>21.954110</td>\n", " <td>3.409589</td>\n", " <td>15.060959</td>\n", " <td>2.758904</td>\n", " <td>43.489041</td>\n", " <td>6.321918</td>\n", " <td>2007.815753</td>\n", " <td>180921.195890</td>\n", " </tr>\n", " <tr>\n", " <th>std</th>\n", " <td>421.610009</td>\n", " <td>42.300571</td>\n", " <td>24.284752</td>\n", " <td>9981.264932</td>\n", " <td>1.382997</td>\n", " <td>1.112799</td>\n", " <td>30.202904</td>\n", " <td>20.645407</td>\n", " <td>181.066207</td>\n", " <td>456.098091</td>\n", " <td>...</td>\n", " <td>125.338794</td>\n", " <td>66.256028</td>\n", " <td>61.119149</td>\n", " <td>29.317331</td>\n", " <td>55.757415</td>\n", " <td>40.177307</td>\n", " <td>496.123024</td>\n", " <td>2.703626</td>\n", " <td>1.328095</td>\n", " <td>79442.502883</td>\n", " </tr>\n", " <tr>\n", " <th>min</th>\n", " <td>1.000000</td>\n", " <td>20.000000</td>\n", " <td>21.000000</td>\n", " <td>1300.000000</td>\n", " <td>1.000000</td>\n", " <td>1.000000</td>\n", " <td>1872.000000</td>\n", " <td>1950.000000</td>\n", " <td>0.000000</td>\n", " <td>0.000000</td>\n", " <td>...</td>\n", " <td>0.000000</td>\n", " <td>0.000000</td>\n", " <td>0.000000</td>\n", " <td>0.000000</td>\n", " <td>0.000000</td>\n", " <td>0.000000</td>\n", " <td>0.000000</td>\n", " <td>1.000000</td>\n", " <td>2006.000000</td>\n", " <td>34900.000000</td>\n", " </tr>\n", " <tr>\n", " <th>25%</th>\n", " <td>365.750000</td>\n", " <td>20.000000</td>\n", " <td>59.000000</td>\n", " <td>7553.500000</td>\n", " <td>5.000000</td>\n", " <td>5.000000</td>\n", " <td>1954.000000</td>\n", " <td>1967.000000</td>\n", " <td>0.000000</td>\n", " <td>0.000000</td>\n", " <td>...</td>\n", " <td>0.000000</td>\n", " <td>0.000000</td>\n", " <td>0.000000</td>\n", " <td>0.000000</td>\n", " <td>0.000000</td>\n", " <td>0.000000</td>\n", " <td>0.000000</td>\n", " <td>5.000000</td>\n", " <td>2007.000000</td>\n", " <td>129975.000000</td>\n", " </tr>\n", " <tr>\n", " <th>50%</th>\n", " <td>730.500000</td>\n", " <td>50.000000</td>\n", " <td>69.000000</td>\n", " <td>9478.500000</td>\n", " <td>6.000000</td>\n", " <td>5.000000</td>\n", " <td>1973.000000</td>\n", " <td>1994.000000</td>\n", " <td>0.000000</td>\n", " <td>383.500000</td>\n", " <td>...</td>\n", " <td>0.000000</td>\n", " <td>25.000000</td>\n", " <td>0.000000</td>\n", " <td>0.000000</td>\n", " <td>0.000000</td>\n", " <td>0.000000</td>\n", " <td>0.000000</td>\n", " <td>6.000000</td>\n", " <td>2008.000000</td>\n", " <td>163000.000000</td>\n", " </tr>\n", " <tr>\n", " <th>75%</th>\n", " <td>1095.250000</td>\n", " <td>70.000000</td>\n", " <td>80.000000</td>\n", " <td>11601.500000</td>\n", " <td>7.000000</td>\n", " <td>6.000000</td>\n", " <td>2000.000000</td>\n", " <td>2004.000000</td>\n", " <td>166.000000</td>\n", " <td>712.250000</td>\n", " <td>...</td>\n", " <td>168.000000</td>\n", " <td>68.000000</td>\n", " <td>0.000000</td>\n", " <td>0.000000</td>\n", " <td>0.000000</td>\n", " <td>0.000000</td>\n", " <td>0.000000</td>\n", " <td>8.000000</td>\n", " <td>2009.000000</td>\n", " <td>214000.000000</td>\n", " </tr>\n", " <tr>\n", " <th>max</th>\n", " <td>1460.000000</td>\n", " <td>190.000000</td>\n", " <td>313.000000</td>\n", " <td>215245.000000</td>\n", " <td>10.000000</td>\n", " <td>9.000000</td>\n", " <td>2010.000000</td>\n", " <td>2010.000000</td>\n", " <td>1600.000000</td>\n", " <td>5644.000000</td>\n", " <td>...</td>\n", " <td>857.000000</td>\n", " <td>547.000000</td>\n", " <td>552.000000</td>\n", " <td>508.000000</td>\n", " <td>480.000000</td>\n", " <td>738.000000</td>\n", " <td>15500.000000</td>\n", " <td>12.000000</td>\n", " <td>2010.000000</td>\n", " <td>755000.000000</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "<p>8 rows × 38 columns</p>\n", "</div>" ], "text/plain": [ " Id MSSubClass LotFrontage LotArea OverallQual \\\n", "count 1460.000000 1460.000000 1201.000000 1460.000000 1460.000000 \n", "mean 730.500000 56.897260 70.049958 10516.828082 6.099315 \n", "std 421.610009 42.300571 24.284752 9981.264932 1.382997 \n", "min 1.000000 20.000000 21.000000 1300.000000 1.000000 \n", "25% 365.750000 20.000000 59.000000 7553.500000 5.000000 \n", "50% 730.500000 50.000000 69.000000 9478.500000 6.000000 \n", "75% 1095.250000 70.000000 80.000000 11601.500000 7.000000 \n", "max 1460.000000 190.000000 313.000000 215245.000000 10.000000 \n", "\n", " OverallCond YearBuilt YearRemodAdd MasVnrArea BsmtFinSF1 ... \\\n", "count 1460.000000 1460.000000 1460.000000 1452.000000 1460.000000 ... \n", "mean 5.575342 1971.267808 1984.865753 103.685262 443.639726 ... \n", "std 1.112799 30.202904 20.645407 181.066207 456.098091 ... \n", "min 1.000000 1872.000000 1950.000000 0.000000 0.000000 ... \n", "25% 5.000000 1954.000000 1967.000000 0.000000 0.000000 ... \n", "50% 5.000000 1973.000000 1994.000000 0.000000 383.500000 ... \n", "75% 6.000000 2000.000000 2004.000000 166.000000 712.250000 ... \n", "max 9.000000 2010.000000 2010.000000 1600.000000 5644.000000 ... \n", "\n", " WoodDeckSF OpenPorchSF EnclosedPorch 3SsnPorch ScreenPorch \\\n", "count 1460.000000 1460.000000 1460.000000 1460.000000 1460.000000 \n", "mean 94.244521 46.660274 21.954110 3.409589 15.060959 \n", "std 125.338794 66.256028 61.119149 29.317331 55.757415 \n", "min 0.000000 0.000000 0.000000 0.000000 0.000000 \n", "25% 0.000000 0.000000 0.000000 0.000000 0.000000 \n", "50% 0.000000 25.000000 0.000000 0.000000 0.000000 \n", "75% 168.000000 68.000000 0.000000 0.000000 0.000000 \n", "max 857.000000 547.000000 552.000000 508.000000 480.000000 \n", "\n", " PoolArea MiscVal MoSold YrSold SalePrice \n", "count 1460.000000 1460.000000 1460.000000 1460.000000 1460.000000 \n", "mean 2.758904 43.489041 6.321918 2007.815753 180921.195890 \n", "std 40.177307 496.123024 2.703626 1.328095 79442.502883 \n", "min 0.000000 0.000000 1.000000 2006.000000 34900.000000 \n", "25% 0.000000 0.000000 5.000000 2007.000000 129975.000000 \n", "50% 0.000000 0.000000 6.000000 2008.000000 163000.000000 \n", "75% 0.000000 0.000000 8.000000 2009.000000 214000.000000 \n", "max 738.000000 15500.000000 12.000000 2010.000000 755000.000000 \n", "\n", "[8 rows x 38 columns]" ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "\n", "home_data.describe()" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:50:31.910704Z", "iopub.status.busy": "2021-02-26T23:50:31.909921Z", "iopub.status.idle": "2021-02-26T23:50:31.914211Z", "shell.execute_reply": "2021-02-26T23:50:31.913700Z" }, "papermill": { "duration": 0.01406, "end_time": "2021-02-26T23:50:31.914355", "exception": false, "start_time": "2021-02-26T23:50:31.900295", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "y = home_data.SalePrice" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:50:31.935396Z", "iopub.status.busy": "2021-02-26T23:50:31.934721Z", "iopub.status.idle": "2021-02-26T23:50:31.938075Z", "shell.execute_reply": "2021-02-26T23:50:31.937443Z" }, "papermill": { "duration": 0.016435, "end_time": "2021-02-26T23:50:31.938220", "exception": false, "start_time": "2021-02-26T23:50:31.921785", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "\n", "feature_names = ['LotArea', 'YearBuilt','1stFlrSF','2ndFlrSF','FullBath','BedroomAbvGr','TotRmsAbvGrd']\n", "\n", "X = home_data[feature_names]\n" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:50:31.956061Z", "iopub.status.busy": "2021-02-26T23:50:31.955376Z", "iopub.status.idle": "2021-02-26T23:50:31.985817Z", "shell.execute_reply": "2021-02-26T23:50:31.986546Z" }, "papermill": { "duration": 0.041082, "end_time": "2021-02-26T23:50:31.986779", "exception": false, "start_time": "2021-02-26T23:50:31.945697", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " LotArea YearBuilt 1stFlrSF 2ndFlrSF FullBath \\\n", "count 1460.000000 1460.000000 1460.000000 1460.000000 1460.000000 \n", "mean 10516.828082 1971.267808 1162.626712 346.992466 1.565068 \n", "std 9981.264932 30.202904 386.587738 436.528436 0.550916 \n", "min 1300.000000 1872.000000 334.000000 0.000000 0.000000 \n", "25% 7553.500000 1954.000000 882.000000 0.000000 1.000000 \n", "50% 9478.500000 1973.000000 1087.000000 0.000000 2.000000 \n", "75% 11601.500000 2000.000000 1391.250000 728.000000 2.000000 \n", "max 215245.000000 2010.000000 4692.000000 2065.000000 3.000000 \n", "\n", " BedroomAbvGr TotRmsAbvGrd \n", "count 1460.000000 1460.000000 \n", "mean 2.866438 6.517808 \n", "std 0.815778 1.625393 \n", "min 0.000000 2.000000 \n", "25% 2.000000 5.000000 \n", "50% 3.000000 6.000000 \n", "75% 3.000000 7.000000 \n", "max 8.000000 14.000000 \n", " LotArea YearBuilt 1stFlrSF 2ndFlrSF FullBath BedroomAbvGr \\\n", "0 8450 2003 856 854 2 3 \n", "1 9600 1976 1262 0 2 3 \n", "2 11250 2001 920 866 2 3 \n", "3 9550 1915 961 756 1 3 \n", "4 14260 2000 1145 1053 2 4 \n", "\n", " TotRmsAbvGrd \n", "0 8 \n", "1 6 \n", "2 6 \n", "3 7 \n", "4 9 \n" ] } ], "source": [ "\n", "print(X.describe())\n", "\n", "print(X.head())" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:50:32.006852Z", "iopub.status.busy": "2021-02-26T23:50:32.006130Z", "iopub.status.idle": "2021-02-26T23:50:33.483308Z", "shell.execute_reply": "2021-02-26T23:50:33.483847Z" }, "papermill": { "duration": 1.488727, "end_time": "2021-02-26T23:50:33.484029", "exception": false, "start_time": "2021-02-26T23:50:31.995302", "status": "completed" }, "tags": [] }, "outputs": [ { "ename": "NameError", "evalue": "name 'step_3' is not defined", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mNameError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m<ipython-input-6-89b899d0508a>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 8\u001b[0m \u001b[0;31m# Check your answer\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 9\u001b[0;31m \u001b[0mstep_3\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcheck\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", "\u001b[0;31mNameError\u001b[0m: name 'step_3' is not defined" ] } ], "source": [ "from sklearn.tree import DecisionTreeRegressor\n", "\n", "iowa_model = DecisionTreeRegressor(random_state=1)\n", "\n", "# Fit the model\n", "iowa_model.fit(X,y)\n", "\n", "# Check your answer\n", "step_3.check()" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:50:33.504818Z", "iopub.status.busy": "2021-02-26T23:50:33.504093Z", "iopub.status.idle": "2021-02-26T23:50:33.511879Z", "shell.execute_reply": "2021-02-26T23:50:33.512380Z" }, "papermill": { "duration": 0.019703, "end_time": "2021-02-26T23:50:33.512643", "exception": false, "start_time": "2021-02-26T23:50:33.492940", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[208500. 181500. 223500. ... 266500. 142125. 147500.]\n" ] } ], "source": [ "predictions = iowa_model.predict(X)\n", "print(predictions)" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:50:33.539505Z", "iopub.status.busy": "2021-02-26T23:50:33.538394Z", "iopub.status.idle": "2021-02-26T23:50:33.542268Z", "shell.execute_reply": "2021-02-26T23:50:33.543069Z" }, "papermill": { "duration": 0.021489, "end_time": "2021-02-26T23:50:33.543319", "exception": false, "start_time": "2021-02-26T23:50:33.521830", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0 208500\n", "1 181500\n", "2 223500\n", "3 140000\n", "4 250000\n", "Name: SalePrice, dtype: int64\n", "[208500. 181500. 223500. 140000. 250000.]\n" ] } ], "source": [ "predictions = iowa_model.predict(X.head())\n", "print(y.head())\n", "print(predictions)" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.9" }, "papermill": { "default_parameters": {}, "duration": 8.454126, "end_time": "2021-02-26T23:50:34.166262", "environment_variables": {}, "exception": null, "input_path": "__notebook__.ipynb", "output_path": "__notebook__.ipynb", "parameters": {}, "start_time": "2021-02-26T23:50:25.712136", "version": "2.2.2" } }, "nbformat": 4, "nbformat_minor": 4 }	0055/327/55327932.ipynb	s3://data-agents/kaggle-outputs/sharded/012_00055.jsonl.gz
{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": { "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19", "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5", "execution": { "iopub.execute_input": "2021-02-26T23:54:50.397383Z", "iopub.status.busy": "2021-02-26T23:54:50.396246Z", "iopub.status.idle": "2021-02-26T23:54:50.408364Z", "shell.execute_reply": "2021-02-26T23:54:50.408981Z" }, "papermill": { "duration": 0.033643, "end_time": "2021-02-26T23:54:50.409366", "exception": false, "start_time": "2021-02-26T23:54:50.375723", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "/kaggle/input/house-prices-advanced-regression-techniques/sample_submission.csv\n", "/kaggle/input/house-prices-advanced-regression-techniques/data_description.txt\n", "/kaggle/input/house-prices-advanced-regression-techniques/train.csv\n", "/kaggle/input/house-prices-advanced-regression-techniques/test.csv\n" ] } ], "source": [ "# This Python 3 environment comes with many helpful analytics libraries installed\n", "# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n", "# For example, here's several helpful packages to load\n", "\n", "import numpy as np # linear algebra\n", "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n", "\n", "# Input data files are available in the read-only \"../input/\" directory\n", "# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n", "\n", "import os\n", "for dirname, _, filenames in os.walk('/kaggle/input'):\n", " for filename in filenames:\n", " print(os.path.join(dirname, filename))\n", "\n", "# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n", "# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:54:50.449881Z", "iopub.status.busy": "2021-02-26T23:54:50.449021Z", "iopub.status.idle": "2021-02-26T23:54:51.292700Z", "shell.execute_reply": "2021-02-26T23:54:51.291521Z" }, "papermill": { "duration": 0.866461, "end_time": "2021-02-26T23:54:51.292876", "exception": false, "start_time": "2021-02-26T23:54:50.426415", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "import matplotlib.pyplot as plt\n", "import seaborn as sns\n", "%matplotlib inline" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:54:51.332369Z", "iopub.status.busy": "2021-02-26T23:54:51.331590Z", "iopub.status.idle": "2021-02-26T23:54:51.417484Z", "shell.execute_reply": "2021-02-26T23:54:51.416876Z" }, "papermill": { "duration": 0.107288, "end_time": "2021-02-26T23:54:51.417648", "exception": false, "start_time": "2021-02-26T23:54:51.310360", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Good, continue\n" ] } ], "source": [ "train_data = pd.read_csv(\"../input/house-prices-advanced-regression-techniques/train.csv\")\n", "test_data = pd.read_csv(\"../input/house-prices-advanced-regression-techniques/test.csv\")\n", "print(\"Good, continue\")" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:54:51.459762Z", "iopub.status.busy": "2021-02-26T23:54:51.458699Z", "iopub.status.idle": "2021-02-26T23:54:51.463978Z", "shell.execute_reply": "2021-02-26T23:54:51.463339Z" }, "papermill": { "duration": 0.02979, "end_time": "2021-02-26T23:54:51.464135", "exception": false, "start_time": "2021-02-26T23:54:51.434345", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "((1460, 81), (1459, 80))" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "train_data.shape, test_data.shape" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:54:51.510190Z", "iopub.status.busy": "2021-02-26T23:54:51.509356Z", "iopub.status.idle": "2021-02-26T23:54:51.544752Z", "shell.execute_reply": "2021-02-26T23:54:51.545205Z" }, "papermill": { "duration": 0.063896, "end_time": "2021-02-26T23:54:51.545430", "exception": false, "start_time": "2021-02-26T23:54:51.481534", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>Id</th>\n", " <th>MSSubClass</th>\n", " <th>MSZoning</th>\n", " <th>LotFrontage</th>\n", " <th>LotArea</th>\n", " <th>Street</th>\n", " <th>Alley</th>\n", " <th>LotShape</th>\n", " <th>LandContour</th>\n", " <th>Utilities</th>\n", " <th>...</th>\n", " <th>PoolArea</th>\n", " <th>PoolQC</th>\n", " <th>Fence</th>\n", " <th>MiscFeature</th>\n", " <th>MiscVal</th>\n", " <th>MoSold</th>\n", " <th>YrSold</th>\n", " <th>SaleType</th>\n", " <th>SaleCondition</th>\n", " <th>SalePrice</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>0</th>\n", " <td>1</td>\n", " <td>60</td>\n", " <td>RL</td>\n", " <td>65.0</td>\n", " <td>8450</td>\n", " <td>Pave</td>\n", " <td>NaN</td>\n", " <td>Reg</td>\n", " <td>Lvl</td>\n", " <td>AllPub</td>\n", " <td>...</td>\n", " <td>0</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>0</td>\n", " <td>2</td>\n", " <td>2008</td>\n", " <td>WD</td>\n", " <td>Normal</td>\n", " <td>208500</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>2</td>\n", " <td>20</td>\n", " <td>RL</td>\n", " <td>80.0</td>\n", " <td>9600</td>\n", " <td>Pave</td>\n", " <td>NaN</td>\n", " <td>Reg</td>\n", " <td>Lvl</td>\n", " <td>AllPub</td>\n", " <td>...</td>\n", " <td>0</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>0</td>\n", " <td>5</td>\n", " <td>2007</td>\n", " <td>WD</td>\n", " <td>Normal</td>\n", " <td>181500</td>\n", " </tr>\n", " <tr>\n", " <th>2</th>\n", " <td>3</td>\n", " <td>60</td>\n", " <td>RL</td>\n", " <td>68.0</td>\n", " <td>11250</td>\n", " <td>Pave</td>\n", " <td>NaN</td>\n", " <td>IR1</td>\n", " <td>Lvl</td>\n", " <td>AllPub</td>\n", " <td>...</td>\n", " <td>0</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>0</td>\n", " <td>9</td>\n", " <td>2008</td>\n", " <td>WD</td>\n", " <td>Normal</td>\n", " <td>223500</td>\n", " </tr>\n", " <tr>\n", " <th>3</th>\n", " <td>4</td>\n", " <td>70</td>\n", " <td>RL</td>\n", " <td>60.0</td>\n", " <td>9550</td>\n", " <td>Pave</td>\n", " <td>NaN</td>\n", " <td>IR1</td>\n", " <td>Lvl</td>\n", " <td>AllPub</td>\n", " <td>...</td>\n", " <td>0</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>0</td>\n", " <td>2</td>\n", " <td>2006</td>\n", " <td>WD</td>\n", " <td>Abnorml</td>\n", " <td>140000</td>\n", " </tr>\n", " <tr>\n", " <th>4</th>\n", " <td>5</td>\n", " <td>60</td>\n", " <td>RL</td>\n", " <td>84.0</td>\n", " <td>14260</td>\n", " <td>Pave</td>\n", " <td>NaN</td>\n", " <td>IR1</td>\n", " <td>Lvl</td>\n", " <td>AllPub</td>\n", " <td>...</td>\n", " <td>0</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>0</td>\n", " <td>12</td>\n", " <td>2008</td>\n", " <td>WD</td>\n", " <td>Normal</td>\n", " <td>250000</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "<p>5 rows × 81 columns</p>\n", "</div>" ], "text/plain": [ " Id MSSubClass MSZoning LotFrontage LotArea Street Alley LotShape \\\n", "0 1 60 RL 65.0 8450 Pave NaN Reg \n", "1 2 20 RL 80.0 9600 Pave NaN Reg \n", "2 3 60 RL 68.0 11250 Pave NaN IR1 \n", "3 4 70 RL 60.0 9550 Pave NaN IR1 \n", "4 5 60 RL 84.0 14260 Pave NaN IR1 \n", "\n", " LandContour Utilities ... PoolArea PoolQC Fence MiscFeature MiscVal MoSold \\\n", "0 Lvl AllPub ... 0 NaN NaN NaN 0 2 \n", "1 Lvl AllPub ... 0 NaN NaN NaN 0 5 \n", "2 Lvl AllPub ... 0 NaN NaN NaN 0 9 \n", "3 Lvl AllPub ... 0 NaN NaN NaN 0 2 \n", "4 Lvl AllPub ... 0 NaN NaN NaN 0 12 \n", "\n", " YrSold SaleType SaleCondition SalePrice \n", "0 2008 WD Normal 208500 \n", "1 2007 WD Normal 181500 \n", "2 2008 WD Normal 223500 \n", "3 2006 WD Abnorml 140000 \n", "4 2008 WD Normal 250000 \n", "\n", "[5 rows x 81 columns]" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "train_data.head()" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:54:51.585344Z", "iopub.status.busy": "2021-02-26T23:54:51.584348Z", "iopub.status.idle": "2021-02-26T23:54:51.616375Z", "shell.execute_reply": "2021-02-26T23:54:51.616893Z" }, "papermill": { "duration": 0.053717, "end_time": "2021-02-26T23:54:51.617097", "exception": false, "start_time": "2021-02-26T23:54:51.563380", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "<class 'pandas.core.frame.DataFrame'>\n", "RangeIndex: 1460 entries, 0 to 1459\n", "Data columns (total 81 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 Id 1460 non-null int64 \n", " 1 MSSubClass 1460 non-null int64 \n", " 2 MSZoning 1460 non-null object \n", " 3 LotFrontage 1201 non-null float64\n", " 4 LotArea 1460 non-null int64 \n", " 5 Street 1460 non-null object \n", " 6 Alley 91 non-null object \n", " 7 LotShape 1460 non-null object \n", " 8 LandContour 1460 non-null object \n", " 9 Utilities 1460 non-null object \n", " 10 LotConfig 1460 non-null object \n", " 11 LandSlope 1460 non-null object \n", " 12 Neighborhood 1460 non-null object \n", " 13 Condition1 1460 non-null object \n", " 14 Condition2 1460 non-null object \n", " 15 BldgType 1460 non-null object \n", " 16 HouseStyle 1460 non-null object \n", " 17 OverallQual 1460 non-null int64 \n", " 18 OverallCond 1460 non-null int64 \n", " 19 YearBuilt 1460 non-null int64 \n", " 20 YearRemodAdd 1460 non-null int64 \n", " 21 RoofStyle 1460 non-null object \n", " 22 RoofMatl 1460 non-null object \n", " 23 Exterior1st 1460 non-null object \n", " 24 Exterior2nd 1460 non-null object \n", " 25 MasVnrType 1452 non-null object \n", " 26 MasVnrArea 1452 non-null float64\n", " 27 ExterQual 1460 non-null object \n", " 28 ExterCond 1460 non-null object \n", " 29 Foundation 1460 non-null object \n", " 30 BsmtQual 1423 non-null object \n", " 31 BsmtCond 1423 non-null object \n", " 32 BsmtExposure 1422 non-null object \n", " 33 BsmtFinType1 1423 non-null object \n", " 34 BsmtFinSF1 1460 non-null int64 \n", " 35 BsmtFinType2 1422 non-null object \n", " 36 BsmtFinSF2 1460 non-null int64 \n", " 37 BsmtUnfSF 1460 non-null int64 \n", " 38 TotalBsmtSF 1460 non-null int64 \n", " 39 Heating 1460 non-null object \n", " 40 HeatingQC 1460 non-null object \n", " 41 CentralAir 1460 non-null object \n", " 42 Electrical 1459 non-null object \n", " 43 1stFlrSF 1460 non-null int64 \n", " 44 2ndFlrSF 1460 non-null int64 \n", " 45 LowQualFinSF 1460 non-null int64 \n", " 46 GrLivArea 1460 non-null int64 \n", " 47 BsmtFullBath 1460 non-null int64 \n", " 48 BsmtHalfBath 1460 non-null int64 \n", " 49 FullBath 1460 non-null int64 \n", " 50 HalfBath 1460 non-null int64 \n", " 51 BedroomAbvGr 1460 non-null int64 \n", " 52 KitchenAbvGr 1460 non-null int64 \n", " 53 KitchenQual 1460 non-null object \n", " 54 TotRmsAbvGrd 1460 non-null int64 \n", " 55 Functional 1460 non-null object \n", " 56 Fireplaces 1460 non-null int64 \n", " 57 FireplaceQu 770 non-null object \n", " 58 GarageType 1379 non-null object \n", " 59 GarageYrBlt 1379 non-null float64\n", " 60 GarageFinish 1379 non-null object \n", " 61 GarageCars 1460 non-null int64 \n", " 62 GarageArea 1460 non-null int64 \n", " 63 GarageQual 1379 non-null object \n", " 64 GarageCond 1379 non-null object \n", " 65 PavedDrive 1460 non-null object \n", " 66 WoodDeckSF 1460 non-null int64 \n", " 67 OpenPorchSF 1460 non-null int64 \n", " 68 EnclosedPorch 1460 non-null int64 \n", " 69 3SsnPorch 1460 non-null int64 \n", " 70 ScreenPorch 1460 non-null int64 \n", " 71 PoolArea 1460 non-null int64 \n", " 72 PoolQC 7 non-null object \n", " 73 Fence 281 non-null object \n", " 74 MiscFeature 54 non-null object \n", " 75 MiscVal 1460 non-null int64 \n", " 76 MoSold 1460 non-null int64 \n", " 77 YrSold 1460 non-null int64 \n", " 78 SaleType 1460 non-null object \n", " 79 SaleCondition 1460 non-null object \n", " 80 SalePrice 1460 non-null int64 \n", "dtypes: float64(3), int64(35), object(43)\n", "memory usage: 924.0+ KB\n" ] } ], "source": [ "train_data.info()" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:54:51.657541Z", "iopub.status.busy": "2021-02-26T23:54:51.656847Z", "iopub.status.idle": "2021-02-26T23:54:51.667781Z", "shell.execute_reply": "2021-02-26T23:54:51.668262Z" }, "papermill": { "duration": 0.03284, "end_time": "2021-02-26T23:54:51.668467", "exception": false, "start_time": "2021-02-26T23:54:51.635627", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "count 1460.000000\n", "mean 180921.195890\n", "std 79442.502883\n", "min 34900.000000\n", "25% 129975.000000\n", "50% 163000.000000\n", "75% 214000.000000\n", "max 755000.000000\n", "Name: SalePrice, dtype: float64\n" ] } ], "source": [ "print(train_data['SalePrice'].describe())" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:54:51.710692Z", "iopub.status.busy": "2021-02-26T23:54:51.709996Z", "iopub.status.idle": "2021-02-26T23:54:52.045040Z", "shell.execute_reply": "2021-02-26T23:54:52.045594Z" }, "papermill": { "duration": 0.358432, "end_time": "2021-02-26T23:54:52.045779", "exception": false, "start_time": "2021-02-26T23:54:51.687347", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/opt/conda/lib/python3.7/site-packages/seaborn/distributions.py:2557: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", " warnings.warn(msg, FutureWarning)\n" ] }, { "data": { "text/plain": [ "<AxesSubplot:xlabel='SalePrice', ylabel='Density'>" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sns.distplot(train_data['SalePrice'])" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:54:52.093192Z", "iopub.status.busy": "2021-02-26T23:54:52.091961Z", "iopub.status.idle": "2021-02-26T23:54:52.098041Z", "shell.execute_reply": "2021-02-26T23:54:52.097392Z" }, "papermill": { "duration": 0.031958, "end_time": "2021-02-26T23:54:52.098197", "exception": false, "start_time": "2021-02-26T23:54:52.066239", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Skewness: 1.8828757597682129\n", "Kurtosis: 6.536281860064529\n" ] } ], "source": [ "print(f\"Skewness: {train_data['SalePrice'].skew()}\")\n", "print(f\"Kurtosis: {train_data['SalePrice'].kurt()}\")" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:54:52.156348Z", "iopub.status.busy": "2021-02-26T23:54:52.145321Z", "iopub.status.idle": "2021-02-26T23:54:52.485768Z", "shell.execute_reply": "2021-02-26T23:54:52.485135Z" }, "papermill": { "duration": 0.366798, "end_time": "2021-02-26T23:54:52.485923", "exception": false, "start_time": "2021-02-26T23:54:52.119125", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/opt/conda/lib/python3.7/site-packages/seaborn/distributions.py:2557: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).\n", " warnings.warn(msg, FutureWarning)\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "from scipy.stats import norm, skew\n", "train_data['SalePrice'] = np.log1p(train_data['SalePrice'])\n", "sns.distplot(train_data['SalePrice'], fit = norm);" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:54:52.536477Z", "iopub.status.busy": "2021-02-26T23:54:52.535763Z", "iopub.status.idle": "2021-02-26T23:54:53.722356Z", "shell.execute_reply": "2021-02-26T23:54:53.722929Z" }, "papermill": { "duration": 1.21458, "end_time": "2021-02-26T23:54:53.723120", "exception": false, "start_time": "2021-02-26T23:54:52.508540", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "<AxesSubplot:>" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 864x648 with 2 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "corrmat = train_data.corr()\n", "f,ax = plt.subplots(figsize=(12,9))\n", "sns.heatmap(corrmat, vmax=0.8, square = True)" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:54:53.780421Z", "iopub.status.busy": "2021-02-26T23:54:53.779509Z", "iopub.status.idle": "2021-02-26T23:54:54.947273Z", "shell.execute_reply": "2021-02-26T23:54:54.947840Z" }, "papermill": { "duration": 1.19983, "end_time": "2021-02-26T23:54:54.948167", "exception": false, "start_time": "2021-02-26T23:54:53.748337", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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4ixUS5ktSqapYSvJJgkPtzw1vH0+8vGzHqUPnepjNFk4UnVO39G3Jt9Mf4tNvhuDrV4XIaOe72Svi+QQQFliFhLRTJXml5xIaUMUuZvuBDMZ+sIrYUX8zb008E6ZuZMG6Y3Yxvt7utG0YStxm58cbhYcFkJhQ+jw//7EyF9rOc7A/Vj26u+5YnRYSVpXkxJJzPiXpJMEhPmfE+NKuQx2qVHHHP8CLZq2i+W+Pa6/PYeF+JCXaH6dzXju7NCy6dmYTFuZPWJgfTZvVBKBHz2bs2hnvdE4n8jMIKFVRC/AI4ETBCbuYDhEd2ZSyEYCUXFv3abiXbRyuQRl5sPHDrE1aXRwjrrwr0WDbAbQuPUMp5QtEAeuANKVUU2AQMO10CNBPa9286Cdaa316wErpUaJ3ASFAK611cyAJW+PugnMBWmGrsgGYKTomRWPv3C9xP2itv9Bat9Zat6Zh6LlCK6RGjaM4ciSVY/FpFBaYmTt7M127NbKLSU05WVxd2r71CNqq8S81FmrObNd2hwI0aVKDw4eSiT+aSkGBmdn/rCM2tqldTEpKZnFeW7cetOUV4M2pU/nFg/pPncpnxYpd1Ktb3fmcGtfg0OEUjsbbcvrn343Edjszp5OlcjqE1aoJ8PfmibG3sWzxayxaMIHJ7z5A+3b1mPT2fc7nVD+Mw/EniE/IpKDQwuxFe4ntUNsuZuG0B1g0fQiLpg+hZ5cYxo/uRvfOdYgIrcqWnYnk5hWitWbVxqPUruF84+iaRtWIP5LG8fgMCgvNLJiznU5d6tvFpKVmFR+nndvi0VaNX9E5lZ5m++BPTDjBkoW76HGjfVfupaiI5xNAkzqBHE7MJj45mwKzhdkrjxDbyn5w/8KPbmLRlJtZNOVmeraLZPyQlnRvU530k3mczLENVM8rMLNqWxK1q/mWtZuLy6lJDQ4dTi45z2ef/1hZte08L+tY1a3nmmN1WoNG1Yg/ks7xYycoLLSwcO5OOnWpZxfTqWs9tmw6itlsJS+3kJ3bjlOjtgura0CjxtEcPpxKfNG1c86/m+jazf6mq9LXzm1bD2O1avz9vQkO8SUsPICDB5MAWLN6L7XrnLM2cEEOZR0i1CuMIM9gjMpI69C2bEndYheTnpdOg0DbnchV3XwJ8wonJS8FgHsb3EfiqQQWHJ3vdC6X09U+hu1KdIkuBN5USt2rtf5eKWUE3sU2luyUUmoatnFkflrr0yMz5wKPKqUe1VprpVQLrfWmMrbtByRrrQuVUt2A8w20+RhYo5T6TWu9WSkVhO3mh9P9eIewNeBmALcBbpe4H5f7acgEutZrSbCPP0cnzuKlv79k6sq/Ltv+TCYjTz/fh5EjvsRq1dzWpw11YsL5ZfpKAAYM6sCCeVv5ZfoqjEYDnp5uvDHp7uIuktzcAtas3MsLL/VzeV4vjh/E0GEfYrVY6devA3XrVmPaz8sAGHzHdcydu5FpPy8rysuddycPQylFWtpJRj3yGWDrGrn55jZ0vq7RuXZ3wTmNf34gw4Z/jMWq6denPXXrRvDzNNs4nTsGd2buvE38PC0Oo8mIp4cbk999wKE7yZVMJgMvPt6VoU/+gdWq6XdjQ+rWCmLan7YxO4Nva3rWdZs1DKdnlxj6Dv8Zk9HANXVDGHSz83f5mkxGxj7bmzEP/4DFqrn59hbUjgnl9xnrAOgzsA2L5+/k9xnrMZoMeHiYmPBW/+Lj9PwTM8jMPIXJZGTcczfh61vlXLu74Jwq2vkEYDIaePGBlgyduMz29+tWi7pRfkybv9+WV4+Ys66bkpHHM5+uxWLVaKum17VRdDujsXdJOZmMjH9xEMOGfojFWnKsfp5mO1Z3DLYdq5+nlRyrye+WHKtHRtkfq+s6u+ZYleRnYMwzN/DEwz9jtVq56bZm1IoJ4Y9fbCNybh/Qipq1g2nXoTb3D/wSg1Lc3Kc5tWNc+4XaZDLy3PP9eHj4Z7axhH3aEVM3ghnTVgAwcHBH5s/bwoxpK4rOczfefve+4vP82ef78uxTP1JYaCYyMohXX7/T6Zys2sq0vT/xePPRGJSBFcdXkJBznOuqdQFg2fGl/HPoL+5vOITxbV8GFL/vn0lOYTZ1/GK4NqID8dnxvNDG9pSCPw78zva0C7uRQriOuhLDsJRSUcAnQANsFazZwDitdb5SKgw4BryqtX6lKL4K8D7QAVu17ZDW+mal1P1Aa631qKK4YOAvbA2rzdju+rxRa33oHI/1uA6YhK0RVhO4X2v9c9GyMODPohwXAo8WbeO8+znn63+4fYUb65bz0fPlnYKDKqbL/nSUi6Ys5vJOoUw6eV95p+AgPaDi3TkW6Bl+/qArbdOi8s7AgWoee/6gcpCcd7S8U3Dg5x5y/qAr7LGlM8s7hTJ9HvvVFS1FVX25+xX7rM16ecEVL7Ndkeewaa2PArecZVnSmXlorXOBB8uI/Rb4ttR0KrabEMrark/Rv4eAxqXmLwPaAiilHgGeU0rN0VpnFOXSvtRmnr3Q/QghhBBCXC7/r/+ng6IH5l7yQ3OFEEIIUTFczmEmFYH8X6JCCCGEEBXc/+sKmxBCCCGuDvIcNiGEEEIIUa6kwSaEEEIIUcFJl6gQQgghKj3pEhVCCCGEEOVKKmxCCCGEqPSkwiaEEEIIIcqVVNiEEEIIUelJhU0IIYQQQpQrqbAJIYQQotKTCpsQQgghhChXUmETQgghRKUnFTYhhBBCCFGupMImhBBCiEpPKmxCCCGEEKJcSYXtCsj56PnyTsGB96Ovl3cKDlLfe7y8U3AQsHxleadQptx/dpd3Cg4yVieUdwoOAn8dUd4pOPi55YzyTsHB/HnHyzuFMn0TO7i8U3CgU/4r7xQcvNXxhvJOoUKQCpsQQgghhChXUmETQgghRKWnlFTYhBBCCCFEOZIGmxBCCCFEBSddokIIIYSo9OSmAyGEEEIIUa6kwiaEEEKISk8qbEIIIYQQolxJhU0IIYQQlZ5U2IQQQgghRLmSCpsQQgghKj3DVV6CuspfnhBCCCFE5ScVNiGEEEJUekb5r6mEEEIIIUR5kgqbEEIIISo9o9wlKoQQQgghypNU2IQQQghR6V3tY9ikwVZBrIjbzTtv/onVYuX2fu0YMjzWbvn6tfsZ8+i3VKseCEBs98Y8OLInhw4m8/QTPxbHHYtP4+FRN3DXvddd9py/vud5bm7SkeSsDJq8etdl399pq1fs4/235mCxWrmlT0vuHdrZbvnGdQd5evQ0qlX3B6BL7DUMeagrANP/t5pZMzeAhlv7tWTQ3de6JKe4HalM/HU3Vqumf8dIhvesZbd84ZZkPvx7PwalMBoVz/arT6uYAAC+X3yYX1bEozUM6BjJfbE1XJKTsUFr3PuMBGXAvOZfChdOt1/eMhb36wcBoPNzKfj1Q6zHDwBg6tIXt/Y3gtZYEw6R//M7YC50SV6nebXvSPDoZ8Bo5OSsmZz44Wu75T49byLgnqEAWHNPkfL2qxTs3+PSHADi1h7m9SnLsVqt9O/dkBF3tiozbtvuJAaNmsnkF3vSq0sMB45kMPbVucXLjyac5LH723Ff/2aXlEfEDZ1p9cHzKKOB/776hZ1vfekQ0+qD56nWuwvmU3msvv8ZMjbtBKD+Y/dSZ/gAUIr/vvyFPR98V7xOvVF3U2/U3VjNZo7/s5TNT79zSfkBNA5qzJ3178CgFMuOxTH70L92y6uYqjCi8TACPYMwKgNzDs9l+fEVmAwmnm39NCaDG0ZlYH3SBv448Ocl51HasridvP7Gr1gtVgb078CI4T3tlq9Zu5eRo74gsnoQAD16NGfUyBuLl1ssVvoNeJuwMD8+//Rhl+QUt+YQr3+0xHZO3dSYEXe1LTNu265EBo2cxuSXetOraz0Avp2xkV//2YZSirq1gnnjmZ54eDj/Ub1q+V4mvzUbq9XKrX1bcd/QLnbLN6w7wJOP/49q1W3Xpa7XN2TYQ7bPoWk/ruTPmevRwG19W3PHPR2czkdcvArbYFNKKSAOeF1r/W/RvIHAEK11Lye2awG2AQqwAKO01ivPs85XwGSt9U6l1CGgNWAG7tRaf3KpuZxmsVh58/Xf+fTLEYSF+XHXoA/o0q0hdWLC7eJatKrFh58MtZtXs1Yo038bW7ydG7q9SrfujZ1N6YJ8u+ofpiz5le/vH39F9ge21zhp4mw++PweQsN8GXrnl3TuWp9adULt4pq1iGbSFPtG5H/7kpg1cwNf/284JjcjY0f+SIfO9YiqEeRcTlbNqzN28fWjrQjz92Tg26vp1iSEmAif4pj29QOJbXotSin2HMtizNdbmD2+E3uPZ/HLinhmPNUeN6Ni+Mcb6dI4mJqh3k7lhDLg3u9R8j57Gn0iFc8xUzBvX4VOOlIcotMTyZ3yBORmY2zQBveBo8l7/zGUXxBunW8n961hUFiAx30vYGrRDfO6ec7lVJrBQMgTL3Ds8eGYkxOJmjqdnLjFFB46UBxiTjjGsZH3Y806iVf7ToQ+8xLxw+50XQ7YzqcJHyxj6ju3Ehbiw4CHfyG2Qy1iagY6xE36YhWdWkcVz6sdHcAfXw4uXt5l4Ld072TfUL9QymCg9cfjWdTjAXLjk7hh3a/Ez1rEyV3/FcdUu/E6qtatyV91exLUrhltPn2Zee0H4teoLnWGD2Bu2wFYCwrpNucrjv+zhKz9hwnt2o7I265ndtNbsBYU4hESeI4szpMjinsa3MWkje+SnpfB+HYvsjllM8dzEopjYiO7cTw7gQ82f0RVNx8mdpzIqoTVmK1m3t4wiXxLPkZl5Nk2z7A1bRsHMg+cY4/nZ7FYmfDaDL75ahRhYf70H/QOsd2aEBMTYRfXulWdszbGvv9hMXXqhJGdnedULnY5vb+Iqe/2JSykKgMe/InYjnWIqRnkEDfp8+V0alPyBS0pJZsfZm7in+/vw9PDxOiX/uafRXvoe2Mjp3N6Z+JffPTFA4SG+XL/HZ/Rues11D7jutm8ZU0mT7nHbt5/+5L4c+Z6vvnpIUxuRkY//B0dr6tHdI1gp3K6HIxX+SCvCvvytNYaeAiYrJTyVEp5A68Dj1zK9pRSxqJfc7XWzbXWzYBngTcuIJdhWuudZ8z2B0ZeSi5n2r7tCFFRQURGBeHmbuKG3s1ZsnjHRW9n7ep9REYFUa3apV+UL0bc/s2k55y8Ivs6bef2Y0RGBVI9MhA3NxPdezUmbsmFVV0OH0ylcdNIPKu4YzIZadGqJksX7XI6p62HMokO8SIq2At3k4HercJZtDXZLsbb04QqKtefyregsP1+IDGHZrX8qeJuxGQ00KZuAAu2JDvs42IZoutjTT2OTksEixnLpiWYGtt/K7Ye2gm52QBYDu9C+YWU2oAR3DxsT6J080CfTHM6p9I8GzahMP4I5uPxYDaTveBffK6zryrnbduMNct2fuXt2IopNMylOQBs3Z1MdHU/oqr54e5mpHdsXRauPOgQ9+Pv2+h5XR0CA7zK3M6qjfFEVfOjerjvJeUR1LYp2fsPk3MwHmthIYen/UPkbdfbxVS/7XoOfv8HAGlrtuDu74tneAi+19QhdfUWLLl5aIuF5KXriOzTA4C6D9/Bjje/wFpgq47mp6RfUn4Atf1qk3wqmZTcVCzawtrEtbQIaeEQ52nyBMDD6ElOYTZWbbXt25IPgFEZMSkjaH3JuZy2ddshakQHExUVjLu7iZtubMnCRVsveP3ExAyWLN1B/36uqxht3ZVIdHV/oqr5F51T9Vm4/D+HuB9/20zPLjEO55TFYiUv34zZbCU330xosI/Duhdr5/Z4IqODiq+bPXo1YdniC7v2HTqYQuOmUSXXzda1WLrQ+eumuHgVtsEGoLXeDvwFPA28BPwIPK+UWqeU2qSUug1AKVVTKRWnlNpY9NOhaH5XpdRipdRP2KpqZ/IFMkrF/n16gVJqilLq/qLflyilWp+x7ptAHaXUZqXUpfcxAMlJmYRF+BdPh4X5k5KU6RC3dfNhBvZ5l0ce/JL/9ic6LJ/772Z69W7uTCoVXkryScJKfSiGhPqSkuTYaNy+NZ57B3zK2JE/cmC/rQFUOyaUzRsOk3niFHm5Baxcvo/kROcbnMkn8ggP8CyeDvP3JOlEvkPc/M1J9J6wnIc/3chrd9u+Mdet5sP6/RlkZBeQW2Bh2Y5UEjOc/6av/IPRJ1KKp3VmKsrv7N+ITe16Ydm9rig2jcIlv+I1/n94vTId8nKw7NngdE6lGUNCKUwuOYfNyUkYQ0LPGu97S19yVi13aQ4ASanZRISWfCCGB/uQlJJjH5OSzfzlBxh8y9mrHLMX7+Om2LqXnEeV6mHkHC05Hqfik/Cqbt9A9aoexim7mES8qoeRuX0vode1xj3QH2MVT6r1vg6vKFt13rdeTUI7t6bn6hlcv+QHAls3ueQcAzz8Sc8vafCl52cQ4OFvF7Pw6CIivCN477p3efXaV/hpzzQ0toaZQvFK+5f4oMt77EjbyYGTjg3ji5WUlEl4eEDxdFh4AEnJjtfOzZsPcmufNxg24hP27SupCE58cyZPjrsdgwvvLrSdU1WLp8NDfEhKzbaPSclmftx+Bt/a1G5+WIgPQwa3InbgV3Tu+wVVvT3sKnCXKjnpJGFhfsXToWG+pCQ7Xvu2bTnCXf2nMPrh7ziwPwmwXTc3bTxUct2M20tSGZ9P4vKrsF2ipbwCbAQKgL+BRVrrIUopf2CtUmoBkAz00FrnKaXqAj9j67YEaAs01lqfvjpUUUptBjyBCMD+a/2Fe6Zou80vcf1zO2PwZIOGkcye/zxe3h7ELdvFmEe/Zda/zxQvLywws3TxDh4d3fuypFNhlPGlXJ1xrOpfE8Fvc0bj5eXByri9PDNmGjP+eoyatUO4+4FOPP7g91TxcqduvTCMJue/s5RVJyhr7GuP5mH0aB7Gun3pfPj3fr55rDV1wn0Y1qMmQ6dswMvdSIPqVV10a3pZ2yi7omGIaYZb+xvJ/XC0bUYVH0yNr+XUq/dAbjYe97+IsdX1WDYsdEFep9MrI7+zVFyqtGyD7y19iX/wnjKXO6XM88l+euLHyxk34lqMZ+lvKSi0sGjlIcYOc2I8ZBnHQ595PM4Sc3L3AXa+9RWx86dizj5FxpY9aLPFtorJiHuAL/PaDySoTRM6zXifWbWvd9jOBSbpuP8zphsHNeJI1hHe3vAOoVVCGddqLONX7SXPkodG89LqV6hiqsKjzUZR3bs6x3KOXWIuRfsv45w5M8tGDaNYtOBVvL09WLp0B488+gXz5rzE4iXbCAysSuNG0axZu9epPOyTcpylzshq4kdLGPdgZ4dzKjMrj4XLD7Bg2hCq+ngw+qV/mDVvF7f2vMZ1+Z3OyeG6WY0/547Dy8uDFXF7eHL0T8z8ewy1aody7wOdeXTEN7brZv3ws74XytvVftNBxTzqpWitc4DpwA9AD+CZogbXEmyNrmjADfhSKbUN+AVoWGoTa0s11qCkS7QB0Av4Xp155rqAUmqEUmq9Umr91C/nnDM2NMyPpIQTxdNJSScICbXvWvHx8cTL2wOAztddg9lsISOjpBKwfPluGjSMJCi4KlezkDBfkkpVxVKSTxIcav+avX088fKyHasOnethNls4UXSsbunbkm+nP8Sn3wzB168KkdHOdx+H+XvaVcWSTuQR6udx1vg2dQM5mnqKjOwCAPp3iOS3Z67lx7Ft8fNyo0Zo2d1uF0OfSEH5l3RxKr9gdKZjt6aKqIXHoLHkfT0eTmUBYKzXEmtaIuRkgtWCZetyjDUbOqzrDEtyEm6hJWM0TaFhWFJTHOLc69Qj9NkJJDz1KNaTrv9WHxbiQ0JySfUjMTWb0GD78YPb9yYz9tV5xN7xPfOW7mfCB8tYsLxk7FXc2sM0rBtCcOCl/91y4xPxjio5Hl6RYeQet+8aPxWfWFw5s8WEF8ccmPorc1r1ZUGXuylIP0HWvsNF6yRx9Lf5AKSt24a2WvEIDuBSZORnEOhR8n4J9AjgRP4Ju5hO1TqxIXkjAMm5yaTmphLhbT+eLNecy56MPTQJdn6sbXi4P4mJGcXTSYkZhIb62cX4+FTBu+ja2aVLI8xmC+kZ2WzceIBFi7cR2308Y5/4htVr9jLuqe9wlu2cyiqeTkwp45zak8TYCbOJHfQ185buY8J7i1gQt59V648QGeFLoL8XbiYjPTrHsGn7cadzCg3ztauKJSedJDjE/rrpU+q62bFzfSylrpu39m3N9zMe4fNvh+PrW4WoaOfG/YpLU+EbbEWsRT8K6FfU4GqutY7WWu8CxgBJQDNslTX3UuvmOGytiNZ6FRAMhGC7iaD08fAsc6ULpLX+QmvdWmvdesjwc98j0ahxFEeOpHIsPo3CAjNzZ2+mazf77pfUlJPF3ya3bz2Ctmr8/Us+IObMvvq7QwGuaVSN+CNpHI/PoLDQzII52+nUpb5dTFpqVvGx2rktHm3V+BUdq/Q024dzYsIJlizcRY8bL72L6LQmNXw5nHyK+NRTFJitzN6QSLcm9t17h5NPFee048hJCs0af283W75Ztu7T4+m5zN+SxE2t7T/gLoX16B4MIdVRgeFgNGFs0RXzjlV2Mco/BM8HXiL/f2+hU0oqHTojGWPNa2xj2ABDvRZYk4/gSnm7tuMWFY0pojqYTPh0v5GcuMV2MaawcMLffJ+kCc9SePSwS/d/WpMGoRw+lkl8wkkKCi3MXrSP2Gtr2sUs/OleFv1s++nZJYbxj19H9061i5f/s8i57lCwNaaq1q2Jd81IDG5u1Bh8E8dmLbKLOTZrEbXuvR2AoHbNKMzMIi/R1sg9fTOBV1QEkX17cuhn2+iO+D8WEBbbHoCqdWticHcjPzWDS3Hw5EFCvcII9gzGqIy0DW/LppTN9q8jL42GgbZqkK+7L+Fe4aTkplDVzYcqpioAuBncaBh4DQmlbla4VE0a1+DQ4RSOxqdSUGDmn383EtvNvpsxpdS1c+vWQ1itmgB/b54YexvLFr/GogUTmPzuA7RvV49Jb9/nfE4Nwjkcn0F8QmbRObWH2I617WIWTh/KoqKfnl3qMn5MLN07xxARVpUtOxPIzStEa82qjUeoXcP5L5XXNKrO0cNpHI9Pp7DQzPw527iuawO7mNLXzR3b4rGe9bq5k5697Y9xRWFU6or9lIfK0CVa2lzgUaXUo1prrZRqobXeBPgB8Vprq1LqPsB47s3YKKUaFMWmAYeBhkopD2yNteuBcw2ayQJcUs4ymYw8/XwfRo74EqtVc1ufNtSJCeeX6babVwcM6sCCeVv5ZfoqjEYDnp5uvDHp7uKSdm5uAWtW7uWFl/q5Ip0L9tOQCXSt15JgH3+OTpzFS39/ydSVf13WfZpMRsY+25sxD/+Axaq5+fYW1I4J5fcZtvFXfQa2YfH8nfw+Yz1GkwEPDxMT3upffKyef2IGmZmnMJmMjHvuJnx9qzifk9HACwMbMOzjjVitmr7XVqduNR+mxR0FYHDnKOZtTuLPNcdxMxrwcDcweUjT4pwe/3ILJ3IKMRkVLw68Bj8vN6dzwmqlYOYUPB98AwwGzGvmohMPY+pwMwDmlX/jdsM9KG9f3Ps/VrSOhbzJj2A9shvzljiqPPEJWC1Yj/2HeeVs53MqzWIh5d2JVHv/c5TByMm/f6fg4H/49hkIwMnfZxAw5GGMvn6EjHsBAG2xED9kkEvTMBkNvPhoZ4Y+PQurRdPvxmuoWyuIabO2AzD41nNXgXLzClmx4SivjOnqVB7aYmH9qAl0m/sVymjkwNSZZO7cT8yDtrtQ938+jeOzl1Ktdxdu2T8fy6lcVj/wXPH6nWd+hEeQP9ZCM+sfeYXCE7Yq9IGpM2k3dSK9t/2FtaCQ1fc9U+b+L4RVW/nfnv/xRMsxGJSBuOPLOZ5znK6RtsdDLIlfyl8H/2ZooyG82v4VUIpf9v1KdmE2kT6RDGs0FINSKGVgXdI6tqRe+M0BZ2MyGRn//ECGDf8Yi1XTr0976taN4OdpcQDcMbgzc+dt4udpcRhNRjw93Jj87gMO3YGuZDIZeHF0LEPH/YbVqunXuxF1awUz7c8tAAy+7eyPfWnWMIKeXerSd/j/MBkNXBMTwqBbnP9Sabve3cxjD3+H1WLllttbUTsmjN9mrAWg78C2LJq/g5kz1mI02q6br709qPg4PTP25+Lr5pPP3eKS66a4eKqsMQAVjVLqZSAb+Bh4H+iArdp2SGt9c9G4tZnAKWAx8KjW2kcp1RUYp7W+udS2Tj/Wg6JtPKe1/qdo2dvAbcA+bGPmZmmtv1VKLSnazvrTj/XQWqcW3czQFPhXa/3k2fI/Zf6rwh1k70dfL+8UHKS+93h5p+AgYPk5n/hSbnL/2V3eKThIWO18xcTV6vw6orxTcPBz5MflnYKD+fM6lXcKZfomdnB5p+BApzje8VneMgMqZhelv8eAK1qKavHjoCv2Wbvp7ulXvMxWKSpsWuuXS00+WMbyfdgaTqc9WzR/CbaxbqVjz1p901o/BTxVxvyupX6vWep31z4USgghhBCiDJWiwSaEEEIIcS7Gq/sm0Upz04EQQgghxP9bUmETQgghRKXnmmdYVlxSYRNCCCGEqOCkwiaEEEKISk/+pwMhhBBCCFGupMImhBBCiEpPxrAJIYQQQohyJRU2IYQQQlR68hw2IYQQQghRrqTBJoQQQghRwUmXqBBCCCEqPbnpQAghhBBClCupsAkhhBCi0pMH5wohhBBCiHIlFTYhhBBCVHpSYRNCCCGEEOVKKmxXQBWTT3mn4CD1vcfLOwUHwWM+KO8UHOT4BZR3CmXKOppV3ik4qNY5srxTcHTyZHln4KB1a2N5p+CgZesG5Z1CmfTmpeWdggN9LLG8U3DgeVOf8k6hQjBe5SWoq/zlCSGEEEJUflJhE0IIIUSlJ2PYhBBCCCFEuZIKmxBCCCEqPfmfDoQQQgghRLmSCpsQQgghKj0ZwyaEEEIIIcqVVNiEEEIIUenJc9iEEEIIIUS5kgqbEEIIISo9GcMmhBBCCCHKlTTYhBBCCCEqOOkSFUIIIUSlJw/OFUIIIYQQ5UoqbEIIIYSo9OSmAyGEEEIIUa6kwiaEEEKISu9qf3CuNNgqiLhlO3j99RlYrVb6D+jIiBG97JavWbOHR0Z+SmRkMAA9erTgkVE3ARAb+xze3p4YDQaMRgMzf3vOJTmtXrGP99+ag8Vq5ZY+Lbl3aGe75RvXHeTp0dOoVt0fgC6x1zDkoa4ATP/fambN3AAabu3XkkF3X+uSnM7n63ue5+YmHUnOyqDJq3ddkX0CGOq1wv2Wh0AZMK+bg3npL3bLjc274dZlAAC6IJeCP6agEw4CYOp4G6Y2vUApzGvnYF7xh0tycm/eHt8HxoDBQO7CWeT88YPdcs/ON+B9+z22nPJOcfKLtzEf3l/qRRkIeusbLOkpnHhjnEtyMtRrhfttD9uO09o5mJfMsFtubNENt64DbTnl51Lw+0f2x6ndjYDCvPZfzMv/cElOcRuP8fpX67FaNf17xDCiX+My47btS2XQ03OYPK4zvTrUKJ5vsVjpP242oUFefP5CrEtyAvC6thOhTzwLBiOZf/5Kxndf2S13q1GL8PGv49GgIWmffkDGj98UL/MffDd+tw8Apcj84xdO/PzDmZu/JBtXHeXL91ZjtWp63Fqf/vc2c4jZtuE4X7+/GrPZiq+/JxM/vbl4mcVi5YkH/iQoxIsX373BJTnFbUnk9e832f5+3Woz4tYGZcZt+y+dQeMXMvmxa+nVLpKEtFM8/elaUk/kYVCKgbG1uffGuq7JaXc6E2cdsOXUNpzhsVF2yxduT+PDuYcwKIXRqHj21tq0quXHweRTjP1xd3Hc0fQ8Hr2hBvd1ru50TividvHWG39gtVjp0789Q4dfb7d83dr9jB41lerVAwGI7dGEh0bewKGDyTw19vviuPj4NEY+2ou77+3idE7i4pyzwaaUUkAc8LrW+t+ieQOBIVrrXuda9zzbtQDbivZ/ELhHa33iUrd3kfu+H2ittR5Vat4WYKfW+o6zrNMVGKe1vrmMZYeKtpd6qTlZLFYmTPiZqd88TlhYAAP6v0FsbFNiYqrZxbVqXZfPP3+kzG18/91YAgJ9LjWFMnOaNHE2H3x+D6Fhvgy980s6d61PrTqhdnHNWkQzaYp9w+i/fUnMmrmBr/83HJObkbEjf6RD53pE1QhyWX5n8+2qf5iy5Fe+v3/8Zd9XMWXA/bZHyP/6OXRmKp6jPsCyaw06+UhxiE5PJO+LpyA3G0O91rj3eYz8T8agwmpgatOLvI9Hg6UQjwdew7J7LTrtuHM5GQz4DhtHxoTHsKQnE/TmN+Stj8MSf6g4xJJ8nPTxD6NzsnBvcS2+Dz1L+rNDi5d79R6EOf4QysvbuVxOUwbc+zxC/pdFx+nRD7HsXO14nD570nac6rfGvd/j5E8ZbTtO7W4k76PHbcdp6Ou245Tq3HGyWKxM+HwtU1/pTliQFwOe/JfYtpHERPk7xE36fiOdmkc4bOP7v3dTO9KP7NxCp3KxYzAQ+tQLHBs1jMKkJGp8N52cZYspOPhfcYj1ZCbJ707Ep4v9B697nRj8bh/AkfsGoc2FVP/wC3KWL6Pw6GGnUrJYrHw+aSWvfHgjQaHejHvgT9p2jia6VkBxTHZWPp+9s5KX3+9FSLgPJ9Jz7bbx9/QdRNX051ROgVO5FOdk1Uz4ZiNTn73O9vd7YQGxLasRE+nrEDfp5610ahpePM9oUDx9VzMa1QogO7eQfs8voEOTMId1LyWnV3//j69HNCbMz4OBH26mW6NAYsJK3kft6/oT26glSin2HM9hzI+7mP1Ua2qFevH72JbF2+n66hq6N3b+ummxWJn42m98/tVDhIX5ceeg9+jarRF1YsLt4lq0qs2UT4fZzatZK5QZv48r3k6Prq8Qe30Tp3O6HP5fj2HTWmvgIWCyUspTKeUNvA6U3Wo4D6WUsejXXK11c611YyD9UrfnCkqpa7Adh+uKXt8Vt3XrIaJrhBIVFYK7u4neN7Vh4cKt5ZFKsZ3bjxEZFUj1yEDc3Ex079WYuCV7LmjdwwdTadw0Es8q7phMRlq0qsnSRbsuc8Y2cfs3k55z8ors6zRDVD102nF0eiJYzJi3LMXYsL1djPXILsjNtv1+dDfKz1YpNYRGYT26GwrzwWrFcnAbxkYdnM7JLaYhlsR4LMnHwWwmb8V8PNtcZxdTuGcbOifL9vve7RgDQ0peU2AIHq06kLtwltO5FG8zqj46NcH+ODWyr7xaD5c6TkdKH6dorEdKHacDrjlOW/elER1Rlajwqri7GendqQYL1xx1iPvxnz30vLYGgX6edvMTU3NYuv4YA3rEOJ1LaZ6NmlB49AiFx+LBXMjJ+f/i3cW+emfJSCd/53Ywm+3mu9esQ962Lej8PLBYyN24Dp+u9o26S7FvZwrhkb6EV/fFzc1I5x61WbvMvhG4bO5/XNu1JiHhti+P/oFVipelJuewfuVRetxa3+lcTtu6P53oMB+iwnxwNxnofW0UCzccc4j7ce4+eraNJNDPo3heaEAVGhU1Nn2quFGnui9JGbkO6150TkeyiA72JCqoii2n5iEs2pFuF+PtYUQVNS5OFVgoq52xet8JooKqUD3A03HhRdq+7QhR0cFERgXh5m6i140tWLJo+0VvZ83qfURFB1GtqAonrqzz9vhqrbcDfwFPAy8BPwLPK6XWKaU2KaVuA1BK1VRKxSmlNhb9dCia31UptVgp9RO2qtqZVgHVi2LrKKXmKKU2FG2rQdH8b5VSnxZt54BSqotSaqpSapdS6tvTG1JK3aGU2qaU2q6UeqvU/AeUUnuVUkuBjmfs/07gB2AecGupdXoppXYrpZYDfUvND1JKzSt67Z8DTjfpk5IyiAgv+ZYaHuZPUlKGQ9zmzQe47dZXGT7sI/btK6ksKBRDh35A374TmT49ztl0AEhJPklYeMk3zZBQX1KSHBtC27fGc++ATxk78kcO7E8GoHZMKJs3HCbzxCnycgtYuXwfyYlXthF1JSnfYHRmSvG0zkxF+Z79W7Gp9Q1Y964HwJp4GEPNxuBVFdw8MNZvg/IPOeu6F8oQGIIlNbl42pKWjCHw7Nutcv0t5G9aXTzt+8AYsn6YAlo7nctpyi/o4o5Tmxuw7ik6TkmHMNQqdZwauOY4JaWfIiK45HtaeJA3SWdUhZLSTjF/zREG3+DYXTbx6/WMu69l8Yevq5hCwjAnJRZPm5MScQsJPccaJQr+20eVFq0x+PmhPDzx7nAdpjDHyuDFSks5RXBoybEKCvUmLeWUXczxo5lkZ+Xz/MN/M/a+31k0e1/xsq/eW8V9o9qW2Ti5VEkZuUQEeRVPhwd6Of790nOZv+4Yg7vXOet24lNy2HUog2Z1nG+IJJ/MJ9y/pGEY5udOUma+Q9z8ban0fns9D0/dwWsD6jksn70lhZtaOH+OAyQnZRIe7l88HRruT1JypkPc1s2HGNDnHUaO+IL9+xIdls+ZvYlevVu4JKfLwaiu3E95uNAxbK8AG4EC4G9gkdZ6iFLKH1irlFoAJAM9tNZ5Sqm6wM9A66L12wKNtdYHS2+0qOJ2PfB10awvgIe01vuUUu2AT4DTXysDin6/FVsDsiMwDFinlGpetP+3gFZABjBPKXU7sKYo/1ZAJrAY2FQqjUFAD6A+MAr4WSnlCXxZtL/9wPRS8S8By7XWE5RSNwEjLvAYnl0Zn4lnfgA0ahTNokWv4+3tydKl2xj1yKfMnfcqAD/9/CRhYf6kpZ1kyAMfULt2OG3aODkW4wJyqn9NBL/NGY2Xlwcr4/byzJhpzPjrMWrWDuHuBzrx+IPfU8XLnbr1wjCaruLRoBfx5jXUboqpTU/yPrN1MeiUoxQu/QXPoRPRBblYEw6A1eKCnMpI6ixtL/dGLfGKvZW0F2ynskerjlgzMzAf2IN7o5bO51KSVBnzyk7KUKcppjY3kPfpE7ao5KMULvkFz+FvoPNdeJzKOs/PmJ749TrG3dsS4xkjmheviyfIz5PGMUGs2eb44eaUMv5+F9p2Ljh0gPTvvyJyytdYT50if98esJjPv+L5lJHAmVlaLJr/dqfy6pTeFORbeGrYLOo3DuX4kUz8A6oQ0yCYbRuc7O4/X05nHLuJ329m3B1Nz/pQ1Zw8M4+9t5Jn72mOj5fb5UipzLdjjybB9GgSzLoDmXw49zDfPFjSzVhgtrJoRxpjbqzpdD62nMr629kndU3DSOYseBEvbw/ilu5kzKNT+WtOyXjowgIzSxfv4PExN7kkJ3HxLqjBprXOUUpNB7KBgcAtSqnTo5A9gWjgODClqPFkAUp/ZVh7RmOtilJqM1AT2ADMV0r5AB2AX0q94TxKrfOX1lorpbYBSVrrbQBKqR1F26kBLNFapxTN/x9wug+o9Pzpp3NTSrUBUrTWh5VS8cBUpVRA0bYOaq33FcX9SEnD7DqKKm5a63+UUo6lMNs6I06v89nnYxkxwmH4W7Gw8AASEks2k5h0gtBQf7sYH5+SroUuXZrwyis/k5GeTUCgD2FhttigIF+692jO1q0HnW6whYT5klSqKpaSfJLg0Kp2Md4+JaX6Dp3rMWniP5zIyME/wJtb+rbklr62D/vPPlxASJhz40IqMp2ZivIr+Sas/ILRJ9Mc4lR4Tdz7jSb/mxfhVFbxfMv6eVjWzwPA7Yb70JmXPByymDUtGWNwSUXGGBSKNSPFIc5UIwbfh58j4/Ux6Gzb39utflM82nQmpGUHcHPH4OWN32Mvk/nhy07lVPZxSneIU+G1cO8/mvyvzzhO6+ZiWTfXlmOv+11ynMKCvEhIzSmeTkzLIbRUNx7A9v1pjJ1kq1yfyMpn2cZjmAyKLftSWbQunqUbjlFQaCH7VCFPvrecd8Z0cjovc3IiprCS8UWmsHDMpSqm53Ny1m+cnPUbAEEjR2NOdr5BGRTqTWpyybFKS84hMMTLIcbXzwPPKm54VnGjUYtwDu1L4789aayNO8yGlUcpKLBwKqeAyS8tZuwr3ZzKKSzQi4S0kipfYvopQs/oQtx+MJ2xH9mqxyey8lm2ORGTQdG9TXUKzVYee28lt3SsQc+2kU7lUpyTnweJJ0oqakmZBYT6epw1vk1tP46m5ZKRU0iAt63BGLc7g4bVfQiu6u6anML9SUw8UTydnHiC0FD7a7JPqet55y4NmfjqTDIysgkIsHVvL4/bTYOG1QkKtv8cqEgM/5/HsJ3BWvSjgH5FY9Caa62jtda7gDFAEtAMW2Wt9JmWc8a2crXWzbE1jNyxjWEzACdKbbe51vqaUuucfgdYS/1+etrEuescZ/tuegfQoOjGgf8AX6DfedY53zJbgNZfaK1ba61bn6uxBtCkSQ0OH0om/mgqBQVmZv+zjtjYpnYxKSmZxd+Stm49iLZq/AO8OXUqn+zsPABOncpnxYpd1Kvr/B1F1zSqRvyRNI7HZ1BYaGbBnO106mI/9iQtNas4p53b4tFWjZ+/7QKenmYbh5SYcIIlC3fR48aKOUjVFazxe1FB1VABYWA0YWrWBcvO1XYxyi8Ej7tfpGD6O+jUM8bYePsVxxgbdcS8ZanTORXu34UxIgpjaASYTHh27EH+OvvuckNwGP7j3iDzo1ewJJSM28r+6VNSHryVlJF9yHz/RfK3r3e6sQZgjd+DCj7PcfIPwePeFymYdo7j5B+CsXFHzJuXOJ1Tk7pBHE7IIj4pi4JCC7OXHya27Rl39H3Rl0Vf2n56XhvN+Afb0b19NE/c05KlX/dj0Zd9efeJzrRrGu6SxhpA3s7tuEXXwFStOpjc8O1xIznLFl/w+sYAW9eeKSyCqt26kzV3ttM51b0mhISjJ0k6nkVhoYW4+Qdo27mGXUy7ztHs3JKExWwlP8/M3h0pRNb0596RbZj61518+cdgxr3ajaatqzndWANoUieAw4nZxCfnUGC2MnvVUWJb2d+stfCDm1j0oe2nZ7tIxj/Qku5tqqO15oUv1lOnui8P3OTYJXnJOUVV5XBqHvHpebacNqfQraF9V+vh1Nzia+eO+GwKLRp/r5L6yT+bk13WHQrQqHEURw6nEB+fRmGBmTn/bqJLN/u7oVNTThbntG3rYaxWjb9/SRf4v7M3cmNvV1bcxcW6lMd6zAUeVUo9WlTxaqG13gT4AfFaa6tS6j7AeO7NgNY6Uyn1GPAn8ClwUCk1QGv9S9Edqk211lsuMK81wAdKqWBsXaJ3AB8Ba4vmBwEngQHAFqWUoej3plrrYwBKqW7AC9jG6dVSStXRWv9XtK3TlgF3Aa8ppW7E1lXrFJPJyIvjBzF02IdYLVb69etA3brVmPbzMgAG33Edc+duZNrPyzAaDXh6uvPu5GEopUhLO8moRz4DbHfw3HxzGzpf18jZlDCZjIx9tjdjHv4Bi1Vz8+0tqB0Tyu8z1gHQZ2AbFs/fye8z1mM0GfDwMDHhrf7F3RHPPzGDzMxTmExGxj13E76+Vc61O5f5acgEutZrSbCPP0cnzuKlv79k6sq/Lu9OrVYKZn2Kx5DXwGDEvH4eOvkIpna9ATCvmY1b9ztR3lVxv912f422Wsif8jgAHne/gPLyBauZgj8/KR5071xOFk5+NYmAFz6wPdZj0d+Y4w9SpWcfAHLn/Y5P/6EYqvrhO+zJ4nXSnn7A+X2fNScrBX9+gsew18FgwLxuHjrpMKb2Rcdp9Wzcut+F8qqKex/bTdzaaiH/w8cA8Lj3RZRXVbBYKPjjY5ccJ5PRwIvD2zL0lYVYLZp+3WOoG+3PtDl7ARjcy3Uf5BfFYiHl7deJ/PBLMBo4Oet3Cg7sx6/vIAAyf5uOMSiY6O9mYPD2AW3Ff/A9HB50C9acHCLe+gCjnz+YC0l6+zWsWc6PITWaDIwY14GXH/8Xq1Vz/c31iK4dwL+/2W4ourHvNUTVCqBF+0geu/s3DAZFj1vrU8MF48LOxmQ08OL9LRj65jKsVk2/rrWoG+nHtAW2u2nPNW5t4540/lx+mHpRftz+rK3CPWZgE7q0cG68n8moeOH2Ogz7cjtWq6Zv2zDqhnszbVWCLadrI5i3LZU/NyTjZlB4uBmYfHeD4mtnboGFlftO8Eo/1zxiBGzX82ef78vDw7/AarVye5+2xNQNZ8a0lQAMHNyB+fO2MGPaSkwmAx4ebrz17j0lOeUWsHrlXl58eYDLcrocymts2ZWiyurbLjNQqZexdYl+DLyPrftSAYe01jcXjVubCZzCNk7sUa21T1mPxFBKZWutfUpN/wXMAJZja7hFAG7AtKKxYt8Cf2utf1VK1Sz6vXHRuqWX3Qk8W5TXbK31U0UxDxTNTwA2Y2tM/gq8qbVuXyoPIxAPtMRWKXwfSC3Kq3HR6wzCNj4vGFiKrXu01bke66FZ7LqR2y6SnufiMTcuEDzmg/JOwUGOn9Pt8cvi5P4ye+LLlW9t//JOwUGVB1xT8XKlfff+VN4pOLDOu4wNdSfUP+A4ML686WMV79pZcFOf8k6hTJ7Gm65oE+rxpcOv2GftB12+POdrU0r1Aj7A1t74Smv95hnL/bAVh6KxFc8maa2/cdhQKRdcYdNav1xq8sEylu8DSvfjPVs0fwmw5IxYnzOmbyk16fB8N631/aV+PwQ0PsuynwCHq2HRQSjrQLQ/I86CrbEItsadwxMYtdZpQM9Ss8aUsV0hhBBCXEFnua/kiisq/nyM7YbGeGw3R87SWu8sFfYItue/3qKUCgH2KKX+p7U+60MKr+Jb94QQQgghrri2wH6t9YGiBtg04LYzYjRQtWj4lw+2Z9Ke83ZuabAJIYQQQrhOdaD0E7jji+aVNgW4BtsTNrYBj2utrefaqPxfokIIIYSo9K7kTQelH91V5Aut9RenF5exypnj627ANqY+FqiD7fFmcVrrs94hJA02IYQQQoiLUNQ4++Isi+OB0s8HisRWSSvtAWw3Pmpgv1LqILZx82vPtk9psAkhhBCi0jNUlLsOYB1QVylVCzgGDMb232CWdgTb//QUp5QKw/a/LR0410alwSaEEEII4SJaa7NSahS259Yagala6x1KqYeKln8GvAp8W/S/Nyng6XM9HgykwSaEEEKIq0BFenCu1no2MPuMeZ+V+v049o8IOy+5S1QIIYQQooKTCpsQQgghKr2KM4Tt8pAKmxBCCCFEBScVNiGEEEJUehVpDNvlIBU2IYQQQogKTipsQgghhKj0DOrqLrFJhU0IIYQQooKTCpsQQgghKj0ZwyaEEEIIIcqVVNiEEEIIUenJc9iEEEIIIUS5kgrbFaAs5vJOwUHA8pXlnYKDHL+A8k7BgXdmRnmnUKYRIxuXdwoOPqtVr7xTcFD4x5ryTsFB5HWR5Z2CA9O3q8s7hbJ1b1LeGThQ17Yv7xQcpOYeK+8UyhTpU94ZXF2kwSaEEEKISs8oj/UQQgghhBDlSSpsQgghhKj05KYDIYQQQghRrqTCJoQQQohKTx6cK4QQQgghypVU2IQQQghR6Rmu8hLUVf7yhBBCCCEqP6mwCSGEEKLSk+ewCSGEEEKIciUVNiGEEEJUevIcNiGEEEIIUa6kwiaEEEKISk+ewyaEEEIIIcqVVNiEEEIIUenJGDYhhBBCCFGupMEmhBBCCFHBSZdoBbEsbievv/ErVouVAf07MGJ4T7vla9buZeSoL4isHgRAjx7NGTXyxuLlFouVfgPeJizMj88/fdglOcXtSGXir7uxWjX9O0YyvGctu+ULtyTz4d/7MSiF0ah4tl99WsUEAPD94sP8siIerWFAx0jui63hkpwADPVa4X7LQ6AMmNfNwbz0F7vlxubdcOsyAABdkEvBH1PQCQcBMHW8DVObXqAU5rVzMK/4w2V5nc3X9zzPzU06kpyVQZNX77rs+zutUWAjBta9A4MysDwhjrmH/7Vb7mmswtBGwwjwCMSoDMw/Oo+VCSsI8AjggYZD8XX3Q2srcceXsSh+oUtyilsfz+ufrsZqtdK/V31GDGpWZty2PSkMGvMXk5/tRq/OtvMu9t7peHu5YTQojEYDMz+6zSU5qRrNMXUdAgYDlu0Lsa773X557TYYO9wB2gragmXJN+jju8EnCFOvx1Be/mg01m3zsW76xyU5ARjqt8b99ofBYMC8Zg7mRdPtlhtbxuLWbSBQdJ7/+hE64QAAps63Y2rXGxSYV/+LOe53h+1fiop4rOI2Hef1bzbarlPX12FEn4Zlxm3bn8ag5+YzeUwHel0bTX6BhbvHL6Cg0IrFYqXntdE8NqiJa3JafZDXP1hoy+nmpoy4p13ZOe1KYNCD/2PyK7fQq1t9AL6fsYFf/tqK1poBtzblvoGtXZLT2pUH+XjSYqwWTe/bG3PHA445bV5/lE/eXYzZbMXPvwrvfTkIgHdemcPquAP4B3rx9Yz7XZLP5XC1Pzj3sjTYlFJBwOkrfDhgAVKKpttqrQtKxY4GvtBanzrPNpcA47TW65VSh4Csou0agRe01n86mXNNoIPW+qeiaS/gS6ApoIATQC+tdbZSygJsK7X67VrrQ5e6b4vFyoTXZvDNV6MIC/On/6B3iO3WhJiYCLu41q3qnLUx9v0Pi6lTJ4zs7LxLTcM+J6vm1Rm7+PrRVoT5ezLw7dV0axJCTIRPcUz7+oHENr0WpRR7jmUx5ustzB7fib3Hs/hlRTwznmqPm1Ex/OONdGkcTM1Qb+cTUwbcb3uE/K+fQ2em4jnqAyy71qCTjxSH6PRE8r54CnKzMdRrjXufx8j/ZAwqrAamNr3I+3g0WArxeOA1LLvXotOOO5/XOXy76h+mLPmV7+8ff1n3U5pCcUf9u3h/02Qy8jN4tvULbE3ZTMKphOKYbpHdSMg5zsdbP8LHzYcJ7V9nTeJqLNrKL/tmcDT7CB5GD55v8yK70nfarXspLBYrEz5eydSJvQgL9mbAY7OIbR9NTI0Ah7hJU9fRqVV1h218/1ZvAvw8ncrDjjJgih1O4W8TICsN051vYf1vHaTHF4foo9sw/7jOFh5cA9NNT1D43WO2Bsmyb9HJB8HNE7e73sF6eIvdus7k5d53FPmfP2M7z0d/hGXHKnTSGef5J+Ns53mDNrgPGE3+h4+hwmtiatebvA8etZ3nwyfa3iOpTp7nFfBYWSxWJny1ganjuxEWWIUBz8wjtnV1YqL8HOIm/biZTs3Ci+e5uxn49qVYvKu4UWi2ctcLC7iuRQTN6wU7n9Pk+Ux9byBhoVUZMOwHYjvVIaZWsEPcpE+X0altzeJ5ew+k8MtfW5nx5d24mYwMf+IXulxbh5pRATjDYrHy4ZsLefuT/oSEVWXkPf/j2i4x1KwdVByTnZXHB28u4M2P+hEW4UtGeslH8g23NOa2gS1466V/y9q8uEIuS5eo1jpNa91ca90c+Ax47/R06cZakdGA1yXsplvR9vsDHzqTb5GawJ2lph8HkrTWTbTWjYGhQGHRstxSr6e5M401gK3bDlEjOpioqGDc3U3cdGNLFi7aesHrJyZmsGTpDvr36+BMGvY5HcokOsSLqGAv3E0GercKZ9HWZLsYb08Tqugbzal8Cwrb7wcSc2hWy58q7kZMRgNt6gawYEuywz4uhSGqHjrtODo9ESxmzFuWYmzY3i7GemQX5Gbbfj+6G+Vnu1AaQqOwHt0NhflgtWI5uA1jI9cds7OJ27+Z9JyTl30/pdXyrUXyqWRS81KxaAvrk9fSLKS5XYxG42G0NX48jJ7kFOZg1VZOFmRyNNvWMMi35JOQk4C/h3MfGABb96QQHeFLVIQv7m5GenepzcJVRxzifpy1k54daxLoV8XpfZ6PCo9Bn0iEzCSwmrHuWY6hThv7oMJSX4LcPEBr2+85J2wNkKIYnR6P8gl0SV6G6Pr25/mmpQ7nqvXQzpLz/PAulH+p8/zIrpLz/L9tGJt0dDqninistu5PJzrch6gwH9s51TGahescG4E//ruXnu2iCCzV2FdK4V3FDQCzxYrZYsUV9ZmtuxKIjgwgqrq/LafuDVi4fL9jTjM30rNLXQIDSj7+DhxKp1mjCKp4umEyGWjTIooFy/Y6ndPuHYlUj/KnWqQ/bm5GuvWsz8ol9jkt/Hc3nWPrEhbhC0BAYEleTVtG4uvKL0qXiUFduZ9yeX1XakdKqeuVUpuUUtuUUlOVUh5KqceAasBipdTiorhPlVLrlVI7lFKvXMCmfYGMonW9lVL/KKW2KKW2K6UGFc0/pJSaqJRaVbTtlkqpuUqp/5RSDxVt502gs1Jqs1JqDBABHDu9E631Hq11vuuOSImkpEzCw0s+EMPCA0hKznSI27z5ILf2eYNhIz5h376SasfEN2fy5LjbMbjwLEo+kUd4QMkbNMzfk6QTji9//uYkek9YzsOfbuS1uxsBULeaD+v3Z5CRXUBugYVlO1JJzHBN5U/5BqMzU4qndWYqyjforPGm1jdg3bseAGviYQw1G4NXVXDzwFi/Dco/xCV5VTT+HgFk5GcUT2fkZzg0uhbHLyLCO4K3O05ifNuXmb7vZzTaLibIM4joqtEcPHnA6ZyS0k4REVJSZQ0P9iIpLcc+JjWH+SsPM/imBg7rKwVDn5tD31F/MH32bqfzAcAnEJ2VWjKdnY7ycTyfVJ22uN33Iabbn8M8/2PH7fiGoEJqoRP3uSQt5ReMPlH6PE9B+Z3jPG/XC+tuW2XLmngIQ+0mJef5NS46zyvgsUpKP0VEcEnDIjzIi6T0XPuYtFPMXxvP4J4xDutbLFZuH/cvHYf+Toem4TRzsroGkJSSTURo1ZKcQqqSlJJ9RkwW85ftY/Dtze3m160dzLrN8WRk5pKbV8jSVQdISM5yOqfU5GxCwkpyCgmrSuoZOcUfySDrZB5jR0znobt+YN7fO5zer3CtKzWGzRP4Frhea71XKfU98LDW+n2l1Fhs1bLTV4LntdbpSikjsFAp1VRrXVa5abGylXdqAwOL5vUCjmutbwJQSpWuix/VWl+rlHqvKJeORXntwFYFfAZbl+vNRes2B+Yppfpj6979Tmt9+gpTRSm1uej3g1rrPpd+aEBr7TDvzKZXo4ZRLFrwKt7eHixduoNHHv2CeXNeYvGSbQQGVqVxo2jWrHX+m1hxTmXMK2t4QI/mYfRoHsa6fel8+Pd+vnmsNXXCfRjWoyZDp2zAy91Ig+pVMbqqMXkRmzHUboqpTU/yPhsHgE45SuHSX/AcOhFdkIs14QBYLa7JqzI44zxrFNiYo1lHmbxpEiFVQhndfAyvrn2FPIutce1h9ODBxiOZsW968Tzn9u84S51xUk38bDXjhrTBaHT8LvnT5JsJC/Im7UQuQ56dQ+0oP9o0iXCIuzhlnFBlvB/1f2sp/G8tqnpDjB3uwDyz1HdJN09MNz+Jeek3UJDrsK7rlPWuBEOdZpja9iJvyhhbVPJRChfNwPPBN9H5eViPHwCL1QX7r4DHqsxzyn564jcbGXd38zLPKaPRwB+TbuRkTgGj3o5j75ET1Iv2v/w5fbCIcQ91ccipTs0ght/dlqFjZuBVxZ0GMaGYysj74nMq4zPmjJwsFiv7diXzzmcDKMgr5NEHfuaaJhFE1XBN1fhKuNofnHulGmxGbA2b0y2K74BHgPfLiB2olBpRlFsE0BAoq8HWTWudqpSqg61htwTbuLJJSqm3gL+11nGl4mcV/bsN8NFaZwFZSqk8pZT/mRvXWm9WStUGegLdgXVKqWu11rso6hI91wsueg0jAD7/9HFGDL/prLHh4f4kJpZUQ5ISMwgNtR+D4eNT0j3UpUsjXnl1OukZ2WzceIBFi7exbNkO8vMLyc7JY9xT3zHp7fvOld55hfl72lXFkk7kEerncdb4NnUDOfrDdjKyCwjwcad/h0j6d4gE4L0/9xEWcPZ1L4bOTEX5lVQLlF8w+mSaQ5wKr4l7v9Hkf/MinCr5hmpZPw/L+nkAuN1wHzoz1WHdq8GJ/AwCSlXUAjwCOFFwwi6mQ0RH5hTdiJCSa+s+DfeK4FDWQQzKyIONH2Zt0mo2pWx0SU5hwV4kpJRU1BJTTxEaaD8aYvu+VMa+sdj2Gk7msWzdUUxGRfcONQkLslXngvyr0L1DDbbuSXW+wZadhqpaqqriE4jOST9ruD62E+UXBp5VIS8LDEZMNz+JdXccev8a53IpvZ/MVLuqmPILQWc65qUiauE+cAz5Xz5vf56vnYNl7RwA3G58wDXneQU8VmFBXiSkloy1Skw7RWiAfVf69gPpjH1vJQAnsvJZtvE4JqOB7m0ji2N8vd1p2yiUuE0JTjfYwkJ97KpiiSlZhAb72MVs35PE2Jf/suWUmcuyVQdtOV1Xl/43N6X/zU0BmPz5MsJDquKs4LCqpCSV5JSSlEXQGTmFhPrg51+FKlXcqFLFjSYtIzmwN6VSNdiudleqSzTn/CGglKoFjMNWiWsK/IOtCnZWWuv/gCSgYVGDsBW2RtkbSqnSo7xP9+dZS/1+errMhqvWOltr/ZvWeiTwI9D7Ql5H0bpfaK1ba61bn6uxBtCkcQ0OHU7haHwqBQVm/vl3I7HdmtrFpKScLK7Ebd16CKtVE+DvzRNjb2PZ4tdYtGACk999gPbt6jndWANoUsOXw8mniE89RYHZyuwNiXRrEmoXczj5VHFOO46cpNCs8fe2jQlJy7Id4uPpuczfksRNrZ2thNhY4/eigqqhAsLAaMLUrAuWnavtYpRfCB53v0jB9HfQqcfsN+DtVxxjbNQR85alLsmrojmUdYhQrzCCPIMxKiOtQ9uyJXWLXUx6XjoNAq8BoKqbL2Fe4aTk2brh7m1wH4mnElhwdL7LcmpSP4TDx08Sn5hFQaGF2UsPENs+2i5m4XeDWPS97adnp1qMH9WB7h1qciqvkOxTtuGvp/IKWbHxGPVqOj+uTifuRwVEgG8oGEwY6ndCH1hvH+RXMlBdhdYCo8nWAAGMPUai0+OxbvzL6VxKsx7dgwqujgoMt53nLbpg2bHKLkb5h+Bx/3gKfn7b8Tz38S+OMTbthHnTYqdzqojHqklMIIcTsohPyradUyuOENsm0i5m4Se3suhT20/P9lGMH96a7m0jSc/M42SO7ZzKyzezamsStav7Op9TgwgOH80g/vgJW04LdhPb0b47duEvI1j064Ms+vVBenatx/gnutP9uroApGXYPi6PJ55k/tJ93NT9GqdzatAwnGNHT5BwLJPCQguL5+2hQ5c6djEdusawbdMxLGYrebmF7N6eQHSts3fDV0QGpa7YT3m4kl2iNZVSMVrr/cA9wOlPyiygKpCKbTxaDpCplAoDbgSWnGvDSqlQoBZwWClVDUjXWv+olMoG7r+IHE/ncXq7HYGdWusMpZQ7tkrfOXO5VCaTkfHPD2TY8I+xWDX9+rSnbt0Ifp5mKxDeMbgzc+dt4udpcRhNRjw93Jj87gMO3Ukuzclo4IWBDRj2se12+b7XVqduNR+mxR0FYHDnKOZtTuLPNcdxMxrwcDcweUjT4pwe/3ILJ3IKMRkVLw68Bj8vN9ckZrVSMOtTPIa8BgYj5vXz0MlHbI8wAMxrZuPW/U6Ud1Xcb38EAG21kD/lcQA87n4B5eULVjMFf35SPGj7cvppyAS61mtJsI8/RyfO4qW/v2TqStd+wJ/Jqq1M2/sTjzcfjUEZWHF8BQk5x7muWhcAlh1fyj+H/uL+hkMY3/ZlQPH7/pnkFGZTxy+GayM6EJ8dzwttbN95/jjwO9vTtp19hxfAZDTw4shrGfr8HKxWTb+e9ahbM4Bp/+wCYPBNZ/9gSsvIZdQE243nFouVm7vVoXPryLPGXzBtxbzoK9z6vgjKgGXHInTaUQxNbY/VsW6dh6FuewwNu4LFDOYCzP9MBkBVa4CxYVesKYcx3TXJltuKn9CHXFCRtFop+G0KHiMm2h5fs3YuOukwpmttX/7Mq/7BrefdKC9f3Ps+WvRSLOS/PwoAj/teLDnPf/vINed5BTxWJqOBF4e1ZuhrS2znVGxt6kb5MW2ubfTK4BvqnnXdlIxcnpmyGotVozX06hBNt9aOdyZfdE4mAy+O7c7Qsb9itVrpd1MT6tYOZtofm205nTFu7UyPPf8nJ07mYTIaGD+2O36+zg/2N5oMPPpULE+PmonVYuXG2xpTs04wf/1q+xJ3S/9m1KgVRJsONRk2+DsMBkXv25tQK8ZWUX3tub/Zsj6ezBO5DLrxc+57sAO9b3fNI1DEhVNljZ9y6Q6UehnIBjYBk7A1EtdhG8OWr5R6FFv3aILWuptS6lugHXAAWyVsltb623M81sMNeFdrPVUpdQPwDraqWWHRPk7Hty7qQr2/6PdRRfkdAloDmcAcIBjbGLc0bNU+ha0S+Q/wtNZaK6Wytdb29eRzscy/vAf5ElgXzzp/0BWWt8DxTqry5p2Zcf6gcjBiQOPyTsHBZ7XqlXcKDgr/cF03pauY450fRO5qpkjnu90uB7fuFbBREO6CLwoudqyKK8Youl6kz4grWor6ac8jV+yz9s76H1/xMttlr7BprV8uNdmijOUfAR+Vmr7/LNvpWur3mmeJmQvMLWN+zVK/f4utQVbWtq4/Y9Xvz7KfC2+sCSGEEEI4Sf6nAyGEEEJUeuU1tuxKkf9LVAghhBCigpMKmxBCCCEqPamwCSGEEEKIciUVNiGEEEJUelJhE0IIIYQQ5UoabEIIIYQQFZx0iQohhBCi0jOoq7sGdXW/OiGEEEKIq4BU2IQQQghR6clNB0IIIYQQolxJhU0IIYQQlZ5U2IQQQgghRLmSCpsQQgghKj2psAkhhBBCiHIlFTYhhBBCVHqGq7wGdXW/OiGEEEKIq4BU2K4AnbyvvFNwkPvP7vJOwUHW0azyTsHBiJGNyzuFMn3xy/byTsHBB1P6lHcKDtzrHyjvFByY2tUu7xQcJL2zrLxTKFN4rxblnYKjCvg0fU+TZ3mnUCHIGDYhhBBCCFGupMImhBBCiEpPKmxCCCGEEKJcSYVNCCGEEJWeoQKOL3Slq/vVCSGEEEJcBaTBJoQQQghRwUmXqBBCCCEqPbnpQAghhBBClCupsAkhhBCi0pMKmxBCCCGEKFdSYRNCCCFEpScVNiGEEEIIUa6kwiaEEEKISk8enCuEEEIIIcqVVNiEEEIIUekZkDFsQgghhBCiHEmFTQghhBCV3tV+l6g02CqIuDWHeH3KUqwWTf+bGjHirjZlxm3bncigkTOYPP5GenWtC8C3v2zk1392oFDUrR3EG0/3wMPD+T+tsUFr3PuMBGXAvOZfChdOt1/eMhb36wcBoPNzKfj1Q6zHDwBg6tIXt/Y3gtZYEw6R//M7YC50OicA9+bt8X1gDBgM5C6cRc4fP9gt9+x8A96332PLK+8UJ794G/Ph/SUBBgNBb32DJT2FE2+Mc0lOjQIbMbDuHRiUgeUJccw9/K99TsYqDG00jACPQIzKwPyj81iZsIIAjwAeaDgUX3c/tLYSd3wZi+IXuiSn8/n6nue5uUlHkrMyaPLqXVdknyvidvHWG39gtVjp0789Q4dfb7d83dr9jB41lerVAwGI7dGEh0bewKGDyTw19vviuPj4NEY+2ou77+3idE5xu9KY+Ps+rBr6t4tgePcadssXbkvhw38PYlAKo0HxbJ8YWtX2B+DbJUf5dfVxlFLUi/Bm4h0N8HAzOp0TQNy2ZCb+tA2rVdP/uhoMv6lumXHbDmQw+LU4Jj/cmhvaVAPg+a83sWRLEoG+Hvz1WjeX5APg0aI9vkPHgsHAqQWzyPnte7vlntfdgE+f0++9XDI/fxvzoX3g5k7Q65+hTO5gNJK3ahHZ0750SU5xG4/x+lfrbcepRwwj+jUuM27bvlQGPT2HyeM606tDyd/YYrHSf9xsQoO8+PyFWNfktPoAr7+/EKvVSv9bmjHinvZl57QrgUEjfmDyhFvp1a0BAN/PWM8vs7agtWbArc24b1DZnwXOWr1iP++/NRerVXNLnxbcM7SjQ8zGdYf44J15mAst+Ad48fHU+y5LLuLCVKoGm1JqKnAzkKy1LvtdaYvrChRorVcWTb8MDAdSikLmaK2fUUotAcZprdeXsY2bgVexdRu7AR9orT8/27aceV0Wi5UJHyxh6qQ+hIX4MOChacR2rE1MzSCHuEmfr6BTm+jieUkp2fwwcwv/fHcPnh4mRr88m38W7aXvjQ2dSQmUAfd+j5L32dPoE6l4jpmCefsqdNKR4hCdnkjulCcgNxtjgza4DxxN3vuPofyCcOt8O7lvDYPCAjzuewFTi26Y181zLicAgwHfYePImPAYlvRkgt78hrz1cVjiDxWHWJKPkz7+YXROFu4trsX3oWdJf3Zo8XKv3oMwxx9CeXk7nw+gUNxR/y7e3zSZjPwMnm39AltTNpNwKqE4pltkNxJyjvPx1o/wcfNhQvvXWZO4Gou28su+GRzNPoKH0YPn27zIrvSdduteLt+u+ocpS37l+/vHX/Z9ge38nfjab3z+1UOEhflx56D36NqtEXViwu3iWrSqzZRPh9nNq1krlBm/jyveTo+urxB7fRPnc7JqXp25l68fak6YvwcD31tPt8bBxISXnBvt6wUQ2zgYpRR7jmcz5rsdzH62HUkn8vkxLp6/n26Lp7uRMd9uZ/amZPq0jXBNXj9s5etx1xIWWIWBE5bRrXk4MdWrOsS9+8suOjYOtZt/e6do7ry+Fs98tcnpXIoZDPiOeJL0lx/FkpZM8Nvfkr82DnP8wZJ8ko6T9oLtvefR8lr8Hn6GtKeHQmEB6eMfQeflgtFI0MQvyN+4isK9251KyWKxMuHztUx9pTthQV4MePJfYttGEhPl7xA36fuNdGru+Lf5/u/d1I70IzvXNV8oLRYrE96dz9T3BxEWWpUBw74jtlMMMbWCHXP6ZAmd2tYqnrf3QAq/zNrCjK/uxc1kZPgTM+jSoQ41owJdklvpfb87cQ7vf34XoWG+DLvzKzp1rUetOiHFMVkn83h34r+8+8mdhEf4kZGW49IcLge5S7Ri+RbodQFxXYEOZ8x7T2vdvOjnnA0spZQH8AVwi9a6GdACWHIp27oQW3cnEV3dj6hqfri7GekdW4+FKw44xP342xZ6XhdDoL+X3XyLxUpevhmz2UpuXiGhwc43RAzR9bGmHkenJYLFjGXTEkyN7Q+p9dBOyM225XB4F8ovpNQGjODmAQYDuHmgT6Y5nROAW0xDLInxWJKPg9lM3or5eLa5zi6mcM82dE6W7fe92zEGluRlCAzBo1UHchfOckk+ALV8a5F8KpnUvFQs2sL65LU0C2luF6PReBg9AfAwepJTmINVWzlZkMnRbFsjON+ST0JOAv4eAS7L7Vzi9m8mPefkFdkXwPZtR4iKDiYyKgg3dxO9bmzBkkUX/4G9ZvU+oqKDqFbd+Q+xrUdOEh1chajgKribDPRuEcai7al2Md4eJlRRV8upAovdsGaLVZNXaMVssZJbaCXU18PpnAC2HsggOtSbqFBvW15tq7NoU6JD3I8LDtCjdQRBZ+y3Tf0g/H3cXZLLaW51G2JJiMeSZHvv5S6fj0fbs7/3CvZsxxhU0pDUebm2X4wmlNEEWjud09Z9aURHVCUqvKrt2tmpBgvXHHWI+/GfPfS8tgaBfp528xNTc1i6/hgDesQ4nUtxTrsSiI70J6q6vy2n669hYdw+x5x+3UDPrvUJDCi5nh84lEazRtWo4umGyWSgTfMoFixzXNdZu7YfJzIqgOqRAbi5Gbm+VyPiluyxi5n/73a6XN+A8Ag/AAKCXPMFV1y6StVg01ovA9JLz1NKPaaU2qmU2qqUmqaUqgk8BIxRSm1WSnW+kG0rpbKVUhOUUmuAdtiqj2lF+83XWu855wackJSSTURIyTfn8BAfklKyHWLmL/+PwbfaVxXCQnwYMqglsQOn0rnfV1T18aBTG/sunUuh/IPRJ1KKp3VmKsov+Kzxpna9sOxeVxSbRuGSX/Ea/z+8XpkOeTlY9mxwOiewNbgsqcnF05a0ZAylGmRnqnL9LeRvWl087fvAGLJ+mOKSD4vT/D0CyMjPKJ7OyM9waHQtjl9EhHcEb3ecxPi2LzN9389o7HMI8gwiumo0B086NtavBslJmYSH+xdPh4b7k5Sc6RC3dfMhBvR5h5EjvmD/PsdGypzZm+jVu4VrcjqRT7h/yYd4mJ8HSZn5DnHzt6bQ+401PPzlVl67w9Z1FebvwQNdo7h+wique2klVT1NdGzgmkpIckYe4YFVSvIK9CQpI9cuJikjlwUbExncraZL9nk+xsBQLKlJxdPWtGSMQWd/73l1v5X8jatKZhgMBE/+gbBv55C/ZS2F+3Y4nVNS+ikiSn1BDQ/yJin9jOOUdor5a44w+AbHLuWJX69n3H0tixvkrpCUkkVEqG9JTqFVy7ieZzF/2T4G397cbn7d2sGs23KUjMxccvMKWbrqAAlJrv9SlZJ8ktDwkhxDQ31JScqyizlyOI2sk3mMGvo9QwZ/yb9/bXF5Hq5mUOqK/ZTL6yuXvbrWM0ALrXVT4CGt9SHgM0qqYHFFcacbcJuVUjeUsR1vYLvWul1Rw3AWcFgp9bNS6i6l7Gqt59uW0868gEycspRxIzpiNNr/yTKz8li44gALpt3PsplDyc0tZNa83a7IoIx5ZTdyDDHNcGt/IwV/FY1JqeKDqfG1nHr1Hk69NBjcPTG2ur7MdS8+rTLyOkvby71RS7xibyXrxykAeLTqiDUzA/OBy9b2LpWTfVKNAhtzNOsoT60Yx2vrJnBHvTvxNJY0FDyMHjzYeCQz9k0nz5J3+fMrB7qMRrI64zy7pmEkcxa8yC+/P8kdd3VizKNT7ZYXFphZungHPW9o7pqcyphX1pnfo2kIs59tx0dDmvDhbFsXYOapQhZtT2X+i+1Z+koHcgsszFrv2MB0WV5nnPtv/LSdJwZcg9FwhT48yrwklP3mc2/cCq/ut3DyhyklM61WUsfeQ/KwW3Cr2whTdG3ncypj92emOfHrdYy7t6XDtXPxuniC/DxpHBOES5WV0xlJTfxgIeMe7uKQU52awQy/qx1DR09n+NgZNIgJxWR0/cd0WX+2M88vi9nK7p0JvPPRYCZ/ehfffrGcI4dc01MiLk2lGsN2FluB/yml/gD+OEfce1rrSedYbgFmnp7QWg9TSjUBugPjgB7A/Re4LZRSI4ARAJ+9fQcj7u501tiwEB8SUkq+3SSmZDt0a27fk8zYCbaB7Ccy81i25hAmowGzxUpkhG9xN2mP62LYtOM4t/ZscK70zkufSEH5l3x7Vn7B6EzHN6uKqIXHoLHkffEcnLK9BmO9lljTEiHHVj2xbF2OsWZDLBucH0xvTUvGGFzSzWIMCsWakeIQZ6oRg+/Dz5Hx+hh0tu0bqlv9pni06UxIyw7g5o7Byxu/x14m88OXncrpRH4GAaUqagEeAZwoOGEX0yGiI3OKbkRIybV1n4Z7RXAo6yAGZeTBxg+zNmk1m1I2OpVLRRYW7k9i4oni6eTEE4SWqkQA+PiUNGI7d2nIxFdnkpGRTUCADwDL43bToGF1goLtx3Jdck7+HiSeKGkgJ2XmE+p39m7NNnX8OZqWS0Z2AWv2n6B6UBUCi7oeuzcNYdOhTG5tHX7W9S84rwBPEktVipLS8wj1t+/O234okyc+tVWuT2QXsGxrEkajontL58fQlcWSlowxOKx42hAUiiU91SHOVCMGv0eeI/3V0egsx+qQPpVNwfYNeLS4FvMR56rJYUFeJKSWjK1KTMshtFRlEmD7/jTGTrJ9bz+Rlc+yjccwGRRb9qWyaF08Szcco6DQQvapQp58bznvjDn7tfqCcgqtSkJyyetOTM4iNNjHPqfdiYx9yTYs40RmLstWHcBkNND9unr0v6UZ/W9pBsDkz5YSHuqac7200DBfkhNLckxOPklwqI9DjH+AF1W83Kni5U7zltHs35tEdE0XN3DFBbsaKmw3AR8DrYANSqlLbYTmaa0tpWdorbdprd/D1ljrdzEb01p/obVurbVufa7GGkCT+mEcjj9BfEImBYUWZi/aS2wH+2+fC6c9wKLpQ1g0fQg9u8QwfnQ3uneuQ0RoVbbsTCQ3rxCtNas2HqV2Dee7ZaxH92AIqY4KDAejCWOLrph3rLKLUf4heD7wEvn/ewudcqzktWckY6x5jW0MG2Co1wJr8hFcoXD/LowRURhDI8BkwrNjD/LXxdnFGILD8B/3BpkfvYIloWQ8S/ZPn5Ly4K2kjOxD5vsvkr99vdONNYBDWYcI9QojyDMYozLSOrQtW1Ltuw/S89JpEHgNAFXdfAnzCiclz9bQvLfBfSSeSmDB0flO51KRNWocxZHDKcTHp1FYYGbOv5vo0s3+3qHUlJPFlbhtWw9jtWr8/Uu+vPw7eyM39m7pspyaRFXlcEou8Wm5FJitzN6URLdG9l3/h1NOFee042gWhRYr/t5uRAR4sOVQJrkFFrTWrN6bQZ1Q14zzaVLLn8PJOcSn5NjyWnuMbi3C7GIWvNOdhZN6sHBSD3q2rsb4e5petsYaQOE++/delU49yF+3zC7GEBxGwNNvcuL9l7EcL3nvGXz9UV5FDQJ3DzyatcV87JDTOTWpG8ThhCzik7Js187lh4ltG2UXs/CLviz60vbT89poxj/Yju7to3ninpYs/bofi77sy7tPdKZd03CnG2sATRpEcDg+g/jjJ2w5LdxFbCf7MXILf32IRTMfZtHMh+nZtT7jx/Wg+3X1AEjLsDVAjyeeZP7SvdzU3ckbyMrQoFE14o+kczw+g8JCCwvn7KBTl3p2MZ271WPLxiOYzVbycgvZse0YNWudfVhMRXC1d4lW6gpbUTdllNZ6sVJqOXAn4ANkAb7nXPnc2/UBWmutlxTNag4cdi7bszOZDLz4eFeGPvkHVqum340NqVsriGl/bgVg8G1Nz7pus4bh9OwSQ9/hP2MyGrimbgiDbj7rDbQXzmqlYOYUPB98AwwGzGvmohMPY+pwMwDmlX/jdsM9KG9f3Ps/VrSOhbzJj2A9shvzljiqPPEJWC1Yj/2HeeVs53Mq2sfJryYR8MIHtsd6LPobc/xBqvTsA0DuvN/x6T8UQ1U/fIc9WbxO2tMPuGb/ZaWkrUzb+xOPNx+NQRlYcXwFCTnHua6a7ZETy44v5Z9Df3F/wyGMb/syoPh9/0xyCrOp4xfDtREdiM+O54U2trs1/zjwO9vTtl22fE/7acgEutZrSbCPP0cnzuKlv79k6sq/Ltv+TCYjzz7fl4eHf4HVauX2Pm2JqRvOjGkrARg4uAPz521hxrSVmEwGPDzceOvde4q7anJzC1i9ci8vvjzAdTkZDbzQrx7DPt+C1arp2y6CuhHeTFth+wIyuGN15m1N4c91ibgZDXi4GZh8byOUUjSr4ccNzULp9+56jAbFNdV9GNihmuvyuqsJw95dbcurczR1q/sybfEhW17nGbf2xGcbWLs7lRPZBXQdO49Rt9en/3VOjm21Wjj55SQCX/qw6JE6f2E+ehCvG2zvvVNzf6fqQNt7z+/BpwDQFgtpT96PISAY/8fG225CMhjIW7GQ/PUrnMsH23F6cXhbhr6yEKtF0697DHWj/Zk2Zy8Ag3vVO88WXM9kMvDimB4MHTvDltPNTahbO4Rpv9vu2B3c59zjLx977g9OnMzFZDIw/oke+Pl6njP+UnMc82wvxj78Exar5ubbm1E7JpTfZ9gqtn0GtqJm7RDadazDfQM+RynFLX1bULtu6Hm2LC4nVda4kopKKfUztjtAg4EkbI/duAfwwzZ04Uet9ZtKqXrAr4AVeBS4Hsg+sxuz9GM9lFLZWmufovlVgelAHSAXyAEeL4p7uaxtnYtO+KTCHeRTb/9e3ik4yDqadf6gK+ylkS5o/F4GX/zi3OMQLofcKS+WdwoO3OdevgboJfN3fReXs5LeWXb+oHIQPvGW8k7BUYhrGuWulObiO4JdJdjz7itaitqcOvGKfdY2D37uipfZKlWFTWt9RxmzPy8jbi9QuiwVd2ZMUVzXUr/7lPo9C+h9lnVevrBshRBCCCFco1I12IQQQgghynK1/9dUV8NNB0IIIYQQVzWpsAkhhBCi0jOU+bDAq4dU2IQQQgghKjipsAkhhBCi0pMxbEIIIYQQolxJhU0IIYQQlZ5BXd01qKv71QkhhBBCXAWkwiaEEEKISk/GsAkhhBBCiHIlFTYhhBBCVHpKxrAJIYQQQojyJA02IYQQQogKTrpEhRBCCFHpGa7yGtTV/eqEEEIIIa4CUmETQgghRKUnNx0IIYQQQohyJRW2KyA9IKC8U3CQsTqhvFNwUK1zZHmn4OCzWvXKO4UyfTClT3mn4KDKqFfLOwUH+98cXN4pOHht7bbyTsHB61Zd3imUzde3vDNwlJ9d3hk4WJt9tLxTKFPvmndf0f3Jf00lhBBCCCHKlVTYhBBCCFHpqau8BnV1vzohhBBCiKuAVNiEEEIIUenJGDYhhBBCCFGupMImhBBCiEpPxrAJIYQQQohyJRU2IYQQQlR6MoZNCCGEEEKUK6mwCSGEEKLSk/9LVAghhBBCXDClVC+l1B6l1H6l1DNniemqlNqslNqhlFp6vm1KhU0IIYQQwkWUUkbgY6AHEA+sU0rN0lrvLBXjD3wC9NJaH1FKhZ5vu9JgE0IIIUSlZ6g4nYZtgf1a6wMASqlpwG3AzlIxdwK/aa2PAGitk8+30Qrz6oQQQgghrgLVgaOlpuOL5pVWDwhQSi1RSm1QSt17vo1KhU0IIYQQld6VvOlAKTUCGFFq1hda6y9OLy5jFX3GtAloBVwPVAFWKaVWa633nm2f0mATQgghhLgIRY2zL86yOB6IKjUdCRwvIyZVa50D5CillgHNgLM22KRLVAghhBCVnkEZrtjPeawD6iqlaiml3IHBwKwzYv4EOiulTEopL6AdsOtcG5UKWwWxesU+3n9rDharlVv6tOTeoZ3tlm9cd5CnR0+jWnV/ALrEXsOQh7oCMP1/q5k1cwNouLVfSwbdfe1lydGrfUeCRz8DRiMnZ83kxA9f2y336XkTAfcMBcCae4qUt1+lYP8el+dhqNcK99seBmXAvHYO5iUz7JYbW3TDretAAHR+LgW/f4ROOAiAqeNtmNrdCCjMa//FvPwPl+QUtz6e1z9djdVqpX+v+owY1KzMuG17Uhg05i8mP9uNXp1rARB773S8vdwwGhRGo4GZH93mkpxWxO3irTf+wGqx0qd/e4YOv95u+bq1+xk9airVqwfa8ujRhIdG3sChg8k8Nfb74rj4+DRGPtqLu+/t4pK8zuXre57n5iYdSc7KoMmrd132/QGsX3WEz99djtWqueG2axh4X0uHmK0bjvHF5BWYzVZ8/T15+/PbKcg389SDf1JYYMFisdLp+trcPaKty/JqHNSYO+vfgUEplh2LY/ahf+2WVzFVYUTjYQR6BmFUBuYcnsvy4yswGUw82/ppTAY3jMrA+qQN/HHgT5fk5NGiPX7DnwCDgVPz/yR75vd2y6t0uQGfvrahODovlxOfvoX50D5wcyd44ucoN3cwGslbuZCsn790SU5xaw/z+pTltvde74aMuLNVmXHbdicxaNRMJr/Yk15dYjhwJIOxr84tXn404SSP3d+O+/qX/d6t7Dmdade6ZH7/bBvaoml3Yw26D6prt3zRL/vZsCgeAKtFk3Q0i1en98Lb193luVxttNZmpdQoYC5gBKZqrXcopR4qWv6Z1nqXUmoOsBWwAl9prbefa7sVqsGmlAoD3gPaAxlAAfC21vr3M+JqAn9rrRufMX8CsExrveA8+2kBbMR2O+3cc8VeCRaLlUkTZ/PB5/cQGubL0Du/pHPX+tSqY3+Xb7MW0UyaYv8h9t++JGbN3MDX/xuOyc3I2JE/0qFzPaJqBLk2SYOBkCde4NjjwzEnJxI1dTo5cYspPHSgOMSccIxjI+/HmnUSr/adCH3mJeKH3enaPJQB9z6PkP/lc+jMVDwf/RDLztXo5CPFITo9kbzPnoTcbAz1W+Pe73Hyp4xGhdXA1O5G8j56HCyFeAx9HcvutejUMyvVF8disTLh45VMndiLsGBvBjw2i9j20cTUCHCImzR1HZ1anTn2FL5/qzcBfp5O5XHmvia+9huff/UQYWF+3DnoPbp2a0SdmHC7uBatajPl02F282rWCmXG7+OKt9Oj6yvEXt/EZbmdy7er/mHKkl/5/v7xV2R/FouVT96O4/UptxAc6s3o+2bSvnNNomsHFsdkZ+Xz8dtxvPrBTYSGV+VE+ikA3NyNvPHJrVTxcsNstjBu+B+0vjaaBk3Cz7a7C6ZQ3NPgLiZtfJf0vAzGt3uRzSmbOZ6TUBwTG9mN49kJfLD5I6q6+TCx40RWJazGbDXz9oZJ5FvyMSojz7Z5hq1p2ziQeeAce7wABgN+Dz5F2kujsKQlEzLpO/LWxmE+erA4xJx0nNTnHkLnZOHR8lr8H3mW1CeHQGEBaS+OROflgtFI8JtfkrdhFYV7z/n5dF4Wi5UJHyxj6ju3Ehbiw4CHfyG2Qy1iagY6xE36YhWdWpf0UtWODuCPLwcXL+8y8Fu6d6rlVD4VNaczWS2amR9v5aE3rsU/uArvPbqMxu3DCa9RtTgmdkAMsQNiANi+OpGlvx2o8I01hbG8UyimtZ4NzD5j3mdnTL8DvHOh26wwXaJKKQX8ga3BVVtr3QpbGTHyjLizNjK11uPP11grcgewvOjfMnNRV3D04s7tx4iMCqR6ZCBubia692pM3JILq0wdPphK46aReFZxx2Qy0qJVTZYuOmdV9ZJ4NmxCYfwRzMfjwWwme8G/+FwXaxeTt20z1qyTtt93bMUUGubyPAxR9dGpCej0RLCYMW9ZirGRfUXRengX5Gbbfj+yG+UXbFs3NBrrkd1QmA9WK5YD2zA26uB0Tlv3pBAd4UtUhC/ubkZ6d6nNwlVHHOJ+nLWTnh1rEuhXxel9ns/2bUeIig4mMioIN3cTvW5swZJFF//huGb1PqKig6hWPfD8wS4Qt38z6Tknr8i+APbuSKZapB8R1X1xczNyXc8YVi07ZBezZO4+OnStRWi47cPMP9ALAKUUVbzcADCbrVjMVlBljTW+eLX9apN8KpmU3FQs2sLaxLW0CGnhEOdpsjXyPYye5BRmY9VWAPIt+QAYlRGTMoI+c7zzxXOr2whzYjyWpONgNpMbNw/PttfZxRTu3obOyQKgYM92jEElXzp1Xi4AymgCownHMdgXb+vuZKKr+xFVzc/23outy8KVBx3ifvx9Gz2vq0NggFeZ21m1MZ6oan5UD/e9KnM605E9GQRX8yY4whuTm4EWXauzfVXiWeM3LT5Gy66OXzTFlVVhGmxALFBQugWqtT6stf5IKXW/UuoXpdRfwLyzbUAp9a1Sqr9S6kal1IxS87sWrXu6YdgfuB/oqZTyLJpfUym1Syn1CbbqW5RS6kml1Dql1Fal1CultvdH0W24O4ruFHFKSvJJwkq9KUNCfUlJcvzQ2r41nnsHfMrYkT9yYL/tkS21Y0LZvOEwmSdOkZdbwMrl+0hOdP0HnjEklMLkkje0OTkJY8jZn/Pne0tfclYtd3keyi8InZlSPK0zU1G+Z68mmtrcgHXPegCsSYcw1GoMXlXBzQNjgzYo/xCnc0pKO0VEiHfxdHiwF0lpOfYxqTnMX3mYwTc1cFhfKRj63Bz6jvqD6bN3O50PQHJSJuHh/sXToeH+JCVnOsRt3XyIAX3eYeSIL9i/z/GCPWf2Jnr1dmwoXC3SUnIIDiv52wWHepOWYv+3O3bkBNlZ+Tz90J88du8vLPyn5MuUxWJl1F0zuPOGb2nRNpIGjV3zJSXAw5/0/PTi6fT8DAI8/O1iFh5dRIR3BO9d9y6vXvsKP+2Zhi5qBCkUr7R/iQ+6vMeOtJ0cOOnYYLhYxqAQLKlJxdOWtGSMQWd//3j1uJW8jatKZhgMhLz3I2HfzyV/81oK9+5wOqek1GwiQn2Kp8ODfUg64++XlJLN/OUHGHxLo7NuZ/bifdwUW/esyyt7Tmc6kZaHf0jJF0e/YE8yU3PLjC3IM7N7fTJNO0VcllxcqQKNYbssKlKXaCNsDaWzuRZoqrVOL+oSPZf5wOdKKe+iOzAGAdOLlnUEDmqt/1NKLQF6A78VLasPPKC1HqmU6gnUxfYAPAXMUkpdp7VeBgwpyqMKticYz9Rap130Kz6tjC+a6oxv6vWvieC3OaPx8vJgZdxenhkzjRl/PUbN2iHc/UAnHn/we6p4uVO3XhhG02U4mcqqHJzlW3uVlm3wvaUv8Q/e4/o8LuhuaRtDnaaY2txA3qdP2KKSj1K45Bc8h7+Bzs/FmnAArBbnU7qAv9/Ez1YzbkgbjEbHv81Pk28mLMibtBO5DHl2DrWj/GjTxLmLoy7jb6POOHbXNIxkzoIX8fL2IG7pTsY8OpW/5jxXvLywwMzSxTt4fMxNTuVSkZV1Cp95hlksmv27U3jj41vJzzfzxNDfqd84jMga/hiNBqb8byDZWfm89tQcDv2XRs06rhiO4Hien5lq46BGHPk/9u47vKny///4807SvWdaOlgtskH2XgIKIiqg4B4gLvSriFscIPhRceNW3IgIDhSU0YqAgGwoQ/Yq0D1o6U7u3x8JbUOKjBTa+ns/risX5Jz75LySnpzc533uk+Qd4pX1rxLuFc6E9uN5dtUuiixFaDTPrX4BL5MXD7QZR5RPFEdOHKn+TKcpkrm3ao93/6FkPFnpeNZqJf3hm1E+vgQ/+Qqm2EaUHXLxNG2V7z3H+1PfXcGEsV2rfO8BlJRaSFx5gPFjqmnsb23MdKqq/m6nqQ5vW51KgxbBtf506P8PalOHzYFS6l2gB7ZxbO8Ci7XWWf++lI19wN/vwFVKqTnAlcBj9tk3ALPs/58F3EJFh+2g1nq1/f8D7beN9vu+2Dpwy4AHlVLX2qfH2Kc7dNgqf0fLa9NHc9toxwHflYWZ/UmtVBVLTztOaLifQxsf34rxTd16NmHa1PnkZJ8gMMiHq4a146phtoHSH7y9hDBz9ZfQLWmpuIVXjM0xhZuxZKQ7tXNv3ITwJydxdPw9WI87V3RcpXMzUAEVR/UqIBR93HmzUBENcR/xEMWfToSCvPLplrULsay1DVt0u+J2dG6Gy5nMod4cq3QEnZJRQHiw42mOrbszGP/SHwDkHC9i2drDmIyK/t0aYA6xVXhCAr3o360+W3ZmuNxhM0cEkpKSU34/LSWH8HDH7cK30jbVs3dzpk6eS3Z2PkFBturAiuX/0LR5FCGhjtvif0louA8ZqRV/u4y0EwRXqpaebOMfEIunlxueXm60bBvJ/t2ZRNcPLG/j6+dBq3b1WL/qcLV02LKLswn2qDgNHewRRE5xjkObHvV6MP+AbYhMWmEaGYUZRPpEsr9SNa2wrJCd2TtpFdrS5Q6bJTMNY2hFBdEYEo41y3kfYKofR+D9T5M56SF0nvM+QJ/IpzhpAx7turrcYTOH+XIsLb/8fkpGPuGhjn+/rbvSGD/ZdmImJ7eQZX8fxGQ00L9HI8B2gUDz+DBCg6s+NflfyHSqwFBPctIrKmq5GUUEhFQ9hnbjn3XndKiqVScNq19tenbbgPLLs7TW92P7QrmTn84nqlroX3wHXI/tVOtarXWe/fe9hgPPKqUOAO8Ag5RSJz+RKq9DAS9prdvab3Fa60+VUn2A/kBXrXUbbB06py1da/2R1rqD1rrDv3XWAJq1qEfyoUyOJmdTWlrGkt+30qP3JQ5tMjPyyqsm25OS0VZNQKDtzZyVads5pBzLYWnCDgYMqv4B4kU7tuIWE4spMgpMJnz7D+LE8j8c2pjMEUT8701SJz1J6eGD1Z4BwJq8ExVaDxVkBqMJU5veWLavdmijAsPwuHUiJbNeRWec8iHlE1DextiyO2WblrqcqdUlYRw8epzklDxKSi0s+HMf/brEOrRJ+GIkiV/abgN7NOTZcd3o360BBUWl5BeUAFBQVMpfG47QpEFQVas5Jy1axnDoYDrJyZmUlpTx+28b6d3X4RodMtKPl29TSVsOYrVqAgMrPlh+W7CBQYOdr5j8L2nSPJyjh3NIOXKc0lILyxbtoUvPBg5tuvRqyLZNx7CUWSkqKmXntlRiGgaSm11Ifp5trFhxURmb1iQ7dOJcsf/4fsK9zYR6hmJURjpFdGJj+iaHNplFmTQPbgaAv7s/Ed4RpBem4+fmi5fJdrrLzeBG8+BmHKt0scL5Kt29HVNkDMbwemAy4dVzIEVrlju0MYaaCX7yZbLffA7L0YpxnAb/QJSP/TShuwcebTpRluz6PqJV03AOHskl+dhx23svcTf9ujZwaJMw81YSv7XdBvaO49n/61XeMQKYn1i9px5rY6ZTxVwSSPqRE2SmnKCs1MrGpUdo0cX5dH7hiVL2bsmkZTfXL6QRrqtNFbZEYKpS6l6t9fv2aa4cXiwFPgXuouJ0aH9gs9b68pONlFJfANcAy09ZfiEwWSn1jdY6XykVBZQCAUC21rpAKdUU2xWtLjGZjIx/cjAP3/sVFqtmyDWX0igunB9nrwXg2us78sfi7fw4ex1GkwEPDxOTXh5Rftrt6Udmk5tbgMlkZMJTV+LvfwEGtVsspL82lXpvfogyGDn+64+U7N+L/7W2r884/uNsgu68F6N/AGETngFAWywk3zmyenNYrZT8/B4eY6aAwUDZ2kXo1IOYugwGoGz1Atz634Ty9sP92nG2HFYLxW8/CIDHrRNR3n5gsVDy07vlFye4wmQ0MPG+rox++nesVs3wgU2IbxDErPm2iz9GXdnstMtmZhcyblICYBsPNaRvY3p2iD5t+7POZDLy5NPDuPeuj7BarVxzbSfi4iOYPWslANeP6sbiRZuZPWslJpMBDw83Xn7tlvJtqrCwhNUrdzHx+etcznIuZt45iT5N2hHqG8jhqfN47tePmbHylwu2PqPJwL2P9uSZB3/FatUMvKop9RsHM3+ubXzVlcNbENswiPZdY7jvptkYFFx+dTMaNA5h/+5MXnshEavVirZqevaPo/Mpnb3zZdVWvtn5DY+0exiDMrD86AqOnjhKn2jbV6ssTf6TX/b/yugWdzK5ywugFN/vnkN+aT7RvtGMaTEag1IoZWBt6lo2Z2yphlAWcj96lZDn37Z9rUfCL5Qd3of3FcMAKPj9B3xHjcHgF0Dg3Y8DtvdexiO3YQgKJeih58BgAGWg8K8lFK9zfYyryWhg4gM9Gf34PKwWzfBBzYhvGMKsebYLbEYNbfmvyxcWlfLX+sO88HAfl7PU5kynMhoNDL+/FR8+tRqrVdN5YCyRDfz569cDAHQf0gCApL+OcUn7MDw8a1NX4fRqamzZxaKqGutSU5RSkdi+1qMzkI6t4vUBtp9t6KC1Hmdv1wDYDaRWWvxhbKc+f9Vaz7G3m47t4oJwewfrc2B15QsblFJDgXvtN4evClFK/R9w8jsP8oGbsX078U/YfhdsJ7YK4PNa66Wne16ZRd/WnhfZLrvvlJqO4KReT9c7KtXN695+Z25UA4pjTz9YuaZ4jZtc0xGc7PnfqJqO4OTFNUk1HcHJlOm1LxNA5Hs313SEOuG30sNnblQDBjd4tXoumz5Lx0vmXrTPWn/34Rf1uUHtqrChtT6G7as8qvJ5pXYHALcq2nx/yuONA8ZVun97FeucR8U3ELc8Zd5bwFtVrGfQaTIKIYQQogZczN8SrQn/7WcnhBBCCPEfIB02IYQQQoharladEhVCCCGEOB+G/3gN6r/97IQQQggh/gOkwiaEEEKIOk8uOhBCCCGEEDVKKmxCCCGEqPP+61+c+99+dkIIIYQQ/wFSYRNCCCFEnSc//i6EEEIIIWqUVNiEEEIIUefJGDYhhBBCCFGjpMImhBBCiDpPxrAJIYQQQogaJRU2IYQQQtR5MoZNCCGEEELUKKmwCSGEEKLOk98SFUIIIYQQNUpprWs6w3+e5o/a9yIfSarpBM6OH6/pBE5Kf99Y0xGqZLokrKYjONnfvWlNR3AS98Ssmo7gxPLelJqO4ERl7K/pCFUrKajpBE70/oM1HcFJVodLazpClUI9b1YXdYX6In7Wqr4X97khFTYhhBBCiFpPOmxCCCGEELWcXHQghBBCiLpPWy/eui76CVGpsAkhhBBC1HpSYRNCCCFE3XcxK2w1QCpsQgghhBC1nFTYhBBCCFH3SYVNCCGEEELUJKmwCSGEEKLukwqbEEIIIYSoSVJhE0IIIUTdZ5UKmxBCCCGEqEFSYRNCCCFE3Sdj2IQQQgghRE2SCpsQQggh6j6psAkhhBBCiJokFTYhhBBC1H3/8QqbdNhqieXLtjFlymysVisjruvO2LFXOMz/+++d3H/f+0RHhwIwYMCl3D/uSgD69XsKHx9PjAYDRqOBuT88VT2Z1hxkyvQVtkyDmzP2xvZVtkv6J5WR4+by+sSBXNE7jn2Hshk/eWH5/MPHjvPg7Z25bUSb6sm14QhTPlmH1aoZMSCOscNbVp1rdwYjH/+d1yf05Ipu9cunWyxWRkxYQHiINx8+069aMqn6bTH1uRMMBixbE7Cu/dFxfqOOGLvdYNuhaAuWpZ+hj/4DviGYrngQ5R2IRmNNWox14/xqybR8RyZTf9yNVcOIzpHc1b++w/yEpHTe/m0/BqUwGhRPXhtH+0aBAHy+9DBzVh9FKUWTSB+m3tAUDzejy5nWrTrEh6+twGrVXH51M66/rZ1Tmy3rj/DR639RVmbFP9CTVz68hpLiMh67+2dKSyxYLFZ6XNaIm8d2cjnP2fj0lqcZ0qo7aXnZtJp800VZJ8Dy5duYOuV723Y+oht3jb3cYf6av3dx//0flO8T+g9oy/33Dwbgsn7P2PYJRts+Yc7cJ6on0+r9THkrwZZpSGvG3tK5ynZJO44x8u5veP2Fq7ii7yUAfP7dOub8sgWlFPGNQnnpqUF4eLj+EVQb91PLk9KY+u02rFozomcsdw2OqzrT/hxGTVnB6/e04/IO9QB4esZmlm5JJdjPg18m93Y5y0mr/9rDmy8vxGrVXHXtpdwyurvD/A1rD/DEQ7OJjAoEoHe/ptx5Ty8AZn/zN/PmbkRrzdDh7Rh5c9V/d3Fh1akOm1LKAiRVmnSN1vrAadreDnTQWo9TSj0P5GutpymlPgd6A7mAJ/Ct1vqFM6z3dmCR1vqo/f4B+2NnuPJ8TrJYrEya9C0zPvs/zOYgrhvxEv36tSYurp5Du/Yd4vnww/urfIwvvxhPULBvdcSpyPTWMma8OhRzmC/X3fs9/bo1JK5BsFO7aR+tokeHmPJpjWKD+OnjUeXze1//Of17NKy+XB+uYcYL/TGHeHPdo7/Rr1M0cTGBzrm+3ECPtpFOj/Hlr//QKDqA/MLSasmEMmDqdxelP0yCvExMN76Mde9ayEoub6IPJ1H29Vpb89D6mK58hNIvHrR13pZ9jk7bD26euN30KtaDmx2WPR8Wq2by3F18ek9bzIEeXP/GOvq2DCUuwqe8TZcmQfRrGYpSip1H83n4i20seLIzqTnFfL08mV8f74Snu5GHP9/Kgo1pXNvJ+bU8p0wWK++9spwp068iNNyHh26bS5eeDYhtVLFN5ecV8+4ry5n81pWER/iRk1UAgJu7kZfeG4qXtxtlZRYm3PUTHbrG0rRVhEuZzsbnq+Yzfekcvrz92Qu+rpMsFiuTJ33HpzMexGwO5PrrXqZvv9bExTn+Ddq3j+ODD++r8jG++PIhgoKqeZ/w+mJmvHE95nA/rhvzFf16NCauYahTu2nvL6NHpwbl01LT8/hqzgbmf30Hnh5uPDRxHvMT/mHY4KoPts4pUy3bT1msmsnfbOXTRzpjDvLi+snL6dvWTFw9P6d2r83ZQfeWYQ7Tr+kezY2XNeCJTza5nKV8XRYrr039nTc/vIlwsz9jbvyEHn2a0LCx47rbXBrLq9NHOUzbtzuNeXM38sk3ozG5GXnkvpl06xlHTP2Qassnzk5dG8NWqLVuW+l24Dwf51GtdVugLXCbUupM79LbgXpnaHPetmw5QGz9cGJiwnB3NzH4yo4kJGy5UKs7u0z/pBEbFUBMvQDc3YwM7hdPwsr9Tu2+/jGJgb0aExzkXeXjrNqQTEy9AKIi/Ksn1+5MYiP9iInws+XqUZ+Evw8755q/k4Fd6xMc4OkwPSXjBH+uO8J1A6o+4j0fKiIOnZMCualgLcO6cwWGxh0dG5UWVfzfzQO0tv3/RI6ts2Zvo7OSUb6OHzbnY8uh48SGehET6oW7ycDgS80kbnU8vvDxMKGUAqCgxIKqNM9i1RSVWimzWCkstRLu7+Fypl3b0qgXHUBklD9ubkZ6DYxj1bIDDm2WLtxNtz4NCY+wfbgFBtu2K6UUXt5uAJSVWbGUWUEpLoblezaRdeL4RVnXSVu2HCA2NoyYmFDbPmFwexITNl/UDE6ZdhwjNjqImKhA23uvf1MSVuxxavf13A0M7B3vtE+wWKwUFZdRVmalsLiU8FAfp2XPOVMt3E9t2ZdDbLgPMWE+tvdepygSN6Y6Z0rYz4D2kYT4Ob63Ol4SQqCPm8s5Ktux9SjRMUFERQfh5mbksitasHzpzrNa9sD+DFq0jsLTyw2TyUDb9rEsSzy7ZS86q/Xi3WpAXeuwOVFKHVBKhdr/30EptfQcFj/5aX7CvvyzSqm1SqmtSqmPlM0IoAPwjVJqk1LKy77MA0qpDUqpJKVUU1eeQ2pqNpERQeX3I8yBpKZmO7XbtGkfVw+dzF1j3mH37qPl0xWK0aPfYtiwqXz33XJXolRkysgnMrzi6Dwi1JfU9BOObdLzWbxiH6OuanHax1nwx26u7BdfLZkAUrMKiKy0o48I8SE1q9CxTWYBi/8+xKjLndc79dN1TLitXXlHpVr4BqPzKnWG8rNQvs5Hn6pxJ9xuexvTNU9Rtvhd58fxD0OFNUSn7HY5UlpOMRGBFZ1Vc4AHqbnFTu0Wb0ln8Et/c+/HW3jxBttmbA704I4+MVw2aRW9nluJn6eJ7k1d70Rmpp8g1FzxtwsN9yHzlG3qyKEc8vOKefyen3nw1u9JmF/xwWCxWBl302xuvPxzLu0UTdOWZpcz1VZpqTlERFbsE8wRQaSm5jq127RpP9dcPYWxd0133CcoxejR7zB82EvM/m5FtWRKTc8nMryiShQR5kdqev4pbfJYvGw3o65p6zDdHObHnaM60m/4h/S85j38fDzo0cn1alZt3E+l5RQSEVzpvRfkSWrOKfuo7EKWbEhhVJ/6py5+QaSnHSe8Umc0PNyf9NQ8p3ZbtyRz23Uf8sh9M9m3Jw2ARnFhbF5/iNycAooKS1m1Yg+pKRf3AEbY1KlTooCXUmqT/f/7tdbXnufjvKqUegaIA97WWqfZp0/XWk8CUEp9BQzRWs9RSo0DJmit19nnAWRordsppe4DJgBjzjMLaOdJp3YoWrSIJTFxCj4+nvz5ZxLj7n+fhYsmAzDz20cxmwPJzDzOnXe8RaNGEXTs6OLOp8pMjvenvruCCWO7YjRW3e8vKbWQuPIA48d0dS3LmXKdcn/qp2uZcGs7p1x/rE0mJMCTlnEh/J2UUn2ZnBJQUUGrPGnvGkr3rkFFNcfY7QbK5lY6E+/miWnIo5T9+RmUFDote66qeJmqSsmA1mEMaB3G2r05vL1gP5/d15bcglISt2aweGIX/LxMPPz5NuatS2FoB9dOP1bxkjhlslg0e/5J56V3h1JcXMYjo3/kkpZmousHYjQamP7N9eTnFfPiY79zYG8mDRr/N0/LVPn3O+XFat4ihoTEyfZ9wlbGjfuQhQtt29TMmY8Qbg4kMzOP0Xe+TcNG5ouzT3grkQn39HZ67+UeLyJhxR6WzB6Ln58HD02cx7yF2xh6+ek7UdWW6SLvp6rezh1DvfTtdh4Z0Qyj4eJUiavMdMoLdUmzSOb+/iDe3u6sXL6bJx/+nu9+uZ8GjcK46Y5uPHT3N3h5uxPXxIzRVEtrPXLRQa1SaD+V6apH7R0xXyBBKdVNa70S6KuUegzwBoKBbcAvp3mMH+z/rgeGnTpTKTUWGAvwwYfjGTt2yGnDmCOCOJZSUVFLSc0hPDzQoY2vr1f5/3v3bsULL3xLdlY+QcG+mM22tiEh/vQf0JYtW/a7vHM2h/lyLK3i6DklI9/pFMbWXWmMn7wIgJzcQpb9fRCT0UD/Ho0A22Dg5vFhhAZXfRrivHKFeHMso+IIOiXzBOHBXg5ttu7JZPw0W6UxJ6+YZRuOYDIoNu/OIHFtMn+uP0JJqYX8glIefWMFrz7cw7VQ+Zkov0rjeHyD0SeyTttcH9mOCjCDpx8U5YHBiGnIo1j/WY7e87drWezMgR6k5FSchk3NLSY84PSnNTs2DuRwZiHZ+SX8vSeHqBAvgn3dAejfOoyNB3Jd7rCFhvuQkVrxt8tIO0FwmI9TG/+AWDy93PD0cqNl20j2784kun5geRtfPw9atavH+lWH/7MdNrM5kJRjFfuE1JRswsMDHNo47hNaMumFWWRn5xMU5Et4+T7Bj/7925C05YDr+4RwX46lVVRlUtLzCA91HCO3dWcq45+37TJzcgtZtmo/JqOBsjIr0ZEB5ackB/SKZ2PSUZc7bLVxP2UO8iIlq9J7L7uI8EDHoRlbD+bwyIcbbJnyS1iWlIbRYKB/uwszJjPc7E9apapYWtpxQsMd/3Y+vhX7h24943lt6m/kZBcQGOTNVcMu5aphlwLwwduJhJurZ4iLODe1tJt8TsqoeB6e/9bwVFrrfGAp0EMp5Qm8B4zQWrcCPj7D4508v2Shio6v1vojrXUHrXWHf+usAbRqVZ+DB9JIPpxBSUkZC+avpV+/1g5t0tNz0fbDpC1b9qOtmsAgHwoKisnPt+0cCgqK+euvHTSJjzrzkz+DVk3DOXgkl+RjxykptbAgcTf9ujZwaJMw81YSv7XdBvaO49n/61W+EwSYn1i9p0MBWsWHcPBYHsmpebZcKw7Sr1OMQ5uEj4aR+LHtNrBrLM/e3Zn+XWJ55JZ2/PnpcBI/HsZrj/Skc+sI1ztrgE7ZgwqKBP9wMJgwXNIDvW+dY6OAih2xCm8IRpOtswYYB9yHzkrGuuF0xwbnrlWMHwfTC0nOLKSkzMqCjan0beE4OPxgekH5NrXtcB6lFiuBPm5EBnmw+UAuhSUWtNas3pVN43DXxxs1aR7O0cM5pBw5TmmphWWL9tClZwOHNl16NWTbpmNYyqwUFZWyc1sqMQ0Dyc0uJD/P9pYrLipj05pkh07cf02rVvU5eDCN5GT7PmHBevr+6z7hAFprAgNt+4QTp+wT4pu4PgS3VdNIDh7OJvloju29t+Qf+nV3HAua8P1YEufcTeKcuxnYpwnPPtKf/r3iiTT7sXnbUQqLStFas2r9IRo1cL2zXRv3U60aBnAw9QTJ6QW2996aI/Rt63j6fsnLl5Hwiu02sH0kz97c8oJ11gCatqhH8qEsjiZnU1pqIeH3bfTo3cShTWZGfvn2tD3pCNqqCQi0HRRkZ9oOtFKO5fJnwj/0H+RiZfRC0daLd6sBda3CVpUDQHvgN2D4uSyolDIBnYF3qOicZdgrbyOAOfZpeYCf8yNUD5PJyMRnRzJ6zNtYLVaGD+9GfHw9Zn27DIBRN/Ri4cINzPp2GUajAU9Pd157fQxKKTIzjzPu/g8A2xifIUM60rOX628mk9HAxAd6MvrxeVgtmuGDmhHfMIRZ87baMg3996u7CotK+Wv9YV54uI/LWZxy3dWJ0S8k2HL1jyM+NpBZv++y5bqiyRke4QLQVsoSP8Ft2ERQBizbEtGZhzG0HgiAdcsiDPFdMDTvA5YyKCuhbP7rAKh6TTE274M1/SCmm6YBYPlrJvrABpcimYwGnhnehDEfbsZq1QzrHEl8pA+z/joCwKjuUSzaks7Pa1NwMxrwcDPw+q0tUErRpn4Al7cJZ/hr6zAaFM2ifLm+m+sf+EaTgXsf7ckzD/6K1aoZeFVT6jcOZv7cbQBcObwFsQ2DaN81hvtumo1BweVXN6NB4xD2787ktRcSsVqtaKumZ/84Op/S2btQZt45iT5N2hHqG8jhqfN47tePmbGy+jrXVTGZjDwzcSRjRk/HarUybHhX2z5hln2fMKoXixZu5NtZyzEZDXh4uvHaa3fa9wl5PDDuQwDKLFaGDOlAz57VsE8wGZg4vj+jx8/BarUy/MpWxDcKZdZPm2yZThm3VlmbFvUY2LcJw+78EpPRQLMm4Ywc2vq07c86Uy3cT5mMBp65qQVj3vjb9t7rEUN8lB+zlh60ZTrDuLVHPtzAmp2Z5OSX0GfCEsZd3YQRPWNdy2Qy8PCTVzD+3plYrJoh17ShUVw4P85eD8C117fnj8U7+HH2OkwmA+4ebrzw8rDy06ZPPfI9x3MLMZkMPPLUIPz9vf5tdeICUbqqk9u1lFIqX2vte8q0nsCnQCrwN7av2+hzll/r4Q4kAA9qrbVS6kVgFLZO4GHgoNb6eaXUcGAqUAh0BXbYHztDKdUBmKa17nO63Jo/at+LfCTpzG0utuO1byBr6e8bazpClUyXhJ250UW2v7tL195cEHFPzKrpCE4s702p6QhOVIbzlZW1QklBTSdwovcfrOkITrI6XFrTEaoU6nnzxRmkd1Lutxfvszbghov73KhjFbZTO2v2acsBp7KK1vpz4HP7/5+vNP32f3n8Z4Bnqpg+F5hbaVKDSvPWAX3OlF0IIYQQ4nzVqQ6bEEIIIURVtLZctHVd9PIa/42LDoQQQggh/tOkwiaEEEKIuq+GfoHgYpEKmxBCCCFELScVNiGEEELUff/xXzqQCpsQQgghRC0nFTYhhBBC1H1SYRNCCCGEEDVJOmxCCCGEELWcnBIVQgghRN0np0SFEEIIIURNkgqbEEIIIeo+qbAJIYQQQoiaJBU2IYQQQtR98tNUQgghhBCiJkmFTQghhBB1n4xhE0IIIYQQNUkqbBfDxsSaTuDk23azazqCkw4djDUdwUl0r+iajlAlU+dGNR3ByYtrkmo6ghPLe1NqOoIT431P13QEJ0vn5dR0hCr1eLNLTUdwYs0qqukITkK7DKzpCLWDVNiEEEIIIURNkgqbEEIIIeo+qbAJIYQQQoiaJBU2IYQQQtR98j1sQgghhBCiJkmFTQghhBB1n4xhE0IIIYQQNUk6bEIIIYQQtZycEhVCCCFE3SenRIUQQgghRE2SCpsQQggh6j75Wg8hhBBCCFGTpMImhBBCiLrPqms6wQUlFTYhhBBCiFpOKmxCCCGEqPtkDJsQQgghhKhJUmETQgghRN33H6+wSYetlli+6RhTvtiE1aoZ0a8hY69uVmW7pL1ZjHwmgdf/rwtXdImhuMTCzS/8QUmpBYtVM7BzNA9e1/K8c0Re3pP2bz2NMhrY+8n3bH/5Y6c27d96mnqDe1NWUMTq258ge+N2AC558FYa33UdKMXej79n51tflC/TZNzNNBl3M9ayMo7O/5NNj7963hm9u/Yg/JEnwWAk9+c5ZH/xicN8t/oNiXh2Ch5Nm5P5/ltkf/1Z+bzAUTcTcI0tY+5P35Pz7VfnnaMywyUdcL/mXjAYKPv7d8oSv3OYb2zXD7e+1wOgSwopmfMO+tg+AEw9r8HUeTAoKFv9G2XLf6yWTMuT0pg6M8m2TfWqz11XxlfZLmlfNqNeXM7r93bg8o71AHj6040s3ZxKsL8Hv7zYt1ryALQMacmNl9yAQSmWHVnOggO/Ocz3MnkxtuUYgj1DMCoDvx9cyIqjf2EymHiyw+OYDG4YlYF1qev5ad/P1ZJp+fJtTJ3yve11GtGNu8Ze7jB/zd+7uP/+D4iODgWg/4C23H//YAAu6/cMPj6eGI0GjEYDc+Y+US2ZzuTTW55mSKvupOVl02ryTRdlnQBBfXoQN+lplMHAsW/ncPhdx/2DV+OGNH3jJXxbNmf/y2+S/OGM8nmdVydQln8CrBZ0mYUNg0dUS6blu7J5acEBLFbNiPZm7uod5TA/YUcW7yw5jFJgMiieGNyA9g38ATheWMazP+1ld2oBSilevLYxbWP9XM60Yv9x/rc0GYtVM7xVCGM6RTjMT9yTwzsrj2FQCqMBnugTTbso3/L5Fqtm5Dc7Cfd1471rG7ucB2DZ8u1M+d8PWC1WrhvelbF3DXCY//ea3dz3wMdER4UAMKB/a8bdN4ji4lJuuvUtSkrKsFisXD6wLQ+OG1wtmcS5OasOm1IqBEiw340ALEC6/X4nrXVJpbYPAR9prQvs9w8AeYAGsoFbtdYHqyO8Uuph4CXArLXOtU+7HeigtR53Do8TD7wBNANygOPAc1rrZWex7AH7+jLONf9JFquVSTM2MOPp3phDvLjuqSX0a1+PuOgAp3bTZm6hRxtz+TR3NwOfT+yNj6cbpWVWbnoukV5tI2kbH3LOOZTBQId3nyVxwB0UJqdy+do5JM9L5PiOveVt6g3qhV98A36JH0hI5zZ0fP95FnW5noAW8TS+6zoWdroOa0kpfX//hKPzl5K35yDhfToTffVlLGh9FdaSUjzCgs/3pQKDgfDHnuHIuDGUpqZS/4vvOLHsD0r2V2S0Hs8l7bWp+Pa+zGFR98ZxBFxzHYduG4kuKyXq7Y84sWIZpYdd3ByVAfdh4yj+8Al0bgaeD72DZdsqdOqh8iY6K4Wi9yZAYT6Gph1xv+4hit9+EBXRAFPnwRS99QBYSvG4ayqWHX+jM466FMli1Uz+agufTuiKOdiL6ycto2/bCOKi/Jzavfb9Drq3DHeYfk2PWG68rCFPfLLRpRyVKRS3NL2JaRteI6som2c7T2RT+iaOnjhW3qZfdF+O5h/jrU3v4Ofmy9TuU1l1bDVl1jJeWT+NYksxRmXkyY5PsCUziX25+1zKZLFYmTzpOz6d8SBmcyDXX/cyffu1Ji4u0qFd+/ZxfPDhfVU+xhdfPkRQkG+V8y6Uz1fNZ/rSOXx5+7MXb6UGA/FTnmXLDXdSfCyVdgu+J3NRIgW7K957ZTm57Jn4IiFX9K/yITZfdytl2TnVFsli1bz4y34+uaM5Zn93Rn6QRN9mQcSFe5e36dIogH7jglBKsTPlBONn7WL+Q5cC8NL8A/SID+TNGy6hpMxKUanrFRqLVfNi4mE+Hh5HhJ8bI7/ZSd/GATQO8arIFOtH38YBtkzphUz4dT+/3NG8fP7XG9NpFOxJfonF5Txg284nTfmezz6+H7M5kBEjp9Gvb0un7bxD+8Z8+N7dDtPc3U18MeMBfHw8KC21cOMtb9KrZzPatmlYLdmqlVwlClrrTK11W611W+AD4I2T9yt31uweArxPmdZXa90aWAo841pkBzcAa4Frz/cBlFKewHxsnczGWuv2wANAoyraXpCK5JY9WcRG+BJj9sXdZGRwt1gS1jl/YH/9+x4Gdooi2N+zciZ8PN0AKLNYKbNYUeeZI6RTa/L3HOTE/mSspaUcnDWf6KsdOz1RV1/G/i9/AiDz7824B/rjGRGGf7PGZKzejKWwCG2xkPbnWqKvtR3Bxd97A9v+9xHWklIAitOzzjMheLZoRenhQ5QeSYayUo4v/g2f3v0c2liysyjevhXKyhymuzdoTFHSZnRxEVgsFG5Yi28fx+d3Pgyxl6Azj6KzUsBSRtnGPzG26ObQxnpgOxTm2/5/cAcq0FatMYTHYD20A0qLwWrFsjcJY6vuLmfasi+b2HAfYsJ9cDcZGNwpisSNKU7tvl6yjwEdIgnx93CY3vGSEAJ93V3OUVmjgEakFaSRXpiBRVtYk7KGS8MudWrnabJt3x5GT06U5mO1/9xMsaUYAKMyYlJG0K7vnLdsOUBsbBgxMaG4u5sYPLg9iQmbXX7cC235nk1knTh+Udfpf2lrCg8couhQMrq0lLSfFxByueP7pzQzi7zNW9GlZad5lOqVlJxPbIgnMcGeuJsMDGoVSuKObIc2Ph5GlLLtFQtLrOX/zy8qY92B4wxvbztYcTcZ8PdyfReflFJAbKAHMYEeuBkNDGoaROLeXIc23u6VMpVaqbzTTskrYdm+XIa3OveD7tPZknSQ+jEV2/mVg9uR8EfSWS2rlMLHx7Z/KCuzUFZmKc8uLq7zvuhAKXWZUmqjUipJKTVDKeWhlHoQqAf8oZT6o4rFVgFR9uUbKKX+UUp9opTaqpT6RinVXyn1l1Jqt1Kqk71db6XUJvtto1LKzz69MeCLrQN4wynriVFK/a6U2qmUes7e/mWlVPkhslLqeaXUI8BNwCqt9byT87TWW7XWn1dq95FSahHwpVIqRCm1yJ7lQzjv/lG51KxCIkMq+rgRwV6kZhWe0qaAxWuPMGqAc3ncYrVyzeOL6D52Ht1amWlzHtU1AK8oMycOV3yoFySn4h1ldmjjHWWmwKFNCt5RZnK37iK8VwfcgwMxenlSb3AvvGNspwH8mzQgvGcHBq6ezWVLvyK4Q6vzygdgCjNTllqx/rLUFNzCwv9liQole3fjdWkHDAEBKA9PfLr1wmSOPPOCZ6ACQtE56eX3dW46KuD0fwNT5yuw/rMWAGvKAQyNWoG3H7h5YGzWERUY5nKmtOwiIoIrjujNwZ6kZp+yTWUXsmRDCqP6NnB5fWcjyCOQrOKKznpWcTZBHoEObRIOJxLpE8kbvV5jctcXmLlzFhpbx0yheKHLc7zV+w22ZW5n3/H9LmdKS80hIjKo/L45IojU1Fyndps27eeaq6cw9q7p7N5dcTCllGL06HcYPuwlZn+3wuU8tZl7hJnioxXV0OJjKXhEmP9lCUdaa1p/+yntfptL5E3XV0um1OMlRARUHGxE+LuTdrzYqd2S7Zlc+eZG7vlqBy/aTzEezi4m2MfE0z/sZdi7m5n4414KqqGilZZfQoRfxcGO2dedtLxS50y7c7jqs+3c9+NeJg+sXz795aVHGN8riursE6Wm5hARGViRyRx42u186LX/Y8zd77N7T8Xf2mKxcvWwl+nW8ym6db2ENq0bVF+46mS1XrxbDTjfwwlP4HPgMq31LqXUl8C9Wus3lVLjsVXUqjpFeAXwU6X7ccB1wFhslbIbgR7AUOAp4BpgAnC/1vovpZQvUGRf9gbgW2A5cIlSKlxrnWaf1wloCRQAa5VS84FZwJvAe/Y219vzPARsOMPzbQ/00FoXKqXeBlZorScppa60Z692p75Zp36xiQk3tsZocO5jGw0Gfnp5IMdPlDDutb/YdTiXJjEBTu3OeaXYdrJn0+b4P/vY/vIn9Fs8g7L8ArI370SX2XZ+ymTEPcifRV2uJ6RjK3rMfpN5jc6zslXl+s9u0ZID+8j68hOip3+KtaCA4t07wXKhKgFVhzI0boOp0xUUTX/Y1irtMKWJs/G8+3/o4iKsR/eBxfWdQVVrP/Wo+KWZW3nkumYYDRfraLmKv90p91uGtOBQ3iFeWf8q4V7hTGg/nmdX7aLIUoRG89zqF/AyefFAm3FE+URx5MQRlxJV/To53m/eIoaExMn4+Hjy559bGTfuQxYufAGAmTMfIdwcSGZmHqPvfJuGjcx07Fj1WME6r6rN5ByqnJuuuZGS1DTcQoJpPWsGBXv2kfv3OpciVbn2KvYR/ZuH0L95COv2H+ftJYeZcWdzLFbN9mMneGpIQ9rE+DF1/n4+WXaEB/vHVnumqjpf/eMD6R8fyLrkfKavPMonI+JZui+XYG8TLczerDmc51KOM2dyDNWieTSJi1/Ax8eDP5dt4/4HPmHRbxMBMBoN/PzD4xw/XsD9D37Crt1HaRJfr9ryibNzvhU2I7Bfa73Lfv8LoNe/tP9DKZUG9AdmVpq+X2udpLW2AtuABG3rISQBDext/gJet1fvArXWJz9hRwGz7Mv+gK3jd9Ji+2ncQvu8HlrrjUC4UqqeUqoNkK21PsQplFI/2it+P1SaPM/+WNif59cAWuv52MblOVFKjVVKrVNKrfto7r/3B83BXhzLLCi/n5JVSHiQl0ObrfuyGf/WKvqN+5VFfyczacYGlqx1/LDy93GnU/Nwlm86xvkoTE7BJ6ZicKx3tJnCo2kObQqSU8orZ7Y2EeVt9s2Yw+/th7Gk982UZOWQt/ugfZlUDv+wGIDMtUloqxWP0CDOR1laCiZzxfpN5gjKMtL+ZQlHx+f9wKFbRpB8961YjudS4ur4NUDnZjhUxVRAGDrX+bSvimyI+/UPUzzjOSio2Blb1vxO0Rv3U/zeI1CQh85wrRMCYA7yJKVSlTY1q4jwQE+HNlsP5PLI++u5bMJiFq07yqSvtrBkw/ltO2cjuzibYI+K8YvBHkHkFOc4tOlRrwfr02zvl7TCNDIKM4j0cayCFpYVsjN7J61Cz//impPM5kBSjlW8hVNTsgkPdzzY8fX1wsfH9tr17t2SslIL2dm209vh5kAAQkL86N+/DUlbDricqbYqOZaKR72Kv4VHZATFqWf/3iuxty3NzCLjtyX4tW3tcqYIf3dScisqainHSwj3O/2p/A4N/TmcVUT2iVLM/u6Y/T1oE2Mb1zmwRQjbj55wOZPZ152UvIqRQqn5JYT5up0+U7Qvh3NKyC4sY+OREyzdm8vAT7bx6PwDrDmcx+MLDricKcIcSMqxnIpMqTmEh/s7tLFt57ZqZe9eLSgrs5Bl385P8vf3pnOneJav2OFypgviP15hO98O27lu1X2B+tg6ZZMqTa9cu7ZWum/FXv3TWv8PGAN4AauVUk2VUq2BeGCxfdD/KBxPi556QHHy/hxgBDASW8UNe6Z25Q21vha4Hag8Mv7U53vGw0qt9Uda6w5a6w5jh7f717atGgdzMCWf5LR8SsosLFh5iH7tHY9eEt65ksTpQ0icPoSBnaN59s529O8YRdbxIo6fsO0cikrKWJWUSqN6/lWt5owy1ybhF98AnwbRGNzcqD/qSo7MS3Roc2ReIg1vvQaAkM5tKM3NoyjFdjrw5MUE3jGRRA8byIFvfwUg+aclmPt1AcAvvgEGdzeKM6rs555R0fatuMXWx1QvCkxu+A8YxIllVZ19r5oxyJbRZI7Er29/8hYuOK8clVkP70SFRqGCI8BownRpbyzbVjm0UYFheNz+LCXfvuLcIfMNLG9jbN2Dso1n/3xOp1XDQA6mnSA5/QQlZVYWrDlC30sdT18tebU/CdMGkDBtAAM71OPZW1rTv53rp4hPZ//x/YR7mwn1DMWojHSK6MTG9E0ObTKLMmkebLtC2t/dnwjvCNIL0/Fz88XLZDuIcTO40Ty4GcdOuN65bNWqPgcPppGcnEFJSRkLFqynbz/HjkR6em55pXnLlgNorQkM9KGgoJgT+baCf0FBMX/9tYP4Jv/dqsPxTUl4NayPZ0wUys2N8KsHk7ko8cwLAgYvL4w+PuX/D+rdnRM7d51hqTNrGeXLwcwikrOKKCmz8ltSBn2bOh4MHswsLP/7bT+aT6nFSqC3iTA/dyIC3NmfbjuwWb03l8bhXk7rOOdMEd4cyikmObeYUouV3/7Jpm8jx4OAQ9nFFZlSCyi1aAI9jTzcsx4JY1uyaEwLXr2yAZ1i/Hh5cAOXM7VqGcuBQ+kcTs6kpKSM+Qs20K+v49CU9PTjlbbzg1itmqBAH7Ky8jh+3FZQKCoqYeWqnTRqePanwkX1ceWUaAOlVJzWeg9wC/CnfV4e4Ac4nBK1n058CEhSSr14titSSjXWWifZl+sKNAU6A89rrV+q1G6/UurkQIABSqlgoBDbadU77dNnAR8DoUBv+7SZwJNKqaGVxrGdetFEZcuwjXt7USk1CDi/UlElJqOBiXe0Y/TUZVitmuF9GxIfE8CsxXsAGDUg7rTLpmcX8cT7a7BYNdqquaJrDH3bn9+HhrZYWDduEn0XfoIyGtk3Yy652/cQd/coAPZ8OIujC/6k3uDeXLVnMZaCQlbf8VT58j3nvoNHSCDW0jLW3f8CpTm2QdH7Zsyl84ypDE76BWtJKatvc+GrDywW0l+ZQvTbH4PRwPF5P1Kybw8Bw0YCkPvDdxhDQon9YjYGH1/QVgJH3cLBkVdhPXGCyJffwhgQCGWlpL7yIta8ahi4bbVS8sN0PMZOBWWgbM1CdOpBTF2vBKBs1XzcBt6M8vbHfdgDAGirheI3bRcye9w2EeXtD9YySn54p/ziBFeYjAaeuakVY15bjdWqGdYzlvgof2b9cQDgjOPWHvlgPWv+ySAnv4Q+4xcx7ppLGNGr/r8ucyZWbeWbnd/wSLuHMSgDy4+u4OiJo/SJtr0Vlyb/yS/7f2V0izuZ3OUFUIrvd88hvzSfaN9oxrQYjUEplDKwNnUtmzO2uJQHwGQy8szEkYwZPR2r1cqw4V2Jj6/HrFm2C8RHjerFooUb+XbWckxGAx6ebrz22p0opcjMzOOBcR8Ctgt+hgzpQM+eLVzOdDZm3jmJPk3aEeobyOGp83ju14+ZsfKXC7tSi4U9z0ym1cxPUQYDKd/NpWDXHiJvsb33jn31HW5hobT/bQ5GX1+wWom+61bW9rkSt+AgWnw6HQBlNJL2069kL3V9zJ/JqHh6SEPu+mIHVqvm2vbhxJu9mbXGNs51VKcIFm/L4udN6ZgMCk83A6+NbFJ+OvDpIQ157PvdlFo00cEeTBl2+n3tWWcyKJ7qG83dc/di0ZprW4YQF+rFd5ttH4kj24SyeHcO83Zk2TKZFNOGNLigA/lNJiPPPj2CMWPfw2K1MvzaLsTHRfKtfdzlDSN7sHDRJr79bgVGowFPTzden3YbSinS0o/zxFNfV3zGXN6Wvn1cr26Lc6ecxiidaQGlngfygY3ANGydvrXYxrAVK6UeAO4Hjmmt+576tRdKqXeANOAr4FetdUv79M/t9+copRqcnGdv3xfbV4lsx1b9+gcYpLX+p1Ku14FU+20w4INtjNxMrfULldolARla676VpjUFXsfWGUzF1ul8RWu95OTz1VpPs7cNwTZ2LhRbJ3UY0P7fvtZDb5xY6641/rbd7JqO4KRDB2NNR3AS3Su6piNUyXN4m5qO4GT0ifO/+vdC+bT/jTUdwYnxvqdrOoKTpfNyajpClXq82aWmIzixZhWdudFF5jb6jpqOUDXT5Rf1clK9+bmL9lmr2rxw0S+VPecKm9b6+Up3na7J11q/A7xT6X6DU+Y/UOluy0rTb6/0/wMn553S/iSnL4DRWo+vdPfzKsPb2jldomjv+FX5TYCnPF+01pnAwEqTHj7duoQQQgghqoP80oEQQggh6r7/+E9TyY+/CyGEEELUclJhE0IIIUTdJz9NJYQQQgghapJU2IQQQghR98kYNiGEEEIIUZOkwiaEEEKIuk8qbEIIIYQQoiZJhU0IIYQQdd65/nKTKy76zxwgFTYhhBBCiFpPKmxCCCGEqPtkDJsQQgghhKhJ0mETQgghRN1ntV682xkopa5QSu1USu1RSj3xL+06KqUsSqkRZ3pM6bAJIYQQQlQTpZQReBcYBDQHblBKNT9Nu5eBhWfzuNJhE0IIIYSoPp2APVrrfVrrEmAWcHUV7R4A5gJpZ/OgctGBEEIIIeq+2vPj71HA4Ur3k4HOlRsopaKAa4F+QMezeVCpsAkhhBBCnAOl1Fil1LpKt7GVZ1exyKm9yTeBx7XWlrNdp1TYLgLVtl9NR3CyeNHRmo7gpF2HpjUdwYnp89U1HaFKqa8uq+kITqbUnqPbcqrt/pqO4GTpvJyajuCkz9DAmo5Qpayhg2o6ghNvk39NR3Cm5KMcuKhf66G1/gj46DSzk4GYSvejgVM/dDsAs5RSAKHAYKVUmdb6p9OtU/7KQgghhBDVZy0Qr5RqCBwBRgE3Vm6gtW548v9Kqc+BX/+tswbSYRNCCCHEf0Et+eJcrXWZUmoctqs/jcAMrfU2pdQ99vkfnM/jSodNCCGEEKIaaa0XAAtOmVZlR01rffvZPKZ02IQQQghR99XCcbTVSa4SFUIIIYSo5aTCJoQQQoi6r5aMYbtQpMImhBBCCFHLSYVNCCGEEHWfVNiEEEIIIURNkgqbEEIIIeo+uUpUCCGEEELUJKmwCSGEEKLukzFsQgghhBCiJkmHTQghhBCilpNTokIIIYSo++SUqBBCCCGEqElSYRNCCCFE3fcf/1oP6bDVEsuWb2PKlNlYrVauG9GdsWOvcJj/9987ue/+94mODgVgwIBLGXf/lQD06/cUPj6eGIwGjEYDP8x9qloytQxpyY2X3IBBKZYdWc6CA785zPcyeTG25RiCPUMwKgO/H1zIiqN/YTKYeLLD45gMbhiVgXWp6/lp38/Vkglgw6rDfPzGaqxWzYChlzDi1jZObZLWH+XTN1dTVmbFP9CTqe8PKZ9nsVh55I6fCQnzZuJrl1dLJlW/LaY+d4LBgGVrAta1PzrOb9QRY7cbQFtBW7As/Qx99B/wDcF0xYMo70A0GmvSYqwb51dLJo9Lu+A/ejwYDBQsmceJH750mO/Z63J8r70FAF1USO6Hr1B2YDe4uRMy5QOUyR2MRopWJZI/6+NqyxRw1yO2TIt/Jn+uYyav3pfjO+zW8kw5779cnil06ocoN3umlQnkfVs9mZav3s+UtxKwWjUjhrRm7C2dq2yXtOMYI+/+htdfuIor+l4CwOffrWPOL1tQShHfKJSXnhqEh0f17FaD+vQgbtLTKIOBY9/O4fC7js/Xq3FDmr7xEr4tm7P/5TdJ/nBG+bzOqxMoyz8BVgu6zMKGwSOqJdO/+fSWpxnSqjtpedm0mnzTBV/fSatW7OaNlxdgtWqGDmvHraN7Ocxfv3Y/j/3fTOpFBQHQ57JmjL6nLwDffb2Kn+euR6O5elh7Rt3SrVoyrVi+g5df+gGrRTNsRBdG39XfYf7aNbv5v3GfEhUVDMBlA1pzz322ff7x4wU8/+x37Nl9DKVg0os30KZtQ5czLVu+jSlTv8dq1Vw3ohtj73Lc9/29Zhf33f9BxWdM/7aMu39w+XyLxcrw6/6HOTyQDz+4z+U84txd0A6bUsoMvAF0AbKBEuAVrfWP/7pg9edoAfwItNFaF9qnzQe+0lrPOqVtH+BnYD+2U8ZpwI1a6zSl1O1AB631OKXUNcAurfV2V/NZLFYmTfqWz2b8H2ZzECOue4l+/VoTF1fPoV2H9vF8+OH9VT7GF1+OJzjI19Uo5RSKW5rexLQNr5FVlM2znSeyKX0TR08cK2/TL7ovR/OP8damd/Bz82Vq96msOraaMmsZr6yfRrGlGKMy8mTHJ9iSmcS+3H0u57JYrHw4bSUvvD2IkHAfJtzxM516xhLbMKi8TX5eMR+8upLn37yCsAhfcrIKHR7j1++2EdMgkIITJS7nAUAZMPW7i9IfJkFeJqYbX8a6dy1kJZc30YeTKPt6ra15aH1MVz5C6RcP2jpvyz5Hp+0HN0/cbnoV68HNDsueF4MB/7GPkvX8A1gy0wh95XOK1yynLHl/eRNL6lEyn7kXfSIPj3ZdCbj3CTIfHw2lJWQ9ez+6qBCMRkKmfkTxhlWU7trqcqaAux8j87lxWDLTCJv2BUVrllN2uCJTWepRMp66pzxT4P1PkvHonVBaQubE+8ozhf7vY4rWu57JYrEy6fXFzHjjeszhflw35iv69WhMXMNQp3bT3l9Gj04Nyqelpufx1ZwNzP/6Djw93Hho4jzmJ/zDsMEtXcoEgMFA/JRn2XLDnRQfS6Xdgu/JXJRIwe695U3KcnLZM/FFQq7oX+VDbL7uVsqyc1zPcpY+XzWf6Uvn8OXtz160dVosVqZN/ZW3P7qNcLM/d9zwIT37NKVh43CHdm3b1ee16Tc7TNu7O5Wf565nxsyxmNyMPHTvV3TrdQmx9UNczjT1xTl89Mm9mM2B3DDydfr0bUnjuAiHdu3aN2L6+2Odln/5pR/p3qMpr795B6UlZRQWub6fslisTJr8HZ99+iBmcyAjrn+Zfn1bExcX6dCuQ/u403bGvvzqDxo3iiA/v8jlPBeMjGE7P0opBfwELNNaN9JatwdGAdFnubyxurJorbcBPwBP2x/7GsCtis7ayQ7scq11W611a2AtUFUv6RqgeXXk27LlAPVjw4mJCcPd3cSVgzuSkLClOh76vDUKaERaQRrphRlYtIU1KWu4NOxSp3aeJk8APIyenCjNx6ptb5hiSzEARmXEpIygq6dUvXt7OhHR/kRE+ePmZqTngEasWXbQoc2yhXvp2qcBYRG2DmxgsFf5vIy0E6xbeZgBQy+pljwAKiIOnZMCualgLcO6cwWGxh0dG5VW2sm5eVS8HidybJ01exudlYzyDXY5k1t8cyzHkrGkHoWyMgpXLMajk2PloXRnEvpEHgAlO7diDKn4kNNF9k6u0YQymqrl7+cW34KylEqZli/C89RM/5w5kzKawGgCXM+0ZccxYqODiIkKxN3NyOD+TUlYscep3ddzNzCwdzzBQd4O0y0WK0XFZZSVWSksLiU81MflTAD+l7am8MAhig4lo0tLSft5ASGXX+bQpjQzi7zNW9GlZdWyTlct37OJrBPHL+o6t29NJjo2mKjoYNzcTAy4ohXL/vjnrJY9sD+dFq2j8fRyx2Qy0q5DA/5McPn4m61JB4mNDSU6JhQ3dxNXDLqUPxKTzmrZ/Pwi1q/by7DhXQBwczfh7+99hqXOzPYZE0ZMTKj9M6Y9CYmbz3r5lJRslv65lREjurucRZy/C3nRQT+gRGv9wckJWuuDWut3lFINlFLLlVIb7LduYKtuKaX+UErNBJLs035SSq1XSm1TSpUfjiilRiuldimlliqlPlZKTbdPD1NKzVVKrbXfTm5hk4DrlFJtgf9h74QppZ5XSn2klFoEOJyfsXc6/bBVBytP7wYMBV5VSm1SSjV25YVKTc0mIrKiQmSOCCQ1Ndup3aZN+xh69WTG3PUOu3cfrRyI0aPfYtiwqXz33XJXopQL8ggkqzir/H5WcTZBHoEObRIOJxLpE8kbvV5jctcXmLlzFtr+IapQvNDlOd7q/QbbMrez7/h+qkNmegGh4RUfiiHhPmSmFzi0OXo4l/y8Yp6+91fG3/YjiQt2l8/75I1V3DauE0pVSxwb32B0XkbF/fwslK/zUbpq3Am3297GdM1TlC1+1/lx/MNQYQ3RKbud550jY3A4lozU8vvWzDSMIWGnbe/dfyjFG1ZVTDAYCH39K8yf/07x5jWU7t7meqaQMIdMljNlGjCUolMyhb3xNeYvF1K8aQ2lu1zPlJqeT2S4X/n9iDA/UtPzT2mTx+Jluxl1TVuH6eYwP+4c1ZF+wz+k5zXv4efjQY9Orp+6AnCPMFN8tKKaXXwsBY8I81kvr7Wm9bef0u63uUTedH21ZKqN0lPzCDcHlN8PN/uTnubcaUzafJibR7zLQ/d+yb49aQA0ijOzacNBcnMKKCosYeXyXaSmut7hTE3NxRzhuD9PS8t1ard50wFGXPsK9479gD27bX/r5MMZBAf7MvHpmVw/7FWemziLgoJi1zOl5RBROZM5iNRU50ybNu1n6DVTGDN2usNnzNSX5vDohGsxGKpzx1n9tEVftFtNuJCnRFsAG04zLw0YoLUuUkrFA98CHezzOgEttdYnP+Hv1FpnKaW8gLVKqbmABzARaAfkAYnAycOFt4A3tNYrlFKxwEKgmda6QCk1AVgGvK61rvyp2B7oobUutJ8S7amU2gSEACcAh0FhWuuVSql5wK9a6znn/Mqcoqo/vTqlR9GiRSyJiVPw8fHkzz+TuH/c+yxaOBmAb2c+itkcSGbmce648y0aNYqgY8d4F1M5vzFPzdkypAWH8g7xyvpXCfcKZ0L78Ty7ahdFliI0mudWv4CXyYsH2owjyieKIyeOuJiJKis9pya1WDR7/8lg8vTBlBRbeGzMPC5pGc7RQ7kEBnkR1zSUpPVHnR7n/FWxE6sip967htK9a1BRzTF2u4GyuS9UzHTzxDTkUcr+/AxKCp2WrY5Ip6uSubdsj3f/q8h4qtLpGauVjPG3oLx9CXriFUyxjSg75Oop7Sq2qdPs99xbtce7/1AynnTMlP7wzSgfX4KfrKZMVaz/1M781LcSmXBPb4xGx+Pb3ONFJKzYw5LZY/Hz8+ChifOYt3AbQy9v4VomOKe/X1U2XXMjJalpuIUE03rWDAr27CP373Wu56pl9Fn8AZs2i+SnhePx9vZg5fJdPPbQTOb8+hANG4Vxyx09eGDsF3h7uxN/SQQmYzXUMKqKdMoftFnzGBYueQ5vHw+W/7mdhx74lF9/fwaLxcqO7ck88dQwWrdpwP+m/sCMTxIY9+Bg5wc9l0hnsZ23aB5DYsJk+2fMVu4f9yGLFr7AH38kERzsS8sWsfy9ZpdLOYRrLtrXeiil3lVKbVZKrQXcgI+VUknA9zieWlxTqbMG8KBSajOwGogB4rF16v7UWmdprUvtj3FSf2C6vcM1D/BXSvkBaK1/AXKA906JN+/k2Da7k6dEY4DPgFfO4/mOVUqtU0qt++ijX/+1bYQ5iJRjFRW11JQcwsMDHdr4+nrh42M7/di7dyvKSi1kZdsqAWazrW1IiD8D+rdlyxbXq1nZxdkEe1Scmgv2CCKnOMehTY96PVifZuuTpxWmkVGYQaSP45iIwrJCdmbvpFVoNYzrwVZRy0g7UX4/M+0EwWHeTm3adYnG08sN/0BPWlwawYHdmezYksqa5Qe565pZTJv4B1vWHeX15/5wPVR+Jsqv0pgn32D0iazTNtdHtqMCzOBpr+wYjJiGPIr1n+XoPX+7ngd79Sq0oiJjCAnHkpXh1M5UP46A+58i66VH0XnO1QVdkE/J1vV4XNq12jMZQ8KxZqVXmSnw/qfJmvooOs+5CqBP5FOctAGPdq5nMof7ciwtr/x+Snoe4aGOY0G37kxl/PO/0G/EhyxauotJry1hybLdrFp3kOjIAIKDvHEzGRnQK56NSdVzIFByLBWPehXvJY/ICIpT085+eXvb0swsMn5bgl/b1tWSq7YJN/uTVqlSlJZ6nLAwP4c2Pr6eeHt7ANCtZxPKyqzkZNv2IUOHtefL2ffyweej8ff3IjrWtfFrAOaIAFJTHPfnYeH+Dm18fT3x9rFl6tm7OWVlFrKz8zGbAzGbA2jdpgEAAwa2Ycd2F8ezAhHmQFIqZ0rNJjw8wKGN42dMS8rKbJ8xGzbuJfGPJPpd9gzjH5nB6r93MuGxz1zOdEFY9cW71YAL2WHbhq0CBoDW+n7gMiAMeBhIBdpgq6y5V1qu/NPYXu3qD3TVWrcBNgKeVH38eZLB3r6t/Raltc6rNN9qv1V2gtObB/T6l/lV0lp/pLXuoLXuMHbskH9t26pVfQ4cTONwcgYlJWXMX7CWfv0cd7Dp6blo+2HSli37sWpNUKAPBQXF5YNACwqK+euvHcQ3iTrXuE72H99PuLeZUM9QjMpIp4hObEzf5NAmsyiT5sHNAPB39yfCO4L0wnT83HzxMtnGjbkZ3Gge3IxjlS5WcEV8szCOHT5O6tE8SkstLF+8j0496zu06dwzlu2bU7GUWSkuKmPXtnSiGwRy630dmfHLjXz80ygmTO5L6w71GP9CX5cz6ZQ9qKBI8A8HgwnDJT3Q+06pZgRUDDhW4Q1tY7CKbJulccB96KxkrBt+cTnLSaW7d2CMjMEYHgkmE149BlC8dplDG0OomaDH/0fOm89jOXq4Yrp/IMrb3mlx98CjTSfKjhyohkzbMUXGYAyvZ8vUcyBFaxxP4RtDzQQ/+TLZbz6H5eghx0w+p2RKdhy7eD5aNY3k4OFsko/mUFJqYcGSf+jXPc6hTcL3Y0mcczeJc+5mYJ8mPPtIf/r3iifS7MfmbUcpLCpFa82q9Ydo1MD1D3yA45uS8GpYH8+YKJSbG+FXDyZzUeJZLWvw8sLo41P+/6De3Tmx879ZGWnWIorDB7M4mpxNaWkZi39Pomefpg5tMjPyyved25KS0VZNQKDtIC8r03bQm3Ish6UJOxg4uJXLmVq0jOXgwQySkzMpLSnj99820qev4wFrRvrx8kxJWw5itWoCA30IDfPHHBHE/v22oQN/r95Fo8Znfyr8dJw/Y9bTr++/fcYcKP+MeWT8NSxbOpXEhBd5/bU76dL5Eqa9cofLmcS5u5CnRBOBqUqpe7XW79unnSyFBADJWmurUuo24HQXGAQA2fbTmU2xXW0KsAZ4QykVhO2U6HDsY96ARcA44FUApVRbrfUmF55HD2BvFdPzsI1vc5nJZOTZiSMZM/ptLFYrw4d3Iz6+Ht/Osn3A3jCqFwsXbuDbWcswGg14errz+mtjUEqRmXmc+8fZhglaLFaGDOlIr56un5Kxaivf7PyGR9o9jEEZWH50BUdPHKVPdG8Alib/yS/7f2V0izuZ3OUFUIrvd88hvzSfaN9oxrQYjUEplDKwNnUtmzOq5yIKo8nA2AndeP7/fsNq1Vw2pAmxjYL47YcdAAwa1oyYhkFc2iWaB2/+AYNBMWDoJdRv7PpA/tPSVsoSP8Ft2ERQBizbEtGZhzG0HgiAdcsiDPFdMDTvA5YyKCuhbP7rAKh6TTE274M1/SCmm6YBYPlrJvrA6UYTnCWrheMfTyP4ubfBYKAw4RfKDu/H+/JrAShY+CN+14/G4BdAwN2P2Z6GxULmo7djCAol8MFnwWAAg4GivxIoXveXa3nsmXI/epWQ522ZChJ+oezwPryvGGbL9PsP+I4ag8EvgMC7H7dlslrIeOQ2DEGhBD30nC2TMlD41xKK161wOZLJZGDi+P6MHj8Hq9XK8CtbEd8olFk/bQJwGrdWWZsW9RjYtwnD7vwSk9FAsybhjBxaTZUsi4U9z0ym1cxPUQYDKd/NpWDXHiJvGQnAsa++wy0slPa/zcHo6wtWK9F33craPlfiFhxEi0+nA6CMRtJ++pXspa6/Vmcy885J9GnSjlDfQA5Pncdzv37MjJXVdxBSFZPJyISnruT/7v0Sq8XKkGva0SgunB9m267IHnZ9RxIXb+eH2WswGg14eLgx+ZXryoecPDl+Frm5hZhMBiY8dSX+/l7/trqzzvTU08O5964PsFitXHNtZ+LiI5k9y/Yeun5UdxYv2szsWX9hNNkyvfLabRWZnh7Gk499TWlpGdHRIUyecmO1ZHr2mZGMGTPd9hkzrKvzZ8yijXz77XKMJgOeHm68/tqdTkNzar0aGlt2sShdTVfvVfngSkVi+1qPzkA6tkrWB9jGts0FCoA/gAe01r72itoErfUQ+/Ie2K40jQJ2YqvOPa+1Xmq/AGECcBTYAWRprZ9WSoUC7wLNsHVIl2mt76mU6QC2r+bIsN9/HsjXWk+z3+9Dxdd6KCAXGKO13nXK13p0Bz4GioERWuuqOnU2+o9atxXdseTrmo7g5PEOTc/c6CJr9Pnqmo5Qpcxlrp8mqW66Fn5pZeQnzl+bUNOWtZ1W0xGc9BkaWNMRqpT15sM1HcGJt8n/zI0uMg/lfuZGNcFw2UXt8Vlm3nrRdkLGG7+86L3ZC/o9bFrrY9i+yqMqlQ9Fn7S3XwosrbR8MTDoNMvP1Fp/ZP8qjh+xVdawd8RG/kumBqfcf/6U+0uxVfaqWvZz4HP7//+imr7WQwghhBCuqY0HjdWpLv+W6PP2Cwu2YquG/VSjaYQQQgghLpA6+9NUWusJNZ1BCCGEELXEf3wMW12usAkhhBBC/H9BOmxCCCGEELVcnT0lKoQQQghRziI//i6EEEIIIWqQVNiEEEIIUefJ13oIIYQQQogaJRU2IYQQQtR98rUeQgghhBCiJkmFTQghhBB1n4xhE0IIIYQQNUkqbEIIIYSo87SMYRNCCCGEEDVJKmxCCCGEqPus8ksHQgghhBCiBkmFTQghhBB13398DJvS+r/9BGuDtMIva92LHO4eWdMRnOhNf9Z0BGfutfSYxlQLc/n713SCOsG6ckNNR3ByfOigmo5QpeCH3qjpCE7adq9f0xGcvNUvvqYjVKlXvRfVxVxfyRvDL9pnrfvDcy/qcwOpsAkhhBDiP0B+S1QIIYQQQtQo6bAJIYQQQtRyckpUCCGEEHXff/yiA6mwCSGEEELUclJhE0IIIUTdJxU2IYQQQghRk6TCJoQQQog6T77WQwghhBBC1CipsAkhhBCi7rPIj78LIYQQQogaJBU2IYQQQtR5MoZNCCGEEELUKKmwCSGEEKLuk+9hE0IIIYQQNUkqbEIIIYSo+2QMmxBCCCGEqElSYRNCCCFEnaf/42PYpMNWC/39117eemURVqtmyLVtufnObk5tNq49yNuvLqKszEpAkDfTP72l2nMsW76dKS/NwWqxct2Iboy9a6BjzjW7uG/cR0RHhQAwYEBbxt03qHy+xWJl+HWvYDYH8OH791ZbruWbU5jy5UasVs2Ivo0YO7Rple2S9mYx8tkEXn+wK1d0juZYZgGPv7+GjJwiDEpxfb9G3DoovnoybTzKlM822DJd1pix1zavOtOeTEY+tZjXH+7GFV1jKS6xcPOzSygptWKxWBnYNZYHR7aqnkwbjjDlk3W2TAPiGDu8ZdWZdmcw8vHfeX1CT67oVr98usViZcSEBYSHePPhM/2qJ9Oag0yZvgKr1cqIwc0Ze2P7qjP9k8rIcXN5feJArugdx75D2YyfvLB8/uFjx3nw9s7cNqLNfzITwPJd2by04AAWq2ZEezN39Y5ymJ+wI4t3lhxGKTAZFE8MbkD7Bv4AHC8s49mf9rI7tQClFC9e25i2sX4uZ1q1YjdvvLwAq1UzdFg7bh3dy2H++rX7eez/ZlIvKgiAPpc1Y/Q9fQH47utV/Dx3PRrN1cPaM+oW5/3ahfDpLU8zpFV30vKyaTX5pouyzm6RbXi04+0YlIGf9iTy2bafHeb7unnxYvcHiPQJxagMfLn9V+btWwrATU0Hc21cPzSwJ+cQz618nxJrqcuZtq5JYdb0jVgtmp5XNmLQjc77zZ2b0pg1fROWMo1fgDuPvmX72y3+fhfL5+9HKYhqFMAdj3fEzd3ociZxbi5Kh00pZQbeALoA2UAJ8IrW+seLsf4q8gwCJgM+gAJ+1VpPqIksp7JYrLz+0u+88cGNhJn9ueumGXTvHU/DxmHlbfKOF/HaS7/z2rujMEcGkJ114oLkmPTibD77ZBxmcyAjRr5Kv76tiIuLdGjXoX3j03bGvvzqDxo3NpOfX1R9uayaSZ9tYMaTvTCHeHPdM0vo164ecdH+Tu2mfbuFHq0jyqcZDYrHb2pDi4ZB5BeWMvzpJXRrZXZa9pwzWaxM+mQ9M57tiznYi+ueWES/DlHExQQ4tZv29SZ6tKnI5O5m4PPn+uHj5UZpmZWbnllCr0sjadsk1PVMH65hxgv9ba/To7/Rr1M0cTGBzpm+3ECPtpFOj/Hlr//QKDqA/ELXPyzKM721jBmvDsUc5st1935Pv24NiWsQ7Jzpo1X06BBTPq1RbBA/fTyqfH7v6z+nf4+G/8lMYNt+X/xlP5/c0RyzvzsjP0iib7Mg4sK9y9t0aRRAv3FBKKXYmXKC8bN2Mf+hSwF4af4BesQH8uYNl1BSZqWo1PVvgLdYrEyb+itvf3Qb4WZ/7rjhQ3r2aUrDxuEO7dq2q89r0292mLZ3dyo/z13PjJljMbkZeejer+jW6xJi64e4nOtMPl81n+lL5/Dl7c9e8HUBGJTiiU53cm/CFFILMvlm0Ev8mbyOfblHyttc3+Ry9uUm89DSVwjy8OPHoW+y4MBygjz8uaHpIIb/Mp5iSykv93yIyxt045d9f7qUyWrRzHxrAw+/2ougMG+m3LOENt3qUa9Bxb6vIL+Eb97cwP+93IsQszfHs2377ez0QhJ+2M2kz6/A3cPIB8+vYk3iYbpf0cClTOLcXfAxbEopBfwELNNaN9JatwdGAdFnuXy1duOVUi2B6cDNWutmQEtg3zksf0E7uTu2HiUqJph60UG4uRm57PLmrFi6y6HNkt+20rvfJZgjbR2CoGCfas+xJekA9WNDiYkJxd3dxJWD2pGQuOWsl09JyWbpn9sYMbx6j6K37Mki1uxLjNkXd5OBwV1jSFh/xKnd1wt3M7BTNMEBHuXTwoO8aNHQduTv6+VG4yh/UrMLqydThD2Tm5HB3WNJWJvsnOm3XQzsHENwgGf5NKUUPl5uAJRZrJRZrCiXE8GW3ZnERvoRE+Fny9SjPgl/H3bONH8nA7vWd8gEkJJxgj/XHeG6AXHVkMae6Z80YqMCiKkXYMvUL56ElfudM/2YxMBejQkO8q7iUWDVhmRi6gUQFeFaR7u2ZgJISs4nNsSTmGBP3E0GBrUKJXFHtkMbHw8jtt0rFJZYy/+fX1TGugPHGd7e1pFyNxnw93J9t7V9azLRscFERQfj5mZiwBWtWPbHP2e17IH96bRoHY2nlzsmk5F2HRrwZ8J2lzOdjeV7NpF14vhFWRdAy5A4DuelciQ/jTKrhYUHVtInuqNTOx+TFwBeJk9yS/KxWG2daqMy4GF0x6gMeBrdSS/Mdlr2XO3/J4uwer6E1fPF5GagY78YNv3luN/8e8khLu0ZTYjZto37B1XsE6wWTWmxBYvFSkmxhcAQx/1FrWHVF+9WAy7GRQf9gBKt9QcnJ2itD2qt31FKNVBKLVdKbbDfugEopfoopf5QSs0EkuzTflJKrVdKbVNKjT35WEqp0UqpXUqppUqpj5VS0+3Tw5RSc5VSa+237vZFHgOmaK3/sWcp01q/Z1/mKqXU30qpjUqpJfbKIEqp55VSHymlFgFfKqVaKKXWKKU2KaW2KKWq57wakJ6WR3hExamLMLM/GWl5Dm0OH8wi73gRD4z+itE3fMrvv5x9R+pspabmEhERVH7fHBFEalquU7tNm/Yz9NqXGDP2PXbvPlY+fer/5vLohGswGKqj+1EpV3YhkSEVH5oRwd6kZjl2ulKzClm89gij+jc+7eMkp59gx4Fs2jQOPm2bs86UVUBkaKVMIVVkyixg8ZpkRg107gBZLFaumfAb3Uf/SLfWEbRxsbpWkamiIx8R4lN1pr8PMepy58136qfrmHBbu/JOQHVIzcgnMty3IlOoL6npjtXh1PR8Fq/Yx6irWpz2cRb8sZsr+1XPW642ZgJIPV5CRKWDjQh/d9KOFzu1W7I9kyvf3Mg9X+3gxWtt2/vh7GKCfUw8/cNehr27mYk/7qWgxOJypvTUPMLNFVXjcLM/6WnOHaGkzYe5ecS7PHTvl+zbkwZAozgzmzYcJDengKLCElYu30Vq6sXrRF1M4d7BpBZklt9PLcgkzDvIoc2snb/TMCCKRcM/4Psh03h13edoNOmF2Xy5/Vd+u/Y9Fg//kPzSQlYfc33/npNRSHCl6mxQmDc5GafsD5LzKcgr4dWHljJ57GJWLjxgb+vFwOsv4fGRvzJh+C94+bjRomME4uK7GB22FsCG08xLAwZordsBI4G3K83rBDyttT45GOhOe3WuA/CgUipEKVUPmIjtVOsAoPJJ+beAN7TWHYHhwCf26S2B9afJswLoorW+FJiFrXN3Unvgaq31jcA9wFta67b2PM7llPNVVcf9lA9Ni8XKzh3HeGX6SF577wa++GgFhw5mVrGgCzG0c5BTP7pbNI8hcclk5v34JLfc1Jv7H/gIgD+WJhEc7EfLFrHVmskezDnXKa/P1C83MeGG1hhP01k8UVTGg2+s5Mlb2uLr7VYNmZwnndrPmfrZBibc3Baj0fktZzQa+GnaIJZ+eDVb9mSy61DOhcl0yv2pn65lwq3tnDL9sTaZkABPWsZV8+mqs3md3l3BhLFdq3ydAEpKLSSuPMAVvaup8lcbM1UdyzkY0L95CPMfupTpNzbl7SW2CqrFqtl+7AQjO5n54f42eLkb+GSZcxX63DOd+cVq2iySnxaO5+s593P9jV147KGZADRsFMYtd/TggbFf8NC9XxF/SQSm07yedV8V+51TXrpu9dqwM/sAA+few6j5j/FExzvxcfPCz92HPjEdGPLTOAbOvQcvkweDG/ZwOVFV+/NT/3ZWi5WDu7J58KUePPRqL+Z/tYOUw3mcyCth08ojvPTtlbw65ypKispYvfigy5kuCIv14t1qwEW/6EAp9S7QA9s4tv7AdKVUW8ACNKnUdI3WuvK5iQeVUtfa/x8DxAMRwJ9a6yz7Y39f6TH6A80rfZj7K6XONOo2GvhOKRUJuAOV1z9Pa33ykGQV8LRSKhr4QWu9u4rnORYYC/DqO7dz6+i+Z1i1TZjZj7SUiopaeupxQsN8T2njT0CgN15e7nh5udOmfSx7d6ZV63iQiIhAUlIqSvGpKdmEhzuOyfL19Sr/f+/eLXhh8ndkZeezYcM+Ev9IYtmybRQXl5J/oogJj33BtFduczmXOdibY5kF5fdTsgoID3Isz2/dn8X4d1YDkJNXzLJNKZgMiv4doygts/LgGyu5qnt9BnY6q7PyZ84U4s2xjEqZMgsID/JyaLN1Xxbj31hZkWnDUUxGA/0rZfD3cadTi3CWbzxGk9jAashUUSlKyTxBePApmfZkMn7a8kqZjmAyKDbvziBxbTJ/rj9CSamF/IJSHn1jBa8+7NoHhznMl2Np+RWZMvIJD3U8nb91VxrjJy+yZcotZNnfB22vU49GgO0CgebxYYQGV31q8r+QCWwVtZTciopayvESwv3cT9u+Q0N/Ds8tIvtEKWZ/d8z+HrSJse3uBrYIqZYOW7jZn7TUiip7WupxwsIcd6k+vhXvxW49m/DKlF/JyT5BYJAPQ4e1Z+gw2wUd77+1mDCz4/7kvyKtIBOzd8W+2Owd4nRac2jjPny21XYhwuF82+nTBv71iPQJ42h+GtnFts+AxENraBN6CQv2r3ApU1CYN1lpFfuo7PQCp9OaQWHe+AZ44OFlwsPLRHzrUJL35gAQGuGDX6Ct4ntpzyj2bs2ky4D6iIvrYnTYtmGrcAGgtb5fKRUKrAMeBlKBNtiqfZVHp5d/2iil+mDrgHXVWhcopZYCnlR5KFPOYG/vUPdVSm3DVi3bXMUy7wCva63n2df5fFV5tNYzlVJ/A1cCC5VSY7TWiZUfSGv9EfARQFrhl2d9wrtpi3okH8ri6JEcwsL9SFi4neemXuPQpkefJrzxv4WUlVkpK7WwPeko19/c6WxXcVZatazPgYPpHE7OwBweyPzfNvDaK7c7tElPP05oqB9KKbZsOYDVqgkK9OGR8VfzyPirAduVpDM+S6iWzhpAq8ZBHEzJJznN1gFZsOow08Z1dmiT8NaV5f9/4oM19Lm0Hv07RqG15pmP1tE4yp87rmxy6kOff6a4YA4eyyM5Nd+W6a9DTHvIcexewntDKzJNX02f9vXo3ymarNwiTCYD/j7uFBWXsWpLKmOuaeZ6pvgQe6Y8woO9WbDiINPGO3a4Ej4aVpHprb/o0zGa/l1i6d8llkduaQfA30kpzPh5u8udNYBWTcM5eCSX5GPHCQ/1YUHibqY9PcAx08xbKzK9nECfLvXLO0YA8xOr99RjbcwE0DLKl4OZRSRnFRHu785vSRm8cp3jOg5mFhIb7IlSiu1H8ym1WAn0NqGUIiLAnf3phTQM82L13lwah3udZk1nr1mLKA4fzOJocjZhZj8W/57EpP9d59AmMyOP4BBflFJsS0pGWzUBgbaObFZmPsEhvqQcy2Fpwg4+/voulzPVRtsy9xLrF0E9nzDSCrO4vEE3nlzxtkOblBMZdIpsycb0fwj2DKCBfz2O5KehULQKjcfT6E6RpYROES3ZnnXWQ6xPq0HTINKO5JN+7ARBoV6sTTzMmGcc95ttu9dj5lsbsVislJVa2b8jiwHXNaG4sIx927MoLirD3cPIPxvSqH9J0GnWVLP+6z/+fjE6bInAVKXUvVrr9+3TTh6KBgDJWmurUuo24HQXGAQA2fbOWlNsp0AB1gBvKKWCgDxsHcMk+7xFwDjgVQClVFut9Sb7/R+UUiu01ruUUgbgIa316/b1nDwUPW0PQynVCNintX7b/v/W9ufpMpPJwMNPXM4j936L1Wrlyqvb0DAujJ++t53Fvea69jRoFErnbo24/fqPMSjFkGvb0igu/AyPfK45jDz79PWMuetdLFbN8Gu7EB8fybezbBWZG0b1ZOGijXw7azlGkxFPDzdef+2Oah3zVGUuo4GJt1/K6P8tw2rVDO/TkPjoAGYt2Qvwr+PWNuzM5OcVB2kSE8A1T9oqJg9f34relzpfIXnOmcZ0YPSLS22Z+jUiPiaAWQtthdeqxoidlJ5dyBPTV2OxarSGK7rF0rdD1Gnbn1Omuzox+oUErBbN8P5xxMcGMut32wUso66ovg7rOWV6oCejH59nyzSoGfENQ5g1b6st09Cqv3bkpMKiUv5af5gXHu7zn85ky6V4ekhD7vpiB1ar5tr24cSbvZm1JsWWq1MEi7dl8fOmdEwGhaebgddGNil//z09pCGPfb+bUosmOtiDKcNcP11rMhmZ8NSV/N+9X2K1WBlyTTsaxYXzw+y1AAy7viOJi7fzw+w1GI0GPDzcmPzKdeWZnhw/i9zcQkwmAxOeuhJ/f9c7kWdj5p2T6NOkHaG+gRyeOo/nfv2YGSt/uWDrs2grL6+dwXuXPYVBGfh571L25SYzIr4/AHN2L+HjpB94oeu9zL7yVZRSvLXxG3KK88gpzmPJob+ZOfh/WLSVf7L2M3f3EpczGY0GbnzwUt58bBnaquk+qCFRDQNYOs+23+wztDGR9f1p2SmCF0YvQilFzyttbQDa947mxbFLMBgVsfGB9BrS6N9WJy4QVeW57epeie0U4xtAZyAdW7XqA2xj2+YCBcAfwANaa197dWuC1nqIfXkPbFeaRgE7gTDgea31UvupxwnAUWAHkKW1ftpexXsXaIatY7pMa32P/fGGAC9g6zhqYL7W+lGl1NX2nEeA1UBHrXUfpdTzQL7Wepp9+SeBm4FSIAW48eRp2aqcS4XtYgl3d62TciHoTa5dun5BuNfSryo01cJc/tVzheR/nXXl6Yb01pzjQweduVENCH7ojZqO4KRt99p3KvCtaq7wVpde9V68sEfwpzjxYP+L9lnr8/aSi/rc4CKNYdNaH8P2VR5VaV3p/0/a2y8FllZavhg43R5lptb6I/vXbfyIrbKG1joD24UMVeX5Ffi1iuk/Az9XMf35U+6/BLx0mjxCCCGEENWqFh6mn7PnlVL9sY1pW4StEieEEEKI/4/IGLZarrb8QoEQQgghxIVS5ztsQgghhBD/9R9//69+c6EQQgghxH+GVNiEEEIIUef918ewSYVNCCGEEKKWkwqbEEIIIeo8q4xhE0IIIYQQNUkqbEIIIYSo82QMmxBCCCGEqFHSYRNCCCGEqOXklKgQQggh6jxttdZ0hAtKKmxCCCGEELWcVNiEEEIIUefJT1MJIYQQQogaJRU2IYQQQtR58rUeQgghhBCiRkmF7SIIcA+r6QhOdPremo7gRB9JqekITlTXLjUdoWqqFh5rFefXdAInev/Bmo7gxJpVVNMRnHib/Gs6QpXadq9f0xGcbPqr9m1TgYPa1nSEWkHGsAkhhBBCiBolFTYhhBBC1Hkyhk0IIYQQQtQoqbAJIYQQos6zSoVNCCGEEELUJKmwCSGEEKLOk6tEhRBCCCFEjZIKmxBCCCHqPLlKVAghhBBC1CjpsAkhhBBC1HJySlQIIYQQdZ6cEhVCCCGEEDVKKmxCCCGEqPPkaz2EEEIIIUSNkgqbEEIIIeo8bbXWdIQLSipsQgghhBC1nFTYhBBCCFHn/dfHsEmHrZZYsXwHL7/0A1aLZtiILoy+q7/D/LVrdvN/4z4lKioYgMsGtOae+64A4PjxAp5/9jv27D6GUjDpxRto07ahy5mW/32AKe8sxWq1MuLKloy9qVOV7ZJ2pDDyvlm8/txgrujTBIDPZ29gzvwklFLENwzlpScG4uFRPZvb8n+ymDpvH1arZkSnCO7qF+MwP2FrJm8vPIBBKYxGxZNDG9G+YQD70woY//U/5e0OZxXxwOX1ua1nlOuZVu9nylsJtkxDWjP2ls5VtkvacYyRd3/D6y9cxRV9LwHgy9nr+f6XLWituW5oa267voPLeWyZ9jHlzQTb3++qNoy9pcvpM439itcnDeWKvk3tmdbx/bzN9kxtuG1kx+rJtOYgU6avsGUa3JyxN7avOtM/qYwcN5fXJw7kit5x7DuUzfjJC8vnHz52nAdv78xtI9q4nikpjanfbsOqNSN6xnLX4LiqM+3PYdSUFbx+Tzsu71APgKdnbGbpllSC/Tz4ZXJvl7NUtmL/cf63NBmLVTO8VQhjOkU4zE/ck8M7K4/ZtnMDPNEnmnZRvuXzLVbNyG92Eu7rxnvXNq6eTLVwP9Utsg2PdrwdgzLw055EPtv2s8N8XzcvXuz+AJE+oRiVgS+3/8q8fUsBuKnpYK6N64cG9uQc4rmV71NiLXU505l8esvTDGnVnbS8bFpNvumCrw9g4+pkPntzDVaL5rKr4rn21tZObbZtOMZnb63BUqbxC/Bg0nuDALhv2Pd4erthMCqMRgMvz7jqomQWji54h00pZQbeALoA2UAJ8IrW+scLve5/yfQzEK617lpTGSqzWKxMfXEOH31yL2ZzIDeMfJ0+fVvSOM5xB92ufSOmvz/WafmXX/qR7j2a8vqbd1BaUkZhUUm1ZJr0ZiIzXhuGOcyP6+6eSb/ujYlrEOLUbtqHK+jRsX75tNT0fL6au5H5X96Gp4eJh577lfmJOxk2qIXruayayT/u5dOxLTEHeHD925vo2yKYOLNPeZsu8YH0a9EOpRQ7j57g4a93sOCxDjQM9+bH8e3KH6fP5L/p3zLkdKs6+0wWK5NeX8yMN67HHO7HdWO+ol+PxsQ1DHVqN+39ZfTo1KB82q596Xz/yxZmf3wzbiYjdz3yPb27NqZBTJDrmV5bzIw3R9ozfUG/HnFVZ3pvKT06VXxw7tqXzvfzNjP7k1vtmWbTu1tjGsQEu57prWXMeHUo5jBfrrv3e/p1a0hcg2CndtM+WkWPDhUd8UaxQfz08ajy+b2v/5z+PVz/sLdYNZO/2cqnj3TGHOTF9ZOX07etmbh6fk7tXpuzg+4twxymX9M9mhsva8ATn2xyOcup63sx8TAfD48jws+Nkd/spG/jABqHeJW36RLrR9/GAbbtPL2QCb/u55c7mpfP/3pjOo2CPckvsVRPplq4nzIoxROd7uTehCmkFmTyzaCX+DN5Hftyj5S3ub7J5ezLTeahpa8Q5OHHj0PfZMGB5QR5+HND00EM/2U8xZZSXu75EJc36MYv+/50OdeZfL5qPtOXzuHL25+94OsC29/u02l/M/GtgQSHe/Pk6F/p0DOWmIaB5W1O5BXz8bTVPP36AMIifMnNKnR4jOenX4F/oOdFyXu+5HvYXKCUUsBPwDKtdSOtdXtgFBB9lssbL0CmQKAdEKiUqnKPr5S6qJXHrUkHiY0NJTomFDd3E1cMupQ/EpPOatn8/CLWr9vLsOG26ombuwl/f2+XM23ZkUJsVCAx9QJxdzMyuN8lJKzY69Tu6x82MbB3HMFBjuu0WKwUFZdRVmalsLiM8FBfp2XPK9ehPGJDPYkJ8cLdZGBw2zASt2U5tPHxMGLb9KCgxIL9vw5W784hJsSLqCDXd0BbdhwjNjqImCj7a9W/KQkr9ji1+3ruBgb2jnd4rfYdyKJNi0i8PN0wmQx0vDSGJct2VVOmwIpMlzUjYflu50xz1jOwzyWnZMqkTYt6FZnaxrBkmfOy55zpnzRiowKIqRdg36biSVi53znTj0kM7NXYaZs6adWGZGLqBRAV4e96pn05xIb7EBPmY9ueOkWRuDHVOVPCfga0jyTEz8NhesdLQgj0cXM5x6mSUgqIDfQgJtADN6OBQU2DSNyb69DG271iOy8stUKl7Twlr4Rl+3IZ3sr1A5KTauN+qmVIHIfzUjmSn0aZ1cLCAyvpE+1cDfYx2Tq6XiZPckvysdgHpxuVAQ+jO0ZlwNPoTnphtsuZzsbyPZvIOnH8oqwLYM/2DCKi/TBH+eHmZqR7/4asW37Ioc2KRfvp3Ls+YRG2fXVAsFdVDyVq0IW+6KAfUKK1/uDkBK31Qa31O0qpBkqp5UqpDfZbNwClVB+l1B9KqZlAkn3aT0qp9UqpbUqp8kM3pdRopdQupdRSpdTHSqnp9ulhSqm5Sqm19lv3SpmGA78As7B1Hk8+1udKqdeVUn8ALyulGiulfrevd7lSqqm93VVKqb+VUhuVUkvsFUSXpKbmYo6oqKiYIwJJS8t1ard50wFGXPsK9479gD27jwGQfDiD4GBfJj49k+uHvcpzE2dRUFDsaiRSM/KJDK+oMkSE+ZKake/YJj2fxcv3MGqoY2ndHObLnaPa0+/6T+g57CP8fDwcKnCuSDteTERgxYemOcCd1Fzn57s4KYPBr6zj3hnbePG6Jk7zF2xO58pLw5ymn4/U9FNfKz9S0099rfJYvGw3o65p6zA9vlEoazclk51bSGFRKX+u2sextLxqyJRHZHhFhyYi/BwzbT7smCnV9Q8X2zZV0XGPCPUlNf3EKZnyWbxiH6OuOn01dsEfu7myX7zLeQDScgqJCK7otJuDPEnNcawspGYXsmRDCqP6VM82fFa58kuI8HOvyOXrTlqe86m6JbtzuOqz7dz3414mD6zI9/LSI4zvFVXlwcr5qo37qXDvYFILMisyFmQS5u1YnZ6183caBkSxaPgHfD9kGq+u+xyNJr0wmy+3/8pv177H4uEfkl9ayOpjW1zOVBtlpRcQUuksRHCYD5npBQ5tjh7O5UReCc/d/xuP3fELf/5W6aBTKV58aBGP3fELi3/aebFinzOrVV+0W0240B22FsCG08xLAwZordsBI4G3K83rBDyttT5Z37/TXp3rADyolApRStUDJmI71ToAaFpp+beAN7TWHbF10D6pNO8G4Fv77YZTMjUB+mutHwE+Ah6wr3cC8J69zQqgi9b6UmydvsfO/DKcQRV/e4XjnrZZ8xgWLnmOOT8+xo039eKhBz4FbJWsHduTuX5kd2b/8CheXu7M+CTB5Uhnk2nqO0uZcHdPjEbHzSg3r4iEFftYMutOlv1wF4VFpcxbtMP1TICuKlcVH0oDWoWy4LEOvHN7c95eeNBhXkmZlcRtmVzeOtR5wfMKdeZMU99KZMI9vZ1eq8YNQrjr5k6Mfng2dz0yh6Zx4ZiM1fC2PKtMCUy4t6pModx1U2dGP/Qdd42ffXEzvbuCCWO7OmU6qaTUQuLKA1zRu+pxZucc6Sy285e+3c4jI5phNFRj7+cMqvo4qGo77x8fyC93NOftqxsxfeVRAJbuyyXY20QLs+sVrDOFqvH9FFW8KKfk7FavDTuzDzBw7j2Mmv8YT3S8Ex83L/zcfegT04EhP41j4Nx78DJ5MLhhj2rIVDecuj1ZLJp9OzN4clp/nnljAHM+28zRQ7YO+YsfDOaVz4fy9Gv9WfjDP2zfmFIDicVFPfWnlHoX6IFtHFt/YLpSqi1gwdZZOmmN1rryuZIHlVLX2v8fA8QDEcCfWuss+2N/X+kx+gPNVcUW6a+U8gO8gThghdZaK6XKlFIttdZb7e2+11pblFK+QDfg+0qPcbKsEw18p5SKBNwB53M6tjxjgbEA099/gDF3DTrt62KOCCA1paIUn5qSQ1i44+keX9+KKkDP3s2ZMvl7srPzMZsDMZsDaN2mAQADBraplh2hOczXodKTkp5PeKiPQ5utO1MZP2kBADm5hSxbvR+T0UBZmZXoSH+CA20fGAN6xrFx61GGDmzmeq4AD1JyKo7MU3NLCPf3OG37jo0COJxZSPaJUoLsp66W/5NN8yhfQitVMFzKFH7qa5XndAp4685Uxj//C2B/rVbZXqv+veIZMaQ1I4bYqpSvf7iMiDDH8VPnl8mPY2kVVbGUtCoy/ZPC+OfmVcq0z56pCSOuasOIq2wD+l//4E8iwqshU5gvx9IqqnwpGVVsU7vSGD95UUWmvw/aMvVoBNguWmgeH0ZocPV0RsxBXqRkFZXfT80uIvyUcTpbD+bwyIe2486c/BKWJaVhNBjo385x7FZ1Mvu6k5JXMcYrNb+EMN/Tn3rtEO3L4ZwSsgvL2HjkBEv35rJ8/3GKy6ycKLHw+IIDvDy4gWuZauF+Kq0gE7N3xWlfs3eI02nNoY378NlW24UIh/Ntp08b+Ncj0ieMo/lpZBfb3ruJh9bQJvQSFuxf4XKu2iY4zJvM1Ipqdlb6CYJDHd9DIWHe+AdE4enlhqeXG83aRnBwTzb1YgMIDrO1DQj2olOvWPbsyKD5pRdu+z9f//WrRC90hW0btvFiAGit7wcuA8KAh4FUoA22ylnlT8/yLUsp1QdbB6yr1roNsBHwpMpDq3IGe/u29luU1joPWyUvCNivlDoANKDSadFK6zUAOZWWb6u1PtnbeAeYrrVuBdxtz+JEa/2R1rqD1rrDv3XWAFq0jOXgwQySkzMpLSnj99820qdvS4c2GenH0fZyQNKWg1itmsBAH0LD/DFHBLF/v23czd+rd9GosctnaWnVNIKDydkkH8ulpNTCgsSd9OveyKFNwnejSbTfBvaO59mH+9G/ZxyRZj82bz9GYVEpWmtWbThEo/quDVgvzxXjx8GMIpKziigps7JgUzp9mzs+9sGMwvLXaltyPqUWTaB3xbHJ/E1p1XY6FKBV00gOHs4m+WiO7bVa8g/9ujtWgBK+H0vinLtJnHM3A/s04dlH+tO/l+20Xma2bbM7mnKcxX/u5sr+rndsWzWNtP39TmZK2EG/HqdkmnMPiXPvJXHuvQzscwnPThhA/15Nqsi0iyv7N3dax7lnCufgkVySjx23b1O76de1gWOmmbeS+K3tNrB3HM/+X6/yzhrA/MTqOx0K0KphAAdTT5CcXmDbntYcoW9bx/fPkpcvI+EV221g+0ievbnlBe2sAbSM8OZQTjHJucWUWqz89k82fRsFOLQ5lF1cvp1vTy2wbeeeRh7uWY+EsS1ZNKYFr17ZgE4xfi531qB27qe2Ze4l1i+Cej5hmAxGLm/QjaXJ6xzapJzIoFOkLWewZwAN/OtxJD+NlBMZtAqNx9No++jpFNGS/cePOK3jvyCuWSjHko+TejSP0lILfy3ZT4cejlfXd+wVy47NaVjKrBQXlbFnWzpR9QMoKiyl8ITtdHxRYSmb1xwlplFgDTyLukUpdYVSaqdSao9S6okq5t+klNpiv61USp3xkvcLXWFLBKYqpe7VWr9vn3ayWx8AJGutrUqp24DTXWAQAGRrrQvs48hOfjfBGuANpVQQkIft1OfJEbCLgHHAqwBKqbZa603YToFeobVeZZ/eEFgMPFN5hVrr40qp/Uqp67TW39svnmittd5sz3PyXX3bebwmTkwmI089PZx77/oAi9XKNdd2Ji4+ktmz/gLg+lHdWbxoM7Nn/YXRZMDDw41XXrutfMDxk08P48nHvqa0tIzo6BAmT7mxGjIZmPhQP0ZP+AGrVTN8cAviG4Yy6+fNAIy6+vTbVpvmkQzsHc+wu77BZDTQLC6MkVe1cjkTgMmoeOaaxoz5eCtWq2ZYJzPxET7MWmUbKzOqaySLkjL4eX0abgaFh5uB129uWjE4u8TCyt05vDC8+j70TSYDE8f3Z/T4OVitVoZf2Yr4RqHM+mmTLdMpY8RO9eDTP5NzvAiT0cCz4/sT4O/6hRAmk4GJDw9g9PjZWC2a4UNaEd8ojFk/brRluvbSf8/01E/kHC/EZDLw7CMDqieT0cDEB3oy+vF5tkyDmhHfMIRZ82wF7lFDW/7r8oVFpfy1/jAvPNzH5SyVMz1zUwvGvPG3bXvqEUN8lB+zltpOo59p3NojH25gzc5McvJL6DNhCeOubsKInrGu5zIonuobzd1z92LRmmtbhhAX6sV3mzMAGNkmlMW7c5i3IwuTQeFpUkwb0gBVnYPWTs1UC/dTFm3l5bUzeO+ypzAoAz/vXcq+3GRGxNu+bmTO7iV8nPQDL3S9l9lXvopSirc2fkNOcR45xXksOfQ3Mwf/D4u28k/WfubuXuJyprMx885J9GnSjlDfQA5Pncdzv37MjJW/XLD1GU0GRo/vwpSHF2O1aPoOiSOmURCLfrR9zdHAa5sS3SCQtl2ieOTWnzEoxWVD44ltHETqkTxefTIRsJ027TGgIZd2OavrBi+62nKVqP2CyXexDddKBtYqpeZprbdXarYf6K21zlZKDcI2DKvq74M6+bi6qkEc1ch+6vANe5B0bFWsD7CNbZsLFAB/YBsv5muvqE3QWg+xL++B7UrTKGAnturc81rrpfbTjhOAo8AOIEtr/bRSKhTbi9UMW6d0GfA/4C8gWld60kqpDcC99tuvWus59ukNgfeBSMANmKW1nqSUutr+fI4Aq4GOWus+//YaFFt+qx1bUSXu6QfP3Ogi02vWnbnRRaa6Vv3dZTVO1cIfKSnOP3Obi0zvr33buWVb7aviWMdUy7Fntevy7ec1HcHJpr9q3za1+cWrazpClVqHPHnxBn4Ce3u0umiftY1XJJ32uSmlumLrp1xuv/8kgNb6pdO0DwK2aq3/9UtBL/gYNq31MRxPO1ZW+fLCk09oKbC00vLFwOnOKc7UWn9k/xqOH7FV1tBaZ2A7/XkqpxfDftEDwN+nTN8PXFFF+5+Bn0+dLoQQQgiBra9xuNL9ZP69ejYa+O1MD1rXf+ngeaVUf2zjyBZhq8QJIYQQ4v8zF/Oig8oXFtp9pLX+6OTsKhapMpxSqi+2DtsZL1Gu0x02rfWEms4ghBBCiP+/2DtnH51mdjK2b7Q4KRrb0C0HSqnW2L52bJDWOvPU+aeq0x02IYQQQgioPRcdAGuBePtY+CPYhoU5XGWjlIoFfgBu0Vqf1c/bSIdNCCGEEKKaaK3LlFLjgIXYvgFjhtZ6m1LqHvv8D4BngRDgPfuV1GVa6w7/9rjSYRNCCCFEnVeLKmxorRcAC06ZVvlnOscAY87lMWvhdwMIIYQQQojKpMImhBBCiDpPfppKCCGEEELUKKmwCSGEEKLOs9aiMWwXglTYhBBCCCFqOamwCSGEEKLOs1prOsGFJRU2IYQQQohaTipsQgghhKjzpMImhBBCCCFqlFTYhBBCCFHnSYVNCCGEEELUKOmwCSGEEELUckrr//YXzdUGdyeOqXUv8svdL6/pCE48Td41HcFJRuGRmo5Qpdr4Wq1J2VzTEZx0imhT0xGchJrCajqCM0PtHB2zLOWPmo7gJNDDp6YjOGnzzM81HaFK+v3V6mKub2Ozphfts/bSHf9c1OcGUmETQgghhKj1audhlRBCCCHEOZCLDoQQQgghRI2SCpsQQggh6jypsAkhhBBCiBolFTYhhBBC1HlSYRNCCCGEEDVKKmxCCCGEqPOkwiaEEEIIIWqUVNiEEEIIUedJhU0IIYQQQtQoqbAJIYQQos6TCpsQQgghhKhRUmETQgghRJ0nFTYhhBBCCFGjpMMmhBBCCFHLySlRIYQQQtR5//VTotJhqyVaBLfg+vgbMCgDK44tZ+HB3xzmexq9GN1iDEEewRiVgcWHF7Hy2F8EeQRxR/PR+LsHoLWV5UeXkZicUC2ZVq3YxesvL8BqtTJ0WHtuG93bYf76tft49P++oV5UEAB9LmvOmHv6ATDr65X8PHcdGrh6WAduuKVbtWQC+Gv5Dl5+6SesFivXjujC6Lsuc5i/ds0eHho3g6ioYAD6DWjFPfddzoH9aTw2/svydsnJmdz3wBXcfKvj8zofa1bu591pf2C1aAZf05Ib7ujs1GbTusO899oflJVZCQj04o2PRwLw6gu/s3r5PgKDvfl09u0uZ6nK6r/28ObLC7FaNVddeym3jO7u1GbD2gO89eoiykotBAZ58+6M2y5IlpN2rE3jxw+S0BZN50H16T8y3mF+4vd7WJ+YDIDVokk9nMfk767Ax9+9WnOc6bXZsPYATzw0m8ioQAB692vKnff0AmD2N38zb+5GtNYMHd6OkTc7/93P17Ll25nyvx+wWqxcN7wrY/9fe+cdHlWZ9uH7lwQCoYUSQu+IAlIUFFFEsPfed3XthbWX/Sxr17Xvuroq6q5l14KuurZVQWkqIiodRWEVEOkd6Ume74/3TDITEogG5j3B976uXMwpM+fHzJk5z3nqeQembP9s3AwuvuRJWjRvCMCBB3Tj9xcfyoYNmzj9jIfYuLGAwsIiDj6oB5f+/rBtpGkad971CkVFxokn9OX88w4upelbLh70OC1aNIo09eD3g0qOXVhYxPEn3k1+41wGP37xNtE0ddwCXnpkAkWFRr/D23HoaTtvts83Exfx0iMTKSww6tSrzjUPDQBg2Cvf8tE73yNB83b1OOsPvalWPbPSmiaMncvTfxlHUaGx/5EdOfaMbpvtM238fJ5+aFykKZvbHj0UgIuPe4UaOdXIyBSZmRnc848jK62nIvz9tzdwxK57s2j1cna9/fS0HDPw84itwSbpBuA0oBAoAi4ws8/K2fcZ4G0z+/cWXu8ZoD+wMnq9QWb2aRn73QaMNrMPKvt/qChCnNrpdP4y4UGWb1jOdb1uZPLiicxfO794nwEtBjB/zTz+NvlhalerzW197uSzBWMptCJemfEyP/w0h+zMbG7o/Ue+XvZVynN/CYWFRdx311s8/MRZNM6vy+9OfZx+++1Cu/aNU/brsVsbHnzktynr/jdjIW+8+gVPv3AhWdUyufyiZ9l7351o1bpRpTQldN11x2sMfupC8vPrcdrJf2a/AV1o36FJyn49d2/HI4+dm7KuTdvGvPz61cWvc+B+tzJw/123iaa/3v0h9z56Ann5dbj4t8+zV/8OtGnXsHifn1av56G7P+Duh48nv2ldli9bW7zt4CO7cvRJPbnn5nfLevltou+Bu97jL4NPp3F+Xc497Sn22W8n2rbPK95n9ar1PHDXuzzw6Gk0aVqP5UvXbBctCYoKjVf/NpkLMYeckQAAMZpJREFU/7QXuY1q8udLRtO1TxOatK5TvM/AEzsw8MQOAEwdu4BRr323zY21irw3AN17tuK+R05JWffdjEW8+eoEnnr+HLKqZXLVxS/Qt18HWrZuSGUpLCzitjtf4eknB5Gfn8sJJ9/PwAFd6dChacp+vXZvz+BHL0hZV716Fs/+4xJq1cpm06ZCTvvtX9i33y706N628ppuH8LTf7/UaTrpHgYO6FaGpg7lGmPP/XME7ds14aef1ldKS4KiQuOFh8ZzxX37Uj8vhzsv/IDufZvRrE3d4n3W/rSR5/8ynsvu2ZeG+TmsWu6OvXzxOj58bQa3PXMI1bMzefyWTxk3/Af2PqRNpTQVFhbx9/s/448PHUSDxjlcd87b9OrXipZtc4v3WbN6A0/eP5YbHjyQvCa1WblsXcpr3PLIIdTNrVEpHT+XZz59h0dG/pvnfndTWo+7LTEz3xK2K7HMYZO0F3AEsJuZdQMOAH7YBi99jZn1AP4PGFzGcTPN7KZ0GmsAbeu2ZdHaRSxZv4RCK+SLRePontcjZR/DyM50X+DszBqs2bSGIiti1caV/PDTHAA2FG5g/pr55GbXr7Smr6bOpUWrhjRv0YBq1bI48JBdGT3i6wo9d9b3i+narSU1alYnKyuTnr3aMurDij13a0ydMoeWrRrRomVDqlXP4pBDezJy+NSf/TqfjZ1By1YNaRZ54SrD9GkLaN4yl2YtcqlWLZMBB3VizMiZKft8+O50+g3sSH5TdyGp3yCneFu33VpQt972+3H+euo8WrSsT/MW9alWLZP9D+nCRyO/Sdln2LtT6b//zjRpWs/pa1hru+kBmPPNcho1q0WjprXIqpZBz/2aM/XTBeXuP2HEj+y2X/NtrqMi7015zPp+CV26NadGzWpkZWXQY/dWjB5esedujclTZtO6ZR4tWzaievUsDj9sNz4cMaVCz5VErVrZABQUFFJQUIikymuaPIvWrZI17c6HwydV+PkLFixn5KipnHDC5t7dX8r305eR16w2ec1qk1Utg94DWzLxkx9T9vnsgzn07NeChvnuO1e3fsl3rajQ2LShkMLCIjZuKCS3YeW/hzO/WkKTFnXIb16HatUy2fuAtnzx0ZyUfT4e+j179m9NXpPaANRrULPSx60sH82cyLI1q3zLCGyBWBpsQFNgiZltADCzJWY2T9JNkj6XNFXSEyrjV0jS7pJGSfpS0vuSmm726jAa6BDtPyt63Y+BEyU9I+mEaFtvSWMkTZI0TlIdSZmS7ot0TJZ0QRmv/7PIza7P8g3Li5eXb1i+mdE1Yu5wmtZqyr17389Ne9zCkBkvYqTeTTSs0ZBWdVrx/arvKiuJRQtXkZ9fr3i5cX5dFi/a/Ms8ZdIcTj/hES6/6Fm+m7kQgHYdGjNh/CxWrljL+nUbGfPRtyxcuLLSmpyulTRpkluiq0kuCxdt/tqTJ87ixGPv4+Lzn2DmjM0Ngff+O4FDDuu5TTQtWfQTefklnqG8/DosWfxTyj5z5yxn9ar1XHn+EC48/Z8MfXvaNjl2RVi8aBWNm5R4HBo3rsvihatT9pkzeymrV63n9+c8x9mnPMm7b1X8QvxLWLF0Pbl5JRepeo1qsHLJujL33bi+gOlfLKLbPmV9lStHRd4bgKmT53LmiYO56uIX+G7mIgDadchj0pdzovN8E59+PJOFC7bNBW/hwhU0aZpbvJyfn1vmd2jixO856ti7OfeCx5gxs8SrXlhYxNHH3UPfftfTd69OdO/WpvKaFq2gSZOS36X8/PrlazrmTs49/xFmzJhXvP6uP/2ba64+loyMyhuPCVYsWUeDxiU3P/XzclhR6jxaOPcn1q7eyH2Xj+T284cx5v1Z0b41OeikTvzh5Le5+vi3qFmrGl16p3rqfwnLFq+lYX7JDU+DvFosXbw2ZZ95P6xkzeqN3DzoXa496y1GvZt0gydxx+VDufastxj2n21zA/BroagofX8+iGtIdChwk6RvgQ+AIWY2CnjEzG4DkPRPnBfurcSTJFUDHgaONrPFkk4G7gTOLvX6RwLJt6vrzWyf6DUOif6tDgwBTjazzyXVBdYB5wArzay3pGzgE0lDzez7bfoOlHLtdmnQlR9W/8CDE+4nr2ZjLu9xBbePu5X1hc69n52ZzQVdL+blGUOK121rStvHnXZpxhvvX01OTjaffPQN11z+Aq++fQVt2zXmjLP6ccn5T1MzpzodOzUhM3Pb3BuU5fIWqbp26dyC9z74Izm1svlo1Fdccck/eOu964u3b9pYwKgR07jsisO3iabSnxVA6VuJwsIiZny9iPseP5GN6zdxyVkvssuuTWnZuvIevl8gb7PPsrCgiOlfzeevT/yGDRsKuOCMp+myawtatal8eK9sUWWsK8cLNG3sQtp0abDNw6FQsfem0y5NefW9S8nJqc6Yj2Zw3RWvMOStQbRpl8fpZ/Xl8guep2ZOdTrslE9m1jY6z8tYV1pXl84tGD7sVmrVymbU6GkMuuQphr77RwAyMzN447U/sGrVWgZd+hTfzpjHTh2bVU5Tme9V6nKXzi0Z/uHt1KpVg1GjpjLo94MZ+v6tjBgxhQYNatO1Sys+G/dtpXSkatq6qKLCImZ/u5yrHujPxo2F3D1oOO06N6RObjYTx/zIn148nJq1qzH4lk8ZO2w2fQ5svc30lSOJwkLju2+WcNNfD2bjhkJuOP8dOnbJo1mretzx+GE0yMth5bJ13H75UJq3rkfnnpU3JANVn1h62MzsJ2B34HxgMTBE0u+AAZI+kzQFGAh0KfXUTkBXYJikicCNQIuk7fdF68/HGV4JhpQhoxMw38w+jzStMrMC4CDgjOh1PgMaAh1LP1nS+ZK+kPTF129P3+L/d8WG5dRP8qjVz67Pio0rUvbp23RvJiweD8DidS582iTHeRwylMkFXS9i3MKxxftUlsb5dVPunhctXEWjvDop+9SuXYOcHBd62btfJwoLClmx3OU+HXVcL557eRCDnzmPunVr0rLVtrnw5zfJZcGCFSW6FqygceO6KfvUrl2DnCgk1K9/ZwoKClm+vMTj9fFH09m5c3MaNkr9//xSGuXXSfHKLF64moaNaqfsk9e4Nr37tqFmzWrUq5/Drru14LtvF2+T42+Nxvl1WZTk+Vm0aBWNGtfebJ8+e7enZk51cuvn0GO3Vsz8duF205TbqAYrFpd4QlYuWU+9csJRE0Ztn3AoVOy9qVU7m5wcZyz27deRgoJCVix3HpMjj+vJ00PO49Gnz6RuvZq0bLVtDPAm+bksmL+ieHnhwrLO85rFoc/++3ahoKCQZctTPbt16+aw5x4d+ejjyqckNMnPZcGCkkjAwoXLady4Xso+TpP7HPv371qsafyE/zF8xBQG7n8jV171D8Z+9g1XX/t0pTXVz8th2aIS79XyxWs3C2vWz8uh6x5NyK6ZRZ162XTs1oi5/1vB118upFGTWtTJzSYrK4Oe/Zrzv6lLK62pQV4OSxeW5IAuW7yGBo1yUvZpmJdDjz1dOL1ubg126dGE2TOXFz8fXJh0j31bMfPrJZXW9GthR/ewxdJgAzCzQjMbaWY3A78HTgceBU4ws12BJ4HSv/ACpplZj+hvVzM7KGn7NdH6A80sOfGprAxrUc6NLnBJ0jHamtnQMvQ/YWa9zKzXLkdsXrWUzKzVs2ick0/DGo3IVCa9Gu/BpCWpIall65exc4NdAKhTrS75OU1YvN5d8M/Y+UwWrJ3PBz8M2+Jxfg67dGnOD7OXMm/uMjZtKmDYe1PYd7/U/8fSJauL73CnTZlLUZFRL9f92Cxb6i4cC+avYOSHX3HQYZtXSf0SunRtyZzZi5k7dymbNhbw3rsT6D+ga8o+SxavKtY1ZfJsioqM3NySEMW7/x3PoYfttk30AOzcuQk//rCC+T+uZNOmQkYM/Ya+/dun7NN3vw5MmfAjhQVFrF+3ielT59Oq7XbyXpXW16UZc+csY97c5WzaVMiH701jn/47pezTb8BOTBo/h4JI37QpP9KmbeWLRMqjZadcFv+4hqUL1lCwqYgJI3+kS5/8zfZbt2YT/5u8lK59t4+HoSLvzdIlPxWfT19N+RErMurlunBuojhjwfyVjPpwOgccWvoe8pexa9dWzJqzmB/mLmXjxgLe+e94Bg5ILZBZnHSeT47O8/q5tVi2bDWrVjkjZv36jYz59Bvatd38vf3ZmnZtzazZi/hh7pJI05cMHJD6vV68eGWSplkUmdN01ZXHMHrkXQz/8A4efOBs+uzZifvvPavSmtrsXJ9FP/7E4vnuPPp8+A9075vqSeyxdzNmTF5CYWERG9YX8P3Xy2jaui4NGufw3VfL2LC+ADNj+vhFKUUvv5QOuzRi/txVLJy3mk2bCvnkg+/ptU/LlH1679uKryctorDAaZo5bTHNW9dj/bpNrFuzCYD16zYxadw8WrbLrbSmwI5BLEOikjoBRWY2I1rVA/gG6AYskVQbOAEoXRX6DZAnaS8z+zQKke5kZr8kYWg60ExS7ygkWgcXEn0fuEjScDPbJGkn4Ecz+8VldUVWxEvfvsBlPS4nQxl8Mu8T5q+Zx77NXLuJ0fNG8c6st/hd57O5aY9bAPH6zFdZs+kn2tfrwF5N+zL3p7nc2NtV9/znu9eZurRiCcrlkZWVydXXH8GlFz1LUWERRx6zO+065PPay+MAOO6kPRg+bBqvvjyOzMwMsrOzuOPek4vDNv935YusXLmWrKxMrrn+SOrW3TZJtVlZmVx3w3FcdN4TFBUVccyxe9ChYxNefmkMACed0pdhQyfx8ktjyMrKIDu7Gvc88NtiXevWbWTsmG/54y0nbhM9AJlZGVxy7UD+8PtXKSos4tCju9KmfSPe+rczuo88oTut2zakd982nHvKs2RkiMOO2ZW2HZxBdMf1bzPpi7msXLGOkw8dzJkX9OWwYypfvZogKyuDK647hCsveoHCIuOIY7rTrkNjXn/5SwCOPWl32rTLY8+923PmiYORxJHH9aRdx8ZbeeVfTmZmBscP2pXB14+lqMjY86BWNG1Tl0/engXA3ke0AWDKJ/PptHse2TW2z09VRd6bEcO+5vWXvyArK4Pq2dW49Z7jis+n6696hVUr15GVlcFV1x+6Tc/zm244gXPPf5TCoiKOP7YPHTs05cUhHwNw6sn78P7Qibw45GMyMzOoUaMaD95/JpJYtHgV/3f9vygsMqzIOOTgHgzYr+tWjlhBTTeezLnnPuI0HbcXHTs248WXRjtNp+zL+0Mn8OKLH5GZlUGN7Go8+MDZ26TgoTwyMzM47dKe/OXa0ViRsfehbWneth4j3/wfAPsd1Z6mrevSdY8m3HrOUCTR73C3D8Du/Vtwx/kfkJEpWnXMZd8j2lVeU1YG51zZhzuvGEZRoTHgiA60bFefoa+7SMtBx+5Miza59OjTnKvOeIMMif2P6kir9vVZ+ONq7rtuOODCpvsc2JaefVps6XDbjBfOvo39dtqNRrVz+eGuN7n57Sf5x5i3tv7EGLGj92FTHMtgJe2Oy0XLBQqAmbgw5uXAKcAsXNXobDO7Jbmth6QewF+BejiD9C9m9mR5rT8kzQJ6mdmSaDn5tXpHOmrijLUDgLXAHbg8OOFCtseYWblZ9RcMPzd2b/I9ex+89Z3STI2snK3vlGaWrPtx6zt5II7v1bgF27dQ4ZewR5PuviVsRqOsvK3vlG4yYnnvzugFI3xL2Izc7O1bQf1L6H7jG74llIk9Nnb7Wetl8F6DTmm71h6y7Ju0/t8gph42M/sSKKvT6o3RX+n9f5f0eCKw75b2KbW+zRZe63OgTxlPuz76CwQCgUAgEAN2dA9bbHPYAoFAIBAIBAKOWHrYAoFAIBAIBH4OwcMWCAQCgUAgEPBK8LAFAoFAIBCo8gQPWyAQCAQCgUDAK8FgCwQCgUAgEIg5ISQaCAQCgUCgyhNCooFAIBAIBAIBrwQPWyAQCAQCgSpPUexmCm1bgoctEAgEAoFAIOYED1sgEAgEAoEqT8hhCwQCgUAgEAh4JXjYAoFAIBAIVHmChy0QCAQCgUAg4JXgYQsEAoFAIFDlCR62QCAQCAQCgYBXgoctEAgEAoFAlSd42AKBQCAQCAQCXpHZDt4aeAdD0vlm9oRvHckETRUjjpognrqCpooRNFWcOOoKmgI/h+Bhq3qc71tAGQRNFSOOmiCeuoKmihE0VZw46gqaAhUmGGyBQCAQCAQCMScYbIFAIBAIBAIxJxhsVY845hYETRUjjpognrqCpooRNFWcOOoKmgIVJhQdBAKBQCAQCMSc4GELBAKBQCAQiDnBYAsEAoFAIBCIOcFgC/xsJN1TkXVp0tJgS3+eNLXycdzAjkscz/NS+tpWZF0gEPjlhBy2wM9G0ngz263Uuslm1s2Dlu8BAwS0ApZHj3OBOWaW9otG8vsj6VUzOz7dGqoikuoDHYEaiXVmNtqfIpC0E3AN0JqkUX5mNjDNOmJ3nidTzm/Cl2a2u0dN7YG5ZrZB0n5AN+A5M1vhUVMe8AegM6nneVrPp7KQ1BroaGYfSKoJZJnZat+6AiWEWaIxRdJq3A/0ZpsAM7O6aZaEpIuAi4F2kiYnbaoDfJJuPQCJC5Wkx4E3zey/0fKhwAE+NOE+owTtPGkoE0l3mdn10eMDzWyYb00Aks4FLgNaABOBPsCngO8L2SvA48CTQKEvETE9z5G0M9AFqCfpuKRNdUkySDzxKtBLUgfg78CbwAvAYR41PQ8MAQ4HLgTOBBZ71AOApPNwDXMbAO1x38PHgf196gqkEjxsgQojqR5QH/gT8H9Jm1ab2TI/qhxl3c1L+sLMennQkuxh28zz4JO4apM0BegNjDWzHpEhcKuZnexZl1cvUWnidJ5Hxz4aOAY4CmcQJVgNvGRmY3zogpLzW9I1wHoze1jSBDPr6VHTl2a2e3JEQtIoM+vvS1OkYSKwB/BZ4v2RNMXMdvWpK5BK8LBVESQ1JtWFPseDjExgFTCo9AZJDTwbbUsk3Qj8C+eZ/A2w1JOW7pJW4TxtNZMegyfvaBVgvZmtl4SkbDObLqmTLzFJeWFvSboYeB3YkNju8VyP03mOmb0BvCFpLzP71JeOctgk6VScF+vIaF01j3oANkX/zpd0ODAP583yzQYz2yi5nylJWZQd4Ql4JBhsMUfSUcADQDNgES6X5mtcGCLdfEnJl1ilthl+w3+nAjfjLqwAo6N1acfMMn0ct4I0lnQl7vNLPC7GzB70I4u5knKB/wDDJC3HXcx8kTjXE+f5NUnbfJ7ryee54fE8B5D0cKSDyDhKwcwuTbuoEs7ChR3vNLPvoyKIf3nUA3BHFKm4CngYFzq+wq8kAEZJuh53g3kgLvXlLc+aAqUIIdGYI2kSLo/nAzPrKWkAcKqZhQG9MUVSDrDJzDZFy51weTOzzOz1LT55+2u7eUvbzezWdGkpD0n9gXrAe2a20bOWGma2fmvr0qQlE3jWzH6T7mOXh6Qzt7TdzJ5Nl5Zk4vhexRlJGcA5wEG4m5T3gacsGAixIhhsMSeRnxIZbj3NrEjSODPbw4OWnaNQVZl5T2Y23oOmt9iC697MjkqjHAAkjQbOMbMZUcLzOFyycWfgczP7vy2+wK8USfvgqtSejqrpapvZ9541lVX96C33T9L7wJG+DdmqQBzfq6jq+DEg38y6SuoGHGVmd3jWVQuXllAYLWcC2Wa21qeuQCohJBp/VkiqjQt9PC9pEVDgScuVuEqiB8rYZvip6Ls/+vc4oAklIY9TgVke9ADUN7MZ0eMzgRfN7BJJ1XGhNm8GW1QNNjIyJoWrnjsemA2caWYTPOm6GegFdAKexuUa/QvY25OeJkBzXIioJyWh0bpAjg9NEbOATyS9CaxJrPQVypbUCJfTuhz4B3Af0A/4H3CVmc30oStiFjF6ryKexIXXB0daJkt6AfBqsAEf4qqNf4qWawJDgb7eFAU2Ixhs8edoYD0uz+F0XKjoNh9CEmFYMxvg4/hlYWajACTdbmb7Jm16K/J0eZGV9Hgg7iJGlNRb5EdSMZcBz0SPTwW64/KxegJ/xV1sfXBspGE8gJnNk1THkxaAg4Hf4RLCky/wq4HrfQiKmBf9ZeDa6fjmBeALXP+8cThj+yHcefQUsJ83ZfF7rwByzGxcIrk/wtcNeDI1zCxhrGFmP0WpHYEYEQy2mGNma5IWveSDlEbSGWWtN7Pn0q0liTxJ7czsOyjusp7nSctkSffjLhYdcHeqREn1vilI5NYBR+AaiS4FPpB0r0ddG83MJCUS2Gt51JLIvXpW0vFm9qpPLcnEIcewFPlmdn3krZ1tZvdF66dL2qyaPJ3E8L0CV+XbnpJCjROA+X4lAbBG0m6JtBZJuwPrPGsKlCIYbDFHqQ10q+NCRWs8t4bonfS4Bq654njAp8F2BTBS0nfRchvgAk9azsN5sloBByXlgXSmJITriyJJTXEhrP2BO5O21fQjCYCXJQ0GcqOw7dm48JFXzOzVqP1CF1Lb6qTVyx3l97VL3BRJ+jeuySnAHWY2PJ16kigE16tG0pJS27x6k6M8yGvZ/LPz2Yx5EPAEsLOkH4HvcZET31wOvCIpUZndFPDaAzGwOcFgizlmluLKl3QMrsGhN8zskuTlqEz9n57kAGBm70nqCOwcrZqOG9vjQ8s64G5Jl5nZpKT1YyT13sJT08FNuBBWJq5j/jQorsz8bktP3F5E3pkhuM9uFS6P7aY4TGGQmyyQAwzAhfhOwIX+0s2tQPL3rhMuZFsLF6L1ZbC1i3LElPSYaNn3LNHEVIEjiMFUgSiR/yIzOyDyIGdYTEY/mdnncs2qO+E+u+lJnvhATAhVolUQSWPNrI9vHQkkVQMmm9kuMdBSD5dEfxqwi5k196ilrApDr53WIw3VgT3N7KOkdbVwvwc/lf/M7aopVhMFEijqSJ/0b23gNTM7KM06Pjez3knLr5nZcdHjT8zMV3HGFjv0J3JMfaAYThWQNNyzhy8FSQPNbLhSx4oVY2avpVtToHyChy3mlPoiZeAq6bxa2aVaaWTgQn0ve9RTEzca5zRgN1yC8TG4ylofek6NtLRN8jgQ6fLWlT5BVPxwL7BX0ro1W3hKOhgrqbeZfe5ZR2kSeTxrJTXDfX4+PEe5yQsJYy0iP71SUnSMinHPszhOFZgQ/Sa8Qmrlqi/DqD/OO3tkGdsMCAZbjAgGW/xJ/iIV4ErVj/YjpZjkPKwCXLLxXB9CJD0P7ItL7H8E9+Mz08xG+tATMQaXSNyI1BYoq4HJXhRtzlBJx+O8RXFwsw8ALpA0G3chEy41qptfWbwdFYvch8vTNPzk1k2XdLiZvZO8UtIRwDce9BRjZoWS8iRVj1PPM+I5VaABzuhP9rJ5M4zM7Oaoae67ZubtpjtQMUJINFApoj5MS31d9KOGwsIVPAwxsx8kfWdmPsdkpSCpLkk3R+Z35ipQXMxSC2dwr6fEQPJSzCKpdVnrzWx2urWUh6RsXPuDlR6O3QF4B3czkGhQvTuuT9YRZvZtujUlExWM7IYbAB+XnmdVgjh4liWNLtUWKRBDMnwLCJSPpKMlfSJpWfQ3NKoWS+RqpVtPH0kjJb0mqaekqcBUYKGkQ9KtB8DMugMn4e6eP5D0EVAnanzqFUnnS1qI86p9gWua+4VfVQ4zq2NmGWZW3czqRsveKo/NbHbiD1gC7AM86ksPOCMyuiFBUh9c0r+XHoRRA9puwEe4Cug2uJB/N9/GWsQ84G1Kep4l/tKOpHslXVjG+isk3eNDU2kkdZZ0m6QZuMkHvhkm6WpJLSU1SPz5FhVIJXjYYoqki3GtDa6l5CLfC9cR+yHg+shYSaemL3AVafVwpemHmtnYqLroRd/J9ACSeuHyx04A5pqZt07d0Y/xXmZWut2BN1TOWLEE5mG8GBQXQhyG++wOAV7FhWu9DKCW9EdcFaYBL+G6wI8E9gQmmdnlnnRdAbziKwWhNJJOilsoTdJXQFczKyq1PgNXHNXVk67WuGbVp+I8262BXmY2y4eeZCSVNQLO4hSpCASDLbZI+hrYu3T4TFJDYC5wpZml9c5M0kQz65HQl1wVGofqx2SiVhH7eq5Sew84zmI0j0/SiC1stnRXsEk6EHcBOxgYgWvD8LCZtUmnjjJ0fQX0wLX0mAM0MbO1krKAiR4v+jfjPMrLcIbkv81soQ8tkZ63ceH+iy1qWu0bSdPMrMvP3badNY3B3ei+BLxkbjTc92bmu/VJoAoRig5iTFm5Tma2VNLsdBtrEcl3rKW7YPvKYXt4K8f2ZrAB1wFjJH0GbEisNLNLfQmyGI0Vi3gfF+bbx6JB75Ie8isJcIOwNwIbJf0vYXSbWYEkb4n15rr33yo3NPxkYJSkuWZ2gCc9R8j1hnxHbibmYyT9TnjK11wrqaOVzPMFQK5Po6/u/YtxFar5uAksM/Bc7Q8gaU9ctKQ9MAU428y+9qsqUB7BYIsvqyR1T268CiCpO5D2pOeI7pJW4RLUa0aPiZZrlP+07UoiXLw3rr3IkGj5RFzOmE8G46pWp+C563sCSXeZ2fXR4wNj0Jx2d+AUXP7hdzgPRKZfSYCbuHAc7tyum9ReRzhPiW8WAQtwFYeNfQoxs/9EIbXRwDmUGCKGm1Obbm4C3pV0ByW/Ab1wN1CXe9CDmR2tkh6Rt0ZFJLmS9jAzH42YE/wNuBr32R0F/AXn7Q7EkBASjSlRccHzuGHKX+J+/HrjunX/xsw+9igvdkShvoMs6s4t18x3qE+PkqQxPnPoykJJzXxVRmNfn0jaGxcePR6YCLxuZk940vL0lrab2Vnp0pKMpItwnrU84N+4yuivfGiJ9GQDN+JyRq8xs7d9aUlGUlfgGiARup4K3G9mU/ypKkFSY9zneCrQ0sxaetKR8hsQt9+EQCrBYIsxUaXjxbhZeAKmAX8zswUeNXlN3C0PSd/gEvyXRcv1gbFm1smjpjuB2cBbpIZEvbX1iLPBliA6xw4ETvFlGMUVSXfjcqAm+tYCxd+7V4HbzY1kix2SapunCR7lIamWRc2qJbX21b4m8mpfnbTq/uRljw19A2UQDLbAz0auWe11ZjbHt5YEks4CbsElroPr4H2LmT3rUVPsKq8kzQUexN0AXBE9LsZX3yy57u8vAW+Y/6kLSLpyS9t99heLKn33wXndP/FV2Rtp6Zzs4Us2RHwjaS/g70BtM2sVpZNcYGYXe9TUFzeTNhaatuJJNjM7O21iAlslGGwxRdIUyk5K9d4BXtJwXHh2HKlNMo/ypQmKPZJ74t63cT49kXElqjIsDzOz29ImJgm5mZQnA4fjzqshwNtmtt6Tni29T4nk/7QTtRs5iZLO+Mfg2nzc4UNPgrgZIpGmz3Ch2jcTFeySpvqMDsRRU6DqEIoO4ssRvgVsAS8XqwqwB9Avemy4UKQ3JJ0IvGdmqyXdiOsEf7uZTfClKWFoSNrbzD5J3hblkHkhar8ySm4u5UDgPOAfuIbIPvTE9Rw/DeiZMGSjEOl4XH9Gn/wZl6z+JoCZTZLkvXO+ucknyasKfWlJEEdNkvKBu4BmZnaopM64FJO/e5YWSCIYbDHFV05DRfDZ26w8ogtXb1yhBsClkvqa2XUeZf3RzF6JCkgOxuWHPI7zAvrmYZwBubV1aUNSTdzs3JMjHT7D2X/d0naPrVlm4SqyE57HbOB/nrSkEEND5IfI82dyjZkvBXy3rIijJoBncAVuN0TL3+K83MFgixHBYIspcrMetxQS9TZGSG5Mz8PALkB1XBuGNT414brk97Cou7mkZ4EJuFJ+XyQuWIcDj5nZG5Ju8agnkdfTF8grladVF4/tNCQNwRmy7+FaDYy0Up3q04zvljApJPUb3ABMkzQsWj4QiEPFeBwNkQtxU2Ga45qNDwUGeVUUT00AjczsZUnXQXG/Qd8Gd6AUwWCLKWbmZQ5fBXkE1zvrFVx/ozOAjl4VOXJxHeAhHr2yfpQbin0AcE/UAsH3/N7qQG3cdz/5HFuFy63xxdPAaWYWi4uEz2KVckj0G/wSeD1p/Uhi0ICVGBoi5kbCne5TQ2niqClijdwUHYPim3Jf/T4D5RCKDqoIUd+e4ua0Pis0JX1hZr0kTU4UP/juOSbpVOBuXJWogH1xlawvedSUg5uLOSUaRdMU2NXMhvrSlCC5lUDURqO2ma3aytO2h46BZjY8qTFtCr7bCkT9/Tb7kbQ0j/AqD0ktce1P7vOtJW6UE9ZeCXxhZm+kWw/EUxMUVx4/jOtbNxXX5+8EM5vsS1Ngc4KHLeZIOgp4AGiG627eGhdqSPs8vCTWRmGPiZLuBeYDtTzqwcxelDQSl8cm4A++q0TNjTN6TVKO3FD62XEw1iL+JOlCXNj2S6CepAc9XPj746ZBHFnGNqOkGtIXyT2qauCa+hZ40gKApEa4SR6n4jxar2/5GdufmBoiNYCdcZEAcJ/dNOAcSQPM7PKgyWFm46NK7U64389vEk3IA/EheNhijqRJuKq5D8ysp6QBwKlmdr5HTa2Bhbjw2hW48OOjZjbTl6ZIVzegDUk3Ij48NJGR/VdcePZGXE7WwkjbH+IQbpM00cx6SDodNx7qD8CXPtvFlEbS8Wb2qm8dpZE0ysz6p/mYdYBjcVWiO+GMtJPNrEU6dZSHpCco2xBpCXznwxCJ2g8dZGYF0XIWLlR7IM7r3fnXrqk8z3YC3x7uQCrBwxZ/Npkb+J4hKcPMRki6x6cgM5sdVfQ1jUv7A0n/ALrhLhKJZHVfHprbgYNwhuwIoJuZfReFtT/EY/VjEtXkxncdAzxiZptKVfjFgT/juuh7Q1KDpMUMnHHbxIOURbj+dDcCH5uZSTrWg47y6AAMTDJEHiPJEPGkqTnO85/IxaqFa1tRKGlD+U/7VWkqy7OdIA4e7kASwWCLPysk1cYN531e0iL8h2SOxLWoqA60ldQDuM1z49w+Pu6Yy6HIzL4FN+3AzL4DMLNFkrx+dkkMxrWImASMjrymcUsyjoMFmVwtWgB8jxtwnm6uxxX6PAa8EFXVxom4GSIA9+LSNkZSktd6l6RawAdBk7+ZuIFfRgiJxpzoi7wOd3d/Os5r87yZLfWo6UtcmHZkUrfuyT7DaZL+DjxgHgdhJ2mZBOyH+8yGR48TxscIM+vuR1n5yLnXzjWzJ31rSSBpjpm18nTsVj4Le8pDUjtc7topuMrsm4HXEzcIHnWdg/P+jSTJEAFexI2Iu8aTrqa4htrCTT+Z50NHMnHUBCDpcFxudHJxm5fJJ4GyCQZbjIm6vr9vZgf41pKMpM/MbE9JE2JksO2Lm2ywANerytsIL0mzcGHZsjxEZh5niW4JHwaStjyCbSczy06nnuKDS+PNbLfo8atmdrwPHVtC0q444+1kM2sfAz2xM0Qk1ccZtslGyGh/imKr6XEgBxiAGzF2Au4z9OFNDpRDCInGmCicsFZSPTPzHq6S9F9cb6Wpkk4DMiV1xDXJHONVnBtj9FtcvozPhquYWRufx98Sksor0xeQn04tEXEdwZZsbMfGwE543KOmwhuAscAtXkWVsB5XMV4D6CCpg09DRNK5wGVAC2Ai0Af4FBcdCJpS6Wtm3aIb71slPUDIX4sdwWCLP+uBKVFn8+RB6z5G4zwDvA/8E9evZwPwQrTudg96kpljZm961gAU9zQqFzMbny4tZZCPG5O1vNR64cHojgpY4uhJtnIe+2Y00C/y0nyIa6h7EvAbn6JiaohchmvzM9bMBkjaGf9zkOOoCVzaDbiWTc1wFe5tPeoJlEEw2OLPO9Gfd6LRJe8AN+Eawv6TkovZIOBBX9qA6ZJewIVFi5OcPZWlP7CFbYbfi9jbuCa5E0tviBKh007cPMkR3SWtwhmyNaPH4H80nMxsbZQz9rCZ3StpoictycTREFlvZuslISnbzKZL6hQ0lcnbknJxRRGJQpun/MkJlEUw2GKOmT0btdBoZWbf+NYDbMJ5+rJxI47i4n2oiTPUDkpa56Us3cwGpPuYFWVLOSlmdlo6tZQiTp5kzMzbXNWtILl5sKdTUq0aB61xNETmRkbIf4BhkpYDvvPqYqVJUm/gBzO7PVqujUsrmY5rqxOIEaHoIOYkt9AwM68tNCQdgvOivRlpWJtuDVUNSV2BzqQmGD/nT1E8kXRm0mLiR0lxaDIcJ+S60V8FfGJm90RVo5f7MmyTdL0OnAVcjvMgLweqmdlhPnUliN63esB7ZrbRtx6IhyZJ44EDzGxZVLj1EnAJ0APYxcx8zhcOlCIYbDGnnBYaU8xsVw9aPgIuNLNp6T721pC0E65HVb6ZdZWbenCUmd3hUdPNuJYenYH/Aofimp6GH8EISUcDLczsb9HyONwcQ8NNhXhlS88PxI+YGCIZwGQz6+rj+GURU02TEm2GJP0NWGxmt0TLE82sh0d5gVJk+BYQ2CoFZeT1eLGyzaxfHI21iCeB63AhW8wNLT7FqyJXGr8/sCBqUNkdF0oOlHAtzmOboDpumsB+wIU+BMUZSb0kvSZpvKTJiT/PmjIkTU0sm9koM3vTpycrqqKdJMlLH7+yiKMmXKV/IjVqf1zfyAQhZSpmhA8k/sSxhUYcyTGzcUodr+R7qsA6MyuSVCCpLm68UGxaRMSE6mb2Q9Lyx2a2DFgWtbAIpPI8cA0xaF+TIDrHJ8Ww2XBTYFrktU3Oi/Q5kSVuml4ERklagqsU/QhAUgfiN/nkV08w2OLPJcANpLbQ8BbmizFLJLUn8j5KOgHXE8onX0QJxk/iKq9+ws2DDJRQP3nBzH6ftJiXZi1VgcVxaV9TirgZIuC/SrUsYqXJzO6U9CHu8xtqJTlSGbhrTyBGhBy2mCOpp5lN8K0j7kTJ108AfXEJz98Dp5vZbK/CIiS1AepGodpAhKTncfmZT5ZafwGwn5md6kdZPJG0P266wYf4b19TTJS3thlmNirdWgKBHZVgsMUcSSNwdz+vAC/FOIcsFkRhtAyce/9kM3veo5YPzWz/ra37NSOpMa7FwQYg0VB4d1yu3zFmttCTtFgi6V/AzsA0SkKiZmZn+1MVTyT1AR4GdsHlRmYCazz20IulpkDVIYREY07UhLIJrpv5E1Eu1BCf1Y9xIno/BgHNgTeAD6Llq4FJuJyfdGuqgZvL1yjqSJ9IrKsLNEu3njhjZouAvpIG4gZPA7xjZsO38LRfM919VIhvjZgaIo/gCo9eAXoBZ+BmePokjpoCVYTgYatCyA17vhbnOaruW08ckPQGLgT6Ka7KqT7ugnFZWd3806TpMlw/qmakNsVcBTxpZo/40BWo+kh6EvizmX3lW0sykr6gDEPEzK73qcnMesnNx+wWrRtjZn2DpkBVJHjYYo6kXYCTcS0ilgJDcI0zA452CY+DpKeAJbipEKt9CTKzh4CHJF1iZg/70hHYIdkHOFPS97gwcmJUVje/ssDMZkrKNLNC4GlJvqvZ10qqjmulcS+uCMl35XEcNQWqCMHDFnMkfYab/zgS+NzM1vtVFC8kjTez3cpb9kn0w3whsG+0aiQw2Mw2eRMVqNJIal3Wet/FNZJGAwcAf8cZIfOB3yWasnrS1BpYiPO4X4FLSXjMzGYGTYGqSDDYYkrUzPAu4GxgDu5OugXwNHBDuOg7JBXi2ggk8sRqAmvxP6Q74fGrBiTGK/0WKDSzc31pCuxYRG1jBpnZnZ51xMYQKWN6xmdAY1zLn2vN7N9BU6AqEkKi8eU+oA7QNhHeixLs74/+LvOoLTbEcUi3pCwzKwB6l/IwDJc0yZeuQNVFUkvgj7i8yP/gejLejrsJeNGjrtKGyChKDJFPAR+eo2tJnXKSjas8ro274fVhHMVRU6CKEUZTxZcjgPOSc7HMbBVwERCLgcpxofRonBiQaI5bGDXzBYp7xRX6kRSo4jyHK2B5GFdNOxZnvHUzM583b6VHiyUMkf1wv1U+KHN6RjSFwVe+WBw1BaoYwcMWX8zKiFebWaGkEMdOIoajcRLh2auBEZK+i5bbAGd5URSo6jRIDOUG3pe0EOfB3bCF56SDOI4Wi+P0jDhqClQxgsEWX76SdIaZPZe8UtJvgOmeNMWZOI3GyZN0ZfR4MFFPKqAG0BMY4UFToIpTqqffAiAnYRRFRpIP4miIfCbpvHKmZ/gaDRdHTYEqRig6iCmSmgOv4Tr2f4nLCemNS6o/1sx+9CgvdsRpNI6k+cBjlFxcUzCzWM0TDMQfSbNwkw3KOqfMzNqlV5EjjqPF4jg9I46aAlWPYLDFnKQO8AKmmdmHniUFtkKcWosEAtuTOBsipaZnTIvD9Iw4agpUHYLBFtghiNNoHEkTzKxnuo8b2PGJ63zaYIgEAtufkMMW2FGI04y+MNw9sE2J5tPWIqbzaSMDLRhpgcB2JBhsgR2GuIzG8ZgAHthxuYCS+bTjk9avAv7mQ1AgEEgvISQa2CFIGo3zFK6CzvtonEBgWxPm0wYCv16CwRbYIShjNE494NEwoy+wIxHm0wYCv16CwRbYYZBUE2hlZt/41hIIbA/CfNpA4NdLMNgCOwSSjsTNWK1uZm0l9QBu89Q4NxDYpiTm00qaVDrMX9a6QCCw4xFmiQZ2FG4B9gBWAJjZRNwoqEBgRyDMpw0EfuWEKtHAjkKBma2UyhwuEAhUdcJ82kDgV04w2AJVGkn/BQYBUyWdBmRK6ghcCnhp6xEIbAfCfNpA4FdOCIkGqjrPAO8Ds4CuuBE5LwArgcu8qQoEti2ZQG2gDu5GW9FyVrQuEAjs4ISig0CVR1It4CbgEOCfQOKkNjN70JuwQGAbEebTBgKBEBIN7AhswoWHsnFeh3AXEtjRCMmZgcCvnGCwBao0kg4BHgTeBHYzs7WeJQUC24MwnzYQ+JUTQqKBKo2kj4ALzWyaby2BQCAQCGwvgsEWCAQCgUAgEHNClWggEAgEAoFAzAkGWyAQCAQCgUDMCQZbIBAIBAKBQMwJBlsgEAgEAoFAzAkGWyAQCAQCgUDMCQZbIBAIBAKBQMz5f08qthXMtyBbAAAAAElFTkSuQmCC\n", "text/plain": [ "<Figure size 720x720 with 2 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "corr = train_data.corr()\n", "highest_corr_features = corr.index[abs(corr['SalePrice'])>0.5]\n", "plt.figure(figsize =(10,10))\n", "g= sns.heatmap(train_data[highest_corr_features].corr(),annot = True, cmap = \"RdYlGn\")" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:54:55.014845Z", "iopub.status.busy": "2021-02-26T23:54:55.014121Z", "iopub.status.idle": "2021-02-26T23:54:55.018352Z", "shell.execute_reply": "2021-02-26T23:54:55.017697Z" }, "papermill": { "duration": 0.041054, "end_time": "2021-02-26T23:54:55.018514", "exception": false, "start_time": "2021-02-26T23:54:54.977460", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "SalePrice 1.000000\n", "OverallQual 0.817185\n", "GrLivArea 0.700927\n", "GarageCars 0.680625\n", "GarageArea 0.650888\n", "TotalBsmtSF 0.612134\n", "1stFlrSF 0.596981\n", "FullBath 0.594771\n", "YearBuilt 0.586570\n", "YearRemodAdd 0.565608\n", "GarageYrBlt 0.541073\n", "TotRmsAbvGrd 0.534422\n", "Fireplaces 0.489450\n", "MasVnrArea 0.430809\n", "BsmtFinSF1 0.372023\n", "LotFrontage 0.355879\n", "WoodDeckSF 0.334135\n", "OpenPorchSF 0.321053\n", "2ndFlrSF 0.319300\n", "HalfBath 0.313982\n", "LotArea 0.257320\n", "BsmtFullBath 0.236224\n", "BsmtUnfSF 0.221985\n", "BedroomAbvGr 0.209043\n", "ScreenPorch 0.121208\n", "PoolArea 0.069798\n", "MoSold 0.057330\n", "3SsnPorch 0.054900\n", "BsmtFinSF2 0.004832\n", "BsmtHalfBath -0.005149\n", "Id -0.017942\n", "MiscVal -0.020021\n", "OverallCond -0.036868\n", "YrSold -0.037263\n", "LowQualFinSF -0.037963\n", "MSSubClass -0.073959\n", "KitchenAbvGr -0.147548\n", "EnclosedPorch -0.149050\n", "Name: SalePrice, dtype: float64" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "corr[\"SalePrice\"].sort_values(ascending=False)" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:54:55.079333Z", "iopub.status.busy": "2021-02-26T23:54:55.078643Z", "iopub.status.idle": "2021-02-26T23:54:55.085486Z", "shell.execute_reply": "2021-02-26T23:54:55.086051Z" }, "papermill": { "duration": 0.039167, "end_time": "2021-02-26T23:54:55.086240", "exception": false, "start_time": "2021-02-26T23:54:55.047073", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "0 856\n", "1 1262\n", "2 920\n", "3 961\n", "4 1145\n", " ... \n", "1455 953\n", "1456 2073\n", "1457 1188\n", "1458 1078\n", "1459 1256\n", "Name: 1stFlrSF, Length: 1460, dtype: int64" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "train_data['1stFlrSF']" ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:54:55.147706Z", "iopub.status.busy": "2021-02-26T23:54:55.146998Z", "iopub.status.idle": "2021-02-26T23:55:07.522226Z", "shell.execute_reply": "2021-02-26T23:55:07.522790Z" }, "papermill": { "duration": 12.4076, "end_time": "2021-02-26T23:55:07.522978", "exception": false, "start_time": "2021-02-26T23:54:55.115378", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "<seaborn.axisgrid.PairGrid at 0x7fbc2b3ba7d0>" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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kISdZhwStHB0OL35RYoRG2bPYQSAkOEwgEAj9SF+dgdpWG46ctWDdjkreQSkvMSIzToMRCT2TGmBJUlLYhNKk/Khs+gW7xnYnVKfZUMGB7eXTca4j9FgJDCgn64lzSRj61LXbUdfmwLP/O87fK7/68WjUtdt7PA8Soh+xOTWceVlszn1qXj5yU3TITdYP6DwaysbkdtoYQmh6agPPtw4LZYclNC7K9Qmn8zyBMJQ5bbJh9bYjKC1MA0UBDAus3nYEWQnRc1/YXAwe/Nd+wZwRTRA/YuggZt8kNPDRwXP9EjsgwWECgUDoZ/riDDR2uPjJHfA7KOt2VGJChiGsCZ5hWOw83ogDdWYwLCChgIL0GMwcnUwWAuehp5qUvVlonS8APTUrQfQYkm1GuBRpsriwac9pXisUADbtOY3CtBgSHCaEBcOwOFjfjmPnOrB0eha27qtDg9mJx94/hGUzslDb6hjQeZRozPeO3trAUOuwUHb49bsmh319SKCFQAgfk82Fuy8fCZPdzfsld18+Eq02V1TMfdG+sUf8iKFDd9szeUQ8aJrC19WmPsUOAiHBYQKBQBhE2NxeUQfF7vaGdXxtqw3VzTa+KZpSRmPF1TnITrSRoEo3Ao2sWi5FZrwKNSYH//dQmpS9XWj1JjgQ7YtSAqE3ONxe3Do5E89/eoK/xx6YlRP2PEi4tBGbo8tmGrH9UAOm5yQhLUaF4+c6MDZVN2B2MdqbMkWK/raB3e1waowSN05Ih8nmQnlJNt6u8G8iAOLXhwRaCISeoZJJ4PIxQX6JUhYdDWajfWOP+BFDg/PJH3oZBkunZwEAvxHek9hBIKQhHYFAIAwiMuM0oo1zwtW2arK4sPaTE4JFwNpPTqDZ4ur3c41mOCN73fovcMsrX+OmjXtw/0wjMuNVSI1RoqwkG88tKALLIqgpTaiF1mmT7bzv2ZumSOdblBIIQxW1XMoHhgH/mH/+0xOkOzghLMTm6PU7K3HPldn+Ri3vHsRfdlfju9r2AWsKF+1NmSJFX21g9yaASbouO5wao8TiqZl47ctq3PvG9/jL7mrcflkmUmOUIa9Pb+0/gXCpYnf7RP0Su9sX4TMLj2hvHk38iKFBKNvzVbUJS16vwIad/sari6d22bDe6GIPyCqboqi/AigF0MSybH7nY6sBzAXAAGgCcCfLsmdFjp0NYB0ACYBXWZb9w0CcM4FAIPSWvpQcjkzQ4I8Lx+GX73TtDP5x4TiMTAhvgjc7PKKLALPD0+PPMRThrk2zxRVkZB97/xDeXjYVVc02PPLewZBZQaEWWjUmW8jmc8l6fxOlnjYrJNlmhEuRdjKPXfL0xY6GmqOPnesQzPmPvHcQRemxGJmguegyAaQ5We+4kA1kGBa1rTY0drhgc3uRGafByITQ+sIbbh3P2+EbJ6Rj/c7gUtzX75qMRJ1C9PpEexYhgTDQhPJLOqLEnvdHo/FIQvyIoUEo21NR0xq0Eb5sRhaGG9TIjOt5E+eBSsH4O4ANADYFPPYsy7IrAYCiqDIAjwO4J/AgiqIkAF4EcDWAOgDfUhT1b5ZljwzESRMIBEJP6Q/NX4VM2NVXIQvfedTIJaKLAJU8Osq3LiaBjuLS6VmiRtZkc/OBYe6x7uVXoRZa359pR4fTi//LTwVNUyHLfz4qm94pZSGB28fgdLegciDRviglRA+DSUeTzGNDl3DG2flK9wFc8PhQc7RPOOXD6WFw9FwHTpmsWP7m9xddJoA0J+s557OB3HqrstEqaMTDXT+xTKvlb36PN5dOwcs/mRjS2WbBhrxGfQm0DKY5lkAYKIaCPdcoaDy3oAg2txcauRQaRfQU3xM/YvATjm3oybomLUaFDbv8msOjkgah5jDLsrspihrR7bGOgF81AMTquiYDqGJZthoAKIp6C/5sYxIcJhAIg5LaVhtarS7kJOlgc3mhUUrRanWhtjU8zd9TLTbeSeVQymj85/7pYU3wUimF8hJjUMdSqYQ4IN0dRTEjq1FIRZ3Fxo6urCCxhRanZwkAnxxtRJpBhTXbj4o2nxsRr8Gxcxbc9fdvLxiMINlmhIFgsOloSugQ8xgZ91FNuOMsVPnk2PLpONJgueDxYnP0ytKx2Lj7pOB8lDIaJxot/HsEvlc4eozhBrpJQLD3nM8GVjdbcaDOjI27q2FQy3HjhHRQFHg96VDB38pGK5748DCWTs/qcaC3t4GWwTbHEqKLaJ5Hot2e17baUNNiR4utq6FevEaOzLjo6OVC/IjBTbi2Qcz2/O6GAqzbcULwekoZjdo2B2pMDtS22gZncDgUFEU9DeB2AGYAV4k8JQ3AmYDf6wBMOc/rLQOwDAAyMjL670QJhH6GjNWhi9nugY+l8OC/9vOT9xNz8mC2h1c+VdNqE3Vmwp3gpRQNjVwiyDzWyCWQ0z3f5R5q4zTQUdy6rw4PzMoRNLwqLzGi1eYWbUzn8bFgGBY0TfELrfi7JuOLqhawLLD9UANm56fyJapcwHjz3hq+uU2gxldPmkOQbLMLM9TG6kAz2BqWyKUUhsUqBfPYsFgl5NLod2Yu5bEa7jgLFdRr7AiWA1rx9g+IuaMYKXoVLyfQ3RlWSSVY/Z/DuKk4QzBHrywdiw07qzB/YnrQe11IJiAchy7aA4KDZayGsoGNHU4wLGBQy7F4aqbg2g6PU2NYjHimlbpzE3j38SY8UZqHVdsO88etnpuP9BjVec+lN4GWwTbHDjUGy1i9GET7PMKyrKhfwrADo/feV0xWN2xun6ChXnmJESarGyMSevZakRqnxI8YvIRrGwJtT2OHE3IpDZPNhXuuyMaqDw8LYg7//LrGb+t60acjojnxLMs+yrLscABvAFgu8hSxGS/kTMKy7EaWZYtZli1OTEzsr9MkEPodMlaHLg6vDy9/XoUl07KwfGY2lk7PwsufV8HhDa/xglouFW18EO4EL5fSotmnMmnPp/uhNk65khyuO/mIBA2WzfBfpyXTsrBpTw1+seUHrLo+X9A0qGymESs/OBjUcMbtZfDqF9V4cVcVpuckBWkXrt9ZiRsndAUduIwkLvCRGqPEfVdl8+Ok1UaaBvaWoTZWB5rB1rDE4wM27zmN7CQdhseqYEzSYfOe0/BER/+a83Ipj9Vwx1lgAyBuniwryYaPZWBQy4OO31Pdiv974QtsP3yObzBH0xRGxGuQpFPCy7AoGZOCLRW1WDItC2Ul2Vi7aBy2fFOLNrsbuck6LJ/pn4u5Ri4XkgkIpzFZtDcvG+xjNVmvhIQCFhYHawc/9v4h7K8zo2ymUWDPV5aORX27HZnxKtw304h2hxur5uThhVvGo7zEiA27KrH3dOt5GxVygZapWQnIStSGFaAbbHPsUGOwj9W+EO3ziFzql5XI6bTnOck6KGU0FJLokJVwen181jPQpU3uDNOvC2Qoj1NC7+huG1JjlFgyLQtHGjqw/0w7vN6uv3Hrmja7Bw3tThyq7xDEHJZM88ccrsxNQnmJEUk6RY/PZ7C0fX4TwH8APNHt8ToAwwN+TwcQ1LSOQCAQBgtWpxd3Xz4SJntX+dHdl4+E1eUN63iVlMYj1+YGlS8pwgzuOjw++HxCp8bnY+EYClGVPpIeo8Lf75qEZosbMSopfCyLdyrq+MxeDofHhyXTskBR4LOCSwvT+PLjEfH+5kWPfXAQK0vHYvW2I6AoiDp+qhCd6TPjVUFZbMYkLSZ0ZicTCAPJYGtY0u7wYE5hGqqaLPw8OKcwjTSki3LON84Cy6aTdEpsuHU8Vm87IpgnN+72Z2z992ADpuckgaL8Y0Mpk8DpYbBm+1GkxSphd/uQpFPyWsJLp2dh67463DYlAyl6JWrb7Fi97QjkUgp/vm0CDp/1K919uL8et1+WCWOy9oIyAeE0JiPNyy4uI+I1KEiPQbtdvOFVnFqORosLzy4oQn27HRanDxanB43tdjy7oAgNZiecHh/+tKMSbXY3ymYa4fayqKhpRbpB1a/XaLDNsYToIdrnERYM1AoZTjR22XNjsg4sxVz44EGAy8OIfv9ub3ScP2FwE2gbCtP0uGlyBlZvO8L7hk/Ny8e8ojRIO+MA3GbRqjl5YFigxuTAi7uq+MSnOUVpmJhhAMCits2GzB5KiEQsOExRlJFl2crOX68HcEzkad8CMFIUNRJAPYCbAdw6QKdIIBAIPSZBK0dlkzWo/Ci+W7ZTKDpcbihlEsHxT16fB6vLHdbxcgmN328/FuSAbFk2tVefZzASSnvtfI+fabPh61NtePyDQ4LSmwdmZeP5T6v4ALFSRiNeI8drX1bz2b3dy1XXLhqHRJ0cNSYHtnxTi7WLxoFhWVHHb2pWPN5aNkVQejoiXoPVcwuwbHOFIBPhoa0HUJAWExWLfcLQYkS8Bn9ZPAEWh4/XStcpJRFrWJKokeOkyDyaoAlvHiVEllBzcaBmnkEtx8LidOQk6UABomXTL9w8Hos27g3K2Hp+0Tg8EPDcB2bloDBNj9n5qbip8/ncmDGo5VDJaLTZ3Xju4xO8A3XX5ZlI0Cnx8ze+E0gBvfVtLf56x+QLOlPhBPtIQPDiQtMUZo5Oxv66NsH3nBqjxMLidIAC3D4Gz318DDcVZ2DbgXr87oZ8xKkVuP2v3wRJQHFd3n0M+j3wRppCEXpLtM8jUkqCM632IHs+PDa0fMtgIjNeI/r9Z8SRe5fQdzjbsGb7UdxzZXZQlcBj7x+CMUmLouEGAF2bRS02F7SdzR4NajnuvHyEQCpxxdU5UEppZBhsGNkDWzYgwWGKov4J4EoACRRF1cGfIXwdRVGjATAAagDc0/ncYQBeZVn2OpZlvRRFLQfwPwASAH9lWfbwQJwzgUC4dOlL4werS7z8qOD24rCOV8tlePzf3wmOf/zfh/HG0pBy6wLsbp+gMQvg19e1u4dG5nAo7bVrxiTj46ONIR9nGJYPDAP+73XVh4excfFE/GKWEWfaHPhwfz1unpSBZL2Cd+JunBBcrrri7R/w9rKpKCvJBsMCp1qsGDtMz2cRBzqcAIupWUJRMpqmIJNQITQ1/UHqaGw6QoheGIZFs8WNx97v2jx5al4+r7M90NjcfZtHCZHjQvqYs/NSMLZ8Or6rbccj7x2E08OgrCSbDxwAXfPsS7dNEJ0nj57rEDz3+U9P4JkFRfh1p9Y/9/i6HZVYflU2tHIp3xCpwezEa19WY+Pi4qANuvU7K7FkWhaarU6MStKKrgUA8I+9srgYj31wEDUmh2iwL9yAYDQ3m+orvfnsgcekxihxtt3JX1+DWo7bL8sUNL8qm2nElopaPDEnDwxD4fF/HxK97i/uqkJ2ohbnzA6k6JW9Pj8xSFOoyBLN91iGQY2n5uUH2ecMgzrSpxYWFpdX3J6nxUT4zMJjZIIGG24djwN1Zj7zuSA9BiMTSHD4YhLN9ywQ/vlztiEtVokdx5pE1zznzE4UdWopJOuVyIxXgaYo5KfpUV5iBAA+MMwds/aTEygvMeJMm71H2cMDEhxmWfYWkYdfC/HcswCuC/j9IwAfXaRTIxAIBAEMw2Ln8cagRcDM0clhTaxWt1d0Yre5wgvOmu0e5CRpsXTGKDhcXqgVUryy+yQ6wiynTtErgxyj8hIj7+hEO6G017Ysmyp43KCW49i5DkhoQCmlYff4RK+L2eHFnz71l5SuLB2LdIMSww0aDDdoMPr+6TjS0CF6XG2bQ5AF8XjpWLz33RmBHMWWilrMzk8R/RyhMkE8PhbXrf8iKpuOEKKXww1m3vEExLMVBhKLU3weDVeehxA5Qs3R8XdNRqJOgRHxGjAs+MAwADCsuCyPRiEVnSd9AU9NjfHbPGkIaZ9ErQIvfV6FhROHY9WcPKgVUpjtLjg94mNMQoOXuege5N5w63i4vazgsTXzC5EWq0ScRhHk/IUTEIz2ZlN9oTefvfsx3MaCQS3HkmlZyE3R4VcBmwQGtRxOrw/3XpENCUXB7BSXoKAo/9iSSWi88U0t0gwapMeqRTede3ttSFOoyBDt91htmx0vdG5gcOvLF3ZWYkKGISrGktUV/fbc7WUFa/61i8ZF+pSGNJG+Z/samO7p+dM0BbvbB4aF6JonJabLh88wqPHgNaNR2WRFi9WNb6pNuGlyRkhppXNmJ06bbGHPFRFtSEcgEAiDjdpWGyob/eXMG3ZW4S+7q1HZaEVta3iNHwxquWhDuVi1LKzjE3Ry3DIlE7/+13489O5B/Opf+3HLlEzEh1lObXF6RHfoLc6hodUZSnvNrx3of7wwTY/lM/0O4882f4d73/wOKplE9LpUNlmweGomDGo5Vm87gvTYrm73FAVUNVlEjzvRaBF8x09uO4Il00bhtS/94+a1L6vx0OwxIUtGuYyywEY5a+YXYuUHBwWvG01NRwjRS+D9w8HdV5EgSacQve8StT1vrkEYWELN0V+fasV16/1N48SeI3a9k3WKoHlyZelYbDtQD8AfGL5nRhYA4Hij+Fwdo5LhpuIMbNhVxdtUCS1BfbtD9PkTMgy8rnz3IPeBOnPQYw9tPSAIVnfnQs3Lor3ZVF/ozWfvfgy3sdBgduLFXVU4HmCbA9cCD717ED/7xz5o5OJrAZoCHpiVgz9sP4rSwjT88p0fcKQh+HpfKtdmKBHt91hjhxNub1cvEYryByujpZmhQSMTvefiwvSLIk20j59oJJLfORfYvW79F7jlla/5dcv5mpR2pzfnn6xX4sP99UFNVJ++oQB5qV1Z9nXtdtR1Jii1292YlZeCow0dIdc/HU5Pj+YKEhwmEAiEABo7XKLB1cYOV1jHO9xePDArRzCxPzArBw5PeDvkrk65g+7yB64wGx+cHWRBnv4msIs9h1JGIzVG1fmvEvdcmc3LOwBc8PYwnpqXL7guZTONeKeiDut3VuLGCelwehg0W7u+p8YOJ96uqAsy1M8uKIRcQgu62zs9DCqbrFgyLQt/+ckEfFQ2PeQOMbcjnaiTY8uyqfjnT6fgo7LpGBarRI3JIXiu00O6mRMuPola8WBsQoSCsR6GQXmJ8L4rLzHCw5AGMJGEYVhUN1ux52QLqputos6SWi4VHUsjEjS8g9T9OVv31QVd77WLxiEjToO8YTo8t6AI624ah2cXFOHTw+dwU3EGlDIaN05Ih8nuxrodlaJz9QOzcqBXS4OkgVZtO4zhceqg93xiTh5iVVLQNCUawA6V4fxFVUuvHEjg/M2mhjrn++yhxprJ5uI7sy+fmQ2tQjzYG2ot8NsPD+PpGwqCNhy0cgkYlkWNycE3mG0wuy7ZazOUiPZ7jKuO4JIPXv2iGrdflhk1FYFSiha15xI6OsJQ0T5+opFIfuf9EZjuzfmPiNfgodljsKWiFkumZaGsJBsv/2Qi5uSn8s3o/K/t4iWU0mLVWL3tiOj6p7zEiDidHAzD9kifPGIN6QgEAmEwYgshC2F3hxfcVcslePObGkH515vf1ODZBYVhHd/YIe6MNFrCC05zQdLzlaREM6E0HPNS9Vi7aByOnevAsXPBUhA1JgfMdg82Li7GN6dbwbLA5r01fNCcooDMeBVUUgn2nGxBsl6J1Bgl2uxubN5bg+VXZSNRq4BBI4fN5cWGXVX8+3N6hi4vg9e+rMZHZdNDlu+EKjWaMjIegHg5UbQ0HSFELzIphVXX5+GJfx/mx+Wq6/OgkEam5LbN5sGmPcJ5dNOeGowgGn8RI9wySbfPh7KZRkETz7KZRpxttwPw2zOPzyeYx9vsbhiTtfjP/dPRbO2SXwCAfTVd2sTca20/1IAl07IwMkGN0yY7vwG6eW/XmBmdrMPvPjqKW0KUWx5rsOCNr2v559MUYHG4oVf5q3TEpH8klPgczbJdDmTueeZ/MaK92VRfCPXZE7VK0bGWN0yHGpODbxjLbQA8cm0uXvt/p1BamAa9QoKnbyhAjckWci0gl1CCuWXDTn9T2uUzs6GU0VBKaShlNLRKySV7bYYS0X6P+RiIJq1cM1Zctmyw0dDhFLXnGXHRoZkc7eMn2mAYFl6feJPvgfjOzxfYDde292bMcDJUo5N1qG21QS2XIlmvEASGAcDeGae4/bJMXiYp1PonI06NYQZ1jxqfkuAwgUAgBJAZ17eutFKaxu2XjcCz/zvOOy+/+vFoSMPcIU/QyUXfP1xZibxUvWjjisCSlGjmfBqOs/NSIJNQ2F9nFv0OzU4PZBIKr35RHfQ3jVyCe6/Mxk2vdHW6f2Z+IV64ZTyqmqxI0CpQ12ZHa2eWWuAiff3OSrx02wScOGfBhlvHn9cIh9qRzi2bTrqZEyIGywI7jjbgL4snot3uQaxahjf2nkJuii4i5xOvlaPN7saLu6r4x5QyGvHq8OZBQv9zvrkr0GGK1yj4zJdA/fXSwjSkxiixsDgdHU4vxqbqgoLBNE1hVFLXa1U3WwXaxNx8u2RaFrYdqMfjpXk402rn53tOWkApo7FsRhYazE74GCbIHmTGq1CYHguGBdw+Blv31aHB7BTM32LzcUF6TNBjZTON2Ly3hj+/njiQod7nUpn3Q312CQ3RsfbcgiI89r5wPPg334vwy2tG42STFX/7qgZyKYWHZo/Bkc5S2+72ngLFB5gDH6cpYGXpWPh8DB65NhfDYlSX7LUZSkT7PdZkEQ9WcY0zBzvJOoWoPU/SRYdM1Ih4Df64cBx++U7X+PnjwugZP9HGaZMNj31wMGiTec38wgH5zi8U2A1Hj7gvc87xRgt/XGa8CqvnFkAmofj3itMokBmvgl4lC7n+WTItC212N1QySY+a0QEkOEwgEAgCRiZo8Nc7J8LrA1ptHsRpZJBKEHZXWrPTDYNaiucWFMHm8kKjlMLt9aLD6Q7reI1cgifm5PHSElypq0YuCet4qZTG9QXDMCJeg3MdTqTqlSgYFhO08xjNhGrqQtMUshK0eOo/R4IWFU/MyUN6rBLHGjrw4q0T8OS2w3yH+ZWlY5GTrMUXlS1YOt2vX7l1Xx3++Mlx3D/TiLe+9Qc2JDSQm6JDTpIWzVY3bpyQDqrT3p5otOBPOyov2KTiQjvSpJs5IRK4fQxm5abA4vDC6fbBQlOYlZsC9/nEVC8iCimNNfMLcLLZxjcGzUrUQDGE5rFoI9xsGq40MtApKi8x4r8HGwTNUgOdHqDL4TLZXJBLaNjdPjg6G4mmxigF823+MD3yUnV4ctth3H35SJSXGAVNWNfML0ScRoYtP5uKFL0CY1L0OHKuA1KaRk6yFm4vg2WbK4KqP8ak6Pn5lttwHFs+HY0dLtjcXmTGaZAZp8ZHZdNRY7Lh+zPtfGD4vquyIaEBlUwKhmHDnrfDaVo3VAn12b8+ZRKMNe76MyyL+2dmI0EtQ2KMCi5uA/5f+3l7zgXrj5/r4PUbu68FDBoZnr6hALUmG96uqOMb0ibrFVj/aSVONFnx6h3FyIzXIDNec0lem6FEtN9j0Z65KpdQeGZBIaqarLw9H5WkhVwSHd8/w7CQSuD369xeaORSSCXo0TxPCJ/GDidqTA5BJizLAmmxyn7/vsUCvecL7IZbQRVuM9rA984wqHG4wYxj5zqwdHoWdh9vwuz8VKz84CDvg07IMCBBK8dvr8/Dz//xHQxqOR6YlYPnPz0RtJ4pLzFCo5SEHb/gIMFhAoFACMDrZVDf5sLKD7oyb1fPzYd3OAN5GAHaWKUcxxqsWLfjsMAxHhkf3u5+h9ODRJ0cGxdPRJvNA4NGBrePgcUVXkM5hmHx6fGmqO3K3Fcy49RYfpURG3b5s8skNDAx0wC7y4efbt7HfydPzyuAVimF28ugzebimxAa1HIsLE7HiqtzoFVK8doXJ3FTcYbAuVx1fR7itXIcqDODYYEP99dj2YxRMKjlFywrvtAin3QzJ0QCrVwCUBQe/Nd+fpw/eX2e//EIIKEBj0/YHfypefmQROZ0CAg/QNHdKUrWKWFxejAyQYNakw3Lr8qGVEJBp5QJArRPzcvHW9/UYGZuCj/flpdkIzNeFTQHP146Fh1OD2pMDry826+/+eyCIjg9PqTEKHH0rBmVTVZIKGBCZiysbq9gLJWXGGFQy/lGjOt3VuLPP5ko6kQdabCI2tMR8Ro4PAzkUkpwfht3V/fY5l7K877YZw8ca6kxSiyemsl/v5nxKtxzRTbufeM7wRqtw+FBm8ODLRW1uHFCOnYda8K9V2bjpc+qBGsBi8OLJa9XCI7Vq2Sobrby8hIAIKEo/vpdqtdmKBHN91i0Zz5LJBTcXkbEnkeHT3KssQPVzTbBBmR5iRFpsR3IT4uN9OkNObj5n8uEBfxrjfkT0vr1fc4X6A0V2K1utoZVQQWcf87p/t6Z8SrcP9MoqPrdcOt4VDdZsWzGKF47XynzN6gbFiPnz0EppfHrH49GglYBmqJQ127H3HFpSDOoMD7N0GPfn6RgEAgEQgAHG8x8YBjwT/wrPziEgw3msI63un2i2mA2ty+s41VSKWpMdizbvA/lW37Ass37UGOyQyUNby/vUu6qyzAsDp81o7HDiQevyYVOKYGPAY6c7cAD3b6TR98/CFVnxlGjxY0ntx2BQS3H4qmZ2Li7Gr/61wE8sOUH3D1tVFAzoyf+fRgH6sxYv8PfGGTZjFF477szfFO7GpMtZFMibpHfvfFStCzyCUMTq8uHx/8tbIT5+L8Pw+oKb97qb+xuhl8kc+fz2PuHYHeThnSRIty5KzAbJkWvxNFzFizauBerPjwCHwts2FUFi9MX1CjssfcP4fbLswTz7dsVdfjN7DFBc/Bfdp/EmFQ9ykqyMX9iOjbtqcH9//webTYXDtWbsfbTSmzYWYW/7K5GXZsTL+z0N2+576psLJ2eBafHh9svy+TP2elhQLHBWWDns6dcEHz9zeODzu9SsbkXi8CxduOEdMH3W1qYFtS0d+UHh9Bq9/D2uDA9Bj+ZmoFWmxv3XpGN3BQdVDIJjpzt4DfAAo89fNaMNduP84FhpYxGcpQ0+yIMfWiawqzRSfjHkinYcOt4/GPJFMwanRQ1CR+OEPbcESX2vM3uwVvf1vKNMJdOz8Jb39aizR5e0s5gIZyGsoOBgfKTLmTfsxK1mJqVgKxELX+v9VejvO7vXVqYhsfeP8SvU+69MhsUKPhYBK2VHn3vIJweoDgzBjdOSMdfvzqFBJ0Sta12cFfUxwB//Pg46syOEGcQGpI5TCAQCAE0hWgI1xRmQzibS7yhndUVXkM7p9eHTXtO86U0ALBpz2mMuaEgrONDGa7Gjp7pIEYbYjvAj5eOBQAYVF07rIHlyRanFw/PzoXJ7obTwwQ5oU4PI9rQxulhwK2pnB4Gq7cdwdpF41DbaoNSRuP7M+1weBjRzDG+4cD90wUNBwiESNJu94iO8/YIOT8mq1v0fEzW8OR5CP3P+cokAyUhzrY78dDWA3B6GJSVZPPZYjdOSOc3TikKotfX1SkjwdFgdqKyyRokMXBTcQZ+FlAJwpVR5qXF4OtTrQJ5oNXbjmD5VdmgKUqQfbyydCxSY5RoMDuRGa+CQibBt6dNvKRFsl4Jky3UesDJO4x2t++8zyGET+DGwthUHV6/azJOt9gE32+oscM9vnrbEZSXGBGvVQgy/VaWjoVCSouuBcYPj0VmvIqXpiAbtoTBhNfL4H9Hz6GyU5ahstGCBrMD1+alRoVkXEsoe26LDnvOMExQ9UrZTCMYJjqC20D4DWUjDWcDEnVybFk2lbfFF0MGpjeN53oj8SImXdH9vSkKfIJS4DhbPTdf9By/P9OGX83ORZvVgxHxapxssggkkj460IAak6NX6xASHCYQCIQA9Eqp6MSvU4Q3XSZoxRvKJYTZUM7l9YkuQtze8BYharkUmfEqlBam8cHlD/fXQx2h8vCB4lRL8A7wk9uOYMm0LDjcfoePM7xcc6TjjRbkD4tBfpoeG3dXizqdDBu6Oz0HF0TOSdLxeodtdvd55SUCGw4M1kUa4dJBr5KJjnO9ShaR84lVi89jMSqybI0kYmWSXi+Dr6pNqKhphTFJxweGAf/8yf2/+/wqNt5SRByv7g3lxDbx1u+sxOt3T0KNySEoXX54di4sLi+GG9SobrEKpCRWd9qHbQfqcc+MbPzm3QNBtnfN/EI+aBh4noGOYLTrgQ4WAscRJ9e05sZCaBRSlJVkg2H9wX7g/DbZ6WEQp5bj8W4VYKu3HcFzC4sEa4Hu1zotVok4jSKq9GgJQ59jjR2oa3MESeMca4wOWYOYEPZcr4wOe65VyERtzhtLpkT4zMIn3IaykSRUAHvKyHjBJvT5GsH1hN7Y7p5KvIT6TKOTdUHvHdiTAfBfo7o2u+g5yiU0ak0OgQQmt95p7HDiVz/Oxbodx3u1DomOu5JAIBAGCK1SGtTcprzECF2Yixgfw2LF1TlY+0mXOPyKq3PgQ3jlO0qZVHQR8rc7J4V1PMMyuGdGNlZtC2hoV5oHlh2c5UP9RU2rMLsI6MomeruiDuUlRjg8PmypqA0KADw1Lx+PXJsLk80dZIQ/3F+P1XPzBQa4vMSITXtq+OcoZTR8DMCCBcOymD8xHQDQanOJLrqiYZFGuLQwOz18Fj3XMCZOLUeHMzKZw2q5FPdckR3cmDPMTTrCwMAwLP5zqEGQKdx9Hg6cU7n/b91XF9Qo7Kl5BVi343jQ4xnxakHDFQkdvIlnUMvh8jCCgKBBLYfd48OGXVWCjdbNe2v4AHFOshYP/TgXK97ZjyXTsoJs70NbD2Dj4mKBNnJ3RzDa9UAHA93HEefoHm7owLP/Oy64fjuPncNT8/IF2ozcdQW6NrXE1gN1bXZ+LSB2rT8iNpgwCGm3e0Tl6grSYiJ8ZuGhlklE7Xm0JK2YbOKZz61RkvkM9C5LdqA5n280Il7T75nPvbXdo5N1eOm2CdAopEjWKZARFzpIHeozbS+fjjXzC7H2k+MoLUyDXiHF6BQdv4HN8XZFXZAPWjbTCCkNgQSm2HrnqXkFyDCoe/y9kFU2gUAgBNDhdGNYrBLLZmSBYQGaAobFKtHhDG8RYPd4YVDLBF1tHR4vHGFqd5od4uXdZkd4QRqaovjAMHfsqm2HsWXZ1LCOj1Y0ITKmWdZfmrxpTw0euW4MSgvTgpzCx94/hOVXZSNWJcOT1+fj8X93GeH7Z/o3Bv5+1yR8ddJfcpykV6DN7h8PgQ7ryAS1wDAbk7SYINLNOBoWaYRLi0StHKdbbILMpBVX54Rd8dDfmB2eIF3RVR8exsbFEyNyPgRxTptsQZnCgcHgrfvq+M3WwP83mJ3YUlGL5xeNg8fHQCahQVNARY0Z9e0uQYfyZosLr3/l71oeo5QgPz2Wfy8uk/T2yzJRUdMmmFcDZSyAro3W5Vdlw9EZZJZJKNS22gWyBIE4PQxkEgofnafjeDhdyQnnp/s4cnoYmOxufj7iHlu/sxLPLxoHi9ONl26bgCNnOzAqUYs/bD+KBrOT37z1sQwemj2a7/WwdZ+/3Nbi9OHd7+rwyHVjRK/1UJffIkQnoaRr7GH2Mok0VpdP1J6/entxhM8sPDRyiah/oYqS4DYQHRUuF9Lz7e+kmp7a7lBZwBlxmpBZzaE+07FzFoyIU+NnM0bhyYBmcyuuzoGPYXnb9eH+ejjcXjy/aByOnuuAjwG2VNTigVmjL7jeeez9g5iQEUtkJQgEAqEvyGgJNu+pxO2XZ8Hh8kKtkOL1r6rxy2tywzo+RinHsQYr1u3o2iEvLzFiVJiTcyhZivgwgzTRvojsLSkxiqDMhFXX52H7wQYA4IO5YllnTg+DlBglfD4WrTYXykuMsLl9YFnghZ2VKC1Mg0JK452KOtw4IR3tNg9eWVyM/XV+beEtFbX4zewxQU3vHtp6AAVpMUGGOZxFWn+XTxEI54NlwVc7AP7xu/aTE3hzaWTKJh0e8Xms+2OEyNLd8emeESyXUihIj8EriydCIZPA4vTg+ZvGocZkg8Xpw5PbjqDN7saSaVkYk6oT7VC+bEYWGsxOv/zDFdm4++/fCjJoKApYt6MSS6dnCebVUMHeFL0SjwVk4awsHYvMeBX/ft3n5WS9MmTHcY7zdSUnXBgxBzpQkoTD6WHgZViwLAWZhIZeKQVNU5g7Lg0M65/H/nuwAdcWpAZVf2kVUrz02Um02d2QSijRa62JomAP4dIhVi0u+xSrjozsU0+Jdr9EqxCvZApXbrC/6Y1/EA0VLufzjS5WUk1PbHf3LGCDWo5j5zqgktGQ0jQe++CgQLd+dl5KyM90sL4DRxo6gjZA135yAs8tKMKxRgskFPDLa0bD5vRALqUwJkUPt4/BL6/JRXOHM6z1Tm82PElwmEAgEAJweX2YmZuCX3d2tO7S/A1vEWN3+/iuttwO81vf1oZd/pWklweVkKyem4/kmPCCw6EM0VDuvM0wLNpsHjSYHVg6PQtb99WhwezEE/8+jLWLxqHaZMM9V2Tj9a+q8fMrjaLfj1IqwfJ3vueDBRTllwi5eVIG4jRyJGjlAj0o7nnD5RKUFqYFNU0C/Ib5ZLMVGQa1oGnIhRZp0dI4gjB0aLL0rRFnf5OgUYhm6sRFKJOZIE53e8NlBP/tzklQymicbrHj0fcOBkn5rOxsFgp0yf9s/PwknpiTJ3DA/3BjAeI0Mvz9rkmgKWBZZxM67rj1Oyvx3IIiOD3BUhUSShjsTY1RYmFxOnwsK7ATq7cdwWt3FONwvRkrS8fyncEHo/M8VBFbt3S/foD/98omC9bvqOIDNKeabVi/o4p/zkOzR8Ph8QmaEq7bUYk//2QC0mIVKCsxornDKSof5vFdXPktsulL6A1JOoWoXF2SLjqaGceqZaL2PDZCPQ16CkVDNPP57Z8NfEVmb/2DaKhwuZBvdDEyn3syJwcGqFNjlEG69StLx8Li9MDq8mHN9qPITdGJfiZOBmn+xHTRdfeJJgs27Kzi7ZIxWYuTTVas/bQSv5hlhN3tQ4xSJogVSCj0W78hEhwmEAiEAEJp/r5+1+Swjnf7fLjz8pFYs/0Ybwgemp0Lty+84PIwvQapsXb87c5JaLG6kKBVwMf6MEwfnoMaDbvD/QHDsDjVYkOD2Y4mixuPvHcwyPACAFgWv5k9BhKawk9nZIOmWVH9prp2O4CuxjVLpmXhtS+rUV5ixJ8+rcTPr8gKcjhXbzuC5Vdl48VdVSgvyQ6xO2yG2eHBvKI0PkB8oUUa0SQmDDRahXgjTm2EMmOcXg/uvTIbT/xbWAng8nojcj4EccTszYqrR2PicAP2nm7Fn3acwC+vyUVVkyUoILtsRhbuvHwE3vymBmNSdBidrIPV6cbrd01GfbsDBo0MDMOiyeLGmVY7VHKJwDG7cUI6KAqI08hQnBmDKVmJ8DIsnl1QhIZ2O0YkaHmtYoM6eHMvUH/461OtWL+jCpnxKrz8k4mQS2hoFBK4fQxOm2yDzokeaoiNo6LhMUHawpzznRqjRIPZyUvNcE3mbr8sE/EaOR4PmDcemJUDhmXR1OHCimty0Wi2Q6tQ4M+fHxXIl2zaU4PcFN15z7MvwV2y6UvoLemxaqTGCOXuUmOUSI/tuZ5oJHB5veL23Bcd9rzFIq45bLIOvOZwX/yDwV7hcj7f6GL4tj2dkwM3McUa4wb6jmUzjehwuHHaBBjUMmxZdhlMNif21Zj5dQcgHvD2df7q9Pi1xZ9bUISi4bFYd/M4gKVwuMGMNocHX59qxuYlk2GyuhGjliDNoOb7LvSl3xAJDhMIhCGH18vgcIMZDWYnUmNUyEvVCzI3z4fZ4YFBLecdT8AfCOwIU/NXr5RhzfbvBQZjzfZj+MeS8ILLtW12LH39uyBjEW6jlGjYHe4rgQadM8Tdg/lrFxWh1ebGine6MsB/9ePRSNIpsWFXJZZMy4KEBgqGxaDB7ECMSoYXbhmPUy02uH0MtAoJb5jLS4yQSmiBHisXWOA0NuPUckHTpMDntNndMCZpUTTcwH+G8y3SiCYxYaBRyChsuHU85BIarTYP4jQyuH0MFLLIzBsKqRRP/Ps7wX39xL8Phz2PEi4egQGy1BglcpO1eO2OYlicXiTpFKAo4ESzBXaXF8uvMuJkkwXvVPg1XwMDsgwLPP/pCbx6x0SwrF+bL92gwWtfVmFOUTrOmV2CLGJO/sHtZQUZOx/uV+G+q4wCp+jJ6/PQbneBBYtnFhRBq5Dg3je+C7ITnP2QS/zrgxqTA/f8Yx82Li7GTRv3kiDeAMCNJ86BZlkGFEXBZHXDoJFh5f+NgUYhQ3WLFRt2VqHN7sYDs3Lw969Oo8HshMPD4Okb8tHU4YLD4+MDw4D/Oj//6QmUlxjx0NaDfCWWzeVCm93Ny5cAfjueERc60NDX4C7Z9CX0lto2O17/6lSQ3F3esGDZssGIShbd9lwTYvNcLR/4MNpQ9w9C+UYXw7c91XL+Obn7ZmCGQc0HqEPJOHCPb6moRWqMEg+/9zVvL56ZX4gYpYRvWn64rj2oWkmQ3NT5mj6GQZvNA4fXh0azEyqZBA6PD3f9KAsWpxdVTVYUpccKGvI6Pb3vNzQgo5qiqL8CKAXQxLJsfudjzwKYA8AN4CSAu1iWbRc59jQACwAfAC/LstGhXk4gECKC18vg/f31gmyTp+blCzI3z0eMSooHZmVDLZfB5vJCo/T/rleFN1222sQbyrXZwgsuhzL8PdENGuy7w30l0MkKZaCPnbNAJZPwnV+dHgbP/u84ykuMqDE58OKuKqTGKJFwhRw2tw8quRR1LRa83RnE+N0N+Xjwmhw4vQzyhukFXWG5wMKyGVmYNMKAZTOy8PLuasilFF7+yURU1LSBZSHYHT5ndqJoeHifLxoaRxD6zmAqMVbJpDjb7sSBZhsYFpC0AFmJGqRESI4mdHfw8OZRwoXpzfgLDJAZ1HL8/Ios2Nw+QUbuquvzoJJL8Ot/HRA4PNsPNcDp9eEXJUacNTug7Jyfz7a5BE1An76hAHqVDL/6l7BB2eptR7B20TgcO9chyNgpLUwLcooe//dhPLegCL/eeggAsObGAtHxJKGB8hJj0OMVNa3nDeINpns3mhELuK6em48Nuyp57cZX7yjG0tcr+E17hZRGmkGFh6/LxckmK59hvm7HISydniV6nRO1Cj7beOUHh/D8onF45Npc/O6/XRVef1w4DjQF7DzWCI1cimS9sAt9X4O7Qz2oQ7h4mGwuzClMQ1WTxW+fKWBOYRpaba6oGDttdvGkm3Z7dNjzZL1CVIYmWT/wsh6Xsn/A+bYj4jU4bbLh61OmXttfhmFxtKEj5Jw8Il4juhk4JkWHl26bAK1Cile/qA66DlyibmlhGh7urGjlXvfXWw9g2YwsXjLiiTl52HWsAX9ZPBHnzE4Mi1Vh3afHBffJ3pPN8DAsHgo4j/ISIz471oRkvZIPLJeVZIt+lt7oeg/UlsffAWwAsCngsU8APMyyrJeiqDUAHgbwUIjjr2JZtuXiniKBQBgKHGkw84FhgOvYeQg5SVoUBmRuhkIjl8LHUngwQHP4iTl50IS5Q6xTiu8wa5ThHa+WS/tNN2io0t3JClWWs26HPzOMyw5yehjEqbs0S2+/LDMosMEFMRo7XNiwq0q0BJl7rQyDGiarG2NS9fjDjflQyqSQSSjRBUNPgmyXijTIpcxgKzF2eRicbXcKsuPLS4wRK1tVySSi97VCFl4FyMVgKAUEezv+AgNkN05IR4vNHdRQ5Yl/H8ayGVmCx7ZU1GL5VUaBnM8Ds3Jw1+WZfGCYe+6j7x3Eqjl5oo5ObasdOUk6wd9CbRCy6LINbXa36HjKTdZh9X+O8pk83OM+4csJgnhi392a+YUYFqtEvEYR1eNioBELuK784BBvt7mNdYNaHqTvWDbTiPd/qIdeJYPH19WsUuw617bZceOEdP41j57rgFxC4/W7JoMFi0StEqdMVly7/gvB/GdM1mLm6OTzdp0PN7h7KQd1CH1DJZPA5WME9nnF1TlQyqLDL4jXBMv6lJcYo6aHQEacBsZkrUDWw5isPW+lwcViRLwGG24djwN1Zn6joCA95pLxD/pr7XzaZENlkyXknBxqM/C5BUV4+qOjkEupINmjwKzfUM3PGbbr/y9/XoV7rsjGzzp7KRRnxmBRcYZAFumpefl4oZt8xbodlXhmQRHfGwkAX8Ua5AuzLBiG7dF3MyCrbJZldwNo7fbYxyzLcmIzewGkBx1IIBCiEoZhUd1sxZ6TLahutoJhLm6Tj0DOmsUX8A3m8BorWVxe0cYDFld42lgOrxcPzMqBsjOIwTnBLk94u3cUxeLeK7Px2pfV2LCzCq9+UY17r8wG8TW74JwsAHwTosDvu2ymEe9+V8dnFqfGKHHfVdkoK8lGaqwSqTF+ZyzdoOYXq0BXRvDSGaNEH79xgjCA0Gx14eg5Cx7Y8gOsLh/iNXKYHR68eOsEZMar+Oc9MScPsZrwG29w5VMflU3HW8um4KOy6aSkeYgRauF52mSLyPlY3d6gMb9uRyVs7shoAmoUUpSXCO/r8hIjtBEo4wS6HJLr1n+BW175Gtet/wLbD58bUNvWG0LZ4t6Ov8AAGUX5HZLzOUAcpYVpQdUXz396AsZkYaA3NUaJJdOyoFNKUV6Szc/VgH8MpMeqeIcuELHfk3UKPLegCCuuzgEL4MFrRgfZ5dX/OYo2u5u3r1zp57YD9UGvxwXxxL67h7YewGfHW6JmXAwWQgVcqQBTp5FLsLA4WN9x/c5KlBam4dn/HUfesBgoZTS27qvDytKxQeuBdyrq+LVAWUk20mJUGJGgQbJegalZCaAoYPmb3wfNfwfqzPw9Ebju4OhJcJfb9A08N7LpO3BE0i/pK3a3j29GB/jH59pPTvQqKzASeHyM6PrC030XbpBC0xRmjk7GvHFpmJYdj3nj0vhNo0jg9rLYuNvvI/5ldzXc3sE5li/GPRdq7XKwvv2C7xN4Pm02N3RKKVbPzefXGkoZjd/dUIAR8ZqQtulEkwWLp2bC7WXxws5K/GPJFDx4TQ423DoBWypq0WB2IjNehUmZcSgrycbymV3rmMDMYgBYOHG4IN4wJSsxSBbpsfcPobQwLeg8HC4vnB6G92+1CkmQ7XtqXj7OmR2obe2ZXzFYNIfvBrAlxN9YAB9TFMUC+AvLshtDvQhFUcsALAOAjIyMfj9JAqG/GMpjNdIZcbFqmejuWbiyEKHLmcNrPJCgUaBO5hDsMKtkdNg75G4vyzdt4N7br801Jazj+5PBNk4ZhkVtqw1tNjeevqEAj753EA1mJ7ZU1OKVxcX4tqYVPqZLzkEpo6FXSIIyjspLjNi0pwYOt1f0WnNGt/vjnbKU/GuoZRJs2lMDg1qO2lY7fhmgb7x6bj7kUgoURePV3ScxMkGNzPjwy/+GujRIfzPYxuqF6A/5mP7E5fGJnk/3xwYKqQQYFitswDMsVglphBKl+lMvdKDG6vlscW+zIAOzHw2dGZti9ra7qQ+VRePw+Pjjxbp/c3N1m92NJ+fmQyWn8XaFf0OwS3O4Hk+U5mHVNmG2zbFzHfjdf4+hbKb/NQBg+VXZSDeoUN1iw9+/Oo02uxsPXjMaw+PUKCvJRnGmAXEaOVaWjuWDhd2DeNx3F9gUDwCvUx8pHdmLkdl+scdqqGzaQAe6rs2OjDh1yCCy08Pg+9p2/GZ2Lv6w/RgsTg8/b3DyTm12NzRySVD24h8XjgMAnGi0hNzk4O6Jvlb0XAr9ICLJ+cZqpP2SvmK2i8vVmaNElqHFKu5XtUSgoVtv6a81eV/n1GjRLr9Y91yotcuOY01Yv6Mq5Pt0l8TqbgtWlo6FzenBhIxY0DQV0jb5GPD9Cl7cVQWPj0FWohbVTRaUFqZBp5RAp5Thp5srBBnFWypqcfOkDH4tAgCJOoXg9UNVQUm6pfIqZTTUCn+V8U3FGfxaKDNehQ23TsCxhg7kDYvBi7tO4PLsRAw3uDAiIfyxEfHgMEVRjwLwAngjxFN+xLLsWYqikgB8QlHUsc5M5CA6A8cbAaC4uHhwbqMQCBjaYzXShkshoUW1oZRhNqRL0ilEDUKiNjxtKavTy+vYBR7/1zvCk0tvsbpCLKLCy3zuTwbTOPV6GXx6rBGnWmxYt6MSv5hlxCu3F6Oh3QGVXIpTJis0cqmgIdzqufnQKaT4RbfxuG5HJV66dQJkUjqkBIjY45dlxWNMih4quQQuL4O3vq7BjRPSkZuiw3MfH+M7nwPAhl3+rKYXd1WR0tEBYDCN1XBQy0M1OIlM9DNOIxc9nzh1+Bnv/YnTzSBWJcWPRiXwgRSnJ9hBHij6Uy90oMbqaZMNa7YfFcxLa7YfRW6Krtcl7oEBsvQ4NaSdmr2B9nbF1TmI13aNJ6WMxpgUvej7xWsUeGpePs602iGT0EHZodxcLZVQONfuQGWjFW12NzbvrcGSaVlQSGkYk7R47cuTfJPRwvRYvLHnNPLSY/kMU86R27CrCi/eOh4AMH9iOmgKiNPI0NzhgEomwUNbD0IupfD0DQV44ZbxnbrIMuQm63lHM1mvDHLKOOeS07UdaB3Zi+WIX+yxOiJegzXzC/HQ1i596lXX5+Glz/xSUJnxKmQmaEBTVMggslJGI3+YHio5jT8tGof6dgeS9TJBk5+n5xVAI5cErQV++c4PfCA51CYHd0/0R3CXbPpePM43ViPtl/QVjVIiLjeniA5ZiVB+VZJu4DV7e0t/bb71dU6NFu3y/rrnun/vSbrQQdvzvU93Sazumeyrtx3BxsXFvFSI2GYgJxvBbUwqZTSS9UpMGRmPg/Vm3LRxD8pLjGjscGLp9CwA/urW9Tsr8fyicaAooM3u5s85JcQ6rPvvhemxgvVUeYkRr+w+iZWleVj+ZlejxxqTA8vf/A5/v2sS7C4v6ttdkNI07D2sAIxocJiiqDvgb1RXwrKs6A3CsuzZzn+bKIp6D8BkAKLBYQKBEHkibbjOdTixaU8N7xCzLLBpTw1GJoSnnSmTsHjy+jyB5s+T1+dBLg3PhltCZJ1aneGVf6XGqESNQ2B57aUGw7D4qtqEIw0dAn3LhnaH4Do9PDsXy6/KxvA4NU40WrHl2xrcPW2U6PX47kw7Ptxfjyfn5gu63D9eOhbtNleQltSKq3NgsrnxYEB28BOleXh5dxV0yoygQEHZTCNoGrwepcnmD+6TTCECADAsg9/OycNvP+wav7+dk4cQS6GLTpvdgwdm5Qg2Vx6YlYN2Z2QykzRyCWpMDjz+7+8D5uF8jE2NjDMZjXqhJptLdF5qtbkwISMu7CzI7s7ZrNFJ2LJsKmpbHTjeYsM/v6kV2Nu//b/TuOPyTCyZloWMOBXq2x3482dVgmxfzq7+eut+vvHY70M0jfvuTDte/aIaK67OQZxaxgejuY23tQuLUDImBTa3Dz4GWPn+IbTZ3bhx4nA+WMs5ck/Ny8eT246gxuTg30Mpo/Hn2ybg+U9OAABunZyJpa9XCByxcx1Ovox4RLwGq+cWYFlnZhB3nqu3HcGSaVl47cvqAR8X0Rb8ChxThcP0eP2uyTDZXDh2zgKX14ebJ2Ug3aBCh9OLn23eB4NaHrQJwWVjlZcY8WjnNecqerYEjMncZB2aLU54GWnI7ODdx5vw/KJxOHquAwzrD7zdPCkDIxM0yDB0rR1JcDc6ibRf0lc0MinuuSKbL0Hn5MoiJbPUUxweL56Ykxd0/g5vZGSrespgyjyPlrVIf9xzYt/7XxZPCNpQDNT65d6ntdPn4tYt3SWxAs+NqwKyu704bbLxftrsvBSk/XQqdhxvCqpKpSkIfLu8VD023DoejR2uIDu1eW8NDjd04MqcBHzUubmYoFHA5fMJ7osP99cH3SflJUaYOvzVyBkGNdLjVDhwph23Tc2E0y1e8XfO7IJUQuG+K7MQq1YIeu2EQ8RmFYqiZsPfgO4KlmXtIZ6jAUCzLGvp/P81AJ4cwNMkEAg9JNKGK0GrgFzaZawpCpBLKcRrwgsqeHwU3q6oxTMLiuBwe6GSS7Hpq2r8evaYsI6PUclEd/j16vCm27xUPZ5dUIjKJivfbCA7SYu81Jiwjh+KnDbZUFHTKtC39PrYIG2m328/hucWFEEmpfkmdD/K7giZceT2srA6PfjTTeMgl9DwMCxe2V2FhcUZ0MlpPLegCDa3Fxq5FLEaKZa+vk/wfqu2HcaSaVlIi1XjVwGNAbhstU13TcbGxcVY+cFBPgASTaWMhIuHTELD7fUJZBPcXh+k3evHBogYlQyfHGnwz3suL9QKKV7/qhrjM8Kb9/obu4cJalT2+L8PYdPdkyNyPtHYJFIukom7fmcltiybGnYWJOecrdl+FKWFaZDQwIQMA978+hTmFA2Hj/E3e+PmW8A/v9rdPry4qwqZ8SrcP9OIE01WNO+twbIZWRgRr8GwGCW+P9OOOUV+Lb2t++pwusUWcq52evwam8tmZOGdirpOXWIJ0mPVUMklGJ2iw6oPD/PzbNlMI577+BgWT83ElopaTMyIxdiFRaBpCnOK0rD7eBOm5yTxNrqy0YLpOUkAwG+QcN/Zuh2VWDYjC1kJ/qAgTVOQSaiQ5Z+RGBfRFPwSc/jLS4z478EGXFuQii8rm3D3tGx8X9vGO9kNZv+m/7IZWRibqkesWo4Ohwe/+nEuNn5+km8Uy12rpTNG4USjBRIK0KmkePqjU5g/MV10fCmlNGbnp+KBgPNZPTcfDrcXv//vUTAsiM2OciLtl/QVL8uK9kJ5IwJyc71BKZNi17HT+MviiWi3eRCrkeGNvaewdHp2pE8tLAbT5luk1iI9yZxmGDZkddyF7rnA91HLpViz/Sj/Gga1HEfOWvDWt7V8pdCEDAM27DzB2wDAX3FS3+7ET177hv+OXrujWHA+55Oz4vw0AHAzDFJjVFj14WEY1HKUlWQjK0GLdIMSG3dXwZgcCwkNTMqMQ2acJki7fv1Ov00CgDiNAlmJWmQY1PjPoQacbXfwn4WiAKWUhoRisWKWEamxatjdXiTrFZBLKNS2u/DCrko8fO0Y/O2rGjxy3RhBhVbgd1zdYoVKJsHoZB28DAsP07OKu14FhymKygRgZFn2U4qiVACkLMtazvP8fwK4EkACRVF1AJ4A8DAABfxSEQCwl2XZeyiKGgbgVZZlrwOQDOC9zr9LAbzJsuz23pwzgUAYGCLtRFMUg3uvzOZ1e7kyRZoKb3Js7HChosaMiprvBY83dYQn6xCrkuK+K7ODMo9jw9Q8pmkKNEULuhL/ceG4S9oxaexw8oFyzhA6vcF6qE4Pg9MmG1JilFj5f2PQ5vBg17GmoJ3YsplGbD/UgDsvH4Fn/ndc4KDeMiUTqXoFDp218A1AuLJUsfejKOBUi030bza3Fz9/47ugBWX8XZORqCNd7S9lbC6fqPzM63dFJvjp9fkwf2IG3/2Yy+zxMZFpeNNsEZfXabYMvLwOEJ16ofYQWSVcE6PALMhQjh8nTdE9A/mpefnYdfQcZoxOCsro/O2cPHQ43Fg+Mxt6hQTpBhWeW1AEUIDd5UGsWoraVntQds32Qw1BlRyBGUFclmeD2Yl3v6vD4qmZeDBgvD59QwFMFifMTh+f4bN+ZyU23DIeCikFpUwGl5fFmBQdpoww4LEPDvHB5JWlY8EAsLrEv7NA7VkgdLCpJDcJBWmxJJvsPIgFWtbt8Et/fFNtwrWFw3DgTBsStEI9xgazE58da0JarAq/2CIs9W22utHQ2Yw4LUYFR2cZ7fs/1CPdoMbPZozEu9/VB2Wvr7g6Bz6GDSoxXvnBISyZloUak2NQZ2ATwiPSfklfaeoIYQ8jIDfXG1xeL64anYqfbd4nqLxzRUnm8GDqERGJtUhPMqcDN5S7z7fcPRdqvSH2PitLx8Li9MDq8kEjl/BzNbchrZTR2Li4mK/k8W/uBVf2HK4382uVrfvq+P/fOCG42Sk35wNAo9mFlz+vQnmJEXqVUK6Iqx7l1hHPLigUHScZcWrEqmX8Z/+q2oSHth7A0ul+GxO4uV6Ypsftl4/kE464GMbX1c1Y+X9joVVK8ZtrcyGTULA4PVhZOlZwTtya6ZdX56CqyYK8tBjEhZkcx9Hj4DBFUT+FX0g7DsAoAOkAXgZQEuoYlmVvEXn4tRDPPQvgus7/VwMo6uk5EgiEyNEfhqsv2k4MS4s2dAs34ywlRiGa+ZusD29y7XD4gjJaH//3YWwKM+hz2mTDL98J1sUbk3ppOicMw8LrY3HiXDtuvywLWYlaSGgK7Ta3qDOclajls9xe+7K6U/9ShucWFMHHsJDQFDbuPonpOUkhM8SGxajwxtc1gr/VtobOanOHaMqklouXsX5R1YJXv6gmWcSXMLYQ8jM91QbrL2QSiWhm0uYIZeomhtJ+j6BGYbSVlIcKGCbrhQHDCzWuKy1MC3KeXthZidVz82GyujEqSYvnF42DxenB8Dg1/vjxMUzJSoROKYFGKcOdf/sWTg/TmUWcgx/OmAXyQIHZNe02FzbdNRltdjc8PhZ17XbBuXNTpZhD9+h7B3ltYQ6nh4FEAngZ4EybXeBEPXjNaLz25SkAfuffmKTj36f7dxaoPQuEDjZFIjB8vvMZjMGvUIGWZL0cP8oehTOtdozPNKDN5kFZSTYY1p9Z3mB2YtmMUfyGAHdcoKa0Ukaj3uzgGxOVzTRiw65KzB2Xhv8rHIZPjjTgtTuKsae6FTQFZCVqcKDOHHLjl/v/YMzAJoRPNG7uBRKvlaM4Mwa3X54lqOwJt9F1pFFKpVi1TZgosWpb+H5ZpBlsPSIGei3Sk8zpUy1dz+V6A0hooGR0EgrSYwFAsN7IjFdh9dwCyCRUUKaw0yOUa1pZOhYGtVyQJez0MJBJKF6uIUmnFLUxHS4ftu7rqjrKjNNg9dx8JOsVePe74Nds7HCCpiiw8Gv5Wl2+oE1Ernr0xV1VcHoYVDVZRcdJZpyaX7tylbAGtRxjU3VBz78yNwmPvX8wKIbxjyVTcLLZitX/OcJXcRWlx0JGQ7QBa22bHRMzDbA4vZgyIjxZTY7eZA7fB7/u79cAwLJsZWezOAKBQADQN8PFMCy+qGqCxeGDzeWFyebGmTYbpmcnhbWQa7K4YFDLBV3Et+6rQ1OYGWcqqURU20slC28R0BSioVy4O/zRVB46EJw22bB5bzVKxqRi6aauneFnFxQFabaWzTTygWFOU+qNr2tQVmJEjcnOZx8vmJiOdod4cI5hgT3VJtxUnMFnnwHA2xV1QTu03K6x28sGZc+tXTQOyXrxABdXJk0yki5dEkIEP+Mj5OyZ7OLdxFvtkekm7nB7g7JOymYa+YxAwoUJFTDMMKhR3WzlN19pCiEdv2S9EhI6WJ/vpuIMLAvIAuOye1RyCWbmpmD9zkosvyqbny8BoLQwDS/sPIF7r8gWz64xqLFpz2kYNAqs7JY9vKWiFvdckc03Tgy3q3dmvAqtNi9qTLaggPRzHx/H8quyQVMU1u+shEEtx12XZwbpzZeXGGFM1goCrYMt2DTYzud8iG1aFGfGQCGV4O6/fyvaSZ4bAz6WDRnI5a4V1w0+MHDMsH65kBdvHQ+mU9adYYEzJjuuMCYKxgbQZae5/w/GDGxCz4i2zb1ANHIJbpqUKajsWT03H5oIBSd7SluI9UV7hNYXPcXt84muR9w+5sIHDwF64pfWtHZVUjaYnfxm7eQRBpw22XDaZMPxcx0wdOrg+tcSFYLvNdD34uZ3LlC8bEYW1u8Qylgl65WCKiiLM3hjUdIpMamS+RvhHjvXgbcr6nit+k17ut5TKaPh8jK45x/7cP/MbChlNHRKiaC5L/e6VICJFfMTV5aORdlbP6DN7sbaReNgUMuglktw31WjUNdqD+pxNCpBK/pdt1hdeOmzKtEqrsx4NR59L7jiSi6hYdDIUddux4iE8Oe93gSHXSzLujulHkBRlBTAoO8MTiAQooMzbTa02jw41WLjg3kjEjQ402ZDZvyFJ7cUvSLIsSgvMYad+Wuyu0Uz6DYunhjW8QkhNIDC3eGPpvLQgaCxw4nSouH8ohjwX5Nf/Ws/1t08XtAIiVtQSGjwnWtvnpSBpg6XQKajvMSISSMMITPEfAwE2UiAf3Frc3rw8k8mwutjcKDejH9+U8MHoiUU8MbSKfD4GN4xBxCy2y33OS7VoP+ljo9h8IcbC1AdMM+NTNCAiVBDOoNKfN6KVUUmWE1TNLZUCBudbamoxVNzCyJyPtGIWMAww6DGx0cbgzSEc5K0OFDfwR/LzU2TR8RjYoZwrhTL2l297QieXVCEGJUUv9p5AAa1HMl6pWA86ZQS3FScgbNmh+hYO9fhxJW5SXxgmHvt9Tsr8cyCIvzx42N4al4Bls3IgjEpOONGKaORm6LnH/c7Zv5u3kunZ4k6XIlaBZ7o1BJcPDUTaz+t5JufjYjXIE4jR7JegYy44EDrYAs2DbbzCYXYpkV5yWj8tDNAINZJnhsDMlo8s3vSCAOKMyfi4XcPBmWAcesBg1qOVpsHKz/oanL59A0FKBgWI3I+/mDBYM7AJlw62Ny+oHlx5QeR0+DvKTFq8fVFTITWFz1FLpGIrkd+NCo+0qc2IPTEL9WIZFlnxqvQZHFj6aZ9Al+IYVnRvgiBvlfgRp3Tw2B0io4P/EoooCA9hp+fxaqguI3FscP0GBarEkhOcv4YVzXKVZysLB2LJzp7Xvxjby0evW4MJDSFP30avGHJnVtqjBILi9ORoFXgL4snotniwjmzExanh7dJK97+AVuWXQa1TAKL04t1Oyrxi1lGQeavWi4R/a5VMoloFddj7x/CK7cXi2YPOzwMNmw7gr/fNfmiB4c/pyjqEQAqiqKuBnAvgA978ToEAoEQhMnqxjmzMyiYZ7K6kRmmHe7uWKzbUYl/LAlvEeX0iGsOOt3h7RBLaIh25ZWGucEfTeWhA0GyXonaVrvoNVFKabz2ZXDGT26KHqu3HQEADDeog8pQ1+2oxCuLJ+LBa0bjuY+7NIdXXJ0DhYTGy51jj8tC4xYLWQkaTMqMAwC0Ozw40WTFgfoOfve2KC0WUqkwdY0LztSYbPj+TLtgR/xSDvpf6sgkNJoswk2LFVfnIDspMoEdFsHZ7+UlRrAR2vuXSyncPCkj6HwCm40SLkz3gGF1s1VUQ3hl6Vg076wKmptomsJlI+Px9A0FePS9g/y8KDYfu7w++BgJlk7PwuhkHaqaLAInh2vcaVDLg7KwnpiTh5c/r8KKq0eLvrbD5fU3r2OB7EQ1nvv4WNBrrCwdi79+eRLLr8pGolYBtUIKV4A9Fy0LVkj5gCT3Wg1mJ9ZsPw6ljMZHZdN75FQRLkzgpkWNyYZj5ywwOz3ISdJi6YxRYBjx7OATjRbsPdmMJ6/P55tVchU8f/zfcdx7VTbaumUiBq4HFhanBwXYHn3vIMalxwo2URK1/mz58RmxgzoDm3DpYLKGqOyxRUfmLVjx9UW05BZ2ON1BNrNsphEWlyfSpzYghOuXMgwLjUISlD37m9lj+IafQFcQeNWcvPNWAHVPqFHKaOgUMsG6ee2icfyxYvIX63dW4o0lU9BqcwdJTgYGoo1JOqyZXwC1XIoWixM1JgcAf/az2eHBhk7piMBjX7ptAlZ9eBipMUrRpLRYtQwWZ1e1m9PDgGUZGJN12FNtwtLpWfjoQANm56fyY6s4Mwarrs8TBLGfmpcPuZQKufb6vrYdKplE8P6Pl47FCzv959zh6Nk47U1w+DcAlgA4COBnAD4C8GovXodAIBCCsLq8osHdcDN3m63ishIt1vAWUaEyf+O1srCOl1D+bqPPLSiCze2FRi6F3e2BhKIvfDCiqzx0IMgwqNFkcUEpowXXVa+QwOryBi04n5pXgL9+6e9efr7y4yaLC3qFxH+dXF5olP4imI2fV/PHZifpsO7mcdAppYhVyjAuw8Bfh3lFaTAmaXHO7ERKjBJ5qTFBgWGgKzgzIl4Dh4fhnddLPeh/qWNz+fiGh4B/TK795ASK0iOTCWRxePHfgw14ZkERr2n4yu6TyI5QFqJSJoFGLuGzIWjKX1qrDHeXjSBKKA3hwHLN7nOTXC7B3MJhyE7UoLHDBZ1SKlqGr5ZL8fM3voNBLcej142BSi7B0zfk85I+MgnF6wVyWoQUBRQOi4FG6c+KUUhpUftbb3Zgw84qvCqj8eTcfDw1Lw8eH4tNd0/G3upWuLwMtnxTizt+NAJNHS480bk5W17iLwnduq8uKJi86vo8yDvfL7SdIJUdFwPOLjZ2OPFNtQmXZcXjlin+svml07NCVvUsKs7AMIOCX1+p5FK8uvskzE4P3D4G5SVGvPVtrUCT8R97TqPN7saoRPFy3dpWG0YlaYOyrsmmAGGwoFOKa95qFb0J4ww8Hc7Btb7oKaEyhydmXhptscLxSwOzdg1qOZbNyEKGQY1mqwtMCDkgtUJ8XGcn6fhkiTXbj/I+2Zr5hVj5gVCPN1CeL5T8RYvVjcMNobXllTIalU0Wfv3z59smCM4rVAN0lUyCv905Gc0WF+742zdwehikxihx44R0ODw+DI9TI9B1L86MwakWOx7u3Gjngt/bDzVg+VXZyIhTg6Yo2D0ebFw8EWaHF1KagtPrw9/+XzVunjRC9PvyMgzSDGosvyobTi/j75HQWS3t3wTv2bq5N7OKCsBfWZZ9BQAoipJ0PmY/71EEAoEQBo4+Zu4macV38BK14clKUKBEd7gpKrzgrFpOQymT4ESThQ9qZCdqoJaHFxwGoqc89GLj9TL4qtqEWpMVzywoRH2bg78uZSXZ+OU7/iw0bsGWm6zD37+qxpSsREwdlQi2s8O8aLm8WoYTjVY8/uERwXW+tiAVJ5qsKJtpxB8/Poa549JQmB6LOK1csBCSSmkUDTegaHh4n4UE/QmB2NyDqyFdok6OawtSBZqG5SVGJGgjU/bp9PhEy/idXl9EzgfoW6PUwYKYhjDg/3388Fi8tWwKLz/R/bMWpMUCaMcXlS14ftE4/GH7Ub5L98rSsViz/Sgvz/BgZ4bwXT8aEVQFxGn7cQ3E/nbnJF67b8s3tUGVN911ZB//4BBeu6MYl2XGoqFTh4/7PG02t2Bz+e2Krq7km/fWYNmMLIxK1KLD7sGfPq0EAJSXGOH0+IicUwRI1itx97Qs2D0+rOqU91BK/XqqdW12XhPyyevz4PT4EKuWw+b0we1jBJlVXFZbTpIWy2aMCtJ8vP3yEThtEm8qq5ZHR4CNcOkik1B45NpctNjcfDl9vEYOmSQ67E+idnCtL3pKsl4hWskUrlzhUOBCfmlg1m6D2ckHWrcsmwqtXCra6D0lRoE18wvx0NYDgmDp7z/yB4S5QGthmh7GZB1MNhef0csRuIkbSv5Cq5SAYUM3m+2+xvjth4fxp5vG4UhDBxgWyE0Rl7HitI65oHRqjBKLp2YKNqFXz83Hb64dje9qTLjj8iwseb1CNHvZ7WPw687vgaO8JBssgI27q7FkWhZe+qwyKCv7yevzkBqjxLodJ1BRY+araV7+rAoLi9OhVUihCbNnEkdvLOIOALMAWDt/VwH4GMDlvXgtAoFAEJAaoxLtypsSE54R9rGMaObxprsnhXV8fbsTm/bUCHaIN+2pQbpBjQmZFz7+ZLMdnx1rwoJJGTBZXYjXKvCvb2shoWnkpsaGdQ4EfyDmP4ca8NBWv37lcwsL8et/dRlOprOpW2DDg+Uzs1FRY0ZFjZl/ncI0fVCJzm/n5IFhxeVH/rJ4IpZflY0tFbW4eVIGUmKUiFFJkRGnEQSHUmOU8DH+4HM4gaJwAktDIfg0WPF6GRxuMHcuOFXIS9WLZnoPFJkGtehic7ihZ12F+wubO7gT87odlSi6ozgi59Nm9+DFXSf5SgEfA7y46yR+OycvIufDMCx2Hm/EgTqzQOtu5ujkfr9HL9ZYZRgWNOXXGBYbe5nxGr6hS3fdvg23jofbywoeW1k6FvFqOQ6e7YDF6UGNyYH7rsrmHaPbpmQEZcd31/Yrm2nEwbp2/O6/x/nfPz7UgL/eMQltdje0Sil+szVYR7a+zQEpTWNihkFQ7sr9cDSY/fb89bsmo9nqwplWO9ptbvx++zH+cxiTtRiVoEVmvAaPBGT0iDXvI3Ny/8EwLFjWL9EEgN9Y6O5Y61UyvLK7CguLM6CQUXj8gyOYODwWr981GadNNqjlUjS0O+D0MJiekyRogshlxT+/aBxcXgar5+YLmh2WlxihUUiw52QLub6EQYtKJoFCJhFstK26Pg/KHgZ9IoXFJb6+KLg9MuuLnpIRp8HYYTpBpaFOKUFGHKn8A/xzebPFhaXTswB0NWvjpU9YiDZ6P97QgZRYFf5z/3Q0W51QySQoe+t73t43mJ147ctqfBTQuDvUJi5nT55bUITKJgu/sbh20TgMi1Hhw/31QdVDq+fmI0WvwOGGDsHncXtZ+JguyZN2myvIdjw1Lx8SGthzsgWazgxosX4MKz84hGUzsnD12GH4vrY9pIxGRpxakHlMUUC8Vo4EjYLPcK6oMaO+3SWITyTq5Ni895QgKerl3VUoLUxDeqwKDrcPth4mnfQmOKxkWZYLDINlWStFUZHxZggEwpDDoJFiUbGwK++T1+fDEKasQ5vdIzr5ttvDmxyT9QqBriXV2eE0SRdecDpBK8e+M+1INWj8O6SNVuw7046bJmeEdTzBz2mTDQ9tPYCcJC1unpyBr0+1Bl3X7osESWd5UKD8RG6KDn//f9UCY/rnz6vwm9ljRMdJo9mJEfEaPDk3H8cbOiChKRQNiwUAQclU9+z0tYvGYXZeiqhjKRZs6f78cJ5D6B1eL4P399fjsfeFC7t5RWkRCxBLpVTQpsWq6/Mgi5CmrtUlnslsdUYmUzdJr0Cb3c1v/AD+eztRF5lMo9pWGyobrUFZsNmJ2n4tP79YYzVwfslJ0gZlnwTKSIjp9h2oMwukJLig29pFRXjty2peCoCTZ0iNUQY1pOOOy4hT44VbxsPu8qLN7oYvoNnM+p3+4HGrzY26djsK0mJEdWTj1HK4vD7srmrG6CQt/nXPZahrcyBeEywL1WZ3Q0JTePCd/fy5LZmWBQkNlOQmoSAtFjRNITNeg3HDY4Oa95E5OTS92dBkGBanWmw42tCByiYLVHIJxg83YGFxaMd6Zm4KXvqsCnPHpSFGKcPkrAS+jJfbqMiMV4WUB+lweuBw+6Ay0PjTonE41NABmgLSDSrc9+Z3fAY8ub6EwYjT6wvSS33i34fDTnqJNPaQlVKRqwTqCf7gpzvILjMMe8nPFaGawG3eWwO5lILN5QPLijd6f3ZBEZa/+T0+KpuOqVkJYBgWD80eE1LbOJT2cYZBHXQOv7uhABMyYvkA/kOzx2DN9qNYMi0LKhmNMal6PLntMD/3c+fcYHbirsszUdtqx8bd1TCo5Vh1fR7OmR0CmTO7y4vj56w4UG9GklaOFVfnhFxHS2kaKz84hGcXFIkGty/LioePYZEZr+K1rTk/02T1927gnhuYEKWU0ZDQWRg3PF7Qzwbw9z8yqOV48bMjeGZ+z+RPehMctlEUNYFl2e8AgKKoiQAcFziGQCAQwqKh3YUXP6vkg3kA8OJnlRiRUIThhgs74SqZeKdPbnK9EDqlBPddZcTjATuET87Nh14V3g69WiYR3SFVR8kO/2ChscMJg1qO+64yonzL9/jFLCPfoRYAdh9vEsh/ZMarMD7DgOcXjfOXoQYEPh6YlQOGZWFz+0BR/l1hjUJ8nDRZXEgz0Hy2mlJGI78sBgD4hYdYN/VA3avunGoJDrasePsHjL5/OkZ1NiATC8ic7zUJ4XO4wcwv6oGuDr/GJC2Khhsick7nzP5y+MBNi5c+q8KI+CJkxg/89daH0jRURmbekkA8eC4JU96nv2nscIlmPk3IMPRrcPhijdXA+eVAfQead1Zh2YwsjB8ei8x4jSCoJ6bbx7AQ1fK3uXzYuHgiTrfYsHpuPlSdnbZvnJCOuja76JjSyKV8cxqljMaD14zGQ7NHw9YZKMgbpsfvPvJLVlwzNgHPLChEVZOVz9gekaCBl2WwfPP3gkD9pj01uOvyzKDsoAdm5cDLMIKsJs65unxUPP+5xZr3kTk5NL3Z0BQ75pFrc8GCRXaiFkunZ/FZZ0CXY82V3kppGr+enYtH3z8oWCNu3H0SD80eg+PnOkTHXG2rA699WY3yEiPGZ8RiYkYs4tRylG35ni9TJtd3aBPNlVlmu3jQyRxm0kukSdQqRO/L+CiRlTh8NoRdTtSiKCMya8jBQqgmcCtmGaFTyfFgp4686OZAZzCVk4W4kPxeqL+LncMj7x3ER2XT+WNn56UgN0WHJosTNCjc3rm5GHjOS6Zl4bUvq5Gbqseyzfv4aha3l8Hv/nssaPw+u6AIr35RjWcXFKLd7sGwWFUIDWUtDGo56tvtQeuTsplG/ObdA7hnRhaevqEA35xq5Zv6/upf+5GTpMUTpXnY+l0t1i4ah2Pn/FIXH+6vx92XjwTDskiNUWFl6ViwLIszbXb885tajEnRgwVw86SMsJPbOHoTHP4FgHcoijrb+XsqgJt68ToEAoEQhNnhwa2TM/H8pycEzp05zG6bWoUUK67O4ctZlTIaK67OCbtxQ5vNwweGgS6Nw7+GWV5tdnpFd0hfjZLyqcFCil6J387JQ7vDDYNaDgpUUNZevFqG5VdlIztJi3a7B/f8Yx9v3AO//+c/PYFlM7KwYWcVf6xcEhx8emBWDt78pga/mT1G4Jw2WZxg2a6MuPxheqyakwe1Qor6djte/8q/YxuqeVFNq010YcQ1wgHEAzKBiyZC7+HK2wJxehicMzvD1ozub+xuL2KUMoxO0fHyOV+ckEVMc1gplYjOm6oIbWq1O9yg2G6NPV0etDsi0519oDSiL9ZY5TbbuOCuSkaDpii4vN2CwAwLtVzCb8RxgTq9QiKq5d9idWHlB4ew4uoc/PnzE5BLKTw1Lx+1rX692O6O0NPzCvCH7UcF8/NzHx8XzM+/u6EAS36UhSarC7uPN6HZ4sIHP9SjtDANLAXEKGV46bPgQP2SaVnocPnw4f56PnColNJQyWjc+bdvg7Ka2uzu82oKkzn5/PRmQ5M7JnAsmmxuHDgjlBbhsqCUMhpjUnQwqOWQ0MDEzFhYXT4+uyrwmjaaHShIjwkq/11ZOhZbvqnlx8mrtxdDKZPAZHefV7+SMHSI9sosnUp881aniha9bFZ0fUGBvfChg4B6s0N0c7Te7EARLu3gsJidNKjlKEiPxV1//9b//7QYQXLP1n1+yYdmqytI2z+wifdpkw1fnzIJNnPEtI/DsdWBr7vjWKPo8/OG6fBR2XTUt9mxZFoWMgwqnDU7QvZC4oLbUprG0x8dxWUj4/D0DQV4tFvDuTXbj2JhcTosTh/e/a4OzywoQlWTBT4GvK3bdbwRd1yehbRYFfRKKVRyCR8kfv2ratwwYbhg/nr6hny4PD5YXQx+EfB4eYkRv7x6ND453ICZY1KgU0rR05yKHs8qLMt+S1FULoDRACgAx1iWDS9qQyAQCBfAoJbj+U+/Dwru/WPJlLCOZ8EiWa8QlH8k6xVgw1yEWFxe0UWA1RVe+ZPd7RM9fiDLp6I5QwLwn//BejN+vfUAfjHLiEevG4MTTRZBVtG6HZVYflU2Nuyqwt/unIRfbPEbx1BlpWmxKqTGKPlj/7RoHNxeBi/cPB4Hz5rhY4A3v6nBfVdm48+fCUvZuYVLZrwKt07OFGS9lZcYcc+MLPz1q1NI1IoHGjRy8YV9YCOcUI0UItUQKdrHUCCpMeK7+SkxkWs2lRqjwG1ThfI5q67PC1tbvb8xO92IVUqDgrFmZ2SWdyq5FC9+fjKogcmzCyLTHTwzTiM6hvpbc/BijdXUmOBGrStLx+K0yV/eX5AegyuNSUEyCmUzjdhSUYuxaTFYGtBIxaCW+7txG9RYOj0Lb3xdg2XTR8Lm9kEjl6I404APfqjH5r1d+v00BUhpiAbkmABpiUfeO8hv8nGN77oHA1eWjkV9u0uwiUdRflsbqFtbVpItyPjhMoSWzchCYXoMWBYh9WZDzckUKFQ3W6N6TuwPehI85+zJiUaLqLbwytKxvH1ev7MS5SVGODw+ZMSp4WNZ3HV5JtLj/JrQf1xYhMNenyATfP3OSvz1zkl4+N0DeGZBIV66bQJ+ONMOH+PPKr6pOAPNVjcazE6YHR489Z+jWFScPmA2dyjZ02gk2iuz7G6vaMZhpDaTe4rZ6RFdX3Q4o+P8U/Tijc5TSMPSIDvJrTX2VJtgUMtxz4ws1JhsQck9KTFKNHc4seHW8bxsBEdPN3PC9Z+41w1VYTI6WY8Mgxr7z7TzSUZKGY0Xbh4v+ny3l8F9V2XD7WPwi1lG6JUymCxOQUUgF/zNTtKivs2B+RPTIaWBdyrq+KZ7T14/FkqZlG9Wx1Uc7z7eBJoCpmQlYvW2I4LYgkIqgcPlhdXlFdhCrq/DzDEpSNIrsHH3SWQn9Uz+LOzgMEVRM1mW3UlR1I3d/mSkKAosy74b9rsSCARCCFptLlGHo9UWXsaYy8Pgoa0HgybxcDN/9Uqp6CJAF2Z5dZJOIXp8T8s6eku0Z0gAfhmGP35yHOUlRsR0liV1z/oC/PpTT83Lh9PjD8hzgQIxI17f7sDiqZm8oT7RZMVLn1Vh+VXZMCbpcLzRgl9dkwuGZfiAWHe9q9VzC7Bss7DTLGeIfzN7DCQhlEuS9QqBBAY3JgI7HYfS0uq+aBoIhsIYCiQvVY+n5uUH6cXlpcZE7JysTnENwX/cPTki56NRyGCyW/H4h0cEY3RkUmQcZ4vTI5odaHVFJlg9MkH8/hyZ0L/358Uaqz4muAHn6m1H+CBseYkRKXqlaHnolmVTYXd3Zc6IdeR+YFYO4nUKrPlXV9fxJ+fmo93mwt++8mfpls008tmg3ednNmDvNnCT7+i5DpQWpgVp0XLnHqi9x7L+zOstFbXYsmwqHB6f4LwDX3/88Fg4PAz+74UvQs5xYnNyeYkRv9jyA9/oJlrnxP6gpw75ird/wNLpWaLawoHX06CWI14jx+MBVT2r5+bj08MNuHlSBk612AWBhrKZRmw/1IAOhwf3zzSi1ebBH/57VLAJEVgyXNtqx40T0vF2RV2QXb4YNneo2dNoJNqrAFQyCXYeO4dnFhTB4fZCLfc36h43fHSkTy0stAoZjg2i9UVPkUooUVmpt382NcJnFnm628mFxX7ZvcDEnu79CgKTe9YuGhf0mj3dzAnXfwqsXAncbMmMV2H13AK02l2oa7PjTztOCGSL/rK7Ck/MyRPIRf5mdi60Sile++9RfiP6T59WYul0YfUq0CmhopHjjx8f5zWOy0uM+O/BBszOT0WcRsH7udznXfXhYTyzoAgnGi2IUUqDNlUz41W498rsIFu4eW8NGNafKNdud+PaglSk6Hu2idGTzOErAOwEMEfkbywAEhwmEAh9RtlHzeCQjZXCzPyV0LToImBTmEEbt48RPX5i5sCUHkVjhgTDsKhttaGxwwWb2wsJBdxUnAGHx4d13SQ61u+sxKPXjkGqQYUDde1gWOCFnZW4/bJMbNpTg637gkuZA8uIOQdxZIIGBrUcbh+DY+cseO3Lav5vGxdPBMuySDdoMDKhK8NHJqFExxbDApVNVhg0MtHd2Yw4DYzJWkE2uzFZK8g6vJDW1kASjWPofEilNK4vGIYR8Rqc63AiRa9E4bCYiDWjA4Bmqxs5SVosnTGKl5V4ZfdJNFsjI5vg8ojPW5GSw9ErZUEBpPU7K7E5QsHzgbo/L9ZYbbI4RStauCDsuh2VyE+LgdPDoDBNz4/LWI0cHh8DmqJ4uyzWkZuT7gl87PHOZmIrrs5BukEJq8uHZoszqLyY0wvmyIxXISdZh+Uz/Rt3De120XmX24zjSpT/9v9O806e3e1Dsl4JmhLfLIzTyHHTxr3nneMCr3mNyYbvz7Rj056upi/RPCf2B+E65IGa+1v31WHF1Tmi15MblwuL0/nAMPe3lR8cwoZbJ+BAXTsvGcH9bf3OSr4CiNOlvvvykXh5d7Ugs1xCAw/MysHfvzqN+RPT0WB2YtOeGrx2RzFoirpoGb1DzZ5GI4OtMqun6JQy/HR6Fjw+AKy/UfZPp2dBrwqvUXekGWzri57SYnGLzlmmCK3XBhOcnRx9/3TUttrg9jK8FOCJJgsYVrya09n5vGOdWbwjAnofhNrMaezwz+eNHf6MWx/jX9sk65W4ZkwyPrrA+ox73QazE5v31qC8xIicZC2kNO1/HZ0C1c3WoMSEh2fnIkHrb0yXpFPgTKsdyTEqlL/VVeXMfc5QPugj7x3Ez2aMgkYuAU3TaGi3Y/lMIzbursKSaaNEP6/D7cXu4014+P/GBG2qlhamBSWYcFVRAJCkU4Jh/ffZNWNTenRNww4Osyz7BEVRNID/siz7do/ehUAgXFL0pYROq5CKZllq5eFNV2q5FJnxqqByZLU8vMzfDodHdJLuCFPzuMXiEnXCW6yusI7vK9GWIcEwLHYeb0Rlo5W/5n++bQLW76wM2cRAr5Zh+Zvf8eNjZelY2JwerF1UiHa7F2da7fjrnZNwoK4dFqdP0MVVQgNlM4147uNjuP2yTBiTtVi97QgfQHZ6GFTUtEGrkMLDsILMwFAOBk0BXoYJ6WjQNIWZo5ORlaA978JFTEsrEkTbGLoQDMPi0+NNgypzK0knxy1ThLIST8zJQ5IuMg1arCHkdGyuyJR9tts9oufTbo+citlA3J8Xa6yGkpXISlBDqxiN17+qgcvjQ3FmDOZPyMCv/7Wf75Zd/pa/czZnl0NJ9zAsBIFltUKKNrtfk5jbeHu8dCy27T+L1+4oxtenWiGX0FDLJGiz+53szHgV7pmRLbgvfndDATLjVYJMUKWMRk6SP4BMU0BGnBp/vm08alodfHUH991tuHU8lr/5veAxt48Ja47jrnljhxPrd1Rd8PmXEuFsmDAMi6MNHfx33WB2osPhCZk9rpTRyErQwunx6/sH3v9nTLaQgQab2xtUtnz7ZZlYs/04//q5yTqs/s9RtNndfKZ6m92Nr0+1IjdFjykj4y+KPRhq9jQaGUyVWb3B52Ng9zA41WITNOb0+ZgLHzwIGGzri56iD6X5rIwWzeeLz/FGC1a8/QOeXVCEhcXpeP7TE1g6PQuSEBu0SikdVIHErXXEpCoWFqej3e7B3moTDpxpx6y8FKwOaDzOHXu+ObX766plEpwI8D0z41X4w42F2FNt4mUMAcDu8eH+f3atIcpmGhHjCU5EU8poPvAspiv8ZLdqLRYsfjJ1BBDiO1LJpbi2IBVn2x0wJmkF2cwGlUzUrmQnahGvlcPu8UCrkMGglqPZ6uT724RDj0Y1y7IMRVHLAZDgMIFAEKWvJXQWpwdqmUSQZamWSWAJs5xYp5Dg3iuzg7rc6xThBYdjVDLRSTomzB36FBEnnCvZHQiiLUPitMmGA3VmbNxdDYNajiXTRoBhWf78xT7LyWarYLd09bYjKC8x4ocz5qDv/d3v6gRyExMzDTja0IE5RWl469taPD2vAAsnDhc0wPExwNpP/JlwWQldwaBQZcYauQTDDKrzOhqDJfAbDtE2hi7EYMzcYliINq6MVGZsKDmcxAGSw+nOMIMSd/1oRFADm2Gx0TkGw+VijdVQshLLZmRBJZPg51dkIVGnwC9/nIu7Opu33TghnT+Gy7JcNiMLxZkG8flBK8ctk4N1tHOStMhN0SEnSYsnO9/T6vIh3aDG4x8cgkEtx7IZWchO1MKgkeOnm4TSPY+8d1B03n36o6OCuX3LT6fioa0Hgr67/9w/PSij6FSLDUoZLQhYSCggOcQcN9TmxP7iQnbttMmGuja74Ltz+xj86sej8ez/jgs2KixOD5ZMy8I5swOZ8aqg7K3Vc/Ph8jGi16G6xSa47ut2VOK5Tn1ypYzGb+fkoabVjoXF6RibqkdThxNlJdkYk6LHnz+rwsbd1RfNHpCxE3kGU2VWb3AzLJotLsEGiL8iQxXpUwuLkOsLbWTWFz1FStOiDfWkdOSqzwYTgeuW+nY7MuLUfBbtPTOyghK+HpiVA4Zlg9YkK97+AfF3TUayXsHb/JwkLX5+ZTaOnuvA4YYO7D3ZjJ9facR9nQlCgcdeaA4fEa/BhlvH40CdGcYkHSoDJC9SY5S4dXIm7vr7txc8z/U7K/GXxRMFiWgJGhk23DIeB+r9FSy1JpvohnJgtdZzC4pQ3WLDBz/UB2UbPzUvH6/uPollM0bh2Y+P4f6ZRoEO8uq5+aKb5lKawpLXK7Dq+jxQegq3X5bZ4/hDb0b1JxRFPUhR1HCKouK4n168DoFAGIKcNtmwZvtRLJmWheUzs7F0ehbWbD+K0yZbWMfLpTQ+PFCP7CQdhseqYEzS4cMD9ZCFEnTthsvLimp5urzhNaTrcHpQNtPIy1hwu4ThBqdDyUq4B2iHnwtgBp7/YM6QaOxwgmH9DY7uvHwEnvv4BI6es0Apo/nynMDPsnpuPt6pqBO8htPDIN2gFv3eFxan88c+UZqHxz84hD/89zhe/aIaNxVnwO7xIVYl5QPDD8zKwbvf1cGglsOYpMOJRgtOt1hxssmKr0+ZMDZVh23Lp+FvdxbjtTuKMXlEHGbkJGLm6OSocTQuRLSNoQtxvsytSNFkEddWb7IMTIVBdxwen+j94/AMXCPNQLw+lnfEuPNZ+8kJeJnw5vGLAcOwqG62Ys/JFlQ3W8FchHO5WGO1ySL+ugzrDxq32Nz46qRJUD6rkAoDWg1mf/asw+3DquvzBPPDg9eMRlaSFqu2BdveZTNGobLJglsmZyInSYuMODVqWqxI1iuw/KpszJ+YDrmERrvdjVabePluVZMVS6ZloawkG6/fNVkg78A9p7bNIXpss9WfoTk1KwFZiVrQNAUJDTxybS5uvywTr31ZjQ07q/CX3dU4WG8Wva6DcU4ciPHY13Mw2VyIU8vw/KJxKCvJxvKZ2dApJJBSlD9gcNM4LJmWhQ07q/CH/x7Hi7uq8PqeGqwszQuSLln5wSF4fSxWlo4VXIeVpWNF1wQSmsKD1+Rg3U3jEaeVY92OSqzfUYVfbPkBNrcP71TU4YG3f8Ds/FQY1PKLZg8G49i5FOE2MgLngWjB1Wn/uttDl2dg/Iq+EnJ94Y3M+qKntNpdUEhoLJvh92uXzciCQkKj1R6Z9RpHJGyA2HsGrlte/6oGMUoZMuNVuHFCOhxeH7IStVi7sAgbF0/ECzePx5vf1MAWoh/AF1UtmL3uC8ilFP5bNh13/mgkHnj7B6zfUYVXv6jG3dNGYX9de8h1Uvfz83oZVDdb8e1pE440mNHh8FeZHG8USl7cNiUDz38qvMee//QERsRrRN+r1mTDvVdm47Uvq7F1Xx0cHgar/3MEPsaf1DY+IzZIDjOwv4LTw8Dm8oJh/U16uea9y2dmY8m0LCilNGaMTgIov4QE14eCO3blB4fw0OwxQbGK2jY7v/aSSfwymT0NP/QmH/7uzn/vC3iMBZAV6gCKov4KoBRAE8uy+Z2PPQu/frEbwEkAd7Es2y5y7GwA6wBIALzKsuwfenHOBAJhgDDZXKKNhFptrrCyMtRyKeZPzAgqt9aEKSvRbBUPujSHKeugkEqwpaJW0G10S4U/wzQcOhzi5dAdjoEpn4q2DIlkvRISCnwZErfbzO2ibt5bg+cWFOG0yYbRyTroVFK+BJlDKaNhD6E1PdygRllJNqZmxWPtx8cEciNbKmrxm9ljoFLIsP7mItS2OvD3r04DAG6/LBO/Ciit7t60Zig3k4m2MXQhBmPmVqJOISp/E6lM3Q6H+P1jiVA38bPt4sHMBrMTRcMH/nwGqqlUf49VTuIpUDM48HXZTudIStPw+FjEdJbP+jfHtEHHZMarEKOSweVjBNU9cgmFc2bxa+ZjWbxTUYc2uxvPLSiCRilFjFKGF3acwOXZidiwsyu75ok5Y0TP0+Vl+OZzuSk6yKXC71wpoxEboupH7LtrMDvR4fRiw64qgcP1660HkJ8WE7RWGWxz4mBochbOOaikErQ7vXj8Q3+n9YXF6dCp5Ghod2DTnhrMn5ge1Lynze5Gu118kwDwV5c9t6AIxxotYFn/72JrAqWMxviMWLTa3KhqsPJNa7nAFNcAj9NpvFj2YLCNHUL0YXOL22e7OzqCq6F6wdic0XH+OoUMv9/+fZBtiVSlFzAwNqC7RGSGQY2PjzYGvWfeMB3KSrLBxab/e/BsUAXvk3PzMSZFjc9PNOPBa3Ihk4ivSUYn62BQy7H8ze+xZdlUPPLeQYGNPnauAwwrXlWaqFUGfSdP31CADrsbKTEqNFuccHp8eLazqkQmofjs20StIqTNEXuvnGQ97vjbN3B6/FVWO46ew7IZo3ipi8x4FVZdnyf4DgIbqitlNFJjlThrdvByFIENdp9fNA56hQQ6pRQSWlxOqbrZGhSrKC1M4//eYnXzG+QXTVYCAFiWHdnTYwD8HcAGAJsCHvsEwMMsy3opiloD4GEADwUeRFGUBMCLAK4GUAfgW4qi/s2y7JFenAOBQBgA5BJaEFwF/BPWj7Ljwzre6vJi675af1feTt3C17+qRsbV4XXlTdIpxI1GmEEXqYTCzZMygsqfpJLwjG2MSiZaPhWjGnhtKjZySXZhk2FQIztJC5dXqAHJsCxWzclDok6BujY7cpJ1OHjWjK+qmvFEaR6focYZ3BabS/S6x6pkWPtJHfKG6TEzNyVo04JhWazfcQKr5xbg11v9i5Cykmz++gWWVgPC0qdEnWLIOnkDJYPRF33ycAksJeP0+grSYyKauSWlgXuuyBZ0P35iTh4i1SMvUScXvX8SNJHRQNYqxDX+NIrIaPwNlDRJf47VQOcxUDO4u6PCBdGUMhrHGzrw1Lx81Lba8YftR4M6et97ZTa+qjYJuo8D/muzcfFE0WtmUMswf2I6tu6rg49l8ci7B9Fmd6NsphGjkjS8UymhgDGpupDnyb3esXMW3HNFNl7+vIrv/F0204h1O45jZelYgQ7h724oEP3ukvXKsHWHOQaTNNCFxuNAzKvh3BMWlxdrPzkR1Gmdu2bbDzXggVk5/MawUkbj8dKxiFOLz0fjMwwwO9yIVcvw6r+6yoG7l+T+7oYC1Jrs+P32Y0HjiAsQc+tTp4dBTrLuotqDwTR2BhsDMVajHZ0ylD0MTy4v0iRqxf2yeG1k1hc9pd0u3osmkj0Qwl2ThHt/hRMIXjO/EGs/OR70nhsXF/PSgAuL0zFnXBp+/oZQ9oFrULt+R1Vn0DY/KHj6wKwcvP5VNVaWjkVVkxUNIpVUDOtPpOg+56+ZXwgJDb5ymZvf1+84gdLCNPx9z2n88urRqG934FfdpK9e+qwK6hBrTq1CKtpgrt3hwdLpXPM3Oe6eNirovd+pqMVrdxSjweyERi7FH7Yf5atUn5iTh/U7TmBOYVrQmmfF1Tlo7lyHPP7BITxRmid6bmNS9by8hthaSSWV8EHznhD2KpuiqCkANgIYBeAggLtZlj0azrEsy+6mKGpEt8c+Dvh1L4AFIodOBlDFsmx15zm8BWAuABIcJhAGKW4fI5o5HK6sAsMyuG3KCFR1djmVUMBtU0aAYcM7Xi7xT7rdgy6KMGUp5BJ/k4HArCidUgp5mMdTFCVaPrVpgHaYB0NGUTgwDItTLTZUt1ghk9BIjVHyGWucE8ktNIYb1KAAqOUSVNSY4fb6xf7dXh8Majme3HYYbi8r2siww+XBqrl5UMskQWWq63f6NZ9KC9Ngd3uxZdllsDjdsLq6yp1CNV/6oqoFr35RPSi/22hhIMeq28sK9PrWLhrXr6/fU+xuBi9/XiVYSL78eVXYFQr9jULql2xZ+cEh/jtaPTcfCllkotV6lXhjUn2EGsAMZFOp/hqrgc4jpxlcXmLEsFgVTjZbsXlvDR+kfez9g/jFrBx4GOD9b2pw75VGMCzAwj+v2tw+5CTr8Ot/7Q/ZKJRhWTw5Nx+PB4yhJ+bk4bn/HceJJiuvz87JQWypqEV5SY7gs2bEqfHfgw1YMi0LCimN7CQt1gQ4VJzz02Z3Y+PiiaioaUNuih4vf1aFA/UdmDU2hb+naAqYkBErOpeMiNdgUmbcoKsoCJfzjccR8ZoBmVfDuScsTg+/ySpmf1+6dQIoGnjp1gn4oa4dPgb4y+6TWDotK3gdV5qH5z85hilZiVDJaLx06wSs2nYYNSYHtlTUYu2icahutmJsqh7xWjnKAjrJc+/HZQsHlvcqZTTGpOiJDY8A0bJejTQauRS/v7EgqCGdNkKbpT2FoljR9QVNR0EGC4CkUBU9+shpJocz/4Z7f4k979U7ioOCzw9tPcDPoYHvWVHTKvDduDVC96aiXGN4p4fBo+8dwou3jhf42gaVFFePTeXft7wkO+h7/3B/PZbNGIWNu09iybQsSGhgbKoeY1J1aLKIVy7TtF+aoarZKtjYdnr88gsbF0+ETELhkWtz0WJz8/dYvEYOqQSi1cRzx6Vhw06/Ldlw6wRUN1lE39vs8OBUix3bDtTjmflFqDHZkByjxOMfHEKNyYH6dhduvywTzy0oAgugxmTD3/7fabTZ3XhqXj5qTA40dziCNr5Xlo7FP/acxrMLinCqxRa0VlpZOhYmmxOPXJuLMMMXPD2ZVV4E8CCA3QCuB/AnAD/u2duF5G4AW0QeTwNwJuD3OgBTQr0IRVHLACwDgIyMjH46NQKh/xnKY1UuoUWdgC3LpoZ1vEYuw6EOS1Dn6cx4dVjH17U78M+v/cFDh9sLlVyKV3efxM+uGIWiDMMFj3d4vNAppQLtT51SCqcnvPLqDof4DnOHY2B2mPszw+1ijVOxhcjvbyzA6rn5ONNm5wPD3TONHi8di8x4FQ7Ud6Dsn98D8Jc5/+6GArTbPYjXyPGnReNwoskKl5fBpj3+IMKyGVnIjBPXjapusUFCAwfrO/CLLT9gw63jkapX8tlsqs7y1O6LQq4cO9KNzaKZgRqrg7EhnYfxiS4kvUxkNAStLh+2fCucNzd9VY1fXpMbkfMZk6xHbatd4DikG1QYk6yPyPn0p9zDQIxVLguou8TRpj01+M21o5GdpMPC4nRBJ+1zZid2HD2HGyYMx73dslG27qvDwuJ0/rzEvotvT7fj6+pmvLK4GGanB2CBjbtP4kB9BwC/tvELN4/H8pnZAIBYlTSoZPTR9w+hvMSINduPA/B3KX/0ujG8hAB3rgBgcXohl9A4dq4D9800orrZLx1gdTnw4f56PDR7DNJj1ahutgZlTdE0hcuy4rFmfiHfxI5znKNBC/Z843Gg5tVw7gmN3J+NFWqT9bsz7aApBGWiP/3RUay/eTzvkOck67Dpq+qg6p/Vc/PR4fAgUa9EbasNbh+D440WrHuzUpApzL0f1dkVvrzEiE17avhrPjJh8F/zochArlejOUPZ5fWJNqRLi5IGrTYXgw27KgUBtg27KiO2Gd5T8lL1eGpePq/7qpT5G4blpcb0+LX6y68KZ/4N9/7q/jyDWh5SJqp7oFEp8zfxvm1KhsD3D9VUtDBNjwP1HXB6GOyvMwuatpWVZAtswdsVdUFJAjdPysCWb2oFkmynWmx803ix+MMzC4pwusUWslqooqYNOclaqORSbPzvMcH5vvPtGdw2JVPQjJCzH9zxB+raYUzS8RnJge/91zsn4evqZiybMQovf1aFSSPjUdfu4BvJNZid/Hpn+cxsgcwWVwl9xuzC1n11/P0zJkWHv3x+EtNzkvwbpZ9VCdZ6NAVQYLFq21Esvyob5zqcGJFwcWQlaJZlP+n8/zsURT3cg2NDQlHUowC8AN4Q+7PIYyG3mViW3Qh/djOKi4ujYzuKcEkylMeqPYTIfLjaWFaXVzTzduPiiWEdn6hTwOz04Pg5C284zE5P2LISMokED209GGRwN90VXuavPoTuIWe4Ljb9meF2scap2ILl4XcP4u2fTYVBLQuZafTktiP4808m4Of/6Apc3FScgUfeO4i549JgTNLh/s6gcSAMC9S22kSvi5dhkJuix+ptfk3EykYrlu/4nn/9h2fnBnUp5jqrp8Yo0WB2XpTswUuBgRqrA5n1GS5qmVR0Efv6XZMicj4mmxv17S7BvFnf7kKrzX3+Ay8SUikNpUxYMquUSSCNkO4G11SqewZObwKJF3uscptvda02UYkjpUyKw2fNQZ20h8Uocfe0UUFzM6fJWpTul54I1IQPDCBzgbifbvZ3yn5o68Ggz3G80cJn2/xxYZHoZ82M1/BzdZvdDbmUxqtfBMtYyCU0NuzyO0WqyySCz7lmfiFmjU4S1UfksqakUhpzCoehIC0GTRYnUvRK+Bjg61OmQR88Ot94/PqUaUDm1XDuCaVMgvISI5weX8hNVgbBgWODWg6FjIaE9tvvs+12TMlKFG1St2xGFlb/5yg/DjftqQnKFObeb4YxAfPH+4MK4zNiif5vhBmoNUC0Zyi7vOINWl+9vTjCZxYedrcXNSaHIOPU/3h0aA5LpTTmFaXBmKTFObMTKTFK5KXG9Go90l9+VTjzb7j3V/fn3TghHWda7aJzdnFAxQ1nazfvOYWbJmXyz926rw4rS8cGrSVWfnAIaxeNw+ptR9Bmdwc1SgtsEAeAr3jiNOYnDI/Fo+8fQoPZyW86A/6gslouwdfVraKft7nDCWOSFsfOdfDnzmU1S2jAmKTDmVZ7UOyBO98WixPlJUbEqeUYFqvE/joz5k9M5z+rv6mcTXwDtKYNv/7xGPxrXw3GpsWCpoHiTENIexj4+8kmK1bPzUddmx1tdjd///zm2tG4tiAV63ZUYt3N4/kAOlcVU15iRLxWCaeHgdvH9DiJoSfB4ViKom4M9TvLsu/26J0BUBR1B/yN6kpYVlQdsw5AYOuRdABne/o+BAJh4EgKoS2VqA0vOOv0+EQbunWfdEPhY3xYcXUOTjZ3lV+tuDoHPja8RUiTpW8N7ZJ0Cjz2f2PQZHHx75+oUwxYo6nB2HyrO40dThjUctw2JQOJWgXUCikYxovTJjt0iuBMo8DSJBr+0p8mq1uQScawCNnggGWBt/fV4fHSsXgyoCynvMSINIMKL39WhQazE/ddlR20OPj99mNYd/N4PHhNDuK1CpxqsWHDziq+HHtLRe2g+m6jiYEaq0k68ffpqQ5Xf2IO0bjSPECNK7uTolfg51dkCUrqfn5FVsTKJk+bbHjqP0f47BCGBZ76zxGMipBu50A1leqPscptvi2/Kjuo4dq6HZVYd9M45CTpUF6Sjbcr6gD4nUG5VAIfy/KNuzicHgbpsSqYLE5eI3Dz3hosm5GF3BQdwAJVzTZeV7jB7IRaLq7fl5uqx2+uHQ2rywe1XCL6HLVcImg4tmFnZZAu7RNz8vDUR0f4jcTu8/ZDWw9gRJw6rKwplgU8Pgbf1bbzmcyDPXh0vvE4UPNqOPdEvFYOjVwCCYWgslhuQ2H+xHSBw37blAykxCjxXU0b38hwZelYeH2s6JpgXHos1t9chOONtqBMYVWnLE5mvAoPzR6Db061oig9Fpdlxfcok4pwcRiosToYq4d6gs3lFV0v2FyRWS/0FE0Ie8DJDEQDUimNouGGiDTEFSOc+Tfc+6v78yjKn7UrpuV+eVY8Pgp4zwyDGjEqGb6vbeNfo8HsRFWTVdSXPnauAwuL05GsV+K9787gvquyQVH+Kk1jsi7ofNvsbhw9Z8GLu6rwwi3jRZuPTsgwwO1jkBqrEv282clavLDjBG6ZkonyEiPe+rZWNKs58DjOxlicHuSk6FDZaMVLn1dh2YxR/LqKs2M7j53Dz680ir43ANS3O1A8MpGX3MqMV4lKcL38eddG5lPz8iGX0jjX7sDUrDgk6ZW8/WRZfyWWQS2HjKbg8bF4dkER6tvtsDh92LSnBr+YZeSD+T1NYuhJcPhzAHNC/M4C6FFwmKKo2fA3oLuCZVl7iKd9C8BIUdRIAPUAbgZwa0/eh0AgDCxuxhckMr/q+jx4mPCCs4laBe760QhBpuaKq3OQGGbjAqlEgrPtziBZimGxqrCO72tDu/RYNZQyieD9n5qXj/TY8GQx+kp/ZrhdLFL0SiydPhLP/u84f45P31AAKcuivs2O5xeNg8XpQXlJNnYda8Ls/NQgI65V+PD6VzW8vhJNAbUmW5CuWaBGZbpBhUevHYNYjRwUgFiNDFRnMUpqjBK5KTq+wQAX5HB6GBw+a4aPAZ77+IRgXKzfWYmNi4sH1XcbTQzUWKUpiOrXRjLmow/RuFIfgcaVACClxTNgZCEev9iYbC7cOjlTEBB8YFYOWm2uiDnzA9FUqj/GKpcF5PQGl1Aa1HJ4fCyONVogoYCHr82B1cUEbZpt2tMVZFPKaHQ4PUjRqyCX0nj9rskwO9yI08hR2+oQBFQfLx0Lq9MDl8eD391QIPjbo9eNQWWjBXFqORxuB9RyWvSzqmQ0FFI533CM47kFRfAxLGiaQpvdxZdlhpIsqDc7QmZNjYjX4EybDftq/AHhJdOy8NqXQi3CwR48CjUeI7EGCNX8NiNOg2EGq7/BIvzXUK2gYXf5JZ3mT0zH7uNNIR12zn6v3nYEf72zGEoZLSo5tbJ0LLYdqBdsaihlNCaNiMMj146GRikLaqw0p3DYoAz8X0oM1Fht7HAiJ0mLpTNG8Y2uX9l9MmqqvlL04n5R0gAlnfQVpZzGb2bn4g8BDSJ/MzsXKln0BIcHIxdak4R7f3VvhJubooNcSmHz3pogDX+plA56T7vbi7cr6vDw7FyY7P4Eg6xEjagv7WOAzDgV/nuwAQuLMwSxghVX5+Dh2bmijUQB4JXdJ4Makj81Lx9vfn0Kd/9oFHRKiWj8QSGFX5JoRyVunpSBZ+YX4Y6/fSOw93VtXZnSqTHKIBtTXmLEzZMy+AAtd9z6nZVYu2gcrA5XkP/J9VlIjVXizr99yx/nz6L3y23a3T74WBZn2+yYOy6Nl1FTSGkoZBLIpTRabR54vQwvsxankSMnSYubJmdg1bbDKC1MQ2WTBUXpsfjHHr9esV4pwzPzC3F5VnyP7VzYXgjLsnf16JUDoCjqnwCuBJBAUVQdgCcAPAxAAeATyr8Ntpdl2XsoihoG4FWWZa9jWdZLUdRyAP8DIAHwV5ZlD/f2PAgEwsXH7PDC5fEJtCJdHt//Z+/M46Mqr///uXf2PftCQgIhCUsSQAxuX6UVlKJFQAS0tlqtlp/fFqFSq7ZVEaXuxS9Uu1CXqt1AsW61VAUtWtegsoQAgUBiQvZ19u3e3x+TuZmbuZPckElmJjnv1ysvyOTeuc/MPfc8z3Oe83yO7Iw4j5+T3D71gszt1u7e7Kj+2VJyt18ZNCzuX1KCe0M6l/uXlMCgkRckqet0CLpUwevf/eohzMlLHpVB6GhluA0Hq9srBIaBYHGCg0JHWtXUI2Qv3jq/CLf2KywT3Ep63Xn52F5Rh2vm5sHQm4FgUCtwx7emItmgxsk2u6jo0j2vHcLPFk6DWslif3033jzQgGvm5uGWb07B6S6XqIJtaFB5wbQMIVAcisvLQaVg4uq7TSRGy1ZPtdvxwse1Ir27Fz6uxbQsEybHaGKoVrCSfuqvN0csqzCiuH1+2D3+sEU1ty822z41ClYIDAOB7+eJd49hh0zt+kQlGrYazAICxNrA2RYtrj8/H7e/vB/JejWuPz8fZp0Gd+zcF2aHoVXFNy0rg0HN4rYd+0V9YqpBE6YZfP+bh7F6XgGSDRr4/H3jALNGAY2Sxa/e6ptsTUjSIdWgEo0VDGoFGJbBr/9VJWQtJevVuKwsG7eH+Oeg/nwwQNx/EpqfqkOaUSNoxwcX+7QqFllmLfYcbYbXxwvtjxRgTpTgUSij5Vc5jseeo81CQEHBAGW5Fsyfmilci2UZzJ+aiYI0I441W5FiVOPrDid+GbJoEKwp8dCVZfjB8xVhE++bLizAK1/Uw+fnAxXpGUawheBxD7x5GE9dOyescnuX04vsJH2YFuSdOw+gdIIFUzIS696ONUbLVickafGdc/NxR4gP2XBFCbItibHry+uXlpV4cZQKXQ8XrUqBlH6+PsWgglYdm8Xn8cJQnq/+hXA3LSvFb/b0SRVsXjUbeSnSizaZJi3USgYuHye8h1R2bHC35U8XTsOquXm4rV82/+Z3jmHNxYVCobl5Rel4+F+HRbtM3V4vnrthbkD2oremUKvNgwMN3bC5fXjtqwbcdGEBTFoFJiTpUdduR16KHnuONKG23YlHdh3Fb797Vlh/v6OiXgjuSskabtldjcdWSEthNXc7oVYpsG3vcaHtwUK5N11UAJ4PX6ivbXfC6fXj/ClpONFiw80hfR8QGNOsnlcAnUoBnZrFsx+dFHbSJenV+N9vFuLhXVVhC6qblpVi5dyJMGhYTEw2nZH0yZBTVBiGyQTwIIAJPM9fxjDMDADn8zz/TKRzeJ7/jsTLksfzPH8awOUhv78F4K2htpMgiDNnOIUbfH4eD/YKugfRqljZwdlup0/S+XbJDC47PNLny9W2crg5PPX+cdHk/Kn3j+PxFbNknR8P+qajkeE2HCIVOihIN6ImpJpssKOTOlbJBgofPvP98kCRAQ+H6hYbHB4/JqcbYXV5UZRhwvcvyIfV5ceuQ41YPDMHTq8fSgWDD461oLbdiS27q7H1mrPQ4/KKsoaDOpvTsswoy0mCSSutWZxpTozJRbwyGrZq0CihVvb5L4YB1EoGhhhW+m63eSTtut0WG41fj58f1qJatGmL9P3ESAN5tIiGrQazhR7ZVSXK5JmWZcJj/z6CZL0aN1wwCU+8e0yoKh6Ky8uhKMOE2xcWoyDdiGc/PIEF07NEtnHv65XYcvVsyXM5HsICXlDX+PaFxcKCa/C4Da9X4o/Xl6O+qy/bk+eBLocX5xakC1lL07NMeOztI0KfDAB/2HsC9y8pxf/78z7s3CcuWpOfqsMt3yjE9c9+JpqU7jnShLULpqKmNaANeKrNHubP+/+eqJJBo+FX6zrsON3pFL12utOJug67SLKB43hYXV5wPA+/nxcCw0Cfn1m3oAhsmnTRWJNWgevPz8fqFwOLGGsXFEYY4/mw5uJCuHycqKJ8fx3L4PFVTT2YnNY3tk3kgmWJzGjYapfdi41viP3Pxjcqsf2H5yE/dcQuGzXa7dL9YaxqAgyVHqcPd0jUcnnuhtjUWBhPyHm+pGRX7n71ELavPg9Or18UVJbykyVZZjx4ZRk+PdmBmy8qwM599UJ27B+vK8fntR3wcwGfvG5BMZq6HMgw6yRt2uXjBG3di4rScM05+aJCgL+4bBpcPj+aetzw+J1otXlw/fn5sLl9yLHocMWsHOw92oIls3NEi0EPXVkGk6YBR5ptMGvDawN1OjzotLvxu++ejXa7tLwkID1OKMoyCcHdUI371fMKcKLVhjRjCsrzLaio7RadF5QLa7H2zYlDJZOKMkx4/O0juGZuHlbPmyJkLd+5aCqcXj8Wz8wJC2Lf/eohbLl6Nj471QU/hzNKgDmTmdGfADwH4Je9vx8DsB0Rgr0EQSQWwy3c4IxQkM4pMzhr0kprU5m08tyVMcL5Bo287UstVrdk4YQWqzzN4UTQ/I0lHMdDq5LWmlSxTFiAKlJRhEm9E8kOuwc9Lp9IyzC4LVqtZHDXoumobXcIq6y17U5BxsLu9uLlinp0OTyigHQwazg3SYcZ2SawLBO27SqYJUWSEvGP1+/HbZcUo6atT4f8tkuK4fXHrhiKSRfBz8VIVsLmll5Us8VI09CgiaRRGLuA/mgQDVsNZgvNyDah8nQP2ns1+jpsbvzqyjJ4fTz+9y/7BpzsVLdYkZeix0uf16Githsrz84TXSNZr46oK8zzfUHiIOlGjaR92d0+TMsy43iLDW4fh2c/OomNV5RgWpZJKPjS4XBLyg0APN5aexGaewLB5XULimD3+DEt0xSWWbq9og5rLi7C6hcrhPd4YtVsof1SRfbiTY4p3mi3eSR3G7TbPJiUFjjG5+Pw6v4GYXL/i8umSdpBil4NY+8zH6qtqmCASSkG/CQkcMHx0jbLgIHHzwkFD39x2TR4/BwyzTpBXztUKuVYsxUzss0oSDcmfMEyYmAaIyRtNPW4IC/tI7Yk6aULXZtHqdD1cOmweyQ1kxMluD3WiZTU5PD4ce7kVJxqt+PTk+3ItmhRedqKn74kluhRsgx++lJgR9LK8lysv7QYLVYX/n2oCT0uL3IsOug1Sli0eZiYooVawYIHJP1yUKJIqwoUnb371UOC7WiULNLNWtz3eqUwl/v5omlQKVmRPNWWq8/Cuu3iHac//8dBbLvubDT3uHCqzSYpQfjcR4Hdon+47mzJ56223R62EL1hcQm67F4hKB6qeZ+XrMev3zkGALjmnElotR0T2r1uQREUvUm9wbiBlGTS2vlFYBjA7vLiiVWzA7tVGQZVTT1wS0iHubwcup1esAzOeLx8Jmel8Ty/g2GYnwNAr/RDYpSbJAhiUIZbuCHVKD2ISTHKG8S4fT7JSuhytzcrGAbrLy0O0+ZSyhzgpxrV0u03yNM8TgTN31jh8fixv6ELAB+mC7V2fpFkdkToVp/QY093OYT78rOXD0hmIvE8hG1LoUHfxm4XfvmPg3hi1Wysu6QIP/6reBARzBqu7XAi3WQXtlL133a1edXsUfz2iDNFp1SisbsnLIiRlzw6OuBSOL3Sfs7ljc1wKtUQwe/p5fm9aGPQKCT1aOUu8iUq0bJVlmXA80BdhwPb9tYIMhI3P18hyhaWCoqGSupsXjkLH5/sEC3OZlu0+N9vFMDPc5J+/MVPaqFVsSKdZH3EYL8CFbWdyLHocLrbiV9cNg2tNo/I3//qyjI88+HJMB/94g/OETKiOI5HplmLFqsLDokF6sUzc4T3DL7Hw7uqhCJpjd0ubK+ow5PXzoHb58e0TLMoq5QIx+XzS+42eOb7fbsNKhu7RTJbU7PDCw5pVSw6HB5kWDR4aHkZmrpdouf+4eUzRcdHstn6LgemZZnw6FVlSDaoUdvuEOoEhC4aB2WmXvykFhdMSUVBujHhC5YRA5NtkS5UlZUgshKRxgvuGI0Xhkpusk6yxkKuzFowxMgSaaFXr1KIFs3WLigUxiZAn0TP6nkFYYHN4A6en77Ul73780XTUNvuFGUCh/rlDVeU4G+f1gpBZ7vbH1Fj3ury4vmPatEektwTbFNlY3eEoKkPmWYtvH4eZp1SVPg2tJhpVWNPxHERAPzismmYkmFEQ6cTP+onZRR8H62KRVOPC50OD/wccPerB/H4illw+fxI1qtw96uVOCsvCZPSjJiUasCDV5bhVLs9LBN4655qPL5iFsw6JVxeDpPTjLC5vDBplChIl05Gy0nWweX1I/MMC0qfSXDYzjBMKgJF6MAwzHkAugc+hSCIRGH4sgjSwVkG8iZZOpUS2yvqRLIO2yvq8OhVM2Wdz7IMtEpWpG2lVbKyJ3laJSspaB/UcJRz/XjX/I0FHo8frx44jXtfO4SbLizAmwcCulAaJYvCDCMe2VWFVeUTJbf6OD2+MHtYOjsH9yyegS/ruiTtNTc5XGcwqF/4VG+l2aqmHpw1MSniiu9v3quGggWcXg5TM000eUxQHF7pIEasJBMAQMGwkn7ugaWlMWnPcP1etHF6/dCrFCI/rlcpYhY8Hy2iaaunu53Cey2fkyt636Cfbex24cVParF6XgFyLDrUdTpFkyQvx2PdgiIYtUrkp+rg8QUW9lptbnxR14XXvmrAmosLkWXWoq7TIQSV719SApfX33edLodksJ8BRIHw/7t6dlgQ95e9BeNCd/O4vBxabW5wvQXqQrfO1rTawvoRBRsuLVDb7oTd5RU0As/KS0ZBmh4Tk6m/loPbK5215PZywtbjrzudov61y+7BbZcUiwpN/uxbU5GkV8Hu8osCw8H3O9kmvp/BQP6jK2bhWO/EPjgmqGm1AwByknV4/O2jYc/R4ytmgQPw0FtV6HR4hB1d8SAHRowcJdlmbFpWKgpKbVpWipJsS6ybJguNUiE5XnjwyrJYN00WHp90LZjy/OQYt4wAAI/fLxkMtbq9onlPJIkejkeYTu/imTlhUi7tDo9QbC74WlDL90iTFb//z3HctWg6Dp3uQV6KDjaXHyvLw/V/t+09gZ8tnIb1lxYLr4USaXeJQa1AY7cLG16vxO++dxb0GgWe/qAm7Diry49XvqjHTRcWID9Fh9qOvnFRtkULhYLFpyc7woLSwTnmMx/WYMPiEuz8og4/XzQNVrcPN19UAL1agdNdDuQkBTSag/0PyzKYk5cEXuKzuLwcePC457VDQtbxH68vx4P/OoLiDKOwwB06bufBY0KyLqJG9GCcSXB4PYDXAUxhGOa/ANIBrDijqxMEEXcMVxahocuF5/57SjSIee6/p5Bt0WFO/uDn2z0+ySr1cjWDe5xeaJUsijNMsLt9MGiVcLi86HF6ZZ1vdXuh6Rdc1ihZ2NzyzgfiX/M3Fhw83S0UJmCYwMT8lS/qsXxOLo632HD7wmlQKRAWoNq0rBQOt0+oJK9VBYoR2VxeJOlUwgptf3t1RNgmH9zSplUFqubuq+vC0x/UhK34ttrcuPacfHA8jyNNPVApGJo8JijWOJNMAACdWoHvnpsftoimU8cmM7bV5gbD83h8xSzYPT4Y1Eo43F602eXJ6USbVINGVIDDzwHPfnQSz92QGAV4zpRo2qrV1fdeoQXXdu6rFwXoOh0eZFt0+O1/jgsF3oA+TXUly8Dm9mHL1WehqsmKQ6e7sW1vDW6+qAC17U48/vYxQSfvqrNzMWdiEjocAbv57bVz0Gp1w+HxQacQ96sZZg3u7hcIPtzYI/n5Ff3WKLQqFmatCgcbuuDw+EUasVK7d6ZnmSX7idkTk2H3+JCXYqBM4SGSZtJIfqdpJnWYREOwf2VZFn/9rBZrLi5EulGDCUk6uP1+rPnrl3hkeRlS9Oqw+7+joj6sSPAt8wrx67ePCJPlexbPgN/P4Xf/qQlkvK+SLhx0pNkKILDo/OCVZcKOLpIDG9solSyWzcpBUYYRTd0uZFm0KMm2nFGxpligVDC4/vxJQiHn4KKKUpEY/qqpR1rDtaknNuMLQkyqQSO5+HB2vtiP6lSspJ9kGYCDOLApVeQ1UnD5aLNVmA96/BxMGgV8HI+7XzuInywoFp2TbdHi6vI8QTpq3YLCsDa9sb8hLGi6bkERfBwPnVqJZL0adldAz/7BK8uEwrTB4Opv3z+Oxm4X3jzQgE1Ly1Df5cRVZ+di575AGx9483DEeg3Tskz47bVz4ON5rF1QhKpGG57sTUgKtqPV5sHDy2eKdhTnpRjwdYdT8vut73QKYzOXlxMWMw809KB1T1+NpHMmJePPn5zEmouLcUFB0hmPZ4YcHOZ5/guGYb4BYCoABsBRnuflR00IgohrhiuLkGXWICdJg6lZJjjdPug1SuQkaWRvb9CpFPjrZ+Jq7X/9rBYPyVwhTzNocKLVjnvf6OsU1l9ajOIss6zzVQoF7nrlizDn/KcbqXDCcOiv+ZafqgvTkbzvihKw4EUBBIfbh5f31Qv2YFArUJxpQlO3C8kGFT450So5CGizuyPqYQYnq9sr6rB4Zk7Yiu89i2fA4/WDZRhhlVtqAEKTx8QgwxghiGE8sy1X0cCgViDTrBHZeqZZA70qNsFhnVqBp/5zQgjG8jzw5oGGmGUmTUo14M5F08edPE80bXVCkngrtej//RZA/RyHH1wwWfB3WhWL+5eU4s6d+0UBuG17T+CKWTmSGcjBqubBCtsKBvji6y4hM2dmjhk3z5sCl8eHLIsWTq9fFIwGImf8TAsJ7gYXjFttbtz8QoXIPoIasYtKsjD11otQ1dSDY81W/O7942GZy5tXzUb5pBQKCJ8hbp8fty+cKmToalUsbl84FV4fH7bLJti/Pv9RDX78zSLc+3pAR3Lzqlk43e3BTy4pgtPLobE7fHLc6fAg1ajGmosL4fFzmJ2bhL9/fgqLZ+YEMr4nJkGnYnGgvhtXnZ0LlgEsOml5M5YBpmeZsXpeAebk9U2eSQ5s7KNUspg1MRmzJsa6JUNHyTJIMahFPjvFoIYqQXxXtkW6X8s+w23vhHzkFNqMNN7KNIvvG8sw+MVl09Bm9wg1EdKMGnAcjw6HR/Iei3bwMNL9u1bJhklH3Lt4BixaFXRqcY2a/hnKOyrqw/r2686bhGSdSvS8ZFm08Pk5/GPf17juvHwhuJyfqsPvvjsHNrcPPBj8Y9/XuH3hNDR2OWDQqvDDkDoFt11SjAlJWskxVfD36hYrtu4+3juGKsE7hxvDMqVXzytApkkrug8sy+D8glQ8etVM3LHzgHDNB68sw2P/Piq6X/qQ7yR07MUyBbj23MkozTnzwDAwhOAwwzDLI/ypmGEY8Dz/yhm3giCIuEKtZERONbR6+mAYNApcf/4kHG+xCp3H9edPglGmVqROpZBcIZcbNHH7OSEbDwg4483vHMMLP5CXcdbl8EquBnY75K+BUdXrcNJCtJx37qvHPYtnhE0g73ujUlThHgh0to+tmIUH36oCAFx3Xj6+98yngm1sWFyC9442YvOq2TjS1AO1goWCAXKT9dhwRYmwrSmoXdnj8OCmCwuwvaIOV5fnCRpSwRXfHavPw/1vVuL6CwpQ127HYytmoaHLAQBhcik0eUwMrG6PZBBjKLsBoo3Ly+FOierdf7353Ji0R6tQ4Jq5eWHb/nXK2ASrWZbBwumZ2L76vN6tfDqUZJtj6kdHw69H01ZnZPVtpd65r28CtXxOrmhrJxCwvSe/cxb+cN3ZaLW6kW7S4C+f9GVuA8C2vYHFg+Dxg+kVb7vubFhdPvzuu3Pw1HvVmD8tS6genp+qw31XlOD2hcVw+ThBduCN/Q1hmTxr5xfh9+8fF0lfMODx81cOivqP9Tu+wtRbL8KUjMBODoYJaGkvmJaJeUVpSDNqsHBGFlptJPcUDdKNGqgV/caKCgYOr3T2+7QsI6ZnmaBS8PjTDXPxdacTN/7p84AvXDQV971RiWS9OsymNlxRgi3vVuNAQw+AgO09d8NcWN0+aJQsuh1u/O9fDomuWZ5vwR++dzb21XWC4wOZZNfMzYNBrUCr1YWZuRbRlluSAyPiGY6DyN8BgefgRZnzmlijYBhJWSEFPV+SDDbWkPo7AMnX5BTajOT/AIgWzRQM4PGLa6/cvnAqXv+qAZeVZYvqw7yxvwEbFpdg45t9c7AUvTpsHrXhihK4PD488m+xDND9bx7G4ytm4aF/VYl2OvWXiGrsduGFj2t752pOFGcasfGNSli0KqyeNwU8eKSbNPD6/Hjs38dwUXGGKLhc2+7E//7lCzy2YhbueDlQVK+23Y4ZE8z40V++ELXpiXeP4Znvl0cc/wT1k4PH3/t6JR5dMQsVtV8K7XV5AzIcHXaPIIsVeh/0mn5yampFWAymvsOBexfPwP0hSVHBsVewiPpwGErm8BUD/I0HQMFhghgDnGq344E3DwuTQo4HHnjzMArS5Mkk2D1+dPULpHY5vLDLlIVw+/1IN4oz6tKNGng4eee3WKW3L7VY5W1fyoi0VVJm5hZVvZYmSa8UgrWN3S7Udzgk75OSZcNeq26x4oYLJoHj+TDdso1vVmLzylnwcxyKM0yoabPD5vHD4+fg9fmFbKO5+SnYsvsozi1Ih4IF7lo0Hb/r3ToEBO7xjGwz8lP0uOacfCGIEZpl/IMLJuPFH5wDP8/T5DGB0CgVkkEMdQy3lLbZpP1Umy022yzb7R7862AjHl0xS9jx8ce9J1AYI8kUjuPxdlVz3PjR0fLr0bTV4Fbq6VkmdDq86HZ68cfrymH3SAfvrG4ffv63g0Lw9pZ5haKJ3dr5RVCywHMf1QqTohc/qY1Y1KWp24U7dh4MBJ6vnYMH3qwUdOaLMoy4742+iuNBH3vjBZORk6zFmosLkZOsw8k2uxBsvqwsG/+3uxqdDg8eWl4mVDAPBq937qtHXYcdk9MMkvdqTl4gSzgYPO4PLeoODT8HPPiv8EWG7T88T3IMBTD41VtVuHV+ISobbUKAIduiRZpRI2RBvfhJ386xcyenoPJ0N+ZNzUCrzYPG7sAOpI9r2pGbpMOOijrcdOEU4XgA2Hu0BfOnZeH//XmfcP8fWFoKp8cnyE7889aLwu4tyYER8UqnXTpppf9cK15p6gkE8EJ3hL7wcS0mp8WuKHC8MthYQ+rvT157FjwhOzaC58zIll8rJZL/W1SShdQbz8EHx9swfYIFP+zdrRN8v8ffPoo1Fxdiy+5q/O57cwLSZL1jyFf2fY3HV8zCsRYr/Bzw+701ACBa6N25rw5rFxTj5osKAEBYKHZ5A1q7te1OcHzfjtKijPCipp0OD+o7HbC5/bC5vPj1ytlo6HLiWIsVL1XUC8Xuul1eSbkLl5fDyTY7fr5omlD3IZJsRJfDiy1Xn4XKxm6wLLBuQRHSTRpkmDS4c+dBYfwTPN7lEUuCaVUspmWa0Gp14VS7XfR9n2yzY01IgfTg8duuK8fqkAzm6dkWVDV2C99JcOzV6fAgzTj83ayyg8M8z9847KsRBBH3tNvdYdv9184vQofdLWvQ7PNzsHv8YdXWfX5u0HMBgOFZ/Pqdo6Lg9K/fOYrHrpol6/zsCNpxWWZ5DtOiU0mucCfpVbLOp6rX4XAcjx6nHxatEn+7+Vy4/RycHr/kfSrKMCLbohUFbf0c8MS7x7B5pbSOoNXlw4aQwgfB80JlIu5+7SBq252oqO0W/r56XgEONPQIA6mJSTp8Vd8lqq4euiX2oV1HsH31eZg1kYpoJBJKlpUMYsQy6yZZr5a0/2S9OibtSTKocFlZtmhRZN2CIiQZ5Pm9aBNvfnS02hNtW+U4HlVNVlEhpieuni1peyfb7MJri2fmCIFhoM8P/vG6cnQ6PEIRu7xkPZL0KsmiLsEFWZeXQ02LVXJcEQwmb91TjW3XnY1TbXb4OR5Pvnccv7hsGmblWlCcYYLT64dJq8Q9i6cjWa/u1eDMD+unzVrVGd0rWtQdOi1W6SJuDq8/TKJh3YIidDrc2LikBIdOd2NSqkE4d/mcXNR3OiJsk4WwRTc0K93PAfe+Xok1FxfC7fOLahKEXjvYpnteO4THVswSdCNbba6IiwQEEW8k6aVlUuTOS2JNqlGDTodHVFRUq2KRYiBZif4M1n+darfjkV1VogWx6mZbWOLM+h1f4fkbz4mQLBVeKyXS4ijLMkg3afD0BzXIT9FLvl+GSYOfL5qGEy120a6ndQuKwIMX7QYFAj79kavKYNIqcOmMbKx+cV/YuKDT4UFesh5aFQu7x48n9wTeY2aOGU+smo2qph5hV8itFxdBrWLxwkcnUTLBjKZuFzb3xhGuOjsXAPD7/xzH4ytnwc/xAY1kvi8QrVWxcPsCC+RBfWBAWjaCZRis2/6l0N57Fs+Ay+ODWqlDp8Mj+pxaFYsJyX3yXsHP99jbR3DtOfnosLsxKdUgfO+2CDUn/ByHt0KyuvOS9XD5/DjeYhONgR5YWoqZE4ZfZPOM0mYYhvk2wzB3MAxzb/Bn2C0hCCIuUCvYsMqgW/dUQ9W/IkwEfBwkq9L65MWG0en04uryPDzzYQ2e3HMcT39Qg6vL89Als6AcywRW8gKZKujbviRzftdidQsr3GvmF+KmCwvwwse1sjOPB6p6PR4JTrqvf/YzPPDPKhxusuKjE+24741K3LN4hug+rZ1fhId3VWFlea7otVe+qA9sJ1KwwvFBtCoWRq1S8jufnmXC5pWzYFQrwrQtXV4ORRkm3L6wGNtXn4dLpmbg9YOnsbe6VfK9gqvNcgsjEvFDl9MjnQEg06eMBBx4ST/FgY9Je7wRqol75TruKBNvfnS02hNNW+U4Hvu+7gxb7Hr4X1XYtKxUZHsbl5Tg/SMtwrmRsms6HG7cvrAYP/vWVBRnmNBmd8Ph9WP9pcWi97vtkmL85dM64dzsJL3kuGL5nFzh9x5XQF/+UEMPHlhaiqlZJhxrtuH2l/fjZy8fwE+2f4VOhxcmrRIaJStpryoFc0b3KtKE/FS7fcjf+3jBoFYiP1WHH19ciDXzAz/5qToAwNQMI16+5Xz8/ntzsP2H5+HbM7OQatCg1ebGa181IL1XWxsI2Np7R1rCbHLdgiK8VFEPoM9eVpbnisYEGSYNakIWNVxeDkeapIsaHm224ukPanD9+fmykwUIIh5gIsxrmARZt+pyerF2flHYeD+WY7B4ZbD+K5jAFTpHDu686H+Ow+OTnDP1r5USnKddvvUDfOePn+LyrR9gV2UTOC4wHg1qshs0Csn3y7Jo4fD6hcBw8PpbdldDwTKS59R1OOHw+AW5iOA5QT//yPKZSDKo8OCVZYJWcbZFi2/PnIDbdnyFrbsDn331vCmw6FV44aOTuHLORKzf8RWae1xh39EPLpiM2nYHbnjuc+HcNfMLUZ5vwf1LS/HmgQa4fJzQlqBsRKjN3rN4Bh7eVSVq7wNvHkZOsh7gOWy4okR0/IYrSnC604FHV8zC2gWBeMKLn9Sitt2JJ949BrWCFX3vhxq6Jb8rvVqJgnQjzitIQ0G6EUoliwXTMvGtGZl4+vpy/O57c/CXm8/F0pkToI5CUeshF6RjGOb3APQALgbwNIAVAD4bdksIgogLHB5/hE5GXlDM6fFJbvd0yjw/Wa+SnETK1Qxu6JLevjQxRY+zZJyvVyslV7j1Mh0uVb0WE7rKPS3LhJ+9vF+ocm91eUX3KZhFNiPbjLULCuHn+l7TqljoVAx+e+0cfFXfJawYr1tQHFY0AQh85xZdoJjAzRcVSP69usWKaVlmlOUk4WBDIGM40rHBQnaZNKlMOJJ0auSn6kT6qW/sb0CSLnZZN512r6SMw+S02GhYR8pYsLljsxgSb350tNoTTVs91W5HnYR8T227Ex02t8j3/vb941g6O0fQdQWks2bSjIGCrw4Ph4J0AyalGtDQ4YBO1aeTNy3ThMfePiLaXlnbbpe0r+Bn1KpYgAdWnJ2LTIsOD751GA9eWRYWAH7gzcNYPa8AxRkmyfeze/xndK8GmpCP1x0/g+Hl/PjJJcU42WYX6kv85JJiVDdbceOfPhf0FzsdHjxy1Uyc7nJiy+5qrFtQBLvbh4eWl+FUmx06tQLfnJYhssmpmSY8+FZV2BbdHIsO/7e7WhgTZJi1eOLdalG7IhU15Pm+gMXCGVmj9j0RxHBp6nFLjhfyUhJDliFJp8L2ijpRn7O9ok72jtDxxGD9l1QCV+jOi9Bz8lLkFdocLFs5qEl8sL4rrCBdqkENr59Dil4dMXYQqhkcmh181dm5kufkWHTQaRT46Y6vcNOFUzBjggX3LJ6B5h5XWDA5OCa4/oICYedbYaYR/683Gzl4XLvDI6q1EDz3d989GyqWw9LZOSLJiqDEUagEhtXllUw0arN5YNYqYdIq8MSq2fD4OCQbVAB4PP7vY5g3NQNP7jmObItWFBvpcXlF37tUcb11C4qQKVG4kWUZFGSYUJBhGsSihs6Qg8MALuB5fibDMAd4nt/IMMyvQXrDBDFmiNQxyQ2KpRjUkts9U2RuT+52SGdOdffbrhGJDLP09qUMk7ztSx6/X7LIjlemLAZVvRYTKlMSquGkVbGwufu2gwbRqlgYNEroVAqRDf3ismlo6HKLCszds3gG/vrpKVx//iTJwUdVYzdcXg57j7aEFUa4f2kpzp2cjInJga1TQY2rSEWWtlfUjev7mMg4vb4w/dQNi0vg9PoGP3mESNJHkHGI0TZRs04p6ffNujMZJg6fePOjo9WeaNpqc48LerX0fe12+UV9JAAUpBmEY9/Y34CNS0qw4fXQgp6laO5xiySjfnVlGf708Sl4fLww6Tnd5cD/fqMQ94X46tIJlgEX3YJbLa+Zm4fmbifuXDQdbi8nORbgeKC6xRpxnDKUexXcSuv0+rFuQSF2VNSLJI3G66KuHLx+Hk3drjAJsYJ0oxCEvenCAjz13nHcufMANl5RgmS9GmadCj8JuTcbrihBXooShxutwnhgzfxCyS26Dd1OITC8bkER0o1qqJUMfnxxoTDh/uREa1gx2tsuKcafPjoFIGBDJCtBJBJZZo3keCFDImgUj3C8Hz/6ZqGoP9m4pAQ8aCdefwbrv6QSuHZU1IcVct28ajYmpxkwOc0waKFNOYujLMvA6fNBrVSIfP59V5SgocuJFqtHsk+u63AgVa/GmosLkWHSoLbDKapNIHVOQ7cTDd1OXH9BAY40BRasX/2qAT/6RmHEMYHX1/e9tErUHuJ4SCauffl1J+bmpwi7VO5ZPAMP9BZ663R4kJukw1PvH0dtuxPrFhRKtrfN5kamWYOOTjdUSiXuflVcUFfJAvmpujBprYK0QO2E4HcRLK4XrOPAMkBRplFUPHU0OJNRfzBk7mAYZgKADgCTo9ckgiBiSTQmwVLbPf98k7zMX0sELU6LTp4Wp4JB2MRgwxUlsmUlUg0ayRXuRaXyMk2o6rWY/qvcWlVfldftFXVhgdhNy0rR5XAhwywuSpiXasAtfxavBD/w5mHcdGEB7th5EOsvKQq7Z4tn5gAALirOwO/3Hhf9/an3qlGef45wX7ItAV2o0II4Fp0Ssycmweb2Yus1Z6Ek2zJu72Mio1IowvRTN75ZiedumBuzNilZ6W3xf77p3Ji0R8GyYVWk119aHNNq4mplv8Jsyti1ZbT8ejRtNdOsxa/fPoJNy0pFmsP3Lp6BP+w9ITo26Ps2r5qNug4HcpN0MGgVeP7Gc7C/vgsTLDooWAa39csu+uU/DuKZ75fjQH037B5/7/ZPBVjwQjHQeUXp2HWwHpuWlYkmTb+6sgztVpew1bKx24Utu6vxzPfLkZOkQ4vVHTGgvGNfvagyeug4Re69ktIZDs12pcXAgfH5wwvEbtldjd9eO0f4PTgJd3k5GLRKrCzPFSbewdc3vhGw7zf2NwjjgZ37wjOo1l9ajCnpBqyZXwiWAbItWrTZ3Pjpwqm44+UDwnEPXVkGl9cn8h3akIKOFPQfnyRywUkGjOSz9pcYjReGioJR4KWKukDms8cHnVqJFz6qwR2Lpse6aXHHYP2XVAJXp8ODOXlJIl3a0HMK0o2Ctu2nJ9vD7F/ubhsWrLDoCwTs8L43KvHoiln43fs1YT47VD/48RWzoNOwuPf1vvOl/Py6BUXISdbh6b01yLHosKOiHrfMK8A1c/Nwutsp2U6WAXJCtH01SkXYcWaNQjJxDQAau51YPicXT713XNjRqlGyKMww4tUv6/DThdPg8vgwMUWPdKMGm96qEvVLerUikMHd5cYzH4plJ7buqcb/rZqN+5aU4n/7zWF/8Y+DWD2vQKTJ3OnwYGKKDmkmdcziB2cSHH6TYZgkAI8C2Nf72tNRaxFBEDGFZRksnJ6J7avPQ2O3C9kW7ZCCYm126czfDru8zN/uXm2q/pmb3S552lQddi/+9mmtaBDy9N4TuHV+kazzJ6UacOei6cMKjlPV6z7sbr9oIBBclX3xk1qsLM/FxBQdNq+cBYfXj7oOBzpsbqSatMgyq5Fq0KClx4UWqxsnWmySdhXUxkwxarD5XekACMMEtlL3z5QLropzHI8kvRL3Ly3Fva8dQmO3C28eaMCPLy7C9c9+JrIDKlCUeNgjSCbY3bHLHO6M4Cc7ZfrJaNNu8+C5/54SLaA8999TyE+ZEZP2nGqXrtr8VgwLe46GX4+mrU5KNeAHF07Bq1/W4YUb56LF5oFepQDDAt89N1+0ELB2fl9Q9IlVs4UgcHBx1eH2osUmbbPBoG7o8Tv21eHcgnQ89d5xTM0yYXKGBS6PT2RfSgZ48F9Hw97P5vJj0ZYPkKxXhy1YhE42O+1ubF99Hpxef9gkSs69ktpKu2V3NZ6/8RykmzQJFTyKBS6vtARZe68PCwbyg//XqVjkRSho1GZzY/W8Kdi29wRuurAACjaQMXX7wmKYtCo0dDmRbtKA44EskxqNPR488e4xXDM3D4oQfWyXl8PJdruQ2RZEq+orUEtB//FHohecbI5Q/LE5QWqZtNs9qKjtRkXtl6LX5c4LxxsD9V+RErjyUgzCef0ZyP6BQH/865WzwAOo73TA6fGjLNcS5id7XF5JOzzVZkenwwODWoHffXcO9tV1iaQCAeBYixV5KXo8vLwMd71yUMjM1asUWLegCBOT9cL1f/32USydnQO9Rgm1koHV7cPEZB2yLFpMTNGLFrvXLSiCXqXAyVabsBD+x70nwpLEirPMYQlGQZkjrVopLGQGd7TedGGB8H29fbgNQJ/W95qLC5Fu1AR2uapZ1Hc48XWHA3nJOsnvx+PnYGKla+MUZ/ZJWQTvS1lOUkz9kuzgMMMwcwF8zfP8A72/GwEcBHAEwBMj0zyCIEYbjuPxfnULDtR3g+OBqsYetNrcmD81U5azStJJV9U1aeVtlzZplZKZuw8vnynrfL1GgW6XF0ebrIKz73Z5odPI0wymzN/oYtD0bWtu7HbB6vIKGT1+DnjwrSPodHiE7adr5hdi87uB1dQJFh0yLWqYtSroNeErwaHbkg1qJZ5YNRt2jw8pejU0KgZ3LZqOqqYeFGWYkJ+qE2lFBVfFQwdNxRlGPL5iFnjwyDJrcV1vYBiQV/GeiE8i+SRLDDWHtSppe9ZGoZjEmZBqUEeoJi5vx0a0ae5xSW4BHOsasNG01eBCb06SFi6fDzwPOLx+HGu24qWKejy2YhaONlvB88CuQ43Cd+3neWGrY+BfJ/JS9Dg7PznittH+maCBDGQ7tCoWRo0Sj+46grsWTRcybgDgZ98qln4GQvqL5/57Cnd8aypSjRqcaLUJgeG184vw3Ee1mDkxCecVpJ3Rdx1pK22w9q5UhhXRR5Je2labe/pkH174uFaQdWi3umGOsDPMrFNBo1Jg6ewcYWxwz6uV6HR48Ntr56Cuw4n/e/cYls7OwbQsM556v0ZYlHhshVi3lOOliynOzDHjrbUX0f0chwymqRrvJEd4bpL1semfh0qKQbr9KQnS/njiTOaokex/6q0X4WizVRQ0Xju/CK9+1YCpWeaw97FEGJ+clZeEP90wFxW1nWizeaBgArt7QqUjzs5Pxm92H8Pqiwrxu+/OQavVjRarG89+dBK3fKMQv+qnMT81y4TXvvxaJEeSn6rDI1fNxOaVs+DnASXL4FS7Hc9+dBKLZ+bgg2Mt+MN1Z6O524V0swZbrp6NLqcXEyw6dEcIbGdbdHjhoxpcUJgOIFDjYcPiEjT2OCWP93M8Hn/7WO9O1zJ02AOf4c5F03G0qUfy+5mRbQbbW5iv/9+mZ5kjZnzHiqFkDv8BwCUAwDDMPAAPA7gVwGwA2xAoTEcQRIJT12FHdbMtTEeuMN2ISWmDD6IYhgvTKty4pAQsw8u6voplcMs3CsNkIdQydSFMGmWY3uF9V5TArJHv7ijzN3r013D+22d1YdpjwWywYLDX5Q1oSP3uP8exbkExfvGPg0jWqyW3LG2vqMOvrixDbYcdNrcfO/fV467LpqLdzou2HG9cUoLf9upGhWaDhw6aDjT0YM3fvhSOlxoYjPXg1Fik3eHF7QunCpWUtSoWty+cik5H7CplJ+mVuH9JibDFTqticf+SEiTFSOPX4/dJtsfjj40mYLZFK7kFMGuMF4SMpq2GLvTmWHQAOExKN8KgTsK2vTU42mzF0x/UIFmvxnXn5Yft1tl1qBGLSrOF1/NTdZKSTVt3iwuCBbJ/vZiRbcbPF03D8WYbFs/MwcO7qkTa8Dsqvg4bK6y/tBguX5/fbex2od3uha9X8/+qs3OFjKROh2dY8gBSW2nzU3Vo6HLhe8/QjpHB6HB48cvLp6PV5haKE01KM8CgVuKft14EBQuclZcEnUqBT2vace8bh1GcYQzT/1+3oAh37TwItTJ87LdxSQnqOx3CohXHA0eaeoQtwC4vB6dHnFUfrGzffxJelGmivnuckugFJ5N08TVeGCpevz/sud+wuARejjSHz4ShzlEj2X9dR3jQeOuewILbI7uqMC1L7DNdvvDicrddUoyTbTYoWRZP9vrk/hJNa+cX4d7XDuGWeYVosTpx92uHBRv+5eUz4HB7RIFhrYqFSaPCmouLsWrbJ71BXC2uLs/DDc99HjYH/PE3i/DnT07hQEMPPj/ViSf3BPqLYAE4vVoJlUI6ONthd+PqufnIS9XBolUh3azF6U4nzi9IldyBUpZrwZr5heB5oMPmgs3jx5qLi/DIrip4fHzYzufNq2YL36FUxvfktMgZ37FiKF5FwfN8R+//rwawjef5nQB2Mgzz1UAnMgzzLIDFAFp4ni/tfW0lgPsATAdwDs/zFRHOPQXACsAPwMfzfPkQ2kwQxBBp7nFLalvNyUuWFxzmFfjt+8fDKqHLrUrLA1AwPB5fMQt2jw8GtRIOjxfyysEBdo9PUhPpuRvIdcSCUA3n6dkmHGu24tMTbXjhxnPQ2OMKywYLDRKvPHuiUGAhKNS/el4BcpN0yLRoUdXYg6Wzc2DSKPHTHUehVQUK16XoNfjhixUiG9jwep9uZ2g2WKRBU6RCTqRVmHikGdVwe73Ydt3Z6LR7kWxQocvhRmqMsmIBwOnl8FQ/P/nU+8fDsuBGCwXDwuPnRDqdHj8HBRObgJifk9auXzhDnvZ7ohJNW5Va6L3tkmL8T2Eq7lk8A9v2nsDa+UVw+fxh1c+37qnGoytmCQWQgIA0z+//cxyPrpiFY73FUlJ6M85D0apY1HY4ce/rlbjtkmLw4KFgAY+Ph1bJimzMolNi3YIi2D1+sAwwwaLDH/eK5X8ULPDcR7VhAewHrywbljyA1PbcB5aWYXW/viORMgxHk2S9Cl93OET29bNvTUVusk4o9jYpLSDb9HWHE8l6NW6eNwW/fvsIbrqwAHnJOjR0O/HCx31bj3//n+P4w3Vno6nLhVabG799/zhWnj0RQJ+2pJ+DsJtAq2IxIURrMjh5j6dilkTskaupGq9Y3X7skNDsnZSWGJq9CpYNq/vx+73H8fBV8naEEoMzkKZ2JPvXq6WlDqpbrLi6PA8ddreo35tgCUg6hN7Hv35Wi58unCYaKwTHa4+vmIWqJqsgL7HxzUo8e8NcZFu0aOx24d7XK7F6XgEmJutRnm9BRW23EPS957WD2HBFX5LOd8/NizhO+fXbR7B0dg4ONPQIi4Ohi97JejXu/va0sMXt+5eWIs2gwi9frcSNF+TDz0P4HPmpurAFjUCh8x48uee4IFVUMsGENKMaHh8v1KwJyk5MSNZhYrIOQGLtSh5ScJhhGCXP8z4ACwCsHsL7/AnAkwBeCHntEIDlCGQkD8bFPM+3DaGtBEGcIXaPtOahwyNP87DV5pbUd221uWWd7/D4oFIocKzFKkwgJ6ca4JJZrd3qkm6/1UUr1LFgUqoB6y+dijt3HkBxhhE3zyuAUaPE9c99hmS9Gtefn4+7LpsmGST+ySVFonvZ2O3C1t0B6Ym6TqewOvzIVWUAAlvv7B4/Pq/tkLQBADh/ingLcqRBU32nQ3IFmCaYiYdawcDp5XHHi/tEGWmxLHDW3CPtJ1t65PnJaKNgWWz6Z1XYc/DiD+QVEo02LRE0FlttLiHwNBaJpq1KLfQ+8e4xTEo9C0/uOY7lc3LBskBRhknyu3ZKjAVq25041mwVfO/tC4tF1b1Dd4IEr3f7wmLMyk0CADy060iYjT26YhaOt1gxJy8Z5+Ylg2UZHDrdF9ibm5+CbXtrhEKhDBMYF8zJG54un9RkLdEzDEcTJcvgsX8fFdnXY/8+ir/9UFwki2UZlEww4/rz83G8xSr4vTXzCwU7ClLb7hRlfgGAyyfWlgxuIdaqWDx61Uyck5cSti0XQEJMwonRIRqFtmNJc49bUrM3VuOFoWJ1+iTHOzZn7Oo+jCUG09SOZP+ZZo3k/MfPAVv3VGP76vNE15mcFl6TZ+38Ipxqs0v2m0earaJ77vJyaOh04rrz8oWAMccD97x2CH+47mzsq+1EYYYJD/VKTARlCZP1amSatZLXONYc6FNm5ljw++/NQaZZg7mTU9Dj8GL9S/uF5KI//KcGt3+rWFh4VytZ2D1e6NRKfPfcPMzIseDm5/sWhmvbnfj93r7F8NBC56FZyzrVRKzfsV/IlAYAlmGwISQIHXovEmFX8lCCw38D8B+GYdoAOAF8AAAMwxQC6B7oRJ7n9zIMM6nfa1W95w+lvQRBjDD5KQbJziIvRd4gKs0k3dmkGTWyzteqlPi/3ZVYPDMnoH/IAf+3+5jsjLpIGZ/6GGl5jndYlsG3S7ORrFejqdsJi06JO14+JnTYj+w6ivxUHX62cBp++e3pONZsFYLEkQK3weyh4O86daArWz4nF1t2V+PW+YWS52VKbEmXGjQFizOplUzEgkdE4uD0cMLWdaAvk/yFG2MT+AQQcVCeYZLnJ6NN+zALiUabDJP0s59uTIxMrzMlmrYaaaGXBy/Sl14TwV9mW6TvQWiRsSnpRrTbXIEJl8OLY802UREal5dDkk6N371fje+eN0myPS6PD34O2PD6Idy5aDoWTs8UBfvykvWCj37qvePCZEvumGQgpCZriZxhOJp02KU1HDvt4RIoHA/Jvnkg+wr+fu7kFEzLNOHrTgee/egk1lxchHa7G6vnFaCp24l3j7ZgUUlW2IQ7ESbhxOiQSFl7UsTbeGGoaNXxVWNhrDGYpnYk+wf6pA6S9epAkfBkPVqsgXoDDo84qSq0YH1DlxMcD2z7zwnMm5oRca4WilbFQqNSYOueaqFAaFBKsLnbBa1SIQSGtSoWmSYNNq+ajSNNPajvdETsL7QqFgcaurF193FhIdHr50XHHmjowZ07D+GXl09HdasNLAMUZRjR4/LC4+fwRW2X5GL48RarkCm8aVkZOmwu3HRhAbZX1OGWeYX422e1Qqb06nkFQmA9kXcfsXIP5Hn+VwB+ikAW8IU8L3TfLALawyMFD+BthmH2MQyzetCjCYIYFvkpejywtBRaVcA9BLZaliI/RS/rfK/fhw2LS0Tnb1hcAp9Mban2kMzjJ/ccx1PvBXRi22VmHitZBKqPhlx/3YIiocgMMfoolSwuLExDdpIWLT3hQajadieONFvh8vpRlGHCbZcU4fkbz4FOxWD9pcVh9zLNoMYrX9T3dtaleHrvCQCBrabJejWMamWYDUTKEgkOmv5560V48tqzsHpegRCcvnPRdJTlBAoeBQdYROIRKfDZ7ohdpWyO92PjErGf3LikBDxis8MhubdgTChaFYukGBWMUYxTPx5NWw0u9IaiVbEAL/5u39jfgPuXiPv8tfOL8Pi/j2LTstKwexD0vfcungGry4NNbx3B9c9+jppWG575sCZMO7Cu04GK2m6c7nJKtqe2wyn08+t3fIW6TgcK0o2C31UqWSwqycJbay/C31efi7fWXjRiGsDBxUI5fcd4R6NkJe+nWhn+kAZ3ArAMI9jezn31Yc/4hitK8OaBBuH3exbPwLEmK461WJFu0uDni6ajzebGw/86iq27j6PH7cf6HV/hVLt95D8wkdAEF4IScTzn80uPF+TOq2KNRsVI9uex3L2VKHAcj5pWGz4+0YaaVhs4Lrx+z0A7XoJI2X9w/vPyLedjzfxCbNtbg5+9fAC/2XMc15+fj2yLeFGU43i8XdWMq7d9gh/95Uvc/tJ+XFaWjb1HW3DP4hmi+3v7wqmYnGYQ+/fFJXh67wm4vIHCr2vn940nJqUasL2iTggMBxeAF5VkYfbEJOyoqMfa+WIbumfxDLx5oAHrFhThpYp64XNv2V2Nwozw8U+nw4Msi1ZIMHrwrSO47/XDAICyHLNkf1aYYcKa+YV4dMUs/P2zU+h2+cEwwOKZOfj93uO4qDhDuO5ZE5NQlmMe9F6cyT0eTYakZM7z/CcSrx2LXnMk+R+e508zDJMB4B2GYY7wPL9X6sDe4PFqAMjLyxvhZhHEmRPPtlrb4cCT71WLNIWefC+gOSxnOy/LsNj5Rbg21m2XTpV1/QyTFvmpOiFzGAhMXtNlZu6olQqkGlRhmsUaBa1QD5Vo2GmoDpZepUSnXbqaK8sAdR0ObN19HPmpOtx3RSmauh2YkKTDugVFSNGrYdAoYdYpcKLFju+ck4dJaQZoFAwunpaB1t4KuSvLc/HQriNI1qtFW5BnZJsiTgZYlsGUDCMmpxkwI9uMC6akJlxmyXhnIFtNNiglfUqyXjXazRRQMArsrmrEH647G10OL5L0Kvzlk5P44UWFMWmPimXCCj6uW1AElcxCoNEmqDEe2g+98HEtzspLkqV9H8+Mlq1OTpPeFXGqw44XPq4VtnH6OcDP+QUt4NCCb0k6lXAPknRKTMs2Y/VFkzE1yww/x+GHvfIXALCjoj7Mhu5ZPEOQCPjzJ3VhUj0/XzQNVrcPa+YH7H7nvnpJCYfR2o6Z6BmG0WYgW1WywM++NVWQltCqAprDChaoabWJtC+DOwHsnkDR2JsuLIBJq0BBqhGbV86CSaeC0+NHU7cTK8+eCJePA8sAdpcX3S6/kDH+22vnCFt3g1ljJPtBAPE9rxouSoUC+0614dkb5qLN5ka6UYN/fFGHyWn5sW6aLJQMC4NaIdKbN6gVULFjfLVXgqHY6WByEUGGo6nNsgx0KqUgDQVErvEglaG8ZXc1nr/xHHj8ftF47ZkPTyLdqMazN8xFfYcDWrUST+89gQMNgTlgcYYJv3qrCp0ODzZcUYIMswbP3XCOZL87KdWATocnTFoqzajB7Qun4cHebGOgrwidgmXwx+vLsf/rLrh8HD450YqfXDpVSEJSKRh8cEyNAw092Lr7OO66bGrY+GTt/CIhk3ntgkI0dLmhU7FIN2qg1yhh0vbdP62KRX7vIvJQ7oXcezyaxH2ZS57nT/f+28IwzD8AnANAMjjM8/w2ANsAoLy8PLZhd4IYgHi21boOu6Q2VF2HXVZwWKVgsOysXBzv1QxWMMCys3JlBxm0KhY/+mahqIL5xiUl0KnkDSIMGhZatVLQLFYwwJQMIwza8TcIGS7DtVOpTu/2hVPx1LVnYX99Nzg+EPi4Zm4eDGoFXt5Xj9sXFiPTrMVXX3fivSMtWHF2LpxeP77ucoJlgFS9Gv/4sgGLSrOFwgHBIITfz0GvUQqSFaE2fMGU1EGDSqEBiIGKOxDxx0C2atGq8ONvFoZV+rZoYzcEMusUWDwrF/tqOwU/tXhWLky62Cxiddg9+NfBxsCintsHvUaJP+49gaIY6ftmmrUi6QNg7GzvHw1bDfqvZL0Kz904F/u/7oLPzwd2V+jUWFWeiz99eBILS7Lx+73H8YMLJkOnUogCuxuXlGDr7mocaOgBEPj+X77lfMydlIKPatphc/uQrFdj+ZxcIZD9r4ONeHzFLPh5Hqe7nLC6vELBumCxltXzCnDOpGTo1EqcbLOjw+HBzn316HR4sG5BEbIk5H9G0x8nii7gaDCQrZq0KuQkaQML8W4fDFollCxg1Khw+dYPBDt65KqZyEnSYNOyUnzd4UCnw4NXvqjHDRdMwtrtXwrHbVpWCpfXD5ePE8YFGqUCr3wRCAa7vBy6nF4hsyy0gO1Y8AvE8IjnedVwSdIpMHdyOn7wp8+F5+WBpaVIitF4Yah0Ojx4eV89bp43RTS+yOkt1jWeGIqdDiYXEWS4mtpyazxEylB2eHzQq5V45sMa0d87HR7YXD5wIYXetCoWdy6aBrWSxc8vnwaNgsXfP6tDQZoBHM9L9u+5Fh0eWFqKe147JCwUbriiBE/tqcbF0zKEMUa2RYvrzsvHniNNKJlgxuenOoR55vpLi3H4dA82v3NMaMd9V5QAn9biWIsNDo8fL1UEFi4np+lhUCvx8K4+iYtZuRYYNUrR+esWFCHDrEF+qg7rL50aJtUh517IvcejSVwHhxmGMQBgeZ639v5/IYD7Y9wsghjTBAXg+696GTTy3IVGoYBKwYoqWG9cUgKtUt4gpsflk9RcfO6GubLOd3l4NHQ6Rddft6AI+cnyZDGI6HGyLbzTe/zto1g9r0DQhvrVlWVIMajwxNvHsKg0W7Rqe8/iGdi29wRq253Ce2pVgQJG/SvjPvDmYayeV4BzM4zD1oyMx5Vc4szpcfmFYBsQsJd7X6/E8zHUHHZ5eTR1u0R+av2lxbLle6JNikGNy8rECy7rFhQhxRAbWYlELyB0pkTDVqX818++NRXpJhV++Y9Dovv7dmUjHlhaitUv7gvbbZFl1uBYiw1An9TEj//6BR5YWorN7xzDTy4pwvXn54dlm1v0SihYBs3dTnCAqGBdp8ODNIMaTT1u3P1qX9G9YKBPKluJ/HF84vZyONnmCLv/yXq1yH7v3HkAm1fNxm/2VOOG8ydh07JS1HU48MS7x0TH3f3qIUGHctOyMrg8Xjz1fp9MiVbFItWgxrbrz8ahhm4hu308+AVifNPl9OOe1w6Jnpd7XjuEF2JUMHaoJOulxxfJutiMLxIFuQVSh7vjRW6Nh0gZyl9+3YWXJHYObVpWipf31eJbpRNEWeOpRjWcHh/qu5z496EmXFaWje8/95lk/85xPD451RG2o/n3/zmO2xdOQ32nA+svLcbmd45h+ZxcbK+ow+p5U8J2TDV3u7D5XbEW8H1vVOLxFbPAsgzUSgbb9tbgqfeOY+2CQrxUUY/lc3KhUbKYlGYAx0MIDAfPD+oM3/mtaVD2yikN9V7EYxHcUUmlYxjmbwA+BjCVYZh6hmFuYhjmSoZh6gGcD+CfDMP8u/fYCQzDvNV7aiaADxmG2Q/gMwD/5Hl+12i0mSDGK06PL0zXZ+38Ijg98qrK2tzSwV2bW975ETUXZRZGsrp9YRXat+yuhlXm9YnowHE8qhp7JO9lUE7J5eXwy38chN3lxzenZYSJ+D/w5mEsnpkTdj7P8ZLve9bEJJw7KTVMM/LBK8vAMpCt4xRpJZd0DROTFqtbOivCGrtK31aXL2ygufmdY7C6YuOnnF6/pN90emOjaRha+OT335uD7avPx8LpmWM+GBgNW5XyX4/9+yhaety46cICrJlfiJsvKsDfP6/D9RdMEq4Z3G3x5J7j2Lr7ODrsXrzwg3OwdkEhbrowoMVe2+5EU3dgMuPz85I2s//rbvzgTxXItOhQnp+MWbkWrFtQhDXzA+/T4/Lh7lfFgY6te6qxfE6ukK002OcZyB/Hm37fWMXmkR5rOSXs90hTDzw+HizDwOX1IydJJ2nnDBMMFB9EVpJeyAgLBpOONvUg06jB8rNy8MTVs0ZUf5og4oV2W4R5kS12dROGQsTxhS8xNJNjRTAYG0qkZJfhaGrLrfEgpckf1PsNSoGtnleA524ox/bV5+GzmlZcf0EBatsd4PiAbNTW3cdxx8sHcKzFjt/sOY7//WZhmG2E9u+n2u2oqO2QrEV0tNmKLburUZBuwD9vvQhlOWYsnpkTJpGxdU81spP0ks8QywKLSrIwf2qmUNdgwbRMYefa5neOYe3fvsTRJmvE+azbx+FQQ7fQ5qHci6Hc49FiVDKHeZ7/ToQ//UPi2NMALu/9fw2AWSPYNIIg+qFSstheUSdaodteUYcHryyTdb7VLV0h3eaSNwjIMGkkNRflVuW1Rbo+BYdHlZNtdlS3WCVXmUOrkbu8HHgAeSnijjuoG5WXosOa+YXYua9e2N6jUjKS75tiUAurtlNvvQhVTT041mzFY/8+KmQYyZlIxuNKLnHmZJoj+BRz7Cp92z3Sfqp/dejRoscp3Z6eGAWrg4VPxlu2aDRsNZL/yjRrseUfB0XZNNXNVmQn6SX9aZpRA4+PEyZ+QVpt7sDxPk7yOsHX79x5AG+tvQjNPS48suuocMya+YURA4NSk6Kh+GPKMh49nF6/rLGWVsVCp1Lg55dPBwvg9pf34+aLCgYcG7i8HOxuryjbLD9Vj9NdgeK1Eyw6nF+QKmRrEcRYxqSV1qI3xVAaayhEGl/EajE8URitHVSRajzMniiu8cCyDC6ZmoE/33QumnpcyDBp8Lv3jgvjg8ZuF7buPo7nbigHx/M4pyAdNz9fEbZDqLHbBY0y4P9PtNokbaO5x4VJqQacareD46V1fKdmmrB6XgEAID9FD5vbh8MRkpKcHp/ke1h0Kpxqt2NSqkEkK9j/ez9rYlLEejnZSVo899+T+J8paUOWvorGPY627FZieBWCIEYNjUKBa+bmhW0VlCsLYdGpJB2oWS/P3Zi0CknNRZNG7vWlB1HmIQyiSG92+NR22LGjol60pThoS8GCMkDANjrtbhSk98lBBHWj+hcG2F5Rh2vm5qHD5g4rHHDP4hlY+/cvceei6VhUkgWGAW5/ab/IDuXqOA2nuAMRf6QaFPjxN4tw7+uHQnxKKVINsdPrSzOoJf1UiiE2RfLSTWrpAGGMZCXiUYdtNIiGrerV0tJQagUr+j637qnGlmvOAssAj141EyzLoL7TAafHj1SDGnfsPCDoAL/wca0wAdxR8TU2XFGCpm7noAG+FqtL5E+zLVqUTDBHnGRJTYqG4o/Hq93EglSDtM9INfa9HpCOKg0Um+tyoDDDhAeWliLFqMKmZaVCBnlo4CD4PnqVMmCzPg5GtQLdTh8ef7tP7/GRq2biipkTAIDGa8SYJtmgwi3fKMTGN/rmRRuuKEFSDIvqDoU0YwRfEaPxRaIwWgVS9WqlZI0HvVo87vD5OLx+8LTIb2+4ogTtdo+oNsGXX3fhf6akSe4QCkoHFWYYkW3RIj/VIGkbKgWLXZVNONrUgzf2NwhzvmS9GivLczE5zYC6DjteqqjHa181wH6pH5vfOYq7Fk2XfL9Mi1aQnwidj97+0oGw5KHg956z+jzsPtICPwd0Ob247ZJiQQ4pOO9M1avBAPjeeXm4Y+d+LJ6ZAwULzM1PkbWAOdx7PBIL4rTkShCECI2KRU6SBtuuOxtbrp6NbdedjZwkDTQqee7CqFbi/iUlom0n9y8pgVEtLzjbYfdKai52OLyyzjdpA4OoZz6swZN7juPpD2pwyzcKYdbKG0QFHe3lWz/Ad/74KS7f+gF2VTbR1tQhYugdbFhdXqy5uBCPr5iJdQuKoFcpRFtFH10xEzq1Er989aAgZ7J8Tm6YxMTWPdX46cJpeOHjWqQYNVCywKMrZuH2hcV46to5eLeyCbXtTmE70kDZZoMhtXWKdA0Tlw67Xwi2AUGfcggd9thtaVQpA4U3Q/3Uj75ZCHWMMuH0agUeWFoqsvkHlpbCKHNRLto097iQrFfjxxcXYs38wE+yXi3r+U1komGrHr9fUhqqvsshOi5Zr0a7zY1b//Yl1v79K9z+0n5wHPDqVw2CNEBw++/K8lzhvVbPm4Kd++qgVSlwz+IZYdd55Yt64ffgRGfzqtkoz7fg/iUl8Pk53NvvvAevLMPys3IkJzRD8cfD8fvxQCJJYihZFnctmia6L3ctmgadUoG31l6Ev/3wXGy7rhxerx8cx8PPAz/66xf42csH8OO/fAmnx487vjUVv/3uWXjq2jnYXlEn7A56YGkpGnuccPk47NxXj26XXwiMAX1axifb7DReI8Y8bi8XZv8b36iEx8cNcmZ8wPEc7rtCPC+874oScHxitD+WDEcuQi6Rxgxev/j+VDZ2hwV8N75RidXzpojOe6miHl93OiT7YgULrJ1fhEd2VWH5nFw0djkkr93l9OCRXVVQKVisubgILAP84rJpWDO/ENv21uC27fvxmz3Hcd15+bhmbh7u3HkAHh+Ppm5nWAzigaWl0CoZXDAlFc/dMBd/+N4crJ5XICx6S0lVsSyDspwkTMsy45kPa2DSKvHXz2qx5uJCbF41C7+9dg627T2BW/7yBb7/3Ofw8wx+/I0peObDGmzdfRw/fLEC/zzUKKsvGs49HgkZRMocJghCBMfz4MGgorYTHA8o2oCCdAN4Xt5g2+bx4an3j4u2pzz1/nE8etVMWecPd3tzt9MrOYh65vvlss6nzKPokGnW4J7FM2B3eTEp1YDbewtRzMwx49EVs+Dy+JCXqsfh0z149N9H4fJyePGTwLamvBRpPcJjzVZ0Ojw40mTF1t3iFe41FxfivWNtktlqocfJyf4drdV6YnRoi6TXJ1PHfCSwu/3DKrwZbbx+HgzD4/EVs2D3+GBQK+Hy+eDxxybIkm3RShY7yzKP7ez9aNhqqkEjKQ21dLZYv31leS7ul9Dme2zFLDz+9hEsn5OLp947DpeXQ44lIO8zNdOEP+49gcvKsrFldyCLZ/W8AkzNMsGkUeGe1w4KAb5gADeoH+3xcbj171/C5eWQn6rDE6tmo7rFBh/HYU6eePtqKEPxx4m86yPRJDE67G4wgEj6gQHQ4XBjdl6ysD334xrg05MdQvFNIGBrv3qrCptXzUJ9hwMFGUY8sLQUJ1psyE8zYOMblahtdyI/VRcYR0SQC6vroPEaMfZpjaBF32ZNDM1hrUqFl/cdxaMrZsHp8UGnVuKFj2pw97dLYt00ApHHDItKxcVhg4HUUIKSUGvmF4LnIchGZJg0kn1xYYYJD71VhcZuF/JTdJiYosddrxzAmosLkW7UQK9RorHLgXSDBleX54l2iP722jn40V+/CBuz/N+q2UjWq3Hdefl45N9HhXFJQZoBBrUSm946jNp2p1Akr6lX/gLokzBkmIBkVujYInTscarDhpsvLECrzY1Uoxr/78V9YXGGx1fMClvALMuxjGhfNBIyiBQcJghCBMcBp7tcwkA+OCnPT5GXNdnl8ArC8aF0ysz8zTRLdygZRnmai06PtA6eU6aWJ+nNRoe8FANarC6caHXgWItV2FK8qFRcsfiBpaXC9x0siLRmfmHEbceblpXh128fFV3L5eWQZdYi26JFp8MjylY7Ux2n4Eou3fPEx6KX3mY/FKmZaNPpkA4CBrPqRxu724e7X60M+46elbmoFm38HCQL2CyckTXImYlNNGx1UqoBdy6aLvJ9D11ZBo2SFW33n5xmkLTB6hYrri7PA8v2Xb/V5sbTH9TgpgsLcKzFhpUaJdZcXIiiDCOKMk2CX33uhnMkA7i1HQ7c9coB4Xq17U7ctuMrrLm4EFt3H8cFU1IjBocB+f54tDQaR4JEW5g2alV4aNeXYbb6wg/OEX5nWQZuX6Boj5StHWmyQqdS4J5XK9Hp8OBXy8qEwHC2RYury/OwfsdXETWK9WoljdeIMY9erZC0f606MTaA97g8mD8tSzT2Xzu/CDa3vHkhMbLkJetx6/wikVzEpmWlyEvWi45LN0aYn5s0+Gk/Gb+WHic2LikRkiCC9zwYGNaqWNR2OPHU+8fx00unoqHLiQ0hsikPLddie0WdqD/8qr5L0t+7/ZwomSCofRzY6VSA2nancOzdrx7CYytmQatihYByMAD99Ac1YQuywbEHA+B4sx3b9tZg4xUlku2we3xhr410XzQSC+KJ4VUIghg1rG7pCtRWmQXdjBqlsJ0jiFbFwqiRN7llIF01VW7iTLJeLXn9JL08bat4rByaiLAsA5ZhsPGNSqGYgJRcRH2nI+z7fmN/Q9h25XsWz4BRrcCkVF1YAE2rYlHX6cDK8lxRttqikiyh+ixVNR+/qBSspE9RxbCYUVrvIDsUrSpQBCwW2NyRikvFRnqjxSq9SNdqSwx5gDMlGrYa9H3/vPUiPHntWVg9rwCP/vsoHvn3ETyxajbWX1qMmy4sQIfNI2mDfg7YuqcaE3oL1a1bUASzVoknr52DyWl6PL5yFniex5PvHUdRpknYBjnQ1sjaDrvk/QxONqPVvyay3080SYx2m3Q2Y4fdLXotP8UARW+xwVCCtrZldzWWz8mFy8vhl68exOKZgQz30PHCzn31YVuPN6+aLSQT9H9fGq8RYwm9WinZLxhkyvXFGrVCIWSmrplfiJsuLMD2ijqoFLGr+0D0UdfpwG969YCD9+c3e6pR1ymWomJZYMNisWTDhsUlUCqYMOmniSlGvFRRh0dXzMLjK2fiyX7SQUEJqtp2Jxq6nGFxh5+/0tcXBAnOJUPRqlicaLVhYrJesj/qr+rg8nJo6JWyWFkePieNJMnA8RD0ivUR4hz9n8fR6ItGQgYxMbwKQRCjhitCBWqXzMxbBRsI7vbfDqyQObdtiFA1NS9Fj7NknG91e8KKlQ1lhTqRM4/ijR6XTzSxc/nCbUuqaN3qeVOw/bO6wBYdnx9N3S48uSdQEfcP150dZl/BQjYPXlmKbxRnhK34UgbR+Kbd5pH0KQVpsXumu51eST/V7YxNJo05UiFRXWwK3iSyPMBwiJatsiwjWZTzth1f4aYLC/DUe8eRbdGGFVgJ+lKXlwMDHjddGNDlu2PRVKzp3c4ZXKx78tqzZPeLhghF8gwaZdT710T1+4lm8xkm6famGcXtnZxmQGmOJWK/HdyWDPRpUgIAw/RlGzd2uwTZqZk5ZlG2Oo3XiLFOt8sDvUohknDRqxTodiWGrESmWSNZ6DzTHJvFcEJMc49Lcsdv/6xXi06NnV/UhcmDPLpiNmblJoukn0612VFR242K2i8B9Mk3TM0y4miTTZCfAAB7hB2//eMGb+xviFjI9O5vSxei678urFWxsLr8eOWLevxkQZHsnSehCQt/3HsCGxaXYOObfZnODywthV4j3p01Gn3RSMggUnCYIAgRWREmKJkWeZ24TqWAQS0exBjUCmiV8laI000ayaqpcjPqTBq1pHbSr1fOlnU+6c1Gj/zkQOZZcGL3i8vDO+9Ohwc9Ti9WzytAXrIerTY3epxeHGuxAQDsLh/+8mnfajPH8Xjh41qsnleAHIsOdZ1OvPhJLTodHuTTfSIkSDdK+5TUGGXpAoBFp5L0U4+tmBWT9hg1CslFvVgVpBuvi3TRtNVImajBQFxjtwt//awWL/7gHHxwvA1+rk8vUKtioWAYPPVeYGvmyba+zF+Xl8MDbx7GP2+9SJa/5Tgehgj2NSlVjxkTLOS3kXg2XzbBgvuXluLe1/om6vcvLcXMCRbRcSzLYMG0TBSmG3HWxCR8VNMeZmvBkhZaFYtpWWZRFlRogPiZD2vwVj+ZDRqvEWMds1aFZz86jMUzc8AwAdmlZz86iV/HaLwwVPJSDCjKNIrmhUWZRuTJlCskRha5C5OTUg34wYVTJPuo/ouyrVa3pP/edt3ZeObDGtG1gjtL+l+/PD9FFGxdf+lUuDxewY6CGsedDg/qOhxhCRfrLy2GRiEO2G5aVorf7KlGY7cLp7udshdkQxdDDzT0AJ/V4vEVs+DneaQZ1Tg7NxlqdaAY62j3RdFeEKfgMEEQIlw+P+5cNA2P7DoiONM7F02TXRVXp2Zh0avQFlJAx6JXQa+RlzqcaVRjwxUlQlE5rYrFhitKkGmSJwvBgQ8TsV87vwg85BdWStTMo3hDoWCEgAAANHY5wiaTm5aVocPmgp8DfvNeNa4uz8P2ijqsnV+EX71VhU6HBzddWIBnPqzB+kuLcardLuhJrV1QKAQv4nkSTcQWpYIJ0z7buKQEKkXsAggmjQI/uaQYJ9vs4HhAyQI/uaQYphgFY51ev2RmktMbG1mJ8bpIF01bjTThC36Fgb59OtJNGkxOM+Bkmx1XnZ0LBQNMSjOgzeYWMmI2v3NM9N5BiY8pGQP3kcEia4/sqsIPLpgcFhygwHAfiWbzarUCS0qzMTlVj6YeN7LMGpRlW6BWh/swlmUwuXc8ZdQohe25wUWCFz6uFcZ6z354Ak+smo3TXc6wXUVS/TyN14ixjkmrkNSENekSQ5aBZRnMn5qJgjRjQvi28YbchcmhFYfVSC4IA3zY65NSDVh/abGoX9i8ajYuKEgVBVvb7W6s/dsRkU5wcIzy5HvV8Ph4rJ5XgNIcCzJ6F9qNGiVevuV8WF0+ZJq1yEvWY05eMlqsLmSZtZiaZZa1INt/V/SxFhu+7pXduHPnAWHRciz0RRQcJghCRLpRAwUjrkCtYCA7c/dkmxOvftGAGy6cjC6HF0l6Ff704Ulcc04epmYlDf4GDAMFw+PxFbNg9/hgUCvh8HghpDsNgtyqq8TI09grEbJuQRHMOhUeePOwUEV2cpoB7TY33q5swOp5Reiwe3BRUSq++roLi2fmiLYc5aXosHpeATQKFr//bw2AQGBjwbQMXDAllQaaxIC02z34yye1oq1wT+89gdsuLY5Zm2weP9ptHlHhz9sXToUtOTbBWLVCgWc/OhmWmbT1GjliPiPDeAz6RNNWI034ZmSbRH5zX12HpC1OSdfjrbUXgQEkdd7lyB2EFln7/d4aLJ+TCwULLJiWgbKcJPLZ/Ugkm+c4HnuqW8PsayCN56YeF5777ymsubgQWRYtMs1agOfxy29Px6k2O/RqFt+cmolT7XY4vX6cW5CCf956EVptFFAixi91HS5wHCeal3Ech7oOF6YmyNQmkXzbeGMoQV+591EqW3xymgH3vFYJj4/HYytmobrFCj8HPPffk7isLBuPr5gFjYpFQZoRk9PCs5GBwFgkKDHEMIH3Lc9PForhZpm1ONxoxTV//CRivxT6nnkpBlmfuzGC5OVVZ+eOuSKoFBwmCEKEnwMe/NeRsGyj/ylMl3V+tkWHmnY7PjvZKcRza9rtyLLI081r7HbhiXePY/mcXMEBv/JFPZ642jBgNfMgUpXaKat0dOE4Hqfa7WAZBp0OD2xuf8QqsotKczAnLxksy6Cm1Yb/e7cayXq1cP8VDFCYbkS2RYd7XjsobEPdvGo2BRcIWeSnGHCsxYa1f/tSeE2rYmO6pVGtYPH420dFW/Uff/sotq8+Lybt8fj9+MEFk9Hu8AiZzD+4YDK8fnk7RojoEE1bHWjCl5diwKl2Oz492Q7VALZYkG4Ex/FnLHcgJW3B8YBL5k4kIn4JDfwDfcV8pvWTfQglw6RFp8ODx9/uy0TPT9XhpwunwePnoGBZ/OXTOnQ6PL0LGYHM8sEy1AliLGPRqXDr374Mm5e98INzYtgqYiwR7eA9yzL4ZlEG0o0aNHa7kG3RgeM51LY7AQAPvlUlygA+1mLD5lWzsWBaZsR5XeiCd+iu0fwQWYuaVtuQ+iW5nzvTrJWU/OL5+K4NcCZQcJggCBEDVYmXM0Cfmm7Ej79ZhHtfD9GhW1KKqekmWdfPNGuhVvZ1DAwDqJWMbMebaFszxxrBbcTrd3yFZL0a6xYUwRmhyGFRhglGjQKn2u2YlGrApFQDnrz2LFQ320RbjqZmmbFweqawMkz3lBgKk9MCdnWgvhscH1hwKMu1YHIMC9LZ3dLPhENm4c9ok27UwO3nRNmj6y8tlr1jhIgO0bZVqYlPqI92eTncvrA4oi0GF/qS9SpsX30+vH4/Ugwa2f43KG2RrFeLJoJPf1AzaJYpEd9E0rSOlEHFcTxOtttEW3PzU3W4ZV4h7nh5v+B3fnVlGTJMakww61DXEZCRyjRTn0+MX+xun7SPdvti1CKC6CM4Tmju6fPVAPB2VbNoUfnRq2YiP1WH2nanUItm9bwC5CbpkGXR4YKC1AF9vJz5/VD7JblI7cRaO78I2yvqxlwCGgWHCYIQEakCdbpRXnD2aKtVCAwDAad87+uHMDXLiFkTkwc9Py9Zj9sXTkV1i02YHN++cCrykvWyPwNtX4ododlEwW04v4xQRba6xSpkEW9eNRsLp2dCq1IIE0egb9U3VM+JIIaKx8eLAp+bV82OaXuMWqXkM2GQ0OscDfwcBL03IPDcbX7nGBZMy4xJe8YzI2GroZM3vVqJR3ZV9d1rHxexKEtoEDnYljl5KbKDdMEJ1ZGmHiEwDMjLMiXiG7lFjIKcardjzV+/RLJejZsuLIBJq8TsiRbc8NznIrv45T8O9tYZ2CfoEQcziWkxgRiPmHUqyWfNpFXFsFUEEb7YHBwnFGcYwzJ479h5AE9/vxw3P18Bl5dDp8MDrVKBJ96tRqfDE1ZsVAqWZYRAbHNPQHowNEA81H5JLqGB6cA4SgGvn8Oi0qwxt3Apr0IUQRDjhqDoemi16HULiqCQ6S0au11I1qvx44sLsWZ+4CdZr0ZTr37sYNR3OVDf6cS2vTV4cs9x/GFvDeo7najvcpzpRyJGkf6rto3dLvzqn1V48MqyMJt6qaIeAJCsV+NIUw/eO9aCHqcXyXpx8UGXlxMGAQQxVCJtfz7Vbo9Zm3iOx0PLy7B2QcBHrltQiIeWl4GXXzczqgy0Y4QYPUbCVoOTtxv/9Bk+PN6O3Ueacdei6ZiZYwYA7NxXj7XzxX3+5lWzoWAx7LYEJ1SzJyZFzOYhEpNg4L+/3UTKoAqODRq7XXjqveN4/qNTaLW6cdOFBcJYMduihcvLgWEC9rFldzWWz8mNC59NELHC6vKG+ei184tgc3tj3DL5cByPmlYbPj7RhppWGzguRoMdIqpEGrOcbLdL9vleH4fnbzwHd102FY+umAUfx+Oqs3ORrFfLGg8ExzOXb/0A3/njp7h86wfYVdkk2NNQ+6WhEEw8O39KGmZNTEb5pFQUpBvHVGAYoMxhgiD6EUl0/ay8JFmav7nJOlx/fn5YhdKcZJ2s6zf3uMMyR7fsrsacvGRZ1ydii9SqbafDgzl5SULVWQYMfrL9q14dKm1Y5dlgtlCwIJ1WxUIfo4xKIvEZqW1mw8Hl96PV6g6TcZiQFBvdspHKtiCGxkjY6ql2Ox7ZVYWry/NEfvaexTPQuuc4Grtd2F5Rh+2rz4PT6xe2an56sj0qbQlm+pB9jS2GKuHV38dcf34+rC4fnvmwzwcGt+kGF8mCgeLg/8dS0R+CkItGqZAstP3w8pmxbposImWX0k6AxCfSmEWrUkj2+Xq1EplmDXgeIjmhdQuKkGUeWpHb4LVCdyGRtOTwocxhgiBEhIquP7nnOJ567zg6HR7ZkzitMlwWYMvuamiV8oJ7dk8EbS0PaWslApFWbfNSDChIN+K8gjSkmzTodHgAAMvn5IZtN96yuxory3OF89fOL6LCWMQZEwxKhBLrwJTPz0vKOPj8scmmGclsC0I+I2GrzT0uLJ6ZE+ZnH3jzMJbPyYVWxeLORdNRlpOE8wrShAlWaFuyLVr8+OJCrF1QCJ1KOeSsL7KvsUkwkyrUbiLR3wYmJutx/5uHRTa5dU817llcgle+COwqChb8Cf6fFhOI8YjH58fV5Xl45sPAjspnPqzB1eV58PhiU6NgqMTj7i0iOkQasyTrVZK7kDPNGvg5SMYJ5EzzBlpADzKUfikS4znTfVQyhxmGeRbAYgAtPM+X9r62EsB9AKYDOIfn+YoI5y4CsAWAAsDTPM8/PBptJohYIiXuPlqrXlKi60OZxLXa3JKOu83uRiEGL0qXn6yXXG2cOATNYSJ2yFm1zUvWY9OyUtz96iFh+2goLi+HHIsOa+YXChkSi0qzRvujEGOE4fq0kcDt5STt3u2NzSIIZVvEByNhq5lmLRSstJ+dmWPGW2svkrzXwbb0zzretnfoxeTIvoj+NmB1SScCdDs8aOx2QatiseGKEvzt09q48NlEYhPLedVwmZCkx72vV4ZlDj99/dxYN00W8bh7i4gOkcYs0zLNaOpxYfW8AnA8wDJAXkpgHj+cwvejscttvGe6j5asxJ8APAnghZDXDgFYDuAPkU5iGEYB4CkAlwKoB/A5wzCv8zx/eOSaShCxJRpOyefjUNnY3bttX4eSbDOUSnkbBYY7iRuu41YoGFE16+Bqo1Ix9h1yIiM18I5UsbyysRtN3S48tmIWVApG0l4aup14ck9fsTqWAT4+0ZZwg3oiPjBoWDy+Yhbsbh8MWiUMmthunEozaSTtPs2oHuCskYUKecYH0bbVSakGzM1PkbS3JH1kewuOBXKTtFi17ZNhF5Mj+xo/cByPug47mnvcsHt8yE8xYHKaQWQDJ5qtEbcdBxeGf/+f43j0qllIN2lE/X4iB/qI0SfRgz0qBYNb5hWgsccNjgeULHDLvAKoEmReRLJVY5eBYgbfLMpAukGDuk4nGAb4w39O4FiLDX+8rly2PfT39XnJ+qgtoEfqRwaTrhjrjEpwmOf5vQzDTOr3WhUAMMyAju0cAMd5nq/pPfbvAJYCoOAwMWYZrlPy+Ti8ur8Bd796SHCcm5aVYtmsHNkB4iBnUhxpuJlPkTSPZ0+Up3lMjD5yB96hxyXr1VhZnovCDCM2LJ6Bjb3bS4Pnzsg24YIpqUg3anGy3YZFWz5IyEE9EXvqOuw4fNoatuCUn2KImU/xcxw2LinBhtcrhTZtXFICf6wq0hFxwUjYKssyOHdSCh66sgw//8dB0fv+ZPtX6HR4BvSpdR1OyvoiZMNxPPYcbUZ1s01kx/1tTKFgsP7SYkFeR6ticfvCqcJWc4YBPD4ePHiRnSV6oI8YfRI92NPp8ECnVgJwC6/p1Ep0OjyYFLNWySced28R0Sd0+MpxPN6uahbd87Xzi9D6SS3ufu0gHrlqJu7ceWBAe4jk6xdOzxRq2JzpLqSB+pHxnuke7wXpcgB8HfJ7PYBzY9QWghgVhuuUKhu7hcBw8Ny7Xz2EogwjZk1MHvT84Q68h5t5rO8d8Dz13nHhNSpIFt/IHXgHj0vWq0VF6PJTdXhi1WzYPT5MTNZj7qSUQBGjNCNqWm1Y89cvE3ZQT8SeeCxyyYCB2+sXbblze/1gQMGN8cxI2CrH8Xj3aAv+b/cx3HRhARQsMD3LjN+9f1wo+hnJp55qt6O6RTrDk7K+CClOtdtxoL5bKLYJSPfbjd0uPPffU0IiQEm2Ga1WFx5/W7ww0r9IUaIH+ojRJ+GDPXzgeQktYBtYNEwMuT2SFRq7RIoZzMg2hfnprXuqcdOFBXjqvePISdIOGuCN5Ovf6vX1w3l2B+pHxnume7wHh6W8RsS0GoZhVgNYDQB5eXkj1SaCGDYD2epwnVJjt/QgqKnbhVkTBz8/GgPv4Wwf9fj9+PmiaWh3eMDxgIIBUvRqKkgWA+T6VLkD7+Bx/YvQ1bY7cduOr3DHt6ZCm8Hi05PtwhafhB/UE6PCQLYaj0UubW4fHvzXiyyyygABAABJREFUkTA///T15TFrE23VHh1G21ZD+/TgoqtWxeKmCwtwoKFHuIaUT23ucWFHRT3Wzi8SfLZWxeLBK8tkZ32RXSUuZzKvau5xgeOlNa5brC5MSjXgVLsdTq8fq8pzsaOiHo3dLty+sBhPvnc8bGFk4YyssPenMQHRn5GcV8Uaq9snuWhYct3ZMW6ZfEhWKMBYi1VFihk8f+M5kn6aYQLPXopBM6g9RMPXRxp/DPTe50xKHdeZ7vEeHK4HEBrOygVwOtLBPM9vA7ANAMrLy2lvJhG3DGSrw91+k23RSQ6CsizyBkHRcMbD0TxON2rg9nOiFfL1lxYjzaiRdT4RPeT6VLkD70yzFvmpOuQl6yRtLNWowdW92pZaFYtHrpqJ2RMtCT2oJ0aHgWw1P8WA8nwLrr+gAE63D3qNEs9/VIO8lNgN9Jxev+Qz4PTGpvo4bdUePUbbViP16aGqbpF8aqZZi06HBy9+0if1xDLAnLwkWXZBdpXYDDYGkJp4Z5q1UPQGAPr32+lGbZg9rFtQhBc+rgUgHVDuX6Qo0QN9xMgwkvOqWOPyShew7f9aPEOLhAHGWqwq0vjC4fEJfjrbosXyOblQsEBxpglPXnuW6NmLZBvD9fUDjT8Geu/xnuke24osg/M5gCKGYSYzDKMGcA2A12PcJoIYUYJO6a21F+Hvq8/FW2svGtJEqiTbjE3LSqFVBR7voOZwSbZF1vlBhxnKUJxxUPP46m2f4JY/f4Grt32MV/c3wOeTN4jxcxA06IBAJ7P5nWOgxOH4JTjwDrU5qYF3XrIet84vwulup6SNnWi1ie77nTsPoLbdiSevPWvQ9yaISExM0mHV3Hzc8fJ+3PnKQfzs5f1YNTcfE5N0MWtTQapB8hmYHCO7jpT9EdT/JEaHkbDVSH16cEgxkE8N+vag1NPTH9RgWpZZdrCa7GrsEpx4X771A3znj5/i8q0fYFdlE/KS9SjLtWDdgqKwflvBIswetuyuxpPfOQtlORZZY0+54w2CCDLceVWsyYrgw7PMiZE0E8lXcFzCx0bHPZHGF3kpAT+dn6rDdefl45kPa7B193Hc/tJ+eHx9930g2xiurx9o/DHYewcz3c8rSENBujFhfEU0GJXMYYZh/gbgmwDSGIapB7ABQAeA3wBIB/BPhmG+4nn+WwzDTADwNM/zl/M872MYZg2AfwNQAHiW5/nK0WgzQcSS4Wy/USpZLJuVg6IMI5q6XciyaFGSbZGduTvcFfbKxm78pldXKJiZ9Js91bI1j1us0quQ/bNHiPhhsFXW4KrwqXY7vu5w4L0jLZLblB/791HR+7q8HCpqO7B0Vs6wiw8Q45eq5h489Z7YJz31XjWmZsrzSSPB5HQjfr1yNn76Up+f/fXK2THbcklbteODkbDVSH16sOjnQD51uBk0ZFdjl4H0IOdPzURhuhFz8pLh8PiQl2LA5DQDPj3ZLrKHYEZZq82NunY7brukGE+821eg7pGrZoaNPcd7VhdxZiSyrIHXz4UVb1x/aTG8/sQIrpJO+Ngl0vhiclrA5+ckaYUdoUD4vR/MNqR8PQDUtNoGzUIfbPxB/Yg0oxIc5nn+OxH+9A+JY08DuDzk97cAvDVCTSMi4PV6cfDgQdFrZWVlUKlUMWoRMRSUShazJibL0hjuD8syWDg9E9tXn9crCxEILst1mO12N64uzxMF/tbOL0KH3T34yaAtg4lKpIG31LaetfOLsOtQoxAAuagwDZlmDTodHtG5WhULPwe02lzC6i1BDJXh+qSRgGUZXFaahenZ8TEwJb8bH4yErQ4UTJNT5G44QRWyq7HLQBPvSakGcDzA8TzyUw2S24SzLVpRYVqtisXPF03DmosL4fJx4HkgJ0kbcdEiUQN9BDFUHF4fNApWVMBWo2Dh9MaubsJQoEXCsctgi3UOj7SEWvDeD9aP9JebACBbqmqw8Qf1I9LEu+YwESX6B3u9Xi8YhoFS2WcCocHfgwcP4kdPvQ5z9iQAQE/jKfz2x8CcOXNGtd3E6MNxPN6uaj5jjUCzVi0qNubyBiqU/vmmc2VdP9G1wQgxUqvCoRVrtSoWy8/KQV6KAY9cNRN37jwgCopsr6jDVXNyYvwpiETGEsEn/UWmTxop4mlgSn43PhgpW42VrZFdjV0iTbyzzOG6wsExZKg99C9M6/JyeGjXEdHYgPp+ggDMGhUe2hVewPbvPzwvhq2SDy0Sjm0GGl8Mdu+H2o9MzTTJzkKn8ceZQcHhcUL/YG/jwY+hNCYjffI0ANLBX3P2JKTkTY1Fc4kYMtztPx6fdOEEr0zRYNoyOLYYqBhSaEfNsgy+XZqNZL0aFbUd8HPA9oo63LloOnXkxLDocXklbbDH5Y1Ri+IP8rvxwVizVbKrsUukibefC9cVltomfKzZKmtsQBDjnQ6HR/JZ6b/bLl6hIN34ZbB7P9R+5LffnSM7C53GH2cGBYfHEaHB3p7GU1CZMyj4S4Qx3O0/WRbpVcBMs/wV4njKqCOGR6RV4amZJjx/4zmYOylF6KiVShYXFqYhN1mHFqsLV83JoY6cGDZ6tVLSBvVqGgKFQn439oxFWyW7GptEmnj31xUGxGPIoD0AkLT1iwrTsPws6vsJIkii9wsUpBu/DHbvh9qPGDTSz0KkLHQafwwdeRWqCIIYN0SqPCp3+w9VkiZCmZQakIsItYe184vw+NtHkG7ShA0Ox3OFWGJkyDRrsG5BkcgG1y0oQmaCVPomxg9kq0QiIdVfyx1DRhorzp2UQn0/QYQwFvoFGtuPXwa790PpRzJNGooxjDCJseREDJn+GsNVVVUAnxhVTYnYMtztP7RCTIRCchFErMlLMaAo0ygq5lKUaUReCtkfEV+QrRKJjtwxJI0VCUIe1C8Q441I/UheigF5KQbqN0YQCg6PUaQ0hpMKZsW2UURCEI0BO23jIEIhuQgilrAsg/lTM1GQZqTBJBHXkK0Sic5QxpA0ViSIwaF+gRhvDNaPUL8xclBweAzTX2N4IDi/L5Bd3AtlGo9vaMBORBuyKSKWkP0RiQLZKpHokA0TRHShZ4oYb5DNxwYKDhMAAFtLPR5/y4X0qkBF7P6Zxv2DxwBQVlYGlUo1qu0kCIIgCIIgCIIgCIIgCCI6UHCYEDBm5EXMNO4fPO5pPIXf/hiYM2fOaDeTIAiCIAiCIAiCIAiCIIgoQMFhQjahwWOCIAiCIAiCIAiCIAiCIBIbCg4TUcPr9eLgwYOi10h6giAIgiAIgiAIgiAIgiDiEwoOjxH6B2ZjUVDu4MGD+NFTr8OcPQkASU+MZziOx6l2O5p7XMg0U1VdYviQTRFjDbJpIpaQ/RGxhOyPIORDzwuRaJDNJiYUHB4j9A/M9i8oF22kCtRVVVXBnJVP0hNRIJEdKsfx2FXZhPU7voLLy0GrYrF51WwsKslKmM9AyGc0bJVsihgu8eZTyaaJSJBPJRKFM7VVsj+CkA/H8dhztBkH6rvB8YCCAcpyLZg/NZOeFyIuGW0fH29j/ESGgsNjCHP2pIgF5aJN/wJ1wMgHpMcLiT5oPtVuF9oOAC4vh/U7vsK0tRehIN0Y49YR0WS0bJVsihgO8ehTyaYJKcinEonCcGyV7I8g5FPXYUd1sw3b9tYIz9q6BUUoTDdiUho9L0T8MZo+Ph7H+IkMBYeJM6Z/gbqRDkiPF+Jh0DycFbjmHpfQ9iAuL4cWq4sG/WOMaNnqYPZGNkUMh1Ptdjyyqwo3XVgAptesHtlVhWlZppjZD9k0IcVo2SrZHzFchtP/t9vdIhvfua8ejd0usj+CkKC5x42/f14nemb+/nkd5uQlU3CYGFXkxgdGc4wRD3GTsQQFhwkizoj1pG24K3CZZi20Klb0GbQqFhkm7Ug2m4gB0bBVOfZGNkUMh3a7G1eX52HrnmrBxtbOL0KH3R2zgSPZNCHFaNkq2R8xXM60/+c4Hqe7XHjmwxqRjW+vqCP7IwgJPH6/ZL/g9ftj3TRiHDGU+MBojjFiHTcZa7CjcRGGYZ5lGKaFYZhDIa+lMAzzDsMw1b3/Jkc49xTDMAcZhvmKYZiK0WgvER2CusRffPGF8OP1egc/cZwTdKihjOakLdIK3Kl2u6zzJ6UasHnVbOEzBDuPSamGEWszERuiYaty7I1sihgOagUrTKqAgI1t3VMNlWJUhkCSkE0TUoyWrZL9EcPlTPv/U+123LnzQJiNP7C0jOyPICQwa1SS/YJJo4pxy4jxxFDiA6M5xoh13GSsMVqZw38C8CSAF0JeuwvAbp7nH2YY5q7e3++McP7FPM+3jWwTiWjTX5e4q+EE1l1ShenTpwvHlJWVQaWizi2UoEPtvzI3FIcaS1kIlmWwqCQL09ZehBarCxkmEoYfq0jZ6pPXngWeBz4+0SbL9uTYG9kUMRwcHr+kjTk8scu6YVkGC6dnYvvq89DY7UK2RYeSbDPZ9DhntGx1IJ9KhV0IOQx1rBq0q2PNVkkbVykYsjNixEhkv+bwRugXvJQ5TIweQ4kPjOa8rX9flJ+qwwNLy9Dc4xL+nijPejwwKsFhnuf3Mgwzqd/LSwF8s/f/zwN4H5GDw0SCEqpL3NN4Co+/dVAIFvc0nsJvfwzMmTMnlk2MO4brUONJFoLnh3wKkUD0t9UssxaHG6349m8+CLM9AJIDc7n2xrIMCtKNtEWIGDKRbCzTHLusAo7j8XZVMxXQIESMpq1K+VQq7ELIZShj1VC7uvmiAkkbZxkGNa02msgTUSfR/Vo8jmGI8ceZxgdGOhYQ2hd12N1o6HJh9YsVCfmsxwOx21MJZPI83wgAvf9mRDiOB/A2wzD7GIZZPdAbMgyzmmGYCoZhKlpbW6Pc3PjB6/WKpBq++OILVFVVJUQkLhgsTsmbCnP2pFg3J2YMZqvBSdt5BWkoSDcOyaHFWhYiOAi7fOsH+M4fP8XlWz/ArsomcFz82ychRo5PDbVVjoek7Z1ss0e0CdreTESDgWw1L1mPTctKRTa2aVkp8pL1sWgqgOH7aSJxiWdbJbskQonWWDXUrnbuq8fa+UUiG1+3oAg/2f4VjReJM2YgW010vxbrfoGIHokcqxrKfG20YwHBvijFoAmTLUqkZz0eSISCdP/D8/xphmEyALzDMMwRnuf3Sh3I8/w2ANsAoLy8fMyOLA4ePIgfPfW6KLjaePBjJBXMil2jooDX68XBgwdFr41V2YmRtNVYy0JQ1dCxw1DtNJLt1XUMbBMkGUEMl4Fsta7Tgd/sqRYqffM88Js91ZiTlxwzn0QFNMYv8WyrZJdEKNEaq4baVWO3Cy9+UoubLixAyQQTjjRZ8cLHtWjsDmwBpvEicSYMZKuJ7tdi3S8Q0SORY1VDiQ/EKhaQ6M96PBDL4HAzwzDZPM83MgyTDaBF6iCe50/3/tvCMMw/AJwDQDI4PFboHyT1er1gGAZKZeB2VVVVwZyVL8g1AAGJhkSnf9CbZCfOjGjIQgxnCz855vFLJNvTq5UD2gRJRhAjSXOPC7XtTjz13nHR67H0SaNZyZlIHGJtq2SXxEjQ364au1145sMaPH/jOdi6+0vRsTReJKJNovu1WPcLBBFE7nwtVrGARH/W44FYykq8DuD7vf//PoDX+h/AMIyBYRhT8P8AFgI4NGotjBHBIOldrxzAXa8cwM0PPov/t+UV4feHd+yF0+GMdTOHDef3oaqqSiSNEQx6j3fZieEQ6236VDV0/BLJ9jLNGrIJImbEo0+KtZ8m4pNY2yrZJTES0NiAiCWJ7tdi3S8QxFCJlc0m+rMeD4xK5jDDMH9DoPhcGsMw9QA2AHgYwA6GYW4CUAdgZe+xEwA8zfP85QAyAfyDYZhgW//K8/yu0WjzaNI/U7h/ZnBP4ymozBmi38cCtpZ6PP6WSyhQNxakMeKB0awQKsVQK1gTY4dItgeAbIKIGfHok2Ltp4n4JNa2SnZJjAQ0NiBiSaL7tVj3CwQxVGJls4n+rMcDoxIc5nn+OxH+tEDi2NMALu/9fw2AMR8t7C+nMJ6CpMECdcDgQW8pTWJg7OoSD4dYbtMnxzy+iWR7ZBNErIhXn0RyKkR/4sFWyS6JkYDGBkQsSWS/Fg/9AkEMhVjabCI/6/FAIhSkGxeYsyeNuczg4RKUnQhSVVWF3+w+BvOEycJrpEscn5BjJvpDNkHEErI/IlEgWyXGE2TvBDE49JwQiQbZbGJCweERYLCCclIF5sAnVMHKUSGS7ERoIb7+AeT+3y1AmcUEQRAEQRAEQRAEQRAEIcW4DA5/8cUXI/r+VVVVePCv70KfmgUAaK+phEJnQlJ2XsTfLfkzgIC2MuxtjVC6XOgw6GX9fibnRPv3EbuGMVn03dpa6kTXbD78Oe6rsCEp+5Dkd+tob8Ivrr0E06dPl3fzZEBZygRBEARBEARBEARBEMRYgOHHaMYqwzCtAGpj2IQ0AG0xvP5woLYPjzae5xfJPXiEbTXW3wddP36vH092GitifX9GirH2uaJpq/H43cRbm6g9AzNafjXePvdwoM8Sf5CtBkjktgOJ3X65bSdb7YPaH1sGa79sW43TeVWi35/+jLXPA0TnM0W00zEbHI41DMNU8DxfHut2nAnU9rFDrL8Puv74vn68M1a/n7H6uaJBPH438dYmas/AjFZ74u1zDwf6LGObRP5OErntQGK3PxZtT+TvC6D2x5pEb/9gjLXPN9Y+DzDyn4kdqTcmCIIgCIIgCIIgCIIgCIIg4hcKDhMEQRAEQRAEQRAEQRAEQYxDKDg8cmyLdQOGAbV97BDr74OuP76vH++M1e9nrH6uaBCP3028tYnaMzCj1Z54+9zDgT7L2CaRv5NEbjuQ2O2PRdsT+fsCqP2xJtHbPxhj7fONtc8DjPBnIs1hgiAIgiAIgiAIgiAIgiCIcQhlDhMEQRAEQRAEQRAEQRAEQYxDKDhMEARBEARBEARBEARBEAQxDqHgMEEQBEEQBEEQBEEQBEEQxDhkzAaHFy1axAOgH/qJxc+QIFulnxj9DAmyU/qJ4c+QIFulnxj+DAmyVfqJ4c+QIFulnxj+DAmyVfqJ4Y9syE7pJ4Y/ERmzweG2trZYN4EgZEG2SiQCZKdEokC2SiQKZKtEokC2SiQKZKtEIkB2SsQjYzY4TBAEQRAEQRAEQRAEQRAEQUSGgsMEQRAEQRAEQRAEQRAEQRDjEGWsGxAKwzDPAlgMoIXn+dLe11IAbAcwCcApAKt4nu+MVRvHKhzH41S7Hc09LmSatZiUagDLMoP+bSSur1crwfEcWIaBw+MXXdPn41DZ2I3mHhdSDRpw4JGi14BlgPouBzQKBXhwULAKtFhdSDNqkGnWYGLy4J9nsM8ZvHZjtwvZFh1Kss1QKml9hSDiDbnPckuPG0l6FaxuL1INWuGZ5jgeJ9vsqO2ww6hRQq1g0WJ1IdOsEx0Teo28ZD3qOh2iawKIiu+Mpu+R0245/jBajNZ1iMGJtz6uy+nCsSY7mnvcyDRrUJxlQJJOG7P2EKNLqG/Itmjh59Drhwf2E8Hzup0esAyDHpcPdrcPGSYNvJwfHMfA5vIhP1UPj59DfacT6UYNWBaw6NSjPv4dieuMFb/af27g8fuRbtSIbCFSHwYEfNrhxm6c7nbBrFMi26xDfm/fHOzjk3Qq8ABarW5Jvyf1HhMHuKbUZ6jrCPgxu8eH/BQDJqcl5v0YCcaKrRIDk+j9ucPpwaEmq9D+0iwT9Dp1rJslG/JDiUHoffL4/TBrVHB4/ZLzytA+sd3ugc3lhU6lRKvNjXRTePxLLnEVHAbwJwBPAngh5LW7AOzmef5hhmHu6v39zhi0bczCcTx2VTZh/Y6v4PJy0KpYbF41G4tKsgAg4t+i5VCkrr9hcQl+v/c4atudwjUvmZqB1w+ext2vHhKOWzu/CNsr6nDT/0yG08vhncONuGpOHja+Wdn3XleUYEKSHRcVZkT8PAunZ+LtquaIn9Pn4/Dq/gbRtTctK8WyWTkUICaIOGIgfxbpWQ74kcO4dX4RlpRNwLtHW0Tnr1tQhBc+rkWnw4NNy0olj9m0rBS/2VMt8llqJYM1f/1yWL4zmr6n/3eTn6rDrfOLRO8txx9Gi8HuFTF6xFsf1+V04e1Drbj39b723L+kFAtL0xNqQkmcGaG+IVmvxvXn52PL7upB/UTwvGc/PIHvnTcJjd0u0XkPLC3Fk+/1+en1lxbjuf+eQqfDgw2LS7Dzizr84MIpozb+7f9Zo3GdseJXpT7HbZcUQ6di8eC/jgzY9y4qyQLH8WE+bd2CIsyYYILNxeGnL0nbVqjfk/KLv7hsGvQaZVi/Gcke9xxtRnWzTZb9jjfGiq0SA5Po/bnD6cGbh5rD2r+4NDMhAsTkhxKD0Pv098/rcHV5Hrbu6btfT157Fjw+XuQvb184FWlGNf78yane+NcXITZagoYUB86bnD6kexxXUS2e5/cC6Oj38lIAz/f+/3kAy0azTeOBU+12wdAAwOXlsH7HVzjVbh/wbyN5/Y1vVmLxzBzRNQ+c7hYGY8HXt+6pxuKZOWize/DEu8dw/QUFQmBYeK83KmF1+gf8PJWN3QN+zsrG8Gvf/eohVDZ2R+17IAhi+Azms6Se5aAfufvVQzhwOtwXbNldjeVzcoXnXuqYu189FO6z6ruH7Tuj6Xv6fzfBzzxUfxgtRqN/IeQRb33csSa7MBELtufe1w/hWBPZxngg1Dcsn5MrTGiBgf1E8LzrLyhATZs97Lx7XhP76c3vHBN8+8Y3K3H9BQWjOv7t/1mjcZ2x4lelPscT7x5Dm90zaN97qt0u6dO27K6G1enHT1+KbFuhfk/qPdrsHsl+M5I9Hqjvlm2/442xYqvEwCR6f36oySrZ/kNN1hi3TB7khxKD0Pu0eGaOEBgGAvfrQH343Ozxt4+ips0uGf+69/VK+PwY8j2Oq+BwBDJ5nm8EgN5/MyIdyDDMaoZhKhiGqWhtbR21BiY6zT0uwZiCuLwcWqyuAf820tdnGPHvTQMcx/GB/zvdPslj7B7fgJ+nsXvgzxnp703dZ/Y9kK0SiUAi2ulgPivSs8wwg/uZ4P8HOyb4O8cj7Jih+s5o+p7+303wM/d/78H8YbSIZv+SiLYaT0S7jxsuzT1uyfY097hj0p5oQrY6OKG+IZKfkvITwfOcbp8wLux/Xn8/HerbnR7fqI5/Q9screuMFb8a6XNI9av972mL1RXRp9lD5gmRbCvo96TeI5JdRbLHoRw/3hgrtkoMTKL359FsfyzslPxQYhB6n6T6pkj3kOMRMf7V6fAO+R4nQnBYNjzPb+N5vpzn+fL09PRYNydhyDRroVWJTUGrYpFh0g74t5G+Ps+Lf88a4DgFE/i/XqOUPMagVg74ebItugE/Z6S/Z1nO7HsgWyUSgUS008F8VqRnmecH9zPB/2fL9Fn9d/Gcie+Mpu+J9N30/z3bMvJ+f6D2nMl1EtFW44lo93HDJdOskWxPplkTk/ZEE7LVwenvG+T6ieB5eo1SGBf2P6+/nw717Tq1clTHv6FtjtZ1xopfjfQ5pPrV/vc0w6SN6NMMWuWgthX0e1LvEcmuItnjUI4fb4wVWyUGJtH782i2PxZ2Sn4oMeh/n+T2PSyDiPGvZL1qyPc4EYLDzQzDZANA778tMW7PmGNSqgGbV80WGePmVbMxKdUw4N9G8vobFpfgzQMNomvOnGDBpmWlouPWzi/CmwcakGpQ47ZLivH8RzXYsLhE/F5XlMCkUwz4eUqyzQN+zpJsc9i1Ny0rRUm2JWrfA0EQw2cwnyX1LAf9yKZlpZg5wRJ2/roFRXjli3rhuS+TOGbTstJwn5VrGbbvjKbv6f/dvLG/Iey9A/4w/PNF2+9LtWekrkMMTrz1ccVZBty/RNye+5eUojiLbGM8EOobdu6rx7oFRbL8RPC85z+qweQ0Q9h5DywV++n1lxYLvn3D4hK88FHNqI5/+3/WaFxnrPhVqc9x2yXFSDOoB+17J6UaJH3augVFMGkV+PXKyLYV6vek3iPVoJbsNyPZY1muRbb9jjfGiq0SA5Po/Xlplkmy/aVZphi3TB7khxKD0Pv0xv4GrJ0vvl9lueFzs9sXTkVBmkEy/nX/khIoFRjyPWZ4nh/8qFGEYZhJAN7keb609/fHALSHFKRL4Xn+jsHep7y8nK+oqBjZxo4hgtViW6wuZJjE1WIH+lu0rx+ovqgAz/NgGAYOj19UvTZYTb25x40Ugxo8eKToNWAZoKHLAbVCAR4cFKwCLVYX0gwaZFrE1RojfZ7BPmfw2k3dLmRZtCjJtkQq1DOkL4dslYgRY9ZO5T7LLT1uJOlVsLq9SDVohGea43icbLOjrsMOg0YJtYJFizVQoTj0mNBrBCumh14TQFR85xB8z5C/G6l2y/GH0ULmdcasrcYT0bSzaJCg1c3JVqNEqG/IMmvh54BW2+D+KHhej9MDhmHQ4/LB7vYh3aiBj/eD4xjYXD7kp+rh8XOo73QizaiBkgXMOvWoj39H4jpjxa/2nxt4/RzSjBqRLUTqw4CATzvc2I3GbjeMWgUmWHTI7+2bg318kk4FDkCr1Y1sCb8n9R4TB7im1GcIVp93eHzISzFgctrI2FEiMlZslRiYBO3PBRxODw41WYX2l2aZIhWjk22ro2mn5IcSg9D75PX7YdKo4PD2xcIASPaJ7XYPbC4vdColWm1upJs0yDSL41/9iHjj4yo4zDDM3wB8E0AagGYAGwC8CmAHgDwAdQBW8jzfv2hdGNQxEDGEBjFEIkB2SiQKZKtEokC2SiQKZKtEokC2SiQKcRkcJoh+RLRT5Wi2YjB4nv9OhD8tGNWGEARBEARBEARBEARBEARBjHESQXOYIAiCIAiCIAiCIAiCIAiCiDIUHCYIgiAIgiAIgiAIgiAIghiHUHCYIAiCIAiCIAiCIAiCIAhiHELBYYIgCIIgCIIgCIIgCIIgiHEIBYcJgiAIgiAIgiAIgiAIgiDGIRQcJgiCIAiCIAiCIAiCIAiCGIdQcJggCIIgCIIgCIIgCIIgCGIcQsFhgiAIgiAIgiAIgiAIgiCIcYgy1g0gxh4cx+NUux3NPS5kmrWYlGoAx/GobOxGY7cL6UYNVEoGPA84PH5kmrXIMqpR2WRFq82NdKMGfp5Hp92LdJMaLp8PFq0a4AGrx48OuweZJg2cXh90KiVcPh+S9RroVQq02jywe3zITzEgP0WP2g4HajvsMKiVyDRrkJdiAAChfXq1Eh6/P3BNDmix9rWZZZkYf5MEQQxEqK/Rq5VgGB5eHy88xw6vH3a3D0aNEjqVAgoGcPk4+DkeNrcPZp0amSYNWBZos3rg8XOwunzQqxVI0qtg1inR2OUW+ZS6Tgfa7W6wYNBu98CkVUCrVKDd7kGyXg2VgoHbz0GtYAX/FupPpPwj+RoiHrA5XTjcZEdzjxuZZg1mZBlg1Glj1p4upwvHQtpTnGVAUgzbQ8gn1M9lW7Rh4ysAqOuwo8XqRrfTixS9GloVC6vbD6vLC4tOhQyTBrlJAZ8b9PEcz0GrYmFz++H0+OHycsgwqeHycfD5eTi9fpi1Stg9PqgVCmhVCqTqVXD5/OhyeuHjAKfHjzSTGnaXD2qlAgaNAl4/B5ZhJH32UD/bQP6c/P+ZwXE8TrbZUdtuh1bNQqtUQK1kYXX5kG3RwuvnUddhh1GjQo/Li3SjOjDH8Prh8fuhVSphdfmQYlDB5vbCrFVDwQIuL48WqxvZFi0yLWqc7nSjp9f+Ms0a+Pw0LxgrJPqz5/Nxwjw626JDSbYZSmXi5Pglen/udHpxsKlHaH9Zlhk6nSrWzSLimGj6HJ+PQ+XpbjR0O5Fm1MCoUaDL4YFKoYDN44VepUK73Y00owZ2jw96tRImjQJGrRK5SUO7LgWHiajCcTx2VTZh/Y6v4PIGBvG/XjkbHM/hZy8fEF7buKQEv33/OGrbnSjPt2DV3Hzc+9oh4e/rFhThhY9r0enw4P4lJehUe2Fzc9j4RqVwzIYrSrBzXzWuOjsPnXYPGrrc2LK7Gi4vh/xUHdZcXIR7+r3njAkm2N2cqH23XVIMnYrFg/86Iry2edVsLCrJSqiBA0GMJ/r7mvJ8C1aW52HD65VI1qtx/fn5gj/Qqlj87FtTkW3Ror7Tic3vHBP5hQlJWlhdPmz6Z5Xw+vpLi5Fp1uDOnQeF1zYtK8XfP6vF/GlZ2LqnWvQe/zrYiMvKsvH3z+twdXme6O9BfwIgzD+SryHiAZvThbcOteLe1/v6zPuXlOLy0vSYBIi7nC68LdGehaXpCTWhHI+E+mYpX7x51WwYNCyONtmw+Z1jSNar8b/fKIDd4w/z2RkmjWjsuHnVLLh9HJq6XdiyuzriuWvnF2F7RR2umZsHk1aJFIMate0O0TG3XVKMv35Wi5v+ZzLUSgXuCxlfRvLLcj5bJH8uNT4m/z84Ut/bugVFMKgVeHlfPZaelYPH/n1UdF877W50OX34y6e1Yf3x7QunYmKyH11OPza8XhniX0rwblUj3j7chvxUHW75RqFozkH3KnFJ9GfP5+Pw6v4G3P3qIdF4dNmsnIQIECd6f+50evHGoaaw9l9RmkUBYkKSaPocqef/oeVl8Pl5PPledVgft2FxCXZ+UY2V5XnIMKlR3+nAeZPTZV83/j0KkVCcarcLDwIAuLwcfvrSV6husYle2/B6JRbPzAEAXH9BgRAYDv59y+5qLJ+TC5eXw72vV8KiUwuDtOAxG9+oxPUXFGDjG5VI0muEAToALJ6ZIwSGQ9/T6vSHte+Jd4+hze4RvbZ+x1c41W4fpW+NIIih0t/XXH9BgTDRWz4nV+QPXF4Oj/37KDgOQmA4+PqW3dU40RrIYAt9ffM7x3Ci1S567e5XD+H6CwqETjj0PW6eNwVbdldj8cycsL8H/YmUfyRfQ8QDh5vswsQHQG/fewiHm2Jjm8citOdYjNpDyCfUz0n54vU7voLV6Rd88fI5uWizeyR9dv+xI8cBJ9vswrGRzt26J+CLt+yuRovVDY5D2DFPvHsMi2fmoM3uEQLDoW2U8styPlskf07+/8yQ+t627K5Gm92Dm+dNEQLDwb898e4x6NUqbH7nmGR//PjbR2HWaYTxQvD1e1+vxHfPmwwgMIfoP+ege5W4JPqzV9nYLQSGgL7xaGVjd4xbJo9E788PNvVItv9gU0+MW0bEK9H0OVLP/8k2O+557ZBkH7fxzUphTqxgWfj8GNJ1KThMRJXmHpdgoEFcXg4cj7DXmN4FDKfbJ3lO8O8uL4cOu1fyGKcncG5nv78zDCSPt0e4llT7WqwuOR+ZIIgY0N/XhPqRiM+/J/LzL+UDpF6L5K+CvijStVusroj+kXwNEWuae9ySttnc46b2EEMi1M/J8cUME/C/csZmdrdPdOxA5wavzfGI6PsHOl/KL8v5bJH8Ofn/M2OgeUWk/tg+SH/capP2L10OL4Ch31sivkn0Z6+xW7r9Td2J0f5E788Tvf3E6BNNnyP1/AfHLZH6KiE+5vCi0+Ed0nUpOExElUyzFlqV2Ky0Khb9M9m1KhZ876Bfr1FKnhP8u1bFIsWgkjxGpw6cmxzh7/1/N2ilryXVvgxT/G91IYjxSn9f09+PSD7/6sjPv5QPkHotkr/Sh7y31N8zTNqI/pF8DRFrMs0aSdvMNGuoPcSQ6O/n5PhiBSN9XH8fbNAqw46NdC7P971HJN/P85HPl/LLcj5bJH9O/v/MGGheEak/NgzSH6cbpf1Lkl4l+r3/3+leJSaJ/uxlW3SS7c+yJEb7E70/T/T2E6NPNH2O1PMfOm4ZMD6mVyFZrxrSdSk4TESVSakGbF41W2Swv145G0UZRtFrG5eU4M0DDQCA5z+qwf1LS0V/X7egCK98US/ogHU7PdhwRYnomA1XlOCFj2qw4YoSdDncWLegSPj7G/sb8IDEe5q0irD23XZJMdIMatFrm1fNFoqmEAQRf/T3Nc9/VIONSwI+Yue+epE/COpXsiyw/tLiML8wJd2ADJNG9Pr6S4sxJd0gem3TslI8/1EN1s4vCnuPP+49gXULivDG/oawvwf9iZR/JF9DxAMzsgy4f4m4z7x/SSlmZMXGNosjtKc4Ru0h5BPq56R88eZVs2HSKQRfvHNfPVINakmf3X/syDLApDSDcGykc9fOL8KbBxqwbkERMnqLjvY/5rZLivHmgQakGtS4r9/4MpJflvPZIvlz8v9nhtT3tm5BEdIMavxx7wn87FtTw+6rw+PF+kuLJfvj2xdORY/TLYwXgq/fv6QEf/nkJIDAHKL/nIPuVeKS6M9eSbYZm5aJ+8NNy0pRkm2Jccvkkej9eVmWWbL9ZVnmGLeMiFei6XOknv9JaQY8sLRUso/bsDgQH9u4pAR+joNSgSFdl+F5fvCjEpDy8nK+oqIi1s0YlwSrM7ZYXcgwBaozchwvVFlNM2qgUTLgeAiVobOMalQ2WdFqcyPdqIGf59Hl8CLNoIbb74dJqwLDAzaPHx12DzJMGrh8PmiVSrh9PiTpNdCrFGi1eeDw+JCXYkB+ih61HQ7UddihVyuRadYgLyXwcASrR+rVgSrVaUYN/BzQautr8zCKFAzpRLJVIkYkvJ2GVoLVqxVgGcDj4wPVxU1aOH1+2N1+GDQK6JSKQHVyHwc/x8Pm9sOsUyGzN3DQZvXA4+dgdfmgVyuQpFPBrFeiscst8il1nQ60291gwaDd7oFRo4BOpUC73YNkvRoqBQO3n4NawQr+LdSfSPnHRCiIEmMS3lYTAZvThcMh1cRnZBliUowuSIJWNydbhdjPZZm1YeMrAKjrsKPV6kaX04sUfWCB3ub2o8flRZJOhXSTBrlJAZ8b9PE8z0PTe5zT44fLyyHDqIbbz8Hr5+H0+mHWKuHw+KFSsNCpFEjWq+D2+dHl9MLHAU6PH2lGNRweH1QKBQwaBXx+DgzDSPrsoX62gfx5nPn/hLFVjuNxss2Oug471EoWepUCKiULq8uHbIsWXj+Pug47jBoVelxepBvV4HnA4fXD6+egUSpgc/mQpFfB7vHBrFUFxgNeHq1WN7IsWmRa1Djd6RbsL8Osgc8ftXkBMTyGbatx9uwNGZ+PQ2VjN5q6XciyaFGSbUmIYnRBErQ/F3A6vTjY1CO0vyzLHKkYnWyjGqv9PxEgmj7H5+NQebobDd1OpBk1MGoU6HJ4oFIoYPd4oVOp0GF3I9WggcPrg06lhFGjgEmnRG6S5HUjNoSCwwQRfRJmwE2Ma8hOiUSBbJVIFMhWiUSBbJVIFMhWiUSBgsNEIhDRThNnyYkgCIIgCIIgCIIgCIIgCIKIGhQcJgiCIAiCIAiCIAiCIAiCGIdQcJggCIIgCIIgCIIgCIIgCGIcQsFhgiAIgiAIgiAIgiAIgiCIcQgFhwmCIAiCIAiCIAiCIAiCIMYhFBwmCIIgCIIgCIIgCIIgCIIYh1BwmCAIgiAIgiAIgiAIgiAIYhxCwWGCIAiCIAiCIAiCIAiCIIhxiDLWDZALwzC3AbgZAA/gIIAbeZ53xbZV8QvH8TjVbkdzjwuZZi0mpRrAssyAfweAug472mxudNq9MGqVcPl8MGtU8PM8uhxeGDRK6FQKdNg90KkVsGhVcHj9aO5xY0q6Hm4vB5fPD4Zh4PXzcHp8SNKroGRZtNrcsOhU0KkUaLe7oVMpYXX5kKRXguN4qJUK8ODRbvPAolOBAYMupxc6tQIGtQJOrw8sw8Lr90OrUqLN5kaaUQOnxweWYaBTK6BiWVj0KuSliD+vnO+EIIjY0/85nWDSorKpBx0OD5J0KnQ5vNBrFDBrlXB6OHQ4PMgwaeDjeLTZ3Eg1auD0eKFgFbDolPD6eLTZPUjWq+D0+GDQKNFp7/UrGgUcHj/sbj9MWgW0SgXa7B6YtEo4PD4Y1EooWBbdTg9MGhW6nF7o1QooWECnUgAAvu50IdOsgY/zw6BWwePj0NrrmxweL5L1WpRkm6FUssJna7e7oVGw6HZ6oVUp0OX0wqxVIdOsQW6SHnWdDvJTUSYe/X+8tanL6cKxJjuae9zINGtQnGVAkk5L7RllRtIuhvvewfO7nR74/Lzg62xuL3QqJZL0Svj8PDw+Dk4vB6fXD7NOhW6HF8l6FYwaBbpdPgCA18/D5fHDolfB5vZCybKw6FRweHzocviQadaAAdDY40KaUYMeV8BPqhUMupwemLVq2Nw+uLwcMs2a3v/7Ydaq0OnwwKJXw+v3QcUqoGAZWN1e6FUqdDjcSDVo0O30IkmvgoL5/+z9eZwcd30n/r8+dXX1rblnLKHLHtlmxrLjKISYcMSywWRlWXESQ5LFuVh+CSTWWoFsYI1lCYdslkSsnZDkC9klhsCCsxBbchYHYwNeMAkRYMsaG0u2rmikuWf67q6qrs/vj55u9TmHpnume+b1fDzmMdPVVZ/6VNW73p9jZroExmIZBDwavIYCQCBju+gNVz8/ritxeiKBc1MJBDwaXOSOw2toSGQcbGz3Y0vnpe2W6z5vtnxSrLhufWETTlbi3HQSYVOHrgmMRjLwGio8uoJoykbYq0NCYjph44p1XriuRMrOYjJhoSdoIitdTCdteHUVPkOFrghACMTSTqEtnkxY8Hs0eHQBQ1EwnbJgaio0RUHScuAzNEwnLQS9ub5BwKPDp6twpUTCyi547LSYc+w4LoYuRnAxkkZf2FvoGxDNp9Xbw1avfzyVxktF9X99rx+BBtV/oXmmWXP+XPUqf29jW+mYJ/86N0+kIpHJImE52FTWrq70cfkMDVY2iw6/B5s7/HBdWZHbAWDoYgSjs30YAIimbXg0FZaTRcCjI5axEPAYiGds+A0NiuJCUzQkrCymEhZ6Qx6EvSrGYzbiGQfrfAZUAdiuBCSgKIDlSMQzDq4Im0jYWUzGc+PisFfFlvYgDENd1HG2xOSwEGI9gHsAvF5KmRJCPArg3QD+bkUr1qRcV+LJoRHse/R5pG0Xpq7g0F034LaBXiiKqPm+36Pg1bEEPvHPrxSW33NzP7589Bze/VMb8bnvncV00sLenf2Fn/ffPoC/+far2Nrhxy/cuB4zSRsAkLCyeOjpk4Vyirf5yDuvQcp28clvnCi8/0e3XQNFAEGvjsM/GsYbtnaUbL/v1m3oCnjwP54+gXft2IiHnzlZtY69YRP2aBavjsdx89U9JclornNCRCuv2n16cPcgHj16Fjdf01u47zd1ePF7P9ePjz5+HG0+A3f/zKaSfFGcEzr8OqaTDj7+/bMluWNThxe/89arcODIUNU89eHbrkEm6+IL/3oWv/qGTSX5au/OfvhnG9u//vYpTCct/I93XY9zk2k8UFRerh4v4fdv7sfu667AN14Zw58++TJ+9Q2b8MXvV5a779Zt6Aub+ND/OcY8VUfNmP+brU4zqTS+fnwc9x8+XnLvvX2wa0UGcM1Wn+XSyLhYatn57f/Xd17DL964EQeeKM11z/x4BP/pzVuRdlxcmElXzckf+Ll+eHWB89OV7z/z4xH84k9urJmT82X82k9vwjpTw8sX43jo6ZOFNuBL/3auon/4wO0DkNLF3zx7quK9e2/ZBq+u4ONf+3FhWb5Pe3YyVfX8VDuH1fq0+e0ALMt93mz5pFbditvrNp+B33zTZhx6qrRt9ekqDj73Et7/tqvw4wszeONVXZhO2HjgyFDNbda3eRFN2fjM/ztVtb0OmhoMRWAm7eAL/3q25jji936uH3/5zZNVr/9Sz7HjuHjshWHc99ilnPbgnkHsuX49J4hpTq3eHrZ6/eOpNP5vlfr//GBX3SeIF5pnmjXnz1UvoLQ93NThxe/f3F+RE7/0/bO4fft6JO3SuaSVPL5qx5VvNw7eMYDxmFVyHJ/4pe2wshL/9R9frOgrfHF2PPrlo5V9lofedT2mkqmSftDB3YP41LcutUsHdg9AQMLKSsTSDh56+iS2dQfwKz+9qWy7AYxEMviZLZ2LmiBupdZIA+AVQmgAfAAurHB9mtaZyUQheAEgbbvY9+jzODOZmPP9WCpbmBjOL3/4mZPYtX09Hnr6JO68cQPStlvy84EjQ9i1fT1+42e34NXxBCYSFiYSVuFmzpdTvM1Ewip03PLv/7cnf4yJhIXTEwn8xs9uqdj+0FMncHoygV3b1xduomp1PD2RgM/Qcex8pHC8CzknRLTyqt2n9x8+jrtv2lpy3+/avh4ffTzXCN9544aKfFGcE3yGjk9+40RF7ti1fX2hEc1vV5ynJpMWDj2V2648Xz309MlCrsuv72RRmBgur8d9jx3HsQsR7Hv0+UJ51co99NQJnByLM0/VWTPm/2ar04mRRGHgk6/P/YeP48QI67OcGhkXSy07v/3dN20tTAzny3n4mZO4+6atsLPAa+OJmjn5/sePI+w1qr5/901b58zJ+TIOPXUCPo9eKCPfBlTrHz5wZAgXo5mq733yGycwkbBKluX7tLXOT7VzWK1Pm99uue7zZssnxYrrVtxe33njhsIkL3Dpek8mLezavh77Dw/hHdeth+3IQttaa5tXx+IYi2VqttdjsQx8Hr3QptcaR3z08eM1r/9Sz/HQxUhh8iC//X2PHcfQxUidzjStVq3eHrZ6/V+qUf+XGlD/heaZZs35c9Wr/L38+Kg8J95901ZMJivnklby+KodV77diKWyFcdxcixemBjOL8v3FfJtULW2yM6ioh90/+HSdmn/4SH4DB1jsUzhHL33LVdW2W4IQggcu7C4NqYlJoellMMA/gzAOQAXAUSklF8vX08I8T4hxFEhxNHx8fHlrmbTGI2mC8GRl7ZdjMXSc76fsJyqy4W49L14WfHP0wkbrkThq1Y5QO3389tOJ+ya7+frUquOrgQSlgNXonC8Czkny42xSq1gueO01n2aypTmpuI8MF9OSMxuW77eXNsBl/JUrfXy+Sq/fiIzd/4cmT224nxaq9zyZSuVp1rJXLHabPkfaL46jUYzVeszGs2wPnW2UrG61LLz25fn43w5KctBIuPM2QdM2y6mavTxUnP0QcvLKM63C8mpi8m3QpS+nq8vWet4x2LpZbvPG7WfevQBiuu2kLa7+HqNx9JVr3W1bea7zrX6Avl1ysc6+eXzjZ0Weo4vRqpvPxJh+14Pq3lc1ertIet/yXxxutA802x9yLy56lX+Xq1cnLJq9yNWro9c/biEqD7+q1b/8nFlteOfayxZ/DpRdo5q9cumkzZGo4s7Zy0xOSyEaANwB4AtAK4A4BdC/Mfy9aSUn5ZS7pBS7ujq6lruajaNnpAJUy+9tKauoDtozvm+39CqLpfy0vfiZcU/t/t1qAKFr1rlALXfVwSgCKDNr9d8P/9zrToqArnPbBEoHO9CzslyY6xSK1juOK11n/o81XNTtZ/zr/M5wW9e2nauMoq3A0rz1Fz5Kr9+8X6q1aO36NjmK7d82UrlqVYyV6w2W/4Hmq9OPSFP1fr0hDysT52tVKwutez89rXysc/Q4De1OfuApq6gvUYfzzdHH7S8jPJ8u5CcutB8K2Xp6/n6krWOtztoLtt93qj91KMPUF63+drufLuar3+ta12+zXzXeb6+QPlYJ798vrHTQs9xX9hbdfveMNv3eljN46pWbw9Z/0vmi9OF5plm60PmzVWvWu+Vv/YZtfsRK9dHrl53KauP/6rVv9q4snyducaSxa/9ZeeoVr+szaejJ7S4c9YSk8MAbgFwWko5LqW0AXwVwE0rXKemtbnDj0N33VASeIfuuqHw0Lla7we9Kj70jqtLlt9zcz+eODaMvTv78dUfnoepKyU/7799AE8cG8Znv3MaV3b50eE30OE3sHdnf0k5xdt0+A3ce8u2kvf/6LZr0Ok3sKXTj7/7zumK7ffdug1bOvw48sIw7rm5v2Ydt3T6kbRsbN8QLhzvQs4JEa28avfpwd2DeOS5UyX3/ZEXhvGxOwZh6gq+8oPzFfmiOCckMzbuvWVbRe448sIw9t8+UDNPtfsM7Ls1t115vtq7sx+dfgOdfqOwvqYAD5SVl6/Hg3sGsf2KMA7ddUOhvGrl7rt1G/q7A8xTddaM+b/Z6rSt14+Duwcr7r1tvazPcmpkXCy17Pz2jzx3Cvt3Vea6R547BV0Btnb5a+bkg3cMIpKyqr7/yHOn5szJ+TL23boNybRdKCPfBlTrHz5w+wD6Qp6q7917yzZ0+o2SZfk+ba3zU+0cVuvT5rdbrvu82fJJseK6FbfXX/nBeey7tbJt7fAZeOLYMA7sHsCTLw5DV0Whba21zVXdAXQHPTXb6+6gB8m0XWjTa40jPnbHYM3rv9RzPNAXwoN7SnPag3sGMdAXrtOZptWq1dvDVq//62vU//UNqP9C80yz5vy56lX+3pEXhqvmxEeeO4V2X+Vc0koeX7XjyrcbQVOtOI6rugP441+4rmpfId8GVWuLdAUV/aCDu0vbpQO7B5C0bHQFPYVz9JlnX6uy3QCklNh+xeLaGCGlnH+tFSaE+GkA/wvATwFIIfcguqNSyr+otc2OHTvk0aNHl6eCTSj/RMWxWBrdwdpP3C1+HwDOTSUwEc9gOmEjYGrIONnc05ilxEzSgd+jwqurmEpY8BoqwqaOpJ3FaDSDrZ0+WI6LtJOFEAJ2ViJlZbHOp0FTFEzELYS8WmF7U1cRTzsI+zS4roShqZCQmIzbCHs1CCEQSdowDRV+Q0XKdqAIBXY2C1PXMDH7lOyU5UAIMfvEYgVhn46N7dWfMD3XOamjRRW61mOVVkxTxmn5fXpF0MTQSBRTSQvrvDpmkjZ8HhVBU0PacjGdtNAV8MCREhPx3FPoU7YDVVEQMjU4WYnJRG7btDP7hPKEDa+hwu9RkbKyiGeyCMzmtsmEhYCpIWk5ud/MKgqiaQsBQ0ckldtOUQCfpgICOD+dRnfIU3hCuuW4GJ/NTUnLQZvPwEBfGJqmFI5tKpGBoSqFp9ZGUjaCpo6ekAcb1uWe1LsMeaqVLDlWlzH/L1iz1anZnibebPVZoKaO1aWWnd8+krLgZGUh18UzNry6hnVeDY4rYTkSKTuLlJVFyKsjkrbR5tUR8KiIpB0AgJ2VSFtZhH06EhkHqiIQ9upIWg5mUg66Ax4oArgYTaPT70E0YyPk0WFoAjMpCyHTQHz2Xyl7gh4kLAcpO4ugqWMmaSHsNeC4WWiKAlURs3XUMZ200O43EE3bCHt1qEJgPJaB36PBayiAFLCybs2nv7uuxOmJBM5NJXL9Y+SOw2toSGQcbCx7qvpy3eeXsZ9l6wMU1603ZMLJSvz7dBIhU4euCYxGMvAaKjy6glg6d52lkJhOOLhinQnXzcXTZMJCT9BEVrqYSTowdQVeQ4WhCEAIxNIOHNeF39AwmbDg92jwaAK6oiCStuHRFGiKgqQ12xdIWgiaOlK2g4Chw2eocKVEwspWvf5LvZaO42LoYgQjkTR6w2ahb0Dzasr+6nJq0fawoNXrH0+l8VJR/V/f66/1MLoFx2qtOF1onmm2PuRC6lX+3sa20jFP/vVUIgNTV5HIZJG0KtvVlTyu0WgaPkOFnXXR7vdgc4cfrisrcjuQ+6z50WgGHQEDAiiM+ywnC79HRzxjIzD73W9oUBQJTahI2llMJSx0Bz1Y51MxHrMRz2SxzqtDVQDHlZDI/ceM5UjEMw6uCJtI2FlMxS10BT0Ie1VsaQ/WehhdzRPZEpPDACCEOADgXQAcAD8C8F4pZc0Pe1mNDQO1jDXfiaGWwDilVsFYpVbBWKVWwVilVsFYpVax5MlhomVQM0615azFUkgp9wPYv9L1ICIiIiIiIiIiIloN+L8sRERERERERERERGsQJ4eJiIiIiIiIiIiI1iBODhMRERERERERERGtQZwcJiIiIiIiIiIiIlqDODlMREREREREREREtAZxcpiIiIiIiIiIiIhoDeLkMBEREREREREREdEaxMlhIiIiIiIiIiIiojVIW+kK0CWuK3FmMoHRaBo9IRObO/xQFHFZZUwmMjBUBUkri+6gB5GUjYl4BiGvjqybhd/QkbJdTCUs9IQ8MHUVM0kb8YyDdT4NqqIgmXEQ9OjIZLNwXCBlZdEZMJCVEqPRDLoCBgKmhkQmi8m4haCpIezVkHFcTMQtBL0avJqKi5E0+sImHNfFdMKG36NBUwVMTYGUwHg8A6+hwW+oiKVthEwdCSuLuOUg7NXRGzSxqcMPADg9kcDZqQT8hoaekAcb2xd/johoZRTnuO6gCVUBLkZy+W5jmw/nppMYiaThN1RASNhZCTvrIjubf0JeDUnbgVfXoAqBmZSNsFdHxnGgKSpiaQcdfh0AkHZcxDMO/IYGU7+Ua7oDHjjSxUzSQV8oV4eZlINY2kG7X4dHy/3ONJax4dE0TMQz6Ax4kLAcrDN1SACj0QzW+TQEPDom4hmYhgqfpiJuOcjYLjZ1+LGlM5ebquXk4uOtle/r0R7QJc14PmdSaZwYSWA0mkFPyINtvX6s85qsT5PWx3FcDF2MzPZpvBjoC0HT6v83Fo3qC3YGPEjbWURSNpJWFmFvbggQTTnoDnmQyNgQQoHlZLHOa2AsnoGpq2j36/BqKs5OJdHuN+BkJeIZG15dw3g8d210VcGFmTSCpgavoSBtZ2GoKqYSFnyGiqCpwXZdOK5E2srC1LXZfG0gkrZgqCpUBfBoKoKmgom4g8mEhd6QBxISk3EbfkMt9B+jKQcJy0HI1OAzNLiuxIVIGt1BD8I+FTPJbCFurmjzIGNJTMQzsByJlO2gK5g/Fw76wibsrIto2sGmdj82tftwZjKB05OJwvH7dA0jTZQ7msVCYjWVsvHiSLRwPV7f68epySQuRjLw6ioCHg2qkmtzdUXDZCKD3pCJtJ1FNO2g3W8gmrbR7jOQtrNIWlmEvDpmUjaCpoagR0PCcmDZEik7i3afjqmUjZCpQZ+tS2R2bBE0VdgOMJW0kLSy6Ap40Bk0sD5ces1DHg0uJMJeg9d7lViu/N0ozdYeLlar1z+RymBoJF6o/0BvAH6vZ0XqsphYrnfft9q+FUXg1HgcwzNJGJqKpOWgM2BCU4FE5lJb3LfOgy6viZMTccQzDqaTFroCHkTTNtp8BrKuxGgsg76wiev6wjAMtWJ/7QENU/FcH2YyYeGKsInBvjA0TZnzOF1X4txULv4SVq6t39Lph+tKvHQxgpFoBiGvBttxccU6H9aHTBwfiWIkksbWLh/iRcfh96i4MJ1Gd8iDlJ2bA9vQ5oWdlZhMWOgOGIhbWcTTDjoCBoKmii1tAbwyHsN0MgOfoWMqYaHDb8DnEUhkJKaTNtp8OhKWDb+hYzKeQXfQA1VRkMk6UKEgmrERNHWkbRcpy0F30APHnZ2TC3oghMR0wkZ30IOk5UBXVbz+MuKUk8NNwnUlnhwawb5Hn0fadmHqCg7ddQNuG+hd8E2cL+NPn3wZ79qxEQ8/cxJtPgN3/8wmPPT0yUK5/+3O63DeyWD/4SGkbRebOrz4nbdehQNHhgrrfOSd10AIASmTSFjZku333boNn/3uGUwnLRzcPYBPfetVnJ1MVS1n785+fO3Fi9h1/RU49NSJkuV+QwUA/PW3T2E6aWHfrduwoc2Lly7GKva3pdMPIYDf++KPSsro7wng5qt72HEjanLVctzenf343PfOwtAEfv/mftz32HG0+Qzce8tV0DUVsZRdkX/uvWUbvLqCj3/tx4Vl+3cN4G+evZSHfvetV+GBojy0//YB/M23c+8X56Vf+skNFeUf2D2AjoCBqbiF+w//sLD8gdsHMDydwoP/9HLV+pfnvkN33YC3X9uDr788WpKT8+8/uGcQf/HMyUKdivN9PdoDuqQZz+dMKo2vHx/H/YePF+p0cPcg3j7YtSIDJtZnbo7j4rEXhnHfY8dL7uE916+v6wRDo/qC+b7e+992FfYfHqraN3zg9gH8nx+cw62v78Mnv1HZX/vmj8fw89v78JfffLUin+Vz4XTSwkfeeQ1MXcX9h0v7lF5Dw19+82TFth98+9X4/L+cwbt/aiPWr/MgbaPkuheXvXdnP65YZ+Lz3zuDo2cjhT6iz1DxqW++BkMT+MDbrirZ93//xe2Ipm3E0k5F3/KJFy7gndf1FZZv6vAW2qLy48/3VVc6dzSLhcRqKmXjyPGRwvXc1OHFPTu34b/+44sl53drlx8zSRv7D/+wamx++LZrcGo8UTKOuOfmfnz56Dn83s/1I+NkS9rme2/Zhi9+/yx+561XQRUSGUfiwHdewgfffjUm4xb+25OX+g8fu2MQPiOKP/iHF0rq1Bsy8YV/fQm/9bNX8nq3uOXK343SbO3hYrV6/ROpDP7p+FhF/f/DYPeyTxAvJpbr3fette+ugIH7Dw9V9DfK2+KDuwexqcODUxPpkvFSblyXKhnXHbxjELcP9OKfXhop7G/HpjD+05u3YirplGx/8I5BbGjz4Lf+7gdVj9N1JZ55ZRQnR+Ml7cr/954bMR6zSo7nnpv78dDTJ3DXjk24//Bx/MyWdtx2XV9hzix3HAM4PxVHX1sAB45c6k996d/O4bdu2oJT46X7Obh7AOcmU/j41yrHggd3D+DRo+dw8zW9+PLRcxXvf+Sd12Cd38Cff/0V/NZNW5C0c2Vv6w7gV356U8l52H/7AP73v57FibE4HtwziC99/yzu2rFp0XFa14wohIgJIaJVvmJCiGg997XanJlMFG5eAEjbLvY9+jzOTCYWXcau7esLgXXnjRsKAZov99REohDkALBr+/pCcOXXmUhYGI9nMJGwKrY/9NQJ3HnjBqRtF/cfHsKu7etrlvPQ0yfx3rdcWejQFS+fSFiYSFiFsg49dQKui6r7e3E4gmPnIxVlHDsfWdQ5IqKVUS3HPfT0Sdx54wbs2r6+0DjfeeMG+AwdpycSVfPPJ79xAhMJq2TZgSdK89ADZXnowJFL7xfnpWrl7z88BENVCh2a/PIHjgxhLJapWf/y3Lfv0ecxdDFSkZPz79/32PGSOhXn+3q0B3RJM57PEyOJwkAjX6f7Dx/HiZGVqRPrM7ehi5FCjsrX577HjmPoYqSu+2lUXxDI5cZ8369a3/CBI0O4+6athYnh/PJ8f+03fnYLPvr4UNV8ls+F+f5jef6cSFj46OPHq277Z19/Bbu2r8dDT5/EOp+n4roXl/3Q0yfx2ngCd9+0tfD+oadOYCyWKeTi8n2/Oh7HWCxTtW/53rdcWbK8uC0qP/58HVY6dzSLhcTqiyPRkuu5a/v6wsRwfpuHnj4J25FzxuZk0qoYRzz8zEns2r4eH338eEXb/MlvnCi0yz5Dx3g8g13b1+PkWLwwMZxf96OPH8cro7GKOp2ezMUZr3frW6783SjN1h4uVqvXf2gkXrX+QyPx5a/LImK53n3fWvuOpbNV+xvlbfH9h48DUCvGS9XGdfc/fhwvjkRL9nf3TVthZ1Gx/f2PH4eTRc3jPDOZwLHzkYp2JZbKVhzPw8+cxN03bS1c79/42S0lc2b5ua839fcU6pFvs3ZtX4/JZOW48v7DQ7Czsmr/5/7DuX5Xvj0rf//jX/sxXh2LV5T93rdcWXEeDhwZwnvfcmXhuuSPY7FxWtfJYSllUEoZqvIVlFKG6rmv1WY0mi5c4Ly07WIsll50GUJcukGKf85zZemyWuvkv6rVS4jKn6uVk7ZdpDJO1eX58ovLSsyzbrXlizlHRLQyauU4IVCRsxIZZ878Uy0XzJeHhCh9nbKcmuVPJexF7bfWPi9GKnPyXHXK57J6tAd0STOez9FopmqdRqMZ1qcJ65O/l8vrMxKpbww1qi8IVObZqv01q3YfbHo2L86Xz6rl1fyyubadK/cW9xNdCaQsp6J+tXLxXG1J+fHWql95X5W5eGGxWn4f1zq/iaLrsJBxS367/Lq12uZ82fnrt5g+RT7OeL1b33Ll70ZptvZwsVj/+llMLNe771tr3wnLmbO/Ub7vhebg8vOeyjg154mmk3bVfQG581At99cqq7hfMF2jT1J8HPljnauNqXaOyvc3X/+juOxac2v5vlFxuYuN04b+L4UQolsIsTH/1ch9tbqekAlTL70cpq6gO7jwf7coLqO4rPJyVVG5rNo6+a9q60pZ+XO1ckxdgc+jVV2uCEARKCnLb869brXlizlHRLQyauW44vs/z29qc+afarlgvjxU/r7P0GqW3+7XF73fauv3havn5Fp1yueyerQHdEkzns/cZ/1X1qkntDKfYcf6zK0v7K1an95wfWOokX3B8tdV+2tG7T5YcV6cK59Vy6vFy2ptO1fuLc6zigC8hlbyfnlfsnzftXJ9reOtdvzF5TMXLyxWa93H5a/9ZddhoeOWfNzUapvzZeev32L6FPk44/VufcuVvxul2drDxWL962cxsVzvvm+tfftn2+OF5PruYPU6VcvB5efd59FqzhO1+fSq+wJy56Fa7q9VVnG/oFafpKfsOPI/12pj5jpHxfub69wUl11rbs1btJ98+7XYOG3I5LAQYrcQ4iSA0wC+DeAMgK81Yl+rxeYOPw7ddUNJcBy66wZsnn0Q22LKOPLCMO65uR+mruArPziPvTv7S8rd0unHgd0DhWVHXhjG/tsHStbp8BvoDHjQ4Tcqtt936zZ89YfnYeq5z0p54thwzXL27uzHZ559Dftu3VaxvNNvoNNvFMrad+s2KAJV93fd+jC2bwhXlLF9Q3hR54iIVka1HLd3Zz+++sPzOPLCMB7cM1jIWcmMjc2d/qr5595btqHTb5Qs27+rNA89UJaH9t9+6f3ivFSt/AO7B2BlXRzcXVrGA7cPoDvoqVn/8tx36K4bMNAXrsjJ+fcf3DNYUqfifF+P9oAuacbzua3Xj4O7B0vqdHD3ILb1rkydWJ+5DfSFCjkqX58H9wxioC9c1/00qi8I5HJjvu9XrW/4wO0DeOS5U7j3lur9tc9+5zQ+dsdA1XyWz4X5/mN5/uzwG/jYHYNVt/3g26/GE8eGsXdnP2aSmYrrXlz23p39uLLLj889d6rw/r5bt6E76Cnk4vJ9X9kVQFfQU7Vv+ZlnXytZXtwWlR9/vg4rnTuaxUJi9breUMn1PPLCMP74F66rOL+6JuaMzXafUTGOuOfmfjxxbBgfu2Owom2+95ZteOJYrl1OWja6Ah48cWwYV3UH8Ee3XVOy7sfuGMTVPcGKOm3pyMUZr3frW6783SjN1h4uVqvXf6A3ULX+A72B5a/LImK53n3fWvsOmmrV/kZ5W3xw9yCAbMV4qdq47uAdg7iut3R/jzx3CrqCiu0P3jEITUXN49zc4cd1G8IV7UrQVCuO556b+/HIc6cK1/uz3zldMmeWn/v6zsnRQj3ybdaRF4bR7qscVx7cPQBdFVX7Pwd35/pd99zcX/X9j7zzGlzVHago+zPPvlZxHvbfPoC/ffa1wnX53OxxLDZOhZRy/rUWSQjxAoCbAXxDSvkTQoifA/ArUsr31X1nNezYsUMePXp0uXZXF/knSo7F0ugOLu0J1VOJDPTZJ1R3Bz2IpGxMxC0ETQ2udOEztNl/4bNmfzOjYiZpI5FxEPbpUBWBZMZB0KMjk83CcYGUlUVHwIArJcaimdknMGpIZHJPjAx6NIS9GjKOW9iXV1NxMZpGX9hE1nUxlXDg96jQVAFTy/1mfzxuwWuo8BsqYrNPFE5YWSQzWQS9GnpDJjbN3uCnJxI4N5WAz9DQE/JgY3tTPkV4URVqxVilVWHZ47Q4x3UFTKgKMBLN5buNbT6cm05iNJqGV1ehCAkrK2FnXWRn80/IqyFlZ2HqKlQhEEnZCHl1ZBwHmqIinnbQ5tchAKQdF4lMFj5Dhanncs1EPIPOgAdZKTGTtNEbMqEpwEzKQSzjoN2nw6MpkAASGRuGmntyekcg9+TXsKlDAhiNZRA2NQRNHRPxDExdhU9XEbccWI6LjbNPwc0/CKE8J/eELh1vrXxfj/ZgFVlyrDbj+Wy2p3ezPnPLPzV7JJJGb9jEwOwTsss0RaxWyzudAQ/SdhaRVO5J32GvBgkglso99Tph2RBCgeVksc5rYDyegUdX0e7T4dVVnJ1Kot1nwHEl4hkbXl3DeDyDnqAHuqbgQiSNoEeDV1eRdhwYqorphA3TUBD0aHCki2wWSNtZePRcvm73G4ikLRiqClUBPJqKoKlgIu5gMmGhN+gBhMRk3IHXUBAwNGiaQDTlIGllEfCo8BsaXClxIZJGd9CDsE/FTHL2yeJBD65o9yBjSUzEM7AciZSdRWfAQMbJIpJy0BcyYbsuYmkHG9v92NTuw5nJBE5PJmDOHr/P0DDaRLmjTpYlVlMpGy+ORAv38et7/Tg1mcRIxIKp566pqgLxTK4dn0pk0BM0kXayiKUdtPkNxNI22rwG0k4WSSuLkKkjkrYR8Gi5cYjl5K6tlUWbT8dMykbQ1KDP1iUyO7YImipsB5hKWrNjGg+6ggbWh0uvedCjAZAIeY3VdL1b2ZJjdYH5u2k1W3u4WK1e/0Qqg6GReKH+A72BWg/5WnCsXu64ajGxXO++b7V9K4rAqfE4hmeSMDQVSctBh98DXRNIZC61xX1tHnR5TZyciCOecTCTtNAZ8CCWsbHOayDrSozFMugNmbjuijAMQy3dX8hEe1DHVDzXh5lKWIV1NU2Z8zhdV+LcVC7+kpZTGKe5rsRLFyMYiWYQ8mpwsi76wj6sD5k4PhLFSDSNLR0+JKxLx+E3VVyYzvU3Uk4Wk3ELG9Z5YbsSUwkLnQEDSSuLeCbXxwmaKra0BfDKeAzTSQs+Q8N0wkK734DfIxDPSEwnbbR5dSRtGz5dx2Qyg66AB5qiIJN1oEJBNGMjaOqzHxmRRXcw1x8bjWbQFfRACInphIOuoIG07UBV1MuK00ZNDh+VUu6YnST+CSmlK4T4vpTyDXXfWQ2ccKMVxMlhagWMU2oVjFVqFYxVahWMVWoVjFVqFQ2fHCaqg5pxqtV6Y4lmhBABAM8C+IIQYgyAM882RERERERERERERLRMGvX/FHcASAG4F8CTAF4DcHuD9kVEREREREREREREi9SQvxyWUiaKXj7SiH0QERERERERERER0eVryOSwECIGIP9hxgYAHUBCShlqxP6IiIiIiIiIiIiIaHEa9ZfDweLXQog9AJbtYXRERERERERERERENLdGfeZwCSnlYwBuXo59EREREREREREREdH8GvWxEncWvVQA7MClj5kgIiIiIiIiIiIiohXWkMlhALcX/ewAOAPgjgbti4iIiIiIiIiIiIgWqVGfOfyb9S5TCLEOwN8CGETur5B/S0r5vXrvh4iIiIiIiIiIiGgtqPvksBDiDgB/CODa2UVHARyUUn5HCBGWUkYus+iHADwppfwlIYQBwFeH6q4o15U4M5nAaDSNoKkhaWWRsbPwGRqmEhaCXg1CSEAqmIhn0Bc24dUVJKwsklYWrnThM3REkjbCPh0SEpGkgw6/jqwERqMZvK7NhONKjEQz6A56YKgKomkLHk1D2nbg1TWMx3PvaSqQtFzEMw7WeXUYam5f8YyDDr8BRQApO/d+m99AyKMilsliNJpBb8gDXRW4EEmjL2zCdYELkTR6Qh6oioSUAuOxDHpDJtKOi0jKxhXrvHh9bwiatiwffU1EK8h1Jc5OJjCVzEBAIG07MDUNCTuLlOXAZ2hQFcCrq3AlMBHPIOw1kHYc+HUN4wkLAUNDwKPCkVmoQkU84yArXfh0HbG0jTafgYyTRSzjwKerCJgaXAnMJCwETB3RtI2wV0fScuA3NBiaQMrOIpLKvfYZKqYSFkxdhakrUITAWCyDdV4NuqbCybowVAWxjIO07aI7aCDtuIilHVzV6YcLgbFYGt1BE6oCXIyk0RMysbnDD0URCzpH+TZhMdvR/GZSaZwYSWA0mkFPyINtvX6s85qsUxPXx7KyOHYhgpFoGn0hE9ddEYZhqCtWn+VSj+uQzyUXZ1LwGirSdhbxTBY+Q4WqAD5DgyslRmMZdPoMZKXETMrO5U2PBghgPG6hy28U+oG9IQ+SVi6/hkwNHk1FLGPDp2uYTFho8xvwqAIp28VUwkJHwIDfUBFNO4imHXQHPMhKF1MJGwGPBl0VUBUBBQLDs/3FsFeB7QjErexsn9EDn0eFAmAm5WAybqEn5MH6Ng9SFjAWK82VC8mh1fre8YyDLe0+xDLObD/Wi4E+9k/nM9/5Ln5/fZsHoxEL4/HcWCBlZxFLO+gKGhAQGI9b6PAbmEpk4NVVtPkNxNIOJhMWeoIeuHDhuoCpKxBQkHaysLMSSctBeHbMMhm3sM6vw5ptl7uDHrgyNwbqCnjQ5lMxmXAKY5BruoM4H0mxzV0DWr1/1Wzt82K1ev2bqT+yXLHsuhKnJxI4O5VAwJMbIyUyDoTIzel0hzzoDnoQSdnI2C7is2Or8VgGnUEP/LqKqaQFx3URMg1MJSx4DRUBQ8V0yoKhqgiZGuIZB/GMA6+hwVAFTE3FZDKDsGkgK10krdzcWDRtIzQ7lgt5dERSNvymip6gCSubxVTChpN1EfDoyMJFxpaIz7YxV/f48epYEmkni6wLOK4Ln5Hru3T4DUTTNroCHthZF6PRDDoCBnyGgowtMRbLoCvogZV1IF0FhiagKAAgMJ2wETBVdPh1xDMuIikLXl1DLG2jM+ABAEzELfSFDdgOMBrLIGhqCJoa0nauzn1hT2Hca872wQRy82jr15kQELDcLBw3N8/nM1SEfToUmesXxTO5Y0w7DjRFhakpGI1ZaPfpuK4vDNNc3HRvXSeHhRDvB/BbyE0OH51dvAPAfxdCPATgIwCuv4xyQwDeAuA3AEBKaQGw6lDlFeO6Ek8OjWDfo8+jzWfg7p/ZhC/92zm8a8dGPPzMSaRtF6au4MDuAfzVt17F2ckUTF3Bwd2DAFx86luvVay7d2c/vn9qEm8f7MOBI0OFch96+tI6H3rH1Wj3GfjCv57EL964EQee+GHJvv7h6DkMz2Twu2/dioSVLdl2/+0D+Jtv5+qyqcOLD7ytH/cfPl6y/8997yymk1bJzwd3D+BT33oVliMr6vPgnkHsuX49O+BEq5jrSjzzyiim4hkoioIvff8sfu2nN2M8HsOhp06U5BD/bGfrr799CoYm8LtvvQoPHPlhyTpbO/04OxXFF/71bCEPVst3xTnL1BXcc3M/vnz0HH7nLVfhm6+cwS3X9uH+w0NVc1h+23ze+tK/ncNv3bQFSTtbkVMf/9Ew3nldX8ny4rIO3XUDbhvonbPzVtwm5MtYyHY0v5lUGl8/Pl7SXh3cPYi3D3at2OCk2erUbPWxrCweO3YB9z9eVJ87BrFn+xWreoK4HtehvH/5m2/aXJJnP/LOa+DRVeyvkfv27uxHb9iECol/GYvjoadPVi3n4O7XQ0Jg/+Fcft7U4cX733ZVodzy19X2U5zvp5MW/vsvbUfGdvHRouv+0Luux3TSwQNHhkrOyaNHz+Lo2UghV7792h58/eXROXNotb53/vjYP12c+dqs4vd/Zcd6XHtFG+4/fLzquf7IO6+BlZXY+6Uf1Yydg7sH8I2XL+Kd161HIuMglnYq2tyvvXixoi3ed+s2fPa7Z2BoorLMOwbxqW+eLPQR2OauTq3ev2q29nmxWr3+zdQfWa5Yrraffbdug0dV8CdP/riw7BO/tB1p28WX/+0sfvEnN+LAkdJ5padfvoif3NSJT37jRyW52qerOHJseHab0j6C31AhJXDguZfw22/agpTt4ovfz433vny0cq5s785+9IVN/P2/nMHt29fD0ARmUk5Fe64KiZGoVXW+7d5btuHCdAof/9qPC23QB952VckYcf+uAXzlh+ew89reirHq7/1cP/7ymyer1q3a3Njenf0Imhoe/bd/xy/95IbCfovPwf/5wXn80k9ugK4KJG0Xn/jnV0quRVfQgw9/9cWKebx3XncFDFXBx//vS/jA2/qx+7q+RU0Q17vH8/sA3i6lfEZKGZ39ega5zyD+OwB/c5nlbgUwDuCzQogfCSH+Vgjhr0+VV8aZyUThhrvzxg146OmT2LV9fSGgACBtu9h/eAi7tq8vvL7/8HH4DL3qug89fRK/8bNbCjdZvtzidT7xz6/g9GQCd9+0FQeeGKrY1903bcWdN27ARMKq2PbAkUt12bV9fSHJF+//zhs3VPx8/+wxVKvPfY8dx9DFy/1jciJqBWcmEzh2PgKfoeO+x47j7pu24vRkojDRAFzKIRMJCxMJC3feuAG7tq8vTAgUr2NnJQ49daIkD1bLL8U5K227ePiZXJ498MQQfu2NWwqNfnHZ+byV37Y4P08mK/PiJ/75Fbz3LVdWLC8ua9+jz+PMZGLec5RvE/JlLGQ7mt+JkURFe3X/4eM4MbJy57bZ6tRs9Tl2IVIYiBXq8/hxHLuwuvsL9bgO5f3L8jw7kbAKE2T5ZeX9t9MTCazzewp5rVo5PkMvKWfX9vVzvq62n+J8n7ZdvDoWL0wM57exs6hoB+4/nGtH8q/3Pfo8hi5G5s2h1fretdoP9k/nNl+bVfz+O667NGaodq4nEhb+7OuvzBk79x/OtdunJxIYi2WqtrnV2uJDT50o9Ccqynz8eEkfgW3u6tTq/atma58Xq9Xr30z9keWK5Wr7OfTUCUwmrZJlJ2fb7Ltv2lqYf8q/t382Z3/yG5VjvcmkVXWbfL9gMmlh1/b1mEhY+OQ3Lo33as1/nZrIzW1NJi1cjFa2D/c9dhy6qtWcb/vkN05gInHp2HLzXKV1O/BEbp6s2lj1o7NtSbW6VZsbe+jpkxiLZfDet1xZmBguPwfvfcuVmEjkjic/MVx8LU5PJKrO433in1/BeDxTmKt7cZH9mLr/OlxKOVVl2SSAs1LKv77MYjUANwL4aynlTwBIAPij8pWEEO8TQhwVQhwdHx+/zF0tj9FounBBhchd1Pz3Yvnlxa8TllNz3emEXVFu+TquBFKz/xZd/l5qtmxXzl2X+epa7eda24xE0nOcqdWplWKV1q56xeloNA1XAonZvJPKODVzjCtz+WeunJGwnIqcudD8mV+vOFdWW788b82VF1NW9XxaXNZYbO48V9wmFJcx33aUM1esjkYzVc/taDSznFUs0Wx1arb6jNS4H0ajrX8/NDpWq/Uvi83Xv8vn4fn6k4myfmT5OgvpJxbn+1p1K99PftuU5ZS8vhiZP4fWOjfsn1Y3d6zOfb6L3x+PLS4ma12PmaRdiJmqMVEjVubqT5T3EdjmtqalxGqza7b2ebFavf717I8sdVy1XLFcaz+uLF0vn4tr5d6ZGmMtV6Lm2Km4X5Avf765snx5c7UP1caOtY6t1jr5Olcbqy52bmyu+biFHE/5tSivX74+i73P6j05HBVCVHxsxOyypfx65TyA81LKf519/X+QmywuIaX8tJRyh5RyR1dX1xJ213g9IROmfun0538uXpZ/LWXpa7+h1Vy33a9XLbf4tSIAn0er+p53tmxVLKwutd6f6+fybXrDzf8vJfXWSrFKa1e94rQnZEIVgN/M5R2fR6uZYxQBKAJz5gy/oVXNmQvJWVLmvreV5cry9avlrVp19hnV82nx9t3BufNceZuw0O0oZ65Y7Ql5qp7bnpBnOatYotnq1Gz16atxP/SEWv9+aHSs1upf5s3Xv8vn4fIcWb5NPp+XlzPf6/L9FOf7anWrtZ98fzX/ui/snTeHznVu2D+tNHeszt1mFb/fHby8mCx/vc6nQxVztMU1xjZz9SfK+whsc1vTUmK12TVb+7xYrV7/evZHljquWq5YrrWf8k+uyOfiWrl3XY2xliJQc+xU3C8ozvVzzZXly5urfag1dqx1bLX6HXONVRczrpxrPm4hx1OtvsX1y493F3uf1Xty+A8AHBZCPCCEuF0IsUsIcQDA47PvXRYp5QiAfxdCXD27aCeAl5Ze3ZWzucOPQ3fdAFNX8JUfnMfenf048sIw7rm5vyTADuwewBPHhguvD+4eRNKyq667d2c/Pvud09h/+0BJucXrfOgdV2NLhx+PPHcK+3cNVOzrc8+dwld+cB4dfqNi2/23X6rLkReGcXD3YMX+v/rD8xU/H5w9hmr1eXDPIAb6wst01oloJWzu8OO6DWEkMzYe3DOIR547hc0dfuy7dVtFDun0G+j0G/jqD8/jyAvDeOD2gYp1dFVg363bSvJgtfxSnLNMPfeZw08cG8b+XQP4wr+cxsHdlWXn81Z+2+L83O6rzIsfesfV+Myzr1UsLy7r0F03YHPH3J+EVNwm5MtYyHY0v229/or26uDuQWzrXblz22x1arb6XHdFGAfvKKvPHYPYfsXq7i/U4zqU9y/L82yH38CBOXLf3p392NLpx0wiU8hr1cpJZuySco68MDzn62r7Kc73pq7gyu4APlZ23XUFFe3Awd2D+NxzpwqvD911Awb6QvPm0Gp971rtB/unc5uvzSp+/8kXL40Zqp3rDr+BD7796jlj5+DuXLu9udOPrqCnaptbrS3ed+u2Qn+iosw7Bkv6CGxzV6dW7181W/u8WK1e/2bqjyxXLFfbz75bt6HDZ5Qsu2q2zX7kuVOF+af8ewdmc/a9t1SO9Tp8RtVt8v2CDp+BJ44No8Nv4N5bLo33as1/be3MzW21+wz0hirbhwf3DMLOOjXn2+69ZRs6/ZeOLTfPVVq3/bty82TVxqofu2OwZt2qzY3t3dmP7qAHn3n2NXzknddUPQefefY1dPhzx/Ohd1xdcS22dPqrzuN96B1XoyvgwRPHcu3udYvsxwgp5fxrLaZAIXoBvB/AAAABYAjAp2YneJdS7g0A/haAAeAUgN+UUk7XWn/Hjh3y6NGjtd5uCuVPTE5ZWWScLLy6hqmEhaBXgxASkAomZp/u6zMUJKwsklYWrpTw6RoiKRthrw4pck8x7PDryEpgLJbBhrAJZ/ZJvd1BDwxVQTRtwaNpSNsOvLqG8XjuPU0FkpaLRCaLsFeDoeb2lchk0e7XoQggZbuIZxy0+QyETBWxTBZj0dwTKw1V4EIkjd6QCcjcUxa7gx6oqoTrCkwmMugJmkg7LqIpB31hD17fF16ND/tY1CfCt0Ks0qq0rHHquhJnJxOYSmYgIJC2HZiahqSdnX0SrQpVAbyaChe5p7uGvTrSjgO/rmEiYcHv0eA3VGRlFqpQEc84cF0Jr5F7Mmybz0DGySKeycJrKAh4NLguMJOyEPDknnAb9upIWg58hgaPJpCys4gms/B5VPgMFdMJCx5dhakrUITAeMxCyKvCUFVkXRe6qiA2+29A3UED6dmnol/Z6YeEwHg8ja6ACVXJ/Stad3DhTxLOtwljscVttwYsOVab8UnZzVanZqtP/ung+Sdyb1/Bp4MvQlPEaj6XjMykYBoq0k4WiXQWXkOFogB+Q4Mrc0/hbvcZcKVEJOXAq+fyJkQuB3f4DSStLBIZB91BD1J2Lr8GPCpMTUXMsuGb7bO2+QwYmkDKdjGVsNARMOA3VMTSDqJpB50BD1yZ+0gfv0eDrgqoioACgQvRXH8x7FVhO0DcymIiljt+n0eFgtxTuScTFrqDHmxo8yBlAePx0ly5kBxare8dzzjY1O5DPOPgYiSN3rCJgdXZPy225Fid73wXv3/FOg9GIxbGZ8czKTuLeDqLzoAOIQTGZ+NtKmHB1BW0+w3E0rlr3hP0QMKFk83/xZSCtJOFnZVIWVmEZscsk3EL6/w6LMdFfDbmJCRGoxl0BjxY51MxlXAKY5BrekI4H0mxzW1+DY/VZtds7fNitXr9F9EfWXBQXe64arli2XUlTk8kcG4qgYBHg9dQkcw4gBAYj+XmjrpDHkRTduFjG3yGhvFYLt/6DRVTSQuO6yJk5nK711ARMFRMpywYqoqQqSGecWbHbSoMVcCjqZhKZhAyDbjSRcrKFsZ5QTM3lgt5dERSNnweFb0hE1Y2i6mEDSfrIuDRkYULy5aIpR10BQxc3evHq2NJpJ0ssi6QdV14jVzfpd1nIJqx0en3wHFzH8PQ7jfg8yiw7Fw/qSvgge1m4UoBQxVQFAAQmEnY8HtUtAd0JDIuIikLXl1DLO2gM2AAACbjFnrCBhwHGI1lEDQ1BD0a0k4W00kbvUFPYdxr6goChgYhcvNo69eZEBCw3Fy9I0kHXkNB2KsX+kUJy0GH34DlZKGqCkxVwVjcQptPx3V94VoPo6sZMHWfHG4WnHCjFcTJYWoFjFNqFYxVahWMVWoVjFVqFYxVahUNnxwmqoOacVp1Kvmy9yLEiwCqzTYLAFJKub2e+yMiIiIiIiIiIiKiy1PXyWEAu+pcHhERERERERERERE1QF0nh6WUZ+tZHhERERERERERERE1Rr0/ViKGuT9WIlTP/RERERERERERERHR5an3Xw4H61keERERERERERERETVGvT9zuIQQohuAmX8tpTzXyP0RERERERERERER0cIojShUCLFbCHESwGkA3wZwBsDXGrEvIiIiIiIiIiIiIlq8hkwOA/gYgDcCOCGl3AJgJ4DvNmhfRERERERERERERLRIjfpYCVtKOSmEUIQQipTym0KIP23Qvlac60qcmUxgNJpGd9CEqgDj8QwMVUHSyqIvbMLJSpybTsJvaOgJebBhnQ/nppMYjabRGzJhZx1MJ7OYSdno8OuYTtoImRo8mgLHlZiIW/AZKtZ5dTiuxIWZNPrCHmiqgoTlwFAV2FmJqYSF3rCJrOsiknQQ9GpIZBwETR1eXUU0bSPjZOE3NKRsBx5NQyxtozvoQdYFLkTS6A174NVVnJ5Ioi/sgSIEppIWOnwGElYWsbSDrqCBaNrGOq8Bj64gbbuYiGfgNzToqoDfo+GanhA0rVG/fyCiZue6EuemEhiPZTCVtOA3NATNXE6KZxz4DQ2mrmIqaSFoatAVAZ9HRSydxXg8g86ABynLhlfXIIRAJGkj7NORtBx4NBUZx0Gb14N0NgvbkUhYDoKmBlNTMRJNoy9kIiuB0WgaXUEP4hkbhqpCUwUgAV0V8GgqJCRiaQexjIOAocGjK3CyLry6hljGQdLKot2vozPgwcZ2PwDg1HgcpycTMHUVbT593nxX3E70hExs7vBDUcRyXYo1byaVxomRBEajGfSEPNjW68c6rzn/hmuoTs1Wn2TKwvGRWKE+g71B+LzGitVnue7helyHfF1jKRuZrIvRaAa9IQ8MTcGFmTSuWOdBxpEYjWawfp2JTNZFIu0g5NWRsHK5OZ62ETB1RFI2gqaGgCfXX4ylc/lQAhiN5OoYMFVMxm3EMw4CHg0BjwpDUxBNO5iIW+gMGPBqCqysxGgsg+6gB4CLsFdHJJUtHKtHA9K2RCTlIGiqCHg0SADjsQyCZq5v3ObT0Rsy0OnzFOKjN+RB0KvizEQKfWEvru4K4JXxGC5G0ujwG0g7Dtp8HpiaivF4Bt1BE5oKjEQys31ZHWk7i7DPQMbJosPvweaOXK4v799fjDCH55XHam9Yw/C0nRtjOA6mEzY2tnuRtNzZ8+ZB2KtiJpnFdNJCu99AJGVjnU9HMuPAo6tw3Cw0RUU05cBrKPDpGjJObrwymcjAq2vwGQpcCUwmcrFlOVmoqgrbcaCpKgKGhqSVxWQi17cwdQVCCETTFry6ht6QiY3tpdePbfTq1urXt9na58Vq9fqn0w5evBjByGx7c11fGKbZ0E9nBVA9bgEsOJbz208mLs1LFW+Tf386kZkdL+Wuz0BvAKNxu7CPjW25eSvHdTCTzGJsth23s1l4dQ1ZV2ImaSNganBkFqaqIWnZ8Bk6JmfHf4YqYGoqLDfXJ+kKGjA1FZPxDAKz7Xu7X4dPVxFNO+gJmbgiaGJoNIpIyoLf0BHL2Fhn6phKWjD1XB+hw68jknYwEkljnU+HJhREMrl2aCyWQVfAA79Hha4C0XQWGdtFwnLQ7tehQMFYLIOAR0PImzuOsVgGYa8GTVFm+z86omkbHX4DjutiJmkj5NVhOVmYuoZoyka734CmAomMi8m4he6QB0FTxVQiA0PVMDXb3tmOi7TtojPoKfQ18ud2NJpG2KshmcniYjSD7pAHAUPFaCyNDr+Jgb7ScabrSpyfSWAiZiE+O1btDBiFserl5rdGRfWMECIA4FkAXxBCjAFwGrSvFeW6Ek8OjWDfo88jbbswdQX7bt0Gj6rgT578Mdp8Bu7+mU146OmThff37uzHhjYv/uzrr8ByJD78zm1I2RJ/9a1X8a4dG7H3mUvrHtw9iE996yTOTqZg6gr23z6Av/n2qzg7mcKmDi/+8y3bYDtZZKXAgSNDVfd3z839eObHI/jlHRvxV996Fb/6hk344vfP4l07NuLhon3tu3UbPvvdM5hOWjiwewBPvngR3zs9hX23bsM6U8PJ0XhJuffesg1f/P5L+MDb+vHo0bM4ejZSOD6/oeL0RALvHOjjBDHRGuS6Es+8Moqzk0l84p9fKeSN4hyWzxc+XcX/eu40PvzOaxCdyOL+x48X1v/wbdcgk3Vx6KkTJTnty0fP4VffsAltvgwmE3ZJbtp36zY88cIFvPO6vopc+OWj5/Dun9oIv6ECANb5dADAH37lxZLtN6zz4uxUpGT7D73jalzV7Uc87eIP/uH5kpw+V76r1k4cuusG3DbQ21KDk1Y1k0rj68fHcf/h4yVt69sHu1ZscNJsdWq2+iRTFp44PlpRn12DPSsyQbxc93A9rkO+ro/96Bx2XtuH/YeHSvLviYszuOaKddh/uHqfcf+uAfzNs0OFHF3chywua+/Ofnzue2cLfcZ/OHqu0A/85F3XI5Jy8MCR3PqbOrx4/9uuKtn+wT2DMNRMSe49uHsAj86Ws6nDi99961WFMopz+B/cejWsrIv7Hjtecmz/+1/PwtAE7tqxqeQcPnD7AM5OpvDgP71csy3K9WnPFvrIH931eliOLLnmxce81nN49VgdwPmpOD79nbPYu7MfX3vxYkk7vKnDiw+87Srcf7jymr5rx0Y88+MR/OKNG3HgiUvvf+Sd18BraPjo4z8olPE7b70KB4ri4mN3DOKply7g5mv6EDIVnM24FbG6zqvBcYG//c4pvPunNqK/J4Cbr+4pTJCwjV69Wv36Nlv7vFitXv902sHhFy9W1H/3dX0NnSCuFbeGJvB7X/zRvLGc3/5Pn3y5Ys7n0F034O3X9uDrL4/if33ntYq8e3D3YMnczoN7BjETTyLk85bk73tv2QavruDjX/vxpfz8lqvwN88OVewzPz8EAH/97VOYTlqFdvvEWBz33NyPj8+O0T73vbNYv86Dd/3UJvzlN0/iXTs2FsZ9n/zGpfHgvlu3oTdk4g+/cqyw7L7/cC00RcEDR35YWHZg9wDWr/PgldEEPvHPr6DNZ+A337S5MLYsbleq9YvuvWUbLs6kKo7zwBOl+/irb13qUxy8YxBhU8XeL/+wZplPvXQR737DJtz32PGq6xzYPQCvJnDgyEv4/Zv7sef69dA0Ba4r8S+nxzERszA8ky7Z5uAdAzg7lcCbr+q+rPzWqFm7OwAkAdwL4EkArwG4vUH7WlFnJhOFmxYA0nZuEmMyaSFtu7jzxg2FC5Z//6GnT+LkWBy7tq/HnTduwDqfB/sPD2HX9vWFmyi/7v2Hj2PX9vWF1weODBVe79q+HqcnEvAZeqGTVG1/Dz9zEnfftLWwj09+40TVfR166gTuvHED0nauU/UbP7ulsNzn0SvKzZdz/+HjuPumrSXHN5GwcHIsjqGLkWW6ErRafOCDH8aeX39/ydcHPvjhla4WLdKZyQSOnY8UJoaByhyWzxeTSQu7tq+Hk0VhYjj//mTSKjTe+WUPP3OykMt8RmVuOvTUCbz3LVdWzYW7tq8v5KiJhIVXxxN4dTxRsb0rUbH9J/75FcRS2cLEcPExzJXvqrUT+x59HmcmE3U/71TpxEii0KkHLrWtJ0ZW7vw3W52arT7HR2JV63N8JLYi9Vmue7ge1yFf119745bCBFm+rANHhvCO69YXllfrMx54ojRHF/chy/NecZ+xuB+YdVGY1AVy/dXy7e977HhF7r2/qJxd29eXlFGcw18djxcmhouP7b1vuRJ337S14hw+cGQIY7HMnG1Rvk+b/37sfKTimhcf81rP4dVjdQhv6u8pnKvydjg3Zqh+TfNxlp+gyL8/kbDw0aJ+wa7t6wtjnvw6H338OH7tjVvwwJEhBEyjaqxejGYwHs8U+gDHzkcK149t9OrW6te32drnxWr1+r94MVK1/i82eI6jVtweOx9ZUCznt68257Pv0ecxdDHXxlXLu+VzO/c9dhzbX9dZkb8/+Y0TmEhYpfn5iepzWsVjr3w7mm+3y8dod964AXfftBUfffx4oax8+1w+Xnt1PF6ybCyWqeg77D88BFVRC2PSO2/cUDK2LG5XqvWLah1n+T6K+xT3P34cdhZzlnn3TVsLfZlq6+w/PIR1fg92bV+P+x47XhhnnplMwMkCr44nKra5//EhxFLZy85vdZ8cFkKoAB6XUrpSSkdK+YiU8mEp5WS999UMRqPpwgXJS9suXJn7WQjUfF+I3NdUwkbadmuuK0T110IArgQSGaewXa0yUrPr5N+fb19pO/dn8/mfi/dRvn7adpGynJLlrszVbSSSnucMEpUaHo/AfNN7Sr6Gx/lLhlYzGk3DlQvLafl8WC3PzFXGXLkpNU/Oyueo/Ff5erXKrbV8rnxXq50YizE/LofRaKbq+R+NZlaoRs1XJ9Znvvoszz1cj+PO13V6tm9ZXtZ47NKxLLTfmbJq59PidfLK8+RcfeHyZfly5qpbrXYhZTk1c3+1fVXrX8+3j+JjXss5vFas5s9JtXZ4rmtaq90uvw61yphJ5uJ9qkbc59v64j5Avq5so1e3Vr++zdYeLlar139kheo/3xxT8bJqsZzfvlbOvBhJzzleKp/bGY3NX5/55pmK83D5fsrb4IXOXZWfj1pt90T80nUsL6v49UL2s9C+U2Ke/kxx36rWOtNJu/Befpw5Gk1jKmHXPNaE5Vx2fqv75LCUMgsgKYQI17vsZtQTMmHqpafR1BUU/xV3rfflbJC1+/XCOtXWlbL2a1UA/tnP05prfz6PVrGPufZl6krh361NXanYR/H6pq7Aa2glyxUBKALoDTf/v4sQUf31hEyoYmE5LZ8Pq+WZucqYKzcV57xq2+VzVP6rfL1a5dZaPle+q9VOdAeZH5dDT8hT9fz3hDwrVKPmqxPrM199lucersdx5+ta3LcsLqs7WHosC8nRPqN2Ps3/XNwPrJUny19Xy73l/clq+6zVLngNrWbur7avav3r+fZRfMxrOYfXitX8OZmrHS5/nT/v1davdR3KX6/z6XPGfb6tL+4D5OvKNnp1a/Xr22zt4WK1ev17V6j+C5ljyi+rFsvF21crpy9szpmny9vixdSn1j6L83D5fsrb4IXOXZXvv1ab0RkovY5ztSuLOc7i1+V9Cv88/ZnyvlW1ddp8euG85MeZPSET7X695rH6De2y81ujPlYiDeBFIcT/FEI8nP9q0L5W1OYOPw7ddUNJ0O67dRs6fAZMXcFXfnAee3f2l7y/d2c/+rsDeOLYML7yg/OYSWZwYPcAjrwwjHtuLl334O5BPHFsuPB6/+0DhddHXhjG5k4/khkb+28fqLm/e27uxyPPnSrs495btlXd175bt+GrPzwPU899xsnffed0YXkybVeUe+8t2/DEsWEc3D2Izz13quT4Ov0G+rsDGOhbE78jIKIymzv8uG5DGB96x9UleaM4h+XzRYfPwBPHhqEpwME7BkvWb/cZ2Hfrtoqc9sSxXC5LZipz075bt+Ezz75WNRc+cWy4kKM6/Qau6vLjqi5/xfYKULH9h95xNYKmij//5Ruq5vRa+a5aO3HorhsKD5agxtrW68fB3YMVbeu23pU7/81Wp2arz2BvsGp9BnuDK1Kf5bqH63Ed8nX9+385jQO7Byry75MvDheWV+sz7t9VmqOL+5Dlea+4z1jcD1QF8MDtl9Y/8sJwxfYP7hmsyL0Hi8o58sJwSRnFOfzKrgAe3DNYcWx/++xreOS5UxXn8IHbB9Ad9FSsX3yc+T5t/vt1G8IV17z4mNd6Dq8eqwP47snRwrkqb4ePvDCMg7urX9N8nO3fVfp+h9/Ax4r6BUdeGC6MefLrfOyOQXzhX07jgdsHEE9bVWO1L+RBV8BT6ANs3xAuXD+20atbq1/fZmufF6vV639dX7hq/a9r8BxHrbjdviG8oFjOb19tzufQXTdgoC/XxlXLu+VzOw/uGcSxcxMV+fveW7ah02+U5udd1ee0isde+XY0326Xj9G++sPzeOS5U/jYHYOFsvJzWOXjtau6AiXLuoKeir7Dgd0DyLrZwpj0Kz84XzK2LG5XqvWLah1n+T6K+xQH7xiErmLOMh957lShL1NtnQO7BzCTyOCJY8N4cM9gYZy5ucMPTQWu7PJXbHPwjgEEvepl5zchpZx/rcUWKsSvV1supXyk7jurYceOHfLo0aPLsq/8kx7HYml0BXJPM56IZ6DPPhWyL2zCyUr8+3QSPkNDT8iDDetyTyYci6XREzRhZx1MJ7OIpHJPYs4/HdqjKXBcicm4Da+hYJ1Xh+NKXIik0RvyzO7DgaHmngI9lbDQGzKRdV1EUg4Cpoak7SDo0eHVVcTSNjKOC5+hImVn4dFUxNIOuoIGXBeFpwl7DRVnJpLoDXugCJF7qrDPQMLKIp5x0OE3EMvYCJsGvIaClJ17OqPPUKGrAn6Phmt6Qmv1YXSL+vTv5YzVVrDn198P803vKVmW/u7n8dgjf7XgMj7wwQ9XfBTF+q4wPvVnf1KXOq4SDY9T15U4N5XARDyDqYQNn6EiaGpIZBzEM1n4DBVeXcVUMvdEcV0R8HlUxNJZTMQz6PB7kLIdeHUVQghEkjbCPh0py4Ghqcg4WazzGshks7AdiaSVRcCjwtRVjEbTuVwogdFYGl0BDxIZG7qqQlNzh64rAoamApCIpS/VydQVOFkXXl1DbPYJsO1+vfAEWAA4NR7H6ckETF1Fm0+fN98VtxPdwdZ7UvYKW3KsNuOTsputTs1Wn2TKwvGRWKE+g73BFXkYXd4C7+GmiNV8XfN9vrHZsgxNwcVIGn1hDzKOxFg0gyvCJjKui0TaQcirI2E58Osa4hkbATPXHw14NAQ9GuIZB7G0gza/DonZJ5sHPQiYKibjNhKZLPweFQGPCkNTEE07mIznntLt03P91PzTwyFchL06IqlsoRyPDqRsiWjKQdBUc391I4DxWAbB2aeZt3l19IYNdPo8hfjoDXkQ9Ko4O5FCb9jE1V1BvDIew8VIGh1+AxnHwTqfB6amYiKRQVfAhKYCI5EMYmkbYa+OjJNFyNRhZV20+z0lT4Uv7t+PRFdNDq97rPaGNQxP59r6tJPFTMLBhnYTKSv377DdIQ/CXhUzySxmkhba/AYiKRvrvHpuLKOpcF0XqqoglnJgGgp8uoaM48CjaZhMWPDqKnyGAlcCkwkLHX4DtpuFKlQ42SxUVUHA0JC0sphMWgjO/vWZAoFoxoapqegNmxVPc2cb3dSWHKutfn2brX1erFavfzrt4MWLkUL9r+sL13oY3YKDaiHjqmpxC2DBsZzffipxaV6qJ3Rpm/z7M4kMHAmMRTPoDnkw0BvAaNwu7GNjW27eynEdzCSzGI9l0BX0wM5m4dU0ZKXETNJGwNSQdV14NBVJy4HP0DCVtOAzNBiqgKmpsNzcR3J0BQyYuoqpRAZ+Q8fM7ByYz1ARTTvoCZm4ImhiaDSKaMqCz9ARy9hYZ+qYStowdQUBj4YOv45I2sFIJIN1Pg2aUBDN2PAZGsZjGXQGPPB7VOgqEE1nkbFdJK0s1vk0qELBeDwDv6Eh5NWQdSXGYxmEvBo0RZmdj9MRTdvo8BlwXBczKQdBU4PtZmGqGqJpG21+A4YqEM9kMZmw0B30IGiqmEpYMFQV07Ptne24SNsuOgNGoa+RP7ej0TRCXg2pTBYj0dz5DXhUjMbS6PB7MNAXLhlnuq7E+ZkEJmNWYazaGTAKY9V58lvNNxsyOQwAQggvgI1SylcasoN5cMKNVhAnh5egHpPD9ShjDWCcUqtgrFKrYKxSq2CsUqtgrFKrqOvkMFGD1IzThvxZpxDidgDPA3hy9vUNQojDjdgXERERERERERERES1eo/7n/wEAbwAwAwBSyucBbGnQvoiIiIiIiIiIiIhokRo1OexIKSNlyxrz+RVEREREREREREREtGhVP0m7Do4LIX4VgCqE6AdwD4DnGrQvIiIiIiIiIiIiIlqkRv3l8O8DGACQAfBFABEA/7lB+yIiIiIiIiIiIiKiRWrUXw5fLaX8rwD+a4PKJyIiIiIiIiIiIqIlaNRfDh8SQvxYCPExIcRAg/ZBRERERERERERERJepIZPDUsqfA/A2AOMAPi2EeFEIcV8j9kVEREREREREREREi9eoj5WAlHIEwMNCiG8C+EMA9wN4cCllCiFUAEcBDEspdy29lkRElT7wwQ9jeDxSsXx9Vxif+rM/WYEaERERERERERHVX0Mmh4UQ1wJ4F4BfAjAJ4MsA/qAORe8F8DKA0OVs7LoSZyYTGI2m0RMysbnDD0URNZcvpKyRSBoeTUEkbaHDb2KgLwRNUyrWG42m0R3wIOVkcX46hb6wF1d3BfDKeAwXI2lc2eVFLO0ilnGQtrMIeTXoigJXApGkjTa/DiebhaFpSNpZJDIOOvwGpATGYhl0hzyABCYTFjoDBnRFwWgsDa+hQVMAQ1OgKQr+fTqF7qAH7T4V08ksppIWvLqKsKnj6u4gLsTSGI2m4TM0WNksDFWFlc2iw+9Z0HlZzHknalbD4xGYb3pP5fLvfn4FatN68vf8ZCKDsFdFKiORcrKYTtgI+zT4dRWOK2FlJaYSFnpDJlxIjMcy6Ax4ELdsBA0dWSkRTTlo9+uIpGwEPBp0VcFYLAOfoSLg0ZC2HWiqiljaRtirQ0BgPJFBu0+HqakYiWZg6grCpo5re3P5uVY+Kq63oSpIWlnmrFViJpXGiZEERqMZ9IQ82NbrxzqvyTo1cX2are/gOC6GLkZwMZJGX9hb0d+rl0ZdB8dxMXQhgguRNHpCHmSlxGgk13/sW6diPOoinnGQlS58uoZIykZP0ISVdRFJ2Qh5dagCSNm59ToDBtJOrp+YyNgIenQoKpCxJeIZB+u8OuIZBz5DQ0/IA8d1MBXPYjSWQV/YAwFgKpnL29NJG+t8OnqDBl7XHij0zU9PJHB2KoGwqUOIXH/X79HQ7tdxdXf1899scdMozXCcC43VfOwNz6Swvs0Ly3ExHs+gO2jCcV1EU7k4cFwXilAQSdnoCnigKrlr3u43YGddxNIO1vkMZLIOvJqG6aSNdp8BIQBXAlOJDHpClfdmM5wrWlnLlb8bpdna58Vq9fo3u6XGt2VlcexCBCPRNPpCJq67IgzDUOdeL2yiw2/gYiSXVze2+XBuOlnIs50BDT8eSWA6aaPNp2MqaWGdV58du2VhObm+RMDUEDJ1pOzS+SbXlfj36QRGIxlEZsd48bSNNp+BpJ1FNOWgO+jBtT0BnJ1JIp7JImVlIaWE36NhLJZBm9+AoQj4PSpMTcFYzMZYPIPOgAGPpmA0mkFXwANDk7AdkZtjsxwETQ0+XcNYLA2/oSHg0WBoAgkrC3t27Nod9MDKZhHyGri6K4gL0RRGoxkkLAeb2v3Y0ukHgEW1PQttqxo5Xm3UXw7/HYAnAPwugH+TUqaXWqAQYgOA/wDgjwHsW+z2rivx5NAI9j36PNK2C1NXcOiuG/D2a3vw9ZdHK5bfNtBb8+RWK+uem/vx5aMv4fdv7see69dD05Sq6+3d2Y/Pfe8sppMWDu4exKe+dRI/+bp1eNs13RieSeOhp08ibbvY1OHF7771KjxwZKiw7YHdA7CzLh78p5exrTuAX/npTThwZAhtPgN3/8ymwrbl+9m7sx9+Q0XQq+Oz3zmNSNrG7/1cPz76+PHC+h955zU4MRYvWZY7pnN4146N+PLRc/gvt10753lZzHlfbDlE1Bry9/yfPvky/vAd2zAZVxBJOdh/eKgoB1yPSMrBgaL8Vpyz8rnn3T+1sbDsv/78tci6Ev/tyR+XbHPFOhP/dGwYb7qyG69lEzj01Am0+Qz85ps249BTJ0rWPTudhFdX8fv/+0cV+QhAod7v2rERDz9zkjlrlZhJpfH14+O4//Cl9u3g7kG8fbBrxQYnzVanZqtPs/UdHMfFYy8M477HLp2fB/cMFvp79dKo61Ct/sU592N3DCLjZPGZ/3eqkP/K+5abOrz4nbdeVZK3D+wewF9961WcnUwVXv/D0XO4+Zrekhz60LuvRySZLTmuajn//W+7CsMzKbxhc2ehb14rn58aT+CdA30Vk4DNFDeN0gzHudBYLY69ucYrhibwO2+5CgeeKI2vL/zLWZwYi2Pfrdvw2e+emR0/DeBT3xoqxN3+XQP4m2cvxWHxvdkM54pW1nLl70ZptvZ5sVq9/s1uqfFtWVk8duwC7i+aAzp4xyD2bL+iZIK42nr7bx/A//7XXI5+cM8g/uKZkzg7mcJdP9mHHZu78KlvnawYU/3JndfBycqSOae9O/vh01X8r+dO47/cdi3efm0PvntqHBdmMvibb79as19i6go+dscgukMGXroQw5f+7VzF/vbfPoBNHSbOT6Vxf9FYtLju+T7Qg//0cs25tP6eAMZjVkkfaP/tA/jKD07gV396M+JpGx//2qUx6p//8g3w6AK/98XKMWetCd+FtFXF4+xGjFfrmhGFEJoQ4r8DuBLALwB4GMC/CyH+uxBCX2Lx/wO5j6dwL2fjM5OJwskGgLTtYt+jz2PoYqTq8jOTiUWV9fAzJ7Fr+3rc99hxDF2M1FzvoadP4s4bNyBtu7j/8HHs2r4ev/RTG/HqeKIQ6ACwa/v6wsRwftv9h4cwFssgbbt471uuLATnnTduKNm2fD8PPX0SEwkLpycSeO9brsSu7esLN2R+/YmEVbEsf0z57/Odl8Wc98WWQ0StIX/P79q+HkHTgJNFYWIYyOUA10Uhf+WXFeesfM4pXjYezxQmhou3eW08gV974xZMJq3C5MGdN24o/Fy87qtjcbw4HKmaj4rrnW9oy9eh1nRiJFEYlAAotL8nRlbumjZbnZqtPs3Wdxi6GCkMvPL1Ke7v1UujrkO1+hfn148+fhxjsUxJ/ivvW+7avr4ib+8/PIRd29eXvL77pq0VOdR2UHFc1XL+/sNDcFyU9M1r5fOTY/GK899scdMozXCcC43V4tiba7yya/v6wsRw/r39h4fw3rdcibTt4tBTJ4rGT6Vxd+CJ0tfzjcVWY0xQbcuVvxul2drnxWr1+je7pcb3sQuRwoRvfvv7Hz+OYxci86534MilHH3fY8cLeXjPjRsL81zl/YHTE4mKOaeHnj6JyaRVmG8auhhBLJXFgSNDc/ZL8v0XQ1Xx0NMnq+7vwJEhqEItTAxXq3u+DzTXXJqhKhV9oANHcn2ej/zji5hIWCXv/cE/PI9j56uPOatZaFvV6PFqvX9d9gkA7QC2SClvlFL+BHITxesA/NnlFiqE2AVgTEr5g3nWe58Q4qgQ4uj4+HjJe6PRdOHk5aVtFxcj1ZePxWr/sXOtsoTIfR+JpOddr/jniVgGrkTJuvmyyrd1Ze7nVMYpvF9r3eL9uDL3L1cpy6m6fvn+y48p/32u81JNrXOw2HJWm7lilahZXE6c5u95IYCphI1EUa7Kq7asWm4sXlYrR7kSmEnaJe/PlT/zObR4+djsx+kU77faOtS85m7/M1Wv6Wg0s5xVLNFsdWq++jRX36FWXzHf31uMlYjVWvUv7ycW57/yXDhfXzP/OmUtLedPJ+2S+s6Vz8vPf7PFTaMs13HWI1YXci2FqP1eynJK1iv/udbr+cZiqy0m1rq5YrWe+XslNFv7vFitXv96asT4f6nxPVIjR45G0wtar1qOnpidaF3MnFNxH+RiJF3oN8zVL8lvOx6vvb98vp+v7tXGh8VtzlTCrllGre1rjTmrWWhb1ejxar0nh3cB+E9Sylh+gZQyitzHS/z8Esp9E4DdQogzAL4E4GYhxN+XrySl/LSUcoeUckdXV1fJez0hE6ZeerimrqAvXH15d7D2vznUKkvK3PfesDnvesU/dwU9UAWqrlv+Ov9X4j6PVvL+fPtRBKAIwGtoVdevtf/8MeW/z3Veqql1DhZbzmozV6wSNYvLidPie77dr8NvahU5oNqyarmxeFmtHKUIYJ1Pr3i/1rrl/2mTz0fF9WbOaj1zt/+eqte0J+RZziqWaLY6NV99mqvv0Bf2Vq1Pvr+3GCsRq7XqX95PzP9cvE75NrXKyL/2GUvL+W0+vaK+tfJ5+flvtrhplOU6znrE6kKuZXEclL9XPG4pj5dqZeRfzzcWW20xsdbNFav1zN8rodna58Vq9frXUyPG/0uN774aObInZC5ovWo5uit46ZovdM5JESj0A/rCZkm/Yb42pCtQe3/5fD9f3auND4vbnHa/XrOMWtvXGnNWs9C2qtHj1XpPDksppayyMAugYvkiCv2wlHKDlHIzgHcDeEZK+R8XU8bmDj8O3XVDyck8dNcNGOgLV12+ucO/qLLuubkfTxwbxoN7BjHQF6653t6d/fjqD8/D1HOft/PEsWH8w7+dw5Vdfuzd2V9Y98gLw3jg9oGSbQ/sHkD37M32mWdfw/7Z97/yg/Ml25bvZ+/OfnT6DWzp9ONvn30NR14YxsfuGCxZv8NvVCzLH1P++3znZTHnfbHlEFFryN/zR14YRixtQVOAA7tLc5kiUMhf+WXFOSufc4qXdQY8+KPbrqnY5souP77wL6fR7jOw79ZthZyY/7l43au6A7hufbhqPiqu9z039zNnrSLbev04uLu0fTu4exDbelfumjZbnZqtPs3WdxjoC+HBPaXnp7i/Vy+Nug7V6l+cXz92xyC6g56S/FfetzzywnBF3j6wewBPHBsuef3Ic6cqcqiuouK4quX8A7sHoCm5+uavf6183t8dqDj/zRY3jdIMx7nQWC2OvbnGK0deGMb+XZXx9bfPvgZTV7Dv1m1F46fSuNu/q/T1fGOx1RgTVNty5e9Gabb2ebFavf7Nbqnxfd0VYRwsmwM6eMcgtl8Rnne9/bdfytEP7hks5OF//OE5HNw9WHVMtbnTXzHntHdnPzp8RmG+aaAvjKCpYv/tA3P2S/L9Fyubxd6d/VX3t//2AWRlFgfLxqLFdc/3geaaS7OybkUfaP/tA/jcc6fw8V+4Dp1+o+S9P//lG7B9Q/UxZzULbasaPV4VVeZyL78wIR4D8FUp5efKlv9HAHdJKXfXYR9vA/BBKeWuudbbsWOHPHr0aMmy/JP9xmJpdAfNkqchVls+l+KnCeqqgljaQrvfg4G+cNUn5I7F0uj0e5B2shieTqE3bOLqriBeGY9hJJLG1i4vYuncUxvTtougqUJXFbgSiMw+5dFxszA0DUk7i2Q6i/aADilzT/LtDnkACUwlLHQEDOiKgtFYBl5DhaYAhqpAUxWcn06hK+BBu1/FdCqL6YQNU1cQMnVc0x3Ehdl/r/YZKqysC0NVYGddtBc9PXKxLuf8trhFHVy1WF3L9vz6+2G+6T0ly9Lf/Twee+Svlq2MattfTj2aXMPiNH/PTyUyCHlVpDISKSeLmaSNkKnBb2hwXBfW7BNfe0ImJCTGYxl0BjxIWDYCho6slIimHLT7dEQyNgKGBl1VMB6z4DWU3BNvHQeaoiI2+yRbAYGJRAbrfDq8moqRaKaQ417fm3t6b618VFxvvc5Pf6UlWXKsNuOTsputTs1Wn2brO+SfBj4SSaM3bFb092Y1baw6jouhCxFcjKbRFfDAhcRoNIPuoAd961SMR3N9UNeVMA0V0ZSN7qAJx3Vzudub+w+NlJ1br8NvwMpmoasqEhkbAY8OVQUytkQ842CdV0fCcuDVNfSEPHBcB1PxLEZjGfSGPFAEMJXM5e3ppI11Xh29IQOvaw8U+uanJxI4N5VAyNQhRK6/6/doaPfpuLqn+tPYmy1uGqUOx7lssZqPveFICuvDXlhZFxPxDLqCJrKui0jKQdib6xcoQkEkZaMz4IGmAGMxC+1+HXbWRSydxTqfDsvJwtRVzCRtrPMZUBUg62K2PzH3WGw1x8QqtuRYXWD+blrN1j4vVqvXfxEWHKv1HP8vNb4tK4tjFyIYjabREzKx/YpwycPoqq3XGzLRETAwEs3l1Y1tPpybThbybGdAw49HEpienceaTloIe/Xc2M3OwnJcxDNZBDwqQqaOtJMtmW9yXYl/n05gNJJBZHaMF0/baPMZSNpZRFMOuoIevL4ngLMzScQzWaSsLKSU8BkaxuMZtPkM6KqA36PCqykYi9kYi2fQGTDg0RSMRTPoCHhgaoDlAEkni+RsnXyGhrFYBj5DRcCjwaMJJK1sYezaHfTAzmYR9Oq4uiuEC9EURqMZJC0HG9v92NKZm6RdTNuz0LaqDuPVmivVe3J4PYCvAkgB+AFyfy38UwC8AH5BSjlct53NgxNutII4ObwEnBxeNoxTahWMVWoVjFVqFYxVahWMVWoVKzI5TLRINeNUq+deZid/f1oIcTOAgdkdf01K+XQ990NERERERERERERES1PXyeE8KeUzAJ5pRNlEREREREREREREtHSt82E7RERERERERERERFQ3nBwmIiIiIiIiIiIiWoM4OUxERERERERERES0BnFymIiIiIiIiIiIiGgN4uQwERERERERERER0RrEyWEiIiIiIiIiIiKiNUhb6QqsJNeVODOZwGg0jZ6Qic0dfiiKuOxtAdQsr3j9vrCJrAuMxdLoDprQVGA0mkEkZcNvqPBoKkxDQdpykbQdtPkMJCwHliORtrPY2uHHlq4AAOD0RAJnpxLwGxp6Qh5sbC+th8/QYGWz6PB75q0jEVGjOI6LoYsRTCYyCJkGXFdCVQQmExb8hgpdEzBUFVlXYiyeQcijoc2vw3Yk4paDjO2iM+hBxrmUzxRFlOTWfL7rCnjgZCXOTSdLciNz3dqVTFk4PhLDaDSDnpAHg71B+LwG69TE9cnnjIuRNPrCXgz0haBpq/9vGhpxHVxX5vqLkwmYhgKPqqIjYBTyYnEe7Q6aUBXgYqR2XzaesZGxXUynbLR5c3m6J1x7u+Jtm73/uZL1bJVzlFcrVuc6juJYDHhVCCkQSdkIeXX0hDyYjFsYjWawzqch4NExGk3Do6to8+nY1hXE+UiqZc4PUb3MpNI4MZIo3Gvbev1Y5zVXuloL1mz9Cyq10Lan2nquK/HySBTTSQtJK4uekAcDvWEYhrrgsmuVW94HVBQxZ1muK3F2MoGxWBozSRs+Q0PI1GC5Ljr8HmwIe/HyaHTN9SsXY81ODruuxJNDI9j36PNI2y5MXcGhu27AbQO983Y0qm37l7/6E7AcWbU8AIX123wG7v6ZTXjo6ZNI2y42dXjxO2+9CgeODBW227uzH35DhaIIeDQFp8cTSFjZwjamruAvfiW3vz/4h+dLtnv9FUEkMm5JPe65uR9fPnoOH931+pp1ZOeKiBrFcVw89sIw/uKZk3jXjo348tFzeNeOjXj4mUs5bd+t29AV9ODDX32xsOwj77wGHl3F/sOX8uO9t2zDF79/Fv/ltmvx9mt78PWXR0ty2odvuwaOlPjEP79Skhv7ewK4+eoe5ro1KJmy8MTxUdx/+HghJg7uHsSuwZ4VG5w0W52arT75nHHfY5fq8+CeQey5fv2q7sg34jpU67Pm+5lXtMXxtv7uijy6d2c/Pve9s5hOWhV92cd+dA47r+3DX33r1Yo8Xm27/OTz5fa5l9NK1rNVzlFerVj9D4Pd+ParU4seD+W2H8CnvvUqzk6mKuJp785+nJpI4M+//krh/WY+P0T1MpNK4+vHxyvutbcPdrXEBHGz9S+o1ELbnlrzXykri/PTqZJc/uCeQey+7gpomjJv2dXK/fNfvgGudPGh/3OspMyuoIH/3+d/WLUs15V45pVRnJ1MVowBfbqKI8eGcddPbcL9j6+tfuVirdkzcWYyUQhCAEjbuQnVM5OJy9r22PlIzfKK17/zxg2FmwcAdm1fX5gYzm/30NMnMZGwMBbLwKtrmEhYJdukbRcvDkcKE8PF28VS2Yp6PPzMSezavn7OOhIRNcrQxQjue+w4dm1fX8hH+QkFIJeLDj11AqcnEiXLJhJWYWI4v+yT3ziBXdvXY9+jz2PoYmVOm0xahU5BftlDT5/EsfMR5ro16vhIrDAoAXIxcf/h4zg+EmOdmrQ++ZxRXJ/7HjuOoYuRFanPcmnEdajWZ833M4+dj1TNow89fRJ33rihal/21964BfsPD1XN49W2q1WHZux/rmQ9W+Uc5dWK1aGR+GWNh3Lb5+Iq/7o4nh56+iReHYuXvN/M54eoXk6MJKreaydGWiP2m61/QaUW2vbUmv86ORavyOX3PXYcxy5EFlR2tXX+4B+ex8mxeEWZsVS2ZllnJhM4dj5SdQw4mbRw901bCxPDxWWu9n7lYq3ZyeHRaLoQHHlp28VYLH1Z27oSNcsrXl+I0vXKX+e3c2WuzETGqVp2rf0lLKfqciHmriMRUaNcjKQLeaj4e7F83itWK2flt8+Xu5BtXAnmujVqNJqpGhOj0cwK1aj56tRs9al2b6dtFyOR1X0PN+I61Orv5vuZtc61EJd+Lu7LTifsOfN4+XZz1aHZcvJK1rNVzlHeXLF6OeOh/HpCVH+dj9ny95v1/BDVS7O1z4vV6vVf7Rba9tSa/6o17hqNphdU9lx9lPJlCcupWdZoND3nGDBVY45stfcrF2vNTg73hEyYeunhm7qC7uD8/55RbVtVoGZ55etXW6/8tSIARQB+U6tadq39+Q2t6nIp564jEVGj9IW9hdxT/j0vn/eK1cpZUua+94UXnosVAea6Naon5KkaEz0hzwrVqPnq1Gz1Kc4ZxfXpDa/ue7gR16FWfzffz6x1rqW89HNxX7bdr8+Zx8u3m6sOzZaTV7KerXKO8uaK1aWMh6Ss/jofs+XvN+v5IaqXZmufF6vV67/aLbTtqTX/VWvc1ROqzPnVyp6rj1K+zG9oFcuK+xlzjQF9NebIVnu/crHW7OTw5g4/Dt11Q0kH99BdNxQe2rbYba/bEK5ZXvH6X/nBeezd2V9Y78gLw9h/+0DJdnt39qPTb6A76EHKctDhN0q2MXUFg+vD+PNfvqFiu6BXrajHPTf344ljw3PWkYioUQb6QnhwzyCOvDCMe27uL3wvzkX7bt2GLZ3+kmUdfgMHdpfmx3tv2YYnjg3j0F03YKCvMqe1+wx86B1XV+TG7RvCzHVr1GBvEAd3D5bExMHdgxjsDbJOTVqffM4ors+DewYx0Bdekfosl0Zch2p91nw/c/uGMAb6QlXf/+oPz1fty/79v5zGgd0DVfN4te1q1aEZ+58rWc9WOUd5tWJ1oDdwWeOh3PYDeOLYcOF1cTzt3dmPq7oDJe838/khqpdtvf6q99q23taI/WbrX1CphbY9tea/ruoOVOTyB/cMYvsV4QWVXW2dP//lG9DfHagoM+hVa5a1ucOP6zaEq44BO3wGHnnuFA7esfb6lYslpJTzr9WCduzYIY8ePTrnOvknI47Fck9nXsxTb6ttC6BmecXr94ZMZF1gPJ5GV8CEpgJj0QwiKRteQ4Wp5QI/bbtI2Q7W+QwkLAeWI5Gxs9jc4cfWrgAA4PREAuemEvAZGnpCHmxsv1SP0WgaPkOFnXXR7vfMW0eqm0Wd0IXE6lqy59ffD/NN7ylZlv7u5/HYI3+1bGVU2/5y6tHkljVOHcfF0MUIphIZBE0DrpRQhcBUwoLXUKFrAqaqwnElxuMZBDwa2vw6HEcibjnI2C46AwasonyWfwBBeb7rDHjgZCX+fTpZkhuZ61rWkmO1GZ+U3Wx1arb65HPGSCSN3rCJgb5wKzw0pClj1XVlob9oaApMTUVHwCjkxeI+alfAhKoAI9HafdlEJvfREtMpG21eHXZW5v5qp8Z2xds2e/9zJeu5zPtuWKzOdRzFsejzqFAgEEnZCHt1dIc8mIxbGI1lEDY1BE0do9E0PLqKNp+ObV1BnI+kmj6GqO7W/LhqJpXGiZFE4V7b1utviYfR5TVb/6KBFhyrzRSnC217qq3nuhIvj0QxnbSQtLLoDnow2BeGYagLLrtWueV9QEURc5bluhJnJxMYj6Uxk3Tg9agIejTYrosOvwcbwl68PBpttX5lI9SM0zU9OUzUIGu+E7MUnBxeNoxTahWMVWoVjFVqFYxVahWMVWoVLTk5TGtOzThdk1PlRERERERERERERGsdJ4eJiIiIiIiIiIiI1iBODhMRERERERERERGtQZwcJiIiIiIiIiIiIlqDtJWuABHRavSBD34Yw+ORkmXru8L41J/9yQrViIiIiIiIiIioFCeHiYgaYHg8AvNN7yld9t3Pr1BtiIiIiIiIiIgq8WMliIiIiIiIiIiIiNYgTg4TERERERERERERrUEtMTkshHidEOKbQoiXhRBDQoi9K10nIiIiIiIiIiIiolbWKp857AD4AynlD4UQQQA/EEI8JaV8aTGFuK7EmckERqNp9IRMbO7wQ1FEfSvquBi6GMHFSBp9YS8G+kLQtJaYgyciumzF+dVnaLCyWXT4PRV5djnyMFG5Zow79heomuWI1bn20Yz3CrUW15U4N5XAaDSDhOVgU7sfm9p9ODedZFzRimj1vMb+ArWaetxzl1NGq9/rK60lJoellBcBXJz9OSaEeBnAegALnhx2XYknh0aw79HnkbZdmLqCQ3fdgNsGeusWMI7j4rEXhnHfY8cL+3hwzyD2XL+eCZyIVq1q+fWem/vx5aPn8F9uu7aQZ5cjDxOVa8a4Y3+BqlmOWJ1rHwCa7l6h1uK6Es+8MoqTo3E89PTJkvz2F8+cxNnJFOOKllUz9gEWg/0FajX1uOcup4xWv9ebQctlFCHEZgA/AeBfF7PdmclEIVAAIG272Pfo8zgzmahb3YYuRgqJO7+P+x47jqGLkbrtg4io2VTLrw8/cxK7tq8vybPLkYeJyjVj3LG/QNUsR6zOtY9mvFeotZyZTODY+UhhYhi4lN92bV9feM24ouXS6nmN/QVqNfW45y6njFa/15tBS00OCyECAL4C4D9LKaNV3n+fEOKoEOLo+Ph4yXuj0XQhUPLStouxWLpu9bsYqb6PkUj99kGrw1yxStQsFhqntfKrEKV5djnyMK1NK93+Lxb7C2vXSsfqXPtoxnuFVs7l9FVHo2m4EjX7BMWvGVdULyudVxuJ/YXVY62M/+txz11OGa1+rzeDlpkcFkLoyE0Mf0FK+dVq60gpPy2l3CGl3NHV1VXyXk/IhKmXHq6pK+gOmnWrY1/YW3UfveH67YNWh7lilahZLDROa+VXKUvz7HLkYVqbVrr9Xyz2F9aulY7VufbRjPcKrZzL6av2hEyoAjX7BMWvGVdULyudVxuJ/YXVY62M/+txz11OGa1+rzeDlpgcFkIIAP8TwMtSykOXU8bmDj8O3XVDIWDyn0GyucNft3oO9IXw4J7Bkn08uGcQA33huu2DqJl94IMfxp5ff3/F1wc++OGVrho1ULX8es/N/Xji2HBJnl2OPExUrhnjjv0FqmY5YnWufTTjvUKtZXOHH9dtCGPvzv6K/PbEseHCa8YVLZdWz2vsL1Crqcc9dzlltPq93gxa4oF0AN4E4D0AXhRCPD+77CNSyv+70AIUReC2gV5cc8+bMRZLoztY/6cXapqCPdevR393ACORNHrDJgb6wvyweFozhscjMN/0nsrl3/38CtSGlktxfh2NpuEzVNhZF7cN9pbk2eXIw0TlmjHu2F+gapYjVufbR7PdK9RaFEXg5qt7cFVXADdubEPScrCx3Y9N7T7cuLGNcUXLrhn7AIvB/gK1mnrcc5dTRqvf682gJSaHpZTfAbDkq6ooAlu7AtjaFahDrarTNAXXv64N17+uYbsgImo6C82vy5GHico1Y9yxv0DVLEeszrWPZrxXqLUoisDmzgA2d5bGEOOKVkqr5zX2F6jV1OOeu5wyWv1eX2n8lRMRERERERERERHRGsTJYSIiIiIiIiIiIqI1iJPDRERERERERERERGsQJ4eJiIiIiIiIiIiI1iBODhMRERERERERERGtQZwcJiIiIiIiIiIiIlqDODlMREREREREREREtAZxcpiIiIiIiIiIiIhoDdJWugLNwHUlzkwmMBpNoydkYnOHH4oimqY8IqJmtZR8x1xJy8VxXAxdjOBiJI2+sBcDfSFoGn8/Ts2HsUqtYqltOPsAtFxaPdZavf60di1H7PL+qJ81PznsuhJPDo1g36PPI227MHUFh+66AbcN9F5WUNW7PCKiZrWUfMdcScvFcVw89sIw7nvseCHWHtwziD3Xr+ekGzUVxiq1iqW24ewD0HJp9Vhr9frT2rUcscv7o77WfE/zzGSiEEwAkLZd7Hv0eZyZTDRFeUREzWop+Y65kpbL0MVIYbINyMXafY8dx9DFyArXjKgUY5VaxVLbcPYBaLm0eqy1ev1p7VqO2OX9UV9r/i+HR6PpQjDlpW0XY7E0tnYFVrw8Ilq7PvDBD2N4vHRSYH1XGJ/6sz9ZoRqVWkq+Y66k5XIxUj3WRiJpXP+6FaoUURWMVWoVS23D2Qeg5dLqsdbq9ae1azlil/dHfa35yeGekAlTV0qCytQVdAfNpiiPiNau4fEIzDe9p3TZdz+/QrWptJR8x1xJy6Uv7K0aa71hxho1F8YqtYqltuHsA9ByafVYa/X609q1HLHL+6O+1vzHSmzu8OPQXTfA1HOnIv85JZs7/E1RHhFRs1pKvmOupOUy0BfCg3sGS2LtwT2DGOgLr3DNiEoxVqlVLLUNZx+Alkurx1qr15/WruWIXd4f9bXm/3JYUQRuG+jFNfe8GWOxNLqDS3vCYb3LIyJqVkvJd8yVtFw0TcGe69ejvzuAkUgavWETA31hPuCLmg5jlVrFUttw9gFoubR6rLV6/WntWo7Y5f1RX2t+chjIBdXWrkDdPpek3uURLZdm/4xbqm2lrt1S8h1zJS0XTVNw/eva+Lmt1PQYq9QqltqGsw9Ay6XVY63V609r13LELu+P+uHkMBEVNPtn3FJtvHZEREREREREtFj8PzUiIiIiIiIiIiKiNYh/OUzUxBbzUQH8SAgiIiIiIiIiIloMIaVc6To0hBBiHMDZFaxCJ4CJFdz/UrDuSzMhpbxtoSs3OFZX+nxw/827/2aK05Wy0tenUVbbcdUzVpvx3DRbnVifuS1XXm22414KHkvzYazmtHLdgdau/0Lrzli9hPVfWfPVf8Gx2qTjqla/PuVW2/EA9TmmmnG6aieHV5oQ4qiUcsdK1+NysO6rx0qfD+5/be+/2a3W87Naj6semvHcNFudWJ+5LVd9mu24l4LHsrq18jlp5boDrV3/lah7K58vgPVfaa1e//mstuNbbccDNP6Y+JnDRERERERERERERGsQJ4eJiIiIiIiIiIiI1iBODjfOp1e6AkvAuq8eK30+uP+1vf9mt1rPz2o9rnpoxnPTbHVifea2XPVptuNeCh7L6tbK56SV6w60dv1Xou6tfL4A1n+ltXr957Pajm+1HQ/Q4GPiZw4TERERERERERERrUH8y2EiIiIiIiIiIiKiNYiTw0RERERERERERERr0KqdHL7tttskAH7xayW+FoWxyq8V+loUxim/VvBrURir/FrBr0VhrPJrBb8WhbHKrxX8WhTGKr9W8GvBGKf8WsGvmlbt5PDExMRKV4FoQRir1AoYp9QqGKvUKhir1CoYq9QqGKvUChin1IxW7eQwEREREREREREREdXGyWEiIiIiIiIiIiKiNYiTw0RERERERERERERrkLbSFaDm4LoSZyYTGI2m0RMysbnDD0URK10tIroMvJ+JaLGYN4hWB97L1CoYq2sDrzNRY9XrHuPkMMF1JZ4cGsG+R59H2nZh6goO3XUDbhvoZeImajG8n4losZg3iFYH3svUKhirawOvM1Fj1fMe48dKEM5MJgrBBABp28W+R5/HmcnECteMiBaL9zMRLRbzBtHqwHuZWgVjdW3gdSZqrHreY5wcJoxG04VgykvbLsZi6RWqERFdLt7PRLRYzBtEqwPvZWoVjNW1gdeZqLHqeY9xcpjQEzJh6qWhYOoKuoPmCtWIiC4X72ciWizmDaLVgfcytQrG6trA60zUWPW8xzg5TNjc4cehu24oBFX+c0o2d/hXuGZEtFi8n4losZg3iFYH3svUKhirawOvM1Fj1fMe4wPpCIoicNtAL665580Yi6XRHeRTRIlaFe9nIlos5g2i1YH3MrUKxurawOtM1Fj1vMc4OUwAckG1tSuArV2Bla4KES0R72ciWizmDaLVgfcytQrG6trA60zUWPW6x/ixEkRERERERERERERrECeHiYiIiIiIiIiIiNYgTg4TERERERERERERrUGcHCYiIiIiIiIiIiJagzg5TERERERERERERLQGcXKYiIiIiIiIiIiIaA3i5DARERERERERERHRGsTJYSIiIiIiIiIiIqI1iJPDRERERERERERERGtQQyeHhRBnhBAvCiGeF0IcnV3WLoR4SghxcvZ7W9H6HxZCvCqEeEUI8Y6i5T85W86rQoiHhRCikfUmIiIiIiIiIiIiWu2W4y+Hf05KeYOUcsfs6z8C8LSUsh/A07OvIYR4PYB3AxgAcBuAvxJCqLPb/DWA9wHon/26bRnqTURERERERERERLRqrcTHStwB4JHZnx8BsKdo+ZeklBkp5WkArwJ4gxCiD0BISvk9KaUE8LmibYiIiIiIiIiIiIjoMjR6clgC+LoQ4gdCiPfNLuuRUl4EgNnv3bPL1wP496Jtz88uWz/7c/lyIiIiIiIiIiIiIrpMjZ4cfpOU8kYA7wTwASHEW+ZYt9rnCMs5llcWIMT7hBBHhRBHx8fHF19bomXCWKVWwDilVsFYpVbBWKVWwVilVsFYpVbAOKVm19DJYSnlhdnvYwD+EcAbAIzOflQEZr+Pza5+HsDrijbfAODC7PINVZZX29+npZQ7pJQ7urq66nkoRHXFWKVWwDilVsFYpVbBWKVWwVilVsFYpVbAOKVm17DJYSGEXwgRzP8M4O0AjgM4DODXZ1f7dQCPz/58GMC7hRAeIcQW5B489/3Zj56ICSHeKIQQAO4u2oaIiIiIiIiIiIiILoPWwLJ7APxjbj4XGoAvSimfFEL8G4BHhRC/DeAcgF8GACnlkBDiUQAvAXAAfEBKmZ0t63cB/B0AL4CvzX4RERERERERERER0WVq2OSwlPIUgOurLJ8EsLPGNn8M4I+rLD8KYLDedSQiIiIiIiIiIiJaqxr9QDoiIiIiIiIiIiIiakKN/FgJWiVcV+LMZAKj0TR6QiY2d/ihKGKlq0VENfCeJaJWxzxGjcT4ouXCWCNqbbyHqZnVMz45OUxzcl2JJ4dGsO/R55G2XZi6gkN33YDbBnqZFImaEO9ZImp1zGPUSIwvWi6MNaLWxnuYmlm945MfK0FzOjOZKAQbAKRtF/sefR5nJhMrXDMiqob3LBG1OuYxaiTGFy0XxhpRa+M9TM2s3vHJyWGa02g0XQi2vLTtYiyWXqEaEdFceM8SUatjHqNGYnzRcmGsEbU23sPUzOodn5wcpjn1hEyYemmYmLqC7qC5QjUiornwniWiVsc8Ro3E+KLlwlgjam28h6mZ1Ts++ZnDNKfNHX4cuuuGis8x2dzhX+mqLTt+GD21gs0dfvzlr/4Ejp2PwJWAKoDrNoTX5D1LRK2JeYzqoVa/jX1bWqil9v0Za0Stjf0RWgkLbXvq3cZwcpjmpCgCtw304pp73oyxWBrdwbU5KcoPo6dWYjkSn372VEmsEhG1EuYxWor5+m3s29J86tH3Z6wRtT72R2g5LabtqXcbw4+VoHkpisDWrgDeuLUTW7sCa7JDww+jp1bBWCWiVsc8Rks1Xwyxb0vzqVceYqwRtS72R2i5LTbm6tnGcHKYaAH4YfTUKhirRNTqmMdoqRhDtFSMISJiHqDltpIxx8lhogXgh9FTq2CsElGrYx6jpWIM0VIxhoiIeYCW20rGHCeHiRYg/2Hf+RuVD5SgZsVYJaJWxzxGS1Uthj7+C9dBEbnP8yOaT7UY+tNf3I6Nbb4VrhkRLRf2R2i5uK7EqfE4JhMZ/Okvbl+RmOMD6YgWyNAE3veWrXAloIjca6JmxFglolbHPEZLkX9Iy9W//2a8PBLFidEYPvHPr2A6afGBwrQgiiLw9mt78On37MDRs1PIusChp16BriqMH6I1hP0RarTyh9Bt6vDi0+/ZAV0V6Akt34NMOTlMtABnJhP4vS/+qOTzX0xdwf+9583Y2hVYwZoRlWKsElGrYx6jelAUASGAD/7DCyWxtO/R53ENY4kW4Nx0Eu/7/FHGD9Eaxf4ILYfyh9CdnUzhfZ8/uuxxxo+VIFoAfhg9tQrGKhG1OuYxqhfGEi0F44dobWMOoOXQLHHGyWGiBeCH0VOrYKwSUatjHqN6YSzRUjB+iNY25gBaDs0SZ5wcJloAfhg9tQrGKhG1OuYxqhfGEi0F44dobWMOoOXQLHHGzxwmWoD8g02uuefNGIul0R1cvg8GJ1oMxioRtTrmMaoXxhItBeOHaG1jDqDl0CxxxslhogVSFIGtXQF++Dw1PcYqEbU65jGqF8YSLQXjh2htYw6g5dAMcdbwj5UQQqhCiB8JIZ6Yfd0uhHhKCHFy9ntb0bofFkK8KoR4RQjxjqLlPymEeHH2vYeFEPxVDREREREREREREdESLMdnDu8F8HLR6z8C8LSUsh/A07OvIYR4PYB3AxgAcBuAvxJCqLPb/DWA9wHon/26bRnqTURERERERERERLRqNXRyWAixAcB/APC3RYvvAPDI7M+PANhTtPxLUsqMlPI0gFcBvEEI0QcgJKX8npRSAvhc0TZEREREREREREREdBka/ZfD/wPAHwJwi5b1SCkvAsDs9+7Z5esB/HvReudnl62f/bl8ORERERERERERERFdpoZNDgshdgEYk1L+YKGbVFkm51hebZ/vE0IcFUIcHR8fX+BuiZYfY5VaAeOUWgVjlVoFY5VaBWOVWgVjlVoB45SaXSP/cvhNAHYLIc4A+BKAm4UQfw9gdPajIjD7fWx2/fMAXle0/QYAF2aXb6iyvIKU8tNSyh1Syh1dXV31PBaiumKsUitgnFKrYKxSq2CsUqtgrFKrYKxSK2CcUrNr2OSwlPLDUsoNUsrNyD1o7hkp5X8EcBjAr8+u9usAHp/9+TCAdwshPEKILcg9eO77sx89ERNCvFEIIQDcXbQNEREREREREREREV0GbQX2+d8APCqE+G0A5wD8MgBIKYeEEI8CeAmAA+ADUsrs7Da/C+DvAHgBfG32i4iIiIiIiIiIiIgu07JMDkspvwXgW7M/TwLYWWO9Pwbwx1WWHwUw2LgaEhEREREREREREa0tjfzMYSIiIiIiIiIiIiJqUgv+y2EhRBtynwNs5pdJKZ9tRKWIiIiIiIiIiIiIqLEWNDkshHgvgL0ANgB4HsAbAXwPwM0NqxnRMnNdiTOTCYxG0+gJmdjc4YeiiJWuFtGiMZaJqNUxj9FSMH6oFsYGES0GcwYtl5WOtYX+5fBeAD8F4F+klD8nhLgGwIHGVYtoaRZ7Y7muxJNDI9j36PNI2y5MXcGhu27AbQO9TP7UUhjLRNTqmMdoKWrFz+v7grgY4eC+1dRzsMzcQrT8VnrCaylWQ85o5fO/ljRDrC30M4fTUso0AAghPFLKHwO4unHVIrp8+Rvr5x/+f/iVz/wrfv7h/4cnh0bgurLmNmcmE4UbEQDStot9jz6PM5OJ5ao2UV2cnqgey6cnGMtE1BqYx2gpavXpvvqj4QX3C6k5XE6ffi7s7xMtr3rfw8ut1XNGq5//taQZYm2hk8PnhRDrADwG4CkhxOMALjSqUkRLcTk31mg0XVg/L227GIulG1pXono7O5WoGsvnplqjE0NExDxGS1GrT5cfC7fa4H4tq/dgmf19ouXVDBNeS9HqOaPVz/9a0gyxtqDJYSnlL0gpZ6SUDwD4KID/CWBPA+tFa4DrSpwaj+N7r03g1Hi8br/BupwbqydkwtRLbwdTV9AdNGtsQatZo2JzOfgNrWos+4wFP3+UiGhFMY/RUtTq08nZprwvbOK3f3YrTozGWq6NX2sW2qdfaL+N/X2i5dUME15L0Ww5Y7Fj1FY//2tJM8TagnvZQoifBdAvpfysEKILwHoApxtWM1rVLuczVRb6eTn5G6s4Ec53Y23u8OPQXTdU1Gdzh3/pB0stpR6f97OSn+3UE/Jg785+PPT0yUL99+7sR0/Isyz7JyJaqt6wB39y53U4PZGAKwFVAJs7/egNM4/R/Kr16fbu7MfnvncWfWET73njJjz8zMnLauP52Y31Nd/5XEiffjH9Nvb3iZbX5YzLm8nGNh8+8UvbcXIsXuiPXNUdwMY237LX5XLGqK16/tdiW9sM7dOCJoeFEPsB7EDuc4Y/C0AH8PcA3tS4qtFqVutfHK65583Y2hWoWL/RHT9FEbhtoBfX3PNmjMXS6A6ujSRElRYbm+VW+sPkN7b70d8TwPveshWuBBQB9PcEsLGdAx8iag2uC4zHMvj0s6cKeXTfrdvguvNvS1Tep+sKmDg9Gcd00sJv/+zWwsQwsLg2fqXb99VmIedzIX36xfTb2N8nWl7NMOG1FOdnkrgYSVf0R87PJLG5c/5xYT1dzhi1Fc//Wm1rm6F9WuhfDv8CgJ8A8EMAkFJeEEIEG1Yramr1+E3OXP/iUC25LUfHT1EEtnYFFjQBSM1tKTG62Ngst9TJ5aVSFIGbr+7B1s4ABz5Es9biXyC0srFYBoeeOlGSRw89dQLXb1iHLau8jWas1kd5n25Lpx//954348Ro7LLb+JVu31ebhZzPhfTpJxMZ/PbPboWYXfSVH5zHxUi65jVlf59o+SiKwNuv7cGX3/dGXIyk0Rf2YqAv1DLt2mi0dn9kuSeHL2eM2ugJx0b0WdZyW7vS7dNCJ4ctKaUUQkgAEEI0768aqKHq9Zucxf6Lw2KT4UrfWLRylhqjS/33m6VOLtcD45/okrX6FwitLGE5VfNo0nJWqEbLg7HaOPl2EcBlt/HN0L6vJgs9n3P1aVxX4sJMGv/zO5f+qu+em/vx5aPnmv7fponWAteV+PrLoy3brjVTf+Ryx6iNGhc2qs/CtnblLOiBdAAeFUL8fwDWCSH+E4BvAPhM46pFzapeT7zM/4tD/kO35/sXh2b4gG5qDUuN0cXGZjnGKlFz4ZOaW8+mdn/VPLraPx6Hsdp4S2nj2b7XVz3O55nJBP7LV46V3DMPP3MSH7vjuqb+t2mitaLV27Vm6o8sdYxab426tmxrV868fzkshBAAvgzgGgBR5D53+H4p5VMNrhs1oXr9Jmex/+JQj8/L4b9qrg1LjdGl/vtNK362E9Fqxr9AaD1bOv3481++AX/wD5fy6J//8g3Y0rm68yhjtXGK+4BX9wTx5N43YyS6uDae7Xt91eN81rpnvIbCPj9RE2j1dq2Z+iPN8Jm0xRp1bdnWzq2Rc1rzTg7PfpzEY1LKnwTACeE1rp5PvFzMvzhUS4Yb23yFG8NnaLCyWXT4PVVvEP6r5tpRjxhd6r/f+D0K/uyXrkci48BvavB7FvpPGkRUb636pObl1my/QA2YpXk0YK7+PLoWYnWxcVaPuKxXH7DZBuatrh7ns9o9s6nDiwszabznf35/zuu93Dmv2XIs0XLoCZnY1OHFru3rC58LfuSF4ZZq1zy6KHnQt0dfufu2mT46sFF9lrXW1ha3Df9/9r48Por6fv+Z2fvO5g4JCSxJSMgFISD6A9SAim0Q5NLaolYsX1sRlKqoVRBQWxSxIrYWq/VorWDxgipVQYtWPEDlPhIgiQm5j73vmd8fm5ns7MwmEwhsAvO8Xr7Uzc7O7OxnPp/35/1+3s+TZlIjSAHNduF14lzntMRqDn9FEMQ4mqa/PeszShjUOJeVHKGgCQDvNUuSXvDBYDTGlk3L5z0gF7Ow+cWGWLPMa9qcOHzajmd3VLLnXzIlB5lm3QVvpCRBwkCExEDoHRRFY+exJuyvs4KiARkBFGWYUD4yJSbBeG278DyaFa877wYw5xMDfayebXIr2qbm6vwU1Ha4eJ/bX5ug/owBB9LG/EJAtPspdqwJPTOrZxRh4et7eL/3yLsmYUSynv3880kakUgqEi5WZJq1uKs8Bw+/e5Ad+4/NLESmWRvrSxOFU61OLHrje14C9N9h88nFinMVs1wshTSKolHb7sR3tZ146J0DMGuVuPnSLE7sG7lOnOucltjk8JUA/o8giBoATgAEQqTi4rO+AgmDCueqkiMUNG24aQx8AVowkBJ6MNbvrMSCiRbBB2Swt7RIEI+zHaNnG8CftrrZSR0IjbNnd1SiOMMkJYclSIgBLjYGwpmgtt2JyiYHNu46yUnGZifpY5KMbbJ5BefR0kzzBZ0cHshjtT+SW9E2NRvnl7HJvN5ivTPZBEkx4OBCX8aa0DMT7fc+0mjD8MTQ83S+SSMSSUXCxYqadhebGAZCY//hdw9izFDzoEiu1rQ5BeeT2nbnoLj+c4lzEbNcLIU05nsebbSxsfes0gxe7Bu5TpzreEZsj961AEYAKAcwHUBF178lXIRgqvwTLImwJOn75UEVCpr211mjipxHezAIovsBoSgaJ1sc2H2iFVqlHFkJGs77L7RWTQndOJsxerbi+g6vsKut0xMUfQ3hY/dkiwMURYs+VoIECXyci3XrQkK0ZGyTzRuT67F5/ILzqM3jj8n1nE8M1LHaH8Yz0WK3PTXtfYr1mu0e0eekKBpapQyLp2RjUXk20kyhuE+KAQcu+jrWIp+ZaGZGx5vsqG5zsqy0sx1bfUF/jGUJEgYjatqjJ1cHA9RKElkJGtx5ZWgNWVSejawEDZTyC1/qSgz6O2YZ7AaGYsF8T4oG+12ZPFY4IteJaOtbqlHdL7kDUcxhmqZrmP8mCEIHYCaAmwD89IzOKmFQozeq/5m0AggFTeEPCwPmAYmmcUPT3Q9IZNXpsZmFeG5nJWra3AOuVVMCF7FsJznbipxRoxAcmwaNuEaNi6ViKkHC+cTF0qJ2pnD6hItaLl8gJtdj1grPo2atIibXcz4xUMdqf7BVosVuQe7H9hrr9ZbUZe5hm9OL050eLNuyX1CCTIoBBybEjrVoz0qmWYs//2Isvq/tAEWH9E1vKMvE61/VYHJOIo422nGs0XZe9b0vBj1xCRKEoFPKBce+Vim2gT220CnkuHtqLk61OlnZrbun5kI/SK7/fONsY5gziTUGatzUE8K/Z/jz0ds6ISTlseGmMTjcYO+X3IGoUU0QhBLATxBKCE8DsAXAC306k4QLAoEAhX8fbOAE2uGD70wTW0JBk4yI/oAIPRhMwL9u3mgEKfCqTg+/exCbFk6A2x8cUK2aEriIdXL0bI0TUvUqLL0qF+s+Ps5e/9KrcpFiUIk6Xmo9lCChfxHrOWUwIMusFZz3hsZIE1CtkGHJlBye5rBaIYvJ9ZwvDOSx2h/JLaHYbc3sYqz7+BjnfT3FemtmF/eoVRl+DxdMtOClL07yJMg2LZyAovS4mN9TCVwwG3y3P4glU7KxeU8dGqwhxlTkWOtJv/qjI02c1x+pGIVN39Siw+WDQkZi6eYfYNYqsbg8B+t3crUdz1XBYKDriUuQcK6QbBDeFyWL3BfFGnIZgUarhye7lXuRS0oIIXxeNmuVmFuWgdxkA/LTjKykT2/oa6wxkOOmnsB8zy1769i1aMveOl7sG7lOCEl50DTw0+c+75fcQY/JYYIgrgLwMwDXAPgUwOsAxtM0/cvePpggCDWAXQBUXef5F03TKwiCiAewCcAwANUA5tE03dF1zIMAFgAIAlhM0/R/ul4fC+AVABoAHwBYQtO01Gd9nkFRNL482cYmhgH+4DvTxJZQ0FSUYYoaSIU/GE02D7RKGfxBCtMKUzEsQYevT7UJVp3c/iAmWBLP3U2ScNaIdXL0bI0TCJKAVinjuNpqlTLRC5SkjShBQv8i1nPKYIBcTuCOy7Oxcushdt5bMb0ACnlsAmu7J4DXdtdgwUQLCAKgaeC13TUYPTQuJtdzvjCQx2p/JLeENjWZZi2bsBOK9a7OT8HG+WXYU9OOIAWs+/gYFDIy6sYv/B5Ga9F0+4MDetN4MUJog79kSg5e212DDpePN9aiPSubFk7gvb5622EsnGzBHVdkw+ULwuOn0GD14PWvuueYSdmJGDcs/pyNi4GsJy5BwrkESQJJBhVnX5RkUIEcJKoMDm8wqgeCBC6YedmsVWL+hCxe8U1MwravscZAjpt6Qvj3fP2rGiycbEFuigEFaUZcPSoVLY7o60SkkevuE639ljvojTn8HwCfA5hI0/QpACAI4lmRn+0FUE7TtIMgCAWALwiC+BDALAA7aJr+A0EQDwB4AMAygiBGAbgRQAGAIQA+IQgil6bpIIA/A1gI4CuEksPTAHzYly8q4exR3ebk6MIxCB98TGIrzaTGrNIMloHU7vT2ODijBU0AogZSPTlGS+1bgxexTo7WdggbJ5RmmkWdv8HqwfOfnmDHf5ACnv/0BLKTxRk7SWNXgoT+RaznlMGARquXTQwDofuzcushvPrL8chKOP/3KMWoRofLh+c/rWJfUytIpBgv7HlwII/V/kpuMbHbsAQdqtuc+LamHSNTDNi+ZBIabfzPre1wsWZ1DHra+EXeQ2k9Hdhg2MItdi9vg//sjkq8+svxSDKoeGMt2rPSYBV+fczQOFyem4zqNic7JkLxWhXUChKzxqSf80RtT/sWCRIuVDRavXjw7QO8eThW8UVfMdBktwYymHl5VmkGmxgG+paw7WuscS7jpnMpV9Hb9+yL2WF/5g56q9mMRSgh+wlBEB8TBLEAgKiePjoER9f/Krr+oQHMAPBq1+uvIqRfjK7X36Rp2tuViK4CMJ4giDQARpqmd3exhV8LO0bCeUSTzQOqS9M3HOGDj2nJnz8hCy99cRIbdlbhr5+fRH2np1dhbCFBc7Ei55EGXplmLdbNG81eq9S+NXgQTWj9fG3moi0yTTZxpiHhSY0NO6vw/KdV6HD5RF8/U0k8m7ErGdpJkNCNWM8pgwGuAbb56Y95cDBioI/V/jKeYViiP1n/OX724tf46XOf43CDHeOHJbCfy6xjx5vsUTd+Qgi/h0y75sU2jgYLwsfB51XCzCcatOBYi/aspJk0gq9ndW26L9a5RYKEWGGgxRd9RVa8TnBOyYyX5oxIMPOyGGO1ntCXWONcxU2RccpP1n+O7Yca+3VP3R8xFUXRIAngieuL+mVd65E5TNP09wC+R4jZ+/8QkphQdjGA36FpemNPxxMEIQOwF0A2gOdpmv6aIIgUmqYbuj6/gSCI5K63pyOUiGZQ1/Wav+u/I1+XcJ6RYlRj6756nkbXmtnF7OAblqDD6hlFHJaHx09h2Zb9KEo3nZNqeU+6Yx9I7VuDDrHWZdNGNU4Qp3V5ttd/tuyswaq9JEHCuUKs55TBgHidSnDei9cqY3ZNSjnBaUNVxkji4nziYhmrvbWBhq9jt0+y9IkRE34PG6webNpTi43zy6CQEYPGqOZiQeQ4ONPfOVyGotPt7fEZkuQdJEg4vxiI8UVfkBWvxWMzC3lyg1nxsfFkGMhg5uXzafh5ruKmwSBXEanxzEhT5KeK13iOhGibRZqm/wfgfwRBLAZwFUISED0mh7skIUYTBBEH4B2CIAp7eLvQ1dM9vM7/AIJYiJD8BDIzM3u6NAlngGEJOiyblo81249gwUQLZCRQlhWPyywJHKkHhYwQrBa1O70AQszMIXFqdDr9aLB5kGbSoCDNCLn8zMSHoj28H3Q9vAPlAQ6HNFajoz8C97NpA/EFg7wCyOLyHPgj7dR7uP6pI5Px9wWXoNHmQZpRjaIhpj5d/9m0HvbnYiaNUwmDBT2NVSkZ0Dt8wSCWV+Sj0eZl3bhTjCr4KXHzXn+jus2JRW98z9tYfDCAgvIzxcU8Vpm1+XiTHbdPsmDL3m7DsfA4sbrNiWONNpi1Suw61oxHKkZh9bbDojZ+F/o9PJ841zFAeKdWuCmP2N+5YIgBa+eUwOkNQKuS48VdJ/Dmt7V4/qZSvPrL8fAHgzCoFHD5g6huc7LjQJJ3uPAgxasDFwMtvugrajtceG5nJccD4bmdlaLlBsNxoY9TZv0dlWZAVoIOD71z4JwXus/Vmt8XuQqKonGq1Ymadid0SjlSjCpkxveN2HUmeYvwPX+D1YP1O6rYWPlMv7+o5DBBEO8DeBPAezRNOxHSIv6P2JPQNN1JEMRnCGkFNxEEkdbFGk4D0Nz1tjoAQ8MOywBwuuv1DIHXhc6zEV0J67KyMqmPup/BPnyphh4fPiHdk6wEDeo7PfjFS98gN1mPn12SxTG+eWxmIWaWpJ9RgrivWjPnUj9GLKSx2jPOJnA/W+Zsgk6FTXtqOUHApj21mFaYKur8gQCF9w+c5lWY+zK+z2aM9qf2kjROJQwW9DZWpWRAz0gxqlDd6uK4ca+eUYhkY2zcxJtsHpi1So53wZa9dQNCe/dscbGOVaG1eXF5Dl7/qgYNVg8nTmT+/uC0PHgCFDbuOsEhJUwYFt/jGnmh3sPzjXMdA4TvFxiDuIWTLRgzNA5ZCboeYx+KorG3ppOTfGDGy5wXdsOsVeLmS7N4ru9MLDgQ9gIS+g9SvDpwMdDii76iyeaBL9A9pAgC8AVoaV8VBSRJYFiiHpnxOoweGndeirTnYs0Xq+MbzUw1J0WP8pEpvX7ns8lbtDm9bL4CAFtwP5tYWSxz+GkANwD4PUEQ3wDYBGAbTdNRhUMIgkgC4O9KDGsATAWwBsD7AG4B8Ieuf7/Xdcj7AN4gCGIdQoZ0OQC+oWk6SBCEnSCICQC+BnAzgOf6+D0l9BPEPHxC9P5wqYnbJ4/A/f/axzGuq213YV9dJ8ZkmvvMENUqZVg8JRsU3f1QRGtdEHoAn7i+CKWZcX2q8EgYuDhb5izDkD/T9pRDDVZOhRkIVZhzkvUoGdq7s+3ZJrclQzsJEiT0Fc02HzZ8yp23NnxaieGJo5EZf/6vJ82kxp1XjkCzvZtpdOeVI5B6gRvSXcgQWpvXd62VL31xUlCSrM3lYxMKjDlhVoIGS68aiWVb9rNr5IabxmB4gh7N9nOf6AtPKqaZ1AhSOC/nvRARuV/ocPmQl2rE5bnJvd7H6jYnmxhOM6nx80syEa9XgSCAu6fmIBCk2cQw0B0LjrxrEoYn6iT5LQkSzhMGWnzRV0jxyJlhsBdpxcpVCMU2z+6oxMLJFlgSe/7+FEXjQH0njjbaON1UYvIWFEXjdKcH2/bXo6I4HTISeGxmIRo6XdAo5CEt4nMlK0HT9H8B/LdLQ7gcwK8AvAzA2MNhaQBe7TqGBLCZpultBEHsBrC5y9yuFsDcrnMcIghiM4DDAAIA7uySpQCAXwN4BYAGwIdd/0gYoGBbCpZMQpPNC5cvALWCxN1Tc+DwBkFTFBvMzZ+QxbaQbdx1EuvmjcaoNAMarD0H2hRFo7bdie9quayBxeU52LSnFsum5Qsm84Qe4IfeOYCFky3ISzVKgeEFgLNlnJEkgavzU7Bp4QQ0WLtlT8SOiw6XFzeUZfJkKTpcPlHHn2oVTm6PvGuSKOfSYQk6bLhpDPbXWdkgpijDdMFpVkqQIKH/0O7y4c7LR0CrUsDpDUCnliMzboToeau/QVE07J4Ah2m0ZEqOZK45SEFRNFrsXtw+yQIgtCYDwKzSDOSnGbBp4aXwBYO8rheK5pvaVBSns4lhADBrlahscrAyJOGJPgBR2aFnwhyN1PfriZkqoXecSTtwuDSJx0+hON2IX1+RjSONNtS2O6EgCSTqVUgyqGDWKlnZEiA0lo402gBgwGtJSpBwoaDd5cNtlw1Hm8vH7ktuu2x4zOKLvoKiaF7sIfTaQMf57pYY7N0ZYten8I5dhvRIEEBOsgHtTm/UNaW3bqrjTXYAiHrfqtucWPfxMV7O4ZGKUVj85ndYNi3/jOIR0ZrDXezf6QgxiEsBvNrT+2ma3g9gjMDrbQCmRDnmcQCPC7y+B0BPesUSBiAON9h5A37rvnosujIHWQkaVBSns4MZ6A7OFk62sJopQoE28zAdbbSxG0fm+PU7K/H3BZdgdEac4MMQreWeoiEFhhcI0kxq3oZtyZQc0RVeiqLx0ZGmM2aU6JQK3rhev7MSr982XtT5a9qdgmO0tt0pKjkMhNqdwpMq6+aNFnWcBAkSLk6kGlRoc/hwb1dXj1pBYsX0AqQYYtP22WDz8Fh/z+6oRHGGCZZkQ0yuScKZQWgDxLT/P/PJcfa1319fjKwEDWra3OyxMoJvUiYjuQnjWaUZURmix5rsgms5gDNijoYTDKKdV4oj+4a+sMsijQqzEjS4YXwm7olo5336o+PocPmwZEoOXttdwyaI1QoSx5vskJPC3igXgmyNBAkDDUk6JU40O3jF3kTd4DCka3F64fQFedff4vTCgsERj5xvs/ILxRxdzPrEdOyatUoO6VGtILFmdjFKwxi84QlzrVLWYzfVgXob7t70Q9T71mTzCObSVm87jAUTLWccj4gSwCQIYhOAIwixhp8HMIKm6bv6dCYJFxWitQ9WFKfjkfcOYnlFAS/AZ97HFOLMWiWONtrw2fFmnGxxsFW6A/WdWLr5B0FGicdP4WSLA7tPtiEQ4AvdMw9wONQKEjTdHRhKGNwIUhBMKoj0k4vK3D3V6hR1fKvDJzgu25ziKuQ6pVxwjGqV4mp50WQ1qtvEXb8ECRIuPrj8QdYHAAjNGyu3HoLLH+zlyHMDuycgOI/aPYGYXI+EnkFRdCj2OtHKxmsMhNakNpePTQwzrz34zn48Or2AXf/UChJFGSasmzea89qYoXGcNZIgosSCrQ72vGkmNRZMtOBoow0HT1txuMF6RutkOMEg2nmlOPLM0dM4imy/3XWsGcum5bNGhUB3vDerNIP977llIdsahqTy1p46BClaMM6S5LckSOh/uP1BwX2ZO0bxRV/hC/Alap7dUcnRIR7oON97wzM9X09rwEBB5DVmmrV4eu5ozC3L4CVql23Zz35nJmH+k/Wf42cvfo0dR5sFYwgZCSwuz8Hb39X1eN+SDeqouTQmPjmTeEQsc/hvAG4Kk3mQIKFHRGPoMoNVRgCTshM5zF8gFJyp5SRPcoKpOCnlBPbXWdljhLRVa9rdWP7+IayZXYzpxUM4lRYh/RiGwi8FhhcGmu3CY6/F4RHFvK1pOzvmbqJeKTguE0RWyPVqGZZMyeExn/Uqmajj+9OQToIECRcHoha1HLFp+4w2jw4WptHFhN4YQkJrUrTi/qHTNmxaOAFuf5Bt4QTAtnVqFDKs3nYIi8tz2PhQiF2sVpDw+qNLmD1SMUpQcqC3dTJS01/S9+8/9DSOAD7Te3F5DmrbXFH3Gsx/Z8Zrsag8GzQNvP5VDTpcPqi64qpISRBJfkuChP6Hw8uXDPL4KTi8gyOt5PYJF6vdvsFx/cD53xueyfkGA9tY6Bo33DQGKgWBzHhtj985MmFO0cIxRHayAb//4AgbnwjdN4qi4fYHkJ9mFPwMuuuzk/R9j0d6TA4TBFFO0/ROAFoAMwiC+8PQNP12n88oYdCjNw2ZkEmcvMfBOjReh86ulq/w4GzpVbnIStDh7ik5OG11s8E7UzlZO6cE6SYNlkzJxqdHmzkbBCZY3H6wAQsmWnCixYED9VYUpZvY62P0Y0beNQlHGm043mRng0UpMBw4OBudorM1ZFMrScHjlXJRjRZQyUPt2AwLj2nPVok83uOjoFPKsHCyBRQNkASgU8p4C040pBjVrGwLM2Vv3VcvbVglSJAQFckGleC8lxQjWQkCwJrZRTjR4mQ1Ci1JOhAx3B8EAhQONVg5WvRykfP6hYzeTGCF1uRoCV3meLqLLERRNGo7XGwsYHX7cPNlFihJ4OVbx+F0pxsGtQIrryvAive719wlU3LQ7vJi8ZRspJs0nHjSrFWiyebB3VNz8GOHu0cj48hYJNOsZQkGW/bWSQnGfkS0cTRqySRY3X4OY/jaojQMNWth1ETfazD/Ha9T4uF3D7K/0SMVo7B622H4AjRrkEUSQH6qQXTcOdi1NCUMPgzmMRenVaAsy4SbL7PA7Q1Aq5Lj1S9PIk6riPWliUJSlPgoUR+bYvWZjIXzaVbeUx6op/OdraH8uQLjc9Vk88Lm8aO2zcnJT+2vs2LjrpO4fZKlx+8cmTDfsreOl8f6w6xiqOUk7p6Sg1anF3//qhZKOQGNQobdJ1qRZlIjEKRxtNEOEMCWPT9iecUorOrqoAn331oyJQeyMwhRe2MOXw5gJ0Jaw5GgAUjJ4YsEFEXjVKsTte1OEASBFe8fRE2bm1fVYSoq735fywvWwwfrqTYHVHISr+2uwaIrs5GkV8GoUcDlD+CJDw5zXBf/vrsanx5vhcdP4XizndUjXjIlBx8eaMDaOSVw+QKoaXdj+8EGTCtM45nchVedSJLAiGQ9hifqMCrNiMtGJIgywZBwfkBRNHYea+IZqpWPTBH1+2SYNFg1oxDL3+veDKyaUYgMk0bU+XVKuWBy16AS12jRZPdCJQfWzimB0xeATimHLxhAk90r6vgOlw//2luH2yePYIOoF3edwJA4cdefadbirvIczmbosZmFyDRrRR0vQYKEixEUVs8oxCNh8+bqGYUAROrx9DOc3gCsLj9H4++ha/NgjtFmMhCg8O6+et68OrMk/aJPEPfGEBLq2MpM0PLW2eUVo5CgV6LF7sXJVieCFIWcFANe+d9J1Hd68atJw5GgV6HJ6gYNAs9s7tbHfvz6QiyZkoO8VAOMagX213VCTpKc8cOQB8JjxJ6MjKOxmK7OT8EHXUzmVKMaV49KRYtDnJmahG5EJjjanF7eODJrlRzj6awEDf4wqwj1HR7c+699MGuVgp1Wr+0OdQM+MC0Ppztc2LRwAtqdPnz/YyfsHj+ra/38p1XsuXJTDLj3rX2c31qIsTYY2G0SLiwM9jEnJ2nMK8vC/WGeBquuK4ScHHiSAUIIUDSWTcvDmu1H2etfNi0PQfr8X/+ZjgWhdfhcFDOZ61uz/Qi7tjI5nXFZ8T3uRQdi5yuTk6hscnDWmXum5uKVL6vRYPWwnVC7jjWzxUehexyZoG+werBpTy02LZwAly+IIE3jZLMDD7zdPc7uu2YkMswafH2yDVmJevzY3o7lYbm1pVflQk4Af5w3GnZvAAk6JfwUjRvHZeK13TUYkxmHYYl9u3c9Zjtoml7R9e9fRv6NIIjZfTqThAGNnqpQ4Q8684A/MC0ff/6sCvvrbZyqTnWbE2u2H8GyaflYs/0IFky0QCUnMSxRh8ZOF357dR5+/8ERdLh8+MeCS6CUEyAJAiu2HsKCiRZs21/Pc118bGYhrsxLRqvTh5xkA9JMajRYQ2Y1T80pwY8dLgxP1OGlL0KfIWRyJ1R16osJhoTzh5o2Jyqb+MYFIxL1GC7itzraZMPmb2vw5JwSToU6L0WP4qHmXo8PUDRe+G8VyyihaeCF/1aJNnWL1ypx1z+/51UO/7HgElHHJ+iUuLYojRNELZmSI1qWorbDxSYwgNAz8PC7B1GaaZbGugQJEgShkcthUMtCRS1vADq1HHIy9HosoFUp8MSHRznz2BMfHsXfRc6j/Y1DDVbBeTUnWY8SEevKhYzeGElMx1b6wgn4vLIVliQ91mw/Al+AxsLJFmQn6aGQkXjpixMoz0vlxH9LpuRg6VW5aLR5Ud3mQrvLj7xUA576D3ds/O6dg1gw0QKDWo66Tjc63H5s/M8xznvW76zEk3NK2LU1/PXXbxuPsVnxnM11NBbTB13xZPh6KtYsVkIIgQCFL0+2YU9NOyg61N10V3kuHrp2JP72ZbeB3NyyDDYxnGZS47bLhqPTFcDDXUWsBqsHr+2uwcLJFqSbNGh3+ZCbosfPxmciQFHITtbhye3HkJ1iwOW5yXD7KRxrtAmO1+NNdlF7h4HKbpNw4WKwj7kgReD5zyrZfRUAPP9ZJdbOKYnthYlEok4FGQFOR6eMCL1+vtHXsRCe3xmZYsD2JZPQaDt3xczw69t+sAELJ4/Axl0nUFGcjm9r2gEAl1oSBIvq55PdLBbVbU6WGRx+z5/55DgWTLTg+U+rICOArAQNphWmYeOuE1gw0QIZCZRmmjFxRCJ7j4US9Mum5aMoPQ7VbU68+0M97zxP/ecYnr9pDII0cOg0/zrWfXwc918zEgQZ4JA7FpfnQCknzujenU3U/wyALWdxvITzDKEEMBAy4DrSYENlsx2b99SxEgtMFYpJ+EYmbR+pGIWWnVVosHrYqg7jnHi00cYKtfuCFI432bFlbx1uuSwLs0ozEK9VwBek8MC1+TjaYENush6ZZo2g6+LD7x7E2jklWP7+YY5GcIPVg2NNdmzYWYXidCMeqRg1IKtOEvqG01Z3VJd6McnhVqcX0wqHcJKr9149UrQhXJvDyzEZIIiQGYFY7c02pxdmrRKzSjPYIGjL3jrR549m3FByS5mo46VnQIKEwYGB1CbqCVI41eriMfAS9LGRlWh18FmEHj+FNoe4Doz+BtM+GHk9jVYPSobG5JL6jHM13qIxkjLNWpxscbDnK0gzweULYvfJNkwvSQcAfHa0GbnJBtyz+QfB4v6zOyrx6m3j0GTzcgrGj1SMgt3jx6tdiUSPn8LwRC28gZABzO2TLIK/FwHg9kkWAGDlJELrI39cSWvpuQFF0fj3wQYs27Kf83u2OzwYYtbi15db8K+9dbgiLxk5yQbcPsmCLXvrMKs0A95AEM4I/c8Gqwfrd1RhUXk2NuwMdRYym/bFU7JxRV4ykg1qtkgxKs2ArAQdm3RmSCitDi9LPgGi6zxWR/GlkMaFhHOFaHNRk21wjLkOtx83jc9iTUgZ5mWH2x/rSxMFu8fPKVYDoaTl5qFx5/1a+rIunW/GOUXRaLF72TVWp5Rh464TvPyRkCcUcP7Yzcy1iomHmmyeqB4JmWYNFk/JRuEQE4rSTVjURQxjOlLUCpJlBTPnmFaQynoopBrVoGng2+p2dLh8GJVmRG6yHpNykzn5A7cvFAtFi2uSjWq264V5bf3OSmycX3ZG9+5sksMDv49BAotoE4RSTmDRG99zKg2vf1XDqUIxCd/IoH31tsNYMNGCl744yQpepxhDzolapQw3X5rF0xNO0CvxyeEa3DZxBHafbGMZA3dMzobV7Yvquuj0Bdj/Xr+zkj0v8xwfb3YgxahC4RCToMmdpLc6eBDNpd7hESf8b1ArsPYjLmNo7UfH8Ppt40Udn2JQ88bukik5SBapvWnWKfDryy1odfpYWYxfX25BnFbcdGuL8v3tIr//QKy8SpAggYuB1ibq9gkXpTbOH3verwUAdCq5oHa6VqS8T38jzaQRnFdTTYNjXj2X441JujEbnmRDSJv3oyNNPNMWmzvAxmhZCRrcMTkbx5tDjE3GsJhBmkmNWaUZ7FiMjD8XTrZg/oQs1jeitt2F6jCDMqHfq7LZziYQmXi3w+UDTYcYQuGba2ktPTeobnOyiWGAu59Y99Y+LL0qF/93+Qj8Nkzi4cFpeRhi1sDpDUIuI5CVoGGlIQCuzjAzltQKEkEKyE8zsBtkkiQwLFGPzHgdSjLiWO+Rpz86jg6Xj0M+ifytmWcoGvNYGhcSzhWi6bdqleKMqmONOI2CTQwD3czL10Tuy2KNxigJ2UabF8Xn+Vr6si6dT8a5UIzxSMUozB07lJc/WrZlP4rSTYId3ZGxxLkgTfQlHkoxqqN6JNRb3azU6WMzCwXHyI6jzex7mHMwcluRchVZCRrccXk2R25ryZQceALBqHFNVoIGRrVcsOgdpKgzundnI5Q2OIRiJACIPkHsr7PyKg03X5qFBRMtON5kx8kWB5IN6qhJWxkJjuD1sAQdxmXFg6bBC+bXfXwcbXYvri8diqWbf8D6HVX46+cncUNZJl7YVQVfkEZ+ash1Mc2kxp1XZmNReTaWTMlGnFbJOa9GQWLj/DKMGRqHTf83AduXTEL5yBQUpZuwbt5o1thEMggZfBgSp2F/PwahMSEuOdvh9AmO1Q6XuAq10xcQTJK4ugoUvUFOCE+rClLcdJse7fvHifv+TOVVegYkSBi4iLYmV7c5Y3I9br+wm3jka+cLRrUcd0/NZWMLGQHcPTUXxhglhwvSjHhsZiFnXn1sZiEK0kwxuZ6+4kzGG0XRONniwO4TrTjZ4gBFRQ/7GZmuCZZEWJL0qO1w8c63v87KsjUBoKI4HSu3HWIdu4Huf6eZ1Jg/IQsvfXES31Z3CI5NigbW76zE3LIMLJmSg7f21LGfwRi9hH9u+HuYeHduWQZWXleALXt/RLPdwzlHX9bSvtyrix3RmG9McWDdx8dB0yG9YSD0b5c/iLv++T3u3vQD7n1rH+6ekotl00aye4QHp+Xh7e+6f3+SAO6ZmguTWgatQobqNifnNyFJAgQB3PvWPqzfUcVuptfvrMSs0gzB35p5hjbv4Y8tKcaScC7hCwZ5Y25xeQ78wdisz32F1eUXfOatIvdlsUaCTiW4L4sXKffXn+jLutQTy7i/IRRjrN52GEkGVZ+uITKWOBdkib7EQ8MSdCjKMGHJlJ7jiR/bXYJjhHlEI8/ByFWE5xsqitPZxDBzzLM7KmHWKbB4SjaUMhLPzBuNrISQB1FWggZ3XpGDha/vxYadoZza/AlZSDOpu4pHZxYv93gUQRAHIJwEJgCknNEZJcQE0SaIyPjVrFXCqFFwWJMbbhqDsqx4wapJXooBq/99hBW8JkkCl1oS0OEWTtClxWlxn4De24KJFngCFP78WRUev74QzTYv5xqWTctj273UChKF6SYsfH0Pp+KTGa87b1UnCecOo1JDm/BI459RIjfhGoVMcKxGTtrRYHULM3etHnHJYXcgCKcvyNNMdgfEMX/1KrmgwYpBJc6ISXoGJEgY+BhobaIGtTAzSa+KDTPJ4w+i0erhzaNDYsTUlctJzCxJR06yHo1WD1JNIZmEwWJG11eJhDNlGjOtmuH6rezfIlozmWQgk8jdtKeWde6eVZrBYRsJjU266/Nykg144oMjaLB6sGVvHWsI8/pXIS3aTLMWOpUcq7YdZiUDmO+fk2zAq1+exJT8VKQauWOLWUtH3jUJte1OaJVypBj5RdqB1gUw0BGN+RbO/D3ebGdZ4bNKMzgbaLNWiUabh9eZyHzO6hmFcHj8kJEE2wou9JtEeyaK0434YPEkXtzEvL/B6sHrX9Ww+qmTshMxbli89FtLOGdI0KmwaU8txwtl055aTCtMjfWliYJRIxxfGDWxKfb2FUGKZtcmZj5ZXJ4DKgaGdH3Z4/WFZXy2slPR5tNkg2rAdVr0JR4iSQLlI1OQnaRHaaYZLl8AWqUcd2/6gRNPbN5TxzN1ZjpRhM4hJFcR2T0FhNa7doefJ6uVpFfBpFHglr99w8upLZxsQZpJIxiviEFvUW0FgOkC/1QAyD2jM0roV/TGVmD+ThKEYEUj8rmfW5bBuiwCoYG26I3vkZWgwZrZxZyqyT1Tc7H63yFzufCHXC4nUdDFAI48n8snnHiTkaHFbn+9DQ2dHh5zc832o1gwcRjUChJPXF+EFe9zjWHCqzG9VZ0khsfABkkSGBKnwsb5Y/HsDaOxcf5YDIlTiV6kmORqZIXPIJJxlmIUrhAni9TeDFJ81vyzOypBiSzwN9pCBisLJlqwqDwbCyZa8NruGjT1odJLUTTsHj86XX7YPQFpjEuQMMDAtImGI5Ztomq5DPddM5Izb4b+PzbX4wvSgvOoPxi7uUwuJ1Ey1IxrCtNQMtQ8aBLDQPcmMRw9bdCiMWsO1HdGjTN3n2jF/6pa8ctXvsHB0zbe+ZjWzMhrYJJtFcXpkJPAxvljkZWgZc8txAJeXJ6Dt7+rg1pBIk6jQIcrpOnfYPXA7vFj4WQLZo/NQJACnv74OI422tj3hJ8bACaMSMKb39ZCiIRHUTQOnrbi1//4Djds/ArTnv0c2w81cu7BQOsCGOgQYr4xvyfz/0EKbCdjplnD2TdEJosZtvHjMwu7JMCUSDSoeYaWkb9JtGciJ8XA2TsI7aMarB48/2mIqZVk6Dk+lfYcEs4WwxJ0WDYtHy99cRIbdlbhpS9OYtm0/EHDVqcBwX3ZYIGMJNjkPLMv27SnFiQRm4KQWHZt+FybZlJj8ZRsrJ1TApoGZx5iCpw/Wf85fvbi1/jJev461xuizafVrU48UjGq3zot+mM+FRMPhZ+nus2JzHgdLrEk4Mq8FCQZVLx4osPlQ1mWGR8snoQ3F16CTQsnYNOeWk4COfwc4XIVkdcRjrllGWzCGehmZMfrlGi2C3tz5KUakJOsQ0acts/3BuiFOUzTdA1BEDIA/6FpeuoZnUHCGaO3Kk5PbAWAazT36dFmHhuR0RxmKjpqBYnhiTrBgdZg9WB68RAUDjGxGl2vfFnNmteFP+SBAIVmh5dlb3j8IR2VR6cXwu0PYsmUbGzeU8c+MGoFidEZcVi57RCAkIGd0DUkGdSshEW41hjzdzFmENHu2dX5KajtcA0IY6CLHbXtThyst2Pdx93GBUuvysUQkxbDEntn1PmDNLQKGcdVVquQwS9yAVHKSPx+VhFOtTpZzeBhiTqoRCYC3FEKIC6feM1gpbx77BEE+uQ4GghQeHdfPY95PbMkfVAlMyRI6E8MJPM3AKBoCr+/vgin2sLmmQRdTJgoAKBVkUgyqDjzZpJBBa0qNnOGxycsc+EWOY8OZpyLsSpk9LLhpjGgaWD3iVbeeaIxa4412tHp8uPS4QlQKmWCMdXi8hxsP9iAe6bmcgyI4rVK9jWzVgmjSoZV1xVi+fsH0WD14KUvTuKeqbmobnWizeljY1MmebxwsgV5qQYcbbSzWsGPVIzCy1+c5LC6/vlNLe4qz+GsgTkpBqyYXsDT8nvigyPs53S6faAompMU/PJkG08fN1KzUTKu6xvCmW+NVg98QQorusZAONvKrFUiQadEfacbagXJGv1mmjWsSV24edwPdZ3QKGRod/rRHkVeLPw36c38iKJoUfuonpIcEqtcQn9gsHcE2tx+fHigAU/OKYHbG4BWJceLu05gRNLgSG5bPT7cdtlwtLlCXjJyErjtsuGwecQZjfcV/RUDsCacSybhu9pOjgln+DxU3ebEmu1HWGY6AKzZfgR5qQZ2vuztmoTm08XlOdj4+SkAwIKJFhSnG5GTYujx+/R0HmY+XbP9CCqK0yEjgXFZ8bjUktCn/a2Yub+neTva8Vld12pJ0iMQoLD0qpEc49Xwc4TLVTBrytZ99bw4xZKoF1zL6jvdONniEGRlG1QK7KpshdtH9fneACIM6WiaDhIE4SIIwkTTtLVPny7hjCEmoIjGVhi1ZBION9h5D+iHBxqwcLIFY4bGIStBxw7QV385Hp9XtYKmgdNdQZgQ/Z8kCYxI1mN4og6j0oy4bEQCb4EKdyE2a5VYONmCnGQ9nN4gfv2PvZyg/LXd3cH9m99WY9k1efAEKJa5GXkNJ1ocAACSIAX/ToDAyRZHj5OO0D1bs/0I/EGK9wBLwVts0Gz3solhoJsVMmZonKjksEYpw8tfnmKNjIIU8PKXp/Dcz8aIOr/TF0C708dp4bjvmpFwmsTJSjDaVJHjU6w2VaZZy9vYPjazEJlmcRXAQw1W9lggdP8efvcgcpL1KBlqFvUZEiRcSBiIG3QCBFocXs48s/SqXAxPjM1myesTbm2I9vq5RpxWITiPxmnFyesMVvT3WA3faI1KM+Dfd01CiyPkkn24wY6fPve54HmitaPWtLux/P1DePz6IswoHiKoLbx+ZyUWXZkNtZzEwskWpMdp0O70we4NQC4j8OyNY9Dm8GLVtsNsnJgZr0Wj1YNXvqwGAPzysiw8NrMID78b2sx2uHxQy2V4+YuT+O3VeVDKSLj9FDbsDOnFnmxz4h8LLoEvSCHFGDLEK800o8nmgTcQSj76AjQWTrYgN8WA4012vLa7hk0uMgZ3TTYvZ8O8p6a91yTjxWxcd6ZJDJIkkGnW4rvaDjy3s5Ld6OelGvHCZ6HfdPGUbCx//xDMWiUenJYHlz/IScxGmsflpxpxosWBU21OXGpJEDStY8yzmWuIlnCLVvQQ2kf19H3PpyGUhAsbTNJpMI6bFIMa1xal4f5/7ePkAVIGyRyZoFWhqtnJi9fitWfWtt8T+jsGIEkCFA2O3n/kPNTm9OKGskyebEa70wtLkl7UNYXPpzVtTnz/Yyc7PwPAS1+cxAe9zHu9nYdJYkde65rZxSjJMKHB6kGaSY0gBTTbo69JvRVbepu3ezueomh8dKQJ6z4+hgUTLZCRQFlWPC6zJHDuV/nIFCTpVBg1xAir2w85ScDh8ePpuSWg6FAcfKjeGjUn9laX/n34vVh5XQEefu8Aatrc7L2ZXjykT2NHbCrZA+AAQRAvEQSxnvlH9Fkk9Bli2tSiaxZ62QrQovJs3D4p1P4wKTcZ63dUAQA7iEObABVIIsRQ1ClleHR6AYf+Hy0xFUlwoigaB+s72SRrg9WD9TuqUNnswKMCAtsP/zQfCyZasGFnFT463IrDjXac7nTjoXcO8FoQFpeHhL8zzVq8uOuEoNHI4/8+jHd/qMcHBxpwolm41UDonlUUpwsyQ6SWwDPH2bR9WN1RjAvc4owL/AEKN47L5LRf3TguE4GAuGsIUDSe+s8xznh46j/HEBD5HXzBIJZelcsZn0uvyoU/KI7xVtPuEkzu1rS7RB3fZPPArFWyho6LyrNh1irRZPOKOl6ChAsNA7Ht2+ENCBbBHF5xRaj+hjdI4+mPjrGt9RQNPP3RMXhjJOPQ4fbjnqncefSeqbnoFLkODFb051iNbBWd9uznONZkx/hhCaBo9Hienlr/PX4Kv3vnAL6r7UB1m1NwvU41qVmWVZxWCRlJYMOnVfjDh8dw6LQVf9l1AgsmhqQfKBp4bmcl3F1xY4PVgyc+PAaDWs5p4339qxrsqbFi98k2JOhU2La/nk0M3lCWiaVv/YAOlx+ZZi3bCaZVyrHi/YOoaXOzMenxJjtrQhZ+zcw9Ye4BownYW/vpxWoCe7atyEwhu6bNjbe/q0OQAo422vCrySOQlaBBZryW3UvYvXyj4HDzuHum5qLZ5sGGT6uwfkcVfvnKt7jj8mzWuIfRaWyxexAIdI/XaO3ZQs/h+p2V7D5Ko5SJMks6n4ZQEiQMVHgDlKBMlDcQm+JzX+GnKMF4LSBWL7APONMYoKd9d2/zkFJGcjT+mflO0eUILFZmiplPL89NRl6qkZVeELsm9vbdm2weVBSn86512Zb9ePv7eizdvA8fHmzET5/jr0mR9wcAO/cPS9Chus3J/q3NKSzXED5v9yTtwXyPmjY3nu9akxa+vge1Hfx9fHW7C//3+l4s/ucPWLp5H1odfjz27yO465/f49vqdry6u4aX81o1oxAahQyzx2aAJIFFXfv9jfPH4k+fVbFFUebe9DV+FKsE/u+uf4BugzqJUnkO0VubGkXRrGZhZDXB4w8IVoBIMvT3yiY7ZCQJhYxAmkmNQ6ftnGrYQ9fmYdGV2fAEKNBdQXtpprnH6tGoNANOd7rR5uQn9iIFt5nvQtGhhPTssRnYuq8eI1MMoCgKFcXp0CtlWDunBCdbnfAGKLaFsMXhxf56G1ocPiyYaEFWvAZ1nW58eKAB0wrTON9ZSC4i2cBneMhI4euTWgLPDGdb9dSphA3lNCK1OBvCNHsZ44bXdtcgM14c89bhFZaFcHrFJXdtngD+9r9qzvn/9r9qrLyuQNTxNe3Cm+3adidGJPc+HlMMatx8aRbP0C7Z0P8VbgkSBgMGYtu3K4psglj5mf6G1e0XjBvEFuX6GwaVHG98w53H3/imBn+YVRyT6zlf6M+x2hP7pbfzMMyY9IUTcKzRjpp2N4cF5PFTONXmhMsXiNopwxQ5F0/JZmPMNJMaBUNMSDGqWdmx8BiV+xkKyEiwsSLzepACVm47hNduG49vTrUDAPQqGe69Og+BYBBbDzTgwbf3cz47/NqZhC9zzWkmNeaWZSDdFJIrYNhSKUY1tu6r5zFz1swu5mxy+9LyPdDkbc4GYlqRe0KD1cOOifkTsjj3+LGZRXB4uqVFPAFhubm8VAPWzimBQk7iiQ+4fikrtx7CM/NGw+kNoLbDhQ07q9Dh8uGJ64tQmhnHmliHoydDRY+fAkH0jRV+MbPKJfQvAgEKhxqsXexIDQrSjINGKq7FIZxsa3UODtJKh0uYtNTh6v/46ExigN723b3NQ73Fo9Gu6buaDrh8QVjdfs6YPFMZlN6+e4pRHTVnQ9HCevRLN/+AkXdNwqk2B/bXWVkZt6IME8pHpgAA796tmV0s2HnS27zNrB/VbQ7OushIIEX+htVtTh45cf3OSiyYaMFLX5xEWVao25ckgafmlOBUqxMKGYGsBA3quhLN//ymFjeUZWLrvnqMzYw7Y9nVcPSYHCYIYgaADJqmn+/6/28AJCGUIF4m+iwS+oyeHuRwzZXIoPWxmYUgSeEK0No5JXhwWki64ZH3DqCiOB2Z8Rqc7nTDrFWygdoTHx7FgokWPP9pFXvu4012AKENmpAswx2XZ2Pl1kO4fZKFn3wlhJ2m47QKbNlbhw6XDyumF+DtvT/iqoJUvPQF1538n9+E3nPv1SORZgrdF0afbu2cEqzfUYU7r8zmfeelm3/AxvllWPj6HvbzNtw0hqcTMy4rXgre+hGnWoU3pCPvmiQquamWy3i6bkum5EAj0hgpyaAS1OxNEpkcNaqFiy4Glcjz60NC9eHPj1pBIkGkrIReJXx+vUhDPW9QuEI/NkuSlJBwcUKoKBjZYny+kaBXCl6T2Hmiv2HSKDhu6EDIDf2p2SUxuR6dUoa7p+ay2u9yErh7am7MDPvOF/pzrIZvtNJMaswqzQBBhDbq0c4THveQJIGi9Dh0uvxY/v4hgTVRDrmMwMM/zUez3ctuujITtKxmHtBNEGCSgIdOW9lkMdAdoz4zbzSbqC1IM+JkC7eNd8mUHGgVMmz5rg4LJlrQYvdCo5AhO1mHFocPVc12KGQkNnxaJbjZYtbkrfvqWU8Ms1bJK6bmJOtRStGsCRSTABVqDQ2/V721fA9EeZuzQW+tyL0hzaSBWkHi5kuz4PYHcfskC4DQRvrhdw9gyZQcdo8DCO8jKptDLHChIoDHT8HpC+DhMDMfINRevXCyBSOS9BgSp0aCThXSe6dofFXdhvoON9JMasHkAEmgT6zw3rQtJUgQg8HuJZJkEJbbSxRp9B1rmDRRZK40/S9zJaagFFlkFMrNhMsg9DYPRTtnilEd9e9ZCRoYNAr88pVvBcfkmcig9PbdhyXoouZs6K4icjRyVWWTgxdPZCfpBbuolm3Zj43zy9hcGaNtPMSgxr4fO9Bg9WBInAYGlRyNXb9BplmLj440Yc32I1g4eQQnl7W4PAeb9tTy8kpMpy8TmwGh9S8zXoOlU3PQ6vDxpExSTWrc8vK3vM9+dHohmm2ufsln9ZZtuB/AjWH/rwQwFoAewN8AvNWns0kQjZ4e5HA2yOtf1bBB6+W5SThUb8W+HzsFHw5PIAi7N4C39v4oGNAxQRVTHWegVpDwB2m890M9CoaYeJ9dUZyOlVtDumBqOYnVMwpR1+HC5j2hpG5mghb3XTOSbdVnzvfwuwdwV3k2bB4/Gq1u3HhJFpa8+T0vqfXMvNE40miDUkagMN2ID8IqUXQXAyTahBCuF+fxU1j0xvfYvmQS5zMyzVopeOtHnC3z1eMPINWo5hgjpRrV8PjFtVvLSAp3XpHNbmbVChKrriuAjBDX6qhVyLHyugKsCDt+5XUF0CrFJWf9QQpLr8rlGeqJbT8yqGWChnh6tbikSHTmc2za1SVIiDXkMvBMHlZML4A8hnlGrZIUnmdiZADn8gl3HLlFzrv9DoJGkKI5gfFjMwtBiJzHByv6c6wyGy2zVslhZv7185PYcNMYPDm7GPdHMUthQJIELh2egMevL8LvwsxsVlQUoNXhxUv/O4U7Ls/m/E4rphfAFyHjlJWgwW+vzkNVsx3pJo3gGkWDxqLybKzedhgLJlqwbX89p1jx5re1uPXSYbwusXAPi9UzCgU/26SW4c4rsyEjgfw0IzZ/U4uFky0ozTTjjr/v5W0MC4eYQBCAWavA+htL4Q8GEd+VRDzTRO6Fpj8brRV508IJoo4vSDPiyTnFsHsCglrCyQYVm9g3qmR4bGYhJzm2ekYhbG4/FpVnY8veOl4RQK0gu2JHYZbZsi37WYbWhpvGwOkNcrxHVkwvwAv/rWK1G3tiHEfDYDcSkzAwMNi9RIJUECsqCrBy2yHOGhKkBofBbLJBJbivE0s66gvOxCxt7ZySHhm3vc1DmWYtb34NlxQVuqZHKgqw6I3v+nVMiimmZSZo8MT1RRxzPSYGmD02QzA5qlPJ8ea3tbz8UmmmGRRNC947jZLkGcqtmlGI5z+tZNeEh67Ng80TgC8YMn5jjPKYrijms9bvrMTG+WWc70FRNLQKmWCnb7vTB4c3iHWfcHWi1318HAsnWzgJZW8giBvHZeLQaSuGJWrZnBlFhwrhd5Xn9jmf1Vu2Q0nT9I9h//8FTdPtANoJgpAyZ+cQPT3IDBsknAlC0YDbF8QTHx4VZO+qFSQarR5kJejwm8uzcdrKZQuHB1VMdZw5bulVuajrcIEGoJARKMsyYU9NyJswzaRGZryGt/lgArdhiVqs+fAI7pqSg7/eXIbTnW5olHLUd7rgC9BY1bUJeOmLk1h1XQF7TQyYpNZbXYnm/5edhBHJ3ZUoiqKxbt5oHGu0CX7nYEQ+zuOn0GjzsBoxDKTgrf+giyJ3Ija5KiNl+MfX1bj5Mgvravvqlydx/zX5oo4PBEkOy8njp7D8/UN49ZfjRR3v8gegURDYOH8sOpx+mHUKdLq8cIlMkjh9AahkJCe5rZKRcPrEHe/yUmix842qxBrSZcXrBO9/Zrw0ZUu4ONFo9eKF/1ZxJApe+G8VLIklyEqITVLG6g7iT59xr+lPn1XhyRgxdTUKmSBzeM3s2Mg4uH204Gb4NZHz+GBFf45VZqN1tNHGS+IteuN7LJ2a0ysjFgCUShmmF6YhK16LRpsHJrUCDVYXSELGkgPCP3vl1kNYONnCelwcquvE8ooCnGi2IyfZAG8giCVTsrF5Tx0b7zEbuKWbQ4ZFBrVMsFgxxKwVJBEw8WtdB585k5WgQaJBzW60mMSf3e0DRQlvDI802nDvW93mSevmjUZpZvxZxYUDUd7mbHC20jhyOYkhJjV+8a9veBvphZMt0CrlmDE6HRQNWD1B7D5xGs/MG40fO1zISzXiaIMVNm8QW/fVY/6ELLz+VQ1kZLdMSGa8lm3BjWQA03S3TITHT2F/nRXv/cAtRrzw3yrcd3UeaACZ8RoUpcedsSHUYDUSkzAwwOzVw+Hxh/S4S4bG6KL6ADkpw5bvavHknBK4fQFolaF93bJp4vZ1sUZmvA6WJB1nX2dJ0p2TfdWZmKVVNttFdQIJzUMUReNQgxXPdeWBmLgjXFI0XGZqx9FmBCmg0+UTHJONVi9cvtYzkk0SaxLKGNnmphiQl2JAdbsTHS4ftuyt43QeZyVosGxaPr451Y4HpuXjz59VYX+9jb1WfzAIg1q4i08pI3mSD8vfO4in5pTgiQ+OAACcviDbqbRx10lWHkvovgQpCl+fauOwjGvanLxO3ze/rcVD1+aj0+3H7ZMsrCQF83etUsbLtz1SMQrBIIUf292cRPMjFaOQk9T3fFZv2RpO6p+m6UVh/5vUpzNJ6DOiPcgpxlC7U2TgPCrNCI+fwpa9fPfCx2YWwuUN4L4wp1AhtrBaQeLJ2cUoSjehIM2Ek60OqGQkfv/xUfa4x68vQryuHlPzU5GVqIPHT+Ghn+SjqtkOszbUEnvzpVnQKGRoc/hw/7R8tDm8aHd5eBpzr39VwwZny9/nbiiA0PXUdrgwqzQDz39ahRaHh2WfUhSN2nYnEvVKKNNNeOEXY1njEbUipBmz7uNjnHsXjV4vBW/9hxSjSlAWIsUorsLq8QdQnpfKcbVdXJ4Dd0BccrU1irZVm0htK6WMhMdPY+HreznMY6VMHKNPq5Tj5S9PoaI4nS3cvPzlKdFJFk8gKGh88NItZaKOH54oXHkdniglhyVcnHD6AqwxRDhcIgs25wJ2j1/wmmwx0vj1+IO47bLhrImYjABuu2w4vP7YMHs6omw82rsMTi5U9OdYZTZakRsfIHQvbd4gh2UZzUmcomh8cqyZs6YsmZIDgoju2ZAZr2VZy1MLUrFq2yHcUJbJxqBZCRosrxiFymYHghSFEcl6BIIU7irPxt+/qkV6nJZ9L/OZIfbNWMHzMQm9zXvqWMkI5lofvDYfd2/ibqZXbj2El28pg04l3C4crjl7tgxfpgXY7RdOig9WCbPeWpHFoDOKlueIJD2cXh+CVKhV2KCW4Wfjs1Dd5kBanAZ7atrZeer2iRb89YuTITmSISaklHP1rFdeV8Ca9ITvPZgkcZpJjcIhxlDCOYxxdUNZJuo6XTBrlHD7gxJhRELMkBxFliFpkMgyuHwBTC9OR1WznX1upxenxzQG6wtIkkD5yBRYEvXnhUTWU05CqMi4eU8dj00rpgOaSbgebbQJxh3hhUtGZqq+04Olm3/AU3NKBMfkoQYrK/VzJrJJ4d89XD5Dq5RjzfYjbFGEOccHiyehfGQK2xGealTjMksCvj7VBp1aEcF2HoWWnSEz2qwEDdqcfvzu3YO8nNm6eaPh9AoXP92+AJZNGwm9So7V/+YzhKPdl6ONdji8QZjUMhSmx6Gu3YUMs5ZDikwzqXFDWSae+PAIK2exvGIUNn9bi1HpcZCRwKg0Ix55j0ucWL3tMNbNLcETb+3jvb5ZZCdPOHpLDn9NEMSvaJp+MfxFgiD+D8A3fT6bhH7BsAQdVs8oYrV0ga62/TYn1IqQHm+43MSUvGSQBIGPjzRxqhCRbOG8FAMWTLTg6Y+PYdm0fBjUMji8QV5V43fvHMCLN4+FyxdEu8PPoa/fetkwmDVytLn8uDcsubdiegE27johyA5gkm4eP4Xhid2sx/AgjmkVSNSpcLLF0eUiTeNEswNPfNiduF4zuxhZ8RoQBAGnN4jHZhTh4fcOsEGhJBdx7pEZr0NOip5TYc1J0YuusGqVcsFWxdduE8cYGxIXKp4wyVkgNDZTRW5YKBqCzOPXRZ7f6w8KMp7EJlmisnFEGuKRJIGpI5Px9wWXoNHmQZpRjaIhJmljI+GixUBk0+ujaJvr1WJ9gvsXRrWCIycFhJIyRnX/a+qJgV4lF5zHxWqvD1aci7GaoBNOLNBhyg9mrRItdq+gUVokU8msVUJGANkpBshJQvCzE/UqbPjZGGiUMnx9qp3TsQYAN5Rl4p6wTdt914zE7z8/hQ6XD/dMzUVzFJZtk83b43fpcPng9Pixbt5oVDU74A1QHKml8I67IEVj9Tb+xvCJ64vw1H+O8c59JgxfoRbgcBkMJiYdjEZ1Z6OnS1F0l7kOKfh7nu50I0GvwpchwJcAAQAASURBVLb99fAFaNx8aRYWb/oey64ZiboON0878tZLhyFOp0Rlkx1v7f2RwwD+02dVeGp2CZodXhxvsrMG14vLc7D9YAMe/ulIOLxBTmKF0XG87+o8/NjhwjhD/Lm6jRIk9AqCANbNKwFFAU5vADq1HCQBjonnQMZAiy/OBAOFRCZUlOtw+VCaGceRzBSzhjBre7SO88jCZTiz1+YOyTgxiUpmLv7wQAPuvDIbBAEca7RhVJoBwxL5bOXe1juhtfORilHY9E0th/3LrMvhv83uE62weoJY9wk3l7A6rFs9PI+2/WADy2rPTtKjJCMOh6N0pNd1utnE9D1Tc/HKl9UcZm+r3cN2bDG5sZ9fkgWVjMSb34bM42579VtePNBg9WBWaQY27anl5RAem1mI53ZW8gqc4ecN0uDo9jPET+cZmFz3FmXfA+BdgiBuAvBd12tjAagAzOzz2ST0C0iSgEJG8ALnV3fXsJUjxrBtw01jUNfhwW/f+oET9DCDimELL70qF49/cKTLBVWNo402FA0xIT/NwKtqzCrNAGig1eHjMYHf+KYG912dh+Vb+a7BkSZ3DLukxR5idDIbCiapSNNggziSAH4/qwj1Vjf21nSwD9yN4zI58hjrPj7G04hZM7sY6XHqs9aLkyAOZ1thbbYLM39bHOKYvyRBsAaJ4cUJmcjztzmFGWttTnGMNc1ZJrf16ihJEZFJo0CAwvsHTg9a4woJEvobA5FNb1DKseq6Ap42uiFGyU9fMBRERiZdfJHaTOcJGgXJMaSTESFDOo3iwp7D+nOs9mRezGxIgFBcd/OlWbjlb99wzskwfiKN7e6YbIHLH8Rv/vEdzFolr1NoxfQC1LY5kWLSoL7TwxlTi8tDjONI0sFT/znGxojPfHI8KvumyebhfRdG92/xlGyUZITYNQ++fZCNWzfcNIZlMXO0l7uuZ/vBBpZMMTknCUkGJToiGOpnyvAVagF+dkclXv3leCQZVGwitT+M6s53gpkkCVydn4JNCyewe4eCtN4L0eGb/txkPU9je3F5d/J8wcTQZre7TViH30ToXD67oxJ/uqkUIIAWm0ewOO8LBvGTwjQUDjHi/41IRLvTB5vbi4cr8tFq96GmzS4oteenKOSk6CVSiYSYgqZp2D0BnkdBqnFwaPAPtPhiMCNaUY7RQu9L8ppZ24U6znsr9Ln9FEqHxuFfd1yK+g439Go51nx4lOcJkJWg4+i0izVmFVo7V287jHXzRmP1tsNosHqirsspRnXUrqbiLu+qcInWaYVpnG7ldfNGIz1OzetCCo+bPH4Kz3xynJPbykrQwKhVcr7bE9cXweHx44kPj2LBRAsvP/Dsjkq2a15Ghny8It/z8LsH2fOEr0/hnV+VzXZs2VuHuWUZ+O3VuWiyebB5z49nFLf0uAuhaboZwGUEQZQDKOh6+d80Te/s7YMJghgK4DUAqQAoABtpmn6WIIh4AJsADANQDWAeTdMdXcc8CGABgCCAxTRN/6fr9bEAXgGgAfABgCU0TQ+OGfEcQWzliKaBnz73OS9RxVROSofGYe2cEri8oVZWxk062iaC+Vteaomg4PaCiRY4oxhiRXblqxUhHeQkvQqPzRiFEckGnO70YFxWPJ7dcQx7aqxQK0gsrxiFdLMapzu9+L+wVv/F5Tl489taVnICCD1UkRoxy7bsj9ouKeHc4kye0mjtU8ki26esbr+gBuLG+WNFHa9VygTPr1WKcwRqj5JcbheZXNbKZYJJEa1C3PkPneZqRwEh7aicJD1KMge+cYUECf2NgWgK5A1QeD5Cc/j5z6qwbu7omFyPL0DzEnbP7qjEi/PFydn0NwiCgD8QRG6ygWVKubx+EJH0owsM/TlWo5kXl49MhtsfhNsfBEUDRpWMx7AJl1EIjzdnlWagzdXtoN1g9eC13TVYONmCjDgNko0qWN1+LNt6CIuuzGb1+JjPZdouhdZI5qf1+Cl4A0HexoxJ5F5dkIqV0wswxKxBQ6cLQZrAhk+PdiUPNXh0eiF+fkkmPAEKX51oQaJeicdmFkKtkOGp/xwVvJ4nusgRShkJS5IeG24ag0VvfN9nRmwkoukM06DZmPRki+OsjerEbrj7ExRF46MjTX0+Z/i4vLogFS/8twpPzSnBsSY7SwphEvsGtQzpcVqWEeXyC3dWeQJBvPDZCfz2mpHsPoH52/qdldj0q1Br7eEGO6tZubh8BL6oamPjrN9cMQJ/+uwEmyCWkcCIJB0Kh5yZ1rAECf2FQBBsYhgIjesV7x8aNBr8Ay2+OBMMlO6O/owRmLVdqONcSGO9p3Wmus2JK/KSeYnNh945gNFD49i1LHz+ZwiHRxttSI/ToCjdxL4nXNqJgcdP4WijDbNKM/DSFycF12WKokEAuNSSwMYpDNQKEjkpBvZa1AoSs0ozeNe8dPMP2Dh/LOwePzbOH4s9NR3ISTawcUL49TC5LbWCxAPT8tmOqPDvzxgGMjKqkd8pI06DReXZyEk2oLJZ+HuHh77MeRl9fUuiHg6PH/dMyUad1YPqNhdkBPDbq0eizeXGcKpv40MURaUrGdxrQjgCAQC/pWn6O4IgDAD2EgTxMYBbAeygafoPBEE8AOABAMsIghgF4EaEktBDAHxCEEQuTdNBAH8GsBDAVwglh6cB+LCP13NBQUzliKJofHa8OWqidsX0AhxvtsPtCyJBp8TNl2YBANz+IIea/uyOSvxx3mhUtThYwxrmc4Q+VxelXbYkI44nGbFpTy1+PdkCGSnDL1/pptmvmlGImaMDaLD5YHX70WjzcB7y8GS0KowNGa1SNFgNPwYjznaTolfJ8OScYlQ1O9igfUSyHnqVuOTo2ZqkGFRyQc1ksYy+BJ2wuH2CTinqeLmMQKPVw6uw5yaLG78tTq8gc6ZFpOayBAkXMgZKWbnN6RXUeBPbodDfcPuFi7ruGGkOUzQFGgRHnmrldQWgBsoPeB5wtl81PDHZYPWwYy03xcAxW3tsZpGgGTATN4XHm4yOfvhYYfT/nr1hNEiCwLqPj8OsVSLFqI6yFgd6lIZgiAP/+DoUb2bFa6BVyrFl74+4YXwmJ2H8p5tK8Zs3Qgzmmy/NglGjwK//sZdNFN95ZQ5u/du3nLUwsh3T7Qvg3mty0Wb3IitRjyc+OIxnbxiDP/28FDqVHCkGFYf5BHR7XjTZvHD6AsiK12F4In8DFk2XN5zN0x9GdUIsq7PRST6X5wz/vkl6FWra3DjWZMdfP+du5LMSNDCqFRyvlD/dVBpVxuSKvGS0ROk8c/mDnOu9q3wEOt0BXpy1cNJwrNx2BGoFieKMOBjVCikxLCHmaI+iwR/Z4TBQ4Y5S1IlVfNFXxKL41hP6S+IifG1nOs7XzRsd1Xyzp8RuQZoRucmGXteycMZuOBlx467QuZVyAove+D6q1EWQAvLTDNi0cAKnU4WRKjraaANJEnjp8xM8NvSa2cWsuXu4YW/kNTPyV4EgDaWMRKpRjapmu2BHUXayAU/OLkKb0wenLxo5MiS/xRwT+Z3i9Sosf/8QcpP1uHtqbq8yYGoFifHD45FqVOMvu06gojgdJrUMar2at6Yl6ZWobnP2aaycs/5FmqYbADR0/bedIIgjANIBzABwRdfbXgXwGYBlXa+/SdO0F8ApgiCqAIwnCKIagJGm6d0AQBDEawhJWlzUyeHeKkfMRMboEIc/yDISGJcVj5o2B/7w4TG2LW/8MDOs7gAON9iQlaBDq92DJ2cX43iTHSoFiZKhRliS8nG00QY5KTzAC9JMsLq8vOTa0qtyEaAo/PkXpfi+thNBKuSEfuO4TGQk6HD7q1z95OXvHcSL88vw2Ad72EQ18/dwzbjSoXGQy0Kvdbh8yE81itLNkXDucLabFJcvyN8V07To5G6SXph5nCiSeayQExgSp+ZoJg+JU0MhFxcAuP0BPDq9AI+GtUk+Or0AHpGGenYBne9nd4RcY8XAqFYIy1oMEoaBBAn9jYEW2APRdWDjRRaR+htJUTo2EvWxuR6KJoSZUiLleQYr+nOsRktMRpqtPfzuAUEz4GSDmmVLmbUKbFp4KbzBAP5X2SYofXS82YGXvgg5dlM0jTaHsD6wSa3gsYKXXpWLv/2vGmoFidUzCmHUhLQoX/riJJZMyUFWoha3T7bg61PtHO+MH+o6WbkItz+IN7+tZdn4I1MMgqZ2ke2YdZ1uaBQyyIiQcdJN47Nw44tf8YgX4b/RzmNNqGxycOLcJ64vQmlmHCeRLEaXV0wCuTf0R4K5r+jrOcON+R6YNhI0QmSSJVOysf/HTt6YWDG9AL/5B1dCYuW2Q3hsZiFHNmv1jEI8uf0I9tRYsWRKdtR7GZ6UGJ6ow+6T7TwiDJN8fuL6IvxjdzX+74oRPL1MCRLON+J1SsE51xyjeKGviEaaiVW801ecanVizfYjnI7MNduPYGSKASNEEncGIsTkksLZ0m1Ob4+J3ZGphl7XMma9Y/R1I+/pjNHp8PiFpS4YUiGQjnvf2sfGRkC3NJNZq8TcsgzcMC4LNrcfS6bkwO0PIjvZgKc/OgqFjGTjqavzU5BiUHHIh4zMFmNKH+pGGgVLog7pcRqOFNzK6wrw9EdHsWxaHlodPvzY7hL8/jnJeqyZXYx1Hx8T/E7/2F2Nl28ZC4DEyRY7T8t51XWFeP6zSvbzFpfn4HC9Ff/4plufeMFEC9Z9coCXO/jL/LFosvUtDjgv4nYEQQwDMAbA1wBSuhLHoGm6gSCI5K63pSPEDGZQ1/Wav+u/I18XOs9ChBjGyMzM7MdvMDARzdGR0Vo52mhDZrwWz9wwGi99fgLleanYtKcWFcXp+LamHSUZcShON6LFEaqEHG1y8Fr4Hn7vAG4oy8SjWw/hzitz8PynIUHsrAQNTydsecUoPP9pJVocPjx6XQHWzimB0xtAi8OLv/2vGh0uH/44bzSAkBB9RXE6Xttdg7un5kStiD41pwRxGjn21HQIasYxAeTvZxXC5gniz59V9Vk3Jxa4kMfq2W9SCHS6/JxXOl1+pMdpRZ1fLqOw6rpCLH+fO7EqZOJoWHZvAOs+Ps4GYUEKWPfxcayZXSzqeI1SDl/AxUku+wJBqBXipluHR9i92+7xRzmCi2iyLmfiCnwhj1MJFxZ6GqunWoULViPvmhSzwD5I01g1fRS0KkW3bILHDxqxYcYSoHhJl8dmFoIkYqMJGE2epyNGzOr+xPkaq0KJScZsLbzIDgCF6SZ2U5OVoMHqGUVoc3pxoN7K8XB4eu5ojMmMQ6pJw9X1ryjAP7+pYROwa2YVodPl5xEFHptZiGSjCkoFgZdvGYcGqxsdLh8oisayaSPR7vTBqFHg0Gkrbr40CwlaBXwUje9qOjmfwzCAKRqYWxZqC717ag6na2bxlOwoLJ7Qf4d/DhNvVjbbeV1qkcXt6jYn9tdZee976J1Qkj0v1chuPsW0AJ+NsRuD/kgwC6GnsZpsEDb/TdLzzxnNmO/xfx9Bh8uHFdMLsGVvLRZdmY1Ukxq17S7BOaCmzY04rQIvzi9Dp9uHFKMaf/28CntqrACAzXvqBDu/ZGT3PXrw2lxBLezXv6qBJxDEn35eim0/1GP3qXY8Mr2A910kDExcyPGqjACWXpWLEy3dcnNLr8qFbJCQ2u3ekNHoM58cZ5+5e6bmwuEdHOt5g9Ul2JHZYHX1eV0eaOM0GgtZaM5eM7sYZVkm3HyZBVXNdk6hdunmH/C3W8fx5t/ItYxZ7+ranYL3lDFZDJe6yIrXoKbdzZq1vf5VDWdtBsAmhpkcEZMkHmrWotnuwelOF2ra3OwxwxJ0+OhIE17+4gTHQC5SZssXoFHZ7GQ7ohZOtsCSqEO704c0kwq/vToPMpKANxDEp0ebeeP899cXsfe3KN2EdqcX/1hwCRpsHhxpCBmk/vpyC05bvWz8nZWg4ZjqGjUydp1lpJdmj83g6BOr5KRgvOPyBZFo7lsR5pwnhwmC0APYAuBumqZtPejFCf2B7uF1/os0vRHARgAoKyu7aHoPIx9gppUuPPDZcFMpVm87xHsQV88ohNsXQKvTF1W2oZtpUYnfXp2H6lYnhifq4PX78fKt49Bi9yJep8SpFgemjkpFdnLIefloU0gcGwC7CdEoZXhrTx2nfVGrFJahAEHgvn/tw8rrCpCfZmCrP5GsyJVbD+GlW8rw+w9CBiQtjpCJRXG6ETkphphrSwrhQh6rZ7tJ8UcxKPBT4pIU3gCBT46cxl/mj0Wn0484nQL/+OoUhiVmizre5grAF+j+SQgitDjYXOKSqx4/hSc+PMr7/i/eLE5bK06rELx/cRpxrr6ZUdzuh56B2/2FPE4lXFjoaazWtDsFg6badmfMksMGtQxUhGzCo9MLRMvn9Dd8QQL1bXa8+svxaLZ7kGJQY3dVEzLjxRXl+hsmjfA8aBQ5Dw5knK+xKpSYJAlAKSd4seCa2cXYvmQSWhxe1Hd4sPD1Paw3BXM9ucl60DQNhzcIg1qO3GQ99tfbWEbngokW9v+TDGose/sAzFolywwiCWB4ohafHW/BULMWdR1WbA6LB9UKEn/5RSn8QRo5yQYQBJCkV2Lfj528bhomLt26rx53T82Fx08hPU7LYQpTtHCHW1mWGc/9bAzqOlysSzgAuLwBnmQGc77Ittho76No8JLJvbUA94eGZH8kmIXQ01iVyyBo/isXmMKiGfMtmGjB29/VocHqxtyxmTBqFfixzQk5SSI9TiO8NwCBX3W5zDMJhQP1DjRYPawG9l/mj8WBOissSXq88FkVRg+Nw7iseLx8y1iQpAy3dpkvMteyfmfIFChJr8I/v67BB4eaBiSxREJ09BavDhTN2DNBgKZhjSDNWF1+pJoGR1esRqHAG9/UcDwW3vimBk/OLon1pYmCUi7rt47M872vOtNxLzRnL9uyH8/fVIo7u0xBI6Wadp9sw1t76jhr/qg0A0iS4FzHyBQDhpjUbIcO8/nrd1Zi7ZzuMcFIXWxaOIGN/SJloZrtHtBd6zGjHyxEJHykYhTSTGo0WD2obHKgxeFBXbsT15cO5aybj80s5MhszSrNYBPDs0ozQNGhIn6cRoEfOzwcUuXj1xeCJAgOOUwhJ7G3th1JehVoGvAHaZAE4PEF2PgqK1HH0cpnkthMDPbi/DK89MVJVj7r4Z/mgyQIBGkalw6Px/VjhyJRJxwzgwbcIjuvGZzT5DBBEAqEEsP/oGn67a6XmwiCSOtiDacBaO56vQ7A0LDDMwCc7no9Q+B1CV2IfIAritOxvIuODoQemP11nYIOiI+8dxDP31QKrUouGOgy4tkGtQw3lGVy3BxXVBTgwbf3wxegcfOlWTxWx9Z99bhjsgWeAMWpojAGd8yD9+qXJ7HyugKOC+uKigL8ddcJePyhVtLnfjaGZUgLXWerw8d+HjOZSCZ0scFZb1IICLraioXLF8CVI9M45oUrKgpEM2dNWjlvPC+ZkgOjVtx06YmieewROTk7vH7hCrvI6+9Pt3sJEi4E6JRyQYabVnlemqcEYfcEWekZIDRHPLr1EF6PkWyCjKSRZtbjlq6kSajjogAyMjY1IW8gINh+5w0MDo3CM0V/jdXIDeH4YQkAgNp2Jx69rhC//jvXtGvZlv3Y9KsJ8AcpPPD2fk78BwDF6Ub8bHwWp5ixoqIA+KaGTQgz15uVoGHbT8O1jtNMagw1awUZmw1WD8xaJVocPg57fcmUHCQbVYKayDISWDh5BJyekIbxqVZuYl2oLXXJlBws23IAHS4fHqkYhVsuy8KrX4aYwy0OL2SEcEI5si022vuYTWpf5RzOVkMyFqabjVavoPnvq78cj6yE7u/BjEWhuMiglgmaYP/zm1ps+e5HrKgowMpt3XuDkPQE95yRUiEdLh/21nQgQatETZsTP5+QBZIgcLSpE3WdXtR1uASvZUSSHnFaGeaNz8SiKbmDKnkooWcMRGmpPoGOsi8aJJQNt98vyBJ1+8V1RMYaUTuZBrjmc1/GfWTMEK0LeF9dp+D8+9IXJxGkuv0NmO6kww02tDl8qO904/6wLqTIJCzzeUD32spcb1F6HAxqJ+7e9EPUtVmtINmYRchkbvW2w+x1ttjdUCq0yE424DdvcKWLHn73IBZOtuCtPXWYVZqBTLNGMNm8ekYhOpxe9jt4/BRq2lyCJnhMDiM8r7DyugI8dG0envjwKKwu4Y5hGQk8NrMIHS4PHv5pPiiKhtMXxG+7PCPKskyY25Wbu3tqjmDMXNPuRICiQFG06LnunO2MiBBF+CUAR2iaXhf2p/cB3ALgD13/fi/s9TcIgliHkCFdDoBvaJoOEgRhJwhiAkKyFDcDeO5cXfdAQV8qPZEPsJAbIkUDiToFR9uFaQXocPmgVwmzd+ku5sXwRD0OnbZy9LkYpgiAqKyOcFdr5m/P7qjExvlj0dAZOne6WQO9WhZierpCbuR/3XUC++tt7DEOTwAKGYkEvbBuUXKYXuJAlZK4WECSBMpzkvD6bePRaPMi1ahCUZhofG8IBGmObiAAvPltLeti2hu0Sjle2HWIc/wLu0Ju2GIgI0hBzV+xSRtzlOpdnFYc401OygQr7I/PLBJ1fCw2iRIkDGSkmlS4e2ouTrV2t2TePTUXqSZxOuTnAtGMk5rtsTGODFIEnv+sijNvPv9ZFZ6KEbNHr1Jw9OhoOuRT8LTIeXywoj/GaviGkGmtzE02wKxT4KF3DuBn47IEx97nVa0YnqjjrV0eP4XbJ49gyQHM+1duO4Qn55Rg8T+/h1pBQqeUYfGUbOQmG2DUhJLcNW1u9rPmlmWwOnrMZ6zfWYlFV2bD7aeQn2pgk8/M35/dEWJ0zi3L4GkiXzYiEY1WN8xaBZ6/aQzcXfEfc3yD1YNNe2rx5JwSuL0B1FvdHGLC6m2HsWRKDpZXjILHH+yKtzVYelUu1n18PGo8OSxBh6IME6999p6puXjly+p+kXM4E/SXSZFYRDPfCS/EM2PxWKNNMC4aEqfljas3v63F8opRsLn9MGkVePnWMnxX04lhCTrQoDljijkmUirk21NtmDcuE0cabaE9jlIGilZh+XsHoxodDTGpMSLJhJwUKVa60BALw8b+hC9IC+5LxHYkxhpapQI7jzayc7FWJcerX55E2bD8WF+aKETzskkQ6WUTK4gd90JJ5Bfnlwl+58jmXo+fgkZB4s+/GItD9VYsKs/GrmPNmFaYxpF4iswFMUnYyHW9us2JhZMtyE0xID/VyBKbaBpY2yX9tHlPHTpcPs7avG7eaHadEcqDMde5cX4pWh1+PPr+IfzmcmHpqeGJOpYkdvskCytdFUmuXDo1B49UjEJVswO+IAWtUib4eRlmLc//YMX7h7DoymwsmGhBklF4fI3NMmP5ewexZlYRUuNIdDr9OBiWiytKN2HJm9+H8mTeILbuq+fFzDNGp4MA0SdTunNJm/l/AOYDOEAQxA9drz2EUFJ4M0EQCwDUApgLADRNHyIIYjOAwwACAO6kaZqhiPwawCsANAgZ0V3QZnRiKz2MM2NI1y2b154XPsi+OtGCmy4ZhjX/OcapKGzaU4vadhfyUg08vUHm7w9Oy0N7mOxEONuD2UQKPQxCrtbM3/bUdGD9jiqoFSTuu2YklHItnvjgIO69Oo/zADHfxaRVYOXWQ7j10mFYNaOQZUYzbWx6lQwfSMmwfsPZtF/5fEF8dKwJVc0OUDRQ1WxHg82DafmpUCp7b5n2BYOCFWZ/UBxjzOoWrlBb3eIq1C0O4aRNq0Nc0sbpFWa8uf3imL8GlYyTHJCToeSAoQ/t5ud7kyhBwkBGIEij0erhsW4CwdjRbhKjGsDFZrPR4RKeNztEzpv9DYfXj/kThmHtR90xy71Xj4TDNziYRmeK/hirzIZQiO2yuDwH2cnC0kMjU0Ltn8zfwpm37iha9m5fgG2npChwTFRWVBTghV1VqGlzh6SNzFrBzxiWqMPxJntUvXyKBoYlaDkEgBXTC7Bsyz72sx+6Ng9BiuaZmt1Qlonff3CEl1xmPjtJr8I9YbH26hmFmDA8Hq/+cjxcvgAy43UYnsiNf0iSQPnIFGQn6VGaaUa704fqNide+bKat2G9kJFl1gqOo6Hmbima8LEYGRc9UjEKvgC30yrNpMZN47M4v8mSKTkwqOQIUhTqOt1RpUIWlWeDpoHtBxtww/hM3NN13t9enYNjzQ5YKPDGNXOOx2cWoSQ9Tto3XKCIhWFjf8IdpRDT13bxWMEXDLIMx3DmpE/kvi7WoEAL7uti5RHB7NHbnF4oZSRcvqDgXl3suBfyOnj4vQNYM7uY4znAmKqFQ60gUTDExHYjMTmrpZt/QG6yHrdPHhG16zvTzF3XwzuJ1AoS/74rpCccKZ36xKwieHxBDInTgKJoyOUhk7lRaQYMjddGNYYryjDB66fw7I7juKEsE6etwutJkl6FB98+wK4XS6/K5V2/WauETq3g5OqWV4ziFcXVChKuKLFNilGNmnYXHJ4Ar2N4cXkOjjTY4AvQaHH44QuG1srw2HDVdQUsc3nL3jpevLf0qlykGFXYsvdHJBpGxD45TNP0FxDWCwaAKVGOeRzA4wKv7wFQ2H9XN7AhVOlZs/0I0uPU7ASQadbioyNNPHOH13bXYOu+ek4rVlaCBkumjGQ1upjPXL+zEuvmjcYLn1VBo5CxbE0ZCZRkxEFGAisqCqCQk/jVa6FjmTYBTyCI3/00Hz+2u+D0BaOyjuWkcOsdU3ny+Ck89Z9jePaGMbjj8mys/egobwJ+4voibD9Qj4WTR2D1tsOsIPiIJD2UMhIvfXEClwwfLSXD+gmME/f+OivLXCrKMKF8ZIqowPlwow31HW7e5vZwow2jM829Hq9XKYS1nUQyd41q4eNfFakNlWxQCbb1ik3aaJRyQcZbWZY4xluAAq8Yc981I5FlFq/9OZi11SRI6G80WD2CrJuidBNGJBtick06pYwnp7TyugLoYqQ5bNYqeM7Rm/bUiu646G8Y1UooZW6OdptSRsCoGhzu5meK/hirzIZQqLVy/c5KvHrbOJ6h8IrpBTBq5bj/X/vZGIxh3m64qRQ6pUwwlstK0LL6rhs+reKca+W2Q/jL/LFotHqgVcrR6ght+BjtPoIIxRenO1xYv6MKS6ZkC56DJEJyG0/NKYHbF0CaSYOH3zvAbsDMWiWcviCe3VHJxofZXfFhdbsTSjmB/FSj4GfXhkkMMGwghs3UkyQTSRIYlqhHZrwOp1qdUClI/PHG0UgxqJAZf3GstwQBQfO38K/OjEXGXOiZeaOhkBNQyWXY92MnshJ0nM30rNIMdoMMcNnjZr0Km/f8yCsAPDq9AHIZAZIAKADXFqVh464TWDDRgstzE7C3phMbd53EU3NKoFaQHKMjGQlcNiIRo4eYRJEXJAxOnCvDxvMFUxQvEpMmdtJYfYFSJmNjHaCbOSl2XxdrxGtVgvu6awpSz/u1MATCNduP8Ar6kURCseO+pt3JWZeBUId4gk7BId5lmrVQyEieye2jW7kdQUcbbchN1uNn47Nw/7/2Re3WaLR5sGCiBflpBtacLVxPuLbdCYIAe740kxo3lGVyEtGPzSzEzJJ0yOUkhiWGckDtDi9vnXji+iL82OaEWilnZVYji5ZZCRosm5aPRpuHNdsDAL2a310/tyyD/XzmeldtO4xn5o3GH7YfQUVxOmQkMGZoHGjQgt//xw4XNuysYgvci67MhidAseOrojgdc8syUNlsBwAe+3r5+4fYeIVZ1xZOtiA/1YhEvRJyGXD3pn2YMTq9T3Pd4JhVLjJEVnqYh+GGjV+xg/zPvxgraO7w1JwSHG20459dbem5KTo4vEF8W9MuWLWobXdhUm4y3vy2lk2GUTSwatsh3Hd1Hh7vYlwwD6VQVWLXsWZegMiwjn81yYLVMwo5bBKmMhR+HQGKYjcq4UFbdrIBr315Er++IocVQG+wetjAfeFkC26bOOKiYGmcL9S2O1HZ5OAld7OT9OzE2xNsHr/g5rZgiFHU+aO1W7eIZO46vMLaPQ6veMaZkMlKdC9NLjpcftw0PounGdwpkoHnCQTxVBfDn7n2p/5zDC/dIq59bNBrq0mQ0M+we4Sr9g6vODb/uUC704cdRxrwl/lj0eH0I16nwN+/OoW0GBnMeHwBQeawR2THQ3/D6QsKGnv+dZC00Z4p+mOsMhvCaK2VHU4/7G4fnppTglOtTihkBDpdPrTY5Jheko7tBxs4m2C3L4A2m5uXUF55XQHkJLC/wQZfkBI814E6K9z+UNv/uCwznpxThPoODydeXDG9AA9cOxIAcN81I9n1j2WNquWobnPC7Q+iJCMOx5vsHGbOrNIM9vPC48On5pTgn9/UYuHkEdj8ba0gc3XDTj6bmKLBEiGONtqQHqdBUTpfGivaWpt5BuavgxEnWp14bTdXAuu13TXITtbD0lXICE9ONFg9aLS6oVbKufFVGMNcRgqPWYoG/IEgbp9owaZvarv2N3okG1Q41erAba/sYTf3K68rxD1TR0KnJBGgumXvXtx1giXOMN4kq2YUIs0oh1otbYcvZJwrw8bzBQVJ4oFpefjD9qPs9T8wLQ8KRk9lgKM1Skdmm8h9XawhI4Ebx2XyCmGxuP0MgXDBRAuv+BspGSF23JvUCkGvHY1CziPeMbKFTTYP/EEaHS4vT+qHokN+AIxMlFC3xiMVo2D3+LFtbz0uzynBvV9wu8azEjTQKeU43mRnXxcqeD/87kHkJOtRMtQMigoxubNTDDjd4cJf5o9Fs82LdLMaOqUcte1uNHS6kJ9qYKUZmHjHoJYhQafi3Kt7puZCLSfxhw+P8K4/WieUyxfEoitzuF1U0wvw+1lFLBs5nNDJHPfEh0excLKFTRYzebR7po5EVYuDfV/k+UYk6dk1tsPlQ5pRg5e+OIHfXJmDDpcfvgCN3BRDn+Y6aTUcgIis9Ag9DN/XdggOkmNNdtaU4XizA+vmlmD1tgO4q1yYkZEZr0WrwyO4Kex0hSovTm+gi9Eh4yX91n18HC/8YiyON9pw79W5SNCpoJCRqOt0YcbodGiUMmz74TRbySAQSj7OHhvyGNyyN6QbE6dVIDdZjxaHj61cUTRwutOFSyxJHAH08O9blG7ClbnJUtKrH9Fk8womd0szzaKSwx6/8CYx8rVoSImivZMskrlr1ioFmb9xGnGMM4+fEjRZEZuUSNQrYXV5sXZOCZy+AHRKOVw+PxJ04s7viNJ+4vSKa78a7NpqEiT0N6LNKUkx1IsjCFrQOJMkYtOmqFLIBJnDpVnFMbkeV1Q908HRhnqm6I+xymwIo+m8Hm6wsQnUB6fl8UyDI1s7GTbLobpObJxfxib4XvvyJK4vHQpLsh40BUFWcMlQE/ZUd2Dznjps3HUSf5k/Fvf/6wBvfWWMYh6clocNPwvpBxMAEg1KNNk8eOzfR9jri2zdjJYEr2y2dxnW+fHLicPRbHPjpVvK0OHyw6iWwxvgGwqpFSQK0oxIK89mWUEbd50ULLBe7GutRiFDh8vH7jmA0P3TKLoZuJHJiRSjGkvf4mtXb5xfhv11nRgzNI4ds0yCXkYCuV2bfYMmZFr40hcnsWRKDkwaBdqdftw+ycLqXN7x9724dHg85l86DD+2u1gG2P56G/BNDZ6cUwICNJINob3W0HhxxIX+gNTVFRsMdi8Otz8Ak0bB6aQxaRQxK972FQk64Y7MeN3A1uxl0GD1CBbCxmTGidoX9ycYAmG0dS9cMkLsuFfICMF9/+aFE6Jeh9sfxL4fO5Gfxu/K2bqvHrlXjWRfC+/WyEvVo7LZgQ07q9Dh8mHVdYVIM6s4JMOsBA3uuDwbN//tGw7rONp3brB6UJBG4bPKZlQ2OfDmt7W4oSyTE1//YVYxTBoZ9GoFx1iXiXfmlmXgj59wGdDPfHIcCydbUNPmxutf1WDRldlINalR2+6Cze0XjK8UcpLvz7D1EP78i1I2lirNjMPv3jnIM+PLSTbgoZ/kIT/VCJc/iBUVBaBoGgk6BfyBkHZzV/6bzZ8lG1WsZ5eCJPDCf0OeXb4AhX9+XY2bL81CXpdkmFhIyeEBiMhgSqiSTtHCcg1GlQx3XpkNGQnkpxlBUTTMWiX0SjmP9bG4PAdrth/B6hmFWPg617l6055aLLoyh1NBeaRilKCz5He1If3gO6/MxtqPjvOuacHEEOX9sRmjoJDLsO4TbmVKr5LjoXcO4I7Ls+HzB/H7sMroIxWjAAAOr7B0xYF6K/xBWmJF9iPEmIz0hFSTcBtLqlFcEKAgScFWRaXIEi1BCDN/SZEV3ujfX1xSQk4SaHP6sfz9w5zrH5kqbnzqlcLmkFqRLY+DXVtNgoRzgUiTqaVX5YruBjgXUMnlWLmN65K8clvs2iw9fmGtd68/NsnYqAYwIots5wLnK7FztmOV2RDmpxqQYdayDJasBA0emJaPymYHFpVnY8veOkHT4HD38aVX5eJv/6vGvLIMFA2Nw8LXuRJjTTYPhpo1aHV78OScYtR3uDlrt1aZi3d/qMf8CVl4/asa7K0RJjYwm77fbz+Kl24pwyPvhdidD107Eg5fkGOGzLRuMrq0MkI4HlbKSNZ0rqrZgQS9CgfqrNAoZLj3rX0wa5WCsUZ1m5O3URZK+sZ6rY11otGgkgveP72qe2sZnpxod3rRbPcJ3rM9Ne0IUsBD7x7APVNz8cY3Nbz5aNm0PLzw3yrMLcuAWauEJUmHvTUdoOhQMmLZtHxW5/KnJemsC314AmB/vQ33/2sf/vKLsXD5/SgZknje7pnU1RVbDGYvDgUpw4PvHODNca+JlMuLNYJUEHdMzmblLplieJAaHMXeFKNasBAWC1kShkDIXAOPSBVxTWLGvdMXFJyXnRH7XqE57Hc/yed5Vt1Qlgm1gitFxXRrrL9xDIIUWJLg859VIjdlDHJS9GzxIy/FIMg6Zr5jZBFao5Th25p27K+zYuOuk4Ks6gfe3o+XbinDqggpiPU7Q7JFlkS94D1gkrENVg/WfnQcaSY1Hr2uAA6vX9CU9nSnS/Bzvq/tBABs2FmFl28pEyxMx2nkcHgVrAxsSDajAEPitLC6/Vj3yUHOWptqUuOBLftZ74V7puaixeGDWkHidKcb15cORYpRBbmsb+uLlBwegIis9GgUck7wDoQCoUg9lafmFMPhDWLdJ91aw8srCvDbq3PR7vAiXq/EoiuzkaRXQauSo77TBV+ARoeL34ZfUZzOc5Veve2woLMkox/MBPfMpoHZzJg1CgCASatizeaY97j9QWQlaOEL0Fi5NaSdEnnOp+aUCGoRMy2BHS7fRcPUOB8QYzLSEwJBSlBLM0iLY8Q12Dz48EBDyNXWF4BWKceLu07AkqiDGPVLhycgyPx98eaxos5vENAWUitI0VqgNk+A1e9mnoE3v61FYbpJ1PEapUxwwyU2OTzYtdUkSOhvdLr9+Nv/qjmsj7/9rxo5ybFbM1rsXkGNN7HGl/0NtUJ+Vlrt/Q0aNP78izGQESTau2Q3gjQFxIhZfb4SO/01VkmSAA1gw6ehRG9usg6+IM0x+lpcnoNAmFFMeOxWOjQOpqmhzcdDP8lDepwGdR1uNn4TkhgbPVSH+/+1n8e8YTZqCyZaohIbmPDA4w91ydw9JQdxOiXcvgAcrU4AoU3gHZMteGHXSXj8Qbx8axl8ARoUTfE2pw9dm4ckgxq/uSIbI1MMWLntEHwBGnPLMpBoUOGu8mz8/atavLa7W6PvSKMNr+2uweyxGYKbuyZbiBjBJGMZ5mks1tqBkGj0BiloFTIOm1GrkMFPce8dk5wAgAP1VsF7FqQAlZxETZsbr3xZjUenj8KSTZHeK0fZDkW5jGBZYYxOpNMbwO2TLJg4wowvT3ZwCgrhBY/fX1+EFKMSlgTDedUZvtiZ5hLOHM1R4oXmQSLLIJfJ2MQwEPtieF8xkGRJmGtZs50vdXCm1xRt35hi5K5lQnPY4x8cwesLxmPtnBIcbbKDpoHXv6pBkl7J8b9SK0g8ObsIte0uvPRFt2zlIxWj0GT3ItWoxrhhJJRyGWvgxsQkJAk8NacEMgJYO7cEpzvdnAL6iop8DI3XId2kwe2TLNCrZIJreH1XDBP5+lCzFnqVsK9CcboJ916dC08g9PrWffUIBin87p2DMGuVbKxGEgBF01F9uIIUMDwxlF/xUzRvn//o9AIQJHj5i9p2NwA3r4j/7I5KLJmSw/FeIEDjiesL4fYH4fAE8PxnVfjDrGI02jx9YrhLyeEBiEg2QKZZy5uUbijLxKZvarFwsgVDzVqoFTLISQIrt+5nH6gbyjJZnd7FU7LR0OmGjCSwIoxRuWRKDpIMSt5ANqnlgg9QZjzXWfLx64uwfsdx9j1ZCRrcdtlwtLl8rJkZQ3n3BaioGwumqk9F7Ps8fgo1bU7ceWUOnu/a5MhIIC/ViBc+q2JZzBIrsv8gkxE83b/7rhkpuvJE0cCfPqvibG7/9FkVnp47WtTxyQYVri1K47jaLpmSI7qt1uUXroC6feJkLVSy0CT9aNhz8uj0Aqjl4qjHQUqYgRekxJ2/zemLquMnBgMpiJEgYSAgK14nyPqIpTZomkktqPGWaoxNEafNGUUT0BmbzadSRqLF5sPysCLjqusKkBijNtTzldjpz7HaZPOgps2N5z+twnM/G4NH3ua2Oq7fWYm1c0tYJk5kXPZIxSg0droRpAGdSoZUU4jNLSR1tu7j43hqTkmPrGCCAL460dKjD4VaQeJEiwNrth/DQ9eORJAGz//gl5dlwaCRY9+PVk4b6rp5o1HV7IBCRsDtpziJ8J7kM9bvqMKTs4t4xIfIzZ0/SOMn6z9nj99w05iYrbUDIdGoksvw8pen2FbxIAW8/OUprL9xjOD7GaZ1JDP+ieuL8OyO47j36jyWEWeLor2dYtTArFPg9lf3dG3MhyFBr8KxRhs276mDUk4gM17LGTPM72xJ1OLlW8bBoJYjPU593g3oYs00v9gRa6b92SA9To1fX25Bq7N7b/3ryy0YEiOPgr6i3SXcMRDJnhyoGEiyJOy1pBrQ7vRi08IJcPmCZzWmo+0bSQLYfaKV/exoc1iD1YPjTQ789fPuBGaD1QPld7Ws7m9anBoeXxBrP+LKSq3edhhPzinBjqNNyE814p3vT+GX/28E7r06FyOS9HjpixO4xJKEymY7SjLiICfBrh9AKCna6Q5g5Wt7OLFLuPQU0CV5FKUzN0GnRFWzHb/7ST5aHF72GUs3qVHd5mTNdplOZDrse4fHakxHVmTSfsX0Arzw3yrc/v8sWDAxVLTUdRHBQl1yMnS6vGi08uNwKqxwHnnfGWZ3mkmNOyZb4PIH8et/dHfM3Hv1SNg8fuT00XhbSg4PMERjA0wdmYy/3lKGJqsHNe0uvP5VDTpcPlxblAaSBAiAwwCJDN4pGvAFaZ6b9LM7KnH/NSM5wXpWggY5KXrBB0inlHOSVnEaOf5v8gis2nYYW/bW4bGZBTjeZWZm1ioxtywD3gAFhYxEbbsz6saCofVHQq0gMSknEfkpRoxM0aPR5sWh01as3naYTQxLrMj+RYvDCzlBcNggcoJAq8MrqvLU6vSyG9JwiE0y+IO0oPaR2PYpYxTmr14k85cG8Of/cpPbf/5vFZ6eK4a3DGgUirNi4OlUwjp+OpEbmYEUxEiQMBCQblRj1YxCLA9LSK2aUYj0GCVigZCMg9A897JI48n+RkJUGYfYJGPdPopNDAOh+7P8/UMxa6M9X4md/hyrKUY1yrJMuPkyC2iaFrx+mqax9KpcOLwB3rrFdItlxevgD9L4obYTK68rQH2nMPtGISMEx5BaTrJr2NyyTJbNrFGQyE8zYlWXQRjbJaOQIc2kxtB4HZvgZc7x7I5KvPCLsTjSYOM8PzVtbtakxxsAy0xijutNPiN80yi0uVszuxiPvMfd1C5643tsXzKJ4+Z+vtbagZBoJAgav7kim9clFimBwiTl3P4ghsZrsfG/J7BgogUqOYmSoSbEqRX4+SVZaOh0hUwwA0HUdbgEx5JRI0d1iwNmrRK3XjaMlbJjksAUTbPPDnNPmP1FskENhZzA0AQ1DJrYtYNHfidp/3LuMRCY9mcDkgi1/kcWyvrYLR4zxGv5JDS1goRZpBfMQMBAkiXp72uJ3Dcm6dU41ebAtGc/5zwvI1MMgr9jqlGNpz86xls3b7lsONzeINQKGRyeALxRyFtVzXbWB+GxmUV44O2QVEJWgoYnR/LHG0ZzPiPckJb5vNXbDvOS3Y9OL8CrX57kXeOSKTn43bsHoZQTuPPKHM4ztrxiFP7xdQ3ns1duPYRn5o0WvA8kEUqKb9pTi2fmjUZlswMBioJSTuBXkyxINarRaPfiVKsD6XEatDodaHV6kWnWIsmogT9I8T5XRoT0/aOdj7kHQjHO2o+O4dVfjkemyM5vBlJyeIAhkg1g1ipxtNEGhYzAwXorq7c3e2wGyyjscPlCTothlPhI0W6NgoQ3IGwU5gvSMGkU+MsvxsIboGBQy/HA2/sFZRxq2p1s0kqtIDH256X4y64TLKNXISPx7I5KQRbKg9PycM/U3KiarpnxWjg9AQ4zed280ShKjwNJEigZakYRRSNI0Wy1UWJF9j+UMpLVfWagVpDY1IMwfTjiNArBSczUJS/SG1qjMNhaRSaXlTJhWQaVXFxytd3pF0xudzj9oo4/WwaeWi58/eEmL71hIAUxEiTEGoeabGznCVPwef7TSoxI0mFsVnxMrima8aRDpPFkf0NJElG03mOz+2yyC8+jzfbYMJnPV2KnP8dqhkmDeeOycP+/9nFMXcKvXy2XgaJp5KcaBe93ukmDmnYnxmXFQ62UwesPmaYIfRZBCI8hGQGsmlGIOI0Ci9/8Hh4/xa6vWQka/PbqPLh9AdS2u9mYdsmUUJJQ6JrcviBPI5FpP800a6BTy3n+GBQtzLyRkcBjM4s4m0Zmc/fCL8ZCJQ+11rY5+Y7sHj+FRpsHEyyJ532tHQiJRq+fEuwSWzunu5BOUTQ+PNiI3771A2dMfHigAdMK07D8vYN48Np8bNt3GvddMxIPv3cQv7k8G3/cUSm4BwkEKRAkiZsvzWJZ4EB3Enjl9ALh/YVZC5c/iKKhBsTFIDEMSF1dscRAYNqfDexe4WJyUXpsisl9hdXt5z3Pi8tzYPWI21dJOPcI3zeebHFg0Rvf856Xf91xqeAcZvf4ceO4TFZSUUYCEyzxqO/w4L739rPvff6m0qiSC8x5Hn73ABZMtOD5T6tQUZyOF3Z1rzEaBclLlEYzqQtSFP4yfyyONNiRFa+F3e3DlPxU9hotiVqo5DLUdbowe2wG1HKSV1hcte0wey3hn+32B3k+XiumF8AfCMldtdi9ONnqwD+/qWUL38/MGw2nL4iXvgiRJ399eYgQ6fAGkWRUorrVjQ2f8te99Dg1FHIZr+OKOV8o9ooe4zTaPKjrdEmyEoMNTFW9zekFTQG/uSIbviDFOu9GBkdv7anjBL0AYFDLEAjS+MOsYpxqdUDZxdRgBgpJEIKOkmoFiZxkPVZtO4SK4vQuyQYDx5mR0ShO0CngCQSRZgoJsz9SMQortx7iJNKenF0Ej58SZAf/fvtRPHRtHkalxQteR4vdy+q/5aYYkJ9qxPBELguDJAlcnZ+CTQsnoMHqQZpJjYI006Co/A4WuKII04s1ZPP6g7hnai6nffOeqbmijY2iGRElipSV6HAJyzKI1Ww0qOWCrrp6tbjpMvEsr18pDzGswpnbOqUMCpGyFhIkSOCi2SbczRCrRCPQA5NGK66I1t84bRXWes9M0EK4SfzcItUoPI8mizQ27W+cr8ROf47VI002drMjxIZdMiUHp1od+MOHx/DAtJGC97ve6mYZPatnFCLDrMYDbx8QTNzZPX7BtXfldQV4/IPDmF6Szostatrc8PgCAI1unwqtEqOGGNFk9WDJlGxsDot51QoSerWcY0IXLlXGdKz99upcNNk8+PtXoc1ZNNO6Sy0J0CgI3Dg+C8/t7JYuK8uKx2WWBMjD1t1YJ2PDMRASjc326GOV2de0OrxsYhjoTmqtnVOCV748ieUVoyAnCSyZmosjDXYsryhAZZMdHS4f627P6DlmxWvw5PZjON7swLp5XAkTpjgQzRC5xeFFboouZolhQOrqiiUGAtP+bBDVKDtGxeS+Ik6rwKY9tZy1YdOeWk4hSUJsES674o7C8P3ocBPGZsVh068moMEWysEY1Qpcu/5z5CbrQ4VebwApJhXkBMnzrlq17RAem1mEh989wCkSMLJSzPuYWMCglnFkGrMSNBg728xJlEZb2482OvDSFyexZEoOFDICy7ceZnW7c1N08Ppp1vSOiW+iFZDD/RhkBNBq92BsVjx+d20+WpxelGaa0Wx3A3IZfhMm6/DgtDzYvQF4AhRUchIykmBzZE98GCLhFacbccnwePb7MOuejATGDYtHgKLw679/hzWzijjPzz+/rsEvLsnE2jkloBGKn4Tuw4kWB1KNaik5PJjAtLqs2X6Ep1Ma7sYM8E3hitONuH3yCNA0FXL5faf7YXtydhGeuL6Ifc3tD+LPn1bxTOxWzyjEnz+r5Jyb2SQAoaRypEbx/dNGosXmgUmj4DEpWhxetooh9JCZdSo8/B5/Y/HE9UUozYzDmMy4HgMmiqLx0ZGmQdsaNBggVpg+GnQqOdJMSmycP5Y1Eup0eaFTiZtu3L6AYIXZ7QuIOt6sUwjKMohNugSiuOoGRLrqyqOwp+Qix6fdE8Cf/3uSXYiCFPDn/57EunlSECVBwpkgTissNWMSWfA5F7B6/IJFNJs3NkyaDLNGUOs9w6SJyfWQJASZGbIY1cjOV2KnP8dqg7U7IdJg9bCbjsx4DcvSnT02A2kmNTQK4Y6VDw804M4rs0EQQF2HC0PjNVh0ZQ42fVuDJ+eUgKZpxOuUePaTY5gwIklw7ZXLCPgCNPv/kd+trrM7Af3gtDx4gxRrNsZcB8MoXj2jEB0uD4Yn6tjrZcgIQh1ri8tzsGlPLbKT9YLMG5WcxJJNP8AXoDlmT5nxGk5ieCAkY8MxEBKNqVFixVSjmm3hXzm9QNBISyEncX3pUKzadhgLJ4/g7EuenFPMPvvPf1rFFh9+bHdhf70NACAnuwkw4cWBt79TCo7jofFajEqLO2/3Jhqkrq7YYCAw7c8GelUUo2z1+dXNPlPolTLceUU2z0NArNyfhHOLSNmVJVOyBcebUkbi8Gk7Z35dO6cEZq0S0wpD8WNush4/uyQLDdZOwWJwu8PDJjlHphiw9qOjHMKjWtFtUJsep8V9XTEp46V169++xd1Tc9jPUCtkvFiaSTgzxcg//7yUcy1xWiUbYwCh/FQ0KaOiISZoLpVxvvO9V49Eh8sHvUaO4Uk6GFRyeP0UlmzqZlubtUq4/EGOXvG9V49EmknN5sjSTGrcMD4T31a3c2I1JoZaVJ4NpSx0TXWdbo5cVppJjU5PAMu3HmYT55Ex86PTC7o6DEx9Gg9ScjjGYFpdGDfn8IF6pNEmmGAdkaTHqutGQSmX4f5/7cOCiRZs21/PPigA8PTHx7F2bnGIBeQNIC1Ojfd+qMeGnVWs1pclUQe1gsQtl1mw9qOj7EBlNgluf5B3Tc/uCGl3TcxOhNXl5z1Im/f8iMdmFuLHduGHzOULsKzk8ApIskGJYYn6Xisbg701aDDgbDdBBBFyprW5Q/pCNg8BuUwGsXsWlUKGnUcbOQy2V788idKsOHEfQAsnZ0PK3CLOL5dj5bbvOGOsL666rVEM5UaIHJ8pRrXgBltscl6CBAlcqOQyrLpuFLRKBZzeAHRqOVxeP9R9kGrpb2iUMuytacVf5o9FR1cR7e9fnUJRujEm1+MPUIJtq+OyzDG5nha7D//8uoZdBzRKOf666wR+c2V2TK4nHMzG5VygP8dqmknDicMarB689MVJtk2S2YTNKs3A77cfRW6ynr3fSXoV/vjJcV732ohkPZKNSsy/dDhONNuxeU8dOlw+LC7PwfaDDTwCwuLyHKzcegi/+0k+tuz9EevmjcbRRhsoOtSRc+O4TLy2O8Qa8viFtYGf3VGJp+aUoLLZDrNWgf31Vrz3Q+jYp+aUINjltxHNz+L128aDJAFfgMKff16KVocPrV1Ehj3V7SzJIXzNvWxEAiceHQjJ2EjEOtFYNMQkqI+doFfi5y99DY+fQpxOyTPefOjaPMRp5KhssnOOB0K/2f3/2o+lXZt/lZzEsEQdGjtdyEszojjdiOPNDtR3uPDYzEI8/O5Bzu/eYPWwHYg5yQYYNXLEaRQoSDNxkv0SLi5kmrXseGHG4WMzC/usxRkrKOQEVk4fhXqrhzXLGmJSQzFIRIdtniCej5Cgef6zKjw5WyK9DARUtzmxZvuRbvkGpYxnHLq4PAcEAew40sjmlrQqOTpdXvzysiw4fEHcPsmCccPM+L/X90aVsgpfM+s7XbhpfEgiiOn6sSTq0Wh1I82kRk2bkz3+5kuz4PaHzpEep8Xaj46ya3eaSc3O+Ucb7Xj9qxo24ezxU2zylCFCquTZbM6LKVxqlDLeHPFIxahQ8ftNblyx9qNjWDunBE9uP4YOlw+PX1+EhggvBiEt5LUfHcNTXWx5pkN5464TuPfqPCyekg2KDhVPGSkKmgZ8XTrEf/+qlpMEn1uWwTHmq2lz44X/VuEv88eisdODFocXnW4fOlw+xImU9WQgJYcRWwfTNqc3xOQwa3iJYIoWZlkcb3JARnY7OEfS7hkGUqPVi/v/1a31sqKiAC/sqsLb39Xh5kuzOHR6psrCbBLMWiUe+km+YHKaooFGmwedTh8vCbd4Si4SdAqkGFRIjwwaryvAkLjQZiW8MqJWkJg1ZpKo+zXYW4MGA/jSHRoUpBlFPxMygoDVHeAxvsS66gapIGaXZnIYbCsqChCkqN4PRqg9Wig5m2HWYqyI421uv+AYs7nFMfp0SmFDOa1IQ7mBxlCSIGGww+nzI0gTnDVvxfQCOH2x07szqhSYkp/GYUiuvK4ARnVsZCUabMIavw222EhvxOuUON7swOJ/fs++plaQiNfGxsDmfBka9edYzU8xYNV1hVj+fnccxrBwmc/959c1mDwymcP8YZhDV+Qlc5KtZq0S9R1u3P+vSl7syJi72T1+ztrLbNKON9txdWEa1mw/gpo2N5ucee3LalHawJXNdqQZNVi/oxKTRyajps2NNduPAQixa3rqWGt2eHFNfio+q2zG/jorKBrISzHgqY+OYnpJumhGYayTsQMNcjmJFKMSa+eUwOkLQKeUw6CRcRjrFMU1GDZrlXD6grjlb9/yxlD4Zj5ep8I/vgl1Nd4f8SzICBqZ8VoQJI0//bwUdje35b7B6sH6HVV4cnYR0kwqjEwySInhixy1HS5WNoaZm57bWYnSTPOgeJ6NajlIkuSYZa2eUQhjDLuf+oKeJGgkxB5tTi8vj/TgtDy8dtt4fFHViiAVWst/fYWFtz9/dHoBshLVWPJmKDZaPCWUeI0mZTU8UYe1XXrGTLHwpVvGor7Dy4lVVs8oRH6aAW/t/RE3jstEgk7JYZ4zOa2aNjc6XD4MNWsRp5Fz2LUA2E74FdMLWMkHX5CbLGY+8/HrC/Gnm0rh7pLB/LHDhb01HYJxxfFmO+ZPyMLrX9Xgd+8cwFNzSjixRLR45FiTHX/9/CRWTC+AxxfADWWZLDs6vNuJKZwr5QQev74Iv3vnAF75shoLJ1tCRS2Bz69pc+Pb6g5s2FnFsrrXzC7qsxzbRb9aMgH/T9Z/jp+9+DV+sv5zbD/UCIo6M2oIRdE42eLA7hOtONni6PFzKIrG6c4Qk+PHTjc7gBls3VePVdcVsK8zg+bt7+o4AXR6nJbHlnjmk+OobHbw2I9PXF+EJ2YV8aoZ63dWstUTpvrOnDMcakXIHdGgkqPN6cOHBxqwYKIFi8qzsXCyBW12D2792x786vW9kJHAn24qxdKrcrHoymy0OX04fNqKJ64v4nyndfNGY3iiuMQX0xoUeU2DpTVoMICR7rhh41e44+/f4YaNu/HRkSbRz4TbT7GJYaDb3dPtF5fcJQkZK+nAHr/tEEhC3HSVYlSxydkNO6vw/KdV6HD5kCJycjR1GeqFQ60Qb6inV8uxMuK5XXldAQwigziGofTB4kl4c+El+GDxJEk2RYKEs4BKLheck1Sy2G2s7N4AVrzPvaYV7x+C3StOPqe/kdKl8RsOtYJEiiE2Gr9yEoLzqCxGZO9oXUvVbc5+PU9/jtU6qxvPfxZKiKyZVdTVQRMyNF4w0YIX/luFiuI0jEwx4Hc/yefEkZv31CEzXtsrE4aJHT3+kE6gwxsyXGHWXoYBE6SAlVtD3hbMsQ+/exBX5CVzrpnRDwyHWkHishEJsLr9mDwyGfou82UGW/bWscZ3Qscea7SjtsOF8pEpmDk6HROzE6BVyVDT5mY3sJExqVSM7R3VbU4sf+8QjjTa8WOHG0eb7Fj+3iHoulrgAXD2IUDPY4iBWkGi0ebBfVfn8fY2K7cegl4VitFIyNDp8iM5ytyVbtYgO0UH9SBJoEk4d2iyedjkJDM31bS50Wz39H7wAIDVFeTptz7y3kFY3YNDc3igxRcSuFDKSFYTelF5Nm6fZMHLX56CVilDXqoRL31xEg1WD4Yl6Hj780e3HoI/QHcXBLuIjeFSVounZOPJOSV4bXcN9tVZOcc/8eFRUBTBJoaZ1x957yAomsadV2TD7Q+yiWHm7yu3HcJ9V+exWrxtTi+e+s8xPDqdGzc+NrMQm7+tRaerm/i161gzHr2ukLe+/O6dg/AGKPz2rX24843v8cdPKjE0Xis4doMUsH5nJR76ST7MWiWsLi8nZo0Wj+SmGHD7JAsarW6MGmJkJbHuvDJ0372BIJ6eW4KSDBNWTB+Fp+eWwKiW45l5ozG3LANBCnju00pWaiby8+mu+796RiGe+ugommxeiOTWsbjoV8z+lCnoK7Okus2JZVv2C1ZYshI0eGBaPvwUhbVzSuD2B1Hd5mKr6xoFyVLSowmHR+byPH4KHS4/Tne4sGCiBSlGJbISdGiyeaFRyGB1edFo97GVjxd3ncCj0wvwaITmsEEtx0PvHGRbCcMr/ovKs9lz/e6dg1g42YIgxW3X+/uCcfjgDFvzJFblucfZPhNtTp/geGx3+kSd3+r2C2rUWfvA3H1yTjGqmh1s+9WIZD10Ipm7Ll9AUOvSJVLz2OkNCDp4//76IlHHAxJDSYKE/kRzFFZssyN2rJU2h09wnmsTOU/2PyieJuvqGYUA0ceosp9A0wQ0CgIbu2Q3zF3a9aBjUyQ7X11L/TVWmY44JiGyqDwbG3ZyWVtpJjXitEqs/egoHpiWj5XTC6BVyVHf6cKrX9agyeYRxYRhjFBoGti2vx4rrytgCx/hzFCzVom8VAMbJ27ZW4cRSXr2HGoFicwELa+ddcX0Aizbsp9lHN8zNRcPXZvHGrp0uHzQKWVQy0lBWYvtBxvw/0Ykst2B44cloLrNydvAmtQylGbFwx+kUN3mjLlsxECHENtscXkOaIpmuwqZltjexhCjJc58xs6jjfjNlTm4fVLI0Z1ptfX4KfgpCk02H/xBGv4ABac3gDWzi7BsS7fvyqoZhRiRqMGR0w6kGAPSb3mRI8WoFjSaHizEoma7VzBeGCzMW5NGxutiWXVdIUxaSXN4IMAXpATncrc/yMopNdk8Uff3zrD9cXg+i5GyWlyeg99/cAQdLh+CESGlx0+h0y38uQ2dXix//xBun2SBx8+VgQAAGjT+uKMSHS4fFk62oMXhA0VTWDjZAq1Show4LXxBCjddkgWZrLsbf1JuMlzeACtdNDxRh/pOFxzeIBqtbs65TrQ48MIvxmLF+wfZGCRc07iy2Y6bL83CiGQDHnh7P0cLmRfLVBTg6S45DLWCxPBEvaBXQppJgw6XD25/EGVZZtz1z+85z/+M0elotXt4uYpHKkbB6fHjmXmjoVORqGlzY93Hx1GSEYfhfYhTL/rkcH8G/H1NqkWemyCAp+aUQK+SodPtxz2bf2A1WHJTDGC6otJMaowaYsTSq3JxosUJjUImrOsSEQepFSTSjGrY3X58dLgRs0szOS2tq64rxNhMDdK6guv99TYo99bi1dvGweun4PAGoZQRWL+jkk0GM62E4fp14feRCnOgZq5BIZOdceJrIOq+XWhosnmiBCHinolkg7DLfJJeXIU41ajiadQtmZKDVJEVZpvHB6+f4rVf2bziki4apRxb9lZyNJVe/fIk7r8mX9TxDm9AsH3KMUhchSVIuNCQbFQJbwxFzknnAhlmteA8ly5Sfqe/oZTJYFDLQi3iXVq3cjL0eiyQoFeirtOFPTUdoSJfK2BJ0iFBHxtZifNlaNQfY5UhKhxrtHGuOfL655Zl4PnPqnDT+CzW/JgZh3dMtmDr/nqOBl+4KzizcZKRQG6KAWvnFkNGkMg0a+D2BbD+xjE4eNrKtqMCIc3A+yIMDw0qGdbNG42TLQ6UZpnh8gWw9j/H2Q1WboqB3UwB3Z1xf725DC/fWoa6djcS9Sr87t2DXTJYao7ZzYu7TuDaojTc8rdvOISCq/NTsOGmMazMhFElQ7xehV90aeWqFd1GyZnxUowpBAIEyzZjxuqmPbUozjCx0l56lQzLK0ZhVVfCXq8U3q9kJxuweEo2Jo5IRG27A9eXDuW4vjOb8Q6XDyMS9TjaZOdoQ666rgCv3DoONe0uDI3XQk5SuOLpz0URdSRc+Mg0a3FXec6g1RzONGsE44VMc2wMY/uKVocfe6pb8PKt49Dq8CJJr8I739Uiwzw4kvNAbCVIzzWUMlJQr3/TwgkgSQLDEnQ42mhHol4pOH8b1QpO4pYkgFdvG4dGqxcnWhzs3L2iYhRe2HWCc261gkRClM/Vq2Xsa+EyEExuLEDRuOXSLAwxa2DWyjEuKx6/en0Pm3ANl+d6bGYhnpxdhPu3HECKUQlPgGIlKJg1Zuu+etxVnoMrcxMxbnhChOREEdrsHlg9QZYUyTCIn91RiXXzSnh7/zSTGhvnj4XHT8EXoPBURCxzqtWBuWV8r4RHtx7CwskWrN9Rxcp0hMuxAsCzN46GSSPH324dh9p2F7RKOV7cdQL760Nx3zPzRrOfJ5bcxuCiTw73Z8Df10Qzc27G2ZHJ/i+eko2Nu04KVhMeujYPbj+FykY7gjTY90Vq/y6blod4nYLDyFhcnoNvqtvx7I5Q4ovRjGGuc/n7B/GX+WNhd/uxZEoOnL4gdEoZ9v1o5YmStzh8bBWfYY0srxiF53ZydVbJiMTwkik5otv7o0FiVZ5bpJnUuH3ScDz1n2Psb37fNSORKtIQTa+SYdV1BXxXWpGuuoEIjTqPv8sYaYE4QzgZKRNsvxJrKOfw+lGel8rRVFpcngOHSM1Hs1Z4kTNrY6MlKkHCxQ6tgsCdV+TwWCtaZewC+0BXQMmf5y6J0fXQONXq4m0+E2OUQHd4Azjd6eEU+ZZMycGIpNjIbpyvrqX+GKsMUcGsVbIMHkZ6Ifz3tSTqUVGczhqcAN3jcO2cEtx6mQUtDg9euXUcWhxeJOiVGJagwx93HOexjFZdV4jnPzvGMmLWzC6CXiVnY8fFU7IFx/szXfd0w02lePDt/Xh0egGU8u7v6u4qtobD46dg9fhxTX4qUgwu1He60OEKFX+ZDZRaQWLBRAuuyEvmnXfp5h+wfckk+AI0O74WT8nGune5ccND7xzAwskW5KUapcSiABxenyDbLEBRHN8FxiwoP9WIBL2C71VSnoOnPzqKG8dl4mijDZkJOtzxd66T/PqdITPsgiFGtDh9bJKP+fvy9w/hL/PHYsX7h3D/NSPhDVBn3P0m4cJDTbuLN2Yefvcgxgw1Y0TywB8TfiqKYeyw2BjG9hXeQBDDEo247RWu1rg3MDhIM+fLcyBWcPmCgqQwly/0+zAxxRPXFwh21qaa+KSue6bm4liDFT8pCUlJKWUkZCRw47hMzvuWXpWLunYXx2wtFEMUI04bymPtOtaM1TOKsDAs8Ru+7vxhVjE6XAFUdckYCZnTPvzuQbzwi7H46y1j4Q8CvxZYY5ZMyUFtuwu3ThzOkieZv//unQNYN2801oWNgXAGsUGl4O39O1w+fH2qA9v21+OeqSN5sczmPXW4f9pIwdwh0/0fzX+s3eGFL0Bxuv3C83OVzQ72velxfctpXvTJ4f4M+KMlmlONapxscaDN6YVSRsLlCyLFqEamWYsNN40BTQF3vfk9y8bISQ7pkYxMMWDtR0c5g7PVGXJyfmpOCcvACHfnzU81orrNCY8/CIqS4bVfjkdNuwtqhQwv7jqBySOT4fFTcHsDgoPx2+oO/PXzk1h6VS627K3D3LIMnnN0JFt4ZIohJJCdoGUDdGYjl2ZSo9nmwaLybJAEMDxRh8x4SQJiIMMfpNnEMBD6zZ/6zzFMzkkSdXy704891a14+dZxaHN4kaBX4d3vajEkTlyFuylaW63I9qmobbkij9erFIIVVLHJZZcvwBPhX1ye0+fKnQQJEvoHHj/Naq8yge/zn1Xi6Tmxc8qOVkxussVGA9HlCwpuPjfOF2Pj2f9od/oEr6dgiDEm13O+upb6Y6wyYytcMiE3WQeVXIbVMwqhVsjQ4fRCJSeRGc83Q/b4Q2Yr63dUsYnfTpcXHU4fRiTr8diMIvzq9T08cgETF3r8FJZtOYCHrs1jO3CSDCqYtUqO+ZzHT7GatFXNji7WTSV+c0U2K0uxZEq2YFxd2+ZCXacLDq8f++useGbeaPwhzOxu3dwSJBlUaHEIxwNNNi+n0y+aER5FQ0osRoFepRSMlf6x4BLOvqrD5YNGIQNJEjjV6mJZxcMTtVDLZajrdKGiOB2v7Q6xy56aUyL4W5RlxUFGyvD1qTbBv3e6/HhgWh6SjSqs3naE93fJuPriRU27U3DM1LY7B0VyONq+qClGhrF9xdnuq2KN/pQgHYhIMwl3sqV1dbIxMUVdhxefHG4Mreu+ADRKOf666wQeuDaPF68988lx/OmmUngDFPJTjYjXKfFtdTsIAiwBkSQAtZxEXacHmfFaPDWnBPWdLtg9QWiUMvzmH99heUU+rO4A9tS0R038PvD2fiycbGETqdHki+o6XMhJNqC+gz8fmLVKGDUKPLujkpWxiDy+qtmBp+aU/H/27jxOjrLOH/inzr67Z6bnTCaTZMhMjpkchAjIAmoCGDUHl0FFWa9l3Z+YLFmVVSEhAd1F2CB4LooKHisoCkkWEUxEZAExIAmZAEnIRZK5rz6r6/z90VOVPqpneo5MT89836/XvJKuruOpqqefq556HhzqCFtvRZk9iN9o7cd/XL0QR7ui1pCWZW4RP3guOV5zW3/ctvHYmePtf/NN/MdeOZk15Nv65cnrd1dGW839uw/h7msX456n30RCPXMfh/vm8pRvHB5tgT/1NYNKnxPf+di5uCllFsbvfOxcHGgN466n3sh6wr5t3RLUlbpwuDOKz15Sj+fe6sCHFk3LmrUwdUxfswAbS9jPzvu9689FmUfE9549jOuW1eErv0sf982AAafAwj0wkLVdZJQUHdueOYhvf/RcyClP302Scqa38PrlDbjn6Tdx3bI6HOmM4L8/fh7aQxI8Dh4OgcUPnj2MC+orwLHAsplluKg+OCmesk1myYcL2ff8WHcUDVW+IbfXoePcuvK0J8SbVzXBQH5jV1aPsjd/uc++5255nq8jd+WoTHblOeajwLNpr1oaRvJVy+GMOUwIGTshWbHt4RbO822AsyHX8DuVBZqgJdfcBZJcmDGHJ1p4gPF5a2ks4mpqR4XWfgm/ffUkblo+B7f89vW0PPk/n3oDqxdPt42H5riAZsPvjZfWo8zrQCShDVouNJW6RXAcm/YGzoYVDXj4xeNpEx6XugSsXzEHpS4BNy2fAyfPpk3U+Oie7B7PyR7tIl490Yev/u7MOd22agHCkpIsx6o6PvHjl/HZS+ptzy8qZ3eQGKxMTA2L2RK5fqMp41R2hCUILIsXj3QjPtAxxuxVbDcONgCrfpG675lBFzojCo539+XsSTUt4MSCGi8EjrM6qqR+Xyzjy5Kx5xHt67xusTiaQSZaeWG4ekY5F02hjdecA4ViDo2Q+TD+igXVAM6UKRqqvPjesxGs/5+/W9s6BRaRHB0OQ5KKe//4Fq5bVpc2dNX65Q147JWTAJJzVaW+IbZ+eQN27jsFjgVk1UC134WtO1+18vJcDb+6kWxI/crKeQh6HVi/Yo61rLVfwsygCy6Rxz/+xL5c8OFltdZ8BeZ5Zf7eEqqObzz5RlbP5WSYW7Fq8bS0c/niFXOt7R968bhtI+/3/3Q4q0PZxssboemGNT+D+SZUXZkLJ3ri+NlLx/HR8+tsr8OhjjA+/74GTAuIaJ62BFt3HkBtqRtLZ+YfH9ihV5n8zAL/hfXlqK/wDqth+KmWNnzw/r/goz/8Kz707b9AVg08teES/OrGC/Dk+kswO+jFxkdfw6pF07OedGx89DU8/UY7/vWR1/CjvxzBF5Y3ZL3elzmLrznmW1c0AaeQPUthmUfE5u0t1vEyZ0D0OXh89QPzEJXkgR4kZ2Z0XL+8Ab999aR1bEnR8U5PzPY486t9+Oa1i3FOpQe3fnABHtlzAl0RGaVuAV6ngH/79V7c9ngLLppTgfk1PqxdPB0XzykHz1OUm+jMp1jpy1g4hfyGhXDyfNZsplt2tsDB51cIU3UdGy9vTIubyYQyv0YBJ598zSV1+82rm+DMM+6Zw0Kk7VNgUerOr3G5xu/CZ/5htjXBCs8Cn/mH2agJFMfYYIRMNh7BvteKWyjcUC8RWcHNl6Wnczdf1pg2scd4CnpypHuewlyjaQGXbXiqS4qjMjxSYxFXzTfizOuXWemRFB0/eO4w/u2KefA6ONy2akHOsqC5vm4Atz6+H7puIOCynyW7sSo52dxNy+fghnfPzDrmr/52Al/74HzctHwONqyYg7uuWYgSj4AHnjuCW377On70lyOoDjizOj48/OJxbPvwYnz7o+fiMxfX4+EXj+Od3rjVMGzu/46dBzC9xI0ZpW7rO3NynNTz27ZuCWaWedLOwRx2w+46UMOiPVFgbeOByLNWver8WUGc7IvjO386jLueehNeB4v/+vBirF8xBzNKXNiwYo7VO83c/p2eWNY9+/pVC3G8O4rpARf8Di4r7bzzyoVoqPagoSqAurL0+D+aN0LJ5FDld9jWK0Y7zOF40Q3DNvy6YQyx5cRQlqN8UZZnvarQzMbRVJMpX+gI2zd+d0aSD3LNMgXHMFn55IYVDSjJUW8+0hWxbf8y27bsyib37z6Ezaua8OybHbh6aa319o+Zl5vtYJnHMpvuFN3AF3+zF7/ecxIsA2y8vBH/vnIublu1AF9LKRdklntmlLqtcNiVGzatWgCvg8M/XjQT9eXJ6/Htj56LDSuSnTgvaay0htEyz+Wep9/C9RfUAUj2Eu6NJnDT++bgm9csxPeuXwq3yKIzIuORPSdwz7WLcdfVC/HFKxpR4XXgvl2H8J3dh/GjvxyBzyngweeP4J3eOB58/ggAoKHSa3sdNB3Y9MR+OAUeW3ceQG9MHnY6VxyPzCao1HHdzHFa3moLYUGNDxfWlwMAXny7y+pRketJh/n/npj9k7WZZS7ctHwOduw9hTK3iJsva8QvXz6eNT7Lxssb0RtVrOPZjcvy9auaoevAbU/sR6lbTA4HUeZGwCng27sPpfXo8Dl5PPTi8awnGretWoA7/zc56+T3PrYUW3a24CPvqkNDlRfN00vQPB00YVwRK/cKWbONb1nThHJvfpXTzhyz6nbmOaxDVFbh4FjrFRGWARwcm3ejSV9cBgcjObGSrMIj8oglFPTF8+t55RE52zGVPGJ+jeMzSt1wO3g8MDCTerLi0owZRTLxBSGTTa63AbqjhXsl08lzcAnp6ZxroGGlEBRVs033VL0wYwLOr/bjG1ctTOsZ+o2rFmJBdaAg4RkvYxFXzTfipt94IXa92YF5Vb60fdYEnLhuWZ3Vq3dm0IVt65ZA03WUeUR89Xevpw3/kNqDVlI0vNMTzerNu3VNc9os3Hddvcj2mKkTxGxe3YQf/PlwWmXK7JCQuq356uXPXjyGPx3sApB7GIi32sNgU8rbqUNrLJruR0OVz2ok3LZuCe566g2sWjQdHAucO6MEO266GG+1h3GwPWxNokMNi/ZCcQVfWTkP3TE57TXaUOJMWetYdxS3PLYPkqIPTGDIIq5oWWOJm0NKrF+e/D8Aayb5c+sCWeOPf/UD83DT++ZA1nScW1eKc+v8KHElG2po4mqSqbbEbY19bea3NQEnakuKo1w+2npRoUVkxXa4vahSuLe3hmO85hywk+9EeKOZMG+o+bfMNHXXm+34/eut1rAS5iRoC6f7s67PHWubse2Zg7jmvFrbvJpjkdYgm/rdgdYQ3juvEroBuAd6/Zt5+Q3vnonbVi2wGpXNjhU1JcmhMe55+i00Vnpx3fl1aetsXt2UNrRVudeB731sKfrjCoJeEUbKGynmsW68tB7TAy5U+B0QOQYHTivwOAX8a0YvaADwOXjbc6kOOK18bue+Vqxsrkmbk2nDigZ4RA4JTcO3diUbze95Or2RefP2/VZ5af3yBkiqhv986g188Yq5uOfpt9LCYo6BvPedfvTGZGxd04yF1cMbju2sNQ4zDPNjAKsAdBiG0TywrAzAIwBmATgGYJ1hGL0D330FwGcAaADWG4bxh4Hl5wH4KQAXgCcBbDCMifGorD0k2TbAzgx6rNmNU5825XplDUhmUjUB+x/n8Z7kk4LbVi3AIy+fQL+k4JvXLEZUVnDPtYtxpCuKhKrjJ/93DOuW1ab1Fsl8WnO8O2YVsMyhKJwDFdT3zqu0ZjncsKIBCTU5VphZsDZnoAzFFfTGZHzjqoVwCgy+ec1iVPkdaTM604RxxUtkOSQULa0QklA0iGx+jaPVfvuxi/Kf0E7Afzz196zfQb5jUzkFHpt2ZG//00+9K6/t+yUZARef1rjMskBIyu/1pxO99hNfLK0rpd8EIQVQkeOVzEJNtgYAPMviG79/MytMPyvQGHwcx+EHfz6cNhzOD/58GHdfU5hxmVmWgd/Fp+VDfhc/6Rt4xiqusiyDhdNL0BlJZL1SnTlm3/HuODY++hp++ql34Z4/vGk7rMXPXjpuvUG0c18rrllaiw0rGlDhdcApcFmzcB/pigx6TEnRsWVHizVOsenRPdnj692xthkvHG7Hpy6uxwcWTYNL4NAVkXKWqXWkl7db+yU8+PwRPJkxPuQV86ugaLrVePnAc0dw1zWL8IEF1VhQ48dF5wSpYXEQAZeAt7VoWqPtxssbEXCe6UiQ+jp2lV9EQjWyykepY5vf9sR+q/L+3T8lZ2r/27HerLlPvvH7N3HPtYtR6hHRNN1rNQybaOJqkupEbwxf+s2+rPSiaVqgKOLIaOtFheYTBdvh9u4p4LwPw1GoB075ToQ32gnz8mn8ZlkGcyq8+MDCmqzhoqaXuHFR0IO5X7gEJ3qicIs8BI5Jm4cqM+6eN7MUcVmz/S6u6Jhb5cXbnRG09sWsh9Gt/RLu23XIejgoqToMA/jly8fxrXVL4OQ5lLpFfO69c7LGiN6yowU3XlqPX+85iU9cOBMbfvX3tHP4/eutaWWP3pgMJ8/he38+jDvXLsRnH96Dz1xcj21/TJZjagJOXL20FpKq4bZV81Hiyp6QzimwmF7iwvevX4qv/m6/bTnovl2H8K11S1DqFfDhZbWYW+XDjz/5LnSFEyhxC/jJ80fxp4Nd8IjJh/CAAUnVcf+uw1A0HfdcuxgHbcZArvQ78aMbluG82hK4XMN7A/Bs9hz+KYDvAHg4Zdm/A9hlGMZ/Mgzz7wOfb2EYZgGAjwBoAjANwB8Zhmk0DEMD8H0ANwJ4CcnG4ZUAfj8WARzNUxYg+aTFrgH2q797HUtmlKC+wou6Uje+//Hz0HIqe8IM82l5TcCZbGDedRCbVzVZr+RnPgW4Y+cB3HhpPVwCh73v9CKU0PDYKydx/QV1qCt14asfnI9YQsbd1y7Cyd44ppW48NlL6q3xVoDBJ92oK3VZE8dV+R347u5D1pM+c/K5O69sRjiu4IFPLMNF9UEaJmISag1Jto0WP7phGc7JY8xhRU++Ppo6oc6v/nYC59aV5HX8XBPI5DvmbyiuoLHSi89eeg7iCRVuR/LJZijPnsNuUcB9fzyEGy6qB5CsaP70+SP4ygcW5LX9ZB+baiLRNA1HjhyxPtfX14Pj8nuIQaYOj8jZvg2R79sAZ0NIUmzTiZBUmJ40neHEwIRg6WOAdhWod/Wx7qg1f4PJKbBZDXyTzVjHVVk18INn38S2dUtwpDOCmUEPEqr9WLF7jvXiqqUzIHDA/dedi6ii4mhX1OpBu355w0BvlXn44XNv47OXnoMv/2YvPntJPWTVwOffN8fK8//0Zge2rmmyeshwrH3Zk8soQvbGZFQHHLh33RK80RaCpgNP7juNK5pqcOPAJHhOgcVd1yzEXVcvwi2/3ZdVXgaQ1UstOceHG0c6I1aZ3zBgNQyb4bnlsX0odYu4eE75pI5nY8EwkPUa7bZnDqY94DI7yDRWeuHgObww8DZlKknREYqr8Do5fOYfZlvlz2UzA7hwdhAdYfsyoWYYmF3OZzUME5LJ7MyV+UZjsZTLRzsXSqGFJAWfuHBWWi/HL14xF+FEcfQcBgrzwCnfifBGO2Fevo3fupF7bGKWZTC73AOGSf7eDAD3XbcEx7ujWT19N6xowH/94S1c0VSNO9Y242RvDI/uOWmVMx7ZcwLv/8i5WFQbwKGOCFgG+Na6JVANA14HD83Q8eCOA1Z72pY1TSj1iJA1Ax9eVos320K2v5fGSi/uumYhWvsl3H3tYvzwubex71QI9+06hHuuXYyakmRv4tdO9kHTkw8w/t975+C+Xcl4a44CYLXbpZQxvvuxc7POc/3yBkQSKkSeRW9MzjmKAMczSCgGvCKHvriCf/v1mcb3LWuaIPDAW+1RPPj863hy/SWIJFQ4BRZRWcPXbcZAvmNtM+55+k385JPnD7thGDiLjcOGYTzHMMysjMVrAbx34P8PAXgWwC0Dy39lGEYCwFGGYQ4DOJ9hmGMA/IZhvAgADMM8DOBKjEHj8GifsgDJJy2NlT7bG90RljAr6MHTb7RndbMPxRXImo7Z5R70xmR85uJ67H6zDV9Y0YhNT+zPGnTabNiVFB3TAy58a9chXHNeLbwODp/6h1lW4cx81YrjdOvHOzPowm2rFuBwRwSypiPosX+ywTLJrvt1pS6U+xz41jMHse9UCJ2RZPjmVXvRHpLw7d2H8F8fXoKldaXUk2KSyjWwfCSR3+tLsqrZ9jyS1fxeT072RBp5z6kqvxOfung2DneErVcdP3XxbFTl2XPZwbNYMb8668moQ8jvQchQr+eQsXPkyBH803efhCdYg2h3K374+Q+ioaGh0MEiE0xfTMGuN1rx3584D31RBSUeAb946ShqSws3DnggRy+DwAgKcmMhZ49VT2F6V0/Vh2xjGVePdUetyZBTy6H3DozHatdb5zs7D+DedUuw/pG/o9Qt4sPLavFvlzeiLSRZ5dFDHWGsbK7Bsa7k5LVeB2f7tlCF32H1/G6o9Nkec0ltibXcrAjd98eD+ORF9bh/V/JBxf0fPRf/9fSbaQ+ctz1zEN/56FI8uf4SHO+O4u/v9KWVlx/ZcwKP3Hgh4oqGSp8TdaXurPL4Pdcutm8kP96D2lLXpI5nY6EtZN9g1RY602Bl9kjTB8aBzDVB4BttYezcdwq3r2nGf314Mco8AjojMj790N9yblNX5kKZk+4RGVpNYHRvNBZarnpRRQHffhqOgEtA0CumvQkU9IrwOws370MxyLccNBblpXwav3ONTdwRljC73JPVrnb76ib84uUTkFUDN15aj5lBD2aUunCsK4IPLKxJH5pqbTO6Iwn86m8n8IXlDVhQEwDLMjjQGrbKMWa7QrJtqwl9A0NOVflF1Ja4EZdVnFPhxaGOiO3vxe3gcePPXrGOuXlVE/Dycew7FYIBYOOjexFwCvj8++ZA0Qy8d+5iKJqOC8+pwIXnVMDrSM7JlNkDuNQtoj2UwAPPvY3PXFwPjgXmVfvx4+ffRvP0RrAMgzuvbIKT520nyovEVXzhd39P65lsXtvN21vwk0++Cxsf3Wtd62V1Zbjzyma80xOzfcO/zCPglpXzRzzsyXiPOVxlGEYrABiG0cowTOXA8ulI9gw2nRxYpgz8P3O5LYZhbkSylzHq6uoGDchon7IAyR/S/Bq/bQR0CRz+dqwn6xi3PZGc9XletR+XzavCk+svwam+KGpLXHjleK/Vc+em5XPw4PNHsvZ7ojeO3pgMwwBUzcB3/nQo7WlomcdhjelmjvGW+kO9+9pF+NL75+LuP7yVlkFW+h1IaBr6YjIkRcO+UyEAZ17H++IVjbjzf98EAHRHEtQwPEpDxdXR9mofjVyz4uZbCHEKvO3g8/m+/iRyTFqPo+R4hk1wcPmdv6LpaOuXssa0m5Fn5TosqXj4xeNprz89/OJxLJlRktf2hRybaqwNJ00tFE+wBr6qGYUOBimwweKqrGtYMiOIf04pFK5f3gBFzW+Sy7OBYxnbMX65AuWtAstkjSO7YUUDhDzT3bE2mR+yjVdcbQ9JtpPBPPj821m9kzevasLTLa34zMX1CEmK9daZOfTYZy6ut15XnFPpw+GOMJbNLIVTYAfKouljB9+36xC+eEUjnDxnTY6cGb/uvLIZ33v2UFpe+71nD+PD580AxzLW/Td03faBc1dEwsLaaswKehBX9LRXWG9ZOR8Lp5dY5aYjnZGs8vihjrBtHNN0FOwhRCHLfnYGi6vTcgyFV+13YO87fZA1DUGPA1fMr8JTLW2QlDOTCmXey6f2t+K6ZXX4l5+/kpb+lLpF223uXNuMar8Ap5OmziFJg8VVTc/d47EYiBxj+0aJWKD8ebgMA/jKb1/PSiuKZViMsTScelW+5aDxKi+5M4aoMo/jFjnbdrXbU4aOMssS37t+KTrCclaZYdMT+3H3tYuxdsl0eB3JdP1ETxRvtoXw/94zB6f749bE8Nctq8NNv3zV+i18/aqFiMmdOHA6DAbAjr2nsvKMr1+10Cpvm8fcsrMF37x2Mb78m70AkkNs1QQM9MdkCAKHv5/oS+uAefvqJmxdvQAn+9Mbya9eWoutAz2GzbfvnAKL73xsKVpOh/Crv53A59/XkDbngtlD+o61C623onL1LO4IJ6zyV4XXCZ5nsWbhNBxo60dtqRu3PbHfesN/69pmnFPhTRvqdbgmSq5qF3pjkOW2DMN4AMADALBs2bJBxyUeq14ps8vPNASZvSzOqfDi1RO98DkF22MsnB7A+xorwfMs6iu86I4ksGXnq2lPx3MVoHa/2YZ71y3BoY4IKryOrDGP16+YYx3TbmyTL/1mHzasaMBN75uDKr8TQY8IRTfgEVl8648Hcf0FsyDwbFpPjpsva8SDzx8DMFDwCxR/5azQBourY9GrfTRYhsF/XL0QR7uiVs/bWeUe8Hkeu2MMJqTzZ4z5y3NAJM+JF2KyZlsINMe0G0qV34nemJz2erVTYPPueTyZJkMZTpo61nINGZG6/NixY9a47Yau49ixY1nrk6lhsLjq5Pm08e6AZM/C/7x60biH0xSWVNsxfu9Y21yQ8LSGJLx8pDutx+pPnz+KmUE3zi1AeOpK3bjzymZrfFKzMbGugBN7jlXD3XjF1Uqvw3Y4hwvqK/C9ZzPi3nOHccvK+WnlDnOYhtZ+CczADOGbVzVZE8/NDLrwresWQ+Q4fPaS5DBMZm8YSdHhcwjo1WXcfe1iHO+O4vzZpXjwH5ehKyyj0u9ASFKw53g/9hzvTwtfdcCJY91Ra/y/Eo+IW1IaFswHzj//zAXWMBFzq3x4asMlaAvZ57l2Zf5H95zEnVcuxK2Pv55VYbtmac5+KGdNoct+dgaLq3yOB0qaYeC6B160ruUtK+ejOpDsdJA6QeDMMheOD7whmWssRrNhwdxmXrUP5V4RJS7geE8CNSVDD3VGpobB4upgPR7PqZz4vc9DCQ2/3nPCmgjMJfJ4+IUj2HDZ3EIHLS+5hobJt144mQynXpVvZ6Px6pQka5pt25RuGHi7M2J7jxkm/bOiGtb/M9d9qz2M7+xONnL+5JPvQmtGRy/zWJl5xdd+9zruuXYx7tuVfBB90/I5Wb14Wcaw5kVIPWZCSZ7Tqb6Y1SvY7RDwTm8sqy3h9h0t+N7HlmL2QDuh2QM4V6NuXE52Nrt6aS02PbHftgyjaHpWY3vm5xK3YOWv5lBcum7AMIDaUid+eMMyxBIqKnwONNcEII5yyLzxbhxuZximZqDXcA2AjoHlJwGkdv2qBXB6YHmtzfJRG6unLGZD0IINl+DVE31pM2vfe539q3uvn+qHohlWgc9MNFMbhFv7JTyy5wS+87GlONIZQXXAhb5YAh+7YCbeaAtBNwCPk7fGPDYb4xak9GTOGVkVzRqQO3XSj69ftRC/+OsxXL20Fvdddy6O90Qxp9KLLTtarCcWd17ZjKaayT1beKGNRa/20UhoGjrDiaxJRqaV5PfbmJbj9a2aPB8qCByHH/3lYHLMXyP5NOhHfzmCL6+cn9f2kmI/nmLmslzGolGCJkMZvVxDRqQu7zy8D74ZjQCAWG87Nv3uBMpqehHpPIVbVzdj1qxZ1v6osXjqklUNn75oNrpjsvXA69MXzc57qJuzIa5otmP85ptOjbUZpS5c0VyT1mN18+qmvN+4GGsnemP49u70XqXf3n2oYBN7jlfD3VjG1biq2b7dxrGwjXup4/SZlZfPXFyPB58/gnlVPnzz2sVWwzAA1Ac9CMVVbNqe3hvGHKP4VH/c6i30zWsWYd/JEO566s20MufMoCutwmZ2QPivpw/iX95bj3vXLUFPRLbN09tDEj7+4F8HvR9mgz7LMFnXoTcm47y6EjzwiWXYc7zHGmNwNK9jjkahy37D9U5v3PYtq2klrrT4c9dTb+ArK+enTSr04PNHcO91S/Dg8y2D1lfMhgVzm4c/fT4qvBw+cP+LeHL9JQU4a1KMBuvxWAwkWRt4kPb3rOXFIOgVba9/0CsWMFQTX76djcarU1LQ48iaWHD3m22oCjhxojtqe4+NlOZvp8CipbUfi1OGk0r9bm6VDzctn4PHXjmJ7ohstakByaEbJFXD/Go/7r52MY52RSFruvVAOjowJGZrv4RHXk7m428OzFtw11Nv4M61C22POa3EhUf+dhyn+hLYsKIBcUVDNKGizC3a5kk9MRn/L6XX8vrlDeBZ+0ZdbiADm1ftw2cvqYfXwUHVkhPKAYABA5W+M+2Rdh1Dt65pQnsojs9cXI+HXzyOc+tKUO114uk323GqL571Nta8Si9EFFfj8HYA/wjgPwf+fSJl+S8ZhtmG5IR0DQBeNgxDYxgmzDDMhQD+CuAGAN8ei4CM1VMWs+DZGU6kRWJJ0fGfv38Dm1YtsLqaZxac537hEjAMUOl3WGOQsCxw0/vmQNZ0XFgfxA///DbWvasOb7SFML/Gj87QmacoM4Mu3HzZ3LTew7e8f65VAAPsI+u8ar/tRHpf+93r+MzF9di68w3cc+1i1Ja6cXF9Oe7/yLlo65dQHXCiqSZAk9CdZWPRq300PZwU1bCdZORHNyzLa3sD9q9v/eKzF+S1fVxWcc15dWlj/m5e3YR4nj2Hyzz2hZAyd35jW020RompJLNXsLssOWREaq/g1OXR7ta07d1l1dbyTb/7O8pqegGAxiOe4vxOAaphpD3w+tL75xZ0vLtcMxsHXIV5oSuu6Nmv3O1oKdhrn+0hybYBs1Cv+49Xw91YxVVdN9AbU3C6N46vX7UQX0vpuDC/2n44NDFjdjhJSU4Yt2VNE3QYONwRsRpyawJO/NN7zsGnf/q3rAZlc+Lkh188bi0/3Bmxzslc9rXfvY571y3BzSnl8A0rGuAYmLxlZtCDf/7ZKznHnH2rPZx1P+Z+4RKrJ2Bqg77dsBbb1i3BzKAHM4Me1Ja60B6ScMWCSsiajmPd0XF/46fYxtmu9Dts37Kq8CWHIJMUHXVlLnzxinn414F78JmL6+HgWTRUeuHgGauOZG6beY/Ny5+sJDejpoTD5dteLNqhukhh5OrxqGiFG1pqOEpzzBdUkme9ptBK3LztMFolBSrvFJN8OxuNR6ekWUFP1htG//3x8/DPP38FpW4x6ze2eXUTfvDnM8Ms3LZqAcKSgu8/e8h6Myh1XV3XMa/ahzuvako2og7Ed3MCuEf2nIBzGZf1O35kzwl4nGceAO07FcIdOw/gw8tqUVfqwqpF0/Gzl45g69pmqwev+SbUvc+8iQ0r5qI3JqPK74BmAD3RM0NUZf7mTvTEsso8P/7HZVnlrM2rm/DrPe/gExfOxJd+sxelbhE3vHumNZyGU0jmgzFZTXtw+sieE/j+x8+DJKvwOHj85Pmj+NPBLuv4lT4nXm/tty1T3fr4ftSVuXH+7OCo7vNZ+1UyDPM/SE4+V84wzEkAm5FsFH6UYZjPADgB4MMAYBhGC8MwjwI4AEAF8HnDMMzHYf8C4KcAXEhORDfqyeiAsXnKklrw/Owl9VmFuuPdcficPO5dtwQtrSEYBtImzDjQ2o97nn4Ln3/vnKzxUWeXenCyJ4rz64NZBedSt4jW/mTFqa0/ntbQ6xZ5PPCXZMOW18HZzpz4g2cP4/oLZuZ8Si8pOjwODu9prATLMlg8oxSLaUjPcTPaXu2j7eEUk+173sbzfELd2m9fwTHj/VBcIo8tO14dcSNFd1TBzZc14t4/nhkn6ObLGtETz29W3PaQBFk986iTYZIzvk/UCtpkkk+v4NTlgzEbigmJK5o1zj6QTFPu/sNb+PE/5vfA62xgWSZr/P8vvX9uwV4fb88xuVR7qDCvfU60MYfHq+FuLOJqZhngqx+YazXKzSr3gIFhO3t45vCVToHFu+uD+I8n30C/pODOtc1wCqzVIeGdlEqSSVJ0zKv2446dB9LyfN2w7xl6qCOS1fN0VtCNDSsasPedfqs3TWZ4b1u1AN/Znd3r/kRP1GocTm3Qb+2X8PCLx3HjpfU4d0YJZgY9aWX+WUEP3mwL41MDjd2FGNJhosX5oaiahs2rmrBlZ/rY1ce7IgDMinTcGtqktV/Cb19NvrVo1mtmBl144BPnQdb0rMaCmy9rhG4Y+PZHz0Wlz4GZZQKO9ch4cv0lRTtUFykMux6Pj+w5gZXNxTHmcE+Oek1vnvWaQptT7seJHiltuEBRYDGnwl/ooJFhEnkmbWLBkHSmx27qxGhLZ5TgW388iH9fOR/RhIoTvTF8Z/dh9MZkrF/egLii4r8/cR5iCRUMw+A/fv8GjnfHrfLIjDK39WaROezQZy6ut53T6HvXL0VfLJH2ALg3JsMlcPjWrkPojcn4+lULYeh62tAsP3rubew7FcLf3+nD9549jLuvXYxTfTEEPSKq/M6sDp65yh3t4QSqfEJy2KyIjKBHxOm+GBbOKLHCe/XS2qyOc7c8tg83XlqPX+85mTah3OygG3VlyQn+Xjzag5qAEx9eVovGSh8MIzkZbK4y1ViU2c9a47BhGB/N8dWKHOt/HcDXbZbvATAmg/DZ9aYc6VMWXTfw+qm+tJ4kdoW6Qx0RNFT68KO/nGndN29yTNbwxSvm4UsDPSSBM70sf/LJdyGSULFp+4Gs78wxuADgoReP498/MM9ax+3g057k1wScAxPg+fBmW9hqnL60L56z+79TYDGTCl4FM9pe7aPt4RTM1fPWk9/rP+W5Xh/Kc/vOUY5NVeoW8I2X0191/OXLx3H3NYvz2r7YZzUuNrl6Cw/WK5iQ4QgPvG6WSlJ0RKTCvZLZG1Xwo78cTUunfvSXo9i6pqkg4any209EWuUvzGzoE21iz/FquBuLuJpZBggltLQJjs3XNjMbZf/tikbrHM18T9V1a4LiN1pDuG3VArSHJNy/+xDuvnZxzt5s5uRwJo6xLyOrup7V89TnFPDwi8dxzXm1cArJcWrDkmJVSA0DCEtK1jGSr4mfqdZkNui39ku4f9dh/OrGC7LKQhNhSIeJFueHwrIc/vRWK/77E+ehN6qg1CPgFy8dRUNVSVovseklyUr+qkXTMa/al1bnOd4dRyiu4mBHGE3TAmn3+KcvHENvTMZDnzofc2s8KHE5UV1S2HMmxcmux+NE/m1l8jl5/NKmXlPIeROGg+dZLG+sREtrP72JXMSOdUdx0y//npavblgxx8rbW/sla2K0b167GPtOhaDqBm5NGW8XAO7ffQj3XLsYLx/txfxqH774m/S8975dyTeQbl/TjH/5+StWx8Vcww8dOB1CQ5UPHlHDDz+xDDFFhVvg0RlJ4Gsfmg+fk0dEUvFGWzStPQ5IlhsSqj7QCU5FTNbw0AuHsOlDc1Hhc+DedUvwxsDwFNEc5Y6jXVFU+4OIyRpueWyf1Uu4odJnHStX2HUD1nUzXXROELPKvTmHrX340+fjcI4JdceizD5l+vOP5Xhxum5g91vtkGTdmoTjubc6bF9Z+dlLx3H9BXXWGKZmhDEbnlInkDNJio4Xj3Sjrsyds3evqTeWnNjDjCCn+mK2T07a+yU4ec6K1Dv2nsqa+fTmyxrxy5ePF1WGORmNtlf7aHs4abphG5e11IGDBiFwjO3rQyKfX/hzjU2Vb+O0qmn43KVzsnqzqHp+letin9W42OTqLUzIWHEJnG2a4hQLVzHxOTnbV7I9jsKMgcgyuu1s6CxTmNduJ9rEnuPVcDcWcTWzDJA5jh3HwDbu1QSc2LCiAVFZA8sAHpHD4fYzvUBnlHkQjstWheeHz72d1XN065omdEfi+MZVC9MqMw1VPmy8vDFt5u/kXAautAbpO9Y245tPvYnWfikt3A+9cDyt7Dwz6MoqZ2xY0ZBWMRpOg/5EGNJhosX5odQEHHjfvPRxyresaUJNwIGmaUtw11PJnmDLZgbw/947B5u3t2S9ZVkTcELVDegG8MPnDuOapXXp8WltM8o8HEpc9HCejFyx/bYyuQUWn3vPnKx6lVsonsZVnmfpTeQil2tiV7shIn703NuoCTiRUO3fRpY1Hb999ST+dUVDzkbTcDz5ULih0gfnQFy3HY7NKSChqIgkNNz6xOu4blldWhvGxssbMafSgx17T2W1b5i9gc12huqAEwGnAJ7jISkKaks8cIml6AhJUPXsN1zMtr751T4smOa3yj53PfVWWsN5rrBnJkGpZRSWZaAbyBq29jd7juPihqqsobLuvLIZzdWjn6R1yjQOj2WvgBM9URxqj6TdkPXLG/DU/lbceGk9pgdcONEbt8YWvqShHE01ASytK0VnOIF//MnLVjh0wz6yaDrwTk/MetpuNgjv2HsqbQyub1y1EL975YRVqXvoheP4l/fUp3X5rytz45t/eBOyaqR1W59X5cMDnzgPkqKj3CtCMwxcvqCqqDLMyWo0YweNtocTxzK2r1+dP7ssv+0ZBgEXn/b6EMvCGph9KF6Rx39cvRBHu6LWhDyzyj3wOvJLrlwij8dezZ7V96sfXJDX9rlmNe6MFMesxsUg397ChIyFgEuwTVMCrsKN1+d28LaNZZ4807mxllCAXW8kewH2xRSUuJO9AKeX1BckPMDEmthzvBoXxiKuZpYBzHHsHvjEMuw72Yd5NdkNtTdf1ohTvTHElTMPUX0uAd986i04heTkcZ1hCd//8xF89YPz4RTYZI/il4/jm9cuhiSrqC1z46f/9zY+tKgW00tE3HPtYhzpiiKh6mjvl/CT/zuWVq74yf8dw7euW4yHP30+2kMJVPkdqPCKuO2JiBXun710ZiiI2eUeXLGgGp0RCRVeJ072RdPKug1VXtSVnWmsH06D/kQZ0mEixfmhqBqyxinfvL0FP//MBbjxZ3+1ll9QX2E9dALO1HkWTffjc++dA0034BU5rF1Sa5XdJFnFtFIXeMbAjMDEvxZk4ium31YmlmVQ5RfxwCfOQ09UQZlHgKrrYPKsVxEyFuzyyd6YjLisWun2jKAbsqqhX1Ks4afs8tbTfXG09kvoiiZyNpoe7ozg/l2HURNwWmMLZw6vsmFFA0o8AqaXuvDlx163HXpi2zMH8eX3z8V1y+qs9g2OBeZX+/H9Z5NDXXzjqoWYVuJEZySBu59+C6VuER9eVguG4dBU40epS8DbXRHUlbqxZU0T3CKPk70xPPxisq2vwufEzKAXM0o9WDKjJFlO9Dowo8yNWx/fj8deOZnVmPuNqxbC7zozVrJdGcW2Qf6VVnzyH+oxo9SFpk+ch5isocLrwPwqL9yu0U/yOGUah8eyV0B7KJHVs9CchKOuzI1v7z5kjZuybd0SLJxeYmVKQ/XoSH0KUeEVraftqU9jFFXD+hVzcG5dCXRNw8rm6diys8UqdEdlDS6BQ22pGwaASr+A9Ssa8bXfvW5199+ypgmiwODi2gpqCJ5kRtvDqV+Ss566rV/egLAkD70xkmMWb3x0b1ZCn++YiSFJhqLqaeNwb13TlPfxDRj4yPkz0ya0u/PKZhjIr+fzRKkkTmbUW5iMp4SqoTOcSEtTNl7eiOklhftN90ZleB1cWuOW18FlvbI2Xlwii3Prgmm9ADesaCiqnkln23g0LoxFXLUrA6xf0YjbnngdqxZNx02//Hva5GBLZgRwoDWE7qgCkWMhqTo0PTlp4tY1TTjcGUFnWMK3/ngoq8fwvlMhfPk3e/H1qxZC4Bj8+weaMCvowV+PduOm//m7Faabls/JMXmZM+166rqRFvbemIx51X5rDgwA1kPa2eUezCj15GysH06DfrEN6TAR5HqQ3hVJHxos9XVas87zyJ4TuO78urTrvfHyRnxo4TRIsopKvxNOnkVjlQdO55SpqhJiSzcM9EQV3Pr4/rR6Tb7D9REyFuzyyQ0rGvD9Px+x5hhwCiye2nAJ7r5mMW74ycu2E9VtWNFgTVj785dOZM2/sWFFA2pL3fjGk28AOPOg+KsfnA+RZ9OGHzIbZ3/4iWWDDj1R6Xfi7j+8iVWLpoNjgWUzSxFwCfjKB+dbQ82yLANdN/CkTZkhHlfwVnsEH//xy2ltIyLPYOuaZjRVJXvsZpYTa0vcmFnmxtGuKAJuEV+8ohF9cRUsAyytK0Fdmcf2eKZcbRJOgceCaWenLDplctyxbPCJyvZjwi2cHsD7GiuxtK4075t8pkfHedhzvBeafmbSug8vq0172i4pyYm5HvjEeTin0ouuSAIbfrUXt31ovu2s3jctn4Mf/eUIvnhFIxqrvHhgYFwwkWfhdrCYWxWghuFJaLQ9nIIeJx7ZcyCr5/D9Hzk3r+374/a/j5Ck5rU9w7DYlBHvN21vwU8++a68ti91OaDrkbSeyzFZQZk7v3F4qJI4PjxB6i1MxkdCNaxeksCZngQ/uqFwE9JxDIv/fu6I9WaQpgP//dwR3HnlwoKEp9TtQImLT2usLnHxKPUUZszhqWos4mpmGaDC68TbnREc745bFafUMe7MsmJm+fh9cy+Aoum466m3rJ479+8+hH2nQhBfPYGffPJd6I8rqLEZPzKzrGvXa8YuXx1O+SWfxvrhzPRezK+dF0KuelVNwH65Ge9+9tJxfO2D8/HFjPlWtj1zEN/72FI4BQ5eB4f6che8NJwEIQhJmtUwDCR/L7c+vh8/LGAZhkw9mfkkAwb/+shraZPPSoqOtpCE+MDk9pkT1V0wuwy9MdnqCNEbk1HmEfHtj5yLfilZnphe4oJhIK2zRGu/hMMdYRgA7t91ODNo6InJgw49Mb/aj5988vwRlyv2t4WwaXv6b/D+3Yfw00+dj3v+8AbmVnuxeEZp1v5EkcN5M8vQGZGx4Vd/Tyv/1JV5hiyjFKJNYso0Do/lxZ1Z5rGNePXlXvA8m/Mm67oBlkHWWGw3XnoO7vnDW1jZXJP2ZGV2uce2kU3TDVw8pwL/d7gLToFFb1zJ2SX/rmsWYXqJE+VeBzQdEHkq9E4Fo+nh1FTjxxeWN2Q9oW6qCeS1fZlHsI2PJe78XouNSLkm5MmvcXlm0IO3uyLYd7LfauRYVBvAzDx/61RJJGRyieaY5CuayC9NORsEnsFH3lWXNfGlwBUmnTHTzdaUmY4r/M68000yNsYqrqaWAY50RtByuj9nxWnH3lO4bdUC3JEyK7f5ttDMoBdOgU2r4HEssGJepfVWnJ3MMndvTEZdmRuP3nghorKW1lNnsLCPp2J+7bwQctWrmmoCact37D2VNj50b0yGZhi28fy1k324YHYQjRU+6jFMyIB4jk5pcblwk+qSqSmzbGE3QVulz4mwpKY9FDTfXGcZ4IoFVXj40+ejrV/C4c4IvvnUW+iNydi2bgneXV9u9eDNzF/m1/ghcKxtG0NtiQvfuGoh7tt1MKun8rZ1SzC7/ExD7Ei0hRK2v8H2kIQ9x5MTLeYaT3s07QqFaJOYMjnvWF7c2eX2BaLZ5bkrUakT4pW6k2OxHewIQ9OTsy4f7IigM+XJCssAzhwTk5hPGt5dH8Rd1yzCtmfeyvohfOOqhVZ39dRzpDFTyVB4nsWVi6ejodI7olllnQJnO7GRi89voqWA275xOZBn4zLLMlg+twr15d4R/9apkkjI5BH0jG6Sy7OBYxl4xPRhJTwiB65AD6HGIt0ko3c24mp7SMKje868zp9ZXrzpfQ145G/Hbd8WSm0AbO2X8ODzR9KGS8uFHrJOfoPd48ye6+b40NNLXDjRE0d1ykTaJqfAYsmMEpw73U8Nw4SkKMuRL5TmWS8i5GwYrOPlKyd6bB86/+yl43h3fRC9MQX/9cxbWLVoOj68rBbLZpbhovqgVUawy1/qSt14+XgX7ryyOasD2+LaEpxbV4olM0rQE03gkRsvRGyIB9HDkSvPKhlos6gODP6Wy2jaFca7TWJK5r5GfkOP5jSSQm/qhHit/RK+/uQb1szLpW7Ret3OfLJyx9pmdIelrB/WXdcsshqheZ7F6kXTsHB64Kz8EEjx0nUDx7qjaA9JI4oPo5lV1i1mT0jHc4DLkd/xK30O24maKn35v95Mjbskl9TJ8ACgvr4eHJffgwtSnCr9jqwZhu9Y24xKf+GGTHCLXFYvYYFj4BYKFxcp3Sy8sxFXq/xO9MZk/Oyl47h6aS1YFrjn2sVgmOSkyHFZwTXn1Vk9O80J6GRNx7HuKK6YXzXomHi5UHya/HLd48zls8s9CHoc6InKONUXh6rrab2JzTg3p8I1JhPqEJJptPWiQnKLHLaubcKmJ878XraubYLbQWVXUjiDtYcFPQ5Epd608YF/9lJyfGC3yOFTP/0bJEW3hrdyCiyeXH9JWl5il79cOLsC7/RG8fCnzkdXNIHpAReapp3pwFZf4cWsoAfHuqOIjWHP+oU1AWxd02wNLWF2fPvFS0eH9XZ1MZgyjcOpPXdTn26sbKoeUeaQq0CUK/PJnIiutV/Cwy8ex0OfOh8GDFT5nPiHc4JoDyXgcfA40hkGw7J44Lm3rdf4Mp+qDBYOMnXpuoHdb7VbwypwDLCwNoDlc6vGpSDUF9eg6Tr8LhGaYcDv4hGWZITi+SXSdWUe1Fd40nrU1Vd40mYhJ2Q4DF3HsWPHAADHjh3DnTsPwFteg2h3K374+Q+ioaGhsAEkZ9WMUg9O9cWS4+7HFJS6BfBccnmhyKqOgFuEzykimlDhcfJgGUDR9KE3JpPW2Yirqb17zA4IX1k5D+GECklNxreWk314+FPnoy+enJdi8/b9aRMrr2yqpnImGZbU+lClz4nj3TH826/PTBR877rFuHfdEoQkBR6Rh8/JobbUV+hgk0lorNsAxltC1VHhE625g0o9AjRDh6JSeYEUVq52qFlBD+bW+BBL6HijLQQdgMgz2LZuCWRNtx2ioSMs5TU/wMygFzOD9uudrd+608ljzcIazC53oz2UQKXfAQM6Pv++xmG9XV0MpkzjcGrPXSAZCTc++hrmZTylGI3BIqTdxA29MRkVPodtA3N1wImeaAL3f+Rc6g1MhuVETxSH2iNps51vWNGAORVezCo/+5W7oMeBL/56rzXRkmEAO/edwk8+eX5e29PrzWSsxXrbsel3J1BW04vOw/vgm9EIX9UIusWTosSyDC6cXYFj3dEJM+6+wLE43h3LGnO4rsxdsDCRwjsbcTWzd4/XweOFt7vxnT8dTot7lX4Hyn0OfPD+v5zVsjKZ/OzqQxtWNKDULaK1P9lZ5uZH9+KBT5wHp8BiZtBT8DSZTF7j0QZwNpW6Rbx6og93/+Et6/f0pffPxYp5Ez/sZOqKJvS0POCuaxbhivlVONEbsx2iodI3+glIz+Zv3enk8a7ZwVGHcaKbPM3cQ8jsuQuceUoxVnJFyGPdUavnRuqEILkmxDOfwiybFcTiGaV49znlqK/wUqGJ5KU9lLAaHIBkPLxv1yG0p0w0dDbNCnpwy8r5ePD5I/jO7sN48PkjuGXl/GFN/mj+Bi6sp7hPxoa7rBq+qhlwl1YUOiikACZamhJNaLbpdDRBE8xMdWcjrqbu0yXw1rBNwJm4p+njU1Ymk59dfei+XYdw9dJaax1J0RGSVLynsXJCpMlk8ir2dE3TYTUMA8mw3/2Ht0AvGpGJyi4PuOWxfTjRGxtWm9hwFftvfSKYMj2H7Xrumk8pxmocosEiZH2FlybnIHkbTZyM5pjVNiYPb7bzkaKJaEixSB1uAqDxhyeziTbeYKHTaTJxne242hG2L6t2RqRBy8qEZMp3KD0gGceYlGjsFFjMr/ZT2ZCcdcWerg2WZtNE82QiGu82MTMvYhmmqH/rE8GUaRzONaNiXal7zMYmGSrzofGBST5GO17OzDKPbTwczzF7Ka6TYpA63ASNPzx5TcTxBidCOk0mnvGIq4OVVQebfZyQVMMdSs8psDCjsLmuOcE2IWdTsadrlT7731OFlxq8yMQ0nm1iqXlRqVvEhhUNaUO2FdNvfSKYMsNKmL0Zn1x/CX514wV4cv0lWNlUjRO9sZxDQQzX2ewmT6aOwYYnycfscvt4SIVwQrKZw014gjWFDgo5S0abpp4NlE4TO+MRVwcrq+YqK1PvTpJpJEPpXX3udIpXZNwVe7rGscCGFQ1pv6cNKxrATZlWHFJsxrNNLDUvau2X8PCLx3HjpfX4ySeXFd1vfSKYMj2HAfunFEN1ex/u/ul1ejJao42TFA8JGR1N03DkyBHrMw03UdzGMp8fK5ROEzvjEVeHinv05g/Jx0hfGx6PiZEJyVTM6ZrZ4PWZi+utib4ffvE4zq0rod8TmZDGs4ybmRe19ku4f9dh/OrGC4ry915oU6px2M5Yj0NUzJkPmRjGIk5SPCRkeFLHHz527Bju3HkA3vIaGm5iEpio4w1SOk0yjVdcpbhHRouG0iNkfFT5neiNyfjunw5byyZCGYaQwYxXHjBRy/jFasq/kEBDQZCJhuIkmYw0TcOhQ4dw6NAhHDt2DIZR6BClS44//Hf866/+jq/9/M/gfaXwVc2Au7QKx44ds8KuaVqhg0qGidJUUiworpJiQXGVkPFBvzVCcqPfx9ia8j2H6dVOMtFQnCST0ZEjR/BP330SnmANOg/vg29GY6GDlMUcfzja3WotS520LtJ5CreubsasWbOsRmJzuAkaemLiojSVFAuKq6RYUFwlZHzQb42Q3Oj3MbamfOMwQK8+kYmH4iSZDFLH7j127BjcZTVZja/FILXReNPv/o6yml50Ht4HzuNHWc2stEZjgBqKJyJKU0mxoLhKigXFVULGB/3WCMmNfh9jhxqHCSGEnBXF0Ft4uFIbijlvaVajca6G4tSGcup1TAghhBBCCCFkoqDGYUIIIaN26NChrGXmBG+mWE8bwg4nYr2d4OTEuPwfwPgcz+MHAMT7u/GlB5+Cv2Ia4n2d+MYNKzBr1iwcO3YMX314F1wlFeg98RY4ly9rnamMJvwjhBBCCCGEkMJgjIk2K9AYYRimE8DxAgahHEBXAY8/GhT20ekyDGNlviuf5bha6OtBx5+4x59I8bRQCn1/zpbJdl5jGVcn4rWZaGGi8AxuvNLViXbeo0HnMvFQXE0q5rADxR3+fMNOcfUMCn9hDRX+vOPqBK1XFfv9yTTZzgcYm3PKGU8nbeNwoTEMs8cwjGWFDsdIUNgnj0JfDzr+1D7+RDdZr89kPa+xMBGvzUQLE4VncOMVnol23qNB5zK5FfM1KeawA8Ud/kKEvZivF0DhL7RiD/9QJtv5TbbzAc7+ObFna8eEEEIIIYQQQgghhBBCJi5qHCaEEEIIIYQQQgghhJApiBqHz54HCh2AUaCwTx6Fvh50/Kl9/Ilusl6fyXpeY2EiXpuJFiYKz+DGKzwT7bxHg85lcivma1LMYQeKO/yFCHsxXy+Awl9oxR7+oUy285ts5wOc5XOiMYcJIYQQQgghhBBCCCFkCqKew4QQQgghhBBCCCGEEDIFUeMwIYQQQgghhBBCCCGETEHUOEwIIYQQQgghhBBCCCFT0KRtHF65cqUBgP7orxB/w0Jxlf4K9DcsFE/pr4B/w0Jxlf4K+DcsFFfpr4B/w0Jxlf4K+DcsFFfpr4B/eaN4Sn8F/Mtp0jYOd3V1FToIhOSF4iopBhRPSbGguEqKBcVVUiworpJiQXGVFAOKp2QimrSNw4QQQgghhBBCCCGEEEJyo8ZhQgghhBBCCCGEEEIImYL4QgdgOBiG4QDsAXDKMIxVhQ7PRKbrBo51R9EeklDld2JW0AOWZcZkW103cLQriuM9UXhEHlV+B+rKBt//aMJDio+q6mhp7Udrv4SagAtNNX7wfP7PogodX0YbfjK0kdzjfNKm8Yo3FEcIIcReIfPwscwnCl0WGcxEDttI5XNOum7gnd4o2vsT6IokUBVwgmWAgEucFNeAEDuyrGHf6X60hSTU+J1YOC0AUeQKHay8UZl57EzGtL/QhlNucIs8ZE1D0OM469e+EPe6qBqHAWwA8AYAf6EDMpHpuoGnWtqw8dHXICk6nAKLbeuWYGVTdV6NL4Nta/f9hhUNaKjyYvncKtv9jyY8pPioqo7H957CrY/vt+73nVc248rF0/MqCBQ6vow2/GRoI7nHI0mbzla8oThCCCH2CpmHj2U+UeiyyGAmcthGKp9z0nUDfzncgdN9CWzZ0WKtt3l1Ex575QQ+ffE5RX0NCLEjyxoe33cam544U+bcurYZVy6aVhQNxFRmHjuTMe0vtJGUG9Yvb8Aje07glpXzz9q1L9S9LppfJMMwtQA+BOBHhQ7LRHesO2pFJACQFB0bH30Nx7qjo97W7vv7dh3CvpP9Ofc/mvCQ4tPS2m8VAIDk/b718f1oae3Pa/tCx5fRhp8MbST3eCRp09mKNxRHCCHEXiHz8LHMJwpdFhnMRA7bSOVzTse6owjHNath2Fxvy44W3HBRfdFfA0Ls7DvdbzUMA8k4v+mJ/dh3ujjKnFRmHjuTMe0vtJGUG+7ffQirFk0/q9e+UPe6aBqHAXwLwJcB6LlWYBjmRoZh9jAMs6ezs3PcAjbRtIckKyKZJEVHR1ga9ba5vtcN5Nz/aMIzWU3muNrab3+/2/rzu9+Fji+jDf9kcrbi6Uju8UjTprMRbyiOTDyTOU092z75zzfh8ms+bvv3yX++qdDBm3Qme1wtZB4+lvlEocsigxmvsI1nXM3nnNpDEqIJ1Xa9uKxOmPtDxt9kTlfbcvw22kPFEdepzHzGaOPpRM6XitVIyw0Mc3avfaHudVE0DjMMswpAh2EYrwy2nmEYDxiGscwwjGUVFRXjFLqJp8rvhFNIv7VOgUWlzznqbXN9zzLIuf/RhGeymsxxtSbgsr3f1YH87neh48towz+ZnK14OpJ7PNK06WzEG4ojE89kTlPPtlNdfQi+//O2f6e6+godvElnssfVQubhY5lPFLosMpjxCtt4xtV8zqnK74THyduu5xL5CXN/yPibzOlqTY7fRpW/OOI6lZnPGG08ncj5UrEaabnBMM7utS/UvS6KxmEA/wBgDcMwxwD8CsByhmF+XtggTVyzgh5sW7fEilDmGCWzgp5Rb2v3/YYVDVhUG8i5/9GEhxSfpho/7ryyOe1+33llM5pqAnltX+j4Mtrwk6GN5B6PJG06W/GG4gghhNgrZB4+lvlEocsig5nIYRupfM5pVtADn5PD5tVNaettXt2Eh184UvTXgBA7C6cFsHVteplz69pmLJpWHGVOKjOPncmY9hfaSMoN65c3YOe+U2f12hfqXjOGYZzVA4w1hmHeC+CLhmGsGmy9ZcuWGXv27BmXME1E5uyGHWEJlb7hzW441La6buBoVxQneqJwizyq/A7UlQ2+/9GEpwgN68QmY1w1Z6Vt65dQHXCiqSYwrEkHCh1fRhv+IlHQeDqSe5xP2jRe8WaKxJGJYsqnqWfT5dd8HMH3f972u+4/fBfPPEbP4oeB4ioKm4ePZT5R6LLIYMYgbBMuruZzTrpu4J3eKNr7E+iKJlDlc4JjAb9LnFD3h4ypCRdXx5ssa9h3uh/tIQlVficWTQsUxWR0pilUZs47ro40nk7kfKlY5VtuaA9JcIscFE1Hmcdx1q/9WbzXOXfCj8XeycTDsgzqK7yor/CO+bYsy+CcSi/Oqcx/36MJDyk+PM9i8YxSLJ4xsu0LHV9GG34ytJHc43zSpvGKNxRHCCHEXiHz8LHMJwpdFhnMRA7bSOVzTizLYGbQi5nByXPehAxFFDksm1VW6GCMGJWZx85kTPsLbSLVLwt93KJrHDYM41kAzxY4GIQQQgghhBBCCCGEEFLUJmV/fkIIIYQQQgghhBBCCCGDo8ZhQgghhBBCCCGEEEIImYKocZgQQgghhBBCCCGEEEKmIGocJoQQQgghhBBCCCGEkCmIGocJIYQQQgghhBBCCCFkCqLGYUIIIYQQQgghhBBCCJmCqHGYEEIIIYQQQgghhBBCpiBqHCaEEEIIIYQQQgghhJApiBqHCSGEEEIIIYQQQgghZAqixmFCCCGEEEIIIYQQQgiZgqhxmBBCCCGEEEIIIYQQQqYgahwmhBBCCCGEEEIIIYSQKYgahwkhhBBCCCGEEEIIIWQKosZhQgghhBBCCCGEEEIImYKocZgQQgghhBBCCCGEEEKmIGocJoQQQgghhBBCCCGEkCmIGocJIYQQQgghhBBCCCFkCqLGYUIIIYQQQgghhBBCCJmCqHGYEEIIIYQQQgghhBBCpiBqHCaEEEIIIYQQQgghhJApiBqHCSGEEEIIIYQQQgghZAqixmFCCCGEEEIIIYQQQgiZgqhxmBBCCCGEEEIIIYQQQqYgahwmhBBCCCGEEEIIIYSQKYgahwkhhBBCCCGEEEIIIWQKosZhQgghhBBCCCGEEEIImYKocZgQQgghhBBCCCGEEEKmIGocJoQQQgghhBBCCCGEkCmIL3QA8sEwjBPAcwAcSIb5N4ZhbC5sqMaWrhs41h1Fe0hCld+JulI3TvTGrM+zgh4AyLmOW+QhaxqCHgdmBT1gWSZrn6n76I/L0HSgK5JATcCFEjeP031n9nu0O4pTfTE4eA6RhIoqnxOKpiMkKfA7BfRJMhwcB7+Lh6IZ6AwnUOoWwLEMEqoGnuUQTiTX7QwnUOFzwC2yiCY0OAUWqgZEZBWSoqHELSDg4hGOa2gPJVDuE+F18OiJyojJGoIeEW6Rg27oiMkG+uIKSt0C+mIyStwiYrIKlmHgdfBgGCAUV+AWeXRGEij3OqBqGniOQ5XfAVUDemIJMGDQG5VR5hGhw0CF1wHDADrCCURlFTPLPJhdnryOJlXV0dLaj9Z+CTUBF5pq/OD5yfl8ZbTnahf3Uq/lUGJxGfvbwmgPJVDld6C52ge3S8x7e1nWsO90P9pCEmr8TiycFoAocnlv3xeXcLAtah2/sdqDEpdzymw/XvJJ91RVx+un+9EaklDhc8Dv4CCpOniWRUxW0RNTUOkToetAezhhpRdgDKiqga6oDI/Iwy1yCEkyfA4RoYQMJ88jLKko94qIyAoEloWD59DaLyHoFSGwDASegaoBkqrBMIBoQoNb5CBwDJwCh7CkIiypqPCJkFUNTpGDpgGdkYSVpjgELi1tBs6k4z4nD0nR0BtLppVVfgdqS7LT9XKPA2FJwekxSHvyuea58o/h/IYJIVNXavpR6XOCY4HW/txpia4beKc3ivb+BEIJBSUuEQx0sAyLcEJFXNHgc/Jw8CycPIeYokLTAUU1EFc01AQciMoaQpKKEpeAnoHynaKpYBkOYUlBmUeAbjBWmTShqvCIAnQDaA9JKPc5YBga3IIASdHRGUkg6E2WR2VVR1RW4XcISGg6WIZBl5nOw0BvTEHAJSCaUFGXUX7M51qY63RHExA5FjFZG3a6W2xptq4bONETRUc4gb6YApfAwilyqPBy6Agn6wNzKt0ISxo6wglU+hwIJxT4HAJUTQPDsIgkVJS5RSi6jr6YgqBHhKypEDke3QN5v9/FQ9MNnO6XEPSIcAksXCKLiJS8xx6Rh8gzAAMILIuQJMPrEFDpd0BRk3UGFgy6ozK8Tg41fhdm5Mg3BzvP9lAC0YSKcp8DCTW9vkbOvmKvw/XHJbyVUq6fW+1BYAKW63MplnpJLhMp/CNJ64faZrT5hyxrVl2t3Csi4OIRSYwunRvpbzbfcxmsnWyoOtJI9pW6rXluvbEEvKKArqiMgIuH3ykgrmiIycm/Cq8DkqpAYHn0xRWUuAUYhoGeqIIKnwiPyCGS0CCpKkpdyXJQRziBar8DFT4OLMOhttQ7rOtfFI3DABIAlhuGEWEYRgDwPMMwvzcM46VCB2ws6LqBp1rasPHR1yApOpwCizuvbMa3dx/C8e44nAKLbeuWQOQZ3PTLv0NSdMwMuvCF5Q249fH91jbrlzfgkT0ncMvK+bhifhWefqM9bZ/mPn7w7GFcs7QOW3a2WN9tXt2E//nrcfRLCr6wvAHf3n0I1y2rw/27D1nrbFjRgIdfPI7emIz1yxvw2jvduHzBNNz2xH6UukV86h9m4emWVlyztA4/eO5w1vZb1zSjyi+gLaTidJ+E+3alfteE7z572DrfLWua8L2Uz1+/aiF4Ftj2zMGs/Zrn/ZF31aGhyouusIzbd7x65txWNeGxV0/gmvPq8NgrJ7B8XnXa9jdf1ohSN4/uqJIWpm3rlmBlUzVYloGq6nh876m0633nlc24cvH0oipc5GO052oXn1Ov5VBicRk797dj0/b9aXFnVXNVXg3Esqzh8X2nsemJlO3XNuPKRdPyaiDui0t4en9n1vGvaK7IqyBQ7NuPl8x4Ypemffuj56IvpuC2lHt5++om1AQcaAslsHl7CxorvfjoBTOxZUd6elbm5vGN379ppSFf/cA8aAbw0xcOZKUhd6xtxiN/O44V86utNO721U2o8ot4pycOSdWx7ZmDaWlhdcCJb/3xoLX/rWub4OBZ3PLY61lp03XL6vDInhO4bdUCyKqBjY++hlK3iBvePTMtzdl4eSNqAk586Tf70tInl8DiG79/c9RpTz7XfNu6JTnzj3x/w4SQqcuuDJBafsxMS3TdwF8Od+B0XwI/+HOy7Lj7zTZcf+EstPWnlxW/9P65qPA5IKsaOsMy7tt1yMoDzG3NtH1m0IXPXToHW3a22Ka3m1c3gWMkbNp+wFr2resW41hMwu0Z+YnAAVFJw49fOJqVf3z1A/MQV3Tc+8eDWeklgCGvhZne3vXUG1n7zjfdHW25a7zpuoHdb7XjSGc0K2+dXuLEfz1zEOfNKEFcLsem7S1peeruN9uy6jDmNRV5ZuCev5r2nUfk8P0/H0FvTMZ/XL0Qmm6k5XvmOizLQNMM/PiFA/j8e+fg0T3ZdYavfmAe3A4+K9+0u9bmeR5qj6TFvZsva8QvXz6OW1bOn7D3aDIp9jpcf1zCH2zK9e9vriiKBuJiqZfkMpHCP5K0fqhtRpt/2NW7N69uAgcDX/zz3hGlcyP9zeZ7Lnbrfedj51p1tMHqSPnsK7PdLnVbXTfw+N5T+PbuQ/jY+TOtssPMoAsbL29MayObGXThX94zJ61dy8zvppc48JHzZ+JXLx/H594zBy19IWxOyS+3rmnGgmlu7DnehWUzy/O+/hM/RQRgJEUGPgoDf0YBgzSmjnVHrQgFAJKi49bH92PVounW542PvoZ9J/utdVYtmm5FVnOd+3cfwqpF07Hx0dfQ0tqftU9zHzdcVG8VqszvtuxowWcvPcfa76pF063CkLnOfbsO4eqltdaxrr9wttVoc/XSWmx75qC1b7vtN23fD6cg4O3OqBXpz3zXkna+mzM+f+13r+Ptzqjtfs3zvm/XIYgcaxXqrXPb2ZIM147kv5nb3/vHg3CLQlaYNj76Go51RwEALa39Wdf71sf3o6W1f4xjQ+GN9lzt4nPqtRzK/rawlQGb22/avh/728J5bb/vdL+VQVnbP7Ef+07nF/6DbVHb4x9syy/8xb79eMmMJ3Zp2uun+q00xlx2+44WiDxnZYCfvfQcq2HYXGfLjhYoGtLSkK6ojLueetM2Dbntif244aL6tDTu9h0t4FgWXVHZqrya69+36xCOdkXT9r/piRa83Rm1TZvMf/edPJMuX720NivN2fbMQRzqiGSlT11ReUzSnnyu+WD5R76/YULI1GVXBkhNWzPTkmPdUYTjGrbsOFN2vOGiehztyi4r3v2Ht3C4IwInz1vfmXlAZtq+atF0q6xrl95u2dECtyikLVM1ZJchd7TAyfPojsm2+UdXVLYqd+Yy8xzzuRZmemu373zT3dGWu8bbse4o9p3st81bDw+U9a99V53VMGx+b8aNzDqMeU1T73nqd11R2brmR7uiWfmeuU5HOGHd503b7esMXVHZNt+0u9bmeWbGvXv/eNCqr03UezSZFHsd7q0c5fq3Jli5PpdiqZfkMpHCP5K0fqhtRpt/2NW7t+xogdshjDidG+lvNt9zsVsvtY4G5K4j5bOvzHa71G3Nc1u1aHpa2WHVoulZbWSrFk3PKpOY+d0NF9Xj1seT9VeRZ616sbnepu37EUsAms4M6/oXReMwADAMwzEM8xqADgDPGIbxV5t1bmQYZg/DMHs6OzvHPYwj1R6SrJtpkhQdDJP+WU9pDmcY5NxGUnS09tvvUzeAeEK1/S4uq9b2g+3f/H9vVLHWMdc3951r+46wBN0YfN+Dnf9Q592TEqbMc0sNX+b30RzLO8ISAOS8nm39EkZiIsfV0Z5rrvhsXsuht0/Ybt8eSuS1fVuO47eHxuf4xb59qrMZTzPjid1vO1da0Rk5c445f9MD6VnmvnKlIWYakZbGxZScYTDTo8xlmeulpqmp+8oVDrt92C0bSdqTzzUfLP/I9zdcCBM5TSUk1WSPq0OVaTPTkvaQZJXBUsuSg6W9qWW2XOXO1M+50rqorKYty1UWjMpqzjJornB2hKW8roWZ3g5Wbh7KaMtduZytuNoeyl0XMK9zV9i+LGPm1ZnLGWbwfNW85oMd1/yz4qHNsQa738M5T/MYEzlfLSaDxdWxrsONt7Es1xcChf+M0aapI0nrh9pmtPlHrnp3NKVdabjp3Eh/s/mei916mWl1vnlyrmPa1d06wlLOPD+znjhYGBjmTNknnlBztn+1hyV0RRLDuv5F0zhsGIZmGMYSALUAzmcYptlmnQcMw1hmGMayioqKcQ/jSFX5nXAK6bfCKbAwjPTPmb3Bc23jFFjUBFy237MM4Hbwtt+5RD5tv4OFySmwKPMIaes4BTZt33bbV/qc4JjB9z3U+Q923plhSj23zPClfu9x2i+v9CVfF8l1PasDI3udZCLH1dGea674bF7Lobd32G5f5XfktX1NjuNX+cfn+MW+faqzGU9zxZNUudKKCu+Zc8z5mxb5tDQkdV+DpRGpaVypW8gZBpZBXmm0mTYZRvb55NpvPstGkvbkc82T+cfofsOFMJHTVEJSTfa4OlSZNjMtqfI708pgZlltsLQ3df2hyp12/zc/e8T00fVylQU9Ip+zDJornJU+Z17XIrXMNdJ0d7TlrlzOVlyt8ueuC5h5a4XPvizjFu3vUeo1zbVPIPf9YhlYf2a+bXeswe73cM7TPMZEzleLyWBxdazrcONtLMv1hUDhP2O0aepI0vqhthlt/pGr3m3Ww0aSzo30N5vvuditlyutHsm+ctXdKn3OQfP8fMNgGGfKPm4Hn7P9q8rnRLnXMazrXzSNwybDMPoAPAtgZWFDMnZmBT3Ytm5JWkS588pm7Nx3yvq8bd0SLKoNWOvs2HsKd17ZnLbN+uUN2LnvFLatW4KmGn/WPs19PPTCEWxe1ZT23ebVTfjRc29b+92x9xTWL29IW2fDigb89tWT1rF+/tJR3LE2GYbHXjmJjZc3Wvu2237rmmZIioL6Cg82rMj8rintfLdkfP76VQtxToXHdr/meW9Y0QBZ03H76oxzW9WEh184gs2rm/DQC0eytr/5skbEEkpWmLatW2INKN5U48+63nde2YymmsAYx4bCG+252sXn1Gs5lOZqH7auac6KO83Vvry2XzgtgK1rM7Zf24xF0/ILf2O1x/b4jdX5hb/Ytx8vmfHELk1rnh6w0hhz2e2rmyCrGrasSf7Of/jc29ic+ZsfGCMyNQ0JekTcsnKebRpyx9pmPPzCkbQ07vbVTdB0HUGPiI2XN2alhbPLPWn737q2CedUeGzTJvPfhbUB65wfe+VkVpqz8fJGNFR6s9Knco84JmlPPtc8mX8ERvUbJoRMXXZlgNS0NTMtmRX0wOfksHn1mbLjQy8cwazy7LLil94/F3MqvZAU1frOzAMy0/Yde09ZZV279Hbz6ibEZCVtGc8iuwy5ugmSqiLoFm3zj6BHxM2XNdqml/lcC7O8brfvfNPd0Za7xtusoAcLawO2eeucimTe+uu/ncDWNen3wowbmXUY85qm3vPU78o9onXNZ5V7svI9c51KnwNBt4id+05h6xr7OkPQI9rmm3bX2jzPzLh382WNVn1tot6jyaTY63Bzc5Tr506wcn0uxVIvyWUihX8kaf1Q24w2/7Crd29e3YRYQhlxOjfS32y+52K3XmodDchdR8pnX5ntdqnbmue2Y++ptLLDjr2nstrIduw9lVUmMfO7h144gjuvbMZDLxyBrOpWvdhcb+uaZrgdAMcaw7r+jGEYQ69VYAzDVABQDMPoYxjGBeBpAHcZhrEz1zbLli0z9uzZM25hHC1zlsOOcHI2Y3N2RPNz6qyHmeskZ7XnoGg6ylJmhczcZ+o+QnEZqg50RRKo8TtR4hHQ2n9mv0e7ozjVF4OD5xBJqKjyOaBoBsKSAq9TQEiSIXIc/C4eimagKyyjxM2DYxkkVA08yyGcUOB3CtbM0G6RRTShwSmwUDUgKquQZB0l7uRswmFJQ3s4gfKB2aF7ojJisoYyT3I2Rt0wEJN19McVlLgE9MVllLhFxGQVLMPA6+DBMEAorsAt8uiMJFDucUDVNQgch0q/A6qWnHmYAYPeqIxSjwgDRnLGaQPoCCcQk7NnmwbOzCzZ1i+hOuBEU00g16Dow5pZYiLG1WGcqy27uDecgehjcRn728LWrLDN1b68JqMzybKGfaf7rRlCF00L5DUZnWm0s9IWyfYFj6f5pHuqquP10/1oC0ko9zrgd3KQVB08yyImq+iNJWds1fXk77fMI8ItcABjQNUMdEcVuEUOboFDKCHD5xARTigQeQ4RSUW5V0RUVsCzLBw8h9Z+CWUeESLHQOAZqBqQULWBV5k1uEUOPMfAJXAISyrCCRUVHhGypsEpcNB0oNOaxR5w8Gxa2gycmb3W5+QhKRp6Y8m0ssrvQG1Jdroe9DgQlhS0jvD3ONxrniv/KOCkOQWPq5PZ5dd8HMH3f972u+4/fBfPPPbzcQ5RUaO4ivR0psLrBMcmXz3NlZbouoF3eqNo708glFBQ4hLBQAfLsAgnkmVFr5ODg+fgFFjEFBWaDiiagbisocbvQFTREJZUBFxCsnznFqHoWnIfkooyjwDdQLJM6nVA1lS4xeSy9oH8xYAGtyBYwxeVeUT4nDwUNfmKrM8hQNZ1MGDQHUkg6HUAMNAbUxBwCYglVMzIKD/mcy3MdXqiCQgci5isDXvG+BGk2QWNq7pu4ERPFB3hBPpiClwCC6fIocLLoSOsoT2UwJxKN8KSZtUjIgkFXocAVdPAMCwiCRWlbhGqrqMvpiDoESFrKkQuWYdwi8n6haYbVt7uEli4RBYRSUdXRIbbwUHkGIABBIZFKKHAK/KoDDigqMk6AwsG3VEZHgeHaQEXZuTINwc7z/ZQsn6RDGN6fY0MadRxdbT1mkLrj0t4K6VcP7faUxST0ZlGW68ptGGEP++4OtI0dSTl86G2GW2ZX5Y1q64W9IoIOHlEZW1U6dxIf7P5nstg7WRD1ZFGsq/Ubc1z643J8Io8uqIyAi4ePqcASdEQk5N/FV4HJFWFwHLojysIuAUYRrLMEfSI8Do4RBIaEqqKEpcDUTmZX1b6Haj0cmBZDrWlXrsw57whxdI4vAjAQwA4JHs7P2oYxtbBtpmsBW5SFKhySIoBxVNSLCiunkXUODymKK6SYkFxlRQLiqukWJz1xmFCxkDOeMrn+mIiMQxjH4BzCx0OQgghhBBCCCGEEEIImSyK530KQgghhBBCCCGEEEIIIWOGGocJIYQQQgghhBBCCCFkCqLGYUIIIYQQQgghhBBCCJmCqHGYEEIIIYQQQgghhBBCpiBqHCaEEEIIIYQQQgghhJApaNwbhxmGOYdhGMfA/9/LMMx6hmFKxjschBBCCCGEEEIIIYQQMpUVoufwYwA0hmHmAHgQwGwAvyxAOAghhBBCCCGEEEIIIWTKKkTjsG4YhgrgKgDfMgzjZgA1BQgHIYQQQgghhBBCCCGETFmFaBxWGIb5KIB/BLBzYJlQgHAQQgghhBBCCCGEEELIlFWIxuFPAXg3gK8bhnGUYZjZAH5egHAQQgghhBBCCCGEEELIlMWP58EYhuEAfNUwjI+bywzDOArgP8czHIQQQgghhBBCCCGEEDLVjWvPYcMwNAAVDMOI43lcQgghhBBCCCGEEEIIIenGtefwgGMA/o9hmO0AouZCwzC2FSAshBBCCCGEEEIIIYQQMiUVonH49MAfC8BXgOMTQgghhBBCCCGEEELIlDfujcOGYWwZ72MSQgghhBBCCCGEEEIISTfujcMMw1QA+DKAJgBOc7lhGMvHOyyEEEIIIYQQQgghhBAyVY3rhHQDfgHgTQCzAWxBcgzivxUgHIQQQgghhBBCCCGEEDJlFaJxOGgYxoMAFMMw/mwYxqcBXFiAcBBCCCGEEEIIIYQQQsiUVYgJ6ZSBf1sZhvkQkpPT1RYgHIQQQgghhBBCCCGEEDJlFaJx+E6GYQIA/g3AtwH4AdxcgHAQQgghhBBCCCGEEELIlDXujcOGYewc+G8/gPeN9/EJIYQQQgghhBBCCCGEjOOYwwzDfJNhmM/ZLL+ZYZi7xischBBCCCGEEEIIIYQQQsZ3QrpVAB6wWX4fgA+NYzgIIYQQQgghhBBCCCFkyhvPxmHDMAzdZqEOgBnHcBBCCCGEEEIIIYQQQsiUN56NwzGGYRoyFw4si49jOAghhBBCCCGEEEIIIWTKG88J6TYB+D3DMHcCeGVg2TIAXwHwr+MYDkIIIYQQQgghhBBCCJnyxq1x2DCM3zMMcyWALwH4wsDi/QCuMQzj9fEKByGEEEIIIYQQQgghhJDx7TkMwzD2A/hHAGAYxmsYRmQ8j08IIYQQQgghhBBCCCEkaTzHHAYAMAzzboZhDgA4MPB5McMw3xtimxkMw/yJYZg3GIZpYRhmw7gElhBCCCGEEEIIIYQQQiapce05POBbAN4PYDsAGIaxl2GYS4fYRgXwb4ZhvMowjA/AKwzDPGMYxoGzG9T86LqBY91RtIckVPmdmBX0gGWZQder9DnBc0BbfwJRWcXsoAe6YaC1X0JYUlEdcMDvZNEV0dAVTaDK54Ci6QhLKqr8TkiKhp6YjAqvA6puQNU1ODge3VEZQa8ITdcRiqvwOnkIHIu+qIIyrwhJ0QDocAkCJEVDWFLhEjn4nTwYhsE7PXGU+0T4nTzCCRWaZiCS0OB38YgrKjyigEhCgcBxKHHxSKgG2kISKrwOCCyDnpgMv0tAQlXBsxzCkgq/i4fIseiOyih1CeiJyXAKHLwOHm4Hi96oip6BcFd4efTHdYQTKiRFQ6XPgbisgmM5VPocYBigNyZD04GuSAI1ARfmV/lwsj8+5PUn+YvFZexvC6M9lECV34Hmah/cLjHv7fviEg62Ra3tG6s9KHE5afs8ReISDqRsv6DaA+8wtldVHS2t/Wjtl1ATcKGpxg+eH/dngWl03cA7vVG09yfQEUmgodKN/riG9lAC1X4HeA5oD8uo8Tkhazq6IjJ8Th6lHgHRhIaOcALlXhEOnoHAcYgmNPREZQTcPFw8h9aQhGl+JxKage5oAkGvA5KswiFwkBUNTpFHb0xBqVsAxxrQdAZBD4eeaDIMQZ8It8ChN5aA3ylCM3T0RBW4BtIqp8DCwQP9cR1RWUNcVuEWeXAsIPIcnAKDWEJH+0A43QKHtnACQbeICr+I9lACIsuiJybD4+DhETm0hxLwOHhU+R2oK5ua6Va++SchZPyoqo4Drf3ojiXg4nmEJRWVfgckRUNXREZNwAndADojCQQ9IiIJBR6HAAfHIK7o6InKKPeJcAkcQnEV4YSKmoADug6c7pdQ7XNAMwz0xhQEPSLiigqnwCPg4iApBkJxFZGEikqfAwIPSIqOhGogIqmo8ImIyio8Ig9VN9AXV1DjdyKuaIgrKryigN6YAo/IwevkYRhAR1jCtIALMUVDVySB6SVuNJZ70NIeRmdYQtDrgG5o4BgO3VF5wuSbIzVe6WpmWae2lMfxbgWVPic4FskyiF9EZ0RBb0xBwCXAMDTwHIfOsAyvk4fXwcIwGJzqk1BX5oKs6ugIJ1ATcCKmaAP33AFV16DrDAxDB89x6AglUOl3QNU0eMRkfaQzktxO1nT0xxV4RR7sQB7tEliIPNAVUdEVkVHuFeHkWfTFlYE8nkNrvwSnwEHkGAgcizKPmJY3j/a6Un6XbbyuiSSpeL21H20DZc6FNQE4nYVoBhmZ0dYrCo3CP/ZSfzs1ASc0PZnXpf6OMuuDJW4ep/vOrAMAx7qj6IvJUHUDHVa934/2aALtoWQ71YxSNxKqhqgsgwGX1j7gdAg41h1FdzQBgWWRUDVouoGYrMHvEiApKpw8j764ApfIwSNy6IrKqPSKUHWgM5yAz5msZ3kcHCKShvZw8nfKMkC/pMDJ8whLCsq9DrCMDlllkusEHFhYHYAocjjaFUVfTALDsFY7UrnXgZ6oDL+Th8/JI6HqiCY0GNDh4Hh0RRMo9zrQH1dQMRCetpCEoFeEk2egakBYUuB1Csl/Hcn2sr6YDLfIQxQYGDrgd/FIKAakgXOPJFR4RR4ukUNfXEaJSwQDoCcuwy0kz6XELcKABhYcQpICt8gjoaoIOEWEEypisoYqvwNeB4uopCOuaghJKtwCD4fIwO/gEZaSZTKvk4fPwUHgWBjQ0BvV4XNymFXhHnY8LUiqaBjGOwyTlvBrQ6zfCqB14P9hhmHeADAdA72PC0nXDTzV0oaNj74GSdHhFFhsW7cEK5uq0zI3u/U2r27CD/58GLJq4PPvOwdhScV9uw5BUnQsmxnAumUzsWn7fmv9DSsa8PvXW/GBhTXWek6Bxa0fmg+RY7Fp+6sodYv41D/MwrZnDtput+uNNlx/wSz0xKK4+w9vpa1THXDiJ88fRb+kYOPljWgPJdL2s355Ax7ZcwIfO38mnjnQimvOq8OWHS1p+3j4xeMQeQafu3QOtuw8893GyxvhEjh84X/+nrb+9BIndu47hacPdMEpsLhjbTPisopv/P5Na707r2zGr14+jhXzqzG9xIGobKQdd+vaZjz6t+PYc7w/5/Un+YvFZezc354W97auacaq5qq8Goj74hKe3t+Ztf0VzRV5JVBTfftIXMKTNtt/sLkirwZiVdXx+N5TuPXx/Wm/oSsXTy9YRVfXDbx0tBPv9EjYvL0F755dhpULa7B5e0taevj0/la8e065le7MDLrw/947J229LWua4BY5fOk3+4ZMG80067pldWn/fv69c6CqMo7xjrTrvHl1EzgY2Lz9AD7yrjo8/OJx9MZkbFjRgPoKDxKqjrZ+KSt9rfCJMAwGtz2Rva+v/+8B3PS+Biiahq0738hKL839N1R5sXxu1ZRKt/LNPwkh48fMQ769+xCuW1aH+3cfQmOlFx+9YCa27GhBqVvEDe+emZXW7n6zDR9eVmel13bpd2a6Z/7/9tVN2P3mMaxaXItTvfG0fd95ZTMkRcOd//tGWj7w6z2HsGJ+tZX2/+pvJ6zwph7PI3L405sduKK5Jr3suKYZj+5Jlh2XzQykhX0i5JsjNV7pqn1ZpwkuwcCnfvo3bFjRgENtIVx4Tjm+++xhXLesDrvfbMO159Xh9oy6g8/JY9eBduse2cWxO9Y245kDp/G+uTVp9YvNq5vAMQY2bT9gu50ZB2rLXOiKKNhkk09v/vPbWXm+R+TAsgyqAxEsn1sFAKO6rpTfZRuvayJJKra/3ppVrl6zsKYoGohHW68oNAr/2Ev97dile9vWLcFlcyux/fXTafXBzaub8D9/PY6DHRF852PnQlYN/Pj5t3HN0rq0dPWb1yxCZySR1la0edV88ByXVtfZuqYZs8qd+NJvXsenL5oNhgEkVU+rx/3Le+bg9h2vpqXJARePuKzilsdez2oX+q9nDuJ4dxxOgcVXPzAPcUXHvX88mLN9bOuaZlT5Rfzir8fwoUXTcbpPSrsWt6ych5++cNRq23q6pXXgfM+E6ebLGtHaF09rf9qypgnfe/awFZavrJyHhKbb1gEdYQ69UTnt3M3v3QKHLS8cwPUXzISDY/EfT6Uf49d7TmD5vGo8sucEPn3RbMSUSFr4v3ntIvREZPxnynb/vnIeyrwivpxRF64tdcHr4LDvRA9EUcSJ3jgubQwOK54WosTzDsMwFwEwGIYRGYb5IoA38t2YYZhZAM4F8NezFL5hOdYdtTI1INm7YeOjr+FYd3TI9bbsaMGqRdNx9dJadIQTVkQAgBsuqrcivrn+fbsO4bOXnpO2nqQkn7BvGijQXr201oqUdtvdcFE9jnafaRhOXedoVxSfvfQcrFo0HW93RrP2c//uQ1i1aDru/eNB3HBRvVXITt3H1UtrsWrRdCuBMb/b9sxBdEYSWesf7ozi+gtnW8tue2I/uqJy2nq3Pr4fN1xUj/t2HUKJ25F13E1PJL8f7PqT/O1vC2fFvU3b92N/Wziv7Q+2RW23P9iW3z2Z6tsfyLH9gTy3b2nttwoC5va3Pr4fLa39eW1/NhzrjkLVYFW8P3nxbOv/Zhi37GjBJy+enZburFo0PWu9zdtbcKgjklfaaKZZmf9u2t6COVWlWdd5y44WuB0CVi2abqVn5v4V1cDhjoht+urkeauwZLev257Yj7ZQdvqXuv99J/unXLqVb/5JCBk/Zh5ippmSouOzl55jlb2uXlprm9becFF9Wnptl35npnvm/2/f0YLrL5yNwx2RrH3f+vh+dIQTWfmAWS400/7U8KYerysq45MXz84uO24/U3bMDPtEyDdHarzSVfuyTguq/F7r2l/7rjps2t5i3ZsbLqq3GobNbe7bdQgd4UTaPbKLY7c9sR/XXzg7q36xZUcL3KKQczszDvAsazUMp22bI8/visroCCesvHm015Xyu2zjdU1eb+23LVe/XiS/79HWKwqNwj/2Un87dunexkdfw77T2fXBLTta8NlLz4Gk6Nh3sh8bH30t2aaTka4e7oxktRW1hhJZdZ1N2/dD0xmsWjQd3TEZXVE5qx5nl+a3hRJ4uzNq2y60atF0a1lXVLYahgH79rFN2/cjLGm4/sLZeLszmnUt7nrqzbS2LbvzvfePB7PanzYP5F3m5+6YnLMOeKgjknXu5vfdMRmrFk3HtmcOojuWfYwbLqq36qfdMTkr/Ic7IlbDsLnsP596E4dt6sKHOiLgWBYXzqlKXs+OyLDjaSEahz8H4PNI9vw9CWDJwOchMQzjBfAYgH81DCNk8/2NDMPsYRhmT2dn59iFeBDtIcm6MSZJ0dERlvJaj2EAhgF0A2nfxxOq7fpxOXt56rYMg0G3iyfUrGOZ6+gGEJdV2/Ckhtfcz2Dnk2v/dsv6YsqQ65nh74kqOc8v9XPm9Z9oChFX89We0ohlkhQd7aEEbV8E27f226c1bf3D/02MVTxtD0lpv93eHL/jzOXDSUsGS5Ps/m0P21+n6EAaaK6bujxXuhi1SZcz92UX5tT96wOvPk8l+eaf+ZjIaSohqSZ6XDXzkNT0NzV9zVnOzEiDc62Xmu6l/r8vpgxaPs06Xkq5NjO8mdvmynPMsmOu/GMk+WahjVe6mrOsMnAcSdHRNdCoP1TdIfMe5bqXfTnuY3TgPg4WB3LVH3Ll+boB668jLI36uo7lfZksxiuuto2yXF1oo60XFBqF/4yxrFcNlV625fh9mfmemd/apct2eXGu/LkrkrDajjLXGSxNztUulDq4QL7tY1FZRW80dxkitW1rsHzIbruhzt+sHw5WfhmsLmiWZXK1vw2nXKQbQG9MQcdAHVc3MOx4Ou6Nw4ZhdBmGcb1hGFWGYVQahvFxwzC6h9qOYRgByYbhXxiG8dsc+37AMIxlhmEsq6ioGOug26ryO+EU0i+jU2BR6XPmtZ4xcGM5BmnfuwfGuMxc3y1mL8/cdrDt3A4+a31zHZYBXCJvu8/U8Jr7Gex8cu3fblmJWxhyPddA+Ms8gu2+zXCbnzOv/0RTiLiaryq/w/YaV/kdtH0RbF8TcNluXx0Y/m9irOJpld+Z9tvN9TsuzbE887NdGjFYmmT3b6402SPyaeumLs+VLnps0uXMfdmFOXX/LIMJn26NtXzzz3xM5DSVkFQTPa6m5iHmv5npq205M0canPk5Nd1L/X+JWxi0fJq5zJVSrs0Mb+a2Q5Udc4V9JPlmoY1XupqzrDJwHKfAosLnSLs3ua6z3T2yW68kx330ZNQB8tl/6rZ2eT7LwPqr9DlHfV3H8r5MFuMVV6tHWa4utNHWCwqNwn/GWNarhkovq3P8vjLbeuzSZbu8OFf+XO51WN/nWifzs5m22i03Uho9820f84g8yjy5yxCGMfj5DlVPG+z8zfrhYOWXweqCqW17w7nuua5fqVtApc9pfR5uPB33xmGGYe63+buDYZi1g2zDAHgQwBuGYWwbv9AObVbQg23rlqQVfratW2IN8j3YeptXN2HnvlN47JWTqPA5sGFFg/X9Qy8cwdY1zWnrb1jRgB8+93baembha+uaJjgFFo+9chIbL2/Mud1DLxzBrKAHX3r/3Kx1Zpd78KPn3saOvadQX+HJ2s/65Q3Yue8Ubr6sEQ+9cASbVzdl7eO3r57Ejr2nsHlV+ncbL29EhdeRtf6cCg9+8dJRa9kda5tR7hHT1rvzymY8/MIRbFjRgL5YIuu4W9cmvx/s+pP8NVf7suLe1jXNaK725bV9Y7XHdvvG6vzuyVTffkGO7RfkuX1TjR93Xtmc9Rtqqgnktf3ZMCvoAc8BWwbSqZ88f9T6vxnGzaub8NPnj6alOzv2nspab8uaJjRUevNKG800K/PfrWuacLitN+s6b17dhFhCwc59p6z0zNy/wDM4p9Jrm75Kqoo71ube1x1rm9MqJ6nppfn/RbWBKZdu5Zt/EkLGj5mH7NibTDOdAosfPve2VfZ67JWTtmntQy8cSUuv7dLvzHTP/P/tq5vwi5eO4pxKb9a+77yyGZUZjYxb1jRZ5UIz7U8Nb+rxyj0ifvL80eyy45ozZcfMsE+EfHOkxitdtS/rNKE9FLGu/a//dgJb1zRZ9+ahF47gdpu6Q6XPkXaP7OLYHWub8YuXjmbVLzavbkJMVnJuZ8YBVdexdZB8OjNulntEVPocVt482utK+V228bomC2sCtuXqhUXy+x5tvaLQKPxjL/W3Y5fubVu3BIumBbLqg5tXN+FHz70Np8BiYW0A29YtSbbpZKSr51R4s9qKqv2OrLrO1jXN4FgDO/aeQplbRNAjZtXj7NL8ar8D51R4bNuFdu47ZS0LekTcfNmZ/dm1j21d0wyfk8PPXzqK+gpP1rW4ZeU87Nx3pm3L7nxvvqwxq/1py5qmtLCUucWcdcA5ld6scze/D7pF7Nx3Chsvb0TQnX2Mh144gvXLG6xrmBn+cyq9+PeV89KW/fvKeZhjUxduqPRC03W8dLg9eT0rvcOOp4xhGEOvNYYYhnkAwDwAvx5YdA2AFgAzABwxDONfbba5GMBfALwOwOxX/VXDMJ7MdZxly5YZe/bsGcOQ52bOFtkRllDpyz3Taup6FV4neA5o608gJquYFfRANwy09ksIJ1RU+RwIuFh0RTR0RxOo8Dqg6jrCkoYqnwOSqlmzPGuGAU3XIXIceqIyyrwiND0527PXwUHgWfRFB2aEVjUABlwCD0nREJE0OEUWfmdy9sV3euMIekQEnDzCsgpNMxBNaPA6eSRUDW6RRyShQOA4lLiSswO3hySUex0QWAY9MRl+l4CEqoJnOUQkFX4XD4Fj0ROTUeIU0BNT4BBY+Bw83A4WvVEVPVEZQa+ICi+P/riOcEJFQtZR4UvOYs2xHCp9DjAMBmbUBLoGZiWeX+XHyf74kNd/HA3r4OMZV/MVi8vY3xZOm400n8noTKOd1XWqbx+JSziQsv2Cak9ek9GZzNlp2/olVAecaKoJ2E2qM67xVNcNvNMbRXt/Ap2RBOZUutEf16xzFLnkzLNVPicULTnOlM/Bo9QtICpr6AgnEPSIcPAMRJ5DNKGhJyYj4OThEji0hSRU+52QNQPd0QSCHgckRYVD4CCrGpwCj96YglKXAI4zoGkMgl4OPdHkrLhBjwi3yKE3JsPnEKBDR29EhVNk4RV5OEQWDh4IxXVEZQ1xWYNb5MCxgMhxcIoMYonkGPBBrwi3wKE9nECpW0SlX0RHKDmLb09MhtfBwy1y6Agn4BZ5VPkdaTOiTyV55p9Fn6ZOZJdf83EE328/ulf3H76LZx77+TiHqKhNiriqqjoOtPajJybDwSfLcpV+ByQlOTN2TcAJ3UiWw8o8IiIJBV5RgMgziCs6eqIyyr0OuEQWobiKSEJFtd8B3UgOW1Hpc0A3DPTGFJR5REiKCqfAI+DiICkGQpKKiKSiwueAyCdfl0yoyRnAKzwiokpyxm7dMNAXS+47rmqIKyq8ooDemAK3yMHn4GEA6Agny4txRUNXJIHpARcaK7xoaQ+jKyKhzOOAbmjgGA7d0eT55cg3i8J4pauZZZ3aUh4nehRUeJ3g2OSs79U+EZ0RBb1xBQGnAMPQwLPJ2eo9Dh5ekYMB4HSfhBmlLsiajo5IAjV+J2KKlowHXgc0Q4OmMzAMHTyXzD8rvQ6oerJuIqsGOge2k3Udobialke7BBaiAHRFVHRHZJR5RLgFFr3x5Az0ToFDW78Eh8BB5BiIHItSj5iWN+db3xvlfZlSxiuuSpKK11v7rbi6sCZQFJPRmUZbryi0KRT+vOPqWNSrzN9Otd8JTQc6I+m/o7T6oN+JEo8wkAc7rYcwx7qj6I/LUDQDHeEEqnwONFf70R5NoD2UbKeqLXUjoWqIygoYsGntA06HgGPdUXRHk/WchKpB0w3EZA1+l5DM33kefXEFLpGDR+DQHZNR7hWTYQ4n4HMme896RA6RhGaFg2WBkKTCwXMISyqCXhE8YyChJvN187csihyOdkXRF5PAMCwiA0NHBD0iemIyfE4ePgcPRdMRSWgwoMPB8VZ9sV9SUOERoRrJITvKPCKcAgNVA8KSAq9TQCShwCMm28v6BsoYIs/AMAC/i0dCMSANnHtU0uB2cHCLHPrjMvxOESwD9MZluAQeYUlFiVuAAQ0sOIQkBW4x2dbmdwqIJFTEZR2VPhFeJ4uopCOuaghLGlwiBwfPwO/kEZaSZTKvk4fPwUHgWBjQ0BvT4RU5zK50DzueFqJxeDeAKwzDUAc+8wCeBnA5gNcNw1gwFseZqAVuMiVMisohmfQonpJiQXH1LKLG4TFFcZUUC4qrpFhQXCXFYtwahwkZhZzxtBCPxKcDSO3f7AEwzTAMDUBxjExOCCGEEEIIIYQQQgghRa4Q71N8E8BrDMM8i2Sr9aUAvsEwjAfAHwsQHkIIIYQQQgghhBBCCJlyxr1x2DCMBxmGeRLA+Ug2Dn/VMIzTA19/abzDQwghhBBCCCGEEEIIIVNRoWZakAC0AugBMIdhmEsLFA5CCCGEEEIIIYQQQgiZksa95zDDMJ8FsAFALYDXAFwI4EUAy8c7LIQQQgghhBBCCCGEEDJVFaLn8AYA7wJw3DCM9wE4F0BnAcJBCCGEEEIIIYQQQgghU1YhGoclwzAkAGAYxmEYxpsA5hYgHIQQQgghhBBCCCGEEDJljfuwEgBOMgxTAuBxAM8wDNML4PSgWxBCCCGEFLlP/vNNONXVl7V8enkJfvrf3xn/ABFCCCGEEEKmvHFvHDYM46qB/97OMMyfAAQAPDXe4SCEEEIIGU+nuvoQfP/ns5f/4bsFCA0hhBBCCCGEjHPjMMMwLIB9hmE0A4BhGH8ez+MTQgghhBBCCCGEEEIISRrXMYcNw9AB7GUYpm48j0sIIYQQQgghhBBCCCEkXSHGHK4B0MIwzMsAouZCwzDWFCAshBBCCCGEEEIIIYQQMiUVonF4SwGOSQghhBBCCCGEEEIIISRFISako3GGCSGEEEIIIYQQQgghpMDGdcxhAGAY5kKGYf7GMEyEYRiZYRiNYZjQeIeDEEIIIYQQQgghhBBCprJxbxwG8B0AHwVwCIALwGcHlhFCCCGEEEIIIYQQQggZJ4UYcxiGYRxmGIYzDEMD8BOGYV4oRDgIIYQQQgghhBBCCCFkqipE43CMYRgRwF6GYb4JoBWApwDhIIQQQgghhBBCCCGEkCmrEMNKfGLguJ8HEAVQC+CaAoSDEEIIIYQQQgghhBBCpqxx6znMMMxaALWGYXx34POfAVQCMAC8CODweIWFEEIIIYQQQgghhBBCprrx7Dn8ZQDbUz47AJwH4L0A/mUcw0EIIYQQQgghhBBCCCFT3niOOSwahvFOyufnDcPoAdDDMAyNOUwIIYQQQgghhBBCCCHjaDx7DpemfjAM46aUjxXjGA5CCCGEEEIIIYQQQgiZ8sazcfivDMP8U+ZChmH+GcDL4xgOQgghhBBCCCGEEEIImfLGc1iJmwE8zjDMxwC8OrDsPCTHHr5yHMNBCCGEEEIIIYQQQgghU964NQ4bhtEB4CKGYZYDaBpY/L+GYewerzAQQgghhBBCCCGEEEIISRrPnsMAgIHGYGoQJoQQQgghhBBCCCGEkAIazzGHCSGEEEIIIYQQQgghhEwQRdE4zDDMjxmG6WAYZn+hw0IIIYQQQgghhBBCCCGTwbgPKzFCPwXwHQAPj2Ynum7gWHcU7SEJVX4nZgU9YFkm5/KR7P9IZwRHu6NwCRx8Dh46DHAMg66IDKfAgucZOFgODANEEho8Dh4JVYNb5BCTNfTHFQRcAroiCZR6RPgcHOKyjvZwApU+B4IeDj1RDZ0RGbWlDkiKgfZQAtNLnFA0Hf1xBZU+B3QDON0nYVqJEwlVQ39cRbXfAYFjEVM0xGUNmqHDJfAIx1WU+0QkVB2huIKAW0A0ocIlcBA5Dm0hCZU+B0QeiMsG+iUFQY8Dum7AIXDQDR0swyA6cD4hSYZb4CHwDLrCMjwOHn4Xh7CkIZJQMbPMg9nlI7vGJD+qqqOltR+t/RJqAi401fjB8/k/C4rFZexvC6M9lECV34Hmah/cLjHv7fviEg62Ra3tG6s9KHE5p8z2Y5WmFJPUc3aLyXTAwXPwOzmEExo03YCiGmBZHSLHozOSwDS/E4puoCsqw+fgwbGAW+QRVzREJBUBlwBF15FQNXhFAd0xGWVuEf1xBV4HD7fIgQUQkVXoBhBNqPA5eTh4Dq39Eip8DiRUFYbBoMwjIprQ0BVJpqV+F4femIawlExzPQ4Ohp7cV09ERl3QDd0w0NovwSvycIkcZE2Di+cRU7Qpc18JIcVHljXsO92PUEJGiVNMlvsSGrwuHrGEiiq/E5KsoSMiI+gRwLHJcmqZR0RcVuESefTFZJS6RYQkBSLPwe/kARiIyTq6ozIqfQ4omgqvQ4Ss6mgbyC85FuiOKKj0iWAZBhFJg0Ng0S/JCHqcmFvhxeHuCHpjCuKyhjKPgKDHAYYBWvvt80xdN3CiJ5knR+XscmRmnltX6saJ3tiw8uCpmG+PViQu4UBKWWlBtQduhwNHu6I43R+Dg+MQlVWUeRzQDRWqxkDRVPAcj85wAhU+BzgG6I4qKPHwYMGiLSSh3CvC6+DRF1MQSago8wrgwKI7KsMlcnALLDQD6InKKPeKCLg4vN0Zh1vk4HXwKPeJUFSgIyyhJuCEpif/T/d16hptvajQRlsvKbRiD/9Eyh/s4jLLMoOGb6jwm2WGtpCEGr8TC6cFIIpc1nZVXgEtbRHrPlb5RbT2S2AZNll2EHh0RBKo8jlQ4ubQG9XQMVDvkhQVfqcAWTPQG1NQ6hYQlhT4nAJisgKO4SDwDFwCB0nR4BJ58CwQkTTEFRU+p4CEqoFhGKiagYiswu/kEfQIiMk62kMJ+Jw8Ai4BABBNaOgIJ8NZ5uGg6kBU0hGVVUiKhkqfA6puoCsiwy0myziaAXSGEyh1C+BYFj3RBFwCD5FPXiuBY8EyOnSdRURWEZM1VPod8DlYhCQFmsaifeCYgA4wDFiw6I3JKHEJCCcUBD3OnOmPrhs42hXF8Z4oPCKPKr8DtSXDL8+MRlE0DhuG8RzDMLNGsw9dN/BUSxs2PvoaJEWHU2Cxbd0SXDG/Ck+/0Z61fGVT9bAuvK4b+P3+Nvzbr8/s56sfmAeHwGHz9hZr2cbLG1Hhc+Arv33dWvbFK+Yi6BXxrT8exHXL6nD/7kPWd1vXNOG7zx7G8e74wOdmfPfZQ6gPerByYQ02b29BqVvEDe+eift2ndluw4oG/P71VnxgYU3a8m9esxBtoQR+8dfjWcfasKIBD794HL0xGeuXN+CRPSfwkXfVWcu2rmnGH984jacPdMEpsLj5skY8c6AV1yytw5adZ87x5ssa4XFwuPN/34Ck6JgZdOFz75mDLTtaRnWNSX5UVcfje0/h1sf3W9f7ziubceXi6XkVhGJxGTv3t2PT9v0p8bAZq5qr8mog7otLeHp/Z9b2VzRX5FUQKPbtc6U1kzm+253z+uUN2P1mGz7x7lnojymIyhp2vdGGa8+rw+07XkWpW8Sn/mEWtj1zcNA086sfmIe4ouPePx5M2/cje07gc++ZgwqfiCOd0bT9pKZlm1c14U9vtWLF/Jq0/W5d04RH95zAnuP9cAosNq+aD57jcNsT+23DtvHyRlR4HfjK7/ZMmftKCCk+sqzh8X2n8d0/HcKnL5qNw1p6+rh19QJ0ReSc5cfNq5rwg+darHKnmd7+0yX1cPDJNNJc9/bVTWAZCZu2Hziz/eomPL2/FefXB9P2u355A1575zhWLarFqb542ndfev9cCCyD7//5CHpjclraqusGdr/VjkPtkbRtzHUApOU/M4MufGF5Q1oZaKi0eirm26MViUt40qasNKfShZsf3ZdWx5gZdOHz723Ao3uOD9QZXh2yvrJlTRO+9+xhyKqRlh/b1SnuWNuMFw934smWdmxY0YDpJU48/OIxnOpLZMVvuq9Tz2jrRYU22npJoRV7+CdS/pArLlf4RPzzz161Dd9Q4TfLDJtS8vata5uxprkGuw91WtutO68Gy2ZVpN3HO9Y2Q+QZ/OzFY1lpe2Yb1ldWzkNC023boFLbnTwiB55j8NqJHiybVY5H95zA9RfOwvHuGAAgKmu2eYV5nLuvXQRJ0dPKKlvXNGNaiYjXT4Vx365DWWWf1HwlV7uaR+QgcMnORke6Ymnff/2qhRBYBl9+bF/atVE1DVt2vpFxngfwheUNWemP3X3asKIBtaUu3PP0W9b5ne24N/FTxDFyrDtqXWwAkBQdGx99DS2t/bbLj3VHh71/s2HY3E9XVLYaI8xl2545iKNd0bRl9zz9Fo52RbFq0XTrh2J+t2l7C1Ytmp7yeT9WLZqOT14829r31UtrrQhqrnffrkP47KXnZC0/PNCIYnes+3YdwtVLayEpOu7ffQirFk1PW7Zp+35cf+Fsa/17/3gQN1xUbzUMpy7vCCesZasWTbcKcaO5xiQ/La39VqYBJK/3rY/vR0trf17b728LWwm/uf2m7fuxvy2c1/YH26K22x9sy+9+F/v2udKayRzf7c75/t2HcMNF9Xi7M4quqIz7diU/377jTLplVvbMbezSzK6obDUMp+7bTFdEjs3aT2q6tWVnC66/cHbWfjdtb8ENF9Vbn1tDCasgYRe2bc8cxNHu6JS6r4SQ4rPvdD82PZEsK3bH5Ky0zO0QBi0/btmZXu4009uO8Jk00vzu9h0tcItC+vY7WvDJi2dn7ff+3Ydw/YWzcbgzkvXd3X94C11R2Uq3U9PWY91R7DvZn7WNuU5m/rNq0fSsMtBQafVUzLdH60COspKiMVl1jFWLpmPT9v22dYZc9ZXNA/WfzPzYrk5x2xP7ce276qz9He6M4oaL6m3jN93XqWe09aJCG229pNCKPfwTKX/IFZfDcS1n+IYKv1lmSLs/T+zH6xltZFcurcu6j7c9sR9vD6S3mWl7ZhuWWR6xa4NKbXfqispoCyUGjpesqx3tStYlzfqkXV5hfj7UEckqq2zavh8cy1nbZuYNqflKrna1rqiM1lACioas77/2u9dxuDOSdW1aQwnb87RLf+zu0327DuFQRyTt/M523JtUjcMMw9zIMMwehmH2dHZ2pn3XHpKsi22SFB2t/fbLO8LSsI5tt3/dgO2+dQO2yxjGfn2Gyf7cG1WsdXNtF5fVnGEa6lip66Qu64sp6cdIZB8j8xxzHWu413gyGSyujlauON3Wn9/1bk9JyFK3bw8laPu8th+bNGUiyDee5jrn+MBwD2a6k5pe2KULdmlmrnTU3D41Lcz83vx/X4514rJqe5xcaZZd2l2M93UyOptpKiFj6WzH1baB9Jhh7NPP6BDpcK5yZ660OJqSjprLcqXLfVFl0LJxarptpq3tISnnNh1hKSv/GUmZczLl22Np8HqVfVmpIyxl3QPzc646g119xYx3ufaVuW53JGH9XzeAuKxS/WMKGSyujrZeVGijrZcUWvGHf+zyh9Hm/7nisl0+nJqHDhb+thzft2Xct66w/X3UDeRM21PLEvm0QZn70w2gK5Kw8g1z2WB1wszjZK5j7g8YPF8ZrA6oGxgYliL/9r1c55mZ/uS6T6llI3PZ2czDJlXjsGEYDxiGscwwjGUVFRVp31X5nXAK6afrFFjUBOyXV/qG95qD3f45Brb7zuwFnrrMbn3DyP5c5hHS1rXbzi3yg4ZpsGOZ/89cVuIW0o/hyD5GrnPM/DzcazyZDBZXR6sm4LK93tWB/K53ld9hu31y/BzafujtxyZNmQjyjae5ztkt8uCYM+lOZnqRT5qZKx0106fSjLQw9Xvz/yU51nGJZ0ZWyjxOvulaMd7XyehspqmEjKWzHVdrUtJju/TT4xw8Hc5V7syVFntEPmtZrnS5xCMMWjZOTbfNtLXK78y5TaXPmTP/sVs3l8mUb4+lwetV9mUl85rZlgly1Bns6iuZ+Xjmd5mfg16H9X+WgZW/032dGgaLq6OtFxXaaOslhVb84R+7/GG0+X+uuGyXD6fmoYOFvybH99UZ963CZ38fWQY50/bUskQ+bVDm/lgGqPA6rHzDrEsOVie0O07qOuXe9PAPlq/kOk+WATw58qvB2vfszjMz/cl1n1LLRuays5mHTarG4cHMCnqwbd2StEi5bd0SNNUEbJfPCnqGvf//+nD6foIeEVvWNKUt23h5I2aXe9KWffGKuZhd7sGOvaewfnlD2ndb1zRh575TKZ+bsXPfKfzk+aPWvh975SQ2rEjfbsOKBvzwubezlp9T4cHGyxttj7VhRQN+++pJOIXkmCg7951KW7Z1TTN+8dJRa/2bL2vEQy8cweZV6ed482WNqExJQHbsPYXNq5tGfY1Jfppq/Ljzyua0633nlc1oqgnktX1ztQ9b1zRnxMNmNFf78tq+sdpju31jdX73u9i3z5XWTOb4bnfO65c34KEXjqC+woOgR8SGFcnPt68+k25tvLxxyDQz6BFx82WNWfveuS+ZrsianrWf1HRr86om/OKlo1n73bqmCQ+/cMT6XO134I61zTnDtvHyRswOeqbUfSWEFJ+F0wLYurYZO/aeQplbzErLYpIyaPlx86r0cqeZ3lb4zqSR5ne3r25CTFbSt1/dhJ8+fzRrv+uXN+AXLx3FORXerO++9P65KPeIVrqdmrbOCnqwsDaQtY25Tmb+s2Pvqawy0FBp9VTMt0drQY6yksAZWXWMHXtPYeuaZts6Q676ypaB+k9mfmxXp7hjbTN+87cT1v7mVHjw8AtHbOM33depZ7T1okIbbb2k0Io9/BMpf8gVl30uLmf4hgq/WWZIuz9rm7Ewo43sd6+eyLqPd6xtxjkVHtu0PbMNyyyP2LVBpbY7lXtEVPsdA8drwkMvHMGs8mRd0qxP2uUV5uc5ld6sssrWNc3QdM3aNjNvSM1XcrWrlXtE1PgdEDhkff/1qxZiToU369rUpDSwp56nXfpjd582rGhAQ6U37fzOdtxjDMMYeq0CYxjmfwC8F0A5gHYAmw3DeHCwbZYtW2bs2bMnbZk542JHWEKl78xsf7mWD5euGzjSGcHR7ihcQnLGXAMGOCY5C7RDYMFzDJwcB4ZJDqjtFjnImg4XzyGmaOiXFAScAroiCZS6RficHOKyjvZwcqbHoIdDT1RDV0TGtBIHEqqBjlAC0wJOKLqO/riKCp8IwwBO90uY5ncioWkIxVVU+h0QOTY5a7WsQTcMOAUO4biKoFeErOkIxVUEXAJisgoHz8LBc2gPSyj3OuDggZhsICQpCHoc0A0DDp6FYRhgGAYxWYNb4BBOKHAJPASeQXdEhlvk4XdxiEgaIgkVdRmzTE9Cwzoxu7g6WuZMpm39EqoDTjTVBIY16UIsLmN/W9iajbS52pfXZHSm0c5KW+zbj1WacpaNaTxNndHWTAccPAefk0M4oUHTDSiaAZYxIHIcuiIJVPudUHUD3VEZXgcPjgXcIo+4oiEiJdMiVdeRUHV4RB49MRmlbhH9cQVeBw+3yIEFEBkYviKa0OBzcnDw3MCM5w7IqgrdSE4gEE1o6BqYNdfv4tAX0xCSFARcAjwiB8NI7qsnKmNGqRsGDLT1J+AWObgFDoquwcnziClawWcrnmIKnqaOlcuv+TiC7/981vLuP3wXzzz28wKEKHeYgMKGq0hNiLhqzjweTsgIOMVkuS+hwevkEZNVVPmckBQNnREZZR4BHJssp5a5RcTV5Izj/TEZAbeIsKRA5Dn4HTzAGIjJOrqjMip9DiiaCq+YLD+2hxKo9DvAsUB3REGlTwTLMIgkNIg8i7Ako8zjwNwKHw53R9AbUxCXNZR5BAQ9DjBM8vVWuzxT1w2c6EnmyTE5uxyZmefWlSZn9x5OHlwk+fZYGnVcjcQlHEgpKy2o9sDtcOBoVxSt/TGIHIeYrKLELQLQoWiAomngOQ6d4QQqfA5wDNAdVVDi5sEyLNpDEso8InxOHn0xBZGEilKPAJ5h0R2V4RI5uAUWmgH0RGWUe0QE3ByOdMbhEpN1r3KfCEUFOiMSqv1OaHry/1Pkvk5Go46ro60XFdpo6yWFVuzhH0b+kHdcHWn+bxeXWZYZNHxDhd8sM7SHJFT5nVg0LQBR5LK2q/IKaGmLWPexyi+irV8Cw7CIy8myQ8dAPavUzaE3qqEzkkCF1wFJVeFzCFB0A30xBSUuAeGEAp8z2e7EMSwEnoGL55BQNTiF5ARwYUlDXFHhcwpIqBoYhoGqGVadL+gVEJN1dIRkeJ0cAq7kW+7RhIaOcDKcZR4Oqg5EJd0aFqLSJ0LVDXRFZLhFDn4nD81IDp9R4hbAsSx6BvIckUteK4FlwbEGVJ1BVFYRlzWU+xzwO1mEJBWaxqA9nECVzwEwOgAGLMOiLyYjMHC+QY8jZ/qj6waOdkVxoicKt8ijyu9AbcnwyzN5yLmDomgcHomJXDkkk96EqBwSMgSKp6RYTJq4So3Dk96kiatk0qO4SooFxVVSLM564zAhYyBnPC2eR2aEEEIIIYQQQgghhBBCxgw1DhNCyP9n77zD46jO/f8924tWq2I1S5Zs2XKTXDACTC4mYANxiMEUYwgJJAGub+4Px744EC4EcExLKDEXY0jihBTITTAl1IApNsTkYgcEuMlNsmwJyepte535/bGa0c7urDSrtrvS+3kePbZGc2bOzLznPee85z3vSxAEQRAEQRAEQRAEMQEh4zBBEARBEARBEARBEARBEMQEhIzDBEEQBEEQBEEQBEEQBEEQExAyDhMEQRAEQRAEQRAEQRAEQUxANImuAEEQBEEQBEGE8/3/WIumjp6o44WTMvDH32wd+woRBEEQBEEQxDiFjMMEQRAEQRBEUtHU0YPsb9waffzdpxNQG4IgCIIgCIIYv1BYCYIgCIIgCIIgCIIgCIIgiAkIGYcJgiAIgiAIgiAIgiAIgiAmIGQcJgiCIAiCIAiCIAiCIAiCmICQcZggCIIgCIIgCIIgCIIgCGICQsZhgiAIgiAIgiAIgiAIgiCICQgZhwmCIAiCIAiCIAiCIAiCICYgZBwmCIIgCIIgCIIgCIIgCIKYgJBxmCAIgiAIgiAIgiAIgiAIYgJCxmGCIAiCIAiCIAiCIAiCIIgJCBmHCYIgCIIgCIIgCIIgCIIgJiBkHCYIgiAIgiAIgiAIgiAIgpiAkHGYIAiCIAiCIAiCIAiCIAhiAkLGYYIgCIIgCIIgCIIgCIIgiAkIGYcJgiAIgiAIgiAIgiAIgiAmIGQcJgiCIAiCIAiCIAiCIAiCmICQcZggCIIgCIIgCIIgCIIgCGICQsZhgiAIgiAIgiAIgiAIgiCICYgm0RUgCIIgCIIYC77/H2vR1NEj+7fCSRn442+2jm2FCIIgCIIgCIIgEgwZhwmCIAiCmBA0dfQg+xu3yv/t3afHuDYEQRAEQRAEQRCJh8JKEARBEARBEARBEARBEARBTEDIOEwQBEEQBEEQBEEQBEEQBDEBIeMwQRAEQRAEQRAEQRAEQRDEBCRlYg4zxpYDeBKAGsDveJ7/RbzX4DgepzqdaLV5kJduQHGmCQ3dLrTaPDDpNPAFg8g26zE12wyVig14rUCAQ3VzL1ptHmSadHD6/Mg0GTAnz4Kvetyo73LCrNMgL12P4iwzAEjuPTU7dOxkhxOne1ww6TTodPqQadbCH+Dg8AZg1muQYdTC5Quize5FllkHi0EDpzeALqcf2Wk6GLQqBDkeHn8QAQ7w+oNIN2rh9AVg1mng8PhhMWgR4Dh4AkGYdVp0u3xI02lg0KnhD3KwewKYMckMDgxt9v76qVQs6p1NzTaD43hUN/eiudeDAqsR5QXp0GhonWEkEeRrqO9Y7rsNJtPhuNw+HGqxo9XmRV66HhX5FpiMOsXle9weHG9xiuVn5puRYTSkTPnhvr/hlk8lBnpWjuPxVbcT7XYvOh0+mHQaGHQMOrUavW4/3P4g0g0aqBiDQauGN8ihzeZFUYYBQY6H28/B5Qsg3aiFxx9ApkmHQBA43etBvlUPvVqFdocXJp0GNo8fOWl6zM1LR5PNg/ouJzKMWvA80Gb3It2gQb7VAI2aoaXXC6cvgJIsM6ZN6td1JzucEt1dlNHfRwz3OyqRiYkkNwRByDPc/osgxgqn24vqFocoq+X5aTAb9ZIxbE6aHgadCm4fhw6HFwUZBvgDPLpcPmSbdOh0emHQqpGm10CrZnD6gvAHebh9oXmQQauG0+tHukGLAMej3e5DhkkLi14DuzeAvHQDJlsMONRiQ4vNg4J0A8rz03Ha7pHM9xp7XGi1Rff9xMQg1cdXqd4vpHr9hzsvj4dwWc21GKBWAc29oyu3Sp/P7fbjYIsN3S4/Mk3aPjuTBmqVKqTvLXr4AkEUpBuh0zE0d3vh9IdsUu12L7LTdDBqVPAGeTi9ARRnmTElw4jj7XZ0u/zw+IMozTZjWk4aOI7H4eZenO71IN2oQUG6Eflpehxts8PuDcDlC2Ky1YjZeRY0293ocvjg8AXh9AaQa9GDMcBq1ElsWnXtDpzsdMKgVcOsV0GnUqPX44fDG0BOmh5Bnke2WS+xEQrfwObxwx/g++adalgNGgR5wOPjYDaE7Ig6tRo2jw86tVq0AYbPiYXvKtgds0x6aNTon5dmmqBWM0XfW7hep9MLvVqFDocPZr0m6r7xkhLGYcaYGsDTAC4G0AjgM8bYGzzPH1Z6DY7jsaO6BRte3AePn0NJthE/WlqGe147BI+fg0GrwrqlZdhe1YA7l8/B8vL8mC81EODw2v4mmbKHceuFZXjxs3pU1ffCoFVh/bIyzJ1sgdPLifc2aFXYvHohdBqGB946jBsWT8Xj7x1DpkmHG88twZM7a8Tz7r+8HE9/VIv6TjcMWhU2XV6OZyJ+z07Toa7dic3vHxfLbVxRjl/vrhbPu/ubs+EL8nj8vWPiOeuXlcGsU+PlzxvxzXkFkvtuXr0Ql8zJw3tHWiX13nr9Gehx+SXP/uAVFbhiQSEZiEcIOfmK5x1HyrrwPQeS6XBcbh/eOtSK+944FCaHFVhRkafIQNzj9uC9Q+1R5S+pyFE0EEh0+eG+v+GWTyUGelYA2HuyHad7vBJZ3nDxTORY9LjrbwfFY3d8Yxa0fe/m5c8bserMIjh9QYlOEvTzdWcV47k99eh2+bDxsnKowePWN78U9fqtF5bhvtcPIdOkww/+bapEL65fVoZ8qwH/88FxUTfG0nV3f3M2THqNpO5D/Y5KZGIiyQ1BEPIMt/8iiLHC6fbi74faomT1mxU5ePdwu9h3VpZYsbqyGPe9US3Oc174rAE3LJ6KdX/9UjI2KM4y4mSHS9L3b7h4JooyjKhpc+Kxd6VzmOf21EOnYbj1gjKxHiXZRsnvwhja5Q3g4XeOUv86AUn18VWq9wupXv/hzsvjQU5WBV3X7fKNitwqfT632483D7Xg6Y9qcG1lMbbsqpGt47qlZfhp1SHcesEMfHCkGRfOLsCmN78Qz910eTleqmoQbWWPrpqPll6PZL72y2sWgON53PHyAcm8LMOsQ1O3W9JHPHTlPJh1qqi+42eXlePlzxtw03nTccmcPLx7uBU/fmmfpB5ef1DSL9x20Uy8f7gZ151dEvE+ygEw8VhJthE//PoMbHqzOmqeem1lsThfLctLw9JZeQAQ9V3XLS3DrqMtuPrMYsl1Nlw8E3/4v1MDfm9BTh7ZcQTXn12CJz6QznWF+w5FTlLFmnc2gFqe5+t4nvcBeAHAyngucKrTKX4QAFgxv1D8wADg8XPYsqsGK+YXYsOL+3Cq0xnzWtXNvTHL3vf6Idz4tVLx+JM7a2B3ByX39vhDhuIDjb1YMb9QNNhetahIFGrhvPveqMaK+YXi7xtlftepVWKDEo5vekt6XofTJ94nvG4dTh9uOX961H03vLgP1c29UfU+0Bj97Pe8dgjVzb3xfA5iAOTkK553HCnrwvccSKbDOdRiFztwofx9bxzCoRa7ovLHW5yy5Y+3KLt/ossP9/0Nt3wqMdCznup0IhBElCxvfv84TnY4Jccee/cYOpw+UR91OH1ROknQsU/urMFVi4pCeu7Napj0Wolev+/1Q6I+jdSLT+6swckOp0Q3xtJ1HU5fVN2H+h2VyMREkhuCIOQZbv9FEGNFdYtDVlaPtDglfeeNXyvFfW9US+Y54XMfoezm948jEERU37/5/ePgeIiGYeG4MBZYMb9QUo/I34UxdIfTR/3rBCXVx1ep3i+kev2HOy+PBzlZDZ/3jIbcKn2+gy023PfGIayYXygahuXqKNrE3qjGdxZPEw2fwrkb36iW2Mpq2xxR87Ufv7QfNW2OqHlZbZsjqo/46asHZfuOn70Zuo8wzxMMw+H1iOwXnvjgOG78WmnU+zBoNJJjK+YXRj2X8Nzh89UDjb3inDjyu27ZVYMbv1YadZ3N7x8f9HsL11sxv1A0DId/C+G+QyFVjMOFAL4K+72x75gExtgaxlgVY6yqvb1d8rdWm0d8caFzIfkdCP0uHG+ze2JWprnXM2BZty8gOe70BWTP53hpPQaq00C/dzn9g5bjePlrczzgjlE/ueeMdZ2W3tjvi4hmIFmNJV9K33GkrAvlB5JpaXmvbPlWm3eClB/u+xte+WRiIDkFBn7WVpsnpm7ieMgeE/RRLD0j6EhBtwn6tb++g+tTQe+GH4tH1w3lOyqRifEkN4lgMFkliGRh4LHq8PovghhJhiqr4cfd3kBUvxyrf3Z65ecjsY4zFt3XD9T3Rx6j/nX8EI8NAEit75/q/UKq13+48/JwhjqvCp/3jLTcKn0+4TsOZq8KP6c7xjww3FY2kI0qHGGeKNtHxLBlCTauWM8o1y/I2cUi+6DB7IjCvxwPcU48UP3kriP8X+57C9cbqL8bqpykinFYzieajzrA89t4nq/keb4yJydH8re8dAMMWunjyv3O86F/cy2xtzkUWI0DljXqNJLjZp1G9nzB0zv8b7GuO9DvWWbtoOXUTP7aKoZQHFCZvxVYo99ZrOvkW5N/W0gyMZCsxpIvpe84lqwPJNPS8nrZ8nnp+glSfrjvb3jlk4mB5BQY+Fnz0g0xdVPkLhfhmKCPYukZQccKuk3Qr5Hnyf0//D6ROjQeXTeU76hEJsaT3CSCwWSVIJKFgceqw+u/CGIkGaqshh836TWy/bJcWbNBfj4S63j4WCDyb5G/y407qH8dPwzFBpAq3z/V+4VUr/9w5+XhDHVeFa7rRlpulT5f+HccrI7CfC3WPDDcVjaQjSocNYt9bixbm7HveKxnlOsX5OxisfoguXcQ/q+KQZwTy50fywY32PcOv16s5xqqnKSKcbgRwJSw34sAnI7nAlOzzdi8eqH4At/c34QHr6iQvNh1S8vw1oEmbF69UEwYJ0d5QXrMsvevrMBzn9SJx9cvK4PFqJbc26ANxTqaX2TFm/ubcPsls2DQqvDK541Yv6xMct79l5fjrQNN4u+bZH73BTlsuHimpNzGFdLzss068T7hdZtk1uG3u09E3Xfz6oUoL7BG1XtekTXq2R+8ogLlBdZ4PgcxAHLyFc87jpR14XsOJNPhVORbcP/lFRFyWIGKfIui8jPzzbLlZ+Yru3+iyw/3/Q23fCox0LNOzTZDo0aULG+4eCamTTJLjt3xjVmYZNaJ+ijbrIvSSYKOXb+sDH/7ojGk5y4rh8vrl+j1+1dWiPo0Ui+uX1aGaZPMEt0YS9dlm3VRdR/qd1QiExNJbgiCkGe4/RdBjBXl+Wmysjon3yzpO//0SR3uv7xcMs8Jn/sIZTdcPBMaFaL6/g0Xz4QKwB3fiJ7D/O2LxlC/H1aPyN+FMfQks4761wlKqo+vUr1fSPX6D3deHg9ysho+7xkNuVX6fPPy03H/5RV4c38T1i0ti1lH0SZ2eTn+vPckNl5WLjl30+XlElvZ9Ny0qPnaL69ZgLLctKh52fTctKg+4qEr50Gjju47fnZZ6D6heV46fnnNwqh6RPYLt100E3/6pC7qfXj8AcmxN/c3RT2X8Nzh89X5RVZxThz5XdctLcOfPqmLus6Gi2cO+r2F6725vwm3XRQ91xXuOxQYz0c54CYdjDENgOMAlgFoAvAZgOt5nq+OVaayspKvqqqSHBOy+rXZQ5kHwzMRmnRq+IMcssx6RZkghayOrTYvMk1aOH0BZJp0mJOXjq963GjocsKk688YCEByb+GDnexwornXBaNWgy6nDxlmLfwBDg5vEGa9GhlGLVy+INrsXmSZdbAYNHB6A+hy+ZFtCgl0kOfh8QcR4ACvP4h0Y6g+Zp0GTq8faXotAhwHb4CDSadBj8sPk04Nk1YNH8fB7glg+iQzeDC0O/rrJ2R2jKw3x/Gobu5FS68H+VYDyguslIxOSlzRv+VkVZCvob5jue8WT1Byl9uHQy12MatsRb5FUTI6geFmpU10+eG+v+GWHyOGLafAwM/KcTy+6nai3e5Fl8MPo14Ng5ZBp1aj1x3aamQxqKFiDAZNSB+12byYbDWA53m4/BxcviDSjRp4/EFkGLUIckLWXj30GhU6nF4YtRrYPH5MStOjPC8dTTYPGrqcsBq14Hmg3eFFml6DAqsBGjVDS68XLl8oS66QsZzjeJzscEp0d1FGqI8Yie+oRCZSRG4SwYjIKgBcfPV3kf2NW2X/1vnu03j/lT/HX7s4iHX/sbh3LBL9TmKRjO9KAcOW1VTP6k6kDMOWVafbi+oWhyir5flpMBv14hi2udeDSWl6mHQquHwcOhxeFFgN8Ad5dLt8yDLp0On0Qa9VwaLXQKtmcPmC8AV5uH1BmPRqGDVqOH1+WPRaBHkeHQ4frEYtLHoN7N4A8tINmGwx4FCLDa22UIb3ivx0nLZ7JPO9xh4XWm3RfT+REgxbVlN9fJXq/UKq1z+OeblioVIyr8pJM0CtAlpsoyu3Sp/P7fbjYIsN3S5/yP7l9SNNr4FapUJzrwc5aXr4uSDyLEbodQzN3V44/SGbVHufLcukVcEb5OH0hnTxlAwjjrfb0e3yw+MPYlq2GaU5aeA4Hoebe9Hc60WaQY3JViPy0/Q42maH3RuAyxfEZKsBs/PS0Wx3o8vhg8MXhNMbQE6aHmoVkG7USWxade0OnOp0Qq9Vw6RTQa9Wo9fjh9MbRHaaDhzPI9usF22E4d/A7vHDF+DR7vDCpFMj3aARw1yY9Wr4ghx0KhXsXj+0arVoAwyfE5/qdErsjpkmPTRqiPPSKZmm0DxVwfcWrtfl9EKnVqHT6ZPYHgeRk5h/TAnjMAAwxi4F8D8A1AB+z/P8QwOdP9DkkCBGmREzZBDEKEJySqQKZBweRRL9TmKRjO9KAaRXiVSBZJVIFUhWiVRh2MZhghgDYsqpJtYfkg2e598G8Hai60EQBEEQBEEQBEEQBEEQBDEeoFgABEEQBEEQBEEQBEEQBEEQE5CUCSsRL4yxdgD1CazCJAAdCbz/cKC6D48OnueXKz15lGU10e+D7p+8908mOU0Uif4+o8V4e66RlNVkfDfJVieqz8CMlV5NtuceDvQsyQfJaohUrjuQ2vVXWneS1X6o/ollsPorltUknVel+veJZLw9DzAyzxRTTsetcTjRMMaqeJ6vTHQ9hgLVffyQ6PdB95/Y9092xuv7Ga/PNRIk47tJtjpRfQZmrOqTbM89HOhZxjep/E5Sue5Aatc/EXVP5fcFUP0TTarXfzDG2/ONt+cBRv+ZKKwEQRAEQRAEQRAEQRAEQRDEBISMwwRBEARBEARBEARBEARBEBMQMg6PHtsSXYFhQHUfPyT6fdD9J/b9k53x+n7G63ONBMn4bpKtTlSfgRmr+iTbcw8HepbxTSq/k1SuO5Da9U9E3VP5fQFU/0ST6vUfjPH2fOPteYBRfiaKOUwQBEEQBEEQBEEQBEEQBDEBIc9hgiAIgiAIgiAIgiAIgiCICQgZhwmCIAiCIAiCIAiCIAiCICYgZBwmCIIgCIIgCIIgCIIgCIKYgIxb4/Dy5ct5APRDP4n4iQuSVfpJ0E9ckJzSTwJ/4oJklX4S+BMXJKv0k8CfuCBZpZ8E/sQFySr9JPBHMSSn9JPAn5iMW+NwR0dHoqtAEIogWSVSAZJTIlUgWSVSBZJVIlUgWSVSBZJVIhUgOSWSkXFrHCYIgiAIgiAIgiAIgiAIgiBiQ8ZhgiAIgiAIgiAIgiAIgiCICYgm0RUgkgOO43Gq04lWmwd56QZMzTZDpWKJrhZBEEOA2jORKpCsJg/0LQiCIIixhPqdiQF9Z4IYXUaqjZFxmADH8dhR3YINL+6Dx8/BoFVh8+qFWF6eT4qbIFIMas9EqkCymjzQtyAIgiDGEup3Jgb0nQlidBnJNjZqYSUYY79njLUxxg7J/O12xhjPGJsUduwuxlgtY+wYY+wbYcfPZIwd7PvbFsYYaZER5lSnUxQmAPD4OWx4cR9OdToTXDOCIOKF2jORKpCsJg/0LQiCIIixhPqdiQF9Z4IYXUayjY1mzOE/AlgeeZAxNgXAxQAawo7NBXAdgPK+Ms8wxtR9f/4VgDUAyvp+oq5JDI9Wm0cUJgGPn0Ob3TPsa3Mcj7p2B/ac6EBduwMcxw/7mgSR7CRS7kezPY8nSDclHpLV5CEZvwW1UYIgRhPSMYklGfsdYuSh70wQo8tItrFRCyvB8/xuxthUmT89AeAnAF4PO7YSwAs8z3sBnGSM1QI4mzF2CkA6z/N7AIAx9hyAKwC8M1r1nojkpRtg0KokQmXQqpBrMQzrurSNhJiIJFruR6s9jycS/Y2IECSryUOyfQtqowRBjCakYxJPsvU7xOiQa5H/zjlp9J0JYiQYyTY2mp7DUTDGLgfQxPP8/og/FQL4Kuz3xr5jhX3/jzwe6/prGGNVjLGq9vb2Ear1+GdqthmbVy+EQRsSB2GANDXbPKzr0jaS2JCsjl8SLfcj2Z7Hq5wm+hsRIUhWk4fRGgcMlfHcRklWiVRhPMvqeNYxqQKNASYGahWwflmZ5DuvX1YG9ZhaoZIDklNiNBjJNjZmCekYYyYAPwVwidyfZY7xAxyXhef5bQC2AUBlZSXtDVKISsWwvDwfs9ctQZvdg1zLyGQRHcjFvTQnbVjXTnVIVscviZb7kWzP41VOE/2NiBAkq8nDaI0Dhsp4bqMkq0SqMJ5ldTzrmFSBxgATg+ZeD57bU4+bzysFYwDPA8/tqccZxRmYOmlitTWSU2I0GMk2NmbGYQDTAUwDsL8vp1wRgC8YY2cj5BE8JezcIgCn+44XyRwnRhiViqE0Jw2lOWngOB6nOp1otXmQlz70jpq2C01cRkqGUpFkkPvw9jyRUCp3yfCNiBATVVaTkWT6FsnYRidyv0YQycRItMVk1DETkWTqd5KZVO5/8tIN6Hb58PSHteIxamtEMpHK7QsY2TY2Zg79PM8f5Hk+l+f5qTzPT0XI8LuI5/kWAG8AuI4xpmeMTUMo8dynPM83A7AzxhazkEX5RkhjFRMjjBCD69ItH+Pbv/0XLt3yMXZUtwwpSUOybVMlxoaRlKFUhOQ+McQjd/SNCCK5SbY2OtH7NYJIFkaqLSabjiGIWKR6/0NtjUhmUr19ASMcoofnR+fBGWN/BXABgEkAWgFs5Hn+2bC/nwJQyfN8R9/vPwVwE4AAgP/ief6dvuOVAP4IwIhQIrof8QoqXVlZyVdVVY3gE00M6toduHTLx1Er6W+vWzKkVV1hJSYZtqmOIXE94HiT1ZGWoVQkReR+XMlpvHKXIt+ICDGuZJVQRjK10Tj0C8kqkSpbSLs5AAEAAElEQVSkpKyO5BgzmXQMMSApKasjxXiYV02gtqb4ocabnKYq46F9AXG3sZh/GLWwEjzPf3uQv0+N+P0hAA/JnFcFoGJEK0fEZKRjcNF2oYkHxXEjuU8E8codfSOCSG6SqY1Sv0YQycFItsVk0jEEEYvx0P9QWyOSlfHQvoCRa2MTME8kMRBCDK5wKC4QEQ8kQ0QiILkjCGK0IP1CEMkBtUViokEyTxCjB7UvKWQcJiRQXCBiuJAMEYmA5I4giNGC9AtBJAfUFomJBsk8QYwe1L6kjFpYCSI1UakYlpfnY/a6JRMhLhAxCpAMEYmA5I4giNGC9AtBJAfUFomJBsk8QYwe1L6kkHGYiILiAhHDhWSISAQkdwRBjBakXwgiOaC2SEw0SOYJYvSg9tUPhZUgCIIgCIIgCIIgCIIgCIKYgJBxmCAIgiAIgiAIgiAIgiAIYgJCxmGCIAiCIAiCIAiCIAiCIIgJCMUcThI4jsepTidabR7kpU/sQNhE4iF5JMYCkjOCIGJB+oEgJh7U7gkiGmoXxESDZD4xkHE4CeA4HjuqW7DhxX3w+DkYtCpsXr0Qy8vzqREQYw7JIzEWkJwRBBEL0g8EMfGgdk8Q0VC7ICYaJPOJg8JKJAGnOp2i8AOAx89hw4v7cKrTmeCaERMRkkdiLCA5IwgiFqQfCGLiQe2eIKKhdkFMNEjmEwcZh5OAVptHFH4Bj59Dm92ToBolLxzHo67dgT0nOlDX7gDH8Ymu0riD5DH1SYV2kgxylgrviSAmIsmgHwiCGFsS0e5pHEAkO+OhP6R2RsTDeJD5sWQk2xeFlUgC8tINMGhVkkZg0KqQazEksFbJB20xGBtIHlObVGkniZazVHlPBDERybXI64ecNOqHCGK8MtbjAhoHEKlAosfLw4XaGREvqS7zY8lIt69R8xxmjP2eMdbGGDsUduwxxthRxtgBxtirjLGMsL/dxRirZYwdY4x9I+z4mYyxg31/28IYG3daZGq2GZtXL4RBG/ocwkedmm1OcM2SC9piMDaQPKY2qdJOEi1nqfKeCGIiolYB65eVSfTD+mVlUNN+N4IYt4z1uIDGAUQqkOjx8nChdkbES6rL/Fgy0u1rND2H/whgK4Dnwo69D+AunucDjLFHANwF4E7G2FwA1wEoBzAZwAeMsZk8zwcB/ArAGgB7AbwNYDmAd0ax3mOOSsWwvDwfs9ctQZvdg1wLZWSUY6AtBqU5aQmq1fiD5DG1SZV2kmg5S5X3RBATkeZeD57bU4+bzysFYwDPA8/tqccZxRmYOonaJ0GMR8Z6XEDjACIVSPR4ebhQOyPiJdVlfiwZ6fY1asZhnud3M8amRhx7L+zXvQBW9f1/JYAXeJ73AjjJGKsFcDZj7BSAdJ7n9wAAY+w5AFdgnBmHgVAjKM1JIyU5ALTFYOwgeUxdUqmdJFLOUuk9EcREIy/dgG6XD09/WCseo/ZJEOOfsRwX0DiASBVSeV5G7YwYCqks82PJSLevRG7Quwn9Rt5CAF+F/a2x71hh3/8jj8vCGFvDGKtijFW1t7ePcHWJRDOethiQrBKjxUi2k/Esp+NJnxDjW1YnIuO5fZKsEqnCeJfV8axnJhrjXVZTGWpn/ZCcEiPNSLcvxvOjly2yz3P4LZ7nKyKO/xRAJYCreJ7nGWNPA9jD8/yf+/7+LEIhJBoA/Jzn+Yv6ji8B8BOe5y8b7N6VlZV8VVXViD4PkXg4jsepTqfiLQbC+a02D/LSx2xLQlw3IFklIhmu3CpsJxNeTiPfU3GmCQ3drrHWF8TgTHhZnYgEAhyqm3vR3OtBgdWA8gIrNJqkDzpMskqkCiSrkI4DctIMUKtCYW1oDJBUkKymOCnanw8FxbJKckqMFBzH42SHEw1dTph0GuSl61GcNWD/FfMPoxlzWBbG2PcArACwjO+3TDcCmBJ2WhGA033Hi2SOExOUeLYYUHZUIhUZCbmlrTjKCH9PpC8IInngOB7vHWml9kgQxKgijAOmZptpDEAQowD15wQx+hxrtY9IGxvTJRvG2HIAdwK4nOd5V9if3gBwHWNMzxibBqAMwKc8zzcDsDPGFjPGGIAbAbw+lnUmUhfKjkqkIiS3iYHeO0EkD9QeCYIYS0jnEMToQG2LIEaXkWxjo2YcZoz9FcAeALMYY42MsZsBbAVgAfA+Y2wfY+zXAMDzfDWAFwEcBrADwK08zwf7LvWfAH4HoBbACYzDZHTE0OE4HnXtDuw50YG6dgc4rj9MykDZGwliNBlILgeD5HZsEb7V8VY7bllSigJrfwB/eu8EkRhabR5kmnS49cIZWLs09JNp0lF7JAhiRKExAJEKDGdekWhoXkMQo8No9F+jFlaC5/lvyxx+doDzHwLwkMzxKgAV0SWIic5g28ApOyqRCIYbnoDkduyQ+1brlpbh+b31aO710HsniARRYDXgxnNL8OTOGrFtrl9Whvx0ao8EQYwMNAYgUoFUD3tG8xqCGHlGq/8al5HAiYnBYC70lB2VSATD3dpBcjt2yH2rLbtqcNWiInrvBJFAghxEwzAQaptP7qxBkBukIEEQhEJoDECkAqkeloHmNQQx8oxW/zXmCekIYqQYaJtKaU4aVCqG5eX5mL1uCdrsHuRaKPMwMfoMJpeDQXI7dsT6VvML0/H2uiX03gkiQbTZ5dtmu8OD6bmUaJMgiOFDYwAiFRjuvCLR0LyGIEae0eq/yDhMpCxKtqkIWYhTofMkxgcjsX2K5HZsiPWtyvIs9O4JIoHQNlSCIEYbGgMQqcB46A9pXkMQI8to9V8UVoJIWWibCpGMkFymDvStCCI5obZJEMRoQ3qGSAVITgmCiGS09AJ5DhMpC21TIZIRksvUgb4VQSQn1DYJghhtSM8QqQDJKUEQkYyWXiDjMJGUcByPU51OtNo8yEuPLey0TYVIZng+0TUgBkOJDlGqjwiCGHlIjxIEEc5I9sk0jyBSgVSXUxpHE8TQGKjtjIZeIOMwkXRwHI8d1S1iBkbBTX55eT51JETSQ/I7vqDvSRBjD7U7giDkIN1AEKkFtVmCGBqJaDsUc5gYEziOR127A3tOdKCu3QGOi+0KdKrTKTYCIJR5ccOL+3CwqSeqfDzXJYixIJb8nup0Kr4GyfXwiPX+hvJe4/me9N0IYmQYCT1KEMT4ILxvPdjUI6sbTnY4o/pf6pOJ8UIqy/J46M9T+f0TqYuSthMIcNj/VTd2HW1B1akufFI7PBklz2FiVOE4Hic7nDjSbENNmx0vVjWi2+UbcNWj1eaRZF4EQo1h59E2bNlZK66aXDInD+8daaWVSCKpaOmVl99Wm0fRtg9aYR8esd6foC8e2XEEK+YXQq0CzirJwrml2dBoYq+TxtJHbXbp96TvRhAjR0uPfLtr6VWmRwmCGB9wHI9dx1pxoLEXHA8UZxpldcORFhtuf2m/2P9uvf4M+AI89clEypPq48tY42il86JEk+rvn0hdBpuD+nxBvHmoGVt2Hse1lcXYsqtm2DJKnsPEqCEo02899THW/vVL/GZ3HW5YXIJMk27AFcO8dIOYeVHAoFUh2Nc2hFWT6ubelF+JJMYfeo1KVn51amXqdjyssCeSWO+vurkXj+w4gmsri/HsP+uwZWct/v35Kvz9UPOAq6ux9FGuxaDovvTdCCJ+tBom2+60apqIEcREoqHLiZpWB7btrsPWXbVo6nHL6objrXZJ/3ugkeYIxPgg1ceXZr1Gts2adeoE1Sg+Uv39E6nLQHNQjuPxyclO/PTVg1gxv1A0DAPDk1EyDhOjhpwy3bKrBndfOge3LClFl9MrW25qthmbVy8UG4NBq8K6pWX42xeN4jkeP4fmGB6abXaPovrRFhFiNOj1+LBuaVmU/No8fkXlB1olJAYn1vtr7vXIdp53vnJgwM5TTh9tXr0QU7PNiu5L340g4qfb7ZfVoz1uZXqUIIjxQavNiyd39vfbL1Y1Yv0yqW54+Mp5eKmqUVKO4xHTW5EgUolUH1/6A1xUm12/rAz+YGrMu1P9/ROpy0Bz0FOdTnzR0A2PnwNj8v3dUGSUwkoQo0YsZXqs1Y7ffVyHstw0LOL4KHd3lYpheXk+Zq9bgja7B0atGute+BIAcOuFM8AYoGZAUaYRBq1Kcg85jz45aIsIMVoYtGrsOtqCR1ctgNsXgEmnwZ8+qcOCKVZF5XMtBlm5zkkbXK6J/lXWyPdXYDWgts0R99a2SH2Ua5HPsjxS340yOhMEkG7QyOrRRSWzE101giBGkMH6PJcvIOlXm3s9eG5PPZ79XiXUKoZciwEqBnS7fJLrqhlk+2R/MBSLmPpVIlWINa5VMt9NBmweP57bU4+bzysFYwDPA8/tqcfsfEuiq6aIXIsBJdlGrJhfCNanNt7c30TzslGG5kMDz0FbbR5wPCSG45GwHYyacZgx9nsAKwC08Txf0XcsC8B2AFMBnAKwmuf57r6/3QXgZgBBAOt4nn+37/iZAP4IwAjgbQDreZ5PjaWmCU6szozn+z325hVaZY0yKhVDaU4aSnPSwHE87l0xFzWtDtF7wKBVYWZeOrZefwbW/uVLiYE30qNPjlhbRGavW5IS8Y+I5CXTpMXVZxbjJy/3x77beFk5skxaReXVKmD9sjKJrK9fVgaFUSkmPMIqa+TCT3mBFS5fUFYnmQbZ2hauj2IxEt+NFq0IIoTVoME1lVI9uunycqQbyKeBIMYLSvq8LLM+qt/udvmQptNgQXGmeJ3Ifn9ekRWPXj0fP3nlgHhs3dIy3Pv6Qfzh+2fTWJ9IGWKNa5XMd5OBLLMe3S4fnv6wVjxm0KqQZdIlsFbK0aiBH359Bja9WS2Z12lSIypGSkLzoX5izUHz0g14c38T1i0tw/aqBqxbWiaJOTxU28FojrL/CGArgOfCjv03gJ08z/+CMfbffb/fyRibC+A6AOUAJgP4gDE2k+f5IIBfAVgDYC9CxuHlAN4ZxXoTMgxl9UauM1u3tAzP760HIJ/USQ6VimFadppoBBbK/vilffj7j5bg7UE8+uRQmmSKSAypvFpo9wTFAQQQkqtNb1bj+ZvOVlRe8IqJXGE/ozgDUyeRbMoRKS+XzMmT1QsaNYvqPNctLYM/yA1+k0EYie9Gi1YEEaLL5cfGN6R6dOMb1Xj2e5UJrhlBECOFkj7PFwzK99tcf78d7l3V5fRCq1bB5Qsi06jD2gtnwBPgwPPA83vr0dzrobE+kVKoVAyXzMnD9jWL0dzrQYHVgPICa8rMi5S04WSmpdcrO6/70w/ORkk26ZHRIFHzoVSyP0zNNmP9spl4cudxrJhfCI0K2HZDJQ4322D3BIZsOxg14zDP87sZY1MjDq8EcEHf//8E4CMAd/Ydf4HneS+Ak4yxWgBnM8ZOAUjneX4PADDGngNwBcg4PKYMdfUmfLBW3+nEl1/1iAMzYOAtMZGNs80ub8xtd3iwuHRS3Ioi1bfojGeSYbVwOJ2DwxuQlVWHN6CofF66QXaFnWRTnoHkJVIvZJv12F7VIDHgbq9qwPKK/AGvr0QWRuK70aIVQYRw+4KybcHtCyaoRgRBjDRK+rxY/fal8/JR1+6Q9M1Ts8042mKXjAfWLyvDK583Kpp7EEQywnE83jvSmrJelNlmvWyYqIHG3smE0yc/r3P5lM3riPhJxHwo0faHeG0PKhXDouIMrFxYiMIMI5p63LjzlQPD7uvGeqNyHs/zzQDQ929u3/FCAF+FndfYd6yw7/+Rx2VhjK1hjFUxxqra29tHtOITmeFk6RRc4b8+Mxez89PFmGADbYkRGuelWz7Gt3/7L1y65WMEgnzMbI1DQWmSqdGCZDU2ic4KKyd/O6pbFCcsLMkyy8pqcZYy2Uq0bIaTCnIaj7xMzTbjzuVz8Ow/Q1nPn/1nHe5cPifmu41HFkbiuw2UlZYYmFSQVUI5kyzybWFSmj5BNRo5SFaJVGG0ZVVJnyfXb9+7Yi4ON9uj+uaTHdHjgSd31uCayiLx2qm0HZ9QznjWq4meFw2X4kwTrju7BD95eT/ufOUg7nh5P647uwTFmaZEV00Rw53XhTOe5XQkScR8KJHtbKi2h+IsM2bnp+OZj2ph0KgV2dkGg41m+N4+z+G3wmIO9/A8nxH2926e5zMZY08D2MPz/J/7jj+LUAiJBgA/53n+or7jSwD8hOf5ywa7d2VlJV9VVTXSjzQh2XOiA9/+7b/E3wusBly1qAjzCtMxM8+i2KtSWBEZLAREXbsDl275WLJiVJJtxIaLZ+HOsNhhj1w9H9+qKIBGM7Q1DqX1GQJxXYRkVcqeEx3Y8OJ+XLWoSAz8/8rnjXji2gVYXDpp1O8vJ38GrQpvK9zKMhIrj8OVTYWrj+NCTiP1k8ALa86RlZd43u1AsiBkig1/xwCG/d0S7TWfpIwLWSWU83FNGw422qK2oc4vSsd5ZbmDX2AUmEh6lZgQJFxWlfZ5kf02A/DqviYI8+ZXPm9Et8uHZ76zCDf9MbqOf/h+JYw69WiOp4jRJeGymkjiHecmG3XtDvzgj59GJXRLldjfcY7NFcvqeJPTkSQR86GB2tnZU7NHtR+I1/YQ3i8VWA0IckC3qz+kkoI6xvzDWGf2aGWMFfA838wYKwDQ1ne8EcCUsPOKAJzuO14kc5wYQ8JDMBRYDbhhcYlkwharscoNqAZL6gTIbyWo73RjcoYB226oRFV9F4IcsPn9Y9CqVUNWFEqSTBFjT4HVgBvPLYlK7JWfPjbek602DzJNuijjtNKtLANlFlXKcGRzohkYI0PEFFgNuKayCC5fEHXtjqh3H8+7jbWtqdPpjdq6Gh7KYqg6ZSRkhyDGAzq1WnYb6pklmQmpz0TTqwQxFijt8yKTVL+2rwnbdtdF5TMx6zWy4wEeoAVbImVJ9VCInU4vrj+7BE98cFxsR7ddNBOdTm9KzMFpbD72JOKdx2pn+emGUe8H4gmjIdcvbb3+DEzLTkObffjG67EOK/EGgO/1/f97AF4PO34dY0zPGJsGoAzAp32hJ+yMscWMMQbgxrAyxBgRvl36qkVFomEYiO1yP5B7PMfxqGt3YM+JDtS1O6Jc5mNtJdCpVVjzfBW27KzF0x/Wor7TnVLbaghlBDmIhmGgf1vgCOQMU4RgnBa2MP7u4zrceG5JXMZpYSIjxMMeywFEqm8/i5dw/SR8u22763DTH6viCgkip5dMOo2sLmJgo/aOEyk7BJEspBvVuPrMYsk21KvPLEa6MTHpwSeaXiWIsWKwPi+ybz7Z4cTdrx6UtMUtu0KhI/Is+hEZDwhQuyeSgWQKNzcUVIyJhmEg1I6e+OA4VCx1xrc0Nh97xvqdx2pnQQ6j3g/EE0Yjsl+amZuGVpsX33pqaOEwI1HkOcwYy0EocdxcAGIteZ5fOkCZvyKUfG4SY6wRwEYAvwDwImPsZoRCRlzTd51qxtiLAA4DCAC4led5IevIfwL4IwAjQonoKBldH2O11Sl89eZ4q13RysapTice2XFETCABAI/sOIJZeRYca5X3uBPqLjTOyHN8QY6SNY0RidxGN1Dywem5o/+dA0EeL3zWIJHdFz5rwMVz8kb93iPBeEtqNpgshuundrsX3/vDpwNmt5W7HgDZVeECq142w3KX0zuu3jFBJBtObxCvfN4Q8hz2BmDShzyHy3LnJKQ+402vEkQyMFj/Hghw+KSuE1X1XeD40Fb0Oy6ZLdsWZ+ZZUJxlDsVgVDgeGAxq90QyoFIxXDInD9vXLEZzrwcFViPKC9JTxkDZ6fDK7sjsdPgSWzFixBgP4XdieSv/62TnqPcDsWxfcgtA4f3S/MJ03P6N2aiq78ItS0rF5Kvx9nXhKA0r8b8AtgP4FoAfIuT1O2AUbZ7nvx3jT8tinP8QgIdkjlcBqFBYzwnDQFudAChqoPE0ZGH1BoCsy31OmkGSNbjT6cW1lcVRRpXmXpfs6svsiBies/Is2LF+CVps/Y3zVKczpbfVpAqJ3kY3EtunAgEO1c29kkGU0tjUzTa3rOy22NyYkWdRdI1EdpLJvv0snnfDcTx2HWvFgcZecDygZsC8IiuWzsqTDRURayJX3+kc0Ag8t8Aiq5e2r1ksmyV9y3WLkvodE6lBsg2mh6M3RxpfIIirF4U8h4W2unFFOXyB4OCFR4Fk16sEkWrIjTUfvnIeFhVnoCjDhPouF6qbe3GizYGXqkIxhdctLcPpHpdsW5ydZxH150DjgVab8gk9tXsiGeA4Hh8eb8PBptBY+EizDW12D5bNzksJA5zVqJUNF2g1jnV0U2I0GEu7wXDGzXJxeiPDMMiFHhyLfiCeMBpCfTJNOlx7djHWPF8VFWKpudczZOO10lF/Ns/zzwLw8zz/D57nbwKwOO67ESNGrK1OJzucirIdDjUrYiyX+5OdDsm1AkE+KvzEll010KnVsoO1LqdXUp9vPfUxDjfbcfbUbHErQapvq0kVEr2NrjjThAevqJB85wevqFCc1TYQ4PDa/iZcu20vfvjnL3Dttj14bX8TAgFlcSn0anVM2VXCUNvWSJHM7STed9PQ5URNqwPbdodCfPxmdx1qWh1o6IqWRY7jEQjysttyvvyqJ2Ym8w0v7kOrTd4T2OULRmVJv3P5HJQXpCftOyZSg0TriUiGqzdHGo1ajU1vVUva6qa3qqFRqIdHmmTWqwSRisiNNe9+9SDeq27Ba/ub8K2nPsa6v+7Db3bX4YbFJcg06bBlVw18QR4PXzlP0hbXLyvDqS6nRH/G2qbrD/KK9Sy1eyIZONXhQG2bdCxc2+bAqQ5HoqumCBVjsuECUymsBBGbsbIbDGfcHF52w4v78c6hFsVhGMaqH1AaRkOozzWVRXjgrcNR9oqrFhWJjptDQemSjb/v32bG2LcQSgpXNMD5xCgTa0W8oUu+gUa6lsdqyIO5oMutbKgYsPzJjyXX+ry+O4axJSCudgjbS9QM0GlUg9ZnoFWVZPPASmUSvY2uoduFp3bVSLw1n9pVg0XFmYruX93ci3teOySRpXteO4Sy3DQsmDJ4MiOnLyD7/E5fQFH9h9q2whmOPCdz4oR4302rzSs7oFxUnImpk9Kirn3P6wejwkDcu2Iutu6qFTOZD6SXPP5Q0s2rFhVBrQJMOg3OKsnC2zLvMlnfMZEajISeGEmGqzdHmna7/IJNu9075nUBkluvEkQqEmusWZBhwh19OwaEY1v6xoRPf1gLAJiZl4Y155eC40NjxOf21KPb5RMzu3McDxUDHr5ynhifWPCquvf1g/jD98+W7FaMNc6idk8kA6d7PbJj4XmFVpTmKtvRmEh63X7Ztt7r9scoQaQSY2U3GM64ObzsVYuKotrTQNdJpn5AsA9kmrSYV2iVfe9qFbB+WRnUQ9z4p9Q4/CBjzArgxwCeApAO4Lah3ZIYCWK5uJt0GkUNdDgNOdLlfs+JjuhrBTjZ+qlUKvzmhkU4fNou2V5SmpOmuD4qFlqFPNHuQLvdi1yLHic6HFj7ly8TEgZhvJHobXStNg98gf7VO8YAX4BX3Mk098rLdkuvBwumDH7/4iyz7PMXZylbIWzp8cjG1mrpVVb/kdyewyfGCTEmA+kduYlaLEO9yxeIMqC39HpQ3+nG83vrxYUFs06NLJMOV58ZWss0aFWy37Yo04TNqxfikR1HJCFFtu2uE999lB6S2XpEEEpJ9CJcJLH0ZrNCvTnSTLLoZdvqpDT92FemD2rzBDFyxBprurzy/T5job+XT06HzR3Alp21Udes73Si0+nF6R4P7nzlAP7rojLcfF4pLAY1JmeYcKrDicsWFOKrLieaetw43eOGSafBwcYelOamRYWsAqjdjxdS2YnI7pFvE3avMqeVRJNm0Mi29TQ9hZUYD4yV3WA44+bwsowh7usIO9iFawEYVIeMtM6JtA+sXzZD9r3PyU/H/W8dxuz8UBz+eO+pqFXyPP9W3397AVwY1x2IUUEucPXDV86DWa9GSbYR9Z1u8dzIBspxPPx9268jBSonzSARZpNOA47noGIMLl9QVrjllMKb+5tw74q5ort7+Ir9L69ZGLViU9fuGFSxCPFH69qd2Pz+cUncIrNOjUyTTpzgJtIDK9WJJyj6aFBgNeDWC6ejze4V48zeeuF05Kcr62QKrEZZWcq3KitfkmXCAysrcO/rh8Tnf2BlBUqylIW1MOpUsrG1jFplS3ixQh/M+tESRQn5lMbpTQSxBhD56QbsqG7BIzuOYMX8QqhVwFklWZiSYZI9PztNh9f2NUk8gv7w/bNg0KrQ3OvB0x/WipnKbwuT41l5adh0eTk2vlEtHtt4WTm+6nbikjl5KMww4Npte6PefeGaxZhXmJHw9zeWpPJEKhVI9CJcJDlpyWWMtejVUW110+XlSNMnJqwEQRAji9xY87aLZiLdpJV3LmHAbRfNxM/erI4Z9//Lr3oQ5IBn/1kHj5+DwxvEWweacG2lNH751Ox5eGrXcdR3usUx2uluNxq6nFG7kkYC6k8TS6JzqQyXPKt8/5xnSdxiaTwYtWpsvKwcm96Ujr2NutTpz6kNx2as7AbDGTdHlpUd75r1Yv6syJjExZkmvHekNaYOiZSPwc5XQuQ1eR4S+8CLVY3YcPHMKJtYm80DnYbB6Q1iR3VL3HpOkXGYMTYTwK8A5PE8X8EYmw/gcp7nH1R8J2JEEVzcZ/1oCY602HC81Y7H3j2GbpcPD15Rgad21YiDnsgGerLDiXtltl9vvKwcGnV0wqaNK8rx6921kuuFC5qcUri2shjbP23AmvNLUWg1oqE75NEHyHsovVjVGGVMfvCKeWKcWY7jcbCpBx4fJzYCoH9rzZrzS3HVoiJxy1kiPbBSnURvn+A4HnZPANt210mUndIYcbNy0nD/5RW4741+4+79l1dgVo6yrVf1XS5s/VAa1mLrh6FQBkqMsy5/UHb71/zvVSq8v1N2RbOhy6no/g1dTpzudkuOjeakJx5iDSCCHKK8dg1aFR5dNR93fGMWHnv3mHjsoSvnYe+JTmz+QPqODzb2SHTaNZXR24buePkANvR5Egnf9tf/qMUDKyvwcW07eMivJu882oamHs+AHex4Gjim+kQqFUj0IlwkPDhZYyxDYmIO97r9eKmqAY+uWgC3LwCjToPnPqlD8SWzElIfgiBGlsh5zFddLhg0KvzinSOy4aGcHj/0GhV8AR4dDk/UnGHDxTPxh/87hW+fXSz24698HppbRC643/PaQTFMRfg8otXmHfFx0kCJ94bi1UXET7KFcYqXSWatrNPKpDRtoqumCLsngF//ozZq7P3QFfMSXTVFJLPTTTyM1jxlrOwGwxk3h5d95fNGrF9WFuXEdaTFhsffOwZfgI9y8nrk6vnY/P4xWR0yNdscpeMHOn+ou4gfX7VAMkdt7vUgyPGyIZY2r16I5h43HnvvWNx6Tqk//28B3AHgNwDA8/wBxthfAJBxOIGoVAyMAbe/tF8iLPe8dgjb1yyG2x+UbaD1Xc6o7dc8D5i0KrT0eqM60E1vVUsGUXKxgC+Zk4dnv1eJPXVd4HmImRIPNNnw9PVnoDjTiFvOmwatmqG2zR61YtPt8sHm9ov1UTHA5fXjk7pOBDkOjDFsfOMQLltQKGu84XggPK59Ij2wxgOJ3EbXbJOPrTW/SFlsrWPtdjz9kdS4+/RHNZiVryx2ptA+hIUGAaXGWZs7xvYvj7LtX2ad/PYrk06Zuu50+OD0BaOM650OH6ZOUnSJUSPWAOJfJzuxYn5hVCLAn7x8AOuXlUn0QqfdA5s3GPWO1SoV/vfTU+K5UzJNst/BE+Bh1KqQk6aHSa+BxVCMo802PPzOsZhbdGbkWnC0xYY8ix4ceGSZ9FCrQh3zSK0QR5JIY3OqT6RSgUQvwkUS4CBrjL39G7MTUp9edwBV9b2oqv8y6jhBEOMDlYphem4apk0y42BTj7hz5/m99Xh01QLUttkR5ICtu2rR3OuBQavCmvNLsb+xFy9VNWLN+aWYPsmMLLMeTl8Aj1w9Dxo1E/vx5l4PatscMcNUhP/O8YDNM/IxUGMl3ltzfilm56fTousYkGxhnOLldK9X1mllStZ8FGcnf8xhhzcgO69ypEhYjPDk2OHzqhk5aQlxuhnK/GC0nT7Gwm6gdNwc6/2ElxVCmjh9QYlR9ebzSgEgyg5x5ysHJHHvheNt9lCIiUgdP9D5St6R0G9IwlSyaI9ntz8oG2Kprt2B4mzzkPScUuOwief5T5k0q2RqtOhxTqwOz+0PYnGpvCVIMD4J26+BvsyL1yyIGeMzchAVLmgcx+O9I6041mLD7z6uk9kKxvA/O2vQ7fJh42XlKMw0YOv1i1DXZkdBhgn1nU7MLUjHMx/VoKq+V/Ri1mkY1jxfJSqxdUvLoFLJbwVQMSBNp8atF84Qt6QLXsdEauGUMfx5/Byc3qCi8s19sWcjByFKYw5bjfJbGtMNylbo82Ns/8pVuP0r36qX9eDLtyor7wnIey4/q9BzebSRG0DkpRugVsl77Tp9Qcm3XLt0BgCpHiiwGlAyyYTbL5mNmjY7OB4w6tSy32FugQVr//qlZICXna5HgdWAF6uiV5M3XV6OX753FPWdbmzbXYd1S8uwvaoBt14wHWl6LZp63OhwePHIjiMjZkxNtOduqk+kUoVkimVpi2GMtSfIGGvRJ1+MwvG0O4AgkgmVKhS6Tmjvzb0eHG+1Y+su6TjO4+cwPScNvS4f7r50DrQqoNcTwL+HzRUeXTUfj1+zAMdbQ2OB0hz5PBIGjUryu4oBGcaR98SM1Z9yfVuEadF19Em2ME7x0uHwyc5rOh2+BNUoPvLShzcvSjTxJMcebYbqxTyWTh+jOVYabNw82PxJKLvnRAce2XEsqrxg75LT2ZEJ3gQdEkvHxzpfCa22UP6iGxaXiI5TJdlGPHjFPNzz2kHx97NKsmTb1qLiTDT2OIek55TmsetgjE0HwAMAY2wVgOa47kSMCkKHF85ggmDWq7F+WZlYTjCQ5KTrUdKXjCvyeuGJrSKvLygcITRE+HXXLS3DL3YcwVWLiuDxc/j1P2rhDwIPvFWNAAfc8fJ+PP7ecfy/v3yBa88qwb3fmoPNqxfC7vbhp69KM6dv2VWDQJDHuqXRdT9jihU5FgOe/WcdXqpqxGf1XdhR3YITbQ7F4QiI5CDbrJOVwWyzTlH5yRlG2fIFCmMOqwDZ9qG0X9OqQgbF8PKbLi+HTmHaUI4DvP4g1pxfirVLZ2DN+aXw+oPgFO7u9vo5ZJp0uPXCGVi7NPSTadLBF0jM9nAlTM02ix1cOHK6R8VCW0XD9cA1lUXg+mJDbdtdh627avHYu0fxs8vKo77j6R43Mk0hWco06eD2BxEI8rj70jkAQqvHz36vErdfMhPbbqjEMx/VijHcBT10w+ISBHmGDS/tx+0vHcCNv/8U11YWS2QsfEU5XmIN4k51Ood0vXgZSr9CpDYWo0b2m6cZEmOMtRq12BjRfjdeVg7rKBhvlCBMOC7d8jG+/dt/4dItH2NHdQuNLwhihIjV70T+np9ugNMXxB0v74ePg7iQDoT6yl++dwxePzfoWCDdoAktLGcb8cTqhZg2yQy9Vj3ibTrWc/H88MYJhHKELeXhMpDIME7xMtkqL0NKc7EkGiG8X/j7v//yChh1Ss1QicXm8csa/0Zjp8FghHsxb91Vi9/srkNNqwMNXQPPDwZy+hhJEj1WUjp/GkgvC/+P/Ftl2Dw1XIfEulas85WQl27ANZVFkh219Z1uvPDpKfzqO4tw9zdnYc3503HP6wdx20Uzo2xvd716ADzP8JsbFsWt55SO+m8FsA3AbMZYE4CTAL4T152IUSHe+Cscx8PlC6Iw04jHVy1AXYcTAY6DSRsKCj9tUvT1hJjDQL9wF2eaxKDdbn9Q3L5l9/ixflkZijJNcHkD6HB64Qvw4krMivmFeOCtw7jzG7PQ7fbjliUh9/1XPm/Eva8fwv+sXojDLTYUWo24ZUkpXvm8Ec29IcUV2hLO4ZXPQ1vJ5hakI9OkA8fz2PdVD174rCE04DNqJXHIHrl6Pr5VUQCVipHXTwrAgcddy2ej0+UTV0WzTDpwUNaxWPQa2VhCFoWev009HrxzsDm0vdobgEmvwW93n8CULBPOUFDe5g30b8/uK/+nT+pQfImy7dltdi+e/b+TWDG/EIwBHA88+38nMSs/HdMUrO5OyzbhB/82VRKgfsPFMxUn1BtrhBVmg06Fn185H3e9ekCstxA/HejXPToNw7bddXh+bz3WnF+K8snp0GsYtGo1evt0yiufN6K+041f/aMWj69agMYel5ipvNPpw43nluC5PfWSFVmhQ91e1YBciwFnFGfgXye7JMk9C6wGXLWoCHnpRtS22SVJMLfsqpFsIVJqTJVbYY81iDveagcweIbc4ZJs8XCJ0SffYsCDV5TDoNHA6Q3AbNDA4w8kbPLp8gfx4dFm/OaGM9Ht9CPLrMWf957E9JzEyCCFWiGI0SWy39l7oh2PrZqPmjaHOBYstBrgC4Z2R96ypBQ8x0X1ldedVYz6LqdkfvGrf9TiidULUd1sk2wh3nLdGbB7A5LEtcKcQaMZGcOVXH+6bmkZnt9bT4uuY0SyhXGKlyyzTnZHYXaaMqeZRNPrDuCDI6ej+vPi7OmJrpoirEYtSrKN4rwMAN7c35SQxeqhejHnWsbGez7RY6Xw+ZMwZ2MMaHd4JW1eTi8Lc05fgI+yI2xevRBfK83G2zI6JNacKdb5A8FxPE52OFHf6URlSSZe6ptnCs9zTmkOOp0+zCpIx32vH4IvwCPTqMG2G87E0WYb8vvmupctKMQzH9Viy7VnxK3nBjUOM8bUAP6T5/mLGGNmACqe5+1x3YUYNeLp8ORc7e9dMRc2tx+//+Qk/vD9syXXa7V5YNKpwfM8tlx3Bly+oGx8zfA4nSadGlq1GneEZQXecPFMBPtWjNQqYGZuGsx6LR4JSzIlDJS8QU4S0+feFXOx/dMGHGiywaBVYU6+Basri5Bt1iHTrIVBo8K12/bivy4qw7WVxXDLJAO785UDyE7TweYOjGjWyFQaWKQSOWn6KDnYcPFM5KQp237UYvPguT3SeNrP7anHGcUZioyr+VY9ViyYLMlsveHimchLV3Z/ly+ApbPzJeXXLS2D06dse7YvEMT1Z5fgiQ/6jbu3XTQT/qCysBp2byAqaePm949j8bQsReXHkkidVJJtxLYbKqFVM1HXLCrOlOg2AHi7Tz8BwIl2B9QqlSQLsqBP6jvdaLV5wHGQfI97V8yVJBsA+r2Cf3PDmWizeVB9OrRlS9BtBVaDrDFZiK/u8XMoyTKiwGoQkwEMZkyNtf1pboFFdhB3sMmG/9q+b1ghJpTosVSfSBHxU2g14jOe4fawdnL/ygoUWo0JqY83EMCFswrwH89/Llmo9gUSE+aCQq0QxOgS3u90Ob1os3nR2OOWjAXvX1mBe147KCbIfmBlBUqyjeIiboHVAKtRK5nUC/200xuQOJwAfV5WLxyMmjNkmnQ4b8Yksc8bzvhfLoH483vrFY8TiJEhmcI4xUu7wwtfgBMTT6kY4Atw6HCMfALF0SDIBWX786DSLZEJxmpU40dLy3DPa/0JAR+8ogJWo3rM6xIr/KdrgDkmx/E42emQNXiOtP5J9FhJ8OKNDMnwu4/rJHMnuXlO+JwzP92AS+bmo90hnQPJ6RAh99b2NYvR3OtBgdWA8gIrNBqVIp0j9C+dTi9Od3tw59/6naTWLyvDc3vqAUB2DjopTQs/BxxttiEQMdddt7QMnS4vOI6Pa/426LIoz/NBAGf2/d9JhuHkQxDWxaWTUJqTFlMA5FZzHnjrMNz+IO5cPkdUEML1zp0+CQumZGJhcRYWTMnEudMnYWq2GdXNvTjaYsMtS0olcTorS6wonZQmGmmEe2x+/zjS+uIczy1Ix5rzp+O+N6JDRlxTWYQT7Y6o+v3wghkoyTZi/bIyPPj3I/jN7jrotWo89NYR7DzaBo+fQ2GGCVt21YDj5ePEdDv9sjFBhW0GHMejrt2BPSc6UNceHYoi0dskJhJBDrLGzaDCMUReesg49/SHtdi6qxZPf1iLbpdP8eqoRsVk769VqFjTDdqoxGpbdtUojlls1mtEw7BQ/okPjitOSHc6RsfcbEu+rYuROqm+0401z1chL92A0pw0aDQqTM02izGdhPZampOGvHQD9tR1wu4JROmcLbtq8J1zimHQqlCWlxb1PR546zCKYiSs++xUN25+rgpmgxbHW3rEUDlXLSqS/a5XLSoCEJpkNva4sXbpDLz8w3NjGm/Ddc3Bpl5ZvRTkELUFct3SMvzti8ZhhZiIR48p7VeI8cGRFhvue13aL9/3+iEcabElpD56jQab3pK2601vVUOnTkyYCwq1QhCjj9DvZJn1ONpqjxqL3ff6IayYXyj+fu/rh7ApbLv6jeeW4P6+nYPCOVt21eDGc0vQ0O0S+2sg1H4dMXJcVNV3oaHLKfbV/1fbgR/88dMhj/+FxHuXVhTgioWFeOLaBXh73RJKRkcoQqdS4aG3j2DLztC8ZsvOWjz09hFoVakRlkGrlu/PtaqxN64OBbuHw1N9uwPXLp2BW5aU4qldNXB4xt64HSv8Z3FWbCPvqU4n1v7lS9FxSghZOLfAMuL6J9FjJcGLNzIkg9zcKXKeIxhzF5dOwtRJaZieq2wOJOTeunbbXvzwz1/g2m178d6RVkV9RPi87KNjHaJhWKjzkztD9rFYc9DJmSZs230CswrSZf9u1mnj7q+UjrK/ZIy9AeAlAOJb5Xn+b4rvRCScWKs5Z0zJwLRJZvzrZOeAK+JyXm7Civw7B5vx/X+bhk9PdcneIyddj998dxHqO13IMOlkz5mdb0FtmxNrl84QV/c9fg5HW2z47+VzcP9bh8UV/41vVOPm80pFz76THU7xmnIedzVtdlxbWSx6+Qn3bLN7MDXbPGjyp1OdTjyy44jojQoAj+w4gtn5lpRchU5m2uzyctru8GB67uDverhb4tvs3hirnsoSP3Q65ct3Ob2Kync4fLLlOxQmnoi1/UmpcXosEFZJj7faB1xhHiixQKvNA44HJqXpZa+RbzXgruWzYfNEr7JnmnSwGjVYt2wGOB6ivgmPA/jAW4fx9PWLcP9bIV1TnGWUvQ9jkOjCbpcPz910Nk51OqN06UA6NFwvtTs84or28VY7DjbZZHVXvLpHboHwkR1HUJhhEHeGkIfwxKSp1y0r3029bixA5pjXpz2GHm53KNOjIw2FWiGI0SXcO9ftD4LjIc3UjlBfHZkgu9Ppw59uOgsNnW6k6TWyeqPAasTv/1mHC2bnAuiPO3yywyE7Z9CpVfiioQd3v3oQmSYdrqkswtoLy9Bm9+DPexuGvE06lb1XicTR5ZKfF3S5UiMhXZstxrwqQf15vNg8Ptz0tWmScIc3fW0abJ6xf/9y4T8398VMj4Vg/2nu9UiSGn5tevaIe54nw1hpboEFKibvLDgaHswDhdKYmm0ecNdJeFkWo85luRaoVUz2b629HlxbWYzP67vlnSNdvrjtVUqNw1kAOgEsDTvGAxiScZgxdhuAW/qucRDADwCYAGwHMBXAKQCreZ7v7jv/LgA3AwgCWMfz/LtDue9EJ1a8GbVKheVPfhzTMCogJ/xCnE21Crj71YO4ZUmp7D0MWjVO93rw8DtH8cTqBbLnHG2xY8vO2ihDS5ADqpttkq1gQiMSElN5A0EYtCq88nmjbLzaX++uQ7fLJxsTVHiu8EHosRYb5hZYRKXZ6fTi2sriKHf+LqeXBnkjTG6afFbbSWZlYR2GuyXeqNXI3t+oVbbCnWWSr3+mSVn9jTq1/P11yu6vZjzWXliGe1/v3/70wMoKqFXJ4eUebiCNpS+EFeaBOty8dAPUDJiUppO9RkOXC0atGlO00vdZYDXgxnNLsCZse5sQa1hYQBLutb+xR8wQvXbpjKjrXFNZhLJcCx5btQC/3X1C1FG7azqitjDFep5YsYqFSSQA/PydI5IJ8pv7m4a0Ch+5QFhgNeDaymJcu23voPqfGN9MiqV3FYbzGWlyLPL1yUlQdnMKtUIQo0f4uCDTpMNPvzUH6Xq1JPyTYNANx6BVob7TiW6nF92uAM6ZlimrN+o6HLhgdi7OLMnEo1fPQ4/LB1+Qh0bNcO+KuZI8JfeumAunxy8ahuW28u441Ix2u5fCzBFjgsUgPy+xJChhbLzkpcv353kJ6s/jxWLQwht0RoU7TEuA081QxiKCN2+suVai6zdSxDO/HEliOV+22jw42mIf0Pkwsmws+5hGJdgS+m1VagYUZBjw09cO4UcRc1ShLPhQvq94jOKK9iPwPP+DyB8Av1J0hwgYY4UA1gGo5Hm+AoAawHUA/hvATp7nywDs7PsdjLG5fX8vB7AcwDN9cZCJQYgMlaBRA+uXlUm2Kj+wsgJbdh4b0O1eIJbwh+IIW+Dxc6KxNvwe966YC7NeLW79/tVHJ6KykK9fVoaXqhrFawphJtYtLcNbB5oQqVMED7/mXg+2VzWgfLIVD14xDzoNgyfASbJ4egKcpK5CeWElq9XmEQeAz/6zv9wXDT2iG75OrZJ119eqU2NLTyrhDgRxz7fmYN2yGVi7dAbWL5uBe741B56Aspi7wPC2xOs0LKqdrF9WBp1G2TVcfn9UG1i3tAxuv7KstlpVdDtdv6wMSnOjqJlaNAwD/Vsv1UmiNsMNpHL6QmiXghdRrJXfqdlmzCuyhuIQXl4epXM+OtqGyRlGGHTS73lNZZFsrOE7Lpkt8c41aFWSUCavfN4oZoQVDMzbdtfhR3/9Ene8vB/LKwpQ0JdRWvA+jtSlA+nQyOcXKM404UdLy0Td9LuP6/CjpWUozow/wWDkdi+5bUpDDVlBxM9g4YzGEqNWHdUvb7ysXPGi2EijYrysHkyk/YVCrRDE6BDupHHD4hI89u5RTJuUJpt4SUAYW71U1QiLQQvGQmHBYo0Hpuek4X/3nkSaQYMAB2z9sBa/eOcYtu0+gc2rF+Lxa+ZjzfmlcHr8mJwRCjsl10dur2rAtWcX43t/GHqYCYKIB40qZIwMl+sNF8+EJkXCSjAmP69hKdKF+gOcbLhBfyAxMZPjHYsI3rxyc63RhB9jlah0fhmOkrCig43TY4XSMOnUsg5O4XOs8LK7j7VFjcOFkIIvVjXi7m/Oxo3nSm1VDZ1uZJp0UDF52wVTMahViMsoHteSU5ih9tsAegFUxlM+4r5GxpgfIY/h0wDuAnBB39//BOAjAHcCWAngBZ7nvQBOMsZqAZwNYM8Q7z0hkNu+/PCV8/BpXSc2r16Ioy02BDlg64c1uLayGE093kG3LMutPJVkG7FkxiQE+8I7NPd68PzeetGb+KySLLj8ARxq7BXLHWiyYVUgiMdXLYDTF0CORY+fvnooyjO40GrEM/+oxY+WliHdqBXvLQj8c3tCmX6vrSzGxjeq8dS3F2LLdWeIXnDCdZ744DhuPq8Uz/6zDstm5+Jr07MlK1l56QbZ2DR3v3oQC6dkoDQnDS6ffFwyl0+5wZJQRrfLC41KJVmh/dll5ehxjc32o0lpelgMGkniB4tBo9iDzqLXYntVgyQh3vaqBvzymgWKyqcZtLL3t+iVrVC3OZJrO3Yk4QbScH0xvzAdZXkWsePeUd2CYy022ZVQBoZTnU5cUJaLLxq7UJRpwBOrF+JIn17btvsErjurGG6vHwGTFu8cbMbaC2cgJ00PU4xtpx5/EN19W/QEffnkzuOS84xaFdacX4qyXIuYdFMov2VXDdacXwqDRi3xPg4PkREI8rLPI6eXBBq6XWISDOGa97x2CIuKM+PetRC53UutGrttV4SUgUKmJMLo2Nzrxl//VY9HVy2A2xeAUafB73afwNqlZZhXNHj5kabL6ZdNLDo9gXJJSWkJYnQQxgXhxtgjLfJhp7LNOqxdOgM8D3GHYUOXG8/+sw4z89IwJSv2eOCqM4phMWok4/36Tjc2vLgPj69agKnZZiwqzkCQ6xtryGzzXTG/UPQ0Fuo01DATBKGELpcXerVKMi/Qq1XoGqN50XDpjtGfz0iR9uKMEZvc6U0NG8BYevMmcmyrZH45WKi/8LoqfZZYoTR8QW5ABychCd0jV8/H5vePYXlFAexuH9acX4rCDCMautwSpyWbJ4CtH9ZK+p6fvVkdWtT0BfHK541Rbew75xSjsiQrroWAQY3DjLEShIzB3wYQAFCCkNfvKcV3CYPn+SbG2OMAGgC4AbzH8/x7jLE8nueb+85pZozl9hUpBLA37BKNfcfk6roGwBoAKC4uHkr1kobhTkLkti/f/epBPL5qgeQ4gJjbmiPrkWsxYOv1Z2DtX76Ex8+hJNuIH54/Azf8/lNkmnRiFszmXg+e/WcdHryiAia9Cic7QrFi7/7mLNi8IeFtc/hw3xuHAQBPffsM0SgjYNCqkGc14PZLZuNPn9ThB/82HS//8Fy8d7gVC4qs8Ad4/NeyMpj0Gvx29wl0u3zIMusH9MzbvHoh5hVmRL3Hqdlm0fM5spxgJIm1JSMvfWjbE8aTrMoxHPk1aDT42ZtfRCm/5286e0zur9cxpBu0aLP3D7rSDVrodcrKBzgePzy/FM02Lzge0KiAH55fioBCr5KZORa02z0ozjKhy+lHllmLIMdhZq5FUfk0vfz2M7M+/u1noyGnkW1J0Bdvh02s6todohfRuqVlki2d65eV4aG/H8YFs3MxK8+CyRkGBBmP2yL02pM7a/DE6oWweQK4pnIKOI7HM/+oxZ3LZ8u3ZasBj69agLoOJ7RqhskZBtxxyWzUtNnxYlUjrqkswsPvHA1NBC+eKasvijKMeOKDGon3cXiIjHtePxj1PI9cPV9WLwmMZObfyAGiUasRF2HC30UqJtlKNZ06UMiURBgYss36/t0RPMAQ2kWRZdaNeV0AwGLUiolFBRK5jXYkJzypJqvExGUsZJXjeJh0aqxbNgNluRZkmnRo7vXAF+TkQ91Y9LjvjWqxHd61fDbs3gBuWVKK091uZJt1MccDjAFdTh8yTTp855xiccG4qceFDJMGX5ueIxoFNq9eKLtATYuqycl41qsWvRY/3/FlVFuIZ16USCxGjWx/npYiYTHCHdQEDFoV0o3xh5VIlJwOFu98pBa/Ezm2VTK/jKeuSsKOArGN76c6nfLh0dIMkvFkSbYRv7hqPn7wx89wy5JSbN0VCmX47D/752cFVgNyLPI5dmbkpkHFmGwbm1doxddKs+P6lgO2SsbYJwCsAF4AsIrn+RrG2MmhGob7rpmJkDfwNAA9AF5ijH13oCIyx2StLDzPbwOwDQAqKytTdn/PSExCYhkUeMgPaiK3NRdnmnCqwyEmZAivh2CknZFrwU/6vOeaez14bk+96FWnUTG4/AF853efimXXLS3Dm/ubcMPiEqhYf1yVbpcXG1eUi5lMhe2sm987huNtDqxbWoZH3z2CR69egJeqGmHWafDEB8clxqJ1eWniqkgsz7xYBhiVimFOQfqAsWlGOsD6eJFVOYYrv51O+cQLnU5lgf+He//TXV785JUDUbLw3A/ORlHG4B1bkAuCsWjP5yCnbPvR6V4XWmw+MQyL0B5O97owNWdwA3G6QSMu1IS3kfQhDMJGQ06VtKXw5AnCyi9jwOw8C7btPoHlFQUSA+u9K+aKE0oBj59DdbMNv/u4DuuXlcGiV+P6s0vwyI6jUQbajZeV457XDqK+040CqwE3LC7B9//wmWTXRaZJC4+fQ4HVgLLcNFl9kWbQSryPw5+r1eZBfadb8jw8DxRmGMY0Vlj4AFGYAI+HJFupplNH0ug/EpgNKqyuLBb7dCFci8WQmG2rHMdFjwtWlIPjE7ONcyQnPKkmq8TEZbRlVW68JuwMFLYFRy4O/8/7x7Hm/FJMz0nD6R43PAFO9KYyaFV48IoKWd16pMWGvHQDCqx6/ODfporbxIXrOsK8AIXJ/twCC0qyzZJ50FklWSPaJxMjw3jWqz0uv6xM97iUhatLNIxx2HR5OTaGLepsurwcqiTJhTIYeel62XlVXnr8MZOTUU5HcvE7kWPbeG01g9U1POxoeD9Ukm1GcZbUeC5nfI9VH7UKkvFkfacbe+o6xd8NWpWk/8s06XDjuSU43eOW7XuOtTjwr7p23H95Be5741DYGL4C55RkQaM0LmUfg1kL2gEUAcgDkAOgBjEMs3FwEYCTPM+3AwBj7G8AvgaglTFW0Oc1XACgre/8RgBTwsoXIRSGYtwyEpOQWAaF4kyj7PFzpmVh+38sRp5Fj6IME9470oqjLTaJV5lQjz/94Gxs2Rla1Qi/TnOvRzzO85CseGSadPAEgvh/X58BfzCIWfnpeGzVfDDGYNSqcP9bhyUGk1//oxYr5hfiQJNN9Gz2B4P46aVzcHvEdu4nd9bg7z9aApWKxWyIA3nmAbGzfwoKhZLRKGe48ltglZfRAquygfdw799qlw/L0GpXtn1Lq5b3fH5O4Qp/s82LX/+jVmwPQKg9TM2er8g4zPE8CqwGyfazAqsB/FgHf4qBkrYUrr+E7LoGrQqPrlqAfz9/elRIhwfeOoz1y8rwyI5j4jUMWhXm5ltwy5JSePxBVBRa8e/PVcHj5yShb2bmWqDTqFDf6QYgH4f37lcPYvuac2HQqnDVoiL8YseRqEnrvSvm4tcf1WLN+aU4Y0oGSrLNkucSnik8W7BBq8LVi2Q3woiMZuZf0muJYywThCjB7g6K3nhASO7veyO+HRsjiU6txq9310rHBbtr8dgqZeF5RppkM+YTxHhAbrz25M5QiKYtO2ux62gLfv+9s2Dz+BEI8mjsceH8Wbl4qaoRqyuLwAPiPKXAasBVi4rAcTzWL5uBF6saJbt4ynItqG2zY2q2KSp+qHDPmXn9Gd1VKoapk9JQnGXGwikZYh9ZnGkaN4uqRGqQG2u8MATjZCJgUOOZj6T9+TMfJa4/j5eiDBOKMo2SeVVRphFFGfHn/khGRnLxO5Fj23jmNKEdK/I7bYW6Kgk7OpT6/OtkZ9R4kusLz7r7WJsY/pUHjw0XlaEsz4L//N8vZHfTCglS//OCGfjFjiOSNvb0RzWYlZ+GBVMy43qPAxqHeZ5fyRizArgawCbG2AwAGYyxs3me/zSuO/XTAGAxY8yEUFiJZQCqADgBfA/AL/r+fb3v/DcA/IUxthnAZABlAIZ675RgJCYhsQwK5ZOtUcfXLyvD7S8dQLfLh82rFwKAmOlRrh4uX0AS8DqyUfE8JHG6BE+8LbtqcO60LHxrwWTc8Pt+j+IHVlbAF+AlrvAARMOYx8/BalCj0+nHiXaHbJ3aHaHQFUM1digpN9iWDCLEcOV3Tp4F96+swH2vh61+razAnLz0Mbl/zKy6CgdhXTE8n7sUej7bvQFcW1kcpfzt3oCi8lajDn/eexg3fq1UjB363Cd1eHTVQkXlx4JYbUnY1iTEYLqzz4Nb0BO/fO8oLltQKPt+C6xGlGQbUd/pFr2BH3n3qPh7aU6aWC7cQLt26QzML+zfOaDXqGSv7wsG8eAVFWjocsl6ANs9fvR6/KgsyYJWHa1vhmrkHW0DLum1xFCcacKDV1SI8aQFj7ehJBocCYa7KDbSdDh9qO90R40LlOrRkSbZjPkEMR6INV47Y0oGXv7hYjT1eHDXqwfwH+dPx/19cX7DJ8Q/OG+aaBiO9O4SPJC7XT6sX1aGh98+gm6XTzIWCL8nx0N2nCjXR9KiKjGWDHdelGja7F7Z/rwtQeOLeGnoduHx945hxfxCMAYEOeDx946hfLJ1XIydR3LxezQdWpSgZE4jeEo/IuPoE15XJWFHh1KfcKO0sKhp0Kiw7YYzcarDKXl3Gy8rh83tF52ldhxqxqOrFoDneBxvc2DHoWZcvagITl9Ato219HqwYEpkrQZm0H3GPM/3Avg9gN/3xQG+FsD/MMam8Dwf5+0Anuf/xRh7GcAXCMUw/hIh9/o0AC8yxm5GyIB8Td/51YyxFwEc7jv/Vp7nUyMC+BAZiUnIQAaF5eX5mPWjJTjeaseRFhue29Mf7FrwDA53bY+sx5RMkxg8W27L13N76nH1mUViWcETL9Okw3fOnYq1f5F6Vd77+iHRSyD8PoKjo0GrwryiDDEWi1ydjFo1OI6HSsWGbOwgI8nIMFz5/arHjRc/kyZGeu6TOpxZnInpuUqMu8O7f7pRjQdWVuDesEHYAysrYDWqFZXPNutk75+tMHZnhlEbtUq5ZVcNnvuBMg++qdlm3HTe9JTzaonc1lSSbcS2GyqhVTNo1Sr8+KV9onev3Put63Dgjktm42irHTPzLPjle0fF8z1+DnXtDtlyKgak6bX43Y2VONXhwLQc+ZAROpUKT+2qwe2XzJb1AH7+prNRYDVizfNVkvcubMsajpGXdNP4o6Hbhaf6dsUICwxP7aoZUqLBkWCyVV5vFgwxrv5wiaVHExUDOdETHoIYj+RaYuxyzAq1q+8++yluPq9UNAwDEQlgtWpxR0/kuOnJnTV45vpF2NfYI5nnDDQWUDGGunbHoH0z9cnEWPJVjxtPfygdLzz9YY3ieVGiybXIO93kWlLD81kICxdt3B4fO4dGcvE7FXYkhntKh+8kPbc0G2eVZIl1HSjsKIOyvkIOXzCIdUvLsL2qIcoZbP2yMjFMosfPYdOb1Xj8mgUwaFXINOmwvKIAP3l5P25ZUopn/1mHm88rRafLhy6XT7ae+UMYw8cbTM7J8/xTPM9/DcB5cd+tD57nN/I8P5vn+Qqe52/ged7L83wnz/PLeJ4v6/u3K+z8h3ien87z/Cye598Z6n1TBWESEu6dO5RJiDB4WVw6CaU5aRJhZww40mLDlp21UXE6Bc9gId5JZD1OdTmx+f3QCppGBfzh+2fhD9+vxE++MQu56Xp0u3x45fNGrF8WKit4EV+1qAgHGntkV2CKM02S+6xfVoa/fdEobtcWGolcndYtLcO6F77EjuoWcAqTfhGjx3Dlt77Liar6Xqz765e485WDWPfXL1FV34uGLueY3D8QAALBINacX4q1S2dgzfmlCASD8Ctz3IXd65eVUbtXWWwwYYUwHI+fg82jrLzQMb+9bgleWHMO3l63ZEyyxA6XyG1N9Z1urHm+Cv4gj9017aKh95XPG3HvirlR7/elqkYcbbVj665aHG+1i+cLvFjViPsiyq1fVoZskw6HmnpwsKkXTKXC3a8ejPp+D6ysQGuf58PDbx+J+vvDV86DUacWPZ2B/m1Zpzr75TaWTiYmHuGTja27avH0h7Wo73Sjze4ZvPAooFUzsc8G+tuHmKRujOlxy+vRXndiYiymql4liGRGrYKs3lGrQmNBj5+T7EQUEOYNv/qwFveumBszSVy7wxs1z4k1Fphk1uHz+m5cuuVjmk8QSUV9l1N2vKB0XpRo3L4ANq4ol7S5jSvK4fYpnFglGGERKxyDNpRYbDwwUnYngWSf64R7SguOPlt21mJPXScaul2Sc4Wwo5H9xX9t3zfkviLbrMf2qgbcv7JCdlHzqkVF4rkeP4fGbhcevKJCEuJCsIepVaGQFC9WRdvH7l0xFwGOj7t+ijIUMca+BuB3CHn3FjPGFgD4DwD/L667EYoY7qpLeMZJs14Df4BDr8ePkiwzpk0KXafV5hHjm8h55jy+agFq2uz47GQnHl+1ADyA4kwjMtO0ePnzJly2IBQn8w+f1KPbVYNnvrMI9791BAVWA9YvK0NRpgneQBC/vaESjPH4XZ+RONY9W2wecUW0vCAdahXDNZVFCHLA1l21uPvSOaK3Xvgqz5klmfjvVw6iudeDDS/uw6wfLRl0FXWkMnIS8gxXfs06DSpLrKGwCN4ATHoN/vRJHUw6ZQnVVCqGS+bkYfuaxWju9aDAakB5gVXx/Xs9fvx6d524fYjjgV/vrsPDV85TVF6jUmF7VYNkhX97VQMeWFmhqLzgCRPZRgxaZZ7LQPJ7tXAcj4YuJ1ptXjh9AZRkmdHl6t/WLmyzYQywefww6frfSXOvB3aPX4z9xfPA83tDW0dn51mwdukMGLWqqHfY7fKh1+3H/6xeiF63Hya9Bo3dLvz+k5NYMb8QxZlGbOxLAhiuY2bkWsDzHKpP98rqoJm5Fjz09hFcU1kkOzmt73SSjiGiSLYwBU09oaSy4XrruT31mDbJjHlFg5cfaSx6jawe/cVV88e+Mn0ku14liFRDSGYttPMMowbTJplxot2BNL0Wt18yEyXZZlldafP4caDJhks9fpTlWuS9pmR2RAhjgSdWL4QtbCzwq3/U4eozi4YVb5MgRoPhzosSjU6jxitfNETtCP3xJbMTXTVFqFXA3d+cjQ6nDxwPqFlod5M6Mfl6R5yR8PaVs60ASJi9Jbw+Jp0GvmAQ2WY9ijNNMWMNB7lob/Dwd1Pf6cSXX/VE7bgX+gql9qWp2WbcuXwOWnrlw3mwsCIGrQouXxCz8y0IcrzEqP383nrcfekc1LbZ0e3yScIdqljI2exEuwOZZl1cfZlSrfIEgG8gFP8XPM/vZ4ydr/guRNwMdRIyUOZfIabw8vJ85KUb8Ob+Jtx20Uw88YE0Y++Jdgf++H+n0Ovx49YLy8QEcCXZRtx6YZmY/EHw5Hl+bz3Meo24WsHzEBNGCfFS7v7mbHQ6fXhtX/Q9N15Wji07a9Dc64FBq8Lvv3cWOvsU8N++CCWUaOpxiZlCm3s9ePafdVi/rAweP4erzyzC7mNtWDIzF8dabWAMAwYgH6mMnERshjOJLsrSY3VlMX4SJkP3X16Ooixl2484jsd7R1qH/I19wSCuP7tEIqO3XTQT/iA3aFkAyDBp8cOvz8CmN6slMp5h1CoqL3jwRWbFlYtjm4pwHI9dx1pR0+qQPOOjV89HSbYRvgAfFTvwtotm4q7ls/HzHUfh8XP44HALrqkslmQ+Xr+sDA/1xRS8a/lsbLysXPIN7l0xF69+8RV+eEGZaAQWdNj2qgbcfsls2ZjE65bNQPlkKzKMWjHcSHOvB28daMLPLitHXbsT311cjNIY4Si+/KoHbj9HOoaQkGxhCrLMWnS7fJJtk6HFYmV6a6RJN2jw/y6YEZXdPN2QGpNhgiAGJy/dIO5OyDRqYTVpcf9bhyVbbUuyjfjZZeX42ZvS/j7TrENJthEObxCPv3dUNlHPUzuPY9Pl5RI9cttFM/GXT+uxcmFhVDg7Q19W96HG2ySI0aAwxryoUOG8KNFYDBpcE1H/TZeXw5Ii/Xm7wwu3n5PYP267aCY6HF5MnZTcOkKpwXI483Y528rW68+AL8AnxN4iV591S8uw62gLrju7BE/tqpHtL7ZXNcgmCRfeTavNI+kzgP6+Ymq2WbF9STA47/uqO2aII+H/Gy6eiQKrAW5/EF91uyXnN/d68Ph7R3HHN2aLdgMhgfumy8vxUlUDbvxaadx9GVOSwZ4x9i+e589hjH3J8/wZfcf28zyftGkmKysr+aqqqkRXY8ypa3fg0i0fRwnazeeVigLz9rolohA3djnh8AVFD7y/fdEoGpHr2h3Y+mGteK1bL5yBZ/9ZF3XtNeeX4qozCnG42Y6jLTZReYaf89sbKxHkONg8AfQ4feLqm4qFYhE9/eEJdLt82HhZOX79j1oxiZRgfAaA//x6qaTcJLMOv/pHXajcinL8end/uVgNMtb7eXtkPQTi0noTVVZj8enJTtzYl7BQwKBV4bmbzsbZ07IHLT/cb1x1qgs/fmmf6DkMAG/ub8Ivr1mIyqlZg5Y/2NSNtX/5UizP88BbB5qw9fozMK9w8IyhX9R34VBTb5SsVxRasahk8PvHQULktK7dgdf2NcnqiW03VKKqvkv2b2svnIHibDM8vgBMOg0ee+8oVswvxOx8C2ra7HgpIjP5C/++GF0uH/Z91YMgF/oGP/z6DHxZ34FLKgpxoLH/+HVnFcOsV6PDEXrnQCh8RbfLh19/90zUtjnw+HvHMDM3Df95wQx81eWE2aDFA2EJcjaumAObJyhZVBD0V7fLN9I6ZqIxLnWqMGhPhrhsX9R34V8nu6IWpc6ZljXSekcRn9d34edvRyfWvOvSuTgzAfWJg3Epq8S4JOGyGghweG1/E+557RBuPq8/hmLkXOPub86Snas8vmoBtBoV7B4/ntpVgx9fMhu1bXYEuX7nkpJso5iPQBhPZafp0enw4uF3jor6bsPFM1FRmI6vOt0wGzSYV5iOkmzqs5OEhMtqIvnsZKeYyF3AoA3lujhLwbwo0XxZ34WHZPrzn146F2ckd38OANj/VTeu3bY36v1vX7MYC6ZEzesUy+poy+lYOcTJzbvXLZshO5cbi7lQLDvAo6sWiAsUwg5VYYfoL987ijuXzxnw3QxkXwAQt+3hZLsD7x9pxeb3++eNd3xjFqZkmnCgqRcqBpTlpuHj46249qyp2PDSvqgYxXd/czamZJlQ02pHQYYJLm8A7Q4vXvr8K9y3ohy/+qgGj65aKFeHmAKgdMnmq77QEjxjTAdgHYAjCssSo0z4qpDbHxzQRT18NXx5eT4+Ot6Gm/4YrZjq2h3ISdNLrhUr7ldZbhqKMkwozjLDGLECIpzj8QXh9AXR3OsWJ58CBq0Kz1y/CBo1w5adxyVJpLb0Jex59p91sBi0cPqCyDLp0NTrxq/+UScagza9VS0awAfaEjaSGTmJ2AwndEerzSv7jVptyrLaDvcb270+Wc9hh8KYwc098ll5m3u8mBe9IBlFj8uHX/2jTgyrEOSAX/2jDg9dUa7o/smOENJG7htp1QwLp2TI65AAh9o2u2i8Fd7xI1fNk13JPd3rxoYX90uutenNajxz/SJ0ODw4Z1oWOhw+PLZqAVp6XWix+SReAeuXlaEw04jTPaEsxR4/h2/OK8CRFhsKrUac7nVLkwa8dQT3rZiDx1YtwLFWuxjuQtBRpGOIWChYox91mno8eOdgs7jt06TT4Le7T6Ao04RFJWNfnza7F1X1vaiq/1JyvD1FspsTBDEwHMejurkXDV0u3LKkFDq1KmaMYZs3iK27aqOu4fQFkGfQIyPTiJULC8FxfNR4oL7TLeYjAEJzjv9ZvRAvf94o6juLQQOH24+b/tifUPbBKypQaDVBoxkne8eJlKVlmPOiRNNik+/PW1OkP3f55G0rLl8wQTVSRmQul3hC5sQzj5ebd8ea543FXCiWHcDtC8juEP3NdxfhD98/e1BbxdRsM7ZefwYONPaK4UXmFVkxNduMf53sjPt5O5xeGLVqMUyiioV2zQX7JrocDzz+3jE8sHKeaBjedbRFdOCcOzkdh0/b8OVXPVH9HgA0dDpx03nT496RqNQ4/EMATwIoBNAI4D0At8Z1J2JUiFwVWr9shqyLujD5NGhVMGrV4DgeKhXD1BixvEpz0qBi8vGBI3+3GLSoaujCggJrzDgu3gCH//7bAdyypFS28XzxVQ9+93Ed1i0tQ1OPVzSoePwcpk0y4dFVC/DL946ivtONtUtnRA0SI2O0xGqQyRbncTwy3JXK/HT5rLZ56cq2T8XKfq00cUCaTisahoGQLD3xwXE8f9PZisobZOLdCscU3d8gv707TZ+Y7d0jTV66AWk6+bjKuRYDWAy9c860LJi0alSf7kVWWr+MmPTyOses18jqGm+QQ6fTj/ve6J8E/vzKefjff9VLvvmTO2vw4prFaOkbZBRYDUg3aiWelYJnsGAgthh0ONZqx+8+jl4tJx1DhJNsIY4KMwz45rwCybbP9cvKUJiRGLm1xGjXafrU2IZKEBOBoToCyOm/p647QxwnRbZ9dYxxQVOPG0atGhoVw5adtXjq22cMOAcCQv27wxeQ1XfhC773vHYIZblpcp6BBDGm5MWYF+UqnBclmnRDavfnseaVyT6uH6qzVLzjUznbSiydPRbvLJatJ5aNKt9qQKstZHcarA/zBXi8vq8JK+YXgmeAXh2yqQ3FvqRXq/DQ20fEMgVWA248twT3vi4NfWhz+7BifiECHI8fLZuJ+14/hPpON+791hz4glzMfF7lhVYsLMyIe06hqFXyPN8B4DtxXZkYNkoGXSc7+leFCqwGGLRq3LtirmS7sxBz2KBV4edXzYPdE8CO6mbkpOnh8gXw6++eiY1vHIIvwOOayiJMzTaDMUCvVeGhK+fhp68ehMfPYe+JdjzznUXY91UPOD601X7DxTNR22aHzROAyxtEl9MrG8elscclCm2sgVu4p7BgGBM6D7WKiUnw0vQhw1KmSSd6V4aUkFpyTbkGmWxxHscjJzuceGTHETEoOgA8suMIZuVZBk0WCAC5Fh0evKIC97x2SOLBkWfRKbq/VgP86jtnQK1SocvpR5ZZiyDHQatwDNLt8st2pt0uZZ7DaXoNNlw8U7JNZMPFMxUPgrpdftk21ONWdn8guZMuTs02Y8GUDDE+UqZJhxvPLUFxlgntDg/A8/jFVfPx33870B+y4bJyPLbjKHo9fqy9sAyPvdsfX/C3u09ExRfeuKIcQY6L0jUl2UZkmXQ44rfhliWleOXz0LbTu149KNE7QOibt/R6wRjD+mUzoFWr8MBbhyV6xxsI4sZzS/DIjmN9C2UavPJ5Y9T337x6IYozTahrdyRNsgYisQzHo2M04DgeO4+0hDzpwhLenFWSGMOIVs1k9eh4ib1OEKmOkD8g0otq6aw8ST8mjEc6nV7o1KHkOhaDBvWdTtyypBRAKIzTyQ4H7v7mbKgY8KvvLkKbzYs0vQZaTSgGY2Ts4PCwTc/ddHYohN3uE9i4ohyb3qqOmgMJGLQqmLRqcfwh9Ocef39/DghjAA8WTBn+e6J+nhgOVqNadl5kNSpPVJ1I9FoVHryiHAaNBk5vAGaDBh5/AHqFTjOJRq2C7Hgk2RPSxWOwlCZwU2PDi/sk+vFYiw1zCyyyMZblbCvziqz45TUL8eOXQte5prIIM3Mt4DkepzocaO5Vrg/j0aEcx0PFgIevnIe7++xXQn/xp0/q8Oiq+ahtc4h91tzJ6fjkRCecvmDMPkzgVGfIvhEZ2uGRq+fjG7Pz8PMr5+GusHs+cvV8dDq94juKvGaHwyf5NlctKorql7yBIHLS9bj95QNRfZ8vyGFOQTp+8c6RKLvBfSvmYl9DNxq6XLhiQWFcO2AUWSsYY1tkDvcCqOJ5/nXFdyMUo2TVhuN4HGm2iYbhGxaX4IXPGnDNmVOw6fJy5KcbkGHSwh/kkG81oN3mQZvNi7v+Jm0s26sasG5ZGXwBXmJgeejKClh0WvzPtQuRa9GjvtOF//e/X0g6Jr1Ghef31mPF/ELsa+zBouJMfHqyI2pr9dVnFsGgVeGVzxtlDV9CXGGPnxOVrfC3n79zBCsXFmLrrlpxi//9l81Fp8sv8eITgnYLMZNjGXx1GiZx4ReSYRAjQ3OvK0pxrltahuZelyLjsN0bhEWvweOrFoiDCK2KwaFw+47dHUCb3ReVyCjPElBU3qBV4ZK5k/CdxdPQ3Wdc/vPek4o9fz3+AHLS9BIZC4VoUXb/LJMWD1c1iMZ1nge2VzXg8VXKQrwnm0diJEIdnttTj/XLypBh0kn0jpA04JnrF+Fwsw1uP4df/6MWt5xXimyzDkdb7bhsQSF2HGrGzeeVQq0CpucY8acfnIVOpx8WvQY8OPS6A3ji2oX4xTtHUN/pDiXUvGAGvveHT2U9fyMHeQatCic6HHB4g1CrgKmTzMg06aKS5d27Yi5Kso247qxi6DQMOg1DgdUg+f5mvSoqSWIikzUQiSeWR0erLTHhR5y+gGzCGKdCvTXSmHRqFGcZJf2ARgUYdakxGSaI8U59pxM1rY6ocEzTJ6VhWp8OE8Yj4RNqYUE4chdOhlmLLJMevZ4A9jX04MOjbbhgdi6Ks0ywGrTYeaQZv/7umaiq74ZZp0aQ43H1mUVI06sRCHJ45Or5UKsYdh1uweOrFiDI8zBp1XD6Auh2+QD0zysaul0x+/MCq0FMkJ1vHZ6XW7KPx4jUwOMPhV0LH1dq1SxqDJG8cACYmOBesCGokBr1b3d4oVerJO9fr1YlfUI6pQ5xkXpq3bIZsvqxJNuM4qxoI6eQYG32uiViDo3iTBM+qmnDhovKonK0CAt2gr1mIH0YK9ldbpoep3s9KLAaUV6QDo1GJTk306TDmvNLMTPPgimZRrTavdCo8tFm80r6rI2XleOFzxrEnFXrl5VhRk6a7HdttXmwYn6h+E6AUNvc/P4xBDgeW3Yex83nlcKoVWHu5HRserN6wFxY5ogdcoxB9r3nW43INIUc5K5aVARPIIh7V8yBP8DhVx/W4vZLZqPb6cUz1y8KhV81a9Hl9KLX7R/SDhil/vwGALMBvNT3+9UAqgHczBi7kOf5/1J8R0IRSryKTnU6UdNmh0GrwlWLirC9qiHKKHfvirkoyjTifz44jh9fMluc+AnXFDx16ztdksDhmSYd2mxe/HTnIVFRhP9d2HL1P9cuxE1fm4af7zgqUfhmvQp7T7TjnNIcXH1mEYzaUNDsh985iuf31osN9nirXRKX06BVYUauBWuXzpDE7BTijApb/J9YvRD3vXk4onEex59+cDZyLPqYq0qnOp1Y+5cvo1bRKFnUyKHTqKMU55ZdNXhOYVgGX4BDXYczKjFSjkXZ9imHNygahoX7b3yjGn/6gbL756frcNGcyfiP5z8X73//5RXIT1fmuaxWqcWVQwGDVqX4/ia9GrdeMAP3hRm377+8HGa9MqNIsnkkypFrCS3iOLxBPLmzWlYn/b+/fIG1F87A0x/WosBqgMMbELffCBO8HYeaceUZhajv9ODe1w9J5MWkVeP3n5zED78+A2l6NaxGLdb0fdPIez37zzrML7Ji3bIZ4mpyjkWPYJAX5XD9shm4prIoSrYfeOswHl21AD9/+wjuzZ6DLdeegWt/K01cIac/DzT2Rh1Ltu9EjB6xtreZEmT8NOu12PjGF1F68883n5OQ+viDPBq63FGeOsm+jZMgJgqnI3KIePyhcEzzi6yicVgYj9x8XqnYdwreUZF98TPfWSQ6oJRkG/HD82dIPIDvXTEXx1tseHN/E64/uwRPfthvaL7pT/1hojZdXo4up1fMS1KSbcTmaxbA5QuioduF5/fWY3VlUcz+XBgTPHhFBcoLrMN6R6kwHpsopLIHt8fP485Xhj6vSDQMatHrGei3IfxvgsYX8aJTq0Q7h4BBG0pIl8zIGW3l5D5ST3E8ZPXj3a8exMIpGbK6S6ViKM1JE/9W1+7A2r98iZvPK8XmD6L7CWG35mD6MLJumSYdalodoi1HsDtdsaAQDd0u8dzmXg+27KwVv9O6v37Zp9ulddn0pjRn1QufNeDM4swoz2aO4xEI8lCromMpr5hfKO6yf/rDWtx64QyxLxPuI/eceel6cRetx89BzeTf+6Y3q7F+WRl4HhIb3/2Xl+O7i4uhYoDTF8T/+0u/A+eGi2diboEFmSZd3DtglPoYzwCwlOf5p3iefwrARQDmALgSwCXKb0coZaA4MeHnvFgV8sRVqyC7mvHAW4fh9gZxbWUxatvsstdkLDpweOTgLVZg8cPNNnS6fJJ73vPaIdS2OrC6sgTP/rMOW3fV4qldtdBr1fjNdxdh42VzMSPXgsYuN+bkp4ueu4Ib/C/fO4qtu2rx9Ie14up9ZLwwb4CTrY/gHTCc90oMjx6XT/Yd9ygMy2D3BmQnHHavMg+2Nrt84oY2hYkPetxB3PeGdBBz3xuH0ONW5rnc5fQi06TDrRfOwNqloZ9Mkw5dLmX3DwR5vFjVgEdXLcAjV8/Do6sW4MWqBviDyrJWpYKMq1XA+mVlsp2soJM8fg756QYxo6zcZPI/L5iBbrdfNAwLf3tyZw06XaEYTZverEZNmwPNPfLvRa0CfnrpHJzqCC2Qbd1Vi9/sroNBq8abB5rEMh8ebcPMXIvsNY632tHt8uFoi12iDwXk9OdAyRqI8Y8vGMS6pWWSGJvrlpbBH0yMJ017DL3Z7khMwhiXLygahoW6bH7/eNIngCGIiYLdE5DVGQ5PfxsVxiPhSeZiJbfe91WPeHzF/ELRMAyEDAKtNg8yzXr8/Mp5Yl4IubHBxjeqUZRpwtVnFqHAakB9pxuHW+x46sMazC/KwHfOKYZBq0Zxlkm2HnMLLNi+ZnHcW3HlSIXx2ERA8Ci8dMvH+PZv/4VLt3yMHdUt4Dhl4+pEM9x5TaJpd8jXvyNB44t4SdWEdEC/0XZx6aRQPimZBZFIPfXK542YkimvH2PpLo7jUdfuwJ4THWIIvUjdH34dIezkYPowsm5yOv+e1w6hurk3pr4V4sgPVpcCqwHXVhbjxj98KuqJNw+cRiDA4VSnE/e8fhBz8tOjdhJHzmVj3SfyOYuzzCjLS8Oa80uxdukMmHVqlE5Kky1blGmKsvHd90Y1ssx6HGu1R72Tze8fBxjDf369FIWZxpjvVw6lvV4hgHAfdDOAyTzPBwGkRstOMYQ4MeFExonJSw953z2/tx5luZaYhhY/x2PLrhoxYHXkNXm+P3C4gJxgy5UNckBk3+rxcyjIMEUZ2Da+UQ0/x8PhDeAnL+/HL3YcxW0v7sOa86fj7m/Owh++fxZe+LQB159dIpkwr19Whr990Si5r0bNZOtzsMk2YKev5L0SwyPdqJV9x+lGZRsVPH75TtjrU2Y0ERLaRd4/X2HihrYYWYGVDsJy00MB5YWFkd99XIcbzy1BrsKEeC5fEFX1vVj31y9x5ysHse6vX6KqvlfxIERInBCOQas8Id9Y0NzrwXN7Qnorlk4yaFVod3jxs8vLMTtf3ih7pMUW08jK8f16jOMhJq6LvNd5MybBH+Tw+HvHogYbN503HQXWkIF6eUWBuFMj8hoqBty7Yi5eqmoUtwmFE6lfYx0jXTRxyDbrsb0vfMzapTNw83ml2F7VgCxzYhLMpMVoH2m6xCSMSeXJGEFMBCZnGGV1RoG1X4eFj7nDz401nxAIn4MIYfO27a7DHS8fwN6TXYMamoUk19//2lSUZBuxaEoGfvKN2djywXGoGMOTO2vQavPI1mNOQToWTMkctmE48vnD70H9/NgSy4P7VKczwTVTRl6MeY3SRN2JxtSXhDocg1aVMmGiYs2rxks7jtRTzb0edDq8ip9ZbvElEORldb/wu+D0N9h7jKxbLJ3f0ufpK98nyfdDkXW5alG01+6drxzAJ3Wd6HR6Ud/pxq8+qsW9K+ZKrndmcaZ4n1svnIEpGUasXzYDBWFhiWI954ycNPzb9EmYX2jF3MlWdLvk37vLF70Ym2nSwekLxpwHt/Z64PQFYdTG186UjvofBbCPMfYRAAbgfAAPM8bMAD6I646EIpTEiQk/5+G3j+C+y+bKblNV98UwMWhUeGBlBRq7XXixqhHdLp8Yc/jmf5uG2y6aKa7GC4YLISi2Tq2SxO8UvJy2VzVg5cJC8X4FVgOuqSxCkOPFhE8AxMDaOrUKT8l4Nz+xeiGcvgB6PX4YNP1xfcw6NQozjZJ4YQ9fOQ/zCtOj3o8QP1To9OW2KVBCutHHH+Bk40oHFHrEFfZNOCLluCBT2SAoL12H+y+vEBcnhLAQeQrDQkyy6FCSbcSK+YXiauKb+5uQbVZW3uMP4oXPGiQJ+V74rAHzi5RtT4yVQCAvXdkgRPDKjQzLkQyJE4RtfSrG0O3y4eG3j0j0TrheuW/FHOSnG9Hl8omGq/DJ4jWVRSi0GmHSa1CSbUR9p1u8j2CwDXJ9CwMWHXRqhkevng+VimHbP07geJsDGy8rx/EWGyal6WU71qMtNly1qAgAxFiJkbL94BXzMCXLgLo2B3QahjyLPkrHTErTRz3nvCIr6aIJzNRsM+5cPidpvn+aXo2NK+ag2eYVQ6vkp+sVh7MZadKN8mE3LIbUyG5OEOOd2bkW3L+yAveFhXS6f2UFZueli+cIY+5HdvQnzHnl88aoMcrDV87DkzuPi+XS9GoxzNOsPAsef69/S3dkZvbwuUp4gmqPPxSG7jc3nIn/3XsSZXkZaHf4wBjw1LfPQIYxlFPlv7ZLdbCKAXtOdIxI6AGacyQHA3lwp0Z4Dw6PXD0PJ9qdYv9cmmMGUiRmr1mvwd3fnI0Op0+sf7ZZB3OCFp/jRa2CbP2TYV41EsjpqRl5aYp1l9ziyz2vH8QjV8/H83tO4t4Vc2VjDivRh1Ozzdh6/Rli4tPZ+RbZsWG+1SD7HA9fOQ/pBi22Xn8GHnjrcNQc7oGVFdj6YQ2AaA9g4VkONPZgcWk27v7mLBRkmNBm8+CxVQtQ3+nE4tJs6DQMj62aj8Zud9TcOzy2cvhzysVSvudbc5Bh0kX1j7dfMkt0vAvv6+YXWaFCqI9cv2wGXqxqlIRpbbN7sfXDWswvsmJ6rkWxPChqlTzPP8sYexvA2QgZh+/mef5035/vUHw3QjFK4sSoVAyXzMnDthsqUVXfhXabBz+7rBw/e1OapTfLrI1K/nDfirmYOsmEA429uP2S2Xj47SMAgEdXLUBtmx0GrRo/vXQOHGFb/IW4Ll0OL3o9QWyvasDaC8tg0KpFgY28z13LZ8MT4KKMP+Fxhj1+Dh5/EO9Xt+GhK+fhlr7YYQIl2UZs//fFcAeCkvcwJdOM2euW4HirHQebbFHXlOv0lcbfIYbO5AwT7nn9UFRCtW+UK4y5q2VRWak3XV4Os1ZZL9ztDADgQomMfAGYdRq4fH50OwMozh68vNWokY35m2FSNojxBznZhHxKt4sPdzIheOWGv//n9tTjjOKMhCZOiEwUIHR+f/zkFNYvK0NpjhlGrRrdTh++f+5UMKYS4yeVZBtFmZDTMxtXlOPXu2slCQWEmMNPXrcQva4A1odNAO+/vAKTM3Q43e3BpreP4pYlpbKDjSAXGiwIq7LNvR48v7f/3QqT1msri7G9qgE/WlqGyelG1LY7JIkrOI7H3w+cxs3nlWJ+YTrK8izi9yRdNDFJtr4ow6SCRq2WJOp4YGUFMk2Jmf14/EHZRUZvgDyHCSIZ+KrHjac/rJGMNZ7+sAZnFmeKyYdFPZdvQZfTi+1rFsPlCyLPosfcyen4vL4bQQ74y79OiTGGM006qBiT6KLweUN4YutXPm/E3d+cDacvKBkT3HbRTDGxnMcXxBVnTEGbzYNblkzDY+8eE8/75TULsWP9ErTYPMhJM+BkpwPLn/xYMvYaTvK4ZNPzE5VYThep4/nJ0O30S9rEfy+fPeyEiWOFRsXDqNNg2ztHJeMLjTo1wnq0O7zwBXnJ+7/9kllJn5BOKbH0FKBsjiK3+FLf6UZJlhE3nDsNm98/JiYQryzJQkm2EWcUZyjWh75A/7svyTZGLUoK8eGF55j1oyU40mLD8VY7Hnv3mGic/dMPzkaHo78f8gd5bNl5DCvmF0KtAs6amiWrJ0pz0vDjl/bhpq9NQ02bHRwP2Dx+TM9Jwy/eOYymHi82r56PO14+IDGQP7mzBr+9oRLpBg0yzFr862Qnci0GqFVAq80bZVB/8O9HsOGiMhg0Kjxz/SJ4AxxOtDvw7D9PAgDuWj4bLn+or8s06ZBu0EjycoQbo++/vBxP9MV6Dg/1pIR4lmw8AJoRSk43gzE2g+f53XHdrQ/GWAaA3wGoAMADuAnAMQDbAUwFcArAap7nu/vOvwvAzQCCANbxPP/uUO6bakQG95ajoduFNc/3G1MLrAasX1aGstw0GHVqGDVq7GvsiYpFcv9bh7H2whl4/L3jWLt0Brr74mQeb7Vj665aAMDtl8zE1r4A3UK5e147hEdXLYCjzY67vzkHD79zBD+7vBxPrF4Io06NH/5ZmvCp0+WLSrokJIF6+sPQfQxaFRyeAM6aNgmfhm0XE6jvdOOrHjcurSgQg4IL8Wzy0g2YnW8RV/4FBur0lbxXYuhMmyTvETdtkkLjps2HZz6qlUw4nvmoFj+/ch5Kcwcvb/cGcN8bh6Pk4Xc3Viq6v8MTFA3DQH9cn+cVJtQz6zSyCfmUlgcAs14VMm57AzAbNDDrlRtohHAzQvsCkmMQHL6yLBiw15xfiuIsE3QaNdptHui1Gtzbt7Dw7Lv9YR7qO9145qNaPLpqARiAOyISa256qxqPr1oAP8fBrNXAatbgWIsDKxcWwqzTYP0L+yK+5yH8/vtn4el/nIDHz+GVzxvxwMoKSVI7wYP5gZUVAPo9lZp7PXj6w1CSg1AyTze27KrB2gtniFlh5ZJeCkluIpNfki6auCRTX9RuD0bF7r739UN47gdnY1rO2NdHr1GJYTfCFxl/cdW8sa8MQRBR1Hc5Ud/plow1AKChyykahwF5Pbf/q24x6a9AuyPUx6sA3B4jebaQi2R7VUNox6E3gDS9Bv8VMcl+4oPjYp/rD/JY+9cvZRPD/vilfdj+74tx9tTsqITVA+1CjIdk0vMTlVT34FYxhl+EJUTz+Dn8YsdR/DmOeUUi8foRc3yRCujVqqjQc4+/dwwvJnlCuniIpaeU6K5Yiy+MMdz5SshgGm7zeXvdEiwunaSoXpFeyaE+pwZ/vvkcdDq8yLcaUF5gFcMAqVQMjAG3v7RfUp8NL+7D2+uWoHJqyEusrt2BH/zxU3GXMMcDT35wLGoueO+KuXhkxxFcd1YxXP6gZIFg/bIyfGveZLj9HBq63LJex6d73Pj3voRyguF2/bIy6NQq2fPnTk5Hm92H//eXL3DLklL87uP+PsvuDYh2uasWFUXl5XhyZw0eX7UAkyw6HG+xi3m7CjLiCz+jyOLAGLsFwG4A7wLY1Pfvz+K6k5QnAezgeX42gAUAjgD4bwA7eZ4vA7Cz73cwxuYCuA5AOYDlAJ5hjKVGkJoxIHK1RjC62DwB3PynKnzV7YJZp5EVQE8gdEzY4hUZj8UTI+nb8VY7tuyshZ/j4QvwaOv14rYX98HhjY6HEisOirAVw6Dty0BuNWDTW9Ux4yIfb7XjVKdTNq7N4WY7tl5/hqT+qdTpjzeElbu31y3BC2vOwdvrlsTleeH0BsQJh5CYsL7TDYdX2cpXrCQpShPatcaIOdyqMOZwp1M+IV+Xc+BkiQINXU4ca3Hg9pf3486/HcTtL+3HsRYHGrqUxUYTBsHJ1h7kdNVLVY3wBjj85OX9uOf1w9j6YQ2euu4MzMyLDshf3+lGbZsdx1rlE2s6vQE8uuMY1vz5c3zv958hw6TDlp21aOqR77Abu1y4trJY9C5y+wPYvHoh1i3rj/96bWUxOJ6HigEPrKyQvNN1S/tjoXv8oeR5mSadmPgg8n5qFSTfITJ5Q6okRiFGjmSSgdYYCW+U6r2RxmLQ4jvn9Mduf/afdfjOOSWw6LUJqQ9BEFLMOvk45SYFW8Xl+sn6TjeOt9pxNEYfHz5vWHthGbQahi6nF36Oj3n++mVl+KrbBSD2fGTnsTbsqG5BpzNWvglKHpfqDHdekmi6XX5Z2ex2K0v0nWhijS9SJaFeh0N+XtepcF433ok174yVOyIenRrLKznAcfhGRYFsfPjBEoFyHI+mntAcMDw/0NLZ+eDBSeaCTo8f9Z1uFGWaohwtn9xZg5JsM7bsqoE1Zr4lrXjuVYuKxP/PLpDPuaNTq3H3qwfh8XPYfawNG1eUi+f5gv12uVixl4+22tHc40GbwxfaWXtZOdIN8Y2blXoOrwdwFoC9PM9fyBibjZCROG4YY+kIxSz+PgDwPO8D4GOMrQRwQd9pfwLwEYA7AawE8ALP814AJxljtQiFt9gzlPuPN+RWa66pLMLdrx5EpkkHX5DH6V637IrO7DwL1i6dATUDJqXp8NsbKnGkuRcPXTkPP331oHheZDkhtolOrcK/L5mGdKMWP79qHrLTdFHnC7GLI69RWZKJR6+eh8JMI7qcPjj7DMvh28XCPfie31uPr00PrfbIJRX4+4+W4G3atpV08EOwdQhxdSJlRmmsySxztBwatCpkmZTFDM62yJdXGnNYmDBFllcyYQJCWYkjVwM3v38cZ0xRFhYiWbcxxtJVQhyqAqsBK+YXosvlE5O6Rems/HQca7HJv1+9BlefWYRXPg/FXHL7AmIyOdkYzlYDGnvc+Nnl5ahptUOvVqOh0wmjVg2nL4gV8wvFmOpbdtaissSKp69fhE6HF409bkkYG4NWhYZuF66pLEKBVT5m9rLZuZhXmCHufoiMNTXc7atEapFsMiAkvIlqJ5bEJLzx+jlJ/gEVAwwaFbyB1IixSBDjnbx0vWx+AyVJsnLS5PUNzwMWvVr2b1+bPgkzcy1QqxgMOhVqWuwAY32h8KLPn5lrgTcYxOPvHpccjzwvyIXmFdvXLE7x0AOEEoYyL0k01hjzImucRp9EkRtjfJGToPFFvMSakyid1413Ys07T3U6h61ThxISZqAywtib43jJLt9Mkw6eQBAmrQnNPW7ML7LiQGMvCjJMMGhVcMk4QIYcLUMGcMZYVH9474q5yDRpRSckIQ+Rx8+huqk3yt61flmZJOHqkpm5eOWLBmy9/gwEAjxMEX2j3DOqGKBVh2x8j65agF++dxSlkxbEFf6E8Qq0JGPsM57nz2KM7QNwDs/zXsbYPp7nFyq+U/+1FgLYBuAwQl7DnyNkfG7ieT4j7LxunuczGWNbETJK/7nv+LMA3uF5/mWZa68BsAYAiouLz6yvr4+3ekmJkMSp1eaBSaeBLxhEtlmPqdlmcByPz7/qgs/PAYzB4QkgTa/GiXYHCjJMqO9wYmGJFU1dHtzVtxJh0Krw86vmwWrQoMcdwGSrARo1gz/Io83uRY4lZAQ71mxHmkErca8Pd4vfdHk5ijKN+LKhB54Ah+MtPbhozmRJIrDHVy2A2x/Ava9Xy17jwSsq8F71adx83gx87w+fikaiqxYVQa0CZuRa8PO3j6Db5cPb65ag1ebBt3/7r6h39MKacxRvURgDBp3Zj1dZBULyureuHQEO6HL6kWXWQqMCFpfmKDJ6fHSsBV1OH3RqjRhWwRcIIMuswwWz8gctv7+hCzXtTtzzmjQeUVmOGQuKswYtX9Pagy8b7FEJ7c4otqAsL2PQ8kdO9+DQabuk3TywsgLlky2YO3nw8u8fbsG/P/d51PHf3ngmLp47+PPHwZjKaaQxrLLEip8snwO7xw+TTgObx4/TPW5s230ShRl6XHf2VNzzWr/Oum/FXLxf3YJzp2cjK00v+b4bLp6JP/zfKXS7fGJMphk5aTAb1Djd7UKQZ5IY1vevrIAKHCxGPbqdPkmc9vBrCbpKMAJXllix4ZJZaOr2RIWgeH5vPe765mwsmGJF9Wn7gEa/unYHLt3ycVSnHhlyghAZdzo1cksbEEp8+Yfvn50QGTjR1oPP66P13pklFkzPzRjz+rx/uAX3vV4tJt7geeBvXzTi/pXlI60HR5pxJ6vEuGVYsspxPHYdaxUTBan6EuQsnZUnGeuFz2EKrAbwPNBqd8Hp5bG/sQccD+w90Y7/OH8GbN4ACtL1qO9yY9Ob0j776Q9rxLwCP79yHnLSdTjR6oQ3EITZoJUkPLp3xVxMn2SGyxfAodN2TJtkRrfLC41KhfvDzguPZfzXfz8H3S5/0izYERKGLavJtBgbL/9X2wanj4Ovb5ec2aCBTqOCWafCv81QEG8vwRxp7sHBxujxxbwiC+YUZCS6eoNyqKkHn5zolMR33XDxTHxtejYqCjMiTx9QoFK1/w/X44Ml6xTObenxACrgUGMPbN4g3tzfhDuXz8HcAguae0P9QSDIo6Fvl3teuh7FWdLr+nxB/P1Qs8SGNVDb5TgeJ9odONHugFGrhk7DcKLNgcmZRhRnmtFic4MHQ4/Lj2OtdrzyeWgH6A2LSySG2l9cNQ8dDi8CQaB8cjo4cPi8PtRfAcDuY224YHYuZuZaUNNmR366Hj3uAIqzTOABfNXlEm1dt100E3/5tB73r6zAkWYb3L4gDFo1nttTj6sWFaE404imXjc+OtqGH14wHUdbQnGN0/Rq8DygVjFsfv+4JOdOpkmHH/zb1KiYw2adGoWZRvS4/Xj83eNo7vXgD9+vxIWz8yJfVUw5Vbrk0dgXJ/g1AO8zxroBnB6wRGw0ABYB+BHP8/9ijD2JvhASMZCrvKxFm+f5bQgZnlFZWZmCa4PRyHVoQizMe1fMBc8DzT1ueAJclIC09rrx1oHTyLfqoFYxiQeOigGb3joMX4DHbRfNQJBnkoHYAysrUJhlwkN/D8UmLs0x42iLXWIo2fhGNdacX4otO2vFelWdasevvnsmvmzohk6twukeFwoyjNi8egFcviAa+hqLcI17XjuEbTdUoq7djo2XlWPTm9UAQkmgirNM+KrLCZ2GSbZjj4eV/fEoqwINXQ581e2JSig3ucuBqZMGz5ZZYDWgzebH3a/ulwwiChQmXrAYVNCppR5nOrUKFoOyuL12DweDFth2w5nodvmRadKix+WF3aPMY83j5+D2BST3d/sC8PqVlbcY5D0E4t0WMhKMpJyGryz3uHyo63Dijpf3RyXv+8VV8+D2c3hq13ExgcHs/HT8/p8nsLqyGFNzTDjeIk34pu/bb5pp0onB+sP15b6vOrHthkq02jwozjKhx+2DCgxfdbvw6LvSOGKb3w9lN3d4Anjw70dEXVVgNWDp7Hzc9Mcq/NdFZeL9eR54fm89dBoGjYrhlS+acM60LLyzbgla7aEkN2oV8K+TneKAKvUzZycfqaZTO51e2cSVXU5vQmTAGwBy0rUSvRfkOSiMxjPiWI1a2djpGcbU8JQaiFSTVWLiMpCsqlQMS2floXRSWsxdSpGJaP/z66UAAK1GLc45SrKNWHthGX70wpeiLrz7m7Px1HVn4EiLHaWTzHjsvaOo73QDCPWVd716EL+54Uz8/pOT8AV43HhuCR5btQBuXwBTJ5lxrMWO4612PByWAGvd0jLsOtqEP3z/LHzV5YJRp0FTTyjkhDCPOGdadtLtuiKUMZCsnuxwyu46nfWjJZL42MlKfrpOdvF2uoI5VTLg9cvPq7y+1NgJ5A9yKMowSnLBqAAEFCYaDycV+/94Fldi2a3e3N+EdctmwqxXYfmTH8smF1+/rAxleWniAmMgwOHdIy1ot3tE/Z5nNeDcqdkxDcPvHGrBj1/aJ7lmvtUAj5/Dzc99FjXuvmv5bOSmG3CkxYZblpSKxuLmXo9Yt5JsI3749RmSeMMbLyvHr/8RCntZkm3Ej5bOxJM7/z973x4fRXW+/8zs/Z5kcyUhCSEbCEkIl4iXAhWCFG24KBf9abEqfqktGBS1VCsiF21RxIJQLWpVbFVUrApVtAKKVqwGlEu4JCGQkJB7Nnu/z/z+2MxkZ3c2bEggWZjn8/EjO9kzc3bmzHvO+573fZ7jiFVKMbcoDYNjlfjVNen4x3e1eP6LCrxw22gcO2dGsk7OBq0T1FJs3luFxZOzUV7XgUd+MRznTA4YEjV449tqzB4zGLFKKcupH6jXkxajQIxSioen5kArlyBBI8PZdjtiVVKIRQTe+O8ZlnM4Pa5ntJIRBYdpmr65859PEgSxF4AOwK4eXakLdQDqaJpm0j/fhz843EQQRApN0w0EQaQAaA74/uCA9mm48MB0VIGiaByp78CJgAHbYHKywgyH60zsd4NFFt75oRaPTB2OhROHIkEjw++3H2IXVoB/IfTsnELUtNmglEpCxB+Wf3QU6+YUoqbNgXWfV2D5L3OxcTdXdMLpoSAmSfbfG/dU4m/zx+I3bx5ATqIa912fjRONZpxssmLHoXosnDgU75XVscEWpl2LxQmVXIpX9p3CxttGw+TwcLLy1s4eiam5fkORHqvEmln5IVmh6bHKi/YcBPQMTUGCcoBfUC5TX4jMCJK7TXYfuwACugTEIhUuaLX58PvthznBN7mExNZ7xiErgvYurw/1HS78fjs3Yz4hwg0Ii8uLV/97mkNy/+p/T7PCZueDRi7iLdVUy6Kfap0RPPj+dBse/9AvPBcs3lfdamPtWaCAwfq5hbC4vPD5gDX/Ph7yfBeM9z/dYE4oxl4ufLMMC8Zn4azRzm5orZ9XyBmnjI11eSmoZGI8dlMuSAI4a7TD6+sqQXrj2xrOLnOGXoH7JmZj6XuHOHbrl/kp+Px4U8iCakQn11S0b3IJuHBIRVzBNcAvuPazbH2/9Mfq8mHznirceV0WnG4fTASBN76txu+n5fZLfxI1Miy9ISckUydaylAFCLgScD6xtUAxoVvGpKG1k6Mz0GcpGZmKTXsrObbw1f+exsxRqfBRwIkmC8d/YaoLO2we/OHGXDSbnPjTrq4g8OqZ+aBpmg0MA11rgSXFBhypN/FmW4lIQTzuckVNu413Qz5YPHGgos0a3i8aOvATh2F2erF1fw1nfbF1fw1Ki3P6u2sRQSIiUdNuD/HL0vUDJ/bQk8zenrYPtOOM/T3RaEZqjAIFqTrOdYIF5AL9sD/+6wgWTsxi54NAfy1WKYXD40Ob1Y0j9SYUpOpwosmMOqMj5L7rVVK+jG2cabOxgWHm2ht2V2LhxCzkJGpQMjI1hErC7vHhwaBANkFwfcmSkansZiZz3pU7ylmR1JKRqXj8Qz+da3AGMlOdYnJ6Qn7HvROG4JzJiXiVBINjU/B/b5axPuUTJXk41WxFWqyS1bMB/EHrjbv9AeVaowOb9nT5yevmFEIiJnCq2YaJwxIxaXgicpO1GBLfx8FhgiBIAIdpms4HAJqmv+rRFYJA03QjQRBnCYIYRtP0SQDF8FNMHAPwawB/7vz/R51NPgbwFkEQ6wEMAmAA8H1v+jBQEVx6dazBErLzwpQ/MUEnBoGTXopOjluL0tmAb3Bb5vuVzRYMjlWyfL+BcHoo2NxdKUOJnfwtsUopW+YpIoCCNC0WTcpmF3QeH4XHbhoOlUwS0vct+05hblEaJ8gsl5BI1MphdngwcVgiXF4qRNF02fbDKEjVIStBjVqjHS/sqeQomL+wpxKGRDXsbt8FGUQBfYsOh4c3I64jQuGE3gojNZldnHEK+IN+kQofeClg9/FGPDOnEA6XF0qZGG98W42CVF1E7Sma5v39VIREZ043BZVUxMmMVUlFIfckmsGI/vER6ocTjTnRKYRZWpzN+/f0WAX7b2bxwjx/tcx//0QkwGz0xyqlMDm8ePUb7k7w3hMNMNs9eDyITidDr2Sv22By4s3varBgfBaGJ2ugVYg5yuuM3crUK8NypG+6fTRbjuu3pbp+Fw0UcOng9lGYf00mq4Atl5B4eOowuC8gE6Uv4PR4MbcoHb8PWDesnJEHp6d/UofT41TISlBx7GBWgqrHGRACBAjoPwRWyTB+i1om4gSCEzXSkDXT8pIR8FEUmi1ujnZJik6Ou67LxPNfcIO7gWKwyz86ir/NH4t7J2QhViFBWpwSHTY3lJ28ofe//WNI8GDxpGw0mp3n5WW8mAEYARcPvdUC6W8MNMHYnoIgaN71RbQMfZvLxytGNiY9tp975kdvaVPO156x4yk6OSf4uWVfdch1wlVGMv4eE7sK9P+Cz8tcP04l4b3v4fzxcNemaMDm9ob4nMEBaiaQ/eycQs73mHZ8vmXg328Zk4aNeyo5MQiX14e7r8uAXCxCbKf20S1j0uDw+ECSJEgAKTFKLHijjL3GrUXpWPTWQc4cF1h1z3ALB7oLTg8Ft4/COZOLs/n59M0FoCi6R/PMeeusaZqmABwiCCI94rOeH/cD+CdBEIcBjALwNPxB4RsIgqgEcEPnZ9A0XQ7gXfiDx7sALKJp2teHfRkQYF7MmzZ+jf/38v/wwY/1vDsvt4xJg1xCQi72k02nxyowPJmreMgMTr62DBgRhjqjHSo5v+KwKmDSrO+w49Fpw3HntV3q4X/bV41msws7D9dj+4E6kARgdfowNEGNP3ZywwRev2RkKtLjlOy1WO5PgsYzn53Apj1VqGnj392tabOBomg0mZ2oaXNg894qbNpThc17/Sn9u0804/+9/D/ctPFrlmhcQP8gTinhHX9xysjKgRlhpEDIJZELI6XGyPHbn2exytYiAvjtz7MwSBtpViaF2WP9i5hlHxzBI+8fwuyx6aARWdBGKRXz/v5IF6Htdjde/KqaNfo+Cnjxq2q02y8fVdzAZxz8rBlHMBCMvQL8zmXg31N0cpQWZwMEoJSJkaFXYP41GRwFWp1CisduHIacRA2UUhIpOjnuuDqddyf4ruuGsoFh5viG3ZUgQHCu22By4tVvqlHTZsOBGiOv3TprdODeCVkcShSnh4LR7oLbS2PLvi5b6vYKNutKgkxMsoFhwD8u1n1+EjJxZPQ3fQ2FRMxSATH9WfFxORSS/nGemZL1WaNSMT5bj1mjUkO4TAUIENC/8HopHDprxK6jDTh0tgPeIMFIRhiIgVYmglYu4czPCokY28pqObZn9c5jGBSjhFYmQrpeiaU35EAuIXHH1elsYJj5LqMCD/jXAwvGZ6Gx04ne+t0ZVLdY8ZfdlXjk/UPwUTQWjM/C4snZWDw5Gymd5cYAzlu5E+yn9dTf6G17ARcORjwxcN0ZqXjiQEBv/aL+hkLMv76Qi6OjIjJcEp3d3U+8W0Hgy9Zd+u5PONNm65P2jB3niy8FXyfY5gNdYqNMUDPwOMAft1r67k+gwthrs9OLH860obrFyrGf4a7tT7ISc64JgDdByR9MprGkOJvjuxVl6LC8ZAQbW9hxqB5auQTLpg3DsCR/HI4gwGYPB8bKYlQyvP5tNe6bmIW7rsvEq99UY+PuKjz83iHEKKWwOLrGF9+92LC7slPw3O/vrpmVj5GpOnxd0cz2Ty4hoZGJQwTtH/vXEZQ3dDENRIJIV/0pAMoJgvgeADsCaJqe0aOrdbX7CUARz5+Kw3z/KQBPXci1BhK62zGuabOhrt2GZ+cUwu7ygiQJ3gErIoEHp+RAISHZzOCiDB1Wz8xnM251chFvqbSi84XI0CuwZlY+AL+AnU4pxp9uKcCjH3SRfa+amQ+VnMSS4my8W1YHh9sHmg4t2V7xcTkWT8oGSRDsYA6X2aeQkEjWyvHUrHzEqaSobLLg+f9UwGh3o3SyAbuONmBogpp3d/fHsx1weCj2BQz+OxM4YgzKcEHYqVfoTXaDyeHhzdw1RZg5LCYpPDO7AFUtNjarcmiCCmJRhAvwMBm6FD9VeQjkYjFW7jgYEjR8854IaS2s/Dv8bdbIdvgvZ65NZlzRNI3n5haitt2O1TPzUWe0492yOhjtbmToFfjrHWPw01k/8f+OQ/X43c+HosXqxtIbcjAiRYO/zR+LAzVGyMT+yZApH2VKcZgdV6Dr+S2cmIXFb//IZnInamX8z8nG//yqW21YXjKCI3qzpNjg/11efi704w0WvPpNNadyQy4hIRGRvAsxwW5dOWgyhckEMrn85FmXGG02N6/dbrP136aUUOItQMDAhddL4cND9SE0b7MKUyHu3OTK1Kuwft4orN11HHIxCUOyFk9+fJTjo2za608e2by3ipOZ5fT4MDRRjRe/rMId12Ri4cQsZOhVvHZTJiZ5s89KJxvwzg+1uGVMGj44WId2m5tTLcRouOQN0iJNp0B1izXsujdcACXSebu37QVcONLjVDAkqTmVKIYkddRUosjEwCt3joGIFKHF4kKCRgYf5YMsStyCVpub971t7cf1RU8Qr5HxrvH1Kmk/9qoLvdUxOV97xo5Xt1h514lN5q7rMN/l08p6+uYCiEX+RJvtB+pYCsVwQdrWMPa6ps2G8nNmvPoNN3M5U6/Cc3NHcTiHV0zPQ6xSArVMjGSNFA9OyWE3GEWEPyYWLAwdo5RgUIwCz8wZib9/XY3vTrXgtnGZLHf+3KI0LJ5kQJvVhaEJalS3WrFieh4aTQ5/hXxQcPeJj/xzXpvdHUID+8TH5Xj5ziJ2fMnEJO+9yNSr8OAUA54I0HNifNDrhydiaIIaOqUEOYlqHK43c9o2mpwoHIyIEWlweGXkpxTAh+5S9gHg6DkzfDTwSGfAd0lxNq8hmpAdDx9N467XfmD/dnVWAjbt9ZdFDY5VwEsD6784wrv42TJ/DGxuH47WmzncJ0/fXIDX7ipCs8UNvUqKrfurMWqwHv+tasHqWflwuL1hy70T1DKsCMjAYzL7gvs+IkWLe7eWsdd8cEoO7rw2Aza3Dy6vD4smG/D0J8dQOtkQUl62aU8VjHY33r/vWjx9cwEe+xf39735XQ2nT4Kw04Wjt+UpsSoJL8l8bISZwwqpBG6fk0P8vmZWfsQZbD6Khs3t47RfUmyAL8LsjJYwwd2WCIO7ejX/IiJOFdkO/+XKtRksTHP3zzI5Y2TNrHyICRpuCvjdP7vKaVZMz4NCJsKmHdyg7HudweTAktKaNgeON5jD7AR3/XvjnkpsmT+W9zmpOrOPgznavRQFs8PDobTZur8Gs8emYfuBOs6Cg7Fvr397hr3egvFZ7ELG7vb1aiEnIPohl4p4x59c2j+ZNLHK3tntiwGhBFuAgIGL8gYTGxgG/HPY4x8ehSFRjcLB/nJrkiQwNTcJHp+faumRqcN4abfEJH9p8eqZ+Vg4MRsauQg6hQQiguC1m7nJGo79YvqzMYCG7pYxaVjVubkb+Pf180bh7e/PgCAIHKw1spvSS4pzMCY9BulxKk5pdSD6MgAjQEA4aGUinGy0hwjSFWVEh1+glvHTeqhl0UHr4fL6eNf4/UUDFgwmYzb4/kaqY3K+9oyg+JG6DohIImSdqJH7nyOzZkvQSPHuwmtw1uiARi6G0e7GI1OHw+72YMdPjXh+3igcb/QHMJcUGzAiRct7/apma4i9fn7eKKzaeQyzx6bxbrDJJARnE8jj9WHljkrWXxwcp8Dz80ahpt2OcUNikBqjDHqv8vDC7gqU1ZjY9yxBI8Vv/3mQl1N41Yw8KKUiyMQEVFIRErRyXjvP0Crx/c3i9GBJsX8j05DInySpV0tD6Avf+aEW90/OweMfdsXEVkzPA/5XwwaI5RISybqe6dlEVL9I0/RXfP/16EqXMSiKRnWLFftPtYakuDMIt2P8w5l2HKnvQGWzhbOoebesLqQEZtXMfDz8/iF8U9XGGTQEAVY4rqLZxkvpsGxaLp7cUQ65RITTrbaQBdRj/zqCFqsHS975CfduLYMhKQYb91TiNxOzUd1sAUAgRiHhTddXysSc/mw/UIfSydy+P3VzAVbu5JaUPP9FBRweH5t2b7K74fbSLJfn4snZWDA+Cxanh+US+/xYE5797CQWTszCpttHY9v/XYNtZbUckbueGEQBoehteQpFhWaYb9hdiUgr5ywOH6/DYXFGxibj8dG81/f4IuuAXsVfvqWPMLjr8XmxoiSPM/5XlOTBS0XW//Q4FYYlq7FuTiHW3lKAdXMLMSw5ejIcwiFYmCa49OXxD48iUafEEx+FUj0ELxCYMtLAfzNweqmwJU3sdzwUnF4Ky0tGcJ5T6WQDVu4ox5PTuc9veckIGBLVeOeHWg6ljdHuZs+rkJD+7OTJ2Vg4MQvyAHoAp4fCyFQtPimdgGl5yWFLnwS7deUgVinhLXPtr2AsSRC8dpMk+icYK5RgCxAwsHHOxB/sDFyPA0Ct0Y5lnSLB2UlqXtqtEak63oyr5R8dxaE6E+5+vQw/ne2A00vx2s3TrVbkpmh5+zM0QYVhSZqwGVm17Xb8fFgy7vvHAWzc7ae6uLUoHRt2V+DTo42s3entvC3M+/2HM202LH7rR2zc7V+/bdxdhcVv/RixX9PfaLHxC9K12qKDZVPW+Z4Gv7cySf/QaPUUepUMb33PjU289X1NxEk/FxtMtm7g/V0/b1TEOibpsUqsmZXPab9mVj7SY7sE90iSgMtH8a4THW4fZ81W+vZPaLG6UNtux8I3D2DJO4fw8PuH0Gbz4LarM/Dguz9h4+4qrN11Emt3ncQTHx/F2tkjQ/yu98rqOP10eihUNls5vhezwQbwv+dPf3qC4y9WNFnhpWh4fRRcHprnvSrH1VkJAZ+PwuWlWN81JCv443Jk6FXYsLsST396Euc6HGF90HC0iRTlTzZ6aOpw/HnX8ZAY2ppZ+TjJk/jECOEF+8wLJw5l2y4pNkDcw6SKiLZsCIK4BsALAHIBSAGIANhomtb26GqXISLNsgy3Y/x1VStInt2EBpMTW/fX4MU7xuBAbQdykjR47vMTbDYb364CszPBd52qZitq2hxo6HCG3blwe33sv5nzeHwUBsepcLzRDKVUxMloZEq4/bsxfvqJBpMTDSYntpXV4pk5hahosoAkAK1czMnEY64jJkn230987C/93ri7ii2pl0tILJ6Uzf7bR3UpNcolJHYtmYBl03JD7r8g7HTh6G12Q6OZP/O20RxZ5m1zLzN3rS4vb9mLzRUZN5TD4w3JXi+dbIAjQmEmmiZwqrkDr989Di0WJxI1cvynvB5pcSkRtQcAm4viCEqunzcq4rYDFcHCNLxjLMzYCY4HMTYq+N+AP+MnkGaHmRy37u+qLpBLSJxqtmJ4spojPPjyvlOoaXPA7PTg5TuL8L/T7SAJIF4tw8v7qrBw4tAQWomt+2swtyiNo4zOXINRspVLSBiSNN2WXQl268pCtl6N6hYbJ8MhNUaBbH3/ZJA1WXon5NnXEEqwBQgY2FCHEflSBWUDBs79LWGEtU42WJCTqAmbcRWrlMKQqIHF6cHW/TW8FTzNZj9tU7BwdoJGivJ6M0ak8NPSDYpRsEJZzDWZjOM4pZS1O72dt4V5v/8Q7VnbTWHWxk0R+lX9DZvLA71SgnVzCmFzeaGSi2F3eiL2y/obmXrVgI41MJm9w0snoLnT7+xJpVWt0Y4XAqosaBp4YY9fcC/w/bA6+bmXrS5vSAKQw80fSP7r7WNCzlHT5kBqjByfdPafAIEfzxphDNLaYao4AyvGAzfYuhPDY/5N0UBlswXpccqw81GgTxmrlEIqIiGXkGF91wM1RtxalI43v6vBZ0cbsX7eKJxoNLNVKAsnDsWWfadwz3VDQjLQlxQb0G53YW5RGhwuL2raHGySJPMs2q0umF2+kPlLRPL3hwaNxZOz2fkxK16FvNSYkOceDpHm828CcBuA9+DnCr4TgCHiq1zGiNSBCZeyT9MABXDUeBkY7W6UnzNj054qLJ6czQZXtx+o43Bf7jhUjxUleVi5s5w9b/B1XJ3ZdEqZmPdacgmJGKUUKTo5pGICeSlarJs7EiqZGCcbzWwJ96PThuOF20bD4fHC7QOvmqLR7sZtV6XjT58ch9HuxsoZeTjVbOW9ZnaiGik6OZsZzAjWBZ6T+S4ffUSj2dkrgyggFL0vT+GnVYhUOCE5TPvECNvHqcOUR6siy8iTiklsK6vlGOZtZbX4080FEbXXq6TISY7FXa99z15/1Yx8xEV4/cs1KKIMciT5nnG8Wsp7PPh1DswEDvy7XELid9dnY9sP/olVRAKj02Ngd/nYRQZTqpqhV6DO6AyhqDE5PTjVYoNGJsErX/v5gp/8uBwNJiemjEjGgvFZGJmqRXaiBiQBDI5ThhWrIAj+HfzeLuQERD9Otliwdf9p3HldFhxuLxRSMbZ+W40MvZItyb6UGKST89rNlB6Wo/UVot2ZFyDgcodSJmI5IwNthlLCpcYJXFPKxPx0Ou12Dzw+ivdveSlaaH+WiUfeP4R7J2TxajKQBNBsceHRacNh9/g4fVJKc/D2D7VY8LMheOrmAra6kpnzGzvsvLZGRIKtjGTsTm/mbWHe7z/01q/pb4T1q6JEUE8jl6CiyYYnAujhlt6Qg6GJ0UErwdDjbFt4DRpMTqToFMhL0Q6od7c3Gg1NZj8tX6BdBRCy3uqOezk4ASisiJ8nNMgpl/ipF5n+V7dY8fb3tSGJWmtmFSA1Ro4/fHCY1XBh/CuKokP8TObcwf6ijwLOtttRlBnH+/1hSRosnpyN7QfqMLcoDX/9shLLS0awG5DB35eKSGzcU4klxQbQNDibCGtmFQC0Dw9NHY4/fXIcUjHRGUfzIUYpwZk2GyQkiS37qnHvhCzIJSQaTE5OkuSC8Vn44GBdyP3IDUPHEa+W4elPTrD36KLQSgAATdNVAEQ0Tftomn4NwPU9utJliu4cmEDwpfyXTjbgg4N12H6gDnFKaUjJxSO/GIZ//q+WPQfztwaTE9u+r8Xm28egtDgbJSNTsf1gLdbPGwW9UoKnbi4Iuc7Ow/UonWzAy/tO8V7rsRuHo7rZgoem5mBFSR7+vOs4Hn7vMH7zjwPw0cB9E7MQq5Ti79+eRofDg6oWW0gq+4bdlfjjTblspu/ssWlY2Nnujf01IWnyq2fm4+/fnGJLwuUSEo0mJ6dsg9nxeP++a0EQ/nP+4cZheHhqDkqLs1ke2qwENa7JikdWgnpAGetoRG/LU/QqEVbN4JanrJqRjzh1ZFyaPorGI78YFvIuhBOaCwYJMkx5dGTmTiIisOj6bFZp9NVvqrHo+mxIxJGNK5vLh81fVrLj+N4JWdj8ZSXsrsjKvyK1KdEGiu6icdh+oI5VHwc6qTem50EiJkJs05pZ+cjrzPhhji0vGQGNXIQMvaJToFOExZOzsfG20Wi3uXHN0AQQBPBeWR1++4+D0MrF+P0vhmHdnJFYODEL6/9TgW+q2tjAMMCl4HmvrA52jw8LxmdxhOS8PhoiEpCI/TvIGXoVbspPwfBkLW+p0ITseJZKItguMQs5wW5dmWgwOVHf4cLJRgvOGh2oaLKgvsOFRlP/vOcEwU8H1E+sEkjSypGhV2DRpGxWqTpDr+hXZz4SCjEBAq4UKKUkBsXIOXRKg2LkUMq4c2HgmvKDA2exemY+r48Sq5SE/G3ljDxIxQSsLi8emGJAjEKMNbPyWSV5JiCdoVfivQNnYXF5Q+zY819UYO7YwXj60xNI1cmweFI2Souz8eY943Dt0DiMzYjjnb9zk7WoM9o5QcTeztvCvN8/6K1f09/QKURYNSMvyK/Kg07RPxoFPYWPQgiV3Pr/VCBCtr9+B0XR+OxYE27d8h3u+8dB3LplPz471nTZrAEipbxhuJcDxyHDvRx8DqPdzXtOKRlKMbJmVj6MNjfOtPrXVUymNpOoVVqcjS3zizCrcBCuHqLHa3eNwzsLr2b9KwDYVd6I0ncOhsSalhT7Y23Mv/VKKT44WIe9J5qhkfmDt8Hff/qT43jl62rceW0GRg3WYfLwZGzZdwojBulC6AiXFBsgIgk4PRSG6FUhtBOPf3gEeo0cLrcXT83Kx7JpudAoRDA7PVj45gGYHV6s7Ez2DEfLuvNwPRpMTjaj+JnZBVg4MQvvfl8b0p8Hp+TgRIMZy0tykaFX4OmbC5CXouvReIh0y8ZOEIQUwCGCIJ4B0AAgOizqRUaku5GBO8Y1bTb8eLaDDToAwN+/PY3Nt4/BmPRY2N1eDI5V4ky7jc1223GonrPjXdFshcvrw4gULY41mHF1VgLW7jqOhROH4n+nmvHiHWNQfs6MdL0KjR12/GFaLl78sgqH683Qq5pxz/ghbHmHze2FTinB09tPcHbTmf6980MtHpk6HA8UG6CUibHu8xOYXpjKG8A60WTBpj3cnadNt4+G0e7GrqMNbKq9j/IrFN9alA6SZIxDAV7YUxEiBJWdqMHJJj8nc6xSijuvzcCmvVVweihs2VfdI7E0AedHb7MbRKQYOqXIP77cXqikYkjEgJiMzNx4KR/ilFJOuXWcUgovFRnxfzhBudYIaSnEBAmnx8e5vtPjgzjC4LLR7uEVXDE6PBG1T9Tw25QEdXRkOPCBomjUtjuwZd8pLBifhXiVBIlaeYhowP+qjfjiWCPHTrywpxK3j8vAYzcOh1YhRXWrFZv2VEEqJvDk9HxUNllgc/vw3akWZMQpORlDjB37ocaI7EQNp3Q0HL1OVSeflUxEclRy/UFokqWPYJyLaXnJKEjV8ZaLXpUZJ9glAbxIi1Xg7p9lhghPpsYq+qU/DWH4Q/srWJ0eq8T9kw0s/zzjQARy4F1K9FaoVYCAyw2GBC1q2x3ISdQErPUIGBK4jIPMmjJt4TUwOb1oszjw/LxRONVi5fgoCRopHnrvEFu1JReTcHl8WPTWj+zaf93nXfZy9cx8xCgloGjA4nDhyRn5aA6zuZ6slSNWKUW73YP3DpzFrUXpePj9Q7h/sgHvfF/DK4Rtcbjxzg+1URVEFMCPaM/abjA5IZeS2DJ/LIx2D2KVEnQ43GgwuTAsub97d36029y872W7zR2mxcBCdYsVD73Hreh86L2fMCxpPLKTNP3cu94jUsqbQO5lprL2re9rcMOIJM45th+ow6M3DgsRV3946jBQ8AfUH56agxiFFLVGO577vIIVjEuPUyJvkBZTc5MwPFnD+74GZ0hXt1jZvjMBVBEJXJUZh9MtVjx2Uy4IAGeNdry0rxoJaimWTDGgvMHK+qUiEshN1uLFL6vY2NyG3ZV4eX4ROzccqTdh+4G6EFqj/zcuHRl6BVw+ip92w+mFWiHByp3lqGlzsEHlnEQ1kgIE7AIDwOlxCtR3OKCWidi1cIPJiVe/qcaaWfl4r6wO86/J4PR/ZFoMXB4vXF4fTjRacN/Ps6GSiXq8iRFpcHg+/FnGiwA8CCANwOweXekyRU84pJgd40y9Cg4PxSlzXjYtFyNSdJyJKitBzfKvJGrksLu8WDgxC0qpCLkpWhypM4EgAIVEBKnIv1CyuryYd1UmfvXq/0KCSwsnZuFwvRmzxw7G/wUoHi6alI1nPjvJMXrbymrx5Iw8eH0UaBqoM9rxRidlROlkA2jQEZd/J6ilWDMrH7Xtdk65PABs3FOJv80fi4UTszA8Wc3rDJIEODw2wVkBl0PJ/UBD78pTXFjyzqGQsfHG3eOQGX/+80lEYjz6r4Mh7bfeMy6i6+sU/GUlWnlk5s7i8vLyx26ZPzbC60t4BVfeuDuy/otI8JZqiqJDt4EXZ9psrCDN5r1VWDQpG2sDbA7gv8fPzinE9cMTQ+zE819U4Jk5hWxwN0Unx61F6fjtPw8gVinF3KI03HntEHTY3Vg8KRtOr7/ttrJazC1Kg48CHDwlTnzjxEtReHBKDsu/JSKBsRmxcHooLHnnx7C2J5odDwGXHjKxiDeTZtKw8f3Sn3h1mHJBdf+UrdYa7bzCpMEceJcKlyvdjwABFwqxmMQkQyIOnzOh0exEilaOgkE6iMWhixWSJODwUDh+zozsRDV+91boGu+lX43llDYvmzYMrTY37p2QhWFJGqz7/ATn/du0txKrZxbgcF0Hhiao8eTHRzG9MJXXjtUa7ZhblIaaNjuW/WI4Vv/7OBpMTjz+4VG2QoiZ78cPjYdSJoLT48Nrd40T5vLLBL3xa/obMrEYz31+DCUjU9lqnh2H6vHnW0b2b8ciRJyKnzIuTiXtx15FjtNtNt6g3+k224APDlMUjTNtNjSZnUjS8vsmkW6edMe9HHwOhViERpMTz84phN3lRYvVhTe/O4OnZhVgw26/f8Vs9jHYsLsSCydm4WSTBcOTtZiWlxzR+xpYcRtIybBl/ljolFKs+/wEm7QVq5Ti1nHpOFRnwpZ91axfCgAZegUemjocFU0WAH4a14agDUc+WqOseBWenJGPn2qNvOP8RKMVr35TzUm83LC7Es/MKcSpZgunDRMADtSs2brgKmy4bTQkJAGnxweCAO6+LgPrv6jk9J+J9Y0aHIN4p69TnC4LepUMRZlx572PDLqNlhAEMRNAGk3Tmzs/fwUgEQANYD+Aqm6aXxG4kN3ISNrwvcyfH2tkdwp+0xncZTLaxCSBhZ3HSouzeY1YbrIWiydnw0vRnL8HE2yn6OS457ohqG6xcgJUK6bnweRww+H2Qa+Shuy0L70hB/oAzlBm993k8OKFPZVYPMnA268jdSbIxSJ02N28hOgrpuex7cIKWQk8hH2KSCaTcLC7+XmGIhV0Cye80Byh8IJGJsbKGXlY8XE5Ow5XzsiDJsLgsMPj471+8LFwMDs9vO3NEWYOM2KUwTuTo9NjIgquD0QEU2VoOnn8AuH0UKjvsGNwrJJ//ASMK0YxNlYpxfxrMth/B1YVMLYxb5AGP501ISXGX6YeyN0eHIRfNTMfbVYXXv/2DBpMThyuNwMAFk/OZvsR3C/G9kSz4yHg0qPOyM9zWWe0w9APzoaP8vHaTR/VP2roA41zeKD1R4CA/gZF0fjiZHPE2fQ2txceioLNzb/Gcri7uChHpmoRr5ZxhGUDHWtmg3jhm2Wcv+862sArKPzmdzV4aGoOnvu8Ag9MMXCuSxDcgMJ1Q/XI74F4jwABFxsOj5e3IjFSv6q/4fR4WW0kNqZQkgdnlPRfLuHnSpdLBjatR08qniLxYc4Xvwo8R02bFRqFFI8EiKuvmJ6HNosDz8wpBEXRuHdClj8A25mp6/R0CZD3ZPM9XBV/dqI/ITN/kA5VLRasm1MImYTE/W//iHsnZIXEvm4tSmeTkJjELJ1Cwp6boX0Ifg/lUhJGmxvvloX+fXnJCGzaU8UmijFBX6eHgsPl5W0TqLEVq5Si0eRCvdHB8VfXzCpATqKa9VMD799PZzswPEnDfm4096wC8HzRkt/DL0THQAZgLAA1gNcAvN+jq12muJCgQHdtwr3M6XEKjmAM0MWntWX+WDwwxQCryweZmGQHcopOjjuuTkeCRgaVTAStTAStQoTS4mz2BVRISM5LdcuYNLTZ3eyOCnOdlTvKsWB8Fl79phrLS0Zg19E6LJyYhfRYJRrNTrz23zO4+7oMdvd9eLIWL31ZhTuuzkBNmwM17Xbelzddr8Jzn59A4eACXkJ0lez8QlbRIioQDeht+axaFkbBWhpZcDac8EJihMILNrcPf/2yihNc/euXVVg7O7Id9lgl/w53jDIyQTlFmEWEQhrZIiJJK+fdmYzmMR48cecO4qqGp+jkmFuUhliFlDMRM5BL/IT6zHFmk4gJEoerKnj+iwosnJiFjbur2MXoS/uqUNPmgNHuhkoqwgu3jcbxRgtGDdaBpmk88dHRkGvTNFhxOT7b05vNFAFXJsLZSbWsfwRaSELEazefmV3YL/0ZaAJCA60/AgT0N0638mfTD7t/AoYmcn0biqIRr5ZBQhIhwrPM/E8QwEu/Gou6dhv0ajkeDDp3oGMdOPcH/z2wLLe23a/8brS70Whywmh3o77DgfnXZLDHA+UshHdawECERsZfkRhpRWV/QyoW4aV93PXFS/si98v6G7FKCW9FZ2yEfmF/4WJUPFEUDYvTgw67B2qZGNUtVrRYXUjSypGmU+B4kxkNJie0CjF+qG7F3+aPRYfdgziVFGaHCxRNorLZAooGRIRf0+qlfdWstgtJANmJGtw7IQstVhevPxXsc6XHKsNW8ZMkgSHxKtR12KCREWix+BO4+GJfwe/Yht2VeHhqDvvsG0xObCvzUw1VNVvh8vor7Z+dUwi5WASj3c3OPwThp0w0Ozyc4DeT+S+XkFDJxZw2DJVEIO3s3KI0VDVbQ2Jyj394BM/PG4VVO4+x32Xun1REwuLysp+TND2rADyfFyKlafpswOdvaJpuB9BOEIRAwHSREO5lfnfhNRikU4TsdNwyJg0NJicy4lR49ZtTmDd2MJ6cnocXv6rC7eMy8PwXXXwvj904HK3WrsAvc2z1zHx2h15EhufjZIIyq3cew7o5hTjeaMFz/6lgX+pBMUroXF7UGh1YvfMYjHY3YtVSlBZnQykV4amb81HTZmeNQoZeiec+P4H7Jxtgc/MrWCZpZBwem2ADLfCB9S16O5l0ODy8u2AdEWbOxin9gnZPfNyVMbJqRj7ilJEFV9usbt5NhjZrZNxWHp8Xq2bk4YmADLpVM/Lg8UWWQaeQ8it4KyLcYe4JVU20IPg3OdxelkOdyfhl7leGXoEV0/OwckfX/V96Qw6e++wke18Bv20IrCQIV1XAbII5PRRW7izHy/OLYHV5O8tGKbywpxIVzVb89fbRIEk/lc3ZdjveLauDVEzg0RtzUdFkhVRE4E83F+DRAKXz9fNGIT1WKXCRCugxbG4vHp46DOs+P8mOm4enDoPN3T+ZNK1WF6/djJSrva8x0OzgQOuPAAH9jZp2/lLr2nYbJzjMJBys3XUcpZNzcNZow6qZ+Xjio6OIVUrx259nodXmxtFzZogIIH+QDkfOmXjPzdBricjwPgpTlrtwYldZbulkA7aV1eKJkhF4YU8VjHY3Fk7MwuBYJTbt7VpTCO+0gIGIcBWJFmdkflV/w+Lw8q4vLI7oyBwenqTF6VYbRyclLVaB4Una8zfuRwRWPDHxIoJA2KDr+eD1UvjwUD0e//BoiO/GVF9u3lvJ8uqumJ6HJz46CreXxm9/noXUWAUqmqycGNSSYgM7B6THKZGkkeF0qw0A8G1VKyxODyYPSwJJEp36NTYcrO1gBcUZuz01N4lDxZoeq2QDyEqpGGfb7MjQq1HdakWGXgG1VMzx1cPNKVq5BGIRiY23jYLXR4MgCPx513H2Nz48dRg+PVyPMZl69nzMvLP0hhy89t8z7PmYZCOmsrXd6sLykhFYvfMYNu+tQoZegfsmZnNoZwfHKlHTzl9peLzRjLlFaWwC1JJiA5J1cni8PsQopXjkF8PYzdie4HzB4djADzRNLw74mNCjKwmIGMzLHPgiKyQkTA4PRCKCkxXMlFQHpuw7vT44PT48MnU4Hg4QYIpVShGnkrHHmPO32ty4LlmDpVMMMLt8yEnSoLLJwhuopQMCLU6vL0Sw6alPjmNuURr7Yjx243B02PzB6FilFHf/LJNjFNbMyse6uYU4fs6MF/ZUhgQV/RnTKqTHqdgyhmStHFNHJKPFKnB7Xgw0mZ2IVUrZsQf4S/AjLZ/VyMXYc6IRz8wphMPlhVImxhvfVmN0+vCIrt9o9uDdshp/e7cXCqkYW7+txqCYYchOOn97vbp33FYKiQROjz1EkE4hiSyjTybuUvBm2g+KkUPGw8PHh2gXzuBD4G9qt7lwtt0BqYjG3++6Ch12D042mhGrlKLB5ERNmwMvfVWFZ+YUoqLJApIAfBSNw/VmtFj9Dl1Bml8xttnsPG9VQWBWkNNDweT04NnPTnBEARbFK9Fu9+LxD49wbKlUTOCBbV3BoIenDsPSKQYYkjTI0KuQqVcJXKQCLggauRh6NVd4U6+WRkx/09ford3saww0OzjQ+iNAQH9DJRUjQ68I4UFVBlWJBc6RjWYH3F4Kg2Pl2HT7GFAUjVMtXcGCDL0Co9NjYUjU8NqjooxYlBZnY3x2PCeTivl7oONNgMaG20ZBKiJR025DychUmJ1dWVypOgUMiSq8dtc44Z0WMKChkUt43zWNbGBnrjJQSHtXUdnfEItJ3JiXgvQ4ExpNTiTr5MhL4edXv5Q4X9UiU/EUSMHn9FB45evqkCSWSCogyxtMrBYEX7XmEx8d5dAmMBXnANBqcyNOJQtp884PtSgtzuGIfS8pNmD7gTpWpC47QY30OBV2lTeips3Gqz31SekEdmPP5HDjm3Y7DtYaQdH+d+X+yTlot/upH5aXjMDSd39CrFLKZvnmJPHPOXUdDk7w9dMjDex7SBLA4DglzE4PHnn/MOd8JAEMTVBxAr1P31yAVosTC8ZnsfSFGXoFtswfi7IaI3wU8Pb3NRy9m+Odm6Z8fZOKSIxM0+HFO8ZApxCjqtmKv3xRgTuuzkBmvAp6VQz+tq8Sf7gxr0fj6nxeyP8Igvg/mqZfDjxIEMRvAHzfoysJiBhJWj83ZjC/EDMomZ0JvhR4hnyaogFzk4WzYzT/mgxUNFt4A8tb9lXjwSk52H6gDgDw259nhWQ/PjglB69/ewZAF03AujmFoAHUtNnw+rdnYLS7cVVGHF74f6MhIoB4jQx3/v171pAEC/A8/uFRvHnPONYoBItCFGXGhVWnDC5bE9A3SNHJQ3YDlxQbkKyNrNROLiYxN4i3Z+WMPCgi3LmyurwoqzGhrOZHznGbK7LMXbmY5OXOjPT6drePV5DulTuLImovIgC5WMRV8BYRPRKUuxz5a5nfBABb9lVhSm4K7nn9B052OVNKU9PmQEWTBZv2+LMMGM7fBpMTG3dXobQ4G++V1eHOazPYXVe+qoIlxQZs3V/D9kEuIVHRZGF5h5myodfvvgpLtv3Aa0sDj637/CS2zC/C+Ox41i4JXKQCLgQ+Cnj0gyMhdqa/ykR7azcvBgaaHRxo/REgoD+RpJHivp9nc6p8VkzPg0xMorrFygYXAufIf3xXi/smZkGvluO3/zyIZ+cUsnM2w/l43z/8QrPB8/nykhE41mDGxt1VSNXKQpJJVs/Mh9Hm4jjecgnJEfZhAhVyCYl6kwNXDYkT3mkBAx5enw+/uz47ZH729pMmQE8hJgne9blYFD0bMWIxicLBsSgc3N898SMSCkim4ulEozkkXhSYxBIpnWSDqcuWh6vWJAj+zxQN2HiEwUtGpuKP/zrC6RsjWLd5bxU27K7EmPRYUDTw929O4Y5rMnmv22R24kSjBWt3HcdvJg7Fqp3HOP7lO9+fwUO/GA6j3Y2qZiucHorDNZ+ik7MVLXw+ZHC/GDwzuwBD49Uh5wOApTfk4NnORDeNXAKNwi/SF5hYuXDiUPhoGokaGdb8+zicHgoVzVYsLxmBmjYbEjopNQMr/JmYnEJCsnpjTAKT20tj/X8q8OIdY9BisWPW6PQeV8OcLzj8IIAPCYK4HcDBzmNj4ecentWjKwWBIAgRgDIA9TRNlxAEEQdgG4BMAGcAzKNp2tj53UcBLADgA1BK0/Rnvbn2QEemXoXVMwtYoQWAOyi37q/BwolZ7GAMRGAZdeBOAxNIvndCFuQSkjew/PwXFVgwPgsfHKyDze1D/iAt/nr7GJidHsSrZTh2zoTZY9Ow41A9Fk4cihe/rMLhejNKi7PZXZVHpw2H1eWF3eXF2Q4HsrzUeQ1Jm83NHg98sUYPjhF28PsBPgohu3Ibdldi6ojkiNq7vDS7gGHar/i4HG/cHVnQQy3jz0ZRySLbYXZ7aV7uzGcj5M60OL28mdMWV2TlTx0OL17++hTuvC4LoP3qnS9/fQoPTY0sc/pyR5PZiTuuGcKKagKhfIKBGb8ZegVykjRsgHjHoXpkJ2owe2wabG4fPj3SwHI1tdvcWDwpG4kaGQbFKNBud3N2bVfPzEer1cWeixFCaDLxiyBSNEKOSUQE7858cJBP4C0U0B16K7zZ13B7abxXVstWbCil/oqP3/8it1/6I0CAgIGNdruHDQwDXZuqiydlY9PeKja4MFgvx7aF17DZuf+tbEKiVg6nh4LdFSo0yzjZjK+TFqOAWi7B3785hauzEpChVyA5VgmR2IUt88eissmKRK0cDR12PP3pSU4fmeBEoKPP/NuQpBYoJK4gRLM2hFgk4vWrtkboV/U7CECvkmDdnEI2acbujg5KjIGKSKoWmYqnYB+F+T6TxBJpBWSKTtGjas1AzRYRARjt7pA2OrmI9deBLr+M+ez0ULC7vWizAfeMH4qTjWbe6yqlItz9+g9YPCmbDQwz7TfuqcQLt43Gc5+d4K06Bfx906skeOPucWgyOxGjlGDZ9iNspQlzrsDgt1zi18MhCYK3T16KQmWzBeOHxuNEoxktVv+9WDk9D0qZGHVGO/518CwWTsxGdqIaf719DKwuL042WbFpTxUrvvrkjDyoZSSenzcKxxvN8FEAARqv/vc05969+d0ZPHZTLp7+xB9kTo1V4Nqs+B7buW6DwzRNNwO4jiCIyQCYnOR/0zS9p0dX4ccSAMcBMIQtfwCwm6bpPxME8YfOz8sIghgBvyheHoBBAL4gCCKHpuno2C67QFjC8AsxfFobd1dh6z1X8Q5GlVSErftr8Lvrh2LpDTlY/58KNjDLKC36qSdCzy8Tk5h/DZf/876J2bh3a5ci8JpZBYhXS/Crq9Ox+atTyE70B25UUhFcPooVkZBLSLx4x5jzGhKNnF+YJz1OWLT1B5pM/JmQTWZnRNnaVhf/2LW6IlsIxKokeGBKDk632lhu6gem5EQsCNdu5+ccZoKE58OgMJnTKRFmTjs8XkwenszJnI4mVeGLCa+XgkREosXCHxgLduIy9Aosut7AuZerZuRj67fVKKsxcbgEb7sqHVaXDyISSItTwun2wub04IXbRuPIOROkIhIiEiGZSDanB4lhRBCD51O5hERS0DgQuEgFXAhSdPxjLilC4c2+htXt4bVbVsGBEyBAAA+arfzzuFhEssGF3NLxKKvp4GQ8rZ6Zj0ExfvvXanOxdjA4gYTxddbeUoC1u47j1qJ07DnRiEWTDOzmslziF5rdcegs/t+4Ibw2daIhHrNHpwIAhidroJSKkaSVIT0ueoKDAnqH3gpt9zeaw20m95MmQE8hExOgQbC0lkzmszSKMocHGiKtWiRJApl6VbdJLJGeKy9FizWz8vH4h0d5qzVXlORh+8FaLJqUDREJjBkcizqjDe+W1WHO2DTEKMX46+1j8FNdByga+O5UC+LUcqz/4ghn3bmtrJYNMjPxIKvLgxONZrxXVhdSNfL0zQVw+yjEKqVI6tx4DP4tZqcH00emYsu+U7jtqvSQTNwlxQY8/mE5jHY3npldAJvbFxI3YPxCRkR1aIIaEjGBz480hGgVLSk2QCUV+atnLE5k6JU42WTl3K+lN+Tg/yYOxakWK975oRYlI1MxPFmDQLaSBpMTL++rwp3XDYG5U7spJ1ENgA5hGCidbEBDhx13XpuBGKUYyVrFBdm3iMjtOoPBfREQBgAQBJEG4JcAngKwtPPwTADXd/77DQBfAljWefwdmqZdAE4TBFEFYByA/X3Vn4GGM202VJyH85chl2aCv7FKKeYWpSFDr0KKTgbpDwS8Pgpysb8c3kfRkEtINJicePO7Gjx2Uy7v+TPjVaxzCPjT/Vfu5O5WPv7hESycmIUUnQJrZxdg2fYjqGlzoLQ4O0RN8ckd5ect+07RynmDK0PiVVG90xutkIj5d8AkEU7i2jDcWFp5ZMFdj5dGo8kZQlifFWGwLUHNH3TRqyMLungpmjdzelxmXETt1VGuKnyxEChk8OycQt5nNGZwDBZP8mf1zh6bhuFJGg5vutND4YmP/e2vGWrB9gN12LinEptvH42qZhtbqrNlXzXWzMqH00P5y3XUUgzWq0KylVfvPIYF47Pwhw8Oh5TUr5ie57ehnf0MF/S9EC5Swa4JkJCdArE2N7sJpldJIe0J/0wfIpwa+ptXuN0SIEAAP+KU/DzluSkaAH4b0mJxsw44c2zT3kqsm1OItbNHoqHDgSdKcrFq53G2ffD5BsUqsGpmPqqbrSgtHhZSVblyZzm2zC/CP76rxlOzCvDHD7mBhkfeP4Rl03IxLS8ZQwT6iCsS0a4NkaSV8fpVSZr+2UzuKXwUwZv5/I8FV/dzz6IXPalaPF8SS6TnEotJzCgYhEy9Co1mJwbp5Pjk/vGoaLbiSL0Zn5c34OYxg7E6gNJhSbEBv/5ZJsSg4aUI/O6tg+zfNt0+Bos7PwNd687n543Cqp3H2MCviATcPn81p9HuZilIGW7fMekxoGhgblEa6ox23t9S024HANS0ObB210mMTNXi+XmjYHF6UNfhwNb9NWymbn2H08+FHBSEXjZtOESEn+ow8DeumpEHrYzEX28fA4+PhkLqF0yvarLixa+q/X2+Z1wIter6/1Rg3ZxCvPNDLS+V7Nb9NTDa3bhn/FCWI/mWMWmIVUlgdnh51+zr5xZi6XuH8PdfR0aFyYf+UT4B/gLg9wA0AceSaJpuAACaphsIgkjsPJ4K4LuA79V1HgsBQRALASwEgPT09D7u8qVDk9mJd3l2RgJLolbPzMfG3RWYPjIVS6cYoJJLOAP1qZsLoJKIcLrNBovTiz/vOs6er8HkxLrPT4QEQ56+uQAEaM4LFY4KIjVGgffKavHQ1OFYPMkAvUoKD0WHfLemzQGb04MF47MgE5MwJKmxpNgAm9sHkgC7q8IXXAEQ1Tu93WEgj1WjwxMy9konG9DhiCyDzB2GG8vjiyzZ3+L04p0fajmlEu/8UIv8QbqI2otI8HJnRkqd2WQJkzltcYZpwUVrmGya1ijZ4Q9EX47TQCGDl/edwoqSPHbjiZlcPRSFTZ1CBoyd47uXJ5sseOXrapanWCIi8fwXoXzmz84pxJ8+PY7HbhoBqYhkS3le3ncKh+vNbLZSTZsDf/2yCuvmFAIEUNFkwcbdlZCKCWy6fQzEBJDeKUDHZ3t6wkUa7RksAxUD2abyocPhhttHczbBHp46DB2OyCoc+r4//BUfpgjtvoDIEW1jVcCVi+7GqtEeZq0YQOUUSBsHgOUVnt+pRcL4HhtvGw2n14enbi5g+SeZTVqKonCgtgOjB8egMkBLhQFT2fb5sVb8siAVz8wpRFWzBT4KrI5BNAUCBVwYuhur0a4NoZCIeP0qhSQ6BN3C+UVtUegX9RZ9Nf/3pGrxfEksaTpFCN/uqpn5SNMpOOehKBpfnGwOuWZusgYPbPsJC8ZnsbEooCu5auHELFxvSMCXlS24d4Kf9337gTocruvgHRdyCYk//jIXFU0WPPvZSRjtbqydPRLfnWph5xyGgnDt7JFspXlOogZPfXI8ZF5aXjICm/ZUYfbYNKTo5CxtZHWrFdmJGvx++xH2+oFCe4E6WDmJGnh8FNpsLqwL0CXyJy2VY92cQtgdHmjlYtz59x9CnkFLmHfA5vaiZGRqSKB3w+5KPDunECcaLahu4XIkJ2lGIFYl5T2fq5POtcXiAkXTF7QhesmDwwRBlABopmn6AEEQ10fShOcYzXMMNE1vAbAFAIqKini/M9BBUTSUUjG7M/K3+WNxoMbIZhPNHpsGkgCkIgLFuclos7thSNTgkaDsuj/+6wjWzSnE4FgljjeaUdPm4Oy00DQQoxDj5flFcHh8EJN+wSy7m+LdcQn+XN/hwOwx6fjDB4dR0+ZgX74MvYIVe2K+OzhOhfWdhiRDr8AfpuWistkKl5fCi19VIydZg8x4dUhwpbrFGtU7vd1hII9VvVKKp8pqOWNlW1ktnps7KqL2ErJ33Fhun4+3VMIdofBCq80Ngqa53FYuD1pskQVd9KowmceqyHbow2UuJ0SYuTyQ0JfjNFDI4HC9Gfi+Bs/MKQQBGlqFBK9/cxrVbTb8bf5YNJtdOGu0o9kSygvFVFAwu6QLJ2bB5AgVOXB6/FxPj/xiGDrsbix558cuh7MkD/i+BhXNVrYao6bNgRNNFkhFJHwU8MAUA2rbHVj+4VE8f2thn9mcaM9gGagYyDaVD0qpGOs+P8kZB+s+P9lvmboqGb+auDJK1MSjCdE2VgVcuehurMYoJdjGs1Z8aOpwNmgQTBvHp3fy2L/81Ygbd1chQ6/AptvHoMPuhlwsgt3lwclGC6trsvn2Mbx2Sibx2y8RSeJEgJgtg2gKBAq4MHQ3Vhmh9+DM22jRhuhwenj9qld6kR14KaFV8NNHquX9laPYf+ir+b+nVYvdJbEcbzJj895Kji3fvLcSw5LUKBwcy34vnP+ybeE1WFJsgMPDpSxlArFD41U43W7nJEOUTjaAJPljTHEqKX77z+84x5dtP4wt84uw/KMjbMC2KCMO12Xp2d+cm6LlzSw2Ozww2t3QykSYf00GJ76wZlYBJ3YVmBQZqIO1eHI2Xvm6Gs/OKeT1N0kSmFWQitOtNt7flBqj5D2ukoohIvkTMU82WfDqN9Uh816z1Y3MeH6qEI3CX719qtWGlKDgfqToj/rFnwGYQRDEGQDvAJhMEMQ/ADQRBJECAJ3/b+78fh2AQG3INADnLl13LwwURaO6xYr9p1pR3WIFFaxsFPSdQ2c78MOZNvy3qhWrdx7Fg1NyYLS78fo3p5Eao8CmvVVYu+skXvm6GgqJyD/IFRJs2VeNk2F20qtbbf7r0GApJTbvrcKmPVV49ZtqUDSB328/jNJ3fkSL1QWxiGQzjBnaih2H6rFqRj77mXmh3yurw8qd5SgZmcpeb/XOY/jDtFzOd1fPzIfZ4cLSKQa8fOdYzByVilU7j2H9fyqweW8VjHZ32Mm5u51eARcPCVopfnd9Nl79ppodK7+7PhuJWmlE7dvtbt7n1h4h569Gzl/erJFFRkuhlUvwxI5jWPz2j1i2/QgWv/0jnthxDNoI29vcHs47wIz5SMUTxCICK0ryOO1XlORFlSpvX4OiaCRoZOw9AfwB4t+/fwgnGq349d9/wN6KVtS0OXCgxgi7yx/Uf7fsLO+z+OBgHQD/2BiaoIZERHDOzXzXRwGgQ8vZVu4sx8KJQznnYrikhsSrsPNwPdptbigkJB6YYgBF0zjTym/HewrBrgkAEJJRB3QJtPYH5CIRlhRz37UlxQbIxUJwWIAAAaFI1spC1oqLJhmQpJHg3/dPwIgUDZRSrl0J5wRTAZu0i986iNOtdnbtlhyjZL+3amc51szi+iQrpudh67fVWF4yAnFqCfIHaXnXAwSIsP6YgMsb6bFK3D/ZwI7VV76uxv2TDUiPVfZ31yKCzcmfAGF3Rof8kkxERv36IpK4zqUGE/C9JiseWQnqC6o+pCgaZqcX0wv9GyfbD9Rh894q1LQ50BggxsbQ4fGNQ0ZArigjln3GKTo55l+TgVe/qUZFs42tCGHabNxTCZoG1swq4IyLZ2aPhNdH494JWVg8ORspOjnbRiIi8Npd4zBpWDyKhydCIiJQa7Szz2JIvD+b2mh3Y/Ne/3suF4vwzg+1eHjqMOQka0PiC49/eIQTuxIR4J0/mKQklVTE+/dUnQK17Ta02Vx4Zs5ILCn29535TRRNYe3skZzfun7eKGgUIhSmxfCec1iSBi/eMQYKCcGdRwnA6aWwvGREiH+8emc5HrtxBN4rq4PNfWFaR5d8y4am6UcBPAoAnZnDD9M0/SuCIJ4F8GsAf+78/0edTT4G8BZBEOvhF6QzAPj+Enc7YlAUjdp2Gw7WduCxgNKo4LJhvtJihoT7nuuGgCQJli6CURB3ur3I0KtgtLtxrsPBSd3n2z3wUv5Sqx2H6kNS7NfMyseLX1axKowrPi7HX24dxZthrFOK8eKv/BnMNN1VpgWAo9rovz6NLfOLUFbTDh8FbNpbid9MHIqMeBV+np0Aj49mCb67K4EAesanI6DvUG90YteRBvxt/lh02D2IUfqzOjP0SqTHnT/rIk7Fz0MXp4osuGwOU95sjrC8uS1c+ZItsvIlrZw/G+a5uYURtdcppNh+0P/OOtxeKKRibP22Gs/MGRVR+8sNjK1rtzqxYnoeq24eSJXDgAno/mnXCSwpNmDmqFQYktTYMn8szE4vKposHPsjl5Aw2z1I0ytCxAAYyokHig284wEEsOdEIxpMTrYvSokI6z4/gQem5KDD7sHaXSc4ZUmNJieKMuIgFl/4vqpg1wQAgFoWJpNG1j+ZNA1mJ7bu5879W/fXID0uOpxnAQIEXFoMjlWhPs6OLfPHwmj3IFYpgVgEjE3X4/PjTSxH4qJJQ7FwYhYoGshJ0oStBmLg9HQpwjs9FM50JroA/uCxxeHBa3dfhRazC7FKKWrarLjruizIpSQe/eAIHpiSE0JPsaTYgAe2/QSj3S3QOF2BqDXaWVozoIt6bEx6bFRkkyul/JU9Cmn/aBT0FO02D+/6IjsK7j1w+dLBhYtFvfmdn+s2uVOAm/neyUYz7zg83WrD2l0nkaFX4MnpeXhyRzmnSiQcRWlarAJmhwcrp+dBJRdDIxPhrNGB3796mLc/SVo50mOVqDM6UFbTCor2JzEynPJMNnXO4vGobLFAI5fgWL0JJSNTsevoOfz6uiFhqkytWDgxC6k6Bdrt7hBflekD886tmVWAxwO47VfNyIfN7cG31W0cXa2nby5Aik7OVtln6BXYMr8IEhHB6s0AQF2HDU/fXMCJG5ZONmDd5ydw21XpSNbJkayTs/OoSiqCSiqCSy7mvFOMf3yyyQKj3c3SbfQUAymf/88A3iUIYgGAWgBzAYCm6XKCIN4FcAyAF8AimqYH5FYZ8/KcaDSHCLMtffcnpC68Bna3D0laOUgCIan5G/f4U/pdXh+sbh+HLqKs5kcA/pfwswcmAABLTK2WiVjRt8ABqZSSaLO68ftfDIeIJLDhttGobLIgN0WLDV9U+Eu7O+H0UJCKSE6GMXO9BeOzICaBV76u7nZBJ5eQGKRT4NaXuaUAq3Yew/PzRuGc2dGjEoie8OkI6DskaeXYf7odeyta2WNyCYnl0/Miam9yePDglByWA1YuIfHglByYnZEFd+US/kWQPEJurfheCtLJxAQWTzKEqGvLxZEtADL1KpY8Xhi3XWVI907Iwr6TzWzQPF4thT1ADVYuIfHotOGwuLy4d0IWhiaqQdDAqWYb0uIUkJD+sRn4/admFcDh9uBATQcS1VK8fvdV+PZUG4drUCXnD8KBBu64OhOLJ0lgdflw1mjHS/uq0WBy4nSrjWPDY5VSNJmdEJMEXF4KPxsaf8EBYsGuCQAAMdklKMuMg6U35KCf9OiQpJWx2RYM/JsW0UeHI0CAgIsPkiQwLiMe5Q0m2N0+6BRS5KVoUWu0s/Ob3584hblFaRgco8DZdnvI+pBvkzhQfNvl9c/DjEJ8olaOQ7UdoAGUvvMTAOD5Wwux5YtTqGlz4NEPjuDT0gn4pHQCatps+PFsBys2BECgcboCEe2cw2qZmHe90F+byT2FUiriXV8oZdGROXy50sHx/S6Gri9Fp0CMSsL5XqxSyquHxaCmzYEXv6rCX+aNgo+m2TjVsDCbghIRidX/Ps5Jwnn562re/gxP1iI9Vol/H23Asu3c4PHaXccxPFmDTL0KZ9psqDXacaLBgr0nmjEhJxEEAZQW5+BAjZG3HyQBbNxdhbWzC0AQfrHV1TPzEa+WorLJgte+9QenV83Mh83lw4lz7ZwEuhazA4fqzCF6SRt2V+C2q9JZyoqaNgcWvlmGT4LGTXqcGslqBeJUUhysNcJH+ZPSbrsqHUqJCH/5wn8eH+VPynT7aMSrJfBRNCvEHvh7vBSF9fNGYUh8FAaHaZr+EsCXnf9uA1Ac5ntPAXjqknXsAhEYBOGbhHafaGZ5s56+uQCxSim7WGG+IxOTUMklWP9FZch5GO6W4w0WxKkluPPaDHaHIkOvwPPzRsHl9YEkSZjtLgASzku3pNiADL0KsUoxKpqtnP7JJSR0CknY3RIAWFJs4OyIrJmVjxf2VLLt188bBTdF8f72441mxKmkvNzC4dBTPh0BfYPeBq9ilBIoJCS7w0USgKJzfEUCvUoSkgW6akYe9KrI2pMEQsbxiul5iJTVweGmcbLBiNfvHocWixMJGjm+KK9HRoQZdMK45SJwUV7RbEXp2z9iUk48fnVtJho6HHh5/lj8UGOEQiKC0+sXpItVSqGSijj2ZvXMfAyKkWHT7WNwuK4DPgrYuMc/YW4/UNcpWFCAFJ2C8+ztTk/oeCjJw5Z9p1DRbMUbd4/DXa+XcfpM0V273ExpVOBiaO3skZg+ctAFPVNhfAgA/HYyWSvj2MlkrQyxysjs3MUAn90khGEpQIAAHlAUzWYIB64VEzRcoZwGkxMbd1exwa0UnRzPzilEZbMFuclatNlcnE3fQPHtlTPy8Ncvq5Cik3N8HiaQkKLzbxjXGx1swovT4xcQviYrHk1m/7UDEU1BQQF9g2iv2JKICd71giTCpJX+hkJG8q4vgkvpByqifXMhHML9LkOiBi/vO4Uh8Upk6NXs9xpMTk51+bAkDZ7+5Dhmj01j29e0OeD2+aBXy1ibHauUhsSQVs/Mx58+Pc4JBK/eeQwLxmdxNhGcHgoFqTqoZWKUN5jYwDDzNyaxst3mwolGC9buOo6SkakQkcBvr8/Gi19W4XC9GWtvKcDeE828FaxKiQgZegXaO2ndlmz7kTPP/Pq6DNjdPiSqpdi0txKzx6bjN28eYL/z5PQ8pMcpefWS0mIVSNHJ2XhfuHEjlYqQqVfiYK0RBAGUjEzF1v3+oPSC8VmwuX2cxM2bClJQNFgZknH89M0FGJMeg/S4C/cro2PLKUoQ+JLxTUK+zo9OD1eAIfA7mfEq/D5AXI45T3CA4pU7x7IvGeB/GR989ye8cNto3P/Oj1gwPguvfsNVU2QUIxM0UvztV2Ngcfpgc3lhtLuREiNHq80Fj9fnT62PUaC23cEp4d66vwZv3D0ONGgkauRI0ylgSFSjweREik6OvBQdao32sL/dfgHcJ90RqAu4OOht8EpMEng6QMkT8I+Bt//v6ojaW1w+bP6yikuM/2UVnp0TGa1Di9WNt/9Xw6F1eGXfKSyaZDh/Y/gF8eLUStz12vccA+/2RV6wIIzbLjCL8u0H6ljqnJtGDsKitw6yG1u/uz4b9R0ONls3UC0W8Nuv5R8dxcvzi/Dbt8o4Y2vD7kp2MbFs+xG8fvdVWP7LXGjkElS1WPH87iqkxsjw6q+LcK7DCZlEhFf2nWIdSbvbG2KzGM4ppi/BHFXLth9GQarugp+vMD4EmJ0+/H77kRA7ubWfBOlabfx2c3GEdlOAAAFXFsJl0/1jwdW8fkBmZxZTg8mJN76txryiDPx513EsLxnBKekF/OLbNA281ylwp5aK8LvONQNzrdU7j2HhxCwoJKKQzGOFRASKoqM+KCigbxDtFVuWMOuF1+66qh97FTm8PuClr7h+3UtfRe7X9TcuVzsS7nedaLSgotnK/r7A7zHV5UxludHuhlxMYtGkbBCE339KjVXi+9PtrB/XYPLTli2cmIURKVoM0slxps3GZtQycHqokOo5uYTEkXoTNu6uQmlxNm8wW0QCEhGJtbuO49aidGwrq0XJyFQcbzRjyZQcbPiiArFqKW4sSIHF4WY3WeSdFaBtdjfWzCzAySYz1n1eETLPLCk2IDdZi1abG7++LgvrPufG157cUY6X7yzi1Ut6ft4o3DImjRPYDTdumI3UYATek0DbRZIEZo1KxajBMX2abHRFBYcZMu0ms5Pl+ujLbK3gIEjw7gGTgQv4B00g91aGXoFl03Jhd3vxwBQDvD4aFA08P28U/ty5CxI46Ix2fl7W0202LBifhSHxSt6/UzTQYnGhzujgZB2v6UyVT9DIYekMGAenqhvtbiRoZMhKUIfl35mam4S1s0eGpPxvK6vFLaNT++xeC+gefTXWA2lDIoXRxj82jbbIaCWazS64vV0XJgjA7aXRbImMM1gjE7MZqgzkEhKqCMuXNDIu5zDgL++4bujoiNpf6Qgee+mxSnZR/uZ3NfjjTbl4OGADzO2l4fH6cFVGHCg/Yw6koq5NsVvGpLHPweH18Y6tQH7CZrMLcSoZFFICUpG/9E6vlsLl9bFUIQzkEhLpcaFOQ0GaDs/NHYWH3vspLFdWtGcMCOhfNHXyZQaO7+0H6tBkjszO9TXilFJeuxkTYcWGAAECriw0mZ28Nqzd5ub1gcx2FxZNyoaIBK7KiMPjHx1BychUdNg92Li7CosnZ2PTnlDHeF6RFxKS4F0TjEjRQkQQkHZmUDLXKn3nRyybloupuUlRHRQU0DcgSQJTc5OwbeE1nISmaKnYarO5ed+1/hKw7SlaLC7UtDk4GaHM8WhAtG8uhAPf72JiNoG/L/B7sUqpnyYoVok2qwvPzhkJo82NTXu7NFqyE9Wwubn+GhP4fGZ2AXQKCWJV/BSQjDhbYGYvs/lH0fzJl9dm6eGjaKyamQ+zw4PS4hwO5/xTNxdAr5SgdLe/Kn/TniqMTNXi1nHp+NfBs7jzuiycMzkwJF7F8f23H6hDg8mJZJ0cD/LwMgdmA5vC6CXZ3F42uHu+cRMuWF+UEYf0OAWuG6oPCQBfjGSjKyY4fCnIxANfnje/8++Q5CRpkB6rwP3v/MihkJBLSOQma/FJ6QS02Vyoa3ewL92d12Zg094qTkp7okbGGSzhyOmHJqjx4peVKEgdGpZXRaeQ4JH3D7MLrXuuG4Kj58ycdP+Hpw7Do9OG408BgkyrZuZDLAL2n2qFUirG2l3ccoCl7/6ET0on4Jf5KYhVSllRum1ltVg2LfeCuU8E9Ay9Heu9bR+jkvCOvZgIy6UHxYSWDy4pNmCQLrIdWpVMFFK+sqTYAJU0suCwxeXhLQ2xuiILbl/J6G7T6JPOTHS7q2vBkKKT476JWbC4fPi/N8vYNs/PG4UMvSLkOayemY8MvYKz2xzMT1jVYoUhUQOAhIgksPyjo4hVSvHbn2eFjAuGk2lIvCokUx4AhiWNxzmT47LMGBDQv0gLY+dSY/pnXDncXl6ueMcFqh0LECDg8kayNvxa7alPjnGyBPecaMQdV2fi1W9OIFYpRWqMfx7/4GAdHrupSymeb66taXdATDp41wTLS0Zgy75TWFKcA51CDJIkUdNqhU4uwYlO8aQRKRr8+/4JaLEKNE5XKsJRoESLoFi49UJaP60XeooEDX8gMCFCLZj+xuVKBxf4u5rMTiilInh8FKblJ4cEIKflJWPEkgk4WNvBoTFYO3skXv3vaU48qKrZCnWYOJVOIUVtmx12t5dXhO3FLytZ0TaSIPDAtp/YDR252O8H1hnteLfMTyf44JQcvPbfU5gyYhCe+OhoZ+U8l7f4j/86gs23j0GsUgoAyNArcN/12fj7N6cwe0w6fv/+IcQqpbh/cjbbNjBQfrrVFpIR/PDUHKz59wn2dynD6SWJRSgensgb2A1Gpl6FTbePxuE6Eyjan4Wdm6LFdVl6iMUkMuMvTUISQV9IamAUoKioiC4r6+KRrG6x4qaNX4c8tGBS6N6CyZoLDjIEBkwy9AqsnlkAMUlAJRPD7HTj+Dkz3D4aw5I1OFLvHxQAWC7Nv/+6CPe8UYacRDXu+/lQSCUkjDYPRzSLGcR/vmUkXvvvKUzNG8SqszITSXaiGmqZGE1mF2RiAo0mJ4wOD0d8ibk3iydlw+2jkB6rRKPZifcOnMUjU4dj8ds/8u6cAMA7C6/GNVnxvPch2o1oD9CjHxo8VnuL3o716hYr7n79e5SMTGV3z3Ycqsdrd42LqP3Bmnb8L6CchBl7Vw+Jw5iMuPO2LzvThl+9+n1I//+xYByKMvXnbf+/6lacbLSg1eZmubniVVIMS9bg6qz487b/vroNd74Wev2td4/DuKzzXz+K0OfjlG/sZegVeG7uKJidbmjlUhjtbpxusUItF3duGBHYX90Giu7apc3QK7Bieh5+98+DIc9h8+1jWEoKZmx9eqQB1w9PxOBYJZotTkhIAkMTNez3Fk3yT/iBmRckAdwyOvW8k63XS4UIIESTU3GZoF9t6sXAwZp23P7K/0LG91v3Xh2RnexrfH+6DY+8f4i1+zQN7Dxcj3VzCnHVkMvK7l1sXHZjVcBli16N1cN1Rtz/9o8ha8UX/t9o1BmdHJ/nz7eMxN2v/4BYpRQLxg+B10fh7R9q2RLg+ddk4s3vzuCe64agze6GUipCWowSbh+FBpMDnx1txG+vz2aztxgwpc2vflPNUvXJJX5dgZf2VaGmzSHM2ZcHejVWL1UM4GKh7Ew7fvVq6HrhHwuuRlHmpV8v9BT/rWpCbZsLK3dytT/S9XL8LDuxv7vX14h4rEbb/B/uPQrmCU7RyfHs3JE4UmcKiQWMGqzDkToTTE4fdHIR8lNjcPScCSaHFx8c9PuAzLsJADdt/BqxSinuui6Tk7ywYnoeLA43ZGIRUmMVONwZOxuW5OdLZoToAL9vObfIz4v8XlkdnigZgeONZmQnalgqV8ZPDP5tL94xBgQBWJ0+f/CcovHO/2rw658NgdnpAUkQ0MnFkEpIHKzpCPm9BWk6pMUoIuIAvhSJrAEIe8IrJnP4UpGJh0vvZnZm2m0u1Hc4sTAgS+7BKTmIVUrQZvPA6vKCQFdQ+MEpOaBoGq02N16ePxbnTE4sfc8/kNfMHOHnB3R5oZSJ8fI+v1Jvm9WNG0YMwgudJN0iEhiZFoMOmxMddg/uf/tHdsG2YnoeVFY37p2QxQZmmHuToJGhtt2B5/5TwR63dWYRMTsngQZBLiGRrJWjusXKlpSPy9QLi7FLjN6O9Tabizdztt3miqh9g9nPLRSYNbJ1fw0y9JEJuhltHt7yqUhpKYx2D/aeaMZd44fAaPMgTiXBa9+cRqI2sh12m9vLe/8uhDP7SkPw2EvRyXFrUToeeu8ndkwxWbxeH42fznIXDsyGU02bA+02NyfDODCo+9iNw9Fs9fNcaWQi/OqaTDzxcddG2PKSETjVbGHbM9QQDFcWg2uz9KBodEu/IhaTmD5yEApSdVfqZpeAi4AmC39JdrPF2X3Di4REjQx3XJ0RooaeoImOzB4BAgRcWrTb3GHWiu4Qn2d/dRucHgoLxmdi19Fz+M3EbDwydTgqmy1we2kopSQW/GwIFFIx/v7tadxalM7STzHnrWmz864JhiVpEKuUskk1Tg+FlTvLWf+EqWwcHiWBQAF9j2gXFGux8q8XWq39s17oKSiaxPaDtRxNg63fVmPJlGH93TUBPUC49yiYJ1gqJmB2eHhjAelxuaBBcDJ0l5eMwGv/PcNmCN8yJg0VTRYMT9Zg/bxRqGmz4fkvKjjvQKPJgTHpMTjZaEFHQJIjEzh+6auuzcEnSkbA66OQpFNAca0/O9qQqAFFUyF+IgOmHxanF6darGym8tIbcjBrTCru+0eXIN2SYgMGxciRlaDiiEYmamV45tMTqGi2RhTkDcfjf6nnrismONzfZOJM0BgAJyvS6aHw/BcVeH7eKDzx8bGQIMnzX1Rg4cQslL79E0qLs9nBn6KTgyBJdseDaWNyehCrkuDhN/zHAwO3z8wpZL/PBG2YzLzgTGC5hER9B5cfSC4hoZB2DZlAgyCXkNh0+2gca7BEbdnO5YLejnWpiOQlVd+28JqI2ieqZTDa3SFjJ9LyIb1ayls+pVdJI7u+VooZo1NxoMboL8toBWaMTkWCJrL24XiQYpSRtb+SETz2GDG3BeOz2DF1y5g0tHbypAVWLARuOL36TTVkYn+JTqxSyhHjZDIO9p1sxuF6c+duL1ccYPXOY/jr7WOwpDgb75bVAeAvV/X4aHYXvDt7JQjICehrJGn4y0T7i64kPU4VsrDNSlAhPU6ggxIgQEAoFBIx71px693jWN0BpVSEZdsP494JWZBLSAyOU+HmMYNx/ztdavAPTslBvFoOp5fCc5+fwENTh3OEuZnzrptbGHZNsKSYK5zp9HRpETCfoyUQKKDv0d8xgN5ioK0XegqpiEBxbjInZrGk2ACpSIgN9BUutq4WACRq+N+jqzLj2OOMyDhFgzcWoJGL2QxgoMtnWzwpGyKSgFYhweqdXfGwTbePRnaCmtfur56ZD7GIZKvkmfOt3FGOxZOy4eicB5rMToxJj0GbzcN5h566uYBDVcj8hhSdPORaTIxs/X/8cbnA623YXYmFE7Mg7QyKDU1QodHkxLrPupIrIwnyDpRNLPL8X7k8wPABB/Ja9QeZeLgHf7zRzA7IBeOz4PT68NhNuZzdcIru2tW4ZUwa+/Iw59i4pxJP31yA8noz7zXcAWJOTNAmuP0tY9Igl5B45BfDkJ2o5tyvFdPz8Mq+U+w55RISxcMT8c7Cq/FJ6QQM0at5dzzOtNn6+C4K6A69Het2N7/ol93ti6i91e1B6WQD5/qlkw1s1vn5YHP7WOPNXHvD7krYPJFdH7SfLmXLvmps2lOFv+2rRqPJCSLCSh+T3cXbf5MjOoQf+hPBY09EdjlpgbuzFM21ZwycHgoZcQo8dXM+Xt53Cg9OycHcolBbtXJnOe6dOJRzjeDzHDzbgb/tq8ad12Zg38lmLCnmPtM/3VyA5R8dEeyVgH6B3cNv5+yR2rk+BkkSmDwsCbNGpWJ8th6zRqVi8rAkYWNXgAABvAis7mHg9FBosbpw08av8f9e/h92n2iG00Nh+4E6/PGmXOgU4hDf5fkvKqCSiUDTFG4tSkdVQNVP4HlJAmHXBBt2V8JHddEkBmoRMJ+jJZAmoO8xUGIAF4qBtl7oKTRyMZK1UqybU4i1txRg3dxCJGulUMuvmBzFiwqGjoCxuzdt/Bq7yhtBUX1LHSsiEeJLLSk2IFUnx5b5RSgtzsaqmflY8XE5tnx1CitK8jjfXTkjD6earbz2PVknh8PjC5kfFr/1I1QyEa/dX/7RUSRo5Pzn08rx6jddcYAmswsbdnOD0n/81xG2j9sP1LG/rbsYmdNDgaL9mcWLJmVj8eRs3DshC0qpCE4vhY27q/CXLyqQqVfhgWIDXr5zLN5cMA5rZxeg1erCnhONOHS2A14vt89A1yZWIPpj7rpi3sruyMQvxW4Lg3C7lz4KvDsVwbvhTNvg9HfA//l/p9sxIkXLT/weQAgfrv3wZA3+Mm8UVDIR7B4PFk7MQm6yFik6OUxONyqarez51s8bhYLUGPZe7T/VGnbHI1OvumT3+EpHb4nzw43RpAhpGUQEiW1ltZxSkm1ltVg9Mz+i9o4wtA6OCIPTNpeXdxH18vyxEbWXSkTYc6KRQ9nyxrfVGJ0eE1H7KxnBY09CktiyrxpAl+1SSEi4vRQUYcj76zocSNEp0GJ1463va7Bs2vAw48ELucQv7Ml3Hpruevbr5hTirNGOJcUGJGhkSNbJIROTHGE75rzMDu2lnBcEXHmwOvntnM3Zf86ekCEvQICASDEoRtHt3At0qcsnqKWQikl8e6qN308wu5ASI8ey7UfYLOPg88rEJDw+Clnxav4EGB/FfvepmwuwcXcF+zmaAoEC+h7RLig2ENcLPYFYBIhEIlQ0W1ihraGJakSoEy7gPLhUdAQNJn7ayNHpMRifHY+0WAWONfgTFA/Xm4Hva1gqkcFxStQZbRiaqEZpcXaItlZtuz1s0pBYTCA9Tsn+LZBWSK+S8AqV1xrtnPvxxMfcbGLm2iaHB3+bPxbNZhfS9Qq8eMcYmB387xtB+M+tkopCK1qn50Erp7Bs2jDoFBI8+O5PiFWGVkL79cGO4f7JBswqTIVY3BUMZjaxgivwL/XcdcUEhwF+x6evyZ+7CyhQFA2SQIg644qSEXhp3ynenYoNuyuxeFI2ALC7Ght2VwLgL5P2UcArX5/C5tvH4FBdB5RSEWgaSNbJ4fFSeHTacPz929MYlqThbQ8AR86ZsfNwPdbMKsDINB2qm23Qq6UADfz9riLIxCLoVVKWXJv5zQ6Pjy3jZtLoGR7iS0iwLSAAF6I32VvjFKOQ4IEpOTjdagNFA2ISeGBKDmIUkojax6v5aR0ipZWwe3y83FwOT+guHR9oisKcsemc8qcnp+eBpiNrf6Ui0PYlauRI1sphtLuxemY+Nu2tROlkAzbuqYRGJkZKogJuH4XNd4xGRaMVNrcPIgKIU0qx/WAdrh+eiIem5iBJIwcFmnc8pOjkeGZOIV78soq1i8HlPwBDf0MgP1UDq5PCqRYrDIka6BRi3vMSIHCm1SpQ5Ai4qIhRSnjHn055RS3LBAgQEKXITdJg1cx8PBEgjL1qZj62dFYYBqrLJ2llWPjmgbCBX7lEBI/Ph2fmFMLp8eHl+UXYsPskympM/vPOGAGAgNvnn8/DlTaXFmejKCMO12TGYfTgmKgMBAq4OIjmzU9tmPWqRh4d0VWrk0K90cHhhV1SbEBajKK/uxaVCI41tdlcl4SOIFEjD0MbKWffL4vTy47VFqsbJxst0MlFSNHJYXH4EK+i8dFP9Swf8JJiAxK1Mqz7rAKzx6aFjPMMvQIiEEjsTHDMSVTj1nHpbIbxK1+HcgyvnpmPN/efwaJJ2Zw4QLJOzlJQMNduNDvx4LuH2N/y6q+LEKPiX5+rpCKsmJ6H1Bg5Fr55gFvRuqMcL/5qDBrNXaJ0t4xJC0lWY+gTH//wKAyJahQOjmWvMVA2sa54L6Qvd1u6CzQDYP8Wq5Ri4cQsDEvWIE2nAA0aD90wDFUt/Kn2zG640e6GUiLC4knZUEhEWDMrnzPISycbsOtoA6blp2DRWwd5dywe/2Uu7vt5NtZ9foIN1jB/W14yAk9/cpwN7B4/Z8LgOBWcXgr/rWpFnFKKv397GrddlQ5DkhrpcSre37y8ZAQsTg/e/r4Wy6blwkdhQBBsXyno7YZHb40TQQAtFhdnEbD0hhxkJ0QWXPZQPqyakYcnPu5StV01Iw9eOrId8hiFhJebS6eIzNyppBI8uYNr9J/cUY5t/xcZ5zJwabifBhL4xtySYgO27q9BQaoaz8wZCbeHwmt3FaHO6MT97/zIa5/+eFMufjlyEEeR9tFpw7H0hhyOUNaKkjys++wkJg5LREWzFbM77WKiRoa6DgfLnQ74J/QzbTbEKKVYucM/pjbtrcLa2SOx8bbRKD9nYoUGlhQb8MC2nzC3KC2ED1mwWQL6EswikxmTTOaBSkilESBAQBTgnNkB0BTWzSmEze2FSioGQdAwOT0hlZClxdlg6CWCfY/SyQZ4KC8aTOAEmlfOyMOsUT4YkjWoMzqx6C2/RkqGXoEVJXlYubOcs8bUyESYNSqVXW9FayBQgIBgxCgkvH5RjDKypJv+hjVMReeWCCs6BwIGil/H52+tnT2SN3u2r+kIGFqJYP86UJAuL0WLNbPy8cKeStxalI5tZbW4tSidDaYGJvA0mJzYsLsSr/66CEa7O2R+YPiL73j1e1w7JA7PzhkJMUniwaCY0sod5fj7r4tw9JwZQxPUcLg9uLEgJaSfdpc3ZAwyCZjMsQM1HdhX0RQSY2OC2PFqKY6d46c++rG2g5P9HK5KnzneaHKicDD3Hg+EueuKDw73Jflzd4FmoCtA2mByYuPuKsglJD7pDDbkD6JwqK6DE5AA/C/38CQNnpldgGSdHMs/OoqaNgcWTcrG1u/O4G/zx+JAjRE+CnjzuxpO9jHfjkVzQNDuze/8pQEiEshJ1KDF4mQDKhl6BVRyCfsCMi/GbVels8TbWfFqzu9irrF65zEsnJiFpTcMw9TcJPxQ035JdrQE+NGXGx4XknlscnjZQB5z/fX/qcArdxZF1J4Aic1fVnHKVjZ/WYVnZxdG1J4kCN5FyJv3jIuofbMl3A6sK6L2fV2NEA3gG3Mbdvt3R9UyEQ7WdLCfGYVaPvvUYnWFBGX/tOsElhQbsHBiFgyJGtAAXtl3ChXNVvzfxKFYMD4LL+2rZlVuS4sNMNr9/NByiV/shqJpNgjHnHfZ9sNsf9bMKkC71YnXvvUvVsKVNgk2S0BfocPhxUtfce3cS19V4alZBf3dNQECBAg4L5rMLlZIm4FcQuLFX43Fj7VGTiUkQy/RYHJyfI/sRA3+9MlxPDevEPe8/gNnjl7xcTle+XURKAr447+69AFq2hx4aV8VW65c3+GAj6JhtHswKj3u0t8IAQIuMqwuH79fNCcyv6i/4fDwa9kEHxuoGEh+HZ+/tWz7YWyZX4SFb5ZdUMVvpOiOViIz3k/HV2u0Y5BOgWfnFOKR9w+hZGQqL3/vgvFZ2Ly3Ck4PBaPdg+dvHYU/f3ocb35Xg4UTszAkXgW5WMTGofZWtOJnhniYw1CsdDg8MDm8WLWzHGtmFeDh94+E+KTPzxsV0s7p5c5fLi+FshoTlk6VswLNzO802t144+5xcHi6sqMD2/oosNQTzN/CUS/JJSSSdQOTB/+KDw73pYIpX6A5VilFi8UFo92NeydkYfuBLsoFJtiQqVfh8+NNWLvrOB6cksPJmltRMgLtNhc0Cikqm6x4oDgHj/7rCAjCv0A63mCGQiJigyyB4kx8OxaBQY8Gk5MtDfjLrX6e4RSdv2TgD9Ny8eddx1kDAADv/FCLVTPzce8Ef5DmTJsVAMH7klI0sGz7YRSk6qJeJTba0NsND4qisedkEw7XmVhuqII0XcTiRFaXl5fWweqKTJCuyexCTZuDU7YCIOLgbJudXySl3R6ZoJwmXPlWhJnHl4r7aSAh3JgjCCAtVolHOik6goXpurNPgeeJU0nxly8q/YIEnRtrq2fmY8ehszAkxWD22DSoZSJIRSR0CjHWzSlEdasNXoqCXEzCFGYxwfTh8Q+PYMH4LNY2A/wTeoJajuoWa79nDgiIflidXl47Z3FGZicFCBiocLvdOHz4MOfYyJEjIZVGRg0lIDpgC6MPAZrGqMExnL8FZoQ1mJx49ZtqrJieh63fVuOOq9PRZuVft5nsHtAIXRfUtDlQ1WyBjwI2761CaXE2lNIr3qUVcJkinF/UZI7ML+pvaOT8fpVKFh2VUgPJrwvnb0lEBD65CHQEgRnTSqmYl1YiUSOH10vhixNNONZgZmMH91w3JMT/YviC8wdp8cY9V6G62QqdXIzjDWY8OT0PLo8PPho4a7TD6uJuKnQ4vOw1g8dSvFoGgrCgps2Bc0YH7z2yOD2cY3IJCeYWBWY0yyUkznX4EzmD0WZzITNeFZJB/fTNBdiwuwJuL83OdYF0sIFZ09vKarFmVj7yUnQX/mAuIi75TEoQxGAAWwEkA6AAbKFpegNBEHEAtgHIBHAGwDyapo2dbR4FsACAD0ApTdOf9VV/+pL82Z+11kWyve9kM24sSMGvX/uePffykhHY9n0tDteb2Rcq0Oj8+/A5PD9vFI43muGjgJf2ncJtV6Vj85cnYLS78fDUYdhw22hIOjm33vi2Bg//Iofd3QgWowt+gUQE/0vVYHLA4fHhqVn5ONZgxrkOB24tSg8p/TrZYMamPVVd9BEOT7eCFM0WJ8Zl6gcEwfaVgt4G42vbbThn5Ap1nTM6UNtuQ2b8+SfBODU/rUOcKrLypyQtP+dwolYWUfvkMO2TNJG1J8BfNhPpFNuX1QjRgnBjTi4mQ4LAF2Kf6jscuPPaDIweHAMA8FHAth9qMLcoHSs+LmcpKp757CTHXr39vZ8u4tk5hWHtFMDwEnctWtQyEZ4oGYFVnZxWjM063WbF4rd+7PfMAQHRj0QNv51KiNBOCRAwUHH48GEs2vwxdCmZAABTwxlsXgQUFUVWPSQgOpARp+K1YelxqpDsqQaTE9vKavHqr6/C/063QSoikZOoxG3jMvD4h0fDchFr5RIcru/g/dvwZC1W7zwGucQvTJsU4RpRgIBoQzi/KFrGfJySnxYjUr+wvzGQ/LokrRwZegVKRqayCVg7DtUjSSvvczqC4IzpDL0ihGd+zax8DNLI8WOdEW02dwiv9LDkLo0rhm5oW1ktVFJRSIzpyR3l+M3EoTA7PXB0atEEj/sdh+p5aVEbzU6oZX6hc6WMfzMiWdclosoEdPUqCTbcNgqnWqx48zt/dvBTNxdgkI7/nTMkauDy+JAWq8CW+WNhd/uQqJFhRJIWcokIS9/9ic1+NiSqkRqjwD/vvRpGmxs6hQQWlwcbbxuNvBQdR4xuIKE/tlm9AB6iafogQRAaAAcIgvgPgLsA7KZp+s8EQfwBwB8ALCMIYgSA2wDkARgE4AuCIHJoOkIC0vOgr8ifKYrGsQYL56V4ft6oEF6U1TuPYf28UVi76ziWTctFpl6FA7XtbIbusCQNpw0Athx7894qrPv8JBaMz8LOw/VYNSMfT3x8FC0BGZUEQeCxG4ej1eaGUhoa4IhTSkOykx+ckoPXvz2D2WPT0G5zY9PeKrYcILgM4JnOEhbmtywpNoQVg2ICkgOFYPtKQW83PNqsbtjcvhAD32Z1IzP+/O1JkLy0Dv9YcHVE15eJCayckYcVAYuIlTPyIBNHNl4oCiEctUtvyGE3bc4Hk8PLWzYzNMIJ90rMlOcbc0tvyIGsk4iKuR+B2UN8O6rpeiUenjoM6z4/GWJPGE5gZid30aRsdox0R/q/eW8VGjrsIfyugaJ1cgmJa7P0nCqMDL0CW+YXQSIikKSVgySAaRu+HhCZAwKiH1JRGDsnEuZFAdEPXUom4jJz+7sbAi4ihsTzrzWHxPvXmsF/WzYtF17Kh5xEDc6ZHPDRBMvpyMdF/OT0PJxutSItRoHlJSNYASImGPDSl1Uw2t1YMT0PSpk/KC1AwOUIjUzEG1zVREnmrcXJT4uxLkpoMQaSX5ceq8T9kw0cPtw1s/KRHqvs82sFZ0z7s9f9saCKJgtoGnjn+xqICAKn22z46Kf6kIrzR6flsradoT5dMD4rLNXEqs7YUnaiGkabm+PP7zhUj9LiHGzcXcFSEw1P1uKlL6tQ0WzFkmIDSicb8Ma31SG89Ktm5OMf31Wz7UalxYAgaRypN+OqzBjkD0rFdUP1bIwKCJ3D1s8bhaEJ6rDxq8sl1nXJg8M0TTcAaOj8t4UgiOMAUgHMBHB959feAPAlgGWdx9+hadoF4DRBEFUAxgHY31d96gvyZ76Sg+ONZt6dphONZmy8bTQKUmMAAOc6nCwPJyPaENyGedGcHgo5SSo8NHU4GjsceOXOIhAEhQaTG49/eBQPTDGAAMEG9jL0Cjw/bxQo2h+8fmlfNQCwL+/Y9Fg89q8jMNrdGJ6kgVRMYsNto+Hy8vMDnWm1cT7b3D5sP1CHN+8ZhyaLCxVNFjaQs+n20aBpYP+pViilYrh9vqh+WaIFvQ3GO70+3uDuq7+OLOunJQxnb6s1svKncx0unDjXgdfvHocWixMJGjk+O1IPnUISQtzOe32rGzIRyWbTkwQgE5FosUZGK6GUinjLZpQRCkX1ZTVCtCB4zCWo5XB4vJjz0n48MMXAKSfdVlaLLfOLUFbTDpVUhM23j8Ghug74KGDj7krcc90QLJ6UjQSNDLXtXHE5m7trT5DJSE7RyZEeq+AdczIxidLibKTrVYhVSfDCbaNxqtWGYckabN5TgVvGpEFEAldlxCFeLeOM+5o2Bxa+WYY37vZzVTeYBk7mgIDoxzmzCwRNc8Sc7C4PzpldEFiHBVxOoHxeHDt2jHNMoJmIfpxvrcn3NwA4a7QhRinhUEkEchHnJKkhFZFotbrw9KcnWF9m/bxRsLu9aLG4MDRBhf+bOBQSkkBanAIjUnSCXyHgssU5kxMEAc56weHx4pzJidxB/d2786MxDC1GY5TQYgwkv67WaGcDwwBDjXcUY9Jj+9wX4cuYrmlzoKLJgk17uhJ1Hv3XETwwxRBScf7glBzolGKk65X4+11FaLd52JhWuFiX00MhO1GNn2cn4JzZgQ67B6/dfRXarW7EqaSQSYCVM/JR1qm3tXrnsQC9LCWkYhJD4ofC4vLgtbuuQpvVjWSdHCOS1BgSr8Q5kxMxSglqWm148atqGO1uVv9raCL3/vU0ljIQxOT6Av1K0EQQRCaA0QD+ByCpM3AMmqYbCIJI7PxaKoDvAprVdR7jO99CAAsBID09/SL1mh98LxAjwBC80+Sj/OTsJEmgusWKZdsPs98J14Ypf87QK2B1+bB65xHOyzcqXYd1cwqhVYhZRUjA/xI/+O5PeO2uq9gANODn6JJLSFzz6yJIxQSWFBvw1CfH2ew8iqZ5++HyhvbLaHdDr5ZhbEYcRqRocd1QPZK1chxrsOCXL3zNydTbVlaLZdNyr/hS7Is9VntjoFyeUJEAp4eC20uFacHFoBgF79hJ0Ua2wzooRo6clBjcFUDHsmJ6HlIiJG6PVUqw5J0fQ66/9e7IBOliFBLejD6dIrLyp8spU74n4zR4zO0/1Qqnh4LV5cOOQ/WcjIHDdR3YuLsKiyZls84fgz/tOoGFE7NQ3+EICdAH38IMvQK3FqXjnMkRpvxHzRHVZGzQ1nvGYf61Q1jbK5eQWDenkHfcf13Vile+rsbL84sGTOaAgFD05/x/IeitnRIQvYi2sXo+BHMMHzt2DHSAmq2luQ7P1TqQdMLPFyjQTEQPzjdWu1trhvsbTfuDXfVGewj1xKvf+DO7AHB8lpo2B5a++xPWzSmEXi3Dg9sOwWh3Y+3skUJgWACAy8+uBkIlE2PRW6HrhdfvvqofexU5EsPRBUYJjVZf+nW9HaeXkuIiXMZ0oFi9ovPvqTHKkIrz57+owMKJWaxWzObbx0Au4VaUBp9XLiFxpN4Ej4/G1NwkHKpr4Phqy0tGgKZovPJ1dUj78nMW7DxcjxXT86BTKJGklePqIXr2OY3NiENLeSN+0xknO1+Q/3IJ9vYU/UZ2QRCEGsB2AA/QNG3u7qs8x3gLxGma3kLTdBFN00UJCQl90c2IwbxAgdhxqB5/urmA8yKUTjZg5+F6NqAQ/JIzpVWBbZYUG/DBwbrOlyKPLa0Cul6+U81W0ABaw4k6ODxYUhx63upmKx6ZOhxb99ewmXEbdleCJIiQfqyZlY+dh+tDfgvzYjEv0TVZ8aBohGRSb9xTiZKRqVj67k8402bDlYz+HKvnQ4ZeFTKWGR65SJCXosWaWfkhYydvUGTE624vxZb/A/6xs3JHecTBaYvTw/sOWFyeMC24kElE+Gtn+dPiydlYMD4Lf/2yCnJJ5OVbge9CVjclKAMdvRmnjE3cfqAOtxal49VvqrFpTxVe/aYaQxPUkEtC+YgB/+eMOCUy9ErOGFoxPQ/xKil7bMehejxRkoeNeyrxblmo3Vw9Mx9/3nU8xAY9dXMBvD5wNuWcHgqVzRbecc/wpz/+0RGsnT2Sc43LPSM8mjCQbSofzI4wdsoZmZ0SEL2ItrF6PjAcw499cBiPfXAYa9/bB7uDq1ugTspAXGYu4jJzWS5iAQMfF2OsNpldeOKjo3i3rA4rpueFzPM7D9d3m1mWHqfA3KI0bJlfhF/mp0Tt+kpA3+Jys6uBsDj4xR8tjugQsFVI/DRage+6/3P0vLt95df1dpzyxZsuVqIKkzHdXSxobEYs5BISp1ttvGOUCtB2WbWzHGtm5bO8wXzxsQen5OC9sjosffcnlDeYQny11TuPwe72hrR/6uYCaOQilIxMxcod5UjWyUOeExPk/6R0At5ZeDU+KZ1wxScr8qFfMocJgpDAHxj+J03TH3QebiIIIqUzazgFQHPn8ToAgcXkaQDOXbreRga+koNl03IxZVgi9GoZymra/SJKnZmzTEAheFeGKbveft+1aLO5YXJ4EKOU4qGpOUjRyXG6hf/lE5EkHG4P0vX8AhFKqYiXR3X22DQ0W91sSj5zPoYuYsH4LIxM1cKQpEF6rBJj0mM7FStF8PgoTMtP5t09C7ezxSz4hFLsgYvz8cidD2IxiVmFqTAkqtFociJZJ+8R8XqjmZ+WIlJVXomI5H0HJKLIrt9q5S9/arW6YEjSRHQOAVybyJDz5yRpkKCR4mSDBctLRqDZ7OR9Vg0mJ9LjFHhmTiHaLE7kDtKiw+7Byh2VHBtW2WSF00NxSlIJAhgzOAYWpwc1bdwAhdNDocPugYggQsbYu2V1ePrmAjz2r66qjEBe4po2B1Jj5BdFDVjAlQepOIydGqACFQIEdIdAjmFTw5luv8tHMwEIVBNXCmxuLztvmxxuPN9JF5GgkUEqIrDsF8PhC1NFqZSKYHF6MWtUqjD/CrhiIJPwrxdkkuhYL9jdFJRSElvmj4XR7kGsUgKTww2HJ7KkHwFduJQUF3wZ00wsiPncZnOhdLIBLq/vvFnGNW0OmOwerJ6ZD7vLh7/fdRVaLE7IxSKIRQRWTM+Dx0cjQS1Fg8kZls4vTi3DC50cxSISKEyLwT/2n8Heilb2e+HiTFdqNnBPcMmDwwRBEABeBXCcpun1AX/6GMCvAfy58/8fBRx/iyCI9fAL0hkAfH/pehwZuis5GJ8dj7RYBZotTswew13Q8L3ky0tGoKbdgbW7juPWonQ88n5XOv3TNxcgQ6/gBD3kEhK17Q68+k01Plp0LdbMyucQla+YngcvRfHyqPKtq5iXmSnx+iRAcCnSF6q7UgShFHtgoy/KZ8RiEoWDYyPiCA5GcrjyowhVeWOVkhDxsRXT8xATIS2EUsqvchop57AAP8ItKj4/3oSnPz2BWKUUd1+XgdUz87E8QPmWoX54dk4hjHY31HIJ7nrtB9w7ISvEhi0pzmafVYPJydLlMEFivudY0WRB8fCkkL8Z7W6MSY/BJ6UTUNNmw49nOzh8x3IJiTiVTFhUCOgTaOXiEEHGJcUGaGT9yvYlQMBFRzDNBCBQTVxJyIjrSmKxunw4226Djwb++OFRxCql+OMvc7Hu8xO8ivRn2+0oHBwjzMECrihE+3pBLROjotGDymYbqwUTr5JiSLzwHvcUl5q6kC+YGvx5W1ktbrsqPUQ4dEmxAVv317Dfk0tImJwelNUYWXHxFJ0cd16bwRnbK0ryID1YixQdP01lokaG9fNGocXiQrxahj9/egxlNaag7whxpgtFf1iVnwGYD+AIQRA/dR57DP6g8LsEQSwAUAtgLgDQNF1OEMS7AI4B8AJYRNO0L+SsAwDhdiPOx8kV/JLTNPDLF77mVXN87F9HsGV+ERa+WRYSTFk/bxSGxmvRaHZxSOs1Cn9QK1DxkXlp0+OUaLW42Jcv8GXuzW4UX9A7sJ9CKfbARn/urCVqpLycv0mayDKK5GIxXvqKq4r70ldVeGV+ZNxcbp8vxCkpnWyAxyfscPcUweOousXK2oQGkxNPf3oSGXoFK1AXWF1RlBGH0602lrecT818aKI6xK6tmZWPF/ZUwu2lQxYqTCbwREM87857epx/gZWpV8Hh8W+oAQKFhIC+B0EQUElFHOFMlVQkZMIJuCLA0EwIuPIQWJ22/UAdVs3Iw/2d/OsNJiee+vdx3HltBt75oZbNDMtN1sJHU6BpIC8lMooyAQIuF0T7emF4khanW21otXUJg8eqpBiepO3HXkUvBlL2a6ZehSXFOXjsX0cQq5Ri4cQspMcq0eFwI0kr5/hRS4oNUMvEoAN0reYWpXHEwJ0eCit3luO1u65CXoo2xFdbO3skrsuKZ6uRKYrGPeOH4ui5/hcLvFxwyYPDNE1/A34eYQAoDtPmKQBPXbRO9TPCCTmF49ySiAh8UjohLL3DhOxEnGmzhSgEZ8SpMHpwDDocHmjlEiR1ZmL++rXvuzLtxCREBPD0zfnI0KsueDcqMOgdCQ2FAAEMzplc2HWkAX+bPxYddg9ilBK8/s1pZOiVyIg/P61Dq42fFqLN7oIB52+vV8mwrayWE1zeVlaLafnJF/ybBPgRTvnW7vaieFgi7B4fp7qi2dL1/UDqiECqm7oOOwrTYmB3e5Eep0JGXFfJk1omZhfTNA28+V0NjHY34lQyjEmPC7vzfjmJCgoYmKjvcODFr6pxy5g0EATgo4AXv6rG8pJcFA6O7e/uCRAgQMBFQbB/YHNx+VQbTE5s3V+Dx3+ZC6vTC6VMjDNtNuSmaDB+aELEFGUCBFwuiPb1glhM4sa8FKTHmS6IblDAwAVJEhiTHsP6Wj4KeO4/FTDa3fi0dAL+ff8E1LbboJSKoZKJ4PT4oFfJ8O7gGDSYnKDAH+syOTwQi8nz+mKCv9b3iI56hCsMgWTjfOn0SVp5tztG4XaUMuPVyAwq4aAoGsum5YZk0P08J7HXL9ZA2tkSED1I0sqx/3Q7hztILiGxfHpexO35y1AiKzHJ1Kt43wlhF7L3CPdscpI0vHaCj5M9mOqGz64xdoeiaNS2O3if5fnsk2C/BFxMpMYoeameUnWKfuyVAAECBFx8BM6v1S1WXpqnYw0W1j7KJST+ff8EIZgk4IrE5bBe6A3doICBjfQ4FYYna0N8rYxOX2toIr8fNXIwcOhsB69fmKLz++yR+GKCv9a3EILDAxAMJcPaXcdDyqj7Okgl7LgIGGjoLdl+b9sL78TFQ0+fjfAsBVyuyEvRhugDrJmVj7xBQsm0gEsHt9uNw4cPc44JwnACLiX45nmGHgroonWKVBRZgIDLDcJ6QcBARm98rbBjW6AP6jcIweEBCPYlS9ag3ebCtoXXwO72IUl7cQIbwo6LgIGE3gb0+iIgKLwTFwc9fTbCsxRwuUIsJjGrMBWGRLVQZimg33D48GEs2vwxdCmZAARhOAGXHuHEaxl6JZJcTgABAABJREFUKGFTV8CVDmG9IGCg40J9LWFsDzwIweEBCiGgIeBKRm/Hv/D+DFz09NkIz1LA5QqhzFLAQIAuJVMQhxPQr+Cb54V5X4CALgjrBQGXK4SxPbAgBIcFCBAgQIAAAQIECBDQLfhoKI4dOwaapvupRwIECBAgQIAAAQL6AkJwWIAAAQIECBAgQIAAAd0imIYCAOqPfIuYoaOg779uCRAgQIAAAQIECOglhOCwAAECBAgQIECAAAEDBANZKC6YhsLUcKb/OiNAgAABAgQIECCgTyAEhwUIECBAgAABAgQIGCDoL6E4yufFsWPHOMcGSlBagAABAgQIECBAwMWDEBwWIECAAAECBAgQIGAAoT+E4izNdXiu1oGkE14Aly4oLUCAAAECBAgQIKB/IQSHBQgQIECAAAECBAi4jBGpmJw6KeOSB6UFCBAgQIAAAQIE9C+E4LAAAQIECBAgQIAAAZcxBrKYnEBnIUCAAAECBAgQ0L8QgsMCBAgQIECAAAECBFzm6KmYXHDQli/TuC8g0FkIECBAgAABAgT0L6ImOEwQxDQAGwCIALxC0/Sfe3oOiqJxps2GJrMTSVo50mOVqDXa0WR2QikVw+3zQa+SIVOvAkkS3Z7L66VQ3mBCk9mJWKUUNrcHsUo5cpM0ONvhQE27DSqpGElaGdLjVADAuXam3n/sdKsN5zrsUErFaLO5EauSwOOlYHV5oZKJEaOQwO72odniQpxKCo1cDJvLi3abB3q1FHIJCR9Fw+nxwUsBLo8PWoUENrcXKqkYVqcHGrkEXoqC0+uDSiqB0e6GWiqGXCqCx0fB4vQiO14FCgSaLV39I0ki5J5l6lWgKBrlDSY0mJxI0SmQl6KFWEz29HEI6AbM+LrQe8z33M43pgNhd7hxtNGCJrMLSVoZ8pM1UCoiz+DpcDhR0Whj2+ckqxCjkEdN+97ev962jyZ091spisZZow0tFhfarG4opWLIpQSkIhFMDg8cHh+0cjFIgoBcIoLLR6HZ7EJajBw+iobDQ8Hu9kKrkMDp8SJWKYXXB5wzOZGsk0EmItFidUEpFcPs9CBBLcOIJC3qzU7UtNsQo5CApoFmiwtauRjJOjnEIgKNJhdsbi8y4lQYEt9l60632ji2Oy2ma47o7XOMZExcSePmUqO3NkGAgCsRwUHbi5lpHEhnIWQSRwdsDhfKG62sXc1LVkOlkHHWsAlqGeRSEg43hVarCykxcni8NNrtbuiVUrTZXJBLRFDLxJCICNjcPnh8NBxuvx8kl4hgc3mglUvgpWi0WNyIUUqgkYlhcXmRpJVjkEaOo41mNJqdSNHKkZesxTmLk+Pv1XXY0WQOnfsFXBmI9vVVtK9hor3/vfXLe4LAsZqokUNEAg2miztuI/19DocHRxrNMNo9iFVKOuNMYohI0m/vNTK4vT6kaBWQSgk0GF2wefwxqRaLC3q1FAoxCZePhs3lRXqcCoNjFKhoscBo98Dp8SFLr8KQBDUoisaxBhPOmZzQKsRI0SqQrJbhRLMFFpcXdrcPg3QKDE/SoMHiQLvVDavbB5vLi0SNDAQB6BRSTkyrusWK0202yCUiqGQkpKQIJqcHVpcXCWoZfDQNvUrGiREyz8Ds9MDjpTv9ThF0cjF8NOB0U1DJ/XFEqUgEs9MNqUjExgADfWLmuTJxxzilDGIRuvzSWCVEIiKi582cr83mgkxEotXqhkomDrluTxEVwWGCIEQANgO4AUAdgB8IgviYpulj3bfsAkXR2FXeiKXv/gSnh0KGXoH7Jxvw+IdH4fRQkEtIlE42YFtZLZZNy8W0vOSwN9XrpfDhoXqetsewaJIB7/5Qg7IaE+QSEkuKDRgxSAObi2KvLZeQWD9vFKRiAqt3HsP8azKx7vOTiFVKcee1Gdiwu5L93qoZedj8ZRVq2hyQS0isnJGHvwZ91qulqG6xYf1/Kth2K0ry8NK+cvZ7j904HG4fjXWfn2S/s6TYAJVUhPcP1OHGghTOddfPG4WpuUn4/HgTp9+bbh+NDruH89vXzMrHrMJUIUDcR+AbXz25x8FjnXme3Y3pQNgdbuw82oQnPj4aMA7zUZKfFFGAuMPhxOdHW0LaT81PiGgh0N/te3v/ets+mtDdbwWA70634FyHizOWl96QgwSNDI9+cIQ99sgvhkHSeW/eP1CHOWPTYHP7ODaJsc+3XZWOrftrYLS7sWJ6HkSgsWjHj6xdXzTJgCc+OopYpRR3/yyTYxeXFBuQrJPjL19UsLYxnK177MbhUMrEnL5f6HOMZExcSePmUqO3NkGAgCsZgUHb82Ua9xWCg9LGulO4f8oxjBgxgv2OECzuX9gcLvz7aHOIXb0xPwGfHWth586iDB3mFaXjiY/LWT/nnR9qMf+aTJS+/SNnbZAep8DpVjtn7l96Qw7SYhSobLbh2c+4PszW/TWQigksut7A9iNDr+B8ZtbQdpcXT396Qphfr0BE+/oq2tcw0d7/3vrlPQHfWGVsndHuvijjNtLf53B4sONoIzZ/WYlbi9KxcU8lbx9LJxvwx7KjWHR9Nr443oBJw1OwcsdB9rsrZ+ThvbJaNlb2zJyRaDQ5Of7ac3MLQdE0Hnn/MMcvi1FJUW90cOaIp24ugEpKhswdT07Pw/sHanHP+KGYmpuEz4414aH3fuL0w+XxceaFB6fk4D/HGnDbuIyg+5EHgGCPZegVuO/n2Vi5ozzET721KJ31Vw1JakwelgQAIc+1dLIBe040YvbYdM55lt6Qg9f+e6bb582Mk7W7juP2cRl4/guur8tc90LGSbRE88YBqKJpupqmaTeAdwDM7MkJzrTZ2AcCACUjU9kHDABOD4WNeypRMjIVS9/9CWfabGHPVd5gCtv2iY+O4s7rstjjG3ZXwuLwca7t9PgDxYfrTCgZmcoGbG8Zk8YOauZ7T3xcjpKRqeznFTyfpSKSfaGY4yt3cr/XanOz1wnsW6vNjXsnDg257tJ3f0J5gymk34frQn/74x8eRXmDqSePQ0A34BtfPbnHwWOdeZ7djelAHG20sBM40/6Jj4/iaKMlovYVjTbe9hWNkV2/v9v39v71tn00obvfeqbNBq8PIWN5/X8qcLrVxjn27Gcn0Wpzs/ao1eYOsUmMjd2wuxK3jEnz27kd5VDKJBy7/sRHR1l7GmwXN+yuxOlWG8c2hrN1rTZ3SN8v9DlGMiaupHFzqdFbmyBAgIBLDyYoHZeZC1IkwnOfHsFjHxzGYx/4uZODxfXOB7fbjbKyMs5/brf7IvX+8kd5o5XXrh5vtHHmzjuvy8ITH5dz/JxA34dpu/4/FfD6EDL3r/9PBSgabGCYOc6sBUpGpnL6EfyZWUO32tzC/HqFItrXV9G+hon2/vfWL+8J+MZqoN9zMcZtpL/vSKMZT3x8FCUjU9nAMF8f2ZjYx+W445ohbOCT+e6Kj8s5sbKqZmuIv/bQe4dQ2WwN8cuqmq0hc8Qf/3WEd+54cof/OoyfxwSGA/sRPC88/0UF7rwuK+R+yMVizrGSkakhv4v53YH+6uE6E+sTBz/XjXsqced1WSHnWf+fivM+b+Z8JSNT2cBw4LNgrnshiJbgcCqAswGf6zqPcUAQxEKCIMoIgihraWnh/K3J7GRvnP+74HwG/J+Z480WZ9jONJic3bZ1uL2c4za3l/f7FM3tR3d96u5zu81z3nYUzX9uigYcYfrH9zvDnafRFP5+CQhFd2M13PiK9B4Hj3WmfXdjmtvexdu+yey6Qtr39v71rv1AQnfjFOj+tzaZnWFtExVEWckcY+xRODvD2EjGtjH2tau/57enjN0NPNYTW3chzzGSMXE5jZv+QPfzf+9sggABfYnz2VUB/AgMFgeK6kUKRpCvNwHmKw0XalcDjztc3pB5Odz8bHPx+yPhjhNE6Fzf3dwffEyYXy8f9CQGAETX84/2NUy097+3fnkgLtSvCvR7+nrcRvr7mOd4vnhV4HeMYfzAwFhZdzGqQDB+Iu8cESaWxcS4wv1GvnmBLy4WPAedL47I/J+iwfrE3fWP7zzMv/meN3O+7ua7Cx0nUUErAYAvJzpEEYOm6S0AtgBAUVER5+9JWjnkEpJzA/k+07T//4ma8GUOKTpFt20VUjHnuEoq5v0+SfgHeeDfwp23u89xKsl524kI/nOTBPw8oDx/S9GF3rNw50nWDfyykIGE7sZquPEV6T0ON9a7G9Pc9jLe9kla2RXSvrf3r3ftBxK6G6fA+X+rx0eFtTuBCDymlIrD2hnGxjK2jbGvwefqzp6SBOCjuN/via27kOcYyZi4nMZNf6D7+b93NkGAgL7E+eyqgPODj5PY4/EAACQSCe/nY8eOQZucwRHkE9A9LtSuBh5XysQh8zLz/+C2Kjm/PxLuON252RuJf8e37hDm18sHFxIDiJbnH+1rmGjvf2/98kBcqF8V6Pf09biN9Pcxz5H5e3d9ZPy1cDGqwFhZdzGqQIiIrr+FzBFhYlmKzuPhfiPfvMAXFws3B3XnpzLnZ54X3/fDxeDO97yZcRLuvIHX7SmiJXO4DsDggM9pAM715ASZehXWzxvF3sgdh+qxZlY+58aWTjZg5+F6rJ83ihWM40NeijZs21Uz87H122r2+JJiAzQKEefacomf62hkmg47DtXj4anDIJeQ2H6gDkuKDZzvrZqRh52H69nPK3k+u30Ult6Qw2m3ooT7Pb1Kyl4nsG/xKile3ncq5Lrr541CXooupN8FabqQ375mVj7yUnQ9eRwCugHf+OrJPQ4e68zz7G5MByI/WYNVM/KDxmE+8pM1EbXPSVbxts9Jjuz6/d2+t/evt+2jCd391ky9CmIRQsby0htyMCRexTn2yC+GIV4lZe2RXiUNsUmMjV1SbMAHB+v8dm56HuwuD8eur5qZz9rTYLu4pNiAIfEqjm0MZ+v0KmlI3y/0OUYyJq6kcXOp0VubIECAgIEFS3Mdh2bisQ8O496nX8V9Gz8I+3nte/tgdzjYczABZoFq4sKQl6zmtau5ySrO3PnGt9VYNSOP4+cE+j5M26U35EBMImTuX3pDDkgAj/wi1If54GCdf94P6EfwZ2YNHa+SCvPrFYpoX19F+xom2vvfW7+8J+Abq4F+z8UYt5H+voJkLVbNyMeOQ/UonWwI20c2JjYjD//47jRWTM/jfHfljDxOrGxoojrEX3tubiEMieoQv2xoojpkjnjq5gKIRaFzx5PT/dfx+3laPDd3VEg/gueFB6fk4I1vq0Puh9Pj5Rzbcag+5HcxvzvQXx2ZpmN94uDnWjrZgDe+rQ45z9Ibcs77vJnz7ThUjwenhPq6zHUvBARND/ykBYIgxAAqABQDqAfwA4DbaZouD9emqKiILisr4xxjVP2aLX7lwUAlQqVUBI+PQpxKFpESJKPq2GR2IVYpgc3tRaxSitwkLc52OFDbboNS2qUYCIBzbeaBnW61ocFkh0IiRrvNjRiVBB4vBavLB5VMhBiFBHa3D80WF+JUUmjkYthcXrTbPdAr/QPaR9NwenzwUoDL44NW4e+PSiqGzeWBWiaBl6Lg8lJQSsXosHuglIqglIjgpihYnF4MjVeBBoEWa1f/GGXH4H5TFI3yBhMaTU4k6+TIS9EJYnRc9Ij9m2+sMuPrQu8x33PrCSm53eHG0UYLqyqbn6yJSIyOQW9Vafu7fW/vX2/bXyL0epwC3f9WiqJx1mhDi8WFdqsHCpkIcgkBqUgEk8NfaqSRi0ASBORivz1qNrswSCcHTdOweyjY3T5oFWI4PT7EKCTwUYxqrwwyMYlWmwsKiRhmpwfxahnykrSoNztR226DTiEBTQMtVhfUMjFSdHKIRQQaTS7Y3X6VXEaxnKJonG61cWx3Wox/juiL5xjJmIiScdMf6PVYjXalbAFRgz6xq2VlZXjsg8Nslmv7meN4+paRKCoqivjcbrebQ5tw7NgxvHncA/2QLlG30/s/hViXiMEjxl7Q52g/h9PpQNKQrkxiU8MZbF40o0f3OYrR67Fqc7hQ3mhl7WpeshoqhYxdwzaYnIhXy6CUkrC7KbRaXUjRyeHx0TDa3YhTStFmc0MmIaGRiSEREbC7fXD7aDjcPihlIijEItjcHmhkEvhoGq1WN3QKCTQyMSwuL5K0cgzSyHG00Ywms1/hPT9Zi3MWJ8ffq+uwo8kcOvcLiAr0eqxG+/oq2tcw0d7/HvjlEQ+qSPyqBLUcIhJoNF/ccRvp73M4PDjSaIbR7vHHv1weqGViiEgSDSYnEtQyeCgfkjQKyKQEGowu2Dz+mFRLZyxLKSHh8tGwufy2eHCMAhUtFhjtHjg9PgzRq5CVoAZF0TjWYEKDyQW1XIRBOgWS1TKcaLbA4vLC7vZhkE6O4UlaNFgcaLe6YXX7YHN5kaCWQUQCWoWUE9OqbrHiTJsNMokISikJmUgEk9MDm8sHvVoKiqahV8nYGGHgM7A4PXB7abRY/z97Zx4fVXn9/88z+0wyk30jIQkhCUtCwhIRW+CroBYtCiqgtcWlWLqoUOniUpGvoLaoxUrVqtW6tl/B2rr9lKogVatWwYUdEgKJCdnX2bf7/P6YuZeZzJ0wWSeTnPfrlRfhZu69z8yc+yznOedznDBolDDpVJLMRZxWCZdXgEahgNnphlqplHyAgWvik23WIL9jkkELlRLSunR8ksG3To3g+xav1251QqNUoM3qCvI9nsFOwv4xJmQlOOcexthNAP4FQAngL705hsOhUDAUpMWjIC1eOtbz/5GiUilQPj5J9m8T0+MxMT30mnL3CvfaaNGzLXKfmULBUD4+CeXje55NDBaiffX3M5b73vqCQa/B7Akp/bs5gES9DrMn9H/Qj/b5A/38Bnp+LNHbe1UoGPJS4pGXMryfw0Rd7/2qXHsUCibbHw/W9xiJTYwluxluBtonEESsIWrsivq89fs/RuLE6ej/yD76EHWMif4Rp9di9oTQ1PCBzmH7Q0V+ctD/C3TBY2l+ajzyU2lsHavE+vwq1ucwsd7+4ezT5Gx1qPuuSN+fXq/uk39gfFJk7S7NTgw5plAwlI1PQlmPNs3ISw55rW+t2fs9FAqGwgwjCjMiy4Qe7P6itz6o57o0ku97qPq0mHAOAwDn/C0Ab0W7HQRBEARBEAQx0knIypecn10NJ6PbmBhATsu4rKwMGk3kmVMEQRAEQRCxSMw4hwmCIAiCIAiCCEVORiIWpONGEubmOvy+1o6MI75K6h11x3Hz+YcwdapPiuNMRe9EAh3KPb+XSP7e8zVnYjCuQRAEQRDE2IacwwRBEARBEAQxggiM9O1qOIlDh3qfsh86dAi/+7/3YEjOBAC0nTgIU95UMOaTlrO0noLKYUe7wSCd0/NYX/8/Kq8Rf1oyztbRhLufO46kzAPSZ6rQG5GUmSv7fwCwtTfitu+dLzmUe34vZ/q73GvORLhrPL9pzVjRTyYIgiAIYoDEREG6/sAYawFQE8UmpAJojeL9BwK1fWC0cs4XRfriIbbVaH8edP+Re/+RZKfRItrfz1Ax2t7XYNrqSPxsRlqbqD29M1z96kh73wOB3svIg2zVRyy3HYjt9kfadrLV01D7o8uZ2h+xrY7QdVWsfz89GW3vBxic9xTWTketczjaMMb2cM5jcrue2j56iPbnQfcf2/cf6YzWz2e0vq/BYCR+NiOtTdSe3hmu9oy09z0Q6L2MbmL5M4nltgOx3f5otD2WPy+A2h9tYr39Z2K0vb/R9n6AoX9PiqG6MEEQBEEQBEEQBEEQBEEQBDFyIecwQRAEQRAEQRAEQRAEQRDEGIScw0PHk9FuwACgto8eov150P3H9v1HOqP18xmt72swGImfzUhrE7Wnd4arPSPtfQ8Eei+jm1j+TGK57UBstz8abY/lzwug9kebWG//mRht72+0vR9giN8TaQ4TBEEQBEEQBEEQBEEQBEGMQShymCAIgiAIgiAIgiAIgiAIYgxCzmGCIAiCIAiCIAiCIAiCIIgxyKh1Di9atIgDoB/6icZPnyBbpZ8o/fQJslP6ieJPnyBbpZ8o/vQJslX6ieJPnyBbpZ8o/vQJslX6ieJPxJCd0k8Uf8Iyap3Dra2t0W4CQUQE2SoRC5CdErEC2SoRK5CtErEC2SoRK5CtErEA2SkxEhm1zmGCIAiCIAiCIAiCIAiCIAgiPOQcJgiCIAiCIAiCIAiCIAiCGIOQc5ggCIIgCIIgCIIgCIIgCGIMoop2A4iRgSBwnGyzoqnbgQyTDvkpcVAoWLSbRRBEP6DnmYgVyFZHDvRdEMTogJ5lgiBGEtQnEcTQMljPGDmHCQgCx46DjVi3/Ss43AJ0agW2rJiORSWZ1HETRIxBzzMRK5CtjhzouyCI0QE9ywRBjCSoTyKIoWUwn7EhlZVgjCUyxv7OGDvCGDvMGDuHMZbMGHuXMVbp/zcp4PW3M8aqGGNHGWPfCTg+izG23/+3rYwx6kkGkZNtVsmYAMDhFrBu+1c42WaNcssIgugr9DwTsQLZ6siBvguCGB3Qs0wQxEiC+iSCGFoG8xkbas3hhwHs4JxPBlAO4DCA2wDs5JwXAdjp/z8YY1MBXAWgBMAiAI8xxpT+6/wJwGoARf6fRUPc7jFFU7dDMiYRh1tAs9kRpRYRBNFf6HkmYgWy1ZEDfRcEMTqgZ5kgiJEE9UkEMbQM5jM2ZM5hxpgJwHwATwMA59zFOe8EsATAc/6XPQdgqf/3JQBe4pw7OecnAFQBmM0YywJg4px/wjnnAJ4POIcYBDJMOujUwaagUyuQbtRFqUUEQfQXep6JWIFsdeRA3wVBjA7oWSYIYiRBfRJBDC2D+YwNZeRwAYAWAM8wxr5kjD3FGIsDkME5bwAA/7/p/tdnA/gm4Pw6/7Fs/+89j4fAGFvNGNvDGNvT0tIyuO9mFJOfEoctK6ZLRiXqlOSnxEW5ZaMXslViqBjM55nslBhKyFZHDjQPGD7IVomhhPpVYixCtjpyofnFachOiaFgUMd9XzDu4MMYqwDwKYBvc87/yxh7GEA3gJs554kBr+vgnCcxxh4F8Ann/EX/8acBvAWgFsBvOefn+4/PA/Brzvklvd2/oqKC79mzZyje2qhErHDYbHYg3UhVRAdInz44slVisInweSY7JaIO2erIgeYBgwLZKhF1qF8lRhlkqzHOGJpfRPymyE6JwaSPz1jYP6iGpnkAfBG+dZzz//r//3f49IWbGGNZnPMGv2REc8DrxwecnwPglP94jsxxYhBRKBgK0uJRkBYf7aYQBDFA6HkmYgWy1ZEDfRcEMTqgZ5kgiJEE9UkEMbQM1jM2ZLISnPNGAN8wxib5Dy0EcAjA6wCu9R+7FsBr/t9fB3AVY0zLGJsAX+G5z/zSE2bG2BzGGANwTcA5BEEQBEEQBEEQBEEQBEEQRD8YyshhALgZwF8ZYxoA1QCuh88hvZ0xtgo+yYjlAMA5P8gY2w6fA9kD4EbOudd/nZ8CeBaAHsDb/h+CIAiCIAiCIAiCIAiCIAiinwypc5hz/hWACpk/LQzz+nsB3CtzfA+A0kFtHEEQBEEQBEEQBEEQBEEQxBhmyGQlCIIgCIIgCIIgCIIgCIIgiJELOYcJgiAIgiAIgiAIgiAIgiDGIOQcJgiCIAiCIAiCIAiCIAiCGIOQc5ggCIIgCIIgCIIgCIIgCGIMQs5hgiAIgiAIgiAIgiAIgiCIMQg5hwmCIAiCIAiCIAiCIAiCIMYg5BwmCIIgCIIgCIIgCIIgCIIYg5BzmCAIgiAIgiAIgiAIgiAIYgxCzmGCIAiCIAiCIAiCIAiCIIgxCDmHCYIgCIIgCIIgCIIgCIIgxiDkHCYIgiAIgiAIgiAIgiAIghiDkHOYIAiCIAiCIAiCIAiCIAhiDELOYYIgCIIgCIIgCIIgCIIgiDEIOYcJgiAIgiAIgiAIgiAIgiDGIOQcJgiCIAiCIAiCIAiCIAiCGIMMqXOYMXaSMbafMfYVY2yP/1gyY+xdxlil/9+kgNffzhirYowdZYx9J+D4LP91qhhjWxljbCjbTRAEQRAEQRAEQRAEQRAEMdoZjsjh8zjn0znnFf7/3wZgJ+e8CMBO///BGJsK4CoAJQAWAXiMMab0n/MnAKsBFPl/Fg1DuwmCIAiCIAiCIAiCIAiCIEYt0ZCVWALgOf/vzwFYGnD8Jc65k3N+AkAVgNmMsSwAJs75J5xzDuD5gHMIgiAIgiAIgiAIgiAIgiCIfjDUzmEO4B3G2F7G2Gr/sQzOeQMA+P9N9x/PBvBNwLl1/mPZ/t97HicIgiAIgiAIgiAIgiAIgiD6yVA7h7/NOZ8J4CIANzLG5vfyWjkdYd7L8dALMLaaMbaHMbanpaWl760liGGCbJWIBchOiViBbJWIFchWiViBbJWIFchWiViA7JQY6Qypc5hzfsr/bzOAfwKYDaDJLxUB/7/N/pfXARgfcHoOgFP+4zkyx+Xu9yTnvIJzXpGWljaYb4UgBhWyVSIWIDslYgWyVSJWIFslYgWyVSJWIFslYgGyU2KkM2TOYcZYHGPMKP4O4EIABwC8DuBa/8uuBfCa//fXAVzFGNMyxibAV3juM7/0hJkxNocxxgBcE3AOQRAEQRAEQRAEQRAEQRAE0Q9UQ3jtDAD/9PlzoQLwN875DsbY5wC2M8ZWAagFsBwAOOcHGWPbARwC4AFwI+fc67/WTwE8C0AP4G3/D0EQBEEQBEEQBEEQBEEQBNFPhsw5zDmvBlAuc7wNwMIw59wL4F6Z43sAlA52GwmCIAiCIAiCIAiCIAiCIMYqQ12QjiAIgiAIgiAIgiAIgiAIghiBkHOYIAiCIAiCIAiCIAiCIAhiDELOYYIgCIIgCIIgCIIgCIIgiDEIOYcJgiAIgiAIgiAIgiAIgiDGIOQcJgiCIAiCIAiCIAiCIAiCGIOQc5ggCIIgCIIgCIIgCIIgCGIMQs5hgiAIgiAIgiAIgiAIgiCIMQg5hwmCIAiCIAiCIAiCIAiCIMYg5BwmCIIgCIIgCIIgCIIgCIIYg5BzmCAIgiAIgiAIgiAIgiAIYgxCzmGCIAiCIAiCIAiCIAiCIIgxCDmHCYIgCIIgCIIgCIIgCIIgxiDkHCYIgiAIgiAIgiAIgiAIghiDhHUOM8Zyh7MhBEEQBEEQBEEQBEEQBEEQxPDRW+Twq+IvjLFXhr4pBEEQBEEQBEEQBEEQBEEQxHDRm3OYBfxeMNQNIQiCIAiCIAiCIAiCIAiCIIaP3pzDPMzvfYIxpmSMfckYe9P//2TG2LuMsUr/v0kBr72dMVbFGDvKGPtOwPFZjLH9/r9tZYwxuXsRBEEQBEEQBEEQBEEQBEEQkdGbc7icMdbNGDMDKBN/9/909+EeawEcDvj/bQB2cs6LAOz0/x+MsakArgJQAmARgMcYY0r/OX8CsBpAkf9nUR/uTxAEQRAEQRAEQRAEQRAEQfQgrHOYc67knJs450bOuSrgdyPn3BTJxRljOQC+C+CpgMNLADzn//05AEsDjr/EOXdyzk8AqAIwmzGWBcDEOf+Ec84BPB9wDkEQBEEQBEEQBEEQBEEQBNEPwjqHGWMGxpg64P+TGGO3MMYu68P1/wDg1wCEgGMZnPMGAPD/m+4/ng3gm4DX1fmPZft/73lcrs2rGWN7GGN7Wlpa+tBMghheyFaJWIDslIgVyFaJWIFslYgVyFaJWIFslYgFyE6JkU5vshI7AOQDAGOsEMAn8BWmu4kx9rszXZgxthhAM+d8b4RtkdMR5r0cDz3I+ZOc8wrOeUVaWlqEtyWI4YdslYgFyE6JWIFslYgVyFaJWIFslYgVyFaJWIDslBjpqHr5WxLnvNL/+7UA/o9zfjNjTANgL/xawb3wbQCXMsYuBqADYGKMvQigiTGWxTlv8EtGNPtfXwdgfMD5OQBO+Y/nyBwnCIIgCIIgCIIgCIIgCIIg+klvkcOB0bkLALwLAJxzF4JlIuRP5vx2znkO5zwfvkJzuzjnPwDwOnzOZvj/fc3/++sArmKMaRljE+ArPPeZX3rCzBibwxhjAK4JOIcgCIIgCIIgCIIgCIIgCILoB71FDu9jjD0IX5RuIYB3AIAxljjAe/4OwHbG2CoAtQCWAwDn/CBjbDuAQwA8AG7knHv95/wUwLMA9ADe9v8QBEEQBEEQBEEQBEEQBEEQ/aQ35/CPAKwFkAvgQs65zX98KoAH+3ITzvluALv9v7cBWBjmdfcCuFfm+B4ApX25J0EQBEEQBEEQBEEQBEEQBBGesLISnHM75/x3AE5wzr8OOP4xgOThaBxBEARBEARBEARBEARBEAQxNPSmOSxyrcyx6wa5HQRBEARBEARBEARBEARBEMQwElZWgjH2PQBXA5jAGHs94E9GAG1D3TCCIAiCIAiCIAiCIAiCIAhi6OhNc/hjAA0AUgH8PuC4GcC+oWwUQRAEQRAEQRAEQRAEQRAEMbSEdQ5zzmsA1AA4BwAYY6aA15sAtA956wiCIAiCIAiCIAiCIAiCIIghobfIYQAAY2w1gE0A7AAEAAwAB1AwtE0jCIIgCIIgCIIgCIIgCIIghoozOocB/ApACee8dagbQxAEQRAEQRAEQRAEQRAEQQwPighecxyAbagbQhAEQRAEQRAEQRAEQRAEQQwfkUQO3w7gY8bYfwE4xYOc8zVD1iqCIAiCIAiCIAiCIAiCIAhiSInEOfwEgF0A9sOnOUwQBEEQBEEQBEEQBEEQBEHEOJE4hz2c83VD3hKCIAiCIAiCIAiCIAiCIAhi2IjEOfw+Y2w1gDcQLCvRPmStIkY1gsBxss2Kpm4HMkw65KfEQaFgI+Z6BDFQPB4BBxu60NDlQFaCHiVZJqhUkUi8EwMhlvqCWGorMTYYaTY50tpDDA4j5XsdKe0gCIIY7cR6fxvr7SdGNn21r6G0x0icw1f7/7094BgHUDAoLSBGPINpgILAseNgI9Zt/woOtwCdWoEtK6ZjUUlmv6452NcjiIHi8Qh49et63PnqAckm71laiqXl2cPmIB6Lk5hY6gtioa1j0YbGMiPNJgWBY9fRJuyr64LAASUDpuUkYMGkDLLDGGak2BnZF0EQxPAwUvr9/kLjBTGU9PX5kHv9I1fPwISUeDSbB75mO6NzmHM+oV9XJkYFg92hn2yzStcCAIdbwLrtX2HymnkoSIsfluuR04MYSg42dEmOYcBnk3e+egBF6fEoH5805PeP9UlYfxnsvkVkKPqLoWrrYDFWbWgsM9JssrbdiuoWK578oFqywXUXFKMwzYr81Og/I0T/6K+dDXY/XNtuRWWTJci+1i4sQmFaPNkXQRDEIHKyzYrNOw5j1dwCMH+3vXnHYUzONI6IOe+ZoPGCGEr6Oi/q+fokgwaVTRbc9LcvJfvcfEUZvlua1a+gtDOewRhbzhgz+n+/kzH2D8bYjD7fiYhJwhnsyTZrv67X1O2QriXicAtoNjuG5Xqi0+PirR/ie3/+Ly7e+iF2HGyEIPB+3Z8getLQJW+TjV39s/G+cqJV/pk90dq/ZzZWGOy+BRi6/mIo2jqYDHa/T4x8RppNNpud2PLusSAb3PLuMbSYnWc4kxjJ9MfOhqIfbup24uGdlUH29fDOSjR1k30RBEEMJm1WJ66syMXTH1XjkV1VeOrDalxZkYt2a2z0tzReEENJX+dFPV9/+cycEPu89ZV9+Li6rV/zpEjcyes552bG2FwA3wHwHIDHz3QSY0zHGPuMMfY1Y+wgY+xu//Fkxti7jLFK/79JAefczhirYowdZYx9J+D4LMbYfv/ftjLGKHRpmBjsBWOGSQedOtjsdGoF0o26YbkeOT2IoSYrQS9rk5kJ/bPxvlLTbpV9ZmvbR7eND3bfAgxdfzEUbR1MRpqjkBh6RppNdtndsjbYaXdHpT3E4NAfOxuKftjq8sjal83l6fc1CYIgiFA0SgW27gp2Xm3dVQm1MjZqsdB4QQwlfZ0X9Xw9Y5C1zz017f2aJ0XyVHr9/34XwJ84568B0ERwnhPAAs55OYDpABYxxuYAuA3ATs55EYCd/v+DMTYVwFUASgAsAvAYY0zpv9afAKwGUOT/WRTB/YlBYLAXjPkpcdiyYrp0TTFdOT8lbliuR04PYqgpyTLhnqWlQTZ5z9JSlGQlDMv94zQq2WfWoIlEYj52Gey+BRi6/mIo2jqYjDRHITH0jDSbNOnUsjZo0qmj0h5icOiPnQ1FP5yXHCdrX7nJI6MPJgiCGC3YXN4wzlVvmDNGFjReEENJX+dFPV+vZJC1T6+Afs2TIvEW1DPGngBwPoDNjDEtInAqc845AIv/v2r/DwewBMC5/uPPAdgN4Fb/8Zc4504AJxhjVQBmM8ZOAjBxzj8BAMbY8wCWAng7grYTA0Q0wJ7ak/1dMCoUDItKMjF5zTw0mx1INw5MO66v1xOdHoGDFDk9iMFEpVJgaXk2itLj0djlQGaCDiVZCcNWjC7DpMXahUVSiomojZVh0g7L/aPFYPctwND1F0PR1sFksPt9YuQz0mxyrPZjo53+2NlQ9MMTUuX7uAmp1McRBEEMJuH68AxTbKy9abwghpK+zot6vj7TpENBWjxufWWfZJ9rFhRh255aXDEzu8/ticQ5vAK+SN0HOeedjLEsAL+K5OL+yN+9AAoBPMo5/y9jLINz3gAAnPMGxli6/+XZAD4NOL3Of8zt/73ncWIYGIoFo0LBUJAWP2gi9H25Hjk9iOFApVKgfHwSyscP/71zk+NQlBGP1fMLIHBAwYCijPgxscM92H3LUPYXg93WwWSkOQqJ4WEk2eRY7sdGO321s6Hoh6mPIwiCGB5ife1N4wUx1PR1XtTz9TmJBiQZNNhT0w6vAGzbU4tbF03p1zPGfAG+EbyQMQOAqQBqOOctfboJY4kA/gngZgAfcc4TA/7WwTlPYow9CuATzvmL/uNPA3gLQC2A33LOz/cfnwfg15zzS2Tusxo++Qnk5ubOqqmp6UsziTGCWPV6CDv4M16MbJUYSiK0cbLTCBiG/oI4M2SrY5AYffbIVoeAGLWFkQ7ZKhErkK3GOGOoD+/1TZGdEkNFH5+x8H8I5xxmjF0KYCuAdgB3AngUQBOAfAC3cs6f60uDGWMbAFgB/AjAuf6o4SwAuznnkxhjtwMA5/y3/tf/C8D/AjgJ4H3O+WT/8e/5z/9xb/erqKjge/bs6UsTCWKw6NNoR7ZKRAmyUyJWIFslYgWyVSJWIFslYgWyVSJWiNhWyU6JKBLWTnsTwdwE4EIAPwawHcBCzvkcAGUAfnnGOzKW5o8YBmNMD59m8REArwO41v+yawG85v/9dQBXMca0jLEJ8BWe+8wvQWFmjM1hjDEA1wScQxAEQRAEQRAEQRAEQRAEQfSD3jSHBc75MQBgjJ3gnFcDAOe8mTHmieDaWQCe8+sOKwBs55y/yRj7BMB2xtgq+CQjlvuve5Axth3AIQAeADdyzsUylj8F8CwAPXyF6KgYHUEQBEEQBEEQBEEQBEEQxADozTmsYIwlwefYFfy/iyHIvUUcAwA45/sAzJA53gZgYZhz7gVwr8zxPQBKz3RPgiAIgiAIgiAIgiAIgiAIIjJ6cw4nANiL0w7hLwL+FlkVO4KIAqIgd1O3AxmmUS16TxCy0DMw9NBnTBBDCz1jxEAg+yEIghgZUH9MEANnOJ6jsM5hznn+oN6JIIYBQeDYcbAR67Z/BYdbgE6twJYV07GoJJMGIWJMQM/A0EOfMUEMLfSMEQOB7IcgCGJkQP0xQQyc4XqOwspDMMZm9vYzaC0giEHkZJtVemgAwOEWsG77VzjZZo1yywhieKBnYOihz5gghhZ6xoiBQPZDEAQxMqD+mCAGznA9R73JSvy+l79xAAsGtSXEmGCow+Gbuh3SQyPicAtoNjtQkBY/aPchiN6IZvoUPQNDh/i9Hmsy02dMjDpGUton9WOjk+GyMbIfgiCIkQH1x8RYZLDnO8P1HPUmK3HeoN2FIDA84fAZJh10akXQw6NTK5Bu1A3K9QniTEQ7fYqegaEh8Hu9YV4BfcbEqCLa/VZPqB8bfQynjZH9EARBjAzSjfL9cVo89cfE6GQo5jvDNa8JKysRCGOslDG2gjF2jfgzqK0gxgTDEQ6fnxKHLSumQ6f2mbb4MOanxA342oLAUd1iwSfHW1HdYoEgUF1GIpRop08N5TMwlgn8Xl/ZW4c1C4pi8jOmfoyQI9r9Vk+oHxt9DKeNydnP5ivK0GZ1Ur9HEAQxjCgVwNqFwXPmtQuLoIzICzUyoLkz0Rf6O9/pzc6Ga17cm6wEAIAxtgHAuQCmAngLwEUAPgLw/KC2hBj1DEY4/JlC9BUKhkUlmZi8Zh6azQ6kGwcnbVEQOHYdbcK+ui4IHFAyYFpOAhZMyiAxfSKIkZA+FadV4MFl5bC6PIjTqBCnjaEZ2AhDTkqiocuBFz6twaq5BSjLNqEowxgTlZfldrIfuXoGJqTEo9kcfSkBInqMhH6rJ9SPjS6G08bEueCkm+ehtt0KpYLhSEM3fvf2EXTYXBFH8IwkqRWCIIhYpKHLgec/8c2ZGQM4B57/pAYzchORnzryZSXIB0D0lf7Md3qu0fJS9Ni0ZBrUSibNP0QfV1O3AwaNEi6vgJNt1kGdm5zROQxgGYByAF9yzq9njGUAeGpQ7k6MKQYaDh9piL5CwVCQFj+oi43adisqmyx48oNq6d5rFxahMC0+JgY2YviIdjprTZsVh06Z8fDOyiBbzU2KwwTS9uoTvUlJNHQ58PRH1XhrzbyY0UzruZOdZNCgssmCm/725YiQEiCiR7T7rZ5QPzb6iIaNHW0yB80Z1ywowguf1mDd9q8w+Qx990iTWiEIgohF0o06dNhcePT9KulYLMlKkA+A6Cv9me8ErtGyEnS4siIXq1/YEzL/yE+Jw5FGM65/9vMhmZtEEoZh55wLADyMMROAZgAFA74zMeYYaDj8UKYknildpKnbKS1SxXs/vLMSTd3OAd+bGF0MRtrHQNKXTnXZZW31VJe9b2+EQG27FUcau3HDvALEa5W45fzimE5z77mTffnMnBBboQrSY5ORJuNA/djoY7htTG7OuHVXJb5/dq4UwdPX86l/JAiC6BtKBbDuguD587oLimNGVoJ8AERf6c98J3CNdvnMHGzdJb8+621uMhjyJ5FEDu9hjCUC+DOAvQAsAD7r852IMc9AJR+GKiUxkugQq8sje2+by9Pv+xKjk4Ha+UCjlcwOeVu1OLz9ej9jFUHg+KK2MyhS4PZFk3HTeYUoSo+PGSmJQHruZDOGESclQESHoZJk6i9Wp1fWNq1O6sdileG2sXBzxkyTDnkp+jNGLI9EqRWCIIhYo8XihFapwOr5BRA4oGCAVqlAq8UZE5G35AMg+kp/5juBa7Te1mecy/+t3erEkUbzgLOdzugc5pz/zP/r44yxHQBMnPN9Ed+BGJOE02kbiOTDUKUkhtuBCUw5zEuOk713bnLsRA0SkTNQncGB2Hkk9tgb4xL1sraalaDtc1vGGoHfu0GjxB3/3B/0Pfx2xxGsnl+AogxjTDoHxJ1s0b6UDCNKSoAYGfARUGclJU4ja5spcZootoroLz3H1Nn5KUO+8RBuzljbYcOmJdPOGLE80qRWCIIgYhGNUoHf7jgS0pduWz0niq2KHPIBED2JxE/QV19A4BoN6H19Jvc3tVIxIP+B1O4zvYAxtlP8nXN+knO+L/AYQfREjHy8eOuH+N6f/4uLt36IHQcb4fEIAwp170+IfiTh9b1Fh4hMSJW/94RUGhhGG+Hsty/2OpC0jkjssTemZppwz9LSIFu9Z2kppmYlRNyGsYggcHxY1YxDp7pR22ZDbbtd9nso9kcMxyLiTvZba+bhpdVn47IZ2SNKSoCIHmLBlVe/qsd/jrfhta/qsetoU9QqcgvgWLMguLr5mgVFEDACPNdEn+jLmDqYFeHzU+Jw32XTQmzo5T11UCvZGZ3TQyGDQRXvCYIYa4TLBLK5YiMTiHwABBA8fv+nqhXXP/tZv/0EcgSu0c4tTsXmK8pk5x/h5ibhnrNI/QciYSOHGWM6AAYAqYyxJADiLMoEYFyf7kKMKeQiHzfvOAwFAw41dA+o0uekDCMe+/5MxGlVyDBqkZscPqIz0vT8SKJDRlrKLTF0nGyzYvOOw1JVXQDYvOMwJmdGFi06UFmIdKO8PUZauEGlUmBpeTaK0uPR2OVAZoIOJVkJUKliRNwrStR1WuHxAseazRA4YNIqZb+HKZkmKBQsZqvY99zJzk2Oo36NGHEFV5INWuw60oj7l5XD7vTAoFXhuY+r8Z2SzGFvCzEwIs2GiWTsFASO2nYrmrqdsLo8yEuOw4RU+T5LoWCYmZsopTJzDrzwaQ06bC5kmM48ng72vI8K3BEEMRYx6lTIS9FjcVm2tK564+t6xGmV0W1YhJAPgJAbv8UCtw1djn5F6IrX7bmWFNdoMwWOadkJsjYXaI+ZJh08Xo5TXfZByXbqTVbixwB+Dp8j+IuA490AHu3TXYgRwXA5M5q6HUgyaHD5zBxpEEiP1+BEq7VPC8/A9qYbdTjRZsFNf/tSOv/3y6cDABq65N9PpAuSnqnW4aJDBiIVQPSNaDre2qxO3DC3AC0Wp7SRccPcArRbnRF99wOVhVApgQ2XlODuNw5K9rjhkhKo+jCHUqkUKB+fhPLxkZ8z1hBtrMvugiAATWYnBM5h0Cjxf5/V4urZebjjosm47+0jQf3ChNS4UbXIp36NAHwFV3YeDnXGzsxNiopzWK0CVlTk4td//1p6xjZeWgJ1JJUyiBFFm9WJtQuLkJ8SB4/AoWDANx22kDH1TGOnGN1e2WSRigPp1Arcf0UZshJ1SInThswVcpPjMDnTFNRX33fZNCiYbww4U389mP3jQOcGBEEQsQjnHLcumgxBAKxOD+J0KkzNmoxYSgSiuXLsMRBfQuC5WQk6dNncUoHyV/bWoaHLga27KrFqbgEefb+qX/UIwq0lL5ySgdoOW68yXKI95qfESddIMmiwdmFR0Pxo8xVlfc52CjvN5pw/DOBhxtjNnPM/9umqxIhjOJ0ZWQk6XHNOXpBxblpSiqf/cyKk0me4hadce9cuLEJxejzmFaeDMeBYUzesThdq2h1QKoCz8pJxToHvATrZZsWxJnPQQyzet+fDSzuCI4toO94MaiUsTk/IRoZeHZl3NpwsRFN3ZINGU7cTj/+7Sopc5hx4/N9VKEwrR15KZIOOxyPgYEMXGrocyErQoyTLRJHDAYg2tvtIA+ZMTJe0hcXv+offmoC/fHwCy2eNx5MrZ0GjUgT1C9UtFlrkE6MMAVfMDHbGblhcAkA445lDQVOXE4/urgrK4Hh0dxUKUsuRm0zPWKwgCBxtFheUCoZbesznWi2uIAftmQrAnWyzYl9dlzQ2i3//9Sv7sGpuAZ7+qDpkriDO7ybdPA+HG7txqsOGU512nGyzSnPGoR4bxUVmb3PS/JS4mMxEIQhieIjVbDUAcHsFmB0ebHj9dNDL3ZeWwO2NzvyCGP0MxJcQeG6SQRPi0wqMGBbnp/2J0A23YfzkygqsfmFPRO2uabOirt2Kh1ZMh0fg0KoU2HrVDFicHhxvsSI7UdfnfiKSGIwnGGNrAMz3/383gCc45+4+3YmIKoMZsXCmAcorQHqIxHutf+2AtLsi0lulz57tTTJooGTAD+bk4S7/4JKXoseGxSVoNrvg8Ai487X9uP2iKRA4wob9h3t4aUdw5DAYtjqQSVSn3R1ivw/vrERZTmSavXHaMOlTmsicy112N2ra7EHPitiuSPB4BLz6dT3ufPWA9Azcs7QUS8uzyUHs52SbFbuPNGDRtGz87K9fhHzXq+cXYHFZNlxeAQk6NcpzkwCc1puKdOPpTMTyZJ8YXSiYAne/eTDoWbj7zYN44Yezo9Ieq8uNH35rAtpsLimD44ffmgALVQePGQSBY399Jzxeji3vHpPtZ4sDinuGk/jKNOmkfrco3Ygkg0bqd8XriZW95eYKCgWDUgGc6rAhTqfGljcPBUXVXFI2bsj63TOloorvbzA2xGk8IYjRSbSDZgaKRwAe67HZ+9juKjxwRXl0G9YHqH+NLSLJRAr3fQaee/nMnBCfgBgx/PRH1eC8//UIwm2IH2noikjaUhA4DpzqBljo5ntusgGVTZ24YmZ2nz+7SJzDjwFQ+/8FgJUA/gTght5OYoyNB/A8gEz4Qk+e5Jw/zBhLBrANQD6AkwBWcM47/OfcDmAVAC+ANZzzf/mPzwLwLAA9gLcArOV8JNTTjh3OFJERKZEMUM1m+Xspe/ildGoF8lPicLzZglNdNmiVSlhdHuQmx6Hd5pSukZWgw8o5eQCAuk47bphXgHitEgwMP/vbF0ET7to2K7a8F/4h3rJiOnKTDKhusVAHP0IZqK0OdBJldnhk729xRFY4QQHgpvOKsP61087ZTUtKoWCR2ZhJp8aFU1Px/TkT0GF1IzlOjRc/PQGTTh3R+QcbuiTHsNj2O189gKL0eJSPT4roGqMZQeDosruwYEoWlIzh4atm4NFdldhX3w3A93kJHFAqgBnjE1EyLkE670yLfHHjKZJJZKxP9onRRbPZGSIH9creOjSbnVFpj0mngVIZXERDqWQwaSPrB4noEti/3TCvQHZMFTiCxnU5ia9Hrp6BQw3moGPrF0+F2eGGxenFK3vroFExTM004qYFhYjXKtFmcQb1vQDwRW0nLC5vyPzw1lf2YUKKAXa3cEYN4/4gt0DtOSf1ChiUDXEaTwhidBLrkjQWpxs/nl+Axu7Tcn0/nl8Aiys24gxFSaN9dV0DqptEDB+9+RICpRjkxsvAc8WN557XUSqAzVeUITtRhytmZvfLlyS3IV6Rl4CkOC22vHcgaK0pJ21Z02aFSsFgcXpww7wCfHC0GfOK02F3e8EBrDxnAsb1MZoZ6L0gnYpz7gFwFuc8cGtnF2Ps6wiu7QHwC875F4wxI4C9jLF3AVwHYCfn/HeMsdsA3AbgVsbYVABXASiBT+f4PcZYMefcC58zejWAT+FzDi8C8HZf3+xYJpKia3L0dHJwfuZJbLh7Tck0SccDJ/33/+swrqzIxdZdwRopeSl61LTZcfnMHGzbU4vV8ydKE/s1CwtDUgu37qrEA8vKZR/ismwT3lozD7lJBrxzuIkm0COY/tqqyEAnUeMS9bL3z0rQRnR/m8srOYbF+69/7QCevz6yCLxxSVqcPyULP35hr2SjGy8twbikyO7f0CU/IDZ0Oca8BrEgcLx9oAG/ePl06vzahUW4/tsT8Mx/TmBffTd0agUUDJiRm4Rz8pKlaOtwi/y1C4tgd3tRnG4E577I7Uj6mFif7BOji3EyclBrFxZhXELfJ5aDgVvwpaH2lPdxc0pDjQV69m9yY6qCAalx2qDN+gunZOCtAIkvzoHv/vHDoH5y05uHJOfqHRdNhlatxLqXv5bSP1f+5bOgvndqlhF3/HN/WCf1sWZLUKbN5ivK8N3SrEHJtAm3QBXnpPkpcfjvibYBB2/QeEIQo5fBCvCKFskGDY7JFLydkqmJdtMiYqQV7CXOTG++hDONlz3PlbvOvMJUgAHJMrUOIqXnhnheih4/O68oJKN1665KbFs9J+hcj0fA3tqOoLnLhsUlePyDKtS02aWNdJ26C7Nyk/vUvt4ihz8DMBOAlzE2kXN+HAAYYwXwRfb2Cue8AUCD/3czY+wwgGwASwCc63/Zc/DJVNzqP/4S59wJ4ARjrArAbMbYSQAmzvkn/vs/D2ApyDncJyItuiYiCBwnWq043NCNymYztu+pQ4fNhQfDOF/PFP2xZkER/uRPKSnLNqEowyhN+lfNLZAcw+L1bn1lH55YOQtf1HRAr1FicVk2NvlTAbMSdChKN+KGeQUAIKV2O9wC7C6PfFpigk7SdAvXIZDm28igr7bak4FOoianG3H/sjJUNVukHeKJ6fGYnGGK6P5tVpdsBF67zRVZ+7tcknSK2Pa7Xj+IF1edjUgCf9PitbLPQGp8ZM7l0YrHI+DAqS4c9UtCAL7vRUxvvmH+RPz6719j/eKpMOlUeHTXMdjnTpTdSRZJMmiQZtQGDc5PrqyIKJXpWJM5YjuldDZiqPFy4KXPa4NS2V76vBaz85Oj0h6Xh8u2Z1p2ZPI+RHQJ7C9f2VuHW84vxkPvHQtaWKfEqVHfZcf+ui44PAI+Pd6CNQsnQa1kUj8XznEqRvO0Wl3Sgv3ymTkhNrN5x2Hcs3QaHrpyOhjkF3k6lTJoTLj1lX1IMmgwtzB1wP1suAVqUQRyGn3RL4x15xFBEOEZjD4imlhc3pgez5u6nbLtj1bBXuLM9OZLCJxXZCXopPV6i8WJ/JS4oHNf2VsXUuRtw+IS/PLvX0tO2IHIQKUZNdi2eg5sLi8MGiV2HmmWHcttrmDX6yGZLOHHP6jCLy6cjGNNZgDAkx8cx8ZLS3GyzdqneUBvzmHxHf4SwPuMsWr///MBXB/xHQAwxvIBzADwXwAZfscxOOcNjLF0/8uy4YsMFqnzH3P7f+95XO4+q+GLMEZubm5fmjjq6UvRtd7SpyubzSEDVF6KHnq1Ep8cb5Um9ItKMpG9eg52HmmGV4CUen2s2YK3/E6ST463Bk3yA3G4BXx+sgNPfVjtS8mHU3IMr5yTh18FFM0R29Zh8znlei5C1iwowpqXvsSti6YgyaCWvVe71YkjjeZhiygmWw3PQAsEDnQS1WC2w+kWgnaINy0pRYPZHlFBuOQ4tWwEXpIhsnToxjCRv43djjBnBKNWMdx9aUlI4Qetqu92PBrsVBA4atss2HeqOyQSUew7BO6rpvzY92dCr2b47VtHsa++GwdOhd9JBoDlFTkhg/OemvaIUplumFcQkZ1SunBkjAZbjSYWpzskg2fNgiKYndFJ+3R5vLLtcXojk/cZyYwFW80w6YK09zk4HvneDLRbXdBrVOiwOtFh8+Cu1/cGLbjWv7ZfWnBtvqIMpVkm2X5SFJYT+On5o1GnlLWZg6e68If3KvGbi6dg3QXFkv6xLyunFA+8c0S6pzgm7KlpR06SfsCO1Ug2uwe6IS5+3kPhPBoLtkqMDkazrQ5GHxFNwo3nrhgZz91e+fa7+9H+0WynI4nefAnieJlk0GDlnDzpe33qw9NFbQPPzTTp8O2JKXjvSDMK0434vX/OAAyuDBTgm9OcaSz3OZZtQa/JStDhyorgotJrFvgyW9tkJCl6/ex6+VsaY2wdgOkAngCwC8AbAP4Mn6M3Ihhj8QBeAfBzznl3by+VOcZ7OR56kPMnOecVnPOKtLS0SJs4ZhCLrs0pSEVBWnxYx0K49Onvn50LnVqJe5aWQqf2mU5eih43+52vH1W14dWv6vGfqlZ4PAIS9Grkp8ThzX31uHxmDtYsLMSfV1YgJ0GP6hYLFIxJ1xH/FREn/2JK/pSsBOjUClw+Myckynjrrkosr8jBpiWl+OOuSjz78Uncv6wcaxYWYtXcArzwaQ1q2uxYt/0rGDQq2XuplQrZaL+TbdbB+wICIFvtnUhtVY78lDg8cvUMrFlYiJsWFGLtwkI8cvWMiCdRzd1OWVmI5u7ItDcVjMkWtItUczjdpJW10XRjZJG/nJ8u/HDTAt8z8NjuKgj9UGmPdTsVBI6dR5rQYnUiUa+Wsg+A4L5DwYBMkw52lxvrtu8P0h9uNvuc8uLkPLDPKk43hjiCxYE9ELlUplf21mHNgqKg68lN9sNlOwxV3xSrxLqtRhu9WoldRxpx/7JybL58Gh5YVo5dRxqhU0dWSHOwMenUsmO9cRRoDo8FW81NMuDmBUV4+qNqPLKrCn94rxIdNjde/LQGRxrN0KqUsLk8SDL40oodbl8BxKvOysWN5xXihnkFqG6xoN3uwv1XlAX1k2sWFOEfX/hiRpTsdH+bnWiQtZlxiQY43ALufeswvALH2oVFePwHM/HnlRXotDnh8vCg1y+vyIFXgNT3DwRxgfrWmnl4afXZeGvNvJCNvUhecybkxqfBcB6NBVslRgdnslWxoPAnx1tR3WKB0J9JcRTRqBhWz/fN61fPL4CmHwEf0SLceB4fI+O5VqWUbb9W1ff5EfWpw0c4X4I4Xi6vCPUpieurwHPzU+Ph9ArwCoDd6cEl5dnICpBcE9eKPfsYj0eQ7XNOtlmxecdhaZ1+w7wCbN5xGAaNCm98XR+yNly/eGpQ3a6TbVac6rT7JS91uPG8Qtxx8RRZG/V4OTxe3qf+rrfIYSWAeAQ7Z0W3szGSizPG1PA5hv/KOf+H/3ATYyzLHzWcBaDZf7wOQKAiZg6AU/7jOTLHiX4iCBy17VY0dTtlC3CES0/LNOlw52sHkGTQSFWmxyfqsWbblyE7avdeNg1tZgc0KgV+8j+FuPuN01GM9yz1OXFdHt8k/aXPa7FmQVHIjtwLn9ZI9z7Y0I31i6eGbdvkTBMe310lOXWqms3YurMq5HVur1d299Xm8lJK3ghiIGn0voJjwRGi9142DYLAI7pGm9Ulawtt1shkIdps8udHKivh8nplI38j3aG2ubyoabPj0ferQo6PNb5pN8OoU+JEiw11nXbZ7yU32QCNkuHpj6owOSsRAHDjeYVgzOd4yDT5JgByu9BcZof3ja/rce9l0/Cbf+7vNZWpocuBFz6tCZLakbNzShceHEiao3e8goArZgZHHWxYXAJBiI7Gb4vFKd8PW6JTIG84iVVbDWy3QaMMyap45P1KrJ4/Udqk61nUM8mggUmvDsq6STfpUJplwqq5BdCqFChKj8fvdhyWioAmGzRSNPCJVquszZxstUq/u70cKgXDz7ed1vhbv3gqqpotcHl9m3a5SQb88f3KflX5lkNcZPbWX0fymjPdYyAZVwQxmon1DKyTbVbc9LcvQ6IJ34oRTfFw66qOCNdV0SbcfKRlDMxHRgs951UXTskIWb8Bvu+1ps0aNH4KAsepTgee/ig081Sci6TF60L6GNHf1VN+os3qlI1E51zA2oXFeHjnMayaWwClApJ/a2JanCRh0mZ1ojTbiN9ePg2NXQ48vLMybE2F6lYrTrZZkWHSRdxX9OYcbuCcb4z8Yw+GMcYAPA3gMOd8S8CfXgdwLYDf+f99LeD43xhjW+ArSFcE4DPOuZcxZmaMzYFPluIaAH/sb7vGMqJT+OCpbtS224Im4IGDZFaCDmsWFkqRhq/s9ekN13b4QtgbuhzYurMKOrUCf/r+TCwuyw7ZrfjNP/f7DduLJz84GvS3O189gCdWzkJjpwMWpwffn52LiRnxeGjFdHg5x7Ems/TAAWIUMUdOkg5F6fFBhejEvyfHqXGs2SL9f0qYVMTkOC1m5iZj8pp50gLG5RWgUSpjWs9ppDFQ5+5AqsIeauiSHHPAaXssSotDWQSivUatStYW4rW9dZenSTFo5G3PEFnhBZ1Kib0nW/GX685Cq8WJtHgt/vlFLQpS8yI6P1x6aYZpbNlyl92BmnYHlAqGu14/GFbGYXySHkcbzXjnUCuWzBgfIgkyKdOE3GSf/fZcwAsCx+YrynDrK/skR8Oti6agqcuOF1edDbdXCLL/nt9NQ5dvstHbBD/WteZGArG+MBwOlAol7n4zWOv87jcP4rkIC2kONunGsamdHqu22nPcnpplRJJBI83jshJ0+MWFk6XNB+B0ZMuquQV49P0qXwZYj+yOTW8ewlPXVEiLso2XTsVti6agscuOgvR4tJidmJSkx1+unQXGFLI24/ScLiqTnxontUFMwwz8rNddUIykODV+deFkcA7ZTeWR6rwfqIOZIEYrsV6wsanbIVvLJFaCBJLj5NdFSXGxUZAuw0jz8FgmcF6VZNBgeUUOitONGJ9skP1ev/ymE3a3IM27TrRapXUeEDx3efojnxSFUoGQPubOVw9I8xuHW8DmHYeRnahDp80Np8crzZHE6327cA5m5iZiyfRsCBzwCsCmNw+hw+aSbM3h8MDl4ei2e6FXKYMyleXei0cQpEyowXAOD3Sm820AKwHsZ4x95T92B3xO4e2MsVUAagEsBwDO+UHG2HYAhwB4ANzIORdD3X4K4FkAevgK0VExul4Ijt5QweX1ItmgxYk2C/bVdQFAkINVHCSzV89BSVYCDjWYQypyFqTFobLJgpsWFAI4XQQuTquCUiGvGTwh1QCtSin7t701HZKD+Zbzi9Ha5YDAFHj831W4siIXHf4oS51agfsum4bkOBXqOhx48oPjIVHGd19aguZuO9YuLEJOkgE2pwdNXXbcd9k03CETvadQMOSnxOFIoxnXP/u55NS5Z2lpUGGpWNJzGkkMdHE70Kqwp8Jo9jZ0OVE2PsxJAWjVyhBdwnUXFEMfYXq11eWWjYS3ujwRna9WMszKT8UP/bYp2nikKWT5KXH4/fLp+MXLpz//3y8fW7bcaXfg/cOtuP2f+3H3JSVwuE/LOPTsO2parfjTv6uhUyuQk6DHL7Z/HTQJP9rYjalZRlnbUygYxiXqsGpuAYw6JYw6dYjdnz0hJSSVqS+6cbGuNTcSONEqvzCcdPM8TEyP3sJqJDmZWsNExrRGKTJGfD57ZlDoNb2pocU+I9FWI7HTcOP285/UIC1egytn56KqWb4IJ/NLQ0xMi5f9e2O3Q+q7k+K0+N2Ow7iyIhc/fmGvNH/7yf8U4vF/V4X08WIbxLlmY+dpnT45mbIt7x7D6vkF0vy059yl5/wmL0WPTUumBRXRGwmOYoIgThPrGVhZCTr89H8K0Gp1SUEzP/2fAimzbaTTZZdfF3XZo1PToK+UZJqw8dJS3PX6aR/BxktLUZoZWaFyIrqIm0M9NYblfD+BdaySrz8LNqcXTq8g239MyzbhrTXzkJ8Sh6/rOnD/snLYnR4YtCr8+YPj2FffLW3miJvRVz75qWz0scMtwOX13SM/JS7If3XfZdOgVAAnWy347GQH7vJLX65ZWCi1S26Ne9uiyUiOU+P5T072KROqN+fwwj598j3gnH+E8A5m2Wtzzu8FcK/M8T0ASgfSnrFCuGJyu4404sfzC1GcboRBowyK6AB8Rv5hZSs6bG5Ut1hww7wCyQH88M5KPPGDWXjk/SokGTS45pw8/ObiKVApGVQKhrPykmR3K8Yl6NDt8Mj+zW//cLgFPPTeMfzl2gr88Lk9SDJowBjwwLJy2F0eGHVqPP3Rcfz03CIpokRMxVYqgHMKUsC5gKpmK0x6dVChuj9cOR3/7+Z5aLH4UuxykwxBKY+BC7CaNjv+uKsS21bPgd3tpZS8ATDQHfrGLgd2Hm4M6mSf+7gaM8YnRuQcTjCoZW3OpI8s8tekV6AoIw5PrpyFDqsbSXFqeLkAoy4yp4ROrcK2Paer2nIObNtTi99dXhbR+VanV3KIAL7Pb8PrB/GXaysiOl8QOAQuYPX8AggcUDBA4ELEshqxjCBwVLd2o83iwe3+gdXgjwQPlHFQKoC5E1NxrKkbj+6uRofNhS0rpsMlCCGTB51agbyUOOQkGqBShdpASpwWT39UjVVzC/CH9yqliLTLZ+bgSGM3shP1mJadIEUei6m/Yj8kcI799Z2wubyyzgVKFx44Ne3y6ea17daoOtxGUoRoarx8ZE9KfHQie8wOr6SdLvajj+2uirgfjVVGmq1GaqdN3c6gCBZRS3jTkhKY9Gq0WlyYkBonm/lVkZcEnaoQ7VanrA02djnw1//6xlQFQ0i22uKybEm6LLCPn5JpgkbF8JuLp8CgUcLLOeK1KikzTqOUTykVOML24YHzG3Gxt/qFPSPiGSYIQp5Yz8AKpxcaK7rJCXq17LrogSvKo920iDhlduDR3ZVB7X90dyUq8pNQoBv5mwtjHXFzqOeGsOj7ef762figqhWcIyhz/ePjbXh5Tx1+890psv1HlkmHpm4HuMDRbHaiqtksbd78cO4EOFwexOk0+OP3ZkCjUmDtS18Gre0DM6cq8hJgdXrxYWU9tCoF7rhoMhIMGhxvseCNr+phd3uRoFNLjuGsBB2K0o1Su8Q17ur5BchJ1GN8sgEtFidcbg/WLJzUp4CisN4Sznl7v74BIqrIOea27anFT/6nEDf7jTIwmiJQuqEgLR4/efF05ejAHY29tR0oTo/HT88txOHGbhxpMuONr+tx1Vm5GJ+sx4ZLSoJ0hdcsKMLt/9yPH80rwC3nF+Oh946FXFfE4RbQaXfj4pIMFGaYglK61y+eioVTMvF1Xaf0nhq6HJKeanGGESadGg63F1vePhL0vn++7Su8tWYe5hSkhixwAndbRGra7LC7vZhTkDrk39NoZqA79B7uxfIeFTfvvrQEXh6Z9mVqnAobLy3BXQERZxsvLUFqfGTOYZcb6LZ7cLzF6uvkW4GCtDikRdivujxe/GR+oZSiLWp3eoTINH8tTnn9a4szsvMPnurCr/6+L2QQy00yoDz3zLIasYrd7sZnte1o7HaiPkBf+M8fHMeGxSW4+82DkozDxiWlmJoVh1SjFoUZRsnherLNKlug4OGdx6TiAz0duGJk75HGbmnADnQuP/lBdZDDIDBz4bZ/7AvRnZJzLlC68MCI08hLxRg0kfUJQ8FIS3PNTFDJRsZkJUTnM2qzuGS10yPVfo9Vom2rPaOEOQ9NlRRTIwM3tKz+4nKXz8yBUadEgk6Nxz84jqtn50nzv7yU0Lni2oVFqOuwoSjDiBOtlpCsnf+9pAR/+69vHvqPL+ow7ZKpIdlqjEF2fnjTgkI89WE1HlxWjsQ4FU602nHz/30ppZVOy5aXH9OpFGH78MD5jVzkcSylqhPEWCHWM7BarE5YXd6QzIwWqxMFkZWBiip2t0d2XWT3RJZRGW0auxyy85Gm7tiIPB/riJtDgXMFEZeHwy0IvkAq/7GsBB2WV+QgN9mADZdMxVMfhmatb7ikBGu2fSnpCW+4pASvfVUv/X/twiIoGXDbPw9K/iy5wEzGgLwUPa6anYefvLhXmp/kJGnQ0GnH7iPN+Mm5hVi3/Svcs7Q0aJ354DtHsH7xVCl4ssPmgk6lxEPvVeI3352C5z8+gZsXFkOtZH3asI7eyogYNAIn8wrGJOMTIx9yk/Q41WUP0jZ5eGdlUOrcXYunYvOOw7I7Gk9/VI3UOA2uOScft/SISH7p81osmZ4NvVqJR743A/vqu6BR+h7AS8qz0WJ2YpxJi5vOK0ReShySDGocOtWFa7+Vh+xEA060WuEVBNS12/Dt4nRs3XksqA2b3jyEB5aV42iTWXYSzzmw/rX9WD1/ouxDJzokey7EBZlCUrG0izySGegOvU6pwmO7D0o7tIAvYuz3yyLbYW63evFoj4izR3dX4f4Id6idHgFmR/CExezwSLqFZ0KvVuHL2nqfZrDZiTSjTzO4MD0yzWCjTt45YNRF1l3Xd8kXXqvvsqMcsekcPlNac6fdgcpGK+xuAeOT9EgyaHDbokl47pMaX5HKz2rw4LJyeDlHVoIORq0S+09ZkGHSYXZ+CgTBF73b0OXAWXnJeNlQF6SVeWVFriRBo1MrsPmKMny3NEuKJEszapBhTMOTH1SHdRhMunkeGIMk97N5x2FZvXZyLgw+GSYt7rhoclBKZkqcBhmm6OnXhttEi9Zio6nbi/cOn8ITK2eh0+ZGokGNv356AvmphchLGfbmIMOkRUVeAq75VkFQBkm6cXRrDkfTVuWihB9cVh5kp3KpkVtWTMfULKOk175qbgH+77Na/OLCyahqNkuZaDVtdjz+7yo8tGI6PP6It/pOG/78YTV+eeFk/OG9Sty+aDIeWjEdBxu6wTnwp39X4bZFU+AROOK0Stz9xkHctsgXxSM6oydlGEPGzLwUPaZmGiWteZeHo83swJYVvvdT02bFQ+8ew9qFRUEBCWsXFgFAUBR0YB9u0CjPGHkcK6nqBDFWiPUMLJeHh/RJD++sxJ+viSyjMNro1Socb27Cs9fPRovZgTSjDu8drMfE9MEp+jnUaFUK5KXosbgsW1qXvvF1PdTK0S1zFUv0tk4UN4dq26xBc4WsBB2uOScPq547nf2z8ZKp8IJJm9h5KXrcefFU2D1ePLFyFlrNTqSbdLjz1f2oabMD8NfoeOMgbjqvEHa/w9fh9mLquATp75vePCT53UR0agWmZhpRnOGrxyCXubp+8VTUtVuRZNAgyV/TSFxnJhk0SI3X4sFl5bC6PLA5PbC6vFhekYMkvRrfOzsPdpcX4zMMffosyTkc48hN5tcuLMLb+xuwqDQrRN8nUNskO0GPzVdMQ32nHXEapWTkIg63AKUCuO+yUsRp1Fi7LTgcftse3+Tf7vQgJV4Dj8Dx8p46rJwTXNBp05JSTM7SobrZAotDjb9+VosrK3KDJCBuOb8YW3cew+Ky7KCdOYdbgM3lwRtf14fs2qxfPBUPvnMEV1bk4skPjvsi/no8dKJDsudCXE6bJZZ2kUcyA92h73a6Zat4mp2RaVO1mJ1weU6nWjHmm1hFWlXW45dgCEQQODwRRi5zCLKawRyRne/weGS1uZyeyCKHU+PDFHKKi02nypnSmjvtDrx7sAXrXwvWjNq2pxbXfzsfz/znJI41W/BNhw3ZSXq8c6AeBp0WW3dWIS9Fj3svm4Y2iwvVLRZs3+MrvhmYWSHn7L31lX1IMmjg8nqlCtKidlVtuw1yDoPDjd345ctfB7VREUavnZwLg0tOogEGrQpP+rNLdGpfFeGcxL5NmAYTQ9gI0ci0zQebLrsb356Yjr01HZJT8tsT06OmCZgUp8SKHhkkGy8tQXJcdD6f4SKatioXzV7ZHLwxL9cfbt5xGL9fPh12txc3zCtAulGDK/3fnRgFs+6CYjSbHXjx01pYnR60W5247+2jUl8oCD5Nv9/uOIKHr5oBziEFGaiVDIcbu5GdoMcl5dl492ADNl8xDac6fbJnSQZNkJNX1CBeF9Df3nHRZHAwrNse3Ae/vb9BSsNsNjthUCvRZnNF1Ic/tGI6BRkQRIwQyxlYDpd8RqHDFdm6INqolRxl45Px8fFWCByoaragbHwyNMrYkMVweNyykc/OGIl8Hu3IrRPvu2waZuYmSgXFF5Vk4lBDFzhOb/4ur8gJkcMy6jVSIGRWgg5Xz84LybxXK1mQnwHwPY/ZSXr84T2fL4szQK1gKMs2YV+9L7M0N6AAnhT9b3bCI3A43KGyF4FBkssrcrDxzYO45fxiKVNr5Zw8SaoiL0WPn8wvxOZ/HZWuv+6CYkzIjeuzb4ucwzGO3GT+4Z2VeHBZOX7ZS1VonVqB+i47vALw6PtV+OP3ZshOckuyEtBmdcDt5bLRI4ELt7sWT8X138rDXz+rDYr6fOT9SiyZng2vAGx5z9eGnsb/0HvHJJ24QHRqBdqtLqnYiPiayZkmPL67CjVtdul95SYFP3SBDsme0awNXQ5s21NLGsNDwEB36PVqVYh9bN1ViWeuOyui88cl6nD9t/NDCsqNS4hswcbDzFXCHQ99oUJWM/j562dHdLpWpZTV5rrvsmkRnZ9h0oak7m64pAQZCbHpHA6Xfj917Tw4PF60mF2SY1j8u9gnbHn3GB5cVo7keA10KgXe2lcHrUaL7EQ9yrJNWFSahRsCdozFDbTAzIpwBTf31XUiPyUON8wrgF6tgFGrQrxGhdJxCVi7sBDb99QFyfYcazKHtPGBZeXkXBgGajtsUsEJ4HQV4Zm5SVFbKLq8XtlNILc3sk2kwSYlToOq5tCCYilRqibebvFK0kCA7zu7S+xH06PSpGEhmrYqF82+fU9dUHHfnv2hOBf8wdP/lezmse/PxM/++oVsFMy6C4ph0quhUytx04JCvLK3Dlt3VWLLcl9mT5JBgzaLE09/VC05lq0uLwxqJf6ws1LSh69ps0qLuoYuB97e34AHl5WDA0jUq3BnjzGh1eoKKcQsjhNbd1bhpgWFeGRXFbISdLjjYnl9wZ59+O92HMZvL5sm6dtTkAFBEENBUpx8LZWkOHUUWxU5nCtQ3+kImV/kJEVvg74vaJQq3P3mF0H9/91vHsQLP4xsXTdWGa6iy3LrxDv+uR+r5xdgcqYJi0oyAfhq+ri9HA8sK/dtSHuCC81dPjMHh/0SgeL/RVks8bri+lAuILGl2xES3LZ+8VS07KpCh82FNKMWf76mAp02F0x6NZq67WizuFE6LiGs7IXDLcDh9qI43YgEnRpTx5lgcXjwm4unBPn5FpdlS5sX4nlb3j2Gp6+t6PNnTs7hGCdcamq4iDSxKvTahUVIMajRbHHhjosmITVegweWlaOq2RwUPQdwqJVK1HXYzhg9svHNQ3hi5SzZqE+F4rSWajjjVyqAsuyEIAfvpiWl0gP0u8vL0GZ14XCDGZvePCQ5XhxuAXnJepj0Kmy9agacHgG5SXqUjEsISSkI3FW6ddEUTMtOJIfwEDCQHfouu1vWPiKNYPMIguQYFs/d8u4xvPDDyJzL4JDV9oqUJrNTPho0wshlnUqJ75+dF+Lc1qsji5gbnxSHcYlWKc0kTqOCUa/E+KTYXLDK9XFJBg3213XhV6/sww3zCsL2dQ63AC/ncHm8qGu34qn/fIM1CwthdXokDadwG2glWSa8uGo2Ou1uWWfvlCwjvq7rAuDbHdZpVPh5QP9y1+KpeOmzWhxrtmD94ql4ZFdVSBtr2qxhMxiGa1I1FhiJlcpT4rSym0CLSjOj0h6byyubtvpUlNJWmy3y/WikGSCxSjRtVU4SqsPmQnFGvFTcV69WBTlZ5eaCX33TGTYKZsu7x4IkzcQNuaoWKwD4o2MOyTqWxdceaeyGwE/PI7MSdFhUmiUtlHpmygEIen3g5yrOicWutaHLgfveOhwiN3HfZdPwwL+OBp1f02ZHTrIe21bPkaTcSrISqJ8mCGJQsTp9zqAWi1PK7EmN18LqjI3IVbPTIzu/eHLlrCi3LDI6wmSTdNiik1kVC+uD4Sy6HG7eJPhrJkxdOw+HGsw9IotLYdKp8csLi5GXEof6ThuS9Bp802mX5kHh/FUCByakBAckrl88FR1WFx55vyrIzkU5Cb1aidte2Y8OmwtrFhRh15ET+Nm5ReBeDjBg8+VlUCoZ8lL0QZn8OrUCrRYnJmXE4wfn5ONHz/sCmnrWzgrX1m67p88F6ck5HOOE03cNl1p+TkEyZucnobbNig67By/v/SZET3P94qkYl6jDwfpuqJUMrRYncpIM+NP3Z6KyyYxnPq4JG01nd3lloz7vX1aOY37dYLEtPds2JdMEi9ODdecXodvphYIBdpcHW949hg6bC5uvKEPpuAQprS/w3Jp2O+56/aCUDi5GlwQWgYplvalYw+MRcLChy79g0qMkywSVKjJtptR4jax9RBrB1mmTdy532CKbRHkEjpc+D45+f+nzWkzLTojo/AyT/LMXqVamWqlAmlGL1fMLIHBAwYA0ozZibSuFguHbBWkBn39sL1gD+zhRR31eUTK+rO3C3ZeUICtRvg/kfl1xi8ONJIMaD71XJfUzbq8XNpenV2eBwIEbnj8dVRzYt9x3WSmOt1glJ8mahYXY8l5wpNrGNw/hsatnoqbNCrPDjQ5bcCEtnVqBeUWpcHsFbFs9BzaXL4NBqQD+e6INHi/Hna/tl4obDNWkaiwwEiuV5yYZcMfFU+D2cFidHsTpVCjLmYLcKEXSWJzyz4MlSovPdKN8P5o26jWHo2er+SlxeOTqGdhX1yU5IJINGtz4ty9w66IpWFSSCUHguGdpqRTdLDcXFHV5sxP0YRdW4u9bd/micJweXz87MS0eSQYNbr94SpBecUOXQ9q806oUcPlfH84JHbjRB/jei9znqmDAxktLoA+QeemwuVAU4BBPN+qgYJDtw+0uAStf+GzIF78EQYxd4nVq2N3BmT3rLiiGURsbkcMOdzhZjOhkSvWVTJNedvyIRt2K4XS69qVNPZ3Vw1l0Ody8iXOxloczqC1JBg2aup14eGewHGGX3RUkYypeR27ekJ2kx6+/MwkmnRp6jRJtVl+NITk7n5gWj7oOm/T/rbsqsWXFdDy2uxJXzMyVHL4++bRSPLq7Ulr7/fayaei0u/FVXVfQxrzAEaSDLVd7QadWgAE40WrFxPTIP3NS0h5BCAJHdYsFnxxvRXWLJUT3VA4xIjbQ6brugmL86f0qbLikJOj42oVF8Ag+B25+ajwe8uuiyOmbcA7sq2tHh9232/erv+/DT//6Bbwc+OV3ijG3MEW6tohOrYAgcNkHw+n24oOjzVi/eKr04AW2beOlJfjT7irc9o/98HJfFJXAfZXJ//fSEtwwrwBb3j0KBQM2LSkNOnfNgiL844s6aSfy8pk5Uid0ss0qtUOMZp1TkIqCtHiavA8RHo+AV7+ux5VPfoqfvPgFrnzyE7z6dT08ERZ0M2iUId/xpiWliNNGFjkbp1XJ2mak57sFL66enYenP6rGI7uq8NSH1bh6dh48EaZ7u70ebFgc/OxtWFwCtzcybbAuuxt//fQkCtONGJ+oR1G6EX/99GTEkdOCwPHO4aaAz/9TvHO4KaL+ZCQi9nF5KXpc9618/Le6Bd+0+7Qmb/3Hfqx/7UBIX3fL+cV4c189bl00GY+8fxyVTRZ02FxYv3gqtn9ei6oWK5L9wv6BiIP++sVT8bseBTof3lmJB5eX4dbvTEKGSQeL04Mb5hXgpgWFUCl8xZFuPK8QNy3w/SQZNPiqrhMpRh3+77NarF88NaiNW1ZMx7TsRFTkp6B8fBLOnpCCo01mLHr4Q3zvz//Fj17YgysrcpGVoJPtz4jIGWfUYeOlpT3GnFKMi6JzuL7LBrvLi2PNZnzTaUdlkxl2lxf1XbaotEdMWw1Ep1Yg2RCdxafD7cEt5xeHPNcOd2xESvWXaNqqIHBYnb6smUd2VeGJD6rh8AhI0KlxpLEbu48142BDN176rAY3nVeIR743A8X+BYlIVoIOCsbw5AfVUgROIOKCTcThFlCYHo9p2SbccdFkJBnUuOacPPz6719j607f+HvTgkLcdtEk3DCvAMkGNdQKhpQ4n85wb6mY4n6quLnc057uWVqKOQXJKEiLwxcnW7F6fgEeXFaGtQuLUJgWj4npp+eLucmhc+3NV5Rh/Wv7Qxa/1E8TBDGYeLxcNiPSHSPz+iSD/PwiMS42YhQVCuCOiyZjzULf/H7twkLccdFkKKPgRwjndI3WuCM6qy/e6lu7XLz1Q+w42IiaNmvYLKjBRs4XJvqGdGoFrP7gh6wEHW48rxB3XDwlJJJ9665KuLwcV52VK2X1mbRK3HvZtBBfWopBg33fdEKrVuL5T06ixeyLXD4VZs5zrMmCP+6qwso5edKa7khjN675VkGIFMRdrx/ALy6cjJsWFGLV3AJfcOSOIyHZTx8cbcZP5hdKvooH3zmCjTK+k8d2V6G2vW+2ERtP5RhgIDtBGhULijLUq5U4d1K6rEav3e3Fa1/VY+OSUtwwrwDjE0MjO5IMGni8HFedlY+f/e2LEAfJ6vkFyDDpcNfiqdj45qGgXZfaAPkJMcpPqQD0GiWumJkDr1fAkunZUCiA+5eV42SrFR5BQJvVhX313chK0MGkVwel84kO5SsrclHfacMj7/s1hpP1qG23B6UOipF/4u9U2Gn4OdTQJauZWJwej7LxSWc8v93qxtGGDqmqbbpRh3cP1iMrQs1gjUohW4FcE2HkcrxGHaIx9NB7xyLWlhIEBV75ohb3LyuH3eWBXqPC8x9XY+3CSRGd7xa8WDA5M0jPe82Cooid08O5WzsciFH/OYk6vPjpCfziO5Nx/TOfS++vps2Ox/9d5ZPRcHpQ32XHuEQdfjy/AH/cdRwdNhfyUuOwdmERtn1WKxXq7FnESOxruu1umB1u2QKdX9Z2ojwnAad6aKc9uXIW1Mo82ar3DpcHV8/Ow7bPan1Oh/R4mHTqkIgDue8tMPqN+rP+c6CxG4/urgyScHh0dyUK0uJQkZ8clTa1WVxo6ArV4Mu1uJCXMvztUTP5flOliE4MgU6jhF6t6DG3UUAXobzOUDAcqZzRslVB4Pi4ug23vrIvqA/622c1+PH8iUFzvVvOL4ZBo8SpTjue+fhk0FxweUWO5MSQK/wrZmCI6NQKHG204OmPqnHP0lJoVYqQRdumNw9h1dwC6TVGnQr/+/ohXHNOHh5YVg6TTr64Y2G6EWsWFmJmbhI0SsDsFPDMdWehzeJEvE6NDa8fkKJzNl5aijSTBnf84wAauhyYkZuI/NTTfa1c9lmb1Sk7TlA/TRAjj1hIxQ9HaxiZpdYYkVlSKXyBaz3l8qI1v+grjd0O2N1C0HztlvOL0djtQGn28LZlpMmkhVtzPrhcvqYKA0N1i2VQnz9xfJ508zwcbuzGsSYzXvj0dBZ5qlGLvBS9JHsaTo7Q4RHwwdFmbFpSioZOBwxaFWxOn8xqskEDg1aFug4b/vLxCSwuy8aW9ypx03mFyE404OaXvsTFJRnYeGkp7no9OCL5hU9rgtZ0T39UDa8A2MNk7B1rMktShJsvnya9JvDznFecHuRYrmmz49H3fZn6Vc1mTMk0odvmxLFmCwyavrl7yTk8QuivQ+dkmxU3/e3LkIdv9fwCv6FUScdWzS2AQaPElRW5+PELe+FwC1i7sDDI2LISdLjmnDycbLUgwaAJmxLY0OlAgd/hYnV5wTnwwqc10KgY7lk6DX/cdSxEe3jtwiJMyTJCq1ZKBbvEB0dcLCyvyMEmv97c5TNzwBjQ3O3AVWfl4uGdlXj++tnS+7ppgW/HRC6NQPydCjsNP6e65Aeuhi4nysaf+XzOBExMT8R1z5xO1dywuARAZDvknVYX3t7fIDlnDRoV/vzBcRRGOGh2hJWliCxy16hTYumMHFQ1m6XU3KUzchAfYeSyQa2WTZF9LsKCdiNt4jAYKBQMHF4smpaN2jZbyPurabPD6vLAoFXhZb9murjjumZBETa9eRCLy7Ixrzhd+mwbuhx4/pMarJ5fgOwEPUx6Nb5pt8Lt5Zg+PgF3XDQJ3U4vXtlbB8DXN+WnxKHL4cEj7wd/PwdPdcvqqa1dWITMBB3s/orSnAM3/9/pqreBG4Dhvjdxs4v6s/7T2O0IGg9FmroHP4IhUiwjTIOvodv3PAQ6JZ//pAa5ydGRuVBAgaf/c0JKmRM48PR/TuD3y6dHpT3DlcoZLVs92WbFnpr2kD5ocVm25PgFTm+W3nnxZJSNT8TPzy/CxLQ4yYk/MTUuSJJpx4EGrJpbgLxkPZrNThjUSkmeoefC6c5XD+CepaVh+0HxNU9dW+GPpvFpAN920aSQjY01C4rw27cOo6HLAZ1agUeunonqFgsYA3ISDfjJi3tDonX+cl3F6YAGtUrS6evpVJqdnyJ957LBEAHnEgQRfUZiKn5fyDTpglLIAeCNr+uRYYqNOWFDlwPP/Odk0Pzimf+cRHaiPtpNiwiTTj5oKNJC44PJSJNJC7d2qeuwyW4O/3zbVyHSn4OBQsEwMT0eE1LjMDXLhG9NTJEkRPfWtmP94hJsevMgVs0tCCvBkGJQ46fnFmJPTQcE7nvGvn92HjJNuqDCs4HzlnSjFvtPdaE4PR7fLc/GRv89wgUw5iXr8dvLp6Gpy4EEg3yhycDsqjidCnkpeuhUvkjgug4btu+pk5X0qmmzS45lnVqBP6yYjvuvKENmHwvSk3N4kOnvzmR/HTq9iXD3PCZOih945whWzS2AUadEbrIBv718Gk62WrF9Tx2WV+Tgpc9rsXr+RCk8vqfRKhhwss2G9a/5JvI7P6vBnpqu01EhH5/ApiWlWP1C8OT74Z2VeOz7M+H2ePHkyllot7pg1Kmx8c2D0gS+IDVethDJ+sVTkWTQwOrySG3qLSpFTPmjqtHDj8nfkfWcxMTrInOOahQqvH/0JJ5YOQsdVjeS49R48dMTWDW3MKLzU+O1uGhaVlDk7dqFRUiNj0yzWK9Rytq9XhNZ++N1CmhVyqAd5k1LSmHUR7ZDHk4L1+aKLJ16pE0cBorV7sSpbjssTqDF7ERWgk5WsL+23Y6nP6qWBu3ijHj88aoZ+OMun3aTUhFalKihy4GtO6twx0WTYHZ6sOW9YOfCG1/X4yfzC+D0CkERD2sWFGHHgQbMK04H8+tyyn1nWQl6PPivozjWbMH9y8olmxT/HrgB2JtmlriQof6sf2SF+WyjubCyuby4uCQDy87KRavZp1X28ue10kbCcJNm1KLD5gpySurU0dP47bK7ZIvbdtldZz55CDjZZsWrX9aGjEuTM42Duuk2XLYqCBy17VY0dTvh8nqhUylRnGHEbYsmgcNXlBUATFplSN92zoRk6DRqaQO3Ii8BV83Oxx93HcPq+ROlTXvxO9u2pxb/e2kpHt1dheWzxuPuS0uQadLhUEM3nv8keOEkyv2EWyw53AJazU7cvmgyfrvjCBxuAf/3WS1+vrDYt9GXKL8ga7c4kWzQwOL0QK1ShLynJIMG9R0Oqe1PflCNLSum4/xJ6fj0ZDv21LRLi0VRf1lMZd2843CQrYrnDrXjKZYjIQliOIn1jDqlAlh3QTGOt1iloBNf5G20WxYZqfEa2flFSoTrsmhjDRPhGem6bDCRqw0wLSdhwOuD/o4n4dYuZocX//iizucoTdKjvsseNN6v2/4VUq6fjTSjdtCjiAvS4oOe62SDFo1dDmmcDswcTTJosLwiB1OzTLC5vLjF30/kpehx66IpqG6xwKhT4U8/mAmrwwu724t4nQrXfisPdpcXWQk61HbYsXr+RHxd13nGAMa6TrtUkPeepSW4+9KSoIDJe5ZOwzsH66XXm/RK/OzcwqDXbFpSKkm19DZXOtTYjXitCtOEyGomiZBzeBAZyM5kpA6dng9vpkmHNQsLJWfwK3t9UXM9byc6deN0CqyePxFPfnAcV1bkYt320w609YunIl6rxOKybCl6V5zYLy7LhlIBTMkywWxz4aGdVVIUxyNXz4TV4cbxVqsUAWx3C0HRI2L0HTjQaHYh1ajD5h1Hce238vDLCyfjaJMZxRlGtFkcWF4RWlxEqvaoUeKOiybjvrePoKHLgW17avH4D2bB7vLgZJtPq3F5RQ4q8pLxrYIUmihHgeR4dUhHdvelJUiJi0y70it4ccHUcVJ0u9gRenlkThO7xysbkTf9uoqIztepFbjzu1PQbD5dFTjNXxwpEtosXkn6RLT/R96vxP1XlKMw/czn5yYZZPuC8REWqhqqiUM06LQ7cLC+Gw1dLtz56v4ge3psd5WUEtwzbWf1/AIcb7FAr1biomlZONZsQVl2AvQaJRTM11+KfdKP5k3AuEQ9NEoFHr5qBh7dVYl99d1S+k+bzRVUBEC8x5YV06W+vmcGBiBWmHVgX32377wwTn9xA1B0NASOH5uvKEN2og5XzMymhf8AKMk0haR6bby0FKWZpqi1qTBND3NhGn4YUAx205JSFKRFJ5JGo1Rg46VTYdCopQJ5NqcbmggLYQ42Bo1KNoPimevOikp7LE43Fk7JChqX7r60BFbn4FYrHw5bFQSOD6uaYXMK+KbdijidGpsCZCPWLiyS5pL3LC1FXooeLg/H5TNzoFUpMCsvEc99XI0nVs5Cp82N1HgNnvu4Gr+4cHLIBpjYV7aZ7VizsAg1bTZ802FHl82FwrR4fG92LlxeQbqfW+Ahm/5i/w74+tXqVitm5yfjr6vORrvNBa1Kgdo2KwrTjVAynHFBtmlJacgG4/KKHKx/LVgOa/OOw3C6vSERQ5t3HJY2BRaVZCI7UYcrn/x0WB1PsR4JSRDDSbhAqqbu2MiocwtCiJzZ2oVFGJcYG0EfOpUSW1aUQxAgzS8UDNCroicT1RfCrctyolRA2OXhQbawZcX0iM4L5wDuy3jS8xq5SYaQtYsYqNfQ5cCj71dhzcJCbN0ZnA3lcAv4sKoVT304NJupHo8gFWZPN2oxLkGPX/3dJ5vV0OXA2/sb8MQPZqLJ7MJdrx2Q5B7ETCCfj+yroPney3tqcXZBGpQKYGqWCU99eByZCXp8erwFxenxEPjpbKIzyWo53AJq2+34uKoFW1ZMx5HGbngF4KXPTmLt+cX4/tkT0O3wwO3heGx3VdD8Yv1rB7B2YRFuXzQZbTZXUAHhxz+oBuBrh1cAtrx7DOU5iZjQh36OnMODyEB2JuUcAz0jxXo+vHkpety8oCiog7hr8VRkJWhhcwlS9KZSAZTnJMLj9QBQSPptcg7Yx66eiSlZRiQZNGjocmDHgQasnj8xaOFwy/nFUpscbgH76jpRlG7E1p1VyErQ4SfzC9BudQVFj9xyfjH0aoWkYaxTK7DhkhKkGTXQKBUwaZU41WnDcx/XYN0FxbKD+ITUONz6yj5cPTtPkrNQMCA/xYDcZF9lTFELjhwpA2MgESkWh1dyDAO+727D6wfx4qrI0m/USmXIIm39awci1vy1OOSdcGZHZM5lgXtlI38FHpnmb6fdHSbiLTInglLJ5LW5lJHbc38nDiOJTrsDlU0WuLyQHMPAaXv688oKdNrdONJoDokSm5Aah/t3HEWHzYUnVs7C/cumocXiwt1vnN6wuH3RZHAAv/NHn4kD9/XfnoBn/nMC++q7pXR2OXs60tgtHd++p042rfnpj04C8A3SBWnxvW4AymlaUj82ONR3O2R1XGflJWGiLjoLw06bV7afezHCfm6wMTtd8HKGXwZkXGy4pAQWZ3QidcP14xZHdArSOf39Ts9+KNJxKVKG2lYFgeNQQxdOdTpx9xu+9EcxYwI4vZl6/7JyHGsy45t2GzZeWoJDDWapf3twWWmIo3zD4hK0hHHAVLdYUJRhRHWLBU9+UI0kgwbXnJOHm1/6MqjvNaiVONFqwbY9vgjt/XVdmJxlwqaA7DLRUSxw4KkPq7HugmJkGLW487VDAHzSaOsXTw1xdj//SY0k/fBNhw33XTYNd/xzv7TBWJAaH9L2xWXZkmNYfC/ipqG4qadQMNhc3l43/oaCWI+EJIjhRCxU3XP+FRdhRmC0cbq5bNDLU9dEFvQSbaxuNywOD+4KCBraeGkJrIbB3VwdKtRqFhLhefelJdCoR05BujP1/b05gCO9ZrhrXDglA2+tmYd2qxMMDHUdNvzmu1NQ1+ErvDwtO0FWgqko3edvGuyxy+MR8OrX9VL9I19Ebqnk2wJ8mr1mhxd3+efhjEGSNJ2cacSvemx0b3j9YIif7n8vKUG33YUfzi1ASrwWv3/3qOQQFgMYH7l6Jo40dGNmbhJ+8fLX0v0Bnxb32QVp0jVFH9qB+u6g9eQt5xfj2Y9PhtTXcniCdbDXXeDzz4l+C9GPYHX2bd5MzuFBZCBan6JjYOraeWjqdsLq8iAvOTjS72SbFZt3HJYWDZMyQo1345uH8Mx1ZyHVqMTtF02Bx8tR3WpFbbsVU8eZ8J+qttNGJdPWL77pxFMfVkuT6XnF6dIkW3zNQ+8dk4okiTsTdr/cw+Uzc2Qj7f72WQ1+deFk3DCvAIAvak9cmDz9ke9+GSYtNCqGZrNDdhDXqZSoabMH3R8AvjUxBfmp8SFpBET/GGhESjjN3s4INXvbrC7Z89uskTkp9Br5SWCkshCMK2Ujfx+4ojyi85MM8prBkWpTNXQ58ObXp0I0k6dlJwQVyAnHaFg0dtod+KbNAZeH48vaDll7aOiyIydJLxsl1mZxSoNoU5cDaUYdfv33YJkbuX5KLLh5w/yJ+P07R1CcYYTD5cHahYXYvqdOuqbY74mI+sV/vqYCB091IzfZgM07TutdblkxHdNzEs+4ASiXDkUMnJp2K1ye01pLjPk2UGrbrZiYHp3PujVMP9caYT832GiVKtz9RnAB2rvfOBgVTT0AiNfLy/vE66OzmG8yyxcEajIPbkGgobRVj0fA/zvQAK1SgbvfOIgkgwa5SaFFiR1uAVXNp3XrNi0phdK/cGrocmBcUpwU8S6+/u43D+KJlbNkv7Op40xQKRhe+rwWDreAy2fmyDo6HloxHU9/dBw/+Z9CHG3ohlLBUN1sxpLp2RA4pNoWHTYXOPe1x+L0ICtBH9RHv3ewEY9ePRNf+wMX7nvrMACEyJVtWlIKjYoh0aCB2yOEtF1O08/hFqBUICirLxpSTqOxtgBBDBVujyBbcNXtjayWSbSxhJE16KvTJ1qoFEo8ursqaF316O6qiNdV0aah04mX99QGrcue+7gaE1LikJs8vP1tf/v+3taGkV6zpx8KgJRJk58ShyON5qA1zu2LJoNzwO72YutVM/DkB1VYMDlTGofzUvRYv3gqqpotaLE4QwJieot07i2A7VBDl+QYFt/Lna8ewOr5BVIEM2OAzX16Yzdeq8Q15/gKi4crWBcYFORwC/jfNw5i9fwC/OyvXyIvRY9fXFCM+k4H7r6kBHH+QrmP767E92bn40B9p1RvQaQgLQ7HmszSNcP50Hr6vXRqBcYlGkIytba8ewxPrJyFow3dcHu90hrUpI8sc1uEnMODyGBMEA81BD9Y9102DTNzE5GbHIc2qzMoInHNwsIQ400yaHCyzYbH/10VEr24aYmvEnReij6sGDfnwU6ScFFzjJ0uJrJtTy1uXzQF9ywtRW27LeQcMTw/MCJJjP7ITzEgyaCR7rdhcQnufvNgSCj+piWl+NPuqqD79/b5khZb/xmoczFOq5TVHI7UOZscJ685mBIXmTaVWslkJ4HqCCNvuxxhIn8dkTm3u+3yzvHuCM836lRYNiu4oN2yWTkw6iLrrmNx0Rj4vE5I0eBYswNtVhfUSgW0KoWsPWQnGZBgUOKepdOCJCd+eeEkPP3RCQBAXooe8VoVms2hn0m4vk3gALiAn51bGKJb/fwnPsfEpiWl2PZ5TdC5HTYXBM4hCByP767C4rJslGWbUJRhlPqf/kYGU382MEw6tTTpC/w+Tbq+TZgGk3D9XHKE/dxg0xzG+dkcpWroKoUCv/rOJDzwr6PSd/ar70yKWnXzcFrAmYOsBTxUtioIHB9Xt+HWV/bhgWXlKE6Px0/OLYTAuez7Eje/HG5fRPvq+QW4aUEhzA432izyGxstZqdsGuVv/nlAKg76wqc1YYMTXF4BNy8sRpJBha9qu5Acr4FGqUSnzRUUcSZqvgc6e/NS9Lhr8VTUtNmQn2rAn3ZX4uyCNDAGqUBpz01b8X0BVujVypC2n5WXLPvZVOQlIzfJgJOtFp9ms8eL315ehtv/sS/sxt9gM9pqCxDEUNLlcMsWXJ2caYx20yIiNX5kzRf6SodNfl3VGeG6KNp0O9xYMDkzaE3Ql3XhYNLXvl9cPxxrMuOGeQV4ZW9dUARqs9kR8TV7+qHEz6Hd6psnBvoOkgwa2NzeoLnMvZdNw9advmhWOemGQJ8XgLBRyu8cbgobwCYIHA1dDikKOFDetDAgg9OkVWJ8kl76v8fL8cj7p+UbepsXiTjcgjQndXk4GrudQe/3niWluLQ8G9lJOjz4ztGQOYZKwTAl0yTdq7dsVVHhTfSJ1bZZZV+3t6YDOYl6vPhpjRR13NMpfSbIOTyIRCIN0RtyTrk7/rkfq+cXYHKmCTmJuqDJrcAR4oQzaZVSRK4oui0+HHUdNoxP0uEn8wvx4DtHetV1c7gFlGQlQKNisg/I5AwjVs0twLY9tbjqrFy0WJwoSDMgN9mA/1S1Bp1z+cxQDWFRF/SbDhuu+1Y+nv34JAQOdNnduG3RFHzTbsX9y8pR22bFxLR42N1uSbtTdGKH+3xJi21gDNS5GKdR4cZzC0PSh+I1kXU3CgZsuKQkSAJgwyUlITra4dCrlDDqVNLmhoL5HK66CLWtEvQDi/yN08pHvBkidI67PAKsLm+ItpjbE5msRbpRfpBPix+Zi8bA53X3L87Bf6q78ZsAjcc7LpqMW84vlioF+9KDpgEQYHf5shYCv2uNfxMgL0WPn/5PIda9/DVumFcQGhXG5Ad/BQPSjDpc3yMy7uGdlXhwWTkON5rxyPuV+Mn8QrRYTuser11YBI/3dNrx0x9V460eGyr9iQym/mxwkItUfHHV2VFrjzJMP9cH9ZhBJd2kDbM4iE5BOpvTAxVjQc+2ijHYohQpNW1cAjYuKZVSEHVqBTYuKUXZuL4V+oiEobDVk21W7KlpR5JBg3SjBlfO9i3KAguzyM0FxTYIHNj05iH88sLisIVQMow6eD1ePH/9bHTY3DjY0BVUgEbsG8XX9zz/WJMFT39Ujd9eNg25KQa0mF345Wv7kGTQYPX8AhSmxaO+01fUJnBeKS4ybwnoIwPfw7oLisNG3uUmGyB4BTRbXNAoGZ67fjYEzpFu1EGlhCQ/IV538xVlmJOfjN2VzahsskifW16KHg+tmI7jLRaU5SQOec2Lga43RiqCIKCpqQkAkJGRAUWUNoOI0UVekkG2IFqktTyiDcPA1kXRJmxGZZRktPrKQNeFg0lf+n659YM4NopRpelGn27wPUtLQ2QYcns8HxqlQvZz2LZ6TojvQC5D6Df/3C9FwF4+Mwfb9tQGRSE/vPMYlkzPxsS0eJRkmWQD1bb9aE7YALb8lDjsONiIVrNDdpM9Qa/Cn34wCwrG0WZx4/fvHJGCEh0eQbqmnF7wvUunYeuuY0Gfh06tQGF6vCSVIco4iO2687UDeHLlLGmTeseBhiB94ZOtVrx3uFGSwgLCr02L0424aUEhFAzweL2YkZsY1oF91+sH8cj3ZkCpYHj0/UrcdtHUPtnYkDmHGWN/AbAYQDPnvNR/LBnANgD5AE4CWME57/D/7XYAqwB4AazhnP/Lf3wWgGcB6AG8BWAt53xE5oEMRmRYuMnrkcZuJOpVSDL4dgkvn5mDdKMGv7hwEqqaLVKEYWaiHkkGjaSd0jON7rHvz8TP/upLHX3hU98uqlIBFKcbce9bh4PSpvUaBZ756ESIftuGS0qQHK/GtGwTzspPwokWC576qBq/vXwaOmwupMZrgxYb4VLzcpMM+P27x9Bhc2Hd+UUYl+jrhI40doekcK9dWCT9fs/SachP0Yct0jQa0uqjSYZJJxv5G2lEis3tlRzDgO/zv+v1g3j2+sgKCdldAh7/d1XQDv/j/67CPUumRXS+lwuI06qAgHTfOK0qYs3ggUb+apRK2chlbYTOabtbvqBe2bWRaYspFcAdF01Gq/W0SH1KnAZRqit1RsTndfcvzsGJNo/kGAZ87/2+t49g3flFUl81IzcJWiXQ7fDihNmKe986EvR95aXo8fvl5Wi3uVDZZEaSQYMPjjYH9WN5KXrMzEsKmQytXViEzAQdGrvkN0iONJmlxcXdbx7Eg8vKYXd78U2HDXEaJTh8/a5SgUFbqFN/NnDCFqMxO8KcMfTYwvVzSyPr5wYbj9d7epIsjvWLS+DxRqbVPtjoNSr85eMT0jgkcOAvH5/AA8uik4aq0SixtGwcClLjpAj+snEJ0AyyZuVg26pYlKXJ7MS3JqYgJ8mAL2o7pTFGlMRZPb8A2Ql6pJu0+N83Dgbp4gVmlaUbdXB5vCHzwrsvLcGdr53W8P3t5dNkC9AoFcDLMhrtoqaewy3g9n/ux1PXVEia3A1dDqmY3CNXz0SHzRUUfRwuAGHV3AL844s6jE8ywCNw3LZoEjgAq8tn0298XY9xCTo4PQLquhxweIBfv/I17vzuVHi5HZ+daIdWpfDNT5MMmJJpwoRUX32LfXVdQamfNW123LL9K6yaW4DVL+wJ2RgcbEarRn1TUxOue+wdAMCzP7sQWVlZUW4RMRpQqZisc1Wtio3nZaTNF/pKexgZrfYoyWj1lbDt72NE5mCgUDBcOCUD21bPQUOXA1kJepRkmWT7/sD1g+jAdHi8uOPiKXjwnSNYd8Ek5Kf4xrQ/7gqudfDHXZWYmZsUNI7ZXF7ZiFybyxsSmBQuQ0hcixp1StkoZIUCuPWVfXhoxXTZ87/ptMser2mzotXixOYdh3HnxVOlmgbi3x/e6duMaDfbYTRocbLNivOnZkKlAJ5YOQsKAE/529/Q5cALn56eF2Uk6PC3/57ATecVSfMSsb2bdxzG5TNzYNSqZNtldXogcCU2XFKChi570HouK0GHa87Jwz+/+AZbVkyHx+uFW+Ah86N1FxSH+Oi2XjUDdy2eio0B87DA4ux2t4AH3zmCDZeU9DmIYSgjh58F8AiA5wOO3QZgJ+f8d4yx2/z/v5UxNhXAVQBKAIwD8B5jrJhz7gXwJwCrAXwKn3N4EYC3h7DdAyJcZFhvacHizs7Rxm7ZXYAEnRpJejXarW7c+d0pMGiUqGwyI8OkR1OXPeg+DpcH9y4tgVKpwPgkPU512iWdOIdbwFffdErXF6tIAsCDy8uksHPRSVLbZsWKs3JR02bDA8vKUd9pg83lRafNV9jpsatn4EB9F1xeAbctmoK6dhvGJxtgcXrAOcefvj8TLWYn4nXyGrCN3Q5/x6ZDUpxWVnZCbHdOkgF//N4M1HXYUJGX2Kv2aiym1Y8kchL0IZsOv7hwEnIS9BGd3213yw4e3fbIIr7sbg9q2uxBO/y+45E5KRxuAW/vr8f350xAh9WN5Dg1Xvz0BK77VkFE5w808rfJ7JBNX8tLiSxCwekWZO3XFWHkcIvFCbs7WKT+lvOL0WpxRqRZPNyYHW689KOz8XWdPWw6TYJeA4vLjrMnJOOhd49iT02X5JAoTo/HvvpulGWbsGZhEVRKBdqsLjR3O/DqV/VY44/offKD47jpvELkpRjQ7fDgxy/slSLSJqbFI0GvhtMj4NFdlVh34SRZGwjclnS4BXgEjjZ/OhX3R9Ytr8jBwsnpmJadGHah3heZCOrPBk5WQhhJgCimYNvdXvl+zhUdZyxjCrx/tAFPrJyFDqsbSXFq/PXTE7j+2xOj0h6zUz4N1eKMXhqqRqNERX7ykN5jMG3V4xHw9sEGdFhdGJ9sQJvFBYNGCYVRG3R90fm6ZmEhWixOXD07LyhTQ5yP6dQKaFQK/OxvX0p9Z15yHDJMWvzhvaNYXJYNo06J7EQD3F5BVqt9coYRv7iwGEadGk/8YBa6HR7UtFlDiq10hqldUNVswer5BZiVmxSUiin3WqNOiZVz8oIiitcuLMIre+vQYXNh45JStNtc+OXLp+Ugbl80GSdarUEFYdcsKMID/zqCZ66bDYWCoanb0avk2nD1z6NVo15nGtpnjBh7NHY5ZZ2rBanlyEsZ+c9P2HVRlOYLfWWkyWj1lawEvfy4PMiyUpEgCLxXWYVAxPVDVoIuJFhw/eKpyEvWS2OaXK2DnuNYpkknG5GbYdSius0SFJhUOs6EirwESd4J8G3IzspNxK2LJiE3OQ5HG7uDfFRbd1Xi4atmYNXcAng5l51DJIfJXDrRakW6UYfFZdnYf6pLdnw+2tgNg1aNnz+3RyqMu94fzJaXosfGS0tx1+s+52+HzQWdSonH/l2FX104GfvrLfjuNBbUh4h+KsaA0myTbLuS4jRos7jw+L+r8LP/KQyZez3/SQ3uv6IMP3rB16ZbFhZiYlo8Hrt6JqwuLxL0Ktz6yn4AwI3nFUqf5clWC7KTDHhgWTkqm83wCgiKCK9sNuPKilzEa1V9DmIYMucw5/wDxlh+j8NLAJzr//05ALsB3Oo//hLn3AngBGOsCsBsxthJACbO+ScAwBh7HsBSjGDnsBxnSgsWd3aSDJqQMPYNl5TA5fXC4RGCnKdrFxZBwRCUfp6XosfPzy/G0YBUt56O1gSd/EOVlaDD2oVFsLq8UDAgxaBGh92DewLavOGSEuQmq9DQ6cCt35kEs9MLt1fAy3t8E+27Ly1BZZMFrVYXshP0+OqbTmzfUwcAvUpYLK/ICanaLkZ9iEXvjjSa8fRH1bhnaSlyEnt3spEW28A41mJGfYc9RNbgWIsZpdmJZzzfpFPh+m/nBy2u1l1QDKMuss4pNV4+vTlSzWGlEji/RyX1jZeWIMLAXWhVSqy7oDik/ZHKUqTFa2XT19LiI0vPzkuJk33/ucmRRaFqlAppYQ+cFrPftnpOROcPJ512B0622nCrX6tx7cJC2fde32VHXkocTrRYUN/pc8Y63L7qsX9YMR1dNifGJRlQ22EPima7ddFkmO0uJMdr8csLJ0MQBDAw6TWBEWmB/U2X3SkbVfz8JzVB7YrTKGFxen0LjQ+q0dDlQHGG8YyO4b7IRFB/NnAYIKtfG80gu5QBaqsPNgoFxwVTxwX1m5uWlEKpiE6illEb22mo/WWwbNXjEbC/vhOMAUqlAj/1Z4zp1Ao8tGK6rO2V5yQC4HB6BDy0Yjrsbi9OtlmlInB3LZ6K3759OKTvfGBZGRZMzsSuI424bOZ4qVByYL/ZYXNh7cIi1HXYkJVowKFTXZg+PhFVzWY88UFwUdG8FD1SjVqsWVgIgUPSSBRTOKuazfjjrmNSHy22v+f7kSvY8vDO03PLu/yaw+LfkwwapMRrcaw5WJtRnI+KC+UMky5s6qcoeUb9M0GMHKwueeeqzRUbBd1S4ga2Loo2GqV85LYmWjpafaQky4RNS0qDokY3LSlF6RDISp2JcNmE2avnhKw9xPWDXHbNpjcPSevC8E7f4HHM7HDjpc99UhBalQITUuPQ0GlDm82F7Z/X4LzJWUG+g01LStFhdaLb6YWSAbcumoxmsyusjyrJoEGX3S0VGu85h9i0pBSnOm24+9ISbAiQrty0pBRZiVqc6nBgxvgE6NTyQV4T041SMd1rzsmD3e3FDfN8gWOv7K3Do7sr8fS1FfjviXZ4BWDbnlr87NxCvLL3G6yck4fqVqtsEfSz85PQ7p/j9MyI6nZ4kKBXw+Xh+KbTHtKu7EQt2m2nI9M77B7c9cbpdezWq2ZAo2IhwRL3LJ2GdJMGm98+ElTkL/Az7bC5+rX2H+5E4wzOeQMA+P9N9x/PBvBNwOvq/Mey/b/3PC4LY2w1Y2wPY2xPS0vLoDZ8IIR7kE+2WQGc3tkRw9hXzfUV/nhwWTk6ba4gZ694/sM7K6FRKYKOLy7LxolWa8hrt+6qxOUzc1CWbULJOBPWL54Kndr31YtGdMc/9yPdqEO8VgmvADRbXCEOprvfOIiDp8x44J2j0KqVePrDajzxQTVWzslDkkGDx3ZXQadW4skPqnHrP/ZLfwMgva9Hrp6Bh1ZMx7Y9tdJkvyA1PmwEhti+f3xRB4fbV22ytsPW6+ct6vEEvseRpsU2Um0V8BUOkLO3DltkEVtqpSJEd2fLu8egjlDXwOH2YNOS0qDvb9OSUjg9kU3iFFDIylqwCLu7dpsLWqVCKsCzen4BtEoFOuyRpQ/FaZXY2KP9G5eUIk4bmXN5Qqq8/U5Ijcx+bS6v7PNk60eEwVDaabfdgYP1ZskxDADb/enGPb/7eI0SD/7rKO556whWzslDVoJvwuJwCwADPGD4vKZDcvqKf9u84wjGJRpwss2GqmYzOm3usPI9Yn/ju78a7Ran1BffdF4hDGplSHZFQ5fdN6F4v0rqz6Zkyqd3iZxpPOhJLPRnI4HebNXsdCPLpMODy8qx+YppeHBZObJMOpijGIXq4YJv0ynge113QTE8EcrfDDYqpgzZpF3/2gEo2eDKJkRKuAJ5LeboFMgbTIbaVj0eAa9+XY/PT7ZDyRQh/eLvdhwOmQfee9k0tFkcuPFvX+Jnf/0St2z/Ci1mJ/RqJZZX5ODpayuQEq9FTVuPbDW3gOQ4DbbtqcUP504MudfDOytxx8VTsGpuAZ7/pAYp8Vrc99ZhPPFBNXRqBfJT44Keg7wUPW48twjXPfMZtu6swlMf+uaReSl6rFlQhE1vHgTnwILJmXC4PFg1twAmrRL3LA0ec+9aPBXKMBHFYuSNw+0vQApIkVW//PvXQffNStDB4falwooO3/yUOEzLSQgZq245vxhv7qsfUP8sCBzVLRZ8crwV1S0WCEJ0NmdERvJclSAC6c1W85LjpGdVpC9BF9HGC/n5goDozBf6isXplSK3b1pQiFVzC/D4v6tgccZG5LNKpcDikkw8/8PZ+OP3ZuD5H87G4pJMqFR9d6MNtE8Nl02480gzdhxsDBozxPVDOHlPcV1odsiv+80BcoqCwNHqL0j39EfV2PLuMfzq71/DIwC/fPlrfG92vuT8F6+x/rUDsLi8eGRXFZ74oBoMTDYY8I6Lp+BX3ynG3ZeWoK7DhhvmFUhj78M7K3HvZaX488oKbPu8BifaHHhsd1XQ+szu8uCG5/bi16/sx03/9yWqWyy45fximTmOb16ZlaCDSa/Gkx9U45Fdp8d7l4djf303zspPxuRMIzYtKUW6SYtp4xOxdVcltu/xaREHzlcevXomzE4Pjjdb8Pb+Bqldq+cXgIHD4xFww/N7cON5E5GoV2HTklKsXViIrASfhOdPzy1CdYtFcuL39L09+UEVNlxSEuLcv/PV/Wg1u/H9s/Ox60gjHlhWLj1bgZn3/Vn7j5SCdHIrad7LcVk4508CeBIAKioqhn1GFZgqnG7UQanwhYwrGENxejzmFacHpdmLUQjpAZGSotSDTq3ATecVwuE5bQgAJM0YxgCPV5B2byZlGqFRMjR3yy+ojDolvnd2Hq579vOAdEADDBoVatqtuKQ8G1t3+YTAH32/CjctKAw7qXa4BWx88xAeu3omDjV0S/o1dR22EKdcYATw0x9V45nrKuD2Cti0pBQWpwcqpkB9l012h2fm+MQgIxeveaZ0vVjQYou2rfaG0y2vKeSMUNah3epCcXo8bpg/EXanBwatCn/+4DjarZEtbrUqFewua1AhIrvLA60qsklcUxinQlOETgWTTo2bdnwZYo+RRqy5PAIyTBo8c91ZaLU4kRqvhcvrjVgWYqD2Gy7SNKMf6U9DZac2uwsNXQ6YHcFFgsQUmweWlcPm8iBOo8ID7xwJckj0zCrweDk2vXkIN8wrkP3ejzWb8ciuKsmhOytPXsR/kr/I5vOf1ODn5xeh2+kN2iHOStBJ+lO1HXZpJ3v1/AIpgu6+y6ZBqfCNBYMlExEL/dlIoDdbjdOocaTREpINMCs3KSptBYAOqxvP/OdkUIraM/85iQ2X9K1wxGDRYgnjjLVExxmbbpSPlEqLUoE8oG9yML0x1LZ6sKELd756AA8sK8fhxu6Q77WmzQ6Hy4tVcwswJdOIdJMWXkHA9c/uCZq/PfTeMdx0XiG8AlDXbkdSvEaK5tWrFVAwBqNWCYEDP/ufQlgc8lIQR/1a7XkpeqQbdbhiVg4AwOzw4q+fnsT3zs6TxvvJGUYpS048f+uuSty/rBy/9WvupRm1+OOuSvziwsm48zVfEZe8FD22LC/HoUYzOAee+OA4fnt5WdjoXvF38evrTbf46Y+qUZGXLDl8FQqGBZMyUJgWj5m5SbC5PEiJ08DlFXDB1Ix+28VILD46kueqBBFIb7YqBl30fLYiDbqINh0W+flCfnJJtJsWEbawkdux4Rx2ubx442BjSEHapWXj+pyyP9A+NdwazysgpB6JuH7ITtQHaeSL52SYdBAEjlNh6qw0dDlQNv702CQIXHacXLuwKOyGvuirTjJo4BV4UKSuGC0MAE6PAC/n2H2kGceaLUERxV/UduKpD6uxZkERPAIPsqUbzyvEI+8fCWrTfW8fwa3fmYT7l5XD4fJgfLIBHsGLg/VmyQnbcyN7665KrJ5fgJxEPSxOD6qazXj/SDMum5GNmblJuPuSErRanahq6saTK2fB7vLC6vLixr+dzsoKbDMAPHzVdLy85xskGTQwOzx46fNaLC7LhlIB3Lu0FEoFsLe2Ey/7nc4OT2hw19kFaahqssh+tr4CuAm4Yd5EJBrU+NXfQ79jDt7rmlSO4XYONzHGsjjnDYyxLADN/uN1AMYHvC4HwCn/8RyZ4yMGcbHQZnXiVKcDt75yWrtMDIXXqBh+8j+FQekUaxcWSVo1do9XtoAV4JuAuzy+Y0kGDX4yvwBtNp9uXIfNF3qfZNBIafw3LwhOy85K0GF5RQ5KxiXgR8/vkR520ZkR6NhYs6AI45P1QTst4SbVDreAbocHj7xfJbV505JSSTtGJDAib90FxWi1uINSDjcuKUVZdkJIReh7L5uGdJNWNnw/knS90arFNhxkhEsvidC5mG7U4vtz8qR0Tp3apw2bbows/cnm9uC+t4+EfO9/vmZWROenxg8sXTtc4YGOCAsntFhceHvfKSw7K1fayXrti3pcVDYuovOBgdnvSK9ibrY7cLTJiuoWGzptTsnZAEDSgqxsNmNmbhKauh2ykWpin7Lx0hJUt56OBA43YRLPe3hnJf6wYnpI4a27Fk9FfacN//jCd3+DRoU3vq4PksPpsLmQk6hHu82Ff3xxWgNrxvhEPHL1DBxrMuOBfx1Fh80lu6AXxwq72yuro9Vbv0b92cCwe7yy2QxPRVjkcSgwalXQBBTDYQzQqBjitdHZszeGqQ0Qr4tWe5TYeGmJtOEsPu+RyhMNNsPluBsMW5UiRpweCFy+XyxMj4PNJcArcLi9Ak60yC8+xiXqccc/90vzzMCU0Y2XToWXM2luGU4WiHOf8/Zn5xbiRy/skc6/Z+k0rKgYj5o2mzQGBPbnge041mSWsjNazE4sLsvGydbT2RY1bXbY3F5pDLn3smnY8s6REEkzcV4uzklT/POF3ornbL6iDN8qSAn6nhUKhvzU+EHV8afiowQxNMT6Jnu8Tn6+EBel8bCvmPTykpYm/UiJUeydfae6JMcw4M9Ife0AClLjhrwOQU/k1niBhch6BpooFAzTshNk14W5SYZea15l+rM0xbHpZ+eGBg4mGTQw6dU4JSOZII7/gZk5gW3ecaABF03LCvILrV88FY/sqgranC3OMOKOiycjPyUOKgULWjfGa5VhgiLVQX6IDZeUINmgxtqFRbC75TNsC1LjpYCkvBQ9bv3OZDDG8EVtBwQOfHq8BSsqcrH6hb1S28IFROrUChi1Spw7KR3LK8ajrsOG1fMn4skPjmNxWTa+quvEjPGJSI3XoMPmwguf1uCOi6eEfIZKBZCVKK95XZAWj9V+KTifZnLwnPmepaVo6nbimw5rn7TVh/upfB3AtQB+5//3tYDjf2OMbYGvIF0RgM84517GmJkxNgfAfwFcA+CPw9zmsAQuFuSMRNQ2AxASav/wzkpcMCUD1S0WnGyzyRawuvZbeUgzaJBq1OG3l0+DXq1Ec7cDT35QjVVzC/CH93wd1ffPzpUWEwa1UnI0i2LbD++sDFs8Qwhw9m7dVYknV87CEytn4Zs2a9gqiIDPKKtbLUHvab1fvy2wQrVOrUBFXhLiNEWYkmXEj57fG9K5bv/xHFgc7qBIUavDDaNONaKdXKOVcOkl5TmRaSt5BEhaQOL5G14/iBdXnR3R+XaXfEE2hyuyyNt4rSpEj+juS0tgjNDJkaCXd5JEen5qvAZnT0yVdI3E+6fGD4822EieBJvtDrx7uBUapQKP7q7E1bPzQrSt4zRKJMdrseH1A7ikPFv2u5iVmwjF/AK021zwCr5zX9lb16u2OeCzoy67G49/UIVnrjsLjd0OnGi14o+7qiRNzHSTFna3G+sXl+BIQze2rCiHV+CobLbgofcq0WFzBek5Jcdp8NO/fhrUxp4LejnHUqCOFvVrQ4vN6ZHtU2xRTGlMMKjxs3MLQ/qpRIM6Ku3RB8wdAm3UoI7O4rOq2YZPj7fiL9edhTaLEynxWvz981roNSpMyUoc9vYMl+NuMGw1K0GPvBQ9jHoV3vh3PdYvnhqkxf6bi6egsdsZYnsVeQnYU9MlXUenVkCj9PW/l8/MCXFaGzTqoChfURYo0IY2LSlFm9WJX1w4OUT/985X9+PxH8yCSa/xbZy5vJiSaQy7wAy0SSUDuhzeoNfUttuw+YppPn0/r4A9NV2o73RKGXZTMo040WrBFbNyoGCATqXAc/5ovEkZ8vc9U3HRwWQsFx8VBAFNTU1oamoCOMC57/8AkJGRAYViuFUQidFGLG+yx2tVIUFmGy4pidpmcl9xuD2y83NHhBmp0aYxTN/c1O0Ic8bgIZextKgkE9mr52DnkWapEBkArFlYCJvLi+oWS9C6L9y6sLeaV2sXFkGlYNL9HW4BLq8QMk4ur/BF4Ya7xvOf1ITNzHlwWXlIptCmNw/hpvMK8eA7x6BUABsWl+DNr7/BeZOysP61AyHrxrsWT0Veij4okEinVqC2wxZ03bvfOIjV8wvw8p46WSesTq1AQ5ddus5VZ+Wiw+4OmjutXzwVj+6ukoKU5GxCDF66a/FUqJQMNrcX617+GqvmFuCvn9WGaAdvuKQEty+ajL98fAI1bVbcs7QU37TbsN1fz6s8JxHHm80h87j1i6di847DUhtq2ux4dHcV/nxNBU512FHbYUeSQY2Nbx7CA1f0rfDmkPUqjLH/g6/4XCpjrA7ABvicwtsZY6sA1AJYDgCc84OMse0ADgHwALiRcy72GD8F8CwAPXyF6PpdjG6wUgJFAhcLvRmJ+HvPvx1pMuOXL3+NB5aVyxawKkiNx8k2K+5644ugBy3JoAm6X1r86crTBo0KT37oc0pPzjRKuzHiNeUm3IFt+uqbLjy2uwq3nF+MJL3vfmlGLZLjNLj7jYNS5MamJaV44ZOTIe8pN9kg3Udsr1cQYHd70W2XX/Q0dDplI0UnZZqCOrNMkw5eAfjvibZB+f4IebrCfE9djsg0f1vDpCe3RpiebArnnI1wh7nd6pL0iMTNlsd2V2HTktKIzteq5J0kkRakc3t50P0B3/0fWFYe0fmDwUicBNvtbuyp7cYd/9yPuy8pweKy7BBtpYd3VuLZ68+SiofIOXw3XFKCR9+vxNkFaXB5OMpyEqRCFy98WoPV8wuQm2SAUafGfW8fCspk8EUq+AoD1HfapYJzIg/vrMSjV89AY7cTN/0tuN992V9cc9XcAjg8Xvzmu1N8EyfOe13QCwLH/vrOEMfSwzsr8dz1s5Fm1Ab1ZYM9ThGAXiPfp+j7mA44mJgdHtlNtGeuOysq7RElXXpuUuem9F4AdqjIMGmx95tOZCXF+frRJgv2ftOJq87Oi0p7hstxNxi2OiXDiBvPK8LmHUdwZUUurA530PeaGq/FLT36ow2vH8STKyuwOiCyd82CItR1+mo8MIYQuameKZCBskCVzWZMyTThT7ursK++O6xU2Z6aDild9NWv6pESpwkpXLR+8VSY/e9B3FB7+toK3PHP/dLnI27YzcpNhFGnxsk2q5ShIc6t81L0+NWFk1GkVcKgUeHn275CQ5cD++q7kZWgCxlrtqyYLusYHqo+eiwXH21qasJ1j70Dp7kThrTx8DrMWPdSC9RqNZ792YXIysqKdhMJImp02d0hQWZ3v3EQT66MLKMy2hi1amzbUxs0Dm3bU4vfLx++ddFAyDL59GEXl2VL498bX9f3S66vL/SWsTQtOxH1nQ7Judsz41d8HYCg8Wp2/uksGLmaV4wBkzKMuO+tw5iYFo+adrsUWfzK3jrccn6xtHbTqRXITTZI19hxoAFPrJyFpi4HjDo1Wi1OdNhcYX1k3jDrp0z/531OQTK++qYL358zAT/2R+v2XDdufPMQHr5yBtZu+zJozvDIrqqQ6wrcN0+5763DIeN9z3NykgxBPjTRcS1GBgPyfrXJfonCJz44jpsXFOGlz2slf+DisuwQJ/ndbxzEr78zCavnTwxx/rrcXngEARPTjfjT7ko8tGI6Djd2wyv4gih7ZtbWtNnRaXPB4vTg6Y+qoZxfgCsrctHdx/oqQ+Yc5px/L8yfFoZ5/b0A7pU5vgdAZF6dXhjslEBB4GgxOyXtFL1aEdb5atQpsWZhIQwaJbITDTjRaoVXEHDKv6vxj73fYPMV03C8xQqBA0oG5Kf6xPN7RmqI0ch6tULqqNICtPkMWpXkaA6cjMs5WcQdncD2Oj2+qM2H3juGdecXgXPgzlcPoDg9HrctmiIZ5SPvV+Kqs3LRYnEFpUY3djkkvdDadp8u5/KKHGQl6KFVKWQ713idfEqAzeWRnFz5KXEjTottKImmgygjQSs/CEao9ZhgkE8fStBHFhHnEbwhaf8bFpfA6xXOfDIAh9srq23V08bC0dgt7yTJj9BJYna48cNvTUCbzSU9zz/81gRYolj8KtrY7C4caDDjy9oOqZ8KVyCh1eJCgj8FTZxsiLpRmQk6ODxeXDA1K2hycv+yMqxdWITkOA3qO+34/bvHAADXfSs/6HW3nF+M3+04jGvOyYNJpw66v6jnbnMJaO52SBI5Yr/70IrpqG23BV1v3QXFACC7a51u1EnjzhEZ3U+HWwAHD3IsjUTNydGARslkN3yiWSm7LYx8TXuE8jWDTbpRK7tJnRYfHY3ftHglfnFBMaoC5kW/uKAYafHRcegPl+NuMGy1rssupcC+8GkNNl8xTUo9BIDNl08LGwW1am4BlAqgMN2I379zBEum+2pAx2uVIYvPR6+eGfKZdNhciNcqMSXThDaLz/EqEm6OLEYRrZpbgPvePoKnr63AQyumo9vhRlq8Fr959UDQJh8AHGkw41cXTsaRJp/G8Auf+iTc2qxu/PjFD0PmuR02F66syMW9bx3GQ1eWI81v7yINXQ5s21OLB5eVo7rVioJUX/rqiVYrJqQGb94NVR890iWhhhqdKTg9W2dMhkqlpAhiYlCI5Y33wSw0HQ2UCoabziuSipGJQWaqGPn8SzJNuPHcItz1eoDm8KWlKM00Dcn9RFs92WbF0cbuoPVIYMaSGEDXYnbi2mc+C/IXrdv+FSbdPA9Hm8xhx6vAeU1gzatVcwukzMgfPP1fKSp4255a6FQ+SVKVQoGC1DikGn3STMXp8fjJuYXYW+OTYHjj6yr88FsT8NCK6fAIXHb8DycDWdthw/9eWoK6Dgce3lmJzZdPw6q5BchN0of1F61dWIT81DgcbuiG2eEOGt/F64rmJjrDRY1hnUaFxk5b0DnhsriU/iEonF/tXn9tBMDnPwt0Jodb945L1OPn24I37EVHtM3tRYJOhSvPysPvdhzG8lnjMTEzHl4u/5nqNSqkmYAHlpXhvreO+CQrIqyZJBIb+QiDQG8pgWJofaQDhtzk8PZFk0N2U9YuLMJn1W24cnYuqpotyEuOw+92HEZNm0+X5ZcXTsKtiyZhnL8iY2CY/K++MwkMoZEar+ytA2M+vUIxxeQfBo20mKjvtEm/Awh66MUHITvBp5uZmaCTHoSeKdgOt4CsxNO7JvOK04MiTQBflF1PzeJte2qxZHo2vAKkTqYiLwmNXXY8/u8q/GR+YZDTb+OSUmSH0VIJrCI7lrTYou0gSonT4MZzC0O0HlMilEVwur0hz8It5xfD6YlsEqNkSrzyRS3uX1YOu8sDg0aF5z6uxi8unBzR+WlhChlFKuuQEi/vJEmOi8xJYtKrYXNbQuQSjLropItHmy67A3tPdqHF4kRR+v9n787j5KrqvPF/Tt2qW1tXVe8LHbKRTgLdWcSw6CijCSBoCOugo8/w6OjDzxk10Yw8jIqJCYijaBwQlcd1YHQUHBxMMopsKjq4BSQhDWQhG0l6X6prv3WX3x/Vt1LLre7q7kpXV/fn/Xrlla5bdzl176nvWerec3xYUOfGt599DZtGZ5LNu05eGTabgU3rUr+4XtXRkjVu1FdvXp33y/H//c99uP+9F+LO3Z1495r5GIqmOt7+40/H8Z1b1uBPxwah6cC/PXcMXcFUZePbt6xJH98cD8tqSAqzQhaKJ/OOu+PJg7j1ssW489oVWXfcmQ16M2596K2Li+pYmktxbjp5ZAmL6j348k2rEBmd6NAupZaXS7PfOk41lmnCNafdlnfH5tZr2uGaxGzcpdAbVnFqOJ4XR5sCLixqmP70TFfHXSnyauZdzl3BOL78ywO467oOfO2ZQ3k3FJhcDhucDgnf/V3qLt6vPPEq3nvxArjsqRsfVM1IzzEBmHfsdOKu6zrST2CY1+jkUAzf+d0RbNvQkT7Orr2ncNd1K3DHYy/lxVhzf+bdRcPRJP7pJ6mYv2ndEstGXjCexMJ6L77z2zP541/fvTqvgXXv04dwz02r8Gp3KD0UkPlIbe71fM9F8/GtZ1/DVR0tWWMjZta/zmaMnslDQpVLIjzMO4hpynTdwDMHerDvZDD9Y+OKeQGsXdZUEd+vhirZ8qadhmkarm6qEqqBh/98PK9d93/fcX65k1aU06F4umMYGB0Wc+d+rFlYg8Wu0tbNrfoActsj5nAWZr9VoScYTwyOXV5lloM1Hhl/s2Yezq3xYCCcwL3vWQ3dODOB3OP7u/BPVy7HV554FetXtkI3Uk/Anxt34lNXLYfdbstL8/eeO4pPXrkcX7YY///Lf7MKkk3gizesxJH+cHoYBfOzLm3y4bM/248ajwxFM/Dd3x0p2JY6OhCBLNmQ1HTc9/RhyyeBvnD9CkiSSG8/FFXgdkiQJAEBAy6HlDX/VTSp5h1rQZ0bFy2oTY95/Myr3dhx82oc7g1j1bkB/POjL+XNu5XZmbxl/QWW6ffI1jdJCgH84A8n8Jl3LUetR8a1q1sRV3X0heIIeBx5Q01sXNuGO3d34trVrVjRGkinZTg6Q+4cnmmsHgms8cjoCyXw8ukRHOoNpTPmeB1xVpXDLzz+KjZf3oYH/tcbsf9Uasw2ryzhnSvPSVdWc7/gX37iAG69bDFeH4rlVbrv+eUB/OCDF1tODCYJoMbrTHfcmo/y3XrZYrT4XbDZBG69bDE8spSVcYaiCppHfyU6t8YDr0vCt29Zg3BcxSvdI1kzLLocNkSVM7+aWD1S+OjzJ7G82Y+N61KzWT+85wTec9F8eGUJ3/zNkXTj8uWuEfx8Xxduv3o5Pvhg9mzYW362H//9sbeOO4vsXBqLrdwdRD0jiXTHsHn8LTs78e9/f3FRY9Z4nBLcDlvWGNLu0eBXDEXVsHZ5c1aH4Ma1bVCK7FyOJTXc9o5luOeXB7J+bCm2czqpqZZjFqt6cdubDdLcBup3binf5FflEokl8PQr/VmTTW5d344Hnj2MH/z+GO68tiPrToKNa9tw+0/34cN/vQR1XgfuvLYj6463eDI1O6tVLDjcG8ZtVy7H6eEovnTTKhzrjyCh6njx9eGscdDN9f9yYjj9Q9pYM9WbP3K5ZXu6IzkzDp7X4IVbtuHnFg16M25Z/cJs1bE0l+LcdEpqBk4MxtJP4ph3fZfzcW3N0CzjjI7innAotVPDcTwx+kjgcCSJaq8D//a7o6jxOLDy3PG3L7WkasyoODpdHXelyKu5dznvOzUCTdXSjy1m3lCQ+UN9rVfCt/9uDQajiXRsVlQDH3zL4qzhy0zHB2KQ7WfKevMpm6Gogg++ZTESSQ333LQKXlmCAQO/P9yLb7zvQvSHEjg5HMurc5rjCktCpBukv3q1N/1DoTnL9/ktfmi6jkhcwUffvgRxVcfyJl/Bu+sO9YbScdyMu7nXU0Dg4w+/aFkWZNa/znaMnolDQpWby1cLhzw3f1yn0jgxGMGhnvybNpY0lHZSybPFaZcs71x1FjncXbmFE0lcs7IVh3tD6c75a1a2IqRUxhOVPaNPE+b2gZyNurlVH0BueySpGXjnfWeekPn2360p0OloH7O8MsvBCza9FS+cGM5qq915bQfu/vmZGxo3rm1D30g878lYt8uBSCiBL4z2NeWm+fhABP90xVKcGo5j2zXt8LrsqPM68Gp3GJ/8SfZEdCOxZLoO4R3tML3hwnnpduKjz5+07BD99z8cxycub4NNiPRTp+YwGZINuHhhLYajCh59/iQe/MDFOD4QgVu2oz8UR+9IArGkhosW1OLf/3AE33zfG1PDYrX4s+pJC+rc+PBfZ0+q+9n1F+CBXx/Gwd4wvnPLGssfslfPq06n6bu/ey3vR/Kt17RD1fPHcjbrRF3BOOzChv2ngnA7pHR61iwI4B/eviTrKWezTmW32aCoOj66dgl27T2FRv/EbjqZM53DuZXlloALt7xpQfo2/MwMNl5HXKHKYVuTD16nhC8/kXqk+SNvX4Lv/u7Vgl/weFJHa8CNGq+cNT7po8+nZrGPKdadTP/2gYswFEnmpUHTAZvNhroqB6qc1fjL68MwDKTHDQ64HPjaM4dwsDeMz1/fgde7oqj1yIgmVSxp8GbdRbx9Qwfm1Z45Z1aPFKYe43bgr86rw2A0iYsW1sAtp34i+cy7zsfrg1Hc9/Sh9ERPobj1Lfp94fi4ja65NBZbuTuIRmL5eSueTE3kVRRD4Lv/czT9C7duAN/9n6NFj7nrddqzxqYCJjY2VULVYBciq3PaLgQSanGdLl7ZDpcje4JEl8MGd5ETM8ULzIIaq5DHv0pF1w28eCqUrmwAo+Mr7e7El25ahcO9IdR6Hfj++y/C748MZE2q0BWMYUGtBwIi/TgVAKxs9WPVvOr0r7ZmrDR/zBoIJyBJtrw7ja1ix+J6L6KJJD769iWWHR/mr7Zm2XBqOIoFde68yQQ+u/4CDIQVvHF+bd7304xbuRWVQpMczaU4N51CCTVviKYdTx7E/yvjeH02SPjJntEnJBIqPM7UnTS3X1WeO2lqvQ68fXlj+pFAqR94+/JG1JRpgrywMvMmEZyOjrtS5FWru2LPqfXi/zy0J++GgvOb/Qh4HOgPxxBLGEioSVS7ZbhlCR/8q0W4+xev4uu/OoxN65bA5bBlNZAlkeq0yP3xDUg9PtnZNZJ+suxLN61EW1MAB7pDaPA5sWpeNX724ikAZ2Lsw3tO4M5rO/Cd372GPceD6eV/OjKAjeuW4jMZDddPXL4U//Gn41i/shXf/d0RfOmmVegKWs+Wvm55I958Xl1e3TLzeh7pC485NqJZ/2KMJqo8PSMJy/b0hfNrKqJzOKQk8fVfH8pqF33914fwxRtXlDdhRSr0RKW/Qp6obPa78IG/Wpj3o23TWYj7hfoAzPbIF29cic/+LLtddcfPXsrrNN20rg1epzRueWWzCegG8tpqn/3Z/qz+qvueSfU/HewOZaVtOKJgXo3HMs2SDVja5MOJwWhW/9G2De34t+eOZh3PHEZhKKrgrus64BlNe26ZXF/lzPpBOv1EkN+FHU8cSN+Ik+qMPYIt6y/Ay6eDaGvy4fdHB/GGBYPY8eTBgk+Mfm7Xftx9/Qo899oAfrLnZPo7t7TJlzep7p27X8atly3G1Sta4JZteT+6f+LypQAMfPXm1YgqKo4PRvHQc0dx62WLsaDWg3k1buw/NQIDctZdy+b1e+j3x+Fy2BBLavj+c8fx4csWZ/VNOGw27N53Kt3fcuMb52HX3lM4v9kHIYDv/PYItm/owLIG34Ty4JzpHM6tLP/Nmnl5BUVmx+1YHXGFKoce2Q5ZktLjT443SZ3LYUMwpkCSbPju745kZc6H95zAcIFOutcHUzMQjvVI9NZr2lElSxhJaKN3cxzEUFTBl29aBZdsw/GB7C/q5iuWYtO6NkSU1Ppf//UhfPZdF6SDjdUjhfc+fQjf/rs34v+M3tnncqSGygAMfPmJg1lpv/fpQ3j41jcVDFLjNbrm0lhs5W58mOO95h6/2DGDo0oyrwNt49o2RJXiJrQbiVtvPxIvrnPa53TgC4//JS/9PyhyzJ2kBux48mBW5/aOJw8W3bndXOD6NQXK87h4OZiTsJ3MmC3WFE/qMAwDq+dV43BvCE0Bd7pzwSqWZY6N/u6L52f9amvGyo++vQ0L6z0YiSdR45bxww9egq5gHJGEitPDMXzqquX4wuOvZm13zxOv4n2XLMAP/3gCN6+ZZ3nNzIkFzE7rLesvyJvIyawcLG3y5cWvzLhlVlQKTXKUu/5sj3PTKVHgB5tEzrLpFEokLZ+QCJVpbHKn3YaIouU13pxSeYaVKFQOFTsxaaUqRV417wZq+PuLcXIoBodkQ18oe6LYrmAc9z19GJuvWIof/enEaNw9c1faJy5fiv/edxoffMtiLG2swmAkgX+5YUV6WB5zvbuvX2E55vr5zX5s3/1yOv3dwzFoBrLvVt7QjnOqXYgoOo72h7F+ZSvu/1Vq6Is9x4PpernVjOZffepg+se2Teva8IWfvwIARU8ql8uMvebEO4XqX4zR5WHoOscepkmLFPqxsch2SbkpSd2yXVTOOsxEJJKV/URlKJG0/NH20sW142w5cYX6AN66pB43vKEVA5GE5URkoZyJZx/6/XFctLCmqPJqrA7pzNcALOuJPpd1J/T5zX4c7Anl9R9t3dmZNRavuXxBrRsffMtifO2ZQ/jY2jbcfX0Hjg9E0z9M/92lC3D3z1/O+y5sWteGgMuOg71h9GVMrGcTqcmNVU2Hw27DjptXpe8uHuuJ0dPDcegGsoaYLDSpbmvAjX99+hDm13rglSXcc9Mq6LoOh2TDkf4IIoqOruEodjx15lj7TqXqGZlDs37xxhX4/vsvwuuDUQyMzj1y4xvnwTAAtyxhKKrggWePZN29XuNxpIeYzez/6xmJoa4qNWTtlp37say5CqvOrSki96XM7lp2BptN4Mrzm/DwrZeiKxiHZBNj/jIzVkecVeVw07o2fPzhF9O/eHztmewxf02Zj85tWtcGRTPSt5cDqaEb4qqG265cDtluPcldz0gcfrdjzEeit+3K/+IBgIHULw3mI/fm+juePIiPvn0JDCM1hMQ1q1oRUVTc/8zh1Nh3BQbm7gklsGldGxbVe+GR7fjsz17CNataLddNatqkK9VzaSy2UjQ+pjLxgg7DckIcHUZR27vsdsuA+/33X1TU9m7H1LbvD1tP9DRQ5ERPwZh153Sxd04rqo7NVyzN+4U5qRZ3/iqdqup47sgAekbiaAlYV3Icki09yZB5R1o8qVvGMnNsc01H+ldx8737njmEL920CqeHo7BLAqFYEl0iBqfDnjVcxScuT/341ehzwmGXcHo4imtWteKHfzyOu6/vwLH+SN442ZuvWIqBcCLrh7tCM+vqBix/UJxo3JpLcW461VdZj7Fa5y3feH1VssMyzj30gYlNHFEqI3HVsvHWXqa7q5t9Lss42nyWZwcvt1LlVZtNoC+cwJd+eQA3XDgPy5t9BWKxwKfeeX7eHTFm5+t3f3cE99y0Cl/85QF88sqleXnk0//1Ul595c5rO/DNXx/OGnsvcw4Lc9stOztx62WL4bJLWUNM5DZIC8VdyQasW9aIvkgiPc78w3tO4Ft/twYOSUyo7pN+vLbFhwV13qw7eDLrX4zR5cGxh2kqFtR6LeNf5tw2M5mrQLvowTLVFyYqXKAPIZKojM7508PWnaddwwmsnFfaYxXqA7hoYW26nLHKy1FFs5wr58L5teOWV40+67aaV5bwkbcvST8plNSsh/v69i1r8voNPn/9Cnzz14dx2bLGguV3JpfDhuODZyaTv+Ox/fjBBy9GXZUTn11/AXpG4unvQOaTmEsbfdANA88f60vf0GgOv3HXdSsg2VKdwbf9ZB+Gokp6jrBCPxi5HTa4HBJ27T2V9WOzJKzPu8dpx81r5uHUUBTnjs4tZvWEaeZTsOaxdOPM37c/+hK+8d4L4Rid5yPzXH75plXptJifbePaNgxH1XTHsLmfbbs6cc9NqzAy2mcRT+roDsaxagLDw82ZzmFdN/DEKz3pL1tmh4TJ5UjNZDheR1xm5fD4QAR/eX0YD/3+TMX2jsf24+FbL0VS09HWWIXbH92XVWkeiSXx1ZtXY/vul3HjG+el05B719yCOnfeBDGfvHIZvvu7o/jbi+fjR386MebsjVZfPCDVCLRav9nvwh05M4kCwKs9oYJfihODUQCp2+0X1nnx/fdfjL5wIj1JSOa6xQapsc77XBiLbaqNj6lOaBeJa3jo98fzfoFc3lzcYwmF7ngfKbJztVAlIlxkJcLvtlvm1SpXceHO77LutCm2EhaMJ/H9/zmWdf6+/z/H0NY4u/MtkMp7/72/Kx3z1iwI5I2rao7RZMbLX73ai+0bOrBl5/6CT1u0Btzpv3PfO9ybesTJbZeguwx4HPa8u3u/+tRBbFrXhriq4zOPZY9xfKAnhH/5xQG0BFy49bLFWD2vGvVVMl4fiuFLv3w1XQFZs6AWrQU6u20CBX9QnGjcmitxbjr1hxV88spl+PITB7LK0oFocT8YnZU0RRKW+XkgkihLemIF7ljNXTZdFtR5sbjBm/UI3eIGLxbM8js0S5lXW6s96TtfrCZoufv6FRACONwbKliH3Li2DQ8+l3o08eSw9ZMgR/rCWeXdUCSBg73hrPViBRpiuoG88RSNjN9RXQ5bwR8ZL15UixXzqgHAcsz3ibLZBBbWV2F+rRerz60uuD/G6PLg2MM0WQtqPXmTZ951XQcW1HrKnbSi9IdnVn1houq8smUMry3jD/QTUbhdWfoxn8frAyjUeSzbz0y2lvmjZjHllfkETmaH5BduWIG+UPYNMsua/Zb5MKZouHRRLTpG57HyOCX4nak7eS9b1mh57laOjsWb2R4zn9I093ukL4KvPnUIt7xpAdoafel9dAXj6U7kb/3dG/HKqUHMr/fjh388hq+95w0YiSdxfDCKrzxxAENRZXR4h9Q+v/D4q9i0rg1vWlyXvgM6M12r51fjX588gFsvOw/fevY13HPTKhzoCcHlkPJuItq0rg13//yV9DFOD8fwT1cuLzj8ROYQXLl1nXgydYPq0sYqtARc+M4taxBTNBzuC+P4YASP7Hk9q5718J4TWFR/foHroaIvnEgfpzkwsZsq5kzncO4A34/sOZn3Rbj7+hW4cH415teOX7E0v2w9I3HLyY5iSQ2XLq7HhbqBFa0BHOwJ4aVTI9jx5EF0BeP46NolWWP8xpP5d80dH4jhgd8cxvfefxEGwgpODkXx3d8dRVcwDkXT05X+j6617ujO/eLddV0HvvzEq7h5zbnWHb0Zj4DHk6nxZu65aRUefO4I/vaSBQUHAf/Mu87PCkBj3fnKSnVxpnKepjqh3YI6b9ajFMDEfmFvKHTnU1Vxwyq4HdaPpxQ75q/LLlne+Vzs9qG4ded2qMhhLRbUTu38VbJjA5F0xzAA7DkeBHAC375lDQbCCdhtNtzzxKtZj0S9bXljeiy1ZU3Wd7edCsagG9Y/UF3Q4oei6RA2gQf/51jBX6kX1Hmw+ZHsAtt8ZBlIPT60vNmPty1rhM0m0NFajfNb/FmVMwCWT420NVXxseIZrNbrwOd/fixn4oZj+EqRQ8WcDYXvEC3P8DN+V4HGj7M8E97YbAJrlzVhcX3VnLpDs5R5tb3Fn+4Q6QrG8fCeE9hx82oc6Qtj1bxqHO0P4+5fvFpwBvA1C2owFFHw/jcvxnA0gbZG6/h84fwafOq/9qUnrvnCDSvw+etXZI0RXOOx7hwwjOyn9rZe044HfnM4/f4Xb1yJem/+BHqb1rWhNeBO54dS1itZTyWaXU4MRfG1Zw5lxdWvPZMac7gSvueNPuv6QkOR7apyiyhq3o+TG9e2IVIhw3q0+N2WZdA5ozeulNpYZVChzmNg8j+SmvMQZH4/BsKJvKE0TgxErO8wdkq4/pu/x4I6N7Zt6EAiqSNqS6afpM+99puvWIr7Rp9OEgJY3uTDPU+8mnVnrcuRmgh8KKrgi48fKNjXpekG2s+txdvaGrHq3GoMhBP42I+zh5Y0n4Qyx0+OJTWMxK3z5LH+CNYub8bDf0pNggsgfcNjS8CFD75lMRbUunFyOJZ1Y+hXnzqIL920Cgd7rH9sn1/ryeqTyxwyMX0eZTt6QgksqPFAklJPf52TdGPHkwey7kY2z7PLYT3CQHPAha8+dSjd99feEigqH5jmTOdw7ngq5hfhwQ9cDAPGpBse440Pa37BAeDjD5/psHv0+ZPpGZjNzGl119zxgRheOD6EBXUeNPic6Q7lXXtPYev6dmzb3ZneV2bQ2ri2DQ/8+hB2jA6CfWIwitZqF95z0Xz8+M8n8n79uOu6DnxldCI9UzyZmuX55jULYOg6mvzWg4Cf3+zPu6uCj92Vz1QntFtUb925v6i+uM4vuyQsHwd2SMVdf5/LnnfH/NZr2uEr8s5fq0Luod8fx/y64u4QOLfWbfmdPre2uEpApd+hMBVWeW/P8SCSqo5//ulL6TGjMgvjc2s8OD4QK3h32+evXwGHJPCVjIkGMu9CVnUd33n2CA72hrFxbRsMGAU6uaxn7fU6Jfz41kvGnKwo01XtzVj2sbfixGAEHtmOJr+zqB8UqXzsNhvec9H8vIq9vUzj6QKAoqnpMjwd59a3I6mXp7EkFYjbUpFx+2yYi510pcyrdrsN161qRVtjFXpHEqj2OBBRVFyyqBavD8XQOzoE06PPn8yLrZvWteFoXwTfe+7M5LJf//WRvLrjxrVt+NR/7cPGtUshYMDncuBofxjN1U58831vxF9eH4KmA//v2cO489qOrOF+zBsMXA4bljX5Uh2+1U7cff0KKKqO+bVeLKr34o9HByzL9DfMr8aiOZQ3ZiN9dCzhnp4eFDlyGdGE9YzE0/XMTNM10fdUGdCxfUM7tmQ8hbd9QzsMVMaYw7LdljXRuHnn493XV8aEegvqvGhrqsp6kqmtqapsTzIVqhtNtr7U5HdBtp+p65n9Ubltpgd/fzyvff6Jy5fi1a7UE5zHB2L48A+ex883vhVDEQU//tMh3PHOCyBJqTt8Q3EVst2GkXgSB3vD6bF3P/PO8/G+SxZk1T+/eONKPPjckXTd5NHnT1repPgvj7+C7/3vi2G329I3bVq19TLn+1ra6MPh3pDl3bi3XbkcX//Va+gKxrHv1AgW1LnxxRtX4vZH96Xnjrnrug7LG0OP9UfSx7DqsP3vj70VfeE4GqpcODoQzrpJdOs17bjt0b3pH9k3X7EU3/+fY5DtAndeuwIuhw3f/d9rcLA7BNkh4cM/eB5LG6vy4sKmdW2IJDTcfX07ar1OtLcEYLdPrP44ZzqHrTpxh6IKGnzOKRUMxY4Pm7veUFRBW1MVvnvLRTgyEME33nshIopmmaHm13kBGEiqWlbn7I/+lJptujXgxmBUwXduWYMXXx/G/DovTg9HccniBnzx8VewdX07jvZH8V8vvI63tDXi2tWtMGDgyzetGu0Yd2Lv68PpTJp5bE0HtuxMzVj50ycP53XsFOo0nIuNupliqhPaTbVz/9RwzHJYhXk17qIGRE9qOh74zeGs7R/4zWF85W+Ku3PK/BEl987dYn9hjyQ03PaOZelxuV0OG257xzJEElpR21f6HQpTUSjvmZMhdQXj6bGihACWNflwYvDML9Hm+7dethjnN/tR7XHAI6fi0GeuvgB2O/Dlm1bhSH8ECVXH/c8cxlBUwQffshj7To3gvmcOYdO6trwfy+66LjWusFXaUo+vF39dbDaB8xqrcN4cGCZktugesf7BqNgfvM4Gl92OR19IjZkdU1S4ZTseeu4Ibr/q/LKkxy5scNltWY0fl90GByd+mlalzqt2uy2v3NV1A/FkP46P3gWUGZdTQ+jUoPP0CL733FG8e818PLwndQdNVzAO3UjVHQ/2hqDpSI8V/JnHXsK/feBifOLhF/G+S+YjqQqcikaw8pwAoqqGSxbVYPfek/jqzasRVzUc7Y+kbzD47PoLcGo4ilhSw7H+KC5b2oCF9Wfia6PPVaBMn93jT88FPT09eP83nkAiNAxPwwQGRSSagHJP9D1VCRV46pUu/L+/eyOGo0lUexz44R+O4u/etLjcSSuKyy5Z/uhZ7BOd5Tbbn2SaX+PBx9a2Zd3U9M33XWjZbxaKKVn1k//40/H0HbbAmZvRJJvAFRe04GM//gs+9NbFuP+ZM+W3eQfuwjoPjg1E8Z3fHcFn11+Q7jxt9Lkwv8YDh2TDFx9/JV03afY7c56qStU/+sLxdJus0Hc9c76vz49OYGvVpyXbRVan7e1XnY8rz2/CwjoPekbiCLhlJDXd8hiqrlvesPnFG1fi0oV1sNtt6XQuqvfi56PD00YSWtZTtfFkai4w827nW/99D37wwUvwwQf3jM4Fkeqf2HdqBJGEmtU3+NDvU/Wqnxf5tLiVOdM5XOoZhjMn/LqgxZfO0E0+F0LxJJ54uRstATfaW/yw221jdrgtbqjCS6eC2PbjFyzvjPvKE6/ib954Ln74xxO45U0LsjLc1Sta8K9PH8JQVMGXbuhAc8CVNfv59ms70B+OY3mzD+3n+HFyMAJZsiGc0PBKdwi7953CZ955Ab7/3PGCw0aYv7hkNiBWtPrT4wzPluA4Wyys8+L+974B+04GoRupQeRXzAtMKq8bk7iTI3OcQ5PLYUuPGzuegYhi+Qv/YLi4YR2WN3vTY9ie+YW9A8ubi/v8p4bj+M5vj2YVQN/57VF8+p3n48IF429f6XcoTJauGzCMVOftod4QHtlzEkNRBXdfvwIeWcrqADbHlvzgWxbjpy9k37U2FFUwr9oNl2zDi6PjuQ9FFXz7ljUIRpP46I/+knds8xfheFLHOdVunB6OYdO6NsyrcePkUAwPPXcMV69oyYtxnGV+bmgJuC1jUksZJzfzuSS85+IFWeX1Xdd1wO8uT2OpL6zkxXvDSC2n6TMdedVmE7hkYS0kG9Dod+HO3S+n74i589oOJLXUY5frV7bi4T0ncOtl50HTdXzyyqWo9ch4tSeU1dADUrG3LxRHVzCOLz9xEAvq3Pjae96AgYiCBT4PekIJPPJ8Fx55vgstARduuHAebnzjPJzf7MOJwSgiigbDAL75myNY2uzL6hy2Gg9x07q2vHk1qDK5/LVFr2uM3mkMAE1NTbDxxysqQqn7AKabzynhDfPr8P/9+/NZMdBXpmGfJqovrMDjkLJ+fPY4pIqqX8zmm95ODEXTHcNAqjz/3K7O9B2zZp77lxtWwoCBHU+dGTLKvMPVZP7oYhNAjcc+eiMisGndEjyy5yS6gvF0fePhWy/FubVu3Hhha7o/KfPGmyvPb8K8ahdOB+Pwu+2okh347u/+MuaPPFbf9S/euBKt1S5c1laPjz/8YnooCLNPa2WrH22jfVqA9fAcK1qrEVH68X8f3YsP/tWivPl07ry2A0sbq7C0yYdzAi488v9dikhCKzgxbubwtM+fGM4abtG8Bplt2+7RO6JzRxkYiCbz6mPA1Poc5kzncCmHOig04dflyxqx86XTeY+TX7eqNd1BbBVYUpkugNuvOj/rF5LlzX5873ev4T0XzU93kMyv9eCRWy9FRNHSX75zaz04PRRF14iC//jTmbs/Lpxfg/MaPdi9txv37szu9H30+ZPpL4dHllK/BsWTlneEmL+4AEh/oafyiwSdXbpuYDiaTA+0buZDXTeKyu9TndAuc5zDzOO3n1PcmDdVTuuxLz1FDvzfH1bRNRTCgx+4OP1d/8PhHvSHa+Avon+6yW9953GTv7g7jyv9DoXJsMoz5hju86o9+J8jfXmPIm3b0I5vjE5M9/CeE/jm/3ojogkVtV4ZX/j5K9h3aiTrGD3BOF4fihb8Rdj8+5yAC01+Jxp9LgxEEvjYj14EAOw7NZL+tTqzIsAft2a/2iq75SOZtb7yTW4UjGrQND2rsaRpOoKx4p5QKLUajwN3//zl9BACmg5877mjuOfG8o3LPBdNR17VdQNPHejF5kdeRI1Hxq2XLcaShiq4HRK+9swh9IUV3HDhPAgB3Hblcnzr2ddw9YoW3P+rw/jQWxcXnKDYLOPMu206WqvT8fVIX9jyB0KrSVpyy8pCQ0W9YX51VicyzX6J8DA2/7gPDocD//aPV6KlpaXcSaIKUOnDHdpsBlqr3Vn1hdZqN2y2yhiLhfWLmc1qKIbjAzG0VruyOkrnBdz45SvdWfmwOXBmSIrMH12OD0QwEEliS0b/kznO7lBUwY6bV2NFRh0hl64beOKVnqx25aevXp7Xv5D7I89Y3/UjfeGsp+QL9WkV6qsTEDg+EMOWnS9jZas//eTfgjoPEqqGd3/7DxPuN2nyuwrWqTLbti2jfQvm69x1S9nnMGc6h4HS/epTaMKvH3zwkrxfXu54bD/aGqvGfZzezMxnHrOWsPfkMK7qaMG5tV58fF0bPE47WqtdWJmzrwV1Xrx0ahjv/lYqU5qdWi6HDQ//n0vTd1uYacqdGbra48COm1fji4+/gr9/8yK4HVLWHRp3XtuB+391KL3PSvq1dS7q7ApOOh8CU5/QLnOcw+5gHM0B14TGvPE4rCeU8xb5+FHPSBxffeYo8MzRrOWXLGksKv0rmv2Wdx6vaPYXdfxKv0NhMqzyzKf/6yX8fONbYbfbMK/aiy0/68xq3P9kzwn805XLcbg3hLecV4/G0bF7jw1E8ma6dzlSE2b+ZM9JfO6adnxuV2deZcN8UmJVazVkWcra1kwXf9yam7qGEnhkz4m8IRwW1nlxbk158oHNJrB118t5FboffPCSsqSnxiPhI29bktcpWeOtjDuTZovpyKuZ8bormJpU2eyoNX+Uy3y6461LG9Pl8aPPn8Q/vu28vDL6zms70FrrtBy/HZj4DOuZmvzWw0rM5h9cqTCXrxZ2u5R3B7HOu4ppDJV852c8CXzlyQNZnatfefJAxXSusn4xsxW6qanW68z6zhzpC+O2/9yXt97Dt16KWFLLKvt7Q4m8/qd7nz6Eb9+yBq3V7nF/nLFqV979i1ex+fI2/OCDlyCp6ePelZv7XZ9q+zzzPO07NYKNP/pL+vO///t/nlS/ycI6L1bMC+TVqcw7ss00rjgnYDnB3669p8btMJ+oOdU5XCqFBrvuLrQ8GMeqIobSyhzL8khfGD/60wm8e818bBqdddG8NX7lvOw7QG02gaiiWR67a4yBuc07Opc3+XFBSwDLm30YjCTgtEtY0RpAKKGiyedEXZWML9WuQlRR0xOEVMqvrXNRV3Bq+XCqE9oBZ8Y5LOZ4ufojiuVdQm1FjvE61Tt33W4HruloxsJ6D3pGEmjyO7Gi2Q+3u7g7tyr9DoXJGC/P9Iash9q49LzU48m6kZoNdsfNq3Hl+U15hffd16/APb88gK5gHMMxBR99+xI0VDlR7ZHhc0v4J99StFa78cZza7I6hudiRz3l648ksOd4EHuO/yVvebkMRRTL78xQpDyPWfaHVfzhtX587/0XYSCcQF2VE//55xM4t9aDtqayJGlOmo68Wihez6/Jnk3bHFrsxjfOy/qB7Ru/fg23vnURvn3LGoTjKhqqZLSPlpHzqq3L6anMsM44TrnMO4jtdglfuukNaGpqQk9PD27/z72AAO8qplmlZyRRYLi68tVhJoL1i5mt2DK2UN0hltRw6eL6rOURRbVcV9X0ovoSCh1rJKHh2UN9WN7sxyWL6ibUtp5q+7zQeVK0/Mn7iu03McezXtJQhQvn1yCqqDi3xgO7JLByXiArjeaNd4ORRFYH+fwaDy6cX1OyPgd2Dk9Coc6nlgLLmwMTv7thYZ0Xd167Arf++56sXyJuf3QfVrQG8jJbk9+FBXXu9K+KALBr7ym0BNyWabpkUS2uOL8x647OsX5RXVBXeb+0zlWFrnmx+bDcwyLUeuS8WVNlu0C1Ry5q+1I0JN1uBy5eVDfhtJsq+Q6FyRgvzxR63ytL2LhuCVoDbnzorYvxxcdfwfJmX17hbRNIPwoUTmj4zm+P5O3rvz/21qyOYWBudtRTvtZqj2X+K3Yc9LOh1itbpqnGW1ycK7UmvwvPvz6Mlhpvqg7RE8bzrw/jo+uWliU9c9V05NVC8bh7JJ4eluyytgb800/OjM2X+wTGF395AI9veit0I9WI6wonsNBpHzO2TnaGdcZxsuLy1UKLh7D5x3vgq2tC8NQReBrOhUMu33BBRGdDk99pXccucri7cmvyu/Dzzh789MWu9DKXw8b6xQxRbBk7kf6BBbVey3Xn1078Lt3M7W2jd85P5IlmIHuusCa/CxcvnFjHMlD4PB0bsJ7wvNh+E5tNYGF9Vd4wWbmvrSYYNpWyz4HP3EyC2fmUOfZH5i3fmcvvuq4D7S3FjbWayWYTcEii4C8RucyZJr/7uyO4/5nD+M5vj+Bja9twfpPPMq1/dV49Vp1bU/Sj/lQ5zDF/J5sPC+Xv6bpLx2YDPnzZkqy8/OHLlhQ9+YwZvH++8a348a2X4Ocb31r0eMk0OePlGav3P3XVckg2gW89ewS3//QlfOe3R/DuNfMxGEmkOxEuXVyPxQ1VmF97ZntzJtjcYy2qt86fuftiPph7CsbEIsdBPxt0GNi4Njsfb1zbBgPlGUOwUB1ifo2nLOmZq6Yjr1rF441r2/DDP57A1391GPc9fRhJTcftV51fMObe/9434OWuEN5532/xt9/+I95532/xeGc3dP3s5F/GcSrE5auFO1APp6+63EkhOiu8TgnbN7RnxeDtG9rhrZAJ6crdrqTxFVPGTuQ6Lqq3XrdQW62YY21a14Y6j4yfvnCyYH+YFXNenFLUV6zO02zL38LInZ56hhJCXAXgXgASgO8YhvEvY62/Zs0aY8+ePWctPeYvELm/sKiqjs6u4KTGWs11pC+Md97327xfIqzGyxxrXfNXDd5xMW0mdHLPRl6daj4slL+nw97Xh9LjZ5vMMX2KGTOZilbSfDpensn81dYjS4gqGj7wb38u+jpn7r/Z74KmA31hxrQ5Ysp5tZRlcykc6QvjA//2p/TTPoYB7N53Ct9//8VleeJgIvUNGlNF5FUznh4fiOAvrw/jJ3tOZt0lnFt3zI25hgG862vMLxWu7HXVrq4ufPgHexAfGYTk8kGLhyb1v7+hBUOvH4Tk8sEhO/DA/1rDYSVml7Ln1XLa+/oQNv74L3n1hfve84aKaReVs105zYr+UJWYTydyHad6zXXdwNH+CI70h5FI6nh9KIqHfn8cXcH4hOob01G/rcD8XTBxFTGshBBCAvB1AFcAOAngz0KInYZhvFyK/efeal7MBTV/OTArz388OpDedryxVq2OB6Qy77GBCHxuB2AYiCc1fP/9F+FwbwhLGn0IxpKo9coIxRT89lAf4kkNDT4ZSc3AYCSZHoezymWHXbKhZySG3pE4uofjaAq40Ox3oS+cQDieRH9YgUu2wSlJqKuSMb/2zGce73xM5nzRxEz1HE9lzF8AiCeS6A8n0BdSYBMCzVUyPO7iH3cejsVxsDuSHrN3abMX1e7iHq+IKhpufcsC/FVbE3pDqc//u4M9iCpa0cef6vljHi/eZB7VqZLtiKsaPn55GxbXV0FRdXhkCbIj9bTEf+87jQafEzFFhd/lgCQJhGManA4booqK08EYWvxuXLywDqqq44UTQ+gZiaPR54TTkZrhNaHqkCUbwgkVsaSGJfVeaAZwYiiKKqcdHllCKK5mXd/Mz9Loc0GypR6hZh6ofIlkEglVh6IZSKg6Eskk7PbyPZK5sM6Lr968EklNpCuT65bXle1Og56ROO658QI0+avQMxp3e4LhCY01T6UxXXnVvDfkwvk1eO5wH953yXw0+JxorXYjGFXwdF8YtR4Zkk1AN1J3Ap3XWAVdN/DnY/340k2rYOg6qr0yXjkdgmboCMWS+OORAUQUFQsy5qhQVR2H+kYQTeiIKhoiiopzAm5c0OLP6/g2O8e7gnG0BNxob0lNBvtyVxCng3H43Xa0+N1YwJhcsczJ43p6elDqhyUMTkxHs0xU0fC+i1qxen59unwOODGhdlG5jSQSWe3K2ip70e3CmWC2twuL/XwTGTax2HULHduci2tRvRePd3ZnTdiWeWeurhs4PhBBbziOpGpACAMOm4S+cAK1Xhluhw0fv7wNAGC3CficDlS57BiIJPD6YAR+lwPRpAZV01HtlhEdnVzPbAN6ZDsUTUOd1znmeZlf40m1UYdjONQbQpVsR5XTjvOb/XnDHk7V2cyPFdE5DOBiAIcNwzgCAEKIHwO4FsCUO4fNW81zxyct5jH0yWxbaBuHJPCxH52ZeO7TVy9HLKnjq08dzJoc5Du/fQ1/s2Y+tmbM+PnPVy1HwOPA/b86nF62aV0bmv0u3P7TfTg+EEvvU9EMfPmJA1nreWUJ59SEsXZZalT4sT7TVM4XFafc5zgaU7B7fw+27Dwz8+X2DR1Y39FUVAfxcCyOJ/b35W1/ZUdDURWB1hoH5tVW4X9//09Zs9q21hQ3jtxUz1+5z38lKfZcWa23+Yql8Mp2bBydcHNBnRv/+LYlWbHtE5cvhdthw92/eDUrDj685wTec9F8rJrnx8nhBLb8bH/WPr7x68P4+zcvQjSp4d6nD6HGI+OWNy3IqlhsWteGh35/HENRJT0R3hOv9GSlMXcd5oHKFIkl8N/7e/Ni0rs6GuF1l6eDOJpI4HBvLC9NSxsTqCpDg2lBnQOvDwrckhN359dy/M7pNB15NTceL6hz46Nvb8Nnf7bfMvaZMff2q87Hlec34U/H+3FyKIGv/+oQ3r1mPm7/6Uvp7Wq9Tjzwm8PpeueOm1fj8mWN+NWhXsSTGk4Px7Pi8F3XdeC6Va3pDmJV1fHY3lNZM2/fc9NKKJqBz/zXS1npa2uqwtplTYzJFainpwfv/8YTSISG4WmY5F0MBVhNVsdOYqpk82odeH3QnVc+z6uQ8nmq7cJym+3twnJ+vmKOPdaYyLpu4JkDPTg9FENE0fD0K9248cL52Lb7TFty6zXtOMfvRF8kiXt+md0HVudx4EBPGD/843G8e8183PeMdTsxsx5kdV5UVccvOrtwciiWVcfZfMVSHB+K4qrzm0vWQXy2r1ellJStAF7PeH1ydNmUHRuIpE8ukBrTd/MjL+LYQOSsbFtom5dOBbOW9UeUdMewuey+Zw7hljcvTneemMv/5fFXcbQ/krXs3qcP4ehABOtXtmbt0+wYzlyvP6Jg38kgjg1Exv1MUzlfVJxyn+P93aF0AW4ef8vO/djfHSpq+4PdEcvtD3YXl/7uoIotOXl8y85OdAfVoraf6vkr9/mvJMWeK6v1djx5EH3hRHrZ+pWtebHtq08dRH9EyYuD61e24t6nD0HVke4YztzH+pWtGIgq6QL6hgvnpf8293Pv04dww4Xz0mnu7ArmpTF3HeaBytTZHbaMSZ3d4bKl6eUCcfLlIuNkqZ0cso67J4eKi7tUGtORV3Pj8fqVremOYfOYmbHPjLlmnFS1VNxdv7I13ZAyt9u2qzOr3rn5kRex73QQSdXAa32RvDh8x2P70dkVPPP5u4LpjmFznUO94XTHcGb6zHorlZeu6+jq6kJXVxd0XR9/g1Euf+1ZGyfY5auFEDZs/vEe/O+vP459+/ZNOH1EM0XXsHX53DVcGeXzVNuF5Tbb24Xl/HzFHrvQmMjHBiLYdzKI/kiqzXfLmxenO4bN/W3b1YlqrzPdMWwuv/fpQ/A4Hdjx5EHL+kyhepDVeensCuJQbzivjrPjyYM43BvGvtPBvG3O9jmbrErpHLbqBs97EEkIcasQYo8QYk9fX19RO+4ZiadPrimeLG6Q68lsW2ib3DGxdQOW68UUtajtzWUi48wV2qdupN7rDcXH/UxTOV90xlh5tdznuGckYXn8npFEhWw/tfNX7vM/k4wXU4s9V8XEPSEKx6fcZea6g5Fk1jbmciGy412hfZvxMZ7U0RW0TmPmOnMxD1SKsWPq1GLK2TDT0jTT0jOblTuv5sbjYuKjuU5XMJ6Ou+NtZ77uHokjklAL1kG7g2fiqlUcHqvuyph8dhXTrjLvAn7/N55ID+cwU2R2Es/E9FHpTKYPoFJUevlc+ekvXbtwJubTcrZ7S9FmN/ux4kkdsYR1P9lQNGm5PDLarzaRepBV2rqC8THrKj0jpTuXZ/t6VUrn8EkAmc8dzQNwOnclwzC+ZRjGGsMw1jQ0NBS14ya/Kz27oMnlsKHRN/5jDpPZttA2uXeBSwKW63lke1Hbm8sy5xsstE+bAGwCaPS5xv1MUzlfdMZYebXc57jJ77Q8fpO/uEday7/91M5fuc//TDJeTC32XBUb94pdxzAw+gizw3IbID/eWa1nxkeXw4aWgHvcdeZiHqgUY8fUqcWUs2GmpWmmpWc2K3deLRSPc19nxj4z5rYEXFlxd6ztzNfNfhe8LnvBOmhz4ExctYrDY9VdGZPPrmLbVS5/LVz+2mlM2cS4fDM7fTR1k+kDqBSVXj5XfvpL1y6cifm0nO3eUrTZJXGmnuBxWveT1Xis24vejH61YutBVmlrCbjHrKs0+Ut3Ls/29aqUzuE/A2gTQiwSQsgA3gNgZyl2vLDOix03r87KGJmDXJd620LbrGgNZC2r88r4xOVLs5ZtXNuGB587gm0b2rOW//NVy9FQ5cxatmldGxbVebF736msfX7yymV569V7ZaycF8DCOu+4n2kq54uKU+5z3NHsw/YNHVnH376hAx3NvqK2X9rstdx+aXNx6Z/q9lM9f+U+/5Wk2HNltd7mK5Zmxa1de0/lxbZPXL4U9V45Lw7u3ncKm9a1wW4Dtl/bkbePXXtPodYjY9O6NrgcNjz6/Mn03+Z+Nq1rw09fOJlOc3uLPy+NueswD1Sm9uYqy5jS3ly+idYuKBDnLigyzpXaVOMulcZ05NXceGwVezNjnxlzU3EyALuEdJzduDY7rm69pj2r3rnj5tVYeU4ADklgcYM3Lw7fdV0H2lsCZz5/ix93XZf9+Zc0VuHz16/IS59Zb6XKYQ5BcTYmoiOarSq9fK709M/2dmE5P18p2uwr5gVQ5021+R587gi2rm/Pq5cMRxK47R35fWDRRBKbr1hqWZ8pVA+ySlt7ix9LGqvy6jibr1iKJY1VWHlOIG+byTrb10sYRmWUzkKIdwL4VwASgO8ZhvH5sdZfs2aNsWfPnqL2bc74lzvI9dna1mobADjSF8axgQh8LgcAA/GkBpfDjnAiCZ/LgWAsiWq3A7IkMJLQEFc0NPhkJHUDw9HUe8PRJHwuO5x2G0biSXhkO5KakfplxQb0hxOQJRv6wwqcDhtcdgl1VTLm155J93ifaSrna46Y0MmwyqvlPsfRmIL93SH0jCTQ5Heio9lX1GR0puFYHAe7I+ntlzZ7JzTpwFS3n+r5K/f5nyZTzqdA8ecqc716rxOxpIbukTiq3Q4MRZNwyxIafQ6MxDT0hhJoqHIillThdzkgSQLhuJaOa7LdhnMCqdnqVVXHvtNB9IzE0ehzwjn6666i6XDYbAgnVMSSGs6r90I3gNeHoqhy2uGWJYTiatYsr5lpbKhKxczukVmdByrFlPNqJJZAZ3c4HVPam6vKNhmdKRyL4+WMOHdBs7csk9GZphp3CUCF5FVdN3C0P4ITgxF4ZDuaA04oair+eWQJHoeEgYiCao8MA0bWLN26buD1oQi6g4lUvdTjwFBUQUOVE7UeB3pCCqKKivm1XiyqT22jqjoO9Y0gmtARTWqIJFS0BFypzmZ79n0qqqqjsyuI7mAczaPrAMDLXUF0BROocknp+M+YPCUlqQN0dXXhwz9ILX/gf61BS0tL1vu6rqeHc+jp6cHt/7kXiXBqIjotHoLk8k35f39DC4ZePzjmOna7hO3vWADzbj2bzcaJ6ipHSfJqJav08rnS0z+BdmHReXUm5dNytntL0WY/PhBBbziOpGpACAMOm4S+cAK1XhkeWUIiqaHR70JSNXB0IJK+azicSMLvciCa1KBqOgJuGbGkhkZfqg3YFYzDI0tIajpqM+pBVlRVx6s9IxiOJhFVNHhkCVVOOy5o9pdsMrrMzzzF61Vw5YrpHJ6omfSFozlnzldiqCIwn1KlYF6lSsG8SpViWjqHu7q68P5vPAGXvxbBU0dK2ik8kc5hLR5CMpmEHo/A5vLCbpfwpZvegKamJnYSz3yMq1QpKrJzmOacgvnUPp2pICIiIiIiotkn807hpqYmAKkxid2BesRHBsuZNLh8tdAcjnRn8eYf70l3EvOOYiIimuvYOUxEREREREQTZnb69vT0oKenB5u+/ysAwL0feHvW+4nQMGzm3bsl/N8hOya3b5cXSngEH/n2k9ASUUhOD+x2O+79wNvTHds0PXLvOCciouk3a4eVEEL0AThexiTUA+gv4/Gngmmfmn7DMK4qduWznFfLfT54/Jl7/JmUT8ul3NfnbJltn6uUeXUmnpuZliamZ2zTFVdn2ueeCn6WmYd5NaWS0w5UdvqLTTvz6hlMf3mNl/6i8+oMbVdV+vXJNds+D1Caz1Qwn87azuFyE0LsMQxjTbnTMRlM++xR7vPB48/t4890s/X8zNbPVQoz8dzMtDQxPWObrvTMtM89Ffwss1sln5NKTjtQ2ekvR9or+XwBTH+5VXr6xzPbPt9s+zzA2f9MHFCJiIiIiIiIiIiIaA5i5zARERERERERERHRHMTO4bPnW+VOwBQw7bNHuc8Hjz+3jz/TzdbzM1s/VynMxHMz09LE9IxtutIz0z73VPCzzG6VfE4qOe1AZae/HGmv5PMFMP3lVunpH89s+3yz7fMAZ/kzccxhIiIiIiIiIiIiojmIdw4TERERERERERERzUHsHCYiIiIiIiIiIiKag9g5TERERERERERERDQHzdrO4auuusoAwH/8V45/E8K8yn9l+jchzKf8V8Z/E8K8yn9l/DchzKv8V8Z/E8K8yn9l/DchzKv8V8Z/RWM+5b8y/ito1nYO9/f3lzsJREVhXqVKwHxKlYJ5lSoF8ypVCuZVqhTMq1QJmE9pJpq1ncNEREREREREREREVBg7h4mIiIiIiIiIiIjmIHs5Dy6EcAF4FoBzNC3/aRjG1px1BIB7AbwTQBTA+w3DeGG60zqX6LqBo/0RnBiMwOu0I6aocMsSBATCCRXzqj2IKCpODsfQ4ndhxTkByLIEVdXR2RVEVzCOeTVueBwS+sIKIoqKBbVeLKr3wmYTWcc5MRhBz0gCI/EkajwOeGUJg9EkogkN1R4HgvEk/C4HmvxOtAY8ODEURc9IHE1+FxbWeQEAR/sjOD4QgUu2wSlJqKuSMb829d6xgUh6/fk1qe0HIgnIkg2RhAav0w5F01Dndabfz9x/ZnozP19LwI32Fj/sdv6+cjbE4ype6gqieySBZr8TK1oCcLmKD1eKomHf6SC6R+JZebRYkVgCnd1h9Iwk0OR3or25Cl63s+jtw7E4Xu6OpLe/oNmLKrer6O1jsSRe6h5Jb7+i2Q+321H09tGYgv3dofT2Hc0+eNxy0dvPFLpuZH2Hc7+TxW7bEnBB04HBaAICAv3hBGq9MhRVQ0vAkxebzO1fH4qgJ5jAQERBk98JSQiEFRW6bsAj2zEQSaA54IbPaUd/JAFJCPSFE/A47PC77EhoOpx2CYqmoaHKCU0HekNxeGQ7EqoGSQhEk0m4HQ4oqo7mgCsrDnlke962Ez0P453TQnFvKud+JpqJ8XumnePhWBwHM+LW0mYvqicQt2Z7eqbL2c6rk8l3E91G1w0cH4jgdDCGUFzFOdVuXNCc+hzmvgYiCTglG/rDCrxOO6pcElTVQFhRkUjqWFDrgSSJ0fPgyoqfuqHDJkRWPS43Ts6v8eDkcDRdx6xySrBLNoTiSQRcMvxuG4YiGvojCbRWe4o+z5nX55zqVPzvniHf4ek22Rimqjpe7RnBUDSJeFJDk8+FxGhd/ByfC/u7R7Lqb3a7DccHIugeiWMknoRXtsMhCdhtNtRVyRiJJdEzkkC1x4GIkkSN24mkrmMokoTPbYdssyEYT2J+rRcLaj04FYyidySB/ogCv9MOtyyh1ptqO1jVBY72R3B8MAKvbEeT32m5XrHnySzX67zOOZdfiGjqJht3S9WmmonHnGiMney+C62bWa+RJRuiilawTdXoc8EmgKMDqTLF65SQ1FJ1GkXT4XZIiCQ0KJoGv9OBaFLLO65ZD+mPJOB3OZBI6ogqKqo9MoKxJBp9rknXHcvaOQwgAWCtYRhhIYQDwO+EEL8wDOMPGetcDaBt9N8lAL45+j+dBbpu4PHObmx+5EXEkzpcDhs+ddVyJDQdO548mF62aV0bHvr9cQxFFWy/tgPXtDfjv1/uxh2P7UeNR8Y//PViRBQN9z59KL3NjptX46r25vSX5JkDPTjUE85aZ+s17XjgN4dxfCAGl8OGjWvb8PCeE/j45UuxxxjGZ/7rpaz9yXaBj/7HX7LS5ZUlLKiPIJLQsz7HXdd14Md/Oo61y5tx3zNnjrlxbRueebUb77l4Ae54bL9lelVVx2N7T2W9f9d1HbhuVWvZOxhmm3hcxc6XurBl55lzvX1DBzasaCmqg1hRNDy27zS2/Cxj+2s7cN3Kc4rqII7EEvjv/b15x39XR2NRHcThWBw/39+Xt/07OxqK6iCOxZLYtb87b/trOpqL6iCOxhTs3t+Tt/36jqaK6iC2ikWZ38lit63xyLjlTQvw4z+fwLvXzM/77n/msf24/arzs/ar6wZ+e7gXp4cT2LarMys+Pfr8ibwY8umrl0MzgC8+/mpWLPI4JHzvuaP4+zcvyouhZmz78GVL8MCznTg+EMOCOjc+trYtK8584vKlcDtsuPsXr074PIx3Tq2Ot+Pm1bjy/CY88UrPpM79TDQT4/dU8vfZMByL4wmLuHVlR0NZOmRnWnqmy9nOq5PJdxPdplD97q7rOrBhxTl46kAvvvj4K3jvxQvw1afOxMTNVyxFg8+JT/30paxlu/eextUrWtL7WlDnxocvW4JtuzsLxskFdW588splODkUy0rD5iuWwinZsO25l/GxtW342jOH0vXNYs6z1fXJrA9XcpycqMnGMFXV8YvOrrxr84nLl+I//nQcH3lbG77+6zPXZfu1HVhY78KLJ0by2iF1XgcO9wls3ZmbF2JZZWbmNbrnppWIKRq2ZGyzaV0bfC47mgNhrF3WlFUXyP2Mm9a1oa2pKmu9iZ4ns/zPrXsQEY1lsnG3VG2qmXjMicbYqe47d11znS8+/kpeO7NQmyqzTNp8xVI0VDnxr08fxN+/eRGiSc2yzWoeV9cNPLb3FL72zKHR9cN5Zeld//0yPvr2Nly/euJ1x7L2ahkp4dGXjtF/uTPoXQvgodF1/wCgWgjRMp3pnEuODUTSmRcA4kkdA1ElXSEzl9379CHccOE8xJM6tvxsP17qHklXlm+4cB76I0o6o5rbbH7kRRwbiKSPs+9kMG+dbbs6sX5la/r1fc8cwvqVrTjaH0l3DGfub9/JYF66+iMKQjEt73Pc8dh+3PLmxekvWuYxbnnz4nT6rdLb2RXMe/+Ox/ajsyt4Fq/G3PRSVzDdIQCkzvWWnfvxUpHnet/pYLpjOL39z/Zj3+nitu/sDlsev7M7PM6WKS93Ryy3f7k7UtT2L3WPWH/+7pGitt/fHbLcfn93qKjtZwqrWJT5nSx22xsunId7n07FEavv/vqVrXn7PTYQQSimpTuGzfW37eq0jCH9ESXdMWwuu/fpQxiIKli/stUyhprH3rb7TMxbv7I1L8589amD6I8okzoP451Tq+NtfuRFdHYFJ33uZ6KZGL+nkr/PhoMF4tbBIuPWbE/PdDnbeXUy+W6i2xSq393xWKoc3vzIi1i/sjXdMWy+v+PJgzjaH8lb9qHLzsvalxk3x4qT61e24lBvOC8NO548mI7Ldzy2P6u+Wcx5tro+mfXhSo6TEzXZGNbZFbS8Nl996iDWr2zFlp3Z12XLz/ZD04RlO8QjO9Idw5n7yS0zM6/Rod5wumM48/3eUAL7Tgbz6gK5n/Hepw/lrTfR81So7kFENJbJxt1Stalm4jEnGmOnum+rNqNZr8ltHxZqU2WWSTuePIijA5F0e7FQm9U8rlkPyVzfqiz97M8mV3cs+y2PQghJCPEigF4ATxqG8cecVVoBvJ7x+uToMqt93SqE2COE2NPX13dW0jvb9YzE0xnMpBvIWxZP6hDizN89I4n0OkIU3qY3FE8fZ7z9Zr4utK6e81OCuSySUC3Xj01wuZnermD+eYkndXQH45gM5tXCujPyksnMY8Vtb32tekaKu1Y9Uzx+pW+fqZz51CoWZX4ni91WiDNxpFC8yd1vz0h8QjFkrPg0VvzKTFtmWq32M5nzkCv3nBY6XqF4N5ljTpex8mqp43cpTCV/n530lC5uzMb0lFI58+pk8t1EtxmrfmeWzxOJdTFFLSpuZW47Xr0xN/am0zfOeS50fTLrwzM5Tk7UWHl1sjGsKzh2/d/quvSFreNBoXLaKh+Z+xwrX+gG8uoChdYt9joX2odV3YMmj+0qqgRTzaeTjbulalPNxGNONMaWYt9W5cRE21SZ9Ybc9mKhffWG4un9FdO+nEzdseydw4ZhaIZhrAYwD8DFQoiOnFWs7jvPvbvY3Ne3DMNYYxjGmoaGhhKndG5o8rvgcmRnC0kgb5nLYYNhnPm7ye/MWqfQNo0+V/o44+0383WhdXOfSjCXeV12y/U9zoktN9PbEnBbvt8cmNzjrcyrhTXn5CXgTB4rRotFHk5tX9y1ys3LEz1+pW+fqZz51CoWZX4nJ7Kt+XeheJO73ya/a0IxZKz4NFb8Mo+dG/Os9pO7rJjzkKvQOc193RKY/Lkvl7HyaqnjdylMJX+fnfSULm7MxvSUUjnz6mTy3US3Gat+15yxr2JjnUe2jsXjbTteXLaKveOd50LXJ7M+PJPj5ESNlVcnG8NaAu4Jl4kNVdbxoFA5bZWPzH2OlS9sAnl1gULrFnudC+3Dqu5Bk8d2FVWCqebTycbdUrapZtoxJxpjS7HvQuXERNpUmfUGs8zKLJ8KHTezHjJeWTqZumPZO4dNhmEMA/g1gKty3joJ4NyM1/MAnJ6eVM09C+u82HHz6qyMWeuRsfmKpVnLNq1rw09fOAmXIzUe2IpmP+66rgMuhw2PPn8SdV4Zm9a1ZW2z4+bV6UnkFtZ5sWJeIG+drde0Y/e+U+nXG9e2Yfe+U1hY78Xnr1+Rt7+V8wJ56ar3yvC5pLzPcdd1HXjwuSPYuDb7mBvXtuHB546k02+V3vYWf977d13XgfaWwFm8GnPTipYAtm/IPtfbN3RgRZHnesU5AWy/Nmf7azuw8pzitm9vrrI8fntzVVHbX9Dstdz+gmZvcelv9lt//mZ/Udt3NPsst+9o9hW1/UxhFYsyv5PFbvvo8yexaV0bdu09Zfnd373vVN5+F9Z54XNJ2HpNe158soohdV4Zt1+1PC8W1Xlk7N53yjKGmsfeuv5MzNu191RenPnE5UtR75UndR7GO6dWx9tx82q0twQmfe5nopkYv6eSv8+GpQXi1tIi49ZsT890Odt5dTL5bqLbFKrf3XVdqhzecfNq7Np7Cp+4PDsmbr5iKRbVe/OWffvZ17L2tWtvKm6OFSd37T2FJY1VeWnYfMXSdFy+67qOrPpmMefZ6vpk1ocrOU5O1GRjWHuL3/LafOLypdi97xS2b8i+Ltuv7YAkGZbtkGgiiW0bxs4LuddoSWMVtudss2ldGxp9TqycF8irC+R+xk3r2vLWm+h5KlT3ICIay2TjbqnaVDPxmBONsVPdt1Wb0azX5LYPC7WpMsukzVcsxaI6L3btTbUXC7VZzeOa9ZDM9a3K0juvnVzdURiG5U2400II0QAgaRjGsBDCDeAJAF80DGN3xjrvAvBRAO9EaiK6+wzDuHi8fa9Zs8bYs2fPWUr57GbOzHtiMAKv046YosIlS7BBIJxQMa/ag4ii4tRwDE1+F1aeE4AsS+mZE7uDcbTWuOFxSOgLK4gqKubXerGo3ps3IPiJwUh6JukajwNeWcJgNIloQkO1x4FgPAm/04GmgBOtAQ9ODEXRG0rN9Gh+Mc20ynYbXHYJdVWpGYeB1Dgw5vrza1LbD0YScIzOJOmRUzNE1nqd6fcz95+Z3szP1xxwob0lUGiQ7wnNLMG8mi8eV/FSVzA9S/2KlkBRk9GZFEXDvtPB9MyiZh4tViSWQGd3OH389uaqoiajM4VjcbzcHUlvf0Gzt6jJ6EyxWBIvdY+c+fzN/qImozNFYwr2d4fS23c0+6wmo5vx+dSc3bXQd7LYbZv9qZnuB6MJCAgMhBOo8chQNA0tAU9ebDK3f30ogp5gAoNRBQ1VTthtAmFFha4b8Mh2DEQUNPud8Lkc6I8kIAmB/rACtyzB57QjqeuQJRuSmo76Kic0PfUoqkeWoGg6BATiySRcDgeSmo4m/5k4lZpxV8rati888fMw3jktFPemcu7Pginn1QnE72kzw84xhmNxHMyIW0ubvWWd/G2mpadIMz6vTibfTXQbXTdwfCCC08EYwnENLQEnLhj9HOa+Bkdn9R6IKPDIdlQ5JaiagbCiQlF1nFvjgV0S6B45E8PN+GkYBoQQWfW43Dg5v8aDk8PRVB0zloTXKcFhtyEcT8LvkuF32zAU0dAfSaA14Eb7OcWd58zr0xJwwedyoGeGfIcnaMp5dbIxTFV1vNozgqFoEomkhgafM10XP8fnwv7ukaz6m91uw/GBCLpH4gjFVXhkCQ5JwG6zoa5KxkgsiZ6RBKo9DkQUFdVuGaquYyiSRJXLDqdkQzCexPxaLxbUenAqGEXvSAIDEQVVTju8soQab6rtYFUXMNsZHtmOJr/Tcr2xZM5Un9nuqLD8Uk4zvr5KNKrovDrZfDrZuFuqNtVMPOZEY+xk9j3Wupn1GrOPqclv3aZqqHLBJlJ9VB7ZDq9TgqrpEEJA0XS4HRIiCQ1JTYPP6UA0mb0v4Ew9ZCCSgM/lQCKpI6qM9p3FkmiocqJj7DpNwYtQ7s7hlQAeBCAhdRfzI4ZhbBdCfBgADMN4QAghANyP1B3FUQAfMAxj3G8SCwYqI1ZiqBIwn1KlYF6lSsG8SpWCeZUqBfMqVYqz3jlMVAIF82nxt+KdBYZh7APwBovlD2T8bQD4yHSmi4iIiIiIiIiIiGi2mzFjDhMRERERERERERHR9GHnMBEREREREREREdEcxM5hIiIiIiIiIiIiojmIncNEREREREREREREcxA7h4mIiIiIiIiIiIjmIHu5E0BERERERERERLPT26+8Gl29/QXfb2msx6+e+MU0poiIMrFzmIiIiIiIiIiIzoqu3n6s/sf7Cr7/4jc2TmNqiCgXh5UgIiIiIiIiIiIimoPYOUxEREREREREREQ0B7FzmIiIiIiIiIiIiGgOYucwERERERERERER0RzEzmEiIiIiIiIiIiKiOYidw0RERERERERERERzEDuHiYiIiIiIiIiIiOYgdg4TERERERERERERzUFl7RwWQpwrhPiVEOIVIUSnEGKTxTpvE0IEhRAvjv7bUo60EhEREREREREREc0m9jIfXwXwT4ZhvCCE8AF4XgjxpGEYL+es91vDMNaXIX1EREREREREREREs1JZ7xw2DKPLMIwXRv8OAXgFQGs500REREREREREREQ0F8yYMYeFEAsBvAHAHy3efpMQYq8Q4hdCiPbpTRkRERERERERERHR7DMjOoeFEFUAHgXwccMwRnLefgHAAsMwVgH4GoDHxtjPrUKIPUKIPX19fWctvURTxbxKlYD5lCoF8ypVCuZVqhTMq1QpmFepEjCf0kxX9s5hIYQDqY7hHxqG8dPc9w3DGDEMIzz6988BOIQQ9Vb7MgzjW4ZhrDEMY01DQ8NZTTfRVDCvUiVgPqVKwbxKlYJ5lSoF8ypVCuZVqgTMpzTTlbVzWAghAHwXwCuGYewosE7z6HoQQlyMVJoHpi+VRERERERERERERLOPvczH/ysAfwfgJSHEi6PLPg1gPgAYhvEAgJsA/IMQQgUQA/AewzCMMqSViIiIiIiIiIiIaNYoa+ewYRi/AyDGWed+APdPT4qIiIiIiIiIiIiI5oayjzlMRERERERERERERNOPncNEREREREREREREcxA7h4mIiIiIiIiIiIjmoHJPSEdERERERERERAW8/cqr0dXbX/D9lsZ6/OqJX0xjiohoNmHnMBERERERERHRDNXV24/V/3hfwfdf/MbGaUwNEc02HFaCiIiIiIiIiIiIaA5i5zARERERERERERHRHMTOYSIiIiIiIiIiIqI5iJ3DRERERERERERERHMQO4eJiIiIiIiIiIiI5iB2DhMRERERERERERHNQewcJiIiIiIiIiIiIpqD2DlMRERERERERERENAexc5iIiIiIiIiIiIhoDmLnMBEREREREREREdEcxM5hIiIiIiIiIiIiojmorJ3DQohzhRC/EkK8IoToFEJsslhHCCHuE0IcFkLsE0JcWI60EhEREREREREREc0m9jIfXwXwT4ZhvCCE8AF4XgjxpGEYL2esczWAttF/lwD45uj/M4KuGzg2EEHPSBxNfhcW1nlhs4mi38+kqjo6u4LoCsZxbq0bNgDDMRVDUQWNPidUTcdIXEOjT0ZE0ZBQNficDvRHFNR6HLAJgf5IAvVeJ+KaCqdkRziRhNthRzCWREvABUXV0RtKoMHnRExRIYSA32WHQ7IhnNAwGFHgd9nhliXEkypkux2DkQR8bgfiSRVe2YFwIgmHJMHvskPTDfSHE/A67XDabRiOJhFwOxBXVdhtEkJxFVUuCV7ZjnBCRSShwiPb4XQIGIZAMJZEwG2HLAkkNaTT5nKk9hVPaqj1ypAlG5K6Ck2zIRhPHWMgoqDOKyOmqPC7HbAJIKroUFQNHtmOvnAC9VVO+FwSwgkNdV4nFtZ5ASDvmlgtK3Sd5oJoTMH+7hB6RhJo8jvR0eyDxy0Xvf1wLI6D3ZH09kubvah2u7h9hWw/XXTdwNH+CIajcWiGQG8ogSafEw5JIBTXEEuqaKhyIpbUEEloCHgciCoqajwykqqOvrCCKqcdAbcdiqZjKJpEwOXAYExBrUeGqmmQbBIGIqlYoGgaZElCVEnC7XBA0zXYJQm9oQTqqmR4HBKGogn4nDJku0AwpiKcUBFw2+GyS+gLJxBwOwAAIzEVAY8Dw9EkajwOVHskBGMaBiNJeJ0S3A4J/REFdR4ZDX4ZPSMJyDYbBqMKvE47PLKEWFKDLNkQVTQ0+V2YX+PBiaFoXhyaSDlSaabrs83E78RMSxPTM7bMOlpLwI32Fj/s9tLfY1HKz62qOl7tGUE4ocLtsCGeNNAbSqDZ70SVS8JgJDn6ngSf0w63M/V5hiIqEqN1qd5QAo0+Jzxyqp44EFZwTsAFVU/tq8nvhE0AimYABqDqBqKKCr/bDqddQiShIZxQUV8lQxLAcDyJKqcDiaSeXh5LqjAMgYDbASGQir1xFY0+JzQjtZ7HYcdwLImGKicUPVXHjCd1xBQN5wScCCsa4snsNBvQYOg2hOIqarwOGAbQM5JAo9+JpKbCZbdDCIH+cAJuhx1u2Qa7zQZF1TEcS6LKJcFtl1JljUtCi9+NBaN1xhODqWsUSahoCjjTn3NBrReL6q3jWKF4V4o4mLmPloALmg70hsoTV7PS4neiL6ykyme3A4qqosrpQFjREEmkyviRhAJJ2OB1ptoDCVVHOJGEy2HHSCwJj2xHlVOCohkYjCio9crp9obPJSGp6YgqOgYjClqrXUhqBnpCCdR5ZXgcNkAInBqOoSXggqoZGI6l6grBeBIuuwTZLiBLNgzHFThsElwOG7yyhKRuIBzX4HXaoWgaGqqc0HRgMJrIKrvHOr+Z56LR54JkA7qCs68sn6zZXL8hmozJ9C0BY/djFKq/mPsKxRQkNCMdyy9o9qI/oqbKOOVMuaYoGl7qCqJ7JIGWgBP1XhlDsSQEBJK6BlUDhqIKGqqciIy2tWLJVN9Pqv3mgKYD/WEF1R4HgtFkKt467RiOKage7WvoH+3DAYCBsAKvS4JTkuB32xBTDESUVF2kJeDCBU0+vDYYwXA0CZsw4HHYERotX2pH+4nccqrfKprQEVJUKEkdNd5U2tx2OwaiCryyHT6XHZGE2fZzQIhUX5XPZUdMUWGXJMiSgNNug6YbiCV1hOIqmgNOyPZUXUPTDUQSKqqc9jNtQa8DLoeEkZiKpGYgrmoIuB0woMEGCSPxVDmXUFVUu2WE4qn6RKPfiVqPDcNRHRBliOMAAQAASURBVJGkhmhChVu2w2ETCHjsCMe1dFlX67VjOKql63i1Xgl1PteE649l7Rw2DKMLQNfo3yEhxCsAWgFkdg5fC+AhwzAMAH8QQlQLIVpGty0rXTfweGc3Nj/yIuJJHS6HDTtuXo2r2pvTlb2x3s+kqjoe23sKdzy2HzUeGZ+4fAk0Q2Dbrs70tpvWteEXL3Xh6hUt+PGfT+C9Fy/AV586iBqPjFvetAD3Pn0I8aSOBXVu/MNfL8E3f9OJd6+Zj/ueOZS3jsthw8a1bXh4zwl88K8WweO0447H9qffu+Nd58PlkHDHY8/nrf/eixfgyZe7cOMb5+el76HfH4dsF/jwZUuwbXdnOj0f/uslWetuvaYdD/zmMI4PxOBy2LB9Qzu+/uszr7dtaMc3Ml7fdV0HZMmGrzx5IP2ZctP10be34cmXT+Pty1qwbfcLWceSYOCTv9mLz66/AIpqZF2T+9/7hrxlha7TXBCNKdi9vwdbdp7JD9s3dGB9R1NRHcTDsTie2N+Xt/2VHQ1FBShuX97tp4sZHx/7ywmsO78FW3eeiRf/+LYl2Lqz0zJuffLKZWjwJXH7oy9lxZcHfnM4LzZsXd+OB57Njis/2XMCa5c345lXu3HjhfPTcSozVtz//GHL+GbG38z0fOLypfj8n47jI29rwyN7jmPP8WB6fY9Dwuf/+2V89O1tSGoatu9+Jb3dp69ejlhSx1efOphedtd1HfjaM4fS6d1x82pceX4TnnilZ1bGp4mUkVMxE78TMy1NTM/YMutomd/X61a1lrSDuJSfW1V1/KKzC0MRBTVeB6KKnhVnP/K2JdiyMzvGzatxQ9MN/OAPx0bj4wt561vF5W0b2iFgYCCSzKqL5tb9bnvHMvhkCa9Gw1nbf+6adjzzahfetbIVp4fjWe9tvmIpnJINX3j81fSyO6/tgGHo2LLzZSxtrMLfXrIAjz5/Ii/NY5UlW69phyTi2LLz5fSyL9ywAoMRBff88kBe3XYoqmDTujYsaayCbBd4+XQI9z5tXb+2imOF4l0pYnzmvotNz1SNlVefOzyEzY+8iDctqsXVK1rw9V+nyueH95zA3795EaJJLa8c/Y8/HU+3R772zKGs8twqL5l1/4+8bQkCbjs2Pbw3nRdy2xsBtx1PdXbjosX1lnWFTeva4JUl2CWB//fsEbzvkgVo8jvx778/li7TP3XVciQ0HT/84/G87QudX6trnpmfZktZPlnTVQcgqhST6Vsarx+jUP1lw4pz8NSB3rx2mMthw5duXInBiIJ/ySh3v/I3q6DpBv7vo/uyyv6AO/UjXm6/1ca1bRltrRfyyvSNP/5LVlys8zhwuDeCHU8eLFj+Lm+uQveIknWc7dd2wCYM/PhPJ/C/Ll2IruCIZfmycd1SROJJ3P2LV7P6yz63K7vP6IHfHIaiGvjAXy3MSotZ5rznovmo8zpgQGSds0L1B49Dwl2jbcGYoqaPn9sufXjPCXzoLYvxSiK7fvSlm1aiL5TI2u9t71iG+io53Ra26kvbvqED5zUmcV4jJlR/nDFjDgshFgJ4A4A/5rzVCuD1jNcnR5eV3bGBSPqLCADxpI7Nj7yIYwORot7P1NkVTH9pb7hwHjyyI53xzW3vffoQPnTZebj36UNYv7I13alww4Xz0pkIANavbMXndnVi/crWdOUld514Usd9z6T20x9R0sc23+sNJfKWmet/9amDuOXNiy3Td8OF87B+ZWu6w8VMT+6620bTZ77esjP79dac13c8th+H+8JZnyk3XZ/92X6879JFWcc2j+VxOrB+ZSv2nQzmXROrZYWu01ywvzuUruwD5vXZj/3doaK2P9gdsdz+YHdx55Pbl3f76WLGx/dduihduAKpeGG+topbX37iAF7ri+TFF6vYsG13fly55c2Lcd8zh1IxrECsKBTfzPibufyrTx3E+pWt2LJzP2558+Ks9QeiSjo2dY8ksrbrjyjpGG4uu+Ox/Vnp3fzIi+jsmr3xaSJl5FTMxO/ETEsT0zO2zDqamZ47HtuPzq5gSY9Tys/d2RXEod4w+iMKAm45L85u2Zkf4w71hnGkP5IXHzPXt4rLW3d2wiM78uqiuXH0nl8egMfpyNv+c7s68b5LF+G1vkjeezuePIiBqJK17LM/2w+P7EA8qeNDl52Hbbs6LdM8VlmybVdneh/msqP9kXQDLPO83HDhvPTfL50KIhQ707lptW+rOFYo3pUixmfuu9j0TNVYedVMy/vfsihdvzfr6gNRpWA5arZHcstzq7xk7m/Lzk4kNWTlhdzrrOvATRfNL1hXuPfpQ+iPKOgeSWD9ylbsePIgXuuLZJXpA1EFO548aLl9ofNrdc0z89NsKcsna7rqAESVYjJ9S+P1YxSqv+w7HbRsh8WTOg73hdMdw+ayf/rJXhzuC+eV/aoGy36rQm0tqzL93qcPweN0pDtjM5dnlr+SzZZ3nC0/2w+X3Y5b3rwYR/rz6xBm+fKZ/3oJ/ZEzxzX7y3LLi/UrW3HDhfPy0mKWOfc+fQge2ZF3zgrVHzLbgpnHz22Xrl/Zir5wIi/9h3vDefu955fZbeFU+Zvbt7YfmmabcP1xRnQOCyGqADwK4OOGYYzkvm2xiVFgP7cKIfYIIfb09fWVOpl5ekbi6Ytiiid19IbiRb2fqSt4Zl0hgEhCtdw2pqSWC4Gs9TPXNV+PtY65PyEA3ch/z2pZ5j5jBdInROH0WK07kde6Mfa+4kkdQ5Gk5fsRRZ3wZ7W6TqUy3Xl1InoyOrFM8aSOnpEEt58D22c6m/nUjI+539li4paeUQJYxbvMdXPjiBlDC8WwiKIWfM/c1uoY5vu56TTf03NKrbFibObrzLIhc/nZjE/TZSJl5HjGyqul/E6UykxLE9MztkLfw+7gzM2rXcE4dCMVawbHiLOZxzHXz42BxcTl3HprwfUKxNHhaLJgXMyNn+Z+gDNpnVSaM2I2MH5cNtOS+VkL7Ts3jhWKd6WI8Zn7LjY9xZhsXjWXm+V7Zjk91jk235tIO8IqL+SuF1FU9IcSY9YVzLyfWWZnlumF0mZub3V+C13zzPw0G8ryyZquOgDRTDFePp1M39J4/RgF6y8F2mFj7bNQWVyw36rA8kL7GS9e5tZlMreNJdRx+6+s2o9W645b5lh8rrHOWaG2YGbbcqL9VFb7ym1D9oTiE64/lr1zWAjhQKpj+IeGYfzUYpWTAM7NeD0PwGmrfRmG8S3DMNYYhrGmoaGh9InN0eR3weXIPoUuhw2NPldR72dqCbiz1vW67JbbeuQzyzPft1q3mHUMA5BE/ntWy8z1XQ4bPE7r9BnG2OmxWrfY1+YTRmOlq9brsHzfK9sn/FmtrlOpTHdenYgmv9PyfDT5ndx+Dmyf6WzmUzM+FvrOWv1tvs592tAq3pmvc+OIGUMLxTCvbC/4Xmb8zT2Gy2GDW7ZnLbcJpN/LTfNYMTbzdUug+HKk0kykjBzPWHm1lN+JUplpaWJ6xpZbRzPT0xyYuXm1JeCGJFKxZrw4a762CcAmUDAGjrVtoXpr3noF4mi1x1EwLlrFfO9ovDXTOqk0y9mj640Xl8205H7WYuJYoXhXKG9NJA7m7rvccdVcnpnvzP/HOseZ7xXbjrDKC7nreWV7ej6TQvsy835mmZ1Zpo+XNqvzW+iaZ+an2VCWT9Z01QGIZorx8ulk+pbG68coWH8Zox020bK4YL9VgZhcaD/jxcux+nk8Tvu4/VeF2o+FjldoP1afd6xzNtbxM9uWE+mnstpXbhuyyeeacP2xrJ3DQggB4LsAXjEMY0eB1XYCuEWkXAogOBPGGwaAhXVe7Lh5dVZlYcfNq9MDg4/3fqb2Fj/uuq4DLocNjz5/EtFEEluvac/adtO6Nnz72dewaV0bdu09hU9cvjS9/qZ1bel1d+09hc9d045de09h49o2y3VcjtTYKbv3nUKdV04f23yvwefMW2au/4nLl+LB545Ypu+nL5zErr2nsHV9e1Z6ctfdek07du87lX69fUP26205r++6rgNLGqqyPlNuuu68tgM/+MPRrGObx4omkti97xRWzAvkXROrZYWu01zQ0ezD9g3Z1377hg50NPuK2n5ps9dy+6XNxZ1Pbl/e7aeLGR9/8Iej2LYhO16Yr63i1ievXIbzGrx58cUqNmxdnx9XHnzuCDaubUvFsAKxolB8M+Nv5vJPXL4Uu/edwvYNHXjouSNZ69d55HRsavZnN0zrvHI6hpvL7rquIyu9O25ejfaW2RufJlJGTsVM/E7MtDQxPWPLrKOZ6bnrug60twRKepxSfu72Fj+WNFahzisjGFPy4uz2Dfkxrq2xCovrvXnxMXN9q7i8bUMqdubWRXPj6G3vWJa3nsuRGnP4h384isUN3rz3Nl+xFHUeOWvZndd2IKqkJrL59rOvYes17ZZpHqss2XpNe3of5rKF9V7c9o5llnVb8+8VrQH4XFJ6f1b7topjheJde4t/ynEwc9/FpmeqxsqrZlq+/7uj2L7hTPm8a+8p1HrkguWo2R7JLc+t8pJZ99++oR0OCVl5Ifc622zAT/58omBdYdO6NtR7ZTT7ndi97xQ2X7EU5zV4s8r0Wo+MzVcstdy+0Pm1uuaZ+Wm2lOWTNV11AKJKMZm+pfH6MQrVX1aeE7Bsh7kcNpzXUIV/vmp51rKv/M0qLGmoyiv77RIs+60KtbWsyvRN69oQTSSx+YqlBePlpnVt0HQ97zjbr+1AXFXx4HNHsKg+vw5hli+fv34F6r1njmv2l+WWF7v3ncKjz5/MS4tZ5phpzT1nheoPmW3BzOPntkt37T2F+ipnXvrPa6zK2+9t78huC6fK39y+tQ5Ikj7h+qMwDGP8tc4SIcRbAPwWwEsAzPulPw1gPgAYhvHAaAfy/QCuAhAF8AHDMPaMt+81a9YYe/aMu9qUmbM89oZSs9AWmlGy0PuZzJkku4NxzKtxwyaA4ZiK4aiC+qrUjM0jMQ2NVTIiSQ2KqqHK6cBAREGNxwGbEBiIJFDndSKhqZAlOyIZs/02+11QtNR4wg1VTsSSKoQQ8DvtcNhTs1APRhX4nHZ4ZAlxNbWPwYgCn8uenrk6nEjCIaVmfdR0A/1hBV6nBNluQ3B09uCEqkGy2RCOq/A6JXiddoQTKiIJDR5ZgtMhYBipGSADLjtku0BSQypto7/uD0dTjw7Ueh2QJRuSugZNEwjGU7MMD0ZTMxbHk6mZjyUbEFV0KKPp7AsnUO91wudOzZZd63VmzeiZeU2slk1hMoQJbThdeXUiojEF+7tD6VlLO5p9RU1GZ5rqbOvcflq2L3s+1XUDR/sjGI7GoekCveEEmnxOOCSBUEJDTNHQUCUjltQQSaRmdo0mVdS4ZSQ1HX0RBVVOOwIuOxRNx1A0Cb/LgeGYghqPDFXTINkkDEYSqKtyQtE0yJKE6OgMupquwS5J6AslUOuV4ZElDEUV+JwOyHaBYCwVs3wuCW5Hasb6gDt1J9FITEXA48BwLIlqtwM1HgnBmIbBSBJep5SeobbWI6PRL6N3JAGHzYbBaCrNbllCLKllzXg+v8aDE0PRvDg0kXKk0hT52aacV6f6nTobZlqamJ6xZdbRmgMutLcErCajm1F5VVV1vNozgnBChdthQzxppGeyrnJJGIokEY5rcMk2VDnt8DptMAAMRdR0na83lECjzwmPnKonDoQVnBNwQdWN9HuSDVC0VHtC1QxEFQ1+lx1Ohw2RRGrW7foqGZIAgnEVXqcdiaSOcEJFnVdGQtWgGxidHRwIxlKzhTdUOaEbOiIJDamZvpOoq3JC1VVINmn0kUwNLQEnIoqGeHK0/jdazzWEDl0XCMdV1HgdMAygJ5RAY5UTSV2D0y7BJgT6wwrcsgS3wwa7zQZF1TEcS6LKjOVhBR6nhHMCbiwYrTOeGExdo6iiotHnRFRJfc75o7O6W8XoQvGuFDE+cx/Nfhc0HegLlyeuZqXF50RfWMFQLFV3V9RUnT08Opt8fZUT4UQSQghUyan2QEJN5Q1zdnePLKHKKUHRDAxGUnX/4dH9VTklqLqOqKJjMKKgtdqFpJbKm7VeGR6HDRACp4djaA64oGoGhmOpukIonoTTkZp9XpZsCMaTsNtscDps8MoSVN1It1uSmp5qi+nAUDQBR0bZPdb1yjwXDVUuSDage2T2leWTNV11gNli+eqLsPof7yv4/ovf2IhXX/zzNKZoYio9/UUoOq8WyqeT6VsCxu7HKFR/MfcViilIaEY6ll/Q7EV/RE2XcWa5pigaXuoKptdrqErFYkAgqWtQNWAoqqChyomoosLlsCOWVOGR7YgqKmrcDmgG0B9RUO1yIBhLwiWn7vwNxlLzIwBAf1hBXZUMAWBgtPx12SX43TbEFAMRRcNAREGz34X2Jh9eG4xgOJqETRjwOOwIjZYvtV4ZMUWFW071W0UTOkKKCiWpo9rjQEJT4ZLsGIwm4ZEl+Jx2RJMqQnENAbcdQgiMxJKoctkRVzRIkg2yJOC026DpBmJJHaGEiiafE06HDaG4Cm203PA6JXjSbUEH3HKqPEvqBuLJVJvWgAYbJIzEk/DIqb62apcDodH6RGOVE7VeG4ajOiJJDdGEBrcswSEJBNx2hOMaekIJ1Hll1HrtGI5q6Asl0Oh3os4roc7nKlR/LJhPy9o5fDbN5oKBZjxWYqgSMJ9SpWBepUrBvEqVgnmVKgXz6qhK71yt9PQXYcqdw0TToGA+LeuwEkRERERERERERERUHuwcJiIiIiIiIiIiIpqD7OOvUjwhxFIAtwFYkLlvwzDWlvI4RERERERERERERDQ1Je0cBvATAA8A+DYArcT7JiIiIiIiIiIiIqISKXXnsGoYxjdLvE8iIiIiIiIiIiIiKrGSdA4LIWpH/9wlhPhHAP8FIGG+bxjGYCmOQ0RERERERERERESlUao7h58HYAAQo69vy3jPALC4RMchIiIiIiIiIiIiohIoSeewYRiLAEAI4TIMI575nhDCVYpjEBEREREREREREVHp2Eq8v+eKXEZEREREREREREREZVSqMYebAbQCcAsh3oAzw0v4AXhKcQwiIiIiIiIiIiIiKp1SjTn8DgDvBzAPwI6M5SEAny7RMYiIiIiIiIiIiIioREo15vCDAB4UQtxoGMajpdgnEREREREREREREZ09pbpzGABgGMajQoh3AWgH4MpYvr2UxyEiIiIiIiIiIiKiqSnphHRCiAcAvBvAx5Aad/hvACwo5TGIiIiIiIiIiIiIaOpK2jkM4M2GYdwCYMgwjG0A3gTg3BIfg4iIiIiIiIiIiIimqNSdw7HR/6NCiHMAJAEsKvExiIiIiIiIiIiIiGiKSt05vFsIUQ3gHgAvADgG4EdjbSCE+J4QolcIsb/A+28TQgSFEC+O/ttS4jQTERERERERERERzTmlnpDuztE/HxVC7AbgMgwjOM5m/wbgfgAPjbHObw3DWF+CJBIRERERERERERERSnjnsBBigRCifvTvS5GalO7t421nGMazAAZLlQ4iIiIiIiIiIiIiGl9JOoeFEJ8F8AyAPwgh7gLwrwDqAWwSQvxrCQ7xJiHEXiHEL4QQ7SXYHxEREREREREREdGcVqphJf4WwPkAPABOAGg2DCMqhLADeHGK+34BwALDMMJCiHcCeAxAm9WKQohbAdwKAPPnz5/iYYnOHuZVqgTMp1QpmFepUjCvUqVgXqVKwbxKlYD5lGa6Ug0rETcMQzEMYxjAa4ZhRAHAMAwVgDKVHRuGMWIYRnj0758DcJjDV1is+y3DMNYYhrGmoaFhKoclOquYV6kSMJ9SpWBepUrBvEqVgnmVKgXzKlUC5lOa6Up153C1EOIGAAKAf/RvjL4OTGXHQohmAD2GYRhCiIuR6tAemFJqiYiIiIiIiIiIiOa4UnUO/wbANaN/P5vxt/m6ICHEjwC8DUC9EOIkgK0AHABgGMYDAG4C8A9CCBVADMB7DMMwSpRuIiIiIiIiIiIiojmpJJ3DhmF8YArb/u04798P4P7J7p+IiIiIiIiIiIiI8pWkc1gIsXms9w3D2FGK4xARERERERERERFRaZRqWAlfifZDRERERERERERERNOgVMNKbCvFfoiIiIiIiIiIiIhoepRqWIn7xnrfMIyNpTgOEREREREREREREZVGqYaVeL5E+yEiIiIiIiIiIiKiaVCqYSUeLMV+iIiIiIiIiIiIiGh6lOrOYQCAEOJXAIzc5YZhrC3lcYiIiIiIiIiIiIhoakraOQzgkxl/uwDcCEAt8TGIiIiIiIiIiIiIaIpK2jlsGEbu2MP/I4T4TSmPQURERERERERERERTV+phJWozXtoAvBFAcymPQURERERERERERERTV+phJTLvHFYBHAXwwRIfg4iIiIiIiIiIiIimqCSdw0KI+YZhnDAMY1Ep9kdEREREREREREREZ5etRPt5zPxDCPFoifZJRERERERERERERGdJqTqHRcbfi0u0TyIiIiIiIiIiIiI6S0rVOWwU+JuIiIiIiIiIiIiIZqBSTUi3SggxgtQdxO7RvzH62jAMw1+i4xARERERERERERFRCZSkc9gwDGmy2wohvgdgPYBewzA6LN4XAO4F8E4AUQDvNwzjhckcS9cNHBuIoGckjia/C/NrPDgxFEV3MA6n3YZgXEGd14X2Fj/s9rFvqlZVHZ1dQfSMxFHndSKqqPDIdjgkge6RBFwOG3xOOyCAGo+MpGbg9HAUsl1CQtXgczowEk/C67QjoqiodTvQE1LQ4JORUHX0hxU0+pyo8UgYimroGUmg0edEtUdCMKahN5TAwlo3okkdPSMJzK91I5HU0RdOoCXgAgCcGo6jtdoFRdMxEkuizitDCCCpG1A1A0lNg9NuRzCWRKPPCZsAXh+Ko8nvhGQzoOkC/eEEajwyXA4b7DaBiJKETUjoCyXQ6HfCBoGBSAK1HhlJXUdC1eGV7egNJdDgc8Ip2XA6OLpPIRBWVEQVDQG3Ax5ZQiypoc7rxPwaD04OR9EbSmA4moRHllDtcWB5U+paZF67Rp8Lkg3oCsbREnBB04HeUOqaLqzzwmYTY167SpCbVyf6ucz8mTpH7qLydKbhWBwHuyPoGUmgye/E0mYvqt0ubj9N20/1+k0nM68ORBKQJRuiipb+jg5FFch2G2KKhsGIgiqXHV7ZjkhChQEdbrsD0aSGiKKiSrbDbhfwO+0IJTT0hxOor3IinEjCK9sBCARjCmo8MoLx1DKPLMErCwxEVAxGkvC57Kj22KGoBk4Px9Hod0LVNLgcdiQ1HcFYEm7ZDlkSsNkAQGAokkSt14G4qsIhSZAgMBBV0Oy3Pu9Wn3c2xZ7ZaqrfybmQppmWnmAsjgMZ6VnW7EWgjOlRFA37TgfRPRJHi9+FFecEIMuTrv4WVIrrYKZ1JKGg2iWn4mxChcchwSVLqPdK6Atp6Akl0FrtgmEAPaE46quciCkq3LIdQ1EFtR4ZEUWFTQgE3A4YhoFQQkM4oaKhSoaiabDbJPSGUnVUVdNglyQEYwpqPU4ABnpDCnwuO1oCDgxEtPTnqvdKCCU0JJJATyi1rMYjIZrQkdAMBKMKAh4ZwVgS82pcCMXPbFvtkaCoQFRJLWsJOFHlknCsP4aWgBvLGqpwoC+E3pEEqj0OhBJJ1HmcSOo6QnEVtV4ndEOHgEA4oY6WWzLU0fpkQ5UTBoD6Kmc6tlvVywCMW1ebSH3ubK17tuTm1ZZqO04Opto2uq5jJK4inkyVkZpuIJxQ4XIIADb0jbYTRuJJ+Jx2+F12RBQN/WEFHllCwO1AKKEiklBR63XABhsGIgm4HXZ4ZBt0AxiIKPA67fA5JQgboCQN9IUTqPM6EVGSqPM6oag6+kIJ1PucMAwdLocDipZqexR7DYmIysEqzuu6gc6uIAYiCfhdMhRVR5P/TN9IZhwrtj1ZqH6TeXyPbEedDzg9dKYstgkdks0GGAJxVYOmAxFFRcBtR73XgcGIht5wAucEXIglU3WH+ionBiIKaj0OOCQbIgkVI3EVVU47JBvgsksIJZIIuGRAALGkBsMwkFA1eJ0OJFUdodH6jFuWEHBLiCo6ekMKajwOCACKpkESUrpuEXBLkAQwEtcRTqjQDR1VsgMDUQV+twPRhIomvwux0TpFU8AJG1JljNthh8Mu4LQLGEaqb8xcJgC4ZQkOm0AwrqI/rKC+SobDJmATAiPxVLszGEui1iMjpqbqYj6XHQG3A231PpweiaE3lEAwmoTfY4cNAr2hVBvY65TQH07AI9thtwkE3DIkG6BoKsJxHXFVg00IJDUDMSV1bkPxJGo8TiQyyrmJlGmlunN4Kv4NwP0AHirw/tUA2kb/XQLgm6P/T4iuG3i8sxubH3kR8aSOBXVufGxtG+54bD/iSR0uhw0b17bh4T0v42Nr23DdqtaCnTGqquOxvaeytv3UVcuR0HTsePJgetmmdW1oCbjwatcIHnj2CN69Zj4e3nMC714zH/c9cyidjn982xL8ww9ewNLGKvztJQuwbVdneh/bN3Tg678+hOMDsdHX7Xhkzwn4nA5ctaIFW3d2Wm63aV0bfvFSF65e0YJ7nz6UXv6FG1ZgMKLgod8fy0qHy2HD5iuW4vv/cwxDUQXbN7Tj678+nD7u1mvaEXDbYRPAF36xH4pq4JY3Lcja9+YrlsIp2fCFx19NL9t6TTt+9MfjONgbxtZr2vHAb87s01x/175T+N9vXoSuYDzv/B3tj+Ad5zfjqQO96Ws31ufbcfNqXNXeXNEVu9y8OtHPZZU/77quY8w8nWk4FscT+/uwZef+rHx4ZUdDUQ1Ubj+17ad6/aaTmVe/+PgrefHktncsw+IGD/pDSXz2Z/uzYsKvXu3C1R2t6AuHs77z2zdcAEBgy87OMWNrKlafwD++bQk8soTb/nNfVmzwyhK++ZsjGIoq+ML1KxCMRfAvGXHJXMdmE/j6r15LxzzAwJadLxc872N93tkQe2arqX4n50KaZlp6grE4fmmRnnd0NJSlg1hRNDy27zS2ZMSy7dd24LqV55S0g7gU18FM69d/dQh//+ZFOKxFsuLnXde142ifwJad+1HjkfPqclvXt+OBZzvTdTUz3n788qXoCyWy9rVtQzu+kVFXzH29aV0bHvr9caxorcLl57dkxfbtGzpwTrWMDz30Qtayaq8DG3/0l/SyT1+9HDFFxf999KX0si/duAKKZmSVk2Z9MxhP4iNva8s6h5+6ajkO92afhy9cvwJ94dTnsToP5ue+/arzceX5TXjilZ6setn9730DFNUYs642kfrc2Vr3bLHOq+0YjsTwwz+fwof/egm27epEjUfGP/z1YkQUDX85MYB156faLrnn+SNvb8PXf3Uoq93xwG8OQ1ENfOCvFqav3YI6d3rfmWV6a40bX3niQHr7T165DMGYik/99KWsvP3oCwewdnkzHt5zAp9df8G415CIqBys4vxX/mY1dEPHl584kNcOMcvboaiCHTevxuXLGrHzpdPjticL1W82dLTgmUN96ePffe0y2O1yTjnejnqfjJODMUQULasMvfPaDtz/q0OWfUafvno5RmIKBiPJvL4fryzB73ZgOKpgOKoiqRt46PfH8PdvXoRETn1m8xVL0eR34vZHM+P8+bBLUlbbc/uGDpxTI+OlkyH8+M8n8N6LF+CrT53Zz2feeT76wwq27uy0rA9svmIpGnzOrPLETCsAVHvlrPJn6zXt8MoCUcXA53a9UHCfJ4diODkUwz2/PGC5zrYN7ajzyvjS46/gxgvn49EXTuDjly/BYETDcFQBgLzz/skrl+Hf/9CJ9168AP/xp+O4/arzJ1Smlb2nwTCMZwEMjrHKtQAeMlL+AKBaCNEy0eMcG4ikMzcArF/Zmv6yAEA8qeO+Zw6ll3d2BQvuq7MrmLftQFRJZ1Zz2b1PH8KR/gi6RhJYv7I1vX/zi2ymw6wkfeiy89KVHXMfW3bux/qVrRmvO3HLmxfj/W9ZNOZ29z59CB+67Lx0ZjGXH+2P4J5fHshLRzyZ6ny54cJ56eNkHnfbrk7oOqBqqTTfcOG8vH3vePIgBqJK1rJtuzrxocvOS/+duU9z/VvevBiHesOW5+9Qbxj7Tgezrt1Yn2/zIy/i2EBkotljRsnNqxP9XFb5c7w8nelgdyRd2Te337JzPw52F3d8bj+17ad6/aaTmVet4sk9vzwASdjShbO5fNuuTrzv0kU4OhDJ+857ZEe60mEus4qtZizdurMTh3rDebGhP6KkY9nRgTMdw7nr9IYSWTHPIzvGPO9jfd7ZEHtmq6l+J+dCmmZaeg4USM+BMqVn3+lguuGUTs/P9mPf6dLG5VJcBzOt61e2WsZPl92ePoZVXW7b7uy6mhlvj/bnx+ytOXXF3Nf3Pn0IN1w4D++7dFFebN+ycz8km5S3TEnqWcvu/sWrONwXyVp2uC+SV06a9c31K1vzzqHVecgsg6zOg/m5Nz/yIjq78uuh+07mL8stByZSnztb654t1nm1E6vn12P9ytZ0u+SGC+ehP6Lg3qcP4X2Xnmm7mNuY59nMs+Zys81ww4Xzsq5d5r7Nde99+hAO94aztv/yEwdwtD8732zbnWpDmccs5hoSEZWDVZz/p5+8iEOjsS63HWKWt2Yc23e6uPZkofrNSznl3pKmGotyvBN2my0d4zPf++xoTLcqX+/+xatw2e2WfT/9EQVH+iOo9jjRH1HS/VZW5fiOJw/itZz6QddIIq/tuWXnfkhCwr1Pp2K/2TFsvt8XTqTLpkJ9XLnliZnW/oiSV/5s29WJao8Tn9s19j6TqoF7fnmg4Dpbd3ZCtttwy5sXp8svWXLgcF84fezcbb78xIH0ZzTrMBMp08reOVyEVgCvZ7w+ObosjxDiViHEHiHEnr6+vqz3ekbi6ROXWhdZr4HUa3N5dzBeMEFdwXjetrphvT/dSL1n7jf3uJmvYwm1YJoyX8cUFUOR5LjbxZT85WY6x/r8hY4bUVREFBVCFD5/es50hGY6Cu1TN4CYoo55/rpH8s93oc8XT+roDRW+djPFRPIqMLHPZZU/x8vT2cdPWG7fM5Lg9tOw/VSvXymNlU+BM3m1UDwYzIhTmcuHI0nL73zEIpYVig3mMa1ijhlzx9o+MzabyyKjsSpzvczzPt7nrYTYM1uNHVOn9p08G2ZampiesRWqh/SMTPw7f7bzandGnBovzo5XF8x8PVYsHu/1UIGyoD+cyFtmFYdz43yhtMRG66jFlCOZy8ZrE0yk3p9ZDkykPne21p2KSeXVUDzrfGbmnUL5ILONlLt8rHZT5rqZ5Xnmstz1zLbDWHmaZXnlGa++SjQTTCSfForzmf1Kue9ltmkK1Vty25MF18uJ8T0h6/WGotZtukIx3HwvUqAfx2yfZe53rHhdbP2gP5wo2IYrpj5QqL2Z255Mn5eM8q6Yc1BonaFoMl1uxRQVPaF41nHHK1MnWqZVQuew1T3QhsUyGIbxLcMw1hiGsaahoSHrvSa/Cy5H9se1em0Yqf+bA4Uf32sJuPO2lYT1/mwCMO/iNt8vlA6P014wTZmv3bIdtV7HuNt55Pzlmekc61hWx/XKqfFCM9ex+ry5y9yyveA+bQLwyPYxz19LgWtn9flcDhsafeUdR7IYk8mrxX4uq/w5Xp7OPr7Tcvsmv5PbT8P2U71+pTRWPgWy86pVmjPjVObyaq/D8jvvdY0dszL3YcZqq5hjE0jHmvFic2Y888r2vPUyz/t4n7cSYs9sNXZMndp38myYaWliesZWqB7S5J/4d/5s59XMtBYTZ4updxrG2LF4vNeFyoL6KmfeMqs4nBvnC6Uls7453vq5y8YqZ1oC+de/UBoyy4GJ1OfO1rpTMam8OpqGzPfMc1UoH5jnuVBeKqb9llmeZy7LXc892nYYK0+zLK8849VXiWaCieTTQnE+t18p873MmFmo3pLbniy4Xk6ML5SeGo91m268GO4t0I9jts9y9ztWey5TofXqq858nsnUBwq1N3Pbk+nzklPeFXMOCp1fs9xyy/bU+NIC6X/jlakTLdMqoXP4JIBzM17PA3B6ojtZWOfFjptXp0/grr2ncNd1HVmZZOPaNuzel1re3hIouK/2Fn/etrUeGZuvWJq1bNO6Niyu96LF78SuvaewcW1b+v/MdGzb0A6Xw4ZvP/satl7TnrWP7Rs6sHvfqYzX7XjouSP4/u+OjrndpnVt+Pazr2HTuras5QvrvbjtHcvy0uFypMY++ekLJ9PHyTzu1mvaYbMBdgnYve8UHn3+ZN6+N1+xFHWjk9dlbvedZ19L/525T3P9B587giWNVZbnr62xCivOCWRdu7E+346bV6cnmKhUuXl1op/LKn+Ol6czLW32YvuGjrx8uLS5uONz+6ltP9XrN53MvGoVT257xzJoho47r+3Iiwk//MNRLKzz5n3no4kktm/IjmVWsdWM1ds2tKOtsSovNtR75XQsW1jnxT9ftdxynUafMyvmRZXkmOd9rM87G2LPbDXV7+RcSNNMS8+yAulZVqb0rDgngO05sWz7tR1YeU5p43IproOZ1l17T1nGz3hSTR/Dqi63dX12Xc2Mtwvr82P2tpy6Yu7rTeva8NMXTuIHfziaF9u3b+iApmt5y2SHLWvZp69ejiUN3qxl5zV488pJs765a++pvHNodR4yyyCr82B+7h03r0Z7S349dMW8/GW55cBE6nNna92zxTqvtuPFE/3YtfdUul3y6PMnUeeVsWldG37whzNtF3Mb8zxvv7Yjr91htjcyr13mvs11N61rw5LGqqztP3nlMiyqz843W9en2lDmMYu5hkRE5WAV57/yN6vR1lhl2Q4xy1szjq04J1BUe7JQ/WZFTrl3uHvIohxvh6rr6Rif+d6dozHdqnz99NXLEVdVy76feq+MxfVeDEcTqPPK6X4rq3J88xVLcV5O/aDZ78xre27f0AHN0LBpXaov7hOXZ++nvsqZLpsK9XHllidmWuu9cl75s/WadgxHE/jcNWPv02EXuO0dywqus21DOxRVx0PPHUmXX4qaxHkNVajzypbn/ZNXLsPufanPaNZhJlKmCcOwvAl3WgkhFgLYbRhGh8V77wLwUQDvRGoiuvsMw7h4vH2uWbPG2LNnT9Yyc8bF3lAcjT4X5td4cGIoip6ROBySDaG4glqvE+0tgXEnfjJnf+wZSWXcWFJNzVwoCXSPJOBy2OBz2gEB1HhkJDUDp4ejkO0SFFVDlTM1e7LHYUc0qaLa7UBfSEGdLzXr5EBYQUOVEzVeCUNRDb0jqVl9qz0SgjENvaEEFtS6EUvq6B1J4NwaNxJqasyU5oALAsCp4ThaAy4ouo6R2OhsvwJI6gZUzUBS0+G0SwjGkmiockKyASeH4mj0OWGXDKh6akbGmtEOX7sQiCSTsInUzIkNPidsEBiIpNZRdR0JVYdHtqM/nJpl0SnZcDo4uk+bQFhREU1oCHgc8MgS4kkNtV4n5td4cHI4it5QAsPRJDyyhGqPA8ubUrNqZl67hqrUjJzdI3E0+13QdKAvnLqmM2SW4QkloJi8OtHPZebP7mAczQFXUXk601RnS+f2U9t+qtevSFPOp8CZvDoYScAh2UZnfU99R4ejChx2G2KKhsFIEl6nhCqnHZGECgMG3HY7okkN0YQGr1OC3S7gc9oRTmjpGBJRUnESEAjGkqjxOBCMJ+GR7fDKEryywEBExWA0NeN5tdsORTNScafKCVXX4HLYkdR0BGMq3LIEWRKw2VKnYDiSRI3XgYSqwS7ZIEFgMJpEk9+6LLD6vJzh/Kybcl6d6nfybJhpaZpp6QnG4jiQkZ5lzd6yTEZnMmfzNmcNXzk6m3eOGZFXzbSGEwr8LjkdZ10OG9yyhHqvhL6Qhp5QAq3VLhgG0BuKo87rRExN1WeHowpqPDIiigqbEAi4HDBgIJxIzThe55Wh6hokm4TeUCIdb+02CcF4EjUeGQIGesMKfE47mgOpmcvNz1XvlRBKaEgkkZpR3Jeq80YTOhKagWA0iYDHgWAsiXk1LoTio9v6nAh4JKg6EEmk6sdNfid8bgnH+2NoDriwrMGHA30h9I4kUO1J1bdrPU6ouo5QXEWtR4YOAwIC4YQ6Wm7JUHWM1jOdgEDWTN9W9TIA49bVJlKfO1vrFlDyvNpSbcfJwSS8sgTdMDASTz0K2+RzQjMMhBMqXA4BwIa+cAINXidGEklUOe0IuOyIKhr6wgo8soSA24FwQkUkrqGmyg4bbKmZ42UJHocNugEMRhR4nHb4nBKEABTVQH84gVqvE1EliVqvE8po26je64SB1JjbSV1H7ei1Bca/hlR2JamvzgbLV1+E1f94X8H3X/zGRrz64p+nMUUTU+npL0LRebWYfGoV53XdQGdXEIORBHwuGUlNT7e7ukey41ix7clC9Rvz+D0jcXhkCXU+gdNDZ8pxSegQwgZAIKFq0HQgqmjwu+2o99oxGNHQF06gJeBCLKkhktBQ55UxGFVQ7XFAlmyIJFSE4ql2oGQDXHYJYSUJn1OGEEAsqcEwDCRUHV6nHUlVRziuwSXbRssKCVFFR29IQY3HAQEgqWuwYbRu4nci4JYgCWAkriOcUKEbBqpkOwajCnwuB2JJFY1VqTT2hFKfLdXHlSpzHJKA0y5gGAL94TPLBACXI9WuDMZVDIQV1FXJcNgEbEJgJJGE22HHSCxVJ4qpqbpYlTNVxrU1+HB6JIa+0f4vv8cOGwR6Q6k2sNeZ6nPzyKk+Rr9LhmQDFE1FOK4joWqwCQFFMxBTUuc2nEii2pPKF7UZdZhi82nZO4eFED8C8DYA9QB6AGwF4AAAwzAeEEIIAPcDuApAFMAHDMMYN+LP5oKBZjxWYqgSMJ9SpWBepUrBvEqVgnmVKgXz6qhK71yt9PQXoaSdw0RnScF8ai/0xnQxDONvx3nfAPCRaUoOERERERERERER0ZxQCWMOExEREREREREREVGJsXOYiIiIiIiIiIiIaA5i5zARERERERERERHRHMTOYSIiIiIiIiIiIqI5iJ3DRERERERERERERHMQO4eJiIiIiIiIiIiI5iB2DhMRERERERERERHNQewcJiIiIiIiIiIiIpqD2DlMRERERERERERENAexc5iIiIiIiIiIiIhoDmLnMBEREREREREREdEcxM5hIiIiIiIiIiIiojmIncNEREREREREREREcxA7h4mIiIiIiIiIiIjmIHYOExEREREREREREc1B7BwmIiIiIiIiIiIimoPK3jkshLhKCHFACHFYCPHPFu+/TQgRFEK8OPpvSznSSURERERERERERDSb2Mt5cCGEBODrAK4AcBLAn4UQOw3DeDln1d8ahrF+2hNIRERERERERERENEuV+87hiwEcNgzjiGEYCoAfA7i2zGkiIiIiIiIiIiIimvXK3TncCuD1jNcnR5flepMQYq8Q4hdCiPZCOxNC3CqE2COE2NPX11fqtBKVDPMqVQLmU6oUzKtUKZhXqVIwr1KlYF6lSsB8SjNduTuHhcUyI+f1CwAWGIaxCsDXADxWaGeGYXzLMIw1hmGsaWhoKF0qiUqMeZUqAfMpVQrmVaoUzKtUKZhXqVIwr1IlYD6lma7cncMnAZyb8XoegNOZKxiGMWIYRnj0758DcAgh6qcviURERERERERERESzT7k7h/8MoE0IsUgIIQN4D4CdmSsIIZqFEGL074uRSvPAtKeUiIiIiIiIiIiIaBaxl/PghmGoQoiPAvglAAnA9wzD6BRCfHj0/QcA3ATgH4QQKoAYgPcYhpE79AQRERERERERERERTUBZO4eB9FARP89Z9kDG3/cDuH+600VEREREREREREQ0m5V7WAkiIiIiIiIiIiIiKgN2DhMRERERERERERHNQewcJiIiIiIiIiIiIpqD2DlMRERERERERERENAexc5iIiIiIiIiIiIhoDmLnMBEREREREREREdEcxM5hIiIiIiIiIiIiojmIncNEREREREREREREcxA7h4mIiIiIiIiIiIjmIHYOExEREREREREREc1B7BwmIiIiIiIiIiIimoPYOUxEREREREREREQ0B7FzmIiIiIiIiIiIiGgOYucwERERERERERER0RzEzmEiIiIiIiIiIiKiOYidw0RERERERERERERzkL3cCRBCXAXgXgASgO8YhvEvOe+L0fffCSAK4P2GYbwwmWPpuoFjAxH0jMTR5HdhYZ0XNpuY4ico33GmcixV1dHZFURXMI6GKidsNiDglsfdfjLHK+X5mM5zW05T/ZzlPk+Z+asl4EZ7ix92e/G/RZX78081/VNV7us3FRNJu7nuQCQBWbIhktDgddqhaBrqvE4srPMCAE4MRtAzkkBEUbGg1osFtR6cGIqiZySOloALmg70hgofr5LPJ5XGTMwD5Y4zueJxFS91BdE9kkCz34kVLQG4XOWrJs608zNdyp1XrY4PIGvZ/JozMXgqdUEgP74vqk/tazrOQ7nP9VySe67n13hwfDCK44MReGU7mvxOzK+1Lr+P9kdwfDCCgMsBhyQQHq0r6IYOmxCIKlpR14/Xm4hoek133C3F8azKq2LrPKqq4+WuIE4H4/A57XDLEmq9smX5VgqlPr9l7RwWQkgAvg7gCgAnAfxZCLHTMIyXM1a7GkDb6L9LAHxz9P8J0XUDj3d2Y/MjLyKe1OFy2LDj5tW4qr25pBdquo4zlWOpqo7H9p7CHY/tT2+3dX07Hn3hBP7+LecV3H4yxyvl+ZjOc1tOU/2c5T5PVvnrrus6cN2q1qIa9uX+/FNN/1SV+/pNxUTSbq77xcdfwbvXzMf/z96Zx0dVXo3/e2dfsodsJCQQkrAkBIS4FqgQtdhG3BCtVq3iy9tfRahWa2sFClhbq8WK2lqXLtrFtW7UWito1dcVVHYkIZCQkH2dfb2/PyZzM5O5AwOETBLu9/PJR5m5yzPPPfc85znPec7ZsLlaOmf5/GKe21LPnQumYNar2H3YwkObqsOex8Obq3F7Ra47uyDsu4H3G8n9qTA4DEcZiLeeGYjT6eW1HU2seq2/PWsXlrFwWk5cHMTDrX+GinjLqtz9H7n6NNxeMeyzoA6u63Acty34yNWnAVDdYo3Q4RdMyeKtPS0ntR/i3denEgP7uiDdyC3zi8Pe7xWVxRRnJTB/Upbs+J1q0oWN9wXpRr43t4g1G3fF9PyU562goKAwtAy13h2M+8ldI1abR852XVFZTKJBQ3ayNWx8Gy6/dyDxtrDPAGpEUawVRdENPAtcPOCYi4GnxQAfAymCIOQc640OdtikjgNwevzc9vyXHOywneBPiM99TuReu5p6JKENnrdm4y6uO6fwiOcfz/0Gsz+Gsm/jyYn+znj3k5x83f3KTnY19cR0frx//4m2/0SJ9/M7EY6l7cFjq8pzJcdw8JwNm6upKs/ltue/xOLwSZPB4Pd3v7KTqvJcLpuZF/HdwPuN5P5UGByGowzEW88MZEdTj+QYDrZn1Ws72RGn9gy3/hkq4i2rcvff3tAT8VlQB8faxmjX3d7QI6vDdzVF3nOw+yHefX0qMbCvq8pzI97vhzZVs72hJ+r4PXC8ryrPlRzDwWsM9hxGQUFBQeH4GWq9Oxj3k7tGrDaPnO360KZqWi2uiPFtMDgZ/Rtv53AucCjk3w19nx3rMQAIgrBUEIQtgiBsaWtrC/uupdcpdVwQp8dPq8V5nE2XZ6jucyL3auqRP8/h9h7x/OO532D2x1D27cnmZMpqvPspmnw19wxN+0/0/BNt/4kS7+cXypHkVI5jaXvwWEFA9pzg5zaXN+r30c4Nvd9w6k+Fk8dwGP+PhXjrmYE097pk29PS64pLe4Zb/wwmw1lW5e7vF6Pr6NB/H6st6BejXzva8x/Mfoh3X48EjtUGiMbAvo42dvtFoo7fA8+JZfw/UhuOdrzCyGKwZFVB4WRyqsnpUOvdwbhftGvEYvNEs12C9s5I8DvG2zksF+8sHscxgQ9F8XFRFCtEUazIyMgI+y4ryYBBG/5zDVoVmYmGY2ju0Rmq+5zIvXKSjbLnGXWaI55/PPcbzP4Yyr492ZxMWY13P0WTr+zkoWn/iZ5/ou0/UeL9/EI5kpzKcSxtDz1W7hxRDPzXbNBE/T7auaH3G079qXDyGA7j/7EQbz0zkOwkvWx7spL0cWnPcOufwWQ4y6rc/dVCdB0d+u9jtQXVQvRr5ySf/H6Id1+PBI7VBohGtL4e+G+VwBHH71iuMZhzGIWRw2DJqsKpzbwLLmTyjNOj/s274MITuv6pJqdDrXcH437RrhGLzRPNdlUJRIxvg8HJ6N94O4cbgHEh/84DDh/HMUdlfLqZ9YtnhDkj1i+eIRXEGCyG6j4ncq/SnCTuuaQs7LzVVaU8/WHtEc8/nvsNZn8MZd/GkxP9nfHuJzn5uueSMkpzkmM6P96//0Tbf6LE+/mdCMfS9uCxr29rZPn84rBzls8vZuP2RtYvnkGiQc2KyuKI57FxeyMvbW2I+G7g/UZyfyoMDsNRBuKtZwYyLSeZtQvD27N2YRnT4tSe4dY/Q0W8ZVXu/tPykiM+C+rgWNsY7brT8pJldXhpTuQ9B7sf4t3XpxID+/r1bY0R7/eKymLK85Kjjt8Dx/vXtzWyuqo05uenPG8FBYWj0dTazozvb4j619TaHu8mjiiGWu8Oxv3krhGrzSNnu66oLCYzUR8xvg0GJ6N/BVGUDcIdEgRB0AD7gEqgEfgMuFoUxV0hx3wLWAZ8k0Ahug2iKJ5xtGtXVFSIW7ZsCfssWM2v1eIkM/HkVUscqvucyL1Cq4CPSdCjUUGSURdzpd9jud9g9sdQ9u0JcEwNOhmyGu9+CspXc4+T7GQDpTnJx1REKN6//0Tbf6IM0fM7YTmV41jaHjy20+ZCq1Zhd/sw6dR4fH7SzPqIavZ2t5f8NDMFaYGqsa0WJ9lJBnx+aLNGv1+83weFEybuOvVkEG89MxCn08uOph5ael1kJemZlpMcl2J0QYZb/8TIiJdVufsDYZ8FK3efqC0Ikfp9wpjAtYaiH+Ld13HmpNgA0RjY1/mpJuo67dR32jDpNGQl6WWrufv9IgfabdR32kgyaNGqBWx9toIoigiCgN3ti6lK+yn+vEcyQyqrw5nJM05nxvc3RP3+y98uZ++Xnw1hi46N4d7+QWhfzLI6muU0lKHWu4NxP7nxKlabx+v1s7uph6YeF2a9GrNOTapZJzu+DQbH+XujHhBX5zCAIAjfBH4DqIE/iKL4c0EQvgcgiuJjgiAIwCPAAsAO3CCK4lHfpFPlhVMYlihGjMJIQJFThZGCIqsKIwVFVhVGCoqsKowUFFntY7g7V4/GcG+/4hxWOEWIKqfxCwnpQxTFN4A3Bnz2WMj/i8DNQ90uBQUFBQUFBQUFBQUFBQUFBQUFBYXRTNydwwoKCgoKCgoKCgoKCgoKCgoni3kXXHjEvLE5mWN4561/DWGLFBQUFIYPcU8rcbIQBKENqItjE8YAIzVrudL2E6NdFMUFsR58kmU13v2h3H/43n84yWm8iPfzOVmMtt81mLI6HPtmuLVJac+RGSq9Otx+94mg/JbhhyKrAUZy22Fktz/Wtiuy2o/S/vhytPbHLKvDdF410p/PQEbb74HB+U1R5XTUOofjjSAIW0RRrIh3O44Hpe2jh3j3h3L/U/v+w53R2j+j9XcNBsOxb4Zbm5T2HJmhas9w+90ngvJbRjcjuU9GctthZLc/Hm0fyf0FSvvjzUhv/9EYbb9vtP0eOPm/adiXfVZQUFBQUFBQUFBQUFBQUFBQUFBQUBh8FOewgoKCgoKCgoKCgoKCgoKCgoKCgsIpiOIcPnk8Hu8GnABK20cP8e4P5f6n9v2HO6O1f0br7xoMhmPfDLc2Ke05MkPVnuH2u08E5beMbkZyn4zktsPIbn882j6S+wuU9sebkd7+ozHaft9o+z1wkn+TknNYQUFBQUFBQUFBQUFBQUFBQUFBQeEURIkcVlBQUFBQUFBQUFBQUFBQUFBQUFA4BVGcwwoKCgoKCgoKCgoKCgoKCgoKCgoKpyCKc1hBQUFBQUFBQUFBQUFBQUFBQUFB4RRk1DqHFyxYIALKn/IXj79jQpFV5S9Of8eEIqfKXxz/jglFVpW/OP4dE4qsKn9x/DsmFFlV/uL4d0wosqr8xfEvZhQ5Vf7i+BeVUescbm9vj3cTFBRiQpFVhZGAIqcKIwVFVhVGCoqsKowUFFlVGCkosqowElDkVGE4MmqdwwoKCgoKCgoKCgoKCgoKCgoKCgoKCtFRnMMKCgoKCgoKCgoKCgoKCgoKCgoKCqcgmng3QEHhWPH7RQ522GjpdZKVZGB8uhmVSoh3sxQUBg1FxgcXpT8VFEYeynurMFgosqQAihwojFwU2VVQUBgKFOewQhjBwafD5kKnVmF3+8hKMpCfaqK+y05Lr5PMRANqFbRZXRi1amwuHx6fD7NOg83jw+7ykmTUkZ2kJy8lcF6HzYVOpaLT7sak05CVpCc/LfaBLXRQFIDdTb2YdRo6bG5ae51UFKSh0Rx/ILwy6I4unE4vO5p6aO51kZ2kZ1pOMgZD7OrO5nCxq9lKS6+LrCQ9pdkJmI36mM93u31sP9xDc6+TnCQD08Ymo9OpYzrX7xf5+EAbXh902jx4fH6ae+2cNSHjuN6XkSzPfr9IfYeVpl4XFqeXVJMWi9OLWR/QIWOTjOxp6aWl10m6WY8fkXSzXtJXQb3T0O1gX4uF7Ye6uXzWOHY39ZKZqMft9ZGTbGLCGPn+GS39qKAQC90OJ/uabZLeK8k2k2I0xKUtfr/Ilrp2fH6BNosLgHarg4qCMco7OIwJtSFNWjXdDg8Wp5exKUZKxiTwVZuFLrsLs05Ll91NVpKR0pwkNBoVfr/IgXYbdZ02zDoNWYk6Ouwemnqc5CQbSDdpqe2wB74LsSGPpqe9Xj8f1nawpa4Tvwivb2vkzgVTWFCaHdP5CicHr9fPrqYemnqc5KYYEYCmHicpJi09Dg9JRi1ZSXrGpYY/j6B91Wl3k2bS0evwYNZryEzUo1JBc48Lm9tLQZpZGtuDsrWnqZfqVgvv7G3lwmk5jE83k2bWyc5JFLlQGC74/SJv7mrmtue/xOnxY9CqWL94hqTDRgLDyb5QUFCIjuIcVpAIDj73vbmHKyvy2bC5WhqE7rmkjIc3V1PX4cCgVXHXhZMRBAGry8uzn9Vz4zkTcPn8rP/PPumcFZXF5KUa+fOHB5g/OTvseisqiynOSmD+pKyjDmyhg2KqScd1Zxfw0Kbwa3U7PFww9fgGydEw6Cr043R6eW1HE6te2yk9z7ULy1g4LScmB7HN4eKfO1sjzv9WWWZMDmK328cr2w+z6tWQ8y8u45LysTE5iBu6bRzqdLL6tV3S+WsWlpKXaiM/LeGo548Wefb7Rd6vbuVwj4vH/lsToZNuO7+E7GQDP3pxu/TZ8vnFPLelnlvmF/Psp3Vheqcg3cj3zy3i9he3hR3/01d2hjkKQu8/GvpRQSEWuh1O3trZFqH3LijLiMsErqHLysF2B6tC9ODahaVkJ1nJT08c8vYoHJ1QG/Km2YVYXV7JVitIN3LzucU8+m61rH25cNpY3v6qVdK3BelGvvf1Ita83v/8V19Uyt8/qWNfq1WyIc8tzuStPS1R9bTfL/LPnU3c+VL4OHHfm3uYnJ3I+HSzoufjgNfr55Vtjdz9ys4wW/7pj+rosrulsfx7Xy9ibIqNOUWZqFSCZF89+k41V59RwPK3vwizCTIS9fzkHzvCnuUFU7LCZEROtgbOSZTxX2E4cbDDJskigNPj57bnv2Ty8jkUZhx9XhBvhpt9oaCgEB1BFMV4t+GkUFFRIW7ZsiXezRgx+P0iOxq72bS3leLMRB54ay91HQ7pe4NWxZLZhTz6Tg0AyyuLAHj8vVqWzC5ErQr8f3DgCp7zwKLpaNQBQ0oQBL5qtuD2+fl4fxs3zZ6IWi2QZNCSnazH64NWS39kclNPYLVeJcDtL3zJ/8wtwqBV0evwkGLS0dLrRK9R8+cPazmnKIPLZ+bSLUWZGJmSlcihbkd/FEpfZAAQFh3t9Pi5/o+fRrT9jeMfdI/JclRkdXD57EAH1/4h8nk+c+MZnD4h/ajnf3qgg+tkzn/6xjM4I4bztxzs5PH3qrnmrAl02TykmbX85eMDLJ1bTMX4tKPfv7aDJz+oiTj/ptlFnFF49PvXtln55b92RZz/4wtLB8rzsJbT2jYruw/3cvuL21gyu5CnPojUL0vnFrJhUw05yQYum5lHskHDtLxkOm1uMhL1tPQ6AYEn3tvPnJJMNm5vpKo8lzSTlqKsBNosLvJSjTg9PgozzHi8UNdpI0GvQadWcdUTH0fc85+3zGFiZn8/hkYX5SQb8PkDeixapJESjRROjP0xrGV1NPDpgQ7ueHEbVeW5CH29/fq2Ru5fND0mvTfo7antoKali6KsVFr63qea5sC/Y9GDceSUldXaNivf3PA+S2YXkmxQY3X78PdNMcw6NQ9tqo6qy/+65EyueeoT6fOb5xXJHverRdNZ/vcvJP1fOTmT5c9+wRWzxpGRoCcjSYdOrabX6SE3xUSqWcOLWxvRqFRMyk7E7xexub3kp5nodXpINer4xb92s6WuJ+w+R7L/jlXnRzt3sPX/cbQrbrK67VAXVz4eOb4G5xnB/9+4vZF1F5fh84ukmfV02V18Ud+NVq3ikXdqZG2CF7Y0sGT2eLKSjCQaNCQZNNJOx4MdNnodXl7YekiSGZNeQ1O3nWl5yeQkG/GL0GZxDdq8QBnzj4xiAxydj/a3c9vz27hsZp40Pr+0tYEHr5zOWYVj4tu4GPj0QAcfVbdwVlGWpJM+qm7h7OKsuNgXx0PoToec5P4dLzLELKujTU4VRhRR5VSJHD5FCVVyealG6joc/PCF/hXy2y+YRKJORUaSEZvbR6pJi9fv5083VKDXCIio6LC6eeiq01AJ0Gl1c9OcQl7a2gDAZTPz0GtUJBk17G7qxeH2UZBu4u3dzeg0AledUcAPQlbkV19UymP/rZEik1dVTeXZT+vZ12rlgSum852zxlPbZuXZz+q5siKfO0KiBVdXlaJWwycHuqRozYJ0IzfPKw6L3lxRWczUsYnYXP6w6Oib5hSGGYAQWJVttThHxIrsaOREjOnmXhepJl2EEdXS64rp/JZeFyWZCdw0dyIOlxeTXsMT7+2nNcbzfaKX86bk8L/PbA2LePOL3pjO9/p9VA44f83CUrx+X0znW10e2ftbXZ6Yzh8O+P0ibRYXPlHE6fGj16gi3tFUk47izER+fOEkUow6fhYSBXT7BZP41b/3snTuRF7+/BDfOXs8BekGkgwa/vZpHVdW5Ef0r8srsuLZ/iiklVVTSTXpaOpxSvd0evzsae6lIM1EQ7edVouL5l4n+1ut0jbV0F0NAyONRlI00lBMaIeyP5QJ+pHpdngiIjqXzy+mxxEfvZFoVKHR6Lmuz0ETjDRKNI7+OsrDXVb9fpHaNisHOmwYtGpSTVqK0hNot7hYc1Ep+elGGrocrH87POo31aRDEJC1tw73OKTPc5IN5KcacXr85CQbuObMfMmJl2rSUJ6bxJySTIozE3B6/CyfX0KH1Ynd7aWpR2Tdxt1h0cqPv1cru+ssGJ36/XOLWHy6SGuvG41aIDfFRH2nFYvTI6VWCz6Do+1kO5L+OpK+A07omZ9Iu+JBU49TVg4EAWmxtzwvicIMM0tDxurl84t55ctGbjt/Upi8BOccp49PITfFGLbz6rbzS0hP0FHXbiM72UhJlhmtWsWDb4fvdGyzuPH6RJ75+AAl2SmDMi8IjaavKs9FrYLTC9I4uzD9hFLhjRZGkk0UT3KSDdzwtfFhu3NvO7+E7KSREXWr10JOaqK04BIczw3aeLcsNrxePy9/2cjKEJ/CuovLuHRGrvIeK4w6FOfwMGMoJgVer59/7WqiutWKXwStRqDD6uT+RdOxu7w4PF5UgoBKreb7f/s8zMHUa3cwJTedhi476WYdKhV8eagHvwgf729j3SWltPa6WLtxN6kmHV5/HuNSTXSILkTghxeU4Efg//1la9j2mDWv75IiBpweP2s37uaJayu4/9972ddiAeDVLxv54QWT+VHftnDp3I27+ON3T+fj2g5STToAfnjBZGpaLZLDuqnHyUObqnlg0XQpEjE4CYZARMDACIHMxJEx6I42/H6R92tasTh82FxeOmxuDnX1bys8GnkpBm6eN5FWiwu/CGoBbp43kdyU2J5nUaaJ684ZL8lZcNvrxAxTTOerUEtboSEgo6te28UzN54R0/katZoXttTzq0XTJef0nz+s5UcLpsR0vqvvfsd7/3gTOpn66TensuGqGeQkG6goSObcSVlkJxvISzHS0O3gjhe3sWxekeQYhsDvfeCtr1izcCo2l4+b5kxEr1GhIjAZHPjuOz1+Vr+2i8evnSU5g50eP+s27pYik4MYtCr2tVjISdZzoN0etiV2ZdVUXv78EEtmF0qLEve9uYfcFIPkYBBFRsTWwKGasA3VVkm/X2TzVy1sb+iRdMK0vOSY0hqdKqQYtXg8bv58wxlhkT3JxvjM3ixOv7QFFYJ6bCdPjxA9drwMd1n1+0X+tbOZX/074OwyalXMKkjly8PddNk8ZCbpUasFko061lxUSpJRQ5vFRVOPg1UXTaW2zSprb6WadBi0KkoyE7j+a+PRq9Xcc/FUDDpNmJ5dVTWVm+cX8dLWesamGLjjxU9JNem44Wvj6XJ4ePzfX0nXrirPlWTospl5krMUAvK0YXM1y+YV0djtYHJ2Ip0qD0aNmgfe2tu3UPJFhP4L1Vly17zt+S+ZNGB3SZBo+m7qijnsbrKckL6NpV3xGmfk5jU5yUYqCpK57pxC3F4fWYl6uh0ekgxaijPN3PnSjogo81STDqfXxx0XTCY9UctdF07CoNVgNmj46cuBVBLLK4vCdjE6PYF0d09dX4FOrSY9QYtGpZYcw8FjHtpUzdK5hZRkJrJwxjj0atWgzAsOdthkU/Xdd3k5F5WPHRbvdDwZynQJw33R7Uh4fCJ//aQuzL786yd1zJuUGd+GxYjLw4gez3ce7uGRd6rD+v+Rd6opzkxgRn5qfBunoDDIKM7hYcRQTMj9fpFdTT3o1AIlmYnYPT4MajUGrYo7XtwmRRw4PD4e/9feMEX+6Ls13HtpOZ8c6MAvwm/freGq0/N5YUsDOo3A9+YWsb2hR4rSuPasAjZsribVpOOKijzUggq9Vs2Wg11RIwZC//1ZXSdXnpGPxRmIXLqyIp+aVovsufWddn7/Xi0//eYU7G5fmGNv+fxinvm4jqYeJza3l1STjsnZidw0pxCA975qZfn84jDDbf3iGYxPNw9Kn5+KnIgRVt8ZKFiw6tWQXJMXl1LfaWP8mKMbi4kGNS6vX5ogGLQq7vjGJBINsRWEc3r80mQ09N9//58zYzq/xeKKEnESW+Sxze3l8pn5YTK8uqoUuzu2yOPWE7x/vDnUaSXNpGXZvGKWh0Tyrr24jEffCeQ9D50AZiToZX9vokHL6tcCEWQVBcksmT1R0jNyxzf3OLn2rAJJVzg9fvJTTdIEsSDdyI8XTMHh8eHy+nl4gIP58ff2s3TuRClqLegwbrG4WP3qLrrsbh5YNH1E7FIYqglbS6989Nhg90d9p43qFmuYTlhRWUxRRkJMOuVUwKSD8vw0XF4fPj84PT7K89PoW28dclp6o+ixGHdwjFSGs6wG048daLfy029O5edv7JZ2e4Xmi73t/BJSjBrarG4aexzMzE+lKNNMbZudWfmp3L9oOoIAj/93P/taray+qJTaNivrF08n1aTB6xNo6dMBN/55S5geWrtxN7+5cgbfOWuCFFF6zZn5rP/PvohdYKG6Pprez04ycPeAHWZLvjaBdptbshFf2togOX1bLf06K1Gvkb3m3pbesCKnQXtoX0t4wELw+JZe1wnr21BdGu23xmOckZvXPPzt08hI0HHj7EL8ItjdXnYedjEmQU9jVy9jU43cccEkEkL6NyfZIM0pQp+Vze3l3n/tkY7zi/K//ZMDnWzYVENBupEffWOy7DF+Efa1WjBq1STq1ay+qDQsL/HxzAtaep1UledGLEjf+dJ2puUmD6txPx4MlQ0w0iOUD3fbufas8Tzw1ldS+2+/YBKHu+0UZw3/HPwjfTxvs7q4+oyCsN0Gt55XQpt1ZLRfQeFYUJzDw4iTNSEPVvZtszgx6jS09jrwiUKY0XPPJWWcPSGNqbkpPLSpP9VCTrKB684uID/NhCjCjoZuXtjSIBWMePazei6bmQfAmo27pPMum5knOYYHGnSPXj1TdkU+NP21QavC54d1G3fzwKLpANz+4jZumlMoe65RFzAi26yuiKiBDZv789wFnd93DHAev7mziaVzCzltXAoF6eYRtaI83DhRI6zd2u8Yhr4V5ld38ZclZ8Q0OW63efjXjsMRkbelY5MoiqH9bRb5tBJtFncMZ8OYBJ2sjKYlxOZlMes0rNn4edjvX7NxF0/fENsKe0aiXvb+GQlHL6Y3lNgdbnY2W6TKxWXZiagEFZ8c6Kah2y69x8Etow1ddm6/YDL3vrEHk04treDnpBjkdYJWTapJR0aCjstn5rO3uReDViV9P/B4g07Dhs27wnIedjvcUv7MNLOeW0NkOnTRCQJRakHHMASeWzD6OOh0rm61jIhdCkM1YctKkn92g90fLb2uiEi6hzZVMzM/Ne4Ot+GCgBqry0l1a1/EajsUZSbETTYzo+mxxOGlxwab4SqrA8f1gnQjK6tK6XV4GJOgY3+rlbu+OYV739jDXz+p4wfnleD2BRxuX9R3UZyVgM3t47t/+kzSoWsWluLx+vD6/Dz1fwe4c8FkDnW5ePSdaqrKc/H5RVln6u6mXkoyE6U+Cl0glJOZI31X32UP6+tnP6tn2bxiKTgiVNfXd9ooSDdLkc6lY5PkbVl/wJ4vzEiQtYdCxw6DVoXN7T1hfTtQlw6XcWbgvCbVpKOm1cotf++fE6y+qJRnPztAXYdDkquMREg399tSwTlFqE3g8PioKEiVdgxeNjOPSVmJsr9dp1aRk2zgyop89rXIj8NmnRqry8dDm6r59RXT+dW/9/LAoumY9erjnhdkJQVqqAwXZ/1wY6hsgJFe0C1Br5Ucw9C/Q+6vS2ILWok3mUl6CtKNETUNRsp4nmzURuw2ePDtfSMm8llB4VhQEqUMI440IT9e3G4fr24/zHee+oS1G/fweX0X2clGyTEcvMfdr+zkmrPHk2hQS58XpBv53txA5MQPX9jGsr9/wW82VfPdc8aTatKxYXO1pOiDkQpGbWArVvDfoQZd8F5rN+5iZdXUMEfN2ovL2Li9Ufr36qpS3t/XitPjx+3z4/H5cXr8vLS1geXzi8POXV1VypPv7QeiRw2oVQSiWUxa2a2F507OZHJ2El8vyaQwI0FxDJ8A0Yywgx22mM5vt7pln2G7NTbnrNfn44qKQOTtnf/YwR0vbuOKinx8Pv/RTwZSzVq+fWZB2PnfPrOAVHNsa2kmbSDiJExGLyrFrI0tcrndKr/C3mGLbYXa4fayuqo04h1xeGKLPB4K7A43b+xu4bo/fMotf/+C6/7wKW/sbmFncy+rXtspvcfBaKGnPqhlw6Ya7nhxG989ZzwZiXqe+qCWRzbXsPLVnRH9vaKymOoWC989Zzzf+/pE1mzcxfNbArrj9W2NETrk55dO48n39uP0BCKLg9fITjaQbtZSnJUoRZdBv94ILowBUSeAfhHp2Oe3NHDvpdPC7r1+8QxUQqDgSG2bFb8//kVigxO2UE7GhG18upn1i2dE9Mdg79qwueSdL7FG458KeHx+GrocPP5e4L36/Xu1NHQ58MSoNwcbs07NmoXh7/WahaWYdbHp0ZHKcJXV0HE96GRb9rfPue35bSx9ZisOj58H3trLktkTWPK1CTT3OMNkyaDVREyuV7+2i6KsRDw+P8vmFZOg1/DoO9VcWZHPUx/UcudLO3jy/VquPauAnOSA7gkGDtjcXkk2THoNBq0qwj58fVtjX17LwHcrKsP1/sqqqbywpSHsd1aV50p5JYPt3LC5misq8tBpVOSnmrj30mlcUZHHnqaeiLFk+fzivnz0zoh+C73eZTPzJH1XkGY+YX0bqkvlfuvJ2g0XzD8dbfwaOK+RS3mx5vVdVJXnhsnV8me/5K5XdrC2TwcE5xQDbYKlz2zlhq+N53tzAwEg976xJ+K3r6gsJlGv4ZozA6kdgrbAwGOykwzSvMMvEijKLcCcogwAPjnQccxj9Ph0M6cXpMk+X6NWPSzG+3gyVDbAyZhfDyUdtmjzgtjmRfEmxajm5nOLJLv9yfdrufncIlJMI2M877bLz0u77SOnlouCQqwokcPDiJOxgrqjqYeVr+4Mi+D1RynAtr2hm+LMRMm4XFk1lb3NvRGRuMG8nY++U4NaBTq1Cqc3sHU7O9nAispinB5fmEEXSl2HA4vTw5LZhahVUFGQRmuvXXI0iyI89l4NVeW57Gu1crjbgUYlYNCqaOpx8szHdSHnpvLAv79ie2MvEMjPJ9eHs4vG0Glz80FNu+xvP21cCl8viS2nrcKRiWaEtfTGFiVh0qlln6EpRqeAXqNh9WufR0xCY825K4ZE1QfPX/P6rphXiA/3OPn7J3WByGW3F6NOw5Pv7ef784ooH3f089PN8hFzaebYVtgTDVpe+rw67P5Pf1jLT745Nabzh4I9LVbZ1B2/uXJGWOST3OLSg2/vY+ncfh1W1+Hgsf/W8MCi6extsaASAg76x96rpcvu5peXleP0+CXdcdnMPFQqeOr6CrbWdePy+kkxBobC5ZVFFGcmsn7xdCx9xmCPw8OOxt6oi07Btp42LiXqjoig07nL7mZmfgpvLA9sT85IMHCgw8qCh96XoqiGw1bH4IRtYPT/YE/YVCqBBaXZTO7rj8zEk5MHcEyUKNR0c5xyJgxDLH0RcwMjVstyK+LSni6Hi3SzjsevnUWX3UOqSYvb66fbMbq3cQ5XWQ0d1+X0cnCH1gNvfcVT11ewZEA6iO0N3VHsAhe/6ssTvLyySHYLfujur2ARuatOz5fSgTV221lRWcxDm6p55uM6ls4tJD/NhFmn4akP9ktjA8CyeUW4fX5mFaTi8vrpsoc7V6It8uWnmdjV2EOPw8tp41Lw+Pwc6nLw+rZGaReLKMJzW+q5eEauZLdHs4fKc5N4Y/kcSaeeqL4dqEuzkwxcMDWbNuvJ06ux7BIbOK+JlvJCECLlqq7DwaPv1vDH755Ou9Ud1SZY/59+m6Cpx8nTHwVkIDfZSH2XQ0p3suai0jBbIPjcJmUlcu8be+iyB3YK7Wu1SnOOyVmJvLWn5bh3wqlUAmcXpnPf5eXc+VJ/Ie3l8wNps+5cMCXu4308GSobYKgilE8WRp0myq7ZkeFc7bR5ZWuh/PG7p8e5ZbFhjtL/sc5LFRRGEkrk8DDiZKygtvbl+RloUMmtYvv8cKDdxorKYrrsbmr6CtZFM+QMWhXleSkk6jXsa+7m++cWs2FTNT6/SHFWIo9ePZOEPkffwHtZnD4efaeGDZtq2N7QzYEOJ4++U8Mjm2t49J0a6jocqFWwfH4xL2w9hFGr5tbzSiQH8VMf1JKTbKS+086+Vqt03XSzjl9cNo3llUUsm1/EisoiHrn6NDIT9fzguS/xi/K/vUBJIzFomPoG0VCOZRBN1GuiRn7EQrTI41hX2Nui5OxtizFnb4Jew75WK8v//gV3vrSD5X//gn2tVhJibL/d45GNRnJ4YluhTjPr+M5Z46lptXCoy8H+VgvfOWt83J0LobRFiY5OGBABdqRo3FDqOhzS//v88Nh7tVLe4DSzVurLpp6AnvnN29V02DyBQjUf1OLxiXz7zAIef6+WW/7+Bbc9vw0vAu1WF6982UhxZoKsTM8qSOW+y6fxxLUVuD1eSUcFv18+v5h/fN6AQatCJQQcAPlpZgozEjircAyCAMv+9sVxR9mfLIITtjeWz+HZpWfyxvI5J20Cq1IJUn+crF0bLq8v4tnc2rftXSGA1SkfsWp1xidi1aDR8Nh/a+h2eHF6fHQ7vDz23xr0mtEd0zBcZTV0N8GRHHxOj59eR6QsRbO99rdZpWP9YnTnbEGakSWzC3luSz3L5hVh1ql5bks9S2YXogLyUk0snVvI5bMCuzlsTi+/e7eGMwsz8IsiagGe/qiOR96pwaBRs+rVnVicHn42YNdJcJFvYDuTDVr++GEdtz3/JYIAY5ONvL6tUYpyfmRzDU99UMvSuRMpz0uW7PZouzCKsxIlfTdY+jZUl44fk8DEzJOrV2PZJTZwXhMM4AgluIgaLZikx+Hhzx/WxmwTNPU42bCphkPdDh59p0ayBYIR5sFjHn0nEMG4t9kiHRPcZXio08b6xTPQqAXZ31jfaTtixHQoGo2Ki8rH8tzSs1heWcSS2YU883EddR2OYTHex5uhsAGGKkL5ZKFTC7LzIp16ZMxbO2wnNi+LN7q+/h7Y/3qt4kZTGH2cNCtbEIRxwNNANuAHHhdF8SFBENKA54DxwEFgsSiKXX3n/ARYAviA5aIo/rvv81nAnwAj8AawQhTFUbcX52SsoCYZNBERvMGo4NDCScFojNVVpdR12Hhw8Qz8onjE3Fwrq6ZyuMvOHz48wK8un05zryOiIu+vFpXzs4tK+VlIfuNgvrXgtUrHJvOz13eGtdugVXF6QRq7mnqoKs/lsfdq0WkEfn/tLL5qtjA5OwmX14deEyxK4UMlQFqCDpvLF1bMZf3iGZIzKuh0UorPnTzcPl9EHy+fXxzz9uT0RB25KQaWzg0UK1EJkJtiID0xNudm0MEYKbOxqbusJPnIrayk2CJ3dVpBimIK/v4VlcXoNLG9xwk6rTTpDY1GCubePhptVhftVnfYO3D7BZNot7qGTX7VaNHhahWsu7iMla/u5JmP6/jpt6bIHjdQJQYNtiffrw07tiDdiFaj4r7Lyqltt/J8X770NQtLeXnrIenZCEJktHgwX3Bg8r8/QmeuWVjKqld3SgWZbju/hH9uP8yKymLGphjZ32blmY8DEUv3XjqNmfkp5KeF6/Ohyu17PAQnbPFux2CQbtbzt0/rwt6pv31ax/lTs+LdtGFDtFzpY2LMlT7YJBjUXHVGQVhhznsuKSNBP7ojdYarrI5PN3PvpdO46+UdgPwOLbHPAWzWq1lRWcTzW/pzBb++rTFCh95zyTSe/vCAdI2Xtjaw+qKpstdOMmgpzlRz76XTePK9WuZNzuTiGbloVCrGpZl56oP9XH9OIdWtFnx+eOnzBhaU5YTZIT+7qJT8dCOHu53ce+k0Grvs/O2TepbOLSQvxUhdp4NH36mOKES2smoqD2+uln5Lc6+TswvTue38Saz/z1fSTrbT8lMpHGNiXGq/no91F8ZI1LexjF8qlcDkrATJnksxalm7sFSKIjRoA2m3HvtvDRdNz40anXfNmeP56ycHuf4c+bojcjbBwDomOk0ghdRPX94RdT4yJTsJr1+kbGwSBelmPjnQEfEbU006Pq/v5q6Q6xwtmlilErC7fWzYVHPE/lI4OQxVhPLJwi+KmHXqsHmRWafGP0JcIdnR5lUjJOewxenBpA3vf5NWjcWppJVQGH2czBAML/BDURQ/FwQhEdgqCMJ/gO8Cm0RR/KUgCD8GfgzcKQjCVOAqoBQYC7wtCEKJKIo+4HfAUuBjAs7hBcC/TmLb48ZgG4hjB6R5CG6peu7Teh5cPIM9zb34/AHn09K5E/npKzvpsrtZUVlMuklL2dhk7rmkjEOddsmxctv5JaQn6PD7RZ75tIErK/K5/o+fcv+i6RHbvX704naeuG4Wf77hDNqtLvRaNes27pIKcaysmopZL3DNmQWs/8++sEmDy+cDEf7xeeC+K6umsqepF4vTx8pXd3DFrHG8sPUQP7xgMgfbbRSOMZNu1nH7C59FrPI/t/QsKeo4NC1F5eRMpuWmjBgDYSSQbtbLOjcXlGXHdH5eipmGLjspJp20nVijDnweCykmDb+4bBoH2m2BSCQBxo8xS6kDjoZGJURMDldfVIomRhnx+yDRoAkzIhINmoho12h4fD6WzSuW8h4atCrWXVyGx+eL6XydWiVbuOK5pWfF1oAhIMmgkXWgGzRq8tOMUt+19TojnsUvLp0GIeljgo5Zu8vDXRdOpt3mxi9Cgk5NVrKBG/7YXwBp7cJSkk06nnivhuvPKWTauBQS9BoOtFtlJ7nBfMFLZhdicXpYOreQ4sxEUoxa7n51hxSxHNza+sCi6YxLM1Kak0x9l51zJqYfcRIy0rc6jhTGp5u5c8GUk54mYySTaFDzq0Xl0o4htQATMxNINMTHGWt1+nj207qI9Dh3LpgSl/YMFcNVVlUqgQunZJFi0lLXbuOeS8qk1EChAQZ3XTiZ7Q09iMCqi6byu3dq2Ndq5cqKfN7e1Rxmdz68eR9XnZ4PwJySTGlH2kAn8orKYlQqgfve3EuX3c3ahaU4PT6SDBomZiTw//4aSCPV2L1HSp+2ZHZhhD36s9d3sXRuIRs21Uht7nF6MGrVPPh2v/O3zVrD0zecgc3t5YtD3TyyuUb6Lqifg9Gg03KTj+hsGulOqSMRy/jl9frZcbg3zClanpvEg4tnAIHF/BSThnUXl+H1+8OefUG6kTsXTGF7Qw8TMxO488LJtPa6I2Tv1vNKMGhUYTbB6qpSHnuvRmrT8vnF3PvGbq46PZ8lswsxhgSmBOcj91xSxuTsxLCdhHK/8YqKPMkxDLEXN1PG+/gyEhdggug18uNwtM+HG2a9mvsun8b+tv55WWGGmYQ42RfHyhizgTWv75bSX/r88IcPD7DhqtPi3TQFhUHnpDmHRVFsApr6/t8iCMIeIBe4GDi377A/A+8Cd/Z9/qwoii7ggCAINcAZgiAcBJJEUfwIQBCEp4FLGKXO4cGmYEwCRZk2DrRZWVU1lbV9Rte+VittFic6tQo3fn68YAq/e7dGcgwbNCo67B5Wvb47zLFic3l5/P0DdNndPHzVaVx6Wi739eWLO9Buk3WwfHawi7MK0wOOlrf38cMLJuNwezHpNDzx3n6uPXs8f/y/gzy4eAZOjw+jTs2T7+/nzMIM1Cq499IyTHo1P3pxuxSld+t5Jfzt0zquOj2fX/TlClvfZ2zKtcHu9knRG8G0FOsXz1AcwyeBE53cqlQCZ03I4GCHDZ3m2CdTfjGQGiI0cva280soHBPb/VstLtmcwcvmF8d0viAEtoCVZCZic3kxGzTYXR5ilbIUs44WizvMuaxRC6SYYovgs7t9Ud+BeOP3ixzssKHVqMhNMQ6IDjcyJSsJgIZupxTdU5BuZP3iGdS0WlEJkJOsp9fl49GrZ9Jld1PfaeeP/3eQjASdlBoi1KmQatJJW0ZXvbaLJbML2VLXw/XnBNqkVwukp5lYXlmEXwxErwUni8F8wckGNWNTTPhEkYxEHT12T1gqC+jTOwKSTollEjJUuX1PdYargyb4PrT0OslKim+bep1eOgfsOPjxgsn0xrhjYrBpt7pp7HbxVbNFqm7e2O0aMdtQj5fhKqsAer2Gscl6EvQarC4PT11fQafNjYCAz+/nmjPycXj8PPJOTdhCf6fVyR8/rOOKijxuDdmiD/DQpmoevuo0dhzuwS8GUqE9srkmbHH56Y/quHxWnuSgXfXaLpbNK+KBt/Zx2/kl0vVCF/9LMhOOmH7A6QnkMn7q+gpuf2G7dG0IpDKwub18vSQTh6c/L/FA/Ryq54/0Lo9kp9SRiGX82tXUQ22bNcwpur2xl1uf/5LbzivG6wenN2CbfFjTxrVnj+eBRdM53G3HbNCGXTsoS9PykvnRNyZh1mkw6TU0dtt5fXsjT1xbwWd1nfj88PdP66gqz0WtgqLMRH791l6urMjn6Y/qpGf9+2tn8pMFU3D7/IxPNzE1JxmNRnXU31iSmXhcO36U8V7heEkwqEgx6WgPGf9STDoSDCMjrUGP3Ruxo/GOb0wiK2lkFAWempPELfOLwxal7rmkjNKc5Hg3TUFh0BmS5G2CIIwHTgM+AbL6HMeIotgkCEJm32G5BCKDgzT0febp+/+Bn8vdZymBCGPy8/MH8ReMXFQqgXklmeg1avY29bD+iuk4PD4ykwwk6TV02Ny4vX7qO21cc2YBnX1GcGFmAv/7zNawlfGgYyVoWO043MNp41KkY9w+v+yquM8PjV0Okk1aLpyWE7ZNdEVlMUlGLV12Nz6/SHOvk2c/q49IT3HvpdPYcOVpdNrdpJt1uH1+zpuS1beVL0WaQB3ssEVJCWDgzAnpw2bCNZpldTAmtycymepxeKQodOiP6nz82lkxnW/U9ecMDmLQxl74QaMSEBG4PUTO1yyMPfLY6vTxk3/siJDhWAviRYtOyUo69uiUwZTTgcVrFs/KYdGsAlosLrKT9EzLScZgCAxJF5ePZXyaif9Wt+Hzw7qNuwG47uwCvvunLSyZXcjG7Y0sm1csRSRdNjMvIjXEQ5uqpeKZwc+C0WkqAV7Y0sB1ZxeELYIFI+CurMjnmY/rKEg3kp5oCHueq6qmUpBuDHMQG7QqJmUlHrOcD1dH0EjjaLI63Bw0sRRzGkpcHpFfvrk37P355Zt7eeK6+BSkSzNrue7sgojdBakmbVzaA4PnzB9psgr98lrXYcPh8fHql41UleeSlaRjYkYCbRY3PU4fT30QXsD47ld2sP6K6fzwghJ8flHWqdbj9EhOgxWVRXTZ3ZLOhsgUAU6Pn+xkAznJBnz+cLszuPh//6LpUVNfhF6ny+6JKEpn0KqkFECx6Ofh9i4PJkeS1Vj6p6nHyfNbItO5ragsxu0TeeSdGm6aUwjAlroeFk73kJFooMfpY/3b1RGytGR2IT/+xw6+f24Rq0NSU/zsolK6He6wCOVgoepHrj6Ni2fk8szHdWER4Al6Lbkphoh0T0f7jcH0KccaAayM9yeX0Tyv0qk1pJnVzE4aQ4vFSVaiAbfPg049MnLwe/wi9/87fEfj/f/+Km72xbGi0ai4ZHouxZkJNPc4yU42UCqzmBQLo1lOFUYHJ33JSRCEBOAl4AeiKPYe6VCZz8QjfB75oSg+LopihSiKFRkZGcfe2FFKfZedpc9s4d5/fcX3//YFP3xhO//z9BYSjVoQYGdTL/f+6ysOdTu4782vuO/Nr7DIFBQJOlag3+nbZnFJ+T6DuYxDE7Yvn1/Mxu2N5KUaSTZoZauhi36RO74xCZ/fT5pJJ1ut+q6Xd9DjDERylI9LpWJ8OhMzExg/JryIwZGKDgxF0YNYGe2yGs++jhY563DHlvNYSnGgVcn++2j4/EiTluC9V7+2i1jrCbVHKdbWbo2tIN5gFt4YTDkdWLzm+a1NXPfHTykdm8TpE9IlxzAEDLH0BB1ZSQae+iBQXO6KijxJfwgCVJXn0tBll37nkYokBQk6hVdUFlPfaeeymXkROmnD5mruuGCylC94dVWpFMUcPGbtxt3cuWBKWB+vrJqKy3vs0dnDSS+NZEaaTo2lmNNQYvfIj/mOOO04EARB1l4QhPi8H0EH4Dc3vM+3n/iEb254nzd3NR+xEFU0RpqsQr+82tw+/GIguvbRd2pY9epuPqrt5EC7NWqxMAS4+5WdHOpyRIyjBq2K+k57/7iwpUF2/P3H5w0R5/z8kjLMOrVsIdAn3tsfUdhV7joH223cdn5JxHg5YUx4dPCR9PNwe5cHk6PJ6tH6JyfZSJfdLUV0L5tfxAOLpvP0R3U4vX6pz4KF6lqtbmqPIEvBsX+gjfWz13chIMjKl06lwqBRh0WAr7u4jNPzUxk/5uhj7sDfOGHM8dtYynh/8hiJejVWfH646ekvWPz4x9zy9y9Z/PjH3PT0FzHPK+KN3T287IvjQaNRMX1cKt8oy2H6uNTjcgzD6JZThdHBSV1yEgRBS8Ax/FdRFP/R93GLIAg5fVHDOUBr3+cNwLiQ0/OAw32f58l8rhAj0YpGtPQ6SdRrwqoHB1fDNWohatRFaHTdFbPGSREBTT1OXv78EL+9eiZfNnRLuYxvPreIlh47Oq1GfpsfIjq1itp2G1NyklD3OGSP21LXSV6q8YjRNCdzZX44bQEe7Xi9fnY19dDU4yQn2UhpTlLMA3GKSb4gXbIpNnV3ooUHuh3yVXm7HbGdn5tikm1/brIxpvNVKoELpmTx3NKz+vovsMIdb1mNpofqQt6p/FQT9V12WnqdODw+Kc+vX4TcZGPY+WpVwJFw63klPPj2PkA+mkcVsqC1smoqGQl6mrodPPZeLZfPypNtkwj8oLKYnBQDe5ssssfUtFqlrc8qAXodHhq7HJTlpgxepw0Bil6LD8OtGGGSUV5vxivncLc9ih61x6cATDQH4NHyjI4WQuU1aDMG//3S1gZunjeR9AT5okMGjRqnR74g8NqFpTz4drV0fFOPk6c/quP3185ia10XOrWKzCR9mGMvWERMo1KhUQk8t6W/jsRZE9L5ycuBFGRtVrf0+dcmjqHN6pK9DsDSuYVMy02mcEzA+XcsOnC4vcvDidKcJClH8KPvBHI9/+6amWHP4aWtDXxvbqFUH+X5LYf4yYXyxWhFMfpCcG27LVK+Li7jkXeq6XF6eOTqmfTY3RSkm5mRlxKzTSk3RioRwApDSavFSUlmAjfNnYjD5cWkD6RlbLM6mZg5/HVMtELhphFUYFaxlRVOFU6ac1gIhHc8BewRRXF9yFevAdcDv+z776shn/9NEIT1BArSFQOfiqLoEwTBIgjCWQTSUlwHPHyy2j0akdtmXpBuRCUINPc6KUg3saKymGc/q5eKQRzsCERThBeJK6PT6mLJ7EKpgN3j7+3H7RXDnCTtVidlY5PRa1VMz0siwaBh/VtfcdOciVEmn1qsTg8ZCTo8PpEpOUlR01MEjW2/X6S+00ZLrwub20tBmlky6I93S+aRFP9o3jY43PB6/fxrVxPVfYWR9jT1Ut9p48LSnJiMebVK4I5vTJK2MAVzW6ljXORNMmj5w4eRhQd+vWh6TOcnGDQUpBul8yFQqT0hRiModDIVlttqbGy5rfx+kbf2tAw7WY2W7uKLQ91s2FRDQbqRm+cV8+g71VSV51KQZkRF4Hk88NZX3DSnv0r5S1sbWFU1lS67mz99eJBl84oYl2pk3cVlYYX81l5cRrfNxbL5RagEMGpVmHQq/vDhAZp6nCTp1VKuYQg4ObrsbqpbLVLRogf7IoQGttvr90uT3eXzA/pzw5WnUdtmjdl4jNXYPFlGqaLX4kdWkkFWT8SrOJFRo+bHCyZLqSWCOYeNcSp4k2TUyr53STEWFh1sTmUHoN8vYtIFdKVJp8asCy8o2mV3k2TUkmRQR+jgFZXFePwiBm14QeBkg5pJOUl0WN0srsjj+S0N0pb/Lrsbh8snpQhYe/FUHlg0HVtIrYouuxuX189L2xu5//LpuH0+EvVauhwuls6dyLqNu6UUEysqi/nBc1+i0wj8ti9XfW27PSzNwIZNNSyvLMLjE6Wo4VhRCo1FR6NRsXDaWManm2nudZKdZKAsO4l7L53GQ5v2Sc7cx96r5YZzCjhjQhp5qSaefH9/RGHCoDP/+nMKZMdtr9/P3z9tCJuPTBhj4oLSbBweP+s27mLp3Il0OwKO6do2Kx02Fzq1CpvLh1mvwe3zkW7WS2PskcbI4Zb6RWH0kpOk53vnTsTfp2IEAb537kSyE+NTE+BYMWnVsvMys3ZkOIcVW1nhVEIQxWPfEhfThQVhNvA+sAMIWkx3EXDwPg/kA/XAFaIodvad81PgRsBLIA3Fv/o+rwD+BBgJFKK7RTxKwysqKsQtW7YM8q8aOYQ6T+1uLxqVirtf3YHbK3Ld2QXkpRoRBIGGLjuIMHVsIj5RQCPAZ3VdJBu0ZCbpJQedSoCSrATSzXp2NPbQ4/DySW0bl8/MZ83G8LxfqWYt7VZ3mFH380unoVWJmPQ6tjd04xcDE+Gb5xWTYtLi8vhQqwT+8EEtC6fnYtRpwiYYwUjlP1x/BhPGmHm/ppWGLmfYPU5EUR9N8de2WfnmhvcjjP835KOGjqkBo1FWT8SZtbOhm9p2CykmPZ02D2lmLd12F4VjEinLSznq+dsbutjV2ENTr0uS3ZwkPVPHJjN9XOpRz9/T1E11q42aPtlXCzAxM4HiTDNTco5+//2t3Wyts7DqtRAn5cIyZhUkMjHz6OdDf+T08eS22t9q5VsPR8rqP2+ZMzDCYEjlVO4dW1FZzNMf1TE5K4H/+fpE2iwuMhP1/PH/9vPW7nYMWhV3f2sKY5ONWF0eXF5R0gsVBclcdcZ47n5lh3S9X1w2jeYeJza3D5UApWOTaeyy02n3oBKgODORcal6uh0+eh1u3D4xzAm/qmoqGhU8+HZ/dfqCdKPkbAget+7iMvLTjDR0OdBp1DR128lJMZJk1PC/z3wek06K1dgcbKM09N006dRc+fjHseq1eHLCsjrcoj4GLoKpBSjKTIh5EWyw2d/aza6mfr2n6mtPaY45Zr01mOxs6Gbn4V5+9nq4fVE2NimmcWCwOQYbYETL6sB75yUb+fhgJ1vqOiW77abZhZRkJ2B1+tjT1EthRgJ/+GA//zO3CKvLQ12HPUyGcpL11HU4eHhzYOEv2aAmLUEfpnuDY0GX3c1t55cwMcPMzX/7glSTju+eM54H394Xpn8TDRrMOg02txe1INDjdFPf6cAvQpJeTVFmInaPj30tFl7oczznJBu4oiKPqTlJ7GnqDXNIG7Qqlswu5KkPao9Z/41gx8FJtwGi9c2U7ETe3NVMXqoRrUqFw+NDq1Zh93jITzNhdfmpbbWQnWKiucdBUWYCa17fhdsrctOcCWFOptvOLyEjUY9fFPnpy+HjudXpYVJOEl819ZKXZuaxd2vocXq47fxJPPPRAS6dOS7CAf3clnruXDCFBaXZHOywyb73MvaUwsnllJ5XbT/URas1sJARnBe5fX4yE/SUxzCviTcH27vZ3hhpX5Tnmhk/JiXezTsqxzCvgmOQ1dEmpwojiqhyetJCMERR/OAIN66Mcs7PgZ/LfL4FKBu81o1u/H6RzV+1UN1iDSvm8psrZ2B3+7jr5R0RhtBVp+dj0Khwev3kp5m4+5WdpJp0XHd2AQXpZhBF6jrtPP7fWuaUZKJWwS2VJfz6319Jq/STsxI51GXncI9DKi4Cgeian768gwcXz2DZ3/odJyurpvKXjw4Gin/1teN7c4t47L0a3F6RpXMLyU81YdZr+OWbe7jq9HzUKqjvtGF3+SWDLniPE9niebQto0dKzTHMnChx50QnSh6/D4dH5Ed9BREN2kBBN48/ttxUXp+Ixxe+duTxifhizA3Z0OWk2xZeVfeuCyfT2K1mSs7Rz++0+STHMASLOe7kmRvPYGJMLejPbTV93NGPHUhdh01WVus7bXGdzAxM+SIg8IPnvmRyVgILpuVw458+C3/eXnhnXzv3/HMPS+cWsmFTDTnJBmmb8NmF6fz6rb0smV2IXqNiSnYiXXYXDk+/nPQ6AtFlU3MS2dts4d439nDDOQX4RHB4fBF6au3G3Ty4eEZYu+s6HNicHpbNKyIn2UBdp531/9lHl90d5tD45WXlPDwgR+qRdFKs29QHczv7wHdzeWXRKRENORydNw3ddhq6HGF6ZkVlMQ3ddsaPGfq+73H4+dGL2yMmP3+76cwhbwuA1e3hd/+tkewLUYTf/beG+y4vj0t7grncB8rQ8eRyPxLxlFW5e6/r25Zf1xHIF/yTBZOxurzYXT5u/tvnLJldKB3f+Noubv9GCUatmowEPfVddn7xxl667G4eumoGyytL+OnLgaJi698OHyMf2lTNE9dWYHN5OdBh43fv1rD6olKaehySYzh47MpXd0qO3OXzi9m8t5nLZ+WHvUurLyrFElKgLCfZwLVnFUQURQvq72BUqpz+O5qzXik0Fp1o49ebK+ZQOjaZpc9skZ5l8Jjy3CRu/0YJhZmJbO9LUffbd6q568KpGHUqlg4olr3+P/v47dWnYXP7eGDRdBq6HRSkmfjlm3skuV19USmPvVvD9sZebp5XxPr/fMWdC6ZEtG3D5mpJpicvnxPV9t/T3HvM6UcUFI4XUYAOqzusCOOahaVkjJDI4XarvH3xlyVnMn5MHBsWI8N1XqWgcDIY+vAUhZPOwQ4b2xt6Ioq57G7qlRzDwc82bK7m9gsm8+xn9YxJNPDsZ/Xkp5tYf8V0fvqtKQB4vD7W/XMPAP8zdyL5qUb0GhXddjfbG3t59J0anny/FoC8VBN+UT4f2J7m3rB7r9u4mzklmVI7qspzWbNxF1XluTT1ONmwqYa7X92JWa/mzgVT+NeOJpp7nbT0usKuFXqPug7bcRWIOdKWUQCTTiNb6MKkGxlbYoaSEy3O4vbKF3Rze2O7f1OPkxe3NlCUmci4FCPFmYm8uLU/QuhoJBu13PuvvWH3v/dfe0kyaGM6v8UiX1Cu1RJbQbkTxaBTyRdliUM04kBCi7FkJAbySH539gTZ531jXwVzp8cvbR9t6nHy6Ds1bNhUQ4/DQ2N3oE/dPj9ev8iq13azYVMNj2wOHLPy1V1YXT4aOu34/HD9OQWU5aXg8PgichgH77WnuZfLZvanuTdoVYxNMVGWm8xPX9nJhk2BqOKgQ+OymYG8xT/+x3ZunD2RnGQDOckGbp5XxE1zCmmzumR10tF0zrEeFwsD302/iKysjLbt0MOxYFRLr0u24FpL79DoiYG0RtFbbRZ3XNrTbfdKRc8e2VzDo+/UUNfhoMce40AwyAQdgG8sn8OzS8/kjeVzTorDNp6yKnfvla/upKo8F4BUkw67x8ezn9Vjdfm4aU4hk7MTSTXpgIB+trm8TB2bxN2vhuvKXYd7pcKe0XLG7mnupdPuRhDgzMIM/v5JHZOzk2SPDV5jw+ZqrjunkDWvh48ha17fRU5f/n6Ay2bmRRQ6fmhTNT+/pIwlswulFBMD9V+shQiVQmPytPQ6STXpuHleEcvmB/5STTqae51oVIL0LEOPmTspk/2tNpb97XM2bAq8+1vqeljx3Bf0RCmWbXP7uePF7Sz7+xdYnF5uff5L6joc0vdrXt/F984NjM9qVaCo3d4o84igbLVanFLKkFAMWhX7WizH9U76/SK1bVY+2t9ObZv1uOYrCqceTrdf1k52xlhoO960RbMvYiy0HW+G87xKQWGwiU/yNoVj4li3GLb0OmUdtNGcttWtFq6syCfBoGbZvGKue+pTaWXyJwsmMyZRz13fnIzF6eWOF7dJ391zSRk5yQa67G5WVk3l52/s4affmhJRrAT6cwYPvHcw12KoQRZajNzp8fPloR5++24NS+cWkplo4GCHTXJqDLzHF4e6cXj8xzxpO1rOOLfPF1HoYvn8YjwjpVTsEHKiuRmjOyliMyLGJhtYNCuPmlaLtF170aw8xibH5vDqjFIIKVhA5Wikm3WyspRm1sV0/omiV6vD8kEGI6QMccodGo1gJF6XzSPb3502t6RfVEIg8uuymXkIQuCZZiQEdjYEf2e0KNhkgxqzQctfP63nyop8KUJ5RWVRVD0VzE8d7Lufv7GHu745JepEMvj/e5t7ue7sAkQRSVc8+X5tROSf3y/i9Ykx5akczHyWA99NuQJRJyMaMt4EHRRB+YHAb49nhLQtSvVue6yrYIOMSaeWlTOjLj6Tn+HWHuh3AJ5MmYmnrEYbu4PtuGxmHs9+FtCjobZgMAIXQK1SsbWuS7pOUG8PXIyTe7YTMxL43bvVnFmYIeVz94vyejKYWM7p8eOI8i7VdfQXKIvmkHZ5/VLUqpz+O9ULEZ4oOckGbvja+LD6JbedX0J2koEehxeDVkWCXh02lgd3FqaadGGL+k6PH3MUvZCgV0ufRXvWe5stXHd2ASXZCWw71BN1HhEsvB2MAL/30mkROy6f+biOcyamnyrpRxTiTLtVfl7UPkKcq9EK0iXoR4YbaqTMqxQUBgNlyWOYE2vUQujxJp2aydmJEatcQadtKEFnyIbN1agFQcrnCYGVfJfPz5I/b2Fvs5W1A9I43P3KTn5+SRlL5xbS6/DQ1OOk0+ZifLo5oDT77hXM/bVxe2PEvQ0aFTfPK2J5ZRGTshIpSDcSmk3aoFXh8vpxevyUZCUyPt1MQZqZ17c1snx++D1WVk3lhS0NxxVlE3RUhV4vdJKQbtbz3JZ6lswuZNn8IqkoX5p5ZGzpGUqiRVrE6szKSdbLnp+dFFtfiyLY3IGUAY9sruH379Vic/uINb16mkkne/9UY2zOXZNOzeqLSsNkafVFpZiGqPBCeoIOs07N0rkBWV06txCzTk16wtA4p2MhuOCVatKSlyovL4e7HVxRkcet55WQl2zgurMLeOqD/mda1+lg057mo0bBTs1NZt3GQIHB0Mix57cEitqFPqfl84vZuL2RM8ansfJbU/j9tbMQBLh8Vh56jXzkQFCuDFoVRq2a0rFJOL2BqLqcZINs5N/BDht3v7ojQofdd3l5hGP2aLrpWBj4bjb1OHluSz3PLT3rpEZDxpuggyIoP0++X8sNXxtPdlL8IqQL0syy8pSfFh/HfIJeEzFur6gsjtvkzaRTy7ZntO/WiaesRhu7gzpOEIjQo8EI3Csq8rhsZh7rNu6WdHEwlcNTH9RyqNshXTu4KDVQ967duIvrzgmkETFoVdx76TQe/+9+1l1cFnHsPz5vkP49NsXYV9C0Pzq1IN1IYUaCZLfJ2cQGrYrizIQjRoMP5s6NUxGvT5Qcw9CfBsLrE3H7fPz80mmIIhG7KNZt3M0VFXlh1zJoVXhFUVYvBOYZU1g2v38uMfBcnz9wnwNtNmbmp8rOI9ZdXEayQc0T11aQn2pCpRKYmZ8i2VPBKPMuu/uYF2iH4w4WhZFBVpL8vChzhKSVSDTIj+eJI2Q812tVsvMqvVZxoymMPkbGks0pzLFELYSuSqeadBGrXNPykvnV5eX86KXtESvgTo+f5t7wlclrzsyXjLpoK/HtVhcGjVqKGkkz6bn/rb18f24hv716Jl82dKNTq0jQq/je14ukrX/B6AG9WsUj7/RXR1+zsJQXttQDhLXPoFUxJTsJlUpgwhgzdy6Ywn1v7pHyj07OTuKxd/uLSB1rlM3RcsaNTzeH5ScbrRF2g8GJ5mY06uRXaI362IwIq9sru1378WtnxXS+ze2RjRK3ezwxne/1e0kzaaTq6madBq0avGJsOZNPlPw0M2NTrbTb+iOdx6Ya4+Z0GsjA6JlfXloq+7wBcpON/GZTNdecmc8j79SEPdO7Xt7B+sUzaOwOVKWXi4Jdd3EZ1c0WWR3W1OPk2U/reeTqmVJew+e2BKLifvrKDr43t4hVr+6UchY+cEU5qy8qDdNhqy8q5e+f1Em7LFw+v5QPMVR/NfU4w3RSS6+Tug4Hz3xcF5ZTdWyKIcIxO5j5LOXezTsXTGFabsqocwiHEs1BMX9SZtzaNGGMvJ6cMCY+72mv041JG5j8BAvGmLRqep2x6b3BxqhVMzbFENaesSkGDCOkuvnxEk9ZldMP91xSxsObq4FAgIEYxRYszkxEFEWcHj8vbW3g1vNKsLm9kj4O1c/BRan1i2dQ02rF5fVLetLp9lKak8Qfv3s6Xp+feZMzEfHz4OIZHOqyMzEjgbUbd0kpIFZUFtNucbBsXnFYEePVF5Xywmf1VJXnIghwuMseob/vu6xcSgERzV4czJ0bpyL1XXZZeTnUZacg3UxTd+C/csfkp5mkvjdoVdx6XgndVheZSfowvZCg11DdYuVXIUXqVl9UymP/rZHG79C5Tq/Ty4QxJm47fxLr//OVNI+YMS6F375TzZa6nrCo3vw0M5Ozk07Y/j/RXXUKpy6+vkWRgXayn5GRlqTb4SZBr4l4b7vjZF8cKw5PZICR2Fe7REFhtKE4h4c5x2JMhDqSm3qcPP1RHUvnFjItN5nCMQlMGGPG7xfJSNTzUW0HPj9hedaMWjUF6UbJmB5osMkZyOPSTTza55Q1aFX4RJG6Dgf13S5Wb9wjHX/7BSW8sPWQ5AgxaFSMTzez/NkvwiZBq1/bxQOLpvOds0SaehxSsZDQSbPkLMlOpK7DxheHulm3cXdY1enjMdyPtGVUKTgSOyfaV70OL09/FO40e/qjOmaMS4npfKfHJ/vODPwsGmadVoo2Ct7/uS313H/59JjO9/tVrHhuW8S78syNZ8R0/omiUgnMn5RF4ZiEYSmrAxe8GnpcvLS1IeJ5X1GRR31XIGdgRoI+yjbRQH7gR9+pkRwODyyajtPrIztZj+iHbq2aFZVF6Poif0Ovs6/Vis8vMiU7iT3NvVSV50o6cc3GXSyZXcijfU7pfS1WXv2yMaydj/23hp9cOIUdjb3YPb6IRYlgcZunPqgN00nBHObBHMoQkJELpso7gAZrO/upqseO5KAoykqMS5uG27PQazX84cMD0vjv88MfPjzALy+LTwG4XqeH9f/ZF9ae9f/Zxy8vmxaX9gwV8ZRVOZnMTzUxMz+VVouT7CQDdR12WVtwb7OFWfkpkl7ziyK5Kf2pJJp6nNJiWH6aEZNOw319BcNCr5OTYuRAm5VbQxxxt51fAn4Ym2xkf6uFi2fk4hfDx4qBxUXXvL5LKmQadA7+/ZNwuyI3NXIxbiBDVYhwtGLWRW4nL0g3YtZp+lLlmVCr5OcXzT1O7l80nepWCz4//OnDgwD8+MJJ+PxIesHqigwIWPP6Lp64toLP6joj5joz81Op77STl2Lk4asChexMOjXLn/0iLE9xaCDOYOhqZaFB4XiJNi8qGiGLCnqthic/qA0bz5/8oDZu9sWxolOrZe2jDVedFu+mKSgMOopzeJhzLMbEQEdysKjbs0vPlKppqlQCpxek0WpxcWdIBPGKymL+sfUQ35tbxJqNgciKR64+Tbq3XFTemoWltPY4WHdxGa0WF/Wddhq6AhOHgVF6Tq9fKi4TZNl8+RyhdreXv3xcx5ySTC6flYdKgKk5iRHVoQszEhifbsbh6c8HezIN96HINzhaOJG+ykoK5JkNlRWDVkVWjNtqMxL1su/MmBjTKnTZPVxZkR8ROdzliG2FO1ouUdsQ5hIdzrIqt+Al97xPy0+lw+Jg3SVlOD0+2Wc6MD/wzecWkZagpbbVRUOnyM9CosTuunAyt55XIlW+N2hV/PzSadz7xm4ump7LI5trwtoUjDYO4heJ0GEAapXAnOJ07G75RQm1igidFM8c5sNZNk4Wcg4Kg1aFSRdfE2g4PQu7yyur9+KVA7nH4ZV933oc8WnPUBFvWZWTydB/j00yyuZgfW5LPbOL0li7sJRVr+3C4xM51OUI+y1NPU6e+qCWpXMLeWFLQ0Se2TULS2npsUcUhF3/n308c+MZdDs89Lp8Ebo6Wj2N3GQjyyuLOLswnR//Yzt1HQ62N/YCgT69fGZuTP0xnBZxRhpZSfqwiMeCdCPf+3oR1/2xv7bJqqop3HNJGXe/0h/5vbJqKo+/tx+3V+TaswrC9JJOrZbyREP0ucQXh7rJSzGx6rX+695zSRmPbN4nRQevqCymOCsg26ELFcFrBANxBkNXKwsNCsdLslErayenmGIrlB1vhpt9caz4RT8/qCzhQF/NI40KflBZghhrvkIFhRGE4hwe5hyLMRGrI1mjUXFR+Vim5SbTanGSkWDgQIcVh8cnOYYBGrrsklEXjMp7cPEMBAEOtNvotLl59rN61l1cRn2nHb8I/97ZzPL5xbi88s6c0H9HK1xX1xkw4INGPMA5E9MZP0aJ6D0VyE81RUwU7rmkjPxUU0znCyLcdeFkaYIZdAzGmhkq1aRl895mfrVoOg6XF5New58/rKVi/JSYzk/Ua2XlOkE/Moy4k81APfXS1oaI7XL3XjqNxk47OSlG1m7chdsrsqpqqpT3PNQh8cMLJrNsflFg23mqEbvbR4pJz+0vbgtzMNz7r708ed0sHr92Fj0OD0lGLT12Fz9eMAWL08OKyiKe39IQtgMh1O6Lpq+SDFpOH5/GjsYe2e8rJ2dGpG0IzWEeGp2+oCz7ZHb9KUt2sl42JUh28sjI1zcUJBvl9d7pMeq9wWZMgnxhzzFDVNgzXgx3WdXp1FSMT4lIx3PV6flUt1gZl27igUXTSTNr+cnLOyIWwe5fVI5GpeIH5xWTl2rkt1efht3jJ9mg5UCHFb1aLevo84kiEzMS2CmjZ6Pp5vquwOLCq182ctv5k8ICIo7FKTecFnFGGvlpZoqzEqTt5JOzEiPG5rUb9/Do1afx26tPQ6NWYXP7aO5xcOM5E/jFm3t55uPALsiJGQmkmXU89PZXrKyayro+eyDa8/f6/SSbtDz2nVlsb+hh/Bgzv35rb1h08EObqlk6t5DKyVknPapXma8oHC+ZiXru+MYk7g9JnXLHNyaRMUJyDg83++JY0apVtFld0g6V4I6W4MKSgsJoQnEOD3NiNSb8fhFRhAf6tmA9v6VBSscgZwAPNHYnjDGjEoQww+jPH9bxvbmFYTmCXF4ff/n4IPMnZ/PmziaurMiPyLH55s4mLpyWI0WQOD1+Xt/WGDHhGT/GHDHYhea3C3I0A00x3EcX9V12nv20LsKImJmfGtMzbup18eLWhsD5bi8mnYYn3ttPZoyRx2a9wOKKfH4UUo197cJSEvSxGfAWl1s2KtTqGhm5tU4249PNPHL1aWxvCFQLVwswdWwi/7wloONcXj+rX9sZkSvwP7uaZR0Sv3hjD112NyurplLbZsXu9pFulk9D0djtZHWfTgoWS9qwuX8RYkVlsZTKZnVVKY+915/yoSQrkdvOLwmrur6ispjMRD1v7mrmvjf3RDz39YtnyObzVXKYDy1eH7y0tT5Cp5wxPi3eTRs2+EQfVwzQe2sWluInPjn1rC5PRKT/reeVYB0hkUbHy0iQ1bwUMwfabZRkJmJzebnjG5PRa1R0WV0c7naybuNufnBeMVdW5EuLYGoVlOcl02F1s/q18LoXeakGuh0efvduLZfPyovqpBufbmZaXnLEYmJGop41C0sl3R46bkAgIjQ3xcAbilNuyBmY5iraDpv6DjsGrUYKUAkuitx14WTabW6mZCfxu3dr6HF6+P65RbzQl7N6b3MvBq1admw2adXUtVsxaNUUZSZgc3m5aHouL23tXwR2evz4RfD4fEMS1avMVxSOh7FJRvJSjYFaJi4vZoMGrVpgbJLx6CcPA4abfXGs2Fw+2VoA0/OGJl2ggsJQojiHRwBHMyYGFngKRt5lJOhINunYWt9JulkvGcN+v8jBDhstvU5ykg34/IECbunmyO34Lq+PGXkptFlddNrcqFQC/zO3iEc3VzOnJDOianUwx+ZDm6q57bxi1l8xnd3NFsw6NdNyk3jsO7No7XXSanHxm7f38YPzSrj9ghK6HV5EEZ79tI4VlSVhWxYVp8mpRYfNxflTc8KMiFvPK6HT5orJoE4za1l8+jhqWi2S83Hx6eNIjXH7ld0lSosaEJDrVa/tijlncKJeJxsV+usrZsR0/mjG7xep77TR6/CGrcDfd3k5Jp0LnVolbf+Ffp2yorIYUYR1G3dRVZ6LWgWrqkpJM2vx+UUcHj+PbK7h8ll5qAXoEF1huiwn2cAVFXloVAIPLp7BL9/cQ1V5boT+emhTNfcvms7eZgsvfR54Zh6fn6ykQO7Nd6tbwxbLirMSEAQk3RvMqalWIRsxHESJIBpaOu0u5k/ODtMpy+cX02V3AfGbpHu9fnY19dDU4yQn2UhpThIaTXyqX6tQS8416K8B8PQQ5UofSKrJwN8+3R2mR//2ad2oz/E31LJ6vDJoc/mlCFCDVsUvLyun2+Fh/dv9OlWjgtsvmIzd7aXN4qK6xSqbl/23V89kW0M3t3+jhI1fHo5YZLvv8nJJP86flEVRRgIz81PpdXpIMWoZk6DH6fXywKLpiEB1q0XKMQsB53KaWa845eJE6Bymts2KQasi1aTjspl5CELARivLTebaP3waJhtrXt/F766ZhUqAtSF1RX77bg33XV5Ol81NSWYite021AI88u3T6HZ40GvUNHTZ+cOHB1i7sJTDPa6w+VFooViDVoVKgDSznpn5acqYrDAsqW6zUNdhD1sAue38EqpTLJTmpsS7eUdluNkXx4rN7Q3TWRDY9ThS0mIoKBwLinN4FDCwwJPT4+eul3dIhZCC26/vXDCFC6Zk8daeFm57/ktSTbqwnG8F6UbWXlzGqld3St8FDf2gQfXrt77i4hm5LCjLwd9XmTqUYI7NFZXFmPQa1v0zENV33+XlGDRqvveXrWHn/OQfO6SiT0F+fKFRifA4hdGrVVK0GARk6sG39/H80rNiOt+gVWNxhjsfV1QWY9DEVuW+w+aWletOmzum860u+ZzFtlM8cji4iLW3uTeieNCdL20P01ehE3unJ1C1/IcvBBwRoQXcls4tJCfJyGPvBQrSvb6tkR+eP4luu1uKLhuo54I7FHRqlexzPtBu46kPalm/eAYz81PDdI9cob9PDnSE5dQMtu+cielH1FtKBNHQoVOrZBcyn4tRp5wMvF4/r2xrjEifc8n03Lg4iLvs8nqv2x4fvVWak8Qt84sj+qc0Jzku7RkqhlJWj1cG5WzOH/9jO/cvmi7tyhAQWP92eCRndrJBVsY+P9TNk+/XsqKymGvOLuCxd2v4zZUzsLt9HO4ORP0GdalKJTB+TEJEmjG/X+RAu4P73tzDlRX5Q1KHQuHYCe4cCl0oMGhVTBiTICsbXxzqYnJ2UtjndR0O2i3usPQU0G8TBIsQrqgsxuURpR2LwWuGFooN5hwOzjOUMVlhONLj8MhGrpaNrYhzy2Kj2+GRfb97YqzlEm8mpJsj5hErKouVcUVhVKI4h0cBcgWenB6/VBRuw+Zq1l8xHYvTwycHOmjotEkrYKFRHHUdDrptLpbOLaQ4M5E7BuQFCxpUfhE2bK7m8WtnyW7/O6swnZoWCxanlysq8qgoSOOcwnQ+q+uM2k7oj+7rdXpJM+s5Y/yRnSsKo5N2q7yToiNG56zFGVm5+qFN1UzLjc2pkGaWz3WZGmOuS51WLRs5PFKq8p4sgg6Fm+YUHlVfhS4YGbSqqAWH/CKs2biLXy2azr4WC6II3Q43WcmBrXa/vXomCPD9v34eJg93v7KTp288I4r+SmPh9Dnkp0UuSslNHpUK5MOfaFuZ7e74bWnc1dQjOeWC7bn7lZ0UZyYwfVzqkLcn0SifKz3REB8zUaNRccn0XIozE2jucZKdbKA0JzlukdVDxVDK6vHKYDSb0+H2YtCquGxmXsQC70ObqvnTDafLypgo9h/zwKLp/PCCyXTY3DT1OHhh6yG+OS3nqL9F2o2RnUinzcVzS8/C7vaRlaQEGAwnVCqBCekJLPvbF2HycaDdGrXo7N7mXi6bmRdmE9hc8oV/izMTue+yaZj0gXRi15xVIHtc6dhE/nzDGWQl6WXHegWF4USvU17eLc6RkZbBoFHLvt8GbWxBO/HGLyI7r7xgqlInRGH0oTiHRwHRnBPBYkqpJh1+EQ51OTjc7aA4K5FfXFZGhzVyJe+PH9axbH4R1a2WqFHBPn/g/3c39UZs/1tZNZWcJAPZSYaIyN9o7VQJAcfwwFW59YtnsKA0WzHaRiChqUuOdXJm0p9YtXZLVCMqtu0/drdHNmdwrNuH3B6fbOSw2zsyjLiTRahD4Uj6Kqhngp8vn19MslFeJoJOhX0tFh7ZHIgWWjK7kFaLmyffD0QnR6tkbnXJP+cv67vISzOTnxZbRIBSgXz4E23syYoxD/nJoKnHKbtNsbnHyfRxQ98eu8sr+z44PPHbNqnRqJg+LjUu/REvhlJWj0UGQ8d0k05eH6eadKyoLMbhkXdwd9s9/OyiUn72unxuYKfHj9Pr46PaDin681iK0cot3p2ILaJwcmi1RC4uPL+lIaIQcXDXYzCVFPTbBO02l6wMVrdawiKH81KNssdNzk5SIoQVRgxmnbxz1aQbGYulWrUQkSt+RWUx2hGii+V0ltPjp83qZGKmokcURhcnzTksCMIfgCqgVRTFsr7PpgOPEUicdhC4RhTFXkEQtMCTwMy+Nj0tiuIv+s6ZBfwJMAJvACtEMbSGvIKccyJocAedrqG54YLbqNoszojBpsvuptfhoTgzUfouJ9nAZTPzUKvg9II07v/3XgxaFXa3jxe2NEgRkioBxqebaLe5SJeJ/JUrRDUtL5mijAS+NnEM1/8xPN/Ybc9/yeTlcxRDf4QhlwP7WBz9CXq1bLV2sz62FeaMRB0F6UaqynOlCe/r2xoZkxBb5G+qycBzW3ZHRP7Gmusy1aRn897qsIJ4f/6wlq8Vpcd0PoxOOQ86PXY1dIcVqzRoVayuKuXvnwYcBAatiqLMRJbNL5L6fmLm1AjH1U8WTMbi8rK8sojizEQK0o1cdXo+T38UuE7w+OA1BxrV6Wa97HOuKs9lvYzugejPRckfPLwZjg78vFSj7DbF3JT4FJgZjtXER6MePBpDKauxyuDAMb0g3RjhyFtRWczDm6u5cFoOc4rHBM7rs9Rf2hookLy7qZfMBB2/WjQdURRRCwKPv7c/LDdwgl6DsS+aLBjJHGsx2oHEYoucijIWb+QWQHQagSSjlgcXz2BPc69UdPbqMwr426d1/PCCySybX8SkrEQeeGsvbq8YZhMUpBv58YIpVLdaWTa/iJe2NvDQpmqe/Z8z+cWl0/hJSB2T+y4vp8PmAjjm563Iy8hlJD+7ZKNWdl6UZIytlkq8MWrVZCTqwgrqOT3eERM5rOwQVDiVOJmRw38CHgGeDvnsSeB2URT/KwjCjcAdwErgCkAviuI0QRBMwG5BEP4uiuJB4HfAUuBjAs7hBcC/TmK7RxyhzomWXicen8jKV3fQ1ONkeWWR7FaI3149k+njUrh/UTl3vNhfOfq280v44/8dZFpuAvdcMo2HN++LiIJcUVnM/6QacbgDaSOCjt7irEQe/M9XbKnrCTPCIbClvMPmwu7yheWCXb94BvlpZpp65FflWi1OaVJwok5HhaFBLh+hnKM/Gj0OD4/9tybMaffYf2v4xaXTYrq/ViVw87xiVr3aP3Fde3EZOnVsMlKak8SyecWsDDl/3cWx57r0iX4unxVelXf1RaX4Y1zTGq1yHnR6+P0i97+1N/z5vldDVXku+1qt3HNJGb9+ay91HQ7JCWzQqMhNMfDkdRV02tw09zhwev088k6N1Ef3XjoNs17DmotLqe+w4fT4eeLaCg532bjnkmnc/Ur/5PCeS8qYkpXEnQumyC6qBXXP+HRzWPHO3U2WqM9FyVU4fBmODny/KMqOzceyiDSYCILI4tMLwvTW2ovLUKvisxY/WvXg0RhKWY0mg6ePT6O2zSrdd+CYXtfh4OG+PMgOj4+MBAMHOqw8+5kHs05NXYc9Iue/Savmpc8buPKM8LFxRWUxbVY3XXY3y+cX8+T7+7nxa4Usm18EBBzLA3VxrI6do9kip6qMxZv8VBP3XV7OnS/1zz1+trCM//eXrWGR7BfPyEVAZPn8Ep7+sJYtdT0UpBv53teLWPP6Lp75uI6lcwuZmpOEze3jVpmxvNXqprnXyZqLSjEbNKQYNfzm7X0R85RYnrciLyMXv19k81ctEcFJ8ydljYhnZ3N7ZedFIyVd3cQMI/tarWGBausuLqMoIz6L4cfKcAwwUFA4WZw057Aoiu8JgjB+wMeTgPf6/v8/wL8JOIdFwCwIgoZAhLAb6BUEIQdIEkXxIwBBEJ4GLuEUdg5HW/kMOifGp5t5v6aVn18yjXarC5fXL+t0DRYAWX1RKY9fO5N2q4eWXicFaSZ+d81pHGi385tN+/jhBZMlQx4CKSocHh9atYqkJCOPvrtfcuLcdn4Jjd0u6R63Pf8lU1fMoabNyvaGHnKTjRzucZBq0knO4KChHsuq3Ik6HRWGhmj5CEMd/UfC4vRS1+EIK1IIgZxbMSEgOYaD91716k6eW3pmbOcDOSk6/vjd02mzuMhI1OMTY08J4fMTUQBlzeu7+MuS2O4/WuU86PR4Y0eT7PPNTzOydG4heo2K7549ni6Hh/K8ZOo67PxvXyFLg1bFA1dMZ1yaWZoIQn8Rzieuq6Cuw8YzH9dRVZ7LZ3WdTMlO4uUv6sPyEj+8uZqZ+aksKM0md+lZbNrbis8Pb+5sknZJGLUaNn/VIuVGXF5ZFFFIbzQ8l1OF4ebAb46yINrc46I8b+jbI/oFHn2nWpp8Ajz6TjW/XjR96BvD6NWDsTBUshpNBg922PjOU59Iji+5Md3tFXF7A7mQ260uJmUncOc3JiMIQoRufmhTNcvmFXHu5EzWbdwd5gB0enzce1kZFqePw10OlsyeyC/f3CPZlSsqi8lJNhyXU+5otsipLGODhdvtY/vhHpp7neQkGZg2NhmdLno0oN8v8m51K4e7HZLD1qBVUd0cSGUXWtQV4L7LprFh8z5umV/MhWUe3D4/Y1P0rL9iOiqVwJgEHR1WDz/tiwyG/toFKyqLabO4IiLjK6dks6Wu55iftyIvI5f6ThvNfTsUgjT3OKnvtEUUtxyORJsXWZwjo6Db3hYbjwywLx55p5oJY0xUjB/+0bfDMcBAQeFkMdQ5h3cCC4FXCUQLB7OavQhcDDQBJuBWURQ7BUGoABpCzm8AcoeuucOLI61aQ8Bwqeuw4fT6OdRhYf3b1dw0p1A+CbwmkJuzqcdBfpqRgnQDmYl6mnudpPp0/PWTg1SV5+IIKfqQk2zg2rMKZLdxuX1+/vpJXVjRiFSTjjaLi267BwH4zaZqKTrkmY/rJAdxq8XJGePTj7oqd6JOR4Wh4US334xJkC8Ilx5jQbiWXrdsHsXW3tgK2lW39dLY5WJ1SNqDNQtLqTb3MiUn5ajnd9pcsnLaGWNBvdEs54Hc43rZ51vfGTB8DVoVT1xXwc7GHpxuP/f/+6uwydjtL2zj11dMl+2jzw52UpBukiKLgs9vZdVUuu0uRBEEAS6ankunzcX4dDMJei0lmYk0dNm5fGYev3hzL06Pn8ffC1QyDy5mRSuKF3wuI3nL4qnAcHs+aWb59yAtRj032PS6PNx4zgQ67G4psurGcyZgccVn8jma9eDRGCpZHZMgL4NZSQacHj/3vbmH3BQDDo+PFZVFPL+lgaaewC6KG742nmv/8KmkY399xXQyEvQc6Nu1ESSYliwrKWBjnj0hjfNKs1m3cXdYBFmXzcWfP6qjy+7m1vNK+NOHB2nqcfLQpmrOKUw/Lqfc0WyRU1nGBgO328ebe5qpabXiF6G6xUJjj4MFU7KjOojrO21Ut1gjHLaFGQmyz6rN6qKuw8Hdr+zkiesq+ORAJ5/XdXPOxDTMOi07DvfSYXXJyty4VBPVrZawgJSHNlVzf8iC17E8b0VeRi6dNjcWpzdiR0OXzc34MfFu3dFJMcnPi1JM8bEXjpUuu7x90WUfGc7tUJTEpgqjnaF2Dt8IbBAEYRXwGoEIYYAzAB8wFkgF3hcE4W1AzhqO+loKgrCUQAoK8vPzB7HZQ8PRJgTRVq2nrpgTsd15ZdVUSjITyE818OT1FTR2OaTcp+dPzcGgUfHIO3tJ7RtYpuYkIYpwuNtJu8XFredPornXRU6II+eymXmSYzgn2cCVFfkR27jy0oyU5yZx4bQckozasMlD0Cm8YXNg9TDoCMpMNMS0Kjeacv6MdFk9EtFyS8e6/cbl9fLQldPx+JByU2lV4PbFFr07JkEnm0cxPcacwxanT3IMQ+A9W/3aLp6+8YyYzs9Kki+AkpWkj/H84SPnJ0NOp+UkyxaeCc2RrhKgLDcZq9PLb66cwW/fqWF7Yy85yQauOTOfhChFC3VqVdiWZgg8v3Ubd/O7a2Zy7xt7pXtOzk7k5S8a+WlIuolQZ3BwIhnUVcF7hC6WXVGRh93t42C7NUIH33d5OWNTDKSb9XF3RJ4KHElWh+OWUr/oZ3XVFJp6XVKbspP0+EX/0U8+CaQYdXzlsUZMnpON8Zl8Dic9ONgMJ1mVKxLk9PjISTZw89cncqjTgc3lZUpOEr+8rIxtDb0UZpi5/997w3aUddndfNViCatXUZ6bxJVn5Ic5gu+5pIyHN4enslj56k6Wzi3k2rMKeObjOv72aR33LyqnsctBu81Fhz1ywTUYfHAkB/rRtgKPZhkbLI4kq7ube2nucYbpjNvOL2F3cy8z8lNlr9fS65JNZfLU9RX87pqZfHGoG78YqBNx1en5mLRq5pWM4YqKcTjcPmYXpdNlc+PyinzV3MVr2xr5f+cWh9VICQ1iMWhVYYsNwfsG05a8vq0x5uetyMvw5kiyanf7ZOVu2nUVQ97O48Hh9kYU8/zZRaVxLRh7LIwx66hpjbQvxsRpMfxYGcyUMqN5/q8wOhhS57AoinuBCwAEQSgBvtX31dXAm6IoeoBWQRD+D6gA3gdCN1jmAYePcP3HgccBKioqRtTajpziuffSaczMTyE/LWD0Rlu1bux2RDiN123czePXzqSx28VNf94iXXPtwlLGpRv4sr6X759bRHFmAk99sB+DRh2RV/jpj+rQaQQpCX5gC2DgHqGO4uA9N2yu5vFrZ3Hj7Ak09TilCUHo90FHiyAg/Ua728tnBzskJ0q0FfjRlPNnJMtqLLg8YpgR8OsrZsR8bppZT2O3JSJncH56bBXLAVkj8G83xZbWocPqPqHI39KcJH5+6TRpm6NBq+Lnl06LOWfxcJLzkyGnBoOG08alBApTuL302N1o1Sru/tYUSS/sOtzL+v/sCzOC03c2cfqEdDZsribVpOO280vCjgnmtXR45FPpfHGoO0wm9rVYIpzIA53BTo8/LPo86EhJNYUvQMilnLjzpe3cv2g6H1S3x90ReSpwJFkNRqsNnJgUZSTEcUupiEatDmvTuovLOML690kl2uT5yThNnk90kXE4Mxxk1e8Xaeh28PRHdWF5LJ/+qI4fVBbz/75eiA8hopjx3z+tj9gBtnTOBPx91ecOtNt48MoZPPX+fm6cPTHCNr37lZ1hOjb4uV+EDZuruf2CEtxekZue7rdb7710GgXpRuo6HADSImKwiHG0iXpo0EGnzYVWHSikfLDDxvh086iWscHiSLJqdXmlMRgCz3H9f/bx5HUVssEuEIjglBufm3qcYQvG91xSRmaiDq9P5JKZeTR02RERePDtfWH68nvnFrF24y6pOJ3c3OTBt/fx2HdmYXF6aeq2Y3O6eWRzjXSf/NTYbMvhZJspRHI0WZWTO5sr9pRx8STJoKXH4ebxa2fRafOQZtbSbXeRpB8ZBensHnn7ovz6keGcH8yUMqN9/q8w8hlS57AgCJmiKLYKgqAC7gYe6/uqHpgvCMJfCKSVOAv4jSiKTYIgWARBOAv4BLgOeHgo2zxUyCmeu17ewdK5hUzOTmJBaXbUVeuGLofsoAdCRO7TR9+tYdm88EiRUGMneFyok+Sx/9bwxLUV9Dg90v1DHcWh99xS19VXlVQv+33Q+TMrPwXV3ELu//dX0kTjuS313LlgStSVOCXnz8jgQLuNH74QLk8/fOFLJmfPYWJmLDmHfbI5g2ON3G23yqd1aLfG5txNNMhHpSboY1eXOrXA0rmF+EVQCcRcDA9ODTlvtbjY22Lh4/1tXHv2eA53O/nhC9uiOlp/9voufn/tLP73ma3SRNLnF6U+Djo1uuxunri2Qvb5+QYEZEZLEyGEdLNBqyLY7V12N8VZCfzzljm0W12SY+JI1/qqxcKT79cOA0fkqU1Lr4tnP6sPy3f37Gf1zMxPjd8zEVVS0Uvoj6B8+obY9NxgY3PLT57tcZw8u71iRAHb0c5QyerBDhv7W6102d1hjlqDVkWSUUuiwSg5aCHSLgxd7C/KSmBnY2/Ys3rk6plsb+iWlSm1KrwtBq0KsU+HZicbuf2FbWH3vevlHTy4eIa0U+2KirwIR0O0ibpKJTA+3cze5shiohdMyTolZWywiKoz3D7ZKLupOYl02lxR0krZw57nw5urWTp3ohRkImcXrHx1Jw8smk5dh4NnPg4scuSnGmXb1GZxsfLVnayoLMag01Cem8T2xl7ufmUnM/NTY3LwnAq22WhlbIr8jr6c5Nh29MUbvyhic4v86KX++hvHUug63ox053y04LyWXiWljMLoQ3X0Q44PQRD+DnwETBIEoUEQhCXAtwVB2AfsJRAB/Me+wx8FEgjkJP4M+KMoitv7vvt/wJNADbCfUVqMLpri8Ytw2/NfSpEO6xfPwKANPLZgJEe71SV9FsSgVdFp84RdMyfZwA8vmMyhLjs3zSkkJzmQV25vc+8RnSR1HQ66HR5+/s89LJ9fHHb/gff0+QNRm1mJBtnvVQKsrJrKz17fxQtbGrhsZh43zSnE5fVx1en50m+NRrBQy1mFYyjMSFCMsmFIXadNVp7qO6M/11Bae12kmnTcPK+IZfMDf6kmHa0WV0znJxq0srKXaIjNuWvSqQMTiAHvmekIRVZC2dXUwx0vbmfDphoe2VzDhk013PHidnY19cR0Pox+Oc9KMvD6tkZunD2R/W22sIl+NEdrryPcuLS5fVIfP/pOjbRldE9Tj6SncpINLK8s4r7Ly0nUq8lJ7t/+qRbkddjkrERykg3SdlSjVs3vvzOTN5bPYf6kLCZmJuAXxYg2yl0r6PB4aFM1Lb2xya/C4OP2+bjxnAmSUyqY784TY6qak0GLRX4RqyVGPTfYBFO1hGLQqjAbYtN7g020SJ0j2QejgaGS1ZZeJ89vaYiw6VZVTeWXb+6h2+45ol0Y6uQVxcjdOtsbAukBZHVsdlLYPZfPL+YfnzcEPoui/6tbrSyZXciy+UXkpsg7AFst4QWngkSTpV1NPaekjA0WCTp5nWHUqWX7taXXxZhEA7edXxL2/NcuLOWFLf3lZYJzlZZepzRXiWYX2NxeDFqVVMjuULdDtk3pZp00Fte227hp7kTpGtHkRo7RbpuNVqZmJ3HPJWVhcnfPJWVMjXFHX7zx+EXZQtce/8hwDke1L/TxsS+OFVMUXRfrvFBBYSRx0iKHRVH8dpSvHpI51kqgQJ3cdbYAZYPYtGFJMCq4JDOBm+ZOxNGXa7WzLwpyX4sFgPMmZfLc0rNo6nGSZtJxzz9302Z1S1uqgiuKP790GgatKiIP149CtggGtwUGDfiBK6rBBclA1KSaLrtbWp1P0KtZWTU1LJdc8HpOjx+LyxORy25l1VR6HR4sTg9urxiRF2xl1dQ+J6CyEjeSMes0FKQbqSrPlSaSr29rxKSLTd1kJetlcwbHmrPX4fFGvA/L5xfHnJur0+7GpFWHRf6atAH5j4WmKBXgm3ucTB8X5aRTjPHpZn5QWUJtm1V20ienj9LMWtnPB/7b7RNRqwQeuuo0euxuVoUUFgymy+myuynMMHP7BZN44K2vwuTk/rf2smx+Eb0OD3/68CBddjdv9EWk+f0itW1WVIIQdu/QlBMD9SEEo6lGRm640UiqUYfd0xuxVT8lTvl0AbKS9LJ6MisxPpFMapUQkarltvNLUMfJ+XGqFn8aKlnNSjLQZXfz5s4mfrVoOm6vj8xEPRanl4um54bZj0EG2oXzJ2VSlJGA3e2LeFbBvLEDx+J1F5fxwmf1LJtXRG6qkQPtNp75uE7aQdbQbZe9r8vrlyKcl80vOqbcr9FkKdpYPdplbLBINmllc1abtWrZfoXAMWpB4PfXzqLX4UFAQK9VSfZVtLmKSiU/3nfawuc/r29rZO3CMla91p+iYmXVVIy6wGJxsLiso288lpOb4Va8VOHE0WhUXDI9l+LMBJp7nGQnGyjNSUajOWkxcoNKh1W+0HZHjDsi441eo5JSVIZGPutHSP+7fT7ZeaVn4JZEBYVRwFAXpFMIIdQAyU4y8LtrTqO51x1mFK2+qJSKgmRqWq3Ud9hINeulraihzo6gge/x+hiXbsLt8ePz+1m7sJRVr+2KmiN4yexCXt/WyLqLy2SvGxo1eet5JTz49j6pkNzPLy3jkW+fxvbGHnx+pPxzBq2Kvc0WXtjSIG2NNOvUpJt1rNu4m5vmFHJFRWR71m3czdK5hZKhphhoI5OsJD3fP7dIKupm0KpYs7A0ZueuCvmcwX9dElvO4FSTjue21IflUXxuSz0PxrhdNMmgZd2HuyWnjc8Pf/jwQFiF6yORkyy/fS07+dQsWuL1+tnV1ENTj5OCdCMuj8jhHgcF6Sby00y0WV1HdbTeel4Jf/6wNiyX8+vbGll7cVlYbup7LinD7vJy77/2smR2IU99EJlT+P5F09nbbGH9f/Zx1en5PLBoOvtaLWE6bN3G3SyZXUiX3S3lFAzNC59q0oW1satvQWHZvCKykw3Ud9qla0Hg+eenKXkJ44UtSj7dmVGKJg0FiQYVN88rjsitnmiMz2TJqFVj0KjCFsUMGhVGbXwiY07V4k9DJavj0808/O3TqO+0h9mcq6qmkqRXo1IRUTg01C586MoZ+EQRR1/xuoHP6vVtjdwyv4SHN+9jyexC1CqYnJ3EHz7Yz/zJ2TzzcR03nFMAwOWz8hDFgP7VaYSIwIPgfUOvPdDRcKTcr9FkKdpYPdplbLCYnJXEgXZbmM7ISzWSnqiL6NeKgmTqOp1h+u7W80oQEJmQmcCvFpVT02qlODORO17cFjFXWTavSNYuMGpVPPV/ByQZm56Xwj+3NbKispjsZAMH2m08srkmLH2dSgjYecsriyjJTEQUA/MNlUoY1MJTCsMLjUbF9HGpIzJIIytJz83zJtJq6S9ge/O8iTHPq+KNgMBj/60Jm5c99t8a1h9DPZp4km7Wy84rF5Rlx7tpCgqDjuIcjhNyBsiT11XIbht54toKatusdNjdrH97Z8Sk4bbzivH64ddv7eXGcyaw9WCXVDTp1vOK+M3iGbh98kWa1CpYOnciGpUoVQrWqVWoBbhzwWQ6bS7UgsDOxl7+9OFBSTFOykrkgbf2ctPsQhL0mrBoo3sumcav3/pK2uYV5C9LTue5pWfxSW0HGUkG2faUZCVGOGIUA21kYXF5JMcwBJ7r6td28cL3zorp/K4o21ljjdz1+UWuObMgIgIu1txcPQ4PV1bkR6wQ9zg8MZ0/JSsxwmm59uIypmQlxXT+aMLr9fPKtkbufmUnJZkJfPvMgrAJ/YrKYsx9aTxCHa2ZSXqeuK6CXoeHph4Hr315mAVlOWzYFO5oeOWLetYvnkFtm5XJOUloVfC/fc6MaHnRv2qxSHrJ4fHh8ATSUww8Lj/NyNK5hUzNSUSlEqhts0r6qKnHydMf1fXlhE9kb7OFx96rpcvu5v5F5UzKSpLkNai7JoxRnMPxwhY13138orntblE2t/pfYyycOdiIokiySUt7SOHNZJMWMU45DU/V4k9DJasqlcCYBB23/P2LMBlc27cw9v2/fsGvr5jOU9dX0NjlINGgpc3i5PYLSshNNdLQ5WDFc4FnU5BujAgwuGV+MQXpen55WTkf1Xbg88O6jbtp6nGy87CFpXMLSU/Uk+gVw8aElVVTKcky8+DiGVicnsC9Ou1h+vSq0/NJM2vZuGw27TbXUXO/RpOl0pykU1LGBguNRsWFpTnkp/WERWOqVEJEv952/mRu/PNnYbL24Nv7WDq3kFWv7OKGr43n8fdquWlOoaz8u31+itITeOK6CnYd7sXi9PKnDw8C8KtF5XTZ3agQeOjtfexrtfLI9FyW/e3zsGtt2FzNg4tn4PX78YuRuaYXlGYPauEpBYXBQqdRYXF6I3aU6AYmcB+mtNlc1HU4wnwCAB22kZFubXy6mTsXTFHGCoVTAsU5HCfkDJDGbvnCcla3lySjljGJelJNOikaLfj91LHJ3PT0FpbMLqTD7ubVLxtZNq+IgnQzggCCSmB/s1U2QuLswnS67G78Ijz6TjVnFmbgFP04PPDXT7/ihxdM5tdv7aWqPFdy9hq0Kn53zUzWXlxGbauVgnQzz9x4Bj5RJDPRQJfNHeHIM2hVaNVqpuWm0NjtpL7DJtueyVmRjpjg71QMtJHB4S5nWHoUk17DE+/tp6nLxbTco58fzBk8UDYSDbFV5W23uvnj/x0MW+H94/8dJD9takznJxg0sivEv7ysPKbzG3ocPP9ZHb9aNB2H24tRp+HpD2upKIit6MloYldTjxR5dtPciVKEGgQivB0eHwVpJiwdNlZUFmNz+xBFeODf+/jxhZNp6LLzl4/rw3Y+BI1Lg1bFktmF3Pb8lzx9wxlYXB4sLn+E3Az8t0HTn3PuaxPH0GV3yx5X3xkwZM+ZmM74MQkRW5Obepxs2FTD7ReU4PP3R7898NZX/PmGM3hDKVozbEgxyeuUZFP8Kn23Rck53BannMMWl49nPjrIdecUSnr7zx/W8oPzJsWlPcOx+NNQ7GYaSllt6ZWXweDC2g9f2MbSuYVhi2cGrYonrq2Q9DoE6lI88k41f77hDP5vfzs+P3xY3UZeaj6tFifFmYkcaLdx/TkFeH0iTq+fGXkpHO62Y3f7+NWi6exrsSCK8MjmGi6flceT79eyfH4xD75dzQ3nFMgWH/3nLXM4q3DMUZ/LkWRpuMnYSCNaNGZov2YnGdh1WL62iV+Ey2bmSYv5xijpTM6ckIYgwMe1nfhF+MfnDdJORa1a4OkPD3BmYQbnTs7klvnF9Drkgwy0aoHJ2clcuOF92fnFqZrORmF40+PwyhYqLcsdGTmTg/nJB77XsaYbjDfKWKFwKjEy3spRSEuvMyx/UIJezViZrXkF6UZ8PpH97TbUAtz+jRLaLC6sLh/vfdXKhdNy6LS5uWlOIZmJOlJMOq4+o4AH3+6PmlxZNZV39rbK5n778T+2U9fhCMuRGep8rmm18P1zi/jtu/0OmVvPK+Gul3dKxy2vLOKSGbmS4VSnsvLg4hnsae6V8s5ddXo+2cl6DnbYSDVpyU8bQ1aSgZ/0bREProIe7LRRmBHpiAHFQBspjEnQ8e0zCyLSo6QlxDa57XV6pBQmodsHLa7YIneTjRp0mv4BWxBApxFIirUgnUYlmxbDpI1thb6l10ljt4uvmi2SEdfY7TolZbepx8nZE9L47uwJ9Do83DSnkJe2BgrPDMw5vnx+MS9t7Z/w7Wux8tQHAQeBRtUfBZyTbJD05qSsRKlY4f1v7eVnF5VKOvSlrQ0ROm9FZTEmrZqCdCNXnZ7PF4e6eGN7E+sXz2BviL66+dwiOu1uCtKN0hbjaFuTHSEO6yDNvU6pYI1C/HH7vBGRjesuLsPji1/ksEmnjjJZik8aB4/Px/zJ2RG5PuNZtC9Y/Gk4vEdDtZtpKGU1mgwGg8WDzrtQnB4/HTZ3hH1W1+Ggy+4mN9lIillHqknLnS9tl3bhpJp0XHd2AY+8UxO2o2Zcmolfv7WP7Y290v3PmZjOpKxENCqYlpvAuDQz/++vn0e0f09zLwVpJt7a03LU5xJNllQqQYr+aukN2LTKpP/ECfb3+HQzb+5qRiRysbYg3UhJViIOl5eb5hTy3letJOg0Eekj1i4spdXi4if/2CFFqq+smkptm5WJGQk88O+9XD4rnzEJOlweP/vbrGjV8k7mCWMSaD7C/CJYxDYo9y9tbQjsZlJSjSjEEU9fodKOvmCu4VBU91jQauRrGmg1I0fPDid7REHhZKI4h+NETrJBKroVNJof2rSP1VWlrNm4SzKAvvf1Im4PmaytqCwGAg6M7329iMf+W0NVeS7JBjUmnRYVguRUg/BcvsFicoIQyA3W1bfNI3hcMAdxaGTemRPSsLl9XDwjV8oplmrUcM2Z+fhFKMwwY9SqEID9rVZaLU68PpFfvrlHcjqvrJrKhDFGdh22hBnwv7lyRli0YDAa5I3lc07ZfIOjARFk06P8ZckZMZ2fbtbR1O0Iy2Nn1KpIM8VWkMek0/CD80o40G6TjKgfnFeCWR+ruhN4YUt9ROTvym+VxnR26Lsd+t5mJ516sluYYWTBtBz+95mtYQ4nQYjMKx3UP0GHcLC45YbN1fz+2lkYtCpSTboIp/KKymIOd9u5siKff+3oz0Pc1OOUck3XddoZm2LkcLedTrubB66Yzta6LkqyEkg9qyBML62+qJS/fFzHvlYray8uIy/ZCERuTS5IN7JmYRk7G3tYNr8ozLGt6KnhhV6tweEOz43pcHvRq+O3JTBRH+kEWVFZTGLMemqw26OVrUvwzI2x6e3RzsEOG/e9uScscuu+N/cwOTtxUCeLQymrcjIYWkjToFWRNiBi2aCNXhx0d1MvGzbVsLyyiMffq2XJ7EJJpi6bmReh81e9upMVlcVceUY+33R6cLh9TMww85OQoIW1C0tpszhl77evxcK4VOMJ7TI7mtNfqX1xYgR3SZZkJrBmYam06B6c34QuRq2smsrj7+3H7RXD5iqFGQl856lPcHoCxbWvrMgPe14rq6by0tZ6zinKYMOmwO7Gh66aIVsAS6sJFBgOOoBDx+2sRAO7mywRW/eLsxKU7eOjgJH8LqcadXzlsQ6rorrHglGjJj/NyAOLpmNzezHrNGjUgc8VFBSGF4pzOE74/P3OkVCj2e0NbEd3ur3kpZm48U/hObqCBZWqynN57L81UlTGktmFrH97B98/t0h2RTw/1USX3S2lhVh7cRkP/mdfxHFqVcC5dUVFHvlpJjQqgYZOO7nJRkx6DV12F91Ob1j0x08WTGZ/my1sRTA0Cnndxt387aYz2dvcxU1zCoGAQfaD574Mc0YHabU4OWN8upILboQSbatqS29s26WdHh/3/mtvxETwD9dXxHa+14dlQH5gi8OD0xvbCnur1UV+qokxCTraLSIZCTryU020WmNrf+i7Hfg9gff2gqmnXuGCHrsvIv/0hs0BHSYnI5OzE1gyuzBsB0Nwq/3Kqqm09DqlKLRg9LDT42PGuBRsbh+TshPY32pl2bwinF4/k7IS+d27NSwoywmbhOamBBy+B9vt/OrfX0UsZNx+QQn3/HMvq17dyaSsBKaPSw3bVtZpc9HY7eR7f9kaNkF9+fND3Dh7oqKnhhmWviKFA3XK49fOilubRETGphjCnIBjUwyIxCfHb5c9MhrU6fHTZY9tx8Zop8Pmks1F32lzDapzeChltdfpITs5IIMalYqSrAR+8a89krPs55dMw6xTs/qiKTz+3gG67G5WVBajUomsXVjGqtcii9UB+MWA7Og1/Q7daDngMxL0PPxONVXluTz1QS23nV+C2ytK3696bRcPLp4RUaQuaGNOzUkKu25wZ8m+Fgtw9CjgI+WYDUa9KrUvjp/gLsDtjb0s8vr40w1nsOVgJ2dMSOO6P3waEcgSnBOEzgsmZiRIx8kV1163cTfrF8+g3erk5nlFJBrUGLVqLA479y+aTmO3HYvTx0tb69FpVFJR26AcPbelniVfm0Cnzc3e5l5ph1NTj5OHNlXzz1vmKM97hDPS69hYXF7ZeUU8bZhjwePz09rrot3WH/mcbtaRkTAyCurByF5cUFA4FhTncJxotThljebtjb0s//sXADz87dNkjWm7y4sgQFV5rmQkBa/h9vllIyxSTFqeuK6Cbrub6lYrnTaXbF7gqdlJ3HpeMate2xUS0dw/GVp9USlPfXAgbIDqsLul1czgZ6FRyE6Pn0NdjrAVz6BhPzCXfjDqTsnvM3JJM0dWqg5EG8W2wt3rlC/I0+uMcVutGKj4PnCFPVafy9gUA2dNHCMtzASjl8amxBYNGvpuh7a/zepkYuaptR2pOcpCgUYtRN0ZcMeL2yM+P9BuZ+P2Ru64YLJs9HCoY9btE5mUlUhDlx2AcydnRkwmV722i6VzC8kaI18Yc0yCnpxkA009Tpp7nFI+xeC2MoDvPBU5sX3sO7OYPXFMmJ5SDMr4Y3f75MdSd/y2ZLp9PgxaNSWZidhcXswGDVq1gMfnP/rJJ4Fkk7zeTjbGLy/zcHp3dGqVbGT1c0tjK7QaK0Mpqwl6LQ9vrmZF5ST2tQTSIN1xwWRJHlUC/PbdGva1WllZNZWCNCMZiTocbpFH390VVqD43jf2hKUkK0g3UpyZECZTsrndu+xUledKNuz6/+wLCxpwevxYXV4sTk9Y3uFnPg7sNMsJSceWk2yIGBvuvXQaM/NTyE+Tl50jpTADlNoXR+Fo72joLsBWi5skg5O/flLPuFSTbL/LzQlC83BHW2TY29xLeV4KT31wgCsr8ln56k6qynOxtlqYnpdCY7ed688p5I6QugfBd/jBxTOo77RzTV908sAAl1PRdhttjPRCg3aP/LjgcMfHXjhWvH5Rdl7mHZi3aJgy0hcXFBSOhZFR5nIUEjSYgoT+f/DfQQfKwM/b+iIY1apAUac7F0xi5rgUfnX5NMaYtdy5YLJ0XkG6kQcXz6DX6cXl8dFjd7NhUw1//rCO5fOLpeOCxtCBDhur+iL95LYBrnl9F1Xl4VXFglEioQSNuOC197dZJeN9yexCnF4fP/3WFM4uTA9rQ2h0cNARE8zdqSjgkYFOLbC6L/crIC0q6NSxPb/gltVQ5La3RsPtFdm0p5lfLZrOfZdN4/5F09m0pxm3LzYjxOb0Se8A9DsTbc7YJucD3+1g+0/FVAPZSXrZvshI0LNmYSkF6UZunlfE8soiHrxyBs09dn4Sor+C+Tb/8XkDdR0OqlstXFEhHzl04+yJ3Pb8lzzw1j5uefYLnF4/T7y3n/w0+UmoX4SD7TbpXjnJBqktGrWK684uwKBVkZ0c+dyiORQ+r++ivs8pDf0G5Tc3vM+3n/iEb254nzd3NeMfIQbxaCEzMbocxgudSkObxcW+VguHuh1Ut1hos7jQquK0zVIUue38krB377bzS4h5VW2QGW7vzlA5bYdKVv1+kSSjluvPmYBeq6Iw00yH1c3tL27jzn/s4PYXtlHXYefm+cWSjt3R2Etjt5Nep4fvf72IydmJvPdVK43ddq6oyGPZ/CKWzS/iva9a+fGCKfzyzT2SnfnS1gZWVk2NsDlf2NKAWkVYnmMhxFQwaFVkJun584d1GDRqnny/lkffqaHL7mb94hmU5iSzfvEMDFqVbFTpXS/v4B9fNEaVnSON10dzHJ/qxPKOBtMxBWUgK1nPFRV51LZbZfv9jAlpLK8MyFEgdVMpr37eEDFfGXiezw/bG7qpKs/luS31XFmRz1Mf1LJhUw03/+1z1CoVdR02+cADhyciHd+GzdVcNjPvlLXdRhsj/V3OijYuJI6MtBJunygV1Fs2v4ib5hTy7Gf1Mc/L4k20xYWDHbY4t0xBYfBRIodPEkdbTQ/NX/nS1oaIvG+rLyrlqff3RxTmuu38Ev74fwfRaQTuubiMMWYdNreP7//tc+mYR68+jaVzCzHp1CQatNwastK1qmqqFBH35s4mfrVoOn6/iFol8MR7+zl3cuZRtwEOXNlXC/IRIaKIFNX3yOYa2aiOX18xgzdXzKG59+jRwcMpikghOia9moxEHY9fO4suu4dUkxa3zx9zoSWNoOKuCydHbD/SqGJbyxJUfi6fmR9eEK+qFJUQmxHSYomSFsMSW1qJgblpT+WUKNNykiO2H69ZWEpdhxWtGpbOnRi2VXhFZTHJRo0UkSaKSIsKN88rQq1SUZ6XTKpJFxalFowcGrjlbsnsQlp65fNViiI8v7WBtQtLefTdmogt4yurpnL/onKSDFo+2t8epnOi5UT3+QkrPDjSo1VGCxq1wD2XlHH3K/1yeM8lZWGFK4cat98f4azy+0U8/vhEAlldXvRqVViaC71ahc0dn6J9w+3difbOZw1yLvmhkNWBUVCBAl+lUnHj0C31v716JkDfcSbarR5WhRTL+8Wl0+h2ePjN2+G5s/2iSF2HI6zWxZgEvWz07+TsJNZt3A0E+lQVEliwuqqUQx02KYf849dWoFULYfo4uMtsX4sl6kKgnOz4/SKiCA8smk51q4XntzRITufgeB1th4tCbHm4g89n0i1z2NfSi1mnYuKYBH755t6IgrGrq0r56cs7wuqVvLClnnMnZfHMx3UsnVvIxDFm1l1cxiN9qUjUKpiSncRTH+znzMKMiF2V0L+AfP+i6bLP06zXRJ3rnKq222gjK8lAQbpR2qUAgdo9I+ddFvnFZdPCaqmMH2NGiHFeE2+8fp9sWiZfnHZKHStHWlxQbHmF0YbiHD4JxLL9YGDahOwkAxdMzabV4sSkVWNxebilsoReh4eHrpyBze0jyaABAa6oyMPnh/pOO+22yJQO2xp6Aqvl84okgz343dq+nF7/+LwhIg/nispiSrKOvg2wPC9F+jwQ0amLqEK6smoqFqeHJbMLsTg9dNndYcVJgu354Qtf8sbyOZxVOOaE+1RheODyiFS3WCMKLY0xxxb51GF34/D4w7Yf3XpeCR0D0qBEQ6fSsGbj5+ER7xt38fQNsRVWyuqLdo10AsTWfiUlSj8Gg4aF03KYMMZES6+LrCQ9mUl6mntc2Fxe7no5/DkFnRF3vbwrcL5WxcPfPo1l84sinMhPf9SflzjomA0lGIH2l4/rIyahwS2jXXY3+ekm7rhgslT4M3juuo27efL6Ci7c8H6Ezhmfbua+y8u586XtYdd8bks9l8/s31mhGJTDgySDFhDDiqE4vV4SDfFLmSAQJf1NnEg0aPnFm19E6L2n41SQbri9O0O16DcUshrqeA8W+FoWEmAQuqXe7glERhu0Kvx+WPXqzrCc71q1ivve3Buhx9cvDjjimnqcUoqIgnRjxILgPZdM4w8f7JfyHK++qJQJ6UZyU6ZJxWBvPX8Sz/3vWWQl6mXTQ4Sm+4m2EDhQduRsyoEpKJSF3iMTax5ulUpgYmYCE8aYOdhhY1xaIMf5Mx/X8ftrZ7G1rouizER+/dbesCLZwRzEGQl6uuxuDBo1v3zzK6blJnDL/BLufqU/d/DahaU8v6WesyZmoFbJB7Y0dtsjbIF7L53G+DEmWbk5uzCd0wvSTknbbbSRn2rilvnFEYtu+ammeDctJlxekTaLK8xeuO38EnJkdrYNR0xajWxapj/dcHqcWxYb0RaHR87igoJC7CjO4ZNArBEvQYM29LNgXqvaNivf7HNK3DyviKc+qOX+RdPD8mUtm18kXT8Uf1/EbmgxkCDB1XC57XcPbarmqesrpAq/0SKa//rRQZbOLWR8uhmjVo3H58Og1fCbxTPY2dSLQaPC7xclx3RBupHVF5XS1OM47snecIsiUoiONUrhhGm5yTGdn2TQRmzxe/Dtffw5Rudum1U+8rctxoJyZp06rKp2MNrVHGPkM8i/26cqBoOG0yekh33m98Mem3wBLJvbR06ygRvOKaA4KxERJGdC8JiHNlWzdG6hVJl8ddVUHntvf/h9tSoMGpUUcfbg4hnYXF7qu+ySY/i280twuL14/H7Ztnx6oDOqzvlWWQ6pJh1b6jrx+eG5LfXcuWBKmONAMSiHBz4/3P3Krojn8M9b5sStTW6vKKsnn7gutsKbg43V6ZF9B6zO+BSkG27vzlAt+g2FrIY63uVswWDNiI3bG0kxalleWcSUnCTaLM6InO/LK+WLIDd0OVhdVcqajf3j6JUV+bz8+SF+e/VMPD4/Oo2KR9+p5szCDM6amIEowmP/reGOCyZz50s7KEg38uMFU9ha143P72daXjL5adEds3LO3KCje6DsyNmUd728gzeWz4kaxJGRYECtgk8OdCi71zj2PNxBh3u9APdeOo27Xt7BtkOBYJZl84skx3CQ4Hwlq69o4mcHOvjpN6eQYNBIxWCDx616bRePXn0aazfu5icXTpHVHV6fyAtbD/HAoulo1ALFmYlMGBOQJ7nF3h//f/a+PDyKKnv7rd73pLOHhARCEsgOISzOD1ATRXTCIou4DI6Kk88ZEcZtGJ0BBNQZXHBEdBTFBZwFFTcYRUdQwVHUgLIvCYGEhOxLp/et6vujU5Wu7uqkQpZOJ/U+j4+hu6vqdvWpc88995z3ff8o3rhjshDHDQFUtVqYxDDgsZk/f3gc+Un6kPh9nS6KKcACOvnZgxUv9BSBtGRMfLVkggxho1DAcIKQHO4H9EXFi7cjoukdzjeZmUqP+fmJGBmuhFoh8QuCdh2pwV/m50AhFXMGSAXJEQETtTWtVkSpZfjrjVmI1CrRbnXi1SUFOFtvRIvFiZe/Lve0bHUkZTbeNB5/+fQMFkxMBABs3uepEIkPU2DZ1alIjlSDABAbJkdmvI5V5UyPh89ib7BVEQkIDIvDxaosAoCdh6p5czMaAyQpjDyTFDRno7+d8av8Pd9kwZ5jtXhlyUS0WZwIV0nx5jfnoZZLkJUQzuscAgKDJCmcuNSOmAAV2hFqKR69YRyqW614bNcJ/O5K7uRDYrgSzy7KRWKEEgQI3FeYhostFqY1eFVxJjQyMVYUpSJCJcO6jrbl+fmJ+P01aahqsTIUPU/MywlIE+F7XdrnSCQiTEuNQqJeiQajDQvyE7qkDxICyuBhMIpEWp3ciyVrkETytAopZ9ttsKqrk/QqTnqFYFZ6DcSm30DYqnfiPRB92OgoFe6/Zix+vNCCd7186p2/SMZGr440uhiB/nd8mAKLChIxMkKFOoMVz988Ae1WJ2J1clidbthc0fjTh8fRanFg3ZxsaOVSprKYub7LjecX58HkcLNo0VYUpSE1WoNRUdz3wZvC4FRdO87WG5mNQF+/yzempH/zUZFqoXvNBxaHu0exnne19u+vScPSaSkYHaVmcQn7zsEZcTqcbzRhQlI4EsKVePrz0wFjAovDjaX/Nxp6lQSrijP9uo3EBHDr5GQ88ckpPDEvm/U8jQhXsOis6Mp5YY0xNBDqa8jBFi/0FGFKKefzrQui4G1PIHSEChhOEJLD/YC+qHjxdkSNJjteO1ABh9tThevdxkVX5a7dxa7OaDbZsf1gpV8L1fq52Vj10THMzkvgHGNlixWrPz6BdXOy8ecPO7m/1hRn4aOfa1DZbGWCQJuTRHmDCa0WB3z9Y63Bhs1fluOtOycjWitngvLLTZQMtioiAYERo1Xg9iuS/Wgl+CZnAwURYTyDCJmUwLo5WYyoHN1yKJPym8TjwxT47nwLvjzbxLr+vYXBa/keSrjQbEZZgxExOhnWzc1m8Vc+NjsL5xtNaDA58NHPNVhckIRLBmtAX7X7aI1fm/Lq4kzE6ORYv/sk47/uvyYdgMcvbf2mAkunpbASEs0mu99icsOCXGz87xnW2H19TnfJIiGgHBwYjPNHpDrQ5khwBGYkYuB3V6X6dUxIgqSPV9VqwQsdFax0wuaFfWVBrfQaCN2DgbBV700r+vy+16tqsTBFAHT17frdJ/HSbfmsz+48VM3EmXqVjHPu3/adJ0G7osgjQEfTAa3++DheXVKA0/UmFkVQm8WBOJ0S63cf86usz0/SB0wOA2wKg8x4HX4xJpLT78Zoue9ztIb7Pg/G7rVg63DEh3HHeoFa3b3vocnuxtZvKqBXyRhKJt/1yqriTFAUhQ9+qsFD143FSx3aAIFiAolIhNgwJf53zrOh4e07tn1XiYdmpqPBaMeigkSo5GKQJMXcr0i1HFu/ubziFQGDH4MxBugJIjUyzvFHBile6CmoDsFbb/rJB65NB0WFBmcyIHSEChg+4KfwdBkgCOJ1giAaCII47vVaHkEQ3xEEcYwgiF0EQei83svteO9Ex/uKjtcndvy7nCCITQRBDPpVtbc6L4DLrhajHdGk5AhsvGk8dh2pwcpZGaw2rspmK17+uhyv3zEJy4tSsXRaCrYfrESb1cUSA1lW6HlPLiFQ2WxlAnrvMS4vTMP7h6s7WrSOozjXw51pc3o4W++eMYbhb6OPcZEkVhSlYWysFpnxOuZ8yZFK/P1XE2FxuJjP04mST5ZPx79LpuCT5dN5V1301T0V0P8wO7hpJSw8hY1om/L+rVcUpcHFU6jJYifx4lflLLt/8atyWOz8js+K02HdnGzW9dfNyUZ2nK6bIwXwQX27De+UVgMAFBLg1SUFeGpBDp5amIf3DlVBo5CBpDpFZd4pDeyrinMT/Cgn1u0+iaPVBhZ34XNfnGWUx1cUeY6loZCKEKaSIT1Wg38snYI37ijAjt9MxYhwBR6fm4PkSCXzud748akpUUiJ1giJ4SCArkL1tqFgV6EG8nPuIAnS2ZwUkxj2/Jvs+HdwFm/17TZUNlvx4pfl2LyvHC9+WY7KZmvQ1OXpqscbNh3ALa9+jxs2HcCeE3V+ooK9xUDYKh2Lvf7rAoyN1eCJG3P87PDdDh9NUwXMz0+EzUmi2eRgPguARduzYUEO59xPH0v/TcPmJFFrsGJRQSLr2lEaOWQBaNH4xhHd+V2xCJzPn6/gMo2uKg+DgYGyx67gJsH5ewfSmPK+h/vPNGBVcSbDPTx3fALSYjV47qbxeGZRLp5emId2qxMbPjuNq8bFwGB1dRsT/HXPKUhFBEjKw2ns7TtaLQ4oZRI8v7cMm/aW4443fmTdL2GNMbQR6r8vSXH7KxKhkVw1WJ14438XWOuyN/53AQZraNBKCBAwnNCflcNvAtgMYJvXa68BeIiiqK8JgrgLwMMAVhEEIQHwNoAlFEUdIQgiEgDdQ/53ACUADgL4BMAsAJ/247h7jcupFuuqAoA+X0K4AmUNJr8AtbLZiqPVBsTrlAy/m5jwTB7eYiAKqQivLJnItI6KRMArSyaiyWhHRZOFaaMCOsWcaNicJGwOF1MFopCK8MSNORgRJsexagMe/88pyCQEtiwpgN3tRkO7Hb/t4ATzbb+jW/QuNJs5udsC3QuhAi80YLIH4Jay82t/Mlhd2PZdpV/VR0pUJq/jW8wOJqng+zof1LTb8E5pJZ5amAer3QWVXIK3vq3AxGQ9xiiEHePeIlanQKvFgRaTE61mF+oMBsSHq2B1uPD/ZqSiqsUCMQFQBJ08sLEU7/OTwvG3/55FrcEWUHjGd31sc5JIiVLhtdsL0Giy46aCRIZ+YkVRGh55/xjTeiyTEFj86kFWBXFCuAIRarngc0IUVa0W/PsH/2c6mFWorRZnAD8XnMVqcwAOcL5+s68x2Cq9BqpydCBttbbdjj99cAx6lQx/uG4sorVyaOQSPPrBcSYWBDrjQYVUBJ1C6tetdvOkJDjdbrRZuLnb6VhSr5JhXJyW0cs4eK4RsWEKyKVivHDLBFS3Wpgq4+cXT+D8/WUSEb6vaEasjlucjkZ3VbW1Bhvn8zchKZyzMnm42mNXCESB0mDkpkCh76FeJcOs7Hhs2X8Oy65ORVyYAlEaOZpMdjz07lG/4zLjddDIJcx87xsTjI3V4slPTqHWYIPDTWLXkRq/KuQnbszBhj2nYHN2UvOdrmtHQrgSOQlhwhpjiCPUf996g53TX42MCA1BPa1CApmk814TBCCTENAqgtSaJECAgIDot+QwRVH7CYIY5fPyWAD7O/7+L4DPAKwCMBPAUYqijnQc2wwABEHEA9BRFPVdx7+3AZiHQZ4cBnrWfsClmuzLZSYSEbA43LjQbOEMUEeEK/Hs56eZiUMhFfsF8MsL0/DR4Wq/1tGXbs3H1m+O+53Tu9tDIRVhZIQKZrsLiwoSMTFJj1FRKlz3twOs40q2l+KZhXl+1XzeQWtX3xdAl/dCaOkY/NDI/HmwFVIRVHJ+QUCsTs5UfXgfH82TliIuAJdtrI7f8ZfaLCgcF4c/dIg/0s9OrcESNH7SoYRRkWq8fsdE2J0UXv/2PIpzEzCCAKrbrHjuizIAwD0zUhAT1rkYpze5FFIRSmak4Je5I2CwOTE+MZzzt/aN9xVSEZQyCe7eVurFX5qDFpMNb3zbuSn2wDs/o2RGCst3rdx5FJ8IwpchjWaznfOZbjbbg/a7xmi5/VwUTz/X14gP405+xeqCk/wabHzdA8VZOVC2eqHZjD99wKZtMFgcUMkkaLWwNwRon7qiKA0VTSYAQMmMFJBUZ5Ki1eLAtrsmc9oQRXVSEDzs9b3WzcnC6o+OM/Q/yzuom2xOEpUtZtx/TTojTktXyj307lFmUy8tVoPCsbF+CR4+MTW9Sen7/AVK9g5Xe+wKqgCxnlLKHevR9/B0XTtDQyIiCIZXfEVRKuf5Tta246vTDVhxTTpnTLB0WgpqDTYopCJcarNicUESdpRWYem0FIhFQEacDiKCgsNFIT5MwRJU3LK/QlhjDBOE8u8bF8YdL8QGKV7oKVQyCe65MpWVk1gzOwsqqcBuKkDAYEO3tBIEQWzg8xpPHAcwp+PvRQBGdvydDoAiCOIzgiAOEwTxh47XEwBUex1f3fFaoLGWEARRShBEaWNj42UOsXcgSQoVjSZ8d64JFY0mXi1egSoALjSbWZ+L1SmYHXHv1pI1s7NQ12ZhtWBu2HMGBqsDS6eleHh+bhqPHaVVuCojzq91dO3uE1hdnOnXRr/7aE3nNYqz8OznpxGtVSA1Rgu1XIxLbdzBqTlA5WiD0QaSpHCspi3g9+V7L0Idg8FW+wtKmRgPXJvOsqcHrk2Hiid5pZuk8PB1Y1nHP3zdWJA8ualEBMHdLsqTkUYq4VbglgTqNx3C6A87FYkIyMQSvPhlGf44KwNiERChlkIpFaPV4kCtwYZdR2sQr5P7tTsvL/S0Oz/3xVmsm5uNf/94wc93PTRzLJIjVazXVhVnMlVDAK1UfQwGm9uvQo6r6jhYrcMC+KMrWyVAcD7TBIJXNeSmeufn+hpicLetSoJ0i0QiAjMzYrGjZCpe/lU+dpRMxcwM/0TgQIGuevTG5VaODgZbpZOL8WEKPHJDBmwuNyI0cqzbfcIvxlw3JwtZI8Kw7btKmB1umB1ubNrb2bJfa/Ccy+xwYu2cLD/fq1WI8acbMvwoCFZ/fIJFX0bTVyikIuQmhiFOJ8crSyZi4015KJmRgm3fVTLXen5vGY5WG5jY0Dv27irGpEEnKpMjlbj36lQsL0rFq0sKAtJ39IYWrT/Ql/bYFbqy1TaLnZPewWDl7jag7+GkUXqsvG4s/rogB1EaGe4rTEV8mALvlFb7+aBHrx8HmViEGWNj0NBu9aNcoWmi6OrgVw+cx/aDlSjOTYBYBKTGaLFu90ms2HEEiwoSMT8/0e/5GoprjOGIobyukok9a33ftb9cEhrrknabi0kMAx25h10nYLQPP1qJoWynAoYG+GzZXAtgpc9r13O8xgd3AdhEEMRqAB8DoCMICYBpACYBsADYSxDEIQDtHOcIuHKiKGoLgC0AUFBQMOArLD7VClwIVAFQ2Wxmtb2MilRj5awMbNhzCk8vzMOZeiPClRJoFWKEq9R+O+5Wh5sRWKDbqEiSYj5Dv0YQQHKkCi/cMgEtZgcajXbEh8vw4MxxsDpcUMokeG3/ORytacfNk914YV8ZNt08Ae1WB1YUpeIdL4ERhVQEtYK7moAAgf+VN+FUrSFg8piiuNvEQ0VRli+Cbav9CYfbheRIFZ5ZmAez3QW1QgKpmICT5Ecr0WpxQkIQTGWSiAAkBIE2q7P7gwHUGGz49Fgtqy331f3nMDJChQk8jm+3cm9utA9Dbqz+slOHy4UVRWNxyWBFWowWZ2qNTMucViGGViHFvjONUMnEeO6m8Wi3OqGSS1DTZgHg+T0OVbZiYnIUxkR32JrDhRazAzIxAbPNhZIZHiV0uVgEp5tkOIhp2JykH79koKpjesEdbAEgAYHRla22BqBMaA0SZQLQhZ+z8PNzfY2Lbdx+M1GvwvjkgR8PSVL4/FR9j+Op/kJfVo4OBluN1SkYgWO6Snl5USpLq4JuX26xONBicWJRQSISwpWcFaPJkUoYbSQsdhfeuGMS6ttt0CqkWLf7BCqbrVhelNol5QT9b5oLuKbNimc+O4tWiwPr52Zj095yv2NJykNtMCpSjX1n6nG02gCSApL0ym7jSHrzwen2dIfYnB6B5/VzcyAVE5z+fTBVHg5UJXNXtioSiZgKXdpWdpRW4fF5OV2e02J3w+Yi8f+2d1LP3X9NOv5z9BLUMjFeujUf5Q1GZIwIQ327Dc1mB3Ye8tBAPTJrHLYsmYgfLrRC0ZEYWzAxERQFKCUiZk0DAO+WVmPBxERmfZIWo+Gk5rM5SZytNwKAMKeHMIbyuqqq1YrPj9filSUT0WZ2IlwtxZvfnIdOIUHuSH2wh9ctAhWNmXnSDQ4G9FX8P5TtVMDQQMDkMEEQvwXwOwApBEF4k0BpAfzvci5GUdRpeCgkQBBEOoBfdrxVDeBriqKaOt77BEA+PDzEiV6nSARw6XKuPRC4XA6wQFxmP11sg9VJshZDY2O1WDM7Cxq5BM98fhorZ2XggXd+xqPXj8PmW/NxtLoNJAXsOlKDCJUMa2dnosZgA0kBYgKI1soYzi/v1qrXDngqPLbsP4ebJyXB6qCYBYP3mDQyCe4rTMPyf//EtAJ6q1G/cMsEqOViPD4vGxdbLCxez9/v+BmtFgdWFWciOVLJStZ4J2AGE6+bgJ4jQi1DdauRaRX0tPBnY3SHsFd3CFNKcd+/fvKzgW13TeZ1fGK4AtfnxLPaclcUpSEhgIK2L+ICtFfH8aSlENA1XC4S1W12rP6o0z62LJmIVosD7x+uxiM3ZKC8wYi0GC1azXa0WhxY10FTQ1cm7SitgpsEnvviLEpmpGDT3nLmva3/O48/zsqAzemGm6TwwPtHcPf0FM7fNCNOx7xOL1AVEhHrNXrBfbmbfwKCjwg1t9K3PohK3+FKKZb3ws/1NUbquf1mYvjw5VT1xkBxVg6UrSbpVXhsTjajDQEA8g7f56tVUTIjBVNGR+KH88342xdlkEkIrJubzfjw5Egl7pmRyrKdv9+Wj9/+4zBzbpLiju186ctSY7T4yyen0GrxdL69+GU5qlu56dREBBCjVaCqxYyyehO27K/okp7AN46sarUwieH4MAUWFyShZHtpSPj3wcChGqWRcraKR6mlAY+50GzGidp25rcCOkVjX11SgOOXDFi7+wQWFyThN140UMsL07D9YCX+suc03rhjEl47UOH3+750Wz5TEEP7L+/3kyJUSIpQs65Nv3esph2/3/HzoP7NBQxfjAhTYHJKJGtDZUVRGuJ5rmuCjdgAdH8x2uDFYD2BEP8LGE7oqh/hnwBmw1PhO9vrv4kURf3qci5GEERMx/9FAP4M4OWOtz4DkEsQhKpDnO5KACcpiqoFYCQIYipBEASA2wF8dDnXHghcrpoxl4oq3T5NtzvRjumXLxzAXW+W4uH3jmB1cRYqGk3Qq2QQi0V4+asypMZoMVKvxJM35qDZZIVYLMKW/RXYvK8cr+yvQGWzGevnZmNRgX9r1frdJ7Fo4khYnW4YbU48t9jTcuc9JoVMhBf2lTGJXbq979EbMvDANWmwOty4681SPPTuUbyyvwIPzkzHA9eksdoB1+8+iZWzMljfl07AhLqi7FCBy0XiyMVW7DleiyMX2+ByBZCf5oDRSjKJYYBu4T8Oo43fOZpMds7nqNlk53W8w0VxKmg73fw2aDPjdJxq8ZnxYbyOF9A1TtQasPqj49CrZLj36lT87qpUOFwkHp+XhduvSMYf3juCTXvL8fB7R5AUqWYSw0Bn6/HKWRl4/3A1iwaCfu/mSUlwkRTClDJcbLFAr5Jh5yF/dfNVxZn4+1flePX2AkY9+c1vL+Dl/RVYOi0Fr/wqn9U6PFwob4Yi3BTF2f5MBVHpuzmQnzPz83N9Daeb22+6eFBj9QcuN57qT9CVo1NTopASremXRWF/2ypDv3C+CWYbu5pLRBB+rcsritIQqZLhWE0bXtlfgXtmpGDRxJFoaLfhzTsnY9PNeXhw5jhGDBnw/E4/XWxjnZvLB6+bk8WiL1tVnInX9p9jYkW6AvSd0mo8uygPy4tSsawwFSuKUvHo9eMwMTkcFAVcbLWybJeLnoArjvS2sVCkGxgIe+wKTjeFnYeq8NTCPGxYkIOnF+Zh56EqOH18hjflx4VmM8gAHYI/VrYgQa/EgzPHcVKrzM9PhM1JoqzB5Genj8/L9mtbf35vGdwkxWz8utwUHG43NizI9Xu+6HhisP/mAoYnrE435/xsdYZG5a3DTXLSaDlI/mvLYEKI/wUMJ3RFKyGGh9bhXt83CIKIoCiqpasTEwTxLwBXAYgiCKIawBoAGoIg6PO9D+ANAKAoqpUgiI0AfoSHNuITiqL+0/G53wJ4E4ASHiG6QStGd7lqxnR7G90qRVHA9oOdIknNZjtazA4YbU48vTAPr3ZQPDS1W1GQrEdmvBYXmi341dTRONdgxJenG3DVuBiMiQ1DbZsVepWMCbbX7T6Ff9w9BSRFcQZncToF/vyRd8VnDppMNhhtbuworcLDM8dxtmfXtFkwIlyF8gYj7p6egp2HPFQTf/7wOCMW4f358gYTIxZRNC4GOQnhTGAb7GqI4Q6Xi8SHR2r8Kn/n5SVAwoPfqtFkR3qMBnfPGMNqT27imdyN1nDvMEdp+FXuNpm5ky5NPJMuEokIc3JGYFSkGnXtNsTpFMgdEcbruwvoHrUGG9JjNFg8OQnrd59EeowGKVFqyCRijI5SIz1Gg6M17bA5SRyuauX8LcsbTIwAjXflmV4lg04pZYke0RVHdKt0coQSsWEKnKptx9kGE3QKqV8V0tZvKvxE6AaDAJCAy4NCIsa+03UsyoS3vq3A/6VGBm1MkQH8XKQqOB0KDUZuv9lgDE6y+nLjqVBHf9qqd/XTyuvGIi1Wi+VFqSApYP+ZBiTqVbC73Hhu8Xg4nG6IRCJUt1oY4VC9SgaL043NX5Yz/nX93Gy0mi1+tuNbKVxrsGFHaRXeunMyGow2RGrkMNrseGx2Fn662AY3CWzZfw6LC5LQaHKg1eJgfLtMQsBNUkzFp0IqwlMLcuF0U/jlCwdw9/QU1vVrDTZs+64SW39dALGICBhHetsYQQwPSrO+RIvZgdm5CShvMDLdibNzE9DiRYHiW3G3oigVYoK7ilwpFcPlJuF0c69PiI7j2q1OfH6iDlt/XYBLbTbIpWI0G22ca5NorRzLrk6FUirCbVu/ZyrdtywpgM3pxpFqA2u9JfzmAgYjjDZuWgajLTTo7kw2FyeNljlEOIeF+F/AcEJXyeFD6OT39c3MUQBSujoxRVG3BHjr+QCffxseGgnf10sBZHd1rcGC3nCAVbVacKiy1S9JkRypRFWLlVGVVkhFeGx2FiKP10KpkKK6zQKSIvDUZ2c627qKs/Dy/nKWAjQd/NicJMrr2hGtU3IGZ1WtnUG+p+LzGJZOS8HWbyrwwLXpqG7zb+9LjlQiUi33U9emrxmI13PrNx6VYO/EMDC4eN2GI07UGjgrf9NiNMjjwW0Vq5PjlinJLHtYMzsLMTxpGShQWFGUxuyS09VLfCunonqZXCZJCl+caRDah/oJcTo5fntVKu5/52ekx2hwy+RkPORtK8VZwA+VOFrTHrAV2e7qtItt31Uy7y0qSMR6jkpjuj156zeeqmAAsDjc2HjTeGTF6/z89oYFuahps6DRaEesTo6kCPWwTVYNBThJNxZMTPLzSa4gVq3IxASnn5MFSQEuWsvtN6N5+s2+xkBxqg429Ket0tVP6TEaaJVS3O3Vtr+mOAvPfH6aky5sVXEmNu8rx/z8RL/qtVUfHcertxf42c6uIzVYVZzJ+GOFVISbJyXhyMVWPPnpGeb3/O2/D7OO27SvDCUzUqCUirHtu8qOBHQOQ/dAX/cPO4+iZEZnUtj3+q0WB+J0SoyJCRxHetuYUioKYP+Cfw8ErVwKi9PNStqvKEqDWi5BRaMJoyLVfhV375RW496rx/j5vuWFaVBIRKhvt8PmdAekEaGpIs42mPD9+RaGUuq5xeM5j2k02uFwk3jy09PMe5XNVpRsL8WO30xlaCi8jxHmdAGDDVEabrqhqCBSY/UEYUop7t3jT6O1PUg0Wj2FEP8LGE4IWApHUdRoiqJSOv4b7fNfl4nh4Qa6Zer7880YG6vFnhU9VzOub7fhy9MNWFWcyWq7WDsnm0kMA56g+LFdJ3DX9BSUN5iglkkZ3jf6/bW7uRWg6XOqFTLIpcCTN+b4tVm/W1rNGpfNSSI9RoPXbi/AG/+7gLe+rfRrDVxdnIVVPmPwVp2meT3pz68oSsMVKZFBV3sWwA16E8EbNieJOgO/dl67i+RUpbXzpKZotTgZcTK63X/bd5Vos/DbYbY4XJxtuVYHv+PPN3G3D51vEtqHeguSpGCyu3GqzlMZfPeMMX7tyGt3n8DdM8YA8CQY1s9lU3w8cWMOchN1eOvOyRgRrkCrxcG8NzpK3WXF0fLCNOw+WoPYMAXyRoZhbKyWpUL/r99MwZYlBdj43zNYsvVH/PqNH/Dp8TrsO1OPJL1KoLwJUVgc3D7J4ghecrjeaOf0cw3G4Ijk2V0urCn2UUMvzoLdHZzKHu/nsqfxVCijP22Vrn66rzDNbwPYN258fm8Z/nRDBp67aTx2/FCFWoMtYHXtiUvtfn56cUESdvzgEStbXpSKZxbmIUwpwagoDZ6/eTw23pSH2jYr5/ky43UQE8CTN2bjP/dNh9Hm5PwczV7ARVmx8abxGB3VtW/2trGpoyP9qChWFKX5FTcI6ITZ4eJsdW9ot+OGTQew50Qdmn06uWoNNuw9WY+CUXq8ccckLC/y+L7tBysRpVXg+b1leKeUmwaK3jCwOt148sYcaGRixnf+/ctyzt9vRLgCYwLEBdUGqzCnCwgJmOxOjyaGl63ef006TDzXNcFGi5nbhwdLgLenECgvBQwndCVIN46iqNMEQeRzvU9R1OH+G1booK9IyuPDPGIwW/afY+gWMuJ0cLjcnA7VbHchIUwJu4sMmAzx/bcnkZsJN0mi1QIkRSjxt5vGgyAAnVIKgGISLTQUUhHEIgI6hQStFo+KNt2eLRYB01Oj8P35Fs4xiEVgeD291Yy3fVeJCUnhQmXwIMWIcO6qcr7CB00mbrX1JhO/pIda5rE1WhCHvr5KJuZ1vCSAgvYT3Sho06hsMXOOv6rF3GUVkoDucaHZjB8utDAVwdYACsZWh4tJMGz/7gKWTktBUoQSNW1WABQqGs3Y9t1JAMCyq1ORHKmGWibGqbp2TtsdF6vF0mkp2FFahRVF6Xhh71mUVhoYfz0zIxaAh9ftyMU2OFwUM5bn93oq2VKiNALlTYjC5uSeR+1B5OtTSsWcfo5efAw0CIiw87CHP9TqcEEpk2DbtxX4/TVjgzIeYHh2EfWnrdLVT04ycNu+77+bTHacbTABQEA6AE9rM4WSGSmQiERIjdFgw55TqGy24myDCauKM9FotEEtE+P4JQNDQTAhKZzzfGqZBIkRalyZHoMLzWacrTcGrCQFPAnH7QcrUTIjBRNGhiO5Q7/C1zcHUptPidbgu/YmZrPGN1YdFTV87K8nsDm51x8Wh5vZVN9RMpX128WHKXBNVhyWbP0BepUMt1+RzCSYrQ5PPED/nk8vzENZgxFuEti8r5yhkpoyOgIuksQD7xxhXbvR5MDTC/Nwpt6IsbFaPNkhbPj0wjxO+zlTZ8T8CQn4pGNOj9Mp4CaB7883s+xDgIBgQ0SI8M8f2P7pnz9UYv3ckGishkIqQnKkEsW5Ccw8s+tIDeRBind6isEgACpAwEChK1qJBwCUAHiW4z0KQGG/jCjE0FeK2m4STIDkrRL95p2TOIMal5vCxTYrJo/Sc77vqwA9MSkcOYsnYOfhSiyYmAypiECj0QGdQoLXDlTgy7NN+OP1YznbXMPVUmTGhzHtd7UGG0MJAQKwdbR4+44hNUaLS20WnG0w4WhNO+s9oRVj8EIrl+DR68ehyexgFnGRahm0isAK1N6ICdCeHMOzPVmrkOD5xXlwugGz3QW1QgKpyDMuPhCLgKX/N5oZv6Tj33wrgNQyCef4VTJ+1xcQGPXtNpCUJyhcXpgGtcL/XidHKpEUocLa2VloMtvRaHJg6zcVeP3Xk6CWSVDdamEELgFg85edm0+7jtTgkVnj0GzptN3kSBUutVkwLk6DK1Jy0Gi0Y+qYaNS02VFrsGHDnlNwuklGtZ6uyHjz2wtMFT1JgeEWG27JqqGAlEg15zMdzKoPtVyCpxZkI1wlR4vZiQi1FG0WO9RB8jPhKiknnUG4kp/fF9A36E9bpauf1DIxCpLDcPsvUmC1uxCmkqKh3Qa5xFOJufNQNVotDkhEIrxbepEpBsgcEYb7r0nHc1+cZWxkVXEmjDYnvjhZhxvzR2L97pPQq2RYVJCIMdEahKuk+OPOY7j9imTYXCSLguDR68dhzewsplKa7u4gCAqZ8Vp8f74ZIoLAl6cbsLwwjREpU0hF+MuNOXC63QxnMh2njI5ScyZzuyvkiNUpODdrhFg1MAK1Wms6YjU6UexND+NN/URzQ5fMSEFShAoj9SpWAqmqxYwotQxPfnoaepUMy4tSMSZaA6mYgFQsYX57WuOk1eLA6TojQx9FxwiVzWasm5vNdFnSdrb9YCV+MSYSU1OiMCpS3SeFPgIE9Ae0cgkevDaNFS+MjVUxz9pgR5hSit9dlYo1H3f6+rVzshDGc105GDAcN6sFDE8E9CoURZV0/P/qgRtO/yJQ1UBvcDkk5VzjaDD6n0ev8nAJ/XV+Ls43mfBOqSdgXzM7Cy1mO3YeqsbkUeF+wfW6Odl48asyAJ2toTWtFnz4cw1umzIKFY0mVgL4iRtz0Gx24F8/VGF5URqLMD5GJ4dWJoFEIuLcNbvQbGYSPd6B+7o5WXj289NwuPz5Y4VWjP5Hb2y9yWwHQbA/SxAEmsx2jOYxKYapxHhqQS7KG03Mom1MtAZhKn6Vv1IxAYPVhdUfn2DZ08gIfuOPUEuhkkuwpYNjTiH1COpFqPgFIbE6OecmSSxPzuThjkC2R5IUVDIxFBIRHrk+A68dOIflRWlYNycbqz/2LNoKksNw8+RRuPPNH1n3Pi5MgUc+OMrJh0kv8gDgt1em+CUgHp+XjcwEHeoMdhbHJp3USAhXMQJ2gMd/P/fFWSy7OhXPfH6WqVATkgShi9HRGjy7aDwefLdz4f/sovFBDfKjtSKcawBKth9izd3RuuBU0lgcbuw8VOUnhDYmOiMo4wH6J2Yb7OhPW6Wrn87UGbCogL0RsKIoDX//ugKtFgdWF2ciXCVFZbMJv7s6Fa8dOIeijDg89vEJyCQEXru9AM1mB841mrDjhypcNS4Gv5o6Gma7E6/fUYDqFisS9EpIxUCD0YlWiwOJen8/++Snp/Hybfl4ZclEtJmdCFdL8Y+D55GTGIZZzx9gje3TY7XMJqCIAOLD5ThysZ3l6++/Jh1NJjtncjhQIUfknZMRrZUztEHDjeO6N3C53dh4Ux5IsnMjX0QAjSZPUlYhFSFWp8CU0ZEYt3w6Wsx22F1sOhDA00URoZLB5nTh3qvTWEncx2ZnYd2cTBCEiKGvo23i3Y410fLCNOworfJQmZRWsWIChVSE6WlRCFdJmbUNLfrdanEw83pfFfoIGLwI5fkkQi1CGUe8EKkOjcpbp5vES15dxADw0lfl2LgoL7gDEyBAgB+63XIiCOJ2rtcpitrW98PpP/QV/YMvekpSHmgcSRHsVv74MAVuvyIZd7zxIyuZ0W514uWvy7Fo4kjUGmx45rOzKLkyBc/dNB4ON4kYrRzPfn6a2XmnKODl/eV4aOY43PV/KThdb2SCacATAP3pg2N45Vf5IAG0mZ2YOjoCTWYHCBCoabMgVutJinHtmo2KVGPlrAxs2HMKy65ORYxWjrgwBS40mXHzpCSYHZ5WyBVFaRgXpw3Y7ieg79BbW5eKRDDZXX4iI1IRvyDEZHPD7pOgWz83GyY7v7ZYo83NJIYBj42u/vgE3rqTn3CB0ermFNR7m6fwQVKEGmmxGtYmSVqsBkkRwiKxOwSyvZkZsfj8VD3r9TWzsyARieBwufDMwjy4KRJahRS/+8dh1m/3/N4y/OG6sYwSOf3aq7cXQEQQ+KmqFQsmJmLXkRqMjFTht28f9vvtt/66wM8m1u8+iWVXp6Kswci5wRcXpsDyolQkRagQH6ZAkl41gHdSQF9DLmUrZculwZ2D6gxuZlMEoP3ccWy7azKSIgZ+PAarE7/MTWAlDFfOGgeDNTicgP0Vs4UC+tNWRSICZgfJVHABnT6VFu5ct/skXrw1H29860mgPXFjDlJj1IjWyiGTeDZ5N/73DG6elITFk5NYonN010WrxYHX7yhAhEqKFUUezn+9Sob5+YlMcmDnoWrYXCRO1nrER8VNwC9zE1BvsPiN7YFr0mCwuSEigEnJEVBKJUwFM/255744ix0lU1nfl04Ina3n9vMHypvw2oEKZp76RGgb5g2JWASD1cUqTlkzOwsjI1Ss5LpIRGBUpBqn64ys5/n+a9KhV0pgc5EobzAic0SYn4bKY7s8sd+v3/ghoL1u2leGN++cjCajDX+clYG/7jnFUFBsWJCLrPgwiEQExsXpAib/L6fQR0DoINTnk3pj4HghOSrIg+MBs92FWycns7pO7r8mHSZ7aHAmA6G9uSBAQE/Apx9hktffCgBFAA4DCKnkcH/tCvdUUTvQON5eOhkbbxqP03WeIFktE/sJPazffRJLp6WgstkKW4e419Gadjz92Rk8OHMcag1WiAkCpZUGlFYaWNclKRIkRYCkuAVF2qwuVlu1d2XehgW5IEmK0wnSlSiZ8VocrmrDox3ieXTbFt3uBQD/LpkiBFkDgN7autHGLTKSnRDG6/oOF+UnULjqo+N4445J3RzpQaPJzmmjTSY7z+O5OY8beXIei0QECsfGIiVKIywSe4hAtvdOyVS/19fuOoFXfjURUrEYy/71E+69OhViEbd/0imkiA9TML7E5iTRYnawfNaq4kxUNHDzRV9q4174xekUaDLbOTf4ItUyJqEcagsJAWxcaDbj5a/KmTZ6lVyCl78qR0pU8FoE69u5/Vx9Oz8/19eIUMlw379+Yj2jG/acxj+WTgnKeIZrJV9/2ypJUgFFZ+mkrc1J4kh1G+bnJ+LFL8vxpw+O4YWbJ6DZ5MCb317AY3OysLggCVan2y9WeO6Ls0zSjgCBSaMi0GZxQiETsfhlaVqJVovTbyM6byQ71tCrZIjQKLDxi8748pmFeZzfweLo3IT2TgjdPT0lIAUbbVufdNjWULavvoTF4eYUT3zjjkn4ZPl0VtzE9Tw/98VZbLp5AtosdkglYvxwgVu/5EIz97zuba9WhwsZ8WEw2hxYOycbh6ta4SY9mxhSsafzsSvO0J4W+ggILYT6fBIoXmgIUrzQUyhl3Jt523gW7QQbob65IEBAT9BtKSBFUfd5/fcbABMAyPp/aH2LrnaFSZJCRaMJ351rQkWjCSRJBTiLP3qqqB1oHLUGGx5452ds2luO1w5UYES4MmAw5C3EoZCKUDJjDP7yySl8crQWERqpn6CNQiqCVOQRlqMFRXzfP9do8ksGzs9PhM3p4eK80GxmPu97vwCApMAkhulzbNrnOQd9DSHI4o/e2GRXts4HFmcAkTCelb+0cKHv8b5ih4FAcxZ7QyEVIVrLn7OY63itoufcXBT/2z5s4W2rXIs4vUqGC82WgDZxyeChiiAIMEJ13lBIRahqtTC+hH7N12et330SqbEazuNjdNw2VdVqgUREcCqjP+az6H3gnZ9ZfrA396mnz7SA3sFgdWBhB5/uyveP4eH3jmDhxCS0W/n5pP5AID8Xw9PP9TWazNyLz2ZzcO5Rb+exUEV/2+qFZjOiNDJO26PnO4VUBDcJVvLN5vIs5m+bkgSVTIxN+8oCFhvQcWp8mMLjY8UEpGL/gocms8Mvufj83jJGEJTGooJE/PlDdnxZ1mDk/A6xus440zshtPNQtZ+fX16YhvcPVzPnHOq21ddoMXPHei1mB1KiNax1UKDnWSkVQauQYe2uEwHnf5WMO6bzttfkSDXGxGigU8pwz9uH8G6p53ednZeAM3XtqGoxM92PU1Oi/MZHF/p424dAKzJ0EOrzSWyAGDZY8UJP0dyFrwgFXGg2Y8OeU1g6LQXLClNx9/QUbNhzqldrAgECBisuh6zGAiCtrwfS36B3hb2hkIoQrVFgz4k63LDpAG559XvcsOkA9pyo63GCOFDAwXccZQ3sREdFo4nzcyICWDc3G3qlFMsKU/H32/Kx44cq1BpsuHvGGGz8/AzWFGf5BcAVTWZs+focRkWqsaKIHSCvnZPFBFI0fHfl6QmU3j3zvV/NARaW9CJBCLL4I9A95muTgWyMb3I+XMW9wRCu4pdcDZjc5SlIZ3a4/Gx4TXEWLA5+7UdyKeFn4yuK0iDj2Zrb2/s/nOB7r45cbPP77RcVJOJcAH9W0WTGO6WeRbuY6BSq803UvltazQgKer/mDZuTRJvZwZkAuNhsxqriTL/X3y2tRrhShn2n67BlyUQsK0xFyYwURGvkDI2F9/kvdyEh2FRwQZLwS/Y/tusE3GQ3B/Yj1HIx1s7J8puL1XJ+3Ox9DaVUzPmM+r42UOjtPBaq6G9brW+34WKLxW+OXVHkSZTSvnH30RpW8k2rkMDm9FCXGW1OZnyB4tTNt07AyVojbth0ACXbD+NHjqrQQMllm9PNGlt6jNbvc++UVuPJG3O6TOZ5J4RqDTZsP1iJpdNS8MqSiSiZkYLtBzuFTYeDbfU1onsQ6wV6nkkAp+rau0zgv7r/nN/r3vb67CI2PYReJcOSqcnY+k0FNu8rxyv7K3C4qq3L+banhT4CQguhPp+4STdnvECCX9FOsKGRc2/wqENEUK/ZbMfigiTGp7x2oAKLC5LQYg6Nym0BAnoCPpzDuwDQM6oIQCaAd/pzUP2BQPQPYhEGtNWEaxxP3piDpz87w/rcO6XVWDcniyXKtao4E2abE3qVFFUtFuw6UoPJo/Q42+Cp3rU6XCitNMDhqsRTC/PgcLkRrZXDZHMhXCXF5i/L8fHPNfhtYSpe/tVEWB1uNBntaLU4/Ko6fXfluxNt2FEylbMla3pqFG4cnwCxCPj+fLPA08MDvW1/6inViS9iNAo8fN1YPP3ZGeb4h68bi2ieQZTZ7vITKFxemMY7uauWSfDlmQt+IjV3T0vldbyIECFcKWFxNoYrJRDz3AsL9fazgYTvvXqntNpPzC89RosnPjnlZxPr52Zj43/PMov2269IRsmMMdiy/xyWTkuBWASMi9Ph5a/K0WpxIDVGi2WFqaAowGxzsnxWfJgCiwoSIRJ5EhMritJgdrhBUcCO0iqsmZ2F8nojpyBNVasFS6eNQYRahmmpkYjRKkB1VDD1VYupYFPBRUMAqppGnlQ1/QE3SWFEuBxv3DEJjSY7ojVyuEg33EHaMNDIJZxCnMFSQ+/tPBaq6Gtb9eVJjNLI0Wx24M3/VXjEBx0ujNQrQYLCnb9IRly4ClXNZvzx+gz8/ctyxg5cbs9vkKBXIk7rSbTQyTxvv766OBNjY7UIV8nwyxcOMN+F5PCpdCebr58dE61hcf9y+eNWiwP5SeFdcgT7UgXUGmzY+k0F9qyYDjdJMXPIcLGtvobT7caa4iys3e3FOVycBSfpn7Diep4fuDYdZpuLsQ3vBH6YQoyx8TocuWjAjLEx2He6Dq8smYhDla3IGRGGWoMVa+dkISVKzSrKidV5YgHaJgHP8/PoB8cwfmR4l/Mtl66KgKGBUJ9PRIQIhy404fU7JqHJZEeURo4PD1dhVGRSsIfGC1q5mDu+kAVnM7ynkIlFfj5l074yP457AQKGAvhE/c94/e0CUEngLBSsAACgk0lEQVRRVHWgDw9W0LvCvnxT359vDthq0h8BAtc4CMAvOdtqccBsdzE8xG4S2LL/HG6elITVH51Aq8WBx+dlY3S0Cn9bPB4na9sRH+YJhI/WtGP5v34C4Am4nrtpPJqNNjxxYzYa2u24fesPrKTdvtN1fgEezTnsO4EGas2xONycE+/EJL2fEJXA09M1eiuMEcjW+d7v5Eg1kiNVrORqcqQKyTyDKJFIhB2lVYwqLZ2ge3xeDq/jxSIS12TE4/+xVHmzIBbzK52y2F1+bakOFwWrk19yWhAm4Q/fe1VrsGHbd5V4687JoEAxC/tWi4NZ9NFq8yP1Ssbv1Rps2LDnDJIjlfjjrAzYXG6cbzJj/e6TaLU48NjsLDz7+WlUNnsoKJ5amIvHZmfhsV0noFfJ/LgsVxR5+M5bLQ6sKErzLCCj1CitbGXxCNOq5n8uzkBmh2gNALhcJB6fl8367OPzsi9blE6wqeCCrlrxTUIFs2qlzepAvcHO2gBeNycLFD9q9z4HRZEYEa5g+f0R4QpQVHDKq3s7j4Uq+tJWfXkSkyOVeHDmWMjFIhSOi2PEB5MjlVh53TioFVKWIOHq4kwYrE5s+64St01JwoqiNCSEK5EU0Zlo2X6wEiUzUpCkV6Gu3YZX9p/DG3dM9vN5XInknMQwPLtoPB58tzM+fHbReIzpSPbRvpEkKc74MilCzfqcLwIlhJIi1EiKUA872+pzUAR2Hq5iNhmUMgm2fVuB318z1u+jvs+ziCBw6lI76o02pmNo074y1Bps2H20BvdeleoTA2ajsd0KNwk8/slJrJyVgWsyYv1+s1GRas5Kc2G+Hd4I9flEJROjYFQU7nrzR1a8oAyR5Krd5UZ8GDu+iA9TwOEOjcpni8MdMPchQMBQQ7fRJkVRX9N/EwQRBaC5X0fUj+DaFQ6GCIHvOC40mfx21JYXpmHLgfMAPG3Z40eGQSwCtn3X2Qb35w+PY8dvpuL3OzyBb26Czi/Ju6o4E3//qhwGmxOPz8vBnz5gC4Vt2leGpxbmYdu3FdiyZCJq22wwO1zIiNdh/Mhwv0rfQPcrVqfAlNGRfhOvUDHXc/SFTfamAqK3gmwamRg3T0q67B1ikhQxCROAVuU9ge08hQvUcgle//Y8inMTQBCAmwRe//Y8Nt40ntfxgjAJf3Ddq1aLA9FaOefC/sWOSrT1c7PxzOensao4k6V0v7ggCX/dcwov3pKPGK0caTFaVLda8M/vK5nfU0QAzUY7PvipBq8smQij1YWHOhIaQCdv5dML81DWYERarIZJIgDgrB4eF6tj2XdVqwUv7CtjbXC8sK8M+Un6y3qmBJsKLnQK7qpY3WXwkPcVlFIJVn982M/PBUugJVylwCv7z+G2qaPRZnEiXOXp2Fg5Kyso4wGGZyVfX9qqb/xVnJuAP7x3FK8uKfDbwK1rt+Gpjm4hwGOP6zpEkFstDoyKVEMhEzG+dFZWHMbeNx2n6tpxtt6IZ/97Fq0WB6uYwLdqd0dpFXaUTIXV6WbiCgDIiO86YXO5iZ3ujhtuttXX0MglKMqIY20odNVt4P08VzSa8Pq353HzpCSsKErH83vPMh1DU0ZHYOlbpT6+8TieWZiHjHgprsucgOyE8IAi2RnxOmG+FeCHUJ5P7C6Kc130dpAEY3sKiUiMtw9e8Aitem0kPXJ9ZrCHxgtd5T4ECBhqCBhtEgQxFcBfAbQAWA9gO4AoACKCIG6nKGrPwAyxfzEYWk3oarul01Igl4iQGqPBhj2nUGuwQSEVYVycDuEqKTbtLWcdZ3OSqPWqzjha0w78UInnbhoPh5vEuUYTNu8rZ6rnfqpq49z5Km8w4s7/G4OkCBVkEhEraL/QbGbRQXR1v7gmXqFirucYDDbZmyDK5HAiTsfeIY7TKWB2OHkd32ZxctpMm4Xn8VYH7p6WgkaTHSQFSETA3dNSeAv6DIb7Hyrgc6/oBXrknZNxoLwJFOXh7/JQ4FCs7ogdpVVYOSsDmSM85ZP7ztQDAM42mHC0pp2p4H1hXxkqm604U9uOMKWM017EImBuXgJGR3UmA5Ii1BgXp/Mb7+go9m9b325DZbMVL37J9rmX67cEmwouSIrirFqhgqg42ZWYUzAwOkqNeROSWNV6XM+GgP5FX9qqb/ylVYixdFoKGox2/HFWBv665xTTjbF+bnZAP/rkjTnITtCxNtlEIgJjYjQYHaVGZrwOvxgTyUq+cvm8lbMykMOR1OMTa1xuTBLKCaHBDgdJQiUVs2xVJRXDSXbfbeDRP0nHox8cww1ZsXh8bjYMVhfMdhdqDdzrBidJ4o1vzuPRX2Z0uTEwOkqYbwUMLbQE0PVpDRHOW4PNwepWoYvg2m2hIUgnxPAChhO6KkXYDOBRAGEA9gG4nqKogwRBjAPwLwBDIjl8uRUJvjxuXR3T3WdjdQrIJJ5/O9wkzjeZsPT/RiM+XAmdQopYnRxuN+W3a5UcqUS0Ro7lRalQycRwuSlIxATcJAWSpHBlWjSmp0VBJRXD6nTD4nBz7nylx2ghlxJMq92FZjMOVbWgts2GP+w86kcH0ZP7Re+26VUyzM9PBEF4eObihN22gAj19iedQo6vT9fjmqwENHaM/78najB7/Ehex8eGBdqh5SdoF6NVoN7AFg6TiMCbM1kkIlCYFo3td01GXbsdcTo5crwoBwR0gq+tkiQFsYjASL0SepUM4WoJNizIgUomwRcnanFVRhysDhc2LhqPvMRwkCSFE7UGkCSF6alRmJisR5PJjoRwFdKjPJtULRYHjDYXqprNnPYiAoHzzSZWcovveGN1CiRHKplqZcAjlne5lUeh/kyHOsKUMnxbfgHz8pPQ1MHv+8HhKuQmpgdtTNEaOaeNRfEU7uxriEQErk6Nwra7JqO+3Y5YnRw5cTrBRgcYfWmr3tVOV6dHIVqrwN++OMbEdE8tzEWcToE2iwNSsQjJkUqWEKdCKkJGnA5SCYHEcBVnHEsnX+lOMe9igr7weS4XiRO1BtQabIgPUyIrXgeJJDgiiQLYiFTLObu03rij++4HkYjAxORw/OPuSRBBBIPNBYvDhSazHWKC4JzTrQ4XrhoXA4vDjYpGU0B7EuZbAUMNURo55zMRoQ5OvNBTRKoVuNB0ycOZbLQjWuuZ1/4vNTLYQ+MFwacIGE7oKjksoSjqcwAgCGIdRVEHAYCiqNME0f3DQBDE6wCKATRQFJXd8VoegJcBaABcAHAbRVHtXsckATgJ4DGKop7peG0igDcBKAF8AmAF1cflPj2tLPDlceuKR7e7z5IkBQLAsqvTsPnLMhTnJsDuIpERr8JLX5ahtNKA5EglHpo5Fg9cm46N/z3LcMTdc2Uqbtv6PcO5+e6hi1hckISnPz+N4twEnG82oyBZj9o2K/6w8xj0Kplfu+L916TjiU9OISFcDr1KhppWK841mqBVSPDM52f96CDG3jcdY2I0rPtFkhQqGk2sRQMAZiHx5h2TcLTGwIxdIRVhbBy7CkUAG8GudunJ5ocv0qJUGBuvxx1vdHJbr5+bjTSeFWhhCjGeWpCD8kYzSMqzmTAmWo0wJb+2WqVUjDarC1v2V7BaHZVSfrQWDocbHx+vxeqPOvlm183NxrzcEZCFCL/XQKI7W3W5SHx4pIbh702OVOKx2Vkw2VxoNTtw1bgYVjXBEzfmQC4R4aF3j3DyCa+bk40Xv/L4yq3fVECvkuH+a9Lx3BdnWb93q8WOEXoVPjtRhxHhnUkFPs9Wkl6F+wrTWJzD6+dmg4Dn2bgcvxXsZ3o4IzFMickp0Sy+vsfnZSMxTBm0MWkUIvzuqlSs8eIcXjsnC1pFcBJfNpsLu47XYfXHx1nP2pyceCiCSL8x3NCXtkpXO73+zTn86opRuPefnTQm6TEaGG0u/OG9znl6zewsvPx1OVNN/NDMsVi3+yRkEgLq+RJ8V9EMkvJsYqyclYFZWXEAgKoWMw5XteHRD475xbm+Pq8nsYXv3EHfi3l5Cf2SIO5N3DMcMSpSjZWzMnhV0/ne2yS9CvXtVtQZHKhps+L5vWXQq2RYVJCI0ZFqbLp5Ap745CRji49ePw5SsZgV13WlXyLMtwKGErQKETYsyME5r3VRSrQaOmVobJSlR6lRMCrahzM5G+lRofN8Cj5FwHBBVxG/d/+C1ec9PsnZN+GpPt7m9dprAB6iKOprgiDuAvAwgFVe7z8H4FOf8/wdQAmAg/Akh2dxfGZA0RMe3a4+OypSjT0n6nC6rh0f/VyDxQVJLLGOVcWZqGmzozg3AQ+/dxQritKY9q30WC2e/fw0lk5LQZJeiUsGK26elIR//1jld54VRWnQq2QMfUXJjBSM1KtwsdUChUSEcbEazMyKx22vfc8c88zCPM4WlqoWM8bEsAN9ruS3TEJg2T9/gs1JYnlRKhPQBbpfQlA+eNCTzQ8unKw3YdVHbG7rVR8dx+goNQpGRXR7fLPZibp2O2sR8MC16Ug0O5Ec1f3469ptTDKRvv7ze8uQmxiGMTHabo8/dsnAJIbp41d/dBxjotSYyGP8Atg4ccnALO7jwxRYXJCE3/7jMKd/sjlJ/OmDYyiZkQKbk8T8/ES/33L1x8fx0Mx0aOVSD7WOwQaSolhcwtu+83AJl8xIwaa95aykgkhEcPoabx+kkomZMdPXXfXRcZTMSMG4OJ0gqBliOF3f7vd7/vnD40iP0SB3pD4oY2oyOZnEMD2mNR+fwOu/LgjKeI7VGpjEMD2e1R8fx+goFSaNDo3qnqGAvrRVutopRivH/rJG5pzxYQrcc1WqX2y6dtcJbP11AVrMTjQabUiKVCFaI8Os7Hjc6bWoX16Yhg17TiEjToujNQacazR1G+MBPY8tTtQaOO9FWowGeX383PY27hmO6EnnkK8w4to52bA53RARBJMYXjI12W8NZLQ5YbS50W5z4clPT/NadwkQMNRgsLpRz7EuSggP3gZ3T3Ci3sgZX6RE81sXChAgYODQ1ZZTHkEQ7QRBGAHkdvxN/zunuxNTFLUfHr5ib4wFsL/j7/8CWEC/QRDEPAAVAE54vRYPQEdR1Hcd1cLbAMzr9lv1M7ri0e3JZ+nEMUl5hELooIj+zPrdJ3HblCSMi9Pi7ukpSNSr8NXpBlAUQJEkSmaMwdZvKrDy/WN4ZX8FdEopFk0c6Xee5/eWYX5+IgAPv/GmveUgALxbWo2/7DmNO6aNZkTs6GNAeFpWvKGQiiDuSKLQCJT8PlptYF4jKXR5v+jA8YZNB3DLq9/jhk0HsOdEHes6AgYOgX7TC81mXsc3Grm5sRqN/LixTHYXU2VOH7vxv2dhsrt4HW+xB1CVtfNTla0N8MzWtfs/3wK6R43BytzP+fmJnP7ptilJzOdtThL0o08Q3L4jWquAUibCiqJUxIcpYHa4sWlvOTbvK8eLX5YziWb6PHRS4cQlA6evcblI1ut7TzdwXpek0KNnQcDgwKUAHJaXDMF7pk02F+eYjLbgqF/XtXP77fr20OA0HCroa1sViQg0dfDv0zHd/PxEnK5r57zOdxUtePi9IwhTyWB1OHH3jDF+PnvTPk/nxsVWC1buPNptjEejp7FFIO7Zun54bnsb9wxX0NV0U1OikBKtYTZaKxpN+O5cEyoaTTjf1Hlv6Q3ie94+hHvePoyzDUZmI5hrDWS0ufHil+WwuUje6y4BAoYaLA4357rI4ghOvNBT1AXy5cK6SoCAQYeAyWGKosQURekoitJSFCXp+Jv+t/Qyr3ccwJyOvxcBGAkABEGoAawEsNbn8wkAqr3+Xd3xGicIgighCKKUIIjSxsbGyxxi96B53LwRSAm3q896J47FIu7gOkGvxMPvHcHmfeV45vPTuGVKMrZ+U4GzDWas333SL5CK1so5z+PNBKKQitBosmN+fiJsTpJTAKy61YIVRWnM2OkKv9O17axgOVDy2zev29X9Go5B+UDZ6uWgJ5sfXAhTSTh/bx1PWgibkzu56/ta4OtLOa8fpuTntiLVMs7jI9QyXscPJfSFndJcaZ7zcfu5OJ0C8WEef6CQiqCWiREfpsDYWC3nb3Gu0YQz9Wa8sr8Ct1+RDKVUxPk5bwIim9Mj4Mnla07UGliveydSfM8nLEgHJ7qyVZVMzPl7qoJIE6OWc/tJtTw4Y4rVyQPM06HBaRhKGGhbjdHKsetIDZYXemI6gujex/3pg2NQy2SQibl9tljETt7yiYnp2CI+TIF7r07FssJU3D09BS0+okp0clGn5H5GIjXyPi8e6G3cM1TR0xiAq9jjVG3nRoRvEpi2w0Cxge/axRuB1l0ChicG87qqt7AGWhc5+K2Lgo1IDfe6KlJYVwV7OAIE+KFLshqCIEQEQRzvw+vdBeBegiAOAdACoGUq1wJ4jqIok+8QOM4RMCKkKGoLRVEFFEUVREdH98mAuUDzuHknTmmeLd8d8yS9KuBn6cTxzkPVyEsM53Sc55vMzIRQnJuAtbtOMAET10QRo+Ve4NFdXnSSVyUVQ6sQM0Jf3sfEhykgApAQ7lHMXlaYipIZKYjTKbD7aC0rWA6U/PbuKtt5qNov0ezNSzYcg/L+tlVfO+zJQqonmx9cUErEnBsLKp6cvxGBkrMqfsnddpuTWQTTxy4vTEO73cnreJVMjDWzs1jHr5mdFdREUrDQF3Yaq5Pj8XnZrPvpDYVUhKpWC+bnJzK2kjlCi9uvSMYzn5/GquJMv9/y3dJqxgc+v7cMqTFarJ/LvsYD16bj/cPVrOvIpWLoVZ5glE5Q3D09Be02F/M64PFZXDb0/uFqYUE6SNGVreoUEk6fpJUHj0tXIiY4xyQRB6eFXSamsG4O+xlaNycbQbxFQxYDaasuFwmT3YX7CtMgEQF/uj4Dk5L1rGQxfZ1VxZmMz7Q5Sfxc3YYIFXdMOSHJIxJKx7C+53ryxhw/7lla6HPJVE+Rw85D1VDLxGgwOvBNWSOO17TB4XAzycUH3znqdy+WF6bhwXd/7vPust7GPUMVPY0B6GIPvUrGzK/enYi+axfadsQBuhXptcSuIzVYO4cdlwXiNxYwPDFQOYBgQKfg3ijTKEJjXaKWc6+r1MK6KtjDESDAD11GmxRFkQRBHCEIIomiqKreXoyiqNMAZgIAQRDpAH7Z8dYUAAsJgngKQDgAkiAIG4CdABK9TpEI4FJvx9FbiEQEZmbEYkfJ1A4FZQWy4sMAgJOzbGZGLD7h4OSik8wPvPMz/nOkBk/cmIM/eQl6rCrOxOZ95cx1fYMqhdRfuVQpE2P93GyG85V2wEarA8sKU1l8nM8szMOKojQ0tFuxdk4W1nx8ghGA2vhFpzjEqAgV6tpt+Nves5g7PoEVLHt/B/p6m2+dAIVUjOVFqYx4iVomxmu/LoCYIPw4hb0Vtb2/i29QLvAS80NvufNGRarxypJ8GK1umO0uqBUSaBVi3kF4q8WBbd9VYum0FBBEJwfs2Fh+vHBtVqefwNj916SjzcYvuatTSLGjtIp1/R2lVXh6YR6v4yM0UkSoJHhmYR7MDhfUMgmkYs/rfCHYaidG6tWoabPgxVvzca7B6OeflhemYfvBSvzx+nFYdnUqtn1XiTWzMxmuYaPNyeIT3n7Q478oL8qIE5cM+EVKJF7+1UTYnG6oZGK021xotXj2H+nrPPbxcSwqSMS7pdUMv6FeJYOIAB6cmY76dhvePliFWoMNO0qr8E7JVFS1WnG23shct78XpILt9D3GRmtR1Wpl7EhEAAl6Jcbx4CDvL1AUBbVMzBqTWiZGH+vt8oabEuGd0ko8tTAPVocLSpkE276twCM3ZAZlPIAnsXmi1tARZ3WKSg5l9KWtkiSF/xyvxcqdR1lxpVYhwvKidGzaexZLp6VALAIy4nT4+1ceSh7A4zPdJFDZYsHywjQWF+yGBblIiVLhsY+PM+9tP+jRsxgdpUadwYb8pHA/vzUqUo2/zs/FdxXN+N1VqUiP1eAvn55iRMdWFKWh2exgYhdvnYzEcCUqW6zYfrAStQZbn/PNcsWyfMXV+tJHh7r/r2+3Qa+S4Z4ZKWi2OEBSwKVWCzPvA+y1Cz3XPnpDJlYVZzIdkXTcl5Ogg+TadNhdJMQEha2/LkCrxYmR4UpkjQgLqXsjQMDlQiIWsUTp6QIIaYjMh0opgTidDFuWTESrxQm9Sgo3SUIpC53nN9R9swABfMGnFCEewAmCIH4AwPT5UxQ1J/Ah3CAIIoaiqAaCIEQA/gzg5Y5zTff6zGMATBRFbe74t5EgiKkAvgdwO4AXenrdvgZJUvj8VL1fEJkZr+VsWf6kI4D1DWJpMYfMFdNxuKoNz3sF6uMTw1HdZmGSGzTooIrebfcVniMAbP6yDE8vzENZgxFuEjBYHfjrp2f8vofN5WYSxX//VT6eWpgHjUyM33UoWtP8xAqpCEunpaCy2Yq0GC0oynMPRCLCT5AiTqfAyVojlv2zlLUY2fFDFc42mJh74Y2ugnLaGTeb7bjUZmMtcgSxEG70RDCRCyRJodHo8FMIp3/z7qBRSNFqceDFLzs3Njw73PySq1q5FP/8gZ1c/ucPlXhqAb/kbrvN6SfKuLwwDUaeyeUWoxOvHqjA7b9IAeBR5nz1QAVW/TILfDRwBGEbNkQiApOTo/DF6XqYHG4kR0k5k73nGk1QSMSQSQgWh+Vb31b6CdXQCWXAY1vj4nRY+f5RLJo4Epu/LMfmW/NBACwbopMK6bFaLCpIZBLDXOfeUVqFlbMykJ0QjuyEcGTG6/CLMZEBBXd6ikBBpmA7/YM6kx1tZvZc2mZ2oM5kx2iedDN9DYWEu2JGHuD1/kazyY7SSgNKK3/yed0R4Ij+hctF4sMjNX7z0Ly8hCGdIO5LW73QbGZiJqCTfuyNOyZh096zKM5NAEF4qtLcFIWzDZ7mPW8/+ODMcdh+sJKJTYvGxiBMJcWlNhsen5uD5/eeYd4bF6fD69+cw13TxiApgjupWtNmY4kq0b681uARkl07J4tVKEDHocsKU1kxBd1d1lfJ4csVV+tLHz0U/H+sToE7f5EMi9PN+p0fvX4cdpRMRZPJ7pcEXlyQhMc+9sjN0HP22Fgtnvn8NNbPzYZERGB/RSNGRSZj6VulIXtvBAi4XJjtTsjFItamoVwsgpmnFkuw0W4lcbrOxBR90DkLnSI0aCWGgm8WIIAv+CSHfXmAeYEgiH8BuApAFEEQ1QDWANAQBHFvx0feB/AGj1P9FsCbAJQAPu34L6gIlHx7687JAekRAgWwIpEnEfJoR8UwHfzSjtM7AbzrSA2z+07vtm+8aTzKG0ywu0hs+64SI8IVuHlSEp75/DRKZozB+t0ncff0FM7K3PNNFqZKpMFgx8r3j2FZYWpA3i+FVITTdUY8/N4RllOkBSlSojWoaDT53Zv1u09i6bQUHK1p57wXgYJyoLMSe+m0FGz9pns1bAFd03TwuVe9VQg3WJ1+GxfLC9NgsPJLzpod3Mldi2NgKodr222cSZK6dhv4nMFbfAXotNWx903HmJjhaatVrRb8fkenIE2gZC9dmSsiOjfCag02piptpF4FtVyCDXtOodZgg0Iqwvq52Xj5q3JUNlsZ0Zqj1W1Ii9GyfAbgOWdGnA4qmRg2J7cIzqZ9ZdhRMhU5CZ2Vb1ybe5eLroLM3m7sCODGJYOVpXQPeGxha4wGo4N0X9ttTmiVUjR5JQK1SinvTay+hlYh5YwTtIrg8Er0dh4KVfSlrQaKBVrMDlQ2W1nJ1vnj4/HSbfn4+WIb3KRnzrxnRipe238OtQYb89n0WC0Wv3qQVUU8IlwBmVgEp5vEUwvHB0yqflvRjD9/eMzP3y6dluIRHXOSUMkknHbou/7uD8oH71g2EPrTRw8F/z8qUo1x8TqUbD/E+h5PfnoaW39dgCPVBrxbWo2l01KQFKFEXJgCqzvWNADw4peegpSSGSm4Z0YqLjSbsWlfGbYsKUDJ9tKQvjcCBFwu5BIxXv/2PLOh5yaB1789j7/Ozwn20HjB5nIziWGgkxJu668LgjwyfhgKvlmAAL7oNuqnKOrryzkxRVG3BHjr+W6Oe8zn36UAsi9nDP2FQAG3xeHiRY/A93zRGjle+LKMqcooSI7A1FERmJisR2WzGT9dbMP63SdZbYAXW6zQyiWYOz4BURo5SmakQCUT++3U+1beNZo6BUECBeb0MV05xUDfhU4uB7oXXEG5d6I5EMdyX1aODBXwpekIhK4UwvNGdn98mDJAcpZn5W+4UsZ5/MabxvM63uJwcSaXrQ5+O+zxYUrO+xcXxu/+VbaYOe9fVYt52CaHvf0Cnex9emEeztQbWVW9gOe5z4jXYkVRGhNMtlocSI5UY9Pes3C4KMzPTwRBeKonmkx2HK1ph0LqEVOi26Fr2vzboTfeNB6jo9SMPwrkV6xOd79VA3QVZPZ2Y0cAN4w2F+d9NdmCp/StlEnwj31luP0XKSwahz9clxGU8dhcLs5NPbsrOPeot/NQqKIvbTVQLECLA3m//smJetw2NRkz0qLRZLLj6rHR+OunJ3G0pp117Nl6I8t3rdx5lLMjzBcXms0orWwJGB/S569ts+AvN+bgES+KtY03jYdMQjBjDibfbH/66KHg/0UiAi43FdCGSQpMZ9mywlQYLA6/eG3dnCwkRiix8fMzmJIS7Xnuh8C9ESDgckEQBG6/YhSe/uwM85w8fN1YEERoVK1aHNyCehZ78GKwnmAo+GYBAvii2+RwB6XDCwAyAMgAiAGYKYrS9fPYBi0CBdxJEfw5y/icr67dhrnjEzBhZDiSI9VMNUZKtAajItWwdiRN6M+vnZOFl74qh8NFYVFBIkiSwqhINR794Bj0KhlKZqQgKUKFcKUU6/9zkqm8e3xeNv79QyXuvToVOrnYj/v48XnZaDTase27zgSOt1P0bpFWySRIjlQyu5uAh3NYRKDLe8HVZu3rjHuT8BxO6Al3Hhd6mxyN1clxz5WpjHgizXsdG8ZP9T47PgzLrk5j8dKun5uNnA5e7+4gEYmw73Qdw52pkknw1rcVyE3kd3xWvA6Pz8v2a2fO4nl9dYDKJ5Vs+Co7+fq4WoMN5Q1GvHbAv7I3NzEcdpcbYgJ4uuM31Ktk+PTYJdx7dRpWf3ScqS5aUZSGbd9Vstqg778mHf/8oRLFuQl4/7CnQik3QYe0WC3jQ5P0KmxZUoB2mzOgX+kJv1hPPttVkNnbjR0B3BgRzu3T4nn6pP6AUirGooIk/OG9I4yfWTsneMKXSqmY02/mJ4cHZTy9nYdCFX1pq1yxwIYFuVBIxH78lQ9fNxYECDjcJNJjtUjSq3DXtDE4fslzbHKkEo/NycaxagOWFaZi56FqJoHfYraDojwbo2qZBLE6OZIi2D6wvt0GkuKO4+hNvRVFaYgPV+K6jDjkjQz36yTj0u4YaPSnjx4q/j85Uh3Qhp/8tIbZhNp5qBqPz8vGut0nWMUAL35VjrnjEzA7NwFGuwvLi1IRp5MjOVKJymYr65yhdm8ECLgcKCViSEUEi1ZCKiKgDBINVU8RppRy5gbCeQqNBxtDxTcLEMAHRHfiJwRBlAK4GcC7AArg4f1Noyjq0f4f3uWjoKCAKi0t7Zdzd9UWDHgqJHoSwLpcJL6taEZpZQsj4La4IInhvQzEaeMt1hKlkeOdHy9gWnocqwrp2ZvGo9XsxMVWCwiCwJavz8Fgc2L93BxIxQRUMjFIisKFJise+eAoswhYOycbDheJWJ0cOoUU12864OcUP1k+HaMi1ax7UZAchpsmJWO1V2Jv3dxsTBmtx0g9970IdD/Hxmrxyxc81+VqRR/EfD89GlB/2CqdrLqchZTLReLTE7UoazCBpAAxAaTGaHB9VjwvrkeSpHCgvMEjaNch6KZVijE9NYbXGEiSwoGyBhhtXscrxJiexu/4s/VtOFVrwrlGMzP+lGg1MuI0SI8L53MLYLU6cayuHfXtdsTq5MiJ00HJk+/xfKMJe07U+XFrzcqKC1oLewAMmJ16P+O00GVqtAY6pRRrPj7OCBJtWJCLX2bHo7rNgvd/qmF4id8/XI1WiwOf/X46jDYXWi1O2JxuxGgVqDfa4HCSqG6zwOJwI0otA0UBL++vYDbAtt05GSaHC8kRaiRHqBjOeFqA0/u3okVEuXjlufxNT7nIKhpNuIGnPx3kfm4g0Stb7a1P6w9UNptQ1WKGRCRGo8mOaI0cLtKNpAg1kiMH3k+crW/Dz1XtWP1x56beujlZGD9Sx9tv9iVCmHN4UNkqW9TPI55c3WbB/rONaDJ7BMMiVFJEa+V4+L2jfn6wqtWCFrMdNT6aD3QnmUxC4IFrx7LeW1GUhtFRakRqZIhUyzEqUo0LzWbc+eYPTJWo9zwQrZWBIAho5BKMix3cooNDjHO4X2KAQN+Dnldf/+Yc0zExJlqNyhYL/vQBuxggUi1Fi8WJiy0WvFPqmf/pAhg6XhDmxmGFoK+rgomKxjZUttggJkRoMTsRoZbCTZFI1iuQEhMe7OF1iwtNJnxX0eJXNHRFSgRGRQ2qdREneuibedvqULNTASGFgHbKKzlMUVQBQRBHKYrK7XjtW4qiftHHg+xT9PcDx66WFcPhJpkguCeBCpfDefLGHGSN0MBoI9Fuc0CnkMHhIhEXxi1cRAfZY6I1qG2z4pNjtbhqXAyyR4TB6nBj5fudQfvq4kykxWogERGoarFi5c6jfny+gCdZsezq1A5xpwlwuKiAHJneiY57r07lPFdXbYeBkiV7VkzHyVojc93kSCWT1B7kSqEhHcSQJIVPj9fhwXc7f+9nF43H9dn8g/DeqMyfazDhrrd+8Nthfv3Xk3nRMhyrbsNPVa3MwldMAJFqGSYk6ZGTGN7t8Q6HGx8eveS3wTEvdwRkPKr6LjSZWAtvEQFEqWWYkR492IKgAbVTkqRQ2WzG8UvtKGswMr9NWqwWUjEBpVSMkXoVRupVuNBsxsm6dpxrMOHL0w24alwM0mO0yBqhw6k6I8sX0dXD3vQ6K4rSsGHPGSYAffnrzgWlL3dhfJgCiwoSWR0avn6NPi+XH+sq2cvl87oLMnuzsTOE0Stb9fi0Wjz47hEvn5aH67Pjg3Zvz9Ub8cOFZtS225lnIU4nx+RRkRgTqx3w8ZReaMGvtn7vZ8dvL52CglERAz4eoHMeqTPYENeR2BzMicMODApbdblInLhkQFWrFQQBbPn6HM42mLDxpvG4ZmwMPjtVh7IGE1QyMVJjtFjWIURMQyEV4a07JyNaKwdFgdmo936/ZEYKCpIjsOqjY37z9dzxCXCTwNZvKliJwQ17TuHmSUnQKaUsqrNQSvT1p48eYP/f6xigK3FVru/hcpH4z/Fa1mbC4/OyMSpSBaPNBbPdDY1CjDUfn2DmbG9NgleXFMBkdyEtxkNDFwr2IqBPENLrqt7i5KU2nK03oaKps+hldJQa6bEaZI4ID/bwusWRi61YvOWg3xyyo2RqyGgI9MA3C8lhAaGAgHbKp8/ZQhCEDMDPBEE8BaAWwMATfQ0yiEQERkWqcbrOiDvf/PGyA1wu/slHPziGl27Lx9pdJ/y4uHyFi/QqGauiNjlSiQdnjkV5gwmtZgcuGazQq2RM+9+63SexoigNJrubSeIG4t2M0ymgV8mw7J8/Yc+K6Zwtfb4t0lqFmGkPA8C0HnbFyxOozbqu3cZLPVpA3+JCs5lJDAOe3+LBd39GRjw/4n2SpHhXXXKh1mDh5AyuNVh4JYctAbiFA73ui2OXDExiGPB8/9UfHceYKDUm8kiS1BpseO9QNe6eMQZWuwsquQSv7j+H9DjtYEsODyhEIgIEAVS3Wlgq5iuK0pAeq8HKnccgkxC4rzANf/7wOFPVe9e0FJxvMuGJT05hUUEicyzQKWrx1MI8nK03AvD4nFGRarxxRwHMdjee/vw004pqc5J+vJe1Bhs27S3Hv0umMPbdE36xnnKRBRLgpJ8NPqJIAnqGikYTk2wDaJ92BGNjtUgNQiIWAFqtDjjd7M15p5tCq9UR4Ij+RZ3BBr1KxvB5A55nqa7dFpTxAIBEIkLeSP2Q5hj2RV/YKlfV9V9uzEGz2Y7Tde2I1crx1rfnMSUlGiP1KhytbuP0YQfKm/DagQo8szDP7329SoYpoyNgtrvwx1kZ+OueU6xknqgjh790WgpO17UjIVyJmRmxGBenRaPRjl+/8QPrOz7wzs9I8BECHazoTx8dSv6/u41Oru9R1WphEsOA57d/YV8Za95fVJCIZVenocFow9sHq1iihd9faMFrByqwYUFuSNwjAQL6AmaHG+0+ot7tVicsjtDg7B0KGgKh5JsFCOgN+CSHlwAQAVgG4H4AIwEs6M9BhQp6q15J70JxOcyfL7ahODeBSZD5nr++3bOQe+SGDIazEABunpSEmlYrK/lC77rTznlkhAotJgezEBwZrsSKolS8U1rNqr6zOFx45IYMnK03ot5ox6TkCL/v5c3DEx+mgFYhxd++YCf1dpRWdcnL0xWXj+CMBx69Jd6/0GzGhj2nWJsEG/acwrg4La/jZRIxS5AO8AjSFSTzE7QDPIGUbwKSL2q72Kzgg/gwBa7PiWdxia4oSkOcbnhzU5EkhZo2K6di8TML8zA/PxEAmAXikqlsugc64cD125Q3GLF5XznTHdFssiEtVodDVW0sjsL4MAUy4nTYsCAHKpkENW0WvPWtpyLJ20f1hF/scrjIBL82sDgfYJ4932wOWnLYRVKcfspFdt3N1V8YEa7Ab69MYXVc/PbKFIwY4hy/gw19Yasnag1MYhjwJHLr2m2MP92yvwLr5mTB4nDB5Sa75ALWq2QAgOVFqSApz4YBANx+RTKWvlXKGWdu2leG524aD4vTBYvDApIC9p2uR6PJhsKxsQFjjDN1RjSa7CgcGzvoE8QCLm8NxPXbF+cmsOZ978KAVcWZ2PFDFSMiO2mUHhp5GioaPbQ8w3nDXcDwgctNcsYLTjfZ/cGDABFqfxFUhVTEzC8CBAgYPOg2OUxRVCVBEEoA8RRFrR2AMYUM+CTRvFuuYrQKiEVguN9O1hpxpq6d02G6SQSs6G0weo6//YpklDcYWZ9J1Kvw8HvsqhPvXXeF1KM2nRajxZ3/N4olSEK3Z7daHHj0+nGQScRMguu1AxWc1Z/egifz8xOZNkHva29ZUtClGFpvBdQE9C16S7zfbLbjrl+MRrOlM8lw1y9Go8Vs55UMM1idnJXDBpuz22MBwOGmOBOQr91ewOv4WK08wPfnJwjkJsF5/ZmZcbyOHwrwbTVN0nt4fi0OF6dPc5MkxsVpYbG7cPf0FKhlYr97uGlfGZ5emBfQX9KfW7f7JJ67aTycbo+onffm1R2/GIX7fSgpfntlCkbolSx/0xOfJPivwQ+FVMxpNwpp8MRcnC4K//6RvQn27x+rkD2Cn/BlX4MA96aakKIbWPSFrfpWac3PT8Tze8tYleE1bVaoZWI4SQoHzzUyImG+SbklU5PxkNdG5/LCNEhEwMYv/P0zHWd6XqfQ0G73s6fUaE3AGKO6zYpmswOp0Roh6RcCuJxCghgt+7f3bNhqcff0FIyN1eKZz0+z7Gp9x3x+scWM5YUeQdrFBUn48OcaJEeq/YQPBQgYigi0ruC7rgk27C4X/nJjDs43d9JijIpUw+Hm19EpQICAgUO3yWGCIGYDeAaADMBogiDGA1hHUdScfh7boEd3STSulis6AUu3R+tVMqwqzmRxr62fm43NX5Zhdl4C5/klIgKNRjuiNHLE6uQoSA5DaaUB8WEKEOBOKNO77nR1R6D27GcX5eFkrRHtNhc2f8kO0rgqArxbpM/WGzmvLRUTXQZv3bVZCxhY9DbZpZSIYXH6JxkUPFV1w5RSv4r5TfvKsO3OybyOtwZIQPJtvxKLCDx6/Tg/zmIxT3tsMHIvmBpNNl60GKEOLr+3ZUkBHnjnZ2y+ZYKfT0uOVMLiJLF21zHm82tmZzF0ODRsThJ2lxsPXJvO2tSifZr3507VtaNwbAxyEsOwoigNz+8tw/z8RDz3xVk/n1cyIwXj4nW40Gxm/E5PfJLgvwY/9Cqpn908cG069EFUynZTbs5NMDcVnEogk8PNufjMCZHF51BBX9hqfJiS5WcJApxVmauLM/HCvjKGFmJFURpG6lUAPIm/mVlxnHPxS7fmB4wzAU+sqZZL/Ozp3z9WYWKSHoQI2LAgl1PgrtXiQH6SXkgOhwB6WkhAkhTON5uYOZmmjvLdfKAr0IHO+TwjTod1u08ylelLp6Xg0Q+OISFciWhtz/VeBAgIJZgCrGvM9tCglVDLpDhlMrHWhQ9cm47kSFWwhyZAgAAf8KGVeAzAZABfAQBFUT8TBDGq/4YUOuguicbVcvX8Xk9QIxF5Aqpagw1fnKjDi7fm40h1G9wksOPHStx7VRpe/KrMr5rj4evG4mKLFY980JlIWT83G3f8goDRTqK61cIZrOUnhWPldWNhdrixYGIi0mK0nMmXU3VGvPhlOZYVpnJORJUdCRT6+3mLUFABWhP5VJwKbdaDB71NdhlsTs4kQ14iv4o4k82J9BiNH2ev2cGvclirkHDaoUbOLzndanHA2tF6Sz9j91+TjjaeXKC9rbwOdXD5vdLKFuhVMhjtLjx83Vg8/dkZ5t4+cn0Gfr+D/fm1u06gZEYKNu0tZ86rkIrQaLQja4QOf//VRFgdLuhVMvzx/aNMN8b8/ESIRUBajBbNFjtEIDAtNQpTRkXgUgDOM5IC9pc1+XVH9MQnCf5rcCM9WouKJjNKZqQwIpFxYQqkRweHUgIAVLIAm2B38dsE62uYbNyLT6NNqOwZSPSFrWbF6/D4vGyGWkJMAIsKEv3sbd3uk9i4KA9uisJf5ueg1mBjJer+Mj8nwEanPSANBS2qrJaJWTFmfJgCiwuScHsH13BypBKv/GoifqxsBUWBlRDk0gcIJHwmIHjoaSHBhWYzlv3zJ1wxOgIv3ZoPi8PN2BvgX4EOeOwpLUbLotuhNyJsThLfn2/BS1+Vh5SgoQABPYUuwLpGqwhe91NPYLa7mA1PwPPsbvzvWbx6+8Qgj0yAAAG+4JMcdlEUZSAIYcL1RXdJtEAtV3KJCGkxGsbRZyaE414fpehGUxkenjkO1W0WPLMwDyCAiy0WJEeosOxfPzFt0vPzE3Gx1YKCZD3e/PYsZucmMLvy3omtl74sw4L8JGzwSsrQVczePMOUF90h10T008U2WJ0kZBICy/75EysgzIjT+l17RVEaxINeXFyAL3qT7DLbuZMMJp473JEaOW6Zkszi7F0zOwsRan60DmqZBGtmZ2HtrhOs4zVyPu4O0CmkfhWmz31xFtt5Jm2S9CrWwpxW407SD48dci6/R1Ke5MQj7x/ziFxenYpojRzqjt+Ey16S9CrGB9G/oUxCoGT7Iea1pxbm4rYpyfjH95V+VZirijOxeV85Wi0OrChKA0lRnD5NRHha9gJ1RwgIfVxss+IP7x31++2z7gsLWjW/0eYMkIzltwnW14gJQKcTzZNOR0DfoC9sVSIRYV5eApIjVDhQ3gSFVIwRYUpOe6tus+LJT04z8Zq3gPGFJjOnTTicJMccl4MWkw1Lp6Xg+b1ncfOkJPz2yhT8/esK1BpsmJ/PTk5XNltxqrYdrx2o8Dv/SJ+5sjvhMwHBQU8LCejYYFHBSPzun4dx9/QUTpuk1wy0TT75ySm0Whys6nJ6IyI1RgO9SibM3QKGNNQyCWdHiZrnuibYsDlJzmfd5ggNzmQBAoYTAnoVgiA+AXAvgOMEQdwKQEwQRBqA5QC+HaDxDXp0lUQLVEE4KkqNv+45xVQF+3ILx4cpUJybALPdBZPdjSc6AqNlV6fC7HAziWHfFkF6B1+vkjE8hiICICkKU1KisXb3Cc6W6k17PVzEa+dk4d3SKtx7dSp0crFf8O8dmJXMSGFVd4oIoMlsB0EATy/Mw/kmM+wuEtu+q8SEpHChRXAYQdPLyl2b080kdj3/9lSSvnXnJF7Ht9tc2HmoCk8tzGMqj9/6tgIjrxnL6/hGk50ziGky2XkdX9VqwQsd1S8EAVAU8MK+MuQn6YfFwoXL7+06UoMHrx3LdEs88/lZZnNrymg9p73Utdvw3E3jYba7UNVqQZvF4VeR/of3jmJFURoenDmOJcxpc3q4CukKpH//WIU/zsrA4/OycbHFgndKq5mksUoqxsv7K5jj+AovCggdVLVwi3xVtZiDlhzWKqTclUDy4FBdiETAhgU5ONfYyQmYEq0WNncHGH1lqxKJCM1mB9N98e+SKZz2NjZOy1yD7myjqzbfKa1m0Z4lRyrxx1kZcLhJ1LZZsaIoDVanG7mJ4Xj5qzKUVhqYc9Px5aKCRGzaWw4xh5goBXAWFEjE7ORib8WfBfQf+BYSkCQFlUyM5UWpgNeah8smrxgTiTFRGojFBLZ8fY4pYNm0z2NTig7R4uWFadiw5xQevSEDZ+qNvHUtBAgINTjcJCLUUjyzMA9muwtqhQQ2pwuOEBGkC1NxxzthyuBRewkQIIAbXW05vQngMwDbAWQDsAP4Z8dr6/t9ZCECrlY3wBPMNpvtfrxqK4rScKnNgspmK7YfrMTSaR4RBm/RJO+kb3KkEquKM1HeYEJmvA4gKCwvSkVCmBKXDFZWlcfpunYm+fLil+VM8iVCJUOEirs6Ly1Gi+cXj4dMIsI7P1bhxvyRrIXAS7fm4/ildthdJPYcr2XETHITwjA6Us2q7vQWtFtemIZ/HfYkYIZLO31fItgtlL25vkzsoTpZ9VHnxsL6udmQSfhlGRpNDpZwDuBRSG808aN1cLjdmJ2bgPIGI5PkmJ2bAIebX+WyXsWtqhvOU1W3vt2GymYrs8CmMVySjlytpitnZSBK47mvepUMt01JwohwJWQSESx2F1YXZ2KdF+/6iqI0fHqsFg9eNxan6tpBUoEFOs0Od0C+c4LobGf2FqJ7fF42RkYocaSqDS/vr2B1T3Tnr4L9bAroOdRyCQqSw3D7L1JYG0bBrLpptTj9aKOWF6ahzRqcyuFGkwNmO7ud32x3oYmn3xXQN+hLWx0R3sk93Grmtjer3Y1lhanYeagatQYbvJsEWy0OtFud2LgoDxKJCAaLk+VHlxem4d3SamzZX4Gl01JYyWGasmdsrBbLClOREa/zm1etTjfeLa1mbaRyFRTUt9s4Y4LhMqeGOnwrv/84ayySI5VQSDzUJReazMyG7bq52fjjzqOobLYyNtZocjDrnIw4HSpbzCjOTWCoSM7UG/HagQqkxWiQT1LCfCyAE6Ecu7VanLDY3fjzh50dkY9ePw5tluDECz1Fm8WJR2aNYwmVR6hkaAtSp5QAAQICI2C0SVHUOwRB/AfAagCz4EkS06QD9wLY2P/DG9wI1OrmTbmQHKnEliUFkIoJxGgVEIuAeqOHr807iestmkQH73RSgz5/cqQS916VyuJC9RZvIL04f32TzCuKUjkTXgSA+nYr4sNVmJUTj0ttnQnnymYrfvfPwyiZkYIDZxuweHISSzjPtwXRu+qE3uEfF6fjLWQmwINgt1D29voKqRgSMcHiTJSICfBVW4/VyfHbK1NYgnC/vTIFsTp+7c16pQxnnCY/QTy9kl9yVyvvHS3FcOcc9m41bTHbIRWLYHG4oZKJ8dTCXNS0WlmVYssL07DvdB2eu2k8yhpMkIoJJEeqcH1OPP6fF4XEquJMJEcqUdlsZa5FU+HQgpu+95yi4NfObHOS+POHx/Gf+6YjMUKNVouD+Xx3wotcz8aGBbn4ZXY8JDw3PwQMPORiAosKklibmWvnZEEuDt7CMEIlxZOlVazE2I7SKjy9MC8o44lSy3Cuwd9vjovl5zcF9A360la1cgkjrqqWe6otfe2tODcBW7+pwPLCNOworQI9xdM+12xzwk0BUQoJlndQmgH+/LC+FeY0ZQ8AvHagAiuK0vyqhDPidWi1OFgbqcmRSiilYnx3rolJ4MSHKXD7Fcl+FcZxuuExp4Y6fCu/VTIx7rkylRVjrZubjeRIJf7w3lFmjve1MYVUhAvNZmzYc4Y5Nz3P25wkVu48ipyEMGHDQIAfgr2u6i0iVTI///vkp6fxj6VTgjwyfojSyHCh2ewnSBelDp34IpQ3FwQI6Am6W806AZgByAFovP7rVhmDIIjXCYJoIAjiuNdreQRBfEcQxDGCIHYRBKHreP1agiAOdbx+iCCIQq9jJna8Xk4QxCZiEJEfB2p1O1ptYPGqlWwvRaxOgTExGoyK0mBScgQ23jQeCqnn9rdaHFBJxVh2dSqS9J28cL5JjeLcBKz++IRfcD4/PxGAp3X78XnZUEhFfse+U1qNFUVpzDWZhJdCjNgwJR5+7whW7jyGV/ZXYMnUZMSHKZhrpMVo8NurUpnEMP06ncymQVfq0X9PGBkeMhPvYEIgu7rQbA6J65vsLjzy/jFs2luOzfvKsWlvOR55/xhMdn7CRjKRCGaHG1v2V2DzvnK8sr8CZocbMhG/5JvJ4eYUxDM5+FUOp0ZpEKHytG9tWJCDZxbmIUIlRRpPahS6ctb7Wesu6TjUIBIRGBWpRoPRgcVbDuKWV7/Hwpe/Q4xW7vfbbNpXhikp0bj/nZ+RN9IjWqiQiP0+t373SayclcG6r2vnZGH30RrsPOTv31YUpeH9w9Wc7cw2J4lGkw2zsuLwyfLp+HfJFHyyfHq3/orr2Vi58yi+rWgG6SWYI2BwweIkscZn7lzz8QlYfOxiICEVE7h5UhK2fuPxc1u/qcDNk5IgDdJ8aQ7gN83O0FBDHyroS1ttMtsZcdVnPjuDe65MZdnb4oIkvH+4mvHDa4qzMDFZj4dmpmPjTeOxZf85PPnpGTz83hHUtXPTLdEbc+MTw/38b2qMBq/uP+epUHa6se07T7fcssJULJ2Wgr9/WY51c7OZ45IjlbivMI2ZM27YdAB7TtTB5aY4bTNEOqqHPXx1CPRquR912OqPjqOx3cHa/KXfo23s4evGQiUVs+xseaFnnqc/22C0QYAAXwR7XdVbNJm5/W+zOTQ6e8QEOAXpgrg/3yPQmws3bDrAmpuEuF/AUERXnMOz4KkO/hhAPkVRlh6e+00AmwFs83rtNQAPURT1NUEQdwF4GMAqAE0AZlMUdYkgiGx4qCsSOo75O4ASAAcBfAJPFfOnPRwLgMC7Ppe7GxRIcC4hTIllhakAwLTqtZjtEBFAfbsdZocLY2M02LNiOtPOXFZvRHKkGmqZGMmRShTnJiBJr8Td01NY7X7e18tN0OGeK8fATQHb7poEqZhAk8mGN++chEajg/XZWoMNnx6rxdZfF6DF7KF6sDpdkEvEWLnzMKtlz+5y4/YrkrFhzxkopCLE6hT4prwp4MKAhregnUIqQnIv7+9wRSC76kkLZW/ueW+v32RycAcxPNuTjXYX/v1jZ4UTAPz7xyrkJITxOt7q4BbEs/JMDl8y2nCxuR25I6NQb6QQo5PjaFUTLsVqkaLo/vv3VKRlqMDX5kQEmGCcEc9ssXL+NlqFGEunpcBodSFRr4IpgKhhRaMJm2+dALuThMnmgsXhwtOLcmGyuuEkKWy6eQLabU40Gu3ISdRhw4IcANxVxTFaRY+FFwM9G6WVLUgIV4IgEPCZE/xg8NBs5vZJLUFcWDUY7fj0WK2HG93hgkomwav7z2FMkKreLL30mwL6Bn1pqzKxCP/8oZKZS+1OF/5203g4SQqn64xM1xl9jbMNJgAUshJ0sDtIPDRzHMKVElidJFwkGVDQ8/F52TDZPRzuESoZ1HIJlDIRRCICCwsSEatVQCwikBmng9HugkIqRk2bBQabE5nxWmy7czKazHbEahV44F3/BM5Lt+UHjEm68rkCgguSpHC+yQyT3YUVRal4p9SzlrEEmN/NDhenjU0ZFYFfpESABAWrg8TGm8ZDJRXhbL0Rb3zLFtWO0ylQ0WgSbEIAC32xrgomlB2bIr7PBr1RMtjRYuEW4G0NEVoMgfdewHBCV33SfwKwiKKoE5dzYoqi9hMEMcrn5bEA9nf8/V94ksCrKIr6yeszJwAoCIKQA4gAoKMo6jsAIAhiG4B5uIzkcKCWkpkZsfj8VP1ltZoEah+vMVixeV85q2W6yeTAjxdaWW1x9PW/KmuA2eHGk58ewRWjI/C7q1KZyhFv6gj6/DYnidwEHW6ZkowH3u1sPVwzOwsRainO1hnRbHawxhYfpsD1OfFY+lYp67wSkYdj1Vfcbv3cbDx6/ViMi9fBbHexKCu8v6t3CyLNOexdKRnqrTzBQG9pCXp7z3t7/cRw7uNHhPM73uF2Y3FBkh83Il/O4KRIFef1kyKVvI63Ol3QqZS4/Y0fOlse52TB5uRX+QzwF2kZKuCyuSdvzIG+g6eZ9i93T0/x+22SI5XQKqT42xedv/dLt+Zz/oZjojU412DGc194KhCSI5V+/vLh68YiIUyOiy02rN11AnqVzK+duaeV3HRiV0QQnONyk8CpunY85OWPvZ85wQ8GFyPCuH1SMNvSozQyXJ8T78fbH6UJjkCLPoBgTLgyNNTQhwr60lbtLpJzLh0Xr8HWbyr8rkFRFNQyMRqNDqz+6Dj0KhlD58DlR9fNzcaYKBXONZrgFolhdbpxsc0KEQGMjlLjwJkGTEqJwpOfnsKSqaPwzOdnWLb+6PUZ+P58C57+7AxrfL5Ja7WMW+TW6aZww6YDgk8dhOCa8+g1gsXJnQRuMTs4ebH//NEx3DwpCXFhCvzti7MMH/Ga2VmQSQjm+M23TsDJWqMwzwrwQ6jTvUWoZZx0dxEhQssQSJBOFyKCdKG+uSBgaOLqmdejtqEp4PvxMVH48vOe19MG3HKiKGr65SaGu8BxAHM6/l4EYCTHZxYA+ImiKDs81cPVXu9Vo7OiuEcItOtzotZw2a0mXO3jK4o8Ah30uTbtK8ODM8fhZG27X1scff2j1QbmvRsnjvRrKaSpI3YdqcH6jha8u2eMYbVlebh/rXC4KERo5PjydAOWF3a2WS8qSORs544PV3nUpH04OVd9dBwGmxsl2w/B5iKx60gN63wMLYVMjBdumYB/3D0Fs7Li8NziPOxeNg1JEUp8frIOh6taQ7qVJxjoLS1Bb9unent9kgJniz/Fs/tGK5f62eOmfWXQyPkFETYHiQeuTWdd/4Fr02Fz8OtBNdvdfvQtqz8+AZOdfwUdSVKoaDThu3NNqGg0DfnWIy6be/SDY1hUkMiiuNl5qNrPj6ycleFHWbN29wmsKs5kfe6JG3NwscWTGNarZLj36lQ8NHOcn798+rMziA1TMf6x1mDDtu8qUTIjBS/cMgHP3TQeWSO0vBeL3u1kv9/xM1b7jGt5YRp2H61hieL5PnOBnsnzTYIfHAiIRQTWzM7ym78kQexpdJMYVK3yEpFnY8X7Hj183VhIfMlkBxDDzY8CfWurIoLgnEulYjHnHJ2fHI4xMRqs7hCTnZ/fGTd6+9EN83M6eGDLYHWSUMml+MfBC4ztukngb1+cxdz8RKzddQKLJo5kEsP0OJ7fWwanm8K27y4wVBN3T0/BjtIqFl2ZQiqCWu4/3lXFmVj10bGAPrcr2xmOdjXQ4Jrznt9bhifmZWNcnNbv93zg2nQk6pXYUVqFpxbmYXmRh3pk+8FKVDZ7dArON3mE6Ojzrd11As8vnoBXb5+IV28vgF4lE9YbAjgR6nRvVocbL39dzqLlefnr8pDp7CEocK7LQmXLht5c8EYobS4IGJqobWjC+N9tCvhfV4njrjDQJSF3AdhEEMRqeOgqWH1yBEFkAdgAYCb9Esc5AkZxBEGUwENBgaSkJNZ7gXZ9aDE139f57Ab5to8TIPD7HT8zFQ/0uQxWJ0iKm/eSFpKj37MGaLdKjlBi5awMRKg97dckSbGqgn0rf5cXpmHP8VosnZYCuUSEtBgN53nPN5kxUq/ifI+msfjrp6dQMmMMtuw/h6XTUiAWAePidHj5q3IcrWnHssJURGtlGB2twUi9Ch8eqcGfP/QsLpYXpQq7bRzoylZ7S0vQ2x3O3l6/ps3GcAt6K5An6lXIT+7++EZTAG4tk53X9evabXjjfxdY13/jfxeQFKHidXx9AG7FhnZ+1x9KVaJd2ak3Atlckl6FqlYL816twYbtBz22kRKlglQi5mxnr2y2wmhzsn5DqZhAtE7B6nS4e3oK53XrfMZTa7Bh095ybFiQgzUfn8Bbd07GSL2aF82D9yK31mDDv3+ownM3jcepuna4SY+oU8mMMdi8r5x1nPczF+j+nKprx+gooe21L9CVrVa1WPGv7ysZCgelTILX9p/Db2aMQd5IfTCGG5DDtY6nn+lrNJsdkBA+QqIEETROw6HkR30xULbaEoCnsr6de462Ot1ICOvUvfClMqP96LLCVEZErqbNikttVszOTcDL+ytY8W+r2dNKHK2Rc47DTXJXNtPanvRv7s1XTI/XaHNy8tM2GG0YFakOaDsAhqxd9Qf4xgC+CDTnNZrsQIe9ef+eu49cwt3TR2Pu+ARY7S5s2us/n5Id4rPer1W2WLDxv2dQ2WwV1hvDHP25rgo26trtqGy2ssQ76ddDAY0mB+RiESu+kItFaAwRzmR6c8F33riczYXL9akCBAwUBjQ5TFHUaXQkfgmCSAfwS/o9giASAXwA4HaKos51vFwNINHrFIkALnVx/i0AtgBAQUEBK4kcqKUkPkALH9/dIO/28YpGE1otbEdHX+NUbXvA63u/p5Jzt8/Fhinwwt6z+OP1mRCLgAh1Z4uGr/icXiWDzeXGbVOS0WS2QyuX4HQd9/VHR6khFXO3StOVnnSipjg3AQQBpMVosX73SdQabFBIRRgXq4XF4UZFowkmm5NJDAMISEcx3HfburJVoHe0BH3RPtW768v9FMgVUhFidXJex0dp5Jzjj1TzO14lEyMhXI6xcVpY7S6o5BIkhMuhkol5j5/z/vEc/1DipurOTmkEsrlGkx1pMVrWe7UGG7Z+U8EokP/x+rFYXpQKunhr56FqtFocMNrcjA0ppCI8szAPUqnIr9OB29a5f0OlTAKbk0SLxYFdRy9h5c6jTKC3YUEuRoQrEKmWsxYN3ovc+DAFpqfHoKzBhIJkPU7WtqM4NwFGm5PT99PPXKD7c7beiMx4XcjZxWBE1/O/HAabE2fqjExywWBzIlbL75nuD8Tq5Iy+AD2mXUdqgjamMKUU93mpoQMeG9125+SgjOdCsxkb9pxicc9v2HMK4+K0If+8DJStxuqUUEhFLE0JMQGMCFfgT7/MQHWrBW91cLbS9Di+MWhXsaFCKkJVixVbv6nAA9em47E5WThWYwDgsWU6Tg0U1+rVMqx8n139u2lfGd5eOgX/LpnCJHAuNJv9YooVRakB45yu5mAAQ2Z+HgjwjQF8EWjOU8skAAHW7xkfpsCfbsjA2QYjSMojvsVlt2qZGAabm3W+S21WFOcm4MUvy4X1xjBHf66rgo3BFi/0FGFKKZ745CQzfpICXv/2PJ5akBfsofFCX24uXK5PFSBgoDCg/YIEQcR0/F8E4M8AXu74dziA/wB4hKKo/9GfpyiqFoCRIIipBEEQAG4H8NHlXDtQS0lWfFiftZp0dY2cxDC/Niqu917df86/pbA4C/84eB43T07Gr7Z+j017y7Fp71k8tSAHy4tSGeG6+DAFU0W8ZX8FVr5/DC/sK4fZ4cbRi21YU+zfqvjq/nP4y6ensG5ONus9bwVghVTEJGpeO1CBsgYjs5hYNzcbT39+Gne9WYobNh3AhWYLKzDjaiMPpVaeUERftE85HG6UXmjB7qOXcOhCCxw9aF0aF6f2s6d1c7IxLo7f9a0Op5/NeNTO+XH+RqhlWFSQhD+8dwQr3z+Gh987gkUFSYhQ8ePmUsvFWDcny2f8WVDL+SWXu6rcHqoIZHNpsRo88/lpzt/z/cPViA9TgACBLfsrsHmfx7/cfkUyNizIwe6jNQA8nMQv3poPN0niUqsV4+K0zP3l8i/r5mbjjf+d8/d3xVl4bf85KKQerko6MQx4fp+VO4/iqzNNfirE9CKX9q1bv6nAxv+eRcn2QyBJ4P3D1Xjr28ou/dyoSDWevDHH7x68W1o9pO1isCA+XI57r0rF1m867ezeq1IRrw/ewkqvEnOOSa/m52f6Gu1WbsGYdltwBGOazXbce+UYZMRpMTJciXFxWtx75Ri0mEOjUupy0Ve2SpIUtHIxnlqYi9uvSGbO98r+ChyrbsfTn50GRQH3zEhBcqSS8cmv7j+Hxzpi0J2HqjnpJ94/XM3y4zanR3n+xCUDM+Z7rkzFh4ersWZ2FmrbLH4txSuK0tBu4+6Uc7pJTE2JYhLDzWY7NizIZR2fkxiGZxdxxzldzcF85meBdqL3CES7Z3E44XC5mBgrN0GH1cWZTGJ415EaaGQS/OmGDD+71avl+L6ikXU+lVQMrcLjM4X1hoChigi1GMuuTmPNC8uuTkNEkOKFnsLmdGJxQRJr/IsLktATLZdgg95cmJoShZRoTchUnQsQ0FP0W+UwQRD/AnAVgCiCIKoBrAGgIQji3o6PvA/gjY6/lwFIBbCKIIhVHa/NpCiqAcBvAbwJQAmPEF3PmZXR9a5PX7aajI3V4qXb8qGWSxCrlSMpwnOuq9JiEKdTIDshDDanG6Mj1YxzKRwbi9RoDfKT9DDbXYhUy/DqkgK0WByIUMngpkjce1U6Fr96kAlqa9rsaDQ5sGV/Basdj6QoP4655/eW4amFeXj289OsNq6Xvy7v4II7ixe/8nzmQpMZqTEabNhzikkAewvN3X9NOkiKwrLCVIgIIFwphcNFMdc612jyqxLcUVqFt5dOgYskQ66VJxTRW5t2ONz4+NglpgJcIRXh8XnZmJMzAjIe1bdNJhdKLzTi9TsmodlkR6RGjg8PV6FglB46HppwKpkUO0qrWLa6o7QKzyzkt8Nstrv9eGhpKgE+cLkovPhVOev6L35VjucXT+B1fKgLX1wOAtkcAKREadBitmPHb6aixeKAWi7Bw+8dQbRGhgevG4v/t/2Qn7/612+m4JmFeWg2O2B2uHHvPw8ztvjEjTlIjlSistnK0FSUzEhBVrwOWqUUj7x/FJXNVtQZHHh+8XjY3SREILBl/zmcbTBheWEaLrVZOBMEdBu1dyUZvcg9XdfOyd9JV0DvKK3CjpKpsDrdfs+cSEQgPymcaamjKGD7wUq0Whwsu6CF7wSl9b6F3cF+pgHPM52fNCloY2qzcHObb7srOJW6Kjm3Gjrfjou+hkYmhhsEHnqPLbqrDtJ4Bgp9YavelBwPzUz347Z+7ouzWDotBc/vLUPJjBSsn5uNVR8dR63B5qGF+L4Sm2+ZAIvDjTqDFcuuToXDTWJScgRkEgIjwpU4W2/yE46jc6g2p4cPduuvCxChluJiiw02pwsritIQoZJBLZdAr5YiRsM9V8bqFH60IsmRSmxZUgCpmECsToEkvQpflTWw2pRpcbLu5uCu3hvKdCYDCTomGHvfdFS1mKGSSRCjlYMgPNRhcrEI/7p7CiqaLLjf614vL0zD69+exx9nZeCJT06x7HbVR8fx3E3jMXVMO0OF0mpx4KmFeYgPU2B+fiIkImD7XZPhIilhDhUwZNBkcmLVR8f9noc375yE1CCPjQ9UMm4tme1BincECBAQGP2WHKYo6pYAbz3P8dnHATwe4DylALL7YkyBWkr6otUkUECZFKEGSVL4/FS933v09UQiAqOiNBgV5aGmoNWXAU+71aKCRFa1HADMz09kFJ6BTke7dnYWZ9LD6nBx8hXF6TzVxpXNVpytN2LzvnImyEqP1aDd4kS8XoHbpiQhJdqTNKaVgpcXpuGJT05iydRkZpHwTmk1s9Cgv+t9hWkYnxgOiWRAC9WHNXpj08drDSxqEJuTxJ8/PI6UKDXykyO6Pb6+3YZ3DtXinUO1rNfnT0ziNR6by4V7ZqRi7W4vVd7iLNhd/KqXmwJwFjfx5CxuMnNzezXzrFjrS26qUEIgm6MTrBeazbA43YjRyrFubhYutdlxqLKV87eyu0hQFHCsph1bv6lg2eKfPjjGur+tFgfiw5SQS0U4WNHM8FA2mhw412jGjtIqFOcm4KpxMbjnqlS8/FU5ZoyN6bJd2punkF7k+n6e/hxBdArr5SSEB1yIJkWoMS5OF9AuhKRE/6Gu3crJbVpvtCI1VhuUMdUbA3CbG4NTGSsmCDxwbTo2/vcsc48euDYd4iDZnsHmYonu0gnHN+8MXkJ/INAXtkrTKuhVMoQpZV1uhJEUYLS7cPOkJCaJfLbBhEaTAzsPVWFKSjTEIiA/SQ+xiMK351qgU0hZfhlg+0/6GiabCyKCQMn2Q0xcaXZYQVHA1WOjMCZGE3Cu9KWGqGy2omR7KT7p2LSraDRh2T/9aVA+WT692zm4q/eGEi1UsCESERgTo8GYGA2z8Vln8Gx81rfb4HCT+NOH/rQiS6eloN3G3clworbdj9+/zmD1013ZeNN4TBkdKcydAoYEDFbuLot2a2hU3gbSkmnkuS4TIEDAwGGgBemGLPqK48yX39JbeMk7OeErFEKfNy4Ah7Jaxs35VtVqwfz8RGz9poIJ7GlO0JIZKXCTwEtfn8P8/ERUtZjx9II8fHOuCW4STELYu3qu1eJAQbIeO0qmos5gQ1yYAlnxYUJiOITQ0MukRaxOwcmNxbdyViIS4+X97Mrdl/eX46/zc3kdHx2AbzaaJzdXIH5ElYyfuwx14Yu+BlfS8407J2HtrhN+fg1gV3GJRdx+rrzBxIhjTkzW49nPzuC2qckszkFvLnZv7uKl01KY9lMuEc97r06FWARIRSK4XCQkEpFnAy9SzTnW6alRmD8hodvfuDu7EJIS/QeZRMxZtRIsPl0AAXmxYzTBobpQSMRQSNiCMQqJCHJJcCp1m0wOzme/2RQaAjaXi76wVTqOnJ+fiOpWS8CNMIVUBBEBjIvVISteh/wkPdosTrhJEhs+O43KZitKKw3MMUunpWDrNxV4ZNY4PDRzLJ75/AxrI8FNerrKAM+cHxemgFbh4R2uNdhYfnhBfkKXPrE7Yd3u3u/K13b1Xm8FfQX4gysGeHVJASx2N+e9FosQcC3jO8UqpCJMGBmOJa//IMydAoYsAq3hg9XZ01Po1TLO8et50v0JECBg4CBk7PoIveU4o0G3wwFgJTd8ubTEHdVq3lBIRXCRpB9H3EMzx0KtEGP9XH9e4XdLqyEWAWuKsxiOT4VUhFXFmXi3tBoEASao/9sXZTA5PCrCL35ZzmonpKvnNt40HsmRauSN1OO67HjkjdQLieEQg0om5rQtvkFIkl6F+wrZ3Fj3FaYhSa/idbzJ1lnlvnmfx9Yqm60w2fjtkJsdLn/e7tlZsDj4He9wujk5ch08K5cBgZvKG1xJz6oObvKuOAJHRaoxKTmC0xbtLk/Cd9Pecvx4oRVnG0xQySTYdaSGOV+gDTSlVMS0n75xxyT88+4p2LKkAPtO12FWdjy2flOBTXvLcdvW7/HhkRq4XJ5zBOJVnjQqgvdv3JVdDEeu6oFCo9EOvUqGe69OxbJCz396lSyoVStWh4uTF5svt3pfw0GSrMpPwLMx5yRJ7gP6GbRYsDcUUhHidEOXngfoG1ul40iCAN4prcaq4ky/+Wz30RqsKs5EZrwOo6PUGBWlwZSUSKTFanC63sh0YNDwrjb+y57TcLpJPL0wD8uLUvHQzHREa+R4fm9ZJ0/y1WnIiNV1q4EQyCd6x8I0vDcOu3u/K1/b1XvdnVdAz8EVA/z5o2PQKCSc93pcnA7PfnbGLzZYMzsLUR1JJvq1jTeNBwLM9cLcKWCoQCwCJ/+7OESW1xIRONdlQdp7FiBAQBcY1pXDfcnv2BuOM9+xvL10MhqNDthdnuD71f3ncLSmHXuO1+KphXkQAZB1JH3pyo3kSCUem5ONsjojRkWp8eKtE+B0U1DJxLA5SZypNUIlFzOcbyq5BDVtFsgkBKaMjsBz/z2D4twEiEVAzogwVLdasKggEemxWsSHKdBqcXgSvxG9q54TMPgRoZZhRVEa02JKByF8d3irWi349w+VeGphHqx2F1RyCd76tgL5SXpeVRzhKiln5XG4Ssrr+lq5BC8e8nBoWx0uKGUSbPu2AitnZfA6PjFchX98fwGvLJmIVrMTEWop3j54HjMzY3kdL4AN36QnLZxJV5NtP1jJVAH/35goONxunG8yIzlChZERSjxxYw7+9MExLz+XhRaTAy/cMgG1bRYAwPLCNLy6/xyW/t9o2JxuPL0wD2oZm0OVpuhJidbgTF073vi2Eq2WMmxYkIvrM+Oguj4Tv9r6vR+dyqhINfKT9P1eET4cuaoHCvFhCtx+RbKfT4sPC969Vcok+PJMp5/Rq6X4x8HzuHt6cBgEI9VyXGwx4pqsBDR22Pd/T9Rgenp0UMaTEx+GdXOzsdqLomrd3GzkjAgLyngGCn1hq3RC9kxdO1otDhhtTpTMSIFEJMKoKDUutVkwd3wCxsZqEKmW4/vzzYgPU8BNAg1GG6anRUEpFcPcIUS781A1ZBIC6bFa/PH6sUgIV8HucqOm1YLUGA3KG0x45vOzLN+5+qPjKEj2zPkzM2Kxo2Qq2m0OKCQStFgc+KmqFSQoRKrlnH60O2qI/qJvGq60UH0N7zWNiCCgV8lQa7Ax9j0qUg2b041Xby/AqUsGtNvd2HWkBiUzxuDlr8pxtKYdjSYHSmakIC1GC51SArVMDLPdxegXqGQSxOrkcJPdr7EECAhlKCRiJITLsWXJRLR0rEvaLPagdfb0FDKRGGoZgS1e8U6bxQ6pKDTGL0DAcMKwTQ73Nb9jbzjOvMeSHqPBLVOSGa49upoo8kQtJo2OxB+8xFn+dEMGXrh5As43maBRSPHbtw8x7z02OwsOlxtPfnqaeW3lrHGI0ynwSEeihV5s5SeE45EbMlHdakW9wYqKJjOe+6KTd/DJG3OQnxSOpIjA32XSqAghKTxEkB6tRUWjmdVenBCuxNgYfnyHBqsDC/KTWLa6pjgLBiu/dmClTIx7rkxlPwOzs6DkWbmsU4pxU0Ey6/rr5mQjTMXv+JF6Fa7JGMEIpdHH8618FsCGd9KTpspZ9dFxhtaBprFZMzsLf9h5hOE0f3xeNl7YV4YwhRTP3TQeF1vM0Cpl+O3bh1lJk7gwBd745jwMNidUcgnj85IjlVg3JxurPz4OvUrml3BZXpiG7QcrsXLnUehVMrhI7hbXikYTGox2Zm7oLT99IAhJif6DiICfKNfze8vw799MCdqYtHIRrsmI9/EzWdDKg1MKFKuRIj1Ojzve+IHl92I1/Dbl+hoymRjzckcgJUrNbODnjgjjJYoayugLW6U3sjLjtUiOVOP5vWf9eIwfuDYdtQYbfrX1B5Z/5PKVD1zrqQx+9vPTWFyQhIe95tZnF43HpGQ9NnH4zvp2G0ZFqvH5qXq8/s05LMhPwtrdh1k+eEdpFVbOyvCLvbvbjOuvzTqBFqr34FpfrShKw6fHarEgPxEWp9tPhG7XkRrcc2UqwhQSnG0wAQBaLQ4oJGI88/lp3DwpCWICcJEegeKbJyUxgnSbb50gzJ0ChjQ0ChFsTqDEZ12iVYRG6bBYTMDuYo9//dxsSCWCXxUgYLCBoHz7CIcICgoKqNLS0oDv+wq/AZ1iFpe78Kd3yrkCyq7e8x7LplsmMEkt73G9smQis4j0fp3mBeYSBymZkYJNe8u7fY3+ziRJ4VhNGxZvOdjlfenqu/jei76oyg5B9OiLdmerA42KRhPufPMHpnKXooDdR2vwxh2TeT0bP55vZvG/AR4b2n7XZEwaHdnt8QfKGvGbbaV+x792ewGmpXVfxfbD+WY8/N4Rv/E/vTAPk3lc/8jFVs5nYEfJVOSN1Hd7fAhhQOzUe6FIc1bSieL5+YlIjlBCJZPg6c9Ps1qZaY5LwOPfvI/1/kzJjBSkx2gRF6ZgVf4C8CSI52bD7abwu38e9juW5kpfXpSKGWnRfsfTvvdQZSuKxsUiJyGsX/0YH986TNErW/3sRC3+3/bDfp/bsmQiZmbF9X50l4Efzjfjdg4/ue2uybz81FAfTwhjUNkq7VMutVnQZnGhoskMu4uERi5mEsD3Xp3K+Fbvv2nQyb0EvYozPt1+12TOOf/tpVMQoZbhhk0H8NTCPM5jab/+1p2TEa3lriIW0G/olxgg0PrqmYV5ONtgxJb9/vZF28GKojTkJ+nxvw5tk/cPV6PWYINCKsLTC/Pw8HtHmM/S87dCKsKeFdNBUhDmzqGLkF5X9RbfVzTj12/4+9i37pyMKSmDf34eCvFFD/IavG11qNmpgIHFuPGTMP53mwK+//NLy3H65x8DvR3QTodt5XB/iE50VVXW1XveY7HaAyuScr1OUoHF6UifvH+g1+jvLBIRsDi4q+e870t31XN9XZUtYGBR325jOH+9wffZ6K2gncnGbetGnpzDjUY75/gbeV6/1sDtG+oMNuSN5HUKAV7wrsQ6W29k7i3NZU4LGAXiuPT+O5CfO11vhERM+L1f2WzFocpWpMdoOY+ludLdJOB0k3h8Xjb+/GFnG/vaOVlY/dFxVDZbsWV/Rb/7sf6sTB7OUErZFCOA53eXS4NXdVPfzu0n69uDw4M82MYzXNHXtkr7lPp2G5b96yfm9WWFqcw1vH1rID8brZGjvMHI+V6jyc4p8Gm0OeB0k7A5yYCxLX29A+VNeO1A//tYAf2PQOsrN0WBpLjti7YDs8ONOoONVcRCf8bSYUP0Z73jg7p2G8MhLUDAUENv11XBRkOA+CJUxi/kNQQMJ4RGP0I/YDCJTniPRSXnFmgIJM5C+6Su3uvuNe/v3Bf3hUt84oF3fsaFZjPvcwgIHnprA3EBjo/lKSQUrZVxHh+l4cd5HK2Vcx4frZXzOj4+TMkthBREftJQB52gSI/V+t1bMRFYYJNubPEWsfD9jIjwtGIH+t2KxsUgI14X8FhanClWp8C8vAS8vXQKnlqQg1eWTMRLX5UzSWvBj4UuNHIJp5iLVh68/fFYHbefitXx81NDfTzDFf1lq4Hm9e7+pv9d1WoBSXG/F6NVYEdpFZZOS8GywlQsnZaCHaVViFDLmesGim0pqvP/go8dGghka+EqaZdzPT0nyyQizs80mux+NkO/J/ALCxjKCPX5OeD4ea7Lgg0hryFgOGHYJoe7U1AO1lhe3X/OT9Hz8XnZyB0Rxjne3MQw7DpSg/uvSWe99xiHqu/aOVlIjlR1+Z374r50VZUtYPCjtzaQM8IjJOR9/Lq5HhvmA51SjPU+x6+fy58zGBT8VK6XF6bxOxZAVrwOj8/L9nsGs+KHthDSQIDLtnISw5CTGOaXEHl8XjZ2H63BzkPVWFGUxunnVhSlIUotQ2a8DhmxWk67zUkIx+go/+uuKs6EUipmOC9HRaohkYiQn6SHRiHFocpWzmpmwY+FHjJitEgIV6Jkhid5VTIjBQnhSmTw5FHvD2THabFujo+fnJON7LjgjImCG2vnZPnFDBTIbo4U0JfoL1sdFanG5lsnYHlRKpYVpkInFzPzHO1jff8GPHbw5I05eLe0GjsPVfvNrRtvGo/cEWG4rzANW7+pwOZ95dj6TQXuK0xDVnwY4/Pf+rYCa4qz/Obl3UdrsLwwDe8frgYg+NihAK55/vF52bjYbEaESuZnX7Qd0PO50erAQzPHsj5z/zXpePfQRdZn3z9cHdS1mwABA4X4cDFnvBAfHhoc/DnxYZzjzwmRdZWQ1xAwnDBsOYeBwcXv6D2W+DAF2sxO1LXbEBemQFZ8GCQSEed4AeB8kxm1BgvkEjEMVid0CikokFBIJKhps8LqdCM2TIGTNQa4O37uRL0SGXE6hk7Cewz17TaoZBI43W5EBFCS7gr9weccYgh5bqzePhsOhxtHLxkuS0ioovH/t3fmYXJU5f7/vD2T2TOTfTLZExgSyEoIEJUgJN4YFCGAuKNc8MarSHAHr1wRRdSr1yuLyy8CIiiLLKIgCF4WwSsIAZKQkEhCSELCZLIyk0wymcz0+f1Rpyc9PVU93dNLVXW/n+fpp6ura3mrzve859Spc867nwdf3sLco+u7z//chmY+cPy4lPTz+o79XH7fCj75zkkcPNRJVXkpv/77Rn5w3iyOGpGa/jo7o6xpamF7S888WGD4olMvP7ZlTxvNrYc40NHJuCHVjB9SxeY9B9i4cz8G6Ioadu4/xFHDq9nf3kllWQnth6O8vnM/d73gNPAuPLaeLXsPeM77vnl3G2+1HKTtUCfDasrpMoahLj7OmX+9hQ8ve7aY/ViQyFirBw8e5pXtrTS3HqK+tpzpI2uprPQn2Bo4Glu+eRddUWHX/kMMqymnJGKYM36YL/WQlW++zW+f28ji2eO67XngpS18fO7EQptrPdcEUqtuw2Jv/NjxTBxaw8797YysraArSq/lEQMriAgsuu6ZHnPFl0RgwZQRTB89iEhEkpaZMZ/ferCDzijsaetgSHUZ7Yc7eX7TXu5Z7swrC94+tsjjWOSKnNUBEsv5cYOrWNfcyjPrdzGqroIhNeUc7OhkYMUADnV2URKJcLCjCwNc+/CrdHQazp09hvLSCJOGVVNTUUJN+QAMhiFV5ZREYHur/89uSt4I/XNVJmzatZ+WAwc51BmheV879QMrKC+NUldVyYRh4aiPBq0Olg5ptmvonMNKXtA5h3NAkOZ3TLRl/FCY2cc2MY4aUePa6BWNGra1tLN5zwG+YefRjBFzarEKVWdnlD+tbuLy+1b1mE9n9rghaVe6Yr0GNHJweMk0b5SVlTBnwpB+7TthaDVTxw7h/17fRdTAhh37mT52SMr6KS2B804Y1x38pmJAhKs+MJXSNF6wl5ZGmDl2sM4xnAO8tDVhWE2vSu5RI2qYOKy6V6PGsgvmsOT25T0aK9Ztb2X0oEqmj67z1O3a7ft6+aUTXHxcJCJMH12nfqyAqKwcEKjAJ5t2t/HJW3oH3vTr5cOx9QOZM3E4F936wpFo6GdP49j62rzbUuzkQqtuw2I/f8fLPLx0HnMnDeveLr4uGVuORk23L2xqaefmv23sHpUR853JysyYz08kGjW0tnex90AH4D1Kya1h+wfnzeD90xoK8aVtQZBYzkejhi17DnYHQawYEOFL/3IM00fXEY3Cy1v28LvlTu/xC+aO5/on1ncHm/vxh2ZxauOIXuV0WBrFFCVTuqLw4V/2ri/86dJ5PlqVOtGo4ckNu0I7Z6+2ayjFRFE3Dhc6sUBQFQMinsMhJg2vIRo1/H3j7u6G4dj/X/rdCqb040E1PgBVEHplK+Gjo9N0R7SOFcKpsr3lEFc/uKaHlq9+cA2//teTGD9UHybChps/iQ3xaqir6H6QbD8cTRo0zmvOMC8fp35MySW5CIqbCW++fZBv/mF1j/zxzT+s5oRxg1MecaEEl0z0litfmOpx3Xz35fetYnBVGacc7U9PeyU93NLwx395jSWnTuL6xzd0Ty9x+3Obuf25zVx8yiRmjK6lsX6glrtK0bNjn7v/3rm/PRTl8xu73Ovfky+dFwr79XlAKSb0lXuBE4kIE4ZWewYRAafStnzznqzOpxPrNRCLHqwOVEmVTCf+b+twj4p+oKMz67Yq+SHRn8QC3pw7e0x3wzAk10p/5gxTP6bkiiAFxQXYvKfNNX9s2aMBVwqBTPWWK1+YynG9fPfyzXs0IFBI8ErDqDmyfP0T6zl39pju3umN9QO13FUUgldfSJdCqF/o84BSLGjjcBHQV4Cx5tb2pFGoFSWfZDrx//gh7i9Dxg3R4T+FQsynlURIWSthr1wrhUWQguICVJeVuuaPqjIdYFYIBE1v6eDlu7uiaECgkOCVhvFhb9oPRxEJlzYVJR+E2X+D1i8UJUzkLFeKyC3AmcAOY8w0u24m8AugBtgEfNwY02r/+zpwMdAFLDXGPGrXnwDcClQCDwOXmQKLoucWaAOOBGhq6+hk4tBqosapCNfXOsEdNu85wOY9bVSXlVJfW864Ic4QB7fjxYZD7Gk7xICSCB1dUV7Z9jYHOrqoKivludd3snR+Y3cvvNicbmEpeJTskmnwl1hAuu2t7TTUVjA9jYB09bUVzBlf1yugXKqNeBOHuc8NNXGYajlsxOtwxMAKSiLQ1OIEzGyoK2d4zbDu6UdiVAyIMLK2go0799Pc2k51eSmHO6McONzJD86b0Wte9ZiPS9T8uMFVbNl7oDtAZ0dXl2vwOiUcxAJmNbW001BXydSGWl/nK41EhPmNw7n9opPY3nqIkbXlTG+o801b9bXlfPW9k/nho//szh9ffe9k6mvLfbEHijcIWS60msmw2Ph0GDXICZjc1OrYdmz9QLa2HOwzjZL5177SdsLQ6l6+e+n8Ru5evoXzZo/u81zFohs/SOVeR6OGiMC150znP37/SncaXragkUdeaeKS049GBEoE3n3McE47Zjh72g6xdnsLnV2GppZ2Rg2qZGB5Kdv7oR9FCTtBqy+kS31tOVcsmsL3/7yuO/9fsWiKr/ULRVHcyeUrm1uBG4Hb4tbdBHzFGPNXEbkI+CrwnyJyHPARYCowCvhfETnGGNMF/BxYAjyH0zi8CHgkh3bnFa8I0gDrm/dz3ePrGVxVxiffMb5HIIdrFk/jhifWs3n3we5KVmN9Dac1juCxtc2uk75PGFrNuu37+MGf1/LhOeN6NAR/++xp/O4FZ56vkggcP3YQ75qkc7kVI26aTCdwQEdHFw+seqt7/sqYvhbPGJVSA3F9zQA+NGd8j4By3z5rGvU1qUW11bmhCgM3HV62oJHbnt3M3gMdLJ3fyBPrtnPVmVO5+qE1Pfznq037XPcrKxWWXTCHASXS44Ey8Vzjh1Zy6fxGrnxgda/GiMsXHRuaIBqKQ2dnlAdWbuuRntcsnsbimaN9ayDu6Ojij6ub+u0ns019dTnDa8pZcuokogYiAsNryqmv9ufhLdNyKKzkUqv9CTQbnw7HjKjhoyeP757Tf/zQSi45vbGHht3SKBX/2lfaDqoq5X8+NIu121vpitLti1MJXlcMuvGDVO51/DaDq8pYcuokjhpew+79h6gpK+GM6Q09nm3GDK7ixifX09Fpej33xJfj6epHUcJM0OoL6TKsupQh1WU96hdDqssYVq09hxUlaEguO+GKyATgobiew61AnTHGiMhY4FFjzHG21zDGmO/Z7R4FvoXTu/hJY8wUu/6jwGnGmM/0de45c+aY5cuXZ/+isszGnft53/XP9Oj5tnTB0QDdPeIuOf1obv5b795xnz/9aA7aYVglAtVlJZw8aSgfXvacawR0gPdd/wwXnzLJ9Xj/9cGZvNa8D2PgoVXb+NWFJ/kSGKcASKt2GjStumkypqFU9LB80x4+cfM/eu3/m4tPZs6EIX3u//wbu/nkLc/32v+2i07KegT3IifQOvXS4cWnTOqOYn7xKZN4aNU2vrxwCht27GPBlBHUlA/g/Tck3y9Ry6/v2N9jHy+fG/OdqeYFJWtkpNWVb+51LRfvXjKXmWMHZ8/KNMjUT2abF97YzQUufvf2i07iRB/8bqblkI8UlFZj6TC4qozvnzedFzfvJWrgvhe3cu7sMa5+MjGNEtPSy796pW28DefOHoOI07hw7vGjmTCsxnXbEOrGDzLSair3Olk5Xjkgwo1PbnB9FhHgq7aDQOJ+QFr6UQqCQNdXc03Q6gvpUmTPdSlrtdB0quSXKbNOZNbnrvf8f8XPlrJuxQtef3vqNN+vbFYDZwF/AM4Hxtr1o3F6BsfYatcdtsuJ610RkSU4vYwZN25c1ozOJW7zq8YHaAAQcZ9Xc2RtBVfGvUX8zzOPY3fbIc85OI05MqeX2zavNe/jxic2dK/zK2p6MRBkrWYS1Rxgu8f+za2pzQ3Y3Oqh4dZDKe2vZA8/deqlQ5Gey5t3H+z2Xe88aigHOrr63C9ey9GoYW1Ta499vHxkbL36xuCRTKtNLe5a2t7Szsyx+EKmfjLbePnd5n3++N1My6EgEyatNre2M7iqjAvmjuczt7/YYyRFZ9SklEaJaenlX73SNrZ/U0s7P33ySB31nUcN7dU4XMi68YNkWk3lXicrx9s7o67/bdixj6jxLoNjy8nOqxQfQX6uypSg1RfSxbN+UYTPdYWsU6UwyPd4youAS0TkRWAg0GHXu7VemyTrXTHGLDPGzDHGzBk+fHjGxuYDtyANJbYncPx6t4nct+w90O1s2w9H+c5Dr1JbUeYZdCn+XH0FhtBATbklyFrNNHBXg8f+9bWp7V9fW+5+fp2bKu/4qdO+AtjEluO/E/2c137xWt60u431O/a57uN2DPWNwSSZVhvqKl3Tc2Sdf+mYqZ/MNiO8/O5Af/xuIQeQDJNW62srOH/OmO5pyMCpb17/xHomDnMP/pqYRl5p2dd+fe3vtn0h68YPkmk1lXudSnmc+F9X1Pu/ZPtpGhc3QX6uypSg1RfSxeu5rhjnHC5knSqFQV4bh40x64wxC40xJwB3Aq/bv7ZypBcxwBjgLbt+jMv6gsEtAun0MXVMH1PHZQsaqRgQ4b4Xt3Yvx7b5ztnTuGf51h7Haj8c5XBX1DOiaexcD67cxtL5PY93zeJpPLRqW699lOIj06i400fV8e2zp/XY/9tnT2PGqLqU9i8RuOrMqT32v+rMqZTqVHJFhZsOL1vQyP0vbe3uufbQqm3d34l+zmu/RC03t7bzu+Vbe/jEB1du66XhxPMo4WFqQy3XLJ7Wq8yb2pCaT8oFmfrJbFMaEVe/O6DEH8cb9ujs/SVoWp0wtJpjRgx07fXV9PaBXhp2S6PEtHxw5bZe15gsbdPRQrHqxg9Suddu28SeN9yebZbOd8rq+17c2us5JVaOp6sfRQk7QasvpEt5iXD1WT3rF1efNZVyn+oXiqJ4k+85h0cYY3aISAQnYN1TxphbRGQqcAdwEk5AuseBRmNMl4i8AFwK/AMnIN0NxpiH+zp3mOZxiUX7jQ+eBbBlTxvNrYc40NHJhKHVRA3s3O9sI8AZHnN9TRha3et48cEhNu1uY0/bIQaURDjQ0dUj8q8G8MoKoZ8by02T6eiho6OLVW+1dEeSnjGqLuWgCRt37udr967gk++cxMGOTirLSrnt7xv5rw/O0iGD2SXwOo3X4fCaCkoizrDrqrISOrqilJVEONwVZUh1uaufa25tp7qshMNdhtb2w4wbUs3EYT217DWf5XmzR9MVdRqPq8pKXM+j5I2MtdrZGWVNUwvbW9oZWVfB1IY634LRxcjET2abIPrdTMshnyg4rSbOyQ5H5rucMaqOrS0H+0yjxLRMt86ZjhZCqhs/yFirqdzrZGk/sraCrqjzbFM5oISld73M5t0HAWioc3qtT22oo6GunIEVA2jup36U0BP4+mquCVJ9IV027tzP9x9Zw8fnTuTtA4cZVDWA3z73BlecMbUQn+t0zmElL+RqzuGcNQ6LyJ3AacAwoBm4CqgBLrGb3A983VgDROQbONNOdAJfMMY8YtfPwWlIrgQeAS41KRhd6BlOIzIHmqKvxGSCajtvqE5RvYUE1WqO0XyQNQpOq6qNgiVQWlWdKUkIlFaV9CiyvK2Nw0peCF1AOmPMRz3+us5j++8C33VZvxyYlkXTCoJIRFg0dSRTls4rqDfn8T3+6msL45qU9ChUbecTzUepky296T1XwkwkIiw8tp67l8ylqaWdBttjVTWsFGqZrD47WKSqM003RQkXhVCGqN9RioWcNQ4ruScSke4pKGIRS8PsrLL5ZlGdeGGQw1lvCpYie0OfFSIRYdLwml7D21L1I7m+5+rPCpMgpWs0anhsbXOg/EaQ7k+x4+UjITzpFG9nQ10FrzbtC5Teld46i0YNG3fut9M7lRI1UbbsOcjl963SdFOUEBGNGva1H+btA4epHFBKNGpCk2f1uUopJrRxOMQUmrPatLut+1rACXjypd+tYMrSeWnNSVRo96XY0PTLjDd2ueejyZfO46gRBTe3V85IR4fZ8l2Z2qGEh6Clay413B+Cdn8Ud8KSTol2Ll1wNMue3hgYvSu9cdPWf555HMuefl3TTVFCRGdnlAdWbuPKB1Z35+VrFk9j8czRvsd+SIWg1Y+U4uD0hWfQtGOX5/9bt73FrBycVxuHQ0xfziqd3hxB6PnR3NruGhF7x772tJyvOvFwE4T0C0J+6C+b97S55qMte9qKtnG4P+nppcPJl85DhB7HypbvSscO9WfhJmjp2tzazjEjavj0qUdx8FAnVeWl/PLp17Oi4f4QtPujuOOVTkP/9SSGD8xNAM9s+POoIWc+W0kPr/R009Z3HnqVH35wJtc+vJamlvbu9ZpuSqETC1TqTPtUydSG2lA0rAKsaWrpbhgGJ89e+cBqGkfUMHPsYJ+t65tc1vGV4NJX42zDiGE8+dgjOTt/045dSecU3nzFOTk5rzYOh5hkzmrC0OqUe3MEpedHfW0FFQMivSJijxhYkdZx1ImHG6/0a27NT/oFJT/0l+qyUtd8VFVWnO6+v+nppcO121v5yj0rexzruIaBWfFd6dih/izcBC1dRw2q4KMnj+dr9x7R9lUfmEpDXeYa7g9Buz+KO17p9MyGXdz0zMasl53Z9Oe58tlK6iRLTy9trd+xjwvmjuf25zbT1NKu6aYUPGHvedvU4p6Xt7e0M3OsT0alQbbaJ5Rw0Vfj7IqfLc2jNfkj+B5F8STmrOKJOSuv3hybdrf1Ok462+aSCUOr+fGHZnVfU6ySGJtXOVWS3Rcl+FTZxs14nMbNkrycPyj5ob/U15Zz2YLGHvnosgWN1NeW+2yZP/Q3Pb38yGvN+3odqytKVnxXOnaoPws3QUvXt9sOc/WDa3po++oH1/B222Ff7Ana/VHc8UonY3JTdmbLn9/34tZe5WS2fLaSOsnS00tbXVG4/on1nDt7jKabUhR49bxd09Tis2Wp0VBX6ZqXR/r08jldstU+oShhQBuHQ0wyZ5Ws100i6WybS2LRTB9eOo+7lpzMw0vn9avHiTrxcNPR1cXS+T0f2pbOb+RwV7SPPbNDUPJDfxk3pJrG+hqWnDqJz88/miWnTqKxvoZxQ4pT//1NTzc/cu0507ln+dZex9q5vz0rvitVO9SfhZ+gpWuTRz7Z3uqP3wva/VHccUunpfMbuf8lx09mu+zMlj/fe6CDxvoa/nRp9n22kjp9jYD00lb74SjTR9dquilFQbKet2FgakMt1yye1iMvX7N4GlMb6ny2LDWy1T6hFBZb33yTKbNO9PycvvAMv03sF8U5zrhAiDmrKUvnsWNfOyMGHpmrK50hEEEaLpEsInY6x/C6L0rwGVpdzt3Lt3DxKZMQAWPg7uVbWDRtZF7OH6T80B8iEWH+5HomDatR/dP/9HTzIxFxGhXiiR0rG74rVTuKOT0LhaCla6xnT2I+8atnT9Duj+JOfDpt3t3Gy2++3T3cH7JfdmbTn8f0VKxz8QeBZOkZS7PRS+by+LoddEXpMZXEMfUDdYoZpSgIWvmcLqWlERbPHE3jiBq2t7Qzsq6CqQ11oZgSI0au6viKf2Qa8K3LUJDTTmjjcMhwC9zg5qzGDa5i2QVzWL55D1EDD67cxuWLjnXtdRN7O58451eYe+ioE/eXTAInTBhazeWLjvVNj4WQH8Kq/1wEAuxPeibacdKEoUQiQjRqfNFGWNNTSQ1j/LbA6dnzww/OYP2O/UQNlAgcPaLG1549qvv8kKnfjaXThKHVHDwc7X6Blsw/9vecmZTPqqdgEY0aIgLXnjOd6x5/jTNnjKYkAieOH8K4wVWAk2bTRw9i29vtoa6TKUomxHreJs45HJaet+Dk5YEVAzjQ0cXAigH6olfxHb8CvgUdbRwOEakG4ohGDY+tbe6x3Q/Om8HCY+tdnbH20FGySaaBE/zWo9/nL1ZyFQgw3fTsyw7VhpINghb4MhIRIhJh2dMbu+357/NnqbYLnGzqMFX/mMk51QcXBvEaOGZEDUtOPYrvPPSqqx40zZViJxIRhg8s40cfnElbRyfVZaUMrCwJTR4IWn1HURRvwtOfX0k5EIfbdpfft4otew94HjvWo2LupGFMGl6jzlrpN9kInOC3Hv0+fzGSy0CA6aRnX3aoNpRsELTAl5t2t/Hle3ra8+V7whOIU+kf2dZhKv4x03OqDw4/8RqYd8yI7oZhcNeDprlSzGza3cZnbn+Jz9/5Mpff9wqfv/NlPnP7S6Epn4NW31EUxRttHA4RqQbiCHtALSXchD1wguIPQfFbQbFDKWyCprOg2aPkBz/SXbWmxGtABNWDoiQh7D4z7PYrSjGh00qEiFQDcWQaUCsX834qxUPYAydkA81D6ZPtQID9TYOwByRUwkHQdBY0e5T84Ed9UbWmJGrATQ+VA0p49vVdWodSip762grGD63kzBmjEZsNHly5LTQ+U32+4geZBpwrVnLWc1hEbhGRHSKyOm7dLBF5TkRWiMhyETnJrh8gIr8WkVdEZK2IfD1unxPs+g0icr2IFG3tIBaIo2KAk2xeQRlS3c6N2LxA77v+GT76y3/wvuuf4c9rthONBiBijhIKYoET4vUXtsAJmaB5qH9k4rcSySQNsmmHongRNJ2NG1zl6rdjgaGUwsSP+mLQtK/kn3gN3PfiVi5b0NjL9yy962WtQykKTvl86fxGbv7bRm58YgM3PbORS+c3hqZ8Vp+v+EEs4JzXp6ury28TA0kuew7fCtwI3Ba37r+Aq40xj4jI++zv04DzgXJjzHQRqQJeFZE7jTGbgJ8DS4DngIeBRcAjObQ7sKQSlCHWi2P4wDLu/re57DnQQVVZKfW15Smdw2teoClL52UU4dmtd0nsfNq7srAoLY2weOZoGkfUsL2lnZF1FUxtqEspGF2MTHveZrp/Z2eUNU0tNLW001BXydSG2pTtz1UeKnSyGXSmv2nQw38umcuBji5P/eS6d7j2Pi9sIhHhPZNH8JuLT2Z7azsNtRVMH1XnWxpv2XuAG55Yz8WnTEIEjIEbnljP7HGDffNbQcsDQbMnHRJtHze4ii17D9Dc2s7k+oH8+bJ5bG9Nz+/218/6HWAsGjW8sauNzXvaqLb143FDwpOWhUAkIiw8tp67l8ylqaWdMYMr+Zdj69nVdojKASUsvetlNu8+SENdBefOHsO67a2MHlTJ9NFOJwO3fBjm/Kkoydiy94BrLBc/y+d0SMzvDfa5MEz5U/2LUizkrHHYGPO0iExIXA3U2uU64K249dUiUgpUAh1Aq4g0ALXGmGcBROQ2YDFF2jgMR4IyuBUGbtFAL1vQyG3PbmbvgY6UIoMmmxeovwWQV5TSslLh83e8rJFLC5DS0ggzxw5m5tj09800qm2m+3d2Rnlg5bbuilisF8vimaNTaiDORR4qFpL5t3TwSoPmVu808NLNyROHujYM5zLyskZ2Lnw6O6P88ZW3+u1nsk1zazubdx/kp09u6LHeL78VtDwQNHvSwc32axZP44Yn1rN598F+X0smZV22fH26eNWTG+trmD+5PvBpWShEo4bH1ja75qd/vLG7u2H4grnjuf6J9bQfjrLs6Y2ezw4Lj633PJ6mqRJ2tnvEcklWpw0SyfJ7GPJnmMt/RUmXfD+BfAH4oYi8CfwIiE0fcS/QBjQBW4AfGWP2AKOBrXH7b7XrFBfcenFc9/h6zp09JuXIoLF5geLJdF4gr94lq7a2aORSpReZRrXNdP81TS2ub+jXNLWktH8u8pCSHlVlpa5pUFVW4rlPOrrJdeRljexc+GTqZ7JN0PxW0PJA0OxJBzfbr3xgNWfOGN39uz/XEjTNpIJXPXnV1pZQpGWhkCw/xXR17uwx3Q3D8du4PTusaWoJbf5UlL4oL424+toBJfl/kdwfwlx+QvjtV5R0yLdX+SzwRWPMWOCLwM12/UlAFzAKmAh8WUQmAW6vYzwnnRKRJXYu4+U7d+7MruUhwKsXR2yW5lQig+ZiXiAvuxKnDyumyKXFrtVkZBrVNtP9mzze0G9vSW3/QppbK6w67ejqYun8nnMYLp3fyOGuqOc+6egm15GXNbJz+oRNq5n6mWwTNL8VtDyQTXvyrdW+6oax3+leS9A0kwrJ6qPqX3uTK60my08xXZVESPnZwcufapoWD2GrA6RDS3uHa512X3uHz5alRtDK83QJc/nvJ6cvPIMps070/Jy+8Ay/TfSVvu7P1m1v9X2QHJDLOYfd+BRwmV2+B7jJLn8M+LMx5jCwQ0T+D5gDPAOMidt/DEemouiFMWYZsAxgzpw5RRe5wCsaqDFHlvvq0ZGLueC87Eo8ZNB7nGSTYtdqMjKNapvp/g11la77j6xLbX+/51PMJmHV6dDqcu5evqXH/Kl3L9/ComkjPfdJRze5jryskZ3TJ2xazdTPZJug+a2g5YFs2pNvrfZVN4z9TvdagqaZVEhWH1X/2ptcaTVZforpavSgSpY9vTGlZ4eGumD5CyX/hK0OkA5Dqyu4e/mrveq013/keL9NS4mglefpEuby309iAeG8WPGzpXm0Jnj0dX82X3FOHq05Qr57Dr8FvNsuzwfW2+UtwHxxqAbmAuuMMU3APhGZKyICfBL4Q55t9p1o1LBx536efX0XG3fu94zY69aL47IFjdz/0ta0enTE5oKbO2kYk4bXZFzR9+pdMmNMXah6nCj5YcLQam782PEsXXA0n59/NJctOJobP3Z8ytrItDfT1IZarlk8rVfk7KkNdSlfQ7bzUDGQqp9LhQlDq7l80bHdkZ1v/ttGLl90bFINpKObXPeYC2OPvKCTTX1lg2z4mWwTJL8VtDyQT3uyrVU3269ZPI2HVm3r/t3fawmSZlLBq548Y0yd+tc8kpgO44dWsuyCOTS3trNx534Apo+uS/nZYWqD+7aapkohMLWhlq8snExsFonSCHxl4WRf6wvpELTyPF3Cbr+ipEPOeg6LyJ3AacAwEdkKXAX8G3CdDTzXDiyxm/8U+BWwGmcqiV8ZY1bZ/z4L3IoTqO4RiiwYXTqToCf24hheU0FJBI4fN8jXHh1evUsAHg5RjxMlf3R0mu4eIzHNp0qmvZlKSyMsnjmaxhE1bG9pZ6SNqutHkKhiIdvBHvqjgXT2yXWPuTD2yAsyQQwmon4mOUHLA/myJxdadbN93OAqZo8bHIh7m09i92LypfPYsqeNqrJS6mvLGTekOK4/KMRrck/bIba93c6S25f30nw6zw5B8heKkk0iESEikR7PRf99/qzQ6Dvs+TPs9itKOuSscdgY81GPv05w2XY/cL7HcZYD07JoWqjwmgR9ytJ5rhFK3SJATxjmfyRTr8jUfkSrVoJNupp3I9NI6KWlEWaOHczMsf3aXUmTbKR5Iv3RQDr7ZKoxv49fTORCX9lA/UxygpYH8mFPrrTqZnuQ7m0+iUSEo0bUcNSI4rv2IBHTJMAnbn7eU/OpPjsEzV8oSrbYtLuNL9/Ts1z48j0rOLbB3zpMOoQ9f4bdfkVJlXzPOaykSbJJ0JM5qGjUsGl3G82t7dTX6hsuJTz0V/NBQvNfegQ1zTUdC4Pm1nYGV5Vx7uwx3UG47ntxq+/6UpREVKtKMRGNGnbuO8Sn500CHK3Hgsup5hXFIah15HTQ+rSihANtHA44/ZkEPYhDaBUlVcIeuEDzX/oEMc01HQuHhroKPvmO8Vz3+PrutLxsQSMja8PhU5TiQbWqFAtuZezS+Y3c/txm9h7oCE2dT1FyTRDryOmg9WmlP5y+8Ayaduzy/L9hxDCefKyoZpvNC9o4HHBik6AnOtRkk6AHdQitoqRCfzQfJDT/pU8Q01zTsXDoitLd2AZOWl73+HoWHjfSZ8sUpSeqVaVYcCtjr39iPUtOncSUkbWhqfMpSq4JYh05HbQ+rfSHph27mPW56z3/f+jr5zBl1ome/2/d9hazcmBXqmx9881A2+eFNg4HnP5Mgl4Iw0+U4iXsE/9r/kufIKa5pmPhsGOfe1ru3N+u844qgUK1qhQLXmXs8WMH8e5jRoSmzqcouSaIdeR00Pq04kamjaddhqSNx5uvOKf/xmWBoNvnhTYOh4B0J0EP+/ATRQnzxP+a//pH0NJc07Fw0LRUwoJqVSkWvLQ+PkSNXoqSL4JWR04HLdcUN8LaeFroRPw2QMk+seEnFQOc5A3b8BNFCTOa/woDTcfCQdNSCQuqVaVYUK0rSnGgeb0wOX3hGUyZdaLnZ+u2t/w2UekH2nO4AAn78BNFCTOa/woDTcfCQdNSCQuqVaVYUK0rSnGgeb0w6WtOYO35G060cbhACfPwE0UJO5r/CgNNx8JB01IJC6pVpVhQrStKcaB5PXycvvAMmnbs8vw/qAHVlMzQxmFFURRFURRFURRFURRFKXK0Z3Bxoo3DiqIoiqIoiqIoiqIoihJw+urZ2zBiGE8+9ki/99eewcWJNg4riqIoiqIoiqIoiqIois+k0nh75nfv9fz/oa+fw5RZJ/Z7f+0ZXJyIMcZvG3KCiOwENvtowjDAO0cHG7U9M3YZYxalunGOter3/dDzB/f8QdKpX/idPrmi0K4rm1oN4r0Jmk1qT3Ly5VeDdt2ZoNcSPFSrDmG2HcJtf6q2q1aPoPb7S1/2p6zVgD5XhT19Eim064HsXJOnTgu2cdhvRGS5MWaO33b0B7W9cPD7fuj5i/v8QadQ70+hXlc2COK9CZpNak9y8mVP0K47E/RaCpsw35Mw2w7htt8P28N8v0Dt95uw298XhXZ9hXY9kPtriuTqwIqiKIqiKIqiKIqiKIqiKEpw0cZhRVEURVEURVEURVEURVGUIkQbh3PHMr8NyAC1vXDw+37o+Yv7/EGnUO9PoV5XNgjivQmaTWpPcvJlT9CuOxP0WgqbMN+TMNsO4bbfD9vDfL9A7febsNvfF4V2fYV2PZDja9I5hxVFURRFURRFURRFURRFUYoQ7TmsKIqiKIqiKIqiKIqiKIpShGjjcBYQkVtEZIeIrI5bd76IrBGRqIgENkqih+0/FJF1IrJKRH4vIoN8NNETD9u/Y+1eISKPicgoP230AxEZKyJPishaq8HLfLKjREReFpGHfDr/IBG512p5rYi8I8/n/6K9/6tF5E4Rqcjx+dzywxAR+YuIrLffg3Npg994aT/ZfRCRr4vIBhH5p4i8N279CSLyiv3vehERP64pnsQ8VSjXlS9EZJG9HxtE5AqfbemVX/0kKOVGnD0VIvK8iKy09lztpz0x8lWuBUmrqSAim6xfWSEiy+26tP2TH6RbdqpvPUIQdVoI9YAwl/XiUvcOgv1B1Go6BK3OkC5Bq2OkS1DrJH3hUb7NFJFnbf56UERq4/4LlD9xI51rEpEJInJQnLrJChH5Rdw+gbimwJVZxhj9ZPgBTgVmA6vj1h0LTAaeAub4bWOati8ESu3yD4Af+G1nGrbXxi0vBX7ht50+3JcGYLZdHgi8Bhzngx1fAu4AHvLpPvwa+LRdLgMG5fHco4E3gEr7+3fAhTk+p1t++C/gCrt8RVDzchbvgav2ve6D/W8lUA5MBF4HSux/zwPvAAR4BDgjANfXI08VynXl6d6V2PswyfqDlX74xTh7euVXn+9PIMqNOHsEqLHLA4B/AHMDcJ9yXq4FTasp2rwJGJawLm3/5JPtKZed6luDr1MvXxamNE30MyGzvVfd22/7g6rVNK8hUHWGftgfqDpGP+wPZJ0kBbvdyrcXgHfb5YuA79jlwPmTLFzTBK88E5Rr8sobfvlN7TmcBYwxTwN7EtatNcb80yeTUsbD9seMMZ3253PAmLwblgIetrfG/awGim5SbWNMkzHmJbu8D1iL01iZN0RkDPB+4KZ8njfu/LU4hcfNAMaYDmPM23k2oxSoFJFSoAp4K5cnc8sPwNk4FXXs9+Jc2uA3SbTvdR/OBu4yxhwyxrwBbABOEpEGnBdNzxqntL0Nn++dR54K/XXlkZOADcaYjcaYDuAunPvkCx751TeCUG4k2GOMMfvtzwH242t5nsdyLVBazYC0/FP+zXNIs+xU33qEQOo07PWAMJf1SereftsfSK2mQ9DqDOkStDpGugSxTpIKHrqZDDxtl/8CnGeXA+VPvEjzmlwJ0jUFrczSxmGlLy7CefMQGkTkuyLyJvBx4Jt+2+MnIjIBOB7nDWc++QnwNSCa5/PGmATsBH4lztC8m0SkOl8nN8ZsA34EbAGagBZjzGP5On8c9caYJmtTEzDCBxt8IUH7XvdhNPBm3G5b7brRdjlxvZ/8hN55qhCuK1943RMlAR/LjUQ7SkRkBbAD+Isxxld7yF+5FkatGuAxEXlRRJbYden6pyChvrVvAp+OIa0H/ITwlvVedW+/7Q+8VouJoNQx0iWAdZL+sho4yy6fD4y1y0HzJ+ngdU0AE60/+quIzLPrAnlNQSiztHFY8UREvgF0Ar/125Z0MMZ8wxgzFsfuz/ttj1+ISA1wH/CFhB7VuT7vmcAOY8yL+TqnC6U4Q05+bow5HmjDGZKRF+y8QGfjDPcYBVSLyCfydf5iJw3tu83FZJKs94V+5KlQXFeeKeZrTxm/yg03jDFdxphZOKOXThKRaX7ZkudyLYxafZcxZjZwBnCJiJyaZNswXl8M9a1HCPQ1h7EeUABlfbp173zZH2itFhNBqmOkS5DqJBlyEU45/SLONAYddn3Q/Ek6eF1TEzDO+qMvAXfYEQ6Bu6aglFnaOKy4IiKfAs4EPm67poeRO+hjWEGhIiIDcBzMb40x9+f59O8CzhKRTThDt+aLyG/ybMNWYGvcW917cSqs+eI9wBvGmJ3GmMPA/cA783j+GM12mElsCM0OH2zIKx7a97oPW+n5dnkMzvQfW+k5nU5svV945amwX1c+8bonisXncsMTOyz5KWCRj2bks1wLnVaNMW/Z7x3A73GGcafrn4KE+ta+CWw6hrgeEPay3qvu7bf9gdVqMRHUOka6BKRO0m+MMeuMMQuNMScAd+LMWQvB8ycp43VNduqF3Xb5Rbv+GAJ2TUEqs7RxWOmFiCwCLgfOMsYc8NuedBCRxrifZwHr/LLFL2xkypuBtcaYH+f7/MaYrxtjxhhjJgAfAZ4wxuS116wxZjvwpohMtqsWAK/m0YQtwFwRqbLpsQBnDqF880fgU3b5U8AffLAhbyTRvtd9+CPwEREpF5GJQCPwvB2+s09E5tpjfhIf712SPBXq68ozLwCNIjJRRMpw7uMffbYpMPhdbrjYM1xEBtnlSpwXbr6V53ku10KlVRGpFpGBsWWcoMarSdM/5dfqPlHf2jeB1GmY6wFhL+uT1L39tj+QWi0mglbHSJeg1UkyQURG2O8IcCXwC/tXoPxJOnhdk023Ers8CeeaNgbpmgJXZhmfIg0W0gfnDUUTcBin1f5i4By7fAhoBh712840bN+AM5fJCvv5hd92pmH7fTgPJauAB4HRftvpw305BWcYwaq4NHyfT7acRg6juvdx7lnAcnsfHgAG5/n8V+NUHFYDtwPlOT6fW34YCjwOrLffQ/xIizzec1ftJ7sPwDdw3iT/k7iorsAcm3avAzcC4vf1Wbu681QhXVee7t37cKIAvw58w2dbeuVXn+0JTLlh7ZkBvGztWQ1802/9xNmW83ItSFpNwdZJOJGzVwJrYvb2xz/5ZH9aZaf61mDrtFDqAWEt63GpewfB/iBqNU37A1Vn6If9gapj9MP+wNZJ0tUNcJnNC68B34/PW0HzJ5leE84I8jU49ZOXgA8E7Zq88oZffjN24xRFURRFURRFURRFURRFUZQiQqeVUBRFURRFURRFURRFURRFKUK0cVhRFEVRFEVRFEVRFEVRFKUI0cZhRVEURVEURVEURVEURVGUIkQbhxVFURRFURRFURRFURRFUYoQbRxWFEVRFEVRFEVRFEVRFEUpQrRxOOSIyDdEZI2IrBKRFSJycpJtbxWRD/ZxvFtF5A17rJdE5B0e231bRN6Tqf1KYSEiY0TkDyKyXkReF5HrRKQsx+fcb78niMjquPWniMjzIrJORP4pIpdk4zxK4SIi9SJyh4hsFJEXReRZETnHZbseWotbn5JfFJHjRcSIyHuzZbtSuKSqyzzac4aILBeRtda//sgvW5TgEDSdWpv+ICLP+mmDEhxEZKh9vlkhIttFZFvc77KEbb8gIlUpHPMpEZljlzeJyCv2eK+IyNlZsHmCiHws7neViPzWHn+1iPxNRGrsf11x17NCRCZken4l+KST7iJyoYjcaJe/JSJfscvxz//rROSqFM57oYiMivu9SUSGZeGSlAJCHP4mImfErfuQiPw5w+PGdL/Stlm9M4V9bhKR4+zyJhEZJiKDRORzmdhSSJT6bYDSf2zD7ZnAbGPMIeuQs9EQ91VjzL0ishD4f8CMhPOWGGO+mYXzKAWEiAhwP/BzY8zZIlICLAO+C3w1g+OWGmM609xnJHAHsNgY85LNG4+KyFvGmN/31xalcLH6fQD4tTHmY3bdeOCshO08y800/OJHgb/Z70c9bBFjTDTF4ykFSqq6TLJ/iTGmK4v2TANuBN5vjFln88OSNPZP258rwSdoOrXHHATMBvaLyERjzBsu26geiwhjzG5gFjgNY8B+Y4zXy60vAL8BDqR5mtONMbtEZDLwGPCHfhl7hAnAx3DqtACXAc3GmOkA9jyH7X8HjTGzMjyfEj6yle6x5/8K4FURuc3Nb8ZxIbAaeCsL51YKFGOMEZF/B+4RkSeBEpy2gUX9OV5cfaFb97azzfeAd/dhy6ddVg8CPgf8rD/2FBraczjcNAC7jDGHAIwxu4wxb4nIN0XkBftGeZmttPdARE4Qkb/a3h2PikiDy/GfBo6222+yx/0bcL7E9UIWkRNF5O/2zc3zIjJQREpE5IfWjlUi8pnc3QYlIMwH2o0xvwKwjvuLwEVWB1NjG9qeFieISLWI3GL/fznWy8K+jb5HRB4EHhORGhF53L4ZTKU3xiXArcaYl6wtu4CvYRupJaEXvRzpfZzueZTCYT7QYYz5RWyFMWazMeaGRD16HSCmK3F6Vv4ubv1pdt9YI8oHcSrVC20lPNY7aK2I/Ax4CRgrIl+N86FXxx3vAeu714hIyg1zSihJpssJIvKM9VfdvSas3p4UkTuAV+w6V82IyMUi8pr1yb+UIz2KhovIfVZ/L4jIu+wuXwO+a4xZZ23pNMb8zO7zARH5h/Xl/ysi9Xb9t2xd5DHgNhGZausKK6y2G3N+F5VcEzSdApwHPAjcBXwk7li3isiPxXlI/YGIHCUif7bnfUZEptjtXPWsFBYissCm8Su2PlouIkuBUcCTVieIyM/FGTGxJr48TkItsNfuWy0ifxLnOWm1iHzYrt8kIteK08t+uYjMFueZ7HVxGlMAvg/Ms/7yizjPfttiJzHG/DP2HKgoMSSuF6+IzBGRp9LYvcJ+t9n9e7UriPMMNQf4rdVmpd3nUjnyDDUlW9ejhBtjzGqc8vhy4CqcF2/fkN7P/ynXFxKI97enichDsT9E5EYRudAud4/0iOP7wFFWxz/M6oWHEWOMfkL6AWqAFcBrOG873m3XD4nb5nbgA3b5VpxGiQHA34Hhdv2HgVvit7HL5wP/sMubgK/FHTd2rDJgI3CiXV+L0yN9CXClXVcOLAcm+n3P9JNTPS4F/sdl/cs4BcHV9ncD8Jpdvhb4hF0eZLVcjdNwtjWmZaupWrs8DNiA07MSnJ4f4PSuWG2X7wfOTrCjDnjbLnfrPOEYfZ5HP4X58dKv/S9Rj91aS9gu5hdLgS1AtV3/8zidnwI8bpfvAM6NO2YUmGt/L8TpeS84L3IfAk61/8XsqMTptTHU7/unH190WQVU2OVGYLldPg3noW5i3La9NIPT+LEJGIJTL3gGuNFudwdwil0eB6y1yy8BMz3sGRznLz8N/Ldd/hbwIlBpf98AfNwul8XW6ye8n6Dp1P7+X2AecAywKm79rdafltjfjwONdvlk4Am77Kpn/RTGx/qlK4E3gWPsutuAL9jlTcCwuO1j2iwBngJm2N9PAXPi9nnFavcAcKZdfx7wy7hj1cVt/1m7/D/AKmAgMBzYYdefBjwUt+8sYAfwLHBNTLv2vy6c58IVwO/9vsf6yZuWe6V7vH5xGnGfsssXxvnPbwFfscu3Am/YY+wHro07vle7Qrf24855qV3+HHCT3/dGP8H54Dzf/9P6yO/h/vyfTn0hpvt1QAtwQty28T7zRuBCu5zor4fh8UxXrB+dViLEGGP2i8gJOJXf04G7ReQKYJ+IfA0ngw0B1uC8rYkxGZgG/EWcTsUlQFPc/z8UkSuBncDFcevvdjFjMtBkjHnB2tQKIM6UFDPkSO/MOpxMnmx4ihJuBDAe65/CaSC7CvgQcI/9byFwltg5r3DeVo+zy38xxuyJO8a1InIqTgPaaKAe2J6mLalcQzrnUQoUEfkpTkNuB/BTeuoxKcaYTnHm0vqAiNwLvB+nxyU4U0ncZZfvAi7AeZkBsNkY85xdXmg/L9vfNTg+9GlgqRyZy3OsXb877YtUQkeCLt8D3Cgis3AqycfEbfq86Tkc1E0zI4G/xnQtIvfEHeM9wHFyZOBRrYgM7MO8MTj1kAacRt/48//RGHPQLj+L02NkDHC/MWZ931euhIkA6LQKZ+Tb34wxRkQ6RWSacXovAdxjjOkSZ67Wd+IMd40do9x+J9OzUhiUAG8YY16zv3+NM/LsJy7bfsj2Zi/F6eRwHE5jbiKxaSWOAh63PTZfAX4kIj/AabR4Jm77P9rvV4AaY8w+nOe4dnGmRumBMWaFiEzCqR+8B3hBRN5hjFmLTitRrGR7WokaHO2+0xjzd+D0PtoV4onVZ18Ezs2CTUqBYIxpE5G7cV4+fAjnGSnx+f8tUq8vxE8r8Q6ckWnTcnsVhY82Docc4wzdfwp4SkReAT6DM0fwHGPMm+LMqVWRsJsAa4wxrsHmsIWDy/o2l3XJGgQvNcb0mk9TKVjW4PSO6EZEanEe8F4AdovIDJye6rFpRgQ4zxjzz4T9Tqan3j6O05PiBGPMYRHZRG9dJ9oyhyOVboATcHqwA3Rip9UR54kwNld3uudRCoce+jXGXGKH5MU04+b/knE3zkPmHuAFY8w+cebhPg/nhcg3cPQ/NK7RLf4cAnzPGPP/4g8qIqfhPBC+wxhzwD54qkYLl2S6/CLQDMzE8Wftcft1aymJZnpNORVHxG5/MH6liKzB8aUrXfa5AfixMeaP9pzfcrPHGHOHiPwD56XJoyLyaWPME0lsUYJP0HT6rzg9f9+wjb61OFNLXJlw3gjOiKJZLsdOpmelMEipXBeRicBXcEZJ7hWRW+mj3DXGvC4izcBxxpjnbWee9wHfE5HHjDHftpvGpoSIxi3Hfrs+pxtj9uM0wt0vIlF73LWpXItSNHQ/55BmHdF2PnsKOEVEXsIZnZysXSGemIa70HYmpTdR+/F6/v8WKdQXEjHGPGvrHMPpqX3QZ6S00DmHQ4yITJaec/XNwumuD7DLvvn7YK8dnW2G27csiMgAiZsPNk3WAaNE5ER7rIHiBKh5FPisiAyw648Rkep+nkMJB48DVSLySXAmjAf+G2fu3wM4vSS/hjOcLjZf0KM481OJ3ed4j2PX4QyxOywipwPj+7Dlp8CF9s0jIjIUZ/L779j/N+E0cACcjTNUtT/nUQqHJ4AKEfls3Lo+I5Un4SmcYEj/xpFRF+8BVhpjxhpjJhhjxgP3AYtd9n8UZ77uWBTy0SIyAkeje23jyRRgbgY2KsEnmS7rcEbuRHF6oJd4HMNLM88D7xaRwbbcjn+59xjw+diPmC8Ffgj8h4gcY9dHRORLceeJzYX5Ka8Lsr3eNhpjrsd5gTfDa1slNARNpx8FFlk/OwGnvP8ICdjRbm+IyPl2fxGRmXH29KlnJdRUABNE5Gj7+wLgr3Z5H84UD+C8XGgDWsSZe/qMvg5sy+uJwGYRGQUcMMb8BvgRTt0gVeLtQETeJSKD7XIZTg/mzWkcTykONnHkOee8JNv1wvrZk4HXOdKw5tau0EObipIGXs//qdYXemDrDCU4oyg344woKheROmBBH7urjuPQNzrhpga4wQ476sSZH3UJ8DbO8KRNOD02e2CM6RBnuofrbaYpxRlCtSZdA+yxPmztqAQO4jSA3IQzh8tLNuPvxL0BRCkQ7NDNc4Cfich/4rx8ehj4D7vJvcB1HGmgxS7/BFhldbIJONPl8L8FHhSR5RyZXyiZLU0i8glgmdX4BJz5hmKV/l8CfxCR53EatWNvI9M6j1I4WP0uBv7HDp/biaOLy3Hmv0xksohsjfv9xYTjdYkTEOFCjjQsfBT4fcJx7gM+izOPZvz+j4nIscCztu60H/gE8Gfg30VkFc6LvudQCpY+dPkScJ9t2HoS714VrpoxxmwTkWuBf+AM5XsVZ942cOaQ/andpxRnOpN/N8asEpEvAHeKSBXOyKE/2X2+hTM8f5s9x0QPez4MfEJEDuNM2fNtj+2UkBAknYrI93GGp3b7RmPMGyLSKs6opEQ+DvxcnOnUBuC8yF5J6npWwks78K846VyK88wUC6q4DHhERJqMMaeLyMs4z0kbgf9LcswnRaQLR0tXGGOaReS9OFP2RYHDOGV+qqwCOkVkJc68sLtx9BqLR/AnnHqEosRzNXCziPwHju9Mhdi0kmU4z0b3W9/+S9zbFW4FfiEiBwGv0ciK4obX8//PSK2+AFApIivssgCfsiPq3xQnKPgqYD1HpudzxRizW0T+T0RWA48YY77a76sqAGKBFhRFUQoWEbkE+HecgF57/bZHURQlCIhIjR1CWorz4uIWY0ziCwxF8RXVqaIoiqIoSm7RxmFFURRFUZQiRER+hDPapwJniP5lRiuGSsBQnSqKoiiKouQWbRxWFEVRFEVRFEVRFEVRFEUpQjQgnaIoiqIoiqIoiqIoiqIoShGijcOKoiiKoiiKoiiKoiiKoihFiDYOK4qiKIqiKIqiKIqiKIqiFCHaOKwoiqIoiqIoiqIoiqIoilKEaOOwoiiKoiiKoiiKoiiKoihKEaKNw4qiKIqiKIqiKIqiKIqiKEXI/we4kEfScOWiWgAAAABJRU5ErkJggg==\n", "text/plain": [ "<Figure size 1440x1440 with 72 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "cols = ['SalePrice','OverallQual','GrLivArea',\n", " 'GarageCars','GarageArea','TotalBsmtSF',\n", " 'FullBath','YearBuilt']\n", "sns.pairplot(train_data[cols])" ] }, { "cell_type": "code", "execution_count": 16, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:55:07.628999Z", "iopub.status.busy": "2021-02-26T23:55:07.627940Z", "iopub.status.idle": "2021-02-26T23:55:07.803180Z", "shell.execute_reply": "2021-02-26T23:55:07.802584Z" }, "papermill": { "duration": 0.237084, "end_time": "2021-02-26T23:55:07.803345", "exception": false, "start_time": "2021-02-26T23:55:07.566261", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "y_train = train_data['SalePrice']\n", "test_id = test_data['Id']\n", "all_data = pd.concat([train_data,test_data], axis = 0, sort = False)\n", "all_data = all_data.drop(['Id','SalePrice'], axis = 1)" ] }, { "cell_type": "code", "execution_count": 17, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:55:07.908459Z", "iopub.status.busy": "2021-02-26T23:55:07.907700Z", "iopub.status.idle": "2021-02-26T23:55:07.918124Z", "shell.execute_reply": "2021-02-26T23:55:07.917524Z" }, "papermill": { "duration": 0.071374, "end_time": "2021-02-26T23:55:07.918313", "exception": false, "start_time": "2021-02-26T23:55:07.846939", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "PoolQC 2909\n", "MiscFeature 2814\n", "Alley 2721\n", "Fence 2348\n", "FireplaceQu 1420\n", "LotFrontage 486\n", "GarageYrBlt 159\n", "GarageFinish 159\n", "GarageQual 159\n", "GarageCond 159\n", "GarageType 157\n", "BsmtExposure 82\n", "BsmtCond 82\n", "BsmtQual 81\n", "BsmtFinType2 80\n", "BsmtFinType1 79\n", "MasVnrType 24\n", "MasVnrArea 23\n", "MSZoning 4\n", "Functional 2\n", "BsmtHalfBath 2\n", "BsmtFullBath 2\n", "Utilities 2\n", "SaleType 1\n", "BsmtFinSF1 1\n", "KitchenQual 1\n", "GarageCars 1\n", "BsmtUnfSF 1\n", "TotalBsmtSF 1\n", "Exterior2nd 1\n", "Exterior1st 1\n", "GarageArea 1\n", "Electrical 1\n", "BsmtFinSF2 1\n", "TotRmsAbvGrd 0\n", "Fireplaces 0\n", "MSSubClass 0\n", "BedroomAbvGr 0\n", "PavedDrive 0\n", "WoodDeckSF 0\n", "OpenPorchSF 0\n", "EnclosedPorch 0\n", "3SsnPorch 0\n", "ScreenPorch 0\n", "PoolArea 0\n", "MiscVal 0\n", "MoSold 0\n", "YrSold 0\n", "KitchenAbvGr 0\n", "HeatingQC 0\n", "dtype: int64" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "total = all_data.isnull().sum().sort_values(ascending = False)\n", "total.head(50)" ] }, { "cell_type": "code", "execution_count": 18, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:55:08.010867Z", "iopub.status.busy": "2021-02-26T23:55:08.010186Z", "iopub.status.idle": "2021-02-26T23:55:08.013498Z", "shell.execute_reply": "2021-02-26T23:55:08.012896Z" }, "papermill": { "duration": 0.051318, "end_time": "2021-02-26T23:55:08.013646", "exception": false, "start_time": "2021-02-26T23:55:07.962328", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "numeric_missed = ['BsmtFinSF1',\n", " 'BsmtFinSF2',\n", " 'BsmtUnfSF',\n", " 'TotalBsmtSF',\n", " 'BsmtFullBath',\n", " 'BsmtHalfBath',\n", " 'GarageArea',\n", " 'GarageCars']" ] }, { "cell_type": "code", "execution_count": 19, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:55:08.109567Z", "iopub.status.busy": "2021-02-26T23:55:08.108824Z", "iopub.status.idle": "2021-02-26T23:55:08.112864Z", "shell.execute_reply": "2021-02-26T23:55:08.112184Z" }, "papermill": { "duration": 0.055398, "end_time": "2021-02-26T23:55:08.113014", "exception": false, "start_time": "2021-02-26T23:55:08.057616", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "for feature in numeric_missed:\n", " all_data[feature] = all_data[feature].fillna(0)" ] }, { "cell_type": "code", "execution_count": 20, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:55:08.211597Z", "iopub.status.busy": "2021-02-26T23:55:08.210722Z", "iopub.status.idle": "2021-02-26T23:55:08.214397Z", "shell.execute_reply": "2021-02-26T23:55:08.215113Z" }, "papermill": { "duration": 0.057888, "end_time": "2021-02-26T23:55:08.215329", "exception": false, "start_time": "2021-02-26T23:55:08.157441", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "0 706.0\n", "1 978.0\n", "2 486.0\n", "3 216.0\n", "4 655.0\n", " ... \n", "1454 0.0\n", "1455 252.0\n", "1456 1224.0\n", "1457 337.0\n", "1458 758.0\n", "Name: BsmtFinSF1, Length: 2919, dtype: float64" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "all_data.BsmtFinSF1" ] }, { "cell_type": "code", "execution_count": 21, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:55:08.312382Z", "iopub.status.busy": "2021-02-26T23:55:08.311616Z", "iopub.status.idle": "2021-02-26T23:55:08.314731Z", "shell.execute_reply": "2021-02-26T23:55:08.314007Z" }, "papermill": { "duration": 0.054515, "end_time": "2021-02-26T23:55:08.314915", "exception": false, "start_time": "2021-02-26T23:55:08.260400", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "categorical_missed = ['Exterior1st',\n", " 'Exterior2nd',\n", " 'SaleType',\n", " 'MSZoning',\n", " 'Electrical',\n", " 'KitchenQual']" ] }, { "cell_type": "code", "execution_count": 22, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:55:08.408667Z", "iopub.status.busy": "2021-02-26T23:55:08.407896Z", "iopub.status.idle": "2021-02-26T23:55:08.423936Z", "shell.execute_reply": "2021-02-26T23:55:08.424516Z" }, "papermill": { "duration": 0.064407, "end_time": "2021-02-26T23:55:08.424697", "exception": false, "start_time": "2021-02-26T23:55:08.360290", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "for feature in categorical_missed:\n", " all_data[feature] = all_data[feature].fillna(all_data[feature].mode())" ] }, { "cell_type": "code", "execution_count": 23, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:55:08.518638Z", "iopub.status.busy": "2021-02-26T23:55:08.517995Z", "iopub.status.idle": "2021-02-26T23:55:08.525338Z", "shell.execute_reply": "2021-02-26T23:55:08.525908Z" }, "papermill": { "duration": 0.05598, "end_time": "2021-02-26T23:55:08.526105", "exception": false, "start_time": "2021-02-26T23:55:08.470125", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "0 RL\n", "1 RL\n", "2 RL\n", "3 RL\n", "4 RL\n", " ..\n", "1454 RM\n", "1455 RM\n", "1456 RL\n", "1457 RL\n", "1458 RL\n", "Name: MSZoning, Length: 2919, dtype: object" ] }, "execution_count": 23, "metadata": {}, "output_type": "execute_result" } ], "source": [ "all_data['MSZoning']" ] }, { "cell_type": "code", "execution_count": 24, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:55:08.622534Z", "iopub.status.busy": "2021-02-26T23:55:08.621733Z", "iopub.status.idle": "2021-02-26T23:55:08.629884Z", "shell.execute_reply": "2021-02-26T23:55:08.629174Z" }, "papermill": { "duration": 0.056854, "end_time": "2021-02-26T23:55:08.630038", "exception": false, "start_time": "2021-02-26T23:55:08.573184", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "0" ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" } ], "source": [ "all_data['Functional'] = all_data['Functional'].fillna('Typ')\n", "all_data['Functional'].isnull().sum()" ] }, { "cell_type": "code", "execution_count": 25, "metadata": { "execution": { "iopub.execute_input": "2021-02-26T23:55:08.727591Z", "iopub.status.busy": "2021-02-26T23:55:08.726907Z", "iopub.status.idle": "2021-02-26T23:55:08.733589Z", "shell.execute_reply": "2021-02-26T23:55:08.734133Z" }, "papermill": { "duration": 0.057165, "end_time": "2021-02-26T23:55:08.734345", "exception": false, "start_time": "2021-02-26T23:55:08.677180", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "all_data.drop(['Utilities'], axis=1, inplace=True)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": 0.046026, "end_time": "2021-02-26T23:55:08.826784", "exception": false, "start_time": "2021-02-26T23:55:08.780758", "status": "completed" }, "tags": [] }, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.9" }, "papermill": { "default_parameters": {}, "duration": 25.485393, "end_time": "2021-02-26T23:55:09.784785", "environment_variables": {}, "exception": null, "input_path": "__notebook__.ipynb", "output_path": "__notebook__.ipynb", "parameters": {}, "start_time": "2021-02-26T23:54:44.299392", "version": "2.2.2" } }, "nbformat": 4, "nbformat_minor": 4 }	0055/328/55328102.ipynb	s3://data-agents/kaggle-outputs/sharded/012_00055.jsonl.gz
{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": { "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19", "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5", "execution": { "iopub.execute_input": "2021-02-27T00:07:10.999452Z", "iopub.status.busy": "2021-02-27T00:07:10.998766Z", "iopub.status.idle": "2021-02-27T00:07:11.014154Z", "shell.execute_reply": "2021-02-27T00:07:11.013386Z" }, "papermill": { "duration": 0.029675, "end_time": "2021-02-27T00:07:11.014374", "exception": false, "start_time": "2021-02-27T00:07:10.984699", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "/kaggle/input/campeonato-brasileiro-de-futebol/campeonato-brasileiro-full.csv\n", "/kaggle/input/campeonato-brasileiro-de-futebol/Legenda.txt\n" ] } ], "source": [ "# This Python 3 environment comes with many helpful analytics libraries installed\n", "# It is defined by the kaggle/python docker image: https://github.com/kaggle/docker-python\n", "# For example, here's several helpful packages to load in \n", "\n", "import numpy as np # linear algebra\n", "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n", "\n", "# Input data files are available in the \"../input/\" directory.\n", "# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n", "\n", "import os\n", "for dirname, _, filenames in os.walk('/kaggle/input'):\n", " for filename in filenames:\n", " print(os.path.join(dirname, filename)) \n", "\n", "# Any results you write to the current directory are saved as output." ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:07:11.035783Z", "iopub.status.busy": "2021-02-27T00:07:11.035096Z", "iopub.status.idle": "2021-02-27T00:07:11.168930Z", "shell.execute_reply": "2021-02-27T00:07:11.168418Z" }, "papermill": { "duration": 0.146248, "end_time": "2021-02-27T00:07:11.169077", "exception": false, "start_time": "2021-02-27T00:07:11.022829", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>Rodada</th>\n", " <th>Data</th>\n", " <th>Horário</th>\n", " <th>Dia</th>\n", " <th>Mandante</th>\n", " <th>Visitante</th>\n", " <th>Vencedor</th>\n", " <th>Arena</th>\n", " <th>Mandante Placar</th>\n", " <th>Visitante Placar</th>\n", " <th>Estado Mandante</th>\n", " <th>Estado Visitante</th>\n", " <th>Estado Vencedor</th>\n", " <th>Placar</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>0</th>\n", " <td>1</td>\n", " <td>2000-07-29</td>\n", " <td>16h00</td>\n", " <td>Sábado</td>\n", " <td>Fluminense</td>\n", " <td>Bahia</td>\n", " <td>Fluminense</td>\n", " <td>Maracanã</td>\n", " <td>2</td>\n", " <td>0</td>\n", " <td>RJ</td>\n", " <td>BA</td>\n", " <td>RJ</td>\n", " <td>2x0</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>1</td>\n", " <td>2000-07-29</td>\n", " <td>16h00</td>\n", " <td>Sábado</td>\n", " <td>Vasco</td>\n", " <td>Sport</td>\n", " <td>Sport</td>\n", " <td>São Januário</td>\n", " <td>0</td>\n", " <td>2</td>\n", " <td>RJ</td>\n", " <td>PE</td>\n", " <td>PE</td>\n", " <td>0x2</td>\n", " </tr>\n", " <tr>\n", " <th>2</th>\n", " <td>1</td>\n", " <td>2000-07-29</td>\n", " <td>16h00</td>\n", " <td>Sábado</td>\n", " <td>Vitória</td>\n", " <td>Palmeiras</td>\n", " <td>Vitória</td>\n", " <td>Barradão</td>\n", " <td>4</td>\n", " <td>1</td>\n", " <td>ES</td>\n", " <td>SP</td>\n", " <td>ES</td>\n", " <td>4x1</td>\n", " </tr>\n", " <tr>\n", " <th>3</th>\n", " <td>1</td>\n", " <td>2000-07-30</td>\n", " <td>17h00</td>\n", " <td>Domingo</td>\n", " <td>Botafogo-RJ</td>\n", " <td>Atlético-MG</td>\n", " <td>-</td>\n", " <td>Caio Martins</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>RJ</td>\n", " <td>MG</td>\n", " <td>-</td>\n", " <td>0x0</td>\n", " </tr>\n", " <tr>\n", " <th>4</th>\n", " <td>1</td>\n", " <td>2000-07-30</td>\n", " <td>18h30</td>\n", " <td>Domingo</td>\n", " <td>Juventude</td>\n", " <td>Flamengo</td>\n", " <td>-</td>\n", " <td>Alfredo Jaconi</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>RS</td>\n", " <td>RJ</td>\n", " <td>-</td>\n", " <td>1x1</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " Rodada Data Horário Dia Mandante Visitante Vencedor \\\n", "0 1 2000-07-29 16h00 Sábado Fluminense Bahia Fluminense \n", "1 1 2000-07-29 16h00 Sábado Vasco Sport Sport \n", "2 1 2000-07-29 16h00 Sábado Vitória Palmeiras Vitória \n", "3 1 2000-07-30 17h00 Domingo Botafogo-RJ Atlético-MG - \n", "4 1 2000-07-30 18h30 Domingo Juventude Flamengo - \n", "\n", " Arena Mandante Placar Visitante Placar Estado Mandante \\\n", "0 Maracanã 2 0 RJ \n", "1 São Januário 0 2 RJ \n", "2 Barradão 4 1 ES \n", "3 Caio Martins 0 0 RJ \n", "4 Alfredo Jaconi 1 1 RS \n", "\n", " Estado Visitante Estado Vencedor Placar \n", "0 BA RJ 2x0 \n", "1 PE PE 0x2 \n", "2 SP ES 4x1 \n", "3 MG - 0x0 \n", "4 RJ - 1x1 " ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#Load dataset\n", "dfDataChampionship = pd.read_csv(\"/kaggle/input/campeonato-brasileiro-de-futebol/campeonato-brasileiro-full.csv\", delimiter=\",\")\n", "\n", "#To String\n", "dfDataChampionship = dfDataChampionship.applymap(str); \n", "\n", "#Create new column Placar\n", "dfDataChampionship[\"Placar\"] = dfDataChampionship[\"Mandante Placar\"].map(str) + \"x\" + dfDataChampionship[\"Visitante Placar\"]\n", "\n", "#Show data\n", "dfDataChampionship.head()" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:07:11.187139Z", "iopub.status.busy": "2021-02-27T00:07:11.186599Z", "iopub.status.idle": "2021-02-27T00:07:11.191895Z", "shell.execute_reply": "2021-02-27T00:07:11.192422Z" }, "papermill": { "duration": 0.015708, "end_time": "2021-02-27T00:07:11.192577", "exception": false, "start_time": "2021-02-27T00:07:11.176869", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "d = {'Clubes': [], 'PG': [], 'j': [], 'V': [], 'E': [], 'D': [], 'GP': [], 'GC': [], 'SG': []}\n", "dfClassChampionship = pd.DataFrame(data=d);" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:07:11.211017Z", "iopub.status.busy": "2021-02-27T00:07:11.210434Z", "iopub.status.idle": "2021-02-27T00:07:11.238198Z", "shell.execute_reply": "2021-02-27T00:07:11.237681Z" }, "papermill": { "duration": 0.037992, "end_time": "2021-02-27T00:07:11.238339", "exception": false, "start_time": "2021-02-27T00:07:11.200347", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>Rodada</th>\n", " <th>Data</th>\n", " <th>Horário</th>\n", " <th>Dia</th>\n", " <th>Mandante</th>\n", " <th>Visitante</th>\n", " <th>Vencedor</th>\n", " <th>Arena</th>\n", " <th>Mandante Placar</th>\n", " <th>Visitante Placar</th>\n", " <th>Estado Mandante</th>\n", " <th>Estado Visitante</th>\n", " <th>Estado Vencedor</th>\n", " <th>Placar</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>7939</th>\n", " <td>1</td>\n", " <td>2020-08-08</td>\n", " <td>19:00</td>\n", " <td>Sábado</td>\n", " <td>Fortaleza</td>\n", " <td>Athlético-PR</td>\n", " <td>Athlético-PR</td>\n", " <td>Castelão</td>\n", " <td>0</td>\n", " <td>2</td>\n", " <td>CE</td>\n", " <td>PR</td>\n", " <td>PR</td>\n", " <td>0x2</td>\n", " </tr>\n", " <tr>\n", " <th>7940</th>\n", " <td>1</td>\n", " <td>2020-08-08</td>\n", " <td>19:30</td>\n", " <td>Sábado</td>\n", " <td>Coritiba</td>\n", " <td>Internacional</td>\n", " <td>Internacional</td>\n", " <td>Couto Pereira</td>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>PR</td>\n", " <td>RS</td>\n", " <td>RS</td>\n", " <td>0x1</td>\n", " </tr>\n", " <tr>\n", " <th>7941</th>\n", " <td>1</td>\n", " <td>2020-08-08</td>\n", " <td>21:00</td>\n", " <td>Sábado</td>\n", " <td>Sport</td>\n", " <td>Ceará</td>\n", " <td>Sport</td>\n", " <td>Ilha do Retiro</td>\n", " <td>3</td>\n", " <td>2</td>\n", " <td>PE</td>\n", " <td>CE</td>\n", " <td>PE</td>\n", " <td>3x2</td>\n", " </tr>\n", " <tr>\n", " <th>7942</th>\n", " <td>1</td>\n", " <td>2020-08-09</td>\n", " <td>16:00</td>\n", " <td>Domingo</td>\n", " <td>Flamengo</td>\n", " <td>Atlético-MG</td>\n", " <td>Atlético-MG</td>\n", " <td>Maracanã</td>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>RJ</td>\n", " <td>MG</td>\n", " <td>MG</td>\n", " <td>0x1</td>\n", " </tr>\n", " <tr>\n", " <th>7943</th>\n", " <td>1</td>\n", " <td>2020-08-09</td>\n", " <td>16:00</td>\n", " <td>Domingo</td>\n", " <td>Santos</td>\n", " <td>Bragantino</td>\n", " <td>-</td>\n", " <td>Vila Belmiro</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>SP</td>\n", " <td>SP</td>\n", " <td>-</td>\n", " <td>1x1</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " Rodada Data Horário Dia Mandante Visitante \\\n", "7939 1 2020-08-08 19:00 Sábado Fortaleza Athlético-PR \n", "7940 1 2020-08-08 19:30 Sábado Coritiba Internacional \n", "7941 1 2020-08-08 21:00 Sábado Sport Ceará \n", "7942 1 2020-08-09 16:00 Domingo Flamengo Atlético-MG \n", "7943 1 2020-08-09 16:00 Domingo Santos Bragantino \n", "\n", " Vencedor Arena Mandante Placar Visitante Placar \\\n", "7939 Athlético-PR Castelão 0 2 \n", "7940 Internacional Couto Pereira 0 1 \n", "7941 Sport Ilha do Retiro 3 2 \n", "7942 Atlético-MG Maracanã 0 1 \n", "7943 - Vila Belmiro 1 1 \n", "\n", " Estado Mandante Estado Visitante Estado Vencedor Placar \n", "7939 CE PR PR 0x2 \n", "7940 PR RS RS 0x1 \n", "7941 PE CE PE 3x2 \n", "7942 RJ MG MG 0x1 \n", "7943 SP SP - 1x1 " ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "filter1 = dfDataChampionship['Data']>='2020-01-01'\n", "filter2 = dfDataChampionship['Data']<='2021-02-26'\n", "brasilianLeague = dfDataChampionship[filter1 & filter2]\n", "brasilianLeague.head()" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:07:11.263810Z", "iopub.status.busy": "2021-02-27T00:07:11.263136Z", "iopub.status.idle": "2021-02-27T00:07:11.265838Z", "shell.execute_reply": "2021-02-27T00:07:11.265313Z" }, "papermill": { "duration": 0.018978, "end_time": "2021-02-27T00:07:11.265981", "exception": false, "start_time": "2021-02-27T00:07:11.247003", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "#Cancatenando as colunas\n", "clubs = pd.concat([brasilianLeague['Mandante'].str.lower(), brasilianLeague['Visitante'].str.lower()], axis=1, keys=['Clubes'])\n" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:07:11.286572Z", "iopub.status.busy": "2021-02-27T00:07:11.285895Z", "iopub.status.idle": "2021-02-27T00:07:11.298854Z", "shell.execute_reply": "2021-02-27T00:07:11.299388Z" }, "papermill": { "duration": 0.024726, "end_time": "2021-02-27T00:07:11.299551", "exception": false, "start_time": "2021-02-27T00:07:11.274825", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>Clubes</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>0</th>\n", " <td>fortaleza</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>coritiba</td>\n", " </tr>\n", " <tr>\n", " <th>2</th>\n", " <td>sport</td>\n", " </tr>\n", " <tr>\n", " <th>3</th>\n", " <td>flamengo</td>\n", " </tr>\n", " <tr>\n", " <th>4</th>\n", " <td>santos</td>\n", " </tr>\n", " <tr>\n", " <th>5</th>\n", " <td>grêmio</td>\n", " </tr>\n", " <tr>\n", " <th>6</th>\n", " <td>botafogo-rj</td>\n", " </tr>\n", " <tr>\n", " <th>7</th>\n", " <td>corinthians</td>\n", " </tr>\n", " <tr>\n", " <th>8</th>\n", " <td>goiás</td>\n", " </tr>\n", " <tr>\n", " <th>9</th>\n", " <td>palmeiras</td>\n", " </tr>\n", " <tr>\n", " <th>10</th>\n", " <td>bragantino</td>\n", " </tr>\n", " <tr>\n", " <th>11</th>\n", " <td>atlético-mg</td>\n", " </tr>\n", " <tr>\n", " <th>12</th>\n", " <td>athlético-pr</td>\n", " </tr>\n", " <tr>\n", " <th>13</th>\n", " <td>bahia</td>\n", " </tr>\n", " <tr>\n", " <th>14</th>\n", " <td>atlético-go</td>\n", " </tr>\n", " <tr>\n", " <th>15</th>\n", " <td>fluminense</td>\n", " </tr>\n", " <tr>\n", " <th>16</th>\n", " <td>ceará</td>\n", " </tr>\n", " <tr>\n", " <th>17</th>\n", " <td>são paulo</td>\n", " </tr>\n", " <tr>\n", " <th>18</th>\n", " <td>internacional</td>\n", " </tr>\n", " <tr>\n", " <th>19</th>\n", " <td>vasco</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " Clubes\n", "0 fortaleza\n", "1 coritiba\n", "2 sport\n", "3 flamengo\n", "4 santos\n", "5 grêmio\n", "6 botafogo-rj\n", "7 corinthians\n", "8 goiás\n", "9 palmeiras\n", "10 bragantino\n", "11 atlético-mg\n", "12 athlético-pr\n", "13 bahia\n", "14 atlético-go\n", "15 fluminense\n", "16 ceará\n", "17 são paulo\n", "18 internacional\n", "19 vasco" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#Obtem todos os clubes \n", "cb = pd.Series(clubs['Clubes'].unique(), name=\"Clubes\")\n", "cb = cb.to_frame()\n", "cb" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:07:11.321611Z", "iopub.status.busy": "2021-02-27T00:07:11.320668Z", "iopub.status.idle": "2021-02-27T00:07:11.341682Z", "shell.execute_reply": "2021-02-27T00:07:11.342204Z" }, "papermill": { "duration": 0.033541, "end_time": "2021-02-27T00:07:11.342373", "exception": false, "start_time": "2021-02-27T00:07:11.308832", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "def getNumberWinner(data, clube ):\n", " df = data.apply(lambda x: x.str.strip())\n", " filter = df[\"Vencedor\"].str.lower() == clube\n", " return (data[filter]['Vencedor'].count()).astype(np.int64)\n", "\n", "def getNumberDepartures(data, clube ):\n", " df = data.apply(lambda x: x.str.strip())\n", " filter1 = df[\"Mandante\"].str.lower() == clube\n", " filter2 = df[\"Visitante\"].str.lower() == clube\n", " return (data[filter1]['Mandante'].count() + data[filter2]['Visitante'].count()).astype(np.int64)\n", "\n", "def getPoints(data, clube ):\n", " df = data.apply(lambda x: x.str.strip())\n", " filter1 = df[\"Mandante\"].str.lower() == clube\n", " filter2 = df[\"Visitante\"].str.lower() == clube\n", " filter3 = df[\"Vencedor\"].str.lower() == clube\n", " filter4 = (df[\"Mandante\"].str.lower() == clube) \| (df[\"Visitante\"].str.lower() == clube)\n", " filter5 = df[\"Vencedor\"].str.lower() == '-'\n", " \n", " v1 = data[(filter1) & (filter3)]\n", " v1 = v1['Vencedor'].count()\n", " v2 = data[(filter2) & (filter3)]\n", " v2 = v2['Vencedor'].count() \n", " v3 = data[(filter4) & (filter5)]\n", " v3 = v3['Vencedor'].count()\n", " return ((v23)+(v13)+v3).astype(np.int64)\n", "\n", "def getDraw(data, clube ):\n", " df = data.apply(lambda x: x.str.strip())\n", " filter1 = (df[\"Mandante\"].str.lower() == clube) \| (df[\"Visitante\"].str.lower() == clube)\n", " filter2 = df[\"Vencedor\"].str.lower() == '-'\n", " df = data[(filter1) & (filter2)]\n", " empates = df['Vencedor'].count()\n", " return empates.astype(np.int64)\n", "\n", "def getDefeats(data, clube ):\n", " df = data.apply(lambda x: x.str.strip())\n", " filter1 = (df[\"Mandante\"].str.lower() == clube) \| (df[\"Visitante\"].str.lower() == clube)\n", " filter2 = (df[\"Vencedor\"].str.lower() != clube) & (df[\"Vencedor\"].str.lower() != '-')\n", " df = data[(filter1) & (filter2)]\n", " derrotas = df['Vencedor'].count()\n", " return derrotas.astype(np.int64)\n", "\n", "def getGP(data, clube ):\n", " df = data.apply(lambda x: x.str.strip())\n", " filter1 = df[\"Mandante\"].str.lower() == clube\n", " filter2 = df[\"Visitante\"].str.lower() == clube\n", " df1 = data[(filter1)]\n", " df2 = data[(filter2)]\n", " placar1 = df1['Placar'].str.split('x')\n", " placar2 = df2['Placar'].str.split('x')\n", " \n", " gp = 0\n", " gc = 0\n", " for g1, g2 in placar1:\n", " gp = (gp + pd.to_numeric( g1 ))\n", " gc = (gc + pd.to_numeric( g2 ))\n", " \n", " for g1, g2 in placar2:\n", " gp = (gp + pd.to_numeric( g2 )) \n", " gc = (gc + pd.to_numeric( g1 ))\n", " return gp, gc" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:07:11.365199Z", "iopub.status.busy": "2021-02-27T00:07:11.364265Z", "iopub.status.idle": "2021-02-27T00:07:12.838343Z", "shell.execute_reply": "2021-02-27T00:07:12.837790Z" }, "papermill": { "duration": 1.486446, "end_time": "2021-02-27T00:07:12.838506", "exception": false, "start_time": "2021-02-27T00:07:11.352060", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>Clubes</th>\n", " <th>PG</th>\n", " <th>J</th>\n", " <th>V</th>\n", " <th>E</th>\n", " <th>D</th>\n", " <th>GP</th>\n", " <th>GC</th>\n", " <th>SG</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>0</th>\n", " <td>Flamengo</td>\n", " <td>71</td>\n", " <td>38</td>\n", " <td>21</td>\n", " <td>8</td>\n", " <td>9</td>\n", " <td>68</td>\n", " <td>48</td>\n", " <td>20</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>Internacional</td>\n", " <td>70</td>\n", " <td>38</td>\n", " <td>20</td>\n", " <td>10</td>\n", " <td>8</td>\n", " <td>61</td>\n", " <td>35</td>\n", " <td>26</td>\n", " </tr>\n", " <tr>\n", " <th>2</th>\n", " <td>Atlético-mg</td>\n", " <td>68</td>\n", " <td>38</td>\n", " <td>20</td>\n", " <td>8</td>\n", " <td>10</td>\n", " <td>64</td>\n", " <td>45</td>\n", " <td>19</td>\n", " </tr>\n", " <tr>\n", " <th>3</th>\n", " <td>São paulo</td>\n", " <td>66</td>\n", " <td>38</td>\n", " <td>18</td>\n", " <td>12</td>\n", " <td>8</td>\n", " <td>59</td>\n", " <td>41</td>\n", " <td>18</td>\n", " </tr>\n", " <tr>\n", " <th>4</th>\n", " <td>Fluminense</td>\n", " <td>64</td>\n", " <td>38</td>\n", " <td>18</td>\n", " <td>10</td>\n", " <td>10</td>\n", " <td>55</td>\n", " <td>42</td>\n", " <td>13</td>\n", " </tr>\n", " <tr>\n", " <th>5</th>\n", " <td>Grêmio</td>\n", " <td>59</td>\n", " <td>38</td>\n", " <td>14</td>\n", " <td>17</td>\n", " <td>7</td>\n", " <td>53</td>\n", " <td>40</td>\n", " <td>13</td>\n", " </tr>\n", " <tr>\n", " <th>6</th>\n", " <td>Palmeiras</td>\n", " <td>58</td>\n", " <td>38</td>\n", " <td>15</td>\n", " <td>13</td>\n", " <td>10</td>\n", " <td>51</td>\n", " <td>37</td>\n", " <td>14</td>\n", " </tr>\n", " <tr>\n", " <th>7</th>\n", " <td>Santos</td>\n", " <td>54</td>\n", " <td>38</td>\n", " <td>14</td>\n", " <td>12</td>\n", " <td>12</td>\n", " <td>52</td>\n", " <td>51</td>\n", " <td>1</td>\n", " </tr>\n", " <tr>\n", " <th>8</th>\n", " <td>Bragantino</td>\n", " <td>53</td>\n", " <td>38</td>\n", " <td>13</td>\n", " <td>14</td>\n", " <td>11</td>\n", " <td>50</td>\n", " <td>40</td>\n", " <td>10</td>\n", " </tr>\n", " <tr>\n", " <th>9</th>\n", " <td>Athlético-pr</td>\n", " <td>53</td>\n", " <td>38</td>\n", " <td>15</td>\n", " <td>8</td>\n", " <td>15</td>\n", " <td>38</td>\n", " <td>36</td>\n", " <td>2</td>\n", " </tr>\n", " <tr>\n", " <th>10</th>\n", " <td>Ceará</td>\n", " <td>52</td>\n", " <td>38</td>\n", " <td>14</td>\n", " <td>10</td>\n", " <td>14</td>\n", " <td>54</td>\n", " <td>51</td>\n", " <td>3</td>\n", " </tr>\n", " <tr>\n", " <th>11</th>\n", " <td>Corinthians</td>\n", " <td>51</td>\n", " <td>38</td>\n", " <td>13</td>\n", " <td>12</td>\n", " <td>13</td>\n", " <td>45</td>\n", " <td>45</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>12</th>\n", " <td>Atlético-go</td>\n", " <td>50</td>\n", " <td>38</td>\n", " <td>12</td>\n", " <td>14</td>\n", " <td>12</td>\n", " <td>40</td>\n", " <td>45</td>\n", " <td>-5</td>\n", " </tr>\n", " <tr>\n", " <th>13</th>\n", " <td>Bahia</td>\n", " <td>44</td>\n", " <td>38</td>\n", " <td>12</td>\n", " <td>8</td>\n", " <td>18</td>\n", " <td>48</td>\n", " <td>59</td>\n", " <td>-11</td>\n", " </tr>\n", " <tr>\n", " <th>14</th>\n", " <td>Sport</td>\n", " <td>42</td>\n", " <td>38</td>\n", " <td>12</td>\n", " <td>6</td>\n", " <td>20</td>\n", " <td>31</td>\n", " <td>50</td>\n", " <td>-19</td>\n", " </tr>\n", " <tr>\n", " <th>15</th>\n", " <td>Fortaleza</td>\n", " <td>41</td>\n", " <td>38</td>\n", " <td>10</td>\n", " <td>11</td>\n", " <td>17</td>\n", " <td>34</td>\n", " <td>44</td>\n", " <td>-10</td>\n", " </tr>\n", " <tr>\n", " <th>16</th>\n", " <td>Vasco</td>\n", " <td>41</td>\n", " <td>38</td>\n", " <td>10</td>\n", " <td>11</td>\n", " <td>17</td>\n", " <td>37</td>\n", " <td>56</td>\n", " <td>-19</td>\n", " </tr>\n", " <tr>\n", " <th>17</th>\n", " <td>Goiás</td>\n", " <td>37</td>\n", " <td>38</td>\n", " <td>9</td>\n", " <td>10</td>\n", " <td>19</td>\n", " <td>41</td>\n", " <td>63</td>\n", " <td>-22</td>\n", " </tr>\n", " <tr>\n", " <th>18</th>\n", " <td>Coritiba</td>\n", " <td>31</td>\n", " <td>38</td>\n", " <td>7</td>\n", " <td>10</td>\n", " <td>21</td>\n", " <td>31</td>\n", " <td>54</td>\n", " <td>-23</td>\n", " </tr>\n", " <tr>\n", " <th>19</th>\n", " <td>Botafogo-rj</td>\n", " <td>27</td>\n", " <td>38</td>\n", " <td>5</td>\n", " <td>12</td>\n", " <td>21</td>\n", " <td>32</td>\n", " <td>62</td>\n", " <td>-30</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " Clubes PG J V E D GP GC SG\n", "0 Flamengo 71 38 21 8 9 68 48 20\n", "1 Internacional 70 38 20 10 8 61 35 26\n", "2 Atlético-mg 68 38 20 8 10 64 45 19\n", "3 São paulo 66 38 18 12 8 59 41 18\n", "4 Fluminense 64 38 18 10 10 55 42 13\n", "5 Grêmio 59 38 14 17 7 53 40 13\n", "6 Palmeiras 58 38 15 13 10 51 37 14\n", "7 Santos 54 38 14 12 12 52 51 1\n", "8 Bragantino 53 38 13 14 11 50 40 10\n", "9 Athlético-pr 53 38 15 8 15 38 36 2\n", "10 Ceará 52 38 14 10 14 54 51 3\n", "11 Corinthians 51 38 13 12 13 45 45 0\n", "12 Atlético-go 50 38 12 14 12 40 45 -5\n", "13 Bahia 44 38 12 8 18 48 59 -11\n", "14 Sport 42 38 12 6 20 31 50 -19\n", "15 Fortaleza 41 38 10 11 17 34 44 -10\n", "16 Vasco 41 38 10 11 17 37 56 -19\n", "17 Goiás 37 38 9 10 19 41 63 -22\n", "18 Coritiba 31 38 7 10 21 31 54 -23\n", "19 Botafogo-rj 27 38 5 12 21 32 62 -30" ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "\n", "dfTable = cb[[\"Clubes\"]].copy()\n", "for column in [\"PG\", \"J\", \"V\", \"E\", \"D\", \"GP\", \"GC\", \"SG\"]:\n", " dfTable[column] = 0\n", "\n", "def ensureUtf(s, encoding='utf8'):\n", " if type(s) == bytes:\n", " return s.decode(encoding, 'ignore')\n", " else:\n", " return s\n", "\n", "for index, row in dfTable.iterrows():\n", " c1 = row['Clubes']\n", " c1 = ensureUtf( c1 )\n", " c1 = c1.strip()\n", " \n", " pg = getPoints(brasilianLeague, c1 )\n", " j = getNumberDepartures(brasilianLeague, c1 )\n", " v = getNumberWinner(brasilianLeague, c1 )\n", " e = getDraw(brasilianLeague, c1 )\n", " d = getDefeats(brasilianLeague, c1 )\n", " gp, gc = getGP(brasilianLeague, c1 )\n", " \n", " dfTable.at[index, 'PG'] = pg\n", " dfTable.at[index, 'J'] = j\n", " dfTable.at[index, 'V'] = v\n", " dfTable.at[index, 'E'] = e\n", " dfTable.at[index, 'D'] = d\n", " dfTable.at[index, 'GP'] = gp\n", " dfTable.at[index, 'GC'] = gc\n", " dfTable.at[index, 'SG'] = gp - gc\n", "\n", "dfTable['Clubes'] = dfTable['Clubes'].str.capitalize() \n", "dfTable = dfTable.sort_values(by=['PG'], ascending=False)\n", "dfTable = dfTable.reset_index(drop=True)\n", "dfTable" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": 0.010332, "end_time": "2021-02-27T00:07:12.859446", "exception": false, "start_time": "2021-02-27T00:07:12.849114", "status": "completed" }, "tags": [] }, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.9" }, "papermill": { "default_parameters": {}, "duration": 8.245267, "end_time": "2021-02-27T00:07:13.379382", "environment_variables": {}, "exception": null, "input_path": "__notebook__.ipynb", "output_path": "__notebook__.ipynb", "parameters": {}, "start_time": "2021-02-27T00:07:05.134115", "version": "2.2.2" } }, "nbformat": 4, "nbformat_minor": 4 }	0055/328/55328534.ipynb	s3://data-agents/kaggle-outputs/sharded/012_00055.jsonl.gz
{ "cells": [ { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.026436, "end_time": "2021-02-27T00:25:06.337744", "exception": false, "start_time": "2021-02-27T00:25:06.311308", "status": "completed" }, "tags": [] }, "source": [ "# London Crime Data Cleaning" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.024729, "end_time": "2021-02-27T00:25:06.387928", "exception": false, "start_time": "2021-02-27T00:25:06.363199", "status": "completed" }, "tags": [] }, "source": [ "# Table of Contents\n", "\n", "* [Cleaning Street Data](#Cleaning-Street-Data)\n", "* [Cleaning Search Data](#Cleaning-Search-Data)" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19", "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5", "execution": { "iopub.execute_input": "2021-02-27T00:25:06.443069Z", "iopub.status.busy": "2021-02-27T00:25:06.441980Z", "iopub.status.idle": "2021-02-27T00:25:06.462698Z", "shell.execute_reply": "2021-02-27T00:25:06.461860Z" }, "papermill": { "duration": 0.049803, "end_time": "2021-02-27T00:25:06.462939", "exception": false, "start_time": "2021-02-27T00:25:06.413136", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "/kaggle/input/london-police-records/london-street.csv\n", "/kaggle/input/london-police-records/london-stop-and-search.csv\n", "/kaggle/input/london-police-records/london-outcomes.csv\n" ] } ], "source": [ "# This Python 3 environment comes with many helpful analytics libraries installed\n", "# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n", "# For example, here's several helpful packages to load\n", "\n", "import numpy as np # linear algebra\n", "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n", "\n", "# Input data files are available in the read-only \"../input/\" directory\n", "# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n", "\n", "import os\n", "for dirname, _, filenames in os.walk('/kaggle/input'):\n", " for filename in filenames:\n", " print(os.path.join(dirname, filename))\n", "\n", "# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n", "# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:25:06.524055Z", "iopub.status.busy": "2021-02-27T00:25:06.523292Z", "iopub.status.idle": "2021-02-27T00:25:37.675195Z", "shell.execute_reply": "2021-02-27T00:25:37.675733Z" }, "papermill": { "duration": 31.184869, "end_time": "2021-02-27T00:25:37.675969", "exception": false, "start_time": "2021-02-27T00:25:06.491100", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/opt/conda/lib/python3.7/site-packages/IPython/core/interactiveshell.py:3147: DtypeWarning: Columns (2,13,14) have mixed types.Specify dtype option on import or set low_memory=False.\n", " interactivity=interactivity, compiler=compiler, result=result)\n" ] } ], "source": [ "#Load in the datasets\n", "street = pd.read_csv(\"/kaggle/input/london-police-records/london-street.csv\")\n", "search = pd.read_csv(\"/kaggle/input/london-police-records/london-stop-and-search.csv\")\n", "outcomes = pd.read_csv(\"/kaggle/input/london-police-records/london-outcomes.csv\")" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.025539, "end_time": "2021-02-27T00:25:37.727696", "exception": false, "start_time": "2021-02-27T00:25:37.702157", "status": "completed" }, "tags": [] }, "source": [ "# Cleaning Street Data" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:25:37.794009Z", "iopub.status.busy": "2021-02-27T00:25:37.793264Z", "iopub.status.idle": "2021-02-27T00:25:37.826377Z", "shell.execute_reply": "2021-02-27T00:25:37.826984Z" }, "papermill": { "duration": 0.073437, "end_time": "2021-02-27T00:25:37.827212", "exception": false, "start_time": "2021-02-27T00:25:37.753775", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>Crime ID</th>\n", " <th>Month</th>\n", " <th>Reported by</th>\n", " <th>Falls within</th>\n", " <th>Longitude</th>\n", " <th>Latitude</th>\n", " <th>Location</th>\n", " <th>LSOA code</th>\n", " <th>LSOA name</th>\n", " <th>Crime type</th>\n", " <th>Last outcome category</th>\n", " <th>Context</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>0</th>\n", " <td>324a40f7da5f81b2f6c96bc6fe3e300173782e3342f409...</td>\n", " <td>2014-06</td>\n", " <td>City of London Police</td>\n", " <td>City of London Police</td>\n", " <td>-0.113767</td>\n", " <td>51.517372</td>\n", " <td>On or near Stone Buildings</td>\n", " <td>E01000914</td>\n", " <td>Camden 028B</td>\n", " <td>Vehicle crime</td>\n", " <td>Investigation complete; no suspect identified</td>\n", " <td>NaN</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>62dde92ceeb12755a8a95a2829048ce4796ba3cfb3f7c0...</td>\n", " <td>2014-06</td>\n", " <td>City of London Police</td>\n", " <td>City of London Police</td>\n", " <td>-0.111497</td>\n", " <td>51.518226</td>\n", " <td>On or near Pedestrian Subway</td>\n", " <td>E01000914</td>\n", " <td>Camden 028B</td>\n", " <td>Violence and sexual offences</td>\n", " <td>Unable to prosecute suspect</td>\n", " <td>NaN</td>\n", " </tr>\n", " <tr>\n", " <th>2</th>\n", " <td>NaN</td>\n", " <td>2014-06</td>\n", " <td>City of London Police</td>\n", " <td>City of London Police</td>\n", " <td>-0.097601</td>\n", " <td>51.520699</td>\n", " <td>On or near Carthusian Street</td>\n", " <td>E01000001</td>\n", " <td>City of London 001A</td>\n", " <td>Anti-social behaviour</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " </tr>\n", " <tr>\n", " <th>3</th>\n", " <td>NaN</td>\n", " <td>2014-06</td>\n", " <td>City of London Police</td>\n", " <td>City of London Police</td>\n", " <td>-0.097601</td>\n", " <td>51.520699</td>\n", " <td>On or near Carthusian Street</td>\n", " <td>E01000001</td>\n", " <td>City of London 001A</td>\n", " <td>Anti-social behaviour</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " </tr>\n", " <tr>\n", " <th>4</th>\n", " <td>NaN</td>\n", " <td>2014-06</td>\n", " <td>City of London Police</td>\n", " <td>City of London Police</td>\n", " <td>-0.097601</td>\n", " <td>51.520699</td>\n", " <td>On or near Carthusian Street</td>\n", " <td>E01000001</td>\n", " <td>City of London 001A</td>\n", " <td>Anti-social behaviour</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " Crime ID Month \\\n", "0 324a40f7da5f81b2f6c96bc6fe3e300173782e3342f409... 2014-06 \n", "1 62dde92ceeb12755a8a95a2829048ce4796ba3cfb3f7c0... 2014-06 \n", "2 NaN 2014-06 \n", "3 NaN 2014-06 \n", "4 NaN 2014-06 \n", "\n", " Reported by Falls within Longitude Latitude \\\n", "0 City of London Police City of London Police -0.113767 51.517372 \n", "1 City of London Police City of London Police -0.111497 51.518226 \n", "2 City of London Police City of London Police -0.097601 51.520699 \n", "3 City of London Police City of London Police -0.097601 51.520699 \n", "4 City of London Police City of London Police -0.097601 51.520699 \n", "\n", " Location LSOA code LSOA name \\\n", "0 On or near Stone Buildings E01000914 Camden 028B \n", "1 On or near Pedestrian Subway E01000914 Camden 028B \n", "2 On or near Carthusian Street E01000001 City of London 001A \n", "3 On or near Carthusian Street E01000001 City of London 001A \n", "4 On or near Carthusian Street E01000001 City of London 001A \n", "\n", " Crime type \\\n", "0 Vehicle crime \n", "1 Violence and sexual offences \n", "2 Anti-social behaviour \n", "3 Anti-social behaviour \n", "4 Anti-social behaviour \n", "\n", " Last outcome category Context \n", "0 Investigation complete; no suspect identified NaN \n", "1 Unable to prosecute suspect NaN \n", "2 NaN NaN \n", "3 NaN NaN \n", "4 NaN NaN " ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#Get look at the dataset\n", "street.head()" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:25:37.891158Z", "iopub.status.busy": "2021-02-27T00:25:37.890003Z", "iopub.status.idle": "2021-02-27T00:25:37.906008Z", "shell.execute_reply": "2021-02-27T00:25:37.906563Z" }, "papermill": { "duration": 0.052622, "end_time": "2021-02-27T00:25:37.906788", "exception": false, "start_time": "2021-02-27T00:25:37.854166", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "<class 'pandas.core.frame.DataFrame'>\n", "RangeIndex: 2946479 entries, 0 to 2946478\n", "Data columns (total 12 columns):\n", " # Column Dtype \n", "--- ------ ----- \n", " 0 Crime ID object \n", " 1 Month object \n", " 2 Reported by object \n", " 3 Falls within object \n", " 4 Longitude float64\n", " 5 Latitude float64\n", " 6 Location object \n", " 7 LSOA code object \n", " 8 LSOA name object \n", " 9 Crime type object \n", " 10 Last outcome category object \n", " 11 Context float64\n", "dtypes: float64(3), object(9)\n", "memory usage: 269.8+ MB\n" ] } ], "source": [ "street.info()" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:25:37.967576Z", "iopub.status.busy": "2021-02-27T00:25:37.966497Z", "iopub.status.idle": "2021-02-27T00:25:40.474019Z", "shell.execute_reply": "2021-02-27T00:25:40.473331Z" }, "papermill": { "duration": 2.540393, "end_time": "2021-02-27T00:25:40.474206", "exception": false, "start_time": "2021-02-27T00:25:37.933813", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "Crime ID 0.240376\n", "Month 0.000000\n", "Reported by 0.000000\n", "Falls within 0.000000\n", "Longitude 0.011769\n", "Latitude 0.011769\n", "Location 0.000000\n", "LSOA code 0.011769\n", "LSOA name 0.011769\n", "Crime type 0.000000\n", "Last outcome category 0.240376\n", "Context 1.000000\n", "dtype: float64" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#Find proportion of missing data in street dataset\n", "street.isnull().sum()/len(street)" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:25:40.873540Z", "iopub.status.busy": "2021-02-27T00:25:40.672552Z", "iopub.status.idle": "2021-02-27T00:25:40.877971Z", "shell.execute_reply": "2021-02-27T00:25:40.877264Z" }, "papermill": { "duration": 0.376015, "end_time": "2021-02-27T00:25:40.878154", "exception": false, "start_time": "2021-02-27T00:25:40.502139", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "#Drop Context Column from dataset\n", "new_street = street.drop(columns=['Context'])" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:25:40.972521Z", "iopub.status.busy": "2021-02-27T00:25:40.971267Z", "iopub.status.idle": "2021-02-27T00:25:40.976683Z", "shell.execute_reply": "2021-02-27T00:25:40.976028Z" }, "papermill": { "duration": 0.068037, "end_time": "2021-02-27T00:25:40.976841", "exception": false, "start_time": "2021-02-27T00:25:40.908804", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>Type</th>\n", " <th>Date</th>\n", " <th>Part of a policing operation</th>\n", " <th>Policing operation</th>\n", " <th>Latitude</th>\n", " <th>Longitude</th>\n", " <th>Gender</th>\n", " <th>Age range</th>\n", " <th>Self-defined ethnicity</th>\n", " <th>Officer-defined ethnicity</th>\n", " <th>Legislation</th>\n", " <th>Object of search</th>\n", " <th>Outcome</th>\n", " <th>Outcome linked to object of search</th>\n", " <th>Removal of more than just outer clothing</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>0</th>\n", " <td>Person search</td>\n", " <td>2015-03-02T16:40:00+00:00</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>Male</td>\n", " <td>25-34</td>\n", " <td>Asian or Asian British - Bangladeshi (A3)</td>\n", " <td>Asian</td>\n", " <td>Police and Criminal Evidence Act 1984 (section 1)</td>\n", " <td>Stolen goods</td>\n", " <td>Suspect arrested</td>\n", " <td>True</td>\n", " <td>False</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>Person search</td>\n", " <td>2015-03-02T16:40:00+00:00</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>Male</td>\n", " <td>25-34</td>\n", " <td>Asian or Asian British - Bangladeshi (A3)</td>\n", " <td>Asian</td>\n", " <td>Police and Criminal Evidence Act 1984 (section 1)</td>\n", " <td>Stolen goods</td>\n", " <td>Suspect arrested</td>\n", " <td>False</td>\n", " <td>False</td>\n", " </tr>\n", " <tr>\n", " <th>2</th>\n", " <td>Person search</td>\n", " <td>2015-03-02T18:45:00+00:00</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>Male</td>\n", " <td>25-34</td>\n", " <td>White - Any other White ethnic background (W9)</td>\n", " <td>White</td>\n", " <td>Police and Criminal Evidence Act 1984 (section 1)</td>\n", " <td>NaN</td>\n", " <td>Suspect arrested</td>\n", " <td>True</td>\n", " <td>True</td>\n", " </tr>\n", " <tr>\n", " <th>3</th>\n", " <td>Person search</td>\n", " <td>2015-03-02T19:15:00+00:00</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>Male</td>\n", " <td>over 34</td>\n", " <td>White - White British (W1)</td>\n", " <td>White</td>\n", " <td>Police and Criminal Evidence Act 1984 (section 1)</td>\n", " <td>Stolen goods</td>\n", " <td>Suspect arrested</td>\n", " <td>False</td>\n", " <td>False</td>\n", " </tr>\n", " <tr>\n", " <th>4</th>\n", " <td>Person and Vehicle search</td>\n", " <td>2015-03-03T15:50:00+00:00</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>Male</td>\n", " <td>25-34</td>\n", " <td>White - White British (W1)</td>\n", " <td>White</td>\n", " <td>Police and Criminal Evidence Act 1984 (section 1)</td>\n", " <td>Stolen goods</td>\n", " <td>Suspect arrested</td>\n", " <td>True</td>\n", " <td>True</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " Type Date \\\n", "0 Person search 2015-03-02T16:40:00+00:00 \n", "1 Person search 2015-03-02T16:40:00+00:00 \n", "2 Person search 2015-03-02T18:45:00+00:00 \n", "3 Person search 2015-03-02T19:15:00+00:00 \n", "4 Person and Vehicle search 2015-03-03T15:50:00+00:00 \n", "\n", " Part of a policing operation Policing operation Latitude Longitude \\\n", "0 NaN NaN NaN NaN \n", "1 NaN NaN NaN NaN \n", "2 NaN NaN NaN NaN \n", "3 NaN NaN NaN NaN \n", "4 NaN NaN NaN NaN \n", "\n", " Gender Age range Self-defined ethnicity \\\n", "0 Male 25-34 Asian or Asian British - Bangladeshi (A3) \n", "1 Male 25-34 Asian or Asian British - Bangladeshi (A3) \n", "2 Male 25-34 White - Any other White ethnic background (W9) \n", "3 Male over 34 White - White British (W1) \n", "4 Male 25-34 White - White British (W1) \n", "\n", " Officer-defined ethnicity \\\n", "0 Asian \n", "1 Asian \n", "2 White \n", "3 White \n", "4 White \n", "\n", " Legislation Object of search \\\n", "0 Police and Criminal Evidence Act 1984 (section 1) Stolen goods \n", "1 Police and Criminal Evidence Act 1984 (section 1) Stolen goods \n", "2 Police and Criminal Evidence Act 1984 (section 1) NaN \n", "3 Police and Criminal Evidence Act 1984 (section 1) Stolen goods \n", "4 Police and Criminal Evidence Act 1984 (section 1) Stolen goods \n", "\n", " Outcome Outcome linked to object of search \\\n", "0 Suspect arrested True \n", "1 Suspect arrested False \n", "2 Suspect arrested True \n", "3 Suspect arrested False \n", "4 Suspect arrested True \n", "\n", " Removal of more than just outer clothing \n", "0 False \n", "1 False \n", "2 True \n", "3 False \n", "4 True " ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#Checking dataset too see if we need too keep Crime ID column\n", "search.head()" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:25:41.049149Z", "iopub.status.busy": "2021-02-27T00:25:41.048101Z", "iopub.status.idle": "2021-02-27T00:25:41.062261Z", "shell.execute_reply": "2021-02-27T00:25:41.062805Z" }, "papermill": { "duration": 0.056408, "end_time": "2021-02-27T00:25:41.063008", "exception": false, "start_time": "2021-02-27T00:25:41.006600", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "<class 'pandas.core.frame.DataFrame'>\n", "RangeIndex: 1947050 entries, 0 to 1947049\n", "Data columns (total 10 columns):\n", " # Column Dtype \n", "--- ------ ----- \n", " 0 Crime ID object \n", " 1 Month object \n", " 2 Reported by object \n", " 3 Falls within object \n", " 4 Longitude float64\n", " 5 Latitude float64\n", " 6 Location object \n", " 7 LSOA code object \n", " 8 LSOA name object \n", " 9 Outcome type object \n", "dtypes: float64(2), object(8)\n", "memory usage: 148.5+ MB\n" ] } ], "source": [ "#Checking dataset too see if any matches for Crime ID column\n", "outcomes.info() #It looks like later we might be able to join datasets on Crime ID so we will leave it alone for now" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:25:41.132559Z", "iopub.status.busy": "2021-02-27T00:25:41.128499Z", "iopub.status.idle": "2021-02-27T00:25:41.247491Z", "shell.execute_reply": "2021-02-27T00:25:41.248229Z" }, "papermill": { "duration": 0.153524, "end_time": "2021-02-27T00:25:41.248463", "exception": false, "start_time": "2021-02-27T00:25:41.094939", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "count 2.911801e+06\n", "mean -1.207649e-01\n", "std 1.488718e-01\n", "min -5.668404e+00\n", "25% -2.025260e-01\n", "50% -1.138210e-01\n", "75% -3.323900e-02\n", "max 1.751738e+00\n", "Name: Longitude, dtype: float64" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#Quick look at Longitude\n", "new_street.Longitude.describe()" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.034174, "end_time": "2021-02-27T00:25:41.316639", "exception": false, "start_time": "2021-02-27T00:25:41.282465", "status": "completed" }, "tags": [] }, "source": [ "Now working with this data and having context we would not find this information valuable if we do not have all the info on the loaction of the event and for that reason we are going to drop all missing values from columns." ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:25:43.859678Z", "iopub.status.busy": "2021-02-27T00:25:43.858906Z", "iopub.status.idle": "2021-02-27T00:25:44.434477Z", "shell.execute_reply": "2021-02-27T00:25:44.433759Z" }, "papermill": { "duration": 3.083391, "end_time": "2021-02-27T00:25:44.434637", "exception": false, "start_time": "2021-02-27T00:25:41.351246", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "#Make new dataframe for dropped nan dataset\n", "new_street1 = new_street.dropna()" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:25:46.377328Z", "iopub.status.busy": "2021-02-27T00:25:46.376424Z", "iopub.status.idle": "2021-02-27T00:25:46.419381Z", "shell.execute_reply": "2021-02-27T00:25:46.419867Z" }, "papermill": { "duration": 1.95526, "end_time": "2021-02-27T00:25:46.420070", "exception": false, "start_time": "2021-02-27T00:25:44.464810", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "Crime ID 0\n", "Month 0\n", "Reported by 0\n", "Falls within 0\n", "Longitude 0\n", "Latitude 0\n", "Location 0\n", "LSOA code 0\n", "LSOA name 0\n", "Crime type 0\n", "Last outcome category 0\n", "dtype: int64" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#Do we have any missing values?\n", "new_street1.isnull().sum()" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:25:46.483496Z", "iopub.status.busy": "2021-02-27T00:25:46.482893Z", "iopub.status.idle": "2021-02-27T00:25:46.501667Z", "shell.execute_reply": "2021-02-27T00:25:46.501118Z" }, "papermill": { "duration": 0.051764, "end_time": "2021-02-27T00:25:46.501842", "exception": false, "start_time": "2021-02-27T00:25:46.450078", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>Crime ID</th>\n", " <th>Month</th>\n", " <th>Reported by</th>\n", " <th>Falls within</th>\n", " <th>Longitude</th>\n", " <th>Latitude</th>\n", " <th>Location</th>\n", " <th>LSOA code</th>\n", " <th>LSOA name</th>\n", " <th>Crime type</th>\n", " <th>Last outcome category</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>0</th>\n", " <td>324a40f7da5f81b2f6c96bc6fe3e300173782e3342f409...</td>\n", " <td>2014-06</td>\n", " <td>City of London Police</td>\n", " <td>City of London Police</td>\n", " <td>-0.113767</td>\n", " <td>51.517372</td>\n", " <td>On or near Stone Buildings</td>\n", " <td>E01000914</td>\n", " <td>Camden 028B</td>\n", " <td>Vehicle crime</td>\n", " <td>Investigation complete; no suspect identified</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>62dde92ceeb12755a8a95a2829048ce4796ba3cfb3f7c0...</td>\n", " <td>2014-06</td>\n", " <td>City of London Police</td>\n", " <td>City of London Police</td>\n", " <td>-0.111497</td>\n", " <td>51.518226</td>\n", " <td>On or near Pedestrian Subway</td>\n", " <td>E01000914</td>\n", " <td>Camden 028B</td>\n", " <td>Violence and sexual offences</td>\n", " <td>Unable to prosecute suspect</td>\n", " </tr>\n", " <tr>\n", " <th>8</th>\n", " <td>92be9a7d4c6c076cf245d15ca162d675ec65139ad5fabe...</td>\n", " <td>2014-06</td>\n", " <td>City of London Police</td>\n", " <td>City of London Police</td>\n", " <td>-0.098572</td>\n", " <td>51.516767</td>\n", " <td>On or near King Edward Street</td>\n", " <td>E01000001</td>\n", " <td>City of London 001A</td>\n", " <td>Bicycle theft</td>\n", " <td>Investigation complete; no suspect identified</td>\n", " </tr>\n", " <tr>\n", " <th>9</th>\n", " <td>d37709a832130d3cfe650daa327b700968b3d1b3620622...</td>\n", " <td>2014-06</td>\n", " <td>City of London Police</td>\n", " <td>City of London Police</td>\n", " <td>-0.097562</td>\n", " <td>51.518864</td>\n", " <td>On or near Parking Area</td>\n", " <td>E01000001</td>\n", " <td>City of London 001A</td>\n", " <td>Bicycle theft</td>\n", " <td>Investigation complete; no suspect identified</td>\n", " </tr>\n", " <tr>\n", " <th>10</th>\n", " <td>6ccf322a44296c494627bfcf687b876841b1012bb08691...</td>\n", " <td>2014-06</td>\n", " <td>City of London Police</td>\n", " <td>City of London Police</td>\n", " <td>-0.097601</td>\n", " <td>51.520699</td>\n", " <td>On or near Carthusian Street</td>\n", " <td>E01000001</td>\n", " <td>City of London 001A</td>\n", " <td>Other theft</td>\n", " <td>Investigation complete; no suspect identified</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " Crime ID Month \\\n", "0 324a40f7da5f81b2f6c96bc6fe3e300173782e3342f409... 2014-06 \n", "1 62dde92ceeb12755a8a95a2829048ce4796ba3cfb3f7c0... 2014-06 \n", "8 92be9a7d4c6c076cf245d15ca162d675ec65139ad5fabe... 2014-06 \n", "9 d37709a832130d3cfe650daa327b700968b3d1b3620622... 2014-06 \n", "10 6ccf322a44296c494627bfcf687b876841b1012bb08691... 2014-06 \n", "\n", " Reported by Falls within Longitude Latitude \\\n", "0 City of London Police City of London Police -0.113767 51.517372 \n", "1 City of London Police City of London Police -0.111497 51.518226 \n", "8 City of London Police City of London Police -0.098572 51.516767 \n", "9 City of London Police City of London Police -0.097562 51.518864 \n", "10 City of London Police City of London Police -0.097601 51.520699 \n", "\n", " Location LSOA code LSOA name \\\n", "0 On or near Stone Buildings E01000914 Camden 028B \n", "1 On or near Pedestrian Subway E01000914 Camden 028B \n", "8 On or near King Edward Street E01000001 City of London 001A \n", "9 On or near Parking Area E01000001 City of London 001A \n", "10 On or near Carthusian Street E01000001 City of London 001A \n", "\n", " Crime type \\\n", "0 Vehicle crime \n", "1 Violence and sexual offences \n", "8 Bicycle theft \n", "9 Bicycle theft \n", "10 Other theft \n", "\n", " Last outcome category \n", "0 Investigation complete; no suspect identified \n", "1 Unable to prosecute suspect \n", "8 Investigation complete; no suspect identified \n", "9 Investigation complete; no suspect identified \n", "10 Investigation complete; no suspect identified " ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#Now lets take a look at the dataset\n", "new_street1.head()" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:25:46.569081Z", "iopub.status.busy": "2021-02-27T00:25:46.568308Z", "iopub.status.idle": "2021-02-27T00:25:46.634595Z", "shell.execute_reply": "2021-02-27T00:25:46.635276Z" }, "papermill": { "duration": 0.102973, "end_time": "2021-02-27T00:25:46.635476", "exception": false, "start_time": "2021-02-27T00:25:46.532503", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n", "A value is trying to be set on a copy of a slice from a DataFrame.\n", "Try using .loc[row_indexer,col_indexer] = value instead\n", "\n", "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", " \n" ] } ], "source": [ "#Want too change Month column to string so I can slice the year\n", "new_street1['Month'] = new_street1['Month'].astype(str)" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:25:46.915338Z", "iopub.status.busy": "2021-02-27T00:25:46.914571Z", "iopub.status.idle": "2021-02-27T00:25:48.653420Z", "shell.execute_reply": "2021-02-27T00:25:48.654016Z" }, "papermill": { "duration": 1.987598, "end_time": "2021-02-27T00:25:48.654238", "exception": false, "start_time": "2021-02-27T00:25:46.666640", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n", "A value is trying to be set on a copy of a slice from a DataFrame.\n", "Try using .loc[row_indexer,col_indexer] = value instead\n", "\n", "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", " \n", "/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:3: SettingWithCopyWarning: \n", "A value is trying to be set on a copy of a slice from a DataFrame.\n", "Try using .loc[row_indexer,col_indexer] = value instead\n", "\n", "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", " This is separate from the ipykernel package so we can avoid doing imports until\n" ] } ], "source": [ "#Make new columns for year and month separately\n", "new_street1['Year'] = new_street1.Month.str[0:4]\n", "new_street1['month'] = new_street1.Month.str[6:]" ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:25:48.740021Z", "iopub.status.busy": "2021-02-27T00:25:48.739186Z", "iopub.status.idle": "2021-02-27T00:25:48.743865Z", "shell.execute_reply": "2021-02-27T00:25:48.743318Z" }, "papermill": { "duration": 0.057744, "end_time": "2021-02-27T00:25:48.744035", "exception": false, "start_time": "2021-02-27T00:25:48.686291", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>Crime ID</th>\n", " <th>Month</th>\n", " <th>Reported by</th>\n", " <th>Falls within</th>\n", " <th>Longitude</th>\n", " <th>Latitude</th>\n", " <th>Location</th>\n", " <th>LSOA code</th>\n", " <th>LSOA name</th>\n", " <th>Crime type</th>\n", " <th>Last outcome category</th>\n", " <th>Year</th>\n", " <th>month</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>0</th>\n", " <td>324a40f7da5f81b2f6c96bc6fe3e300173782e3342f409...</td>\n", " <td>2014-06</td>\n", " <td>City of London Police</td>\n", " <td>City of London Police</td>\n", " <td>-0.113767</td>\n", " <td>51.517372</td>\n", " <td>On or near Stone Buildings</td>\n", " <td>E01000914</td>\n", " <td>Camden 028B</td>\n", " <td>Vehicle crime</td>\n", " <td>Investigation complete; no suspect identified</td>\n", " <td>2014</td>\n", " <td>6</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>62dde92ceeb12755a8a95a2829048ce4796ba3cfb3f7c0...</td>\n", " <td>2014-06</td>\n", " <td>City of London Police</td>\n", " <td>City of London Police</td>\n", " <td>-0.111497</td>\n", " <td>51.518226</td>\n", " <td>On or near Pedestrian Subway</td>\n", " <td>E01000914</td>\n", " <td>Camden 028B</td>\n", " <td>Violence and sexual offences</td>\n", " <td>Unable to prosecute suspect</td>\n", " <td>2014</td>\n", " <td>6</td>\n", " </tr>\n", " <tr>\n", " <th>8</th>\n", " <td>92be9a7d4c6c076cf245d15ca162d675ec65139ad5fabe...</td>\n", " <td>2014-06</td>\n", " <td>City of London Police</td>\n", " <td>City of London Police</td>\n", " <td>-0.098572</td>\n", " <td>51.516767</td>\n", " <td>On or near King Edward Street</td>\n", " <td>E01000001</td>\n", " <td>City of London 001A</td>\n", " <td>Bicycle theft</td>\n", " <td>Investigation complete; no suspect identified</td>\n", " <td>2014</td>\n", " <td>6</td>\n", " </tr>\n", " <tr>\n", " <th>9</th>\n", " <td>d37709a832130d3cfe650daa327b700968b3d1b3620622...</td>\n", " <td>2014-06</td>\n", " <td>City of London Police</td>\n", " <td>City of London Police</td>\n", " <td>-0.097562</td>\n", " <td>51.518864</td>\n", " <td>On or near Parking Area</td>\n", " <td>E01000001</td>\n", " <td>City of London 001A</td>\n", " <td>Bicycle theft</td>\n", " <td>Investigation complete; no suspect identified</td>\n", " <td>2014</td>\n", " <td>6</td>\n", " </tr>\n", " <tr>\n", " <th>10</th>\n", " <td>6ccf322a44296c494627bfcf687b876841b1012bb08691...</td>\n", " <td>2014-06</td>\n", " <td>City of London Police</td>\n", " <td>City of London Police</td>\n", " <td>-0.097601</td>\n", " <td>51.520699</td>\n", " <td>On or near Carthusian Street</td>\n", " <td>E01000001</td>\n", " <td>City of London 001A</td>\n", " <td>Other theft</td>\n", " <td>Investigation complete; no suspect identified</td>\n", " <td>2014</td>\n", " <td>6</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " Crime ID Month \\\n", "0 324a40f7da5f81b2f6c96bc6fe3e300173782e3342f409... 2014-06 \n", "1 62dde92ceeb12755a8a95a2829048ce4796ba3cfb3f7c0... 2014-06 \n", "8 92be9a7d4c6c076cf245d15ca162d675ec65139ad5fabe... 2014-06 \n", "9 d37709a832130d3cfe650daa327b700968b3d1b3620622... 2014-06 \n", "10 6ccf322a44296c494627bfcf687b876841b1012bb08691... 2014-06 \n", "\n", " Reported by Falls within Longitude Latitude \\\n", "0 City of London Police City of London Police -0.113767 51.517372 \n", "1 City of London Police City of London Police -0.111497 51.518226 \n", "8 City of London Police City of London Police -0.098572 51.516767 \n", "9 City of London Police City of London Police -0.097562 51.518864 \n", "10 City of London Police City of London Police -0.097601 51.520699 \n", "\n", " Location LSOA code LSOA name \\\n", "0 On or near Stone Buildings E01000914 Camden 028B \n", "1 On or near Pedestrian Subway E01000914 Camden 028B \n", "8 On or near King Edward Street E01000001 City of London 001A \n", "9 On or near Parking Area E01000001 City of London 001A \n", "10 On or near Carthusian Street E01000001 City of London 001A \n", "\n", " Crime type \\\n", "0 Vehicle crime \n", "1 Violence and sexual offences \n", "8 Bicycle theft \n", "9 Bicycle theft \n", "10 Other theft \n", "\n", " Last outcome category Year month \n", "0 Investigation complete; no suspect identified 2014 6 \n", "1 Unable to prosecute suspect 2014 6 \n", "8 Investigation complete; no suspect identified 2014 6 \n", "9 Investigation complete; no suspect identified 2014 6 \n", "10 Investigation complete; no suspect identified 2014 6 " ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#Year and month column have now been created\n", "new_street1.head()" ] }, { "cell_type": "code", "execution_count": 16, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:25:48.816277Z", "iopub.status.busy": "2021-02-27T00:25:48.815555Z", "iopub.status.idle": "2021-02-27T00:25:49.772483Z", "shell.execute_reply": "2021-02-27T00:25:49.771740Z" }, "papermill": { "duration": 0.994853, "end_time": "2021-02-27T00:25:49.772672", "exception": false, "start_time": "2021-02-27T00:25:48.777819", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "#Import package for plotting\n", "import seaborn as sns" ] }, { "cell_type": "code", "execution_count": 17, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:25:50.053395Z", "iopub.status.busy": "2021-02-27T00:25:50.052615Z", "iopub.status.idle": "2021-02-27T00:25:52.594584Z", "shell.execute_reply": "2021-02-27T00:25:52.593388Z" }, "papermill": { "duration": 2.788815, "end_time": "2021-02-27T00:25:52.594781", "exception": false, "start_time": "2021-02-27T00:25:49.805966", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "<AxesSubplot:xlabel='Reported by', ylabel='count'>" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "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\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "#Count plot to show frequency of unique values in Reported by column\n", "sns.countplot(x='Reported by', data=new_street1)" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.033515, "end_time": "2021-02-27T00:25:52.662278", "exception": false, "start_time": "2021-02-27T00:25:52.628763", "status": "completed" }, "tags": [] }, "source": [ "The count plot shows interesting data. It can be see that there are only two places that report London Crime. What I am interested in is if 'Reported by' and 'Falls within' are going to be very similar in their results." ] }, { "cell_type": "code", "execution_count": 18, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:25:52.973995Z", "iopub.status.busy": "2021-02-27T00:25:52.973021Z", "iopub.status.idle": "2021-02-27T00:25:55.457368Z", "shell.execute_reply": "2021-02-27T00:25:55.456713Z" }, "papermill": { "duration": 2.759792, "end_time": "2021-02-27T00:25:55.457530", "exception": false, "start_time": "2021-02-27T00:25:52.697738", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "<AxesSubplot:xlabel='Falls within', ylabel='count'>" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": "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\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "#Count plot to show frequency of unique values in Falls within by column\n", "sns.countplot(x='Falls within', data=new_street1)" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.036599, "end_time": "2021-02-27T00:25:55.531020", "exception": false, "start_time": "2021-02-27T00:25:55.494421", "status": "completed" }, "tags": [] }, "source": [ "We have a very similar graph so I want to go in and check the actual value counts for each column" ] }, { "cell_type": "code", "execution_count": 19, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:25:56.138182Z", "iopub.status.busy": "2021-02-27T00:25:56.137219Z", "iopub.status.idle": "2021-02-27T00:25:56.145409Z", "shell.execute_reply": "2021-02-27T00:25:56.144755Z" }, "papermill": { "duration": 0.578576, "end_time": "2021-02-27T00:25:56.145573", "exception": false, "start_time": "2021-02-27T00:25:55.566997", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "Metropolitan Police Service 2188554\n", "City of London Police 15358\n", "Name: Reported by, dtype: int64" ] }, "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#Value count for Reported by\n", "new_street1['Reported by'].value_counts()" ] }, { "cell_type": "code", "execution_count": 20, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:25:56.756491Z", "iopub.status.busy": "2021-02-27T00:25:56.547172Z", "iopub.status.idle": "2021-02-27T00:25:56.765564Z", "shell.execute_reply": "2021-02-27T00:25:56.765013Z" }, "papermill": { "duration": 0.58262, "end_time": "2021-02-27T00:25:56.765747", "exception": false, "start_time": "2021-02-27T00:25:56.183127", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "Metropolitan Police Service 2188554\n", "City of London Police 15358\n", "Name: Falls within, dtype: int64" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#Value count for Falls within\n", "new_street1['Falls within'].value_counts()" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.03561, "end_time": "2021-02-27T00:25:56.837426", "exception": false, "start_time": "2021-02-27T00:25:56.801816", "status": "completed" }, "tags": [] }, "source": [ "From the results it can be shown that there was not a whole lot of value in making two separate columns when these columns show the exact same data. It is possible that randomly the numbers add up and the columns are not the same for every entry, but the odds of that are incredibly low given we have an exact match for over 232,000 entries." ] }, { "cell_type": "code", "execution_count": 21, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:25:56.916187Z", "iopub.status.busy": "2021-02-27T00:25:56.915338Z", "iopub.status.idle": "2021-02-27T00:26:01.460881Z", "shell.execute_reply": "2021-02-27T00:26:01.461776Z" }, "papermill": { "duration": 4.588386, "end_time": "2021-02-27T00:26:01.461985", "exception": false, "start_time": "2021-02-27T00:25:56.873599", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "<AxesSubplot:xlabel='Latitude', ylabel='Longitude'>" ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "#Quick sketch of Latitude and Longitude columns for entries\n", "sns.scatterplot(x=\"Latitude\", y=\"Longitude\", data=new_street1)" ] }, { "cell_type": "code", "execution_count": 22, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:26:01.542602Z", "iopub.status.busy": "2021-02-27T00:26:01.541547Z", "iopub.status.idle": "2021-02-27T00:26:02.302595Z", "shell.execute_reply": "2021-02-27T00:26:02.302037Z" }, "papermill": { "duration": 0.802858, "end_time": "2021-02-27T00:26:02.302779", "exception": false, "start_time": "2021-02-27T00:26:01.499921", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "On or near Supermarket 98057\n", "On or near Shopping Area 62376\n", "On or near Petrol Station 59273\n", "On or near Parking Area 59244\n", "On or near Nightclub 35202\n", " ... \n", "On or near Pike Lane 1\n", "On or near Muncaster Close 1\n", "On or near Buchanan Court 1\n", "On or near Lichfield Terrace 1\n", "On or near Sylvester Drive 1\n", "Name: Location, Length: 36352, dtype: int64" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#Find value_count of Location column\n", "new_street1['Location'].value_counts()" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.038641, "end_time": "2021-02-27T00:26:02.379988", "exception": false, "start_time": "2021-02-27T00:26:02.341347", "status": "completed" }, "tags": [] }, "source": [ "The Location column is very interesting. Out of our 230,000+ entries we have over 36,000 locations that were recorded. For each entry there can only be one location so it will be interesting too see how this columns fits with analyzing the datasets later." ] }, { "cell_type": "code", "execution_count": 23, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:26:03.028039Z", "iopub.status.busy": "2021-02-27T00:26:03.026957Z", "iopub.status.idle": "2021-02-27T00:26:03.040301Z", "shell.execute_reply": "2021-02-27T00:26:03.040827Z" }, "papermill": { "duration": 0.622057, "end_time": "2021-02-27T00:26:03.041048", "exception": false, "start_time": "2021-02-27T00:26:02.418991", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "Westminster 013E 15970\n", "Westminster 018A 13232\n", "Westminster 013B 11487\n", "City of London 001F 10718\n", "Westminster 018C 8259\n", " ... \n", "Gravesham 003D 1\n", "Tonbridge and Malling 014C 1\n", "Salford 003B 1\n", "Wealden 004B 1\n", "Slough 012F 1\n", "Name: LSOA name, Length: 6907, dtype: int64" ] }, "execution_count": 23, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#LSOA name and LSOA code have same information\n", "new_street1['LSOA name'].value_counts()" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.040858, "end_time": "2021-02-27T00:26:03.121346", "exception": false, "start_time": "2021-02-27T00:26:03.080488", "status": "completed" }, "tags": [] }, "source": [ "Like our Locations column this might not give us a lot of information. However, we may be able to get more information out of this if we make a new column negating the code identifcation at the end of the LSOA name." ] }, { "cell_type": "code", "execution_count": 24, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:26:03.208431Z", "iopub.status.busy": "2021-02-27T00:26:03.206862Z", "iopub.status.idle": "2021-02-27T00:26:03.269411Z", "shell.execute_reply": "2021-02-27T00:26:03.270184Z" }, "papermill": { "duration": 0.109658, "end_time": "2021-02-27T00:26:03.270457", "exception": false, "start_time": "2021-02-27T00:26:03.160799", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:2: SettingWithCopyWarning: \n", "A value is trying to be set on a copy of a slice from a DataFrame.\n", "Try using .loc[row_indexer,col_indexer] = value instead\n", "\n", "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", " \n" ] } ], "source": [ "#Want too change LSOA name column to string so I can slice end of it off\n", "new_street1['LSOA name'] = new_street1['LSOA name'].astype(str)" ] }, { "cell_type": "code", "execution_count": 25, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:26:03.372523Z", "iopub.status.busy": "2021-02-27T00:26:03.371463Z", "iopub.status.idle": "2021-02-27T00:26:03.377337Z", "shell.execute_reply": "2021-02-27T00:26:03.376795Z" }, "papermill": { "duration": 0.066287, "end_time": "2021-02-27T00:26:03.377504", "exception": false, "start_time": "2021-02-27T00:26:03.311217", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>Crime ID</th>\n", " <th>Month</th>\n", " <th>Reported by</th>\n", " <th>Falls within</th>\n", " <th>Longitude</th>\n", " <th>Latitude</th>\n", " <th>Location</th>\n", " <th>LSOA code</th>\n", " <th>LSOA name</th>\n", " <th>Crime type</th>\n", " <th>Last outcome category</th>\n", " <th>Year</th>\n", " <th>month</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>0</th>\n", " <td>324a40f7da5f81b2f6c96bc6fe3e300173782e3342f409...</td>\n", " <td>2014-06</td>\n", " <td>City of London Police</td>\n", " <td>City of London Police</td>\n", " <td>-0.113767</td>\n", " <td>51.517372</td>\n", " <td>On or near Stone Buildings</td>\n", " <td>E01000914</td>\n", " <td>Camden 028B</td>\n", " <td>Vehicle crime</td>\n", " <td>Investigation complete; no suspect identified</td>\n", " <td>2014</td>\n", " <td>6</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>62dde92ceeb12755a8a95a2829048ce4796ba3cfb3f7c0...</td>\n", " <td>2014-06</td>\n", " <td>City of London Police</td>\n", " <td>City of London Police</td>\n", " <td>-0.111497</td>\n", " <td>51.518226</td>\n", " <td>On or near Pedestrian Subway</td>\n", " <td>E01000914</td>\n", " <td>Camden 028B</td>\n", " <td>Violence and sexual offences</td>\n", " <td>Unable to prosecute suspect</td>\n", " <td>2014</td>\n", " <td>6</td>\n", " </tr>\n", " <tr>\n", " <th>8</th>\n", " <td>92be9a7d4c6c076cf245d15ca162d675ec65139ad5fabe...</td>\n", " <td>2014-06</td>\n", " <td>City of London Police</td>\n", " <td>City of London Police</td>\n", " <td>-0.098572</td>\n", " <td>51.516767</td>\n", " <td>On or near King Edward Street</td>\n", " <td>E01000001</td>\n", " <td>City of London 001A</td>\n", " <td>Bicycle theft</td>\n", " <td>Investigation complete; no suspect identified</td>\n", " <td>2014</td>\n", " <td>6</td>\n", " </tr>\n", " <tr>\n", " <th>9</th>\n", " <td>d37709a832130d3cfe650daa327b700968b3d1b3620622...</td>\n", " <td>2014-06</td>\n", " <td>City of London Police</td>\n", " <td>City of London Police</td>\n", " <td>-0.097562</td>\n", " <td>51.518864</td>\n", " <td>On or near Parking Area</td>\n", " <td>E01000001</td>\n", " <td>City of London 001A</td>\n", " <td>Bicycle theft</td>\n", " <td>Investigation complete; no suspect identified</td>\n", " <td>2014</td>\n", " <td>6</td>\n", " </tr>\n", " <tr>\n", " <th>10</th>\n", " <td>6ccf322a44296c494627bfcf687b876841b1012bb08691...</td>\n", " <td>2014-06</td>\n", " <td>City of London Police</td>\n", " <td>City of London Police</td>\n", " <td>-0.097601</td>\n", " <td>51.520699</td>\n", " <td>On or near Carthusian Street</td>\n", " <td>E01000001</td>\n", " <td>City of London 001A</td>\n", " <td>Other theft</td>\n", " <td>Investigation complete; no suspect identified</td>\n", " <td>2014</td>\n", " <td>6</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " Crime ID Month \\\n", "0 324a40f7da5f81b2f6c96bc6fe3e300173782e3342f409... 2014-06 \n", "1 62dde92ceeb12755a8a95a2829048ce4796ba3cfb3f7c0... 2014-06 \n", "8 92be9a7d4c6c076cf245d15ca162d675ec65139ad5fabe... 2014-06 \n", "9 d37709a832130d3cfe650daa327b700968b3d1b3620622... 2014-06 \n", "10 6ccf322a44296c494627bfcf687b876841b1012bb08691... 2014-06 \n", "\n", " Reported by Falls within Longitude Latitude \\\n", "0 City of London Police City of London Police -0.113767 51.517372 \n", "1 City of London Police City of London Police -0.111497 51.518226 \n", "8 City of London Police City of London Police -0.098572 51.516767 \n", "9 City of London Police City of London Police -0.097562 51.518864 \n", "10 City of London Police City of London Police -0.097601 51.520699 \n", "\n", " Location LSOA code LSOA name \\\n", "0 On or near Stone Buildings E01000914 Camden 028B \n", "1 On or near Pedestrian Subway E01000914 Camden 028B \n", "8 On or near King Edward Street E01000001 City of London 001A \n", "9 On or near Parking Area E01000001 City of London 001A \n", "10 On or near Carthusian Street E01000001 City of London 001A \n", "\n", " Crime type \\\n", "0 Vehicle crime \n", "1 Violence and sexual offences \n", "8 Bicycle theft \n", "9 Bicycle theft \n", "10 Other theft \n", "\n", " Last outcome category Year month \n", "0 Investigation complete; no suspect identified 2014 6 \n", "1 Unable to prosecute suspect 2014 6 \n", "8 Investigation complete; no suspect identified 2014 6 \n", "9 Investigation complete; no suspect identified 2014 6 \n", "10 Investigation complete; no suspect identified 2014 6 " ] }, "execution_count": 25, "metadata": {}, "output_type": "execute_result" } ], "source": [ "new_street1.head()" ] }, { "cell_type": "code", "execution_count": 26, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:26:03.673577Z", "iopub.status.busy": "2021-02-27T00:26:03.672854Z", "iopub.status.idle": "2021-02-27T00:26:04.657312Z", "shell.execute_reply": "2021-02-27T00:26:04.656632Z" }, "papermill": { "duration": 1.238592, "end_time": "2021-02-27T00:26:04.657475", "exception": false, "start_time": "2021-02-27T00:26:03.418883", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/opt/conda/lib/python3.7/site-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \n", "A value is trying to be set on a copy of a slice from a DataFrame.\n", "Try using .loc[row_indexer,col_indexer] = value instead\n", "\n", "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", " \"\"\"Entry point for launching an IPython kernel.\n" ] } ], "source": [ "new_street1['LSOA_Region'] = new_street1['LSOA name'].str[:-4]" ] }, { "cell_type": "code", "execution_count": 27, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:26:04.765037Z", "iopub.status.busy": "2021-02-27T00:26:04.763716Z", "iopub.status.idle": "2021-02-27T00:26:04.770017Z", "shell.execute_reply": "2021-02-27T00:26:04.769259Z" }, "papermill": { "duration": 0.07136, "end_time": "2021-02-27T00:26:04.770236", "exception": false, "start_time": "2021-02-27T00:26:04.698876", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>Crime ID</th>\n", " <th>Month</th>\n", " <th>Reported by</th>\n", " <th>Falls within</th>\n", " <th>Longitude</th>\n", " <th>Latitude</th>\n", " <th>Location</th>\n", " <th>LSOA code</th>\n", " <th>LSOA name</th>\n", " <th>Crime type</th>\n", " <th>Last outcome category</th>\n", " <th>Year</th>\n", " <th>month</th>\n", " <th>LSOA_Region</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>0</th>\n", " <td>324a40f7da5f81b2f6c96bc6fe3e300173782e3342f409...</td>\n", " <td>2014-06</td>\n", " <td>City of London Police</td>\n", " <td>City of London Police</td>\n", " <td>-0.113767</td>\n", " <td>51.517372</td>\n", " <td>On or near Stone Buildings</td>\n", " <td>E01000914</td>\n", " <td>Camden 028B</td>\n", " <td>Vehicle crime</td>\n", " <td>Investigation complete; no suspect identified</td>\n", " <td>2014</td>\n", " <td>6</td>\n", " <td>Camden</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>62dde92ceeb12755a8a95a2829048ce4796ba3cfb3f7c0...</td>\n", " <td>2014-06</td>\n", " <td>City of London Police</td>\n", " <td>City of London Police</td>\n", " <td>-0.111497</td>\n", " <td>51.518226</td>\n", " <td>On or near Pedestrian Subway</td>\n", " <td>E01000914</td>\n", " <td>Camden 028B</td>\n", " <td>Violence and sexual offences</td>\n", " <td>Unable to prosecute suspect</td>\n", " <td>2014</td>\n", " <td>6</td>\n", " <td>Camden</td>\n", " </tr>\n", " <tr>\n", " <th>8</th>\n", " <td>92be9a7d4c6c076cf245d15ca162d675ec65139ad5fabe...</td>\n", " <td>2014-06</td>\n", " <td>City of London Police</td>\n", " <td>City of London Police</td>\n", " <td>-0.098572</td>\n", " <td>51.516767</td>\n", " <td>On or near King Edward Street</td>\n", " <td>E01000001</td>\n", " <td>City of London 001A</td>\n", " <td>Bicycle theft</td>\n", " <td>Investigation complete; no suspect identified</td>\n", " <td>2014</td>\n", " <td>6</td>\n", " <td>City of London</td>\n", " </tr>\n", " <tr>\n", " <th>9</th>\n", " <td>d37709a832130d3cfe650daa327b700968b3d1b3620622...</td>\n", " <td>2014-06</td>\n", " <td>City of London Police</td>\n", " <td>City of London Police</td>\n", " <td>-0.097562</td>\n", " <td>51.518864</td>\n", " <td>On or near Parking Area</td>\n", " <td>E01000001</td>\n", " <td>City of London 001A</td>\n", " <td>Bicycle theft</td>\n", " <td>Investigation complete; no suspect identified</td>\n", " <td>2014</td>\n", " <td>6</td>\n", " <td>City of London</td>\n", " </tr>\n", " <tr>\n", " <th>10</th>\n", " <td>6ccf322a44296c494627bfcf687b876841b1012bb08691...</td>\n", " <td>2014-06</td>\n", " <td>City of London Police</td>\n", " <td>City of London Police</td>\n", " <td>-0.097601</td>\n", " <td>51.520699</td>\n", " <td>On or near Carthusian Street</td>\n", " <td>E01000001</td>\n", " <td>City of London 001A</td>\n", " <td>Other theft</td>\n", " <td>Investigation complete; no suspect identified</td>\n", " <td>2014</td>\n", " <td>6</td>\n", " <td>City of London</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " Crime ID Month \\\n", "0 324a40f7da5f81b2f6c96bc6fe3e300173782e3342f409... 2014-06 \n", "1 62dde92ceeb12755a8a95a2829048ce4796ba3cfb3f7c0... 2014-06 \n", "8 92be9a7d4c6c076cf245d15ca162d675ec65139ad5fabe... 2014-06 \n", "9 d37709a832130d3cfe650daa327b700968b3d1b3620622... 2014-06 \n", "10 6ccf322a44296c494627bfcf687b876841b1012bb08691... 2014-06 \n", "\n", " Reported by Falls within Longitude Latitude \\\n", "0 City of London Police City of London Police -0.113767 51.517372 \n", "1 City of London Police City of London Police -0.111497 51.518226 \n", "8 City of London Police City of London Police -0.098572 51.516767 \n", "9 City of London Police City of London Police -0.097562 51.518864 \n", "10 City of London Police City of London Police -0.097601 51.520699 \n", "\n", " Location LSOA code LSOA name \\\n", "0 On or near Stone Buildings E01000914 Camden 028B \n", "1 On or near Pedestrian Subway E01000914 Camden 028B \n", "8 On or near King Edward Street E01000001 City of London 001A \n", "9 On or near Parking Area E01000001 City of London 001A \n", "10 On or near Carthusian Street E01000001 City of London 001A \n", "\n", " Crime type \\\n", "0 Vehicle crime \n", "1 Violence and sexual offences \n", "8 Bicycle theft \n", "9 Bicycle theft \n", "10 Other theft \n", "\n", " Last outcome category Year month LSOA_Region \n", "0 Investigation complete; no suspect identified 2014 6 Camden \n", "1 Unable to prosecute suspect 2014 6 Camden \n", "8 Investigation complete; no suspect identified 2014 6 City of London \n", "9 Investigation complete; no suspect identified 2014 6 City of London \n", "10 Investigation complete; no suspect identified 2014 6 City of London " ] }, "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ "new_street1.head()" ] }, { "cell_type": "code", "execution_count": 28, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:26:05.448358Z", "iopub.status.busy": "2021-02-27T00:26:05.447590Z", "iopub.status.idle": "2021-02-27T00:26:05.457180Z", "shell.execute_reply": "2021-02-27T00:26:05.456529Z" }, "papermill": { "duration": 0.644663, "end_time": "2021-02-27T00:26:05.457345", "exception": false, "start_time": "2021-02-27T00:26:04.812682", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "Westminster 146901\n", "Lambeth 100443\n", "Southwark 92588\n", "Newham 89084\n", "Camden 87449\n", " ... \n", "Gedling 1\n", "Hartlepool 1\n", "South Ribble 1\n", "South Tyneside 1\n", "Isle of Anglesey 1\n", "Name: LSOA_Region, Length: 312, dtype: int64" ] }, "execution_count": 28, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#Now we will look at new LSOA region\n", "new_street1['LSOA_Region'].value_counts()" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.0428, "end_time": "2021-02-27T00:26:05.543076", "exception": false, "start_time": "2021-02-27T00:26:05.500276", "status": "completed" }, "tags": [] }, "source": [ "We are able to see that we have 312 different section that are have entries in the dataset." ] }, { "cell_type": "code", "execution_count": 29, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:26:05.958747Z", "iopub.status.busy": "2021-02-27T00:26:05.957996Z", "iopub.status.idle": "2021-02-27T00:26:06.174298Z", "shell.execute_reply": "2021-02-27T00:26:06.174855Z" }, "papermill": { "duration": 0.588928, "end_time": "2021-02-27T00:26:06.175062", "exception": false, "start_time": "2021-02-27T00:26:05.586134", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "Violence and sexual offences 584602\n", "Other theft 329281\n", "Vehicle crime 260235\n", "Burglary 211926\n", "Criminal damage and arson 183108\n", "Shoplifting 134777\n", "Public order 128034\n", "Theft from the person 106704\n", "Drugs 103542\n", "Robbery 67641\n", "Bicycle theft 53889\n", "Other crime 27532\n", "Possession of weapons 12641\n", "Name: Crime type, dtype: int64" ] }, "execution_count": 29, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#Frequency of unique values in Crime type column\n", "new_street1['Crime type'].value_counts()" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.042998, "end_time": "2021-02-27T00:26:06.261492", "exception": false, "start_time": "2021-02-27T00:26:06.218494", "status": "completed" }, "tags": [] }, "source": [ "We have 13 different types of crime that were reported in the dataset." ] }, { "cell_type": "code", "execution_count": 30, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:26:06.353209Z", "iopub.status.busy": "2021-02-27T00:26:06.352165Z", "iopub.status.idle": "2021-02-27T00:26:06.902205Z", "shell.execute_reply": "2021-02-27T00:26:06.902981Z" }, "papermill": { "duration": 0.598385, "end_time": "2021-02-27T00:26:06.903189", "exception": false, "start_time": "2021-02-27T00:26:06.304804", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "Investigation complete; no suspect identified 1068494\n", "Status update unavailable 616948\n", "Under investigation 163653\n", "Offender given a caution 62570\n", "Court result unavailable 48733\n", "Offender given a drugs possession warning 37798\n", "Defendant found not guilty 28052\n", "Awaiting court outcome 27463\n", "Offender sent to prison 27375\n", "Offender given community sentence 23325\n", "Local resolution 20308\n", "Offender fined 19555\n", "Offender given penalty notice 18460\n", "Offender given suspended prison sentence 13200\n", "Offender given conditional discharge 11432\n", "Court case unable to proceed 8399\n", "Offender otherwise dealt with 2439\n", "Unable to prosecute suspect 1655\n", "Offender ordered to pay compensation 1648\n", "Offender deprived of property 1215\n", "Suspect charged as part of another case 537\n", "Offender given absolute discharge 303\n", "Defendant sent to Crown Court 188\n", "Formal action is not in the public interest 147\n", "Further investigation is not in the public interest 12\n", "Action to be taken by another organisation 3\n", "Name: Last outcome category, dtype: int64" ] }, "execution_count": 30, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#Frequency of unique values in Last outcome category column\n", "new_street1['Last outcome category'].value_counts()" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.046719, "end_time": "2021-02-27T00:26:06.994838", "exception": false, "start_time": "2021-02-27T00:26:06.948119", "status": "completed" }, "tags": [] }, "source": [ "We have quite a few outcome category results. Not sure what I want done to this column yet. May come back to it later in the data cleaning process." ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.044302, "end_time": "2021-02-27T00:26:07.082866", "exception": false, "start_time": "2021-02-27T00:26:07.038564", "status": "completed" }, "tags": [] }, "source": [ "# Cleaning Search Data" ] }, { "cell_type": "code", "execution_count": 31, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:26:07.175239Z", "iopub.status.busy": "2021-02-27T00:26:07.174206Z", "iopub.status.idle": "2021-02-27T00:26:07.196227Z", "shell.execute_reply": "2021-02-27T00:26:07.196713Z" }, "papermill": { "duration": 0.069878, "end_time": "2021-02-27T00:26:07.196916", "exception": false, "start_time": "2021-02-27T00:26:07.127038", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>Type</th>\n", " <th>Date</th>\n", " <th>Part of a policing operation</th>\n", " <th>Policing operation</th>\n", " <th>Latitude</th>\n", " <th>Longitude</th>\n", " <th>Gender</th>\n", " <th>Age range</th>\n", " <th>Self-defined ethnicity</th>\n", " <th>Officer-defined ethnicity</th>\n", " <th>Legislation</th>\n", " <th>Object of search</th>\n", " <th>Outcome</th>\n", " <th>Outcome linked to object of search</th>\n", " <th>Removal of more than just outer clothing</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>0</th>\n", " <td>Person search</td>\n", " <td>2015-03-02T16:40:00+00:00</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>Male</td>\n", " <td>25-34</td>\n", " <td>Asian or Asian British - Bangladeshi (A3)</td>\n", " <td>Asian</td>\n", " <td>Police and Criminal Evidence Act 1984 (section 1)</td>\n", " <td>Stolen goods</td>\n", " <td>Suspect arrested</td>\n", " <td>True</td>\n", " <td>False</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>Person search</td>\n", " <td>2015-03-02T16:40:00+00:00</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>Male</td>\n", " <td>25-34</td>\n", " <td>Asian or Asian British - Bangladeshi (A3)</td>\n", " <td>Asian</td>\n", " <td>Police and Criminal Evidence Act 1984 (section 1)</td>\n", " <td>Stolen goods</td>\n", " <td>Suspect arrested</td>\n", " <td>False</td>\n", " <td>False</td>\n", " </tr>\n", " <tr>\n", " <th>2</th>\n", " <td>Person search</td>\n", " <td>2015-03-02T18:45:00+00:00</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>Male</td>\n", " <td>25-34</td>\n", " <td>White - Any other White ethnic background (W9)</td>\n", " <td>White</td>\n", " <td>Police and Criminal Evidence Act 1984 (section 1)</td>\n", " <td>NaN</td>\n", " <td>Suspect arrested</td>\n", " <td>True</td>\n", " <td>True</td>\n", " </tr>\n", " <tr>\n", " <th>3</th>\n", " <td>Person search</td>\n", " <td>2015-03-02T19:15:00+00:00</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>Male</td>\n", " <td>over 34</td>\n", " <td>White - White British (W1)</td>\n", " <td>White</td>\n", " <td>Police and Criminal Evidence Act 1984 (section 1)</td>\n", " <td>Stolen goods</td>\n", " <td>Suspect arrested</td>\n", " <td>False</td>\n", " <td>False</td>\n", " </tr>\n", " <tr>\n", " <th>4</th>\n", " <td>Person and Vehicle search</td>\n", " <td>2015-03-03T15:50:00+00:00</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>Male</td>\n", " <td>25-34</td>\n", " <td>White - White British (W1)</td>\n", " <td>White</td>\n", " <td>Police and Criminal Evidence Act 1984 (section 1)</td>\n", " <td>Stolen goods</td>\n", " <td>Suspect arrested</td>\n", " <td>True</td>\n", " <td>True</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " Type Date \\\n", "0 Person search 2015-03-02T16:40:00+00:00 \n", "1 Person search 2015-03-02T16:40:00+00:00 \n", "2 Person search 2015-03-02T18:45:00+00:00 \n", "3 Person search 2015-03-02T19:15:00+00:00 \n", "4 Person and Vehicle search 2015-03-03T15:50:00+00:00 \n", "\n", " Part of a policing operation Policing operation Latitude Longitude \\\n", "0 NaN NaN NaN NaN \n", "1 NaN NaN NaN NaN \n", "2 NaN NaN NaN NaN \n", "3 NaN NaN NaN NaN \n", "4 NaN NaN NaN NaN \n", "\n", " Gender Age range Self-defined ethnicity \\\n", "0 Male 25-34 Asian or Asian British - Bangladeshi (A3) \n", "1 Male 25-34 Asian or Asian British - Bangladeshi (A3) \n", "2 Male 25-34 White - Any other White ethnic background (W9) \n", "3 Male over 34 White - White British (W1) \n", "4 Male 25-34 White - White British (W1) \n", "\n", " Officer-defined ethnicity \\\n", "0 Asian \n", "1 Asian \n", "2 White \n", "3 White \n", "4 White \n", "\n", " Legislation Object of search \\\n", "0 Police and Criminal Evidence Act 1984 (section 1) Stolen goods \n", "1 Police and Criminal Evidence Act 1984 (section 1) Stolen goods \n", "2 Police and Criminal Evidence Act 1984 (section 1) NaN \n", "3 Police and Criminal Evidence Act 1984 (section 1) Stolen goods \n", "4 Police and Criminal Evidence Act 1984 (section 1) Stolen goods \n", "\n", " Outcome Outcome linked to object of search \\\n", "0 Suspect arrested True \n", "1 Suspect arrested False \n", "2 Suspect arrested True \n", "3 Suspect arrested False \n", "4 Suspect arrested True \n", "\n", " Removal of more than just outer clothing \n", "0 False \n", "1 False \n", "2 True \n", "3 False \n", "4 True " ] }, "execution_count": 31, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#Moving on to cleaning the search dataset\n", "search.head()" ] }, { "cell_type": "code", "execution_count": 32, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:26:07.289718Z", "iopub.status.busy": "2021-02-27T00:26:07.288670Z", "iopub.status.idle": "2021-02-27T00:26:07.605053Z", "shell.execute_reply": "2021-02-27T00:26:07.605569Z" }, "papermill": { "duration": 0.364901, "end_time": "2021-02-27T00:26:07.605825", "exception": false, "start_time": "2021-02-27T00:26:07.240924", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "<class 'pandas.core.frame.DataFrame'>\n", "RangeIndex: 302623 entries, 0 to 302622\n", "Data columns (total 15 columns):\n", " # Column Non-Null Count Dtype \n", "--- ------ -------------- ----- \n", " 0 Type 302623 non-null object \n", " 1 Date 302623 non-null object \n", " 2 Part of a policing operation 120808 non-null object \n", " 3 Policing operation 0 non-null float64\n", " 4 Latitude 110615 non-null float64\n", " 5 Longitude 110615 non-null float64\n", " 6 Gender 299453 non-null object \n", " 7 Age range 288579 non-null object \n", " 8 Self-defined ethnicity 299848 non-null object \n", " 9 Officer-defined ethnicity 298958 non-null object \n", " 10 Legislation 302623 non-null object \n", " 11 Object of search 216156 non-null object \n", " 12 Outcome 302623 non-null object \n", " 13 Outcome linked to object of search 1206 non-null object \n", " 14 Removal of more than just outer clothing 2789 non-null object \n", "dtypes: float64(3), object(12)\n", "memory usage: 34.6+ MB\n" ] } ], "source": [ "#Basic info of search dataset\n", "search.info()" ] }, { "cell_type": "code", "execution_count": 33, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:26:07.700861Z", "iopub.status.busy": "2021-02-27T00:26:07.700095Z", "iopub.status.idle": "2021-02-27T00:26:08.012317Z", "shell.execute_reply": "2021-02-27T00:26:08.012841Z" }, "papermill": { "duration": 0.36265, "end_time": "2021-02-27T00:26:08.013054", "exception": false, "start_time": "2021-02-27T00:26:07.650404", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "Type 0.000000\n", "Date 0.000000\n", "Part of a policing operation 0.600797\n", "Policing operation 1.000000\n", "Latitude 0.634479\n", "Longitude 0.634479\n", "Gender 0.010475\n", "Age range 0.046408\n", "Self-defined ethnicity 0.009170\n", "Officer-defined ethnicity 0.012111\n", "Legislation 0.000000\n", "Object of search 0.285725\n", "Outcome 0.000000\n", "Outcome linked to object of search 0.996015\n", "Removal of more than just outer clothing 0.990784\n", "dtype: float64" ] }, "execution_count": 33, "metadata": {}, "output_type": "execute_result" } ], "source": [ "#Find proportion of missing data in search dataset\n", "search.isnull().sum()/len(search)" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.046593, "end_time": "2021-02-27T00:26:08.104825", "exception": false, "start_time": "2021-02-27T00:26:08.058232", "status": "completed" }, "tags": [] }, "source": [ "Resources\n", "\n", "https://stackoverflow.com/questions/13413590/how-to-drop-rows-of-pandas-dataframe-whose-value-in-a-certain-column-is-nan\n", "https://stackoverflow.com/questions/31460146/plotting-value-counts-in-seaborn-barplot" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.9" }, "papermill": { "default_parameters": {}, "duration": 69.645041, "end_time": "2021-02-27T00:26:09.665962", "environment_variables": {}, "exception": null, "input_path": "__notebook__.ipynb", "output_path": "__notebook__.ipynb", "parameters": {}, "start_time": "2021-02-27T00:25:00.020921", "version": "2.2.2" } }, "nbformat": 4, "nbformat_minor": 4 }	0055/329/55329140.ipynb	s3://data-agents/kaggle-outputs/sharded/012_00055.jsonl.gz
{ "cells": [ { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.050698, "end_time": "2021-02-27T00:29:58.176713", "exception": false, "start_time": "2021-02-27T00:29:58.126015", "status": "completed" }, "tags": [] }, "source": [ "# Purpose\n", "\n", "This Notebook analyzes the Ames Housing dataset (\"Ames Dataset\") with a variety of basic regression models. \n", "\n", "The Ames Dataset is comprised of data regarding houses that were sold in Ames, Iowa, from 2006 to 2010. It consists of 79 explanatory variables for the target variable of Sale Price. \n", "\n", "## Setting Up the Necessary Packages\n", "\n", "Here we just read in the various Python packages we will use in the notebook. " ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "_cell_guid": "cb1464a5-22df-4c2a-8a5f-7ddaa23a9c4e", "_uuid": "87f41ca1-f953-47b2-aff4-20696e97a066", "execution": { "iopub.execute_input": "2021-02-27T00:29:58.283174Z", "iopub.status.busy": "2021-02-27T00:29:58.282294Z", "iopub.status.idle": "2021-02-27T00:30:00.681130Z", "shell.execute_reply": "2021-02-27T00:30:00.681665Z" }, "papermill": { "duration": 2.457338, "end_time": "2021-02-27T00:30:00.682120", "exception": false, "start_time": "2021-02-27T00:29:58.224782", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "import numpy as py\n", "import pandas as pd\n", "import os\n", "import math\n", "\n", "from sklearn.metrics import mean_absolute_error\n", "from sklearn.metrics import mean_squared_error\n", "from sklearn.model_selection import cross_val_score\n", "from sklearn.metrics import make_scorer\n", "from sklearn.model_selection import GridSearchCV\n", "\n", "\n", "import matplotlib.pyplot as plt\n", "from matplotlib.pyplot import plot\n", "\n", "from sklearn.ensemble import RandomForestRegressor\n", "from sklearn.linear_model import LinearRegression\n", "from sklearn.linear_model import Ridge\n", "from sklearn.linear_model import Lasso\n", "from sklearn.tree import DecisionTreeRegressor\n", "from xgboost import XGBRegressor" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.04932, "end_time": "2021-02-27T00:30:00.779891", "exception": false, "start_time": "2021-02-27T00:30:00.730571", "status": "completed" }, "tags": [] }, "source": [ "## Loading the Data\n", "\n", "Here we are just reading in the data. " ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "_cell_guid": "aab3b3fc-21ff-4d47-9663-b1aed574864f", "_uuid": "64567815-fea1-46bf-9964-b0c51166b746", "execution": { "iopub.execute_input": "2021-02-27T00:30:00.883296Z", "iopub.status.busy": "2021-02-27T00:30:00.882429Z", "iopub.status.idle": "2021-02-27T00:30:00.977694Z", "shell.execute_reply": "2021-02-27T00:30:00.978295Z" }, "papermill": { "duration": 0.150798, "end_time": "2021-02-27T00:30:00.978500", "exception": false, "start_time": "2021-02-27T00:30:00.827702", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "############################\n", "######## Reading Data\n", "############################\n", "# Path of the file to read. \n", "\n", "iowa_file_path = '../input/home-data-for-ml-course/train.csv'\n", "test_data_path = '../input/home-data-for-ml-course/test.csv'\n", "\n", "home_data = pd.read_csv(iowa_file_path)\n", "test_home_data = pd.read_csv(test_data_path)" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.048018, "end_time": "2021-02-27T00:30:01.074189", "exception": false, "start_time": "2021-02-27T00:30:01.026171", "status": "completed" }, "tags": [] }, "source": [ "## Exploratory Data Analysis\n", "\n", "Below we can see all the explanatory variables in the set. Note that some of these variables probably could not be collected until a sale had completed or was imminment; such as, 'MoSold,' 'YrSold,' 'SaleType,' 'SaleCondition'. Additionally, the vague variables like 'MiscFeature,' and 'MiscVal' may be difficult to accommodate if one were to try to predict their values for a new house. \n" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:30:01.189267Z", "iopub.status.busy": "2021-02-27T00:30:01.187706Z", "iopub.status.idle": "2021-02-27T00:30:01.198275Z", "shell.execute_reply": "2021-02-27T00:30:01.199463Z" }, "papermill": { "duration": 0.077074, "end_time": "2021-02-27T00:30:01.199736", "exception": false, "start_time": "2021-02-27T00:30:01.122662", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "['MSSubClass',\n", " 'MSZoning',\n", " 'LotFrontage',\n", " 'LotArea',\n", " 'Street',\n", " 'Alley',\n", " 'LotShape',\n", " 'LandContour',\n", " 'Utilities',\n", " 'LotConfig',\n", " 'LandSlope',\n", " 'Neighborhood',\n", " 'Condition1',\n", " 'Condition2',\n", " 'BldgType',\n", " 'HouseStyle',\n", " 'OverallQual',\n", " 'OverallCond',\n", " 'YearBuilt',\n", " 'YearRemodAdd',\n", " 'RoofStyle',\n", " 'RoofMatl',\n", " 'Exterior1st',\n", " 'Exterior2nd',\n", " 'MasVnrType',\n", " 'MasVnrArea',\n", " 'ExterQual',\n", " 'ExterCond',\n", " 'Foundation',\n", " 'BsmtQual',\n", " 'BsmtCond',\n", " 'BsmtExposure',\n", " 'BsmtFinType1',\n", " 'BsmtFinSF1',\n", " 'BsmtFinType2',\n", " 'BsmtFinSF2',\n", " 'BsmtUnfSF',\n", " 'TotalBsmtSF',\n", " 'Heating',\n", " 'HeatingQC',\n", " 'CentralAir',\n", " 'Electrical',\n", " '1stFlrSF',\n", " '2ndFlrSF',\n", " 'LowQualFinSF',\n", " 'GrLivArea',\n", " 'BsmtFullBath',\n", " 'BsmtHalfBath',\n", " 'FullBath',\n", " 'HalfBath',\n", " 'BedroomAbvGr',\n", " 'KitchenAbvGr',\n", " 'KitchenQual',\n", " 'TotRmsAbvGrd',\n", " 'Functional',\n", " 'Fireplaces',\n", " 'FireplaceQu',\n", " 'GarageType',\n", " 'GarageYrBlt',\n", " 'GarageFinish',\n", " 'GarageCars',\n", " 'GarageArea',\n", " 'GarageQual',\n", " 'GarageCond',\n", " 'PavedDrive',\n", " 'WoodDeckSF',\n", " 'OpenPorchSF',\n", " 'EnclosedPorch',\n", " '3SsnPorch',\n", " 'ScreenPorch',\n", " 'PoolArea',\n", " 'PoolQC',\n", " 'Fence',\n", " 'MiscFeature',\n", " 'MiscVal',\n", " 'MoSold',\n", " 'YrSold',\n", " 'SaleType',\n", " 'SaleCondition']" ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "list(home_data.columns[1:80])" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.054748, "end_time": "2021-02-27T00:30:01.324342", "exception": false, "start_time": "2021-02-27T00:30:01.269594", "status": "completed" }, "tags": [] }, "source": [ "#### Missing Data" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:30:01.425604Z", "iopub.status.busy": "2021-02-27T00:30:01.424837Z", "iopub.status.idle": "2021-02-27T00:30:01.491102Z", "shell.execute_reply": "2021-02-27T00:30:01.492418Z" }, "papermill": { "duration": 0.119632, "end_time": "2021-02-27T00:30:01.492711", "exception": false, "start_time": "2021-02-27T00:30:01.373079", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "LotFrontage 259 Total Number 1460\n", "Alley 1369 Total Number 1460\n", "MasVnrType 8 Total Number 1460\n", "MasVnrArea 8 Total Number 1460\n", "BsmtQual 37 Total Number 1460\n", "BsmtCond 37 Total Number 1460\n", "BsmtExposure 38 Total Number 1460\n", "BsmtFinType1 37 Total Number 1460\n", "BsmtFinType2 38 Total Number 1460\n", "Electrical 1 Total Number 1460\n", "FireplaceQu 690 Total Number 1460\n", "GarageType 81 Total Number 1460\n", "GarageYrBlt 81 Total Number 1460\n", "GarageFinish 81 Total Number 1460\n", "GarageQual 81 Total Number 1460\n", "GarageCond 81 Total Number 1460\n", "PoolQC 1453 Total Number 1460\n", "Fence 1179 Total Number 1460\n", "MiscFeature 1406 Total Number 1460\n" ] } ], "source": [ "for col in list(home_data.columns):\n", " if sum(pd.isna(home_data[col]))>0:\n", " print(col, sum(pd.isna(home_data[col])), \"Total Number\", len(home_data[col]))" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.049456, "end_time": "2021-02-27T00:30:01.594420", "exception": false, "start_time": "2021-02-27T00:30:01.544964", "status": "completed" }, "tags": [] }, "source": [ "Here we can see that while there are a number of variables that have a few missing values, some are nearly entirely missing. For the variables with the highest missing values ('Alley,' 'FireplaceQU,' 'PoolQC,' 'Fence,' and 'MiscFeature') the missing values indicate that that feature does not exist (e.g., that there is no fence). So these missing values should be easy to accommodate with one-hot encoding. A review of the description of these variables shows that this is explicitly the case for all the variables with missing values except for 'Electrical.' But, it is likely safe to assume that this is the case for Electrical as well, or at least that 1 missing value will not impact the overall model much. \n", "\n", "### Review of Sale Price\n" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:30:01.704971Z", "iopub.status.busy": "2021-02-27T00:30:01.704076Z", "iopub.status.idle": "2021-02-27T00:30:02.313805Z", "shell.execute_reply": "2021-02-27T00:30:02.314384Z" }, "papermill": { "duration": 0.670727, "end_time": "2021-02-27T00:30:02.314588", "exception": false, "start_time": "2021-02-27T00:30:01.643861", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.hist(home_data.SalePrice, bins = 200)\n", "plt.ylabel('Counts')\n", "plt.xlabel('Sale Price (USD)')\n", "plt.ylim(0,52)\n", "x = [py.mean(home_data.SalePrice) + 3py.std(home_data.SalePrice) for i in range(60)]\n", "h = plt.plot(x, range(60), color='g', alpha=1)\n", "plt.annotate('Outlier Limit',xy = (py.mean(home_data.SalePrice) + 3py.std(home_data.SalePrice),45), xycoords='data',\n", " xytext=(500000,45), arrowprops=dict(arrowstyle=\"->\",facecolor='black')) \n", "plt.show()\n" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.049388, "end_time": "2021-02-27T00:30:02.414134", "exception": false, "start_time": "2021-02-27T00:30:02.364746", "status": "completed" }, "tags": [] }, "source": [ "In the plot above we can see that the data is right skewed, and has a number of outliers. In fact we have 22 outliers in the training dataset, as seen below. Note that I am using the common rule of thumb of three standard deviations above the mean as the threshold for outliers. " ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:30:02.523393Z", "iopub.status.busy": "2021-02-27T00:30:02.522529Z", "iopub.status.idle": "2021-02-27T00:30:02.528141Z", "shell.execute_reply": "2021-02-27T00:30:02.527481Z" }, "papermill": { "duration": 0.064088, "end_time": "2021-02-27T00:30:02.528277", "exception": false, "start_time": "2021-02-27T00:30:02.464189", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "22" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "len(home_data.SalePrice[home_data.SalePrice>=py.mean(home_data.SalePrice) + 3py.std(home_data.SalePrice)])" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.050893, "end_time": "2021-02-27T00:30:02.629707", "exception": false, "start_time": "2021-02-27T00:30:02.578814", "status": "completed" }, "tags": [] }, "source": [ "## Building the Dataset\n", "Below we cover building the datasets we will use in the final models. \n", "\n", "### Creating the 'Full' Datasets\n", "First we read in, and create the full datasets 'X,' 'y_train,' and 'X_test_full.' Since, the y_train variable is skewed and has a number of outliers, taking the logarithm may improve our results. Additionally, in the description of this compeition, it states that the evaluation will be based on the root-mean-squared-error ('RMSE') of the logarithm of the predictions and the true values." ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:30:02.740860Z", "iopub.status.busy": "2021-02-27T00:30:02.740043Z", "iopub.status.idle": "2021-02-27T00:30:02.822924Z", "shell.execute_reply": "2021-02-27T00:30:02.823499Z" }, "papermill": { "duration": 0.14373, "end_time": "2021-02-27T00:30:02.823672", "exception": false, "start_time": "2021-02-27T00:30:02.679942", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "X = pd.read_csv(iowa_file_path)# Our full training dataset\n", "X_test_full = pd.read_csv(test_data_path)# Our testing dataset, that we will make predictions on\n", "\n", "# Remove rows with missing target, and separating the target from the predictors\n", "X.dropna(axis=0, subset=['SalePrice'], inplace=True)\n", "y_true = X.SalePrice ## keeping to compare fit\n", "y_train = py.log(X.SalePrice) \n", "X.drop(['SalePrice'], axis=1, inplace=True)" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.049921, "end_time": "2021-02-27T00:30:02.924446", "exception": false, "start_time": "2021-02-27T00:30:02.874525", "status": "completed" }, "tags": [] }, "source": [ "Next, to control for over-fitting, we will use k-fold stratified cross-validation. To do this we will use the 'cross_val_score' function from sklearn. To compare using RMSE we will need to make our own function." ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:30:03.031161Z", "iopub.status.busy": "2021-02-27T00:30:03.030377Z", "iopub.status.idle": "2021-02-27T00:30:03.037368Z", "shell.execute_reply": "2021-02-27T00:30:03.038075Z" }, "papermill": { "duration": 0.063277, "end_time": "2021-02-27T00:30:03.038255", "exception": false, "start_time": "2021-02-27T00:30:02.974978", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "def root_mean_square(X,y):\n", " val = mean_squared_error(X,y)\n", " return val(1/2)\n", "basic_score = make_scorer(root_mean_square)\n", "def root_mean_square_X(X,y):\n", " val = mean_squared_error(py.log(X),py.log(y))\n", " return val(1/2)\n", "basic_score_X = make_scorer(root_mean_square_X)" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.050518, "end_time": "2021-02-27T00:30:03.140615", "exception": false, "start_time": "2021-02-27T00:30:03.090097", "status": "completed" }, "tags": [] }, "source": [ "Now, we will look at the categorical columns, and separate them based on whether or not they are ordinal. A reveiw of the categories of each variable reveals that all the ordinal categorical variables contain one of 'Gd,' 'GdWo,' 'RFn,' 'Mod,' 'ALQ,' 'IR1,' 'Bnk,' or 'ELO.' We separate out these variables below." ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:30:03.246939Z", "iopub.status.busy": "2021-02-27T00:30:03.246211Z", "iopub.status.idle": "2021-02-27T00:30:03.266267Z", "shell.execute_reply": "2021-02-27T00:30:03.266944Z" }, "papermill": { "duration": 0.075337, "end_time": "2021-02-27T00:30:03.267148", "exception": false, "start_time": "2021-02-27T00:30:03.191811", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "all_categorical_cols = [cname for cname in X.columns if X[cname].dtype == \"object\"]\n", "ordinal_categorical_cols = []\n", "ord_vals = ['Gd', 'RFn', 'Mod', 'ALQ', 'IR1', 'Bnk', 'ELO']\n", "for col in all_categorical_cols:\n", " sety = set(X[col])\n", " if sety.intersection(ord_vals) != set():\n", " ordinal_categorical_cols.append(col)\n", "\n", "dummy_categorical_cols = list(set(all_categorical_cols)-set(ordinal_categorical_cols))" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.050689, "end_time": "2021-02-27T00:30:03.368979", "exception": false, "start_time": "2021-02-27T00:30:03.318290", "status": "completed" }, "tags": [] }, "source": [ "Additionally, a review of the variable coding in the dataset documentation reveals that the variable 'MSSubClass' should be treated as categorical, even though after reading in the training data, it is automatically treated as an integer." ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:30:03.475862Z", "iopub.status.busy": "2021-02-27T00:30:03.474921Z", "iopub.status.idle": "2021-02-27T00:30:03.482063Z", "shell.execute_reply": "2021-02-27T00:30:03.481302Z" }, "papermill": { "duration": 0.062155, "end_time": "2021-02-27T00:30:03.482215", "exception": false, "start_time": "2021-02-27T00:30:03.420060", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "dtype('int64')" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "home_data.MSSubClass.dtype" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.051742, "end_time": "2021-02-27T00:30:03.585857", "exception": false, "start_time": "2021-02-27T00:30:03.534115", "status": "completed" }, "tags": [] }, "source": [ "MSSubClass has different integer encoding for the type of dwelling involved, but the integer values are not ordinally related. For example, a two family conversion is encoded as '190' while a two-story home that is dated 1946 or newer is encoding as '60'. But, it would be incorrect for the dataset to interpret this as two family conversions somehow being better than two-story homes. Thus, this variable should be re-encoded with dummy variables instead. " ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:30:03.694071Z", "iopub.status.busy": "2021-02-27T00:30:03.693330Z", "iopub.status.idle": "2021-02-27T00:30:03.698497Z", "shell.execute_reply": "2021-02-27T00:30:03.697935Z" }, "papermill": { "duration": 0.060027, "end_time": "2021-02-27T00:30:03.698634", "exception": false, "start_time": "2021-02-27T00:30:03.638607", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "vars_to_remove = 'MSSubClass'\n", "dummy_categorical_cols.append('MSSubClass')" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.05378, "end_time": "2021-02-27T00:30:03.803988", "exception": false, "start_time": "2021-02-27T00:30:03.750208", "status": "completed" }, "tags": [] }, "source": [ "Looking at the variable coding, we can see that there are no columns with an extremely high number of categories. There may be some computing concerns about having a couple hundred of coding varaibles, but this notebook should be able to easily handle that. Additionally, there could be some concerns about using this full model if we wanted to either make some statement about the association between certain variables and housing prices, or predict housing prices from new data (as mentioned earlier). Here our only goal is the make a model that predicts the test dataset well. So, there should be no issue with using the full dataset. \n", "\n", "### Encoding the Categorical Variables\n", "\n", "Below we will apply one-hot encoding and ordinal encoding to the categorical variables. Ordinal encoding would preserve the relationship between the categories (e.g., coding 'poor,' 'fair,' 'good,' to '1,' '2,' '3.'), while one-hot encoding just creates a dummy variable for each category (e.g., 'poor,' 'fair,' 'good,' would each get their own variable that had a value of '1', wherever the original category reported 'poor.')." ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:30:03.920267Z", "iopub.status.busy": "2021-02-27T00:30:03.919137Z", "iopub.status.idle": "2021-02-27T00:30:03.936481Z", "shell.execute_reply": "2021-02-27T00:30:03.937063Z" }, "papermill": { "duration": 0.081471, "end_time": "2021-02-27T00:30:03.937268", "exception": false, "start_time": "2021-02-27T00:30:03.855797", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "#### First lets separate out the numeric columns\n", "numeric_cols = [cname for cname in X.columns if \n", " X[cname].dtype in ['int64', 'float64']]\n", "### we also have to make sure to take out the MSSubClass variable\n", "numeric_cols.remove(vars_to_remove)\n", "\n", "#### Now we need to make our new encoded datasets\n", "my_cols = dummy_categorical_cols + ordinal_categorical_cols + numeric_cols\n", "X_train = X[my_cols].copy()\n", "X_test = X_test_full[my_cols].copy()" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:30:04.058113Z", "iopub.status.busy": "2021-02-27T00:30:04.056998Z", "iopub.status.idle": "2021-02-27T00:30:04.209161Z", "shell.execute_reply": "2021-02-27T00:30:04.209731Z" }, "papermill": { "duration": 0.20992, "end_time": "2021-02-27T00:30:04.209978", "exception": false, "start_time": "2021-02-27T00:30:04.000058", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "#### This should encode the ordinal categorical varibles ordinally\n", "## We have to be careful to set the paraticular encoding (e.g. 'Good': 2), so that\n", "## the automatic coding that LabelEncoder does won't misclassify our ordinal variables\n", "##\n", "## We will use Pandas Factorize\n", "ord_set1 = ['LotShape']\n", "ord_set2 = ['LandContour']\n", "ord_set3 = ['LandSlope']\n", "ord_set4 = ['Functional']\n", "ord_set5 = ['GarageFinish']\n", "ord_set6 = ['PoolQC']\n", "ord_set7 = ['BsmtExposure']\n", "ord_set8 = ['ExterQual','ExterCond','HeatingQC','KitchenQual']\n", "ord_set9 = ['BsmtQual','BsmtCond','FireplaceQu','GarageQual','GarageCond']\n", "ord_set10 = ['BsmtFinType1','BsmtFinType2']\n", "Ord_Set_All = [ord_set1,ord_set2,ord_set3,ord_set4,ord_set5,ord_set6,ord_set7,ord_set8,ord_set9,ord_set10]\n", "##\n", "ord_para1 = {'Reg':3, 'IR1':2, 'IR2':1, 'IR3':0}\n", "ord_para2 = {'Lvl':3, 'Bnk':2, 'HLS':1, 'Low':0}\n", "ord_para3 = {'Gtl':2, 'Mod':1, 'Sev':0}\n", "ord_para4 = {'Typ':7, 'Min1':6, 'Min2':5, 'Mod':4, 'Maj1':3, 'Maj2':2, 'Sev':1, 'Sal':0}\n", "ord_para5 = {'Fin':3, 'RFn':2, 'Unf':1, 'NA':0}\n", "ord_para6 = {'Ex':4, 'Gd':3, 'TA':2, 'Fa':1, 'NA':0}\n", "ord_para7 = {'Gd':4, 'Av':3, 'Mn':2, 'No':1, 'NA':0}\n", "ord_para8 = {'Ex':4, 'Gd':3, 'TA':2, 'Fa':1, 'Po':0}\n", "ord_para9 = {'Ex':5, 'Gd':4, 'TA':3, 'Fa':2, 'Po':1, 'NA':0}\n", "ord_para10 = {'GLQ':6, 'ALQ':5, 'BLQ':4, 'Rec':3, 'LwQ':2, 'Unf':1, 'NA':0}\n", "Ord_Para_All = [ord_para1,ord_para2,ord_para3,ord_para4,ord_para5,ord_para6,ord_para7,ord_para8,ord_para9,ord_para10]\n", "##\n", "#### we need to set the parameters for each kind of variable\n", "for i in range(len(Ord_Set_All)):\n", " ordy = Ord_Set_All[i]\n", " ord_mapper = Ord_Para_All[i]\n", " for col in ordy:\n", " ### For the training data\n", " hld = X_train[col].replace(ord_mapper)\n", " hld = hld.fillna(0) ### dealing with missing values (as discussed above)\n", " X_train[col] = hld\n", " ### For the testing data\n", " hld = X_test[col].replace(ord_mapper)\n", " hld = hld.fillna(0)\n", " X_test[col] = hld\n" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:30:04.333471Z", "iopub.status.busy": "2021-02-27T00:30:04.332229Z", "iopub.status.idle": "2021-02-27T00:30:04.413190Z", "shell.execute_reply": "2021-02-27T00:30:04.411721Z" }, "papermill": { "duration": 0.145455, "end_time": "2021-02-27T00:30:04.413354", "exception": false, "start_time": "2021-02-27T00:30:04.267899", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "#### Finally we one-hot encode the remaining data using pandas again\n", "X_train = pd.get_dummies(X_train)\n", "X_test = pd.get_dummies(X_test)\n", "X_train, X_test = X_train.align(X_test, join='right', axis=1)" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.053142, "end_time": "2021-02-27T00:30:04.520111", "exception": false, "start_time": "2021-02-27T00:30:04.466969", "status": "completed" }, "tags": [] }, "source": [ "Thus, are final datasets are: X_train, y_train, y_true, and X_test.\n", "\n", "Finally, we have to consider the missing values in the numeric columns." ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:30:04.702393Z", "iopub.status.busy": "2021-02-27T00:30:04.700987Z", "iopub.status.idle": "2021-02-27T00:30:04.728645Z", "shell.execute_reply": "2021-02-27T00:30:04.727918Z" }, "papermill": { "duration": 0.154705, "end_time": "2021-02-27T00:30:04.728808", "exception": false, "start_time": "2021-02-27T00:30:04.574103", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "LotFrontage 259\n", "MasVnrArea 8\n", "GarageYrBlt 81\n" ] } ], "source": [ "for col in X_train:\n", " if sum(pd.isna(X_train[col]))>0:\n", " print(col,sum(pd.isna(X_train[col])))" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.056147, "end_time": "2021-02-27T00:30:04.841118", "exception": false, "start_time": "2021-02-27T00:30:04.784971", "status": "completed" }, "tags": [] }, "source": [ "For these three columns, there are a few ways we could potnetially fill, or resolve missing values. First, we could fill them with a specific value. For example, zero, or the mean, or median for that variable. Alternatively, we could fill it with some sort of predicted estimation based on the values in the other columns. To determine the appropriate fill, we must analyze the data. Observe:" ] }, { "cell_type": "code", "execution_count": 16, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:30:04.963145Z", "iopub.status.busy": "2021-02-27T00:30:04.962242Z", "iopub.status.idle": "2021-02-27T00:30:04.969552Z", "shell.execute_reply": "2021-02-27T00:30:04.968823Z" }, "papermill": { "duration": 0.073596, "end_time": "2021-02-27T00:30:04.969712", "exception": false, "start_time": "2021-02-27T00:30:04.896116", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "39 NaN\n", "48 NaN\n", "78 NaN\n", "88 NaN\n", "89 NaN\n", " ..\n", "1349 NaN\n", "1407 NaN\n", "1449 NaN\n", "1450 NaN\n", "1453 NaN\n", "Name: GarageYrBlt, Length: 81, dtype: float64\n", "81\n", "81\n" ] } ], "source": [ "print(home_data.GarageYrBlt[pd.isna(home_data.GarageType)==True])\n", "print(len(home_data.GarageYrBlt[pd.isna(home_data.GarageType)==True]))\n", "print(sum(pd.isna(home_data.GarageYrBlt)==True))" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.053762, "end_time": "2021-02-27T00:30:05.080053", "exception": false, "start_time": "2021-02-27T00:30:05.026291", "status": "completed" }, "tags": [] }, "source": [ "Based on this we can conclude that replacing the missing values with zeroes is appropriate since every instance of a missing value in Garage Year Built corresponds to there not being a garage." ] }, { "cell_type": "code", "execution_count": 17, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:30:05.200880Z", "iopub.status.busy": "2021-02-27T00:30:05.195777Z", "iopub.status.idle": "2021-02-27T00:30:05.206878Z", "shell.execute_reply": "2021-02-27T00:30:05.206045Z" }, "papermill": { "duration": 0.073805, "end_time": "2021-02-27T00:30:05.207038", "exception": false, "start_time": "2021-02-27T00:30:05.133233", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "1 0.0\n", "3 0.0\n", "5 0.0\n", "8 0.0\n", "9 0.0\n", " ... \n", "1454 0.0\n", "1455 0.0\n", "1457 0.0\n", "1458 0.0\n", "1459 0.0\n", "Name: MasVnrArea, Length: 864, dtype: float64\n", "234 NaN\n", "529 NaN\n", "650 NaN\n", "936 NaN\n", "973 NaN\n", "977 NaN\n", "1243 NaN\n", "1278 NaN\n", "Name: MasVnrType, dtype: object\n", "864\n", "8\n" ] } ], "source": [ "print(home_data.MasVnrArea[home_data.MasVnrType=='None'])\n", "print(home_data.MasVnrType[pd.isna(home_data.MasVnrArea)==True])\n", "print(len(home_data.MasVnrArea[home_data.MasVnrType=='None']))\n", "print(sum(pd.isna(home_data.MasVnrArea)==True))" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.054755, "end_time": "2021-02-27T00:30:05.316653", "exception": false, "start_time": "2021-02-27T00:30:05.261898", "status": "completed" }, "tags": [] }, "source": [ "Here we see that while where MasVnrArea is missing MasVnrType is missing as well, there is a separate category for there not being a masonry veneer. So, it is unclear whether or not zeroes would be appropriate to fill the missing values. " ] }, { "cell_type": "code", "execution_count": 18, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:30:05.435656Z", "iopub.status.busy": "2021-02-27T00:30:05.434878Z", "iopub.status.idle": "2021-02-27T00:30:05.439998Z", "shell.execute_reply": "2021-02-27T00:30:05.439374Z" }, "papermill": { "duration": 0.067956, "end_time": "2021-02-27T00:30:05.440152", "exception": false, "start_time": "2021-02-27T00:30:05.372196", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "861 1460\n" ] } ], "source": [ "print(sum(home_data.MasVnrArea==0),len(home_data.MasVnrArea))" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.053358, "end_time": "2021-02-27T00:30:05.550357", "exception": false, "start_time": "2021-02-27T00:30:05.496999", "status": "completed" }, "tags": [] }, "source": [ "But, since it appears that the median of MasVnrArea is zero, it should be an appropriate value as well. " ] }, { "cell_type": "code", "execution_count": 19, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:30:05.669680Z", "iopub.status.busy": "2021-02-27T00:30:05.668905Z", "iopub.status.idle": "2021-02-27T00:30:05.672937Z", "shell.execute_reply": "2021-02-27T00:30:05.672236Z" }, "papermill": { "duration": 0.068383, "end_time": "2021-02-27T00:30:05.673068", "exception": false, "start_time": "2021-02-27T00:30:05.604685", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "70.04995836802665\n", "733\n", "0\n" ] } ], "source": [ "print(py.mean(home_data.LotFrontage))\n", "print(sum(home_data.LotFrontage<75))\n", "print(sum(home_data.LotFrontage<=1))\n" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.05751, "end_time": "2021-02-27T00:30:05.786655", "exception": false, "start_time": "2021-02-27T00:30:05.729145", "status": "completed" }, "tags": [] }, "source": [ "Again, with 'LotFrontage', there does not appear to be any clear reason for the missing values. But, there are also no zero values, and given the variables description ('Linear feet of street connected to property') zero does not appear to be an appropriate value. Instead, we will apply the mean value (the mean and median values are fairly close together regardless). " ] }, { "cell_type": "code", "execution_count": 20, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:30:05.911425Z", "iopub.status.busy": "2021-02-27T00:30:05.910203Z", "iopub.status.idle": "2021-02-27T00:30:05.916906Z", "shell.execute_reply": "2021-02-27T00:30:05.916109Z" }, "papermill": { "duration": 0.07391, "end_time": "2021-02-27T00:30:05.917050", "exception": false, "start_time": "2021-02-27T00:30:05.843140", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "numeric_missing = ['LotFrontage', 'MasVnrArea', 'GarageYrBlt']\n", "for col in numeric_missing:\n", " if col == 'MasVnrArea' or col == 'GarageYrBlt':\n", " ### For the training data\n", " hld = X_train[col]\n", " hld = hld.fillna(0) ### dealing with missing values (as discussed above)\n", " X_train[col] = hld\n", " ### For the testing data\n", " hld = X_test[col]\n", " hld = hld.fillna(0)\n", " X_test[col] = hld\n", " elif col == 'LotFrontage':\n", " lot_mean = py.mean(home_data[col])\n", " ### For the training data\n", " hld = X_train[col]\n", " hld = hld.fillna(lot_mean) ### dealing with missing values (as discussed above)\n", " X_train[col] = hld\n", " ### For the testing data\n", " hld = X_test[col]\n", " hld = hld.fillna(lot_mean)\n", " X_test[col] = hld\n", " \n", " " ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.054412, "end_time": "2021-02-27T00:30:06.026972", "exception": false, "start_time": "2021-02-27T00:30:05.972560", "status": "completed" }, "tags": [] }, "source": [ "We also need to consider missing values in the test data." ] }, { "cell_type": "code", "execution_count": 21, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:30:06.225036Z", "iopub.status.busy": "2021-02-27T00:30:06.224073Z", "iopub.status.idle": "2021-02-27T00:30:06.229974Z", "shell.execute_reply": "2021-02-27T00:30:06.229280Z" }, "papermill": { "duration": 0.147271, "end_time": "2021-02-27T00:30:06.230124", "exception": false, "start_time": "2021-02-27T00:30:06.082853", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "BsmtFinSF1 1\n", "BsmtFinSF2 1\n", "BsmtUnfSF 1\n", "TotalBsmtSF 1\n", "BsmtFullBath 2\n", "BsmtHalfBath 2\n", "GarageCars 1\n", "GarageArea 1\n" ] } ], "source": [ "for col in X_test:\n", " if sum(pd.isna(X_test[col]))>0:\n", " print(col,sum(pd.isna(X_test[col])))" ] }, { "cell_type": "code", "execution_count": 22, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:30:06.375347Z", "iopub.status.busy": "2021-02-27T00:30:06.365475Z", "iopub.status.idle": "2021-02-27T00:30:06.387004Z", "shell.execute_reply": "2021-02-27T00:30:06.386090Z" }, "papermill": { "duration": 0.100124, "end_time": "2021-02-27T00:30:06.387167", "exception": false, "start_time": "2021-02-27T00:30:06.287043", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "660 NaN\n", "Name: BsmtFinSF2, dtype: float64\n", "660 NaN\n", "Name: BsmtUnfSF, dtype: float64\n", "660 NaN\n", "Name: TotalBsmtSF, dtype: float64\n", "660 NaN\n", "Name: BsmtFullBath, dtype: float64\n", "660 NaN\n", "Name: BsmtHalfBath, dtype: float64\n", "660 0.0\n", "Name: BsmtExposure, dtype: float64\n", "660 0.0\n", "Name: BsmtFinType1, dtype: float64\n", "660 0.0\n", "Name: BsmtFinType2, dtype: float64\n", "660 0.0\n", "Name: BsmtQual, dtype: float64\n", "660 0.0\n", "Name: BsmtCond, dtype: float64\n", "660 0.0\n", "728 0.0\n", "Name: BsmtQual, dtype: float64\n", "660 0.0\n", "728 0.0\n", "Name: BsmtCond, dtype: float64\n", "660 0.0\n", "728 0.0\n", "Name: BsmtQual, dtype: float64\n", "660 0.0\n", "728 0.0\n", "Name: BsmtCond, dtype: float64\n" ] } ], "source": [ "print(X_test['BsmtFinSF2'][pd.isna(X_test['BsmtFinSF1'])==True])\n", "print(X_test['BsmtUnfSF'][pd.isna(X_test['BsmtFinSF1'])==True])\n", "print(X_test['TotalBsmtSF'][pd.isna(X_test['BsmtFinSF1'])==True])\n", "print(X_test['BsmtFullBath'][pd.isna(X_test['BsmtFinSF1'])==True])\n", "print(X_test['BsmtHalfBath'][pd.isna(X_test['BsmtFinSF1'])==True])\n", "print(X_test['BsmtExposure'][pd.isna(X_test['BsmtFinSF1'])==True])\n", "print(X_test['BsmtFinType1'][pd.isna(X_test['BsmtFinSF1'])==True])\n", "print(X_test['BsmtFinType2'][pd.isna(X_test['BsmtFinSF1'])==True])\n", "print(X_test['BsmtQual'][pd.isna(X_test['BsmtFinSF1'])==True])\n", "print(X_test['BsmtCond'][pd.isna(X_test['BsmtFinSF1'])==True])\n", "\n", "print(X_test['BsmtQual'][pd.isna(X_test['BsmtFullBath'])==True])\n", "print(X_test['BsmtCond'][pd.isna(X_test['BsmtFullBath'])==True])\n", "print(X_test['BsmtQual'][pd.isna(X_test['BsmtHalfBath'])==True])\n", "print(X_test['BsmtCond'][pd.isna(X_test['BsmtHalfBath'])==True])\n" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.055717, "end_time": "2021-02-27T00:30:06.500643", "exception": false, "start_time": "2021-02-27T00:30:06.444926", "status": "completed" }, "tags": [] }, "source": [ "Thus, we can conclude there is no basement for the properties corresponding to these missing values (BsmtFinSF1, BsmtFinSF2, BsmtUnfSF, TotalBsmtSF, BsmtFullBath, BsmtHalfBath), and set them all to zero." ] }, { "cell_type": "code", "execution_count": 23, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:30:06.631097Z", "iopub.status.busy": "2021-02-27T00:30:06.630083Z", "iopub.status.idle": "2021-02-27T00:30:06.635285Z", "shell.execute_reply": "2021-02-27T00:30:06.634486Z" }, "papermill": { "duration": 0.079401, "end_time": "2021-02-27T00:30:06.635438", "exception": false, "start_time": "2021-02-27T00:30:06.556037", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "1116 NaN\n", "Name: GarageArea, dtype: float64\n", "1116 0.0\n", "Name: GarageQual, dtype: float64\n", "1116 0.0\n", "Name: GarageYrBlt, dtype: float64\n", "1116 0.0\n", "Name: GarageCond, dtype: float64\n", "1116 0.0\n", "Name: GarageFinish, dtype: float64\n", "1116 1\n", "Name: GarageType_Detchd, dtype: uint8\n" ] } ], "source": [ "print(X_test['GarageArea'][pd.isna(X_test['GarageCars'])==True])\n", "print(X_test['GarageQual'][pd.isna(X_test['GarageCars'])==True])\n", "print(X_test['GarageYrBlt'][pd.isna(X_test['GarageCars'])==True])\n", "print(X_test['GarageCond'][pd.isna(X_test['GarageCars'])==True])\n", "print(X_test['GarageFinish'][pd.isna(X_test['GarageCars'])==True])\n", "print(X_test['GarageType_Detchd'][pd.isna(X_test['GarageCars'])==True])\n" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.05787, "end_time": "2021-02-27T00:30:06.751977", "exception": false, "start_time": "2021-02-27T00:30:06.694107", "status": "completed" }, "tags": [] }, "source": [ "This suggests that either the missing value is for a detached garage, that wasn't fully recorded. Or, that there was no garage, but it was mislabeled as a detached one. Either way the data was mislabeled, as the varible description file explicitly states that NAs correspond to no garage. Given that four variables indicate that there is no garage, while one indicates that there is a garage, I am going to fill these variables with zeroes as well. " ] }, { "cell_type": "code", "execution_count": 24, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:30:06.879770Z", "iopub.status.busy": "2021-02-27T00:30:06.878539Z", "iopub.status.idle": "2021-02-27T00:30:06.885156Z", "shell.execute_reply": "2021-02-27T00:30:06.884249Z" }, "papermill": { "duration": 0.073984, "end_time": "2021-02-27T00:30:06.885309", "exception": false, "start_time": "2021-02-27T00:30:06.811325", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "test_missing = ['BsmtFinSF1', 'BsmtFinSF2', 'BsmtUnfSF','TotalBsmtSF',\n", " 'BsmtFullBath','BsmtHalfBath','GarageCars','GarageArea']\n", "for col in test_missing:\n", " hld = X_test[col]\n", " hld = hld.fillna(0)\n", " X_test[col] = hld" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.057609, "end_time": "2021-02-27T00:30:07.001170", "exception": false, "start_time": "2021-02-27T00:30:06.943561", "status": "completed" }, "tags": [] }, "source": [ "Additionally, it may be beneficial to create a few additional variables using combinations of existing variables. These variables can help account for non-linear relationships between the target variable and the explanatory variable, or allow us to add additional data, which should or could have been in the original dataset, but were missing for whatever reason (such as the total square-footage of the house.)." ] }, { "cell_type": "code", "execution_count": 25, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:30:07.148504Z", "iopub.status.busy": "2021-02-27T00:30:07.131742Z", "iopub.status.idle": "2021-02-27T00:30:07.186247Z", "shell.execute_reply": "2021-02-27T00:30:07.185524Z" }, "papermill": { "duration": 0.127404, "end_time": "2021-02-27T00:30:07.186418", "exception": false, "start_time": "2021-02-27T00:30:07.059014", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "X_train['Overall_Score'] = X_train['OverallQual'] + X_train['OverallCond']\n", "X_train['Overall_Score_sq'] = X_train['Overall_Score']2\n", "X_train['Overall_Score_cu'] = X_train['Overall_Score']3\n", "X_train['Overall_Score_sqrt'] = X_train['Overall_Score'](1/2)\n", "X_train['Overall_Score_log'] = py.log(X_train['Overall_Score'])\n", "\n", "X_train['Total_Living_SF'] = X_train['TotalBsmtSF'] + X_train['1stFlrSF'] + X_train['2ndFlrSF']\n", "X_train['Total_Living_SF_log'] = py.log(X_train['Total_Living_SF'])\n", "X_train['Total_Living_SF_sq'] = X_train['Total_Living_SF']2\n", "X_train['Total_Living_SF_cu'] = X_train['Total_Living_SF']3\n", "X_train['Total_Living_SF_sqrt'] = X_train['Total_Living_SF'](1/2)\n", "\n", "X_train['GrLivArea_log'] = py.log(X_train['GrLivArea'])\n", "X_train['GrLivArea_sq'] = (X_train['GrLivArea'])2\n", "X_train['GrLivArea_cu'] = (X_train['GrLivArea'])3\n", "X_train['GrLivArea_sqrt'] = (X_train['GrLivArea'])(1/2)\n", "\n", "X_train['OverallQual_log'] = py.log(X_train['OverallQual'])\n", "X_train['OverallQual_sq'] = (X_train['OverallQual'])2\n", "X_train['OverallQual_cu'] = (X_train['OverallQual'])3\n", "X_train['OverallQual_sqrt'] = (X_train['OverallQual'])(1/2)\n", "\n", "X_train['GarageCars_sq'] = (X_train['GarageCars'])2\n", "X_train['GarageCars_cu'] = (X_train['GarageCars'])3\n", "X_train['GarageCars_sqrt'] = (X_train['GarageCars'])(1/2)\n", "\n", "X_train['GarageArea_sq'] = (X_train['GarageArea'])2\n", "X_train['GarageArea_cu'] = (X_train['GarageArea'])3\n", "X_train['GarageArea_sqrt'] = (X_train['GarageArea'])(1/2)\n", "\n", "X_train['YearBuilt_diff'] = X_train['YrSold']-X_train['YearBuilt']\n", "X_train['YearBuilt_diff_sq'] = X_train['YearBuilt_diff']2\n", "X_train['YearBuilt_diff_cu'] = X_train['YearBuilt_diff']3\n", "\n", "X_train['YearRemod_diff'] = X_train['YrSold']-X_train['YearRemodAdd']\n", "X_train['YearRemod_diff_sq'] = X_train['YearRemod_diff']2\n", "X_train['YearRemod_diff_cu'] = X_train['YearRemod_diff']3\n", "\n", "X_train['Total_Outside_SF'] = (X_train['WoodDeckSF'] + X_train['OpenPorchSF'] + X_train['EnclosedPorch'] \n", " + X_train['3SsnPorch'] +X_train['ScreenPorch'] + X_train['PoolArea']\n", " + X_train['GarageArea'])\n", "\n", "X_train['Total_Bathrooms'] = X_train['BsmtFullBath'] + (1/2)X_train['BsmtHalfBath'] + X_train['FullBath'] + (1/2)X_train['HalfBath']\n", "X_train['Total_Bathrooms_log'] = py.log(X_train['Total_Bathrooms'])\n", "X_train['Total_Bathrooms_sq'] = (X_train['Total_Bathrooms'])2\n", "X_train['Total_Bathrooms_cu'] = (X_train['Total_Bathrooms'])3\n", "X_train['Total_Bathrooms_sqrt'] = (X_train['Total_Bathrooms'])(1/2)\n", "\n", "X_train['Total_Rooms'] = X_train['TotRmsAbvGrd'] + X_train['Total_Bathrooms']\n", "X_train['Total_Rooms_log'] = py.log(X_train['Total_Rooms'])\n", "X_train['Total_Rooms_sq'] = (X_train['Total_Rooms'])2\n", "X_train['Total_Rooms_cu'] = (X_train['Total_Rooms'])3\n", "X_train['Total_Rooms_sqrt'] = (X_train['Total_Rooms'])(1/2)" ] }, { "cell_type": "code", "execution_count": 26, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:30:07.334518Z", "iopub.status.busy": "2021-02-27T00:30:07.312790Z", "iopub.status.idle": "2021-02-27T00:30:07.370221Z", "shell.execute_reply": "2021-02-27T00:30:07.369593Z" }, "papermill": { "duration": 0.125322, "end_time": "2021-02-27T00:30:07.370361", "exception": false, "start_time": "2021-02-27T00:30:07.245039", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "# For X_test\n", "X_test['Overall_Score'] = X_test['OverallQual'] + X_test['OverallCond']\n", "X_test['Overall_Score_sq'] = X_test['Overall_Score']2\n", "X_test['Overall_Score_cu'] = X_test['Overall_Score']3\n", "X_test['Overall_Score_sqrt'] = X_test['Overall_Score'](1/2)\n", "X_test['Overall_Score_log'] = py.log(X_test['Overall_Score'])\n", "\n", "X_test['Total_Living_SF'] = X_test['TotalBsmtSF'] + X_test['1stFlrSF'] + X_test['2ndFlrSF']\n", "X_test['Total_Living_SF_log'] = py.log(X_test['Total_Living_SF'])\n", "X_test['Total_Living_SF_sq'] = X_test['Total_Living_SF']2\n", "X_test['Total_Living_SF_cu'] = X_test['Total_Living_SF']3\n", "X_test['Total_Living_SF_sqrt'] = X_test['Total_Living_SF'](1/2)\n", "\n", "X_test['GrLivArea_log'] = py.log(X_test['GrLivArea'])\n", "X_test['GrLivArea_sq'] = (X_test['GrLivArea'])2\n", "X_test['GrLivArea_cu'] = (X_test['GrLivArea'])3\n", "X_test['GrLivArea_sqrt'] = (X_test['GrLivArea'])(1/2)\n", "\n", "X_test['OverallQual_log'] = py.log(X_test['OverallQual'])\n", "X_test['OverallQual_sq'] = (X_test['OverallQual'])2\n", "X_test['OverallQual_cu'] = (X_test['OverallQual'])3\n", "X_test['OverallQual_sqrt'] = (X_test['OverallQual'])(1/2)\n", "\n", "X_test['GarageCars_sq'] = (X_test['GarageCars'])2\n", "X_test['GarageCars_cu'] = (X_test['GarageCars'])3\n", "X_test['GarageCars_sqrt'] = (X_test['GarageCars'])(1/2)\n", "\n", "X_test['GarageArea_sq'] = (X_test['GarageArea'])2\n", "X_test['GarageArea_cu'] = (X_test['GarageArea'])3\n", "X_test['GarageArea_sqrt'] = (X_test['GarageArea'])(1/2)\n", "\n", "X_test['YearBuilt_diff'] = X_test['YrSold']-X_test['YearBuilt']\n", "X_test['YearBuilt_diff_sq'] = X_test['YearBuilt_diff']2\n", "X_test['YearBuilt_diff_cu'] = X_test['YearBuilt_diff']3\n", "\n", "X_test['YearRemod_diff'] = X_test['YrSold']-X_test['YearRemodAdd']\n", "X_test['YearRemod_diff_sq'] = X_test['YearRemod_diff']2\n", "X_test['YearRemod_diff_cu'] = X_test['YearRemod_diff']3\n", "\n", "X_test['Total_Outside_SF'] = (X_test['WoodDeckSF'] + X_test['OpenPorchSF'] + X_test['EnclosedPorch'] \n", " + X_test['3SsnPorch'] +X_test['ScreenPorch'] + X_test['PoolArea']\n", " + X_test['GarageArea'])\n", "\n", "X_test['Total_Bathrooms'] = X_test['BsmtFullBath'] + (1/2)X_test['BsmtHalfBath'] + X_test['FullBath'] + (1/2)X_test['HalfBath']\n", "X_test['Total_Bathrooms_log'] = py.log(X_test['Total_Bathrooms'])\n", "X_test['Total_Bathrooms_sq'] = (X_test['Total_Bathrooms'])2\n", "X_test['Total_Bathrooms_cu'] = (X_test['Total_Bathrooms'])3\n", "X_test['Total_Bathrooms_sqrt'] = (X_test['Total_Bathrooms'])(1/2)\n", "\n", "X_test['Total_Rooms'] = X_test['TotRmsAbvGrd'] + X_test['Total_Bathrooms']\n", "X_test['Total_Rooms_log'] = py.log(X_test['Total_Rooms'])\n", "X_test['Total_Rooms_sq'] = (X_test['Total_Rooms'])2\n", "X_test['Total_Rooms_cu'] = (X_test['Total_Rooms'])3\n", "X_test['Total_Rooms_sqrt'] = (X_test['Total_Rooms'])(1/2)" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.056846, "end_time": "2021-02-27T00:30:07.486045", "exception": false, "start_time": "2021-02-27T00:30:07.429199", "status": "completed" }, "tags": [] }, "source": [ "Finally, there may be some issues of skewness or non-normality of the explanatory variables. So, it may be benefical to standardize the data. Alternatively, we could do a deeper review of skewness and transform those variables that are highly skewed. " ] }, { "cell_type": "code", "execution_count": 27, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:30:07.615702Z", "iopub.status.busy": "2021-02-27T00:30:07.614871Z", "iopub.status.idle": "2021-02-27T00:30:07.670120Z", "shell.execute_reply": "2021-02-27T00:30:07.669425Z" }, "papermill": { "duration": 0.127309, "end_time": "2021-02-27T00:30:07.670282", "exception": false, "start_time": "2021-02-27T00:30:07.542973", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "for col in numeric_cols:\n", " hld = X_train[col]\n", " hld = (hld-py.mean(hld))/py.std(hld) ### normalizing\n", " X_train[col] = hld\n", " hld = X_test[col]\n", " hld = (hld-py.mean(hld))/py.std(hld) ### normalizing\n", " X_test[col] = hld" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.057961, "end_time": "2021-02-27T00:30:07.786616", "exception": false, "start_time": "2021-02-27T00:30:07.728655", "status": "completed" }, "tags": [] }, "source": [ "## Models\n", "\n", "Here we will compare the results of a variety of common regression models.\n", "\n", "### Multivariate Regression\n", "\n", "First, we can consider a basic multivariate regression model. This is a simple model that minimizes the residual sum of squares using linear algebra." ] }, { "cell_type": "code", "execution_count": 28, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:30:07.911353Z", "iopub.status.busy": "2021-02-27T00:30:07.910493Z", "iopub.status.idle": "2021-02-27T00:30:07.913838Z", "shell.execute_reply": "2021-02-27T00:30:07.913129Z" }, "papermill": { "duration": 0.066879, "end_time": "2021-02-27T00:30:07.913993", "exception": false, "start_time": "2021-02-27T00:30:07.847114", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "modelOLS = LinearRegression()" ] }, { "cell_type": "code", "execution_count": 29, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:30:08.041357Z", "iopub.status.busy": "2021-02-27T00:30:08.040594Z", "iopub.status.idle": "2021-02-27T00:30:08.295053Z", "shell.execute_reply": "2021-02-27T00:30:08.295640Z" }, "papermill": { "duration": 0.321384, "end_time": "2021-02-27T00:30:08.295839", "exception": false, "start_time": "2021-02-27T00:30:07.974455", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Cross-Validated RMSE: 0.3567579234809929\n" ] } ], "source": [ "CV_RMSE = py.mean(cross_val_score(modelOLS,X_train,y_train,scoring = basic_score,cv = 5))\n", "print('Cross-Validated RMSE:',CV_RMSE)#0.3567548888921507" ] }, { "cell_type": "code", "execution_count": 30, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:30:08.419968Z", "iopub.status.busy": "2021-02-27T00:30:08.419074Z", "iopub.status.idle": "2021-02-27T00:30:08.471896Z", "shell.execute_reply": "2021-02-27T00:30:08.472463Z" }, "papermill": { "duration": 0.119363, "end_time": "2021-02-27T00:30:08.472656", "exception": false, "start_time": "2021-02-27T00:30:08.353293", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Root Mean Square Error: 0.09609471169404045\n" ] } ], "source": [ "modelOLS.fit(X_train, y_train)\n", "\n", "predictions_X = modelOLS.predict(X_train)\n", "\n", "MAE_OLS = mean_squared_error(predictions_X, y_train)(1/2)\n", "\n", "print(\"Root Mean Square Error:\", MAE_OLS)#0.09609467307102444" ] }, { "cell_type": "code", "execution_count": 31, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:30:08.601414Z", "iopub.status.busy": "2021-02-27T00:30:08.600162Z", "iopub.status.idle": "2021-02-27T00:30:08.800318Z", "shell.execute_reply": "2021-02-27T00:30:08.799578Z" }, "papermill": { "duration": 0.269664, "end_time": "2021-02-27T00:30:08.800452", "exception": false, "start_time": "2021-02-27T00:30:08.530788", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "resid_v = ((predictions_X)-y_train)2\n", "plt.ylabel('Squared Residuals')\n", "plt.xlabel('Index')\n", "plt.xlim(0,len(y_train)+10)\n", "plt.plot(range(len(resid_v)),resid_v, \"o\")\n", "plt.plot([-10, 2000], [MAE_OLS, MAE_OLS], 'k-', lw=2)\n", "\n", "plt.annotate('Root Mean Squared Error',xy = (1400,MAE_OLS), xycoords='data',\n", " xytext=(1500,max(resid_v)/2), arrowprops=dict(arrowstyle=\"->\",facecolor='black')) \n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.059977, "end_time": "2021-02-27T00:30:08.920147", "exception": false, "start_time": "2021-02-27T00:30:08.860170", "status": "completed" }, "tags": [] }, "source": [ "Alternatively, you could look at the R-squared value. To get a feel for the fit of the model." ] }, { "cell_type": "code", "execution_count": 32, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:30:09.052064Z", "iopub.status.busy": "2021-02-27T00:30:09.050588Z", "iopub.status.idle": "2021-02-27T00:30:09.127971Z", "shell.execute_reply": "2021-02-27T00:30:09.127302Z" }, "papermill": { "duration": 0.147433, "end_time": "2021-02-27T00:30:09.128145", "exception": false, "start_time": "2021-02-27T00:30:08.980712", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.9420881249336328\n", "0.932621981734588\n" ] } ], "source": [ "modelOLS.fit(X_train, y_train)\n", "\n", "print(modelOLS.score(X_train, y_train))#0.9420881714862639\n", "\n", "modelOLS.fit(X_train, y_true)\n", "\n", "print(modelOLS.score(X_train, y_true))#0.9326219998440954" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.059353, "end_time": "2021-02-27T00:30:09.251808", "exception": false, "start_time": "2021-02-27T00:30:09.192455", "status": "completed" }, "tags": [] }, "source": [ "We can see that a basic multivariate regression model gives a RMSE of about 0.357, and has fairly decent R-squared values. So, this model is a decent fit. We can also see that the overall fit improves when we use the log-transformed target variable, since this helps control fitting to the extreme outliers in SalePrice. \n", "\n", "The plot above also shows us that the residuals have a few extreme outliers. While it is possible that further modification of the linear model could improve the fit (e.g., addressing skewness in the variables, or adding additional variables), instead we will apply some machine learning models to this regression, and see if these more complex models yield any improvements over this basic model. " ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.059137, "end_time": "2021-02-27T00:30:09.371217", "exception": false, "start_time": "2021-02-27T00:30:09.312080", "status": "completed" }, "tags": [] }, "source": [ "### Decision Tree\n", "\n", "A decision tree is a non-parametric supervised learning method that uses a series of branching if-then-else decisions to predict the value of a target variable. For example, if you observe higher-value houses all having a pool, then when you have a new observation that has a pool you would predict its sale value as being higher than it would be otherwise. " ] }, { "cell_type": "code", "execution_count": 33, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:30:09.498025Z", "iopub.status.busy": "2021-02-27T00:30:09.497006Z", "iopub.status.idle": "2021-02-27T00:30:09.501097Z", "shell.execute_reply": "2021-02-27T00:30:09.500368Z" }, "papermill": { "duration": 0.07025, "end_time": "2021-02-27T00:30:09.501234", "exception": false, "start_time": "2021-02-27T00:30:09.430984", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "DT_model = DecisionTreeRegressor(min_samples_split = 44, min_samples_leaf=2, \n", " criterion = 'mae',max_features = 57, \n", " random_state=31415)" ] }, { "cell_type": "code", "execution_count": 34, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:30:09.630026Z", "iopub.status.busy": "2021-02-27T00:30:09.628808Z", "iopub.status.idle": "2021-02-27T00:30:09.633187Z", "shell.execute_reply": "2021-02-27T00:30:09.632542Z" }, "papermill": { "duration": 0.072242, "end_time": "2021-02-27T00:30:09.633331", "exception": false, "start_time": "2021-02-27T00:30:09.561089", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "paraDT = {'min_samples_split':list(range(40,50)),'min_samples_leaf':[1,2],\n", " 'max_features':list(range(50,60))}\n", "DT_search = GridSearchCV(DT_model,param_grid = paraDT,\n", " scoring = basic_score, n_jobs = -1, cv = 5,refit = False)" ] }, { "cell_type": "code", "execution_count": 35, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:30:09.762633Z", "iopub.status.busy": "2021-02-27T00:30:09.761678Z", "iopub.status.idle": "2021-02-27T00:31:22.128053Z", "shell.execute_reply": "2021-02-27T00:31:22.128709Z" }, "papermill": { "duration": 72.435474, "end_time": "2021-02-27T00:31:22.128919", "exception": false, "start_time": "2021-02-27T00:30:09.693445", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "{170: {'max_features': 58, 'min_samples_leaf': 2, 'min_samples_split': 40}}\n", "0.1775936009873552\n" ] } ], "source": [ "DT_search.fit(X_train,y_train)\n", "Search_Hld = pd.DataFrame(DT_search.cv_results_)\n", "print(dict(Search_Hld.params[Search_Hld.rank_test_score==max(Search_Hld.rank_test_score)]))\n", "print(min(Search_Hld.mean_test_score))" ] }, { "cell_type": "code", "execution_count": 36, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:31:22.259027Z", "iopub.status.busy": "2021-02-27T00:31:22.257936Z", "iopub.status.idle": "2021-02-27T00:31:22.261272Z", "shell.execute_reply": "2021-02-27T00:31:22.260550Z" }, "papermill": { "duration": 0.070759, "end_time": "2021-02-27T00:31:22.261417", "exception": false, "start_time": "2021-02-27T00:31:22.190658", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "DT_model = DecisionTreeRegressor(min_samples_split = 45, min_samples_leaf=2, \n", " criterion = 'mae',max_features = 52, \n", " random_state=31415)" ] }, { "cell_type": "code", "execution_count": 37, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:31:22.386965Z", "iopub.status.busy": "2021-02-27T00:31:22.386257Z", "iopub.status.idle": "2021-02-27T00:31:22.814612Z", "shell.execute_reply": "2021-02-27T00:31:22.813984Z" }, "papermill": { "duration": 0.492584, "end_time": "2021-02-27T00:31:22.814781", "exception": false, "start_time": "2021-02-27T00:31:22.322197", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[0.18016572 0.18913791 0.18140496 0.18586576 0.19035927]\n", "Root Mean Squared Error: 0.185386725372532\n" ] } ], "source": [ "full_CV = cross_val_score(DT_model,X_train,y_train,scoring = basic_score,\n", " cv = 5, n_jobs = -1)\n", "CV_MAE = py.mean(full_CV)\n", "print(full_CV)\n", "print('Root Mean Squared Error:',CV_MAE)#0.1774702304319352" ] }, { "cell_type": "code", "execution_count": 38, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:31:22.952477Z", "iopub.status.busy": "2021-02-27T00:31:22.951562Z", "iopub.status.idle": "2021-02-27T00:31:23.166200Z", "shell.execute_reply": "2021-02-27T00:31:23.166842Z" }, "papermill": { "duration": 0.288041, "end_time": "2021-02-27T00:31:23.167025", "exception": false, "start_time": "2021-02-27T00:31:22.878984", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Root Mean Squared Error: 0.14024450561682314\n" ] } ], "source": [ "DT_model.fit(X_train, y_train)\n", "DT_val_predictions = DT_model.predict(X_train)\n", "DT_val_mae = mean_squared_error(DT_val_predictions, y_train)(1/2)\n", "print(\"Root Mean Squared Error:\", DT_val_mae)# 0.14423140509255775" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.061516, "end_time": "2021-02-27T00:31:23.290560", "exception": false, "start_time": "2021-02-27T00:31:23.229044", "status": "completed" }, "tags": [] }, "source": [ "### Random Forest\n", "A random forest is an ensemble that fits multiple decision trees on various sub-samples of the dataset. So, we would expect it to perform better than the decision tree model." ] }, { "cell_type": "code", "execution_count": 39, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:31:23.421217Z", "iopub.status.busy": "2021-02-27T00:31:23.420309Z", "iopub.status.idle": "2021-02-27T00:31:23.423803Z", "shell.execute_reply": "2021-02-27T00:31:23.423219Z" }, "papermill": { "duration": 0.072002, "end_time": "2021-02-27T00:31:23.423933", "exception": false, "start_time": "2021-02-27T00:31:23.351931", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "rf_model = RandomForestRegressor(n_estimators = 1050, min_samples_split = 2, \n", " min_samples_leaf=1, max_features = 12, \n", " criterion='mse', n_jobs=-1,random_state=31415)" ] }, { "cell_type": "code", "execution_count": 40, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:31:23.552801Z", "iopub.status.busy": "2021-02-27T00:31:23.551690Z", "iopub.status.idle": "2021-02-27T00:31:37.595848Z", "shell.execute_reply": "2021-02-27T00:31:37.595105Z" }, "papermill": { "duration": 14.109557, "end_time": "2021-02-27T00:31:37.595989", "exception": false, "start_time": "2021-02-27T00:31:23.486432", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[0.12652027 0.14641051 0.14091629 0.12089556 0.13730284]\n", "Cross-Validated RMSE: 0.13440909377508736\n" ] } ], "source": [ "full_CV = cross_val_score(rf_model,X_train,y_train,scoring = basic_score,\n", " cv = 5, n_jobs = -1)\n", "CV_RMSE = py.mean(full_CV)\n", "print(full_CV)\n", "print('Cross-Validated RMSE:',CV_RMSE)#0.13474172228451703" ] }, { "cell_type": "code", "execution_count": 41, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:31:37.733928Z", "iopub.status.busy": "2021-02-27T00:31:37.732578Z", "iopub.status.idle": "2021-02-27T00:31:42.963083Z", "shell.execute_reply": "2021-02-27T00:31:42.963783Z" }, "papermill": { "duration": 5.306051, "end_time": "2021-02-27T00:31:42.963991", "exception": false, "start_time": "2021-02-27T00:31:37.657940", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Root Mean Squared Error: 0.04889805162118445\n" ] } ], "source": [ "rf_model.fit(X_train, y_train)\n", "rf_val_predictions = rf_model.predict(X_train)\n", "rf_val_mae = mean_squared_error(rf_val_predictions, y_train)(1/2)\n", "print(\"Root Mean Squared Error:\", rf_val_mae)#0.04864128166289313" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.063285, "end_time": "2021-02-27T00:31:43.090698", "exception": false, "start_time": "2021-02-27T00:31:43.027413", "status": "completed" }, "tags": [] }, "source": [ "Here, we can see that a Random Forest model is a great improvement on the multivariate model. The cross-validated RMSE here is about 0.135 compared to the multivariate score of 0.357. It is also an improvment over the single decision tree's score of 0.177. However, this model is much more complicated and computationally expensive. " ] }, { "cell_type": "code", "execution_count": 42, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:31:43.220096Z", "iopub.status.busy": "2021-02-27T00:31:43.219368Z", "iopub.status.idle": "2021-02-27T00:31:43.447181Z", "shell.execute_reply": "2021-02-27T00:31:43.446600Z" }, "papermill": { "duration": 0.293958, "end_time": "2021-02-27T00:31:43.447324", "exception": false, "start_time": "2021-02-27T00:31:43.153366", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "resid_v = (rf_val_predictions-y_train)2\n", "plt.ylabel('Squared Residuals')\n", "plt.xlabel('Index')\n", "plt.xlim(0,len(y_train)+10)\n", "plt.plot(range(len(resid_v)),resid_v, \"o\")\n", "plt.plot([-10, 2000], [rf_val_mae, rf_val_mae], 'k-', lw=2)\n", "\n", "plt.annotate('Root Mean Squared Error',xy = (1400,rf_val_mae), xycoords='data',\n", " xytext=(1500,max(resid_v)/2), arrowprops=dict(arrowstyle=\"->\",facecolor='black')) \n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.064404, "end_time": "2021-02-27T00:31:43.577201", "exception": false, "start_time": "2021-02-27T00:31:43.512797", "status": "completed" }, "tags": [] }, "source": [ "Looking at this residual plot, we can see some similar patterns to the previous plot for the OLS model, suggesting that there are a few outliers that this model is not accommodating. " ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.063045, "end_time": "2021-02-27T00:31:43.704104", "exception": false, "start_time": "2021-02-27T00:31:43.641059", "status": "completed" }, "tags": [] }, "source": [ "### XGBoost\n", "XGBoost, which stands for extreme gradient boosting, is an implementation of gradient boosting. Gradient boosting is an ensemble method that iteratively adds models in cycles. That is to say, gradient boosting forms a group of models to use as regressors or classifiers by starting with an initial model and using that to fit new models each cycle. The cycle uses the current models in the ensemble to generate predictions for each observation in the dataset. These predictions, via a loss function, are used to fit a new model to add to the ensemble. I performed the hyper-parameter optimization by hand." ] }, { "cell_type": "code", "execution_count": 43, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:31:43.841162Z", "iopub.status.busy": "2021-02-27T00:31:43.840097Z", "iopub.status.idle": "2021-02-27T00:31:43.843989Z", "shell.execute_reply": "2021-02-27T00:31:43.842864Z" }, "papermill": { "duration": 0.075051, "end_time": "2021-02-27T00:31:43.844147", "exception": false, "start_time": "2021-02-27T00:31:43.769096", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "XGBModel2 = XGBRegressor(n_estimators=2000, learning_rate=0.02, \n", " max_depth = 3, subsample = 0.8, colsample_bytree = 0.2, \n", " gamma = 0, n_jobs=-1, random_state = 31415)" ] }, { "cell_type": "code", "execution_count": 44, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:31:43.983419Z", "iopub.status.busy": "2021-02-27T00:31:43.982555Z", "iopub.status.idle": "2021-02-27T00:32:02.461436Z", "shell.execute_reply": "2021-02-27T00:32:02.460478Z" }, "papermill": { "duration": 18.553249, "end_time": "2021-02-27T00:32:02.461724", "exception": false, "start_time": "2021-02-27T00:31:43.908475", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/opt/conda/lib/python3.7/site-packages/joblib/externals/loky/process_executor.py:706: UserWarning: A worker stopped while some jobs were given to the executor. This can be caused by a too short worker timeout or by a memory leak.\n", " \"timeout or by a memory leak.\", UserWarning\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "[0.11138019 0.13152756 0.12390859 0.10421113 0.11524729]\n", "Cross-Validated RMSE: 0.11725495295277473\n" ] } ], "source": [ "full_CV = cross_val_score(XGBModel2,X_train,y_train,scoring = basic_score,\n", " cv = 5, n_jobs = -1)\n", "CV_RMSE = py.mean(full_CV)\n", "print(full_CV)\n", "print('Cross-Validated RMSE:',CV_RMSE)#0.11686018766610913" ] }, { "cell_type": "code", "execution_count": 45, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:32:02.603207Z", "iopub.status.busy": "2021-02-27T00:32:02.602404Z", "iopub.status.idle": "2021-02-27T00:32:09.966029Z", "shell.execute_reply": "2021-02-27T00:32:09.965076Z" }, "papermill": { "duration": 7.435667, "end_time": "2021-02-27T00:32:09.966200", "exception": false, "start_time": "2021-02-27T00:32:02.530533", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Root Mean Square Error: 0.048782088704088504\n" ] } ], "source": [ "# Fit the model\n", "XGBModel2.fit(X_train, y_train, \n", " eval_metric = 'rmse',\n", " verbose=False)\n", "\n", "# Get predictions\n", "predictions_X = XGBModel2.predict(X_train) # Your code here\n", "\n", "# Calculate MAE\n", "mae_X = mean_squared_error(predictions_X, y_train)(1/2) # Your code here\n", "print(\"Root Mean Square Error:\", (mae_X)) \n", "#0.048673194399949625" ] }, { "cell_type": "code", "execution_count": 46, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:32:10.123055Z", "iopub.status.busy": "2021-02-27T00:32:10.122254Z", "iopub.status.idle": "2021-02-27T00:32:10.320103Z", "shell.execute_reply": "2021-02-27T00:32:10.319442Z" }, "papermill": { "duration": 0.286225, "end_time": "2021-02-27T00:32:10.320271", "exception": false, "start_time": "2021-02-27T00:32:10.034046", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "resid_v = ((predictions_X)-y_train)2\n", "plt.ylabel('Squared Residuals')\n", "plt.xlabel('Index')\n", "plt.xlim(0,len(y_train)+10)\n", "plt.plot(range(len(resid_v)),resid_v, \"o\")\n", "plt.plot([-10, 2000], [mae_X, mae_X], 'k-', lw=2)\n", "plt.annotate('Root Mean Squared Error',xy = (1400,mae_X), xycoords='data',\n", " xytext=(1550,max(resid_v)/2), arrowprops=dict(arrowstyle=\"->\",facecolor='black')) \n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.065331, "end_time": "2021-02-27T00:32:10.451884", "exception": false, "start_time": "2021-02-27T00:32:10.386553", "status": "completed" }, "tags": [] }, "source": [ "Here, we can see that a XGBoost model is a great improvement on even the random forest model. The cross-validated RMSE here is about 0.117 compared to the random forest score of 0.135. The residual plot also shows that there are still a few outliers. \n", "\n", "Although it is interesting to note that the XGBoost model's fit to the full training data is slightly worse than the random forest model's, indicating that the random forest may be overfitting the data. Below we can see an even more extreme example of overfitting. " ] }, { "cell_type": "code", "execution_count": 47, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:32:10.600657Z", "iopub.status.busy": "2021-02-27T00:32:10.599113Z", "iopub.status.idle": "2021-02-27T00:32:20.736963Z", "shell.execute_reply": "2021-02-27T00:32:20.736292Z" }, "papermill": { "duration": 10.219127, "end_time": "2021-02-27T00:32:20.737108", "exception": false, "start_time": "2021-02-27T00:32:10.517981", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Root Mean Squared Error: 0.00045737980164642415\n" ] } ], "source": [ "XGBModel3 = XGBRegressor(n_estimators=2000, learning_rate=1.151, n_jobs=-1, random_state = 31415) # Your code here\n", "\n", "# Fit the model\n", "XGBModel3.fit(X_train, y_train,\n", " eval_metric = 'rmse',\n", " verbose=True)\n", "\n", "\n", "# Get predictions\n", "predictions_X = XGBModel3.predict(X_train) # Your code here\n", "\n", "# Calculate MAE\n", "mae_X = mean_squared_error(predictions_X, y_train)*(1/2) # Your code here\n", "print(\"Root Mean Squared Error:\", mae_X) #0.00045737980164642415" ] }, { "cell_type": "code", "execution_count": 48, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:32:20.883025Z", "iopub.status.busy": "2021-02-27T00:32:20.881796Z", "iopub.status.idle": "2021-02-27T00:32:42.974127Z", "shell.execute_reply": "2021-02-27T00:32:42.972936Z" }, "papermill": { "duration": 22.16959, "end_time": "2021-02-27T00:32:42.974289", "exception": false, "start_time": "2021-02-27T00:32:20.804699", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[0.20155222 0.21452853 0.2138819 0.18744547 0.24808154]\n", "Cross-Validated RMSE: 0.21309793394835164\n" ] } ], "source": [ "full_CV = cross_val_score(XGBModel3,X_train,y_train,scoring = basic_score,\n", " cv = 5, n_jobs = -1)\n", "CV_RMSE = py.mean(full_CV)\n", "print(full_CV)\n", "print('Cross-Validated RMSE:',CV_RMSE)#0.2131412227630994" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.067483, "end_time": "2021-02-27T00:32:43.110910", "exception": false, "start_time": "2021-02-27T00:32:43.043427", "status": "completed" }, "tags": [] }, "source": [ "Here, we can see that it is easy to make a model that can fit the training data extremely well, but that this same model does not perform well on cross-validation, because it is overfitting the training data. " ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.067771, "end_time": "2021-02-27T00:32:43.247115", "exception": false, "start_time": "2021-02-27T00:32:43.179344", "status": "completed" }, "tags": [] }, "source": [ "## Exporting Predictions\n", "We will use our ensemble model to determine the predictions. Tedious testing has allowed me to put together the below model." ] }, { "cell_type": "code", "execution_count": 49, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:32:43.392546Z", "iopub.status.busy": "2021-02-27T00:32:43.391764Z", "iopub.status.idle": "2021-02-27T00:32:52.365891Z", "shell.execute_reply": "2021-02-27T00:32:52.366443Z" }, "papermill": { "duration": 9.051283, "end_time": "2021-02-27T00:32:52.366650", "exception": false, "start_time": "2021-02-27T00:32:43.315367", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[0.10972589 0.13381449 0.12600797 0.10507106 0.12020696]\n", "Cross-Validated RMSE: 0.11896527353577183\n" ] } ], "source": [ "XGBModel1 = XGBRegressor(n_estimators=2000, learning_rate=0.02, max_depth = 3, \n", " subsample = 0.95, colsample_bytree = 0.05, gamma = 0, \n", " n_jobs=-1, random_state = 31415)\n", "full_CV = cross_val_score(XGBModel1,X_train,y_true,scoring = basic_score_X,\n", " cv = 5, n_jobs = -1)\n", "CV_RMSE = py.mean(full_CV)\n", "print(full_CV)\n", "print('Cross-Validated RMSE:',CV_RMSE)#0.11916145928557147" ] }, { "cell_type": "code", "execution_count": 50, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:32:52.515790Z", "iopub.status.busy": "2021-02-27T00:32:52.514979Z", "iopub.status.idle": "2021-02-27T00:32:56.510099Z", "shell.execute_reply": "2021-02-27T00:32:56.509289Z" }, "papermill": { "duration": 4.075879, "end_time": "2021-02-27T00:32:56.510250", "exception": false, "start_time": "2021-02-27T00:32:52.434371", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "XGBModel1.fit(X_train, y_true, eval_metric = 'rmse',verbose=False)\n", "XGBpredictions_Test = XGBModel1.predict(X_test)" ] }, { "cell_type": "code", "execution_count": 51, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:32:56.651902Z", "iopub.status.busy": "2021-02-27T00:32:56.651089Z", "iopub.status.idle": "2021-02-27T00:32:56.654487Z", "shell.execute_reply": "2021-02-27T00:32:56.653875Z" }, "papermill": { "duration": 0.076319, "end_time": "2021-02-27T00:32:56.654622", "exception": false, "start_time": "2021-02-27T00:32:56.578303", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "predictions_Test = XGBpredictions_Test" ] }, { "cell_type": "code", "execution_count": 52, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:32:56.799055Z", "iopub.status.busy": "2021-02-27T00:32:56.798207Z", "iopub.status.idle": "2021-02-27T00:32:57.088983Z", "shell.execute_reply": "2021-02-27T00:32:57.089559Z" }, "papermill": { "duration": 0.367112, "end_time": "2021-02-27T00:32:57.089784", "exception": false, "start_time": "2021-02-27T00:32:56.722672", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "output = pd.DataFrame({'Id': test_home_data.Id,\n", " 'SalePrice': predictions_Test})\n", "output.to_csv('submission.csv', index=False)" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.080887, "end_time": "2021-02-27T00:32:57.249017", "exception": false, "start_time": "2021-02-27T00:32:57.168130", "status": "completed" }, "tags": [] }, "source": [ "As of the time of this writing, this model placed in the top 2% with a mean absolute error ('MAE') (despite the competition description using RMSE the actual evaluation is based on MAE) of about 13,236 on the test data. So, there is still room for improvement. I would suggest: explore ensemble methods and other linear regression machine learning procedures, create further interaction variables (e.g., the ratio of rooms to bathrooms, or remodel year to sale year, etc.), then further hyperparameter optimization (as the models I used were not fully optimized, and adding new variables will necessitate further optimization). To that end I would suggest using Lasso, or ElasticNet, and a stacked regression or voting ensemble, the Pandas corr method, and the Sklearn RandomizedSearchCV or GridSearchCV from model_selection." ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.6" }, "papermill": { "duration": 184.791878, "end_time": "2021-02-27T00:32:57.446917", "environment_variables": {}, "exception": null, "input_path": "__notebook__.ipynb", "output_path": "__notebook__.ipynb", "parameters": {}, "start_time": "2021-02-27T00:29:52.655039", "version": "2.1.0" } }, "nbformat": 4, "nbformat_minor": 4 }	0055/329/55329289.ipynb	s3://data-agents/kaggle-outputs/sharded/012_00055.jsonl.gz
{ "cells": [ { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.068779, "end_time": "2021-02-27T00:47:02.936589", "exception": false, "start_time": "2021-02-27T00:47:02.867810", "status": "completed" }, "tags": [] }, "source": [ "## cellular automata evaluation\n", "Original: https://www.kaggle.com/nroman/melanoma-pytorch-starter-efficientnet" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.064831, "end_time": "2021-02-27T00:47:03.068132", "exception": false, "start_time": "2021-02-27T00:47:03.003301", "status": "completed" }, "tags": [] }, "source": [ "#### Versions oc:\n", "* v1: fork from https://www.kaggle.com/octaviomm/melanoma-pytorch-starter-efficientnet\n", "* v2: THISONE\n", "* v3: multiple changes to work only with the files from the TRAIN folder (for training and validation)\n", "* v4: adding WeightedRandomSampler\n", "\n", "#### Versions:\n", "* v9: ColorJitter transformation added [0.896]\n", "* v10: Changed the dataset to [this one](https://www.kaggle.com/shonenkov/melanoma-merged-external-data-512x512-jpeg) with external data. [0.894]\n", "* v11: Switched to [another dataset](https://www.kaggle.com/nroman/melanoma-external-malignant-256/) which I've created by myself. Also switched from StratifiedKFold to GroupKFold [0.916]\n", "* v12: Switched to efficientnet-b1 [0.919]\n", "* v13: Using meta featues: sex and age [0.918]\n", "* v14: anatom_site_general_challenge meta feature added as one-hot encoded matrix [0.923]\n", "* v16: Fixed OOF - now it contains only data from original training dataset, without extarnal data. Also switched back to StratifiedKFold. Added DrawHair augmentation. [0.909]\n", "* v18: Too many things were changed at the same time. All experiments should have only one small change each, so it would be easy to understand how changes affect the result. Said that I rolled back everything, keeping only OOF fix, to make sure it work.\n", "* v19: Added 'Hair' augmentation. OOF rework posponed untill the best time, since there is some bug in my code for it. [0.925]\n", "* v20: Advanced Hair Augmentation technique used. Read more about it here: https://www.kaggle.com/c/siim-isic-melanoma-classification/discussion/159176 [0.923]\n", "* v21: Microscope augmentation added instead of Cutout. Read more here: https://www.kaggle.com/c/siim-isic-melanoma-classification/discussion/159476 [0.914]\n", "* v22: Changed the dataset to [this one](https://www.kaggle.com/cdeotte/jpeg-melanoma-256x256) by Chris Deotte. More info [here](https://www.kaggle.com/c/siim-isic-melanoma-classification/discussion/165526) [0.900]\n", "* v23: All the same as v22 but effnet-b0 instead of b1 and more epochs per fold. [0.895]\n", "* v24: effnet-b01 and more epochs. [0.9092]\n", "* v25: Fixed a mistake in a way of filling preds. See [this comment](https://www.kaggle.com/nroman/melanoma-pytorch-starter-efficientnet/comments?scriptVersionId=39125585#913846). [0.9016]\n", "* v26: Fix for another mistake. This time with a way of averaging TTA. See [this comment](https://www.kaggle.com/nroman/melanoma-pytorch-starter-efficientnet/comments#955916) [0.915]\n", "* v27: Back to [my dataset](https://www.kaggle.com/nroman/melanoma-external-malignant-256/)" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.067255, "end_time": "2021-02-27T00:47:03.201648", "exception": false, "start_time": "2021-02-27T00:47:03.134393", "status": "completed" }, "tags": [] }, "source": [ "# * change roc for val loss to save model\n", "# * check the threshold change for imbalanced classification \n", "# * Maybe change the way the images are loaded to match the mthos used in the augmentation !!!!!!! !!!!!!!!!!" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "_kg_hide-input": false, "_kg_hide-output": true, "execution": { "iopub.execute_input": "2021-02-27T00:47:03.328665Z", "iopub.status.busy": "2021-02-27T00:47:03.327833Z", "iopub.status.idle": "2021-02-27T00:47:14.430168Z", "shell.execute_reply": "2021-02-27T00:47:14.429534Z" }, "papermill": { "duration": 11.159336, "end_time": "2021-02-27T00:47:14.430290", "exception": false, "start_time": "2021-02-27T00:47:03.270954", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[33mWARNING: You are using pip version 20.1; however, version 21.0.1 is available.\r\n", "You should consider upgrading via the '/opt/conda/bin/python3.7 -m pip install --upgrade pip' command.\u001b[0m\r\n" ] } ], "source": [ "!pip install -q efficientnet_pytorch torchtoolbox" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19", "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5", "execution": { "iopub.execute_input": "2021-02-27T00:47:14.538869Z", "iopub.status.busy": "2021-02-27T00:47:14.538072Z", "iopub.status.idle": "2021-02-27T00:47:17.250214Z", "shell.execute_reply": "2021-02-27T00:47:17.249242Z" }, "papermill": { "duration": 2.772908, "end_time": "2021-02-27T00:47:17.250359", "exception": false, "start_time": "2021-02-27T00:47:14.477451", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "import torch\n", "import torchvision\n", "import torch.nn.functional as F\n", "import torch.nn as nn\n", "import torchtoolbox.transform as transforms\n", "from torch.utils.data import Dataset, DataLoader, Subset\n", "from torch.optim.lr_scheduler import ReduceLROnPlateau\n", "from sklearn.metrics import accuracy_score, roc_auc_score\n", "from sklearn.model_selection import StratifiedKFold, GroupKFold, KFold\n", "import pandas as pd\n", "import numpy as np\n", "import gc\n", "import os\n", "import cv2\n", "import time\n", "import datetime\n", "import warnings\n", "import random\n", "import matplotlib.pyplot as plt\n", "import seaborn as sns\n", "from tqdm.notebook import tqdm\n", "from efficientnet_pytorch import EfficientNet\n", "from torch.utils.data import WeightedRandomSampler\n", "from sklearn.metrics import precision_score, recall_score\n", "from IPython.display import FileLink\n", "%matplotlib inline" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:47:17.351615Z", "iopub.status.busy": "2021-02-27T00:47:17.350842Z", "iopub.status.idle": "2021-02-27T00:47:17.356489Z", "shell.execute_reply": "2021-02-27T00:47:17.355788Z" }, "papermill": { "duration": 0.058304, "end_time": "2021-02-27T00:47:17.356607", "exception": false, "start_time": "2021-02-27T00:47:17.298303", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "warnings.simplefilter('ignore')\n", "def seed_everything(seed):\n", " random.seed(seed)\n", " os.environ['PYTHONHASHSEED'] = str(seed)\n", " np.random.seed(seed)\n", " torch.manual_seed(seed)\n", " torch.cuda.manual_seed(seed)\n", " torch.backends.cudnn.deterministic = True\n", " torch.backends.cudnn.benchmark = True\n", "\n", "seed_everything(47)" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:47:17.470883Z", "iopub.status.busy": "2021-02-27T00:47:17.457443Z", "iopub.status.idle": "2021-02-27T00:47:17.473511Z", "shell.execute_reply": "2021-02-27T00:47:17.473036Z" }, "papermill": { "duration": 0.070286, "end_time": "2021-02-27T00:47:17.473613", "exception": false, "start_time": "2021-02-27T00:47:17.403327", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "def make_train_test_df_for_cea_aug2(train_df_orig, df_cea_done, test_set_size = 2000, test_set_1s = 100, add_0s_into_train_df=0, add_1s_into_train_df=0):\n", " '''make a train_df that contains all the files that cea==completed & target==1\n", " and a test_df that has all the files that cea!=completed & target==1\n", " Optionally you can include fewer files'''\n", " # make a train_df that contains all the files that cea==completed & target==1\n", " image_name_cea_done = df_cea_done['image_name'].values\n", " train_df = train_df_orig[train_df_orig['image_name'].isin(image_name_cea_done)]\n", " # make sure test_df has all the files that cea!=completed & target==1\n", " test_df_large = train_df_orig[~train_df_orig['image_name'].isin(image_name_cea_done)]\n", " # divide in target==1 & target == 0\n", " test_df_only1s = test_df_large[test_df_large['target']==1]\n", " test_df_only0s = test_df_large[test_df_large['target']==0]\n", " test_df_only0s = test_df_only0s.reset_index(drop=True)\n", " test_df_only1s = test_df_only1s.reset_index(drop=True)\n", " # if add_0s_into_train_df more samples are wanted in train_df (of zeros)\n", " if add_0s_into_train_df >0:\n", " random.seed(0)\n", " rand_ints = random.sample(range(len(test_df_only0s)-1), add_0s_into_train_df)\n", " extra_0s_for_train_df = test_df_only0s.iloc[rand_ints]\n", " train_df = train_df.append(extra_0s_for_train_df)\n", " test_df_only0s =test_df_only0s.drop(rand_ints, axis=0)\n", " # if add_1s_into_train_df more samples are wanted in train_df (of ones)\n", " if add_1s_into_train_df >0:\n", " random.seed(0)\n", " rand_ints = random.sample(range(len(test_df_only1s)-1), add_1s_into_train_df)\n", " extra_1s_for_train_df = test_df_only1s.iloc[rand_ints]\n", " train_df = train_df.append(extra_1s_for_train_df)\n", " test_df_only1s = test_df_only1s.drop(rand_ints, axis=0)\n", " # if only a subset of the target == 1 is wanted\n", " if test_set_1s > 0:\n", " random.seed(0)\n", " rand_ints = random.sample(range(len(test_df_only1s)), test_set_1s)\n", " test_df_only1s = test_df_only1s.iloc[rand_ints]\n", " \n", " # if add_1s_into_train_df > 0 or add_0s_into_train_df > 0\n", " if add_1s_into_train_df > 0 or add_0s_into_train_df > 0:\n", " test_df_large = pd.DataFrame()\n", " test_df_large = test_df_large.append(test_df_only1s)\n", " test_df_large = test_df_large.append(test_df_only0s)\n", " random.seed(0)\n", " rand_ints = random.sample(range(len(test_df_large)), len(test_df_large))\n", " test_df_large.index = rand_ints\n", " test_df_large = test_df_large.reindex()\n", " test_df = test_df_large\n", " else:\n", " # get a large subset of test_df_large that contain all target 1 from test_df_large\n", " test_df = test_df_large\n", " if test_set_size > 0:\n", " number1s_already_in_test = len(test_df_only1s)\n", " random.seed(0)\n", " rand_ints = random.sample(range(len(test_df_only0s)), test_set_size - number1s_already_in_test)\n", " test_df_only0s_subset = test_df_only0s.iloc[rand_ints]\n", " test_df = test_df_only1s.append(test_df_only0s_subset)\n", " return train_df.reset_index(drop=True), test_df.reset_index(drop=True)" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:47:17.570676Z", "iopub.status.busy": "2021-02-27T00:47:17.569834Z", "iopub.status.idle": "2021-02-27T00:47:17.573024Z", "shell.execute_reply": "2021-02-27T00:47:17.572473Z" }, "papermill": { "duration": 0.053664, "end_time": "2021-02-27T00:47:17.573128", "exception": false, "start_time": "2021-02-27T00:47:17.519464", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "# # OC cea files\n", "# df_cea = pd.read_csv('/kaggle/input/files-cea-done/train_for_classification_v0.csv')\n", "# df_cea.drop(['note', 'folder', 'inpainting'], axis=1, inplace=True)\n", "# print(df_cea.shape)\n", "# df_cea.head()" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:47:17.681219Z", "iopub.status.busy": "2021-02-27T00:47:17.680334Z", "iopub.status.idle": "2021-02-27T00:47:17.683529Z", "shell.execute_reply": "2021-02-27T00:47:17.682886Z" }, "papermill": { "duration": 0.060375, "end_time": "2021-02-27T00:47:17.683627", "exception": false, "start_time": "2021-02-27T00:47:17.623252", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "# # OC comparison of the original datasets used\n", "# extra_train_files = os.listdir('/kaggle/input/melanoma-external-malignant-256/train/train')\n", "# train_files = os.listdir('/kaggle/input/jpeg-melanoma-256x256/train')\n", "# extra_test_files = os.listdir('/kaggle/input/melanoma-external-malignant-256/test/test')\n", "# test_files = os.listdir('/kaggle/input/jpeg-melanoma-256x256/test')\n", "# print(' extra default')\n", "# print('train:',len(extra_train_files), len(train_files))\n", "# print('test: ',len(extra_test_files), len(test_files))" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:47:18.145280Z", "iopub.status.busy": "2021-02-27T00:47:18.141996Z", "iopub.status.idle": "2021-02-27T00:47:18.149167Z", "shell.execute_reply": "2021-02-27T00:47:18.148623Z" }, "papermill": { "duration": 0.418974, "end_time": "2021-02-27T00:47:18.149272", "exception": false, "start_time": "2021-02-27T00:47:17.730298", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "device(type='cuda')" ] }, "execution_count": 7, "metadata": {}, "output_type": "execute_result" } ], "source": [ "device = torch.device(\"cuda\" if torch.cuda.is_available() else \"cpu\")\n", "device" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:47:18.266343Z", "iopub.status.busy": "2021-02-27T00:47:18.264505Z", "iopub.status.idle": "2021-02-27T00:47:18.267103Z", "shell.execute_reply": "2021-02-27T00:47:18.267584Z" }, "papermill": { "duration": 0.071071, "end_time": "2021-02-27T00:47:18.267706", "exception": false, "start_time": "2021-02-27T00:47:18.196635", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "class MelanomaDataset(Dataset):\n", " def __init__(self, df: pd.DataFrame, imfolder: str, train: bool = True, transforms = None, meta_features = None):\n", " \"\"\"\n", " Class initialization\n", " Args:\n", " df (pd.DataFrame): DataFrame with data description\n", " imfolder (str): folder with images\n", " train (bool): flag of whether a training dataset is being initialized or testing one\n", " transforms: image transformation method to be applied\n", " meta_features (list): list of features with meta information, such as sex and age\n", " \n", " \"\"\"\n", " self.df = df\n", " self.imfolder = imfolder\n", " self.transforms = transforms\n", " self.train = train\n", " self.meta_features = meta_features\n", " \n", " def __getitem__(self, index):\n", " # print(index)\n", " im_path = os.path.join(self.imfolder, self.df.iloc[index]['image_name'] + '.jpg')\n", " # print(im_path)\n", " x = cv2.imread(im_path)\n", " meta = np.array(self.df.iloc[index][self.meta_features].values, dtype=np.float32)\n", "\n", " if self.transforms:\n", " x = self.transforms(x)\n", " \n", " if self.train:\n", " y = self.df.iloc[index]['target']\n", " return (x, meta), y\n", " else:\n", " return (x, meta)\n", " \n", " def __len__(self):\n", " return len(self.df)\n", " \n", " \n", "class Net(nn.Module):\n", " def __init__(self, arch, n_meta_features: int):\n", " super(Net, self).__init__()\n", " self.arch = arch\n", " if 'ResNet' in str(arch.__class__):\n", " self.arch.fc = nn.Linear(in_features=512, out_features=500, bias=True)\n", " if 'EfficientNet' in str(arch.__class__):\n", " self.arch._fc = nn.Linear(in_features=1280, out_features=500, bias=True)\n", " self.meta = nn.Sequential(nn.Linear(n_meta_features, 500),\n", " nn.BatchNorm1d(500),\n", " nn.ReLU(),\n", " nn.Dropout(p=0.2),\n", " nn.Linear(500, 250), # FC layer output will have 250 features\n", " nn.BatchNorm1d(250),\n", " nn.ReLU(),\n", " nn.Dropout(p=0.2))\n", " self.ouput = nn.Linear(500 + 250, 1)\n", " \n", " def forward(self, inputs):\n", " \"\"\"\n", " No sigmoid in forward because we are going to use BCEWithLogitsLoss\n", " Which applies sigmoid for us when calculating a loss\n", " \"\"\"\n", " x, meta = inputs\n", " cnn_features = self.arch(x)\n", " meta_features = self.meta(meta)\n", " features = torch.cat((cnn_features, meta_features), dim=1)\n", " output = self.ouput(features)\n", " return output" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:47:18.372201Z", "iopub.status.busy": "2021-02-27T00:47:18.371460Z", "iopub.status.idle": "2021-02-27T00:47:18.375465Z", "shell.execute_reply": "2021-02-27T00:47:18.374999Z" }, "papermill": { "duration": 0.061031, "end_time": "2021-02-27T00:47:18.375557", "exception": false, "start_time": "2021-02-27T00:47:18.314526", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "class Microscope:\n", " \"\"\"\n", " Cutting out the edges around the center circle of the image\n", " Imitating a picture, taken through the microscope\n", "\n", " Args:\n", " p (float): probability of applying an augmentation\n", " \"\"\"\n", "\n", " def __init__(self, p: float = 0.5):\n", " self.p = p\n", "\n", " def __call__(self, img):\n", " \"\"\"\n", " Args:\n", " img (PIL Image): Image to apply transformation to.\n", "\n", " Returns:\n", " PIL Image: Image with transformation.\n", " \"\"\"\n", " if random.random() < self.p:\n", " circle = cv2.circle((np.ones(img.shape) * 255).astype(np.uint8), # image placeholder\n", " (img.shape[0]//2, img.shape[1]//2), # center point of circle\n", " random.randint(img.shape[0]//2 - 3, img.shape[0]//2 + 15), # radius\n", " (0, 0, 0), # color\n", " -1)\n", "\n", " mask = circle - 255\n", " img = np.multiply(img, mask)\n", " \n", " return img\n", "\n", " def __repr__(self):\n", " return f'{self.__class__.__name__}(p={self.p})'" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:47:18.486664Z", "iopub.status.busy": "2021-02-27T00:47:18.485004Z", "iopub.status.idle": "2021-02-27T00:47:18.492533Z", "shell.execute_reply": "2021-02-27T00:47:18.493081Z" }, "papermill": { "duration": 0.071126, "end_time": "2021-02-27T00:47:18.493252", "exception": false, "start_time": "2021-02-27T00:47:18.422126", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "train_transform = transforms.Compose([\n", " #AdvancedHairAugmentation(hairs_folder='/kaggle/input/melanoma-hairs'),\n", " transforms.RandomResizedCrop(size=256, scale=(0.8, 1.0)),\n", " transforms.RandomHorizontalFlip(),\n", " transforms.RandomVerticalFlip(),\n", " Microscope(p=0.5),\n", " transforms.ToTensor(),\n", " transforms.Normalize(mean=[0.485, 0.456, 0.406],std=[0.229, 0.224, 0.225])\n", "])\n", "test_transform = transforms.Compose([\n", " transforms.ToTensor(),\n", " transforms.Normalize(mean=[0.485, 0.456, 0.406],std=[0.229, 0.224, 0.225])\n", "])" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:47:18.653862Z", "iopub.status.busy": "2021-02-27T00:47:18.652872Z", "iopub.status.idle": "2021-02-27T00:47:19.903541Z", "shell.execute_reply": "2021-02-27T00:47:19.902825Z" }, "papermill": { "duration": 1.333218, "end_time": "2021-02-27T00:47:19.903687", "exception": false, "start_time": "2021-02-27T00:47:18.570469", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Downloading: \"https://github.com/lukemelas/EfficientNet-PyTorch/releases/download/1.0/efficientnet-b1-f1951068.pth\" to /root/.cache/torch/checkpoints/efficientnet-b1-f1951068.pth\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "eda9591e42394aaf812897dc82670770", "version_major": 2, "version_minor": 0 }, "text/plain": [ "HBox(children=(FloatProgress(value=0.0, max=31519111.0), HTML(value='')))" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "Loaded pretrained weights for efficientnet-b1\n" ] } ], "source": [ "arch = EfficientNet.from_pretrained('efficientnet-b1');" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:47:20.016081Z", "iopub.status.busy": "2021-02-27T00:47:20.015370Z", "iopub.status.idle": "2021-02-27T00:47:20.114371Z", "shell.execute_reply": "2021-02-27T00:47:20.113813Z" }, "papermill": { "duration": 0.160295, "end_time": "2021-02-27T00:47:20.114475", "exception": false, "start_time": "2021-02-27T00:47:19.954180", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "train_df_orig = (33126, 11), train_df total 1's = 584\n", "df_cea_done = (264, 1)\n" ] } ], "source": [ "# OC just checking shapes and files that completed cea reconstruction\n", "train_df_orig = pd.read_csv('/kaggle/input/jpeg-melanoma-256x256/train.csv')\n", "df_cea_done = pd.read_csv('/kaggle/input/files-cea-done-264/files_cea_done_264.csv')\n", "print(f\"train_df_orig = {train_df_orig.shape}, train_df total 1's = {np.sum(train_df_orig['target'].values)}\")\n", "print(f'df_cea_done = {df_cea_done.shape}')" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:47:20.219419Z", "iopub.status.busy": "2021-02-27T00:47:20.218640Z", "iopub.status.idle": "2021-02-27T00:47:20.221309Z", "shell.execute_reply": "2021-02-27T00:47:20.221938Z" }, "papermill": { "duration": 0.056432, "end_time": "2021-02-27T00:47:20.222054", "exception": false, "start_time": "2021-02-27T00:47:20.165622", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "# # OPTION 1\n", "# train_df, test_df = make_train_test_df_for_cea_aug2(train_df_orig, df_cea_done, \n", "# test_set_size = 2000, test_set_1s = 450,\n", "# add_0s_into_train_df = 1524-len(df_cea_done),#1500-len(df_cea_done)\n", "# add_1s_into_train_df = 0) # 0\n", "# np.shape(train_df), np.shape(test_df)\n", "# print(f\"train_df = {train_df.shape}, train_df total 1's = {np.sum(train_df['target'].values)}, train_df total 1=0's = {np.sum(train_df['target'].values==0)}\")\n", "# print(f\"test_df = {test_df.shape}, test_df total 1's = {np.sum(test_df['target'].values)}, test_df total 0's = {np.sum(test_df['target'].values==0)}\")" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:47:20.332823Z", "iopub.status.busy": "2021-02-27T00:47:20.332235Z", "iopub.status.idle": "2021-02-27T00:47:20.437569Z", "shell.execute_reply": "2021-02-27T00:47:20.438224Z" }, "papermill": { "duration": 0.16564, "end_time": "2021-02-27T00:47:20.438381", "exception": false, "start_time": "2021-02-27T00:47:20.272741", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "train_df = (25000, 11), train_df total 1's = 134, train_df total 1=0's = 24866\n", "test_df = (8126, 11), test_df total 1's = 450, test_df total 0's = 7676\n" ] } ], "source": [ "# OPTION 2\n", "train_df, test_df = make_train_test_df_for_cea_aug2(train_df_orig, df_cea_done, \n", " test_set_size = 2000, test_set_1s = 450,\n", " add_0s_into_train_df = 24890-len(df_cea_done),#1500-len(df_cea_done)\n", " add_1s_into_train_df = 110) # 0\n", "np.shape(train_df), np.shape(test_df)\n", "print(f\"train_df = {train_df.shape}, train_df total 1's = {np.sum(train_df['target'].values)}, train_df total 1=0's = {np.sum(train_df['target'].values==0)}\")\n", "print(f\"test_df = {test_df.shape}, test_df total 1's = {np.sum(test_df['target'].values)}, test_df total 0's = {np.sum(test_df['target'].values==0)}\")" ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:47:20.552621Z", "iopub.status.busy": "2021-02-27T00:47:20.551660Z", "iopub.status.idle": "2021-02-27T00:47:20.573547Z", "shell.execute_reply": "2021-02-27T00:47:20.574077Z" }, "papermill": { "duration": 0.084858, "end_time": "2021-02-27T00:47:20.574208", "exception": false, "start_time": "2021-02-27T00:47:20.489350", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "train_df = (264, 11), train_df total 1's = 24, train_df total 1=0's = 240\n", "test_df = (2000, 11), test_df total 1's = 450, test_df total 0's = 1550\n" ] } ], "source": [ "# OPTION 3 (small, only for testing)\n", "train_df, test_df = make_train_test_df_for_cea_aug2(train_df_orig, df_cea_done, \n", " test_set_size = 2000, test_set_1s = 450,\n", " add_0s_into_train_df = 0,#1500-len(df_cea_done)\n", " add_1s_into_train_df = 0) # 0\n", "np.shape(train_df), np.shape(test_df)\n", "print(f\"train_df = {train_df.shape}, train_df total 1's = {np.sum(train_df['target'].values)}, train_df total 1=0's = {np.sum(train_df['target'].values==0)}\")\n", "print(f\"test_df = {test_df.shape}, test_df total 1's = {np.sum(test_df['target'].values)}, test_df total 0's = {np.sum(test_df['target'].values==0)}\")" ] }, { "cell_type": "code", "execution_count": 16, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:47:20.691468Z", "iopub.status.busy": "2021-02-27T00:47:20.690650Z", "iopub.status.idle": "2021-02-27T00:47:20.693989Z", "shell.execute_reply": "2021-02-27T00:47:20.694504Z" }, "papermill": { "duration": 0.064684, "end_time": "2021-02-27T00:47:20.694617", "exception": false, "start_time": "2021-02-27T00:47:20.629933", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "False" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# check intersection of train and test\n", "bool(set(train_df['image_name'].values) & set(test_df['image_name'].values))" ] }, { "cell_type": "code", "execution_count": 17, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:47:20.861690Z", "iopub.status.busy": "2021-02-27T00:47:20.851437Z", "iopub.status.idle": "2021-02-27T00:47:20.900359Z", "shell.execute_reply": "2021-02-27T00:47:20.899848Z" }, "papermill": { "duration": 0.15429, "end_time": "2021-02-27T00:47:20.900458", "exception": false, "start_time": "2021-02-27T00:47:20.746168", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "# Make sure there are no train samples in test subset and vicecersa\n", "for i in train_df['image_name'].values:\n", " assert(i not in test_df['image_name'].values)\n", "for i in test_df['image_name'].values:\n", " assert(i not in train_df['image_name'].values)" ] }, { "cell_type": "code", "execution_count": 18, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:47:21.011634Z", "iopub.status.busy": "2021-02-27T00:47:21.010148Z", "iopub.status.idle": "2021-02-27T00:47:21.404421Z", "shell.execute_reply": "2021-02-27T00:47:21.404945Z" }, "papermill": { "duration": 0.453312, "end_time": "2021-02-27T00:47:21.405085", "exception": false, "start_time": "2021-02-27T00:47:20.951773", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "train_df_orig: 0.0176, 32542, 584\n", "train_df: 0.0909, 240, 24\n", "test_df: 0.2250, 1550, 450\n" ] }, { "data": { "image/png": "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\n", "text/plain": [ "<Figure size 648x144 with 3 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# Check target distribution \n", "print(f'train_df_orig: {np.sum(train_df_orig[\"target\"].values==1)/len(train_df_orig):.4f}, {np.sum(train_df_orig[\"target\"].values==0)}, {np.sum(train_df_orig[\"target\"].values==1)}')\n", "print(f'train_df: {np.sum(train_df[\"target\"].values==1)/len(train_df):.4f}, {np.sum(train_df[\"target\"].values==0)}, {np.sum(train_df[\"target\"].values==1)}')\n", "print(f'test_df: {np.sum(test_df[\"target\"].values==1)/len(test_df):.4f}, {np.sum(test_df[\"target\"].values==0)}, {np.sum(test_df[\"target\"].values==1)}')\n", "fig, ax = plt.subplots(1,3, figsize=(9,2))\n", "ax[0].hist(train_df_orig['target'].values);\n", "ax[1].hist(train_df['target'].values);\n", "ax[2].hist(test_df['target'].values);" ] }, { "cell_type": "code", "execution_count": 19, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:47:21.530656Z", "iopub.status.busy": "2021-02-27T00:47:21.529739Z", "iopub.status.idle": "2021-02-27T00:47:21.544036Z", "shell.execute_reply": "2021-02-27T00:47:21.543505Z" }, "papermill": { "duration": 0.082517, "end_time": "2021-02-27T00:47:21.544162", "exception": false, "start_time": "2021-02-27T00:47:21.461645", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>image_name</th>\n", " <th>patient_id</th>\n", " <th>sex</th>\n", " <th>age_approx</th>\n", " <th>anatom_site_general_challenge</th>\n", " <th>diagnosis</th>\n", " <th>benign_malignant</th>\n", " <th>target</th>\n", " <th>tfrecord</th>\n", " <th>width</th>\n", " <th>height</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>0</th>\n", " <td>ISIC_0015719</td>\n", " <td>IP_3075186</td>\n", " <td>female</td>\n", " <td>45.0</td>\n", " <td>upper extremity</td>\n", " <td>unknown</td>\n", " <td>benign</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>6000</td>\n", " <td>4000</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>ISIC_0078703</td>\n", " <td>IP_7279968</td>\n", " <td>male</td>\n", " <td>45.0</td>\n", " <td>torso</td>\n", " <td>unknown</td>\n", " <td>benign</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>6000</td>\n", " <td>4000</td>\n", " </tr>\n", " <tr>\n", " <th>2</th>\n", " <td>ISIC_0084086</td>\n", " <td>IP_4023055</td>\n", " <td>male</td>\n", " <td>60.0</td>\n", " <td>lower extremity</td>\n", " <td>nevus</td>\n", " <td>benign</td>\n", " <td>0</td>\n", " <td>12</td>\n", " <td>1872</td>\n", " <td>1053</td>\n", " </tr>\n", " <tr>\n", " <th>3</th>\n", " <td>ISIC_0085172</td>\n", " <td>IP_1705144</td>\n", " <td>female</td>\n", " <td>50.0</td>\n", " <td>lower extremity</td>\n", " <td>unknown</td>\n", " <td>benign</td>\n", " <td>0</td>\n", " <td>11</td>\n", " <td>6000</td>\n", " <td>4000</td>\n", " </tr>\n", " <tr>\n", " <th>4</th>\n", " <td>ISIC_0085718</td>\n", " <td>IP_1264754</td>\n", " <td>female</td>\n", " <td>65.0</td>\n", " <td>torso</td>\n", " <td>unknown</td>\n", " <td>benign</td>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>5184</td>\n", " <td>3456</td>\n", " </tr>\n", " <tr>\n", " <th>...</th>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " </tr>\n", " <tr>\n", " <th>259</th>\n", " <td>ISIC_7973598</td>\n", " <td>IP_8124898</td>\n", " <td>male</td>\n", " <td>35.0</td>\n", " <td>torso</td>\n", " <td>melanoma</td>\n", " <td>malignant</td>\n", " <td>1</td>\n", " <td>7</td>\n", " <td>4288</td>\n", " <td>2848</td>\n", " </tr>\n", " <tr>\n", " <th>260</th>\n", " <td>ISIC_8281208</td>\n", " <td>IP_9086201</td>\n", " <td>female</td>\n", " <td>40.0</td>\n", " <td>torso</td>\n", " <td>melanoma</td>\n", " <td>malignant</td>\n", " <td>1</td>\n", " <td>7</td>\n", " <td>4288</td>\n", " <td>2848</td>\n", " </tr>\n", " <tr>\n", " <th>261</th>\n", " <td>ISIC_8672524</td>\n", " <td>IP_7373371</td>\n", " <td>female</td>\n", " <td>55.0</td>\n", " <td>torso</td>\n", " <td>melanoma</td>\n", " <td>malignant</td>\n", " <td>1</td>\n", " <td>2</td>\n", " <td>4288</td>\n", " <td>2848</td>\n", " </tr>\n", " <tr>\n", " <th>262</th>\n", " <td>ISIC_9312164</td>\n", " <td>IP_4263066</td>\n", " <td>female</td>\n", " <td>65.0</td>\n", " <td>torso</td>\n", " <td>melanoma</td>\n", " <td>malignant</td>\n", " <td>1</td>\n", " <td>11</td>\n", " <td>5184</td>\n", " <td>3456</td>\n", " </tr>\n", " <tr>\n", " <th>263</th>\n", " <td>ISIC_9900191</td>\n", " <td>IP_6459335</td>\n", " <td>male</td>\n", " <td>60.0</td>\n", " <td>torso</td>\n", " <td>melanoma</td>\n", " <td>malignant</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>2592</td>\n", " <td>1936</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "<p>264 rows × 11 columns</p>\n", "</div>" ], "text/plain": [ " image_name patient_id sex age_approx \\\n", "0 ISIC_0015719 IP_3075186 female 45.0 \n", "1 ISIC_0078703 IP_7279968 male 45.0 \n", "2 ISIC_0084086 IP_4023055 male 60.0 \n", "3 ISIC_0085172 IP_1705144 female 50.0 \n", "4 ISIC_0085718 IP_1264754 female 65.0 \n", ".. ... ... ... ... \n", "259 ISIC_7973598 IP_8124898 male 35.0 \n", "260 ISIC_8281208 IP_9086201 female 40.0 \n", "261 ISIC_8672524 IP_7373371 female 55.0 \n", "262 ISIC_9312164 IP_4263066 female 65.0 \n", "263 ISIC_9900191 IP_6459335 male 60.0 \n", "\n", " anatom_site_general_challenge diagnosis benign_malignant target \\\n", "0 upper extremity unknown benign 0 \n", "1 torso unknown benign 0 \n", "2 lower extremity nevus benign 0 \n", "3 lower extremity unknown benign 0 \n", "4 torso unknown benign 0 \n", ".. ... ... ... ... \n", "259 torso melanoma malignant 1 \n", "260 torso melanoma malignant 1 \n", "261 torso melanoma malignant 1 \n", "262 torso melanoma malignant 1 \n", "263 torso melanoma malignant 1 \n", "\n", " tfrecord width height \n", "0 0 6000 4000 \n", "1 0 6000 4000 \n", "2 12 1872 1053 \n", "3 11 6000 4000 \n", "4 1 5184 3456 \n", ".. ... ... ... \n", "259 7 4288 2848 \n", "260 7 4288 2848 \n", "261 2 4288 2848 \n", "262 11 5184 3456 \n", "263 1 2592 1936 \n", "\n", "[264 rows x 11 columns]" ] }, "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ "train_df" ] }, { "cell_type": "code", "execution_count": 20, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:47:21.678468Z", "iopub.status.busy": "2021-02-27T00:47:21.677453Z", "iopub.status.idle": "2021-02-27T00:47:21.694099Z", "shell.execute_reply": "2021-02-27T00:47:21.693572Z" }, "papermill": { "duration": 0.08996, "end_time": "2021-02-27T00:47:21.694205", "exception": false, "start_time": "2021-02-27T00:47:21.604245", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>image_name</th>\n", " <th>patient_id</th>\n", " <th>sex</th>\n", " <th>age_approx</th>\n", " <th>anatom_site_general_challenge</th>\n", " <th>diagnosis</th>\n", " <th>benign_malignant</th>\n", " <th>target</th>\n", " <th>tfrecord</th>\n", " <th>width</th>\n", " <th>height</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>0</th>\n", " <td>ISIC_7183212</td>\n", " <td>IP_4294140</td>\n", " <td>male</td>\n", " <td>75.0</td>\n", " <td>lower extremity</td>\n", " <td>melanoma</td>\n", " <td>malignant</td>\n", " <td>1</td>\n", " <td>7</td>\n", " <td>2592</td>\n", " <td>1936</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>ISIC_7748311</td>\n", " <td>IP_2457893</td>\n", " <td>male</td>\n", " <td>75.0</td>\n", " <td>upper extremity</td>\n", " <td>melanoma</td>\n", " <td>malignant</td>\n", " <td>1</td>\n", " <td>8</td>\n", " <td>4288</td>\n", " <td>2848</td>\n", " </tr>\n", " <tr>\n", " <th>2</th>\n", " <td>ISIC_1009042</td>\n", " <td>IP_9954107</td>\n", " <td>male</td>\n", " <td>70.0</td>\n", " <td>torso</td>\n", " <td>melanoma</td>\n", " <td>malignant</td>\n", " <td>1</td>\n", " <td>3</td>\n", " <td>3264</td>\n", " <td>2448</td>\n", " </tr>\n", " <tr>\n", " <th>3</th>\n", " <td>ISIC_4960784</td>\n", " <td>IP_9663529</td>\n", " <td>female</td>\n", " <td>75.0</td>\n", " <td>upper extremity</td>\n", " <td>melanoma</td>\n", " <td>malignant</td>\n", " <td>1</td>\n", " <td>2</td>\n", " <td>1779</td>\n", " <td>1779</td>\n", " </tr>\n", " <tr>\n", " <th>4</th>\n", " <td>ISIC_9199429</td>\n", " <td>IP_6514499</td>\n", " <td>male</td>\n", " <td>50.0</td>\n", " <td>head/neck</td>\n", " <td>melanoma</td>\n", " <td>malignant</td>\n", " <td>1</td>\n", " <td>9</td>\n", " <td>4032</td>\n", " <td>3024</td>\n", " </tr>\n", " <tr>\n", " <th>...</th>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " </tr>\n", " <tr>\n", " <th>1995</th>\n", " <td>ISIC_2445235</td>\n", " <td>IP_5543080</td>\n", " <td>male</td>\n", " <td>60.0</td>\n", " <td>torso</td>\n", " <td>unknown</td>\n", " <td>benign</td>\n", " <td>0</td>\n", " <td>6</td>\n", " <td>5184</td>\n", " <td>3456</td>\n", " </tr>\n", " <tr>\n", " <th>1996</th>\n", " <td>ISIC_6908286</td>\n", " <td>IP_6724798</td>\n", " <td>male</td>\n", " <td>60.0</td>\n", " <td>torso</td>\n", " <td>unknown</td>\n", " <td>benign</td>\n", " <td>0</td>\n", " <td>11</td>\n", " <td>6000</td>\n", " <td>4000</td>\n", " </tr>\n", " <tr>\n", " <th>1997</th>\n", " <td>ISIC_7331345</td>\n", " <td>IP_0891666</td>\n", " <td>male</td>\n", " <td>65.0</td>\n", " <td>torso</td>\n", " <td>nevus</td>\n", " <td>benign</td>\n", " <td>0</td>\n", " <td>4</td>\n", " <td>1872</td>\n", " <td>1053</td>\n", " </tr>\n", " <tr>\n", " <th>1998</th>\n", " <td>ISIC_7194695</td>\n", " <td>IP_2068150</td>\n", " <td>male</td>\n", " <td>85.0</td>\n", " <td>torso</td>\n", " <td>seborrheic keratosis</td>\n", " <td>benign</td>\n", " <td>0</td>\n", " <td>12</td>\n", " <td>3264</td>\n", " <td>2448</td>\n", " </tr>\n", " <tr>\n", " <th>1999</th>\n", " <td>ISIC_5615250</td>\n", " <td>IP_4366219</td>\n", " <td>male</td>\n", " <td>35.0</td>\n", " <td>torso</td>\n", " <td>unknown</td>\n", " <td>benign</td>\n", " <td>0</td>\n", " <td>13</td>\n", " <td>640</td>\n", " <td>480</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "<p>2000 rows × 11 columns</p>\n", "</div>" ], "text/plain": [ " image_name patient_id sex age_approx \\\n", "0 ISIC_7183212 IP_4294140 male 75.0 \n", "1 ISIC_7748311 IP_2457893 male 75.0 \n", "2 ISIC_1009042 IP_9954107 male 70.0 \n", "3 ISIC_4960784 IP_9663529 female 75.0 \n", "4 ISIC_9199429 IP_6514499 male 50.0 \n", "... ... ... ... ... \n", "1995 ISIC_2445235 IP_5543080 male 60.0 \n", "1996 ISIC_6908286 IP_6724798 male 60.0 \n", "1997 ISIC_7331345 IP_0891666 male 65.0 \n", "1998 ISIC_7194695 IP_2068150 male 85.0 \n", "1999 ISIC_5615250 IP_4366219 male 35.0 \n", "\n", " anatom_site_general_challenge diagnosis benign_malignant \\\n", "0 lower extremity melanoma malignant \n", "1 upper extremity melanoma malignant \n", "2 torso melanoma malignant \n", "3 upper extremity melanoma malignant \n", "4 head/neck melanoma malignant \n", "... ... ... ... \n", "1995 torso unknown benign \n", "1996 torso unknown benign \n", "1997 torso nevus benign \n", "1998 torso seborrheic keratosis benign \n", "1999 torso unknown benign \n", "\n", " target tfrecord width height \n", "0 1 7 2592 1936 \n", "1 1 8 4288 2848 \n", "2 1 3 3264 2448 \n", "3 1 2 1779 1779 \n", "4 1 9 4032 3024 \n", "... ... ... ... ... \n", "1995 0 6 5184 3456 \n", "1996 0 11 6000 4000 \n", "1997 0 4 1872 1053 \n", "1998 0 12 3264 2448 \n", "1999 0 13 640 480 \n", "\n", "[2000 rows x 11 columns]" ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "test_df" ] }, { "cell_type": "code", "execution_count": 21, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:47:21.815285Z", "iopub.status.busy": "2021-02-27T00:47:21.814390Z", "iopub.status.idle": "2021-02-27T00:47:21.816640Z", "shell.execute_reply": "2021-02-27T00:47:21.817174Z" }, "papermill": { "duration": 0.063711, "end_time": "2021-02-27T00:47:21.817283", "exception": false, "start_time": "2021-02-27T00:47:21.753572", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "def get_sampler_for_imbalanced_classification(train_df):\n", " '''https://discuss.pytorch.org/t/how-to-handle-imbalanced-classes/11264/2'''\n", " target = train_df['target'].values\n", " # print(f'target train 0/1: {len(np.where(target == 1)[0])}/{len(np.where(target == 0)[0])}')\n", " class_sample_count = np.array([len(np.where(target == t)[0]) for t in np.unique(target)])\n", " weight = 1. / class_sample_count\n", " samples_weight_py = np.array([weight[t] for t in target])\n", " samples_weight = torch.from_numpy(samples_weight_py)\n", " samples_weigth = samples_weight.double()\n", " sampler = WeightedRandomSampler(samples_weight, len(samples_weight))\n", " return sampler, samples_weight_py" ] }, { "cell_type": "code", "execution_count": 22, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:47:21.939462Z", "iopub.status.busy": "2021-02-27T00:47:21.938526Z", "iopub.status.idle": "2021-02-27T00:47:21.967464Z", "shell.execute_reply": "2021-02-27T00:47:21.966633Z" }, "papermill": { "duration": 0.096485, "end_time": "2021-02-27T00:47:21.967645", "exception": false, "start_time": "2021-02-27T00:47:21.871160", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "# One-hot encoding of anatom_site_general_challenge feature\n", "concat = pd.concat([train_df['anatom_site_general_challenge'], test_df['anatom_site_general_challenge']], ignore_index=True)\n", "dummies = pd.get_dummies(concat, dummy_na=True, dtype=np.uint8, prefix='site')\n", "train_df = pd.concat([train_df, dummies.iloc[:train_df.shape[0]]], axis=1)\n", "test_df = pd.concat([test_df, dummies.iloc[train_df.shape[0]:].reset_index(drop=True)], axis=1)\n", "\n", "# Sex features\n", "train_df['sex'] = train_df['sex'].map({'male': 1, 'female': 0})\n", "test_df['sex'] = test_df['sex'].map({'male': 1, 'female': 0})\n", "train_df['sex'] = train_df['sex'].fillna(-1)\n", "test_df['sex'] = test_df['sex'].fillna(-1)\n", "\n", "# Age features\n", "train_df['age_approx'] /= train_df['age_approx'].max()\n", "test_df['age_approx'] /= test_df['age_approx'].max()\n", "train_df['age_approx'] = train_df['age_approx'].fillna(0)\n", "test_df['age_approx'] = test_df['age_approx'].fillna(0)\n", "\n", "train_df['patient_id'] = train_df['patient_id'].fillna(0)" ] }, { "cell_type": "code", "execution_count": 23, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:47:22.084963Z", "iopub.status.busy": "2021-02-27T00:47:22.084074Z", "iopub.status.idle": "2021-02-27T00:47:22.447316Z", "shell.execute_reply": "2021-02-27T00:47:22.447883Z" }, "papermill": { "duration": 0.425082, "end_time": "2021-02-27T00:47:22.448077", "exception": false, "start_time": "2021-02-27T00:47:22.022995", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "train_df_orig: 0.0176, 32542, 584\n", "train_df: 0.0909, 240, 24\n", "test_df: 0.2250, 1550, 450\n" ] }, { "data": { "image/png": "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\n", "text/plain": [ "<Figure size 648x144 with 3 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "# OC check target distribution \n", "print(f'train_df_orig: {np.sum(train_df_orig[\"target\"].values==1)/len(train_df_orig):.4f}, {np.sum(train_df_orig[\"target\"].values==0)}, {np.sum(train_df_orig[\"target\"].values==1)}')\n", "print(f'train_df: {np.sum(train_df[\"target\"].values==1)/len(train_df):.4f}, {np.sum(train_df[\"target\"].values==0)}, {np.sum(train_df[\"target\"].values==1)}')\n", "print(f'test_df: {np.sum(test_df[\"target\"].values==1)/len(test_df):.4f}, {np.sum(test_df[\"target\"].values==0)}, {np.sum(test_df[\"target\"].values==1)}')\n", "fig, ax = plt.subplots(1,3, figsize=(9,2))\n", "ax[0].hist(train_df_orig['target'].values);\n", "ax[1].hist(train_df['target'].values);\n", "ax[2].hist(test_df['target'].values);" ] }, { "cell_type": "code", "execution_count": 24, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:47:22.568718Z", "iopub.status.busy": "2021-02-27T00:47:22.567941Z", "iopub.status.idle": "2021-02-27T00:47:22.571658Z", "shell.execute_reply": "2021-02-27T00:47:22.571188Z" }, "papermill": { "duration": 0.064109, "end_time": "2021-02-27T00:47:22.571754", "exception": false, "start_time": "2021-02-27T00:47:22.507645", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "array(['sex', 'age_approx', 'site_head/neck', 'site_lower extremity',\n", " 'site_oral/genital', 'site_palms/soles', 'site_torso',\n", " 'site_upper extremity', 'site_nan'], dtype='<U20')" ] }, "execution_count": 24, "metadata": {}, "output_type": "execute_result" } ], "source": [ "meta_features = ['sex', 'age_approx'] + [col for col in train_df.columns if 'site_' in col]\n", "meta_features.remove('anatom_site_general_challenge')\n", "np.asarray(meta_features)" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.058183, "end_time": "2021-02-27T00:47:22.689611", "exception": false, "start_time": "2021-02-27T00:47:22.631428", "status": "completed" }, "tags": [] }, "source": [ "### Create a subset DF (train_df2) and check that dataloaders work " ] }, { "cell_type": "code", "execution_count": 25, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:47:22.806599Z", "iopub.status.busy": "2021-02-27T00:47:22.805819Z", "iopub.status.idle": "2021-02-27T00:47:22.808390Z", "shell.execute_reply": "2021-02-27T00:47:22.808958Z" }, "papermill": { "duration": 0.063558, "end_time": "2021-02-27T00:47:22.809077", "exception": false, "start_time": "2021-02-27T00:47:22.745519", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "train_df2 = train_df" ] }, { "cell_type": "code", "execution_count": 26, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:47:22.930532Z", "iopub.status.busy": "2021-02-27T00:47:22.929664Z", "iopub.status.idle": "2021-02-27T00:47:23.840184Z", "shell.execute_reply": "2021-02-27T00:47:23.841011Z" }, "papermill": { "duration": 0.976494, "end_time": "2021-02-27T00:47:23.841159", "exception": false, "start_time": "2021-02-27T00:47:22.864665", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "X and Y = 2\n", "X = 2 (image) and (meta features)\n", "image =torch.Size([64, 3, 256, 256]), meta features = torch.Size([64, 9])\n", "Y len = (64) ,number 1s: 36 first 5: tensor([0, 1, 1, 1, 0])\n" ] } ], "source": [ "# OC check datasets and dataloaders\n", "rand_ints = np.random.randint(0,len(train_df2),100)\n", "rand_ints = np.random.randint(0,len(train_df2),100)\n", "df=train_df2.iloc[rand_ints].reset_index(drop=True)\n", "sampler, samples_weight_py = get_sampler_for_imbalanced_classification(df)\n", "train_or_test = MelanomaDataset(df, \n", "# imfolder='/kaggle/input/melanoma-external-malignant-256/train/train/', \n", " imfolder='/kaggle/input/jpeg-melanoma-256x256/train/', \n", " train=True, \n", " transforms=train_transform,\n", " meta_features=meta_features)\n", "# XX WARNING shuffle should be false \n", "train_or_test_loader = DataLoader(dataset=train_or_test, batch_size=64, shuffle=False, num_workers=2,\n", " sampler=sampler)\n", "train_or_test_loader_item = next(iter(train_or_test_loader))\n", "print(f'X and Y = {len(train_or_test_loader_item)}')\n", "print(f'X = {len(train_or_test_loader_item[0])} (image) and (meta features)')\n", "print(f'image ={np.shape(train_or_test_loader_item[0][0])}, meta features = { np.shape(train_or_test_loader_item[0][1])}')\n", "print(f'Y len = ({len(train_or_test_loader_item[1])}) ,number 1s: {torch.sum(train_or_test_loader_item[1])} first 5: {train_or_test_loader_item[1][:5]}')" ] }, { "cell_type": "code", "execution_count": 27, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:47:23.962835Z", "iopub.status.busy": "2021-02-27T00:47:23.961946Z", "iopub.status.idle": "2021-02-27T00:47:24.576863Z", "shell.execute_reply": "2021-02-27T00:47:24.575549Z" }, "papermill": { "duration": 0.678736, "end_time": "2021-02-27T00:47:24.577040", "exception": false, "start_time": "2021-02-27T00:47:23.898304", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "# new test dataset. we get the images from the TRAIN folder\n", "test = MelanomaDataset(df=test_df.reset_index(drop=True),\n", " # imfolder='/kaggle/input/melanoma-external-malignant-256/test/test/', \n", " imfolder='/kaggle/input/jpeg-melanoma-256x256/train/', \n", " train=False,\n", " transforms=train_transform, # For TTA\n", " meta_features=meta_features)\n", "test_loader = DataLoader(dataset=test, batch_size=16, shuffle=False, num_workers=2)\n", "test_loader_item = next(iter(test_loader))" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.058891, "end_time": "2021-02-27T00:47:24.696483", "exception": false, "start_time": "2021-02-27T00:47:24.637592", "status": "completed" }, "tags": [] }, "source": [ "### check folds splits" ] }, { "cell_type": "code", "execution_count": 28, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:47:24.836281Z", "iopub.status.busy": "2021-02-27T00:47:24.834765Z", "iopub.status.idle": "2021-02-27T00:47:24.991735Z", "shell.execute_reply": "2021-02-27T00:47:24.991214Z" }, "papermill": { "duration": 0.237916, "end_time": "2021-02-27T00:47:24.991845", "exception": false, "start_time": "2021-02-27T00:47:24.753929", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "fold=1, train_idx=(211,), train_idx=[1-263], val_idx=(53,), val_idx[0-260]\n", "fold=2, train_idx=(211,), train_idx=[0-262], val_idx=(53,), val_idx[1-263]\n", "fold=3, train_idx=(211,), train_idx=[0-263], val_idx=(53,), val_idx[6-256]\n", "fold=4, train_idx=(211,), train_idx=[0-263], val_idx=(53,), val_idx[2-253]\n", "fold=5, train_idx=(212,), train_idx=[0-263], val_idx=(52,), val_idx[4-262]\n", "count_1s_per_val_fold = [3, 9, 5, 4, 3]\n" ] }, { "data": { "image/png": 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"text/plain": [ "<Figure size 2448x144 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "skf = KFold(n_splits=5, shuffle=True, random_state=47)\n", "train_idx_all = []\n", "count_1s_per_val_fold = []\n", "for fold, (train_idx, val_idx) in enumerate(skf.split(X=np.zeros(len(train_df2)), y=train_df2['target'], groups=train_df2['patient_id'].tolist()), 1):\n", " train_idx_all.append(train_idx)\n", " count_1s_per_val_fold.append(np.sum(train_df2.iloc[val_idx]['target'].values))\n", " print(f'fold={fold}, train_idx={np.shape(train_idx)}, train_idx=[{train_idx[0]}-{train_idx[-1]}], val_idx={np.shape(val_idx)}, val_idx[{val_idx[0]}-{val_idx[-1]}]')\n", "#figure\n", "fold_samples = np.zeros(len(train_df2))\n", "fold_samples[train_idx_all[2]]=1\n", "fold_samples_x = np.linspace(1,len(fold_samples),len(fold_samples))\n", "plt.figure(figsize=(34,2))\n", "plt.scatter(fold_samples_x, fold_samples, s=1);\n", "print(f'count_1s_per_val_fold = {count_1s_per_val_fold}')" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.059591, "end_time": "2021-02-27T00:47:25.110425", "exception": false, "start_time": "2021-02-27T00:47:25.050834", "status": "completed" }, "tags": [] }, "source": [ "* run for one epoch to save the LAST models, \n", "* then make a new main loop block that loads the previous LAST models and epochs " ] }, { "cell_type": "code", "execution_count": 29, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T00:47:25.276293Z", "iopub.status.busy": "2021-02-27T00:47:25.259781Z" }, "papermill": { "duration": null, "end_time": null, "exception": false, "start_time": "2021-02-27T00:47:25.169216", "status": "running" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "==================== Fold 1 ====================\n", "Loaded pretrained weights for efficientnet-b1\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Epoch 001: \| Loss: 1.791 \| Train acc: 0.749 \| Val acc: 0.943 \| Val roc_auc: 0.980 \| Training time: 0:00:06\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "02cb09f9a7764c78918b6e1603fb6119", "version_major": 2, "version_minor": 0 }, "text/plain": [ "HBox(children=(FloatProgress(value=0.0, description='test set', max=126.0, style=ProgressStyle(description_wid…" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "==================== Fold 2 ====================\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Loaded pretrained weights for efficientnet-b1\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Epoch 001: \| Loss: 1.739 \| Train acc: 0.720 \| Val acc: 0.830 \| Val roc_auc: 0.755 \| Training time: 0:00:03\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "c06bd55a447b4852b8cd074b8dd85143", "version_major": 2, "version_minor": 0 }, "text/plain": [ "HBox(children=(FloatProgress(value=0.0, description='test set', max=126.0, style=ProgressStyle(description_wid…" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "\n", "==================== Fold 3 ====================\n", "Loaded pretrained weights for efficientnet-b1\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Epoch 001: \| Loss: 2.239 \| Train acc: 0.701 \| Val acc: 0.925 \| Val roc_auc: 0.950 \| Training time: 0:00:03\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "a72cecd36b104796ba8ceff72b9f3972", "version_major": 2, "version_minor": 0 }, "text/plain": [ "HBox(children=(FloatProgress(value=0.0, description='test set', max=126.0, style=ProgressStyle(description_wid…" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "WEIGHTED_SAMPLER = True\n", "epochs = 1 # orig 12 \n", "BATCH_SIZE_TRAIN = 64 # orig 64\n", "BATCH_SIZE_VAL_TEST = 16\n", "es_patience = 5 # orig 3 # Early Stopping patience - for how many epochs with no improvements to wait\n", "# TTA = 3 # Test Time Augmentation rounds\n", "start = time.time()\n", "skf = KFold(n_splits=5, shuffle=True, random_state=47)\n", "\n", "val_acc_all = [ [] for _ in range(skf.n_splits) ]\n", "val_roc_all = [ [] for _ in range(skf.n_splits) ]\n", "val_precision_all = [ [] for _ in range(skf.n_splits) ]\n", "val_recall_all = [ [] for _ in range(skf.n_splits) ]\n", "epoch_loss_all = [ [] for _ in range(skf.n_splits) ]\n", "epoch_loss_val_all = [ [] for _ in range(skf.n_splits) ]\n", "\n", "oof = np.zeros((len(train_df2), 1)) # Out Of Fold predictions\n", "oof_all = np.zeros((len(train_df2), skf.n_splits)) # Out Of Fold predictions OC\n", "preds = torch.zeros((len(test), 1), dtype=torch.float32, device=device) # Predictions for test test\n", "preds_separate = []\n", "\n", "val_acc_all = [ [] for _ in range(skf.n_splits) ]\n", "val_roc_all = [ [] for _ in range(skf.n_splits) ]\n", "for fold, (train_idx, val_idx) in enumerate(skf.split(X=np.zeros(len(train_df2)), y=train_df2['target'], groups=train_df2['patient_id'].tolist()), 1):\n", " print('=' * 20, 'Fold', fold, '=' * 20) \n", " \n", " model_path = f'model_{fold}.pth' # Path and filename to save model to\n", " best_val = 0 # Best validation score within this fold (for val_roc)\n", " # best_val = 1000 # Best validation score within this fold (for val_loss)\n", " patience = es_patience # Current patience counter\n", " arch = EfficientNet.from_pretrained('efficientnet-b1')\n", " model = Net(arch=arch, n_meta_features=len(meta_features)) # New model for each fold\n", " model = model.to(device)\n", " \n", " optim = torch.optim.Adam(model.parameters(), lr=0.001)\n", " scheduler = ReduceLROnPlateau(optimizer=optim, mode='max', patience=1, verbose=True, factor=0.2) # for val_roc\n", " # scheduler = ReduceLROnPlateau(optimizer=optim, mode='min', patience=1, verbose=True, factor=0.2) # for val_loss\n", " criterion = nn.BCEWithLogitsLoss()\n", " \n", " if WEIGHTED_SAMPLER:\n", " sampler, samples_weight_py = get_sampler_for_imbalanced_classification(train_df2.iloc[train_idx].reset_index(drop=True))\n", "\n", " train = MelanomaDataset(df=train_df2.iloc[train_idx].reset_index(drop=True), \n", " # imfolder='/kaggle/input/melanoma-external-malignant-256/train/train/', \n", " imfolder='/kaggle/input/jpeg-melanoma-256x256/train/', \n", " train=True, \n", " transforms=train_transform,\n", " meta_features=meta_features)\n", " val = MelanomaDataset(df=train_df2.iloc[val_idx].reset_index(drop=True), \n", " # imfolder='/kaggle/input/melanoma-external-malignant-256/train/train/', \n", " imfolder='/kaggle/input/jpeg-melanoma-256x256/train/', \n", " train=True, \n", " transforms=test_transform,\n", " meta_features=meta_features)\n", " \n", " if WEIGHTED_SAMPLER:\n", " train_loader = DataLoader(dataset=train, batch_size=BATCH_SIZE_TRAIN, num_workers=2, sampler=sampler)\n", " else:\n", " train_loader = DataLoader(dataset=train, batch_size=BATCH_SIZE_TRAIN, shuffle=True, num_workers=2)\n", " val_loader = DataLoader(dataset=val, batch_size=BATCH_SIZE_VAL_TEST, shuffle=False, num_workers=2)\n", " test_loader = DataLoader(dataset=test, batch_size=BATCH_SIZE_VAL_TEST, shuffle=False, num_workers=2)\n", " \n", " for epoch in range(epochs):\n", " start_time = time.time()\n", " correct = 0\n", " epoch_loss = 0\n", " epoch_loss_val = 0\n", " model.train()\n", " \n", " for x, y in train_loader:\n", " x[0] = torch.tensor(x[0], device=device, dtype=torch.float32)\n", " x[1] = torch.tensor(x[1], device=device, dtype=torch.float32)\n", " y = torch.tensor(y, device=device, dtype=torch.float32)\n", " optim.zero_grad()\n", " z = model(x)\n", " loss = criterion(z, y.unsqueeze(1))\n", " loss.backward()\n", " optim.step()\n", " # pred_proba_train = torch.sigmoid(z) # added by OMM\n", " pred = torch.round(torch.sigmoid(z)) # round off sigmoid to obtain predictions\n", " correct += (pred.cpu() == y.cpu().unsqueeze(1)).sum().item() # tracking number of correctly predicted samples\n", " epoch_loss += loss.item()\n", " train_acc = correct / len(train_idx)\n", " \n", " model.eval() # switch model to the evaluation mode\n", " val_preds = torch.zeros((len(val_idx), 1), dtype=torch.float32, device=device)\n", " with torch.no_grad(): # Do not calculate gradient since we are only predicting\n", " # Predicting on validation set\n", " for j, (x_val, y_val) in enumerate(val_loader):\n", " x_val[0] = torch.tensor(x_val[0], device=device, dtype=torch.float32)\n", " x_val[1] = torch.tensor(x_val[1], device=device, dtype=torch.float32)\n", " y_val = torch.tensor(y_val, device=device, dtype=torch.float32)\n", " z_val = model(x_val)\n", " loss_val = criterion(z_val, y_val.unsqueeze(1))\n", " val_pred = torch.sigmoid(z_val)\n", " \n", " val_preds[jval_loader.batch_size:jval_loader.batch_size + x_val[0].shape[0]] = val_pred\n", " epoch_loss_val += loss_val.item()\n", " val_acc = accuracy_score(train_df2.iloc[val_idx]['target'].values, torch.round(val_preds.cpu()))\n", " val_roc = roc_auc_score(train_df2.iloc[val_idx]['target'].values, val_preds.cpu())\n", " val_precision = precision_score(train_df2.iloc[val_idx]['target'].values, torch.round(val_preds.cpu()))\n", " val_recall = recall_score(train_df2.iloc[val_idx]['target'].values, torch.round(val_preds.cpu()))\n", " \n", " val_acc_all[fold-1].append(val_acc)\n", " val_roc_all[fold-1].append(val_roc)\n", " val_precision_all[fold-1].append(val_precision)\n", " val_recall_all[fold-1].append(val_recall)\n", " \n", " epoch_loss_all[fold-1].append(epoch_loss)\n", " epoch_loss_val_all[fold-1].append(epoch_loss_val)\n", " \n", " print('Epoch {:03}: \| Loss: {:.3f} \| Train acc: {:.3f} \| Val acc: {:.3f} \| Val roc_auc: {:.3f} \| Training time: {}'.format(\n", " epoch + 1, epoch_loss, train_acc, val_acc, val_roc, str(datetime.timedelta(seconds=time.time() - start_time))[:7]))\n", " \n", " # scheduler.step(val_roc)\n", " scheduler.step(epoch_loss_val)\n", " \n", " if val_roc >= best_val: #val_roc >= best_val epoch_loss_val <= best_val\n", " best_val = val_roc # best_val = val_roc best_val = epoch_loss_val\n", " patience = es_patience # Resetting patience since we have new best validation accuracy\n", " torch.save(model, model_path) # Saving current best model\n", " else:\n", " patience -= 1\n", " if patience == 0:\n", " print('Early stopping. Best Val roc_auc: {:.3f}'.format(best_val))\n", " break\n", " \n", "# assert(1==2) # continue in this block\n", " # save model after epoch iterations\n", "# model_last_epoch_path = f'model_last_epoch_{fold}.pth'\n", "# torch.save(model, model_last_epoch_path)\n", " \n", " # TRANINIG FINISHED (FOR THIS FOLD)\n", " model = torch.load(model_path) # Loading best model of this fold\n", " model.eval() # switch model to the evaluation mode\n", " val_preds = torch.zeros((len(val_idx), 1), dtype=torch.float32, device=device)\n", " test_preds = torch.zeros((len(test), 1), dtype=torch.float32, device=device)\n", " with torch.no_grad():\n", " # Predicting on validation set once again to obtain data for OOF\n", " for j, (x_val, y_val) in enumerate(val_loader):\n", " x_val[0] = torch.tensor(x_val[0], device=device, dtype=torch.float32)\n", " x_val[1] = torch.tensor(x_val[1], device=device, dtype=torch.float32)\n", " y_val = torch.tensor(y_val, device=device, dtype=torch.float32)\n", " z_val = model(x_val)\n", " val_pred = torch.sigmoid(z_val)\n", " val_preds[jval_loader.batch_size:jval_loader.batch_size + x_val[0].shape[0]] = val_pred\n", " oof[val_idx] = val_preds.cpu().numpy()\n", " \n", " # Predicting on test set\n", " \n", " # Not using TTA (new block) \n", " for i, x_test in tqdm(enumerate(test_loader), desc='test set', total = len(test_df)//BATCH_SIZE_VAL_TEST + 1):\n", " x_test[0] = torch.tensor(x_test[0], device=device, dtype=torch.float32)\n", " x_test[1] = torch.tensor(x_test[1], device=device, dtype=torch.float32)\n", " z_test = model(x_test)\n", " z_test = torch.sigmoid(z_test)\n", " test_preds[itest_loader.batch_size:itest_loader.batch_size + x_test[0].shape[0]] += z_test\n", " \n", " # preds = test_preds # XX WARNING use this for working with one fold\n", " preds += test_preds # use this for working with one 5fold\n", " preds_separate.append(test_preds)\n", " # TTA predictions\n", " # tta_preds = torch.zeros((len(test), 1), dtype=torch.float32, device=device)\n", " # for _ in range(TTA):\n", " # for i, x_test in tqdm(enumerate(test_loader), desc='test'):\n", " # x_test[0] = torch.tensor(x_test[0], device=device, dtype=torch.float32)\n", " # x_test[1] = torch.tensor(x_test[1], device=device, dtype=torch.float32)\n", " # z_test = model(x_test)\n", " # z_test = torch.sigmoid(z_test)\n", " # tta_preds[itest_loader.batch_size:itest_loader.batch_size + x_test[0].shape[0]] += z_test\n", " # preds += tta_preds / TTA\n", "\n", " \n", "preds /= skf.n_splits\n", "stop = time.time()\n", "print(f'epochs {epochs}: {(stop - start)/60:.3f} mins (in {device})')" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "outputs": [], "source": [ "prediction_separate = [i.detach().cpu().numpy() for i in preds_separate]\n", "plt.figure(figsize=(15,3))\n", "plt.plot(prediction_separate[0])" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "outputs": [], "source": [ "for i in epoch_loss_val_all:\n", " plt.plot(i)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "outputs": [], "source": [ "for i in epoch_loss_all:\n", " plt.plot(i)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "outputs": [], "source": [ "for i in epoch_loss_all:\n", " plt.plot(i)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "outputs": [], "source": [ "!mkdir /kaggle/working/classification_results" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "outputs": [], "source": [ "# val_acc_all, val_roc_all, val_precision_all, val_recall_all\n", "df_val_acc_all = pd.DataFrame(val_acc_all).T\n", "df_val_roc_all = pd.DataFrame(val_roc_all).T\n", "df_val_precision_all = pd.DataFrame(val_precision_all).T\n", "df_val_recall_all = pd.DataFrame(val_recall_all).T" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "outputs": [], "source": [ "path_class_results = '/kaggle/working/classification_results/'\n", "np.save(f'{path_class_results}prediction_separate.npy',prediction_separate)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "outputs": [], "source": [ "FileLink(f'{path_class_results}prediction_separate.npy')" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "outputs": [], "source": [ "# save results to folder\n", "path_class_results = '/kaggle/working/classification_results/'\n", "np.save(f'{path_class_results}epoch_loss_all.npy',epoch_loss_all)\n", "np.save(f'{path_class_results}oof.npy',oof)\n", "train_df.to_csv(f'{path_class_results}train_df.csv')\n", "test_df.to_csv(f'{path_class_results}test_df.csv')\n", "np.save(f'{path_class_results}preds.npy',preds.detach().cpu().numpy())\n", "df_val_acc_all.to_csv(f'{path_class_results}df_val_acc_all.csv')\n", "df_val_roc_all.to_csv(f'{path_class_results}df_val_roc_all.csv')\n", "df_val_precision_all.to_csv(f'{path_class_results}df_val_precision_all.csv')\n", "df_val_recall_all.to_csv(f'{path_class_results}df_val_recall_all.csv')\n", "np.save(f'{path_class_results}WEIGHTED_SAMPLER.npy',WEIGHTED_SAMPLER)\n", "np.save(f'{path_class_results}epoch.npy',[epoch])" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "outputs": [], "source": [ "!zip -qr classification_results.zip /kaggle/working/classification_results/" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "outputs": [], "source": [ "FileLink('classification_results.zip')" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "outputs": [], "source": [ "path_source = '/kaggle/working/classification_results/'\n", "# read files\n", "df_val_acc_all = pd.read_csv(f'{path_source}df_val_acc_all.csv')\n", "df_val_precision_all = pd.read_csv(f'{path_source}df_val_precision_all.csv')\n", "df_val_recall_all = pd.read_csv(f'{path_source}df_val_recall_all.csv')\n", "df_val_roc_all = pd.read_csv(f'{path_source}df_val_roc_all.csv')\n", "epoch_loss_all = np.load(f'{path_source}epoch_loss_all.npy', allow_pickle=True)\n", "oof = np.load(f'{path_source}oof.npy')\n", "preds = np.load(f'{path_source}preds.npy')\n", "WEIGHTED_SAMPLER = np.load(f'{path_source}WEIGHTED_SAMPLER.npy')\n", "epoch = np.load(f'{path_source}epoch.npy', allow_pickle=True)\n", "# transform dataframes into list of lists\n", "val_acc_all = df_val_acc_all.T.values.tolist()\n", "val_precision_all = df_val_precision_all.T.values.tolist()\n", "val_recall_all = df_val_recall_all.T.values.tolist()\n", "val_roc_all = df_val_roc_all.T.values.tolist()" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "outputs": [], "source": [ "epoch[0]" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "outputs": [], "source": [ "# continue training\n", "WEIGHTED_SAMPLER = True\n", "epochs = 1 # orig 12 \n", "BATCH_SIZE_TRAIN = 64 # orig 64\n", "BATCH_SIZE_VAL_TEST = 16\n", "es_patience = 3 # Early Stopping patience - for how many epochs with no improvements to wait\n", "# TTA = 3 # Test Time Augmentation rounds\n", "start = time.time()\n", "skf = KFold(n_splits=5, shuffle=True, random_state=47)\n", "\n", "# val_acc_all = [ [] for _ in range(skf.n_splits) ]\n", "# val_roc_all = [ [] for _ in range(skf.n_splits) ]\n", "# val_precision_all = [ [] for _ in range(skf.n_splits) ]\n", "# val_recall_all = [ [] for _ in range(skf.n_splits) ]\n", "# epoch_loss_all = [ [] for _ in range(skf.n_splits) ]\n", "\n", "oof = np.zeros((len(train_df2), 1)) # Out Of Fold predictions\n", "oof_all = np.zeros((len(train_df2), skf.n_splits)) # Out Of Fold predictions OC\n", "preds = torch.zeros((len(test), 1), dtype=torch.float32, device=device) # Predictions for test test\n", "\n", "val_acc_all = [ [] for _ in range(skf.n_splits) ]\n", "val_roc_all = [ [] for _ in range(skf.n_splits) ]\n", "for fold, (train_idx, val_idx) in enumerate(skf.split(X=np.zeros(len(train_df2)), y=train_df2['target'], groups=train_df2['patient_id'].tolist()), 1):\n", " print('=' * 20, 'Fold', fold, '=' * 20) \n", " \n", " model_path = f'model_{fold}.pth' # Path and filename to save model to\n", " best_val = 0 # Best validation score within this fold\n", " patience = es_patience # Current patience counter\n", " arch = EfficientNet.from_pretrained('efficientnet-b1')\n", " model = Net(arch=arch, n_meta_features=len(meta_features)) # New model for each fold\n", " model = model.to(device)\n", " \n", " optim = torch.optim.Adam(model.parameters(), lr=0.001)\n", " scheduler = ReduceLROnPlateau(optimizer=optim, mode='max', patience=1, verbose=True, factor=0.2)\n", " criterion = nn.BCEWithLogitsLoss()\n", " \n", " if WEIGHTED_SAMPLER:\n", "# train_df2 = \n", " sampler, samples_weight_py = get_sampler_for_imbalanced_classification(train_df2.iloc[train_idx].reset_index(drop=True))\n", "# else: train_df2 = \n", " train = MelanomaDataset(df=train_df2.iloc[train_idx].reset_index(drop=True), \n", " # imfolder='/kaggle/input/melanoma-external-malignant-256/train/train/', \n", " imfolder='/kaggle/input/jpeg-melanoma-256x256/train/', \n", " train=True, \n", " transforms=train_transform,\n", " meta_features=meta_features)\n", " val = MelanomaDataset(df=train_df2.iloc[val_idx].reset_index(drop=True), \n", " # imfolder='/kaggle/input/melanoma-external-malignant-256/train/train/', \n", " imfolder='/kaggle/input/jpeg-melanoma-256x256/train/', \n", " train=True, \n", " transforms=test_transform,\n", " meta_features=meta_features)\n", " \n", " if WEIGHTED_SAMPLER:\n", " train_loader = DataLoader(dataset=train, batch_size=BATCH_SIZE_TRAIN, num_workers=2, sampler=sampler)\n", " else:\n", " train_loader = DataLoader(dataset=train, batch_size=BATCH_SIZE_TRAIN, shuffle=True, num_workers=2)\n", " val_loader = DataLoader(dataset=val, batch_size=BATCH_SIZE_VAL_TEST, shuffle=False, num_workers=2)\n", " test_loader = DataLoader(dataset=test, batch_size=BATCH_SIZE_VAL_TEST, shuffle=False, num_workers=2)\n", " \n", " for epoch in range(epochs):\n", " start_time = time.time()\n", " correct = 0\n", " epoch_loss = 0\n", " model.train()\n", " \n", " for x, y in train_loader:\n", " x[0] = torch.tensor(x[0], device=device, dtype=torch.float32)\n", " x[1] = torch.tensor(x[1], device=device, dtype=torch.float32)\n", " y = torch.tensor(y, device=device, dtype=torch.float32)\n", " optim.zero_grad()\n", " z = model(x)\n", " loss = criterion(z, y.unsqueeze(1))\n", " loss.backward()\n", " optim.step()\n", " # pred_proba_train = torch.sigmoid(z) # added by OMM\n", " pred = torch.round(torch.sigmoid(z)) # round off sigmoid to obtain predictions\n", " correct += (pred.cpu() == y.cpu().unsqueeze(1)).sum().item() # tracking number of correctly predicted samples\n", " epoch_loss += loss.item()\n", " train_acc = correct / len(train_idx)\n", " \n", " model.eval() # switch model to the evaluation mode\n", " val_preds = torch.zeros((len(val_idx), 1), dtype=torch.float32, device=device)\n", " with torch.no_grad(): # Do not calculate gradient since we are only predicting\n", " # Predicting on validation set\n", " for j, (x_val, y_val) in enumerate(val_loader):\n", " x_val[0] = torch.tensor(x_val[0], device=device, dtype=torch.float32)\n", " x_val[1] = torch.tensor(x_val[1], device=device, dtype=torch.float32)\n", " y_val = torch.tensor(y_val, device=device, dtype=torch.float32)\n", " z_val = model(x_val)\n", " val_pred = torch.sigmoid(z_val)\n", " val_preds[jval_loader.batch_size:jval_loader.batch_size + x_val[0].shape[0]] = val_pred\n", " val_acc = accuracy_score(train_df2.iloc[val_idx]['target'].values, torch.round(val_preds.cpu()))\n", " val_roc = roc_auc_score(train_df2.iloc[val_idx]['target'].values, val_preds.cpu())\n", " val_precision = precision_score(train_df2.iloc[val_idx]['target'].values, torch.round(val_preds.cpu()))\n", " val_recall = recall_score(train_df2.iloc[val_idx]['target'].values, torch.round(val_preds.cpu()))\n", " \n", " val_acc_all[fold-1].append(val_acc)\n", " val_roc_all[fold-1].append(val_roc)\n", " val_precision_all[fold-1].append(val_precision)\n", " val_recall_all[fold-1].append(val_recall)\n", " \n", " epoch_loss_all[fold-1].append(epoch_loss)\n", " \n", " print('Epoch {:03}: \| Loss: {:.3f} \| Train acc: {:.3f} \| Val acc: {:.3f} \| Val roc_auc: {:.3f} \| Training time: {}'.format(\n", " epoch + 1, epoch_loss, train_acc, val_acc, val_roc, str(datetime.timedelta(seconds=time.time() - start_time))[:7]))\n", " \n", " scheduler.step(val_roc)\n", " \n", " if val_roc >= best_val:\n", " best_val = val_roc\n", " patience = es_patience # Resetting patience since we have new best validation accuracy\n", " torch.save(model, model_path) # Saving current best model\n", " else:\n", " patience -= 1\n", " if patience == 0:\n", " print('Early stopping. Best Val roc_auc: {:.3f}'.format(best_val))\n", " break\n", " \n", "# assert(1==2) # continue in this block\n", " # save model after epoch iterations\n", " model_last_epoch_path = f'model_last_epoch_{fold}.pth'\n", " torch.save(model, model_last_epoch_path)\n", " \n", " # TRANINIG FINISHED (FOR THIS FOLD)\n", " model = torch.load(model_path) # Loading best model of this fold\n", " model.eval() # switch model to the evaluation mode\n", " val_preds = torch.zeros((len(val_idx), 1), dtype=torch.float32, device=device)\n", " test_preds = torch.zeros((len(test), 1), dtype=torch.float32, device=device)\n", " with torch.no_grad():\n", " # Predicting on validation set once again to obtain data for OOF\n", " for j, (x_val, y_val) in enumerate(val_loader):\n", " x_val[0] = torch.tensor(x_val[0], device=device, dtype=torch.float32)\n", " x_val[1] = torch.tensor(x_val[1], device=device, dtype=torch.float32)\n", " y_val = torch.tensor(y_val, device=device, dtype=torch.float32)\n", " z_val = model(x_val)\n", " val_pred = torch.sigmoid(z_val)\n", " val_preds[jval_loader.batch_size:jval_loader.batch_size + x_val[0].shape[0]] = val_pred\n", " oof[val_idx] = val_preds.cpu().numpy()\n", " \n", " # Predicting on test set\n", " \n", " # Not using TTA (new block) \n", " for i, x_test in tqdm(enumerate(test_loader), desc='test set', total = len(test_df)//BATCH_SIZE_VAL_TEST + 1):\n", " x_test[0] = torch.tensor(x_test[0], device=device, dtype=torch.float32)\n", " x_test[1] = torch.tensor(x_test[1], device=device, dtype=torch.float32)\n", " z_test = model(x_test)\n", " z_test = torch.sigmoid(z_test)\n", " test_preds[itest_loader.batch_size:itest_loader.batch_size + x_test[0].shape[0]] += z_test\n", " \n", " # preds = test_preds # XX WARNING use this for working with one fold\n", " preds += test_preds # use this for working with one 5fold\n", " \n", " # TTA predictions\n", " # tta_preds = torch.zeros((len(test), 1), dtype=torch.float32, device=device)\n", " # for _ in range(TTA):\n", " # for i, x_test in tqdm(enumerate(test_loader), desc='test'):\n", " # x_test[0] = torch.tensor(x_test[0], device=device, dtype=torch.float32)\n", " # x_test[1] = torch.tensor(x_test[1], device=device, dtype=torch.float32)\n", " # z_test = model(x_test)\n", " # z_test = torch.sigmoid(z_test)\n", " # tta_preds[itest_loader.batch_size:itest_loader.batch_size + x_test[0].shape[0]] += z_test\n", " # preds += tta_preds / TTA\n", "\n", " \n", "preds /= skf.n_splits\n", "stop = time.time()\n", "print(f'epochs {epochs}: {(stop - start)/60:.3f} mins (in {device})')" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "outputs": [], "source": [ "predictions = preds.detach().cpu().numpy()\n", "predictions /=5\n", "fig, ax = plt.subplots(1,2, figsize=(12,3))\n", "ax[0].plot(oof[:,0])\n", "ax[0].set_title(f'oof val weighted={WEIGHTED_SAMPLER}')\n", "ax[0].plot(train_df['target'].values * np.max(oof[:,0]), c='y')\n", "ax[1].plot(predictions)\n", "ax[1].plot(test_df['target'].values * np.max(predictions), c='y')\n", "ax[1].set_title(f'test set weighted={WEIGHTED_SAMPLER}')" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "outputs": [], "source": [ "predictions = preds.detach().cpu().numpy()\n", "predictions /=5\n", "fig, ax = plt.subplots(1,2, figsize=(12,3))\n", "ax[0].plot(oof[:,0])\n", "ax[0].set_title(f'oof val weighted={WEIGHTED_SAMPLER}')\n", "ax[0].plot(train_df['target'].values * np.max(oof[:,0]), c='y')\n", "ax[1].plot(predictions)\n", "ax[1].plot(test_df['target'].values * np.max(predictions), c='y')\n", "ax[1].set_title(f'test set weighted={WEIGHTED_SAMPLER}')" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "outputs": [], "source": [ "oof_val_true = train_df2['target'].values # we collect the whole train_df from the 5 folds of val\n", "print('OOF_val ROC: {:.3f}'.format(roc_auc_score(oof_val_true, oof)))\n", "print('OOF_val accuracy: {:.3f}'.format(accuracy_score(oof_val_true, oof.round())))\n", "print('OOF_val precision: {:.5f}'.format(precision_score(oof_val_true, oof.round())))\n", "print('OOF_val recall: {:.5f}'.format(recall_score(oof_val_true, oof.round())))" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "outputs": [], "source": [ "oof_val_true = train_df2['target'].values # we collect the whole train_df from the 5 folds of val\n", "print('OOF_val ROC: {:.3f}'.format(roc_auc_score(oof_val_true, oof)))\n", "print('OOF_val accuracy: {:.3f}'.format(accuracy_score(oof_val_true, oof.round())))\n", "print('OOF_val precision: {:.5f}'.format(precision_score(oof_val_true, oof.round())))\n", "print('OOF_val recall: {:.5f}'.format(recall_score(oof_val_true, oof.round())))" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "outputs": [], "source": [ "test_true = test_df['target'].values\n", "print('test ROC: {:.3f}'.format(roc_auc_score(test_true, predictions)))\n", "print('test accuracy: {:.3f}'.format(accuracy_score(test_true, predictions.round())))\n", "print('test precision: {:.5f}'.format(precision_score(test_true, predictions.round())))\n", "print('test recall: {:.5f}'.format(recall_score(test_true, predictions.round())))" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "outputs": [], "source": [ "test_true = test_df['target'].values\n", "print('test ROC: {:.3f}'.format(roc_auc_score(test_true, predictions)))\n", "print('test accuracy: {:.3f}'.format(accuracy_score(test_true, predictions.round())))\n", "print('test precision: {:.5f}'.format(precision_score(test_true, predictions.round())))\n", "print('test recall: {:.5f}'.format(recall_score(test_true, predictions.round())))" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "outputs": [], "source": [ "fig, ax = plt.subplots(1,4,figsize=(16,4))\n", "plt.style.use('seaborn-white') # seaborn-white\n", "titles_metrics = ['acc', 'roc', 'precision', 'recall']\n", "for idx, metrics in enumerate([val_acc_all, val_roc_all, val_precision_all, val_recall_all]):\n", " for i in metrics:\n", " ax[idx].plot(i)\n", " ax[idx].set_title(titles_metrics[idx])\n", " if idx<3:\n", " ax[idx].set_ylim([.4, 1])\n", "plt.suptitle(f'val ROC epochs:{epochs} weighted={WEIGHTED_SAMPLER}', fontsize=18)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "outputs": [], "source": [ "fig, ax = plt.subplots(1,4,figsize=(16,4))\n", "plt.style.use('seaborn-white') # seaborn-white\n", "titles_metrics = ['acc', 'roc', 'precision', 'recall']\n", "for idx, metrics in enumerate([val_acc_all, val_roc_all, val_precision_all, val_recall_all]):\n", " for i in metrics:\n", " ax[idx].plot(i)\n", " ax[idx].set_title(titles_metrics[idx])\n", " if idx<3:\n", " ax[idx].set_ylim([.4, 1])\n", "plt.suptitle(f'val ROC epochs:{epochs} weighted={WEIGHTED_SAMPLER}', fontsize=18)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "outputs": [], "source": [ "fig, ax = plt.subplots(1,4,figsize=(16,4))\n", "plt.style.use('seaborn-white') # seaborn-white\n", "titles_metrics = ['acc', 'roc', 'precision', 'recall']\n", "for idx, metrics in enumerate([val_acc_all, val_roc_all, val_precision_all, val_recall_all]):\n", " for i in metrics:\n", " ax[idx].plot(i)\n", " ax[idx].set_title(titles_metrics[idx])\n", " if idx<3:\n", " ax[idx].set_ylim([.4, 1])\n", "plt.suptitle(f'val ROC epochs:{epochs} weighted={WEIGHTED_SAMPLER}', fontsize=18)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "outputs": [], "source": [ "sns.kdeplot(pd.Series(preds.cpu().numpy().reshape(-1,)));" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "outputs": [], "source": [ "plt.plot(tta_preds.detach().cpu().numpy())" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "outputs": [], "source": [ "# Saving OOF predictions so stacking would be easier\n", "pd.Series(oof.reshape(-1,)).to_csv('oof.csv', index=False)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "outputs": [], "source": [ "sub = pd.read_csv('/kaggle/input/siim-isic-melanoma-classification/sample_submission.csv')\n", "sub['target'] = preds.cpu().numpy().reshape(-1,)\n", "sub.to_csv('submission.csv', index=False)" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "source": [ "## Not used:" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "source": [ "# Extra" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "outputs": [], "source": [ "# ORIGINAL DATAFRAME\n", "# for fold, (train_idx, val_idx) in enumerate(skf.split(X=np.zeros(len(train_df)), y=train_df['target'], groups=train_df['patient_id'].tolist()), 1):\n", "# print(f'fold={fold}, train_idx={np.shape(train_idx)}, train_idx[0]={train_idx[0]}, val_idx={np.shape(val_idx)}, val_idx[0]={val_idx[0]}')\n", "# train_idx" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "outputs": [], "source": [ "# # SMALLER test dataloader\n", "# n_ints =50\n", "# rand_ints = np.random.randint(0,len(test_df),n_ints)\n", "# test = MelanomaDataset(df=test_df.iloc[rand_ints].reset_index(drop=True),\n", "# imfolder='/kaggle/input/jpeg-melanoma-256x256/test/', \n", "# train=False,\n", "# transforms=train_transform, # For TTA\n", "# meta_features=meta_features)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "outputs": [], "source": [ "def make_train_test_df_for_cea_aug2(train_df_orig, df_cea_done, test_set_size = 2000, test_set_1s = 100, add_0s_into_train_df=0, add_1s_into_train_df=0):\n", " '''make a train_df that contains all the files that cea==completed & target==1\n", " and a test_df that has all the files that cea!=completed & target==1\n", " Optionally you can include fewer files'''\n", " # make a train_df that contains all the files that cea==completed & target==1\n", " image_name_cea_done = df_cea_done['image_name'].values\n", " train_df = train_df_orig[train_df_orig['image_name'].isin(image_name_cea_done)]\n", " # make sure test_df has all the files that cea!=completed & target==1\n", " test_df_large = train_df_orig[~train_df_orig['image_name'].isin(image_name_cea_done)]\n", " # divide in target==1 & target == 0\n", " test_df_only1s = test_df_large[test_df_large['target']==1]\n", " test_df_only0s = test_df_large[test_df_large['target']==0]\n", " test_df_only0s = test_df_only0s.reset_index(drop=True)\n", " test_df_only1s = test_df_only1s.reset_index(drop=True)\n", " # if add_0s_into_train_df more samples are wanted in train_df (of zeros)\n", " if add_0s_into_train_df >0:\n", " random.seed(0)\n", " rand_ints = random.sample(range(len(test_df_only0s)-1), add_0s_into_train_df)\n", " extra_0s_for_train_df = test_df_only0s.iloc[rand_ints]\n", " train_df = train_df.append(extra_0s_for_train_df)\n", " test_df_only0s =test_df_only0s.drop(rand_ints, axis=0)\n", " # if add_1s_into_train_df more samples are wanted in train_df (of ones)\n", " if add_1s_into_train_df >0:\n", " random.seed(0)\n", " rand_ints = random.sample(range(len(test_df_only1s)-1), add_1s_into_train_df)\n", " extra_1s_for_train_df = test_df_only1s.iloc[rand_ints]\n", " train_df = train_df.append(extra_1s_for_train_df)\n", " test_df_only1s = test_df_only1s.drop(rand_ints, axis=0)\n", " # if only a subset of the target == 1 is wanted\n", " if test_set_1s > 0:\n", " random.seed(0)\n", " rand_ints = random.sample(range(len(test_df_only1s)), test_set_1s)\n", " test_df_only1s = test_df_only1s.iloc[rand_ints]\n", " \n", " # if add_1s_into_train_df > 0 or add_0s_into_train_df > 0\n", " if add_1s_into_train_df > 0 or add_0s_into_train_df > 0:\n", " test_df_large = pd.DataFrame()\n", " test_df_large = test_df_large.append(test_df_only1s)\n", " test_df_large = test_df_large.append(test_df_only0s)\n", " random.seed(0)\n", " rand_ints = random.sample(range(len(test_df_large)), len(test_df_large))\n", " test_df_large.index = rand_ints\n", " test_df_large = test_df_large.reindex()\n", " test_df = test_df_large\n", " else:\n", " # get a large subset of test_df_large that contain all target 1 from test_df_large\n", " test_df = test_df_large\n", " if test_set_size > 0:\n", " number1s_already_in_test = len(test_df_only1s)\n", " random.seed(0)\n", " rand_ints = random.sample(range(len(test_df_only0s)), test_set_size - number1s_already_in_test)\n", " test_df_only0s_subset = test_df_only0s.iloc[rand_ints]\n", " test_df = test_df_only1s.append(test_df_only0s_subset)\n", " return train_df.reset_index(drop=True), test_df.reset_index(drop=True)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "outputs": [], "source": [ "predictions = preds.detach().cpu().numpy()\n", "predictions /=5\n", "fig, ax = plt.subplots(1,2, figsize=(12,3))\n", "ax[0].plot(oof[:,0])\n", "ax[0].set_title(f'oof val weighted={WEIGHTED_SAMPLER}, ep={epochs}')\n", "ax[1].plot(predictions)\n", "ax[1].set_title(f'test set weighted={WEIGHTED_SAMPLER}, ep={epochs}')" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "outputs": [], "source": [ "predictions = preds.detach().cpu().numpy()\n", "predictions /=5\n", "fig, ax = plt.subplots(1,2, figsize=(12,3))\n", "ax[0].plot(oof[:,0])\n", "ax[0].set_title(f'oof val weighted={WEIGHTED_SAMPLER}')\n", "ax[1].plot(predictions)\n", "ax[1].set_title(f'test set weighted={WEIGHTED_SAMPLER}')" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "outputs": [], "source": [ "def make_train_test_df_for_cea_aug(train_df_orig, df_cea_done, samples_subset = 2000, samples_subset_tgt1 = 100):\n", " '''make a train_df that contains all the files that cea==completed & target==1\n", " and a test_df that has all the files that cea!=completed & target==1\n", " Optionally you can include fewer files'''\n", " # make a train_df that contains all the files that cea==completed & target==1\n", " image_name_cea_done = df_cea_done['image_name'].values\n", " train_df = train_df_orig[train_df_orig['image_name'].isin(image_name_cea_done)]\n", " # make sure test_df has all the files that cea!=completed & target==1\n", " test_df_large = train_df_orig[~train_df_orig['image_name'].isin(image_name_cea_done)]\n", " # divide in target==1 & target == 0\n", " test_df_only1s = test_df_large[test_df_large['target']==1]\n", " test_df_only0s = test_df_large[test_df_large['target']==0]\n", " test_df_only0s = test_df_only0s.reset_index(drop=True)\n", " test_df_only1s = test_df_only1s.reset_index(drop=True)\n", " # if only a subset of the target == 1 is wanted\n", " if samples_subset_tgt1 > 0:\n", " random.seed(0)\n", " rand_ints = random.sample(range(len(test_df_only1s)), samples_subset_tgt1)\n", " test_df_only1s = test_df_only1s.iloc[rand_ints]\n", " # get a large subset of test_df_large that contain all target 1 from test_df_large\n", " if samples_subset > 0:\n", " number1s_already_in_test = len(test_df_only1s)\n", " random.seed(0)\n", " rand_ints = random.sample(range(len(test_df_only0s)), samples_subset - number1s_already_in_test)\n", " test_df_only0s_subset = test_df_only0s.iloc[rand_ints]\n", " test_df = test_df_only1s.append(test_df_only0s_subset)\n", " return train_df.reset_index(drop=True), test_df.reset_index(drop=True)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "outputs": [], "source": [ "# # THIS IS NOT IS DONE IN make_train_test_df_for_cea_aug()\n", "# # make a train_df that contains all the files that cea==completed & target==1\n", "# image_name_cea_done = df_cea_done['image_name'].values\n", "# train_df = train_df_orig[train_df_orig['image_name'].isin(image_name_cea_done)]\n", "# # make sure test_df has all the files that cea!=completed & target==1\n", "# test_df_large = train_df_orig[~train_df_orig['image_name'].isin(image_name_cea_done)]\n", "# print(f'train_df_orig = {train_df_orig.shape}, train_df 1s = {np.sum(train_df_orig[\"target\"].values)}')\n", "# print(f'train_df = {train_df.shape}, train_df 1s = {np.sum(train_df[\"target\"].values)}')\n", "# print(f'test_df_large = {test_df_large.shape}, test_df_large 1s = {np.sum(test_df_large[\"target\"].values)}')\n", "# # divide in target==1 & target == 0\n", "# test_df_only1s = test_df_large[test_df_large['target']==1]\n", "# test_df_only0s = test_df_large[test_df_large['target']==0]\n", "# test_df_only0s = test_df_only0s.reset_index(drop=True)\n", "# test_df_only1s = test_df_only1s.reset_index(drop=True)\n", "# print(np.shape(test_df_only1s), np.shape(test_df_only0s))\n", "# # if only a subset of the target == 1 is wanted\n", "# n_ints = 100\n", "# if n_ints > 0:\n", "# random.seed(0)\n", "# rand_ints = random.sample(range(len(test_df_only1s)), n_ints)\n", "# test_df_only1s = test_df_only1s.iloc[rand_ints]\n", "# print(np.shape(test_df_only1s))\n", "# # get a large subset of test_df_large that contain all target 1 from test_df_large\n", "# number1s_already_in_test = len(test_df_only1s)\n", "# n_ints = 2000\n", "# random.seed(0)\n", "# rand_ints = random.sample(range(len(test_df_only0s)), n_ints - number1s_already_in_test)\n", "# test_df_only0s_subset = test_df_only0s.iloc[rand_ints]\n", "# print(np.shape(test_df_only0s_subset))\n", "# df_test = test_df_only1s.append(test_df_only0s_subset)\n", "# print(df_test.shape)\n", "# df_test.tail(5)" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "outputs": [], "source": [ "# # OC check a df with a subset\n", "# train_df2 = train_df[train_df['image_name'].isin(df_cea['image_name'].values)]\n", "# print(train_df2.shape)\n", "# train_df2 = train_df2[train_df2['age_approx'].notna()]\n", "# print(train_df2.shape)\n", "# train_df2.tail()\n", "# # OC add fake target 1s just to see if the code works\n", "# n_ints =20\n", "# rand_ints = np.random.randint(0,len(train_df2),n_ints)\n", "# for i in rand_ints:\n", "# train_df2['target'].iloc[i] = 1\n", "# print(np.sum(train_df2['target'].values==1)/len(train_df2), np.sum(train_df2['target'].values==1))\n", "# plt.figure(figsize=(3,2))\n", "# plt.hist(train_df2['target'].values);" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "outputs": [], "source": [ "# # OC just checking shapes\n", "# extra_image_path = os.path.join('/kaggle/input/melanoma-external-malignant-256/train/train', \n", "# train_df2.iloc[10]['image_name'] + '.jpg')\n", "# new_image_path = os.path.join('/kaggle/input/jpeg-melanoma-256x256/train', \n", "# train_df2.iloc[10]['image_name'] + '.jpg')\n", "# x1 = cv2.imread(extra_image_path)\n", "# x2 = cv2.imread(new_image_path)\n", "# fig, ax = plt.subplots(1,2)\n", "# ax[0].imshow(x)\n", "# ax[1].imshow(x)" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.4" }, "papermill": { "duration": null, "end_time": null, "environment_variables": {}, "exception": null, "input_path": "__notebook__.ipynb", "output_path": "__notebook__.ipynb", "parameters": {}, "start_time": "2021-02-27T00:46:58.797308", "version": "2.1.0" } }, "nbformat": 4, "nbformat_minor": 4 }	0055/329/55329828.ipynb	s3://data-agents/kaggle-outputs/sharded/012_00055.jsonl.gz
{ "cells": [ { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.056538, "end_time": "2021-02-27T01:00:55.086071", "exception": false, "start_time": "2021-02-27T01:00:55.029533", "status": "completed" }, "tags": [] }, "source": [ "# Classificação - Presença de Doença Cardíaca\n", "\n", "Este notebook realiza um estudo, um conjunto de experimentos, de algoritmos de classificação sobre o dataset [Heart Disease UCI](https://www.kaggle.com/ronitf/heart-disease-uci). Um conjunto de dados que reúne mais de 300 pacientes e 14 atributos, tais como idade, sexo, nível do colesterol, nível de açucar no sangue, entre outros. Nosso objetivo é distinguir a presença (valor 1) ou ausência (valor 0) de uma doença cardíaca.\n", "\n", "> Conteúdo voltado para iniciantes na área de Aprendizado de Máquina e Ciência de Dados!\n", "\n", "\n", "<a id=\"top\"></a>\n", "\n", "## Conteúdo\n", "\n", "> Nota. Alguns códigos foram ocultados a fim de facilitar a leitura e dar destaque para os conteúdos mais importantes.\n", "\n", "O notebook está organizado como segue:\n", "\n", "- [Dados](#data) - Carregamento dos dados, pré-processamento.\n", "- [Visualização](#visual) - Análise exploratória dos dados.\n", "- [Classificação](#class) - Aplicação de algoritmos de Aprendizado de Máquina.\n", " - [KNN](#knn) - Classificação com k-NN.\n", " - [Naive Bayes](#naive) - Classificação com Naive Bayes.\n", " - [Support Vector Machines](#svm) - Classificação com Support Vector Machines.\n", " - [Árvore de Decisão](#decision) - Classificação com Decision Tree.\n", " - [Random Forest](#forest) - Classificação com Random Forest.\n", " - [Bagging](#bagging) - Classificação com estratégia de Bagging.\n", " - [Ensemble](#ensemble) - Classificação com estratégia de Ensemble.\n", "- [Hyperparameter Tuning](#tuning) - Tuning de parâmetros." ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.053741, "end_time": "2021-02-27T01:00:55.194319", "exception": false, "start_time": "2021-02-27T01:00:55.140578", "status": "completed" }, "tags": [] }, "source": [ "<a id=\"data\"></a>\n", "\n", "-----\n", "\n", "# Dados\n", "\n", "- Carregamento dos dados.\n", "- Pré-processamento dos dados.\n", "\n", "[Voltar para o Topo](#top)" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.055781, "end_time": "2021-02-27T01:00:55.304242", "exception": false, "start_time": "2021-02-27T01:00:55.248461", "status": "completed" }, "tags": [] }, "source": [ "## Carregamento dos Dados" ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:00:55.419575Z", "iopub.status.busy": "2021-02-27T01:00:55.418879Z", "iopub.status.idle": "2021-02-27T01:00:55.421498Z", "shell.execute_reply": "2021-02-27T01:00:55.422066Z" }, "papermill": { "duration": 0.063499, "end_time": "2021-02-27T01:00:55.422390", "exception": false, "start_time": "2021-02-27T01:00:55.358891", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "# processamento de dados, algebra linear\n", "import numpy as np \n", "import pandas as pd" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19", "_kg_hide-input": true, "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5", "execution": { "iopub.execute_input": "2021-02-27T01:00:55.537932Z", "iopub.status.busy": "2021-02-27T01:00:55.537257Z", "iopub.status.idle": "2021-02-27T01:00:55.551881Z", "shell.execute_reply": "2021-02-27T01:00:55.550784Z" }, "papermill": { "duration": 0.074635, "end_time": "2021-02-27T01:00:55.552047", "exception": false, "start_time": "2021-02-27T01:00:55.477412", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "/kaggle/input/heart-disease-uci/heart.csv\n" ] } ], "source": [ "# imprime os arquvios\n", "import os\n", "\n", "for dirname, _, filenames in os.walk('/kaggle/input'):\n", " for filename in filenames:\n", " print(os.path.join(dirname, filename))" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:00:55.667455Z", "iopub.status.busy": "2021-02-27T01:00:55.666696Z", "iopub.status.idle": "2021-02-27T01:00:55.718361Z", "shell.execute_reply": "2021-02-27T01:00:55.717775Z" }, "papermill": { "duration": 0.111287, "end_time": "2021-02-27T01:00:55.718517", "exception": false, "start_time": "2021-02-27T01:00:55.607230", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>age</th>\n", " <th>sex</th>\n", " <th>cp</th>\n", " <th>trestbps</th>\n", " <th>chol</th>\n", " <th>fbs</th>\n", " <th>restecg</th>\n", " <th>thalach</th>\n", " <th>exang</th>\n", " <th>oldpeak</th>\n", " <th>slope</th>\n", " <th>ca</th>\n", " <th>thal</th>\n", " <th>target</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>51</th>\n", " <td>66</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>120</td>\n", " <td>302</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>151</td>\n", " <td>0</td>\n", " <td>0.4</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>2</td>\n", " <td>1</td>\n", " </tr>\n", " <tr>\n", " <th>230</th>\n", " <td>47</td>\n", " <td>1</td>\n", " <td>2</td>\n", " <td>108</td>\n", " <td>243</td>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>152</td>\n", " <td>0</td>\n", " <td>0.0</td>\n", " <td>2</td>\n", " <td>0</td>\n", " <td>2</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>231</th>\n", " <td>57</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>165</td>\n", " <td>289</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>124</td>\n", " <td>0</td>\n", " <td>1.0</td>\n", " <td>1</td>\n", " <td>3</td>\n", " <td>3</td>\n", " <td>0</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " age sex cp trestbps chol fbs restecg thalach exang oldpeak \\\n", "51 66 1 0 120 302 0 0 151 0 0.4 \n", "230 47 1 2 108 243 0 1 152 0 0.0 \n", "231 57 1 0 165 289 1 0 124 0 1.0 \n", "\n", " slope ca thal target \n", "51 1 0 2 1 \n", "230 2 0 2 0 \n", "231 1 3 3 0 " ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df = pd.read_csv('/kaggle/input/heart-disease-uci/heart.csv')\n", "df.sample(3)" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.057409, "end_time": "2021-02-27T01:00:55.835019", "exception": false, "start_time": "2021-02-27T01:00:55.777610", "status": "completed" }, "tags": [] }, "source": [ "## Pré-Processamento dos Dados\n", "\n", "Vamos normalizar os dados entre valor 0 e 1, utilizando o transformador `MinMaxScaler`. \n", "Este transformador normaliza os valores por coluna, utilizando o valor máximo e mínimo para normalizar o valor real.\n", "\n", "> Este procedimento é necessário, pois alguns algoritmos de classificação se beneficiam de valores normalizados, tal como o K-NN." ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:00:55.955383Z", "iopub.status.busy": "2021-02-27T01:00:55.954687Z", "iopub.status.idle": "2021-02-27T01:00:56.954917Z", "shell.execute_reply": "2021-02-27T01:00:56.955416Z" }, "papermill": { "duration": 1.06266, "end_time": "2021-02-27T01:00:56.955616", "exception": false, "start_time": "2021-02-27T01:00:55.892956", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "# normalizador\n", "from sklearn import preprocessing" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.055252, "end_time": "2021-02-27T01:00:57.067403", "exception": false, "start_time": "2021-02-27T01:00:57.012151", "status": "completed" }, "tags": [] }, "source": [ "Segmenta os dados e as classes." ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:00:57.182005Z", "iopub.status.busy": "2021-02-27T01:00:57.181352Z", "iopub.status.idle": "2021-02-27T01:00:57.186657Z", "shell.execute_reply": "2021-02-27T01:00:57.187193Z" }, "papermill": { "duration": 0.064194, "end_time": "2021-02-27T01:00:57.187357", "exception": false, "start_time": "2021-02-27T01:00:57.123163", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "# recupera os valores (X), e as classes (Y)\n", "X = df.drop('target', axis=1)\n", "Y = df['target']" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.055309, "end_time": "2021-02-27T01:00:57.298230", "exception": false, "start_time": "2021-02-27T01:00:57.242921", "status": "completed" }, "tags": [] }, "source": [ "### Normalização dos Dados\n", "\n", "Nesta seção vamos utilizar a normalização [MinMaxScaler](https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.MinMaxScaler.html?highlight=minmaxscaler#sklearn.preprocessing.MinMaxScaler). Esta função de preprocessamento normaliza os dados conforme segue:\n", "\n", "$$x_{new} = x_{\\sigma} * (x_{max} - x_{min}) + x_{min}{}$$\n", "\n", "Em que:\n", "\n", "$$x_{\\sigma} = \\frac{(x - x_{min})}{(x_{max} - x_{min})}$$\n", "\n", "\n", "A grosso modo, normaliza os dados entre 0 e 1 e mantem sua distribuição original." ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:00:57.412914Z", "iopub.status.busy": "2021-02-27T01:00:57.412267Z", "iopub.status.idle": "2021-02-27T01:00:57.420185Z", "shell.execute_reply": "2021-02-27T01:00:57.420646Z" }, "papermill": { "duration": 0.066868, "end_time": "2021-02-27T01:00:57.420844", "exception": false, "start_time": "2021-02-27T01:00:57.353976", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "min_max_scaler = preprocessing.MinMaxScaler()\n", "X = min_max_scaler.fit_transform(X)" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.055496, "end_time": "2021-02-27T01:00:57.532525", "exception": false, "start_time": "2021-02-27T01:00:57.477029", "status": "completed" }, "tags": [] }, "source": [ "<a id=\"visual\"></a>\n", "\n", "-----\n", "\n", "# Visualização\n", "\n", "Nesta seção será realizado a transformação dos 13 atributos / dimensões (removendo-se a classe) para 2 dimensões utilizando um algortimos de redução de dimensionadade, chamado de [PCA - Principal Component Analysis](https://en.wikipedia.org/wiki/Principal_component_analysis). \n", "\n", "> Faremos este procedimento a fim de visualizar os dados em 2 dimensões.\n", "\n", "[Voltar para o Topo](#top)" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:00:57.647540Z", "iopub.status.busy": "2021-02-27T01:00:57.646917Z", "iopub.status.idle": "2021-02-27T01:00:58.015271Z", "shell.execute_reply": "2021-02-27T01:00:58.015775Z" }, "papermill": { "duration": 0.427653, "end_time": "2021-02-27T01:00:58.015959", "exception": false, "start_time": "2021-02-27T01:00:57.588306", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "# visualização de dados\n", "import seaborn as sns\n", "import matplotlib.pyplot as plt\n", "\n", "# redutor de dimensionalidade\n", "from sklearn.decomposition import PCA" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:00:58.131863Z", "iopub.status.busy": "2021-02-27T01:00:58.131072Z", "iopub.status.idle": "2021-02-27T01:00:58.155345Z", "shell.execute_reply": "2021-02-27T01:00:58.154774Z" }, "papermill": { "duration": 0.083335, "end_time": "2021-02-27T01:00:58.155500", "exception": false, "start_time": "2021-02-27T01:00:58.072165", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "# redução da dimensionalidade\n", "pca = PCA(n_components=2).fit(X)\n", "X_reduced = pca.fit_transform(X)\n", "\n", "# registrando os valores num novo DataFrame\n", "df_2d = pd.DataFrame(X_reduced)\n", "df_2d.columns = ['0', '1']" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.055525, "end_time": "2021-02-27T01:00:58.266725", "exception": false, "start_time": "2021-02-27T01:00:58.211200", "status": "completed" }, "tags": [] }, "source": [ "Visualização dos Dados transformados em duas dimensões.\n", "\n", "> Note. Os dados transformados não representam a realidade, ou seja, eles não são linearmente divididos como demonstrado visualmente. Contudo, indica que é possível realizar uma divisão nos dados." ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:00:58.382616Z", "iopub.status.busy": "2021-02-27T01:00:58.381598Z", "iopub.status.idle": "2021-02-27T01:00:58.651837Z", "shell.execute_reply": "2021-02-27T01:00:58.652475Z" }, "papermill": { "duration": 0.330088, "end_time": "2021-02-27T01:00:58.652648", "exception": false, "start_time": "2021-02-27T01:00:58.322560", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sns.scatterplot(data=df_2d, x='0', y='1')\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.064695, "end_time": "2021-02-27T01:00:58.777048", "exception": false, "start_time": "2021-02-27T01:00:58.712353", "status": "completed" }, "tags": [] }, "source": [ "Visualizando os dados transformados, colorindo pela classe." ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:00:58.917668Z", "iopub.status.busy": "2021-02-27T01:00:58.916979Z", "iopub.status.idle": "2021-02-27T01:00:59.209864Z", "shell.execute_reply": "2021-02-27T01:00:59.210471Z" }, "papermill": { "duration": 0.374968, "end_time": "2021-02-27T01:00:59.210656", "exception": false, "start_time": "2021-02-27T01:00:58.835688", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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p7635cGiN+XlycFP6rfl9XbI2+nIiYXvrCLddb9i4BPiuVfPVFK11tlIqDPhcKbVHa72yzQ21XggsBBg3blxH9xfihFXWOtibW05uWQ2xgV4khfng0RMry5Zmmu1rA2Jh0j3w6W/MVrPT7gfvkO5/PtE3HNXmB8B6Ygsp9pS+DCCZQGyzxzFAdgfnzqdV85XWOtv1b55S6gNMk1ibACLEEfnlNWzOKCElt4LkcF9GxwUQ4uPRLfeurnPw4uqDPPm5WQ1XKXhi3giuGBNzwnsutOHmAf4xsG4hbHkT6irggj+aNbHEqe+qV03Nw9FsRV43G1z9Wt+VqQN92YS1HkhSSiUopdwxQWJp65OUUv7ANGBJszxvpZTvkTQwE9jRK6UWp6TKGgePL9/Lglc38sSKvdz+6gb++UUKVXWObrn//ryKxuABoDX87sOdpBVWdsv9W/AJhck/BXdvEzyC+sOIq7u+97k4ubzzY3DWt8xz1sPbN/RNeY6izwKI1toB3AOsAHYD72itdyql7lRK3dns1MuAz7TWzf8nhgOrlVJbgXXAJ1rr7htaIE47+wsqeHdjZou81384xMH8LnzAl+e2SRdWtu3grK53UlpV3yb/hJVmmmarukoITICiA7Dqb2YbW3H6sNrNysnd2Hx1zTXXMGnSJPbu3UtMTAwvvvjiCd2vTxdT1FovA5a1yvtPq8cvAy+3yjsAjOzh4onTSE2rLUKPaL116DGlrYYvHoHLF0JZlklf9h9iA8PxtFmoqW9oPDXCz5PIE9wEqF1uHuAfa5qtRlwFK/9mmrSkCev0cM2ipg7zq141NZIj+Sforbe6dyCrrMYrzgj9gr2JDbKTUdTUrpwY6k2/YO/jv4mzHiryIGs9vHwxVBWAhw/UV9E/3JuFN4zj1+9uJa+8loQQL568ahThfp7d/8v4hML0+8HqaZqtmqfFqc/qDjcsbnrcPH2SkQAiTk6OerDa2qa7KNzPk+dvGMdz36byfWohZyeFcOe0REJ8O/Gt3c0Ggy+GKb+A1U+avBs+hIjhKOCc5FCW3jOFkqp6Qn09CO6mDvp2eYe2nxaiF0kAESefooOwdRGMvQkcNa70jWbHvU6qqXeSmldBQUUt0YF2Hrt8OBW1TvztVtytXRhim7EO1v7bfON31pq+iCtfhuBEACL87UT4n5xDLkXf0lp3/4i8bqZ152Y6SAARPavoIPhGQIMDitMhuL9JV5dCQEzb87U2W69++yjkbofSbMjZDP2mdDqAVNc5eO2HQ/z10z1oDR5WC/++fgznDQrv2u9ypAnLwxeufx/yU2D5/VBf1bX7iTOGp6cnhYWFBAcHn7RBRGtNYWEhnp7H3+yqOhtxTmXjxo3TGzbIuou9Jm+3WYLhwr9C0X7Y/wWc/3vzLf7gSrjkn2YCXGs1pbDy77DmKfP44qdg5DVg61yT0LbMEuY8812LvCBvdz7+6VSiutq57agznedBCa50phlGK8RR1NfXk5mZSU1NTV8X5ag8PT2JiYnBZmvZZKyU2tjemoNSAxE9x2aHwH7wwzMQOxHSv4e3r4OqIkie1Xas+xFVRZC2qunxwW8heSbYjl0DySur4dt9+XywOYuLhkW0OV5UWUdRZV3XA4jV3QSPxrQED3FsNpuNhISEvi5Gt5P9QET3yt0JebtMuq4SZvwf5GwBNESPNcFBWeDcB2HDy1DRag2nI01Y2Ztg7rMw/UHYuRgK9rc4raKmnryyGpwNTTVoZ4PmpTVp3PfeNtakFlJSVY+lVWtBlL8nYX4y3FWI7iA1ENF9SjLgTdf49bnPwAd3mFrI7L9B/j7I2gg+4VCRazqfY8+CqnwzLPUIpWDoXIgYBmFDwVkDSTNNGtNOuy6tiMc/3cuBggquGBPDDZPiiQ/2JrO4ihdXHWy81Yebs/j5jGT+820qVXVOQn09eGr+aMJ8e2BorRBnIAkgovv4RcPFT5pJUK/OATd3mPUYeAaDXyT0nw7n3Af7PjM1jMFzIGxI2/t4+kP0GJO2eTSlgT2Hy7nhhXXUOc2EvRdWH6Skup4/X2Y2yGneP3mgoJJF69JZeMNYvD2sRPh7EikjpIToNtKEJbqPxWJGStm8zGN3bwhJhu1vQ8I0mP4QLLkHMtdC8AAzPLd1E9Yx7M+raAweRyzelMnh0hpiAr24+9xE/Dybvhc5tSYu2JvRcYESPIToZlIDEd3nSBOWowbOvg/W/BOW/tTUQvYsg9J0qC2Fef8zq8jufB/G39qyCesYvNzbzt3wt9uw29zYnVOGh9WNW6cmEOHvSWlVHdMGhhEX5NWNv6QQ4ggJIKL7HGnCctbB2v/CJU9DXZUJIuWHYe5zMPFOiBhh1nIafyuEDe7UUwyJ8mNEjD/bMksb8/7fj4aQXVrD1f/9nlqHqZ24u1l4a8FEBkb4deuvKIRoIgFEdB+LBRLPNwsOHt4G5z8Ca58zwQNMYAlOMmmf0E7VPI6I9Lfz3HVj2JpRQn55LYMj/RgZ489jK/Y2Bg+AOmcDi9alMzY+sDt+MyFEOySAiO5lsUC/qbBgJWx7G7a/A5N+Cpnr4OOfQ8RwiGkzH6lTYgK9iAls2SxVUF7b5rz88tpTYvkIIU5VEkBE+4oPgT0QPP1M2jMQ7K7mIK1bDndqzWKBwDgYcaUZfTX4EqguNjWTkKQeKe7lY2L4aFtOi7zrJsZJ8BCiB0kAOYM1NGhS8ipIK6wgwO7OwAhfArzcofAALF5gVp4dMhc+fxiSL4DwoRA2DFJWQGC8qU0cTWA/CIg3wcbTvyndAyYkBPHv68fwzFf7adCau6cPYFL/4B55LiGEIQHkTFJbCY4qs/x3bSWrD5Zx22tbGofFXjE2hodmxBFUcRjOuhN2vGuG4U64Fd682ux9MeWX8NmDkDDdjKbyCjr6czYPGD1YG/D2sDJrWCRnDwhBA76eJ7b8uxDi2GQeyOmittzMqyg60DLdeLwStrwGX/0Jig9RcGATv12yq8Wcivc3ZrL7UA68NAsK9pjtUhddY5YfufIVsxLtigdM/uy/HTt49AEfT5sEDyF6idRATheFqWbpkKgxMGAGrHwcpv7CrCWVvw8KU8zqsQMugPQfKK/2JLO45Z/f292NWjcfiJ8KK58wmckXQm2ZCUpH1JaDoxohxJlNaiCni9DBMOdZs0TIysfNcNrxt5ml0Tf8D967GRrqYdXf4YMFhMYmM7Gff+PlN07ux48n9WPJjgLeTfwzGec/hyNyLIQMNMuNfPob8+/Vb5iA8tnvTM1ECHHG6tMaiFLqIuApwA14QWv9aKvj04ElwJEV8hZrrf9wPNeecRrqzB7dR1QVQX01uPvA6GshawN8+Qdz7PyH8akv5pFh+fymLpDoYF9255Sx7qAJCEu2wvmDkhmZ8C+meGcxpiIfdc0iM1EwZADcsMT0o5yETVhCiN7TZzUQpZQb8CwwCxgCXKOUamdlPVZprUe5fv7QyWvPHIWp8MX/wcDZcPE/zS5+G16CHR+AxR1o3pltgZ2LGVixllfDF3HNYI/G4HHEl3vyaLDYuPZTJ7t0vBmBFTLAHIyf1JQWQpyx+rIGMgHYr7U+AKCUWgTMBXb18LWnp9DBcMOHZp6FV6hZrLA8xyxWeGg1aCdMewBSPoMvfg83LYMNL+K/+308QmYCbffI0BpqHQ1sK7Mz1Duk138lIcTJrS/7QKKBjGaPM115rU1SSm1VSn2qlBrayWtPP0UHYecSs8ZU87TNAxLPBf8YqCuHPR+DsxbCh5jNmMbeBLGTYOaf4bL/mmt2vA9D5tI/1Ich4S1Xqh0VG0BqfgUANquMtRBCtNWXnwztTQpovUH7JiBea12hlJoNfAgkHee15kmUWgAsAIiLa2f/7VNJfQ388BysWwgX/BF2fmA6ze9YBZEjms6rLTf7jq/9j2l6yt0JI642+48XZ8K+FWYhw/lvwoFvCfGy8q+5cXywr45vUgoZFROAn93Gc9+k4m+3MTImoM9+ZSHEyasvayCZQGyzxzFAdvMTtNZlWusKV3oZYFNKhRzPtc3usVBrPU5rPS40tPOL951UbJ4w6W6zk9/nv3Nt+/oceIdDQ7M9MoIS4NJ/g5vNBI/wYRCcaOZ0aGDyvfD5/4FvNIy4Cr54mETven590RBev/UsLh4ZSUl1PffNTGbRgokkhfv22a8shDh59WUNZD2QpJRKALKA+cC1zU9QSkUAuVprrZSagAl4hUDJsa49LZVkmM7y+mZzMGrLIfVL8A42czxqSkA3mKG7znpXENkBgy6GCx+FZb+ExPPMfuMRw0xT1pUvQ3B/AAK83JnYP4SJ/aXPQwhxdH1WA9FaO4B7gBXAbuAdrfVOpdSdSqk7XafNA3YopbYCTwPztdHutb3/W3Sz2kqodu1zUVUM5XkmXV8DNeWQuRF2vGeWSp/+AESPheX3g1cgoMzM88W3m76RzA0w/na4ay1EjTYd6kMuhWvegTE3Ne3D4e7VGDyEEKIzlNbtdh2clsaNG6c3bNjQe09YnmvmS1gsLdNH1JaDh6t5qLLABIfachh9I+xcDHUVponp4GqTTpoJxWlQmQcNTvAJMzWI2nKoLoQDq2H/crh8IUSPN/f2CTWLI7r7gG+YGVqldctyCCHEUSilNmqt2+zDIJ8iPaU4Dd6/HQ58DSXpJp36VVNfRdZG+OrPZn2prI2w5xOz3PlXf4KD38DeT8HNHRbfYYKD1QOW3m2ao8pzYNsieOMKKNgHXz4MX/8Zhl4M0+43NY3g/k0bNgX3N8EDzIKGEjyEEN1Axmf2lLoqKNoPb11tOqtL0mDEPLMrn1PD/i9g7b+hcD9krjfzNG75DMbeYgLOjP9zHVsHxQfNB39FHoy50SwrMukes0/HV67Z5Rf9Fb78o7l/8kUQPaZPf30hxOlPvor2lPAhcPXrpiO7JM30Owy/0nzAVxbA+AVmYl/IANPxfd1is/XryscAbSYA7l4KF/7V1DjKss0Mc+8wqK8Cm900ax3h5glXvmqerzDFNHEJIUQPkgDSU4rTYMVvTdrqCVvfgIz1ZnTUhz+BsgwTODLWmaG5RQehrtLUOlY8aH5iJsCap03tQymzQm7uDrNI4r7PzKKGP/o7hA2Fz35r9utY8A0MngsWt+Mual5ZDYdLa3riVRBCnMakCasn5GwDR41pipr9NzMK6p0fu4bVukPaKlhyL+TtNLPHE86FnC2m03vey/DKxVBdZDrJqwpg3kvgqDV7ivuGm3kew66A0kwzr+P835l02hoYfwu4Hd+ftbSqnqXbsvjH5yk4Ghr46blJXD42mmDvtsuaCCFEazIKq7uVZJgNmRqccOVL8M1fTSC59L9QmQ91ZWaIbm0ZhA4C/1gzLNfNZoLAnk/MY6uHOXbxP1z9KekQEAVrnoHzH4LI0ZC1CYKTwNMX0teY7Wb9o467qMt3HObO1ze2yHvyqpFcPiamu18VIcQpTEZh9ZaAWLj0OTNy6n8XQvoPMOdfYA8AeyBsfNXUIFb9HZY/ANveNjWLA9+Y7WPLc8wmUNd/YPbyKEgxS7P7BJu1q/J2wKLrIX8v9D8H/CNN01XSzE4FD4CPt7advP/2+gycDWfOlwohRNdJAOkJngGmqQrMvx5+sO6/UFthgsfHv4Dz/88Ei3X/NRMCB86GJXfB2b+E3R+ZZq7rP4CY8bDlDdMsdeFf4KrXTB+IT/gJFzMh1LtN3oAwH9wsPbd3uRDi9CEBpLuVZJg1pxocMOsJM+rq4ErIWAuLroIhcyHItdT6EWU5ZkRV5Gjofy54hZgaiT3ALJJ41SuQMB38IiGwPwybBwExZoJgzrYuF3X28EgCvJr2D/fxsHL1+NijXCGEEE2kD6QnHFxpNm2KnwLp35uZ4srNTCTMXAfjboGPfmY610ddC8vuM5P/kmdD9Chzrnaa2kpdFeTvNs1bNeVm0uG2N2HSz0xNZcc7cO27ZrfAIxMHOyE1r4Kd2WVoNIMj/UiWhROFEK101AciAaS7lKSDxQp+US3T9dVm+fRdS8xQXK3NOlQxE6As08xMD00y/SNuHiZoNLdvBbx5Fcx4GGxeZhLhJU/D1rfANxLOuhOW3gv9p8P0+2WbWSFEt+sogMgw3mOpLgW7f9t0cyWZ8NEvwS8Czv4VfPJr8PQzkwD9IkzA+PZxCB1oJhPuXAyVRTDpTrM+lnvbvohG4UMheRZ88bB5HD/F9Kv4Rpr77PrQ5J/326Z1tYQQohdIH8jRlGaa1W6zNkFpVlP6iIYG2P+VGXGVdIGZfb53GaSthNgJZnQUmLkcgy826bevhdiJMOFWCOx39OABYA+CflObHocPga1vwtgbTTOZbjBNYfFTzFBgIYToJVIDOZrKQrOcyL7lEDIQMn4wH9bhw8DqbpZPf+d68PA3y6t/8ktzfMrPzGxwDx/ThHV4B6x/3oyqGjgblv/GNGFVFYJX8NHLkLYKPnvIBAibHdY9bzaL+vbv5njUGNMv8u0T0oQlhOhV0gdyLAe+gVfnmvSEBWb47ZGahdZmtd3XrzA1Ad8ImPYgLPsVDJ7T1IRVWwGlGbDlTXPemJtg8yuAgqm/OPqHfmkmbH4dRl5rVtHd/LoZybXhZeg32exzvurv0G8KDJwltRAhRLeTPpCuKM2EH/7T9Hj7uzDymqaVbrUGp4PG7dgbGiBqlAkiHl5NgcbDxzRFVZfA5lfNXuZlWWbfD2f90cvgHwNTfwVWV2A4kp5+v+nzcGuVFkKIXiJ9IEdTWWj6M2Y8Ajd/auZ0ZK4HR505XnQA3rsJ/OPg8hfM4ojL74dR18DoHzcFEDBrWE1/ALxDTPDwDjUf/L7HMSHQamub9gpqChjN00II0UukBnI0USPhti9NLcDDtyltdc0yD06E+W+ZWeGhA82/PmHgH932XlVFZv+PygIzU70yH9b+59hNWEIIcZKSAHIsR/YOb50GM6+j/7Smx/3P6fg+znozDHj0jTDtPjOst7rk2E1YQghxkpIA0hNqK5qar46kfcPhvP9n8lqnhRDiFCR9IN0tY72pXVQWNKUr8s0x3/CmgNE8LYQQp6A+rYEopS4CngLcgBe01o+2On4dcL/rYQXwE631VtexNKAccAKO9oaY9bq6CjORcM1TULAPDn1n8kde3aV1qoQQ4mTWZwFEKeUGPAtcAGQC65VSS7XWu5qddhCYprUuVkrNAhYCZzU7fq7WuqDXCn0s7j4w+R4TPPZ8bPJuWWGWIxFCiNNMXzZhTQD2a60PaK3rgEXA3OYnaK3XaK2LXQ9/AE7+rfIKD5jVeI/Y/l5TE5YQQpxG+jKARAMZzR5nuvI6civwabPHGvhMKbVRKbWgo4uUUguUUhuUUhvy83v4g/xIExbALZ+ZlXK3vQ2VeT37vEII0Qf6sg+kvW3v2l1XRSl1LiaANFtVkCla62ylVBjwuVJqj9Z6ZetrtdYLMU1fjBs3rmfXbXH3gUl3w/B5ptkqOBHG/FiasIQQp6W+DCCZQPPt72KANpt0K6VGAC8As7TWhUfytdbZrn/zlFIfYJrE2gSQXucdYn5ap4UQ4jTTl01Y64EkpVSCUsodmA8sbX6CUioOWAzcoLXe1yzfWynleyQNzAR29FrJhRBC9F0NRGvtUErdA6zADOP9n9Z6p1LqTtfx/wC/B4KB55RS0DRcNxz4wJVnBd7UWi/vg19DCCHOWLKcuxBCnCaq6500NGi8PVrWDWrrnXjY3Lp8X1nOXQghTlM19U7WpBby7Fcp1DgauHNaItOTQymsqmPplmw+35XLtORQLhsdTWKYz7FveJy6HECUUjdrrV/qtpIIIYQ4LocKK8kvryXUx4PIADurUvK5/dWNjcd/+tZmnrl2NIvWpbN6vxl7tD2rlC/35PLaLWcR4uvRLeU4kRrII4AEECGE6EVf7cnlZ29tobzWgbe7G09dM5qPt+W0Oe/VNWlY3VqOk9qdU86BgoreCSBKqW0dHcJ0ZAshhOglhwoqufetLVTUOgCorHPyp493MX1gWJtzA73cySuvbZNvUe1NweuaYw3jDQd+DFzSzk/hUa4TQgjRzQ6X1TQGjyPSCqsY1y8QT1vTx7mbRXHTlARig+wtzp06IJgBvdgH8jHgo7Xe0vqAUuqbbiuFEEKIYwr19cDTZqGmvqExz93NQkZRFT87P4ncsloczgZmDAlnQkIQ8cF2zk4KZU1qIeP7BXJ2cigBXu7dVh4ZxiuEED0oJbeclSkFZBVXM21gCGPjg/Dx6Fr3c0OD5pPtOfzqna3UORuwuSkeu2IEcUF2Xl5zCC+bhSvHxzIyJgB3a9eH7bbW0TBeCSBCCNFDDuRXcPXCH8hv1hfx5FUjuXzM8S8snlVcTWWdgwg/T/zsNpwNmgP5FRwuqyHcz5P+Id5tOsu7m8wDEUKIXrYju6xF8AB4bPkezkkKPeZIqDqHkxU7c/ndkh2UVNUzNi6Qv1w+jIERfiSF+5IU7tuTRT8uEkCEEOIEpeSWs2LnYbZnljJreCRTBgQT6utJbb2zzbnV9U4cDablp6rOwc6sMtIKK4n092RghC+hvp6AGXJ776LNHGkk2phezCMf7eL5G8bh7XlyfHSfHKUQQoiTlNYadZShrxlFVdz80joyS2oAWLErl3vOTeTmKf1wd7PgYbVQ62jq9F5wdn8i/E2QWLolm2/35TM40o/N6SXsziljUmIwqfmVVNY6ePba0by9PpNv95m9jNakFpJbXkN/z+4bSXUiJIAIIUQ7SsoqWJmSz6JNucQH2Zk/KoSR8aFgbTmKaW9ueWPwOGLhyoOMiQ/kT5/s5v6LBvHtvnxyy2r40fBIJsT789HmdEL8vNiUVoS3h5UnP29cbJzJicH42W0s33EYP08rT141irggL/bnVZBRVImvh5VN6cWs2peP1WLh7OQQhkf7twhy9Y4GDhVVUe9sIDbQjo+nrUdeIwkgQgjRjo+2ZPC7ZQcAWJMKH27JYfGNyQwe0L/Febqh7UAkjSa/vJb8ilr+8PEuxsQFMi05FB9PK98fLMHRoNl5uJLpg8K4563NLa5dk1rIL2YksXzHYcpqHCzZksVtUxPYllVK/xBvDhRWct3zaxubwZ7+KoW3F0xiVFwAAEWVtby4+iD//fYAjgbNtORQHpkzlH4h3t3+GvXlfiBCCHFSKiiv5V+rslrkVdc72VHUtinL9Fu07BD/8aR4ogOaJvFtSi8mOcKXlfsK+McXKfzrq/28tS4Dm9XCbVP7c/OUfi3u4Ww2OvZAQSWpBZX8fulOXvshnT05ZY3BA6DW0cDH25r24tt4qIRnv05tPOfbffm8vT6DnhhxKzUQIYRoRSkzm7s1i6XtR2ZcsDev3TKBDzZnsSWjhBsnxRPm60F2aQ1/vWw4zoYGXlh9EA83RVK4DwMjfPh8Vy6p+ZU8v/IgAV5W1h4s5rqz4tiRVcre3HIqappmm09KDOZwaQ1aw/Kdh+kf6k2QtztFlXWN5xRXNaU3HSpqU8ZPtudwx7T+3TqJECSACCFEG8E+HvxiWjS/WZramOfnaWV4YF275w+K9OPBSD9q6h18vC2bV3/IZelWUyuwKHj+hrFsyijhte8P0aA1l4+JZkRMAJ/tPMxV42Mp3ZXHc9+k8sicocyfEMdvP9iOzU1xycgoqusc1DebeLgmtZAhkX6s3l/QmHfp6GhKquqodzaQ3M7w3rFxAXi7d//HvQQQIYRox0UDvAi8LIol+xuIDfTk4qgKkoM6+MiszIfD20nzHElOaW1j8ACwWizsOlzOs183BaO31mVw1/REzkkKZWtGaWP+1owSpiWH8PMZyeSV1bAru4yzk0N4YdXBxnMGRfgyJMqP8pp6bG4W7piWSENDA5f/ew3l1Q4emTOEsxKCWHvQ1ERCfNy5/Zz+2Kzd32MhAUQIIYDKOgcH8yupdzbQL9ibwLA4LggI4YKzvMwJdVXg7tX+xftWwJK7KbvkK2odLYfYJoX7sDm9pM0l6w4Wcf3EeH7+9pbGPD+7jae/3M/9swYR4u1OcrgPz688SE6pGeUV6e9JTKAXf1m2m+euG8OkxBC2ZhQzf+Haxnvc9eZm/nP9GH4+I4ma+gYGhPkQG9RBuU+QBBAhxBkvt6yax5fv5f1NpuN8ZEwA/7h6JP1DmwWDjoIHUJ0wk8oZTxFduhFfj/Nxsyicrk7svPJaxvcLanPNoAhfXlx9oPFxqK8H4/sFMm9sDLX1Dv722T5GxATwqwuTSSuopLTaQUWtg6e+3Ee909zbbnNjTWrbhdEfX76XD+6ejL+9e/s8WpMAIoQ44609UNQYPAC2Zpbw1rp0Hpw1GItFkV9ew8GCSqwWC4lhPvjbm+ZVbDpUzJOfHyAlL4b5Q704J7mBh2YP4tmvUymsrCPE250pA4JZtj2ncX+OAC8bgyLN6K2LR0QR5ufB6NjAxqG2DmcD9180iN055dTUmRrRHa9vbAwc5yaHMizKH4BQn7ZLokT4e+Lu1n2LKXZEAogQ4oy3Kb24Td5Xe/K5+9xEDhZUsfZgEal5FXy4Jcs1r2IY0YF29h0u57oX1lLtWrLkqe9rya6y8EDcXoZd9yMOFlSxLq2Qb/fm8fi8EeSX1+LUmqziav6ybA9Vdea6yYnBXDC4aY8+q5uFUXGBjIoLBMwqvEvvnkpqQQV+njaGRPoS4lryZFJiCKE+HuRXmOBktSjuPS8Ju/tpHkCUUhcBTwFuwAta60dbHVeu47OBKuAmrfWm47lWCCGOparOwaHCSs4dGMagCF9ySmvZl1vOpzsOM3VACMt3Hub3H+6iztlAYqgPv7loEH9Ztps5I4uwu4eSX16Lj4e1MYAAvL+tkLvGjGZcGAT5BBIX7MXvl+zk9bUZKAXXToijsLKuMXiAGVmVU1pDUgczxi0WxeAoPwZH+bU5NiDMh7fvmMiWjBKq65wMi/ZnWLR/979Y7eizAKKUcgOeBS4AMoH1SqmlWutdzU6bBSS5fs4C/g2cdZzXCiFEh7KKq3lsxR6WbjEjps4fHEakv53csloeuGggQ6L9+PGL6xvPT82v4ItdudwwMY6iyjouffY7auqdXDYmmsziKpZtPwyAj4cVW+gALD5exHk6efbr/aTkVQCgNbyxNp1fzxzIip2HGxdKDPSy4d3FPUIA+of6tOyv6SV9ORN9ArBfa31Aa10HLALmtjpnLvCqNn4AApRSkcd5rRBCdOjrvXmNwQPgy915eLm7sT+vnLzyWvYcLm9zzYZDRYyIDuDhj3aRXlRFXnktC1ceoH+oT+MmUfdfNIgY16inkqp6Vu4raHOf8tp6vGxNTUyPzBlKVIC9zXknu75swooGMpo9zsTUMo51TvRxXguAUmoBsAAgLi7uxEoshDhlNTRoDhZWUlxZR3yQNyt2Hm5zzvasUgaE+bImtZAFZ/dvc3z6wDA2pLXtL/lmbx5/unQYob4ejIwNaMz397IxPiGQ5TtyW5w/KNyX564bS2FlLf1DvBkc2bZp6lTQlwGkvfWRWy/W0tE5x3OtydR6IbAQzI6EnSmgEOL0UOdwsnRrNg99sINaRwNJYT78aEQkq1Ja1g6Swnz4dPthzkkOYVN6EbOHRzQ2TfnZrdx+dv92O9xjAry4eERkm50BPaxuXDk2lm0ZpWS75nLMHBLOjuwy7j1/QI8Ps+1pfRlAMoHYZo9jgOzjPMf9OK4VQpwpqgrBK7hluvAABPYDi4X9mXnc9962xj6HlLwKwn09SArzaeyfSAw1w3O9PdwYGRPA75fu5OykEH55QTJJoZ4MiQ4iPtibALuNhSsPUFJVD4C7m4Xbzk7ocFvZrOJqZgwJJ8DLhptSbDhUzKqUfH42I6mnX5Ue15cBZD2QpJRKALKA+cC1rc5ZCtyjlFqEaaIq1VrnKKXyj+NaIcSZIH0trP4n1bP+SXZpNfbcLURFhMNbV8O8l8DqSXZqOa0Xo33qyxTuu3AgGcXVBHm7E2C3cSC/kt9cmMyuQzn42a2UVtUx3q+YidEhqGAzR2NQpB/v3jGJrZkl1DkaGB4TwLB2RkcdMSY+kL98upua+qZNpZ65ZjR+PbRHR2/qswCitXYope4BVmCG4v5Pa71TKXWn6/h/gGWYIbz7McN4bz7atX3wawgh+pKjDvJ2cTBiJn9ZnMLnKaX42734/UVh/Cj2bDzfvBJQhE1/EWj5ge1o0LhZFMu257Av19RCRsUGcOnoaC7s78n104bibbPi6ywBn9AW13ZmT/Jh0f68vWASH27JIre0hnljY5mQYGamH2u3w5Od6ok14k9W48aN0xs2bOjrYgghulFdTRUPLt7G+9taLunx7g3JjH93HABVV7/PN44h7Mopx93Nwq7sUsb2C+LZr/Zz4bAILhgcjq+nlQFhPgS3M7O7u6XmVfDRtmy+21/ARcMimTkkvMP1qqrqHKTkmpFh0QF2BoT54t4DCyMejVJqo9Z6XOt8mYkuhDilFeTn8vGuth3bB7LzGG8PBHsQPxR4cO+nWxo3WZo7Moqd2WWUVNezJb2E31w4sFcCB0BeWQ0/eWNjY61nfVoxG9KK+NuVI9vMBampd/DKmjQeW74XMEvD/+PqUcwZGXVS1FxkR0IhxKnLUYd35SESgz3bHAryBH68hNwrl/DAytoWu/gt2ZrNwHAfLh8dzb+uHd1rwQNgf35FY/A44tMdh0krrGxzbkpuJY+v2Nv4uEHDbxdvJ72wqsfLeTwkgAgh+kZlAez7DKqKW6bra5rOaZ5uj9Ud//7j+d3sZDyaNeucPSCE4YMGQuRIyt0CGxcxbC7U14O/Xj683Q2YepJqdxaCqV20VlhR26bzv7LOSXF1fQ+UrPOkCUsI0TdSv4bFt8HUX0BdJaxbCFe/Abk7YfAl4B0CP/wHhs+D8CEd38fdm4nJXiy9x5f9+RX4etgYHOnXuMd4uK8H4+ID2XCoqZlLKRgU4YeHrfMLDtY7GzhUWEWdw0lckBc+nRxNNSDMh+HR/mzPatpI6rJRUfQLbrsUSXSgHQ+rhVpH0wiucD8PIv3b1rj6ggQQIUTfSDgbhl8Jq/9hHo+9Gfyi4b2bYPNrEDUadi8FD18ITgKr64O6qhiq8iEkuTGtQpIZGOHHwIi2w2l97Tb+dOkw7l+8ja0ZpQR6mcddqXkUV9bx0ncHee6bVBwNmikDgvnTpcNICDn+dahCfT14+ppRfLk7j7UHijhvcBjTkkPbXT03MdSH564bw33vbaOoso7oADtPzR9FuN/JEUBkFJYQom9UFsDXf4UNL5jHU38Bk++F9O9hkWta1+gb4II/gJdrQ6bacvj+WdjwEtywGHa8D5vfgB9/CGGDj/p0pdV1HC41q+dGB3Zt3amvdudyyysbsFoUfnYbxVV13Dw5gYd+NBi39tqgukl2STXFlXWE+nkQ5tv7wUNGYQkhTi6pX5vgMeYmqK80NZGY8XBgZdM5B76B8sNNAcTdB2Inwuon4d+TTd6I+WAPPObT2W1ulNfUszIljwC7O2PjAzu9gu3WzFKuPyuOYB8PCipqifS3k1ZQQUlVXY92xEcF2E/KxRYlgAgh+kbC2XDZfyBxBmgnDDgffKNg44umJhI/Gd65wew3fqQJSymIHAUJ0yFlhbnPmBug6AD4Rhz16VbvL+DWVzY0dkpH+nvyxm1ndSqIjIkL4Kkv97MpPb0x7+Yp/bC7n5njkSSACCF6T1kO1JWb/gutIfasplneI6+Bhga47UvwjwXPgKb0kf6P2nL44RnqyvM5OPM1qmtqiNvxBUERCWbdK7+odp+2tLqex5fvaTGiKae0hs3pJZ2uhbReTPH1Hw5x3VnxDAg79Zcm6SwJIEKcpspr6ql3NhDk3XtzHI6qMh8++3+QsxWufg2+fQIOb4Nr34Fg19LpFgtEjmy6pnkawN2Hkv6X8ELlRfz74zycDd4MDp/OUyOSSe4geADUOxoorGw79LW81tGpX6GhnS7jeqemzulse+AMcGbWu4Q4jdU5nHy9J4/5C3/gkn99x4urD5Jffoz5FL3BMxCGXgZFqfDcRNj5Pgy7AryDj/8eSrGtLpJnvsvF6fo0351byTOrsql1dPwhHuLrwc2T+7XIsygYEdO5rV8Tw3wI8m65BPvZA0KIC2x/GZLTndRAhDjNbM0o5ZZX1jc21/zx4124WRQ3tfoA7XVuVogZB6GDIW8nuNlg+BXg2bkP8dTc0jZ53+wvpLi4iIjQ0HauMK4YG43Fonh1TRqhvh78euZAhndy7/C4IC9evWUCz32zny3pJcwaHsn1E+M6PRfkdCEBRIjTzPq0ojazl1/67iBzR0UR6NWHGxgdacLK2wmJ58OBr+Gta1s2YR2HuJC2cz3Gxvrj7x901OvC/ezcOS2RK8fG4GG1dPlDf1i0P/+4ehQVNQ4CvNx7dPjuyU4CiBCnGX+vth+MIT7uuHew4VGv8QyEIZdCcDKcdQekrYLcXZ1rwsI0O102OooPNps95EJ83PnVhYPbnYjXnu4YbuthdcPDp/Oz2E83MpFQiNPM/rxy5i/8gYKKOsC09b96ywSmJnXcvHNMlfngHdo23VlOB9RXgadfy3QnlVXXsz+vgqo6Bwkh3kSfoX0QvUUmEgpxCiitqkMpM8u5qwaE+bJowUQ2HiqmvMbB6LjATncWt1CSAZ/+BibeBUEJsOw+mPgTSDjn2Nfm7gKrBzV+8WxOPczqg6WE+nsxOVGZpUTcOh88APzsNsbEH3vyoOhZEkCEOAmUVtfz2c7DPPdNKlY3xc/PT2b6wNA2+0Mcr9ggL9zd3PBytxByoktf1JZB5np480oITIC8XaYPI2Y82I4yO7ooDV6/Avxj+Wbcf7lz0a7GQ8He7rxzxyQSwzo3B0OcXGQYrxAngVUp+dz33jYOFlSSklvB3W9uYkNaUZfudbCggl+/s5Vpf/uaH/1rNZ/tPExds9VcOy18KFyzCOqrTfAYcyOMusYEj/rqpvOap8FM6pv5R0oCB/PEFwdbHCqsrGNzRttNoMSpRQKIEH3M6Wzg9R8Otcn/aGt2p+9V63Dy1BcpfLQtB60ht6yWO17fyK6csq4XsCQDvvqzSVvcYPs7kLXJzArf8BKkfQe1Fa706qbrrO4QNhiHRxAVdW0DWE39CQQ1cVKQACJEH7NYFGG+bUcGBft40NlBLvnltSxtFXi0Nntwd1ltGeRuh1mPw4Jvwd0b8vdCWRas+hu8MQ8+vR9WPAjrXoBK197kRWnw+jxC9r/H7eNDWtzSalEn1i8jTgrSByJEH1NKcePkBJbvyKXOab6Ve7u7EezjzuqUAs5ObhrxlFdWQ62jgQg/T2xWC4UVtaTmV+Bs0CSG+eBlcyM60E5GUcvmpIB2hvYet/ChcPNy8I0ED2+4eUVT+oYPYOE02PI6RIyAi/7SNCzX1YSFVzBzQ5Lw9PTglfV5RPp7cve5AxgWJQHkVNcnAUQpFQS8DfQD0oCrtNbFrc6JBV4FIoAGYKHW+inXsYeB24F81+m/1Vov642yC9ETxsQF8NLN4/lmbz4WBb6eNp79OhW7zY0l90zB327js125/PGjXRRV1TFvbDQ/ntSP/1uygw2HSgAYGO7Dv68fyx/mDOO2Vzc0LvUxsX8QQzs547qNkAFt07XlcOBbGmctFu6HooNNCxpa3WHwHHCzEaoU109KZO64RNytbl3aCVCcfPqqBvIA8KXW+lGl1AOux/e3OscB/EprvUkp5QtsVEp9rrU+MpTjH1rrv/VimYXonKKDoNwgMK5luh1KKUqr63lj7SEatG7sHyitrqe4qo5DBZXc+9bmxvPfXp+Jzc2N4qqmxQD35lbwweYsfnZ+Eh/ePYXUvHL87DaGRvr3zA525Yfhu39C8kVwzn3w5lWw7nkIHdRUC7E2m/ludcdX2jxOK33155wLTHelXwG+oVUA0VrnADmudLlSajcQDexCiL6QvxfKsiFhGhSmNKUt7XQllmTChz8Bqx1mPw5Lf2rSlz7b4ZLjsUFeVNc7WyxDkhjqzZ6cMg7kV7Y5/6Ot2cwZGUVqflP/xuqUAu49P4nh0f6dXuep00KS4MaPzFpW/jFN6U7OLBenrr7qRA93BYgjgSLsaCcrpfoBo4G1zbLvUUptU0r9TynV4YwipdQCpdQGpdSG/Pz8jk4T4uiqimH5A6bDePu7ZsvVt642zTbtsbtWnj3wFTwzzmzTOvSyo+6clxzmw+NXjMDTZv5bRvp7ct+FAzlUWIWtnWVI4gK9yCuvbZF34dCIds899u9X1H76WMKHmuDROi3OCD0WQJRSXyildrTzM7eT9/EB3gd+rrU+Mhbx30AiMApTS/l7R9drrRdqrcdprceFHmWlTiGOqr4aLnoMAhKg5BBU5MK8lyCog0UAPbxN086RgOEbAYnnHnXinYfNjXljY3jvzkk8OGsQ5w8K4/Hle1i0PoOkcB8Ghvs2nmtzU9x30UB8PJr6Es4dGMqs4Uffla9dJenw0c8gYx2UZrrS6zt/H3HG6bEmLK31jI6OKaVylVKRWuscpVQkkNfBeTZM8HhDa7242b1zm53zPPBx95VciFayt8B7N8MlT8Pku2DNv+Dch8DNA1QH38Hy98LSe6G6GPpPN3t7L733qE1YYPpC9hwuZ8XOw1wwJJwx8UH4220UVNRx+ZhoahwNRPp7MjLGH19PG7+5aCC3Tk3A2aDpF+KNb1dWmK0ugYPfmtVxA/vB4e2QeJ7ZzMnah6v3ipNeX/WBLAVuBB51/buk9QlKKQW8COzWWj/Z6ljkkSYw4DJgR88WV5zRnHVmAcFtb0PEMNOc5R9jNkYKjDd9Ac3VlsPe5RA7AYZdDlZPM8Q1IO6oTVhH5JbWcO6gMB5bvrcxL8THnftmDmJzRjGXjozi9bWHeHNtOuH+njw0ezBnJ4Xibu1ig0LkCJj/Frw82wSPCXfCiKsleIhj6qs+kEeBC5RSKcAFrscopaKUUkeG404BbgDOU0ptcf3Mdh17XCm1XSm1DTgX+EUvl1+cSWInwJWvgKMaVv8DrnoF9n0Gq54ER23b8z18IeFss3Xr5tfh459RHz+VsuR5aOuxR0NNSAjm7fUZLfIKKupwNDTwixnJvL72EM+vOkhlnZMD+ZXc9uoGdma33WTpuJWkw8onTFop2PoG5Mp3MnFsfVID0VoXAue3k58NzHalVwPt7tSitb6hRwsoRHPZW8ws6zE3wu6P4NU5Jn/UtWZtqMB4EzSaC+wHNm+qnbB6zgaWbCjF7p7OhUPrQJkZ4/1DvBkW7d9mwcQIfw+q6tpuz2p1UzSgeWtdy+CiNew5XM7ouJa1m9LqOpwNtNmCtY3qYsjeBLOegOix8PplkLsTIkdJLUQclYzKFuJYnHWmnyB2IkSNMSOqwPRt2LxME5VLan4Fn+/MYUtaIRfG/gT3oHjufrvp2/zSrdn8fEZSY/PUny8bxnVnxbd4utggbxac059HP93TmOfuZmFYlD92mxvhfh5U5DtaXONvb/qvXFXn4Nt9+Tz5+T6q65z8ZHois4ZFEOTdwUZKkSPh1i/AL9p0/h9JS/AQxyABRIijcDZo0jyHUHH5N8Qc/oHgrA2QMB0yvofPfw/XLzZ7ewM5JdUseHUDqa45G3WEUbi7ZW2h1tFAblkt/nYbpdX1/OWT3ZydFEpcUMsNka4YE42Pu5XXfjhEbJDZinVIlB9KKf7fxUO49eX1uCaaMzDcp8Wcj02HSvjJ65saHz/0wQ7clGJIlB/RAfb2d+QLTW4/LcRRSAARoqoYvALbpAsranl3Ywb/+DyFWkcDSWHBPH3pcgYfehMGXww5W0xTT0AcePiyL6+iMXiAWTCw3tl2McQGrTmyjXZlnZOa+rbNVaG+nlw/KZ7LxkRjc1O4W5uG604dEMLiuyaz73A5Pp42hkf7E9ssAH2++3Cb+725Lp0gb3dySmt4ev4oBkZ0bSMnIZqT1XjFmS1vN7x/C+Tvg7w9TWlgQ1oRj366l1rXXhopeRX86fs6KgfPg0EXg08kWD0am7Bar5y7KqWAK8e1nFhntSiiAuwUV9UDMGVAMFH+HXese3tYWwQPAJubhVGxgVw1Po7ZwyNbBA+AsHZqGAF2G2XVDvYeLufvn+1rN2gJ0VkSQMTpLf37pklxzdOVBaZfoyQd3H3NGk6vXwEHV0JZNsWVdew+XA6Ar4eVi0dEMmtYBJsyyijU/mZi4FkLYODsxiaspDBfYgKagkF1vZPKOgfPXDuaKYnBzBoWwX9vGMu61EI8bRYuGxXFH+YMw6eduRv1jgYyi6soKG9nlNcxnDcoHD/PpsYFm5ti2sBQNqWb9UpXpuRTVFnX6fsK0Zo0YYnTV0kGvHeL2exo1mOw7NfgFWL6LXK2mqGq42+FkdeYGdhaQ9wESDgHZ2U9nlY3pg4IYVy/QD7amo2bRfHLC5KxB/ia4a4+LVfgiQ6087+bJ/Dh5izWHSxizqgoZgwOJyrAzqxhkViUmSg4vl8QFbUOgn3c8bC2XZU2vbCS575J5b2NmYT4ePDInCGcOyisTU2kI4Oj/Hj3zslsSi+mrLqeBq15YVXTjoCjYwPw78qEQyFaUZ3dsOZUNm7cOL1hw4a+LoboTZkb4JVLoL7KDLW98WNw1sNH98K4W9jlO5kPdpaRUqq4bHgQU3PfwGfiTRxwBJNdUkleWR0PftByTsQT80ZwML+SC4aGE+Hnyd5cU1NJDvclKsAsVdLQoLFYmo1Cz1gPXkEQnNgy3YrD2cAjH+3ktR/SG/OUgvfvnMyY+GNPQmytoKKWx5fv4Z0NmQAEetl4+eYJjIwN6PS9xJlLKbVRaz2udb7UQMTpp6YMqgohKAE0MPWX8M1fQDdAg9MEk+KDpFbZuebTLEqrTX/ENymFPDDtYnz31fO7j1dx57T+bE5vO0Hvi925RAfYWZWST0ygF1szS3lrbTqRAZ68eON4BoT5tAweBSnw2qVmbsj5/wfv3gjR4+Cql8Gr5cq1+RW1vLcxq0We1pCSW96lABLi48HvLh7C/AlxVNQ4SAjxbtNnIkRXSR+IOL3UlsPGl+DN+WYC4I73YNtbcP37YLGaNa2cTrjgj+x2RjcGjyOe+aGIA8UOGjTEBHrhZ2/b1BPp70lRZR1Pfp7CL9/Zyhe7cvnlzGQOFVbx6facNucTEG/W0crdAW9eaTreZ/6hTfAAsNvciA5s26nufwI7Cvp62hgTF8g5yaESPES3kgAiTi9WT/NNv3AfvHQRbHqZ3LG/YkNtLHsvW07BvPdZ74hnu9tg/ML7MTSq4+Gs2aU1jO8XiHuz5dHtNjcmJYbw4ZamfcezSqrZlV3GrVP7sSm9naXQre7gF9m08KI9EDzaf94AL3d+f/FQ3JrVYEbE+DMiOqBTL4MQvUH6QMTpp6YMFi+A/Z+xfcYb3PGtO9mlNVgtirumJTA6PpiDBRVU1zsprKgjyNuDJz/fS4OGX89M4us9+UQHejFjSBh/+ng3N03uR2FlHRal6B/iRVphFf9deaDFU8YE2pkzIoqz+gcxbWCr7W0KUmDhdBNIpvwcvvg/iD+73SYsMJMXd+WUkZJbjq+HlaHR/o19K0L0BekDEae++lozZNZiaZluztWEVVtZTN7s13g7PZzs0qZmpYFR/jyweBu5ZbW4WRTXT4znUFElP5uRhNawK6ecu88bwF+X7WFndil3TOvPs1+nUudoYES0L+cmeFFR13aexdj4QD7bncu6tCLGxAe2XFY9IB7mPmvWzAobZh4HxrcbPADcLKp3dhQU4gRJABEntwYnWNzMhk47Fpv5F/GTm9L9z20ZRKye7Iq+kg1cQnl5A05dxe8uHswTK/YyfWAY//0mldwyM7fC2aB5ZU0av545ELvNwuMrzKRBb3cr1fVOMourefbrVG6aHM/5ib7E+VvxPbyO/gNGkT4xjtfXpqM1DI3yo3+oD0tczVq5ZbUtA4jVHQbPaSpn87QQpzAJIOLk5ayHfcvBOxTcfeDrv0BlLoy8Dja9DPFTzTaq7j5ma1mfcDYVuXPnG7vIK6/FouC6s+JZn1bEtRPisLtbWb6j7TIfNQ4ndU5n44zzeqdu7IM40ll+nlslvvv+DdmbiLjkaR6aOY8Lh4Sx7lAJaQVV/PMLM3s91McDH8925ms0DxgSPMRpQt7J4uRVmgk//MfMEN/+Psz8oxlJtell0ww052mzFPmK38KO9yjLPcAjH+9q3Ce8QcNrPxxiWFQAPp5WDhVWMiTSt83TxAba+W5/AWDmXAyJ8uNQYVXj8XHxAbgF9aco9CwYfztEjcZz3xKGbvsLWYUVLN2ajdZgUfCXy4cR4Sf9FeLMIDUQcfLSGgacDwNmgLuX6Yw++z746g9Qng0Za8E7HHa8DyPmU9zgzdbMrDa3qXE4GRvrx0yvFKpHJHHHB7UUVdahFNw8uR85pdVcOioab3crs4dHsjOrrPHau6YnklNSxSWLDhPpP4OHp3pzTs5ObJ/+isDQwfzu0gjmjY+nqLKOfiHeLfYtF+J0J6OwxMmpqgg2vwaOGrMkSUiy2RGwLAeGzIEld5u9xSfeY/Jzd1BaVccNmXPZ1iwAAPxx7lCyS6qZF3yI7+sSqceKp7sbnlYLr3x/iC0ZJfzqgmRWpRSw/lARM4dEMCzaj34hXnyzJ5/3NzUFJYuCD+ZHMnLVHfCjJ83Og0dTkQ8VuWYr3OZpIU4hMgpL9KmSqjrWHizis52HSQz1YcaQcJI7+rZeUwZr/2M60P0iTd9HxAhocED+bogYDlN/RZr/eHZV+aFLsxkUO5DET6/jD5Mv5LZSdwoqTA3jlin9KKqsI6ukhgcP+bEubV/j00wdEEKgl9k0qbLWwdbMErSGFTsP8/WePD64ezK/2LK1RdEaNOwvaWBkeQ68fT38eAlEjWr/96irhO+fhfXPw7Vvw84PYetbcMsKCSLitCABRPSKxZsy+cPHuxsfv/x9Gu8umER8iHfbk929zS55xYcgZwecdacJKAAz/wS7l7Jn1G+5/t08CirMGk/+dhtvXvIio76+lX9e9Q1r00qxuVn4cncuWzNL+eUFySzdmt3iaVbvL+DnM5JYvT+fcf2CeH61WXDQzaL482XDCPPxIDLAk4yi6hbX+QWFm5ntX/0FPI8y1Nbd29SWNr0ML//I5J11pxk9JsRpQAKI6HE5JdX84/OUFnl5ZbXszClrGUCqiuHgN2APgoiRZh2r6DFQngdl2bD/C/AOg+kP8enmBgoqmpYkL62u570UzdDzfkdobTrf7a9nU3pJ4/HIDvbcCPJ2543bJjIyxp9PfjqVw6U1hPt7khjqg7vVwsOXDOX2Vzc07v43JjaAYbEhEBAL814E75Cj//IBcRA3GfZ+Yh4PnnPsa4Q4RUgAET2uQWvqGxra5jc0QM42CEkCN3c4tAbevQmGXsr+pNv5+KAvGws1Fw9OYnrCZYSPvgE+vAOm/pJ9JePb3G9XiYWGpAtJLj7Ifef3Y2NWFSXV9YT6eJDk72RktB9bm/WPTEkM5kcjIgn29oDcnQzyCWZQZITZZbA6GHwjOCc5lA/umsL+vAr8PK0Mi/En0t81yupYgaCuEtY8Y4LHkLlmr5E3r4RbPpMmLHFa6JMAopQKAt4G+gFpwFVa6+J2zksDygEn4DjSiXO814uTQ6S/nTvOSeSpL5tqIX6eVgb5VMHz0+HS/5g5H8oC424lyy2Km5bX4NSKsuoqVu0v4qZRofy29GHc62vAw5eLhwTx6e7CFs8zb0wUFp8Q8AlhUlUR0aEBZBZVoRucOAt28viEej477Mc32W5cMDCIWQPsBHtaIH8PvHIxJM6As+4wH/KDLoEL/oDNHsDI2ICuLX9+pAnLYoFJd5smuT0fSxOWOG30ySgspdTjQJHW+lGl1ANAoNb6/nbOSwPGaa0LunJ9azIKq2/UOZwUV9bz7d5c3lyfyaBQD64bYmN48ZfgE25+3pwHE+4Arfk++DI2VYWSVlBJoLc7HlYLz686wCfTsknMXgpJF1JUWsK7tkt5+tt0nFrzk+mJXDshDotSZBVX4+1h5n3c1qz56aaRPvzK+g5eI+biVpgCnz9kagMhyaaze+Xj5kSbF1z/HsRP6aYXoMoMQ26dFuIU0dEorL4KIHuB6VrrHKVUJPCN1npgO+el0X4AOa7rW5MA0osanNQd3sO68mAWrj5Eea2DWyfHMTnKjcCPbkW5WWD0DWYS4OA5EDYU7H6w/EFem/IZv/tob+OtIv09uXRUFPMC9pO44nqYcDtEjUVHjSaHELTNi6gAO3sPl/PTtzaTkleBu5uFm6b0Y3N6MevTmiqn785WjP/2RtMZX5AC59wHvuFm6feF08xJsRPhqldNvhCiwwDSVzPRw7XWOQCuf8M6OE8DnymlNiqlFnThepRSC5RSG5RSG/Lz87up+KJRfa1Zpwqg7DD5B7axJyOXgsMZ7CixccPLG1mZUsDm9BLuWbSNNZm1qJjxkLYaPrjDbO4UP9UsUbJnGXlzF/HU1wdbPEVOaQ3hfh7EWkvM9rNB/cEnDOUdSlSgN9F+Nqrqnfxl2W5S8ioAqHM2sHDlAaYlt3xrFHklQOxZpn8iZrzZGTB/D7x+mal5DL0cMn6Ar/9s9kwXQnSox/pAlFJfAO019j7UidtM0VpnK6XCgM+VUnu01is7Uw6t9UJgIZgaSGeuFcdQXwu7PjABZPhV/JBexq8/ySOzOIO4IDv3XTAAXw8rZTWOxkteWJPJ+XOuwP7D02ameVB/CIyDD26D2Ek4cKOy1tnmqXzcHLh/cg8kzQRnHRSnmQmGCrAHUhR2Lqv2F7S5rsbRdC+rRRFfscV0aG94CfJ3mV0LQ5LhrJ9AvylmtdywIdBvMtgDuv81E+I00mMBRGs9o6NjSqlcpVRksyaovA7uke36N08p9QEwAVgJHNf1oodVF8Cm1+DwNg75jWXBezmNwSK9qJrff7SHK8fF8uLqphqFt4cVt++eNBs/Db0MtrwJOz6Aa98Fm52I1Y9x68SHeGZVZuM1njYLQxtcTVopn5nZ6NPvh9pK+O6fULAXvxl/Y2hEf3bkVDUvIQGuHQVDfT14dO5Akio+gSGXm1V8dy42a2rZA2Di3eDhGlI88a6mtBCiQ301jHcpcCPwqOvfJa1PUEp5AxatdbkrPRP4w/FeL3qBXzRc+hykfEZWVjplNarF4eKqerw9mlamVQrunByFe9lZMOl2iBwF4cPMv/2mQMF+LO6eXD8qgEAvG29tzichyM5Pzgpi8Mez4NyHAE1RUTGV1njCIsPxiBkHL5yH/1f38/DMxdy8zEp5rQli14yLYpb6nnNuHIFfRAIRgT7guBWsNvAJgym/MGloGTAkeAhxXPqqEz0YeAeIA9KBK7XWRUqpKOAFrfVspVR/4APXJVbgTa31n492/bGeVzrRu9mRJqwVD7Lnko+Y/eqhxhFPADY3xZs3jeT7PZlUNNiYEVzAqLKVuE/7edMcivpqsDVbvbamHA6thrXPU37en3GvzMLDTYHNjrM0j9V1/fn9VwWkF1cza3AIv5roTeKbrtFS9iDSLv+IQ/ll+NbmkJS5GN/Mb+H6xRA7oddeFiFONyfVKKy+IgGkm5VlwfsLAEXteY/wzkF3cmpsWCwKm0UR66u4JPAQNqsV6qqhLBNqy2DwJabfoSO1FZCzBV67FEZcDQnnwJK72TV3OXMW5eFoFqXOS/TjmagVeI2dD+/dCt5BMOMP8KKrBXXyvXDub1sGKSFEp8hiiqL7HWnCqq/C450biZ3wb/76VRZVdU4sCh6alYzTNxpbVQ5EDjfDYivyILB/+/fL3gz2YHCzgrLC4Eth8+vmxy+a1LoAHA25LS75KrWMw7PvoX9EBMx/3Wxp+9pl4OELfjGw5mkIHQjDrzI7Awohuo1sKCVOTGA8hA0mZ86b3PdZMVV1ZtRTg4Y/LtvHPmckJJ4H/jFmXauBF5kA0Vr+Xnj5Ylj6U7O7YPZmSGo2DiN6HP72tgEg2NsdLx/XgoYhSWZYbswE02x13TswYKap7UjwEKLbSQAR3aLQLZT8ito2+YdLa47vBv6xcMEfwFkDu5ZA2GBYeo+p5STNhN1LGFK7lXMHhTZeohT8Ye5QIvybNU8F9oPL/m36PALimtJCiG4nTViiW4T5ehDp70lOs4ChFEQFHGffg7uX2edDO6GyyDR1TbjD1F48/SAkmZDQcB6bHcfOSf0orqilv3ctQ/zLwBkG+z8H3yiIGtlykUNZ+VaIHiM1ENEtwqzV/GN2OEHepqnIw2rh0ZnhJHuWHeNKl/y9cHgHfPNXM4y2oR6sdqgpgbdvgEEXQ1UJYa9N51zfbC6Pr2XU4mm4vzYbNv4P3r4OPv0NVLadTCiE6BlSAxHdw+bJRL2dj8Znk2OLJ1CXklD/PRb3u4/vev9Ys8dG6GD47P+Bxc3sdz77CagphTeuMDPQvULBzQYhA8wuf69cAsvuA79YmPMvqXEI0YskgIj2aW3aoFqnO2KzQ9JMotdeTnTOFhMA7l5//AsSuntB/+ng4Qf/m2m2sx04G6LHwvQH4PPfm/PmPgPhQ8HpMIEF15BeR2XTmlxCiF4hTViirbTVcPBbEziap4+mqtgMmc3ZAsEDTAD48C4oSjv+583fC4vmm0UNQwfD7g8h/Xv46k9gDzRBavFtZuXc4jSzGGNQIlz9hgke0oQlRK+SGohoqTQLltwN5Tkw4xH48hHwCoabl5smpo7YPCE4EUZfD+f9HlJWQMbazk3g8/AzQ3Cn3Av+cabW4e5jmreufh1qimHJT80w4JABcN17JrCEDoTrPzBDeKUJS4heIzPRRVuHd8DLPzId2B6+cNMyiBxx7Ovqq81EPp+wlunOqCxoCgJH0qVZ4B9t8pqnhRC9Qmaii+NXUwIO13BcRy1UFx1/P8iRGkfzdGe0NwS3ecCQ4CHESUP6QERLR5qwPHzMbG57kOnLKM089rVCiDOK1EBES/7RplNaOyFyJFz/vkkfrf9DCHFGkgAi2ooY1n5aCCGakSYsIYQQXSIBRAghRJdIABFCCNElEkCEEEJ0iQQQIYQQXSIBRAghRJecUUuZKKXygUrgZF1xLwQpW1dI2TrvZC0XSNm6qifLFq+1Dm2deUYFEACl1Ib21nQ5GUjZukbK1nkna7lAytZVfVE2acISQgjRJRJAhBBCdMmZGEAW9nUBjkLK1jVSts47WcsFUrau6vWynXF9IEIIIbrHmVgDEUII0Q0kgAghhOiS0zKAKKWuVErtVEo1KKU6HNamlLpIKbVXKbVfKfVAs/wgpdTnSqkU17+B3Vi2Y95bKTVQKbWl2U+ZUurnrmMPK6Wymh2b3Ztlc52XppTa7nr+DZ29vqfKppSKVUp9rZTa7fr7/6zZsW593Tp67zQ7rpRST7uOb1NKjTnea0/UcZTtOleZtiml1iilRjY71u7fthfLNl0pVdrs7/T74722F8p2X7Ny7VBKOZVSQa5jPfa6KaX+p5TKU0rt6OB4n73X0Fqfdj/AYGAg8A0wroNz3IBUoD/gDmwFhriOPQ484Eo/ADzWjWXr1L1d5TyMmcgD8DDw6x563Y6rbEAaEHKiv1t3lw2IBMa40r7AvmZ/02573Y723ml2zmzgU0ABE4G1x3ttL5RtMhDoSs86Uraj/W17sWzTgY+7cm1Pl63V+ZcAX/XS63YOMAbY0cHxPnmvaa1PzxqI1nq31nrvMU6bAOzXWh/QWtcBi4C5rmNzgVdc6VeAS7uxeJ299/lAqtb6UDeWoSMn+nv36eumtc7RWm9ypcuB3UBPbKJ+tPdO8/K+qo0fgAClVORxXtujZdNar9FaF7se/gDEdOPzn1DZeujanrj/NcBb3fj8HdJarwSKjnJKX73XTs8AcpyigYxmjzNp+rAJ11rngPlQAsK68Xk7e+/5tH2j3uOqqv6vO5uJOlE2DXymlNqolFrQhet7smwAKKX6AaOBtc2yu+t1O9p751jnHM+1J6Kz978V8+31iI7+tr1ZtklKqa1KqU+VUkM7eW1Plw2llBdwEfB+s+yefN2Opa/ea6fulrZKqS+AiHYOPaS1XnI8t2gnr1vGNB+tbJ28jzswB3iwWfa/gT9iyvpH4O/ALb1ctila62ylVBjwuVJqj+tb0gnpxtfNB/Of++da6zJX9gm9bq2fop281u+djs7psffdMZ637YlKnYsJIFObZffI37YTZduEaa6tcPVTfQgkHee1PV22Iy4BvtNaN68V9OTrdix99V47dQOI1nrGCd4iE4ht9jgGyHalc5VSkVrrHFdVMK+7yqaU6sy9ZwGbtNa5ze7dmFZKPQ983Ntl01pnu/7NU0p9gKkqr+QkeN2UUjZM8HhDa7242b1P6HVr5WjvnWOd434c156I4ykbSqkRwAvALK114ZH8o/xte6VszQI+WutlSqnnlFIhx3NtT5etmTatAj38uh1LX73XzugmrPVAklIqwfVNfz6w1HVsKXCjK30jcDw1muPVmXu3aWd1fXgecRnQ7siMniqbUspbKeV7JA3MbFaGPn3dlFIKeBHYrbV+stWx7nzdjvbeaV7eH7tGyEwESl1Nb8dz7Yk45v2VUnHAYuAGrfW+ZvlH+9v2VtkiXH9HlFITMJ9RhcdzbU+XzVUmf2Aazd5/vfC6HUtfvddO21FYl2Gici2QC6xw5UcBy5qdNxszUicV0/R1JD8Y+BJIcf0b1I1la/fe7ZTNC/Mfx7/V9a8B24FtrjdDZG+WDTOiY6vrZ+fJ9LphmmK067XZ4vqZ3ROvW3vvHeBO4E5XWgHPuo5vp9lowI7ed934Wh2rbC8Axc1eow3H+tv2YtnucT33VkwH/+ST5XVzPb4JWNTquh593TBfInOAeszn2q0ny3tNljIRQgjRJWdyE5YQQogTIAFECCFEl0gAEUII0SUSQIQQQnSJBBAhhBBdIgFEiD7W4yumCtFDZBivEH1IKeWGGad/AWaM/3rgGq31rj4tmBDHQWogQvStHl8xVYieIgFEiL7V4yumCtFTJIAI0bd6fMVUIXqKBBAh+lZPrzIrRI+RACJE3+r5FVOF6CGn7H4gQpwOtNYOpdQ9wArMHtb/01rv7ONiCXFcZBivEEKILpEmLCGEEF0iAUQIIUSXSAARQgjRJRJAhBBCdIkEECGEEF0iAUQIIUSXSAARQgjRJf8fHJ1f4oNUtCcAAAAASUVORK5CYII=\n", "text/plain": [ "<Figure size 432x288 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "sns.scatterplot(data=df_2d, x='0', y='1', hue=Y, style=Y)\n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.059658, "end_time": "2021-02-27T01:00:59.330139", "exception": false, "start_time": "2021-02-27T01:00:59.270481", "status": "completed" }, "tags": [] }, "source": [ "<a id=\"class\"></a>\n", "\n", "-----\n", "\n", "# Classificação\n", "\n", "- Conjunto de dados.\n", "- Experimentos.\n", "\n", "[Voltar para o Topo](#top)" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:00:59.457361Z", "iopub.status.busy": "2021-02-27T01:00:59.456319Z", "iopub.status.idle": "2021-02-27T01:00:59.462720Z", "shell.execute_reply": "2021-02-27T01:00:59.462140Z" }, "papermill": { "duration": 0.073578, "end_time": "2021-02-27T01:00:59.462878", "exception": false, "start_time": "2021-02-27T01:00:59.389300", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "# métricas\n", "from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "_kg_hide-input": true, "_kg_hide-output": true, "execution": { "iopub.execute_input": "2021-02-27T01:00:59.585419Z", "iopub.status.busy": "2021-02-27T01:00:59.584770Z", "iopub.status.idle": "2021-02-27T01:00:59.588018Z", "shell.execute_reply": "2021-02-27T01:00:59.587438Z" }, "papermill": { "duration": 0.066726, "end_time": "2021-02-27T01:00:59.588164", "exception": false, "start_time": "2021-02-27T01:00:59.521438", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "# variável de resultado final\n", "# será armazenado o resultado de todos experimentos\n", "experiment = {}" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.058938, "end_time": "2021-02-27T01:00:59.705852", "exception": false, "start_time": "2021-02-27T01:00:59.646914", "status": "completed" }, "tags": [] }, "source": [ "## Conjunto de Dados\n", "\n", "Separa os conjuntos de treinamento e teste." ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:00:59.829661Z", "iopub.status.busy": "2021-02-27T01:00:59.829034Z", "iopub.status.idle": "2021-02-27T01:00:59.832294Z", "shell.execute_reply": "2021-02-27T01:00:59.831807Z" }, "papermill": { "duration": 0.067035, "end_time": "2021-02-27T01:00:59.832434", "exception": false, "start_time": "2021-02-27T01:00:59.765399", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "# treinamento, test split\n", "from sklearn.model_selection import train_test_split" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:00:59.956991Z", "iopub.status.busy": "2021-02-27T01:00:59.956343Z", "iopub.status.idle": "2021-02-27T01:00:59.958889Z", "shell.execute_reply": "2021-02-27T01:00:59.959478Z" }, "papermill": { "duration": 0.067994, "end_time": "2021-02-27T01:00:59.959671", "exception": false, "start_time": "2021-02-27T01:00:59.891677", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "X_train, X_test, y_train, y_test = train_test_split(X, Y, test_size=0.3, random_state=26)" ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "_kg_hide-input": true, "execution": { "iopub.execute_input": "2021-02-27T01:01:00.081797Z", "iopub.status.busy": "2021-02-27T01:01:00.081093Z", "iopub.status.idle": "2021-02-27T01:01:00.087511Z", "shell.execute_reply": "2021-02-27T01:01:00.088374Z" }, "papermill": { "duration": 0.069079, "end_time": "2021-02-27T01:01:00.088621", "exception": false, "start_time": "2021-02-27T01:01:00.019542", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "treinamento: 212\n", "teste : 91\n" ] } ], "source": [ "print('treinamento:', len(y_train))\n", "print('teste :', len(y_test))" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.060564, "end_time": "2021-02-27T01:01:00.210793", "exception": false, "start_time": "2021-02-27T01:01:00.150229", "status": "completed" }, "tags": [] }, "source": [ "<a id=\"knn\"></a>\n", "\n", "## K-NN\n", "\n", "_(k-Nearest Neighbors)_" ] }, { "cell_type": "code", "execution_count": 16, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:01:00.333720Z", "iopub.status.busy": "2021-02-27T01:01:00.332978Z", "iopub.status.idle": "2021-02-27T01:01:00.393899Z", "shell.execute_reply": "2021-02-27T01:01:00.393072Z" }, "papermill": { "duration": 0.123911, "end_time": "2021-02-27T01:01:00.394101", "exception": false, "start_time": "2021-02-27T01:01:00.270190", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "# classificador\n", "from sklearn.neighbors import KNeighborsClassifier" ] }, { "cell_type": "code", "execution_count": 17, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:01:00.544818Z", "iopub.status.busy": "2021-02-27T01:01:00.543767Z", "iopub.status.idle": "2021-02-27T01:01:00.551309Z", "shell.execute_reply": "2021-02-27T01:01:00.550636Z" }, "papermill": { "duration": 0.086379, "end_time": "2021-02-27T01:01:00.551452", "exception": false, "start_time": "2021-02-27T01:01:00.465073", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "KNeighborsClassifier(n_neighbors=3)" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "model1 = KNeighborsClassifier(n_neighbors=3)\n", "model1.fit(X_train, y_train)" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.059876, "end_time": "2021-02-27T01:01:00.671862", "exception": false, "start_time": "2021-02-27T01:01:00.611986", "status": "completed" }, "tags": [] }, "source": [ "### Avaliação" ] }, { "cell_type": "code", "execution_count": 18, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:01:00.799515Z", "iopub.status.busy": "2021-02-27T01:01:00.798434Z", "iopub.status.idle": "2021-02-27T01:01:00.808370Z", "shell.execute_reply": "2021-02-27T01:01:00.807733Z" }, "papermill": { "duration": 0.076204, "end_time": "2021-02-27T01:01:00.808525", "exception": false, "start_time": "2021-02-27T01:01:00.732321", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "y_pred = model1.predict(X_test)" ] }, { "cell_type": "code", "execution_count": 19, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:01:00.938522Z", "iopub.status.busy": "2021-02-27T01:01:00.937472Z", "iopub.status.idle": "2021-02-27T01:01:00.945654Z", "shell.execute_reply": "2021-02-27T01:01:00.945101Z" }, "papermill": { "duration": 0.075578, "end_time": "2021-02-27T01:01:00.945834", "exception": false, "start_time": "2021-02-27T01:01:00.870256", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "acc = accuracy_score(y_pred, y_test)\n", "pre = precision_score(y_pred, y_test)\n", "rec = recall_score(y_pred, y_test)\n", "f1 = f1_score(y_pred, y_test)" ] }, { "cell_type": "code", "execution_count": 20, "metadata": { "_kg_hide-input": true, "execution": { "iopub.execute_input": "2021-02-27T01:01:01.074879Z", "iopub.status.busy": "2021-02-27T01:01:01.073655Z", "iopub.status.idle": "2021-02-27T01:01:01.079561Z", "shell.execute_reply": "2021-02-27T01:01:01.078854Z" }, "papermill": { "duration": 0.072691, "end_time": "2021-02-27T01:01:01.079728", "exception": false, "start_time": "2021-02-27T01:01:01.007037", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "acurácia : 0.7912087912087912\n", "precisão : 0.8823529411764706\n", "revocação: 0.7758620689655172\n", "f1-score : 0.8256880733944953\n" ] } ], "source": [ "experiment['KNN'] = {'acc':acc, 'pre':pre, 'rec':rec, 'f1':f1}\n", "\n", "print('acurácia :', acc)\n", "print('precisão :', pre)\n", "print('revocação:', rec)\n", "print('f1-score :', f1)" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.060765, "end_time": "2021-02-27T01:01:01.201402", "exception": false, "start_time": "2021-02-27T01:01:01.140637", "status": "completed" }, "tags": [] }, "source": [ "Discussão k-NN\n", "\n", "O k-NN conseguiu classificar bem o conjunto de dados, alcançando resultados satisfatórios. \n", "Acurácia de 79% e F1-score de 82%.\n", "\n", "-----" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.061775, "end_time": "2021-02-27T01:01:01.324053", "exception": false, "start_time": "2021-02-27T01:01:01.262278", "status": "completed" }, "tags": [] }, "source": [ "<a id=\"naive\"></a>\n", "\n", "## Naive Bayes" ] }, { "cell_type": "code", "execution_count": 21, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:01:01.451335Z", "iopub.status.busy": "2021-02-27T01:01:01.450657Z", "iopub.status.idle": "2021-02-27T01:01:01.458318Z", "shell.execute_reply": "2021-02-27T01:01:01.457559Z" }, "papermill": { "duration": 0.072423, "end_time": "2021-02-27T01:01:01.458468", "exception": false, "start_time": "2021-02-27T01:01:01.386045", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "# classificador\n", "from sklearn.naive_bayes import GaussianNB" ] }, { "cell_type": "code", "execution_count": 22, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:01:01.588674Z", "iopub.status.busy": "2021-02-27T01:01:01.587363Z", "iopub.status.idle": "2021-02-27T01:01:01.593734Z", "shell.execute_reply": "2021-02-27T01:01:01.593019Z" }, "papermill": { "duration": 0.073574, "end_time": "2021-02-27T01:01:01.593887", "exception": false, "start_time": "2021-02-27T01:01:01.520313", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "GaussianNB()" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" } ], "source": [ "model2 = GaussianNB()\n", "model2.fit(X_train, y_train)" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.061199, "end_time": "2021-02-27T01:01:01.720588", "exception": false, "start_time": "2021-02-27T01:01:01.659389", "status": "completed" }, "tags": [] }, "source": [ "### Avaliação" ] }, { "cell_type": "code", "execution_count": 23, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:01:01.850987Z", "iopub.status.busy": "2021-02-27T01:01:01.850297Z", "iopub.status.idle": "2021-02-27T01:01:01.853151Z", "shell.execute_reply": "2021-02-27T01:01:01.853657Z" }, "papermill": { "duration": 0.071363, "end_time": "2021-02-27T01:01:01.853856", "exception": false, "start_time": "2021-02-27T01:01:01.782493", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "y_pred = model2.predict(X_test)" ] }, { "cell_type": "code", "execution_count": 24, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:01:01.988747Z", "iopub.status.busy": "2021-02-27T01:01:01.987681Z", "iopub.status.idle": "2021-02-27T01:01:01.991011Z", "shell.execute_reply": "2021-02-27T01:01:01.990451Z" }, "papermill": { "duration": 0.074266, "end_time": "2021-02-27T01:01:01.991171", "exception": false, "start_time": "2021-02-27T01:01:01.916905", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "acc = accuracy_score(y_pred, y_test)\n", "pre = precision_score(y_pred, y_test)\n", "rec = recall_score(y_pred, y_test)\n", "f1 = f1_score(y_pred, y_test)" ] }, { "cell_type": "code", "execution_count": 25, "metadata": { "_kg_hide-input": true, "execution": { "iopub.execute_input": "2021-02-27T01:01:02.123782Z", "iopub.status.busy": "2021-02-27T01:01:02.122565Z", "iopub.status.idle": "2021-02-27T01:01:02.129127Z", "shell.execute_reply": "2021-02-27T01:01:02.129685Z" }, "papermill": { "duration": 0.076828, "end_time": "2021-02-27T01:01:02.129901", "exception": false, "start_time": "2021-02-27T01:01:02.053073", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "acurácia : 0.7472527472527473\n", "precisão : 0.7843137254901961\n", "revocação: 0.7692307692307693\n", "f1-score : 0.7766990291262137\n" ] } ], "source": [ "experiment['Naive Bayes'] = {'acc':acc, 'pre':pre, 'rec':rec, 'f1':f1}\n", "\n", "print('acurácia :', acc)\n", "print('precisão :', pre)\n", "print('revocação:', rec)\n", "print('f1-score :', f1)" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.064702, "end_time": "2021-02-27T01:01:02.261092", "exception": false, "start_time": "2021-02-27T01:01:02.196390", "status": "completed" }, "tags": [] }, "source": [ "Discussão Naive Bayes\n", "\n", "Neste conjunto de dados, o Naive Bayes teve um desempenho inferior ao k-NN. \n", "Contudo, apresentou uma acurácia de 74% e F1-Score de 77%.\n", "\n", "-----" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.061868, "end_time": "2021-02-27T01:01:02.385451", "exception": false, "start_time": "2021-02-27T01:01:02.323583", "status": "completed" }, "tags": [] }, "source": [ "<a id=\"svm\"></a>\n", "\n", "## Support Vector Machines (SVM)" ] }, { "cell_type": "code", "execution_count": 26, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:01:02.514452Z", "iopub.status.busy": "2021-02-27T01:01:02.513779Z", "iopub.status.idle": "2021-02-27T01:01:02.517320Z", "shell.execute_reply": "2021-02-27T01:01:02.516625Z" }, "papermill": { "duration": 0.070033, "end_time": "2021-02-27T01:01:02.517466", "exception": false, "start_time": "2021-02-27T01:01:02.447433", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "# classificador\n", "from sklearn.svm import SVC" ] }, { "cell_type": "code", "execution_count": 27, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:01:02.648659Z", "iopub.status.busy": "2021-02-27T01:01:02.648011Z", "iopub.status.idle": "2021-02-27T01:01:02.654841Z", "shell.execute_reply": "2021-02-27T01:01:02.654312Z" }, "papermill": { "duration": 0.074515, "end_time": "2021-02-27T01:01:02.654993", "exception": false, "start_time": "2021-02-27T01:01:02.580478", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "SVC()" ] }, "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ "model3 = SVC()\n", "model3.fit(X_train, y_train)" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.062097, "end_time": "2021-02-27T01:01:02.780778", "exception": false, "start_time": "2021-02-27T01:01:02.718681", "status": "completed" }, "tags": [] }, "source": [ "### Avaliação" ] }, { "cell_type": "code", "execution_count": 28, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:01:02.915249Z", "iopub.status.busy": "2021-02-27T01:01:02.914360Z", "iopub.status.idle": "2021-02-27T01:01:02.917116Z", "shell.execute_reply": "2021-02-27T01:01:02.916553Z" }, "papermill": { "duration": 0.072098, "end_time": "2021-02-27T01:01:02.917276", "exception": false, "start_time": "2021-02-27T01:01:02.845178", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "y_pred = model3.predict(X_test)" ] }, { "cell_type": "code", "execution_count": 29, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:01:03.053608Z", "iopub.status.busy": "2021-02-27T01:01:03.052969Z", "iopub.status.idle": "2021-02-27T01:01:03.060310Z", "shell.execute_reply": "2021-02-27T01:01:03.060858Z" }, "papermill": { "duration": 0.078693, "end_time": "2021-02-27T01:01:03.061049", "exception": false, "start_time": "2021-02-27T01:01:02.982356", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "acc = accuracy_score(y_pred, y_test)\n", "pre = precision_score(y_pred, y_test)\n", "rec = recall_score(y_pred, y_test)\n", "f1 = f1_score(y_pred, y_test)" ] }, { "cell_type": "code", "execution_count": 30, "metadata": { "_kg_hide-input": true, "execution": { "iopub.execute_input": "2021-02-27T01:01:03.195189Z", "iopub.status.busy": "2021-02-27T01:01:03.194511Z", "iopub.status.idle": "2021-02-27T01:01:03.200458Z", "shell.execute_reply": "2021-02-27T01:01:03.199837Z" }, "papermill": { "duration": 0.07676, "end_time": "2021-02-27T01:01:03.200616", "exception": false, "start_time": "2021-02-27T01:01:03.123856", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "acurácia : 0.7912087912087912\n", "precisão : 0.9019607843137255\n", "revocação: 0.7666666666666667\n", "f1-score : 0.8288288288288289\n" ] } ], "source": [ "experiment['SVM'] = {'acc':acc, 'pre':pre, 'rec':rec, 'f1':f1}\n", "\n", "print('acurácia :', acc)\n", "print('precisão :', pre)\n", "print('revocação:', rec)\n", "print('f1-score :', f1)" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.062964, "end_time": "2021-02-27T01:01:03.327503", "exception": false, "start_time": "2021-02-27T01:01:03.264539", "status": "completed" }, "tags": [] }, "source": [ "Discussão Support Vector Machines (SVM)\n", "\n", "O SVM foi o melhor modelo até o momento. \n", "Ultrapassando o k-NN, com acurácia de 79% e F1-score de 82%.\n", "\n", "-----" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.063047, "end_time": "2021-02-27T01:01:03.453927", "exception": false, "start_time": "2021-02-27T01:01:03.390880", "status": "completed" }, "tags": [] }, "source": [ "<a id=\"decision\"></a>\n", "\n", "## Árvore de Decisão" ] }, { "cell_type": "code", "execution_count": 31, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:01:03.584815Z", "iopub.status.busy": "2021-02-27T01:01:03.584123Z", "iopub.status.idle": "2021-02-27T01:01:03.626782Z", "shell.execute_reply": "2021-02-27T01:01:03.627312Z" }, "papermill": { "duration": 0.110475, "end_time": "2021-02-27T01:01:03.627487", "exception": false, "start_time": "2021-02-27T01:01:03.517012", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "# classificador\n", "from sklearn.tree import DecisionTreeClassifier" ] }, { "cell_type": "code", "execution_count": 32, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:01:03.765354Z", "iopub.status.busy": "2021-02-27T01:01:03.761418Z", "iopub.status.idle": "2021-02-27T01:01:03.770064Z", "shell.execute_reply": "2021-02-27T01:01:03.769416Z" }, "papermill": { "duration": 0.078124, "end_time": "2021-02-27T01:01:03.770213", "exception": false, "start_time": "2021-02-27T01:01:03.692089", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "DecisionTreeClassifier(random_state=26)" ] }, "execution_count": 32, "metadata": {}, "output_type": "execute_result" } ], "source": [ "model4 = DecisionTreeClassifier(random_state=26)\n", "model4.fit(X_train, y_train)" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.063827, "end_time": "2021-02-27T01:01:03.899301", "exception": false, "start_time": "2021-02-27T01:01:03.835474", "status": "completed" }, "tags": [] }, "source": [ "### Avaliação" ] }, { "cell_type": "code", "execution_count": 33, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:01:04.034624Z", "iopub.status.busy": "2021-02-27T01:01:04.033771Z", "iopub.status.idle": "2021-02-27T01:01:04.037843Z", "shell.execute_reply": "2021-02-27T01:01:04.037087Z" }, "papermill": { "duration": 0.074333, "end_time": "2021-02-27T01:01:04.037998", "exception": false, "start_time": "2021-02-27T01:01:03.963665", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "y_pred = model4.predict(X_test)" ] }, { "cell_type": "code", "execution_count": 34, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:01:04.175479Z", "iopub.status.busy": "2021-02-27T01:01:04.174643Z", "iopub.status.idle": "2021-02-27T01:01:04.181729Z", "shell.execute_reply": "2021-02-27T01:01:04.181103Z" }, "papermill": { "duration": 0.079414, "end_time": "2021-02-27T01:01:04.181885", "exception": false, "start_time": "2021-02-27T01:01:04.102471", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "acc = accuracy_score(y_pred, y_test)\n", "pre = precision_score(y_pred, y_test)\n", "rec = recall_score(y_pred, y_test)\n", "f1 = f1_score(y_pred, y_test)" ] }, { "cell_type": "code", "execution_count": 35, "metadata": { "_kg_hide-input": true, "execution": { "iopub.execute_input": "2021-02-27T01:01:04.318054Z", "iopub.status.busy": "2021-02-27T01:01:04.316852Z", "iopub.status.idle": "2021-02-27T01:01:04.322394Z", "shell.execute_reply": "2021-02-27T01:01:04.322962Z" }, "papermill": { "duration": 0.076795, "end_time": "2021-02-27T01:01:04.323176", "exception": false, "start_time": "2021-02-27T01:01:04.246381", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "acurácia : 0.6813186813186813\n", "precisão : 0.6862745098039216\n", "revocação: 0.7291666666666666\n", "f1-score : 0.7070707070707071\n" ] } ], "source": [ "experiment['Decision Tree'] = {'acc':acc, 'pre':pre, 'rec':rec, 'f1':f1}\n", "\n", "print('acurácia :', acc)\n", "print('precisão :', pre)\n", "print('revocação:', rec)\n", "print('f1-score :', f1)" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.06518, "end_time": "2021-02-27T01:01:04.454420", "exception": false, "start_time": "2021-02-27T01:01:04.389240", "status": "completed" }, "tags": [] }, "source": [ "### Visualização\n", "\n", "Nós conseguimos visualizar a árvore de decisão, como as ramificações ocorreram. \n", "É muito útil para uma apresentação de negócio, em que você consegue explicar a inteligência induzida." ] }, { "cell_type": "code", "execution_count": 36, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:01:04.593867Z", "iopub.status.busy": "2021-02-27T01:01:04.593163Z", "iopub.status.idle": "2021-02-27T01:01:04.596950Z", "shell.execute_reply": "2021-02-27T01:01:04.596251Z" }, "papermill": { "duration": 0.074817, "end_time": "2021-02-27T01:01:04.597134", "exception": false, "start_time": "2021-02-27T01:01:04.522317", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "# visualizador da árvore\n", "from sklearn.tree import plot_tree" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.072581, "end_time": "2021-02-27T01:01:04.742461", "exception": false, "start_time": "2021-02-27T01:01:04.669880", "status": "completed" }, "tags": [] }, "source": [ "Visualizando a árvore inteira." ] }, { "cell_type": "code", "execution_count": 37, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:01:04.902610Z", "iopub.status.busy": "2021-02-27T01:01:04.900830Z", "iopub.status.idle": "2021-02-27T01:01:07.717508Z", "shell.execute_reply": "2021-02-27T01:01:07.718057Z" }, "papermill": { "duration": 2.903143, "end_time": "2021-02-27T01:01:07.718231", "exception": false, "start_time": "2021-02-27T01:01:04.815088", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 720x432 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(10,6))\n", "_ = plot_tree(model4) \n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.066765, "end_time": "2021-02-27T01:01:07.851933", "exception": false, "start_time": "2021-02-27T01:01:07.785168", "status": "completed" }, "tags": [] }, "source": [ "Visualizando a primeira profundidade, apenas para observarmos os valores presentes na figura.\n", "\n", "> Na figura vemos: (1) O atributo selecionado e a questão (condição de separação) (nota, este nome pode ser personalizado); (2) a métrica de impureza; (3) número de exemplos; (4) número de exemplo para cada classe; e (5) a cor significa a classe majoritária do respectivo nó." ] }, { "cell_type": "code", "execution_count": 38, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:01:07.996873Z", "iopub.status.busy": "2021-02-27T01:01:07.996200Z", "iopub.status.idle": "2021-02-27T01:01:08.313399Z", "shell.execute_reply": "2021-02-27T01:01:08.313923Z" }, "papermill": { "duration": 0.388832, "end_time": "2021-02-27T01:01:08.314118", "exception": false, "start_time": "2021-02-27T01:01:07.925286", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 720x432 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(10,6))\n", "_ = plot_tree(model4, max_depth=1) \n", "plt.show()" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.067217, "end_time": "2021-02-27T01:01:08.449536", "exception": false, "start_time": "2021-02-27T01:01:08.382319", "status": "completed" }, "tags": [] }, "source": [ "Discussão Árvore de Decisão\n", "\n", "A Árvore de Decisão obteve resultados razoáveis. \n", "Com acurácia de 68% e F1-score de 70%, abaixo do k-NN. \n", "\n", "São excelente algoritmos de Aprendizado de Máquina para compreensão/estudo do negócio.\n", "\n", "-----" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.06736, "end_time": "2021-02-27T01:01:08.584368", "exception": false, "start_time": "2021-02-27T01:01:08.517008", "status": "completed" }, "tags": [] }, "source": [ "<a id=\"forest\"></a>\n", "\n", "## Random Forest" ] }, { "cell_type": "code", "execution_count": 39, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:01:08.730453Z", "iopub.status.busy": "2021-02-27T01:01:08.729509Z", "iopub.status.idle": "2021-02-27T01:01:08.761606Z", "shell.execute_reply": "2021-02-27T01:01:08.762195Z" }, "papermill": { "duration": 0.110039, "end_time": "2021-02-27T01:01:08.762376", "exception": false, "start_time": "2021-02-27T01:01:08.652337", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "# classificador\n", "from sklearn.ensemble import RandomForestClassifier" ] }, { "cell_type": "code", "execution_count": 40, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:01:08.904780Z", "iopub.status.busy": "2021-02-27T01:01:08.904130Z", "iopub.status.idle": "2021-02-27T01:01:09.106244Z", "shell.execute_reply": "2021-02-27T01:01:09.106717Z" }, "papermill": { "duration": 0.275401, "end_time": "2021-02-27T01:01:09.106899", "exception": false, "start_time": "2021-02-27T01:01:08.831498", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "RandomForestClassifier(random_state=26)" ] }, "execution_count": 40, "metadata": {}, "output_type": "execute_result" } ], "source": [ "model5 = RandomForestClassifier(n_estimators=100, random_state=26)\n", "model5.fit(X_train, y_train)" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.068431, "end_time": "2021-02-27T01:01:09.244277", "exception": false, "start_time": "2021-02-27T01:01:09.175846", "status": "completed" }, "tags": [] }, "source": [ "### Avaliação" ] }, { "cell_type": "code", "execution_count": 41, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:01:09.384945Z", "iopub.status.busy": "2021-02-27T01:01:09.384208Z", "iopub.status.idle": "2021-02-27T01:01:09.398877Z", "shell.execute_reply": "2021-02-27T01:01:09.399371Z" }, "papermill": { "duration": 0.086684, "end_time": "2021-02-27T01:01:09.399590", "exception": false, "start_time": "2021-02-27T01:01:09.312906", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "y_pred = model5.predict(X_test)" ] }, { "cell_type": "code", "execution_count": 42, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:01:09.541977Z", "iopub.status.busy": "2021-02-27T01:01:09.541246Z", "iopub.status.idle": "2021-02-27T01:01:09.549480Z", "shell.execute_reply": "2021-02-27T01:01:09.550072Z" }, "papermill": { "duration": 0.081068, "end_time": "2021-02-27T01:01:09.550270", "exception": false, "start_time": "2021-02-27T01:01:09.469202", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "acc = accuracy_score(y_pred, y_test)\n", "pre = precision_score(y_pred, y_test)\n", "rec = recall_score(y_pred, y_test)\n", "f1 = f1_score(y_pred, y_test)" ] }, { "cell_type": "code", "execution_count": 43, "metadata": { "_kg_hide-input": true, "execution": { "iopub.execute_input": "2021-02-27T01:01:09.692382Z", "iopub.status.busy": "2021-02-27T01:01:09.691715Z", "iopub.status.idle": "2021-02-27T01:01:09.699356Z", "shell.execute_reply": "2021-02-27T01:01:09.698786Z" }, "papermill": { "duration": 0.079513, "end_time": "2021-02-27T01:01:09.699507", "exception": false, "start_time": "2021-02-27T01:01:09.619994", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "acurácia : 0.7582417582417582\n", "precisão : 0.8235294117647058\n", "revocação: 0.7636363636363637\n", "f1-score : 0.7924528301886793\n" ] } ], "source": [ "experiment['Random Forest'] = {'acc':acc, 'pre':pre, 'rec':rec, 'f1':f1}\n", "\n", "print('acurácia :', acc)\n", "print('precisão :', pre)\n", "print('revocação:', rec)\n", "print('f1-score :', f1)" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.069557, "end_time": "2021-02-27T01:01:09.839406", "exception": false, "start_time": "2021-02-27T01:01:09.769849", "status": "completed" }, "tags": [] }, "source": [ "### Visualização\n", "\n", "Também é possível extrar as `DecisionTree`do `RandomForest` para visualização. Neste caso, é necessário acessar cada uma das árvores utilizando o comando `RandomForest.estimators_[indice]` e visualizar como demonstrado na seção da Árvore de Decisão." ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.080389, "end_time": "2021-02-27T01:01:09.989202", "exception": false, "start_time": "2021-02-27T01:01:09.908813", "status": "completed" }, "tags": [] }, "source": [ "Discussão Random Forest\n", "\n", "Random Forest obteve um dos melhores resultados. \n", "Com acurácia de 75% e F1-score de 79%, abaixo do k-NN. \n", "\n", "Random Forests são um dos algoritmos mais utilizados em competições de Aprendizado de Máquina.\n", "\n", "> Nota. Possui alto custo computacional, pois tem que treinar vários modelos.\n", "\n", "-----" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.07406, "end_time": "2021-02-27T01:01:10.145739", "exception": false, "start_time": "2021-02-27T01:01:10.071679", "status": "completed" }, "tags": [] }, "source": [ "<a id=\"bagging\"></a>\n", "\n", "## Bagging\n", "\n", "Classificação com estratégia de Bagging, com algoritmo base SVM." ] }, { "cell_type": "code", "execution_count": 44, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:01:10.289735Z", "iopub.status.busy": "2021-02-27T01:01:10.289045Z", "iopub.status.idle": "2021-02-27T01:01:10.291936Z", "shell.execute_reply": "2021-02-27T01:01:10.291346Z" }, "papermill": { "duration": 0.076852, "end_time": "2021-02-27T01:01:10.292091", "exception": false, "start_time": "2021-02-27T01:01:10.215239", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "# ensemble\n", "from sklearn.ensemble import BaggingClassifier" ] }, { "cell_type": "code", "execution_count": 45, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:01:10.438004Z", "iopub.status.busy": "2021-02-27T01:01:10.437163Z", "iopub.status.idle": "2021-02-27T01:01:10.476988Z", "shell.execute_reply": "2021-02-27T01:01:10.476372Z" }, "papermill": { "duration": 0.115569, "end_time": "2021-02-27T01:01:10.477139", "exception": false, "start_time": "2021-02-27T01:01:10.361570", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "BaggingClassifier(base_estimator=SVC(), random_state=26)" ] }, "execution_count": 45, "metadata": {}, "output_type": "execute_result" } ], "source": [ "model_base = SVC()\n", "model6 = BaggingClassifier(base_estimator=model_base, n_estimators=10, random_state=26)\n", "model6.fit(X_train, y_train)" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.069605, "end_time": "2021-02-27T01:01:10.616238", "exception": false, "start_time": "2021-02-27T01:01:10.546633", "status": "completed" }, "tags": [] }, "source": [ "### Avaliação" ] }, { "cell_type": "code", "execution_count": 46, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:01:10.763146Z", "iopub.status.busy": "2021-02-27T01:01:10.762280Z", "iopub.status.idle": "2021-02-27T01:01:10.772057Z", "shell.execute_reply": "2021-02-27T01:01:10.771300Z" }, "papermill": { "duration": 0.085746, "end_time": "2021-02-27T01:01:10.772220", "exception": false, "start_time": "2021-02-27T01:01:10.686474", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "y_pred = model6.predict(X_test)" ] }, { "cell_type": "code", "execution_count": 47, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:01:10.927935Z", "iopub.status.busy": "2021-02-27T01:01:10.925929Z", "iopub.status.idle": "2021-02-27T01:01:10.932933Z", "shell.execute_reply": "2021-02-27T01:01:10.932268Z" }, "papermill": { "duration": 0.082389, "end_time": "2021-02-27T01:01:10.933079", "exception": false, "start_time": "2021-02-27T01:01:10.850690", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "acc = accuracy_score(y_pred, y_test)\n", "pre = precision_score(y_pred, y_test)\n", "rec = recall_score(y_pred, y_test)\n", "f1 = f1_score(y_pred, y_test)" ] }, { "cell_type": "code", "execution_count": 48, "metadata": { "_kg_hide-input": true, "execution": { "iopub.execute_input": "2021-02-27T01:01:11.075934Z", "iopub.status.busy": "2021-02-27T01:01:11.075310Z", "iopub.status.idle": "2021-02-27T01:01:11.082373Z", "shell.execute_reply": "2021-02-27T01:01:11.083110Z" }, "papermill": { "duration": 0.080533, "end_time": "2021-02-27T01:01:11.083342", "exception": false, "start_time": "2021-02-27T01:01:11.002809", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "acurácia : 0.8241758241758241\n", "precisão : 0.8823529411764706\n", "revocação: 0.8181818181818182\n", "f1-score : 0.8490566037735848\n" ] } ], "source": [ "experiment['Bagging'] = {'acc':acc, 'pre':pre, 'rec':rec, 'f1':f1}\n", "\n", "print('acurácia :', acc)\n", "print('precisão :', pre)\n", "print('revocação:', rec)\n", "print('f1-score :', f1)" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.069938, "end_time": "2021-02-27T01:01:11.224455", "exception": false, "start_time": "2021-02-27T01:01:11.154517", "status": "completed" }, "tags": [] }, "source": [ "Discussão Bagging\n", "\n", "Bagging obteve o melhor resultado, utilizando 10 modelos SVM. \n", "Com acurácia de 82% e F1-score de 84%. \n", "\n", "> Nota. Possui alto custo computacional, pois tem que treinar vários modelos.\n", "\n", "-----" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.069718, "end_time": "2021-02-27T01:01:11.364559", "exception": false, "start_time": "2021-02-27T01:01:11.294841", "status": "completed" }, "tags": [] }, "source": [ "<a id=\"ensemble\"></a>\n", "\n", "## Ensemble\n", "\n", "Classificação com estratégia de Ensemble, utilizando os algoritmos SVM e Random Forest." ] }, { "cell_type": "code", "execution_count": 49, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:01:11.509976Z", "iopub.status.busy": "2021-02-27T01:01:11.509276Z", "iopub.status.idle": "2021-02-27T01:01:11.512823Z", "shell.execute_reply": "2021-02-27T01:01:11.512161Z" }, "papermill": { "duration": 0.078324, "end_time": "2021-02-27T01:01:11.512966", "exception": false, "start_time": "2021-02-27T01:01:11.434642", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "# ensemble\n", "from sklearn.ensemble import VotingClassifier" ] }, { "cell_type": "code", "execution_count": 50, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:01:11.663206Z", "iopub.status.busy": "2021-02-27T01:01:11.662364Z", "iopub.status.idle": "2021-02-27T01:01:11.867031Z", "shell.execute_reply": "2021-02-27T01:01:11.866442Z" }, "papermill": { "duration": 0.283257, "end_time": "2021-02-27T01:01:11.867177", "exception": false, "start_time": "2021-02-27T01:01:11.583920", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "VotingClassifier(estimators=[('SVM', SVC()),\n", " ('RandomForest',\n", " RandomForestClassifier(random_state=26))])" ] }, "execution_count": 50, "metadata": {}, "output_type": "execute_result" } ], "source": [ "clf1 = SVC()\n", "clf2 = RandomForestClassifier(n_estimators=100, random_state=26)\n", "\n", "model7 = VotingClassifier(estimators=[('SVM', clf1), ('RandomForest', clf2)], voting='hard')\n", "model7.fit(X_train, y_train)" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.071978, "end_time": "2021-02-27T01:01:12.010617", "exception": false, "start_time": "2021-02-27T01:01:11.938639", "status": "completed" }, "tags": [] }, "source": [ "### Avaliação" ] }, { "cell_type": "code", "execution_count": 51, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:01:12.159222Z", "iopub.status.busy": "2021-02-27T01:01:12.158303Z", "iopub.status.idle": "2021-02-27T01:01:12.175175Z", "shell.execute_reply": "2021-02-27T01:01:12.174550Z" }, "papermill": { "duration": 0.09307, "end_time": "2021-02-27T01:01:12.175330", "exception": false, "start_time": "2021-02-27T01:01:12.082260", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "y_pred = model7.predict(X_test)" ] }, { "cell_type": "code", "execution_count": 52, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:01:12.327038Z", "iopub.status.busy": "2021-02-27T01:01:12.326001Z", "iopub.status.idle": "2021-02-27T01:01:12.331182Z", "shell.execute_reply": "2021-02-27T01:01:12.331687Z" }, "papermill": { "duration": 0.085166, "end_time": "2021-02-27T01:01:12.331911", "exception": false, "start_time": "2021-02-27T01:01:12.246745", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "acc = accuracy_score(y_pred, y_test)\n", "pre = precision_score(y_pred, y_test)\n", "rec = recall_score(y_pred, y_test)\n", "f1 = f1_score(y_pred, y_test)" ] }, { "cell_type": "code", "execution_count": 53, "metadata": { "_kg_hide-input": true, "execution": { "iopub.execute_input": "2021-02-27T01:01:12.482565Z", "iopub.status.busy": "2021-02-27T01:01:12.481633Z", "iopub.status.idle": "2021-02-27T01:01:12.486315Z", "shell.execute_reply": "2021-02-27T01:01:12.485614Z" }, "papermill": { "duration": 0.082711, "end_time": "2021-02-27T01:01:12.486476", "exception": false, "start_time": "2021-02-27T01:01:12.403765", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "acurácia : 0.7802197802197802\n", "precisão : 0.8235294117647058\n", "revocação: 0.7924528301886793\n", "f1-score : 0.8076923076923077\n" ] } ], "source": [ "experiment['Ensemble'] = {'acc':acc, 'pre':pre, 'rec':rec, 'f1':f1}\n", "\n", "print('acurácia :', acc)\n", "print('precisão :', pre)\n", "print('revocação:', rec)\n", "print('f1-score :', f1)" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.072377, "end_time": "2021-02-27T01:01:12.631737", "exception": false, "start_time": "2021-02-27T01:01:12.559360", "status": "completed" }, "tags": [] }, "source": [ "Discussão Ensemble\n", "\n", "Ensemble obteve bons resultados, porém não o melhor. \n", "Com acurácia de 78% e F1-score de 80%. \n", "\n", "> Nota. Possui alto custo computacional, pois tem que treinar vários modelos.\n", "\n", "-----" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.071881, "end_time": "2021-02-27T01:01:12.777153", "exception": false, "start_time": "2021-02-27T01:01:12.705272", "status": "completed" }, "tags": [] }, "source": [ "# Conclusão\n", "\n", "Por fim, o melhor algoritmo foi o SVM com a mesma acurácia do KNN, mas com precisão e f1-score maiores. \n", "A estratégia de ensemble Bagging superou todos os classificadores, porém teve maior custo computacional." ] }, { "cell_type": "code", "execution_count": 54, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:01:12.937460Z", "iopub.status.busy": "2021-02-27T01:01:12.936739Z", "iopub.status.idle": "2021-02-27T01:01:12.941069Z", "shell.execute_reply": "2021-02-27T01:01:12.940516Z" }, "papermill": { "duration": 0.089874, "end_time": "2021-02-27T01:01:12.941224", "exception": false, "start_time": "2021-02-27T01:01:12.851350", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>acc</th>\n", " <th>pre</th>\n", " <th>rec</th>\n", " <th>f1</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>KNN</th>\n", " <td>0.791209</td>\n", " <td>0.882353</td>\n", " <td>0.775862</td>\n", " <td>0.825688</td>\n", " </tr>\n", " <tr>\n", " <th>Naive Bayes</th>\n", " <td>0.747253</td>\n", " <td>0.784314</td>\n", " <td>0.769231</td>\n", " <td>0.776699</td>\n", " </tr>\n", " <tr>\n", " <th>SVM</th>\n", " <td>0.791209</td>\n", " <td>0.901961</td>\n", " <td>0.766667</td>\n", " <td>0.828829</td>\n", " </tr>\n", " <tr>\n", " <th>Decision Tree</th>\n", " <td>0.681319</td>\n", " <td>0.686275</td>\n", " <td>0.729167</td>\n", " <td>0.707071</td>\n", " </tr>\n", " <tr>\n", " <th>Random Forest</th>\n", " <td>0.758242</td>\n", " <td>0.823529</td>\n", " <td>0.763636</td>\n", " <td>0.792453</td>\n", " </tr>\n", " <tr>\n", " <th>Bagging</th>\n", " <td>0.824176</td>\n", " <td>0.882353</td>\n", " <td>0.818182</td>\n", " <td>0.849057</td>\n", " </tr>\n", " <tr>\n", " <th>Ensemble</th>\n", " <td>0.780220</td>\n", " <td>0.823529</td>\n", " <td>0.792453</td>\n", " <td>0.807692</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " acc pre rec f1\n", "KNN 0.791209 0.882353 0.775862 0.825688\n", "Naive Bayes 0.747253 0.784314 0.769231 0.776699\n", "SVM 0.791209 0.901961 0.766667 0.828829\n", "Decision Tree 0.681319 0.686275 0.729167 0.707071\n", "Random Forest 0.758242 0.823529 0.763636 0.792453\n", "Bagging 0.824176 0.882353 0.818182 0.849057\n", "Ensemble 0.780220 0.823529 0.792453 0.807692" ] }, "execution_count": 54, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pd.DataFrame(experiment).T" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.073001, "end_time": "2021-02-27T01:01:13.086932", "exception": false, "start_time": "2021-02-27T01:01:13.013931", "status": "completed" }, "tags": [] }, "source": [ "<a id=\"tuning\"></a>\n", "\n", "-----\n", "\n", "# Hyperparameter Tuning\n", "\n", "[Random Search](https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.RandomizedSearchCV.html) no algoritmo SVM.\n", "\n", "[Voltar para o Topo](#top)" ] }, { "cell_type": "code", "execution_count": 55, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:01:13.236767Z", "iopub.status.busy": "2021-02-27T01:01:13.236104Z", "iopub.status.idle": "2021-02-27T01:01:13.238323Z", "shell.execute_reply": "2021-02-27T01:01:13.238854Z" }, "papermill": { "duration": 0.079822, "end_time": "2021-02-27T01:01:13.239063", "exception": false, "start_time": "2021-02-27T01:01:13.159241", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "# random search\n", "from sklearn.model_selection import RandomizedSearchCV\n", "# uniform distribution\n", "from scipy.stats import uniform" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.072233, "end_time": "2021-02-27T01:01:13.384527", "exception": false, "start_time": "2021-02-27T01:01:13.312294", "status": "completed" }, "tags": [] }, "source": [ "### Hiper-parâmetros\n", "\n", "Quais são os hiper-parâmetros do SVM?" ] }, { "cell_type": "code", "execution_count": 56, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:01:13.533069Z", "iopub.status.busy": "2021-02-27T01:01:13.532422Z", "iopub.status.idle": "2021-02-27T01:01:13.539460Z", "shell.execute_reply": "2021-02-27T01:01:13.538963Z" }, "papermill": { "duration": 0.082426, "end_time": "2021-02-27T01:01:13.539601", "exception": false, "start_time": "2021-02-27T01:01:13.457175", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "{'C': 1.0,\n", " 'break_ties': False,\n", " 'cache_size': 200,\n", " 'class_weight': None,\n", " 'coef0': 0.0,\n", " 'decision_function_shape': 'ovr',\n", " 'degree': 3,\n", " 'gamma': 'scale',\n", " 'kernel': 'rbf',\n", " 'max_iter': -1,\n", " 'probability': False,\n", " 'random_state': None,\n", " 'shrinking': True,\n", " 'tol': 0.001,\n", " 'verbose': False}" ] }, "execution_count": 56, "metadata": {}, "output_type": "execute_result" } ], "source": [ "model = SVC()\n", "model.get_params()" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.072816, "end_time": "2021-02-27T01:01:13.685961", "exception": false, "start_time": "2021-02-27T01:01:13.613145", "status": "completed" }, "tags": [] }, "source": [ "Escolhendo uma distribuição dos parâmetros, _i.e.,_ um espaço de busca." ] }, { "cell_type": "code", "execution_count": 57, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:01:13.839740Z", "iopub.status.busy": "2021-02-27T01:01:13.838986Z", "iopub.status.idle": "2021-02-27T01:01:13.842004Z", "shell.execute_reply": "2021-02-27T01:01:13.841497Z" }, "papermill": { "duration": 0.082947, "end_time": "2021-02-27T01:01:13.842162", "exception": false, "start_time": "2021-02-27T01:01:13.759215", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "distributions = {\n", " 'random_state':[26],\n", " 'C':uniform(loc=1, scale=9),\n", " 'kernel': ['rbf', 'sigmoid'],\n", "}" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.074825, "end_time": "2021-02-27T01:01:13.991585", "exception": false, "start_time": "2021-02-27T01:01:13.916760", "status": "completed" }, "tags": [] }, "source": [ "### Busca / Tuning\n", "\n", "Executando a tunagem de parâmetros pelo espaço pré-fixado, utilizando 10-fold cross validation e em no máximo 50 experimentos, bem como otimizando a acurácia." ] }, { "cell_type": "code", "execution_count": 58, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:01:14.152655Z", "iopub.status.busy": "2021-02-27T01:01:14.151996Z", "iopub.status.idle": "2021-02-27T01:01:16.022190Z", "shell.execute_reply": "2021-02-27T01:01:16.022800Z" }, "papermill": { "duration": 1.956707, "end_time": "2021-02-27T01:01:16.022982", "exception": false, "start_time": "2021-02-27T01:01:14.066275", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "clf = RandomizedSearchCV(model, distributions, n_iter=50, random_state=26, refit='acc', cv=10)\n", "search = clf.fit(X_train, y_train)" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.073081, "end_time": "2021-02-27T01:01:16.169510", "exception": false, "start_time": "2021-02-27T01:01:16.096429", "status": "completed" }, "tags": [] }, "source": [ "Quais foram os melhores parâmetros?" ] }, { "cell_type": "code", "execution_count": 59, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:01:16.319694Z", "iopub.status.busy": "2021-02-27T01:01:16.319079Z", "iopub.status.idle": "2021-02-27T01:01:16.324143Z", "shell.execute_reply": "2021-02-27T01:01:16.324728Z" }, "papermill": { "duration": 0.082264, "end_time": "2021-02-27T01:01:16.324903", "exception": false, "start_time": "2021-02-27T01:01:16.242639", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "{'C': 1.9764917991406659, 'kernel': 'rbf', 'random_state': 26}" ] }, "execution_count": 59, "metadata": {}, "output_type": "execute_result" } ], "source": [ "search.best_params_" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.07366, "end_time": "2021-02-27T01:01:16.472499", "exception": false, "start_time": "2021-02-27T01:01:16.398839", "status": "completed" }, "tags": [] }, "source": [ "Qual foi a acurácia deste parâmetro no dataset de validação?" ] }, { "cell_type": "code", "execution_count": 60, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:01:16.623294Z", "iopub.status.busy": "2021-02-27T01:01:16.622591Z", "iopub.status.idle": "2021-02-27T01:01:16.627782Z", "shell.execute_reply": "2021-02-27T01:01:16.628314Z" }, "papermill": { "duration": 0.082037, "end_time": "2021-02-27T01:01:16.628491", "exception": false, "start_time": "2021-02-27T01:01:16.546454", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "0.8725108225108226" ] }, "execution_count": 60, "metadata": {}, "output_type": "execute_result" } ], "source": [ "search.best_score_" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.07373, "end_time": "2021-02-27T01:01:16.777167", "exception": false, "start_time": "2021-02-27T01:01:16.703437", "status": "completed" }, "tags": [] }, "source": [ "### Avaliação\n", "\n", "Avaliando o melhor modelo no dataset de teste." ] }, { "cell_type": "code", "execution_count": 61, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:01:16.937015Z", "iopub.status.busy": "2021-02-27T01:01:16.936031Z", "iopub.status.idle": "2021-02-27T01:01:16.941068Z", "shell.execute_reply": "2021-02-27T01:01:16.941610Z" }, "papermill": { "duration": 0.089901, "end_time": "2021-02-27T01:01:16.941838", "exception": false, "start_time": "2021-02-27T01:01:16.851937", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "y_pred = search.predict(X_test)" ] }, { "cell_type": "code", "execution_count": 62, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:01:17.095283Z", "iopub.status.busy": "2021-02-27T01:01:17.094600Z", "iopub.status.idle": "2021-02-27T01:01:17.102662Z", "shell.execute_reply": "2021-02-27T01:01:17.103225Z" }, "papermill": { "duration": 0.085805, "end_time": "2021-02-27T01:01:17.103401", "exception": false, "start_time": "2021-02-27T01:01:17.017596", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "acc = accuracy_score(y_pred, y_test)\n", "pre = precision_score(y_pred, y_test)\n", "rec = recall_score(y_pred, y_test)\n", "f1 = f1_score(y_pred, y_test)" ] }, { "cell_type": "code", "execution_count": 63, "metadata": { "_kg_hide-input": true, "_kg_hide-output": true, "execution": { "iopub.execute_input": "2021-02-27T01:01:17.263162Z", "iopub.status.busy": "2021-02-27T01:01:17.262465Z", "iopub.status.idle": "2021-02-27T01:01:17.269873Z", "shell.execute_reply": "2021-02-27T01:01:17.269348Z" }, "papermill": { "duration": 0.084744, "end_time": "2021-02-27T01:01:17.270007", "exception": false, "start_time": "2021-02-27T01:01:17.185263", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "acurácia : 0.8021978021978022\n", "precisão : 0.9019607843137255\n", "revocação: 0.7796610169491526\n", "f1-score : 0.8363636363636364\n" ] } ], "source": [ "experiment['Random Search'] = {'acc':acc, 'pre':pre, 'rec':rec, 'f1':f1}\n", "\n", "print('acurácia :', acc)\n", "print('precisão :', pre)\n", "print('revocação:', rec)\n", "print('f1-score :', f1)" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.074424, "end_time": "2021-02-27T01:01:17.419271", "exception": false, "start_time": "2021-02-27T01:01:17.344847", "status": "completed" }, "tags": [] }, "source": [ "### Comparando o modelo padrão com o Tuning\n", "\n", "Será que o Hyperparameter Tuning melhorou os resultados do SVM?" ] }, { "cell_type": "code", "execution_count": 64, "metadata": { "_kg_hide-input": true, "execution": { "iopub.execute_input": "2021-02-27T01:01:17.583982Z", "iopub.status.busy": "2021-02-27T01:01:17.582961Z", "iopub.status.idle": "2021-02-27T01:01:17.589327Z", "shell.execute_reply": "2021-02-27T01:01:17.588831Z" }, "papermill": { "duration": 0.094494, "end_time": "2021-02-27T01:01:17.589471", "exception": false, "start_time": "2021-02-27T01:01:17.494977", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>acc</th>\n", " <th>pre</th>\n", " <th>rec</th>\n", " <th>f1</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>SVM</th>\n", " <td>0.791209</td>\n", " <td>0.901961</td>\n", " <td>0.766667</td>\n", " <td>0.828829</td>\n", " </tr>\n", " <tr>\n", " <th>Random Search</th>\n", " <td>0.802198</td>\n", " <td>0.901961</td>\n", " <td>0.779661</td>\n", " <td>0.836364</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " acc pre rec f1\n", "SVM 0.791209 0.901961 0.766667 0.828829\n", "Random Search 0.802198 0.901961 0.779661 0.836364" ] }, "execution_count": 64, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pd.DataFrame(experiment)[['SVM', 'Random Search']].T" ] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": 0.075915, "end_time": "2021-02-27T01:01:17.740896", "exception": false, "start_time": "2021-02-27T01:01:17.664981", "status": "completed" }, "tags": [] }, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.9" }, "papermill": { "default_parameters": {}, "duration": 29.739397, "end_time": "2021-02-27T01:01:18.529984", "environment_variables": {}, "exception": null, "input_path": "__notebook__.ipynb", "output_path": "__notebook__.ipynb", "parameters": {}, "start_time": "2021-02-27T01:00:48.790587", "version": "2.2.2" } }, "nbformat": 4, "nbformat_minor": 4 }	0055/330/55330323.ipynb	s3://data-agents/kaggle-outputs/sharded/012_00055.jsonl.gz
{ "cells": [ { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.020299, "end_time": "2021-02-27T01:03:55.677737", "exception": false, "start_time": "2021-02-27T01:03:55.657438", "status": "completed" }, "tags": [] }, "source": [ "# Predicting Job Change using Python\n", "\n", "This notebook covers how to use Python machine learning libraries to construct a predictive model from HR data. The dataset is from the Kaggle task \"HR Analytics: Job Change of Data Scientists\" provided by user Möbius (https://www.kaggle.com/arashnic/hr-analytics-job-change-of-data-scientists)\n", "\n", "First, we'll take a look at the two datasets. We'll load up some useful libraries, and create dataframes from the .csv files provided. We'll also set a RandomState for reproducibility." ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:03:55.724654Z", "iopub.status.busy": "2021-02-27T01:03:55.723908Z", "iopub.status.idle": "2021-02-27T01:03:55.853923Z", "shell.execute_reply": "2021-02-27T01:03:55.854545Z" }, "papermill": { "duration": 0.158625, "end_time": "2021-02-27T01:03:55.854943", "exception": false, "start_time": "2021-02-27T01:03:55.696318", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>enrollee_id</th>\n", " <th>city</th>\n", " <th>city_development_index</th>\n", " <th>gender</th>\n", " <th>relevent_experience</th>\n", " <th>enrolled_university</th>\n", " <th>education_level</th>\n", " <th>major_discipline</th>\n", " <th>experience</th>\n", " <th>company_size</th>\n", " <th>company_type</th>\n", " <th>last_new_job</th>\n", " <th>training_hours</th>\n", " <th>target</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>0</th>\n", " <td>8949</td>\n", " <td>city_103</td>\n", " <td>0.920</td>\n", " <td>Male</td>\n", " <td>Has relevent experience</td>\n", " <td>no_enrollment</td>\n", " <td>Graduate</td>\n", " <td>STEM</td>\n", " <td>>20</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>1</td>\n", " <td>36</td>\n", " <td>1.0</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>29725</td>\n", " <td>city_40</td>\n", " <td>0.776</td>\n", " <td>Male</td>\n", " <td>No relevent experience</td>\n", " <td>no_enrollment</td>\n", " <td>Graduate</td>\n", " <td>STEM</td>\n", " <td>15</td>\n", " <td>50-99</td>\n", " <td>Pvt Ltd</td>\n", " <td>>4</td>\n", " <td>47</td>\n", " <td>0.0</td>\n", " </tr>\n", " <tr>\n", " <th>2</th>\n", " <td>11561</td>\n", " <td>city_21</td>\n", " <td>0.624</td>\n", " <td>NaN</td>\n", " <td>No relevent experience</td>\n", " <td>Full time course</td>\n", " <td>Graduate</td>\n", " <td>STEM</td>\n", " <td>5</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>never</td>\n", " <td>83</td>\n", " <td>0.0</td>\n", " </tr>\n", " <tr>\n", " <th>3</th>\n", " <td>33241</td>\n", " <td>city_115</td>\n", " <td>0.789</td>\n", " <td>NaN</td>\n", " <td>No relevent experience</td>\n", " <td>NaN</td>\n", " <td>Graduate</td>\n", " <td>Business Degree</td>\n", " <td><1</td>\n", " <td>NaN</td>\n", " <td>Pvt Ltd</td>\n", " <td>never</td>\n", " <td>52</td>\n", " <td>1.0</td>\n", " </tr>\n", " <tr>\n", " <th>4</th>\n", " <td>666</td>\n", " <td>city_162</td>\n", " <td>0.767</td>\n", " <td>Male</td>\n", " <td>Has relevent experience</td>\n", " <td>no_enrollment</td>\n", " <td>Masters</td>\n", " <td>STEM</td>\n", " <td>>20</td>\n", " <td>50-99</td>\n", " <td>Funded Startup</td>\n", " <td>4</td>\n", " <td>8</td>\n", " <td>0.0</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " enrollee_id city city_development_index gender \\\n", "0 8949 city_103 0.920 Male \n", "1 29725 city_40 0.776 Male \n", "2 11561 city_21 0.624 NaN \n", "3 33241 city_115 0.789 NaN \n", "4 666 city_162 0.767 Male \n", "\n", " relevent_experience enrolled_university education_level \\\n", "0 Has relevent experience no_enrollment Graduate \n", "1 No relevent experience no_enrollment Graduate \n", "2 No relevent experience Full time course Graduate \n", "3 No relevent experience NaN Graduate \n", "4 Has relevent experience no_enrollment Masters \n", "\n", " major_discipline experience company_size company_type last_new_job \\\n", "0 STEM >20 NaN NaN 1 \n", "1 STEM 15 50-99 Pvt Ltd >4 \n", "2 STEM 5 NaN NaN never \n", "3 Business Degree <1 NaN Pvt Ltd never \n", "4 STEM >20 50-99 Funded Startup 4 \n", "\n", " training_hours target \n", "0 36 1.0 \n", "1 47 0.0 \n", "2 83 0.0 \n", "3 52 1.0 \n", "4 8 0.0 " ] }, "execution_count": 1, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import numpy as np\n", "import pandas as pd\n", "\n", "rng = np.random.RandomState(123)\n", "train = pd.read_csv(\"../input/hr-analytics-job-change-of-data-scientists/aug_train.csv\")\n", "test = pd.read_csv(\"../input/hr-analytics-job-change-of-data-scientists/aug_test.csv\")\n", "\n", "train.head()" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:03:55.916198Z", "iopub.status.busy": "2021-02-27T01:03:55.915200Z", "iopub.status.idle": "2021-02-27T01:03:55.919980Z", "shell.execute_reply": "2021-02-27T01:03:55.920600Z" }, "papermill": { "duration": 0.046136, "end_time": "2021-02-27T01:03:55.920796", "exception": false, "start_time": "2021-02-27T01:03:55.874660", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>enrollee_id</th>\n", " <th>city</th>\n", " <th>city_development_index</th>\n", " <th>gender</th>\n", " <th>relevent_experience</th>\n", " <th>enrolled_university</th>\n", " <th>education_level</th>\n", " <th>major_discipline</th>\n", " <th>experience</th>\n", " <th>company_size</th>\n", " <th>company_type</th>\n", " <th>last_new_job</th>\n", " <th>training_hours</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>0</th>\n", " <td>32403</td>\n", " <td>city_41</td>\n", " <td>0.827</td>\n", " <td>Male</td>\n", " <td>Has relevent experience</td>\n", " <td>Full time course</td>\n", " <td>Graduate</td>\n", " <td>STEM</td>\n", " <td>9</td>\n", " <td><10</td>\n", " <td>NaN</td>\n", " <td>1</td>\n", " <td>21</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>9858</td>\n", " <td>city_103</td>\n", " <td>0.920</td>\n", " <td>Female</td>\n", " <td>Has relevent experience</td>\n", " <td>no_enrollment</td>\n", " <td>Graduate</td>\n", " <td>STEM</td>\n", " <td>5</td>\n", " <td>NaN</td>\n", " <td>Pvt Ltd</td>\n", " <td>1</td>\n", " <td>98</td>\n", " </tr>\n", " <tr>\n", " <th>2</th>\n", " <td>31806</td>\n", " <td>city_21</td>\n", " <td>0.624</td>\n", " <td>Male</td>\n", " <td>No relevent experience</td>\n", " <td>no_enrollment</td>\n", " <td>High School</td>\n", " <td>NaN</td>\n", " <td><1</td>\n", " <td>NaN</td>\n", " <td>Pvt Ltd</td>\n", " <td>never</td>\n", " <td>15</td>\n", " </tr>\n", " <tr>\n", " <th>3</th>\n", " <td>27385</td>\n", " <td>city_13</td>\n", " <td>0.827</td>\n", " <td>Male</td>\n", " <td>Has relevent experience</td>\n", " <td>no_enrollment</td>\n", " <td>Masters</td>\n", " <td>STEM</td>\n", " <td>11</td>\n", " <td>10/49</td>\n", " <td>Pvt Ltd</td>\n", " <td>1</td>\n", " <td>39</td>\n", " </tr>\n", " <tr>\n", " <th>4</th>\n", " <td>27724</td>\n", " <td>city_103</td>\n", " <td>0.920</td>\n", " <td>Male</td>\n", " <td>Has relevent experience</td>\n", " <td>no_enrollment</td>\n", " <td>Graduate</td>\n", " <td>STEM</td>\n", " <td>>20</td>\n", " <td>10000+</td>\n", " <td>Pvt Ltd</td>\n", " <td>>4</td>\n", " <td>72</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " enrollee_id city city_development_index gender \\\n", "0 32403 city_41 0.827 Male \n", "1 9858 city_103 0.920 Female \n", "2 31806 city_21 0.624 Male \n", "3 27385 city_13 0.827 Male \n", "4 27724 city_103 0.920 Male \n", "\n", " relevent_experience enrolled_university education_level \\\n", "0 Has relevent experience Full time course Graduate \n", "1 Has relevent experience no_enrollment Graduate \n", "2 No relevent experience no_enrollment High School \n", "3 Has relevent experience no_enrollment Masters \n", "4 Has relevent experience no_enrollment Graduate \n", "\n", " major_discipline experience company_size company_type last_new_job \\\n", "0 STEM 9 <10 NaN 1 \n", "1 STEM 5 NaN Pvt Ltd 1 \n", "2 NaN <1 NaN Pvt Ltd never \n", "3 STEM 11 10/49 Pvt Ltd 1 \n", "4 STEM >20 10000+ Pvt Ltd >4 \n", "\n", " training_hours \n", "0 21 \n", "1 98 \n", "2 15 \n", "3 39 \n", "4 72 " ] }, "execution_count": 2, "metadata": {}, "output_type": "execute_result" } ], "source": [ "test.head()" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:03:55.972240Z", "iopub.status.busy": "2021-02-27T01:03:55.969899Z", "iopub.status.idle": "2021-02-27T01:03:56.117170Z", "shell.execute_reply": "2021-02-27T01:03:56.115670Z" }, "papermill": { "duration": 0.174555, "end_time": "2021-02-27T01:03:56.117355", "exception": false, "start_time": "2021-02-27T01:03:55.942800", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>city</th>\n", " <th>gender</th>\n", " <th>relevent_experience</th>\n", " <th>enrolled_university</th>\n", " <th>education_level</th>\n", " <th>major_discipline</th>\n", " <th>experience</th>\n", " <th>company_size</th>\n", " <th>company_type</th>\n", " <th>last_new_job</th>\n", " <th>target</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>count</th>\n", " <td>19158</td>\n", " <td>14650</td>\n", " <td>19158</td>\n", " <td>18772</td>\n", " <td>18698</td>\n", " <td>16345</td>\n", " <td>19093</td>\n", " <td>13220</td>\n", " <td>13018</td>\n", " <td>18735</td>\n", " <td>19158.0</td>\n", " </tr>\n", " <tr>\n", " <th>unique</th>\n", " <td>123</td>\n", " <td>3</td>\n", " <td>2</td>\n", " <td>3</td>\n", " <td>5</td>\n", " <td>6</td>\n", " <td>22</td>\n", " <td>8</td>\n", " <td>6</td>\n", " <td>6</td>\n", " <td>2.0</td>\n", " </tr>\n", " <tr>\n", " <th>top</th>\n", " <td>city_103</td>\n", " <td>Male</td>\n", " <td>Has relevent experience</td>\n", " <td>no_enrollment</td>\n", " <td>Graduate</td>\n", " <td>STEM</td>\n", " <td>>20</td>\n", " <td>50-99</td>\n", " <td>Pvt Ltd</td>\n", " <td>1</td>\n", " <td>0.0</td>\n", " </tr>\n", " <tr>\n", " <th>freq</th>\n", " <td>4355</td>\n", " <td>13221</td>\n", " <td>13792</td>\n", " <td>13817</td>\n", " <td>11598</td>\n", " <td>14492</td>\n", " <td>3286</td>\n", " <td>3083</td>\n", " <td>9817</td>\n", " <td>8040</td>\n", " <td>14381.0</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " city gender relevent_experience enrolled_university \\\n", "count 19158 14650 19158 18772 \n", "unique 123 3 2 3 \n", "top city_103 Male Has relevent experience no_enrollment \n", "freq 4355 13221 13792 13817 \n", "\n", " education_level major_discipline experience company_size company_type \\\n", "count 18698 16345 19093 13220 13018 \n", "unique 5 6 22 8 6 \n", "top Graduate STEM >20 50-99 Pvt Ltd \n", "freq 11598 14492 3286 3083 9817 \n", "\n", " last_new_job target \n", "count 18735 19158.0 \n", "unique 6 2.0 \n", "top 1 0.0 \n", "freq 8040 14381.0 " ] }, "execution_count": 3, "metadata": {}, "output_type": "execute_result" } ], "source": [ "train.loc[:,train.dtypes == \"object\"] = train.loc[:,train.dtypes == \"object\"].astype(\"category\")\n", "train['target'] = train['target'].astype(\"category\")\n", "\n", "train.select_dtypes(\"category\").describe()" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:03:56.196547Z", "iopub.status.busy": "2021-02-27T01:03:56.195200Z", "iopub.status.idle": "2021-02-27T01:03:56.216647Z", "shell.execute_reply": "2021-02-27T01:03:56.215960Z" }, "papermill": { "duration": 0.075392, "end_time": "2021-02-27T01:03:56.216848", "exception": false, "start_time": "2021-02-27T01:03:56.141456", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>city_development_index</th>\n", " <th>training_hours</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>count</th>\n", " <td>19158.000000</td>\n", " <td>19158.000000</td>\n", " </tr>\n", " <tr>\n", " <th>mean</th>\n", " <td>0.828848</td>\n", " <td>65.366896</td>\n", " </tr>\n", " <tr>\n", " <th>std</th>\n", " <td>0.123362</td>\n", " <td>60.058462</td>\n", " </tr>\n", " <tr>\n", " <th>min</th>\n", " <td>0.448000</td>\n", " <td>1.000000</td>\n", " </tr>\n", " <tr>\n", " <th>25%</th>\n", " <td>0.740000</td>\n", " <td>23.000000</td>\n", " </tr>\n", " <tr>\n", " <th>50%</th>\n", " <td>0.903000</td>\n", " <td>47.000000</td>\n", " </tr>\n", " <tr>\n", " <th>75%</th>\n", " <td>0.920000</td>\n", " <td>88.000000</td>\n", " </tr>\n", " <tr>\n", " <th>max</th>\n", " <td>0.949000</td>\n", " <td>336.000000</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " city_development_index training_hours\n", "count 19158.000000 19158.000000\n", "mean 0.828848 65.366896\n", "std 0.123362 60.058462\n", "min 0.448000 1.000000\n", "25% 0.740000 23.000000\n", "50% 0.903000 47.000000\n", "75% 0.920000 88.000000\n", "max 0.949000 336.000000" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "train.select_dtypes({\"int64\",\"float64\"}).drop(columns = \"enrollee_id\").describe()" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:03:56.273972Z", "iopub.status.busy": "2021-02-27T01:03:56.272820Z", "iopub.status.idle": "2021-02-27T01:03:56.280112Z", "shell.execute_reply": "2021-02-27T01:03:56.280784Z" }, "papermill": { "duration": 0.04, "end_time": "2021-02-27T01:03:56.280972", "exception": false, "start_time": "2021-02-27T01:03:56.240972", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Percent of training set with target = 0: 0.751\n", "Percent of training set with target = 1: 0.249\n" ] } ], "source": [ "target_counts = pd.DataFrame({'target': train['target']})\n", "print(\"Percent of training set with target = 0: %.3f\" % (len(target_counts[target_counts['target'] == 0]) / len(target_counts)) )\n", "print(\"Percent of training set with target = 1: %.3f\" % (len(target_counts[target_counts['target'] == 1]) / len(target_counts)) )" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:03:56.333236Z", "iopub.status.busy": "2021-02-27T01:03:56.332260Z", "iopub.status.idle": "2021-02-27T01:03:56.344831Z", "shell.execute_reply": "2021-02-27T01:03:56.345341Z" }, "papermill": { "duration": 0.040415, "end_time": "2021-02-27T01:03:56.345540", "exception": false, "start_time": "2021-02-27T01:03:56.305125", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>dtype</th>\n", " <th>null_count</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>enrollee_id</th>\n", " <td>int64</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>city</th>\n", " <td>category</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>city_development_index</th>\n", " <td>float64</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>gender</th>\n", " <td>category</td>\n", " <td>4508</td>\n", " </tr>\n", " <tr>\n", " <th>relevent_experience</th>\n", " <td>category</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>enrolled_university</th>\n", " <td>category</td>\n", " <td>386</td>\n", " </tr>\n", " <tr>\n", " <th>education_level</th>\n", " <td>category</td>\n", " <td>460</td>\n", " </tr>\n", " <tr>\n", " <th>major_discipline</th>\n", " <td>category</td>\n", " <td>2813</td>\n", " </tr>\n", " <tr>\n", " <th>experience</th>\n", " <td>category</td>\n", " <td>65</td>\n", " </tr>\n", " <tr>\n", " <th>company_size</th>\n", " <td>category</td>\n", " <td>5938</td>\n", " </tr>\n", " <tr>\n", " <th>company_type</th>\n", " <td>category</td>\n", " <td>6140</td>\n", " </tr>\n", " <tr>\n", " <th>last_new_job</th>\n", " <td>category</td>\n", " <td>423</td>\n", " </tr>\n", " <tr>\n", " <th>training_hours</th>\n", " <td>int64</td>\n", " <td>0</td>\n", " </tr>\n", " <tr>\n", " <th>target</th>\n", " <td>category</td>\n", " <td>0</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " dtype null_count\n", "enrollee_id int64 0\n", "city category 0\n", "city_development_index float64 0\n", "gender category 4508\n", "relevent_experience category 0\n", "enrolled_university category 386\n", "education_level category 460\n", "major_discipline category 2813\n", "experience category 65\n", "company_size category 5938\n", "company_type category 6140\n", "last_new_job category 423\n", "training_hours int64 0\n", "target category 0" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pd.DataFrame({'dtype': train.dtypes,\n", " 'null_count': train.isna().sum()})" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.021804, "end_time": "2021-02-27T01:03:56.390489", "exception": false, "start_time": "2021-02-27T01:03:56.368685", "status": "completed" }, "tags": [] }, "source": [ "As the documentation mentioned, the attributes of the data may pose some issues while modeling, such as:\n", "\n", "1. Imbalanced data set\n", "2. High cardinality (uniqueness) in some features\n", "3. Missing data\n", "\n", "Let's explore our training set further and do some basic summary/visualization to explore the data." ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.022521, "end_time": "2021-02-27T01:03:56.434936", "exception": false, "start_time": "2021-02-27T01:03:56.412415", "status": "completed" }, "tags": [] }, "source": [ "# Exploratory Data Analysis\n", "\n", "Let's begin by looking at the distribution of our categorical variables." ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:03:56.519100Z", "iopub.status.busy": "2021-02-27T01:03:56.517934Z", "iopub.status.idle": "2021-02-27T01:04:01.380332Z", "shell.execute_reply": "2021-02-27T01:04:01.379470Z" }, "papermill": { "duration": 4.922865, "end_time": "2021-02-27T01:04:01.380550", "exception": false, "start_time": "2021-02-27T01:03:56.457685", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 864x360 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 864x360 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 864x360 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "image/png": 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8NHDuwDpL2/wLgQsHgrkkSZI0K83bWIUkHwUOA/ZIshp4G91dOrYDzm/XBX65ql5dVVcmORu4im7Ix3FVdX/b1LF0dwDZnm5M9cS46lOBf0yykq4nesmWOTRJkiRp68lc7fwdGxur8fHxmdm5NxXRXDNHz3NJkmaDJJdV1dhwub9sKEmSJPVgkJYkSZJ6MEhLkiRJPRikJUmSpB4M0pIkSVIPBmlJkiSpB4O0JEmS1INBWpIkSerBIC1JkiT1YJCWJEmSejBIS5IkST0YpCVJkqQeDNKSJElSDwZpSZIkqQeDtCRJktSDQVqSJEnqwSAtSZIk9WCQliRJknowSEuSJEk9GKQlSZKkHgzSkiRJUg8GaUmSJKkHg7QkSZLUg0FakiRJ6sEgLUmSJPVgkJYkSZJ6MEhLkiRJPRikJUmSpB4M0pIkSVIPGw3SSU5LcmuSbwyU7Zbk/CTXtsddB5Ydn2RlkmuSHDFQfnCSK9qyE5OklW+X5GOt/JIki7bwMUqSJElb3Kb0SJ8OLB4qexNwQVUdAFzQnpPkQGAJcFBb56Qk27R1TgaWAQe0aWKbxwC3V9X+wAnAu/sejCRJkvRg2WiQrqovAN8bKj4SWN7mlwNHDZSfVVX3VtV1wErgkCR7AztV1cVVVcAZQ+tMbOsc4PCJ3mpJkiRptuo7RnqvqloD0B73bOULgFUD9Va3sgVtfrh8vXWqah1wJ7D7qJ0mWZZkPMn42rVrezZdkiRJmr4tfbHhqJ7kmqJ8qnU2LKw6parGqmps/vz5PZsoSZIkTV/fIH1LG65Be7y1la8G9hmotxC4qZUvHFG+3jpJ5gE7s+FQEkmSJGlW6RukVwBL2/xS4NyB8iXtThz70V1UeGkb/nFXkkPb+Oejh9aZ2NYLgQvbOGpJkiRp1pq3sQpJPgocBuyRZDXwNuBdwNlJjgFuBF4EUFVXJjkbuApYBxxXVfe3TR1LdweQ7YHz2gRwKvCPSVbS9UQv2SJHJkmSJG1Fmaudv2NjYzU+Pj4zO/emIppr5uh5LknSbJDksqoaGy73lw0lSZKkHgzSkiRJUg8GaUmSJKkHg7QkSZLUg0FakiRJ6sEgLUmSJPVgkJYkSZJ6MEhLkiRJPRikJUmSpB4M0pIkSVIPBmlJkiSpB4O0JEmS1INBWpIkSerBIC1JkiT1YJCWJEmSejBIS5IkST0YpCVJkqQeDNKSJElSDwZpSZIkqQeDtCRJktSDQVqSJEnqwSAtSZIk9WCQliRJknowSEuSJEk9GKQlSZKkHgzSkiRJUg8GaUmSJKkHg7QkSZLUw7SCdJI/SXJlkm8k+WiSRybZLcn5Sa5tj7sO1D8+ycok1yQ5YqD84CRXtGUnJsl02iVJkiRtbb2DdJIFwGuBsap6MrANsAR4E3BBVR0AXNCek+TAtvwgYDFwUpJt2uZOBpYBB7Rpcd92SZIkSQ+G6Q7tmAdsn2QesANwE3AksLwtXw4c1eaPBM6qqnur6jpgJXBIkr2Bnarq4qoq4IyBdSRJkqRZqXeQrqrvAH8L3AisAe6sqs8Be1XVmlZnDbBnW2UBsGpgE6tb2YI2P1wuSZIkzVrTGdqxK10v837AY4FHJXnpVKuMKKspykftc1mS8STja9eu3dwmS5IkSVvMdIZ2PBu4rqrWVtWPgU8Avwjc0oZr0B5vbfVXA/sMrL+QbijI6jY/XL6Bqjqlqsaqamz+/PnTaLokSZI0PdMJ0jcChybZod1l43DgamAFsLTVWQqc2+ZXAEuSbJdkP7qLCi9twz/uSnJo287RA+tIkiRJs9K8vitW1SVJzgEuB9YBXwFOAXYEzk5yDF3YflGrf2WSs4GrWv3jqur+trljgdOB7YHz2iRJkiTNWululDH3jI2N1fj4+Mzs3Ntca66Zo+e5JEmzQZLLqmpsuNxfNpQkSZJ6MEhLkiRJPRikJUmSpB4M0pIkSVIPBmlJkiSpB4O0JEmS1INBWpIkSerBIC1JkiT1YJCWJEmSejBIS5IkST0YpCVJkqQeDNKSJElSDwZpSZIkqQeDtCRJktSDQVqSJEnqwSAtSZIk9WCQliRJknowSEuSJEk9GKQlSZKkHgzSkiRJUg8GaUmSJKkHg7QkSZLUg0FakiRJ6sEgLUmSJPVgkJYkSZJ6MEhLkiRJPRikJUmSpB4M0pIkSVIPBmlJkiSph2kF6SS7JDknyTeTXJ3kGUl2S3J+kmvb464D9Y9PsjLJNUmOGCg/OMkVbdmJSTKddkmSJElb23R7pP8e+GxV/QzwFOBq4E3ABVV1AHBBe06SA4ElwEHAYuCkJNu07ZwMLAMOaNPiabZLkiRJ2qp6B+kkOwG/ApwKUFX3VdUdwJHA8lZtOXBUmz8SOKuq7q2q64CVwCFJ9gZ2qqqLq6qAMwbWkSRJkmal6fRI/zSwFvhQkq8k+WCSRwF7VdUagPa4Z6u/AFg1sP7qVragzQ+XbyDJsiTjScbXrl07jaZLkiRJ0zOdID0PeBpwclX9PPBD2jCOSYwa91xTlG9YWHVKVY1V1dj8+fM3t72SJEnSFjOdIL0aWF1Vl7Tn59AF61vacA3a460D9fcZWH8hcFMrXziiXJIkSZq1egfpqroZWJXkia3ocOAqYAWwtJUtBc5t8yuAJUm2S7If3UWFl7bhH3clObTdrePogXUkSZKkWWneNNf/I+DMJI8Avg28gi6cn53kGOBG4EUAVXVlkrPpwvY64Liqur9t51jgdGB74Lw2SZIkSbNWuhtlzD1jY2M1Pj4+Mzv3Nteaa+boeS5J0myQ5LKqGhsu95cNJUmSpB4M0pIkSVIPBmlJkiSpB4O0JEmS1INBWpIkSerBIC1JkiT1YJCWJEmSejBIS5IkST0YpCVJkqQeDNKSJElSDwZpSZIkqQeDtCRJktSDQVqSJEnqwSAtSZIk9WCQliRJknowSEuSJEk9GKQlSZKkHgzSkiRJUg8GaUmSJKkHg7QkSZLUg0FakiRJ6sEgLUmSJPVgkJYkSZJ6MEhLkiRJPRikJUmSpB4M0pIkSVIPBmlJkiSpB4O0JEmS1MO0g3SSbZJ8Jcmn2vPdkpyf5Nr2uOtA3eOTrExyTZIjBsoPTnJFW3Zikky3XZIkSdLWtCV6pF8HXD3w/E3ABVV1AHBBe06SA4ElwEHAYuCkJNu0dU4GlgEHtGnxFmiXJEmStNVMK0gnWQj8JvDBgeIjgeVtfjlw1ED5WVV1b1VdB6wEDkmyN7BTVV1cVQWcMbCOJEmSNCtNt0f6PcAbgAcGyvaqqjUA7XHPVr4AWDVQb3UrW9Dmh8slSZKkWat3kE7yPODWqrpsU1cZUVZTlI/a57Ik40nG165du4m7lSRJkra86fRI/xLwgiTXA2cBv5bkw8AtbbgG7fHWVn81sM/A+guBm1r5whHlG6iqU6pqrKrG5s+fP42mS5IkSdPTO0hX1fFVtbCqFtFdRHhhVb0UWAEsbdWWAue2+RXAkiTbJdmP7qLCS9vwj7uSHNru1nH0wDqSJEnSrDRvK2zzXcDZSY4BbgReBFBVVyY5G7gKWAccV1X3t3WOBU4HtgfOa5MkSZI0a6W7UcbcMzY2VuPj4zOzc29zrblmrp3nnmOai+baeSZpkyW5rKrGhsv9ZUNJkiSpB4O0JEmS1INBWpIkSerBIC1JkiT1YJCWJEmSejBIS5IkST0YpCVJkqQeDNKSJElSDwZpSZIkqQeDtCRJktSDQVqSJEnqwSAtSZIk9WCQliRJknowSEuSJEk9GKQlSZKkHgzSkiRJUg8GaUmSJKkHg7QkSZLUg0FakiRJ6sEgLUmSJPVgkJYkSZJ6MEhLkiRJPRikJUmSpB4M0pIkSVIPBmlJkiSpB4O0JEmS1INBWpIkSerBIC1JkiT1YJCWJEmSeugdpJPsk+Tfklyd5Mokr2vluyU5P8m17XHXgXWOT7IyyTVJjhgoPzjJFW3ZiUkyvcOSJEmStq7p9EivA/6sqp4EHAocl+RA4E3ABVV1AHBBe05btgQ4CFgMnJRkm7atk4FlwAFtWjyNdkmSJElbXe8gXVVrquryNn8XcDWwADgSWN6qLQeOavNHAmdV1b1VdR2wEjgkyd7ATlV1cVUVcMbAOpIkSdKstEXGSCdZBPw8cAmwV1WtgS5sA3u2aguAVQOrrW5lC9r8cPmo/SxLMp5kfO3atVui6ZIkSVIv0w7SSXYEPg78cVV9f6qqI8pqivINC6tOqaqxqhqbP3/+5jdWkiRJ2kKmFaSTbEsXos+sqk+04lvacA3a462tfDWwz8DqC4GbWvnCEeWSJEnSrDWdu3YEOBW4uqr+98CiFcDSNr8UOHegfEmS7ZLsR3dR4aVt+MddSQ5t2zx6YB1JkiRpVpo3jXV/CXgZcEWSr7ayNwPvAs5OcgxwI/AigKq6MsnZwFV0d/w4rqrub+sdC5wObA+c1yZJkiRp1kp3o4y5Z2xsrMbHx2dm597mWnPNXDvPPcc0F82180zSJktyWVWNDZf7y4aSJElSDwZpSZIkqQeDtCRJktSDQVqSJEnqwSAtSZIk9WCQliRJknowSEuSJEk9GKQlSZKkHgzSkiRJUg/T+YlwSZI0F/nroZqLZuGvh9ojLUmSJPVgkJYkSZJ6MEhLkiRJPRikJUmSpB4M0pIkSVIPBmlJkiSpB4O0JEmS1INBWpIkSerBIC1JkiT1YJCWJEmSejBIS5IkST0YpCVJkqQeDNKSJElSDwZpSZIkqQeDtCRJktSDQVqSJEnqwSAtSZIk9WCQliRJknqYNUE6yeIk1yRZmeRNM90eSZIkaSqzIkgn2Qb4B+C5wIHA7yY5cGZbJUmSJE1uVgRp4BBgZVV9u6ruA84CjpzhNkmSJEmTmi1BegGwauD56lYmSZIkzUrzZroBTUaU1QaVkmXAsvb0B0mu2aqt0oNtD+C7M92Ih6SMOsX0MOV5trV4nqnjOba1zOw59rhRhbMlSK8G9hl4vhC4abhSVZ0CnPJgNUoPriTjVTU20+2QHso8z6Sty3Ps4WW2DO34T+CAJPsleQSwBFgxw22SJEmSJjUreqSral2S1wD/AmwDnFZVV85wsyRJkqRJzYogDVBVnwE+M9Pt0Ixy2I609XmeSVuX59jDSKo2uKZPkiRJ0kbMljHSkiRJ0pxikJakB0GSRUkqybz2/KIkf7AZ65+XZOnWa6EkgCQvSfK5mW6H5gaDtGa9Fj72b/OnJ/nLmW6THt6SXJ/kniQ/GJgeuwW3//YkHx4sq6rnVtXyLbUPabYaOr9uSfKhJDv23NaUH1iHP+ACVNWZVfWcPvvTw49BWtoEo4KNHvaeX1U7Dkwb3Pteow2GFmkSz6+qHYGnAb8AvHVzVk7HjAMk2Wam2/BQ5h+ZZpRvqHooaT1pzx54vtkfwJIsBt4MvLj1yH2tlf//nrUkL0/yxSQnJLkjybeT/GIrX5Xk1sFhIEm2S/K3SW5sPXzvS7L9FG14ZZKrk9yV5KokT2vlT2rtuCPJlUleMLDOej1/rS3/MfC8khyX5Frg2hZ0TmhtvTPJ15M8uU979dBVVd8BzgOenGTXJJ9KsjbJ7W1+4UTd9jf4jiRfBO4G/hF4JvDedi69d8QuvtAe72h1njHJ3+4fJrm2nRP/K8njk1yc5PtJzm6/gTFR/3lJvtrOky8l+bnJji/JQUnOT/K99rf+5la+XZL3JLmpTe9Jsl1btl77Bto4+M3tyUk+k+SHwK8m+Y12Lt+V5DtJXt+nvdqQQfphor3Bv769Wd2Z5GNJHtmWvTLJynYir8gmfEWd5GcGTv5rkvzOwLLTk/xDkk+3k/aSJI8fWL7eG+o02nBYktVJ3tDejNckOar9h/Gttq03D9T/qSRvSvJfSW5r//nt1pZNfL23tL15fzfJW9qykcFG2hqq6rPAO4GPtZ7up0xS9enA14HdgY8AZ9H13O0PvJQuPEx8Hf5u4AnAU9vyBcD/GLXRJC8C3g4cDewEvAC4Lcm2wD8DnwP2BP4IODPJEzfj8I5q7T4QeA7wK61duwAvBm7b3PbqoS3JPsBvAF+hyywfovup5n2Be4DhcPwyYBnwaODlwL8Dr2nn0mtG7OJX2uMurc7FkzRlMXAwcCjwBrpb3L2E7leZnwz8bmvv04DTgFfRnZvvB1ZMhOChY3s08K/AZ4HH0v2tX9AWv6Xt66nAU4BD2Lxe+d8D3kH3OvwHcCrwqqp6dGvvhZvbXo1mkH54+R26/wz2A34OeHmSXwP+qi3bG7iB7g15UkkeBZxP9+a9J91/ICclOWig2u8CfwHsCqykO6EHHUV7Q+3ThgGPAR7JT95oP0AXIg6m64n4H0l+utV9bdvvs+j+07od+Ieh7f0y8ETg8LbukzYj2Ojh5ZOtB+eOJJ+cgf1fV1Ufqqr7gY/RvaH/z6q6t6o+B9wH7J8kwCuBP6mq71XVXXR/z0sm2e4fAH9dVf9ZnZVVdQPdm/qOwLuq6r6quhD4FC1AbKK/am24B/gx3Zv8z9DdivXqqlrTo716aPpkkjvoQuDngXdW1W1V9fGqurv9XbyD7v/zQadX1ZVVta6qfrwF2/Puqvp++7G4bwCfq6pvV9WddD3mP9/qvRJ4f1VdUlX3t+sa7qU7f4Y9D7i5qv6uqn5UVXdV1SVt2Uvozudbq2ot3fvpyzajvedW1Rer6oGq+hHd+XZgkp2q6vaqurxHezWCQfrh5cSquqmqvkfXs/RUupP1tKq6vKruBY4HnpFk0RTbeR5wfXsTX9dOyI8DLxyo84mqurSq1gFntn0NGnxD7dOGCT8G3tH+wzwL2AP4+/Yf0pXAlXQfGqD7xP2Wqlrd9vN24IVZf3jJX1TVPVX1NeBrdD0B0ihHVdUubTpqBvZ/y8D8PQBVNVy2IzAf2AG4bCL40/WAzZ9ku/sA/zWi/LHAqqp6YKDsBroPsZtq1cRMC+Lvpfswe0uSU5Ls1KO9emiaOL8eV1V/WFX3JNkhyfuT3JDk+3TDMnbJ+mOAV02yvekaPrdGnWvQ9Zb/2cCH7DvozqlR37JOdq7R6t8w8PyGSbYxmeHX4bfpevZvSPL5JM/o0V6NYJB+eLl5YP5uuhN/vZO1qn5A9/XqVG+OjwOePnTivYSud3iqfQ0aPMn7tGHCba1HDlqYYOr/4P5poM1XA/cDe21Gu6Wp/JAuBE54zGQVN2JL/lLWd+nOg4MGgv/O7UKuUVYBjx9RfhOwT9a/gGtf4DttflOOfb3jqqoTq+pg4CC6oRx/3qO9evj4M7pvDJ9eVTvxk2EZGagzfO5s7Fza0r9Kt4quc2eXgWmHqvroJHVHnWvQnW+PG3i+byuDoXMtyaaca/9ZVUfSfYv8SeDsHu3VCAZprXeytmEbu/OTN8dRVgGfHzrxdqyqYzdjv4MneZ829LEKeO5Qux9Z3cUsG+NPgGpTfBVYkmTbJGOs/y3N5rgFWJQtcNeB1oP8AeCEJHsCJFmQ5IhJVvkg8PokB6ezf5LHAZfQvYG/oR3fYcDz+ckwrK8Cv9V6DfcHjpmqXUl+IcnT29jrHwI/Au7v0V49fDya7kPWHe36lrdtwjq3AD89xfK1wAMbqbM5PgC8uv1tJ8mjkvxmGw897FPAY5L8cbqLCx+d5Olt2UeBtyaZn2QPuqGLExcufw04KMlT013r9PapGpTkEenujb1z+/b2+3SdSJvbXo1gkNZHgFe0E3I7urGIl1TV9VOs8yngCUle1t5Qt21vik96ENvQx/uAd7RQQPsP6shNXHeLBRs9pP13uh6m2+nGNH6k53b+b3u8LcnlU9bcNG+ku1bhy+0r8X+l69nbQFX9X7qxpx8B7qLrvdqtqu6ju/DwuXS9xicBR1fVN9uqJ9CNy74FWE43pGsqO9G9id9O943UbcDfbm579bDyHmB7ur+/L9MN+dmYv6cbwnd7khOHF1bV3XR/719s31ZOa2xwVY3TjTt+L93f9kq6ix5H1b0L+HW6D6Q30118/6tt8V8C43QXFF8BXN7KqKpvAf+T7ry4lm4c+ca8DLi+nU+vpruWaLPaq9FSZUfbw0GS64E/qKp/bc/fDuxfVS9N8mq6r1R3Bb4EvLqqVm9ke08E/jfdlcQ/RfcJ+U+r6qtJTgdWV9VbW93DgA9X1cL2vIADqmrlwPYmbcNg/cFtj9juPLox0/tNhPB0twh6X1V9uIXgP6YbK/1Y4Fa6Cwjf3MZjXwds28Z1k+Sitv0PJtkdOJfuK+jrquppm/TCS5KkhyyDtCRJktSDX1NLkiRJPfirchopyTPp7o25Aa+elyRJcmiHJEmS1ItDOyRJkqQeDNKSJElSDwZpSZIkqQeDtCRJktSDQVqSJEnq4f8BTyvqQaWDqikAAAAASUVORK5CYII=\n", "text/plain": [ "<Figure size 864x360 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 864x360 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 864x360 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 864x360 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "image/png": 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"text/plain": [ "<Figure size 864x360 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "image/png": 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wSEuSJEkDGKQlSZKkAQzSkiRJ0gAGaUmSJGkAg7QkSZI0gEFakiRJGsAgLUmSJA1gkJYkSZIGMEhLkiRJAxikJUmSpAEM0pIkSdIABmlJkiRpAIO0JEmSNIBBWpIkSRrAIC1JkiQNYJCWJEmSBjBIS5IkSQMYpCVJkqQBDNKSJEnSAAZpSZIkaQCDtCRJkjSAQVqSJEkawCAtSZIkDWCQliRJkgYwSEuSJEkDGKQlSZKkAQzSkiRJ0gAGaUmSJGkAg7QkSZI0gEFakiRJGsAgLUmSJA1gkJYkSZIGMEhLkiRJAxikJUmSpAEM0pIkSdIABmlJkiRpAIO0JEmSNIBBWpIkSRrAIC1JkiQNYJCWJEmSBjBIS5IkSQMYpCVJkqQB5hSkk2yf5GNJvpvk4iQPS7JjkjOTXNrvdxgZ/5gkK5JckuSQkfIDklzQh70rSebSLkmSJGlDm+se6X8APltV9wceBFwMvBo4q6r2Bc7qz0myH3AksD9wKPDeJFv16RwLHA3s22+HzrFdkiRJ0gY1OEgn2Q54JPB+gKr6RVXdCBwGnNhHOxE4vD8+DDi5qm6tqsuBFcCBSXYHtquqc6qqgA+O1JEkSZIWpLnskb4PsBo4Psk3k7wvyT2AXavqaoB+v0sff09g5Uj9Vb1sz/54vFySJElasOYSpBcBDwaOrarfBm6hd+OYxqR+zzVD+doTSI5OsjzJ8tWrV69veyVJkqR5M5cgvQpYVVVf788/RgvW1/buGvT760bG32uk/hLgql6+ZEL5WqrquKpaVlXLFi9ePIemS5IkSXMzOEhX1TXAyiS/2YseA1wEnA4c1cuOAk7rj08HjkyydZJ9aAcVntu7f9yc5KB+to5nj9SRJEmSFqRFc6z/UuAjSe4KXAY8lxbOT03yPOBK4AiAqrowyam0sH078OKquqNP54XACcA2wBn9JkmSJC1YaSfK2PwsW7asli9fvmlm7mmu589m+v6TJEl3HknOq6pl4+Ve2VCSJEkawCAtSZIkDWCQliRJkgYwSEuSJEkDGKQlSZKkAQzSkiRJ0gAGaUmSJGkAg7QkSZI0gEFakiRJGsAgLUmSJA1gkJYkSZIGMEhLkiRJAxikJUmSpAEM0pIkSdIABmlJkiRpAIO0JEmSNIBBWpIkSRrAIC1JkiQNYJCWJEmSBjBIS5IkSQMYpCVJkqQBDNKSJEnSAAZpSZIkaQCDtCRJkjSAQVqSJEkawCAtSZIkDWCQliRJkgYwSEuSJEkDGKQlSZKkAQzSkiRJ0gAGaUmSJGkAg7QkSZI0gEFakiRJGsAgLUmSJA1gkJYkSZIGMEhLkiRJAxikJUmSpAEM0pIkSdIABmlJkiRpAIO0JEmSNIBBWpIkSRrAIC1JkiQNYJCWJEmSBjBIS5IkSQPMOUgn2SrJN5N8uj/fMcmZSS7t9zuMjHtMkhVJLklyyEj5AUku6MPelSRzbZckSZK0Ic3HHumXAxePPH81cFZV7Quc1Z+TZD/gSGB/4FDgvUm26nWOBY4G9u23Q+ehXZIkSdIGM6cgnWQJ8ETgfSPFhwEn9scnAoePlJ9cVbdW1eXACuDAJLsD21XVOVVVwAdH6kiSJEkL0lz3SL8T+EvglyNlu1bV1QD9fpdeviewcmS8Vb1sz/54vHwtSY5OsjzJ8tWrV8+x6ZIkSdJwg4N0kicB11XVebOtMqGsZihfu7DquKpaVlXLFi9ePMvZSpIkSfNv0RzqPhx4SpInAHcDtkvyYeDaJLtX1dW928Z1ffxVwF4j9ZcAV/XyJRPKJUmSpAVr8B7pqjqmqpZU1VLaQYSfr6pnAqcDR/XRjgJO649PB45MsnWSfWgHFZ7bu3/cnOSgfraOZ4/UkSRJkhakueyRns7bgFOTPA+4EjgCoKouTHIqcBFwO/Diqrqj13khcAKwDXBGv0mSJEkLVtqJMjY/y5Ytq+XLl2+amXua6/mzmb7/JEnSnUeS86pq2Xi5VzaUJEmSBjBIS5IkSQMYpCVJkqQBDNKSJEnSAAZpSZIkaQCDtCRJkjSAQVqSJEkawCAtSZIkDWCQliRJkgYwSEuSJEkDGKQlSZKkAQzSkiRJ0gAGaUmSJGkAg7QkSZI0gEFakiRJGsAgLUmSJA1gkJYkSZIGMEhLkiRJAxikJUmSpAEM0pIkSdIABmlJkiRpAIO0JEmSNIBBWpIkSRrAIC1JkiQNYJCWJEmSBjBIS5IkSQMYpCVJkqQBDNKSJEnSAAZpSZIkaQCDtCRJkjSAQVqSJEkawCAtSZIkDWCQliRJkgYwSEuSJEkDGKQlSZKkAQzSkiRJ0gAGaUmSJGkAg7QkSZI0gEFakiRJGsAgLUmSJA1gkJYkSZIGMEhLkiRJAxikJUmSpAEGB+kkeyX5QpKLk1yY5OW9fMckZya5tN/vMFLnmCQrklyS5JCR8gOSXNCHvStJ5vayJEmSpA1rLnukbwdeWVUPAA4CXpxkP+DVwFlVtS9wVn9OH3YksD9wKPDeJFv1aR0LHA3s22+HzqFdkiRJ0gY3OEhX1dVV9Y3++GbgYmBP4DDgxD7aicDh/fFhwMlVdWtVXQ6sAA5MsjuwXVWdU1UFfHCkjiRJkrQgzUsf6SRLgd8Gvg7sWlVXQwvbwC59tD2BlSPVVvWyPfvj8XJJkiRpwZpzkE6yLfBx4BVV9eOZRp1QVjOUT5rX0UmWJ1m+evXq9W+sJEmSNE/mFKST3IUWoj9SVZ/oxdf27hr0++t6+Spgr5HqS4CrevmSCeVrqarjqmpZVS1bvHjxXJouSZIkzclcztoR4P3AxVX19yODTgeO6o+PAk4bKT8yydZJ9qEdVHhu7/5xc5KD+jSfPVJHkiRJWpAWzaHuw4FnARckOb+XvQZ4G3BqkucBVwJHAFTVhUlOBS6infHjxVV1R6/3QuAEYBvgjH6TJEmSFqy0E2VsfpYtW1bLly/fNDP3NNfzZzN9/0mSpDuPJOdV1bLxcq9sKEmSJA1gkJYkSZIGMEhLkiRJAxikJUmSpAEM0pIkSdIABmlJkiRpAIO0JEmSNIBBWpIkSRrAIC1JkiQNYJCWJEmSBjBIS5IkSQMYpCVJkqQBDNKSJEnSAAZpSZIkaQCDtCRJkjSAQVqSJEkawCAtSZIkDWCQliRJkgYwSEuSJEkDGKQlSZKkAQzSkiRJ0gCLNnUDpHmXbOoWbFmqNnULJElakNwjLUmSJA3gHmlJG5//Gswv/zWQpE3CPdKSJEnSAAZpSZIkaQCDtCRJkjSAQVqSJEkawCAtSZIkDWCQliRJkgYwSEuSJEkDGKQlSZKkAbwgiyRpbV40Z3550Rxpi+QeaUmSJGkA90hLkrQ58l+D+eW/BhrAPdKSJEnSAAZpSZIkaQCDtCRJkjSAQVqSJEkawCAtSZIkDWCQliRJkgYwSEuSJEkDGKQlSZKkAQzSkiRJ0gALJkgnOTTJJUlWJHn1pm6PJEmSNJMFcYnwJFsB7wEeB6wC/jPJ6VV10aZtmSRJ0kBexn1+LcDLuC+UPdIHAiuq6rKq+gVwMnDYJm6TJEmSNK2FEqT3BFaOPF/VyyRJkqQFaUF07QAm/fex1v77JEcDR/enP0lyyQZt1eZtZ+D6Td2Idbpz/+3lOlr4XEcLn+to4XMdLXyuo3Xbe1LhQgnSq4C9Rp4vAa4aH6mqjgOO21iN2pwlWV5VyzZ1OzQ919HC5zpa+FxHC5/raOFzHQ23ULp2/Cewb5J9ktwVOBI4fRO3SZIkSZrWgtgjXVW3J3kJ8G/AVsAHqurCTdwsSZIkaVoLIkgDVNVngM9s6nZsQewCs/C5jhY+19HC5zpa+FxHC5/raKDUAjwnnyRJkrTQLZQ+0pIkSdJmxSCtdUrynCRf3tTt2NSSHJxk1cauq5mt6/2Z5Owkz++Pn5HkcxuvdVuOJFckeeymboek+TO6fdQwBukFpH9R/SzJT5Jcm+T4JNvOot4JSd6yjnEqyf0mlG8RIXls2U3d9tjU7ZqtJIclOT/Jj5Ncn+SsJEv7sDcm+fAcp7/gg/zQ9//6qKqPVNXvDWjbkiQf7+vmpiQXJHnOXNqyodfJNJ+Jd2+o+c3Qju2TfCDJNUluTvJfSV41Mnzitmkjte0RSb7a1+kPk3wlyUP6sDlvG5Ms7a9vwRyPNB/6e+vaJPcYKXt+krP74yR5SZJvJ/lpX/dnJzlybDpPSnJukluS3JDkI0mWbOSXs0Xp79sLRpb7sUm278Pm/F2itRmkF54nV9W2wIOBhwCv3cTt2Zw8uaq2HbmtdS7yhaiHiA8CrwTuBewDvBf45TxNf3P6El+o7/8P0a6+ujewE/Bs4NpN2aBZrtfxz8RLNtB8ZvIOYFvgAbT391OA781xmnOWZDvg08A/AjvSrqb7JuDWeZr+5vS5G2IR8PJphr0LeAVtm7YTbdm+Fjh0aoQkTwVOAv6BdjGQ/WnL/stJdthgrd6CJXkl8LfAX9A+awfRtlln9lMLb8h5J8mdM1NWlbcFcgOuAB478vx/0Tb0RwLLx8b9M9q5to8GbgN+AfwE+NQ00y7gfmNlDwB+DtzR697Yy3fq0/4xcC7wV8CXN/XyWZ9lN8MyfSPw4f54aV8uRwFX0q7q9D9Hxt0GOAH4EXARbeO0amT4HsDHgdXA5cDLZlt3rI1PBc6fZtihfd3e1tfRt3r5c4GLgZuBy4A/GalzMO0iR68CrgH+BfgZLZj/pN/26O17y3i9sWV3TG//j4Djgbttgvf/1HpaNDLsbOD5/fFzgK/QAtFNwHeBx8ww7pdHhu0PnAn8kBaMXzNN234C/NYMbT8I+CpwI/At4OCRYTv2ZXdVX46fBO4xzTrZGnhnH/eq/njradbrh4Z8Jvqw+wKfB26gve8/Amw/VvdVwLdp4WbR1PSA3YCfAjuNjH8A7XNwlwnz+g5w+DTt+FJft7f0ZfCHwA59va/uy+vTwJKROvv0ejcD/w68h/6ZXte6GJv3Mvo2b8Kw6baNTwS+Sds2rgTeOFJnaX8tz6NtT77U72tkHT+MkW3QWL1FI+/Xv6Fte28CTgN23FCfuzl8Vl9N+9xs38ue39v+3/pyWzZD/QDfB/5yrPw3+vvlzZv6NW5uN2C7/h572lj5tsB1wIuY/F1yNu07/iv9M/U5YOeR+jNt284G3trr/oyxjHFnud05fz1sBpLsBTyBttE+HfjNJPuOjPJHwEnVrvb4EeDt1fY4PXm286iqi4E/Bc7pdbfvg95D+xLZHfjjftuSPQL4TeAxwOuTPKCXv4EWOO4LHEIL3AD0X96fom1Y9ux1X5HkkHXVneAbwP2TvCPJo0e7M1TVZ4G/Bk7p6+hBfdB1wJNoG8/nAu9I8uCRae5GC3B70/aePh64qtZ/b/0zevvvS/uC3Ch7iMfe/7PxUNoPip1py/4TSXZcxzzuSQtin6WF2PsBZ00z+teA9yQ5Msm9x6azJ/CvwFtoy/zPgY8nWdxH+RBwd1po3wV4R1XdwuR18j9pX1y/BTwIOJA1l/noej16pte3DqGFtT1ooXEvWsAb9XRacNy+qm6fKqyqa2hfoE8bGfeZwMlVdduEeX0NeGuS545tw6iqR/aHD+rL4BRamDqe9hrvTfuCHu2SchItZO7U2/ysX72oda+LUf8F3JHkxCSPH90LOsO28Rba52n7vmxemOTwsek+irZMDwGmXt/2fTrnTGjHJM+mbXf3AG6n7eFdaJbT3gd/Plb+u8DKqlo+Q93fpK3bfxktrKpf0nZOPG7+mnmn8T+AuwGfGC2sqp8AZwC/w+TvEmh54rm07dNd6et0lp+nZ9G2Rfek/Ti60zFILzyfTHIj8GXgi8BfV9VPaXslng7Qv4zuzwa4+mOSrYA/AF5fVbdU1XeAE+d7PhvIJ5Pc2G+fXI96b6qqn1XVt2jBeGoD8zTgrVX1w6payZpfZg8BFlfVm6vqF1V1GfDPtH8P1lV3Db3uwbRAfipwfVq/92n7B1fVv1bV96r5Im0vwu+MjPJL4A1VdWtV/WzWS2Jt766qlVX1Q9qeh6fPYVqzsdb7f5b1rgPeWVW39TB2CS3ozORJwDVV9b+r6udVdXNVfX2acY8A/gN4HXB5Wn/2h/RhzwQ+U1WfqapfVtWZtJDxhCS70wLzn1bVj3r7vjhDm55B2xt3XVWtpnU1eNbI8PVdr6OfiRuTvACgqlZU1Zl9OquBv6cFwFHv6ut+0nxO7K97apvxdNoPhkleSvux/xLgoiQrkjx+ugZX1Q1V9fGq+mlV3Ux73z2qz+vetM/e6/vn7susuR2cdl1MmM+PaT+ii/bZXZ3k9CS7ztC2s6vqgj7tbwMfZe3l9sa+7ZzL5+5DVfWd/oPrdcDT+nJeaF4PvHQsWO1M+8fkV5Ks6u+/nyfZu48DcPWEaV49MlyztzNw/eiP3hHrWqbHV9V/9ffsqbQf8jC7z9MJVXVhVd0+zQ/pLZ5BeuE5vKq2r6q9q+pFIxvjk/h1iPkj4JM9YM+3xbS/cVeOlG0uvzKnlt32VXX4etQb3ej/lPZXGLS9QdMth72BPUZDCvAaYNdZ1F1LVX2tqp5WVYtpgfiRtL2TE/U9aF/rB0jdSNuwjW4oV1fVz2ea5yyNv4YNfQDndO//dflBVY2eFH82bd2LWfbV7SH41VW1P20dn08LqaG9F44Yey88gvaPzl7AD6vqR7N8HXuw5ntl/HWs73od/UxsX1X/DJBklyQnJ/lBkh8DH2btL9qVa03t104D9ktyH9rew5uq6txJI/YfqX9dVQfQ9iKfCvzLdP8YJLl7kn9K8v3eti8B2/cguQdteY5u+0bbOdO6mNS2i6vqOVW1BHhgn/47p3vRSR6a5AtJVie5ibbXen2W22yNf+7uMmE+m1zf0fJpWjePKTcwtrz78t2Z1nUptO5EjI83Unb9hHLN7Hpg52n65q9rmU73HTibz9N8vN83awbpzcfnaB+S36IF6pNGhs3lqjrjdVfT/krca6Ts3my+bqH9rT5lt/WoezXTL4eVwOVjIeWeVfWEWdSdUVX9J+3vuQdOFY0OT7I17e/PvwN2rfa382doX1BMqjPhOcxu2Yy/hk1xAOct/X6mtu7ZQ+2U2bR1Ja3Lynqpqutpy34P2t+dK2l7EEffC/eoqrf1YTtOHTU/PqkJZVfRvrymjL+O+bqC1t/0af0/VbUdbc9TxsaZdl49zJ9K24P+LKbfGz1e78e0fxnuQevrPMkraX/9P7S3bap7RGifqx2TjL4XRt+jM62LdbXtu7TjBiZ+7rqTaHvA96qqewH/h5mX23x97m5j4YbLNwAvoP2jBq3v/ZIky2aocwmtv/8Ro4W9y9wfMH0XK03vHNrxDL8/Wph2ZpXH05bp+m4/ZvN5utNf1c8gvZnof9d8jHYA1o60A6SmXAvcZxaTuWuSu43ctup1l0wd0VtVd9BC3Bv7nqH9mLl/70J3PnBkkrv0DftT16PuqcAxSXZIOyXTS0eGnQv8OMmrkmyTZKskDxz5u3+mumtIOwXXC5Ls0p/fn3Zmg6/1Ua4Flo4cEX1X2p6d1cDt/W/ydZ3S7VpgpyT3Gik7n9b9YMcku9GOsh/34rRTv+1I2+N+yjrmM+9614MfAM/sy/mPWTsA7wK8rK/nI2h9VD+zjkl/GtgtySuSbJ3knkkeOmnEJH/b1++itL7VLwRWVNUNtL25T05ySG/f3dJObbekqq6m9U98b38v3CXJVDCctE4+Crw2yeIkO9P+Ot8Qp6u6J/0gurR+kH8xYBofpB28+RRmaGOS1yV5SJK7Jrkb7UwPN9LCFKy9/bonrV/0jf1994apAVX1fdpfy2/s03sYMHpcyLTrYkK77p/klVPD0vrlP501P3e/2jaOtO2HVfXzJAfS/h2cyWpad5zR13c+8Mgk9+7r/pgJ9Z6ZZL/+g+HNwMf6tnnBqaoVtO3Cy/rzS4B/Ak5O8rip7SOtD+9UnaL1t31tkj/q4+wGvI923Mc7Nvbr2NxV1U20rmD/mOTQvq1ZSuuHvor2Y3f8u2RdZv15ujMzSG9eTqIdNf8vY/2g3k/7m3VdfYMvpH1BTd2eS9t7cCFwTZKpPR4vof21cw1tD83x8/gaNrbX0ULXj2gbmZNmHn0Nb6L9rXo57R+BX+11619qT6b1JbuctrfofbRTDs1Yd4IbaWHkgiQ/oR389n+Bt/fhUwfk3JDkG73f6MtoYf1HtC/zGfvL971tHwUu6++TPXqbvkU7Av9zTA7JJ/Vhl/XbjOcr34BeQAt7N9AO2vvq2PCvA/vS1sNbgaf2kDutvhwfR1uP1wCXAo+eZvS709bJjbTlsDdtnVGtD/xhtB8aq2l7cf6CX29fn0Xbo/hdWl/uV/R6k9bJW2hB8dvABbQDUeeyzD+VNc8j/X97+Ztopxi8iXYw0SemncI0quortJD4jaq6YqZRaduQ62l71x8HPLHaQVDQDhg8sS+Dp9G6VmzTx/8a7fMw6hm0s1/cQFs2p9BPWTeLdTHqZtpBql9Pckuf13doe8Rh8rbxRcCbk9xM+5Fz6gyvm94F5a3AV/rrO6j3Mz2Fto7Po/2gG/ch2rb3GtoBZC+baT4LwJtp/zJMeTHtuJC/p53ZYxXtzBB/SDuTCdWOZXgW7QxU19PODrQN8PB1fXY1WVW9nfbe/zvamWW+TvsMPKaqbmXsu2QW01ufz9OdVtbsVihJTZIraKeN+/dN3RYtTEk+Tzt70Ps2YRtOAb5bVW9Y58ibgbSLmnx4Uy5TSbPnrwpJ0nrr3ZgezEbu7tO7idw3yW8kOZS2x+yTG7MNkjRlS7/ykiRpniU5ETgceHnvIrMx7UbrirITrcvAC6tqtucbl6R5ZdcOSZIkaQC7dkiSJEkDGKQlSZKkAQzSkiRJ0gAGaUmSJGkAg7QkSZI0gEFakiRJGuD/B0CP8rlZ7x3sAAAAAElFTkSuQmCC\n", "text/plain": [ "<Figure size 864x360 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 864x360 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "import matplotlib.pyplot as plt\n", "\n", "cat_list = train.select_dtypes(\"category\").columns.drop('target').tolist()\n", "for i in cat_list:\n", " val_counts = pd.DataFrame(train[i].value_counts())\n", " plt.figure(figsize = (12, 5))\n", " plt.title(i, fontsize = 20)\n", " if i == 'city':\n", " plt.bar(range(len(val_counts)), val_counts[i], color=\"r\", align=\"center\")\n", " plt.xticks(range(len(val_counts)), fontsize = 8)\n", " else:\n", " plt.bar(val_counts.index, val_counts[i], color=\"r\", align=\"center\")\n", " plt.xticks(val_counts.index, fontsize = 12)\n", " plt.show()" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.04843, "end_time": "2021-02-27T01:04:01.478315", "exception": false, "start_time": "2021-02-27T01:04:01.429885", "status": "completed" }, "tags": [] }, "source": [ "Let's also take a look at the relationship between each categorical variable and the outcome." ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:04:01.600879Z", "iopub.status.busy": "2021-02-27T01:04:01.599708Z", "iopub.status.idle": "2021-02-27T01:04:05.510001Z", "shell.execute_reply": "2021-02-27T01:04:05.509268Z" }, "papermill": { "duration": 3.983306, "end_time": "2021-02-27T01:04:05.510155", "exception": false, "start_time": "2021-02-27T01:04:01.526849", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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JAAAL5biBubs/keTPVvl+Vya5rbuf7e5HkhxMcmlVnZfkld19d3d3kluTXHWCdQYAgE2zljHM76qqzwxDNs4ayrYneXxqm0ND2fZheWX5TFW1p6qWq2r5yJEja6giAACszYkG5huTvDbJJUkOJ/nFoXzWuOQeKZ+pu2/q7qXuXtq2bdsJVhEAANbuhAJzdz/V3Ue7+ytJPpDk0mHVoSTnT226I8mTQ/mOGeUAALDQTigwD2OSn/fWJM/PoLE/ye6qOqOqLszky333dPfhJM9U1WXD7BhvT3L7GuoNAACb4ri3xq6qDyW5PMnZVXUoyU8nubyqLslkWMWjSd6ZJN19oKr2JXkwyXNJru3uo8NbXZPJjBtnJrljeAAAwEKryaQVi2tpaamXl5c3/bgrZ4k+5mVa9YYAACyqqrq3u5dmrXOnPwAAGCEwAwDACIEZAABGCMwAADBCYAYAgBECMwAAjDjuPMwwxqx6AMDJTg8zAACMEJgBAGCEwAwAACMEZgAAGCEwAwDACIEZAABGCMwAADBCYAYAgBECMwAAjBCYAQBghFtjn0TcphoAYP3pYQYAgBECMwAAjBCYAQBghMAMAAAjBGYAABghMAMAwAiBGQAARgjMAAAwQmAGAIARAjMAAIw4bmCuqpur6umqemCq7NVVdWdVfW54Pmtq3fVVdbCqHq6qK6bK31hV9w/r3l+18kbOAACweFbTw3xLkl0ryq5Lcld370xy1/A6VXVRkt1JLh72uaGqThv2uTHJniQ7h8fK9wQAgIVz3MDc3Z9I8mcriq9MsndY3pvkqqny27r72e5+JMnBJJdW1XlJXtndd3d3J7l1ah8AAFhYJzqG+dzuPpwkw/M5Q/n2JI9PbXdoKNs+LK8sBwCAhbbeX/qbNS65R8pnv0nVnqparqrlI0eOrFvlAADgpTrRwPzUMMwiw/PTQ/mhJOdPbbcjyZND+Y4Z5TN1903dvdTdS9u2bTvBKgIAwNqdaGDen+TqYfnqJLdPle+uqjOq6sJMvtx3zzBs45mqumyYHePtU/sAAMDCOv14G1TVh5JcnuTsqjqU5KeT/HySfVX1jiSPJXlbknT3garal+TBJM8luba7jw5vdU0mM26cmeSO4QEAAAutJpNWLK6lpaVeXl7e9OOunCX6mJdp1RtuvHlUZYFOHwDghFXVvd29NGudO/0BAMCI4w7JOFX1iyb20HUKAHAq0sMMAAAjBGYAABghMAMAwAiBGQAARgjMAAAwQmAGAIARAjMAAIwQmAEAYITADAAAIwRmAAAYITADAMAIgRkAAEYIzAAAMEJgBgCAEQIzAACMEJgBAGCEwAwAACMEZgAAGCEwAwDACIEZAABGnD7vCvBCVS983T2fegAAMKGHGQAARgjMAAAwQmAGAIARAjMAAIwQmAEAYITADAAAI9YUmKvq0aq6v6ruq6rloezVVXVnVX1ueD5ravvrq+pgVT1cVVestfIAALDR1qOH+du6+5LuXhpeX5fkru7emeSu4XWq6qIku5NcnGRXkhuq6rR1OD4AAGyYjRiScWWSvcPy3iRXTZXf1t3PdvcjSQ4muXQDjg9MqXrhAwB4adYamDvJx6rq3qraM5Sd292Hk2R4Pmco357k8al9Dw1lAACwsNZ6a+w3dfeTVXVOkjur6rMj287q25p54+chfO9Jkte85jVrrCIAAJy4NfUwd/eTw/PTSX43kyEWT1XVeUkyPD89bH4oyflTu+9I8uQx3vem7l7q7qVt27atpYoAALAmJxyYq+prq+rrnl9O8p1JHkiyP8nVw2ZXJ7l9WN6fZHdVnVFVFybZmeSeEz0+AABshrUMyTg3ye/W5FtEpyf5re7+var6oyT7quodSR5L8rYk6e4DVbUvyYNJnktybXcfXVPtAQBgg51wYO7uzyd5/YzyP03yHcfY5+eS/NyJHhMAADabO/0BAMAIgRkAAEYIzAAAMEJgBgCAEQIzAACMWOud/jiJ1Yp7M/bM+zICAJzc9DADAMAIgRkAAEYIzAAAMEJgBgCAEQIzAACMEJgBAGCEaeXYFPOaos7UeADAWulhBgCAEXqYSaInFgDgWPQwAwDACD3MrDu91QDAyURg5iVZGYYXiaAOAGwEgXnBdFYmUqkPAGCeBOYtalF6UwV8Fsmi/F4AcHIRmAEWjOAPsFgEZtgCBCgAmB+BGZI1JVJhFgBObgLzScR44o236OF4Peu36OcKAJtFYGbhCW6LQ1sAcCoSmJkb4Qs2/vfA7xnA2gnMm2QtH1o+8E4Oi96O0/VbtLoBwDwJzKegRQ9uJ2q1Y7gX/fw3o36Lfg14sVltdrwy7QqwPgTml+BUCxmzAuiLy+ZjXm2xFb9YuRXrvNFOtd/l9eTaAaeil232AatqV1U9XFUHq+q6zT4+s3XqBQ/mZ9VtUfXCx4KbVd0tdgonty3YGFuwysAWtak9zFV1WpJfTfIPkhxK8kdVtb+7H9zMemy0WT0wa+nlW8u+8+gNWlOP5jpXeNF7V/XWLZAZjXGqt89WPP+tWOdZNnpozWqH+AATmz0k49IkB7v780lSVbcluTLJSRWYNyOkLXoQXGle/2BYy/st0hc1V1vnRfm5WNP5b8Kn9iL9I3SRfjdO9JhrCV/zCmmbERgF0BO3SH9/13Jcc+OfPDY7MG9P8vjU60NJ/vYm1+GErfuH05yCwaKEqkUPCusdUhepLY5fl9l1W21YOrFjTspmmXmMGYVrqd8sa7kGq63zWo57/H3Xv83Wst2q//dtlb39q75Oq/xZWe+2Xb9zW/1+qy1bS5ut+md7DWVraYv1Pre5BNU1/Dyt5V+r/tF4bJsdmGeNMnvR5auqPUn2DC+/XFUPb2itxp2d5AszB8gp2+xjbtm2mHnpFqh+LypbQ1us+kdnTtdzM9piM67BqtrjJL4m8/qdWsVma/479aKidb7Gq7126/1+C9UWM6znR+Fa9z3hN1vnCp9wfV/s7CRfWMf32yh//VgrNjswH0py/tTrHUmeXLlRd9+U5KbNqtSYqlru7qV51wNtsUi0xWLRHotDWywObbE4Toa22OxZMv4oyc6qurCqvirJ7iT7N7kOAACwapvaw9zdz1XVu5L8fpLTktzc3Qc2sw4AAPBSbPqNS7r7o0k+utnHXYOFGBpCEm2xSLTFYtEei0NbLA5tsTi2fFtUb+WvLAIAwAbb9Dv9AQDAViIwj3Ab7/mpqvOr6uNV9VBVHaiqdw/lr66qO6vqc8PzWfOu66mgqk6rqj+uqo8Mr7XDnFTVq6rqt6vqs8Pvx9/RHvNRVT82/H16oKo+VFVfrS02R1XdXFVPV9UDU2XHvPZVdf3wWf5wVV0xn1qfvI7RHv96+Dv1mar63ap61dS6LdceAvMxTN3G+7uSXJTke6vqovnW6pTyXJL3dvc3J7ksybXD9b8uyV3dvTPJXcNrNt67kzw09Vo7zM+vJPm97v6bSV6fSbtoj01WVduT/PMkS939uky+yL472mKz3JJk14qymdd++OzYneTiYZ8bhs941s8teXF73Jnkdd39LUn+W5Lrk63bHgLzsf3/23h3918kef423myC7j7c3Z8elp/JJBRsz6QN9g6b7U1y1VwqeAqpqh1J/mGSX58q1g5zUFWvTPL3k/xGknT3X3T3F6M95uX0JGdW1elJviaT+wpoi03Q3Z9I8mcrio917a9Mclt3P9vdjyQ5mMlnPOtkVnt098e6+7nh5SczufdGskXbQ2A+tlm38d4+p7qc0qrqgiRvSPKpJOd29+FkEqqTnDPHqp0q/k2Sf5HkK1Nl2mE+/kaSI0l+cxgi8+tV9bXRHpuuu59I8gtJHktyOMmfd/fHoi3m6VjX3uf5/P1wkjuG5S3ZHgLzsc26gaMpRTZZVb0iye8keU93f2ne9TnVVNV3J3m6u++dd11IMunR/FtJbuzuNyT53/Ff/nMxjI+9MsmFSb4hyddW1ffPt1Ycg8/zOaqqn8pkmOUHny+asdnCt4fAfGyruo03G6eqXp5JWP5gd394KH6qqs4b1p+X5Ol51e8U8aYk31NVj2YyLOnbq+o/RDvMy6Ekh7r7U8Pr384kQGuPzffmJI9095Hu/sskH07yd6Mt5ulY197n+ZxU1dVJvjvJ9/VfzWO8JdtDYD42t/Geo6qqTMZpPtTdvzS1an+Sq4flq5Pcvtl1O5V09/XdvaO7L8jkd+A/d/f3RzvMRXf/zySPV9U3DUXfkeTBaI95eCzJZVX1NcPfq+/I5LsW2mJ+jnXt9yfZXVVnVNWFSXYmuWcO9TulVNWuJP8yyfd09/+ZWrUl28ONS0ZU1VsyGb/5/G28f26+NTp1VNW3JvkvSe7PX42d/clMxjHvS/KaTD6w3tbdK7/4wQaoqsuT/Hh3f3dVfX20w1xU1SWZfAHzq5J8PskPZdL5oT02WVW9L8k/yeS/m/84yY8keUW0xYarqg8luTzJ2UmeSvLTSf5TjnHth2EBP5xJW72nu+948btyoo7RHtcnOSPJnw6bfbK7/+mw/ZZrD4EZAABGGJIBAAAjBGYAABghMAMAwAiBGQAARgjMAAAwQmAGAIARAjMAAIwQmAEAYMT/AwGAJvkmTgVFAAAAAElFTkSuQmCC\n", "text/plain": [ "<Figure size 864x360 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "image/png": 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QpAEAYIAgDQAAAwRpAAAYIEgDAMAAQRoAAAYI0gAAMECQBgCAAYI0AAAMEKQBAGCAIA0AAAMEaQAAGCBIAwDAAEEaAAAGCNIAADBAkAYAgAErDtJVtamqrquq35veH15VV1bVzdP2sLm251XVLVV1U1WdMlc/oaqunz47v6pqpeMCAIDVtD/uSP9Ikhvn3r88yVXdvSPJVdP7VNVxSc5McnySU5O8rqo2TX1en2Rnkh3T69T9MC4AAFg1KwrSVbUtybckecNc+bQkF0/7Fyc5fa5+SXff2923JrklyYlVdXSSQ7v7vd3dSd481wcAANalld6R/rUk/zXJ5+dqR3X3nUkybY+c6luT3D7XbvdU2zrtL60/QFXtrKrFqlrcs2fPCocOAADjhoN0VX1rkru7+9qH22WZWj9I/YHF7gu6e6G7F7Zs2fIwTwsAAPvf5hX0fXaSb6+q5yd5fJJDq+q3ktxVVUd3953TtI27p/a7kxwz139bkjum+rZl6gAAsG4N35Hu7vO6e1t3b8/sIcJ3dfeLk1ye5Kyp2VlJLpv2L09yZlU9rqqOzeyhwvdP0z/uqaqTptU6XjLXBwAA1qWV3JHel1cnubSqzk5yW5IzkqS7d1XVpUluSHJfknO7+/6pzzlJLkpySJIrphcAAKxbNVsoY+NZWFjoxcXFNTm3Va7ZaDboZQ4A60JVXdvdC0vrvtkQAAAGCNIAADBAkAYAgAGCNAAADBCkAQBggCANAAADBGkAABggSAMAwABBGgAABgjSAAAwQJAGAIABgjQAAAwQpAEAYIAgDQAAAwRpAAAYIEgDAMAAQRoAAAYI0gAAMECQBgCAAZvXegAbUafWegjwCPVaDwAADjruSAMAwABBGgAABgjSAAAwQJAGAIABgjQAAAwQpAEAYIAgDQAAAwRpAAAYIEgDAMAAQRoAAAYI0gAAMECQBgCAAYI0AAAMEKQBAGCAIA0AAAMEaQAAGCBIAwDAAEEaAAAGCNIAADBAkAYAgAGCNAAADBgO0lV1TFW9u6purKpdVfUjU/3wqrqyqm6etofN9Tmvqm6pqpuq6pS5+glVdf302flVVSv7sQAAYHWt5I70fUn+c3d/VZKTkpxbVccleXmSq7p7R5KrpveZPjszyfFJTk3yuqraNB3r9Ul2JtkxvU5dwbgAAGDVDQfp7r6zu/902r8nyY1JtiY5LcnFU7OLk5w+7Z+W5JLuvre7b01yS5ITq+roJId293u7u5O8ea4PAACsS/tljnRVbU/yjCTXJDmqu+9MZmE7yZFTs61Jbp/rtnuqbZ32l9YBAGDdWnGQrqonJfmdJC/r7k89WNNlav0g9eXOtbOqFqtqcc+ePY98sAAAsJ+sKEhX1WMyC9G/3d1vn8p3TdM1Mm3vnuq7kxwz131bkjum+rZl6g/Q3Rd090J3L2zZsmUlQwcAgBVZyaodleSNSW7s7l+Z++jyJGdN+2cluWyufmZVPa6qjs3socL3T9M/7qmqk6ZjvmSuDwAArEubV9D32Um+O8n1VfVnU+0VSV6d5NKqOjvJbUnOSJLu3lVVlya5IbMVP87t7vunfuckuSjJIUmumF4AALBu1WyhjI1nYWGhFxcX1+bklrlmo9mg1zkArAdVdW13Lyyt+2ZDAAAYIEgDAMAAQRoAAAYI0gAAMECQBgCAAYI0AAAMEKQBAGCAIA0AAAMEaQAAGCBIAwDAAEEaAAAGCNIAADBAkAYAgAGCNAAADBCkAQBggCANAAADBGkAABggSAMAwABBGgAABgjSAAAwQJAGAIABgjQAAAwQpAEAYMDmtR4AwFJVaz0CeOS613oEwIHmjjQAAAwQpAEAYIAgDQAAAwRpAAAYIEgDAMAAQRoAAAYI0gAAMECQBgCAAYI0AAAMEKQBAGCAIA0AAAMEaQAAGCBIAwDAAEEaAAAGbF7rAQAs1am1HgIM6LUeAHCAuSMNAAADBGkAABggSAMAwIB1M0e6qk5N8pokm5K8obtfvcZDAoCDUnkMgQ2o1+FjCOvijnRVbUryG0n+fZLjkryoqo5b21EBAMC+rYsgneTEJLd090e6+7NJLkly2hqPCQAA9mm9TO3YmuT2ufe7kzxzjcYCAAc1S0yyMa2/uR3rJUgvd0U/4LdVVTuT7Jze/n1V3bSqo+JAOyLJ36z1IA5KJkTyz1xnq8V1xoxrbLWs7TX2JcsV10uQ3p3kmLn325LcsbRRd1+Q5IIDNSgOrKpa7O6FtR4HHMxcZ7C6XGOPLutljvQHkuyoqmOr6rFJzkxy+RqPCQAA9mld3JHu7vuq6geTvDOz5e8u7O5dazwsAADYp3URpJOku38/ye+v9ThYU6btwOpzncHqco09ilSvx9WtAQBgnVsvc6QBAGBDEaRZdVXVVfWbc+83V9Weqvq9h+h38kO1gUeTqrq/qv5s7rV9Fc/10ao6YrWODxtFVW2rqsuq6uaq+nBVvaaqHltVT6+q58+1+8mq+i9rOVYOPEGaA+Efkjytqg6Z3n9Tko+t4Xhgo/p0dz997vXRtR4QHMyqqpK8PcnvdveOJF+e5ElJfibJ05M8f9+9H/G5Nu2vY3HgCNIcKFck+ZZp/0VJ3rL3g6o6sar+X1VdN22/YmnnqnpiVV1YVR+Y2vkKeUhSVSdU1Xuq6tqqemdVHT3Vr66qX62qP6qqG6vqa6vq7dNdtZ+e6/+7U99d05deLXeOF1fV+6e74P/DP/g8inxjks9095uSpLvvT/KjSf5Tkl9I8sLpunjh1P646dr7SFX98N6D7Osaqqq/r6qfqqprkjzrgP5k7BeCNAfKJUnOrKrHJ/m3Sa6Z++wvkjynu5+R5L8l+dll+v9Yknd199cm+YYkv1hVT1zlMcN6c8jctI53VNVjkvx6khd09wlJLszsTtlen+3u5yT570kuS3JukqcleWlVPXVq871T34UkPzxXT5JU1VcleWGSZ3f305Pcn+S7Vu9HhHXl+CTXzhe6+1NJPprkp5O8dfrr0Funj78yySlJTkzyE1X1mIe4hp6Y5EPd/czu/uPV/mHY/9bN8ncc3Lr7g9N8zhflgcscPjnJxVW1I7Ovhn/MMof45iTfPjf/7PFJ/lWSG1dnxLAufXr6hzhJUlVPyywYXzn7C3Q2Jblzrv3eL7a6Psmu7r5z6veRzL5N9m8zC8/fMbU7JsmOqb7Xc5OckOQD0zkOSXL3fv2pYP2qzP5derj1/9Pd9ya5t6ruTnJUHvwauj/J7+zvQXPgCNIcSJcn+aUkJyeZv+v1qiTv7u7vmML21cv0rSTf2d03rfIYYSOpzALyvv4kfO+0/fzc/t73m6vq5CTPS/Ks7v7Hqro6s/9JXXqOi7v7vP01aNhAdiX5zvlCVR2a2f903r9M+/nr7P7MctaDXUOfmaaLsEGZ2sGBdGGSn+ru65fUn5x/fvjwpfvo+84kPzQ9+JGqesaqjBA2lpuSbKmqZyXJ9Gfk4x9B/ycn+bspRH9lkpOWaXNVkhdU1ZHTOQ6vqi9Z6cBhg7gqyROq6iXJPz0Q+MtJLkpyV5J/8TCP4Ro6SAnSHDDdvbu7X7PMR7+Q5Oeq6k8y+9P0cl6V2ZSPD1bVh6b38KjW3Z9N8oIkP19Vf57kz5J83SM4xB9kdmf6g5ldU+9b5hw3JHllkj+c2l2Z5OgVDh02hJ59a913JDmjqm5O8pdJPpPkFUnendnDhfMPGy53DNfQQcw3GwIAwAB3pAEAYIAgDQAAAwRpAAAYIEgDAMAAQRoAAAYI0gAAMECQBgCAAYI0AAAM+P/9lOjjP6xgfwAAAABJRU5ErkJggg==\n", "text/plain": [ "<Figure size 864x360 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 864x360 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 864x360 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 864x360 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 864x360 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 864x360 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 864x360 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 864x360 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 864x360 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "for i in cat_list:\n", " unique_vals = pd.Series(train[i].unique())\n", " plot_df = pd.DataFrame()\n", " plt.figure(figsize = (12, 5))\n", " plt.title(i, fontsize = 20)\n", " for j in unique_vals:\n", " width = .35\n", " unique_df = pd.DataFrame(train[train[i] == j])\n", " t0 = len(unique_df[unique_df['target'] == 0])\n", " t1 = len(unique_df[unique_df['target'] == 1])\n", " new = pd.DataFrame({'j' : j, 't0' : t0, 't1' : t1}, index = [0])\n", " plot_df = plot_df.append(new)\n", " plot_df = plot_df.reset_index(drop = True)\n", " plot_df = plot_df.dropna(axis = 0)\n", " if i == 'city':\n", " plt.bar(range(len(unique_vals)), plot_df['t0'], color=\"b\", align=\"center\")\n", " plt.bar(range(len(unique_vals)), plot_df['t1'], color=\"r\", align=\"center\")\n", " else:\n", " plt.bar(plot_df['j'], plot_df['t0'], color=\"b\", align=\"center\")\n", " plt.bar(plot_df['j'], plot_df['t1'], color=\"r\", align=\"center\")\n", " plt.show()" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.041768, "end_time": "2021-02-27T01:04:05.594334", "exception": false, "start_time": "2021-02-27T01:04:05.552566", "status": "completed" }, "tags": [] }, "source": [ "It seems that within some variables, some categories differ in terms of the proportion of new job seekers versus those who want to remain at their current job. Let's use a chi-squared test on each variable to see if the proportions differ to a significant degree. Features with a high chi-squared value should be useful to the model." ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:04:05.685439Z", "iopub.status.busy": "2021-02-27T01:04:05.684477Z", "iopub.status.idle": "2021-02-27T01:04:06.876795Z", "shell.execute_reply": "2021-02-27T01:04:06.877729Z" }, "papermill": { "duration": 1.241345, "end_time": "2021-02-27T01:04:06.878054", "exception": false, "start_time": "2021-02-27T01:04:05.636709", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Variable [ city ] has a chi2 statistic of [2998.78] with a p-value of [0.00]\n", "Variable [ gender ] has a chi2 statistic of [9.04] with a p-value of [0.01]\n", "Variable [ relevent_experience ] has a chi2 statistic of [315.34] with a p-value of [0.00]\n", "Variable [ enrolled_university ] has a chi2 statistic of [455.17] with a p-value of [0.00]\n", "Variable [ education_level ] has a chi2 statistic of [165.66] with a p-value of [0.00]\n", "Variable [ major_discipline ] has a chi2 statistic of [12.21] with a p-value of [0.03]\n", "Variable [ experience ] has a chi2 statistic of [701.57] with a p-value of [0.00]\n", "Variable [ company_size ] has a chi2 statistic of [45.53] with a p-value of [0.00]\n", "Variable [ company_type ] has a chi2 statistic of [35.04] with a p-value of [0.00]\n", "Variable [ last_new_job ] has a chi2 statistic of [132.50] with a p-value of [0.00]\n" ] } ], "source": [ "from scipy.stats import chi2_contingency\n", "\n", "for i in cat_list:\n", " table = pd.crosstab(train[i], train['target'])\n", " chi2_stat, p, dof, expected = chi2_contingency(table)\n", " print(\"Variable [\",i,\"] has a chi2 statistic of [%.2f] with a p-value of [%.2f]\" % (chi2_stat, p))" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.057188, "end_time": "2021-02-27T01:04:06.996919", "exception": false, "start_time": "2021-02-27T01:04:06.939731", "status": "completed" }, "tags": [] }, "source": [ "All p-values are significant at α = .05 and the chi-squared values are relatively large. Next, let's take a look at the continuous variables." ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:04:07.090694Z", "iopub.status.busy": "2021-02-27T01:04:07.089540Z", "iopub.status.idle": "2021-02-27T01:04:07.092965Z", "shell.execute_reply": "2021-02-27T01:04:07.092209Z" }, "papermill": { "duration": 0.053099, "end_time": "2021-02-27T01:04:07.093122", "exception": false, "start_time": "2021-02-27T01:04:07.040023", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "#### CONTINUOUS! ####" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.043249, "end_time": "2021-02-27T01:04:07.180370", "exception": false, "start_time": "2021-02-27T01:04:07.137121", "status": "completed" }, "tags": [] }, "source": [ "# Data Preprocessing\n", "\n", "We'll begin by preprocessing the data. First, it will be helpful to convert categorical variables to sets of binary variables. Training hours and city development index are also both on different scales; we'll also rescale training hours to be between 0 and 1." ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:04:07.275912Z", "iopub.status.busy": "2021-02-27T01:04:07.275108Z", "iopub.status.idle": "2021-02-27T01:04:07.525825Z", "shell.execute_reply": "2021-02-27T01:04:07.525065Z" }, "papermill": { "duration": 0.301856, "end_time": "2021-02-27T01:04:07.526062", "exception": false, "start_time": "2021-02-27T01:04:07.224206", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>city_development_index</th>\n", " <th>training_hours</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>count</th>\n", " <td>19158.000000</td>\n", " <td>19158.000000</td>\n", " </tr>\n", " <tr>\n", " <th>mean</th>\n", " <td>0.828848</td>\n", " <td>0.192140</td>\n", " </tr>\n", " <tr>\n", " <th>std</th>\n", " <td>0.123362</td>\n", " <td>0.179279</td>\n", " </tr>\n", " <tr>\n", " <th>min</th>\n", " <td>0.448000</td>\n", " <td>0.000000</td>\n", " </tr>\n", " <tr>\n", " <th>25%</th>\n", " <td>0.740000</td>\n", " <td>0.065672</td>\n", " </tr>\n", " <tr>\n", " <th>50%</th>\n", " <td>0.903000</td>\n", " <td>0.137313</td>\n", " </tr>\n", " <tr>\n", " <th>75%</th>\n", " <td>0.920000</td>\n", " <td>0.259701</td>\n", " </tr>\n", " <tr>\n", " <th>max</th>\n", " <td>0.949000</td>\n", " <td>1.000000</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " city_development_index training_hours\n", "count 19158.000000 19158.000000\n", "mean 0.828848 0.192140\n", "std 0.123362 0.179279\n", "min 0.448000 0.000000\n", "25% 0.740000 0.065672\n", "50% 0.903000 0.137313\n", "75% 0.920000 0.259701\n", "max 0.949000 1.000000" ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from sklearn.preprocessing import minmax_scale\n", "\n", "X_train = train.drop(['enrollee_id', 'target'], axis = 1)\n", "y_train = train['target']\n", "X_train = pd.get_dummies(X_train)\n", "X_train['training_hours'] = minmax_scale(X_train['training_hours'])\n", "y_train = train['target']\n", "X_train[{'city_development_index','training_hours'}].describe()" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.049466, "end_time": "2021-02-27T01:04:07.625721", "exception": false, "start_time": "2021-02-27T01:04:07.576255", "status": "completed" }, "tags": [] }, "source": [ "We have a lot of missing values, which we'll deal with using a simple imputation procedure." ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:04:07.731563Z", "iopub.status.busy": "2021-02-27T01:04:07.730645Z", "iopub.status.idle": "2021-02-27T01:04:08.286561Z", "shell.execute_reply": "2021-02-27T01:04:08.287549Z" }, "papermill": { "duration": 0.613224, "end_time": "2021-02-27T01:04:08.288433", "exception": false, "start_time": "2021-02-27T01:04:07.675209", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>city_development_index</th>\n", " <th>training_hours</th>\n", " <th>city_city_1</th>\n", " <th>city_city_10</th>\n", " <th>city_city_100</th>\n", " <th>city_city_101</th>\n", " <th>city_city_102</th>\n", " <th>city_city_103</th>\n", " <th>city_city_104</th>\n", " <th>city_city_105</th>\n", " <th>...</th>\n", " <th>company_type_NGO</th>\n", " <th>company_type_Other</th>\n", " <th>company_type_Public Sector</th>\n", " <th>company_type_Pvt Ltd</th>\n", " <th>last_new_job_1</th>\n", " <th>last_new_job_2</th>\n", " <th>last_new_job_3</th>\n", " <th>last_new_job_4</th>\n", " <th>last_new_job_>4</th>\n", " <th>last_new_job_never</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>0</th>\n", " <td>0.920</td>\n", " <td>0.104478</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>1.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>...</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>1.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>0.776</td>\n", " <td>0.137313</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>...</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>1.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>1.0</td>\n", " <td>0.0</td>\n", " </tr>\n", " <tr>\n", " <th>2</th>\n", " <td>0.624</td>\n", " <td>0.244776</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>...</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>1.0</td>\n", " </tr>\n", " <tr>\n", " <th>3</th>\n", " <td>0.789</td>\n", " <td>0.152239</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>...</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>1.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>1.0</td>\n", " </tr>\n", " <tr>\n", " <th>4</th>\n", " <td>0.767</td>\n", " <td>0.020896</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>...</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>1.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " </tr>\n", " <tr>\n", " <th>...</th>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " </tr>\n", " <tr>\n", " <th>19153</th>\n", " <td>0.878</td>\n", " <td>0.122388</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>...</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>1.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " </tr>\n", " <tr>\n", " <th>19154</th>\n", " <td>0.920</td>\n", " <td>0.152239</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>1.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>...</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>1.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " </tr>\n", " <tr>\n", " <th>19155</th>\n", " <td>0.920</td>\n", " <td>0.128358</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>1.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>...</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>1.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>1.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " </tr>\n", " <tr>\n", " <th>19156</th>\n", " <td>0.802</td>\n", " <td>0.286567</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>...</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>1.0</td>\n", " <td>0.0</td>\n", " <td>1.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " </tr>\n", " <tr>\n", " <th>19157</th>\n", " <td>0.855</td>\n", " <td>0.376119</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>...</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>1.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " <td>0.0</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "<p>19158 rows × 186 columns</p>\n", "</div>" ], "text/plain": [ " city_development_index training_hours city_city_1 city_city_10 \\\n", "0 0.920 0.104478 0.0 0.0 \n", "1 0.776 0.137313 0.0 0.0 \n", "2 0.624 0.244776 0.0 0.0 \n", "3 0.789 0.152239 0.0 0.0 \n", "4 0.767 0.020896 0.0 0.0 \n", "... ... ... ... ... \n", "19153 0.878 0.122388 0.0 0.0 \n", "19154 0.920 0.152239 0.0 0.0 \n", "19155 0.920 0.128358 0.0 0.0 \n", "19156 0.802 0.286567 0.0 0.0 \n", "19157 0.855 0.376119 0.0 0.0 \n", "\n", " city_city_100 city_city_101 city_city_102 city_city_103 \\\n", "0 0.0 0.0 0.0 1.0 \n", "1 0.0 0.0 0.0 0.0 \n", "2 0.0 0.0 0.0 0.0 \n", "3 0.0 0.0 0.0 0.0 \n", "4 0.0 0.0 0.0 0.0 \n", "... ... ... ... ... \n", "19153 0.0 0.0 0.0 0.0 \n", "19154 0.0 0.0 0.0 1.0 \n", "19155 0.0 0.0 0.0 1.0 \n", "19156 0.0 0.0 0.0 0.0 \n", "19157 0.0 0.0 0.0 0.0 \n", "\n", " city_city_104 city_city_105 ... company_type_NGO \\\n", "0 0.0 0.0 ... 0.0 \n", "1 0.0 0.0 ... 0.0 \n", "2 0.0 0.0 ... 0.0 \n", "3 0.0 0.0 ... 0.0 \n", "4 0.0 0.0 ... 0.0 \n", "... ... ... ... ... \n", "19153 0.0 0.0 ... 0.0 \n", "19154 0.0 0.0 ... 0.0 \n", "19155 0.0 0.0 ... 0.0 \n", "19156 0.0 0.0 ... 0.0 \n", "19157 0.0 0.0 ... 0.0 \n", "\n", " company_type_Other company_type_Public Sector company_type_Pvt Ltd \\\n", "0 0.0 0.0 0.0 \n", "1 0.0 0.0 1.0 \n", "2 0.0 0.0 0.0 \n", "3 0.0 0.0 1.0 \n", "4 0.0 0.0 0.0 \n", "... ... ... ... \n", "19153 0.0 0.0 0.0 \n", "19154 0.0 0.0 0.0 \n", "19155 0.0 0.0 1.0 \n", "19156 0.0 0.0 1.0 \n", "19157 0.0 0.0 0.0 \n", "\n", " last_new_job_1 last_new_job_2 last_new_job_3 last_new_job_4 \\\n", "0 1.0 0.0 0.0 0.0 \n", "1 0.0 0.0 0.0 0.0 \n", "2 0.0 0.0 0.0 0.0 \n", "3 0.0 0.0 0.0 0.0 \n", "4 0.0 0.0 0.0 1.0 \n", "... ... ... ... ... \n", "19153 1.0 0.0 0.0 0.0 \n", "19154 0.0 0.0 0.0 1.0 \n", "19155 0.0 0.0 0.0 1.0 \n", "19156 0.0 1.0 0.0 0.0 \n", "19157 1.0 0.0 0.0 0.0 \n", "\n", " last_new_job_>4 last_new_job_never \n", "0 0.0 0.0 \n", "1 1.0 0.0 \n", "2 0.0 1.0 \n", "3 0.0 1.0 \n", "4 0.0 0.0 \n", "... ... ... \n", "19153 0.0 0.0 \n", "19154 0.0 0.0 \n", "19155 0.0 0.0 \n", "19156 0.0 0.0 \n", "19157 0.0 0.0 \n", "\n", "[19158 rows x 186 columns]" ] }, "execution_count": 12, "metadata": {}, "output_type": "execute_result" } ], "source": [ "from sklearn.impute import SimpleImputer\n", "\n", "imputer = SimpleImputer(strategy = 'most_frequent')\n", "\n", "X_train_cols = X_train.columns\n", "X_train = imputer.fit_transform(X_train)\n", "X_train = pd.DataFrame(X_train, columns = X_train_cols)\n", "X_train" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.068052, "end_time": "2021-02-27T01:04:08.427452", "exception": false, "start_time": "2021-02-27T01:04:08.359400", "status": "completed" }, "tags": [] }, "source": [ "Now we're ready to fit our model! We'll use a random forest model, as it is great for classification problems like these. Random forest models tend to perform well with mixed data types. We'll also call for the algorithm to balance classes when " ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:04:08.579699Z", "iopub.status.busy": "2021-02-27T01:04:08.578630Z", "iopub.status.idle": "2021-02-27T01:06:10.761257Z", "shell.execute_reply": "2021-02-27T01:06:10.764161Z" }, "papermill": { "duration": 122.267624, "end_time": "2021-02-27T01:06:10.764444", "exception": false, "start_time": "2021-02-27T01:04:08.496820", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0.782 cross validated mean accuracy, with a std of 0.005\n", "0.585 cross validated mean precision, with a std of 0.016\n", "0.439 cross validated mean recall, with a std of 0.012\n", "0.681 cross validated mean F1 score, with a std of 0.007\n", "0.786 cross validated mean AUROC, with a std of 0.003\n" ] } ], "source": [ "from sklearn.ensemble import RandomForestClassifier\n", "from sklearn.model_selection import cross_val_score\n", "\n", "rf = RandomForestClassifier(random_state = rng, class_weight = \"balanced_subsample\").fit(X_train, y_train)\n", "\n", "crossval_acc = cross_val_score(rf, X_train, y_train, scoring = 'accuracy')\n", "crossval_prec = cross_val_score(rf, X_train, y_train, scoring = 'precision')\n", "crossval_rec = cross_val_score(rf, X_train, y_train, scoring = 'recall')\n", "crossval_f1 = cross_val_score(rf, X_train, y_train, scoring = 'f1_macro')\n", "crossval_auroc = cross_val_score(rf, X_train, y_train, scoring = 'roc_auc')\n", "\n", "print(\"%.3f cross validated mean accuracy, with a std of %0.3f\" % (crossval_acc.mean(), crossval_acc.std()))\n", "print(\"%.3f cross validated mean precision, with a std of %0.3f\" % (crossval_prec.mean(), crossval_prec.std()))\n", "print(\"%.3f cross validated mean recall, with a std of %0.3f\" % (crossval_rec.mean(), crossval_rec.std()))\n", "print(\"%.3f cross validated mean F1 score, with a std of %0.3f\" % (crossval_f1.mean(), crossval_f1.std()))\n", "print(\"%.3f cross validated mean AUROC, with a std of %0.3f\" % (crossval_auroc.mean(), crossval_auroc.std()))" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.064101, "end_time": "2021-02-27T01:06:10.903410", "exception": false, "start_time": "2021-02-27T01:06:10.839309", "status": "completed" }, "tags": [] }, "source": [ "This is a good start. However, our AUROC metric (which will be the final performance metric for the task) is a little on the low size at .79. Furthermore, it seems that the model's true positive rate is not...\n", "\n", "We can try to improve the performance of the model by performing hyperparameter tuning. We'll try Will Koehrson's method using RandomizedSearchCV. You can find his post [here](https://towardsdatascience.com/hyperparameter-tuning-the-random-forest-in-python-using-scikit-learn-28d2aa77dd74). " ] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": null, "end_time": null, "exception": false, "start_time": "2021-02-27T01:06:10.971331", "status": "running" }, "tags": [] }, "outputs": [], "source": [ "from sklearn.model_selection import RandomizedSearchCV\n", "\n", "search = {'bootstrap': [True, False],\n", " 'max_depth': [10, 20, 30, 40, 50, 60, 70, 80, 90, 100, None],\n", " 'max_features': ['auto', 'sqrt'],\n", " 'min_samples_leaf': [1, 2, 4],\n", " 'min_samples_split': [2, 5, 10],\n", " 'n_estimators': [200, 400, 600, 800, 1000, 1200, 1400, 1600, 1800, 2000]}\n", "\n", "rf_ht = RandomizedSearchCV(rf, search, random_state = rng, n_iter = 100).fit(X_train, y_train)\n", "\n", "crossval_acc = cross_val_score(rf_ht, X_train, y_train, scoring = 'accuracy')\n", "crossval_prec = cross_val_score(rf_ht, X_train, y_train, scoring = 'precision')\n", "crossval_rec = cross_val_score(rf_ht, X_train, y_train, scoring = 'recall')\n", "crossval_f1 = cross_val_score(rf_ht, X_train, y_train, scoring = 'f1_macro')\n", "crossval_auroc = cross_val_score(rf_ht, X_train, y_train, scoring = 'roc_auc')\n", "\n", "print(\"%.3f cross validated mean accuracy, with a std of %0.3f\" % (crossval_acc.mean(), crossval_acc.std()))\n", "print(\"%.3f cross validated mean precision, with a std of %0.3f\" % (crossval_prec.mean(), crossval_prec.std()))\n", "print(\"%.3f cross validated mean recall, with a std of %0.3f\" % (crossval_rec.mean(), crossval_rec.std()))\n", "print(\"%.3f cross validated mean F1 score, with a std of %0.3f\" % (crossval_f1.mean(), crossval_f1.std()))\n", "print(\"%.3f cross validated mean AUROC, with a std of %0.3f\" % (crossval_auroc.mean(), crossval_auroc.std()))" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "source": [ "Now that we have a model that is distinguishing between those who want to change jobs and those who don't, we can now examine which variables were important to the model." ] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "outputs": [], "source": [ "#### permutation importance: takes a long time! ####\n", "\n", "# from sklearn.inspection import permutation_importance\n", "\n", "# perm_imp = permutation_importance(rf, X_train, y_train)\n", "\n", "# import matplotlib.pyplot as plt\n", "\n", "# plt.figure(figsize = (20,10))\n", "# plt.title(\"Permutation Feature Importances - Random Forest\", fontsize = 20)\n", "# plt.bar(range(X_impute_train.shape[1]), perm_imp['importances_mean'], yerr = perm_imp['importances_std'], color=\"r\", align=\"center\")\n", "# plt.xticks(range(X_impute_train.shape[1]))\n", "# plt.show()\n", "\n", "# var_imp = pd.DataFrame({'variable': X_impute_train.columns.values,\n", "# 'mean_importance': perm_imp['importances_mean']}).sort_values(by = 'mean_importance', ascending = False)\n", "# var_imp\n" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "source": [ "Finally, we'll examine the test data, preprocess it, and generate our predicted classes, completing our task." ] }, { "cell_type": "code", "execution_count": null, "metadata": { "papermill": { "duration": null, "end_time": null, "exception": null, "start_time": null, "status": "pending" }, "tags": [] }, "outputs": [], "source": [ "# pd.DataFrame({'dtype': test.dtypes,\n", "# 'null_count': test.isna().sum()})" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.4" }, "papermill": { "default_parameters": {}, "duration": null, "end_time": null, "environment_variables": {}, "exception": null, "input_path": "__notebook__.ipynb", "output_path": "__notebook__.ipynb", "parameters": {}, "start_time": "2021-02-27T01:03:49.146701", "version": "2.2.2" } }, "nbformat": 4, "nbformat_minor": 4 }	0055/330/55330434.ipynb	s3://data-agents/kaggle-outputs/sharded/012_00055.jsonl.gz
{"cells":[{"metadata":{"trusted":true},"cell_type":"code","source":"import os\nfrom tensorflow.keras.layers.experimental import preprocessing\nimport numpy as np\nimport matplotlib.pyplot as plt\nimport pandas as pd\nimport tensorflow as tf\nfrom tensorflow.keras import layers\nfrom kaggle_datasets import KaggleDatasets\nfrom sklearn.model_selection import train_test_split\nfrom keras.layers import Dense, Flatten, Activation, Conv2D, MaxPooling2D, Dropout, Conv2D,MaxPooling2D,GlobalAveragePooling2D,BatchNormalization\nfrom tensorflow.keras import Model\nfrom keras.applications import ResNet50 \nfrom tensorflow.keras.applications import ResNet152\nfrom keras.applications.inception_resnet_v2 import InceptionResNetV2\nfrom keras.applications.inception_v3 import InceptionV3\nfrom keras.models import Sequential\nfrom keras import optimizers\nfrom keras.optimizers import Adam,RMSprop\nfrom keras.callbacks import EarlyStopping\nfrom keras.callbacks import ReduceLROnPlateau\nfrom keras.callbacks import ModelCheckpoint\nimport tensorflow_hub as hub","execution_count":1,"outputs":[]},{"metadata":{"trusted":true,"collapsed":true},"cell_type":"code","source":"print(\"update TPU server tensorflow version...\")\n\n!pip install cloud-tpu-client\nimport tensorflow as tf \nfrom cloud_tpu_client import Client\nprint(tf.__version__)\nClient().configure_tpu_version(tf.__version__, restart_type='ifNeeded')","execution_count":2,"outputs":[{"output_type":"stream","text":"update TPU server tensorflow version...\nRequirement already satisfied: cloud-tpu-client in /opt/conda/lib/python3.7/site-packages (0.10)\nRequirement already satisfied: oauth2client in /opt/conda/lib/python3.7/site-packages (from cloud-tpu-client) (4.1.3)\nRequirement already satisfied: google-api-python-client==1.8.0 in /opt/conda/lib/python3.7/site-packages (from cloud-tpu-client) (1.8.0)\nRequirement already satisfied: httplib2<1dev,>=0.9.2 in /opt/conda/lib/python3.7/site-packages (from google-api-python-client==1.8.0->cloud-tpu-client) (0.18.1)\nRequirement already satisfied: six<2dev,>=1.6.1 in /opt/conda/lib/python3.7/site-packages (from google-api-python-client==1.8.0->cloud-tpu-client) (1.15.0)\nRequirement already satisfied: google-auth-httplib2>=0.0.3 in /opt/conda/lib/python3.7/site-packages (from google-api-python-client==1.8.0->cloud-tpu-client) (0.0.4)\nRequirement already satisfied: google-api-core<2dev,>=1.13.0 in /opt/conda/lib/python3.7/site-packages (from google-api-python-client==1.8.0->cloud-tpu-client) (1.22.4)\nRequirement already satisfied: uritemplate<4dev,>=3.0.0 in /opt/conda/lib/python3.7/site-packages (from google-api-python-client==1.8.0->cloud-tpu-client) (3.0.1)\nRequirement already satisfied: google-auth>=1.4.1 in /opt/conda/lib/python3.7/site-packages (from google-api-python-client==1.8.0->cloud-tpu-client) (1.24.0)\nRequirement already satisfied: protobuf>=3.12.0 in /opt/conda/lib/python3.7/site-packages (from google-api-core<2dev,>=1.13.0->google-api-python-client==1.8.0->cloud-tpu-client) (3.14.0)\nRequirement already satisfied: pytz in /opt/conda/lib/python3.7/site-packages (from google-api-core<2dev,>=1.13.0->google-api-python-client==1.8.0->cloud-tpu-client) (2020.5)\nRequirement already satisfied: setuptools>=34.0.0 in /opt/conda/lib/python3.7/site-packages (from google-api-core<2dev,>=1.13.0->google-api-python-client==1.8.0->cloud-tpu-client) (49.6.0.post20201009)\nRequirement already satisfied: googleapis-common-protos<2.0dev,>=1.6.0 in /opt/conda/lib/python3.7/site-packages (from google-api-core<2dev,>=1.13.0->google-api-python-client==1.8.0->cloud-tpu-client) (1.52.0)\nRequirement already satisfied: requests<3.0.0dev,>=2.18.0 in /opt/conda/lib/python3.7/site-packages (from google-api-core<2dev,>=1.13.0->google-api-python-client==1.8.0->cloud-tpu-client) (2.25.1)\nRequirement already satisfied: rsa<5,>=3.1.4 in /opt/conda/lib/python3.7/site-packages (from google-auth>=1.4.1->google-api-python-client==1.8.0->cloud-tpu-client) (4.6)\nRequirement already satisfied: pyasn1-modules>=0.2.1 in /opt/conda/lib/python3.7/site-packages (from google-auth>=1.4.1->google-api-python-client==1.8.0->cloud-tpu-client) (0.2.7)\nRequirement already satisfied: cachetools<5.0,>=2.0.0 in /opt/conda/lib/python3.7/site-packages (from google-auth>=1.4.1->google-api-python-client==1.8.0->cloud-tpu-client) (4.1.1)\nRequirement already satisfied: pyasn1<0.5.0,>=0.4.6 in /opt/conda/lib/python3.7/site-packages (from pyasn1-modules>=0.2.1->google-auth>=1.4.1->google-api-python-client==1.8.0->cloud-tpu-client) (0.4.8)\nRequirement already satisfied: idna<3,>=2.5 in /opt/conda/lib/python3.7/site-packages (from requests<3.0.0dev,>=2.18.0->google-api-core<2dev,>=1.13.0->google-api-python-client==1.8.0->cloud-tpu-client) (2.10)\nRequirement already satisfied: certifi>=2017.4.17 in /opt/conda/lib/python3.7/site-packages (from requests<3.0.0dev,>=2.18.0->google-api-core<2dev,>=1.13.0->google-api-python-client==1.8.0->cloud-tpu-client) (2020.12.5)\nRequirement already satisfied: chardet<5,>=3.0.2 in /opt/conda/lib/python3.7/site-packages (from requests<3.0.0dev,>=2.18.0->google-api-core<2dev,>=1.13.0->google-api-python-client==1.8.0->cloud-tpu-client) (3.0.4)\nRequirement already satisfied: urllib3<1.27,>=1.21.1 in /opt/conda/lib/python3.7/site-packages (from requests<3.0.0dev,>=2.18.0->google-api-core<2dev,>=1.13.0->google-api-python-client==1.8.0->cloud-tpu-client) (1.26.2)\n2.4.1\n","name":"stdout"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"# Initializing Parameters.\nimg_size = 224\n","execution_count":3,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"def auto_select_accelerator():\n try:\n tpu = tf.distribute.cluster_resolver.TPUClusterResolver()\n tf.config.experimental_connect_to_cluster(tpu)\n tf.tpu.experimental.initialize_tpu_system(tpu)\n strategy = tf.distribute.experimental.TPUStrategy(tpu)\n print(\"Running on TPU:\", tpu.master())\n except ValueError:\n strategy = tf.distribute.get_strategy()\n print(f\"Running on {strategy.num_replicas_in_sync} replicas\")\n \n return strategy\n\n\ndef build_decoder(with_labels=True, target_size=(224, 224), ext='jpg'):\n def decode(path):\n file_bytes = tf.io.read_file(path)\n if ext == 'png':\n img = tf.image.decode_png(file_bytes, channels=3)\n elif ext in ['jpg', 'jpeg']:\n img = tf.image.decode_jpeg(file_bytes, channels=3)\n else:\n raise ValueError(\"Image extension not supported\")\n\n img = tf.cast(img, tf.float32) / 255.0\n img = tf.image.resize(img, target_size)\n\n return img\n \n def decode_with_labels(path, label):\n return decode(path), label\n \n return decode_with_labels if with_labels else decode\n\n\ndef build_augmenter(with_labels=True):\n def augment(img):\n img = tf.image.random_flip_left_right(img)\n img = tf.image.random_flip_up_down(img)\n img = tf.image.random_hue(img, 0.01)\n img = tf.image.random_saturation(img, 0.70, 1.30)\n img = tf.image.random_contrast(img, 0.80, 1.20)\n img = tf.image.random_brightness(img, 0.10)\n return img\n \n def augment_with_labels(img, label):\n return augment(img), label\n \n return augment_with_labels if with_labels else augment\n\n\ndef build_dataset(paths, labels=None, bsize=32, cache=True,\n decode_fn=None, augment_fn=None,\n augment=True, repeat=True, shuffle=1024, \n cache_dir=\"\"):\n if cache_dir != \"\" and cache is True:\n os.makedirs(cache_dir, exist_ok=True)\n \n if decode_fn is None:\n decode_fn = build_decoder(labels is not None)\n \n if augment_fn is None:\n augment_fn = build_augmenter(labels is not None)\n \n AUTO = tf.data.experimental.AUTOTUNE\n slices = paths if labels is None else (paths, labels)\n \n dset = tf.data.Dataset.from_tensor_slices(slices)\n dset = dset.map(decode_fn, num_parallel_calls=AUTO)\n dset = dset.cache(cache_dir) if cache else dset\n dset = dset.map(augment_fn, num_parallel_calls=AUTO) if augment else dset\n dset = dset.repeat() if repeat else dset\n dset = dset.shuffle(shuffle) if shuffle else dset\n dset = dset.batch(bsize).prefetch(AUTO)\n \n return dset","execution_count":4,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"COMPETITION_NAME = \"ranzcr-clip-catheter-line-classification\"\nstrategy = auto_select_accelerator()\nBATCH_SIZE = strategy.num_replicas_in_sync * 4\nGCS_DS_PATH = KaggleDatasets().get_gcs_path(COMPETITION_NAME)\nprint('batch size', BATCH_SIZE)","execution_count":5,"outputs":[{"output_type":"stream","text":"Running on TPU: grpc://10.0.0.2:8470\nRunning on 8 replicas\nbatch size 32\n","name":"stdout"}]},{"metadata":{},"cell_type":"markdown","source":"# Create Dataset."},{"metadata":{"trusted":true},"cell_type":"code","source":"path = '/kaggle/input/ranzcr-clip-catheter-line-classification/'\ntrain_df = pd.read_csv(path + 'train.csv')\ntrain_images = GCS_DS_PATH + \"/train/\" + train_df['StudyInstanceUID'] + '.jpg'\n\nsample_submissions_df = pd.read_csv(path + 'sample_submission.csv')\ntest_images = GCS_DS_PATH + \"/test/\" + sample_submissions_df['StudyInstanceUID'] + '.jpg'\n\n\n\n# Get the multi-labels.\nlabel_columns = sample_submissions_df.columns[1:]\nlabels = train_df[label_columns].values","execution_count":6,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Split Training Data."},{"metadata":{"trusted":true},"cell_type":"code","source":"# Train Test Split.\ntrain_img, valid_img, train_labels, valid_labels = train_test_split(train_images, \n labels, \n test_size=0.10, \n random_state=42,\n shuffle=True\n )","execution_count":7,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Build TensorFlow Dataset."},{"metadata":{"trusted":true},"cell_type":"code","source":"# Build the Tensorflow Train and Validation datasets.\n\ndecoder = build_decoder(with_labels=True, \n target_size=(img_size, img_size)\n )\n\ntrain_data = build_dataset(train_img,\n train_labels, \n bsize=BATCH_SIZE, \n decode_fn=decoder \n )\n\nvalid_data = build_dataset(valid_img, \n valid_labels, \n bsize=BATCH_SIZE, \n repeat=False, \n shuffle=False, \n augment=False, \n decode_fn=decoder\n )","execution_count":8,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Visualizing Data."},{"metadata":{"trusted":true},"cell_type":"code","source":"# Visualize training data with augmentation.\nimport matplotlib.pyplot as plt\n\ndata, _ = train_data.take(2)\nimages = data[0].numpy()\n\nfig, axes = plt.subplots(4, 4, figsize=(12,12))\naxes = axes.flatten()\nfor img, ax in zip(images, axes):\n ax.imshow(img)\n ax.axis('off')\nplt.tight_layout()\nplt.show()","execution_count":null,"outputs":[]},{"metadata":{},"cell_type":"markdown","source":"# Building Model :Transfer learning with BiT_m_r_152x4."},{"metadata":{"trusted":true},"cell_type":"code","source":"# Function for decaying the learning rate.\n# In BiT-HyperRule, we use a vanilla SGD optimiser with an initial learning rate of 0.003, momentum 0.9 and batch size 512. \n# We decay the learning rate by a factor of 10 at 30%, 60% and 90% of the training steps.\n\ndef decay(epoch):\n if epoch < 6:\n return 1e-3\n elif epoch >= 6 and epoch < 12:\n return 1e-4\n else:\n return 1e-5\n# Callback for printing the LR at the end of each epoch.\nclass PrintLR(tf.keras.callbacks.Callback):\n def on_epoch_end(self, epoch, logs=None):\n print('\\nLearning rate for epoch {} is {}'.format(epoch + 1,\n model.optimizer.lr.numpy()))","execution_count":null,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"MODELPATH = KaggleDatasets().get_gcs_path('big-transfer-models-without-top')\n# module = hub.KerasLayer(f'{MODELPATH}/bit_m-r101x1_1/')\nmodule = hub.KerasLayer(f'{MODELPATH}/bit_m-r101x3_1/')\n# module = hub.KerasLayer(f'{MODELPATH}/bit_m-r152x4_1/')\n# module = hub.KerasLayer(f'{MODELPATH}/bit_m-r50x1_1/')\n# module = hub.KerasLayer(f'{MODELPATH}/bit_m-r50x3_1/')","execution_count":9,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"with strategy.scope():\n inputs = tf.keras.layers.Input(shape=(224,224,3))\n \n MODELPATH = KaggleDatasets().get_gcs_path('big-transfer-models-without-top')\n module = hub.KerasLayer(f'{MODELPATH}/bit_m-r101x3_1/')\n \n back_bone = module\n back_bone.trainable = True\n logits = back_bone(inputs)\n outputs = tf.keras.layers.Dense(11, activation='sigmoid', dtype='float32')(logits)\n model = tf.keras.Model(inputs=inputs, outputs=outputs, name='Dr_Kudzayi_bit_m-r152x4_1_ranzcr_clip_catheter_possition_model')\n \n # Compile full Model.\n model.compile(optimizer = tf.keras.optimizers.SGD(learning_rate=0.003, momentum=0.9),\n loss='binary_crossentropy',\n metrics=[tf.keras.metrics.AUC(name='auc',multi_label=True)]\n )\n \n model.summary()","execution_count":10,"outputs":[{"output_type":"stream","text":"Model: \"Dr_Kudzayi_bit_m-r152x4_1_ranzcr_clip_catheter_possition_model\"\n_________________________________________________________________\nLayer (type) Output Shape Param # \n=================================================================\ninput_1 (InputLayer) [(None, 224, 224, 3)] 0 \n_________________________________________________________________\nkeras_layer_1 (KerasLayer) (None, 6144) 381789888 \n_________________________________________________________________\ndense (Dense) (None, 11) 67595 \n=================================================================\nTotal params: 381,857,483\nTrainable params: 381,857,483\nNon-trainable params: 0\n_________________________________________________________________\n","name":"stdout"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"steps_per_epoch = train_images.shape[0] // BATCH_SIZE","execution_count":11,"outputs":[]},{"metadata":{"trusted":true},"cell_type":"code","source":"# Save best Model weights.\ncheck_point = ModelCheckpoint('BiT_m_r152x4_1_RANZCR_Model_Best_Weights_TPU.h5',\n monitor = 'val_loss',\n save_best_only = True, \n mode = 'min',\n verbose = 1\n )\n\n# Reduce learning rate when a metric has stopped improving.\nreduce_learning_rate = tf.keras.callbacks.ReduceLROnPlateau(monitor=\"val_loss\", \n patience=2, \n factor=0.1,\n min_delta = 1e-4, \n min_lr=1e-6, \n mode='min',\n verbose = 1\n )\n\nearly_stop = EarlyStopping(monitor = 'val_loss', \n min_delta = 1e-4, \n patience = 6, \n mode = 'min', \n restore_best_weights = True, \n verbose = 1) \n\n# lrschedule = tf.keras.callbacks.LearningRateScheduler(decay)\n \n\ncallbacks_list = [check_point,reduce_learning_rate]\n\ninitial_epochs = 20\n\n# Train Model..\nhistory = model.fit(train_data, \n validation_data=valid_data,\n epochs= initial_epochs,\n steps_per_epoch=steps_per_epoch , \n callbacks=callbacks_list\n )","execution_count":12,"outputs":[{"output_type":"stream","text":"Epoch 1/20\n940/940 [==============================] - 1147s 1s/step - loss: 0.2805 - auc: 0.7123 - val_loss: 0.2210 - val_auc: 0.8302\n\nEpoch 00001: val_loss improved from inf to 0.22100, saving model to BiT_m_r152x4_1_RANZCR_Model_Best_Weights_TPU.h5\nEpoch 2/20\n940/940 [==============================] - 169s 180ms/step - loss: 0.2159 - auc: 0.8141 - val_loss: 0.2021 - val_auc: 0.8500\n\nEpoch 00002: val_loss improved from 0.22100 to 0.20211, saving model to BiT_m_r152x4_1_RANZCR_Model_Best_Weights_TPU.h5\nEpoch 3/20\n940/940 [==============================] - 169s 180ms/step - loss: 0.2070 - auc: 0.8347 - val_loss: 0.1967 - val_auc: 0.8632\n\nEpoch 00003: val_loss improved from 0.20211 to 0.19669, saving model to BiT_m_r152x4_1_RANZCR_Model_Best_Weights_TPU.h5\nEpoch 4/20\n940/940 [==============================] - 169s 180ms/step - loss: 0.1990 - auc: 0.8516 - val_loss: 0.2013 - val_auc: 0.8660\n\nEpoch 00004: val_loss did not improve from 0.19669\nEpoch 5/20\n940/940 [==============================] - 169s 180ms/step - loss: 0.1908 - auc: 0.8640 - val_loss: 0.1910 - val_auc: 0.8767\n\nEpoch 00005: val_loss improved from 0.19669 to 0.19098, saving model to BiT_m_r152x4_1_RANZCR_Model_Best_Weights_TPU.h5\nEpoch 6/20\n940/940 [==============================] - 174s 185ms/step - loss: 0.1804 - auc: 0.8826 - val_loss: 0.1897 - val_auc: 0.8893\n\nEpoch 00006: val_loss improved from 0.19098 to 0.18969, saving model to BiT_m_r152x4_1_RANZCR_Model_Best_Weights_TPU.h5\nEpoch 7/20\n940/940 [==============================] - 169s 180ms/step - loss: 0.1706 - auc: 0.8949 - val_loss: 0.1854 - val_auc: 0.8926\n\nEpoch 00007: val_loss improved from 0.18969 to 0.18537, saving model to BiT_m_r152x4_1_RANZCR_Model_Best_Weights_TPU.h5\nEpoch 8/20\n940/940 [==============================] - 169s 180ms/step - loss: 0.1618 - auc: 0.9092 - val_loss: 0.1951 - val_auc: 0.8895\n\nEpoch 00008: val_loss did not improve from 0.18537\nEpoch 9/20\n940/940 [==============================] - 169s 180ms/step - loss: 0.1513 - auc: 0.9212 - val_loss: 0.1944 - val_auc: 0.8855\n\nEpoch 00009: val_loss did not improve from 0.18537\n\nEpoch 00009: ReduceLROnPlateau reducing learning rate to 0.00030000000260770325.\nEpoch 10/20\n940/940 [==============================] - 169s 180ms/step - loss: 0.1320 - auc: 0.9407 - val_loss: 0.1931 - val_auc: 0.8909\n\nEpoch 00010: val_loss did not improve from 0.18537\nEpoch 11/20\n940/940 [==============================] - 169s 180ms/step - loss: 0.1116 - auc: 0.9510 - val_loss: 0.1996 - val_auc: 0.8877\n\nEpoch 00011: val_loss did not improve from 0.18537\n\nEpoch 00011: ReduceLROnPlateau reducing learning rate to 3.000000142492354e-05.\nEpoch 12/20\n940/940 [==============================] - 169s 180ms/step - loss: 0.1009 - auc: 0.9617 - val_loss: 0.2019 - val_auc: 0.8866\n\nEpoch 00012: val_loss did not improve from 0.18537\nEpoch 13/20\n940/940 [==============================] - 169s 180ms/step - loss: 0.0993 - auc: 0.9663 - val_loss: 0.2035 - val_auc: 0.8876\n\nEpoch 00013: val_loss did not improve from 0.18537\n\nEpoch 00013: ReduceLROnPlateau reducing learning rate to 3.000000106112566e-06.\nEpoch 14/20\n940/940 [==============================] - 169s 180ms/step - loss: 0.0960 - auc: 0.9676 - val_loss: 0.2034 - val_auc: 0.8868\n\nEpoch 00014: val_loss did not improve from 0.18537\nEpoch 15/20\n940/940 [==============================] - 169s 180ms/step - loss: 0.0948 - auc: 0.9650 - val_loss: 0.2035 - val_auc: 0.8853\n\nEpoch 00015: val_loss did not improve from 0.18537\n\nEpoch 00015: ReduceLROnPlateau reducing learning rate to 1e-06.\nEpoch 16/20\n940/940 [==============================] - 169s 180ms/step - loss: 0.0942 - auc: 0.9658 - val_loss: 0.2036 - val_auc: 0.8865\n\nEpoch 00016: val_loss did not improve from 0.18537\nEpoch 17/20\n940/940 [==============================] - 169s 179ms/step - loss: 0.0929 - auc: 0.9689 - val_loss: 0.2036 - val_auc: 0.8861\n\nEpoch 00017: val_loss did not improve from 0.18537\nEpoch 18/20\n940/940 [==============================] - 169s 180ms/step - loss: 0.0939 - auc: 0.9696 - val_loss: 0.2038 - val_auc: 0.8849\n\nEpoch 00018: val_loss did not improve from 0.18537\nEpoch 19/20\n940/940 [==============================] - 169s 180ms/step - loss: 0.0961 - auc: 0.9683 - val_loss: 0.2038 - val_auc: 0.8844\n\nEpoch 00019: val_loss did not improve from 0.18537\nEpoch 20/20\n940/940 [==============================] - 169s 179ms/step - loss: 0.0970 - auc: 0.9665 - val_loss: 0.2039 - val_auc: 0.8844\n\nEpoch 00020: val_loss did not improve from 0.18537\n","name":"stdout"}]},{"metadata":{"trusted":true},"cell_type":"code","source":"# Reduce learning rate when a metric has stopped improving.\nreduce_learning_rate = tf.keras.callbacks.ReduceLROnPlateau(monitor=\"val_auc\", \n patience=2, \n factor=0.1,\n min_delta = 1e-4, \n min_lr=1e-6, \n mode='max',\n verbose = 1\n )\n\n\n# Save best Model weights.\ncheck_point = ModelCheckpoint('./BiT_m_r_152x4_RANZCR_Model_Best_Weights_TPU.h5',\n monitor = 'val_auc',\n save_best_only = True, \n mode = 'max',\n verbose = 1\n )\n \n\n\n\n\ncallbacks_list = [reduce_learning_rate, check_point]\n\ninitial_epochs = 50\n\n# Train Model......\n\n\nhistory = model.fit(train_data, \n validation_data=valid_data,\n epochs=initial_epochs,\n steps_per_epoch=steps_per_epoch , \n callbacks=callbacks_list\n )","execution_count":null,"outputs":[]}],"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.7.9","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"}},"nbformat":4,"nbformat_minor":4}	0055/330/55330441.ipynb	s3://data-agents/kaggle-outputs/sharded/012_00055.jsonl.gz
{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": { "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19", "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5", "execution": { "iopub.execute_input": "2021-02-27T01:10:56.458975Z", "iopub.status.busy": "2021-02-27T01:10:56.458261Z", "iopub.status.idle": "2021-02-27T01:10:56.471510Z", "shell.execute_reply": "2021-02-27T01:10:56.472068Z" }, "papermill": { "duration": 0.046411, "end_time": "2021-02-27T01:10:56.472384", "exception": false, "start_time": "2021-02-27T01:10:56.425973", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "/kaggle/input/stroke-prediction-dataset/healthcare-dataset-stroke-data.csv\n" ] } ], "source": [ "# This Python 3 environment comes with many helpful analytics libraries installed\n", "# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n", "# For example, here's several helpful packages to load\n", "\n", "import numpy as np # linear algebra\n", "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n", "\n", "# Input data files are available in the read-only \"../input/\" directory\n", "# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n", "\n", "import os\n", "for dirname, _, filenames in os.walk('/kaggle/input'):\n", " for filename in filenames:\n", " print(os.path.join(dirname, filename))\n", "\n", "# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n", "# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session" ] }, { "cell_type": "code", "execution_count": 2, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:10:56.529499Z", "iopub.status.busy": "2021-02-27T01:10:56.528835Z", "iopub.status.idle": "2021-02-27T01:10:58.120735Z", "shell.execute_reply": "2021-02-27T01:10:58.121661Z" }, "papermill": { "duration": 1.621871, "end_time": "2021-02-27T01:10:58.121907", "exception": false, "start_time": "2021-02-27T01:10:56.500036", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "import matplotlib.pyplot as plt\n", "import seaborn as sns\n", "from sklearn.model_selection import train_test_split\n", "from sklearn.preprocessing import StandardScaler\n", "from sklearn.ensemble import AdaBoostClassifier\n", "from sklearn.tree import DecisionTreeClassifier\n", "from sklearn.model_selection import cross_val_score\n", "from sklearn.linear_model import LogisticRegression\n", "from sklearn.ensemble import GradientBoostingClassifier\n", "from sklearn.svm import SVC\n", "from sklearn.ensemble import RandomForestClassifier\n", "from sklearn.ensemble import GradientBoostingClassifier\n", "from sklearn.metrics import accuracy_score, recall_score, f1_score\n", "from sklearn.metrics import confusion_matrix\n", "from sklearn.metrics import classification_report\n", "from sklearn.model_selection import GridSearchCV\n", "from sklearn.pipeline import Pipeline" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.02425, "end_time": "2021-02-27T01:10:58.170998", "exception": false, "start_time": "2021-02-27T01:10:58.146748", "status": "completed" }, "tags": [] }, "source": [ "# EDA" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:10:58.227636Z", "iopub.status.busy": "2021-02-27T01:10:58.226973Z", "iopub.status.idle": "2021-02-27T01:10:58.266168Z", "shell.execute_reply": "2021-02-27T01:10:58.264137Z" }, "papermill": { "duration": 0.06662, "end_time": "2021-02-27T01:10:58.266354", "exception": false, "start_time": "2021-02-27T01:10:58.199734", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "df = pd.read_csv('/kaggle/input/stroke-prediction-dataset/healthcare-dataset-stroke-data.csv')" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:10:58.334006Z", "iopub.status.busy": "2021-02-27T01:10:58.333256Z", "iopub.status.idle": "2021-02-27T01:10:58.361439Z", "shell.execute_reply": "2021-02-27T01:10:58.361957Z" }, "papermill": { "duration": 0.068468, "end_time": "2021-02-27T01:10:58.362148", "exception": false, "start_time": "2021-02-27T01:10:58.293680", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>id</th>\n", " <th>gender</th>\n", " <th>age</th>\n", " <th>hypertension</th>\n", " <th>heart_disease</th>\n", " <th>ever_married</th>\n", " <th>work_type</th>\n", " <th>Residence_type</th>\n", " <th>avg_glucose_level</th>\n", " <th>bmi</th>\n", " <th>smoking_status</th>\n", " <th>stroke</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>0</th>\n", " <td>9046</td>\n", " <td>Male</td>\n", " <td>67.0</td>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>Yes</td>\n", " <td>Private</td>\n", " <td>Urban</td>\n", " <td>228.69</td>\n", " <td>36.6</td>\n", " <td>formerly smoked</td>\n", " <td>1</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>51676</td>\n", " <td>Female</td>\n", " <td>61.0</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>Yes</td>\n", " <td>Self-employed</td>\n", " <td>Rural</td>\n", " <td>202.21</td>\n", " <td>NaN</td>\n", " <td>never smoked</td>\n", " <td>1</td>\n", " </tr>\n", " <tr>\n", " <th>2</th>\n", " <td>31112</td>\n", " <td>Male</td>\n", " <td>80.0</td>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>Yes</td>\n", " <td>Private</td>\n", " <td>Rural</td>\n", " <td>105.92</td>\n", " <td>32.5</td>\n", " <td>never smoked</td>\n", " <td>1</td>\n", " </tr>\n", " <tr>\n", " <th>3</th>\n", " <td>60182</td>\n", " <td>Female</td>\n", " <td>49.0</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>Yes</td>\n", " <td>Private</td>\n", " <td>Urban</td>\n", " <td>171.23</td>\n", " <td>34.4</td>\n", " <td>smokes</td>\n", " <td>1</td>\n", " </tr>\n", " <tr>\n", " <th>4</th>\n", " <td>1665</td>\n", " <td>Female</td>\n", " <td>79.0</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>Yes</td>\n", " <td>Self-employed</td>\n", " <td>Rural</td>\n", " <td>174.12</td>\n", " <td>24.0</td>\n", " <td>never smoked</td>\n", " <td>1</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "</div>" ], "text/plain": [ " id gender age hypertension heart_disease ever_married \\\n", "0 9046 Male 67.0 0 1 Yes \n", "1 51676 Female 61.0 0 0 Yes \n", "2 31112 Male 80.0 0 1 Yes \n", "3 60182 Female 49.0 0 0 Yes \n", "4 1665 Female 79.0 1 0 Yes \n", "\n", " work_type Residence_type avg_glucose_level bmi smoking_status \\\n", "0 Private Urban 228.69 36.6 formerly smoked \n", "1 Self-employed Rural 202.21 NaN never smoked \n", "2 Private Rural 105.92 32.5 never smoked \n", "3 Private Urban 171.23 34.4 smokes \n", "4 Self-employed Rural 174.12 24.0 never smoked \n", "\n", " stroke \n", "0 1 \n", "1 1 \n", "2 1 \n", "3 1 \n", "4 1 " ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.head()" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:10:58.416601Z", "iopub.status.busy": "2021-02-27T01:10:58.415912Z", "iopub.status.idle": "2021-02-27T01:10:58.420976Z", "shell.execute_reply": "2021-02-27T01:10:58.421780Z" }, "papermill": { "duration": 0.034595, "end_time": "2021-02-27T01:10:58.421981", "exception": false, "start_time": "2021-02-27T01:10:58.387386", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "df = df.rename(columns={'Residence_type':'residence_type'})" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:10:58.486267Z", "iopub.status.busy": "2021-02-27T01:10:58.485570Z", "iopub.status.idle": "2021-02-27T01:10:58.494483Z", "shell.execute_reply": "2021-02-27T01:10:58.493915Z" }, "papermill": { "duration": 0.04228, "end_time": "2021-02-27T01:10:58.494658", "exception": false, "start_time": "2021-02-27T01:10:58.452378", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "# Converte genero para 0 ou 1\n", "df['gender'] = df['gender'].apply({'Male':1, 'Female':0}.get)" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:10:58.555521Z", "iopub.status.busy": "2021-02-27T01:10:58.554479Z", "iopub.status.idle": "2021-02-27T01:10:58.557389Z", "shell.execute_reply": "2021-02-27T01:10:58.556513Z" }, "papermill": { "duration": 0.037986, "end_time": "2021-02-27T01:10:58.557546", "exception": false, "start_time": "2021-02-27T01:10:58.519560", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "# Converte status de se já foi casado para 0 ou 1\n", "df['ever_married'] = df['ever_married'].apply({'Yes':1, 'No':0}.get)" ] }, { "cell_type": "code", "execution_count": 8, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:10:58.617396Z", "iopub.status.busy": "2021-02-27T01:10:58.616737Z", "iopub.status.idle": "2021-02-27T01:10:58.734210Z", "shell.execute_reply": "2021-02-27T01:10:58.733517Z" }, "papermill": { "duration": 0.147586, "end_time": "2021-02-27T01:10:58.734358", "exception": false, "start_time": "2021-02-27T01:10:58.586772", "status": "completed" }, "tags": [] }, "outputs": [ { "ename": "KeyError", "evalue": "'Residence_type'", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m 3079\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3080\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcasted_key\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3081\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n", "\u001b[0;32mpandas/_libs/index.pyx\u001b[0m in \u001b[0;36mpandas._libs.index.IndexEngine.get_loc\u001b[0;34m()\u001b[0m\n", "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n", "\u001b[0;32mpandas/_libs/hashtable_class_helper.pxi\u001b[0m in \u001b[0;36mpandas._libs.hashtable.PyObjectHashTable.get_item\u001b[0;34m()\u001b[0m\n", "\u001b[0;31mKeyError\u001b[0m: 'Residence_type'", "\nThe above exception was the direct cause of the following exception:\n", "\u001b[0;31mKeyError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m<ipython-input-8-21e28ca3f7f3>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[0;31m# Converte o tipo de residência para 0 ou 1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Residence_type'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdf\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m'Residence_type'\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mapply\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m{\u001b[0m\u001b[0;34m'Rural'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'Urban'\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pandas/core/frame.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m 3022\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnlevels\u001b[0m \u001b[0;34m>\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3023\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_getitem_multilevel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3024\u001b[0;31m \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3025\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mis_integer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3026\u001b[0m \u001b[0mindexer\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mindexer\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/pandas/core/indexes/base.py\u001b[0m in \u001b[0;36mget_loc\u001b[0;34m(self, key, method, tolerance)\u001b[0m\n\u001b[1;32m 3080\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_loc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcasted_key\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3081\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mKeyError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3082\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mKeyError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0merr\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 3083\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 3084\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mtolerance\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;31mKeyError\u001b[0m: 'Residence_type'" ] } ], "source": [ "# Converte o tipo de residência para 0 ou 1\n", "df['Residence_type'] = df['Residence_type'].apply({'Rural':1, 'Urban':0}.get)" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:10:58.799448Z", "iopub.status.busy": "2021-02-27T01:10:58.797848Z", "iopub.status.idle": "2021-02-27T01:10:58.802224Z", "shell.execute_reply": "2021-02-27T01:10:58.801272Z" }, "papermill": { "duration": 0.041783, "end_time": "2021-02-27T01:10:58.802430", "exception": false, "start_time": "2021-02-27T01:10:58.760647", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "# modificando strings\n", "df['smoking_status'] = df['smoking_status'].apply(str.lower)\n", "df['smoking_status'] = df['smoking_status'].apply(lambda x: x.replace(' ','_'))" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:10:58.872077Z", "iopub.status.busy": "2021-02-27T01:10:58.871108Z", "iopub.status.idle": "2021-02-27T01:10:58.874929Z", "shell.execute_reply": "2021-02-27T01:10:58.875446Z" }, "papermill": { "duration": 0.044027, "end_time": "2021-02-27T01:10:58.875647", "exception": false, "start_time": "2021-02-27T01:10:58.831620", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "# modificando strings\n", "df['work_type'] = df['work_type'].apply(str.lower)\n", "df['work_type'] = df['work_type'].apply(lambda x: x.replace('-','_'))" ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:10:58.961569Z", "iopub.status.busy": "2021-02-27T01:10:58.956557Z", "iopub.status.idle": "2021-02-27T01:10:59.096044Z", "shell.execute_reply": "2021-02-27T01:10:59.095366Z" }, "papermill": { "duration": 0.192895, "end_time": "2021-02-27T01:10:59.096188", "exception": false, "start_time": "2021-02-27T01:10:58.903293", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 720x504 with 1 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(10,7))\n", "sns.boxplot(data=df,x=df[\"bmi\"],color='green');" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:10:59.165772Z", "iopub.status.busy": "2021-02-27T01:10:59.164958Z", "iopub.status.idle": "2021-02-27T01:10:59.168340Z", "shell.execute_reply": "2021-02-27T01:10:59.167714Z" }, "papermill": { "duration": 0.044454, "end_time": "2021-02-27T01:10:59.168483", "exception": false, "start_time": "2021-02-27T01:10:59.124029", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "df[\"bmi\"] = df[\"bmi\"].apply(lambda x: 50 if x>50 else x)\n", "df[\"bmi\"] = df[\"bmi\"].fillna(28.4)" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:10:59.229162Z", "iopub.status.busy": "2021-02-27T01:10:59.228191Z", "iopub.status.idle": "2021-02-27T01:10:59.246047Z", "shell.execute_reply": "2021-02-27T01:10:59.245479Z" }, "papermill": { "duration": 0.048569, "end_time": "2021-02-27T01:10:59.246196", "exception": false, "start_time": "2021-02-27T01:10:59.197627", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "df = pd.get_dummies(df)" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:10:59.312104Z", "iopub.status.busy": "2021-02-27T01:10:59.311384Z", "iopub.status.idle": "2021-02-27T01:10:59.317031Z", "shell.execute_reply": "2021-02-27T01:10:59.317658Z" }, "papermill": { "duration": 0.041934, "end_time": "2021-02-27T01:10:59.317839", "exception": false, "start_time": "2021-02-27T01:10:59.275905", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "df = df[~df.isnull().any(axis=1)]" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.029604, "end_time": "2021-02-27T01:10:59.376340", "exception": false, "start_time": "2021-02-27T01:10:59.346736", "status": "completed" }, "tags": [] }, "source": [ "# Heatmap Correlation" ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:10:59.441324Z", "iopub.status.busy": "2021-02-27T01:10:59.436958Z", "iopub.status.idle": "2021-02-27T01:11:02.485384Z", "shell.execute_reply": "2021-02-27T01:11:02.485936Z" }, "papermill": { "duration": 3.081991, "end_time": "2021-02-27T01:11:02.486128", "exception": false, "start_time": "2021-02-27T01:10:59.404137", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 2160x1440 with 2 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "plt.figure(figsize = (30,20))\n", "sns.heatmap(df.corr(),annot=True);" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.035498, "end_time": "2021-02-27T01:11:02.569867", "exception": false, "start_time": "2021-02-27T01:11:02.534369", "status": "completed" }, "tags": [] }, "source": [ "# Scaling The variance in Features" ] }, { "cell_type": "code", "execution_count": 16, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:11:02.651601Z", "iopub.status.busy": "2021-02-27T01:11:02.650877Z", "iopub.status.idle": "2021-02-27T01:11:02.659325Z", "shell.execute_reply": "2021-02-27T01:11:02.658656Z" }, "papermill": { "duration": 0.051983, "end_time": "2021-02-27T01:11:02.659472", "exception": false, "start_time": "2021-02-27T01:11:02.607489", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "std=StandardScaler()\n", "columns = ['avg_glucose_level','bmi','age']\n", "scaled = std.fit_transform(df[['avg_glucose_level','bmi','age']])\n", "scaled = pd.DataFrame(scaled,columns=columns)\n", "df=df.drop(columns=columns,axis=1)" ] }, { "cell_type": "code", "execution_count": 17, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:11:02.738309Z", "iopub.status.busy": "2021-02-27T01:11:02.737367Z", "iopub.status.idle": "2021-02-27T01:11:02.773543Z", "shell.execute_reply": "2021-02-27T01:11:02.772258Z" }, "papermill": { "duration": 0.07684, "end_time": "2021-02-27T01:11:02.773722", "exception": false, "start_time": "2021-02-27T01:11:02.696882", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/html": [ "<div>\n", "<style scoped>\n", " .dataframe tbody tr th:only-of-type {\n", " vertical-align: middle;\n", " }\n", "\n", " .dataframe tbody tr th {\n", " vertical-align: top;\n", " }\n", "\n", " .dataframe thead th {\n", " text-align: right;\n", " }\n", "</style>\n", "<table border=\"1\" class=\"dataframe\">\n", " <thead>\n", " <tr style=\"text-align: right;\">\n", " <th></th>\n", " <th>id</th>\n", " <th>gender</th>\n", " <th>hypertension</th>\n", " <th>heart_disease</th>\n", " <th>ever_married</th>\n", " <th>stroke</th>\n", " <th>work_type_children</th>\n", " <th>work_type_govt_job</th>\n", " <th>work_type_never_worked</th>\n", " <th>work_type_private</th>\n", " <th>work_type_self_employed</th>\n", " <th>residence_type_Rural</th>\n", " <th>residence_type_Urban</th>\n", " <th>smoking_status_formerly_smoked</th>\n", " <th>smoking_status_never_smoked</th>\n", " <th>smoking_status_smokes</th>\n", " <th>smoking_status_unknown</th>\n", " <th>avg_glucose_level</th>\n", " <th>bmi</th>\n", " <th>age</th>\n", " </tr>\n", " </thead>\n", " <tbody>\n", " <tr>\n", " <th>0</th>\n", " <td>9046</td>\n", " <td>1.0</td>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>2.706450</td>\n", " <td>1.069148</td>\n", " <td>1.051242</td>\n", " </tr>\n", " <tr>\n", " <th>1</th>\n", " <td>51676</td>\n", " <td>0.0</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>2.121652</td>\n", " <td>-0.051569</td>\n", " <td>0.785889</td>\n", " </tr>\n", " <tr>\n", " <th>2</th>\n", " <td>31112</td>\n", " <td>1.0</td>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>-0.004867</td>\n", " <td>0.508790</td>\n", " <td>1.626174</td>\n", " </tr>\n", " <tr>\n", " <th>3</th>\n", " <td>60182</td>\n", " <td>0.0</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>1.437473</td>\n", " <td>0.768468</td>\n", " <td>0.255182</td>\n", " </tr>\n", " <tr>\n", " <th>4</th>\n", " <td>1665</td>\n", " <td>0.0</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>1.501297</td>\n", " <td>-0.652929</td>\n", " <td>1.581949</td>\n", " </tr>\n", " <tr>\n", " <th>...</th>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " <td>...</td>\n", " </tr>\n", " <tr>\n", " <th>5105</th>\n", " <td>18234</td>\n", " <td>0.0</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>0.420922</td>\n", " <td>1.533836</td>\n", " <td>1.670400</td>\n", " </tr>\n", " <tr>\n", " <th>5106</th>\n", " <td>44873</td>\n", " <td>0.0</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>-0.511266</td>\n", " <td>0.249111</td>\n", " <td>-0.363976</td>\n", " </tr>\n", " <tr>\n", " <th>5107</th>\n", " <td>19723</td>\n", " <td>0.0</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>1.328375</td>\n", " <td>-0.434252</td>\n", " <td>0.343633</td>\n", " </tr>\n", " <tr>\n", " <th>5108</th>\n", " <td>37544</td>\n", " <td>1.0</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>-0.460692</td>\n", " <td>-0.352249</td>\n", " <td>0.034054</td>\n", " </tr>\n", " <tr>\n", " <th>5109</th>\n", " <td>44679</td>\n", " <td>0.0</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>0</td>\n", " <td>1</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " <td>NaN</td>\n", " </tr>\n", " </tbody>\n", "</table>\n", "<p>5109 rows × 20 columns</p>\n", "</div>" ], "text/plain": [ " id gender hypertension heart_disease ever_married stroke \\\n", "0 9046 1.0 0 1 1 1 \n", "1 51676 0.0 0 0 1 1 \n", "2 31112 1.0 0 1 1 1 \n", "3 60182 0.0 0 0 1 1 \n", "4 1665 0.0 1 0 1 1 \n", "... ... ... ... ... ... ... \n", "5105 18234 0.0 1 0 1 0 \n", "5106 44873 0.0 0 0 1 0 \n", "5107 19723 0.0 0 0 1 0 \n", "5108 37544 1.0 0 0 1 0 \n", "5109 44679 0.0 0 0 1 0 \n", "\n", " work_type_children work_type_govt_job work_type_never_worked \\\n", "0 0 0 0 \n", "1 0 0 0 \n", "2 0 0 0 \n", "3 0 0 0 \n", "4 0 0 0 \n", "... ... ... ... \n", "5105 0 0 0 \n", "5106 0 0 0 \n", "5107 0 0 0 \n", "5108 0 0 0 \n", "5109 0 1 0 \n", "\n", " work_type_private work_type_self_employed residence_type_Rural \\\n", "0 1 0 0 \n", "1 0 1 1 \n", "2 1 0 1 \n", "3 1 0 0 \n", "4 0 1 1 \n", "... ... ... ... \n", "5105 1 0 0 \n", "5106 0 1 0 \n", "5107 0 1 1 \n", "5108 1 0 1 \n", "5109 0 0 0 \n", "\n", " residence_type_Urban smoking_status_formerly_smoked \\\n", "0 1 1 \n", "1 0 0 \n", "2 0 0 \n", "3 1 0 \n", "4 0 0 \n", "... ... ... \n", "5105 1 0 \n", "5106 1 0 \n", "5107 0 0 \n", "5108 0 1 \n", "5109 1 0 \n", "\n", " smoking_status_never_smoked smoking_status_smokes \\\n", "0 0 0 \n", "1 1 0 \n", "2 1 0 \n", "3 0 1 \n", "4 1 0 \n", "... ... ... \n", "5105 1 0 \n", "5106 1 0 \n", "5107 1 0 \n", "5108 0 0 \n", "5109 0 0 \n", "\n", " smoking_status_unknown avg_glucose_level bmi age \n", "0 0 2.706450 1.069148 1.051242 \n", "1 0 2.121652 -0.051569 0.785889 \n", "2 0 -0.004867 0.508790 1.626174 \n", "3 0 1.437473 0.768468 0.255182 \n", "4 0 1.501297 -0.652929 1.581949 \n", "... ... ... ... ... \n", "5105 0 0.420922 1.533836 1.670400 \n", "5106 0 -0.511266 0.249111 -0.363976 \n", "5107 0 1.328375 -0.434252 0.343633 \n", "5108 0 -0.460692 -0.352249 0.034054 \n", "5109 1 NaN NaN NaN \n", "\n", "[5109 rows x 20 columns]" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df=df.merge(scaled, left_index=True, right_index=True, how = \"left\")\n", "df" ] }, { "cell_type": "code", "execution_count": 18, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:11:02.854998Z", "iopub.status.busy": "2021-02-27T01:11:02.853603Z", "iopub.status.idle": "2021-02-27T01:11:02.860291Z", "shell.execute_reply": "2021-02-27T01:11:02.859708Z" }, "papermill": { "duration": 0.049466, "end_time": "2021-02-27T01:11:02.860438", "exception": false, "start_time": "2021-02-27T01:11:02.810972", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "df = df[~df.isnull().any(axis=1)]" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.035926, "end_time": "2021-02-27T01:11:02.935806", "exception": false, "start_time": "2021-02-27T01:11:02.899880", "status": "completed" }, "tags": [] }, "source": [ "# Class" ] }, { "cell_type": "code", "execution_count": 19, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:11:03.018120Z", "iopub.status.busy": "2021-02-27T01:11:03.017393Z", "iopub.status.idle": "2021-02-27T01:11:03.021835Z", "shell.execute_reply": "2021-02-27T01:11:03.021137Z" }, "papermill": { "duration": 0.049502, "end_time": "2021-02-27T01:11:03.021986", "exception": false, "start_time": "2021-02-27T01:11:02.972484", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "df_class = df.drop(['id','stroke'], axis=1)\n", "df_target = df['stroke']" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.036806, "end_time": "2021-02-27T01:11:03.094777", "exception": false, "start_time": "2021-02-27T01:11:03.057971", "status": "completed" }, "tags": [] }, "source": [ "# Spliting" ] }, { "cell_type": "code", "execution_count": 20, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:11:03.176880Z", "iopub.status.busy": "2021-02-27T01:11:03.175756Z", "iopub.status.idle": "2021-02-27T01:11:03.179919Z", "shell.execute_reply": "2021-02-27T01:11:03.179262Z" }, "papermill": { "duration": 0.047966, "end_time": "2021-02-27T01:11:03.180071", "exception": false, "start_time": "2021-02-27T01:11:03.132105", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "X_train, X_test, y_train, y_test = train_test_split(df_class, df_target, test_size=0.3, random_state=11)" ] }, { "cell_type": "code", "execution_count": 21, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:11:03.262033Z", "iopub.status.busy": "2021-02-27T01:11:03.260979Z", "iopub.status.idle": "2021-02-27T01:11:03.265206Z", "shell.execute_reply": "2021-02-27T01:11:03.264704Z" }, "papermill": { "duration": 0.049619, "end_time": "2021-02-27T01:11:03.265356", "exception": false, "start_time": "2021-02-27T01:11:03.215737", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "0 1449\n", "1 84\n", "Name: stroke, dtype: int64" ] }, "execution_count": 21, "metadata": {}, "output_type": "execute_result" } ], "source": [ "y_test.value_counts()" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.035569, "end_time": "2021-02-27T01:11:03.338030", "exception": false, "start_time": "2021-02-27T01:11:03.302461", "status": "completed" }, "tags": [] }, "source": [ "# adaboost classification" ] }, { "cell_type": "code", "execution_count": 22, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:11:03.419751Z", "iopub.status.busy": "2021-02-27T01:11:03.419010Z", "iopub.status.idle": "2021-02-27T01:11:03.455563Z", "shell.execute_reply": "2021-02-27T01:11:03.454839Z" }, "papermill": { "duration": 0.081601, "end_time": "2021-02-27T01:11:03.455733", "exception": false, "start_time": "2021-02-27T01:11:03.374132", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "training....\n", "\n", "prediction: \n", " [0 0 0 ... 0 0 0]\n", "\n", "parms: \n", " <bound method BaseEstimator.get_params of AdaBoostClassifier(base_estimator=DecisionTreeClassifier(), learning_rate=0.5,\n", " n_estimators=100, random_state=100)>\n", "\n", "mean accuracy: 0.90\n" ] } ], "source": [ "#create adaboost classification obj\n", "ab_clf = AdaBoostClassifier(base_estimator=DecisionTreeClassifier(), n_estimators=100, \n", " learning_rate=0.5, random_state=100)\n", "\n", "#training via adaboost classficiation model\n", "ab_clf.fit(X_train, y_train)\n", "print(\"training....\\n\")\n", "\n", "#make prediction using the test set\n", "ab_pred_stroke= ab_clf.predict(X_train)\n", "print('prediction: \\n', ab_pred_stroke)\n", "\n", "print('\\nparms: \\n', ab_clf.get_params)\n", "\n", "#score\n", "ab_clf_score = ab_clf.score(X_test, y_test)\n", "print(\"\\nmean accuracy: %.2f\" % ab_clf.score(X_test, y_test))" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.037356, "end_time": "2021-02-27T01:11:03.530258", "exception": false, "start_time": "2021-02-27T01:11:03.492902", "status": "completed" }, "tags": [] }, "source": [ "# XGboost" ] }, { "cell_type": "code", "execution_count": 23, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:11:03.615130Z", "iopub.status.busy": "2021-02-27T01:11:03.614244Z", "iopub.status.idle": "2021-02-27T01:11:04.335441Z", "shell.execute_reply": "2021-02-27T01:11:04.334633Z" }, "papermill": { "duration": 0.767628, "end_time": "2021-02-27T01:11:04.335615", "exception": false, "start_time": "2021-02-27T01:11:03.567987", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Training Score 0.9619580419580419\n", "Testing Score \n", " 0.9465101108936725\n", "0.9465101108936725\n" ] }, { "data": { "image/png": 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bz4cB51bVQ1V1G7AC2Gvgexr0QEmSJGlUVNUPgHcDdwCrgJ9U1UXATlW1qtlnFTC3OWQX4M4xp1jZtA3EUC5JkqROyaBLsiTJNWOWJY+ds1crfhiwENgZ2CrJn0/RjXXVoPfk7CuSJEnqlEFnX6mqpcDSCTa/FLitqn4IkOTfgRcA9ySZV1WrkswD7m32XwksGHP8fHrlLgNxpFySJEmdMqSa8juAvZNsmd5TofsBNwPnA0c1+xwFnNd8Ph9YnGTzJAuBRcBVg96TI+WSJEnqlKlmUhlEVV2Z5LPAN4FHgGvpjao/GViW5LX0gvsRzf43JlkG3NTsf2xVrRn0+oZySZIkdcqwXh5UVW8D3rZO80P0Rs3H2/8U4JSNcW1DuSRJkjpl9N7naSiXJElSxwxrpLxNhnJJkiR1iqFckiRJatkwHvRsm6FckiRJnTKKc3obyiVJktQpjpRLkiRJLbOmXJIkSWqZoXwAP/7it4d9CUmSJG1CLF+RJEmSWjZrBF8fZCiXJElSp4ziSPkozigjSZIkdYoj5ZIkSeoUH/SUJEmSWhZryiVJkqR2jWJNuaFckiRJnWL5iiRJktSyjOBcJYZySZIkdYoj5ZIkSVLLrCmXJEmSWubsK5IkSVLLLF+RJEmSWmb5iiRJktSyWc6+IkmSJLXLkXJJkiSpZYZySZIkqWWznH1FkiRJapcj5ZIkSVLLRnFKxNF7dFWSJEnqGEO5JEmSOiUD/unr3Mk2ST6b5DtJbk7y/CTbJbk4ya3Nz23H7H9ykhVJbkly4KD3ZCiXJElSp8zKrIGWPp0KXFhVuwO/C9wMvAVYXlWLgOXNOkn2ABYDzwIOAk5LMnugexrkIEmSJKktSQZa+jjv1sCLgTMAquqXVfVj4DDg7Ga3s4HDm8+HAedW1UNVdRuwAthrkHsylEuSJKlTBi1fSbIkyTVjliXrnPo3gB8CH09ybZLTk2wF7FRVqwCan3Ob/XcB7hxz/Mqm7Qlz9hVJkiR1yqCzr1TVUmDpJLtsBvwe8KaqujLJqTSlKhMYryM1SN8cKZckSVKnDPFBz5XAyqq6sln/LL2Qfk+SeQDNz3vH7L9gzPHzgbsGuSdDuSRJkjplVjLQMpWquhu4M8kzmqb9gJuA84GjmrajgPOaz+cDi5NsnmQhsAi4apB7snxFkiRJnZL+Z1IZxJuAc5I8Cfge8Ff0BrKXJXktcAdwBEBV3ZhkGb3g/ghwbFWtGeSihnJJkiR1Sr9zjg+iqq4D9hxn034T7H8KcMqGXtdQLkmSpE4Z9EHPmcxQLkmSpE7pZ87xrjGUS5IkqVNmDbF8pS2GckmSJHWKI+WSJElSy4Y8+0orDOWSJEnqFMtXJEmSpJZZviJJkiS1bJjzlLdl9ApyJEmSpI5xpFySJEmdYvmKJEmS1DIf9JQkSZJa5pSIkiRJUstG8UFPQ7kkSZI6xZpySZIkqWWOlEuSJEktc6RckiRJapmzr0iSJEktc6RckiRJallG8KX0hnJJkiR1iiPlkiRJUsucfUWSJElq2SxHyiVJkqR2OVIuSZIktcyackmSJKllozj7yujdkSRJktQxjpRLkiSpUyxfkSRJklo2awQf9LR8RZIkSZ2SZKClz3PPTnJtki8069sluTjJrc3Pbcfse3KSFUluSXLghtyToVySJEmdkgH/9OlvgZvHrL8FWF5Vi4DlzTpJ9gAWA88CDgJOSzJ70HsylEuSJKlThjVSnmQ+cChw+pjmw4Czm89nA4ePaT+3qh6qqtuAFcBeg96ToVySJEmdEmYNtPThfcCbgUfHtO1UVasAmp9zm/ZdgDvH7LeyaRuIoVySJEmdMisZaEmyJMk1Y5Yla8+Z5GXAvVX1jT67Md7Qew16T86+IkmSpE55AvXhj1NVS4GlE2x+IfDyJIcAc4Ctk/xv4J4k86pqVZJ5wL3N/iuBBWOOnw/cNVDHMJSrw75/2/f5x3/474+t37XyByw59vVc/60b+P7tdwDwswce4MlPeQrnfPYTbXVTkjbY7bfdzptPOOmx9ZUrf8Ab33QMf/6aP2uxV1J7hjFPeVWdDJzcnH8f4O+r6s+TvAs4Cnhn8/O85pDzgU8leQ+wM7AIuGrQ6xvK1Vm7Ltz1sbC9Zs0aDt3v5eyz3x9y5F8sfmyf973r/Tz5yVu11UVJ2ih2W7gbyz7/GaD3fbf/Pgfykv32bblXUnsGHSkf0DuBZUleC9wBHAFQVTcmWQbcBDwCHFtVawa9iKFcI+HqK69h/oJdmLfzvMfaqoqvfHk5p53xwRZ7Jkkb15VXXMWCp81n5112brsrUmuG/UbPqroEuKT5fB+w3wT7nQKcsjGuOVAoT7J7VX1nY3RA2hguvuBiDjh4/8e1XfuN69hu++142q4LJjhKkrrnwi99mYMOOajtbkitmjWCc5UMekcXbdReSBvg4Ycf5tJLvs5+Bzz+l9iLLriYAw/Zf4KjJKl7Hv7lw3ztq1/jgAP9btOmbZhv9GzLhCPlSd4/0SZgm8lO2kwvswTgfR96D3/5uqMG7Z80pf+67HJ2f+Yz2H6H7R5re+SRR7jkK5dw9mfOaq9jkrSRff2yr7P7Hruz/Q7bt90VqVXTXFM+LSYrX/kr4ETgoXG2HTnZScdON/OTX94/8HyNUj8uGqd05eorrmbXhbuy06/PneAoSeqeC750IQdbuiLN+FHvQUxWvnI1cENVnb3uAjwwTf2TJvWL1b/gysuvYt+X7vO49osu+AoHWLoiaYSsXr2aK/7rSvbb/yVtd0VqXQb8M5OlavyB7CTbAb+oqgc35AKOlEsaVZvPntN2FyRpaObM3nLGptirf/j1gfLl7+/432bsPU1YvlJV909nRyRJkqR+zPRR70H0NftKkrdPti5JkiRNm2SwZQbrd57yb0yxLkmSJE2LURwp7yuUV9V/TLYuSZIkTZdRnH1lsnnKPwBMWERfVccNpUeSJEnSJDa1kfJrpq0XkiRJUp82qVDezEcuSZIkzSibVPnKWkl2BE4C9gAem5S3qnx7gSRJkqbdKI6U9zMl4jnAzcBC4B3A7fTe9ilJkiRNu1F8o2c/oXz7qjoDeLiqvlZVfw3sPeR+SZIkSeNKMtAyk/UzJeLDzc9VSQ4F7gLmD69LkiRJ0sRm+qj3IPoJ5f+S5KnAicAHgK2B44faK0mSJGkCM33UexBThvKq+kLz8SfAvsPtjiRJkjS5TXKkPMnHGeclQk1tuSRJkjStNslQDnxhzOc5wCvo1ZVLkiRJ025TLV/53Nj1JJ8GvjK0HkmSJEmTGMWR8n6mRFzXIuBpG7sjkiRJ0qaqn5ryB3h8Tfnd9N7wKUmSJE27URwp76d85SnT0RFJkiSpH6NYUz5l+UqS5f20SZIkSdMjAy4z14Qj5UnmAFsCOyTZll/dydbAztPQN0mSJGk9ozhSPln5yhuAv6MXwL/Br0L5T4EPDbdbkiRJ0vg2qZryqjoVODXJm6rqA9PYJ0mSJGlCoxjK+5kS8dEk26xdSbJtkjcOr0uSJEnSxJIMtPRx3gVJvprk5iQ3Jvnbpn27JBcnubX5ue2YY05OsiLJLUkOHPSe+gnlr6+qH69dqaofAa8f9IKSJEnShsiAf/rwCHBiVT0T2Bs4NskewFuA5VW1CFjerNNsWww8CzgIOC3J7EHuqZ9QPitjfrVoLvSkQS4mSZIkbahhhfKqWlVV32w+PwDcDOwCHAac3ex2NnB48/kw4NyqeqiqbgNWAHsNck9TzlMOfBlYluQj9F4idDRwwSAXkyRJkjbUdMy+kmQ34LnAlcBOVbUKesE9ydxmt12AK8YctrJpe8L6CeUnAUuAY+jNwHItMG+Qi0mSJEkbatAHPZMsoZdr11paVUvH2e/JwOeAv6uqn07yS8B4G2qQvvXzRs9Hk1wB/AbwamC7ppOSJEnStBt0pLwJ4OuF8HXO/Wv0su45VfXvTfM9SeY1o+TzgHub9pXAgjGHzwfuGqRvE9aUJ3l6kv+R5Gbgg8Cdzc3sW1UfHORikiRJ0oYaVk158xzlGcDNVfWeMZvOB45qPh8FnDemfXGSzZMsBBYBVw1yT5ONlH8HuAz4o6pa0XT0+EEuIkmSJG08Q6spfyHwF8D1Sa5r2v4ReCe9ZyxfC9wBHAFQVTcmWQbcRG/mlmOras0gF07V+GUvSV5Bb4qXFwAXAucCp1fVwidygZ/88v6B6mokaabbfPactrsgSUMzZ/aWM/YNPasevGOgfDlvy6fN2HuasHylqj5fVa8GdgcuAY4Hdkry4SQHTFP/JEmSpMcZ1suD2jTlPOVV9fOqOqeqXkaveP06mgnTJUmSJG24CctXNhbLVySNKstXJI2ymVy+cvfqlQPly1/fYv6Mvad+5imXJEmSZowZm6w3gKFckiRJHTN6sdxQLkmSpE6Z6Q9tDmLKBz0lSZIkDZcj5ZIkSeqUft7O2TWGckmSJHXKKIZyy1ckSZKkljlSLkmSpE7xQU9JkiRJG50j5ZIkSeqUUawpN5RLkiSpYwzlkiRJUqtGL5IbyiVJktQxo/igp6FckiRJHWMolyRJklo1epHcUC5JkqTOGb1Y7jzlkiRJUsscKZckSVKnjOKDno6US5IkSS1zpFySJEmd4hs9JUmSpNYZyiVJkqRWjV4kN5RLkiSpY0bxQU9DuSRJkjrGUC5JkiS1avQiuaFckiRJnTN6sdxQLkmSpE4ZxZpyXx4kSZIktcyRckmSJHXKKL48KFXVdh+kjSbJkqpa2nY/JGkY/I6TRpflKxo1S9rugCQNkd9x0ogylEuSJEktM5RLkiRJLTOUa9RYaylplPkdJ40oH/SUJEmSWuZIuSRJktQyQ7mGLsmaJNcluSHJvyXZcgPOdVaSVzWfT0+yxyT77pPkBQNc4/YkO4zTvjDJlUluTfKZJE96oueWNHpG6Dvub5KsSFLjbZc0XIZyTYfVVfWcqno28Evg6LEbk8we5KRV9bqqummSXfYBnvA/WJP4n8B7q2oR8CPgtRvx3JK6a1S+4/4TeCnw/Y14Tkl9MpRrul0G/FYzwvPVJJ8Crk8yO8m7klyd5NtJ3gCQng8muSnJF4G5a0+U5JIkezafD0ryzSTfSrI8yW70/mE8vhnBelGSHZN8rrnG1Ule2By7fZKLklyb5KOw/mvCkgR4CfDZpuls4PBh/SVJ6qxOfscBVNW1VXX7MP9yJE1ss7Y7oE1Hks2Ag4ELm6a9gGdX1W1JlgA/qarfT7I58J9JLgKeCzwD+G1gJ+Am4Mx1zrsj8DHgxc25tquq+5N8BPhZVb272e9T9Ea6v57kacCXgWcCbwO+XlX/lORQxrycI8mXgNfRG/36cVU90mxaCeyycf+GJHVZl7/jququ4fytSOqXoVzTYYsk1zWfLwPOoPdfrldV1W1N+wHA76ytpQSeCiwCXgx8uqrWAHcl+T/jnH9v4NK156qq+yfox0uBPXqD3gBsneQpzTX+uDn2i0l+tHaHqjoEHvtHcV1OXSQJRuA7TlL7DOWaDqur6jljG5p/NH4+tgl4U1V9eZ39DmHq8Js+9oFeudbzq2r1OH2Z6vj/B2yTZLNmtHw+4MiSJBiN7zhJLbOmXDPFl4FjkvwaQJKnJ9kKuBRY3NRjzgP2HefYy4E/TLKwOXa7pv0B4Clj9rsI+Ju1K0me03y8FPizpu1gYNt1L1C9Cf2/Cqwd5ToKOO+J36akTdSM/o6T1D5DuWaK0+nVUn4zyQ3AR+n9T87ngVuB64EPA19b98Cq+iG9Gsl/T/It4DPNpv8AXrH2ISjgOGDP5iGrm/jVDAnvAF6c5Jv0/ov5jrXnTvKlJDs3qycBJyRZAWxP77+oJakfM/47LslxSVbS+5/Abyc5faP+DUialG/0lCRJklrmSLkkSZLUMkO5JEmS1DJDuSRJktQyQ7kkSZLUMkO5JEmS1DJDuSRJktQyQ7kkSZLUMkO5JEmS1LL/Dxuom5tumqI8AAAAAElFTkSuQmCC\n", "text/plain": [ "<Figure size 1008x360 with 2 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "xgboost = GradientBoostingClassifier(random_state=0)\n", "xgboost.fit(X_train, y_train)\n", "#== \n", "#Score \n", "#== \n", "xgboost_score = xgboost.score(X_train, y_train)\n", "xgboost_test = xgboost.score(X_test, y_test)\n", "#== \n", "#testing model \n", "#== \n", "y_pred = xgboost.predict(X_test)\n", "#== \n", "#evaluation\n", "#== \n", "cm = confusion_matrix(y_test,y_pred)\n", "print('Training Score',xgboost_score)\n", "print('Testing Score \\n',xgboost_test)\n", "\n", "#=== \n", "#Confusion Matrix \n", "plt.figure(figsize=(14,5))\n", "\n", "conf_matrix = pd.DataFrame(data=cm,columns=['Predicted:0','Predicted:1'],index=['Actual:0','Actual:1'])\n", "sns.heatmap(conf_matrix, annot=True,fmt='d',cmap=\"Greens\");\n", "print(accuracy_score(y_test,y_pred))" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.037737, "end_time": "2021-02-27T01:11:04.411430", "exception": false, "start_time": "2021-02-27T01:11:04.373693", "status": "completed" }, "tags": [] }, "source": [ "# SVM" ] }, { "cell_type": "code", "execution_count": 24, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:11:04.498836Z", "iopub.status.busy": "2021-02-27T01:11:04.497873Z", "iopub.status.idle": "2021-02-27T01:11:05.207078Z", "shell.execute_reply": "2021-02-27T01:11:05.206478Z" }, "papermill": { "duration": 0.758034, "end_time": "2021-02-27T01:11:05.207230", "exception": false, "start_time": "2021-02-27T01:11:04.449196", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Training Score 0.9538461538461539\n", "Testing Score \n", " 0.9452054794520548\n", "0.9452054794520548\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 1008x360 with 2 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "svc = SVC(random_state=0)\n", "svc.fit(X_train, y_train)\n", "#== \n", "#Score \n", "#== \n", "svc_score = svc.score(X_train, y_train)\n", "svc_test = svc.score(X_test, y_test)\n", "#== \n", "#testing model \n", "#== \n", "y_pred = svc.predict(X_test)\n", "#== \n", "#evaluation\n", "#== \n", "cm = confusion_matrix(y_test,y_pred)\n", "print('Training Score',svc_score)\n", "print('Testing Score \\n',svc_test)\n", "\n", "plt.figure(figsize=(14,5))\n", "\n", "conf_matrix = pd.DataFrame(data=cm,columns=['Predicted:0','Predicted:1'],index=['Actual:0','Actual:1'])\n", "sns.heatmap(conf_matrix, annot=True,fmt='d',cmap=\"Greens\");\n", "print(accuracy_score(y_test,y_pred))" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.038442, "end_time": "2021-02-27T01:11:05.284793", "exception": false, "start_time": "2021-02-27T01:11:05.246351", "status": "completed" }, "tags": [] }, "source": [ "# Random Forest Classifier" ] }, { "cell_type": "code", "execution_count": 25, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:11:05.374194Z", "iopub.status.busy": "2021-02-27T01:11:05.372917Z", "iopub.status.idle": "2021-02-27T01:11:06.088375Z", "shell.execute_reply": "2021-02-27T01:11:06.088887Z" }, "papermill": { "duration": 0.765616, "end_time": "2021-02-27T01:11:06.089072", "exception": false, "start_time": "2021-02-27T01:11:05.323456", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Training Score 1.0\n", "Testing Score \n", " 0.9432485322896281\n", "0.9432485322896281\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 1008x360 with 2 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "forest = RandomForestClassifier(n_estimators = 100)\n", "#== \n", "forest.fit(X_train, y_train)\n", "#== \n", "#Score \n", "#== \n", "forest_score = forest.score(X_train, y_train)\n", "forest_test = forest.score(X_test, y_test)\n", "#== \n", "#testing model \n", "#== \n", "y_pred = forest.predict(X_test)\n", "#== \n", "#evaluation\n", "#== \n", "cm = confusion_matrix(y_test,y_pred)\n", "print('Training Score',forest_score)\n", "print('Testing Score \\n',forest_test)\n", "\n", "plt.figure(figsize=(14,5))\n", "\n", "conf_matrix = pd.DataFrame(data=cm,columns=['Predicted:0','Predicted:1'],index=['Actual:0','Actual:1'])\n", "sns.heatmap(conf_matrix, annot=True,fmt='d',cmap=\"Greens\");\n", "print(accuracy_score(y_test,y_pred))" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.03984, "end_time": "2021-02-27T01:11:06.169255", "exception": false, "start_time": "2021-02-27T01:11:06.129415", "status": "completed" }, "tags": [] }, "source": [ "# Logistic Regression" ] }, { "cell_type": "code", "execution_count": 26, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:11:06.260820Z", "iopub.status.busy": "2021-02-27T01:11:06.258828Z", "iopub.status.idle": "2021-02-27T01:11:06.624972Z", "shell.execute_reply": "2021-02-27T01:11:06.625507Z" }, "papermill": { "duration": 0.415981, "end_time": "2021-02-27T01:11:06.625700", "exception": false, "start_time": "2021-02-27T01:11:06.209719", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Training Score 0.9538461538461539\n", "Testing Score \n", " 0.9458577951728636\n", "0.9458577951728636\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 1008x360 with 2 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "model = LogisticRegression()\n", "model.fit(X_train, y_train)\n", "#== \n", "#Score \n", "#== \n", "logistic_score = model.score(X_train, y_train)\n", "logistic_test = model.score(X_test, y_test)\n", "#== \n", "#testing model \n", "#== \n", "y_pred = model.predict(X_test)\n", "#== \n", "#evaluation\n", "#== \n", "cm = confusion_matrix(y_test,y_pred)\n", "print('Training Score',logistic_score)\n", "print('Testing Score \\n',logistic_test)\n", "\n", "plt.figure(figsize=(14,5))\n", "\n", "conf_matrix = pd.DataFrame(data=cm,columns=['Predicted:0','Predicted:1'],index=['Actual:0','Actual:1'])\n", "sns.heatmap(conf_matrix, annot=True,fmt='d',cmap=\"Greens\");\n", "print(accuracy_score(y_test,y_pred))" ] }, { "cell_type": "code", "execution_count": 27, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:11:06.720521Z", "iopub.status.busy": "2021-02-27T01:11:06.719546Z", "iopub.status.idle": "2021-02-27T01:11:06.724445Z", "shell.execute_reply": "2021-02-27T01:11:06.723932Z" }, "papermill": { "duration": 0.052505, "end_time": "2021-02-27T01:11:06.724611", "exception": false, "start_time": "2021-02-27T01:11:06.672106", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "dict_keys(['ccp_alpha', 'criterion', 'init', 'learning_rate', 'loss', 'max_depth', 'max_features', 'max_leaf_nodes', 'min_impurity_decrease', 'min_impurity_split', 'min_samples_leaf', 'min_samples_split', 'min_weight_fraction_leaf', 'n_estimators', 'n_iter_no_change', 'random_state', 'subsample', 'tol', 'validation_fraction', 'verbose', 'warm_start'])" ] }, "execution_count": 27, "metadata": {}, "output_type": "execute_result" } ], "source": [ "xgboost.get_params().keys()" ] }, { "cell_type": "code", "execution_count": 28, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:11:06.822615Z", "iopub.status.busy": "2021-02-27T01:11:06.821851Z", "iopub.status.idle": "2021-02-27T01:19:01.984429Z", "shell.execute_reply": "2021-02-27T01:19:01.983777Z" }, "papermill": { "duration": 475.215527, "end_time": "2021-02-27T01:19:01.984604", "exception": false, "start_time": "2021-02-27T01:11:06.769077", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Fitting 5 folds for each of 151 candidates, totalling 755 fits\n" ] }, { "name": "stderr", "output_type": "stream", "text": [ "/opt/conda/lib/python3.7/site-packages/sklearn/model_selection/_search.py:921: UserWarning: One or more of the test scores are non-finite: [0. 0. 0. 0. 0. 0.\n", " 0. 0. 0. 0. 0. 0.\n", " 0. 0. 0. 0. 0. 0.\n", " 0. 0. 0. 0. 0. 0.\n", " 0. 0. 0. 0. 0. 0.\n", " 0. 0. 0. 0. 0. 0.\n", " 0. 0. 0. 0. 0. 0.\n", " 0.00606061 0. 0.00606061 0.00606061 0.00606061 0.\n", " 0. 0. 0.03030303 0.00606061 0.01818182 0.01818182\n", " 0. 0.00606061 0.01818182 0.00606061 0.00606061 0.01212121\n", " 0.03636364 0.02424242 0.00606061 0.01212121 0. 0.00606061\n", " 0.00606061 0.00606061 0. 0.01212121 nan nan\n", " nan nan nan nan nan nan\n", " nan nan nan nan nan nan\n", " nan nan nan nan nan nan\n", " nan nan nan nan nan nan\n", " nan nan nan nan 0. 0.03636364\n", " 0.03030303 0. 0. 0. 0. 0.\n", " 0. 0. 0. 0. 0. 0.09090909\n", " 0.05454545 0. 0. 0.07878788 0. 0.\n", " 0. 0. 0. 0. 0.01212121 0.13939394\n", " 0.05454545 0. 0.00606061 0.13333333 0. 0.\n", " 0. 0. 0. 0. 0.04848485 0.13939394\n", " 0.05454545 0.03636364 0.03636364 0.12121212 0. 0.\n", " 0.01818182 0. 0. 0. 0.00606061 0.01818182\n", " 0.04242424]\n", " category=UserWarning\n" ] } ], "source": [ "pipe = Pipeline([('classifier' , RandomForestClassifier())])\n", "\n", "\n", "param_grid = [\n", " {'classifier' : [LogisticRegression()],\n", " 'classifier__penalty' : ['l1', 'l2'],\n", " 'classifier__C' : np.logspace(-4, 4, 20),\n", " 'classifier__solver' : ['liblinear']},\n", " {'classifier' : [RandomForestClassifier()],\n", " 'classifier__n_estimators' : list(range(10,101,10)),\n", " 'classifier__max_features' : list(range(6,32,5))},\n", " {'classifier' : [SVC()],\n", " 'classifier__C': [0.1,1, 10, 100], \n", " 'classifier__gamma': [1,0.1,0.01,0.001],\n", " 'classifier__kernel': ['rbf', 'poly', 'sigmoid']},\n", " {'classifier' : [GradientBoostingClassifier()],\n", " 'classifier__max_depth' : [3,4,5]}\n", "]\n", "\n", "# Create grid search object\n", "\n", "clf = GridSearchCV(pipe, param_grid = param_grid, cv = 5, verbose=True, n_jobs=-1, scoring='recall')\n", "\n", "# Fit on data\n", "\n", "best_clf = clf.fit(X_train, y_train)" ] }, { "cell_type": "code", "execution_count": 29, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:19:02.079912Z", "iopub.status.busy": "2021-02-27T01:19:02.079123Z", "iopub.status.idle": "2021-02-27T01:19:02.082222Z", "shell.execute_reply": "2021-02-27T01:19:02.082740Z" }, "papermill": { "duration": 0.053652, "end_time": "2021-02-27T01:19:02.082918", "exception": false, "start_time": "2021-02-27T01:19:02.029266", "status": "completed" }, "tags": [] }, "outputs": [ { "data": { "text/plain": [ "{'classifier': SVC(C=10, gamma=1, kernel='poly'),\n", " 'classifier__C': 10,\n", " 'classifier__gamma': 1,\n", " 'classifier__kernel': 'poly'}" ] }, "execution_count": 29, "metadata": {}, "output_type": "execute_result" } ], "source": [ "best_clf.best_params_" ] }, { "cell_type": "markdown", "metadata": { "papermill": { "duration": 0.04302, "end_time": "2021-02-27T01:19:02.170490", "exception": false, "start_time": "2021-02-27T01:19:02.127470", "status": "completed" }, "tags": [] }, "source": [ "parameters = {\n", " \"loss\":[\"deviance\"],\n", " \"learning_rate\": [0.01, 0.025, 0.05, 0.075, 0.1, 0.15, 0.2],\n", " \"min_samples_split\": np.linspace(0.1, 0.5, 12),\n", " \"min_samples_leaf\": np.linspace(0.1, 0.5, 12),\n", " \"max_depth\":[3,5,8],\n", " \"subsample\":[0.5, 0.618, 0.8, 0.85, 0.9, 0.95, 1.0],\n", " \"n_estimators\":[10]\n", " }\n", "gsearch1 = GridSearchCV(estimator = GradientBoostingClassifier(), \n", "param_grid = parameters, scoring='recall',n_jobs=-1,cv=2, verbose=True)\n", "gsearch1.fit(X_train,y_train)\n", "gsearch1.best_params_, gsearch1.best_score_" ] }, { "cell_type": "code", "execution_count": 30, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:19:02.263009Z", "iopub.status.busy": "2021-02-27T01:19:02.262263Z", "iopub.status.idle": "2021-02-27T01:19:02.697404Z", "shell.execute_reply": "2021-02-27T01:19:02.696795Z" }, "papermill": { "duration": 0.48148, "end_time": "2021-02-27T01:19:02.697558", "exception": false, "start_time": "2021-02-27T01:19:02.216078", "status": "completed" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Training Score 0.9227972027972028\n", "Testing Score \n", " 0.9125896934116112\n", "0.9125896934116112\n", " precision recall f1-score support\n", "\n", " 0 0.95 0.96 0.95 1449\n", " 1 0.17 0.15 0.16 84\n", "\n", " accuracy 0.91 1533\n", " macro avg 0.56 0.56 0.56 1533\n", "weighted avg 0.91 0.91 0.91 1533\n", "\n" ] }, { "data": { "image/png": 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\n", "text/plain": [ "<Figure size 1008x360 with 2 Axes>" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "model = SVC(C=100, gamma=0.1, kernel='sigmoid')\n", "model.fit(X_train, y_train)\n", "#== \n", "#Score \n", "#== \n", "logistic_score = model.score(X_train, y_train)\n", "logistic_test = model.score(X_test, y_test)\n", "#== \n", "#testing model \n", "#== \n", "y_pred = model.predict(X_test)\n", "#== \n", "#evaluation\n", "#== \n", "cm = confusion_matrix(y_test,y_pred)\n", "print('Training Score',logistic_score)\n", "print('Testing Score \\n',logistic_test)\n", "\n", "plt.figure(figsize=(14,5))\n", "\n", "conf_matrix = pd.DataFrame(data=cm,columns=['Predicted:0','Predicted:1'],index=['Actual:0','Actual:1'])\n", "sns.heatmap(conf_matrix, annot=True,fmt='d',cmap=\"Greens\");\n", "print(accuracy_score(y_test,y_pred))\n", "print(classification_report(y_test, y_pred))" ] }, { "cell_type": "code", "execution_count": 31, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:19:02.792983Z", "iopub.status.busy": "2021-02-27T01:19:02.792269Z", "iopub.status.idle": "2021-02-27T01:19:02.795669Z", "shell.execute_reply": "2021-02-27T01:19:02.794996Z" }, "papermill": { "duration": 0.052513, "end_time": "2021-02-27T01:19:02.795811", "exception": false, "start_time": "2021-02-27T01:19:02.743298", "status": "completed" }, "tags": [] }, "outputs": [], "source": [ "import pickle\n", "filename = 'logistic_model.pkl'\n", "pickle.dump(model, open(filename, 'wb'))" ] }, { "cell_type": "code", "execution_count": 32, "metadata": { "execution": { "iopub.execute_input": "2021-02-27T01:19:02.897173Z", "iopub.status.busy": "2021-02-27T01:19:02.896470Z", "iopub.status.idle": "2021-02-27T01:19:02.917626Z", "shell.execute_reply": "2021-02-27T01:19:02.917018Z" }, "papermill": { "duration": 0.076601, "end_time": "2021-02-27T01:19:02.917772", "exception": false, "start_time": "2021-02-27T01:19:02.841171", "status": "completed" }, "tags": [] }, "outputs": [ { "ename": "AttributeError", "evalue": "predict_proba is not available when probability=False", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m<ipython-input-32-0f83f6f07311>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mmodel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpredict_proba\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m100\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m23\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m50\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/sklearn/svm/_base.py\u001b[0m in \u001b[0;36mpredict_proba\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 664\u001b[0m \u001b[0mdatasets\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 665\u001b[0m \"\"\"\n\u001b[0;32m--> 666\u001b[0;31m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_check_proba\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 667\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_predict_proba\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 668\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m/opt/conda/lib/python3.7/site-packages/sklearn/svm/_base.py\u001b[0m in \u001b[0;36m_check_proba\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 631\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_check_proba\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 632\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mprobability\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 633\u001b[0;31m raise AttributeError(\"predict_proba is not available when \"\n\u001b[0m\u001b[1;32m 634\u001b[0m \" probability=False\")\n\u001b[1;32m 635\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_impl\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32min\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0;34m'c_svc'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'nu_svc'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;31mAttributeError\u001b[0m: predict_proba is not available when probability=False" ] } ], "source": [ "model.predict_proba([[1, 1, 1, 1, 1, 0, 1, 0, 0, 0, 0, 1, 0, 0, 100, 23, 50]])" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.9" }, "papermill": { "default_parameters": {}, "duration": 493.623358, "end_time": "2021-02-27T01:19:03.877126", "environment_variables": {}, "exception": null, "input_path": "__notebook__.ipynb", "output_path": "__notebook__.ipynb", "parameters": {}, "start_time": "2021-02-27T01:10:50.253768", "version": "2.2.2" } }, "nbformat": 4, "nbformat_minor": 4 }	0055/330/55330662.ipynb	s3://data-agents/kaggle-outputs/sharded/012_00055.jsonl.gz

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