{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "4da8c3f9",
   "metadata": {},
   "source": [
    "# 02. Одномерный и парный анализ\n",
    "\n",
    "Цели: описать распределения показов/кликов/заказов, категоризировать демографию и устройство, изучить базовые парные связи и корреляции."
   ]
  },
  {
   "cell_type": "code",
   "id": "03456348",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-12-05T18:34:03.072465Z",
     "start_time": "2025-12-05T18:34:02.753518Z"
    }
   },
   "source": [
    "\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "from pathlib import Path\n",
    "from eda_utils import (\n",
    "    load_data, DATA_PATH, CATEGORIES, ACTIVE_IMP_COLS, PASSIVE_IMP_COLS,\n",
    "    ACTIVE_CLICK_COLS, PASSIVE_CLICK_COLS, ORDER_COLS, NUMERIC_COLS, CAT_COLS,\n",
    "    describe_zero_share, safe_divide, build_daily, build_client, add_contact_density\n",
    ")\n",
    "pd.set_option(\"display.max_columns\", None)\n",
    "pd.options.display.float_format = '{:,.3f}'.format\n",
    "sns.set_theme(style=\"ticks\", palette=\"deep\")\n",
    "\n",
    "df = load_data()"
   ],
   "outputs": [],
   "execution_count": 1
  },
  {
   "cell_type": "code",
   "id": "b806797c",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-12-05T18:34:03.217978Z",
     "start_time": "2025-12-05T18:34:03.078068Z"
    }
   },
   "source": [
    "\n",
    "stat_groups = {\n",
    "    'active_imp': ACTIVE_IMP_COLS,\n",
    "    'passive_imp': PASSIVE_IMP_COLS,\n",
    "    'active_click': ACTIVE_CLICK_COLS,\n",
    "    'passive_click': PASSIVE_CLICK_COLS,\n",
    "    'orders': ORDER_COLS,\n",
    "}\n",
    "described = {name: describe_zero_share(df, cols) for name, cols in stat_groups.items()}\n",
    "agg_totals = df[['active_imp_total', 'passive_imp_total', 'active_click_total', 'passive_click_total', 'orders_amt_total']].describe().T\n",
    "agg_totals"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "                          count  mean   std   min   25%   50%   75%     max\n",
       "active_imp_total    118,189.000 1.857 1.316 0.000 1.000 2.000 2.000  29.000\n",
       "passive_imp_total   118,189.000 4.003 4.022 0.000 1.000 3.000 5.000 132.000\n",
       "active_click_total  118,189.000 1.247 0.633 0.000 1.000 1.000 1.000  16.000\n",
       "passive_click_total 118,189.000 0.153 0.431 0.000 0.000 0.000 0.000  12.000\n",
       "orders_amt_total    118,189.000 0.105 0.356 0.000 0.000 0.000 0.000  11.000"
      ],
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       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>active_imp_total</th>\n",
       "      <td>118,189.000</td>\n",
       "      <td>1.857</td>\n",
       "      <td>1.316</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>2.000</td>\n",
       "      <td>2.000</td>\n",
       "      <td>29.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>passive_imp_total</th>\n",
       "      <td>118,189.000</td>\n",
       "      <td>4.003</td>\n",
       "      <td>4.022</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>3.000</td>\n",
       "      <td>5.000</td>\n",
       "      <td>132.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>active_click_total</th>\n",
       "      <td>118,189.000</td>\n",
       "      <td>1.247</td>\n",
       "      <td>0.633</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>16.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>passive_click_total</th>\n",
       "      <td>118,189.000</td>\n",
       "      <td>0.153</td>\n",
       "      <td>0.431</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>12.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>orders_amt_total</th>\n",
       "      <td>118,189.000</td>\n",
       "      <td>0.105</td>\n",
       "      <td>0.356</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>11.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "execution_count": 2
  },
  {
   "cell_type": "code",
   "id": "876a72d6",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-12-05T18:34:03.267569Z",
     "start_time": "2025-12-05T18:34:03.251571Z"
    }
   },
   "source": [
    "for name, table in described.items():\n",
    "    display(table)"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "                    col   count  mean  median   std   min   q25   q75    max  \\\n",
       "0        active_imp_ent  118189 0.314   0.000 0.614 0.000 0.000 0.000  9.000   \n",
       "1      active_imp_super  118189 0.380   0.000 0.809 0.000 0.000 0.000 11.000   \n",
       "2  active_imp_transport  118189 0.574   0.000 0.944 0.000 0.000 1.000 24.000   \n",
       "3   active_imp_shopping  118189 0.255   0.000 0.565 0.000 0.000 0.000  6.000   \n",
       "4      active_imp_hotel  118189 0.141   0.000 0.483 0.000 0.000 0.000  7.000   \n",
       "5       active_imp_avia  118189 0.193   0.000 0.523 0.000 0.000 0.000  6.000   \n",
       "\n",
       "   share_zero   p95   p99  \n",
       "0       0.755 2.000 2.000  \n",
       "1       0.781 2.000 3.000  \n",
       "2       0.665 3.000 3.000  \n",
       "3       0.803 2.000 2.000  \n",
       "4       0.902 1.000 2.000  \n",
       "5       0.857 1.000 2.000  "
      ],
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>active_imp_ent</td>\n",
       "      <td>118189</td>\n",
       "      <td>0.314</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.614</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>9.000</td>\n",
       "      <td>0.755</td>\n",
       "      <td>2.000</td>\n",
       "      <td>2.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>active_imp_super</td>\n",
       "      <td>118189</td>\n",
       "      <td>0.380</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.809</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>11.000</td>\n",
       "      <td>0.781</td>\n",
       "      <td>2.000</td>\n",
       "      <td>3.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>active_imp_transport</td>\n",
       "      <td>118189</td>\n",
       "      <td>0.574</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.944</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>24.000</td>\n",
       "      <td>0.665</td>\n",
       "      <td>3.000</td>\n",
       "      <td>3.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>active_imp_shopping</td>\n",
       "      <td>118189</td>\n",
       "      <td>0.255</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.565</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>6.000</td>\n",
       "      <td>0.803</td>\n",
       "      <td>2.000</td>\n",
       "      <td>2.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>active_imp_hotel</td>\n",
       "      <td>118189</td>\n",
       "      <td>0.141</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.483</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>7.000</td>\n",
       "      <td>0.902</td>\n",
       "      <td>1.000</td>\n",
       "      <td>2.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>active_imp_avia</td>\n",
       "      <td>118189</td>\n",
       "      <td>0.193</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.523</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>6.000</td>\n",
       "      <td>0.857</td>\n",
       "      <td>1.000</td>\n",
       "      <td>2.000</td>\n",
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       "  </tbody>\n",
       "</table>\n",
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     "data": {
      "text/plain": [
       "                     col   count  mean  median   std   min   q25   q75    max  \\\n",
       "0        passive_imp_ent  118189 0.552   0.000 1.256 0.000 0.000 1.000 42.000   \n",
       "1      passive_imp_super  118189 0.280   0.000 0.859 0.000 0.000 0.000 26.000   \n",
       "2  passive_imp_transport  118189 0.794   0.000 1.472 0.000 0.000 1.000 43.000   \n",
       "3   passive_imp_shopping  118189 0.689   0.000 1.768 0.000 0.000 1.000 83.000   \n",
       "4      passive_imp_hotel  118189 0.987   0.000 1.811 0.000 0.000 1.000 44.000   \n",
       "5       passive_imp_avia  118189 0.702   0.000 1.400 0.000 0.000 1.000 52.000   \n",
       "\n",
       "   share_zero   p95   p99  \n",
       "0       0.709 3.000 6.000  \n",
       "1       0.837 2.000 4.000  \n",
       "2       0.597 3.000 7.000  \n",
       "3       0.673 3.000 8.000  \n",
       "4       0.535 4.000 8.000  \n",
       "5       0.615 3.000 6.000  "
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       "      <th>0</th>\n",
       "      <td>passive_imp_ent</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>passive_imp_super</td>\n",
       "      <td>118189</td>\n",
       "      <td>0.280</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.859</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>26.000</td>\n",
       "      <td>0.837</td>\n",
       "      <td>2.000</td>\n",
       "      <td>4.000</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>passive_imp_transport</td>\n",
       "      <td>118189</td>\n",
       "      <td>0.794</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.472</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>43.000</td>\n",
       "      <td>0.597</td>\n",
       "      <td>3.000</td>\n",
       "      <td>7.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>passive_imp_shopping</td>\n",
       "      <td>118189</td>\n",
       "      <td>0.689</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.768</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>83.000</td>\n",
       "      <td>0.673</td>\n",
       "      <td>3.000</td>\n",
       "      <td>8.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>passive_imp_hotel</td>\n",
       "      <td>118189</td>\n",
       "      <td>0.987</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.811</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>44.000</td>\n",
       "      <td>0.535</td>\n",
       "      <td>4.000</td>\n",
       "      <td>8.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>passive_imp_avia</td>\n",
       "      <td>118189</td>\n",
       "      <td>0.702</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.400</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>52.000</td>\n",
       "      <td>0.615</td>\n",
       "      <td>3.000</td>\n",
       "      <td>6.000</td>\n",
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      "text/plain": [
       "                      col   count  mean  median   std   min   q25   q75  \\\n",
       "0        active_click_ent  118189 0.240   0.000 0.483 0.000 0.000 0.000   \n",
       "1      active_click_super  118189 0.276   0.000 0.542 0.000 0.000 0.000   \n",
       "2  active_click_transport  118189 0.443   0.000 0.645 0.000 0.000 1.000   \n",
       "3   active_click_shopping  118189 0.199   0.000 0.450 0.000 0.000 0.000   \n",
       "4      active_click_hotel  118189 0.035   0.000 0.185 0.000 0.000 0.000   \n",
       "5       active_click_avia  118189 0.054   0.000 0.227 0.000 0.000 0.000   \n",
       "\n",
       "     max  share_zero   p95   p99  \n",
       "0  6.000       0.781 1.000 2.000  \n",
       "1  9.000       0.765 1.000 2.000  \n",
       "2 11.000       0.630 2.000 2.000  \n",
       "3  5.000       0.820 1.000 2.000  \n",
       "4  2.000       0.965 0.000 1.000  \n",
       "5  2.000       0.946 1.000 1.000  "
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       "      <td>active_click_ent</td>\n",
       "      <td>118189</td>\n",
       "      <td>0.240</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.483</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>6.000</td>\n",
       "      <td>0.781</td>\n",
       "      <td>1.000</td>\n",
       "      <td>2.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>active_click_super</td>\n",
       "      <td>118189</td>\n",
       "      <td>0.276</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.542</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>9.000</td>\n",
       "      <td>0.765</td>\n",
       "      <td>1.000</td>\n",
       "      <td>2.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>active_click_transport</td>\n",
       "      <td>118189</td>\n",
       "      <td>0.443</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.645</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "      <td>11.000</td>\n",
       "      <td>0.630</td>\n",
       "      <td>2.000</td>\n",
       "      <td>2.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>active_click_shopping</td>\n",
       "      <td>118189</td>\n",
       "      <td>0.199</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.450</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>5.000</td>\n",
       "      <td>0.820</td>\n",
       "      <td>1.000</td>\n",
       "      <td>2.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>active_click_hotel</td>\n",
       "      <td>118189</td>\n",
       "      <td>0.035</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.185</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>2.000</td>\n",
       "      <td>0.965</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>active_click_avia</td>\n",
       "      <td>118189</td>\n",
       "      <td>0.054</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.227</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>2.000</td>\n",
       "      <td>0.946</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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       "                       col   count  mean  median   std   min   q25   q75  \\\n",
       "0        passive_click_ent  118189 0.027   0.000 0.190 0.000 0.000 0.000   \n",
       "1      passive_click_super  118189 0.009   0.000 0.118 0.000 0.000 0.000   \n",
       "2  passive_click_transport  118189 0.020   0.000 0.155 0.000 0.000 0.000   \n",
       "3   passive_click_shopping  118189 0.011   0.000 0.128 0.000 0.000 0.000   \n",
       "4      passive_click_hotel  118189 0.058   0.000 0.242 0.000 0.000 0.000   \n",
       "5       passive_click_avia  118189 0.028   0.000 0.182 0.000 0.000 0.000   \n",
       "\n",
       "     max  share_zero   p95   p99  \n",
       "0 11.000       0.976 0.000 1.000  \n",
       "1  5.000       0.993 0.000 0.000  \n",
       "2  7.000       0.981 0.000 1.000  \n",
       "3  7.000       0.991 0.000 0.000  \n",
       "4  8.000       0.944 1.000 1.000  \n",
       "5  8.000       0.974 0.000 1.000  "
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       "      <td>0.190</td>\n",
       "      <td>0.000</td>\n",
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       "      <td>0.000</td>\n",
       "      <td>0.118</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>5.000</td>\n",
       "      <td>0.993</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>passive_click_transport</td>\n",
       "      <td>118189</td>\n",
       "      <td>0.020</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.155</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>7.000</td>\n",
       "      <td>0.981</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>passive_click_shopping</td>\n",
       "      <td>118189</td>\n",
       "      <td>0.011</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.128</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>7.000</td>\n",
       "      <td>0.991</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>passive_click_hotel</td>\n",
       "      <td>118189</td>\n",
       "      <td>0.058</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.242</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>8.000</td>\n",
       "      <td>0.944</td>\n",
       "      <td>1.000</td>\n",
       "      <td>1.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>passive_click_avia</td>\n",
       "      <td>118189</td>\n",
       "      <td>0.028</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.182</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>8.000</td>\n",
       "      <td>0.974</td>\n",
       "      <td>0.000</td>\n",
       "      <td>1.000</td>\n",
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       "                    col   count  mean  median   std  min   q25   q75  max  \\\n",
       "0        orders_amt_ent  118189 0.010   0.000 0.115    0 0.000 0.000   11   \n",
       "1      orders_amt_super  118189 0.022   0.000 0.155    0 0.000 0.000    4   \n",
       "2  orders_amt_transport  118189 0.053   0.000 0.242    0 0.000 0.000    5   \n",
       "3   orders_amt_shopping  118189 0.008   0.000 0.114    0 0.000 0.000   11   \n",
       "4      orders_amt_hotel  118189 0.004   0.000 0.067    0 0.000 0.000    3   \n",
       "5       orders_amt_avia  118189 0.009   0.000 0.109    0 0.000 0.000    6   \n",
       "\n",
       "   share_zero   p95   p99  \n",
       "0       0.991 0.000 0.000  \n",
       "1       0.980 0.000 1.000  \n",
       "2       0.950 0.000 1.000  \n",
       "3       0.994 0.000 0.000  \n",
       "4       0.996 0.000 0.000  \n",
       "5       0.993 0.000 0.000  "
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       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>orders_amt_ent</td>\n",
       "      <td>118189</td>\n",
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       "      <td>0.115</td>\n",
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       "      <td>orders_amt_super</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>orders_amt_transport</td>\n",
       "      <td>118189</td>\n",
       "      <td>0.053</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.242</td>\n",
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       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
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       "      <td>1.000</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>orders_amt_shopping</td>\n",
       "      <td>118189</td>\n",
       "      <td>0.008</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.114</td>\n",
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       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>orders_amt_hotel</td>\n",
       "      <td>118189</td>\n",
       "      <td>0.004</td>\n",
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       "      <td>0.000</td>\n",
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       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>orders_amt_avia</td>\n",
       "      <td>118189</td>\n",
       "      <td>0.009</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.109</td>\n",
       "      <td>0</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
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   ],
   "execution_count": 3
  },
  {
   "cell_type": "code",
   "id": "b3a98135",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-12-05T18:34:06.591330Z",
     "start_time": "2025-12-05T18:34:03.435168Z"
    }
   },
   "source": [
    "\n",
    "def plot_histogram(cols, title):\n",
    "    fig, axes = plt.subplots(2, 3, figsize=(12, 6), sharey=False)\n",
    "    for ax, col in zip(axes.flat, cols):\n",
    "        sns.histplot(np.log1p(df[col]), bins=40, ax=ax)\n",
    "        ax.set_title(col)\n",
    "        ax.set_xlabel('log1p')\n",
    "    fig.suptitle(title)\n",
    "    plt.tight_layout()\n",
    "\n",
    "plot_histogram(ACTIVE_IMP_COLS, 'Активные показы')\n",
    "plot_histogram(ACTIVE_CLICK_COLS, 'Активные клики')\n",
    "plot_histogram(PASSIVE_IMP_COLS, 'Пассивные показы')\n",
    "plot_histogram(PASSIVE_CLICK_COLS, 'Пассивные клики')\n",
    "plot_histogram(ORDER_COLS, 'Заказы')"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1200x600 with 6 Axes>"
      ],
      "image/png": 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     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1200x600 with 6 Axes>"
      ],
      "image/png": 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     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1200x600 with 6 Axes>"
      ],
      "image/png": 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     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1200x600 with 6 Axes>"
      ],
      "image/png": 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     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1200x600 with 6 Axes>"
      ],
      "image/png": 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     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    }
   ],
   "execution_count": 4
  },
  {
   "cell_type": "code",
   "id": "c4f340f9",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-12-05T18:34:07.305972Z",
     "start_time": "2025-12-05T18:34:06.647160Z"
    }
   },
   "source": [
    "agg_cols = ['active_imp_total', 'passive_imp_total', 'active_click_total', 'passive_click_total', 'orders_amt_total']\n",
    "melted = df[agg_cols].melt(var_name='metric', value_name='value')\n",
    "plt.figure(figsize=(10, 4))\n",
    "sns.boxplot(data=melted, x='metric', y='value')\n",
    "plt.xticks(rotation=30)\n",
    "plt.title('Агрегаты: boxplot')\n",
    "plt.tight_layout()"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1000x400 with 1 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    }
   ],
   "execution_count": 5
  },
  {
   "cell_type": "code",
   "id": "efff2757",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-12-05T18:34:07.325082Z",
     "start_time": "2025-12-05T18:34:07.313902Z"
    }
   },
   "source": [
    "\n",
    "gender_dist = df['gender_cd'].value_counts(dropna=False).to_frame('count')\n",
    "gender_dist['share'] = gender_dist['count'] / len(df)\n",
    "device_dist = df['device_platform_cd'].value_counts(dropna=False).to_frame('count')\n",
    "device_dist['share'] = device_dist['count'] / len(df)\n",
    "age_groups = df['age_group'].value_counts().sort_index().to_frame('count')\n",
    "age_groups['share'] = age_groups['count'] / len(df)\n",
    "display(gender_dist, device_dist, age_groups)"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "           count  share\n",
       "gender_cd              \n",
       "M          81030  0.686\n",
       "F          37159  0.314"
      ],
      "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>count</th>\n",
       "      <th>share</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>gender_cd</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>M</th>\n",
       "      <td>81030</td>\n",
       "      <td>0.686</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>F</th>\n",
       "      <td>37159</td>\n",
       "      <td>0.314</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    },
    {
     "data": {
      "text/plain": [
       "                    count  share\n",
       "device_platform_cd              \n",
       "iOS                 61679  0.522\n",
       "Android             55232  0.467\n",
       "iPadOS               1278  0.011"
      ],
      "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>count</th>\n",
       "      <th>share</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>device_platform_cd</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>iOS</th>\n",
       "      <td>61679</td>\n",
       "      <td>0.522</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Android</th>\n",
       "      <td>55232</td>\n",
       "      <td>0.467</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>iPadOS</th>\n",
       "      <td>1278</td>\n",
       "      <td>0.011</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    },
    {
     "data": {
      "text/plain": [
       "           count  share\n",
       "age_group              \n",
       "<25         2293  0.019\n",
       "25-34      22051  0.187\n",
       "35-44      50483  0.427\n",
       "45-54      29494  0.250\n",
       "55+        13868  0.117"
      ],
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\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>count</th>\n",
       "      <th>share</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>age_group</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>&lt;25</th>\n",
       "      <td>2293</td>\n",
       "      <td>0.019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25-34</th>\n",
       "      <td>22051</td>\n",
       "      <td>0.187</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35-44</th>\n",
       "      <td>50483</td>\n",
       "      <td>0.427</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45-54</th>\n",
       "      <td>29494</td>\n",
       "      <td>0.250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55+</th>\n",
       "      <td>13868</td>\n",
       "      <td>0.117</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    }
   ],
   "execution_count": 6
  },
  {
   "cell_type": "code",
   "id": "57c4189f",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-12-05T18:34:07.617855Z",
     "start_time": "2025-12-05T18:34:07.403608Z"
    }
   },
   "source": [
    "fig, axes = plt.subplots(1, 3, figsize=(14, 4))\n",
    "sns.barplot(x=gender_dist.index, y=gender_dist['share'], ax=axes[0])\n",
    "axes[0].set_title('Пол')\n",
    "axes[0].set_ylabel('Доля')\n",
    "sns.barplot(x=device_dist.index, y=device_dist['share'], ax=axes[1])\n",
    "axes[1].set_title('Платформа')\n",
    "axes[1].tick_params(axis='x', rotation=20)\n",
    "sns.histplot(df['age'], bins=30, ax=axes[2])\n",
    "axes[2].set_title('Возраст')\n",
    "plt.tight_layout()"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1400x400 with 3 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    }
   ],
   "execution_count": 7
  },
  {
   "cell_type": "code",
   "id": "1492f73e",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-12-05T18:34:08.241394Z",
     "start_time": "2025-12-05T18:34:07.629780Z"
    }
   },
   "source": [
    "\n",
    "num_for_corr = ACTIVE_IMP_COLS + PASSIVE_IMP_COLS + ACTIVE_CLICK_COLS + PASSIVE_CLICK_COLS + ORDER_COLS + ['age']\n",
    "corr = df[num_for_corr].corr(method='spearman')\n",
    "plt.figure(figsize=(14, 10))\n",
    "sns.heatmap(corr, cmap='coolwarm', center=0)\n",
    "plt.title('Спирмен: числовые признаки')\n",
    "plt.tight_layout()"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1400x1000 with 2 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    }
   ],
   "execution_count": 8
  },
  {
   "cell_type": "code",
   "id": "65c43375",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-12-05T18:34:10.553748Z",
     "start_time": "2025-12-05T18:34:08.248621Z"
    }
   },
   "source": [
    "\n",
    "fig, axes = plt.subplots(len(CATEGORIES), 2, figsize=(12, 16))\n",
    "for i, cat in enumerate(CATEGORIES):\n",
    "    sns.scatterplot(data=df, x=f'active_imp_{cat}', y=f'active_click_{cat}', ax=axes[i, 0], alpha=0.3)\n",
    "    axes[i, 0].set_title(f'Active {cat}: imp->click')\n",
    "    sns.scatterplot(data=df, x=f'active_click_{cat}', y=f'orders_amt_{cat}', ax=axes[i, 1], alpha=0.3)\n",
    "    axes[i, 1].set_title(f'{cat}: click->order')\n",
    "plt.tight_layout()"
   ],
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1200x1600 with 12 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    }
   ],
   "execution_count": 9
  },
  {
   "cell_type": "code",
   "id": "68dbabeb",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-12-05T18:34:10.898323Z",
     "start_time": "2025-12-05T18:34:10.592095Z"
    }
   },
   "source": [
    "\n",
    "bin_frames = []\n",
    "for channel, imp_tpl, click_tpl in [('active', 'active_imp_{}', 'active_click_{}'), ('passive', 'passive_imp_{}', 'passive_click_{}')]:\n",
    "    for cat in CATEGORIES:\n",
    "        imp_col = imp_tpl.format(cat)\n",
    "        click_col = click_tpl.format(cat)\n",
    "        bins = pd.qcut(df[imp_col], q=5, duplicates='drop')\n",
    "        grouped = df.groupby(bins).agg({imp_col: 'mean', click_col: 'mean'})\n",
    "        grouped = grouped.rename(columns={imp_col: 'imp_mean', click_col: 'click_mean'})\n",
    "        grouped['ctr'] = safe_divide(grouped['click_mean'], grouped['imp_mean'])\n",
    "        grouped['category'] = cat\n",
    "        grouped['channel'] = channel\n",
    "        grouped = grouped.reset_index().rename(columns={imp_col: 'imp_bin'})\n",
    "        bin_frames.append(grouped)\n",
    "ctr_bins = pd.concat(bin_frames, ignore_index=True)\n",
    "plt.figure(figsize=(12, 6))\n",
    "sns.lineplot(data=ctr_bins, x='imp_mean', y='ctr', hue='category', style='channel', markers=True)\n",
    "plt.xscale('log')\n",
    "plt.title('CTR по квантилям показов')\n",
    "plt.tight_layout()"
   ],
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/mx/y1qcnthj1154ngqj00r8gz480000gn/T/ipykernel_25594/4204725324.py:8: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  grouped = df.groupby(bins).agg({imp_col: 'mean', click_col: 'mean'})\n",
      "/var/folders/mx/y1qcnthj1154ngqj00r8gz480000gn/T/ipykernel_25594/4204725324.py:8: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  grouped = df.groupby(bins).agg({imp_col: 'mean', click_col: 'mean'})\n",
      "/var/folders/mx/y1qcnthj1154ngqj00r8gz480000gn/T/ipykernel_25594/4204725324.py:8: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  grouped = df.groupby(bins).agg({imp_col: 'mean', click_col: 'mean'})\n",
      "/var/folders/mx/y1qcnthj1154ngqj00r8gz480000gn/T/ipykernel_25594/4204725324.py:8: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  grouped = df.groupby(bins).agg({imp_col: 'mean', click_col: 'mean'})\n",
      "/var/folders/mx/y1qcnthj1154ngqj00r8gz480000gn/T/ipykernel_25594/4204725324.py:8: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  grouped = df.groupby(bins).agg({imp_col: 'mean', click_col: 'mean'})\n",
      "/var/folders/mx/y1qcnthj1154ngqj00r8gz480000gn/T/ipykernel_25594/4204725324.py:8: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  grouped = df.groupby(bins).agg({imp_col: 'mean', click_col: 'mean'})\n",
      "/var/folders/mx/y1qcnthj1154ngqj00r8gz480000gn/T/ipykernel_25594/4204725324.py:8: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  grouped = df.groupby(bins).agg({imp_col: 'mean', click_col: 'mean'})\n",
      "/var/folders/mx/y1qcnthj1154ngqj00r8gz480000gn/T/ipykernel_25594/4204725324.py:8: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  grouped = df.groupby(bins).agg({imp_col: 'mean', click_col: 'mean'})\n",
      "/var/folders/mx/y1qcnthj1154ngqj00r8gz480000gn/T/ipykernel_25594/4204725324.py:8: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  grouped = df.groupby(bins).agg({imp_col: 'mean', click_col: 'mean'})\n",
      "/var/folders/mx/y1qcnthj1154ngqj00r8gz480000gn/T/ipykernel_25594/4204725324.py:8: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  grouped = df.groupby(bins).agg({imp_col: 'mean', click_col: 'mean'})\n",
      "/var/folders/mx/y1qcnthj1154ngqj00r8gz480000gn/T/ipykernel_25594/4204725324.py:8: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  grouped = df.groupby(bins).agg({imp_col: 'mean', click_col: 'mean'})\n",
      "/var/folders/mx/y1qcnthj1154ngqj00r8gz480000gn/T/ipykernel_25594/4204725324.py:8: FutureWarning: The default of observed=False is deprecated and will be changed to True in a future version of pandas. Pass observed=False to retain current behavior or observed=True to adopt the future default and silence this warning.\n",
      "  grouped = df.groupby(bins).agg({imp_col: 'mean', click_col: 'mean'})\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ],
      "image/png": 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yiIiIiIiIiPoy58wnqXwiz2Bvfy3ltT3eAKpX7YIn5V+33HKLriNt1yMiIiIiIiKik4dtd57D0I0tlG6vgDoaf/3rX5GQkIBLLrnkqD5Odsk7luooIiIiIiIiIiLqYwHU//73P1itVowcOdLVXyrOPPNM3HjjjbqIiIiIiIiIiNyprKwMCxcuxEUXXcQXojcGUPPnz+/0540bN+pueM8//zxSU1Pddl9ERERERERERE6PPPII9u7dywCqtwRQUuFUWloKPz8/eHt7Iy4u7nvbO4rIyEgEBga66S6JiIiIiIiIiA5qbW3l09GbhpDLDnVTpkzB559/7u5bISIiIiIiIqI+pKamBn/5y180l5BRQFdccQW2bNmi5959912cddZZGDZsGEaMGIHLLrsMmzdv1nO33347PvjgA6xatQppaWmuQOqFF17QOdTDhw/HOeecg48//rjT55PHvvzyy/W8XCfnBw0ahPT0dFeRzksvvYRTTjkFQ4cO1bdvvvmm6+PlOrleusTGjx+P888/HzfddBOuuuqqTp8nOztb72vXrl3osxVQDz30UKc/R0dHY+fOnT94vTyhhztPREevvqkeJqMJNQ118LHa0NzSDC+zF59KIiIiIiLqU26++Wbk5ubiwQcfRGxsLJ599llce+21uP/++3HffffpRmljxozB/v37Naj605/+hI8++gh33nknHA6Hdm09+eST+lj/+Mc/8Omnn+Kuu+5CYmIiVq9ejXvuuQdVVVUaOhUXF+OnP/2pBk/33nsv8vPz9bxz9rUzM5HH//Of/6wB1JIlS/Re6uvrcfXVV+s1cv23336Lt99+G3V1dSgoKNAQSgp8IiIi9JoPP/xQPz4lJaXvBlBE5F4NzY34aMd8fJHxDWoaa+FjseO01Bk4d+CpsJosfHmIiIiIiKhPkCohCXhefPFFrYASEgj5+/sjICBAg5+zzz5bj0dFReHCCy/UUEo4xwhZLBb069cPtbW1Wrn02GOPYcaMGXqNBFoSMsnjSwAlgZF8nDyufFxycrIGWr/4xS/0+urqaq12kuoqqbwS8fHxOmdKKp4kvHKSkEzOCQmZQkNDtZrq5z//OVpaWjTEuuGGG07yM8oAiog6VD5J+PTe1oMtrxJCOf98zoB5rIQiIiIiIqI+ISMjQ99Ke52Tl5cX7rjjDn0/KysLTz/9tAZVeXl52p0l4U5XMjMztUrp97//PYzGg5OQmpqa0NDQoNVS27Ztw5AhQzR8cho7dqzrffk8jY2NGD16dKfHHjduHF5++WWUlJS4jjnDJ2E2mzUok9BJAqiVK1fqrO0zzzwTJxsroIhISdudVD51RY6fP+g0PlNERERERNQnSHDzQz755BNXJdKoUaNwySWXaGDlrID6oYHk//znP7X97lBWqxUmk+kHA6yOj3Eo58d0vF8Jyjq64IILtNJKZkxJJZS0+UkV18nWo4eQE9HJIzOfpOKpy3ONtahtqOPLQUREREREfUJSUpK+dQ4Wd1YszZo1C//617+05U5mMkn7nFQq7dmzp1NQZDAYXB8noZPZbNZ5THFxca4ls5okGJKqqAEDBmgVlFQ5Oa1fv77T/Uh11Nq1azvd55o1a7TN73CBknysDFH/4osvsGjRIh1O7g4MoIhIycBxmfnUFTkug8i/271W50QRERERERF5soSEBMybN08HgkvbWk5Ojg7/llY62TBt3bp12Lp1K3bv3q3znV577TX9OGmpE3a7Hfv27dNgSmY7XXLJJXj88ce1FU6Ovffee3j00UcRFham18suepWVlfo5pL1vxYoVOtjcGWb5+vriJz/5CZ544gkdZi5tf6+//jreeOMNnfnUMfDqilRByT3KbKrJkyfDHdiCR0RKdruTgeMdZ0A5nZoyHZuKtuEf3/0bflYfzEiYiLlJUxHu1/Y/SyIiIiIiIk/zwAMP4JFHHsFvfvMbDZaGDx+uFUs+Pj66m90VV1yh7XNSvSTX/fa3v9WKKdkZ79xzz8WCBQt01tL8+fN1dlRQUJCGUBJMyY50v/71r3H99dfr5woJCcG///1v/ZznnHMOwsPDcemll+rjOudCOR/jb3/7Gw4cOKCznuQ+Lr744h/9Wk477TQNtOS+pN3PHQytP9RI2EdI76OQMjSivk6qmz7c/uX3dsE7Z8ApWJK7Eh9s/woHaktd1w/rPxBzk6diTOQwnSFFRERERER9lwzTlkohqR6SShs6cpmZmaioqOg0ZFyqrCSE+uabbzSwOh5SdSUVXdKG13FI+fG+pkeTqbACiohcrCaL7nYnA8dl5pPdatPKKC+zFXOTp2F24hSsL9qK+ZlLsKFwKzYVb9cVZAvA7MTJej7EHsRnlIiIiIiI6CgUFRXpLnX333+/zpSSKqkHH3xQd7k7nvCpsLAQmzZt0la9qVOnHlX41N0YQBFRJzLrSfh7+7X9T8J48H8TMhxvdORQXftqSrAoaxkWZy9HWV2Ftu79b9sXGB05DPOSpmJY+EAYDRwzR0RERERE9GOmTJmCO++8E88995zOgZK5UTLw/JZbbsHxKCsr0x37JHh66qmn4E5swWMLHtFxaWpuwqr8jViQtQRb92W4jof5hGBO0lTMSpjkCrOIiIiIiMhzsQXP8zjYgkdEPYXZZMak2NG68iuLsCBrKb7N+U4rpN7Y9CHe2fIpxkePwLzkaRgQmvyjuzMQERERERGR52ELHhF1myj/cFw98iJcOvQcfLdnrc6KyizNxfLda3RF+0fo7nnT4yfofCkiIiIiIiLqGxhAEVG3k6HlMxIm6sou3Y2FWUuxdPdq7K0sxH/Xv6OVUZNjx2hVVGJwHF8BIiIiIiIiD8cAiohOqMTgWNwQfDmuGH4+luatwvysJdhTUYDFOSt0JQXFYW7yVEyKHQPv9gHoRERERERE5FkYQBHRSSEtd6ekTNeqp50HsjWIWrlnHbLK8pC1Og+vbPgfpsWPx7ykaYgOOPZtRomIiIiIiKjnYQBFRCeVDCEf0C9Jl8yL+ibnOx1cXly9H1/u+kbXwH4pOitKhpdbTBa+QkRERERERL0cAygicht/L1+cPWAuzkybjS3FO3Vo+ZqCTdi+f5cuOT8zYZKGUWG+oXyliIiIiIiIeikGUETkdkaDEcPCB+oqrS3H4pzlWJi1DKV15fhox3x8vGMBhocPxNzkaRgVMQQmo8ndt0xERERERHRYBQUFWL9+Pc444ww+UwygiKinCbYH4sLBZ+C8gadiXeEWrYraWLQNG9pXiC0Is5MmY1biZATbAt19u0RERERERF267bbbEBUVxQCqHSugiKhHkiqnsVHDdRVV79eKqK9zVqCkrgzvbPkU7239HGOihunQ8iH907SKioiIiIiIiHomBlAeoqXRAYPRjBZHDYzePmhtaYLR4u3u2yLqFuG+/XDF8PPwkyFnIn3vBizIWoLt+zOxau8GXXJ+TtJUzEyYCD8vXz7rREREREQ9SGtrK+obmt32+b2sJt0M6WhVVVXhkUcewYIFC9DY2IjBgwfjD3/4A4YOHYonn3wSa9euxaRJk/Daa6+hrKwMw4cPx7333oukpCRceeWVWLVqlT6OvF28eDH6OgZQHqClqQHlKz5E5ZrPXQGU/9gzEDjpPBjNVnffHlG3kR3xpsSN1bWnogALMpfi27yVWiH12sb38fbmjzEhZhTmJU9DakjiMf0lQ0RERERE3Rs+3fbUMmzPLXXb0zowPhgP/3LKUf37QO77Zz/7Gby9vfHcc8/B19cXH330ES699FK88847es2aNWvg5eWF559/XgOqW2+9VQOoV155RQOqG2+8EeHh4bjrrrtO4FfXezCA8oDKJwmfype9e/CYowblS9v+gwiceA4rocgjxQRE4trRP8Flw8/F8rzVmJ+1BDlle7A0b5Wu2IAozEueiilx42C32Nx9u0RERERE1IusXLkSGzZs0LeBgW2zZ3/3u99h3bp1GjDJbKempiatkAoICNDzl1xyCR599FF9Xz7GYrFogBUcHOzWr6WnYADVy0nbnVQ+daVy9WcImnzBSb8nopPJ2+yF2UlTdGWV5unQ8uW7V2N3RT7+vfYtvLrxA0yNHatVUfFBMXxxiIiIiIhOIqk6kuqj3taCt3XrVq2CmjlzZqfjDQ0NqK+v1wAqNDTUFT4JPz8/rYSirjGA6uWk2knW4c6ZfA7+B0HkyZKC4/B/467EVSMuwLe5K7EgaynyK4uwMHuZrpTgeMxNnoZJMaNhZXsqEREREdFJIeGPt1fvih9aWlq07e7999//3jmr1Yr33ntP39KR613fAfQ9Mu9JVlchlBw3WLxQ+MZ98I4bAp+0cbCGRvNZJI/nY7Xj9NRZOC1lpg4rl/a89L3rsas0F7tW5eLlDe9hevwEzEuaikj/cHffLhERERER9TCpqamorq7Wiqbk5GTX8T/96U8YMGCAW++tt2IA1cvJbncycNw586kj/zGnoS5nE+pyNuoq++Z1WEKi4JM2Hva08fCKSOKQZvL437QMCkvRVeGoxNc532lV1P6aEnyesVjX4LBUbc8bGzkcZhP/l0hERERERMDUqVMxcOBA/Pa3v8Wdd96JiIgIvPHGG1oR9eKLL+oA8h/j4+OD/Px8FBUV6TDyvo7/2urljBZv3e3OOfPp0F3wWurrEHraz1GzcxXqcjejsSQf5Sve12XyD4VP6jitjPKOHQSD0eTuL4fohAnw9se5A0/B2QPmYlPRdp0VtbZwM7buy9Al52clTMKcpCno5xPCV4KIiIiIqA8zmUz4z3/+o0PFb775ZtTV1SEpKQlPPfUUJk6ceEQBlAwlv+2223D22Wfju+++08fsywytMlWrD5s9e7a+XbRoEXr7bngykLylvgZGLx+0NjfBaPXufI2jBrVZ61CzMx21mevR2uhwnTPa/GBPGaPVUbaEYTBavNzwVRCdXAdqS7EoazkWZy9HmaNCjxlgwMiIwVoVNSJ8MIxGI18WIiIiIqIj4HA4kJOTg4SEBN39jTz/NZ19FJkKK6A8qBJKmOxtA8cNXbQSSWWU7+CpulqaGrQ9r3ZnOmoyVqOlrgrVm77WZbB4w540Qtv07MmjYfL2OelfD9HJEGoPxk+GnoULBp+OtQWbtCpqc/EOrCvcokvOS0WUVEYF2jjMn4iIiIiI6FgxgOqjjGYrfKTiKWUMQlua4dizXSujpFWvufIAanas1AWjGbb4wfBJHQ976jiY/YLcfetE3c5sNGF89EhdhVX7dE7UNznfaYXUW5s/xrtbPsXY6BGYlzRNZ0Yd7RauREREREREfR1b8DykBa+7SEdmQ1F2exiVjsYDezucNcArOlXb9GRZgjhEjTxXQ3MjVu5ZhwWZS7CzJNt1PNKvP+YmTdVd9Hy9WB1IREREROTEFjzP4+jGFjwGUAygDquhpKCtTW9nOuoLdnU6Zw2LhT21LYyy9o9nVQh5rLzyvViQuRRL8tLhaKrXYxaTBZNiRuusqORgfv8TERERETGA8jwOBlDdhwHUkWuqLEFNxioNpOrytgKtLa5z5sAw3VFP5kZ5R6dxRz3ySHWNDizLW435WUs0lHKKD4zWIGpK7Fh4t89jIyIiIiLqaxhAeR4GUN2IAdSxaa6rQu2utVoZVZe9Aa1NDa5zJp8A2FPGtu2oFz8UBrOl214vop7SqrqrJEdnRa3YsxaNzY163Gb2xtT4cTorKjYwyt23SURERER0UjGA8jwO7oJH7may+cFv2AxdLQ0O1GVvRE1GOmp3rUFzTQWqNizUZbDaYE8epWGUPWkUjF42d9860XGTIeSpoYm6fjriQnyTuxILspboAHPZSU9WWkgi5iZPw4SYUbCaGMISEREREVHfxl3w6LgZrd7wGTBeV2tzE+p2b0XtzlVaHdVcXYaabct1GUwW2BKGwZ42Dj4pY7VSiqi3k0HkZ6bNxhmps7B1307Mz1qK1Xs36OByWS+tfxczEibq4PIIvzB33y4REREREZFbMICibmUwmWFPGK4r5JTrUF+QqUGUzI1qLC1EbeZaXQcMz8E7ZiB80mRu1DhYAvgPc+r9VVFD+g/QVV5XgcU5K7AwaxkO1Jbi050LdQ3tP0BnRY2OHAaz0eTuWyYiIiIiIjppuAsed8E7aTNzGg/sQU17ZVRD0cFt7YU1PFHb9CSQsoTGcEc98ggtLS1YX7QVCzKXYH3hVrSiVY8HeQdgdtJkzEqcjFB7sLtvk4iIiIioW3AGlOdxcAYU9cbqEGu/WF1BUy5EY8U+V5ueY88ODaRklX37JizBEbqbngRSXpHJMBiM7r59omNiNBoxOnKorn01JViUtQyLs5ejzFGB97Z+jv9t+wKjI4ZqVdSw8IEw8nudiIiIiIg8FCugWAHldjK0vGbXag2kanM2As1NrnMm32D4pI6FfcB42GIHa4sfUW/W1NyEVfkbdWj51n0ZruNhPiGYkzQVMxMmIsDb3633SERERER0LFgB5Xkc3VgBxQCKAVSP0lJfh9qsdW1zozLXobWhznXO6O0Le8po+KSOhy1pBIwWL7feK9Hxyq8swoKspfg25zvUNLZ9r5uMJoyPHol5SdMwsJ9UABr4RBMRERFRr+BpAdS3336Lxx9/HFlZWbDb7Zg+fTruuOMO7NixA1dddZWGLtHR0Xptenp6p2NXXnklBgwYgJKSEj0WEBCAK664Aj/72c9cP+PL4z700ENYs2YNfHx8MH78eNx+++3o16+fnpfHiI+P188nz+tdd92Fs88++6Q+B2zBI49l9LLBd9BkXa1NjajL3axhVE3GKrTUVqJ687e6DGYrbIkjtE1PQimTzc/dt0501KL8w3H1yItw6dBz8N2etToraldpLlbsXqMr2j9Cd8+bFj8ePlY7n2EiIiIi6rUzgVsb6932+Q0Wr6P+xW5paSl++ctfaiA0Y8YMFBUV4dZbb8UjjzxyxCHQm2++iQsuuADvv/8+Nm3ahHvuuUeP33DDDSguLsZll12Gs846Sz9HXV0dnnzySfzkJz/Bp59+qoGXePfdd/Hoo48iLS3NFUz1Vuxnoh7LYLbAnjxKV+hpN8Cxd6fupieDzJtkhlTGKl0wGGGLGwx72gRt1zP7h7j71omOipfZihkJE3XllO3RIGrp7tXYW1mI/65/B29s+hCTY8dgbvI0JAXH8dklIiIiol4VPhW8cifq9+502z14RQ9A5FV/PaoQSgKihoYGREZGIioqStezzz6L5uZmVFRUHNFjSCWYhE7yeZOSkrTi6ZVXXtEqKAmnwsPD8ac//cl1/T//+U9MmDABX375Jc4//3w9NnDgQA2pPAEDKOoVDEYTbLGDdAXPuRoNxbltbXoZ6WjYt1srpWSVfPUCvCJT2iqj0sbDGhLp7lsnOioJQTG4YezluGLE+Viauwrzs5ZgT0UBFues0JUYFKtDyyfFjoG3mW2oRERERNQb9L6xEhL8nHnmmbjxxhu18mjy5MlaCTV37lysXbv2iB5DWuo6hl4jR47ECy+8gLKyMmzbtg27du3SYx3V19drUOUUF+c5v4BmAEW9jvwH7BWeoCt4+iVoLC3UFj0JpOr3ZqC+YJeu0q9fgyU0WsMoWdbwRM7ToV7DbrHhlJTpGjbtPJCtQ8u/27MO2WW78ezq1/DyhvcwPW4C5iZPRUwAg1YiIiIi6rn/fpPqo97Wgif+/ve/46abbsKSJUuwYsUK/OEPf8Do0aPxi1/84nvXSmXUoczmzpFLS0uLvjWZTPq+VDvdfffd3/s4P7+DI2Y8YZaWEwMo6vUswREInHCOrqaqMm3Lq8lIR13uFjQe2ItyWcv/B7N/KOxp4zSM8o4ZqFVVRD2d/EU5oF+Srp+OvAjf5Hyng8uLq/fjy8xvdA3sl6KzosZHj4DFZHH3LRMRERERfe9nWoO1dwUpGzduxGeffYY//vGPSExMxNVXX42PP/5YQyiZDSWqq6td1+fm5n7vMTZv3tzpz+vWrdMB5TKQPCUlBZ9//jkiIiJgtVr1fHl5OW677TZcc801Gk55GgZQ5FHMfkHwH32KrmZHDWoz1+rcqNqs9WiqPIDK1Z/rMtr94ZMyRtv0bAnDYDS3/QdP1JP5e/ni7AFzcWbabGwp3qnteWvyN2H7/l265PzMhEmYkzQF/X1794BCIiIiIiJ38vX1xRtvvAGLxYKLL75YW+MkMJJd6WR3OxkS/vzzz+Pmm29GXl4e/vvf/37vMWR3uyeeeEKHlq9Zswavv/667qInZAD522+/jVtuucVVUfXwww9j586dSE1NhSdiAEUey+TtA78h03S1NNajLmdT29yoXat1R72qjYt1SRJvTxrZNjcqaRSM3j7uvnWiwzIajBgWPlBXaW05Fucsx8KsZSitK8dHO+brGh4+SNv3RkUMgYnVfkRERERER0WGhsuudE899ZQGUUajUauSZIaTtMjJznR/+9vfcPrpp2sgJZVL0q7X0ezZs3WekwRQYWFhGj5deumlei4mJgavvfaatvnJMWnLGzVqlA4pDw4O9shXy9AqI+n7MPmGEIsWLXL3rdBJ0trSDMfubRpGyY56zVUlB08azbDFD4VP2jjYU8fB7BvI14V6heaWZqwr3KI76G0s2o5WtP2vPcQWhNlJkzErYTKC7fx+JiIiIqITx+FwICcnR3d/86TZRcfiyiuv1J3zHnroIXjyazr7KDIVVkBR39xRL36orpB516G+MEvb9CSQaizJR132el344nl4xwxwzY2yBPZ3960T/SCpchobNVyXzIeSiijZNa+krgzvbPkU7239HGMih2lV1JD+aVpFRUREREREdLIwgCL09WF43pHJuoJnXo6GA3u1KkoCqfrCTDj2bNdVuvBlWMPi29r00sbBGhbHHfWox5L5T5cPPw8XDzkT6Xs36NBymRG1Kn+DrnDffpiTNBUzEibq3CgiIiIiIqITjS14bMGjHyBDyyWMqslYBUfeVundc50zB/bXMEqWV3QqDKwmoR5uT0WBBlHf5q5EXaNDj1mMZkyIGYW5SdOQFprIUJWIiIiIjgtb8DyPoxtb8HpUAPXcc89h2bJlePXVV3/wml27dumwL9kSUYaAjR07FrfffjsiIyOP6XMygKIj0VxbpcPLJZCqy9mI1qYG1zmTTyDsqWM1jLLFD4HBZOGTSj2Wo6keK3avwfzMJcgu2+06HhsQhblJUzE1fhzsFptb75GIiIiIeicGUJ7H4YkBlGxH+Ne//hVjxoz5wQCqrKwMZ511lk6G/+Uvf4mGhgYd6FVaWooPPvgAXl5eR/15GUDR0WppcKA2ez1qpVVv1xq01Ne6zhm97LAnj4Zdd9QbAaOV/5CnniurNE+Hli/bvRoNzY16zMvshamxYzE3eRoSgmLcfYtERERE1IswgPI8Dk8aQl5cXIy7774b6enpiI+PP+y1CxcuRG1tLR555BHXFy7VUDNmzMC6deswceLEk3TX1JcZrd7wHTBRV2tzI+rytuoAcwmkmmvKUb11qS6phLIlDm+bG5UyBia7v7tvnaiTpOA4JI27EleOuABLctMxP2sJ8iuLsDB7ma6U4HgNoibGjIaX2cpnj4iIiIiIjpnbA6itW7fCYrHg448/xtNPP438/PwfvFYCpmeeeaZT6iZteKKysvKk3C9RRxIy2RNH6Go99Weoz8/QMEpa9ZrKirRCShYMRnjHDnTNjTL7h/KJpB7Dx2rHaakzcWrKDGzfn4kFWUuwcu967CrNxa5VuXh5/buYnjBRW/Si/MPdfbtERERERNQLuT2AmjVrlq4jER0drauj559/XgMpmQVF5E4yiNw7eoCu4FlXoXH/blcY1VCco4PMZZXM/w+8IpK0TU/CKGto5+9pInfuCjkoLEXX1Y5KfJ3zHRZmLcW+mhJ8nrFY1+CwVB1aPi5qOMwmt/8VQkREREREvUSv/teDzIp67bXX8Kc//QnBwcE/eJ2zJ7ErhYWFiIiIOEF3SH35H/LWsDhdQVMvRmN5sQZRtTvT4dizA/WFWbrKvnkDlpDItja91PHwikzijnrUIwR4++Pcgafg7AFzsalouw4tX1u4GVv3ZeiS87MSJmF20hSE+YS4+3aJiIiIiKiH65UBlMxNf/zxx/Gvf/0L//d//4crr7zS3bdEdFiWwP4IHH+Wrqbq8vYd9dJRl7sZjSUFKF/xgS6TXzB8UsdpIOUdOwgGVpiQmxkNRoyIGKzrQG0pFmcvx6Ks5ShzVOCD7V/iw+1fYWTEYJ0VNTJ8sKstmoiIiIiIqFcHUI2Njbjjjjvw6aef6turr776Rz/mcNPYD1cdRXQimH0D4T9yri7ZQa82c13bEPOsdWiuKkXl2i91Gb19dXi5T9o42BJHwGg5+l0eibpTqD0YFw85C+cPOh1rCzZhQeZSbCrejnWFW3TJ+TlJU7QyKtAWwCefiIiIiHqtgoICrF+/HmeccQY8TVlZmW7ydtFFF53Uz9vrAqhbb70VCxYswN///neP/EagvsXoZYfv4Cm6Wpoa4MjZ3DY3atdqtNRWonrzN7oMFi8NoVw76nn7uPvWqQ8zG00YHz1SV2HVPp0TJfOipELqrc0f490tn2Js9AjMS5qKwWFp2pJKRERERNSb3HbbbYiKivLI3OGRRx7B3r17GUB11NzcjNLSUvj5+emg8ffffx+ff/65hlDjxo3D/v37Xdc6ryHqrYxmK+wpo3WFtjTDsXdH29yoHSvRVHlA50fJgtEEW9wQrYySuVFmvyB33zr1YRF+YbhyxAX4ydCzsXLPOizIXIKdJdn6viw5L0PLZ8RPgK8Xg1MiIiIiop4w1sgdDK3u+sxduP3225Gfn6/DxYUkctIi9+CDD+L888/Htddei+XLl3f5sc5rjpazBe9wbXpE7iT/iTYU5bRVRmWko3H/nk7nvaJStTJKAilLcKTb7pPIKa98LxZkLcXS3FWoa3LoMYvJgkkxozE3aSpSQhJYFUVERETkgRwOB3JycpCQkNCrC0RkzvSqVav0famCEqeccgq+/fZblJSU4Mknn0RaWhoeffRRPSaFM/7+/pov3HnnnbDZbEhPT8c111yjs6vlutzcXERHR+OWW27BnDlz9DHl2F/+8hds2LABLS0tGDVqlBbcyGMLeXvXXXfho48+wvbt2xEfH4+bb7650yihb775Bs888wx27doFHx8frdj67W9/63r+5TFuuukmfPDBBzrSaPz48TrSyGnnzp3H9ZoeTabSowIod2AARb1NY2mBVkZJIFWfn9HpnKVfrAZREkhZ+/Mf+eRedY0OLN+9WnfQyy3f6zoeHxitVVFT4sbCZum9P5gQERER0ZGFFRI71Dc3uO3p8jJZj+oXoOXl5bjxxhsRHh6uAdCFF16oHVjPPfecdl9JqPOb3/wGxcXFuPvuuxESEoJ169bhj3/8owZMMqtaAqirrroKKSkpGkpFRETgscce06KaJUuWaFgkRTQDBgzADTfcgKamJjz88MMaSsnYISGfx26362NOnDhRu8JefPFFvP766xpWyXW//vWv8atf/QqnnXYasrOzcc8992Do0KEaSjkfIygoCC+88IJ2mSUlJeHPf/4zioqKNEjr16/fSQuget0MKKK+TqqcAieeq6upqhS1GW1hVF3eVjTu341yWcvegzkgDHYNo8bBO3oADEaTu2+d+hgJl+YkTcXsxCnILM3VoeXL96zRMOqFtW/gtY3vY2rcOMxNnoq4wGh33y4RERERnQASPt216G86psFd0kKTcN+s3x9xCBUYGAiLxaKBS3BwsB6bPn06Jk2a5Lpm8uTJGDt2rKtaSaqbXnvtNWRkdC4SkIolCY/EL37xC3z11Vd6zciRI7F79259TKmyks/3wAMPaIgk1VDO3aUlpLr88sv1fQmipDJLPo8EUM8//zzmzp2rjyskJJLnWyqeMjMzkZycrMfPOeccDaWc5OuSz/dj4VN3YwBF1IuZ/YLhP/pUXc111ajNXKPVUXVZ69FUsQ+Vqz7VZbT7wydlrFZG2RKGwWC2uPvWqQ+Rv+il7U7WVSMuwLe5K7VFr6CqGPOzluhKC0nE3ORpmBAzClYTvz+JiIiIPIoHbEoTFxfX6c+XXXYZFi9erK1tUrUkgY+MEUpMTOx0Xcc/+/r66ltphRPSKieh0xtvvKFzrqdOnYozzzzTFT4JaZnrSIIr52giCbIOHZIuj+M85wygDr13d2EAReQhTDZf+A2doaulsR512RvahpjvWqM76lVtXKTLYPWGPWkUfAZMgD1ppO7ER3SyyCDyM9Jm4/TUWdi6L0PDp9V7N+hvxGS9tP5dzEiYqLOiZIA5EREREfX+X0ZK9VFvasHrSsf2M6lQ+vnPf65zlyQwOv300zF48GBtbTuU1Wr93rHW9klIUtl06qmn6hyp7777Dk888YTOjPrwww8RGhqq15jNnWMbaaNzBlRdTVSSezv043rKPC4GUEQeyGjxah9MPh6tzU1w7N7WPsR8FZqrSlGzfYUumMywxQ9ruzZ1LEw+Ae6+deoj5AeAIf3TdJXXVWBxzgoszFqGA7Wl+HTnQl1D+w/QIGpM1HCY2UJKRERE1Kt/9vM2e8FTyEBwmeP0zjvvYPjw4a6qJmmpi4mJOaLHKCkpwdNPP63zn6TNTpbMlJo2bZq22UmoJTZv3oxZs2a5Pm79+vUadglp/5PZUzJzymnNmjX6VmY9/ZDjDeOOFQMoIg9nkJApYZiukFOuQ31BFmp2rkTtzlU60Lwua52uA188B+/oNNjbgytLIKtP6OQItAXg/EGn4dwBp2BD0VbMz1qK9QVbsLl4h64g7wDMSpyM2UmTEWpv68EnIiIiIjqRZEh4fn6+Dus+lFQnSYXRF198oTOiZGj5s88+q4PKGxqOrNIrICBAd7CT0Or3v/+9tufJkHGZzTRkyBDXdS+//LK28ckxCbxk17r7779fz11//fU6DF0GjssQcueuejNnzjxsACWDzfft24c9e/YccWDWHRhAEfUhBoMR3lEpuoJnXoHGA3vbKqN2rkJDURYce7brKl34ku6i56yisvSLcVtKTn2HlBKPihyqa39NCRZlL8Oi7BUoc1Tgf9s+x/vbv8DoiKE6tHx4+CAYDQd744mIiIiIutMll1yC2267DWeffTZsNlunc/3798dDDz2ku8jJjnQyzHvGjBlaiSRzoY6E2WzWnelk5zv5uLq6OgwcOFAHi8fGxna6j5deeklnOsmOebILnrwVp5xyiu6sJ217EkJJGCYtgbIz3uGce+65uoOeXDt//nz9ek4GQ2tXTYN9yNFsGUjkyZoq9muLngRSjt3bgda23mFhDgp3hVFeUSkaZBGdlO/L5iasLtiI+ZlLdGaUUz+fEG3Pm5kwEQHe/nwxiIiIiHoAh8OBnJwc3Y2tp8wd6s3S0tLw4IMPanteT31NjyZTYQUUEbX9zyCgHwLGnqGruaYCNbvWoHZnOupyNqGprAgVKz/SZfINgj21fUe9uMEwcMcyOoHMJjMmxozWlV9ZpHOivsn9Tiuk3tj0Id7e8gnGR4/EvKSpGNhPwlFW6hERERER9UQMoIjoe2QYuf+I2bpa6utQm71eK6NqM9ehuboMVevm65Id9OwpY2BPGwd74kgYrfwtB504Uf7h+OnIC3Hp0LOxYs9aLMhcgl2luVixe40uOS9VUdPjJ8DHyt0diYiIiIh6ErbgsQWP6Ii1NjWiLm9LWxiVsRrNNeUH/2ditsKWOFwroySUMtn8+MzSCZdTtkeDqKW7V6O+qV6PWU0WTI4dq2FUckg8XwUiIiKik4QteJ7H0Y0teAygGEARHZPWlmbU5+9qH2K+Ek3l+zr8n8UI77jB8Ekdp4GU2T+EzzKdULWNdViauwrzs5ZgT0WB63hiUKwGUZPjxnrU1r9EREREPREDKM/jYADVfRhAER0/2cugYV9eW2XUznR9vyOviGTYdYj5OFhDo/mU0wn9Xswoydah5Sv3rENjS5Met1m8MT1ugu6gFxMQyVeAiIiI6ARgAOV5HAygug8DKKLu11hWhJqdbTvq1e/dKbGA65wlNNpVGWWNSOLQaDphKuur8W3OSizIWoKi6v2u4wP7JWtVlAwvt3CIPhEREVG3YQDleRzcBY+IejJLUDgCJ5ytq6m6TOdFSSBVl7sZjQf2olzWivdh8g9tD6PGwTt2EAxGk7tvnTyIv5cvzhowB2ekzcKW4p3anrcmfxO278/U5ef1LmYmTMLcpCno79vP3bdLREREROTRuAseEZ3Y/8n4BsF/1DxdLY4a3UlPW/Wy1qO58gAq13yuy2jz0+HlUhllSxgGo4Xzeqh7GA1GDAsfqKu0rhyLs5djUdZylNSV4eMd83UNDx+kVVGjI4fCxCCUiIiIiKjbMYAiopPG6O0D3yFTdbU01qMuZ5NWRtXuWo2WuipUb/pal8HiDXvSCJ0bZU8eDZO3D18l6hbBtkBcOPgMnDfwVKwv3KKzojYWbcfGom265PzsxMmYnTgFwfZAPutERERERN2EARQRuYVUOPmkjtUlO+o59mxv31FvlVZG1exYqQtGM2zxQ7Qyyp46ViuqiI6XVDmNiRquq7h6PxZmLcPXOSu0QurdrZ/hf9u+wJjIYTq0fGj/AVpFRUREREREx87QKlsG9WEcQk7UA3fUK8xqC6MyVunMqIMM8IpO1TBKlsyaIuoujc2NSN+7AQuylmL7/l2u4zIfSuZEzUiYpHOliIiIiKhvDyFPT0/HVVddhUWLFiE6Otqj78PBIeRE5KkMBgO8IpN1Bc+8HA0l+ahtr4yqL9ilu+rJKl30CqxhsbCntoVR1v7x3FGPjovsiDclbqyuvRWFOrR8SW66Vki9tvEDvLX5E0yIGYV5SVORFsodHImIiIjIvUaOHIlly5YhODi4V7wUbMEjoh7NGhIF66TzETjpfDRVlmhVlARSdXlb0bBvt67yZe/CHBjmqozyikrljnp0XKIDInDtqJ/gsmHnYsXuNViQuRRZZXlYlrdKV0xApA4tnxY/HnaLjc82EREREZ10VqsV/fr1nt2cGUARUa9h9g9BwJjTdDXXVaF211pt1avL3oCm8n2oSP9El8knAPaUsW076sUPhcFscfetUy/lbfbCrMTJurJK87AgcwmW7V6NPRUF+M+6t/H6pg8xJXashlGJwbHuvl0iIiKiHjtmo6W+3m2f3+jldUzdEt9++y0ef/xxZGVlwW63Y/r06bjjjjs6nX/zzTeRm5uLuLg4/OEPf8CMGTP0XHNzM1599VU9X1BQgMjISFx99dW49NJLO7XPPfnkk3jkkUdw4MABjBgxAn/+85+RlJSk11x55ZUYMGAASkpKtM0uICAAV1xxBX72s5/p13NoC96sWbNw+eWXY8OGDVoZJQHVWWedhdtvvx1mc1v8I8f//ve/IzMzU+/5mmuuwR//+MeT0k7IAIqIeiWTzQ9+w2boamlwaAglYVRt5lo011SgasNCXQYvO+xJI9uGmCeNgtGL1Sp0bJKC45A07kpcOeICbc2TWVF7KwuxKHuZruTgeA2iJsWOgZfZyqeZiIiIqD182nz7najasdNtz4ffwAEY+uBfjyqEKi0txS9/+UsNbyRUKioqwq233qph0dlnn63XvPLKK7jvvvsQFhaGv/3tb7j55puxfPly+Pj44KGHHsJHH32kgdLQoUOxZMkS3H///aivr9cgykmuu/vuuxEeHo5HH31UA6Uvv/wSfn5+el4CrAsuuADvv/8+Nm3ahHvuuUeP33DDDV3etwRmt9xyi97rqlWrcOedd2LIkCE499xzsX37dvz85z/HT3/6Uw2h5M/33nsvThYGUETU6xmt3vAZMEFXa3OTtufp3KiMVWiuLkPNtuW6DCYLbAnDYJdWvdSxMNn93X3r1Av5WO04LXUmTk2ZgR0HMjE/cwlW7l2PzNJcXa9seA/T4ydgbvI0RPlzUD4RERERjqH6yN2Ki4vR0NCglUtRUVG6nn32Wa1sqqio0Gukcmj8+PH6/k033YSFCxdqtVRiYqIGRxJeSQWSiI+Px969e/H8889rAOR02223aWWVkBBLwq7PPvsMl1xyiR6Tge4SOkl4JpVR8vgSfEkVVFemTJmiIZaIiYnRKqx169ZpAPXSSy9pGCXhlJD7lOoqCcZOBgZQRORRDCYz7InDdYWcej3qCzLbdtTbsRJNZUVaISXrwOdGeMcMhE/aONjTxsESEObuW6deRn4IGNgvRdfVjkp8nfMdFmYtxb6aEny+62tdg8NStSpqXNQImE38K5eIiIj65s9MUn3U21rwBg4ciDPPPBM33nijzlmaPHmyhkNz587F2rVrXeGQk7+/v2vXuOzsbDQ2NmL06NGdHnPcuHF4+eWXNfRxcgZYIjAwUB8zIyOj0/mO9y6Dx1944QWUlZV1ed/O9j0nqaSSexHbtm3DpEmTOp0fO3YsThb+NExEHstgMMI7KlVX8Mwr0Lh/T1sYtTMdDcU5cOzeqqtkwX9hDU9sH2I+DpbQGO6oR0clwNsf5w48BWcPmItNRTt0B721BZuwdV+GrgAvP8xMnIQ5SVMR5hPCZ5eIiIj6FAlQTN7e6G2kTU0qm6R9bsWKFTrjSUKlX/ziF3reaDR22XIoqystLS361jmP6dD3hVRYdXzcQ887H8NkMnX5OWTuU1f35PwY58e7AwMoIuozf+lZw2J1BU29CI3l+1CbsUrDKMeeHWgoytZV9u2bsARHtLXpyY56kckaZBEdCaPBiBERg3SV1Ja1zYfKWo4yRwU+3P4VPto+HyMiBmNe8jSMDB/c5Q8tREREROR+Gzdu1FY4abOTVjWZ2/Txxx9rCPWTn/zksB8rVUgWi0UrpaSSymnNmjVaTSXDxJ02b96MiRMnuuZO5eXl6WDwjuc7knY6GRbe8TGOlAw0lzlSHa1fvx4nCwMoIuqTLIFhCBh3pi4ZWl6zazVqd65Cbc5GNJYWouK7D3WZfINdbXq22MHa4kd0JELsQbh4yFk4f9DpWg21IHMpNhVvx/rCLbrk/JzEKbrDXpDt6H+AICIiIqITx9fXF2+88YYGSRdffLEOD//88891llNQUNCPfqyEVE888YS21ckQ8mXLlunj/e53v+vUbSFDwP/yl79oq9zDDz+sAdWpp57aKbSSx5HB5/L+66+/3mknvqNx7bXX6iwomTUlg81lJzx5bHEsuwQeLf5Lioj6PJNPAPxHzNHVUl+H2qx17TvqrUNzdSkq136py+jtC3vKaPikjoctaQSMFq8+/9zREfxFazRhfPRIXUVV+3T3vG9yvtMKqbe3fIL3tn6GsVEjMC95KgaHpbH9k4iIiKgHkCqmJ598Ek899ZQGR1K5PmHCBJ2/VFhY+KMfLyGRBFUS9hw4cECDq7vuukvDrI4kqJKh4OXl5fr4MmDcZju4c/fs2bN18LgEULLbnjzupZdeekxfU2pqqn49jz32mA4kl3lTV1xxhX6dErSdaIbWH2pO7CPkxRSLFi1y960QUQ/T2tSIutxNqNm5SnfUa6mtdJ0zmK2wJY6Az4DxsCePgcnm69Z7pd6lobkRK/es0zBq54Es1/EIvzAdWj4jfiJ8vXzceo9ERERER0sGcOfk5Giw4d0LZz6dTOnp6bpbnWQR0lLXlSuvvFJ333vooYe65XNK+53MlBo0aJDr2CeffKJthtKKd+i8qSN5TY8mU2EFFBHRDzCYLbAnj9YVetoNcOzdiVodYr4KTRVtM6RkwWiCLW4w7KltQ8zNfsF8TumwrCYLpsWP15VXvleDqKW5q1BYtQ+vbPgf3tz0ESbGjsa8pGlICUlgVRQRERERHbft27fj0Ucf1VY/mU0l86ak+umMM87oMnzqbgygiIiOgEFCpthBuoLnXI2G4lzU7FypYVTj/t2oy9mkq+SrF+AVmaIDzGWQuTUkks8vHVZcYDSuH30prhh2HpbtXo35mUuQW74XS3LTdcl5qYqaGjcONgt/k0hEREREx0ba//bv348HHngAxcXFCAkJ0fDp17/+NU4GtuCxBY+IjpMMLZeZURJG1efv7HTOEhqtYZQsa3giK1noR0lnfGZprg4tX75nDRqbG/W4t9lLQyjZQU9CKSIiIqKehi14nsfRjS14DKAYQBFRN2qqKtO2vJqMdNTlbgFaml3nzP6hWhUlYZR3zACtqiI6nOqGGnybs1Jb9Aqqil3HU0MStSpqYswoWM1WPolERETUIzCA8jwOBlDdhwEUEZ0ozXXVqM1cq9VRddkb0NpY7zpntPvDJ2WMBlK2hGEwMkSgH6mK2rovQ4OoVXvXo7m1RY/7Wn0wI34C5iZP0wHmRERERO7EAMrzODiEnIio55Od8fyGTtfV0liPuuyNWhlVu2uN7qhXtXGxLoPVG/akkW1zo5JHw+hld/etUw9jMBgwpH+arvK6CizOWYFFWcuwv7YUn2Ys0jW0fxrmJk3DmKjhMLO6joiIiIh6GA4hJyI6CYwWL90hT1ZrSzMcu7e55kY1V5WgZvt3umA0w5YwtC2MShkLs28gXx/qJNAWgPMHnYZzB5yCDUVbMT9rKdYXbMHm4p26Ar39MStxMuYkTkGoD3dkJCIiIqKegQEUEZE7dtSLH6orZN51qC/MQq2GUeloLMlHXdZ6XcBzOivKrsHVeFgC+/O1Ihej0YhRkUN17a8pwaLsZViUvQLljkq8v+0LfLD9S4yKGKJDy4f3H6TXExERERG5C4eQcwg5EfUgDQf2ahAlgZQEUx1Zw+LbKqPSxsEaFscd9eh7mpqbsLpgo+6gt2XfwR0Z+/mEaEXUzMRJWiFFREREdCJwBpTncXAGFBGRZ7KGRusKmnwBmioPaIueBFLSstewL1dX2dK3YQ7sr2GULK/oVBgMrG4hwGwyY2LMaF0FlUVYkLUM3+R+pxVSb27+CO9s/RTjo0ZoVdTAfikMMYmIiIh+QFpaGh588EGcf/75x/wcFRQUYP369TjjjDOO6Pr3338fd9xxB3buPPiLRE/CFjwioh7K7B+KgLGn62qurULtrtUaSNXlbERTeTEq0j/WZfIJhD21bb6ULX4IDCaLu2+deoBI/3D8dOSFuHTo2VixZ63uoLerJEfflxXlF465yVMxPX4CfKwcfE9ERETU3W677TZERUUdcQDl6RhAERH1Aia7H/yGz9LV0lCH2qwNbXOjMteiuaYcVevn65Id9GQnPbu06iWNgNFqc/etk5tZzVbMSJioK6dsjwZRS/NWIb+qCC+tfxdvbPoQk2LHYF7SNCQFs7WTiIiIiE4MBlBERL2MhEq+Ayfqam1uRF3uFq2Mqs1YpWFU9dalugxmK2wJw9p31BsDk52zf/q6hKAY3DDmMlwx/Dwsy1uF+ZlLsbsiH9/kfKdLzs9NmoYpcWPhbfZy9+0SERERuVVOTg6uvvpqrF27FoGBgbjiiivw85//3HX+m2++wTPPPINdu3bBx8dHK51++9vfwtvbG1deeSVWrVql18nbxYsXo6GhAY8//jg+/vhjVFdXIyUlBb/+9a8xZcoU9AUMoIiIejFpt7MnjdTVetrPUJ+foTOjJJBqKitC7a41umAwwjt2UPvcqHHa3kd9l91iw7zk6Ro2ZZRk69Dy7/as1Qqp59e8jlc3/g/T4sZjbtJUxAZGuft2iYiIqJdrbW1FY0Oz2z6/xWo6ptmXr732Gu6++2785S9/wSeffILHHnsMw4YNw8SJE7FgwQINj371q1/h4YcfRnZ2Nu655x7s2bNHQ6knn3wSN954I8LDw3HXXXfp48l8p6ysLPztb39D//798fXXX+s1Tz31FGbMmAFPxwCKiMhDyCBy7+gBuoJnXYXG/btdYVRDcQ4ceVt0lcx/EV4RSdqmJ4GUDD2nvkl+EEsLTdJ11cgL8W3OSizIWoKi6v34KvNbXQNCk3Ro+fjokbBwvhgREREdQ/j036dWYG9umdueu5j4IFz9y0lHHUJddtllOPfcc/X9X/ziF/jPf/6DLVu2aAD1/PPPY+7cuXpcJCQk6Nd60003ITMzE8nJybBYLFoNFRwcjLy8PHz66af48MMPMXDgQP2Ya665Bjt27MCLL77IAIqIiHon+cvVGhanK2jqxWgsL9YwqnbnKjj27EB9YZausm/egCUksq1NL3U8vCKTuTNaH+Xv5YuzBszBGWmzsKV4p86KWp2/ETsOZOny83oXMxMmYk7SVIT79nP37RIREVEvcvS1Rz1DfHx8pz/7+/ujvr5e38/IyPjecPFx48a5zkkA1dG2bdtcoVZHjY2N+rh9ASugiIj6AEtgfwSOP1tXU3V5+4566ajL2YzGkgKUr/hAl8kvGD6yo96ACdqyZzCa3H3rdJIZDUYMCx+oq7SuHIuzV2BR1jKU1JXh4x0LdA0PH6jte6Mjh8LE7xEiIiL6kV+MSvVRb2zBM5m+/7OwVDl1fNtRS0uLvjWbvx+1tLZf//rrr+u8qI6MRiP6AgZQRER9jNk3EP4j5+pqqa9Fbea6tuqorHVoripF5dovdRltvjq83Cd1PGyJw2G0cCh1XxNsC8SFg0/HeQNPwfrCLVoVtaFwGzYWbdcl52cnTsbsxCkItge6+3aJiIioJ1fne3lW/JCWloZ169bpkHKnNWvW6NukpKTvXZ+SkqJv9+/fj0GDBrmO/+Mf/9AA6je/+Q08nWd9BxAR0VExetnhO3iKrpamBtTlbEKtzI3atQYttZWo3vSNLoPFC7bEEQd31PPu/Fsb8mxS5TQmariu4ur9WJS9HIuzl2uF1LtbP8P/tn2h1VAyK2po/wFaRUVERETkya6//noNjWTg+GmnnYbc3FwdVj5z5kxXACWVTvn5+SgqKtIASs7JUHMZSi5//vLLL/Hcc8/hwQcfRF/AAIqIiJTRbIWPVDyljEFoS7POimqbG5WOpsoD+lYWjCbY4obobnoyN8rsF8RnsA/p79sPlw07FxcNPgOr8jfoDnrb9u/SeVGy+vuE6pwomRfl7+3n7tslIiIiOiFOOeUU3RXvX//6l4ZQMmj8zDPP1J3xnC655BLcdtttOPvss/Hdd99ptZMsCaAqKioQGxuL+++/H+edd16feJUMrV01LvYhs2fP1reLFi1y960QEfVI8tdEQ1FO+456K9F4YG+HswZ4RaVqGCXVUZbgCDfeKbnL3opCbc/7Nnclahvr9JjZaMaE6JFaFSW77B3L3AUiIiLqXRwOB3JycnRHONn9jTz/NZ19FJkKAygGUERER6WhpKCtTW9nOuoLdnU6Z+kX6wqjrP0TGDr0MY6meqzYvRYLMpcgqyzPdTwmIBJzk6ZiWtx42K02t94jERERnTgMoDyPgwFU92EARUR07JoqS1CTsRq1Gemoy9sKtBzc3cQcEAZ7exjlHZ3GHfX6mKzSPK2KWp63GvXNDXrMy2TF5LixmJc0DYnBse6+RSIiIupmDKA8DwOobsQAioioezTXVaM2cw1qdq5CXdZ6tDa1hQ7CaPeHT6qEUeNgix8Gg9nCp72PqGmoxdK8VZifuQR7Kwtdx5OC4zSImhQ7Bl5mq1vvkYiIiLoHAyjP42AFVPdhAEVE1P1aGutRl72hbYi57KjnqHGdM1htsCePattRL2kUjF5syeors8R2HMjUIGrl3vVobq+Ws1tsmB4/AXOTpyLanzPEiIiIejMGUJ7H0Y0BVI/aBU+2H1y2bBleffXVH7ymrKwMf/3rX7FkyRKdLXLGGWfg1ltvhc3Gf8AQEfUURouXBkyyWpubULd7K2p3rtLqqObqUtRsW64LJrNWROm1qWNh8glw963TCSJ/Zw/sl6LrakclvslZiYVZS1FccwBf7Ppa16B+KTq0fFzUCJhNPepHFCIiIiI6Tj3mp7vXX38d//znPzFmzJjDXidbGtbV1eGll15CZWUl7rzzTtTW1uLhhx8+afdKRERHzmAyw54wXFfIKdehviCzrTJq5yo0lhagLmudrgNfPKezonwGTIA9dRwsgWF8mj1UgLc/zhk4D2cNmINNRTuwIGsJ1hRswrb9u3QFePlhZuIkzEmcgjDfUHffLhERERF5QgBVXFyMu+++G+np6YiPjz/stevXr8eqVavw+eefIykpSY/dd999uP766/G73/0O/fv3P0l3TUREx8JgMMI7KlVX8Mwr0Hhgr4ZRshqKsuHYs11XyYL/6i56zioqS78Y7qjngYwGI0ZEDNJVUluGRdnLsSh7GcrqKvDh9q/w0fb5em5u0jSMihgCo9Ho7lsmIiIiot4aQG3duhUWiwUff/wxnn76aeTn5//gtWvWrEG/fv1c4ZMYN26c/qNk7dq1OP3000/SXRMR0fGS/3db+8XoCppyIRor9rna9CSEaijO0VW25C2Yg8JdYZRXVIoGWeRZQuxBuHjImTh/0GlYV7BZZ0VtKt6O9YVbdcl5qYialTgZQTa2ahIRERH1Nm4PoGbNmqXrSKulIiI6Dyi1Wq0IDAxEYeHBnXV+aChWV+TjDn1MIiI6+SwBYQgYd6au5poK1Oxag9qd6ajL2YSmsiJUrPxIl8k3SHfUs6eNhy1usLb4kecwG00YFz1CV1HVPizMXoavs1dohdTbWz7Be1s/w9ioETq0fHBYqlZREREREVHP16t+apfZTxI4HcrLywv19fVuuSciIup+Mozcf8RsXS31dajNXt82NypzHZqry1C57itdRm8f2JNHa2WULXEEjNbv78xBvVe4XxiuGH4+Lh5yFtL3rMf8rCXYeSALK/eu0xXhG6ZBlOyi5+fl6+7bJSIiIiJPCaBky7+GhobvHZfwyW63/+DHHW47wMNVRxERkfsZvWzwHThJV2tTI+pyN7eFUbtWa6VU9ZYlugxmK2yJwzWMsqeMgcnm5+5bp25iNVkwNX6crt3l+ViQtRRLctNRWL0Pr2z4H97c9BEmxozWHfRSQhI4L4yIiIjcTjq9zjvvPPzqV79y9630GL0qgAoPD8fChQs7HZNAqry8HGFh3C2JiMjTGcwW2JNH6WptuQH1+RmuIeZN5ftQm7FaF2TYedxgbdWTQMrsH+LuW6duEhsYhetGX4LLh52LZbvXYEHmEuSU78GSvHRdcYHRmJs0FVPjxsFmYUUcERERucd7772n3VrUSwOosWPH4m9/+xvy8vIQFxenx2RXPDF69Gg33x0REZ1MBqMJ3jEDdQXP/ika9uW1VUbJjnr78uDI3ayrZP6L8IpMgU9a29woa0gUXygP4G3xxpykKZidOBlZpXk6tHz5njXIK9+Lf699E69tfB9T4sZhXtI0xAdFu/t2iYiIqI8JDg529y30OD06gGpubkZpaSn8/Py0/W748OEYNWoUfvvb3+Kee+5BbW0t7rrrLpx77rno37+/u2+XiIjcuKOeV/94XcHTfoLGsiJXZVT93gzUF+zSVfr167CERrsqo6wRSWzX8oDXPjkkXtdVIy/Q1rwFmUuRX1WEhVlLdUlbngRRE2NGwWr+/ixJIiIioq5kZGTg73//O9atW6czqSV3uPzyyzF37lxdzz33HKZPn+66/o477kBubi7efPPNTi14LS0teOGFF/D+++8jPz9fZ1tLtiF5RmxsbJ958nt0ACU71MmMpgcffBDnn3++/pD51FNP4d5778VPf/pTLWc79dRT9UUmIiJysgSFI3DCObqaqsu0LU/CqLrcLWg8sBflsla8D5N/aHsYNQ7esYO0qop6L1+rD05PnYXTUmZi2/5d2p6Xnr8Bu0pydL284T3MiJ+AOclTEenHX1wRERGdLK2trWhq/P4855PFbLEe9S8dJXC69tprMXnyZLz11lswmUx499138fDDD2PixInaofXpp5+6AiiZTT1//nzcfvvt33usV155BS+++KJ+bGpqKnbv3o0///nPeOihh/DMM8+grzC0yndCH+YcQn64QeVEROQZmh01qMtc19aql7UerY0O1zmjzQ/2lLEaRskwcyMrZTxCuaMSX2ev0Eqo/bWlruNDwtJ0aPmYqOEwM3gkIiLqFg6HAzk5OUhISNAuJiGRw/+eewBFeZlue5Yj4lJw/s/vOKoQSrqxZI6TVDz5+Pi4QqZhw4ZpkCRf13333YcVK1bAZrPhiy++0OKYZcuWwdfXt1MF1OLFi/Vzz5w50/X4Ml7oyy+//N6c697wmh5rptKjK6CIiIi6k8nbB75DpupqaaxHXc6m9h311qClrgrVmxbrMli8YU8a2bajXvIoGL3bfuig3ifQ2x/nDToV5wyYhw1F2zA/awnWF2zBln07dcn5WYmTMSdxCkJ9OKuBiIjoRDDg6KqPesoMp8suu0yrnLZt26ZVSzt27NBz0lIn3VgSQEnwcuaZZ+Ljjz/GnDlzNHw6lIRRGzduxOOPP65hjqzMzMw+N0qIARQREfVJRosXfFLH6mptaYZj9zbU7FyFmoxVaK48gJod3+mC0Qxb/JC2MCp1LMy+Qe6+dToGRqMRoyKH6NpfU4JF2cuwKHuFVki9v+0LfLD9S4yKGIK5SdMwInyQXk9ERETHTyp/pPqot7Xg7d+/Hz/5yU80iJIAacqUKRg6dKir5c5ut2sI9cknn+i5pUuX4vnnn+/yseT4008/rRVR0r539dVXa3D12WefoS9hAEVERH2ezH6yxQ/VFTLvWjQUZrUNMc9YpTOj6rI36MIXz8MrOlXDKFkya4p6n34+Ibhk6Dm4cPCZWJO/UXfQk2qotQWbdcl5qYiamThJK6SIiIjo+Ej4Y7F69aqnUSqfysvL8dVXX8FiseixnTt36lvnJKMLLrhAw6QPP/wQoaGhmDBhQpeP9eyzz+Kmm27CDTfc4DomM6H62kQkBlBERESH7qgXmawreOblaCjJR63uqLeqbTe9vTt1lS56BdawONjbwyh5/2h/s0buJbOfJsSM0lVQWYQFWcvwTe53WiH15uaP8M7WTzE+agTmJk/DoH4pfH2JiIj6kPDwcB1ELnOaRo8ejezsbN0gTTQ0tFVzjRkzBhEREXjiiSdw5ZVX/mAFtVyzfPlyraSSaz766CMdWC6hVV/CAIqIiOgwrCFRsE46H4GTzkdTZYmrMsqRtxUN+/J0lS99B+bAMFdllFdUKnfU62Ui/cPx05EX4tKhZ+O7Pet0VpTsnLdiz1pdUX7hmJs8FdPix+tue0REROTZpL1u69atulNddXU1oqKicNFFF2nr3ObNm3HppZfqddJWJ7Odzj///B98rEceeUTnRUnFlAw0Hz58OO69917cc889KCgoQGRkJPoC7oLHXfCIiOgYNNdWoTZzjQZSddkb0dp0cK6BySegfUe98drWZzC3lW1T75Jbtgfzs5Ziad4q1DfV6zGryYJJsWMwL2kakoJZ9UZERHQ0O6ZR79Odu+AxgGIARUREx6mlwaEzolw76tXXHvyL1suuO+npEPOkkTBabXy+e5naxjosy1uNBZlLkFeR7zqeEBSjQ8unxI6Bt4U/ZBMRETGA8jwOBlDdhwEUERF1p9bmRtTlbW0Lo3auQnNNueucwWSBLWFY29yo1LEw2TngujeRQaHSlidDy7/bsxaNLU163GbxxrS48ZibNBWxgVHuvk0iIiK3YQDleRwMoLoPAygiIjpRWltbUJ+/q21u1M50NJUVHTxpMMI7ZiB80sZpdZQ5oB9fiF6kqr4a3+SsxIKsJSiq3u86nhaapO15E2JGwmJi6yUREfUtDKA8j4MBVPdhAEVERCereqZx/x5XGNVQnNPpvDU80TXE3BIazR3XeomW1hZs3ZehVVGr8zfqn4Wfly9mJkzEnMQpCPcLc/dtEhERnRQMoDyPoxsDKO6CR0REdBIYDAZYw2J1BU29CI3l+1CbsQo1O1bCsWcHGoqydZV9+yYswZGwt1dGeUUmw2Doektfcj+jwYih/QfoKq0rx+LsFViUtQwldWX4eMcCXcPDB+qsqNGRQ2Eymtx9y0RERERuwSHkHEJORERu1lxTgZqM1W076uVuAprbZgsJk2+wtulJIGWLHQyDib876umaW5qxvnALFmQtxYbCbWhFqx4PsgVgduIUzE6cjBB7kLtvk4iIqNuxAsrzOFgBRURE5DlMPgHwHzlHl+ygV5u1vm2IeeZaNFeXonLtl7qM3r6wp4zWyihb4ggYLV7uvnXqglQ5jYkarmtf9QEszF6GxdnLUVZXgfe2fob3t32h1VBSFTUsfIBWURERERF5Ov4alYiIqAcxetnhO2iyrtamRq2IqtmRjppdq9FSW4nqzd/qMpitsCWNbKuOSh4Dk83X3bdOXQjzDcVlw87FxYPPRHr+eizIXIpt+3fpvChZ/X1CMSdpqs6L8vf243NIREREHosBFBERUQ9lMFtgTx6tK7SlGY69O1CzcxVqZUe9iv36VhaMJtjiBsOeKkPMx8HsF+zuW6dDmE1mTI4dq2tvZaEGUd/mrkRxzQG8vukDvL3lE0yIHom5yVMxIFTmfhn4HBIREZFH4QwozoAiIqJeuKOe7KLXtqPeKjTu393pvFdkirbp2dPGwxoS6bb7pMOrb2rA8t1rsCBrCbJK81zHY/wjMDd5GqbFjYfdauPTSEREvQZnQHkeRzfOgGIAxQCKiIh6ucbSAg2iZNXn7+x0zhIaDZ+0CRpIWcMTWFnTQ2WX5mF+1lIsz1uN+uYGPeZlsmJy3FjMS5qKxOA4d98iERHRj+orAdT777+PO+64Azt3dv65qyeaNWsWzjvvPPzqV786po/nEHIiIiJysQRHInDiubqaqkpRm9EWRtXlbUHjgb0oP/Aeype/B3NAP9hTx2kY5R0zAAajic9iDyEB043Bcbhq+AVYkpeOBZlLsKeyUIeXy0oKjtOh5ZNjx8DLbHX37RIREREdNc6AIiIi8iAy/8l/9Km6muuqdSc9adWry96gc6MqV3+my2j3h0/KGG3TsyUMg5GhRo8gLXenpszAKcnTseNAps6KWrl3vbboZZW+ilc2vIfp8RMwN2kqogMi3H27REREREeMARQRuTgammAyGlHjaISPtwXNLS3wtvJ/E0S9leyM5zd0uq6WxnrUZW9ETUY6anet0R31qjYu1mWwesOeNKptblTyKN2Jj9xLhpAP7Jei62pHFb7O+Q4Ls5bq0PIvdn2ta1C/FB1aPi5qBCwmC18yIiKiblZTU4PHHnsMX331lb4/ePBg3H777Z1a8Z555hkUFxcjJSUFd999N4YPH67nCgoK8Oijj2LlypWorKxESEgIzjrrLPz+97+H0WjUj/3Xv/6F//u//9O3hYWFSE1NxZ133onRo0e72ucuv/xybNiwAcuWLYPVatXHkHswm9v+nbZu3Tr8/e9/x+bNmxEcHIyZM2fq5/D17Xk7JPNflkSkGhqb8b+vM/HJ0mzU1DXCx2bB2VMTceGsFFgtbNMh6u2MFi/dIU9Wa3MTHHu2o2bHStRkrEJzVSlqtq/QBZMZtvihbWFUyliYfQPdfet9nr+3H84ZOA9nDZiDTUU7dGj5moJN2LZ/ly5/L1/MSpyMOYlTEOYb2uefLyIiou5y8803Izc3Fw8++CBiY2Px7LPP4tprr8UvfvELPf/OO+9oQCXzru666y69/uuvv9ZzEiz169cP//3vf+Hj46NDuuVxRo4ciTlz5ug1Ejq99dZbGlTJNffcc4+GS/Pnz3fN7Xz88cdxyy234NZbb8WqVas0oBoyZAjOPfdc7NixA9dcc41+rvvvvx8HDhzAI488ovf49ttv97jZnwygiEgrnyR8emv+wSF6EkK92f7n82cmsxKKyIMY2kMmWSGnXIf6gizUZsiOeuloLClAXdZ6XcBzOivKrsHVeFgC+7v71vs0o8GIERGDdJXUlmFR9nIsyl6GsroKfLj9K3y0fb6ek/a8URFD9berREREdGyys7OxZMkSvPjii5gyZYoek4DI398fdntbtbiEPklJSfr+ddddh1/+8pcoKSnRMOmcc87BaaedhoiItpb5q6++Gi+88IIOLncGUI2Njbj33nsxcOBA/bOESTfddBP279+PsLAwPSaf+6qrrtL3Y2Ji8Oqrr2rVkwRQcm+TJ0/GjTfeqOfj4+O1GkoeX8Kq8ePH96iXnwEUEWnbnVQ+deXjpdm4YFYKlm7Yi6h+fojp7wuLmRVRRJ7CYDDCOypFV/DMK9BwYK8GUbU701FfmKWVUrJKF74Ma1h8W2VU2jhYw+J63G/V+pIQexAuHnImLhh0GtYWbNaqqI1F27G+cKsuOT87cQpmJU5CsI1VbEREREcrIyND344YMcJ1zMvLS3e/k/Y5Z+DjJMGUc9c4abe74oor8OWXX2LTpk3Iy8vT4EkqlFpaWjp9HmeAJfz8/FzBVFfnndc4z2/btk0fW6qqDpWVlcUAioh6Hpn5JBVPXZ6ra0R5VT3eXpCBvKIqGI0GRPXzRUKEP+Ij/REnbyP80S/Qxn+MEnkAa2i0rqDJF+jQcmnRk0DKsXs7Gvbl6ipb+jbMQeHtLX3j4RWVqkEWnXwmownjokfoKqrah4XZy/B19gqtkHpnyyd4b+tnGBs1XKuihvRP0yoqIiIi+nHOGUuH/XvY9P1fzLe2tqK2tlYDKAmjTj31VJx33nkYNmyYznM6lMx16uoxjuS8hFkyE8pZAdWRzIPqaVgBRUQ6cFxmPnUVQsnxQD8v9A+2o6TCgeq6RuwprtK1ZEP+weu8za4wqm0FIC7CD3ZvDsYl6q3MAf0QMPYMXc21lTq8vG1HvY1oKitCxcqPdZl8AmFPbZsvZYsfAgMHYrtFuF8Yrhh+Pi4echbS96zXqqgdB7KQvne9rgjfMMxJmooZCRPg59XzBpMSERH1JM7KIxnuPXHiRH2/qakJ8+bN6zJI6kgGhm/duhXLly9HaGjbfMby8nJtz+sYLh0vGXyemZmJuLi4TpVPMlPqd7/7nauiqqdgAEVEutudDBx3znzqSI7L/yT/fN0EfSshVG5hZdsqqEReUaWGUTWOJmzLKdXVUViwXaulOoZTkaE+MJn4W3ii3sRk94ff8Fm6WhrqUJu1Qdv0ajLXormmHFXr5+uSHfTsyaNhl1a9pBEwWm3uvvU+x2qyYGr8OF27y/OxIGspluSmo7B6H17d+D+8tfkjTIwZrTvopYYksnqViIioCwkJCRo2yYwmmf3Uv39/PP/886ivr//R5ys8PFzffvzxxzjllFN02Phjjz2mrXMNDQ3d9nzLsHEJw+QepeJKdtuT96XyqmN7YE/BAIqIdMC47HbnnPn0Q7vgybyX0ECbrjEDDw4jbmxqQf7+auQWVBwMpworNazaV1qrK31rket6i9mI2HC/DtVSbQFVkJ83Xw2iXkBCJd+BE3W1NjeiLncLanauQq3sqFdTjuqtS3UZzFbYEoZrZZTsqGey96zfwvUFsYFRuG70Jbh82LlYtnsNFmQuQU75HizJS9cVFxClQdTUuPGwWfj/YCIioo4eeOAB3VXuN7/5jQZHw4cP18HfMnvpcKTdTmZFvfTSS/jnP/+p4dXpp5+uA8mloqq7yHyqf//737pTnrT5yXB0qda67bbbumzdczdDa3fWf/VCs2fP1reyJSJRXye74clA8lpHo7bOSWWUhFPHqqq2wVUpJW/z5P2iStQ3NHd5faCvlyuM0mAq0h+x/f1cARgR9WytLc2oz9+lbXqymsqLD56UYeexg3RmlARSZv+2cnQ6ya9RayuySvMwP2sJlu9eg8bmttZrb7MXpsSNw7ykqYgPiuHLQkREx0Qqb3JycrR6yNubv9joC6/p7KPIVBhAMYAiOqlaWlpRXFqL3MKKtmCqqC2gKiypQVdxuNEARPbz1VBKB5+3B1RhQXYdiE5EPTfoaNiXh9qdbUPMZXh5R14RSdqmJ4GUDD2nk6+6oUZb8xZkLkV+1cEq1ZSQBB1aPilmNKzmnvfbUyIi6rkYQHkeBwOo7sMAiqhncNQ3YXdx1cFKqcJK5BRUahVVV2xe5s7VUu3v+9o49JyoJ2osK9Id9SSQcuzZIRGV65wlJEqDKAmkJJiSdl86uWHhtv27tD0vPX8DmlvaqlR9rHbMiJ+IuUlTEOnfNsuCiIjocBhAeR4HA6juwwCKqGf/o6isqt7VwqdVU4Uy9LwaTc0tXX5MvyAb4sL9kRDpr2+ljS+qny/MHHpO1GM0VZfrvCiZG1WXuxloaXKdM/mFaIueBFLSsmcwsgX3ZCp3VOLr7BVYmLUU+2sPbioxJCxNZ0WNjRoBM18TIiL6AQygPI+DAVT3YQBF1PtI+NQ29LxtFz6plJJg6kB5XZfXS/gU09+3vVIqwDVfKsjPi5UWRG7W4qhBbdY6bdOrzVyP1kaH65zR5gt7yhj4pI6HLXE4jBYvt95rX9LS0oINRduwIGsJ1hVucW0ZHejtj1mJkzA7cQr6+YS4+zaJiKiHYQDleRwMoLoPAygiz1Fd1+hq32sbfl6hAVVdfddDz/19rJ3a9+St7M53PIPXiejYtTQ1oC5nE2pliPmuNWiprXSdM1i8YEsc0daqlzIGJm8fPtUnyYGaUizMXobF2cu1QkpfD4MBIyOG6NDyEeGDYTQa+XoQEREDKA/kYADVfRhAEXn+0PN9ZbUH50q1z5gq2F+Nli6GnsvomYgQH62Qim9v4ZOqqf7BHHpOdLJ31JNZUVoZJTvqVR44eNJogi1+iFZG2VPHwewXxBfnJGhqacaa/I1aFbW5eKfreD97MGYnTcGsxMlaIUVERH0XK6A8j4MBVPdhAEXUN9U3NmNPUdvQc+fg85zCClRUdz303Ntqcs2Ucr6Viik/O3eIIjopO+oVZWsYJavxwN4OZw3wikp1zY2yBEfwBTkJCiqLsDBrGb7O/Q41DbV6zGQwYlz0SN1Bb3BYKluciYj6IAZQnsfBAKr7MIAioo7KqhydduGTFr7dRVVobOp66HlIgLerja9ttlSADj23mNmOQnSiNJQUtLXp7UxHfcGuTucs/WLbw6gJsPaPZwhygjU0NeC7PeuwIGspMkqyXccj/fprEDU9YQJ8rWyXJCLqKxhAeR4HA6juwwCKiH5Mc3MLCg7UHFItVYl9pW2/9T+UyWhATH+/TpVSsiSs4vbyRN2rqbIENRmrUbtzJerytkrvnuucOSBMwyi77KgXncYd9U6w3LK92p63NG8VHE31esxismByzBjMS56GpOA4/j+QiMjDMYDyPA4GUN2HARQRHatahww9lza+ioODzwsrUes4uKV8R742iw47T2jfhU/el5DK5sWh50TdobmuCrW71mplVF32BrQ2HWypNfkEwJ4yVgMpW/wwGMwWPuknSF2jQ0OoBZlLkFeR7zqeEBiDuclTMSV2LLwt3nz+iYg8EAOog8rKyrBw4UJcdNFF+ucrr7wSUVFReOihh9CbMIDqRgygiKi7Z9XsL69r34XvYLVUvgw972rqOdqGnsdF+Omw87Y2Pn+Eh/hoJRURHZuWxnrUZW1ATUY6amVHPUeN65zBaoM9eVTbjnpJo2D0svFpPkH/P9xVkoP5WUvw3e61aGxpC+dtZm9MjR+HeUnTEBsYxeeeiMiDMIA66I477sDevXvx6quv6p/Ly8thMpng5+eHvhpA8dfuRETdSFrswoLsusYNCncdb2xqxp7i6vZqqSrkFrRVTZVV1aOwpEbXyi1FruutFhNiw/3aqqWkUqr9bYCvF18voiNgtHjBZ8B4Xa3NTajbvRW1O1dpdVRzdRlqti3XBZNZK6L02pSxWilF3ff/w9TQRF0/HXEhvs1diQWZS1FYvQ/zM5foSgtN0llRE2JGwWpiVRoREX1fXV0dzGYzqqqqNLxpamqCzWbrFb+I6SgwMBB9naH10Gelj2EFFBG5U0V1vWuulA4+L2wbet7Q2Nzl9UF+Xq5h5/HtVVMx/WXouemk3ztRb9Ta2oL6gkwNomSQeWNp4cGTBiO8Ywa0VUaljYMlIMydt+qRWlpbsHVfhgZRq/M3oLl9Zpef1QczEiZqGBXux+ediKi36u4KqPr6erz00kt46623XAHUJZdcgquvvhpeXif+F7MZGRn4+9//jnXr1mkQ1r9/f1x++eW49tpr9fzSpUvx1FNPYceOHQgICMB5552HX//617jzzjvxwQcfuB5n586drha8P//5z5gyZQr+8Ic/4LLLLnNdI4/z3nvvYfHixfpLnH//+9/6dR84cADx8fG47rrrcPbZZ+NkYwUUEZGHkIqm4Sn9dDk1t7SiqKR96HmBBFMVOmtKqqSkYqqsaj/WZ+x3XW80GnTnvQRnpVT74PN+gTYO/CU6hEFCpqhUXcEzr0DjgT2oaa+MaijKhmP3Nl0lC/4La/8EDaNkWfrF8L+nbmA0GDG0/wBdZXUVWJy9HAuzl6Gktgyf7Fyoa1j/gTorakzkMJiMDNeJiDyB1L1IkHE0Wlpa8Nprr+GFF15wHZMQyvnnK664Akbjke08LWHY0W4GJIGTBE2TJ0/WIEja59599108/PDDmDhxon49N9xwA6655ho88MADyM/P11BJqrUkgJLzRUVFePLJJzs9ro+PD0499VR8+umnnQKoTz75BOecc45+TY899piev+uuu5CYmIjVq1fjnnvu0a9fArDeii14REQ9jKk9UJI1eVik63hdfRPyitqrpSSYKmp7W13XiD3FVbqw4eDAXx9vs6t1r20F6KwpuzfbXIiE/CBq7RerK2jKhWis2NfeprcKjj3b0VCco6tsyVswB4XDZ8AEDaO8IpM1yKLjE2QLwAWDT8e5A0/B+sKtWJC1FBsKt2JT8XZdcn524mTMTpyCEHsQn24iol4cPkn1zqZNm474Y6RdTQIZCX66IsevuuoqnHXWWTpb6ccMHz5cK4qOJoSSAEo+hwQ+EhoJqW6Sx5GKpiVLlujj3nrrrXouKSkJ9913H0pKSrRSS0Ivi8WCfv0O/qLZSSql5LEltJKqKHlucnNzcf7556O2tlarviSEmjFjhl4fGxur17744osMoIiI6MST3fIGxAXr6vgXekmF4+AufDL4vKhSw6gaRxO25ZTq6igs2H6wWqp9RYb6wGTiP6ipb5OWu4BxZ+pqrqlAza412qZXm7MRTWVFqPjuQ10m3yD4pI6DPW08bHGDYTDx93nHQ6qcxkQN07Wv+oBWRH2dvUIrpN7b+jn+t+0LjI4chnlJUzEsfKBWURERUe9ytNVHISEhKC0t1Yqfrshx2WVOrjuSAOpYBAcHa4WSVCJt27YNu3fv1lY7Z3WWtOdJdVRHp5xyyhE99tixYxEdHa2P/fOf/xwff/wxRo0ahbi4OA2jpPXw97//facKL5l91dDQoJVV3dHe6A78iYmIqJf/ZR4aaNM1ZmB/1/HGphbdec857Ny5JKzaV1qrK33rwaHnFrNRh57Hhfsjob2FTwKqIL/e+Zcb0fGSYeT+I2braqmvQ23Wura5UZnrdIh55bqvdBm9fWBPHq2VUbbEETBa+d/M8QjzDcVlw87FxYPPxKr8DTqofNv+XViTv1FXmE8I5iRNxayESfD37l27CBER9VXOeUZH24InrWxSSdRVCCXHpbJIKoVOVAve/v378ZOf/ESDqFmzZuncpqFDh2L69Omu+ztWBoMB5557rlZ5XX/99fjiiy9w88036znnmO5//vOf2n53KKvVit6KARQRkQeSQMlZ3dRRVW1Dp0opZytffUMzsvZW6Ooo0NdL2/akfc/5eDHhfvCycC4L9R1GLxt8B03W1drUiLrczW1h1K7VWilVvWWJLoPZClvi8LYh5iljYLIxIDlWZpMZk2LH6NpbWYiFmUvxTe5K7KspwRubPsQ7Wz7F+OgRmJc8DQNCk4/6HxVERHRyyf+nj3bnOmmBk4HjHWdAOcnxE70bnlQnSXXVV199pa10QlrvnCGRtNxt3ry508e8/PLL+nEyK+rH/m4677zzdPC4tBPW1NTgtNNO0+MSOkm4VVBQgJkzZ7quf+WVV5CZmaltfr0VAygioj7Ez27F0KRQXU4tLa0oLq3VYecdZ0vJ0PPy6nqU76rHxl0HXNcbDUBkP1+tkOrYyhcWZNeB6ESezGC2wJ48Sldryw2oz89AzY6VOjeqSWZIZazWpTvqxQ1uG2KeOg5m/xB333qvFe0fgatHXYxLh52LFbvX6KyozNJcLN+9Rpecl93zpsdPgN3a87flJiKiIyPhkux2J9yxC154eLiGYF9++SVGjx6N7OxsPPjgg3pOWuGkcumCCy7A448/rsPD8/Ly8Mwzz+hsJ2G327Fv3z7s2bMHMTEx33t8mf00fvx43WVvzpw58PX11ePOr1EeV45Ja156ejoeffRRbdfrzQytzvquPmr27Nn6dtGiRe6+FSKiHsVR34TdxVVaMaWDzwsrkVNQqVVUPzSjKi7cD/GRB6ulJJzytXHoOXk++XGqoTi3rTIqIx0N+3Z3Ou8VmQKftLa5UdaQKLfdp6fILs3D/KylWJ63GvXNbf9P8jJZMTl2jFZFJQbHufsWiYj6JGmzy8nJQUJCQrfNKZIQSCqCqqurNZA50ZVPHf9ul3Dogw8+0M8tgdFFF12k2YEMBZed777++ms88cQT2LVrF8LCwjSQ+r//+z+d3STVUTfddBMqKiowf/583HLLLfoYDz30kOtzfPTRRzrE/L///S8mTZrkOi5f47PPPov3339fQ6yIiAhcfPHFGnqd7KrfH3tNjyZTYQDFAIqI6Kj+Ii6rqm+rlNJQqm3G1J7iajQ1t3T5MTKfSsIomS0lM6biI/11hz8zh56TB2ssLURNhuyol476vRnyX4/rnCU0WquipDrKGpHE9rHjUNtQhyV56ViQuQR7Kgtdx5OC4jA3eaq28HmbT+xvyImI6MQGUOReDKC6EQMoIqLjJ+GTDD3vWCklM6b2l9V1eb2ETzH9fV2VUjpjKlKGnnvxH+PkcZqqy7QtT8KoutwtQEuT65zJP1QroySM8o4ZCIOR89WONRzfeSBLq6JW7lmHpvbn2G6xYVr8eMxLmobogIhue02JiKhrDKA8j4MVUN2HARQR0YlTXdfoCqUOtvJVoK6++QdnVHXchU/eyu583laOLCTP0OyoQW3mWtRKq17WerQ21rvOGW1+sKeM1UBKhpkbzb13lxt3qnRU4Zvc77AgcymKaw7OrxvYL0VnRcnwcouJrcFERCcCAyjP42AA1X0YQBERnVwy9HxfWe3Baqn2YKpgfzVauphKKG3uESE+WiEV397CJxVT/YM59Jx6t5bGetTlbHLtqNdSV+06Z7B4w540sm1HveRRMHr7uPVee6OW1hZsLt6B+ZlLsLZgs/5Z+Hv5YmbCJA2jwnwPbshARETHjwGU53EwgOo+DKCIiHqG+sZm7JGh5+3zpZwBlezE1xVvq0lnSjkrpdqCKX+toiLqbVpbmuHYvU1305NAqrmq5OBJoxm2+CFtYVTqWJh9g9x5q71SSW0ZFmcvx6Ls5SitK9djBhgwPHwg5iZPw6iIITCx/ZGI6LgxgPI8Dk8KoFpaWvDUU0/h3Xff1W0Vx44di7vuuqvLbQpFSUmJTptfvny59vvLpPjbb78d/fv3P6bPzwCKiKhnK6tydGrjk7W7qAqNTV0PPQ8J8NZQKqHDTnzRYX6wmI0n/d6JjoX8fFNfmKVtehJGNZbkdzhrgFd0moZR0qpnCQrnk3wUmluatRpqQdYSbCza7joeYgvC7KTJmJU4GcG2QD6nRETHiAGU53F4UgAl4dNrr72mWxGGh4fj0Ucfxd69e/HJJ5/Aav3+b7GvvPJK3ZJQQiq59XvvvRfNzc147733junzM4AiIup9mptbUHCgptNsKWnl21da2+X1JqMBMf39XLvwOYefS1h1sreyJTpaDQf2amWUBFL1hZmdzlnD4mDXMGq8vs/v5yNXVL0fC7OW4eucFaiqb2t/NBqMGBM1TIeWD+mfpn8mIqIjxwDK8zg8JYBqaGjAhAkTcMstt+Cyyy7TY5WVlZg6dSruv/9+nHnmmZ2ul3NSIfWvf/0Ls2bNcn2Rv/jFL5Ceno7AwKP/jRUDKCIiz1HrkKHnVTrovGPFVK3j4K5jHfnaLAerpSLbqqUkpLJ5ceg59UxNlQfa2vQyVsGRt1V691znzIH9XTvqeUWlcke9I9TY3Ij0vet1VtSOA1mu4+G+/TAnaSpmJkyEn5dv97+YREQeiAGU53F0YwDl1p+wd+zYgZqaGkycONF1zN/fH4MGDcLq1au/F0DJF+vj44MPP/wQ48aN02MfffSRPhHycURE1LfZvS0YmBCsy0l+z7K/vO7gXKmCtmqp/P3Vukvf1uwSXR2Fh9jbq6QCXPOlwkN8tJKKyJ3M/qEIGHu6rubaKh1eLoFUXc5GNJUXoyL9E10mn0CdFyVhlMyPMnDXtx8kO+JNiRuna3d5PhZkLcWS3HStkHpt4/t4e/PHmBAzCvOSpyE1JJFVZkRERMfIrQFUUVGRvo2IiOh0PCwszHWuI2nJk1Y9ab8bM2aM/gAg10oLn9H4wyXSzkSuK4WFhd/7/ERE5Dn074ogu65xgw7Oy2lskqHn1QcrpQoqkFdUidLKehSV1OpaueXg30VWiwmx4X5aLeUafB7hjwBfLzd9ZdTXmex+8Bs+S1dLgwO12etRK616u9aguaYcVesX6DJ42XUnPR1injQSRqvN3bfeY8UGRuG60Zfg8mHnYvnuNZiftQQ5ZXuwNG+VrtiAKMxLnqphld3C55GIiKjXBFB1dXX69tBZT15eXqioqPje9fJb7O3bt2PkyJG4/vrrdfbTP/7xD23Be/PNN+Hry/JoIiI6MhazCYlRAbo6qqiu77QLn75fVIWGxmZk7inX1VGQn1d7lZRUS/lp1VRMf199fKKTxWj1hu+AibpamxtRl7dVB5hLICVhVM3WZbqkEsqWMKxtblTqWJjsrCDvirfFG7OTpuhQ8qzSPA2iVuxeg90V+fj32rfw6sYPMDV2rFZFxQd1vXEOERER9aAAytk/KLOgOvYS1tfXw2b7/m+VvvjiC612+vrrr11h07PPPouZM2fqEPKrr766y89zuF7Ew1VHERFR3yMVTcNT+ulyam5pRVFJ+9DzAgmlKnTWVGFJDcqq6lFWtR/rM/a7rjcaDYjq53uwWqp98Hm/QBvbd+iEk5DJnjhCV+upP0N9/i4No2Q1lRWhNnOtrgOfG+EdO7BtR73UcTAHHPyep/bn0mBAcki8rqtGXKCteQsylyK/qggLs5fpSgmOx9zkaZgUMxpW8/c30CEiIjoWTz75JD744AMsXrzYY55AtwZQzta3ffv2ITY21nVc/pyWlva969esWaPznjpWOgUEBOixvLy8k3TXRETU15jaAyVZk4dFuo7X1Tdhd5Gzha8SufJ+QaXOltpTXKULG/Jd1/t4m9sGnTsHn0cEIC7CT2dXEZ0IBoMR3tFpuoJnXYnG/bvbw6hVaCjO0UHmskrm/wfW8CTXEHNLaDTD0kP4Wn1weuosnJYyE9v379Kh5en5G7CrNBe7VuXi5Q3vYXr8BMxLmopI/4PtvkREdPxDsDsWrBz6Z0917bXX4vLLL4cncWsANWDAAA2TZAc7ZwAlO91t27YNV1xxxfeuDw8Px2effaYVUtKmJ2pra7F3716cffbZJ/3+icjzNTscMJjNaKqpgdnHB61NTTD1gb/w6MjIbnlpccG6OraLl1Y6kKOVUgdb+SSMqnE0YVtOqa6OwoLtiA8/WCklKzLUByYTt4Cn7q3msYbF6QqaejEay4s1iKrdmQ7Hnh1oKMrSVfbtm7AER8Lu3FEvMlmDLDr4PA4KS9VV7qjE19krsDBrKfbXluLzjMW6Boelanve2MjhMJu4qyYR0bGSf/v/97//1TBGMoBD/+zJfHx8dHkSQ6v8pOxGMsPprbfewgMPPICoqCg8+uijGih9+umnOli8tLQUfn5+mnBKZdRZZ52FUaNG4Te/+Y1+/D//+U8NrCSYkuuO1tFsGUhEfUtLQwP2vPc+Cj/9HM01NTD5+CDyrDMQfcF5MB4yu47oxzQ2tejOezLs3DX4vLASJRWOLq+3mI069Dwu3B8Jkf76VgKqID8GoNT9mmsqUJMhO+qloy53E9Dc5Dpn8gvWFj0Jo7xjB8HAQOV7WlpasLF4m1ZFrSvcokG0CPD2x6yESZiTNAX9fEL4rUtEHk+qk3JycrRL6dAqJecM6B9isVhgNreF9o2NjWhqasJLL72EF198EePHj8ef//xn/OUvf9ECluuuuw7XXHONfg75f6583sPpasTPj5GuLNkA7aOPPtJZ1PHx8bj55ptdGYL8v/+FF17A+++/j/z8fJ1tLVmFfIyzwObbb7/F448/jqysLNjtdkyfPh133HGHdnIJ+dpknrVswiYbrF1wwQU641p+2dGxBe/KK69ESEiI5h9Oq1ev1sKd+fPnIy4uTkcVycdkZmaif//+OOOMM/SxDp253Z2v6dFmKm7/lcyvf/1r/cb605/+pF/Y2LFj9UWQbz4JouSLefDBB3H++efrC/LGG29oSPXTn/5UAyrZDU+OHUv4RER0uMqnve9/iL1vv3vwWE0N9rz1jr4fdd45rISioyKBkrO6qaOq2gZXC5/swuds5atvaEbW3gpdHQX6emnbnrTvOR8vJtwPXhYOPadjZ/IJgP/IObpa6mtRm7mubYh51jo0V5Wicu2XuozevrCnjNFWPVviCBgtnv3b5yMlP5OOjBii60BNqc6GWpy9XCukPtj+JT7c/hVGRgzWqqgR4YMPu3szEZGnmjp16mHPy473c+bM0fefeeYZZGRkaBawZcsWDZ3OPPNMPSdhlAQvzjCkvLwcc+fOPexjyzifY/G3v/0Nt9xyi96bBE2//OUv8frrr2vQ9Morr2h28fDDDyM1NRW7d+/WkEyulfuXYhq5/vbbb8eMGTM0ZLr11lvxyCOP4P7779dg6bnnntOiHAl3NmzYoOejo6NxzjnndLoPyUPuueceVFdXu0YSffzxx3ofEj4tWbJEwzEJtyZNmqT3ImGdBEcSgPUUbg+gTCYT/vCHP+g6lDzxO3fu7HQsKSlJB48TEZ1I0nYnlU9dKfjkM0RfdAFfAOoWfnYrhiaF6nJqaWlFcWmtDjvPLaxqe1tQqUPPy6vrUb6rHht3HXBdbzQAEaG+WiHlGnwe4Y+wILsORCc6GkYvO3wHT9HV0tQAR87mtrlRu1ajpbYS1Zu/0WUwW2FLGqlhlD15DEw27kYsQn2CccnQs3Hh4DOwJn8jFmQtwebinVoZJSvUHqwVUVIZFWjrvAsnEREdJKGThD0SykhlkJP8Wap+Oh47UST4cc5hkiBq1apVujGaBD9S5SThk2yKJqSj69RTT8WXX36pfy4uLtYN1yIjI/VcVFSUZhnNzc16XkIiqU6S43KNLCm6kbeHOuWUU3Dfffdh4cKFOPfcc/Vxv/rqK1eOIo978cUX45JLLtE/y73de++9WrgjhT2SrfQEbg+giIh6Ipn5JBVPXZHjsoztpbNE3U1Co4hQH10Thx487miQoedVrrlSsmTWlFRRSXufrOUbCzrNqIoL90N8ZADi299KOOVr49BzOsLvRbMV9pTRukJbmuHYu8M1N6qpYr++lQWjCba4wdqmZ5cd9fwOzkXrq8xGEybEjNJVUFWMhZlL8XXudzhQW4q3Nn+Md7d8irHRIzAvaZrOjJJ2CyIiT7Z06dLDnpcuKCdpHbvxxhu1ve73v/99p+ukgujvf/+768+BgYE/+tjHSqqtOho5ciSWL1+u78+aNQsbN27UCiOpNJLlbH8TAwcO1Kot+Tr69euHyZMnayWUs1pL5lj/73//03ApOTlZK5fk/a4CKGnfk3Drk08+0QBKWvskhDrttNP0vIwl2rRpE9577z3XxzjbwaX9jwEUEVEPJgPHZeZTVyGUHJdFdLJ5W81IjQ3S1fGHi7Kq+rbWPQ2lKpBXWIXdxVW6S9+OvDJdHYUG2rRCquNsKdnhz8yh53QYBgmZYgfrap1zte6i17ajXjoa9+9BXc4mXfjyBXhFpWoYJdVRMtC8r4v064+rRl6olVEr967XWVEZJdlYuWedLjk/N2mq7qLn68W/X4jIMx3NHCYJo2REjwwcl0ooCYJktpJUAcmf5bhzBpQE+Mcy4+lIOGdSOUn1krON+vnnn8fTTz+N8847DxMnTsTVV1+tc5BkPrWTBGU33XSTtsitWLFCK5ZGjx6Nl19+GcHBwTpfav369RpqLVu2TNv6fvWrX2nrXlfVWFLRdODAAQ2ipF3R2Y4n86iuv/56vZdDSfjVU7ACioioC7LbnQwcd8586kiOy3kc8hcSkTvID13B/t66Rg0Icx1vam4bep7XoVJKZkztL6vDgfK2tWZ7set6CZ9i+vu65krpjCkdeu7Fygzq8vvOKzxRV/D0S9FYWqCVURJG1ednuFbp4ldh6RcDn1QJo8bDGp7Qp7+frGYrpsWP15Vbtlfb85bmrdIKqZc3vIc3Nn+ESTGjdVZUcnB8n36uiIgkXJLd7oRz17vHHnsM//nPf07aLnibN2/WSicnCYsGDx7sanuTcOmGG25wnZeZUM7KI6mOkjDqj3/8IxITEzWgkrlNEkKVlJRo6FRVVaUtfhJKyXxsmY39+eefdxlAyfxradeT0Oqbb77pNJooJSVFK7BkHpSTBHUSaMnsKKmg6gn4rycioi6YvL11tzvnzCfugke9jQRKUt0ka9rIg8er6xo7tfA535dqKQmpZB06o0orpVzBlL/uzifVWEROUuUUOPFcXU1VpajNkDBqFerytmh1VLms5e/BHNBPW/R0R72YAVpV1VfFB0XjZ2MuwxXDz9cQakHmEuRV5OPb3JW64gOjNYiaEjsW3hbufklEfZOETFLp5AybDv3ziSaVShIeDRkyBO+8847OqJYB4iIiIkJDJAmopCpKgiGZTRUa2jbXU6qTZMM0qeaS+Uz19fUaLsluekFBQfpnmSHl4+Oj4ZIMKZed7eT9rsgvJaT9TqqupHpqwoQJrnM/+9nPdAj5U089pbvfyWPdeeed2nrXkyqgDK3OeK6POpotA4mob+6GJwPJnQGUVD5JOEXkSeRHgX1ldcgtkKHnB8Opgv3VaOnipwQpyogI8dFQSoaeS6WUvB8e7MOh59RJc101ajPXamVUXdZ6tDY1uM4Z7f7w0R31JsA7YajOm+rr/x3uKsnB/Kwl+G73WjS2NOlxm9kbU+PH6ayo2MAod98mEdFhSducVOLIrm7OXep6q7S0NFx33XVaSSQ78g0YMEAHkTvnQm3dulVbAnfs2KEh0vDhwzF9+nStOJId7mSW09dff62hUHZ2toZUEhrddtttOiRcvPDCC3j33XdRWFiIgIAAnQEln0NaCp988kl88MEH+lhOBQUFmmFI1dVvf/vbTvf7xRdf6K56ModK5mJJMCaP5e/feQfm7n5NjyZTYQDFAIqIiKhL9Y3N2FNc5Zov5ayWkp34uuJtNbVVXXWolpL3/X36drBAbVoa61GXvaFtiPmuNWhxVLueGoPVG/akUW1DzJNH6U58fVl1fQ2+yf0OCzKXorB6n+t4Wkgi5iZP08HmVhM3EyCinsfTAqgHH3xQZy/1ZY5uDKBYP09ERERd8rKYkBwdqKujsipHpzY+WbI7n6OhGTt3l+nqKCTA+2C1VHsoFR3mB4u5bYgn9Q1Gi1f7YPLxaG1ugmP3trYh5hmr0FxViprtK3TBZIYtfmjbtanjYPLpezuOyiDyM9Pm4IzU2diyb6cGUavzN2BnSbaul9e/ixkJEzEnaSoi/A7OfiMiIurJGEARERHRUQny89Y1IvXgP3ybm1tQcKCmU6VUTmEl9pXWoqTCoWvdjoOVHCajAdFhvq5h586KKQmrOHjZ8xkkZEoYpivklOtQX5CF2oz2HfVKCrRdT9aBz5/TWVH29uDKEti3whb5b2Fo/wG6yuoqsDh7ORZmL0NJbRk+2blQl5yTWVGjI4fB3IdnahERUc/HFjy24BEREZ0wtQ4Zel6F3KJK14wpCahqHG3zbQ7la7O4qqXinPOlwv1h8+LvzPqKhgN7UbNjpbbqNRRldTpn7Z8An7S2IeaWfrF9MqyUrbbXFW7Bgqyl2FC4Fa1oG9QW5B2A2UmTMStxMkLtwe6+TSLqozypBY/acAZUN2IARUREdPKHLe8vrztYLSUzpooqsXdfNVq6mnoOIDzE3l4lFdD2NtIf4SE+WklFnqupYr+26ElllGP3dqC1xXXOHBTuCqO8olJhMPS9ls59NSVYmLUUX2evQEV9lR6TUE6qoeYlTcWw8IEw9sHnhYjchwGU53FwCHn3YQBFRETUMzQ2ydDz6oOzpQoqkFdUidLKroeeWy0mxIb7HayWal8Bvidna2Y6uZprK3V4ue6ol70Rrc2NrnMmn0DYUyWMGgdb/BAY+tiA7qbmJqzK36BVUVv3ZbiOh/mE6JyomQkTEeB9fLsgEREdCQZQnsfBAKr7MIAiIiLq2Sqq6zWIcu7Gp5VTRVVoaGzu8vogPy/XsPMEnS8VgJj+vrCYOR/HU7Q01KE2a72GUbWZ69BaX+s6Jzvo2VPGwJ42DvbEkTBa+1YLyN7KQizMXIpvc1eiprFOj5mMJoyPHol5SdMwsF9yn2xdJKKTG1bEx8fDZrPxafcAdXV1yM3N7ZZd8DgDijOgiIiIep3mllYUl9TooHMJppwBVWFJTZfXG40GRPWToeftlVISTIX7o1+Qjf8Y7+WkEqoud0tbGJWxGs015a5zBrMVtoThWhllTxkLk90PfUV9UwNW7F6jVVGZpbmu49H+EZibNBXT4sfDx2p36z0Skedpbm5GRkYGwsLCEBIS4u7boW5QUlKCffv2ITU1FSbT93+ZxwDqKDCAIiIi8hx19U3YLWGUs42vPaCqrjvYrtWRj7dZK6U6DT6P8Ifdu2+1cHmK1pZm1Ofv0jBKVlN58cGTBiO8YwfpzCgJpMz+oegrskt3axC1LG8V6psb9JiXyYrJsWMwN3kakoLj3H2LRORBCgsLUV5eriGU3W7nL3p68czO2tpaDZ8CAwMRERHR5XUMoI4CAygiIiLP/wGqtNKBnPYWPh18XliJPcVVWknVlbBgu1ZIaaVUeygVGeoDk4kDnXvT696wL6+tMmpnur7fkVdEMuztYZQ1NBp9QW1DHZbkpWNB5hLsqSx0HU8MisW85GmYFDsG3mbOUCOi4///b1FRkYZQ1PsFBgYiPDz8B4NEBlBHgQEUERFR39TY1IL8/dU67LxjxVRJhaPL6y1mI2L6+2kYJbOl4toDqiC/vjVjqLdqLCtCzc62HfXq9+6UfyK5zllCorQySgIpr4gkj/9tvfzjcOeBLMzPWoqVe9ahqaVJj9stNm3Nkxa9mIBId98mEXlAO15jY9cVyNQ7WCyWLtvuOmIAdRQYQBEREVFHVbUNnSqlnDOmHA1dDz0P8LW2V0kFID5CAqoAxIT7wcvCoec9VVN1mc6LkkCqLncz0B7ACJNfiFZFSSAlLXsGo2e/jpX11fgmZwUWZC1DcfV+1/GB/VI0iBofPQKWPrarIBERHTkGUCfoySIiIqK+qUWGnpfWIrdQqqWq9K0EVAUHatDaRRef0QBEhPp2auGTFRZk14Ho1HO0OGpQm7WufUe99WhtPFgBZ7T56o56PqnjYUscDqPFc9vTWlpbsLl4BxZkLsWagk36Z+Hv5YuZCZMwJ2kK+vv2c/dtEhFRD8MA6gQ9WUREREQdORpk6HnVwWqpwkqdNSVVVF2xeZnaW/cCEB/up29l8LmvjRUmPUFLYz3qcjZpZVTtrtVoqatynTNYvGBPGqltevbk0TB5+8BTldaWY1H2MizKXo7SurYZLgYYMDx8oA4tHxUxBCYPrwwjIqIjwwDqKDCAIiIiou6er1NWVe9q32urlqrC7uIqNDW3VZUcKjTQ1qlSSiqnovr5wsyh527dUc+xZ3v7jnqr0Fx54OBJowm2+CFaGWVPHQezXxA8UXNLM9YWbNYd9DYWbXMdD7EFYXbSZMxKmIxge6Bb75GIiNyLAdQJerKIiIiIjpWETwUy9LxDtZSs/WV1XV4v4VNMf1+tkEponzEVF+GHYH9vjx+S3SN31CvKbg+j0tF4YG+HswZ4RaW65kZZgrveprq3K6rej4VZy/B1zgpU1VfrMaPBiDFRwzAvaRqG9E/TPxMRUd8y+ygyFUOr/I16lJ555hmccsopSEpKQm/HAIqIiIjcqbqu0dXC17GVr67+4GDsjvzs1rZd+DpUTMX294O3l/mk33tf1VCSj9r2yqj6gl2dzlnDYmFPHa9hlLV/vMeFhY3NjUjfu16rorbvz3QdD/fthzlJUzEjYaLOjSIior5h9okOoIYPH44nnngC06dPR2/HAIqIiIh6GvnxbF9ZHXILZOj5wVBKKqhauvjJTTKOiBCfg9VS7QFVeLAPh56fYE2VJajJWKWBVF3eVundc50zB4RpZZTMjfKOTvO4HfV2l+drVdS3eStR1z683WI0Y0LMKMxNmoa00ESPC+CIiOgkB1AXXHABzjrrLFx99dXo7RhAERERUW9R39iMPcVVOlsqr8g5Y6oS5dX1XV7vbTUhVoadRwS4qqUkmPL3sZ70e+8LmuuqULtrrbbp1WVvQGvTwWH0Jp8A2FPGaiBlix8Gg9lzBs87Gh1YvnsN5mctQU7ZHtfx2IAozE2aiqnx42C32Nx6j0RE1EsDqKeeegrPP/88xo4di7S0NNjt9s4PajDgpptuQm/AAIqIiIh6u7IqR3v7XpUOPZdQSnbna2zqeui5zJGSKimplnK28kWH+cFi5gyf7tLS4EBd9kbUZKSjdtcatDhqXOcMVhvsyaO0Tc+eNApGL88JZzJLcrU9b/nu1WhobtRjXmYvTI0dqzvoJQTFuPsWiYioNwVQAwYMOPyDGgzYvn07egMGUEREROSJmmXo+YGa782WKi6t7fJ6k9GA6DBf17DzhMi2qqmQAA49P16tzU3anqdzozJWobm6zHXOYLLAljAMdhlinjJWK6U8QU1DLb7NXalhVH5lket4SnC8BlETY0bDy8xKPCKi3o674J2gJ4uIiIiot6t1yNDzKuRqC1+FK6CqcXQ99NzHZtEgylUtJfOlwv1h49DzY9La2oL6gkxt05NAqrG08OBJgxHeMQPaKqPSxsESEIbeTn7XvX3/LszPWqrDy5tbmvW4j8WG6QkTtUUvyj/c3bdJREQ9uQXvoosuQv/+/b93bu/evfjPf/6Du+66C70BAygiIiLq6+THwf3ldQcrpWS2VFEl9u6rRktXU89l17MQu2umVILMmIr0R3iIj1ZS0ZE/740H9uhuejU7VqKhOKfTeWv/BA2jfAaMhyU0ptcP9C53VOKbnO+0Kmp/TYnr+OCwVB1aPi5qOMwm7uZIRNSbnPAAauDAgXj77bcxbNiw75377LPPcPvtt2Pz5s3oDRhAEREREXWtsalZQ6ic9mHnbQFVBUorux56brW0Dz0Pb6uUcg4+D/D14lN8BBrL96E2Y5VWRzn27Oi0o54lOEJ305NAyisyGQZD753X1dLago1F27AgcynWFm7WIE4EePtjVsIkzE6agjCfEHffJhERuSuAuuSSS7Bx40Z9Xz7kcL+BGTp0KN555x30BgygiIiIiI5ORXV9p134NJwqqkJDY1t71aGC/LwOVku1t/DF9PfTwIq61lxTgZpdq1G7cxVqczYCzQdbJE2+wfBJHauBlC1uMAy9uGroQE0pFmUvx+Ls5ShzVOgxAwwYGTFYZ0WNDB8Mo7H3hm1ERJ5u9okIoDIzM/Hll19q+PT000/jwgsvRHj4wX7txsZGWCwWBAYGYt68eQgL6x096wygiIiIiI5fc0sriktqkNPewucMqApLDu7+1pHRaEBUPxl63l4pJRVT4f7oF2Tr9a1m3a2lvg61Weva5kZlrkNrQ53rnNHbB/bk0VoZZUscAaPVG71RU0sz1uRvxIKsJdhcvNN1PNQejDlJU7QyKtDmGQPaiYg8yQlvwXvyySdhNpuxfv16PP/883osPT0dv//973HjjTfiiiuuQG/BAIqIiIjoxKmrb8JuCaM67MQnwVR1XWOX19u9zVohJYGUa/B5hD/s3ha+TNKJ0NSIutxNbXOjMlahpbbS9bwYzFbYEofDJ20C7CmjYbL59crnrKCqGAuzlum8qOqGtgDTZDBibPQIzEuaisFhaQwpiYh6YaZyTPW6Pj4++Nvf/tYpaIqNjcWpp56Khx56CF5eXjqknIiIiIj6NtktLy0uWJeT/P6ztNKhs6Vcg88LZeh5FWodTdieW6qro7AgG+Lbh507Z0xFhvrAZOpb7VkGs0UrnmSFnnYDHHt36m56Ekg1VcgMqdW6ZEc9ac/TuVGp42D27z0zlSL9+uOqERfgkiFnYeXe9ViQuQQ7S7Kxcs86XRF+YTq0fEb8BPh6+bj7domI6AgdUwWUtNhJC94NN9zwvXPPPvssPvnkEx1G3huwAoqIiIioZ2hsakH+/mrkFlQcnC1VWIkDFY4ur7eYjTpLytXG197KF+TXO9vQjof8SN9QnNvWppeRjoZ9uzud94pMgU/aOA2krCFR6G1yy/ZiYdZSLMlLh6OpbQi+xWTBpJjRmJs0FSkhCayKIiLyxBa84cOHa9A0ceLE75377rvvtA3PObC8p2MARURERNSzVdU2dNiF7+CMKUdD10PPA3yt7YFUAOIjJKAKQEy4H7z60NDzxtJCDaOkMqo+/+BMJWEJjdaZUbKs4Ym9Kripa3RgWd5qzM9agrzyva7j8YHRWhU1JW4sbJa+F0ASEXlsAHX66adjzpw5+N3vfve9c0888YRWP3311VfoDRhAEREREfU+LTL0vLS2w2ypCg2oCg7UoKufbo0GICLUt62Fr0PFVFiQXQeie7KmqjLUZsjMqHTU5W4BWg4Gd2b/UNjTxmkY5R0zEAZj7wjp5J8wu0pysCBrKVbsWYvG5raZYjazN6bGjcPc5KmIC4x2920SEXm82Sc6gHrppZfw6KOP4qqrrtIgKiQkBKWlpfj666/x3//+V4eRX3PNNegNGEAREREReQ5HQxP2FFdplZQznJJZU1JF1RWbl0mHnsuwcxl6Hh8ZoO/72jxz6Hmzowa1mWt1blRt1nq0Nra1swmjzQ/2lLHaqifDzI1mK3qD6voafJO7UnfQK6za5zqeFpKIucnTMCFmFKwmz3w9iYg8PoASDz/8MF599VU0Nx/8DYrJZMJPf/pT/OEPf0BvwQCKiIiIyLPJj7tlVfWd2vfk7e7iKjQ1t3T5MaGBMvS8c7VUVJgvzB409LylsR512Ru1Mqp21xq01FW7zhks3rAnj9TKKHvSKBi9fXrF67x1307Mz1qK1Xs3oLm17bX1tfpgRsJEnRUlA8yJiKiXBVCiqqoKGzZsQHl5Ofz9/TFs2DAEBQWhN2EARURERNQ3SfhUIEPPO+zEJ2t/WV2X15tNBh167qqWipBqKT8E+3v3qjlKXWltaYZj9zbX3KjmqpKDJ41m2OKHtg0xlx31fAPR05XVVeDrnBVYmLUMB2oP7qg4tP8ADaLGRA2HuZe0GxIR9WQnLYDyBAygiIiIiKij6rpG18Bz1+DzwkrU1Td1+UT52duHnneYLxXb3w/eXuZe+cTKPw/qC7O0TU8CqcaS/A5nDfCKTmsfYj4OlqBw9GQtLS1YX7QV8zOXYEPhVrSi7Z8+Qd4BmJU4GbOTJv9/e/cB30Z9/3/8Y8vyXrETx4mz994TsiAQ9ijQslsoo7S0lPZPKVDKr5S2UELLKIWWFjoYhbJHIUCYAUISEsiezk6cOIkd7yXZ/8fne7rTSZYcp40SO3k9W6F1Op1OsqJ73+f7OemYmnOkFxMA2i0CqBitLAAAABybNJQpLq2RzTvLZHNgCJ+GUlpB1Rhhd64WROXnppkwSqulegYCqvyctHbX9Lx+73ZTFaWBVF3RhpD7EvN6Sqp9RL28nm26Eqy4ap+8V/iJvL/xUymrqzC36fKO7TLcNC0fmT9E4uOOniGWAHA4EEDFaGUBAAAAbnUNfqfpud1bSgOq/RXB5t5uSYna9DzDGb7X25xnSmZa+2j47Svfa8IorYzSIXsS6LOkErI7ByqjJkpStwES10bDHJ/fJwt3LDVNy1cWr3Nu75SWa4bnndB7smQlZx7RZQSA9oIAKkYrCwAAAGiN0orawPC9CtlcVGaqpbbtqpB6X+Sm59pHSiuknGqpLpnSLS9DvAltM8RR/uoKqV6/yARSNZuWSpMveKRBT1q2pA7QI+pNlJRewySujR6Fbkf5Lnm3cJ58tGm+VDVYvb888R6Z2G20zOo7VQZ36t+mq7oA4EgjgIrRygIAAAD+W35ter63KlgpFegttbukOuL0nvg46ZaXHqyW6pplgqncrLbX9LyxvkaqN34l1TpUT4+oVxd8TXFJqZLab0zgiHqjJT4xRdqaOl+9zN+22PSK2lCy2bm9IDPfVEVN7zVJ0hJTj+gyAkBbRAAVo5UFAAAAHGrVtQ2ydVeFbNJAameZbNmlQ/rKpKo2ctPztBSv0+zcbn7eMz9TUtpI0/Mmf4PUbF5h9Y1at1D8Vfud+7QSKqXPSCuM6j9OPKltb6jbxpKtMrdwnszbukjqfNZQykSPV47vMd6EUf1yex3pRQSANoMAKkYrCwAAADhcTc/37K8JOQqfnrYXV0pjpK7nok3PU00gpUP4rN5SGdKlY7qppDpSmpoapW7HOtMzSgMpX+mu4J1x8ZLcY7DVN2rABEnI6iRtSXV9jczbslDeKfxYtpXtdG7v06GHCaKO7zlekhOSjugyAsCRRgAVo5UFAAAAHEkNPr8JoTYFhvBZAVWZlJRHbnqe6PVID216nm9VStlVU1npSUckVGvYs9UJo+p3bwpd1vy+kjZwggmkvB27tZlhhrrca/duNEHU59uWiK/RqkxL8SbL9J6TzBH0umd1PdKLCQBHBAFUjFYWAAAA0BaVVdY16y2lQ/nqG/wRp++QkeQ0O+8dGMLXvXOGCawOl4b9u00YpX2jaret0ajHuc+b01VSTRg1SZK69m0zR9Qrr6uUDzfNN43Ld1fucW4f3KmfqYrS5uXeNtpwHQBigQAqRisLAAAAaC/8jU2ye1+V6S3lDOXbWS67SqqkKcIovvj4OCnolGaanrt7THXqkBLzaiRf5f7AEfUWSM3m5SL+YP8rT0aOGaKnlVHJPYZInOfI97pqbGqUFbvXmqblX+xcZq6rjKR0OaH3cXJy3ynSOb1tDSkEgFgggIrRygIAAADau5o6n2zVail3f6md5VJZ0xBx+tTkBFMh5R7Cp6fU5NhU+ugR9Ko3LLGqowqXSFN9rXNffHK6aV6uQ/VS+oySeO+R78FUUr1f3t/0qcwt/ERKaoIN10fmDzFVUWO7DhdP/OGrLAOAw4kAKkYrCwAAADgaaZ+jkvJa01vK3fh8e3GF+PyRm57ndUixqqU0mAoEVF07ponHc+iGyzX66qV203Krb9T6RdJYXe7cF+dNMiGUhlGp/caJJyVdjiR/o1+WFK0wVVFLd61ybs9JyZaZfY6XmX2mSE5q9hFdRgA41AigYrSyAAAAgGNJg69RduypDFRJlTmNz/eWBauS3LwJ8aaXlLtSSoOpDhnJ//OyNDX6Ta8oq2/UAvGV7w3eGe+RlJ7DrDBKj6iXkSNH0q7KPaYi6oNNn0lFXaW1iHHxMq7rCNO0fHjnQeY6ALR3BFAxWlkAAAAARCqq60MqpexgqrY+ctPzrPREE0Zp4/PeJpjKku75GZL0XzY914qt+l2brMqodQukYc+2kPuTCgaYnlEaSGlD8yOlwd8gC7Z/Je8Wfiyr92xwbtf+UNonakbv4yQz6chWbgHAMRNANTY2ysMPPyzPP/+8VFRUyPjx4+WOO+6Q7t27R5y+oaFBHnroIXnllVfM9MOGDZOf/exnMnjw4P/q+QmgAAAAgP9dozY9L6kOCaQ2F5XJzr1Rmp7HiXTpmN6st1Reh1TTEP1gNJTslKq1C6VqzedSt3N9yH3eTt0lbYCGURMlMb93zBuqR7OtbKe8u2GefLTlc6lpsCrIEuITZFL3MTKr71QZ2LHvEVs2ADgmAigNn5566im55557JD8/X2bPni3bt2+X119/XRITE5tNr2HThx9+aKbv2rWrPPjgg7J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     },
     "metadata": {},
     "output_type": "display_data",
     "jetTransient": {
      "display_id": null
     }
    }
   ],
   "execution_count": 10
  }
 ],
 "metadata": {
  "kernelspec": {
   "name": "python3",
   "language": "python",
   "display_name": "Python 3 (ipykernel)"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}