exam(1).ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "9caca0ed",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Importing the libraries required\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "f5d20fbc",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Loading the dataset for analysis\n",
    "df=pd.read_csv(\"metadata.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "323de7ef",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>patientid</th>\n",
       "      <th>offset</th>\n",
       "      <th>sex</th>\n",
       "      <th>age</th>\n",
       "      <th>finding</th>\n",
       "      <th>survival</th>\n",
       "      <th>intubated</th>\n",
       "      <th>intubation_present</th>\n",
       "      <th>went_icu</th>\n",
       "      <th>in_icu</th>\n",
       "      <th>...</th>\n",
       "      <th>date</th>\n",
       "      <th>location</th>\n",
       "      <th>folder</th>\n",
       "      <th>filename</th>\n",
       "      <th>doi</th>\n",
       "      <th>url</th>\n",
       "      <th>license</th>\n",
       "      <th>clinical_notes</th>\n",
       "      <th>other_notes</th>\n",
       "      <th>Unnamed: 28</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>M</td>\n",
       "      <td>65.0</td>\n",
       "      <td>COVID-19</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>January 22, 2020</td>\n",
       "      <td>Cho Ray Hospital, Ho Chi Minh City, Vietnam</td>\n",
       "      <td>images</td>\n",
       "      <td>auntminnie-a-2020_01_28_23_51_6665_2020_01_28_...</td>\n",
       "      <td>10.1056/nejmc2001272</td>\n",
       "      <td>https://www.nejm.org/doi/full/10.1056/NEJMc200...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>On January 22, 2020, a 65-year-old man with a ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>3.0</td>\n",
       "      <td>M</td>\n",
       "      <td>65.0</td>\n",
       "      <td>COVID-19</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>January 25, 2020</td>\n",
       "      <td>Cho Ray Hospital, Ho Chi Minh City, Vietnam</td>\n",
       "      <td>images</td>\n",
       "      <td>auntminnie-b-2020_01_28_23_51_6665_2020_01_28_...</td>\n",
       "      <td>10.1056/nejmc2001272</td>\n",
       "      <td>https://www.nejm.org/doi/full/10.1056/NEJMc200...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>On January 22, 2020, a 65-year-old man with a ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>5.0</td>\n",
       "      <td>M</td>\n",
       "      <td>65.0</td>\n",
       "      <td>COVID-19</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>January 27, 2020</td>\n",
       "      <td>Cho Ray Hospital, Ho Chi Minh City, Vietnam</td>\n",
       "      <td>images</td>\n",
       "      <td>auntminnie-c-2020_01_28_23_51_6665_2020_01_28_...</td>\n",
       "      <td>10.1056/nejmc2001272</td>\n",
       "      <td>https://www.nejm.org/doi/full/10.1056/NEJMc200...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>On January 22, 2020, a 65-year-old man with a ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2</td>\n",
       "      <td>6.0</td>\n",
       "      <td>M</td>\n",
       "      <td>65.0</td>\n",
       "      <td>COVID-19</td>\n",
       "      <td>Y</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>January 28, 2020</td>\n",
       "      <td>Cho Ray Hospital, Ho Chi Minh City, Vietnam</td>\n",
       "      <td>images</td>\n",
       "      <td>auntminnie-d-2020_01_28_23_51_6665_2020_01_28_...</td>\n",
       "      <td>10.1056/nejmc2001272</td>\n",
       "      <td>https://www.nejm.org/doi/full/10.1056/NEJMc200...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>On January 22, 2020, a 65-year-old man with a ...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>0.0</td>\n",
       "      <td>F</td>\n",
       "      <td>52.0</td>\n",
       "      <td>COVID-19</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</td>\n",
       "      <td>January 25, 2020</td>\n",
       "      <td>Changhua Christian Hospital, Changhua City, Ta...</td>\n",
       "      <td>images</td>\n",
       "      <td>nejmc2001573_f1a.jpeg</td>\n",
       "      <td>10.1056/NEJMc2001573</td>\n",
       "      <td>https://www.nejm.org/doi/full/10.1056/NEJMc200...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>diffuse infiltrates in the bilateral lower lungs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 29 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   patientid  offset sex   age   finding survival intubated  \\\n",
       "0          2     0.0   M  65.0  COVID-19        Y       NaN   \n",
       "1          2     3.0   M  65.0  COVID-19        Y       NaN   \n",
       "2          2     5.0   M  65.0  COVID-19        Y       NaN   \n",
       "3          2     6.0   M  65.0  COVID-19        Y       NaN   \n",
       "4          4     0.0   F  52.0  COVID-19      NaN       NaN   \n",
       "\n",
       "  intubation_present went_icu in_icu  ...              date  \\\n",
       "0                NaN      NaN    NaN  ...  January 22, 2020   \n",
       "1                NaN      NaN    NaN  ...  January 25, 2020   \n",
       "2                NaN      NaN    NaN  ...  January 27, 2020   \n",
       "3                NaN      NaN    NaN  ...  January 28, 2020   \n",
       "4                NaN      NaN    NaN  ...  January 25, 2020   \n",
       "\n",
       "                                            location  folder  \\\n",
       "0        Cho Ray Hospital, Ho Chi Minh City, Vietnam  images   \n",
       "1        Cho Ray Hospital, Ho Chi Minh City, Vietnam  images   \n",
       "2        Cho Ray Hospital, Ho Chi Minh City, Vietnam  images   \n",
       "3        Cho Ray Hospital, Ho Chi Minh City, Vietnam  images   \n",
       "4  Changhua Christian Hospital, Changhua City, Ta...  images   \n",
       "\n",
       "                                            filename                   doi  \\\n",
       "0  auntminnie-a-2020_01_28_23_51_6665_2020_01_28_...  10.1056/nejmc2001272   \n",
       "1  auntminnie-b-2020_01_28_23_51_6665_2020_01_28_...  10.1056/nejmc2001272   \n",
       "2  auntminnie-c-2020_01_28_23_51_6665_2020_01_28_...  10.1056/nejmc2001272   \n",
       "3  auntminnie-d-2020_01_28_23_51_6665_2020_01_28_...  10.1056/nejmc2001272   \n",
       "4                              nejmc2001573_f1a.jpeg  10.1056/NEJMc2001573   \n",
       "\n",
       "                                                 url  license  \\\n",
       "0  https://www.nejm.org/doi/full/10.1056/NEJMc200...      NaN   \n",
       "1  https://www.nejm.org/doi/full/10.1056/NEJMc200...      NaN   \n",
       "2  https://www.nejm.org/doi/full/10.1056/NEJMc200...      NaN   \n",
       "3  https://www.nejm.org/doi/full/10.1056/NEJMc200...      NaN   \n",
       "4  https://www.nejm.org/doi/full/10.1056/NEJMc200...      NaN   \n",
       "\n",
       "                                      clinical_notes other_notes Unnamed: 28  \n",
       "0  On January 22, 2020, a 65-year-old man with a ...         NaN         NaN  \n",
       "1  On January 22, 2020, a 65-year-old man with a ...         NaN         NaN  \n",
       "2  On January 22, 2020, a 65-year-old man with a ...         NaN         NaN  \n",
       "3  On January 22, 2020, a 65-year-old man with a ...         NaN         NaN  \n",
       "4   diffuse infiltrates in the bilateral lower lungs         NaN         NaN  \n",
       "\n",
       "[5 rows x 29 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f493eb56",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 372 entries, 0 to 371\n",
      "Data columns (total 29 columns):\n",
      " #   Column                  Non-Null Count  Dtype  \n",
      "---  ------                  --------------  -----  \n",
      " 0   patientid               372 non-null    int64  \n",
      " 1   offset                  276 non-null    float64\n",
      " 2   sex                     329 non-null    object \n",
      " 3   age                     318 non-null    float64\n",
      " 4   finding                 372 non-null    object \n",
      " 5   survival                116 non-null    object \n",
      " 6   intubated               72 non-null     object \n",
      " 7   intubation_present      77 non-null     object \n",
      " 8   went_icu                35 non-null     object \n",
      " 9   in_icu                  7 non-null      object \n",
      " 10  needed_supplemental_O2  12 non-null     object \n",
      " 11  extubated               23 non-null     object \n",
      " 12  temperature             35 non-null     float64\n",
      " 13  pO2_saturation          44 non-null     float64\n",
      " 14  leukocyte_count         11 non-null     float64\n",
      " 15  neutrophil_count        2 non-null      float64\n",
      " 16  lymphocyte_count        10 non-null     float64\n",
      " 17  view                    372 non-null    object \n",
      " 18  modality                372 non-null    object \n",
      " 19  date                    291 non-null    object \n",
      " 20  location                254 non-null    object \n",
      " 21  folder                  372 non-null    object \n",
      " 22  filename                372 non-null    object \n",
      " 23  doi                     104 non-null    object \n",
      " 24  url                     372 non-null    object \n",
      " 25  license                 206 non-null    object \n",
      " 26  clinical_notes          362 non-null    object \n",
      " 27  other_notes             234 non-null    object \n",
      " 28  Unnamed: 28             4 non-null      object \n",
      "dtypes: float64(7), int64(1), object(21)\n",
      "memory usage: 84.4+ KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "9ef3a6c0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "patientid                   0\n",
       "offset                     96\n",
       "sex                        43\n",
       "age                        54\n",
       "finding                     0\n",
       "survival                  256\n",
       "intubated                 300\n",
       "intubation_present        295\n",
       "went_icu                  337\n",
       "in_icu                    365\n",
       "needed_supplemental_O2    360\n",
       "extubated                 349\n",
       "temperature               337\n",
       "pO2_saturation            328\n",
       "leukocyte_count           361\n",
       "neutrophil_count          370\n",
       "lymphocyte_count          362\n",
       "view                        0\n",
       "modality                    0\n",
       "date                       81\n",
       "location                  118\n",
       "folder                      0\n",
       "filename                    0\n",
       "doi                       268\n",
       "url                         0\n",
       "license                   166\n",
       "clinical_notes             10\n",
       "other_notes               138\n",
       "Unnamed: 28               368\n",
       "dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "7f778b82",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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wGJlMptb8w807jDHGWPlVKjUoOTk5WL9+PQYNGgQjo//FQOnp6Zg4cSJOnz6Nu3fvIjo6Gt26dYO1tTX8/PxKoyiMMcYYK4NKpQbl0KFDuH//PoYMGaKSbmhoiEuXLmHTpk14/vw57Ozs4O3tje3bt8Pc3Lw0isIYY4yxMqhUAhQfHx8QkVq6qakpDhw4UBpPyRhjjLFy5KNei4dH3zCmPZ6ojTH2PnzUAQpjTHscXDD28dLFD5SoHHHHcYDCGGOMMVHe5w+UUglQXr58iWnTpiEiIgKpqalo2LAhQkJC0KRJEwAAEWHmzJlYu3Ytnj17hqZNm+Knn36Cm1vJJl5j+kFfms74l746/tswxsqKUglQhg0bhsTERGzevBn29vbYsmUL2rdvjytXruCTTz7BggULsGTJEmzYsAG1atXC7Nmz0aFDB1y/fp1H8zBWijgwYIyVFRLSNNymBF6/fg1zc3Ps2bNHZZK2Bg0aoGvXrvjxxx9hb2+PcePGYfLkyQBy19qxtbXF/Pnz8dVXX4l6ng4GfXRZbFYO8ZexOq5B0T19eU2ZOl28z/SlU7i+vM90cS0GihvijivxM73j7du3yM7OhomJiUq6qakpTpw4gaSkJKSkpMDHx0fYJ5PJ0KZNG5w6dUrXxWGMMcZYGaTzJh5zc3M0b94cP/74I+rUqQNbW1ts27YNf/31F1xcXJCSkgIAsLW1VTnP1tYW9+7d03VxmJbK0y9bxhhjZVepTHW/efNmEBE++eQTyGQyLF++HP3794eh4f/Wz5FIJCrnEJFaWh6lUokXL16obDmUXRpFZ4wxxpgeKJVOsjVq1EBMTAwyMjLw4sUL2NnZwd/fH87OzlAoFACAlJQUlQUCU1NT1WpV8gQHB2PmzJkqac6ogxrgUT+6pi/tnLrAtUHqylNbOGOsfCvVeVAqVKiAChUq4NmzZzhw4AAWLFggBClRUVFo2LAhACAzMxMxMTGYP3++xnyCgoIwYcIElTQ/eUCJy6erL7DydMPmL/XyrTy9Vxlj5VupBCgHDhwAEcHV1RW3bt3CpEmT4OrqisGDB0MikWDcuHGYO3cuXFxc4OLigrlz58LMzAz9+/fXmJ9MJoNMJlNJM5AYajxWG3yzZowxxvRTqQQoaWlpCAoKwt9//w1LS0v07t0bc+bMgbGxMQDg22+/xevXrzFy5EhhoraDBw++9zlQuAaFfWy4iYcxVlaUSoDSt29f9O3bt8D9EokEM2bMwIwZM0rj6VkJ6MuYf8YYYx83XouHqeDggjHGmD74qAMUrqpmjDHG9NNHHaBwHxTGtMe1bIyx9+GjDlA4sGCMMcb0k9YzyR47dgzdunWDvb09JBIJdu/erbKfiDBjxgzY29vD1NQUXl5euHz5ssoxXl5ekEgkKlu/fv1KdCGMMcYYKz+0DlAyMjJQv359rFy5UuP+BQsWYMmSJVi5ciXOnj0LhUKBDh064OXLlyrHDR8+HMnJycK2Zs2a4l0BY4wxxsodrZt4fH194evrq3EfEWHZsmX47rvv0KtXLwDAxo0bYWtri61bt+Krr74SjjUzMxOmvWf6g4cZl2/60qzJ7xHGWFF0ulhgUlISUlJS4OPjI6TJZDK0adMGp06dUjk2LCwM1tbWcHNzw8SJE9VqWBhjjDH28dJpJ9mUlBQAUFv0z9bWFvfu3RMeDxgwQFiTJzExEUFBQbhw4QKioqJ0WRzG2Du45oIxVlaUyigeiUSi8piIVNKGDx8u/N/d3R0uLi7w9PREfHw8GjVqpJafUqmEUqlUScuhbJ2sx8MYY4wx/aPTACWvT0lKSgrs7OyE9NTUVLValfwaNWoEY2Nj3Lx5U2OAEhwcjJkzZ6qkOaMOasCtROXleVDU8S9sxhhj+kCnAUpes01UVBQaNmwIAMjMzERMTAzmz59f4HmXL19GVlaWSlCTX1BQECZMmKCS5icPKHF5y1NgwRhjjJUnWgco6enpuHXrlvA4KSkJCQkJsLS0RNWqVTFu3DjMnTsXLi4ucHFxwdy5c2FmZob+/fsDAG7fvo2wsDB07twZ1tbWuHLlCgIDA9GwYUO0bNlS43PKZDLIZDKVNG7eYUx7PEqLMVZWaB2gnDt3Dt7e3sLjvJqNQYMGYcOGDfj222/x+vVrjBw5Es+ePUPTpk1x8OBBmJubAwCkUikOHz6MkJAQpKenw9HREV26dMH06dNhaMhBB2OlSV+CCw6UGGNFkRARfehCFEcHgz4fugisAPzFwT4m3FTMiqKLe2J5CuoNFDfEHVfK5WCMMcYY09pHvVggKx368otSX34tMMYY0x7XoDDGGGNM73CAwhhjjDG9o3UTz7Fjx7Bw4ULExcUhOTkZERER6NmzJwAgKysL33//Pfbv3487d+5ALpejffv2mDdvHuzt7YU8lEolJk6ciG3btuH169do164dVq1aBQcHB51dGPtwuGmFMcb+R1+avcsarWtQMjIyUL9+faxcuVJt36tXrxAfH49p06YhPj4eu3btwo0bN9C9e3eV48aNG4eIiAiEh4fjxIkTSE9PR9euXZGdnV38K2GMMcZYuVGiYcYSiUSlBkWTs2fP4tNPP8W9e/dQtWpVpKWloUqVKti8eTP8/f0BAP/88w8cHR2xf/9+dOzYUdRz62KYMU91r45rPxjTTnn6/LPSwcOMVenNMOO0tDRIJBJYWFgAAOLi4pCVlQUfHx/hGHt7e7i7u+PUqVOlXRzGGGOMlQGlGqC8efMGU6ZMQf/+/VGpUiUAuQsJSqVSVK5cWeVYW1tbpKSklGZxGGOMMVZGlNo8KFlZWejXrx9ycnKwatWqIo8nIkgkEo37lEollEqlSloOZevNejz6Um3GVc2MsZLgZu/Swa9H8ZRKDUpWVhb69u2LpKQkREVFCbUnAKBQKJCZmYlnz56pnJOamgpbW1uN+QUHB0Mul6tsSbhWGkVnjDHGmB7QeYCSF5zcvHkThw4dgpWVlcr+xo0bw9jYGFFRUUJacnIyEhMT0aJFC415BgUFIS0tTWVzRm1dF50xxhhjekLrJp709HTcunVLeJyUlISEhARYWlrC3t4e//nPfxAfH48//vgD2dnZQr8SS0tLSKVSyOVyDB06FIGBgbCysoKlpSUmTpwIDw8PtG/fXuNzymQyyGQylTR9ad5hjDHGmO5pHaCcO3cO3t7ewuMJEyYAAAYNGoQZM2Zg7969AIAGDRqonHf06FF4eXkBAJYuXQojIyP07dtXmKhtw4YNMDTkoIMxxhhjxQhQvLy8UNjUKWKmVTExMcGKFSuwYsUKbZ+eMcYYYx8BXouHMcYYY3qHAxTGGGOM6R0OUBhjjDGmdzhAYYwxxpje0XqxwGPHjmHhwoWIi4tDcnKy2mKBM2bMQHh4OB48eACpVIrGjRtjzpw5aNq0qXCMl5cXYmJiVPL19/dHeHi46HLoYrFAXeGZZFXpy+vB2PugL587xt4HXdzfS22xwIyMDNSvXx8rV67UuL9WrVpYuXIlLl26hBMnTqBatWrw8fHBv//+q3Lc8OHDkZycLGxr1qzRtiiMMcYYK6e0Hmbs6+sLX1/fAvf3799f5fGSJUuwbt06XLx4Ee3atRPSzczMoFAotH16xhhjjBVDWavdLtU+KJmZmVi7di3kcjnq11etBg0LC4O1tTXc3NwwceJEvHz5sjSLwhhjjLEypFRWM/7jjz/Qr18/vHr1CnZ2doiKioK1tbWwf8CAAXB2doZCoUBiYiKCgoJw4cIFlfV5yhJug2aMMVYQXdRcfIzfM6USoHh7eyMhIQGPHz/Gzz//jL59++Kvv/6CjY0NgNz+J3nc3d3h4uICT09PxMfHo1GjRmr5KZVKKJVKlbQcyub1eBhjjLFyqlQClAoVKqBmzZqoWbMmmjVrBhcXF6xbtw5BQUEaj2/UqBGMjY1x8+ZNjQFKcHAwZs6cqZLmjDqoAbfSKP5Hray1UTLt6OJXmL78GuT3KiuKvrxX9UVZ+9yVSoDyLiJSqwHJ7/Lly8jKyoKdnZ3G/UFBQcKihHn85AG6LCJjHwV9uWFzcMEYK4rWAUp6ejpu3bolPE5KSkJCQgIsLS1hZWWFOXPmoHv37rCzs8OTJ0+watUq/P333+jTJ3fektu3byMsLAydO3eGtbU1rly5gsDAQDRs2BAtW7bU+JwymQwymUwljZt3GGOMsfJL6wDl3Llz8Pb2Fh7n1WwMGjQIq1evxrVr17Bx40Y8fvwYVlZWaNKkCY4fPw43t9zmGKlUisOHDyMkJATp6elwdHREly5dMH36dBgactDxoZWn6szy9CtdV38XfXlNuBaGMVYUrQMULy8vFDb57K5duwo939HRUW0WWcZY2cGBAWPsfeC1eBhjjDGmd95LJ1lWdvCvY/3Ef5fSUZ6aNBkrbzhA0RP6MrqC+wawj4m+fO5Y6eC/jaqydm/mJh7GGGOM6R2ta1COHTuGhQsXIi4uDsnJyYiIiEDPnj2F/QEBAdi4caPKOU2bNkVsbKzwWKlUYuLEidi2bRtev36Ndu3aYdWqVXBwcCj+lRSDrqJJfam50IWyFmEzxnRHn+6JulCeasj05Vr0eqK2jIwM1K9fH4MHD0bv3r01HtOpUyesX79eeCyVSlX2jxs3Dr///jvCw8NhZWWFwMBAdO3aFXFxcTzUmDHGPhB9+TIub/h1LR6tAxRfX1/4+voWeoxMJoNCodC4Ly0tDevWrcPmzZvRvn17AMCWLVvg6OiIQ4cOoWPHjtoWqdj4TaOurEXYjDFWEL7Hqypr9+ZS6SQbHR0NGxsbWFhYoE2bNpgzZ46wUGBcXByysrLg4+MjHG9vbw93d3ecOnXqvQYoTF1ZewMzxlhBylOziL50JXif3xE67yTr6+uLsLAwHDlyBIsXL8bZs2fRtm1bYS2elJQUSKVSVK5cWeU8W1tbpKSk6Lo4jDHGGCuDdF6D4u/vL/zf3d0dnp6ecHJywr59+9CrV68CzyMiSCQSjfuUSqXaYoM5lF2u1uPRlwibMcYY0welPg+KnZ0dnJyccPPmTQCAQqFAZmYmnj17plKLkpqaihYtWmjMIzg4GDNnzlRJc0Yd1IBb6RX8PePggjH2oZW3UTysbCv1AOXJkyd48OAB7OzsAACNGzeGsbExoqKi0LdvXwBAcnIyEhMTsWDBAo15BAUFCYsS5vGTB5RquT9W5enGwv1pGGOs7NI6QElPT8etW7eEx0lJSUhISIClpSUsLS0xY8YM9O7dG3Z2drh79y6mTp0Ka2tr+Pn5AQDkcjmGDh2KwMBAWFlZwdLSEhMnToSHh4cwquddMpkMMplMJa08Ne/oE25qYowxpg+0DlDOnTsHb29v4XFezcagQYMQGhqKS5cuYdOmTXj+/Dns7Ozg7e2N7du3w9zcXDhn6dKlMDIyQt++fYWJ2jZs2MBzoJQTXHPBWNnEPy6YPtE6QPHy8gIRFbj/wIEDReZhYmKCFStWYMWKFdo+PWOsBMraMEPG2Mfro14skDuEsY8NBxeMsbLiow5QOLBgjDHG9BOvZswYY4wxvcMBCmOMMcb0jtZNPMeOHcPChQsRFxeH5ORkREREoGfPnirHXL16FZMnT0ZMTAxycnLg5uaG3377DVWrVgWQ29E2JiZG5Rx/f3+Eh4cX/0qYTnAnSsY+Xtwvr3Tw61E8WtegZGRkoH79+li5cqXG/bdv30arVq1Qu3ZtREdH48KFC5g2bRpMTExUjhs+fDiSk5OFbc2aNcW7AsYYY4yVO1rXoPj6+sLX17fA/d999x06d+6sMits9erV1Y4zMzODQqHQ9ukZY4wx9hHQ6SienJwc7Nu3D99++y06duyI8+fPw9nZGUFBQWrNQGFhYdiyZQtsbW3h6+uL6dOnq0zmxj4Mbp5hjDGmD3TaSTY1NRXp6emYN28eOnXqhIMHD8LPzw+9evVS6XMyYMAAbNu2DdHR0Zg2bRp27txZ6ErHjDHGGPu46LwGBQB69OiB8ePHAwAaNGiAU6dOYfXq1WjTpg2A3P4nedzd3eHi4gJPT0/Ex8ejUaNGavkqlUoolUrV56JsXo+HMcYYK6d0WoNibW0NIyMj1K1bVyW9Tp06uH//foHnNWrUCMbGxrh586bG/cHBwZDL5SpbEq7psuiMMcYY0yM6rUGRSqVo0qQJrl+/rpJ+48YNODk5FXje5cuXkZWVBTs7O437g4KChEUJ8/jJA0pcXqaOhxkzxhjTB1oHKOnp6bh165bwOCkpCQkJCbC0tETVqlUxadIk+Pv7o3Xr1vD29kZkZCR+//13REdHA8gdhhwWFobOnTvD2toaV65cQWBgIBo2bIiWLVtqfE6ZTAaZTKaSxs07jDHGWPmldYBy7tw5eHt7C4/zajYGDRqEDRs2wM/PD6tXr0ZwcDDGjh0LV1dX7Ny5E61atQKQW8ty+PBhhISEID09HY6OjujSpQumT58OQ0MOOhhjjDFWjADFy8sLRFToMUOGDMGQIUM07nN0dFSbRZYxxhhjLD9ei4cxxhhjeocDFMYYY4zpHQ5QGGOMMaZ3OEBhjDHGmN7ROkA5duwYunXrBnt7e0gkEuzevVtlf3p6OkaPHg0HBweYmpqiTp06CA0NVTlGqVRizJgxsLa2RoUKFdC9e3f8/fffJboQxhhjjJUfWgcoGRkZqF+/PlauXKlx//jx4xEZGYktW7bg6tWrGD9+PMaMGYM9e/YIx4wbNw4REREIDw/HiRMnkJ6ejq5duyI7O7v4V8IYY4yxckPrYca+vr7w9fUtcP/p06cxaNAgeHl5AQC+/PJLrFmzBufOnUOPHj2QlpaGdevWYfPmzWjfvj0AYMuWLXB0dMShQ4fQsWPH4l0J0wmeBZYxxpg+0HkflFatWmHv3r14+PAhiAhHjx7FjRs3hMAjLi4OWVlZ8PHxEc6xt7eHu7s7Tp06peviMMYYY6wM0ulaPACwfPlyDB8+HA4ODjAyMoKBgQF++eUXYSbZlJQUSKVSVK5cWeU8W1tbpKSk6Lo4TEu8Fk/5pi9/X12Ug7Gi6Mv7TF8+M2Xt3lwqAUpsbCz27t0LJycnHDt2DCNHjoSdnZ3QpKMJEUEikWjcp1QqoVQqVdJyKJvX49FT+nJT0IXydmPRlxuUvpRDF8rT+708XQugP59ffXld9aUcUTnijtNpE8/r168xdepULFmyBN26dUO9evUwevRo+Pv7Y9GiRQAAhUKBzMxMPHv2TOXc1NRU2Nraasw3ODgYcrlcZUvCNV0WnTHGGGN6RKc1KFlZWcjKyoKBgWrcY2hoiJyc3JCpcePGMDY2RlRUFPr27QsASE5ORmJiIhYsWKAx36CgIGFRwjx+8gBdFp0xxhhjRXiftZ9aByjp6em4deuW8DgpKQkJCQmwtLRE1apV0aZNG0yaNAmmpqZwcnJCTEwMNm3ahCVLlgAA5HI5hg4disDAQFhZWcHS0hITJ06Eh4dHgU1AMpkMMplMJY2bd0oHV73rXnl6TQH9arJijJVfWgco586dg7e3t/A4r2Zj0KBB2LBhA8LDwxEUFIQBAwbg6dOncHJywpw5c/D1118L5yxduhRGRkbo27cvXr9+jXbt2mHDhg0wNOSggzHGGGPFCFC8vLxARAXuVygUWL9+faF5mJiYYMWKFVixYoW2T88YY4yxj4DOR/Ewxk0r+ktf/jaMMVYUDlAY+4hw0MYYKyt4NWPGGGOM6R0OUBhjjDGmd7Ru4jl27BgWLlyIuLg4JCcnIyIiAj179hT2P3r0CJMnT8bBgwfx/PlztG7dGitWrICLi4twjJeXF2JiYlTy9ff3R3h4ePGvpBh0Vd3N7fqquBmBMcZYSWldg5KRkYH69etj5cqVavuICD179sSdO3ewZ88enD9/Hk5OTmjfvj0yMjJUjh0+fDiSk5OFbc2aNcW/CsYYY4yVK1rXoPj6+sLX11fjvps3byI2NhaJiYlwc3MDAKxatQo2NjbYtm0bhg0bJhxrZmYGhUJRzGLrBtd8MMYYY/pJp6N48hb0MzExEdIMDQ0hlUpx4sQJlQAlLCwMW7Zsga2tLXx9fTF9+nSYm5vrsjhF4iYexhhjTD/pNECpXbs2nJycEBQUhDVr1qBChQpYsmQJUlJSkJycLBw3YMAAODs7Q6FQIDExEUFBQbhw4QKioqI05surGb8/PI05Y4wxfaDTAMXY2Bg7d+7E0KFDYWlpCUNDQ7Rv316tSWj48OHC/93d3eHi4gJPT0/Ex8ejUaNGavkGBwdj5syZKmnOqIMacNNl8RljjDGmJ3Q+zLhx48ZISEjA8+fPkZycjMjISDx58gTOzs4FntOoUSMYGxvj5s2bGvcHBQUhLS1NZXNGbV0XnTHGGGN6otRmkpXL5QByO86eO3cOP/74Y4HHXr58GVlZWbCzs9O4X99XM9aXJg1unmGMlQT3y2P6ROsAJT09Hbdu3RIeJyUlISEhAZaWlqhatSp27NiBKlWqoGrVqrh06RK++eYb9OzZEz4+PgCA27dvIywsDJ07d4a1tTWuXLmCwMBANGzYEC1bttTdlTHGGPuocaBUtmkdoJw7dw7e3t7C4wkTJgAABg0ahA0bNiA5ORkTJkzAo0ePYGdnhy+++ALTpk0TjpdKpTh8+DBCQkKQnp4OR0dHdOnSBdOnT4ehof7UijDGGCvbdFEjxEHOh6N1gOLl5QUiKnD/2LFjMXbs2AL3Ozo6qs0iW9Zx0wpjjDGmW7wWD2OMMcb0Tql1kmXa4WpExhhj7H+4BoUxxhhjeocDFMYYY4zpHa0ClODgYDRp0gTm5uawsbFBz549cf36dZVjdu3ahY4dO8La2hoSiQQJCQlq+SiVSowZMwbW1taoUKECunfvjr///rtEF8IYY4yx8kOrACUmJgajRo1CbGwsoqKi8PbtW/j4+CAjI0M4JiMjAy1btsS8efMKzGfcuHGIiIhAeHg4Tpw4gfT0dHTt2hXZ2dnFvxLGGGOMlRtadZKNjIxUebx+/XrY2NggLi4OrVu3BgAMHDgQAHD37l2NeaSlpWHdunXYvHkz2rdvDwDYsmULHB0dcejQIXTs2FHba2CMMcZYOVOiPihpaWkAAEtLS9HnxMXFISsrS5hZFgDs7e3h7u6OU6dOlaQ4jDHGGCsnij3MmIgwYcIEtGrVCu7u7qLPS0lJgVQqReXKlVXSbW1tkZKSovEcpVIJpVKpkpZD2SVej0dXQ3v1ZZI1XVwPTzrHGGO6xTPaFk+xa1BGjx6NixcvYtu2bTopCBFBIpFo3BccHAy5XK6yJeGaTp6XMcYYY/qnWDUoY8aMwd69e3Hs2DE4ODhoda5CoUBmZiaePXumUouSmpqKFi1aaDwnKChIWPMnj588QOtys6Jx7QdjjDF9oFUNChFh9OjR2LVrF44cOQJnZ2etn7Bx48YwNjZGVFSUkJacnIzExMQCAxSZTIZKlSqpbCVt3mGMMcaY/tKqBmXUqFHYunUr9uzZA3Nzc6HPiFwuh6mpKQDg6dOnuH//Pv755x8AEOZJUSgUUCgUkMvlGDp0KAIDA2FlZQVLS0tMnDgRHh4ewqgexhhjjH3ctKpBCQ0NRVpaGry8vGBnZyds27dvF47Zu3cvGjZsiC5dugAA+vXrh4YNG2L16tXCMUuXLkXPnj3Rt29ftGzZEmZmZvj9999haMi1IowxxhjTsgaFiIo8JiAgAAEBAYUeY2JighUrVmDFihXaPD1jjDHGPhK8Fg9jjDHG9E6x50Fh//Mxjk8vjL68HjwiiTGmD/TlnljWcIDCGGOMMVF0EWxF5Yg7jgMUxhhjjInyPmumtQpQgoODsWvXLly7dg2mpqZo0aIF5s+fD1dXVwBAVlYWvv/+e+zfvx937tyBXC5H+/btMW/ePNjb2wv5eHl5ISYmRiVvf39/hIeH6+CS2IfGTSuMlU3cFMH0iVadZGNiYjBq1CjExsYiKioKb9++hY+PDzIyMgAAr169Qnx8PKZNm4b4+Hjs2rULN27cQPfu3dXyGj58OJKTk4VtzZo1urkixhhjjJV5WtWgREZGqjxev349bGxsEBcXh9atW0Mul6vMEAsAK1aswKeffor79++jatWqQrqZmRkUCkUJis4YY4yx8qpEw4zT0tIAAJaWloUeI5FIYGFhoZIeFhYGa2truLm5YeLEiXj58mVJisIYY4yxcqTYnWSJCBMmTECrVq3g7u6u8Zg3b95gypQp6N+/PypVqiSkDxgwAM7OzlAoFEhMTERQUBAuXLigVvuSR6lUQqlUqqTlUDavx8MYY4yVU8UOUEaPHo2LFy/ixIkTGvdnZWWhX79+yMnJwapVq1T2DR8+XPi/u7s7XFxc4Onpifj4eDRq1Egtr+DgYMycOVMlzRl1UANuxS0+K4AuOslxJ1n9pS+dIPk9wj4muni/68tn932SkJj5698xZswY7N69G8eOHdO4onFWVhb69u2LO3fu4MiRI7Cysio0PyKCTCbD5s2b4e/vr7ZfUw2KnzygxDUourpJlqc3Dn9xMKad8vT5L284MNA9XbymBooboo7Tei2eMWPGICIiAtHR0YUGJzdv3sTRo0eLDE4A4PLly8jKyoKdnZ3G/TKZDDKZTCWNm3cYY4yx8kurAGXUqFHYunUr9uzZA3Nzc6SkpAAA5HI5TE1N8fbtW/znP/9BfHw8/vjjD2RnZwvHWFpaQiqV4vbt2wgLC0Pnzp1hbW2NK1euIDAwEA0bNkTLli11f4WMMcYYK3O0ClBCQ0MB5E60lt/69esREBCAv//+G3v37gUANGjQQOWYo0ePwsvLC1KpFIcPH0ZISAjS09Ph6OiILl26YPr06TA05FoRxhhjjBWjiacw1apVK/IYR0dHtVlkGWOMMcbyK9E8KIwxxhhjpYEDFMYYY4zpHQ5QGGOMMaZ3tApQgoOD0aRJE5ibm8PGxgY9e/bE9evXCzz+q6++gkQiwbJly1TSlUolxowZA2tra1SoUAHdu3fH33//XawLYIwxxlj5o9PVjPPbvXs3/vrrL9jb26vtGzduHCIiIhAeHo4TJ04gPT0dXbt2RXZ2dvGvhDHGGGPlhk5XM87z8OFDjB49GgcOHECXLl1UzklLS8O6deuwefNmtG/fHgCwZcsWODo64tChQ+jYsWNxr0VrPEMgY4wxpp90vppxTk4OBg4ciEmTJsHNTX2tnLi4OGRlZcHHx0dIs7e3h7u7O06dOlWS4jDGGGOsnCh2gFLQasbz58+HkZERxo4dq/G8lJQUSKVSVK5cWSXd1tZWmHWWMcYYYx83na5mHBcXh5CQEMTHx0MikWiVHxEVeI6mxQJzKJvX49FT+tJ0xgsfMqYdXkCV6ZNi1aCMGTMGe/fuxdGjR+Hg4CCkHz9+HKmpqahatSqMjIxgZGSEe/fuITAwENWqVQMAKBQKZGZm4tmzZyp5pqamwtbWVuPzBQcHQy6Xq2xJuFacojPGGGOsDNAqQCEijB49Grt27cKRI0fUVjMeOHAgLl68iISEBGGzt7fHpEmTcODAAQBA48aNYWxsjKioKOG85ORkJCYmokWLFhqfNygoCGlpaSqbM2pre62MMcYYKyN0upqxlZUVrKysVM4xNjaGQqGAq6urcOzQoUMRGBgIKysrWFpaYuLEifDw8BBG9bxLJpNBJpOppHHzDmOMMVZ+6XQ1Y7GWLl0KIyMj9O3bF69fv0a7du2wYcMGXs24nOC+H4wxxkpKp6sZa3L37l21NBMTE6xYsQIrVqzQOj/GGGOMlX+8Fg9jjDHG9A4HKIwxxhjTO8WeB4Ux9nHSxRwX3E+JMVYUDlAY+4jwBFqsMPz+KB26CMg/xr+NVk08wcHBaNKkCczNzWFjY4OePXvi+vXrKscEBARAIpGobM2aNVM5xsvLS+2Yfv36lfxqGGOMMVYuaFWDEhMTg1GjRqFJkyZ4+/YtvvvuO/j4+ODKlSuoUKGCcFynTp2wfv164bFUKlXLa/jw4Zg1a5bw2NTUtDjlZ4xpgX/JMcbKCq0ClMjISJXH69evh42NDeLi4tC6dWshXSaTQaFQFJqXmZlZkccwxhhj7ONUoj4oaWlpAABLS0uV9OjoaNjY2MDCwgJt2rTBnDlzYGNjo3JMWFgYtmzZAltbW/j6+mL69OkwNzcvSXEYY+8Bd3BljL0PxQ5QiAgTJkxAq1at4O7uLqT7+vqiT58+cHJyQlJSEqZNm4a2bdsiLi5OmK5+wIABcHZ2hkKhQGJiIoKCgnDhwgWV9XneB165kzHG/ofviaWDX4/iKXaAMnr0aFy8eBEnTpxQSff39xf+7+7uDk9PTzg5OWHfvn3o1asXgNz+J/mPcXFxgaenJ+Lj49GoUSO151IqlVAqlSppOZTN6/Ewxhhj5VSxApQxY8Zg7969OHbsGBwcHAo91s7ODk5OTrh582aBxzRq1AjGxsa4efOmxgAlODgYM2fOVElzRh3UgFtxii/gqLZ06Mvryk0RjDFWdmk1zJiIMHr0aOzatQtHjhyBs7Nzkec8efIEDx48gJ2dXYHHXL58GVlZWQUeExQUhLS0NJXNGbW1KTpjjDHGyhCtalBGjRqFrVu3Ys+ePTA3N0dKSgoAQC6Xw9TUFOnp6ZgxYwZ69+4NOzs73L17F1OnToW1tTX8/PwAALdv30ZYWBg6d+4Ma2trXLlyBYGBgWjYsCFatmyp8XllMpnQfyUPN+8wxhhj5ZdWAUpoaCiA3InW8lu/fj0CAgJgaGiIS5cuYdOmTXj+/Dns7Ozg7e2N7du3CyN0pFIpDh8+jJCQEKSnp8PR0RFdunTB9OnTYWjIQQdjjDHGtAxQiKjQ/aampjhw4EChxzg6OiImJkabp2VlDPf9YIwxVlK8mjFjjDHG9A4HKIwxxhjTO7yaMdM5HmbMGGOspD7qAIVnTSwdHBgwxhgrKa0ClODgYOzatQvXrl2DqakpWrRogfnz58PV1VU4RiKRaDx3wYIFmDRpEoDcmWEnTpyIbdu24fXr12jXrh1WrVpV5KRvusaBBfvY6OI9ry8rInMgrHvl7Z6oL9fDn5ni0SpAiYmJwahRo9CkSRO8ffsW3333HXx8fHDlyhVUqFABAJCcnKxyzp9//omhQ4eid+/eQtq4cePw+++/Izw8HFZWVggMDETXrl0RFxfHQ40ZK0Vl7QZV2vTlC4wxpk6rACUyMlLl8fr162FjY4O4uDi0bt0aAKBQKFSO2bNnD7y9vVG9enUAuSsgr1u3Dps3b0b79u0BAFu2bIGjoyMOHTqEjh07FvtimH74GCP9soL/NoyxsqJEfVDS0tIAAJaWlhr3P3r0CPv27cPGjRuFtLi4OGRlZcHHx0dIs7e3h7u7O06dOsUBCgPAX6T6TF9qHfSlHOVJeeuXpy9NK/qirN1Xix2gEBEmTJiAVq1awd3dXeMxGzduhLm5ubCKMQCkpKRAKpWicuXKKsfa2toKU+czxkoHB226V56+wBjTJ8UOUEaPHo2LFy/ixIkTBR7z66+/YsCAATAxMSkyPyIqsIOtUqmEUqlUScuhbL1Zj0dfbvr6cqPUl9eDMfZx05d7oi58jPfVYk3UNmbMGOzduxdHjx4tcOTN8ePHcf36dQwbNkwlXaFQIDMzE8+ePVNJT01Nha2trca8goODIZfLVbYkXCtO0RljjDFWBmgVoBARRo8ejV27duHIkSNwdnYu8Nh169ahcePGqF9fNYJt3LgxjI2NERUVJaQlJycjMTERLVq00JhXUFAQ0tLSVDZn1Nam6IwxxhgrQ7Rq4hk1ahS2bt2KPXv2wNzcXOgzIpfLYWpqKhz34sUL7NixA4sXL1bLQy6XY+jQoQgMDISVlRUsLS0xceJEeHh4CKN63iWTySCTyVTS9KV5hzHGGGO6p1WAEhoaCgDw8vJSSV+/fj0CAgKEx+Hh4SAifPbZZxrzWbp0KYyMjNC3b19horYNGza89zlQPsY2PcYYY2VPWRuBowtaBShEJOq4L7/8El9++WWB+01MTLBixQqsWLFCm6dnjDHG2EeCVzNmjDHGmN7hAIUxxhhjeocDFMYYY4zpnRJNdV/WladJfHTlY+yIxd4/fp8xxoqiVYASHByMXbt24dq1azA1NUWLFi0wf/58uLq6Csekp6djypQp2L17N548eYJq1aph7NixGDFihHCMl5cXYmJiVPL29/dHeHh4CS+HMVYWcHDBGCuKVk08MTExGDVqFGJjYxEVFYW3b9/Cx8cHGRkZwjHjx49HZGQktmzZgqtXr2L8+PEYM2YM9uzZo5LX8OHDkZycLGxr1qzRzRUxxhhjrMzTqgYlMjJS5fH69ethY2ODuLg4tG7dGgBw+vRpDBo0SJgr5csvv8SaNWtw7tw59OjRQzjXzMwMCoWihMVnusa/bBljjOmDEvVBSUtLAwBYWloKaa1atcLevXsxZMgQ2NvbIzo6Gjdu3EBISIjKuWFhYdiyZQtsbW3h6+uL6dOnw9zcvCTF0Vp5W1qcMfbx0sX9rLzdy/TlNdGX17Ws9f0qdoBCRJgwYQJatWoFd3d3IX358uUYPnw4HBwcYGRkBAMDA/zyyy9o1aqVcMyAAQPg7OwMhUKBxMREBAUF4cKFCyrr87wP+vKmYawsKWs3OcZY2VTsAGX06NG4ePEiTpw4oZK+fPlyxMbGYu/evXBycsKxY8cwcuRI2NnZCWvtDB8+XDje3d0dLi4u8PT0RHx8PBo1aqT2XEqlEkqlUiUth7J5PR7GPgAOLhhj70Ox5kEZM2YM9u7di6NHj8LBwUFIf/36NaZOnYolS5agW7duqFevHkaPHg1/f38sWrSowPwaNWoEY2Nj3Lx5U+P+4OBgyOVylS0J14pTdMYYY4yVAVqvxTNmzBhEREQgOjoazs7OKvuzsrKQlZUFAwPVuMfQ0BA5OTkF5nv58mVkZWXBzs5O4/6goCBMmDBBJc1PHqBN0dl7VJ6azri2gDHGPgytApRRo0Zh69at2LNnD8zNzZGSkgIAkMvlMDU1RaVKldCmTRtMmjQJpqamcHJyQkxMDDZt2oQlS5YAAG7fvo2wsDB07twZ1tbWuHLlCgIDA9GwYUO0bNlS4/PKZDLIZDKVNG7eYYwxxsovrQKU0NBQABCGEOdZv349AgICAADh4eEICgrCgAED8PTpUzg5OWHOnDn4+uuvAQBSqRSHDx9GSEgI0tPT4ejoiC5dumD69OkwNOSggzHGGGPFaOIpikKhwPr16wvc7+joqDaL7IeiT8OM9WU4nC5wswhjjLGS+qjX4tEn+hJcMMYYY/qAVzNmjDHGmN7hAIUxxhhjeocDFMYYY4zpHa1H8YSGhuLu3bsAADc3N/zwww/w9fUFkNuJdubMmVi7di2ePXuGpk2b4qeffoKbm5uQh1KpxMSJE7Ft2za8fv0a7dq1w6pVq1QmfHtfuN8HY4wxpp+0qkFxcHDAvHnzcO7cOZw7dw5t27ZFjx49cPnyZQDAggULsGTJEqxcuRJnz56FQqFAhw4d8PLlSyGPcePGISIiAuHh4Thx4gTS09PRtWtXZGdn6/bKGGOMMVZmaVWD0q1bN5XHc+bMQWhoKGJjY1G3bl0sW7YM3333HXr16gUA2LhxI2xtbbF161Z89dVXSEtLw7p167B582ZhXZ4tW7bA0dERhw4dQseOHXV0WexD0peaKR7uzBhjZVex+6BkZ2cjPDwcGRkZaN68OZKSkpCSkgIfHx/hGJlMhjZt2uDUqVMAgLi4OGRlZakcY29vD3d3d+EYxhhjjDGt50G5dOkSmjdvjjdv3qBixYqIiIhA3bp1hQDD1tZW5XhbW1vcu3cPAJCSkgKpVIrKlSurHZM3bf77pE8TtZUnXHPB2PvH9yF1+vKa6MtEnGXt3qx1gOLq6oqEhAQ8f/4cO3fuxKBBg1RmhpVIJCrHE5Fa2ruKOkapVEKpVKqk5VB2idfj0Zc3rz75GD8EjDHG9I/WTTxSqRQ1a9aEp6cngoODUb9+fYSEhEChUACAWk1IamqqUKuiUCiQmZmJZ8+eFXiMJsHBwZDL5SpbEq5pW3TGGGOMlRElngeFiKBUKuHs7AyFQoGoqChhX2ZmJmJiYtCiRQsAQOPGjWFsbKxyTHJyMhITE4VjNAkKCkJaWprK5ozaJS06Y4wxxvSUVk08U6dOha+vLxwdHfHy5UuEh4cjOjoakZGRkEgkGDduHObOnQsXFxe4uLhg7ty5MDMzQ//+/QEAcrkcQ4cORWBgIKysrGBpaYmJEyfCw8NDGNWjiUwmg0wmU0krafMOwH1QNOHmGcYYY/pAqwDl0aNHGDhwIJKTkyGXy1GvXj1ERkaiQ4cOAIBvv/0Wr1+/xsiRI4WJ2g4ePAhzc3Mhj6VLl8LIyAh9+/YVJmrbsGEDDA1LHnAw/aAvARsHW+q4j1H5pS8dMfWJvrwm+vK6lrXPv4SI6L09mw51MOjzoYtQLunLB1pf8JcxK4q+vN/5s6uOXxPd08VraqC4Ieo4rUfxMPY+8I2FMcY+brxYIGOMMcb0DtegML3EtR+MMfZx+6gDFB7FUzq43wZjjLGS0qqJJzQ0FPXq1UOlSpVQqVIlNG/eHH/++aewf9euXejYsSOsra0hkUiQkJCgloeXlxckEonK1q9fvxJfCGOMMcbKD61qUBwcHDBv3jzUrFkTQO5qxT169MD58+fh5uaGjIwMtGzZEn369MHw4cMLzGf48OGYNWuW8NjU1LSYxS8ZXdV86EuNAdfkMMYYKy+0ClC6deum8njOnDkIDQ1FbGws3NzcMHDgQADA3bt3C83HzMxMmBq/PChrY8s/Fvx3KR38ujLG3odij+LJzs5GeHg4MjIy0Lx5c63ODQsLg7W1Ndzc3DBx4kS8fPmyuMVgjDHGWDmkdSfZS5cuoXnz5njz5g0qVqyIiIgI1K1bV/T5AwYMENbtSUxMRFBQEC5cuKCyPs/HSF+aZ/SlHEwV/10YYyVV1moutQ5QXF1dkZCQgOfPn2Pnzp0YNGgQYmJiRAcp+fumuLu7w8XFBZ6enoiPj0ejRo00nqNUKqFUKlXScihbJ+vxMMYYY0z/aB2gSKVSoZOsp6cnzp49i5CQEKxZs6ZYBWjUqBGMjY1x8+bNAgOU4OBgzJw5UyXNGXVQA27Fek7GPlZl7RcUY+zjVeKZZIlIrXZDG5cvX0ZWVhbs7OwKPCYoKAhpaWkqmzNqF/s5GWOMMabftKpBmTp1Knx9feHo6IiXL18iPDwc0dHRiIyMBAA8ffoU9+/fxz///AMAuH79OgBAoVBAoVDg9u3bCAsLQ+fOnWFtbY0rV64gMDAQDRs2RMuWLQt8XplMBplMppLGzTuMMcZY+aVVgPLo0SMMHDgQycnJkMvlqFevHiIjI9GhQwcAwN69ezF48GDh+LwJ2KZPn44ZM2ZAKpXi8OHDCAkJQXp6OhwdHdGlSxdMnz4dhoYccOgDXqRPP+nTrMfcTMQYex+0ClDWrVtX6P6AgAAEBAQUuN/R0RExMTHaPCVjjJUaDqYZ018f9Vo8jH1suPZDFdcYMqa/PuoARZ+qzcsT/hJkjDFWUh91gMKBBWOMMaafSjzMmDHGGGNM17SqQQkNDUVoaKiwGKCbmxt++OEH+Pr6AgBmzJiB8PBwPHjwAFKpFI0bN8acOXPQtGlTIQ+lUomJEydi27ZteP36Ndq1a4dVq1bBwcFBd1fFPih9qZnipiZ1PIpHlb68Vxlj6rQKUBwcHDBv3jxhJtmNGzeiR48eOH/+PNzc3FCrVi2sXLkS1atXx+vXr7F06VL4+Pjg1q1bqFKlCgBg3Lhx+P333xEeHg4rKysEBgaia9euiIuL46HGjJWy8hRc6AJ3kmVMf0mIiEqSgaWlJRYuXIihQ4eq7Xvx4gXkcjkOHTqEdu3aIS0tDVWqVMHmzZvh7+8PAPjnn3/g6OiI/fv3o2PHjqKft4NBn5IUm5Ui/hJkHxN9CVA42FLHr4kqfbk3GyhuiDuuuE+QnZ2N8PBwZGRkoHnz5mr7MzMzsXbtWsjlctSvn/sHjouLQ1ZWFnx8fITj7O3t4e7ujlOnThW3KIwxxhgrZ7QexXPp0iU0b94cb968QcWKFREREaGykvEff/yBfv364dWrV7Czs0NUVBSsra0BACkpKZBKpahcubJKnra2tkhJSSnhpTDGGGP/oy+1H/pSk1PW+qBpXYPi6uqKhIQExMbGYsSIERg0aBCuXLki7Pf29kZCQgJOnTqFTp06oW/fvkhNTS00TyKCRCIpcL9SqcSLFy9UthzK1rbojDHGGCsjtK5BkUqlQidZT09PnD17FiEhIVizZg0AoEKFCqhZsyZq1qyJZs2awcXFBevWrUNQUBAUCgUyMzPx7NkzlVqU1NRUtGjRosDnDA4OxsyZM1XSnFEHNeCmbfHZe1CefrXoC129puXpNWG6V94mr9SXmgt9UdY+/yWeB4WIoFQqRe1v3LgxjI2NERUVJexPTk5GYmJioQFKUFAQ0tLSVDZn1C5p0RljjDGmp7SqQZk6dSp8fX3h6OiIly9fIjw8HNHR0YiMjERGRgbmzJmD7t27w87ODk+ePMGqVavw999/o0+f3BE3crkcQ4cORWBgIKysrGBpaYmJEyfCw8MD7du3L/B5ZTIZZDKZSpqBhIckM8YYY+WVVgHKo0ePMHDgQCQnJ0Mul6NevXqIjIxEhw4d8ObNG1y7dg0bN27E48ePYWVlhSZNmuD48eNwc/tfU8zSpUthZGSEvn37ChO1bdiwgedAYYwxxpigxPOgfCg8Dworir60t5anNmxAf15XfVHe/r5M98pTXxhdXIvYeVA+6sUCGfvYcHDBGCsreLFAxhhjjOmdj7oGpbwNqdMF/oWte/yasvdBn95n+nJP1JemlbI2QZq++KgDFH35EDHGGGNMlVYBSmhoKEJDQ3H37l0AgJubG3744Qf4+vqqHfvVV19h7dq1WLp0KcaNGyeke3l5ISYmRuVYf39/hIeHa1/6EuIaFMYYY2XBx1gLo1WA4uDggHnz5gkzyW7cuBE9evTA+fPnVYYS7969G3/99Rfs7e015jN8+HDMmjVLeGxqalqcsjPGGGOsnNIqQOnWrZvK4zlz5iA0NBSxsbFCgPLw4UOMHj0aBw4cQJcuXTTmY2ZmBoVCUcwiM8YYY6y8K3YflOzsbOzYsQMZGRlo3rw5ACAnJwcDBw7EpEmTVGpU3hUWFoYtW7bA1tYWvr6+mD59OszNzYtblA9OXzpiMcYYK5/KWvOMLmgdoFy6dAnNmzfHmzdvULFiRURERKBu3boAgPnz58PIyAhjx44t8PwBAwbA2dkZCoUCiYmJCAoKwoULF1TW53mXUqlUW+8nh7J5unvGGGOsnNI6QHF1dUVCQgKeP3+OnTt3YtCgQYiJicHr168REhKC+Ph4SCSSAs8fPny48H93d3e4uLjA09MT8fHxaNSokcZzSms1Y31aIbY81cJ8jJ25GGOsIPpyfy9r91WtJ2qTSqWoWbMmPD09ERwcjPr16yMkJATHjx9HamoqqlatCiMjIxgZGeHevXsIDAxEtWrVCsyvUaNGMDY2xs2bNws8hlczZowxxj4uJZ4HhYigVCoxcOBAtRWJO3bsiIEDB2Lw4MEFnn/58mVkZWXBzs6uwGNKazVjHmZcOspalM4YY0z/aBWgTJ06Fb6+vnB0dMTLly8RHh6O6OhoREZGwsrKClZWVirHGxsbQ6FQwNXVFQBw+/ZthIWFoXPnzrC2tsaVK1cQGBiIhg0bomXLlrq7KpE4sCgdH2NVJGOMMd3SKkB59OgRBg4ciOTkZMjlctSrVw+RkZHo0KGDqPOlUikOHz6MkJAQpKenw9HREV26dMH06dNhaPj+O7xyDYq68nQtjDHGyi6tApR169ZplXnejLN5HB0d1WaR/ZD4y1gd11wwxhjTBx/1WjysdOhL4MfBFmOMlV0coDC9xMEFY4x93DhAYTrHwYXu6dOcPYwx9j5wgML0Eo8EUlWeroXpL31pni1v+HUtHq0ClNDQUISGhgqdX93c3PDDDz/A19dXOObq1auYPHkyYmJikJOTAzc3N/z222+oWrUqgNxp6ydOnIht27bh9evXaNeuHVatWgUHBwfdXRX7oPjDqL/05W+jLwGXvrwejDF1WgUoDg4OmDdvHmrWrAkA2LhxI3r06IHz58/Dzc0Nt2/fRqtWrTB06FDMnDkTcrkcV69ehYmJiZDHuHHj8PvvvyM8PBxWVlYIDAxE165dERcX90GGGjPdK09fPvpyLbpS3q6npPRlCnLGmDqtApRu3bqpPJ4zZw5CQ0MRGxsLNzc3fPfdd+jcuTMWLFggHFO9enXh/2lpaVi3bh02b94szDq7ZcsWODo64tChQ+jYsWNJroUxxhhj5YTWa/Hkyc7ORnh4ODIyMtC8eXPk5ORg3759qFWrFjp27AgbGxs0bdoUu3fvFs6Ji4tDVlYWfHx8hDR7e3u4u7vj1KlTJboQxhhjjJUfWneSvXTpEpo3b443b96gYsWKiIiIQN26dZGSkoL09HTMmzcPs2fPxvz58xEZGYlevXrh6NGjaNOmDVJSUiCVSlG5cmWVPG1tbZGSklLgcyqVSiiVSpW0HMrWyXo8rPzi5gzGGCu7tA5QXF1dkZCQgOfPn2Pnzp0YNGgQYmJiYGFhAQDo0aMHxo8fDwBo0KABTp06hdWrV6NNmzYF5klEkEgkBe4PDg7GzJkzVdKcUQc14KZt8VkZwf1HSoe+9JfQl7+NvrwerHzTl75OZe2+qnWAIpVKhU6ynp6eOHv2LEJCQrBixQoYGRmhbt26KsfXqVMHJ06cAAAoFApkZmbi2bNnKrUoqampaNGiRYHPGRQUhAkTJqik+ckDtC06Yx89fQkM9IW+fHEwxtSVeB4UIoJSqYRUKkWTJk1w/fp1lf03btyAk5MTAKBx48YwNjZGVFQU+vbtCwBITk5GYmKiSsfad8lkMshkMpU0bt5hTHv68mXKgRJjrChaBShTp06Fr68vHB0d8fLlS4SHhyM6OhqRkZEAgEmTJsHf3x+tW7eGt7c3IiMj8fvvvyM6OhoAIJfLMXToUAQGBsLKygqWlpaYOHEiPDw8hFE9jLHSwzUGjL1//JkpHq0ClEePHmHgwIFITk6GXC5HvXr1EBkZiQ4dOgAA/Pz8sHr1agQHB2Ps2LFwdXXFzp070apVKyGPpUuXwsjICH379hUmatuwYQPPgcJYGcG1H4yx90FCRPShC1EcHQz6fOgisALwr3RV+vR6cHChe/ryXtWn95m+4NdE93Txmhoobog7rsTPxBhjjDGmYxygMMYYY0zvcIDCGGOMMb3DAQpjjDHG9A4HKIwxxhjTOxygMMYYY0z/UDn15s0bmj59Or1584bz0KM89KksnAfnUVbKwnlwHmWlLLq6HiKichugpKWlEQBKS0vjPPQoD30qC+fBeZSVsnAenEdZKYuuroeIiJt4GGOMMaZ3OEBhjDHGmN7hAIUxxhhjeqfcBigymQzTp0+HTCbjPPQoD30qC+fBeZSVsnAenEdZKYuurgcow4sFMsYYY6z8Krc1KIwxxhgruzhAYYwxxpje4QCFMcYYY3qHAxTGGGOM6R0OUN5x7NgxvH37Vi397du3OHbsWInz5z7JjLGPxdu3bzFz5kw8ePDgQxeFvUe6+p7jAOUd3t7eePr0qVp6WloavL29ReUxcOBApKenq6XfvXsXrVu31qo8t27dwoEDB/D69WsA7yfAuXjxouitLLl//36h28fq+PHj+Pzzz9G8eXM8fPgQALB582acOHHiA5esbIqKisKrV68+dDEEH/Lva2RkhIULFyI7O1sn+W3evBktW7aEvb097t27BwBYtmwZ9uzZo5P8y5LIyEiVv+FPP/2EBg0aoH///nj27JnofOLj43Hp0iXh8Z49e9CzZ09MnToVmZmZBZ6nVCoRGBiINm3aYOHChQCA2bNno2LFiqhYsSL69++PFy9eFOPK/seoRGfrAW1egEqVKhV5DBFBIpGopT958gQVKlQQ9TxXrlyBh4cHtmzZgpYtWwIANm7ciLFjx6JDhw6i8njy5An8/f1x5MgRSCQS3Lx5E9WrV8ewYcNgYWGBxYsXF5mHn5+fxmuRSCQwMTFBzZo10b9/f7i6uqrsb9CgASQSSYHBUN4+iUSisxuPGJs2bYK/v7/a+PrMzEyEh4fjiy++KPT8atWqaXw98rzPaymuhg0bFnoN+cXHxxd5zM6dOzFw4EAMGDAA58+fh1KpBAC8fPkSc+fOxf79+0WX7caNG4iOjkZqaipycnJU9v3www9Fnl+9enWcPXsWVlZWKunPnz9Ho0aNcOfOnSLzGDJkCEJCQmBubq6SnpGRgTFjxuDXX38tMo+Svs969+4NpVKJxo0bo02bNvDy8kLLli1RsWLFIp87vw0bNqBv374wMzPT6rz8dPn3zczM1Pi3rVq1aqHntW/fHtHR0QgICNC6/PmFhobihx9+wLhx4zBnzhzh82phYYFly5ahR48eGs+ztLTEjRs3YG1tjcqVKxf6+dH04zSPrr9rgNz39n//+1/cvn0bkyZNgqWlJeLj42Fra4tPPvmk0HMnTZqE+fPnAwAuXbqEwMBATJgwAUeOHMGECROwfv16UWX46quvMGXKFHh4eODOnTvo168f/Pz8sGPHDrx69QrLli3TeF5QUBC2b9+Ozz77DOvXr8e9e/fw+++/Y82aNTAwMMAPP/yA77//HsuXLxdVDk3K/DwoBgYGom/YhX0B9erVC0Bu9NipUyeVm1N2djYuXrwIV1dXREZGFvk8b9++xffff4+lS5ciMDAQN2/eRGRkJEJCQjBkyBBRZf3iiy+QmpqKX375BXXq1MGFCxdQvXp1HDx4EOPHj8fly5eLzCMgIAC7d++GhYUFGjduDCLC+fPn8fz5c/j4+ODChQu4e/cuDh8+LARSAIRfJmI4OTkVuK+om0F+hd0Y8hgaGiI5ORk2NjYq6U+ePIGNjU2RAcaFCxdUHmdlZeH8+fNYsmQJ5syZI7wHilLU37CwL8GsrCx899132LVrFywtLTFixAgMHjxY2P/o0SPY29sXeC0zZ84U/v/mzRusWrUKdevWRfPmzQEAsbGxuHz5MkaOHIng4OAir6Vhw4YYP348vvjiC5ibmwvvs4SEBHTq1AkpKSlF5gEAP//8M0aMGAFra2soFAqVv7tEIhEVLBkYGCAlJUXt7/vo0SNUrVpV+HItTEHvkcePH0OhUGhsvhWbh9j3WXZ2Ns6cOYOYmBhER0fj1KlTePPmDRo1agQvLy/MmzevyDIAgJ2dHTIyMtCnTx8MHToULVq0EHVefrr4+968eRNDhgzBqVOnVNLF/khZs2YNZsyYgQEDBqBx48ZqP/S6d+8u6lrq1q2LuXPnomfPnirXkpiYCC8vLzx+/FjjeRs3bkS/fv0gk8mwcePGQp9j0KBBBe4T812jzQ+3ixcvon379pDL5bh79y6uX7+O6tWrY9q0abh37x42bdpU6PkVK1ZEYmIiqlWrhhkzZiAxMRH//e9/ER8fj86dO4v+7MrlcsTHx6NGjRqYP38+jhw5ggMHDuDkyZPo169fgc1zVatWxa+//or27dvjzp07cHFxwa5du4RAMSoqCsOHD8fdu3dFlUOTMl+DcvToUeH/d+/exZQpUxAQECDcsE+fPo2NGzcWebOWy+UAct9g5ubmMDU1FfZJpVI0a9YMw4cPF1UmIyMjzJs3DzKZDD/++COMjIwQExMjlEmMgwcP4sCBA3BwcFBJd3FxER1AKBQK9O/fHytXroSBQW5rXk5ODr755huYm5sjPDwcX3/9NSZPnqxSVVhY0KGN/JH3kydPMHv2bHTs2FHlb3PgwAFMmzZNVH4F1W79/fffwt+vMPXr11dL8/T0hL29PRYuXCg6QHm3+jQrKwuJiYl4/vw52rZtW+i5c+bMwaZNmzBx4kQ8f/4c48ePR2xsLNasWSMcU9hvhunTpwv/HzZsGMaOHYsff/xR7Rixbf7Xr1/X2OxYqVIlPH/+XFQeQG7V7pw5czB58mTR5+TZu3ev8P8DBw6o/C2zs7Nx+PBhVKtWrdA8Xrx4AcpdnR0vX76EiYmJSh779+9XCzgKUtL3maGhIZo3b47mzZtjypQpSExMxKJFixAWFoazZ8+KDlD+/vtv7Nu3Dxs2bIC3tzecnZ0xePBgDBo0CAqFQlQeuvj7BgQEwMjICH/88Qfs7OxE/+jIM2LECADAkiVL1PZpUwublJSEhg0bqqXLZDJkZGQUeF7+oKOwAKQo+b9rdGHChAkICAjAggULVGr8fH190b9//yLPl0qlQlPioUOHhJo9S0tLrWp7iEioFTt06BC6du0KAHB0dCww6ANyg/5atWoByK39NDQ0RM2aNYX9Li4u+Pfff0WXo6DClRtt27alrVu3qqWHhYVRmzZtROUxY8YMSk9PL1E5MjMzacKECSSTyWjq1KnUunVrsrW1pX379onOo2LFinTjxg3h/7dv3yYiojNnzpClpaWoPKytren69etq6devXycrKysiIrp48SLJ5fIi87p8+TL9+eeftGfPHpVNrF69etGKFSvU0lesWEE9evQo9NwGDRpQw4YNycDAgDw8PKhhw4bCVq9ePTI3N6c+ffqILsu7bty4QWZmZsU+n4goOzubvvrqK5o/f36hx9WsWZN+//134fGtW7fIxcWFAgICKCcnh1JSUsjAwEDUc1aqVEl4j+R348YNqlSpkqg8qlevTlFRUUSk+j7buHEj1alTR1QeRETm5ubCudqSSCQkkUjIwMBA+H/eJpVKqVatWiqvWUF5GBgYFLgZGhrS7NmzC81DV++zK1euUGhoKPn7+5NCoaAqVaqQn58fhYSEUEJCglavTZ5Hjx7R4sWLycPDg4yNjalbt260e/duys7OLvQ8Xfx9zczM6OrVq8Uqty7VqVOHdu/eTUSq1xISEkKNGjUSnc/bt2/pv//9L/344480e/Zs2rVrF719+1b0+VlZWTRjxgy6f/++dhfwjkqVKtGtW7eISPV67t69SzKZrMjzu3XrRh07dqRZs2aRsbEx/f3330REdODAAXJxcRFdDm9vb/riiy9o06ZNZGxsTDdv3iQioujoaHJycirwPFdXVwoPDyei3O8lqVRKv/76q7A/PDxcq3JoUq4CFFNTU4037OvXr5OpqanofLKysigqKopWr15NL168ICKihw8f0suXL0WdX69ePapZsyadPn2aiIhycnJo3rx5JJPJaMSIEaLy6Ny5M33//fdElPvmvXPnDmVnZ1OfPn2od+/eovKwsLDQGETs2bOHLCwsiCj3yyzv/5rcvn2b6tWrp/YFknfjF6tChQrCGz+/GzduUIUKFQo9d8aMGTRjxgySSCQ0ceJE4fGMGTNo7ty5tHXrVlIqlUWWIS0tTWV7/vw5Xb16lfz9/al+/fqir6Ug165dI4VCUegxpqamlJSUpJL28OFDcnV1pQEDBtDDhw9Fv662trYqN4Q8v/76K9nY2IjKY/78+VS3bl2KjY0lc3NzOn78OG3ZsoWqVKmiMaAsyJAhQyg0NFT08ZpUq1aN/v3332KdGx0dTUePHiWJREK7du2i6OhoYTt16hQ9fPiwyDx09T6TSCRkY2NDc+fOpcTExGJdjyaxsbH05Zdfkkwmo2rVqpGFhQVVq1aNjh49WuA5uvj7enp60vHjx3VyDa9fvy72ub/++it98sknFB4eThUqVKBt27bR7Nmzhf+LcfPmTXJxcSEzMzNq2LAhNWjQgMzMzMjV1VUIFsSoWLGi2udYWzY2NhQfHy/klxegHDhwgBwcHIo8/969e9SlSxeqV68e/fLLL0L6uHHjaMyYMaLLceHCBXJ3d6dKlSrRjBkzhPTRo0fTZ599VuB5S5cuJRMTE2rfvj1VrlyZVqxYQQqFgr799luaMmUKyeVymjVrluhyaFKuApRatWrRhAkT1NInTJhAtWrVEpXH3bt3qXbt2mRmZkaGhobCm+abb76hr776SlQeQ4YM0VgLc/78eXJzcxOVx+XLl6lKlSrUqVMnkkql9J///Ifq1KlDtra2oj9IY8aMIWtra1qyZAkdP36cTpw4QUuWLCFra2saO3YsERH9/PPP1LJlywLz6Nq1K/Xo0YNSU1OpYsWKdOXKFTp+/Dh9+umndOzYMVHlICKqWrUqLViwQC19wYIFVLVqVVF5bNiwoUQ3OE2/siUSCVWtWpVOnTpV7Hzz7Nu3j6ytrQs9xtnZmQ4dOqSW/vDhQ6pVqxa1b99edIASHBxMMpmMRo0aRZs3b6bNmzfTqFGjyNTUlIKDg0WXe+rUqWRqaioEnyYmJkJwLNbcuXPJ2tqaBg0aRIsWLaKQkBCV7X25e/dukbUKRSnp++ybb76hhg0bklQqpU8//ZS+/fZb2r9/v+gfOPmlpKTQwoULqW7dumRiYkL9+vUTakRevXpFEyZMKPLzU9K/7+HDh6l58+Z09OhRevz4sVqgX5S3b9/SrFmzyN7eXuWe+v3336t8sYqxdu1aqlq1qnAtDg4OWuXh6+tLnTp1oidPnghpjx8/pk6dOlHnzp1F59OjRw9av369NkVXM3z4cOrZsydlZmYKP0Lv3btHDRs2pG+++aZEeevC69evKTMzs9BjtmzZQqNHjxZqUo4ePUr/93//R40bN6YZM2aU+LNY5jvJ5rd//3707t0bNWrUQLNmzQDkdhq8ffs2du7cic6dOxeZR14HrHXr1sHKykroiBUTE4Nhw4bh5s2bJSqjUqkUvcpjSkoKQkNDERcXh5ycHDRq1AijRo2CnZ2dqPOzs7Mxb948rFy5Eo8ePQIA2NraYsyYMZg8eTIMDQ1x//59GBgYqPV1yWNtbY0jR46gXr16kMvlOHPmDFxdXXHkyBEEBgbi/PnzosqyYcMGDB06FJ06dVLp0BkZGYlffvlFqx7+xR1NEB0drdJ+bmBggCpVqqBmzZowMhLfHWvChAkqj4kIycnJ2LdvHwYNGoSVK1cWeO6wYcNARFi3bp3avocPH8LLywt37twR3S7/22+/ISQkBFevXgUA1KlTB9988w369u1b5LnZ2dk4ceIEPDw8YGJigitXriAnJwd169bVesSJs7NzgfskEomoETgAcPjwYRw+fFjj31fMCBwgd2TEmTNnNOZR1Aic/Ir7PstfjuPHjyMmJgYxMTG4dOkSGjRogNjYWFHnd+vWDQcOHECtWrUwbNgwfPHFF7C0tFQ55p9//oGDg4NaGd/16tWrYv998/qvvdv3hER2CJ01axY2btyIWbNmYfjw4UhMTET16tXx22+/YenSpTh9+rTosuR5/PgxcnJyRPcrylOhQgXExsbCw8NDJf3ChQto2bKlxukhNNFFx98XL16gc+fOuHz5Ml6+fAl7e3ukpKSgefPm2L9/v6hRo7dv38b69etx+/ZthISEwMbGBpGRkXB0dISbm5uoawFKNpqoVJUovNFD9+/fp6CgIPLz86OePXvS1KlTtWortLKyomvXrhGRarVbUlKSVs1EmzZtohYtWpCdnR3dvXuXiHKrxPLaUN83sb923mVhYSG8BtWrV6cjR44QUW7fCW1eD6LcKur+/fsLVav9+/en2NhY0effuHGDWrVqpbEWRJvmppLy8vJS2dq2bUv+/v60Zs0aysrKKvTcu3fvUmRkZIH7//nnH9qwYYOui1wgmUxGd+7ceW/PV5gZM2aQgYEBffrpp9SjRw/q2bOnyibG3r17ydzcnAwMDEgul5OFhYWwVa5cWVQeunqfPXnyhHbt2kVjxowhDw8PMjAwIFtbW9HnDxkypMiavZycHOH+osngwYOFZur80tPTafDgwaLKkb+5TNNWlBo1agi1hvnvqVevXi20ebk0VK5cmU6ePKmWfuLECdHvDyJS6yuVf9P2XnT48GFauHAhzZ8/X6gdEyM6OppMTU2pffv2JJVKhdd1/vz5orsBEOU28VhbW1PNmjXJyMhIpYZr4MCBWl2LrpW7AKWkKleuTJcvXyYi1Q/T8ePHRbfrr1q1iqytrWn27Nlkamoq5LF+/Xry8vISlceFCxc0bhcvXqQbN27QmzdvinF12mvVqhVFREQQEdFnn31GnTp1ohMnTtAXX3whurlKV1q0aEGtW7em/fv30/nz5ykhIUFlK8rcuXNp3bp1aunr1q2jefPmlUaRS92zZ8/o559/pqCgIKHaOi4uTugwVxRPT0+NTU4lkZOTQzk5OVqfp1AoaNOmTSV6bhcXF/rmm28oIyOj2HmU9H02duxYqlevHhkaGlKVKlWod+/etGLFCrp06ZJW5di4caPGz7lSqaSNGzeKysPAwIAePXqklv7vv/+SoaGhVuUpLhMTEyGIyn9PvXz5cpH9z/J7/PgxjRw5kurUqUNWVlZUuXJllU2MgQMHkpubG8XGxgrv09OnT5O7uzsNGjRI62vTtWfPnok+tlmzZrR48WIiUh9IYW9vLzqfdu3a0aRJk9TyOXnyZKGdZImIEhIS6Mcff6SffvpJrf9YWlqa6CC4IGU+QLlw4YLQzlXQl3reJkbfvn1p+PDhRPS/zqkvX76ktm3bUkBAgKg86tSpI3yp5/+DX7p0SRg9U5T8/SXe7ZhqYGBAMpmMvvjii0LbylNSUujzzz8nOzs7MjQ0VPtFKEZkZCTt3LmTiHI7zNapU4ckEglZW1vT4cOHReWR59atW/Tdd9/RZ599Jtw0//zzT9EdCUs6msDJyUnjr6fY2FiqVq2a6Hzu3LlT4OgZsR3nfvvtN/Lz8yM3Nzdyd3cnPz8/2rFjh+gyEOW+36tUqVKiXz4HDhygBg0a0O+//07//POP1v0L8tu4cSO5u7uTTCYjmUxGHh4eWgUclpaWWnVU1MTMzKzYo4ny51GS91lxA5J3FRRcPH78uMjPb14ncIlEQrdu3VL5mz59+pQ2btxIdnZ2osvy7NkzWrRoEQ0dOpSGDRtGS5YsoefPn4s6t3HjxrR582YiUr0fzpgxg1q1aiW6DJ06dSIXFxeaN28erV+/njZs2KCyib2O7t27CyPEpFIpSSQS6tmzp1bBwcyZMwvcxHYMnTdvntB3g4ioT58+ZGBgQPb29qIC4QoVKgi1n+/W9osZBZSnuKOJDhw4QFKplNzc3Khq1apkbW0t1LATkVYjEgtS5gMUiUQifIgLGqqoTbVbXmfFOnXqkJGRETVr1oysrKzI1dVV481Ck4J+Mdy4cYNMTExE5bF7925ydXWlX375hS5evEgXLlygX375herUqUPh4eG0ZcsWcnBwoMDAwALz6NSpE9WtW5dWrVpFERERtHv3bpWtuJ48eaL1L2RdVEeWdDRBQc0Zt2/f1uoD3bp1a403xM2bNxc5nD07O5v69u1LEomEXF1dqUePHtS9e3eqVasWGRgYkL+/v+jXtiS/fPK8+xkpbnPG4sWLyczMjL799lvas2cP7d69myZNmkRmZma0ZMkSUXl8++23Je717+fnR9u3by9RHroctVISEomEUlNT1dITEhKKrDHQxbDrPGfPniVLS0v65JNPhKZzBwcHsrKyori4uCLP37t3L8nlcpo3bx6ZmZnRwoULadiwYSSVSungwYOiykCU+x4v7jDtd928eZP27t1Le/bs0Ti6sCgNGjRQ2dzc3MjMzIwqVapEDRs2FJWHs7Oz8IPp4MGDZGFhQQcOHKChQ4dShw4dijz/k08+Ec7P//nftWsXVa9eXfS1FHc0UfPmzWnq1KlElFtrumDBAqpYsSL9+eefRKSbAKXMT9SWlJSEKlWqCP8vKXt7eyQkJCA8PFzonDp06FAMGDBAZfK2wjg7OyMhIUFtwrM///wTdevWFZXHnDlzEBISgo4dOwpp9erVg4ODA6ZNm4YzZ86gQoUKCAwMxKJFizTmceLECRw/fhwNGjQQ9ZyabNy4Ef/5z39UOmy921FPjClTpmD27NmYMGGCyqRE3t7eCAkJEZXH/Pnz8e2332Lu3Lnw8PCAsbGxyv6ippd2dHTEyZMn1Tp0njx5Evb29iKvBDh//rzKzLt5mjVrhtGjRxd67rJly3Do0CHs3btXmBApz969ezF48GCEhIRg3LhxRZbj7NmzKhO85fnkk09EzyKpq8mnVqxYgdDQUJVOqD169ICbmxtmzJiB8ePHF5nHmzdvsHbtWhw6dAj16tVT+/tqmujrXV26dMGkSZOE5SbezUNM58WSvs+A3DVjVq9ejaSkJJw+fRpOTk5YtmwZnJ2dC5ySPU/ecgYSiQTt2rVT6cCdnZ2NpKQkdOrUqdA8jh49CiJC27ZtsXPnTpXPrFQqhZOTk+j3/Pjx49G9e3f8/PPPQlnevn2LYcOGYdy4cUUuotqtWzds374dc+fOhUQiwQ8//IBGjRrh999/F730BwDUrl1bWJNMG+92an9XdHS08H8x7zEAGgcHvHjxAgEBAfDz8xOVR3JyMhwdHQEAf/zxB/r27QsfHx9Uq1YNTZs2LfL8/v37Y/LkydixYwckEglycnJw8uRJTJw4UavO4D169MCsWbPw22+/AcjtDH3//n1MmTIFvXv3LvC8y5cvY/PmzcI5kyZNgoODA/7zn/9g27Zt+PTTT0WXoUAlCm/0TExMjMZOillZWRQTE/PeyqGL8fomJiYaq5mvXr0q1MIU1XG3Tp06QmRcXNbW1mRmZkb+/v70+++/F9kJtCC6qI7U9Etfm1/78+bNIysrK/r111/p7t27dPfuXVq3bh1ZWVnR3LlzRV9LpUqVNL6u586do4oVKxZ6roeHh8Z+MHl++eUXcnd3F1WOks6joEsymazAeW7E/n3f7Xycf/P29haVhy46L5b0fVbSPmi6mo+FSDfDrgu6F12+fFnrjvIlcebMGWrbti1FR0drNdz53feSubm5MA9Kw4YNqUKFClSpUiXR77HCXLp0SXTtpZ2dnVADUqtWLfrtt9+IKHc+JXNz8yLPz8zMpP79+wvvTWNjYzIwMKDPP/9cq4nn0tLSqGXLlmRhYUGGhobk6OhIxsbG1Lp160InLa1SpQqdO3dOLT08PJzMzMwoNDSUm3jyK0mbbZ4NGzbQH3/8ITyeNGkSyeVyat68eaG95d/17nh9R0dHrcbrN2jQgAYNGqRyI8rMzKRBgwZRgwYNiCi353lhfScOHDhAPj4+JZpQKCsri37//Xfq378/VahQgaytrWnEiBEa+3IURhfVkSUdTZCTk0PffvstmZiYCF86ZmZmNHPmTK2upUuXLtSnTx+Vm8Dbt2+pd+/e1KlTp0LPNTExoXv37hW4/+7du6KbAXUxj0JMTEyhm1hubm40Z84ctfQff/xRdMClL0r6PtNFHzSiks/Hkl9GRgZdvXq1WP3ybGxs6MCBA2rpkZGRogcO6MKNGzeocePGJRpdtXjxYurWrRs9ffpUSHv69Cn16NGDFi1aVOIyHj9+XPTIpFGjRpGTkxO1b9+erKyshHlywsPDRTcTEeU2Ue/YsYO2b9+usW+cWNqOJurQoQMtXLhQ476tW7cKAVNJlKsApaA22+vXr4uKSIlyI9m8zp+nTp0iU1NTWrNmDXXr1o38/PxE5fHq1SthFMG///5Lf/31Fy1ZsqTQ4aXvOnnyJFlZWVGVKlWoXbt21L59e7KxsSErKythhtpNmzZpnPwsj4WFBUmlUjIwMKCKFSsWq9d7fhkZGbRlyxbq3LkzSaVSrdo5J02aRK1ataLk5GQyNzenmzdv0okTJ6h69eoqsxe+Dy9fvqQzZ87QpUuXijUa6vLly2RlZUU1atSggIAACggIoBo1alCVKlWK7BhZuXLlQr8YLl68KPpvU9xfPvkVVNOg7UzB//3vf8nQ0FCYevvHH3+kjh07kpGREe3atUt0PuWBLvqg6Upqaip16dKlwL4oYowZM4YcHBwoPDyc7t+/Tw8ePKBt27aRg4NDgYFw3rBuMZtYTZo0oebNm1N4eDgdPXpU68CRiMje3l5jp/xLly5p1Wn43YkIly1bRpMnTyZ7e3vq16+fqDwyMzNp4cKFNHbsWJUa2aVLl9LPP/9c5PkzZ87UOFrt1atXWv3oKu5osV27dtG4ceMK3L9161bRo1YLUi4matPlSsRmZma4du0aqlatismTJyM5ORmbNm3C5cuX4eXlJWrxIx8fH/Tq1Qtff/01nj9/jtq1a8PY2BiPHz/GkiVLhMWzipKeno4tW7bgxo0bICLUrl0b/fv3V1tKviAlWbmzII8fP0Z4eDhWr16Nq1evip5QLCsrCwEBAQgPDwcRwcjICNnZ2ejfvz82bNgAQ0NDUfkcP34ca9aswZ07d7Bjxw588skn2Lx5M5ydndGqVSutr6e4/vnnH6xcuRIXLlyAqakp6tWrh9GjRxfZP6dLly6oWrUqQkNDNe7/+uuv8eDBA+zbt090WY4cOYL4+HhhMr/27duLPjctLU3lcd4Kz9OmTcOcOXPQrl070XnFxcVh6dKluHr1KogIdevWRWBgoMYF3jTx9vYudCG6I0eOFJnHrFmzCt3/ww8/FJlHUX0qNC2+l1/dunURHByMHj16qKy6u3z5cmzcuBFxcXEFnmtpaYkbN27A2tq6yNXAxawAPmDAANy9exfLli2Dt7c3IiIi8OjRI8yePRuLFy9Gly5diswjMzMTkyZNwurVq4XVoI2NjTFixAhhUdR35b/3FLVQqJj+SUDuvfn8+fNwdXUVdbwm5ubm2LNnj9qinkeOHEGPHj3w8uVLUfm8248tb9LHtm3bIigoSPQ9uiRKuuq2rvMpDWW+kyyg25WIK1asiCdPnqBq1ao4ePCg8OExMTER3UErPj4eS5cuBQD897//ha2tLc6fP4+dO3fihx9+EB2gVKxYEa1bt0a1atWQmZkJ4H+dGsV09ivJyp35vXr1ChEREQgLC8OhQ4fg6OiIzz77DDt27BCdh7GxMcLCwvDjjz8KX6YNGzaEi4uL6Dx27tyJgQMHYsCAAYiPj4dSqQQAvHz5EnPnzsX+/fvVzunVqxc2bNiASpUqFbla8a5du0SXxd7eHnPnzhV9fJ7vvvsOXl5eePLkCSZOnIjatWuDiHD16lUsXrwYe/bsEd1xddOmTfD390fbtm1VbriZmZkIDw8X1VFO0+q8HTp0gEwmw/jx4wv9Mn1X48aNsWXLFtHHv+vdztxZWVlISEhAYmKi6PdyRESEWh5JSUkwMjJCjRo1RAUoXl5eamn5A4WibtiTJk3CqFGj8ObNGxARzpw5g23btiE4OBi//PJLoecuXbpU+HJbunSp1isHv+vIkSPYs2cPmjRpAgMDAzg5OaFDhw6oVKkSgoODRQUoUqkUISEhCA4Oxu3bt0FEqFmzJszMzAo8J//fq3fv3pg1a5ZKB/KxY8di5cqVOHTokOgAxdPTEw8ePChRgOLn54fBgwdj8eLFKrONT5o0SfRq5oBuBmQAwI0bNxAdHa1xxuKi3qtUwKrbFy5c0GogQ0H5iF29u1SVqP5Fz+hiJeL+/ftTo0aNaOjQoWRmZkaPHz8motwF9sROTGZqair0M+jTp4/QhHH//n3Rnco0LdInpmo2f2exdzuRFWeOi379+lGFChWoSpUqNHLkSK37nuTRRXVkgwYNhCrH/FXn58+fL3CGzoCAAGEmzbzmmIK2wuhyvp1du3aRtbW1WnW7lZUV/fe//xX1WhDpps9VQa5cuVLkJFq6fq8VZPr06YUOpy9KWloa+fn5iZ6T5fnz5yrbv//+SwcPHqSmTZuKntSupGvG6Iq5ubnQB83JyYlOnDhBRLlz+byvDq4lWSg0v99++43q1q1L69evp3PnzhWrP01GRgaNGDGCZDKZ8LmTSqU0YsSIEn93aGvt2rVkaGhItra2VL9+fZVhy4X1QclrPjMwMFBrSqtUqRIZGBjQyJEji3z+0l4lXhfKRROPLj1//hzff/89Hjx4gBEjRgjD+aZPnw6pVIrvvvuuyDzq1auHYcOGwc/PD+7u7oiMjETz5s0RFxeHLl26iBoC2q1bNxgaGuLnn39G9erV8ddff+Hp06fCsOL/+7//03he/uo6AwMDjZExiVxDA8gdyjZgwAB07NhRq/VqCitXftpUI5qZmeHKlSuoVq2aStX5nTt3ULduXbx586bY5cvv5MmT8PT0VKm6NjAwQEpKisrrqumjI/Z1ffXqFQ4cOCCs7VSrVi34+PgU+qv0XQYGBnj06JEwzD7PhQsX4O3tLaoJ4OLFiyqP6f+vKzRv3jxkZWXh5MmTBZ6r6/daQW7duoVPP/1U1PUUJDExEV27dsXdu3eLncexY8e0rlXSds2YFy9eiM5bzHDnJk2aCM0rPXv2FGpOli9fLqy9ookuax6dnJwwevRoTJo0SSV94cKFWLlyJe7du1fkdQD/WxMov7zPobbvsYyMDJXaIDHr3uiak5MTRo4cicmTJ2t13saNG0FEGDJkCJYtW6ZSyyGVSlGtWjWhKa0wM2fOFP4NDAxUWZ8pL5/evXtDKpVqVT5dKhdNPHkePXqEiRMnCouNvfsFUtAbOP+Hce/evVi0aBFMTExUjsn7Y4rxww8/oH///hg/fjzatWsnvFkOHjwouj3+9OnTOHLkCKpUqQIDAwMYGhqiVatWCA4OxtixYwtcpO/IkSNC9Z4u5rjYunVrifMAdFMdaWdnh1u3bqFatWoq6SdOnED16tV1UUwAgK+vLxISElTy1PV8O2ZmZqLmS/Dw8MD+/fuF+RIA3cyTkadBgwYag61mzZoVuTifrt9rBTl9+rTa51Fbz58/V+tvo60qVarg+vXrWp1jbW2t1fEWFhZFNuto84U8btw4JCcnA8j9kdWxY0ds2bIFUqm00D5qcrlcKEelSpVK1NQ0c+ZMDB06FNHR0RoXChVLV80qQO6igfXq1dNZfsXx7Nkz9OnTR+vz8prPnJ2d0aJFC7V5esSaPn06AKBatWrw9/cv8WesNJSrGhRfX1/cv38fo0ePhp2dndqHqqAJkqRSKe7duwc7OzsYGhoiJSVF7VeptlJSUpCcnIz69esLkf+ZM2dQqVIl1K5du8jzK1eujLi4OFSvXh01atTAL7/8Am9vb9y+fRseHh549epVicpXmOXLl+PLL7+EiYkJli9fXuixY8eOLXR/Xke/tLQ0tRtddnY20tPT8fXXX+Onn34qslwLFizAxo0b8euvv6JDhw7Yv38/7t27h/Hjx+OHH34ocpI0sfLXzpREly5d8Msvv4hefVpsWXT5y+fdX695nf20vVndv38fjo6OGle8ffDggagVgN/9pZ5Xm3Pu3DlMmzZNuKEW5t33a14emzdvRuvWrbFt27Yi8yhOrVKjRo1w+PBhVK5cWQggCxIfH1/gvpiYmCLLl6dNmzaij83z6tUrYRCAtsFTSfz1119Yvny5SgfqsWPHipqQrLwaOnQomjRpgq+//rrYeWRnZ2P37t24evUqJBIJ6tati+7du4sedJBfXFycSj5if0yXpnJVg1LcmVNr166NoKAgeHt7g4iwffv2AqtPxc7Qp1AooFAoVNK0mVnP3d0dFy9eRPXq1dG0aVMsWLAAUqkUa9euLfSL892ba2EK+gWxdOlSDBgwACYmJkJnX00kEkmRAcqyZcuE6siZM2cWuzoSAL799lukpaXB29sbb968QevWrSGTyTBx4kSdBSe6dOzYsWLNfFkUXf7yiYmJgb+/v9pIDG062gK5v+Y0NeE9ffoUzs7Oon7tv9shz8DAAK6urpg1axZ8fHxElePd92tewDVo0CAEBQWJyqM4tUo9evQQXsOePXuKeh5NihN0vKuomVPzEzNzatu2bbFr1y5YWFiopL948QI9e/YUNbqqadOmCAsLE12uwly5cgX3798XBg7kETNwQJ/UrFkT06ZNQ2xsrMYZi4u6t966dQudO3fGw4cP4erqCiLCjRs34OjoiH379qFGjRqiypGamop+/fohOjoaFhYWICLhPhseHi7qx/qxY8dgZmYGT09PIe3cuXN49epVkaPeClOualDq1q2LsLAwrSO/kydPIjAwELdv38bTp09hbm6u8ReQRCIpUTu4Ng4cOICMjAz06tULd+7cQdeuXXHt2jVYWVlh+/btasPk8uTvH1FUtez7HD4WExNTourI/F69eoUrV64gJycHdevWValB0AVd1aDoIh9dlaUguhpiWFB/mHv37qFu3brIyMjQWZlLW0lrlQYPHowBAwagXbt2JR6FA+S+3zV9IRf0A8Pb21vlcVxcHLKzs4XRLzdu3IChoSEaN24sKrjI3/8qv9TUVHzyySfIyspSO0fXfWkA4M6dO/Dz88OlS5dUAsi81/hDDoctjneHKucnkUhw586dQs/v3LkziAhhYWFCU+uTJ0/w+eefw8DAQPRUBf7+/rh9+zY2b96MOnXqAMgNAgcNGoSaNWuKqnU0MDBA7dq1ceXKFSGtTp06uHHjRon+LuWqBmXZsmWYMmUK1qxZo9ZPoTAtW7ZEbGwsgNwX+saNG6I7tZWW/GvwVK9eHVeuXMHTp0+LnBshfzvt+fPnMXHiREyaNEll/oHFixdjwYIFosoRExOjk191+fN4/fq12k1N7E0KgBCpv3jxAocOHYKrq6vwwfqYZGdnY+nSpfjtt980foGJCaYLCmTFDjHM+7UukUgwbdo0lU6+2dnZ+Ouvv7Su0dRVVfPff/8NiUSCTz75RKvz3l1DS1tPnjxB165dYWVlhc8++wyff/55sdbD+vfffzF48GD8+eefGvcXdOPP3x9oyZIlMDc3x8aNG1G5cmUAuX0fBg8eXGBH+zz5a2OvXLmi0rk/OzsbkZGRBb62uu5LAwDffPMNnJ2dcejQIVSvXh1nzpzBkydPCl2PTJ+VtE9NTEwMYmNjVfrwWVlZYd68eRrXCitIZGQkDh06pHIPrVu3Ln766SfRNZdJSUlqPz4PHz6sMXjVSukPFHp/ijtzqp+fnzAUcsOGDfTq1av3VeRS1aRJE9q3b59a+r59+6hRo0ai8jA2NiZHR0eaPHkyXbx4sdhlycjIoFGjRlGVKlWKPaNlnz59aMWKFUSUOzy5Vq1aZGxsTEZGRloNzy2Kubm5MIS5JPIPhS6NPKZNm0Z2dna0cOFCMjExoR9//JGGDh1KVlZWFBISUmi+uhpimLe+iUQioRYtWqiseeLj40Nffvml6Om3Hz16RN7e3iSRSKhy5cpkYWFBEomE2rZtq3GGaE2ys7Np5syZwnBLAwMDksvlNGvWLK3WpImOjqauXbtSjRo1qGbNmtStWzc6duyY6POfPXtGa9asoTZt2pCBgQHVqVOH5syZo9WyE/3796cWLVrQmTNnqEKFCnTw4EHavHkzubq6qizHUZiSzJyaf2oDTTMOm5mZFbiuVFHLBWg7AywRkZWVlTCcuFKlSnTt2jUiyp2iPW/5j7JIqVTStWvXtF7nrHLlyhqnfThx4oRWM/RWrFiRzp8/r5YeHx8vegb20lKuApQNGzYUuhXE2NiY/vnnHyIqeG6JssjExISuXLmiln7lyhXRU27/+++/tGLFCmrRogVJJBLy8PCg+fPn04MHD7Qqy8iRI6lOnTq0Y8cOMjU1pV9//ZV+/PFHcnBwoC1btojKw9bWVlhuPSwsjGrWrEkZGRm0atUqnd6gdBFY6CqfwvKoXr268EVVsWJFunXrFhHlTsP92WefFZqvLhekI8qdY6ak85307duXGjdurPKevXz5Mnl6eoqePnzKlClUpUoVWrVqFV24cIESEhLop59+oipVqghLwxdl8+bNZGRkRH379hWmMe/bty8ZGxtTWFiY1tf14MEDWrBgAdWuXZsMDQ1Fn6dQKOivv/4iotyg+fr160SUOydTy5YtReVRsWJFYemO/A4fPlzkwpZ3796lpKQkkkgkdPbsWWGBzbt379I///yj1YJ0umBhYSF8FqpXr05HjhwhIqJbt26910ULdSUjI4OGDBlChoaGZGhoKFzbmDFjKDg4uMjzBw4cSG5ubhQbG0s5OTmUk5NDp0+fJnd3dxo0aJDocnTv3p1at25NDx8+FNL+/vtvatOmDfXs2VPr69KlchWgFJeHhwcNGjSINmzYQBKJhFasWEEbN27UuJUlDRs2pP79+6ssOPbmzRvq37+/VotR5blz5w7Nnj2b3NzcyNDQUKvVPx0dHeno0aNERMJaPES56wn5+vqKysPExITu379PRLkfzsmTJxMR0b1790RN+OTt7U3Pnj1TS09LS9PJSqbv0kWAEhYWVuAEUmZmZsKEgAqFguLi4ogod5K/SpUqicpflwvSlVSlSpXozJkzaul//fUXyeVyUXnY2dnRnj171NJ3795N9vb2ovKoXbs2LVmyRC198eLFVLt2bVF55MnMzKSIiAjq3bs3mZiYiC4DkW4mWRs4cCBVrVqVduzYQQ8ePKAHDx7Qjh07qFq1avTFF19odS0l8ezZM1q0aBENHTqUhg0bRkuWLKHnz59rlUerVq2ERRg/++wz6tSpE504cYK++OIL0ZNo6pOxY8dS48aN6fjx41ShQgXhXrFnzx5RP7iePXtG3bt3J4lEQlKpVGg96Nmzp1av7f3796lhw4ZkbGxM1atXpxo1apCxsTE1atSowB+ipbHWkiblqg8KANy+fRvr16/H7du3ERISAhsbG0RGRsLR0RFubm4az1m9ejUmTJiAffv2QSKR4Pvvvy+wk6zYUQ36YPXq1ejWrRscHR1Rv359ALnzjkgkEvzxxx9a5+fs7IwpU6agfv36mDZtmlZDIvNGcwC5/U3y+ke0atVK9NT/jo6OOH36NCwtLREZGYnw8HAAuW3qYjowRkdHq/XTAIA3b97g+PHjYi9FtKlTp6q0Dxc1ZDu/vB78/fv3L/AYBwcHJCcno2rVqqhZsyYOHjyIRo0a4ezZsxrXR9FEV8shAMDZs2exY8cOjf1hxCwjkJOTo7ETtbGxsdo04AV5+vSpxmH8tWvXFt3B/c6dO+jWrZtaevfu3TF16lRReRw9ehRbt27Fzp07kZ2djV69euH3338vsHO7Jq6urrh+/TqqVauGBg0aCH3rVq9eLXro+urVqzFx4kR8/vnnQn8AIyMjDB06FAsXLhRdFqD4o2fOnTuHjh07wtTUFJ9++imICEuWLMGcOXOE96wY33//vdDZevbs2ejatSv+7//+Txg4UNbs3r0b27dvR7NmzVS+b+rWrVvgBHr5WVhYYM+ePbh58yauXbsmDN+uWbOmVuVwdHREfHw8oqKiVPIpbE2vZcuWCf8vaq2lEilReKNnoqOjydTUlNq3b09SqVSISOfPn0+9e/cWlYdEIqGUlJTSLOZ7lZGRQWvWrKHx48fTuHHjaO3atcWa0vnEiRM0YsQIqlKlCpmbm9OAAQNo//79os/38PAQ2ps7dOggTF0eEhJCn3zyiag8fvrpJzIyMiILCwuqV6+e0Kdg+fLlha6amTcVtkQioaNHj6pMjx0fH09z584lJycn0ddClLtC9po1a+jHH3+kmTNnqmwFqVatmqjN2dlZVBkmT55Mc+bMISKiHTt2kJGREdWsWZOkUqlQu1SUt2/f0sKFC6lJkyZka2tb7F8/27ZtI2NjY+rSpQtJpVLq2rUrubq6klwuL3IZgTy6qGr+9NNPacyYMWrpo0ePpqZNm4rKo0aNGrR69Wq19NWrV1PNmjWLPP+TTz4hExMT6tGjB/3222/FrqHasmULrV+/nohy+wPk9d8yMTGh8PBwrfJKT08Xmry0/fxrWnYjf/+UorRq1YoCAgJU+lhkZWXRoEGD6P/+7/+0Ksu7njx5Qjk5OSXK40MxNTUVvqPy17YmJCSIrgHVB7169RL6Bua3YsUK6tGjR4nyLlcBSrNmzWjx4sVEpPoHP3PmjOiq1bt379LTp0/VqiNL2r5eVk2ZMoWqVatGUqmUOnfuTGFhYRrX1CnKkiVLhI6bR44cIVNTU6FKctmyZaLzOXv2LO3atYtevnwppP3xxx9C9bcmJensp0lx19AobadPn6bFixdrbOIoSEk62ubn4eFBK1euJKL/ffZycnJo+PDh9MMPP4jKozhVze+Kjo6mChUqUJ06dWjIkCE0dOhQqlOnDlWsWFF0J9dVq1aRVCqlr7/+mjZt2kSbN2+mr776imQymcbA5V1r1qyhp0+finoubWRkZFBcXBz9+++/Os+7MF27dqUePXpQamoqVaxYka5cuULHjx+nTz/9VNRramJiQlevXlVLv3z5cpnsO6IrrVu3puXLlxNR7mfmzp07REQ0atQo6tixY5Hnv337ln755Rf67LPPqF27duTt7a2yaePQoUMUFBREQ4cOpcGDB6tsRdHVWkualKt5UCpWrIhLly7B2dlZZf6Iu3fvonbt2qLWatFUHXnu3Dm8fv0aBw4cQOPGjd/DlehOSVbLBIAWLVpgwIAB8Pf31+nMk/fu3UNcXBxq1KghND+JlZmZiaSkJNSoUUPU+kD37t0DEQlDE/PP1SGVSmFjY6PVzIvFXUNDH9WoUQPLly9Hly5dYG5ujoSEBCEtNjZW9FIHFSpUwOXLl1GtWjVYW1vj6NGj8PDwwNWrV9G2bVthunUxtKlq1uThw4dYtWqVSh4jR46Evb296DwiIiKwePFiXL16FUDunA6TJk0qcDbq8sza2hpHjhxBvXr1IJfLcebMGbi6uuLIkSMIDAwscNmNPLa2tti8ebPakNUDBw7giy++wKNHj0SVIyMjA/PmzROWMnn3flbUvCH65tSpU+jUqRMGDBiADRs24KuvvsLly5dx+vRpxMTEFPldM3r0aGzYsAFdunTROHN6YZNs5jdz5kzMmjULnp6eGvN5d4Xwd+lqrSVNylUfFAsLCyQnJ6tNgHP+/HnRcyGMHz8e3bt3x88//yx8+b19+xbDhg3D+PHjcezYMZ2Xu7T8/PPPGDFiBKytraFQKFTeeBKJpMgAJSsrC66urvD19dX5tNhOTk5azzfx6tUrjBkzRlhD5MaNG6hevTrGjh0Le3t7TJkypcDnAiC6H0NRiruGxrv+/vtv7N27V2O7vpgZPgHg+vXrWLFihTBvSO3atTFmzBjRS9KnpKTAw8MDQG6An7deTdeuXbVqP7a0tMTLly8BAJ988gkSExPh4eGB58+fa70sQ4cOHdChQwetzsnvk08+wZw5c4p9PgD4+fmJWitJ13Q9C6wuZGdnC5MhWltb459//oGrqyucnJxErU3k7++PoUOHYtGiRWjRogUkEglOnDiBSZMm4bPPPhNdjmHDhiEmJgYDBw7U+EVa1rRo0QInT57EokWLUKNGDaE/zunTp4XPZGHCw8Px22+/oXPnziUqx+rVq7FhwwYMHDiwWOfraq0ljUpU/6JnJk2aRK1ataLk5GRhpMiJEyeoevXqNGPGDFF5lKfqyKpVq9K8efNKlIdcLtfJkFui3GrELl26CNX3Xbp0oaioKNHnl7TXO1Hx+o68a8iQIRQaGir6eE0OHTpEZmZm5ObmRkZGRtSgQQOysLAguVwuuno2r99Js2bNaPz48TR+/Hhq3rw5GRkZ0W+//SYqj1q1alFsbCwR5fYVyBveGB4eTlWqVBF9PZ999pnQvDp79myqUqUKDRs2jJycnMjPz09UHmPGjNHYrLRixQr65ptvROXx66+/arz23377rdCpBvI7c+aM8JrkFxsbS2fPnhWVR3Hln0fGy8uLzM3NyczMTJijpkKFClSpUqVSGXVWkOKMnrlw4YLQR0ypVNLYsWOFJl0DAwOSyWQ0btw4evPmjehyyOXyQptyPzZ2dnbC0POSsLS0FKYoKK7Y2FhhdGiDBg2of//+Gj9D2ipXAUpmZib1799f6GtgbGxMBgYG9Pnnn4ses29jY0MHDhxQS4+MjCQbGxtdF7lU6WLCsYCAAOGLpyRWrFhBRkZG1K9fPwoJCRHm6jA2NtbYwUqTqlWr0unTp4lItY/RzZs3RU0opKu+I3PnziVra2saNGgQLVq0SLievE2MJk2a0LRp01Su5eXLl9S9e3datWqVqDycnZ2FPPL74Ycf3mtHW6Lczop5nVuzs7Np/vz51K1bNxo/frzo/hj29vZ07tw5tfS4uDjRHalr1aolzI+RX3R0NNWqVUtUHk2aNKEdO3aope/cuZM+/fRTUXnowuLFi6lbt24qr9/Tp0+pR48etGjRovdWjsjISNq5cycR5XaYrVOnDkkkErK2ttY4xwqR6nxSzs7O9PjxY8rIyBA6pxenH1u1atU0zutUVu3bt48iIyPV0iMjI0UNQFi0aBGNHDmyxJ2Ev/32W5o1a1aJ8igt5SpAyXPr1i3asWMHbd++XfQslnnGjBlDDg4OFB4eTvfv36cHDx7Qtm3byMHBQfSvOH2hi1/6s2fPJgsLC+rduzfNnTu3WF/GRLlfPpoCkZUrVxY5o2WekvZ610WNElHho3HEBgb5J1azsLAQZvtMSEgQPaLI1NS0wM5pxa3ti42N1bqjbVZWFm3YsIGSk5OL9Zx5ZDKZxuu5efMmyWQy0Xlomq01KSlJ9OSE+Wvn8rtz506Rk5vpUklmgS1tRY2esbS0FH5BSyQS0TMBF2bz5s30n//8p1jBjT7y8PDQONP3n3/+SfXq1Svy/J49e5JcLidnZ2fq2rUr+fn5qWxijR07liwsLKh169Y0evRooTY2bxPj1q1b9N1339Fnn30mBKZ//vmnxvevNspVH5Q8NWrUEL2S47sWLVokzHfy9u1bALnzMIwYMQLz5s3TZTFLXUlXywSAX375BRYWFoiLi0NcXJzKPjGrGed58eIFOnXqpJbu4+MjurNpkyZNsG/fPowZM0Z4fiC3r42YFZF11XekpGtoALmdSpVKJQDA3t4et2/fFubpefz4sag8vLy8cPz4cbV5D06cOFHkOitAbh+jL7/8EtOmTRMWI2zatCmaNm2qzaXAyMgII0aMEDqUFlfNmjURGRmptjL1n3/+KXqxRBsbG1y8eFFtLa4LFy7AyspKVB4ymQyPHj1Se87k5GRRnbJ15cWLF3j06JHa/E2pqalCf5/3IS0tDdnZ2Spz+lhaWuLp06cwMjLSuI5W79690aZNG6GviKenZ4Ed0cV2bl28eDFu374NW1tbVKtWTe1+Fh8fr8VVfXg3b95E3bp11dJr166NW7duFXm+hYWFTvpJXbx4UVgrKjExUWWfmH4+MTEx8PX1RcuWLXHs2DHMnj1b+Bz+8ssv+O9//1vsspX5AGXChAn48ccfUaFChSI7mInpVCaVShESEoLg4GDcvn0bRISaNWuqLIJWVqxduxYVK1ZETEyM2qRqYoMLXXwZA7mTOUVERKj19N6zZ4/GSbE0CQ4ORqdOnXDlyhW8ffsWISEhKr3ei9KnTx8cPHgQX3/9tdblF/s+k0gkWLx4cZH5NWvWDCdPnkTdunXRpUsXBAYG4tKlS9i1axeaNWtW4Hl79+4V/t+9e3dMnjwZcXFxwjmxsbHYsWMHZs6cWWQZjI2NERERUfLJlJAb2Jw/f75EC+1NmDABo0ePxr///itMaHb48GEsXrxYZWKowvTr1w9jx46Fubm5sMx7TEwMvvnmG/Tr109UHh06dEBQUBD27NkjLJj4/PlzTJ06tUSdd7Xl5+eHwYMHY/HixSp/30mTJqFXr17vrRz9+vVDt27dMHLkSJX03377DXv37sX+/fvVzlm7di169eqFW7duYezYsRg+fDjMzc1LVI6ePXuW6Hx9I5fLcefOHbVg+tatW6hQoUKR569fv17U85w8eRKenp4FTt6Yf3HJwvz999+wt7eHgYGBSvqUKVMwe/ZsTJgwQeVv7O3tjZCQEFF5F6TMDzP29vZGREQELCws1JYZf5fYPwTTjfwzp7548QKLFi1Cy5YtVXp6nzx5EoGBgfj+++9F5ZmYmIiFCxciLi4OOTk5aNSoESZPniyq13twcDCWLFmCLl26aF2jJPZ9JpFIRC1hf+fOHaSnp6NevXp49eoVJk6ciBMnTqBmzZpYunRpgV/0794cCiuHmFViBw8eDA8PD61Gj2iyY8cOTJkyBePHj0fjxo3VbrD16tUTlU9oaCjmzJmDf/75BwBQrVo1zJgxQ/QMzpmZmRg4cCB27Ngh1Hbk5OTgiy++wOrVqyGVSovM4+HDh2jdujWePHkirKSckJAAW1tbREVFwdHRUVRZSirvffHrr79qnAVWzJeYLlhaWuLkyZNqK4Zfu3YNLVu2xJMnTwo9f/DgwVi+fHmJA5Ty5ssvv0RsbCwiIiKEGv9bt26hd+/eaNKkSclHwPx/lSpVQkJCguhaSG3z0cX0HgUp8wEKK11DhgwpdP+vv/5a4L53h3sXRCKRFFnNq6k5QluFlUdMGcqjOXPmYNGiRWjXrp3GwEJsE56mwEkikYCIRAdL+f37778wNTUVhrfmV9QvQiC3+jwhIQGmpqbw8PDQumYnIyMDYWFh/6+9e4+LMX//B/6aSmpXJypaUpKNKCTWZpfQsqvdkHWmJbGxm2Qp1obCaiPHtU4RsXLOLlHtdkJYOpAUEh1QOYYOPh3m/v3h13ybZqp7mmnumVzPx6PHI/fMvOcK01zzPlwXbty4AU1NTVhbW2Py5MliS/E3t9LSUqHZXHklJjU+/PBDwTJxbTdv3sQnn3wi8TFyaRQXF+P48ePIzs7G4sWL0bZtW6SkpKB9+/asS0koilevXuHLL79EUlISOnXqBODdLMXnn3+OkydPQldXVybPUztpaI5xOnXqhKNHj8LOzk7oPuHh4Vi0aBGrsv31aVEJiqurKzZv3iySqZeWlsLDw6PBN9OWQtZLXnXXOCsrK5Geno7i4mIMGzaMVY8VWdHV1UVKSorULzRFYGZmhmvXronsiyguLoaNjY3ckiVZJW2NFWOSZumnLll8IpTFGI6OjggODmbdF0caDx8+BI/H4+RN2N7eHlZWVti6davQ9R9++AFpaWnN0sdKnLS0NDg4OEBHRwc5OTm4c+cOzMzM4Ovri9zcXISGhsolDlliGAb//POPUCJcszQpK82doHh7e+Py5cs4duwYPv74Y6SkpKCoqAguLi5wcXHBihUrmvycLSpBUVVVRUFBAQwNDYWuP3v2DB06dBBsem3J2rZti7t370JfX18mSxHi8Pl8zJs3D2ZmZvD29m5qqBKT1XKEpJVom4OKigoKCwtF/q8WFRWhc+fOgg20DfH392/wdjaVgpWRLH7hKsoYDeHz+Vi9ejWCgoJQUlIieM6ffvoJy5YtY73cJ63ExEQ4ODigf//+GD58OIB3e4OuXbuG6OhoVhuyZcHBwQE2NjYIDAwU+ru/dOkSpkyZgpycHLnEoWyaO0GprKzEjBkzcPjwYTAMAzU1NVRXV2PKlCnYt2+fRFW661L6TbLAu/0NzLsj03jz5o1QZ9vq6mqcPXtW5I2gpSouLhZUTM3NzRX7KV1aKioq8PLygr29PesERZqlohrm5uZYtWoVLl261KTliKZWopWl2ptco6KiBJswgXf/V2NiYkQ2zdWnbgnqyspKPHjwAGpqaujatatECYq0SVtjn16VqQu4oli2bBn27NmDgIAADBo0CAzDIDExEStXrsTbt2+lrpbL1qBBg3D58mUEBgbi6NGjgk/6e/bsQbdu3eQSA/CuW/bOnTtFrnfs2BGFhYVyi0MaW7ZswZw5c6ChodFod3O2y6tca9WqFf7880/4+/sjNTUVfD4fffv2lc3/DakOKSuI2s3gxH2pqqoyq1ev5jpMuWiO+gPiREREMPr6+qzvP2bMGKEvR0dHxsTEhNHR0WF9Zl/a+iOyqEQrrdqdYOs2LVRXV2c+/vhj5vTp000e/9WrV8zYsWOZ0NBQVvcvLS1lXF1dGVVVVUZVVVXwd+Lh4SGoKsuGrq6u0NeHH37I8Hg8pnXr1hJ1RWajdg0cZR+jIUZGRmLr0Zw6dYp189OWxNDQkElJSWEYRvjvPioqiunUqROXobFmamrKPHv2TPC9tPWU2JBFwU5ZjiOJFjGDEhcXB4ZhMGzYMJw4cULovL66ujpMTEwkahSmzGRdf6DucgrDMCgoKEBERAS+++471nGJazhVe6mIDWmPPJ86dQpHjhzBwIEDhc73W1paSrWRSxI1s1tdunTBtWvXZN7jSFtbG/7+/vj6669Z9dZYunQpbty4gfj4eKE6NQ4ODlixYgXrWaWXL1+KXMvKysLcuXNFjpYTdl68eIHu3buLXO/evTtevHgh11iqq6tx6tQpQc8nS0tLODk5STV9L6nRo0fD398fR48eBfBumTovLw9LlizBuHHj5BaHNGr/DpNVCYfGMDLaxVHfOAzD4Pjx44iLixPbxFGafYotIkEZMmQIgHf/4MbGxnJbm1VEsq4/ULdTqYqKCgwMDBAUFNTosk1jmrJUVKPmxSJJw7CnT5+KXeorLS2Ve+Ox5vzlVFxcLGj615jmTNq6deuGgIAATJs2Dbdv35ZqrNpk8W+lDI3mevfujd9//11kKeD333+XuAO4NO7duwdHR0c8fPgQFhYWYBgGd+/ehbGxMSIiIppcFFNS69evx6hRo2BoaIjy8nIMGTIEhYWF+PTTT+W23CUttvvn2NZTYqOhon5VVVXQ0NDA9evX0atXrwbHycjIEPtB39PTE7t27cLQoUPRvn17mb62WkSCUqPmpEBZWZnYDrFsazEou5pPwsnJyfD09JQqQYmIiADDMIL9Hjk5OTh16hRMTExkssE0Oztbos3Le/bswcaNG5GVlQXg3ZvgggUL4Obm1uhjpa1EK2sxMTH1to5nsyen7htXzezWgQMHxFbtFae5kzZVVVVBTRNZkcUnQll9qmxOgYGBcHR0xL///otPP/0UPB4Ply5dQl5eHs6dOye3OObPnw8zMzNcvnxZMDv9/PlzTJs2DfPnz0dERIRc4tDW1sbFixcRGxuLlJQUQR0kBwcHuTy/LNT9wFef+l57ffv2Zf26ZFNZV01NDSYmJqzKANRX/+fgwYM4efKk1F2VxWlRCcrTp08xc+bMel+8ktZiUHZsKw02ZMyYMXB2doa7uzuKi4sxcOBAtGrVCs+ePcOGDRswd+5cVuPIYqnI19cXGzduhIeHhyChuHz5Mry8vJCTk4PVq1c3+HhpK9HKkp+fH/z9/WFra9vk1vEbN24U+nPN7NZ3332HpUuXshpDVklb7c2/wP/9+/7+++8YNGgQ63GqqqoQHx+P7OxsTJkyBVpaWnj8+DG0tbUFNVFkUeb93LlzUh/Z/fnnn4WWk2VtyJAhuHPnDrZv347MzEwwDANnZ2fMmzdPrkvWCQkJuHLlitDP2q5dO8HmXXkbNmyYoNKwspG2WGhzVNP95ZdfsHTpUhw8eLBJ/591dHSa7SRbizpmPHXqVOTk5GDTpk2Cyp9FRUWCo3qOjo5ch6h09PX1kZCQgJ49eyI4OBhbt25FamoqTpw4geXLl7Puv1L3yHPNm+mwYcPg6urKajZGX18fW7duxeTJk4Wuh4WFwcPDg1UPG2kq0cqSkZERAgMDWe0TaU6XLl3Cl19+ialTp2Lfvn34/vvvhZK2fv36sRqn7rIqj8cT/PsGBQWxqhWSm5uLL7/8Enl5efjf//4nOGW1YMECvH37Fjt27BD7OEmOnbOp/QMABw4cwI4dO/DgwQNcvnwZJiYm2LRpE7p06YLRo0ezfj5pvX37FmlpaWJn2ZycnOQSQ9u2bXHmzBnY2dkJXU9MTMQ333zTrPthGjvpUpuynHpRNH379sW9e/dQWVkJExMTkdORjc3E7N+/H5GRkdi7dy80NTVlGluLmkGJjY3FX3/9hf79+0NFRQUmJib44osvoK2tjbVr11KC0gRlZWWCJaLo6Gg4OztDRUUFAwcObLQ4V22yaDNQXV0NW1tbkev9+vVjtUw0depU2NvbY9myZfj444+ljkcaFRUVIr/wJSWLwoR2dnZITEzE+vXr0bVrV0RHR8PGxgaXL1+WKGmr++bZFJ6enrC1tRVp7Dd27NgGl/CknTava/v27Vi+fDkWLFiANWvWCGZedXV1sWnTJrklKJGRkXBxccHz589FlqSaUp23qb7++mvMmTMHe/bswYABAwAA//33H9zd3Zs9Sao7S1gfSRqXEmHSzsqMHz8eYWFhMDQ0lH0TR7meGWpmWlpaglbrJiYmzMWLFxmGedcmvant5993VlZWzObNm5m8vDxGW1ubuXTpEsMwDJOUlMS0b9+e9ThDhw5lXr58KXL91atXzNChQ1mNUdMKvK6ffvqJmTdvXqOPnzNnDmNhYcGoqKgwRkZGzKRJk5jt27czmZmZrJ5flry9vRl/f3+pxlBRURG0Nq/t6dOnjKqqqlRjS8rPz48pLS0VuV5WVsb4+fmxGqNdu3bM7du3GYYRPkb64MEDub5+e/TowYSHh4vEcfPmTaZdu3Zyi6Nr167MvHnzmMLCQrk9pzgvX75knJycBEfh1dXVGR6Px4wZM0bsa5rIR1VVFbNu3Tqmf//+TPv27Rk9PT2hL3kZP348o6+vz7i7uzMrVqxgVq5cKfQljRY1g2JhYYE7d+7A1NQUffr0wc6dO2FqaoodO3bIpRx1S7R8+XJMmTIFXl5eGD58uGBfQnR0tKCRGhvx8fEim5aBd1PYkpTK3rNnD6Kjo4W6u+bn58PFxUVoql/cVH5NkafCwkLEx8cjPj4emzdvxg8//ABDQ0MUFBSwjkNab9++xa5du/Dvv//C2tpa5FNHQ0sRsi5MWF1djfDwcMER0h49emD06NESbYL28/ODu7u7SNfvsrIy+Pn5sSoax+fzxc4KPHz4UK6N5h48eCD2/3br1q1RWloqtziePHmChQsXon379nJ7TnF0dXXx119/4d69e4K9MJaWljA3N+c0rvedn58fgoODsXDhQvj6+mLZsmWCQwySVpGWpsdRREQEoqKi8Nlnn0nz44jVohKUBQsWCN5kVqxYgZEjR+LgwYNQV1cXVA8lkvn222/x2WefoaCgQOho4/Dhw0X69IiTlpYm+D4jI0Oo4mN1dTUiIyNZb1ZMT0+HjY0NAAiOwBoYGMDAwADp6emC+zU2la+lpQU9PT3o6elBV1cXampq6NChA6sYZCUtLQ19+vQBAKHYgcbj19XVBY/HA4/HE7tUxePx4OfnxyqO9PR0jB49GoWFhbCwsADwrsKugYEB/v77b9bLPMz/bwpY140bN1hvvPviiy+wadMm7Nq1S/BzlJSUYMWKFQ2eEHB2dsa+ffugra0NZ2fnBp+DTU2GLl264Pr16yL9g86dOwdLS0sWP4lsfPvtt4iPj5fbMd7aGtvXEx8fL/ie7b6epsYhy95iLcmff/6J3bt3w9HREX5+fpg8eTK6du0Ka2trXLlyhfWSV90eR7Nnz0bbtm0RHh7OqseRsbExtLW1ZfEjiWhRm2RrYxgG5eXluH37Njp37izzgliEHRUVFcEbl7j/apqamti6davUNVVqe/jwIT766CORjZs+Pj5ISEjAjRs30KtXLwwePBhDhgzB4MGDZdY5VB4SEhJkVphw4MCBMDQ0xP79+6GnpwfgXdG1GTNm4MmTJ7h8+XKDj9fT0wOPx8OrV6+gra0tlKRUV1ejpKQE7u7u2LZtW6OxPH78GEOHDoWqqiqysrJga2uLrKws6Ovr4/z58/XOCs2cORNbtmyBlpYWZs6c2eBzsDnZFhISAl9fXwQFBWHWrFkIDg5GdnY21q5di+DgYEyaNKnRMWShrKwM48ePh4GBAaysrERm2Zpzz0VDfbxqk6anFxvy6C2mrD788ENkZmaic+fOMDIyQkREhKDRaN++fVnXQpK2x1FERAS2bt2KHTt2sG7TwVaLS1CkqZNBZC83NxcMw8DMzAxXr16FgYGB4DZ1dXUYGhrKvBplfZ1qa04OeXl5YfTo0ejRo4dMn7cp7t27h+zsbAwePBiampr1zkSIk5ubK3VhQk1NTSQlJaFnz55C19PT09G/f3+Ul5c3+Pj9+/eDYRi4urpi06ZNQr2F1NXVYWpqKtFx5fLychw+fFjolNXUqVNlfjqgMbt378bq1auRn58P4F2/l5UrV2LWrFlyiyE4OBju7u7Q1NREu3bthP5fSNJpWpnVbqpZXwfw95WFhQVCQ0PxySef4PPPP4ejoyOWLFmCI0eOwMPDA0+ePGE1jo6ODlJSUtC1a1ehBCU3NxcWFhZ4+/Ztg4/X09NDWVkZqqqq8MEHH4gk0tKc8mpRSzzS1skgslczTS6LUx5s1Zdzp6amIiEhAfHx8QgKCoKqqiqGDBkCe3t72NvbyzVhef78OSZMmIC4uDjweDxkZWXBzMwMbm5u0NXVZVVFMjg4GCtXrhS5/urVK7i7uyMsLKzRMSwsLFBUVCSSoDx58oTVHoOaGjZdunSBnZ2dyC8nSZw/fx52dnaYOXOm0ExIVVUVzp8/L/M29A2ZPXs2Zs+ejWfPnoHP53PSbPSXX36Bv78/lixZ8t5Wx9bT08ODBw9gaGiInJwcuf4eUXRjx45FTEwMPvnkE3h6emLy5MnYs2cP8vLy4OXlxXocDQ0NvH79WuT6nTt3hD5Q1mfTpk2ShC0ZqbbYKph27doxhw4dErl+6NAhue6+J+LduXOH2blzJ7Nq1SrGz89P6EuW2DZxu379OjNjxgxGTU2NUVFRkWkMjZk+fTozcuRIJj8/X6TxmaWlJasxOnfuzHzyySfMvXv3BNfi4uIYY2NjZuDAgazGiIiIYHr27MkcO3aMyc/PZ/Lz85ljx44xVlZWTEREBPPq1SvBF1tlZWVCj2P72PpOJT179oz1v09hYSEzbdo0xsjIiFFVVRVpHMqGLE6cyYKenp7Qv+37aPbs2Uzr1q0ZU1NTRkVFhencuTPTpUsXsV/vuytXrjBBQUFiG0w2ZPbs2cyYMWOYiooKpk2bNsz9+/eZ3Nxcpm/fvoynp2fzBMtSi1ri0dPTw9WrV0XaPN+9excDBgxAcXExN4ER7N69G3PnzoW+vj46dOggMl0t1Vn5OmpPU9aVmpoqOMFz4cIFvH79Gn369MHQoUOxbt06mcXQmA4dOiAqKgq9e/cWivfBgwewsrJCSUlJo2O8evUK33//PSIiIrBhwwbcvXsXmzdvxpIlS7BixQpWS2e1P5nX3StU+8+N1d0oKyuDt7c3jh49iufPn4vczqZmh4qKCoqKikQ+td29exe2trZiP+XV9dVXXyEvLw8//vij2Aq9bGqY1F5WqO3Jkyfo2LEjKisrGx1DFry8vGBgYICff/5ZLs+nqCIjIwW9xfz9/es90eXp6SnnyFqG169fY9SoUbh16xbevHmDjz76SNDj6OzZsyKF2xpSXl4u8vqQZgNti1rimTZtGrZv3y6ym3vXrl2YOnUqR1ERAFi9ejXWrFkDHx8fzmLQ09NDSUkJevfuDXt7e8yePRuDBw9uth3oDSktLRU5kgsAz549Q+vWrVmNoaOjg8OHD2PZsmX4/vvvoaamhnPnzmH48OGs45BFAT0AWLx4MeLi4vDHH3/AxcUF27Ztw6NHj7Bz504EBAQ0+Niakzc8Hg8zZswQ+vmrq6uRlpbGuqjdxYsXceHCBcEJKUnI8sSZLFRXVyMwMBBRUVESH0VvSWTZW6wlWbt2Ldq3by9ywGDv3r14+vQp69+10vY4Ki0thY+Pj1QfTurTomZQPDw8EBoaCmNjY7F1Mmq/wN+XF7eiqG/jqjyf68yZM5wlJHU5OjrCxsYGq1atgpaWFtLS0mBiYoJJkyaBz+fj+PHjrMbZunUrfHx8MHbsWCQnJ0NVVRWHDh2Sa7dbAOjcuTNCQ0Nhb28PbW1tpKSkwNzcHAcOHEBYWBjOnj1b72Nr9pvs378fEyZMENoQW7PRdvbs2axO4llaWuLPP/+UqEZPDS5OnDWETq2QhpiamuLQoUMiyft///2HSZMmNWvH9Np++OEHxMXFwd/fX+yHE2kmB1pUgqIoR+OIqFmzZqF///5wd3dv9udqaIlHUWRkZMDe3h79+vVDbGwsnJyccOvWLbx48QKJiYmsal989dVXuHr1Knbu3Ilvv/0W5eXlWLhwIfbt2wc/Pz94e3uzikUW/V7atGmDW7duwcTEBJ06dcLJkycxYMAAiZas/Pz8sGjRIommlOuKjo5GUFCQoEijJLg4cUZIU2loaCAzMxNdunQRun7//n1YWlo2evqmNmk6q0vz4aQxLWqJR1bT1UT2zM3N4evriytXrjR7TYeMjAy5dnttCktLS6SlpWH79u1QVVVFaWkpnJ2d8cMPP7CuelxVVYWbN28KflZNTU1s374dX3/9Ndzc3FglKDX9XsQ1WpSk34uZmRlycnJgYmICS0tLHD16FAMGDMDp06dZ15hhGAbPnj2TOEGpqcVSo7S0FF27dpX4yGPNibM3b95IlSQRIg/GxsZITEwUSVASExMl+v0nbWf1Fy9eCGLQ1tYWvMY+++wz1t3u69OiZlCI4qr7IqqNbU2H0tJSBAQE1Jvpvw91Ieq6cOECdu7ciezsbBw/fhwdO3bEgQMHYGpqis8//7zRx5ubm2PkyJFYvny5VCXVN27cCFVVVcyfPx9xcXFwdHREdXU1qqqqsGHDBlYbGG1tbXH9+nUMGTIEs2bNgrOzs1AZ//pIUiW65lh0Q9q0aYMJEybA1dW1Wcp3EyILv/32G9atW4d169Zh2LBhAN7NhHh7e+Onn37C0qVLWY0jbWd1a2trbN26FUOGDMGIESNgbW2N9evXY8uWLQgMDMTDhw+bNC5ACQpRIpMnT0ZCQgKmT58uNtNXtl380i6tnDhxAtOnT8fUqVNx4MABZGRkwMzMDH/88QfOnDnDampVW1sbqampMi+nnpeXh6SkJHTt2lWi/TBpaWkICQnBoUOHUFFRgUmTJsHV1RX9+/eXaXwNOX36NPbt24czZ87AxMQErq6ucHFxUfhZOfJ+YRgGS5YswZYtWwR9zjQ0NODj4yNRL5527drh6tWrTf4dIIsPJ/WhBIU0G7Z9NHg8HqvCZLq6uoiIiMCgQYNkGSYnZLG00rdvX3h5ecHFxUVo383169fx5ZdfCp1CqY+rqysGDRrULBVSi4uLm9xCoKqqCqdPn0ZISAgiIyNhYWEBNzc3zJgxQ6harTiyaH4IvCumFxoain379iEjIwMjR46Eq6srnJycJB6LkOZSUlKCzMxMaGpqolu3bqxPAdbw8fFBmzZt4OvrK5N4mvrhRBxKUEizGTp0KMLDw6GrqyuTEwldunTB2bNnFaJEvbRksbTywQcfICMjA6ampkIJiiSb5GTV7+W3336DqakpJk6cCACYMGECTpw4gQ4dOuDs2bMS/6KqqKhAeHg49u7di9jYWNjZ2aGoqAiPHz/G7t27Bc9Tl6yaH9a1detWLF68GBUVFdDX14e7uzuWLFki9qg4IYqu9gdGPp+P/fv3w9raWuGOs1OCQpTGwYMH8ddff2H//v1K/8Ygi6WVrl27YufOnXBwcBBKUEJDQxEQEICMjIxGx5BVvxczMzMcPHgQdnZ2+OeffzBhwgQcOXIER48eRV5eHqKjo1mNk5ycjJCQEISFhaF169ZwcXGBm5uboOx+UFAQAgMDUVRUJPbx0jY/rK2wsBChoaEICQlBXl4exo4di1mzZuHx48cICAiAkZER65+LEFmQVedutideAXaHT6Q5BdQQmqckSiMoKAjZ2dlo3749TE1NRTJ9WVajbW7ffvst4uPjpUpQvv/+e3h6emLv3r3g8Xh4/PgxLl++jEWLFrFeg5ZVv5eCggIYGxsDeFdvZsKECRgxYgRMTU3xySefsBrD2toamZmZGDFiBPbs2YNvvvlG5Fivi4sLFi9eXO8YN27cQFJSkiA5Ad6d8lmzZg3rfSwnT55ESEgIoqKiYGlpiR9++AHTpk0TWq7q06dPk2qtECINHR0dwYeIxpY6GyLLE6/SngJqCCUoRGmMGTOG6xBk5vfff8f48eNx4cKFJi+teHt749WrVxg6dCjevn2LwYMHo3Xr1li0aBF+/PFHVnFUVFRg4sSJUjej09PTQ35+PoyNjREZGSlozMkwDOujyuPHj4erq2uD1VoNDAwabBgnbfND4F3huEmTJiExMbHepMbMzAzLli1jNR4hshISEiL2e2m4urpi8+bNIhV6S0tL4eHh0egMyI4dO7Bv374mnwJqCC3xEMIBWS2tAO/2kWRkZIDP58PS0hJt2rRh/VhZ9Xv58ccfcebMGXTr1g2pqanIyclBmzZtcOTIEfz2229ym906e/YsvL29sXLlSqFq0v7+/ggICBA6NlxfReGysjKlX0IkhC1VVVUUFBSI9J569uwZOnTogKqqqgYfL+0poIZQgkKUTnJysuCEhqWlpVJOtXfo0AHz58+XemlFWvPnz0doaCh69+4t1Qa5yspKbN68Gfn5+ZgxY4bg32TTpk1o06YN3NzcGh3j22+/ha2tLZYsWSJ0fd26dbh69SqOHTvW6BiyaH549uxZqKqqYuTIkULXo6KiwOfz8dVXXzUaByHNraioCIsWLRLs/aj7Vt7YzOXr16/BMAz09PSQlZUlVDm5uroap0+fxpIlS/D48eMGx5H1KaDaKEEhSuPJkyeYNGkS4uPjoaurC4ZhBEschw8fFumCq8jatm2La9euNcunDknIu9+Lo6MjgoODxVbLNTAwQGxsrMhJm5s3b8LBwaHejbG1JSQksI5lyJAhYq9bW1sjICAAo0aNEroeGRkJHx8f3Lhxg/VzENJcpO3cXbv3lDg8Hg9+fn6NLmV6enoiNDS0WU4BUYJClMbEiRORnZ2NAwcOCI4aZ2Rk4LvvvoO5uTnCwsI4jpA9WS2tKJuG+iRpamri+vXrguPBNW7fvo2+ffuivLxcLjFqamoiMzNTpJdPTk4OevbsidLSUrnEQUhDtLS0mty5G3iXzDMMg2HDhuHEiRNo27at4DZ1dXWYmJiwKk7YnB9yaJMsURqRkZH4999/heqgWFpaYtu2bRgxYgSHkUmuuroagYGBiIqKUojaA/fu3UN2djYGDx4MTU1NwTKIPPXq1QtHjhwROYF0+PBhWFpash6nuLgYe/bsEVoGdHV1ZX3qQUdHB/fv3xdJUO7du0c9eojCMDY2Ftt1m62aGcQHDx5AW1sbe/fuFXrNsH3NNWcPPEpQiNLg8/kib+QA0KpVqwZPdiiimzdvCvZppKenC90mz8Tg+fPnmDBhAuLi4sDj8ZCVlQUzMzO4ublBV1eXVYVfWfH19cW4ceOQnZ0t1FskLCyM1f4TAEhKSsLIkSOhqamJAQMGgGEYbNiwAWvWrEF0dDRsbGwaHcPJyQkLFixAeHi4YAnu3r17+Omnn1h3dyakuW3atAlLlixpUufu2p4+fYp+/fpBQ0Ojya+ZZsMQoiScnJyYwYMHM48ePRJce/jwITNkyBBmzJgxHEamvKZPn86MHDmSyc/PZ9q0acNkZ2czDMMwUVFRjKWlpcyfr/ZziHPmzBnGzs6O+eCDD5h27doxQ4cOZeLj41mP/9lnnzEzZsxgKisrBdcqKyuZ7777jvn8889ZjVFcXMwMHDiQUVNTY0xNTRlTU1NGTU2NGTp0KPPy5UvWsRDSnHR1dRl1dXVGRUWFadOmDaOnpyf0xZa0r5mSkhLml19+YT799FOma9euTJcuXYS+pEF7UIjSyM/Px+jRo5Geng5jY2PweDzk5eXBysoKf/31Fzp16sR1iBLjemmlQ4cOiIqKQu/evYX2hzx48ABWVlYoKSmR6fM1tAdFFjQ1NZGamoru3bsLXc/IyICtrS3KyspYjcMwDP755x/cuHEDmpqasLa2xuDBg5sjZEKapLEu3mw6dwPSv2aas4krLfEQpWFsbIyUlBT8888/uH37NhiGgaWlJRwcHLgOTWKKsrRSWloqtubHs2fPJG46JivSHCPX1tZGXl6eyC/b/Px8kUJUDeHxeBgxYoTS7W0i7w+2CUhjpH3NnDt3rtmauHJXgIGQJvriiy/g4eGB+fPnK2VyArw7xdOqVSvk5eUJJQgTJ05EZGSk3OIYPHgwQkNDBX/m8Xjg8/lYt26dRP062Pr555+FTgvU9uTJEwwbNgz9+/fH/Pnz8eOPP6Jfv34YPnw4nj59ymr8iRMnYtasWThy5Ajy8/Px8OFDHD58GG5ubpg8eTLrOBMSEvDNN9/A3Nwc3bp1g5OTEy5cuMD68YQ0h9evXwt939AXW9K+ZvT09Op9TUuLlniIQtuyZQvmzJkDDQ0NbNmypcH7su28qwjkvbRSn4yMDNjb26Nfv36IjY2Fk5MTbt26hRcvXiAxMZF1nRY+ny+24Byfz8fDhw/RuXPnRseQxTHyiooKLF68GDt27BBUwGzVqhXmzp2LgIAAVrNCBw8exMyZM+Hs7IxBgwaBYRhcunQJ4eHh2LdvH6ZMmdLoGIQ0h9pVX+urY8I0UoiwLmlfM83ZxJUSFKLQunTpgqSkJLRr1w5dunSp936SlofnmpaWFlJSUtCtWzehBOXatWv48ssv8fz5c7nEkZeXBzU1NezcuRPJycng8/mwsbHBDz/8gMrKykYTi9evX8PNzQ2nT5+GtrY23N3dsXz5ckGTv6KiInz00Uesflnq6Ojg33//Fel/c/XqVYwYMQLFxcUNPr66uhoXL16ElZUVNDQ0kJ2dDYZhYG5uLtEvzh49emDOnDnw8vISur5hwwbs3r0bmZmZrMciRJYSEhIwaNAgqKmpNVqUsL5ChPUpKytr0mumb9++gsfJuokrJSiEcMDR0RE2NjZYtWoVtLS0kJaWBhMTE0yaNAl8Ph/Hjx+XSxz19eF4/vw5DA0NG00sPD09ERkZiTVr1qC4uBirV69Gr169cPLkSairq6OoqAhGRkasjoHXV3gqNTUVQ4YMYTVtraGhgczMzAaT2ca0bt0at27dEmkueO/ePfTq1Qtv375t8tiEtDR+fn4N3r5ixYomj02bZInS8Pf3x6JFi0Qy+/Lycqxbt06kwJciW7duHezt7ZGUlISKigp4e3sLLa3IS32fT0pKSqChodHo40+dOoX9+/fD3t4eADB27Fg4Ojrim2++wd9//w2AfV2XYcOGwdPTE2FhYYIKlo8ePYKXlxeGDx/OagwrKyvcv39fqgTF2NgYMTExIglKTEwMjI2NmzwuIdJKS0tjfV9ra+tmjOT/SJOANIZmUIjSkPbTvqIpLCzE9u3bRZZWxPWpkbWFCxcCADZv3ozZs2cLJX3V1dX477//oKqq2miy9OGHHyI9PV0oIXjz5o2gWFpwcDDMzc1Z/dvI4hh5dHQ0fHx8sGrVKvTr10+k8mt9HYxr2759OxYsWABXV1fY2dmBx+Ph4sWL2LdvHzZv3ozvv/++0TEIaQ41+04ae9uWZA+KIqMEhSgNFRUVFBUViTQFjI2NxcSJE1mf9CD/1z8jISEBn376KdTV1QW3qaurw9TUFIsWLUK3bt0aHKd79+7YsGGDSGO9kpISjBgxAmVlZbh586ZEvyzFHSNnWx9GXDdjQPKNg+Hh4QgKChLsN+nRowcWL17caAM2QppTbm4u6/uamJg0YyT1NxvU1taGhYUFvL294ezsLNVzUIJCFJ6enh54PB5evXoFbW1toRdFdXU1SkpK4O7ujm3btnEYZeMUcXp25syZ2Lx5M6uZBXHmz5+PgoICsaXo37x5gy+++ALXrl1jlRisXbsWS5cuFbleXV2NadOmsTrFI+uNg4QoqrVr16J9+/ZwdXUVur537148ffoUPj4+zfr8f/31l9jrxcXFuHr1KkJCQrB//36MHz++yc9BCQpRePv37wfDMHB1dcWmTZuEmr7VfNr/9NNPOYyQnZY4Pfvy5Us8fvwYPXv2FHt7SUkJkpOTWSUG7du3x6pVqzBnzhzBterqakyaNAnp6emsTs/k5eUJlodqYxgG+fn5rI4716ioqMCTJ09ENvhKMgYhzcXU1BSHDh2CnZ2d0PX//vsPkyZNwoMHDziK7J1t27YhNDQU//33X5PHoASFKI2EhATY2dmJbRioDBRpelYRJScnw8HBATt37sSECRNQWVmJiRMn4vbt24iNjUWHDh0aHUMW+5SysrLg6uqKS5cuCV2XdJmIkOZU34m1+/fvw9LSkvPTZllZWRgwYABevnzZ5DHoFA9RGrU/hZeXl6OyslLo9qYuU8hLS006qqqqsHHjRoSFheHu3bvg8Xjo1q0bpkyZAk9PT9YJZb9+/RAeHo7Ro0ejdevW2LNnD7KzsxEXF4f27duzGqO+vSpsTyUBwIwZM6CmpoYzZ86I7S1CiCIwNjZGYmKiSIKSmJgoOAXHpfLyctavufpQgkKURllZGby9vXH06FGxhcyU7ZPtnTt3sHXrVkHfme7du8PDwwMWFhZch8ZaeXk5vvjiC1y+fBkODg4YPHgwGIbB7du34ePjg7///hvR0dGsf1HZ29vjwIEDGDduHHr06IGEhATo6+s3+riaU0k8Hg++vr5iTyXVra9Sn+vXryM5OVmkNwkhisTNzQ0LFixAZWUlhg0bBuDdUXhvb2/89NNPHEcH7N69W6I+WuJQgkKUxuLFixEXF4c//vgDLi4u2LZtGx49eoSdO3ciICCA6/Akcvz4cUyePBm2traC/TNXrlxBr169cOjQIak2lsnT2rVrkZ+fj9TUVJGNvTdu3ICTkxMCAgKwcuVKsY+vb5e/gYEBdHV1hfajnDx5st44UlNTAbybQbl586bIqaTevXtj0aJFrH4mS0tLPHv2jNV9CeGKt7c3Xrx4gXnz5qGiogLAu2UfHx8fsZvNZa3mQ0Fdr169QlJSErKzs6XuX0V7UIjS6Ny5M0JDQ2Fvbw9tbW2kpKTA3NwcBw4cQFhYGM6ePct1iKyZmZlh2rRp8Pf3F7q+YsUKHDhwQGnK9n/88cdYu3Ytxo0bJ/b2Y8eOYdmyZbh7967Y22fOnMn6uUJCQhq9T1NPJdWuUpuUlIRffvkFv/76K6ysrESWqBR9KZG8X0pKSpCZmQlNTU1069ZNbl3I62smqq2tje7du2PevHlSL2tTgkKURps2bXDr1i2YmJigU6dOOHnyJAYMGCD3Bnuy8MEHHyAtLU2kWmlWVhZ69+6NsrIyjiKTjIaGBrKysuqtsJqfn49u3bpxvmGvMXVrOojby0KbZAmRL1riIUrDzMwMOTk5MDExgaWlJY4ePYoBAwbg9OnT0NXV5To8idjb2+PChQsiCcrFixfx+eefcxSV5LS1tfHkyZN6E5TCwkK5zjjUrMXXJzY2Vuz1uLi45giHECIFmkEhSmPjxo1QVVXF/PnzERcXB0dHR1RXV6OqqgobNmyAp6cn1yGytmPHDixfvhwTJkzAwIEDAbzbg3Ls2DH4+fkJ7cJ3cnLiKsxGTZw4EVVVVThx4oTY28eNGwdVVVUcPXq00bG6dOnS4IkZNstedTsQV1ZW4vr160hPT8d3332HzZs3NzoGIUQxUIJClFZubi6Sk5PRtWtX9O7dm+twJFK7JHtDFH1JISMjA5988gl69uyJhQsXCk6+ZGRkYOPGjcjIyMCVK1fqLeRWW93kobKyEqmpqYiMjMTixYuxZMmSJse5cuVKlJSUYP369azu//LlS+zZs0dwwqpHjx6YOXMm2rZt2+QYCCGSoQSFECKVK1euYNasWYI385pfKd27d0dwcLBIpUtJbdu2DUlJSaw2ydbn3r17GDBgAF68eNHofRMSEuDk5AQdHR3Y2toCeFdErri4GH///TeVyydETihBIUolJiYGGzduFKodsmDBAjg4OHAd2nvv+vXrgtM63bp1k7oGQo379++jT58+QidtJHXgwAH4+Pjg8ePHjd63V69esLOzw/bt26GqqgrgXS2VefPmITExEenp6U2OgxDCHm2SJUrj999/h5eXF7799lvBfpMrV65g1KhR2LBhA3788UeOI5RMS0u2kpOTsXHjRmRlZQF4l6QsWLAAbm5uUo17/Phx1ksrdeuqMAyDgoICJCUlwdfXl9UY2dnZOHHihCA5Ad6V0F+4cCFCQ0PZB04IkQolKERprF27Fhs3bhRKRObPn49BgwZhzZo1SpWgtLRky9fXFxs3boSHh4eg8Nzly5fh5eWFnJwcrF69utEx+vbtK3LUt7CwEE+fPsUff/zBKo7ajSSBd3t9LCws4O/vjxEjRrAaw8bGBpmZmSIVfTMzM1lXoyWESI+WeIjS0NLSQmpqqtjaIX379lWqOigdO3bE0qVLRRKRbdu2Yc2aNayWIhSJvr4+tm7dismTJwtdDwsLg4eHB6vKrH5+fkJ/VlFRgYGBAezt7eVadv7IkSPw9vaGh4eH0Amrbdu2ISAgAD169BDct271XEKI7FCCQpTG1KlT0adPHyxevFjo+vr165GcnIywsDCOIpNcS0q2AEBPTw9Xr15Ft27dhK7fvXsXAwYMQHFxsdxiKS4uxvHjx5GdnY3Fixejbdu2SElJQfv27dGxY8dGH9/YCauajcCKfsKKEGVHSzxEoW3ZskXwfY8ePbBmzRrEx8cL9a9JTExUiOZYknByckJ4eLhIsvXXX3/hm2++4Siqpps2bRq2b9+ODRs2CF3ftWsXpk6dynqc7OxshISEIDs7G5s3b4ahoSEiIyNhbGzM6qhyWloahg8fDl1dXeTk5GD27Nlo27YtwsPDkZuby2oPyYMHD1jHSwhpPjSDQhRa3Vbi9eHxeErTvwYAVq9ejfXr12PQoEFik63a1Vfnz5/PVZiseXh4IDQ0FMbGxkLLIvn5+XBxcRHqZ1M3iamRkJCAr776CoMGDcL58+eRmZkJMzMzBAYG4urVqzh+/HijcTg4OMDGxgaBgYHQ0tLCjRs3YGZmhkuXLmHKlCnIycmRyc9LCGl+lKAQwoGWlnjV1zisLh6PV2+5+U8//RTjx4/HwoULhZKLa9euYcyYMXj06FGj4+vo6CAlJQVdu3YVGiM3NxcWFhasewI9evQIiYmJePLkCfh8vtBtypAwEtIS0BIPIRxoacsIsuhlc/PmTRw6dEjkuoGBAZ4/f85qDA0NDbH1Uu7cuQMDAwNWY4SEhMDd3R3q6upo166d0MkiHo9HCQohckIJClEarq6uDd6+d+9eOUVCmoOuri4KCgpEZpdSU1NZbW4FgNGjR8Pf31/Q+4fH4yEvLw9LlizBuHHjWI2xfPlyLF++HEuXLmXdkoAQInuUoBCl8fLlS6E/V1ZWIj09HcXFxY12sVU0lGyJmjJlCnx8fHDs2DHweDzw+XwkJiZi0aJFcHFxYTXG+vXrMWrUKBgaGqK8vBxDhgxBYWEhBg4ciDVr1rAao6ysDJMmTaLkhBCO0R4UotT4fD7mzZsHMzMzeHt7cx0Oa2PHjhX6c91k6+TJkxxFxp3KykrMmDEDhw8fBsMwUFNTQ1VVFaZOnYp9+/YJVXZtTFxcHJKTk8Hn82FjYyNRdV5vb2+0bdtWquaEhBDpUYJClN6dO3dgb2+PgoICrkORirImW7J2//59pKSkgM/no2/fviK1VRoTExODmJgYsRtc2cxMVVdX4+uvv0Z5eTmsrKyETiAB9Z9CIoTIFi3xEKWXnZ2NqqoqrsOQmoqKCry8vGBvb//eJCgLFy5s8PYrV64IvmeTGPj5+cHf3x+2trYwMjIS2uDK1q+//oqoqChBqfu6m2QJIfJBCQpRGnXfzGoawUVEROC7777jKCrZainJFlupqams7sc2MdixYwf27duH6dOnNzmmDRs2YO/evZgxY0aTxyCESI8SFKI06r6Z1fRqCQoKanTTqaJ5H5ItNmRxPLm2iooK2NnZSTVG69atMWjQIBlFRAhpKtqDQggH6hY2q0m2hg0bBldXV6ip0WeHpvDx8UGbNm3g6+vb5DHWrl2LgoICoTYLhBD5owSFKI2a0y26urpC11+/fo0xY8bUW6GUvD88PT0RGhoKa2trWFtbN2mD69ixYxEbG4t27dqhZ8+eImO8jyesCOECfUwjSiM+Ph4VFRUi19++fYsLFy5wEFHTlZeXg2EYfPDBBwCA3NxchIeHw9LSEiNGjOA4OuWVlpaGPn36AADS09OFbmO7j0VXVxfOzs6yDo0QIiGaQSEKLy0tDQDQp08fxMbGom3btoLbqqurERkZiZ07dypVI7gRI0bA2dkZ7u7uKC4uhoWFBdTV1fHs2TNs2LABc+fO5TpEQgjhFCUoROGpqKgIPv2K+++qqamJrVu3KtVGWX19fSQkJKBnz54IDg7G1q1bkZqaihMnTmD58uXIzMzkOsT31sqVKzFz5kyYmJhwHQoh7zVa4iEK78GDB2AYBmZmZrh69apQ0zd1dXUYGhpKVGVUEZSVlUFLSwsAEB0dDWdnZ6ioqGDgwIHIzc3lOLr32+nTp7F69WoMGTIEs2bNgrOzMzQ0NLgOi5D3DjWbIArPxMQEpqam4PP5sLW1hYmJieDLyMhI6ZITADA3N8epU6eQn5+PqKgowb6TJ0+eQFtbm+Po3m/JyclISUmBtbU1vLy8YGRkhLlz5+LatWtch0bIe4WWeIhSuXv3LuLj48WWMV++fDlHUUnu+PHjmDJlCqqrqzF8+HBER0cDeHfE9fz58zh37hzHERIAqKqqwunTpxESEoLIyEhYWFjAzc0NM2bMgI6ODtfhEdKiUYJClMbu3bsxd+5c6Ovro0OHDiIlyFNSUjiMTnKFhYUoKChA7969BZ1zr169Cm1tbXTv3h0A8PDhQ3z00UfUWZcjFRUVCA8Px969exEbGws7OzsUFRXh8ePH2L17NyZOnMh1iIS0WJSgEKVhYmKCefPmwcfHh+tQ5EZbWxvXr1+HmZkZ16G8V5KTkxESEoKwsDC0bt0aLi4ucHNzg7m5OQAgKCgIgYGBKCoq4jhSQlouSlCI0ngf36y1tLRw48aN9+pn5pq1tTUyMjIwcuRIzJ49G998843IPqenT5+iffv2IsuMhBDZoXljojTGjx8v2KtBSHMZP348cnNzERERgTFjxojdhG1gYEDJCSHNjI4ZE6Vhbm4OX19fXLlyBVZWViIlyOfPn89RZETZ1W3eGBQUVO992ZTLJ4RIj5Z4iNLo0qVLvbfxeDzcv39fjtHIBy3xyEfd5o314fF41POJEDmhBIUQBfY+7rshhBCAlniIglu4cCFWrVqFDz/8UGQavjYej9fgtLyyos8PhJD3FSUoRKGlpqaisrJS8H192HaqVTYZGRn46KOPuA6DEELkjpZ4CJETZ2dn1vc9efJkM0ZCCCGKj44ZEyInOjo6gi9tbW3ExMQgKSlJcHtycjJiYmKohDohhIBmUAjhhI+PD168eIEdO3YI6mxUV1dj3rx50NbWxrp16ziOkBBCuEUJCiEcMDAwwMWLF2FhYSF0/c6dO7Czs8Pz5885iowQQhQDLfEQwoGqqipkZmaKXM/MzKQKpYQQAjrFQwgnZs6cCVdXV9y7dw8DBw4EAFy5cgUBAQGYOXMmx9ERQgj3aImHEA7w+XysX78emzdvRkFBAQDAyMgInp6e+Omnn8T2fyGEkPcJJSiEcOz169cA3lWNJYQQ8g7tQSGEI1VVVfj3338RFhYmKDT3+PFjlJSUcBwZIYRwj2ZQCOFAbm4uvvzyS+Tl5eF///sf7t69CzMzMyxYsABv377Fjh07uA6REEI4RTMohHDA09MTtra2ePnyJTQ1NQXXx44di5iYGA4jI4QQxUCneAjhwMWLF5GYmAh1dXWh6yYmJnj06BFHURFCiOKgGRRCOMDn81FdXS1y/eHDh9DS0uIgIkIIUSyUoBDCgS+++AKbNm0S/JnH46GkpAQrVqzAqFGjuAuMEEIUBG2SJYQDjx8/xtChQ6GqqoqsrCzY2toiKysL+vr6OH/+PAwNDbkOkRBCOEUJCiEcKS8vR1hYGFJSUsDn82FjY4OpU6cKbZolhJD3FSUohBBCCFE4dIqHEDn5+++/Wd/XycmpGSMhhBDFRzMohMiJiorwnnQej4e6L7+airLiTvgQQsj7hE7xECInfD5f8BUdHY0+ffrg3LlzKC4uxqtXr3Du3DnY2NggMjKS61AJIYRzNINCCAd69eqFHTt24LPPPhO6fuHCBcyZMweZmZkcRUYIIYqBZlAI4UB2djZ0dHREruvo6CAnJ0f+ARFCiIKhGRRCODB48GC0atUKBw8ehJGREQCgsLAQ06dPR0VFBRISEjiOkBBCuEUJCiEcuHfvHsaOHYs7d+6gc+fOAIC8vDx8/PHHOHXqFMzNzTmOkBBCuEUJCiEcYRgG//zzD27fvg2GYWBpaQkHBwfBSR5CCHmfUYJCCMfevn2L1q1bU2JCCCG10CZZQjjA5/OxatUqdOzYEW3atMGDBw8AAL6+vtizZw/H0RFCCPcoQSGEA6tXr8a+ffsQGBgIdXV1wXUrKysEBwdzGBkhhCgGSlAI4UBoaCh27dqFqVOnQlVVVXDd2toat2/f5jAyQghRDJSgEMKBR48eiT2pw+fzUVlZyUFEhBCiWChBIYQDPXv2xIULF0SuHzt2DH379uUgIkIIUSzUzZgQDqxYsQLTp0/Ho0ePwOfzcfLkSdy5cwehoaE4c+YM1+ERQgjn6JgxIRyJiorCr7/+iuTkZPD5fNjY2GD58uUYMWIE16ERQgjnKEEhhBBCiMKhPSiEcKS4uBjBwcH4+eef8eLFCwBASkoKHj16xHFkhBDCPdqDQggH0tLS4ODgIOhe7ObmhrZt2yI8PBy5ubkIDQ3lOkRCCOEUzaAQwoGFCxdixowZyMrKgoaGhuD6V199hfPnz3MYGSGEKAZKUAjhwLVr1/D999+LXO/YsSMKCws5iIgQQhQLJSiEcEBDQwOvX78WuX7nzh0YGBhwEBEhhCgWSlAI4cDo0aPh7+8vqBrL4/GQl5eHJUuWYNy4cRxHRwgh3KNjxoRw4PXr1xg1ahRu3bqFN2/e4KOPPkJhYSEGDhyIc+fO4cMPP+Q6REII4RQlKIRwKC4uTqhQm4ODA9chEUKIQqAEhRCOxMTEICYmBk+ePAGfzxe6be/evRxFRQghioHqoBDCAT8/P/j7+8PW1hZGRkbg8Xhch0QIIQqFZlAI4YCRkRECAwMxffp0rkMhhBCFRKd4COFARUUF7OzsuA6DEEIUFiUohHDAzc0Nhw4d4joMQghRWLQHhRAOvH37Frt27cK///4La2trtGrVSuj2DRs2cBQZIYQoBtqDQggHhg4dWu9tPB4PsbGxcoyGEEIUDyUohBBCCFE4tAeFEEIIIQqHEhRCCCGEKBxKUAghhBCicChBIYQQQojCoQSFEEIIIQqHEhRCCCGEKBxKUAghhBCicChBIYQQQojC+X8gc2uN/6rGUwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(df.isnull(),cbar=False,cmap='viridis')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "478a2ac5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 400x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Plot for the count of male and female.\n",
    "plt.figure(figsize=(4,7))\n",
    "sns.countplot(x='sex', hue='sex', data=df)\n",
    "\n",
    "plt.title('Count of male and female', size=15)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "88dec11e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 400x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot for finding count for male and female\n",
    "plt.figure(figsize=(4,7))\n",
    "sns.countplot(x='sex', hue='finding', data=df)\n",
    "\n",
    "plt.title('finding Count between Male and Female')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "a3a36d2c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1400x700 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Plot for age variation between male and female\n",
    "plt.figure(figsize=(14,7))\n",
    "sns.countplot(x='sex', hue='age', data=df)\n",
    "\n",
    "plt.title('age variation between male and female')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "c2639f65",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\91939\\AppData\\Local\\Temp\\ipykernel_15444\\4152667385.py:1: FutureWarning: The default value of numeric_only in DataFrameGroupBy.mean is deprecated. In a future version, numeric_only will default to False. Either specify numeric_only or select only columns which should be valid for the function.\n",
      "  df.groupby(['sex','survival']).mean()\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>patientid</th>\n",
       "      <th>offset</th>\n",
       "      <th>age</th>\n",
       "      <th>temperature</th>\n",
       "      <th>pO2_saturation</th>\n",
       "      <th>leukocyte_count</th>\n",
       "      <th>neutrophil_count</th>\n",
       "      <th>lymphocyte_count</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sex</th>\n",
       "      <th>survival</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">F</th>\n",
       "      <th>N</th>\n",
       "      <td>116.928571</td>\n",
       "      <td>9.700000</td>\n",
       "      <td>66.642857</td>\n",
       "      <td>38.00</td>\n",
       "      <td>73.333333</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Y</th>\n",
       "      <td>72.325000</td>\n",
       "      <td>10.175000</td>\n",
       "      <td>50.526316</td>\n",
       "      <td>37.84</td>\n",
       "      <td>95.600000</td>\n",
       "      <td>3.13</td>\n",
       "      <td>1.63</td>\n",
       "      <td>1.2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">M</th>\n",
       "      <th>N</th>\n",
       "      <td>109.153846</td>\n",
       "      <td>8.000000</td>\n",
       "      <td>53.461538</td>\n",
       "      <td>39.00</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.22</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Y</th>\n",
       "      <td>79.790698</td>\n",
       "      <td>8.069767</td>\n",
       "      <td>54.534884</td>\n",
       "      <td>38.68</td>\n",
       "      <td>93.000000</td>\n",
       "      <td>7.16</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               patientid     offset        age  temperature  pO2_saturation  \\\n",
       "sex survival                                                                  \n",
       "F   N         116.928571   9.700000  66.642857        38.00       73.333333   \n",
       "    Y          72.325000  10.175000  50.526316        37.84       95.600000   \n",
       "M   N         109.153846   8.000000  53.461538        39.00             NaN   \n",
       "    Y          79.790698   8.069767  54.534884        38.68       93.000000   \n",
       "\n",
       "              leukocyte_count  neutrophil_count  lymphocyte_count  \n",
       "sex survival                                                       \n",
       "F   N                     NaN               NaN               NaN  \n",
       "    Y                    3.13              1.63               1.2  \n",
       "M   N                    0.22               NaN               NaN  \n",
       "    Y                    7.16               NaN               0.9  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.groupby(['sex','survival']).mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "72407d4f",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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