Covid-19-sg_EDA.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import gmaps\n",
    "import gmaps.datasets\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import json\n",
    "%matplotlib inline\n",
    "sns.set_style(\"darkgrid\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "def read_json(filename):\n",
    "    datafile = open(filename, 'r',  encoding='utf-8')\n",
    "    return json.loads(datafile.read())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = read_json('covid-sg.json')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "list_pro = []\n",
    "for dic in data['features']:\n",
    "    list_pro.append(dic['properties'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "covid = pd.DataFrame(list_pro)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 248,
   "metadata": {},
   "outputs": [],
   "source": [
    "gen = covid[(covid.gender == 'Male') | (covid.gender== 'Female')]['gender'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>title</th>\n",
       "      <th>confirmed</th>\n",
       "      <th>discharged</th>\n",
       "      <th>hospital</th>\n",
       "      <th>source</th>\n",
       "      <th>nationality</th>\n",
       "      <th>residenceAreas</th>\n",
       "      <th>placesVisited</th>\n",
       "      <th>age</th>\n",
       "      <th>death</th>\n",
       "      <th>transmissionSource</th>\n",
       "      <th>gender</th>\n",
       "      <th>linkedClusters</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>case-1</td>\n",
       "      <td>Case 1</td>\n",
       "      <td>2020-01-23</td>\n",
       "      <td>2020-02-19</td>\n",
       "      <td>Singapore General Hospital</td>\n",
       "      <td>https://www.straitstimes.com/singapore/health/...</td>\n",
       "      <td>Chinese</td>\n",
       "      <td>[Shangri-La Rasa Sentosa Resort &amp; Spa]</td>\n",
       "      <td>[]</td>\n",
       "      <td>66</td>\n",
       "      <td></td>\n",
       "      <td>Imported</td>\n",
       "      <td>Male</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>case-2</td>\n",
       "      <td>Case 2</td>\n",
       "      <td>2020-01-24</td>\n",
       "      <td>2020-02-07</td>\n",
       "      <td>National Centre for Infectious Diseases</td>\n",
       "      <td>https://www.straitstimes.com/singapore/health/...</td>\n",
       "      <td>Chinese</td>\n",
       "      <td>[J8 hotel, 8 Townshend Road]</td>\n",
       "      <td>[Raffles Hospital, Tan Tock Seng Emergency Dep...</td>\n",
       "      <td>53</td>\n",
       "      <td></td>\n",
       "      <td>Imported</td>\n",
       "      <td>Female</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>case-3</td>\n",
       "      <td>Case 3</td>\n",
       "      <td>2020-01-24</td>\n",
       "      <td>2020-02-21</td>\n",
       "      <td>Singapore General Hospital</td>\n",
       "      <td>https://www.straitstimes.com/singapore/health/...</td>\n",
       "      <td>Chinese</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>37</td>\n",
       "      <td></td>\n",
       "      <td>Imported</td>\n",
       "      <td>Male</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>case-4</td>\n",
       "      <td>Case 4</td>\n",
       "      <td>2020-01-25</td>\n",
       "      <td>2020-02-12</td>\n",
       "      <td>Sengkang General Hospital</td>\n",
       "      <td>https://www.moh.gov.sg/news-highlights/details...</td>\n",
       "      <td>Chinese</td>\n",
       "      <td>[Village Hotel Sentosa]</td>\n",
       "      <td>[USS, Vivocity]</td>\n",
       "      <td>36</td>\n",
       "      <td></td>\n",
       "      <td>Imported</td>\n",
       "      <td>Male</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>case-5</td>\n",
       "      <td>Case 5</td>\n",
       "      <td>2020-01-27</td>\n",
       "      <td>2020-02-18</td>\n",
       "      <td>National Centre for Infectious Diseases</td>\n",
       "      <td>https://www.moh.gov.sg/news-highlights/details...</td>\n",
       "      <td>Chinese</td>\n",
       "      <td>[Ceylon Road]</td>\n",
       "      <td>[Tan Tock Seng Hospital]</td>\n",
       "      <td>56</td>\n",
       "      <td></td>\n",
       "      <td>Imported</td>\n",
       "      <td>Female</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6585</th>\n",
       "      <td>case-6586</td>\n",
       "      <td>Case 6586</td>\n",
       "      <td>2020-04-19</td>\n",
       "      <td></td>\n",
       "      <td>National Centre for Infectious Diseases</td>\n",
       "      <td>https://www.channelnewsasia.com/news/singapore...</td>\n",
       "      <td>Bangladeshi (Work Permit holder)</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>35</td>\n",
       "      <td></td>\n",
       "      <td>Local</td>\n",
       "      <td>Male</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6586</th>\n",
       "      <td>case-6587</td>\n",
       "      <td>Case 6587</td>\n",
       "      <td>2020-04-19</td>\n",
       "      <td></td>\n",
       "      <td>National Centre for Infectious Diseases</td>\n",
       "      <td>https://www.channelnewsasia.com/news/singapore...</td>\n",
       "      <td>Singapore Citizen</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>54</td>\n",
       "      <td></td>\n",
       "      <td>Local</td>\n",
       "      <td>Male</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6587</th>\n",
       "      <td>case-6588</td>\n",
       "      <td>Case 6588</td>\n",
       "      <td>2020-04-19</td>\n",
       "      <td></td>\n",
       "      <td>National Centre for Infectious Diseases</td>\n",
       "      <td>https://www.channelnewsasia.com/news/singapore...</td>\n",
       "      <td>Bangladeshi (S Pass holder)</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>47</td>\n",
       "      <td></td>\n",
       "      <td>Local</td>\n",
       "      <td>Male</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9681</th>\n",
       "      <td>case-9682</td>\n",
       "      <td>Case 9682</td>\n",
       "      <td>2020-04-22</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>https://www.channelnewsasia.com/news/singapore...</td>\n",
       "      <td></td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>81</td>\n",
       "      <td>2020-04-27</td>\n",
       "      <td></td>\n",
       "      <td>Male</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11579</th>\n",
       "      <td>case-11580</td>\n",
       "      <td>Case 11580</td>\n",
       "      <td>2020-04-24</td>\n",
       "      <td></td>\n",
       "      <td>National Centre for Infectious Diseases</td>\n",
       "      <td>https://www.channelnewsasia.com/news/singapore...</td>\n",
       "      <td></td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>43</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>Female</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>6535 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               id       title   confirmed  discharged  \\\n",
       "0          case-1      Case 1  2020-01-23  2020-02-19   \n",
       "1          case-2      Case 2  2020-01-24  2020-02-07   \n",
       "2          case-3      Case 3  2020-01-24  2020-02-21   \n",
       "3          case-4      Case 4  2020-01-25  2020-02-12   \n",
       "4          case-5      Case 5  2020-01-27  2020-02-18   \n",
       "...           ...         ...         ...         ...   \n",
       "6585    case-6586   Case 6586  2020-04-19               \n",
       "6586    case-6587   Case 6587  2020-04-19               \n",
       "6587    case-6588   Case 6588  2020-04-19               \n",
       "9681    case-9682   Case 9682  2020-04-22               \n",
       "11579  case-11580  Case 11580  2020-04-24               \n",
       "\n",
       "                                      hospital  \\\n",
       "0                   Singapore General Hospital   \n",
       "1      National Centre for Infectious Diseases   \n",
       "2                   Singapore General Hospital   \n",
       "3                    Sengkang General Hospital   \n",
       "4      National Centre for Infectious Diseases   \n",
       "...                                        ...   \n",
       "6585   National Centre for Infectious Diseases   \n",
       "6586   National Centre for Infectious Diseases   \n",
       "6587   National Centre for Infectious Diseases   \n",
       "9681                                             \n",
       "11579  National Centre for Infectious Diseases   \n",
       "\n",
       "                                                  source  \\\n",
       "0      https://www.straitstimes.com/singapore/health/...   \n",
       "1      https://www.straitstimes.com/singapore/health/...   \n",
       "2      https://www.straitstimes.com/singapore/health/...   \n",
       "3      https://www.moh.gov.sg/news-highlights/details...   \n",
       "4      https://www.moh.gov.sg/news-highlights/details...   \n",
       "...                                                  ...   \n",
       "6585   https://www.channelnewsasia.com/news/singapore...   \n",
       "6586   https://www.channelnewsasia.com/news/singapore...   \n",
       "6587   https://www.channelnewsasia.com/news/singapore...   \n",
       "9681   https://www.channelnewsasia.com/news/singapore...   \n",
       "11579  https://www.channelnewsasia.com/news/singapore...   \n",
       "\n",
       "                            nationality  \\\n",
       "0                               Chinese   \n",
       "1                               Chinese   \n",
       "2                               Chinese   \n",
       "3                               Chinese   \n",
       "4                               Chinese   \n",
       "...                                 ...   \n",
       "6585   Bangladeshi (Work Permit holder)   \n",
       "6586                  Singapore Citizen   \n",
       "6587        Bangladeshi (S Pass holder)   \n",
       "9681                                      \n",
       "11579                                     \n",
       "\n",
       "                               residenceAreas  \\\n",
       "0      [Shangri-La Rasa Sentosa Resort & Spa]   \n",
       "1                [J8 hotel, 8 Townshend Road]   \n",
       "2                                          []   \n",
       "3                     [Village Hotel Sentosa]   \n",
       "4                               [Ceylon Road]   \n",
       "...                                       ...   \n",
       "6585                                       []   \n",
       "6586                                       []   \n",
       "6587                                       []   \n",
       "9681                                       []   \n",
       "11579                                      []   \n",
       "\n",
       "                                           placesVisited age       death  \\\n",
       "0                                                     []  66               \n",
       "1      [Raffles Hospital, Tan Tock Seng Emergency Dep...  53               \n",
       "2                                                     []  37               \n",
       "3                                        [USS, Vivocity]  36               \n",
       "4                               [Tan Tock Seng Hospital]  56               \n",
       "...                                                  ...  ..         ...   \n",
       "6585                                                  []  35               \n",
       "6586                                                  []  54               \n",
       "6587                                                  []  47               \n",
       "9681                                                  []  81  2020-04-27   \n",
       "11579                                                 []  43               \n",
       "\n",
       "      transmissionSource  gender linkedClusters  \n",
       "0               Imported    Male             []  \n",
       "1               Imported  Female             []  \n",
       "2               Imported    Male             []  \n",
       "3               Imported    Male             []  \n",
       "4               Imported  Female             []  \n",
       "...                  ...     ...            ...  \n",
       "6585               Local    Male             []  \n",
       "6586               Local    Male             []  \n",
       "6587               Local    Male             []  \n",
       "9681                        Male             []  \n",
       "11579                     Female             []  \n",
       "\n",
       "[6535 rows x 14 columns]"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "covid[(covid.gender == 'Male') | (covid.gender== 'Female')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 250,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Gender')"
      ]
     },
     "execution_count": 250,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,10))\n",
    "sns.barplot(x= gen.index,y = gen.values)\n",
    "plt.title(\"Gender\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 241,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2020-04-20    1426\n",
       "2020-04-17    1207\n",
       "2020-04-21    1111\n",
       "2020-04-23    1037\n",
       "2020-04-22    1016\n",
       "              ... \n",
       "2020-02-27       2\n",
       "2020-02-01       1\n",
       "2020-02-23       1\n",
       "2020-01-23       1\n",
       "2020-01-25       1\n",
       "Name: confirmed, Length: 91, dtype: int64"
      ]
     },
     "execution_count": 241,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "covid.confirmed.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 251,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Number of confirmed cases per day')"
      ]
     },
     "execution_count": 251,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABrUAAARrCAYAAAAtnS2mAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjMsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+AADFEAAAgAElEQVR4nOzdaZSkBXU38H91Vc10z0I3ROTFDGMisiT6gghEISxGo2jECCgTQFFRMQviUQIBAaNCNEYQjXjAEw6eE5FFMALHJW6RgJohCkQUX0BFBQYRxkA3s/V0Vz31fugFBmbprq6qrm5+vy8yNd237lP4hfqfe2+p0Wg0AgAAAAAAAF2sZ7YbAAAAAAAAgG0RagEAAAAAAND1hFoAAAAAAAB0PaEWAAAAAAAAXU+oBQAAAAAAQNcTagEAAAAAAND1hFoAAMBmrVq1KnvssUeuueaaTV6/9NJLc8YZZ7TsfV760pfmxz/+ccvqbc3atWtzzDHH5NWvfnW+8Y1vdOR9vvSlL+WYY45p23s92eGHH57//u//7tj7daOvfe1rOf7442e7DQAAoMUqs90AAADQvXp6evJP//RP2XffffOc5zxnttuZsTvvvDP/+7//m29+85sdfZ/XvOY1bX0/AACApwOhFgAAsEW9vb054YQTcuqpp+aqq67KggULNvn7M844I7vttlve9ra3PeXPL33pS3P44Yfn5ptvztDQUN7+9rfntttuy09+8pNUKpVcfPHF2WmnnZIkV1xxRe66666MjIzkhBNOyOtf//okybe//e1cfPHFGR0dTW9vb04//fTss88+ufDCC/PDH/4wDz/8cPbYY4+cf/75m/T1rW99K5/61KdSFEUWL16c9773vVmyZEnOPPPMPPTQQ3nta1+bz3/+8+nt7Z38ndWrV+f9739/fvGLX6SnpyfHHHNM3vSmN+U3v/lNPvCBD+SBBx5Io9HIEUcckbe//e1ZtWpV3vKWt+TQQw/N7bffnsceeyynnXZadt11103e54ILLsjrX//6/M///M9T+n72s5+d++67Lw899FBWr16d5z3veXnRi16U6667LqtWrcppp52Www8/PEly8cUX5xvf+EaKosjv/u7v5v3vf3922mmn/PznP8+ZZ56ZDRs25DnPeU7Wr1+/2X+XW3q+H/7whznvvPMyMjKS1atX58ADD8yHP/zh1Gq1nHvuubnttttSrVazbNmy/OM//mMWL16c2267Leeff342bNiQnp6evPOd78yf/MmfZPXq1Tn99NPz6KOPJkkOPfTQvPvd735KL3/4h3+YE088Md/5zneyfv36nHLKKXnFK16RJLnmmmty5ZVXpiiKDAwM5H3ve1923XXXnHHGGRkcHMz999+fl7zkJTnttNM2qfnP//zP+dKXvpSBgYE8+9nPnnz9l7/8Zc4555ysW7cuq1evzp577plPfOIT+frXv54rrrgiV111VZLk17/+dVasWJFvf/vbT/n/OQAA0B2EWgAAwFb99V//dVauXJmPf/zjOf3006f1uxs3bszVV1+dr371q/nbv/3bXHvttdlzzz1z0kkn5dprr81f/dVfJUkWLlyYa6+9Ng899FCOPPLI7L333qlWq/n4xz+ez372s9l+++3zs5/9LCeccMLk2sAHHnggX/7yl1OpbPqfNffcc0/e//7356qrrsouu+ySlStX5m/+5m/yta99Lf/wD/+Qc889N9dff/1Tev3gBz+Y3/u938tFF12UNWvW5Nhjj82hhx6as846Ky972ctywgknZM2aNXnDG96QnXfeOXvvvXfuv//+HHTQQXnf+96Xr3/96/nwhz+cG264YZP3WbVq1Sbv88S+L7zwwtx66625/vrrU61Wc8ghh+QZz3hGLr/88nzrW9/Keeedl8MPPzzXXXddfvrTn+aaa65JpVLJ5z//+Zx99tm55JJLcuqpp+YNb3hDjj766Nx66615wxvesNl/F1t6vs9+9rN517velRe96EVZt25dXvayl+WOO+7I8PBwvv/97+erX/1qSqVSzjvvvNx9993Zdddd8973vjeXXnppli1bloceeigrVqzIHnvskWuvvTbLli3LZz7zmaxfvz5nnXVW1qxZk6VLl27SS71eT19fX774xS/mrrvuyhvf+Mbst99++fnPf57rrrsul19+efr6+vLd734373znO/Pv//7vSZLh4eF85Stfecqzfetb38o3vvGNXHfddent7c1JJ500+XdXX311jjjiiLz2ta/N6OhojjrqqPznf/5nXvnKV+YjH/lIfvazn2W33XbLNddckyOPPFKgBQAAXUyoBQAAbFVPT0/OO++8HHHEETnooIOm9bsT0ze77LJLnvGMZ2TPPfdMkixfvjxDQ0OTPzdxc2qnnXbKH//xH2flypUpl8t5+OGH85a3vGXy50qlUu67774kyQte8IKnBFpJcvPNN+fFL35xdtlllyTJAQcckB122CF33HFHSqXSFnv9r//6r8npn6VLl+bLX/5y1q9fn9tuuy2f+cxnJl8/6qijctNNN00Gb4ceemiSsemjwcHBbX4mT+77wAMPnAx9nvnMZ+bggw+e/Iwm6t1www358Y9/nNe97nVJkqIosmHDhjz66KO5++67c8QRRyRJ9t133+y2225Tfr4k+chHPpKbbropn/70p/OLX/wiGzduzPr167PnnnumXC7n6KOPzkEHHZTDDjsse+21V2688casXr16k+CoVCrl7rvvzsEHH5x3vOMdefDBB3PggQfmb//2b58SaE144xvfmCTZc889s/vuu+cHP/hBbr/99tx7772b3CB77LHHJj+Hfffdd7O1Vq5cmZe//OVZsmRJkuR1r3tdLrvssiTJaaedlu9973u55JJL8qtf/SoPP/xw1q9fnwULFuToo4/ONddck9NPPz3XXnvt5O8AAADdSagFAABs084775wPfvCDOf300ycDlGQszGg0GpN/Hh0d3eT3njj1Uq1Wt1i/p6dn8p+LokilUkm9Xs8BBxyQT3ziE5N/9+CDD+aZz3xmvvnNb2bRokWbrVUUxVPCq0ajkVqtttUeKpXKJr93//33Z2BgYJPnm6hfq9Umn2mi960FZk/05L6fPBm0uaCuKIq8/e1vz3HHHZckGRkZ2SQUfGKPm/v9idef/Hzbb7993vrWt2aPPfbIwQcfnFe96lW5/fbb02g0st122+X666/Pbbfdlptvvjnvfve787a3vS0777xzdt1111xzzTWTtR566KHssMMOqVar+Y//+I+sXLkyN998c44++uhccsklef7zn/+Ufsrl8ibPVy6XUxRFXvva106Gb0VR5OGHH05/f/9mP7sneuJn8MTap5xySur1el71qlflJS95SR588MHJnz3mmGPy+te/Pn/0R3+U3XbbbTIIBQAAulPPtn8EAAAgeeUrX5lDDjkk//qv/zr52vbbb5877rgjyViw8f3vf7+p2tdee22SsbtGK1euzAEHHJADDjgg3/ve93LPPfckSW688cb8+Z//eYaHh7da64ADDsh3v/vd3H///UnGpngefPDB7L333tv8vX/7t39LkqxZsyZvfvObc++992bvvffO5ZdfPvn6ddddlwMPPLCp52zWQQcdlC984QtZu3ZtkrH7UX/3d3+X7bffPs973vMmA6af/OQn+elPf7rZGpt7vl/96lf58Y9/nFNPPTWveMUr8pvf/Cb33XdfiqLIDTfckLe85S3ZZ599cvLJJ+eII47IHXfckRe84AW5995784Mf/CBJcuedd+awww7LQw89lPPPPz8XXXRR/vRP/zRnnXVWnvvc5+ZnP/vZZvu57rrrJnv+5S9/mf333z8HHXRQvvKVr+Thhx9Oklx55ZV585vfvM3P55BDDsnXvva1PPbYYymKYpP1kt/97ndz0kkn5c/+7M+SJLfffnvq9XqSsbD2BS94QT784Q/n2GOP3eb7AAAAs8ukFgAAMGVnn312br311sk/H3/88Tn11FNz2GGHZdmyZXnxi1/cVN2NGzfmyCOPzOjoaM4+++z8/u//fpLknHPOySmnnJJGo5FKpZKLL744ixcv3mqt5z73uXn/+9+fd77znanX6+nt7c2nP/3pLa7Bm/D3f//3+cAHPpDXvOY1aTQa+cu//Ms8//nPz/nnn59zzjknX/ziFzMyMpLXvOY1Oeqoo/LAAw809azNOProoydvV5VKpey88875yEc+kiS54IIL8t73vjdXXXVVli9fnuc85znTer53vOMdOfLII7No0aLstNNOeeELX5h77703Rx99dG666aYcfvjhWbRoUfr7+3Puuedmhx12yCc/+cl89KMfzcaNG9NoNPLRj340y5Yty5vf/OacccYZOfzww7NgwYLsscceefWrX73Zfm677bZcffXVKYoiH//4x9Pf35+DDjooJ554Yt761remVCplyZIl+dSnPrXNKbhDDz00d999d173utdlu+22y5577plHH300SfKe97wnJ510UhYtWpQlS5Zk//33n1xhmSRHHXVUzj333Mk1kgAAQPcqNZ68SwMAAADaaI899sjKlSuzww47zGofRVHknHPOybOe9ay84x3vmNVeAACAbbN+EAAAgKedtWvX5kUvelEefPDBvOlNb5rtdgAAgCkwqQUAAAAAAEDXM6kFAAAAAABA1xNqAQAAAAAA0PWEWgAAAAAAAHS9ymw3sDlFUaRed+prqsrl0ow/r/lSoxt6UEONdtfohh7UUKPdNbqhBzXUaHeNbuhBDTXaXaMbelBDjXbX6IYe1FCj3TW6oQc11Gh3jW7oQQ01eFy1Wt7s610ZatXrjQwOrp/tNuaMgYFFM/685kuNbuhBDTXaXaMbelBDjXbX6IYe1FCj3TW6oQc11Gh3jW7oQQ012l2jG3pQQ4121+iGHtRQo901uqEHNdTgcTvuuHSzr1s/CAAAAAAAQNcTagEAAAAAAND1hFoAAAAAAAB0PaEWAAAAAAAAXU+oBQAAAAAAQNcTagEAAAAAAND1hFoAAAAAAAB0PaEWAAAAAAAAXU+oBQAAAAAAQNcTagEAAAAAAND1hFoAAAAAAAB0PaEWAAAAAAAAXU+oBQAAAAAAQNcTagEAAAAAAND1hFoAAAAAAAB0PaEWAAAAAAAAXU+oBQAAAAAAQNcTagEAAAAAAND1hFoAAAAAAAB0PaEWAAAAAAAAXU+oBQAAAAAAQNcTagEAAAAAAND1hFoAAAAAAAB0PaEWAAAAAAAAXU+oBQAAAAAAQNcTagEAAAAAAND1hFoAAAAAAAB0PaEWAAAAAAAAXU+oBQAAAAAAQNcTagEAAAAAAND1hFoAAAAAAAB0PaEWAAAAAAAAXU+oBQAAAAAAQNcTagEAAAAAAND1hFoAAAAAAAB0PaEWAAAAAAAAXU+oBQAAAAAAQNcTagEAAAAAAND1hFoAAAAAAAB0PaEWAAAAAAAAXU+oBQAAAAAAQNcTagEAAAAAAND1hFoAAAAAAAB0PaEWAAAAAAAAXU+oBQAAAAAAQNcTagEAAAAAAND1hFoAAAAAADAD9z26Ied+5c7Ui8ZstwLzmlALAAAAAABmYOUvH8lnb743D63ZONutwLwm1AIAAAAAgBmojU9oDW4YneVOYH4TagEAAAAAwAzUhVrQEUItAAAAAACYAZNa0BlCLQAAAAAAmAGTWtAZQi0AAAAAAJiBWlEkSYaGa7PcCcxvQi0AAAAAAJiBifWDQya1oK2EWgAAAAAAMANuakFnCLUAAAAAAGAG3NSCzhBqAQAAAADADJjUgs4QagEAAAAAwAw8flOrNsudwPwm1AIAAAAAgBl44qRWo9GY5W5g/hJqAQAAAADADEzc1KoVjawbqc9yNzB/CbUAAAAAAGAGavXHp7Pc1YL2EWoBAAAAAMAM1J+wcnBIqAVtM6VQ6/bbb8/xxx+/yWtf+tKX8hd/8ReTf7766qtz1FFHZcWKFbnhhhuSJMPDwzn55JNz3HHH5cQTT8wjjzzSwtYBAAAAAGD21erF5D8PDtdmsROY37YZal1yySU5++yzs3HjxsnX7rzzznzhC1+YPHi3evXqXHbZZbnqqqty6aWX5oILLsjIyEiuvPLK7L777rniiityxBFH5KKLLmrfkwAAAAAAwCyoFY3091WTmNSCdtpmqLV8+fJceOGFk39+9NFHc/755+fMM8+cfO1HP/pR9tlnnyxYsCBLly7N8uXLc9ddd+XWW2/NwQcfnCQ55JBDsnLlyjY8AgAAAAAAzJ560cgzlixI4qYWtFNlWz9w2GGHZdWqVUmSer2es846K2eeeWYWLlw4+TNr167N0qVLJ/+8ePHirF27dpPXFy9enDVr1kypqXK5lIGBRdN6kKezcrlnxp/XfKnRDT2ooUa7a3RDD2qo0e4a3dCDGmq0u0Y39KCGGu2u0Q09qKFGu2t0Qw9qqNHuGt3QgxpqtLvGjHvoKWWHxQvyq/9dn+EiTdfqhs9Cje6twRRCrSf6yU9+knvvvTcf+MAHsnHjxvz85z/Phz70obz4xS/OunXrJn9u3bp1Wbp0aZYsWTL5+rp167LddttN6X3q9UYGB9dPp7WntYGBRTP+vOZLjW7oQQ012l2jG3pQQ4121+iGHtRQo901uqEHNdRod41u6EENNdpdoxt6UEONdtfohh7UUKPdNWb6+xtH6lnUW0l/byW/GVzfdK1u+CzU6N4aTyc77rh0s69PK9Taa6+98pWvfCVJsmrVqpxyyik566yzsnr16nziE5/Ixo0bMzIyknvuuSe77757XvjCF+bGG2/MXnvtlZtuuin77rvvzJ8EAAAAAAC6SK1opNLTk/6+aoY21Ga7HZi3phVqbcmOO+6Y448/Pscdd1wajUbe8573ZOHChTn22GNz+umn59hjj021Ws3HPvaxVrwdAAAAAAB0jVrRSKVcykBf1U0taKMphVrLli3L1VdfvdXXVqxYkRUrVmzyM319ffnkJz/ZgjYBAAAAAKA71YtGKj1joda9j1gxB+3SkkktAAAAAAB4uqoVRSo9PVnc22NSC9qoZ7YbAAAAAACAuaxeNFIen9Qa2jCaRqMx2y3BvCTUAgAAAACAGagVjVTHb2rVG8najfXZbgnmJaEWAAAAAADMQK1opFLuyUBfNUkyNGwFIbSDUAsAAAAAAGbgiesHk7irBW0i1AIAAAAAgBmoFY1Ue0oZ6KskEWpBuwi1AAAAAABgBiYmtfpNakFbCbUAAAAAAGAGnnxTa3BDbZY7gvlJqAUAAAAAADNQqxep9pSyeEE55Z5ShkxqQVsItQAAAAAAoEmNRiP1RlLuKaVUKmWgr2r9ILSJUAsAAAAAAJpULxpJkkp57Ov2gb6KUAvaRKgFAAAAAABNqk2EWj2lJEl/b9X6QWgToRYAAAAAADRpMtQqj4VaY+sHa7PZEsxbQi0AAAAAAGjSkye1BvqqGRo2qQXtINQCAAAAAIAmTd7U6nn8ptbQhtEUjcZstgXzklALAAAAAACa9OT1g/191dQbydqNVhBCqwm1AAAAAACgSROTWuUnrB9M4q4WtIFQCwAAAAAAmjQxqVUdXz/YPxlquasFrSbUAgAAAACAJtWKIsnj6wcHhFrQNkItAAAAAABo0lPXD1aSJENCLWg5oRYAAAAAADTpyesHTWpB+wi1AAAAAACgSZOTWuPrBxdVy6n0lDK4oTabbcG8JNQCAAAAAIAm1epjoVZlfP1gqVTKQF/V+kFoA6EWAAAAAAA0aXL94PikVjK2gtD6QWg9oRYAAAAAADRpcv1gz+Nftw/0VTI0LNSCVhNqAQAAAABAkyYmtSbWDyYmtaBdhFoAAAAAANCkzYVa/X3VDG6ozVZLMG8JtQAAAAAAoEn1okiSVMqPf93e31fNY8Ojk6sJgdYQagEAAAAAQJO2tH6waCRrNprWglYSagEAAAAAQJMmQ63yE0OtSpJkyF0taCmhFgAAAAAANGlLk1pJMijUgpYSagEAAAAAQJMm7maVex7/uv3xUMv6QWgloRYAAAAAADRpYlKr+oT1g/29Y6GW9YPQWkItAAAAAABokvWD0DlCLQAAAAAAaNLm1g/2VXuyoFwSakGLCbUAAAAAAKBJtXqRZNP1g6VSKQN91QwNC7WglYRaAAAAAADQpHpjYlKrtMnr/X3VDG6ozUZLMG8JtQAAAAAAoEm1+lNvaiUToZZJLWgloRYAAAAAADSpVjRS7imlVNo01BroFWpBqwm1AAAAAACgSfWi8ZQprSQZ6KtkSKgFLSXUAgAAAACAJtW2GGpV89hwLfWiMQtdwfwk1AIAAAAAgCbVx9cPPtlAXzWNJGuGa51vCuYpoRYAAAAAADRpS5Na/X3VJHFXC1pIqAUAAAAAAE2qFcUWb2olQi1oJaEWAAAAAAA0aWvrBxOhFrSSUAsAAAAAAJq0pfWDE6HW0LBQC1pFqAUAAAAAAE3a9qRWrdMtwbwl1AIAAAAAgCaNTWo99av23mo5Cys91g9CCwm1AAAAAACgSVtaP5gk/b0VoRa0kFALAAAAAACaVNvC+sFkbAWhUAtaR6gFAAAAAABN2tqk1kBfNUNuakHLCLUAAAAAAKBJ9W1Mag0Nm9SCVhFqAQAAAABAk2r1rU9qWT8IrSPUAgAAAACAJtWKIpXy5kOt/r5KHhuupVY0OtwVzE9CLQAAAAAAaFK9aKRc2vKkVpI8ZgUhtIRQCwAAAAAAmlQrGqmUN/9V+0SoZQUhtIZQCwAAAAAAmrS1Sa3+8VBraEOtky3BvCXUAgAAAACAJo1Nam19/aBJLWgNoRYAAAAAADSpVjRS6dnCpFZvJYlQC1pFqAUAAAAAAE2qF42UtxBqmdSC1hJqAQAAAABAk7Y2qdVbLae30iPUghYRagEAAAAAQJPqWwm1krFpraHhWgc7gvlLqAUAAAAAAE2qFcUW1w8m46GWSS1oCaEWAAAAAAA0aWz94Ja/au/vq1g/CC0i1AIAAAAAgCaNrR/c8t8P9FWFWtAiQi0AAAAAAGhC0WikaGSrk1pCLWgdoRYAAAAAADShXjSSZKs3tfr7qlm7sZ5avehUWzBvCbUAAAAAAKAJtfFQq7KVUGugr5okGRqudaQnmM+EWgAAAAAA0IRafTzUKm871LKCEGZOqAUAAAAAAE2YXD9Y2sr6wd5KEqEWtIJQCwAAAAAAmlArxu5kTWVSa0ioBTMm1AIAAAAAgCbUpjCpZf0gtI5QCwAAAAAAmjARam1tUqt/YlJruNaRnmA+E2oBAAAAAEATJkOtni1/1b6w0pNF1bJJLWgBoRYAAAAAADShPrF+sGfLk1pJ0t9XEWpBCwi1AAAAAACgCY9Pam091Broqwq1oAWEWgAAAAAA0ISpT2pVM7jBTS2YKaEWAAAAAAA0YTqTWkMmtWDGhFoAAAAAANCEWlEksX4QOkWoBQAAAAAATZjy+sHeStaN1DNaLzrRFsxbQi0AAAAAAGjCdNYPJrGCEGZIqAUAAAAAAE2oTzPUGtxQa3tPMJ8JtQAAAAAAoAm1+kSotfWv2icntYZNasFMCLUAAAAAAKAJE+sHy+WpTmoJtWAmhFoAAAAAANCEyfWDpa2HWv19lSRCLZgpoRYAAAAAADRhYlKrso1Jrf5ek1rQCkItAAAAAABowsSkVrln66HWgkpPFi8oZ3BDrRNtwbwl1AIAAAAAgCbUiiJJUtlGqJUk/X3VDJnUghkRagEAAAAAQBMm1w9OIdQa6KtaPwgzJNQCAAAAAIAm1Ka4fjBJBvoqQi2YIaEWAAAAAAA0oT45qbXtr9r7e60fhJkSagEAAAAAQBOmN6lVzeCGWrtbgnlNqAUAAAAAAE2Y7k2t9aP1jNSKdrcF85ZQCwAAAAAAmlArGill6je1kmRo2ApCaJZQCwAAAAAAmlAvGlMKtJKxSa0kGXRXC5om1AIAAAAAgCbU6o0prR5Mkn6hFsyYUAsAAAAAAJpQb0x9UuvxUKvWzpZgXhNqAQAAAABAE2r1YsqTWtYPwswJtQAAAAAAoAm1opFKeWpfsw/0VpIkQ0ItaJpQCwAAAAAAmlAvGilPbVArlXJPliwsm9SCGRBqAQAAAABAE6YzqZUk/b1VoRbMgFALAAAAAACaUC8aU76plYzd1RraUGtjRzC/CbUAAAAAAKAJtaKR8jRDLZNa0DyhFgAAAAAANGH6k1qVDA0LtaBZQi0AAAAAAGhCbZqhVr9JLZgRoRYAAAAAADShVhTTvqm1YbTI8Gi9jV3B/CXUAgAAAACAJtSneVOrv6+aJBkarrWrJZjXhFoAAAAAANCE6a4fHBgPtawghOYItQAAAAAAoAn1opFKz9S/Zh/oqyQRakGzhFoAAAAAANCE2jTXD05Mag0JtaApQi0AAAAAAGhC8+sH3dSCZgi1AAAAAACgCdOd1Nqu16QWzIRQCwAAAAAAmlCf5qRWpaeUpQsrbmpBk4RaAAAAAADQhFrRSKU89VArSQb6hFrQLKEWAAAAAAA0oVYvUi5NN9SqZmhYqAXNEGoBAAAAAEATmpnU6u+rZnBDrU0dwfwm1AIAAAAAgCbUi8a0J7XGQi2TWtAMoRYAAAAAADRhbFJrel+zD/QKtaBZQi0AAAAAAGhCvWik0jPdm1qVbKwVGR6tt6krmL+EWgAAAAAA0IRa0Uh52qFWNUlMa0EThFoAAAAAADBNjUZjbP1gk6HW0IZaO9qCeU2oBQAAAAAA01Q0xv53upNa/Sa1oGlCLQAAAAAAmKbaeKrV7KSWUAumT6gFAAAAAADTVG861KokEWpBM4RaAAAAAAAwTbWiSDL99YNLe6spJRkaFmrBdAm1AAAAAABgmh5fPzi9r9krPaVs11vJ4IZaO9qCeU2oBQAAAAAA0/T4+sHp/25/X9X6QWiCUAsAAAAAAKap2UmtJOnvFWpBM4RaAAAAAAB03PBoPadce0d++dt1s91KUyYntcrTu6mVJAN9FaEWNEGoBQAAAABAxz342MZ85xeP5OZf/u9st9KUWn0s1CqXmgm1qhkSasG0CbUAAAAAAOi40XqRJHl03dwMd2ozmtSqZmi4lkaj0eq2YF6bUqh1++235/jjj0+S3HnnnTnuuONy/PHH50FnBFoAACAASURBVG1ve1t++9vfJkmuvvrqHHXUUVmxYkVuuOGGJMnw8HBOPvnkHHfccTnxxBPzyCOPtOkxAAAAAACYSyZCrcENI7PcSXMm1g82O6m1sVZkuFa0ui2Y17YZal1yySU5++yzs3HjxiTJhz70obzvfe/LZZddlpe//OW55JJLsnr16lx22WW56qqrcumll+aCCy7IyMhIrrzyyuy+++654oorcsQRR+Siiy5q+wMBAAAAAND9RsfX9w2un6uTWmOBVDOTWv19lSRxVwumaZuh1vLly3PhhRdO/vmCCy7IH/zBHyRJ6vV6Fi5cmB/96EfZZ599smDBgixdujTLly/PXXfdlVtvvTUHH3xwkuSQQw7JypUr2/QYAAAAAADMJSPjk1qPzNlQa3z9YE9zk1qJUAumq7KtHzjssMOyatWqyT8/85nPTJLcdttt+dznPpfLL7883/nOd7J06dLJn1m8eHHWrl2btWvXTr6+ePHirFmzZkpNlculDAwsmtaDPJ2Vyz0z/rzmS41u6EENNdpdoxt6UEONdtfohh7UUKPdNbqhBzXUaHeNbuhBDTXaXaMbelBDjXbX6IYe1JifNRY8vC5JMrRhdNafpZnf7310OEnSv11fBgYWTavGsh3Hvjev9Wz6O7P970SN7q7BFEKtzfnqV7+aiy++OP/yL/+SHXbYIUuWLMm6desm/37dunVZunTpJq+vW7cu22233ZTq1+uNDA6ub6a1p6WBgUUz/rzmS41u6EENNdpdoxt6UEONdtfohh7UUKPdNbqhBzXUaHeNbuhBDTXaXaMbelBDjXbX6IYe1JifNQaHNiRJHlk3MuvP0szvDz421v/w+rH+p1OjXK8nSR747boM7rh4Rn08mRrzt8bTyY47Lt3s69tcP/hk119/fT73uc/lsssuyy677JIk2WuvvXLrrbdm48aNWbNmTe65557svvvueeELX5gbb7wxSXLTTTdl3333ncEjAAAAAAAwX0ysHxxcPzLLnTSnPr5+sGz9IHTMtCa16vV6PvShD2XnnXfOySefnCTZf//98653vSvHH398jjvuuDQajbznPe/JwoULc+yxx+b000/Psccem2q1mo997GNteQgAAAAAAOaWiZtUjw3XUisaTd2mmk0zuam1dGElpQi1YLqmFGotW7YsV199dZLk+9///mZ/ZsWKFVmxYsUmr/X19eWTn/zkDFsEAAAAAGC+GakVk//82PBodli0YBa7mb76DEKtck8p2/VWhFowTdNePwgAAAAAADM1Oh4KJcnQhtosdtKc2gzWDyZjKwiHhFowLUItAAAAAAA6brT++KTWXAx3asVY/82uTRzoq2ZweO6FeTCbhFoAAAAAAHTcE9cPzsU1fHWTWtBxQi0AAAAAADpuk/WDw3Mv3KnVm7+plST9fW5qwXQJtQAAAAAA6Lgnrh8cnIM3teqN8VCr3NzX7AN91QxuGE2j0dj2DwNJhFoAAAAAAMyC0XojCys9WVjpmZNr+CYntUrNrx8crTeyfrTeyrZgXhNqAQAAAADQcaP1IgvKPRlYVJ2b6weLiUmtZtcPVpPMzXtiMFuEWgAAAAAAdNxovZFquZTtFy2Ym+sHx0OtcpM3tQbGQ62hOfjsMFuEWgAAAAAAdNxIvUi13JPtF1Xn5vrBiUmtJkOt/t5KEpNaMB1CLQAAAAAAOm5s/eDYpNZcXD/YqkktoRZMnVALAAAAAICOG603Uhm/qTUX1w/WiiI9paSnJNSCThFqAQAAAADQcSP1IgvKPRnoW5DHhkdTNBqz3dK01IpG06sHk2RpbyU9pczJ1YswW4RaAAAAAAB0XK3eSLVcyvaLqykayZrhuTWtVSsaTa8eTMYmvPp7qxmaY88Ns0moBQAAAABAx43Ui1TLPdm+b0GSzLlwp140UumZ2VfsA31V6wdhGoRaAAAAAAB03Gi9kWpPKQOLxm5LzbU1fDNdP5gk/X0VoRZMg1ALAAAAAICOG60XWVDpyfaLxia15lq4M9P1g4lJLZguoRYAAAAAAB03sX5wclJreG6FO62Z1KpmcMPcWrsIs0moBQAAAABAx9WKsfWDj09qza1wp96iSa2hDaNpNBot6grmN6EWAAAAAAAdN1IrUq30ZMnCcso9pbl3U6s+80mtgb5qakUj60bqLeoK5jehFgAAAAAAHTc6PqlVKpXS31uZc+sH641GKuUZrh/srSSZe/fEYLYItQAAAAAA6LjRepEF5bGvqAfm4G2pWr1IuTTzSa0kc25KDWaLUAsAAAAAgI4brReTk07947el5pJa0UilPLOv2CdCrbkW6MFsEWoBAAAAANBxI/XGJpNac279YNFo3aTWHHt2mC1CLQAAAAAAOqpoNFIvHg+1+nsrc25aaWxSqzWhlptaMDVCLQAAAAAAOmq03kiSp6wfbDQas9nWtNSLRio9Mwu1liwsp1wSasFUCbUAAAAAAOio0XqRJJusH6wVjawbqc9mW9NSKxopzzDUKpVK6e+rCrVgioRaAAAAAAB01ESoVZ2Y1OqtJJlbt6VqLZjUSjIeas2t1YswW4RaAAAAAAB01Mj4+sHqxE2t8dtSQ3Mo3GnF+sFkbErNpBZMjVALAAAAAICOevKk1sB4qDWXwp1aUbQs1BqaQ88Ns0moBQAAAABAR42OT2pN3NSai+sH6y24qZWMPftcCvNgNgm1AAAAAADoqJHJSa2xr6gfn9SaO+sHW3VTa2JSq9FotKArmN+EWgAAAAAAdFTtSesHl/ZW0lPKnFrDNxZqzfwr9oG+auqNZO3Gegu6gvlNqAUAAAAAQEeNjK8fnJjU6imVsnRhZU6FWq1aPzgX74nBbBFqAQAAAADQUaNPmtRKxsKdp+v6wWRu3ROD2SLUAgAAAACgo0bHJ7UWlB//irq/rzqngp160Uil3IpQq5LEpBZMhVALAAAAAICOmpzUesJNqv7eubV+sFY0Ui7NPNTqt34QpkyoBQAAAABAR41MhFqVJ68fnDvBTq1etGhSayLUmjurF2G2CLUAAAAAAOioifWDm0xq9VUzNDw3gp1Go5F6Iy2Z1Fq8oJxyT2lOBXowW4RaAAAAAAB01OT6wfKmk1oba0WGR+uz1daU1YuxUK4Vk1qlUikDfdU5tXoRZotQCwAAAACAjhoZn9RaUNn0plYyN25L1SZCrZ7WfMU+0FeZE88Ns02oBQAAAABAR9WK8UmtJ60fTDInVhBOhFrlnplPaiVJf69JLZgKoRYAAAAAAB01Utv8+sFkrk1qtSbUGuirZnBD94d5MNuEWgAAAAAAdNToeChULT9xUmts/eBcmFiqt3hSayzU6v7nhtkm1AIAAAAAoKNG60XKpU1DoYE5uH6wdZNalQwNj6YYrwtsnlALAAAAAICOGqk1Uilv+vX0dr1zZ/1gvcWhVn9fNUUjWbOx+wM9mE1CLQAAAAAAOqpWFFnwpFCr0lPKkoXlObF+sNaG9YNJ8uj6kZbUg/lKqAUAAAAAQEeN1ItUy08NhObKbalaUSRp7aRWkjy6TqgFWyPUAgAAAACgo0brjVTLT/16ur+3OiduarV6/eDEpNYj67s/0IPZJNQCAAAAAKCjRutFFmxmUqu/rzLH1g+25iv2gb5KEusHYVuEWgAAAAAAdNRovZHKZia1BvqqcyLUmpzU2kww14yJSa1Bk1qwVUItAAAAAAA6aqReZMEcXj9Yq4+HWqXWhFqLquVUekomtWAbhFoAAAAAAHTUaL1IdTNTTgN91awbqWe0XsxCV1NXa/GkVqlUykBfNY+a1IKtEmoBAAAAANBRo/VGqpub1Bq/LdXtKwgn1g+WWzSplYwFeo+uM6kFWyPUAgAAAACgo0brRRZsZsqpv3f8tlSXryBs9aRWkgz0VawfhG0QagEAAAAA0FFbmtQa6BsLtbp9Umsy1Opp8aSW9YOwVUItAAAAAAA6aqRezPH1g2M3v8otDLX6+6omtWAbhFoAAAAAAHRUrWikuplAaM6tH+xp3Vfsv7NoQQY3jGb9SL1lNWG+EWoBAAAAANBRI7Ui1crmJrXm1vrBVk5q/d9nLU2jkdz+66GW1YT5RqgFAAAAAEBHjdSLzU5qLaz0pK/ak8E5Emq18qbW3r/bn2q5lFvuE2rBlgi1AAAAAADoqFrRyILN3NRKkoG+atdPatXbEGr1VcvZe9lAbrl/sGU1Yb4RagEAAAAA0FEjtSLVLYRa/b3VDM2Rm1qtXD+YJC/+/R1y10NrsnZjdz8/zBahFgAAAAAAHTVaNFItbz4Q6u+rdP2kVjvWDybJi5/zOykayW2rrCCEzRFqAQAAAADQMUWjkfo21g92+02tepsmtV6wy0AWVnpyy31WEMLmCLUAAAAAAOiY0fr4lNOWJrXmwvrBepGk9ZNaCys92etZ27mrBVsg1AIAAAAAoGNGxwOhrU1qrRmuTa7460b1xkQw1/qv2PdfPpCfrV6XwfXdPa0Gs0GoBQAAAABAx0yEWlu7qdVIsma4e0Od2vi02RYeYUb222UgSXLrKtNa8GRCLQAAAAAAOmZkPBCqbmHKqb+3miQZ2tC9KwhrRSPlnlJKpdanWn+w05IsqpbzA3e14CmEWgAAAAAAdMxU1g8myeCG7p3UqheNlt/TmlAp92SfZf25RagFTyHUAgAAAACgY0YnJ7W2vH4wSYa6ef1gG0OtJNlv+UDufXRDVq/d2Lb3gLlIqAUAAAAAQMeMTN7U2sL6wb7uXz/YzkmtJNlvl/4kyS33m9aCJxJqAQAAAADQMbXJUGvzodBcWD84cVOrXXbbcUm2661YQQhPItQCAAAAAKBjRibXD27+6+neSk8WlEtdvn6waOukVrmnlBcu688t9w+17T1gLhJqAQAAAADQMaPbmNQqlUoZ6Kt29aRWvc2TWkmy3y4D+fXQcB4Y2tDW94G5RKgFAAAAAEDHjI5Pai3YwqRWMnZXq5tvatXafFMrSfZbPpAkufU+01owQagFAAAAAEDHjExOam0l1OqtdPX6wXrRSKWnvV+vP+d3FmWHRdXccr+7WjBBqAUAAAAAQMdsa/1gkq5fP1jrwPrBUqmU/XYZyC33D6bRaLT1vWCuEGoBAAAAANAx1g9O3b7LB7J67UjufdRdLUiEWgAAAAAAdNDEpNbWQqH+3koeGx5N0aUTSp2Y1EqS/XcZu6t1y31WEEIi1AIAAAAAoINGJia1Kluf1Ko3krUbu3Naq1OTWssGerPT0oW51V0tSCLUAgAAAACgg2rF+E2tni1/PT3QV02Srl1BWC8aqWzlJlirjN3V6s8t9w917dQadJJQCwAAAACAjhmpjYdaWwmF+sdDrcENox3pabpq9UbKpfaHWkmy3/KBDG4YzT2/XdeR94NuJtQCAAAAAKBjRsfXD1bLW5nU6q0kSYaGuzTUKoqOTGolyX4Td7XuH+rI+0E3E2oBAAAAANAxo0WRcikpb+UmVf8cWD/YqUmt/7Ndb5YN9OaW+9zVAqEWAAAAAAAdM1JrbHVKK3n8plbXrh8sGqls4xlaab9dBnLbqsHUC3e1eHoTagEAAAAA0DG1othmqLV4QTnlnlLXrh+sF41UtjJp1mr7Lx/I2o313P3w2o69J3QjoRYAAAAAAB0zUi9S3cY9qlKplP7eSldPam1tfWKr7TtxV8sKQp7mhFoAAAAAAHTMaH3b6weTsbta3XpTq9bhSa3fWbwgv/87i/KD+4VaPL0JtQAAAAAA6JjRepEF25jUSpKB3kpXrx/s5KRWkuy/y0B+uGooo/Wio+8L3USoBQAAAABAx4xMY1Krm9cPdnJSK0n2Wz6Q4VqR//ebNR19X+gmQi0AAAAAADpmtF7M+fWD9VkItV64rD+lJD9wV4unMaEWAAAAAAAdM9X1g/291QwNj6bRaHSgq+mpFUXH1w/291Wz+zOX5BZ3tXgaE2oBAAAAANAxo/VGKlOY1Broq2S03sj60XoHupqesfWDnf96fb9dBvLjXz+W4S78TKAThFoAAAAAAHTMlCe1+qpJ0pUrCMfWD3b+ffdb3p+ReiM/fvCxzr85dAGhFgAAAAAAHTNab0zpptbAeKg1uGG03S1NS9FopGhkVia1XvC7/SmXklvc1eJpSqgFAAAAAEDHjNSLKYVa/b2VJMnQcHeFWvVi7MZXZQrTZq22ZGElf/h/luYH9w11/L2hGwi1AAAAAADomLm+frA2HmqVS50PtZJkv+UD+X8Prcm6ke76XKAThFoAAAAAAHTMaL2RyhxeP1irz96kVpLsu8tA6kUjP3zAXS2efoRaAAAAAAB0zMgUJ7WWLqyklGSoy0Kt+ixPau39rO1SLZfc1eJpSagFAAAAAEDH1IpGqj3b/mq63FPKdr2VDA1315q9WlEkmb1Jrd5qOf935+1y6/1CLZ5+hFoAAAAAAHTMSK1IdQrrB5Oxu1pdt35wfFKr0jM7oVaS7LfLQP4/e/caI1l+nof9qWt3V/VMX2aGlERyJe7sjiJCkkWJkmDYEeIgACEjCRTD2IALMDIc2YjgOBDhwBIMy4KhD0oCmJCvUWDYMSCBIgg7QYIkcIIotoTQAS0xshTTonZ2ViIpUuTuTk/3zvT0perUyYfq6tn79OWcU9XTv9+XJXu7//2v7q79cB487/vFbzzIa/uL9bOBugm1AAAAAABozGhSpnfCltPacm/hxg/OQq3OPEOtp9ZTJvl/v7IztzvAPAi1AAAAAABoxKQsU0zK9E/Y1Fpf6S5cU6s4bmrN7/H6d37zlSx12/kNIwi5ZIRaAAAAAAA04nA83Ud14qbWSm8Bd2rNv6nV67TzPe+7KtTi0hFqAQAAAADQiFkgdOKdWgs8fnCeO7WS6V6tO68+zN3dw7neA5ok1AIAAAAAoBGHxaypdfLxg/vjSfZHRZ3XOpViQUKt739qPUnyeW0tLhGhFgAAAAAAjRgVs6bWyccPJlmoEYSLMH4wSb79vVcy7Hfy+a/szPUe0CShFgAAAAAAjRgdNbX6J25qTUOt7QUaQbgoTa1uu5UPv3/NXi0uFaEWAAAAAACNOH1Tq5skC7VXazyZBnPzbmol0xGEX763l2/cP6jkvP1Rkb/+T383P/u//k4l50HVhFoAAAAAADTitDu11pYXd/zgvJtaSfKRD1S3V+vu7mH+s8/8dv6XL3wj/+O/+mrKsjz3mVA1oRYAAAAAAI14osYPnvA11OmZG8OsLXfz618+X6j10t3d/NlP/WbuvLqbf/fZ67m/P66s/QVVmv+7DgAAAACAS2E2frB70vGDyws4fnD2Glrzb2q1W6183wfW8xtf3j5zs+pffule/tNf/lc5KMr8d//xH8nHvvd9SZI7rz6s8qpQCaEWAAAAAACNODxlU6vbaWfY7yzU+MHiKDzqnDCYq9tHnlrP1+8f5Ks7+6f+2v/5X389/8X/8K/z3itL+e+f/5586Juu5OnrgyTJnVd3q74qnFt33hcAAAAAAOBymLWceqcIhNZXegs1fnCRmlrJo71av/Hl7bx/feVEX1OWZX7hs7+ff/i5r+QHv3U9/9V/8KGsLk3jgqvLvXzT1eW8KNRiAWlqAQAAAADQiFlTq3eKfVRrK73FGj84Od0Ixbp92+ZKrg37+Y2vnGyv1sF4kp/+376Yf/i5r+RHvuub8vP/0XceB1ozt967KtRiIWlqAQAAAADQiNFxqHWaplY39x4uTqhVzEKt9mKEWq1WKx/5wFp+/QR7tbYfjvJf/k9fyG997bX85//2B/OffP/703qbxtmt917J//PS3Ywn5cK8Tkg0tQAAAAAAaMjoaHTfSXdqJcnacm+hdmqNJ9NgrrNAYc/3P7WerYej/P7W3jt+zpfv7eXP/vJv5ne+cT8/9+9/R370Bz7wtoFWknz7e1czKsp85d47nwfzINQCAAAAAKART8b4wek/F6nB9H1He7V+/ctvP4LwN/9gJ3/2U7+Z+wdF/tvn/kj+vW+/8a7nPfueK0mSO0YQsmCEWgAAAAAANGLW1Drt+MHdw+J4dOG8LWJT631ry/nmq0tvu1frn/7Oy/kL//i3s77Sy3///Pfku7/l6mPPe+bGMO1W7NVi4dipBQAAAABAI2bB1GnHDybJzv4414f9Wu51Go92ai1OZ2S6V2s9v3bnbiZH9yvLMv/wc1/OL3z2S/ne96/lv/kPP5S1ld6JzlvqdfKB9RVNLRbO4rzrAAAAAAB4os1CrdOM7psFMdsLMoJwfBxqLU5TK0k+8tR6dvbH+eI37mdUTPLX//cX8guf/VL+5Ifek7/zp7/rxIHWzDM3hkItFo6mFgAAAAAAjXg0fvDkfYv1lelj7EXZqzULtRZp/GDyaK/W//FvvpHP3Xk1v/GVnfz5P/qt+bE/+lRardPf9eb1Yf6vF17N3qjISq9T9XXhTIRaAAAAAAA0YjSZpNM6XSD0+vGDi6CYlGll8UKt915ZylMbK/m7//xOuu1W/voPf3v+5Ifee+bzbl4fpkzye3cf5kPfdKW6i8I5GD8IAAAAAEAjDsflqVpaSbK+gOMHFy3Qmvl3nrme9ZVe/s6f/q5zBVpJ8sz1YZLkRSMIWSCaWgAAAAAANGJUTNLvni7Umu2CWpjxg0W5cPu0Zn78j39bfvJPfkcePtg/91nvW1vOUrdtrxYLRVMLAAAAAIBGjCaTUwdCS912lrvt7OwtyPjBsky3s5ihVrfdOnVo+E467VaevjYQarFQhFoAAAAAADTisCjTP+X4wWQ6gnB7f1GaWpN0WosZalXt6evDvPjqw3lfA44JtQAAAAAAaMS4mKR3hpbT2kpvYcYPTptal+PR+jPXh7m7e5jth4vxs4fL8c4DAAAAAGDuDosyvTM1tboLE2qNizILOn2wcs9cHyRJ7tw1gpDFINQCAAAAAKARo2JyplBrbbmXnf3F2Kk1nlyeptbN68MksVeLhXE53nkAAAAAAMzdqJikf9HHD07KdNuXo6p1fdjP2nI3Lwq1WBBCLQAAAAAAGnGe8YOv7Y9TTMoabnU640mZziUJtVqtVp6+PsyLrzyc91UgyQlDrd/6rd/Kxz/+8STJl770pXzsYx/L888/n5/5mZ/JZDJJknzmM5/Jn/pTfyrPPfdc/tk/+2dJkv39/fzFv/gX8/zzz+fP/bk/l62trZpeBgAAAAAAi25cTNI7S1NruZcyyf0FGEF4mZpaSfLM9WFeurubspx/oAiPDbX+/t//+/mrf/Wv5uDgIEnycz/3c/mJn/iJfOpTn0pZlvmVX/mVvPLKK/nFX/zFfPrTn84/+Af/IJ/85CdzeHiYX/7lX86tW7fyqU99Kj/yIz+Sv/f3/l7tLwgAAAAAgMV01qbW2kovSbK9P/8RhONLFmrdvD7I7mGRr98/mPdVIN3HfcJTTz2Vv/23/3b+8l/+y0mSL3zhC/mBH/iBJMkP/dAP5bOf/Wza7XY+/OEPp9/vp9/v56mnnsoXv/jFfP7zn8+P/diPHX/uSUOtTqeV9fXBWV/TpdPptM/983pSzliEOzjDGXWfsQh3cIYz6j5jEe7gDGfUfcYi3MEZzqj7jEW4gzOcUfcZi3AHZzij7jMW4Q7OeHLOmCQZLPfe8DUnOeN9N1aTJEWn87af2+jfebuVpf5b73FRfyePO+N7vu1akhfz9b1xvuOpk5+7iK/lop/BCUKtj370o/mDP/iD4/9flmVarWkKPRwOc//+/Tx48CBXrlw5/pzhcJgHDx684eOzzz2JoiizvW1G50mtrw/O/fN6Us5YhDs4wxl1n7EId3CGM+o+YxHu4Axn1H3GItzBGc6o+4xFuIMznFH3GYtwB2c4o+4zFuEOznhyztg/HKc1mbzha05yRrcokiR/8MqD3FxbOvc9zvP1B4fjtCZvfYZ9UX8njzvjvcudJMlv/f5WPvze1bndwxmXy40bV97246fuebbbj75kd3c3V69ezerqanZ3d9/w8StXrrzh47PPBQAAAADgchoVZbpnGD+4fjR+cGdvMcYPdi7R+MHVpW7ee2UpL766+/hPhpqd+r8eH/rQh/K5z30uSfJrv/Zr+chHPpLv/u7vzuc///kcHBzk/v37uXPnTm7dupXv/d7vza/+6q8ef+73fd/3VXt7AAAAAAAujMNikn7n9IHQ2vJRqLUAO7WKSZlu+/TB3EX2zPVhXrqrZcT8PXb84Jv95E/+ZH76p386n/zkJ/P000/nox/9aDqdTj7+8Y/n+eefT1mW+cQnPpGlpaV87GMfy0/+5E/mYx/7WHq9Xv7G3/gbdbwGAAAAAAAugFFRpn+GptZKr51ep5XtvXENtzqdy9bUSpKb1wf53JfuZVxMztS0g6qcKNR6//vfn8985jNJkg9+8IP5pV/6pbd8znPPPZfnnnvuDR9bWVnJ3/pbf6uCawIAAAAAcNGNismZWk6tVivrK72FGT/YvXSh1jDjSZkvb+/l6WvDeV+HS0ykCgAAAABAI0bFJP3u2QKhteXeQowfHE/KdM8wQvEiu3l9GmS9+Iq9WsyXUAsAAAAAgNoVkzJFmfTOuI9qbaWb7QVoahWTMp3W5Qq1Prg5SKeV3HlVqMV8CbUAAAAAAKjdqJgkSXpnbDlNxw8uxk6ty9bU6nfbeWpjkDuvPpz3VbjkhFoAAAAAANRuPCmTJL3OGZtaizJ+sJhcuqZWkty8PsiLmlrMmVALAAAAAIDaHR43tc72WHp9pZudvVHKsqzyWqd2GZtayXSv1ld39rM3KuZ9FS4xoRYAAAAAALU7HE9Drf4ZA6G1lV6KMnlwMN9QpZiU6Z5xL9hFdvP6MEnykrYWc3T53nkAAAAAADSuivGDSeY+gnA8KdNpX76m1jNHoZa9WsyTUAsAAAAAgNo9Gj94tkBofWUaam3vzTfUmja1Ll+o9S1ry1nqtu3VYq6EWgAAAAAA1G5UnLOptdJNkuzsjSu701lc1qZWp93K09cGQi3mSqgFAAAADFJ4dAAAIABJREFUAEDtRsVsp9bZHksvQlOrLMuML2lTK5mOILwj1GKOhFoAAAAAANRu1tTqnnH84CLs1DpaC3ZpQ62b14fZejjKvYeH874Kl5RQCwAAAACA2h2es6m1utRJp5XszLGpNT5KtS7j+MFk2tRKkjuvPpzzTbishFoAAAAAANTu0fjBswVCrVYrayu9bM9xp1ZxFGpd3qbWIEns1WJuhFoAAAAAANTu0fjBsz+WXlvuzXX84HgyDeYua1Pr2rCfteWuUIu5EWoBAAAAAFC70TnHDybJ2kp3IcYPdtuX89F6q9XKMzeGeUmoxZxcznceAAAAAACNmjW1emccP5gk64syfvAcr+Giu3ltmDuvPsykLOd9FS4hoRYAAAAAALU7PGpq9S70+MGjUKt1iUOtG8M8HBX5+msH874Kl5BQCwAAAACA2lXR1Fpb6WV7b5RyTi0hTa3k5rVBktirxVwItQAAAAAAqF0VO7XWV7oZFWX2RpOqrnUq46NgrnOZm1rXh0mSO0It5kCoBQAAAABA7UYVjR9MMrcRhGNNrawudfNNV5aEWsyFUAsAAAAAgNpVNX4wSbb35hNqHY8fbF/eUCtJnrkxNH6QuRBqAQAAAABQu8Nikk67lfY5Rvetr3STJDtzCrXGk2nbrHPJQ62b14f5/a294/YdNEWoBQAAAABA7UZFmd45w6DZ+MHtvXEVVzq1saZWkuTm9UGKSZkv3dub91W4ZIRaAAAAAADUblRM0u+e75H0+tH4wfk1taah1mVvaj1zfZgkeckIQhom1AIAAAAAoHajyeTcDacry920kuzszzfU6rYv96P1b90YpNOKvVo07nK/8wAAAAAAaMRhUabfOd8j6U67lavL3bmNHyyMH0yS9LvtPLU5yIuvCLVollALAAAAAIDajYtJep3zh0FrKz3jBxfAzWvD3Ln7cN7X4JIRagEAAAAAULvDokzvnE2tJFlb7s5t/KCm1iPP3Bjkazv72T2cT2uOy0moBQAAAABA7UbF5NzjB5NpU2te4wc1tR555vowSfJ72lo0SKgFAAAAAEDtRk/E+MFJEk2tJLl5FGrZq0WThFoAAAAAANSuqvGD68u9bM8p1DoeP1hBOHfRfcvacpa77bz4qlCL5gi1AAAAAACo3biyplY3++NJDsaTCm51OuPiaPxgS6jVbrXy9PVh7hg/SIOEWgAAAAAA1K6qptbaSi9J5jKCsChnTS2P1pPkmeuD3DF+kAZ55wEAAAAAULvpTq0Kxg8ehVrzGEE4a2p1NbWSTPdq3dsbZevh4byvwiUh1AIAAAAAoHajYpJ+FeMHl7tJkp39OYRadmq9wc3rwyTJi9paNESoBQAAAABA7aoeP7i9Nz73WadVzEKttlArSZ6ZhVqvCrVohlALAAAAAIDaTccPnj8MWp/jTq1ZU6sj1EqSbA56WV/p5aVXH877KlwSQi0AAAAAAGo3Ksr0q2hqzXH8YCHUeoNWq5Vnrg80tWiMUAsAAAAAgNqNikm67fM/ku512hn2O3MZPzieTNJuJe2WUGvm5vVhXrq7m0lZzvsqXAJCLQAAAAAAajcqJul3qwmD1lZ6cxs/aJ/WG928PszeaJKv7ezP+ypcAkItAAAAAABqVUzKFGXSq6CplUxHEM5j/OA01PJY/fVuXh8mSe7Yq0UDvPsAAAAAAKjVqJgkSXqdalpO6yu9uYwfLCalfVpvcvP6IElyZwH3av1/X3std3cP530NKiTUAgAAAACgVqNium+p362oqWX84MIY9rv5lqtLeXHBQq2yLPMX/vFv5+/+8xfnfRUqJNQCAAAAAKBWo8m0qVXV6L615W625xRqaWq91dPXhwvX1No9LLI3muTffO21eV+FCgm1AAAAAACo1eF4Gmr1Kxw/uHtYZHw01rApmlpv75nrw3zp3t7xmMlFMAs9v/iN+5mU5ZxvQ1WEWgAAAAAA1Go8mYYKvU514weTZGe/2b1axaRMt6Jg7kly8/owxaTMl7b25n2VY7PxlLsHRb62sz/n21AVoRYAAAAAALU6PGrw9CpsaiVpfAThuCjTaQm13uyZ68MkWai9Wtt7jwLPF15ZnHtxPkItAAAAAABqNSoqbmotd5MkO/vNhlpFqan1dr51cyWddmvBQq1Hfxu3X34wx5tQJaEWAAAAAAC1mu1a6lc9fnCv2fGD42KiqfU2ep12vnVjJXcWKNSaBZ7vubKU25paTwyhFgAAAAAAtXpixg9OynQrCuaeNM9cHy5UqLW9N0qnlXz/t27khVc0tZ4U3n0AAAAAANSqtvGDDYdaxaRMt62p9XZuXh/mD187yIODZttz72R7b5S1lV6+45uv5g9fO8j9/cW4F+cj1AIAAAAAoFaPxg9WEwgt9zpZ7raz3fT4wUmZjlDrbd28PkySvHT34ZxvMrW9N876Si//1jddSZLcflVb60kg1AIAAAAAoFazplaVo/vWVnrHe5Oaoqn1zm5eHyRJXlyQEYTbe6Osr/TyHd88DbVeeHkx7sX5CLUAAAAAAKjVo6ZWhaHWcrfx8YOaWu/sW9aWs9Jr56UFC7VurC5lY6WX2/ZqPRGEWgAAAAAA1OrRTq3qAqH1ld5cxg9qar29dquVm9eHC9PU2jkKtVqtVp69McztVxbjXpyPUAsAAAAAgFodHjW1esYPPtFuXhvmxVd2U5blXO8xKcujUKubJHn2xmruvLqb8WS+9+L8hFoAAAAAANTq0fjB6gKh+YwfnAi13sXNG8Ps7I9z92Gzv5c3e3AwTlFOg88kufWeYQ6LMl/aejjXe3F+Qi0AAAAAAGr1aPxgdY+k11d6eW1/nKLB9k1hp9a7unltkCS5M+cRhLOxlOuzUOvGapIYQfgEEGoBAAAAAFCrusYPlknuHzS3V8tOrXf3zI1hkkUItaZNsVmo9W2bK+l1Wrn9yoN5XosKCLUAAAAAAKjV+LipVV0gNAssthscQTgNtTxWfyebg342Vnp5cc6NqDeHWt1OO09fG+aFlzW1LjrvPgAAAAAAanVYTNJpt9JuVbhTa6WbJI3u1SomZboVBnNPops3hrlzd767q2ah1uxvJEmevTHMC5paF55QCwAAAACAWo2KMr2Kx/atLU9bODv7zY4f7FQYzD2Jnrk+zEuv7mbS4K6zN9t5U1MrmYZaWw9Hubt7OK9rUQGhFgAAAAAAtRoVk/S71T6Onsf4QU2tx7t5bZD98SRf2d6b2x2290bpdVoZ9DrHH7t1YzVJ7NW64IRaAAAAAADU6rCYpNep9nH0PMYPamo93jM3hkmSF75+f2532N4bZX2ll9brflfPzu5lr9aFJtQCAAAAAKBWo0n14wcHvU667Va29xocP1hMNLUe44PXBkmS3/3G/EKtnb3xG0YPJsnaSi/vvbJkr9YFJ9QCAAAAAKBWo3H14wdbrVbWV3rZ2W+mqVWWZYoy6VYczj1phv1uvmVtObdfnl94tL03ytqbQq1k2ta6/Yqm1kUm1AIAAAAAoFajSVlLGLS20m1s/GAxKZMkHaHWY71vbTlf25nvTq315beGWrfes5ovbT3MwXgyh1tRBaEWAAAAAAC1GhWT9CveqZVk2tRqKNQaH4Va3bbH6o+zOejl7oPDuX3/6U6t7ls+fuvGMEWZvHRXW+ui8u4DAAAAAKBWo2KSXg27qNaWe9neb2an1lhT68Q2B/1s7c4n1ComZV7bf+tOrSR59sZqkuT2y0Kti0qoBQAAAABArQ6LMr0amlpNjh981NQSaj3OxqCX3cMi+6Oi8e99f3+cMnnbUOv968tZ6bXzwivz2/fF+Qi1AAAAAACoVa3jB/fHKcuy8rPfrBBqndjmYBoobT1sJnB8ve2jkPPtQq12q5Vnrq/mhVc0tS4qoRYAAAAAALUaFWW6NY0fLCZlHhzUP4LQ+MGT2xz0kyRbD5sfQfhuoVaS3HrPMLdfedBIEEr1hFoAAAAAANTqsMamVtJMI0hT6+QWtamVJM/eGObBQZGv3z9o8lpURKgFAAAAAECtxsUkvTqaWivdJMl2A40gTa2T2xxOm1r35tjUmv1tvNmtG6tJkhdeNoLwIhJqAQAAAABQq8OiTK+GptaVpWlw8dp+E+MHJ0k0tU5io8EG3Zs9rqn1zI1hWkleeOVBg7eiKkItAAAAAABqNaqpqbXUnT7iPhxNKj/7zY7HD9YQzj1plnudDPudOYVa4yx321nudd7236/0OvnAxkpuv6KpdRF59wEAAAAAUKtRUdayU2vW/jos6g+1jscPtjS1TuLa6tJ8xg/uj96xpTXz7I1hbmtqXUhCLQAAAAAAanVYTGoZPzhrah2Mi8rPfrNHTS2h1klcG/Zzdw5NrZ29UdYeE2rdurGaP9jez4OD+sdWUi2hFgAAAAAAtRrXNH5w1v46HDfQ1CqOQi1NrRO5NuzPp6m1N8r6SvddP+fZG8MkyZ1XjSC8aIRaAAAAAADUppiUKcrU0tSahVoHTYRamlqncm21n3tz2al1svGDSfKCvVoXjlALAAAAAIDajI72XfXaNTS1us2FWsfjB2t4HU+ia8OlbO+Njn9uTdnZGz821HrvlaVcXe7aq3UBCbUAAAAAAKjN6Ghs3yyAqlL/qDXVyPjBo3CmI9Q6keur/UzKZGe/ubbWuJjk/sH4sTu1Wq1Wbt0Y5oWXNbUuGqEWAAAAAAC1GU2mgVO3Xf3j6E67lXar4fGDQq0TuTbsJ0m2dpsLtXb2x0ny2KZWkjx7YzUvvrrbeJOM8xFqAQAAAABQm1mLql/DLqpWq5V+p52DcVH52W9WHIVzmlonc231KNR6eNjY99zemwZoJwu1hjkYT/KV7b26r0WFhFoAAAAAANSmzvGDs3MPiyabWh6rn8S14VKS5N7D5ppaj0Kt7mM/99Z7VpMkL7xsr9ZF4t0HAAAAAEBtHo0frKfh1O+0G92pZfzgycyaWncbbGrtnKKp9cHNQTrtVm6/Yq/WRSLUAgAAAACgNqPxUVOrU19T62DUXKhl/ODJrC330mnNq6n1+FCr323ng5sDodYFI9QCAAAAAKA2s6ZWr65Qq9NqZPxgoal1Ku12KxuDfsOh1jjJNFA7iWdvDHP7FeMHLxKhFgAAAAAAtZkFTr1OfeMHDxocP6ipdXIbg16j4we390YZ9jsn3t926z2refnBYbYbDN44H6EWAAAAAAC1GRXTMKiuptZSt52DcVHL2a9np9bpbQ56jY8fXDvB6MGZZ28MkyQvaGtdGEItAAAAAABqMzpqavVramr1Ou0cNtDUOh4/WNPreBJtDvrZaripdZJ9WjO3jkIte7UuDqEWAAAAAAC1Oay5qdXvNjR+8Cic67SEWie1Mehl6+EoZVk28v2moVb3xJ+/MejnxmpfU+sCEWoBAAAAAFCb8fFOrZrGDza0U6soZ00tj9VP6tqgn4PxJHuj+n8/SbJzyqZWMh1BqKl1cXj3AQAAAABQm8PjUOtijx8cHzXOTB88uY3BNGBqagTh9t44a8unDbVW83t3Hx6PyWSxCbUAAAAAAKjNqObxg0vdVjOh1qRMp91Ky/jBE9sc9JMkWw9HtX+vg/EkD0fFqZtat24MM56U+b27D2u6GVUSagEAAAAAUJtZA6ZfU8WpqZ1axaRMty3QOo3N4TRgutdAU2tnbxqcnWanVpLcurGaJPZqXRBCLQAAAAAAalN3U6vfaR+POKzTWKh1ahtHram7DTS1dvZnodbpmlof2FjJUrdtr9YFIdQCAAAAAKA2j3Zq1RdqHYyLWs5+PU2t09s4Gj/YRFNr+6iptXbKUKvTbuXm9WFeEGpdCEItAAAAAABqMzoOteoJhHrddg7Hk5RlWcv5M7OdWpzcUred1aVO7jXQ1NreGyc5fVMrme7Vuv3yg9r/hjg/oRYAAAAAALUZFdMwqN2qJxBa6rQzKadNqjqNJxNNrTPYHPRzd7eJUOts4weT5Nkbq9nZH+flB/U3yjgfoRYAAAAAALU5LCbp19TSSpJ+d/qY+6DmvVqFptaZbA56ubfX4PjB5e6pv/bWjWGS5PYrDyq9E9UTagEAAAAAUJtxUda2TyvJcWA2Gtc/flBT6/Q2Bv1sNdDU2tkb5cpSN90z/K09cxxq2au16IRaAAAAAADU5rCY1BxqNdfU6rY9Uj+tzUEvWw+baWqtr5y+pZUkq0vdvG9tOS+8rKm16LwDAQAAAACozWhSpldjw2k2fvBwXG+oNTZ+8Ew2B73s7I8zrnnn2TTUOv0+rZlnbwzzgqbWwhNqAQAAAABQm9F4chw81WHW1Dqsuall/ODZbAz6SZLtmtta23vjrJ0j1Lp1YzVfubeXvVFR4a2omlALAAAAAIDajCZlep0GmloNhFqaWqe3OZgGTVsP692rdd6m1q33DFMmeVFba6EJtQAAAAAAqM2omKRX4y6qpU5z4wc1tU5v86ipdW/BQ61nb6wmSW6/Yq/WIhNqAQAAAABQm8PxJL1OfY+ie91p0FR3U6uYlOnW2Dh7Um0cNbXu1jh+cH9U5GA8OVeo9c1Xl7K61LFXa8EJtQAAAAAAqE3d4wcfNbXK2r5HkoyLMp2WUOu0ZuMH62xqbe9Nz15f6Z75jFarlWevD3NbqLXQhFoAAAAAANRmVEzSr7GpNdupdVB3U6vU1DqLK0vddNutbNXY1HoUap29qZUkt96zmtuvPMikrDcg5eyEWgAAAAAA1GZU1BsGzUYbjureqVVMNLXOoNVqZXPQy1YDTa215fOFWs/eGGZvNMlXt/eruBY1EGoBAAAAAFCbw5qbWksNNbXGkzLdGl/Hk2xz0K95/OA4yfmbWs/eWE2S3H7lwbnvRD28AwEAAAAAqM24mNS6U6t/vFOr5vGDkzLdtqbWWWwMerWOH9ypaPzg09cG6bSS37VXa2EJtQAAAAAAqM1hUR6PCKzDcajVQFOrI9Q6kybGD7aSXFnunuuc5V4nT20OcvtlTa1FJdQCAAAAAKA2o5rHD/a7mlqLbjp+8DBlWdZy/vbeKFeXu5WEjrduDHNbU2thCbUAAAAAAKjNqChrHT84O1tTa3FtDHo5LMrsHha1nL+9Nz736MGZZ2+s5uv3D/Lafn3NMs5OqAUAAAAAQG0Oi0mt4wfbrVZ6nVYOi3paQDNjTa0z2xz0k6S2EYTb+6PKQq1b7xkmibbWghJqAQAAAABQm3ExqbWplSRL3Y7xgwtsczgNnO49PKzl/J296kKtZ2+sJkleEGotJKEWAAAAAAC1KCZlijK1NrWS6V6t+scPTowfPKPNlWlT625dTa0KQ63rw342B73cfvlBJedRLaEWAAAAAAC1GB0FTf2aQ62lbruhppZH6mdRZ1OrLMts742yVlGolSS3bqxqai0o70AAAAAAAGoxOtpzVf/4wSaaWmW6nqifyaxFtbVbfVPr4ajIqCizvtKt7Mxnbwzz0t3djGv+m+L0vAUBAAAAAKjFLGiqffxgp53DowCtDpOyzKSMptYZ9TrtXF3uZquGptb23jQoq2r8YJI8+55hRkWZ37+3V9mZVMM7EAAAAACAWszGD/Zq3kW11Kt3/GAxmQZm3ZobZ0+yzUEv9/aqb2pt742TVBxq3VhNktx+xV6tRSPUAgAAAACgFrPxg/2a5/YtdTs5qHFU3Pgo1Oq0hFpntTHoZ2v3YjS1vm1jJf1OKy+8bK/WohFqAQAAAABQi9FkGjR1a25q9TvtjDS1FtrmoJeth9U3tXZqCLW6nXaevjbU1FpAQi0AAAAAAGoxGh81tereqdVtH+/vqsO40NQ6r81Bv6bxg9WHWkny7I1hXnh5N2VZ3642Tk+oBQAAAABALWZNrV7t4wfbOaixqTWeNc40tc5sY9DLa/vj4z1rVdneG6XTSlaXOpWee+s9q7m3N8rdGkYmcnZCLQAAAAAAajFrT/XqHj/YbVcelrzebKdW3WMUn2Sbg2mT6l7FIwi390ZZW+mlVXGL7tkbwyTJC6/Yq7VIhFoAAAAAANSiqfGD9Te1jsYPCrXObHPQT5JsPay2+bSzN85axaMHk0eh1m2h1kIRagEAAAAAUIvj8YM1j+1b6nZyWNS3+6g4bmp5pH5Ws6bWVg1Nrar3aSXJ1eVevunKUm6/8qDyszm77lm+aDQa5ad+6qfy1a9+Ne12Oz/7sz+bbrebn/qpn0qr1cqzzz6bn/mZn0m73c5nPvOZfPrTn063282P//iP50/8iT9R9WsAAAAAAGABzYKmXs1NrX631cj4QU2ts5s1teoYP/itm4NKz5y59Z7VvPCyptYiOVOo9au/+qsZj8f59Kc/nc9+9rP5+Z//+YxGo/zET/xEfvAHfzB/7a/9tfzKr/xKvud7vie/+Iu/mH/yT/5JDg4O8vzzz+eP/bE/ln6/X/XrAAAAAABgwYxnO7VqHz/YaWT8oJ1aZ7dx3NSqdvzg9t4of2TlTFHHYz17Y5j/+6W72R8VtZzP6Z3pvyQf/OAHUxRFJpNJHjx4kG63my984Qv5gR/4gSTJD/3QD+Vf/It/kd/+7d/Ohz/84fT7/Vy5ciVPPfVUvvjFL1b6AgAAAAAAWEyHRTPjB/uddsaTMpOynhGEhVDr3Ib9TvqdVqXjB8uyzE5N4weT5NaNYSZlcvtlIwgXxZniy8FgkK9+9av54R/+4dy7dy+/8Au/kF//9V9PqzV9Qw+Hw9y/fz8PHjzIlStXjr9uOBzmwYPH//I7nVbW1+upCz6JOp32uX9eT8oZi3AHZzij7jMW4Q7OcEbdZyzCHZzhjLrPWIQ7OMMZdZ+xCHdwhjPqPmMR7uAMZ9R9xiLcwRkX94ze0jRsuL45zPrV5drusdzvJEkGq8tZ7nVO/fWPu8PKawdJkrWry+/4eRfldzLPM66vLmV3PDnx2Y+7x2t7oxRl8s2bw1p+L9/3zI0kv5PffflBvuvD7zvTGVXcg0fOFGr9o3/0j/LH//gfz1/6S38pf/iHf5gf/dEfzWj0KF3d3d3N1atXs7q6mt3d3Td8/PUh1zspijLb2w/PcrVLaX19cO6f15NyxiLcwRnOqPuMRbiDM5xR9xmLcAdnOKPuMxbhDs5wRt1nLMIdnOGMus9YhDs4wxl1n7EId3DGxT1j5/5+kmTvwX62J28/HrCKe8yaYC/ffZCry6dv7TzuDtuvTV/H/sPDd/y8i/I7mecZa8vd/OH23onPftw9vnJvL0mylHfOFM7zWlZTpt1Kvrr1cCF+ppfJjRtvnyWdafzg1atXj8OptbW1jMfjfOhDH8rnPve5JMmv/dqv5SMf+Ui++7u/O5///OdzcHCQ+/fv586dO7l169YZXwIAAAAAABfJYTEd21f3Tq3+0fmHNe3VGh8Fch3jB89lc9DPvQrHD27vTc9aq2n8YKfdyvpKL6/uVrsHjLM7U1Prz/yZP5O/8lf+Sp5//vmMRqN84hOfyHd+53fmp3/6p/PJT34yTz/9dD760Y+m0+nk4x//eJ5//vmUZZlPfOITWVpaqvo1AAAAAACwgEbHO7XqDbWWukehVlHPTq2xnVqV2Bz0cvuV6vZTzUKtunZqJdMg7u6Dg9rO53TOFGoNh8P8zb/5N9/y8V/6pV96y8eee+65PPfcc2f5NgAAAAAAXGCPQq16w6Cl7nSPVl1NrWIWatUczj3pNgb9bD0cpSzLtFrn/5t4FGqdKeo4kc1BL68+0NRaFN6BAAAAAADUYlSU6bRbaVcQYLyb/nFTq6bxg0cNsG7Nr+NJd23Yy3hS5v7BuJLzGmlqDft5VVNrYQi1AAAAAACoxWExSb/mllby+vGDNTW1ymmo1WngtTzJNgbT8Glrt5q9Wtt74/Q6rQx6nUrOezuaWotFqAUAAAAAQC3GRZl+AyP7ZqHWQU3jBzW1qrG50k+SbO1VExLt7I2yvtKrZJThO7k26GdvVOThYVHb9+DkhFoAAAAAANTisJg0sodqNn5wVNf4weOdWkKt89gcTpta9x5W1dQa1Tp6MHl0562H2lqLQKgFAAAAAEAtRg2PHzwYl7WcX8xCrbZQ6zw2BtOm1t3Kxg+OslZ3qHV8Z6HWIhBqAQAAAABQi1FRptdIU2u6U6munVrjyfTcjlDrXNZXemkluVdR62l7b5T15W4lZ72Ta0eh1lZF7TLOR6gFAAAAAEAtDotJeg00teofPzj9p6bW+XTbrayt9HJvr5qAaGd/XH9Ty/jBhSLUAgAAAACgFuNJmV67/sfQj8YPamotuo1Br5JRfsWkzGv79e/U2jg6f6uikYmcj1ALAAAAAIBaHI4njYwfnIVahzWFWo92anmkfl7XBr3cq2CU3/2DcSZlag+1up32NIjT1FoI3oEAAAAAANRiNCnT7zYwfvAoOKtvp9Ys1NLUOq+NQb+SUX7bRyMM6w61kuTacMlOrQUh1AIAAAAAoBajYtLo+MG6Qy3jB89vc9CrJCDaOQ61uuc+63Gur/azVcHIRM5PqAUAAAAAQC2m4wfrD4K6nXbarXrHD7Yi1KrC5qCf3cPi3PvPGm1qrVbTLuP8hFoAAAAAANRiNCkb2amVTEcQHhZlLWePJ6VAqyIbg2kIde+cIVGTodb1VeMHF4VQCwAAAACAWoyKZppayXQEYV1NrXFR2qdVkc2jUOu8IdH23jhJQ6HWcNou2x8VtX8v3p1QCwAAAACAWoyK5ppavU47BzXt1CrKMt2Gwrkn3eagnyS5d+5Qa5SlbjvLvU4V13pX11aXkpw/iOP8hFoAAAAAANRiVEzSb2r8YLedUU2h1riYpNMSalVhNn7wbgXjB5toaSXJ9dVpEGev1vwJtQAAAAAAqMW0qdXQ+MFOfeMHp00tj9OrUGVTq7lQa9rUururqTVv3oUAAAAAANTisJg0OH6wlYMad2qZPliNQb+T5W773K2nnb1R1le6Fd3q3WlqLQ6hFgAAAAAAtZiOH2yoqdVtZ1SUtZw9nmhqVWlz0Dv3fqomm1qbw9lOLaHWvHk67bJUAAAgAElEQVQXAgAAAABQuWJSZlKmsTCo323noKadWsWkTLetqlWVzWE/9869U2vcWKi11G3nylI3W8YPzp1QCwAAAACAyo2OAqZ+Y+MH28ffs2rjSZmOUKsyGyvna2qNi0nuH4yz1lColczaZZpa8ybUAgAAAACgcrNRgL2mxg922rXt1NLUqtbmoH+uUGtnf5wkjTW1kmm77O45RyZyfkItAAAAAAAqd3jUmuo1OH7wsKZQayzUqtTmsJfth4eZlGfbgbazPw2X1pa7VV7rXV0b9LK1q6k1b0ItAAAAAAAqNxsF2GsoDOp3WjWOH5wItSq0MeinKJPX9sZn+vrtvWmo1WhT65ztMqoh1AIAAAAAoHKz8YP9bnNNrYPibM2fxzF+sFqbR2HU1t7Zmk/be/MYP9jL/YNxbW1ATkaoBQAAAABA5RofP9ipd/xgR6hVmc3hNIy6d8bm07yaWkmy9dAIwnkSagEAAAAAULnxUWuqufGD7eMgrWrTppbH6VXZOAqI7p5xR9XOUai1NpdQywjCefIuBAAAAACgcsdNrQbHDx6OJynL6kcQampV69rg/E2tQa+TpYb+tpLk2lG7TFNrvoRaAAAAAABUbjQ5CrUabGqVmQZQVRvbqVWpq8u9tFtnD4i290ZZX+lWfKt3d9zU2tXUmiehFgAAAAAAlRuNp+FSv6mdWketnTpGEI4nZbodoVZVOu1W1ld6Zx7lt703anT0YJJsHrXL7mpqzZVQCwAAAACAyh03tRoKg2bh2eG4+lCrmJTptIRaVdoc9M8xfnCc9YZDreVeJ8N+x06tORNqAQAAAABQucNi2tTqNdXUOgrPDmoItTS1qrcx6J1z/GCzoVaSXBv2s7WrqTVPQi0AAAAAACo3OgqXmh4/OCpq2KlVTDS1KrY5OPv4wZ05hVqb5wjiqIZQCwAAAACAys3GDzbVcFo6CrUO7NS6EM46fvBwPMnuYTGnUKufu7vGD86TUAsAAAAAgMrNxg821dTq1bxTq9v2OL1KG4NeHo6K7I+KU33dzv40VFpf6dZxrXelqTV/3oUAAAAAAFRufNSY6jXV1OrMxg/W09TqtDW1qrQ5mDatTjuCcHtvFmrNoak17Gdnf3z8t03zhFoAAAAAAFRu1tTqNbxT66C2ppZQq0qbg36S5N4pm0+zUGttDqHWtTMGcVRHqAUAAAAAQOVGx02thkKto0bYoabWhTBrat09dVNrnGROTa2jIM4IwvkRagEAAAAAULlRw+MHZ02tWUOsKmVZZqypVbnN4dmaWjtzHj+YnD6IozpCLQAAAAAAKndYTIOgdquhUOuoEXZY8fjByVFGJtSq1sbK+XZqrS13K7/T4xzvAdvV1JoXoRYAAAAAAJUbFZPGWlrJ65ta1YZa46NUy/jBai33Ohn0OmcKtVaXOuk2NNby9a4NZ+MHNbXmRagFAAAAAEDlRkV53J5qQl1NreIo1NLUqt7msHfq8YPbe6O5jB5MkpVeJyu9tp1acyTUAgAAAACgcqNi0mibZqm2ptb0PE2t6m2s9E+9n2pnbzy3UCtJNgf93DV+cG6EWgAAAAAAVG5UTNJvcPxgr6am1vi4qeVxetU2BxerqZVMQy3jB+fHuxAAAAAAgMqNivI4aGrCLECruql1PH6wwYDuspiOHzz9Tq21OYZa14Y94wfnSKgFAAAAAEDlDotJeg0GQa1WK71OKwfjstJzj5taLaFW1TYG/WzvjY6Dw5PY3htlfXnOTa1dTa15EWoBAAAAAFC5UVGm32BTK0n6nXZGmloXxrVBL5My2dk/WUi0PyqyP55kfaVb883e2eagl+290XHYSbOEWgAAAAAAVG5UTBrfQ7XUbVc+fnBcTMOLjqZW5TYG/SQ5cfNpe2/6eXPdqTXsp3zdXWiWUAsAAAAAgMqNikn63WaDoF6nnYNxxaGWplZtNgfTcOqkO6p29sZJ5htqXZvdedderXkQagEAAAAAULnRpExvDk2t2sYPtoVaVds8amrde3iBmlqzdtkJgziqJdQCAAAAAKByh+NJeg23m/q1NLWm53WEWpXbOGo93T1hQLQQodZwFmoZPzgPQi0AAAAAACo3mpTpdZp9BN3rtKrfqaWpVZury910WhetqXUUxBk/OBdCLQAAAAAAKjcqmm9qLXXbOSzKSs+chVqaWtVrt1rZGPRPFWq1klxZ7tZ7sXcx7Hey1G1ras2JUAsAAAAAgMqNijL9hpta/U47h5WPH5w1tTxOr8PGoHeq8YNXl7tzDRhbrVY2Bz07tebEuxAAAAAAgMpNm1oNh1rd6kOtwvjBWm0Oeiduau3sj+c6enBmc9DP1q6m1jwItQAAAAAAqNzhHMYP9jvt2nZqGT9Yj81BP/dO0dRaW4hQ6+TtMqol1AIAAAAAoHKjopxPU6viUEtTq17T8YOjlOXjd6Ft740Wo6k17NupNSdCLQAAAAAAKjcqJuk33tRq1bZTS1OrHtcG/RyMJ9kbPf73trM3yvpKt4Fbvbtrg162Hx5mcoIgjmoJtQAAAAAAqFQxKTMpk27TTa1OO4dFtUHDeDINWzS16rExmDavth4zzq8sy8Vpag36KcppyEazhFoAAAAAAFRqdDQCsD+P8YMVN7WOxw823Dq7LDYH/SR57Di/vdEkh0W5GKHWcHrnu0YQNk6oBQAAAABApUZHbale4+MHq9+pNT56LZ2WUKsOm8NpSHXvMU2t7aNW1NoihFqzdtnuu9+Z6gm1AAAAAACo1CxY6s2hqTWelMftqioU5ayp5XF6HTaOQqrHtZ5modYiNLWunbBdRvW8CwEAAAAAqNSj8YPNtpuWjoKnUYVtrVlTq6upVYuNo4DopE2thQi1hrNQS1OraUItAAAAAAAq9Wj8YLOPoHvd6fercgTh2E6tWi1121ld6uTeBWpqrS510uu0cndXU6tpQi0AAAAAACo1r/GDS0fB0+G4ulBrNsqw2xZq1WVz0H9sQPQo1Oo2caV31Wq1pnfW1GqcUAsAAAAAgErNRvb1Gg6CZiHaQQ1NrY5Qqzabg17u7b17QLSzN0qnlawuzT/USqZ33toVajVNqAUAAAAAQKWOm1rdhptaR99vNC4rO7MQatVuY9DP1mObWuOsrfTSXpDdZteG/Ww9ZmQi1RNqAQAAAABQqdFkGmr1G95D1a+lqTVJu5WFCVOeRJuDXrYeM8pve2+UtQXYpzVzkjtTPaEWAAAAAACVmjWleu1mH0HPmmFV7tQaT0r7tGq2OehlZ398POrx7WzvjbK+UKHWtKk1KatrBfJ4Qi0AAAAAACo1t/GDR02tw4p3anUbDucum41BP0my/S7Np4ULtYb9FJMyr+2P532VS8U7EQAAAACASo0ms6ZWw+MHu9WHWsWktE+rZpuDaVj1bjuqdvbHWV/pNnWlx7p2fGcjCJsk1AIAAAAAoFKj8WynVrOPoGc7vIwfvFg2j5pa994h1CrLcvGaWkd33tp95yCO6gm1AAAAAACo1GgyDZW6nXk1tarbczTW1KrdxlHr6e47tJ52D4sUkzJrywsUag01teZBqAUAAAAAQKVmoVLzTa2jUEtT60K59pim1vbe9OOL2NS6+y4jE6meUAsAAAAAgEqNi3mNH5x+v4OKd2o13Ti7bFaXOum2W++4U2sRQ62ry9102q1s7WpqNUmoBQAAAABApWZNrXmNHxxV2dQqynRaQq06tVqtbA567zjK71Go1W3yWu+q/Zg7Uw+hFgAAAAAAlRrNqam1dLxTq8KmVqmp1YTNQf+x4wfXFqiplUzv/E7tMuoh1AIAAAAAoFKzUKvpMKg3Gz9YaVNroqnVgI13bWqNkyzW+MEk2Rz0ctf4wUYJtQAAAAAAqNRhUabbbqXdcBjUbbfSaT0K1aownpTpNtw4u4ymo/zeuanVbbcy7HcavtW72xxqajXNOxEAAAAAgEqNikl6cxrZ1++2czAuKzuvmEwDOuo1HT94mLJ86+9ue2+U9ZVeWgvWmLt21C57uztTD6EWAAAAAACVGhVl4/u0ZvqdduVNrY5Qq3Ybg14OizK7h8Vb/t3OUai1aDYH/YyKMg8O3npn6iHUAgAAAACgUtOm1pxCrW47BxWGWppazdgc9JPkbcf5TZta3aav9Fibw2nQdvcddoFRPaEWAAAAAACVmuf4wV6nncOxptZFMwuI7r1NQLS9wE2tJNkSajVGqAUAAAAAQKUOi3JuTa2lGsYPamrVb3NlGhDdfdum1jhrCxhqXZuFWrtvvTP1EGoBAAAAAFCpeTa1+t12Dipsahk/2Ix3amoVkzKv7S9oU+vozppazRFqAQAAAABQqVFRpj+vnVqdVg4rbWpNhFoNmIVWb2493T8YZ1JmIUOtteVe2q23b5dRj8XbrAYAAAAA8IT6r//P29m4spw//4MfmPdVajUqJum25xRqdds5LMrKzivs1GpEr9PO1eXuW1pPO3vTwGgRQ61Ou5X1lV62djW1mqKpBQAAAADQkN/+2mv5l7+/Ne9r1G5UTNLvzmn8YKedwwrHD9qp1ZzNQS/39t7Yeto+DrUWs6NzbdjPlqZWYxbzrwAAAAAA4Am0P55kv3jyH4CPJmVWe525fO9+p13x+MFybq2zy2Zj0H9L62l7b5xkMZtayTSIs1OrOd6JAAAAAAANORhPcu8SPAA/HE/Sm1O7qd+ttqlVTMp0O5paTZgGRG8MfWfjB9cWNtR6axBHfYRaAAAAAAAN2R8Vub8/zrjCJtEiGhVl+t157tSqtqnVaQm1mrA56L/L+MHFDbXuPhylLKvb48Y7E2oBAAAAADRk/6hBtL0/nvNN6jWaTOa2h6rfaeVAU+tC2hj08tr+OKPXhZLbe6MsddtZnlNI+jjXhr0cjCd5OCrmfZVLYTH/CgAAAAAAnjBlWR6HLdt7T/ZercPxJP3OnJpanXZGRXWtGU2t5lwbTNtY9143gnB7b5S15W5aC/o72Bz0kyRbu0/2e3pRCLUAAAAAABrw+vbQzhMeao0nZXpzCrWWqh4/WEw0tRqycRQQvTnUWtTRg0myOZzebesS7MpbBEItAAAAAIAGvD7UeuKbWsUkvTkFQb1OOwfjSSU7jsqyTFFmbqMUL5vNo6bW3dcFRNt748UOtY6CuLsPn+z39KIQagEAAAAANGD/EoVao6Kc2/jBpaPdS+PJ+UOt4uiMjlCrEZtv09Ta2V/sptZsZOLWrqZWE4RaAAAAAAAN2B8Vx//7yQ+15tfUmoVpr2/GndUsGOu2PUpvwsbgraP8Fn384Pqgn1aSu0KtRngnAgAAAAA04I3jB8dzvEm9xpMykzJz26k1+75V7NUaa2o1atjvpN9pZeuoqTUuJnltf7HHD3bbrayv9I7vTL2EWgAAAAAADbgs4wfHR2HSvEKtpe40gDqstKkl1GpCq9XK5qCfe0dNrZ2j98naAodaSbI57L2hXUZ9hFoAAAAAAA04GF+O8YOHx6HWfIKgR02t6nZqCbWaszHo5e5R62nWflpf6c7zSo+1Oej//+zdS4hk+WHv+d95xqsiMyszW2oZWdaU5J5RXxAIaxq8cNu6MIjZGtPXatBywMIwSBvLGCStLkKbXtsGrbotNwJrNat7kQ2ykWmM8EUzarWvuzRXgyR3uzOz8hWZcZ7/WZxzorKq8hGPcyL+J+L72UhUZ544Ud1xFvHj9/vrcLS+n2mbEGoBAAAAAAAAwBKMkyLs2RuEkwbKOkrKMGl1TS3mB9usaGoVn4+qsWXz/KAk7fZpai0LoRYAAAAAAAAALEE1P/iR7e5aN7WSMkwKV9TUCqumVg3zgzS1lm+3H0zCrEejdoRae4OQUGtJCLUAAAAAAAAAYAmq+cGPbPfWPNRabVOrzlCLptby3e+HOrpIZIyZNLZsD7V2+6Euk1yXSXb3D2MhhFoAAAAAAAAAsATV/OBHtru6THKN1/QL8Mdnaq0o1KpxfpCm1vLtDQKludFZlOq4bD9tWx9qFfd3OKKt1TRCLQAAAAAAAABYgmp+8Nd2upKkk3G6yttpzMrnB2s9U6u4hr+igG4T3S8DoqOLRI8uEvUDb3JOmq12B6Gk4p7RLLv/SwAAAAAAAACANTGZH9wqQq11nSCs5gdXFQRVYVqt84MOTa1l2e1VAVGsRxexdnr+iu/obntVEEdTq3GEWgAAAAAAAACwBOMkl+c6em7YkbS+oVa86qZWdaZWGa4tYjI/uKL3sol2B0VA9Ogi0dFFYv30oFScqSUVQRyaRagFAAAAAAAAAEsQpbm6vqv75RfgJ2saaqVlmBS4q/n6uZqqq6WpVbXOaGotTfX5OBwlenQRtyTUKs/UYn6wcYRaAAAAAAAAALAE4zRTx3d1vzx/Z92bWsGKzkEKyqZWVMOZWpmhqbVsO71AjqRHF7EejWLttCDU8j1X212f+cElINQCAAAAAAAAgCUYJ7m6gaftri9H6xtqJeVk36rmB6umVlJDqDVparmEWsviu462e4EeXSZ6dJG0ItSSignCI5pajSPUAgAAAAAAAIAlqOYHfc/VVtfX8WW66ltqRFLO/q1qfrA6UyuqY36wDOg8Qq2lut8P9P5ZpPMo1U7PX/XtTGV3EHCm1hIQagEAAAAAAADAElTzg5K03QvWtqn1eH5wNUFQUDbEajlTK6eptQp7/UD/7+GFJNHUwhMItQAAAAAAAABgCaK0mB+Uii/q1zXUquYHV9XUchxHoecoLqcDF5HlRTBGU2u57vdD/epkLKlNoVagQ87UahyhFgAAAAAAAAAswTgp5gelNQ+1yoZUNQO4CqHvThpji3jc1OKr9GXa7QeqIsm2hFp7g1CjOKtl9hI345MIAAAAAAAAAEtwdX5wp+frZF1DrSoI8lbXbgo9l/nBFtvth5P/v92SUGu3X9wn52o1i1ALAAAAAAAAAJbguvlBYxafyLNNklnQ1PLqbWoxP7hc9/uPg6y2NLWqIO6ICcJGEWoBAAAAAAAAwBKMk/xKUytQnBldJus3VVaFWsEqm1p+PU2tjKbWSuxeDbW6/grvZHq7gyLUOrxYzwamLQi1AAAAAAAAAGAJxmk2OVOrmlRbx3O14szIdx05zornB2lqtVbVehp2ffkrbPzNYq+aH6Sp1ah2/NcAAAAAAAAAAC339PygtJ6hVpLlK50elMqmVg2hFk2t1ajmB+9fOVvLdtW9HtHUahShFgAAAAAAAAA0LMuNksw8MT8orWuoZVY6PShJoefUMj9YNbX8Fb+fTVM1ta6erWW7ju/qXsfT0QVNrSYRagEAAAAAAABAw6IyYOluQKgVZ7mCVTe1PFdxZha+Tlq2vbwVTiluon7oqeu7rWpqSUUYdzhav8+0TQi1AAAAAAAAAKBh4zSTJHX8an7Ql7SeoVaa5atvavluLU2tzFRNLb5KX7aP7/b18b3+qm9jJnv9gKZWw/xV3wAAAAAAAAAArLtxUja1giIcudfx5TnSyRqGWnFmrGhqRTWcqZWWbS/WB5fvz//Tp7W/e0+X5+NV38rUdgehHh6MVn0ba414GQAAAAAAAAAa9vT8oOs42u4FOr5MV3I/f/uvB/r/ji4auXaS5QpXHWr5rpIaQq3MGHmuI4f5waUbhP7kDLq22O2HOrpYv6DaJu36LwIAAAAAAAAAWujp+UFJZai1/C/As9zoz/6vn+qNt37eyPWTzKx8frDj1TM/mGZGvkughens9gOdjtNaAlVcj1ALAAAAAAAAABr29PygJO2sKNQ6GSfKcqPjhholcZavfH4w8JxJO24RaU6ohentDkJJoq3VIEItAAAAAAAAAGhYVDa1uv7qQ62D81iSGnvtNMtX3tQq5gfNwtfJCLUwg71+IEk6uohXfCfri1ALAAAAAAAAABo2aWpdmR/c6fkrCbUOyy/cTxt67TgzK29qdXxXUQ0TcGlenKkFTGO3Xza1RjS1mkKoBQAAAAAAAAANq6bwOk/ND55cJjJm8UbRLA5HzTa1kixXsOIgKPBcZblRli/2d0tTC7PYHRRNreozhvoRagEAAAAAAABAw8Y3zA9mRjqPsqXey2HZIjm9TBu5fpIZhf6Km1plUyxZsK2V5jmhFqa2Vza1DpkfbAyhFgAAAAAAAAA07Pr5waLVsewJwsdNrbiRlliS5yufH6xCtaohNy/mBzGLbuBpEHo6umB+sCn+vL/4F3/xF/rbv/1bJUmiL3zhC3rppZf0p3/6p3IcR7/5m7+pb3zjG3JdV9/97nf15ptvyvd9felLX9LnPve5Ou8fAAAAAAAAAKxXhSvdK/OD21dCrV+/31vavRyUoVaSGUVprm7g3fEbs4nT1c8Phl7x+vGCTa1ifpBuCKa32w90xPxgY+b6NL711lv653/+Z/31X/+1Xn/9db333nv65je/qS9/+cv6zne+I2OMvv/97+uDDz7Q66+/rjfffFPf/va39dprrymO+ZcJAAAAAAAAYLNU84PhU/OD0uqaWpJ0Mq5/gtCG+cHq9RcNtWhqYVa7/VBHzA82Zq4nyz/8wz/ohRde0B//8R/rj/7oj/R7v/d7+slPfqKXXnpJkvTyyy/rhz/8oX784x/rM5/5jMIw1HA41Mc+9jG98847tb4BAAAAAAAAALBdlObq+K5c53FAstMrhrRWEWpV50SdNRFqWXAOVVjOH8bpYvOKaW5W/l7QLruDUIfMDzZmrvnBR48e6Ve/+pX+/M//XL/4xS/0pS99ScYYOeUDeTAY6OzsTOfn5xoOh5PfGwwGOj8/v/P6nudoZ6c/z61tJM9zF/77Wpdr2HAPXINrNH0NG+6Ba3CNpq9hwz1wDa7R9DVsuAeuwTWavoYN98A1uEbT17DhHrgG12j6Gjbcwzpcw7iueoGnnZ3+5Bp+L5QkRZr9+9BF3svRZaKP7w307gfnynyv9v8+ksxoOOhMfd0m/r3c3yrmHMNeONW1b7oHx3XVCaf7O2r7f6Nco55rfOR+T//tlyfP/Hwd94E5Q62dnR09ePBAYRjqwYMH6nQ6eu+99yb/fDQaaWtrS/fu3dNoNHriz6+GXDfJMqPj44t5bm0j7ez0F/77Wpdr2HAPXINrNH0NG+6Ba3CNpq9hwz1wDa7R9DVsuAeuwTWavoYN98A1uEbT17DhHrgG12j6Gjbcwzpc42QUKfQcHR9fTK5hjFHgOfq3o4uZrznvfYyTTGfjVC99rKt3PzjXvx2c6/h+d+br3HYfSZYrT9Kp76+Jfy9JVDRljo4vdNy/+2vwm+7hMk6lfLrvq9v+3yjXqOca9zxXjy4SHRyey/euzI3WcB+b5Lnnrs+S5pof/K3f+i39/d//vYwxev/993V5eanf/u3f1ltvvSVJ+sEPfqDPfvaz+vSnP60f/ehHiqJIZ2dnevjwoV544YX53wUAAAAAAAAAtFCU5uoG3hN/5jiOdnqBTpY4P3hYnvXz8d2iMXIa1Ts/mOZGuZECb8Vnann1nKmV5Ua+x/wgprc7KM7Ke7TkWdFNMVdT63Of+5z+6Z/+SX/wB38gY4y+/vWv66Mf/ai+9rWv6bXXXtODBw/0+c9/Xp7n6Ytf/KJeffVVGWP0la98RZ1Op+73AAAAAAAAAABWGyfFmVpP2+kFSz1T63BUvNaDvTLUqvlMrbQMkcJVh1rl33WULhZqpZlRL1jte0G77PaLWdGjUaLn7pGH1G2uUEuS/uRP/uSZP3vjjTee+bNXXnlFr7zyyrwvAwAAAAAAAACtN04zda8JtbaXHmoVTa1fv9+T5zo6G9f72lUzatXtpk4ZqiWLNrUMTS3MZrdfNLWqViTqRcQMAAAAAAAAAA2L0lydp+YHJWmnu5pQ67lBqK2ur5Oam1pJZiStvqkV+EUQtXhTK5fv8jU6prc3KJtahFqN4NMIAAAAAAAAAA0bJ/m1Ta2dnr/0UMuRtNMPtd0LdFZ7qFWESMGK203hpKllFrpOmht5Lk0tTO/q/CDqR6gFAAAAAAAAAA2L0ptCrUCn41RZvlj4Mq3Di1j3+4F819F2+dp1issQKVhxU6s6vyxadH4wN/IJtTCDfuip67vMDzaEUAsAAAAAAAAAGjZOs0nQctVOL5CRam9M3eTgPJ7Mo233Ap1GTTW1Vjw/WL5+vOj8IE0tzGF3EOrogqZWEwi1AAAAAAAAAKBh4yRX97oztXqBJC1tgvDwItFe/0qoNa73datQK1zx/GAVICY0tbACe/1ARyOaWk0g1AIAAAAAAACAhkVpfmNTS1piqDWKtXfvcahV/5laxfygb0lTK6qhqUWohVnt9mlqNYVQCwAAAAAAAAAaZIzROM1uPFNLWk6oZYwpQq0nmlqpclPfeV6xJU0t33XkOY/vZ17MD2Ieu4NAR5yp1QhCLQAAAAAAAABoUJob5UbXzg9u93xJywm1Tsep0txobxCUr12c5zWKstpeIy2bWuGKm1qSFPqu4nSxwI75Qcxjtx/q+DJRltcXGKOw+icLAAAAAAAAAKyxcVK0hVY9P3hQnvGzP3jc1JKkkxrP1aqaUaueH5SKYG3xplZOUwsz2+2Hys3yZkU3yeqfLAAAAAAAAACwxsZp0YS6bn6wG3jq+q6OL+s92+o6h2WotVeFWt0i1DqL6nvtxJL5Qalqai0WahVNLb5Gx2yqNiQThPXj0wgAAAAAAAAADYrKYOW6+UGpaGsd19iWusnhxVOhVr/44v20xkAtKecHAwuCoHqaWka+BQEd2mW3PLfuaERTq26rf7IAAAAAAAAAwBq7bX5QKkKtkyXMlB2WX7BP5ge7xXlepzU2taoQKfBXHwQtGmrlpjgLzXdW/17QLrtlYHxIU6t2hFoAAAAAAAAA0KDH84O3NLWWEmrF6viuBmFxH5OmVo0tsSS3qKnlu5OW3Dyy8r3Q1MKsqjbk0QVNrbqt/skCAAAAAAAAAGvs8fzg9V/Hbvf8pYRaB6NYe/1ATtk8qs7UOh3XOD+YVmdqrf6r59BzJ2d8zSMtQ1T+Z90AACAASURBVC2PphZmNAg9hZ6joxFNrbqt/skCAAAAAAAAAGtsmvnBZTW1qgaJJHUCTx3frTfUqppaNswP+o5imlpYAcdxtNsPdcT8YO0ItQAAAAAAAACgQdEU84PnUaZ0gVbRNJ4OtSRpq+vrrM5QqzpTy4b5Qc9VlJm5fz8tf9d3CbUwu91BqEPmB2u3+icLAAAAAAAAAKyxcXp3U0uSjmsMl65zU6h1UuOZWlUzKrCg3dTxF50fLH7XI9TCHHb7AfODDSDUAgAAAAAAAIAGjZOyqXXDmVqTUKvBCcIky3UyTp8NtTq+zqJ65wd915mc27VKgedOzjObR3WmFk0tzGOvH+qIplbtCLUAAAAAAAAAoEFVU+u2+UFJOmkw1Kq+XH+2qRXUe6ZWliv07PjaOfTdhc7UqkItmlqYx+4g0KOLWLmZfwITz7Lj6QIAAAAAAAAAayqadn6wwVDroJxB2+s/GWoNu37NoZaxYnpQkjqeq3iB+cFs0tTia3TMbrcfKjPS6WWzs6Kbhk8jAAAAAAAAADRonOZynZvPmdrp+ZKaDbUOy1BrfxA88edbXV+ndZ6pleUKLGlqBZ6zUKjF/CAWsdsvPmuHF5yrVSc7ni4AAAAAAAAAsKbGSaau7914ztT2EppaVaj17Pygr8skV7JA+HNVmuUKbWlq+a6SbP7pN+YHsYjqs1Z99lAPQi0AAAAAAAAAaFCU5jdOD0pS4LkahJ6OG5wpq75Y3316frBTBGp1TRDGmZFvSVMr9FxFaS4z55lGGU0tLKD6rFXn2aEedjxdAAAAAAAAAGBNjdNc3eD2r2J3ekHjTa3trq/wqXBtu1tMH57VFGolWa7QllCrfK/ztrVoamER1fzgEfODtbLj6QIAAAAAAAAAaypKslubWlLzodbBKNbuU9ODkjQsQ63TqK5Qy9x4dtiyVeHavOdq0dTCIra6vnzX0eGIpladCLUAAAAAAAAAoEHjNFfX9279mZ1eoJNGm1rJM+dpSY+bWqfjel47znIFljW15g210rz4Pd+SkA7t4jiOdvsBTa2a2fF0AQAAAAAAAIA1Nd38oN/s/OBFrP1rm1r1nqmVZrlFTa3iPuJ03lCrnB907Hg/aJ+9QUioVTNCLQAAAAAAAABo0DTzg9sNzg8aY3Q4irXXfzbU2po0teoJteLMWNjUmu9Mrcn8oCXvB+2z2w91xPxgrfg0AgAAAAAAAECDpp0fvExyjZOs9tcfxZmiNNfeIHjmnw07Rah1VlOolWT55CyrVZucqTVvU6sMw3yaWpgT84P1s+PpAgAAAAAAAABrKkrzO5taO70icDqpKVy66mBUfKl+3ZlanuvoXsfTSU1naiWZsWh+sPg7j+Y8Uysz5fygJe8H7bM7CHV0kciY+dqCeBahFgAAAAAAAAA0aJxkU5ypVYRaTUwQHt4SaknSVsfXWVTX/GBu3fxgsmhTyyXUwnx2+4HS3NQ27wlCLQAAAAAAAABoVDTl/KDUbKi1f1Oo1Q1q+9I9yXIFloRAiza10pxQC4upzrE7uuBcrboQagEAAAAAAABAg8azzA82EWqVX6jf1NQadv0aQy0zaUitWnUf856plRFqYUG75Tl2nKtVHzueLgAAAAAAAACwhnJjiqbWnfODvqTmmlq+62ir61/7z7e7vk7rOlMrz60JgTplUyuZu6lV/J5nyftB++yWTa2qLYnFEWoBAAAAAAAAQEOqltBd84PDbiBHzYVau/1ArnN9OFN7U8uSM7UCr3i/888PFv9rS0iH9mF+sH52PF0AAAAAAAAAYA2NkyIZuWt+sGpSHV/WEy5ddTCKb5welB6fqWWMWfi1kixXYMn8YGfB+cGqqeW7drwftM9Wz5fnMD9YJz6NAAAAAAAAANCQcZpJ0p3zg5K03Qsaa2rdGmp1fKW50XjO8KeS5ka5kQJLmk2TM7Wy+cK66kwt5gcxL9dxdL8f6mhEU6suhFoAAAAAAAAA0JAqKOrcMT8oSTsNhlr7tza1irO2ThZ87ersKlvmB6v7mL+pVYRazA9iEbv9QIc0tWpjx9MFAAAAAAAAANZQlFRnat39VWwToVaWGx1fJnfMDxah1lm02PRhFWr5nh0h0CTUmvtMLZpaWNzuIORMrRoRagEAAAAAAABAQ2aZH9zp+Qu3pZ726DJRbnTnmVqSdDpeLNSqZv5saWoFZbg2b1Mry40cEWphMXv9QEcjmlp1sePpAgAAAAAAAABraJ75QWPmOwPqOofnxZfpt4Vaw7KptWiolZaNqMCSppbjOAo9Z6Gmli2tM7TXbj/U0UVc6+d6kxFqAQAAAAAAAEBDojLUmq6pFSjOjC6T+UKY6xyUZ/ns9YMbf2Z7Emot1hKrmlqBJU0tSQp9d3Jfs0ozI88h1MJidgeh4szofMF5TxTseboAAAAAAAAAwJoZJ8X8YGeKM7W2e0XwVOe5Wofl7Nn+veabWtWZWrbMD0rFvcw9P2hoamFxu2WgfHDOBGEd7Hm6AAAAAAAAAMCaqeYHu1POD0rNhFp7/ZtDrX7gyXOd2kItW+YHpSLUiuadH8xymlpYWPXZOziPVnwn64FQCwAAAAAAAAAaMuv8oFR/qDUIPXWDm0M1x3G01fF1tuA8mq3zg8lCTS173gvaqTrP7tFFfZ/rTcYnEgAAAAAAAAAaMsv8YFOhVvWl+m22ur5OLtezqRXP3dQy8l173gva6cF+X//ny/+TXvr4/VXfylog1AIAAAAAAACAhlRNrc5U84PF2VarCrXOosVe18oztXx38u9gVmlu5BFqYUGu4+iL/+uva+eWCVBMz56nCwAAAAAAAACsmXGaK/CcqRo/9zq+PEc6qTPUuki0P1WoFdRwplYxP2jTZF/HcyZh26yynKYWYBt7ni4AAAAAAAAAsGbGSTbV9KBUNDq2e4GOF5wBvGraptaw69cQalVNLXuCoMBzFaVmrt+lqQXYh1ALAAAAAAAAABoSpbm6U0wPVopQq56m1mWSaRRn2usHd/7sVqeOUKsIjwKLmlqhP/+ZWjS1APvY83QBAAAAAAAAgDUzTvOpm1qStFNjqHU4iiVp6jO1zqNUuZmv1SRpEh4FFjW1OguEWimhFmAdQi0AAAAAAAAAaMg4ydQN7A+1hl1fRtJ5NH9b6/H8oD1fOweeqzidN9TKCbUAy9jzdAEAAAAAAACANTPr/OBOz6891NqfItTa7hYThYtMEE7mB117vnbueMwPAuvEnqcLAAAAAAAAAKyZeeYHTy4TmQVmACsHoyIcm7apJS0Wak3mB317gqDQX6SpZeQRagFWIdQCAAAAAAAAgIZEaT7z/GBmpPMoW/i1Dy9iuU5xzbtsT0Kt+VtiaW5fUyvwnAWbWva8FwCEWgAAAAAAAADQmHGSqTPT/GARQNUxQXg4inW/H07VNqqlqVU2ogLPnnZTZ8Gmlm/RewFAqAUAAAAAAAAAjRmnubozzA9u1xxq7fXvbmlJ0lYdZ2rlRoHnyHHsCYJCz1VmHrfIZpHmRp5F7wUAoRYAAAAAAAAANGae+UGpvlBr/97d52lJ0lanaGqdRQuEWllu1fSgVIRaUnFvs6KpBdjHricMAAAAAAAAAKyR2ecHi3CpvqbWdKFW6Lvq+q5OLhebH7RpelAq3pdUhIuzymhqAdYh1AIAAAAAAACAhkQzzg/W1dTKjdHhRaK9wXShliRtdX2dRfO/bjE/aNdXzlWoRVMLWA92PWEAAAAAAAAAYE2kWa40NzPND/YDT4Hn6HiBxpQknV6mynIzY6gVLHamVpYrtCwEqu5nnqZWmuXyXbveD7DpCLUAAAAAAAAAoAHjMkiZZX7QcRzt9AKdLNjUOhjFkjRTqDXs+guGWka+bU2tyZlaZubfTXMjj1ALsIpdTxgAAAAAAAAAWBNVO2iW+UGpmCBcdH7wcBJqBVP/zvbCoVY+CZFsUd1PPOeZWr5r1/sBNh2fSAAAAAAAAABowDjNJEmdGUOt7TpCrYsi1NofdKb+nWHH1+l4gTO1MqPAtvnB8u8+mvNMLZpagF0ItQAAAAAAAACgAeOkbGoF088PStJOdzVNrUXP1IqzXIFlTa0qUEzmCLWKphahFmATu54wAAAAAAAAALAm5p8f9BcOtQ5Gsbq+q/4MgdpW19c4zeea6pOq+UG7QqAqZIvmeE8poRZgHUItAAAAAAAAAGjAvPODO72iMZXlZu7XPhzF2huEcpzpQ5mtri9JOo3ma2slmZFvW1NrzjO1jDHMDwIWsusJAwAAAAAAAABrYtLUmnV+sBfISDpbYAqwCrVmUYVa875unOUKLQu1qjO14hnnB6s8kaYWYBe7njAAAAAAAAAAsCaqM7XmaWpJWmiC8HCUaH/OUOt0PN/rpplRYN38YHE/s4ZaaZlq0dQC7EKoBQAAAAAAAAANqOYHZz9Tq4ZQ62L2ptawW7zu6QJNrcCyplYVKM46P1hNP9LUAuxi1xMGAAAAAAAAANZElMw/PyjNH2rFaa7Tcaq9QTDT721PmlrznqmVK7SsqVXNIcbZbOeTpXnx7862M8KATccnEgAAAAAAAAAaME7nmx/c7hXh0ryh1tFFLEna68/Y1OqUoVY0b6hlrGtqhXM2tSbzg45dIR2w6ex6wgAAAAAAAADAmhgnq5kfPBiVodaM84P3Or4cSafzNsQsnB+s7iea8UytyfygZc0zYNPZ9YQBAAAAAAAAgDURzdnU6gaeur6r48v5GlOHZai1f2+2UMtzHd3r+Dqbs6mV5kaBZWdQ+a4jz3WUzBhqVU0tn6YWYBVCLQAAAAAAAABowDjN1fFdOXMEIzu9QMfj+RpTVag16/ygJG11fZ3McaaWMUZxmiuYMcBbhtBzJgHjtGhqAXay7wkDAAAAAAAAAGsgSvOZpwcrO71AJ3POAB6Oit/b7Qcz/+5W19fZHKFWZiQjWdfUkqTQc2c/UysrQy0L3w+wyQi1AAAAAAAAAKAB4ySbeXqwstML5j5T6/Ai1k4vkD/H+VZbXV+nczTEqnm/0LIztaRi/jEpQ6ppVfODHqEWYBX7njAAAAAAAAAAsAbGaa5u4M31u9s9f+5Q6+A81t5g9paWJA07gU7naGpVoZaN84OB5yqa8UytyfwgoRZgFfueMAAAAAAAAACwBhadH1ykqbU/mP08LamcH4xmD7Xisgll5fygP8f8YF78PE0twC6EWgAAAAAAAADQgGJ+cL6m1k4v0HmUKZ2xYSRJh6NYewuEWifjVMbMNtdn8/xg6LmKZ/x7TGlqAVay7wkDAAAAAAAAAGsgSnN1g/mbWpJ0POMUoDGmCLX684daWW50mcwWAlVnVvmefSFQ6M3T1KpCLb5CB2zCJxIAAAAAAAAAGjBOc3UWmB+UNPME4XmUKc7MQk0tSTodz/a6scVNrY7vTJpk06pCLeYHAbvY94QBAAAAAAAAgDUwTjJ1F5gflKSTGUOtw1EsSXOHWsNu8bqnMzbEqpnEwMKmVuC5irLZ5hQz5gcBKxFqAQAAAAAAAEADapkfnDHUOpiEWsFcr7s9aWrNFmrFZWgUWNnUmn9+kKYWYBf7njAAAAAAAAAAsAYWmx8swqVZQ62qqbU/6Mz1usNOGWpFs4VaicXzg6HnTuYRp0VTC7CTfU8YAAAAAAAAAFgDi8wPbs/Z1Dq8WKypNTlTa8bXTWyeH1ygqeVb+H6ATUaoBQAAAAAAAAA1M8YsND8YeK4Goafjy9kaU4ejWIHnTBpXs9oqz9Q6m7GpZfX84BxNrTQvft5zCLUAm9j3hAEAAAAAAACAloszIyPNPT8oFedqzTM/uNcP5cwZxvQCV77r6GTGM7VSi5taob/A/KCF7wfYZIRaAAAAAAAAAFCzKM0kSd1gvvlBab5Q62AUa28Qzv2ajuNoq+vrbMZQy+amVug5s88Plu+HphZgF/ueMAAAAAAAAADQcuOkCFEWbWqdzNzUSrS/QKglFedqnY7X50yt0HOL5pwxU/9OZqqmFl+hAzbhEwkAAAAAAAAANRuXzaDuQqGWP9/84IKh1rAT6HTGplYVaoUWhkBh+e8gyaYPtaqmlu/aF9IBm8y+JwwAAAAAAAAAtFwd84PbM84Pplmu48tEe4Ng7tcsXtefI9SyeX6wuKdZztVKc0ItwEb2PWEAAAAAAAAAoOXqmh+8THKNk2yqn390mchINTS1fJ1Gs56pZfH8YPnvIJrhXK2MUAuwEqEWAAAAAAAAANQsqmV+sGhcnUzZmjoYxZKkvf7yz9Sqmk02zg92vGp+cPamlkeoBVjFvicMAAAAAAAAALTcuIb5wSrUmnaC8LAMtfbvLR5qnUfZpK00jbgM8WxsNgV+cU80tYD2I9QCAAAAAAAAgJrVNT8ozR5qLTo/uNUtXvdshgnCODMKPEeOY18I1JnrTK1cniMr3w+wyQi1AAAAAAAAAKBmtc4PTh1qFT+3W8P8oCSdTTl7KBUhUODa+XVzMAm1pm+epblhehCwkJ1PGQAAAAAAAABoscn84EKhVhEuzdLUGnb8hdph0uNQa5ZzteI0V+DZGQKF5d9HPMP8YJob+ZaGdMAm41MJAAAAAAAAADWr5gcXOVNr2A3kaIZQ6yLW3iCY+/Umr9spQ60Z5geT3EzCI9tM5gdnPFOLphZgHzufMgAAAAAAAADQYnXMD/quo62ur+PL6cKlg/NY+wuepyVJ2+WZWqdTvq4kJVmuwNIQKPDnOVPLyLf0/QCbjFALAAAAAAAAAGo2TjN5juR7i30Fu90LZmxqLR5qDbtzNLUyMzm7yjaTptasoZalc4rAJrPzKQMAAAAAAAAALRal+ULTg5WdWUKtUT2h1jxnaiVZbm2oFc7R1MpyI88h1AJsY+dTBgAAAAAAAABabJzk6tRwxtS0odZFnOkyybXXXzzUCjxXvcDV6Xj6plac5QosbTaF5X3NcqYWTS3AToRaAAAAAAAAAFCzcZotdJ5WZafn62SKUOtwFEtSLU0tSdrqBjqbIdSyeX6wampFqZn6d9KMphZgIzufMgAAAAAAAADQYlGaq1Pj/KAxtwcyB2WotV9bqOXP1NRKsnzSiLJNWIZtySzzg4amFmAjQi0AAAAAAAAAqNk4yWtqagWKM6PL5PZApu6m1rDj6zRak6aWN/uZWmmWy3ftfD/AJuNTCQAAAAAAAAA1i2qaH9zuBZJ057laj0OtYOHXlKqm1t2zh5XiTC07v26uzvqKZjhTKzNGnktTC7CNnU8ZAAAAAAAAAGixcY3zg9IUodZFLM95HIItaqvrz3SmVpoZa+cHHcdRx3dnmh9MMyOfUAuwDqEWAAAAAAAAANSszvlBabqm1u4glOvUE8RsdQOdzBBqxVku39KmllS0tWZpaqU5TS3ARvY+ZQAAAAAAAACgpaI0U2epoVaivX4952lJRVMrSvOpg6Aky61taknFuVqznKmV5TS1ABsRagEAAAAAAABAzcZprq5fx/ygL+nuUOtgFGv/Xr2hliSdTXmuVpIZa8/UkqSO7yrOzNQ/nxJqAVay9ykDAAAAAAAAAC01TnJ1g8W/fr3X8eU50skU84N1NrWGnSLUOo2mmyCMs9zqUCvwXMUzzA9mzA8CVrL3KQMAAAAAAAAALVXMDy7e1HIdR9u9QMeXN4dLWW706CLW3iBY+PUq293iWqe3vO5VaW6snh/s+LOFWjS1ADsRagEAAAAAAABAjbLcKM6MujWcqSVJ271Aj25pap2ME2VG2hvU2NTqTt/UMsYoTnP5tje1ZjhTK81zQi3AQvY+ZQAAAAAAAACgharwpI75QUna6QW3nql1OIol1RtqVWdqnU5xplZmJCPZ3dTynJlCLeYHATsRagEAAAAAAABAjcZJJqmYvKvDXaHWQRlq7TcSat3d1ErKsChw7f26OZxnftDi5hmwqfhUAgAAAAAAAECNxmV40q3hTC1J2un5OllyU+tex5ej6UKtKiwKagrxmlDMD5qpfz7LjXyHphZgG3ufMgAAAAAAAADQQlFS//zgyWWi3FwfyhyOisBrt19fqOU6joZdX2fTNLXy4r4Ci+f6OnM1tex9P8CmItQCAAAAAAAAgBqN0/rnBzMjnUfXB0yHo1j9wFM/rKcZVtnq+jqZ4kytan4wtHiuL/RcRTOcqZXmRh5NLcA69j5lAAAAAAAAAKCFotrnBwNJ0vHlzaHW3iCo5bWuGnZ8nd0QpF2VlLN+gW9vCBR67iR8m0ZGUwuwEqEWAAAAAAAAANRoXPP84PYk1Lq+NXUwirVf43lak9ftBtOdqVWGRYFr79fN4TzzgxbPKQKbyt6nDAAAAAAAAAC0UBPzg9LNoVbR1Ko/1Bp2/alCrbQKtSyfH4xnnR8k1AKsY+9TBgAAAAAAAABaqP75QV/SLaHWRTOh1taUoVZczQ9aPNcX+s7UTS1jTDE/SKgFWIdQCwAAAAAAAABqVM0PdmqaH6yaWifXhFrjJNN5lDUWap2NExljbv256qyq0PKmVmaKBtZdsvJnaGoB9rH3KQMAAAAAAAAALVTND3Zrmh/sB54Cz7m2qXV0UfzZXr+JUCtQZqRRnN36c8lkftDeEKiagkymmCCsgi/f4jPCgE3FpxIAAAAAAAAAajSZHwzqmR90HEc7veDaUOtwFEuS9u41EGp1itnDs+j2CcLH84P2ft1c3Vs0xQTh41DL3pAO2FT2PmUAAAAAAAAAoIUm84M1NbUklaHWs+HSQRlq7TfS1CpCrdNrXveqtA3zg+W/i2nO1WJ+ELCXvU8ZAAAAAAAAAGihcZor9By5Tn2hyPZdTa1BUNtrVYZVqBU9+7pXVU0t3+b5wTJwi2eaH7T3/QCbilALAAAAAAAAAGoUpZk6fj3Tg5Wd7s2hliNpp4Gm1na3CMpOx7c3tZIWNLWq875mCbVoagH2sfcpAwAAAAAAAAAtNE5ydYN6v3rd6fk6uS7Uuoh1vx800iqaNLWmDLUCm5tac8wP0tQC7EOoBQAAAAAAAAA1GqeZujWepyUVZ2qdjtNJi6hyOEq0N6i/pSVJ22WodXZHqFXNDwZWN7Wq+UFzx09emR+0OKQDNtVCT5nDw0P97u/+rh4+fKif//zn+sIXvqBXX31V3/jGN5TnReL93e9+V7//+7+vV155RX/3d39Xy00DAAAAAAAAgK2iNK9/frAXyEg6Gz/Z1joYxY2FWh3fVeA5OtnQppZX45loAOoxd6iVJIm+/vWvq9vtSpK++c1v6stf/rK+853vyBij73//+/rggw/0+uuv680339S3v/1tvfbaa4rjuLabBwAAAAAAAADbjNMm5geL862OL58MmA4bDLUcx9Gw4+ssenb28KqkbD/ZfKZWdW/RVGdqFT/jW/x+gE0196fyW9/6lv7wD/9QH/rQhyRJP/nJT/TSSy9Jkl5++WX98Ic/1I9//GN95jOfURiGGg6H+tjHPqZ33nmnnjsHAAAAAAAAAAtFSTPzg5J0fOVcLWNMEWr1mwm1JGm7G0x9ppbNZ1BVoVYyRVMrpakFWMuf55e+973vaXd3V7/zO7+jv/zLv5RUPECd8kM+GAx0dnam8/NzDYfDye8NBgOdn5/feX3Pc7Sz05/n1jaS57kL/32tyzVsuAeuwTWavoYN98A1uEbT17DhHrgG12j6GjbcA9fgGk1fw4Z74Bpco+lr2HAPXINrNH0NG+6hbddIjLTVC2/8uXnu46MfKoKlxC1+1/NcOZ1AaW700f3BXO9rmvu4fy/UZWpufS9u4CnwHN2/P5j5Hqa9j0WvsReXwVsnuPbnrv5+76xYG9vZ6s50X236b5RrtPMamDPU+pu/+Rs5jqN//Md/1E9/+lN99atf1dHR0eSfj0YjbW1t6d69exqNRk/8+dWQ6yZZZnR8fDHPrW2knZ3+wn9f63ING+6Ba3CNpq9hwz1wDa7R9DVsuAeuwTWavoYN98A1uEbT17DhHrgG12j6GjbcA9fgGk1fw4Z7aNs1RlGqD98Lb/y5ee7DS4tQ65cH5zo+Hmpnp6+f/duJJGngaq73Nc199H1XH5xHt76X84tYoefO/Xe7jH8v0WUkSXp0enntz139/eOTS0nS+DKe6b7a9N8o12jnNTbJc89dnyXN1YH9q7/6K73xxht6/fXX9alPfUrf+ta39PLLL+utt96SJP3gBz/QZz/7WX3605/Wj370I0VRpLOzMz18+FAvvPDC/O8CAAAAAAAAACwXJZk6S5gfPDgvGkVNnaklSVtdX2fj28/UitPc6ulB6cr84BRnamWmmB+0/T0Bm2iuptZ1vvrVr+prX/uaXnvtNT148ECf//zn5XmevvjFL+rVV1+VMUZf+cpX1Ol06npJAAAAAAAAALDOOM3V9b1ar9kNPHV994lQ6/BiGaFWoJM7z9QyCmsO8epWhVpRZu782TQj1AJstXCo9frrr0/+/xtvvPHMP3/llVf0yiuvLPoyAAAAAAAAANAKUZqrG9Qf8uz0Ap1cDbVGxf/fbzLU6vgaxZnS3NwY8iR5rsDyAKhqzsXp3U2tNC9CLc/y9wRsIrvjcwAAAAAAAABomXED84NSEWodXz5uTR2OYnV8V4Ow3lbYVVvdohdxfktbK06NAs/ur5qr+4unmB+sQi2aWoB97H7SAAAAAAAAAECLpFmuzKj2+UGpCrWuNrVi7fUDOU5z4cuwDLVOo5tDrTTPrQ+1PNeR5zpTNbWyvPgZ37X7PQGbiE8lAAAAAAAAANRkXIYmTTS1tnv+s6HWoFP76zzxmt1AknQ6Tm78mTjLFXj2t5o6njtTU4v5QcA+hFoAAAAAAAAAUJNxkklSY2dqXQ21Dkax9gZB7a9z1aSpdcv8YJIZhZY3tSQp8KZrajE/CNjL/icNAAAAAAAAALRE1dRqan5wFGdKyrZR0dQKa3+dq7amCrVa0tTyaWoBbUeoBQAAAAAAAAA1aXJ+cKdXtLJOLhPFaa6TcWpFqBVnxvoztSQp9F3FmbnzvAAr4QAAIABJREFU5zKaWoC1/FXfAAAAAAAAAACsi6hqajU0PyhJx5epBqNYkpoPtTpVqHXzmVpFU8v+UCvw3NnmB1vQPgM2DaEWAAAAAAAAANRkcqZWQ/ODknR8mahzHkmS9hsOtXzPVT/wdBbdPj8YtiAA6njTzQ9WTS3Psf89AZuGUAsAAAAAAAAAarKM+cHjy0TOWRFqNd3UkooJwpNbz9Qy8lvQ1Ap9mlpA2xFqAQAAAAAAAEBNmp0fLL7OPb5MlJUh0l4/qP11njbs+jq7NdRqR1Mr9Jypmlpp+TM0tQD7EGoBAAAAAAAAQE2q+cFOA/OD21eaWuOiTKTdfvNNre2uf8eZWqYVZ2qFvqvRxc3vo5KZqqll/3sCNg2fSgAAAAAAAACoSTU/2G1gfjDwXA1CT8eXiQ7OY213fYUNvM7Tht1Ap7c0teIsb0eo5blKMnPnz6VZdaZW03cEYFY0tQAAAAAAAACgJk3OD0rFuVrHl4lMlC3lPC2pOFPrtlCrPfOD7lTzg5kx8lxHDvODgHUItQAAAAAAAACgJk3OD0pFqHVymSrKzfJCrY6vs+j6UMsYoyQzrZjqC313EjreJs2MfJdAC7CR/U8aAAAAAAAAAGiJKM3lSI01l6qm1gfn0VKbWlGaTwK7q9LcyKi591unYn5wilArJ9QCbEWoBQAAAAAAAAA1GSe5Or7b2HTdTs/Xo8tEB+eR9vrLC7UkXdvWqkKiwLX/q+Zpm1oZoRZgLfufNAAAAAAAAADQEuM0UzdoZnpQkrZ7gQ7OI42TXHuDoLHXuWqrW7zOyTXnasVlSBT49n/VPO2ZWmlenKkFwD72P2kAAAAAAAAAoCWiNFe3wYBnpxcoM8X/X9b84LBqal0TaiXlzbRjftBRkhkZY279OZpagL0ItQAAAAAAAACgJtX8YFN2eo/bWftLCrW2y1Dr9LqmVsvmByUpzm4PtdI8J9QCLGX/kwYAAAAAAAAAWiJqeH7waqi17KbW6Th55p89nh+0PwSqwsb4jnO1mB8E7EWoBQAAAAAAAAA1GS9hfrCyrFBruzxT6yy6bn6wPU2twKuaWreHWsX8oP3vB9hEfDIBAAAAAAAAoCbLmh8MPEdbZYOqaf3Qk+tIJ9fND1ZNLc/+r5o7U4ZaaW7kt+CMMGAT2f+kAQAAAAAAAICWaH5+sAiy9gYduc5yghfXcTTs+Dq7JtSaNLVaEAKFs8wPLunvFsBsCLUAAAAAAAAAoCbjtNmm1rAbyJH0oWGnsde4zlbXv/5MrTLUClvQ1ArL4I2mFtBe9j9pAAAAAAAAAKAlxknW6JlavlvMDu7fW855WpVhN9DpdfODmZFEUwvAcixndBUAAAAAAAAANkCU5o3OD0rSf3xhX5/5+G6jr/G0oqnV7jO1wsmZWubWn8toagHWItQCAAAAAAAAgJo0PT8oSX/2v72gnZ2+jo8vGn2dq7Y6vn51Mn7mz6tQqx3zg1M2tTKjfmj/+wE2EZ9MAAAAAAAAAKiBMaZoajUcaq3CVtfXyeWzZ2ol5flUbWg2VfOD0R1namXGyHPtfz/AJlq/pysAAAAAAAAArEBUNoCabmqtwlbX11mUKjdPTvfFWfuaWskdoVaa5fJd+98PsIn4ZAIAAAAAAABADcZlqNX0mVqrsNUNlBvpIs6e+PMqIAra1NS6a34wp6kF2IpQCwAAAAAAAABqUIUl6zg/OOz6kqTTcfrEn1fnUwWtaGoVQdVdZ2pluZFPqAVYyf4nDQAAAAAAAAC0wDgpWkydYP2+dt2ehFpPnquVZMUcYSvmB8uwMc7MrT+XEmoB1rL/SQMAAAAAAAAALTCZH/TXb37w7qaW/SFQFbzFd5yplTE/CFiLUAsAAAAAAAAAajCZH1zDptZWN5B0TahVBkRtaDZ1qqbWFGdqteH9AJto/Z6uAAAAAAAAALACk/nBNTxTa6tTNrWiJ0OtJMsVeI4cx/4QqAqq7mpqpTS1AGut39MVAAAAAAAAAFYgWuP5wa1qfvDyyTO14jRvxXlakuQ4jjq+e2dTK6OpBVirHU8bAAAAAAAAALBcdabWOja1uoGn0HN09kxTq10BUOi5UzS1cvnu+v07BNYBn0wAAAAAAAAAqEE1P7iOZ2pJxblaJ9ecqRW2KMQLPOfOUCtjfhCwVnueNgAAAAAAAABgsXWeH5SkYdfX2VOhVpLmCloyPyhpqvnBNDfyPUItwEbtedoAAAAAAAAAgMXWeX5Qkra7vk7HT52pleUKWtRqCj1XUWpu/Oe5McqN5DvteU/AJlnPpysAAAAAAAAALFmUlvODaxpqDTu+Tp9uarVsfjD0XSW3zA9meRF40dQC7NSepw0AAAAAAAAAWGyc5PJdR36L5vhmsdULngm14rR4z20Req6iW0KttAq1WvSegE2ynk9XAAAAAAAAAFiycZqv7fSgJG11fJ1FT4VaWa6wRSHetE0tj1ALsFJ7njYAAAAAAAAAYLEozdQNvFXfRmO2ur5Gcab0SiiUZEZBi6b6Qs9RnN7S1MpoagE2I9QCAAAAAAAAgBqMkzVvanV9SXqirRWnuYI2NbU8V9FtoVZe/DOaWoCd2vO0AQAAAAAAAACLjdNc3bUOtQJJeuJcrXbOD5ob/zlnagF2a8/TBgAAAAAAAAAstu7zg8OyqfVEqJXmLZsfdBXdcqbW41CLr84BG/HJBAAAAAAAAIAarPv84HYVal2ZH0yyls0P+u6tZ2plZajF/CBgp/Y8bQAAAAAAAADAYtGazw8OO1VTK5n8WZy1r6mVTNXUas97AjbJ+j5hAQAAAAAAAGCJxmm21k2trbKpdfbM/GB73nPouYpuaWqlNLUAq7XnaQMAAAAAAAAAFhsn+ZqfqRVIkk7GV+cHTatCrY7vKL6lqZXR1AKs1p6nDQAAAAAAAABYbN3nB33X0SD0nmxqZbnCFs0PBp6r3DxuZD1tMj/YovcEbJL1fcICAAAAAAAAwBKt+/ygVEwQVmdqGWOUZO2aH6z+/cQ3TBBWTS3PIdQCbNSepw0AAAAAAAAAWCxK13t+UJKGHV+nZVMry42MkYIWtZpC7/ZQK82LP6epBdiJUAsAAAAAAABAY949GOmr3/u/ld5yjtE6SHOjJDNrPT8oSVu9YBJqJWWrKWxRUyuomlo3/PeY0tQCrNaepw0AAAAAAACA1vkv7/y7vvfPv9S/fDBa9a00KkozSVr/+cGOr9OoCLWqtpPfolCr490eamWTM7Xa856ATcInEwAAAAAAAEBjHh5cSJLefu9sxXfSrKgMeNZ9frA4U6tsapXBUNiiqb6wDB2jm+YHszLUctvznoBNQqgFAAAAAAAAoDHvHhQNrXUPtcZJEZKsfVOr6+tsnMgYM5kfDNz2vOcqgEtuamqZcn6QUAuwUnueNgAAAAAAAABa5SLO9KuTsaQNCLXK+cG1P1OrGyjOjKI0n8wPBn57AiCaWkC7rfcTFgAAAAAAAMDK/OywaGl96vmh/sfRhS7ibMV31JxNmR8cdn1J0uk4nTS1whadPxXecaZWmhNqATZrz9MGAAAAAAAAQKs8LKcH/+C3PqrcSO/8+/q2tTZlfnD7aqhVBkN+q+YHq1DLXPvPM0ItwGrtedoAAAAAAAAAaJV3Dy7UC1z97//heUnS2++dr/iOmhNtyPzgsFOGWlGipAyGwhbOD8Y3zQ/mVVDXnvcEbJL1fsICAAAAAAAAWJl3D0Z6sDfQc8OOnh921vpcraqp1fXXe35wuxtIkk4vHze1ghY2tZIb5weL//UItQArtedpAwAAAAAAAKBVfnYw0if2+5KKc7V++v4ah1plGtIJ1vsr18mZWlE6OZcq8NoTAFWtsujOptZ6/3sE2opPJgAAAAAAAIDaHV3EOrpI9In9gSTpxQ/f0y+Oxzq5TFZ8Z83YlPnBrSfO1CrmBwOvPe+5MzlT6/pQqzpTi6YWYKf2PG0AAAAAAAAAtMbDg5EkPQ61nh9K0tq2tTZlfnAQevIc6WycTCb8whaFWsEk1DLX/vO0DLU4UwuwU3ueNgAAAAAAAABa492DC0nSJ8tQ61MfLkKtt987X9k9Namas+uu+fyg4zgadgOdPNHUak8A1CmbdPGN84NlqNWi9wRskvV+wgIAAAAAAABYiYcHI+30Au32A0nFWUwfu9/T2++taVOrnB8M13x+UComCM/GV8/Uas97njS1bgi1stzIkeQ6hFqAjdrztAEAAAAAAADQGg8PRvrkfl/OlXDgxeeHenuN5wc7vrsRYchW19fpOFU6mR9sz3v2XEee69x4plaaG1pagMUItQAAAAAAAADUKjdGDw9Gk/O0Ki8+P9QH57E+OI9WdGfNidJc3Q1oaUnSsOPrNEon51L5LWpqSVLHc28OtTIjbwOCSaCt2vW0AQAAAAAAAGC9fzsd6zLJnw21PnxPktZygnCcZpPzmtZd0dRKlEyaWu1636HvTs5Ae1pmaGoBNmvX0wYAAAAAAACA9d794EKS9MmnQq3/+UP35DlrGmolubqBt+rbWIqtbqCzcaqkbGoFLQuBQs+ZBHJPS7NcvsvX5oCt+HQCAAAAAAAAqNXPDkeSpAf7/Sf+vBt4erA/0Nvvn6/ithoVpflGNbXOolRRGQz5bstCrTuaWl7L3g+wSTbjKQsAAAAAAABgad79YKRf2+poEPrP/LMXPzzUT987kzFmBXfWnHGabcyZWltdX7mRji8Shb4rp2VnUIWeOzkP7GlpZloX0gGbZDOesgAAAAAAAACW5t2DkR48NT1YefH5ezoZp/rlyXjJd9WsKM3V2Zj5wSKsPBzFrZselIpQ68b5wZymFmAzQi0AAAAAAAAAtUmyXD9/dPnMeVqVF58fSlq/c7XGSb4xTa1hJ5AkHV7ECr32vedb5wdzmlqAzdr3xAEAAAAAAABgrZ8fXSrLzY2h1if3Bwo9R2+/t17nam3a/KBUNLXaGmrFN4RaKaEWYLX2PXEAAAAAAAAAWOvhwUiS9IkbQi3fc/XCh+7p7ffXq6m1sfODLQzyQs9RfMP8YMb8IGC19j1xAAAAAAAAAFjr3YORPNfRb+z2bvyZFz881DvvnynLzRLvrFmbND9YhVpxZtrZ1PLcG0MtmlqA3dr3xAEAAAAAAABgrYcHI/3G/Z6CW8KOF58f6jLJ9T+OLpZ4Z82K0lydDQm1hh1/8v9bG2rdOD+YE2oBFmvfEwcAAAAAAACAtR4ejG48T6vy4vNDSdLb763HBKExpjhTa0PmB7uBNwnwwhYGeaHvKs6ubwlmNLUAq7XviQMAAAAAAADASqM41a9OoxvP06r8xm5Pg9Bbm1AryYxyo42ZH5QeTxAGXvsCoI5/W1PLyGth+wzYFHw6AQAAAAAAANTiZwfFnOBdoZbrOPpfPnxPP33/fBm31bioDEg2ZX5QejxB2MamVnDLmVpZbuQ77QvqgE3RvicOAAAAAAAAACu9ezCSJH3yuf6dP/upDw/13z84V3JDuNAm4zSTtFlNre1JU6t97zm8JdRKcyO/he0zYFO074kDAAAAAAAAwEoPD0bqBa4+stW982dffH6oJDOTIKzNxkkRkGzKmVqSNOwGkoqAqG06vlNORj57rlaaG3k0tQBrte+JAwAAAAAAAMBKDw9G+sT+QO4UocCLz9+TpLU4V6uaH9ykptZWi5ta1T0n2fWhFk0twF7te+IAAAAAAAAAsNLDgwt9Yu/287Qqv7bV1XbXX4tQq5of7Pib09SqQq02nqlVnX0Wp89OEGa5ke8SagG2at8TBwAAAAAAAIB1DkexHl0m+sRz04VajuPoxeeHevu984bvrHmTplawOV+3tjnUqiYTo2vO1UpzI49QC7BW+544AAAAAAAAAKxTnY31ib3+1L/z4vND/exwpMska+q2lqI6U6vTwoBnXsNOcaZW0MKpvnAyP3hNqJXlNLUAi23OUxYAAAAAAABAYx6WodYnp2xqSUWolRvpX95vvq11cB7p//nlSSPXruYHuxs0P7hdNbVaeKZW1S6LrpkfpKkF2K19TxwAAAAAAAAA1nl4MNJuP9BuP5z6d158fihJevv95s/V+s//9V/1f7zxo0auvYnzg8My1ApaHGrdfKZW+94TsCn8Vd8AAAAAAOD/Z+/Ow+M6y/v/f84sZ6SZ0WbNSLIteZXlNY5tKQtb1oaEhLITSMJW6JeyN7SF0iaFlkL7AwotlK20BcoaaEKBQsKWQBNISOIlcRI5ki0vkmxLmpGtZUaa/fz+GI0sR16k0Yw0R36/rosrzsyZZx57PE8uzkf3fQMAYH9d4TGtCcy8SkuSAj5TdX5T7X3FDbVOjCX0yKETSlvZIKPQc6BiE+0TL6T2g1W2nqmVrcQ6Y/vBjEX7QaCE2e/EAQAAAAAAAFBSMpalg4NRNc8y1JKy1Vr7itx+8BfPhpS2sr8ORxMFXz+Wq9S6gNoPVpTlZmrZ7xZzrmVi/AyhVpr2g0BJs9+JAwAAAAAAAKCkHBuOaTyZ0dpa76xfu6mhQt0nxzUaSxVhZ1n3tvdPBhXFCLUuxPaDuUotO1anec7RfpBKLaC02e/EAQAAAAAAAFBSusJRSVJzMI9KrfriztU6PDimff0R3bAhKEkKR+IFf49YMi2HoQsqDKkqd+uO69bppVuXLvRWZi1XXZbIle9NsCxLKSq1gJJGqAUAAAAAAABgTg5MhFqr86jU2tjgl6SizdW6d1+/HIZ0W1ujJCkUKU77wTKXU4ZxYYUhr9i6VA2VZQu9jVkzz1KplZnIuC6kcBKwG0ItAAAAAAAAAHPSFR7Tsqoy+UzXrF9bWeZWU3VZUUKtjGXpvvYBXbayRmsDPrkcRtHaD9qxDd+Fypys1Do91EpNpFqEWkDp4qQFAAAAAAAAMCcHwlE1B2bfejBnU0NFUUKtPb3D6huN68ZN9XIYhgJ+j0JFCLViyfQFNU/L7kxnNrR6bqVWeiLUov0gULo4aQEAAAAAAADkLZHKqPvkuNYGZt96MGdTQ4UGIomCV1Hd294vr9upq5prJUl1lZ6izNSKT7QfhD3kquqmV2pl/93l5LY5UKr4dgIAAAAAAADI25GTY0pnrLlVatVXSCrsXK1YMq37O8O6uiWgMnc2cKrze4rSfjBG+0FbcU+EVvGzVWpdYLPRADvhpAUAAAAAAACQtwPhqCRpzRxCrfX1fjkMaV8BQ60HuwYVTaR106a6yceylVrFCbVoP2gfuQAymbZOe3xyppaTUAsoVZy0AAAAAAAAAPLWFR6Ty2FoZU153muUu51aU+tTe3/hQq379g2ozm+qtal68rG6ijINx1LTKnTmKp5MU6llIy6HIUNSfFr7QWvyeQCliZMWAAAAAAAAQN66wlGtXFI+2dItXxvr/Wrvi8iyrPNffB4nxhJ65NAJ3bCxXo4preTqKjySpMECtyCMMVPLVgzDkOlyKHmW9oOEWkDpItQCAAAAAAAAkLeucHRO87RyNjVUaGg8qeMj8Tmv9YtnQ0pb0o1TWg9Kp0KtUGTu7zFVnPaDtmM6HUo8t1IrTagFlDpOWgAAAAAAAAB5icRTOj4S19oChVqS1F6AuVr3tvdrfZ1/2r5yoVa40JVatB+0HdPlmNaGMjVRJegk1AJKFictAAAAAAAAgLwcHByTpIKEWuuCPrmdxpxDrUODY9rXH5lWpSVNCbUihQ214rQftB3TaSj5nEqtNJVaQMkj1AIAAAAAAACQlwPhqCQVpP2g2+nQuqBf7f1zC7Xube+Xw5BevGF6qFXjNeV0GAoVY6YW7QdtxXQ6FE+dPr8tlcmGXC4HnyVQqvh2AgAAAAAAAMhLVygqr9uphkpPQdbbVO/Xs/0RZSzr/BefQcay9LN9A7p8VY0CPnPa8w6HoYDPVLiAM7UylqV4KkP7QZsxXWeYqZXJtR9ciB0BmAm+ngAAAAAAAADy0jUY1dqAVw6jMO3aNjVUKJpI68iJ8bxev6d3WH2jcd24sf6s1wR8pkIFbD+YmJjLRPtBezGdZw+1qNQCShffTgAAAAAAAACzZlmWDoSiWlOA1oM5mxoqJCnvuVr3tvfLZzp1ZXPtWa8J+k2FC9h+MJbMBiNUatmL6XJMBpI56clKLWZqAaWKkxYAAAAAAADArA2OJTUcSxVknlbOqiVelbsd2pfHXK1YMq37O8O6el1AZe6zV00FfAUOtVJpSWKmls14zlmpRagFlCpOWgAAAAAAAACz1hWKSlJBQy2nw9CGOn9elVoPdg0qmkjrxk1157wu6PdoJJZSLJnOd5unidF+0JbcTmNapdZkqOUk1AJKFaEWAAAAAAAAgFk7EM6GWmsD3oKuu7GhQp2hqFLPqaI5n/v2DajOb6q1qfqc1wV8piRpcKww1Vpx2g/aksc1vVJrsv1ggWbEASg8TloAAAAAAAAAs9YVjmqJ160ar1nQdTc3VCieyqgrPDbj1wxGE3rk0AndsLFejvMEEgF/dr/hSGFCLdoP2pPbOX2mFpVaQOnjpAUAAAAAAAAwawfCUa0tYOvBnE0NFZKkZ2YxV+sXHSGlLZ239aAkBSdCrVDBQq1cpRbtB+3EdDmUSFunPUalFlD6CLUAAAAAAAAAzErGsnRwcKyg87RylleVqarMNau5Wve192tDnX9GIVuu/WA4WqBQa6L9IJVa9uJxTm8/mMpk/51KLaB0cdICAAAAAAAAmJWjQzHFU5mCz9OSJMMwtLG+Ysah1qHBMe3rj+glM6jSkqSqcrdcDqNglVrxXPtBKrVsxe10KP7c9oMTlVsuB7fNgVLFtxMAAAAAAADArHSFo5JUlEotSdrU4NfBcFSxZPq8197b3i+nIV2/YWahlsMwFPCZCkfjc92mpKntB7nVaicel6FkOiPLOtWCMD3xa6eDSi2gVHHSAgAAAAAAAJiVAxOh1pqihVoVSltSx0DknNdlLEs/2zegy1bVqHaireBMBPymwoWaqUX7QVsyXQ5lrFNztKSplVqEWkCp4qQFAAAAAAAAMCtd4aiWV5Wp3F2clnubGiokSfv6zx1q7ekdVt9oXDdurJ/V+gGfqVCBZmrRftCeTGf21nh8ylytXKUWoRZQugi1AAAAAAAAAMxKV3isaK0HJSno9yjoN887V+unz/TLZzp1ZXPtrNcvWKUW7QdtKRdqJVNUagF2wkkLAAAAAAAAYMYSqYy6T45pbcBb1PfZWF9xzlArlkzrgf1hXbMuoLJZVowFfKZG46kZzew6n3gqI7fTYA6TzZiu6ZVaqQyhFlDqCLUAAAAAAAAAzNjhE2NKW9LaIlZqSdKmBr+OnBxXJJ464/MPdg0qmkjrxk2zaz0oZWdqSVK4AC0IY8k0VVo2NFmpNbX94ESoRUAJlC5OWwAAAAAAAAAzdiAclTQfoVZurtaZq7XubR9QfYVHO5qqZr12MBdqFaAFYSyVYZ6WDU1WaqWmVmpl5DQkwyDUAkoVoRYAAAAAAACAGesKR+VyGFpZU17U99lYnw212vsi054bjCb0+8MndMPGOjnyCCACvsJVasVTGZW5uc1qN7lKrcRp7Qep0gJKHactAAAAAAAAgBnrCo9pda1XLmdxby1Wl7u1vKrsjHO1ftERUtqSbtxUl9faQZ9HkhSi/eAFy3Rlw6vEcyq1XA4+S6CU8Q0FAAAAAAAAMGMHwlGtqfXOy3ttaqg4Y6h1X3u/NtT5taY2vxaIVeUuuRyGwpH4XLeYrdSi/aDtnKlSK52x5HJSqQWUMkItAAAAAAAAADMSiafUPxpXc5HnaeVsaqhQ32hcJ8ZOVVQdHIxqX39EN26uz3tdwzAU9JsFaT8YS2Wo1LKh3GeWSFmTj6UylpzM0wJKGqctAAAAAAAAgBnpCkclSWvnLdTyS5L2TZmrdW/7gJyGdP2G4JzWDvhMhSKFaT/ITC37cZ9xphaVWkCp47QFAAAAAAAAMCO5UKs5OD+h1oa6ChnSZAvCjGXpZ/sGdPmqJVriNee0dsDvUbgAoRbtB+3Jkwu1Uqe3H6RSCyhtrnxelEwm9dd//dc6evSoEomE3vnOd6q5uVkf+tCHZBiG1q1bp4985CNyOBz6/ve/r7vuuksul0vvfOc7dfXVVxf69wAAAAAAAABgHhwIj8lnOtVQ4ZmX9/OaTq2q9aq9Pxtq7e4ZVv9oXO+7YvWc1w76TO3sHprzOrQftCe3KxtexanUAmwlr1Drxz/+saqrq/WpT31KJ0+e1Ctf+Upt2LBBt99+uy677DJ9+MMf1v33369t27bpm9/8pu655x7F43HdeuutesELXiDTnNtPUQAAAAAAAACYfwfCUa2p9cmYx2qWTQ0VeuTQCVmWpXvb++Uznbpibe2c1w34TY3GUxPtA/OvtKL9oD3lKrWSU0OttCWXg1ALKGV5nbY33HCD/vRP/3Ty351Op5555hldeumlkqQrrrhCDz/8sPbu3avt27fLNE1VVFRoxYoVevbZZwuzcwAAAAAAAADzxrIsHQxH1Rz0zuv7bqqv0ImxpA6Fo3pgf1jXrAvMKYTKCfiyP3gfjs6tBSHtB+3JnKiui09tP2hZchJqASUtr0otny/bMzcSieh973ufbr/9dn3iE5+Y/AkNn8+n0dFRRSIRVVRUnPa6SCRyxjWncjoNVVfP738c7czpdMz5z2uxrFEKe2AN1ij2GqWwB9ZgjWKvUQp7YA3WKPYapbAH1mCNYq9RCntgDdYo9hqlsAfWYI1ir5F7ff9ITMOxlLY01cx6vbns4bJ1AemBA/rsAwcUTaR186Ur8l5r6j5WNVRKksY1u3uRz/29xFMZVfk9c1ojH6wxtzU8iXT2dW6Xqqu9cjodMhyGPBP/Ph97YA3WwOzlFWpJ0vHjx/Xud79bt956q/7wD/9Qn/rUpyafi0ajqqyslN/vVzQaPe3xqSHX2aTTloaGxvLd2gWnuto75z+vxbJGKeyBNVij2GuUwh5YgzWKvUYp7IE1WKPYa5TCHliDNYq9RinLHRfKAAAgAElEQVTsgTVYo9hrlMIeWIM1ir1G7vV7Dp+QJC33uWe93lz2sLTMJZfD0L1P96m+wqOWmrK815q6j3LLkiQd7h/VuuqyvNZIpTNKZSwpnZ7Vnkrhc73Q10hnsp//SCSuoaExVVd7FUukJCv/e9N2/bNgDfuscSEJBs+cJeXVfjAcDuutb32rPvCBD+g1r3mNJGnTpk169NFHJUkPPvig2tratHXrVu3atUvxeFyjo6Pq6upSS0tLnr8FAAAAAAAAAAvlQDh7M3ZtrW9e39d0ObQumH3Pl2ysk6NA87wC/mz7wVAknvcasYnWdR7aD9qO02HI5TAUZ6YWYCt5VWp9+ctf1sjIiL74xS/qi1/8oiTpjjvu0Mc+9jF95jOf0Zo1a3T99dfL6XTqjW98o2699VZZlqX3v//98ng8Bf0NAAAAAAAAAJiufzSuD/64Xe+5ulmXLDt/96Tz6QpHVeszVe11F2B3s7OpoUL7+iO6cVN9wdasKnPJ7TQUjuQ/UysXapW58qodwAIznQ4lpszUSmUItYBSl1eodeedd+rOO++c9vi3vvWtaY/dfPPNuvnmm/N5GwAAAAAAAAB5euzISbX3jeo9d+3RX/7BOr1q69I5rdcVjmpt7cLMg7m1tVHbVy3R6gK+v2EYCvhMhaP5h1rxVHYuU5mbUMuOTJdDiSmVWumMJZOAEihpfEMBAAAAAACARagzFFWZy6EXrQvqH3+5X//+yBFZE3OkZiudsXRwcEzNwfltPZizoqZcr2trKvi6AZ9HoTmEWrEk7QftzHQaVGoBNkOoBQAAAAAAACxCHQMRrQv69KVbt+umzfX6ysNH9In7DyidmX2wdXQ4pngqo7WBhQm1iiXoNxWew0ytOO0Hbe1MlVpOQi2gpHHaAgAAAAAAAIuMZVnqHIiopc4vt9Ohj1zfojdf2qR7njyuD/1v+2QYM1MHwlFJWnSh1lzbD8ZoP2hrptOhRPpUyEulFlD6OG0BAAAAAACARebocEzRRFotdX5J2flR73nRav351Wv1fwcG9d6792o0lprxel3hqAxJaxZoplaxBPymIvG0xpPpvF5P+0F787gcz2k/mJHLwS1zoJTxDQUAAAAAAAAWmc5QtrJq/USolfP6Hcv1sZs26Knjo3r7957UwOjMWu91haNaXl2mcvfiCm+CflOSFI7kV61F+0F7czvP1H5wATcE4Lz4igIAAAAAAACLTOdARA5DWnuGyqoXb6jTZ1+1RcdHYnrbd5/Q4cGx8653IBRV8yJrPShl2w9KyrsFYa79oIdQy5bMaZVallykWkBJ4xsKAAAAAAAALDIdAxGtXOJV2Vkqqy5dWaN/u/liJdIZ/fFdT+ipYyNnXSueTKtnaFxrFmOo5fdIkkKRmVWsPVeu/eDZ/pxR2jxnqNRyGczUAkoZoRYAAAAAAACwyHQORKa1Hnyu9fV+/ect21RR5tI7/3uvfntw8IzXHQhFlbG0KCu1gnOs1KL9oL25ncZpoVa2UotQCyhlnLYAAAAAAADAIjI0ltRAJKGW4PlDqMbqcv3nLdu0ptarv/jhM/rx033Trtk/MCpJWhuY3srQ7irLXDKdRt4ztWJJ2g/amedM7QcdhFpAKeO0BQAAAAAAABaRjlBEktRynkqtnCVeU1+6eavaVlTr73/eqa892i3Lsk6t1x+R22loRXV5Ufa7kAzDUMBnKjTHSi1CLXtyOx2Tn6GUbT/oJNQCShqnLQAAAAAAALCIdA5kQ631wZmFWpLkM13651du0fUbgvribw/r07/uUmYi2NrfP6pVS7xyORfnrcSA36NwvjO1Uhl5XA4ZzGGyJY/LoWT6VIBLpRZQ+lwLvQEAAAAAAAAAhdMxEFGd31S11z2r17mdDn30xg2q9Zn6zq6jGowm9XcvWa+O/oi2La8s0m4XXtBvqisczeu1sWSaeVo2Zjod02ZqUakFlDZCLQAAAAAAAGAR6QxFtX6GrQefy2EYev9VaxXwmfrcg4c0GI2rbySm5ouXFniXpSPgM/X7wyfzem08lVGZ21ngHWG+TG0/aFmW0lRqASWPHyMAAAAAAAAAFolYMq0jJ8ZmPE/rbN54SZP+7iXrtff4qCRpbcBbiO2VpIDPVDSR1ngyPevX5toPwp48LkOpjKWMZSmVybYhdDn4PIFSRqUWAAAAAAAAsEh0haPKWJpzqCVJN26qV43Xrf9tH9C25VUF2F1pCvo9kqRwJKGmmvJZvTaeytB+0MbMiTlxiVRG6YlQi/aDQGkj1AIAAAAAAAAWiY5QdjbU+jpfQdZ73qolesm2Rg0NjRVkvVIU8JmSpFA0PutQK5ZM037QxsyJQDKRziiZzlVqEWoBpYwfIwAAAAAAAAAWic6BiPwep5ZVli30Vmwj4M+GWuFIYtavpf2gvU1WaqUtpTPZ2VpUagGljRMXAAAAAAAAWCQ6ByJqCfplGNyYn6ngRKgVyiPUov2gvU1WaqUyU2Zq8d0BShknLgAAAAAAALAIpDOW9oeiBZmndSGp8LhkOg2Fo3lUaiXT8rhoP2hXU2dq0X4QsAdCLQAAAAAAAGAR6Dk5rlgqo5ZgYeZpXSgMw1DA71EoEp/1a2OpjMrc3GK1q6kztWg/CNgDJy4AAAAAAACwCHSGIpKk9VRqzVrQZ+ZVqUX7QXvzOE+FWpPtB52EWkAp48QFAAAAAAAAFoGOgahcDkOra70LvRXbCfhNhfOYqUX7QXtzTwRY8VRGqYn2g07m0QEljVALAAAAAAAAWAQ6ByJaU+uV28ktv9kK5FGpZVlWtlKL9oO25ZmoskueVqnF5wmUMr6hAAAAAAAAgM1ZlqWOgQitB/MU9HsUTaQ1lkjP+DWJtCVLp4IR2E9uplY8ZSmVzs7UcjFTCyhpnLgAAAAAAACAzYWjCZ0cT6qFUCsvAZ8pSbOq1oolswFYmZv2g3aVq2qcWqnlJNQCShqhFgAAAAAAAGBznQNRSaJSK08BfzbUCkXiM35NPJWt7CmjUsu2PBOhVmJq+0FCLaCkceICAAAAAAAANtcZikiS1gV9C7wTewpOhFrhyCwqtSZCLdoP2pfbmQ2w4qmM0hnaDwJ2wIkLAAAAAAAA2FzHQETLq8rk97gWeiu2FPR5JM2u/WA8RftBu8sFksl0Rsk0lVqAHRBqAQAAAAAAADbXORCh9eAc+D1OeVwOhWZTqZWk/aDdmROfXTxF+0HALjhxAQAAAAAAABuLxFPqGYqppY7Wg/kyDEMBn6lwdOYztWITlVq0H7Qvc8pMrfREpZaTUAsoaZy4AAAAAAAAgI0dCEUlSS1BKrXmIug3Z9l+cKJSi/aDtuVyGDIkJdKWkpMztbhlDpQyvqEAAAAAAACAjXWGIpJE+8E5CvjMvNoPUqllX4ZhyHQ5lEhllM5QqQXYAScuAAAAAAAAYGMdAxFVl7sV9JsLvRVbC/g9Cs8m1JpoP8hMLXszndlQK5VmphZgB5y4AAAAAAAAgI11DkS1vs4nw+Bm/FwEfabGkmlFE6kZXU/7wcXBdDmUSGdOtR908j0CShmhFgAAAAAAAGBTqXRGXYNR5mkVQGCi0m2m1Vq59oNUatmbx2kokZ7SfpBwGChpnLgAAAAAAACATR06MaZk2lIL87TmLOCbCLWiMwu1Jiu1CLVszf3c9oNUagEljRMXAAAAAAAAsKnOgagkaT2h1pwF/R5Js6jUSqXlNCSXk1usdpZtP2gpNdF+kEotoLRx4gIAAAAAAAA21TEQkcfl0Iqa8oXeiu3lKrVCM6zUiiUzzNNaBDyuiUqtDJVagB0QagEAAAAAAAA21RmKqDngk9PBjfi58nuc8rgcCkXiM7o+nsrIQ+tB23M7HYqnp7QfdPCZAqWMbygAAAAAAABgQ5ZlqXMgSuvBAjEMQ0G/qcGZVmql0szTWgQ8ToeS6VOVWgTEQGnj1AUAAAAAAABs6PhIXKPxlFrqfAu9lUUj4DMVmuFMrXgqIw/tB23PdDkUT2WUSudmai3whgCcE6EWAAAAAAAAYEOdAxFJolKrgAI+j8KzmalFpZbtmU5DiVRG6Ywlp8OQYZBqAaWMUxcAAAAAAACwoY6BiByG1BygUqtQgn5zxjO1aD+4OJiubPvBZMaSi9aDQMnj1AUAAAAAAABsqDMU1YqacpXRAq9gAj5T48mMoonUea+l/eDi4HY6FE9bSqUzhFqADRBqAQAAAAAAADbUORCh9WCBBfymJM1orhbtBxcHjzNbqZWmUguwBU5dAAAAAAAAwGaGxpPqG42rJUioVUjBiVArPJNQK5WWh1DL9kyXQ/FUtv2gk1ALKHmcugAAAAAAAIDN7A9FJEktdczTKqSgzyNJCkfPH2rFUxlaPy4CptNQIpWh/SBgE4RaAAAAAAAAgM10DEQlSS20HyyoU+0H4+e9lvaDi4PpcshS9vMk1AJKH6cuAAAAAAAAYDOdAxEF/aaWeM2F3sqi4jOdKnM5ZliplZbHRaWW3ZnO7C3yaCIll5Pb5UCp41sKAAAAAAAA2ExnKKL1VGkVnGEYCvrN887USmcsJdIWlVqLQC7UGkuk5TSo1AJKHacuAAAAAAAAUECJVEZvv+sJ/bpjoCjrx5JpHR4cU0uQeVrFEPCZCp2nUiueykiSytzcXrU705ULtVJyOQm1gFLHqQsAAAAAAIBF4+FDJ9TRN7qge3imb1R7jo7oM7/cL8uyCr7+wcExpS3maRVLwO9R+DwzteKptCTRfnAR8EyEWtE4lVqAHRBqAQAAAAAAYFFIpTP665/s0//382cXdB+7eoYkSc/2j+qxI0MFX79zICJJtB8skqDfVDiaOGcgGctVatF+0PbcU9oPUqkFlD5OXQAAAAAAACwK+/ojiibS2nVkSMl0ZsH2sbt3WKtrvQr6PfrWrt6Cr98xEJHPdGpZVVnB10a2/eB4MqNoIn3Wa+JJ2g8uFrmZWtFESi4HoRZQ6jh1AQAAAAAAsCjsnKiQGk+m1b5ALQgTqYz2HhvRZStr9MbLV+j3h09qfyhS0PfoDEW1LuiTg1ZpRRHwm5KkcOTsc7VitB9cNDyu7PdoLJGWk1ALKHmEWgAAAAAAAFgUHu8e0rJKjwwj++uF0N43qngqo9bGKt1ySZPKXA59e9fRgq2fzljaH4rQerCIgj6PJCkcPUeolaT94GKRaz+YzlhUagE2wKkLAAAAAAAA28tVSF3RHND6+orJuVbzbXfvsCRpW2OVqr2mXralQT/fN6BQJF6Q9XuHxjWezKglSKhVLAFftlIrFD37ZxZP0X5wsfBMCSap1AJKH6cuAAAAAAAAbO+p4yOKpzJqa6rW5auXaO+xkcngYT7t6hnSuqBP1eVuSdItrcuVsSx9b8+xgqzfGYpKEpVaRTS79oPcXrW73EwtSXI5+DyBUse3FAAAAAAAALa3s3tIDkPa0Vily1fXKpG29PTxkXndQzKd0ZPHRrSjsWryscbqcl29LqAfPHlcY4n0nN+jYyAip8PQ6lrvnNfCmflMp8rdjhm2H2Smlt2dHmpRqQWUOkItAAAAAAAA2N6uniFtqK9QRZlLl6yqkcPIBl3zKTdPa0dT9WmP39baqNF4Sj9+um/O79E5ENGaWq9MKoSKxjAMBXymQueo1KL94OJh0n4QsBVOXQAAAAAAANjaeDKtp46Pqq0pWyFVWe7W+jr/vM/Vys3T2rG86rTHL1pWqYuXVeq7u48qlbHm9B4dAxG10Hqw6AJ+j8LnmING+8HFw3SeCrKo1AJKH6cuAAAAAAAAbO3Jo8NKZSy1rThVIdXaVK2njo8qlpx7y7+Z2tUzpOaAT9Ve97Tnbmtr1LHhmH6zP5z3+uFoQifGkmoJ+uayTcxA0Gees/3gqUot2g/aHZVagL0QagEAAAAAAMDWdvYMy+kwtG1KhVRbU7VSGUtPHpufuVqpdEZPHj19ntZUV6ytVVN1mb61s1eWlV+1VudARJK0nkqtogv4s+0Hz/ZZ5WZqUallf8zUAuyFUxcAAAAAAAC2trN7SFsaKlQ+pWpmW2OlnIbmrQVhe39EsVRGrU1nDrWcDkO3tDbqmb5RPXk0v6CtYyLUagkSahVbwGcqlsoomjhzpV8slZbpNOQwCEHsbmqlFqEWUPoItQAAAAAAAGBbkXhK+/pHT2s9KEk+06WNDRXa2T08L/vIhWfbz1KpJUl/uLleVWUufWtnb17v0TkQ1bJKjyrKXHm9HjMX9HskSeHImVsQxlMZWg8uEg7DmAyzaD8IlD5CLQAAAAAAANjWnt5hZSzpkueEWlJ2rlZ7/6jGzlJtU0i7e4e1ptarGq951mvK3E69ZtsyPdg1qCMnxmb9Hp2hiFpoPTgvgv7s5xiKxs/4fCyZofXgIpL7LF0OPlOg1PEtBQAAAAAAgG3t7BmS6TS0ZWnltOfamqqUzlh64mhxq7Wy87SG1do0PVh7rtduWya309B3dx+d1XuMJdLqOTlOqDVPan0TodZZKrViqbTKCLUWDffEXC0qtYDSx8kLAAAAAAAA23q8e0hbl1edsWrm4uVVcjmMos/V2tcf0Xjy7PO0pqr1mXrJpnr95Jl+nRw7c2ByJvtDEVlintZ8yVVq0X7wwmA6s2GWy0moBZQ6Qi0AAAAAAADY0tBYUvtDUV1ylgqpcrdTmxsqtLOnuJVau3uz659rntZUt7U2Kp7K6O4nj8/4PToGopKk9XW+2W8Qs+YzXfK6nQpHz1KpRfvBReVU+0FCLaDUcfICAAAAAADAlnb3Ziuw2s4wTyundUW1nu0fVSSeKto+dvUMaXWtV0vOMU9rqtW1Xr1wzRL9955jiiVnNu+rMxRRVZlL9RWeuWwVsxDwm2dtPxin/eCikms/SKgFlD5OXgAAAAAAANjS491DKnc7tKn+7C352pqqlLGkPb3FqdbKztMaUesMq7Ry3tDWqJPjSd23b2BG13cORNRS55dhcNN9vgR8psLR+Bmfi6Uy8rhoP7hYUKkF2AehFgAAAAAAAGxpZ8+QtjdWyeU8+y2ui5ZWyu00tLNIc7WeHYhoLJlW61laIJ7NjsYqbajz69s7e5WxrHNem0pn1BWOMk9rngX95jnbD5a5ubW6WJgTZ4iTUAsoeZy8AAAAAAAAsJ1wJK7DJ8bVdp4wqczt1EVLK7WrSHO1dvfMbp5WjmEYekNbo46cHNfvDp4457WHT44rkbbUwjyteVXry7YftM4QOtJ+cHFxU6kF2AYnLwAAAAAAAGxn50SYdK55WjltTdXqHIhoeDxZ8H3s6h3S6iVe1fpmNk9rqmtbAqqv8OhbO3vPeV3nQESStL6OSq35FPR7FE9lFIlPn3tG+8HFxcNMLcA2CLUAAAAAAABgOzu7h1Thcc2oJV/riipZKvxcrVTG0hO9I9rRNLsqrRyX06FbdizX7t5htfeNnvW6joGITKehlUu8+W4VeQhOBJVnakEYT9F+cDExXbQfBOyCkxcAAAAAAAC2s7NnSK1NVTO6Cb2loVIel6Pgc7U6JuZp7Zhl68GpXn5Rg3ymU98+R7VWZyiqtQEfVSTzLODPhlqhSPy0xy3LUiyZlof2g4uG6cx+t1wOPlOg1PEtBQAAAAAAgK0cG47p6HBMreeZp5Vjuhzauqzwc7V2T4RkO2a4jzPxe1x65dalur8zpOMjsWnPW5alzoEIrQcXQOAslVrJtKW0JZXRfnDRMJ1UagF2QagFAAAAAAAAW8lVXM1knlZOW1O1DoSjOjk2vZVcvnb1DGvVkvLJ8CNfr9u+TDIM3bX76LTnjg/HNBJLqYVQa97lKrXCkdP/zsRT2RlbtB9cPHLtB6mGBEofJy8AAAAAAABsZWf3kGrK3VpbO/MZU60Tc692F2iuVipj6Ymjw9rRmH+VVk5DZZmuWx/UD/f2aTSWOu25fcezs7ao1Jp/PtMlr9up0HMqtcaT2VCL9oOLR65Si1ALKH2cvAAAAAAAALANy7K0q2dIbSuqZRgzvwG9uaFC5W6HdnYXZq5W50BE0UR6Miybqze0NmosmdYPnzp+2uPtx0dkSGoO+AryPpidgN9U+DkztcaTGUm0H1xMcpVatB8ESh+hFgAAAAAAAGyj++S4BiIJtc0yTHI5Hbp4eVXB5mrtys3TaixMqLW+3q+2FdW6a/dRJdOZycf39Y2oqaZcXpMAZSEE/ea0mVrxJO0HFxvTmQ2zXE5CLaDUcfICAAAAAADANk7N06qZ9Wvbmqp16MTYtJAiH7t7h7WiplwBv2fOa+W8oa1RA5GEftkRmnys/fgIrQcXUMBnKhSh/eBil2s/6JxF9SeAhcHJCwAAAAAAZuzwiTENjycXehu4gO3sHlad31RTddmsX5ur7trdM7cWhOmMpT29wwVrPZjz/FU1Wl3r1bd29sqyLI3Ekjo6FFNLkNaDCyXg8ygcTciyrMnHYrQfXHRy7Qep1AJKH6EWAAAAAACYkb6RmG77xi69+LMP6VcdodNu8gLzIZPnPK2c9fUV8pnOyWqvfHWGJuZpNVbPaZ3nMgxDb2ht1P5QVI91D2l/KCpJaqFSa8EE/abiqYwi8fTkYzEqtRadXKWWy8FnCpQ6vqUAAAAAAGBGvvLwEUnS0qoy/dVP9ukv/3dfQdq4ATN1MDymk+NJtTXlFya5HIa2N859rtbuidfvKHClliTdsLFOS7xufXtnrzoGIpJE+8EFFPSbkqRQND752DgztRadXKWW00GlFlDqOHkBAAAAAMB5HRyM6qft/XrttuW6++2X6z0vWq3fHRzU676+U/e299uuaisUieubj/fo5BihnJ2cmqeVf4VUa1O1uk+Oa2A0fv6Lz2JXz5BW1JQrWMB5Wjmmy6HXbV+uRw6f1M/2DSjo96jWZxb8fTAzuT/7qXO14rQfXHQ8k5VahFpAqSPUAgAAAAAA5/Wl3x5Wudupt1zWJJfToTdf2qRvv6lVq5Z49ZH7OvT+/3lG/XMICeZLOmPpe7uP6rVf26nPPXhIr/2336v75PhCbwsztLN7SMuryrS0cvbztHJyc7XybUGYzljac3RYOxoLX6WV86qLl6rM5dC+/og2La0o2vvg/HLB5eCUqtRx2g8uOuvqfGoO+tVQUfigGkBhcfICAAAAAIBzevr4iH5zYFBvaGtUdbl78vFVS7z6yusu1p9fvVa7eob0uq/v1A/2Hi/Zqq32vlH90Xf26J9+3aUtSyv08Zs2aCSW1Fu/s0dP9M6tHR2KL52xtKt3aE5VWpK0LuhXhcelXXmGWgdCUUXiabXm2QJxJqrL3XrZlgZJ0sallUV7H5xf4AyVWrEU7QcXmzW1Pt33vheqasp/4wCUJk5eAAAAAABwVpZl6QsPHVJNuVu3tjZOe97pMPT6Hcv13Te3amO9X//4y/16191PqXeodKqfRmMpffL+A3rLt/doIJLQx2/aoH999UV68YY6/fefPE9V5W696+69+vm+gYXeKs6hMxRRJJ7WJXMMk5wOQzsaq7Qzz7lau3qzYVgxK7Uk6ZbW5aoqc+n5a2uL+j44N6/plM90KhQ5VYkaS+QqtWg/CADzjVALAAAAAACc1WNHhrSzZ1hvu3yFvObZb+A2VpfrC6/dqr/6g2bt6xvVLf+1S9/bfVSZBazasixLP983oNd87XHd8+Qx3bx9me7+oza9eEOdDCM7N2XlEq++ess2bVlaqTvvfVZf/X13yVaaXeh2dmfDpNY5Vmrl1jg2HNPxkdisX7urZ1hN1WWqK3Kbssbqcv3yXc/T89YQai20gM9U+LT2gxkZkkwn85cAYL4RagEAAAAAgDOyLEtf+O0hLa306JVbl573eodh6FUXL9Ndb27V9sYq/dOvu/T2u57UkRNj87Db0x05MaZ33/2U7rz3WdVXePT127brL65plt/jmnZtVblbn3/1RXrJxjp96XeH9dGfdyqZzsz7nnFuj3cPafUS72Q7uLmYnKvVPbsWhBnL0hNHh7WjiK0Hp8qFr1hYQb+p8JT2g/FUWmVuB58PACwAQi0AAAAAAHBGD+wPa19/RH/y/FUyXTO/hdBQWabPvmqLPnJDiw4Ojum2b+7WNx/vUSpT/AqoeCqjf/vdYd3yjV1q7xvVB65p1tdu3a6N9RXnfJ3pcujvXrJe/+95K/STZ/r1vh88rdFYquj7tbt0xtKJsYS6wlHt6hlSeEqLtkJKpTN64ujwnOdp5awN+FRVNvu5WvtDUY3EUkVvPYjSUuszFTqtUitN60EAWCDTfzwJAAAAAABc8FIZS1/87WGtqfXqho11s369YRh66eYGXb6yRp+4/4A+9+Ah/aozrL+5vkXNAV8Rdiz9/vAJffL+A+oZiun6DUHdfuUaBfwzbxFnGIbe/vxVWl5Vro/9olNv++4T+udXbdbyqvKi7LcUJdMZDY0ndXIsqZPjSQ1N/HPqr4fGEtnHxpIaiaU0Napc4jP1vTe1qtrrLui+nukb1XgyU7BQy2EYam2q1s6eYVmWNeOKm1wIRqh1YQn6PQpHwpN/V8aTaZXNIugHABQOoRYAAAAAAJjmJ0/3qfvkuP7p5ZvkdOTfYivg9+iTL9ukX3WG9cn7D+iN39ytt16+Qrc+b5U8GUuuOaydE4rE9c+/OahfdoS0oqZcn3/NRbpsZU3e6920uV4NlR594Efteut3ntCnX7FZW5ZWznmfpSqaSOlffnNQD+wPa+Qs1WkOQ6oqc6va61ZNuVtrAz5Vl2d/XeN1q7o8G2L97c869E+/PqCP3bSxoHvc2TMkQ4UNk1qbqvXA/rCODsfUWD2z4HJ3z7Aaq8vUUFlWsH2g9AX9phJpS6PxlCrL3IonMypzE2oBwEIg1AIAAAAAAKeJJdP690eO6KKlFbpibe2c1zMMQ9etD6qtqUqf/nWXvvLwEX3l4SNyGlJdhUdLK8u0tDL3zzItrcr+ur7CI7fz7DeO0xlL39t9VF/63WEl0xm9/fkr9aZLmuQpQAVFa1O1vnrLNt3+P0/rHWNdxqkAACAASURBVN/fq4/euEHXrAvMed1S80TvsD7ysw71jcT08m3LVDcRUtWU5wIsUzXlblWUuWYUbvaPp/S5Bw7ouvVBXdlcuD+vnd1DWhf0TYZnhdC24tRcrZmEWhnL0p6jw7qqee7fCdhLbo5bKJJQZZmb9oMAsIAItQAAAAAAwGnufvK4BiIJffTGDTNuyzYTNV5TH7tpo16/Y7mORpM62DeiYyNx9Y3E9Hj3kEKRxGmt7AxlKySWVpapodKjZVXZCplllR4ZhqEvP/yEnj42ostX1uiD1zarqaawbQJX1Xr1tVu36c9/+Iw+9ON2vfeK1XpDW2NB/0wWSjKd0VcePqJvPN6jhsoyfeV1F+vKzUs1NDQ2p3XfccUa3ffUcf3jrw5oe2OVKsvmHkLFUxntPTai12xbNue1plq9xKslXrd29gzpFVuXnvf6AxPztFqbCtMCEfYR8GdDrXAkobUBX7ZSi/aDALAgCLUAAAAAAChxlmXpsSNDaqxLabm3uP9XPhJP6euPduvyVTVFu3m/ZWmlXljtnRagJNMZ9Y/GdXwkpuMjcR0fjun4aPafTx0b0a86QkpPSb3qKjz6+E0bdN36YNGCphqvqS++dqv+7mcd+tyDh9Q7FNMHrm0uSNvEhXJwMKoP39uhjoGIXr6lQe+/eo18ZmH+XrmdDn3k+vV687d36zO/Oai/vWH9nNd86tiIEmlLbQX++2hMzNXaNcO5Wrt6hyUxT+tCFPRlZ/OFowlJmqjUItQCgIVAqAUAAAAAQImyLEsPdg3qPx7p1rMDEXlNp/711Rdp67LizXf61s5eDcdSevcLVxXtPc7G7XSosbr8rK3gUhlL4Uhcx0ZiOjmW1Iu3LlM6liz6vsrcTn38pRu17KHD+sbjPTo+EtM/vHSj/B573VbJWJa+t+eYPv/gQXlNlz71sk26qggtFdfX+/XmS5v01Ud7dN36oF6wesmc1nu8Z0hOQ9pehDCpralKv+wI6cjJca1a4j3ntbt7hiarBXFhyVVqhSJxSdlQq2KiJSEAYH7xIwUAAAAAAJSYjGXpgc6Qbvvmbv3Fj9o1Gk/pg9c2K+j36PYfPK39oUhR3ncwmtB3dvXquvVBbaivKMp7zIXLYaihskw7Gqt1bUtQFQVobTdTDsPQe69Yrb++bp0eO3JSb//ek+obic3b+89V/2hc7737KX3m1126dGWN7npza1ECrZy3Xb5Sa2q9+odfdCoST81prV3dQ9rYUFGUEDFXjbirZ+ic12UsS3t6h9VKldYFqdztlM90TlZqxZNp2g8CwALh9AUAAAAAoESkM5Z+8eyAbvmvXfrL/92neCqjv71hve5+6yV67bZl+vpb2lTudug9dz+l7pPjBX//rz3arUQqo3e8YFXB114sXrl1qT77qot0bDimt373CT1zbGSht3Reub9Te4+N6K+uW6fPvGKzaotcZWK6HPrw9S0KRxP67P8dzHudsURaT/eNFrz1YM6KmnIF/aZ2dg+f87qucFTDzNO6oAX95pT2gxnaDwLAAuH0BQAAAADgHAZG43rm2LBSGev8F+cplbF0375+vf6/duqOnz4ry5L+/sYN+v5b2nTT5vrJ+U2NNV59/jVblbGkd//33oJWCh0bjumeJ4/rZRc1aEXNmdv/IeuyVTX6j1u2yWEYuuU/HtXnHzqkk2OJhd7WNKOxlO786T7d8dNntXJJub79pla9auvSos0fe67NSyt1W2ujfvhUnx49cjKvNZ44Oqx0pvDztHJyc7V29w7Jss7+Hd/dMzFPq4lKrQtVwO9RKDJRqZVKq8ztXOAdAcCFyV7NnwEAAAAAmAd9IzE9sD+s+zvD2jtRieN1O7V1eaV2NFZpR2OVNjVUyO2c28+KpjKWfravX197tEfdJ8e1NuDVP7x0o65ZF5DTcebgYXWtV//66i16x/f36j13P6V/f/3FqvHOvermKw8fltNh6I8vXznntS4EzQGfvn7rNn3+d0f0jcd69P09R/Wai5fptrbGoldBzcTj3Sf1t/d1aDCa0Nufv1J/dNmKyXB0Pr39+Sv1f12D+vgvOnXXm9vkNWcXBOzsHpLLYeji5cWbI9fWVKWf7RvQwcExrQ34znjNrt5hLav0aCnztC5YAZ+pvUez4eY47QcBYMEQagEAAAAAIKl3aFy/ngiynukblSS1BH165wtWad2ySj3cGdLu3mF98beHJUkel0MXLTsVcm1ZWjnjdlTJdEb3tmfDrKPDMa0L+vSJl23SVc21csygimZDfYX++ZVb9N57ntJ773laX75565zmDR0IR3Vv+4De0NaougpP3utcaAJ+j/7lddv05rawvvZot769q1fff+KYXrV1qd54SaOC/vn/s4ynMvribw/pO7uOakVNuf7zlm3avLR4gdD5lLmd+vD1Lfp/dz2pzz90SB+8tnlWr9/ZM6SLllUWtSpm6lytM4VaGcvS7p4hvWhtbdH2gNIX9GXbD2YsSzHaDwLAgiHUAgAAAABcsI6cGNMD+8N6oDOsZwcikqSN9X6950Wrdc26gJom2vBVV3v1ohXZG98nxxLac3REu3uGtLt3WP/+8BFZkkynoc1LT4VcW89wIz6Ryugnz/Tp64/16PhIXBvr/Xr/VZt1xdols24Jt72xSp982Sb9+Q+f0fv/52n966svyvvG/5d/e1g+j1NvvrQpr9df6FbXevXRGzfoj5+3Ul99tFvf33NU9zx5TK+4aKnedGmT6ucpKOwciOhv7n1WBwfH9OqLl+pPr1yj8hJokXbx8iq9bsdy3bX7qK5tCcx4LtVILKmOgYjedvmKou5veVWZGio82tkzrJu3L5/2/MHBMQ3HUtrRSOvBC1nAbyqRthSeaEFI+0EAWBiEWgAAAACAC8rBwaju78wGWQfCUUnSRUsr9KdXrtE16wJaVnXu9mI1XlPXrAvomnUBSdkb73t6R7S7d0h7eof1tUe79Z+/l1wOQ5saKrIhV1OVBuMhfek3XRqIJLRlaYX+8tp1ev7qmjnNN3r+6iX6+xs36I6f7tMHf9yuT79i86xbIu49NqL/6xrUu164SlXl7rz3AmlFTbn+9ob1+uPLV+jrj/bonr3H9T9PHdfLtjTozZc2Fa11XSqd0VceOqh//tV+VZW79S+v2qIXrF5SlPfK17teuEoPdQ3qY7/o1Hff1DqjQGBP77AyltS2ojjztHIMw1Drimr9tmtQGcuaVi25u2dIkmYcxmFxCky0Fe0ZGpckKrUAYIEQagEAAAAACm48mdZDe4+pXNkqliVe95zCm7mwLEv7Q5HJIOvQiTEZki5eXqk/u3qtrm6uVcMcwobKMreubK7Vlc3Z1mSReEpPHs2GXLt7h/XNx3v09cd6JElbl1Xqb65v0WUr5xZmTfUH64OKJlL62C/268P3PquP3bTxrPO4nsuyLH3hoUNa4nXr9TumV6ggP43V5brz+ha99fIV+sbjPfrRU3364VN9eunmer3l0iY1VpfnvXbGsnTkxLj29Y+qvW9U7X0RdYYiiqcyuqq5Vndc16Jqb+mFk+Vup/7m+ha94/t79aXfHdb7r1p73tfs7BmWx+XQlobit09sa6rST5/p14FQVC11/tOe29UzrKWVnvMG3ljccu1Ejw7FJImZWgCwQAi1AAAAAAAFFUumdfsPntbu3uHJx6rKXFpd6534n09rlmR/HfSbBQt3Ysm0+kbj6huJ6fhIXMcn/vnsQESHB8fkMLIt+16zrVlXr6st2rwjv8elF6xZohesyVbKjCXS2ntsWMEan9ZUFu73O9XLL1qqSDytf/m/g/KZ+3XHi9fN6H1+f+SkdvcO6wPXNJdEm7rFZllVmT70B+v0lkub9M3He/XDp47rJ0/36SWb6vVHl63Qippzh1uWZenocEz7+iNq7xvVvv5RPdsfUTSRliSVux3aUOfXqy9eqis31mt7nW/BwuOZaG2q1qsvXqrv7jqqa1uC2rrs3GHVzu4hbVteKXMewoO2iSqsnT1Dp4ValmVpd+/w5PcZF66gP1up1TucrdSi/SAALAxCLQAAAABAwcSSaf35D5/RE0eH9fGXb1aV26FDg2MT/4vqgc6whmN9k9f7TKfWTAm7Vtd6tabWq/oKz7QWYOPJdDaoGs4FVqfCq2PDMZ0YS552vdOQ6is8aq6v0C3bl+nK5oBqJ9pHzSev6dTlq5aoutqroaGxor3PbW2NGo2n9J+/75bP49TtV645Z8CRsSx94aHDWlZVpldubSjaviA1VJbpA9c26y2XZcOtH+w9rnvb+3XDxjr90WUrtK3aK8uyFIokJsOr9r6I9vWPajiWkiS5nYZagn7duKleG+v92tRQoVVLvJNVecX++1Uo771itR4+dEJ///MOfeuNrWdt4XZyLKED4ahevGHVvOyrobJMy6vKtKtnWLe2Nk4+fnBwTEPjSeZpYbL9YO9EpRbtBwFgYRBqAQAAAAAKIpHK6IM/btfj3UP68A0turmtSUNDY7psZc3kNZZl6eR4UocGx9QVzgZdh06M6bcHT+jHT/dPXlfudmjVEq+W1Xh17OSYjo/ENTR+emjlchhaWulRQ2WZXrSmVg0T7cEaKj1aVlmmgN8jl8Owzc3+QviT569UJJ7Sd3YdVYXHpT9+3sqzXvurjpA6BiL66I3rZz2HC/kJ+j36s6vX6k2XNunbO3t19xPHdF/7gFpX1uhQOKrBaEJSNpBdG/DpqnUBbWqo0KZ6v9YGfIvic/KZLt1xXYvec89T+srDR/TeK1af8bpdPdlKz0uKPE9rqramat2/P6R0xpoMC3P7aG0i1LrQlbmd8nuc6h3KVWrZ//sIAHZEqAUAAAAAmLNkOqMP/W+7Hjl8Undct04v3Xzmyh/DMLTEa2qJ11Rr0+k3q4fGkjp0Iht0HRwc0+ETY+o+MaZar1sb6ysmw6pceFXrM6dVc13oDMPQn129VpF4Sv/28BH5Pa4zzspKpTP68u8Oqzng0/Ub6hZgpxe2gM/Un165Rm+6pFHf3nVUO3uHddnKam2qr9CmhgqtC/oWdWuzy1bV6OVbGvStnT26piWgzQ0V067Z2TMkn+nUhvrpzxVL64oq/ejpPnWGIto48b57eofUUJE9e4Cgz0OlFgAsMEItAAAAAMCcpNIZ3fHTZ/XQwRP64LXNesXWpXmtU+11a7u3StuntPm6kKqsCsVhGLrz+vWKJtL69K+75Pc4p4WMP36mXz1DMX3mFZsJBhdQjdfUe160+oL8e377VWv0yOFsG8Jv3LZj2tysx7uHtL2xSi7H/P39nJyr1T2kjfUVsixLu3qG9bzVNSU9qwzzp9Zv6tCJ7He1zLV4g2cAKGX8SAEAAAAAIG/pjKWP3NehX+8P6/1XrdFrty1b6C1B2daMH79poy5dUa2//3mnHtgfnnxuPJHWfzxyRBcvq9QL1yxZwF3iQub3uPRX161TV3hMX320+7Tn+kZi6j45PhkyzZeg36MVNeWTLQcPhKI6OZ5Ua+P87gOlKzhlLiPtBwFgYXD6AgAAAADyks5Y+ujPO/SLjpDe+6LVurW1caG3hClMl0OfevlmbW6o0J0/3adHD5+UJH3z0SMKRRJ694tWU32CBfXCNbW6cVOdvv5YjzoGIpOPP3rwhCSpbR7naeW0NVXriaPDSmUsPXY4u48dzNPChKD/VKhF+0EAWBicvgAAAACAWctYlv7xl/t1b/uA3vGClXrTpU0LvSWcgdd06l9etUUra7z6ix89o98dOqGvPHRIL1i95LQ2j8BC+bOr1qq63K2P/qxDqXRGkvTIoUFVlbm0Luib9/20NlUpmkjr2f5RPXbohOr8ppZXMU8LWbVTK7VoPwgAC4JQCwAAAAAwK5Zl6ZP3H9CPnu7T2y5fobddvnKht4RzqCxz619fc5GCflO3/+BpDY8n9a4XrlrobQGSpKpytz50bbM6Q1H91+M9kqTfHxzUjqbqBZn31jrR8vDx7iE9euiEWpuqqWjEpKDfM/lr2g8CwMLg9AUAAAAAzJhlWfr0r7t0z5PH9aZLGvUnzyfQsoOAz9QXXrtVyyo9em1ro1rq/Au9JWDSVesCum59UP/xSLce6hrU0aHYvM/Tyqn1mVpd69WPnurTYDShVloPYoqpM7U8VGoBwIIg1AIAAAAAzIhlWfrcg4f0vT3HdMuO5XoPM5lsZWllme5526X62Ms2L/RWgGk+cM3/396dx0dV3vsD/8y+T2Ymk4UkQEgCyA6ioOAFKoUCVlBRoS6t8rNacCtQb724oMiVciuiotJ6KVJRKlCtCl5txY3VsAhSZROTkEASQiZkmX07vz+SGSbJLOewlKl+3q9XX1TQL+ec+eR5nnO+c84phkmjxH9tPAgAuPwivE8r4rKuFpxo8gIALi24eNtB6cfe9k4tlUIGpZzzHxHRxcCmFhEREREREaUkCAKWb6vA67uP48ZBXTB7TBEbWv+GlHIZ5LwQS2nIqlfjobEl8AXDyDJqUGjTXbRtuazt7qwcswYFFr5Pi86wt92pxbu0iIguHuXF3gAiIiIiIiJKfyu+qMSrpVWYMiAXD40tYUOLiM67H/eyY+/gPBRkGi7qGHNp26MPhxXaONZRO1qVAiaNEloVm1pERBcLm1pERERERESU1KrSSryy/Riu6ZeDeeN6Qs6LvER0AchkMvzn2BJYLHo0Nrov2nZYdCo8ObE3hvfMumjbQOnLblQjGBYu9mYQEf1g8fGDRERERERElNAbu4/jpa0V+MklWXhsfC82tIjoB2FS3xwUZxkv9mZQGrIb1LxTi4joIuKdWkRERERERBTX6i+O4bnPyzC2lx1PTLwECr6LiYiIfuB+cXlXhPlOLSKii4ZNLSIiIiIiovPEGwihxRtEKCz82zaAwoIAXzCM/ztwEr/bdBSjizOxcNIlUP6b7g8REdH5NLzQetEfkUlE9EPGphYREREREdFZ8AXD+PaUEwdqW3DgZOuvFQ43Im/ZUClk0KkU0Crl0Lb9qlMpoFW1/qqJ/rMCOpUcWmXrn2lVCpgMGrjdvrPetrAAKNRKNDR54A2G4QmE4Gv71Rto+zUYhrfDP0f+vYjRvbLw9MTeUCr45HoiIiIiIrr42NQiIiIiIjrPBEGAJxDGaY8fje4ATnsCOO0OoLHt19OeAAS5DH2zjBhZZEV+hu5ibzKlEAyF8V29GwdOtuBAbQsOnnTiaL0LobYXxdv0KvTNNeHHveywmXU43eKFN9DWNAqG4Gn7/55gGG5/CA5XoN3vewMhhC7QO+dlQGuzTNnaPNOoFNFmm02vbvuzSOOtrcGmUsCqU2HaFd3hcZ19c42IiIiIiOh8YlOLiIiIiEgCtz+Evceb4Ao7cMLhateoijSwGj2Bdne7xFIrZLDoVFAo5Hj/n7X4/SdAd6sOI4tsGFFow5CCDKiVvCvmYgqFBRw77W5tXtU6ceBkC47UOeFv6zqZtUr0yTHi9ssK0DfXhD45RuSYNJDJWh/Pd7aPJAqEwtG7pkxmLZqaPOe0H9mZRvjdPmiU8ui2SaVRKXBuW0FERERERHT+sKlFRERERJSC0xfEljIHPjlSjx0Vp9s1rHQqOaw6FSx6NTINahRnGWDVqdp+r/VXq14FS9uvepUCMpkMFose+8sd2FbegO3lDfjrvmqs2XMCOpUcl3ezYkQPK0b0sKGLWfsv2cdQWEjwSLrYu4nC7e86avtnvVYFq0aBLmYtumRo0cWsgVWnOutGyrmKbQ55o4/ci7P9wTN3SXnb7qA60eLDNyea4Q6EAAB6lQK9c4y4aXA++uYa0TfXhPwM7QXZN5VCDpVCDpNWCUuGDjrh3G7dshjUaAwEz9PWERERERERXXxsahERUUqhsICKBnf0cUsHaltQ7/LDpFGeuWCb4OKtVaeCWauCgi+XJ6J/M83eADZ/58DHR+pReuw0AiEB2UY1rhuQi9ElmejXzQZ5IAitSnHWf0c3qw7drPn42aX58ARC2FPViG1lrU2uzd85AAA9MvUY2cOGET2sGJyfAZXEdxsJggCHO4CaJi9qmr2oafa1/dr6/xvcAbj9QQTO4tl3kXdEBQUBLd72zRONUo4uZk1ro8usPfP/25pemQY15CkaQ4IgoMUXjD66sd1dcXHukHP5Q/AEQtFHAoollyH6PquuNj1+2i+n9Q6sXCO6W/Wcw4iIiIiIiNIEm1pERAl4AyHUNvtQ0+JFTZMXp5x+FOaYkKtTokemHmat6mJv4gUhCAKON3rbXnrfgoO1LThU54Qn0HpXgl6lwCU5RowsscPR7MVpTwCH65w47Q6gxRf/2+ByGWDWdm585Vr10MnQqQlm0an4Qnoiuiga3QF8/l09Pj5Sj52VjQiFBeSaNLhpcB7G9spC/y6maCPGYtGd1SPmEtGpFLiqKBNXFWVCEAQca/Bge0UDtpU1YO3eE3h993HoVQoM627BiB42jOhhg8WiRygsoN7lb21atXhR09S+aVXb7I0+Ni8iQ6tErlnb+tjDEjvkYQFalTz6niWdqrXBo43558jv6dqaP7GPtLNY9KiqbY7bNKttbp1Tmjo0vVQKGXJNZ5peZoMatY2eTo9xTNSgineHnN2shTwcjjaotKq290MpY39VQNNhX1UK2Tk/OpCIiIiIiIguPDa16HshLAho9gbhggeqYJjvoTgP/MEwTnsC8MrlUITCkr8V/u/A5Q9GL7ZVN7X+GnsxrsEdSPrfZxrU6JGpR5FNjx6Zrf8rytTDqlf/i/bg3AmCgJMtPhxou/vqYNudWJHmlEYpR68sAyb3z0WfHBP65prQzaqDQi6Le9EvGAq3fnO+7dvzkW/RN8ReoHT7UeZw4XRVAM2+IBI9WcmkUZ5pdiW5C6y7TAZ5MAwNf+6JzrtQWIAveOYRdIJaCQjCRXuk3IXS4Pbjs29bG1l7qhoREoC8DC1uHZqPq3tloW+O8V++zzKZDIWZehRm6nHL0AK4/SHsqmzEjrYm12dHW+/iyjFpUO/yd2r82PQq5Jq16JVlwKjizDN3SrXdJWVQnzkNOF9NHJNWCZPWiF7Zxrh/7vaHUNPsRW2zD9XN3jPzb4sXW8ocCIQFWLRKWHRq5GVo0S/XlHDst+hUce+QY0OKiIiIiIjo+41NLUpLwbCAJk/7x8m0XiD3n7lQHnPRvMkTQOQLyDIAdqMauSYt8jI0yDVrkWeO/KpFrllzTo8J+nflCYQ6PKLH367pEPsYn8a2x/fEMqgV7S4ktV5cUp/5vZiLTtYEF5piCYIAf0hoex9Hh/d3BEPt3oPhDYSg0arg8SRvMqX6+1qCYZTXOVvvvmr2dvrGuFohQ27bRb/oBcAMDbqYWh+VlGlQwyuT4avyBpQ5XCh3uFHe4Mb7B062O14WnSra4OphO9PsyjSo/+UXRQVBgMt/5rOP/Bw1+sPYe+w0Dp5siTbvFHIZetoN+HFvO/rmmNAn14TiTL2kO6aUCjnsRg3sRo2of99k1uFYbVPnLHbY3uNNHvyzprndz3pHepWi88XPeBdC9SpYdWroVPLv3YV5IiDxHBqSy9DY4o2+Ayn6jqRO70868/ux742K0KnkCR8n18WshU1/8d6jJEVdixfv7K3GJ9+ewt7jTQgLrY8C/PmwrhjbMwu9sg1ptR96tQKjSzIxuqT1Lq7yBje2lTWgssmHDI3i32Kto1crUGw3oNhuiPvnbEgRERERERFRKhe8qRUOh/HEE0/g8OHDUKvVWLhwIbp3736h/1oSKRhubSroAiEIF/Cb14FQuPPF6rY7NmKbU82+EBxOH5q9QSR6E0KGVhm9QN3NqsOgfHP00TP2DB0q6lraHr/jw9c1Lfj4SD2CCb69HLkAFPvt5R4qJU41e1M2WZK9fFyhUECvlMdt+ES2PeMc3jGUqFHRsTnV4g+hvsWH055A3AuTQOujf2IbVfkZWlj16uh263QqVDtc7ZoOtS0+HGp73FzHYxuhbdt/i04FlUoBpyfQ7th5gyFIfN3FOdOpFK2POcrQoF8XU6cLsja9KuW7PQosehhlwMgiW/T3BEFAndOPcocLZQ53a7PL4cY/Dp1q9zg+k0aJ7jYdrAYNFBDOPMap7fFHWpWi9TFJCR77FHmEUkilRJXDnfDnKDYHjZ5A3HekyGWt72gZ0cOGPjkm9Ms1oiTL+C+/20khl8GmV8Mm8u62cNs7W2LHEh9kqHa4os3uRncAp5x+HKlzotET6PTIrQiNUn6m8WVUQwm0e0yVtsPnE/8zOfPnQaUCtY2eJGNEuF0Tt+N44g2GoFEroQRitiHOo7PastBuG2L+Xbkm0Om9NlLJPRe/hsIbQOAC3iUqCAI8gTBOe/wdmqjtf4YCAqKfiabt57Pj8Y+fiTN/JtOozvl4epu9OFbnTDqHRufSJHOoDGi33bHZshvV0e1OlPugXI6yky1td9h48c+aZjTHeY9S9JFyGe3fp5Rr1kJ+jsdDgAB/ixcnT3vaNec8gTB8wVD05y32Z80X83PoCYTQ6AngUJ0TgtA6Fs4Y3g1je2Wh2K5Pq0ZWIjKZDEWZBhRlGtgIIiIiIiIioh+UC97U2rRpE/x+P9auXYt9+/bhd7/7HZYvX36h/9ofjIMnW1DxbT1ON3s7XcSJd1G140Wd2IZE7AuyO12wa7vgFXtBL/bCr0YpQ1AuR7XDHfduqo53/cT+nRnaM02fXjlGGNqaVFZ957uAMnQqKJM0guJd2Im8Z6K22dv2qBsfqttelH7klAubv3MkvOidikIu63yxWamAUgkcP+1O+o4hGQCzVhmzj+r2+2rSdGomxTasxDSTss1adLdoE95RZdGpYFArkl7AS3axTGxzTalUIFOnSnwROEUTR6OUw2Y1oKnp3C7a5WWZ0NTkOaca8chkMuSYNMgxaXBFYftml8MdQHnbXV1lDjcqT3vQ7A3A6Q2c+fk8T02+2Lvpck0a9MkxJvzse3TJgNflO8c9/9eTBT/yVQAAIABJREFUy2TIaBsL0HaoU2XU3XaXYtw7wdr+vzcYRoM3eKZB3TaGnu3YkIpGKe/UBNEo5fD4Q23ZCLW7mybR+2R+CBRyWdwmYrxGkiZmLNap5DAaNGcanh0++0aRzX6zXo3m2J/XmPn0Yus4h5ZkGRLcoaiGRa9C12wT3E7vOTVt4v28OX3BuI+Tq27ytr5v7xzusj1XMiDulwcMGiUe+FEJRnTLQFFm/LuGiIiIiIiIiCj9XPCm1p49e/Af//EfAIDBgwfj66+/vtB/5Q/KU38/gm9PuaL/nKjJolW13pHQsXnQ2jBQQKVWoqHF2+6OAU/bBTxfIASHy9/pUUXxLugp5bKYR9Op0NesTfjoL6tOBbNO2e7OmAvxbWOF/EzDYVB+Rqc/DwsCGtyB1ru7mr3wQoawP5i0yRI5vokeyxa7H4neMRTb9DntCaDC4cbetkcpxl6+ltKo6PjYvwv97W2ZTAajRgmjRomuVl3Cf+98bIdRo0RQfW5D1sV4H4rdoIbdoMbl3azR3493PKQ8jlGpVkIlhFs/97YsWHQqSe+S06oU8J63PU1fMpkMBrUSBrUSBRbpGQ2GhbY7P8IdxsfOXyIwGDQQAsFOd+l0HJM1SnnCOwITbkcoHG1yJboDLDJGtz6q03/2Bw2ATqe+6DW0WhUaW3wJ74j1BMLRxlSiL2tEa8U0+20GFYrtetHN/kSfSVhofddUxwZkvJwo1MpzPp5WsxYaABadMuEcmopGpYDnAoyDRo0SJVlKlGTFbw55AqF2TS+56tyPh8WkBYKhpHctapWtX4pINPbzDiciIiIiIiKifz8yQRAu6Ne/H3nkEYwfPx6jR48GAIwZMwabNm2CUpn44nQ4HEboAn07/vvG7Q/C5Q9Do5BBq1JIuqgdS6GQIxSS9q3zcFhod1eDRa+G/hzfUXM223E+//t0qBEKC2j0BBAWWu/kOpfHwV3sfWGNC1MjHbaBNVjjQtc42/8+EDrzmEcBMpg1SujUZ/9uoXQ4Fqzx/a2RDtvAGqxxoWukwzawBmtc6BrpsA2swRoXukY6bANrsMaFrpEO28AarEFnqBK8K/qC36llNBrhcp25kygcDidtaAFAKCTwm7MSZLV909jtC+Bsj9q5fFtZAcCA1juKzvVzO9dvTZ+Pb12nQw0FgMy2GufysLx02BfWOP810mEbWIM1LnSNc/3v1TE1fOewK+lwLFjj+1sjHbaBNVjjQtdIh21gDda40DXSYRtYgzUudI102AbWYI0LXSMdtoE1WIPOyMoyxf39C/P29RiXXnopNm/eDADYt28fevXqdaH/SiIiIiIiIiIiIiIiIvqeueB3ao0bNw7btm3D9OnTIQgCnn766Qv9VxIREREREREREREREdH3zAVvasnlcixYsOBC/zVERERERERERERERET0PXbBHz9IREREREREREREREREdK7Y1CIiIiIiIiIiIiIiIqK0x6YWERERERERERERERERpT02tYiIiIiIiIiIiIiIiCjtsalFREREREREREREREREaY9NLSIiIiIiIiIiIiIiIkp7bGoRERERERERERERERFR2mNTi4iIiIiIiIiIiIiIiNIem1pERERERERERERERESU9tjUIiIiIiIiIiIiIiIiorTHphYRERERERERERERERGlPTa1iIiIiIiIiIiIiIiIKO2xqUVERERERERERERERERpj00tIiIiIiIiIiIiIiIiSntsahEREREREREREREREVHaY1OLiIiIiIiIiIiIiIiI0h6bWkRERERERERERERERJT22NQiIiIiIiIiIiIiIiKitMemFhEREREREREREREREaU9NrWIiIiIiIiIiIiIiIgo7bGpRURERERERERERERERGmPTS0iIiIiIiIiIiIiIiJKe2xqERERERERERERERERUdpjU4uIiIiIiIiIiIiIiIjSHptaRERERERERERERERElPbY1CIiIiIiIiIiIiIiIqK0x6YWERERERERERERERERpT02tYiIiIiIiIiIiIiIiCjtsalFREREREREREREREREaY9NLSIiIiIiIiIiIiIiIkp7bGoRERERERERERERERFR2mNTi4iIiIiIiIiIiIiIiNIem1pERERERERERERERESU9tjUIiIiIiIiIiIiIiIiorTHphYRERERERERERERERGlPTa1iIiIiIiIiIiIiIiIKO2xqUVERERERERERERERERpj00tIiIiIiIiIiIiIiIiSntsahEREREREREREREREVHaY1OLiIiIiIiIiIiIiIiI0h6bWkRERERERERERERERJT22NQiIiIiIiIiIiIiIiKitMemFhEREREREREREREREaU9NrWIiIiIiIiIiIiIiIgo7ckEQRAu9kYQERERERERERERERERJcM7tYiIiIiIiIiIiIiIiCjtsalFREREREREREREREREaY9NLSIiIiIiIiIiIiIiIkp7bGoRERERERERERERERFR2mNTi4iIiIiIiIiIiIiIiNIem1pERERERERERERERESU9pQXewO+zwKBAObNm4cTJ07A7/dj5syZKCkpwcMPPwyZTIaePXti/vz5kMvlWLVqFd5//30AwOjRo3HffffB6/Vi7ty5+PLLLxEMBpGfn4/777+/XY2ioiI0NjaioaEBp0+fhlarhVKpxOjRozFz5kw88MADcDgcOHbsWKca9957L6qrq6HT6SCTyVBQUICmpiY0NzfD5XLBbDbj+eefx4oVKyTX0Gq1kMvlqK2txX//939j/fr1kmvU1dUhHA7DarWiR48e0Gq1kmrU1NSgubkZMpkMGRkZqKmpwfDhw+Hz+SRtR2NjIzweD2w2G5YsWZL0eNx33304fvw4tFotLBYLrFYrTp8+jZaWFjidTmRkZOC5557DK6+8gn379sHv90Mmk+Gxxx7D4MGD8fDDD8PlcuHUqVPIy8uDx+OBz+dDU1MTunbtiqFDh+KTTz5BZmYmjh07BrfbDZ1O1ykbbrcbdXV1CAaDMBgM0Ol00WxkZ2dj69at6Nu3L6qqqhAMBhEKhdrVuP/++1FVVQWdToeMjIzofkSyodVqYbfbYTKZJNeIZKOyshJ2ux0Wi0VyjUg2dDod/H4/evbsKbmG1+vF6dOnoVarodPpkJeXJ6nGiRMnovmKZLNPnz6or6+XtB2RfGm1WmRmZsJsNifcjocffhgAcPLkSWRnZ0Mul7fLl06nQ2ZmZtLPJVENrVaLUCiE6upqFBcXQy6XS67R1NQEj8cDtVoNk8kEu92OAwcOQKlUQi6Xt8u5TCZDSUkJ6uvro59pU1MTNBoNFAoFDAYDZDIZ6uvrE+ZcJpOhR48e+Pzzz5GRkYFwOBzNebdu3bBp0ybk5+ejublZ0n5IyVeiGlLyFa+G1Hwl2o7zka9IDb1eD5vNljRficZRKRlNNq+IzWiiGh0zmpWVJblGx3HQaDQmzLnT6YTD4UC3bt1w4sQJqFQqNDc3w2QyIRQKQavVwuv1wuv1Jsy50+lEfX09QqEQZDIZLBYLwuEwHA5H9L93uVyw2WwQBEH0fkjJRqoaBoMBFosFOp0OLpcLjY2NnebHZHNCKBRCTU0NCgsLIQiC5Bqxn6vRaITVapVcI/ZzzczMPOt9ieTSZrPBaDRKrhEZf/R6PXw+HwoLCyXXiIw/Go0GGo0G2dnZkmrEjj86nQ719fUoKSlBbW0tAHRat0TWHAUFBXC5XNF1i0qlglKphMlkimY2EAhApVKJXrecPHkSoVAIgUAAubm5EAQh7n6ImR9tNlvSzzXV/Cgmo2Lmx1QZTVRDSkaT7YvYjKaaI8VkNNUcKSajqebISEZ79uyJUCgkaTtix8FIPioqKuLmPNG6RaVSQaFQwG63w+fzob6+PmHO443ner0eDocDfr8fPp8PXbp0SZjzVPOjmIyKmR9TZVTM/Jgqo6nOIcVkNNU5pJiMJqohJaOpzkPFZFTMXG2z2aDX6yXvS8e5WqvVJsx5ovNQrVYbPacOhUJJcx6pEe88dNCgQfjiiy/wk5/8BOvWrUMwGJS8Xjh16hR27NiBZcuWSa4RybnRaMT999+PkydPSq4Re63kxRdfxOeff35W+xK5VrJo0SJ89dVXkmvEXispKirCoEGDJNeI5NxoNOJnP/sZwuGwpBqxY3FGRgZqa2sxffp0bNq0SdJ2RDJqNpuxdOlSbN++XfK+xF6zWbp0KT799FO8+uqrUCqVosfzSM7z8/Mxd+5czJ8/H1VVVdBqtZLOQ8XkPNV6QUxGU60XxGQ01XpBTEZTrRfEZDTVekFMRlOtF8RkNNV6QUxGU9WIZHTz5s0Ja6Q6p87IyMCyZcvwySefJMx5ovPQyHXFL774An/9619xww03JMx5onVLXV0dlEol7HZ79JqPlP2QklEx15xTZVTMNedUGU21XojN6Pr161FQUACDwYDFixfDZrMBAHbs2IHnnnsOcrkcx48fR35+fnQuValUEAQBe/bswW233Yb6+nosXbq0U58hUkOpVCIzMxOLFy+GTqfDokWLsGfPHsjlcvz2t7/F0KFDE3Qqvl8UTzzxxBMXeyO+r9555x04nU48//zzGDduHGbNmoVDhw5h5syZePDBB/Hpp58iFApBrVbj+eefx7p163DTTTdh6dKl6N+/Pz744AMcP34cl112GaZPn45AIIDVq1e3q/HHP/4RGRkZePzxx/HWW2/hiiuuwLJly/C73/0Ob775Jg4dOgSLxYJRo0Z1qnH8+HFs3LgRW7duBQD86Ec/wldffQW5XI7t27fjb3/7G/785z/j5MmTkmocOHAAV1xxBcxmMw4cOIA9e/agrKxMcg2/34+dO3fivffeg8vlkrwv3377LSZMmIDXX38dK1eujF4ckVLjyy+/hEqlwrZt26LHo7a2NmENh8OBv/zlLygtLUVtbS0eeughfPTRRwBaB5+3334br732GqqqqmC327FlyxZYLBYsXLgQ5eXlmDlzJnbs2IGBAwciKysLR48ehV6vx29+8xuUl5fjk08+QWNjI2666SYolUrodDoMHToUeXl57bKxZcsWGI1GDBw4EEqlEvX19Rg5ciTGjh2LFStWQK/XY/r06Th8+DC6du2K+++/v91+nDx5Em+++SZKS0tx6tQpzJ07Fx999FE0G8uWLYNGo8H1118vqcZnn30Wzcb+/fsxY8YM9OrVS3KNSDaWLVuG5cuXIyMjQ1KNTZs2wefzYfPmzfjDH/6AUaNGYdiwYThy5IjoGtu2bYvm69lnn8U111yDUaNGST6mgiDgiy++wLJly6DX63HdddclrDF16lT885//RHl5Obp06YLFixfjzTffjObrhRdegMFgwJQpUyTVeOutt5CTkwO/348TJ05g8eLFSY9pvBpr1qyBVqvF1q1b8eKLL0KpVKJHjx5obGzEvffei9GjR7fL+fXXX4/f//73KCsrQ8+ePREMBnHjjTfim2++QV5eHhwOBzweD4YMGZIw59dffz2eeuop+Hw+/PrXv8YXX3wRHQNnz56NLl264PLLL0ddXZ2kYyElX/FqrF27VlK+4tV47733JOUrUTbONV9vvPFGdAx84YUXUtZINK9IyWiiOUFKRuPV2Lt3b6eMXnPNNfjuu+8k7UvHcbCkpAQOhyNuzjdt2oRhw4bBarVGm0933303SktLUVBQgJaWFhQUFKCwsDBhzjdt2oTMzEz0798f/fv3x9dff40f//jHeP311/HCCy/g2muvhdlsht/vl7QfUrKRan588cUXodVqMXXqVGzZsgUjR47EnXfeKWo8j3yux48fx1NPPYWsrCxJNf7+979HP9eXX34ZCoUCkydPxhdffCG6Ruz89tJLL0GlUuHGG2+UvC+R+e2rr77Cbbfdhn79+kmuERl/XnzxRSxdulTy8Yid31555RWMGDECI0aMwLZt20TXiJ3fnnvuOYwfPx52ux0VFRV4/fXX0bNnz3Y537JlS3TdUlFRAa1Wi5/97GfYv38/unbtipaWFrhcLgwZMgTNzc244447oNPpUq5bCgsLYbPZotn49NNP4XQ64+5HqvnxxRdfhE6nww033JDweKaaH8VkNNX8KCajifZFSkYT7YuUjKaaI8VkNNUcKSajqebISEavvvpqSdsRO0e+9NJL0Ol06NmzZ8Kcx1u3jBs3DuXl5dEv0DidzqQ5jzeeDxgwAGq1GtXV1Zg/fz62bNmClpaWuPuRan4Uk9FU86OYjKaaH8VkNNU5pJiMpjqHFJPReDX2798vKaOpzkPFZDTVXB3JaLJ5VuxcnSzn8c5Dp0+fjq+//hr5+fmixvMdO3bAaDRiwIABCIVCOH36dPQ8dPny5XA6naioqEA4HMakSZM6nU+nWi9UV1fDYrFgzZo1kmrErhf+8Y9/4MMPP8TRo0cl1YhdL7z//vtYv349jhw5InlfIjk/ePAgtFotPvzwQ8k1Ijn/+9//jp/85CeSj0fseuHTTz+Fw+HAjh07JNWIXS+89tprGDBgAL766ivJxzSS840bN+Kdd97B4cOHJdX48MMPozl///338dZbb2Hfvn1QKBTYvXt3p+stic5DIzm/9957MXv2bDidTmRnZ+O3v/1tp2txic5DxeY81XpBTEZTrRfEZDTVekFMRlOtF8RkNNV6QUxGU60XxGQ01XpBTEZTnVNHMpqsRqpz6o0bN+Ltt9/G3r17E+Y83nnovHnzotcVfT4fTpw4gf379yfMebx1S+/evZGTkwOlUomf/vSnWLNmDXQ6Ha655hrJ15zFZDTVekFMRlOtF8RkNNV6ITajBoMBb7/9NhQKBTZs2IBRo0YBAO666y786U9/in5BY9KkSRg5ciTC4TCee+45NDQ0wGw2o7y8HEajERMmTOjUZ4jUuP3223HgwAFUVFRAo9HgL3/5C9atW4dhw4bh0UcfxbRp0+I3Kr5n+PjBC2jChAl48MEHo/+sUCjwzTffYNiwYQCAUaNGYfv27cjNzcWKFSugUCggl8sRDAah0WiwZ88e/OIXv8CDDz6IUaNGYdeuXZ1qRL6VnZubi1WrVqG0tBRyuRyBQABz5syBwWDA2LFj49ZYv3497HZ7tEZWVhbeeOMNGI1GKBQKuN1uFBUVSa6xatUqfPjhh7j00kuhUqlw/fXXS67x7LPPwuVyYdasWSgrK8OPf/zjs9qO0tJS1NXVobGxEU899ZTkGtdddx2CwSCUSiXC4TByc3Oh0+kS1ti4cSO6du0a7eyXlJTghhtuQCgUgkKhAIDoHU7XXXcdAODKK6+E3++Pfq7r1q3DxIkTsXPnTuh0OixZsgRjxoxBeXk5ioqKYDKZcOjQIfziF7/AkCFD0Ldv33bb0LdvX/j9fqjVaoRCIVx99dWYPHkySktLYbVa0atXLygUCuzZswd9+vTB+PHj2+3H119/Hb3TRRAEZGZm4ujRo+2ykZubi+zsbMk1YrNhNpthsVgk14jNhlwuR0VFheQa06ZNQygUwn/9139BLpdj2LBh2Ldvn+R9ieRLqVTinnvukbwdL730EtxuN4LBIPLy8qDT6RLW+Oabb1BSUoKFCxfCaDRG8xibr8jdKzt27JBUY9WqVSgvL8cbb7wBhUKBnJwcyduxatUqqFQqyOVyFBYWAgB8Ph+GDh0KjUbTKedutxszZ86ETCbD0KFDsWLFCtx2220wGo0IBoO45557IAhCwpxHanTr1g02mw1WqzX6mbz66qvIzs5Gr169cPToUUn7ISVfiWpIyVey4yk2X4lqnI98xY6BxcXF0Gq12L59e8Ia8cZRqRlNNJ5LyWiiGh0zun//fkk14o2DHo8nYc5Xr16N8ePHY9euXejevTt+8YtfQCaTIRQKoby8PHrH1h133JEw56tXr4ZCoYje2XXHHXdE5/quXbti586d0Ov1kvZDajZSzY8lJSXQ6XTYsmULzGYzZs6cKXocjf1cu3XrhtLSUsk1Ip9rUVERZDIZ9u7dK6lG7OfapUsX5OTknNV2ROa3jIwMZGdnS64RO/7IZDLU1NRIrhE7/shkMlx55ZXYvXu35H2JjD9yuRz33nsvWlpakJmZCYvF0i7nkTXHpEmTsGvXLowdOxYTJkzApEmT4Ha7EQgEMHfuXAQCAdx8882wWCz40Y9+JGrd8s9//hOjRo1CcXEx+vXrB7fbDYPB0Gk/xMyPJSUlUCgU2Lp1a9xjIXZ+TJZRMfNjqowmqiElo8m2Q2xGxcyRqTIqZo5MlVExc2Qko1K3I3YczM/Ph16vT5jzROuWyJolGAzi5Zdfht/vx4QJE+LmPNF4vnPnTvzHf/wHiouLMXjwYDidzoQ5FzM/pspoqvlRTEZTzY9iMprqHFJMRlOdQ4rJaLwaUjOa6jxUTEZTzdWRjEqtEW+ubmhoSJjzeOehkcwGg0EsX74cXq8XkyZNSpjzdevWQaVSwefzIRAIYMmSJdHz0IKCAvj9fuTk5KCwsLDT+bSY9YIgCPjoo4/OqkYk5263Gy6XC9nZ2ZJqxOa8ubkZPp/vrLYj9lrJl19+KblGbM4PHjyIdevWSa4Rm/NDhw6hvr7+rPYlkvPI0ySk1ojNucvlQktLi+QasTn3+/1oaWlBXl4eevfuHfd6S7zxPDbncrkczc3NuP3229GrV6+41+ISnYeKybmY9UKqjIpZL6TKqJj1QqqMilkvpMqomPVCqoyKWS+kyqiY9UKqjIo5p45k1GazJayR6pw6GAyiqakJ+fn5CXMe7zw09rpiOBzGZ599hl/96lcJcx5v3VJeXo5FixbB7Xbj448/jq49zuaas5iMirnmnCqjqdYLYjKaar0Qm9GsrKzoNf8dO3ZEewKrV6+G3W7Hnj17kJeXB41GE/13amtrsX79eni9Xtx///0J+wyRGgCivYPs7GxotVr4/X44nU4olT+ch/KxqXUBGQwGGI1GOJ1OPPDAA/j1r38NQRAgk8mif97S0gKVShV9bNDixYvRt29f9OjRA06nE1lZWTAajQCA48ePd6oRCATa3frf3NyMxYsX49JLL8Xo0aMRDAZhsVji1sjJyQEAOBwOOBwOTJ06NfoNrJtvvhknT57Ez3/+c8k1Kisr4XK5UF5ejszMTAwYMEByDbvdDq1Wi8LCQvzkJz/Bhg0b4Pf7Je9Lc3MzZs2ahUGDBmHs2LGSt2P48OFoamrC008/jV69eqGurg6BQCBhDZVKhX379uHw4cNQqVTIzs6OLuojn0tubi5CoRCsViucTifmzZsHvV4f/VyVSiVqa2tRU1ODrKws9OjRA3q9Hk1NTejfvz9UKhWcTie+/fZbfPnll7jmmmvabYPL5YLRaIxmw2w2RxdmO3fuxODBg6FQKFBZWRld0MbuRzgchslkiuYLANxud7tsVFdX46abbpJcIzYbVqsVubm5kmvEZmP8+PFYuXIlysrKJNUAAKfTCbvdjvHjx2PFihUoLy+XfDwi+Ro4cCB69eoleV8iDdARI0bgxIkTmDlzZsIagiCgT58+KC4uRjgcRjAYjN6mHMnXwIEDYbPZJNfIz89HKBTCsmXLoFKp0KNHD8k1ioqK4HK58PTTT8Pj8eC2225DXV0djh49inHjxnXK+SWXXILi4mKEQiGYTKboI1VqamoQDAaxZMkSWK3WhDmP1JDL5QiHw1AqlcjPz0d9fT3effddjB49GiaTKboNYvdDSr4S1ZCSr2Sfidh8JapxPvIVOwYWFRWhqqoKVVVVCWvEG0elZjTReC4lo/FqxMtodXW15O3oOA5GasTLeXZ2NgwGA5qamnDkyBHceuutcLlcaG5uxtixY/Hqq6/i4MGD2L9/f8KcZ2dnIxAIoLq6Grt27cIdd9wRnevlcjnuvvtuHD9+XNJ+SM1Gqvmxe/fuqKiowK5du5CdnY2CggLR42js59rU1ITt27dLqhH7uba0tODqq69GaWmp5O2IfK5VVVUYPny45O2Ind8sFgtcLpfkGrHjz7hx47B8+XJs27ZNUo3Y8WfcuHF46aWXJNfoOP643W7s3LkT2dnZ0Gg07XIeWXMYDAZ4vV7YbLbouO7z+VBWVobHH38cZrMZjz/+OHJycmC1WkWtW0KhEF577TX06dMHR44cQUtLS/RikZjxK3bs6devH9RqdXQ/xNaQklEx82OqjCbbDrEZTVRDSkbFzJGpMipmjkyVUbFzpNvtlrwvseNgZWVl9EJ+vJwnWrcMGDAADQ0NuOSSS6DRaNDS0oLFixfHzXmi8dzj8WD79u3o168fmpqa4HK5EuZczPyYKqOp5kcxGU01P4rJaKpzSDEZTXUOKSaj8WpIzWiq81AxGU01V0cyKrVGvLn6yy+/TJjzeOehfr8fzc3N6Nu3L0pKShAKhbBo0aKEOVcqlWhqasK2bduQlZWFfv36obm5Gdu2bUNLSwtMJhO8Xi+0Wm2n8+lU64Vnn30WgiDgmWeekVwjkvMFCxagsrISd955J/x+v+TtaGlpwdSpU1FVVYV7771X8nZEcn7kyBH4/X788pe/lFwjkvP8/HyYTCY4nc7ooz/F1ojkPHJdw+l0wu12Sz4ezc3N+NWvfgWtVotnn31W8r5Ecn7llVeisrISDz/8sOQakZwvWLAADocD4XAYgUAAWq027vWWeON5JOc9e/bEypUrodPpoNPpoheHxZyHis15qvWCmIymWi+IyWiq9YKYjKZaL4jJaKr1gpiMploviMloqvWCmIymOqeOzWiyGsnOqRcuXIimpib07NkTPp8vYc7jnYdGriv27t0bHo8H3bt3h9VqTZjzeOuWlpYWLFu2DI2NjTCZTLBYLNFr32L2Q2pGk60XxGY02XpBbEaTrRc6ZjSS38g1/4js7GwAQGVlJQ4dOoTrrrsu+u+88sorUKlUWLhwYfSGiHgiNT766COUlpbiuuuui74GYeLEibjzzjsxY8aMhP/9980Pp33xoqB9AAATSklEQVR3kdTU1ODee+/FLbfcgmuvvRa///3vo38WeYYo0HpHw7x582AwGDB//nwAiD5DvKamBjNnzoTVasXAgQPR2NiI22+/HZMnT4ZKpYJarQYANDQ0RL/REamhVCrh9XpRU1MTvVD12muvRWvY7XY0NDRg+PDh0Gg00ffXXHLJJfjf//1f3HLLLZDJZJJqrFmzBn6/Hxs2bEA4HMbvf/97CIIgqYZcLodMJoPH48GiRYswZ84c7Nq166z25dixY9i8efNZHY++fftCJpPh/fffx7hx49CvXz9UVlYmrTF58mT07ds3OjBFvo0R+VwiE1JdXR1+/vOfo2vXrggEAvB4PJg2bRrUajV69uyJ/Px8dO3aFS+//DIqKiqgVCoxf/58fPzxx3A4HFi3bh3+53/+B3fddRc0Gg1ee+011NfX44EHHkBNTQ3y8vKgVqvhcrmgVCrbZWPjxo2ora3FkiVL0NDQ0G4/Is+3Xb9+PVQqFcLhMMxmczRfkWxMmjQJPp8PS5cuFV2jYzbmzZsHj8cTvdVWTI2O2Yg8A/j5558XXSMcDkfvaFy0aBEmT56M2tpaSdsROR6RfK1atUryMV2zZg0EQcDEiRMxd+5c/PSnP4Xf78ezzz7bqUZsvuRyeXSilMlk7fI1ZswYeL1eSTVixw6DwZB0X5LVcLlc+OCDD3DzzTdDo9GgtrYWjzzyCO66666EOVcoFPB6vfD5fHjooYegVCrx1ltvwePx4Morr8Qbb7yBpUuXdsr5tGnTcOONN0a/zRbZBqfTCYVCgbKyMhw4cAAejwePPfaY6P2Qkq9ENSLbJCZfqT4TMflKVON85KvjGJiZmQmHw5G0Rsdx9Gwymmg8l5LReDXiZVRqjXjj4GOPPZYw56FQCD6fL/p89U2bNrVbsCoUCqxfvx4vvPBCwpw3NjbC5XLhww8/hMvlgtvthtPphM/nQ0NDg+T9+NOf/iQ5G6nmx4EDB8JgMMBqtWLJkiX4+9//LnocjXyugwcPxqhRo2A0GiXViP1c77//fjgcDsk1Oq59LrvsMmRnZ4uu0XF+e/vttzFkyBB06dJFdI14a5/6+np07dpVdI2O89t9990Hp9OJ/Px8yccjMv4YDAaMGjUKcrkcU6ZMwdChQ6M5f+CBB3DkyBF89NFH0Ol0aGpqgs1mwx133AGFQoHS0lJ4vV6MGTMGS5YswdatW3HdddeJWrcEg0FYrVZ89913UKvVsFgs6NGjR6f9EDs/Tp06FVdeeWX0HaliakjJqNj5MVlGU22HmIwmmxPEZlTsHJkso2LnyGQZFTtHRjIq5Zh2nCNvv/12DBs2DHq9vlPOE61b3nrrLahUKnz33Xd49dVXkZGRgSVLlmDTpk2dcp5oPI9883v+/PlQKBQwGo3o3r17wv1INT+KyWiq+VFMRsWcQ6bKaKpzSDEZFXMOmSqjHWucTUZTnYeKyWiquTqSUbvdLrpGorlao9EkzXnseejnn38OuVwevb6gUCiwePFifPbZZwlznpGRgd69e6NHjx54/vnn4Xa7UVZWBrPZjLKysujjMp955hm89957ouelsrIyAMDs2bNRWVkpuYbL5cLGjRthMBiwd+/es6rhdruRkZGBkpISPPvss9F3o4itEcn5u+++C7/fj0cffRQymUxSjUjOKyoqYLVacerUKTgcDtTU1IiuEVkvVFVVwWq1oq6uDg6HA9XV1ZKPR+Q9PWfzuUTG4kGDBqGurg5PP/205GMayfl7770HuVwOpVKJ6upq1NTUYNKkSRgyZEjK8TzyaMnRo0fj5Zdfhsfjwdq1a9Hc3IyJEyeKOg8Vm/NU6wUxGU01P4rJaKr1gpiMploviMloqvWCmIymOh5iMppqvSAmo6nOqTtm9OTJkwlrJDqnjmTs22+/hUwmQ21tbcKcdzwPnT17NpRKJUaPHo13330X3333Hf7whz+gsbExYc7jnYcePnwYzc3NOHjwINxuN/bt2yd6PyLzo5SMJlovSMloovWClIwmWi/Ey+grr7wSvbngpptuglwuh1qtht1uj567R74QZTKZ8I9//ANWqxWzZ89Gc3Mz6urq8Morr0Cv10fn+2eeeQY5OTnRO9VWrFgBjUaDtWvXwm63409/+hNcLhduueUWDBkyJNqI+z7jnVoXUH19PWbMmIGHHnoIN954I4DWway0tBQAsHnzZlx22WUQBAGzZs1C7969sWDBgmhX9tJLL8UHH3yAGTNmYPTo0bj66qvRvXt3XHXVVbjvvvtw0003Re/YEgQBM2bMQHFxcbsamZmZ2L17N2bMmIHrr78eU6dOxfr163HVVVdFL76VlJRArVZDEARMmzYNGo0GCxYsgF6vh1KphMVikVSjqqoKAwYMwNatWzFq1Cg89NBDyM3NlVTj1ltvhUwmw4IFC+D1evHtt98iKytLUo0ZM2YgLy8Pl19+OQwGw1kdj9tuuw3Z2dnYtm0b7rnnHshksoTbMXLkSDQ2NmL8+PGQyWRQKBSQyWR45513oFKp8MQTT+DkyZMIh8PRW9QfeughjB8/HlOmTMFVV12F2bNnIxQKwe12Y8iQIaipqcEHH3wApVKJSZMmRR8LKQgCrrjiCsyZMwejR4/GT3/6U6xfvx5jxozB3LlzkZmZCb/fD0EQsGXLFmzYsCGajVdeeQWBQAD/7//9P2zfvj3uscjKysLw4cMBAKdOncLQoUPbZWP16tXwer24+eabJdWIzUZOTg4KCgpw9913S6oRm40XX3wRVVVV+PnPfy6pxl//+lcoFAo88sgjeOmll3DixAnJNWLz9dprr2H37t2Sj+natWthNpuxcOFCrFmzBj6fDzfccEPCGpGf+8jPvCAI7fK1ZMkSuN1u3HXXXZJqxI4dHo8n5b7Eq3HHHXcgHA5HG1O7d+/G9OnTsWjRok45nzNnDlavXo1gMIjMzEzs378fs2bNQmNjI7Kzs6FQKLBq1SoAwODBg+PmfM6cOXHHwH79+mH79u0YOXIkzGYzpkyZgqqqKtH7ITVf8WpIzVeiz0RKvuLVOB/5ih0D9Xo9nE5n0nzFG0elZjTReC4lo/FqxMuo1BrxxsFrr702Yc5HjBiB2tpajBs3Dnv37sWsWbOQmZkJnU6HYDCIF154AT6fD1deeWXCnNfX18PpdOLyyy+H1WqNHotbb70VcrkcX331leT9kJqNZPPj1q1b8fXXXyMUCmH48OGorKzEhg0bRI+jxcXFePLJJ9HU1ISmpiZceumlkmpEPtff/OY32LFjx1nViHyuTz75JH71q19BJpOhf//+kmpE5rctW7YAAGbNmoXRo0dLqhEZf5588knccsstOHToUPRboWJrRMafefPm4dZbb8WRI0dwxRVXSP5c8vLycNlll+GXv/xl9BudmzdvxsiRI9vlfO7cuSgsLERjYyMGDx6Mjz/+GB9//DE0Gg26desGlUqFe+65B3q9Hv/4xz/wf//3fygsLBS1bikoKMDNN98MmUyG6dOnw2Qyobq6Ou5+JJsf58+fj2nTpiEQCCQ9FsnmR7EZTTY/is1ovBpSMxqvhtSMJpsjxWY02RwpNqPJ5sjYjEo9ppFx8KmnnsKsWbOgUCjQtWvXuDlPtG7x+XwYOHAg1qxZg/3798NgMGDz5s1xc55oPO/WrRt0Oh1uv/12HD58GFqtFrW1tXH3I9n8KDajyeZHsRlNNj+KzWiyc0ixGU12Dik2o/FqSM1osvNQsRlNNlfHZrR3796SasSbq/v37x8354nOQ+12OzIyMgAAN954I9RqNbZv3x4357Nnz8bf/vY3hEIhAIBer4+eh65cuRIbNmyAxWLBtddeC5vNho8//ljSemHlypWw2WxYvXq15BqRnD/66KPYvn37WdWI5HzlypV45513UFhYiKuvvlpSjUjOd+3ahSlTpuCFF17AlClTJNWI5HzlypV48803YbPZMGHCBEk1Ijlfvnw51q5di4yMDEycOFHy55KXl4crr7wSGzduPKtjGsn5q6++ivfeew9FRUUYM2aMpBqRnO/evRvvvvsu+vTpg3HjxkXv1hYznkdyPn78ePzhD3+AzWZDv379EAwGMXXqVFHnoVJynmy9IDajydYLYjOabL0gNqPJ1gtiM5psvSA2o8nWC2Izmmy9IDajyc6pYzM6efLkhDWSnVOvWLECf/zjH9G1a9ekOY93Hhq5rjhhwgRYrVbcfffd6NOnT8Kcx1u3RJ4qtmDBAnzyySdJj2ey9YLYjCZbL4jNaLL1gtiMJlsvdMxodnY27r77bnTp0gVTpkzB+vXrsXbtWowYMSJ6LXbfvn0AWvsCJSUl6N+/PzZs2IDVq1dj3rx5uOKKK3D33Xfjtttuw+rVq7F69Wrk5ORg+fLl2L17N1atWgWbzQYAMJvN0Ov1UCgUMBgM0S8J/hDIBEEQLvZGfF8tXLgQH3zwAYqKiqK/98gjj2DhwoUIBAIoKirCwoUL8cknn2DOnDkYPHhw9N+bM2cOLrnkEkyePBnV1dXQ6XQoLi6GWq1uV6N79+7weDw4evQoysvLMWjQoOidW3PmzMEbb7yB0tJSNDQ0tKsxa9Ys3HnnndHbqiPPZm1oaIDNZoPP54MgCLjllltQW1sruUZkO8rKynDXXXfhm2++kVzDbrfD7XZDJpPhnnvuwZEjRyTXiByf7t27n/XxMJvN0WcrP/7449i8eXPcGo888gjmzp0b/byUSiV0Oh2OHTuGnJwctLS0QBAE/Od//if+/Oc/o6qqClqtFjKZLHoyunDhQtTX16OxsRGFhYUoLy9HU1MTjEYjiouLo8+4HzBgQPRWW7VajT59+rTLRmNjY/SZwQqFAk1NTRg0aBBkMhn27dsHuVyOwYMH4+uvv0YgEIDBYGi3Hw8//DCOHTsGtVoNq9UKmUyG8vJy2Gw2eDweuN1uZGVloVu3bpJrRLZj79696NKlC/Ly8iTXsNvt0W+J5ObmIj8/X3KNvLw8NDQ0wOPxIDs7G127dpVco3v37nC5XKivr0dxcTEyMjLO6Zja7XZ07949YY3Iz73D4UBWVhYaGxtRXl6OnJwcNDc3Rx8DkZubK7lG7OdSUlKSdF/i1SgrK4NcLo82PrRaLQwGAxoaGqBWq6FWq9vlPDIG+v1+HDhwIPoyTLVaHT0eeXl5cDgcCXMeGQN37twJQRBw8uTJdjk3Go3IyclBVVWVpGMhJV+JakjJV6IaUvKVqMb5yJfZbEYgEIg+Oz4rKytujWTjqNiMpppXxGQ0UQ2Hw9EpoyUlJfj2228lbUfHcVAmk+HUqVOdcj5//nx89dVX0btLDh8+DJfLBZPJFP12q8fjiT42M17OY2tE7nj2er0YPHgwGhsbUVFRcVbHouN+JMuGmPkxHA4jKysLdrsdhw4dgt/v7zQ/JpsT1Go19uzZgx49esBsNkuqERl7DAYDgsEgBEFASUlJ9BuyYrcjsvaJPP6ua9euZ70vBw8ehNFoRJcuXSTXiKx9QqEQLBYL8vLyJNfIy8vD6dOnEQqFkJGRgYKCAsk1Iusns9kMQRDQ1NQEh8MBnU4HuVzebjyPrDlyc3PR0NCAurq66Hju8/mij/A4ffo0/H4/DAZD9IQw2bpl4MCBqKysjK4Fi4qKUFFREXc/ks2PLS0tCAaDsNvtyMnJSXgsks2PYjOabH4Um9Fk47nYjKbaFzEZTTZHis1osjlSbEaTzZGxGZX6uXQ8piaTCTKZLGHOE61bIu9Dtlqt0Ol0qKysjJvzZON55Ju9giCgsLAQx48f77QfYs67UmU01fwoJqNiziFTZVTMvqTKqJhzyFQZTVZDbEbFnIemyqjYY2oymdCtWzfJNTrO1R6PJ2HOE52HRh6PZDQaodfrUV1dnXA8j9QQBCG6foy9RnH48GE888wzePDBB89qjv3yyy/x+uuvo6WlRVKN2LEYAAoKCnD77bdj4cKFZ7VeiFwrGTZs2FnvS+RaSXFxseQaHa+VXHLJJZJrRHIOAHe0vd9Vao2O11ukfi4dj+kNN9yAUaNGSa7R8ZrNhx9+iE8//RR6vb7T9ZZE43kk5zk5OXj00Ufx8MMP49SpU9FrMWLOQ8XmPNV6QUxGU81tYjKaar0gJqOp1gtiMppqvSAmo6nWC2IyKuaYpsposnPq2IxaLJa4NVKdU8deV9yyZUvcnCc7D438PYcPH8bnn3+O8ePHx815onVLfn4+amtrodfrUVBQgFAoFL3ecrbXnBNlVMo150QZlXLNOVFGxawXYjP62GOPIS8vDyqVCkuWLEFWVhbq6+sxZswY9O3bF0qlEmVlZTAajcjLy8M111yDo0eP4pFHHgEAlJaW4s0338TSpUvb9Rhia2g0GgDAxIkTMW3aNDz55JM4cuQIQqEQJk2ahDvvvPN8tTbSGptaRERERERERERERERElPb4+EEiIiIiIiIiIiIiIiJKe2xqERERERERERERERERUdpjU4uIiIiIiIiIiIiIiIjSHptaRERERERERERERERElPbY1CIiIiIiIiIiIiIiIqK0x6YWERERERERERERERERpT02tYiIiIiIiIiIiIiIiCjtsalFREREREREREREREREae//AyZxUZiVGfpgAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 2160x1440 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(30,20))\n",
    "sns.lineplot(data=covid[covid.confirmed != ''].confirmed.value_counts())\n",
    "plt.title(\"Number of confirmed cases per day\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 244,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2020-02-04     1\n",
       "2020-02-07     1\n",
       "2020-02-09     4\n",
       "2020-02-10     1\n",
       "2020-02-11     2\n",
       "              ..\n",
       "2020-04-24    38\n",
       "2020-04-25    46\n",
       "2020-04-26    58\n",
       "2020-04-27    35\n",
       "2020-04-28    33\n",
       "Name: discharged, Length: 77, dtype: int64"
      ]
     },
     "execution_count": 244,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "covid[covid.discharged != ''].discharged.value_counts().sort_index()\n",
    "\n",
    "#Last updated : 2020-04-28"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 238,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Number of discharged cases per day')"
      ]
     },
     "execution_count": 238,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 2160x1440 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(30,20))\n",
    "sns.lineplot(data=covid[covid.discharged != ''].discharged.value_counts())\n",
    "plt.title(\"Number of discharged cases per day\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 226,
   "metadata": {},
   "outputs": [],
   "source": [
    "def temp(row):\n",
    "    if row.age > 70:\n",
    "        return \"age > 70\"\n",
    "    elif row.age >50:\n",
    "        return \"50 < age < 70 \"\n",
    "    else:\n",
    "        return \"age < 50\"\n",
    "    \n",
    "age_death = covid[covid.death != ''].apply(temp, axis='columns').value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 390,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x15c96777a88>"
      ]
     },
     "execution_count": 390,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,10))\n",
    "sns.barplot(age_death.index,y = age_death.values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 391,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x15c96818f48>"
      ]
     },
     "execution_count": 391,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "age_death.plot.pie(y='values', figsize=(10, 10))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 375,
   "metadata": {},
   "outputs": [],
   "source": [
    "nationality_extract = covid[covid.nationality != ''].nationality.value_counts()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 368,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "925"
      ]
     },
     "execution_count": 368,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "761 + 87 + 77"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 376,
   "metadata": {},
   "outputs": [],
   "source": [
    "nationality_extract = nationality_extract[:9]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 379,
   "metadata": {},
   "outputs": [],
   "source": [
    "nationality_extract['Other'] = 925"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 387,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x15c96706408>"
      ]
     },
     "execution_count": 387,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nationality_extract\n",
    "nationality_extract.plot.pie(y='values', figsize=(10, 10))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6553"
      ]
     },
     "execution_count": 179,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "covid[covid.nationality != ''].nationality.value_counts().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 194,
   "metadata": {},
   "outputs": [],
   "source": [
    "transmission_extract= covid[covid.transmissionSource != ''].transmissionSource.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 198,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Transmission Source')"
      ]
     },
     "execution_count": 198,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10,10))\n",
    "sns.barplot(x=transmission_extract.index,y = transmission_extract.values)\n",
    "plt.title(\"Transmission Source\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 253,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>title</th>\n",
       "      <th>confirmed</th>\n",
       "      <th>discharged</th>\n",
       "      <th>hospital</th>\n",
       "      <th>nationality</th>\n",
       "      <th>residenceAreas</th>\n",
       "      <th>placesVisited</th>\n",
       "      <th>age</th>\n",
       "      <th>death</th>\n",
       "      <th>transmissionSource</th>\n",
       "      <th>gender</th>\n",
       "      <th>linkedClusters</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>case-1</td>\n",
       "      <td>Case 1</td>\n",
       "      <td>2020-01-23</td>\n",
       "      <td>2020-02-19</td>\n",
       "      <td>Singapore General Hospital</td>\n",
       "      <td>Chinese</td>\n",
       "      <td>[Shangri-La Rasa Sentosa Resort &amp; Spa]</td>\n",
       "      <td>[]</td>\n",
       "      <td>66</td>\n",
       "      <td></td>\n",
       "      <td>Imported</td>\n",
       "      <td>Male</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>case-2</td>\n",
       "      <td>Case 2</td>\n",
       "      <td>2020-01-24</td>\n",
       "      <td>2020-02-07</td>\n",
       "      <td>National Centre for Infectious Diseases</td>\n",
       "      <td>Chinese</td>\n",
       "      <td>[J8 hotel, 8 Townshend Road]</td>\n",
       "      <td>[Raffles Hospital, Tan Tock Seng Emergency Dep...</td>\n",
       "      <td>53</td>\n",
       "      <td></td>\n",
       "      <td>Imported</td>\n",
       "      <td>Female</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>case-3</td>\n",
       "      <td>Case 3</td>\n",
       "      <td>2020-01-24</td>\n",
       "      <td>2020-02-21</td>\n",
       "      <td>Singapore General Hospital</td>\n",
       "      <td>Chinese</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td>37</td>\n",
       "      <td></td>\n",
       "      <td>Imported</td>\n",
       "      <td>Male</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>case-4</td>\n",
       "      <td>Case 4</td>\n",
       "      <td>2020-01-25</td>\n",
       "      <td>2020-02-12</td>\n",
       "      <td>Sengkang General Hospital</td>\n",
       "      <td>Chinese</td>\n",
       "      <td>[Village Hotel Sentosa]</td>\n",
       "      <td>[USS, Vivocity]</td>\n",
       "      <td>36</td>\n",
       "      <td></td>\n",
       "      <td>Imported</td>\n",
       "      <td>Male</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>case-5</td>\n",
       "      <td>Case 5</td>\n",
       "      <td>2020-01-27</td>\n",
       "      <td>2020-02-18</td>\n",
       "      <td>National Centre for Infectious Diseases</td>\n",
       "      <td>Chinese</td>\n",
       "      <td>[Ceylon Road]</td>\n",
       "      <td>[Tan Tock Seng Hospital]</td>\n",
       "      <td>56</td>\n",
       "      <td></td>\n",
       "      <td>Imported</td>\n",
       "      <td>Female</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14946</th>\n",
       "      <td>case-14947</td>\n",
       "      <td>Case 14947</td>\n",
       "      <td>2020-04-28</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14947</th>\n",
       "      <td>case-14948</td>\n",
       "      <td>Case 14948</td>\n",
       "      <td>2020-04-28</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14948</th>\n",
       "      <td>case-14949</td>\n",
       "      <td>Case 14949</td>\n",
       "      <td>2020-04-28</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14949</th>\n",
       "      <td>case-14950</td>\n",
       "      <td>Case 14950</td>\n",
       "      <td>2020-04-28</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14950</th>\n",
       "      <td>case-14951</td>\n",
       "      <td>Case 14951</td>\n",
       "      <td>2020-04-28</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td></td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>14951 rows × 13 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "               id       title   confirmed  discharged  \\\n",
       "0          case-1      Case 1  2020-01-23  2020-02-19   \n",
       "1          case-2      Case 2  2020-01-24  2020-02-07   \n",
       "2          case-3      Case 3  2020-01-24  2020-02-21   \n",
       "3          case-4      Case 4  2020-01-25  2020-02-12   \n",
       "4          case-5      Case 5  2020-01-27  2020-02-18   \n",
       "...           ...         ...         ...         ...   \n",
       "14946  case-14947  Case 14947  2020-04-28               \n",
       "14947  case-14948  Case 14948  2020-04-28               \n",
       "14948  case-14949  Case 14949  2020-04-28               \n",
       "14949  case-14950  Case 14950  2020-04-28               \n",
       "14950  case-14951  Case 14951  2020-04-28               \n",
       "\n",
       "                                      hospital nationality  \\\n",
       "0                   Singapore General Hospital     Chinese   \n",
       "1      National Centre for Infectious Diseases     Chinese   \n",
       "2                   Singapore General Hospital     Chinese   \n",
       "3                    Sengkang General Hospital     Chinese   \n",
       "4      National Centre for Infectious Diseases     Chinese   \n",
       "...                                        ...         ...   \n",
       "14946                                                        \n",
       "14947                                                        \n",
       "14948                                                        \n",
       "14949                                                        \n",
       "14950                                                        \n",
       "\n",
       "                               residenceAreas  \\\n",
       "0      [Shangri-La Rasa Sentosa Resort & Spa]   \n",
       "1                [J8 hotel, 8 Townshend Road]   \n",
       "2                                          []   \n",
       "3                     [Village Hotel Sentosa]   \n",
       "4                               [Ceylon Road]   \n",
       "...                                       ...   \n",
       "14946                                      []   \n",
       "14947                                      []   \n",
       "14948                                      []   \n",
       "14949                                      []   \n",
       "14950                                      []   \n",
       "\n",
       "                                           placesVisited age death  \\\n",
       "0                                                     []  66         \n",
       "1      [Raffles Hospital, Tan Tock Seng Emergency Dep...  53         \n",
       "2                                                     []  37         \n",
       "3                                        [USS, Vivocity]  36         \n",
       "4                               [Tan Tock Seng Hospital]  56         \n",
       "...                                                  ...  ..   ...   \n",
       "14946                                                 []             \n",
       "14947                                                 []             \n",
       "14948                                                 []             \n",
       "14949                                                 []             \n",
       "14950                                                 []             \n",
       "\n",
       "      transmissionSource  gender linkedClusters  \n",
       "0               Imported    Male             []  \n",
       "1               Imported  Female             []  \n",
       "2               Imported    Male             []  \n",
       "3               Imported    Male             []  \n",
       "4               Imported  Female             []  \n",
       "...                  ...     ...            ...  \n",
       "14946                                        []  \n",
       "14947                                        []  \n",
       "14948                                        []  \n",
       "14949                                        []  \n",
       "14950                                        []  \n",
       "\n",
       "[14951 rows x 13 columns]"
      ]
     },
     "execution_count": 253,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "covid"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 258,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "National Centre for Infectious Diseases    1983\n",
       "0                                          1716\n",
       "National University Hospital                585\n",
       "Khoo Teck Puat Hospital                     461\n",
       "Singapore Expo and MAX Atria (CIF)          444\n",
       "Ng Teng Fong General Hospital               392\n",
       "Singapore General Hospital                  349\n",
       "Changi General Hospital                     279\n",
       "Sengkang General Hospital                   225\n",
       "Alexandra Hospital                           58\n",
       "KK Women's and Children's Hospital           43\n",
       "TTSH                                         20\n",
       "KK Women’s and Children’s Hospital           12\n",
       "Mount Elizabeth Hospital                      4\n",
       "Mount Alvernia Hospital                       3\n",
       " Singapore General Hospital                   3\n",
       "Parkway East Hospital                         3\n",
       "Gleneagles Hospital                           2\n",
       "MEN                                           2\n",
       "Sengkang Hospital                             1\n",
       "Tan Tock Seng Hospital                        1\n",
       "Mount Elizabeth Novena Hospital               1\n",
       "RH                                            1\n",
       " Mount Elizabeth Hospital                     1\n",
       "Farrer Park Hospital                          1\n",
       "Khoo Teck Phuat Hospital                      1\n",
       "Name: hospital, dtype: int64"
      ]
     },
     "execution_count": 258,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "covid[covid.hospital != ''].hospital.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "data = read_json('locations.json')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'cluster'"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data['features'][0]['properties']['type']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "locations_cluster = []\n",
    "weights_cluster =[]\n",
    "locations_hospital = []\n",
    "weights_hospital =[]\n",
    "for dic in data['features']:\n",
    "    if dic['properties']['type'] == 'cluster':\n",
    "        locations_cluster.append(tuple(dic['geometry']['coordinates'][0][0][::-1]))\n",
    "        if 'caseCount' in dic['properties']:\n",
    "               weights_cluster.append(((dic['properties']['caseCount'])))\n",
    "        else:\n",
    "               weights_cluster.append((len(dic['properties']['cases'])))\n",
    "    if dic['properties']['type'] == 'hospital':\n",
    "        locations_hospital.append(tuple(dic['geometry']['coordinates'][0][0]))\n",
    "        weights_hospital.append(float(len(dic['properties']['cases'])))\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[23,\n",
       " 23,\n",
       " 9,\n",
       " 10,\n",
       " 3,\n",
       " 5,\n",
       " 14,\n",
       " 45,\n",
       " 6,\n",
       " 5,\n",
       " 3,\n",
       " 27,\n",
       " 11,\n",
       " 8,\n",
       " 4,\n",
       " 2302,\n",
       " 10,\n",
       " 9,\n",
       " 203,\n",
       " 13,\n",
       " 7,\n",
       " 114,\n",
       " 6,\n",
       " 8,\n",
       " 5,\n",
       " 6,\n",
       " 82,\n",
       " 901,\n",
       " 131,\n",
       " 283,\n",
       " 5,\n",
       " 90,\n",
       " 210,\n",
       " 323,\n",
       " 5,\n",
       " 108,\n",
       " 210,\n",
       " 167,\n",
       " 107,\n",
       " 5,\n",
       " 30,\n",
       " 31,\n",
       " 313,\n",
       " 72,\n",
       " 101,\n",
       " 896,\n",
       " 40,\n",
       " 44,\n",
       " 8,\n",
       " 79,\n",
       " 7,\n",
       " 7,\n",
       " 7,\n",
       " 12,\n",
       " 13,\n",
       " 118,\n",
       " 89,\n",
       " 202,\n",
       " 28,\n",
       " 176,\n",
       " 8,\n",
       " 303,\n",
       " 47,\n",
       " 144,\n",
       " 230,\n",
       " 123,\n",
       " 8,\n",
       " 95,\n",
       " 98,\n",
       " 237,\n",
       " 68,\n",
       " 136,\n",
       " 74,\n",
       " 26,\n",
       " 281,\n",
       " 300,\n",
       " 17,\n",
       " 46,\n",
       " 133,\n",
       " 100,\n",
       " 148,\n",
       " 15,\n",
       " 62,\n",
       " 57,\n",
       " 23,\n",
       " 17,\n",
       " 133,\n",
       " 33,\n",
       " 16,\n",
       " 61,\n",
       " 96,\n",
       " 60,\n",
       " 14,\n",
       " 12,\n",
       " 323,\n",
       " 203,\n",
       " 91,\n",
       " 46,\n",
       " 32,\n",
       " 71,\n",
       " 23,\n",
       " 27,\n",
       " 6,\n",
       " 5,\n",
       " 6,\n",
       " 102,\n",
       " 68,\n",
       " 27,\n",
       " 15,\n",
       " 78,\n",
       " 7,\n",
       " 58,\n",
       " 23,\n",
       " 24,\n",
       " 31,\n",
       " 22,\n",
       " 29,\n",
       " 64,\n",
       " 4,\n",
       " 15,\n",
       " 6,\n",
       " 4,\n",
       " 8,\n",
       " 11,\n",
       " 9,\n",
       " 22,\n",
       " 68,\n",
       " 19,\n",
       " 15,\n",
       " 16]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weights_cluster"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(1.2942341, 103.8162054),\n",
       " (1.3649022, 103.7472061),\n",
       " (1.3109204, 103.8616363),\n",
       " (1.327888, 103.8906279),\n",
       " (1.30679, 103.8331),\n",
       " (1.406049, 103.864784),\n",
       " (1.2884919, 103.7789882),\n",
       " (1.3347785, 103.7056551),\n",
       " (1.3106196, 103.8631139),\n",
       " (1.3445999, 103.7755481),\n",
       " (1.3705046, 103.8458113),\n",
       " (1.3281944, 103.9384597),\n",
       " (1.30674, 103.778623),\n",
       " (1.3190448, 103.8933889),\n",
       " (1.4375866, 103.8415606),\n",
       " (1.416786, 103.895337),\n",
       " (1.332753, 103.787398),\n",
       " (1.286358, 103.848909),\n",
       " (1.3365402, 103.7512038),\n",
       " (1.3305125, 103.8394219),\n",
       " (1.409748, 103.74348),\n",
       " (1.3103732, 103.854922),\n",
       " (1.2801398, 103.8427344),\n",
       " (1.3016827, 103.649821),\n",
       " (1.2842924, 103.8607721),\n",
       " (1.2891531, 103.8517852),\n",
       " (1.2839472, 103.8496109),\n",
       " (1.3785975, 103.7168933),\n",
       " (1.3380759, 103.7520908),\n",
       " (1.4612032, 103.8172741),\n",
       " (1.3168435, 103.8940056),\n",
       " (1.3667094, 103.9284585),\n",
       " (1.4600462, 103.8190869),\n",
       " (1.4317819, 103.7588166),\n",
       " (1.2851428, 103.8514774),\n",
       " (1.3369676, 103.8836988),\n",
       " (1.4070668, 103.7532526),\n",
       " (1.4561891, 103.7970409),\n",
       " (1.4662909, 103.8121602),\n",
       " (1.3064424, 103.8621448),\n",
       " (1.2968791, 103.7813658),\n",
       " (1.4615273, 103.8091554),\n",
       " (1.45571, 103.789192),\n",
       " (1.318409, 103.732034),\n",
       " (1.3387045, 103.7547235),\n",
       " (1.31391, 103.62511),\n",
       " (1.4542005, 103.7971326),\n",
       " (1.3105425, 103.8664298),\n",
       " (1.282092, 103.8571588),\n",
       " (1.2979605, 103.8446328),\n",
       " (1.306076, 103.8283532),\n",
       " (1.3057434, 103.8310242),\n",
       " (1.3004786, 103.8491438),\n",
       " (1.3359025, 103.9073664),\n",
       " (1.3036773, 103.8591533),\n",
       " (1.3092534, 103.6295192),\n",
       " (1.4349154, 103.7479273),\n",
       " (1.419396, 103.896221),\n",
       " (1.333507, 103.692091),\n",
       " (1.3280277, 103.6941373),\n",
       " (1.321423, 103.853437),\n",
       " (1.410755, 103.7693252),\n",
       " (1.3375424, 103.9033104),\n",
       " (1.4522285, 103.7925308),\n",
       " (1.4522285, 103.7925308),\n",
       " (1.418464, 103.744949),\n",
       " (1.41651, 103.74783),\n",
       " (1.2710161, 103.6314368),\n",
       " (1.3206699, 103.7291997),\n",
       " (1.3159822, 103.7303663),\n",
       " (1.412573, 103.750545),\n",
       " (1.3377867, 103.9082644),\n",
       " (1.2705173, 103.6357002),\n",
       " (1.3118392, 103.6565574),\n",
       " (1.45017, 103.79431),\n",
       " (1.3124611, 103.9964391),\n",
       " (1.3254544, 103.8956326),\n",
       " (1.31718, 103.72788),\n",
       " (1.4638975, 103.8160426),\n",
       " (1.3286633, 103.676063),\n",
       " (1.45125, 103.79715),\n",
       " (1.42085, 103.74093),\n",
       " (1.35808, 103.96484),\n",
       " (1.3268243, 103.6759091),\n",
       " (1.39912, 103.75343),\n",
       " (1.43489, 103.74646),\n",
       " (1.2985395, 103.6278902),\n",
       " (1.2990645, 103.6280879),\n",
       " (1.3003565, 103.6285662),\n",
       " (1.4665011, 103.807495),\n",
       " (1.4017279, 103.7549682),\n",
       " (1.4042412, 103.7551448),\n",
       " (1.3121, 103.87865),\n",
       " (1.3335921, 103.6943722),\n",
       " (1.4597711, 103.7999601),\n",
       " (1.3133629, 103.6268395),\n",
       " (1.4544049, 103.8035735),\n",
       " (1.3744365, 103.9706498),\n",
       " (1.4086, 103.74356),\n",
       " (1.45981, 103.82486),\n",
       " (1.32152, 103.98693),\n",
       " (1.4065938, 103.760286),\n",
       " (1.3130146, 103.9245373),\n",
       " (1.2985986, 103.8495778),\n",
       " (1.3254614, 103.6994246),\n",
       " (1.3373491, 103.8844022),\n",
       " (1.3997676, 103.7541124),\n",
       " (1.3312796, 103.6464477),\n",
       " (1.32255, 103.72744),\n",
       " (1.25268, 103.61345),\n",
       " (1.4265882, 103.8354616),\n",
       " (1.34416, 103.89821),\n",
       " (1.29367, 103.83791),\n",
       " (1.3202, 103.75367),\n",
       " (1.3327231, 103.6935832),\n",
       " (1.4659733, 103.8038629),\n",
       " (1.33275, 103.69033),\n",
       " (1.43003, 103.74795),\n",
       " (1.3011243, 103.6277759),\n",
       " (1.46061, 103.81121),\n",
       " (1.322732, 103.6585316),\n",
       " (1.4509635, 103.8047773),\n",
       " (1.3179739, 103.6689791),\n",
       " (1.4594368, 103.7959337),\n",
       " (1.3370974, 103.7529244),\n",
       " (1.45309, 103.79503),\n",
       " (1.41529, 103.74341),\n",
       " (1.40932, 103.74848),\n",
       " (1.38799, 103.82738),\n",
       " (1.3177524, 103.6284623)]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "locations_cluster"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Clusters in Singpore\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "c08711a0547a40ce8bebe73ecf068446",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Figure(layout=FigureLayout(height='420px'))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = gmaps.figure()\n",
    "heat_layer = gmaps.heatmap_layer(locations = locations_cluster, weights = weights_cluster)\n",
    "fig.add_layer(heat_layer)\n",
    "heat_layer.max_intensity = 150\n",
    "heat_layer.point_radius = 7\n",
    "print('Clusters in Singpore')\n",
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 326,
   "metadata": {},
   "outputs": [],
   "source": [
    "list_pro = []\n",
    "for dic in data['features']:\n",
    "    list_pro.append(dic['properties'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 325,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "loca_data = pd.DataFrame(list_pro)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 353,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "cluster     130\n",
       "hospital     16\n",
       "other         2\n",
       "Name: type, dtype: int64"
      ]
     },
     "execution_count": 353,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "loca_data.type.value_counts()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 354,
   "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>location</th>\n",
       "      <th>type</th>\n",
       "      <th>cases</th>\n",
       "      <th>caseCount</th>\n",
       "      <th>isDorm</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>Mei Hwan Drive</td>\n",
       "      <td>other</td>\n",
       "      <td>[50, 55, 65, 66, 68, 70, 71, 80, 83, 84, 88, 91]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131</th>\n",
       "      <td>Changi Airport (Imported Cases)</td>\n",
       "      <td>other</td>\n",
       "      <td>[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            location   type  \\\n",
       "130                   Mei Hwan Drive  other   \n",
       "131  Changi Airport (Imported Cases)  other   \n",
       "\n",
       "                                                 cases  caseCount  isDorm  \n",
       "130   [50, 55, 65, 66, 68, 70, 71, 80, 83, 84, 88, 91]        NaN   False  \n",
       "131  [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14...        NaN   False  "
      ]
     },
     "execution_count": 354,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "loca_data[loca_data.type == 'other']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 347,
   "metadata": {
    "scrolled": false
   },
   "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>location</th>\n",
       "      <th>type</th>\n",
       "      <th>cases</th>\n",
       "      <th>caseCount</th>\n",
       "      <th>isDorm</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>S11 Dormitory @ Punggol (2 Seletar North Link)</td>\n",
       "      <td>cluster</td>\n",
       "      <td>[826, 829, 852, 860, 946, 947, 966, 979, 982, ...</td>\n",
       "      <td>2302.0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Sungei Tengah Lodge (500 Old Choa Chu Kang Road)</td>\n",
       "      <td>cluster</td>\n",
       "      <td>[1054, 1077, 1124, 1267, 1306, 1319, 1342, 136...</td>\n",
       "      <td>901.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>Tuas View Dormitory (70 Tuas South Avenue 1)</td>\n",
       "      <td>cluster</td>\n",
       "      <td>[1473, 1539, 1996, 2071, 2134, 2242, 2329, 233...</td>\n",
       "      <td>896.0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>Hulett Dormitory (20 Senoko Drive)</td>\n",
       "      <td>cluster</td>\n",
       "      <td>[]</td>\n",
       "      <td>323.0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Kranji Lodge I (12 Kranji Road)</td>\n",
       "      <td>cluster</td>\n",
       "      <td>[880, 1190, 1241, 1506, 1519, 1520, 1630, 2141...</td>\n",
       "      <td>323.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>Hai Leck Engineering Pte Ltd (12 Tuas Drive 1)</td>\n",
       "      <td>cluster</td>\n",
       "      <td>[]</td>\n",
       "      <td>6.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>Natureland East Coast (907 East Coast Road)</td>\n",
       "      <td>cluster</td>\n",
       "      <td>[]</td>\n",
       "      <td>6.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>Strand Hotel (25 Bencoolen Street)</td>\n",
       "      <td>cluster</td>\n",
       "      <td>[]</td>\n",
       "      <td>5.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121</th>\n",
       "      <td>Lingjack Dormitory (1 Woodlands Terrace)</td>\n",
       "      <td>cluster</td>\n",
       "      <td>[]</td>\n",
       "      <td>4.0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>133 Tuas View Square</td>\n",
       "      <td>cluster</td>\n",
       "      <td>[]</td>\n",
       "      <td>4.0</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>96 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                             location     type  \\\n",
       "15     S11 Dormitory @ Punggol (2 Seletar North Link)  cluster   \n",
       "27   Sungei Tengah Lodge (500 Old Choa Chu Kang Road)  cluster   \n",
       "45       Tuas View Dormitory (70 Tuas South Avenue 1)  cluster   \n",
       "94                 Hulett Dormitory (20 Senoko Drive)  cluster   \n",
       "33                    Kranji Lodge I (12 Kranji Road)  cluster   \n",
       "..                                                ...      ...   \n",
       "120    Hai Leck Engineering Pte Ltd (12 Tuas Drive 1)  cluster   \n",
       "102       Natureland East Coast (907 East Coast Road)  cluster   \n",
       "103                Strand Hotel (25 Bencoolen Street)  cluster   \n",
       "121          Lingjack Dormitory (1 Woodlands Terrace)  cluster   \n",
       "118                              133 Tuas View Square  cluster   \n",
       "\n",
       "                                                 cases  caseCount  isDorm  \n",
       "15   [826, 829, 852, 860, 946, 947, 966, 979, 982, ...     2302.0    True  \n",
       "27   [1054, 1077, 1124, 1267, 1306, 1319, 1342, 136...      901.0   False  \n",
       "45   [1473, 1539, 1996, 2071, 2134, 2242, 2329, 233...      896.0    True  \n",
       "94                                                  []      323.0    True  \n",
       "33   [880, 1190, 1241, 1506, 1519, 1520, 1630, 2141...      323.0   False  \n",
       "..                                                 ...        ...     ...  \n",
       "120                                                 []        6.0   False  \n",
       "102                                                 []        6.0   False  \n",
       "103                                                 []        5.0   False  \n",
       "121                                                 []        4.0    True  \n",
       "118                                                 []        4.0   False  \n",
       "\n",
       "[96 rows x 5 columns]"
      ]
     },
     "execution_count": 347,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "loca_data[pd.notnull(loca_data.caseCount)].sort_values(by='caseCount', ascending = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 346,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "def find_dorm(row):\n",
    "    if 'Dormitory' in row.location:\n",
    "        return True\n",
    "    else: \n",
    "        return False\n",
    "loca_data['isDorm'] = loca_data.apply(lambda x: find_dorm(x),axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 350,
   "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>location</th>\n",
       "      <th>type</th>\n",
       "      <th>cases</th>\n",
       "      <th>caseCount</th>\n",
       "      <th>isDorm</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>S11 Dormitory @ Punggol (2 Seletar North Link)</td>\n",
       "      <td>cluster</td>\n",
       "      <td>[826, 829, 852, 860, 946, 947, 966, 979, 982, ...</td>\n",
       "      <td>2302.0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Dormitory at 55 Sungei Kadut Loop</td>\n",
       "      <td>cluster</td>\n",
       "      <td>[868, 972, 974, 1356, 1510, 1549, 2085]</td>\n",
       "      <td>NaN</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Toh Guan Dormitory (19A Toh Guan Road East)</td>\n",
       "      <td>cluster</td>\n",
       "      <td>[963, 1079, 1106, 1148, 1150, 1195, 1254, 1262...</td>\n",
       "      <td>131.0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Tampines Dormitory (2 Tampines Place)</td>\n",
       "      <td>cluster</td>\n",
       "      <td>[1049, 1140, 1193, 1226, 1299, 1261, 1313, 131...</td>\n",
       "      <td>90.0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>Dormitory at 31 Sungei Kadut Avenue</td>\n",
       "      <td>cluster</td>\n",
       "      <td>[1549, 1731, 1735, 1830, 1831, 2209, 2245, 236...</td>\n",
       "      <td>210.0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>Tuas View Dormitory (70 Tuas South Avenue 1)</td>\n",
       "      <td>cluster</td>\n",
       "      <td>[1473, 1539, 1996, 2071, 2134, 2242, 2329, 233...</td>\n",
       "      <td>896.0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>85 Kallang Dormitory (85 Kallang Avenue)</td>\n",
       "      <td>cluster</td>\n",
       "      <td>[1585, 2059, 2062, 2097, 2172, 4742, 5445, 5466]</td>\n",
       "      <td>44.0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>Kranji Dormitory (17 Kranji Way)</td>\n",
       "      <td>cluster</td>\n",
       "      <td>[2247, 2248, 2250, 2390, 2398, 2399, 3203, 328...</td>\n",
       "      <td>89.0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>10 Kian Teck Crescent Dormitory</td>\n",
       "      <td>cluster</td>\n",
       "      <td>[1125, 1540, 1959, 2929, 3824, 5926]</td>\n",
       "      <td>28.0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>Kian Teck Dormitory (26 Kian Teck Avenue)</td>\n",
       "      <td>cluster</td>\n",
       "      <td>[2955, 2956, 3370, 4171, 4658, 5447, 5547, 6411]</td>\n",
       "      <td>176.0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>SJ Dormitory (180 Woodlands Industrial Park E5)</td>\n",
       "      <td>cluster</td>\n",
       "      <td>[2971, 3112, 3114, 3124, 3181, 3330, 4381, 455...</td>\n",
       "      <td>144.0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>Tuas South Dormitory (1 Tuas South Street 12)</td>\n",
       "      <td>cluster</td>\n",
       "      <td>[1427, 1456, 2114, 2733, 3971, 4414, 5009, 504...</td>\n",
       "      <td>95.0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>Avery Lodge Dormitory (2D Jalan Papan)</td>\n",
       "      <td>cluster</td>\n",
       "      <td>[1204, 1324, 3368, 3369, 3880, 3981, 3986, 441...</td>\n",
       "      <td>98.0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>Jurong Penjuru Dormitory (58 Penjuru Place)</td>\n",
       "      <td>cluster</td>\n",
       "      <td>[3314, 3372, 3558, 3559, 3560, 3675, 4174, 437...</td>\n",
       "      <td>237.0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>CDPL Tuas Dormitory (6 Tuas South Street 15)</td>\n",
       "      <td>cluster</td>\n",
       "      <td>[4657, 4697, 4702, 4768, 4921]</td>\n",
       "      <td>74.0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>Blue Stars Dormitory (3 Kian Teck Lane)</td>\n",
       "      <td>cluster</td>\n",
       "      <td>[]</td>\n",
       "      <td>12.0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>Hulett Dormitory (20 Senoko Drive)</td>\n",
       "      <td>cluster</td>\n",
       "      <td>[]</td>\n",
       "      <td>323.0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>Seatown Dormitory (69H Tuas South Avenue 1)</td>\n",
       "      <td>cluster</td>\n",
       "      <td>[]</td>\n",
       "      <td>203.0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>Woodlands Dormitory (27 Woodlands Sector 1)</td>\n",
       "      <td>cluster</td>\n",
       "      <td>[]</td>\n",
       "      <td>91.0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>SSKBJV Dormitory (31A Tanah Merah Coast Road)</td>\n",
       "      <td>cluster</td>\n",
       "      <td>[]</td>\n",
       "      <td>23.0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121</th>\n",
       "      <td>Lingjack Dormitory (1 Woodlands Terrace)</td>\n",
       "      <td>cluster</td>\n",
       "      <td>[]</td>\n",
       "      <td>4.0</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                            location     type  \\\n",
       "15    S11 Dormitory @ Punggol (2 Seletar North Link)  cluster   \n",
       "20                 Dormitory at 55 Sungei Kadut Loop  cluster   \n",
       "28       Toh Guan Dormitory (19A Toh Guan Road East)  cluster   \n",
       "31             Tampines Dormitory (2 Tampines Place)  cluster   \n",
       "36               Dormitory at 31 Sungei Kadut Avenue  cluster   \n",
       "45      Tuas View Dormitory (70 Tuas South Avenue 1)  cluster   \n",
       "47          85 Kallang Dormitory (85 Kallang Avenue)  cluster   \n",
       "56                  Kranji Dormitory (17 Kranji Way)  cluster   \n",
       "58                   10 Kian Teck Crescent Dormitory  cluster   \n",
       "59         Kian Teck Dormitory (26 Kian Teck Avenue)  cluster   \n",
       "63   SJ Dormitory (180 Woodlands Industrial Park E5)  cluster   \n",
       "67     Tuas South Dormitory (1 Tuas South Street 12)  cluster   \n",
       "68            Avery Lodge Dormitory (2D Jalan Papan)  cluster   \n",
       "69       Jurong Penjuru Dormitory (58 Penjuru Place)  cluster   \n",
       "72      CDPL Tuas Dormitory (6 Tuas South Street 15)  cluster   \n",
       "93           Blue Stars Dormitory (3 Kian Teck Lane)  cluster   \n",
       "94                Hulett Dormitory (20 Senoko Drive)  cluster   \n",
       "95       Seatown Dormitory (69H Tuas South Avenue 1)  cluster   \n",
       "96       Woodlands Dormitory (27 Woodlands Sector 1)  cluster   \n",
       "100    SSKBJV Dormitory (31A Tanah Merah Coast Road)  cluster   \n",
       "121         Lingjack Dormitory (1 Woodlands Terrace)  cluster   \n",
       "\n",
       "                                                 cases  caseCount  isDorm  \n",
       "15   [826, 829, 852, 860, 946, 947, 966, 979, 982, ...     2302.0    True  \n",
       "20             [868, 972, 974, 1356, 1510, 1549, 2085]        NaN    True  \n",
       "28   [963, 1079, 1106, 1148, 1150, 1195, 1254, 1262...      131.0    True  \n",
       "31   [1049, 1140, 1193, 1226, 1299, 1261, 1313, 131...       90.0    True  \n",
       "36   [1549, 1731, 1735, 1830, 1831, 2209, 2245, 236...      210.0    True  \n",
       "45   [1473, 1539, 1996, 2071, 2134, 2242, 2329, 233...      896.0    True  \n",
       "47    [1585, 2059, 2062, 2097, 2172, 4742, 5445, 5466]       44.0    True  \n",
       "56   [2247, 2248, 2250, 2390, 2398, 2399, 3203, 328...       89.0    True  \n",
       "58                [1125, 1540, 1959, 2929, 3824, 5926]       28.0    True  \n",
       "59    [2955, 2956, 3370, 4171, 4658, 5447, 5547, 6411]      176.0    True  \n",
       "63   [2971, 3112, 3114, 3124, 3181, 3330, 4381, 455...      144.0    True  \n",
       "67   [1427, 1456, 2114, 2733, 3971, 4414, 5009, 504...       95.0    True  \n",
       "68   [1204, 1324, 3368, 3369, 3880, 3981, 3986, 441...       98.0    True  \n",
       "69   [3314, 3372, 3558, 3559, 3560, 3675, 4174, 437...      237.0    True  \n",
       "72                      [4657, 4697, 4702, 4768, 4921]       74.0    True  \n",
       "93                                                  []       12.0    True  \n",
       "94                                                  []      323.0    True  \n",
       "95                                                  []      203.0    True  \n",
       "96                                                  []       91.0    True  \n",
       "100                                                 []       23.0    True  \n",
       "121                                                 []        4.0    True  "
      ]
     },
     "execution_count": 350,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "loca_data[loca_data.isDorm == True]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 404,
   "metadata": {},
   "outputs": [],
   "source": [
    "locations = read_json('covid-sg.json')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 405,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "528978cf1554474493cd5a1960a7170b",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "Figure(layout=FigureLayout(height='420px'))"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = gmaps.figure()\n",
    "geojson = gmaps.geojson_layer(locations)\n",
    "fig.add_layer(geojson)\n",
    "print ('Coordinates of the place of residence (other fallback values might include locations such as location of hospitalisation, if the former is not made available)')\n",
    "fig"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}