99_Feature_Engineering_and_Modeling.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 189,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import accuracy_score, roc_auc_score\n",
    "from xgboost import XGBClassifier\n",
    "from xgboost import plot_importance\n",
    "from sklearn.naive_bayes import GaussianNB\n",
    "from sklearn.decomposition import PCA\n",
    "from sklearn.feature_selection import SelectKBest\n",
    "from sklearn.feature_selection import f_classif, mutual_info_classif\n",
    "from numpy import sort\n",
    "from sklearn.feature_selection import SelectFromModel\n",
    "\n",
    "\n",
    "# Comment this if the data visualisations doesn't work on your side\n",
    "%matplotlib inline\n",
    "\n",
    "plt.style.use('bmh')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 190,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(30139, 15)\n"
     ]
    }
   ],
   "source": [
    "df=pd.read_csv('adult_income.csv')\n",
    "df.drop_duplicates(keep='first',inplace=True)\n",
    "df.drop(index=df[(df[' Work-class']==' ?')|(df[' Occupation']==' ?') |(df[' Native-country']==' ?')].index,inplace=True)\n",
    "df['income']=df[' Income'].map(lambda x: 0 if x ==' <=50K' else 1)\n",
    "df.drop(\" Income\",axis=1,inplace=True)\n",
    "print(df.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 191,
   "metadata": {},
   "outputs": [],
   "source": [
    "# One-hot Encoding for categorical data (native-country 0 for US,1 for others)\n",
    "df=pd.get_dummies(df, columns=[' Work-class'],drop_first=False)\n",
    "df=pd.get_dummies(df, columns=[' Marital-status'],drop_first=False)\n",
    "df=pd.get_dummies(df, columns=[' Occupation'],drop_first=False)\n",
    "df=pd.get_dummies(df, columns=[' Relationship'],drop_first=False)\n",
    "df=pd.get_dummies(df, columns=[' Race'],drop_first=False)\n",
    "df=pd.get_dummies(df, columns=[' Sex'],drop_first=False)\n",
    "df[' Native-country']=df[' Native-country'].map(lambda x: 0 if x ==' United-States' else 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 192,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Eduction and Eduction_num are essentially duplicate\n",
    "df.drop(' Education', axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 193,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(30139, 49)\n",
      "(30139, 48)\n"
     ]
    }
   ],
   "source": [
    "print(df.shape)\n",
    "df['Capital'] = df[' Capital-gain'] + df[' Capital-loss']\n",
    "df.drop(' Capital-gain', axis=1, inplace=True)\n",
    "df.drop(' Capital-loss', axis=1, inplace=True)\n",
    "print(df.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 194,
   "metadata": {},
   "outputs": [],
   "source": [
    "index=df[df['Capital']>=10000].index\n",
    "df.drop(index=index,inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 195,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(29407, 48)"
      ]
     },
     "execution_count": 195,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 196,
   "metadata": {},
   "outputs": [],
   "source": [
    "#scaling\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "scaler = StandardScaler().fit(df[[' fnlwgt','Capital',' Hours-per-week']])\n",
    "df[[' fnlwgt','Capital',' Hours-per-week']] = scaler.transform(df[[' fnlwgt','Capital',' Hours-per-week']])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 197,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(29407, 48)"
      ]
     },
     "execution_count": 197,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## feature selection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 212,
   "metadata": {},
   "outputs": [],
   "source": [
    "dataX=df.drop('income',axis=1)\n",
    "dataY=df['income']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 199,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.set_option('display.float_format', lambda x: '%.3f' % x)\n",
    "importance_f=f_classif(dataX, dataY) \n",
    "feature_importance=pd.DataFrame(importance_f,columns=dataX.columns,index=['f-statistics','p-value']).T.sort_values(by='f-statistics',ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 200,
   "metadata": {},
   "outputs": [],
   "source": [
    "feature_importance=feature_importance.reset_index().rename(columns={'index':'feature'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 201,
   "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>feature</th>\n",
       "      <th>f-statistics</th>\n",
       "      <th>p-value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Marital-status_ Married-civ-spouse</td>\n",
       "      <td>7401.515</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Relationship_ Husband</td>\n",
       "      <td>5721.788</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Marital-status_ Never-married</td>\n",
       "      <td>3318.909</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Education-num</td>\n",
       "      <td>3158.748</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Capital</td>\n",
       "      <td>2373.282</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Age</td>\n",
       "      <td>1608.196</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Relationship_ Own-child</td>\n",
       "      <td>1488.501</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Hours-per-week</td>\n",
       "      <td>1455.586</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Sex_ Female</td>\n",
       "      <td>1402.533</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Sex_ Male</td>\n",
       "      <td>1402.533</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Relationship_ Not-in-family</td>\n",
       "      <td>1242.109</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Occupation_ Exec-managerial</td>\n",
       "      <td>1237.866</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Occupation_ Prof-specialty</td>\n",
       "      <td>844.883</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Occupation_ Other-service</td>\n",
       "      <td>756.446</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Relationship_ Unmarried</td>\n",
       "      <td>615.580</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Marital-status_ Divorced</td>\n",
       "      <td>549.168</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Relationship_ Wife</td>\n",
       "      <td>485.392</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Work-class_ Self-emp-inc</td>\n",
       "      <td>431.681</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Work-class_ Private</td>\n",
       "      <td>368.309</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Occupation_ Adm-clerical</td>\n",
       "      <td>256.542</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Occupation_ Handlers-cleaners</td>\n",
       "      <td>233.351</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Race_ Black</td>\n",
       "      <td>223.191</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Race_ White</td>\n",
       "      <td>206.987</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Relationship_ Other-relative</td>\n",
       "      <td>199.931</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Marital-status_ Separated</td>\n",
       "      <td>161.338</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Occupation_ Machine-op-inspct</td>\n",
       "      <td>139.434</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Work-class_ Federal-gov</td>\n",
       "      <td>111.384</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Marital-status_ Widowed</td>\n",
       "      <td>107.236</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Occupation_ Farming-fishing</td>\n",
       "      <td>89.669</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Marital-status_ Married-spouse-absent</td>\n",
       "      <td>54.641</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Occupation_ Priv-house-serv</td>\n",
       "      <td>42.257</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Native-country</td>\n",
       "      <td>41.744</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>Work-class_ Local-gov</td>\n",
       "      <td>34.822</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Race_ Amer-Indian-Eskimo</td>\n",
       "      <td>28.513</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>Race_ Other</td>\n",
       "      <td>28.425</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>Occupation_ Protective-serv</td>\n",
       "      <td>27.193</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>Occupation_ Tech-support</td>\n",
       "      <td>21.066</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>Work-class_ Self-emp-not-inc</td>\n",
       "      <td>12.599</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>Occupation_ Transport-moving</td>\n",
       "      <td>12.267</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>Occupation_ Sales</td>\n",
       "      <td>7.872</td>\n",
       "      <td>0.005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>Marital-status_ Married-AF-spouse</td>\n",
       "      <td>7.132</td>\n",
       "      <td>0.008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>Occupation_ Craft-repair</td>\n",
       "      <td>4.810</td>\n",
       "      <td>0.028</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>Work-class_ State-gov</td>\n",
       "      <td>4.332</td>\n",
       "      <td>0.037</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>Work-class_ Without-pay</td>\n",
       "      <td>4.202</td>\n",
       "      <td>0.040</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>Race_ Asian-Pac-Islander</td>\n",
       "      <td>4.087</td>\n",
       "      <td>0.043</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>fnlwgt</td>\n",
       "      <td>2.830</td>\n",
       "      <td>0.093</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>Occupation_ Armed-Forces</td>\n",
       "      <td>0.726</td>\n",
       "      <td>0.394</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                   feature  f-statistics  p-value\n",
       "0       Marital-status_ Married-civ-spouse      7401.515    0.000\n",
       "1                    Relationship_ Husband      5721.788    0.000\n",
       "2            Marital-status_ Never-married      3318.909    0.000\n",
       "3                            Education-num      3158.748    0.000\n",
       "4                                  Capital      2373.282    0.000\n",
       "5                                      Age      1608.196    0.000\n",
       "6                  Relationship_ Own-child      1488.501    0.000\n",
       "7                           Hours-per-week      1455.586    0.000\n",
       "8                              Sex_ Female      1402.533    0.000\n",
       "9                                Sex_ Male      1402.533    0.000\n",
       "10             Relationship_ Not-in-family      1242.109    0.000\n",
       "11             Occupation_ Exec-managerial      1237.866    0.000\n",
       "12              Occupation_ Prof-specialty       844.883    0.000\n",
       "13               Occupation_ Other-service       756.446    0.000\n",
       "14                 Relationship_ Unmarried       615.580    0.000\n",
       "15                Marital-status_ Divorced       549.168    0.000\n",
       "16                      Relationship_ Wife       485.392    0.000\n",
       "17                Work-class_ Self-emp-inc       431.681    0.000\n",
       "18                     Work-class_ Private       368.309    0.000\n",
       "19                Occupation_ Adm-clerical       256.542    0.000\n",
       "20           Occupation_ Handlers-cleaners       233.351    0.000\n",
       "21                             Race_ Black       223.191    0.000\n",
       "22                             Race_ White       206.987    0.000\n",
       "23            Relationship_ Other-relative       199.931    0.000\n",
       "24               Marital-status_ Separated       161.338    0.000\n",
       "25           Occupation_ Machine-op-inspct       139.434    0.000\n",
       "26                 Work-class_ Federal-gov       111.384    0.000\n",
       "27                 Marital-status_ Widowed       107.236    0.000\n",
       "28             Occupation_ Farming-fishing        89.669    0.000\n",
       "29   Marital-status_ Married-spouse-absent        54.641    0.000\n",
       "30             Occupation_ Priv-house-serv        42.257    0.000\n",
       "31                          Native-country        41.744    0.000\n",
       "32                   Work-class_ Local-gov        34.822    0.000\n",
       "33                Race_ Amer-Indian-Eskimo        28.513    0.000\n",
       "34                             Race_ Other        28.425    0.000\n",
       "35             Occupation_ Protective-serv        27.193    0.000\n",
       "36                Occupation_ Tech-support        21.066    0.000\n",
       "37            Work-class_ Self-emp-not-inc        12.599    0.000\n",
       "38            Occupation_ Transport-moving        12.267    0.000\n",
       "39                       Occupation_ Sales         7.872    0.005\n",
       "40       Marital-status_ Married-AF-spouse         7.132    0.008\n",
       "41                Occupation_ Craft-repair         4.810    0.028\n",
       "42                   Work-class_ State-gov         4.332    0.037\n",
       "43                 Work-class_ Without-pay         4.202    0.040\n",
       "44                Race_ Asian-Pac-Islander         4.087    0.043\n",
       "45                                  fnlwgt         2.830    0.093\n",
       "46                Occupation_ Armed-Forces         0.726    0.394"
      ]
     },
     "execution_count": 201,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "feature_importance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 204,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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O7ueYj0raVUVj/SLbx0TEj/sZv7aulrRLRNyW+Lz7SjojIn4jSeXM8u061PEUSSsjYmbiWgAAAAAAAACa5MC6YPt/Jd0v6a+S7lWx1MinJM1SsY63VMzc/pbteSpuaDlSxc0vN4qIb9h+toobex4WEZfb/rCkb9q+NCLuSFzy5yT9wfbdkn4labWKpU+eERGfGsJ5b5X0Wtu/VzHL/PPq/zdaLlbx/pxv+2OSZkjaSsVyLb+JiKuGUAswYMOWpv6+CE236abcDBbpkSukRqaQA7lCDuQKqZGp5mG5FWDduFjFsim/VNHo/bWKZUumRMRsSYqI0yUdK+kYFUuQXCrpaBU38Bwl6acqZmH/vhz/fRVriv/EdtL1RMobb75K0kslXSnpX5I+JOmuIZ76w5IelfRPSb+XdJGK2eJ91RGSXiHp7ypuADpD0jmSttVja6AD+a1e3HkMMAgjRvS1yhSw9sgVUiNTyIFcIQdyhdTIVPMwkxxYByLi1yoa453G/UzSz/rY/fRexh88hJqO7rD/IhVN7L72u+35TEnt2y5p3VaOeXHbqb7ddsx2bc8XSPpA+QAqsXrMszRs3n1Vl4Eauf/++zVhwoSqy0DNkCukRqaQA7lCDuQKqZGp5mEmOQAAAAAAAACgsWiSAzVg+0TbC/t4XFh1fcCTXdfCy6suATWz/fbbV10CaohcITUyhRzIFXIgV0iNTDUPTXKgHr4rafc+HsdWUhFQI6tH7lR1CaiZWbNmVV0CaohcITUyhRzIFXIgV0iNTDUPa5IDNRARcyTNqboOoK5i+BZVl4CaWbhwYdUloIbIFVIjU8iBXCEHcoXUyFTzMJMcAIBOVi+pugLUzPDhw6suATVErpAamUIO5Ao5kCukRqaahyY5AAAddC24tOoSUDM77cQSPkiPXCE1MoUcyBVyIFdIjUw1D8utAKidPV5zurq6uqouAzUyffp0TZ48ueoyUCM33XQTmUJy5AqpkSnkQK6QA7lCamSqeZhJDgAAAAAAAABoLJrkAAB0sPHGG1ddAmqGTCEHcoXUyBRyIFfIgVwhNTLVPDTJAQDoYPTo0VWXgJohU8iBXCE1MoUcyBVyIFdIjUw1D01yAAA6uO+++6ouATVDppADuUJqZAo5kCvkQK6QGplqHprkAAAAAAAAAIDG6q66AABI7R+/f7sUy6suA3XStZEuveXRqqtYZ/Y/9GdVl1B72223XdUloIbIFVIjU8iBXCEHcoXUyFTzMJMcAIAOPGLbqktAzcyZM6fqElBD5AqpkSnkQK6QA7lCamSqeWiSAwDQgYdvWXUJqJn58+dXXQJqiFwhNTKFHMgVciBXSI1MNQ9NcgAAOohYUXUJqJmurq6qS0ANkSukRqaQA7lCDuQKqZGp5qFJDgBAB7Hg4qpLQM3ssssuVZeAGiJXSI1MIQdyhRzIFVIjU81DkxwAgA6GjT+o6hJQMzfddFPVJaCGyBVSI1PIgVwhB3KF1MhU89AkBwCgI1ddAGomIqouATVErpAamUIO5Ao5kCukRqaahyY5AAAdxPJ7qi4BNTNhwoSqS0ANkSukRqaQA7lCDuQKqZGp5qFJDmC9YXs722F796prAVrFyoerLgE1M27cuKpLQA2RK6RGppADuUIO5AqpkanmoUkOPInYfoftabYX2p5r+xrbn6ywnjPKpvZ3e9n37XLfGRWUBiQ1bMxzqy4BNXPPPfx2AtIjV0iNTCEHcoUcyBVSI1PNQ5MceJKw/TZJp0r6lqTdJe0r6auSxlZXlSTpHkmH2x7ds8H2KElvlnR3ZVUBAAAAAAAAA0CTHHjyeI2kcyPihxFxW0TcGBE/j4iTWgfZPtb2TbaX2r7Z9nta9v3I9nW2R5bPR5Sz0c8aQl1Xq2iUv7Zl22tVNMivaavtINv/KGfBz7b9B9s79ndy28+wfWE5e/4h2z+xvekQ6gUGbfXiK6suATWzzTbbVF0CaohcITUyhRzIFXIgV0iNTDUPTXLgyeNBSfvY3ravAbaPkPQ5SSdJmiTpREmft31UOeQDkjaQ9OXy+RclTZD0viHW9iNJx7Q8f5ukH/cybgNJ35C0h6QpklZL+o3tXv8usj1B0l9VNNv3kHSQpC0kndtfMUuWrtTiJY89VqxYPbhXA7Rx95ZVl4CamT9/ftUloIbIFVIjU8iBXCEHcoXUyFTzdFddAIAB+6yk8yTNtD1D0hWSLpD0q4hY3TLmhIg4r3x+p+3Jkt4l6cyIWGj7LZIutb1A0vGSXhQRQ/3b/6eSvtTSwN9X0uGSDmgdFBG/bn1eLiEzS9JkSTf0ct73SbomIk5sO+Ye2xMjYkZvxRz7kUu0ePHiNc/f+JoddfjBOw/2NQFreMTTFEuvr7oM1MjcuXO11VZbVV0GaoZcITUyhRzIFXIgV0iNTDUPTXLgSSIiHpD0PNvPkPRCSc+XdKakY20fJGm0pB0l/dD2D1oO7ZY0r+U8V9j+mqRPS/pKRPwjQW2zbP9R0tGSLOmPEfGI7ceNs72zipnue0vaVI/9Nss26r1JvpukF9le2Mu+HSX12iQ//WsHKFYvX/N8eDe/NIOhWlV1AaiZ9r8fgRTIFVIjU8iBXCEHcoXUyFTz0CQHnmQi4gYVDeXv2P6upMsk7S9pejnkHZL+r+2wNR2+cmmTfcttOyUs7UeSTit/fm8fY34v6a6yxvtVNMlvkDSij/Fjy2M+3su+B/oqZPSobilYYgXprJ7/56pLQM1MmjSp6hJQQ+QKqZEp5ECukAO5QmpkqnmYXgk8ufU0xjeIiIdUNJ53KG/s2fq4s+WYj0raVUVj/SDbxyiNP6lodg+XdFH7TtubSNpF0hciYmpE3CRpow7nvFrS0yXN7OU1LUpUN9CRx72k6hJQM7fcckvVJaCGyBVSI1PIgVwhB3KF1MhU8zCTHHiSsP2/Kprgf5V0r6QtJX1KxZreV5TDTpb0LdvzVDStR6q44eVGEfEN289WsdzJYRFxue0PS/qm7Usj4o6h1BcRq2xP6vm5lyGPSpot6Z22H1CxxMqXexnX6tsqZp3/3PZXJc1RMfv9cEnH9nEdIDl7uKLqIlArq1bx1xfSI1dIjUwhB3KFHMgVUiNTzcNMcuDJ42JJ+0j6pYq1uH8taamkKRExW5Ii4nRJx0o6RtL1ki5VsU74nbZHqbjB5hkR8fty/Pcl/U3ST2x3DbXAiJjf101Ay5uLHi7puSqWWPlvFbPa+zvf/SqWhumS9OfyNZ0qaa4k1lPBOhMr7q+6BNTM+PHjqy4BNUSukBqZQg7kCjmQK6RGppqHmeTAk0RE/FpFY7zTuJ9J+lkfu5/ey/iDh1DT0R32H9L2/GJJk9uGuWX/zNbn5bZbJb12bWsEUojl91RdAmpmo406rTYFDB65QmpkCjmQK+RArpAamWoeZpIDANDBsA32rroE1Mxdd91VdQmoIXKF1MgUciBXyIFcITUy1Tw0yQFIkmyfaHthH48Lq64PAAAAAAAAyIHlVgD0+K6kc/vYt2RdFgKsb1YvvqbqElAzT3va06ouATVErpAamUIO5Ao5kCukRqaah5nkACRJETEnIm7r43Ff1fUBVXL3xlWXgJpZvHhx1SWghsgVUiNTyIFcIQdyhdTIVPPQJAcAoAOP2LbqElAzc+bMqboE1BC5QmpkCjmQK+RArpAamWoemuQAAAAAAAAAgMZyRFRdAwAkMXXq1PGS5u22227q6uqquhwAAAAAAABUaNWqVZo2bZokbThlypT5fY1jJjkAAB3MmDGj6hJQM2QKOZArpEamkAO5Qg7kCqmRqeahSQ4AQAcrV66sugTUDJlCDuQKqZEp5ECukAO5QmpkqnlokgMA0MG4ceOqLgE1Q6aQA7lCamQKOZAr5ECukBqZah6a5AAAdLDppptWXQJqhkwhB3KF1MgUciBXyIFcITUy1Tw0yQEA6ODOO++sugTUDJlCDuQKqZEp5ECukAO5Qmpkqnm6qy4AAFK7+I/HKGJ51WWgRkaNe6XuvvVzVZexxkEHn1N1CQAAAAAA1AYzyQEA6GDFkmurLgE1s9VWW1VdAmqIXCE1MoUcyBVyIFdIjUw1D01yAAA68LCxVZeAmlm2bFnVJaCGyBVSI1PIgVwhB3KF1MhU89AkBwCgg+6RO1VdAmpm9uzZVZeAGiJXSI1MIQdyhRzIFVIjU81DkxwAAAAAAAAA0Fg0yQEA6GDpgj9VXQJqZtddd626BNQQuUJqZAo5kCvkQK6QGplqHprkAAB0MHKDF1RdAmrmjjvuqLoE1BC5QmpkCjmQK+RArpAamWoemuQAAHTAjTuR2vLly6suATVErpAamUIO5Ao5kCukRqaahyY5+mV7pu3j15fzDOJ6Z9g+v8OYdVrTumD7FNvXJjjPU2z/xfYi23OHXlm/13rc52A7bB+S85rAYK1eOavqElAzG2ywQdUloIbIFVIjU8iBXCEHcoXUyFTz0CSvKdsHlM3Gnscs2xfYfmbm6x7dR1N1T0nfz3nttZC1prJRH7Y/0bb9ENsxyHMNtKH/NUlTBnPuPnxI0paSdpc0McH5+rM+ZgN4nBXLplddAmpmiy22qLoE1BC5QmpkCjmQK+RArpAamWoemuT1t4uKZufLJI2U9EfbI9Z1ERExKyIWr+vr9mcd1bRU0sdtb5T5OpKkiFgYEbMTnGpHSf+JiFsj4uEE5+vT+pgNoN3IDfavugTUDGscIgdyhdTIFHIgV8iBXCE1MtU8NMnr7+GIeDAirpZ0qqStJa25Ra/tF9i+zPYS2/fY/pbtPn+nxPaHbV9fLsNxj+3v2B5b7jtA0o8lbdgyg/2Ucl/7khrb2P6t7YW259s+1/YWLftPsX2t7beWx86zfY7tcS1jDitrWWJ7tu2L22u3/RHbD5T7v217eMu+3pb5OM72heU577B92CDf73YXS3pQ0if7G2T7dbZvtL2srOuEln2XSNpW0n/3vK/9nOdxy630LDvT3/vQyzlmSnqdpCPL651Rbu/zsy/3H217ru1X2b7F9mLbv7I9xvZR5et6tMxYV+v1+polb/uvtk9r27aZ7eW2U8yYBwAAAAAAQMPRJG8I2xtKOrx8urzctqOkP0n6taRnSXqjpBdIOq23c5RWS/qApKdLOkrSiyV9tdz3T0nHS5qvYvb6liqW/2ivZZik30raWNL+kg6UtIOkX7QN3VHSIZJeVT72l/SJ8hxbSvq5pB9JmiTpAEnnSXLL8S8qz/Gistajy0d/Pq/i/dhN0tmSzrE9qcMx/Vkl6URJ77f9tN4G2H6upHMlnSPpmZJOkfR52z21vlbSvZI+o8fe18EY7Puwp4pcnFte64Pl9v4++x5jyjGHSzpIxefyG0mvKB9vlfQuSQP98uF0SW+2PbJl21sk3Sfpr30dtHjpSi1e8thjxYrVA7wc0LsVS6+vugTUzJZbDvavcqAzcoXUyBRyIFfIgVwhNTLVPN1VF4Ds7rUtST0zrH8XETeXP39S0tkRcWr5/FbbH5B0qe3jImJp+8laxkrSTNufkvRdSe+JiOW25xXD4sF+apqiohm8fUTcI0m2j5R0o+09I+LKctwwSUdHxIJyzE/KY09S0bztlnReRNxVjm/vYj0q6X0RsUrSzbb/WB7/g35q+2VEnF7+/GnbB0p6v6T39HNMvyLiN+Xs7s9KensvQz4saWpEfL58PsP2ZEkflXRGRMyxvUrSgg7va18G9T5ExCzbyyQtab1ef599y/bhko6LiNslyfavVDTGt4iIhZKm2/6bioZ9+5civTlPxZc2B6to2ktFg/+MiOhzRv37P/x3LV782Aourz14Bx12yE4DuBzQuwpWqULNrVy5suoSUEPkCqmRKeRArpADuUJqZKp5aJLX336SFkvaR8WM5ne37NtN0rNsH9GyzSqa09tLuqn9ZLZfoqK5vquk8SoyNMr2mEGsKz1J0j09DXJJiojpLm74OUlST5N8Zk+DvPSApM3Ln6dJmirpetsXSfqzpF9FxKMt428sG8Otx3e6cekVvTzfveMr6uzjkv5q+wkz61W85t+2bbtc0vG2u9pewxq2F7Y8/WlEvLu3cernfbB9oopc9JgcEXf3cb2BfPaLexrkpYdUfI4L27ZtrgGIiKXllyNvk3Su7edIeoak1/R33P9844WK1cvXPB/ezS/NYGi6R+6ilctvq7oM1MisWbO02WabVV0GaoZcITUyhRzIFXIgV0iNTDUPTfL6uzMi5kq6xfbmKmbvvrDcN1bS9yR9q5fjntAotb2dpD9I+l8Vs7nnqFie5YeSRqhoxqe0ou15qFwiKCJWlbO8ny/ppSpme3/R9t4RcWen49e1iPh72cz/kqQzEp1295af5/czrr/34bt6bIa2JN3f2wkG8dn3dq2hfg6nS7q2XK7mGEl/bfntgV6NGdWtCJZYAQAAAAAAQGc0yZvl25I+afvQiPiNpKtVzBwe6PTI56pobp4QZQfS9hvaxiyX1NV+YJubJG1te+uW5VYmS5ogafoAa1G53Mblki63/TlJd0k6VNI3BnqOXuwj6ay259cM4XytPiHpWkm3tG2/SdK+bdv2lTSjZQb4E97XQXxufYqIOSoa3p0M5LPPIiKut32VpHdIerOk962L6wKtli78S9UloGYmTpxYdQmoIXKF1MgUciBXyIFcITUy1TysQdAg5ZIYP5D0WRcLlX9F0vNtn2Z7d9s72z7Ydl837rxNxZrT77e9g+236vHLt0jSTEljbU+xvantMb2c52IV64efbfs5tvdS0Zi+NCKuGshrsb237RNt72F7GxU3t9xMvSwRM0ivt/022xNtf1bSXur/RqYDFhHXq7gZ6Afadn1d0hTbny6ve5SKRnDr0iwzJb3Q9lNtb5qinkEayGef0+kqvmSwihuBAuvUiNF7VV0Caubuu3td2QoYEnKF1MgUciBXyIFcITUy1Tw0yZvnNBVrYL8+Iq6TtL+kiZIuUzFj+nPqY8mNiJim4iaTH5d0g6QjVKxR3TrmnyqW8PiFpFmSPtbLeULFjRgflfR3FU3zOyS9cRCvY76KZWMukDRD0hdUzHK+cBDn6M3Jkg6XdJ2kIyW9KSIGPLt9AD6jtn/uIuJqSW8or3uDis/gMxFxRttx20m6XcX7uk4N5LPP7OeSVkr6eW83lAVyG9a1YdUloGaWLuWvMqRHrpAamUIO5Ao5kCukRqaax0W/EoDtkHRoRJxfdS14vHJN9Nsl7Vl+qdCrqVOnjpc0b9a9pypieV/DgEEbMeZ5Wr64/b6+1Tno4HOqLgFDdOedd2r77bevugzUDLlCamQKOZAr5ECukBqZqo9Vq1Zp2rRpkrThlClT+rynH2uSA1hv2R4uaRMVvynwr/4a5EBOK5ZcW3UJqJmnPvWpVZeAGiJXSI1MIQdyhRzIFVIjU83DcivAAJTrny/s4zHUJV7Qt30lPSBpT63bNdCBxxk59sVVl4Caue22Id97GXgCcoXUyBRyIFfIgVwhNTLVPMwkB0oR4X52f1fSuX3sW5KhHEiKiEtU3KwTAAAAAAAAyIImOTAAETFH0pyq6wBQjRVLU96/F5C22GKLqktADZErpEamkAO5Qg7kCqmRqeZhuRUAAAAAAAAAQGPRJAcAoIPhoyZXXQJq5qGHHqq6BNQQuUJqZAo5kCvkQK6QGplqHpZbAVA7L3nlj9XV1VV1GaiR6dOna/KL31p1GQAAAAAAIANmkgMA0MFOO+1UdQmoGTKFHMgVUiNTyIFcIQdyhdTIVPPQJAcAoIP77ruv6hJQM2QKOZArpEamkAO5Qg7kCqmRqeahSQ4AQAdLliypugTUDJlCDuQKqZEp5ECukAO5QmpkqnlokgMA0MGoUaOqLgE1Q6aQA7lCamQKOZAr5ECukBqZah6a5AAAdLDNNttUXQJqhkwhB3KF1MgUciBXyIFcITUy1TzdVRcAAKn94YKjFbG86jJQI+PGvlILFv6x6jIkSYe85hdVl4AEZsyYocmTJ1ddBmqGXCE1MoUcyBVyIFdIjUw1DzPJAQAAAAAAAACNRZMcAIAOli2fUXUJqJnNNtus6hJQQ+QKqZEp5ECukAO5QmpkqnlokgMA0EHEsqpLQM10d7PiHdIjV0iNTCEHcoUcyBVSI1PNQ5McAIAORo18ZtUloGYeeOCBqktADZErpEamkAO5Qg7kCqmRqeahSQ4AAAAAAAAAaCya5AAAdLBo8aVVl4Ca2WGHHaouATVErpAamUIO5Ao5kCukRqaahyY5AAAdjBr59KpLQM089NBDVZeAGiJXSI1MIQdyhRzIFVIjU81DkxzrlO1TbF9bdR1Yf9i+xPapgxh/gO2wPSFfVcDjdXVtWnUJqJlFixZVXQJqiFwhNTKFHMgVciBXSI1MNQ9N8vWI7S7bH7J9ve2lth+1faHtfauubW2UjcxD2jZ/TdKUCspZw/bMsrb2xyeqrKvBXivp01UXAfRn9Wr+AwlpjRgxouoSUEPkCqmRKeRArpADuUJqZKp5uqsuAAXblnSOpJdI+qikqZLGS3qvpEtsvz4izq+uwjQiYqGkhVXXIekzkn7Qtm1BFYU0le0REbE8IuZUXQvQyaLFl1VdAmqGNQ6RA7lCamQKOZAr5ECukBqZah5mkq8/3iDpMElHRsTpEXFnREyLiHdK+p2k021v0DPY9qttX1nOOH/E9m9a9o20/RXb99heZvs2228v9x1te27rhW0fYjtanp9i+1rb7yrPsdj2ubY3bBmzp+2/lNeeZ/tS289p2T+z/PE35Sztma3nbhk3zPZnbN9b1nqt7YNa9m9XHv9a238ra5lm+3lDerelBRHxYNtjUXnNz9i+3/YmLXX8sbz+sPL5C2xfZntJ+R59q+3z6fMz6E3P52L7VbZvKV/nr2yPsX1UOfv90fI6XS3HvdX2VbYX2H7Q9s9sb96yv2dpkinluMW2/2l7l5YxO9r+re2HbC8sc/WStvq2LN+DJbbvtP3msqbjW8ZMsH267Vm259v+q+3dWvb35OpY23dKWlpuf9xyK51eE1CFcWMP6jwIGISbb7656hJQQ+QKqZEp5ECukAO5Qmpkqnlokq8/3ixpRkT8vpd9X5e0iaQDJcn2KyX9RtIFkp6tYvmSf7eMP0vSmyR9QNIkSe/S4Gdv76Sicf9qSQeV1/lOy/5xks6U9AJJ+0i6VdIFtseV+/cs/zxG0pYtz9t9UNIJkj4i6VmSLpL0O9s7t437ooqlWnaXNEPSz23n+k2IL0qaKel0SbL9XknPl3RURKy2vaOkP0n6dVnzG1W8D6e1nGNtPoMx5fjDVbznB6j4nF9RPt5anuewlmOGq1iqZDdJh0jaTtIZfbymEyTtIWmlpB+17BurIktTVHzOf5L0e9vbtL2ercqaXifpnZLaG9e/LLe9XNJzJV0taartjVvG7FQe/1oVn2VvBvqa+rR06UotWfLYY8WK1YM5HAAAAAAAAA3Ccivrj4mSbupj300tYyTpJEnnRMTJLWOmSZLtiSqa2wdGxMXlvjvWop5RKma131ee9/2S/mj7hHLW9V9bB9t+p6S5kvaX9IeImGVbkuZGxIP9XOcjkr4SEeeUzz9u+0WSjlex1EyPr0XEH8trnSzpRhUN17X9au8rtr/Qtu3lEXFZRKyy/RZJ19r+sorG9bERcXc57pOSzo6IU8vnt9r+gKRLbR8naRut3WcwXNJxEXG7JNn+lYrG+BblMjXTbf9N0osk/UKSIqK12X1HWceVtseWx/Q4KSIuLc/7ZRWf5aiIWBoR01Tmp/Rp24dKeo2k02zvqmIZoD0j4qryHMeq+GJE5fMXSNpL0uYRsazc/BEXa9IfJun75bYRKnI1q683YRCvqU8nfOgyLV68eM3z1xy8gw45dMeBHAr0avny26suATWzySabdB4EDBK5QmpkCjmQK+RArpAamWoemuTrFw9w3O564nrarftWSbp0iLXc3dMgL12h4jcPdpH0oO0tJH1BxczizSV1qZgJvY0GyPZ4FbOTL2/bdbmKWcStrmv5+YHyz8219k3y/9ITZyeveb0RcYftj0j6nqRfRMTPWsbtJulZto9o2WYV78/2kp6pfj4D2zdK2rZ8ellEvLz8eXFPg7z0kKSZbY3hh9Qyg9v2cyWdUta0kR777ZBtJE1vOa6v9+9u22PLc7xSxaz/bkmj9dhnuYuK2edX95wgIm6z/WjLOXdTMSN9dvnlSI/Rklq703f11yAf5Gvq09f/ez+tXr18zfPubn5pBkOzejW3LEBaI0eOrLoE1BC5QmpkCjmQK+RArpAamWoemuTrjxkqluXozaSWMZK0pJ/z9LdPklbric344R2O6c2ZKpaA+aCkuyQtU9FIz3X73xUtP/esnz6UzucjEXFbhzEvVNHs3s52d0SsLLePVdE8/1Yvx9ytYoZ7f16hx97z1s9rRdu46GNbz7roG6hYnuYiSUdImqWikXyRnvg59Pf+fU3FUj4fkXRbWdOvejlHf8aqaL4f0Mu+uS0/L+rvJIN8TX0aNapbESyxgnRGjdpdKxbe13kgMED333+/JkyYUHUZqBlyhdTIFHIgV8iBXCE1MtU8TK9cf5wjaWfbr+5l3wmSZkv6S/n8OhXrR/fmehWf6/597J8laVzrTSbV+9rQ29jequX5Pioa7LeUz/eV9K2IuCAiblTRJN+07RwrVMww71VEzJd0f3muVvtqgDOGc7H9RhXrZh+gokn76ZbdV0uaHBG39fJYrg6fQUTc1TJ+KF23XVV8UfGJcpmYm/XEdcIHYl9JZ0TEbyLiekkPqlgHvMctKr5Qe3bPBts7qZjl3eNqSU+RtLKX9+SRCl4TAAAAAAAAMCA0ydcf56i4SeOZtt9uezvbz7L9PRVrQx8bET2zcD8r6U22P2t7ku1n2v64JEXETBWzvH9k+xDb29s+wPYbymP/T9JiSf/P9o623yzp6F7qWVrWspvt/VTMmj63ZX3xWyW9tbz+3pLO1hNnsc+UNMX2U2xvpN79l4p1yN9oe5dyvezdJX1zYG/bWhtX1tX6GC9Jtp8m6X8lfTwi/qHi5qMn2t6nPPYrkp5v+zTbu9ve2fbBtk+TBvQZpHK3pOWS3m97B9uv0eOb+QN1q6TXlq9lN0k/U8vfDWWj+mJJ37e9l+1nq1hjfIkem5V+sYrfJDjf9kvL/D7f9hdt71HBawKSWrT4H1WXgJrZfvvtqy4BNUSukBqZQg7kCjmQK6RGppqHJvl6IiJCxc0e/5+kD6mYvXuZirWrD4iI81vGXiLp9Sqa59dK+quKmyb2OE7FchnfUbFm9w8kbVAeO0fSW1Qs+XG9pDepWP+53W2SzpN0gaQ/q5i9/p6W/W9XMZP4akk/UdFEf7jtHCeoWMbjHknX9PHSvyXpG5K+XtZzkKTXRMStfYxP5XMqlgdpfXzVxYLaZ0j6t6SepvdFKprmPy1vHnmdilniE1V8RteU57u/5fx9fgaplGt7H60iC9MlfULFkimD9WFJj0r6p6Tfq1ja5Oq2MUeqWA/97yq+zPmBpAUqvkzpye8ryv0/VrE00Dkq8vtQBa8JSGrkiE6rKAGD88gjg/klG2BgyBVSI1PIgVwhB3KF1MhU87jobQGPsX2KpEMiYveKS8F6qpxtf4+kl0TE1Krr6TF16tTxkubdc99/q1j5Bkhj3NhXasHCP1ZdhiTpkNf8ouoSkMD06dM1efLkqstAzZArpEamkAO5Qg7kCqmRqfpYtWqVpk2bJkkbTpkyZX5f47hxJ4CObL9Yxc05r5e0paSvqlhO5+8VlgWsMxFLqy4BNdPdzX+CIT1yhdTIFHIgV8iBXCE1MtU8LLeCJzXbF9pe2MfjxKrrq5HhKpYCulHFciuzVCwDtKLSqoB1ZOGi9eYXJlATEydOrLoE1BC5QmpkCjmQK+RArpAamWoemuR4gog45Um01MqxKm702dvju5VUVEMRcVFEPCMixkTEFhFxaETcVXVdwLoybuwrqy4BNTN9+vSqS0ANkSukRqaQA7lCDuQKqZGp5uF3B/CkFhH3VV0DAAAAAAAAgCcvZpIDANDB8hUzqy4BNbPxxhtXXQJqiFwhNTKFHMgVciBXSI1MNQ9NcgAAOli1anbVJaBmxowZU3UJqCFyhdTIFHIgV8iBXCE1MtU8LLcCoHZe9Yoz1NXVVXUZqJHp06dr8uTJVZeBGrn33nvJFJIjV0iNTCEHcoUcyBVSI1PNw0xyAAAAAAAAAEBj0SQHAKCDbbfdtuoSUDNkCjmQK6RGppADuUIO5AqpkanmoUkOAEAHjz76aNUloGbIFHIgV0iNTCEHcoUcyBVSI1PNQ5McAIAO5s+fX3UJqBkyhRzIFVIjU8iBXCEHcoXUyFTz0CQHAKADbgSL1MgUciBXSI1MIQdyhRzIFVIjU83jiKi6BgBIYurUqeMlzbvtwVO1OpZXXQ7WocNfeU7VJQAAAAAAgPXMqlWrNG3aNEnacMqUKX3+igAzyQEA6OCmm26qugTUDJlCDuQKqZEp5ECukAO5QmpkqnlokgMA0AG/dYXUyBRyIFdIjUwhB3KFHMgVUiNTzUOTHACADiZMmFB1CagZMoUcyBVSI1PIgVwhB3KF1MhU89AkBwCgg/Hjx1ddAmqGTCEHcoXUyBRyIFfIgVwhNTLVPDTJAQDo4O677666BNQMmUIO5AqpkSnkQK6QA7lCamSqeWiSAwAAAAAAAAAaiyY5AAAdbL311lWXgJohU8iBXCE1MoUcyBVyIFdIjUw1D01y1IbtU2xfW3UdOdgeY/vXtufbDtsTqq6pne0zbJ8/iPHbla9l93xVAWksWLCg6hJQM2QKOZArpEamkAO5Qg7kCqmRqeahSd4Qtrtsf8j29baX2n7U9oW29626trVRNlcPadv8NUlTKihnDdszy9rC9iLbV9t+fYJTHyVpP0nPl7SlpHkJzpnaByUdvbYH2z5gff0CAJg7d27VJaBmyBRyIFdIjUwhB3KFHMgVUiNTzUOTvAFsW9I5kj4j6ZuSJkk6QNI9ki7ppdn8pBQRCyNidtV1qHift5T0bElXSvqF7ef3NtD2iAGec0dJN0XEDRHxYEREmlLTiYh5ETG36jqAHIq/RoF0yBRyIFdIjUwhB3KFHMgVUiNTzUOTvBneIOkwSUdGxOkRcWdETIuId0r6naTTbW/QM9j2q21fWc44f8T2b1r2jbT9Fdv32F5m+zbbby/3HW17buuFbR9iO1qen2L7WtvvKs+x2Pa5tjdsGbOn7b+U155n+1Lbz2nZP7P88TflzOOZreduGTfM9mds31vWeq3tg1r29yz38VrbfytrmWb7eUN6t6UFZSN7hqT3Sloi6dU9tdv+tO2zbM+X9P1y++ts31jWOdP2CS11XiLpBEkvLOu9pLeL2j6s/E2BJbZn276453PtWQrF9sm2Z5XLtny3tUlfvl+ftH1neY5ptg9ru8bTbf+hPH6B7cts79h6jZaxB9n+h+25ZT1/6BnbS+3bSfpb+fTR8nWeYfvI8tiRbePPt/2TTh8E8P/Zu++wuco6/+PvDwlViqCggBTpYCGrYkMlGNvqqtgQdVUU1/ZbK7quugqK7lpXZO1YQGXBjgXU1VBUxAoEpIUWQIqUUAwJJIT798c5D0yGp6ScOwMz79d1zfU8c84953zPzCfo9Z37uU9Xdt1110GXoCFjplSDuVLXzJRqMFeqwVypa2Zq9NgkHw0vBeaWUn48zr5PAvcDngqQ5FnAD4DjaWZCzwL+0DP+68BLgDfTzEh/HbBgBevZgaZx/2zgGe15PtezfwPgSOAJwGOBC4Djk2zQ7t+j/fkqmhnbezC+t9A0l98BPBz4OfCjJDv2jfswzVItM4C5wNFJpq/gNY2rlHI7sATonTH+DmAOzXUfkuSRwLdpZvs/DDi43b5/O/75wOHAqTTX+/z+8yTZHDga+Cp3/aXA94Herz5n9ex7SXucg3r2vxt4BfB64CHAp4BvJtmrPceWwK+A24AnA49szzfRe3Uf4L+BR7XnvoPmi43x/rtzOfCC9ved2+t8C/AdYBrwnJ5r3Qx4VnvucS1adPsyjyVL7phoqLRczj///EGXoCFjplSDuVLXzJRqMFeqwVypa2Zq9HTSCNQ93k7AuRPsO7dnDMB7gWNKKb3N0zkASXaiaW4/tZTyy3bfxStRzzo0s9qvaI/7JuC4JAe2M7BP6B2c5LXAjcBewE9KKde2f/ZyYynl6knO8w7go6WUY9rn70qyN/BWmhneYz5RSjmuPddBwNk0jfzzVuLaeutei6ZJvxHQe00nlFI+2TPuKGB2KeWQdtPcJLsB7wSOKKXMT7IQWDzJ9W5O8+/5+6WUS9ttZ/WNWQy8upSyEDg7yfuBjyd5H7Am8B7gKaWUU9vxFyd5As0XISfTvGc3AfuVUpaM1TrR9ZdSvtf3frwauBbYDfhL39ilSea3T6/pXbYlyf/SfCHynXbTPwOXASdNdO73vuVXLFy48M7nz3zedvzT83eYaLg0paVLlw66BA0ZM6UazJW6ZqZUg7lSDeZKXTNTo8cm+ehY3sWUZtDMWp5o31KahumquGysQd46leavGnYGrk7yAOBDNDOeN6OZSbwesPXyniDJhsAWwCl9u04Bdu/bdmbP71e1Pzdj5ZvkH03yIZovAxYA/z7WhG/9qW/8rsAPx6nzrUmmlVKW+S9zkicCP+3Z9DqaWeizgbOS/Bz4P+C7pZQbesbNaRvkY04F1ge2an+uB/wiy667tRZwevv7DODXPQ3ySbUz9j8IPAa4P3f95crW9DXJp3A48MckW7a52Z/my4MJ12X/8KefxB1l8Z3Pp0/3j2a0ajbccMNBl6AhY6ZUg7lS18yUajBXqsFcqWtmavTYJB8Nc2kasePZtWcMNOtnT2SyfdAsp9HfjF9ziteM50iaJWDeAlxKs7zHqSy7ZEmXepu+Y43XVemqfhw4gqZB/rdxmrm3rMKxoWmyz+h5/rd2JvZTgccDTwPeBHw4yWNKKZcsxzHXb38+C7iib99t7c+pPv9+P6b5/P4FuJLmPf0LK/g5llJOTzIHeEWS/6NZCuZZk71m3XWnc0dxiRV1Z5NNNhl0CRoyZko1mCt1zUypBnOlGsyVumamRo/TK0fDMcCOSZ49zr4DgeuBX7TPz6RZP3o8Z9FkZq8J9l8LbJCem4CybDN3zNZJtuh5/liaBvvYgk97AoeVUo4vpZxN06S9f98xltDMMB9XKeVmmsbsnn279gTOmeh1HbmulHJhu3TMhLOde5zL+HXO7Z9FDlBKWdQef+zx93Z7KaWc0i6V8w80y6s8r+eluydZt+f5Y2ka+ZfTvCe3AVv3HfvCUsrl7fgzgScmmfKLjyT3o/nLgA+VUmaXUs4FNp7iZWNTv8f7XL9MM4P8VcAve2qSVot58+YNugQNGTOlGsyVumamVIO5Ug3mSl0zU6PHJvloOIbmZpxHJjkgybZJHp7kizQ3RHxNKWVsdvMHgJck+UCSXZM8LMm7AEop82hmeX81yT5JHpxkZpJ929f+HlgI/GeS7ZO8lKax2e/Wtpbd26VDDgO+3bPe9gXAy9vzPwY4irvPYp4HzErywCQTNV8/TrMO+YuT7JzkIzRN+08v39u22nyS5lrel2SnJK8E/pXmZqLLJcljkrwnyaOSbE1zU85NWXYt+rWAryTZLckzaT7rz5RS7mgb7Z8APpXkle3n94gkb2rrAfgMsCFwTHueHZO8PMnO45R0A82XL69NskOSJ9PcxHMyl9LM5P+nJJsmWb9n3/8CD6KZlT7hDTslSZIkSZKkFWWTfAS0s5n3Bf4TeBvNjO1fA9sAM0spx/aMPQl4EU3z/AyaG04+uudwbwC+C3yOZs3uw4H7tK+dT3NTxWfSzDp/CXDwOCVdCHwfOJ5m7ewzgTf27D+AZtbxacA3aJro1/Qd40DgqTSzoE9nfIfRNGY/2dbzDOA5pZQLJhg/EKWU02g+n/1oliP5IPD+UsoRK3CYm4En0bync2nWdD+wlNK7dvlsmi8gfgV8C/gRy34+7wMOAd5N01z/Gc2yJpe0dV4PPJlmaZaTgT/TNK3vtkZ5KeWO9noe2V7Tp2huRDqhdr3xg4CPAH+jacqP7bsJ+B7NzPdjJzuOVMOWW2456BI0ZMyUajBX6pqZUg3mSjWYK3XNTI2eLN9qEFI3khwM7FNKmTHgUkZKkiOA+5ZS9hlwKSstyWzg7FLKmycaM3v27A2Bmy68+tBlbtyp4bffs46pevyrr76aBz7wgVXPodFiplSDuVLXzJRqMFeqwVypa2ZqeCxdupQ5c+YAbDRr1qybJxrnTHJJ92hJNk7yPGAm8NkBl6MRNX/+/EGXoCFjplSDuVLXzJRqMFeqwVypa2Zq9NgklyaQ5KdJFkzweM+g6xshpwNHAO8qpZw/xVhJkiRJkiRphbjcijSBJFsC606we367BrvuQVxuZXTVXm6llEKSqufQaDFTqsFcqWtmSjWYK9VgrtQ1MzU8XG5FWkWllCtKKRdO8LBBLo2QCy+8cNAlaMiYKdVgrtQ1M6UazJVqMFfqmpkaPTbJJUmawpIlSwZdgoaMmVIN5kpdM1OqwVypBnOlrpmp0WOTXJKkKay//vqDLkFDxkypBnOlrpkp1WCuVIO5UtfM1OiZPugCJKlrL3j615g2bdqgy9AQ2XTTTQddgoaMmVIN5kpdM1OqwVypBnOlrpmp0eNMckmSpnDJJZcMugQNGTOlGsyVumamVIO5Ug3mSl0zU6PHJrkkSZIkSZIkaWTZJJckaQpbbLHFoEvQkDFTqsFcqWtmSjWYK9VgrtQ1MzV6bJJLkjSFxYsXD7oEDRkzpRrMlbpmplSDuVIN5kpdM1Ojxya5JElTuO666wZdgoaMmVIN5kpdM1OqwVypBnOlrpmp0TN90AVIUte+8ctXcUfxW997q1c/45hBlyBJkiRJkkaIM8klSZrCzjvvPOgSNGTMlGowV+qamVIN5ko1mCt1zUyNHpvkkiRNYd68eYMuQUPGTKkGc6WumSnVYK5Ug7lS18zU6LFJLknSFG677bZBl6AhY6ZUg7lS18yUajBXqsFcqWtmavTYJJckaQr3uc99Bl2ChoyZUg3mSl0zU6rBXKkGc6WumanRY5NckqQpPPCBDxx0CRoyZko1mCt1zUypBnOlGsyVumamRo9NckmSpnDRRRcNugQNGTOlGsyVumamVIO5Ug3mSl0zU6PHJrkkSZIkSZIkaWTZJNfQSHJwkjMGXceqSHJEkmMHXUdNSUqSfQZdh7Qi/FM7dc1MqQZzpa6ZKdVgrlSDuVLXzNTosUk+IpJMS/K2JGcluTXJDUl+mmTPQde2MiZotH4CmDWAcpaR5PFJjm/f41vb9/ztSab1jNm2vYYZAyx1UDYHfjroIqQVcccddwy6BA0ZM6UazJW6ZqZUg7lSDeZKXTNTo8cm+QhIEuAY4P3Ap4FdgZnA5cBJwzKrt5SyoJRy/SBrSPI84GTgr8DewC407/l/AMe0n8Xqrmlakur/1pOsuTzjSilXl1Juq12P1KVrrrlm0CVoyJgp1WCu1DUzpRrMlWowV+qamRo9NslHw77AC4FXlFK+XEq5pJQyp5TyWuBHwJeT3GdscJJnJ/ljOwv6uiQ/6Nm3dpKPJrk8yW1JLkxyQLtv/yQ39p44yT5JSs/zg5OckeR17TEWJvl2ko16xuyR5BftuW9KcnKSR/Tsn9f++oN2Nva83mP3jFsjyfuT/LWt9Ywkz+jZPzab+/lJTmxrmZPkcSvzJrfv4eHAj0opry2lnFFKmVdK+TLwyvYz2Lcdfkn78/S2hpP6jvWOJFcluT7JZ3sb0O1n8IkkVyS5Jcnvk8zs2b9/khuTPCfJOcBtwNbj1DszyR/aY9yY5JQk2/Tsf26S09ocXJzkoCTTe/aXJG9I8qMktwDva9/rN/Sd5x+S3DF27P6/AkjyoCRHJ5nf1vKnJI9Z3jokSZIkSZKkVWGTfDS8FJhbSvnxOPs+CdwPeCpAkmcBPwCOB/6BZvmSP/SM/zrwEuDNNDPSXwcsWMF6dqBpFj8beEZ7ns/17N8AOBJ4AvBY4ALg+CQbtPv3aH++imbpjj0Y31uAA4F3AA8Hfg78KMmOfeM+TLNUywxgLnD0SjZhn0bzXn6if0f73s+lee8AHt3+fEp7Dc/vGb43sH3785XA/u1jzGeAxwH7tdf1HeBnfde1HvAu4DXAQ4BlvgJtr+9YmlnvD2+P9yWgtPufSPNZfxrYjeZz3h94b9+lHUyTl4cBXwaOpslbr5cBp5RSLu3bTpL12xq2BJ4D7A58jPa/TStQxzJuW3g7t/Y8bl/in0lp1ey4Y/9/NqRVY6ZUg7lS18yUajBXqsFcqWtmavQ4G3M07AScO8G+c3vGQNN8PKaUclDPmDkASXaiaW4/tZTyy3bfxStRzzo0s9qvaI/7JuC4JAe2S3Gc0Ds4yWuBG4G9gJ+UUq5tVy25sZRy9STneQfw0VLKMe3zdyXZG3gr8P96xn2ilHJce66DgLNpGvnnreB1jb2HE73X5/WMubb9ef0413AD8K+llKXAeUmOo/my4vAkW9N8ObB1KeXKsfrbGfKvAt7TblsTeGMpZc4EtWwIbETzfl40Tt0HAR8ppRzZPr84yftoGtgf6Bn3v6WUr409SXIUcGCSrUspl7XLvOwHfGiCOl4KbArsUUqZ3267cCXqWMYhb/oVCxcuvPP5U5+/HU9/4Q4TDZemdPnll7PddtsNugwNETOlGsyVumamVIO5Ug3mSl0zU6PHJvnoWN61sGfQLBky0b6lNDN/V8VlYw3y1qk0M4d3Bq5O8gCapupMYDNgGs3M6LstGTKRJBsCWwCn9O06hWa2cq8ze36/qv25GSveJL/z9Cv5ujFntw3yMVfRzNSm/TkNmJtllzdfG+hdj30x7XW1jfVzevb9ZynlP5McAfw8yS+AXwLfLqWMXf/uwJ5JemdsTwPWSbJeKWWsA/2n3iJKKWckOZem+f0Rmi82NqOZ7T6eGcDpPQ3yfstbxzLe9z9PYmlZfOfz6Wv6RzNaNbfeeuugS9CQMVOqwVypa2ZKNZgr1WCu1DUzNXpsko+GuTRLo4xn154xAIsmOc5k+wDu4O4N4uW6mWOfI2mWLXkLcCnNmtqnAmutxLGWx5Ke38fWT1+ZrurYe7gr8Ntx9u/Kss3q5alnrKaxetan+aLike3PXr3L3iwqpYxdy5U0zegx8wFKKa9KchjNkjcvBj6U5KmllN+15zkI+P449fX+L8Ut4+w/irua5C8FfjbJDVWnytTy1rGMtdebzh3FJVbUnXXXXXfQJWjImCnVYK7UNTOlGsyVajBX6pqZGj1OrxwNxwA7Jnn2OPsOpJmB/Iv2+Zk0S3uM5yyazOw1wf5rgQ3ScxNQlm3Ojtk6yRY9zx9L02A/v32+J3BYKeX4UsrZNE3y+/cdYwnNjOJxlVJupmkO79m3a0+Wr1G9Mv6PpgF9YP+OJM8BdqRZsxuamd4wyTVM4PT2NZuVUi7se4y79Ewp5fa+cfN79p1eSvmvUsrjgb9w13ripwE7j3OOC0uZsvv8v8BDkzyS5malR00y9kxgRpJNJti/KnVInXnQgx406BI0ZMyUajBX6pqZUg3mSjWYK3XNTI0em+Sj4RiamysemeSAJNsmeXiSL9LcLPE1pZSxGcEfAF6S5ANJdk3ysCTvAiilzKOZ5f3VJPskeXCSmUn2bV/7e2Ah8J9Jtk/yUpa94eSYW9tadm9vzHgYzVIfY03eC4CXt+d/DE2TtX/G8TxgVpIHJtl4guv+OM065C9OsnOSj9A07T+9fG/bimnfw9cBz03ypfY93jbJAcARwHeBb7fDr6G5pmckeUCSjZbzHHNp3o+vJ3l++xk8Osm725uuLpf2df+V5HFJtknyNJom/ti65B8EXpHkoCQPaT+L/ZJMtLZ4b43zaGbSf4Wmof+jSYYfDVwNHJtkzyTbJXlBksetah1Sly644IJBl6AhY6ZUg7lS18yUajBXqsFcqWtmavTYJB8B7bIb+wL/CbyNZsb2r4FtgJmllGN7xp4EvIimeX4GcALw6J7DvYGm2fs5mjW7Dwfu0752PvDPwDNpZp2/BDh4nJIupFk+43ia2ddnAm/s2X8AsDHNLOJv0DTRr+k7xoHAU4HLaWZXj+cw4L+BT7b1PAN4Timl2n/pSinfBfamWT/91zTv9duADwP7jS2BUkq5HXgzTVP9SuCHK3CaVwFfp7mu84FjgT2Ay1bgGAuBXYDv0SwT8yXgs8AX2/p+DvwT8DTgj8Dv2uu4dDmPfxTNeuI/KKVMuKRKKWVxe45raPJwFvDvtEvJdFCHJEmSJEmSNKnctWyxVF+Sg4F9SikzBlyKhtDs2bM3BG4689pDuaPnxp26d3n1M44ZdAl3c91113H/+/ev+iStPDOlGsyVumamVIO5Ug3mSl0zU8Nj6dKlzJkzB2CjWbNm3TzROGeSS5I0haT/nsTSqjFTqsFcqWtmSjWYK9VgrtQ1MzV6bJJLE0jy0yQLJni8Z9D1SVp9/va3vw26BA0ZM6UazJW6ZqZUg7lSDeZKXTNTo2f6oAvQaCmlHMz465TfE70GWHeCffNXZyGSJEmSJEmS6rBJLk2glHLFoGuQdM+w/fbbD7oEDRkzpRrMlbpmplSDuVIN5kpdM1Ojx+VWJEmawlVXXTXoEjRkzJRqMFfqmplSDeZKNZgrdc1MjR6b5JIkTWHhwoWDLkFDxkypBnOlrpkp1WCuVIO5UtfM1OhxuRVJQ+flT/ka06ZNG3QZGiJrr732oEvQkDFTqsFcqWtmSjWYK9VgrtQ1MzV6nEkuSdIUttlmm0GXoCFjplSDuVLXzJRqMFeqwVypa2Zq9NgklyRpCnPnzh10CRoyZko1mCt1zUypBnOlGsyVumamRo9NckmSJEmSJEnSyLJJLknSFDbddNNBl6AhY6ZUg7lS18yUajBXqsFcqWtmavTYJJckaQrTp3ufa3XLTKkGc6WumSnVYK5Ug7lS18zU6LFJLknSFK666qpBl6AhY6ZUg7lS18yUajBXqsFcqWtmavT4tYikofPFE17F0rJ40GWMhDc97ZhBlyBJkiRJkrRKnEkuSdIUtttuu0GXoCFjplSDuVLXzJRqMFeqwVypa2Zq9NgklyRpCtdcc82gS9CQMVOqwVypa2ZKNZgr1WCu1DUzNXpskkuSNIUFCxYMugQNGTOlGsyVumamVIO5Ug3mSl0zU6PHJrkkSVNYa621Bl2ChoyZUg3mSl0zU6rBXKkGc6WumanRY5NckqQpuB6dumamVIO5UtfMlGowV6rBXKlrZmr02CSXJGkK55133qBL0JAxU6rBXKlrZko1mCvVYK7UNTM1emySq7ok85K89Z5ynBU43xFJjp1izGqt6d4uycFJzljFY2ybpCSZ0U1VkiRJkiRJGmU2yTWhJDPbZuTY49okxyd5WOXz7p/kxnF27QF8qea5V0LVmpKclOTQcbZP9B7d030CmDXoIqQVdb/73W/QJWjImCnVYK7UNTOlGsyVajBX6pqZGj02ybU8dgY2B54OrA0cl2S138GglHJtKWXh6j7vZO6JNQ3aeNlIY3opZUEp5fpB1CWtinXWWWfQJWjImCnVYK7UNTOlGsyVajBX6pqZGj02ybU8rimlXF1KOQ04FNgK2GVsZ5InJPl1kkVJLk9yWJL7THSwJG9PclaSW9rxn0uyfrtvJvA1YKOeGewHt/uWWdokydZJfphkQZKbk3w7yQN69h+c5IwkL29fe1OSY5Js0DPmhW0ti5Jcn+SX/bUneUeSq9r9n02yZs++/ppKkjck+Wl7zIuTvHAF3+8VNrY0zHLU+h9Jvt6+Z5cmeU6STXvexzOTPKrnNfdLcnSSK5IsbN+rl/Sd+6Qkn0lyaJLrgJ/3/BXCPyb5M3Ab8ITxlltJ8pok5ya5Ncl5Sd7Yt//RSU5v9/8J+IcKb6E0qSuuuGLQJWjImCnVYK7UNTOlGsyVajBX6pqZGj02ybXckmwE7Nc+Xdxu2x74GfA94OHAi4EnAJ+Z5FB3AG8GHgK8Engy8LF232+BtwI308xe35xmiY7+WtYAfghsAuwFPBXYDvhW39DtgX2Af2ofewH/3h5jc+Bo4KvArsBM4PtAel6/d3uMvdta928fkzmE5v3YHTgKOCbJrlO8pgvLU+vbgFNoGs3HAd8Avg58E3gEcBHw9SRj78E6wJ+BZwEPpVla5htJHt133FfSZGJP4PU92z9C837vCpzZX3CSlwEfBN7bjnkPcEiSV7b71wd+ApwDPBI4mHHy0O/Whbcv87h9yR1TvUSSJEmSJEkjavqgC9C9wl/bnunYDOsflVLGbvP7buCoUsqh7fMLkrwZODnJG0opt/YfrGcswLwk/wF8AXhjKWVxkpuaYeXqSWqaBTwMeHAp5XKAJK8Azk6yRynlj+24NYD9Syl/b8d8o33te2ka8NOB75dSLm3Hn9V3nhuAfy2lLAXOS3Jc+/rDJ6ntO6WUL7e/vy/JU4E3AW+c5DVdWJ5ajy+lfBEgyQeBNwB/LKV8p932UeBU4AHA1aWUK1i2Kf0/SZ4O7Av8oWf7BaWUfxt70n4BAfD+Usoverb31/wB4MBSyvfb55ck2Q14HXAk8FKaz/CANktnJ3kQ8PnJ3oj//n+/YuHCu1bBmfmC7dj7RTtM9hJpUttuu+2gS9CQMVOqwVypa2ZKNZgr1WCu1DUzNXpskmt5PBFYCDyWZqZv70zh3YGHtzOCx4Smsflg4Nz+gyV5Ck1zfRdgQ5ocrpNkvRVY33tX4PKxBjlAKeWcNDez3BUYa5LPG2uQt64CNmt/nwPMBs5K8nPg/4DvllJu6Bl/dtt07n39VDcuPXWc5zOmvKJVtzy19s7m/lv786xxtm0GXJ1kGs1nvi+wJbAWzbr0/Z/Tnyeo6U8TFdsua7M98JUkvY386cBN7e+7Amf2fdnS//7ezds/+ySWlsV3HXBN/2hGq2b+/Pmst956gy5DQ8RMqQZzpa6ZKdVgrlSDuVLXzNTosUmu5XFJKeVG4Pwkm9EsafKkdt/6wBeBw8Z53WX9G5JsS7N8xudpZnPPp1me5Ss0Ddiub4K5pO95oV1mqJSytJ3l/XjgaTSzvT+c5DGllEumev1qcjOw0Tjb78tdjeQxy1PrnWNKKaWd2b2k7zX0vO6dwFtolsA5C7iFZl36/ptz3jJ++RNuhyY7AP8C/L5v31JWwTrrTWdpcYkVdefmm28edAkaMmZKNZgrdc1MqQZzpRrMlbpmpkaP0yu1oj4LPDTJ89rnpwG7lVIuHOexeJzXP5ImdweWUn5XSpkLbNE3ZjEwbYo6zgW2SrLV2IZ2mY770qxfvVxK45RSykE063QvBp43xcum8thxnt9tRv1yOp9mrfB+jwDmruQxV8SewA9LKd8spcwBLgZ26uLApZS/AVcC242TnbEvKc6l+UuF3ttK97+/UnXTp/udsrplplSDuVLXzJRqMFeqwVypa2Zq9Ngk1wppl0M5HPhAe3PHjwKPT/KZJDOS7JjkuUkmunHnhcCawJuSbJfk5Sy7fAvAPGD9JLOS3D/JeH/f8kuamc1HJXlEeyPJrwMnl1ImXOKjV5LHJHlPkkcl2Rp4PrApK9/QHvOiJK9OslOSDwCPZvIbmU7m88BOSQ5L8vAkOyd5O/AS4JOrWOfyuAB4apLHtzcf/SLNeuVdOQh4d5I3t+/Xw5K8qr1GgP+lmd1+eJLdkjwTeEeH55eWy047dfLdkHQnM6UazJW6ZqZUg7lSDeZKXTNTo8cmuVbGZ2jWin5RKeVMYC+a2cW/Bk4HPkgzQ/hu2tnIbwfeBfwFeBnN+uS9Y35LcyPPbwHXAv/WdxhKKQV4Ls3NKn9F0zS/GHjxClzHzTTLxhxPMyv7QzQz3H+6AscYz0HAfjTrf78CeEkpZblnt/cqpVzc1rgLzTX+nmZ98BeVUn62inUujw/R/LXAz4GTgKuBY7s6eHuD09cAr6L50uNkYH/gknb/AuDZNGurnw58mCY70mp1zjkr9U9YmpCZUg3mSl0zU6rBXKkGc6WumanRk6bXKKkLSQrwvFLKsYOuZRTNnj17Q+Cm311/6DI37lQ9b3raMYMuYbU455xz2G233QZdhoaImVIN5kpdM1OqwVypBnOlrpmp4bF06VLmzJkDsNGsWbMmXGzemeSSJE1h4403HnQJGjJmSjWYK3XNTKkGc6UazJW6ZqZGj01yaTVp1z9fMMFjVZd4kVTR+uuvP+gSNGTMlGowV+qamVIN5ko1mCt1zUyNHpvkUodKKZlkqZUvADMmeLymcmmSVsHll18+6BI0ZMyUajBX6pqZUg3mSjWYK3XNTI2e6YMuQBoVpZT5wPxB1yFJkiRJkiTpLs4klyRpCltvvfWgS9CQMVOqwVypa2ZKNZgr1WCu1DUzNXpskkuSNIWbbrpp0CVoyJgp1WCu1DUzpRrMlWowV+qamRo9Lrciaei87slfY9q0aYMuQ0PkpptuYssttxx0GRoiZko1mCt1zUypBnOlGsyVumamRo8zySVJmsIaa/g/l+qWmVIN5kpdM1OqwVypBnOlrpmp0ZNSyqBrkKROzJ49e0Pgpt13392Z5JIkSZIkSSNu6dKlzJkzB2CjWbNm3TzROL8WkSRpCuedd96gS9CQMVOqwVypa2ZKNZgr1WCu1DUzNXpskkuSNIU77rhj0CVoyJgp1WCu1DUzpRrMlWowV+qamRo9NsklSZrCRhttNOgSNGTMlGowV+qamVIN5ko1mCt1zUyNHpvkkiRNwf+DpK6ZKdVgrtQ1M6UazJVqMFfqmpkaPdMHXYAkde2jJ7+a21k86DLu1d7/5KMHXcI9ymWXXcZuu+026DI0RMyUajBX6pqZUg3mSjWYK3XNTI0eZ5JLkiRJkiRJkkaWTXJJkqaw1VZbDboEDRkzpRrMlbpmplSDuVIN5kpdM1Ojxya5JElTWLBgwaBL0JAxU6rBXKlrZko1mCvVYK7UNTM1emySS5I0hRtuuGHQJWjImCnVYK7UNTOlGsyVajBX6pqZGj02ySVJkiRJkiRJI8smuSRJU/Cu5uqamVIN5kpdM1OqwVypBnOlrpmp0WOTXJKkKcydO3fQJWjImCnVYK7UNTOlGsyVajBX6pqZGj02yXWPkaQk2eeecpxhluTgJGcMuo6VkWRm+xnfd9C1aHTcfvvtgy5BQ8ZMqQZzpa6ZKdVgrlSDuVLXzNTosUmuSfU0JG9Isk7fvj3afaWj020O/LQ99rbtsWd0dOzlsirnHXRzvqf2scffk5yd5LNJduwb/glg1iDqlO6NNtxww0GXoCFjplSDuVLXzJRqMFeqwVypa2Zq9Ngk1/L6O/C8vm0HAJet6oGTrAVQSrm6lHLbqh5PPIXmC4fdgfcAuwJzktzZFC+lLCilXF+ziLHPVRoGm2yyyaBL0JAxU6rBXKlrZko1mCvVYK7UNTM1emySa3kdCbx67EmSdYH92u30bL9fkqOTXJFkYZKzkrykb8xJST6T5NAk1wE/b7f3zsS+pP15erv9pHbMHkl+keS6JDclOTnJI1bkQpJsnOSoJNcmWZTkgiSvWpXzJpnX/vqD9nXz2u1HJDm27/yHjh23ff7C9n1alOT6JL9Mcp8VuaY+17dfOFxcSvkhTdP898BXkkxrz3nncitJnpbk1v7lS5J8OskJPc9f0M5Mvy3JvCQH9o2fl+R9Sb6e5GbgS+32PdvPfGH7Fwk/T7Jxu2+NJO9Ockl7/XOSvLDvuM9MMrfdfyKw7Sq8N9JKmTdv3qBL0JAxU6rBXKlrZko1mCvVYK7UNTM1emySa3l9A3hikq3b5y8A5gGn9Y1bB/gz8CzgoTSN0m8keXTfuFcCi4E9gdePc76x8WOzop/fPt+ApjH/BOCxwAXA8Uk2WIFrOQTYDfhHmlnWbwCuW8Xz7tH+fFX7urHnk0qyOXA08NW2lpnA94GswPVMqpRyB/BpYBvgkeMMmQ3cSPOZjtU1DXgxcFT7/JHAt4FjgIcBBwOHJNm/71jvAOYA/9Dun9Ee/xzgcTTv34+Bae34dwOvoMnAQ4BPAd9Msld73q1o3o8fAzOALwMfmeqab1t0O7ctvOtx+5I7pnqJJEmSJEmSRtT0QRege41raNYL3x/4IM2s8q/2DyqlXEGz3vWY/0nydGBf4A892y8opfzbJOe7tv15fSnl6p7jn9A7KMlraRq8ewE/Wc5r2Ro4vZTyp/b5vFU9bynl2iQAN/a+bjlsTvPv8PullEvbbWetwOuX13ntz21Z9nOglLI0yTHAS4GvtJtnAfcFvtc+fzswu5RySPt8bpLdgHcCR/Qc7oRSyifHniT5X+BPpZQ39ow5u923Ns1yME8ppZza7rs4yROA1wEn03yBcVEpZWzW+vlJHga8a7KL/crrTmbhwoV3Pn/Mi7bncS/eYbKXSJPacsstB12ChoyZUg3mSl0zU6rBXKkGc6WumanRY5NcK+KrwKeTfJNmVvCLgCf2DmhnIL+Hpim+JbAWsDawcNlD8eeVKSDJA4AP0cy43oxmRvJ6NI3v8cb/tKfGS0spDwE+D3yvXS7l/4BjSym/7fK8K2AOzUzrs5L8vK3nu6WUG1bxuP3GZqZPdJPVo4DfJdmilHIl8DLguFLKje3+XYEf9r3mFOCtSaaVUpa22/7UN2YG8J0JzrkDzXv4i/YLhjFrAaf3nPf3fa87lSkc8MW9uL0svvP5tDX9oxmtmltvvZWNNtpo0GVoiJgp1WCu1DUzpRrMlWowV+qamRo9do60In4KrEsz2/jHE9z48Z3AW4CPAnvTNEl/TtP47HXLStZwZHvMtwCPb3+/fpzjj3lNO2YG8EyAUspPaZYe+RSwBTA7yScmeP3KnnfMHdx96ZQ1x35pm8tPpVn65RzgTTSzpR88xXFX1K7tz0vG21lK+SNwEbBfu97882iXWllB/Z/roknGrt/+fBZ3fUYzaJbCeeG4r1hOa687nbXXu+sx3Sa5VtH111e9z61GkJlSDeZKXTNTqsFcqQZzpa6ZqdFj50jLrZRyO/B1mtnUd1tqpbUn8MNSyjdLKXOAi4GdVuJ0Y9OAp/Vt3xM4rJRyfCnlbOA24P6T1HxFKeXC9nFpz/ZrSylHllL+GXgr8NoOzrtknNddS7OkSq8ZfTWWUsoppZSDaNbyXkzTpO5EkjWAN9M0yE+fZOhRNDPIn03T3D+uZ9+5NO9Brz2BuT2zyMdzJs3SLeM5h+Z93LrnMxp7XN5z3v717B87yfkkSZIkSZKkFWKTXCvqfcCmNLPDx3MB8NQkj0+yK/BF4AErcZ5raGYhPyPJA5KM/Y3LBcDLk+ya5DE0jd3JZivfTZIPJnlukh2SPAT4J5pm7Kqedx4wK8kDk2zcbjsBeFSSVyTZMckHaG5oOlbLY5K8J8mj2puiPp/m/T2XlXe/tobtkjwH+CVNo/mAKRraRwGPAN5Ls+TLbT37Ptle2/uS7JTklcC/suz68+P5L2CPJJ9L8vAkuyR5Q5L7l1L+3r7+U0lemWT7JI9I8qb2+ABfAHZM8vEkOyd5Kc26+NJqtcsuuwy6BA0ZM6UazJW6ZqZUg7lSDeZKXTNTo8cmuVZIKWVxKeW6UspEa1t/CDiNpol+EnA1cOxKnOd2mtnPrwOu5K71sA8ANm7P8Q3gMJrG9opYTNO8PRP4FbAU2K+D8x5Is3TK5bQztkspPwcOAT4G/BHYgGY2/pibgScBxwNzad6/A9slYVbWL4GraG4A+hGahvvDSyknTvaiUsqFNDf1fDh9S62UUk6jWWd+P+AvNDdvfX8p5YgpjjkXeBqwe3vsU4HnAre3Q95H8/68u63zZzTLr1zSvv4y4AXAPjTrt7+eZs17abW6+OKLB12ChoyZUg3mSl0zU6rBXKkGc6WumanRk4l7nZJ07zJ79uwNgZt+duOnuZ3FU47XxN7/5KMHXcI9yjnnnMNuu+026DI0RMyUajBX6pqZUg3mSjWYK3XNTA2PpUuXMmfOHICNZs2adfNE45xJLknSFNZff/2pB0krwEypBnOlrpkp1WCuVIO5UtfM1OiZPugCJI0vyYJJdv9jKeXXq60YacRtttlmgy5BQ8ZMqQZzpa6ZKdVgrlSDuVLXzNTocSa5dM81Y5LHnwZRkDSqXI9OXTNTqsFcqWtmSjWYK9VgrtQ1MzV6nEku3UO1N9KUJEmSJEmSVJEzySVJmsLmm28+6BI0ZMyUajBX6pqZUg3mSjWYK3XNTI0eZ5JLGjrv2uurTJs2bdBlaIjcfvvtgy5BQ8ZMqQZzpa6ZKdVgrlSDuVLXzNTocSa5JElTuPbaawddgoaMmVIN5kpdM1OqwVypBnOlrpmp0WOTXJIkSZIkSZI0smySS5I0hZ122mnQJWjImCnVYK7UNTOlGsyVajBX6pqZGj02ySVJmsKll1466BI0ZMyUajBX6pqZUg3mSjWYK3XNTI0em+SSJE3htttuG3QJGjJmSjWYK3XNTKkGc6UazJW6ZqZGj01ySZKmsN566w26BA0ZM6UazJW6ZqZUg7lSDeZKXTNTo2f6oAuQpK69+ZRXs4TFgy7jHutLTzp60CXc62y++eaDLkFDxkypBnOlrpkp1WCuVIO5UtfM1OhxJrkkSVO46KKLBl2ChoyZUg3mSl0zU6rBXKkGc6WumanRY5NckiRJkiRJkjSybJJLkjSFBzzgAYMuQUPGTKkGc6WumSnVYK5Ug7lS18zU6LFJLknSFEopgy5BQ8ZMqQZzpa6ZKdVgrlSDuVLXzNTosUkuSdIUrrnmmkGXoCFjplSDuVLXzJRqMFeqwVypa2Zq9NgklyRJkiRJkiSNLJvkkiRNYccddxx0CRoyZko1mCt1zUypBnOlGsyVumamRo9NcqmVZF6St95TjrMC5zsiybFTjFmtNS2PJDOTlCT37dm2T5ILkyxNcujgqpOW9de//nXQJWjImCnVYK7UNTOlGsyVajBX6pqZGj02yXWv19NsHXtcm+T4JA+rfN79k9w4zq49gC/VPPdKqFZTktcn+XuS6T3b1k+yJMlJfWPHPqvtgd8CmwM39Qz5IvBdYCvgfTXqlVbGokWLBl2ChoyZUg3mSl0zU6rBXKkGc6WumanRY5Ncw2Rnmqbr04G1geOSrLW6iyilXFtKWbi6zzuZyjWdCKwPPKpn2xOBq4HHJFmnZ/vewGWllItKKYtLKVeX9pbRSdYHNgN+Xkq5spTy90r1SitsnXXWmXqQtALMlGowV+qamVIN5ko1mCt1zUyNHpvkGibXtE3X04BDaWYj7zK2M8kTkvw6yaIklyc5LMl9JjpYkrcnOSvJLe34z7WNXJLMBL4GbNQzg/3gdt8yS5sk2TrJD5MsSHJzkm8neUDP/oOTnJHk5e1rb0pyTJINesa8sK1lUZLrk/yyv/Yk70hyVbv/s0nW7NnXX1NJ8oYkP22PeXGSF67g+w1AKeV84CpgZs/mmcAPgUuAx/ZtP3HsPRxbbqV9P8ea4ie022e241boc5Nq2GqrrQZdgoaMmVIN5kpdM1OqwVypBnOlrpmp0WOTXEMnyUbAfu3Txe227YGfAd8DHg68GHgC8JlJDnUH8GbgIcArgScDH2v3/RZ4K3Azzez1zYFPjFPLGjTN4k2AvYCnAtsB3+obuj2wD/BP7WMv4N/bY2wOHA18FdiVptH8fSA9r9+7Pcbeba37t4/JHELzfuwOHAUck2TXKV4zkRPbc/fWcxJw8tj2JOsCj2nH9vstzV8CALyA5v387Up+bixZdDtLFt71WLrkjpW8LKlxwQUXDLoEDRkzpRrMlbpmplSDuVIN5kpdM1OjZ/rUQ6R7jb8mARibZfyjUsp57e/vBo4qpRzaPr8gyZuBk5O8oZRya//BesYCzEvyH8AXgDeWUhYnuakZVq6epKZZwMOAB5dSLgdI8grg7CR7lFL+2I5bA9h/bImRJN9oX/temobxdOD7pZRL2/Fn9Z3nBuBfSylLgfOSHNe+/vBJavtOKeXL7e/vS/JU4E3AGyd5zUROBA5t1yVfF/gHmgb5msDr2zGPo1kG525N8vb9vKZ9On/sPU2ywp8bwPEHnMzChXetLrPri7fnIS/ZYSUuS5IkSZIkScPOJrmGyROBhTTLe7yHu5qz0MyWfniSl/VsC01z+sHAuf0HS/IUmub6LsCGNP9e1kmy3gqs770rcPlYgxyglHJOe8PPXYGxJvm8vjW4r6JZnxtgDjAbOCvJz4H/A75bSrmhZ/zZbYO89/VT3bj01HGez5jyisZ3Es2XE3sAGwNzSynXJjkZ+Fq7LvlM4OJSymUrcNwV/twAnvmVvVhSFt/5fI01/aMZrZrNNtts6kHSCjBTqsFcqWtmSjWYK9VgrtQ1MzV6bJJrmFxSSrkROD/JZjRLmjyp3bc+8EXgsHFed7embZJtgZ8An6eZzT2fZpmPrwBr0TTju7Sk73mhXQ6plLK0neX9eOBpNLO9P5zkMaWUS6Z6/epQSrkwyV9pllbZmGYWOaWUK5NcTlP73sAJK3joFfrcxqy57nSa1XKkbqyxhl+0qFtmSjWYK3XNTKkGc6UazJW6ZqZGj5+4htVngYcmeV77/DRgt1LKheM8Fo/z+kfS/Ps4sJTyu1LKXGCLvjGLgWlT1HEusFWSO+/4kGQ34L7AOct7MaVxSinlIJqlTBYDz5viZVN57DjPx52ZvZxOpJktPpNmZvmYXwH/CDya8dcjn8yKfm5SFVdfPdmqStKKM1OqwVypa2ZKNZgr1WCu1DUzNXpskmsotcuhHA58IM1C5R8FHp/kM0lmJNkxyXOTTHQDyAtp1tN+U5LtkrycZZdvAZgHrJ9kVpL7J1lvnOP8kmb98KOSPCLJo4GvAyeXUv60PNeS5DFJ3pPkUUm2Bp4PbMqqNbQBXpTk1Ul2SvIBmib2pDfEnMKJNLPtZ9DOJG+dDLyOZgb+ijbJV/RzkyRJkiRJklaITXINs8/QrPv9olLKmcBewE7Ar4HTgQ8CV473wlLKHODtwLuAvwAvo1mfvHfMb2lu5Pkt4Frg38Y5TgGeS3NjzV/RNM0vBl68AtdxM82yMccDc4EP0cxw/+kKHGM8BwH7AWcCrwBeUkpZ7tnt4ziR5qadF5ZS/taz/WRgA+D8UspVK3LAFf3cpFq23377QZegIWOmVIO5UtfMlGowV6rBXKlrZmr0pOnhSRolSQrwvFLKsYOupUuzZ8/eELjpKws+zRJcjWUiX3rS0YMu4V7n0ksvZZttthl0GRoiZko1mCt1zUypBnOlGsyVumamhsfSpUuZM2cOwEazZs26eaJxziSXJGkKt9xyy6BL0JAxU6rBXKlrZko1mCvVYK7UNTM1emySS1pGu/75ggkeq7rEi3SvtPbaaw+6BA0ZM6UazJW6ZqZUg7lSDeZKXTNTo2f6oAuQtPqVUjLJ7i8A355g36IK5Uj3eNtuu+2gS9CQMVOqwVypa2ZKNZgr1WCu1DUzNXqcSS5pGaWU+aWUCyd4XDHo+qRBOP/88wddgoaMmVIN5kpdM1OqwVypBnOlrpmp0WOTXJIkSZIkSZI0smySS5I0hfvf//6DLkFDxkypBnOlrpkp1WCuVIO5UtfM1OhxTXJJQ+ewPb/KtGnTBl2Ghshaa6016BI0ZMyUajBX6pqZUg3mSjWYK3XNTI0eZ5JLkjSFK6+8ctAlaMiYKdVgrtQ1M6UazJVqMFfqmpkaPTbJJUmSJEmSJEkjyya5JElTePCDHzzoEjRkzJRqMFfqmplSDeZKNZgrdc1MjR6b5JIkTeHaa68ddAkaMmZKNZgrdc1MqQZzpRrMlbpmpkaPTXJJkqawYMGCQZegIWOmVIO5UtfMlGowV6rBXKlrZmr0TB90AZLUtQNOeT+LuX3QZQzM/z7po4MuYeisueaagy5BQ8ZMqQZzpa6ZKdVgrlSDuVLXzNTocSa5JElT2GGHHQZdgoaMmVIN5kpdM1OqwVypBnOlrpmp0WOTXJKkKZx77rmDLkFDxkypBnOlrpkp1WCuVIO5UtfM1OixSS5JkiRJkiRJGlk2ySVJmsImm2wy6BI0ZMyUajBX6pqZUg3mSjWYK3XNTI0em+SSJE1h3XXXHXQJGjJmSjWYK3XNTKkGc6UazJW6ZqZGj01ySZKmcMUVVwy6BA0ZM6UazJW6ZqZUg7lSDeZKXTNTo8cmuSRJkiRJkiRpZNkk10Al2TZJSTKjw2MenOSMro53TzLe+5VkzyRnJVmS5NjBVbd8kuyf5MZB1yGtiG233XbQJWjImCnVYK7UNTOlGsyVajBX6pqZGj02ybWMJOu3zdb9+rYf0zZnt+3bPi/JIau1yHuxJP+SZE6SBUluTHJ6knev4mH/GzgDeDCw/6rWuBp8C9hp0EVIK2L+/PmDLkFDxkypBnOlrpkp1WCuVIO5UtfM1OixSa5llFIWAH8CZvbtmglc3rs9yYOBbYATVuZcSdZamdfdWyV5NXAocBgwA9gT+Biw/ioeenvghFLKX0spN67isaorpSwqpVwz6DqkFXHzzTcPugQNGTOlGsyVumamVIO5Ug3mSl0zU6PHJrnGcyLLNsN3BdYBPs+yzfOZwG3Aqe24FyQ5O8lt7QzzA3sP2m57X5KvJ7kZ+FL/iZNMS/LVJOcl2XqiApM8KMnRSeYnuSXJn5I8ZoKxeyT5RZLrktyU5OQkj+jZn3aJlsva2q9McljP/jcmuSDJrUn+luS7k7x3k3kO8O1SyldKKReWUs4upRxdSnlvX72vSXJue77zkrxxguvaNkkB7gd8tZ3pv/8EY7dK8u129vr8JD/s/auAJEckOTbJe9prvDHJ+5NMT/Lx9jV/TfKq/vMn2S/Jb9t6/5Jkr8nehP7lVsaWx0ny8jYjN7V/ubBBz5g1kvxbkgvbz+iyJO8d9wRSBdOmTRt0CRoyZko1mCt1zUypBnOlGsyVumamRo9Nco3nRGDnJJu3z/cGfkMzY3xmz7i9gVNLKbcmeSTwbeAY4GHAwcAh4zRt3wHMAf4BWGaZliRrA9+hmWX9xFLKZeMVl2R94GRgS5rG8+40M7InyvMGwJHAE4DHAhcAx/c0YV8AvA14HbAjsA9wVnuuR9HM/H4/sDPwDOBXE5xnKlcDj02yzUQDkrwM+CDwXmBX4D007+Mrxxl+ObA5cDPw1vb3b41zzDWBnwN/B55IM4N9AfCzvtn8Twa2AJ4EvB34APAT4AbgMcAXgC8meVDfKT4OfJLmMz0V+HGS+010jRPYnuZ9/6f2sRfw7z37/6t9fgiwG/BS4G8THez2RUu4feHiOx93LFm6guVIy9p5550HXYKGjJlSDeZKXTNTqsFcqQZzpa6ZqdFjk1zjOQVYzF0N8Zk0Tek/A/dvl1mBppF5Yvv724HZpZRDSilzSylHAJ8B3tl37BNKKZ8spVxUSrmoZ/v6wHHApsDepZRrJ6nvpe24fUopv2lnZX+7lHLqeINLKSeUUr5ZSjmvlHIu8FpgvbZ+gK1pGti/LKVcVkr5Qynl8J59twA/KaVcWko5vZRy2N1Osnw+ANwIzEtyfjt7e98ka/SNObCU8v1SyiWllO8Dn6Jp4Pdf19JSytVAAW4qpVxdSlk0znlfTPNv/TWllLPa9+BV7bXN7Bk3H3hzKeX8UspXgfOB9Uop/1lKuYCmUb2Y5suGXp8ppXyvPe4bgJuAA1bonWnq27+U8pdSyq+BbwCzANovM94C/Fsp5cg2O78ppXx5ooOddMD/8suXHnnn46LvnrGC5UjLOvfccwddgoaMmVIN5kpdM1OqwVypBnOlrpmp0TN90AXonqeUsjDJH2kaqEfTNJM/Xkq5PclvgZlJQtNkHWuS7wr8sO9QpwBvTTKtlDI2lfdPE5z2aOCvwJN7G71JvgD8c09t69PMND+9lLJcd1FI8gDgQ+31bAZMo2mSjy3n8h2amdgXJ/kZcDzw41LK7cAvgEt79v0M+EEpZeHynLtXKeUq4HFJHkozW/vxNDPcX5PkGcC6NDOqv5Lk8J6XTqdpPC/PtY73fu0O7AD8vfnY7rROe74xZ5dS7uh5/jfgLz3HWprkepr3sNepPWNuT/InmjyQ5GyadesBfl1K+ccJSp9XSvl7z/Ores6zK7A2MHuC197NzK+8lMVlyZ3P11jTP5PSqimlDLoEDRkzpRrMlbpmplSDuVIN5kpdM1Ojxya5JnIi8OIkD6Fp3p7Wbj+ZZpmVNYCFwO9X8Li3TLD9eJrm7uNY9kag7wc+0Td2vNnSkzmSZt3ut9A0vMfWUV8LoJRyeZKdgacATwU+B7wzyV6llL+365fPBJ5GsxTKwUn2WNmbZJZS/kLTfP5c29T+Nc0XEee0Q/6Fu7+vy7teyHjv1/o0fwXwsnHG987YX9K3r0ywbUX+AuWZwJrt75N9bpOdZ0U/b6avuyZ3kKkHSsvpvve976BL0JAxU6rBXKlrZko1mCvVYK7UNTM1emySayInAv9Bs7TJb3pmgv+KZrmSAKeUUha328+lWeu6157A3J7XTubzNI3jHyV5VinlZIBSyjXANX1jz6SZfb3Jcs4m3xN4YynleGhuYgncv3dAO3v9xzTraX8WOI9mbfXT2hnlvwR+mWRsyZQnA99fjnNPZawxfp9Syt+SXAlsV0o5amUONsH7dRrNkivXlFJq3J75sbTrtCeZDjySZqkdSimXdnD8C2ga5bOACZdYkWraYIMNph4krQAzpRrMlbpmplSDuVIN5kpdM1OjxzXJNZHf0sy4fhPN7PExf6BZBuO53LXUCjQ3bpyV5H1JdmpvNPmv3H1W84RKKf9D05j/SZL+da97HU2zhvixSfZMsl2SFyR53ATjLwBenmTXJI8BjqJndnKS/ZMckOShSbajmdG+CLg0yT8leXOSGe0NN19B8+/m/OW9rp7zfL59f/ZMsk2SxwJfp5nNPbZkyUHAu9tz7pTkYUleleTtK3q+HkcB1wE/TPLEJA9OMjPJYePchHNl/L8kz0uyC/BZYGPgqx0cF4BSyq3AR4GPJXlFku2TPDbJiq57Lq20yy+/fNAlaMiYKdVgrtQ1M6UazJVqMFfqmpkaPTbJNa62Mfk7YAPgpJ7tt/VsP7Fn+2nAvsB+NDPCPwi8v72B54qc91CaRvHxSR4/wZjFNEufXEOzTMtZwL8z8ZIkB9A0bk+juSHkYSw72/pGmiVOTqGZpf4U4NmllOvbfc+nWQLmXOD1wEtKKWevyHW1fkkz6/o7wFzge8CtwKz2XLQ3o3wNzY01z6L5gmJ/4JKVOB/tMRfSrIF+Gc3s93OBr9CsSd7FzPJ/bx9zaG7q+ZxSynUdHLfXITRfxHyQpv5vcfe10SVJkiRJkqQVFheil7QykmxL07z/h1LKGYOtpjF79uwNgZsOW/A9FnP7oMsZmP990kcHXcLQWbBgAeuvv/6gy9AQMVOqwVypa2ZKNZgr1WCu1DUzNTyWLl3KnDlzADaaNWvWhJNFnUkuSdIUbr65xnL+GmVmSjWYK3XNTKkGc6UazJW6ZqZGj01yaSUk2TrJgkkeWw+6RkndufHGGwddgoaMmVIN5kpdM1OqwVypBnOlrpmp0TN90AVI91JXAjOm2D/USinzgAy6Dml1SIy6umWmVIO5UtfMlGowV6rBXKlrZmr02CSXVkIp5XbgwkHXIWn12HXXXQddgoaMmVIN5kpdM1OqwVypBnOlrpmp0eNyK5IkTeH8888fdAkaMmZKNZgrdc1MqQZzpRrMlbpmpkaPTXJJkqawdOnSQZegIWOmVIO5UtfMlGowV6rBXKlrZmr0uNyKpKHzlT0/yLRp0wZdhobIhhtuOOgSNGTMlGowV+qamVIN5ko1mCt1zUyNHmeSS5I0hY033njQJWjImCnVYK7UNTOlGsyVajBX6pqZGj02ySVJmsKll1466BI0ZMyUajBX6pqZUg3mSjWYK3XNTI0em+SSJEmSJEmSpJFlk1ySpCk86EEPGnQJGjJmSjWYK3XNTKkGc6UazJW6ZqZGj01ySZKmsHDhwkGXoCFjplSDuVLXzJRqMFeqwVypa2Zq9EwfdAGS1LXX/OZQFrN00GV07qi9/m3QJYys+fPn88AHPnDQZWiImCnVYK7UNTOlGsyVajBX6pqZGj3OJJckSZIkSZIkjSyb5JIkTWG33XYbdAkaMmZKNZgrdc1MqQZzpRrMlbpmpkaPTXJJkqYwd+7cQZegIWOmVIO5UtfMlGowV6rBXKlrZmr02CSXJGkKt99++6BL0JAxU6rBXKlrZko1mCvVYK7UNTM1emySS5I0hQ022GDQJWjImCnVYK7UNTOlGsyVajBX6pqZGj02ySVJmsL973//QZegIWOmVIO5UtfMlGowV6rBXKlrZmr02CSXJGkKl1xyyaBL0JAxU6rBXKlrZko1mCvVYK7UNTM1emySS32SbJukJJnR4TEPTnJGV8cbtGG7HkmSJEmSJI0um+S6x0uyfpIlSfbr235M28zetm/7vCSHrNYi76WSzGzfw7HH35J8L8l2U7z0E8Csjms5KcmhXR5T6soWW2wx6BI0ZMyUajBX6pqZUg3mSjWYK3XNTI0em+S6xyulLAD+BMzs2zUTuLx3e5IHA9sAJ6zMuZKstTKvGwI7A1sALwIeAvw4ybT+QWlML6UsKKVcv7qLlAbltttuG3QJGjJmSjWYK3XNTKkGc6UazJW6ZqZGj01y3VucyLLN8F2BdYDPs2zzfCZwG3BqO+4FSc5Ocls7w/zA3oO2296X5OtJbga+1H/iJNOSfDXJeUm2nqjAJA9KcnSS+UluSfKnJI+ZYOweSX6R5LokNyU5OckjevanXdLksrb2K5Mc1rP/jUkuSHJrO/v7u5O8d8vjmlLKVaWUXwEfBHYDduiZaf6PSf5M894+oXe5lSRPa+u4b981fjrJCe3v92vfmyuSLExyVpKX9Iw9AtgLeEvPrPZt230PTfLTJAvaa/1GEu+godXq+uv9TkjdMlOqwVypa2ZKNZgr1WCu1DUzNXpskuve4kRg5ySbt8/3Bn5DM2N8Zs+4vYFTSym3Jnkk8G3gGOBhwMHAIUn27zv2O4A5wD8AyyzTkmRt4DvADOCJpZTLxisuyfrAycCWwHOA3YGPMfG/sQ2AI4EnAI8FLgCOT7JBu/8FwNuA1wE7AvsAZ7XnehRwGPB+mhngzwB+NcF5Vsai9mfvrPqPAP8O7Aqc2Td+NnBjWzNtjdOAFwNHtZvWAf4MPAt4KM2XEd9I8uh2/1tovtg4HNi8fVzeNt5PAE4HHkVzrQ+g+VwntGTRYpYsvO3Ox9Ilty/PdUuSJEmSJGkETR90AdJyOgVYTNMQP7r9eTJN4/X+SR5cSrmEZjbyV9rXvB2YXUoZa3zPTbIb8E7giJ5jn1BK+eTYk541ztcHjgPWBvYupdw0SX0vBTYF9iilzG+3XTjR4FLKMsvBJHktTaN5L+AnwNbA1cAvSylLgMuAP7TDtwZuAX5SSvk7cClNE3mVtV9CvAO4AjgfeHy76/2llF/0jOu9lqVJjqF5D8be+1nAfYHvtWOuoFnHfMz/JHk6sC/wh1LKTUkWAwtLKVf3nOdfgdNLKe/p2fZqmgb6TqWUueNdx0mv+SwLFy688/kOL96THfd74oq8FdIydtlll0GXoCFjplSDuVLXzJRqMFeqwVypa2Zq9DiTXPcKpZSFwB+5a9b4XsBJpZTbgd8CM9ubTW5NM+scmlnPp/Qd6hRgx771tv80wWmPBu4DPK23QZ7kC+3SHwuSLGg3z6Bp5s4f5zh3k+QBSQ5vl0y5CbiZpik/tpzLd4B1gYvbcc9LMval1i9oGuMXt0uPvCzJestz3kn8NcktwJXtNb+glLK4Z/9E79GYo2g+g7E7W7wMOK6UciPcuWTN+9plVua379vTe653IrsDe/e93+e1+7af6EUzv/z/eMpRb7vzsd0LHjfFaaTJXXzxxYMuQUPGTKkGc6WumSnVYK5Ug7lS18zU6LFJrnuTE2kapg+haSCf1m4/mWaZlb2BhcDvV/C4t0yw/Xjg4UB/h/X9NE3xsQfctUTJ8jqyfe1baGZrzwCup13ipJRyOc1SKm9sj/054FdJ1mxnjz8CeAlwFc0a4nP61wRfQU+kudYNSykzSin97+FE7xFtvX8ELgL2S7Iu8DzuWmoFmtn7bwE+SvM5zQB+zrJLuoxnfeDHLPt+z6BZgmbCJWbWXHct1lxv7Tsf09b0j2a0ahYvXjz1IGkFmCnVYK7UNTOlGsyVajBX6pqZGj12jnRvciLwHzTLevymlLK03f4r4LVAgFN6ZkCfC+zZd4w9gbk9r53M54G/AD9K8qxSyskApZRrgGv6xp4JvCbJJss5m3xP4I2llOMBkmwFLHMzylLKIpoG8Y+TfJZmBvXDgNPaGfS/BH6Z5AM0S7U8Gfj+cpx7PJeMzfpeBUfRzCD/K3AHzVI1Y/YEflhK+SZAkjWAnYBzesYsBnpn+EPzRcgLgHntNUsDcZ/73GfQJWjImCnVYK7UNTOlGsyVajBX6pqZGj3OJNe9yW+B24A30cweH/MHYDPgudy11ArAJ4FZ7TIfOyV5JfCvLLs29qRKKf9D05j/SZInTDL0aJo1xI9NsmeS7ZK8IMlE63xcALw8ya5JHkPTYL5zNnqS/ZMckOSh7TIy/9zuvzTJPyV5c5IZSbYBXkHzb/n85b2uSo6imeH+XuC7pZTbevZdADw1yeOT7Ap8keYGnL3mAY9Jsm2S+7eN9M8CmwBHJ9kjyfZJnp7ka31L5khVPeAB/XGVVo2ZUg3mSl0zU6rBXKkGc6WumanRY5Nc9xqllFuB3wEbACf1bL+tZ/uJPdtPo7kx5H40M8I/SHMDyiNW8LyHAgcBxyd5/ARjFgNPo5lhfjxwFvDvwEQz1g8ANqaZKf0N4DCWnZ1+I/AvNGuonwk8BXh2KeX6dt/zgRNoZsu/HnhJKeXsFbmurpVSLqT5wuLhLLvUCsCHaK715zSf3dXAsX1jPkHzfp0DXAtsXUq5kmYW+jTg/2je10Np3oM7Or8IaQKuR6eumSnVYK7UNTOlGsyVajBX6pqZGj0ut6J7lVLKzAm27z3B9u8B35vkeNuOs20ezdItvdv+G/jvKWq7FHjhBPsOBg7ueX46sEffsO/27D+WuzeRx/b9hrtuYLpKSikn0Xety7O//3p6tj9mguPMB/aZopa53H39d0opF9B8KSBJkiRJkiR1zpnkkiRNYfPNNx90CRoyZko1mCt1zUypBnOlGsyVumamRo8zyaUhkWRrlr0RZr/dSimXra56pGFy++3eN1bdMlOqwVypa2ZKNZgr1WCu1DUzNXqcSS4NjyuBGZM8rhxATdJQuPbaawddgoaMmVIN5kpdM1OqwVypBnOlrpmp0eNMcmlIlFJuBy4cdB2SJEmSJEnSvYkzySVJmsJOO+006BI0ZMyUajBX6pqZUg3mSjWYK3XNTI0em+SSJE3hsstczl/dMlOqwVypa2ZKNZgr1WCu1DUzNXpcbkXS0PnyE97KtGnTBl2Ghsitt9466BI0ZMyUajBX6pqZUg3mSjWYK3XNTI0eZ5JLkjSFddddd9AlaMiYKdVgrtQ1M6UazJVqMFfqmpkaPTbJJUmawpZbbjnoEjRkzJRqMFfqmplSDeZKNZgrdc1MjR6b5JIkTeHCCy8cdAkaMmZKNZgrdc1MqQZzpRrMlbpmpkaPTXJJkiRJkiRJ0siySS5J0hQe8IAHDLoEDRkzpRrMlbpmplSDuVIN5kpdM1OjZ/qgC5Ckrr3m119hMUsHXcYyjpr5hkGXIEmSJEmSpHE4k1ySpCn87W9/G3QJGjJmSjWYK3XNTKkGc6UazJW6ZqZGj01ySZIkSZIkSdLIskkuSdIUdthhh0GXoCFjplSDuVLXzJRqMFeqwVypa2Zq9NgklyRpCldcccWgS9CQMVOqwVypa2ZKNZgr1WCu1DUzNXpskkuSNIVFixYNugQNGTOlGsyVumamVIO5Ug3mSl0zU6PHJrkkSVNYZ511Bl2ChoyZUg3mSl0zU6rBXKkGc6WumanRY5NckqQpbL311oMuQUPGTKkGc6WumSnVYK5Ug7lS18zU6LFJrpGQ5OAkZwy6jpWR5KQkhw7gvPOSvLWD43Raf5Ijkhzb1fGk5TF37txBl6AhY6ZUg7lS18yUajBXqsFcqWtmavTYJBdJpiV5W5Kzktya5IYkP02y56BrWxlJSpJ9+jZ/Apg1gHLuJsm7kyxN8s5B17KaPB9436CLkCRJkiRJksZjk3zEJQlwDPB+4NPArsBM4HLgpHGazfdKpZQFpZTrB11H69XAx9qfQyvJWgCllPmllL8Puh5pVWy66aaDLkFDxkypBnOlrpkp1WCuVIO5UtfM1OixSa59gRcCryilfLmUckkpZU4p5bXAj4AvJ7nP2OAkz07yx3bG+XVJftCzb+0kH01yeZLbklyY5IB23/5Jbuw9cZJ9kpSe5wcnOSPJ69pjLEzy7SQb9YzZI8kv2nPflOTkJI/o2T+v/fUH7Yzyeb3H7hm3RpL3J/lrW+sZSZ7Rs3/b9vXPT3JiW8ucJI9blTc7yV7AujRfSmyY5PF9+++T5OtJFiS5KsmB4xxjXpL/6Bl3aZLnJNk0yQ/bbWcmedRy1DPh5znO2Psm+XKSa5PcnOSEJLv37B/7/F6T5BLg1nb7MsutTJGTaUm+kuSSJIuSnJ/kLVO+sVJl06dPH3QJGjJmSjWYK3XNTKkGc6UazJW6ZqZGj01yvRSYW0r58Tj7PgncD3gqQJJnAT8Ajgf+gWb5kj/0jP868BLgzTQz0l8HLFjBenagadw/G3hGe57P9ezfADgSeALwWOAC4PgkG7T792h/vgrYvOd5v7cABwLvAB4O/Bz4UZId+8Z9mGaplhnAXODoJKvyX8oDgKNLKUuAo9vnvT4O7AU8F3gazaz+R3B3bwNOoXl/jgO+QfP+f7MdfxHw9fYvBca1HJ9nv+8AmwH/CDwSOA2YnWSTnjE7AC+gWWJlxgTHmSwnawB/BV4E7AZ8EPjPJPtOUtfdLFl0K0sW3vVYuuT2FXm5dDdXXXXVoEvQkDFTqsFcqWtmSjWYK9VgrtQ1MzV6/FpEOwHnTrDv3J4xAO8FjimlHNQzZg5Akp1omttPLaX8st138UrUsw7NrPYr2uO+CTguyYGllKtLKSf0Dk7yWuBGmsbyT0op17Z94RtLKVdPcp53AB8tpRzTPn9Xkr2BtwL/r2fcJ0opx7XnOgg4m6YRfN6KXliSDWlm7Y/NRv8m8OskbymlLEiyPk3T/J9LKbPb17ySpmnc7/hSyhfbMR8E3gD8sZTynXbbR4FTgQcAE70PE36e49T+BODRwGallNvaze9ol+N5IfCldttaNJ/ftRMcZ9KctF8e9NZzSTt7f1/g2xNcx92c9C8fY+HChXc+32HfJ7PjfveIJeklSZIkSZJ0D2OTXAATzjbuMwM4fJJ9S4GTV7GWy8Ya5K1TaWYX7wxcneQBwIdoZlhvBkwD1gO2Xt4TtM3qLWhmYvc6Bdi9b9uZPb+PfY24GSvRJKeZPX1RKWUOQCnljCSXAi8GvgJsT9Nk/v3YC0op85OcP86xeuv6W/vzrHG2bUbzvvXO6P9mKeX1TP559tsdWB+4vm9y+rpt3WMunahB3prBFDlJ8v9o1mvfuj3+WsAZy1knADMP/zcWl6V3Pl9jTf9Tp1Wz3XbbDboEDRkzpRrMlbpmplSDuVIN5kpdM1Ojx+VWNJdmyYvx7NozBmDRJMeZbB/AHdy9Gb/mFK8Zz5E0jda3AI9vf7+eppFaw5Ke38fWT1/ZfzcHAA9JcvvYg2ZJkZW5geeddZVSSv827l7rjJ7H+9ttU31mvdan+ZJgRt9jZ5olYsbcMsVxJj1nkv1olrf5Cs1yMzOAr7GCn++a667Dmuvd9Zhmk1yr6G9/+9vUg6QVYKZUg7lS18yUajBXqsFcqWtmavTYJNcxwI5Jnj3OvgNpGtC/aJ+fSbNu9XjOosnTXhPsvxbYID03AWX8Nau3TrJFz/PH0jTYx2ZT7wkcVko5vpRyNnAbcP++YyyhmWE+rlLKzcCV7bF67QmcM9HrVkWShwGPopkBP6PnMRN4XJJdaNYRXwI8pud1G3PXcjcrrZRyYc/jmnbzZJ9nv9OABwK39x3rwlLKdStQylQ52RP4bSnlc6WU00spF7LsTHVpIG65Zarvf6QVY6ZUg7lS18yUajBXqsFcqWtmavQ4vVLH0Nwk8cgk7wRmAxvSrMv9HOBFpZSx/zJ8gOZGjRe1r5sOPLOU8tFSyrwkRwJfTfJmmrWtt6FZw/rbNEuILKS5CeNhNI3g/cep59a2lne0dRwGfLtnffELgJcn+VO7/+PcfXbyPGBWklOA20opN4xzno8DH2iv5QyaG33OAF429Vu2Ug4A/lBK+VX/jiR/BA4opbwzyVeAjye5HriG5sahd1SqacLPc5yxv6RZ+ubYJP9G89cFWwDPAn5QSvnT8pxwOXJyAfCKJE8HLgFeTnPz1UtW4TqlVbbWWrX+WEWjykypBnOlrpkp1WCuVIO5UtfM1OhxJvmIa5fq2Bf4T+BtNDO2f03TuJxZSjm2Z+xJNA3159A0lk+guZnjmDcA3wU+R7Nm9+HAfdrXzgf+GXgmzWzilwAHj1PShcD3geOB/6OZ7fzGnv0HABvTzGz+Bk0T/Zq+YxwIPBW4HDh9gks/DPhv4JNtPc8AnlNKuWCC8SstyVo01/69CYZ8j6YxvCbwTpr3/8c0jenfAH/uuiZYrs+zd2yh+ex+RbP8yVyaxvo23LX++fKaMCfAF2k+/2/RfLFyv3acNFCuR6eumSnVYK7UNTOlGsyVajBX6pqZGj25azljabCSHAzsU0qZMeBSdC81e/bsDYGb/ufmP7GYpVOOX52OmvmGQZegVXDOOeew2267DboMDREzpRrMlbpmplSDuVIN5kpdM1PDY+nSpcyZMwdgo1mzZt080ThnkkuSJEmSJEmSRpZNcmklJPlpkgUTPN4z6Pokdet+97vfoEvQkDFTqsFcqWtmSjWYK9VgrtQ1MzV6vHGn7jFKKQcz/jrl90SvAdadYN/81VmIpPrWXnvtQZegIWOmVIO5UtfMlGowV6rBXKlrZmr0OJNcWgmllCtKKRdO8LBJLg2ZK6+8ctAlaMiYKdVgrtQ1M6UazJVqMFfqmpkaPTbJJUmSJEmSJEkjyya5JElTePCDHzzoEjRkzJRqMFfqmplSDeZKNZgrdc1MjR7XJJc0dL78xAOYNm3aoMvQELnuuuvYaqutBl2GhoiZUg3mSl0zU6rBXKkGc6WumanR40xySZKm8Pe//33QJWjImCnVYK7UNTOlGsyVajBX6pqZGj02ySVJmsL06f7hlbplplSDuVLXzJRqMFeqwVypa2Zq9KSUMugaJKkTs2fP3hC4affdd3e5FUmSJEmSpBG3dOlS5syZA7DRrFmzbp5onDPJJUmawjnnnDPoEjRkzJRqMFfqmplSDeZKNZgrdc1MjR6b5JIkSZIkSZKkkeUCO5KGzr/86igWc8egy+Cbe+8/6BLUkU022WTQJWjImCnVYK7UNTOlGsyVajBX6pqZGj3OJJckaQrrrbfeoEvQkDFTqsFcqWtmSjWYK9VgrtQ1MzV6bJJLkjSFv/71r4MuQUPGTKkGc6WumSnVYK5Ug7lS18zU6LFJLkmSJEmSJEkaWTbJJUmawjbbbDPoEjRkzJRqMFfqmplSDeZKNZgrdc1MjR6b5JIkTeGGG24YdAkaMmZKNZgrdc1MqQZzpRrMlbpmpkaPTXJJkqZw8803D7oEDRkzpRrMlbpmplSDuVIN5kpdM1Ojxya5JElTmDZt2qBL0JAxU6rBXKlrZko1mCvVYK7UNTM1emySqzNJDk5yxqDrGKQkM5OUJPdtn++f5MbBVnV3SY5Icuyg65DuLXbeeedBl6AhY6ZUg7lS18yUajBXqsFcqWtmavTYJF9NkkxL8rYkZyW5NckNSX6aZM9B17Yy2kbwPn2bPwHMGkA5d0oyL8lbx9k+8g18SSvv3HPPHXQJGjJmSjWYK3XNTKkGc6UazJW6ZqZGj03y1SBJgGOA9wOfBnYFZgKXAyeN02y+VyqlLCilXD/oOoZNkjUHXcOgtF8u+d8pDVwpZdAlaMiYKdVgrtQ1M6UazJVqMFfqmpkaPTafVo99gRcCryilfLmUckkpZU4p5bXAj4AvJ7nP2OAkz07yx3bG+XVJftCzb+0kH01yeZLbklyY5IB2392W9kiyT5LS8/zgJGckeV17jIVJvp1ko54xeyT5RXvum5KcnOQRPfvntb/+oJ1RPq/32D3j1kjy/iR/bWs9I8kzevZv277++UlObGuZk+Rxq/RuL4eprrEdU5K8JskP2touSPKcvjHPTDI3yaIkJwLbLse5n5vktPbzvTjJQUmm9533DUl+lOQW4L1JNk5yVJJr23NdkORVU5znIUl+kuTmJH9P8usk208wdo0k705ySXv8OUle2LN/WpKv9Ow/P8lb+o5xRJJjk7wjyVVJrk/y2d4mf5vfTyS5IsktSX6fZGbP/v2T3JjkOUnOAW4Dtk6zjM0f2tfcmOSUJNtM9V5LXbnvfe876BI0ZMyUajBX6pqZUg3mSjWYK3XNTI0em+Srx0uBuaWUH4+z75PA/YCnAiR5FvAD4HjgH2iWL/lDz/ivAy8B3kwzI/11wIIVrGcHmsb9s4FntOf5XM/+DYAjgScAjwUuAI5PskG7f4/256uAzXue93sLcCDwDuDhwM+BHyXZsW/ch2mWapkBzAWO7m0aVzLVNY45CPg2Tf3HA0cl2QQgyVbA94Eft7V/GfjIZCdN8kSaz/DTwG40n9/+wHv7hh5Mk4OHAV8FDmnH/yPN5/4G4LpJzrMl8CuaJvOTgUe2x5nofX038Arg9cBDgE8B30yyV7t/DeCvwIvaOj4I/GeSffuOszewffvzle217d+z/zPA44D9aN7T7wA/68vEesC7gNe0tcwHjgVObl/zOOBLwIRf6y5ZdCtLFt71WLrk9omGSstlww03HHQJGjJmSjWYK3XNTKkGc6UazJW6ZqZGT+1GpBo7ARMtZnRuzxhomqXHlFIO6hkzByDJTjTN7aeWUn7Z7rt4JepZh2ZW+xXtcd8EHJfkwFLK1aWUE3oHJ3ktcCOwF/CTUsq1SQBuLKVcPcl53gF8tJRyTPv8XUn2Bt4K/L+ecZ8opRzXnusg4GyaRv55K3FtAB9N8qG+bWsB54w9meoae3YdUUo5uh3zHpovJx4N/IymUX1RKeXAduz5SR5G0+CdyEHAR0opR7bPL07yPuBjwAd6xv1vKeVrPfVtDZxeSvlTu2neJOeA5v29CdivlLKk3TZ3vIFJ1gbeAzyllHJqT11PoGnin9weozeTl7Qz/vel+RJhzA3Av5ZSlgLnJTmO5ouew9treBWwdSnlynb8J9q/LnhVWwPAmsAbSyljud8E2Igmexe1YyZdHOzE136QhQsX3vl8h32fxk4vfsYkr5Amd9lll7HbbrsNugwNETOlGsyVumamVIO5Ug3mSl0zU6PHJvnqk+UcNwM4fJJ9S2lm1K6Ky8Ya5K1TaWYK7wxcneQBwIdo1k3fDJhGM7t36+U9QZINgS2AU/p2nQLs3rftzJ7fr2p/bsbKN8k/DhzRt+3NwJN66lvea7yztlLKLUlubsdDM6P7933jT2VyuwN7JumdOT4NWCfJeqWUsc7un/pe93nge+2SMP8HHFtK+W17LT8FntiOu7SU8hCarPy6p0E+mR1orv0X7ZcfY9YCTh97kuT/Aa+meY/Wbfef0Xess9sG+ZiraGbD0/6cBsztO8/aQO9a9otZ9n2fn+QI4OdJfgH8Evh2KeUqJrD3l97P4nLHnc/XWNP/1EmSJEmSJGl8do5Wj7k0DdXx7NozBmDRJMeZbB/AHdy9Gb8yN308kmYJmLcAl9Is2XEqTVO0ht5G7tgSGquyFNB1pZQLezckmd83Znmvsb/JXFaxtvVpZmR/f5x9t/b8fssyJy3lp+0a3M+kWZpndpLPllLeQbMsybp99U6Vlf6aAJ4FXNG37zaAJPvRLIlzIM379HfgncBj+sZP9n6tT/MlzyPbn716lwxaVPrukFFKeVWSw2iWB3ox8KEkTy2l/G68C1pz3XUo3DHeLmmlbLXVVoMuQUPGTKkGc6WumSnVYK5Ug7lS18zU6HFN8tXjGGDHJM8eZ9+BNLNof9E+P5NmeYrxnEXzme01wf5rgQ3ScxNQmhnF/bZOskXP88fSNNjPb5/vCRxWSjm+lHI2TaP0/n3HWEIzK3hcpZSbgSvbY/Xak55lTwZoea5xKufSLL3S67FTvOY0YOdSyoXjPCbt6pZSri2lHFlK+WeaJWte226/oucYl7bDzwSe2HvTzEnceYPMcWq6vB2zJ/DbUsrnSimnt19CjHsT0EmcTpOZzcY5z2TL9tBe5+mllP8qpTwe+AvNWv/SavH3v/990CVoyJgp1WCu1DUzpRrMlWowV+qamRo9NslXj2NobsJ4ZJIDkmyb5OFJvgg8B3hNKWVs5vAHgJck+UCSXZM8LMm7AEop82hmQH81yT5JHpxkZs/NE38PLKS5oeL2SV7KsjdNHHNrW8vu7Y0kD6NZvmKsUXkB8PL2/I8BjuLuM5PnAbOSPDDJxhNc98dp1iF/cZKdk3yEpmn/6eV726panmucyhdovvz4eHt9E73fvT4IvCLJQUke0p5/v3HWUF9Gkg8meW6SHZI8BPgnJl+X+zPAhsAxSR6VZMckL0+yc//AUsrfaWaJfyrJK9vsPCLJm5K8sh12AfCoJE9PslOSQ5j4hq3jKqXMpXmfv57k+W1+H53k3e0Naye69gcn+a8kj0uyTZKnATtOcf1Sp2688cZBl6AhY6ZUg7lS18yUajBXqsFcqWtmavTYJF8N2qUj9gX+E3gbzYztXwPbADNLKcf2jD0JeBFN8/wM4ASWna38BuC7wOdo1uw+HLhP+9r5wD/TLMlxFvAS4OBxSrqQZrmP42nWtz4TeGPP/gOAjWlmPX+Dpol+Td8xDqRZ9uNyetat7nMY8N/AJ9t6ngE8p5RywQTjV6flucZJlVIuA14A7ENzc9XXc9fNJyd6zc9pGtxPA/4I/I4mE5dO9jqadbr/i+az+hXNciX7TXKe64En0yxxcjLwZ+BfuPtyKGPeBxwCvJum+fwzmuVXLmn3f5EmM9+i+TLmfjQZXFGvAr5Ok4nzgWNpmu2XTfKahcAuwPdoliX6EvDZtiZptehbR19aZWZKNZgrdc1MqQZzpRrMlbpmpkZP+pb+1ZBLcjCwTyllxoBLkTo3e/bsDYGbPnPTX1h8D1iT/Jt77z/oEiRJkiRJkkbW0qVLmTNnDsBGs2bNunmicc4klyRpCueff/7Ug6QVYKZUg7lS18yUajBXqsFcqWtmavTYJNc9VpKfJlkwwWPSZU0kqUtLly4ddAkaMmZKNZgrdc1MqQZzpRrMlbpmpkbP9EEXoNWrlHIw469Tfk/0GmDdCfbNX52FSBptG2644aBL0JAxU6rBXKlrZko1mCvVYK7UNTM1emyS6x6rlHLFoGuQJIBNNtlk0CVoyJgp1WCu1DUzpRrMlWowV+qamRo9LrciSdIU5s2bN+gSNGTMlGowV+qamVIN5ko1mCt1zUyNHpvkkiRJkiRJkqSR5XIrkobO4U96GdOmTRt0GRoiW2655aBL0JAxU6rBXKlrZko1mCvVYK7UNTM1epxJLknSFBYtWjToEjRkzJRqMFfqmplSDeZKNZgrdc1MjR6b5JIkTWH+/PmDLkFDxkypBnOlrpkp1WCuVIO5UtfM1OixSS5JkiRJkiRJGlkppQy6BknqxOzZszcEbtp9991dk1ydKqWQZNBlaIiYKdVgrtQ1M6UazJVqMFfqmpkaHkuXLmXOnDkAG82aNevmicY5k1ySpClceOGFgy5BQ8ZMqQZzpa6ZKdVgrlSDuVLXzNTomT7oAiSpa//yq++ymDsGdv5v7v2SgZ1bdSxZsmTQJWjImCnVYK7UNTOlGsyVajBX6pqZGj3OJJckaQrrr7/+oEvQkDFTqsFcqWtmSjWYK9VgrtQ1MzV6bJJLkjSFTTfddNAlaMiYKdVgrtQ1M6UazJVqMFfqmpkaPTbJJUmawiWXXDLoEjRkzJRqMFfqmplSDeZKNZgrdc1MjR6b5JIkSZIkSZKkkWWTXJKkKWyxxRaDLkFDxkypBnOlrpkp1WCuVIO5UtfM1OixSS5J0hQWL1486BI0ZMyUajBX6pqZUg3mSjWYK3XNTI0em+SSJE3huuuuG3QJGjJmSjWYK3XNTKkGc6UazJW6ZqZGj01ySZ1JMjNJSXLfjo63bXu8GV0cT5IkSZIkSepnk1xazXoayWOPa5Mcn+Rhg65tMklO6qv7b0m+k2SbQdcm1bbzzjsPugQNGTOlGsyVumamVIO5Ug3mSl0zU6PHJrk0ODsDmwNPB9YGjkuy1mBLmtLhNDVvATwX2Ar45kArklaDefPmDboEDRkzpRrMlbpmplSDuVIN5kpdM1Ojxya5NDjXlFKuLqWcBhxK03DeZWxnkrcnOSvJLUkuT/K5JOv3HiDJnu0M74VJbkjy8yQbt/vWSPLuJJckWZRkTpIXrmLNC9uaryql/A74DPCIiQYnuV+So5Nc0dZ4VpKX9I1ZI8m/JbkwyW1JLkvy3gmONy3JV5Ocl2TrVbwWabnddtttgy5BQ8ZMqQZzpa6ZKdVgrlSDuVLXzNTomT7oAqRRl2QjYL/2ae/tk+8A3gxcAmwHfA74GPDG9nUzgNnAV4G3ALcDewPT2te/G/hn4PXABcCTgG8mubaUcnIHdW8C7Av8fpJh6wB/Bj4K3Aw8C/hGkotKKX9ox/wX8C/A24Df0MxU36X/QEnWBo4GtgWeWEq5dqKTLlm0iCXljjufr7HmdKatueZyX5vU7z73uc+gS9CQMVOqwVypa2ZKNZgr1WCu1DUzNXpskkuD89ckAGP/5f1RKeW8sZ2llEN7xs5L8h/AF2ib5MC/AX8qpbyxZ9zZcGdD+T3AU0opp7b7Lk7yBOB1wMo2yd+Y5DVAgPWAuTTLxYyrlHIF8ImeTf+T5Ok0zfU/JNmApsH/r6WUI9sxF9E0y3utDxxHsyzN3qWUmyYr8sTX/gcLFy688/kO+z6TnV78rOW4PGl8D3zgAwddgoaMmVIN5kpdM1OqwVypBnOlrpmp0WOTXBqcJwILgcfSNLRf37szyVNoZoPvAmxI8+91nSTrlVIWAjOA70xw7B1omti/aBvxY9YCTl+Fmo8CPtz+/oC27v9L8shSyt/7ByeZ1o7ZF9iyPf/aNNcNsGv7fPYU5z0a+Cvw5FLKoqmK3PtLH2Jx30xyaVVcdNFF7LbbboMuQ0PETKkGc6WumSnVYK5Ug7lS18zU6LFzJA3OJaWUG4Hzk2wGfItmSRSSbAv8BPg88F5gPvAE4Cs0jeaFwGTN4rG1y58FXNG3b1UW1rqplHJh+/uFSQ4ArgJeDHx5nPHvpJkp/lbgLOAWmvXXx25QOmXDu3U8zdIxjwNOmGrwmuuuS+GOqYZJkiRJkiRJ3rhTuof4LPDQJM9rnz+S5t/ngaWU35VS5gJb9L3mTGDWBMc7h6YZvnUp5cK+x+Ud1r20/bnuBPv3BH5YSvlmKWUOcDGwU8/+C2ga5RNdx5jPA/8O/CjJXqtQr7RS/FM7dc1MqQZzpa6ZKdVgrlSDuVLXzNTocSa5dA9QSlmY5HDgA0mOBS4E1gTelOTHNM3m1/e97L+As5J8jmat8sU0N+78TinluiSfAD6VZA2aNb43ao9zc8/63ytqvSRj/0vxAOB9wK3A/00w/gLghUkeD9wAvL193Tntdd+a5KPAx5IsBk4BNgUeUkr5Su+BSin/0y7f8pMk/1hK6V+3XKrmjjv8ywR1y0ypBnOlrpkp1WCuVIO5UtfM1OhxJrl0z/EZmjW6X9TOun478C7gL8DLaNYnv1M7u/xpwO7AH4BTgecCt7dD3gcc0r7uXOBnNMuvXLIKNf4LzfIqVwEnAvcHnllKOX+C8R8CTgN+DpwEXA0c2zfmEOCTwAfbOr8FbDbewdqbmR4EHN823qXV4pprrhl0CRoyZko1mCt1zUypBnOlGsyVumamRo8zyaXVrJRyEpBxtl9OM3t87PmngE/1DftG32tOppkdPt55CvDp9rHKSikzl2PMSfRcWyllPrDPFK+5g+ZmoB8eZ988+t6rUsp/A/89dcWSJEmSJEnS1JxJLknSFHbcccdBl6AhY6ZUg7lS18yUajBXqsFcqWtmavTYJJdGUJIvJFkwweMLg65Puqe5/PIu73crmSnVYa7UNTOlGsyVajBX6pqZGj0utyKNpvcDn5hg382rsxDp3uDWW28ddAkaMmZKNZgrdc1MqQZzpRrMlbpmpkaPTXJpBJVSrgG8C4W0nNZdd91Bl6AhY6ZUg7lS18yUajBXqsFcqWtmavS43IokSVN40IMeNOgSNGTMlGowV+qamVIN5ko1mCt1zUyNHpvkkiRN4YILLhh0CRoyZko1mCt1zUypBnOlGsyVumamRo/LrUgaOoc/6YVMmzZt0GVIkiRJkiTpXsCZ5JIkTWGzzTYbdAkaMmZKNZgrdc1MqQZzpRrMlbpmpkaPTXJJkqaQZNAlaMiYKdVgrtQ1M6UazJVqMFfqmpkaPTbJJUmawt/+9rdBl6AhY6ZUg7lS18yUajBXqsFcqWtmavTYJJckSZIkSZIkjSyb5JIkTWH77bcfdAkaMmZKNZgrdc1MqQZzpRrMlbpmpkaPTXJJkqZw1VVXDboEDRkzpRrMlbpmplSDuVIN5kpdM1OjZ/qgC5Ckrv3LyT9iMWW1n/ebT37+aj+nVo+FCxcOugQNGTOlGsyVumamVIO5Ug3mSl0zU6PHmeSSJE1h7bXXHnQJGjJmSjWYK3XNTKkGc6UazJW6ZqZGj01ySZKmsM022wy6BA0ZM6UazJW6ZqZUg7lSDeZKXTNTo8cmuSRJU5g7d+6gS9CQMVOqwVypa2ZKNZgr1WCu1DUzNXpskkuSJEmSJEmSRpZNckmSprDpppsOugQNGTOlGsyVumamVIO5Ug3mSl0zU6PHJrkkSVOYPn36oEvQkDFTqsFcqWtmSjWYK9VgrtQ1MzV6bJJLkjSFq666atAlaMiYKdVgrtQ1M6UazJVqMFfqmpkaPTbJJXUuybZJSpIZk4zZP8mNq68qSZIkSZIk6e5skkurSZKZbeN47HFtkuOTPGzQtU0kyUeSnNe3bZe2/iP6tu+f5LYk6y7n4b8F7NTz+oOTnLGqNUs1bLfddoMuQUPGTKkGc6WumSnVYK5Ug7lS18zU6LFJLq1+OwObA08H1gaOS7LWYEua0InAzkke2LNtb+ByYGbf2L2B35VSFi3PgUspi0op13RSpVTZNdcYVXXLTKkGc6WumSnVYK5Ug7lS18zU6LFJLq1+15RSri6lnAYcCmwF7DK2M8nbk5yV5JYklyf5XJL1ew+QZM8kJyVZmOSGJD9PsnG7b40k705ySZJFSeYkeeFK1vobYAnLNsRnAp8FNkmybd/2E/tev12SE9s65yR5XM813LncSpL9gYOA3Xtm2u/f7rtvki+3M+9vTnJCkt0nK3rJoltZsnDRnY+lS5as8IVLvRYsWDDoEjRkzJRqMFfqmplSDeZKNZgrdc1MjR5v1SoNSJKNgP3ap4t7dt0BvBm4BNgO+BzwMeCN7etmALOBrwJvAW6nmcU9rX39u4F/Bl4PXAA8CfhmkmtLKSevSI2llFuS/LE9/jHt5pnAx9ufewNfS7IdsDV3b5J/GHhHW8eHgaOT7FBKub1v3LeAhwLPAJ7Sbrup/fkdYBHwj+221wGzk+xUSpk/Xt0nvu6dLFy48M7nO7zo2ez04ucu/4VLfdZa6576xx66tzJTqsFcqWtmSjWYK9VgrtQ1MzV6bJJLq99fkwDcp33+o1LKnet+l1IO7Rk7L8l/AF+gbZID/wb8qZTyxp5xZwMkWRt4D/CUUsqp7b6LkzyBprm8Qk3y1onAi9rj7wasA5wO/IqmUf619uetwO/6XvuJUspx7WsPauvcAVhmnfNSyqIkC4DbSylXj21v6340sFkp5bZ28zuS7AO8EPjSeAXv/cWPs7jccefzNdb0P3VaNa5Hp66ZKdVgrtQ1M6UazJVqMFfqmpkaPS63Iq1+TwQeCewPzKWZ8X2nJE9JMjvJFUn+DnwDuF+S9dohM2hmko9nB2A94BdJFow9gFcA269kvScBOyXZnKYZ/ptSylKahvvMdsxM4Lc9jewxZ/b8flX7c7MVOPfuwPrA9X3X82AmuZ41112HNddb987HtDXXXIFTSnd33nnnTT1IWgFmSjWYK3XNTKkGc6UazJW6ZqZGj9MrpdXvklLKjcD5STajWWrkSQDtGt8/AT4PvBeYDzwB+AqwFrCQZumRiYytXf4s4Iq+ff0N7OV1Cs1yMHu3j7HZ6H8E7t8utTIT+OI4r+1dDLy0P1fky7n1aZrrM8fZd+MKHEeSJEmSJEkalzPJpcH6LPDQJM9rnz+S5t/lgaWU35VS5gJb9L3mTGDWBMc7h6YZvnUp5cK+x+UrU2ApZRHwe5pG9V40M8sppSyhWV7lAJqbj/avR76iFnPXuupjTgMeSLMMS//1XLeK55OW2/3ud79Bl6AhY6ZUg7lS18yUajBXqsFcqWtmavR00iRPslGS/uaWpCmUUhYChwMfSLNQ+YXAmsCbkmyX5OX0LccC/BewR5LPJXl4kl2SvCHJ/Uspfwc+AXwqySuTbJ/kEUnelOSVq1DqiTQ3GV2HpnE95mTgTcAtNDPLV8U84MFJZiS5f7u++i+BU4FjkzwtybZJHp/kw0ketYrnk5bbOuusM+gSNGTMlGowV+qamVIN5ko1mCt1zUyNnpVukid5VJKfJVkIXE8zw5S2ufXDJDO7KVEaep8BdgVeVEqZA7wdeBfwF+BlwLt7B7ezy59Gs173H2iayM8Fbm+HvA84pH3ducDPaJZfuWQVajwR2AA4pZRye8/2k9vtv2lnlq+K79HUeiJwLfCSUkoBnklzk9Cv0azhfgywDfC3VTyftNyuuKJ/9SJp1Zgp1WCu1DUzpRrMlWowV+qamRo9K7UmeZLHAyfQrHn8TeA1Y/tKKdcl2Qh4He2yDJKglHISkHG2X04ze3zs+aeAT/UN+0bfa04G9pzgPAX4dPvoxCS1nzzB9nn929t12NPz/AjgiJ7ntwEvHOdYfwfe3D4kSZIkSZKkTq3sTPL/pJmhuhvwnnH2nwg8ZmWLkiTpnmTbbbcddAkaMmZKNZgrdc1MqQZzpRrMlbpmpkbPyjbJ9wC+1s78LOPsv4LmZnuS7kGSfCHJggkeXxh0fdI91fz58wddgoaMmVIN5kpdM1OqwVypBnOlrpmp0bNSy60AS5i8wb4lsGAljy2pnvfT3NhzPDevzkKke5Obb/afh7plplSDuVLXzJRqMFeqwVypa2Zq9Kxsk/x3NGsHH9q/I8l9gFfR3NBP0j1IKeUa4JpB1yHd20yfvrL/cymNz0ypBnOlrpkp1WCuVIO5UtfM1OhZ2eVWDgIeleQ44B/bbbsneQ3wZ2BT4JAO6pMkaeB22mmnQZegIWOmVIO5UtfMlGowV6rBXKlrZmr0rNTXIqWU3yd5JvB54Ovt5k+2Py8CnllKObOD+iRphR2+13OYNm3aoMvQEDnnnHPYbbfdBl2GhoiZUg3mSl0zU6rBXKkGc6WumanRs8JN8iQBNgB+W0rZOckMYEeaWekXAX8upYx3M09JkiRJkiRJku5RVmYm+VrAfOA9wMdKKWcAZ3RYkyRJ9ygbb7zxoEvQkDFTqsFcqWtmSjWYK9VgrtQ1MzV6VnhN8lLKbcDVwG3dlyNJ0j3P+uuvP+gSNGTMlGowV+qamVIN5ko1mCt1zUyNnpW9cecRwCuSrNVhLZIk3SNdfvnlgy5BQ8ZMqQZzpa6ZKdVgrlSDuVLXzNToWakbdwJnAfsAZyc5ApgHLOofVEr5/soWJkmSJEmSJElSbSvbJD+65/dDJhhTgGkreXxJku4xtt5660GXoCFjplSDuVLXzJRqMFeqwVypa2Zq9Kxsk3zvTquQpA699qSfspiyWs/5jVnPXq3n0+p10003uSadOmWmVIO5UtfMlGowV6rBXKlrZmr0rFSTvJRycteFSJJ0T3XTTTex5ZZbDroMDREzpRrMlbpmplSDuVIN5kpdM1OjZ2Vv3ClJ0shYYw3/51LdMlOqwVypa2ZKNZgr1WCu1DUzNXpWaiZ5khOWY1gppcxameNLknRPsssuuwy6BA0ZM6UazJW6ZqZUg7lSDeZKXTNTo2dlvxZZA0jfYzqwPTATeNAqHFuSpHuU8847b9AlaMiYKdVgrtQ1M6UazJVqMFfqmpkaPSu7JvnMifYl+SfgS8DbV7ImSZLuUe64445Bl6AhY6ZUg7lS18yUajBXqsFcqWtmavR0Ptu7lPIT4JvAoV0fW5KkQdhoo40GXYKGjJlSDeZKXTNTqsFcqQZzpa6ZqdFTa0mUi4A9Kh1bkqTVyv+DpK6ZKdVgrtQ1M6UazJVqMFfqmpkaPZ03yZNMB/YFruv62Konybwkb72nHGcFzndEkmOnGLNaa1pRSfZPcuOg65hMVzXeG65VGs9ll1026BI0ZMyUajBX6pqZUg3mSjWYK3XNTI2elVqTPMlXJ9h1X+CxwANxTfLVIslM4MSeTdcBfwTeVUo5q+J59wcOLaXct2/XHsAttc67kqrXlGQr4APAM4D7A1cBxwIfLKVc3zNuHs37dmjNeu4JJrjWbwHHD6QgSZIkSZIkaRwr1SQHngyUvm0FuAH4DfDlUsr/rUphWmE7AzcDWwAfB45LskMpZfHqLKKUcu3qPN/yqF1Tku2AU4G5wEuAS4CH0HwO/5jksaWU+TVrmKCuNUspS6YYMw0opZTVckeKUsoiYNHqOJfUpa222mrQJWjImCnVYK7UNTOlGsyVajBX6pqZGj0rtdxKKWXbUsqD+x7blVIeWUrZ1wb5QFxTSrm6lHIazU1TtwJ2GduZ5AlJfp1kUZLLkxyW5D4THSzJ25OcleSWdvznkqzf7psJfA3YKElpHwe3+5ZZ2iTJ1kl+mGRBkpuTfDvJA3r2H5zkjCQvb197U5JjkmzQM+aFbS2Lklyf5Jf9tSd5R5Kr2v2fTbJmz77+mkqSNyT5aXvMi5O8cAXf716fBRYDTyulnFxKuayU8lPgKcCWwIfb854EbAN8aux967uGpyc5t32vfpZk8779r2n335rkvCRv7Nm3bXvMFyc5OcmtwMv6Cx1b7iTJc5KcA9wGbJ1k7SSfSHJF+5n/vv2cx5Vk+/Zz/Vtb7x+TPKVn/7jX2rvcSpKd2n279B37bUku6nn+0PazWtCe7xtJ7j9RbVINCxYsGHQJGjJmSjWYK3XNTKkGc6UazJW6ZqZGz0o1yZO8Ism2k+zfNskrVroqrbQkGwH7tU8Xt9u2B34GfA94OPBi4AnAZyY51B3Am2lmRL+S5q8HPtbu+y3wVpqZ65u3j0+MU8sawA+BTYC9gKcC29EsudFre2Af4J/ax17Av7fH2Bw4GvgqsCswE/g+kJ7X790eY++21v3bx2QOoXk/dgeOAo5JsusUr7mbJJsATwc+186SvlMp5er22C9OEuD5wF+B93PX+zZmPeAdwMuBJwFb0/OeJnkZ8EHgvTTvw3uAQ5K8sq+kjwCfbsf8fIKy1wPeBbyG5vO9hiYLj6PJzsOB7wA/S7LjBMdYn2bZlFnAP9Dk68dJtm73T3atY+/PXOBP3L2Z/zLgf9vrvi9wAnA68Cia5WweAHx7groAWLJoEUsW3vVYumTSCfXSlG644YZBl6AhY6ZUg7lS18yUajBXqsFcqWtmavSs7HIrX6Np5s2bYP9j2jFfX8nja8X9tenDMjbD+kellPPa398NHNWzNvQFSd4MnJzkDaWUW/sP1reO9Lwk/wF8AXhjKWVxkpuaYeXqSWqaBTwMeHAp5XJovmABzk6yRynlj+24NYD9Syl/b8d8o33te2maq9OB75dSLm3H96+1fgPwr6WUpcB5SY5rX3/4JLV9p5Ty5fb39yV5KvAm4I2TvGY8O9I07M+dYP+5wMbApqWUa5IsBf4+zvu2JvD6UspFAEk+Q9NgHvMB4MBSyvfb55ck2Q14HXBkz7hDe8ZMZE2az3FOe66tgVcBW5dSrmzHfCLJM9rt7+k/QPvaOT2b3pfkecBzgM+UUuZPcq29jgL+FXhfW8tOwCOBf273/ytweinlzhqSvBq4PMlObaP9bk54/dtYuHDhnc93fNE+7LTv8yYp4/+zd+dhclRl+8e/NyFAIIAsgqgEkD2KxAVBAxIMKi4oqCC4AYKA/FwBFfWVRVwRFBERRX1Z5AVRAQVZhLCogAoCAdkSlkDYZMsCJJBkeH5/nNOh0pmZnpnUSSfd9+e6+prpqtNVT3XfQa+nz5wyMzMzMzMzM7NuNdQmuVrsXwmYN8Rj29BsB8wi3Tj1a8CBlX1bAq/Ns5EbRGpOb0AvDd68dMZXSUu2rELKygqSVoyIWc3j+7A5MLXRIAeIiNvzchubk24wCjCl0SDPHgHWyr9PBCYAt0q6FPgL8PuIqH6ld1tukFdfv0WL2q7r5fmYllfUt1b/JlqZ1WiQZ/Pfg7y0zIbAryRVG//LAjOajnPD/IKk20hLngD8LSLelX+fA9xSec0WwDBgUv6ipWF54El6obT0zpHAe3jxi4wRpBnwg3E2qSG/TUT8gzSL/MbKFzxbAjtI6u3vnDYkrQO/kLed/CPmxIur2SwzfKj/qTNLRo8e3e4SrMM4U1aCc2V1c6asBOfKSnCurG7OVPcZcOdI0mtZsIm4naTeXv8SUoO21+aVFXNfREwH7pK0FmlJk7fmfSOBnwMn9PK6B5o35KV0LgR+RprN/RRpeZZfAcuRmvF1al4LI8hLAUVET57l/RbgHaTZ3t+WtHVE3Nfq9YvB3fl8mwPn9bJ/c9JM91Y3D+3tGhod65H556eAfzaN62l6/mzl93eTZo3DgjfLnB1R6SCn4/eQZnA3H6+vRbiOJS2fcyjpPZgN/J6UjwGLiEclXQF8BPhH/vmzptouIC0P0+yRvo47fMQIYqF7C5sN3aRJk9hkk03aXYZ1EGfKSnCurG7OlJXgXFkJzpXVzZnqPoOZXrkrcET+PUjLPBzQx9jpgNckb5+fAl+VtGtEnAfcCIyOiLsH+Po3kJrMh0TECwCSdm8aM4c0+7g/dwDrSlq3stzKaNIXKbcPsBZyQ/ca4BpJ3wTuJ+XxhwM9Ri+2YcHlgLYhrXs9KBHxpKTLgIMk/ai6Lrmkl5FmRp9eaUoP5H1rPsd/JT0MvCoizhzE6+5vPQpI1z0MWCsi/jbA14wFTs35aswsX79pzECv9UzgGElnkdasP7uy70bgg6S/NvBfp1jbzJvn+Fm9nCkrwbmyujlTVoJzZSU4V1Y3Z6r7DGa27S+ArYA3kWa4Hp6fVx9vJM2cXSsiLqy3VBuovBzKKcBR+YaR3wfeIulESWMkbSzp/Xnd697cTZqB/FlJr5L0cRZcvgXSevQjJY2XtKak5+OG3gABAABJREFUFXs5zuWk9cPPlPR6SW8iNaavjogbehm/EElbS/qapDfmtbM/ALyUvtcAH6jdJH1S0iaSjiLlur8bmfbnM6SlSS6V9FZJ6+b1vC8DHiLNxm+YArxV0iskrTmIcxxB+uLjc7nmLSTtI+ngIdY8X17X+0zgdEkfkLSBpDdJ+qqk9/TxssnAB3KetiTdaLP5vydTGNi1ngusTJpBfmVlXXRIX/isDpwlaStJG0p6p6T/lTSoLxvMFsUqq6zS7hKswzhTVoJzZXVzpqwE58pKcK6sbs5U9xlwkzwiHomIf+fm5g7AL/Lz6uPGiLjLMz6XCCeSvrDYLSJuAbYHNgH+Rpo5/E3g4d5emG/KeDBpiYv/kGZDf7VpzLWkG3n+lrSUyJd7OU4A7yctN/JXUtP8XuDDg7iOmaRlYy4iLeHzLdIM94sHcYzeHAHsQVqb+xPAnhEx4NntVRExmfQF0b3AOcA9pC+VrgTeHBFPVYYfTppxfQ+tl2CpnuOXwH6kG2neClwN7A3c18/LBmMf0hcYxwF3AeeTvvhaaDme7GDS53otaTmUS0mzvqsGdK15PfoLSOuPn9m072HSrPVhpPXobwWOJ/21ygsDuTCzOqy++urtLsE6jDNlJThXVjdnykpwrqwE58rq5kx1Hy24NLFZ55MUwK4RcX67a7F6TZgwYRVgxk+nPcycxbwm+Rnjd16s57PF6/bbb/eNW6xWzpSV4FxZ3ZwpK8G5shKcK6ubM9U5enp6mDhxIsCq48ePn9nXuMGsSb6AvN7yvsDrgVVZeFZ6RMT4oR7fzMzMzMzMzMzMzKy0ITXJJb0WuAoYQVqaYQvSjRhfAryCtLzC1FoqNFuMJH0N+Fofu/8WEe9anPWY2ZLhFa94RbtLsA7jTFkJzpXVzZmyEpwrK8G5sro5U91nMDfurPoe8AywKbAj6Uaen4+IdUnrTa8GHFZLhWY1iwj1s9TKycCYPh77FS7NzJZQzz33XLtLsA7jTFkJzpXVzZmyEpwrK8G5sro5U91nqE3yscDPI+IBXrx53jIAEfE70s33frDo5ZktXhHxVETc3cfjoXbXZ2bt8eSTT7a7BOswzpSV4FxZ3ZwpK8G5shKcK6ubM9V9htokXwb4b/59OtADVG/7eivwhqGXZWZmZmZmZmZmZmZW3lBv3HkfsAFARLwg6T7Ssivn5P1vITXPzcwWu1+MexfDhg1rdxnWQTbbbLN2l2AdxpmyEpwrq5szZSU4V1aCc2V1c6a6z1Bnkv8F2K3y/GfAfpIulzQB2Av4v0UtzszMbElw7733trsE6zDOlJXgXFndnCkrwbmyEpwrq5sz1X2GOpP828BZkoZHxFzgeGAl4IOkpVeOBr5TS4VmZmZtNmfOnHaXYB3GmbISnCurmzNlJThXVoJzZXVzprrPkJrkETEN+HfleQDfyg8zM7OOMnLkyHaXYB3GmbISnCurmzNlJThXVoJzZXVzprrPUJdbmU/SOpK2lLRSHQWZmZktadZaa612l2AdxpmyEpwrq5szZSU4V1aCc2V1c6a6z5Cb5JLeL+lO4EHgRmDrvH1NSTdJ2qWeEs3MzNrL69FZ3ZwpK8G5sro5U1aCc2UlOFdWN2eq+wypSS5pZ+Bc4AngKECNfRHxBPAQsE8dBZqZmZmZmZmZmZmZlTLUG3ceDvw1InaQtAZwZNP+64ADFqUwM7Oh2v+qCcwhihz7jPHvLHJcW7Kts8467S7BOowzZSU4V1Y3Z8pKcK6sBOfK6uZMdZ+hLrfyGuCcfvb/F/DiPWZm1hHmzZvX7hKswzhTVoJzZXVzpqwE58pKcK6sbs5U9xlqk3wW0N+NOl8FPDnEY5uZmS1RHn/88XaXYB3GmbISnCurmzNlJThXVoJzZXVzprrPUJvkVwJ7SVpouRZJLwM+BfxlUQozMzMzMzMzMzMzMyttqE3y/wFeCVxPWns8gHdK+hZwK+lGnkfVUqGZmVmbbbLJJu0uwTqMM2UlOFdWN2fKSnCurATnyurmTHWfATXJJb1W0qqN5xFxJzCWtKTK0aSm+JeAr5Ga5NtFxJTaqzUzM2uD+++/v90lWIdxpqwE58rq5kxZCc6VleBcWd2cqe4z0JnkNwHvaTyRdAWwTkTsCKwJbA28GVg7It4WEXfUXqmZmVmbPP/88+0uwTqMM2UlOFdWN2fKSnCurATnyurmTHWfhdYU78NsYMXK83HALwEiYhpp2RUzM7OOtOKKK7YeZDYIzpSV4FxZ3ZwpK8G5shKcK6ubM9V9BtoknwgcLKkHmJG3bSXpuf5eFBHnLkpx1hkkBbBrRJy/JBzHlm6S1gfuA14XETe3txrrFuuss067S7AO40xZCc6V1c2ZshKcKyvBubK6OVPdZ6DLrXyeNJP8V8DvSTfq/Hz+va/H7+ou1uojaZykkDRN0gpN+7bK+6Km060DXJyPvX4+9piajj0gi3Le/Lpd6q9qUDXsKukfkmZIelrSbZKOb2dNg9Guz92sLvfcc0+7S7AO40xZCc6V1c2ZshKcKyvBubK6OVPdZ0AzySPiBkkbARsCawNXAd8GLi9Xmi0mTwO7AmdVtu0LPACMWpQDS1ouIuZExKOLcpxuJ2k88Fvg68CfSF9SjQbe3s664MXPuN11mJmZmZmZmZmZDdVAZ5ITEfMi4q6I+CtwGnBhRFzd36Nc2Vaj04BPNp5IGgHskbdT2b6GpLMkPSRplqRbJe3ZNOYqSSdKOl7SE8CleXt1JvZ9+edNeftVecxWki6T9ESeLX21pNcP5kIkrSbpTEmPS5otabKkfRblvJKm5F/Py6+bkrefKun8pvMf3zhufv6h/D7NlvSkpMslrTSYa8p2Bq6JiB/kf4OTIuL8iPh/Ted/v6QbJT0n6V5JR0hatrI/JH1a0sW5pnslfajpGN+XNCl/xvdKOlrS8Mr+IyXdLGk/SfcBz+XtO0n6u6Tp+VovlLRh5dC9vv/5tftJuiPXfaekg5pqepOkm/L+G4DXDeE9NFska6+9drtLsA7jTFkJzpXVzZmyEpwrK8G5sro5U91nwE3yqojYJyL+WXcx1hZnANtJaswa/yAwBbixadwKwL+B9wCvAX4BnCHpTU3j9gLmAGOBA3s5X2P8jqRlWD6Qn69MasxvC2wDTAYukrTyIK7laNIM63cBmwOfBp5YxPNulX/uk1/XeN4vSeuQZuf/OtcyDjgX0CCup+FR4NWSXtPP+bYDTgd+THoPDgD2Js0+rzoa+AOwJXAmcLakzSv7n86vG01aUulTwBebjrERKScfAMbkbSsBPwTeCIwHXiB9sdD4b0yv77+kjwLfzHVuDnwNOFrSXnn/SOBC4HbgDcCRwLF9vQ8Nc2fPYu6sFx89c+e2eolZvyLqWn3KLHGmrATnyurmTFkJzpWV4FxZ3Zyp7jPQG3da53qMtF743qRm5SdJjd0FRMRDLNic/ImkdwK7A/+qbJ8cEV/u53yP559PVpdhiYgrqoMk7Q9MB7YnNUkHYhRwU0TckJ9PWdTzRsTjkgCmD3LZmHVI/77OjYj787ZbB/H6qp8A2wG3Srof+AfwF+DMiHg+jzkC+F5ENP4C4F5J3wCOAY6qHOt3EfHL/Ps3JL0d+CxwEEBEfKsydoqkY0l/WXBMZftywCciovGeEhF/qBYs6ZOk93w08B/6eP9zbYdUbvJ7n6RGk/804COkL/P2jYjngNskvRL4Wd9vF1xx4GeYNWvW/Ocb7/ZBNtn9Q/28wqx/jz32GGuuuWa7y7AO4kxZCc6V1c2ZshKcKyvBubK6OVPdx01yg9QU/7Gk3wBvBnYjNWXnkzSMNMt3d+AVpEbp8sCsBQ/Fv4dSgKS1gW+RZlyvBQwj3Sy213XRJV1cqfH+iHg1qXH6h7xcyl+A8yPi2jrPOwgTgQmkxvaluZ7fR8S0wR4oIp4F3pOXL9mBNOP9OODzkt4cEbNIM8PHSqrOHB8GrCBpxTwG4Lqmw1/Hi7PBkfRh4HOk+w+MJP03YmbTa+6vNsjz6zYmfcmyNbAmL/6VyihSk3wheemZDYFfSTqlsmtZYEb+fXPgltwgr9bcr7edfCJzKt/6LjN8eD+jzczMzMzMzMysm7lJbpBmkv8C+BVwQUQ8mWdPV32JtPzGF0gzop8Fjic1y6ueHWINpwFr5HPcDzxPaoY2H79hP2BE/n0uQERcLGk94N2km1pOkPTTiDi0xvM2vMDCS6fM78RGRE+epf0W4B2k2drflrR1RNzHEETEPcA9wC8lfRuYBHwY+F9SQ/sI0pIuzZ7rZdtCJL2ZtATLEaT15GeQZpEf0jS0t8/4AtL79yngYVKT/D/0/z6OzD8/BTQv39QzkJr7MnzEigT+0yirz8Ybb9zuEqzDOFNWgnNldXOmrATnykpwrqxuzlT3GdKa5NZZImIeaT3rcfSy1Eo2FvhjRPwmIiYC9wKbDOF0c/LPYb0c/4SIuCgibiM1q/v8u5aIeCgi7s6P+yvbH4+I0yLiY6SG/v41nHduL697nLSkStWYphojIq6JiCNIN5ucA+za1zUN0hTSLP7GjUBvBDatvCfVxwuV123TdJxtgDvy728hzRL/dkTcEBGTgfVaFSJpDWBT4FsRMSEi7gBWaxq20PsfEf8lNdRf1UvNjS8S7gBeK2mFfq7BrLgHH3yw3SVYh3GmrATnyurmTFkJzpWV4FxZ3Zyp7uOZ5NbwDeAHwJN97J8MfEjSW4BpwMHA2qQbKg7GY8BsYCdJDwLPRcSMfPyPS7oBWCXXMnswB5b0TdJyL7eRloJ5Ly82gBflvFOA8ZKuAZ7PS6ZcAXxJ0idIM88/Rrqh6U25lq1JN7D8Sz731sBLK/UM5rqOJC0BcxFptvZLSEuiDAcuy8O+CVwo6QHg96SZ7lsCr4mI/6kcbrd8rX8HPkq6oea+ed9kYJSkPYDrSTdpHUhTfxopN/tLeoS0xMr3msb09f4fAZwgaQZwCelzeyOwWkT8EPg/4NvAKZK+C6wP9PeXAWZFzJ49qP8cmbXkTFkJzpXVzZmyEpwrK8G5sro5U93HM8kNgIiYExFPRN+37/0WabbypcBVwKPA+UM4zzxSg/cA0iziP+Zd+5JmH98InAGcQGqsDsYc4LvALcBfSUt27FHDeQ8hLd8yldwEj4hLgaNJN7S8HliZNBu/YSbwVlJjexLp/TskIi4e5DUBXA28Kh//TtLyOC8D3hERd1XqeS9paZfrSTf3/CKpqV51BOk9uQX4BLBnRNyej/En4EfAicDNpJnlR7cqLs9U3wN4A2mJlR+Rluepjun1/c83Ed0P2Ie0jM/VpJvI3pf3PwPsDGxBeu+/DXylVU1mdVthhRVaDzIbBGfKSnCurG7OlJXgXFkJzpXVzZnqPuq7J2pmnURSALtGxPntrqWUCRMmrALM+Om0J5hTaE3yM8a/s8hxbck2d+5chvsGsFYjZ8pKcK6sbs6UleBcWQnOldXNmeocPT09TJw4EWDV8ePHz+xrnGeSm5mZtTB58uR2l2AdxpmyEpwrq5szZSU4V1aCc2V1c6a6j9ckN1vMJD3Tz+53RcTfFlsxZmZmZmZmZmZmXc5NcrPFb0w/+x4qddKIUKljm3W6tdZaq90lWIdxpqwE58rq5kxZCc6VleBcWd2cqe7jJrnZYhYRd7e7BjMbnGWW8epkVi9nykpwrqxuzpSV4FxZCc6V1c2Z6j7+xM3MzFp49NFH212CdRhnykpwrqxuzpSV4FxZCc6V1c2Z6j5ukpuZmZmZmZmZmZlZ1/JyK2bWcX4xbjzDhg1rdxnWQTbccMN2l2AdxpmyEpwrq5szZSU4V1aCc2V1c6a6j2eSm5mZteA/tbO6OVNWgnNldXOmrATnykpwrqxuzlT3cZPczMyshWeffbbdJViHcaasBOfK6uZMWQnOlZXgXFndnKnu4ya5mZlZC8svv3y7S7AO40xZCc6V1c2ZshKcKyvBubK6OVPdx01yMzOzFtZff/12l2AdxpmyEpwrq5szZSU4V1aCc2V1c6a6j5vkZmZmLdx1113tLsE6jDNlJThXVjdnykpwrqwE58rq5kx1n2XbXYCZWd0OuOpq5tR4vNPHv63Go5mZmZmZmZmZ2ZLEM8nNzMxaWHPNNdtdgnUYZ8pKcK6sbs6UleBcWQnOldXNmeo+bpKbmZm1sNxyy7W7BOswzpSV4FxZ3ZwpK8G5shKcK6ubM9V93CQ3MzNr4eGHH253CdZhnCkrwbmyujlTVoJzZSU4V1Y3Z6r7uEluZmZmZmZmZmZmZl3LTXIzM7MWNthgg3aXYB3GmbISnCurmzNlJThXVoJzZXVzprqPm+RmZmYtPP744+0uwTqMM2UlOFdWN2fKSnCurATnyurmTHUfN8nNzMxaeOaZZ9pdgnUYZ8pKcK6sbs6UleBcWQnOldXNmeo+bpLbIpN0pKSb213H4iTpKknHtxgTknZZPBXVrxs/V7O+DB8+vN0lWIdxpqwE58rq5kxZCc6VleBcWd2cqe7jJnlhkoZJ+qKkWyU9J2mapIsljW13bUPRR+P3WGB8G8qZT9KUXNsevey7Le/bezGXtQ5w8WI+Z53a/rlWSRqXP8eXtLsW6z4bbbRRu0uwDuNMWQnOldXNmbISnCsrwbmyujlT3cdN8oIkCTgbOBz4MbA5MA6YCly1NM8yroqIZyLiyXbXQXpf96lukLQN8DLg2cVdTEQ8GhHPL+7z1mUJ+lzN2u6OO+5odwnWYZwpK8G5sro5U1aCc2UlOFdWN2eq+7hJXtbuwIeAT0TELyPivoiYGBH7A38CfilppcZgSTtLuj7POH9C0nmVfctL+r6kqZKel3S3pH3zvr0lTa+eWNIukqLy/EhJN0s6IB9jlqRzJK1aGbOVpMvyuWdIulrS6yv7p+Rfz8szeqdUj10Zt4ykwyU9mGu9WdJOlf3r59d/QNKVuZaJkt68SO82nAlsL2ndyrZP5u3zmt6fg/Ps/mfz+3GSpJFNY8bmZVVm5b8AuFTSapUhy0g6RtJTkh6VdGTT6+fPuh/oNUvaVtLfJM3OdZ1QzUhvcjZOkPRYzs7fJW1V2d+Ygf0eSbfkMf+Q9JoWx23+XE+VdL6kQyU9IulJST+VNLwy5iBJk/M5/ivp95V9V0k6MT9m5Jwdnb9Mql7LQjmXtD5wZR42LV/Pqf3Vb2ZmZmZmZmZmNhBukpf1EWBSRFzQy77jgDWAtwNIeg9wHnAR8DrSMhf/qow/HdgT+BxpRvoBwGDvIrARqXG/M7BTPs9Jlf0rA6cB2wLbAJOBiyStnPc3Gq/7kJYS2YrefR44BDgUeC1wKfAnSRs3jfs2aUmPMcAk4CxJyw7ymqr+m8+1F4CkFYEPA7/uZewLpPfy1Xn824BjGjsljQEmALcDbya9JxcAwyrH2Is0Q31r4MvA4ZLe3qLGPq9Z0obAJcAfSO/bh/N5T2xxzGOAD+Z6Xg/cDVwqafWmcT8gfS5bAY8DF1Qb3AO0A7Bh/rkXsHd+IOmNwAmkv5zYlJSxvza9fi/SFxZvIuXkYGC/yv6+cj41XyP52Ovk1/dq7uzZzJ01a/6jZ+7cQV6m2YJWX735n5PZonGmrATnyurmTFkJzpWV4FxZ3Zyp7rMoDUlrbROgr7/PuKMyBuDrwNkRcURlzEQASZuQmttvj4jL8757h1DPCqRZ7Q/l434W+LOkQ/LSIFdUB0vaH5gObA9cGBGP50m/0yPi0X7Ocyjw/Yg4Oz//iqQdgC8A/68y7tiI+HM+1xHAbaRG/p1DuLaGXwPHSfo2aRb/PRFxc2WyMgARcXzl6RRJ/wOcDByUt30ZuCEiDqqMu63pXLdExFH598mSPkP6cuOyfurr75q/CpxZqW2ypM8BV0v6dEQ813ywPMv808DeEXFx3vYp0pcv+5Ia4w1HRcRlecxewIPArsA5/dTbbBrwmYjoAe6U9Od8zacAo0hfGlwYEU8D9wM3Nb1+KvDFiAjgLklbAF8ETmmVc0lP5V8fi4jp/RU54cADmDVr1vznG++2G5vu/uFBXKbZgkaMGNHuEqzDOFNWgnNldXOmrATnykpwrqxuzlT3cZO8PLUeAqSZxaf0s68HuHoRa3mg0SDPriP9NcGmwKOS1ga+RVo3fS3SrOkVSc3PAZG0CvBy4JqmXdcAWzZtu6Xy+yP551osWpP8z8DPgbeSllrpbRY5knYkNaU3A1Yh/VtYQdKKETGL9J7/rsW5bml6/gip/oG+pvmatwReK+mj1VJJn9EGknYFvlbZNxp4CTCcyvsdEXMl/Ys0E7vqusqYpyTd1RgjqfpXCb+JiAP7qP+23CCvXsMW+ffLSI3xeyVdQpoVf15+Pxv+kRvk1ZoOkTSM+nLO+JN/zpzKaZbxXaltET300EOsuuqqrQeaDZAzZSU4V1Y3Z8pKcK6sBOfK6uZMdR83ycuaxMKNyobNK2MAZvdznP72QVo6pLkZP5Su4GmkJWA+T2p2Pk9qYi43hGMNRHUNjEZHc5GWAIqIeZLOAI4iLYOya/OYvL71hcDPSDP4nyIta/Ir0rXOovV7DgvWD+kaWtXf3zWPJDX4T+jldQ+QZrpXZ30/TGqS12FM5feZ/Yzr85oj4mmlNezHAe8AvgkcKWmrVjO/s4G85wMyfMQIovUwMzMzMzMzMzMzr0le2NnAxpJ27mXfIcCTvLg0xy2kZSt6cyvps9q+j/2PAys33eBxTC/jRkl6eeX5NqQG+135+VjghIi4KCJuIzXJ12w6xlwWXJd7ARExk9S8Hdu0ayxpfe/F4dek9+qPETGtl/1vIL2fh0TEPyJiEmn2e1V/n0cpNwKjI+LuXh5zIuKppm3zgHuAOVTe77zO+FYs/H5vUxmzGpXlgJqO+9hQLyAi5kXE5RHxZdK66uuT1ntv2LqXmibn2emtcj4n/+wzf2alrL/++u0uwTqMM2UlOFdWN2fKSnCurATnyurmTHUfN8nLOpt0M87TJO0raX1Jr5X0c+B9wH4R8WweexSwp6SjJG0uaQtJXwGIiCmkWd6/lrSLpA0kjZO0e37tP0mzn78jaUNJHyHfTLHJc7mWLSVtR5qxfE5lffHJwMfz+bcGzmTh2b1TgPGSXpYbrb35AWkd8g9L2lTS90hN+x8P7G1bNBFxB6m5v08fQ+4mzbT/rKRXSfo40Ly8yHeBrSSdlD+zzSR9WlLzlwZ1+j7wFkknShojaWNJ75fU5407c35+BvxA0k6SRpOW7VmRNDO+6nBJ4yW9BjgVeAI4v67iJb1X0udy7esBnyD9N+auyrBRkn6Yc7En8FlyLgaQ8/tJM9ffK+mlkkbWVbtZK0899VTrQWaD4ExZCc6V1c2ZshKcKyvBubK6OVPdx03ygvLay7sD3yHdnPAu4G/AesC4iDi/MvYqYDdS8/xm4ArgTZXDfRr4PXASaf3qU4CV8mufAj4GvJs0G3dP4MheSrobOBe4CPgLabZ09caU+wKrkWY0n0FqojfPKj6EdFPIqSx8U8aGE4AfAsflenYC3hcRk/sYX7uIeDIiel2+IyImAgcDXwH+A3yUtD55dcwk0pIhWwL/Ii07835gXsGabyHNot6ElJObSEuWPNzipYcBfyB9ZjeSbgT6zl5m0R9Gakj/G3gZsHNEzKE+04EPkLJ7B+mLhz3zXyU0nA6MIL2nP831/KKyv7+cPwQcAXwP+C/Q55cHZnWbObO/VYjMBs+ZshKcK6ubM2UlOFdWgnNldXOmuo8WvIeedSpJRwK7RMSYNpdii5mkccCVwGoDXBu8VB1XATdHxBdKnWPChAmrADNOmjadOrv/p49/W+tB1tHuuusuNt1003aXYR3EmbISnCurmzNlJThXVoJzZXVzpjpHT08PEydOBFh1/PjxfX774ZnkZmZmLfj/HFndnCkrwbmyujlTVoJzZSU4V1Y3Z6r7uEluSxxJF0t6po/H19pdn5l1nzvuuKPdJViHcaasBOfK6uZMWQnOlZXgXFndnKnus2y7C7DFIyKOpPd1ypdE+5HWre6N75wwSHm9ey0BdYxrdw1mQ+WlyaxuzpSV4FxZ3ZwpK8G5shKcK6ubM9V93CS3JU6+QaOZ2RLjJS95SbtLsA7jTFkJzpXVzZmyEpwrK8G5sro5U93Hy62YmZm1sPLKK7e7BOswzpSV4FxZ3ZwpK8G5shKcK6ubM9V93CQ3MzNrYerUqe0uwTqMM2UlOFdWN2fKSnCurATnyurmTHUfL7diZh3n5+O2Z9iwYe0uw8zMzMzMzMzMlgKeSW5mZtbCqFGj2l2CdRhnykpwrqxuzpSV4FxZCc6V1c2Z6j5ukpuZmbUwc+bMdpdgHcaZshKcK6ubM2UlOFdWgnNldXOmuo+b5GZmZi1Mnz693SVYh3GmrATnyurmTFkJzpWV4FxZ3Zyp7uMmuZmZWQuS2l2CdRhnykpwrqxuzpSV4FxZCc6V1c2Z6j6KiHbXYGZWiwkTJqwCzNhyyy19404zMzMzMzMzsy7X09PDxIkTAVYdP358n+voLLv4SjIzWzwOvOofzFmE1582fmxttVhnuOuuu9h0003bXYZ1EGfKSnCurG7OlJXgXFkJzpXVzZnqPl5uxczMrIWenp52l2AdxpmyEpwrq5szZSU4V1aCc2V1c6a6j5vkZmZmLayyyirtLsE6jDNlJThXVjdnykpwrqwE58rq5kx1HzfJzczMWlhttdXaXYJ1GGfKSnCurG7OlJXgXFkJzpXVzZnqPm6Sm5mZtXD//fe3uwTrMM6UleBcWd2cKSvBubISnCurmzPVfdwkNzMzMzMzMzMzM7Ou5Sa5mZlZC6985SvbXYJ1GGfKSnCurG7OlJXgXFkJzpXVzZnqPm6Sm5mZtTBr1qx2l2AdxpmyEpwrq5szZSU4V1aCc2V1c6a6j5vktkSRtL6kkDSmxmMeKenmuo63JJN0qqTzF9O5pkj6wuI4l1m7PfXUU+0uwTqMM2UlOFdWN2fKSnCurATnyurmTHUfN8mtX5JGSporaY+m7WfnZvb6TdunSDp6sRa5lJI0Lr+HzY9vtbs2MzMzMzMzMzOzbuEmufUrIp4BbgDGNe0aB0ytbpe0AbAecMVQziVpuaG8rgNsCqxTeXyvXYUoWbZd5zdbUo0ePbrdJViHcaasBOfK6uZMWQnOlZXgXFndnKnu4ya5DcSVLNgM3xxYAfgZCzbPxwHPA9flcR+UdJuk5/MM80OqB83bviHpdEkzgV80n1jSMEm/lnSnpFF9FSjplZLOkvSUpGcl3SBp6z7GbiXpMklPSJoh6WpJr6/sV16i5YFc+8OSTqjsP0jSZEnPSfqvpN/3894NxGMR8Wjl8Uw+z7qSzpE0PV/XH6sz9/N788O8/0lJxwBqutZlJH1V0n2SZkuaKOlDlf2N2ezvkvRv0ue3raQN8/n+K+kZSddL2nGwFybpLZJuzu/VDZJ2aV5OR9L2kv6V3+tHJH2v0aiXtH9+/5dpOu4fJf16sPWYDdWkSZPaXYJ1GGfKSnCurG7OlJXgXFkJzpXVzZnqPm6S20BcCWwqaZ38fAfg76QZ4+Mq43YArouI5yS9ATgHOBvYAjgSOFrS3k3HPhSYCLwOWGCZFknLA78DxgDbRcQDvRUnaSRwNfAK4H3AlsAx9J3vlYHTgG2BbYDJwEWSVs77Pwh8ETgA2BjYBbg1n+uNwAnA4aQZ4DsBf+3jPEMmaThwKfA0sB0wFngGuKQy4/4QYG/gk/laVgd2bTrUV4FPAAcCrwZ+BPxG0vZN474HHAZsDtwCjAQuAsaTPptLgAv6+6Kil2tYBbiA9N69HvgG8P2mMa/I57me9Ll9GtgX+J885HfAGqRsNV6zOul9P7Ovc8+dPZu5s2bNf/TMnTvQss16NW/evHaXYB3GmbISnCurmzNlJThXVoJzZXVzprqPl1WwgbgGmENqiJ+Vf14N/BtYU9IGEXEfsD3wq/yag4EJEdFofE+SNBr4EnBq5dhXRMRxjSeVmdIjgT8DywM7RMSMfur7CPBSYKuIaNxZ4e6+BkfEAsvBSNofmJ7rvxAYBTwKXB4Rc4EHgH/l4aOAZ4ELI+Jp4H7gpn5qG4gHpQUmgK8HvIvU5N8vIiLXuU+ucxzwF+ALwHcj4ty8/0DgnZXrWh74GrBjRFyXN98raVvSFwBXV855eERcVnn+FOnLi4ZvSNqV9CXEiQO8ro8AAXwqIp4Dbs9N8VMqYw4iLdvzmXydd0p6OfB9Sd+MiGmSLs7HmpBf8yHgCdKXN726/MC9F7gT9Sa77cmmu39kgGWbLWzllVduPchsEJwpK8G5sro5U1aCc2UlOFdWN2eq+7hJbi1FxCxJ1/Nik3x74AcRMU/StcA4pS7vKF5sXG4O/LHpUNcAX5A0LCJ68rYb+jjtWcCDwNsiYnZjo6STgY9VahtJmml+U6VB3i9JawPfytezFjAMWDHXD2n28hdIDeVLSDOdL4iIecBlpMZ4Y98lwHkRMYuh2440Y7xhGmlW9UbA000N9BWADSWtSlq//J+NHfnzuIEXl1zZKF/XZU3HWI6FG/sLfA55dv6RwHvyeZYFRvDie0TT+N4+l02BW3KDvOFfTS/dnPTXB1HZdg3pS5JXkr6gOBM4RdJBEfE88FHg7Ih4obdaAHY8+VTmVA65zPDhfQ01G5A111yz3SVYh3GmrATnyurmTFkJzpWV4FxZ3Zyp7uPlVmygrgR2kPRqUrP0xrz9atJSGDsAs6g0bQfo2T62XwS8Fnhz0/bDSU3xxgNgNoNzWn7t54G35N+fJDWPiYippAbvQfnYJwF/lTQ8zx5/PbAn8AjwTWCipJcMsoaq+yLi7srjBVKT+N8seK1jgE2A/xvgcUfmn+9pOsZo0mzsqubP4VjS0i1fIzXxx5CWTenr5qq9fS51uYDU+H+PpHVzPX0utQIwfMQIhq+44vzHMDfJbRHdd9997S7BOowzZSU4V1Y3Z8pKcK6sBOfK6uZMdR/PJLeBupK0TvRHgL9XZoL/Fdif1MS8JiLm5O13kNbRrhoLTKq8tj8/A/4D/EnSeyLiaoCIeAx4rGnsLcB+klYf4GzyscBBEXERpBtkAgt8RZhnr19AWof7p8CdpLXVb8wzyi8HLpd0FGkJlLcB5w7g3AN1I/Bh0k09Z/Y2QNIjwNbkNdHzzS7fwItfYNxOuhHnqMb7NwhjgVMj4rx87JHA+n0N7uNzuQv4mKTl8wxwgK2axtwBfFCSKrPJx5Jm1j+Yj/2cpHNJM8g3Au6KiBsxMzMzMzMzMzOrgWeS20BdS2q4fpYF17L+F2nJkvez4BrRxwHjJX1D0iaS9gI+Q5qhPCAR8RNSY/7CvI52X84irSF+vqSxkl4l6YOSmmehN0wGPi5pc0lbk2YlV5d02VvSvpJeI+lVpGVEZgP3S3qvpM9JGiNpPdJNMZchNYTrdCZp3e0/StpO0gaSxkk6QdIr85gfA4dJ2kXSZqQZ7y9pHCDPej8W+JGkvSRtKOn1kj6bP4/+TAY+kK9zS9Ls9cH+96Lxml/k9/qdpBu1QlqrnFzzusBPJG0m6f3AUcAPm5ZTOZM0I/6TtJhFblbCy1/+8naXYB3GmbISnCurmzNlJThXVoJzZXVzprqPm+Q2IHld6X8AKwNXVbY/X9l+ZWX7jcDuwB6kGeHfJN0c8tRBnvd44AjgIklv6WPMHOAdpJnMF5GWBTkM6GvG+r7AaqQZ12cAJ7DgLOjpwKdIa2PfAuwI7BwRT+Z9HwCuIM2CPhDYMyJuG8x1tZLXOH8raU3uc/O5fkVak7wxs/y4XP9pwHWk2dfnNR3qG8DRwFfzMS4hNZtb/d3QwaS10a8lzai/lBdnqA/0GmYCO5OWX7kZ+DYpBwDP5TEPAe8G3kS6UejJ+Tq/1XS4K0g3E92UgS83Y1ab559/vvUgs0FwpqwE58rq5kxZCc6VleBcWd2cqe6jBe+XZ2ZWjqSPAv8LrFq9IWtdJkyYsAow42fTZjOn5ei+nTa+eaUg63a33347o0ePbncZ1kGcKSvBubK6OVNWgnNlJThXVjdnqnP09PQwceJEgFXHjx/f65LG4DXJzawgSZ8A7gUeArYEvg+cU6JBbmZmZmZmZmZmNhRukpvVQNIo0o0y+zI6Ih5YXPUsQV5GWmLlZcAjwO+Ar7e1IrMh2GyzzdpdgnUYZ8pKcK6sbs6UleBcWQnOldXNmeo+XpPcrB4Pk9be7uvxcBtqaruIOCYi1o+IFSJig4j4Yl5v3Wypcu+997a7BOswzpSV4FxZ3ZwpK8G5shKcK6ubM9V9PJPcrAYRMQ+4u911mFkZc+Ysyir3ZgtzpqwE58rq5kxZCc6VleBcWd2cqe7jmeRmZmYtrLTSSu0uwTqMM2UlOFdWN2fKSnCurATnyurmTHUfN8nNzMxaWHvttdtdgnUYZ8pKcK6sbs6UleBcWQnOldXNmeo+Xm7FzDrOyeO2YdiwYe0uwzrIvffey+jRo9tdhnUQZ8pKcK6sbs6UleBcWQnOldXNmeo+nkluZmZmZmZmZmZmZl3LTXIzM7MW1llnnXaXYB3GmbISnCurmzNlJThXVoJzZXVzprqPm+RmZmYtzJs3r90lWIdxpqwE58rq5kxZCc6VleBcWd2cqe7jJrmZmVkLjz/+eLtLsA7jTFkJzpXVzZmyEpwrK8G5sro5U93HTXIzMzMzMzMzMzMz61qKiHbXYGZWiwkTJqwCzDh5Wg9zh3iM/x2/VZ0lWYeYN28eyy67bLvLsA7iTFkJzpXVzZmyEpwrK8G5sro5U52jp6eHiRMnAqw6fvz4mX2N80xyMzOzFh544IF2l2AdxpmyEpwrq5szZSU4V1aCc2V1c6a6j5vkZmZmLTz33HPtLsE6jDNlJThXVjdnykpwrqwE58rq5kx1HzfJzczMWhgxYkS7S7AO40xZCc6V1c2ZshKcKyvBubK6OVPdx01yMzOzFl7xile0uwTrMM6UleBcWd2cKSvBubISnCurmzPVfdwkNzMza+Huu+9udwnWYZwpK8G5sro5U1aCc2UlOFdWN2eq+7hJbmZmZmZmZmZmZmZdy01yMzOzFtZee+12l2AdxpmyEpwrq5szZSU4V1aCc2V1c6a6j5vk1naSQtIuS8pxuoWkqyQd32LMFElfWDwVDYykUyWd3+46zMzMzMzMzMysM7hJbr2SNC43nadJWqFp31Z5X9R0unWAi/Ox18/HHlPTsQdkUc7b7ua8pEckHda07Xu5rnFN26+SdEZ++gHgG4unSrOl23//+992l2AdxpmyEpwrq5szZSU4V1aCc2V1c6a6j5vk1srTwK5N2/YFHljUA0taDiAiHo2I5xf1eF3sKmBc07YdgKnV7fnLjm2AKwAi4qmIeHqxVGhmZmZmZmZmZraEcpPcWjkN+GTjiaQRwB55O5Xta0g6S9JDkmZJulXSnk1jrpJ0oqTjJT0BXJq3V2di35d/3pS3X5XHbCXpMklPSJoh6WpJrx/MhUhaTdKZkh6XNFvSZEn7LMp5JU3Jv56XXzclb19oSZB83VdVnn8ov0+zJT0p6XJJKw3mmrIrgbGSls3HXRl4HfB9FmyevxlYPo9faLkVSWtJuiDXc5+kjzafSNIoSX+U9IykmZLOkbR23reqpB5Jb8zPl5H0lKR/VF7/MUlTK8/XzceYnsf+UdL6lf3DJP0w739S0jGAhvAemS2SjTbaqN0lWIdxpqwE58rq5kxZCc6VleBcWd2cqe7jJrm1cgawnaRR+fkHgSnAjU3jVgD+DbwHeA3wC+AMSW9qGrcXMAcYCxzYy/ka43ckLcPygfx8ZVJjflvSbOjJwEW5ITxQRwOjgXcBmwOfBp5YxPNulX/uk1/XeN4vSesAZwG/zrWMA85laA3gK4GRlXNvB0wC/gBsXVkuZwdgSkRM6eM4pwLr5nEfAg4C1qrUvAzwR2B1YHvg7cCrgN8CRMQM4GZebMxvAQTwOkkj87btgavz8YaTvih5Otc8FngGuKTxVwbAIcDepC9qts3nbv7LhoXMm/0sc2e9+OiZO6fVS8z69dBDD7W7BOswzpSV4FxZ3ZwpK8G5shKcK6ubM9V9lm13AbbEe4y0XvjewDdJzcpfNw+KiIeAYyubfiLpncDuwL8q2ydHxJf7Od/j+eeTEfFo5fhXVAdJ2h+YTmq6XjjAaxkF3BQRN+TnUxb1vBHxuCSA6dXXDcA6pH9/50bE/XnbrYN4/XwRMVnSQ6Tm9HX559UR8aikB0gzyK/M26/s7RiSNiF9efCmiLg+b9sXuKMybDyp8b1BREzNYz4B3CZpq/y6q/J5js0/LwM2IzW4L8nbjsnH+zDpi7r9IiLy8fYhvb/jgL8AXwC+GxHn5v0HAu9s9Z785cCPMWvWrPnPN93tY2y2+8dbvcysT7Nnz253CdZhnCkrwbmyujlTVoJzZSU4V1Y3Z6r7uEluA/Fr4MeSfkNquO5Gmvk7n6RhwNdITfFXAMuRlvaYteCh+PdQCshLenyL1DxdCxgGrEhqfPc2/uJKjfdHxKuBnwF/yMul/AU4PyKurfO8gzARmADcKunSXM/vI2LaEI93Va7xu/nnD/L2q4FxecmTrYFT+nj95sA8Kp9PRNwpaXrTmKmNBnkec3seszlwfT7fvjkP2+frejTXcAuwUa4VYMv8/On8RUPDCsCGklYlfZnwz8r55km6gRYz7t9x8m+YU7mt7DLDh/c33KylFVZYofUgs0FwpqwE58rq5kxZCc6VleBcWd2cqe7jJrkNxMWk5VN+BVwQEU82NTUBvgR8njTz91bgWeB4UrO86tkh1nAasEY+x/3A86RZ083Hb9gPGJF/nwsQERdLWg94N2mpkAmSfhoRh9Z43oYXWLiRO79TGxE9kt4OvAV4B/BZ4NuSto6I+xi8K0lfZKxBWo/86rz9auAA4K+55it6f3lt/kpaoub1wFtJX5w8ChxG+mLg4YiYnMeOJDXlF1r7nBdn9g/JsiNWIloPMxuwUaMW9XsxswU5U1aCc2V1c6asBOfKSnCurG7OVPfxmuTWUkTMA04nzVBeaKmVbCzwx4j4TURMBO4FNhnC6RqLRw/r5fgnRMRFEXEbqVm9Zj81PxQRd+fH/ZXtj0fEaRHxMVJDf/8azju3l9c9TpoFXTWmqcaIiGsi4ghSY3sOA1hvuw9XAisBB5OWtHksb/8rab31d+XtfS2qdSfpS7M3NDZI2hR4SWXMHcC6ktatjBmdx9yer2k6cAvwGWBuRNyZa3gd8F5ebN5DWtd+Y+CxymfVeMzIa5w/QpoB3zjfAjWaLS6TJk1qdwnWYZwpK8G5sro5U1aCc2UlOFdWN2eq+7hJbgP1DeClpBst9mYy8HZJb5G0OfBzYO0hnOcxYDawk6S185IbjeN/XNLmkrYGzszjBkzSNyW9X9JGkl5Nato21txelPNOAcZLepmk1fK2K4A3SvqEpI0lHUW6oWmjlq0lfU3SG/NNUT9Aen/vYAgi4l7gAdKM9Ksr26cCD5O+DOh1PfI87i7SmuE/z7W9Afhl07VeTvorgTMlvT7flPV00vrnN1TGXUWaHX51PvZT+bo+zIJN8jNJN079o6TtJG0gaZykEyS9Mo/5MXCYpF0kbQacxIKNezMzMzMzMzMzs0XiJrkNSETMiYgnGjdY7MW3SDODLyU1SR8Fzh/CeeYBnyMtEfIw8Me8a19gtXyOM4ATSI3twZhDWrP7FtLs5h5gjxrOewhp+ZapwE35eJcCR5NuUnk9aQmS0yuvmUlajuQiYBLp/TskIi4e5DVVXZnPc1XT9qvz9j6b5Nk+pGu/GjiXtMTO/GvNn/37gWmk9+9y0l8MfLiX8w1rquOq5m0RMYv0HjyQz3cHaUmfFUjvD8BxpPf9NNIyN08D57W4DrPavfSlL213CdZhnCkrwbmyujlTVoJzZSU4V1Y3Z6r7qO+ep5nZ0mXChAmrADNOntaTFqIfgv8dv1WdJVmHmDZtGquttlrrgWYD5ExZCc6V1c2ZshKcKyvBubK6OVOdo6enh4kTJwKsOn78+Jl9jfNMcjMzsxYeeeSRdpdgHcaZshKcK6ubM2UlOFdWgnNldXOmus+y7S7AzBYk6Zl+dr8rIv622IoxMzMzMzMzMzPrcG6Smy15xvSz76HFVYSZvehVr3pVu0uwDuNMWQnOldXNmbISnCsrwbmyujlT3cfLrZgtYSLi7n4es9tdn1k3+u9//9vuEqzDOFNWgnNldXOmrATnykpwrqxuzlT3cZPczMyshWeffbbdJViHcaasBOfK6uZMWQnOlZXgXFndnKnu4ya5mZlZC8stt1y7S7AO40xZCc6V1c2ZshKcKyvBubK6OVPdRxHR7hrMzGoxYcKEVYAZW265JcOGDWt3OdZBXnjhBZZZxt8rW32cKSvBubK6OVNWgnNlJThXVjdnqnP09PQwceJEgFXHjx8/s69x/rTNzMxauPPOO9tdgnUYZ8pKcK6sbs6UleBcWQnOldXNmeo+bpKbmZmZmZmZmZmZWddyk9zMzKyFNdZYo90lWIdxpqwE58rq5kxZCc6VleBcWd2cqe7jJrmZmVkLyy+/fLtLsA7jTFkJzpXVzZmyEpwrK8G5sro5U93HTXIzM7MWHn744XaXYB3GmbISnCurmzNlJThXVoJzZXVzprrPsu0uwMysbgddfRtz0YDH//ptWxSsxszMzMzMzMzMlmSeSW5mZtbCBhts0O4SrMM4U1aCc2V1c6asBOfKSnCurG7OVPdxk9zMzKyFJ554ot0lWIdxpqwE58rq5kxZCc6VleBcWd2cqe7jJrmZmVkLTz/9dLtLsA7jTFkJzpXVzZmyEpwrK8G5sro5U93HTXIzM7MWll3Wt/CwejlTVoJzZXVzpqwE58pKcK6sbs5U93GT3MzMrIVNNtmk3SVYh3GmrATnyurmTFkJzpWV4FxZ3Zyp7uMmuZmZWQu33357u0uwDuNMWQnOldXNmbISnCsrwbmyujlT3cdNcjMzMzMzMzMzMzPrWm6S2xJH0pGSbm53HUsCSadKOn8xnWuspFslzZV0vqRxkkLSSwbw2pZj/bna0mz11VdvdwnWYZwpK8G5sro5U1aCc2UlOFdWN2eq+7hJvpSRNEzSF3Mz8zlJ0yRdLGlsu2sbitxY3aVp87HA+DaUM5+kKbm26uPBNpTyeWDvxXSuHwI3Axvkc14LrAPMqOn4bf9czYZqxRVXbHcJ1mGcKSvBubK6OVNWgnNlJThXVjdnqvu4Sb4UkSTgbOBw4MfA5sA4YCpwVS/N5qVSRDwTEU+2uw7S+7xO5fG6oRxE0nJDLSAiZkTE9KG+fpA2BK6IiAcjYnpEzImIRyMi6jj4EvS5mg3agw+24zsy62TOlJXgXFndnCkrwbmyEpwrq5sz1X3cJF+67A58CPhERPwyIu6LiIkRsT/wJ+CXklZqDJa0s6Tr84zzJySdV9m3vKTvS5oq6XlJd0vaN+/bW9L06okl7SIpKs+PlHSzpAPyMWZJOkfSqpUxW0m6LJ97hqSrJb2+sn9K/vW8PFN7SvXYlXHLSDpc0oO51psl7VTZv35+/QckXZlrmSjpzYv0bsPTuUnceDyeZ/L/StJ9kmZLukvS55veq1PzciVfl/QwcFelxt0l/S2/9npJm+T36QZJz+S/Cnhp87Eqz6+SdIKkYyQ9JelRSUc2nX8zSX/Pn/vtknbsY8b+Au8fsAbw6zx27+YlVCStJ+mC/NcLz0q6TdK7mw73hnwtsyRdK2nTynmaP9fG+3SopEckPSnpp5KGV8asI+nP+f26T9JH8iz/LwzsIzQzMzMzMzMzM+ufm+RLl48AkyLigl72HUdqcr4dQNJ7gPOAi0gzoMcD/6qMPx3YE/gcaUb6AcAzg6xnI1Ljfmdgp3yekyr7VwZOA7YFtgEmAxdJWjnv3yr/3Ic0U3srevd54BDgUOC1wKXAnyRt3DTu26QlPcYAk4CzJC07yGtqZRngQWA3YDTwTeA7knZvGjce2JT0eby3sv0o4FvA64F5wP8Bx5CucTvSe/rNFjXsBTwLbA18GThcUuNzHwacD8zK+/cnvS/9mUp6/2cCX8i//7aXcT8FlgfeCmwBfIWFM/Nt0mf1xnx9v25x7h1IM9h3yNe1NwsuL3M68HLSX0x8MF/PWi2OybzZs5g769n5j565c1q9xKxf6623XrtLsA7jTFkJzpXVzZmyEpwrK8G5sro5U92n7gailbUJcEcf++6ojAH4OnB2RBxRGTMRQNImpOb22yPi8rzv3iHUswJpVvtD+bifBf4s6ZA88/qK6mBJ+wPTge2BC/PMbIDpEfFoP+c5FPh+RJydn39F0g6khu7/q4w7NiL+nM91BHAbqel85xCuDeD7kr5Vef61iDgBqL6n9+UZ67sD51S2PwvsFxFzcj3rV2q8NG/7MXAWMD4irsnbfkXrNchviYij8u+TJX2G1JS/jNSU3xAY13hPJX097+tVRPQAj+bZ5DMqr2seOgr4Q0Tcmp/3lpmvR8TV+fXfI+VhhYh4ro/TTwM+k2u4U9Kf87WcImkzYEdgq4i4IR9zP9KXLf269IAPMWvWrPnPN91tbzb/8D6tXmbWp2nTprHSSiu1Hmg2QM6UleBcWd2cKSvBubISnCurmzPVfdwkX/os1LnswxjglH729QBXL2ItDzQa5Nl1pJnWm5KarmuTZk2PI83+HQasSGq2DoikVUgzia9p2nUNsGXTtlsqvz+Sf67F0JvkPwBOrTx/Itf0/4BPkq5jBLAc6YaXVbc2GuT91Pjfxtimba1mSt/S9PyRyms2BaY2felQ/QsCJF1MmrUOcH9EvLrF+RpOAH4m6R3A5aSGeXMtfX0GD/RxzNtyg7z6mi3y75uSZqPf2NgZEXdLmtaq0Hf+/PfMqaykvszw4X0PNhuAmTNntrsE6zDOlJXgXFndnCkrwbmyEpwrq5sz1X3cJF+6TCItjdKbzStjAGb3c5z+9gG8wMLN+KF0GU8jLQHzeeB+4HlSI33IN7JsYW7l90aLdFGWFHoiIu6ubpC0B2lJl0NI1/I08CXS0iZVzw6ixuZtrWqe2/R8IK+p2o/U3O/tWH2KiF9KuhR4D/AO4Kv5rwZ+0kdtA/kMFvVaerXsiBWJAX+fZNbasGHD2l2CdRhnykpwrqxuzpSV4FxZCc6V1c2Z6j5ek3zpcjawsaSde9l3CPAkLy6rcQtp2Yre3Er67LfvY//jwMqq3ASUNPu82ShJL68834bUYL8rPx8LnBARF0XEbaQm+ZpNx5hLmmHeq4iYCTycj1U1Fri9r9cVNBa4NiJOioibchN9wzbU0Ze7gHXzLP6GBdZ6j4iHIuLu/Lh/MAePiKkRcXJEfIC0Dv6nFr3kPt1F+iLvdY0NkjYCVit4TrNebbrppq0HmQ2CM2UlOFdWN2fKSnCurATnyurmTHUfN8mXLmeTbsZ5mqR9Ja0v6bWSfg68j7QGdmMG81HAnpKOkrS5pC0kfQUgIqaQZnn/WtIukjaQNK5y88l/km78+B1JG0r6CL2vk/1crmVLSduRluM4p7LUx2Tg4/n8WwNnsvAs9inAeEkvk9RX8/MHpHXIPyxp07zW9RjgxwN722o1GXijpHdK2kTS0fR9w9F2uAy4h/S5vFbSWNKSN/DizO4hkXR8vu4NJL2edLPNvtbIX2QRcSdpWZdfSHqTpNcBvyBlaJGuxWyw7rijWNStSzlTVoJzZXVzpqwE58pKcK6sbs5U93GTfCkSEUG6QeR3gC+SZtr+DViPdKPG8ytjrwJ2IzXPbwauAN5UOdyngd8DJ5HW7D4FWCm/9ingY8C7SbPO9wSO7KWku4FzgYuAv5Bmrx9U2b8vadbvjcAZpCb6Y03HOIR0s8mpwE19XPoJwA9JM5dvBXYC3hcRLW/gWMDPSdf8W9KXCWuQ3sMlQl7fexdgJHA98Evg23l3XzfPHKhhwE9JjfFLSEv7HNTvKxbdJ0jrtP+V9AXRKaQlbhb1WswGJf3n16w+zpSV4FxZ3ZwpK8G5shKcK6ubM9V95A/dhkLSkcAuETGmzaVYC3k2+d+BjSLinnbXsygkvZL0hcqOETGhef+ECRNWAWb8fPqyzB3EmuS/ftsWrQdZV3v44Yd5+ctf3nqg2QA5U1aCc2V1c6asBOfKSnCurG7OVOfo6elh4sSJAKuOHz++zzuy+sadZh1G0q7AM6SlYTYiLUtzzdLYIJf0NtKs+FuBdYBjSEv0/LWNZVkXWmWVVdpdgnUYZ8pKcK6sbs6UleBcWQnOldXNmeo+Xm7FOp6kiyU908fja+2ur4CVScui3AmcSlp25f3tLGgRDCctL3QbabmVx0lLC81ta1XWdR544IF2l2AdxpmyEpwrq5szZSU4V1aCc2V1c6a6j2eS25BExJH0vk75kmg/YEQf+55anIUsDhFxOnB6u+uoQ0RcClza7jrMzMzMzMzMzKxzuUluHS8iHmp3DWa2dFt33XXbXYJ1GGfKSnCurG7OlJXgXFkJzpXVzZnqPl5uxczMrIWnn3663SVYh3GmrATnyurmTFkJzpWV4FxZ3Zyp7uMmuZmZWQvTp09vdwnWYZwpK8G5sro5U1aCc2UlOFdWN2eq+3i5FTPrOCdt/2qGDRvW7jKsg0hqdwnWYZwpK8G5sro5U1aCc2UlOFdWN2eq+ygi2l2DmVktJkyYsAowY8stt3ST3MzMzMzMzMysy/X09DBx4kSAVcePHz+zr3FebsXMzKyFu+66q90lWIdxpqwE58rq5kxZCc6VleBcWd2cqe7jJrmZmVkLPT097S7BOowzZSU4V1Y3Z8pKcK6sBOfK6uZMdR83yc3MzFpYZZVV2l2CdRhnykpwrqxuzpSV4FxZCc6V1c2Z6j5ukpuZmbWw+uqrt7sE6zDOlJXgXFndnCkrwbmyEpwrq5sz1X2WbXcBZmZ1+8zV9zKX3u9E/cu3bbSYq7FOMGXKFEaPHt3uMqyDOFNWgnNldXOmrATnykpwrqxuzlT38UxyMzMzMzMzMzMzM+tabpKbmZm18IpXvKLdJViHcaasBOfK6uZMWQnOlZXgXFndnKnu4ya5mZlZC7Nnz253CdZhnCkrwbmyujlTVoJzZSU4V1Y3Z6r7uEluZmbWwlNPPdXuEqzDOFNWgnNldXOmrATnykpwrqxuzlT3cZPczMzMzMzMzMzMzLqWm+RmZmYtbL755u0uwTqMM2UlOFdWN2fKSnCurATnyurmTHUfN8nNzMxauPvuu9tdgnUYZ8pKcK6sbs6UleBcWQnOldXNmeo+bpJnkkLSLkvKcWxwJO0taXoNx/Hn1wdJUyR9od11mLXD3Llz212CdRhnykpwrqxuzpSV4FxZCc6V1c2Z6j5LdJNc0rjctJwmaYWmfVvlfVHT6dYBLs7HXj8fe0xNxx6QRTlvu5u7ldp7JL2iad86kubl/esXKuG3wCaFjm1LCEmnSjq/3XVY9xk5cmS7S7AO40xZCc6V1c2ZshKcKyvBubK6OVPdZ4luklc8DezatG1f4IFFPbCk5QAi4tGIeH5Rj2c8BHyiadteefsiaXxWvWwfHhGzI+KxRT2HmVlvXvrSl7a7BOswzpSV4FxZ3ZwpK8G5shKcK6ubM9V9lpYm+WnAJxtPJI0A9sjbqWxfQ9JZkh6SNEvSrZL2bBpzlaQTJR0v6Qng0ry9OhP7vvzzprz9qjxmK0mXSXpC0gxJV0t6/WAuRNJqks6U9Lik2ZImS9pnUc4raUr+9bz8uil5+0KzbvN1X1V5/qH8Ps2W9KSkyyWtNJhranIasE/Ttn1Y+LMaJulXku7L575L0uebxpwq6XxJX5f0MHBXZcb6h/P78Bzw0d6WW5H0fkk3SnpO0r2SjpC0bGX/xpL+mvffLuntrS6uv8+vUtsekq7Nx/2PpO2bjrG9pH9Jel7SI5K+11TXQsuaSLpZ0pH5d0k6UtID+RgPSzqhMnZ5ScfmfwfPSvqnpHEtrmtDSX+U9F9Jz0i6XtKOvQxdOf8bezYf//9VjrFIdTU+Q0nvlHRHruMSSevk/UeSvnB5f36fo9V1mdXlvvvuaz3IbBCcKSvBubK6OVNWgnNlJThXVjdnqvssLU3yM4DtJI3Kzz8ITAFubBq3AvBv4D3Aa4BfAGdIelPTuL2AOcBY4MBeztcYvyNpGZYP5Ocrk5q92wLbAJOBiyStPIhrORoYDbwL2Bz4NPDEIp53q/xzn/y6xvN+5ebjWcCvcy3jgHMBDeJ6mv0JWE3Stvkc2wKrARc0jVsGeBDYjfR+fBP4jqTdm8aNBzYF3g68t7L9e8CPc92XNhchaTvg9DxmNHAAsDfw9bx/GdK1zgG2JuXg+wO4vv4+v4YfAMcBrwOuAy6QtEY+7yuAi4DrgS3z6/cF/mcA5274IPDFfE0bA7sAt1b2nwi8mfRF0muB3wGXSNq4n2OOzHWNz3Vfkuse1TTuS8DEPOZ7wI8rXy7UUdeKwKHAx4G3AqOAY/O+Y4Fzcm3r5Me1vV3MvNnPMHfWi4+euXP6uXQzMzMzMzMzM+tmy7YeskR4jLRe+N6kZuonSY3dBUTEQ7zYUAP4iaR3ArsD/6psnxwRX+7nfI/nn09GxKOV419RHSRpf2A6sD1w4QCvZRRwU0TckJ9PWdTzRsTjkgCmV183AOuQMnBuRNyft93az/iBmAv8hvQZ/T3//E3ePl9EzAWOqGy6T9KbSZ/VOZXtzwL7RcQcSLO18/bjI+LcxqB8/VVHAN+LiMYM9nslfQM4BjiK9EXEZsA7I+LhfIyvkdel70d/n1/DiRHxh3zMTwM7kRrhxwAHAVOBz0REAHdKejnwfUnfjIgXWpy/UcOjwOX5fXyAnO/c1N4HGNW4LuBYSTvl7V/r7YARMZHU/G74hqRdgfeRmtsN10TE9/LvkySNJTXGL6upruHAgRFxT37dicDhucZnJM0Glm+V84sP2JlZs2bNf77Zbvsx+sP79/cSs369/OUvb3cJ1mGcKSvBubK6OVNWgnNlJThXVjdnqvssLU1ySE3xH0v6DWk26m7AdtUBkoaRmm27A68AlgOWB2YteCj+PZQCJK0NfIs043otYBhp5mvzbNvG+IsrNd4fEa8Gfgb8QWm5lL8A50dEr7Nhh3reQZgITABulXRpruf3ETFtEY/7a+Da3HTejfR5LZS1vFTHJ0nXMYL0ed3cNOzWRoO8yQ29bKvaEhgr6euVbcOAFSStSJoFPrXSsIU067ta31A/v/nHiYh5km7I5yP/vC43yBuuIc3kfiUDW2f/d8AXSI3/S0gzwC+IiHnAFvk6JzV9cbA88GS+rmcq238TEQdKGgkcSforjMaXJyNYOGPX9fL8C3XUlc1qNMizR0iZH5R3/fwC5sSL51lmeK/L2ZsN2Jw5/msEq5czZSU4V1Y3Z8pKcK6sBOfK6uZMdZ+lqUl+MWn5lF+RGm9P9jJ7+EvA50mNultJs5CPJzVfq54dYg2nAWvkc9wPPE9qEvbVgduP1GiEPJM6Ii6WtB7wbtISIhMk/TQiDq3xvA0vsPDSKcMbv0RET14q4y3AO4DPAt+WtHVEDHnxpYi4VdKdpKVc7oiI/0gaUx0jaQ/SrP9D8rU8Tfr8tm46XF+fVavPcCRpNvm5vex7rsVrG+r6/Aar1ec2VdKmpNnwbwdOAr6ktPb5SKAHeEP+WdVojo+pbJuZfx6bj3UocDcwG/g9rTM2Xw11QdNfHADBEJb/WXbESGKRVg0yW9ATTzzBWmsN+vsasz45U1aCc2V1c6asBOfKSnCurG7OVPdZaprkeUbu6cCXSetB92Ys8MeI+A3MX3d6E+D2QZ6u8XXRsF6Of1BEXJSPvy6wZj81P9TH9sdJje/TJP2NtIb1oYt43rm9vO5x0trsVWOoNCLzjOZrgGskfZPUhN8V+GFf1zVAvyY1ST/dx/6xwLURcVJjg6QNF/GcVTcCm0bE3b3tlHQHsK6kdSLikbx5m+qYIXx+DdsAf83nWZbUGG4sWXIH8EFJqswmH0v6kuDB/Pxx0mzuRq2rABs01TCbtM77BZJ+CtxJmq19EykHa0XE3/qov7f3ZCxwakScl885Eli/l3Hb9PL8jjrqGqA5LJxzMzMzMzMzMzOzIVtqmuTZN0gNySf72D8Z+JCktwDTgIOBtRl8k/wx0kzanSQ9CDwXETPy8T+el89YJdcyezAHzo3ofwO3kZaaeC8vNhkX5bxTgPGSrgGez0umXEGayfsJ0mztj5Ga5jflWrYm3ajxL/ncWwMvrdSzKE4hLb8xvY/9k4FP5DXj7yPdqHGr/HsdvglcKOkB0ozoF0hLsLwmIv4HuByYRGp0f4n0vn671UFbfH4N/0/S5Lz9i6QblzbW0D+J9JcOP8nrbW9KWiP9h5X1yK8A9pZ0Aen9+yaV2deS9iY1iv9JWkroY6Q83J//wuJM4HRJh5A+65eSPudbIuLPfVzaZOAD+ZxBukFpbzf2HSvpy8D5pNniu5GWaClVV7MpwDvzjPUngRl5/XOzojbddNN2l2AdxpmyEpwrq5szZSU4V1aCc2V1c6a6T29NsCVWRMyJiCea1nOu+hZpBvGlwFWkmwieP4TzzAM+BxwAPAz8Me/al9TwvBE4AziB1FwejDnAd4FbSLONe4A9ajjvIaSm5VRyEzwiLiU1O48BrgdWBk6vvGYm8FbS2tGTSO/fIRHR6uaVLUXEvPxZzetjyM9JS6H8ltRUXYPUQK5Fvvb3kpaRuR74B6lhfX/e/wJpxvwI0s0lfwl8vdeDLajPz6/isPyYCGwLvC8insjnfYi0VMub8v6TSUsIfavy+u8CV5NuBvtnUoar63RPBz5F+guAW0jLm+wcEY0vj/Yhfc7HAXfl129F/+udH0z6Yula0kzwS0l5a3Yc8EZSxv4HODi/16XqanZKfu0NpBn3YwfxWrMhmzJlSrtLsA7jTFkJzpXVzZmyEpwrK8G5sro5U91HffebzWwwJK1Pmgn/uoi4ub3VdKcJEyasAsw4ZfrKzO1jTfJfvm2jxVuUdYTbb7+d0aNHt7sM6yDOlJXgXFndnCkrwbmyEpwrq5sz1Tl6enqYOHEiwKrjx4+f2de4pWomuZmZWTustNJK7S7BOowzZSU4V1Y3Z8pKcK6sBOfK6uZMdZ+lbU1yW0wkPdPP7nct4s0XzcyWKi972cvaXYJ1GGfKSnCurG7OlJXgXFkJzpXVzZnqPp5Jbn0Z08/jhnYUtKSLiCkRIS+1YtZ57rnnntaDzAbBmbISnCurmzNlJThXVoJzZXVzprqPZ5JbryLi7nbXYGZmZmZmZmZmZlaaZ5KbmZm14D+1s7o5U1aCc2V1c6asBOfKSnCurG7OVPdxk9zMzKyFF154od0lWIdxpqwE58rq5kxZCc6VleBcWd2cqe7j5VbMrOOcuP2rGDZsWLvLsA7y2GOPseaaa7a7DOsgzpSV4FxZ3ZwpK8G5shKcK6ubM9V9PJPczMzMzMzMzMzMzLqWm+RmZmYtbLzxxu0uwTqMM2UlOFdWN2fKSnCurATnyurmTHUfN8nNzMxamDp1artLsA7jTFkJzpXVzZmyEpwrK8G5sro5U93HTXIzM7MWnnvuuXaXYB3GmbISnCurmzNlJThXVoJzZXVzprqPm+RmZmYtjBgxot0lWIdxpqwE58rq5kxZCc6VleBcWd2cqe7jJrmZmVkLr3zlK9tdgnUYZ8pKcK6sbs6UleBcWQnOldXNmeo+bpKbWcf53NWPsP8VDy/wMFsUkydPbncJ1mGcKSvBubK6OVNWgnNlJThXVjdnqvu4SW5mZmZmZmZmZmZmXctNcjMzsxbWWmutdpdgHcaZshKcK6ubM2UlOFdWgnNldXOmuo+b5GZmZi1IancJ1mGcKSvBubK6OVNWgnNlJThXVjdnqvu4SW5mZtbCf//733aXYB3GmbISnCurmzNlJThXVoJzZXVzprqPm+RmZmZmZmZmZmZm1rXcJDczM2thww03bHcJ1mGcKSvBubK6OVNWgnNlJThXVjdnqvu4SW5mZtbCI4880u4SrMM4U1aCc2V1c6asBOfKSnCurG7OVPdxk9yWSJKOlHRzu+sYLEnrSwpJYxbhGEvltZt1slmzZrW7BOswzpSV4FxZ3ZwpK8G5shKcK6ubM9V93CRfCkkaJumLkm6V9JykaZIuljS23bUNRW4q79K0+VhgfBvKmU/SlFxbSHpW0o2SdmvxsqnAOsB/FkOJZraYLL/88u0uwTqMM2UlOFdWN2fKSnCurATnyurmTHUfN8mXMpIEnA0cDvwY2BwYR2rOXtVLs3mpFBHPRMST7a6D9D6vA7wOuB74raS39DZQ0nIR0RMRj0bEvMVZZCfKXwb5v1G2RFhvvfXaXYJ1GGfKSnCurG7OlJXgXFkJzpXVzZnqPm5ALX12Bz4EfCIifhkR90XExIjYH/gT8EtJKzUGS9pZ0vV5xvkTks6r7Fte0vclTZX0vKS7Je2b9+0taXr1xJJ2kRSV50dKulnSAfkYsySdI2nVypitJF2Wzz1D0tWSXl/ZPyX/el6esT2leuzKuGUkHS7pwVzrzZJ2quxvLHPyAUlX5lomSnrzIr3b8HRuek8C/h8wG9i5Ubukb0g6XdJM4BfV5VZyzQ9K+nTT+/g6SS9I6ve/uJI+ns8xQ9LZklau7Fte0gmSHsuf7d8lbVXZP5DPb8v8Xj0taaakf0t6Y2X/tpL+Jml2/nxPqGarl3qVP7cH8mf0sKQTmmo+VtJDeWb+PyWNa65Z0vsk3Q48D+yXr+8lTef6saQr+qpl7uxnmTvrmfmPnrlz+hpqNiCTJk1qdwnWYZwpK8G5sro5U1aCc2UlOFdWN2eq+7hJvvT5CDApIi7oZd9xwBrA2wEkvQc4D7iINBN6PPCvyvjTgT2Bz5FmpB8APDPIejYiNe53BnbK5zmpsn9l4DRgW2AbYDJwUaXh22js7kOasb0Vvfs8cAhwKPBa4FLgT5I2bhr3bdJSLWOAScBZkpYd5DX1Ks8OnwssV9l8KDCRdN1HN41/ATiL9JlVfRS4JiLu7+d0GwK7AO/Nj+2Bwyr7jwE+COwFvB64G7hU0uqDuKQzgQdJ7/kbgO+Rrg9JGwKXAH8gvd8fJn2GJ/ZzvA8CXyTlaONc/62V/ScCbwb2yMf8HXBJ02e4IvAVYD/g1bnG6fnY5NqG5XrO7KuQiw4Yzx8/sc38x53nntJP2WZmZmZmZmZm1s1qaR7aYrUJcEcf++6ojAH4OnB2RBxRGTMRQNImpOb22yPi8rzv3iHUswJpVvtD+bifBf4s6ZA8A3uB2b6S9ic1PbcHLoyIxyUBTI+IR/s5z6HA9yPi7Pz8K5J2AL5AmuHdcGxE/Dmf6wjgNlIj/84hXFu17uVITfpVgeo1XRERx1XGrd/00jOBQySNiogHlJYP2QP4VotTLgPsHRFP5+OeQfqS4+t5Nven8/6L8/5Pkb4c2Rf4wQAvaxTwg4hovDeTK/u+CpwZEcc39kn6HHC1pE9HxHN9HO9R4PKImAs8QP5SRtIo0hchoyLi4Tz+2PzXAPsAX8vbhgMHRcTExkElnU36ouFXedN44CWkBn6v3v3zCcwNzX++zPDl+hpqNiAvfelL212CdRhnykpwrqxuzpSV4FxZCc6V1c2Z6j6eSb50UushQJpNPaGffT3A1YtYywONBnl2HSlXmwJIWlvSKZImS5oBzARGkhqqAyJpFeDlwDVNu64hzYCvuqXy+yP551oDPVcvvi/pGWAWaYbzYY0mfHZDfy+OiJtJX140ZpNvn+v5HYCkZyqPkysvndJokGePVK5jQ1Izef77kZvS/2Lh96M/PyQtz3O5pMPy7PGGLYG9q/WRZu8vA2wg6WtNtY/K1zQCuDd/5rtWZvFvAQwDJjUdc/t8PQ1zWPAzhPRFwzhJL8/PPwr8OSKm93Vhw0esxPAVR85/DHOT3BbRssv6O2WrlzNlJThXVjdnykpwrqwE58rq5kx1HzfJlz6T6LsRunllDKT1s/vS3z6AF1i4GT+8xWt6cxqpIf954C359ydZcMmSOs2t/N5Yf3tRcv4DUs2vBFaLiO837X92AMc4kxeb5B8BLqnclHRM5XF45TXV64B0LYO5jpafX0QcSVrS5M/A24DbJe2ad48Eft5U35akZVTuAU5u2vdwREwlfTlyEClfJwF/lTQ8H6+HtKxL9XWbk7LRMDsiovKciLg+n3MPSSOAXelnqRWzEh555JHWg8wGwZmyEpwrq5szZSU4V1aCc2V1c6a6j5vkS5+zgY0l7dzLvkNIDejL8vNbSEtT9OZW0ue/fR/7HwdWbrpR45hexo2qzPCFtO74C8Bd+flY4ISIuCgibiPdjHHNpmPMJc0y7lVEzAQezseqGgvc3tfravJERNydl46J1sN79X/AayS9gXTT1fkN3nzsxuOxAR7vHtKM6/nvR25Eb8WL78eAPr+ImBQRP4qIdwDnkpY+AbgRGN1UX+MxJyKeato2Lx9vdkRcEBGfA8aR1iDfAriJ9Bmv1cvx+ltmp+FM0gzynUn5+nP/w83MzMzMzMzMzAbGTfKlz9mkm3GeJmlfSetLeq2knwPvA/aLiMbs5qOAPSUdJWlzSVtI+gpAREwhzfL+taRdJG0gaZyk3fNr/0laYuQ7kjaU9BFg717qeS7XsqWk7YATgHMqjc/JwMfz+bcmNTubZ7FPAcZLepmk1fq47h+Q1iH/sKRNJX2P1PT98cDetvbJ7/W1pDW1hwF/WsTjPQv8DPiBpJ0kjQZOId30srFud7+fn6QRkk7Mn/l6ksaSmuyNde2/D7wljxkjaWNJ75fU5407Je2dM/kaSa8CPkb6rO+PiEmkz/50SR/IeXuTpK/mG8y2cibpBqVfB34fEc8P8O0yq8WrXvWqdpdgHcaZshKcK6ubM2UlOFdWgnNldXOmuo+b5EuZPJt5d+A7wBdJM7b/BqwHjIuI8ytjrwJ2IzXPbybdcPJNlcN9Gvg9aVmMO0mN1pXya58iNTnfTZp1vidwZC8l3U2agXwR8BfS7PWDKvv3BVYjzUw+g9REb54xfQjpppNTSTOOe3MCaQ3t43I9OwHvi4jJfYxf0pxJWq7kvIhotdTNQBxGunHlGaT3diPgnRExDQb0+fUAawCnk5bnOQe4GDgiv/4W0l8ZbELK103AN0kz+vsyHfgUaa30W4AdgZ0rS8vsk893HCm355Ma8w+0utiIuJu05vpr8VIr1gaPPTbQP/QwGxhnykpwrqxuzpSV4FxZCc6V1c2Z6j4a+goS1u0kHQnsEhFj2lyKGQATJkxYBZjxq+lrMbfpO8BfvO3lvb/IbABuv/12Ro8e3e4yrIM4U1aCc2V1c6asBOfKSnCurG7OVOfo6elh4sSJAKuOHz9+Zl/jPJPczMysheWWK3WvYetWzpSV4FxZ3ZwpK8G5shKcK6ubM9V93CS3riDpYknP9PH4WrvrM7Mlm9ejs7o5U1aCc2V1c6asBOfKSnCurG7OVPdxk9yGLCKOXIqWWtmPdKPP3h4nt6UiM1tq3Hnnne0uwTqMM2UlOFdWN2fKSnCurATnyurmTHWfZdtdgNniEBEPtbsGMzMzMzMzMzMzW/J4JrmZmVkLa6yxRrtLsA7jTFkJzpXVzZmyEpwrK8G5sro5U93HM8nNrOOcsP06DBs2rN1lWAdZYYUV2l2CdRhnykpwrqxuzpSV4FxZCc6V1c2Z6j6eSW5mZtbCQw95xSarlzNlJThXVjdnykpwrqwE58rq5kx1HzfJzczMzMzMzMzMzKxruUluZmbWwvrrr9/uEqzDOFNWgnNldXOmrATnykpwrqxuzlT3cZPczMyshaeeeqrdJViHcaasBOfK6uZMWQnOlZXgXFndnKnu4ya5mZlZCzNnzmx3CdZhnCkrwbmyujlTVoJzZSU4V1Y3Z6r7uEluZmbWwrLLLtvuEqzDOFNWgnNldXOmrATnykpwrqxuzlT3UUS0uwYzs1pMmDBhFWDG2TNexVyGLbDvRzus3J6izMzMzMzMzMysLXp6epg4cSLAquPHj+/zTwQ8k9zMzKyF22+/vd0lWIdxpqwE58rq5kxZCc6VleBcWd2cqe7jJrmZmZmZmZmZmZmZdS03yc3MzFpYbbXV2l2CdRhnykpwrqxuzpSV4FxZCc6V1c2Z6j5ukpuZmbUwcuTIdpdgHcaZshKcK6ubM2UlOFdWgnNldXOmuo+b5GZmZi1MnTq13SVYh3GmrATnyurmTFkJzpWV4FxZ3Zyp7uMmuZmZmZmZmZmZmZl1LTfJzczMWhg1alS7S7AO40xZCc6V1c2ZshKcKyvBubK6OVPdx01ysyWEpCmSvtDuOsxsYTNmzGh3CdZhnCkrwbmyujlTVoJzZSU4V1Y3Z6r7uEluNgCSxkkKSbdJGta0b7qkvQdxrL0lTe9l11bALxat0qWDpKskHd/uOswGyv8HyermTFkJzpXVzZmyEpwrK8G5sro5U93HTXKzwXkV8IkSB46IxyNiVoljL42ULNvuOswAllnG/3Np9XKmrATnyurmTFkJzpWV4FxZ3Zyp7uNP3GxwfgIcJWn5vgZIOljSrZKelTRV0kmSRuZ944D/BVbNM9ND0pF53/zlViT9n6TfNh13uKQnJH0iP19G0lcl3SdptqSJkj7U6gIkjc0zuWdJmibpUkmr5X3LSzpB0mOSnpP0d0lbVV670Cx4SbtIisrzIyXdLOnj+ZpmSDpb0sp5/6nA9sDnK+/B+pXZ+u+S9G/geeBjkl6Q9Mamc35B0v2S/N8wWyw222yzdpdgHcaZshKcK6ubM2UlOFdWgnNldXOmuo8bTGaDczywLPDZfsa8AHwOeDWwF/A24Ji871rgC8BMYJ38OLaXY5wJ7NxormfvBFYEzsvPv0qa1X5gPtePgN9I2r6vwiSNASYAtwNvBrYFLgAaS8gcA3ww1/164G7gUkmr93O9vdkQ2AV4b35sDxyW930euA44hRffg6mV134vj90c+BNwObBP0/H3AU6NiBd6O/mc2c8wZ9bT8x89c58fZPlmC7rzzjvbXYJ1GGfKSnCurG7OlJXgXFkJzpXVzZnqPl7KwGxwZgFHAd+RdEpELLRIVUQcX3k6RdL/ACcDB0XEHEkz0rB4tJ/zXAo8C+wKnJG3fQT4U0Q8nWeyfw3YMSKuy/vvlbQtcABwdR/H/TJwQ0QcVNl2G4CklYBPA3tHxMV526eAtwP7Aj/op95my+TjPJ2PcwYwHvh6RMyQNAeYVX0PJDV+PTwiLqts/yVwsqSDI+J5Sa8HtgDe39fJf7//Nsya9eLKNVvu/gV4x+GDKN9sQS+80Ov3MWZD5kxZCc6V1c2ZshKcKyvBubK6OVPdx01ys8H7FXAI8BVSo3oBknYkzfLeDFiF9O9sBUkrDnTN8YiYJ+kc4KPAGbmB/X5gjzxkI9Ks8ssqzWWA5YCbch23Aevl7X+LiHcBY4Df9XHaDYHhwDWVOuZK+hdpVvdgTGk0yLNHgLUG+Nobmp6fD/yU9IXB2cDewJURMaWvA3zoF/9gbrz4hzLDhi83wFOb9W7VVVdtdwnWYZwpK8G5sro5U1aCc2UlOFdWN2eq+7hJbjZIuYH9deBUSSdW90laH7gQ+BnwdeAp0pImvyI1sAdzY84zgaslrUWazT0buCTvayzD8h7goabXNdYWeTep6U1+bfXnUL0AqGnb8F7GzW16Hgx8eadnF3hhmn1/OrCPpHNJM+o/398BlhsxEs1fQcZs0fn/IFndnCkrwbmyujlTVoJzZSU4V1Y3Z6r7eE1ysyGIiN+Rlik5omnXG0j/rg6JiH9ExCTg5U1j5kDrDm5EXEtaq/vDpBnlv4uIRvP5dlIzfFRE3N30mJpff39lW6ORfgtp2ZPe3JNrG9vYIGk4sFU+H8DjwMp5ZnvDmFbX0osBvQcVvwR2BA4ifbl37hDOaTZkDzzwQLtLsA7jTFkJzpXVzZmyEpwrK8G5sro5U93HM8nNhu4w0trhVXeTZlZ/VtIFpIbzgU1jpgAjJY0HJpLW5u5rhvn/5ddvAuzQ2JjXJT8W+JGkZYC/A6vm882MiNP6ON53gVslnURaJ31OPu7vIuIJST8DfiDpKeAB0hrmK5JmwgP8kzQb/juSTgC2Ji1/MlhTgK3zzPtnSDPu+xQRd0j6B/B94NcRsagz4s3MzMzMzMzMzADPJDcbsoi4AriCypdNETEROJi0Xvl/SDPAv9r0umtJDerfkmZmf7mf05wJjCYtqXJN075vAEfn499BWorlPcB9/dQ8CXgHsCXwL+A60lrn8/KQw4A/kG4WeiNp7fN3RsS0/PqngI+RlnK5FdgTOLKf+vtyLNBDmqH+ODBqAK9pLFnz6yGcz2yRrLvuuu0uwTqMM2UlOFdWN2fKSnCurATnyurmTHUfRUS7azAza0nSN4DdIuK1fY2ZMGHCKsCMs2e8irlNq7n8aIeVC1doneyRRx5hnXXWaXcZ1kGcKSvBubK6OVNWgnNlJThXVjdnqnP09PQwceJEgFXHjx8/s69xnkluZks0SSMlvQb4DPCTdtdj3WnatGntLsE6jDNlJThXVjdnykpwrqwE58rq5kx1HzfJzWxJdyLwb+AqvNSKmZmZmZmZmZnVzMutmFnH8HIrZmZmZmZmZmbW4OVWzMzMajJp0qR2l2AdxpmyEpwrq5szZSU4V1aCc2V1c6a6j5vkZmZmLcybN6/dJViHcaasBOfK6uZMWQnOlZXgXFndnKnus2y7CzAzq9t337oyw4YNaz3QbIBWWWWVdpdgHcaZshKcK6ubM2UlOFdWgnNldXOmuo9nkpuZmbWw+uqrt7sE6zDOlJXgXFndnCkrwbmyEpwrq5sz1X3cJDczM2thypQp7S7BOowzZSU4V1Y3Z8pKcK6sBOfK6uZMdR83yc3MzMzMzMzMzMysa7lJbmZm1sIrXvGKdpdgHcaZshKcK6ubM2UlOFdWgnNldXOmuo+b5GZmZi0899xz7S7BOowzZSU4V1Y3Z8pKcK6sBOfK6uZMdR83yc3MzFp48skn212CdRhnykpwrqxuzpSV4FxZCc6V1c2Z6j7LtrsAM7O6nfy32fQwbP7zz40b0cZqzMzMzMzMzMxsSeaZ5GZmZi1sttlm7S7BOowzZSU4V1Y3Z8pKcK6sBOfK6uZMdR83yc3MzFq49957212CdRhnykpwrqxuzpSV4FxZCc6V1c2Z6j5ukpuZmbUwZ86cdpdgHcaZshKcK6ubM2UlOFdWgnNldXOmuo+b5GZmZi2MHDmy3SVYh3GmrATnyurmTFkJzpWV4FxZ3Zyp7uMmuZmZWQtrrbVWu0uwDuNMWQnOldXNmbISnCsrwbmyujlT3cdNcjMzsxa8Hp3VzZmyEpwrq5szZSU4V1aCc2V1c6a6j5vkZmZmZmZmZmZmZta13CS3jiFpfUkhaUyNxzxS0s11Ha9TlHivzZZk66yzTrtLsA7jTFkJzpXVzZmyEpwrK8G5sro5U93HTXIrRtJISXMl7dG0/ezcYF2/afsUSUcv1iKXUpLG5ffwJe2uxawbzJs3r90lWIdxpqwE58rq5kxZCc6VleBcWd2cqe7jJrkVExHPADcA45p2jQOmVrdL2gBYD7hiKOeStNxQXmdmNhCPP/54u0uwDuNMWQnOldXNmbISnCsrwbmyujlT3cdNcivtShZshm8OrAD8jAWb5+OA54Hr8rgPSrpN0vN5hvkh1YPmbd+QdLqkmcAvmk8saZikX0u6U9KovgqU9EpJZ0l6StKzkm6QtHUfY7eSdJmkJyTNkHS1pNdX9isv0fJArv1hSSdU9h8kabKk5yT9V9Lv+3nvhkzSavm9mSZplqSLJW3cNGaspKvy/mmSLpW0Wt63k6S/S5ou6UlJF0racAh1fErS1HyO8yQdLGl605hPS7pH0hxJd0n6eGXf/0n6bdP44fn9/8Rg6zEzMzMzMzMzM2vmJrmVdiWwqaTGYk47AH8nzRgfVxm3A3BdRDwn6Q3AOcDZwBbAkcDRkvZuOvahwETgdcACy7RIWh74HTAG2C4iHuitOEkjgauBVwDvA7YEjqHvfxsrA6cB2wLbAJOBiyStnPd/EPgicACwMbALcGs+1xuBE4DDgU2BnYC/9nGeRXUq8EbSNb0ZUK5zeK5lDDABuD3v3xa4ABiWX78S8MN8jPHAC8B5kgb83wxJY4GTgR+TPofLgK83jdk17z8OeA3wc+B/Je2Qh5wJ7Jw/p4Z3AisC5/V17udmP8Nzs56e/3j++ecHWrZZrzbZZJN2l2AdxpmyEpwrq5szZSU4V1aCc2V1c6a6z7LtLsA63jXAHFJD/Kz882rg38CakjaIiPuA7YFf5dccDEyIiEbje5Kk0cCXSM3fhisi4rjGk8oa5yOBPwPLAztExIx+6vsI8FJgq4h4Km+7u6/BEbHAcjCS9gem5/ovBEYBjwKXR8Rc4AHgX3n4KOBZ4MKIeBq4H7ipn9qGJM8Yfx8wNiKuzds+SlriZhfSlwdfBm6IiIMqL72t8UtE/KHpmJ8EHgdGA/8ZYCmfBS6OiGPz80mS3gK8tzLmUODUiDgpP/+hpG3y9iuBS0nv2a7AGXnMR4A/5fewVz/61BuZNWvW/OcvfPnLHHbYYQMs22xh999/PxtuOOg/pjDrkzNlJThXVjdnykpwrqwE58rq5kx1H88kt6IiYhZwPS/OGt8euCoi5gHXAuMkvYrUQL4yj9mc1FyvugbYWNKwyrYb+jjtWaSZ0O+oNsglnSzpmcYjbx4D3FRpkPdL0tqSTslLpswAZpKa8o3lXH4HjADuzeN2ldT4MuoyUmP8XklnSPqopBUHct5B2hyYB/yzsSEingTuyvsgXfeEvg4gaeO8BM29eTmbKXlXr8vW5KVxGu/txXnzprz4BUFD8/O+PuvNc93zSH9V8NF8npWA95NmmPfpi6fcwGG/uXP+44tf/GJ/w81a8l8jWN2cKSvBubK6OVNWgnNlJThXVjdnqvt4JrktDlcCH5b0alID+ca8/WrSMivLALOoNHUH6Nk+tl8EfIy0jEh15vfhwLFNY2cP8pynAWsAnyc1vBvrqC8HEBFTJW0K7Ai8HTgJ+JKk7SPi6bx++TjgHcA3gSMlbRUR0wdZx6Jqdd0XkK7vU8DDpM/oP+Tr7MW7geEDPPZgnQlcLWkt0ns6G7ikvxesMGIkPbz4fcryyy9fc0nWbVZcscT3WdbNnCkrwbmyujlTVoJzZSU4V1Y3Z6r7eCa5LQ5Xktbn/gjw94joydv/SppZPg64JiLm5O13AGObjjEWmFR5bX9+BhwG/EnS9o2NEfFYRNzdeOTNtwBjJK0+wGsZC5wQERdFxG2kJvma1QERMTsiLoiIz+VrezNpbXUiYl5EXB4RXwZeC6wPvG2A5x6oO0hfgM2/+aikNUgzu2/Pm24hrTW+kMrYb0XEhIi4A1itvxNGxP2V9/ahvPkuYKumoc3P+/qsG3WSl4yZCnyYNKP8d3kpG7PFZp111mk9yGwQnCkrwbmyujlTVoJzZSU4V1Y3Z6r7uElui8O1pGbyZ0mzxxv+BaxFWj7jysr244Dxkr4haRNJewGfYeFZ4H2KiJ8A/wNcKGnbfoaeRVpD/HxJYyW9StIHJb25j/GTgY9L2lzS1qRZzvNnTkvaW9K+kl6Tl5H5WN5/v6T3SvqcpDGS1gM+Qfo3eNdAr6sXW+TjNR5bRsRk4I/AKZK2lbQl8Bvgobwd4LvAVpJOkvRaSZtJ+rSkNYFpwJPA/pI2kvQ20k08B+snwLslHZyXbzkAeBcQlTE/APbO595Y0sHAB1j4s/4/4EDSTPJ+l1oxK+Gee+5pdwnWYZwpK8G5sro5U1aCc2UlOFdWN2eq+7hJbsVFxHPAP4CVgasq25+vbL+ysv1GYHdgD9ISH98EDo+IUwd53uOBI4CL8g0jexszh7T0yWOkZVpuJc1C72vG+r6kWdU3km4keUJ+bcN00hIl15Bma+8I7JzXBJ9OagBfQZpBfSCwZ56RPlR/Jd38s/H4d96+T/79QtJyMALe3ZiBHRGT8nVvSfqy4jrSlxXzIuIF0nv/BtL7/yPSTVMHJSKuIV3jwcBEYKd8rOcqY84nLV1zKOnGoQcA+0TEVU2HO5N009CHWHgNczMzMzMzMzMzsyFTRLQeZWZWA0mnAJtFxHYljj9hwoRVgBnXzdxkgTXJPzduRInTWRd58sknWWONNdpdhnUQZ8pKcK6sbs6UleBcWQnOldXNmeocPT09TJw4EWDV8ePHz+xrnG/caWbFSDoUuIx0k9V3AXsBB7W1KLMh8BfKVjdnykpwrqxuzpSV4FxZCc6V1c2Z6j5ebsWszSSNkvRMP49R7a5xEbyJ1CS/lbT0yuci4pftLcls8B577LHWg8wGwZmyEpwrq5szZSU4V1aCc2V1c6a6j2eSm7Xfw8CYFvuXShGxe7trMDMzMzMzMzMz64+b5GZtFhHzgLvbXYeZ9W3jjTdudwnWYZwpK8G5sro5U1aCc2UlOFdWN2eq+3i5FTMzsxYefPDBdpdgHcaZshKcK6ubM2UlOFdWgnNldXOmuo+b5GZmZi3Mnj273SVYh3GmrATnyurmTFkJzpWV4FxZ3Zyp7uPlVsys4xy43QiGDRvW7jKsg6ywwgrtLsE6jDNlJThXVjdnykpwrqwE58rq5kx1H88kNzMza2HddddtdwnWYZwpK8G5sro5U1aCc2UlOFdWN2eq+7hJbmZm1sLkyZPbXYJ1GGfKSnCurG7OlJXgXFkJzpXVzZnqPm6Sm5mZmZmZmZmZmVnXcpPczMyshbXWWqvdJViHcaasBOfK6uZMWQnOlZXgXFndnKnu4ya5mZlZC8ss4/+5tHo5U1aCc2V1c6asBOfKSnCurG7OVPfxJ25mHecPf53D2Vemh1kdHn300XaXYB3GmbISnCurmzNlJThXVoJzZXVzprqPm+RmZmZmZmZmZmZm1rXcJDczM2thww03bHcJ1mGcKSvBubK6OVNWgnNlJThXVjdnqvu4SW5mZtaC/9TO6uZMWQnOldXNmbISnCsrwbmyujlT3cdNcjMzsxaeffbZdpdgHcaZshKcK6ubM2UlOFdWgnNldXOmuo+b5GZmZi0sv/zy7S7BOowzZSU4V1Y3Z8pKcK6sBOfK6uZMdR83yc3MzFpYf/31212CdRhnykpwrqxuzpSV4FxZCc6V1c2Z6j5ukpuZmbVw1113tbsE6zDOlJXgXFndnCkrwbmyEpwrq5sz1X3cJDdrM0lTJH2h8jwk7dK+igamVZ3N12VmZmZmZmZmZrYkcpO8w0kal5uZjcfjki6StEW7axsISXtK6pH003bX0kzSkZJuLnDodYCLCxx3AZKuaspG43FyTafYCvhFTccya6s111yz3SVYh3GmrATnyurmTFkJzpWV4FxZ3Zyp7uMmeffYlNR8fSewPPBnScu1t6QB2Rc4BthT0grtKEDSMEmL7d9KRDwaEc8vptOdQspF9fHlOg4cEY9HxKw6jmXWbssttzT859KWJs6UleBcWd2cKSvBubISnCurmzPVfdwk7x6P5ebrjcDxwLrAZo2dkg6WdKukZyVNlXSSpJHVA0gam2cfz5I0TdKlklbL+5aR9FVJ90maLWmipA8tSsGSNgDeAnwPmAR8oGn/3pKmS3qvpLtyXb+XtKKkvfJyH9MknSBpWOV1y0s6VtJD+Xr/KWlcL8d9n6TbgeeBUQOo91RJ50s6VNIjkp6U9FNJwytj1pJ0QX6P7pP00V6Os8AyJpK+L2lSvr57JR3ddMwjJd0s6eP5mmdIOlvSygN4m2flXFQfM/Nxl5N0Yr6W5yTdL+mr/Vz/UXnsa/Pz3paROUDShfla7pD0Zkkb5Vw9K+laSRs2HffTku6RNCd/zh8fwHWZ1erhhx9udwnWYZwpK8G5sro5U1aCc2UlOFdWN2eq+7hJ3mUkrQrskZ/Oqex6Afgc8GpgL+BtpBncjdeNASYAtwNvBrYFLgAazeevAp8ADszH+BHwG0nbL0K5+wB/jogZwG9Is8qbrZjr3gPYCRgHnAe8Oz8+DhwAVBv2J+Zr2AN4LfA74BJJGzcd9yvAfvl6HhtgzTsAG+afewF750fDqaQvKHbINR0ErNXimE/nY4wGPg98Cvhi05gNgV2A9+bH9sBhA6y5L58D3gfsTvpLhI8CU5oHKfkJ6fPfLiJu6eeY3wBOB8YAdwL/B/wc+C7wRkCkz6dx7F2BHwPHAa/JY/9X0g79FT579jPMnvU0s2c9zcyZM3n++cU1Md/MzMzMzMzMzJY2y7a7AFtsHpQEsFJ+/qeIuLOxMyKOr4ydIul/gJNJTVxIS3DcEBEHVcbdBmlmNvA1YMeIuC7vu1fStqQG9dWDLTYvb7I38Nm86WzgOEkbRMR9laHDgU9HxD35db8nNcbXjohngNslXUlqSv9W0ihS831URDS+FjxW0k55+9cqxz0oIiYOsvRpwGcioge4U9KfgfHAKZI2Ad4FvCkirs/17gvc0d8BI+JbladTJB1LavAfU9m+DLB3RDydj3tGPu/XW9R7kKT9mrYdEBFnkmbPTwb+HhEB3N/L65clfYHxOmDbiHioxfn+NyLOyTV+H7gOODoiLs3bfgz8b2X8ocCpEXFSfv5DSdvk7Vf2dZKv7/86Zs1KK70cAnz5y1/msMMW9TsD62YbbLBBu0uwDuNMWQnOldXNmbISnCsrwbmyujlT3cdN8u6xHTAL2IbUCD6wulPSjqTZ4JsBq5CysYKkFfO60mNIM657sxFp5vVluRHfsBxw0xDrfTupoX8RQEQ8Ieky4JOk2cgNsxoN8uy/wJTcIK9ua8zW3oI0+31SU63LA09Wns8BbgHIjfXbK/u+ExHf6aPu23KDvOGRfE6AzYF5wL8bOyPiTknT+zgW+fwfJs3q3hAYSfpsZjYNm9JokFfOu1Z+/UdJM7Ab3hURf8u/nwl8u+lY/80/TwUuA+6SdAlwYUT8pWnsj0jL0WwTEU/0dx1ZdZZ54zy3Nm1bQdIqedmXzVn45p/XkGbU9+nbv7iJFyL9ocwHtxvO8ssvP4DSzPr2+OOPM2pUy1WXzAbMmbISnCurmzNlJThXVoJzZXVzprqPm+Td476ImE5qeK4F/BZ4K4Ck9YELgZ+RZh4/RVpO5VekRvcsYHY/x26sXf4eoHkm8VDXudgXWB2YXWlmLwO8VtIREfFC3ja36XXRx7bG0kIjgR7gDflnVbWxPjvPngZ4mPQlQcNT/dTd37kHTdKbSY3sI4BLgRmkWeSHDOK8fwL+WdlX/YxmRMTdvZ07Im7M68K/C9gROEfS5RFRXbrmMmBP0g1hzxzAJVXrjH62LdJSUCNGjOSFvBLQKqv4Zhu26J555pnWg8wGwZmyEpwrq5szZSU4V1aCc2V1c6a6j5vk3emnwFcl7RoR55EaxssAhzSaz5J2b3rNLaTlO47o5Xjzb24ZEYNeWqWZpDWA95OawbdVdg0D/g68A7hkiIe/KR9nrcps6n5FxDyg10byIN1J+jf3BqCx3MqmwEv6ec1bgPsjYv5sb0nrDeakeYb50y0H9v7amaQvVH6bl7K5RNLqEdH4ouBPpLXp/09ST0ScPZTz9OMOYCxwWmXbWBac2W9W3PDhw1sPMhsEZ8pKcK6sbs6UleBcWQnOldXNmeo+bpJ3oYiYJekU4ChJ55MawMOBz0q6gNSEPLDpZd8FbpV0Emmt8jmkdb5/l5dCORb4UV5L/O/Aqvk4MyPiNAbn46SlT86pzOYGQNJFpFnmQ2qSR8QkSWcCp0s6hNQ0fynpC4BbIuLPQznuAM/dWLbk55I+TVp65Xj6n6U/GRglaQ9SY/09wK41lrWipJc1bXs+IqZJOpi0bMtNpBu77gY8CkyvDo6I8yR9HDhD0ryI+H2N9f2ANIP9JuByYGfgA6SZ7WaLzUYbbdTuEqzDOFNWgnNldXOmrATnykpwrqxuzlT3WaQlDWypdiJpvefd8s0pDwa+AvwH+ChpffL5ImISaQb3lsC/SDdcfD+p0QtpnfCj8+vuIDWx3wNUb7I5UJ8EzmtukGd/AN4nac0hHLdhH+B04DjgLuB8YCvggUU45mDO/TDpZqbnktbbfqyvwRHxJ9K63ycCN5Nmlh9dYz2fIjXCq4+z8r6nyTdsJTXo1wfeXVnqplrn74G9SI3yD9RVXEScT1p//FDSXxUcAOwTEVfVdQ6zgbjjjn7vr2s2aM6UleBcWd2cKSvBubISnCurmzPVfdR7H9LMbOkzYcKEVYAZd8/YfP6a5Hvs4DXJbdHdfvvtjB49ut1lWAdxpqwE58rq5kxZCc6VleBcWd2cqc7R09PDxIkTAVYdP378zL7GeSa5mZlZC6uvvnq7S7AO40xZCc6V1c2ZshKcKyvBubK6OVPdx01yK07SyZKe6eNxcrvrMzNrZcSIEe0uwTqMM2UlOFdWN2fKSnCurATnyurmTHUfN8ltcTgcGNPH4/C2VGRmNggPPfRQu0uwDuNMWQnOldXNmbISnCsrwbmyujlT3WfZdhdgnS8iHqOfm1OamZmZmZmZmZmZtYtnkpuZmbWw/vrrt7sE6zDO1P9n786j5KrK9Y9/HwKEKQEEQRxCkEkQTdSLolEJRhQHuIgTOIKgKFdFBBEnBvE6o4iKXlF/oHJBHEBQkAthUAEHBMIUSAKEeQiETCQkJLy/P/bucFJ0dXV3zuaQquezVq3uqrPrnPeceoiut3bvYyU4V1Y3Z8pKcK6sBOfK6uZM9R43yc3MzDqYPXt20yVYl3GmrATnyurmTFkJzpWV4FxZ3Zyp3uPlVsys67z9tWsyYsSIpsuwLjJv3rymS7Au40xZCc6V1c2ZshKcKyvBubK6OVO9xzPJzczMOvCXLlY3Z8pKcK6sbs6UleBcWQnOldXNmeo9ioimazAzq8XkyZNHA3PHjRvn/0EzMzMzMzMzM+txy5YtY8qUKQDrT5o0qe2fCHgmuZmZWQdTp05tugTrMs6UleBcWd2cKSvBubISnCurmzPVe9wkNzMz68B/dWV1c6asBOfK6uZMWQnOlZXgXFndnKne4ya5mZlZBxtssEHTJViXcaasBOfK6uZMWQnOlZXgXFndnKnes3rTBZiZ1W3ypcvo+873ja/z2uS28kaNGtV0CdZlnCkrwbmyujlTVoJzZSU4V1Y3Z6r3eCa5mZlZB3feeWfTJViXcaasBOfK6uZMWQnOlZXgXFndnKne4ya5mZmZmZmZmZmZmfUsN8nNzMw6GDNmTNMlWJdxpqwE58rq5kxZCc6VleBcWd2cqd7jJrmZmVkH8+bNa7oE6zLOlJXgXFndnCkrwbmyEpwrq5sz1XvcJDczM+tgzpw5TZdgXcaZshKcK6ubM2UlOFdWgnNldXOmeo+b5GZmZh1IaroE6zLOlJXgXFndnCkrwbmyEpwrq5sz1XsUEU3XYGZWi8mTJ48G5j44ZweCEQC88XUjmi3KzMzMzMzMzMwasWzZMqZMmQKw/qRJk9quo+OZ5GZWnKSjJV3TdB1mw3XzzTc3XYJ1GWfKSnCurG7OlJXgXFkJzpXVzZnqPW6Smz2FJE2UFJXHLEnnSnpR07V1IumFks7INS+WNE3SlyWt0zIuJO3ZUJlmRSxbtqzpEqzLOFNWgnNldXOmrATnykpwrqxuzlTvcZPcrBnbApsBbwRGAn+StGazJbUnaSfgH8CawFuAbYAvAPsCFzRRu5LVn+rjWm8aPXp00yVYl3GmrATnyurmTFkJzpWV4FxZ3Zyp3uMmuVkzHoiI+yLiKuB44HnAC/o2Svq0pOskPSLpTkknSlqvugNJEyRdImmhpIclnS9pw7xtNUmfk3SbpEWSpkh6x3AKVbpbxc+AqcBeEfHPiLg9In4D7A68Ejgkj52Z33ZmnlE+s2Vf75c0U9JcSadLGlXZNmDNlVn4b5L0b2Ax8OrhnJPZUG244YZNl2BdxpmyEpwrq5szZSU4V1aCc2V1c6Z6j5vkZg2StD6wd366pLLpceCTwAuBDwKvA75Zed94YDJwI6lJ/WrgHKDvLpWfAz4AfDTv47vAryTtPIwyxwPbA9+JiMerGyJiCnAhsE9+acf8cz/STPkdK8O3BPYE3pofOwNHVLYPtuav5/dtB1zbX8ELFy1g4cL5LFw4n3nz5rF48eLBnqtZv26//famS7Au40xZCc6V1c2ZshKcKyvBubK6OVO9x0sVmDXjrjRBm3Xz87Mj4qa+jRFxfGXsTElfBH4MHJRfOxy4MiIOqoy7AUDSSODzwOsj4oq87VZJrwYOBC4dYq3b5J9T22yfSp7RHRGz8nnNiYj7WsatBuwbEfNznb8EJgFfGGLNR0bEBQMV/PEDX8zChQuXPz/88MM54ogjBniHmZmZmZmZmZn1KjfJzZrxGmAhsBOpOfzR6kZJryfNrH4BMJr03+paktaJiIWk2d2/abPvrYB1SGuFV19fE7h6JWpW5yEDmtnXIM/uBTbJvw+l5is7HegH/3MtEekPZSa9djVGjhw53JrNAHjuc5/bdAnWZZwpK8G5sro5U1aCc2UlOFdWN2eq97hJbtaM2yJiDnCzpE2AXwOvBZA0Fvgj8CPSzTFnk2Zq/4zUNF4ILBpg331rl78FuLtl23DWHZmWf25H/0327SpjBvJYy/PgiSWfhlLzI50OtM7a6xF55ZnRo0d0GG3W2cKFC33jFquVM2UlOFdWN2fKSnCurATnyurmTPUer0lu1rwfAjtIelt+/jLSf5uHRsTfI2Ia8OyW91xLWqqkPzeSGstjImJGy+POYdR3DXATcIikFf7NkDQOeD1wWuXlx3hibfTBqrtms1rNnj276RKsyzhTVoJzZXVzpqwE58pKcK6sbs5U7/FMcrOGRcRCSScBx0g6C5gBrAF8QtI5wARalmMBvgZcJ+lE0lrlS4BdgN9ExIOSvg18Nze1/wasn/czLyJOGWJ9IWl/4ALgd5K+BtwHvAI4DrgCOL7ylpnAJEmXAYsj4uFBHGN+nTWbmZmZmZmZmZkNlmeSmz09/IC0bMk7I2IK8Gngs8D1wHtJ65Mvl2eXvwEYB/yT1Kj+T2BpHvIl4Nj8vqnAn0lLmdw2nOIi4nLS+unLgPNIjfyvAacAu0ZEdUmUQ4FdgTsZ2hrotdZsVqftt9++6RKsyzhTVoJzZXVzpqwE58pKcK6sbs5U71FENF2DmVktJk+ePBqY++CcHZavSf7G13lNclt506ZNY5tttmm6DOsizpSV4FxZ3ZwpK8G5shKcK6ubM9U9li1bxpQpUwDWnzRp0rx24zyT3MzMrIOlS5d2HmQ2BM6UleBcWd2cKSvBubISnCurmzPVe9wkN+sxkn4saUGbx4+brs/s6WjUqFFNl2BdxpmyEpwrq5szZSU4V1aCc2V1c6Z6j2/cadZ7jgS+3WZb2z87MetlG2+8cdMlWJdxpqwE58rq5kxZCc6VleBcWd2cqd7jmeRmPSYiHoiIGW0eDzRdn9nT0W23+f6xVi9nykpwrqxuzpSV4FxZCc6V1c2Z6j1ukpuZmZmZmZmZmZlZz3KT3MzMrINnP/vZTZdgXcaZshKcK6ubM2UlOFdWgnNldXOmeo/XJDezrjNp5xGMGDGi6TKsiyxevLjpEqzLOFNWgnNldXOmrATnykpwrqxuzlTv8UxyMzOzDh566KGmS7Au40xZCc6V1c2ZshKcKyvBubK6OVO9x01yMzMzMzMzMzMzM+tZbpKbmZl18IIXvKDpEqzLOFNWgnNldXOmrATnykpwrqxuzlTvcZPczMysg1tvvbXpEqzLOFNWgnNldXOmrATnykpwrqxuzlTvcZPczMysgyVLljRdgnUZZ8pKcK6sbs6UleBcWQnOldXNmeo9qzddgJlZ3f5+8TKI9PuEXUc0W4x1hXXXXbfpEqzLOFNWgnNldXOmrATnykpwrqxuzlTv8UxyMzOzDjbddNOmS7Au40xZCc6V1c2ZshKcKyvBubK6OVO9x01yMzOzDrwendXNmbISnCurmzNlJThXVoJzZXVzpnqPm+RmZmZmZmZmZmZm1rPcJDczM+tgs802a7oE6zLOlJXgXFndnCkrwbmyEpwrq5sz1XvcJDczM+tg6dKlTZdgXcaZshKcK6ubM2UlOFdWgnNldXOmeo+b5GZmZh3MmjWr6RKsyzhTVoJzZXVzpqwE58pKcK6sbs5U73GT3MzMzMzMzMzMzMx6lpvk9rQm6WhJ1zRdx6pO0iWSjm+6DrNV1TbbbNN0CdZlnCkrwbmyujlTVoJzZSU4V1Y3Z6r3uEm+CpM0QtIhkq6T9KikhyWdJ2lC07UNh6SQtGfLy98GJjVQznKSZubaQtIjkq6S9M6a9vupGkqs7nNirnODlk17AV+q81hmveSOO+5ougTrMs6UleBcWd2cKSvBubISnCurmzPVe9wkX0VJEnA6cCTwPWA7YCJwJ3BJP83mVVJELIiIh5qug3SdNwNeAvwL+LWkV/U3UNKaT2VhgxERsyNiftN1DMXT8Tpa73r00UebLsG6jDNlJThXVjdnykpwrqwE58rq5kz1HjfJV13vAt4BfCAifhoRt0XElIj4CHA28FNJ6/YNlrS7pH/lGecPSjqzsm2kpG9IulPSYkkzJO2ft+0raU71wJL2lBSV50dLukbSgXkfCyWdIWn9ypgdJV2Qjz1X0qWSXlrZPjP/emaeCT2zuu/KuNUkHSnprlzrNZJ2q2wfm9+/l6SLcy1TJL1ypa42zI+I+yJiGvBfwCJg977aJX1J0i8kzQN+kl9/u6Qbcp0zJR1aqfMSYHPgu32z1CvbXi3pr5IW5et5Qstn2e/nJWkscHEe9nDe78l9x+tbbkXSVyX9o/UE83U6svL8AElTc2ZuknTQQBdI0oaSTpU0K9c+XdJ+le3Py7mYI2m2pD/kmvu2nyzpLElfkHQPcPNgazUrbe211266BOsyzpSV4FxZ3ZwpK8G5shKcK6ubM9V73CRfdb0HmBYR5/Sz7ThgI2BXAElvAc4EziXNhJ4E/LMy/hfAPsAnSTPSDwQWDLGerUiN+92B3fJxTqxsHwWcArwa2AmYDpwraVTevmP+uR9pxvaO9O9g4FDgMODFwPnA2ZK2bhn336SlWsYD04DTJK0+xHPqV0QsBR4DqjOdDwOmkM77WEkvA84gzfZ/EXB0fn3fPH4v4C6emKG+GYCkLYE/A7/L5/du0jX7QeVY7T6vO4G35zHb5n0e3M8pnAq8PB+LfNwX5uP9b37+XuDLwBfyMT6f6//gAJfmWGB74E35PR8DHsz7W4P0Wc0HXgNMyDX/uWXG+KRc+67AWwdTa38WLVzAwoXzWbhwPvPmzWPx4sUDlG3W2XOe85ymS7Au40xZCc6V1c2ZshKcKyvBubK6OVO9p5amoTViG2Bqm21TK2MgNTpPj4ijKmOmAEjahtTc3jUiLszbbh1GPWuRZrXfnff7CeBPkg7NM7Avqg6W9BFgDrAz8MeImCUJYE5E3DfAcQ4DvhERp+fnn5W0C/Ap0gzvPt+OiD/lYx0F3EBq5N80jHOr1r0mqUm/PlA9p4si4rjKuFOByRFxbH5pmqTtgc8AJ0fEbEnLyDPUK/v5HHBqRByfn0+X9EngUkkfA8YwwOclaXb+9YGImNPfOUTEDZKmkL5o6avvvcA/ImJGfn4McGhE/D4/vy3XfyDpy47+jAGujogr8/OZlW3vJn0pd0BERK51P1IGJgL/l8c9kscsqZxTp1qfZN+DXszChQuXPz/88MM54ogj2g0362jGjBlsv/32TZdhXcSZshKcK6ubM2UlOFdWgnNldXOmeo+b5Ks2DXLceOCkAbYtAy5dyVru6GuQZ1eQmqLbAvdJ2hT4CqkhugkwAliH1FgdFEmjgWcDl7VsugwY1/LatZXf780/N2H4TfJvSPoK6cuABcARfU347MqW8dsBf+inzk9JGhERy9ocZxzw4jyTu49I13IL0qz0Oj6vU4EPkWaHizQz/TsAeWmXLYGfSarmZnVgbh5zHmlGOMDtEfFC4EfA7/IyOv8HnBURl1fOaytgfv4ypM9a+Vh9rqs2yDvV2s7JJ15LRPpDmVfsshojR44caLiZmZmZmZmZmfUwN8lXXdNIjdj+bFcZA2n97HYG2gbwOE9uxq/R4T39OYW0BMzBwO3AYlIjvdTNGR+r/N633vfKLC/0LeBkUoP8/r7Z0BWPrMS+q9YD/gc4oZ9td5AazXU4jdT4fymwNvA84NeVGgA+DLSuB97X3D8gvw/ytY6I8yRtDryZtFzKZEk/jIjD8j7/TZoF3mpW5ff+ruNAtfZr7XXWgxgBwOjRIwYaajYom266adMlWJdxpqwE58rq5kxZCc6VleBcWd2cqd7jJvmq63TgfyXt3s+65IcCDwEX5OfXktZ6/n/97Oc6UvN4Z+DCfrbPAkZJWjci+hqY4/sZN0bSsyPinvx8J1KD/eb8fAJwUEScC+kmjsDGLft4jDTDvF8RMS/f0HECK86knsCKa6yX8OBAy3v0YyqprqoJpHXk+xrNS3jy+V4FbN/uWJI6fV59s7AH7AxHxF2SLiU1rdcGLoiIB/K2+/N1fn5EnNrm/Xe3eX0W6QuRUyT9lfTlwmH5vN5NWgZm3kC1DaVWMzMzMzMzMzOzleUbd666TifdjPMUSftLGivpxZL+B9iDtK5zX1P7GGAfScdI2k7SiyR9FiAiZpKamj+XtKekLSRNlPSu/N5/AAuBr0raUtJ7gH37qefRXMs4Sa8hzYQ+o7Le9nTg/fn4ryAtodE6i30mMEnSsyRt2Oa8v0Vah/zdkraV9HVS0/57g7tsT5njSOfyJUnb5Btefpx0M9E+M4HXSnqOpL4vDL4BvErSDySNl7S1pP+U9AMY1Od1O2nm/FslPVPSerR3KrA38M78e9VRwOckfTLX/yJJ+0n6dLudSfpyrnWrfHPNt/LE+vinkm7i+QdJr6nUfYKk5w5Q42BqNSvu/vvvb7oE6zLOlJXgXFndnCkrwbmyEpwrq5sz1XvcJF9F5eU+3gV8FTiENGP7r8DmwMSIOKsy9hJSc3EP4BrSDSdfXtndx4DfAieS1uw+CVg3v3c28D7SEhrXkdaDPrqfkmYAvwfOJa1HfS1wUGX7/sCGpBnFvyQ10VtnAx9KWqbjTuDqNqd+Amk96uNyPbsBe0TE9DbjGxERV5E+n72B64EvA0dGxMmVYUcCY4FbyEuORMS1pFni25A+z6vze++pvG+gz+tuUoP768D9wA8GKPO3pCVw1gHOaqn/p6QlVfYjXedLSV+O3DbA/pYAXyN99n8hLc2yd97fQuC1pCVjfk9qnv+MtCb5YGaWt63VzMzMzMzMzMxsZejJSyubDY2ko4E9I2J8w6VYj5s8efJoYO6i2TssX5N8wq5ek9xW3pIlS1hzzVK3ULBe5ExZCc6V1c2ZshKcKyvBubK6OVPdY9myZUyZMgVg/UmTJrWdqOmZ5GZmZh3cfXe/y/CbDZszZSU4V1Y3Z8pKcK6sBOfK6uZM9R43ya2nSDpP0oI2j883XZ+ZPT0tWtR6CwWzleNMWQnOldXNmbISnCsrwbmyujlTvWf1pguwVV9EHE3/65Q/HR0ArN1m2+ynshAzW3WstdZaTZdgXcaZshKcK6ubM2UlOFdWgnNldXOmeo+b5NZT8o0tzcyGZMyYMU2XYF3GmbISnCurmzNlJThXVoJzZXVzpnqPl1sxMzPrYNq0aU2XYF3GmbISnCurmzNlJThXVoJzZXVzpnqPm+RmZmZmZmZmZmZm1rO83IqZdZ2ddhnBiBEjmi7Dusgzn/nMpkuwLuNMWQnOldXNmbISnCsrwbmyujlTvcczyc3MzDpYfXV/p2z1cqasBOfK6uZMWQnOlZXgXFndnKne4ya5mZlZB/fee2/TJViXcaasBOfK6uZMWQnOlZXgXFndnKne4ya5mZmZmZmZmZmZmfUsN8nNzMw6eP7zn990CdZlnCkrwbmyujlTVoJzZSU4V1Y3Z6r3uEluZmbWwf333990CdZlnCkrwbmyujlTVoJzZSU4V1Y3Z6r3uEluZl3n2v9byjXnLm26DOsijzzySNMlWJdxpqwE58rq5kxZCc6VleBcWd2cqd7jJrmZmVkHa665ZtMlWJdxpqwE58rq5kxZCc6VleBcWd2cqd7jJrmZmVkHXo/O6uZMWQnOldXNmbISnCsrwbmyujlTvcdNcjMzsw5uuummpkuwLuNMWQnOldXNmbISnCsrwbmyujlTvcdNcjMzMzMzMzMzMzPrWW6Sm5mZdbDRRhs1XYJ1GWfKSnCurG7OlJXgXFkJzpXVzZnqPW6Sm5mZdTBy5MimS7Au40xZCc6V1c2ZshKcKyvBubK6OVO9x01yMzOzDu65556mS7Au40xZCc6V1c2ZshKcKyvBubK6OVO9x01y61qSjpZ0TdN1lCDpEknHN12HmZmZmZmZmZnZqs5N8h4laYSkQyRdJ+lRSQ9LOk/ShKZrGw5JIWnPlpe/DUxqoBwkTcw1DfSY2ERtq6rKNd2g6Vqs92yxxRZNl2BdxpmyEpwrq5szZSU4V1aCc2V1c6Z6j5vkPUiSgNOBI4HvAdsBE4E7gUv6aTavkiJiQUQ81NDhLwc2qzzOAP7c8trlDdW2ypG0RtM1WG978MEHmy7BuowzZSU4V1Y3Z8pKcK6sBOfK6uZM9R43yXvTu4B3AB+IiJ9GxG0RMSUiPgKcDfxU0rp9gyXtLulfecb5g5LOrGwbKekbku6UtFjSDEn75237SppTPbCkPSVF5fnRkq6RdGDex0JJZ0havzJmR0kX5GPPlXSppJdWts/Mv56ZZxrPrO67Mm41SUdKuivXeo2k3Srbx+b37yXp4lzLFEmvHOoFjoglEXFf3wNYBCyuPH8Y+KqkuyU9IukfrTPLJU3Iy6oszDP9z5e0YWXIapK+KWm2pPskHT1QTZLWlPQDSffmz/J2SZ9rOffxlfEbVGe8V2Zyv0XStXkff5e0Q+U9+0qakz/n6XnM+ZKe11LLxyTdImmJpJslvb9le+QxZ0t6BDgJuDhvfjhvP7nDx2BWm/nz5zddgnUZZ8pKcK6sbs6UleBcWQnOldXNmeo9bpL3pvcA0yLinH62HQdsBOwKIOktwJnAucBLSMuX/LMy/hfAPsAnSTPSDwQWDLGerUiN+92B3fJxTqxsHwWcArwa2AmYDpwraVTevmP+uR9phvaO9O9g4FDgMODFwPnA2ZK2bhn336SlWsYD04DTJK0+xHPq5AfAK4G9cy2/Af7cV0tuVk8GbszjXg2cA4yo7OODwCPAK4DDgSMl7TrAMT8J7EG61tsC7wVmDqP2b5Gu447ALOCclpne6wBfAD4ATAA2IP3lAvnc3kb6C4bjgB2A/wH+n6RdWo5zNCl7LwKOAt6eX9+W9Dkf3K7AhQsX8MjC+cybN4958+axePHiYZym2RNWX73ufwKs1zlTVoJzZXVzpqwE58pKcK6sbs5U7/En3pu2Aaa22Ta1MgZSs/P0iDiqMmYKgKRtSA3XXSPiwrzt1mHUsxZpVvvdeb+fAP4k6dA88/qi6mBJHwHmADsDf4yIWWkFGebkWdrtHAZ8IyL6GrafzY3ZTwH/VRn37Yj4Uz7WUcANpEb+TcM4tyeRNIbU0B8TEX23S/52ntW+H/B5UtP7yog4qPLWG1p2dW1EHJN/ny7p46QvMS5oc+gxpC8Y/hYRAdw+zFM4JiIuyOfyQeAu4G2kJWUA1gA+HhH/qIyZKunlEfFP0udwckT0fRHyHUk75dcvrhznfyPi//U9kdS3INgDETFnoALfffA4Fi5cuPz54YcfzhFHHDGskzUD2GabbToPMhsCZ8pKcK6sbs6UleBcWQnOldXNmeo9nkneuzTIceNJM5rbbVsGXLqStdzR1yDPriBlc1sASZtKOikv3zEXmAesR2r6Doqk0cCzgctaNl1GmgFfdW3l93vzz00Ge6xBeBFpRvg0SQv6HqSm/5Z5zHjaX/f+6oRU6yYAkn7csm+Ak/N+b5Z0gqQ3DLP+K/p+iYjZwM2seA2XAv+qjLmJ9KVG35jtGNzncOUw6+PX35vCOT+5hZkzZzJz5kwOOeSQ4e7KDIAbb7yx6RKsyzhTVoJzZXVzpqwE58pKcK6sbs5U7/FM8t40jSc3JPtsVxkDaS3tdgbaBvA4T27GD+cGjKeQloA5mDT7eTGpUbvmMPY1GI9Vfu9bP73OL5TWI3258LL8s6qvod3p2sKKdUKqta/OI0lLxjyxMeKqPBv7TcDrgTMkXRgR7yB9VrDi59X0zTIfGe4b11lnPRQjGD3a/8SZmZmZmZmZmdnAPJO8N50ObC1p9362HQo8xBNLdlxLWsKjP9eRMrRzm+2zgFGq3ASUNJO51RhJz64834nUtL05P58AnBAR50bEDaQm+cYt+3iMFdfrXkFEzAPuyfuqmkBa9/updDWp1k0iYkbLo2+5mIGue0cR8UB1v5XX50XEryPiw8C7gbdLegbps4K01nef8W12v1PfL/lGoq3L96wO/EdlzLakdcn7xkxleJ/Dkvyz7edsVsoznvGMpkuwLuNMWQnOldXNmbISnCsrwbmyujlTvcfTLHvT6cA7gVMkfYa0rMdo0rrcewDvjIi+WbzHAJMl3ZLftzrw5oj4RkTMlHQK8HNJnyStVb45qfl7BvAPYCHwVUknkG4wuW8/9Tyaazks13ECcEalYTwdeL+kK/P2b/HkmdYzgUmSLgMWR8TD/RznW8Ax+VyuIa3/PZ50A8unTERMk3Qq8AtJh5Ka5s8kNcWvzeuhfw24TtKJwI9JDeJdgN9ExIPDOa6kT5OWZLma9CXEO4H7SGu5Py7p78ARkm4jLdvylTa7OlLSQ8D9pJucPgicVdn+GPD9nImlpJuU/j2vRw7pczhD0tXAhaQbtu5Fmt0+kNtJs+XfKulcYFFEDPUmsWbDss466zRdgnUZZ8pKcK6sbs6UleBcWQnOldXNmeo9nkneg/JNG98FfBU4hDRj+6+kBvfEiDirMvYSUjN1D1Jj+SLg5ZXdfQz4LXAi6caWJwHr5vfOBt4HvJk063wf4Oh+SpoB/B44F/g/0izq6g0r9wc2BK4Cfklqoj/Qso9DgV2BO0lN4P6cAHwHOC7XsxuwR0RMbzO+pP2AX+RabiY1mXcE7oDUSAfeAIwD/klaXuY/SU3n4ZpPviEoac3wsaQvPPqWWvkQ6UuQfwPHA19ss58jgO/lcc8Cdo+IJZXtC4FvAP9LWmt8AWnWOvncziItnXMY6WakBwL75ay1ldetPwr4OqlB/4NOJ2xWl7vuuqvpEqzLOFNWgnNldXOmrATnykpwrqxuzlTvUeqXmjVD0tHAnhExvuFSrANJE4GLgQ0jYk6bMfsCx0fEBk9VXVWTJ08eDczV/S9EMYLxb/Yfy1g9brzxRrbffvumy7Au4kxZCc6V1c2ZshKcKyvBubK6OVPdY9myZUyZMgVg/UmTJs1rN84zyc3MzDrYfPPNmy7BuowzZSU4V1Y3Z8pKcK6sBOfK6uZM9R43yc0GSdJ5kha0eXy+6frMrJyHH+7vNgdmw+dMWQnOldXNmbISnCsrwbmyujlTvcdrEVijIuJo+l+n/OnoAGDtNttmP5WFNCGvGa4OY04GTn4KyjF7Ss2b1/YvssyGxZmyEpwrq5szZSU4V1aCc2V1c6Z6j5vkZoOUbxxpZj1oxIgRTZdgXcaZshKcK6ubM2UlOFdWgnNldXOmeo9v3GlmXcM37jQzMzMzMzMzsz6+caeZmVlNpk6d2nQJ1mWcKSvBubK6OVNWgnNlJThXVjdnqvd4mqWZdZ0Xv2F1/2mU1cp/dWV1c6asBOfK6uZMWQnOlZXgXFndnKne45nkZmZmHWywwQZNl2BdxpmyEpwrq5szZSU4V1aCc2V1c6Z6j5vkZmZmHYwePbrpEqzLOFNWgnNldXOmrATnykpwrqxuzlTvcZPczMysgzvuuKPpEqzLOFNWgnNldXOmrATnykpwrqxuzlTvcZPczMzMzMzMzMzMzHqWm+RmZmYdPO95z2u6BOsyzpSV4FxZ3ZwpK8G5shKcK6ubM9V73CQ3MzPrYP78+U2XYF3GmbISnCurmzNlJThXVoJzZXVzpnqPm+Rm1nVm/OmxpkuwLjNnzpymS7Au40xZCc6V1c2ZshKcKyvBubK6OVO9x01yMzOzDiQ1XYJ1GWfKSnCurG7OlJXgXFkJzpXVzZnqPYqIpmswM6vF5MmTRwNz171re7bdY62myzEzMzMzMzMzswYtW7aMKVOmAKw/adKkee3GeSa5mZlZBzfffHPTJViXcaasBOfK6uZMWQnOlZXgXFndnKne4ya5mZlZB8uWLWu6BOsyzpSV4FxZ3ZwpK8G5shKcK6ubM9V73CQ3MzPrYPTo0U2XYF3GmbISnCurmzNlJThXVoJzZXVzpnqPm+RmZmYdPOMZz2i6BOsyzpSV4FxZ3ZwpK8G5shKcK6ubM9V73CS3FUgaKykkja9xn0dLuqau/T2d9He9JE2QdJ2kxySd1Vx1T0+SLpF0fNN1mA3FzJkzmy7BuowzZSU4V1Y3Z8pKcK6sBOfK6uZM9R43yZ/mJK2Xm617t7x+em7Ojm15faakY5/SIldhkj4saYqkBZLmSLpa0udWcrffAa4BtgD2XdkaVwVD/HJlL+BLhUsyMzMzMzMzMzMbFDfJn+YiYgFwJTCxZdNE4M7q65K2ADYHLhrOsSStOZz3raokfQg4HjgBGA9MAL4JrLeSu94SuCgi7oqIOSu5r64TEbMjYn7TdZgNxXOe85ymS7Au40xZCc6V1c2ZshKcKyvBubK6OVO9x03yVcPFrNgM3w5YC/gRKzbPJwKLgSvyuLdLukHS4jzD/NDqTvNrX5L0C0nzgJ+0HljSCEk/l3STpDHtCpT0XEmnSZot6RFJV0p6RZuxO0q6QNKDkuZKulTSSyvblZdouSPXfo+kEyrbD5I0XdKjku6X9NsBrt1A9gDOiIifRcSMiLghIk6LiC+01HuApKn5eDdJOqjNeY2VFMBGwM/zzOp924x9nqQz8uz12ZL+UP2rAEknSzpL0ufzOc6RdKSk1SV9K7/nLkn7tR5f0t6SLs/1Xi9p54EugqR98/7fmM9zgaQ/S9qsMma1fPy78mdyjaTdKru5Lf+8OtdwyQDHW2G5lZzDz+eczc+f+0da3jPofJmVsGjRoqZLsC7jTFkJzpXVzZmyEpwrK8G5sro5U73HTfJVw8XAtpWm5S7A30gzxidWxu0CXBERj0p6GXAGcDrwIuBo4Nh+mraHAVOAlwArLNMiaSTwG9Is69dExB39FSdpPeBS4DmkxvM40ozsdvkaBZwCvBrYCZgOnCtpVN7+duAQ4EBga2BP4Lp8rP8gzfw+EtgW2A34S5vjdHIfsJOkzdsNkPRe4MvAF4DtgM+TruMH+xl+J7AZMA/4VP791/3scw3gfGA+8BrSDPYFwJ9bZvO/Dng28Frg08AxwB+Bh4FXAD8G/kfSc1sO8S3gONJnegVwjqSN2p1jtg4pC+/PxxsDfLuy/WDg0Dzmxbn+syVtnbe/PP98fT7vvTocr9WhpL+YeAlwIvAjSdvCsPLFI48uYN68ecsfixcvHmI5ZiuaPXt20yVYl3GmrATnyurmTFkJzpWV4FxZ3Zyp3rN60wXYoFwGLCE1xE/LPy8F/g1sLGmLiLgN2Bn4WX7Pp4HJEdHX+J4maXvgM8DJlX1fFBHH9T2pzGZeD/gTMBLYJSLmDlDfe4BnAjtGRN+/IjPaDY6IFZaDybOG5+T6/0hq0N4HXBgRjwF3AP/Mw8cAjwB/zEt23A5cPUBtAzkG+D0wU9I0UkP5XOC3EfF4ZcyhEfH7/Py2fB0PJDX6q+e1DLgvzyafGxH3tTnuu0kN3gMiIvI12C9fg4nA/+Vxs4FP5lpulnQ4sE5EfDW/52vAEaQvG06v7P8HEfG7POZjpC8S9ic1lttZA/hoRNyS3/cD0hcRfQ4DvhERfcf5rKRdSF8G/BcwK7/+0ADnPZBzI+LEfOxvkL4k2QW4mSHmC2CPT49n4UcXLn9++OGHc8QRRwyjLDMzMzMzMzMz63aeSb4KiIiFwL94Ytb4zsAlEbEUuByYKOn5pAbyxXnMdqTmetVlwNaSRlReu7LNYU8D1gXeUG2QS/pxXo5jgaQF+eXxwNWVBuaAJG0q6aS8ZMpc0szr9XL9kGavrw3cmse9TVLfFzoXkBrjt0r6paT3SlpnMMdtFRH3RsQrSTPtv0f60ugU0ozu1SStS1pf/Gct5/zF/PpgzrW/6zUO2AqYX3l9NmkJnep+b6g06wHuJ8+oz/UvAx4CNmk57BWVMUtJn/F2uZ4bKvWcV3nPwr4GeXZv334ljSbNaO8vT9sNcO6vqZ57npXfzrWVmoP0JUnfeY1nCPkCOPs71zBz5szlj0MOOWSwbzXr13bbtY262bA4U1aCc2V1c6asBOfKSnCurG7OVO9xk3zVcTGwi6QXkhrIV+XXLyXNuN0FWAj8Y4j7faTN6+eSltV4ZcvrR5Kaln0PgKEu1HRKfu/BwKvy7w8BawJExJ2kpVQOyvs+EfiLpDXy7PGXAvuQGrlfBqZI2mCINSwXEddHxIkR8T5g1/zYmSdu4PlhVjznHUjLxAxGf9drPdJfAYxveWwD/G/lvY+1ltrmtaH8d/zmyvEO6HAsDWG//bmSFc/v7AHGDnReQ14IbN211mP06NHLHyNHjhzqLsxWMGPGgH+8YDZkzpSV4FxZ3ZwpK8G5shKcK6ubM9V7vNzKquNi0gzm9wB/y7OIIa3H/RFSQ/OyiFiSX59KWuu6agIwrfLegfwIuJ607vRbIuJSgIh4AHigZey1wAGSnjHI2b4TgIMi4lxIN7EENq4OiIhFwDmk9bR/CNxEmvF9VZ4dfSFwoaRjSMuUvI60dMrKujH/XDci7pd0D/D8iDh1ODtrc72uIi258kBEzBt+qW3tRF6nPc/Afxnwg1zP7UPdWUTMy9dhAulLmT4TeGIZnL7cjai8bxEdlkUZpKHmy6x2jz3W+j2O2cpxpqwE58rq5kxZCc6VleBcWd2cqd7jJvmq43JgMfAJ4L8rr/+TtCzFfwJfq7x+HPAvSV8i3TzylcDHSbOzByUivp+XZvmjpDdFxN/aDD2NdEPLsyR9jjTD+yXAPRFxRT/jpwPvl3QlMJp0o8nls4XzzUVHkGbFLwTel7ffLumtwPNJTeCHSTOjVyOtXT0kkn4E3EO6AepdpBtOfpG0vnZf3UcBJ+RlYf5MWqP9P4ANI+I7Qz1mdippbfg/SDoyH3tz0s0uvxkRdw1zv33+S9J00hclhwAbAj9fyX1+CzhG0i3ANcB+pNnhfUuoPED6jHaTdBfwaId17IdiqPkyq916663XeZDZEDhTVoJzZXVzpqwE58pKcK6sbs5U7/FyK6uIiHgU+DswCrik8vriyusXV16/CngXsDdpRviXgSMj4uQhHvd4UqP4XEmvajNmCfAGUqP0XNK62UcA7Was709q3F4F/BI4gRVnW88hLXFyGWkW8euB3SPiobxtL1JjeyrwUWCfiLhhKOeVXUiadf0bYBrwO+BRYFI+FhHxU9KyJPvl87oU2Be4bRjHI+9zIfBa0g1Jf5/P42ekNcnrmFl+RH5MId3Uc4+IeHAl93kC8B3Sly/XkW4GukdETIfla59/knRD03uAP6zk8ZYbRr7MavfMZz6z6RKsyzhTVoJzZXVzpqwE58pKcK6sbs5U71G6R56ZreokjSU1718SEdc0W00zJk+ePBqYu+5d27PtHms1XY51kRtvvJHtt9++6TKsizhTVoJzZXVzpqwE58pKcK6sbs5U91i2bBlTpkwBWH/SpEltJ6d6JrmZmZmZmZmZmZmZ9SyvSW5dQdIYnrjpZn+2j4g7nqp6zKy7PPvZz266BOsyzpSV4FxZ3ZwpK8G5shKcK6ubM9V73CS3bnEP6UaSA23vahExE1DTdZh1oyVLljRdgnUZZ8pKcK6sbs6UleBcWQnOldXNmeo9Xm7FukJELI2IGQM8ljZdo5mtuh58cGXvfWu2ImfKSnCurG7OlJXgXFkJzpXVzZnqPW6Sm5mZmZmZmZmZmVnPcpPczMysg2233bbpEqzLOFNWgnNldXOmrATnykpwrqxuzlTvcZPczLrOVm9Zo+kSrMvMnDmz6RKsyzhTVoJzZXVzpqwE58pKcK6sbs5U73GT3MzMrIPFixc3XYJ1GWfKSnCurG7OlJXgXFkJzpXVzZnqPW6Sm5mZdbDuuus2XYJ1GWfKSnCurG7OlJXgXFkJzpXVzZnqPW6Sm5mZdfCsZz2r6RKsyzhTVoJzZXVzpqwE58pKcK6sbs5U73GT3MzMrINbbrml6RKsyzhTVoJzZXVzpqwE58pKcK6sbs5U73GT3MzMzMzMzMzMzMx6lpvkZmZmHfhP7axuzpSV4FxZ3ZwpK8G5shKcK6ubM9V73CQ3s65z9+8fa7oE6zKPP/540yVYl3GmrATnyurmTFkJzpWV4FxZ3Zyp3uMmuZmZWQcPPPBA0yVYl3GmrATnyurmTFkJzpWV4FxZ3Zyp3uMmuZmZmZmZmZmZmZn1LDfJzczMOth6662bLsG6jDNlJThXVjdnykpwrqwE58rq5kz1HjfJzczMOrjzzjubLsG6jDNlJThXVjdnykpwrqwE58rq5kz1HjfJzczMOnj00UebLsG6jDNlJThXVjdnykpwrqwE58rq5kz1HjfJzczMOlh77bWbLsG6jDNlJThXVjdnykpwrqwE58rq5kz1HjfJzczMOnjuc5/bdAnWZZwpK8G5sro5U1aCc2UlOFdWN2eq97hJbkVIOlrSNU3XYU8fzoStyqZPn950CdZlnCkrwbmyujlTVoJzZSU4V1Y3Z6r3uEneAEkjJB0i6TpJj0p6WNJ5kiY0XdtwSApJe7a8/G1gUgPlIGlirmmgx8QmaitF0th8XuObrmUAjWXCzMzMzMzMzMysndWbLqDXSBJwOvB64DPAZGA08F/AJZLeGRFnNVdhPSJiAbCgocNfDmxWef490jXer/La7L5fJK0ZEUueotpqJ2nNpmsYjIYzYbZSNtlkk6ZLsC7jTFkJzpXVzZmyEpwrK8G5sro5U73HM8mfeu8C3gF8ICJ+GhG3RcSUiPgIcDbwU0nr9g2WtLukf+UZ5w9KOrOybaSkb0i6U9JiSTMk7Z+37StpTvXAkvaUFJXnR0u6RtKBeR8LJZ0haf3KmB0lXZCPPVfSpZJeWtk+M/96Zp7JPLO678q41SQdKemuXOs1knarbO+bCb2XpItzLVMkvXKoFzgilkTEfX0PYBGwuPL8o8A/JR0g6Tbg0VzDbpL+JmmOpIck/VHSlkOpUdLmks7Jfx3wiKQbJL05b+ub4f4WSdfmz/TvknZo+Zzent+3WNJMSYe2bJ8p6UuSfiFpHvAT4La8+ep8jEvaXR9Jl0j6vqTjc533S/qwpHUl/T9J83OW3tTyvp0l/TPXda+kr0taPW/7iKR7JK3W8p4/SPp5/r01EydLOkvSYXl/D0n6oaQ1KmM2k/QnSYsk3SbpPfn8P9Xu/AAeeXQB8+bNW/5YvHjxQMPNOpLUdAnWZZwpK8G5sro5U1aCc2UlOFdWN2eq97hJ/tR7DzAtIs7pZ9txwEbArgCS3gKcCZwLvIS0VMU/K+N/AewDfBLYDjiQoc/U3YrUuN8d2C0f58TK9lHAKcCrgZ2A6cC5kkbl7Tvmn/uRZm/vSP8OBg4FDgNeDJwPnC1p65Zx/01almM8MA04ra8RW7OtgLcDe+VjAawLfAf4D9K1fpzU/G/972SgGn8IjAReC7wI+CxP/ky+RboWOwKzgHP6GsOSXgacQfprgxcBRwPHStq3ZR+HAVNIn9exwMvz668nfQ57dTj/DwIP5vd9H/gR8BvSLPyXAv8H/FLSOrmu55By+C9gHPAxYH/gi3l/vyFld5e+A0h6BilTpw5Qxy7AlvnnB4F986PPL4BnAxNJn9dHgI5f5+76ufGMHTt2+eO73/1up7eYDej+++9vugTrMs6UleBcWd2cKSvBubISnCurmzPVe7zcylNvG2Bqm21TK2MAvgCcHhFHVcZMAZC0Dam5vWtEXJi33TqMetYizWq/O+/3E8CfJB2aZ15fVB0s6SPAHGBn4I8RMSt/uzYnz9Ju5zDgGxFxen7+WUm7AJ8iLTXT59sR8ad8rKOAG0gN7ZuGcW4DWZN03rP6XoiI31UHSPoQqYm9PXD9IGscA/wuIq7LY/v7TI6JiAvy+z8I3AW8jdQc/zQwOSKOzWOnSdqetDTPyZV9XBQRx1VqXZZ/fajD59BnSkR8Jb/3a8ARwIMRcVJ+7cukRviLgb8DBwF3Ah+PiABukvRs4BuSvhwRD0s6j/Ql0OR8jHeQGvEXD1DHw3mfy/I+/0T6guIkSS8gNf13jIgrc10HkL6oGdAFX7uG5/znE6vQjBw5chCXxMzMzMzMzMzMepFnkjdjsH+zMZ4nGo79bVsGXLqStdzR1yDPriDlYlsASZtKOknSdElzgXnAeqRm8KBIGk2aDXxZy6bLSDPgq66t/H5v/lliIajbqw1yAElbSzpN0q15GZOZeVPruQ5U4wnAFyVdJukYSS/u59hX9P0SEbOBm3niOmxH/9dpa0kjKq9d2f7Ulp/PayQtqDze29855Ab1Q8B1le19X5n2ndd2wBW5QV6taz3gufn5qcDbJfV1pN9L+pLn8QHKvCEfv8+9lWNuCywFrqrUOoPUWB/Qumutx+jRo5c/3CS3lbXlllt2HmQ2BM6UleBcWd2cKSvBubISnCurmzPVe9wkf+pN48mN4T7bVcZAWku7nYG2QVoqpLUZv0Z/Azs4hdSQPxh4Vf79IdJM7BIeq/ze15AtkdNH+nntHOAZwIeBV+QHPPlc29YYET8Fng/8krRcypV5dn7d+qu/1ZWkz6vvcXZl22MtY6P6WqUZPpRrfw4pc2+R9DzgNQy81Eq7Ovzvkj3t3HvvvZ0HmQ2BM2UlOFdWN2fKSnCurATnyurmTPUeN6OeeqeTZgXv3s+2Q0kN6Avy82tJS0/05zrS57dzm+2zgFGq3ASUJ9berhqTl83osxOpwX5zfj4BOCEizo2IG4DFwMYt+3gMGEEbETEPuCfvq2oCcGO79z2VJG1Emrn8lYiYHBFTgQ2Hs6+IuDMifhwRe5HWmf9wy5CdKsfdkBWX4JlK/9dpWsuM61ZL8s/ln0NELIqIGZXH/GGcTp+pwCu14p0rJgDzScvFEBGPAr8nzSDfB7g5Iq5q3dEQ3ExaEuolfS9I2ophfi5mK2PhwoVNl2BdxpmyEpwrq5szZSU4V1aCc2V1c6Z6j9ckf+qdDrwTOEXSZ0jLqYwmrcu9B/DOiOibJXwMMFnSLfl9qwNvjohvRMRMSacAP5f0SdJa5ZsDm0TEGcA/gIXAVyWdQJoVvW8/9Tyaazks13ECcEZlXevpwPslXZm3f4snz2KfCUySdBmwOCL6Ww7jW8Ax+VyuId3oczypofp08DDpC4qPSLqXtMTK14e6E0nHA+eR/hpgQ9INKVvXoD9S0kOkJU3+m7Ru91l523HAvyR9Cfg18Erg46Q1wQfyAOlz2U3SXcCjETF3qPUP4ETS+vHfl/QD0hcKxwDfaVlO5VTgj8ALgV+tzAEj4iZJFwI/kfQx0pcxx5HOMwZ8s1nNvGSP1c2ZshKcK6ubM2UlOFdWgnNldXOmeo9nkj/F8jIW7wK+ChxCmi37V1KDe2JEnFUZewmpob4HqbF8EfDyyu4+BvyW1MC8CTgJWDe/dzbwPuDNpFnn+wBH91PSDNLs33OB/yPNXq82ZPcnNXuvIi0hcgKpIVt1KLAr6caOV7c59ROA75CanNcBuwF7RETHmzA+FXKjd2/gZaSbdH6XdLPMoRoB/JDUGP8zqVne2uA+Avge8G/gWcDuEbEk13EVKR975zq+DBwZESd3qH8p8EngQNKs/T8Mo/aB9n83KUsvJ30h82PgZ8BXWoZeBMwmNdH/t4ZDf4D0ZcJfgDNJGZ9P+nLH7Cmz+eabN12CdRlnykpwrqxuzpSV4FxZCc6V1c2Z6j1a8T581kskHQ3sGRHjGy6lJ0iaCFwMbBgRcxotZhUl6bmkL2NeHxFPuqnt5MmTRwNzN75le8a8c62nvD7rXjfeeCPbb79902VYF3GmrATnyurmTFkJzpWV4FxZ3Zyp7rFs2TKmTJkCsP6kSZPmtRvn5VbM7GlL0uuA9Uh/fbAZ8E3S8j5/abAsMzMzMzMzMzPrIl5uxVYJks6TtKDN4/NN12fFrEFamugG0nIrs0jLEj3WaFXWc575zGc2XYJ1GWfKSnCurG7OlJXgXFkJzpXVzZnqPZ5J3sMi4mj6X6f86egAYO0222Y/lYUMV15jXk3XsSqJiPOB85uuw2z11f0/l1YvZ8pKcK6sbs6UleBcWQnOldXNmeo9nkluq4SIuDsiZrR5rBJNcjNbdd17771Nl2BdxpmyEpwrq5szZSU4V1aCc2V1c6Z6j5vkZmZmZmZmZmZmZtaz3CQ3s67znL3WaLoE6zLPf/7zmy7BuowzZSU4V1Y3Z8pKcK6sBOfK6uZM9R43yc3MzDp44IEHmi7BuowzZSU4V1Y3Z8pKcK6sBOfK6uZM9R43yc3MzDpYsGBB0yVYl3GmrATnyurmTFkJzpWV4FxZ3Zyp3uMmuZmZWQdrrrlm0yVYl3GmrATnyurmTFkJzpWV4FxZ3Zyp3uMmuZmZWQdej87q5kxZCc6V1c2ZshKcKyvBubK6OVO9x01yMzOzDm666aamS7Au40xZCc6V1c2ZshKcKyvBubK6OVO9x01yMzMzMzMzMzMzM+tZbpKbmZl1sNFGGzVdgnUZZ8pKcK6sbs6UleBcWQnOldXNmeo9bpKbmZl1sNZaazVdgnUZZ8pKcK6sbs6UleBcWQnOldXNmeo9bpKbmZl1cPfddzddgnUZZ8pKcK6sbs6UleBcWQnOldXNmeo9bpKbmZmZmZmZmZmZWc9yk9zMzKyDsWPHNl2CdRlnykpwrqxuzpSV4FxZCc6V1c2Z6j1ukpuZmXUwe/bspkuwLuNMWQnOldXNmbISnCsrwbmyujlTvcdNcjMzsw7mzZvXdAnWZZwpK8G5sro5U1aCc2UlOFdWN2eq97hJbmZm1sHqq6/edAnWZZwpK8G5sro5U1aCc2UlOFdWN2eq97hJbrYKkXS0pGuarmNlSTpZ0llN12E2WNtss03TJViXcaasBOfK6uZMWQnOlZXgXFndnKne4ya5dQ1JIyQdIuk6SY9KeljSeZImNF3bcEgKSXu2vPxtYFID5SwnaZyksyU9kK/zTEm/lrRJk3WZlXTjjTc2XYJ1GWfKSnCurG7OlJXgXFkJzpXVzZnqPW6SW1eQJOB04Ejge8B2wETgTuCSfprNq6SIWBARDzV1fEnPBCYDs4E3kq7zfsA9wLpN1WVmZmZmZmZmZjZcbpJbt3gX8A7gAxHx04i4LSKmRMRHgLOBn0pa3sSVtLukf+WZ0A9KOrOybaSkb0i6U9JiSTMk7Z+37StpTvXAkvaUFJXnR0u6RtKBeR8LJZ0haf3KmB0lXZCPPVfSpZJeWtk+M/96Zp5RPrO678q41SQdKemuXOs1knarbB+b37+XpItzLVMkvXKY13kCsD5wQERcna/zxRFxSETclo85QtLPJN0maZGkmyUdPNBO83l8rvKeKZLeUdm+oaRTJc3K26dL2m+Y52A2ZBtuuGHTJViXcaasBOfK6uZMWQnOlZXgXFndnKne4ya5dYv3ANMi4px+th0HbATsCiDpLcCZwLnAS0jLl/yzMv4XwD7AJ0kzpQ8EFgyxnq1Ijfvdgd3ycU6sbB8FnAK8GtgJmA6cK2lU3r5j/rkfsFnleauDgUOBw4AXA+cDZ0vaumXcf5OWahkPTANOkzScu1DcB6wOvC3P3u/PasBdwDuB7YEvA1+V9K4B9vs54APAR4EXAt8FfiVp57z92LyvN5E+k48BD7bb2fz585k3b97yx+LFiwd7fmb9Wm+99ZouwbqMM2UlOFdWN2fKSnCurATnyurmTPUeN8mtW2wDTG2zbWplDMAXgNMj4qiImJpnnH8NQNI2pOb2hyLizIi4NSImR8Svh1jPWqRZ7ddExF+ATwB7S3oWQERcFBG/ioibImIq8BFgHWDnvH1W3s+ciLiv8rzVYcA3IuL0iLg5Ij4LXAN8qmXctyPiTxExDTgK2JzUyB+SiPg78FXgf4EH85rvn5G0aWXMY/naXplnmp8K/D/SdX0SSSOBz5Ou+fn5mp8M/Ir0BQXAGODqvM+ZEXFhmy9EANhhhx0YO3bs8sd3v/vdoZ6q2QruvPPOpkuwLuNMWQnOldXNmbISnCsrwbmyujlTvWc4M0nNnq7azWxuNR44aYBty4BLV7KWOyLi7srzK0hfSm0L3Jebyl8hrZu+CTCC1CQfM9gDSBoNPBu4rGXTZcC4lteurfx+b/65CXDTYI/XJyK+IOk7wOuAV5Bmf39e0msj4rpc238BHyKdz9rAmqTmfX+2Ip37BS2T09cErs6//wj4XV6S5v+AsyLi8nY1Xn/99ay22hPfAY4cOXKIZ2lmZmZmZmZmZr3CTXLrFtNIy3D0Z7vKGIBFA+xnoG0Aj/PkZvwaHd7Tn1NIS8AcDNwOLCY10tccxr4G47HK733rpw/7L0nyzUN/A/xG0udJzezDgA9K2pu0tMuhpHOaD3yG1FDvT9/fML0FuLtl2+J8vPMkbQ68mbRszmRJP4yIw/rb4ahRoxgxYsRwT8/sScaMGfT3V2aD4kxZCc6V1c2ZshKcKyvBubK6OVO9x8utWLc4Hdha0u79bDsUeAi4ID+/lrQOeX+uI/13sXOb7bOAUdWbgJJmn7caI+nZlec7kRrsN+fnE4ATIuLciLiB1AzeuGUfj5FmmPcrIuYB9+R9VU0Abmz3vrpFxBLgFqDvmkwALo+IE/PNPWcAWw6wixtJ5z8mIma0PJb/fVNEzIqIUyLifaTlZD5S5ITM+jF37tymS7Au40xZCc6V1c2ZshKcKyvBubK6OVO9x01y6xank27GeYqk/SWNlfRiSf8D7AEcEBGP5LHHAPtIOkbSdpJeJOmzABExkzTL++eS9pS0haSJlZtO/gNYSLoR5ZaS3gPs2089j+Zaxkl6DXACcEZE3Je3Twfen4//CuBUnjyLfSYwSdKzJLW7rfK3gM9KerekbSV9ndS0/97gLtvQSHqrpF/ln9vkYx5GmuH9hzxsOvAfkt6YxxxL+xuPEhHzSTPPvyvpg/m6vlTSJyR9MB/3y5L+U9JWkl4IvJX2a9Cb1c7/B8nq5kxZCc6V1c2ZshKcKyvBubK6OVO9x01y6woREaQbQ34VOIQ0Y/uvpBtUToyIsypjLwHeSWqeXwNcBLy8sruPAb8FTiSt2X0SeZZ0RMwG3kdqCl8H7AMc3U9JM4DfA+eS1tC+Fjiosn1/YEPgKuCXpCb6Ay37OJS0tMidPLE2d6sTgO8Ax+V6dgP2iIjpbcavrBtJXxIcR7p2fydd9wMi4pd5zP+Qzv3XpC8VNiJdy4F8CTgW+Byp+f1n0vIrt+XtS4Cvka7jX0jrxu9dxwmZDUZ1jXuzOjhTVoJzZXVzpqwE58pKcK6sbs5U71HqLZpZXSQdDewZEeMbLqXnTJ48eTQwd9y4cV6T3MzMzMzMzMysxy1btowpU6YArD9p0qR57cb5axEzM7MObrrppqZLsC7jTFkJzpXVzZmyEpwrK8G5sro5U73HTXKzHibpPEkL2jw+33R9Zk8Xjz/+eNMlWJdxpqwE58rq5kxZCc6VleBcWd2cqd6zetMFmHWbiDia/tcpfzo6AFi7zbbZT2UhZk9n66+/ftMlWJdxpqwE58rq5kxZCc6VleBcWd2cqd7jJrlZD4uIu5uuwWxV4P+DZHVzpqwE58rq5kxZCc6VleBcWd2cqd7j5VbMzMw6uOOOO5ouwbqMM2UlOFdWN2fKSnCurATnyurmTPUeN8nNzMzMzMzMzMzMrGe5SW5mZtbB8573vKZLsC7jTFkJzpXVzZmyEpwrK8G5sro5U73HTXIzM7MOFixY0HQJ1mWcKSvBubK6OVNWgnNlJThXVjdnqve4SW5mZtbBww8/3HQJ1mWcKSvBubK6OVNWgnNlJThXVjdnqve4SW5mZmZmZmZmZmZmPUsR0XQNZma1mDx58mhg7rhx4xgxYkTT5ZiZmZmZmZmZWYOWLVvGlClTANafNGnSvHbjPJPczMysg2nTpjVdgnUZZ8pKcK6sbs6UleBcWQnOldXNmeo9bpKbmZl1sHTp0qZLsC7jTFkJzpXVzZmyEpwrK8G5sro5U73HTXIzM7MORo8e3XQJ1mWcKSvBubK6OVNWgnNlJThXVjdnqve4SW5mZtbBM57xjKZLsC7jTFkJzpXVzZmyEpwrK8G5sro5U73HTXIzM7MOZs6c2XQJ1mWcKSvBubK6OVNWgnNlJThXVjdnqve4SW5mZmZmZmZmZmZmPctNcjMzsw6e85znNF2CdRlnykpwrqxuzpSV4FxZCc6V1c2Z6j1ukpuZmXXw6KOPNl2CdRlnykpwrqxuzpSV4FxZCc6V1c2Z6j1ukpuZmXXw0EMPNV2CdRlnykpwrqxuzpSV4FxZCc6V1c2Z6j1ukjdMUkja8+myHxsaSftKmlPDfvz5mZmZmZmZmZmZNcBN8n5Impiblg9LWqtl2455W9R0uM2A8/K+x+Z9j69p34OyMsdturlbqX2ZpOe0bNtM0tK8fWyhEn4NbFNo308iaW1JsyU9KGlkP9tn9uWz8rjrqarPrFu94AUvaLoE6zLOlJXgXFndnCkrwbmyEpwrq5sz1XvcJB/YfOBtLa/tD9yxsjuWtCZARNwXEYtXdn/G3cAHWl77YH59pfR9Vv28vkZELIqIB1b2GEPwduAG4CZgzzZjjiR9+dL3eMlTUplZF7v11lubLsG6jDNlJThXVjdnykpwrqwE58rq5kz1HjfJB3YK8KG+J5LWBvbOr1N5fSNJp0m6W9JCSddJ2qdlzCWSfiDpeEkPAufn16szsW/LP6/Or1+Sx+wo6YI8e3iupEslvXQoJyJpQ0mnSpolaZGk6ZL2W5njSpqZfz0zv29mfv1kSWe1HP/4vv3m5+/I12mRpIckXShp3aGcU4tTgP1aXtuPJ39WIyT9TNJt+dg3Szq4ZczJks6S9AVJ9wA3V2asvztfh0eB9/a33Iqk/5R0laRHJd0q6ShJq1e2by3pL3n7jZJ2HcJ57g/8Kj/2bzNmfv7ype8xq93OJK2Zc3lvrud2SZ+rbA9JH5N0Xr5et0p6R8s+XiTpospn+RNJ61W2XyLp+Jb3nCXp5Mrzg3ImH5V0v6TfVratJulzlc9sSmsNZqUtWbKk6RKsyzhTVoJzZXVzpqwE58pKcK6sbs5U73GTfGC/BF4jaUx+/nZgJnBVy7i1gH8DbwF2AH4C/FLSy1vGfRBYAkwAPtrP8frGv540A3iv/HwUqdn7amAnYDpwrqRRQziXY4HtgTcB2wEfAx5cyePumH/ul9/X93xAkjYDTgN+nmuZCPwe0BDOp9XZwIaSXp2P8WpgQ+CclnGrAXcB7yRdjy8DX5X0rpZxk4BtgV2Bt1Ze/zrwvVz3+a1FSHoN8Is8ZnvgQGBf4At5+2qkc10CvIKUg28M5gQlbQm8EjgjP14jafPBvHcAnwT2AN5FOt/3kjJedSzwO2AccCpwuqTtck3rkq7Dw6TP/52kHP1gsAVI+g/gBNIM+G2B3YC/VIZ8jvRXAh8FXgh8F/iVpJ3b7XP+/PnMmzdv+WPxYv+xhq2c9dZbr/MgsyFwpqwE58rq5kxZCc6VleBcWd2cqd6zeuchPe0B0nrh+5KaqR8iNXZXEBF3A9+uvPR9SW8kNR7/WXl9ekQcPsDx+mb8PhQR91X2f1F1kKSPAHOAnYE/DvJcxgBXR8SV+fnMlT1uRMySBDCn+r5B2IyUvd9HxO35teuG8P7+PEaaXf0h4G/556/y68tFxGPAUZWXbpP0StJndUbl9UeAAyJiCaS1z/Prx0fE7/sG5fOvOgr4ekT0zWC/VdKXgG8Cx5AayC8A3hgR9+R9fJ68Ln0HHwLOi4iH8/vOJ31BcXTLuG9I+krl+ecj4oQ2+xxD+vLjbxERwO39jPlNRPw0//6lPPP9E8BBwHtIXxJ9ICIeyXV9HDhH0mcj4v5BnNcY0vX+Y0TMzzVcnfc1Evg88PqIuCKPvzV/CXIgcGl/O9xhhx1YuHDh8ueHH344RxxxxCBKMevfJpts0nQJ1mWcKSvBubK6OVNWgnNlJThXVjdnqvd4JnlnPwf2lfR80izeU1sH5CU8vpSXD5ktaQHwRlLzr+rfwylA0qaSTsrLUcwF5gHr9bP/vvHnSVqQHzfkl38E7C3pGknflPSquo87BFOAycB1kn4j6cOSNlzJfUL6rN4p6VmkGc1P+kIDQNJ/Sfq30tIzC4CP8ORzuq6vQd7iyn5eqxoHHFm5/guAk4DNJK1DmoF+Z1+DPLuiuoP+Pj9JI0h/ifCrytBfkbLZ+t/xt4Dxlccv8j5+3FIXwMl5zM2STpD0hn7O6Yp+nm+Xf98OmNLXIM8uI/3bsm0/++rPBaTG+K2SfinpvflaAWwFrANc0FL7B4At2+3w+uuvZ+bMmcsfhxxyyCBLMeuf16OzujlTVoJzZXVzpqwE58pKcK6sbs5U7/FM8s7OIy2f8jPgnIh4qJ/Zw58BDgY+RZoR/QhwPNB6w8dHGJ5TgI3yMW4HFpMalf3eUBI4AFg7//4YQEScl5fmeDNpCZHJkn4YEYfVeNw+j/PkpVPW6PslIpbl2civAt5AmpX835JeERG3MUwRcZ2km0hLuUyNiOslja+OkbQ3adb/oflc5pM+v1e07K7dZ9XpM1yPNJv89/1se7TDe/s86fMjfenyHODXLfkbQVoa5oLKaw9GxIx+9nskK/7FAxFxlaQtSMvwvB44Q9KFEVHnmt+d8jBfaa37iaQ8fBk4WtKOpOsJaSmj1puwtl1DZdSoUYwYMWIlyzYzMzMzMzMzs17gJnkHEbFU0i+Aw0mNxP5MAP4QEb+C5etObwPcOMTD9c1cbu3uTQAOiohz8/6fB2w8QM2tzcS+12eRGt+nSPoracbxYSt53Mf6ed8s0trsVeOpLH2Sl/a4DLhM0pdJTfi3Ad9pd16D9HPgRNKa6/2ZAFweESf2vZDX+q7LVcC2bZrUSJoKPE/SZhFxb355p+qYNp/f/sDpwH+3vP6FvO2CJ72jRUQ8QFpCqPX1ecCvSQ343wJ/lvSMiJhdqe8XlbfsRF4OBZhKms2+bmU2+QRSY/zm/HwWaYkdYPms+B2Aiys1LAUuBC6UdAxpWZ/X5fNaDIyJiH6XVjF7Kmy22WadB5kNgTNlJThXVjdnykpwrqwE58rq5kz1HjfJB+dLpIbyQ222TwfekZcweRj4NLApQ2+SPwAsAnaTdBfwaETMzft/v6QrgdG5lkVD2XFuRP8buAEYSboZ5dQajjsTmCTpMmBxXi/7IuAzkj5Amq39PlJTtG+d6VeQZj//Xz72K4BnVupZGScBvyE1WfszHfhAXjP+NuD9pBtODnsGe4svA3+UdAfwW1KzeBywQ0R8kdQInkb6ouIzpOva2vhegaRnArsDe0TE9S3bfgGc2dLUHjRJnwbuJX02j5OWqbmPFa/fO3MG/ka6sefLSY15SMsPHZPP52jS5/h94JeV9cgvAr4j6S3ALaT/Pjao1PBW4Pmkm3U+TPprh9WAm/Ms828D381fPv0NWJ/UiJ9XWfvdrKilS5c2XYJ1GWfKSnCurG7OlJXgXFkJzpXVzZnqPV6TfBAiYklEPJhnP/fnK6QZxOcDl5CajGcN4zhLgU+Sbkh4D/CHvGl/YMN8jF8CJ9DPjOAOlgBfA64lNSOXAXvXcNxDScu33ElugkfE+cCxpJtV/gsYxYozkecBrwXOJTWMvwIcGhGDuXnlgCJiaf6s2v1r9j+kpVB+DfyDtJzMiW3GDuf455O+gHgD6dz/DhxCviFmRDxOmjG/Nummrj8lzQYfyAdIy7xM7mfbZNIXF+8bZsnzSX8lcWWudyzw5lxnn6NIWbk217JPRNwIEBELSUvBPCO//7e5po9X3v9z0l8w/IJ0o81bqcwiJzXk9yI106cCH83H6FtP/0ukPH0ub/8zafmVur7YMOto1qxZnQeZDYEzZSU4V1Y3Z8pKcK6sBOfK6uZM9R617/uaWa+TFMDbIuKspmsZjMmTJ48G5o4bN85rklutbrzxRrbffvumy7Au4kxZCc6V1c2ZshKcKyvBubK6OVPdY9myZUyZMgVg/UmTJs1rN84zyc3MzDrYZpttmi7BuowzZSU4V1Y3Z8pKcK6sBOfK6uZM9R43ye1pRdKCAR6vabo+M+tNt99+e9MlWJdxpqwE58rq5kxZCc6VleBcWd2cqd7jG3fa0834Abbd/VQVYUlEqOkazJ4OFi9e3HQJ1mWcKSvBubK6OVNWgnNlJThXVjdnqve4SW5PKxExo+kazMxarbPOOk2XYF3GmbISnCurmzNlJThXVoJzZXVzpnqPl1sxMzPrYLPNNmu6BOsyzpSV4FxZ3ZwpK8G5shKcK6ubM9V73CQ3MzPr4JZbbmm6BOsyzpSV4FxZ3ZwpK8G5shKcK6ubM9V73CQ3MzMzMzMzMzMzs57lJrmZmVkHm266adMlWJdxpqwE58rq5kxZCc6VleBcWd2cqd7jJrmZmVkHEdF0CdZlnCkrwbmyujlTVoJzZSU4V1Y3Z6r3uEluZmbWwQMPPNB0CdZlnCkrwbmyujlTVoJzZSU4V1Y3Z6r3uEluZmZmZmZmZmZmZj3LTXIzM7MOtt5666ZLsC7jTFkJzpXVzZmyEpwrK8G5sro5U73HTXIzM7MO7rrrrqZLsC7jTFkJzpXVzZmyEpwrK8G5sro5U73HTXIzM7MOFi1a1HQJ1mWcKSvBubK6OVNWgnNlJThXVjdnqve4SW5mZtbBWmut1XQJ1mWcKSvBubK6OVNWgnNlJThXVjdnqve4SW5mZtbB8573vKZLsC7jTFkJzpXVzZmyEpwrK8G5sro5U73HTXIzM7MOpk+f3nQJ1mWcKSvBubK6OVNWgnNlJThXVjdnqve4SW5mZmZmZmZmZmZmPctNcjMzsw422WSTpkuwLuNMWQnOldXNmbISnCsrwbmyujlTvcdNcjMzsw5WW83/c2n1cqasBOfK6uZMWQnOlZXgXFndnKne40/cepqkoyVd03QdJUlaR9LvJM2TFJI2aLqmwZA0cVWq17rbfffd13QJ1mWcKSvBubK6OVNWgnNlJThXVjdnqve4SW5tSRoh6RBJ10l6VNLDks6TNKHp2oYjN1z3bHn528CkBspZgaSXSPqNpPvztZ4u6SRJ29Sw+w8CrwFeBWwGbJivxfga9l3S5aR65zZdiJmZmZmZmZmZdS83ya1fkgScDhwJfA/YDpgI3Alc0k+zeZUUEQsi4qEma5D0VuDvwEjgvaRr/T5Sc/jYNu+RpNUHeYgtgakRcX1E3AfEStS65nDfO1QRsSQi7ouIfuvNX+L43zB7Smy55ZZNl2BdxpmyEpwrq5szZSU4V1aCc2V1c6Z6jxtM1s67gHcAH4iIn0bEbRExJSI+ApwN/FTSun2DJe0u6V95FvSDks6sbBsp6RuS7pS0WNIMSfvnbftKmlM9sKQ9JUXl+dGSrpF0YN7HQklnSFq/MmZHSRfkY8+VdKmkl1a2z8y/nplnUc+s7rsybjVJR0q6K9d6jaTdKtvH5vfvJeniXMsUSa8czkWWtA7w/4BzI2KPiLgwX+t/RMRhwIF5XN/SI2+S9G9gMfBqSVtK+kOegb4gfwavr+z/EuBQ4LX5/ZcAt+XNV1dea1ffJZJ+IOl4SQ8C5+fXd8h/VbAgH/uXkjbu530/yJ/Hg5KOzV++9I15v6QrJc2XdJ+k/5W0SWX7Csut9GVF0h6SbszXYMxwrrvZUPlP7axuzpSV4FxZ3ZwpK8G5shKcK6ubM9V73CS3dt4DTIuIc/rZdhywEbArgKS3AGcC5wIvIS1f8s/K+F8A+wCfJM2SPhBYMMR6tiI17ncHdsvHObGyfRRwCvBqYCdgOnCupFF5+475536kJTx2pH8Hk5rKhwEvJjWFz5a0dcu4/yYt1TIemAacNoSZ3VVvBDYGvtnfxoiY0/LS14EjSNfxWmA90nWfRLomfwbOkdTXPN4LOAm4gnTeewEvz9teX3ltIB8ElgATgI/mpvVFwNXAf5A+j02BM/p539J8vIOBTwMHVLavAXwJGAfsCYwFTu5QyzrAZ/N+Xgg80N+g+fPnM2/evOWPxYsXd9it2cAeeeSRpkuwLuNMWQnOldXNmbISnCsrwbmyujlTvWc4TT3rDdsAU9tsm1oZA/AF4PSIOKoyZgpAXlP7XcCuEXFh3nbrMOpZizSr/e68308Af5J0aF6S46LqYEkfAeYAOwN/jIhZeRLznLzkSDuHAd+IiNPz889K2gX4FPBflXHfjog/5WMdBdxAauTfNMTz6mu+D/Z9R0bEBZXns8nXOvuSpLcBewA/iIjZkhYCS/rOW9LoPPahDteiz/SIOLzviaQvAldHxOcrr30IuFPSNhExLb98J3BIXi7lZkkvAg4hNe2JiJ9XjnGrpE8C/5K0XkS0+xJlDeCgiJjSZjsAO+ywAwsXLlz+/PDDD+eII44YxKma9W/kyJFNl2BdxpmyEpwrq5szZSU4V1aCc2V1c6Z6j5vkNhB1HgKk2dQnDbBtGXDpStZyR1+DPLuC9JcQ2wL3SdoU+App3fRNgBGkWceDXo4jN4+fDVzWsuky0mznqmsrv9+bf27C0Jvkg73Gfa5c4c3SesDRwFtIs8JXB9ZmiMuQSHoNcF7lpQMj4tT8+79bho8DdpHUXyN7S9LMeoC/t6wnfgVwqKQREbFM0sty7eOADXniL1vGADe2KXUJK177fl1//fWsttoTfyjj/3GzlTV27NimS7Au40xZCc6V1c2ZshKcKyvBubK6OVO9x8utWDvTSEt69Ge7yhiARQPsZ6BtAI/z5EbxGh3e059TSA35g4FX5d8fAkrdaPKxyu99jeDh/PfUdw1fMMjxrX/v823gbcDngdeQzvs6hn7eV+b39j3OHuCY6wHntIwfT5oV/5fBHExpPfvzgXmkm5XuSDoPGLj2Re1u5Fk1atQoRo8evfzhJrmtrJtvvrnpEqzLOFNWgnNldXOmrATnykpwrqxuzlTvcZPc2jkd2FrS7v1sO5TUgO5b9uNa0prY/bmOlLOd22yfBYxS5SagpIZrqzGSnl15vhOpwd73r9YE4ISIODcibiDd1HHjln08Rpph3q+ImAfck/dVNYH2M5tX1v8BDwKH97ex76aVA5gAnBwRZ0bEdcB9pLW9B7Ik/1x+LSJiUUTMqDzmD/D+q0jrgc9sec+MiKg21F/R8r6dSEu3LCN9KbARcERE/DUibiLNxDczMzMzMzMzM3tKuUlu7ZxOuhnnKZL2lzRW0osl/Q9pvesDKg3RY4B9JB0jaTtJL5L0WYCImEma5f1zSXtK2kLSREnvyu/9B7AQ+KqkLSW9B9i3n3oezbWMy0uDnACcUVlTezrw/nz8VwCn8uRZ7DOBSZKeJWnDNuf9LdI65O+WtK2kr5Oa9t8b3GUbmnwNDwDeIulsSa/P1/o/JH0T+HGHXUwH9pI0XtI44H/p/N/1A6Rrs5ukTSWtP8Syfwg8g3Sz0h3z5/ZGSf9PUvVLiDGSvpOv4z7AJ3jiOt5BatZ/QtLzJe1Buomn2dPSxhu3fudmtnKcKSvBubK6OVNWgnNlJThXVjdnqve4SW79yktavAv4KulmizcDfwU2ByZGxFmVsZcA7yQ1z68BLgJeXtndx4DfAieS1uw+CVg3v3c28D7gzaRZ5/uQ1qluNQP4PXAuafb1tcBBle37k9a1vgr4JamJ/kDLPg4FdiXdUPLqNqd+AvAd4Lhcz27AHhExvc34lRYRfyAtEfMYqcl9E3AasD7wxQ5v/zTwMHA5aQmU80nXYKDjLQU+CRxImjn/hyHW2zfbfgTps7gOOJ50o9THK0N/QVof/Z+kxvr3gJ/kfcwifRnyTtIs/SNIN001e1pac81SKzdZr3KmrATnyurmTFkJzpWV4FxZ3Zyp3qNBLO9r1ihJRwN7RsT4hkuxQZJ0CXBNRHzqqTzu5MmTRwNzx40bx4gRbVfWMRuyG2+8ke23377pMqyLOFNWgnNldXOmrATnykpwrqxuzlT3WLZsGVOmTAFYf9KkSfPajfNMcjMzMzMzMzMzMzPrWW6Sm9VI0nmSFrR5fL7p+sxseLbYYoumS7Au40xZCc6V1c2ZshKcKyvBubK6OVO9x01ye9qLiKNXoaVWDiDd6LO/R6ebcHaNiJj4VC+1YlbSrFmzmi7BuowzZSU4V1Y3Z8pKcK6sBOfK6uZM9Z7Vmy7ArJtExN1N12Bm9VuwYEHTJViXcaasBOfK6uZMWQnOlZXgXFndnKne45nkZmZmHayxxhpNl2BdxpmyEpwrq5szZSU4V1aCc2V1c6Z6j5vkZmZmHWy11VZNl2BdxpmyEpwrq5szZSU4V1aCc2V1c6Z6j5vkZmZmHUydOrXpEqzLOFNWgnNldXOmrATnykpwrqxuzlTvcZPczMzMzMzMzMzMzHqWm+RmZmYdPOMZz2i6BOsyzpSV4FxZ3ZwpK8G5shKcK6ubM9V73CQ3MzPrYO211266BOsyzpSV4FxZ3ZwpK8G5shKcK6ubM9V73CQ3MzPr4O677266BOsyzpSV4FxZ3ZwpK8G5shKcK6ubM9V73CQ3MzMzMzMzMzMzs57lJrmZmVkHY8eObboE6zLOlJXgXFndnCkrwbmyEpwrq5sz1XvcJDczM+tg9uzZTZdgXcaZshKcK6ubM2UlOFdWgnNldXOmeo+b5GZmZh3Mmzev6RKsyzhTVoJzZXVzpqwE58pKcK6sbs5U73GT3MzMrIMRI0Y0XYJ1GWfKSnCurG7OlJXgXFkJzpXVzZnqPYqIpmswM6vF5MmTRwNzx40b5/9BMzMzMzMzMzPrccuWLWPKlCkA60+aNKntnwh4JrmZmVkHU6dObboE6zLOlJXgXFndnCkrwbmyEpwrq5sz1XvcJDczM+vAf3VldXOmrATnyurmTFkJzpWV4FxZ3Zyp3uMmuZmZWQcbbLBB0yVYl3GmrATnyurmTFkJzpWV4FxZ3Zyp3uMmuXUFSWMlhaTxNe7zaEnX1LU/M1t1jRo1qukSrMs4U1aCc2V1c6asBOfKSnCurG7OVO9xk9yKkLSepMck7d3y+um5mT225fWZko59SotchUn6sKQpkhZImiPpakmfq2w/WdJZw9ivvxgw68edd97ZdAnWZZwpK8G5sro5U1aCc2UlOFdWN2eq97hJbkVExALgSmBiy6aJwJ3V1yVtAWwOXDScY0laczjvW1VJ+hBwPHACMB6YAHwTWK+5qszMzMzMzMzMzFZNbpJbSRezYjN8O2At4Ees2DyfCCwGrsjj3i7pBkmL8wzzQ6s7za99SdIvJM0DftJ6YEkjJP1c0k2SxrQrUNJzJZ0mabakRyRdKekVbcbuKOkCSQ9KmivpUkkvrWxXnol9R679HkknVLYfJGm6pEcl3S/ptwNcu4HsAZwRET+LiBkRcUNEnBYRX8jHORr4IPCfedZ+SJqYt31D0jRJCyXdKulYSWvkbfsCRwHjKu/bN2/bQNJPJc2SNE/SRZLGDVSkpNUlnZBnuj+Uj31KdYa7pJF5zAP5uvxN0o5522qS7pL0sZb9vkTS45I2H+b1MxuyMWPa/jNiNizOlJXgXFndnCkrwbmyEpwrq5sz1XvcJLeSLga2lbRZfr4L8DfSjPGJlXG7AFdExKOSXgacAZwOvAg4Gji2r1lbcRgwBXgJsMIyLZJGAr8hzbJ+TUTc0V9xktYDLgWeQ2o8jyPNyG7338Uo4BTg1cBOwHTgXEl9C1W9HTgEOBDYGtgTuC4f6z9IM7+PBLYFdgP+0uY4ndwH7DRAk/jbpGv4Z2Cz/Lg8b5sP7AtsDxwMfDjXDPBr4Djghsr7fp23/QbYBHgT8DLgKmCypGcMUOdngfcC+5Fmu48mXZOqb5Ku2weBlwIzgPMlPSMiHgdOA97T8p73ApdFxO3tDjx//nzmzZu3/LF48eIByjTrbN68eU2XYF3GmbISnCurmzNlJThXVoJzZXVzpnqPm+RW0mXAEp5oiE8kNaX/DWycl1kB2JnUUAf4NDA5Io6NiGkRcTLwA+AzLfu+KCKOi4hbIuKWyuvrAX8CngnsEhGzBqjvPXncnhHxtzwr+4yIuKK/wRFxUUT8KiJuioipwEeAdXL9AGNIDewLI+KOiPhnRJxU2fYI8MeIuD0iro6IE550kME5BpgDzJR0c15//F2SVst1LgAWAYsj4r78WJK3fSUiLo+ImRFxDqmh/q68bRGwAFhaed8iSa8GXg68MyKujIjpEXFYruEdA9T5CeBrEXFmRNwEfDy/BwBJ6wIfAz4TEedFxI2kpv0iYP887FRgQt9fA+Rz3Du/3tYOO+zA2LFjlz+++93vdr6qZgOYM2dO0yVYl3GmrATnyurmTFkJzpWV4FxZ3Zyp3uMmuRUTEQuBf/FEk3xn4JKIWEqa2TxR0vNJDeS+Jvl2pOZ61WXA1pJGVF67ss1hTwPWBd4QEXP7XpT043yTywWSFuSXxwNXR8TswZyPpE0lnZSXTJkLzCM15fv+Buc3wNrArXnc2yStnrddANyet/1S0nslrTOY47aKiHsj4pWkmfbfA1YnzXD/c1+jfIBzeLekyyTdl6/DVyr1tzMun+dDLddwC2BLSWOqr0v6vKT1gU2Bf1bqXkb6gqTPlsAaVD7viHgsv2e7/PwaYCpPzCbfmTSj/TcDFXz99dczc+bM5Y9DDjlkoOFmHUlqugTrMs6UleBcWd2cKSvBubISnCurmzPVe1bvPMRspVwMvFvSC0kN5Kvy65eSlllZDVgI/GOI+32kzevnAu8DXsmKNwI9kjRrumrREI95CrARaZmS23liHfU1ASLiTknbAq8HdgVOBD4jaeeImJ/XL58IvAH4MnC0pB0jYs4Q6yAf73rgeuBEST8G/sqKs/JXIOmVpBnYRwHnA3NJs7IP7W98xXrAvTz5JqyQZobPIX3h0GdQXzoMwamkJvnX888/R8RDA71h1KhRjBgxYqAhZkOy3XbbNV2CdRlnykpwrqxuzpSV4FxZCc6V1c2Z6j2eSW6lXUxan/s9wN/ybGJI63HvTGq8Xta3HAhp1vCEln1MAKZV3juQHwFHAGdL6lsGhYh4IC+nMiMiZuSXrwXGd1hXu7WOEyLi3Ii4gdQk37g6ICIWRcQ5EfHJfG59M76JiKURcWFEHA68GBgLvG6Qx+7kxvxz3fxzCdDaJX4VcHtE/HffsilA67rm/b3vKuBZpGVYZrQ8HsznVX1tdp7Ffz+wY99O8l8CvLSy31vy8SZUxqyR33NjZdz/Ajvk9erfQYelVsxKuPnmm5suwbqMM2UlOFdWN2fKSnCurATnyurmTPUezyS30i4nNZM/Afx35fV/kpbN+E/ga5XXjwP+JelLpJtGvpK0lvVBgz1gRHw/N2T/KOlNEfG3NkNPAz4PnCXpc6TZ0i8B7mmzLvl04P2SriTdhPJbVGaj55uLjiDNil9ImtG+CLhd0luB55O+HHgYeDPpS6oh/6sr6UfAPaSZ8neRbrD5RWAWaWY7wEzgjXlm+0OkWePTgTGS9iYtg/MW4G0tu58JbCFpfN73fODCvN+zJB0OTAOend9/ZkS0W/rm+8DnJM0AbiJlYEMgACLikXwu35I0G7gDOJy0zvvP+nYSETMlXZ5fGwGcPfirZVaPZcsG8x2d2eA5U1aCc2V1c6asBOfKSnCurG7OVO/xTHIrKiIeBf4OjAIuqby+uPL6xZXXryLdSHJv0lIiXwaOzDfwHMpxjyctK3KupFe1GbOEtPTJA6RlWq4jzUJv9y/h/qQm71XAL4ET8nv7zCHdePIy0iz11wO756VB5gB7kRrbU4GPAvvkGelDdSGwE2ld7mnA74BHgUmVZUhOIjXgryQ1zydExNnAd0k3Qr2GNLP82JZ9/w74M+kzmZVrDFJT/y/A/8vHPJ00C/3+Aer8BumLiF+QmuwLSMu8PFoZc0Q+5i9J13Ur4I0R8XDLvk4lrY1+Zr7BqNlTavTo0U2XYF3GmbISnCurmzNlJThXVoJzZXVzpnqPUv/LzKysfFPRqcAZEfGlEseYPHnyaGDuuHHjvCa51eqRRx5h3XXX7TzQbJCcKSvBubK6OVNWgnNlJThXVjdnqnssW7aMKVOmAKw/adKkee3GeSa5mRUhaXNJH5a0jaQXkdaL34K0xrjZKuX2229vugTrMs6UleBcWd2cKSvBubISnCurmzPVe7wmuVmDJI1hxZtUtto+Iu54quqp2ePAvsC3AZGWz3l9RExtsigzMzMzMzMzM7MqN8nNmnUPML7D9lVSRNwJTGi6DrM6PPe5z226BOsyzpSV4FxZ3ZwpK8G5shKcK6ubM9V7vNyKWYMiYmlEzBjgsbTpGs0MFi5c2HQJ1mWcKSvBubK6OVNWgnNlJThXVjdnqve4SW5mZtbB7Nmzmy7BuowzZSU4V1Y3Z8pKcK6sBOfK6uZM9R43yc3MzMzMzMzMzMysZykimq7BzKwWkydPHg3MHTduHCNGjGi6HDMzMzMzMzMza9CyZcuYMmUKwPqTJk2a126cZ5KbmZl1MG3atKZLsC7jTFkJzpXVzZmyEpwrK8G5sro5U73HTXIzM7MOli71PXStXs6UleBcWd2cKSvBubISnCurmzPVe9wkNzMz62DUqFFNl2BdxpmyEpwrq5szZSU4V1aCc2V1c6Z6j5vkZmZmHWy88cZNl2BdxpmyEpwrq5szZSU4V1aCc2V1c6Z6j5vkZmZmHdx2221Nl2BdxpmyEpwrq5szZSU4V1aCc2V1c6Z6j5vkZmZmZmZmZmZmZtaz3CQ3MzPr4NnPfnbTJViXcaasBOfK6uZMWQnOlZXgXFndnKne4ya5mZlZB4sXL266BOsyzpSV4FxZ3ZwpK8G5shKcK6ubM9V73CQ3MzPr4KGHHmq6BOsyzpSV4FxZ3ZwpK8G5shKcK6ubM9V73CQ3MzMzMzMzMzMzs57lJrmZmVkHL3jBC5ouwbqMM2UlOFdWN2fKSnCurATnyurmTPUeN8nNzMw6uPXWW5suwbqMM2UlOFdWN2fKSnCurATnyurmTPUeN8nNzMw6WLJkSdMlWJdxpqwE58rq5kxZCc6VleBcWd2cqd7jJrk1TtJYSSFpfI37PFrSNXXtr2mSZkr6VIcxXXXOZk8n6667btMlWJdxpqwE58rq5kxZCc6VleBcWd2cqd7jJrk9iaT1JD0mae+W10/PzeyxLa/PlHTsU1rkKmglr+uOwE8q20LSnqVr7o+b8daLNt1006ZLsC7jTFkJzpXVzZmyEpwrK8G5sro5U73HTXJ7kohYAFwJTGzZNBG4s/q6pC2AzYGLhnMsSWsO532ropW5rhExKyIWPhV1mtmTeT06q5szZSU4V1Y3Z8pKcK6sBOfK6uZM9R43ya2di1mxabsdsBbwI1Zs8k4EFgNX5HFvl3SDpMV5JvSh1Z3m174k6ReS5lGZHV0ZM0LSzyXdJGlMuwIlPVfSaZJmS3pE0pWSXtFm7I6SLpD0oKS5ki6V9NLKduUZ0nfk2u+RdEJl+0GSpkt6VNL9kn47wLUbyHCv6/LlViTNzGPOzDPKZ1beh6T35/Fz8yz1UZVtIyWdIOmBfC5/k7RjZfu+kua07G9PSdG3HTgKGJePHfm1J6kso7O3pMvz8a6XtHNlzAhJP5N0m6RFkm6WdHBl+2vz7Ptntez7eEl/7e+4ZmZmZmZmZmZmQ+EmubVzMbCtpM3y812Av5FmNk+sjNsFuCIiHpX0MuAM4HTgRcDRwLH9NFEPA6YALwFWWKZF0kjgN8B44DURcUd/xUlaD7gUeA6wBzAO+CbtMz0KOAV4NbATMB04t9JAfjtwCHAgsDWwJ3BdPtZ/ACcARwLbArsBf2lznE6GfF372UdfU3s/YLPKc4Atc+1vzY+dgSMq279JOtcPAi8FZgDnS3rGIOv/NXAccEM+9mb5tYF8K7/nJaSm/zmSNsrbVgPuAt4JbA98GfiqpHcBRMRfgFuB9/ftTNIawHuBn7c74Pz585k3b97yx+LFiwd5emb922yzzToPMhsCZ8pKcK6sbs6UleBcWQnOldXNmeo9bpJbO5cBS3iicTuR1JT+N7BxXg4EUhP24vz7p4HJEXFsREyLiJOBHwCfadn3RRFxXETcEhG3VF5fD/gT8Exgl4iYNUB978nj9oyIv0XEjIg4IyKu6G9wRFwUEb+KiJsiYirwEWCdXD/AGOA+4MKIuCMi/hkRJ1W2PQL8MSJuj4irI+KEJx1kcIZzXVvPpe+6zImI+1qu02rAvhFxfUT8FfglMAlA0rrAx4DPRMR5EXEj8GFgEbD/YIqPiEXAAmBpPvZ9+bWB/CAifpev+8eAuX3Hi4jHIuKoiLgyIm6LiFOB/we8q/L+n5G+EOizO2n2/RntDrjDDjswduzY5Y/vfve7gzk9s7aWLl3adAnWZZwpK8G5sro5U1aCc2UlOFdWN2eq97hJbv3K61//iyeauTsDl0TEUuByYKKk55MayH3N3O1ITeCqy4CtJY2ovHZlm8OeBqwLvCEi5va9KOnHkhb0PfLL44GrI2L2YM5H0qaSTspLpswF5pGa8n3LufwGWBu4NY97m6TV87YLgNvztl9Keq+kdQZz3FbDvK5DMTMi5lee3wtskn/fEliDymcUEY8B/yR9dsPW5jPqs/yLi3yeV1aPJ+m/JP1b0qz83o/wxOcCcDKwlaSd8vN9gTMi4pF29Vx//fXMnDlz+eOQQw5ZmdMzY9asgb6zMxs6Z8pKcK6sbs6UleBcWQnOldXNmeo9bpLbQC4GdpH0QlID+ar8+qWk5UB2ARYC/xjifts1N88FXgy8suX1I0lN8b4HpNnPQ3FKfu/BwKvy7w8BawJExJ2kpVQOyvs+EfiLpDVy0/mlwD6kpvOXgSmSNhhiDX1KXVeAx1qeB0P77/xxQC2vrTGI9/X3GXUkaW/g26TZ4m/I7/1/5M8FICIeAM4B9pO0KfAmBlhqBWDUqFGMHj16+WPkyJGDLcnMzMzMzMzMzHqMm+Q2kItJ63O/B/hbRCzLr/+FNAN6InBZRCzJr08FJrTsYwIwrfLegfyItH722dWbO0bEA3k5lRkRMSO/fC0wfghraU8AToiIcyPiBtJNMTeuDoiIRRFxTkR8Mp/bK0lrqxMRSyPiwog4nNTIHwu8bpDHbjXU69qfx4ARA2zvzy2kpV6Wf0Z5fe8dgRvzS7OAUXlplj7jW/azpPXYbT6jPn0zwMmz819Gygq5lssj4sS8jM0M0oz3Vj8F3k2aZX5LRLT+xYJZUdtss03TJViXcaasBOfK6uZMWQnOlZXgXFndnKne4ya5DeRyUjP5E6RZzn3+SVrC4z9ZcUmQ44BJkr4kaRtJHwQ+TpopPCgR8X3gi8AfJb16gKGnkdYQP0vSBEnPl/R2Sa2z0PtMB94vaTtJrwBOpTIbXdK+kvaXtENe7uR9efvtkt4q6ZOSxkvaHPgA6b+dmwd7Xi2Gel37M5N0rZ8lacPBHDQvT/Ij4FuSdpO0PXASaW32n+Vh/yDNYv+qpC0lvYe0vEnrsbfI12PjfLPVgfxXXr7mBcAPgQ15Yib4dOA/JL0xZ+ZYVrwRaZ/zSUvkfJE009zsKXXHHf3eQ9hs2JwpK8G5sro5U1aCc2UlOFdWN2eq97hJbm1FxKPA34FRwCWV1xdXXr+48vpVpBsu7g1cT1qW5Mh8A8+hHPd44CjgXEmvajNmCWl5jgdIy7RcR5qF3m7G+v6k5uxVpJtZnpDf22cO6SaWl5Fmqb8e2D0iHsrb9gIuIs2A/iiwT56RPmRDva5tHArsCtwJXD2Ewx8B/I50Da4CtgLeGBEP5xpmk74geDPpmu4DHN2yj98Bf841zspjOh3zCGAK8Gpgj4h4MG/7H+D3wK9JDfqNSEvdrCAiHietTT4C+MUgz9WsNo8++mjTJViXcaasBOfK6uZMWQnOlZXgXFndnKneo4hougYz60KSxgK3AS+JiGtq2N/PgGdGxB7txkyePHk0MHfcuHGMGDHU1WjM2rvtttvYYostmi7DuogzZSU4V1Y3Z8pKcK6sBOfK6uZMdY9ly5YxZcoUgPUnTZo0r9241Z+6kszMhk7S+qS14d8DtG2Qm5X0nOc8p+kSrMs4U1aCc2V1c6asBOfKSnCurG7OVO/xcitmwyRpjKQFAzzGNF1jl/gD8H/AjyPigqaLsd40Y0br/WjNVo4zZSU4V1Y3Z8pKcK6sBOfK6uZM9R7PJDcbvnuA8R2296yImAmohv1MXOlizMzMzMzMzMzM2nCT3GyYImIp4K8WzXrApptu2nQJ1mWcKSvBubK6OVNWgnNlJThXVjdnqvd4uRUzMzMzMzMzMzMz61lukpuZmXVw//33N12CdRlnykpwrqxuzpSV4FxZCc6V1c2Z6j1ukpuZmZmZmZmZmZlZz3KT3MzMrIOtttqq6RKsyzhTVoJzZXVzpqwE58pKcK6sbs5U73GT3MzMrIO777676RKsyzhTVoJzZXVzpqwE58pKcK6sbs5U73GT3MzMrINFixY1XYJ1GWfKSnCurG7OlJXgXFkJzpXVzZnqPW6Sm5mZdbDWWms1XYJ1GWfKSnCurG7OlJXgXFkJzpXVzZnqPW6Sm5mZdTBmzJimS7Au40xZCc6V1c2ZshKcKyvBubK6OVO9x01yMzOzDqZNm9Z0CdZlnCkrwbmyujlTVoJzZSU4V1Y3Z6r3uEluZmZmZmZmZmZmZj3LTXIzM7MOnvnMZzZdgnUZZ8pKcK6sbs6UleBcWQnOldXNmeo9bpKbmZl1sPrqqzddgnUZZ8pKcK6sbs6UleBcWQnOldXNmeo9bpKbmZl1cO+99zZdgnUZZ8pKcK6sbs6UleBcWQnOldXNmeo9bpKbmZmZmZmZmZmZWc9yk9zMzKyD5z//+U2XYF3GmbISnCurmzNlJThXVoJzZXVzpnqPm+RmZmYd3H///U2XYF3GmbISnCurmzNlJThXVoJzZXVzpnqPm+RmgKSJkkLSBk3X0iRJY/N1GP8UHGumpE+VPo5ZHR555JGmS7Au40xZCc6V1c2ZshKcKyvBubK6OVO9x01yW0GlWdz3mCXpXEkvarq2wZC0j6Rlkn44xLdeDmwGzC1Q1gparu9cSZdJel3B4z1ljW+zbrXmmms2XYJ1GWfKSnCurG7OlJXgXFkJzpXVzZnqPW6SWzvbkprGbwRGAn+StCr8C7E/8E1gH0lrDfZNEbEkIu6LiChX2gr2I13fCcCDwB8lecGrIVhF8mhdwuvRWd2cKSvBubK6OVNWgnNlJThXVjdnqve4SW7tPJCbxlcBxwPPA17Qt1HSpyVdJ+kRSXdKOlHSetUdSJog6RJJCyU9LOl8SRvmbatJ+pyk2yQtkjRF0jtWpmBJWwCvAr4OTAP2atm+uaRzci2PSLpB0pvzthWWW5G0kaTTJN2d679O0j4t+7tE0gmSvilptqT7JB09yHLn5Ot7PfAxYG1g10EedzVJh0uaIWmxpDskfWEI12lDSafmvxJYJGm6pP3ajB0h6WeVz+lmSQe3jDlZ0lmSDpN0r6SHJP1Q0hqVMZvka78o7+u9/RxrA0k/zXXNk3SRpHGV7UdLukbSAZJuAx4d7Dmbraybbrqp6RKsyzhTVoJzZXVzpqwE58pKcK6sbs5U71m96QLs6U3S+sDe+emSyqbHgU8CtwHPB04kzeA+KL9vPDAZ+DlwMLAU2AUYkd//OeB9wEeB6cBrgV9JmhURlw6z3P2AP0XEXEm/Is0q/9/K9h8Ca+ZjPQJsDyxos6+1gH8D3wDmAW8Bfinploj4Z2XcB4HvAK8AXgmcLOmyiLhgCHUvyj/XHORxvwZ8GDgE+BtpRvoLGLxjSef+JtIs9q1ITfr+rAbcBbwTeIj0JcRPJN0bEWdUxu0C3Jt/bgX8GrgGOClvPxl4dt7+GHACsEnLsX5DuhZvIi17cyAwWdI2ETE7j9kKeDvpC5Bl7U5w/vz5rLbaE98Bjhw5kpEjR7YbbmZmZmZmZmZmPcxNcmvnLkkA6+bnZ0fE8q/RIuL4ytiZkr4I/JjcJAcOB66MiIMq424AkDQS+Dzw+oi4Im+7VdKrSY3RITfJJa0G7At8Ir90OnCcpC0i4rb82hjgdxFxXd8x2+0vIu4Gvl156fuS3gi8C6g2ya+NiGPy79MlfRyYBAyqSS5pHeArpIbvpZ2OK2kU6UuHj0fEKXnMLaRm+WCNAa6OiCvz85ntBkbEY8BRlZduk/TKXE+1Sf5wrmkZcJOkP5Guw0mStiE1vl8eEf/K570/MLXvzfmzfzmwSUQszi8fJmlP4B3AT/JrawIfiIhZA53gDjvswMKFC5c/P/zwwzniiCMGeovZgDbaaKOmS7Au40xZCc6V1c2ZshKcKyvBubK6OVO9x01ya+c1wEJgJ1JD+6PVjZJeT5oN/gJgNClLa0laJyIWAuNJM4P7sxWwDnBBbsT3WRO4epj17kpq6J8LEBEPSroA+BDwpTzmBOBHkt4AXEhqmF/b384kjSCd97uA5+TaRpKuSVXr++8lz5CW9GPSbHlyTdXlaE6TtIw0g3sWsH9EXDuI426Xn09uU/d5pM8O4PaIeGE/w34E/E7SS4H/A86KiMv721/e53+RruOYXO+apFniVTfkBnmfe4G+m71uR/pLgn/3bYyImyTNqYwfB6wHPNSSibWBLSvPb+/UIAe4/vrrnzST3GxlOENWN2fKSnCurG7OlJXgXFkJzpXVzZnqPW6SWzu3RcQc4GZJm5CWz3gtgKSxwB9JzdYvALOBVwM/IzVQF/LEEiL96WsWvwW4u2XbYoZnf+AZwKJKk3U14MWSjoqIxyPip5LOz8d9A/A5SYdGxPf72d9nSDO2PwVcR1qe5XjS+VU91vI8eGKt/yNZcVZ41SGkRv3clqZvp+MOdF0BDuCJpVNaa0sFRpwnaXPgzaQvFyZL+mFEHNY6VtLe+RwOBa4A5ucaX9EydKDrMBjrkRrrE/vZNqfy+yOD2dmoUaMYMWJE54Fmg3TPPfewwQYbNF2GdRFnykpwrqxuzpSV4FxZCc6V1c2Z6j1ukttg/JDUUH5bRJwJvIzUAD00Ih4HkPSulvdcS1pu4yie7EZSM3zMSqw/vpykjYD/JK2dfkNl0wjSMiRvAP4MEBF3kpaF+bGkvrW9+2uSTwD+EBG/ysdYDdgm1z4oEfEA8ECbzfdFxIxhHHc6qVE+CfhpP8ds/dKhXW2zgFOAUyT9FfgW8KQmea7n8og4se8FSVv2M24gN5H+rXkZ0LfcyrbABpUxVwHPApZGxMwh7t/MzMzMzMzMzGzY3CS3jiJioaSTgGMknQXMANYAPiHpHFIj9aMtb/sacJ2kE0lN6SWkmzb+Ji+F8m3gu7kJ/Ddg/byfeZW1tgfr/aSbSp4REVHdoP/f3p3H2VXX9x9/vQmbQAJGRUQRKJsoGlxwQyU2pS5Vf1jXalUo7q1aN0RtEaF1RcW1YkHAakUtiCuiRIMUKIpIAFkTCYtssoSEJRNIvr8/zhk4uZnJJJNzuMm9r+fjcR4z957vPedz574fN5PP/c73JD+lmmX+syRHAqcAlwMPruu5hLFdAbw8yTOp1tt+D/Bw1qBJPkmrPG8pZUmSTwKfSrIUOBN4GPC4Usoxq3OCJIdRLX3yB6qlW17Eqn8Or6/XRb+S6me9V/39aimlXJbkZ8BRSd5GtfTKkaw4K/40qpnqJyc5iOo12pZq1v/3G+unS32x44479rsEDRgzpS6YK7XNTKkL5kpdMFdqm5kaPmuyHIKG25eo1pZ+RSllLlXz9gPARcBrqdYnv08p5XKqGdwzqC50eTbVbO976yH/ChxeP+4Sqpnef8MaNF8b/oGqkVrG2Hci8JIkD6WaWf7lxvku5/4Ljfb6N6rZzacCc4AbgJMnUduaWp3zHg58BjiM6rl8h3od9NW0lOpDjAuAX1NdNPTV44w9CjipPsc5wEOAr4wzdlUOAK6juijrSVQX4rxvln392r2wrudYqtfmBGB74MZJnE9q1c0339zvEjRgzJS6YK7UNjOlLpgrdcFcqW1mavhk7L6iJK1/Zs+ePQ24fcaMGa5JrlZdfPHFPPaxj+13GRogZkpdMFdqm5lSF8yVumCu1DYzNTiWLVvG3LlzAbacNWvWovHGOZNckqQJbLihq5OpXWZKXTBXapuZUhfMlbpgrtQ2MzV8bJJrnZPkq0nuGGf7ar/rkzR8dt11136XoAFjptQFc6W2mSl1wVypC+ZKbTNTw8cmudZFhwB7jrMd0peKJA21iy/u+pq9GjZmSl0wV2qbmVIXzJW6YK7UNjM1fPzbAa1zSik30biooyRJkiRJkiR1xZnkkiRNYPr06f0uQQPGTKkL5kptM1PqgrlSF8yV2mamho9NckmSJrDZZpv1uwQNGDOlLpgrtc1MqQvmSl0wV2qbmRo+NsklSZrAtdde2+8SNGDMlLpgrtQ2M6UumCt1wVypbWZq+NgklyRJkiRJkiQNLZvkkiRNYPvtt+93CRowZkpdMFdqm5lSF8yVumCu1DYzNXxskkuSNIHbbrut3yVowJgpdcFcqW1mSl0wV+qCuVLbzNTwsUkuSdIEFi1a1O8SNGDMlLpgrtQ2M6UumCt1wVypbWZq+NgklyRpAlOmTOl3CRowZkpdMFdqm5lSF8yVumCu1DYzNXxSSul3DZLUitmzZ08Dbp8xY4b/oEmSJEmSJA25ZcuWMXfuXIAtZ82aNe6fCDiTXJKkCVxyySX9LkEDxkypC+ZKbTNT6oK5UhfMldpmpoaPTXJJkibgX12pbWZKXTBXapuZUhfMlbpgrtQ2MzV8bJJLkjSBrbbaqt8laMCYKXXBXKltZkpdMFfqgrlS28zU8LFJLknSBKZNm9bvEjRgzJS6YK7UNjOlLpgrdcFcqW1mavjYJJckaQJXX311v0vQgDFT6oK5UtvMlLpgrtQFc6W2manhY5NckiRJkiRJkjS0bJJLkjSB7bbbrt8laMCYKXXBXKltZkpdMFfqgrlS28zU8LFJLmklSfZLMi/JsiRHruZjjktycreVSf2xePHifpegAWOm1AVzpbaZKXXBXKkL5kptM1PDxya5pLEcBfwPsB3wr32uBYAkhyY5v991aDgtXLiw3yVowJgpdcFcqW1mSl0wV+qCuVLbzNTw2bDfBUhatyTZAtgaOLWUcl2/65HWBUn6XYIGjJlSF8yV2mam1AVzpS6YK7XNTA0fZ5JLuk+SmcDo3xT9MklJMjPJ/kkWJnlekkuS3JHkZ0keMY136kUAAB6QSURBVM5xXlSPn1Lf3rM+1icaY45O8s3G7TcluSbJXUm+n+Q9SRbW+/YHPgLMqI9T6vukB8Tuu+/e7xI0YMyUumCu1DYzpS6YK3XBXKltZmr42CSX1HQWsFv9/cuAR9T3AWwGvA94HfAc4NHAEeMc5wxgKvDE+vY+wM3AzMaYfYA5AEn2Br4KfB7YE/gF8OHG2O8AnwH+UNf0iPq+MS1evJhFixbdt42MjIz/jKXVcNlll/W7BA0YM6UumCu1zUypC+ZKXTBXapuZGj42ySXdp5SyFLipvnlrKeWG+j6AjYC3llLOLaWcB3wJmDXOcW4Hzuf+pvhM4HPAE5NskeSRwM7A6fX+dwCnlFKOKKVcXkr5CnBK43h3A3cA99Y13VDfN6Y99tiDHXbY4b7tc5/73Br+JKQVLVu2rN8laMCYKXXBXKltZkpdMFfqgrlS28zU8HFNckmr665SyvzG7eup1i4fz+nAzCSfAZ4NfBB4JfAsYDpwXSnlinrsbsD3ex7/G+BFkyn0oosuYoMN7v8McJNNNpnMYaT7TJs2rd8laMCYKXXBXKltZkpdMFfqgrlS28zU8LFJLml13dNzuwCrupLFHOAfgBnAPaWUS5PMoZpV/mDun0XeuqlTpzJlypSuDq8hNH369H6XoAFjptQFc6W2mSl1wVypC+ZKbTNTw8flViR1ZXRd8ndzf0N8DlWTfGb9/ajLgL16Ht97eylg51t9sWDBgn6XoAFjptQFc6W2mSl1wVypC+ZKbTNTw8cmuaROlFJuAy4AXsv9DfFfA08CdmXFmeRfBF6Y5D1JdknyFuAFVLPVRy0AdkyyZ5KHJnENFUmSJEmSJK01m+SSunQ61ezvOQCllFuBi4EbSin3XSq6lHIm8FbgPcBc4PlUF/pc0jjWicDPgF8Bfwb+rvvypcojH/nIfpegAWOm1AVzpbaZKXXBXKkL5kptM1PDxya5pBWUUhaWUlJKmdO477hSylY9404upaRxe/9Syn49Y/65Ptaljfv2LKU8Yozz/mcp5VGllM1KKS8FdgDmNfaPlFJeXkp5cH3M49b6yUqr6e677+53CRowZkpdMFdqm5lSF8yVumCu1DYzNXxskktaJyR5X5IZSXZO8g7gDcDx/a5LArj11lv7XYIGjJlSF8yV2mam1AVzpS6YK7XNTA2fDftdgCTVngocRHWxzz8C7yylHN3fkiRJkiRJkjToUkqZeJQkrQdmz549Dbh9xowZTJkypd/laICUUkgy8UBpNZkpdcFcqW1mSl0wV+qCuVLbzNTgWLZsGXPnzgXYctasWYvGG+dyK5IkTWDevHkTD5LWgJlSF8yV2mam1AVzpS6YK7XNTA0fm+SSJE3gnnvu6XcJGjBmSl0wV2qbmVIXzJW6YK7UNjM1fGySS5I0gS222KLfJWjAmCl1wVypbWZKXTBX6oK5UtvM1PCxSS5J0gQe9rCH9bsEDRgzpS6YK7XNTKkL5kpdMFdqm5kaPjbJJUmawJVXXtnvEjRgzJS6YK7UNjOlLpgrdcFcqW1mavjYJJckSZIkSZIkDS2b5JIkTWDbbbftdwkaMGZKXTBXapuZUhfMlbpgrtQ2MzV8bJJLkjSBpUuX9rsEDRgzpS6YK7XNTKkL5kpdMFdqm5kaPjbJJUmawM0339zvEjRgzJS6YK7UNjOlLpgrdcFcqW1mavjYJJckSZIkSZIkDS2b5JIkTWC33XbrdwkaMGZKXTBXapuZUhfMlbpgrtQ2MzV8bJJLkjSBBQsW9LsEDRgzpS6YK7XNTKkL5kpdMFdqm5kaPjbJJUmawMjISL9L0IAxU+qCuVLbzJS6YK7UBXOltpmp4WOTXJKkCWy++eb9LkEDxkypC+ZKbTNT6oK5UhfMldpmpoaPTXJJkiawzTbb9LsEDRgzpS6YK7XNTKkL5kpdMFdqm5kaPjbJJUmawPz58/tdggaMmVIXzJXaZqbUBXOlLpgrtc1MDR+b5JIkSZIkSZKkoWWTXJKkCfindmqbmVIXzJXaZqbUBXOlLpgrtc1MDR+b5FrvJTk0yfn9rmN9kKQk2a/fdUjrm+XLl/e7BA0YM6UumCu1zUypC+ZKXTBXapuZGj42yQdckilJ3p3kwiRLktyW5JQke/e7tskYp8l7BDCrD+WsJMkHkyxL8v5+1zIZSXaof8a92zf7XZvUTzfddFO/S9CAMVPqgrlS28yUumCu1AVzpbaZqeFjk3yAJQlwAnAI8Hlgd2AmcA0wZ1BmFJdS7iil3NLvOmr/AHyq/rpKSTbuvpxJ+yvgEY3tHydzkFQ2bLMwSZIkSZIkqU02yQfbK4GXA68vpRxdSrmylDK3lPJm4IfA0Uk2Hx2c5MVJflvPOL85yfcb+zZJ8skk1yQZSTIvyYH1vv2TLGyeOMl+SUrj9qFJzk/ylvoYdyX5bpItG2P2SvKL+ty3Jzk9yZMa+xfU336/nt28oHnsxrgNkhyS5Nq61vOTPL+xf3S29N8m+VVdy9wkz1ibH3aSfYAHUX0oMS3JM3v2j/4M3pjkSmBJfX+pfy4/rmu5JMkzkuycZE6SO5OclWSnnuP9vyTn1a/XH5N8pNmQTrJLkl/X+y9Osu8aPJ1bSik3NLbb62NukuQLSW6qj/u/SfZqnHNm/XxekOR3wAjwrPo1OajOzUiSq5N8uPG47eo8LExya5IfJNmh57i/qX8WC5OcmWT7NXg+0lrZZZdd+l2CBoyZUhfMldpmptQFc6UumCu1zUwNH5vkg+01wOWllB+Nse8zwEOAfQGS/A3wfeCnwBOpli/5TWP8N4C/A95JNSP9LcAda1jPzlSN+xcDz6/P85XG/qnA8cCzgKcDVwA/TTK13j/ajD2AanbzXoztXcB7gfcBTwBOBX6YpPcd7t+plmrZE7gc+PZazno+EPh2KeUe4Nv17V47Ay8D/rY+76h/pfoZ7wlcCvw3cBTwceApQIAvjQ5O8ux6/OeBx1K9HvsDH673bwCcBCwFnga8FfjkWjy3UZ+q638D8CRgHnBqkuk94z4BHEyVlQvq53EwcHhd72uAG+taN6J6jRYDzwb2psrWz5JsXL8mJwOnU72ezwC+BhTGsXjxYhYtWnTfNjIysvbPXEPtmmuu6XcJGjBmSl0wV2qbmVIXzJW6YK7UNjM1fFwGYbDtClwyzr5LGmOgaq6eUEr5SGPMXIAku1I1t/ctpZxW7/vjJOrZlGpW+5/q474D+EmS99azlX/ZHJzkzcBCYB/gx6WUPycBWFhKuWEV53kf8MlSygn17Q8keS7wz6y4bMgRpZSf1Of6CPAHqib2pWv6xJJMo5q1Pzob/ZvAGUneVUppfpiwMdXP4M89hzi2lPLd+lifBM4GDi+lnFrf93ng2Mb4jwCfKKUcX9/+Y5J/pWpif5RquZTHAM8rpVxXH+NDwCmr+ZTOStK8SsWzqT5IeBuwfynllPqYb6L6oOVA4NON8YeUUn5Rj5lK9cHFPzXqnQ/8b/39q6g+sHtjKaXUjzmA6rWfCZwLbEmVgfn1Y8bLNQB77LEHd9111323DzroIA4++ODVfOrSypYsWdLvEjRgzJS6YK7UNjOlLpgrdcFcqW1mavjYJB98Wc1xewL/uYp9y6hm8q6Nq0cb5LWzqZqjuwE3JHk48G9UjdGtgSnAZsCjV/cEdbN6W+DMnl1nAjN67rug8f319detmUSTnGqW/fxSylyAUsr5Sa6iagAf0xh31RgN8t5abqy/Xthz36ZJppVSFlE9l72bS5ZQ/bw2TbIZ1Qzua0Yb5LWzmydMcgpV83u0rsc1dr+KFRvR11C9ThvR+NmWUu5J8pv6fE3nNr7fHdgEmM3YZlB9OLG4/hBk1KbATqWUnyc5jmrG+i+A04DvllKuX+lItYsuuogNNrj/D2U22WST8YZKq+VBD3pQv0vQgDFT6oK5UtvMlLpgrtQFc6W2manhY5N8sF3Oys3LUbs3xgDcvYrjrGofwHJWbsZvNMFjxnI81RIw7wKuolrP+myq2ddduKfx/ejSHZNdguhA4HFJ7m3ctwHVBTybTfI716CWVdW3BdVs8pPGONbqftz5Rqo11HvPBVWDfV7zjp4G9kSaz3Oi/GwB/A547Rj7/gxQSjkgyReolul5FfBvSfYtpfzfWAecOnUqU6ZMWZN6pVV61KMe1e8SNGDMlLpgrtQ2M6UumCt1wVypbWZq+Lgm+WA7AdglyYvH2Pde4BbgF/XtC6jWIR/LhVRZ2Wec/X8GpqZxEVBWXG971KOTbNu4/XSqBvtl9e29gS+UUn5aSvkDVZP8oT3HuIdqxvSY6lnW19XHatobuHi8x62NJI+nWjd8JtXzHt1mAs9I8pgOTnsesFspZd4Y23KqWeDbJXlE4zFPbx6glPKnxmOuWo1zzqda4/y+n229nvherPpnewVVo3y8fJ0H7ALcNMZzub1R7+9LKR8vpTwTuIhqXXPpAXHFFVf0uwQNGDOlLpgrtc1MqQvmSl0wV2qbmRo+ziQfbCcArwCOT/J+quUuplGty/0S4BWllNEZvx8FZieZXz9uQ+CFpZRPllIWJDke+HqSd1KtVb49sHW9jvY5wF3Ax+rZvk+juohkryV1Le+r6/gC1bIZo+uLXwG8Lsm59f5Ps/Is5AXArCRnAiOllNvGOM+ngY/Wz+V8qgt97snYM5XbcCDwm1LKr3t3JPltvf/9LZ/zMODHSa4G/ofqw4YZwB6llH+hWpLkcu5/7adRXah00kopdyb5D+DTSW4FrgYOoloS55hVPG5Jvc76p5IspVqu5WHA40opxwDfovr5/CDJIcC1VPn6W6o11jcC3gz8kOoDkN2omurfWJvnI0mSJEmSJIEzyQdafRHEVwIfA95NNWP7DKoG5MxSysmNsXOoGuovoWos/xJ4auNwb6Nqxn6Fas3u/wQ2rx97K/D3wAupZp3/HXDoGCXNo1oe5KfAz6lmr7+9sf9A4MFUM4v/i6qJflPPMd5LdaHIa4Dfj/PUvwB8FvhMXc/zgZeUUlr/GDDJxlTP/cRxhpwIvL6ecd2a+oKeLwL+Gvgt8H9Ur/FV9f7lwEupllP5DXA01cVZ19bBVM/pv6hep52pLg461ocVTYdTvR6HUc1y/w7V+u+UUu4CnkPVdD+p3n8M1Zrki6g+gHlMfd7Lga8BXwaOauH5SKtl66237ncJGjBmSl0wV2qbmVIXzJW6YK7UNjM1fFL1UaVuJTkU2K+UsmefS9EAmz179jTg9hkzZrgmuVp1yy238JCHPKTfZWiAmCl1wVypbWZKXTBX6oK5UtvM1OBYtmwZc+fOBdhy1qxZi8Yb50xySZImcOONN/a7BA0YM6UumCu1zUypC+ZKXTBXapuZGj42yaUeSU5Jcsc424f6XZ8kSZIkSZKk9njhTj0gSimHMvY65euiN1Kt5T2WWx/IQiStG3baaad+l6ABY6bUBXOltpkpdcFcqQvmSm0zU8PHmeRSj1LKn0op88bZbJJLQ+j666/vdwkaMGZKXTBXapuZUhfMlbpgrtQ2MzV8bJJLGhhnnHHGxgAjIyP9LkUDZGRkhC9+8YvmSq0xU+qCuVLbzJS6YK7UBXOltpmp4WSTXNLAuOqqqzYBWLp0ab9L0QAZGRnh2GOP9RcktcZMqQvmSm0zU+qCuVIXzJXaZqaGk01ySZIkSZIkSdLQskkuSZIkSZIkSRpaG/a7AElqy5QpUwBYvnw5y5Yt63M1GhTLly9ns802M1dqjZlSF8yV2mam1AVzpS6YK7XNTA2W1X0NU0rpuBRJemAcddRRO+y8885X9rsOSZIkSZIkrVMeNWvWrD+Nt9OZ5JIGxs4773wV8Chgcb9rkSRJkiRJ0jphKnDdqgY4k1ySJEmSJEmSNLS8cKckSZIkSZIkaWjZJJckSZIkSZIkDS2b5JIkSZIkSZKkoWWTXNLASPKPSRYkWZLknCRP7XdNWjckeU6SHyW5LklJsl/P/iQ5LMn1Se5OclqSXXrGTE/yrSSLkixMckySLXrGPCHJGXUGr0ly0APw9NQHST6Y5LdJFie5KcnJSXbrGbNpki8nuSXJHUlOTPLwnjGPTvKTJHfVx/l0kg17xsxMcl6SkSTzkuz/ADxFPcCSvC3JBfV7zKIkZyd5QWO/edJaS3Jw/e/gkY37zJbWSJJD6xw1t0sb+82U1liSRyb5Zp2bu5NcmOQpjf3+vq41kqo30PteVZJ8ud7ve5VWYJNc0kBI8irgs8BHgScBc4FTk2zd18K0rticKhP/OM7+g4B3Am8FngbcSZWfTRtjvgU8DtgXeBHwHOBrozuTTAN+DlwFPBl4P3Bokje3+ky0rtgH+DLwdKpMbAT8PMnmjTGfA14MvKIevy1w0ujOJFOAnwAbA88E3gDsDxzWGLNjPeZXwJ7AkcDRSZ7XybNSP10LHEz1/vEU4JfAD5I8rt5vnrRWkuwFvAW4oGeX2dJk/AF4RGN7VmOfmdIaSfJg4EzgHuAFwGOB9wK3NYb5+7rW1F6s+D61b33/9+qvvldpRaUUNzc3t/V+A84BvtS4vQHwJ+Dgftfmtm5tQAH2a9wOcD3wvsZ9WwJLgFfXt3evH/eUxpjnA8uBbevbbwNuBTZujPkEcGm/n7PbA5Krh9UZeU4jQ0uBlzfGPKYe8/T69guAZcDDG2PeCtw+miPgk8BFPec6AfhZv5+z2wOSq1uBA82T29puwBbA5cBfAXOAI+v7zZbbZPJ0KHD+OPvMlNtkMvUJ4IxV7Pf3dbc2cnYkMK/Ok+9VbittziSXtN5LsjHVTIDTRu8rpSyvbz+jX3VpvbEjsA0r5ud2qg9eRvPzDGBhKeXcxuNOo/ql+2mNMb8upSxtjDkV2K2eHaPBtmX99db665OpZpc3c3UpcDUr5urCUsqNjeOcCkyjmgU1OuY0VnQqvrcNtCRTkrya6q9gzsY8ae19GfhJKaX39TdbmqxdUi1j98d6eYtH1/ebKU3GS4Bzk3yvXtLi90ne1Njv7+taK3XP4O+Br5eqk+17lVZik1zSIHgoMAW4sef+G6l+mZJWZTQjq8rPNsBNzZ2llHupGqLNMWMdo3kODaAkG1DNTDmzlHJRffc2wNJSysKe4b25migz442ZluRBa1e51jVJHp/kDmAE+Crw0lLKxZgnrYX6A5cnAR8cY7fZ0mScQ7XkwPOpZubuCJyRZCpmSpPzF1RZugJ4HvAfwBeSvKHe7+/rWlv7AVsBx9W3fa/SSjaceIgkSZJW4cvAHqy4Hqs0GZdRrWe5JfBy4Pgk+/S1Iq3XkmwHfB7Yt5SypN/1aDCUUk5p3LwgyTlUazy/Eri7P1VpPbcBcG4p5UP17d8n2YNqaYvj+1eWBsiBwCmllOv6XYjWXc4klzQIbqZeK6zn/ocDNzzw5Wg9M5qRVeXnBmCFi8DWVzWf3jNmrGM0z6EBk+RLVBeGem4p5drGrhuAjZNs1fOQ3lxNlJnxxiwqpdiIGDCllKWllHmllN+VUj5IdcHhd2GeNHlPpvr367wk9ya5l+riZO+sv78Rs6W1VM/EvBzYGd+vNDnXAxf33HcJMLqMj7+va9KSbE91TY6jG3f7XqWV2CSXtN6r15T7HTBr9L56+YNZVGu5SqtyJdUvN838TKNau3A0P2cDWyV5cuNxf0n17+g5jTHPSbJRY8y+wGWllNs6ql19ksqXgJcCf1lKubJnyO+Ae1gxV7tR/WevmavHJ2n+h25fYBH3/0fx7OYxGmN8bxsOGwCbYJ40ebOBx1P9hcLodi7wrcb3ZktrJckWwE5UjU7frzQZZwK79dy3K9VfKIC/r2vtHEC1FM9PGvf5XqWV9fvKoW5ubm5tbMCrqK5u/gaqK5sfBdxG40rUbsO7AVtwf3OgAO+uv390vf8DdV5eQtVMOBn4I7Bp4xinAOcBTwX2ppox9d+N/VtS/fL+DaoLubwKuBN4c7+fv1snmfoKsJBqRuY2je1BjTH/QfWfu+dSzeY8CzirsX8KcCHVxX1mUK3BeRPwscaYHescfQp4DPB24F7gef3+Gbi1nqmPA88Bdqjfhz5OdbGxfc2TW8tZmwMc2bhtttzWNENH1P/+7QA8E/gF8GfgYWbKbZKZ2ouqYfkhqr9IeE39+r+2Mcbf190mk60N6vejT4yxz/cqtxUz0e8C3Nzc3NragH+q/5EboZot8LR+1+S2bmzATKrmeO92XL0/wGH1L81LqK5QvmvPMaYD/w0sBm4Hvg5s0TPmCcAZ9TGuBT7Q7+fu1lmmxspTAfZvjNmUar3yW+tfnk8Ctuk5zvbAT4G7qBoMRwAb9oyZCfy+fm+b3zyH2+BswDHAgvp1vql+H9rXPLm1vbFyk9xsua1phk4Arqtf62vr2zuZKbe1zNWLqBqSS6iWWnlTz35/X3ebTK7+mup39F3H2Od7ldsKW+oXVJIkSZIkSZKkoeOa5JIkSZIkSZKkoWWTXJIkSZIkSZI0tGySS5IkSZIkSZKGlk1ySZIkSZIkSdLQskkuSZIkSZIkSRpaNsklSZIkSZIkSUPLJrkkSZIkSZIkaWjZJJckSZKkNZRkryRnJbkzSUmyZ79r6pXkuCQLWjzenCRz2jqeJEnSusImuSRJkiStgSQbAd8DpgPvBl4HXDXJY709yf5rUcu2SQ5tq0mf5LH18XZo43iSJEnrg5RS+l2DJEmSJK03kjwGuAR4Uynl6LU81kXAzaWUmZN8/FOA3wIHlFKO69m3EbBBKWVkDY73cqoPAJ5bSpnTs29jgFLK0snUKkmStK7asN8FSJIkSdJ6Zuv668J+FjGRUso9LR/P5rgkSRpILrciSZIkSaspyXHA6fXN79Xrkc8ZZ+w2SY5Ncm2SkSTXJ/nB6FIm9XrhjwP2qY9z37GSTE9yRJILk9yRZFGSU5LMaBx/JtUscoBjG8fYf7TW3jXJk7w6ye+SLK6PeWGSd9X79qeaRQ7wq8bxZtb7V1qTPMmm9fIslydZUj/Hk5LstDrnlCRJWhc4k1ySJEmSVt9RwJ+ADwFfoGpS3zjO2BOpmuBfBBZQzUDfF3h0ffuf6313AP9eP2b0WH8B7EfVtL4SeDjwFuD0JI8tpVxHteTLIcBhwNeAM+rHnjVWMUn2Bb4NzAY+UN+9O7A38Hng1/Vzeifwsfr4NL72Hm8K8GNgFnBCfYyp9XPcA5i/GueUJEnqO9cklyRJkqQ1UM+s/hXwilLK/4wzZivgNuD9pZQjVnGsMdckT7IJcE8pZXnjvh2AS4F/L6UcXt+3qjXJjwNmllJ2qG8fCRwATC+lLBunnlWtST4HYLTWJAcAXwfeU0r5XM/YlFLK6pxTkiSp31xuRZIkSZLadzewFJiZ5MFr+uBSyshogzzJlCQPoZpxfhnwpEnWtBDYnGqmdxteBtxMNRt+BeX+2Vhtn1OSJKl1NsklSZIkaZKSbFyvPd7cppRSRqiWF3kBcGOSXyc5KMk2q3ncDZK8O8kVwAhVM/rPwBOALSdZ7leAy4FT6nXSv57k+ZM8FsBOwGWllHsfwHNKkiS1zia5JEmSJE3eM4Hre7btAEopRwK7Ah8ElgCHA5ckeeJqHPdDwGep1gn/e+B5VLOx/8Ak/x9XSrkJ2BN4CfBD4LlUzevjJ3O8dfWckiRJa8oLd0qSJEnS5M1l5aVEbhj9ppQyH/gM8JkkuwDnA++lanwDjHeRqJcDvyqlHNi8s17r/ObGXWt0kalSylLgR8CPkmxANdP7LUkOL6XMW8PjzQeelmSjUso9a3FOSZKkvnImuSRJkiRNUinltlLKaT3bkiSbJdm0Z/h8YDGwSeO+O4Gtxjj0MiDNO5K8Anhkz7g7669jHWMF9brmzdqXAxfUN0drWu3jAScCDwX+aYxzZQ3OKUmS1FfOJJckSZKk9u0KzE7yXeBi4F7gpcDDgRMa434HvC3JvwDzgJtKKb8EfgwckuRY4Czg8cBrgT/2nGc+1cUx35pkMVWT+5xSypVj1HR0kunAL4Frge2Bd1DNbr+kHnM+VYP+A0m2pFoP/Zf1sim9vgG8HvhskqcCZ1BdpPOvqGaL/2A1zylJktRXNsklSZIkqX3XAN8GZgGvo2qSXwq8spRyYmPcYVSN44OAqcDpVA3lj1E1nF8DvAo4D/gb4BPNk5RS7knyBuDjwFep/o93ADBWk/ybwJuBt1PNFL8B+A5waD3Dm1LKDUneSrWO+jHAFKp1xFdqkpdSliV5IfDhus6XAbcA/wtcuLrnlCRJ6reUskZL2EmSJEmSJEmSNDBck1ySJEmSJEmSNLRskkuSJEmSJEmShpZNckmSJEmSJEnS0LJJLkmSJEmSJEkaWjbJJUmSJEmSJElDyya5JEmSJEmSJGlo2SSXJEmSJEmSJA0tm+SSJEmSJEmSpKFlk1ySJEmSJEmSNLRskkuSJEmSJEmShpZNckmSJEmSJEnS0LJJLkmSJEmSJEkaWjbJJUmSJEmSJElD6/8DRcIwZzlTulIAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 1500x2000 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,20),dpi=100)\n",
    "sns.barplot(y=feature_importance.feature,x=feature_importance['f-statistics'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 205,
   "metadata": {},
   "outputs": [],
   "source": [
    "# maybe choose the first 28 features\n",
    "chosen=list(feature_importance.feature[0:29].values)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# PCA after feature selection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 206,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.93957867 0.03522914]\n"
     ]
    }
   ],
   "source": [
    "dataX_pca = dataX[chosen].copy()\n",
    "variance_explained = 0.95\n",
    "pca = PCA(variance_explained)\n",
    "principalComponents = pca.fit(dataX_pca)\n",
    "print(principalComponents.explained_variance_ratio_)\n",
    "principalComponents = principalComponents.transform(dataX_pca)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 207,
   "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>0</th>\n",
       "      <th>1</th>\n",
       "      <th>income</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.775</td>\n",
       "      <td>-2.983</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>11.786</td>\n",
       "      <td>-2.725</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-0.245</td>\n",
       "      <td>1.094</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>14.754</td>\n",
       "      <td>3.192</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-10.211</td>\n",
       "      <td>-3.013</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29402</th>\n",
       "      <td>-16.252</td>\n",
       "      <td>-0.031</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29403</th>\n",
       "      <td>-11.219</td>\n",
       "      <td>-1.976</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29404</th>\n",
       "      <td>1.775</td>\n",
       "      <td>1.096</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29405</th>\n",
       "      <td>19.741</td>\n",
       "      <td>1.257</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29406</th>\n",
       "      <td>-16.283</td>\n",
       "      <td>1.095</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>29407 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            0      1  income\n",
       "0       0.775 -2.983       0\n",
       "1      11.786 -2.725       0\n",
       "2      -0.245  1.094       0\n",
       "3      14.754  3.192       0\n",
       "4     -10.211 -3.013       0\n",
       "...       ...    ...     ...\n",
       "29402 -16.252 -0.031       0\n",
       "29403 -11.219 -1.976       0\n",
       "29404   1.775  1.096       1\n",
       "29405  19.741  1.257       0\n",
       "29406 -16.283  1.095       0\n",
       "\n",
       "[29407 rows x 3 columns]"
      ]
     },
     "execution_count": 207,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "principalDf = pd.DataFrame(data = principalComponents)\n",
    "# # Concatenate dataframe with 'shares_bin2' column\n",
    "df_pca = pd.merge(principalDf, df[['income']].reset_index(drop='index'),right_index=True,left_index=True)\n",
    "df_pca"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 208,
   "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>0</th>\n",
       "      <th>1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>PC0</td>\n",
       "      <td>Age</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>PC1</td>\n",
       "      <td>Education-num</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     0               1\n",
       "0  PC0             Age\n",
       "1  PC1   Education-num"
      ]
     },
     "execution_count": 208,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "n_pcs=pca.components_.shape[0]\n",
    "most_important = [np.abs(pca.components_[i]).argmax() for i in range(n_pcs)]\n",
    "initial_feature_names  = chosen\n",
    "most_important_names = [initial_feature_names[most_important[i]] for i in range(n_pcs)]\n",
    "dic = {'PC{}'.format(i): most_important_names[i] for i in range(n_pcs)}\n",
    "pd.DataFrame(dic.items())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# PCA with no feature selection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 213,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0.93122718 0.03496091]\n"
     ]
    }
   ],
   "source": [
    "dataX_pca_nofs = dataX.copy()\n",
    "variance_explained = 0.95\n",
    "pca = PCA(variance_explained)\n",
    "principalComponents = pca.fit(dataX_pca_nofs)\n",
    "print(principalComponents.explained_variance_ratio_)\n",
    "principalComponents = principalComponents.transform(dataX_pca_nofs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 210,
   "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>0</th>\n",
       "      <th>1</th>\n",
       "      <th>income</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.781</td>\n",
       "      <td>-3.015</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>11.794</td>\n",
       "      <td>-2.747</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>-0.247</td>\n",
       "      <td>1.095</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>14.751</td>\n",
       "      <td>3.198</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>-10.220</td>\n",
       "      <td>-2.971</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29402</th>\n",
       "      <td>-16.259</td>\n",
       "      <td>-0.012</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29403</th>\n",
       "      <td>-11.223</td>\n",
       "      <td>-1.970</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29404</th>\n",
       "      <td>1.777</td>\n",
       "      <td>1.086</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29405</th>\n",
       "      <td>19.742</td>\n",
       "      <td>1.248</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29406</th>\n",
       "      <td>-16.283</td>\n",
       "      <td>1.091</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>29407 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            0      1  income\n",
       "0       0.781 -3.015       0\n",
       "1      11.794 -2.747       0\n",
       "2      -0.247  1.095       0\n",
       "3      14.751  3.198       0\n",
       "4     -10.220 -2.971       0\n",
       "...       ...    ...     ...\n",
       "29402 -16.259 -0.012       0\n",
       "29403 -11.223 -1.970       0\n",
       "29404   1.777  1.086       1\n",
       "29405  19.742  1.248       0\n",
       "29406 -16.283  1.091       0\n",
       "\n",
       "[29407 rows x 3 columns]"
      ]
     },
     "execution_count": 210,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "principalDf = pd.DataFrame(data = principalComponents)\n",
    "# # Concatenate dataframe with 'shares_bin2' column\n",
    "df_pca_nofs = pd.merge(principalDf, df[['income']].reset_index(drop='index'),right_index=True,left_index=True)\n",
    "df_pca_nofs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 211,
   "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>0</th>\n",
       "      <th>1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>PC0</td>\n",
       "      <td>Marital-status_ Married-civ-spouse</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>PC1</td>\n",
       "      <td>Marital-status_ Never-married</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     0                                    1\n",
       "0  PC0   Marital-status_ Married-civ-spouse\n",
       "1  PC1        Marital-status_ Never-married"
      ]
     },
     "execution_count": 211,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "n_pcs=pca.components_.shape[0]\n",
    "most_important = [np.abs(pca.components_[i]).argmax() for i in range(n_pcs)]\n",
    "initial_feature_names  = chosen\n",
    "most_important_names = [initial_feature_names[most_important[i]] for i in range(n_pcs)]\n",
    "dic = {'PC{}'.format(i): most_important_names[i] for i in range(n_pcs)}\n",
    "pd.DataFrame(dic.items())\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Comparison"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import GridSearchCV\n",
    "import sklearn.metrics as metrics\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.metrics import classification_report\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn import decomposition, ensemble\n",
    "from sklearn import model_selection, preprocessing, linear_model, naive_bayes, metrics, svm\n",
    "import xgboost\n",
    "import lightgbm as lgb\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 464,
   "metadata": {},
   "outputs": [],
   "source": [
    "def model(X_train, X_test, y_train, y_test):\n",
    "    models = {'knn': KNeighborsClassifier(),\n",
    "            'lr':linear_model.LogisticRegression(random_state=123),\n",
    "            'rf':ensemble.RandomForestClassifier(random_state=123),\n",
    "            'xgboost':xgboost.XGBClassifier(random_state=123),\n",
    "            'lighGBM':lgb.LGBMClassifier(random_state=123)\n",
    "            }\n",
    "\n",
    "    y_predicts = pd.DataFrame()\n",
    "    for name, model in models.items():\n",
    "        clf = model.fit(X_train, y_train)\n",
    "        y_train_pred = clf.predict_proba(X_train)\n",
    "        auc = metrics.roc_auc_score(y_train, y_train_pred[:,1])\n",
    "        print('Model: {} | train AUC: {:.4f}'.format(name, auc))\n",
    "        y_test_pred = clf.predict_proba(X_test) \n",
    "        auc_test = metrics.roc_auc_score(y_test, y_test_pred[:,1])\n",
    "        print('Test: Model: {} | Test AUC: {:.4f}'.format(name, auc_test))\n",
    "        y_predicts.loc[name,'train AUC']=auc\n",
    "        y_predicts.loc[name,'test AUC']=auc_test\n",
    "    return y_predicts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 465,
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train, x_test, y_train, y_test = train_test_split(dataX, dataY,\n",
    "                                                    stratify=dataY, \n",
    "                                                  random_state=2017, \n",
    "                                                  test_size=0.3, shuffle=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 466,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: knn | train AUC: 0.9378\n",
      "Test: Model: knn | Test AUC: 0.8463\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:814: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: lr | train AUC: 0.8947\n",
      "Test: Model: lr | Test AUC: 0.8928\n",
      "Model: rf | train AUC: 1.0000\n",
      "Test: Model: rf | Test AUC: 0.8903\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/lib/python3.8/site-packages/xgboost/data.py:173: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
      "  from pandas import MultiIndex, Int64Index\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: xgboost | train AUC: 0.9628\n",
      "Test: Model: xgboost | Test AUC: 0.9157\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/lib/python3.8/site-packages/xgboost/data.py:173: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
      "  from pandas import MultiIndex, Int64Index\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: lighGBM | train AUC: 0.9458\n",
      "Test: Model: lighGBM | Test AUC: 0.9181\n"
     ]
    }
   ],
   "source": [
    "result_no=model(x_train, x_test, y_train, y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 327,
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train_fs, x_test_fs, y_train_fs, y_test_fs = train_test_split(dataX[chosen], dataY,\n",
    "                                                    stratify=dataY, \n",
    "                                                  random_state=2017, \n",
    "                                                  test_size=0.3, shuffle=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 467,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: knn | train AUC: 0.9352\n",
      "Test: Model: knn | Test AUC: 0.8396\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:814: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: lr | train AUC: 0.8921\n",
      "Test: Model: lr | Test AUC: 0.8910\n",
      "Model: rf | train AUC: 0.9952\n",
      "Test: Model: rf | Test AUC: 0.8758\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/lib/python3.8/site-packages/xgboost/data.py:173: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
      "  from pandas import MultiIndex, Int64Index\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: xgboost | train AUC: 0.9495\n",
      "Test: Model: xgboost | Test AUC: 0.9130\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/lib/python3.8/site-packages/xgboost/data.py:173: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
      "  from pandas import MultiIndex, Int64Index\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: lighGBM | train AUC: 0.9388\n",
      "Test: Model: lighGBM | Test AUC: 0.9172\n"
     ]
    }
   ],
   "source": [
    "result_fs=model(x_train_fs, x_test_fs, y_train_fs, y_test_fs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 329,
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train_pca, x_test_pca, y_train_pca, y_test_pca = train_test_split(df_pca.drop('income',axis=1), df_pca['income'],\n",
    "                                                    stratify=df_pca['income'], \n",
    "                                                  random_state=2017, \n",
    "                                                  test_size=0.3, shuffle=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 468,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: knn | train AUC: 0.9172\n",
      "Test: Model: knn | Test AUC: 0.7996\n",
      "Model: lr | train AUC: 0.7729\n",
      "Test: Model: lr | Test AUC: 0.7643\n",
      "Model: rf | train AUC: 0.9947\n",
      "Test: Model: rf | Test AUC: 0.8250\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/lib/python3.8/site-packages/xgboost/data.py:173: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
      "  from pandas import MultiIndex, Int64Index\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: xgboost | train AUC: 0.9237\n",
      "Test: Model: xgboost | Test AUC: 0.8536\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/lib/python3.8/site-packages/xgboost/data.py:173: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
      "  from pandas import MultiIndex, Int64Index\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: lighGBM | train AUC: 0.8870\n",
      "Test: Model: lighGBM | Test AUC: 0.8518\n"
     ]
    }
   ],
   "source": [
    "result_fs_pca=model(x_train_pca, x_test_pca, y_train_pca, y_test_pca)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 331,
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train_pca_nofs, x_test_pca_nofs, y_train_pca_nofs, y_test_pca_nofs = train_test_split(df_pca_nofs.drop('income',axis=1), df_pca_nofs['income'],\n",
    "                                                    stratify=df_pca_nofs['income'], \n",
    "                                                  random_state=2017, \n",
    "                                                  test_size=0.3, shuffle=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 469,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: knn | train AUC: 0.9167\n",
      "Test: Model: knn | Test AUC: 0.7934\n",
      "Model: lr | train AUC: 0.7727\n",
      "Test: Model: lr | Test AUC: 0.7641\n",
      "Model: rf | train AUC: 1.0000\n",
      "Test: Model: rf | Test AUC: 0.8195\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/lib/python3.8/site-packages/xgboost/data.py:173: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
      "  from pandas import MultiIndex, Int64Index\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: xgboost | train AUC: 0.9228\n",
      "Test: Model: xgboost | Test AUC: 0.8427\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/lib/python3.8/site-packages/xgboost/data.py:173: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
      "  from pandas import MultiIndex, Int64Index\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: lighGBM | train AUC: 0.8804\n",
      "Test: Model: lighGBM | Test AUC: 0.8444\n"
     ]
    }
   ],
   "source": [
    "result_pca=model(x_train_pca_nofs, x_test_pca_nofs, y_train_pca_nofs, y_test_pca_nofs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 470,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x800 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,8),dpi=100)\n",
    "plt.plot(result_no['train AUC'],marker='o',label='baseline')\n",
    "plt.plot(result_fs['train AUC'],marker='o',label='28 important features')\n",
    "plt.plot(result_pca['train AUC'],marker='o',label='pca')\n",
    "plt.plot(result_fs_pca['train AUC'],marker='o',label='28 important features+pca')\n",
    "plt.legend(loc='best')\n",
    "plt.ylabel('train AUC')\n",
    "plt.xlabel('models')\n",
    "plt.title('Train AUC comparison')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 471,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x800 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,8),dpi=100)\n",
    "plt.plot(result_no['test AUC'],marker='o',label='baseline')\n",
    "plt.plot(result_fs['test AUC'],marker='o',label='28 important features')\n",
    "plt.plot(result_pca['test AUC'],marker='o',label='pca')\n",
    "plt.plot(result_fs_pca['test AUC'],marker='o',label='28 important features+pca')\n",
    "plt.legend(loc='best')\n",
    "plt.ylabel('Test AUC')\n",
    "plt.xlabel('models')\n",
    "plt.title('Test AUC comparison')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 236,
   "metadata": {},
   "outputs": [],
   "source": [
    "# select random forest and xgboost, light GBM"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Model building"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Find suitable methods to deal with imbalanced data\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 339,
   "metadata": {},
   "outputs": [],
   "source": [
    "X=df.drop('income',axis=1)\n",
    "y=df['income']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 473,
   "metadata": {},
   "outputs": [],
   "source": [
    "from imblearn.under_sampling import RandomUnderSampler \n",
    "from imblearn.over_sampling import RandomOverSampler \n",
    "from imblearn.over_sampling import SMOTE\n",
    "# Apply the random under-sampling\n",
    "rus = RandomUnderSampler()\n",
    "X_RUS, y_RUS = rus.fit_resample(X, y)\n",
    "# Apply the random over-sampling\n",
    "ros = RandomOverSampler()\n",
    "X_ROS, y_ROS = ros.fit_resample(X, y)\n",
    "# Apply regular SMOTE\n",
    "sm = SMOTE()\n",
    "X_SMOTE, y_SMOTE = sm.fit_resample(X, y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 474,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_RUS_train, X_RUS_test, y_RUS_train, y_RUS_test = train_test_split(X_RUS, y_RUS, test_size=0.3, random_state=2017)\n",
    "X_ROS_train, X_ROS_test, y_ROS_train, y_ROS_test = train_test_split(X_ROS, y_ROS, test_size=0.3, random_state=2017)\n",
    "X_SMOTE_train, X_SMOTE_test, y_SMOTE_train, y_SMOTE_test = train_test_split(X_SMOTE, y_SMOTE, test_size=0.3, random_state=2017)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 475,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "RUS - Train AUC :  0.9267501828254847\n",
      "RUS - Test AUC :  0.9211062370455572\n",
      "\n",
      "ROS - Train AUC :  0.9287443289485932\n",
      "ROS - Test AUC :  0.9220175539737682\n",
      "\n",
      "SMOTE - Train AUC :  0.9713159546578004\n",
      "SMOTE - Test AUC :  0.9664389092746485\n"
     ]
    }
   ],
   "source": [
    "clf = lgb.LGBMClassifier(objective='binary',random_state=123)\n",
    "clf_rus = clf.fit(X_RUS_train, y_RUS_train)\n",
    "clf_ros = clf.fit(X_ROS_train, y_ROS_train) \n",
    "clf_smote = clf.fit(X_SMOTE_train, y_SMOTE_train)\n",
    "# Evaluate model performance\n",
    "print (\"\\nRUS - Train AUC : \",metrics.roc_auc_score(y_RUS_train, clf.predict_proba(X_RUS_train)[:,1]))\n",
    "print (\"RUS - Test AUC : \",metrics.roc_auc_score(y_RUS_test, clf.predict_proba(X_RUS_test)[:,1]))\n",
    "print (\"\\nROS - Train AUC : \",metrics.roc_auc_score(y_ROS_train, clf.predict_proba(X_ROS_train)[:,1]))\n",
    "print (\"ROS - Test AUC : \",metrics.roc_auc_score(y_ROS_test, clf.predict_proba(X_ROS_test)[:,1]))\n",
    "print (\"\\nSMOTE - Train AUC : \",metrics.roc_auc_score(y_SMOTE_train, clf.predict_proba(X_SMOTE_train)[:,1]))\n",
    "print (\"SMOTE - Test AUC : \",metrics.roc_auc_score(y_SMOTE_test, clf.predict_proba(X_SMOTE_test)[:,1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 669,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:814: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n",
      "/opt/anaconda3/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:814: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "RUS - Train AUC :  0.8875207091412741\n",
      "RUS - Test AUC :  0.877338071877135\n",
      "\n",
      "ROS - Train AUC :  0.8851122102349254\n",
      "ROS - Test AUC :  0.8879110745159042\n",
      "\n",
      "SMOTE - Train AUC :  0.9361338911096526\n",
      "SMOTE - Test AUC :  0.9346778814762605\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:814: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n"
     ]
    }
   ],
   "source": [
    "clf = linear_model.LogisticRegression(random_state=123)\n",
    "clf_rus = clf.fit(X_RUS_train, y_RUS_train)\n",
    "clf_ros = clf.fit(X_ROS_train, y_ROS_train) \n",
    "clf_smote = clf.fit(X_SMOTE_train, y_SMOTE_train)\n",
    "# Evaluate model performance\n",
    "print (\"\\nRUS - Train AUC : \",metrics.roc_auc_score(y_RUS_train, clf.predict_proba(X_RUS_train)[:,1]))\n",
    "print (\"RUS - Test AUC : \",metrics.roc_auc_score(y_RUS_test, clf.predict_proba(X_RUS_test)[:,1]))\n",
    "print (\"\\nROS - Train AUC : \",metrics.roc_auc_score(y_ROS_train, clf.predict_proba(X_ROS_train)[:,1]))\n",
    "print (\"ROS - Test AUC : \",metrics.roc_auc_score(y_ROS_test, clf.predict_proba(X_ROS_test)[:,1]))\n",
    "print (\"\\nSMOTE - Train AUC : \",metrics.roc_auc_score(y_SMOTE_train, clf.predict_proba(X_SMOTE_train)[:,1]))\n",
    "print (\"SMOTE - Test AUC : \",metrics.roc_auc_score(y_SMOTE_test, clf.predict_proba(X_SMOTE_test)[:,1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 479,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/lib/python3.8/site-packages/xgboost/data.py:173: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
      "  from pandas import MultiIndex, Int64Index\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "RUS - Train AUC :  0.9416991468144045\n",
      "RUS - Test AUC :  0.9396031067503985\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/lib/python3.8/site-packages/xgboost/data.py:173: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
      "  from pandas import MultiIndex, Int64Index\n",
      "/opt/anaconda3/lib/python3.8/site-packages/xgboost/data.py:173: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
      "  from pandas import MultiIndex, Int64Index\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "ROS - Train AUC :  0.9482962622337356\n",
      "ROS - Test AUC :  0.9270879516144198\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/lib/python3.8/site-packages/xgboost/data.py:173: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
      "  from pandas import MultiIndex, Int64Index\n",
      "/opt/anaconda3/lib/python3.8/site-packages/xgboost/data.py:173: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
      "  from pandas import MultiIndex, Int64Index\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "SMOTE - Train AUC :  0.9811065367286692\n",
      "SMOTE - Test AUC :  0.9660262794986427\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/lib/python3.8/site-packages/xgboost/data.py:173: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
      "  from pandas import MultiIndex, Int64Index\n"
     ]
    }
   ],
   "source": [
    "clf = XGBClassifier(random_state=123)\n",
    "clf_rus = clf.fit(X_RUS_train, y_RUS_train)\n",
    "clf_ros = clf.fit(X_ROS_train, y_ROS_train) \n",
    "clf_smote = clf.fit(X_SMOTE_train, y_SMOTE_train)\n",
    "# Evaluate model performance\n",
    "print (\"\\nRUS - Train AUC : \",metrics.roc_auc_score(y_RUS_train, clf.predict_proba(X_RUS_train)[:,1]))\n",
    "print (\"RUS - Test AUC : \",metrics.roc_auc_score(y_RUS_test, clf.predict_proba(X_RUS_test)[:,1]))\n",
    "print (\"\\nROS - Train AUC : \",metrics.roc_auc_score(y_ROS_train, clf.predict_proba(X_ROS_train)[:,1]))\n",
    "print (\"ROS - Test AUC : \",metrics.roc_auc_score(y_ROS_test, clf.predict_proba(X_ROS_test)[:,1]))\n",
    "print (\"\\nSMOTE - Train AUC : \",metrics.roc_auc_score(y_SMOTE_train, clf.predict_proba(X_SMOTE_train)[:,1]))\n",
    "print (\"SMOTE - Test AUC : \",metrics.roc_auc_score(y_SMOTE_test, clf.predict_proba(X_SMOTE_test)[:,1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 249,
   "metadata": {},
   "outputs": [],
   "source": [
    "# select SMOTE\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 678,
   "metadata": {},
   "outputs": [],
   "source": [
    "def confusion(model, X_test, y_test):\n",
    "    plt.figure(figsize=(15,10),dpi=200)\n",
    "    metrics.plot_confusion_matrix(model, X_test, y_test,\n",
    "                                  display_labels=np.unique(y_test),\n",
    "                                  #include_values=False,\n",
    "                                  values_format = 'd',\n",
    "                                  cmap=plt.cm.Blues)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 487,
   "metadata": {},
   "outputs": [],
   "source": [
    "def report(model,X_test,y_test):\n",
    "    roc_auc_score = metrics.roc_auc_score(y_test, model.predict_proba(X_test)[:,1])\n",
    "    accuracy_score = metrics.accuracy_score(y_test, model.predict(X_test))\n",
    "    f1_score = metrics.f1_score(y_test, model.predict(X_test), average=None)\n",
    "    precision_score = metrics.precision_score(y_test,model.predict(X_test), average=None)\n",
    "    print('ROC AUC score:', roc_auc_score)\n",
    "    print('Accuracy score:', accuracy_score)\n",
    "    print('F1 score:', f1_score)\n",
    "    print('Precision score:', precision_score)\n",
    "\n",
    "    print(\"Classification report for classifier %s:\\n%s\\n\"\n",
    "    % (model, metrics.classification_report(y_test, model.predict(X_test))))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 481,
   "metadata": {},
   "outputs": [],
   "source": [
    "def feature_importance(model):\n",
    "\n",
    "    df_importance = pd.DataFrame()\n",
    "    df_importance['importance'] = model.feature_importances_\n",
    "    df_importance['features'] = df.drop('income',axis=1).columns\n",
    "    df_importance = df_importance.sort_values(by='importance', ascending=False) \n",
    "    df_importance = df_importance.reset_index(drop=True)\n",
    "    \n",
    "    return df_importance"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## LightGBM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 484,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0    15834\n",
      "1    15834\n",
      "Name: income, dtype: int64\n",
      "0    6787\n",
      "1    2036\n",
      "Name: income, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "# use SMOTE only for train dataset\n",
    "sm_new=SMOTE()\n",
    "X_SMOTE_train, y_SMOTE_train = sm_new.fit_resample(x_train, y_train)\n",
    "print(y_SMOTE_train.value_counts())\n",
    "print(y_test.value_counts())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 485,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train: Model: lightGBM | Train AUC: 0.9740\n",
      "Test: Model: lightGBM | Test AUC: 0.9114\n"
     ]
    }
   ],
   "source": [
    "model_lightGBM = lgb.LGBMClassifier(random_state=123)\n",
    "model_lightGBM.fit(X_SMOTE_train, y_SMOTE_train)\n",
    "y_SMOTE_pred=model_lightGBM.predict_proba(X_SMOTE_train)\n",
    "train_auc = metrics.roc_auc_score(y_SMOTE_train, y_SMOTE_pred[:,1])\n",
    "y_pred=model_lightGBM.predict_proba(x_test)\n",
    "test_auc = metrics.roc_auc_score(y_test, y_pred[:,1])\n",
    "name='lightGBM'\n",
    "print('Train: Model: {} | Train AUC: {:.4f}'.format(name, train_auc))\n",
    "print('Test: Model: {} | Test AUC: {:.4f}'.format(name, test_auc))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 488,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ROC AUC score: 0.9113867361125785\n",
      "Accuracy score: 0.8563980505496996\n",
      "F1 score: [0.90591817 0.69681742]\n",
      "Precision score: [0.91317365 0.67942137]\n",
      "Classification report for classifier LGBMClassifier(random_state=123):\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.91      0.90      0.91      6787\n",
      "           1       0.68      0.72      0.70      2036\n",
      "\n",
      "    accuracy                           0.86      8823\n",
      "   macro avg       0.80      0.81      0.80      8823\n",
      "weighted avg       0.86      0.86      0.86      8823\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "report(model_lightGBM,x_test,y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 679,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/lib/python3.8/site-packages/sklearn/utils/deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.\n",
      "  warnings.warn(msg, category=FutureWarning)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 3000x2000 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "confusion(model_lightGBM,x_test,y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 491,
   "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>importance</th>\n",
       "      <th>features</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>496</td>\n",
       "      <td>Hours-per-week</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>452</td>\n",
       "      <td>Age</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>350</td>\n",
       "      <td>Capital</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>274</td>\n",
       "      <td>fnlwgt</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>199</td>\n",
       "      <td>Education-num</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>68</td>\n",
       "      <td>Marital-status_ Married-civ-spouse</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>50</td>\n",
       "      <td>Sex_ Female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>50</td>\n",
       "      <td>Occupation_ Adm-clerical</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>46</td>\n",
       "      <td>Occupation_ Machine-op-inspct</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>44</td>\n",
       "      <td>Work-class_ Self-emp-not-inc</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>44</td>\n",
       "      <td>Occupation_ Other-service</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>44</td>\n",
       "      <td>Occupation_ Craft-repair</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>41</td>\n",
       "      <td>Marital-status_ Never-married</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>41</td>\n",
       "      <td>Relationship_ Unmarried</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>41</td>\n",
       "      <td>Occupation_ Sales</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>40</td>\n",
       "      <td>Occupation_ Farming-fishing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>39</td>\n",
       "      <td>Work-class_ Private</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>38</td>\n",
       "      <td>Occupation_ Transport-moving</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>36</td>\n",
       "      <td>Occupation_ Exec-managerial</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>36</td>\n",
       "      <td>Marital-status_ Divorced</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>36</td>\n",
       "      <td>Occupation_ Prof-specialty</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>35</td>\n",
       "      <td>Work-class_ Local-gov</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>35</td>\n",
       "      <td>Occupation_ Protective-serv</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>34</td>\n",
       "      <td>Relationship_ Not-in-family</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>30</td>\n",
       "      <td>Native-country</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>30</td>\n",
       "      <td>Relationship_ Own-child</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>30</td>\n",
       "      <td>Occupation_ Handlers-cleaners</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>29</td>\n",
       "      <td>Sex_ Male</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>27</td>\n",
       "      <td>Work-class_ State-gov</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>26</td>\n",
       "      <td>Relationship_ Wife</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>24</td>\n",
       "      <td>Work-class_ Federal-gov</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>23</td>\n",
       "      <td>Marital-status_ Separated</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>22</td>\n",
       "      <td>Relationship_ Husband</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>21</td>\n",
       "      <td>Occupation_ Tech-support</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>20</td>\n",
       "      <td>Work-class_ Self-emp-inc</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>20</td>\n",
       "      <td>Race_ White</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>20</td>\n",
       "      <td>Marital-status_ Married-spouse-absent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>19</td>\n",
       "      <td>Relationship_ Other-relative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>18</td>\n",
       "      <td>Race_ Black</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>17</td>\n",
       "      <td>Race_ Asian-Pac-Islander</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>16</td>\n",
       "      <td>Occupation_ Priv-house-serv</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>16</td>\n",
       "      <td>Race_ Amer-Indian-Eskimo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>16</td>\n",
       "      <td>Marital-status_ Widowed</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>7</td>\n",
       "      <td>Race_ Other</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>0</td>\n",
       "      <td>Marital-status_ Married-AF-spouse</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>0</td>\n",
       "      <td>Work-class_ Without-pay</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>0</td>\n",
       "      <td>Occupation_ Armed-Forces</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    importance                                features\n",
       "0          496                          Hours-per-week\n",
       "1          452                                     Age\n",
       "2          350                                 Capital\n",
       "3          274                                  fnlwgt\n",
       "4          199                           Education-num\n",
       "5           68      Marital-status_ Married-civ-spouse\n",
       "6           50                             Sex_ Female\n",
       "7           50                Occupation_ Adm-clerical\n",
       "8           46           Occupation_ Machine-op-inspct\n",
       "9           44            Work-class_ Self-emp-not-inc\n",
       "10          44               Occupation_ Other-service\n",
       "11          44                Occupation_ Craft-repair\n",
       "12          41           Marital-status_ Never-married\n",
       "13          41                 Relationship_ Unmarried\n",
       "14          41                       Occupation_ Sales\n",
       "15          40             Occupation_ Farming-fishing\n",
       "16          39                     Work-class_ Private\n",
       "17          38            Occupation_ Transport-moving\n",
       "18          36             Occupation_ Exec-managerial\n",
       "19          36                Marital-status_ Divorced\n",
       "20          36              Occupation_ Prof-specialty\n",
       "21          35                   Work-class_ Local-gov\n",
       "22          35             Occupation_ Protective-serv\n",
       "23          34             Relationship_ Not-in-family\n",
       "24          30                          Native-country\n",
       "25          30                 Relationship_ Own-child\n",
       "26          30           Occupation_ Handlers-cleaners\n",
       "27          29                               Sex_ Male\n",
       "28          27                   Work-class_ State-gov\n",
       "29          26                      Relationship_ Wife\n",
       "30          24                 Work-class_ Federal-gov\n",
       "31          23               Marital-status_ Separated\n",
       "32          22                   Relationship_ Husband\n",
       "33          21                Occupation_ Tech-support\n",
       "34          20                Work-class_ Self-emp-inc\n",
       "35          20                             Race_ White\n",
       "36          20   Marital-status_ Married-spouse-absent\n",
       "37          19            Relationship_ Other-relative\n",
       "38          18                             Race_ Black\n",
       "39          17                Race_ Asian-Pac-Islander\n",
       "40          16             Occupation_ Priv-house-serv\n",
       "41          16                Race_ Amer-Indian-Eskimo\n",
       "42          16                 Marital-status_ Widowed\n",
       "43           7                             Race_ Other\n",
       "44           0       Marital-status_ Married-AF-spouse\n",
       "45           0                 Work-class_ Without-pay\n",
       "46           0                Occupation_ Armed-Forces"
      ]
     },
     "execution_count": 491,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "feature_importance(model_lightGBM)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Random Forest"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 670,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train: Model: lrmodel | Train AUC: 0.9361\n",
      "Test: Model: lrmodel | Test AUC: 0.8864\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/lib/python3.8/site-packages/sklearn/linear_model/_logistic.py:814: ConvergenceWarning: lbfgs failed to converge (status=1):\n",
      "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n",
      "\n",
      "Increase the number of iterations (max_iter) or scale the data as shown in:\n",
      "    https://scikit-learn.org/stable/modules/preprocessing.html\n",
      "Please also refer to the documentation for alternative solver options:\n",
      "    https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n",
      "  n_iter_i = _check_optimize_result(\n"
     ]
    }
   ],
   "source": [
    "model_lr = linear_model.LogisticRegression(random_state=123)\n",
    "model_lr.fit(X_SMOTE_train, y_SMOTE_train)\n",
    "y_SMOTE_pred=model_lr.predict_proba(X_SMOTE_train)\n",
    "train_auc = metrics.roc_auc_score(y_SMOTE_train, y_SMOTE_pred[:,1])\n",
    "y_pred=model_lr.predict_proba(x_test)\n",
    "test_auc = metrics.roc_auc_score(y_test, y_pred[:,1])\n",
    "name='lrmodel'\n",
    "print('Train: Model: {} | Train AUC: {:.4f}'.format(name, train_auc))\n",
    "print('Test: Model: {} | Test AUC: {:.4f}'.format(name, test_auc))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 672,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ROC AUC score: 0.8863990965045565\n",
      "Accuracy score: 0.8160489629377763\n",
      "F1 score: [0.87477818 0.65357524]\n",
      "Precision score: [0.91820538 0.57795394]\n",
      "Classification report for classifier LogisticRegression(random_state=123):\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.92      0.84      0.87      6787\n",
      "           1       0.58      0.75      0.65      2036\n",
      "\n",
      "    accuracy                           0.82      8823\n",
      "   macro avg       0.75      0.79      0.76      8823\n",
      "weighted avg       0.84      0.82      0.82      8823\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "report(model_lr,x_test,y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 680,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/lib/python3.8/site-packages/sklearn/utils/deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.\n",
      "  warnings.warn(msg, category=FutureWarning)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 3000x2000 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "confusion(model_lr,x_test,y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 495,
   "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>importance</th>\n",
       "      <th>features</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.133</td>\n",
       "      <td>Age</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.121</td>\n",
       "      <td>fnlwgt</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.108</td>\n",
       "      <td>Hours-per-week</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.092</td>\n",
       "      <td>Marital-status_ Married-civ-spouse</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.090</td>\n",
       "      <td>Education-num</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.052</td>\n",
       "      <td>Relationship_ Husband</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.050</td>\n",
       "      <td>Marital-status_ Never-married</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.042</td>\n",
       "      <td>Capital</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.024</td>\n",
       "      <td>Relationship_ Not-in-family</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.024</td>\n",
       "      <td>Relationship_ Own-child</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.019</td>\n",
       "      <td>Sex_ Female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.019</td>\n",
       "      <td>Occupation_ Other-service</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.015</td>\n",
       "      <td>Relationship_ Unmarried</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0.014</td>\n",
       "      <td>Marital-status_ Divorced</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0.012</td>\n",
       "      <td>Occupation_ Craft-repair</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.012</td>\n",
       "      <td>Work-class_ Private</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>0.012</td>\n",
       "      <td>Work-class_ Self-emp-not-inc</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0.011</td>\n",
       "      <td>Occupation_ Farming-fishing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0.010</td>\n",
       "      <td>Occupation_ Transport-moving</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0.010</td>\n",
       "      <td>Occupation_ Machine-op-inspct</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0.010</td>\n",
       "      <td>Native-country</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0.010</td>\n",
       "      <td>Occupation_ Adm-clerical</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>0.009</td>\n",
       "      <td>Occupation_ Exec-managerial</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>0.009</td>\n",
       "      <td>Relationship_ Wife</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>0.009</td>\n",
       "      <td>Occupation_ Handlers-cleaners</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0.009</td>\n",
       "      <td>Sex_ Male</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>0.008</td>\n",
       "      <td>Occupation_ Sales</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0.008</td>\n",
       "      <td>Occupation_ Prof-specialty</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>0.007</td>\n",
       "      <td>Race_ Black</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>0.006</td>\n",
       "      <td>Work-class_ Local-gov</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>0.006</td>\n",
       "      <td>Race_ White</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>0.005</td>\n",
       "      <td>Work-class_ State-gov</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>0.005</td>\n",
       "      <td>Marital-status_ Separated</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>0.004</td>\n",
       "      <td>Relationship_ Other-relative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>0.004</td>\n",
       "      <td>Work-class_ Self-emp-inc</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>0.003</td>\n",
       "      <td>Occupation_ Tech-support</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>0.003</td>\n",
       "      <td>Marital-status_ Widowed</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>0.003</td>\n",
       "      <td>Occupation_ Protective-serv</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>0.003</td>\n",
       "      <td>Work-class_ Federal-gov</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>0.002</td>\n",
       "      <td>Race_ Asian-Pac-Islander</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>0.002</td>\n",
       "      <td>Race_ Amer-Indian-Eskimo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>0.002</td>\n",
       "      <td>Marital-status_ Married-spouse-absent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>0.001</td>\n",
       "      <td>Race_ Other</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>0.000</td>\n",
       "      <td>Occupation_ Priv-house-serv</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>0.000</td>\n",
       "      <td>Marital-status_ Married-AF-spouse</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>0.000</td>\n",
       "      <td>Work-class_ Without-pay</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>0.000</td>\n",
       "      <td>Occupation_ Armed-Forces</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    importance                                features\n",
       "0        0.133                                     Age\n",
       "1        0.121                                  fnlwgt\n",
       "2        0.108                          Hours-per-week\n",
       "3        0.092      Marital-status_ Married-civ-spouse\n",
       "4        0.090                           Education-num\n",
       "5        0.052                   Relationship_ Husband\n",
       "6        0.050           Marital-status_ Never-married\n",
       "7        0.042                                 Capital\n",
       "8        0.024             Relationship_ Not-in-family\n",
       "9        0.024                 Relationship_ Own-child\n",
       "10       0.019                             Sex_ Female\n",
       "11       0.019               Occupation_ Other-service\n",
       "12       0.015                 Relationship_ Unmarried\n",
       "13       0.014                Marital-status_ Divorced\n",
       "14       0.012                Occupation_ Craft-repair\n",
       "15       0.012                     Work-class_ Private\n",
       "16       0.012            Work-class_ Self-emp-not-inc\n",
       "17       0.011             Occupation_ Farming-fishing\n",
       "18       0.010            Occupation_ Transport-moving\n",
       "19       0.010           Occupation_ Machine-op-inspct\n",
       "20       0.010                          Native-country\n",
       "21       0.010                Occupation_ Adm-clerical\n",
       "22       0.009             Occupation_ Exec-managerial\n",
       "23       0.009                      Relationship_ Wife\n",
       "24       0.009           Occupation_ Handlers-cleaners\n",
       "25       0.009                               Sex_ Male\n",
       "26       0.008                       Occupation_ Sales\n",
       "27       0.008              Occupation_ Prof-specialty\n",
       "28       0.007                             Race_ Black\n",
       "29       0.006                   Work-class_ Local-gov\n",
       "30       0.006                             Race_ White\n",
       "31       0.005                   Work-class_ State-gov\n",
       "32       0.005               Marital-status_ Separated\n",
       "33       0.004            Relationship_ Other-relative\n",
       "34       0.004                Work-class_ Self-emp-inc\n",
       "35       0.003                Occupation_ Tech-support\n",
       "36       0.003                 Marital-status_ Widowed\n",
       "37       0.003             Occupation_ Protective-serv\n",
       "38       0.003                 Work-class_ Federal-gov\n",
       "39       0.002                Race_ Asian-Pac-Islander\n",
       "40       0.002                Race_ Amer-Indian-Eskimo\n",
       "41       0.002   Marital-status_ Married-spouse-absent\n",
       "42       0.001                             Race_ Other\n",
       "43       0.000             Occupation_ Priv-house-serv\n",
       "44       0.000       Marital-status_ Married-AF-spouse\n",
       "45       0.000                 Work-class_ Without-pay\n",
       "46       0.000                Occupation_ Armed-Forces"
      ]
     },
     "execution_count": 495,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "feature_importance(model_rf)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### XGBoost"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 497,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/lib/python3.8/site-packages/xgboost/data.py:173: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
      "  from pandas import MultiIndex, Int64Index\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train: Model: XGBoost | Train AUC: 0.9836\n",
      "Test: Model: XGBoost | Test AUC: 0.9063\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/lib/python3.8/site-packages/xgboost/data.py:173: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
      "  from pandas import MultiIndex, Int64Index\n"
     ]
    }
   ],
   "source": [
    "model_xgb = XGBClassifier(random_state=123)\n",
    "model_xgb.fit(X_SMOTE_train, y_SMOTE_train)\n",
    "y_SMOTE_pred=model_xgb.predict_proba(X_SMOTE_train)\n",
    "train_auc = metrics.roc_auc_score(y_SMOTE_train, y_SMOTE_pred[:,1])\n",
    "y_pred=model_xgb.predict_proba(x_test)\n",
    "test_auc = metrics.roc_auc_score(y_test, y_pred[:,1])\n",
    "name='XGBoost'\n",
    "print('Train: Model: {} | Train AUC: {:.4f}'.format(name, train_auc))\n",
    "print('Test: Model: {} | Test AUC: {:.4f}'.format(name, test_auc))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 500,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/lib/python3.8/site-packages/xgboost/data.py:173: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
      "  from pandas import MultiIndex, Int64Index\n",
      "/opt/anaconda3/lib/python3.8/site-packages/xgboost/data.py:173: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
      "  from pandas import MultiIndex, Int64Index\n",
      "/opt/anaconda3/lib/python3.8/site-packages/xgboost/data.py:173: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
      "  from pandas import MultiIndex, Int64Index\n",
      "/opt/anaconda3/lib/python3.8/site-packages/xgboost/data.py:173: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
      "  from pandas import MultiIndex, Int64Index\n",
      "/opt/anaconda3/lib/python3.8/site-packages/xgboost/data.py:173: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
      "  from pandas import MultiIndex, Int64Index\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ROC AUC score: 0.9063475606173017\n",
      "Accuracy score: 0.8511844043975972\n",
      "F1 score: [0.90253136 0.68550898]\n",
      "Precision score: [0.90948534 0.66900421]\n",
      "Classification report for classifier XGBClassifier(base_score=0.5, booster='gbtree', colsample_bylevel=1,\n",
      "              colsample_bynode=1, colsample_bytree=1, gamma=0, gpu_id=-1,\n",
      "              importance_type='gain', interaction_constraints='',\n",
      "              learning_rate=0.300000012, max_delta_step=0, max_depth=6,\n",
      "              min_child_weight=1, missing=nan, monotone_constraints='()',\n",
      "              n_estimators=100, n_jobs=0, num_parallel_tree=1, random_state=123,\n",
      "              reg_alpha=0, reg_lambda=1, scale_pos_weight=1, subsample=1,\n",
      "              tree_method='exact', validate_parameters=1, verbosity=None):\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.91      0.90      0.90      6787\n",
      "           1       0.67      0.70      0.69      2036\n",
      "\n",
      "    accuracy                           0.85      8823\n",
      "   macro avg       0.79      0.80      0.79      8823\n",
      "weighted avg       0.85      0.85      0.85      8823\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "report(model_xgb,x_test,y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 501,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1440x1440 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from xgboost import plot_importance\n",
    "fig, ax = plt.subplots(figsize=(20,20))\n",
    "plot_importance(model_xgb, ax=ax)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 681,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/lib/python3.8/site-packages/sklearn/utils/deprecation.py:87: FutureWarning: Function plot_confusion_matrix is deprecated; Function `plot_confusion_matrix` is deprecated in 1.0 and will be removed in 1.2. Use one of the class methods: ConfusionMatrixDisplay.from_predictions or ConfusionMatrixDisplay.from_estimator.\n",
      "  warnings.warn(msg, category=FutureWarning)\n",
      "/opt/anaconda3/lib/python3.8/site-packages/xgboost/data.py:173: FutureWarning: pandas.Int64Index is deprecated and will be removed from pandas in a future version. Use pandas.Index with the appropriate dtype instead.\n",
      "  from pandas import MultiIndex, Int64Index\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 3000x2000 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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LCcxHiwUWG2NWj8S1nfDp2jKOn/frXcpP//Hvdyk7Yr9CHn1+RX+PbLA5l/7OifCUDanJiaz9584jnHIyU3nm7svZWLqWiZOn9pePyc/kyUWDDtAflfzYdB2xe3TGmBcJzF0bVVZvDDsFT3lQVk6u2yF4mBDjsY4GOzzTGRGtstOT3A5BRaizo93tELxLtOmqBjE2L8XtEFSEWlta3A7BswS0Rqd21TeOTvnHcA3DiFZ+rNGN1uHdI+aEGbqIo99s37bF7RA8zY8zI7RG57C6pg63Q1ARSkhMdDsE79J7dGow68t0FzC/ycjMcjsEzxKf9rpq09VhM76S73YIKkLVlRVuh+BpIvYOL9EancM+Lq1xOwQVoZy8wXbpU33s339zfnqpXVqjc1hRrg4v8RsdXhKGzdqc1uhGmYLsZLdDUBFqb9M5x6EE5rr6r0anic5hOo7Of3QcXXheq63ZoU1Xh+k4Ov/RcXThxcSIrcNLtEbnsMo6bQb5TVKy3m4ISXT1EjWI8ppWt0NQEUpJTXU7BM/y63p02nR12IGTdckfv6mt1i0nQ/Pn5jhao3PY+19UuR2CilBeQaHbIXiax3KYLVqjc9ik4gy3Q1ARamyodzsE7xLtjFCDyE7XCeJ+09mhCzGEEtk4Ou/QROcwHUfnPzqOLjw/JjptujpMx9H5j46jC8+PU8A00Tlse7UOL/EbHV4S3p72uopIrIh8KCLPW88nisgKESkVkcdFJMEqT7Sel1qvTwj6jOus8jUictJQMWuic1hdk2604jcJibqhUUjDM6n/P4HPg57/CrjTGDMZqAMussovAuqs8jut8xCRfQnsDb0fMBv4g4jEhrtgyHt0IvIwNmblGmN+MNQ5o9l+E3P4bFOd22GoCNTX1pCtWx4Oak8X3hSRccA3gduA/5JA1e94vtzQfglwI/BHYK71GOAp4G7r/LnAY8aYDmCjiJQChwFvh7puuM6I0t39MupL76zWRRz9Jr9wjNsheFpMmOratn8/S9m/lwJQe8fNgy3s9zvgp0C69TwXqDfGdPd9BFBsPS4GtgIYY7pFpME6vxh4J/iyQe8ZVMhEZ4y5KdwblT37Tcxha2Wz22GoCNTX1ZCWruMfQwnXLC056nRKjjodgJyclp2mmIjIKUClMWaliBzrWICDsD28REROJNAuLjDGnCoiM4AMY8wrjkUXBdJT4t0OQUWoq7PL7RA8S/ZsUv/XgdNEZA6QBGQAdwFZIhJn1erGAWXW+WVACbBNROKATKAmqLxP8HsGZaszQkSuINBmXgccbRW3Abfaef9opuPo/EfH0YUXI/aOgYwx1xljxhljJhCoNL1ijDkXeBU4wzptHrDUevyc9Rzr9VeMMcYqP8vqlZ0ITAHeDRuzze92JXCCMWYh0GuVfQFMs/n+UUvH0fmPjqMLz4EpYNcS6JgoJXAP7n6r/H4g1yr/L2A+gDFmNfAE8Bnwf8BlxpiecBew23RNx7opyJc9sfFAp833j1pbKvT+nN+kpqcPfdIoJQR6XveUMWY5sNx6vIFAr+nAc9qB74Z4/20Eem5tsVujex0rmwb5CYEqpwqjvbN76JOUp8TG6szIcHa36eomu4nuCuBbIrIJSBeRNcD3CFQnVRhTS7LcDkFFqLFexz2GZHNWhNfmw9r6p8sYUy4ihwKHAnsRaMa+a4zpDf9O9eaqcrdDUBEqLBrrdgie5rEcZkskU8BiCNyXA4iFYWiojwKHTMt3OwQVoeqqSrdD8CwhMGDYzuEltmp0InIA8CyQSGC8yjigXUS+ZYz52Lnw/C8+TqcT+01vrzZUwvHaopp22P0tXAzcA4wzxhxGYLrF3Va5CkObrv6jTdcwhmdS/4izm+imAr+zButh/XkXgYF6KoxjDwo7BU950I4yHeQdil+brnYT3YvAaQPKTgVeGN5wos+G7Y1uh6AilJ6R6XYIniY2Dy+xu0xTLPCYiKwk0ONaAhzCl1M1lFKjhNeGjtgRyTJNnwY9/gx4afjDiT57j81g5Rrd8tBPmhobdMvDEAJNV7ejiJwu0+Sw5R+GXVRBedCYYp2fHJJ4bytDO2yPfRCRBBH5qogcJyLH9x1OBhcNjjqgyO0QVIQqyre7HYKnRe3MCBE5CniSwDi6DKCRLyf67+1YdFGgq1vHZPlNTIyOfQwl6pquA9wJ/NoYc6eI1BljckTkBkC3uBqC3p/zn7z8ArdD8DSv1dbsiGQc3V0DyhYCVw1vONFHm67+o03X8KJqeMkADQSarPVAubXdWA2Q5lBcUWPt1nq3Q1ARysjKdjsEzxKBWB+2Xe3W6J4B5liPFxNYh24lgS3IVBhJCbq2md/09OgaguFEbWeEMebKoMe/FZEVBGpzOpZuCOML01jxmW556CctTU1QqLccQvFYDrNlt6obxpg3hjuQaKWb4/iPbo4TjvfmsdoRbgrYG3w5BSwkY8zRQ50zmp0wYxxPvrre7TBUBLZv28LEyVPdDsOThOir0d03YlEA0/cZT917d4/kJUfElk0buffXE90OwxFbqqNzdFFrt7C9rt3tMLxpz/Z1dU24KWBLRjKQaJWdm+t2CCpCKena6xqKALE+THQ6BNxhlTt04U2/aarTpdTD8eMuYDr2wWHZOVqj8xut0YXntSRmhyY6h3V06L0ev+nu6nA7BM8KdEb4L9NponNYa0uL2yGoCHW2R2cny7DwYLPUDlv36EQkUURuE5ENItJglc0SkcudDc//ikv2cjsEFaGsfN3nI5xo3hznTmB/4Fy+HFu3GviRE0FFk7Ktm90OQUWovkoXSw1FgDgRW4eX2G26fguYbIxpEZFeAGNMmYjoP31DSExMdDsEFaG4+AS3Q/A0j+UwW+wmus6B54pIPoEVTFQYGZlZboegIpSUmuF2CJ4lPp0CZrfp+iSwREQmAohIEYENrB9zKrBoUVWpE/r9prm+2u0QvGsPNrAWkSQReVdEPhaR1SJyk1U+UURWiEipiDwuIglWeaL1vNR6fULQZ11nla8RkZOGCttuovsZsBH4BMgC1gHbAd1AZwi5efluh6AilJqR43YInrYHA4Y7gOONMQcC04HZInIE8CvgTmPMZKAOuMg6/yKgziq/0zoPaz3Ms4D9gNnAH0QkNmzMdr6YMabTGHOVMSYNKATSreeddt4/munwEv/p7NDhJaEIgYU37RwDmYBm62m8dRjgeL5c23IJcLr1eK71HOv1mRIYxDcXeMwY02GM2Uhga9bDwsVtd3OcgRvgpPcNGjTGbLDzGaNVW5v+0vhNlw7yDk32bN6oVfNaCUwG7gHWA/XGmL7VTrcBfZ2cxQQ24MIY020Nbcu1yt8J+tjg9wzKbmdEKYHMG5ym+4aZhK0yjnY6js5/dBxdeBJmR4h3n3+M914M3LqfeusNeQNfN8b0ANNFJAv4X+ArzkS5M7srDO+UxEVkDLAA0AU4h1C2dTOTpkxzOwwVgfqqMvKKdRfPwQy13eERp57FEaeeBUCO2RSyV8cYUy8irwJHAlkiEmfV6sYBfQMZy4ASYJuIxAGZBEZ69JX3CX7PoHarFmqM2QFcCdy+O+8fTZKTU9wOQUUoPjHJ7RA8bXc7I0Qk36rJISLJwInA5wT2oDnDOm0esNR6/Jz1HOv1V4wxxio/y+qVnQhMAd4NF/OezHWdBuhv8RBSUlPdDkFFKCFR/7cOZw8m9RcRGKYWS6CS9YQx5nkR+Qx4TERuBT4E7rfOvx94WERKgVoCPa0YY1aLyBPAZ0A3cJnVJA7JbmfEwGXVUwh07d5s8wuOWjXVVWRl63AFP2lprCU5PcvtMDwpsN2hzZMHpB5jzCrgoIGnWR2au/SaGmPage8O9tHGmNuA22xGYrtGN3BZ9RbgY2PMOrsXGq3yCwrdDkFFKC1rl3voKogfZ0YMmeisaubxwKXGGF2oK0KNDfU6Dcxn2lsadRpYCEN1RnjVkInOGNMjIrOA3hGIJ+p0dOi/DX7T3aXj4MPxYYUuomWabhKReCeDiUY6js5/dBxdOEKMzcNLwiY6ETnbengFcA3QJCJbRWRL3+F4hD6n69H5j65HF1rfvq5+W3hzqKbrn4FHgfNGIJaopMNL/CchSYeXhCQQ58ObdEMlOgEwxrw2ArFEpUQdfOo7cfG6WGoofTU6vxkq0cWKyHEQusFtjHlleEOKLnW1NeTk6nAFP2ltqiMlQ7c8DCUah5ckEhidHOqbGUAnBYZRMKbI7RBUhNKzC9wOwdN8mOeGTHQtxhhNZHugrqaG9HQdk+UnrU11JKakuR2GJwl7tkyTW3RfV4d16Zgs3+np7nI7BO+S6Gy6+u8beYyOo/MfHUcXnh8TXdhaqDEmfaQCiVY6js5/dBxdaBLB4SXadHVYWrr+W+E3icl6fy4cH1boNNE5LTZWf8R+ExOruwOEJnuyHp1r/NiB4isN9XVuh6Ai1Nbc4HYInhZj8/ASrW44bEyR3tj2m4wcXUMwlMAyTVqjUwNUVVW4HYKKUHNDyD1dlASWUrdzeInW6BxmenUZP78xvWbok0YxP9aONNE5TJuu/pORq03XUAKT+r1VW7PDj8nZV7aXbXU7BBWhhupyt0PwNB1Hp3aRkZHpdggqQkmpOvYxHB9W6DTRKaXsEyDWh5lOm64Oa2zUMVl+097S5HYIHia2//MSrdE5bGxxidshqAhl5ukaguH4sEKnNTqn7SjXCeJ+01ijYx/D8eMuYFqjc5jE6L8lfiM+3PxlpHhxhy87NNE5LD9fx2T5TVqm7vERjk4BU7vQpqv/NNZq0zWUwFxXe4eXaI3OYZlZupuU3ySn6djHcOz2qHppIp0mOof19HS7HYKKUG9Pj9sheJrdlqsmuijT0NTKT279G5+vL0cEfv+Lc5myVyEX/mwx6zfvYNJeY3jg9ovIykjhzZVrOefqe9lrbC4Apx43nZ9ecrLL3yD63fA/T/D6u5+Tk5XGM3+6eqfXljz9Gv9z3wssf2wB2ZmpvPLWJzz8wsfExAixsTFcc+lpHLz/RAB+dP19fPLFFqbvN4G7b7rQja/iut0dIyciJcBDQCGBPHivMeYuEckBHgcmAJuA7xlj6iQwqfYuYA7QCpxvjPnA+qx5wPXWR99qjFkS7tojkuhEZDFwClBpjNl/JK45kubf8RQzj9yXJb+6mM6ubtraO7njgX9y9KHTePSOS/jjY69z55J/ctMVpwNw5EGTePzOH7kb9Cgz98QZnH3a1/j5bx/fqXxHVT1vf7COooKs/rLjvnEop33zeESEtRvLueaXj7D0L9cAcP53jqGto4un/vHOSIbvGX336OwYpF7cDVxtjPlARNKBlSKyDDgfeNkYs1BE5gPzgWuBk4Ep1nE48EfgcCsxLgBmEEiYK0XkOWNMyFVuR6oz4kFg9ghda0Q1NLfx1ofr+f7cIwFIiI8jMz2Ff7y2irNPOZyyrZs5+5TDeXH5KpcjHd0O+ereZKSn7FL+mz//nasumrNTLaWzubp/hY629s6dVus4/KAppKYkOh+wV4kQY/MYyBhT3lcjM8Y0AZ8DxcBcoK9GtgQ43Xo8F3jIBLwDZIlIEXASsMwYU2slt2UMkV9GpEZnjHldRCaMxLVG2payGvKy0rjspkf4dF0Z0/cp4farz6CytokxeZlsaa6lMDeDytovpxW998lGjjrndsbkZXLLf36LfSbpSHw3vPr2agryMpi299idymPj4nn535+y6MF/UFvfzN03j84maijD0aFq5YODgBVAoTGmb8mYHQSathBIgsHL/2yzykKVh6TDS/ZQd08PH6/ZyoVnfIPX/zqflKREfvfgsv7Xs3NzrRVXA88PmFbCqudu4c2/XcelZx7Dedfc61Lko1tbeyf3Pf4KP/7+rF1eS0nPZubX92fpX67hdzfM456HXnIhQm/qW0o91PHc40u4+NvHc/G3j6e2tnbQAYkikgY8DVxpjGkMfs0YY3CgH8MznRGVlRUcMn1/4uPj6e7u5owzvsuVV/+Usq2bSUtPJzY2job6OsYUFVNVVYHp7WVMUTHby7b2L4XU2NjA2OISdpSXITEx5OcXsqO8jMysbHp6umluaqK4ZC/Ktm4mPj6B7NxcKneUk52TS0dHO60tLf2vJyYmkpGZRVVlBbl5+bS2tNDW1tr/enJyCimpqXS21FCUl8GYDFi/bg2zv7Evv73vBXIykvli7UaaareTPWYvstKSWL9ujfX+TbSkp3Pw1Hza2trZWlZBT2ezZ75TTXUV+QWFNDbU09HR0f96SmoqiYlJ1NXWUDCmiLqKcnq6u8jKL6a+qozE5DRiYmNpa24gI6eQ5oZqTK8hI7eQhury/uWP2luayMwrorGmAokR0jLzaKytIDktk96eHjramvs/MzYunpT0bJrqKklJz6a7q4PO9tb+1+PiE0hKzaC5vprUjBw6O1rp6mjvfz0+MYmExBRaGmvp6Iyjt7uL6rINVLXEsm17FWf88A4QobKmkTMvv5M/XH8GCb0tjJ20P/VVZUwtTmPr9irWf7Gakr0m0NxQTWP1DkxvL9VlG1z/TmlZebS3NNLd1dn/ekJSCnHxibQ21ZGeXUBrU13/39NwCFej+9ZZ5/Ots84HoGXzyl3WpBeReAJJ7q/GmGes4goRKTLGlFtN00qrvAwIniw+ziorA44dUL48bMyBBOo8q6r6fKjOiHdWvGumH3LYiMQy3E6+5E4W/fwcpkwoZOG9L9DS1glATmYq8049mCV//4C6xlZu/snpVFQ3UpCbjoiwcvUm5l17P5/8/WZfrtq6pbrV7RAiUlZRyxULHtil1xXg5Hm387dFPyE7M5U1a9czdcreiAifl27jihsfZNnDP+//O3pv1XqWPP2aL3tdt65+e+XMmTNn7O77X33jbZM8dh9b57ZsWrnTtaxe1CVArTHmyqDy3wA1QZ0ROcaYn4rIN4HLCfS6Hg4sMsYcZnVGrAQOtj7iA+AQY0xtqFg8U6Pzs1//93e59IYH6ezqYUJxHvfccB69vb1ccN1iHnzmDSaOK+CB2wO/FEtf+ZAHnnqD2LhYkhPjuf+2C3yZ5Pzm2oV/5f1VG6hvbOHE827jR98/kW+fNPg/rK+8tZr5dzxLfFwMiQnx/Hr+uf1/R+f/9x/YtLWK1vYOTjzvNm686gy+fsi0kfwqrtuDKWBfB74PfCIiH1llPwMWAk+IyEXAZuB71msvEkhypQSGl1wAYIypFZFbgPes824Ol+RghGp0IvIogapmHlABLDDG3B98jp9rdOGsX7eGSVOi8xfBbzU6u6rLNpBXvLfbYThiOGp0acX72jq3ceP7e3St4TRSva5nj8R1vKi4ZC+3Q1ARGq57WVHLhw0Q7XV1WNnWzW6HoCJUX6ULMYQS2PhGVxhWAyQmjuLBpT4VF5/gdgjepevRqcFkZGa5HYKKUFJqhtsheJoP85w2XZ1WValrm/lNc/0uw79UkMAA+KEPL9EancNy8/LdDkFFKDUjx+0QPM1jOcwWrdE5rLWlxe0QVIQ6O6Jz2MxwkAgOL9EancPa2vSXxm+6OtrdDsHbvJbFbNBE5zAdR+c/Oo4uHO8NHbFDm64O03F0/qPj6MLr2/JwqMNLtEbnsOTkXRd7VN4Wn5jkdgje5cEkZocmOoelpKa6HYKKUEKi/uMUjjZd1S5qqqvcDkFFqKUx7EIYo5qgTVc1iPyCwqFPUp6SljXowrjK4rEcZovW6BzW2FDvdggqQu0tjUOfNJr5cCCd1ugc1tHR4XYIKkLdXZ1uh+Bpe7Dwpms00TlMx9H5j46jC89/aU6bro7TcXT+o+PohqBNVzWQDi/xn4QkHV4SSt/Cm36jic5hiTr41Hfi4nWx1JA8OHTEDm26OqyutsbtEFSEWpvq3A7B03zYctUandMKxhS5HYKKUHp2gdsheJrXFtW0Q2t0Dqur0Rqd32iNLjydGaF20aVjsnynp7vL7RA8y4vNUjs00TlMx9H5j46jG4IPM502XR2m4+j8R8fRhWN3V1dvZUOt0TksLT3d7RBUhBKT09wOwdO8dv/NDk10DouN1R+x38TExrodgncJxPgw0WnT1WEN9dqD5zdtzQ1uh+Bx/htJp9UNh40p0hvbfpORo2sIhtK38KbfaI3OYVVVFW6HoCLU3FDtdgie5r/6nCY6x5neXrdDUBEyvcbtEDxtTwYMi8hiEakUkU+DynJEZJmIrLP+zLbKRUQWiUipiKwSkYOD3jPPOn+diMwbKmZNdA7Tpqv/ZORq0zUcEbF1hPAgMHtA2XzgZWPMFOBl6znAycAU67gU+KN1/RxgAXA4cBiwoC85hqKJzmHby7a6HYKKUEN1udsheNqeNF2NMa8DA3cfmgsssR4vAU4PKn/IBLwDZIlIEXASsMwYU2uMqQOWsWvy3Il2RjgsIyPT7RBUhJJSdexjKA51RhQaY/r+ddkB9FWpi4HgmsI2qyxUeUhao1NKRSTcbIiHH7iPWcccwaxjjqC2tjbi7dSMMQYY9pukmugc1tioY7L8pr2lye0QvGuI9uoPLryEZa+vYNnrK8jJybHbfV1hNUmx/qy0ysuAkqDzxlllocpD0kTnsLHFJUOfpDwlM0/XEAzHgeElzwF9PafzgKVB5T+wel+PABqsJu5LwCwRybY6IWZZZSFponPYjnKdIO43jTU69jGcGBFbx2BE5FHgbWCaiGwTkYuAhcCJIrIOOMF6DvAisAEoBf4C/BjAGFML3AK8Zx03W2UhaWeEwyRG/y3xG/HjZM4RsqedEcaYs0O8NHOQcw1wWYjPWQwstntd/S10WH6+jsnym7TMiO+hK4/TROcwbbr6T2OtNl3D0aXU1S4ys8IO2FYelJymYx9D896imnZoonNYT0+32yGoCPX29Lgdgqd5rbZmhzZdHdbcpGOy/KajrdntELzLZrPVa8lQa3QO081x/Ec3xwktMEbOY1nMBq3ROUw3x/Ef3RwnPD/W6DTROeyZp592OwQVob8/+4zbIXiaLrypdvH000+6HYKK0HOa6MLzYabTe3QO6+rSXd/9pqdH/87CCTW9y8skMMvCfS+//HIVEHU3tGpra/MiWMVBeUCU/53tNXPmzPzdffPLL7/8f4DdqSPVM2fODLsg5kjxTKJTSimn6D06pVTU00SnlIp6mugcJCKzRWSNtV3b/KHfodw02FZ8KjpoonOIiMQC9xDYsm1f4GwR2dfdqNQQHmSI3aSUP2mic85hQKkxZoMxphN4jMD2bcqjQmzFp6KAJjrnRLwlm1LKGZrolFJRTxOdcyLekk0p5QxNdM55D5giIhNFJAE4i8D2bUqpEaaJziHGmG7gcgL7TX4OPGGMWe1uVCqcEFvxqSigU8CUUlFPa3RKqainiU4pFfU00Smlop4mOqVU1NNEp5SKeproRgkReVBEbrUef0NE1ozQdY2ITA7x2nIRudjm52wSkRN2M4bdfq+KDproPMT6hWwTkWYRqbCSU9pwX8cY84YxZpqNeM4XkTeH+/pKjTRNdN5zqjEmDTgYmAFcP/AEEdFNjZSKgCY6jzLGlAH/APaH/ibgZSKyDlhnlZ0iIh+JSL2IvCUiB/S9X0QOEpEPRKRJRB4HkoJeO1ZEtgU9LxGRZ0SkSkRqRORuEdkH+BNwpFXDrLfOTRSR34rIFqvW+ScRSQ76rGtEpFxEtovIhXa/r4hMEpFXrOtXi8hfRSRrwGmHishnIlInIg+ISPB3CvmzUEoTnUeJSAkwB/gwqPh04HBgXxE5CFgM/AeQC/wZeM5KRAnAs8DDQA7wJPCdENeJBZ4nsAPbBAJLST1mjPkc+CHwtjEmzRiTZb1lITAVmA5Mts6/wfqs2cB/AycCU4BI7osJcDswFtiHwIIINw4451zgJGCSFcP11nVD/iwiuL6KZsYYPTxyAJuAZqCeQOL5A5BsvWaA44PO/SNwy4D3rwGOAY4GtmNN8bNeewu41Xp8LLDNenwkUAXEDRLP+cCbQc8FaAEmBZUdCWy0Hi8GFga9NtWKe3KI77scuDjEa6cDHw742fww6PkcYP1QP4ug957g9t+vHu4deq/He043xvwrxGvBC3nuBcwTkSuCyhII1IgMUGaMCZ7IHGrP3BJgswksQjCUfCAFWClfbmIsQKz1eCyw0sY1dyEihcBdwDeAdAKtjboBpwV//83W9SD8z0Ipbbr6THDi2grcZozJCjpSjDGPAuVAschOW6qPD/GZW4HxITo4Bq74UA20AfsFXTPTBDpPsK4bvAZfqGsO5pfW9b5qjMkAziOQRIMN/OztQd8h1M9CKU10PvYX4IcicrgEpIrIN0UkncBSQ93AT0QkXkS+TWAPi8G8SyBBLbQ+I0lEvm69VgGMs+75YYzpta57p4gUAIhIsYicZJ3/BHC+iOwrIinAggi+TzqBZnuDiBQD1wxyzmUiMk5EcoCfA4/b+FkopYnOr4wx7wOXAHcTaOKVErinhglsxvNt63ktcCbwTIjP6QFOJdCxsIXA3hZnWi+/AqwGdohItVV2rXWtd0SkEfgXMM36rH8Av7PeV2r9addNBIbUNAAvhIj3b8A/gQ3AeuDWoX4WSoGuR6eUGgW0RqeUinqa6JRSUU8TnVIq6mmiU0pFPU10Sqmop4lOKRX1NNEppaKeJjqlVNTTRKeUinr/D+wCBxnJA+STAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "confusion(model_xgb,x_test,y_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Tuning LightGBM"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 664,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Fitting 3 folds for each of 4 candidates, totalling 12 fits\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/opt/anaconda3/lib/python3.8/site-packages/lightgbm/engine.py:177: UserWarning: Found `num_iterations` in params. Will use it instead of argument\n",
      "  _log_warning(f\"Found `{alias}` in params. Will use it instead of argument\")\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[LightGBM] [Warning] min_gain_to_split is set=1, min_split_gain=0.0 will be ignored. Current value: min_gain_to_split=1\n",
      "{'learning_rate': 0.1, 'max_bin': 300, 'max_depth': 20, 'min_gain_to_split': 1, 'num_iterations': 150, 'num_leaves': 31}\n",
      "Train: Model: lightGBM | Train AUC: 0.9770\n",
      "Test: Model: lightGBM | Test AUC: 0.9122\n"
     ]
    }
   ],
   "source": [
    "#set estimator\n",
    "estimator = lgb.LGBMClassifier(random_state=123)\n",
    "\n",
    "#set parameter\n",
    "parameters = {\n",
    "                'num_leaves':[31],\n",
    "                'max_depth':[20],\n",
    "                # 'feature_fraction':[0.8],\n",
    "                'min_gain_to_split':[1],\n",
    "                'learning_rate':[0.05,0.1],\n",
    "                'num_iterations':[100,150],\n",
    "                'max_bin':[300]\n",
    "                }\n",
    "\n",
    "#configure the GridSearchCV object\n",
    "grid_search = GridSearchCV(\n",
    "    estimator=estimator,\n",
    "    param_grid=parameters,\n",
    "    scoring = 'roc_auc',\n",
    "    n_jobs = 10,\n",
    "    cv = 3,\n",
    "    verbose=True)\n",
    "\n",
    "# fit the model\n",
    "grid_search.fit(X_SMOTE_train, y_SMOTE_train)\n",
    "print(grid_search.best_params_)\n",
    "best=grid_search.best_estimator_\n",
    "\n",
    "y_SMOTE_pred=best.predict_proba(X_SMOTE_train)\n",
    "train_auc = metrics.roc_auc_score(y_SMOTE_train, y_SMOTE_pred[:,1])\n",
    "y_pred=best.predict_proba(x_test)\n",
    "test_auc = metrics.roc_auc_score(y_test, y_pred[:,1])\n",
    "name='lightGBM'\n",
    "print('Train: Model: {} | Train AUC: {:.4f}'.format(name, train_auc))\n",
    "print('Test: Model: {} | Test AUC: {:.4f}'.format(name, test_auc))\n",
    "\n",
    "dictl[str(grid_search.best_params_)]=test_auc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 653,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{\"{'feature_fraction': 1, 'learning_rate': 0.1, 'max_bin': 455, 'min_gain_to_split': 0.5, 'num_leaves': 70}\": 0.9089937917253688,\n",
       " \"{'feature_fraction': 1, 'learning_rate': 0.1, 'max_bin': 400, 'min_gain_to_split': 0.5, 'num_leaves': 70}\": 0.9092712854199768,\n",
       " \"{'feature_fraction': 1, 'learning_rate': 0.1, 'max_bin': 400, 'min_gain_to_split': 0.3, 'num_leaves': 80}\": 0.9091630234387189,\n",
       " \"{'feature_fraction': 1, 'max_depth': -1, 'min_gain_to_split': 1, 'num_leaves': 31}\": 0.9106971087393182,\n",
       " \"{'max_depth': -1}\": 0.9113867361125785,\n",
       " \"{'max_depth': 50}\": 0.9113867361125785,\n",
       " \"{'max_depth': 100}\": 0.9113867361125785,\n",
       " \"{'max_depth': 20}\": 0.9114575116591496,\n",
       " \"{'max_depth': 10}\": 0.9106154056799329,\n",
       " \"{'max_depth': 15}\": 0.9109844444322224,\n",
       " \"{'max_depth': 25}\": 0.9113867361125785,\n",
       " \"{'max_bin': 400, 'max_depth': 20}\": 0.9108275152167425,\n",
       " \"{'max_bin': 300, 'max_depth': 20}\": 0.9116266710048652,\n",
       " \"{'max_bin': 250, 'max_depth': 20}\": 0.9114568603504388,\n",
       " \"{'max_bin': 300, 'max_depth': 20, 'num_leaves': 70}\": 0.9090778467328764,\n",
       " \"{'max_bin': 300, 'max_depth': 20, 'num_leaves': 20}\": 0.9114614918790488,\n",
       " \"{'max_bin': 300, 'max_depth': 20, 'num_leaves': 10}\": 0.9064274544858236,\n",
       " \"{'max_bin': 300, 'max_depth': 20, 'num_leaves': 40}\": 0.9110462463921116,\n",
       " \"{'max_bin': 300, 'max_depth': 20, 'num_leaves': 30}\": 0.9115602013325488,\n",
       " \"{'max_bin': 300, 'max_depth': 20, 'num_leaves': 49}\": 0.9103620465914409,\n",
       " \"{'max_bin': 300, 'max_depth': 20, 'num_leaves': 200}\": 0.904506455627206,\n",
       " \"{'max_bin': 300, 'max_depth': 20, 'num_leaves': 29}\": 0.9113328945924878,\n",
       " \"{'max_bin': 300, 'max_depth': 20, 'num_leaves': 19}\": 0.9100915363735651,\n",
       " \"{'boosting': 'gbdt', 'max_bin': 300, 'max_depth': 20}\": 0.9116266710048652,\n",
       " \"{'max_bin': 290, 'max_depth': 20}\": 0.9111621793426299,\n",
       " \"{'learning_rate': 0.1, 'max_bin': 300, 'max_depth': 20}\": 0.9116266710048652,\n",
       " \"{'learning_rate': 0.1, 'max_bin': 300, 'max_depth': 20, 'num_iterations': 100}\": 0.9116266710048652,\n",
       " \"{'learning_rate': 0.1, 'max_bin': 300, 'max_depth': 20, 'num_iterations': 200}\": 0.9113114014050321,\n",
       " \"{'learning_rate': 0.1, 'max_bin': 300, 'max_depth': 20, 'num_iterations': 150}\": 0.9119546411245584,\n",
       " \"{'learning_rate': 0.1, 'max_bin': 300, 'max_depth': 20, 'num_iterations': 170}\": 0.911742025014307,\n",
       " \"{'learning_rate': 0.2, 'max_bin': 300, 'max_depth': 20, 'num_iterations': 150}\": 0.9073390333941895,\n",
       " \"{'learning_rate': 0.15, 'max_bin': 300, 'max_depth': 20, 'num_iterations': 150}\": 0.9096447024141553,\n",
       " \"{'feature_fraction': 1, 'learning_rate': 0.1, 'max_bin': 300, 'max_depth': 20, 'num_iterations': 150}\": 0.9119546411245584,\n",
       " \"{'feature_fraction': 0.8, 'learning_rate': 0.1, 'max_bin': 300, 'max_depth': 20, 'num_iterations': 150}\": 0.9117335580010668,\n",
       " \"{'feature_fraction': 0.4, 'learning_rate': 0.1, 'max_bin': 300, 'max_depth': 20, 'num_iterations': 150}\": 0.9104516739068073,\n",
       " \"{'feature_fraction': 0.9, 'learning_rate': 0.1, 'max_bin': 300, 'max_depth': 20, 'num_iterations': 150}\": 0.9107360063428785,\n",
       " \"{'learning_rate': 0.1, 'max_bin': 300, 'max_depth': 20, 'min_gain_to_split': 1, 'num_iterations': 150}\": 0.91222772039346,\n",
       " \"{'learning_rate': 0.1, 'max_bin': 300, 'max_depth': 20, 'min_gain_to_split': 0.5, 'num_iterations': 150}\": 0.9103949014975179,\n",
       " \"{'learning_rate': 0.1, 'max_bin': 300, 'max_depth': 20, 'min_gain_to_split': 0.8, 'num_iterations': 150}\": 0.9108878336401238,\n",
       " \"{'learning_rate': 0.1, 'max_bin': 300, 'max_depth': 20, 'min_gain_to_split': 0.8, 'num_iterations': 150, 'num_leaves': 31}\": 0.9108878336401238,\n",
       " \"{'learning_rate': 0.1, 'max_bin': 300, 'max_depth': 20, 'min_gain_to_split': 1, 'num_iterations': 150, 'num_leaves': 31}\": 0.91222772039346,\n",
       " \"{'learning_rate': 0.05, 'max_bin': 300, 'max_depth': 20, 'min_gain_to_split': 1, 'num_iterations': 150, 'num_leaves': 70}\": 0.9096033443110212,\n",
       " \"{'learning_rate': 0.1, 'max_bin': 300, 'max_depth': 20, 'min_gain_to_split': 1, 'num_iterations': 150, 'num_leaves': 12}\": 0.9099619621239379,\n",
       " \"{'learning_rate': 0.1, 'max_bin': 300, 'max_depth': 20, 'min_gain_to_split': 1, 'num_iterations': 150, 'num_leaves': 25}\": 0.9116214243513617,\n",
       " \"{'learning_rate': 0.1, 'max_bin': 300, 'max_depth': 20, 'min_gain_to_split': 1, 'num_iterations': 150, 'num_leaves': 32}\": 0.9107804762542975,\n",
       " \"{'learning_rate': 0.1, 'max_bin': 300, 'max_depth': 20, 'min_gain_to_split': 1, 'num_iterations': 150, 'num_leaves': 30}\": 0.9100571255633458,\n",
       " \"{'learning_rate': 0.1, 'max_bin': 300, 'max_depth': 19, 'min_gain_to_split': 1, 'num_iterations': 150, 'num_leaves': 31}\": 0.9109103399744629,\n",
       " \"{'boosting': 'dart', 'learning_rate': 0.1, 'max_bin': 300, 'max_depth': 20, 'min_gain_to_split': 1, 'num_iterations': 150, 'num_leaves': 31}\": 0.9073114251416162,\n",
       " \"{'feature_fraction': 1, 'learning_rate': 0.1, 'max_bin': 300, 'max_depth': 20, 'min_gain_to_split': 1, 'num_iterations': 150, 'num_leaves': 31}\": 0.91222772039346,\n",
       " \"{'feature_fraction': 0.5, 'learning_rate': 0.1, 'max_bin': 300, 'max_depth': 20, 'min_gain_to_split': 1, 'num_iterations': 150, 'num_leaves': 31}\": 0.9109403363589758,\n",
       " \"{'feature_fraction': 0.4, 'learning_rate': 0.1, 'max_bin': 300, 'max_depth': 20, 'min_gain_to_split': 1, 'num_iterations': 150, 'num_leaves': 31}\": 0.9098461015410544,\n",
       " \"{'feature_fraction': 0.8, 'learning_rate': 0.1, 'max_bin': 300, 'max_depth': 20, 'min_gain_to_split': 1, 'num_iterations': 150, 'num_leaves': 31}\": 0.9110051415756981,\n",
       " \"{'bagging_fraction': 1, 'learning_rate': 0.1, 'max_bin': 300, 'max_depth': 20, 'min_gain_to_split': 1, 'num_iterations': 150, 'num_leaves': 31}\": 0.91222772039346,\n",
       " \"{'bagging_fraction': 0.75, 'learning_rate': 0.1, 'max_bin': 300, 'max_depth': 20, 'min_gain_to_split': 1, 'num_iterations': 150, 'num_leaves': 31}\": 0.91222772039346}"
      ]
     },
     "execution_count": 653,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dictl"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 666,
   "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>importance</th>\n",
       "      <th>features</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>788</td>\n",
       "      <td>Hours-per-week</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>666</td>\n",
       "      <td>Age</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>609</td>\n",
       "      <td>fnlwgt</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>521</td>\n",
       "      <td>Capital</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>309</td>\n",
       "      <td>Education-num</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>62</td>\n",
       "      <td>Occupation_ Adm-clerical</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>58</td>\n",
       "      <td>Occupation_ Machine-op-inspct</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>58</td>\n",
       "      <td>Occupation_ Craft-repair</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>54</td>\n",
       "      <td>Occupation_ Other-service</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>52</td>\n",
       "      <td>Occupation_ Transport-moving</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>51</td>\n",
       "      <td>Work-class_ Self-emp-not-inc</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>48</td>\n",
       "      <td>Occupation_ Farming-fishing</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>47</td>\n",
       "      <td>Marital-status_ Never-married</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>42</td>\n",
       "      <td>Work-class_ Local-gov</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>42</td>\n",
       "      <td>Occupation_ Sales</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>41</td>\n",
       "      <td>Sex_ Female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>41</td>\n",
       "      <td>Relationship_ Not-in-family</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>40</td>\n",
       "      <td>Marital-status_ Divorced</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>40</td>\n",
       "      <td>Occupation_ Handlers-cleaners</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>39</td>\n",
       "      <td>Occupation_ Protective-serv</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>38</td>\n",
       "      <td>Work-class_ State-gov</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>37</td>\n",
       "      <td>Work-class_ Private</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>37</td>\n",
       "      <td>Relationship_ Unmarried</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>34</td>\n",
       "      <td>Marital-status_ Married-civ-spouse</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>33</td>\n",
       "      <td>Occupation_ Prof-specialty</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>33</td>\n",
       "      <td>Occupation_ Exec-managerial</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>29</td>\n",
       "      <td>Native-country</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>29</td>\n",
       "      <td>Relationship_ Own-child</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>28</td>\n",
       "      <td>Race_ Black</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>27</td>\n",
       "      <td>Occupation_ Tech-support</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>23</td>\n",
       "      <td>Work-class_ Self-emp-inc</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>22</td>\n",
       "      <td>Work-class_ Federal-gov</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>22</td>\n",
       "      <td>Marital-status_ Separated</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>21</td>\n",
       "      <td>Race_ White</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>21</td>\n",
       "      <td>Relationship_ Wife</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>19</td>\n",
       "      <td>Relationship_ Other-relative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>18</td>\n",
       "      <td>Race_ Amer-Indian-Eskimo</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>18</td>\n",
       "      <td>Relationship_ Husband</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>18</td>\n",
       "      <td>Occupation_ Priv-house-serv</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>17</td>\n",
       "      <td>Marital-status_ Married-spouse-absent</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>13</td>\n",
       "      <td>Race_ Asian-Pac-Islander</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>11</td>\n",
       "      <td>Sex_ Male</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>9</td>\n",
       "      <td>Race_ Other</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>6</td>\n",
       "      <td>Marital-status_ Widowed</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>0</td>\n",
       "      <td>Marital-status_ Married-AF-spouse</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>0</td>\n",
       "      <td>Work-class_ Without-pay</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>0</td>\n",
       "      <td>Occupation_ Armed-Forces</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    importance                                features\n",
       "0          788                          Hours-per-week\n",
       "1          666                                     Age\n",
       "2          609                                  fnlwgt\n",
       "3          521                                 Capital\n",
       "4          309                           Education-num\n",
       "5           62                Occupation_ Adm-clerical\n",
       "6           58           Occupation_ Machine-op-inspct\n",
       "7           58                Occupation_ Craft-repair\n",
       "8           54               Occupation_ Other-service\n",
       "9           52            Occupation_ Transport-moving\n",
       "10          51            Work-class_ Self-emp-not-inc\n",
       "11          48             Occupation_ Farming-fishing\n",
       "12          47           Marital-status_ Never-married\n",
       "13          42                   Work-class_ Local-gov\n",
       "14          42                       Occupation_ Sales\n",
       "15          41                             Sex_ Female\n",
       "16          41             Relationship_ Not-in-family\n",
       "17          40                Marital-status_ Divorced\n",
       "18          40           Occupation_ Handlers-cleaners\n",
       "19          39             Occupation_ Protective-serv\n",
       "20          38                   Work-class_ State-gov\n",
       "21          37                     Work-class_ Private\n",
       "22          37                 Relationship_ Unmarried\n",
       "23          34      Marital-status_ Married-civ-spouse\n",
       "24          33              Occupation_ Prof-specialty\n",
       "25          33             Occupation_ Exec-managerial\n",
       "26          29                          Native-country\n",
       "27          29                 Relationship_ Own-child\n",
       "28          28                             Race_ Black\n",
       "29          27                Occupation_ Tech-support\n",
       "30          23                Work-class_ Self-emp-inc\n",
       "31          22                 Work-class_ Federal-gov\n",
       "32          22               Marital-status_ Separated\n",
       "33          21                             Race_ White\n",
       "34          21                      Relationship_ Wife\n",
       "35          19            Relationship_ Other-relative\n",
       "36          18                Race_ Amer-Indian-Eskimo\n",
       "37          18                   Relationship_ Husband\n",
       "38          18             Occupation_ Priv-house-serv\n",
       "39          17   Marital-status_ Married-spouse-absent\n",
       "40          13                Race_ Asian-Pac-Islander\n",
       "41          11                               Sex_ Male\n",
       "42           9                             Race_ Other\n",
       "43           6                 Marital-status_ Widowed\n",
       "44           0       Marital-status_ Married-AF-spouse\n",
       "45           0                 Work-class_ Without-pay\n",
       "46           0                Occupation_ Armed-Forces"
      ]
     },
     "execution_count": 666,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "feature_importance(best)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 416,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1440x1440 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from lightgbm import plot_importance\n",
    "fig, ax = plt.subplots(figsize=(20,20))\n",
    "plot_importance(best, ax=ax)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 665,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ROC AUC score: 0.91222772039346\n",
      "Accuracy score: 0.8579848124220787\n",
      "F1 score: [0.90695775 0.7001675 ]\n",
      "Precision score: [0.91422156 0.68268782]\n",
      "Classification report for classifier LGBMClassifier(max_bin=300, max_depth=20, min_gain_to_split=1,\n",
      "               num_iterations=150, random_state=123):\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.91      0.90      0.91      6787\n",
      "           1       0.68      0.72      0.70      2036\n",
      "\n",
      "    accuracy                           0.86      8823\n",
      "   macro avg       0.80      0.81      0.80      8823\n",
      "weighted avg       0.86      0.86      0.86      8823\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "report(best,x_test,y_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 667,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LGBMClassifier(random_state=123)"
      ]
     },
     "execution_count": 667,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lb=lgb.LGBMClassifier(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,\n",
    "               importance_type='split', learning_rate=0.1, max_depth=-1,\n",
    "               min_child_samples=20, min_child_weight=0.001, min_split_gain=0.0,\n",
    "               n_estimators=100, n_jobs=-1, num_leaves=31, objective=None,\n",
    "               random_state=123, reg_alpha=0.0, reg_lambda=0.0, silent='warn',\n",
    "               subsample=1.0, subsample_for_bin=200000, subsample_freq=0)\n",
    "lb.fit(X_SMOTE_train, y_SMOTE_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 668,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ROC AUC score: 0.9113867361125785\n",
      "Accuracy score: 0.8563980505496996\n",
      "F1 score: [0.90591817 0.69681742]\n",
      "Precision score: [0.91317365 0.67942137]\n",
      "Classification report for classifier LGBMClassifier(random_state=123):\n",
      "              precision    recall  f1-score   support\n",
      "\n",
      "           0       0.91      0.90      0.91      6787\n",
      "           1       0.68      0.72      0.70      2036\n",
      "\n",
      "    accuracy                           0.86      8823\n",
      "   macro avg       0.80      0.81      0.80      8823\n",
      "weighted avg       0.86      0.86      0.86      8823\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "report(lb,x_test,y_test)"
   ]
  }
 ],
 "metadata": {
  "interpreter": {
   "hash": "40d3a090f54c6569ab1632332b64b2c03c39dcf918b08424e98f38b5ae0af88f"
  },
  "kernelspec": {
   "display_name": "Python 3.8.3 ('base')",
   "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": "3.8.3"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}