LP1/DA/DA_Assign_2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# https://www.andreagrandi.it/2018/04/14/machine-learning-pima-indians-diabetes/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as no\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "import seaborn as sns #for finding heatmap\n",
    "from sklearn.metrics import confusion_matrix\n",
    "from sklearn.metrics import accuracy_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Reading data from csv file\n",
    "names=[\"NumTimesPrg\", \"PlGlcConc\", \"BloodP\",\n",
    "    \"SkinThick\", \"TwoHourSerIns\", \"BMI\",\n",
    "    \"DiPedFunc\", \"Age\", \"HasDiabetes\"]\n",
    "dataset=pd.read_csv(\"http://ftp.ics.uci.edu/pub/machine-learning-databases/pima-indians-diabetes/pima-indians-diabetes.data\",names=names);\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(768, 9)"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset.shape #find no. of rows and columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>NumTimesPrg</th>\n",
       "      <th>PlGlcConc</th>\n",
       "      <th>BloodP</th>\n",
       "      <th>SkinThick</th>\n",
       "      <th>TwoHourSerIns</th>\n",
       "      <th>BMI</th>\n",
       "      <th>DiPedFunc</th>\n",
       "      <th>Age</th>\n",
       "      <th>HasDiabetes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>3.845052</td>\n",
       "      <td>120.894531</td>\n",
       "      <td>69.105469</td>\n",
       "      <td>20.536458</td>\n",
       "      <td>79.799479</td>\n",
       "      <td>31.992578</td>\n",
       "      <td>0.471876</td>\n",
       "      <td>33.240885</td>\n",
       "      <td>0.348958</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>3.369578</td>\n",
       "      <td>31.972618</td>\n",
       "      <td>19.355807</td>\n",
       "      <td>15.952218</td>\n",
       "      <td>115.244002</td>\n",
       "      <td>7.884160</td>\n",
       "      <td>0.331329</td>\n",
       "      <td>11.760232</td>\n",
       "      <td>0.476951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.078000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>99.000000</td>\n",
       "      <td>62.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>27.300000</td>\n",
       "      <td>0.243750</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>117.000000</td>\n",
       "      <td>72.000000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>30.500000</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>0.372500</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>6.000000</td>\n",
       "      <td>140.250000</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>127.250000</td>\n",
       "      <td>36.600000</td>\n",
       "      <td>0.626250</td>\n",
       "      <td>41.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>17.000000</td>\n",
       "      <td>199.000000</td>\n",
       "      <td>122.000000</td>\n",
       "      <td>99.000000</td>\n",
       "      <td>846.000000</td>\n",
       "      <td>67.100000</td>\n",
       "      <td>2.420000</td>\n",
       "      <td>81.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       NumTimesPrg   PlGlcConc      BloodP   SkinThick  TwoHourSerIns  \\\n",
       "count   768.000000  768.000000  768.000000  768.000000     768.000000   \n",
       "mean      3.845052  120.894531   69.105469   20.536458      79.799479   \n",
       "std       3.369578   31.972618   19.355807   15.952218     115.244002   \n",
       "min       0.000000    0.000000    0.000000    0.000000       0.000000   \n",
       "25%       1.000000   99.000000   62.000000    0.000000       0.000000   \n",
       "50%       3.000000  117.000000   72.000000   23.000000      30.500000   \n",
       "75%       6.000000  140.250000   80.000000   32.000000     127.250000   \n",
       "max      17.000000  199.000000  122.000000   99.000000     846.000000   \n",
       "\n",
       "              BMI   DiPedFunc         Age  HasDiabetes  \n",
       "count  768.000000  768.000000  768.000000   768.000000  \n",
       "mean    31.992578    0.471876   33.240885     0.348958  \n",
       "std      7.884160    0.331329   11.760232     0.476951  \n",
       "min      0.000000    0.078000   21.000000     0.000000  \n",
       "25%     27.300000    0.243750   24.000000     0.000000  \n",
       "50%     32.000000    0.372500   29.000000     0.000000  \n",
       "75%     36.600000    0.626250   41.000000     1.000000  \n",
       "max     67.100000    2.420000   81.000000     1.000000  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "info=dataset.describe(); #View Statistics related to data\n",
    "info #print(info)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>NumTimesPrg</th>\n",
       "      <th>PlGlcConc</th>\n",
       "      <th>BloodP</th>\n",
       "      <th>SkinThick</th>\n",
       "      <th>TwoHourSerIns</th>\n",
       "      <th>BMI</th>\n",
       "      <th>DiPedFunc</th>\n",
       "      <th>Age</th>\n",
       "      <th>HasDiabetes</th>\n",
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       "  </thead>\n",
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       "      <th>0</th>\n",
       "      <td>6</td>\n",
       "      <td>148</td>\n",
       "      <td>72</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>33.6</td>\n",
       "      <td>0.627</td>\n",
       "      <td>50</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>85</td>\n",
       "      <td>66</td>\n",
       "      <td>29</td>\n",
       "      <td>0</td>\n",
       "      <td>26.6</td>\n",
       "      <td>0.351</td>\n",
       "      <td>31</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8</td>\n",
       "      <td>183</td>\n",
       "      <td>64</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>23.3</td>\n",
       "      <td>0.672</td>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>89</td>\n",
       "      <td>66</td>\n",
       "      <td>23</td>\n",
       "      <td>94</td>\n",
       "      <td>28.1</td>\n",
       "      <td>0.167</td>\n",
       "      <td>21</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>137</td>\n",
       "      <td>40</td>\n",
       "      <td>35</td>\n",
       "      <td>168</td>\n",
       "      <td>43.1</td>\n",
       "      <td>2.288</td>\n",
       "      <td>33</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "   NumTimesPrg  PlGlcConc  BloodP  SkinThick  TwoHourSerIns   BMI  DiPedFunc  \\\n",
       "0            6        148      72         35              0  33.6      0.627   \n",
       "1            1         85      66         29              0  26.6      0.351   \n",
       "2            8        183      64          0              0  23.3      0.672   \n",
       "3            1         89      66         23             94  28.1      0.167   \n",
       "4            0        137      40         35            168  43.1      2.288   \n",
       "\n",
       "   Age  HasDiabetes  \n",
       "0   50            1  \n",
       "1   31            0  \n",
       "2   32            1  \n",
       "3   21            0  \n",
       "4   33            1  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#check Data\n",
    "dataset.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>NumTimesPrg</th>\n",
       "      <th>PlGlcConc</th>\n",
       "      <th>BloodP</th>\n",
       "      <th>SkinThick</th>\n",
       "      <th>TwoHourSerIns</th>\n",
       "      <th>BMI</th>\n",
       "      <th>DiPedFunc</th>\n",
       "      <th>Age</th>\n",
       "      <th>HasDiabetes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>NumTimesPrg</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.129459</td>\n",
       "      <td>0.141282</td>\n",
       "      <td>-0.081672</td>\n",
       "      <td>-0.073535</td>\n",
       "      <td>0.017683</td>\n",
       "      <td>-0.033523</td>\n",
       "      <td>0.544341</td>\n",
       "      <td>0.221898</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>PlGlcConc</th>\n",
       "      <td>0.129459</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.152590</td>\n",
       "      <td>0.057328</td>\n",
       "      <td>0.331357</td>\n",
       "      <td>0.221071</td>\n",
       "      <td>0.137337</td>\n",
       "      <td>0.263514</td>\n",
       "      <td>0.466581</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BloodP</th>\n",
       "      <td>0.141282</td>\n",
       "      <td>0.152590</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.207371</td>\n",
       "      <td>0.088933</td>\n",
       "      <td>0.281805</td>\n",
       "      <td>0.041265</td>\n",
       "      <td>0.239528</td>\n",
       "      <td>0.065068</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SkinThick</th>\n",
       "      <td>-0.081672</td>\n",
       "      <td>0.057328</td>\n",
       "      <td>0.207371</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.436783</td>\n",
       "      <td>0.392573</td>\n",
       "      <td>0.183928</td>\n",
       "      <td>-0.113970</td>\n",
       "      <td>0.074752</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TwoHourSerIns</th>\n",
       "      <td>-0.073535</td>\n",
       "      <td>0.331357</td>\n",
       "      <td>0.088933</td>\n",
       "      <td>0.436783</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.197859</td>\n",
       "      <td>0.185071</td>\n",
       "      <td>-0.042163</td>\n",
       "      <td>0.130548</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BMI</th>\n",
       "      <td>0.017683</td>\n",
       "      <td>0.221071</td>\n",
       "      <td>0.281805</td>\n",
       "      <td>0.392573</td>\n",
       "      <td>0.197859</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.140647</td>\n",
       "      <td>0.036242</td>\n",
       "      <td>0.292695</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>DiPedFunc</th>\n",
       "      <td>-0.033523</td>\n",
       "      <td>0.137337</td>\n",
       "      <td>0.041265</td>\n",
       "      <td>0.183928</td>\n",
       "      <td>0.185071</td>\n",
       "      <td>0.140647</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.033561</td>\n",
       "      <td>0.173844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Age</th>\n",
       "      <td>0.544341</td>\n",
       "      <td>0.263514</td>\n",
       "      <td>0.239528</td>\n",
       "      <td>-0.113970</td>\n",
       "      <td>-0.042163</td>\n",
       "      <td>0.036242</td>\n",
       "      <td>0.033561</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.238356</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HasDiabetes</th>\n",
       "      <td>0.221898</td>\n",
       "      <td>0.466581</td>\n",
       "      <td>0.065068</td>\n",
       "      <td>0.074752</td>\n",
       "      <td>0.130548</td>\n",
       "      <td>0.292695</td>\n",
       "      <td>0.173844</td>\n",
       "      <td>0.238356</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               NumTimesPrg  PlGlcConc    BloodP  SkinThick  TwoHourSerIns  \\\n",
       "NumTimesPrg       1.000000   0.129459  0.141282  -0.081672      -0.073535   \n",
       "PlGlcConc         0.129459   1.000000  0.152590   0.057328       0.331357   \n",
       "BloodP            0.141282   0.152590  1.000000   0.207371       0.088933   \n",
       "SkinThick        -0.081672   0.057328  0.207371   1.000000       0.436783   \n",
       "TwoHourSerIns    -0.073535   0.331357  0.088933   0.436783       1.000000   \n",
       "BMI               0.017683   0.221071  0.281805   0.392573       0.197859   \n",
       "DiPedFunc        -0.033523   0.137337  0.041265   0.183928       0.185071   \n",
       "Age               0.544341   0.263514  0.239528  -0.113970      -0.042163   \n",
       "HasDiabetes       0.221898   0.466581  0.065068   0.074752       0.130548   \n",
       "\n",
       "                    BMI  DiPedFunc       Age  HasDiabetes  \n",
       "NumTimesPrg    0.017683  -0.033523  0.544341     0.221898  \n",
       "PlGlcConc      0.221071   0.137337  0.263514     0.466581  \n",
       "BloodP         0.281805   0.041265  0.239528     0.065068  \n",
       "SkinThick      0.392573   0.183928 -0.113970     0.074752  \n",
       "TwoHourSerIns  0.197859   0.185071 -0.042163     0.130548  \n",
       "BMI            1.000000   0.140647  0.036242     0.292695  \n",
       "DiPedFunc      0.140647   1.000000  0.033561     0.173844  \n",
       "Age            0.036242   0.033561  1.000000     0.238356  \n",
       "HasDiabetes    0.292695   0.173844  0.238356     1.000000  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#The correlation matrix is an important tool to understand the correlation between the different characteristics.\n",
    "#The values range from -1 to 1 and the closer a value is to 1 the bettere correlation there is between two characteristics.\n",
    "corr=dataset.corr();\n",
    "corr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fa580deeda0>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(corr,annot=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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W1R2jyihJkiStBp5JJEkaB79UVcdU1WQzvQW4tKqOAi5tpiVJkiQNkEUiSdI4Ohk4q7l9FvDsEWaRJEmSVgUvN5MkjVoBH01SwNuqahswUVU7AapqZ5JDej0wySZgE8DExATT09OL3vju3buX9LhhM2d/bF6/B4CJfX90G+DNZ184x/LL295yX4txfz1nmLO/2pJTkrTyWCSSJI3ak6rq1qYQdEmSLy70gU1BaRvA5ORkTU1NLXrj09PTLOVxw2bO/tjYDFO/ef0eXnfV4D8GbT91almPH/fXc4Y5+6stOSVJK4+Xm0mSRqqqbm1+7wI+CBwL3J7kUIDm967RJZQkSZJWB4tEkqSRSbJ/kgfN3AZ+GbgauAjY0Cy2Aeh9LZAkSZKkvvFyM0nSKE0AH0wCnTbpvVX1kSSfBs5PchpwE3DKCDNKkiRJq4JFIknSyFTVjcBje8z/OnD88BNJkiRJq9e8l5sleUeSXUmu7pp3YJJLklzf/D6gmZ8kf5nkhiSfT/L4QYaXJEmSJElSfyzkTKIzgb8C3tU1bwtwaVVtTbKlmX4F8HTgqObnZ4G3Nr8lSZIWbF0zClm37VtPXPCye1tekiRJvc17JlFVfRz4xqzZJwNnNbfPAp7dNf9d1fFvwNqZ0WkkSZIkSZI0vpbaJ9FEVe0EqKqdSQ5p5h8G3Ny13I5m3s7ZK0iyCdgEMDExwfT09Lwb3b179z2W27x+T8/lFrKuYZudvU3MPnxtzQ1mlyRJkqS26nfH1ekxr3otWFXbgG0Ak5OTNTU1Ne/Kp6en6V5u41ynl586/7qGbXb2NjH78LU1N5hdkiRJktpq3svN5nD7zGVkze9dzfwdwBFdyx0O3Lr0eJIkSZIkSRqGpRaJLgI2NLc3ABd2zX9hM8rZccBdM5elSZIkSdIgJFmb5IIkX0xybZKfm2tEZknS3OYtEiU5B/gk8IgkO5KcBmwFnprkeuCpzTTAPwA3AjcAfwv89kBSS5IkSdKPvAn4SFU9EngscC0/GpH5KODSZlqStBfz9klUVc+f467jeyxbwIuXG0qSJGm51s3Rd6GklSXJg4FfBDYCVNX3ge8nORmYahY7C5gGXjH8hJLUHv3uuFqSJEmShuknga8C70zyWOBy4KXMPSLzPSxl1OXZ2jpCaltzQ3uzLyV3P0b1vuqWu+ZYd+/lZ697Nb3e42CUuS0SSZIkSWqzNcDjgZdU1WVJ3sQiLi1byqjLs7V1hNS25ob2Zl9K7n6M6j3XOuYye92r6fUeB6PMvdSOqyVJkiRpHOwAdlTVZc30BXSKRnONyCxJmoNFIkmSJEmtVVW3ATcneUQz63jgC8w9IrMkaQ5ebiZJkiSp7V4CnJ3kfnRGW34RnQPi5zejM98EnDLCfJLUChaJJEmSJLVaVV0JTPa4614jMkuS5maRSJIktYJD2kuSJA2WfRJJkiRJkiTJM4kkSZIkSWqbuc6w3b71xCEn0UrimUSSJEmSJEmySCRJkiRJkiSLRJIkSZIkScIikSRJkiRJkrBIJEmSJEmSJCwSSZIkSZIkCYtEkiRJkiRJwiKRJGkMJNknyWeTfKiZPjLJZUmuT3JekvuNOqMkSZK00lkkkiSNg5cC13ZNvxZ4Q1UdBdwBnDaSVJIkSdIqYpFIkjRSSQ4HTgTe3kwHeDJwQbPIWcCzR5NOkiRJWj3WjDqAJGnVeyPwcuBBzfRBwJ1VtaeZ3gEc1uuBSTYBmwAmJiaYnp5e9MZ37969pMcN22rLuXn9nvkXWoaJfQe/DWDZr8Vq+7sPmjklSdo7i0SSpJFJchKwq6ouTzI1M7vHotXr8VW1DdgGMDk5WVNTU70W26vp6WmW8rhhW205N265ePlh9mLz+j287qrBfwzafurUsh6/2v7ug2ZOSZL2ziKRJGmUngQ8K8kzgAcAD6ZzZtHaJGuas4kOB24dYUZJkiRpVbBIJEkamao6HTgdoDmT6A+q6tQk7wOeA5wLbAAuHFlIaQDWzXGm1PatJw45ibQyJNkOfAu4G9hTVZNJDgTOA9YB24HnVtUdo8ooSW2wrI6rk/xekmuSXJ3knCQPcNhiSVIfvAL4/SQ30Omj6IwR55Ekjb9fqqpjqmqymd4CXNqMlHlpMy1J2oslF4mSHAb8LjBZVUcD+wDPw2GLJUlLUFXTVXVSc/vGqjq2qh5eVadU1fdGnU+S1Don0xkhExwpU5IWZLmXm60B9k3yA2A/YCedYYt/rbn/LOBVwFuXuR1JkiRJmksBH01SwNuagQ0mqmonQFXtTHJIrweuppEyZ2trbmhv9vlyX3XLXfeat3n94rbRa/2LHdFz9jpW6us9rkaZe8lFoqq6JclfADcB3wU+ClzOAIctnv1CzbWjj+NO0NadE8w+Cm3NDWaXJEkj8aSqurUpBF2S5IsLfeBqGilztrbmhvZmny93P0b37DWy5mLXO3sdK/X1HlejzL3kIlGSA+icwnkkcCfwPuDpPRbt27DFs1+ouXb05Q43Owht3TnB7KPQ1txgdkmSNHxVdWvze1eSDwLHArcnObQ5i+hQYNdIQ0pSCyyn4+qnAF+uqq9W1Q+ADwBPpBm2uFnGYYslSZIkDUyS/ZM8aOY28MvA1cBFdEbIBEfKlKQFWU6fRDcBxyXZj87lZscDnwE+hsMWS5IkzTnUvaS+mgA+mAQ632/eW1UfSfJp4Pwkp9H57nLKCDNKUissp0+iy5JcAFwB7AE+S+fysYuBc5O8ppnnsMWSJEmSBqKqbgQe22P+1+kcyJYkLdCyRjerqlcCr5w1+0Y61wBLkiRJkiSpJZbTJ5EkSZIkSZJWiGWdSSRJkiRJkrQQc/XVt33riUNOorl4JpEkSZIkSZIsEkmSJEmSJMkikSRJkiRJkrBIJEmSJEmSJCwSSZIkSZIkCYtEkiRJkiRJwiKRJEmSJEmSgDWjDiBJkiRJkvpj3ZaLRx1BLeaZRJIkSZIkSbJIJEmSJEmSJItEkiRJkiRJwiKRJEmSJEmSsONqSZKksTG7s9HN6/cwNZookiRpFbJItAhz9RK/feuJQ04iSZIkSZLUX15uJkmSJKn1kuyT5LNJPtRMH5nksiTXJzkvyf1GnVGSxp1nEkmSpJGZ6yxdSVqClwLXAg9upl8LvKGqzk3yN8BpwFtHFU6S2sAziSRJI5PkAUk+leRzSa5J8upmvkd/JUkLluRw4ETg7c10gCcDFzSLnAU8ezTpJKk9PJNIkjRK3wOeXFW7k9wX+ESSDwO/j0d/JUkL90bg5cCDmumDgDurak8zvQM4rNcDk2wCNgFMTEwwPT296I3v3r17SY8btbbmhvZmny/35vV75rxvmN589oX3mJ7Yl7683nM9v0H9LVfqfjJIFokkSSNTVQXsbibv2/wUnaO/v9bMPwt4FRaJJEk9JDkJ2FVVlyeZmpndY9Hq9fiq2gZsA5icnKypqalei+3V9PQ0S3ncqLU1N7Q3+3y5N47pZdib1+/huX14ved6fttPXf66e1mp+8kgWSSSJI1Ukn2Ay4GHA28BvoRHf+9lpeYc1RHTiX3H52jt3vTryO2grdT9c1TaknOMPAl4VpJnAA+g0yfRG4G1SdY07cnhwK0jzChJrWCRSJI0UlV1N3BMkrXAB4FH9VpsjseumqO/KzXnqI6Ybl6/h9ddNf4fg/p15HbQVur+OSptyTkuqup04HSA5kyiP6iqU5O8D3gOcC6wAbhwzpVIkoBldlydZG2SC5J8Mcm1SX4uyYFJLmk6G70kyQH9CitJWrmq6k5gGjiO5uhvc5dHfyVJS/EK4PeT3ECnj6IzRpxHksbeckc3exPwkap6JPBYOkNObgEuraqjgEubaUmS7iXJQ5oziEiyL/AUOm3Jx+gc/QWP/kqSFqiqpqvqpOb2jVV1bFU9vKpOqarvjTqfJI27JReJkjwY+EWainxVfb85CnwynU5GwaEmJUl7dyjwsSSfBz4NXFJVH8Kjv5IkSdLQLedi/J8Evgq8M8lj6XQ6+lJgoqp2AlTVziSH9HrwUjobnd2J37CHz1vO9trcAaHZh6+tucHsWpyq+jzwuB7zbwSOHX4iSZIkafVaTpFoDfB44CVVdVmSN7GIS8uW0tno7E78hj183nK21+YOCM0+fG3NDWaXJEmSuq3r+h65ef0eNm65mO1bTxxhImluy+mTaAewo6oua6YvoFM0uj3JoQDN713LiyhJkiRJkqRBW3KRqKpuA25O8ohm1vHAF4CL6HQyCnY2KkmSJEmS1ArLudwM4CXA2UnuB9wIvIhO4en8JKcBNwGnLHMbkiRJkiRJGrBlFYmq6kpgssddxy9nvZIkSZIkSRqu5Z5JJEmSJEmr2lW33NVzkBs7J9Zc1s0xKJI0asvpuFqSJEmSJEkrhEUiSZIkSZIkWSSSJEmSJEmSRSJJkiRJkiRhkUiSJEmSJElYJJIkSZIkSRIWiSRJkiRJkoRFIkmSJEmSJGGRSJIkSZIkSVgkkiRJktRiSR6Q5FNJPpfkmiSvbuYfmeSyJNcnOS/J/UadVZLGnUUiSZIkSW32PeDJVfVY4BjghCTHAa8F3lBVRwF3AKeNMKMktYJFIkmSJEmtVR27m8n7Nj8FPBm4oJl/FvDsEcSTpFZZM+oAo7Zuy8U952/feuKQk0iSJElaiiT7AJcDDwfeAnwJuLOq9jSL7AAOm+Oxm4BNABMTE0xPTy96+xP7wub1e+41fynrGqbdu3ePfca5tCl7974x174y7ib2hTeffWHP+9Yf9mMLXs9cz31Qf8s27SfdRpl71ReJJEmSJLVbVd0NHJNkLfBB4FG9FpvjsduAbQCTk5M1NTW16O2/+ewLed1V9/5qtf3Uxa9rmKanp1nK8x0Hbcq+sevEhM3r9/TcV8bd3nIvZj/fONdJGgP6X2nTftJtlLnbt3dKkiRJUg9VdWeSaeA4YG2SNc3ZRIcDt440nLRCeXXOyrKqikRz7bySJGmwbIMlDUqShwA/aApE+wJPodNp9ceA5wDnAhuA3tfKSJJ+aFUViSRJkiStOIcCZzX9Et0HOL+qPpTkC8C5SV4DfBY4Y5QhJakNLBJJkiRJaq2q+jzwuB7zbwSOHX4iSWqv+4w6gCRp9UpyRJKPJbk2yTVJXtrMPzDJJUmub34fMOqskiRJ0kpnkUiSNEp7gM1V9Sg6nYy+OMmjgS3ApVV1FHBpMy1JkiRpgCwSSZJGpqp2VtUVze1vAdcChwEnA2c1i50FPHs0CSVJkqTVwz6JJEljIck6On1KXAZMVNVO6BSSkhwyx2M2AZsAJiYmmJ6eXvR2d+/evaTHDVvbc25ev2f4YfZiYt/xy9TLxL60+u8+bswpSdLeLbtI1Iwi8Bnglqo6KcmRdIaZPBC4AnhBVX1/uduRJK1cSR4IvB94WVV9M8mCHldV24BtAJOTkzU1NbXobU9PT7OUxw1b23Nu3HLx8MPsxeb1e3jdVeN/rGzz+j08t8V/93FjTkmS9q4fl5u9lM7lATNeC7yh6UfiDuC0PmxDkrRCJbkvnQLR2VX1gWb27UkObe4/FNg1qnySJEnSarGsIlGSw4ETgbc30wGeDFzQLGI/EpKkOTXtxhnAtVX1+q67LgI2NLc3ABcOO5skSZK02iz3POs3Ai8HHtRMHwTcWVUzF/nvoNMB6b0spR+J2ddnz9WXwFzrWkzfA4vpT2Ep2dvE7MPX1txgdi3ak4AXAFclubKZ94fAVuD8JKcBNwGnjCifNLbWzXEJ3/atJw45iSStLr7/aiVbcpEoyUnArqq6PMnUzOwei1avxy+lH4nZ12fP1b/B9lN7r2sx/SH0Wsdit9etzdeWm3342pobzK7FqapP0LvtADh+mFkkSZKk1W45ZxI9CXhWkmcADwAeTOfMorVJ1jRnEx0O3Lr8mJIkSZIkSRqkJReJqup04HSA5kyiP6iqU5O8D3gOnRHORtKPxFyn/0mSJLXNYj/X9FreSyAkSdJC9GN0s9leAfx+khvo9FF0xgC2IUmSJEmSpD5absfVAFTVNDDd3L4ROLYf65UkSZIkSdJwDOJMIkmSJEmSJLWMRSJJkiRJkiRZJJIkSZIkSZJFIkmSJEktluSIJB9Lcm2Sa5K8tJl/YJJLklzf/D5g1Fkladw4++5tAAAgAElEQVT1peNqSZIkSRqRPcDmqroiyYOAy5NcAmwELq2qrUm2AFvojMQsDcS6LRePOsJY8fVoJ4tEc3CHliRJksZfVe0Edja3v5XkWuAw4GRgqlnsLDqjMVskkqS98HIzSZIkSStCknXA44DLgImmgDRTSDpkdMkkqR08k0iSJElS6yV5IPB+4GVV9c0kC33cJmATwMTEBNPT04ve9sS+sHn9nnvNX8q6hmn37t1jn3Euo8ze62+9UHPtK+Nu0LkH9bds6z4+ytwWicZcr8vetm89cQRJJEmSpPGU5L50CkRnV9UHmtm3Jzm0qnYmORTY1euxVbUN2AYwOTlZU1NTi97+m8++kNddde+vVttPXfy6hml6epqlPN9xMMrsG5fRNcnm9Xt67ivjbtC5B/W/0tZ9fJS5vdxMkiRJUmulc8rQGcC1VfX6rrsuAjY0tzcAFw47myS1TftKmJIkSZL0I08CXgBcleTKZt4fAluB85OcBtwEnDKifJLUGhaJJEmSJLVWVX0CmKsDouOHmUWS2s4iUR/06jcI7DtIkiRJkiS1h0UijZQFNkmSJEmSxoMdV0uSJEmSJMkikSRJkiRJkiwSSZIkSZIkCfskkiRJWvHsA1CSJC2ERSLdQ68PkWeesP8IkkiSJEmSpGHycjNJkiRJkiR5JtGwebq3JEmSJEkaRxaJJEkjleQdwEnArqo6upl3IHAesA7YDjy3qu4YxPavuuUuNvYo4Fu8n1+vAx+b1+/p+XpqPHnwSpIkdfNyM0nSqJ0JnDBr3hbg0qo6Cri0mZYkSZI0QEs+kyjJEcC7gB8H/hPYVlVvGubRXw2HR9klDVJVfTzJulmzTwammttnAdPAK4YWSpIkSVqFlnO52R5gc1VdkeRBwOVJLgE20jn6uzXJFjpHf1flB/vuU7g9/V6SFmWiqnYCVNXOJIf0WijJJmATwMTEBNPT04vf0L6d9+jZlrKuQdq9e/fYZer1us31eo4bc+7dYve1cdw/ezGnJEl7t+QiUfPhfeYD/LeSXAschkd/JUlDUlXbgG0Ak5OTNTU1teh1vPnsC3ndVfduDrefuvh1DdL09DRLeX6D1Ovgx+b1e3q+nuPGnHu32P1/HPfPXswpaS720SZ19OVTR3OZwOOAyxjg0d/ZR1XacARwxnxHAud6/sM+ur2Yo8L9yDHXa9Kv59jWI3FtzQ1mV9/cnuTQph05FNg16kCSJEnSSrfsIlGSBwLvB15WVd9MsqDHLeXo7+yjKm26fGu+I4FzHbHr2RfQAI9uL+aocD9yzPU37NdzbOuRuLbmBrOrby4CNgBbm98XjjaOJEmStPItq0iU5L50CkRnV9UHmtke/R0zvU6d9LRJSeMiyTl0LlM+OMkO4JV0ikPnJzkNuAk4ZXQJJUmSpNVhOaObBTgDuLaqXt91l0d/Vwmv25XUD1X1/DnuOn6oQSRJrZXkHcBJwK6qOrqZ56jLkrRIyzmT6EnAC4CrklzZzPtDPPorSZIkabjOBP4KeFfXvC046rKWaa4D49JKtZzRzT4BzNUBkUd/JUmSJA1FVX28GUynm6MuS9Iijf/Yr6tEPyrUi1nHaq2Ie4mcJEnSqjGwUZfvtaEBjgY8SG0e2bXf2Yc1cvZ8o16Pq0HnHtR+2NZ9fJS5LRJJkiRJWrWWMurybG8++8KBjQY8SG0e2bXf2Yc1cvZ8o16Pq0HnHtT/Slv38VHmvs9ItipJkiRJg3V7M9oyjrosSQtjkUiSJEnSSjQz6jI46rIkLYhFIkmSJEmtluQc4JPAI5LsaEZa3go8Ncn1wFObaUnSXrTvYkiNvV6dQ9sxtCRJkgalqp4/x12Ouiy1gN8hx4dnEkmSJEmSJMkziaRB6lURB6vikiRJkqTxY5FIkiRJkiSNFQ+4j4aXm0mSJEmSJMkzidporoqqJEmSJKnDzpBXl15/7zNP2H8ESdrNM4kkSZIkSZLkmUSSJGl+nsUqSZK08lkk0lCM4svFui0Xs3n9Hjb6xUaSJEkSHvSQ5uPlZpIkSZIkSbJIJEmSJEmSJC8305gah5EI5joV1RERJEkr3WIux7BdlCQNk5cMDpZnEkmSJEmSJMkzidQeg6wYj0s1eiZHd4fbiz1COw5nYUmSJElS2yzmu9RKvfLEIpEkSZKWrB+jibb9A7UkSSuFRSJpkcalYtyPs58860iSJEmSNMMikdQniynaDPvytn5kW+hplpvX72FqwVuTJEnSSjMuB1WluYzzd7dRs+NqSZIkSZIkDe5MoiQnAG8C9gHeXlVbB7UtaSVbbZVrqZttibQ6DKqj0F5nu27ccvHAzmbw7InxZFuyOOOyH8/3GXg5A71o9bjqlruW1WfeUiy3S4+5+vob1n4+kCJRkn2AtwBPBXYAn05yUVV9YRDbkzR4g+oDCcajYR/1m7HuzbZEkrRctiWStDiDutzsWOCGqrqxqr4PnAucPKBtSZJWJtsSSdJy2ZZI0iKkqvq/0uQ5wAlV9RvN9AuAn62q3+laZhOwqZl8BHDdAlZ9MPC1PscdFrOPRluztzU3mH3Gw6rqIX1a16o0wLZktrbss+bsL3P2lzn7ayanbcky2ZbMq625ob3ZzT1c5l5kWzKoPonSY949qlFVtQ3YtqiVJp+pqsnlBBsVs49GW7O3NTeYXX01kLbkXhtpyd/dnP1lzv4yZ3+1JWdL2JbsRVtzQ3uzm3u4zL14g7rcbAdwRNf04cCtA9qWJGllsi2RJC2XbYkkLcKgikSfBo5KcmSS+wHPAy4a0LYkSSuTbYkkablsSyRpEQZyuVlV7UnyO8A/0hlq8h1VdU0fVr2s00BHzOyj0dbsbc0NZlefDLAtma0tf3dz9pc5+8uc/dWWnGPPtmRebc0N7c1u7uEy9yINpONqSZIkSZIktcugLjeTJEmSJElSi1gkkiRJkiRJ0ngWiZIckeRjSa5Nck2SlzbzD0xySZLrm98HjDrrbEkekORTST7XZH91M//IJJc12c9rOs4bS0n2SfLZJB9qpluRPcn2JFcluTLJZ5p5Y7/PACRZm+SCJF9s9vufa0P2JI9oXu+Zn28meVkbsgMk+b3m//TqJOc0/7+t2N/VH0lOSHJdkhuSbBl1nhlJ3pFkV5Kru+aN3f9VW9rrNrXNbWmD29LmtqF9bXtbqvFtS2Zry3v2XNry/titDe9BvbTpM/JiPjOl4y+b/9XPJ3n8mOX+82Zf+XySDyZZ23Xf6U3u65I8bZDZxrJIBOwBNlfVo4DjgBcneTSwBbi0qo4CLm2mx833gCdX1WOBY4ATkhwHvBZ4Q5P9DuC0EWacz0uBa7um25T9l6rqmKqabKbbsM8AvAn4SFU9Engsndd/7LNX1XXN630M8DPAd4AP0oLsSQ4DfheYrKqj6XRm+Tzatb9rGZLsA7wFeDrwaOD5TVszDs4ETpg1bxz/r9rSXrepbW5TG9yGNnfs29c2t6Ua+7Zktra8Z8+lTe+PM8b+PWi2Fn5GPpOFf2Z6OnBU87MJeOuQMvZyJvfOfQlwdFU9Bvh34HSA5v/0ecBPN4/56+a9ZzCqaux/gAuBpwLXAYc28w4Frht1tnly7wdcAfws8DVgTTP/54B/HHW+OTIfTucf6cnAh4C0KPt24OBZ88Z+nwEeDHyZpiP5NmWflfeXgf/dluzAYcDNwIF0Rnr8EPC0tuzv/vRlH7jH35dOQ3z6qHN15VkHXN013Yb/q7Fvr8e5bW5TG9yGNreN7Wvb2lJ/xr8tmSf72L9nd2VtzftjV+bWvQc1mVr3GXmhn5mAtwHP77XcOOSedd+vAGc3t+/xvkJntMafG1SucT2T6IeSrAMeB1wGTFTVToDm9yGjSza35lTIK4FddKqBXwLurKo9zSI76PzzjaM3Ai8H/rOZPoj2ZC/go0kuT7KpmdeGfeYnga8C72xOoX17kv1pR/ZuzwPOaW6PffaqugX4C+AmYCdwF3A57dnftXwzH4JmjPvfe6z/r8a9vW5J29ymNrgNbW4b29dWtaUC2teWAOP/nt1Dm94fZ7TxPWilfEae6zVu0//rrwMfbm4PNfdYF4mSPBB4P/CyqvrmqPMsVFXdXZ1Thg8HjgUe1Wux4aaaX5KTgF1VdXn37B6Ljl32xpOq6vF0TiN8cZJfHHWgBVoDPB54a1U9Dvg2Y3ba6Xyaa5KfBbxv1FkWqrk2+WTgSOChwP509p3ZxnV/1/K16f1trLWhvR73trmFbXAb2txWta9tbEsFjPf/aU9teM/u1sL3xxmteg+ascI/I7dhvyHJH9G5PPTsmVk9FhtY7rEtEiW5L503r7Or6gPN7NuTHNrcfyido4Fjq6ruBKbpXPO7Nsma5q7DgVtHlWsvngQ8K8l24Fw6p3O+kXZkp6pubX7vonMt/7G0Y5/ZAeyoqsua6QvoNChtyD7j6cAVVXV7M92G7E8BvlxVX62qHwAfAJ5IS/Z39cUO4Iiu6XH/e4/l/1Xb2usxbptb1Qa3pM1tW/vaxrZULWtL2vae3WjV+2OXtr0HzVgJn5Hneo3H/v81yQbgJODUaq4tY8i5x7JIlCTAGcC1VfX6rrsuAjY0tzfQuY52rCR5yEwv5En2pfNPdi3wMeA5zWJjmb2qTq+qw6tqHZ3Tnf+5qk6lBdmT7J/kQTO36VzTfzUt2Geq6jbg5iSPaGYdD3yBFmTv8nx+dHo8tCP7TcBxSfZr3nNmXvex39/VN58GjkpntI770Xnfu2jEmfZm7P6v2tJet6FtblMb3JY2t4XtaxvbUrWoLWnLe/ZsbXp/7NbC96AZK+Ez8lyv8UXAC9NxHHDXzGVp4yDJCcArgGdV1Xe67roIeF6S+yc5kk7H258aWJBBdXa0nB/g5+mcPvV54Mrm5xl0rj29FLi++X3gqLP2yP4Y4LNN9quBP27m/2Tzh7yBzmnE9x911nmexxTwobZkbzJ+rvm5BvijZv7Y7zNNzmOAzzT7zd8BB7Qo+37A14Ef65rXluyvBr7Y/K++G7h/G/Z3f/q6DzyDzugRX5p53xiHHzpfFHcCP6Bz9Oi0cfy/akt73ba2edzb4Da1uW1pX9vclvozvm1Jj5yteM+e5zmM9ftjj7yteA/qkbs1n5EX85mJzmVbb2n+V6+iM4LbOOW+gU7fQzP/n3/TtfwfNbmvA54+yGxpNihJkiRJkqRVbCwvN5MkSZIkSdJwWSSSJEmSJEmSRSJJkiRJkiRZJJIkSZIkSRIWiSRJkiRJkoRFIkmSJEmSJGGRSJIkSZIkSVgkkiRJkiRJEhaJJEmSJEmShEUiSZIkSZIkYZFIkiRJkiRJWCSSJEmSJEkSFokkSZIkSZKERSJJkiRJkiRhkUiSJEmSJElYJJIkSZIkSRIWiSRJkiRJkoRFIkmSJEmSJGGRSJIkSZIkSVgkkiRJkiRJEhaJJEmSJEmShEUiSZIkSZIkYZFIkiRJkiRJWCSSJEmSJEkSFokkSZIkSZKERSJJkiRJkiRhkUiSJEmSJElYJJIkSZIkSRIWiSRJkiRJkoRFIkmSJEmSJGGRSJIkSZIkSVgkkiRJkiRJEhaJJEmSJEmShEUiSZIkSZIkYZFIkiRJkiRJWCSSJEmSJEkSFok0ppL8TZL/OYD1virJe/q9XknSypPkw0k2LHDZ7UmeMuhMkqT2SPILSa4bdQ5pMSwSaSSaD9PfTfKtJHcm+T9JfivJfQCq6req6k+aZaeS/GeS3c3y1yV5UR8yrEtSzXpnfj633PVKkvqnV/ElycYkn1jmeivJt5v3/q8nuTTJr3YvU1VPr6qzlrOdBWaxwCRJfdS8r96eZP+ueb+RZLrP2/lw1/eIHyT5ftf031TVv1bVI/q5zQVk2pjk7ibDN5NcmeSkYWZQu1kk0ig9s6oeBDwM2Aq8AjhjjmVvraoHAg9ulvvbJI/uU461VfXA5uexfVqnJGn8PbZpWx4BnAn8VZJXjjaSJKlP1gAvHeQGmoMJD2zakrOB/9X1veK3BrnteXyyybSWzver85McOHuhJGuGnkxjzyKRRq6q7qqqi4BfBTYkOTrJmUle02PZqqq/A+4AHg2Q5LjmTKQ7k3wuydTM8kmOTPIvzRlIlwAHLyTT7MvSus46WtNMTyf5kyT/u1n3R5Mc3LX8z3dlujnJxiW9OJKkvUqyJcmXmvfiLyT5la77Ht60AXcl+VqS83qto6q+VlXvBv4f4PQkBzWPn07yG83tn0ryz81ZR19LcnaStbNW9YQmwx1J3pnkAV1ZTmqO5s6cPfuYZv67gZ8A/r456vvyZv7e2raNSW5snvOXk5zaj9dSklaYPwf+YPZ79ezP9c287vf7jc1n/Dc078E3JnliM//mJLuy8EuRp5Ls6JrenuS/J/l8czbrGUkmmjOSvpXkn5Ic0LX8stqCqvpP4B3AvsBPzuRJ8ooktwHvbNb18iQ7k9yazhlXleThC3uZtdJYJNLYqKpPATuAX5hrmST3ab4ArAWuSnIYcDHwGuBA4A+A9yd5SPOQ9wKX0ykO/QmwoDf0Bfo14EXAIcD9mm2T5CeADwNvBh4CHANc2cftSpJ+5Et02o0fA14NvCfJoc19fwJ8FDgAOJzO+/LeXEjnyPOxPe4L8GfAQ4FHAUcAr5q1zKnA04CfAv4L8D8Akjyezof0/xs4CHgbcFGS+1fVC4Cb6Jxd+8Cq+l97a9vSuXTiL4GnN2fjPhHbGEnq5TPANM1n9EX6WeDzdN6z3wucCzwBeDjwf9E58/SBS8z134Cn0mknnknne8Mf0vm+ch/gdwH60RY0hbDfAHYD1zezf7xZ38OATUlOAH4feErz/P7rEp+XVgiLRBo3t9J505rtoUnuBL4GvBJ4QVVdR+dN+h+q6h+q6j+r6hI6DcIzmmLNE4D/WVXfq6qPA3/fY91fa6rzdyZZTCPyzqr696r6LnA+nWIQdL4k/FNVnVNVP6iqr1eVH+Alaen+rut9+k7gr2fuqKr3VdWtTRtwHp0PwTNFnh/Q+RD80Kr6j6raaz9GVfUDOu3Mvdqhqrqhqi5p2pOvAq/n3h+k/6qqbq6qbwB/Cjy/mf+bwNuq6rKqurvp5+h7wHFzRJmzbWvu/0/g6CT7VtXOqrpmb89LklaxPwZe0nUAeaG+XFXvrKq7gfPoHBj4f5s24KPA9+kUVJbizVV1e1XdAvwrcFlVfbaqvgd8EHhcs9xy2oLjmvbyNjpt0a9U1V1dj3tl81y+CzyXzveaa6rqO3QOuGgVs0ikcXMY8I0e82+tqrVVdWBVHVNV5zbzHwacMuvLw88Dh9I52ntHVX27az1f6bHug5t1r62qv1hE1tu6bn8HmDmacASdI9uSpP54dtf79Frgt2fuSPLCrsu47gSO5keXFr+czhlAn0pyTZJf39tGktyXzhmg92qHkhyS5NwktyT5JvAe7n0J881dt79Cpx2CTlu1eVZbdUTX/bPN2bY1bdqvAr8F7ExycZJH7u15SdJqVVVXAx8Ctizyobd33f5us67Z85Z6JtHs9cy13uW0Bf/WtJkHV9VxVfVPXfd9tar+o2v6odyz/eq+rVXIIpHGRpIn0CkSLWbEmpuBd3d/eaiq/atqK7ATOCBdoxrQ6fdhIb4N7Nc1/eOLzPRTi1hekrQESR4G/C3wO8BBTQHpajqFIarqtqr6zap6KJ1Lvf56nj4WTgb2AJ/qcd+fAQU8pqoeTOcIb2Ytc0TX7Z+gc3YsdNqFP53VVu1XVec099es9eytbaOq/rGqnkrngMgXm9dAktTbK+mc0XlYMz1zAHmpn/WHZVBtwew2ZyedS7JnHIFWNYtEGrkkD05nWMZzgfdU1VWLePh7gGcmeVqSfZI8oOmQ7fCq+gqdUzJfneR+SX6eznW/C3El8ItJfiLJjwGnLyLT2cBTkjw3yZokByU5Zt5HSZIWa386H3a/CpDkRXTOJKKZPiXJzAffO5pl7569kiQHNh1+vgV4bVV9vce2HkSnT4c7m34i/nuPZV6c5PB0RpD5QzqXKEDng/tvJfnZdOyf5MQk/z979x9va1nX+f/11qOGiAKSe05AHSssfzAq3zNI2dgecQzBwCYtjBSI5oyNleZp4qTzHbXpx3EKLalsTmJgg6L5CxJtQGTb1wpSFEEE44gnOHIEFUGOGnXo8/3jvjess8/aZ6/9c617rdfz8diPte7r/rE+11prr2utz31d131Qu/4O4Ht7jjNv29ZOcHpyewLkvjamfeokSWpU1Xaaz+Nfbpe/AnwJ+Nn2M/bnGM0TvGvVFrwbODPJE5M8kmaIniaYSSIN018muZcmS/4amvkdzlzMAarqNpozv6+m+ZFwG80X99n39s/QTDx3F81ZhLcPeNzLaRqT62gmvv7gImK6lWas8Ob2ca8Fnjro/pKkwVTV54BzgL+jSbQcDfxNzyb/Drg6yW7gEuAVVfXFnvWfaddtp5nY81eqar4vx68HjgHuoZlI9H19tnkHzUTZt7R/v9nG+Umas9h/SJOs2g6c0bPf7wD/fXZuvAXatofQtC+307QxP0rP8DtJUl+/QXNiYdZ/pvlc/RrwZOBvhxHU/qxVW1BVH6aZBPtKmvbp79pV9y0jfHVYqub2NpMkSZIkSZMmyRNphm4/oqr2DDserT17EkmSJEmSNKGS/EQ7PcchwBuAvzRBNLlMEkmSJEmSNLn+C82Qti/QzG30C8MNR8PkcDNJkiRJkiTZk0iSJEnS6EvytiR3Jvlsn3W/mqSSHNYuJ8mbk2xPcl2SY9Y+YknqnnXDDgDgsMMOqw0bNuxV9s1vfpMDDzyw/w5jyPqOt0mrL0xenefW95prrvlqVX3nEEOaOP3akkFMwnt13Oto/bpv3Ou41PrZluzjfJqrBO51tdokRwL/Ebi1p/h5wFHt3zOAt7S3+zXubUkX4uxCjNCNOLsQI3Qjzi7HuNi2ZCSSRBs2bOCTn/zkXmUzMzNMT08PJ6AhsL7jbdLqC5NX57n1TfKPw4tmMvVrSwYxCe/Vca+j9eu+ca/jUutnW7K3qvrrJBv6rHoT8GvAxT1lpwBvr2ZujauSHJxkfVXt2t9jjHtb0oU4uxAjdCPOLsQI3YizyzEuti1xuJkkSZKkTkpyMvClqvrMnFWHA7f1LO9syyRJ+zESPYkkSZIkaTGSPBJ4DfDcfqv7lPW9Yk+STcAmgKmpKWZmZhYdy+7du5e031rrQpxdiBG6EWcXYoRuxDlJMZokkiRJktRF3wc8HvhMEoAjgE8lOZam59CRPdseAdze7yBVtQ3YBrBx48ZaypCSLgxFgW7E2YUYoRtxdiFG6EackxTjgsPN+l1FIMmhSS5PcnN7e0hb7lUEJEmSJK26qrq+qh5XVRuqagNNYuiYqvoycAnw0vb3yXHAPQvNRyRJGmxOovOBE+aUbQGuqKqjgCvaZdj7KgKbaK4iIEmSJEnLkuSdwN8BP5BkZ5Kz9rP5h4BbgO3AnwL/dQ1ClKTOW3C42TxXETgFmG7vXwDMAGezxKsISJLGX5IdwL3A/cCeqtqY5FDgXcAGYAfwU1X19TTjBv4AOBH4FnBGVX1qGHFLkkZDVb14gfUbeu4X8PLVjkmSxs1S5ySamk38VNWuJI9ry+e7isA+SaKFJojrwsRQK8n6jrdJqy9MXp0nrb7L8B+q6qs9y7M9U7cm2dIun83ePVOfQdMz9RlrHawkSZI0SVZ64uqBryKw0ARxXZgYaiVZ3/E2afWFyavzpNV3BdkzVZIkSRoRg8xJ1M8dSdYDtLd3tuUDX0VAkjRxCrgsyTVtb1KY0zMVWKhnqiRJkqRVstSeRJcApwNb29uLe8p/MclFNMMCRv4qAhu2XNq3fMfWk9Y4Ekkae8+sqtvbIcqXJ7lpP9sO1DN1oaHLg7jzrns498KL9yk/+vDHLPpYo2rch0Nav+4b9zqOe/20eP1+g/j7Q9IoWDBJ1F5FYBo4LMlO4LU0yaF3t1cUuBV4Ubv5h2gmGd1OM9HomasQsySpg6rq9vb2ziTvB46l7Znazm+36J6pCw1dHsS5F17MOdfv2xzuOG3xxxpV4z4c0vp137jXcdzrJ0kaH4Nc3Wy+qwgc32dbryIgSdpHkgOBh1TVve395wK/wRj1TJUkSZK6bqUnrpYkqZ8p4P3Nle1ZB7yjqv4qySewZ6okSZI0EkwSSZJWXVXdAjy1T/nXsGeqJEmSNBKWenUzSZIkSZIkjRGTRJIkSZIkSTJJJEmSJEmSJJNEkiRJkiRJwiSRJEmSJEmSMEkkSZIkSZIkTBJJkiRJkiQJk0SSJEmSJEnCJJEkSZIkSZIwSSRJkiRJkiRMEkmSJEmSJAmTRJIkSZIkScIkkSRJkiRJkjBJJEmSJEmSJEwSSZIkSZIkCZNEkiRJkjogyduS3Jnksz1lv5vkpiTXJXl/koN71v16ku1JPp/kx4YTtSR1i0kiSZIkSV1wPnDCnLLLgadU1b8F/gH4dYAkTwJOBZ7c7vPHSR66dqFKUjeZJJIkSZI08qrqr4G75pRdVlV72sWrgCPa+6cAF1XVfVX1RWA7cOyaBStJHWWSSJIkSdI4+Dngw+39w4HbetbtbMskSfuxbtgBSJIkSdJyJHkNsAe4cLaoz2Y1z76bgE0AU1NTzMzMLPrxd+/evaj9Nh+9Z5+ypTzuYi02zmHoQozQjTi7ECN0I85JitEkkSRJkqTOSnI68Hzg+KqaTQTtBI7s2ewI4PZ++1fVNmAbwMaNG2t6enrRMczMzLCY/c7Ycuk+ZTtOW/zjLtZi4xyGLsQI3YizCzFCN+KcpBgdbiZJkiSpk5KcAJwNnFxV3+pZdQlwapJHJHk8cBTw98OIUZK6xJ5EkiRJkkZekncC08BhSXYCr6W5mtkjgMuTAFxVVS+rqhuSvBv4HM0wtJdX1f3DiVySusMkkSRJkqSRV1Uv7lN83n62/y3gt1YvIkkaPw43kyRJkiRJkkkiSZIkSZIkmSSSJEmSJAwvQrsAACAASURBVEkSJokkSZIkSZKESSJJkiRJkiRhkkiSJEmSJEmYJJIkSZIkSRImiSRJkiRJkoRJIkmSJEmSJAHrlrNzkl8Bfh4o4HrgTGA9cBFwKPAp4CVV9c/LjFOSJEmSRtL1X7qHM7Zcuk/5jq0nDSEaSVq6JfckSnI48MvAxqp6CvBQ4FTgDcCbquoo4OvAWSsRqCRJkiRJklbPcoebrQMOSLIOeCSwC3g28J52/QXAC5b5GJKkMZHkoUk+neSD7fLjk1yd5OYk70ry8Lb8Ee3y9nb9hmHGLUmSJE2CJQ83q6ovJfk94Fbg28BlwDXA3VW1p91sJ3B4v/2TbAI2AUxNTTEzM7PX+t27d+9Ttho2H72nb/laPHavtarvqLC+42/S6jxp9V2GVwA3Ao9ul2d7n16U5E9oep++pb39elV9f5LZXqo/PYyAJUmSpEmx5CRRkkOAU4DHA3cDfwE8r8+m1W//qtoGbAPYuHFjTU9P77V+ZmaGuWWrod/YYYAdp63+Y/daq/qOCus7/iatzpNW36VIcgRwEvBbwKuShKb36c+0m1wAvI4mSXRKex+a3ql/mCRV1bdNkSRJkrR8y5m4+jnAF6vqKwBJ3gf8MHBwknVtb6IjgNuXH6YkaQz8PvBrwEHt8mOZv/fp4cBtAFW1J8k97fZf7T3gQr1SBzF1QP9epePUM2zce7pZv+4b9zqOe/0kSeNjOUmiW4HjkjySZrjZ8cAngSuBF9Jc4ex04OLlBilJ6rYkzwfurKprkkzPFvfZtAZY92DBAr1SB3HuhRdzzvX7Nodr3aN0NY17Tzfr133jXsdxr58kaXwseeLqqrqaZgjAp4Dr22NtA86mGUawneas73krEKckqdueCZycZAfNSYRn0/QsOri9+AHs3ft0J3AkQLv+McBdaxmwJEmSNGmWdXWzqnptVf1gVT2lql5SVfdV1S1VdWxVfX9Vvaiq7lupYCVJ3VRVv15VR1TVBuBU4KNVdRoP9j6FvXufXtIu067/qPMRSZIkSatrWUkiSZKWab7ep+cBj23LXwVsGVJ8kiRJ0sRYzpxEkiQtWlXNADPt/VuAY/ts80/Ai9Y0MEmSJGnC2ZNIkiRJkiRJJokkSZIkSZLkcDNJkiRJ6pQNWy7tW75j60lrHImkcWNPIkmSJEkjL8nbktyZ5LM9ZYcmuTzJze3tIW15krw5yfYk1yU5ZniRS1J3mCSSJEmS1AXnAyfMKdsCXFFVRwFX8ODVMJ8HHNX+bQLeskYxSlKnmSSSJEmSNPKq6q+Bu+YUnwJc0N6/AHhBT/nbq3EVcHCS9WsTqSR1l0kiSZIkSV01VVW7ANrbx7XlhwO39Wy3sy2TJO2HE1dLkiRJGjfpU1Z9N0w20QxJY2pqipmZmUU/2NQBsPnoPfuUz3esxWw76P6DHGP37t1Lqt9a6kKM0I04uxAjdCPOSYrRJJEkSZKkrrojyfqq2tUOJ7uzLd8JHNmz3RHA7f0OUFXbgG0AGzdurOnp6UUHce6FF3PO9fv+tNpxWv9jndHn6mTzbTvo/oMcY2ZmhqXUby11IUboRpxdiBG6EeckxehwM0mSJElddQlwenv/dODinvKXtlc5Ow64Z3ZYmiRpfvYkkiRJkjTykrwTmAYOS7ITeC2wFXh3krOAW4EXtZt/CDgR2A58CzhzzQOWpA4ySSRJkiRp5FXVi+dZdXyfbQt4+epGJEnjx+FmkiRJkiRJMkkkSZIkSZIkk0SSJEmSJEnCJJEkSZIkSZIwSSRJkiRJkiRMEkmSJEmSJAmTRJIkSZIkScIkkSRJkiRJkoB1ww5gVG3Ycuk+ZTu2njSESCRJkiRJklafPYkkSZIkSZJkkkiSJEmSJEljOtys31AxSZIkSZIkzc+eRJIkSZIkSTJJJEmSJEmSJJNEkiRJkiRJwiSRJEmSJEmSMEkkSZIkSZIkTBJJkiRJkiQJk0SSJEmSJEnCJJEkSZIkSZJYZpIoycFJ3pPkpiQ3JvmhJIcmuTzJze3tISsVrCRJkiRJklbHcnsS/QHwV1X1g8BTgRuBLcAVVXUUcEW7LEmSJEmSpBG25CRRkkcDzwLOA6iqf66qu4FTgAvazS4AXrDcICVJ3ZbkO5L8fZLPJLkhyevb8scnubrtffquJA9vyx/RLm9v128YZvySJEnSJFhOT6LvBb4C/FmSTyd5a5IDgamq2gXQ3j5uBeKUJHXbfcCzq+qpwNOAE5IcB7wBeFPb+/TrwFnt9mcBX6+q7wfe1G4nSVJfSX6lPQnx2STvbE9O9D0RIUma37pl7nsM8EtVdXWSP2ARQ8uSbAI2AUxNTTEzM7PX+t27d+9TNqjNR+9Z0n4LWWo8g1hOfbvI+o6/SavzpNV3saqqgN3t4sPavwKeDfxMW34B8DrgLTS9Ul/Xlr8H+MMkaY8jSdIDkhwO/DLwpKr6dpJ3A6cCJ9KciLgoyZ/QnIB4yxBDlaSRt5wk0U5gZ1Vd3S6/hyZJdEeS9VW1K8l64M5+O1fVNmAbwMaNG2t6enqv9TMzM8wtG9QZWy5d0n4L2XHa9KocF5ZX3y6yvuNv0uo8afVdiiQPBa4Bvh/4I+ALwN1VNZvZ3wkc3t4/HLgNoKr2JLkHeCzw1TnH3O8Jh0FMHdD/5MI4Jf3GPYlp/bpv3Os47vUbEeuAA5L8C/BIYBfzn4iQJM1jyUmiqvpyktuS/EBVfR44Hvhc+3c6sLW9vXhFIpUkdVpV3Q88LcnBwPuBJ/bbrL3Nftb1HnO/JxwGce6FF3PO9fs2h6t5YmCtjXsS0/p137jXcdzrN2xV9aUkvwfcCnwbuIzmpMR8JyIkSfNYTk8igF8CLmzH994CnEkzz9G7k5xF80H9omU+hiRpjFTV3UlmgOOAg5Osa7/EHwHc3m62EzgS2JlkHfAY4K5hxCtJGm1JDqEZpvx44G7gL4Dn9dm075DlYfRKXW4P1vmm11joGF3o1daFGKEbcXYhRuhGnJMU47KSRFV1LbCxz6rjl3NcSdJ4SfKdwL+0CaIDgOfQTEZ9JfBC4CL27n16Sbv8d+36jzofkSRpHs8BvlhVXwFI8j7gh5n/RMRehtErtd/0GIvpwTrf9BoLHaMLvdq6ECN0I84uxAjdiHOSYlzO1c0kSRrUeuDKJNcBnwAur6oPAmcDr0qynWbOofPa7c8DHtuWv4pFXBhBkjRxbgWOS/LIJOHBaTBmT0SA02BI0kCWO9xMkqQFVdV1wNP7lN8CHNun/J9wuLIkaQDtlZbfA3wK2AN8mqZn0KXARUl+sy07b/6jSJLAJJEkSZKkjquq1wKvnVPc90SEJGl+DjeTJEmSJEmSSSJJkiRJkiSZJJIkSZIkSRLOSSRJkiRJE2fDlkv7lu/YetIaRyJplNiTSJIkSZIkSSaJJEmSJEmSZJJIkiRJkiRJOCfRojhuV5IkSfOZ77vi+SccuMaRSJK0NPYkkiRJkiRJkkkiSZIkSZIkmSSSJEmSJEkSJokkSZIkSZKESSJJkiRJkiRhkkiSJEmSJEnAumEHIEmSJEnqng1bLu1bvmPrSWsciaSVYk8iSZIkSZIkmSSSJEmSJEmSSSJJkiRJkiRhkkiSJEmSJEmYJJIkSZIkSRImiSRJkiRJkoRJIkmSJEmSJGGSSJIkSZIkSZgkkiRJktRxSQ5O8p4kNyW5MckPJTk0yeVJbm5vDxl2nJI06tYNO4BxsGHLpX3Ld2w9aY0jkSRJkibSHwB/VVUvTPJw4JHAq4Erqmprki3AFuDsYQYpSaPOnkSSJEmSOivJo4FnAecBVNU/V9XdwCnABe1mFwAvGE6EktQd9iSSJEmS1GXfC3wF+LMkTwWuAV4BTFXVLoCq2pXkcf12TrIJ2AQwNTXFzMzMogOYOgA2H71nn/L5jrWYbQfdf5Bj7N69+4FtlnqMlYhjf3pjHGVdiLMLMUI34pykGE0SSZIkSeqydcAxwC9V1dVJ/oBmaNlAqmobsA1g48aNNT09vegAzr3wYs65ft+fVjtO63+sM/pMVzHftoPuP8gxZmZmmK3fUo+xEnHsT2+Mo6wLcXYhRuhGnJMUo8PNJEmSJHXZTmBnVV3dLr+HJml0R5L1AO3tnUOKT5I6w55Eq6jfhNZOZi1JkiStnKr6cpLbkvxAVX0eOB74XPt3OrC1vb14iGFKUieYJJIkSZLUdb8EXNhe2ewW4EyaURPvTnIWcCvwoiHGJ0mdYJJIkiRJUqdV1bXAxj6rjl/rWLQ4c0dfbD56D2dsudQRGNKQLHtOoiQPTfLpJB9slx+f5OokNyd5V5vNlyRJkiRJ0ghbiYmrXwHc2LP8BuBNVXUU8HXgrBV4DElShyU5MsmVSW5MckOSV7Tlhya5vD2xcHmSQ9ryJHlzku1JrktyzHBrIEmSJI2/ZSWJkhwBnAS8tV0O8GyaKwoAXAC8YDmPIUkaC3uAzVX1ROA44OVJnkRzieIr2hMLV/DgJYufBxzV/m0C3rL2IUuSJEmTZblzEv0+8GvAQe3yY4G7q2pPu7wTOLzfjkk20XzxZ2pqipmZmb3W7969e5+yQW0+es/CGw3JfHVaTn27yPqOv0mr86TVd7Gqahewq71/b5IbadqHU4DpdrMLgBng7Lb87VVVwFVJDk6yvj2OJEmSpFWw5CRRkucDd1bVNUmmZ4v7bFr99q+qbcA2gI0bN9b09PRe62dmZphbNqgz+lx6flTsOG26b/ly6ttF1nf8TVqdJ62+y5FkA/B04GpgajbxU1W7kjyu3exw4Lae3WZPOuyVJFrohMMgpg7of3JhnJJ+457EtH7dNy51nO9E5bjUT5I0/pbTk+iZwMlJTgS+A3g0Tc+ig5Osa3sTHQHcvvwwJUnjIMmjgPcCr6yqbzSjlPtv2qdsn5MOC51wGMS5F17MOdfv2xzOl9TvonFPYlq/7huXOs53ovL8Ew4ci/pJksbfkuckqqpfr6ojqmoDcCrw0ao6DbgSeGG72enAxcuOUpLUeUkeRpMgurCq3tcW35Fkfbt+PXBnW74TOLJnd086SJIkSatsJa5uNtfZwKuSbKeZo+i8VXgMSVKHtBc2OA+4sare2LPqEpoTCrD3iYVLgJe2Vzk7DrjH+YgkSZKk1bXciasBqKoZmslGqapbgGNX4riSpLHxTOAlwPVJrm3LXg1sBd6d5CzgVuBF7boPAScC24FvAWeubbiSJEnS5FmRJJEkSftTVR+n/zxDAMf32b6Al69qUJIkSZL2YpJIkiRJktRZG+aZNH7H1pPWOBKp+1ZjTiJJkiRJkiR1jEkiSZIkSZIkmSSSJEmSJEmScxKNvH7jax1bK0mSJEmSVpo9iSRJkiRJkmSSSJIkSZIkSSaJJEmSJEmShHMSjYzrv3QPZ/SZf0iSJEmStLr6zQULzgeryWNPIkmSJEmSJJkkkiRJkiRJksPN1tx83Rg3H722j2m3SUmSJEmS1MueRJIkSZIkSTJJJEmSJKn7kjw0yaeTfLBdfnySq5PcnORdSR4+7BgladSZJJIkSZI0Dl4B3Niz/AbgTVV1FPB14KyhRCVJHWKSSJIkSVKnJTkCOAl4a7sc4NnAe9pNLgBeMJzoJKk7nLhakiRJUtf9PvBrwEHt8mOBu6tqT7u8Ezi8345JNgGbAKamppiZmVn0g08dAJuP3rNP+XzHWsy2g+4/yDF27979wDZLPcZKxLG/Y8w+l8OOY6Fj9D6Xo6oLMUI34pykGE0SSZIkSeqsJM8H7qyqa5JMzxb32bT67V9V24BtABs3bqzp6el+m+3XuRdezDnX7/vTasdp/Y91Rr+rD8+z7aD7D3KMmZkZZuu31GOsRBz7O8bmo/dwzvXrhh7HQsfofS5HVRdihG7EOUkxmiSSJEmS1GXPBE5OciLwHcCjaXoWHZxkXdub6Ajg9iHGKEmd4JxEkiRJkjqrqn69qo6oqg3AqcBHq+o04Erghe1mpwMXDylESeoMexJJkiRJGkdnAxcl+U3g08B5Q45HY27DfEPWtp60xpFIS2eSSJIkSdJYqKoZYKa9fwtw7DDjkaSuMUk0RubLXEuSJEmSJC3EOYkkSZIkSZJkkkiSJEmSJEkmiSRJkiRJkoRzEnWScw9JkiRJkqSVZk8iSZIkSZIkmSSSJEmSJEmSSSJJkiRJkiRhkkiSJEmSJEmYJJIkSZIkSRImiSRJkiRJkoRJIkmSJEmSJLGMJFGSI5NcmeTGJDckeUVbfmiSy5Pc3N4esnLhSpK6KMnbktyZ5LM9ZX3bizTenGR7kuuSHDO8yCVJkqTJsZyeRHuAzVX1ROA44OVJngRsAa6oqqOAK9plSdJkOx84YU7ZfO3F84Cj2r9NwFvWKEZJkiRpoq1b6o5VtQvY1d6/N8mNwOHAKcB0u9kFwAxw9rKilCR1WlX9dZINc4rnay9OAd5eVQVcleTgJOvbdkeSJGlsbdhy6T5lO7aeNIRINKmWnCTq1X7xfzpwNTA1+0W+qnYledw8+2yiOUPM1NQUMzMze63fvXv3PmVzXf+le/qWbz56EcGPiKkDYPPRe9bs8RZ6blfbIK/vOJm0+sLk1XnS6rtC5msvDgdu69luZ1u2T5JoobZkoCDm+fwdp9dz3N+f1q/7xqWO832XG5f6SZLG37KTREkeBbwXeGVVfSPJQPtV1TZgG8DGjRtrenp6r/UzMzPMLZvrjD5Z1q7afPQezrl+RXJ2A9lx2vSaPVY/g7y+42TS6guTV+dJq+8q69eQVL8NF2pLBnHuhRf3/fwd9ufkShr396f1675xqeN8303PP+HAsaifJGn8LevqZkkeRpMgurCq3tcW35Fkfbt+PXDn8kKUJI2p+dqLncCRPdsdAdy+xrFJkiRJE2c5VzcLcB5wY1W9sWfVJcDp7f3TgYuXHp4kaYzN115cAry0vcrZccA9zkckSZIkrb7ljG96JvAS4Pok17Zlrwa2Au9OchZwK/Ci5YUoSeq6JO+kmaT6sCQ7gdcyf3vxIeBEYDvwLeDMNQ9YkiRJmkDLubrZx+k/bwTA8Us9riRp/FTVi+dZtU970V7V7OWrG5EkSdJ4mr1C2uaj9zwwV5pXSNOg1m6mZI2UfpdWBD88JEmSJEmaVMuauFqSJEmSJEnjwSSRJEmSpM5KcmSSK5PcmOSGJK9oyw9NcnmSm9vbQ4YdqySNOpNEkiRJkrpsD7C5qp4IHAe8PMmTgC3AFVV1FHBFuyxJ2g+TRJIkSZI6q6p2VdWn2vv3AjcChwOnABe0m10AvGA4EUpSdzhxtSRJkqSxkGQD8HTgamCqqnZBk0hK8rh59tkEbAKYmppiZmZm0Y87dUBzJam55jvWYrYddP9BjrF79+4HtlnqMVYijv0dY/a5HHYcCx2j97lc7TgW+56cPUbv+3Ip7+u10u+5HDWTFKNJIkmSJEmdl+RRwHuBV1bVN5IMtF9VbQO2AWzcuLGmp6cX/djnXngx51y/70+rHaf1P9YZfa40PN+2g+4/yDFmZmaYrd9Sj7EScezvGJuP3sM5168behwLHaP3uVztOBazf+8xZp/LpRxjLfV7LkfNJMVokkh72TDPB1s/O7aetIqRSJIkSYNJ8jCaBNGFVfW+tviOJOvbXkTrgTuHF6EkdYNzEkmSJEnqrDRdhs4DbqyqN/asugQ4vb1/OnDxWscmSV1jTyKtuH69kex1JEmSpFXyTOAlwPVJrm3LXg1sBd6d5CzgVuBFQ4pPkjrDJJEkSZKkzqqqjwPzTUB0/FrGIkldZ5JIS7aY+YskSZIkSdJoc04iSZIkSZIkmSSSJEmSJEmSSSJJkiRJkiRhkkiSJEmSJEmYJJIkSZIkSRImiSRJkiRJkoRJIkmSJEmSJGGSSJIkSZIkScC6YQcgSZIkSZJGx4Ytl+5TtmPrSUOIRGvNJJEkSZIkSRop/RJVYLJqtTncTJIkSZIkSfYkkiRJkiRJK8sha91kkkidMV93w/n4ASRJkiRJ0uAcbiZJkiRJkiR7EmltzO0FtPnoPZyx5dJ5e/ssttfQUuOYZa8jSZIkSdKksyeRJEmSJEmSTBJJkiRJkiTJ4WYastUaVraax3bImiRJkiRpHNmTSJIkSZIkSfYkklZKvx5G9i6SJEmSJHWFPYkkSZIkSZJkTyIJutkLyLmRJEmSJEkradWSRElOAP4AeCjw1qraulqPJUkaT7YlkqTlsi2RJpcn1hdvVZJESR4K/BHwH4GdwCeSXFJVn1uNx5NWw2peeW0xj7nYD7DFxN3v2MP4IF2tnlwr8RragAyPbYkkablsSyRpcVarJ9GxwPaqugUgyUXAKYAfxpKkQdmWSJKWy7ZE0rJs2HIpm4/ewxlzTkCv1snkYfd+SlWt/EGTFwInVNXPt8svAZ5RVb/Ys80mYFO7+APA5+cc5jDgqyse3OiyvuNt0uoLk1fnufX9nqr6zmEFMw5WqC0ZxCS8V8e9jtav+8a9jkutn23JMtmW7KMLcXYhRuhGnF2IEboRZ5djXFRbslo9idKnbK9sVFVtA7bNe4Dkk1W1caUDG1XWd7xNWn1h8uo8afVdI8tuSwZ6kAl47ca9jtav+8a9juNevxFnW9KjC3F2IUboRpxdiBG6EeckxfiQlQimj53AkT3LRwC3r9JjSZLGk22JJGm5bEskaRFWK0n0CeCoJI9P8nDgVOCSVXosSdJ4si2RJC2XbYkkLcKqDDerqj1JfhH4vzSXmnxbVd2wyMMsq8tnB1nf8TZp9YXJq/Ok1XfVrVBbMohJeO3GvY7Wr/vGvY7jXr+RZVuyjy7E2YUYoRtxdiFG6EacExPjqkxcLUmSJEmSpG5ZreFmkiRJkiRJ6hCTRJIkSZIkSRp+kijJCUk+n2R7ki191j8iybva9Vcn2bD2Ua6cAep7RpKvJLm2/fv5YcS5EpK8LcmdST47z/okeXP7XFyX5Ji1jnGlDVDn6ST39Ly+/2OtY1wpSY5McmWSG5PckOQVfbYZm9d4wPqOzes7jsa9vRmgfq9K8rn2f/GKJN8zjDiXY6E69mz3wiSVZKQvVTvXIPVL8lPt63hDknesdYzLMcB79Lvbz9lPt+/TE4cR51JN4veeSTTqbUmXvq8k2ZHk+jaGT/ZZP9T/mSQ/0PMcXZvkG0leOWeboTyX/T5vkhya5PIkN7e3h8yz7+ntNjcnOX2NY/zdJDe1r+f7kxw8z777fW+sQZyvS/Klnte1b3s06PeSVYrxXT3x7Uhy7Tz7Lv65rKqh/dFMHvcF4HuBhwOfAZ40Z5v/CvxJe/9U4F3DjHkN6nsG8IfDjnWF6vss4Bjgs/OsPxH4MBDgOODqYce8BnWeBj447DhXqK7rgWPa+wcB/9Dn/Tw2r/GA9R2b13fc/sa9vRmwfv8BeGR7/xe6VL9B69hudxDw18BVwMZhx73Cr+FRwKeBQ9rlxw077hWu3zbgF9r7TwJ2DDvuRdZx4r73TNpfF9qSLn1fAXYAh+1n/cj8z7Sv/ZeB7xmF57Lf5w3wv4At7f0twBv67HcocEt7e0h7/5A1jPG5wLr2/hv6xTjIe2MN4nwd8KsDvCcW/F6yWjHOWX8O8D9W6rkcdk+iY4HtVXVLVf0zcBFwypxtTgEuaO+/Bzg+SdYwxpU0SH3HRlX9NXDXfjY5BXh7Na4CDk6yfm2iWx0D1HlsVNWuqvpUe/9e4Ebg8Dmbjc1rPGB9NbrGvb1ZsH5VdWVVfatdvAo4Yo1jXK5B29D/SfNF+Z/WMrgVMEj9/jPwR1X1dYCqunONY1yOQepXwKPb+48Bbl/D+JZtEr/3TKCRb0vG7PvKKP3PHA98oar+cUiPv5d5Pm9633sXAC/os+uPAZdX1V1tW3I5cMJaxVhVl1XVnnZxJL6LLOP325r9tt9fjO3ny08B71ypxxt2kuhw4Lae5Z3s+yH2wDbtG+oe4LFrEt3KG6S+AD/ZdsF7T5Ij1ya0oRj0+Rg3P5TkM0k+nOTJww5mJbRdqZ8OXD1n1Vi+xvupL4zh6zsmxr29Wez/2lk0Z2e7ZME6Jnk6cGRVfXAtA1shg7yGTwCekORvklyVZFW+2K+SQer3OuBnk+wEPgT80tqEtmbGsk2cMJ1qSzrwfaWAy5Jck2RTn/Wj9D9zKvP/CB+F5xJgqqp2QZMsBB7XZ5tRek5/jvm/iyz03lgLv9j+Jn/bPEP3RuW5/PfAHVV18zzrF/1cDjtJ1C+rXkvYpisGqctfAhuq6t8CH+HBbPA4GqfXdlCfoumm+lTgXOADQ45n2ZI8Cngv8Mqq+sbc1X126fRrvEB9x+71HSPj3t4MHHuSnwU2Ar+7qhGtvP3WMclDgDcBm9csopU1yGu4jmbI2TTwYuCt883nMIIGqd+LgfOr6giaYSZ/3r6u46LLnzFqdKYt6cj3lWdW1THA84CXJ3nWnPWj8lw+HDgZ+Is+q0fluRzUqDynrwH2ABfOs8lC743V9hbg+4CnAbtohnPNNRLPJU3bub9eRIt+Lofd8O4EenvKHMG+XYsf2CbJOprux10dzrNgfavqa1V1X7v4p8D/s0axDcMgr/9YqapvVNXu9v6HgIclOWzIYS1ZkofRfAG5sKre12eTsXqNF6rvuL2+Y2bc25uB/teSPAd4DXByT1vTFQvV8SDgKcBMkh0081dcku5MXj3oe/TiqvqXqvoi8HmapFEXDFK/s4B3A1TV3wHfAYzTZ+hYtYkTqhNtSVe+r1TV7e3tncD7aYbv9BqV/5nnAZ+qqjvmrhiV57J1x+xwvPa235DkoT+n7WTZzwdOq3bSnLkGeG+sqqq6o6rur6p/pflN3u/xR+G5XAf8J+Bd822zlOdy2EmiTwBHJXl8m6E9FbhkzjaXALOzrr8Q+Oh8b6YOWLC+c8bZnkwzjnhcXQK8NI3jgHtmu0iOqyT/ZnZcepJjaf4HvzbcqJamrcd5wI1V9cZ5Nhub13iQ+o7T6zuGxr29GaR9eTrwv2kSRF2ay2bWfutY+iqbQgAAIABJREFUVfdU1WFVtaGqNtDMdXByVa3qVVFW0CDv0Q/QTEBO+yPkCTSTjnbBIPW7lWbeD5I8kSZJ9JU1jXJ1jU2bOMFGvi3pyveVJAcmOWj2Ps2ExnOvDDgq/zPz9tQYheeyR+9773Tg4j7b/F/guUkOaYdQPbctWxPtMOmzadrnb82zzSDvjVU15zf5T8zz+IN8Hqy25wA3VdXOfiuX/FzWGswYvr8/mu7E/0AzM/hr2rLfoHnjQPMF4S+A7cDfA9877JhXub6/A9xAMzv6lcAPDjvmZdT1nTTd8/6FJtN6FvAy4GXt+gB/1D4X19Ohq9Aso86/2PP6XgX88LBjXkZdf4SmS+V1wLXt34nj+hoPWN+xeX3H8W/c25sB6vcR4I6e9+8lw455pes4Z9uZrn3mDPAaBngj8Ln2M/XUYce8wvV7EvA37WfotcBzhx3zIus3cd97JvFv1NuSrnxfobki1Gfavxt6nsuR+p8BHkmT9HlMT9nQn8t5Pm8eC1wB3NzeHtpuuxF4a8++P9e+P7cDZ65xjNtp5vGZfW/OXgnwu4AP7e+9scZx/nn7nruOJvGzfm6c7fI+nwdrFWNbfv7se7Fn22U/l2l3liRJkiRJ0gQb9nAzSZIkSZIkjQCTRJIkSZIkSTJJJEmSJEmSJJNEkiRJkiRJwiSRJEmSJEmSMEkkSZIkSZIkTBJJkiRJkiQJk0SSJEmSJEnCJJEkSZIkSZIwSSRJkiRJkiRMEkmSJEmSJAmTRJIkSZIkScIkkSRJkiRJkjBJJEmSJEmSJEwSSZIkSZIkCZNEkiRJkiRJwiSRJEmSJEmSMEkkSZIkSZIkTBJJkiRJkiQJk0SSJEmSJEnCJJEkSZIkSZIwSSRJkiRJkiRMEkmSJEmSJAmTRJIkSZIkScIkkSRJkiRJkjBJJEmSJEmSJEwSSZIkSZIkCZNEkiRJkiRJwiSRJEmSJEmSMEkkSZIkSZIkTBJJkiRJkiQJk0SSJEmSJEnCJJEkSZIkSZIwSSRJkiRJkiRMEkmSJEmSJAmTRJIkSZIkScIkkUZUkpkkP7+I7TckqSTrVjMuSVK3JDkjycfnWXdakstW6HEqyfcv53GSvC7J/1mJeCRJkpbCJJGGKsmOJN9OsjvJHUn+LMmj+my3PsmfJrm93faWJOcn+cElPOajk/x+klvbY21vlw9bmVpJktZakh9J8rdJ7klyV5K/SfLv9rdPVV1YVc8d4NivbtuL3Un+Kcn9Pcs3LLT/oI8jSVqans/k3Un+tef3xe4kp63QY7wsyUf6lH85yY+sxGP0OfZjk7y9/Z30jSQ3JfmVZRzvoiT/fSVj1PgxSaRR8ONV9SjgGODfAXt9cCV5LPC3wCOBfw8c1G77MeA/LuaBkjwcuAJ4MnAC8Gjgh4GvAccuqxaSpKFI8mjgg8C5wKHA4cDrgftW4vhV9dtV9ai2rXoZ8Hezy1X15JV4DEnS0vV8Jj8KuJX290X7d+Gw41uKdoTEHwIBngAcDPwnYMcSj/fQFQtOY80kkUZGVX0J+DDwlDmrfgX4BvCSqvpCNe6uqj+rqnP7HSvJoW2vpNuTfD3JB9pVLwW+G/iJqvpcVf1rVd1ZVf+zqj7U7vvEdrjb3UluSHJyz3HPT/JHSS5Ncm+Sq5N8X8/6Jye5vD2LfUeSV6/cMyRJmscTAKrqnVV1f1V9u6ouq6rr5m6Y5HeTfDzJY+YORWuHjL0syc1t2/FHSbKIOJ7Tb98+j7NgW5HkYUnemeS97QkOSdISJDmo7QX66Hb5N5Pcl+SAdvn3kmxt7x+a5B1JvpLki0l+bTHtQJKHJnl9O2LhjiRvS3JQu+6EJNvnbP9AL6QkW9vHfleSe4FTaU6gX1hV97S/Wz5XVe/v2f8pST7atjs3JnlBz7qLkrw5yWVJvgn80JzH/sEke5KcmWRnW+f/1rP+mUk+3fZg+nKS3xn0eVC3mSTSyEhyJHAi8Ok5q54DvL+q/nURh/tzmp5HTwYeB7yp51h/VVW754nhYcBfApe1+/0ScGGSH+jZ7MU0Z6gPAbYDv9XuexDwEeCvgO8Cvp+m15IkaXX9A3B/kguSPC/JIXM3SPKQJH8K/FvguVV1zzzHej7Nl/KnAj8F/Ngi4lhw30HaivaHywdoekL9VFX98yJikCT1qKp7getoRiQAPAvYCRzXs/yx9v6fAA8DHk8zYuEXgJ9ZxMP9F5rP/38PHEXze+KNi9j/J4ELgMcA7wWuAt6Q5PTMmfeuTXpdDpwHHEZzMvxtc7b7WeD/pRmJ8Yk+j/dQYCNNW3Qi8FtJvrdd94fAb1fVo9u6fKDP/hpDJok0Cj6Q5G7g4zQf0L89Z/1hwJdnF5Kc3PbyuTd9JgJNsh54HvCyqvp6Vf1LVc1+8D8W2LWfWI4DHgVsrap/rqqP0gxheHHPNu+rqr+vqj3AhcDT2vLnA1+uqnOq6p+q6t6qunrA50CStERV9Q3gR4AC/hT4SpJLkky1mzwMeCfNULQfr6pv7edwW9veqrcCV/LgZ/wgBtl3obbi0TQJpC8AZ1bV/Yt4fElSfx8DfjTJI2gSHm9plw+iOXnwN+26nwTOrqrdVbUd+H3gJT3H+dH2d8gDfzSJoFmnAb9bVf/Ytk2vAU5bRG+kj1XVh9peQ9+mSTq9l2ZkxU1JPp/kOe22PwF8tp337v6q+gTNye6f7Dnee6rq6vZ48w3Bfm3bHn0CuKl9PgD+BXhCksf6u2aymCTSKHhBVR1cVd9TVf+1/UDs9TVg/exCVV1SVQfTfFj264J/JHBXVX29z7q9jtXHdwG3zem19I8081vM+nLP/W/RJJVmH/cL+zm2JGmVVNWNVXVGVR1BM2z5u2i+3ENzhvQU4PUD9MqZ7zN+EIPsu1BbcRzNF/StVVWLeGxJ0vw+BkwDzwA+CXwU+FHgmcD1bULn39D8Pr61Z7+5vwM+1v5ueeAPuLNn/Xe1+/TufwDNSYpB3Na7UFXfrKrfqKqn0Zzs/kvgvW1y63uAZ81JWP0ke//W2et4fdxfVV/tWe5tu06naY/+oZ1iYzE9a9VhJonUBVcAL0gy6Pv1NuDQJAf3WfcR4MeSHDjPvrcDR855rO8GvjTg437fgltJklZVVd0EnM+Dc9zdCJwJfHjO8OFhWKituAz4HeCKnp5QkqTl+f9ohgKfRJMwuhb4QeC5PDjU7MvAv9J895816O+AWbfTJG969/82cBfwTZrpMIAHprmYmzya9+RAO0x6K02P0++maU8um5O0elRVvXKQ4y2kPfny0zQ9pd4MvM858iaDSSJ1wRtp5v/58yTfl8ZBzDMEoKp20UyA/cdJDmkn/3xWu/rPaT5Q39tO1vaQNJeWfHWSE4GraT7Af63dbxr4ceCiAeL8IPBvkrwyySPaSfKesZyKS5IW1n6eb05yRLt8JM0w4atmt6mqdwKvBj6SngsODMGCbUVV/S/gHTSJosOGEqUkjZE2wXIDzRxDH2tHDXwS+HnaJFE7HOv9wG8nObBtK14B/J9FPNQ7gV9N8t3t75XfBN7R9gy9keZE9vFtguj1LPB7PMnrkhzT/i45APhl4Ks086J+AHh6kp9u1z88yXFJnrCIePf32C9th5rdD9xDk3BazByx6iiTRBp5bRfI44B/opm36F6a7P9BNB/0/byEZhztTTRdQF/ZHus+msmrb6KZ6O0bwN/TzHt0dTsM4WSaOY2+Cvwx8NL2rPRCcd5LM8Hdj9OcibgZ+A+LrrAkabHupRlCcHV7BZergM8Cm3s3qqoLgN8APppkwxrHOBvDQG1FVf1Pmh8AH0ky6DAFSdL8PkZzOflP9SwfSPP7YtZ/aW//kWZI2ltp5iAd1FuA9wF/SzO0+C7gVfDAb5pXtMfbSdMGfLX/YR7wEJok1V3tPs8ETqyq+9qpNX6MpqfsLppeTL9JMw/fSng+8Pn2Smu/Q3MhhT0rdGyNsDjcXZIkSZIkSfYkkiRJkiRJkkkiSZIkSZIkmSSSJEmSJEkSsG45OyfZQTNZ5P3Anqra2E6u+C5gA7CDZoKrry8vTEmSJEmSJK2mZU1c3SaJNrYztc+W/S/grqrammQLcEhVnb2/4xx22GG1YcOGRT/+N7/5TQ488MBF77daRimeUYoFRiseY5nfKMUzSrHA4uO55pprvlpV37mKIWmOcWlLVoN1HA/WcTwspo62JWvPtmT5fC4e5HPR8Hl40DCei8W2JcvqSTSPU4Dp9v4FwAyw3yTRhg0b+OQnP7noB5qZmWF6enrB7dbKKMUzSrHAaMVjLPMbpXhGKRZYfDxJ/nH1olE/49KWrAbrOB6s43hYTB1tS9aebcny+Vw8yOei4fPwoGE8F4ttS5abJCrgsiQF/O+q2gZMVdUugKraleRx8wS6CdgEMDU1xczMzKIffPfu3Uvab7WMUjyjFAuMVjzGMr9RimeUYoHRi0eSJEmSVtpyk0TPrKrb20TQ5UluGnTHNqG0DWDjxo21lGzaqGUkRymeUYoFRiseY5nfKMUzSrHA6MUjSZIkSSttWVc3q6rb29s7gfcDxwJ3JFkP0N7eudwgJUmSJEmStLqWnCRKcmCSg2bvA88FPgtcApzebnY6cPFyg5QkSZIkSdLqWs5wsyng/Ulmj/OOqvqrJJ8A3p3kLOBW4EXLD1OSJEmSJEmraclJoqq6BXhqn/KvAccvJyhJkiRJkiStrWXNSSRJkiRJkqTxYJJIkiRJkiRJJokkSZIkSZK0vImrpc7ZsOVSNh+9hzO2XLpX+Y6tJw0pIknDdv2X7tnnMwH8XJAkDc62RNK4sCeRJEmSJEmSTBJJkiRJkiTJJJEkSZIkSZIwSSRJkiRJkiRMEkmSJEmSJAmTRJIkSZIkScIkkSRJkiRJkjBJJEmSJEmSJEwSSZIkSZIkCZNEkiRJkiRJwiSRJEmSJEmSMEkkSZIkqQOSfEeSv0/ymSQ3JHl9W35+ki8mubb9e1pbniRvTrI9yXVJjhluDSRp9K0bdgCSJEmSNID7gGdX1e4kDwM+nuTD7br/VlXvmbP984Cj2r9nAG9pbyVJ8zBJJM1jw5ZL+5bv2HrSGkciSZKkqipgd7v4sPav9rPLKcDb2/2uSnJwkvVVtWuVQ5WkznK4mSRJkqROSPLQJNcCdwKXV9XV7arfaoeUvSnJI9qyw4Hbenbf2ZZJkuZhTyJJkiRJnVBV9wNPS3Iw8P4kTwF+Hfgy8HBgG3A28BtA+h1ibkGSTcAmgKmpKWZmZhYd19QBsPnoPfuUL+VYXbd79+6JrHc/PhcNn4cHdeG5MEkkSZIkqVOq6u4kM8AJVfV7bfF9Sf4M+NV2eSdwZM9uRwC39znWNprkEhs3bqzp6en/v737D5arPA87/n0MBCvYCSY2dxRJrXCsuCZWDeQOVUuTuQE74YdrkdYkMBoQjlolUzzBjWZi2fnDaRPPyNPIJCYOiWwoIqOAKTaVxtDEVGbLeKYQG0wQWHaR8S1cpEqJDTK3bu1c/PSPfa/vcu+urL13f5yz9/uZ2dk9757d85z3nN1373Pf9z1dx3Pznr3sPLDwT6vJTd2/V901Gg0WU4ejyLposh7m1KEuTBJJdJ5/SJIkSdUQEW8A/r4kiFYAbwc+MjvPUEQEcCXwZHnJPuC9EXEXzQmrjzsfkSSdmEkiSZIkSXWwEtgdEafQnFv17sz8bER8viSQAngc+I2y/v3A5cAh4DvAe4YQsyTVikkiSZIkSZWXmU8A57cpv7jD+gnc0O+4JGmUeHUzSZIkSZIkmSSSJEmSJEmSSSJJ0gBExJqIeDAiDkbEUxFxYyk/KyIeiIiny/3rSnlExMci4lBEPBERFwx3DyRJkqTRZ5JIkjQIM8C2zHwLsAG4ISLOBbYD+zNzHbC/LANcBqwrt63ALYMPWZIkSVpeTBJJkvouM49k5mPl8UvAQWAVsBHYXVbbTfPSxZTyO7LpYeDMiFg54LAlSZKkZcWrm0mSBioi1tK8Os0jwFhmHoFmIikizi6rrQKea3nZVCk7Mu+9ttLsacTY2BiNRqPreMZWwLb1MwvKF/NeVTU9PT1S+9OO+zga3EdJkobLJJEkaWAi4jXAp4H3Zea3I6Ljqm3KckFB5i5gF8D4+HhOTEx0HdPNe/ay88DC5nByU/fvVVWNRoPF1E2duI+jwX2UJGm4HG4mSRqIiDiNZoJoT2Z+phQfnR1GVu6PlfIpYE3Ly1cDhwcVqyRJkrQcmSSSJPVdNLsM3QoczMyPtjy1D9hcHm8G9raUX1eucrYBOD47LE2SJElSfzjcTJI0CBcB1wIHIuLxUvZBYAdwd0RsAZ4FrirP3Q9cDhwCvgO8Z7DhSpIkScuPSSJJUt9l5hdoP88QwCVt1k/ghr4GJUmSJOkVHG4mSZIkSZKkpSeJIuKUiPhyRHy2LJ8TEY9ExNMR8amI+JGlhylJkiRJkqR+6kVPohuBgy3LHwFuysx1wAvAlh5sQ5IkSZIkSX20pCRRRKwGrgA+WZYDuBi4p6yyG7hyKduQJEmSJElS/y114uo/BH4beG1Z/gngxcycKctTwKp2L4yIrcBWgLGxMRqNRtcbn56eXtTr+qVK8VQpFqhOPNvWzzC2onm/WL3cj6rUy6wqxVOlWKB68UiSJElSry06SRQR7wSOZeajETExW9xm1Wz3+szcBewCGB8fz4mJiXarnVCj0WAxr+uXKsVTpVigOvFcv/0+tq2fYeeBxedHJzdN9CyeqtTLrCrFU6VYoHrxSJIkSVKvLaUn0UXAuyLicuDVwI/R7Fl0ZkScWnoTrQYOLz1MSZIkSZIk9dOi5yTKzA9k5urMXAtcDXw+MzcBDwLvLqttBvYuOUpJkiRJkiT1VS+ubjbf+4HfiohDNOcourUP25AkSZIkSVIPLXXiagAyswE0yuNngAt78b5SFa3dfl/b8skdV3T9HtvWz3B9y/t18x6SJEnLSUS8GngIOJ3m3zH3ZOaHIuIc4C7gLOAx4NrM/F5EnA7cAfws8E3gVzNzcijBS1JN9KMnkSRJkiT12neBizPzbcB5wKURsQH4CHBTZq4DXgC2lPW3AC9k5puAm8p6kqQTMEkkSZIkqfKyabosnlZuCVwM3FPKdwNXlscbyzLl+Usiot3VmCVJRU+Gm0mSJElSv0XEKcCjwJuAjwNfB14sV1YGmAJWlcergOcAMnMmIo7TnDP17+a951ZgK8DY2BiNRqPruMZWNKcRmG8x71V309PTy3K/27EumqyHOXWoC5NEUh91mr9IkiRJ3cvMl4HzIuJM4F7gLe1WK/fteg3lgoLMXcAugPHx8ZyYmOg6rpv37GXngYV/Wk1u6v696q7RaLCYOhxF1kWT9TCnDnXhcDNJkiRJtZKZL9K8cM4G4MyImM3QrAYOl8dTwBqA8vyPA98abKSSVC8miSRJkiRVXkS8ofQgIiJWAG8HDgIPAu8uq20G9pbH+8oy5fnPZ+aCnkSSpDkON5MkSZJUByuB3WVeolcBd2fmZyPiK8BdEfH7wJeBW8v6twJ/HhGHaPYgunoYQUtSnZgkkiRJklR5mfkEcH6b8meAC9uU/z/gqgGEJkkjwySRRlYdJ41uF/PkjiuGEIkkSZIkablxTiJJkiRJkiSZJJIkSZIkSZJJIkmSJEmSJOGcRBoBdZx7SJIkSZKkqrEnkSRJkiRJkkwSSZIkSZIkySSRJEmSJEmSMEkkSZIkSZIknLhaNVL1CaqrHp8kSZIkSSdiTyJJkiRJkiSZJJIkSZIkSZJJIkmSJEmSJGGSSJIkSZIkSZgkkiRJkiRJEiaJJEmSJEmShEkiSZIkSZIkYZJIkiRJkiRJmCSSJEmSJEkSJokkSZIkSZKESSJJ0gBExG0RcSwinmwp+92IeD4iHi+3y1ue+0BEHIqIr0XELw0naklSlUTEmoh4MCIORsRTEXFjKbc9kaQeOXXYAUiSloXbgT8G7phXflNm/kFrQUScC1wN/Azwk8B/i4ifzsyXBxGoJKmyZoBtmflYRLwWeDQiHijP2Z5IUg/Yk0iS1HeZ+RDwrZNcfSNwV2Z+NzO/ARwCLuxbcJKkWsjMI5n5WHn8EnAQWHWCl9ieSFKX7EkkSRqm90bEdcCXaP53+AWaP/gfbllnig5/BETEVmArwNjYGI1Go+sAxlbAtvUzC8oX815VNT09PVL70477OBrcR52siFgLnA88AlzEEtoT25Le8hyfY100WQ9z6lAXJokkScNyC/B7QJb7ncCvAdFm3Wz3Bpm5C9gFMD4+nhMTE10HcfOevew8sLA5nNzU/XtVVaPRYDF1Uyfu42hwH3UyIuI1wKeB92XmtyNiSe2JbUlveY7PsS6arIc5dagLh5tJkoYiM49m5suZ+X3gE8wNAZgC1rSsuho4POj4JEnVExGn0UwQ7cnMz4DtiST1kkkiSdJQRMTKlsVfBmavfLYPuDoiTo+Ic4B1wF8POj5JUrVERAC3Agcz86Mt5bYnktQjDjeTJPVdRNwJTACvj4gp4EPAREScR7Pr/yTw6wCZ+VRE3A18heaVbG7wSjSSJJpzD10LHIiIx0vZB4FrbE8kqTcWnSSKiFcDDwGnl/e5JzM/VLL0dwFnAY8B12bm93oRrCSpnjLzmjbFt55g/Q8DH+5fRJKkusnML9B+nqH7T/Aa2xNJ6sJShpt9F7g4M98GnAdcGhEbgI8AN2XmOuAFYMvSw5QkSZIkSVI/LTpJlE3TZfG0ckvgYuCeUr4buHJJEUqSJEmSJKnvljQnUUScAjwKvAn4OPB14MXMnCmrTAGrOrx2K7AVYGxsjEaj0fX2p6enF/W6fqlSPFWKBXoTz7b1Mz98pZMwtqJ377VUJxPLII9jlc6bKsUC1YtHkiRJknptSUmiMvHbeRFxJnAv8JZ2q3V47S5gF8D4+HhOTEx0vf1Go8FiXtcvVYqnSrFAb+K5fvt9PYll2/oZdh6oxpztJxPL5KaJwQRDtc6bKsUC1YtHkiRJknptKXMS/UBmvgg0gA3AmREx+1fvauBwL7YhSZIkSZKk/ll0kigi3lB6EBERK4C3AweBB4F3l9U2A3uXGqQkSZIkSZL6ayljblYCu8u8RK8C7s7Mz0bEV4C7IuL3gS9zgkscS1q8tR2G303uuGLAkUiSJEmSRsGik0SZ+QRwfpvyZ4ALlxKUJEmSJEmSBqsncxJJkiRJkiSp3kwSSZIkSZIkySSRJEmSJEmSljZxtaSacJJrSZIkSdIPY08iSZIkSZIkmSSSJEmSJEmSSSJJkiRJkiThnESqqE5z6EiSJEmSpP6wJ5EkSZIkSZJMEkmSJEmSJMkkkSRJkiRJkjBJJEmSJKkGImJNRDwYEQcj4qmIuLGUnxURD0TE0+X+daU8IuJjEXEoIp6IiAuGuweSVH0miSRJkiTVwQywLTPfAmwAboiIc4HtwP7MXAfsL8sAlwHrym0rcMvgQ5akejFJJEmSJKnyMvNIZj5WHr8EHARWARuB3WW13cCV5fFG4I5sehg4MyJWDjhsSaqVU4cdgCRJkiR1IyLWAucDjwBjmXkEmomkiDi7rLYKeK7lZVOl7Mi899pKs6cRY2NjNBqNruMZWwHb1s8sKF/Me9Xd9PT0stzvdqyLJuthTh3qwiSRJEmSpNqIiNcAnwbel5nfjoiOq7YpywUFmbuAXQDj4+M5MTHRdUw379nLzgML/7Sa3NT9e9Vdo9FgMXU4iqyLJuthTh3qwuFmkiRJkmohIk6jmSDak5mfKcVHZ4eRlftjpXwKWNPy8tXA4UHFKkl1ZJJIkiRJUuVFs8vQrcDBzPxoy1P7gM3l8WZgb0v5deUqZxuA47PD0iRJ7TncTJIkSVIdXARcCxyIiMdL2QeBHcDdEbEFeBa4qjx3P3A5cAj4DvCewYYrSfVjkkiSJElS5WXmF2g/zxDAJW3WT+CGvgYlSSPG4WaSJEmSJEkySSRJkiRJkiSTRJIkSZIkScIkkSRJkiRJkjBJJEmSJEmSJEwSSZIkSZIkCZNEkiRJkiRJwiSRJEmSJEmSMEkkSZIkSZIkTBJJkiRJkiQJk0SSJEmSJEnCJJEkaQAi4raIOBYRT7aUnRURD0TE0+X+daU8IuJjEXEoIp6IiAuGF7kkSZK0fJgkkiQNwu3ApfPKtgP7M3MdsL8sA1wGrCu3rcAtA4pRkiRJWtZMEkmS+i4zHwK+Na94I7C7PN4NXNlSfkc2PQycGRErBxOpJEmStHydOuwAtLyt3X7fsEMYOdapamQsM48AZOaRiDi7lK8CnmtZb6qUHZn/BhGxlWZvI8bGxmg0Gt0HsQK2rZ9ZUL6Y96qq6enpkdqfdtzH0eA+SpI0XCaJJElVE23Kst2KmbkL2AUwPj6eExMTXW/s5j172XlgYXM4uan796qqRqPBYuqmTtzH0eA+SpI0XIsebhYRayLiwYg4GBFPRcSNpbztRKSSJM1zdHYYWbk/VsqngDUt660GDg84NkmSJGnZWcqcRDPAtsx8C7ABuCEizqXzRKSSJLXaB2wujzcDe1vKrytXOdsAHJ8dliZJkiSpfxadJMrMI5n5WHn8EnCQ5pwRnSYilSQtUxFxJ/A/gDdHxFREbAF2AO+IiKeBd5RlgPuBZ4BDwCeAfzuEkCVJkqRlpydzEkXEWuB84BE6T0Q6/zVLnmy0ahP/VSmeKsUCneNpN1lsv3WapHYYTiaWm/fsbVu+bf3Stz//mFTpvKlSLFC9eOomM6/p8NQlbdZN4Ib+RiRJkiRpviUniSLiNcCngfdl5rcj2s03ulAvJhut2sR/VYqnSrFA53iuH8KVuLatn2k7Se0wDDuW+RPzVum8qVIsUL14JElabiLiNuCdwLHMfGsp+13g3wB/W1b7YGbeX577ALAFeBn4zcz8q4EHLUk1s5Q5iYiI02gmiPZk5mdKcaeJSCVJkiRpsW4HLm1TflNmnlduswmic4GrgZ8pr/mTiDhlYJFKUk0t5eoUxhPRAAATPklEQVRmAdwKHMzMj7Y81WkiUkmSJElalMx8CPjWSa6+EbgrM7+bmd+gOc/dhX0LTpJGxFLGuVwEXAsciIjHS9kHaU48eneZlPRZ4KqlhShJkiRJHb03Iq4DvkTz6ssv0LygzsMt60yVsgV6MVdqp3kml+N8hs7jOMe6aLIe5tShLhadJMrMLwCdJiBaMBGpJEmSJPXYLcDvAVnudwK/Rvu/U7LdG/RirtSb9+xtO8/k/PkflwPncZxjXTRZD3PqUBdLmpNIkiRJkoYlM49m5suZ+X3gE8wNKZsC1rSsuho4POj4JKluTBJJkiRJqqXZC+YUvww8WR7vA66OiNMj4hxgHfDXg45PkuqmGtcBlyRJkqQTiIg7gQng9RExBXwImIiI82gOJZsEfh0gM5+KiLuBrwAzwA2Z+fIw4pakOjFJJEmSJKnyMvOaNsW3nmD9DwMf7l9EkjR6HG4mSZIkSZIkk0SSJEmSJEkySSRJkiRJkiSck0jSPGu339e2fHLHFQOORJIkSZI0SPYkkiRJkiRJkkkiSZIkSZIkmSSSJEmSJEkSJokkSZIkSZKESSJJkiRJkiRhkkiSJEmSJEmYJJIkSZIkSRImiSRJkiRJkgScOuwAJNXD2u33tS2f3HHFgCORJEmSJPWDPYkkSZIkSZJkkkiSJEmSJEkmiSRJkiRJkoRJIkmSJEmSJOHE1dKyNn8y6m3rZ6j614ITaEuSJElSf9iTSJIkSZIkSSaJJEmSJFVfRNwWEcci4smWsrMi4oGIeLrcv66UR0R8LCIORcQTEXHB8CKXpPowSSRJkiSpDm4HLp1Xth3Yn5nrgP1lGeAyYF25bQVuGVCMklRr1Z58RFLldZojqB3nDZIkSYuVmQ9FxNp5xRuBifJ4N9AA3l/K78jMBB6OiDMjYmVmHhlMtJJUT/YkkiRJklRXY7OJn3J/dilfBTzXst5UKZMknYA9iSRJkiSNmmhTlm1XjNhKc0gaY2NjNBqNrjc2tmL2KrGvtJj3qrvp6ellud/tWBdN1sOcOtSFSSJJkiRJdXV0dhhZRKwEjpXyKWBNy3qrgcPt3iAzdwG7AMbHx3NiYqLrIG7es5edBxb+aTW5qfv3qrtGo8Fi6nAUWRdN1sOcOtSFw80kSZIk1dU+YHN5vBnY21J+XbnK2QbguPMRSdIPZ08iSZIkSZUXEXfSnKT69RExBXwI2AHcHRFbgGeBq8rq9wOXA4eA7wDvGXjAklRDJokkSZIkVV5mXtPhqUvarJvADf2NSJJGj8PNJEmSJEmSZE8iSdJwRcQk8BLwMjCTmeMRcRbwKWAtMAn8Sma+MKwYJUmSpOXAJJEG4sDzx7l++33DDkMVtbbNuXH7pWcMIRIN0S9k5t+1LG8H9mfmjojYXpbfP5zQJEmSpOXBJJEkqYo20pycFGA30MAkUa21SwYDTO64YsCRSJIkqZMlJYki4jbgncCxzHxrKXOIgCSpGwl8LiIS+LPM3AWMzV6qODOPRMTZ7V4YEVuBrQBjY2M0Go2uNz62Aratn1lQvpj3qqrp6emh70+7Oobe1XMV9rHf3MfRsBz2UZJUX0vtSXQ78MfAHS1lDhGQJHXjosw8XBJBD0TEV0/2hSWhtAtgfHw8JyYmut74zXv2svPAwuZwclP371VVjUaDxdRNL3Uactyreq7CPvab+zgalsM+SpLqa0lXN8vMh4BvzSveSHNoAOX+yqVsQ5I02jLzcLk/BtwLXAgcjYiVAOX+2PAilCRJkpaHfsxJNLAhAlXrrluleIYZy4Hnjy8o6zScYxiMpbN+x3Pznr1ty7etX1jW6Rzu95CVTqr0+R4lEXEG8KrMfKk8/kXgPwD7gM3AjnLf/uSRJEmS1DNDm7i6F0MEqtZdt0rxDDOWdkMKtq2faTucYxiMpbMqxXP7pWe0PYf7PWSlkyp9vkfMGHBvRECzTfqLzPzLiPgicHdEbAGeBa4aYozqUqdJqiVJklRt/fhr8GhErCy9iBwiIEnqKDOfAd7WpvybwCWDj0iSJElavpY0J1EHs0MEwCECkiRJkiRJtbCknkQRcScwAbw+IqaAD9GcP8IhApKW5MDzxzsOLeuHTsNjJndcMbAYJEmSJGmYlpQkysxrOjzlEAFJkiRJkqQa6cdwM0mSJEmSJNWMSSJJkiRJkiT15epmkiRpxLSbt8s5uyRJkkaLSSJJI6HTxNPt+IetRlWnz8Htl55x0uv6+ZAkSVq+TBJJkqRF6SY5K0mSpOpzTiJJkiRJkiSZJJIkSZIkSZLDzbQEDjNQXXnuSpI0WiJiEngJeBmYyczxiDgL+BSwFpgEfiUzXxhWjJJUB/YkkiRJkjQKfiEzz8vM8bK8HdifmeuA/WVZknQC9iSSJEm1tnb7fWxbP8P183oJeqU2adnbCEyUx7uBBvD+YQUjSXVgkkiSJFVOu2GhJn0knUACn4uIBP4sM3cBY5l5BCAzj0TE2e1eGBFbga0AY2NjNBqNrjc+tgK2rZ9ZUL6Y96q76enpZbnf7VgXTdbDnDrUhUkiSZIkSXV3UWYeLomgByLiqyf7wpJQ2gUwPj6eExMTXW/85j172Xlg4Z9Wk5u6f6+6azQaLKYOR5F10WQ9zKlDXZgkkiRJP+DE7pLqKDMPl/tjEXEvcCFwNCJWll5EK4FjQw1SkmrAiaslSZIk1VZEnBERr519DPwi8CSwD9hcVtsM7B1OhJJUH/YkkiRJklRnY8C9EQHNv2/+IjP/MiK+CNwdEVuAZ4GrhhijJNWCSSJJklQLDoWT1E5mPgO8rU35N4FLBh+RJNVXrZNEB54/vuByt+DVTyRJkiRJkrpV6ySRJEn64Tr9U6UK7B0kSU2dvg/b/QO8m3U7re8/1iW148TVkiRJkiRJsieRJEmSJFWVPS4lDZJJIkmSKsw/DiRJJ8s2Q9JSOdxMkiRJkiRJ9iSSJKkK/O+vJC0ffudLqiqTRJIkaSR5NR9JkqTumCSSJEmSJAGdezmZZJeWB5NEy5Rf/pIkSZJOlr0zpeXBJJEkSZIkLTPOiySpHZNEkiRp2bOHrSRJkkkiSZIGyv/cDpf1L0mS1JlJIkmSJElS19ol3retn2Fi8KFI6hGTRHoF/8MqSZIkSdLyZJJIkiRJktQzzvMm1ZdJIkmSpA685LMkSVpOTBJJkiRJkvpuqYl3eyhJ/WeSqIb8cpQkSZKqz/k+JdWNSSJJkqQu+M8aSeqdQX+n+h0unVjfkkQRcSnwR8ApwCczc0e/tiVJGk22JZKkpbItqaduemEt18TPct1v9VdfkkQRcQrwceAdwBTwxYjYl5lf6cf2JEmjp05ticMJBN2dB/6AlwajTm2Jes/2Wepev3oSXQgcysxnACLiLmAj4JexJOlk2ZZoZHXz39/Zdbetn+H6k/iDxwTU8Phf/UqyLdFJ6UdC6UTf252+F3oRR7+SY4uNubUe+vl92IsrklbhqqbDbksiM3v/phHvBi7NzH9dlq8F/klmvrdlna3A1rL4ZuBri9jU64G/W2K4vVSleKoUC1QrHmPprErxVCkW6D6ef5iZb+hXMMvBMm5L+sF9HA3u42joZh9tS5bItmQorIs51kWT9TBnGHXRVVvSr55E0absFdmozNwF7FrSRiK+lJnjS3mPXqpSPFWKBaoVj7F0VqV4qhQLVC+eZWJZtiX94D6OBvdxNCyHfawY25IBsy7mWBdN1sOcOtTFq/r0vlPAmpbl1cDhPm1LkjSabEskSUtlWyJJXehXkuiLwLqIOCcifgS4GtjXp21JkkaTbYkkaalsSySpC30ZbpaZMxHxXuCvaF5q8rbMfKoPm1pSt9A+qFI8VYoFqhWPsXRWpXiqFAtUL56Rt4zbkn5wH0eD+zgalsM+VoZtyVBYF3OsiybrYU7l66IvE1dLkiRJkiSpXvo13EySJEmSJEk1YpJIkiRJkiRJ9U0SRcSlEfG1iDgUEdsHvO01EfFgRByMiKci4sZS/rsR8XxEPF5ulw8wpsmIOFC2+6VSdlZEPBART5f71w0gjje37P/jEfHtiHjfIOsmIm6LiGMR8WRLWdu6iKaPlfPoiYi4YACx/MeI+GrZ3r0RcWYpXxsR/7eljv50ALF0PC4R8YFSL1+LiF/qZSwniOdTLbFMRsTjpbzfddPpMz2U80aDM8y2pF+6PZ/rKiJOiYgvR8Rny/I5EfFI2b9PRXOC2lqLiDMj4p7SZhyMiH86SscxIv5dOUefjIg7I+LVo3Acq/Q7RIMxim1JJ/5mWuhk26OIOL0sHyrPrx1m3L3UTXs16udEN21bVc+JWiaJIuIU4OPAZcC5wDURce4AQ5gBtmXmW4ANwA0t278pM88rt/sHGBPAL5Ttjpfl7cD+zFwH7C/LfZWZX5vdf+Bnge8A95anB1U3twOXzivrVBeXAevKbStwywBieQB4a2b+Y+B/Ah9oee7rLXX0GwOIBdocl3I+Xw38THnNn5TPXV/jycxfbTl/Pg18puXpftZNp8/0sM4bDUAF2pJ+6fZ8rqsbgYMtyx+h+X22DngB2DKUqHrrj4C/zMx/BLyN5v6OxHGMiFXAbwLjmflWmhMKX81oHMfbqc7vEPXZCLclnfibaaGTbY+2AC9k5puAm8p6o6Kb9mpkz4lFtG2VPCdqmSQCLgQOZeYzmfk94C5g46A2nplHMvOx8vglmh+CVYPafhc2ArvL493AlQPe/iU0/7D/X4PcaGY+BHxrXnGnutgI3JFNDwNnRsTKfsaSmZ/LzJmy+DCwulfb6zaWE9gI3JWZ383MbwCHaH7uBhJPRATwK8CdvdzmCWLp9JkeynmjgRlqW9IvizifayciVgNXAJ8sywFcDNxTVqn1/gFExI8BPw/cCpCZ38vMFxmh40jzKrsrIuJU4EeBI4zAcazS7xANxEi2JZ34m+mVumyPWuvoHuCSsn6tLaK9Gulzgu7atkqeE3VNEq0CnmtZnmJISZrSJex84JFS9N7Sbe62GGwX8AQ+FxGPRsTWUjaWmUeg+YUOnD3AeKCZNW39I39YdQOd62LY59KvAf+1Zfmc0l31v0fEzw0ohnbHZdj18nPA0cx8uqVsIHUz7zNd1fNGvTHyx/Ekz+c6+kPgt4Hvl+WfAF5sScCPwrF8I/C3wH8q332fjIgzGJHjmJnPA38APEvzB/Rx4FFG7zjOsj0ZXcv2GPqbCeiuPfpBXZTnj5f1667b9mpkz4lFtG2VPCfqmiRql13LgQcR8RqaQ2Lel5nfptlV7qeA82ieFDsHGM5FmXkBze57N0TEzw9w2wuUcZbvAv5zKRpm3ZzI0M6liPgdml1295SiI8A/yMzzgd8C/qJk5vup03EZ9mfsGl6ZYBxI3bT5THdctU3ZwL+DtGQjfRy7OJ9rJSLeCRzLzEdbi9usWvdjeSpwAXBL+e77P9R0aFk75Z8SG4FzgJ8EzqD5G2a+uh/HH2YUz93lZlkeQ38zLao9GtW66La9GtV6WEzbVsm6qGuSaApY07K8Gjg8yAAi4jSaX4x7MvMzAJl5NDNfzszvA5+gx8NzTiQzD5f7YzTnALoQODrbda/cHxtUPDQ/DI9l5tES19DqpuhUF0M5lyJiM/BOYFNmJkAZ2vXN8vhR4OvAT/czjhMcl6F9xkrXzH8JfKolzr7XTbvPNBU7b9RzI3scuzyf6+Yi4F0RMUlzWMfFNP+Te2b5/oDROJZTwFRmzvZUvofmj/BROY5vB76RmX+bmX9Pcw66f8boHcdZtieja9kdQ38z/UC37dEP6qI8/+Oc/FQQVdZtezXK50S3bVslz4m6Jom+CKwrs4T/CM1hTfsGtfEyTvBW4GBmfrSlvHUs5S8DT85/bZ/iOSMiXjv7GPjFsu19wOay2mZg7yDiKV7RE2RYddOiU13sA66Lpg3A8dlukf0SEZcC7wfelZnfaSl/w+zk0BHxRpqTuT3T51g6HZd9wNXRnHH/nBLLX/czlhZvB76amVMtcfa1bjp9pqnQeaO+GGpb0i+LOJ9rJTM/kJmrM3MtzWP2+czcBDwIvLusVtv9m5WZ/xt4LiLeXIouAb7CiBxHml3xN0TEj5Zzdnb/Ruo4trA9GV0j2ZZ04m+mOYtoj1rr6N1l/aH3GlmqRbRXI3tO0H3bVs1zIjNreQMup3llqK8DvzPgbf9zmt3AngAeL7fLgT8HDpTyfcDKAcXzRuBvyu2p2fqgOZ5xP/B0uT9rQPH8KPBN4MdbygZWNzSTU0eAv6eZnd3SqS5odvH7eDmPDtCcib7fsRyiOfZ09tz507LuvyrH72+Ax4B/MYBYOh4X4HdKvXwNuGwQx6mU3w78xrx1+103nT7TQzlvvA3uNsy2pI/71NX5XOcbMAF8tjx+I81k9iGaQ51PH3Z8Pdi/84AvlWP5X4DXjdJxBP498FWa/6D4c+D0UTiOHdpb25MRvo1iW3KCffU3U/t6+aHtEfDqsnyoPP/GYcfdw/0/6fZq1M+Jbtq2qp4TUYKTJEmSJEnSMlbX4WaSJEmSJEnqIZNEkiRJkiRJMkkkSZIkSZIkk0SSJEmSJEnCJJEkSZIkSZIwSSRJkiRJkiRMEkmSJEmSJAn4/48kRX5BDxvYAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 1440x1080 with 9 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Visualize the dataset\n",
    "dataset.hist(bins=50, figsize=(20,15));\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "#An important thing I notice in the dataset (and that wasn't obvious at the beginning) \n",
    "#is the fact that some people have null (zero) values for some of the features: \n",
    "#it's not quite possible to have 0 as BMI or for the blood pressure.\n",
    "\n",
    "#DATA CLEANING (Replace null values by median)\n",
    "nonzero_column_array=[\"BMI\",\"BloodP\",\"PlGlcConc\",\"SkinThick\",\"TwoHourSerIns\"]\n",
    "for column in nonzero_column_array:\n",
    "    median=dataset[column].median();\n",
    "    dataset[column]=dataset[column].replace(to_replace=0, value=median)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fa57dc26048>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#dataset.hist(bins=50, figsize=(20,15)); #uncomment if you want see data after cleaning\n",
    "#plt.show();\n",
    "corr=dataset.corr();\n",
    "sns.heatmap(corr,annot=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Split the training dataset in 80% / 20%\n",
    "from sklearn.model_selection import train_test_split\n",
    "train_set,test_set=train_test_split(dataset,test_size=0.20,random_state=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Separate labels from rest of dataset i.e. Final column\n",
    "train_set_labels=train_set[\"HasDiabetes\"].copy()\n",
    "train_set=train_set.drop(\"HasDiabetes\", axis=1)\n",
    "\n",
    "test_set_labels=test_set[\"HasDiabetes\"].copy()\n",
    "test_set=test_set.drop(\"HasDiabetes\",axis=1);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(614, 8)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_set.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(154, 8)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_set.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.naive_bayes import GaussianNB\n",
    "classifier=GaussianNB();\n",
    "classifier.fit(train_set,train_set_labels);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "154"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Predict=classifier.predict(test_set);\n",
    "len(Predict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[[92 15]\n",
      " [19 28]]\n"
     ]
    }
   ],
   "source": [
    "cm=confusion_matrix(test_set_labels,Predict)\n",
    "print(cm)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7fa57e2311d0>"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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i0Yh4PCJOrR3/YET8KiJmRsQNEbF0vZoMWkmV0kk2POr4G7BjZm4JjAR2i4iPAWcC52fmRiy4x+DgehMZtJIqpa9uwc0F3qi9fF9tJLAjcHPt+ERgr3o1GbSSKqU3D5Xp+lyW2mjrOldEDIqIacBcYDLwe+D1zJxfe8tsYES9mrwYJqlSerProOtzWRZxvgMYGRErA5OAD3f3tnqfY9BKqpQSd7tm5uu1xw58DFg5IgbXutq1gOfq/b5LB5IqpYNsePQkIlardbJExLLAPwEzgLuAz9fedgBwa72a7GglVUof3rAwHJgYEYNY0JTemJm3R8Rvgesj4nTgEaDuU9oNWkmV0ldLB5n5GLBVN8dnAdv0Zi6DVlKleAuuJBXWirfgGrSSKqUVH/xt0EqqFJcOJKkwg1aSCiv99VzvhUErqVLsaCWpMHcdSFJhHdl63xpm0EqqFNdoJakw12glqTDXaCWpsE6XDiSpLDtaSSrMXQeSVJhLB5JUmEsHklSYHa0kFWZHK0mFdWRHs0tYiEErqVK8BVeSCvMWXEkqzI5Wkgpz14EkFeauA0kqzFtwJakw12glqTDXaCWpMDtaSSrMfbSSVJgdrSQV5q4DSSqsFS+GLdXsAiSpL2Vmw6OeiLgsIuZGxPQux06JiDkRMa029qg3j0ErqVKyF38acAWwWzfHz8/MkbVxR71JXDqQVCl9eTEsM++NiPUWdx47WkmV0pnZ8FgMR0TEY7WlhVXqvTlacStEVUVEW2a2N7sOtRb/XTRPRLQBbV0Otb/7v0Wto709MzevvV4DeBlI4L+A4Zl5UI+fY9D2n4iYmplbN7sOtRb/XbS2dwdto+e6culAknohIoZ3ebk3MH1R7/07L4ZJ0iJExHXADsCwiJgNnAzsEBEjWbB08BRwSL15DNr+5TqcuuO/ixaVmft1c3hCb+dxjVaSCnONVpIKM2j7SUTsFhFPRMSTEXF8s+tR83V3e6eqyaDtBxExCPgBsDuwKbBfRGza3KrUAq6g+9s7VTEGbf/YBngyM2dl5jzgemBMk2tSk2XmvcCrza5D5Rm0/WME8GyX17NrxyQtAQza/hHdHHO7h7SEMGj7x2xg7S6v1wKea1ItkvqZQds/HgY2iogPRsTSwL7AbU2uSVI/MWj7QWbOB44AfgLMAG7MzMebW5WarXZ754PAxhExOyIObnZNKsM7wySpMDtaSSrMoJWkwgxaSSrMoJWkwgxaSSrMoJWkwgxaSSrMoJWkwv4fQioWza31CQUAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.heatmap(cm,annot=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.7792207792207793\n"
     ]
    }
   ],
   "source": [
    "accuracy=accuracy_score(test_set_labels,Predict)\n",
    "print(accuracy)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Correct Count 120\n",
      "Accuracy  :  0.7792207792207793\n"
     ]
    }
   ],
   "source": [
    "testlen=len(test_set_labels)\n",
    "correctCount=0;\n",
    "for i in range(154):\n",
    "    if(Predict[i]==test_set_labels.iloc[i]):\n",
    "        correctCount+=1;\n",
    "print(\"Correct Count\",correctCount)\n",
    "\n",
    "print(\"Accuracy  : \",correctCount/testlen)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}