Updated_time_series_forecasting.ipynb

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  "metadata": {
    "colab": {
      "name": "Updated_time series forecasting.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
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  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "wrIbUdIoF9LB",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import warnings \n",
        "warnings.filterwarnings('ignore')\n",
        "import numpy as np # linear algebra\n",
        "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
        "%matplotlib inline\n",
        "from scipy.stats import *\n",
        "import matplotlib.pyplot as plt  # Matlab-style plotting\n",
        "import seaborn as sns # informative statistical graphics.\n",
        "import statsmodels.api as sm #for ARIMA and SARIMAX\n",
        "import datetime\n",
        "from datetime import timedelta\n",
        "\n",
        "\n",
        "sns.set_style('darkgrid') #set color style for plot"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vTv8oBdIGAdi",
        "colab_type": "code",
        "outputId": "00d87ce0-7226-4740-9bf0-c4b76cbe5cc8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        }
      },
      "source": [
        "#importing dataset for API\n",
        "\n",
        "train = pd.read_csv('https://api.covid19india.org/csv/latest/state_wise_daily.csv')\n",
        "\n",
        "#DF = DF[:-1]\n",
        "# train = train[:-1]\n",
        "\n",
        "train['Date'] = pd.to_datetime(train['Date'], format=\"%d-%b-%y\")\n",
        "\n",
        "train.tail()"
      ],
      "execution_count": 219,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date</th>\n",
              "      <th>Status</th>\n",
              "      <th>TT</th>\n",
              "      <th>AN</th>\n",
              "      <th>AP</th>\n",
              "      <th>AR</th>\n",
              "      <th>AS</th>\n",
              "      <th>BR</th>\n",
              "      <th>CH</th>\n",
              "      <th>CT</th>\n",
              "      <th>DN</th>\n",
              "      <th>DD</th>\n",
              "      <th>DL</th>\n",
              "      <th>GA</th>\n",
              "      <th>GJ</th>\n",
              "      <th>HR</th>\n",
              "      <th>HP</th>\n",
              "      <th>JK</th>\n",
              "      <th>JH</th>\n",
              "      <th>KA</th>\n",
              "      <th>KL</th>\n",
              "      <th>LA</th>\n",
              "      <th>LD</th>\n",
              "      <th>MP</th>\n",
              "      <th>MH</th>\n",
              "      <th>MN</th>\n",
              "      <th>ML</th>\n",
              "      <th>MZ</th>\n",
              "      <th>NL</th>\n",
              "      <th>OR</th>\n",
              "      <th>PY</th>\n",
              "      <th>PB</th>\n",
              "      <th>RJ</th>\n",
              "      <th>SK</th>\n",
              "      <th>TN</th>\n",
              "      <th>TG</th>\n",
              "      <th>TR</th>\n",
              "      <th>UP</th>\n",
              "      <th>UT</th>\n",
              "      <th>WB</th>\n",
              "      <th>UN</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>202</th>\n",
              "      <td>2020-05-20</td>\n",
              "      <td>Recovered</td>\n",
              "      <td>3099</td>\n",
              "      <td>0</td>\n",
              "      <td>43</td>\n",
              "      <td>0</td>\n",
              "      <td>7</td>\n",
              "      <td>54</td>\n",
              "      <td>79</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>442</td>\n",
              "      <td>0</td>\n",
              "      <td>176</td>\n",
              "      <td>21</td>\n",
              "      <td>3</td>\n",
              "      <td>31</td>\n",
              "      <td>2</td>\n",
              "      <td>13</td>\n",
              "      <td>5</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>103.0</td>\n",
              "      <td>679</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>36</td>\n",
              "      <td>0</td>\n",
              "      <td>152</td>\n",
              "      <td>53</td>\n",
              "      <td>0</td>\n",
              "      <td>987</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>148</td>\n",
              "      <td>1</td>\n",
              "      <td>62</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>203</th>\n",
              "      <td>2020-05-20</td>\n",
              "      <td>Deceased</td>\n",
              "      <td>134</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>10</td>\n",
              "      <td>0</td>\n",
              "      <td>30</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>65</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>204</th>\n",
              "      <td>2020-05-21</td>\n",
              "      <td>Confirmed</td>\n",
              "      <td>6024</td>\n",
              "      <td>0</td>\n",
              "      <td>45</td>\n",
              "      <td>0</td>\n",
              "      <td>22</td>\n",
              "      <td>211</td>\n",
              "      <td>16</td>\n",
              "      <td>14</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>571</td>\n",
              "      <td>2</td>\n",
              "      <td>371</td>\n",
              "      <td>38</td>\n",
              "      <td>42</td>\n",
              "      <td>59</td>\n",
              "      <td>13</td>\n",
              "      <td>143</td>\n",
              "      <td>24</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>246.0</td>\n",
              "      <td>2345</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>51</td>\n",
              "      <td>0</td>\n",
              "      <td>23</td>\n",
              "      <td>212</td>\n",
              "      <td>0</td>\n",
              "      <td>776</td>\n",
              "      <td>38</td>\n",
              "      <td>2</td>\n",
              "      <td>340</td>\n",
              "      <td>19</td>\n",
              "      <td>94</td>\n",
              "      <td>307</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>205</th>\n",
              "      <td>2020-05-21</td>\n",
              "      <td>Recovered</td>\n",
              "      <td>3131</td>\n",
              "      <td>0</td>\n",
              "      <td>41</td>\n",
              "      <td>0</td>\n",
              "      <td>6</td>\n",
              "      <td>0</td>\n",
              "      <td>42</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>375</td>\n",
              "      <td>0</td>\n",
              "      <td>269</td>\n",
              "      <td>33</td>\n",
              "      <td>5</td>\n",
              "      <td>6</td>\n",
              "      <td>7</td>\n",
              "      <td>15</td>\n",
              "      <td>8</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>110.0</td>\n",
              "      <td>1408</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>50</td>\n",
              "      <td>0</td>\n",
              "      <td>25</td>\n",
              "      <td>81</td>\n",
              "      <td>0</td>\n",
              "      <td>400</td>\n",
              "      <td>23</td>\n",
              "      <td>32</td>\n",
              "      <td>138</td>\n",
              "      <td>0</td>\n",
              "      <td>57</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>206</th>\n",
              "      <td>2020-05-21</td>\n",
              "      <td>Deceased</td>\n",
              "      <td>148</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>18</td>\n",
              "      <td>0</td>\n",
              "      <td>24</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>64</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>7</td>\n",
              "      <td>5</td>\n",
              "      <td>0</td>\n",
              "      <td>11</td>\n",
              "      <td>0</td>\n",
              "      <td>6</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          Date     Status    TT  AN  AP  AR  AS  ...   TN  TG  TR   UP  UT  WB   UN\n",
              "202 2020-05-20  Recovered  3099   0  43   0   7  ...  987   2   0  148   1  62    0\n",
              "203 2020-05-20   Deceased   134   0   1   0   0  ...    3   2   0    4   0   3    0\n",
              "204 2020-05-21  Confirmed  6024   0  45   0  22  ...  776  38   2  340  19  94  307\n",
              "205 2020-05-21  Recovered  3131   0  41   0   6  ...  400  23  32  138   0  57    0\n",
              "206 2020-05-21   Deceased   148   0   1   0   0  ...    7   5   0   11   0   6    0\n",
              "\n",
              "[5 rows x 41 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 219
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Wu_WlP-IGJBo",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#Since we are predicting total cases ('TT') column we don't need state data ,  hence droping out state data\n",
        "\n",
        "cols = ['AN','AP',\t'AR',\t'AS',\t'BR',\t'CH',\t'CT',\t'DD',\t'DL',\t'DN',\t'GA',\t'GJ',\t'HP',\t'HR',\t'JH', 'JK',\t'KA',\t'KL',\t'LA',\t'LD',\t'MH',\t'ML',\t'MN',\t'MP',\t'MZ',\t'NL',\t'OR',\t'PB',\t'PY',\t'RJ',\t'SK',\t'TG',\t'TN',\t'TR',\t'UP',\t'UT',\t'WB']\n",
        "train.drop(cols, axis=1, inplace=True)\n",
        "train = train.set_index('Status')\n",
        "train.drop(['Recovered','Deceased'],inplace=True)\n",
        "train = train.reset_index()\n",
        "train.drop([\"Status\"],axis=1,inplace= True)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NuHqAbAzH_aV",
        "colab_type": "code",
        "outputId": "76c49917-6b5d-477b-ef60-df9056d24487",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        }
      },
      "source": [
        "train.tail()"
      ],
      "execution_count": 221,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date</th>\n",
              "      <th>TT</th>\n",
              "      <th>UN</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>64</th>\n",
              "      <td>2020-05-17</td>\n",
              "      <td>5049</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>65</th>\n",
              "      <td>2020-05-18</td>\n",
              "      <td>4628</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>66</th>\n",
              "      <td>2020-05-19</td>\n",
              "      <td>6154</td>\n",
              "      <td>814</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>67</th>\n",
              "      <td>2020-05-20</td>\n",
              "      <td>5716</td>\n",
              "      <td>282</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>68</th>\n",
              "      <td>2020-05-21</td>\n",
              "      <td>6024</td>\n",
              "      <td>307</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
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            ],
            "text/plain": [
              "         Date    TT   UN\n",
              "64 2020-05-17  5049    0\n",
              "65 2020-05-18  4628    0\n",
              "66 2020-05-19  6154  814\n",
              "67 2020-05-20  5716  282\n",
              "68 2020-05-21  6024  307"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 221
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QQOQQ1wPIvlp",
        "colab_type": "code",
        "outputId": "15f322a7-5933-41a5-ba1d-8dac32f89364",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        }
      },
      "source": [
        "# # copying data into train_df Dataframe so that our orignal data is untouched \n",
        "\n",
        "train_df = train\n",
        "\n",
        "train_df.head()"
      ],
      "execution_count": 222,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date</th>\n",
              "      <th>TT</th>\n",
              "      <th>UN</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2020-03-14</td>\n",
              "      <td>81</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2020-03-15</td>\n",
              "      <td>27</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2020-03-16</td>\n",
              "      <td>15</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2020-03-17</td>\n",
              "      <td>11</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2020-03-18</td>\n",
              "      <td>37</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
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            ],
            "text/plain": [
              "        Date  TT  UN\n",
              "0 2020-03-14  81   0\n",
              "1 2020-03-15  27   0\n",
              "2 2020-03-16  15   0\n",
              "3 2020-03-17  11   0\n",
              "4 2020-03-18  37   0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 222
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZDyWqNzgJNAJ",
        "colab_type": "code",
        "outputId": "ba7f624b-0807-48a1-93ba-a17f31c2f3e4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 296
        }
      },
      "source": [
        "#plotting current data\n",
        "\n",
        "sns.lineplot(x=\"Date\", y=\"TT\",legend = 'full' , data=train_df)"
      ],
      "execution_count": 223,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f4cc2a4a5c0>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 223
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5GEAVjfPK0e6",
        "colab_type": "code",
        "outputId": "46833b3d-2abd-4af9-eab7-8881d4e554d2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        }
      },
      "source": [
        "#setting 'date' column as index columna as forecasting will be done for this column\n",
        "#making 'TT' as float for statistical calculations\n",
        "\n",
        "train_df = train_df.set_index('Date')\n",
        "train_df['TT'] = train_df['TT'].astype(float)\n",
        "\n",
        "train_df.head()"
      ],
      "execution_count": 224,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>TT</th>\n",
              "      <th>UN</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2020-03-14</th>\n",
              "      <td>81.0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-03-15</th>\n",
              "      <td>27.0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-03-16</th>\n",
              "      <td>15.0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-03-17</th>\n",
              "      <td>11.0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-03-18</th>\n",
              "      <td>37.0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "              TT  UN\n",
              "Date                \n",
              "2020-03-14  81.0   0\n",
              "2020-03-15  27.0   0\n",
              "2020-03-16  15.0   0\n",
              "2020-03-17  11.0   0\n",
              "2020-03-18  37.0   0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 224
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xPHgNdocLRjx",
        "colab_type": "code",
        "outputId": "28ddd314-bb59-4517-e1f9-37427db8f635",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 715
        }
      },
      "source": [
        "#Decomposing data to observe if there exists a sesional trend\n",
        "\n",
        "from statsmodels.tsa.seasonal import seasonal_decompose\n",
        "result = seasonal_decompose(train_df['TT'], model='additive')\n",
        "\n",
        "fig = plt.figure()  \n",
        "fig = result.plot()  \n",
        "fig.set_size_inches(20, 12)"
      ],
      "execution_count": 225,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 0 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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            "text/plain": [
              "<Figure size 1440x864 with 4 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "elhXQw_GHih9",
        "colab_type": "text"
      },
      "source": [
        "The 'trend' graph has a upward growth which shows that the data is not stationary. Time Series forecasting can be done on stationary data and hence we need to nake it stationary."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4i3VMqFnLe9o",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "from statsmodels.tsa.stattools import adfuller #adfuller stands for Augmented Dickey-Fuller unit root test.\n",
        "\n",
        "#The function find mean and standard deviation of the series and and performs augmented dickey fuller test.\n",
        "#returns pvale .. The samaller the pvalue more stationary is the series.\n",
        "\n",
        "def test_stationarity(timeseries, window = 15, cutoff = 0.01):\n",
        "  rolmean = timeseries.rolling(window).mean()\n",
        "  rolstd = timeseries.rolling(window).std()\n",
        "  fig = plt.figure(figsize=(12, 8))\n",
        "  orig = plt.plot(timeseries, color='blue',label='Original')\n",
        "  mean = plt.plot(rolmean, color='red', label='Rolling Mean')\n",
        "  std = plt.plot(rolstd, color='black', label = 'Rolling Std')\n",
        "  plt.legend(loc='best')\n",
        "  plt.title('Rolling Mean & Standard Deviation')\n",
        "  plt.show()\n",
        "\n",
        "  print('Results of Dickey-Fuller Test:')\n",
        "  dftest = adfuller(timeseries, autolag='AIC',)\n",
        "  dfoutput = pd.Series(dftest[0:4], index=['Test Statistic','p-value','#Lags Used','Number of Observations Used'])\n",
        "  for key,value in dftest[4].items():\n",
        "      dfoutput['Critical Value (%s)'%key] = value\n",
        "  pvalue = dftest[1]\n",
        "  if pvalue < cutoff:\n",
        "      print('p-value = %.4f. The series is likely stationary.' % pvalue)\n",
        "  else:\n",
        "      print('p-value = %.4f. The series is likely non-stationary.' % pvalue)\n",
        "  \n",
        "  print(dfoutput)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oGILHoqnM7Hb",
        "colab_type": "code",
        "outputId": "d21f27f5-8868-4c03-f2fd-2694e8c92b87",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 669
        }
      },
      "source": [
        "test_stationarity(train_df['TT'])\n",
        "\n",
        "#calling the function gives below result , where we can observe the huge gap between orignal data and mean,std\n",
        "#also the pvalue is 0.9778 which is not so good and hence , the output says \"The series is likely non-stationary.\""
      ],
      "execution_count": 227,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Results of Dickey-Fuller Test:\n",
            "p-value = 1.0000. The series is likely non-stationary.\n",
            "Test Statistic                  2.890746\n",
            "p-value                         1.000000\n",
            "#Lags Used                      8.000000\n",
            "Number of Observations Used    60.000000\n",
            "Critical Value (1%)            -3.544369\n",
            "Critical Value (5%)            -2.911073\n",
            "Critical Value (10%)           -2.593190\n",
            "dtype: float64\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FHQDpcCuM-JC",
        "colab_type": "code",
        "outputId": "a0028203-a786-492f-dc37-83c508a917c4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 669
        }
      },
      "source": [
        "#here are various methods for making series stationary like log, differencing and so on..\n",
        "#here we are using differencing , shift operator shifts the 'TT' cloumn of df by 4 places and difference is taken.\n",
        "\n",
        "#plotting the data after differencing we see the pvalue is reduced to 0.3427 which is quite good as compared to our previous value 0.9778\n",
        "#you can try different values in shift to reduce the pvalue (if possible , #try to choose one where number of observations used is MAX abd pval is MIN)\n",
        "\n",
        "first_diff = train_df.TT - train_df.TT.shift(4)\n",
        "first_diff = first_diff.dropna(inplace = False)\n",
        "test_stationarity(first_diff, window = 12)"
      ],
      "execution_count": 228,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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FgRlqIiIiIqIwMKAmIiIiIgpDi26b53a74XKJUKsFuFysTAHAuWhGnHsvzoWE8+DFuYg8zqkX58KLcyGJxjwkJqpDPrdFB9QulwiLxYbUVB0sFltzD6dF4Fw0H869F+dCwnnw4lxEHufUi3PhxbmQRGMeMjNTQj6XJR9ERERERGFgQE1EREREFAYG1EREREREYWjRNdS+uFxOlJUdg9NZ09xDaRZms4CW1Do8IUGDtLRMqNUx91EiIiIiioiYi4LKyo5Bq9VBr89R5K5oarUKLpe7uYcBABBFEVVV5SgrO4Y2bXKbezhEREREzSLmSj6czhro9a0UGUy3NIIgQK9vpdhfC4iIiIiAGAyoATCYbkH4XhAREZHSxWRA3RKUlJgxc+Y0XHPNlRg7diSeeeZJ1NbWNjiutPQYHnzwAb/Xmz59CioqKkIay8svv4DVq1eFdC4RERERhYcBdQhEUcScOfejb99LsGbN+3jrrXWw221YufL/6h3ndDrRpk0mFi583O81n3zyOaSkhN5QnIiIiIiaR8wtSmwJvv/+O2g0SRg27AoAgFqtxpQp03D11SORm9sW3377Nex2O9xuN+bMWYAHHpiKVavegcPhwKOPLsChQwfRrl17lJYew333zUCXLudhzJgReOmlVbDbbZg+fQq6du2Gn3/ei8zMTCxe/BSSkrT48MP38dFH76Omphann3465s59BFqttplng4iIiEjZYjqgfvvtBLz1VmJEr3nttbUYN87Z5DGHDv2Bzp271LtPrzcgOzsbLpcLv/32K1577S20atUaRmOx55h169YiJSUFb7yxFn/8cQATJ17v8/pHjhzGggWPYsaMBzF37kx89dUXGDx4KPr3vxRXXnkVXC43Vq78P3z88XqMGXNN+C+aiIiIiEIW0wF1S1VQ0BOtWrVucP/PP/+Iq6++FgDQsePZOOuss32en5vbFp06dQYAdO7cxROU//HHQcyePR0VFRWw2+3o0ePvUXoFRERERBSomA6ox41z+s0mR8OZZ3bAV19tqXdfVVUlzGYz1Gp12GUYiYnerLtKpYbLVQ0AWLToISxZ8jQ6djwbn3zyEfbs+T6s5yEiIiKi8HFRYgjy83vA4XBg48aPAQAulwvLlj2DIUOGNxlM/+1vF+KLLz4HIJWNHDx4IKjntdmqkJHRBk6nE5s2bQz9BRARERFRxDCgDoEgCFi06Al8+eUWXHPNlbj22tHQaDS4447JTZ535ZVXw2Ipww03XI0XX1yBDh3Ogl5vCPh5b731Ttx66424886b0b79mWG+CiIiIiKKBEEURbG5B9GY2loXLBYbUlN1sFhsAACT6U/k5LRv5pGFxuVywel0IikpCUePHsHUqXdh9er36pV4+NOSth6XxfJ7Eoy6n0Ol41xIOA9enIvI45x6cS68OBeSaMxDZmbo7YtjuoY61lRXO3DPPZPgdDoBiJg2bUZQwTQRERERtTwMqE8hnU6Pl1/mjoZEREQUH44fF3DxxXqsXm1D9+4t6xf0U4k11EREREQUkqNHBZSVCfjtN2WHlMp+9UREREQUMrtdAADYbEIzj6R5MaAmIiIiopDY7dJtVRUDaiIiIiKioHkz1M08kGbGgDoE/fr1wE03XYfx48figQf+gYqKiiaPf/TRBfjyy80AgLvvvh379/8XADB9+hS/5wbCaCxGnz75WLny/zz3WSwW9O/fE08/vSTs6xMRERH54nBIt8xQU9CSkpLw6qursWrVO2jVqhXWrXsnpOs8+eRzSEkJvedhXbm5p2Hnzh2ev3/55WZ06HBWRK5NRERE5Itc8qH0DDXb5oXpggv+hgMHpC3Ef//9VzzxxGOornagbdvTMWvWPLRq1arRc8eMGYGXXloFu92G6dOnoGvXbvj5573IzMzE4sVPISlJi337fsHixY9AEFQoKOiJb7/9Gq+//naDa2m1SWjfvgP27/8vunQ5D1u2bEJh4WUoLT0GACgrK8OTTy6C2WwGAEyZMg1du3bDf//7Hzz77FOoqalGUpIWs2fPwxlnnIlPPvkIO3Zsg8PhQHHxEfTrdwnuuuveKMwgERERxSq55EPpGeqYDqiT3l4N7VtvRPSajmtvQPW46wI61uVyYffu7zB8+EgAwMKF8zF16v3Iy+uOl156Hq+88iLuvfe+gK515MhhLFjwKGbMeBBz587EV199gcGDh2LRoocwY8aDuOCCrlixYmmT17jsskHYvHkT0tLSoVar0aZNpiegfvbZJzF27PW48MJuMJlMuO++u/Hmm++iffszsXz5i0hISMB3332LF15YjkcffQIA8Pvvv+GVV95EYmIirrvuKlx11ThkZ+cE9HqIiIgo/jFDLYnpgLq5VFdX46abrkNpaQnat++AgoKeqKysREVFBfLyugMAhgwZjrlzZwR8zdzctujUqTMAoHPnLjAai1FRUQGbzYYLLugKABg48PJ6ZR0n69nzYrz44vNIT09HYeHAeo/t3r0LRUWHPH+vqqqCzWZDZWUlFi5cgCNH/oIgCP/bxVGSn18Ag8EAADjzzI4wmUwMqImIiMiDGWpJTAfU1eOuCzibHElyDbXD4cC0aXdj3bq1GDJkeFjXrLsFuUqlhstVHdI1OnfugjVr3sQbb7yDHTu2eR4TRTdeeOEVJCUl1Tvnn/98HBddlI/HHnsSRmMx7rnnDp9jUqtVcLmcICIiIpLJixLZh5pCptVqMXXqdKxZ8wa0Wi1SUlrhp5/2AAA+/XQDunW7KKzrp6SkQKfT4Zdf/gMA2LJlk99zrrnmBtx55z1o1ap1vfsLCv6O997z1l7//vuvAIDKykpkZmYCAD755KOwxktERETK4s1QN/NAmllMZ6hbgnPO6YKzzuqEzZs/w4MPLqizKPE0zJo1P+zrz5w5D48/vhCCoEK3bhdBrzc0eXzHjmehY8eG3T2mTr0fTz+9BBMmXAOXy4ULL8zD/ffPxvXX34iFCxfgtddeRq9efcIeLxERESkHM9QSQRRFsbkH0ZjaWhcsFhtSU3WwWKRqd5PpT+TktG/mkZ06NpsNOp0OALBq1asoKzuOKVMCW+h4qijlPan7OVQ6zoWE8+DFuYg8zqkX58Krpc3FpElarFuXiIwMN/btO3Vp6mjMQ2Zm6K2MmaFu4Xbu3IFVq16Fy+VETk4u5s59uLmHRERERASgbpcPZWeoGVC3cAMGDMKAAYM8f5cWB7qbcUREREREEodDCqTtdgEuF6BWN/OAmgkXJRIRERFRSOQMNaDsXtQMqImIiIgoJHKXD0DZZR8MqImIiIgoJHKXD0DZrfMYUBMRERFRSOx2AXq91DBOybslMqAOQb9+PXDTTddh/PixeOCBf6CioqLJ4x99dAG+/HIzAODuu2/H/v3/BQBMnz7F77mBcLvdeOaZJzB+/FjceOM43HrrjSguPgoAeP31fzV63ssvv4DVq1eF/fxERESkTHY7kJHBgJoBdQjkrcdXrXoHrVq1wrp174R0nSeffA4pKaH3PJRt2bIJpaXH8Npra/D6629j0aInYDBI11216pWwr09ERETki90uIDNTCqiVvCiRbfPCdMEFf8OBAwcASNt5e3dKPB2zZs1Dq1atGj13zJgReOmlVbDbbZg+fQq6du2Gn3/ei8zMTCxe/BSSkrTYt+8XLF78CARBhYKCnvj226/x+utv17vO8eOlyMhoA5VK+n6UlZUNAFixYimqq6tx003XoUOHjpg/fyFee+1lbNy4AWlpacjKykbnzudGaWaIiIgo3jFDLYnpgPrtt1fjrbfeiOg1r732Bowbd11Ax7pcLuze/R2GDx8JAFi4cD6mTr0feXnd8dJLz+OVV17EvfcGtqvhkSOHsWDBo5gx40HMnTsTX331BQYPHopFix7CjBkP4oILumLFiqU+zy0sHIi77roVP/30I7p3L8DgwUNwzjldcOed92Ddunfw6qurAQD79+/Dli2b8Oqrq+FyOXHzzTcwoCYiIqKQ1NYCLpfgCaiVnKFmyUcI5KzvyJGDUVZ2AgUFPVFZWYmKigrk5XUHAAwZMhw//fRDwNfMzW2LTp06AwA6d+4Co7EYFRUVsNlsuOCCrgCAgQMv93luVlY2Vq9+D3fcMRkqlQr33nsXdu/e1eC4vXv3oF+/S6HVaqHXG9CnT79gXzoRERERAG8P6owMacM5Zqhj1Lhx1wWcTY4kuYba4XBg2rS7sW7dWgwZMjysayYmJnr+rFKp4XJVB3W+RqNBr1690atXb6SlpWP79q+Qn98jrDERERERNUbuQc0MNTPUYdFqtZg6dTrWrHkDWq0WKSmt8NNPewAAn366Ad26XRTW9VNSUqDT6fDLL/8BIC0+9OXXX/ejtPQYAKnjx8GDvyM7OxcAoFYnwOl0AgAuvPAibN/+FaqrHbDZqvDvf28Pa3xERESkXHKGOj2dNdQxnaFuCc45pwvOOqsTNm/+DA8+uKDOosTTMGvW/LCvP3PmPDz++EIIggrdul0Evd7Q4JiyshNYsmQhamtrAADnnns+rrpqLADgiiuuxIQJ1+Ccc7pg/vyFKCwciAkTrkNaWhq6dDkv7PERERGRMskZap0O0OlERe+UKIiiKDb3IBpTW+uCxWJDaqoOFov0O4LJ9Cdycto388hOHZvNBp1OBwBYtepVlJUdx5QpgS10PFWU8p7U/RwqHedCwnnw4lxEHufUi3Ph1ZLmYs8eFQYP1uONN2yYOlWLoUOdePLJ4EpWQxWNecjMDL2VMTPULdzOnTuwatWrcLmcyMnJxdy5Dzf3kIiIiIg8GerkZECvZ8kHtWADBgzCgAGDPH9Xq1VwudzNOCIiIiIibw21Viv+r+SjecfTnLgokYiIiIiCxgy1V0wG1C247Ftx+F4QEREpk5yhTk4Wodcre1FizAXUCQkaVFWVM5BrAURRRFVVORISNM09FCIiIjrFHA5vhlqnE1FV1cwDakYxV0OdlpaJsrJjqKy0NPdQmoUgCC3qy0RCggZpaZnNPQwiIiI6xepnqKHoDHXMBdRqdQLatMlt7mE0m5bULoeIiIiUS66h1mqZoY65kg8iIiIian7eLh9QfIaaATURERERBc1uF5CcLEIQvDsluhXa2ZcBNREREREFzeGQ6qcBQK+XbuWstdIwoCYiIiKioEkZaunPOp10q9Re1AyoiYiIiChodrtUPw14M9RK3S2RATURERERBc3hEDwlH8xQExEREREFyWaDp+RDzlArtXUeA2oiIiIiCprDIUCrrZ+hVmrrPAbURERERBQ0u90bSHsz1AyoiYiIiIgCYrd7M9RclEhEREREFCSpD7X0Z71eumWGmoiIiIgoQHY76nT5YIa6SUajEePHj8fQoUMxbNgwvPbaawAAi8WCiRMnYtCgQZg4cSKsVisAQBRFLFy4EAMHDsSIESPwyy+/eK71/vvvY9CgQRg0aBDef//9KL0kIiIiIoo2qeRD+jPb5vmhVqsxc+ZMfPLJJ3j77bexevVqHDhwACtXrkSvXr2wadMm9OrVCytXrgQAbNu2DUVFRdi0aRMeeeQRLFiwAIAUgC9btgzvvPMO1q5di2XLlnmCcCIiIiKKHaIo75QoZabVailbzS4fjcjKysL5558PADAYDOjYsSPMZjO2bNmCUaNGAQBGjRqFzZs3A4DnfkEQ0K1bN5SXl6OkpAQ7duxA7969kZqaitatW6N3797Yvn17FF8aEREREUWDwyHdyjXUgFT2wT7UAThy5Aj27duHCy+8EMePH0dWVhYAIDMzE8ePHwcAmM1m5OTkeM7JycmB2WxucH92djbMZnMkXgMRERERnULegFr03KfXK7cPdUKgB1ZVVWHKlCmYPXs2DAZDvccEQYAgRH4C1WoBqak6qNUqpKbqIn79WMS5aD6cey/OhYTz4MW5iDzOqRfnwqulzEVlpXSbkaFBamoiAMBgEFBTk3BKxtdS5kEWUEBdW1uLKVOmYMSIERg0aBAAICMjAyUlJcjKykJJSQnS09MBSJlnk8nkOddkMiE7OxvZ2dnYtWuX536z2YwePXo0+bwulwiLxYbUVB0sFoUuGz0J56L5cO69OBcSzoMX5yLyOKdenAuvljIXZrMAwAC3uxoWixMAkJysg9UqwmaLSc8AACAASURBVGKxR/35ozEPmZkpIZ/rt+RDFEXMmTMHHTt2xMSJEz33FxYWYv369QCA9evXY8CAAfXuF0URP/74I1JSUpCVlYU+ffpgx44dsFqtsFqt2LFjB/r06RPywImIiIioedjtUmUCa6glfjPU33//PT744AOcc845GDlyJABg2rRpuP322zF16lS8++67aNu2LZ555hkAQP/+/bF161YMHDgQycnJWLRoEQAgNTUVd911F8aMGQMAmDx5MlJTU6P1uoiIiIgoSuz/S0LL/acBabfEEyeUucWJ34A6Pz8fv/76q8/H5J7UdQmCgPnz5/s8fsyYMZ6AmoiIiIhik8MhZajlPtSA1ItaqYsSlfk1goiIiIhCJmeo63f5UG7JBwNqIiIiIgqKXEPNDLWEATURERERBaWpDLUoNnJSHGNATURERERB8d3lAxBFwbPpi5IwoCYiIiKioPjeKVH6c1WV8so+GFATERERUVAa60MNALbm33fmlGNATURERERBsdsBtVpEYqL3Pr1eumWGmoiIiIjID4dDqJedBrwlH8xQExERERH5YbPVr58GpEWJADPURERERER+2e3MUNfFgJqIiIiIguJw+MpQs8sHEREREVFA7Hah3i6JgHdRohJ3S2RATURERERBaTpD3Rwjal4MqImIiIgoKL5qqLkokYiIiIgoQHY7oNXWz1AnJgIajchFiURERKRMZrMAi6W5R0GxwleGGpDqqJmhJiIiIkUaPz4Z8+Zp/R9IBClDLddM16XTiYpclJjQ3AMgIiKi5nfggAqpqQ0DJCJfHI6GXT4AqRc1FyUSERGR4lRWApWVgiJ/qqfQ2O0Nu3wA0sJEJWaoGVATEREpnNEohQOVlc08EIoJLhdQU8MMdV0MqImIiBTOaJQyisxQUyDsdumWGWovBtREREQKJwfUzFBTIOx26fPiu8uHqMgvZgyoiYiIFM5kkks+lBcIUfAcDunWV4Zar2cfaiIiIlIgOUNdUyOgpqaZB0MtXlMZap1OmaVDDKiJiIgUTg6oAShyQRkFR66hbmxRos0GiArrwMiAmoiISOHkkg+AZR/knzdD7XtRotOpvF86GFATEREpnNEoICVFCo4YUJM/3i4fDR/T66XPkdJ+6WBATUREpGBOJ1BSIuDss90A2OmD/POXoQaU1zqPATUREZGCHTsmwO2uG1ArKxCi4Hm7fDR8zJuhVtbniAE1ERGRgskLEjt1YkBNgWk6Qy3dp7TWeQyoiYiIFEzedlzOUCut9pWCJ2eofXf5kG6ZoSYiIiLFMJnqZ6iVFghR8OT6aGaovRhQExERKZjRKCAxUcQZZ7DkgwLTdJcP6VZpX8wYUBMRESmY0ahCTo4IrRZISBDZ5YP8cjiApCQRKh9RpDdDzYCaiIiIFMJkEpCTI0IQpOwiM9Tkj90u+MxOA+xDTURERApkNArIzZXKPQwGkQE1+eVwAFqt773F2YeaiIiIFMdoVCE3VwqODAZRcZlFCl5TGWqNRiodUtrniAE1ERGRQlVUSIvHcnLkDDVLPsg/m63xDLUgSFlqZqiJiIhIEeQe1HKGWq9nyQf553AIntIOX/R6ZqiJiIhIIeRdElnyQcGw2333oJZJAbWyvpgxoCYiIlIoOaCWSz7Y5YMC4XAIPndJlLHkg4iIiBTDZJLCgJwcb4aaATX5E1iG+hQOqAVgQE1ERKRQRqOAtDTR07GBJR8UiKa6fADMUBMREZGCGI3eDh+A1OWjpkZATU0zDopaPLu98S4fADPUREREpCAmk7cHNSBlqAFw+3FqEjPUDTGgJiIiUqi6uyQCdQNqZQVDFDhRZJcPXxhQExERKZDTCRw7JngWJAJSlw+AATU1rrYWcLv9ZahF2GynbkwtAQNqIiIiBSopEeB2Cyz5oKDY7dJt0xlqqRa/tvYUDaoFYEBNRESkQN5NXbwlH3KGWmk/11PgHA7ps9F0H2op2FZSlpoBNRERkQIVF9fvQQ2whpr8k4NkfxlqQFlfzBhQExERKZDJVH/bccAbUCut5RkFzm6XPjf+aqgBZqiJiIgozhmNAjQaERkZdQNq6ZYZamqMwyHd+uvyATBDTURERHHOaFQhJ0eEUCfmkQMhBtTUmMAy1NItA2oiIiKKayZT/V0SASApCUhIENnlgxolZ6j97ZQIsOSDiIiI4pzRWH+XRAAQBKnsQ0mZRQqOvANiUxlqLkokIiKiuCeKcoa6YZbRYBBZ8kGNCqQPNRclEhERUdwrL5cyjXV7UMukgLoZBkUxQe5DzQx1fQyoiYiIFMZolP77P7nkA5CCIWaoqTHBZaiV8zliQE1ERKQw3l0SfQXULPmgxsldPpraKVGrBVQqUVH9zBlQExERKYy8qcvJXT4AqeRDSYEQBcfhAARBRFJS48cIgtQ6jxlqIiIiiltyyYfvRYnKqn2l4NhsApKTUa9/uS96vbK+mDGgJiIiUhijUUB6utvnz/bs8kFNcTiarp+WMUNNREREcc1kUvnMTgPs8kFNs9uFJjt8yKQMNQNqIiIiilNGo+BzQSIglXzU1gqorj7Fg6KYYLc3vUuiTKcT2YeaiIiI4pcUUDdckAh4t41m2Qf54nAEmqFWVi2+34B61qxZ6NWrF4YPH+65b+nSpejbty9GjhyJkSNHYuvWrZ7HXnjhBQwcOBCDBw/G9u3bPfdv27YNgwcPxsCBA7Fy5coIvwwiIiIKRG0tUFrqe5dEQCr5AMCyD/LJbg+0hlpZGeoEfweMHj0aN9xwA2bMmFHv/ptuugm33HJLvfsOHDiADRs2YMOGDTCbzZg4cSI+++wzAMDDDz+MV155BdnZ2RgzZgwKCwtx9tlnR/ClEBERkT9mswBRbLrkA5Czi/4DJ1IWu13wbNzSFGaoT1JQUIDWrVsHdLEtW7Zg2LBh0Gg0aNeuHdq3b4+9e/di7969aN++Pdq1aweNRoNhw4Zhy5YtYQ+eiIiIguPd1MVfyccpGxLFELsdAQXUOh3b5gXkzTffxIgRIzBr1ixYrVYAgNlsRk5OjueY7OxsmM3mRu8nIiKiU8tkarwHNVC35EM52UUKnN0uNLlLokyvV1bbPL8lH75ce+21uOuuuyAIAp599lksXrwYjz32WKTHBrVaQGqqDmq1CqmpuohfPxZxLpoP596LcyHhPHhxLiIvWnNqsUhBTpcuWqSmNnw8N1e6FcUkn483B36+vJp7LmpqBLRurfY7howMAQ6HgJQUHdTqyI+juefhZCEF1G3atPH8+eqrr8akSZMASJlnk8nkecxsNiM7OxsAGr2/KS6XCIvFhtRUHSwWBVW2N4Fz0Xw4916cCwnnwYtzEXnRmtM//khCUlIi1GobLJaGj4uiAMCAkpIaWCzOiD9/KPj58mruuaiqMkCtdsJiabqvokqVCECL4mIbUlIiP45ozENmZugDDanko6SkxPPnzZs3o1OnTgCAwsJCbNiwATU1NTh8+DCKiorQtWtX/O1vf0NRUREOHz6MmpoabNiwAYWFhSEPmoiIiEJjNArIzhYb3Tpar5duWfJBvjgcCLjkA1DOwkS/Gepp06Zh165dKCsrQ79+/XDPPfdg165d2L9/PwDgtNNOw8MPPwwA6NSpE4YMGYKhQ4dCrVZj3rx5UP8vzz9v3jzceuutcLlcuOqqqzxBOBEREZ06JlPjPagBbw21UgIhCpzbLe+UGNiiRACKaZ3nN6B++umnG9x39dVXN3r8nXfeiTvvvLPB/f3790f//v2DHB4RERFFktGowoUXuhp9PCkJSEzk9uPUkMMh3Qa6sQugnPaL3CmRiIhIIURRylA31uFDZjCw5IMa8gbUgWeolfJLBwNqIiIihbBapZ/smyr5AKSyDwbUdDK7XfpMBJahVlbJBwNqIiIihTAapf/2G9slUSYF1KdiRBRL7HbpVqsNJEMt3TJDTURERHFF3iXRX8mHTseSD2oolAy1UnZLZEBNRESkECZT09uOywwGUTGZRQqcnKEOrIZaulXKbokMqImIiBRCLvnwvyhRVExmkQLncISSoWZATURERHHEaBSQkeFGUlLTx7HLB/kSTIZaDrqV8sWMATUREZFCmEwqv9lpgF0+yDe5hjqQnRJVKql1Hks+iIiIKK4YjYLfDh+At8uHGP/7cVAQgulDDUgBNTPUREREFFekgLrpBYmAtMud0ymguvoUDIpihpxtDqSGGpA+R8xQExERUdyoqQFKSwMv+QCUs6CMAsMMdeMYUBMRESmA2Sy3zAs8oObmLlRXMDXUADPUREREFGfkTV0CLfkA2OmD6rPbgcREEYmJgR2v1yunnzkDaiIiIgUwmQLrQQ3UzVArIxiiwDgcQsDZaUDu8hG98bQkDKiJiIgUIJgMtbeGOqpDohhjtwdePw1Iv3QwQ01ERERxw2hUISlJRFqa/2NZ8kG+2O3MUDeGATUREZECmEwCcnJECAHEyMxQky92uxQkB4qLEomIiCiuBNqDGmANNflmtwsB96AGvDslugP72MU0BtREREQKYDSqAmqZBwAGg3TLgJrqcjgArTaYDLV0rBLKPhhQExERxTlR9JZ8BEKjATQakX2oqZ7gM9TSrRIWJjKgJiIiinMWi9TyLNCSD0Aq+2CGOj65XMDGjQlBby1vtzND3RgG1ERERHHOaJT+uw+05AOQFpQxoI5Py5drMGFCMjZtSgjqPGaoG8eAmoiIKM6ZTFJAE2jJByBlqNnlI/7s3avC4sUaAN7PRaCC7/LBDDURERHFCW+GOvCSD2ao44/NBkyapEVmpoiEBBElJcG9v8HvlCjdMkNNREREMU/eJTH4DHX8B0JK8tBDSThwQI2lSx3IzBRRUhJcGBj8Tolyhjr+P0cMqImIiOKc0SigTRs3NJrAz5EWJUZvTHRqff65Gq+8osGdd9agXz8XsrKCy1A7nUBtbXAZajmgVkLpEANqIiKiOGcyqYLKTgNSL2qWfMSHY8cE3HuvFued58Ls2VJrj2ADaodDug0uQy3dMkNNREREMU/aJTG4gFqvZ9u8eCCKwD/+oUVFhYAVKxxISpLuz8pyBxVQy0FxMF0+mKEmIiKiuCFt6hLc/s9ylw8xuDicWpjXX0/Epk0JmDu3Guee6/0MZGWJKC0V4HIFdp1QMtRy8M0MNREREcW06mqgtDTwbcdlBgPgdApBb/5BLceBAwLmzUvCJZc4ceuttfUey8oS4XIJOHEisGDXbg8+Q61WSwG4Eha3MqAmIiKKY2azFMwEH1BLx7PsIzbV1gJ33pmM5GQRzz3ngOqkiC8rS3p/Ay37sNul22Ay1IDUt5p9qImIiCimhdKDGvDWv7LTR2x64gkNfvpJjSefrPa5IDUzM7iA2uGQjgumywcgLUxkhpqIiIhiWii7JAJSyQfADHUs+uYbNZ59VoPrrqvB8OFOn8dkZUlfsAINqOUscygZai5KJCIiophWXCwFTG3bhpqhZkAdS8rLgcmTtWjfXsTChY0XwMslH8eOBZehDqaGGpAy1EpYlJjQ3AMgIiKi6CkuVkGnE9G6dXDnyTXUSqh/jSePP56E4mIBH31k8/zK4IvBIGWPA90tMZwaapZ8EBERUUwzGgW0beuGEGRMw5KP2LRvnwoXXeRGfr7/XySC2dwllC4fgPRLhxK+lDGgJiIiimPFxcG3zAPqdvmI9IgomiwWAampgb3fmZliECUf0m2wixJ1Oi5KJCIiohgnZajDCajjPxiKJ1argNatA3u/g9kt0btTYvA7bjJDTURERDHL5ZK6fAS7IBGQFpMBDKhjTXl5MAF18DXUzFD7xoCaiIgoTpWUCHC5hJBKPjQaQKMRWfIRQ9xuqctHMAF1WVlgu2E6HAK0WrHBBjH+yBnqeN/CngE1ERFRnAq1ZZ7MYFBGh4Z4UVUFuN0CWrUKPKAGgNJS/++x3R78gkRAylCLouDJcMcrBtRERERxqrhY3iUxtPSgwcCSj1hitUrvVaAtEoPZ3MXhALTa4D9Hcj/zeO9FzYCaiIgoThmNcoY6tIBar2fJRyyxWKT3O9gMdSABtd0uhJShlgPqeN8tkQE1ERFRnCouViEpSUR6OjPUSlBeLr1XgbbN8wbU/sNBqeQj+M+RTifdMkNNREREMclolBYkBrupi4w11LHFW/IRWODbpk1wGepgO3wAzFATERFRjCsuDq1lnsxgYMlHLLFapdtASz6SkoC0tMB2S7TbpW3Eg8UMNREREcU0o1EVcv00IPWiZoY6dsglH4FmqIHAN3eR2uYFPyZvhjq+P0cMqImIiOKQ2y3vkhhuhjq+A6F4Ipd8pKQEfk6gm7uEXkPNkg8iIiKKUaWlAmprQ9vURSaXfMT7phzxwmoVYDCISEgI/JzMTBHHjkWzy4d0y5IPIiIiijnhtswDpC4fLpcAhyNSo6JoslqFgDt8yKQMdfT6UDNDTURERDFL3tQlnJIPuf6VZR+xwWoNfEGiLCvLDZtN8Lv41GYLLUPNRYlEREQUs+Rtx8Mt+QDATh8xorxcCGpBIhDY5i6iKGWoQ6mhTkwENBqRGWoiIiKKPcXFAhITRU+v4VDI9a/x3qEhXlitwQfUmZn+N3epqQHc7tAy1ID0OWKGmoiIiGJOcbEKubkiVGH8T+/NUMd3MBQvyssFtGoV3DlyhrqphYl2u3QbSoYakOqo4/1LGQNqIiKiOCTtkhh6/TTgDajj/ef6eGGxRKfkw+GQHgulDzUg1eLbbKGdGysYUBMREcWh4uLwNnUBpC4fADPUscDlAioqgg+o09NFqNVNd/qQg+HQM9TxXzbEgJqIiCjOiKKcoQ43oGbJR6yoqJBugw2o1WqgTZumA2q7XXos9BpqZqiJiIgoxpw4IaC6OrxdEgF2+Ygl8i6JwQbUgP/dEuU+5MxQN44BNRERUZyJRMs8gF0+Ykl5ufQeBbsoEfC/uUtkMtTx/RliQE1ERBRn5F0STzstvAx1YiKQlCQyQx0Dws9QN7UoUboNZadEQAqo431hKwNqIiKiOOPdJTG8DDUglX2whrrls1jkDHUoAbUbx44JcDfy/SvcDDVLPoiIiCjmGI0C1GrRs2lHOPR6LkqMBeXl0m1qamgZaqdTQFmZ7/c53C4f8qJEMfyPY4vFgJqIiCjOFBerkJMjQq0O/1pShjq4c2w2oLo6/OemwIVb8gE03ota7kMdToba5RLi+jPBgJqIiCjOFBeH3zJPZjAEv8vdDTck4/77Q9wFhEJitQoQBNHTOzwY/nZLDHenRL1eOi+eW+cxoCYiIooz0qYu4S1IlOn1wdW/iiLw449q/PorQ4xTSd52PJSt5rOypM+Kvwx1qDsl6nTSbTzXUfud9lmzZqFXr14YPny45z6LxYKJEydi0KBBmDhxIqxWKwBAFEUsXLgQAwcOxIgRI/DLL794znn//fcxaNAgDBo0CO+//34UXgoRERFFalMXWbAlH6WlAiorBZhM8Rs8tURWa/C7JMr8lXzY7YBKJUKjCW1s3gx1/H4m/AbUo0ePxksvvVTvvpUrV6JXr17YtGkTevXqhZUrVwIAtm3bhqKiImzatAmPPPIIFixYAEAKwJctW4Z33nkHa9euxbJlyzxBOBEREUWO1SoFLpHKUBsMwS1KLCqSjm2qawRFntUqhNThA5De4+Tkxjd3sdkEJCcDQojxsE4njSueW+f5DagLCgrQunXrevdt2bIFo0aNAgCMGjUKmzdvrne/IAjo1q0bysvLUVJSgh07dqB3795ITU1F69at0bt3b2zfvj0KL4eIiEjZItkyDwi+bV5RkfT8TqeA48fjNyPZ0litoXX4AKRAOTOz8V7UDkfo9dOAd4MgRWeofTl+/DiysrIAAJmZmTh+/DgAwGw2Iycnx3NcTk4OzGZzg/uzs7NhNpvDGTcRERH5IG/qkpsbqQy1VPIRaMuzQ4e8oQXLPk4dqYY69KC3qc1d7HYh5A4fgDIy1AnhXkAQBAih/gbgh1otIDVVB7VahdRUXVSeI9ZwLpoP596LcyHhPHhxLiIv1DmVN/jo0kWL1NTwx9GmjQC3W0BSks6zuKwp8rbnAFBVFZkx8PPl1dhcVFSokJkphDxPbduqcPAgfJ7vdKqg0/l+LBDenKo25Cz6yVraZyKkgDojIwMlJSXIyspCSUkJ0tPTAUiZZ5PJ5DnOZDIhOzsb2dnZ2LVrl+d+s9mMHj16+H0el0uExWJDaqoOFksc91oJAuei+XDuvTgXEs6DF+ci8kKd0wMHNBAEDZKTbbBYwh+HSpUIQIujR+0BbRTz6686nHGGG3/9pcLBg7WwWGrDHgM/X16NzUVZmQFarRMWS2jNntPSkmAyJfi8dkVFMpKShJDfA5dLAGDAsWM1Efk8ANH5TGRmpoR8bkglH4WFhVi/fj0AYP369RgwYEC9+0VRxI8//oiUlBRkZWWhT58+2LFjB6xWK6xWK3bs2IE+ffqEPGgiIiLyzWgUkJ0tIjExMtczGKQgOtBOH3/+KaBnTxcAwGxmycep4HRKLelC7fIBSCUfx4+rUOsj3rXbw62hjv8+1H4z1NOmTcOuXbtQVlaGfv364Z577sHtt9+OqVOn4t1330Xbtm3xzDPPAAD69++PrVu3YuDAgUhOTsaiRYsAAKmpqbjrrrswZswYAMDkyZORGonfgIiIiKgeqQd15PZ4ljcKkRYmNn3digqgtFSFzp1rkZYmsob6FAlnl0SZ3DqvtLRhy0W7XfB8sQpFoH2o//MfFRYtSsLChQ507Bhb+5T7Daiffvppn/e/9tprDe4TBAHz58/3efyYMWM8ATURERFFh9Eo4OyzI9evTg6kAtmUQ+7w0aGDG9nZbmaoTxG5E3EkAuqSEl8BNQIq92mMRgMkJIhNLkrcsCEBkydLNdZyV5BYwm2MiIiI4kjkM9SBl3zIHT7OPNP9v64RDDNOhfLySGSoG98t0W4XAlqQ2hhBkFrn+WqbJ4rAU09pMHFiMs49143PPrMhOzu2stMAA2oiIqK4UVEBVFQIEWuZB5xc8tG0uhnqnByWfJwq3pKP0K/hzVA3DA0dDkCrDS/I1enEBr9y2GzAHXdosWRJEq6+uhbvvx+bwTQQgbZ5RERE1DIYjZHd1AXwLigLpOTj0CEBbdq4YTAA2dlulJQkwO0GVEzfRZWcoQ6nD7Vc0tFYhjqcPtSA9DmquyixuFjAhAnJ2LtXhblzq3H33TUh78TYEjCgJiIiihNHj0oRSXOVfBQVqdChg3R8To6I2loBJ04IaNMmNrOOsSISixK1Wul8XwG1lKEO+dIApIWJ8pey779XYcKEZFRVCVi1yo5Bg1zhXbwF4HdGIiKiOBHpXRKB4Eo+Dh1S4cwzpeeWf7rnwsTok/uNhxNQA1Id9bFj9d8vtxtwOISw2uYB3gz12rUJGDVKh+RkYONGW1wE0wADaiIiorhRXCz9t56TE7mMcEKCVD/rL6C226Xn79CBAfWpVl4uQK0OvzuGr+3H7XbpNtySD50O+P57NSZPTkZ+vguffmpDly6R++LX3BhQExERxQmjUaphTkqK7HUNBtFvycdff3k7fABSDTXAgPpUsFqlTV3CrUH21ZnF4ZAuGm6G2mAQUV0t4MYba/DOO3ZkZMRXGRBrqImIiOJEpFvmyfR6/yUfRUXS4w0z1MzdRZvVKqBVq/CvE80M9T331GD4cCeuuMIZ04sPG8OAmoiIKE4UFwto3z7yP6Pr9U1vygHU7UEtBdLJyVJNL1vnRV95eXjbjssyM6XSnqoqeMpHHA7pNty2eV27utG1a/yUeJyMXxuJiIjihNGoarDLXSQYDA17CJ+sqEiFVq1EpKd7n5+7JZ4aUoY6/Pdd3tyl7sJEu10u+Qj78nGNATUREVEcqKoCLBYBp50WjYDaf8mH3OGj7s/52dkiTCaGGtFmtYbf4QOov/24TN7dMNwa6njHTzkREVEckEsrItkyTxbIokSpB3X9587O9t3XmCLLahWQmhqZkg+g/m6JcskHM9RNY0BNREQUB+SWedFYlCgF1I0Hxk4ncPiw4OnwIcvJkUo+RCY3o6q8PHKLEoH6GWrvokS+iU1hQE1ERBQHioujmaFuuuTjyBEBTqfgWZAoy84WUVMjoKws4kOi/6muluqcI1Hy0aaNCJVKPCmgZg11IBhQExERxQGjUfovPRqLEuUuH41lmouKpOf2VfIBsHVeNJWXSwFvJBYlqtVARoZYb1FipLp8xDt+womIiOLA0aMC0tPdUckk6vWA2y14fv4/mbdl3sklH1IQxtZ50VNeLt1GIkMNNNzcxbsoMSKXj1sMqImIiOJAtFrmAVINNdB42UdRkQpardhgy3O5DRtb50WPxSLNbWQD6oYZatZQN40BNRERURwoLhaisiARqBtQ+3780CFpQxnVSVEFSz6iz2qNbkAt11BrtRG5fNziJ5yIiCgOGI1CVBYkAtKiRACNbu7y558NW+YBUqlISorIDHUUyTXUrVtH5npZWW6UlHg7s9jtgEYjIoF7azeJATUREVELFEyrOYcDOH5cdQoy1A0DY1GUSj7at/f93NwtMbqikaGurRVgsUh/dzgEZqcDwICaiIiohfn6azXatVPh6NHAAlGjUTqubdvoZKj1eilYq6pq+JjZLMBuF3xmqAFpYSJ3S4weOaCORJcPwNuL+tgx6T2z21k/HQh+womIiFqYH39UoaREwOrViQEdH82WeYC35MNXhrqxDh+yrCyWfEST1QokJooR68Jx8uYudjsz1IFgQE1ERNTCyBndNWsS4Q4g6Sxv6tIcJR9FRdJ9TWWouVti9Fit0qYuQoS+szQMqAGdjm+ePwyoiYiIWhg5o3v4sArbtqn9Hi9vOx69RYmNd/k4dEgFtVrE6ac3XkNdXS3Aao3K0BSvvFyI2IJEwNvqsG6Gmj2o/WNATURE1MKYTAIKCkSkpooBlX0YjVKWUi7NiDS9Xrr1naFWoV07EYmNvX8yDwAAIABJREFUDNO7uQtDjmiQM9SR0qoVkJTkbZ3ncHCXxEDw001ERNTCmEwqdOggYsyYWnzySQJOnGj6eKkHdXSy0wCQkCAtTGushrqx+mmgbi9q1lFHQ3m5ELEFiQAgCPV3S2SGOjAMqImIiFoQUZSCz7Ztgeuuq0VNjYD33ms6Sx3NXRJler3YoMuHKEoBdWP104BU8gEwoI4WqzVyLfNkdTd3cTjY5SMQDKiJiIhakMpKwGYTkJsLXHCBGxde6MKbbyY2uagv2hlqQCr7ODlDXVYmZUgDyVCz5CM6LJbIZqgBIDPT7QmobTZ2+QgEP91EREQtiBx45uZKf7/uulr8979q/PST7/+ya2qAY8eEqGeoDYaGGeqiImlMTWWoDQYpu113O2uKDFGUFyVGOqAW63X5YIbaPwbURERELYjJJAUycoA8enQttFoRb77pu+zDZBIgikLUWubJDIaGNdTeHtRNP7e0uQsD6khzOICaGgGpqZG9blaWiOPHBTid0k6JrKH2jwE1ERFRC+INqKW/t24NDB/uxLp1ibDZGh4f7ZZ5MoOhYcmHnKFu377p5+b249FRXh7ZXRJlWVkiRFHA8ePCKc9Qq44eQSw2LWdATURE1IKcXPIBANdfX4uKCgEff5zQ4HjvtuOnIkNd/75Dh1TIzXX7zWBy+/HokLcdj8aiRAA4elSA09l0hrqkpAT9+/8dK1YsgxhmIJy8Yhky8s5Dwne7wrpOc+Cnm4iIqAUxmwUYDCJSUrz3XXyxC2ee6fbZk9q7S2K0M9QiqqpOzlA3vSBRJneNiMHEY4smb5YT+YBaek//+ksKE5vqQ/3FF59j377/Yv782bj77jvgcDhCes7kFctgmD8bjiuuhDPvopCu0ZwYUBMREbUgJpOAnJz6QaogSIsTv/46AX/8UT+oNRpV0OvrB+DR4KvLh7+WebLsbDfsdgEVFdEanTLJGepolHwAwJ9/SmFiUxnqrVu/RJs2mXjggdlYu3YNRo68HEZjcVDPVzeYrljxEhrdJagFY0BNRETUgkgBdcMAady4WqhUItasqR9syC3zhCiXKMtdPuQsc2UlcOyYyu+CRIC7JUaLt+QjstfNzJTer7/+kq7fWA21KIrYtu0r9OvXH9Onz8Rrr72F3377DQMH9sd3330b0HMlPy8F09UjRsVsMA0woCYiImpRTCaVp3dzXbm5IgYMcGHNmkQ4nd77jUZV1OunASlD7XYLnoWRcvYysAw1d0uMhmjVUOt0QEqK6DdDvX//Phw7VoJ+/S4FAAwZMgyffLIZycnJuPLKYXjrrTeafJ7k55fBME8Kpsuffzlmg2mAATUREVGLIe+S6CtDDUhlHyaTCl9+qfbcJ2Woox9QGwzSc8hlH96Wef4DarmEha3zIitaXT4AqezDG1D7vv727V8BAPr1u8Rz37nnnodNm77C3//eG/feexfmzHkAzrrfAP/HE0wPHxnzwTTAgJqIiKjFsFiA6uqGNdSyQYOcaNPG7elJ7XRKAXi0W+YB3oBa3tylqEgK5gIJqFtKhvrgQaFBDXoss1oFaLViVHYyzMpy4+hRaa4au/62bV+hY8ezcPrp7erdn5aWjjVr3sMdd0zGiy8+j3HjrsSJE8c9j9cLpl/4V8wH0wADaiIiohbDbJb+W24sQ52YCIwd68SmTQkoKRFQUiLA7T5VGWrpVu70ceiQCunp7oDqdw0GQKcTPa+vuUyZkoxp0+JnH+3y8uhkpwEpQ+10Nl5DXVtbi3//ewf69r3E5/kJCQl45JHH8NxzK7Br1zcYNOhS7Nr1LTQrlsZdMA0woCYiiitOp7eVFsUeuSTCVw217Prra+F0Cli7NuGUtcwDpO3DAW/JR1GRCh06BBbMCYL0mpo7Q33okIADB+In9LFYIr/tuEzu9AH4zlD/8MP3qKqqrFfu4cs111yP9es/QXW1A8OHD8Tp8+egf0Yb3NfuDHz06QYcOXI47P7VLUHDDvFERBSzXnwxEc8+q8F//lOFBP4LH3O8AXXjAXKnTm4UFLiwenUi2rWTAhF5m/Jo8tZQS38vKlKhoMAV8PnNvVtiZSVQWqry/FnOuMcyq1VAq1bRuXbdgFqna/j52r79KwiCgD59+vq9VvfuBfjmrnuwff4c7GzfAd+mp+HFl19AzYqlAIDMzCzk5V2EvLzuKCjoib59+0OIdtuaCOM/t0REceSbb9Q4cUIFo1HwBFsUO+SSiKYy1ABw/fU1mDo1GR9+KP03fioy1HIAWlkpoLpa2kVv7NjAnzcnR8RPP6n9HxglR454M9NFRSpccEH05yzayssFZGREK0PtnR9fXT62bfsKF17YDWlp6X6vpTr8F9oveRRtLynE5W+uBRITUV1djX37fsEPP3yPPXu+x48//oDPP/8Moijio482oWfPv0fy5UQdA2oiojjy3/9KAcvhwyq0axd49pBaBpNJ+glfp2v6uCuucGLOHBEffpiI5GQRqanRH1vdLh+HD0u124EsSJTJJR+iiKj3zPZF7qkMxE9AbbUK6NgxOq+jfslH/aC9srISu3fvwp133uP/QqIIw6zpAICKp57z1EwnJSWhW7eL0K3bRQBukx6vKMdff/2Fc889LzIv4hSKn0IiIiKFq6jw9gauGzxQ7PC1S6IvBgMwalQtAKnc41QEqHVLPoqKAu9BLcvOdsNmEzwlI6fa4cPekEdu+Rfror0oUXZyhvrbb7+G0+n0Wz/9/+ydd3gU9dqG79meTQdCQgkkgdCrcCgCwkFBbIgUKVYQwYIKoiAIgmIBFRW76KcIQpASEFGPikho0kvovQQhIYT0ZPt8fwyTQtpudjcF5r6uXAuzO3Vnd5955/k9L4Dul5/R//E/sl+eiiO8Qamv9fcPoGXLVqhU1e/9qX5brKCgoKBQLEeO5H+lFxQPCtWHkpq6FMeIEZKgrgi7B0iNXUBK+cjPoHZezFV2dN65cyp8fERq1nTkRf5VZ0RRqlB7a1Ci3C0Rig5KjIvbgF6vp1On0m0ZQlYmfq9OwtaiFbljnvbGZlYZlG9cBQUFhRuEQ4cku4deLxbyiypUH0pr6nI9HTs66NDBTvv2FWPtUaul+LSsLIGzZ1X4+oqFRFdZVHb78YQEgfBwB5GRYl6FvTqTnQ02m/cGJdasKSIIIj4+Re+AbNy4gU6duuJTUgvFaxhnv4kq8RKZ7390w8TjlYTioVZQUFC4QTh8WEVAgEiTJg4SEqp/Be5mw+GQBbVzFWdBgF9+yaEi7477+opkZcHFiyoiIhwuWU0qu0J9/ryK8HCR4GCRbdsqb3Ckp5C7JHqrQq3VSqLacd3pmJyczOHDB3n11Rmlzq+J34fPN19hemwUto6dvLKNVYnqf4mmoKCgoABIAxJbtLDToIGD8+eVr/fqxtWrAlar8xVqoELFNEjebalCLbjkn4b8KMDKFNQNGjiIjJQ6AJrNlbIZHiM9XTqOQUHeS/MJCSnahXHz5jiA0v3Tdjt+L72Ao1YI2WUI7xsFpUKtoKCgcAPgcEgV6mHDrPj7i6xZo8FmQ8mirkY409SlsvHzE8nMFDh3TkW/fjaX5g0IkCwjlWH5SE+XBGh4uIPQUBFRFDh/XkV0dNGLAs3unRhiFiOkpyGYchFychFMuZArPQq5uQi5OQgmE/Z69TEPHIJp0IM4IiIreJ+k88VbgxJBGphosRS+ANq4cQOBgUG0adOuxPkM332Ndt9eMr76FjGwAiJoqgDKV62CgoLCDcD58wLZ2QItWjgQRclbmZgoUL9+1RVnCoW5fFkSLs5aPioDPz+RY8dUWK2CSwMSQbKo1K4t5u1nRSLfsWnYUKROHen4njkjEB2d/xrNtn/w/WAOug3rcfj54wgNRfQxgo8PosEHsUYNRB8fMPgg+vgg6g1oDuzHd85b+M55C2unLpgGD8XcfwBijZpe36eMDOnRW5YPkLpyyhd6AKIoEhf3N92734ZaXbxtRnXpIr5vz8LSqzfmAYO8tm1VDUVQKygoKNwAyAMSW7a051WuEhJU1K+vZFFXF2Th4orlo6Lx88sXp65aPkC6WCgo0MriwoUERo16mCtXkrn//kE8+ODwcmUUy6k3DRo48i4yz55VgWhDu3Uzxrlz0G3eiKNWLbKmv4Fp5BOIfv5OLVt1IQF97AoMK5biP2kCfq9OwnJ7X0xDhmLp06/4vt0FyMrK5IknHuXy5cvMnPkmPXv+16n1yp9zbwrqAQMK34U4c+Y0Fy4kMG7c+BLn8Zv2CoLNSuacDyoncLySUEx2CgoKCjcAhw+rEASRpk0dNGggCR13ByZeuSKwbl31H7xVXZCtEAXzf6savr752+ZKUxeZ0FCRK4kOVOfPod26Ge36P8Fe/EXfwYMHuPvuOzh16hStWrXiq68+o2fPLvTu3Z0vvviUpKQkp9cr57KHhzuoUUPE38+Bz+b1BPXvR9AD96A+foysN94mZecBcp8b77SYBnDUDyf3+Qmkxm3j6vot5D75NJp9ewh84lFqtorGb+LzCOlpxc6bmnqVwYP7s3HjBtLT0xgy5H4efXQ4Z86cLnO9+ZYPpzfVbTZtkvzTPXv2KvZ53Z//Q//zanImvIwjMqriNqwKoFSoFRQUFG4ADh9WERkp4usL9epJosfdLOpvvtHy4Yc6Tp3Kyms7reA9EhMFatRwoNdX9paUjNzcRacTqVu3ZOEvpKWi2bcX9YUEVAnnUCckoLqQwLcHLxCUdQF1x3wxbr6jL5lf/h9iQGDetLi4vxk58mH8/f1Zs+Z/dOvWiRMnzrF69QqWL1/KjBlTef31afTq1ZsHHxxOv373YCylvWRCggo/P5HgIBH9X3+w2fEebf63A3udumS+8x6mEY8W31/bFQQBe6vWZLdqTfb019Fu2YRhxY8Yli5GdekiGT8sKzSKNCkpiQcfHMCpUyf49tsf+O9/b+errz7jww/fp0ePTjz99HO88MKL+JUg7iuiQn09GzduoF69+kRFNS76ZHY2fq+8hK1JU3KefaHCtqmqoAhqBQUFhRuAQ4fUtG4tVfoMBilRwd0K9cmTKkRRIDlZyBNSCt4jMVGo0gMSgbwLqwYNHJRgoUV1IYGgu+9AnXgJAFGtxlG3Hvb64SREdufzA1E89U4o2kbhaE4cw3fGqwTddTsZi5Zij2rMsmUxjB//LNHRTYiJWUnduvUACAkJ4cknn+bJJ5/m+PFjLF++lBUrfuSpp57Az8+fvn3vJOCaKBdFye8rSgMKOPDHZTpYLjAl+jztMzPpbwhnWq3PeGHHg3jlCkatxnpbL+mvfQf8J7+Ice4ccl6eAkhWlsGD+5OYmMiSJSvyEjNeeGEiQ4eO4M03ZzJv3lyWLl3MtGkzGTJkWJHugenpAkajWGHxzna7nc2b4+jX7x6EYqwcvnPnoE44T9pPv4FOVzEbVYVQBLWCgoJCNUduBT10qDVvWni46HaF+tQpaf7Ll1VERipebG+TlKSq0v5pyLd8REYWv51CWiqBwwYi5OSQvngZtmYtcNSpmxc3s/lHDa8950Pf/2YRFSVi7dUbW4tWBDzxCIF9/8vr99zHrJgf6N79NhYsWJwnkK+nSZOmvPrqDKZMmc4//2xh2bIY1q9fh80mfQYEuwPBakGwWBCsVgQgETgiavkWmKK2k3MVnrQLlFzX9gymx59Au2cXxvdnY2t/C0cioxg8+H6ysrJYvnw1//lP50KvDwurw6effsXjjz/BtGmTee65p1iw4BvefHMOHTr8J+91GRkVW50+eDCe1NRUevToWeQ59eFD+Hz5KbnDH8batVuFbVNVQvFQKygoKFRzjh6VvspbtswXveHh7mVRiyJ57aWTk2+egUWVSWKiaxnUlYF8p6JY/7TJRMCjw1GfPUPG90uw9OmHI7xBoezG4rolWrv1IPmXdTyjUjEr5geGtm3H0piVJYrpgqhUKrp168G82XM59vZ7JNx1L0l6A8lpqVzOzubfyChOj32WTvrfGDgyjYP/phAbu5aQ2g1xOJ6la9dbWLJkETabaxGALiEIZL77IbaWrTk9ZhT97+6D2WwiNnZtETFdkI4dO/Hrr3/xySdfkpCQwF133c64cWPJzs4GvNt2vDg2bpT80z169Cr8hMOB/8vjEQMDyZ4xq8K2p6qhCGoFBQWFao6c8NGiRb7ICQ+XmleUMN6rTBITBXJyJCFdGTFnNxt2u3ScKzMyb/Hihbzxxmv88svPJCUlFvsa2fJRJOHD4cB/3Fh027aS+cmXWLv1KHb+4rolZmdn89jMV5mflspLUY1Ysn8fNV6ZiDOdV9SHDuI79WVqtmlK4BOPoF+zGtstHcmc+zEpew6RunknCRPeYY25H3WiJGtH9+638cEHfwK/YTTWYvz4Z+nWrSPLly/FXt4PTFn4+LD+xZfpnZ2FPjOTNT+upnXrNmXOplKpGDp0BNu27eG55yawbFkMs2e/A0idEr2ZQX09Gzf+TfPmLQgNDS00XbvhL7Q7t5M97fUKiQusqiiWDwUFBYVqzuHDKvz9RcLD839cw8NFbDaBpCSh1MFjJSHbPUAR1BXBlSsCdnvleahTU6/yyisTMRcQsfXrh9Ox43/o0EH6a926Lb6+kmy4vkLtO+NVdGtWkTB5Gpfa3ULa3t0ABAQEEBAQRGBgIDqdLu+CQY7OS05O5pFHHmTfvr3Mnj2XUY8/Qe67b+P7wbtoThwn/dsfEGvXLryxWVkYVq/E8MMCtHt2I+p0mO/tj2nEo1hv7V6km5F8p6bg5yMqSgT68eSTPalbdw2zZ7/Js8+OYd68uUyaNJV7772/iGfZHTZtiuORcU8RWjuU9UmJhH35KZmffuV0rJyfnz/Tp7/Ov/8m8MknH/Pww6NIS4uqsDsaJpOJ7dv/4bHHRhV5zmfR9zhq1sQ0ZFiFbEtVRRHUCgoKCtWcQ4dUtGhhL/TbHB4uCZfz51XUret61e30aUlMaDSiYvmoAOSKbWVZPmJjV2A2m/ntt78QRZHdu3eye/dOdu3ayerVsQDodDoaN25LYGBbYmKy+Pbbq6SmXiXt7BnSUlJIFQQcc96EOW8Wuw4fHx8CAgIRhGA+/zyQuDg/jh8/RkrKFb77bjF33XUPADmvTMPevAX+zz9N8J29yFgYA927oNmzC8MP36NftRJVdha2ps3ImvUOpiHDSq2MFsyglgkNFfHxETl7Vs2oUXfTt28/1q79iXfffZvRox+jSZOmREZGodcb0Ov1GAzSY+H/GzAYDBiNRoxGX3x9pUf5/9KjkX/+2cqYMY8TFdWIZctWE7JoAYZ338Z6S0dMT4xx6X2aNOlV1qxZzdy5c0hPn0+TJhVzR2Pnzu2YTKYi/mnh8mV0v/9K7pNP35QDEQuiCGoFBQWFaowowuHDaoYMsRaaXjCLuksX15d76pQKg0EkMtKhCOoKIL+pS+VYPmJifqB167Z5g946duxUYNsusXv3rjyRnZS0iv37/QkODqam1Up0SgpBDSMxDhxMcI0aBAfXICgoCEEQSE9PJz09nYyM/MfY2GxEMY3U1KvUrl2b+fO/K7Q+APP9A7FHNSLg0eEE3dsXGjUm+OABRKMR0/0DMT38GLaOnZyq8J47J72moKBWqaBhQwdnzwrX/q+if/8HuOee/sTGLmfx4oX8+++/mM0mzGbLtUcTZrMZk8kkpYe4QPv2txATs5IaNWqS8+IkNHt34zf9FWyt22LrVLKP+nqiohoxevSTfPPN1/j4TCYoqKFL21FeNm2KQ61Wc+ut3QtNNyxdjGCzYXr4sQrZjqqMIqgVFBQUqjEJCQJZWQItWxYWYu5mUZ8+rSIy0nGtVbQy3MbbJCVJx7gyKtQHDsQTH7+Pd955r9jnw8LqcM8993HPPfcVmq7dupnABwdg69yVtOU/ldkRUObYMSN6vUhsbG6pr7O1bkvq7xvwn/As2vRUst77CPPAwYj+rnUySUhQERQkFmmAEhHhkLolFkCtVjNkyDCGlGJfEEURq9WKyZRLbq6JnJxscnJyCjzmkJ2dlTdNrVYzbNhD+MvbrVKR+dl8gvv0JGD0o6T+uRHxOl9yaUyd+irff/89mZmvERi4wOn53GHjxr/p0OE/hTOxRRHD4u+xdLkVe3STCtmOqowiqBUUFBSqMfkDEgvbOnx8ICSk/FnUp08LNGniwGjMt38oeI/ERAFBEAkJqXhBvXTpD+h0OgYOHOL0POqjRwh4bAT2iEjSF8Y4LaZBykg/dsy5c0qsXZuMxcsJCjJiSstxeh0FOX9elWeBKkhkpEhcnAqHo1C/lTIRBAGdTodOpyszieT8eYHBg43cfnsO/v75760YFEz6giUE3307AWMeJ33FGpwNlA4LC2PkyGf4/PP3yc5+AWjp/MaXg7S0VPbt28uLL04qNF27ZROaM6fJmDjZq+uvLijfkgoKCgrVGLnleLNmRQVDgwbly6K22aRc60aN5Aq1gIt3uBVcJDFRoGbNimvSIWM2m1mx4kfuvvtegoNrODWP6tJFAocPQjQYSI9ZiejkfDJhYWKh2Dxvk5AgFLJ7yEREOMjNFQoljniaTZs0nD2ryrvwLYi9ZSsy35+H7p8t+L7xmkvLHTp0PFCDuDjX5itITo5zFyhbtmzG4XDkNZ+RMfywAEdgEOb7BpR7G24kFEGtoKCgUI05dEhFRIRYbGvw8HBHuQT1hQsCVqtAVJSDkBAHZrNARoYHNlahRCqrqcvvv/9Kamoqw4c/4tTrheRkAocPRkhPJ33JCiln2kVCQ0UyMwWuxSl7FVGULB8FEz5k5Og/OW/dG8THS8u+erV40W4eMozcJ8Zg/Ooz9KtWOL1cuz0ImMrRo3+yefNGl7fr559X06hRPe6++w5WrVqB1Wot8bWbNm3AaPTllls65k0TrqagX7sG8+AH3W/ZfoOgCGoFBQWFaszhw+oidg+Z8HAHFy4IOFwc5yZbPKKiRGrXloSIMjDRu1RWU5clSxZRr179ItXHIogi+qWLqdG9I+qTx8n4dhF2J3KUiyM0VDohvVkZlklOFsjNFWjYsDjLhzRNHpjoDeLjpcp0WlrJ68h6/W2s/+mM34vPoz51wqnlZmQIwLPUrFmPN9+c4dIgyU2b4nj66dE0a9aCK1eSGTt2FB06tGLu3Dlcvny5yOs3btzArbd2Q1cgxcOw4kcEi4Xchx93er03OoqgVlBQUKimZGfDmTNFByTKhIeLWK2u39KWM6hlywegDEz0MpKgrtiEj3//vcDff//F0KEjUKuLWhJkVKdPETi4PwHPP409uimpf23G2qt3udcrZ21XxDl1/rx07hfnoa5XT0SjEb1WobbZJEsWlFyhBkCnI+PrBaDXETD6ccgtfbAmSF0SwcDjj7/Knj27+fXXtU5t04ED+3nssRFERTVi1aq1bNu2l8WLl9G8eQvmzHmLW25pwbhxY9m/fy8gnSMnT54ofMElihh++B7rLR2wt2zl1HpvBtw6i3r37s19993H/fffz8CBAwFIS0tj5MiR9O3bl5EjR5Keng5Io2LffPNN+vTpw3333cehQ4fc33oFBQWFm5ijR1WIolCoQ2JBCmZRu8Lp01KjmFq18gfJKc1dvIfNJlVSK7qpy7JlMYiiyLBhDxX/AqsVn3lzqdGrK5p9e8l87yPS1vwPe9Nmbq1X3k85KtCb5GdQFz22Go003VuC+sQJFbm50j6mppa+r4669cj89Cs0hw7gN31Kmcu+Jq0YNGg40dFNePvt18tsn3769CmGDh1IUFAQP/64iqCgYFQqFX369OPHH1exZcsuHn74MX755Wf69OnJ3XffwXvvSV0ZC7Yb1+zageboEUxKdboQbp9F33//PT/99BOxsVLw+/z58+natSt//PEHXbt2Zf78+QBs3LiRs2fP8scffzBr1ixmzpzp7qoVFBQUbmoOH5aqii1blmT5kKPzXK9QN2rkQBBQLB8VQHKygChWrOXD4XCwZMkiune/jYiIyCLPa3bvJPiO2/B763UsffqRumUnpsdGuRaHUQJyJb4iLB/yxWT9+sVfdBYXnecpZP+00SiWKagBLHfcSc6zL+Cz8Fv0q1eW+lrJ8gE1a6qZOnUGJ04cZ9mymBJfn5SUxNChD+Bw2Pnxx1XUqVO3yGuio5swe/Zc9u8/wptvzubKlWSWLFlErVohNG/eIu91hh++RzT6Yh4wsMx9upnw+Fn0119/MWCANOJzwIABrFu3rtB0QRBo164dGRkZxXp1FBQUFBSc49AhFX5+YrEDriBfRFy44HqFOipKmjc4WLotrlSovUdlNHXZtm0r586dZfjwhwtNF7Iy8Z36MkF334GQlkr6wqVk/N9CHGF1PLbu4GDQ6cQKEtQCtWo5ih20C5KP+swZlVdSbA4cUGM0irRrZy/d8lGA7KmvYe3YCb8Xn0d1+lSJr5MsH+DvD3fffS8dOnTk3XffJrcYu0hGRjrDhw8iOfkyixcvJ7qMzOiAgEDGjHmGbdv2EhOzgu++W5zXhl3IzMDwUyymgYMRC2ZSK7ifQ/3EE08gCAJDhw5l6NChpKSkULt2bQBCQkJISUkBpKujsLCwvPnCwsJISkrKe21xqNUCQUFG1GoVQUFGdzf1hkA5FpWHcuzzUY6FRGUfh+PHVbRuDTVqFL8NQUFShTkpSUtQkHNf92azlPLx6KPqvH2rXRvS0kpfRmUfC2/z228QGQnN3HM7FEtmpvQYHa0nKCh/ujeP6YoVMQQEBPDQQ8MwGqV1CH+tQ/3kaPj3XxzPPIvj9TcwBgTgjS2oUweuXnX+vCzvsbh0SUVkJCXO26KFQGamgM1mJCTE5cWXyuHDKtq2hTp1VBw4IDi//UuXIvynAzWeGoVt46YiGd9qtQqTSXvNliUtc/bs2fTpcwcxMQt48cWJea81mUwMGfIwR48eZvXqn7j99sKtw8ti0KDCkXiqZYsQcnLQPj220j/vVe07xy1BHROIec5TAAAgAElEQVQTQ2hoKCkpKYwcOZKoqKhCzwuCgOBEW9CSsNtF0tJyCAoyklbOQPcbDeVYVB7Ksc9HORYSlXkcRBHi4/0YONBKWpq5xNfVr2/k5EmRtLSyBzqBJNIdDl/q1TORliZ5MmvVMnLhQunLuNHPicce86NvXxuffmry+LJPn9YCanx9c0lLyy+VeuuYZmZmsHLlCoYMGY7FAhZLDuTmUnP4MOwhtcn85U+prbcD8NJ7WquWkYQE58/L8h6LU6d8adPGTlpa8e9baKgaMLJ/v4mOHT13h8DhgL17/Rg2zIrVCikpGue3P6AWuo+/JPCRodjGTyBr9txCTwcFGbl82UFgoDpvmW3bduK//72d2bPfYdCg4QQGBmG32xk9+jHi4uL4/POv6dSph9vnU9D8rxFbtCK1cUuvnRtOb4sXPh8hIeWvurtl+Qi91iqzZs2a9OnTh/j4eGrWrJln5bh8+TI1atTIe21iYmLevImJiXnzKygoKCi4xoULAhkZJQ9IlHE1i1pO+JAtHyBVuW9mD3VWlhR7dumSd45BYqKASiUNAq0IVq+OJTc3lxEj8u0e+rU/oUpLI2v2XElMe5mwMIfXLR8Oh/Q5Ka6pi0xkpHTMPT0w8cwZgexsgTZt7NSoIXmoXYmvtNx5FzlPjcPn26/R/by6yPPp6RAQUPh8mTZtJmlpaXz22ceIosjkyRP55Zc1vPHG2wwePNTdXUITvw9t/D5yH3kM3CiW3qiU+wzKyckhKysr799btmwhOjqa3r17s3q19OavXr2a22+/HSBvuiiK7Nu3D39//1LtHgoKCgoKJSPHcZU0IFGmfn3RpSzqU6ekH8rCgtpxU3uoZY+zt1IpkpIEQkJESkmu8yhLliyiWbPmtG/fIW+aYdECbJFRWLv1qJBtCA0VSUrybmxeYqLUoKikMQYADRo4EATR4wMT5fzp1q0dBAeLOBxCnrXHWbKnzcTaoSP+48ehOnO60HMZGQKBgYX3q3XrtjzwwCDmz/+cV1+dxMKF3/LccxN46qlxbu2LjGHR94gGA+ZBD3pkeTca5T6DUlJSGDFiBP3792fIkCH07NmT2267jTFjxrBlyxb69u3L1q1bGTNmDAA9e/YkPDycPn36MH36dGbMmOGxnVBQUFC42ZBbGTdvXnaF2mIRnBbEZ86oqFXLQWBg/rSQEKlC7WqDmBuFixeln0pvtctOTKy4LonHjh1l9+6dDB/+SJ4lU338GLptW6UYNA+keDhDaKhIerrgTORyuZETPkqrUOv1Uh61pyvU8fFqdDqRpk0lQQ1lZFEXh05HxlffgUpFwJiR0gCHa6SnFxXUAJMnT8NisfDNN18xfPjDTJs2053dyCc7G33scsz3DUAMCvbMMm8wyu2hDg8PZ82aNUWmBwcH8/333xeZLgiCIqIVFBQUPMThwyoiIkpOL5CRxURCgnOxbKdOqQpVp0GyfNjtAqmpAjVrVnw3v8pGtnpkZgpkZVHmMXeVxESB+vUr5rjGxPyARqMpZAEwLFqAqNViKimP2gsUjM6LiPDOvstNXUoT1JCf9OFJ4uNVtGjhQKuFGjWk/UtNFfIsJs7iaNCQzHmfE/j4CHzfmE72W+8CkqBu2bLo66OiGjFlymucPXuGOXPmljqOTX36JPaGkThza0T/82pUmRmYHnncpe2/mVBaXykoKChUQw4fVpXYcrwg+VnUzn3dS5F5hX/087sl3py2j0uX8o+dN3y/SUlCXjtub2K1Wlm2LIa+fe8iRI60MJkwLFuC+a57ET0dc1EKcnMXb9o+5HO+rIuViAgH58557n0VRSkyr3Vr6fMpV6idyaIuDsvd95Iz5mmMX3+J7pefgZIr1ADPPTeeuXPnodGUUDMVRYzvz6ZGl1sI7tUV3do1lJUb6LNoAbbG0Vg7dy3XPtwMKIJaQUFBoZqRkyMJ37IGJEJ+FrUzgjorS7IfNGpUeLk3e7fEixfz99vTtg+LBa5cqRjLx7p1f3DlSnLhwYi//owqNbXCK4/5gtp759T58ypCQx3Xp84VISJC5MoVFRkZnllvQoJAWppAmzbS50iuULts+ShA9muzsLa/Bf8XnsGxL57MzJIFdamIIsZ3ZuH77tuY+90NDgeBox4mqG8vtOv/LFZYq48eQbtzO6aHlMGIpaEIagUFBYVqxrFjKhwOgZYtyxbUvr5Qs6Yj7/Z3aci3vYtaPqT/36xJH5cuqfDx8U67bPkipSIEdUzMImrXDqV37z550wyLFmBvGIG1h2v5xO5SEYI6IUEotuX49URGSue3pwYmygMS27TxTIUakPzU8xcg+vig7dWDgax0XVCLIr4zXsX3o/fJfWQkGQuWkLpxOxkff4Eq9SpBwwYReP9daLdtLTSbYfH3kiVo6Ijyb/9NgCKoFRQUFKoZ8oBEZywfINk+nKlQnz5dkqC+uSvUly4JeeLI09F5FdUlMSkpkT///J2hQ0fkWQHUp06g27KJ3Ecer7DBiDI1aohotaLXklNAqlCHh5d9XCMiPCuoDxxQoVaLeQOGAwNBEJxrP14ajoYRpP0Zh7lJK1YymL6bZ+L0SGGHA78pL2H88lNyRo8l6/2PpPdcrcY87CGubt1N5pwPUJ85TVD/fgQOfQDNvj3XLEExkiWoVi23tv9GRxHUCgoKNw0ff6yjd2+jV9oMVySHD6vw9RVp2NC5HXE2i1rOoJYrdjL+/qDXi1y+fHP+ZFy8KNCkiQOj0fNRb7KFRK7Yeotly5Zit9sLtRo3LPoeUaPBNLTiBiPKqFRyF0/vnFM2G/z7r0DDhs4Lak8NTIyPV9O0ab7VRK2WRLW7ghrAEVaHg5+s5/8YRaff5xDw2HCEzDK8Kg4Hfi+9gM+3X5PzzPPSwMbrrRs6HaaRo7m6fR9ZM95Es38vwX17EXRvX8kS9PBjbm/7jc7N+e2ooKBwU7JqlYaDB9WcOVO9K62HD6to3tzhdFExPFzk33+FMi8kTp9WUbeuA+N13XwF4eZt7mI2Sx7nOnVE6tTxfEVVtjx40/IhiiIxMYvo1KkLjRtHSxPNZgw/LsbS7x7ESmqyFhrqvQr1xYsCdnvpGdQyfn6SrckT3wuiCPv3q/L80zLBwe5XqGVSc/SM5hv2PzkX3bo/COrXG/WpE8W/2G7H//mn8fnhe7InvET2jFml+6CNRnKffZ6rO+PJnjQV9elT2KIaYb2tl0e2/UZGEdQKCgo3BZcvC3lWiR07KqiDhhcQRcny4azdA6QKtclUdhb1qVNFByTK1K4t3pSWD1nw1q3rICzM4XHLR1KSgEYjejWO8J9/tnDy5AlGjHgkb5r+t7WoUlIku0clERrqvYZB8h2ZsiLzZCIiHB6xfCQlCVy5osqzCMnUqCG6NSixIGlpAAIpw8aSvmINqqspBN3ZG91ffxR+odWK/zOjMSyLIfuVaeRMec3pQYWifwA5L73C1X2HSft1XYVbgqojyhFSUFC4Kdi4URLRKpXItm3VV1BfvChcy6B13nNbMIu6NM6cEYrYPWRCQm7ObolyU5c6dcRrFVXPWz5CQ0Wv6RWz2cwrr0ykbt169O//QN50w6IF2Bs0xNrzv95ZsRN4s1uiPAjXGQ81SC3IPWH52L9fWsb1gtqTFer0dGk5QUEi1m49SP19A/YGDQkYMQSfjz+QrrotFgLGjMSwaiVZr80i58VJ5VqXGBCIWKOmR7b7RkcR1AoKCjcFcXEaatRwcPvtdrZtK3dPq0pHbjnuTGSejJzDW5qP+upVuHq15Aq13C3xZkOuSMuWj6Sksq0zrpCYKHjVP/3RR+9z9OgR3n//I/yudaRRnz6JblMcpocerdTKY1iYJDJNJs8v+/x5FSqVSL16zh3biAgHly6p3O7cGB+vRhDEIhe8nhTUUoWavJQPR4OGpK39A/P9D+D35kz8x44kYNTD6H9ZQ9Zbc8gd94JH1qtQOoqgVlBQuOERRYiLU9Ojh52uXW2cPq3yalyXN3E14QPyq3SlCWo54aM0y0dKioDN5vRqbwhkQS1bPsxmgdRUzy3fm01dDh48wLx5cxkyZBh33HFn3nTDDwsR1WpMBQYoVgbyhYQ37nycPy/53nU6514v35k5d849WXTggIroaAe+voWne9ryIQhi4Y6dRiOZX31H1rTX0f+0Cv0f/yPzvY/IffJpj6xToWwUQa2goFApWK0wY4aekye9L2yPHVORmKiiZ087XbpIQrS6+qgPH1bRoIEDf3/n5/Hzgxo1Ss+iLikyTyYkREQUBVJSqueFSHm5dElKVPH3zx846EnbR2Kid5q62Gw2JkwYR1BQMLNmvZP/hMWCYekPWPrehSOsjsfX6wryhYQ3Lm6lDGrnL1RkQe2u7SM+Xk3r1kXXGxQkkp0tYLG4tXgA0tMhIKCYmwuCQO7zE0hf9QvpS5ZjemyU+ytTcBpFUCsoeBCbrcwOrgrX+PtvNV98oeO553ycjlItL3Fxknju2dNGmzYOfHyqr4/60CEVLVs6X52WCQ8XuXCh9Aq1Wi2W2AjjZs2ivnhRoE4dB4JQUFB75hiYTFKUmjcE9eeff8L+/XuZM2cuNQp4YHW//4rqyhVMjz7u8XW6ityBMznZ81JEyqB2/rjmZ1GX/71NTha4eLHogETwUHOXa6SmUmpTF+ut3bEUuCOhUDFUXyOhgkIVY9cuFcOHG8nIAKMRfH1FfH3lR+nfRqP02KePjf79b7J759cRG6tFrRbZvVvN4sVaHnnE6rV1xcVpaNTIkfcD26GDvVoK6txcKYmjPOdOeLiDY8dKF9Th4SXfIr9ZuyVevChZByC/+YqnBHV+ZJ5nryhPnjzBe++9zT339Oe++wYUes5n4XfY64dj6XW7R9dZHrx1kWY2S1YdVyrUwcFSFdmdCvWBA/KAxKLrlduPp6a675lPSxMICPByFULBZZQKtYKCB8jJgXHjfPD3F3nxRQuPPGLlzjtttG9vp359Bzqd9CV44oSKv/5SM3asgYMHb96PX3Y2/O9/GkaMsNK1q41Zs/RcueIdoWY2w9atanr2zBehnTvbOXRIRWamV1bpNY4fl1qOuzIgUUbulljSHZTSIvMgv5p4s1WoExMF6taV9l0WQp6yfHijqYvD4WD8+Gfx8fFh9uy5hZ5TnT2DLu5vaTCiuvIvKGvVkivUnj2npMx11wQ1SLYP9wS1dExbtfJuhTo9XRL/ClULpUKtoOAB3nlHz+nTKlauzKFHj9Jvx6emQrduvrz8soFffsm5KeM9f/9dQ06OwODBNoKDRXr3NjJrlp558zw/3H/XLjU5OQK9euUL6i5d7DgcAjt3qund23X7RGVx6JB0spTP8iFlUScnC3mVQRlRlAR1ly4l3yXIF9Q3zwlrt0uCuk4dSZgZDJIX3fMVas+Jo2+/nc+OHdv45JMvCb2uYYvP4oWIKhWmAnnUlYlWKwlNTwvq8+flDGrXjmtEhIM9e8p/oREfryIiwkFgYNHn5Aq1JwYmpqXhdJdUhYrj5vlmVFDwEv/8o2b+fC2jRlnKFNMg3Vp8/XUzu3er+f57bQVsYdUjNlZL3boOOne206yZg6eeshATo/WKDSMuTo1aLdKtW/5706GDHbVaZPv2yq/SucLhw2qMRpGICNd/TPOTPor+oF++LJCTI5Q4IBGkgY2+vjdXdF5ystRtT7Z8gGe7+8nL8ZTl49y5s7z55kx6976DBx8cXvhJqxXDkkVY+vbDUaeuR9bnCUJCHB4/p1xt6iITGekgIaH8Awfj49XF+qfB8xXq4kS7QuWiCGoFBTfIyoLnnjPQsKHI9Olmp+cbPNhGjx423npLX23j28rL1auwfr2aBx6w5VXnJ060UK+eg8mT9Vg9bKXesEFDhw72QqkYfn7QurWj2vmoDx1yreV4QWT/eHHReadOlR6ZJxMScnN1SywYmScTFua55i6JiQI6nUhwsPvLEkWRiRNfQBBUvP/+PITrOuLpfv8NVfJlTJXYGbE4vJFvfv681H2y4IWQM0REOHA4BC5ccH170tKkyL3i/NOQL6g9VaEOCFAq1FUNRVArKLjBG2/oSUgQ+PhjU5Hc0dIQBHjvPRNmM0yfrvfeBlZB1q7VYrMJDByYr5x9feGtt8wcOaLm6689V7W/elXqXNarV9GqUefOdvbsUWN2/jqoUhFFqULtSv50QUrLoi4rMk+mdm3PVxOrMgW7JMrUqeNJy4cUmedkN+hSWbJkERs3/s2MGbOoXz+8yPM+i77DXrcelt593F+ZB5EEtWelSEKCinr1RJdt4vKdn/K0ID94UFpZ69bFfz6NRtDp3G/uYrVCVpZQasqHQuWgCGoFhXISF6dmwQIdY8da87KNXSEqSmT8eAurV2tZv756VUrdITZWQ3S0nVatCou3u+6y0bevjXff1XPxomcEy+bNGkRRKDQgUaZLFztms8C+fdXj2GdkSLeLy6oil4S/v1QlK87yceqUCr2+7K5ytWvfnBXqgoI6LEw6BnYPWO891SXx0qWLvPbaVG69tTuPPjqyyPPqkyfQblhfZQYjFsQb59S5cyqX7R7gXhZ1fLw0T3EZ1CAVUYKDxbwuh+UlI0M6VoqgrnooglpBoRxkZMD48QYaN7YzZUr5S5zjxllo3NjOpEkGcnI8uIFVlIsXBf75R83AgbYiVTlBgLfeMiGKMG2aZ6r2cXFqAgJE2rcv+iPXubOkiKqLjzopSfq6dmcAW/36jhIq1AIREY4ytZZk+bh5fjYuXZIsGTVrFvZQOxyCRyr1nuiSKIoikyZNwGaz8sEHn6C6zg+k2bmdoPvvQvTzlwR1FSMkRGp44snvP1ebusjUri1iNJYvOi8+Xk29eo685JLi8ES3xPR06VER1FWPm+ebUUHBg8yYoefSJYFPPjHh41P+5ej18P77Zs6fV/Hhh072yK3GrF4tVYwfeKB4o3TDhiITJlhYu1bLX3+5J3RFUfJPd+tmQ1NMnlGtWiLR0fZqI6jlKt71CR2uEB7uKLZCffq0qky7h7zutDSh2thk3OXiRcmSUVCjyokfnrB9eKJL4vLlS/n999+YPHkaUVGNCj2nX7qYoAfuQfT1Je3XdTjq1nNrXd4gJMSz+ea5uVISjStNXWQEQfJRl8fyceBA8Q1dChIc7L7lQ6lQV10UQa2g4CLr1qlZvFjHuHEWOnRwf3T+rbfaGTbMymef6Thy5Mb+SMbGamnf3k5UVMk/Bk8/LVXtX3nFQG5u+dd15oxAQkLx/mmZLl3s7Nih9nqnRk8gD151xyJQXBa13S7d4nbGSiKLeW9lhruLKErV9gULtIwaZaBlS1+3PPmXLuVH5sl4qltidrYkjsojqC9fvsxXX31Gnz49GTduLB06dGTs2GfyX2Cz4Tt9CgHPP421862k/v439qbN3Npeb5HfLdEz55TcDbQ8FWqQs6hd25asLDh5suQBiTKeENTp6bKgdmsxCl7gxv71VlDwMGlp8OKLBpo3t/Pyy+XMViqGGTPMBASIvPyyvlqIu/Jw4oSK+Hh1ocGIxaHXw5w5Zs6dU/Hxx+Wv2m/YIJWli/NPy3TqZCc9XfDqhUxSkoDNA00x8wV1+U+QBg0c5OYKhQTxv/8KWCxCqRc5MnI1sSr5qJOTBWJjNUyYoKdjR1+6dPFj0iQDe/eqsViEvPOgPFy8qMpr6iIjC+BLl9w7Z1x9P7Ozs1m5chnDhg2kbdumTJ8+BVEUeeONt1m6NBb1Nb+OkJZK4IjBGL/6jJwnnyL9x1jE4Bpubas38XT78fPnpeNango1SAMTz51TueSRP3RIjSgKZVaoPWH5kCvUSspH1UNp7KKg4AJTpxq4ckXghx9y0XswnKNmTZGZM808/7yP19twVxaxsRoEQWTAgLLVZY8edgYOtPLJJzoGD7bSqJHrPx4bNqhp0MBBZGTJ88qDSbdtU9OypeevZNLToXNnX2bMMDNypHvvaVKSCh8fsVD8n6vISR8XLgh5QsbZyDzIr1BXdtLH1aswb56euDg1hw9LQjIwUKR7dxvjxlno2dNGZKTIk08a8rrXuUpy8hUuXtxNgwbxTJ58gJMnTxAd3YSRI59CpWrvdtylM554u91OXNzfLF++lF9++Zns7Czq1w9n3LjxDB48lKbXVZ3VJ44T8MhQ1AnnyfzgE0wPP+bWNlYEnq5Qy01dGjYsf4XaYhG4dEmgfn3nvnfkAYnOVqhFkXInu6SlKZaPqooiqBUUnOSnn2DFCi0vvWQu84uzPAwdamPpUhtvvKHnzjttbnllqxqiKNk9une3O21ZeP11M3/+qWHyZAPLl+e69ANks8GWLRoGDLCWOl+DBiJ16jjYvl3NE094/iJm506pS+PJk+5X35KSpA6H7kSsFcyilgdqOhuZB/mCWhqYWHkdJqdPNxAbq+HWW+28+qqZ226z0aZN0UGVjRs7WLtWg9lMiRfAKSkpHD9+lKNHj3Ds2BGOHTvKsWNHuHLlCgAbN8KePf40atSYH374nm+//Rqd7k727HkGh6NnkUGAzpLf1OX6rpUiBw7sZ+XK5fz000ouXrxIQEAgDzwwiMGDh9Kly63FrlP31x/4jxkFeh1pK9di69K1XNtV0Xi6/fj581JiTXm/PwsmfdSv79w5Hh+vpnZtR5nfbUFBIjabQFYW5b4wVgYlVl0UQa2g4AQpKQLPPquidWs7EyZ4zupRECmb2kyvXkZmzNDzxReeb8NdWezfr+LMGRXPP+/8sQsNFZk61cyUKQbWrNFw//3O+yb27FGRmSmU6p8G6Zh36WLnn3/UblWNSkJuHOOJAWyXL7ufCCFXqOXb4iAJal9f5wSILH6ut3yIokhubi4pKSnk5GSTm5tLTk42OTk5BR5zMJlMiKJ47c9R4N8F/yAoKIjQ0DDCwuoQFhZGcHCNvEYlp08LrFypYexYK6+/XvroyOhoqVHH6dMCgYEXOH78GMePH+X48eMcP36UEyeOkZKSkvd6Pz9/mjZtSt++dxEY2IIvvmjPe+9F8eijoQiCQHJyMgsXfsvcuf/Hhg330717NE88MZahQ0fg5+fn3Jtwjeu7JJ49e4bY2OWsXLmMEyeOo9VqufPOfsyaNZs+ffphMBiKX5Ao4vP5J/i+MR17i1akL4zBEd7ApW2pTPR6SWh6ykaUkCBVlst5nUNEhPx+qJzqfAtShdqZIovcfjw1VcDfv3yCOCNDQK0WXep7oFAxKIJaQcEJZszQk5oKy5aZ0HqxW3h0tIPnnrPwwQd6hg2z0rNn5VUBPcnKlVp0OpF77nGtCvz441ZiYrS8+qqebt3spUZSFSQuTrKXdO9etgjv3NnOqlVazp8XaNjQs1UfOUHEXb8tSCK2aVP3BHVAgFTZKhidd+qUlPDhzMWEwSDNn5hoZceO7WzbtoWtWzezY8d2srIy3dq20tDpdISGhhEaGkZiYj0EoR6CEMDs2TZsNhtWqxWbzXrtUfq/1WrlyhUrcJE77zyCyZS/fUFBQTRp0oy77rqX6OimNG3alKZNm1O3br084b5unZovvjDSsmU2giAd95CQECZOnMzevVM4eDAWf/+PmDLlJd5++w1GjHiEJ54YQ0REpFP7lJiowmC4zPLlC4mNXc6uXTsA6Nq1G2PHPst9991PZGR90tJKzpMTUlLwm/oShlUrMd97PxmffEl1VFqebD9+/rwq78KxPNStK6LTiU4PTMzNhePHVdx1V9nFArkjZmqqQIMG5fuuSU8XCAry/MW/gvsoglpBoQzOnBFYsULDCy+ItGjh/RGD48dbWLVKy6RJBjZsyHYrlq8qYLdLcXm3324jKMi1edVq+OgjE/36GRk/3sCiRc5ZPzZs0NCuncOpls4FfdQNG3pg9OA1TCbYu1cS1J5oL5+U5HzFrDSk6Lx8QX36tIp27YouV33yBL7vzEJ95BApTz/HP5FRbP1nCxbLNhYu3MaCBVIES7NmzRk06EGaNGmEIGgwGn0xGo0YjUZ8fIzX/u2Lj48PBoMBQVChUqkQBOHaH3n/lq0MaWlpJCYmkpR0icTESyQmJpKYeIkzZxK5cOEoOt16Pv9cuvet1WrRarVoNFq0Ws21Ry0ajQa1WguE07Llwzz4YDRNmjQlOropISEhRVpzX09xXRJl6tbVsmvXQ/z++wB27drB119/wf/931fMn/853bv3pFatmmi1OvR6PVqtFp1Oj06ny/tTqzXExm7FZPqTqVPttGjRimnTXmfgwMHFdjksgiiiXxaD34ypCBkZZL8yjZzxL1Husmwl48n24wkJZQ8OLA21Whq862wW9ZEjKux2ocSGLgXxRPtxWVArVD0UQa2gUAaff65Do4EXXqgYz5rBILUlHzzYyOuv65k9u3qH/m7dqiYpScWgQeXbj1atHMyYYebVVw18+622TK9zRoZk+XDWXtKsmYPAQJHt29UMHeo5Qb1vn5QyER1t5+xZlVuWktxc6YfUE131wsMdeb5pi0WyfwwcmC8GVBf/xfj+bC4vWcTXag0/azTsnPg8FiThazS2pXbt0bzzThc6d+5KrVq1AAgKMpZaTXWFgIBAGjRoWGT6888bOHhQw86d2dSqZcsT5qXRrp0vUVF2Ro50zUJ18aKASlW8FSYsTOTqVRUmE3Ts2ImOHTsxc+ZFFiz4hj/++J2LFy9gsViwWCxYrRbMZunRYsk/J/X6BtStO5GYmIE0b97C6e1Snz6J38svotu0AWvHTmS+Pw97i5Yu7VtVIyRELPfg0YJkZUFKiqrc1V+ZyEjR6Szq+Hhpu50R8QUtH+UlI0NQIvOqKIqgVlAohaQkgaVLtQwdaqVuXbXbbWOd5bbb7Iwda+Grr3R07Wp3yT9c1Vi1SoOvr0ifPuXfh9Gjrfz9t4aZM/V07Wov9U7Bli0a7HbBabuMSiXF58l+Z08h2z3697cxd66elBTBacvK9cj+Unc91CANxIyLkwT++fMCDocgWT5Sr5I95y3WLvyOGGVZaJ4AACAASURBVLudLaIIDgvtWrTkmRo16b1zG91zctgY1ovp9pncc0/FVkPPnBFYvlzD6NHWaxcWzr1fjRs78pJMXCExURoEWpzFS86mTkrKtwnVqVOXKVNeY8qU10pcpiiKWK1WLBYLd9xRmzZtHDRv7qTQt1gwfvoRxg/fQ9TpyXz3Q0yPjqy2VemCeKpCLd95KW8GtUxkpIMtW7ROXQQfOKAiOFh0KhFErlC7I6jT0pQKdVVFEdQKCqXw1VdarFZ49lkLULHei+nTzezapWbCBAOtW2c7lRNc1TCb4eeftdx9t80t64ogwLx5Jnr1MvLUUwZ+/z2nxOVt2KDGaBTp2NH5276dO9v58089ycn5cXLusm2bmiZN8sV/YmL5BbWzTV0yMzOYNWsGf/75O5GRUTRp0pQmTZrRrFlzmjRpRq1atahf30FOjsDVqwKnTqkwkEjm0md4aPzP/GWzYQeaN2rM1KEjGDBgUJ4nWLiaguGt17lv0Tz+IyxDv/otzPcPrDAz50cf6dFqYdw41wYFN27sYPly58RRQYrLoJaR34fERBUNGzp/ngmCkGf7SEpSERrq3Lya7dvwf+l5NMeOYur/ANlvzcERGub0eqs6tWuLZGYK5Obi1veEPNjWXUEdESF9RqSBwKV/5uLj1bRubXfq3PKE5SMjA8KdcAUpVDzV/9JWQcFLpKfDggU6+ve3VYqY1eng669z0Wph9Ggft7oGVhbr12tITxcYNMj9SLqQEJFPPzVx9KiamTNLDgGPi9PQrZsdnQs9Ybp0karnnmpDbrdLkXmdO9vzUhzc8VHLmcWlJXGsW/c7PXp0ZuHC72jdui25ubksX/4jr7wykQED7qZFiyiaN4/khx/6AE/z4dyP+PzlWxGpw5TNqziu1fL8w48RF7eNuH/2MH78S4UG2Ik1apI192O+HhnHJTGMgDEjCRwyAPXJE+XeL2c5c0Zg2TINjz5qddn2Eh3tIDNTcDlF4tIlIe+9ux53uyVmZUF2thOpLWlp+E18geD7+iJkZ5P+w49kfvP9DSWmwXNZ1HIGdXmbusjImexjxxpYvVqKXSwOi0XyUDvr2dZowN/fvW6J6elCnjBXqFooFWoFhRL47jsdWVkCzz3nnZg8Z6hfX+TTT3N56CEj06bpmTu3evmpY2M11Krl8MhgOoD//tfO009b+OILHb162bnrrsI2koQEgdOnVYwa5dp71q6dA4NB8lHfe6/79pojR1RkZAjXBHXBznrlOw75lo+iP6RXr6bw6quTWblyGc2aNefbbxdxyy0dAclikJh4KS9b+fie3RzcsRcjO5j/jYVQ4H6hDk/MmUy7x0aW6UcGMLfrSCd2cHrSx4R/+TrBPbuQ+8zz8MokUHvnLs68eTq0Wsr1WWzcWBJHJ086XxEGqUJd0nkrWz4SEwWwWtHs34t26xa0/2xGc/IEtiZNsbVqja1VW2yt2+BoGFGoPF5sBrUoIly+jOboYTRHDqE+egTNX3+gSU4m56lxZE+aCi5G81UX5A6cycnlT78ASVAbjWK57wTJ9Ool5ZsvXKhlzBgfgoNFhgyxMmKEtZDd7NgxFRaL4FJfAnfbj2dkCAQFKYK6KqIIagWFYsjJgfnztdx+u82p0dvepE8fO+PGmfn0Uz233mpn0KDq4afOyoI//tAwbJjVo1GDU6ea2bxZzfjxBtq1yy6UwhAXJ7cbd0246nRwyy12j1Wo5eV06WIvYA8o/4/o5ctS9mzNmvn7Kooia9asYsqUl0hLS2PixMmMH/8S+gIdTNT/XiBiyyait25m4JbNqM+fBSCFII436kWsdgx/G++n/ePO3/6oXVvEgZpDPcfg+2h//N6YjnHeXJg3l+AWrbB074G1221Yu96KGOREzEoZnD0rsGyZlpEjXa9OQ76gPnFCRbduzp0XWVmQmSkUm/CBxUKtE3uZpt7BoPl/U+udfxBysgGwNW2GrU071CePo1u/DuFa/2qHf8A1gd0aW+u25Frb0gXocmAPvnsOoDl6BM2RQ6gKZGI7aoUg/qcj6ROnYGvTzuX9rk54rkItEB7uXARkaQgCvPCCheees7Bxo5rFi7V8952W+fN13HKLnYcesvLAA1YOHJA7JDr/fVOjRvkFtdkMubmC0tSliqIIagWFYoiJ0XLliooXXqgazVWmTLGwc6eaiRMNtGmTQ3R05Yp8Z/jtNw25uQIDB3r2AkCvh6++yuWOO3wZN87AsmW5eR3yNmxQU6eOgyZNChwfUUSVlIgmfh+aA/EIOTlYbuuFtXNXKVLlGl262Jk3T0dWlvuFwO3b1dSt6yA8XOpsWKuWwy1BnZQkebvl8WdJSYlMmvQiv/22lrZt27N8+RpatmwFgProEXy++ARdAQHtCA7G2rU7uWOfxnJrDxr178Sgnnb+9z8N3V2MGCvYLVH8T20yP/2K3LHPELD5bxzr1uOz8DuM879AFARsrdpg7dYDa/ceWLvcihjgejzBvHk61OryVadBir0zGkWXulXKueF16jjAYkGzdw+6rZvQbt2Mdud2hJwcZgHn0ltiGv4Qllu7Y+3SDTEkJH8hublojh1BcyAezcF4NAfi8Vm8ECEnh97APwBfgGj0xda8Oea77sXerDm25i2xNWuBGBJCUJARm4eSU6oy+YLavQ6cCQnuJ3wURKWSqtW9etlJSZEGxS5ZomXiRAPTp+sJCRHx9xeJiHB+ne5UqDMypPmUQYlVE0VQKyhch9UKn32mo1MnW15GcWWj1cL8+SZ69zYyerSB337LwWis7K0qndhYLeHhDv7zH88fw8aNRd56y8yECQY++0zH889bsNth00Y1j3Q/gX7tDjQH4tHG70MTvx/VlWQAREEAjQbjJx8iGo1Ybu2OpfcdWHvfQedOTbDb9ezapS6zw2JpiKI0ILFr1/yBSqGhIomJ5R+yIg1gkzoJLl26mNdem4rZbOK112bx1FPPotFIX+XajRsIePwhUKmwdr8tT0Dbm7colAZRv4FUsb14UUWjRq7524urJtpat8XRoyvpT48Hsxntnl1oN29Eu2UTPt/Ox/jlp4gqFfboJoh+foh6A+j1iHoDoo8B9Abp3wY96A3Y69bD3rwFZ/1a8OOP4Tz+uLVIi+5icThQnzmFZv8+NPv2ojkYj+jjwye+bUja1ALNgcbYGjcpfeSb2Yxl3R6msZ3BX/xFrYk7EK4NYLC1aEXuQ49i7dqdBz+9nWyfWqx6p4Tqvo8Ptna3YGt3S/40ux31mdOsm3uYH1YG8FlcJIamDW6IpA538FT78fPnVXTq5P54jeKoWVPkqaesjB1rZfduFUuWaImN1dKjh92lty84WMyLrXSV/Lbj5ZpdwcsoglpB4TpiYzVcuKBizpyqUZ2WqVNH5LPPTAwf7sOUKQbmzata21eQK1cENmxQ88wzFre1gpCRjvrsGYT0dIT0dFQZ0uOTGek0iswm7a0MxHUpGDJSOJ12hKC16bAWRI0Ge9PmWO7oi7VNW2yt22Fr2QoEAd3WTejWr0P791/4r/sDgAcaRPAZd5G5+HaEjl0R/fzLtb3nzwskJqro3Dm/ohoWJpZaob58+TJ//PEbOTnZmEymvDbdJlMuubm57NplRafLpU+f88TH76Nz56589NGnNGoUnbcM/Yof8X/hGeyNo0mPWYmjbr0S1xce7uDvv6Wv/6go1+521KwpIgiltIrW67F27Ya1azd4eQrk5qLdtQPtlk1oDh9CMJvAbEbISEdlugymXASzGcF0bbopF8EqiaJ2wDnq4H+wOerpzbE3b4GtWXNsTZqBry+qM6fR7t8rCej9e6WLp8wMAESDAVuLlqhSUnjkynq0yVa4HUnYR0Rib9YCW7Nm2Ju1wBEUjHbndqkCvXsnvUwmbkMg19ya3EdHYu3aHWuXrog1aubtps9PBk4ddPHkVquxN45mfa1WrPfVYmie5dr8NyhyB053BHV6ulTBdTfhoywEATp2dNCxo5m33jLn3R1zFncsH3I6iJxnrVC1UAS1gkIBHA749FMdzZvbueOOqlGdLkjv3nYmTJBak3ftamPYsKrpp/75ZykL2mW7R24umoPxaPftQbNnN5p9e9CcOlnsS0VB4G7/QP5VBZG8JwhdSADrGM79M1vg060ttqbNC1k6CmLp0w9Ln34AqM6cRvf3X+j+XsfjFxZi/OkLxF+1mO/tT+5T47C17+DSLsh51gXvbtSp4+DAgeK/bo8fP8bQoQ/w778XCk2XOwsaDD5kZfkSEGBAp/PhnXfeZ+TI0XldBRFFfD75EL83Z2Lp1oOMBYsRA0u/JxweLmI2Sz/OrgpqrVYS1U6nZvj4YO3RE2uPns69XhRRXbrI1Y1H+Hr8Se5vdIBOuQfRLPw2r1IMklVC9i6Lej22lq0wD34QW9v2WNu2x96kKbJ5/4M5AmvmnmPD57sxnjqM5thR1EcPo/v91zyfs6hSYWvVhtzHR7PiSi9eWNGb/X9qSixmh4WJ/PmnUK6GPYmJgnMV95uIkBCHy0ksBfFUwocrlCfiLzhYJCNDwGaTUj9c4d9/pX2sX9/19Sp4H0VQKygU4PffNRw7puaLL5xrcV0ZvPyyhe3b1UyebKBduxyaNat6fuq1azVER5fegAVAffwY2h3b0OzdjWbvHjRHDyPYJBFuD6uDrd0tmB8cjq1JM8TgYBwBgYiB1/78/EGlYv82NQMG+CBehJatHAx+JgdXZLwjMgpTZBSmUU8ycwqcXLiTlY+uwLhsMYZVK7F26kLOU+Ow3HUPzpSjduxQExgoFnpfQkOl6pvVSqEBmjt3bufhhx9Eo9Hy889/EB0djY+P8VqLbukEtNmgXj0/Ro2yMHnydT5iux2/qS/j8903mB4YRObHX0om8zIID8/ftshI188fT7aKLoIg4Khbj1k7o/hRo+Wh5dmk1RXBbkd17iyaY0el8+RKMvYWrbC2aYe9WXNKG/naqJmaw7TkUPMIWg5+IP8Jkwn1yROoUq5ga9c+70Jk/ct6VDU0+Phkl7jMsDApqzgrC/xdvJkhCeqq97mtTNw9p2RB7e0KtbsUbO7iaub9hQvyPkrFH4WqhSKoFRSuIYrw8cc6GjZ0VOnOhGo1fPllvp/6f//LqVJpWpmZUpV2zBhr8Rclooh2yyaMH81Ft/FvAByBQdjatSdn3HjJd9r+Fhx16jq1vi5d7Lz4ooX339e7nO5xPR1u1fD5//Vm06DO/9/encc3VWb/A//cm6VJF7rQtCkFEQFBZBVlX4Yqi0ApsiggIIg6OiL4ZVx+oIKiKCDjwrgAo6IiggIiAuMIoqgoBUWgFIusQtqm6ULTPet9fn9cbpsuabO0zdLzfr14gbVpbp6kNyfnnucc3PbMs1B9ugnqDesQef9M2K+7HhUP/h2mGbPAIlo5/RmpqTL061e9rlKrZWCMQ14eVzksZP/+/+GBB+6DVpuAzz7bWa3ns6P8fA6M1TFgoqICrR6eh5Cv96D80YUoe+4Fl2txpSyeVit49NrRaBhyc5uu7len47BliwKzZlmrhqvIZBBu6AjLDR3FDzdukPoKnz/P4+abHSIRlQr27j1qbYPLyeHr7vDhoKoXNY+ICPeiG72ed2vwUEug0TCcPu15l53MTPFk4/hh0R9JAbXR6ElALXb4aNUKzTa1l7iuZe+EIMTBzz/LcOyYDI8+anH7Ulxzi49nWLfOhHPneDz7bMMZyeZ08KAcViuHUaNqfChhDMpvvkbU2DsQNWk8ZGf+QOnSF1GQehwFZy+jaNsulC9ZCsvY8S4H05JFiyx49lkz5s3zrmd4//5ikJOaKgMLj0DFQ//A1SPHUfTBJxASEhD+3GLE9O6GsKVLwF+5XOv2+fkczp2ToX8/G1BWBi4vD3xWJhK04s+V6qi3bt2M2bOn48Ybu2LPnv1Og2mgqge141AXrqAAUZOTofzfXpS8vBply150a2OblMVzt9xDEhfXhBlqiJ09eB5YsKBxesDfcIMAjmM4d861NcrO5pxOSZRU9Rd3bx2Ki8Vsqj9eWfIlbzPUOh2PsDCGaO87NTYpb6YlZmbyaNuWXjf+ys/DBkKaz9q1Smg0AqZNa5pd4o1t6FA75s2z4sMPFVi2zOw3byTffitHZCSr6u5hsyHkq50IffM1yDNOw35de5Ssfh2mafc6rXF2l1zeOMFXXBxDx44CjhyRY/78a68DmQyW8RNgGT8B8uPHoF7/NtTvrYN6wztg/fsjymwBV14Orrwc4YXlKEUZwlaUAyuqfu647gPRCR8hOzsRhw69jpdeWobhw0dg48ZPEN7A5seqsePiGyn/1yVETp8MWaYOxe99DEtyituPU8riSZlbd0nBjyf1ww3JzBSz0/fea0ViYuPUw4aGill5V1vn6fUceveuP4NcbbiLG06dErOw7vQubgk0GrG22GTy7LSg0zVOD+qmJm0oLCx0/7aZmdLgGz9/kC0UBdSEADh5ksfBg3I8+6y5sWK8ZjFtmhXvvafE3r0KzJzp+w8CggB8+60MI0bYILebodqyBaH/fh2yvy7B1qUrit/eAPNdU9zfjdOMBgywYe9eBQShdtLX1qcvStZ9gLKlL0L9/gaojv8KFhkFISERLDQUv54Ox+9/RuD++QrwEWFgYaHgysoR8ebrOIEemL28L7746xdMmjQFa9eug9KF+ejS2PH4eAb5yeOInD4FsFlh3L4btv4DPHqMkZHAzJkWTJzoWWlTXJyAigrP6ocb8uab4po0VnZa0qmT4FJAbTYD+fl8gxlq6YqBu+0QT56UhoFQptGRtJ75+RzatnX/g5ROxzfrhkRPOdZQuyszk8egQVYAjTOAijQu/31XI6QZrV2rRKtWDHPn+m7MuCd63GxD9/ZF+O8XMsycZhMLrN1N0djt4s43q1UcGehCkFcXLj8fV/b+iUl5f+EfhWmI6bcLMn02rL37oPTDT2EZMzYg+u3272/H5s1K/Pknj5tuqjvoEdokouy5F6CICkWRw+CN/xsTCuVtDPc+U703cVHKJMy4bQx+/OsXLIiLw3MLnwBzcZ0NBg69cRxdVqyG+qsdELQJKNr6Neydb/T4MXIc8Nprno+xrxruwiEiovGCmJ9/luGTT8TaaU+Cqvp06iQgNbXuD0qOpIxzmzb1B7zh4UBERP3tEOuSliZDYqLg9XjsYOM4ftzTgPq223yfVGiIlKF2t+SjqEic3imWfFBA7Y8ooCYt3vnzHPbskWPhQkujZ9saXUUFFCd+h+LIYciPpkLx61GcKjIClwFcKztmCgUgl4PJFYBcBsgVYHI5YLeDs1kB27W/rVbAZgPHqr95CdHRELQJEOLiIcRrxT9aLezxWghxWrDWrcEV5UH9+0nIzp6F7OwZyM/9Cb6gALEAbgNg/zUc9ttuQ8mb78A6fETj1wW4obDwKtLTT+HUqTSkp6chPz8P8fFaJCS0qfxbq9VCq01AXFw8BgwQj/XgQZnTgLouZWVAWhqP+fOrfygrLS3BnH8uwI/IQvJ19+C1kn3gRw5D+T+fRvn8x513pxAEKPd/g/s+ehcrcRDs6zBUzJmH8oVPgMXFebwejcFxsl3Hjo1TuqDXc3jwQRU6dBDw3HOeB/vOdOokduXQ67l6S0mkKYmutLVLSHB/AmZaGk/lHnWQXlOetM4rLgaKiji/35AIiB/E5HL3e1FLHT4a+4MmaTwUUJMW7623lAgJAR580P+yG1xeHhRHUyv/yNNOVA69sHXpCvOEidCHd8KGd2UYe0cF+vYyi23nrFbAbhO/12oD7Ney13K5GHDL5IDiWqDt8DXObAJvyAFvMIDPzYHiwnnwhpzK+3QUDkCIioK9y00wj02G/cYueHJjL+jCb8LG/TENBtEmkwlXrxbAZmu47IDjOCgUCshkcigUcsjlCigU4h+pHzNjDFlZmTh1Kg2nTp1EevoppKenITNTV/lzpOD57Nk/YTDkwG6317ofjSYOoaFtsGJFJL7/Xg61WgWVKgQqlRohISEICVFd6w+tQliYCkZjMUwmMy5eNMNms+HXX0swd64JZrMJJpMJly//hezsLLRv/wGKr5+FwneuIHzJkwh75UUod+9CyZvvwN6jZ9VBlJVB9fkWqDe8A/mF87Co2mJN3ErM+XlGg/2lm4tjhroxWCzAvHlqlJdz2Lmzokk+2HbuXNXpIzHReUCbnS1lqBsOXNydgFlaCly4wGPyZP/tIuQr3owf1+mavwe1pzjOs/HjUhcT2pTovyigJi2WTsfhiy8U2LZNgdmzrW63MPIWYwwVFRUwGgthNBrFv/+6hJJjv6LkdDrKLl2AprAQbQC0USgQf3MPxD74CLhBg2G9rT9YdAwAIALAVwdDcbCEYffTTsYge8hutyM/LxeGs3/CcPYMDBcvIi87C4rYaNijNZBHRUGpVEIuV8BkUmLdxXykpPyEPXt52GxW5OfnIT8/D3l5+ZX/Fv/ko+TaRDtv8TwPhUIBjuNgMonTIzmOQ6dOndGvX3/MnfsgevToie7deyI2Nrb6Y8vPh8Ggh16vR06OHnp9NnJy9MjIMOD48QqcP1+CiAhxYqHZbL4WJJthMlVUC8bVajUYUwNQQacLQUGBqnIoS+fON+LVV1/Hxx8n4+JFDkyjQcl/PoQ5ZRIinl6E6NF/Q/mCRTDNmAXVJx9B/dH74AsLYe3dB8XrP8D49dOhCpfjvsjGfW690dgB9dKl4sj3996rQJcuTRMwdOpUFVDX115R6trRUMkHIGaxDx92PaA+dUoGxjj06kUZ6prqGmnvqkBpmSfxLKCmDLW/o4CatChGI/DVVwps3y5Haqr48h840IbHH2/62un8/Hx8/fUe7N79JTIy/oDRWAiz2cVL21YrcOJ34MTviP38U8THJyAhIQEJCW0QHh6B0FA7jhwR8OCDZVAoLLBarbBYLLDZpL9tldldhUIJpVIJhUJRGQwrlQooFEqYzSbk5ORUBpm5uYZaWdyG7Nol/pHwPI+YmNbQaDSIjdWgd+8+iI0V/926daxLG/MEQYDNZoPVaoXNZoXVarv2txV2uw1Wqw12ux3t21+P7t17oFu37ggLC6v3Z8pkMsTHxyM+Ph49e/au9v8YA1JS1Lh8mcc335TVuVHVZrMhPFyJigo7OI7D5MlqFBZy+O678trfDGDfPoaff64KvizjJ+Dq4CEIf/b/Iey11Qh7bTUYx8EyNhnlf39U3HDIcdC/pMSARiqraCwxMQwyWeO0zvv8czk++ECJRx6xYMKEpsvcxsUxREQ03DpPrxfbr7mSJddqBRgM8gbrsiVpabQh0RmVSqxJ9+Q1JWWoAyXY9DSgVipZsyd+iOsooCZBz2QC9u+XY/t2OQ4ckMNi4dC5sx2LF5sxaZIV7ds33QkqNzcX//3vbuze/SV+/vknCIKADtoEjI6MRJzVilizGTEAIkNUaNXtZrS6rT8ihg1HeL8BCIuMQmHhVeTk5CAnJ9shi6qv/O+TJ0+grKwUMpkSgBLff69AdLRjoCwGznK5HBaLBcXFFlitNlitFlgsNQNvKxQKeWVt8Y03dkVCQgLi4xOg1YoBvFabAI0mDjEx4cjLK4LVKv0MKxYu5JGebseOHUWw2ayQyWSIjdUgOjoaMhcmDPoTjhMnUk6eHIrNmxWYN692yYtcLodKpYLJVA6rFTh2TIbp052XDWm1DEVFHMrLxTZuAMCiY1Dy9gaYJk+F4thvME25B0KHGypvw5i4KVFqmecveB6IjXVj/LgT6ek8nnxShUGDbE1SN+2I48Syj4Y6fYg9qF1b74QEBquVw9WrnEubDE+elEGrFar1FCdVPO1vrtPxUKkCJ9iMjma4fNm9DdqZmWLtfwDs626xKKAmQevPP3msW6fA7t0KFBdziIsTMHeuFVOnWtGjR9P1K83J0WPv3q+we/cuHD78Mxhj6HhDRywaORr3nDuHvhfPA0VGWPsNgGXIMFgHD4WtV586N6fFxLRGTExrdOt2c4P3O3JkKHge+OabujOkjYnn+Wv1xOJQGbMZOHIkHJMnW9GlS9MGRs1lyBA7Bgyw4c03lbj3Xmu97RTT03mUl3MYMMB5JlkaNW0wcOjQofobvzVpJKxJI2vdxmgELJY6piT6gbg476YlGo3A3LlqREYybNhgapZOih07Cvj55/o/3On1DU9JlEjPS06OawF1WhqPXr3868ORP9FoBA8DarH7hb/3oJbExDCcOOF+hprqp/0bBdQkKBUXA1OmqFFSwmH8eBsmT7Zi6FB7k75pp6b+gldeeRGpqb+AMYauXW/CE/9YgClmM275aifk33wNW5euKH3t3zBNvhtQqxv1/idOtOKFF1S4dKl2wNbUUlNlKCvjMHJk8Gy24jjgqacsmDTJeZZakpoqBmnSpMW6OI6q7tDBtRIOxx7U/sabyXaCADz6qBrZ2Ry+/LK82TK2nTsL2LZNgdJSOB25rtdzGDbMtcBF+pCUk8Ohe/f6v7esDDh3jkdKSmC15mxOGg1DRob7H9IyMwOjB7UkOlrsQ+3OYKTMTA5JSRRQ+zO6eECC0ooVIcjL47BzZzneesuEESOaLpjOydHjkUcewIQJY3DlymU89dQS/LJlO34fMAirPtiAfu+tg9DtZhi3foHCH4/ANPO+Rg+mASAlRQxmd+1y0oatCX37rRwqFcPQof5V6+utwYPtGDhQzFJf2+9YpyNHZGjfXqi31VpVQO16EFo1JdH/ggUxQ+1ZQP3660rs3y/H8uVm3HZb8wUJ0sbEixfrfuuz2cQ1l6YgNkTKZLvS6SM9XdyQSC3znBM/pLkflkgZ6kARHc1gNovlX64wm8UP14H0GFsiCqhJ0Pn1Vx4ffihmFPv0aboTkMViwdtvr8XAgX2xZ88uLFr0FI7+6028cOJ3DJgxFapPN8F01xRcPXgYRZ9/CWvSHU3aj7ltW4Z+/WzYubP5Lzzt2yfH4MH2ytrgYCHVUufkxWcrFwAAIABJREFU8Pjkk7o/qDAGHD0qq7fcA/BsVHXNseP+JC5OqBw/7o4DB2RYvVqJqVOtuP/+5m1VKQXUzjYm5uVxsNs5l0s+qqYlNvycShsSqeTDOY1G3Gfg6l5tQMz8FxTw10ZyB4aq8eOunQukVo6B0sWkpaKAmgQVqxV44gkVEhIYFi9uulreH374HiNGDMILLzyLIf0G4Og/HsOqPbvQZtpkKH47ivJFT6Hg9z9Q+sbbsLtQ/9xY7rrLhowMGf78s/l+tS9c4HDpEo877giecg9HQ4bYMWiQ8yz1+fM88vP5ess9AKBVK0CtZpWDQ1whZYD9cRObRiNuyDMaXb/N5cscHnlEjW7dBLz6qqnZa147dBDA8847fbjTMg8Qh4rGxgqVt6vPyZMyxMXVfxWjpZM2Febnu/7CqGonFzjBZlSUewG19BjrG0hEfI8CahJU3n1XiYwMGV55xey0RtIbmZk6zJs3G1OnpsBWWoovhgzD14cPoefra8AiIlDyxtso+P0PlD/9jE+m2Y0fbwPPM3z5ZfNlqffvF+8rmOqna3rySQsMhrqz1EeOiPXTAwbU//g5TizdkLLOrjAYeISGsiZ5LXurqhe1a28jFRXA/ferwRjwwQcVPrmaERICtG/PcOFC3cecnS1+3dUMNSCW8ki17vU5dYo2JDYkLq5q/LirAq0HNeB+hpqGugQGCqhJ0Lh0icOaNUqMHWvFnXc2bnBnNpvxyisvY/Cgvvj2f3uxPFaDP/TZSDlxHKZp9+Lqdz/D+PV3MM2Y1ST10a6Kj2cYPNiOL79UuH0p3lP798vRtas9oC65umvw4KosdUWN+SqpqTLExgro2LHxR1Xn5vpnhw/A/eEu776rxKlTMrzzTkWzb5p11KmT0GCG2t2AuqHntLxc7DrUowfVT9fHk+EuV66Iz2UgnX+io93PUHMcc2l6J/EdCqiDTEkJsHu3HC5Mc/YbWVkctmyR4+GHVejePQyTJ6tx9ap7P4Mx4KmnVJDLgVdeabxSD5vNhq2bP8agW27GsmVLMc5iwRmrFf+vXTtYX38LBafOonT167B379Fo9+mtiRNtuHCBR3p60/96l5QAhw/Lgrbcw5GzLPWRIzL062d3qXxBq3Wv5MMfe1BLpODHlYBaEIBPP1Vg2DAbRo70bVDZqZOAixd5CHUsq17PQalkaN3anYC64ZKP06d5CAJHGeoGVL2mXP8d0enE58wfy6KckTLUV6+6HlDHxTFc61JK/BQF1H7AYoE4ktjL80FqqgwjRoRh3jw1Fi1S1fmG4Q+MRmDvXjmefjoEAweGoU+fcCxcqMaPP4qByZEjMqSkhLpUlyjZsUOOH36Q45lnzG5ll5wRiovx36VLMKJLeyz4v/mIz8vFfrUaH8+ai4gDP8H4zUGY7p0NNDCNzxfGjbNCLmfNsjnx4EE5bDYOo0YFf+Zt8GA7Bg+2Ye3aqix1djZw+TLf4IZEiVTy4ervusHA+3GG2vXL84cOyXDlCo97723eTYh16dxZgMnEVV5Gd5SdzUOrZW7Vdmu1DPn5HKz1PLS0NLEsiEaO18+TDHVmJh9wA0/cz1BzATMFsiULoJdgcGFM3PX9zDMh6NkzDAMGhOPuu9U4c8b9p8RiAV56SYmUFDV4Hpg1y4KtWxVYtiyk2S77N6S0FFi5UokxY0LRtWs45s5V47PPFOjQQcDy5SYcPFiG06fL8MEHJmzdWoGsLB7jx4fiwoWGTziFhcDSpSHo29eOOXM8f8PmDTkI+egDHB41HHd2boc5696CvKwMWwcNwf73N2F4dg5KX30dth69PL6P5hATA/ztb3bs2tX0ZR/798sRFcVw660tI1B44gkxS71pk5ilPnRIfH02tCFRkpAgoKKCQ3Gxa/cnZqj95Je4hshIQKl0rXXep58qEBXFGr0UyxNSp4+6Jibq9a5PSZRotQyMcfUGgWlpYllQY3zYD2ZqNRAe7l5/c50u8NrJKZVAWJjr48fFPtuB9RhbIhrs0sxyczns2CHH1q0KZGTIoFSKbzJdu1qxbp0SI0aEYs4cK556yozo6IZ/3tmzPB55RIVTp2S4914LXnzRjLAwQKUC1q9XIjqaYdEi3w4SKCkBpk0LxbFjPG691Y5FiywYNsyOW26xQ6ms/f1Dhtjx5ZflmDZNjeTkUGzZUlHvpdIXXgiB0chh27YKuDPhmisogDw9DYrff4Ny39c4fOw3PAPgEIAOrVph3f0PIeWfT0MWEgIrAISFAsamn0LYGCZOtGL+fPW1NW+aE7EgAN9+K0NSkq1Zptz5A8cs9axZVvzyCxAaytCjh6uDQMSASq/nERlZ/23KyoDSUs5vL2VznJhRbOjyvHRFatas+qdNNhfH1nlJSdU/COn1PG65xb0Ph9JwFzEYr/u5OnmSR8+egTPJz5fcHRik03E+LyPyREwMc6nkQxDEssixY/3zPECqtJC3Qd8ym8U+vZ99psCBAzLY7Rz69rVj9WoTJk60IipK/L45c6xYvVqJjRsV2LFDgaefNuO++6x1BiviTnkFXnghBKGhDB9+WIGxY6uyPy++aIbRyGHlyhBERrJ6p7w1pZIS4J57QnH8OI///MeE5GTXMlQ9ewrYvbscd98dirvuCsXHH1dgyJDaJ81ffpHh00+VeOwxM26+2UmAwhj4y39BfioN8tNpkKefgjz9FGTZWbABOAZgaUQE9gHQxmqw+qnFmDFjNpR1RfsB4s47bQgJYfjySwVuvbVp2geePCm2i7vjjuAYNe6qJ5+0YOLEUGzapMChQ+LvsqsfKByHu3TtWv/3VrXM89/MVFxcw8HPjh0KmM0cZszwfbkHALRuzRAdzWplqBkTg2J3s8jVh7vUfq4qKsQNiaNH04REV0j9zV1hMon11oFYDhEVxWA0Nvw48/I4WCyBNbimpaKAugmVlwOvvabEpk1KFBZy0GoF/OMfFtxzjw033lj7l6N1a4ZVq8Qg+rnnQrB4sQoffaTAiy+aMXx4VTBpMHBYuFCF776TIynJhjffNNW6LMzzwBtvmFBSAixerEJkJMOUKc17uVUKpk+c4LFhg+vBtKRjR4Y9e8px991qTJumxvr1JowbV/UzzGbgiSdCcN11Av75z2tvVoyBv3IZ8mO/Ar8dRcnxY8jOyEBWeRl0AC4D0EVE4IpCCV1EK+SUlkJgAmIUCjz//ArMnfsA1D7s0tFYIiKAO+6wYdcuOV54wexW5t5V+/bJwfMMSUm+v4zfnAYNsmPIEBveeEOJggLgiSdcz445jqpuiD+PHZfExbE6a5Edbd6sQM+ednTv7h8BAceJWeqaAfXVqxzMZtenJEqk58fZc5qRwcNu51y+itHSaTQMZ8+6VvqYlRV4LfMk0dGuZaipZV7goIC6iRw9ymPBAjUuXuQxYYIVM2ZYMXy43aXApls3Adu3V+Drr+VYtiwEU6eGYswYK55/3ozLl4FHHglFeTmHlStNmDvX6vQyokIBbNhgwvTpHB57TIVWrSqabfOYYzC9fr37wbQkIYHhq6/KMWNGKObNU+Ff/zLjzjtzMHPmPTh3LhfFRVZEhZXhlpvMsFmtsNpssAJwdm+qEBXaaOKQmNgOwxIT0aZNItq3vx7jx09AREQrjx+vP5o40Ya9exVITZVh8ODGf96//VaOW2+1Iyam0X+033vySQtSUsRGyq5uSAQcg6+GAwYpQ+3fAbWA3393/jaSlsYjPV2GlSvrmdvuA506CThwoPrJWJpG526GOjaWQS533jrv5EnakOgOjYbh559dC6illnnt2vnv74gzMTGscmBLfaoG1wTeY2xpKKBuZBUVwMqVIVi3ToG2bRl27CjH0KHun0g5Dhg71obbb7dh/XolXn9dicGD5bDbOfTsace771agc+eGP7GqVMCmTRWYNCkUDzygxmefVWDgwKY9sZeUAHffHYqTJ8XM9Pjx3mUwo6OB7dvLMW+eGv/3fyrk6eTofrUMCUWFaI0iKMoABQBZVBRk8QmQtWkDvm078PEJiIyJRmJiOyQmJiIxsR1iYmLAtZBCxjvusCE0VOz20dgBtV4vBgrPPNOyyj0kAwfaMXSoDYcPy9yquQ0NBSIjG+5bDDiOHfffN1KNhqGggIPdyRJs3qyASsUwebJ/lHtIOnUSsGWLAsXF4gRLoCrD7O6mRJ4XnyNnH5LS0njExAgUELlIoxE361ksqHOPjSMp2AzUDLUrmxIDcXBNS0UBdSP67TceCxaocP68DPfdZ8GyZd5P6wsJARYssOCee6z417+UaNtWjocfLm/wROMoPBzYsqUCEyaoMXOmGjt3lqNnz6b55SwuFjPTJ0+KNdOOJRreCAsDPv64AgsWqLD+NRUOyEKQIx+CPg/3gXJoX9j63AIW5cIuzhYkLAwYM8aGPXvkeOUVMxS1h/x57H//E0/yLaH/tDNr15qQna12u3Oiq8NdDAYOCgWr7FnrjzQaBkHgUFDAoXXr6v+vokKsnx43zobISN8cnzOdO4ufAM6f53HLLeK50JMpiZL6hrukpcloQ6IbHMePNzTIRKfjIJOxgBznHh3NYDQCdjvqvXKdmckjIoJVfvAj/qvZ2+b9+OOPGD16NEaOHIkNGzY09903CZMJWL5cifHjQ2Eycdi2rRyvvtq4o6/j4xlWrzZj6VLmVjAtad2aYdu2CkRGMkybpsb58w2f3e12sd2dq5oqmJYolcA775gwcV4r9LYfw5k128AtfQrWEbdTMO3ExIlWXL3K46efGq41stlQby9dR//9L4fERAHdurXcrEliIsPIke7frr5spiODQRzm4M+BWH3TEvfulaO4mPOL3tM1OXb6kOj1HHjeswEh8fF1f0gym4EzZ3j07EnlHq5ypxe1Tif2oA7ELkMxMWK7xaKi+r8vMzPw2gK2VM36MrTb7Vi+fDk2btyI+Ph4TJkyBUlJSejUqVNzHkaj+v13MSt99qwMs2ZZ8PzzZkRE+Pqo6tamDcO2beVITg7F1KmhWLPGhJISDrm50h/e4d8c8vM5CAKHdu0E9O1rr/zTo4dQa2JTUwfTEp4HXn7ZjH/8wxKQdXPNbcQIO1q1Ert91GwRZjBwOHZMhmPHeBw7JsOJEzLIZMDUqVbMnm11GiybzcCBA8DkyTa/Dvb8lVbLnI6+dpSb678t8yT1BT+ffqpA+/YCBg3yv2CyfXux7vnCBceAWhyi40lwlpBQd91vRgYPq5UmJLrDnYFBOl3gdr9wHO5S31WozEyO3usCRLMG1GlpaWjfvj3atWsHABg3bhwOHDgQkAG12Qy8+qoSb72lhFbLsHVrea2AxR917Mjw2WcVmDgxFNOnh1Z+XaEQMzNxcQyJiQx9+tih0TCo1UB6Oo/ffpPhyy/FmgGlUuy7e8stYoB9000CFi1S4eRJHu+9Z6rWvq8pcFxgbkLxhZAQYNw4sexjxgwZTp7krwXRMuh0YgCgUDB07y5gxgwrCgs5bN6swAcfKNGvnw2zZ1sxYYKtWv/gw4dlKC3lMHJkyy338EZCggCDQQ5BQL3T3QwGDtdd59/BghT81MxQX7rE4dAhORYvNvvlBDuFAujQQaj2wSY72/2WeRKtlqGoiEN5uVgnL5E2JFKG2nXuZKgzM3mP9ij5g+rTEusLqHn06+d/V3lIbc0aUBsMBmi12sr/jo+PR1pamtPvl8k4REWFQibjERUV6vT7mtuJE8DcuTxOn+YwZ46AV19liIwMafiGjaAx1mLoUODECQHnzgFarfgnOhoO2UYOQM0SAYbsbDuOHgWOHOHw6688Nm/m8Z//iPUncjnD1q0CJkxQAgjc/s318bfXoatmzgS2bOEwYYJ47Nddx9C/P8OCBQL692fo3RvXAmbxOS8oELBpE4cNG2SYP1+OpUsZZs9mmDePoUsX4KefOKhUDOPHh1QLHloiT14THTpwsNs5WCyhcDgd1pKXx2PwYM6vX3M33ij+XVISUnm+BoCdO8XyiYcekiMqyj+vx3ftyuP8+arnz2Dg0bUrPFrvDh3Ek2d5eSjatKn6+p9/coiOZujZU+3R1ZxAPed4QyppLCkJQVRU1XtJzbWwWMQynU6dZAG5RtddJ/5tsagqZ1HUVFwMFBVx6NxZjqioqvfklvi6qIu/rYN/numusdsZjMZyREWFwugHE+psNuDf/1ZizRpxAuHmzRUYOdIOxsRpYM2hsdYiIgK45Zaq/26ojgsQMy9/+5v4BxDXIyODx/HjMnTrZsettwrNtg6+4C+vQ3f17QusWaNAbCxD3772Wl0jTCbxj0QmA+bMAe67Dzh0SIaPP1bgrbfkeOMNHkOG2HD+PIcRIwCLpRyWFj6rwpPXRKtWcgBqnD1rgkpVdwbaagXy8iIQFWWB0ejfixwaGo4rV2yw22UwGsthtwMffRSGpCQ7wsIq/PaccP31SnzzjRL5+eWQy4HMzHAMHWqF0eh+55rISBmAUJw7Z0ZsbFXG9NdfQ9G9u4CiogqPjjFQzzneCgsTX1OOz0XNtbh0iQNj4YiLM8FoDLyrZXI5ByAcOp3F6fFnZPAAwhAba672PS31dVFTU6yDRuN5zW6zBtTx8fHIycmp/G+DwYD4+PjmPASPXbjAXRvlLENKihWrVplaZP9dR3I50KOHQAML/BzPA7Nnu3/JkOOAoUPtGDrUDoOBw9atCmzapEBODo8JE+g595Q0OCQnh0PPnnV/j3S5259b5knE8eNV6dfvv5dBr+exYoV/t1Ts3FmAxcLhyhUOGg1DaSnncbcIxwmYEotFDIgeesi/PxD5I1fGjwd6f2apbrq+1nlSy7zERDrfBoJmrW7r0aMH/vrrL+h0OlgsFuzduxdJSUnNeQhuEwTg/fcVSEoKw4ULPNavr8B//kPBNGlZ4uMZFi604OjRMhw4UIY5cwLzTcwfSMGXXu/89FvVg9r/30hrjh/fvFmB2FgBo0b5d9awY0dxbc+f5yufC3d7UEukCZh6fdU6/PknD4uFa7IWpcHMlYBapwvs/sytWgE8X38vammfC+0ZCgzNmqGWy+VYunQpHnjgAdjtdkyePBmdO3duzkNwS1aWOOL7xx/FEd9vvGEKyH6XhDQWnhevSjTFKPOWQqNh4Lj6h7sEwlAXiUYj4OJF8Y0/L4/DN9/I8eCDVo/aezYnqXXe+fM8lErx3w31PXamVSsgNLR6O0TakOi5uLjao+Fr0ul48Dzz+DnzNZ5vePx4VhZX2TCA+L9mr6EePnw4hg8f3tx36xbGgG3b5FiyRAWbDXj1VRNmz3Y+4psQQlylUIhBtRQ01yU3VwwmAuGNNC6OITVV7FSwbZscNhuHGTP8vytBdDQQGysGbtLld6kcx10cJ374cXxOT57k0aoVQ4cO/v8c+huNhuHw4YYy1Dy0Ws/mMviLhqYlZmbyaNOG+WWnHFKbX29K9JVly0Kwbp0S/fvbsHatiU6IhJBGpdWyBks+OI5VthDzZ3FxDFev8rBY7Pj0UwX69rWjS5fAuAzfubPYOk+qw/XmCqRWK1Qr+Th1SoYePeyUiPGARiO+pqxWOJ3wKvZnDozXmTNRUQ3VUPMB/xhbEvrcU4f27QWsWGHCl19WUDBNCGl09Y2qBsSAunVr1qjj4puKFPTv2QOcPSvzy8mIznTqJODCBR7Z2Rxatxaq9Vt3V0JCVcmH1QqcPs1T/bSHHMePO6PT8QG7IVESE9NQhpoL+MfYklCGug7z5gXOGwIhJPBotQJ+/9356TcQpiRKpONcuZJHaCjDxImBc/7s1ElAfj6PP/6QeTzURSKVfDAmbkg0mzn06kX1055wHO5S1/Nis4mDePx98FFDoqMZTp+uO69psYhdY6jDR+CgDDUhhDQzrZYhP5+H2UlnOYOBD4gNiUDVtMQTJzikpNgQHu7jA3JD587isR8/znsdUGu1AioqOBQVAWlp4lsrBdSe0WjqHz+u14vDkQI9e1tfDbVez4GxwC9raUkooCaEkGYm1erWHNktMRi4gAmoHeu8A2EzoiOpdZ7dznm8IVEiBeQ5OTzS0mQID6cNiZ6Srno4C6ilHtSBHmzGxDCUl3PVBmtJAr3PdktEATUhhDQzx+EuNQmCGEhImV9/JwXUN97I0K9fYGVkr7uOQakUj9/b9muOw11OnhQ3JFJ3Bs9Irymp201NV64Edg9qSXS08+EuUp/ttm0D+zG2JPTrTgghzUzKPjv2LZYUFnKwWgMnQ61WA6NH27BkCQu4jhYyWVWW2tsMtTSEJyuLxx9/0IZEb4SFiX29G8pQJyYGxu+IM1K7xrp6UWdlScOGAvsxtiS0KZEQQppZXaOqJYE01EWyaVMFoqJCYTT6+kjc17GjgIwM7zclSs/pTz/JUFHB0UAXL9U3LVGnE6/geNOVxR9ERYmvGaOx9uPMzAyOx9iSUIaaEEKamdgSr+7WeVJAHShdPgKdtDHR20ygWi0GSAcOiHmqXr0oQ+2N+gNqPijGcUslH3VlqIOhLWBLQwE1IYQ0M45zPtylKkNNAVlzGDPGhr/9zYb27b1fb61WQFERh9BQVllKQjyj0QgNBNSBv75SyUddNdRZWTzVTwcYCqgJIcQHao6qlkgbsQKp5COQ9ekj4PPPKxAS4v3Pkso+une3Qybz/ue1ZHFxdWeoBQHIygqOdnLONiUyJj7GQK8Rb2kooCaEEB/QagWnJR8REQyhoT44KOIVKaCmcg/viePHOdhs1b9uMIibdoOhHEKtBtRqVqvkIy+Pg8kUHB8aWhIKqAkhxAcSEuou+QikKYmkOq1WDIBoQ6L3NBoGxjgUFFQPNq9cEX9nAn1KoqSu4S5ZWdQyLxBRQE0IIT4QH89QWsqhtLT618WhLvRGGoikjY29e9Pz562qXtTVg83MTCnYDI4PnXUF1MHSFrClobZ5hBDiA1I202DgEB5e9cZpMPDo3ZsynIFoyhQrWrdm6NKFAmpvSQF1zTpqnU6aIBgcaxwTw1BYWP1r0lAXKvkILJShJoQQH5D6Htcs+zAYqOQjUIWHA8nJtoa/kTRImhRaM0Ot03GIjRUQFuaLo2p8UVF1lXzwCA9niIz00UERj1BATQghPlDXcJfSUqC8nEo+CKnKUFcPU4KtP3NdJR86HYe2bYWAmzza0lFATQghPiCVfDgG1IE4JZGQphAeXvf48czM4Op+IZZ8cGAOv/JiD2o6BwQaCqgJIcQHIiKAsDCGnJyq07DBQD2oCZHExlYPqBkTN+wFU7AZHc1gt3MoLq76mvgYg+dDQ0tBATUhhPiIVlt9/LhUL0o11ITUHj8u9WcOlpZ5QO3x46Wl4qCXYPrQ0FJQQE0IIT5Sc7gLjR0npErN8eNS94tgyt7WHD+elRVcXUxaEgqoCSHER8QMtWPJB4eQEIaoKB8eFCF+oub4callXrt2wZO9lTLURqP4OKv6bFNAHWgooCaEEB+RSj6kDUkGA4+4OEa7+wmBWPJRUFA1frwqoA6eYLNmyUdVn+3g+dDQUlBATQghPqLVCrBYuMrBDtSDmpAqNceP63QcoqIYIiJ8fGCNKDpa/Luq5IODXM5oY3IAooCaEEJ8pOZwl9xc6kFNiKTmtMRg7H4RFcXAcaxahrpNGwaZzMcHRtxGATUhhPiIlIWSNiPm5lKGmhBJzYBapwuuHtQAIJMBkZFVGerMTC7oPjS0FBRQE0KIjzgOd7FYgKtXebrUS8g10vjxvDxxn4FOxwfVhkSJ47REGuoSuCigJoQQH5HGj+v1fGUPagqoCRFJV2tyczkUFADl5cGXoQbE1nlXr3KwWgG9njLUgYoCakII8ZGQECAmRuxFTT2oCakuLAxQqxny8nhcuSJ+LRizt1KGWq/nIAg01CVQUUBNCCE+FB/PYDBwNHackBo4rmpa4l9/iV8LpimJkqgoBqORo6EuAY4CakII8aGEBAa9nnfIUFNATYhECqivXAnegSdSyYc0CTIYy1paAgqoCSHEh6Tx4wYDB55niI2lgJoQiTR+/PJlIDw8OKeIRkczlJZyuHRJDMnatKFzQCCigJoQQnxIqxUzcHo9j9atqf8sIY6kDPXly+KGxGCcIipNSzx9mkdsrAC12scHRDxCATUhhPiQVssgCBxOn6aWeYTUJI0fv3gRQdkyDxBLPgAgLU1GGxIDGAXUhBDiQ1Iv6owMCqgJqUmjET9wnjkTvLXFUoY6Ozv4JkG2JBRQE0KID0m9qK1WGjtOSE1SL2qxnVxw/n5IGWogONsCthQUUBNCiA8lJFS9gVKGmpDqpPHjAHDddcH5+xEV5RhQB+eHhpaAAmpCCPGh2FgGnhffUKVsHCFEpNFUBZjBGmxKJR8AZagDGQXUhBDiQzJZVSBNATUh1TlmqIN1U2JYGKBUio8tWOvEWwIKqAkhxMeksg+qoSakuogIQKViUKsZWrcOzoCa46qy1ImJdA4IVHJfHwAhhLR0YiAtoxpqQmqQxo+HhXFB2YNaEhPDUFLCEB3t6yMhnqKAmhBCfEzq9EEBNSG1de4sIDY2uC+oR0cz2O3BObimpaCAmhBCfGziRBtCQgCVytdHQoj/ef/9CkRHh8Ji8fWRNJ0FCywwmSiaDmQUUBNCiI8NGmTHoEF2Xx8GIX4pLAwIDUVQB9RJSfT7H+iC+xoKIYQQQgghTYwCakIIIYQQQrxAATUhhBBCCCFeoICaEEIIIYQQL1BATQghhBBCiBcooCaEEEIIIcQLFFATQgghhBDiBQqoCSGEEEII8QIF1IQQQgghhHiBAmpCCCGEEEK8QAE1IYQQQgghXqCAmhBCCCGEEC9QQE0IIYQQQogXKKAmhBBCCCHECxRQE0IIIYQQ4gUKqAkhhBBCCPECBdSEEEIIIYR4gQJqQgghhBBCvMAxxpivD4IQQgghhJBARRlqQgghhBBCvEABNSGEEEIIIV6ggJoQQgghhBAvUEBNCCGEEEKIFyigJoQQQgghxAsUUBNCCCGEEOIFjwJjN+WWAAAKtElEQVRqvV6PWbNmYezYsRg3bhw++ugjAIDRaMTcuXMxatQozJ07F0VFRQCAr776CsnJyUhOTsa0adNw5syZyp/1448/YvTo0Rg5ciQ2bNjg9D537tyJUaNGYdSoUdi5c2fl1+fNm4cJEyZg3LhxWLp0Kex2e523X7x4MQYOHIjx48dX+/q///1vDB06FCkpKUhJScEPP/wQ1Gvh7HgBYNWqVRgzZgySk5Px6KOPori42K21aG7+tPaShx9+uNZrzJGz+/nkk08wcuRIdOnSBVevXm3Ra3H48GHcddddSElJwfTp03H58uWgXoeWcG5yZS0C4dzkT2s6a9YsjB49uvL1UVBQUOft09PTkZycjJEjR+Kll16C1Cn366+/xrhx49C1a1ecOnWqRa9FRkYG7r77bqSkpGDSpElIS0sL6nV4/fXXMXz4cPTp06fa17/44gsMGDCg8vbbtm1zeR0CcS0qKirw0EMPYcyYMRg3bhzWrFlT+f82btyIsWPHIjk5Gffddx+ysrIaXgDmAYPBwNLT0xljjJWUlLBRo0axc+fOsVWrVrH169czxhhbv349W716NWOMsWPHjjGj0cgYY+zgwYNsypQpjDHGbDYbu/3229mVK1eY2WxmycnJ7Ny5c7Xur7CwkCUlJbHCwkJmNBpZUlJS5c8rKSlhjDEmCAKbP38+27NnT53HfPToUZaens7GjRtX7etr165l7733nifLEJBr4ex4GWPsp59+YlarlTHG2OrVqyuP2V/509ozxtg333zDFi1aVOs1Jqnvfk6fPs10Oh0bMWIEKygoaNFrMWrUKHb+/HnGGGOffPIJe/rpp4N2HRhrGecmV9YiEM5N/rSmM2fOZGlpaQ0e8+TJk9nx48eZIAhs3rx57ODBg4wxxs6fP88uXLjg8s8J5rWYO3du5b8PHjzIZs6cGdTrcPz4cWYwGFjv3r2rfX3Hjh3shRdecPmx1xRoa1FeXs4OHz7MGGPMbDaz6dOnV74ODh8+zMrLyxljjG3evJktXLiwwcfvUYY6Li4ON998MwAgPDwcN9xwAwwGAw4cOICJEycCACZOnIhvv/0WAHDLLbcgMjISANC7d2/k5OQAANLS0tC+fXu0a9cOSqUS48aNw4EDB2rd36FDhzB48GBERUUhMjISgwcPxk8//VR5/wBgs9lgtVrBcVydx3zbbbdVHkNjCrS1cHa8ADBkyBDI5fJax+av/Gnty8rKsHHjRjzyyCNOj7e+++nWrRvatm1La3FNaWlp5d9xcXFBuw5Ayzg3ubIWgXBu8qc1dUVubi5KS0vRu3dvcByHiRMnVt5Px44dccMNN9BaAOA4DmVlZQCAkpKSgD3nuKp3795uPUZXBdpaqNVqDBgwAACgVCrRrVu3ynPOgAEDoFarax1bfbyuoc7MzERGRgZ69eqFgoKCyidJo9HUmWLfvn07hg0bBgAwGAzQarWV/y8+Pr7ywThq6PvmzZuHQYMGISwsDKNHj3b7MWzevBnJyclYvHhx5aUITwTaWjgeb007duyoPLZA4Ou1f/PNN3H//fdDpVI5PUZX78dbgb4WK1aswEMPPYRhw4Zh165deOihh9x5+JUCYR0aEiznJnfXIhDOTb5eUwBYsmQJUlJS8Pbbb1eWL9R3e61WG5TnHMC7tViyZAlWr16N4cOHY9WqVVi0aJG7SwAgMNahIfv27UNycjIWLFgAvV7v9u0lgbYWxcXF+P777zFw4MB6j60+XgXUZWVlWLBgAZYsWVKZHZVwHFcrQ5qamort27fjiSee8OZua3n//fdx6NAhWCwWpKamunXb6dOnY//+/di1axfi4uKwcuVKj44h0NaivuN99913IZPJMGHChEY9tqbi67XPyMjAlStXMHLkyEb5ed4IhrX48MMPsWHDBvz444+YNGkSXnnlFbd/RjCsQ7Ccm9xdi0A4N/l6TQFgzZo12L17NzZv3oxjx45h165djfaz3REMa7FlyxYsXrwYP/zwAxYvXoxnnnnG7WMIhnUYMWIEvvvuO+zevRuDBg3C008/7dFxBNpa2Gw2LFq0CLNmzUK7du2q/b9du3YhPT0dDzzwQIP36XFAbbVasWDBAiQnJ2PUqFEAgNatWyM3NxeAeHklJiam8vvPnDmDZ599Fu+88w6io6MBiJ8mHNPoBoMB8fHxOHnyZGUh+YEDB5x+n6OQkBDcfvvtOHDgAPR6feXtt2zZUu/jiI2NhUwmA8/zmDp1qkebMwJtLeo6XskXX3yBgwcPYs2aNU7LZ/yJP6z98ePHkZ6ejqSkJMyYMQN//fUXZs2aVWvtXXnuWvpaXL16FWfOnKnMTI4dOxbHjx8P2nWoT7Ccm9xZi0A4N/nDmko/AxAvrY8fPx5paWmw2+2Vt3/zzTdr3T4nJyfozjmNsRbSxjYAuPPOO93alBho61Cf6OhoKJVKAMDUqVNx+vRpt9YhUNfiueeew/XXX485c+ZUeyy//PIL1q1bh3fffbdyXerVYJV1HQRBYE8++SR76aWXqn195cqV1QrPV61axRhjLCsri91xxx3s2LFj1b7farWypKSkaoXnZ8+erXV/hYWFbMSIEcxoNDKj0chGjBjBCgsLWWlpKTMYDJU/a+HChWzTpk1Oj1un09XaECPdnjHGNm7cyB5//HE3ViLw1sLZ8TLG2A8//MDuvPNOjzbF+YK/rL2jul5j7tyPp5sSg2UtrFYr69evH7t48SJjjLHPP/+czZ8/P2jXob7vCZZzU0OPs6HjZcx/zk3+sqZWq7VyLSwWC3vsscfYp59+WucxO9uIJ/F0U2IwrcWYMWNYamoqY4yxX375hd11111BvQ6SmpsSHc85+/btY1OnTnVxFUSBuBavvfYamz9/PrPb7dW+fvr0aXb77bezS5cuufz4OcbcL7L57bffcO+99+LGG28Ez4tJ7kWLFqFnz554/PHHodfr0aZNG7zxxhuIiorCM888g3379qFNmzYAAJlMhi+++AIA8MMPP+Dll1+G3W7H5MmTnW5a2b59O9avXw9AbL00efJk5Ofn4+9//zssFgsYY+jfvz8WL15cuXnF0aJFi3D06FEUFhaidevWeOyxxzB16lQ8+eSTla1aEhMTsXz5creK9QNtLZwd7/DhwzFy5EhYLBZERUUBAHr16oXly5e7vBbNzV/W3lFmZiYefvhh7Nmzp87bO7ufjz/+GO+99x7y8/MRExOD4cOHY8WKFS1yLfbv34+1a9eC4zhERkbi5ZdfrnUZLpjWIdjPTa6uRSCcm/xlTcvLyzFz5kxYrVYIgoCBAwdi8eLFkMlktW5/6tQpLF68GCaTCcOGDcNzzz0HjuOwf/9+vPjii7h69SpatWqFm266Ce+//36LXIvffvsNL7/8Mmw2G0JCQrBs2TJ07949aNdh9erV2LNnD3JzcxEXF4epU6fisccew7/+9S989913kMlkiIyMxPPPP4+OHTu6tA6BuBY5OTkYPnw4brjhhsoM9MyZMzF16lTMmTMHZ8+ehUajAQAkJCRg3bp19T5+jwJqQgghhBBCiIgmJRJCCCGEEOIFCqgJIYQQQgjxAgXUhBBCCCGEeIECakIIIYQQQrxAATUhhBBCCCFeoICaEEIIIYQQL1BATQghhBBCiBcooCaEEEIIIcQL/x/SLH689Tp2kwAAAABJRU5ErkJggg==\n",
            "text/plain": [
              "<Figure size 864x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Results of Dickey-Fuller Test:\n",
            "p-value = 0.9028. The series is likely non-stationary.\n",
            "Test Statistic                 -0.442218\n",
            "p-value                         0.902808\n",
            "#Lags Used                      9.000000\n",
            "Number of Observations Used    55.000000\n",
            "Critical Value (1%)            -3.555273\n",
            "Critical Value (5%)            -2.915731\n",
            "Critical Value (10%)           -2.595670\n",
            "dtype: float64\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Dbcpfax5O1H7",
        "colab_type": "code",
        "outputId": "1d872994-b63c-4277-ba88-3c4ad03af470",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 499
        }
      },
      "source": [
        "#plotting autocorrelation and partial autocorrelation for both data (data before differencing and data after differencing)\n",
        "\n",
        "import statsmodels.api as sm\n",
        "\n",
        "fig = plt.figure(figsize=(12,8))\n",
        "ax1 = fig.add_subplot(211)\n",
        "fig = sm.graphics.tsa.plot_acf(train_df.TT, ax=ax1, ) # using default value of lag\n",
        "ax2 = fig.add_subplot(212)\n",
        "fig = sm.graphics.tsa.plot_pacf(train_df.TT, ax=ax2) # using default value of lag"
      ],
      "execution_count": 229,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x576 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9vNyTWu3Mgda",
        "colab_type": "text"
      },
      "source": [
        "Here in partial autocorrelation we can see a small upward trend for ( almost ) every second plot as compared to previous plot. "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Och4_Dt3Re4g",
        "colab_type": "code",
        "outputId": "8d84b099-63d4-46ad-9012-9414ae151a58",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 499
        }
      },
      "source": [
        "fig = plt.figure(figsize=(12,8))\n",
        "ax1 = fig.add_subplot(211)\n",
        "fig = sm.graphics.tsa.plot_acf(first_diff, ax=ax1)\n",
        "ax2 = fig.add_subplot(212)\n",
        "fig = sm.graphics.tsa.plot_pacf(first_diff, ax=ax2)"
      ],
      "execution_count": 230,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x576 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "497s4I4ETh0d",
        "colab_type": "code",
        "outputId": "a2aa8048-57ae-4804-84c7-258d8fbb3bf2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 629
        }
      },
      "source": [
        "# we can see a recurring correlation exists in both ACF and PACF hece we should choose SARIMAX model which also deals with seasonality\n",
        "\n",
        "#RULE : A model with no orders of differencing assumes that the original series is stationary (mean-reverting). A model with one order of differencing assumes that \n",
        "      #the original series has a constant average trend (e.g. a random walk or SES-type model, with or without growth). A model with two orders of total differencing assumes that \n",
        "      #the original series has a time-varying trend \n",
        "\n",
        "#Since our series has a contant average trend ( with growth ) we would take I = 1 and MA = 0 ( I-1 ).\n",
        "\n",
        "\n",
        "sarimax_mod = sm.tsa.statespace.SARIMAX(train_df.TT, trend='n', order=(14,1,0)).fit()\n",
        "print(sarimax_mod.summary())"
      ],
      "execution_count": 231,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "                           Statespace Model Results                           \n",
            "==============================================================================\n",
            "Dep. Variable:                     TT   No. Observations:                   69\n",
            "Model:              SARIMAX(14, 1, 0)   Log Likelihood                -473.597\n",
            "Date:                Fri, 22 May 2020   AIC                            977.194\n",
            "Time:                        17:29:25   BIC                           1010.487\n",
            "Sample:                    03-14-2020   HQIC                           990.385\n",
            "                         - 05-21-2020                                         \n",
            "Covariance Type:                  opg                                         \n",
            "==============================================================================\n",
            "                 coef    std err          z      P>|z|      [0.025      0.975]\n",
            "------------------------------------------------------------------------------\n",
            "ar.L1         -0.3661      0.158     -2.316      0.021      -0.676      -0.056\n",
            "ar.L2          0.2570      0.109      2.366      0.018       0.044       0.470\n",
            "ar.L3          0.2805      0.178      1.575      0.115      -0.069       0.630\n",
            "ar.L4          0.0518      0.150      0.345      0.730      -0.242       0.346\n",
            "ar.L5         -0.0622      0.150     -0.414      0.679      -0.357       0.232\n",
            "ar.L6          0.2543      0.169      1.506      0.132      -0.077       0.585\n",
            "ar.L7          0.0626      0.130      0.482      0.629      -0.192       0.317\n",
            "ar.L8         -0.0939      0.186     -0.506      0.613      -0.458       0.270\n",
            "ar.L9          0.1441      0.147      0.983      0.325      -0.143       0.431\n",
            "ar.L10         0.0292      0.170      0.172      0.863      -0.304       0.362\n",
            "ar.L11        -0.1287      0.190     -0.677      0.499      -0.501       0.244\n",
            "ar.L12        -0.0282      0.270     -0.105      0.917      -0.557       0.501\n",
            "ar.L13         0.4091      0.166      2.464      0.014       0.084       0.734\n",
            "ar.L14         0.0255      0.174      0.146      0.884      -0.316       0.367\n",
            "sigma2      5.979e+04    1.3e+04      4.615      0.000    3.44e+04    8.52e+04\n",
            "===================================================================================\n",
            "Ljung-Box (Q):                       24.51   Jarque-Bera (JB):                 3.27\n",
            "Prob(Q):                              0.97   Prob(JB):                         0.19\n",
            "Heteroskedasticity (H):              29.37   Skew:                             0.38\n",
            "Prob(H) (two-sided):                  0.00   Kurtosis:                         3.77\n",
            "===================================================================================\n",
            "\n",
            "Warnings:\n",
            "[1] Covariance matrix calculated using the outer product of gradients (complex-step).\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Hd6QjoFvTzaA",
        "colab_type": "code",
        "outputId": "fc6d9e44-4297-4092-80b9-c9968fb14050",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 998
        }
      },
      "source": [
        "import scipy.stats as stats\n",
        "\n",
        "resid = sarimax_mod.resid #gives residual degree of freedom (mu, sigma, pvalue ... )\n",
        "print(normaltest(resid))\n",
        "\n",
        "fig = plt.figure(figsize=(12,8))\n",
        "ax0 = fig.add_subplot(111)\n",
        "\n",
        "sns.distplot(resid ,fit = stats.norm, ax = ax0) # need to import scipy.stats\n",
        "\n",
        "# Get the fitted parameters used by the function\n",
        "(mu, sigma) = stats.norm.fit(resid)\n",
        "\n",
        "#Now plot the distribution using \n",
        "plt.legend(['Normal dist. ($\\mu=$ {:.2f} and $\\sigma=$ {:.2f} )'.format(mu, sigma)], loc='best')\n",
        "plt.ylabel('Frequency')\n",
        "plt.title('Residual distribution')\n",
        "\n",
        "\n",
        "# ACF and PACF\n",
        "fig = plt.figure(figsize=(12,8))\n",
        "ax1 = fig.add_subplot(211)\n",
        "fig = sm.graphics.tsa.plot_acf(sarimax_mod.resid, ax=ax1)\n",
        "ax2 = fig.add_subplot(212)\n",
        "fig = sm.graphics.tsa.plot_pacf(sarimax_mod.resid, ax=ax2)"
      ],
      "execution_count": 232,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "NormaltestResult(statistic=4.161019804209335, pvalue=0.12486652625862307)\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x576 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KoWLvPWxT6Hm",
        "colab_type": "code",
        "outputId": "0276084e-32d6-4e78-8af1-7dc3f39a2f25",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 549
        }
      },
      "source": [
        "#Now lets predict using out model.\n",
        "today = datetime.date.today() -timedelta(days=1)\n",
        "\n",
        "start_index = '14-Mar-20'\n",
        "end_index = today.strftime(\"%Y-%m-%d\")\n",
        "\n",
        "#adding forecasted values and plotting\n",
        "train_df['forecast'] = sarimax_mod.predict(start= start_index,end = end_index,dynamic= False,)  \n",
        "\n",
        "train_df[start_index:][['TT', 'forecast']].plot(figsize=(12, 8))"
      ],
      "execution_count": 233,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.axes._subplots.AxesSubplot at 0x7f4cc2b0d160>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 233
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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EREREBrRwJEq1L0Tm0ZIM1+bfkvT+zwmnTyQw7mIC4y8hkjG53V37rJW7SCh4Fe8Zt4Ij6bier8AsIiIiIgNaZfOmJclNm5bYyjYRcWUTdWbg2vgrkjY+QDhtLIFxlxAcdwnhzGkt4dn14UNE7ck0zrj2uJ+vwCwiIiIiA1rV0cDcvOjPVrWH0LAzaVj0awxvOQkfvULCwdW4Nv2apA8fIuIeRWDcxYSyZ5Fw4O80nnoDZmLacT9fgVlEREREBrSKY3b5M4INWBsK8U/9PABmUjb+6dfgn34NRmNVS3h2bn0MVzSMaUvEN/urPXq+ArOIiIiIDGgVzSUZSQ6s1TsACA+Z3OY80zkE/9Sr8U+9GsNfg6PgVczEDEznkB49X4FZRERERAa0Sk8Ai9G0y5/t8B4AwkMmdXqNmZhOYPKVcXm+2sqJiIiIyIBW6Q0yJMmB1WJgrdpD1J5ENGV4nz1fgVlEREREBrQKT7ClpZyteg+RjElg9F2MVWAWERERkQGtadOSBDBNbFV7uizHiDcFZhEREREZ0JpnmA1fBRZ/TdMmJX1IgVlEREREBqxQJEptY4jMZAe26r1A+x0yepMCs4iIiIgMWMduWmKrau6QocAsIiIiIgIcu2lJQlOHDGdWj/sqd5cCs4iIiIgMWMduWmKr7vsFf6DALCIiIiIDWKUnAEBmkg1b9b4+L8cABWYRERERGcAqvUGsBmSGSzDCjU09mPuYArOIiIiIDFgVnqZd/uz91CEDFJhFREREZACr9DRtWtLSIUMzzCIiIiIin6jwBshMcmCt3kvEPQrsrj4fgwKziIiIiAxYlZ5g06YlVXv6pRwDFJhFREREZIAKhqPU+cPkusBae6hfyjFAgVlEREREBqjKoz2YxxslGGaEiGaYRUREREQ+UXG0B/PISAHQPx0yQIFZRERERAao5hnmHP9HmBY7kdQx/TIOBWYRERERGZAqPU2BOc27n0j6eLDa+2UcCswiIiIiMiBVeIPYLAbO2v39tuAPFJhFREREZICq9AQY5Qph9RT1W/0yKDCLiIiIyABV4QlyqrMEgMiQKf02DgVmERERERmQKr1BplmLgP7ZEruZArOIiIiIDEiV3iAT+JioPZloyrB+G4cCs4iIiIgMOP5QhHp/mBHhw0SGTALD6LexKDCLiIiIyIDT1IPZJNt/iHBG/y34AwVmERERERmAKj1BsqklMVzXrx0yQIFZRERERAagSm+QSZYjAE0lGf1IgVlEREREBpwKb5BJRlNgVkmGiIiIiJzwTNPs1vmVngBTrUeIuLIxnRm9NKrYxBSYFy5cyGWXXcZnP/tZrrjiCgBqa2u57rrrWLRoEddddx11dXVA04dxxx13kJ+fz2WXXcbOnTtb7rNq1SoWLVrEokWLWLVqVS+8HREREREZaLYX13P+w++wrbg+5msqPEGmWIuI9HP9MnRjhvnJJ5/kpZde4oUXXgBg5cqVnHnmmaxZs4YzzzyTlStXAvDmm29SUFDAmjVr+OlPf8rtt98ONAXshx9+mGeeeYZnn32Whx9+uCVki4iIiMiJKRw1uefV/XiDEV7YVhLzddWeRsaaR/q9HAN6UJKxbt06lixZAsCSJUt49dVXWx03DIPZs2dTX19PeXk5b7/9NvPnzyctLY3U1FTmz5/PW2+9FZ93ISIiIiID0gtbi9lX4WVkupPX9lXSGIrEdJ294QgJBAn384I/6EZgvv7667niiiv4y1/+AkBVVRXZ2dkAZGVlUVVVBUBZWRm5ubkt1+Xm5lJWVtbmeE5ODmVlZXF5EyIiIiIy8FR5gzzyrwLOGJnG9/In4AtFeP1AZUzXZjYeABgQJRm2WE56+umnycnJoaqqiuuuu46xY8e2et0wDIxe2H3FMCAtzRX3+4r0JavVou+xiAw4+m2SvnDX+gMEwlF+umQ6o4ckMSxtH2v3VfG5M8d0ep0vGGZU+DCm3SB5zCyw9+93NabAnJOTA8CQIUPIz89n27ZtDBkyhPLycrKzsykvLycjI6Pl3NLS0pZrS0tLycnJIScnhw0bNrQcLysr44wzzuj0uaYJtbW+br8pkYEkLc2l77GIDDj6bZLetqWwjlWbi7n2jBFk2C3U1zeyeFIWf9hwhAOFNWQmJ3R47ZGaRiZajtDgHE7AC9D739WsrJQOX+uyJMPn8+HxeFr+/V//+hcTJkxg4cKFvPjiiwC8+OKLXHDBBQAtx03TZMuWLaSkpJCdnc2CBQt4++23qauro66ujrfffpsFCxbE4/2JiIiIyAASjpr8bN0BclIS+PK8kS3HL5qaQ9SEl/dUdHp9pTfIZOMIXvfE3h5qTLqcYa6qquKGG24AIBKJcOmll3LOOecwY8YMli9fznPPPcfQoUN54IEHADj33HN54403yM/Px+l0ctdddwGQlpbGt771LZYtWwbADTfcQFpaWm+9LxERERHpJ89uKeZApZefXT4Vp93acnx0hotpuSn8Y1cZXzhteIfXV9XVc4FRSsmQpbGVQ/Qyw+xuF+k+FI2aVFV5+nsYIj2iv/YUkYFIv03SWyo9AZY9sZGZQ9386orpbda5PbO5mHvXH+CpL57KhKzkdu+x9s11XL39S5QufBjrlCV9MeyelWSIiIiIiMTqV29+RDAS5daF49ttCrFoUhZWi8E/dpV3eA9H9V4A7NlTe22c3aHALCIiIiJx8eGRWl7eXc41p49gZLqz3XPSXHbmj8ng5d3lRKLtFzq4PQcIYCeaPrbd1/uaArOIiIiI9Fg4EuXn6w4w1J3AdWeM6PTcS6ZmU+kN8sHHNe2+nuU7SJF1BFgGQgWzArOIiIiIxMFfNhdzqMrHd84fT+IxC/3as2DsEFISbB2WZQwLF1CW0Hmv5r6kwCwiIiIiPVLeEGDlO4dZMDaDc8ZldHm+w2Yhf1IWr+2vxBdsvVW24a8l26yiJnl8bw232xSYRURERKRHfvXGIcLRKLecPy7m3Z8vnpqNPxzltf2tt8oOl+0GoDF1YPRgBgVmEREREemBDz6uYc3eCq49YyTD09pf6NeemUPdDEtNZPWuslbHA2U7AYhmTo7rOHtCgVlEREREjkvUNLl33UGGpSZyzekdb0TSHsMwuHhqNhs/rqWsIfDJ8Yrd1JsuXBmdLxzsSwrMIiIiInJcimr9fFTt44tnjOhyoV97LpqSgwm8svuTxX8JNfvYaw4nKyUxjiPtGQVmERERETkuBdVNu0VOyEw6rutHpDuZOdTN6l1lmKYJpkmq5wB7oyPISnbEc6g9osAsIiIiIselOTCPyoi9dvnTLp6azaEqH/vKvVi8JSRGGjhojCTJ0f0Z696iwCwiIiIix+VwdSMZLjvuRPtx3+MzE7OwWw1W7yrDXvIhAOXOsTF32+gLA2P7FBEREREZdAqqfYzKcPXoHqlOOwvGDiG6+0VS9v6GUksuVclT4jTC+FBgFhEREZHjUlDtY+HEzJ7dxDS5xfEi083fUOU+ha823kRuSmp8BhgnCswiIiIi0m21vhB1/jCjezLDHPaTsv5Wsg6+yN84h3+m/BcHKhuYnjRwFvyBArOIiIiIHIfDNc0L/o4vMBu+ClL/cT32sk145v03b1QvYu3OMkIRc0B1yAAt+hMRERGR49DcIWP0cXTIsFbuIv3ZS7FV7aLuwkdpnPOfXDI9l1DEBCBTgVlEREREBruC6kYSbBZyu7nBiKPgVdJeWApmmNorVhEcdwkA03JTGJneFL6zkhLiPt6eUGAWERERkW4rqPYxMt2J1RJj+zfTxLllJe7V1xFJG0ftsr8TzprR8nLzVtkAOSkDKzCrhllEREREuu1wtY9J2SkxnWsEPST968c4dz1NYNzF1F/wK7C3LeX4/JzhjBuSxIj0498IpTcoMIuIiIhItwTDUYrq/CyenN35iSEfzu1/wLX5ESz+GrxzbsQ3dwUY7Rc5JNqtnDehh23qeoECs4iIiIh0y5HaRqImHbeUCzfi3PFnXJt+jaWxkuDI8/CecQvhnFP6dqBxosAsIiIiIt1yuLq5pdynSifCfhJ3PYXrw4ex+soJDl/QFJTzTu+HUcaPArOIiIiIdEtBdSMAI9OPzjBHgiTu/guuDx/E6ikhOHQuDYt+TWjYmf04yvhRYBYRERGRbjlc4yMnJQGXw0rCvlUkvXsPVk8RodzTaLjgAULDzgIjxu4Zg4ACs4iIiIh0S0F1I6MznFgainGvvZFQ1gwazv8ZoRHnnlBBuZn6MIuIiIhIzEzT5HC1j9EZLuwlGwDwnPczQiPPOyHDMigwi4iIiEg3VHqDeIMRRmW4sJd+gGlzEc6c2t/D6lUKzCIiIiISs4KjHTJGZzixlWwklHMKWE7sKl8FZhERERGJWXOHjLEpUWxVuwnlndbPI+p9CswiIiIiErPD1T6SHFZyGnZimFFCg7zHciwUmEVEREQkZgXVPkamO3GUbsTEIJxzan8PqdcpMIuIiIhIzJpayrmwl24kMmQSZoK7v4fU6xSYRURERCQmjaEIZQ0BxqQnYCvdRCj3xC/HAAVmEREREYnRx0cX/M1yFGEJeU6KBX+gwCwiIiIiMWpuKTcxuAvgpFjwBwrMIiIiIhKjgmofFgNy6rcRceUQTRnR30PqEwrMIiIiIhKTgupGhqUmklC2kXDenBN2K+xPU2AWERERiaNAOMpPXt5LUV1jfw8l7g7X+Jid6sPaUHjSLPgDBWYRERGRuNpX7uFvO8t4ZXdFfw8lriJRk49rGpnvOABw0iz4AwVmERERkbgqPDqzvLO0oZ9HEl+lDX4C4SjTInswbYmEM6f395D6jAKziIiISBwV1voB2FFSj2ma/Tya+Ck42lJupG87oezZYLX384j6jgKziIiISBwV1TUF5mpfiNKGQD+PJn4OV/tw4sddt+ekaSfXTIFZREREJI6KahtJSbABsLPkxCnLOFzdyPzEAgwzQjj35KlfBgVmERERkbgqqvMzf2wGDqvBjhMoMBdU+zjPeQiAUO6p/TyavqXALCIiIhIn/lCECk+Q0RlOJmWnsLO0vr+HFDcF1T5ONfYRTp+ImZje38PpUwrMIiIiInHSXL88PNXJtLwUdpd5CEei/Tyqnqv3h6jxBRgb2H1StZNrpsAsIiIiEifNgXlYWiLTc1MIhKMcrPL186h67nB1IxOMIhIjDSfdgj9QYBYRERGJm8LaptZrzTPMADtLBn9ZRkG1j9Ms+wAInWQL/kCBWURERCRuimr9JDmspDptDEtNJM1pPyEW/hVUN3K6ZR+RxCFEU0f393D6nAKziIiISJwU1fkZlpqIYRgYhsG03JQTYse/w9U+zrDtI5x3GhhGfw+nzykwi4iIiMRJYW0jw9OcLX+elpfCR1U+PIFwP46q5+qrihhmlp2U9cugwCwiIiISF1HTpLi+aYa52fS8FExgd9ngnWUOR6LkNmwHUGAWERERkeNX3hAgFDEZnvZJYJ6a07Twryd1zPbi90hZcwMEvT0e4/EorPNzqrGXiMVBOGt6v4yhv9n6ewAiIiIiJ4KWlnKpn5RkpDrtjEx3sut465gjQZLXr8BW9xHRxAy85/w0HkPtlsNHO2Q0pM8Aa0KfP38giHmGORKJsGTJEr7+9a8DcOTIEa688kry8/NZvnw5wWAQgGAwyPLly8nPz+fKK6+ksLCw5R6PPvoo+fn5LF68mLfeeivOb0VERESk/xTVftKD+VjTclPYUdKAaZrdvqdzx5+w1X1EKPc0XNufwF78flzG2h2FlTVMMz6CYSdfO7lmMQfmP/7xj4wbN67lz/fddx/XXnsta9euxe1289xzzwHw7LPP4na7Wbt2Lddeey333XcfAAcOHGD16tWsXr2axx9/nB//+MdEIpE4vx0RERGR/lFY14jVgFx328Bc6Q1S1hDo1v0Mfy2uD35JcPjZ1F7+FBH3SJLX3wKhxngOu0tmyRYcRgRj+Nw+fe5AElNgLi0t5fXXX2fZsmUAmKbJe++9x+LFiwFYunQp69atA2D9+vUsXboUgMWLF/Puu+9imibr1q3jkksuweFwMGLECEaNGsW2bdt64z2JiIiI9LmiWj+57kRsltZt16Yf3cCku2UZrg8fwgjU4Zn/A7C7aDj/Xmx1BSS9fxApkU8AACAASURBVG/cxhyLjJrNwMm5YUmzmALzXXfdxYoVK7BYmk6vqanB7XZjszWVQOfm5lJWVgZAWVkZeXl5ANhsNlJSUqipqaGsrIzc3NyWe+bk5LRcIyIiIjLYFdb5Wy34azYhKxm71ejWwj9L3WGc257AP+UqIplTAQgNn0/j9C/i3PoYtpKNxz1OTyCMNxhbmzvTNBnl20G5YwSmM+O4nznYdbno77XXXiMjI4Pp06fz/vt9WzdjGJCW5urTZ4rEm9Vq0fdYRAYc/TbFX3Gdn4um57b7uU7Nc7On0hvzZ25d/3Ow2rDl/5C0lGOuufCncOQ10t5YQfj618Hu7PAe7QmGo/zHH/9FYzDC8984k8zkzhfxVTY0Mot9lA+5gLEn8fely8C8adMm1q9fz5tvvkkgEMDj8XDnnXdSX19POBzGZrNRWlpKTk4O0DRzXFJSQm5uLuFwmIaGBtLT08nJyaG0tLTlvmVlZS3XdMQ0obbW18O3KNK/0tJc+h6LyICj36b4avCHqW0MkeW0tfu5Ts5K4qXtpVRWe9uUbHyarWQj6btfwnv6d/BFUqHV/azYz/0ZaX+9mtDaO/CedVu3xvm/Gws5WNE0hq/98UMeuWomCbaOCw4O7PqQsw0Ph7NOPeG/L1lZKR2+1mVJxi233MKbb77J+vXruf/++5k3bx6/+MUvmDt3Lq+88goAq1atYuHChQAsXLiQVatWAfDKK68wb948DMNg4cKFrF69mmAwyJEjRygoKGDmzJnxeH8iIiIi/aqormkh3rC09md8p+Wl4A9H+aiqi17Kpknyv35CxJWD75RvtHtKaMQ5NE79HM4tj2Ir2xzzGKt9QR579zBnjUnnjksms72knp++srfT7h3RI03VBa7R82J+zonouDcuWbFiBU888QT5+fnU1tZy5ZVXArBs2TJqa2vJz8/niSee4NZbbwVgwoQJXHTRRVx88cV85Stf4Yc//CFWqzU+70JERESkH33Sg7ltDTPA9Fw30PUGJgkH/oa9bBO+uSvA3nEJhPesHxBNyiFl3S0Qia37xiNvF+APR7n53HFcMDGLb84fzSt7Knji/SMdXpNUuZkaM4XUYVNiesaJyjCPpylgH4lGTaqqPP09DJEe0V97ishApN+m+HpywxEefusjXr/xLJIcbSteTdMk/zfvct74TL6/eGL7Nwn7yXjqfExHMjVXvQyWzicWHYfXk/r3L+KdcyO+ef/V6bl7yhr44p8387k5w7j5vHEtY/rRP/fyz93l3HPZFC6YmNXmutBv53LYGMb4r7/Q6f1PBD0qyRARERGRzhXWNpLutLcblgEMw2Bqbgo7O2kt59z2BNaGI3jm/7DLsAwQHLUQ/+SrcG36Dbbyjlv1mqbJL147SJrTzlfmjWo1ptsWTWTmUDc/+ufeNm3vjMYqhkaKKEmZ0eVYTnQKzCIiIiI9VFTnb7PD36dNz0vhUJUXX7Dtxm1GYzWuDx8iMGohoRFnx/xcz/wfEnVmkrL+OxAJtnvO2r0VbCmq51sLRpOS2DrQJ9gs3PvZqWS47Nz60k7Kj9lcxSzc0PSMrDkxj+dEpcAsIiIi0kNFtY0d1i83m5bnJmrC7rK2s8xJH9yPEfLiPev73XqumZiG57x7sFXtwbXxwTav+0MRfvXGISZlJ3PZ9Nx27gAZLgf3L5mONxDhlhd30hhqCvTBw+8RNK04hp3arTGdiBSYRURERHogFIlS2hBgeAcdMppNy2mqkf30wj9rzUESd/4Z/9SriWR0UN/cieCYfPwTr8C16WGsFTtbvfbkhiOUe4Lccv44rJ20sxuflcSdl05mX4WHH/1zL1HTxFG6kR3mGEZkpnV7TCcaBWYRERGRHiitDxA1O+6Q0SzNZWd4WmKbOuakd+7EtCbiPeOW4x6D5+wfYyakk/LarWBGASip9/OnjYUsmpTFKcNTu7zHgrFDuOncsby2v5Ln171GZt023orOZGR69zZHOREpMIuIiIj0QOHRHsxdzTADTMtNYWdJfcuf7UXvkFCwBt+c/8R0ZR73GMzEdDwLfoi9YjsJ+5r2w3jwjUMA3HjOmJjv87lTh/HZGbmM3fUQXpz803k5iXa1AVZgFhEREemBotrOezAfa3qem3JPsGlxnRkl6V8/JZI8jMZZ1/d4HIEJnyWUNYOk9+9lc0EZr+6r5EtnjCDX3fW4mhmGwfdneLnQ+gGPhi4mfUjnuzKfLBSYRURERHqgsNZPgs1CZrKjy3On5R6tYy5tIGHfi9grtuOd919gi0PZg2HBe+b3sDYUcujVX5ObksA1pw3v9m1SP7iXSGIGb2UsY+6o9J6P6wTQfrNAEREREYlJUV0jQ1MTsRgdL6prNjE7GZvFYHdxDcs+/gXhIVMJTFwSt7GERpzNkbS5/HvNM2Sed223yynshf/CceRNPPN/xGOzF8RtXIOdZphFREREeqCozh9TOQY09T2emJ1MTsELWOsP4527Aoz4xbF6f4hba68g3fBwUf1funexaZL03s+IJOfROP2auI3pRKDALCIiInKcTNOksLYxpgV/zWZlO1jS8BTB7FMIjv5MXMfz2Lsf80FgBOUjL8O17XEsnuKYr3UUvIq9bBO+05aDLfa655OBArOIiIjIcappDNEYijI8xhlmgKXRNeQZVeyfehPEUMYRq0NVXp7dXMSSGXlYz/0emCauDffHdrEZJen9nxFOHY1/8lVxG9OJQoFZRERE5DgVNnfI6GJb7BYhH6cc+QPvRKbybnRa3MZR7w9x29/34HLY+Mb8UUTdI2ic8UUS9zyDtXpfl9cn7P8rtqo9+M64Faz2uI3rRKHALCIiInKcCmuP9mBOja0kw7nt99gDVfzGcnWbHf+Oly8YYfkLOzhc4+Puy6aQ7mrq1uGb821MexJJ797d+Q0iIVwb7iM8ZDKBCZfHZUwnGgVmERERkeNUVOfHAPJiKMkwAnW4Nj9CYNQFhHPntNnx73gEw1FufWknO0sbuPOSKa3awJnODHyn3kBCwVrsxe93eI/EPc9gqyvAO/e/4roA8USiT0VERETkOBXVNpKV7CDB1nWkcm5ZiSVQh3fud5mWl8LBSi+NochxPzscNblt9W4++LiWHyyeyPkT2u4U2DjzeiJJOSS9cyeYZjs38eP64JeEck6N+wLEE4kCs4iIiPS6usYQt/19N5XeYH8PpS0zSsLe57CVbur2pYW1/pg6ZBiNVTi3Po5/3KVEsqYxPS+FqAm7y45vljlqmtyxZh+vH6jilvPHcem03PZPtDvxnXEL9rJNOD56uc3Lzh1/wuotbdo8JY4LEE80CswiIiLS694pqGbN3gpe31/Z30NpxeIpJvWvn8f96nLca2+EaPdmfGPtwez68NcY4UZ8c28FPtnxb+dx1DGbpsn9rx1k9c4yvn7WKP7j1GGdnu+ffBXh9AkkvXsPRMMtx42gB9eHDxEcfjah4fO7PY6TiQKziIiI9LodxU3BcHtJfT+P5BMJ+18i/f/ysZduxD9pGdb6wzgK1sR8vT8UodIb7HKG2eIpwbnjSQKT/o1I+ngA0l0OhqYmHlcd88p3DvOXzcVcPWcY188b2fUFFhveef+NrfYgibv+r+Wwc+vjWPzVeOd9t9tjONkoMIuIiEivaw7K24rjE5i9wTAFVb7jutbw15Ky5gbca24gkjaO6n9fQ8PC+4ikjMC1ZWXM9ymqO9pSrosZZtfGB8GM4j395lbHp+emdLtTxlMfFvL4ex9z+fQclp87FiPGMorgmEWE8k7H9cH9EPJh+GtwbnmUwJjFhHNO6dYYTkYKzCIiItKr/KEI+yq8JCdYKaz1U+3reR3zyncO87k/fsjh6u6FZvuRt0n/Sz4JB1fjnbuC2iteIJo2Biw2Gmddj73kg5hrmZt7MA/vpAezpe4wibufxj/1c0TdrWeDp+WlUNYQ4LF3D/POR9Vdfi5/3V7KL18/xAUTM/le/sSYwzIAhoHnzNuw+spxbX0M16bfYAQ9TVtzS5ds/T0AERERObHtLfcQiZosnZHHnzYWsr24gXPHD+nRPTd+XEs4anLfawd58IrpXYfHcCNJ7/0M19bHCaeNo/bfXiKcPavVKf4p/4Frw/04tz5GQ+4jXY6hqK6pB/OwTkoykj74JRhWfHNubPPagrFDeGFrCSvfOdxyLDvZwaTsZCbnJDMpO4UpOclkJTtYv7+SO9fuY97odH5y0WSslu4v0AvnnUZgzGKcmx7BMMMEJi4lMmRyt+9zMlJgFhERkV61/WjZwZWnDOXpTUVsK67vUWCu94fYX+FlfJqFDQVVvHGgivPaaanWzFaxg5S138ZWsw/fjOvwnvk9sLcNuaYjGf+0q3FuWYm3/ghR94hOx1FU6yfJYSU1sf04Za3eT8K+F2ic+RWiyXltXh+Z7uS5L59Ogz/MvgoPe8o87Cn3sLfMw9uHqmluApfhslPvDzMjz83PL5+KI4YWdh3xnvk/pD99ARgG3jO+c9z3OdkoMIuIiEiv2lFSz1B3AnnuRCZlJ/d44d+BfTv4o/0uzvbvgEQIrrFhe92FaUsEWyKmNRHT7sS0JoLVgb34PaLODGov+19CI8/t9N6NM76Mc+vjOLf9Hu+CH3V6bmFdI8PTnB3Obrs2/ALT5sQ354ZO75OSaGPOiDTmjEhrOeYLRthf4WFveVOQNoHvnDcOp93a6b26Ekkfj2fB7WBYiKaO7tG9TiYKzCIiItKrdpQ0MGuoG4AZQ92s2lZCOBLFZu3mTGkkhHPLoyx8/378Fiv1s2+gvNFk7c4jzMlMYEa2AyPsxwg3QtiPEfFjhDz4J12B96zvYyamd/mIaMpQAuMuJXHX0/hOvxkzwd3huUW1fsZnJbX7mq1iB4kH/473tJswnd2fTXc5rMwalsqsYandvrYr/pnXxf2eJzoFZhEREek15Q0ByhoCTD8amGcOdfN/m4rYV+Fl6tFexLGwlX5Iyuv/ha1qD2/bz+J3yV/n5/MvIBXYEtjNL/dX8pfFp8W0iUhXGmd/jcT9L5K462kaT/l6u+dEoibF9f4OS0tc799LNCGVxtlf6/F4pP+pS4aIiIj0mh1H+wzPyEtp9c9Y28sZwQaS3/w+ac8vwQjUUb7ocb7k+U/GjBzbcs5N547FZrFw/2sH4zLmcPZMgkPn4dz2O4iE2j2nwhMgFDHbXfDnOLiahMPr8J3yTcyE+M8QS99TYBYREZFes6O4HrvVYGJWMgC57kSykx1sjyEwOw69TPpT55O4/UkaZ15HzedeY4N9LhETThn+SRDNSk7gK2eO5K1D1bx9qCou426c/XWsnmISDv2j3dc76sFsrTlIyrpbCGXPpnH2V+MyFul/CswiIiLSa3aU1DM5O7lVZ4eZQ92dLvyzeEpw//MrpP7zK5iJ6dQu+yves3+C6UhmU2EtVqOpFvpY/3HqMEZnOPnFawcJhKM9Hndw9AWE08bi3LISTLPN64W1TS3lWvVgDnpx//OrYHVQf+FKsCb0eBwyMCgwi4iISK8IR6LsKvMwPa91uJ0x1E1JfYAKT6DNNfYjb5P+1Pk4Dr+G58zvUXPlP1rtRLe5sI7JOSkkOVovw7JbLdy6cDyFtX7+d2NhzwdvWGic9VXs5Vuxl7zf5uXCWj9Wi0FOytHAbJqkvP5drLUHqF/0G6IpQ3s+BhkwFJhFRESkVxyo9BIIR5me13px38yjs8OfLsuw1h7C/crXiaYMo/pz62g89Vtgtbe8HghH2VHa0Koc41hzR6VzwcRMfv/+x5TU+3s8fv+kZUQT03FueazNa0V1fvLcCdiObiDi3PZ7Eve/hHfudwmNWNDjZ8vAosAsIiIivaJ5w5JPzzBPyk7GYTXYekxgNgL1uP/xZTAs1F3yRLs9gneU1BOKmB0GZoDl547FAB54/VDP34DdSeP0L+L4aA3W2tb3K6xtZHhq04I/W8kHJL3zUwKjFzWFfDnhKDCLiIhIr9hZUk+Gy06eu3Utr91qYUpOCtuLmwI10Qgpa27AWldA/YUribpHtnu/zYV1GMDsYR33Rs51J/LleSNZv7+S9wtqevweGqd/CSx2nFt/1+p4cZ2fYWmJGN5y3C9/g2jyMBo+80swFK1ORPqvKiIiIr1ie0kDM/Lc7e6EN2Oomz3lDQTDUZLeu5uEj1/Dc/YdhIad2eH9NhXWMT4rCXeivcNzAD4/Zzgj0hK5d/0BQpGeLQA0k7LxT1xK4p6/YPibAniDP0ydP8xwtw33mm9hCdZRd9FjaiF3AlNgFhERkbirbQzxcU1jm/rlZjOHuglFTGo3PoVr829pnP4l/NO/0OH9QpEo24rrObWTcoxmDpuFW84fz+GaRp7+sOi430OzxtlfxQj7ce74M9C0JTbAReWP4Sh+j4bz7iGSObXHz5GBS4FZRERE4m5n84YlQ9svn5gx1M1s4wCTNv2Q4LAz8Sy4vdP77SnzEAhHYwrMAPPHZnDOuCE8/t5hyhvaduPojsiQyQRHnEvi9icgEqCo1s+Flg1MPvxHGqd/kcCkZT26vwx82hpbRERE4m5HcT0WA6bktD/DnG1W8VjCL6mxZGAsfrRVN4z2bCqsA2B2jIEZ4ObzxvLvf9jIN57ZyrBUJw6bBYfVQoLNIMFmbfPnBWMzGJeZ1O69fLO/RtrfPk/Cvpfwludxr/1RAtmz8Sz4UczjkcFLgVlERETibkdJA+Myk3A5rG1fDDfi/udXiBh+ruUHPJiYTtsq59Y2F9YxOsNJhssR8xiGpzn5weJJvLi9BG8wTLUvSiAcJRhp+mfzv4ciTRuTPPH+xzx61Swm5SS3uVdoxDmEMybh2vIol3j8hA0bQW1OctJQYBYREZG4ipomO0rrWTQpu+2LpknK+hXYyrexZvLPeW9LLqUNAfLciW3PPSoSNdlSVMfiye3crwsXTsnmwimdXxeJmpTU+/nGM9u48fntrPyPWYzOcLU+yTDwzf4a7vW3kI2FHyb/hOXanOSkoRpmERERiavD1Y14AhGmtbPgz7n5NyTufxHf3O/inn4p0HYDk0/bX+HBG4x02n+5J6wWg+FpTn69bAYA//ncdkrb2fgkMHEJwaHzeMB6HVVZ83plLDIwKTCLiIhIXG0vaQrAMz61YYnjo7UkvXsP/vGX45vzn4zPSibRZmFbF4G5uX65twJzs1EZLh5aNgNvMMwNz22nyhtsfYI1gcrLn+HXvgsYntrxjLiceBSYRUREJK52ljSQnGBlVIaz5ZjFW0rK2hsJZ82gYeEvwDCwWQym5aV0GZg3F9YxLDWRnJTerxeelJ3MA0unU94Q4Mbnt9PgD7d6vaQ+QNSEYWkKzCcTBWYRERGJq+0l9UzPdWM5ZsMSe9F7WEIePOfdA/ZPgvSMPDf7Krz4Q5F27xU1TTYX1vX67PKxZg1L5d7PTuWjKh/LV+2g8ZixFdY29WBu3hZbTg4KzCIiIhI3vmCEg5XeNhuW2Cp3YlochIdMaXV8xlA3kajJrrKGdu/3UZWPOn+4TwMzwLzRGdx5yWR2lNTz3Zd2EQw37RhYVNdU26wZ5pOLArOIiIjEze6yBqImTP/UhiW2yp2Eh0xq02955tE65+3F7QfmzUfrl2PdsCSeFk7M4rZFE3nvcA0/+McewlGTwtpGEmwWMpNib28ng5/ayomIiEjcNHe8mJZ7zAyzaWKr3Elg9GfanJ/msjMy3dlhp4xNhXVkJzsY1k+L7C6fnos3GOH+1w5y55p91PvDDEtNxDC66hwtJxIFZhEREYmbHSUNjEx3kub8ZCbZ4ivD0lhFOHNau9fMGOrmnUPVmKbZKoiaR+uX54xI7deA+rlTh+Hxh1n57mEsBswfk9FvY5H+oZIMERERiQvTNJsW/H26frliJwCRDgLzzLwUahpDLfXBzQpr/VR6g/1SjvFpXzlzJJ87dRhRs2kHQTm5aIZZRERE4qKkPkC1L8T0vE/XL+8CIJw5td3rZg5tCsTbiutbhdFNhbUAnDI8rTeG2y2GYbD8vLGMSHcyd1R6fw9H+phmmEVERCQudrRsWNJ6htlauZOIexSmo+3OfwBjhrhIcljb9GPeXFhHutPO6IyBMaNrMQyunD2UkekDYzzSdxSYRUREJC52lDSQYLMwPjOp1XFb5U7CWe2XY0DT1tTTcttuYNLcf1kL7KS/KTCLiIhIXOwoqWdqTjI26yfxwgh6sNYVdLjgr9nMoW4OVnrxBpt21iut91NcH+jz/ssi7VFgFhERkR4LhqPsKfe0qV+2Vu3GwOwyMM8Y6iZqwq7Spn7Mm472X1ZgloFAgVlERER6bF+Fh1DEbHfDEuh4wV+zGUeDdnNZxubCOlISbG3KO0T6gwKziIiI9Nj2kqaZ4U8v+LNV7iSamE40Ka/T61MSbYwZ4mrZ8W9TYR2zhrmxWlS/LP2vy8AcCARYtmwZl19+OZdccgkPPvggAEeOHOHKK68kPz+f5cuXEwwGAQgGgyxfvpz8/HyuvPJKCgsLW+716KOPkp+fz+LFi3nrrbd66S2JiIhIX9tRXE92soOs5IRWx22Vu5rKMWJYuDczz832knoqPQE+rmkcEP2XRSCGwOxwOHjyySf561//yosvvshbb73Fli1buO+++7j22mtZu3Ytbreb5557DoBnn30Wt9vN2rVrufbaa7nvvvsAOHDgAKtXr2b16tU8/vjj/PjHPyYSifTuuxMREZE+saOknhmfKscgGsZWtafL+uVmM4e6qfeHeXF7KYACswwYXQZmwzBISmqqHwqHw4TDYQzD4L333mPx4sUALF26lHXr1gGwfv16li5dCsDixYt59913MU2TdevWcckll+BwOBgxYgSjRo1i27ZtvfW+REREpI9UeYMU1wfaLvirOYgRCcQcmJsD9182F+O0W5iUnRz3sYocj5hqmCORCJ/97Gc566yzOOussxgxYgRutxubrWmjwNzcXMrKygAoKysjL6+pTslms5GSkkJNTQ1lZWXk5ua23DMnJ6flGhERERm8dnRSvwzEHJhHZThxJ9qobQwxc6i7VXs6kf4U09bYVquVl156ifr6em644QYOHTrU2+MCmsqd0tJcffIskd5itVr0PRaRASeev00HagqxWQzmTswm0W5tOW7x7MO0JpAyZgZYYoocnDIijTf2V3LW+Cz9dsqAEdu39yi3283cuXPZsmUL9fX1hMNhbDYbpaWl5OTkAE0zxyUlJeTm5hIOh2loaCA9PZ2cnBxKS0tb7lVWVtZyTUdME2prfcfxtkQGjrQ0l77HIjLgxPO3aeNHVUzISsLvDeA/5nhq4RaiQyZTWx8EgjHda0p2Em/sr2RKpn47pW9lZbW/dTvEUJJRXV1NfX1TT0S/388777zDuHHjmDt3Lq+88goAq1atYuHChQAsXLiQVatWAfDKK68wb948DMNg4cKFrF69mmAwyJEjRygoKGDmzJk9fnMiIiLSf8JRk12lnpY+yi1Ms2lL7C76L3/a5dNzuX7eyLYLCEX6UZczzOXl5fz3f/83kUgE0zS58MILOf/88xk/fjw333wzDzzwAFOmTOHKK68EYNmyZaxYsYL8/HxSU1P55S9/CcCECRO46KKLuPjii7Farfzwhz/EarV29mgREREZ4N4vqMEXijBnZFqr4xZvCRZ/Tcz1y82ykhP4xvzRcRyhSM8Zpmma/T2IjkSjJlVVnv4ehkiPqCRDRAaieP02rXhpJ1uL6ln99bnYj1mk5yh4ldTV11JzxYuE807r8XNEeluPSjJERERE2lPpCfDWwSoum57TKixDU4cME4PIkMn9NDqR+FFgFhERkePyt51lREz47Iy2217bKncSSR2N6VAvZRn8FJhFRESk26KmyYvbSzltRCoj051tXrdV7Ox2/bLIQKXALCIiIt32weFaiuv8LGlndtkINmCtP0xEgVlOEArMIiIi0m0vbi8hNdHGeRMy27xmq9wF0O2WciIDlQKziIiIdEu1L8jrB6q4ZFoOCba2UcLavCV2lmaY5cSgwCwiIiLdsnpnGeGo2W45BjQt+Is6hxB1db6jr8hgocAsIiIiMTOPLvabNdTNmCGuds+xVe4inDkdDKOPRyfSOxSYRUREJGabCuv4uKaRpTPbn10mEsJWtVf1y3JCUWAWERGRmK3aVkJygpULJrZd7AdgrT2AEQ2qpZycUBSYRUREJCa1jSHW76/k4ik5JNqt7Z5ja17wp8AsJxAFZhEREYnJP3aVEYqYLJmZ2+E5topdmLZEImlj+3BkIr1LgVlERES61LzYb1puChOyOt7u2la5k3DGZLC0PwMtMhgpMIuIiEiXthXX81GVj6WdzC5jmtgqd6gcQ044CswiIiLSpVXbS3HZreRPyu7wHIunGEugThuWyAlHgVlEREQ61eAP8+reCi6cko3L0XGphRb8yYlKgVlEREQ69c/d5QTC0U4X+0FTYDYxCA+Z0kcjE+kbCswiIiLSoabFfiX8P3v3HR9Vlf9//HWnTyaZTHqFAKH3jhQRUFBBFBtr3RV1LWv9qrtr+6lr113L7rq6oru2tawNsIBSpCO9t5AAISSkJzOTTJ+59/dHXDSSikCAfJ6PB4/onXPvOTOEe9+5OfdzeiRH0yslpsm2hoodddUxjA2vACjEqUoCsxBCCCEatbOkhtxyT9MP+/2gbklsmY4hTj8SmIUQQgjRqFnbSrAYdJzbs/GH/QCUgAu9u0CWxBanJQnMQgghhGiQJxhm/u4yJvZIItpsaLKtoXIXIA/8idOTBGYhhBBCNOjb3eX4QioX909rtq2hfDsggVmcniQwCyGEEOIIwbDKp5sPkZ0YRd+0ph/2g7r5y6o1Cc3W9NQNIU5FEpiFEEIIUU9E1Xhk3m5yyz38dmQWiqI0u4++YocsWCJOWxKYhRBCCHGYpmn8+bs8Fu2p4O6zunB296Tmd4oEMVTtkekY4rQlgVkIIYQQh73x/QE+21LM2uIeMgAAIABJREFUr4d14OqhmS3aR1+dh6KGJDCL05YEZiGEEEIA8PGmQ7zxfQEX9k3h9jM7tXg/WRJbnO4kMAshhBCC+bvL+Mt3eYzNTuCBid1bNG/5fwwVO9AMViKxnY7fAIVoQxKYhRBCiHZuTX41j87LYWCGnaem9MSga3lYhrrAHE7oBTr9cRqhEG1LArMQQgjRju0oqeH3X+ygc0IUL0zri8XYytCrabIktjjtSWAWQggh2qn8Si93fbaNuCgTf7ukLzGWplfza0jUuhfRBVyE0ocfhxEKcXKQwCyEEEK0Q8UuP7d/tg29TuGVS/uRGG1u9TEsOz/Etu4l/D2nE+g27TiMUoiTQ+t/lBRCCCHEKc3pC3HLJ1upDYR5ffoAOsRZW30M04HviF5yP8EOZ1Ez7jloxUOCQpxqJDALIYQQ7cxT8/dQUOXl75f2o0dKdKv3N5Rvw/7NLYQTeuI+73XQG4/DKIU4eciUDCGEEKIdCYZVvs+v5ophHRjSwdHq/XXug8R++WtUSxzuC95FM7U+cAtxqpE7zEIIIUQ7sq3YTSCsMrpLYqv3VfzVxH55DahBXNM+RrWlHIcRCnHykTvMQgghRDuyrsCJToFhneJat2PYT+zc69G7D+Ke/G8i8d2OzwCFOAlJYBZCCCHakfUFTnqlxGC3tmLesaZiX3gXxuJ11JzzV0LpI47fAIU4CUlgFkIIIdoJbzDC9pIahnZs3dxl28onMO/9mtrRjxDoNvU4jU6Ik5cEZiGEEKKd2FzkIqJqDGvFw37WzW8QteUNvP1vwDfgt8dxdEKcvCQwCyGEEO3E+gInBp3CgAx7i9qb8r7CtvJxAtmT8Yx+RGoti3ZLArMQQgjRTqw/6KRfuh2LUd9sW33lbuyL7iacOgT3OX8FXfP7CHG6ksAshBBCtANuf4jdpbUtm44R9GD/9hZUkx3X+W+AofUrAQpxOpE6zEIIIUQ7sPGgCw1a9MBfzLKH0FfvxXXRR2hRScd/cEKc5OQOsxBCCNEOrD/oxGzQ0Tctpsl25l0fY8n5FO+wuwlljj5BoxPi5CaBWQghhGgH1hY4GZQRi1Hf+KVfX7WHmGUPEcwYhXfo3SdwdEKc3CQwCyGEEKe5Ck+Q/ZVehjU1HSPkxf7NLWhGGzUT/y4P+QnxEzKHWQghhDjNbShwAk3PX45e9v/QV+fiuvB9VFvKiRqaEKcEucMshBBCnObWHXQSbdbTIzm6wdfNOZ9i3f1fvEPvJNRh7AkenRAnPwnMQgghxGlufYGTIZkO9LojFx7RV+cRs+RBgukj8A77vzYYnRAnPwnMQgghxGnskMtPkcvf8HSMkA/7NzejGSzUTHwFdDJTU4iGyL8MIYQQ4jS2/mDj85ejVzyCoSoH5wXvoUanneihCXHKkDvMQgghxGlsfYGTOKuR7ISoetuV7Z9i3fkh3sG3Ecoa30ajE+LUIIFZCCGEOE1pmsb6g06GdnSgKD/OX9Y796Gfdw+htGF4Rvy+DUcoxKlBArMQQghxmjpQ5aO8Nlh/OoamEfPdvaA34Z70D5m3LEQLNBuYi4uLufbaa5k8eTJTpkzhnXfeAcDpdDJjxgwmTZrEjBkzcLlcQN1Ps08++SQTJ05k6tSp7Nix4/CxZs2axaRJk5g0aRKzZs06Tm9JCCGEEFBXTg5g+E8Cs7F4Lcbidahn/hE1Or2thibEKaXZwKzX67n//vuZO3cu//3vf/nggw/Iy8tj5syZjBw5kvnz5zNy5EhmzpwJwLJly8jPz2f+/Pk88cQTPPbYY0BdwH7llVf4+OOP+eSTT3jllVcOh2whhBBCHHvrC5ykxpjJiLUc3mbd9E9USxzqwKvbcGRCnFqaDczJycn06dMHgOjoaLp06UJpaSmLFi1i2rRpAEybNo2FCxcCHN6uKAoDBw7E7XZTVlbGihUrGD16NA6Hg9jYWEaPHs3y5cuP41sTQggh2i9V09jws/nL+qo9mPMX4Ot3HRijmtxfCPGjVs1hLiwsZNeuXQwYMIDKykqSk5MBSEpKorKyEoDS0lJSU1MP75OamkppaekR21NSUigtLT0W70EIIYQQP5Nb7sHlDzPsJ9MxrJtfRzNY6gKzEKLFWjzT3+PxcOedd/Lggw8SHV1/aU1FUeo9fXusKAo4HPITsDi16fU6+T4WQpxwO3bU3ZQa3ycNR6wFaoox5HyOOug3xKZ1kHOTEK3QosAcCoW48847mTp1KpMmTQIgISGBsrIykpOTKSsrIz4+Hqi7c1xSUnJ435KSElJSUkhJSWHt2rWHt5eWljJ8+PAm+9U0cDq9rX5TQpxMHI4o+T4WQpxwy/eU0zHOilVTcTq92Fa9gkGL4Ow1A9XplXOTED+TlBTT6GvNTsnQNI2HHnqILl26MGPGjMPbJ0yYwOzZswGYPXs2Z599dr3tmqaxefNmYmJiSE5OZsyYMaxYsQKXy4XL5WLFihWMGTPml743IYQQQvxMOKKy8aDr8HQMJViDZcd/CGRPQY3NauPRCXHqafYO84YNG5gzZw7du3fnoosuAuCee+7hpptu4u677+bTTz8lPT2dl19+GYCzzjqLpUuXMnHiRKxWK08//TQADoeD3/3ud1x22WUA3HbbbTgcDaxrL4QQQohfZGdpLd5QhKEd6q6zlh3vowvW4Bt0SxuPTIhTk6JpmtbWg2iMqmpUVta29TCE+EXk155CiBPt36sLeG1lPvNvPYM4M8S/N4qIowuuaR8fbiPnJiHq+0VTMoQQQghxfKiaxvZiN+oxvne17qCTbkk24qJMmHPnoPeU4B106zHtQ4j2RAKzEEII0UY+3nSIGR9s5p21B4/ZMQNhla1FP8xf1jSiNv2TcEJPQh3HHbM+hGhvJDALIYQQbSAcUXl/fSF6Bf65Mp81B6qPyXG3HXITjGgM7eDAdOA7DFU5eAfdUlerVQhxVCQwCyGEEG1g4Z4KSmoC/On8nnSKj+Lhr3dT4vb/4uOuO+hEr8CgzFism14jEp1OoOtFx2DEQrRfEpiFEEII6sqonqjn4DVN4911B+kcH8XEnkk8f2FvQhGVP365i2BY/UXHXl/gpFdqDA7nNkyHVuMb8FvQG4/RyIVonyQwCyGEaPc0TeOGDzfz/+buPiGhee0BJ7nlHq4ZlolOUciKj+LR83qws6SGF5fsPerjeoJhdpTUMLSDg6hN/0Q12fH3vvIYjlyI9kkCsxBCiHZvT7mHbcU1fLu7nPm7y497f++uO0iizcR5PZMPbxvfLZFfD+vAZ1uK+XJ7SRN7N25zkZuIqjE2wY1p71z8fX+NZoo+VsMWot2SwCyEEKLdm7ezDINOoWdyNM9/l0dFbeC49bW7tIa1BU6uHJyByVD/MnzrmE4M7RDLc4vyyClr3ToETm+IjzYWYdQrDC/9EHRGfP1nNL+jEKJZEpiFEEK0axFV49vdZYzuHM8TU3oSCKs8vSC30akZ+qpcDCUb0Dv3ofiqQA23qr/31hViM+m5ZEDaEa8ZdApPXdCLWIuBP3yxE7c/1OzxNE3jqx0lXPbWOtYVOLlnuB1bzif4e16Kaktp1diEEA1rdmlsIYQQ4nS2/qCTCk+Q83sn0yk+it+N6cRLS/bx9c5SLuiT+mNDNULUupewrX/5iGOo5lg0swPV4kCzOFDNDlRbKr6BN9ULrUUuH4v2lHPVkEyizQ1fguOjTDw7tTc3/XcLj8zN4cWL+2Aq3YhlxwdE4roQTh5IOKkfmtnOgSovzy7MZf1BF/3S7Dw4sRv9970KkSC+gbIMthDHigRmIYQQ7dq8naVEm/WM6ZIAwK8GZbA4t4IXFu9lWMc4UmLMKP5q7Atux1SwFH/P6fi7TkXnr0YJOOu++uu+6gJOFH81Rmc+utpDGAtX4Lr4s8PziD/cUISiKFwxOKPJMfVLt3PP+GyeX5TH7CXL+e3eW1EiAZTwj2XnKs0dKPJ1ZKiSzTXDz2TkiKHoFLBue4dg50lE4rKP34cmRDsjgVkIIUS75QtFWJxbycSeSZh/mE+s1yk8cm4Prnp3A0/O38OrY1Riv70ZnaeMmnHP4u99dYsWATEd+A771zOImf873JP/jdOvMXtbCef1SiY5xtzs/pcNSGN/4UHO3f47QhYdtVd+h2aKIX/HKjatX0qWN4expt1cFFkJW99F26ZDtaWiCzhlGWwhjjEJzEIIIdqtZXmVeEMRzu+VXG97hzgrd4ztTMHSN7F/9g7YknBe8jnhlIEtPnYwawK1Y58kZukDRC9/lDeMvyUQVrlmaGaL9lfUIE8EnkOnq+KG4CPc6I3jk1WH+GpHDOmxl/HHqV0Jd46n0lOCoWwrhrItGMs2E+x4FuG0oa36HIQQTZPALIQQot2at6uMlBgzgzJj678Q9nF91YtYjf9lpdofx/lvkpyc3urj+/tei96VT9Tm1zGiMKbLFWQn2prfUdOIWfwHLCVr2T/qRTatzOA3729Cr1O4bngHbjijIxajHgDVlkqwcyrBzpNaPT4hRMtIYBZCCNEuVXmDrM6v4pphHdD9ZIqFzl2A/ZubMZZvo7Tvbdy8ZQw9l1bwj8vS6rVrKc+ohyg5uId7K95hS+YgoG+z+0Rt+BuWnM/wDL+P6EHTeTaumlnbirlxZBZdWxK4hRDHlJSVE0IIcUryBMMcqPIe9f4LdpcT0ag3HcN04DviPj4fvesArslvoTvrAe4Y15X1BU4+21J8VP1ENIUba24i19CNgRv/iKFsS5PtzblzsK35M/4el+IdehcAIzrF8ezU3hKWhWgjEpiFEEKcVBRfFeacT0FTm2z3wnd7uerdDRQ6fUfVz7xdZXRPstVNkdA0otb/FftXv0GNzqB6+lyCnScCcHG/VM7IiuNvS/cdVV+LcyvY59bYNeY1VGsSsV9dh85d2GBbQ8kGYhbdQzBtBDXjn2/Rw4VCiONPArMQQoiTSszi32NfeDfmvC8bbePyhZifU04wovHi4r2t7uNAlZcdJTWc3zsF1AjRS+7HtubPBLpfTPWlc1BjOx1uqygKD03qhl6n8Pg3OaiNLGjSEE3TeG99IR3jrJzRuzuuC96BSIDYr3+DEnDXa6tzFxA793oi0Wm4J78J+uYraQghTgwJzEIIIU4apvxFmPd/i6Y3E7XmzxBpeKW7r3aUEgirTO6dzPJ9VazcV9WqfubtKkMBzutmx/7tzVh3vo938O3UnPNXMFqPaJ9qt3DP+Gw2Fbn5aGNRi/vZWOhiZ0kNVw/JQK9TiMR3x33+G+ide7F/c/Ph96cEXMR+9RtQw7invINmiWvV+xFCHF8SmIUQQpwcwn6ilz9C2JGNe+LfMLjyseR8ckQzVdP4fGsx/dLsPDypO1lxVl5YnEcw3PQUjv/RNI15u8oYm2kk+7vrMe/7htoxj+EZeX+TUyCm9klhTJd4Xl2Rz9K8CrzBSLN9vbvuIPFRRib3/nG1v1DmaGrGPY+pcDnRSx+ASAj7t7eid+3Hff4bsuCIECchCcxCCCFOClGbXkPvPkDt2KcIdplMKGUwUetegp+sbgewvsBJQbWPywamYdTruG9CNgedft7f0PC84J/beshNyFXCi76HMJasxz3x7/gG3Njsfoqi8ODEbkSbDdw3ZycT/rGK6z/YzKsr9rPmQDX+UP0AnVfuYdX+an41KONwCbj/CfSajmfoXVh3fUTcJ5MxHVxGzbjnCGWMatF7EEKcWPrHHnvssbYeRGM0DXy+YFsPQ4hfxGIx4vc3/GtlIU5mqqbx+qoDKAqkx1oabad4K3B8fgma3kgkqfmSaQ3RuQ5gn38bgewp+AbfCopCxN6RqG1voVnjCacOPtz2b8v2U+UN8vC5PTDoFDIdVvIqPHy5vYTJvZOJNjddMfXLFat5quYBUrRy3Of/i2D2+S0ep81k4NIBaQzOjCUx2swht59FOeV8vbOM/6wvZE1+NYdcfhQFPtpYxCGXnycm9zwiMAOEMkahd+7HVLgC7+Db8Q26peUf2DEg5yYh6rPZGn9uQNG0Vjy9cIKpqkZlZW1bD0OIX8ThiMLpPPrSV0K0lffWHeRvy/bTMc7KJzOGNlqDOHrJA1h3vIemM+Ca+j6hzNGt7sv+9XUYi76n+qolqNFph7fHzrkCQ+Uuqq5ZiWaKprw2wNSZa7hicCZ3j+tyuN0hl5/pb6/nzC4JPDO1V+MdlWxB99lVmHUaoYv/Uy+IHy1PMMzmIjcbCpysP+gkp6wW9Ycr6xWDM7h3fBNTLCJBjCXrCaWfAcqJ/aWvnJuEqC8pKabR12RKhhBCiCPsKHbzjxX5ZMRaKKj2saKRh+r0VXuw7PwAX89fEYntgv2bm9A797WqL9P+BZjzF+Iddk+9sAzgGfEHdL5KrFv/BcDsbSVENLhkQP126bEWfjO8Awv3lLOuoLrBfoyFK3HMno5PM7J69HvHJCxD3V3n0Z3jufOsLrx7zWAW/m4UL0zrw02jsrhhRMemd9ab6qZhnOCwLIRoHfkXKoQQop7aQJgHv95NcrSJt64aSGqMmffXNzw/2LbqKTSjDc+oh3BNeQsUPfavr0PxO49om1fh4ap3N7Cj+Cfl1EK+ugf94rrj63/9EfuEUwcT6Hwu1k2vE/FWMXtrMSOyHHSMO7KSxbVDM0mPtfDn7/YSjtR/ANCU9xWxX15LmS6RG5Qn6dNnUCs/lZaLsRgYm53Ab0dm4YgyHrd+hBAnjgRmIYQQh2maxlPz91Dq9vPklF7ERZm4YnDG4fJoP2U8uALzgUV4h9yBZo1Hjc2qK5nmPoj921uOKAn36vL95JZ7eGL+nsOBNmrjK+hrDlJ71pOgbzhcekbchxKsoXrJy5TVBrl0QHqD7SxGPfeMy2Z/pZePNx/6cfuO97F/eyuBxH5M8z7MwF49Mejl8ieEaDk5YwghhDhs9rYSFu6p4JbRneifbgfgon6p2Ez6+neZ1QjRKx8nEtMBX/8ZhzeH0kdQM+45TIUriF7xaN3T28D2YjfL91UxIsvB3gov/1lfiM65n6iNr+HvfnGT1SEiCb0IdJ9Gl/3v08vm4czshEbbjs2OZ1TnOGauOkCFJ4hlx3+IWfJHgh3H8WG3lymP2OothS2EEC0hgVkIIQQAeys8vLB4L8M7Ovj18A6Ht0ebDVzcP41Fe8opdteVeDPnfIahcieekQ+AoX4FjUCv6XgH3Yp1+7tYtr0NwD9X5uOwGnn+wj6M75bIm6sPYPzuITSDGc+oh5sfW4/b0Glhnoj7BoOu8VrJiqJw7/iuBCMqG79+hZgl9xPImoB78pt8tcdNxzgrvVMbf7BHCCEaIoFZCCEE/lCEB7/ahc2k50+Tex5REeNXg9JBUepWuQt5sa15jlDKIAJdpzZ4PM8Z9xPoNInoFY+Sv+Fr1hxwct3wDkSZ9Nw3PptzdeuxFy/DM+xeVFtKg8f4qY/2m/hEHcfgqi/QuQ822bZjnJU/d97ClWUvUZE8Bvd5MynxaGw46OK8XskoTSxOIoQQDZHALIQQghcW72VfpZfHz+9Jos10xOupdgvndE9kzrYSDOtfQ+8ppXb0o42vjKfT4574d8LxPem95v8YGlXGpT9Utki2RHjK8h92qR34wji52bEFwipfbC9hXeYNKIoO27qXmmxv3v0JFxU+x1pdf67z3U1EZ+bb3eUAMh1DCHFUJDALIUQ7N393GbO3lfCb4R0Y0Smu0XbXDM0kKliBbfM/CWRPIZw2tOkDm2wsHfASXtXIv0x/xhqpq45hW/83YoKl/Nt+Gy8sO4DL1/TiGYv2lOPyhzl7SD98/a7DnPMp+qrcBtuacz4lZtE9hDLHkH/Wa2wvDzJrazFzd5bSL81OpuPI6hpCCNEcCcxCCNGOFTp9PL0gl35pMdwyKqvJtj1TYnjG8QWKGsI1/I/NHlvTNF7cGOQB4/3YQxXY592IvnIX1s2v4+95OdPOn4bLF+KV5fubPM5nW4rp4LAwrKMD7+Db0AxWbGv/ckQ7c87ndWE5YxSuyf9mQu8ODOkQy1+X7mNfpZfze8vdZSHE0ZHALIQQ7VQoovLw17tRFHhySq9mS63pK3dxtn8B74Qn8k2prdnjL9tbxc6SGkaOmkjNhL9gOrQGx2fT0AxWakc+SPfkaK4aksnsbSVsKnQ1eIzc8lq2HnJzyYB0dIqCZo3HN+C3mPd+jaF82+F25j2ziVl0N6H0EbimvA1GK4qicN+EroQiKnqdwsTuSa36fIQQ4n8kMAshRDv12op8dpTU8P8mdSc91tJs++iVT6KZY5gTcyXvry9C+6FkXENUTeP1Vfl0cFiY3CeFQPeL8Qy9C13Ig+eMP6BF1YXX347KIs1u5pkFuYR+ttgI1N1dNukVLujz44OBvoE3oZodRK1+HgBz7hfELLyTUNowXFPeAeOP0y66Jtq4Y2wXrhveQRYREUIcNQnMQgjRDq3aX8V76wu5dEAaE1pw59V4YDGmg0vxDvs/Lhzai5yyWtYfPHI1v/9ZtKeC3HIPN43qdLgMnHf4fVRdsQB/398cbmc16vnjOd3YX+Xl3XX1q194gmHm7SxjYo8kHNYfw65mtuMdfBvmgsXYVj1FzII7CKcOxTXlXTBGHTGWq4dmcsvoTs2+RyGEaIwEZiGEaGc0TePFxXvpnBDF3Wd1aX4HNUz0qieJ2LPw9f015/dOIT7KyPvrixpsHlY1Xl+ZT5eEKCb2+EkYVxQiCb2OqKwxunM853RP4t+rCyio9h3ePm9nGd5QpMGV/Xz9riMSlULUptcIpw7GdcG7YGp+mogQQhwNCcxCCNHO7CnzcKDaxxWDM7AY9c22t+z6L4aqHGpHPQh6E2aDjssGprNyfxX7K71HtP92VxkHqn3cPLoT+iYWGfmpe8d3wWTQ8czCXDRNQ9M0PttSTPckG33TGlhoxGildtwz+LtfjOuCd9FM0S3qRwghjoYEZiGEaGfm55SjV2BC18Rm2yrBWmxr/kIobTjBLj/WTL58QDpmg473NxTWax+OqMz8/gA9kqMZ37XxJax/LjHazO1ndmZ9gZO5O8vYeshNXoWHSwemN7rQSLDzJGom/h3NJCv3CSGOLwnMQgjRjmiaxsKcMoZnxbXoITjrptfQ+cqpHfVwvakUjigjF/RJYe7OUio9wcPbv9hRyiGXn1tHd2r1inoX90+jX5qdl5bs5e21B7GZ9JzXU0rBCSHangRmIYRoR3aU1HDIHWBSz+Yf9FMCLqI2z8Tf9ULCqYOPeP3KwRmEIxqfbD4E1K3I96/vD9Avzc6ozo0vgNIYnaLw4KRu1AYjrNhXxeTeKUSZmp8yIoQQx5sEZiGEaEfm7y7HqFcY14LpGJZdH6OEffgG/67B17PioxibncCnmw/hD0WYtbWYstogt47JavXd5f/pmmjj18My0SkcXkpbCCHamgRmIYRoS2E/xoKloB1Zg/hYUzWNhXvKGdUpnmizoenGmop129uE0oYRTurbaLOrh2bi8of5dEsxb60pYGhHB8M6tv7u8k/dMroTn8wYRnaiVL0QQpwcJDALIUQr+UORJhftaDFNxb7wThxfXo3t+2d++fGasbnIRXltsH6pt0aYDixG7z6Ar9+MJtsNzLDTOzWGvy/bR5U31Ozy2i2hUxQ6xlmbbyiEECeIBGYhhGgFXyjCBTPX8PLSfb/4WLbVz2LeO5dQUj+iNr2GZcd/jsEIGzd/dzlmg44zs5uvXmHZ9jaRqBQCXc5vsp2iKFwzNBNVq6unPCAj9lgNVwghThoSmIUQohW+31+Fyx/mgw1FrNhXedTHsez8kKiNr+Lrcw3Oy74k0HE80UsfqpuecRyEVY3v9lRwZpeEZh+k0zv3YS5YjL/vNaBvvpLG+G6JzBjRgXvHZx+r4QohxElFArMQQrTC4rxKYi0GuiXZ+NM3e6ioDbT6GMbClUQvfYBgh7OoPfMJ0BmoOfc1IvHdsX9zM/rK3cd83BsKnFT7QkxsQXUMy/Z30XRGfL2vbtGxDTqF343pTAeZRiGEOE1JYBZCiBYKRVRW7KtkbHYCT03phS8U4dF5OaitmM+sr87D/s1NRBzZuM997fAdXM0UjeuCd9BMNmK/+jU6T+kxHfuCnHJsJj2jOjXzQF7Qg2XXfwlkT0azSQ1kIYQACcxCCNFi6w86qQ1EGNctkc4JUdw3Ppu1BU7+s66w+Z0BxVdJ7Fe/AZ0R15S30cz2eq+r0em4p7yDzu/E/vUMCB257PTRCEVUvsutYGx2QrNLYVv2fI4uWIOv//XHpG8hhDgdSGAWQogWWpJbidWoY0RW3V3ai/qlcnb3RF5dmc+OYnfTO4f9xM67EZ2nBNfkf6HaOzTcLKkv7nNfxVCxHfuCO0CN/OJxr86vpiYQbn6xEk2rKyWX1I9wypELlQghRHslgVkIIVpA1TSW7q1kVOd4zIa6U6eiKDw4sRtJNhMPz91NbSDc8M6aRsx392EsXof7nL8STh3SZF/BTudQO+ZPmPd/i23Vk7947AtyyrFbDIeDfmOMRaswVOXUlZI7yoVHhBDidCSBWQghWmDbITeVnuARK+TZLUaenNKTQy4/zy/Ka3DfqHUvYsmdTe0Z9xPsekGL+vP3n4G3/w1EbXkDy7a3j3rc/lCEpXmVjO+aiFHf9Cnfuu0tVEscgW5Tj7o/IYQ4HUlgFkKIFliSV4lBpzCmS/wRrw3IiOXGkVnM21XG3J31H9Yz53yGbd1L+HtOxzf4tlb16Rn9CIFOE4le/gim/EVHNe5V+dV4Q5Fmq2Poaoow7Z+Pv/dVYJBqF0II8VMSmIUQohmaprEkr4JhHR2NLil9/YiODMqw89zCPA5W+wAwHlpDzHe/J5gxkppxz7Z+moNOj3viK4QT+xAz/3foy3e0euwLdpcRZzUypIOjyXbW7e8C4Otzbav7EEKI050EZiGEaMbeCi+FTj/juiU22kavU3h8ck8MeoWH5+5GdRZgn3cjEXsm7vNmgt50dJ2bbLgSmtszAAAgAElEQVSnvIVmthP79a/RO1u+wqA3GGH5virO7p6IQddEWA/7sez8gGCniaj2zKMbpxBCnMYkMAshRDMW51WgAGc1s6R0qt3CQ5O6s6ekmuDnvwU1jHvK22iWZmofN0O1pXLg7H8TCgaJnXUZ+uqG50r/3PK9lQTCKpN6Nl1P2Zz3JTp/tZSSE0KIRjQbmB944AFGjhzJBRf8+KCK0+lkxowZTJo0iRkzZuByuYC6X1s++eSTTJw4kalTp7Jjx4+/Ppw1axaTJk1i0qRJzJo16zi8FSGEOD6W5FbQP91Ogq35u8QTuiUyM20uHXw72NTnESKOLr+4f7c/xA0LAkytfQBPIETsrMvRV+Y0u9/8nHKSo00MyLA33kjTsG59i3Bcd0IZo37xWIUQ4nTUbGC+5JJLePPNN+ttmzlzJiNHjmT+/PmMHDmSmTNnArBs2TLy8/OZP38+TzzxBI899hhQF7BfeeUVPv74Yz755BNeeeWVwyFbCCFOZkUuH3vKPU1Ox/gp04HvmFD9EXMM53HT1s5HtXT2TwXDKr+fs5NCl4/uvQZzsfdB3IEIsbOno6/Y2eh+Nf4w3+dXcU6PJHRNzJ02lG7EWL4VX//rpJScEEI0otnAPGzYMGJjY+ttW7RoEdOmTQNg2rRpLFy4sN52RVEYOHAgbrebsrIyVqxYwejRo3E4HMTGxjJ69GiWL19+HN6OEEIcW0tyKwEY17Xp6RgAutpiYhbeTTihFykXPos3GObmj7dS4vYfVd+qpvGnb3LYWOjikXN78Nj5Pblk/Fgu8T1EdVAhdvZ0DOXbGx53XgWhiMbEHk1Xx7BufQvVFIO/+6VHNUYhhGgPjmoOc2VlJcnJdXPikpKSqKysu6CUlpaSmpp6uF1qaiqlpaVHbE9JSaG0tH7pJSGEOBktyaugW5KNTEczpdbUCDEL7kAJ+3Cf+xrZaYn8/dJ+VHmD3PjRFg5UtX6Z638s38/8nHJuG9OJ83rVnXOnD8rgt1MmMD3wMBVBI/bZ0zGUbTli3wU55aTbzfRJjWn0+IqnDPPer/H3nA4mW6vHJ4QQ7UXD9ZFaQVEUlOP0azxFAYcj6rgcW4gTRa/XyffxKaqiNsCWQ25uH5fd7N+hbtmz6A+tJjz1VWI69wfgLEcU78fbmPHOem7+eCtvXzeMnk0E2J96f00B764r5KrhHbhrUo9659nLR2SRmTSFaz7Q83bwSVJnX4F29adoGcMAqPIEWVvg5IbRnYiLazwI67Z9jKKGMI66Wb5H2yE5NwnRckcVmBMSEigrKyM5OZmysjLi4+sK+aekpFBSUnK4XUlJCSkpKaSkpLB27drD20tLSxk+fHiz/WgaOJ2tvysjxMnE4YiS7+NT1Jdbi9E0OCMztsm/Q2PhSmKX/xl/z8up6Xgh/KRtutXA69P7c9snW7nqzTX89ZK+9Etv4iE8YGleJY9/vZMxXeK5Y3QnXC7fEW16xVt59PKJ3PiZgX+G/kTGfy6h9sL/EE4bxuytxURUjbGd4hofdyRE/Pq3CHY8C5c+vd6YRfsg5yYh6ktKavyGxlFNyZgwYQKzZ88GYPbs2Zx99tn1tmuaxubNm4mJiSE5OZkxY8awYsUKXC4XLpeLFStWMGbMmKPpWgghTpgleRVkxFroltT4XVrFW0HMgjuIxGVTc+aTDbbpFB/Fm1cOJNZq4LZPt7KuoLrR4+0odvPQ17vokRzN0xf0arJ+co+UaJ6+6hzuMj9BQSiWmDlXYSz6ngW7y8iKs9K9iXGb981D7y3F109KyQkhRHMUTdO0phrcc889rF27lurqahISErjjjjs455xzuPvuuykuLiY9PZ2XX34Zh8OBpmk8/vjjLF++HKvVytNPP02/fv0A+PTTT3n99dcBuOWWW7j00uYfMFFVjcrK2mPwNoVoO3IX5xShqehqitAscWimaGoDYSa99j3TB2Zw97hGSsNpKrFfXovx0GqqL/uSSGLvJruoqA1w+2fbOFjt45mpvRn7s7rOhU4f13+wGatJz7+vHNiiMnYAlZ4gf/p0OX9yP0hnQwWPB65iZOcEzsrQofir0Pmq0PmrUPzV6Hw/fA3VErFnUXX1MtDpW9SPOL3IuUmI+pq6w9xsYG5LEpjF6UAuSieZH4KxoWoP+qqcH77uwVCdixL2oRksBDqfxyrbOdy42sHMKwYxICO2wUNZN7xC9OpnqRn3LP4+17Soe6cvxF2fbyenrJY/ndeDc394mM/pDXHDR5tx+UK8eeVAOsW3bm6pJxjmyVmruLfsj/TSHTy8XTVGo1njUS1xaJY4VEs8qjUezRJPMGs84aR+repHnD7k3CREfRKYhWhDclFqe8bClZhzPsdQlYO+OhddyHP4tYgthUh8D8Lx3YnEdcVQsRNz7hx0ARflxBE1cDqBnpcRSehV75iG4nU4Zl1GIHsyNZNebVUNY08wzD2zdrCp0MX9E7sxuVcyt326jd2lNfzjsv4MzGw4oDcnFFH5y4KdWGsPcM/5Q1AtcaA3H9WxxOlPzk1C1CeBWYg2JBeltmXKX4R93o1opmjCCb3rgnF8D8IJPYjEdUOzOI7YJxDw8fzrr/Fb+2r6+taiqGFCiX0I9LgMf/dpoDMQ999zQWekevo8NHPTD/E1xB+KcP+Xu1i5v4quiTb2Vnh4+oJenNNM3WQhjhU5NwlRnwRmIdqQXJSOnypvkANVPpKiTSRFmzEb6j/HbCxcSexXvyYc3x3XRR+hmVt253b53krumb2Dv17Sl9GpGubcOVhyPsNYtgVN0aPaUtF5y3BeOptw8oCjHn8oovLI3BwW7inn7rO6cPXQzKM+lhCtJecmIeprKjD/4jrMQghxIoUjKiv3V/Hl9lJW7K8iov74M3+c1UhyjJnkaBPDDbncXPgHnNZMNg5+lSw1ipZOdFiSV4HNpGdYRweaXoe///X4+1+PvmoPlpzPMO2dS+2ZT/yisAxg1Ot4ckpPbhqVRaf4ZhZGEUII0WbkDrMQx5ncxTk2cstr+WpHKfN2llHtC5FgMzG5VzJDOjio8gYpqw1QWhOgrCaI3bWT57wPU6nGMD34COXEYTPpuf3MzlwyIA1dE/ONw6rG+f9czYgsB09O6dVoOyFOdXJuEqI+ucMshDglOX0h5u8u48vtpewuq8WgUxibncDUvimc0Sm+wRrF+socHLOfQIuOo+bCT3hNS6TY7eeddYU8tyiPuTtLeWBiN7olRTfY55YiF05fiHFdE4/32xNCCHGKkMAshDjplNUEeHHJXpbtrSQU0eiRHM1947M5t2cyjihjo/vpnfuI/eJKNJ0J57T/YortSBaQFR/FiKw45u0q46Ul+7j2vY1cPTSTG0dmYTXWr0G8JK8Sk15hVOf44/wuhRBCnCokMAshTiqapvH4tzlsKXJz2YB0LuiTQvfkhu8G/5TOXUjsnCtQ1DDOiz9Fje1U73VFUZjcO4VRneN5Zdl+3l1XyMKccv5wTjdG/xCONU1jSW4FI7LiiDLJYh5CCCHqHNXS2EIIcbwsyClnzQEnd4ztzD3js1sWlj2lOOb8CiXkwXnhh0Tiuzfa1mE18vC53Xn9V/0xGXTc/fl2HvhyFxW1AXLKaimpCTCum0zHEEII8SO5wyyEOGnU+MO8sHgvvVKiuXRAeov2UXyVxM65EsVXgevCD4gk9WnRfoMzHbx/7RDeW3+Qf68u4Pv8KronR6NTYGyXhOYPIIQQot2QO8xCiJPGqyv24/SFeHBiN/QNPND3c0rARewXV6N3H8A95W3CqUNa1Z/JoOOGM7L48DdD6Z0aw6ZCF4MyY5ucJy2EEKL9kTvMQoiTwo5iN59tKeZXgzPomdJ4aZ//MZRvJ+bbW9HXFOKa/G9CGSOPuu+OcVb+cVk/Vu6vooND6iELIYSoTwKzEKLNhVWNpxfkkhRt4pbRWU031jQs294meuUTqNZ4XBd9SCj9jF88BkVRGCNTMYQQQjRAArMQos19vKmIPeUenpvaC5up8dOS4ncSs/g+zPu+IZB1NjVnv4RmlfJvQgghji8JzEKINlXi9vPPlfmM6RLP+CaqUxhKNmD/9nfovGXUjn4E34DfQhMr9gkhhBDHigRmIUSbemHxXlQNfj+hK0pDAVhTsW56Ddvq51FjMnBe8jnhlEEnfqBCCCHaLQnMQrRTiq8Sfe0hNL0ZzWBB01vAYEEzmEFnOiF3b5ftrWRJXiW3n9mZ9FjLkWP0VmBfdBemgqX4sy+gdvzzaGb7cR+XEEII8VMSmIVobyIBojbNJGrD31DCvgabaCg/hOe6P8EOZ+Eddg9qTMtqI7eELxThz4vy6JIQxdVDMo543Vi4kpgFd6ALuKg561n8fa6WKRhCCCHahARmIdoRU/4ibCsexeDKJ9D5XPw9L0OJBCEcQIn4UcJ+lHAA/vffET+K34kl53Mse2bh63cd3iG3o1nifvFY3lh1gJKaAG9eMQCD/icl4SNBbGtfwLrxVSJx2VRf+D6RhF6/uD8hhBDiaElgFqId0LnyiV7xGOb8hYRis9k8+g3WKAPoaommf3rzUxw87kJs617EuuUNLDs/wDfoFrz9bwST7ajGk1teywcbCrmoXyoDMmIPb9dX7SFmwZ0YK7bj63UFtWc+Dsaoo+pDCCGEOFYUTdO0th5EY1RVo7Kytq2HIcQv4nBE4XR626Rvr8dNZNXLZOW+RQgD7xin81LN2fi1up+VdQrcObYLVw3JaPiBu5/RV+ZgW/M85v3folqT8Ay7C3/vq0BvavGYVE3jxg+3cNDp45MZQ3FYjaCpdbWVVz2FZrRRM/55gl3OO+r3LYRoXluem4Q4GSUlNb5olgRmIY6z431RCqsa5bUBDrn8lLgDHHL7ya/wkFoyn5sDb5GhVDIrMprXDL8mKTWLHinR9EyOpnN8FK+uzGdxbgWTeyfz4MTumA265jukrsSb7funMR1aQ8TeEc/w+6jMuoCwphBl1GPUK40G8M+3FvPMglweO68HU/qkoPOUELPoXkwHlxLImkDN+L+g2ZKP5UckhGiABGYh6pPALEQbOlYXpUpPkFX7qzjk8lNcE6DY5afY7aesJoCmqSThJE2pIk2p5HrzdwzTtlFq7UpO/4dI6jmWxGjzEcdUNY1/ry7g9VUH6J0aw58v7E1yzJHtGqRpGAuWYF31DOaqnexSO/JZ5ExWqX3YQ0csJiNRRj0Wo54oox6rSY/VqGNLkZueKdG8dnl/zHu/JmbJ/SgRP7WjH8Xf5xp5sE+IE0QCsxD1SWAWog390otSidvPe+sKWbw9j6HqNtKVSrqYXGQZnaQplSSqFcSEKtERObyPao7FM+IPdZUldM0/qrAkt4JH5+VgNel5/sLeLZrXHFY1Pt9yiDdW7WdsaAX3274mPbgfAI8+lryoweyyDGKrcQAFWjLekIovFMFs0PHouDR6bX8GS86nhJIHUDPx70QcXY76MxJCtJ4EZiHqk8AsRBs62otSQbWPd9YWsGTnAa7TzeMW01yiVA8AmsFKJDoNNTodNTqNiC0N9Yf/j0SnEYnt1OqH5fIqPNw3ewdltQHuP6cbF/ZNbbTt9/lVvLRkH/srvQzt6OCecV3olhSNrrYYY+FKTIUrMBauQO8pASASk0kwczShzDFoJjvRyx5CV3sI75A78Q69C/TGVn8+QohfRgKzEPVJYBaiDbX2opRX4eHtNQUszynkN4aF3G76ElvETaDzuXgH3UokriuaOfa4TF1w+UI8+NUu1hY4uWJwBned1QWD7sd+8qu8/HXpPlbsqyLTYeHus7owNjuhkRX6NPTOfRgLV9QF6KJV6AIuACL2LNwT/0Y4dcgxfw9CiJaRwCxEfRKYhWhDLb0o7Sip4a3VBXy/t4RrTUu5yzQHe7iSYMez8Az/PeGUgSdgtHVTLf62dB8fbixiaEcHz1zQC50C/1pdwH83HcJi0HHDGR351aAMTC18SBAANYKhYjv66jwCnc876pJ0QohjQwKzEPVJYBaiDTV1UYqoGqvzq/loYxHrD5RzlXkV95pmERsqJZg+Au+IPxBKH3GCR1zny+0lPLMwl0SbCW8wgtsfZlr/VG4Z3Yn4qJaXkRNCnJwkMAtRX1OBWRYuEaINVNQGmLO9hNlbSyip8XO1dQ2vxX5OXKCQUNxAnGe8TChzTJtWjJjaN5XOCVH88YuddEuy8X/jsumeHN1m4xFCCCHaitxhFuI4+99dHFXTWHugms+3lrBsbyURVWNYRweP2ObQb//rhBN64znjDwSzzj6pSqtpmtaiRU2EEKcWucMsRH1yh1mINlRZG+A/aw8ya2sxRS4/DquRKwdncHH/NLLdq4n9aib+npdTM+EFUFoxJ/gEkbAshBCivZPALMRxUl4b4K9L9/FdbgWhiMbgzFhuHd2J8d0SMRl06GqKsC+4g0hCT2rGPn1ShmUhhBBCSGAW4rhYnV/FI3Nz8IUiXD28I5N7JNE54Sd1kSNB7N/cDFoE93mvg9HadoMVQgghRJMkMAtxDIVVjTdW5fPWmoN0Toji9akDGJSdeMQ8weiVj2Ms24zrvJmywp0QQghxkpPALMQxUlYT4OGvd7GpyM1FfVO5b0I2FqP+iHbm3DlYt72Nd+DNBLMnt8FIhRBCCNEaEpiFOAa+/2EKRiAc4U/n92By75QG2+mrcon57veE0obhOeP+EzxKIYQQQhwNCcxC/AJhVeP1lfm8vfYg2YlRPHvBADr9dK7yTwU92L+5Cc0YhXvSq6A3ntjBCiGEEOKoSGAW4iiV/jAFY3ORm4v6pXLf+IanYACgacQs+QN6515cUz9AjU47sYMVQgghxFGTwCzEUVi1v4pH59VNwXh8cg/O79XwFIz/sWx/F0vuHDwj/kCow5gTNEohhBBCHAsSmIVoBVXT+NfqAmauOkDXRBvPTO1Fp/hGpmD8QCnaQPSKxwhkTcA75PYTM1AhhBBCHDMSmIVoodpAmEfn5bBsbyWTeyfzwDndGp+C8QPFX43+8xmothRqzvmrLE4ihBBCnIIkMAvRAvsqPfx+zk6KXH7uG5/N9EHpzS8ZHQkRs+BO8JThvmQWmiXuxAxWCCGEEMeUBGYhmvFdbgV/mpeDxajj1cv7MTjT0ew++qpcYhbehbF8K5HzXiCcPOAEjFQIIYQQx4MEZiEaEVE1/vlDybi+aTE8N7U3yTHmpnfSVKxb38L2/dNoxihc571O1JDL4Wcr/QkhhBDi1CGBWYgGuHwhHp67m9X51Uzrl8rvJ3TFZGh6/rGu9hAxi+7FVLicQNYEasb/Bc2WTNOPBAohhBDiZCeBWYif2VNWy++/2El5bYAHJ3bj4v7N1EzWNMy5s4le9jBKJETNuGfx974ampvjLIQQQohTggRmIX6gahpf7Sjl+UV5xFoMvD59AP3S7U3uo/iriV76IJa8LwmlDsF99suojs4naMRCCCGEOBEkMIvTX9iHZfdn6LxlhNKGEUoZDCbb4ZdVTWPRngre/P4A+yq9DMqw8/TU3iTaTE0e1liwhJjv7kXnq8Qz4o94B98KOvknJYQQQpxu5OouTjreYIRXV+xn/u5yEqNNZDqsZMZayHRYyHBYyXRYSImxYNA1PeVBCdZi2f4eUZtnovOVo6GgoKEpesJJfQmmDmUjvXgpL5GNVSY6x0fx1JSenN09Cf3Pjx0JoK8pQuc6gN5dgLFkA5Y9nxOO645zytuEk/odx09ECCGEEG1J0TRNa+tBNEZVNSora9t6GOIEWrW/imcW5FJaE2B8t0QCYZVCp49Dbj+hyI/fqnqdQrrdTIbDSqf4KHqnRtM31U6mw4Iu4MS69S2sW/+FLuAi2GEs3iF3EE7qi6FkA4ZDa/HsXYnDuQ0zQQDcUVkYOp5BOH0E6I3o3QXoXAXo3XUBWVdbjMKP/WsGC74+1+I5449gsDT5nhyOKJxSJUMIcZKRc5MQ9SUlxTT6mgRmcVJwekO8uGQv83aV0SneysOTujMgI/bw6xFVo7w2QKHTT6HTR6HLT5HTR6HTT36VF39YJREXt1nmcYWyAKvmozhlHJERd2HuMAyom3qxOLeCN74/wN4KL13jDNzX28NoYy6mknUYi9eiC7h+7NOWgmrPImLvWPcntiMRexaqvSNqVFKLV+2Ti5IQ4mQk5yYh6pPALE5amqYxf3c5LyzeizsQ5rrhHbh+REdMqg+9+wDoTWh6C5rBAoYfvv5snrDqLiLy/d9J3vcJOjXIYv0Y/uKdwi6tIwAd46z0SY1hT3kteyu8dIq3cuMZWZzT42dTLzQVfXUeoBCxZ4LBekzeo1yUhBAnIzk3CVGfBGYBQDCssrusli1FLrYecrPrUDXp+mpGJYUZGBekR7SPeM2J3leOzluB4q1A5ytH56tEM8UQsXdAjelAxN6BSEwHVHsmkZiOqLYUvGEodPpIsJmIjzI2v2w0UOL289yiPFbtq+C8pGru7eEi3bsDY+km9FV7UDS1wf00nQFNbwGDGU1vQectAzT83S/FN+Q2Io4u1AbC7CypYUdJDTuKa9heUoPdYuD6ER2Z+POgfJzJRUkIcTKSc5MQ9Z2ygfmQ08eG3DKGdoxr9AEvXW0x+uo8IvHdUaOST7vat5qmUekJUuTyU+Ty4/aHsVsM2C0GYi3Gw19jLIYjQmClJ8i2Q262HnKz5ZCb/aUV9NVyGaHbxZnGPfQjF5MWOKJPjy6akDkBfUwyxpgUtKgElEAN+pqDKO6D6D2l9ebzhjBQpCZQpCVSRQw+fQw6SyxmWxxR9gRiHQkkxCcS60gESywRxcD69csp2rWKflougwz5mNS6k7ZqjiWcPJBQykAi8T1BC6OEAxDxo4R//EMkUPffET+qJR5fvxmo9szj+5dxlOSiJIQ4Gcm5SYj6mgrMJ3WVjGpvkDs+2058lJGJPZI4t2cyfdNiUBQFXU0RURv/gWXnRyhq3YNbqjWBcEJvwom9CSf2IpzQm0hcV9A3XR6srQXDKvlV3sOh+NAPf4pcPordAQLhhu+0/lyM2XA4TNcGwlQ7qxiiy2WkfhdXmnLpbsrFoIXRFB3hxD6E0q8lEN+TiDWRg6FoNlWbWVWqY22Rl6rqEFRDos3EoMxYQhGVvdUeilx+DFqIdKWCTroK+kc76WmuppO+gu6RUgzBQxhCNVj8NRj9YahseKznA2FFTzChN5GMy3GnDCKcMphIbOfT7oceIYQQQpzaTvgd5mXLlvHUU0+hqiqXX345N910U6NtIxGVz9Yc4NvdZSzfW0kwojHY7uah6LkMcs5DAfy9fkWgy/kYqvPQV+7EULELQ1UOSqTuzqmmMxKJ61YXohN6EonrStiRjWrv0CY1c0MRlb0VHnaV1rKrtIZdJbXkVXiIVt0kKG5i8ZBm8tLJGiDT4ifV4CPJ4MGheIhRazCpPiIohFUIaTrCmkJIhZCqEFQVgppCMAKJagVZob3oUNF0BsLJAwiljyCUNoJQ2jA0c+MLcmiaxoEqHxsLnWwsdLG5yI3VqCM70UaXhCi6JNjITrTRwWHBoG/kwTdNg7CfGmc5h8rKqKgqp7qqnFr3/2/v3oOqug49jn8PTx+oKJHDVYmKxkcVfKS5Jk2sUxRQTxCCxJigJrQZO04qJUad+EpumtQ0Tqq2MZnRmcYxTWrTGoO5IPGBFVtTdUjNUG/VWJUIBo8RFQF5nMe6fxBP5QZOa/WejfL7zDDh7LPR396Zvfi5WOx9EVdjPfcMv5dx/zkeW+itWSfcnmkWR0TaI41NIi21myUZHo+HlJQUNm7ciN1uJzMzk9WrVzN48OBW979+DXPDV6e4+sfVDKr8bzzGxvue7/Fxj8cY+60RPDiwF1FdQ+neKbR5WYLXTfDlU4Rc+BshVX8j5MLfCL5wlOCrTt+fbYLC8EQObC7QPQfjiRzkK9PXP9QCmgvkuZpGTl6o49SFq5ysquOLi/UE2aBbp5CvZ3ZD6RYeTLdOoXQPD/FtDw8J4lTVtYJcy4mvan23RxsQXsuT3UpI9hTTt/54q+fA2IIw4ZF4O0ViwiMxoV0BA8YDxtu8ztfb/Hnzhweb8eLtFNlcjvvcjytmLIR2uQX/B+XfoW9KItIeaWwSaandLMkoLS2lf//+xMbGAuBwOCgqKmqzMAMEVZfRpeQN7jq+BYJCqI+fw5fDnuZKRQg1x86z7o+nWffH0wDYoHlNb+dQIjuHEtn5HiI7Dyeyx0wiY0LpZaslqrGcqIYv6NnwBT2ultH93BG6nPqYIOPx/Z11XfpxttNQjtriONDQnz1X+uB0/eNeu70jwhjQqws24NJVF2cu1VPT4Kam0Y23jX9+RIQHM8zejdmjopgYVMLIizvoXvknbLUeXL3jqR31PN5u/XzF2NupJ6ZTJCas2798+zIRERERufUCWpidTicxMTG+13a7ndLS0jb3t1Wfodd7E74uyk9RP3Ye3q4x9AAei4bHxval4nI9/1NZQ3WDi8v1Li5ddXG53s3lBheVVxo46mze/o+HXnQChn790SwMF3fbnAyyfclg25d8q6aMhNpS0oKKSAMIhuqusdRHjSSk72hC/mM07t4DvrGswWsMV5s81DS6fQX6apOH/pHhxNV9SufP3ybsRCFBrjo8EX2pHzOPhqEZeHoNuVWnWERERERusXb9S380VOO9by7e++cT2i2G0FZ2iYzswsgBUX7/GGMMtY0erja5afJ4cbm9NHkMTW4vLo+3eZvHS5O7+aNHRBih0d1w2WqxnfsMW+VndKv8jO6Vn2E7VPiPPze0S/PyjbAICO2KufZ5WFcI69o8O+x1E/Sn7dhqz2HCu2NGZOAeOQNz9wOE2oJaPSa5swQHBxEZqSUxItK+aGwS+dcFtDDb7XbOnTvne+10OrHb7W3ub+zxXLxvGXiAW7DOKhwItwGhQTQ31eC2d3a5uUwn6HV/88eI5s22+ipCzpcScuF/CGq4hM1V1/zR9PV/a6uwucqxuQjVOFkAABDgSURBVGqbX3tcNPV7iIYH/4umAZP+8Rjl6oabPh65PWidoIi0RxqbRFpqN2uY4+PjKSsro7y8HLvdTkFBAT//+c8DGeGmmc5RuPp/D1f/71kdRUREREQCIKCFOSQkhBdeeIGnn34aj8fD9OnTueeeewIZQURERETkhrTrJ/3p0dhyJ9CPPUWkPdLYJNKSvyUZul+ZiIiIiIgfKswiIiIiIn6oMIuIiIiI+KHCLCIiIiLihwqziIiIiIgfKswiIiIiIn6oMIuIiIiI+KHCLCIiIiLihwqziIiIiIgfKswiIiIiIn6oMIuIiIiI+KHCLCIiIiLihwqziIiIiIgfKswiIiIiIn6oMIuIiIiI+KHCLCIiIiLih80YY6wOISIiIiLSXmmGWURERETEDxVmERERERE/VJhFRERERPxQYRYRERER8eOOLcxLlizhgQce4OGHH26x/de//jWTJ0/G4XCwatUqi9IFXmVlJbNnz2bq1Kk4HA42bdoEwNq1a0lNTSUtLY3vf//7OJ1Oi5MGTmNjI5mZmUybNg2Hw8Evf/lLAMrLy3n00UdJSkoiNzeXpqYmi5MG1r59+0hJSSEpKYkNGzYAYIxhzZo1pKSkMGXKFN555x2LUwZWa+NJR7522hpPLl++THZ2NsnJyWRnZ1NdXW1x0sBp65zk5uaSlpZGWloaiYmJpKWlWZw0sFobT6555ZVXGDNmjEXJrNHaWFJYWIjD4WDYsGH89a9/tTCdNVo7J0ePHmXGjBmkpaWRkZFBaWmphQm/Zu5Qhw4dMkeOHDEOh8O37c9//rN58sknTWNjozHGmAsXLlgVL+CcTqc5cuSIMcaYmpoak5ycbE6cOGFqamp8+2zatMmsWLHCqogB5/V6TW1trTHGmKamJpOZmWkOHz5scnJyTH5+vjHGmBUrVpj33nvPypgB5Xa7zcSJE82ZM2dMY2OjSU1NNSdOnDBbtmwxixYtMh6PxxjTsa4dY1ofTzrytdPWePLaa6+Z9evXG2OMWb9+vVm1apWVMQOqrXNyvVdffdW88cYbVsSzRFvjiTHGlJaWmoULF5rRo0dbnDKwWhtL/v73v5uTJ0+aWbNmmdLSUgvTWaO1c5KdnW327t1rjDFm7969ZtasWVbF87ljZ5jvu+8+evTo0WLb5s2bmTt3LmFhYQBERUVZEc0S0dHRjBgxAoCIiAji4uJwOp1ERET49qmvr8dms1kVMeBsNhtdu3YFwO1243a7sdlsHDhwgJSUFAAeeeQRioqKrIwZUKWlpfTv35/Y2FjCwsJwOBwUFRWxefNmnnnmGYKCmoeMjnTtQOvjSUe+dtoaT4qKikhPTwcgPT2d3bt3WxkzoNo6J9cYYygsLPzGTz3vZG2NJx6Ph1WrVrFo0SKrIwZca2PJoEGDiIuLsyiR9Vo7Jzabjbq6OgBqamqIjo62IloLIVYHCKSysjJKSkpYs2YN4eHhLF68mISEBKtjBVxFRQVHjx5l1KhRAKxZs4a8vDy6devW4X7U7vF4yMjI4MyZMzzxxBPExsbSvXt3QkKaL42YmJgO9aN2p9NJTEyM77Xdbqe0tJTy8nK2b9/Orl276NWrF8uXL2fAgAHWBW0nOvK1c83140lVVZXvG1vv3r2pqqqyOJ01/u8YC1BSUkJUVFSHum7aGk/effddJk6c2C5KkLRPS5cu5Qc/+AGvvfYaXq+X3/72t1ZHunPXMLfG4/FQXV3N7373OxYvXkxubi6mgz23pa6ujpycHJYuXeqbIXv22WcpLi4mNTWVd9991+KEgRUcHMy2bdsoLi6mtLSUU6dOWR2pXWpqaiI8PJytW7cyY8YMli5danWkdqEjXzvQ+nhyjc1m61Cz7te0dU7y8/M71OxyW+rr6/n444+ZNWuW1VGkHdu8eTNLliyhuLiYJUuWsGzZMqsjdazCbLfbSUpKwmazkZCQQFBQEJcuXbI6VsC4XC5ycnJITU0lOTn5G++npqayc+dOC5JZr3v37owbN47PPvuMK1eu4Ha7ATh37hx2u93idIFjt9s5d+6c77XT6cRut/uuHYCkpCSOHz9uVcR2qSNeO62NJ1FRUZw/fx6A8+fP06tXLysjBlxbY6zb7WbXrl1MnTrVwnSB19p4cvfdd3PmzBmSk5NJTEykvr7eN7aIXPPhhx/6rqEpU6a0i1/661CFedKkSRw8eBCA06dP43K56Nmzp8WpAsMYw7Jly4iLiyM7O9u3vayszPd5UVFRh1pHdfHiRa5cuQJAQ0MDn3zyCYMGDWLcuHHs2LEDaL5oExMTrYwZUPHx8ZSVlVFeXk5TUxMFBQUkJia2uHYOHTrUoX6s3JaOfO20NZ4kJiaSl5cHQF5eHhMnTrQqYsC1dU4APvnkE+Li4losT+gIWhtPJk2axP79+9mzZw979uyhc+fO7Nq1y+qo0s5ER0dz6NAhAA4cONAuvufYzB26JmHBggUcOnSIS5cuERUVxfz580lLS2Pp0qUcO3aM0NBQFi9ezAMPPGB11IAoKSkhKyuLIUOG+H5xa8GCBWzZsoXTp09js9no27cvL730UoeZUT127BjPP/88Ho8HYwyTJ0/mRz/6EeXl5Tz77LNUV1czfPhwXn/9dd8vinYExcXFrFy5Eo/Hw/Tp05k3bx5Xrlxh4cKFVFZW0qVLF1566SWGDRtmddSAaW082bdvX4e9dtoaTxISEsjNzaWyspI+ffqwdu1aIiMjLU4bGG2dkwkTJvD8888zatQoHn/8cYtTBl5r48n1xowZw+HDhy1KF3itjSWRkZG8/PLLXLx4ke7duzN8+HB+9atfWR01YFo7JwMHDmTlypW43W7Cw8N58cUXGTlypKU579jCLCIiIiJyK3SoJRkiIiIiIjdKhVlERERExA8VZhERERERP1SYRURERET8UGEWEREREfFDhVlERERExA8VZhERERERP1SYRURERET8UGEWEREREfFDhVlERERExA8VZhERERERP1SYRURERET8UGEWEREREfFDhVlERERExA8VZhERERERP1SYRURERET8UGEWuQV2797N0KFDOXnypNVRREQYOnQoCxcu9L12u93cf//9/PCHP7QwlcjtS4VZ5BbIz8/n3nvvpaCg4Ia+zuPx/D8lEpGOrEuXLpw4cYKGhgYA9u/fj91utziVyO1LhVnkJtXV1fHpp5/y05/+1FeYDx48SFZWFnPnziUlJYUXXngBr9cLwJgxY/jZz37GtGnTOHz4sJXRReQONmHCBPbu3QtAQUEBDofD915paSmPPfYY6enpzJw5k1OnTgGQlZXF0aNHffs9/vjjHDt2LKC5RdojFWaRm1RUVMT48eMZOHAgPXv25MiRI0DzN6QVK1awfft2ysvL2blzJwBXr14lISGBjz76iG9/+9tWRheRO9jUqVPZvn07jY2NHD9+nFGjRvnei4uL47333iMvL4+cnBzWrFkDQGZmJlu3bgXg9OnTNDY2MmzYMEvyi7QnKswiN+n6mZupU6f6ZpkTEhKIjY0lODgYh8PBp59+CkBwcDApKSmW5RWRjmHYsGFUVFSQn5/PhAkTWrxXU1PDj3/8Yx5++GFeffVVTpw4AcDkyZPZu3cvLpeLDz74gIyMDCuii7Q7IVYHELmdXb58mQMHDvD5559js9nweDzYbDYmTJiAzWZrse+11+Hh4QQHB1sRV0Q6mMTERFatWsU777zD5cuXfdt/8YtfMG7cON58800qKiqYM2cOAJ07d+Y73/kORUVFFBYW+mabRTo6zTCL3IQdO3aQlpbGH/7wB/bs2UNxcTH9+vWjpKSE0tJSysvL8Xq9FBYWcu+991odV0Q6mMzMTJ555hmGDh3aYntNTY3vlwA//PDDFu89+uijvPLKK8THx9OjR4+AZRVpz1SYRW5Cfn4+kyZNarEtOTmZgoIC4uPjefnll5kyZQp9+/YlKSnJopQi0lHFxMT4Zo+v9/TTT7N69WrS09Nxu90t3hs5ciQRERFajiFyHZsxxlgdQuROc/DgQd5++23Wr19vdRQRkRvidDqZM2cOhYWFBAVpXk0ENMMsIiIiX8vLy2PGjBnk5uaqLItcRzPMIiIiIiJ+6J+PIiIiIiJ+qDCL3KDKykpmz57N1KlTcTgcbNq0CWi+xVx2djbJyclkZ2dTXV0NwEcffURqaiqpqanMnDmzxVOz9u3bR0pKCklJSWzYsMGS4xERERH/tCRD5AadP3+er776ihEjRlBbW8v06dN588032bp1K5GRkcydO5cNGzZQXV3NokWL+Mtf/sKgQYPo0aMHxcXFrFu3jt///vd4PB5SUlLYuHEjdrudzMxMVq9ezeDBg60+RBEREbmOZphFblB0dDQjRowAICIigri4OJxOJ0VFRaSnpwOQnp7O7t27ARg7dqzvXqajR4/m3LlzQPOjs/v3709sbCxhYWE4HA6KioosOCIRERHxR4VZ5CZUVFRw9OhRRo0aRVVVFdHR0QD07t2bqqqqb+y/ZcsWvvvd7wLNt26KiYnxvWe323E6nYEJLiIiIv8yPRpb5N9UV1dHTk4OS5cuJSIiosV7NpvtG4/GPnDgAFu2bOE3v/lNIGOKiIjITdIMs8i/weVykZOTQ2pqKsnJyQBERUVx/vx5oHmdc69evXz7Hzt2jOXLl/PWW2/Rs2dPoHlG+dryDGiecb72qFoRERFpP1SYRW6QMYZly5YRFxdHdna2b3tiYiJ5eXlA883/J06cCMCXX37J/PnzWbVqFQMHDvTtHx8fT1lZGeXl5TQ1NVFQUEBiYmJgD0ZERET+Kd0lQ+QGlZSUkJWVxZAhQ3xPwlqwYAEJCQnk5uZSWVlJnz59WLt2LZGRkSxbtoydO3fSp08fAIKDg9m6dSsAxcXFrFy5Eo/Hw/Tp05k3b55lxyUiIiKtU2EWEREREfFDSzJERERERPxQYRYRERER8UOFWURERETEDxVmERERERE/VJhFRERERPzQk/5ERG4Dw4cPZ8iQIbjdboKDg0lPT+epp57y3dqwNRUVFRw+fJjU1NQAJhURufOoMIuI3AY6derEtm3bAKiqquK5556jtraWnJycNr/m7Nmz5OfnqzCLiNwk3YdZROQ2MGbMGA4fPux7XV5eTmZmJgcOHODs2bMsXryY+vp6AFasWMHYsWOZMWMGJ0+epF+/fjzyyCPMnj2b119/nUOHDtHU1ERWVhYzZ8606pBERG4bmmEWEbkNxcbG4vF4qKqqIioqio0bNxIeHk5ZWRkLFixg69atPPfcc7z99tusX78egPfff59u3brxwQcf0NTUxMyZM3nwwQeJjY21+GhERNo3FWYRkduc2+3mJz/5CceOHSMoKIiysrJW99u/fz/Hjx9nx44dANTU1PDFF1+oMIuI/BMqzCIit6Hy8nKCg4OJiopi3bp13HXXXWzbtg2v10tCQkKrX2OMYfny5YwfPz7AaUVEbm+6rZyIyG3m4sWLvPjii2RlZWGz2aipqaF3794EBQWxbds2PB4PAF27dqWurs73dQ899BCbN2/G5XIBcPr0aa5evWrJMYiI3E40wywichtoaGggLS3Nd1u5tLQ0srOzAXjiiSeYP38+eXl5jB8/ni5dugAwdOhQgoKCmDZtGhkZGcyZM4ezZ8+SkZGBMYaePXvy1ltvWXlYIiK3Bd0lQ0RERETEDy3JEBERERHxQ4VZRERERMQPFWYRERERET9UmEVERERE/FBhFhERERHxQ4VZRERERMQPFWYRERERET9UmEVERERE/Phf/LT8+cOC+DkAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 864x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "y-C-AgipbD4I",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#lets predict for upcomming dates ..\n",
        "\n",
        "future_predict = sarimax_mod.predict(start= datetime.date.today() ,end = datetime.date.today()+timedelta(days=7) ,dynamic= True,)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1KUOb1eZccdu",
        "colab_type": "code",
        "outputId": "6da45201-c087-45fd-bc70-1a3e78f8971e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 170
        }
      },
      "source": [
        "future_predict"
      ],
      "execution_count": 235,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "2020-05-22    6419.538464\n",
              "2020-05-23    7007.670186\n",
              "2020-05-24    6375.071332\n",
              "2020-05-25    7317.266789\n",
              "2020-05-26    7147.678329\n",
              "2020-05-27    7125.577477\n",
              "2020-05-28    7524.998542\n",
              "2020-05-29    7986.179586\n",
              "Freq: D, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 235
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "B2KYnjXUEjzs",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# train_df=train_df.reset_index()\n",
        "# train_df.head()"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-1egMCQOhxRa",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# dates=[]\n",
        "# for i in future_predict.index:\n",
        "#     if type(i)==type(future_predict.index[0]):\n",
        "#       dates.append(i)\n",
        "# data=[]\n",
        "# for i in future_predict.values:\n",
        "#   if type(i)==type(future_predict.values[0]):\n",
        "#     data.append(i)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mkufGVPZjmYL",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# train_df=train_df.reset_index()\n",
        "# DF=pd.DataFrame({'forecast':data,'date':dates})\n",
        "# train_df=train_df.append(DF)\n",
        "# train_df=train_df.reset_index()\n",
        "# train_df = train_df.set_index('date')\n",
        "# train_df[start_index:][['TT', 'forecast']].plot(figsize=(12, 8))"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "68LdP4l25D7O",
        "colab_type": "code",
        "outputId": "6dc98e19-1e0d-4b2d-ebea-1e531adf8ba3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 499
        }
      },
      "source": [
        "figg = plt.figure(figsize=(12, 8))\n",
        "orig = plt.plot(train_df['TT'], color='blue',label='Original')\n",
        "fore = plt.plot(future_predict, color='red', label='Forecast')\n",
        "plt.legend(loc='best')\n",
        "plt.title('Forecast of upcomming Covid-19 Cases')\n",
        "plt.show()"
      ],
      "execution_count": 239,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hn5jA1HBu04Q",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "f_temp = pd.DataFrame()"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ygan1lftVrhH",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "f_temp['date'] = future_predict.index\n",
        "f_temp['values'] = future_predict.values"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RJnd0OVHke5H",
        "colab_type": "code",
        "outputId": "626c2b68-5aed-40d6-8177-85fdbc894215",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 297
        }
      },
      "source": [
        "f_temp"
      ],
      "execution_count": 242,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>date</th>\n",
              "      <th>values</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2020-05-22</td>\n",
              "      <td>6419.538464</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2020-05-23</td>\n",
              "      <td>7007.670186</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2020-05-24</td>\n",
              "      <td>6375.071332</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2020-05-25</td>\n",
              "      <td>7317.266789</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2020-05-26</td>\n",
              "      <td>7147.678329</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>2020-05-27</td>\n",
              "      <td>7125.577477</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>2020-05-28</td>\n",
              "      <td>7524.998542</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>2020-05-29</td>\n",
              "      <td>7986.179586</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        date       values\n",
              "0 2020-05-22  6419.538464\n",
              "1 2020-05-23  7007.670186\n",
              "2 2020-05-24  6375.071332\n",
              "3 2020-05-25  7317.266789\n",
              "4 2020-05-26  7147.678329\n",
              "5 2020-05-27  7125.577477\n",
              "6 2020-05-28  7524.998542\n",
              "7 2020-05-29  7986.179586"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 242
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yj9UacnlkopD",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "f_temp.loc[-1] = [train_df.index[-1],train_df['TT'][-1]]"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "052jb-7Ik7OR",
        "colab_type": "code",
        "outputId": "e7c25d52-acef-4404-d90d-52d8835fd412",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 328
        }
      },
      "source": [
        "f_temp"
      ],
      "execution_count": 244,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>date</th>\n",
              "      <th>values</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2020-05-22</td>\n",
              "      <td>6419.538464</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2020-05-23</td>\n",
              "      <td>7007.670186</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2020-05-24</td>\n",
              "      <td>6375.071332</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2020-05-25</td>\n",
              "      <td>7317.266789</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2020-05-26</td>\n",
              "      <td>7147.678329</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>2020-05-27</td>\n",
              "      <td>7125.577477</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>2020-05-28</td>\n",
              "      <td>7524.998542</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>2020-05-29</td>\n",
              "      <td>7986.179586</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>-1</th>\n",
              "      <td>2020-05-21</td>\n",
              "      <td>6024.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         date       values\n",
              " 0 2020-05-22  6419.538464\n",
              " 1 2020-05-23  7007.670186\n",
              " 2 2020-05-24  6375.071332\n",
              " 3 2020-05-25  7317.266789\n",
              " 4 2020-05-26  7147.678329\n",
              " 5 2020-05-27  7125.577477\n",
              " 6 2020-05-28  7524.998542\n",
              " 7 2020-05-29  7986.179586\n",
              "-1 2020-05-21  6024.000000"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 244
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4LNNkBFLyE8p",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "f_temp.index = f_temp.index + 1"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nveqqei-ykYx",
        "colab_type": "code",
        "outputId": "519d4749-2290-4cfa-c0b4-0051b409dc54",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 328
        }
      },
      "source": [
        "#f_temp = f_temp.sort_index()\n",
        "f_temp"
      ],
      "execution_count": 246,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>date</th>\n",
              "      <th>values</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2020-05-22</td>\n",
              "      <td>6419.538464</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2020-05-23</td>\n",
              "      <td>7007.670186</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2020-05-24</td>\n",
              "      <td>6375.071332</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2020-05-25</td>\n",
              "      <td>7317.266789</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>2020-05-26</td>\n",
              "      <td>7147.678329</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>2020-05-27</td>\n",
              "      <td>7125.577477</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>2020-05-28</td>\n",
              "      <td>7524.998542</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>2020-05-29</td>\n",
              "      <td>7986.179586</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2020-05-21</td>\n",
              "      <td>6024.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        date       values\n",
              "1 2020-05-22  6419.538464\n",
              "2 2020-05-23  7007.670186\n",
              "3 2020-05-24  6375.071332\n",
              "4 2020-05-25  7317.266789\n",
              "5 2020-05-26  7147.678329\n",
              "6 2020-05-27  7125.577477\n",
              "7 2020-05-28  7524.998542\n",
              "8 2020-05-29  7986.179586\n",
              "0 2020-05-21  6024.000000"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 246
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IXKVjfb8Bvz7",
        "colab_type": "code",
        "outputId": "b9eeaf28-1d85-468a-9cc0-df216e86b902",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 328
        }
      },
      "source": [
        "# f_temp.drop(1,inplace=True)\n",
        "f_temp = f_temp.sort_index()\n",
        "f_temp"
      ],
      "execution_count": 247,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>date</th>\n",
              "      <th>values</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2020-05-21</td>\n",
              "      <td>6024.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2020-05-22</td>\n",
              "      <td>6419.538464</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2020-05-23</td>\n",
              "      <td>7007.670186</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2020-05-24</td>\n",
              "      <td>6375.071332</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2020-05-25</td>\n",
              "      <td>7317.266789</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>2020-05-26</td>\n",
              "      <td>7147.678329</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>2020-05-27</td>\n",
              "      <td>7125.577477</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>2020-05-28</td>\n",
              "      <td>7524.998542</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>2020-05-29</td>\n",
              "      <td>7986.179586</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        date       values\n",
              "0 2020-05-21  6024.000000\n",
              "1 2020-05-22  6419.538464\n",
              "2 2020-05-23  7007.670186\n",
              "3 2020-05-24  6375.071332\n",
              "4 2020-05-25  7317.266789\n",
              "5 2020-05-26  7147.678329\n",
              "6 2020-05-27  7125.577477\n",
              "7 2020-05-28  7524.998542\n",
              "8 2020-05-29  7986.179586"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 247
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Kvwben5zCmKC",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "f_temp['date'] = pd.to_datetime(f_temp['date'], format=\"%d-%b-%y\")\n",
        "f_temp = f_temp.set_index('date')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LahMtIRnC5Hk",
        "colab_type": "code",
        "outputId": "5b95d444-a6c3-4703-e608-b88e0e75d374",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 499
        }
      },
      "source": [
        "figg = plt.figure(figsize=(12, 8))\n",
        "orig = plt.plot(train_df['TT'], color='blue',label='Original')\n",
        "fore = plt.plot(f_temp['values'], color='red', label='Forecast')\n",
        "plt.legend(loc='best')\n",
        "plt.title('Forecast of upcomming Covid-19 Cases')\n",
        "plt.show()"
      ],
      "execution_count": 249,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "a-v-H-g4C7Sm",
        "colab_type": "code",
        "outputId": "7fa78393-7c42-460f-dda0-825efc138511",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 297
        }
      },
      "source": [
        "fcast = sarimax_mod.get_forecast(datetime.date.today()+timedelta(days=7))\n",
        "fcast = fcast.conf_int()\n",
        "fcast\n",
        "\n",
        "#This will give us confidence levels for our predictions"
      ],
      "execution_count": 250,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>lower TT</th>\n",
              "      <th>upper TT</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2020-05-22</th>\n",
              "      <td>5940.288369</td>\n",
              "      <td>6898.788558</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-23</th>\n",
              "      <td>6440.250819</td>\n",
              "      <td>7575.089553</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-24</th>\n",
              "      <td>5624.565721</td>\n",
              "      <td>7125.576942</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-25</th>\n",
              "      <td>6408.785735</td>\n",
              "      <td>8225.747842</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-26</th>\n",
              "      <td>6096.850817</td>\n",
              "      <td>8198.505842</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-27</th>\n",
              "      <td>5943.571664</td>\n",
              "      <td>8307.583290</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-28</th>\n",
              "      <td>6156.897498</td>\n",
              "      <td>8893.099585</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-29</th>\n",
              "      <td>6485.167985</td>\n",
              "      <td>9487.191186</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "               lower TT     upper TT\n",
              "2020-05-22  5940.288369  6898.788558\n",
              "2020-05-23  6440.250819  7575.089553\n",
              "2020-05-24  5624.565721  7125.576942\n",
              "2020-05-25  6408.785735  8225.747842\n",
              "2020-05-26  6096.850817  8198.505842\n",
              "2020-05-27  5943.571664  8307.583290\n",
              "2020-05-28  6156.897498  8893.099585\n",
              "2020-05-29  6485.167985  9487.191186"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 250
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-_Ydpv4DWyhm",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 359
        },
        "outputId": "93fbbe27-cc72-49e8-b41f-65d6c565d9fb"
      },
      "source": [
        "fcast = fcast.reset_index()\n",
        "fcast.loc[-1] = [train_df.index[-1],train_df['TT'][-1],train_df['TT'][-1]]\n",
        "fcast.index = fcast.index + 1\n",
        "fcast = fcast.sort_index()\n",
        "fcast['index'] = pd.to_datetime(fcast['index'], format=\"%d-%b-%y\")\n",
        "fcast = fcast.set_index('index')\n",
        "fcast"
      ],
      "execution_count": 251,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>lower TT</th>\n",
              "      <th>upper TT</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>index</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2020-05-21</th>\n",
              "      <td>6024.000000</td>\n",
              "      <td>6024.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-22</th>\n",
              "      <td>5940.288369</td>\n",
              "      <td>6898.788558</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-23</th>\n",
              "      <td>6440.250819</td>\n",
              "      <td>7575.089553</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-24</th>\n",
              "      <td>5624.565721</td>\n",
              "      <td>7125.576942</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-25</th>\n",
              "      <td>6408.785735</td>\n",
              "      <td>8225.747842</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-26</th>\n",
              "      <td>6096.850817</td>\n",
              "      <td>8198.505842</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-27</th>\n",
              "      <td>5943.571664</td>\n",
              "      <td>8307.583290</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-28</th>\n",
              "      <td>6156.897498</td>\n",
              "      <td>8893.099585</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-05-29</th>\n",
              "      <td>6485.167985</td>\n",
              "      <td>9487.191186</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "               lower TT     upper TT\n",
              "index                               \n",
              "2020-05-21  6024.000000  6024.000000\n",
              "2020-05-22  5940.288369  6898.788558\n",
              "2020-05-23  6440.250819  7575.089553\n",
              "2020-05-24  5624.565721  7125.576942\n",
              "2020-05-25  6408.785735  8225.747842\n",
              "2020-05-26  6096.850817  8198.505842\n",
              "2020-05-27  5943.571664  8307.583290\n",
              "2020-05-28  6156.897498  8893.099585\n",
              "2020-05-29  6485.167985  9487.191186"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 251
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0rBvh-FzW7Yv",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 499
        },
        "outputId": "9a6f853f-a026-4b3a-bc79-c1668d6ee04f"
      },
      "source": [
        "figg = plt.figure(figsize=(12, 8))\n",
        "orig = plt.plot(train_df['TT'], color='blue',label='Original')\n",
        "fore = plt.plot(f_temp['values'], color='orange', label='Forecast')\n",
        "lower = plt.plot(fcast['lower TT'], color='green', label='Lower Bound')\n",
        "upper = plt.plot(fcast['upper TT'], color='red', label='Upper Bound')\n",
        "plt.legend(loc='best')\n",
        "plt.title('Forecast of upcomming Covid-19 Cases')\n",
        "plt.show()"
      ],
      "execution_count": 252,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 864x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    }
  ]
}