Notebook.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.7.4"
    },
    "colab": {
      "name": "PIC.ipynb",
      "provenance": [],
      "include_colab_link": true
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/SandeepanMahapatra/FDI-Analysis/blob/master/Notebook.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fkcxw5Zy0DTA",
        "colab_type": "text"
      },
      "source": [
        "### Importing necessary modules and reading in the dataset"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qf5d2GiH0DTB",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "import seaborn as sns\n",
        "from sklearn.linear_model import LinearRegression\n",
        "from sklearn.preprocessing import PolynomialFeatures\n",
        "from statsmodels.tsa.stattools import adfuller\n",
        "from statsmodels.tsa.arima_model import ARMA\n",
        "from statsmodels.tsa.statespace.sarimax import SARIMAX\n",
        "from statsmodels.graphics.tsaplots import plot_acf, plot_pacf\n",
        "from statsmodels.tsa.arima_model import ARIMA\n",
        "from statsmodels.tsa.seasonal import seasonal_decompose\n",
        "file1 = 'D:\\\\Studies\\\\Project\\\\Resources\\\\FDI_in_India.csv'\n",
        "file2 = 'D:\\\\Studies\\\\Project\\\\Resources\\\\dipp.csv'\n",
        "\n",
        "\n",
        "dataframe = pd.read_csv(file1, index_col=0)\n",
        "dataframe.dropna(thresh = 2, inplace=True)\n",
        "# dataframe.isnull().sum()"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LbfmUXLh0DTF",
        "colab_type": "code",
        "colab": {},
        "outputId": "92a8e038-b40b-4a28-e996-3cc3d5ee5608"
      },
      "source": [
        "dataframe.head()"
      ],
      "execution_count": 0,
      "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>2000-01</th>\n",
              "      <th>2001-02</th>\n",
              "      <th>2002-03</th>\n",
              "      <th>2003-04</th>\n",
              "      <th>2004-05</th>\n",
              "      <th>2005-06</th>\n",
              "      <th>2006-07</th>\n",
              "      <th>2007-08</th>\n",
              "      <th>2008-09</th>\n",
              "      <th>2009-10</th>\n",
              "      <th>2010-11</th>\n",
              "      <th>2011-12</th>\n",
              "      <th>2012-13</th>\n",
              "      <th>2013-14</th>\n",
              "      <th>2014-15</th>\n",
              "      <th>2015-16</th>\n",
              "      <th>2016-17</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Sector</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>METALLURGICAL INDUSTRIES</th>\n",
              "      <td>22.69</td>\n",
              "      <td>14.14</td>\n",
              "      <td>36.61</td>\n",
              "      <td>8.11</td>\n",
              "      <td>200.38</td>\n",
              "      <td>149.13</td>\n",
              "      <td>169.94</td>\n",
              "      <td>1175.75</td>\n",
              "      <td>959.94</td>\n",
              "      <td>419.88</td>\n",
              "      <td>1098.14</td>\n",
              "      <td>1786.14</td>\n",
              "      <td>1466.23</td>\n",
              "      <td>567.63</td>\n",
              "      <td>359.34</td>\n",
              "      <td>456.31</td>\n",
              "      <td>1440.18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>MINING</th>\n",
              "      <td>1.32</td>\n",
              "      <td>6.52</td>\n",
              "      <td>10.06</td>\n",
              "      <td>23.48</td>\n",
              "      <td>9.92</td>\n",
              "      <td>7.40</td>\n",
              "      <td>6.62</td>\n",
              "      <td>444.36</td>\n",
              "      <td>34.16</td>\n",
              "      <td>174.40</td>\n",
              "      <td>79.51</td>\n",
              "      <td>142.65</td>\n",
              "      <td>57.89</td>\n",
              "      <td>12.73</td>\n",
              "      <td>684.39</td>\n",
              "      <td>520.67</td>\n",
              "      <td>55.75</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>POWER</th>\n",
              "      <td>89.42</td>\n",
              "      <td>757.44</td>\n",
              "      <td>59.11</td>\n",
              "      <td>27.09</td>\n",
              "      <td>43.37</td>\n",
              "      <td>72.69</td>\n",
              "      <td>157.15</td>\n",
              "      <td>988.68</td>\n",
              "      <td>907.66</td>\n",
              "      <td>1271.79</td>\n",
              "      <td>1271.77</td>\n",
              "      <td>1652.38</td>\n",
              "      <td>535.68</td>\n",
              "      <td>1066.08</td>\n",
              "      <td>707.04</td>\n",
              "      <td>868.80</td>\n",
              "      <td>1112.98</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>NON-CONVENTIONAL ENERGY</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>1.70</td>\n",
              "      <td>4.14</td>\n",
              "      <td>1.27</td>\n",
              "      <td>1.35</td>\n",
              "      <td>2.44</td>\n",
              "      <td>58.82</td>\n",
              "      <td>125.88</td>\n",
              "      <td>622.52</td>\n",
              "      <td>214.40</td>\n",
              "      <td>452.17</td>\n",
              "      <td>1106.52</td>\n",
              "      <td>414.25</td>\n",
              "      <td>615.95</td>\n",
              "      <td>776.51</td>\n",
              "      <td>783.57</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>COAL PRODUCTION</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.00</td>\n",
              "      <td>9.14</td>\n",
              "      <td>1.30</td>\n",
              "      <td>14.08</td>\n",
              "      <td>0.22</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>2.96</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                          2000-01  2001-02  2002-03  2003-04  2004-05  \\\n",
              "Sector                                                                  \n",
              "METALLURGICAL INDUSTRIES    22.69    14.14    36.61     8.11   200.38   \n",
              "MINING                       1.32     6.52    10.06    23.48     9.92   \n",
              "POWER                       89.42   757.44    59.11    27.09    43.37   \n",
              "NON-CONVENTIONAL ENERGY      0.00     0.00     1.70     4.14     1.27   \n",
              "COAL PRODUCTION              0.00     0.00     0.00     0.04     0.00   \n",
              "\n",
              "                          2005-06  2006-07  2007-08  2008-09  2009-10  \\\n",
              "Sector                                                                  \n",
              "METALLURGICAL INDUSTRIES   149.13   169.94  1175.75   959.94   419.88   \n",
              "MINING                       7.40     6.62   444.36    34.16   174.40   \n",
              "POWER                       72.69   157.15   988.68   907.66  1271.79   \n",
              "NON-CONVENTIONAL ENERGY      1.35     2.44    58.82   125.88   622.52   \n",
              "COAL PRODUCTION              9.14     1.30    14.08     0.22     0.00   \n",
              "\n",
              "                          2010-11  2011-12  2012-13  2013-14  2014-15  \\\n",
              "Sector                                                                  \n",
              "METALLURGICAL INDUSTRIES  1098.14  1786.14  1466.23   567.63   359.34   \n",
              "MINING                      79.51   142.65    57.89    12.73   684.39   \n",
              "POWER                     1271.77  1652.38   535.68  1066.08   707.04   \n",
              "NON-CONVENTIONAL ENERGY    214.40   452.17  1106.52   414.25   615.95   \n",
              "COAL PRODUCTION              0.00     0.00     0.00     2.96     0.00   \n",
              "\n",
              "                          2015-16  2016-17  \n",
              "Sector                                      \n",
              "METALLURGICAL INDUSTRIES   456.31  1440.18  \n",
              "MINING                     520.67    55.75  \n",
              "POWER                      868.80  1112.98  \n",
              "NON-CONVENTIONAL ENERGY    776.51   783.57  \n",
              "COAL PRODUCTION              0.00     0.00  "
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jLwYjmGT0DTI",
        "colab_type": "code",
        "colab": {},
        "outputId": "7929cc97-9a7a-489e-b32c-3d9e8b215469"
      },
      "source": [
        "dataframe2 = pd.read_csv(file2,index_col=0)\n",
        "dataframe2.head()"
      ],
      "execution_count": 0,
      "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>AMOUNT_IN_RS</th>\n",
              "      <th>AMOUNT_IN_USD</th>\n",
              "      <th>UNIT</th>\n",
              "      <th>FROM_DATE</th>\n",
              "      <th>TO_DATE</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>SECTOR_NAME</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>METALLURGICAL INDUSTRIES</th>\n",
              "      <td>601207.09</td>\n",
              "      <td>11372.21</td>\n",
              "      <td>MILLION</td>\n",
              "      <td>01/04/2000</td>\n",
              "      <td>30/06/2019</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>MINING</th>\n",
              "      <td>150461.67</td>\n",
              "      <td>2651.22</td>\n",
              "      <td>MILLION</td>\n",
              "      <td>01/04/2000</td>\n",
              "      <td>30/06/2019</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>POWER</th>\n",
              "      <td>792091.15</td>\n",
              "      <td>14505.55</td>\n",
              "      <td>MILLION</td>\n",
              "      <td>01/04/2000</td>\n",
              "      <td>30/06/2019</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>NON-CONVENTIONAL ENERGY</th>\n",
              "      <td>489595.36</td>\n",
              "      <td>8063.07</td>\n",
              "      <td>MILLION</td>\n",
              "      <td>01/04/2000</td>\n",
              "      <td>30/06/2019</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>COAL PRODUCTION</th>\n",
              "      <td>1191.89</td>\n",
              "      <td>27.73</td>\n",
              "      <td>MILLION</td>\n",
              "      <td>01/04/2000</td>\n",
              "      <td>30/06/2019</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                          AMOUNT_IN_RS  AMOUNT_IN_USD     UNIT   FROM_DATE  \\\n",
              "SECTOR_NAME                                                                  \n",
              "METALLURGICAL INDUSTRIES     601207.09       11372.21  MILLION  01/04/2000   \n",
              "MINING                       150461.67        2651.22  MILLION  01/04/2000   \n",
              "POWER                        792091.15       14505.55  MILLION  01/04/2000   \n",
              "NON-CONVENTIONAL ENERGY      489595.36        8063.07  MILLION  01/04/2000   \n",
              "COAL PRODUCTION                1191.89          27.73  MILLION  01/04/2000   \n",
              "\n",
              "                             TO_DATE  \n",
              "SECTOR_NAME                           \n",
              "METALLURGICAL INDUSTRIES  30/06/2019  \n",
              "MINING                    30/06/2019  \n",
              "POWER                     30/06/2019  \n",
              "NON-CONVENTIONAL ENERGY   30/06/2019  \n",
              "COAL PRODUCTION           30/06/2019  "
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MKdeuICl0DTL",
        "colab_type": "text"
      },
      "source": [
        "## Preprocessing the dataframes and joining"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "J6hHonc-0DTM",
        "colab_type": "code",
        "colab": {},
        "outputId": "299b2301-70fa-49ba-925a-19d8dfe3de7d"
      },
      "source": [
        "data_sum = dataframe.copy()\n",
        "data_sum['Sum_upto_16-17'] = dataframe.sum(axis=1)\n",
        "dataframe2 = dataframe2[['AMOUNT_IN_USD']]\n",
        "data_join = data_sum.join(dataframe2,how='outer')\n",
        "data_join"
      ],
      "execution_count": 0,
      "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>2000-01</th>\n",
              "      <th>2001-02</th>\n",
              "      <th>2002-03</th>\n",
              "      <th>2003-04</th>\n",
              "      <th>2004-05</th>\n",
              "      <th>2005-06</th>\n",
              "      <th>2006-07</th>\n",
              "      <th>2007-08</th>\n",
              "      <th>2008-09</th>\n",
              "      <th>2009-10</th>\n",
              "      <th>2010-11</th>\n",
              "      <th>2011-12</th>\n",
              "      <th>2012-13</th>\n",
              "      <th>2013-14</th>\n",
              "      <th>2014-15</th>\n",
              "      <th>2015-16</th>\n",
              "      <th>2016-17</th>\n",
              "      <th>Sum_upto_16-17</th>\n",
              "      <th>AMOUNT_IN_USD</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>AGRICULTURAL MACHINERY</th>\n",
              "      <td>3.64</td>\n",
              "      <td>1.04</td>\n",
              "      <td>13.48</td>\n",
              "      <td>47.54</td>\n",
              "      <td>0.00</td>\n",
              "      <td>92.71</td>\n",
              "      <td>25.19</td>\n",
              "      <td>6.72</td>\n",
              "      <td>5.57</td>\n",
              "      <td>1.88</td>\n",
              "      <td>0.49</td>\n",
              "      <td>2.77</td>\n",
              "      <td>95.41</td>\n",
              "      <td>48.78</td>\n",
              "      <td>72.35</td>\n",
              "      <td>16.44</td>\n",
              "      <td>15.19</td>\n",
              "      <td>449.20</td>\n",
              "      <td>540.07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>AGRICULTURE SERVICES</th>\n",
              "      <td>17.52</td>\n",
              "      <td>14.06</td>\n",
              "      <td>11.01</td>\n",
              "      <td>0.59</td>\n",
              "      <td>3.83</td>\n",
              "      <td>9.08</td>\n",
              "      <td>12.53</td>\n",
              "      <td>58.13</td>\n",
              "      <td>5.35</td>\n",
              "      <td>1222.22</td>\n",
              "      <td>43.90</td>\n",
              "      <td>49.02</td>\n",
              "      <td>161.47</td>\n",
              "      <td>91.01</td>\n",
              "      <td>59.95</td>\n",
              "      <td>84.65</td>\n",
              "      <td>76.43</td>\n",
              "      <td>1920.75</td>\n",
              "      <td>2127.83</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>AIR TRANSPORT (INCLUDING AIR FREIGHT)</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>3.80</td>\n",
              "      <td>0.94</td>\n",
              "      <td>4.11</td>\n",
              "      <td>10.27</td>\n",
              "      <td>62.29</td>\n",
              "      <td>99.08</td>\n",
              "      <td>61.37</td>\n",
              "      <td>23.71</td>\n",
              "      <td>136.60</td>\n",
              "      <td>31.22</td>\n",
              "      <td>15.89</td>\n",
              "      <td>45.95</td>\n",
              "      <td>74.56</td>\n",
              "      <td>361.25</td>\n",
              "      <td>83.40</td>\n",
              "      <td>1014.44</td>\n",
              "      <td>1904.37</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>AUTOMOBILE INDUSTRY</th>\n",
              "      <td>195.33</td>\n",
              "      <td>235.76</td>\n",
              "      <td>419.96</td>\n",
              "      <td>119.09</td>\n",
              "      <td>121.97</td>\n",
              "      <td>139.93</td>\n",
              "      <td>260.72</td>\n",
              "      <td>656.10</td>\n",
              "      <td>1150.03</td>\n",
              "      <td>1236.29</td>\n",
              "      <td>1299.41</td>\n",
              "      <td>922.99</td>\n",
              "      <td>1537.28</td>\n",
              "      <td>1517.28</td>\n",
              "      <td>2725.64</td>\n",
              "      <td>2526.82</td>\n",
              "      <td>1609.32</td>\n",
              "      <td>16673.92</td>\n",
              "      <td>22358.84</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>BOILERS AND STEAM GENERATING PLANTS</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.54</td>\n",
              "      <td>0.00</td>\n",
              "      <td>3.31</td>\n",
              "      <td>1.51</td>\n",
              "      <td>0.00</td>\n",
              "      <td>3.96</td>\n",
              "      <td>0.63</td>\n",
              "      <td>31.79</td>\n",
              "      <td>20.05</td>\n",
              "      <td>0.17</td>\n",
              "      <td>1.33</td>\n",
              "      <td>77.91</td>\n",
              "      <td>53.91</td>\n",
              "      <td>195.15</td>\n",
              "      <td>263.37</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>CEMENT AND GYPSUM PRODUCTS</th>\n",
              "      <td>67.72</td>\n",
              "      <td>139.90</td>\n",
              "      <td>21.08</td>\n",
              "      <td>9.58</td>\n",
              "      <td>0.16</td>\n",
              "      <td>452.08</td>\n",
              "      <td>242.47</td>\n",
              "      <td>16.89</td>\n",
              "      <td>724.80</td>\n",
              "      <td>33.80</td>\n",
              "      <td>637.68</td>\n",
              "      <td>267.90</td>\n",
              "      <td>12.38</td>\n",
              "      <td>254.01</td>\n",
              "      <td>208.99</td>\n",
              "      <td>19.69</td>\n",
              "      <td>2130.10</td>\n",
              "      <td>5239.23</td>\n",
              "      <td>5277.26</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>CERAMICS</th>\n",
              "      <td>4.03</td>\n",
              "      <td>0.78</td>\n",
              "      <td>0.21</td>\n",
              "      <td>1.47</td>\n",
              "      <td>26.79</td>\n",
              "      <td>5.67</td>\n",
              "      <td>122.23</td>\n",
              "      <td>115.11</td>\n",
              "      <td>198.43</td>\n",
              "      <td>7.21</td>\n",
              "      <td>12.00</td>\n",
              "      <td>9.87</td>\n",
              "      <td>4.33</td>\n",
              "      <td>150.09</td>\n",
              "      <td>35.29</td>\n",
              "      <td>51.21</td>\n",
              "      <td>15.40</td>\n",
              "      <td>760.12</td>\n",
              "      <td>868.46</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>CHEMICALS (OTHER THAN FERTILIZERS)</th>\n",
              "      <td>111.14</td>\n",
              "      <td>87.23</td>\n",
              "      <td>128.12</td>\n",
              "      <td>20.24</td>\n",
              "      <td>69.39</td>\n",
              "      <td>387.72</td>\n",
              "      <td>138.85</td>\n",
              "      <td>233.70</td>\n",
              "      <td>651.22</td>\n",
              "      <td>365.94</td>\n",
              "      <td>2354.40</td>\n",
              "      <td>4040.71</td>\n",
              "      <td>292.16</td>\n",
              "      <td>786.76</td>\n",
              "      <td>762.76</td>\n",
              "      <td>1469.95</td>\n",
              "      <td>1392.80</td>\n",
              "      <td>13293.09</td>\n",
              "      <td>16726.96</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>COAL PRODUCTION</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.00</td>\n",
              "      <td>9.14</td>\n",
              "      <td>1.30</td>\n",
              "      <td>14.08</td>\n",
              "      <td>0.22</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>2.96</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>27.74</td>\n",
              "      <td>27.73</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>COIR</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.47</td>\n",
              "      <td>0.59</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.25</td>\n",
              "      <td>0.10</td>\n",
              "      <td>0.55</td>\n",
              "      <td>0.15</td>\n",
              "      <td>0.54</td>\n",
              "      <td>1.36</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>4.06</td>\n",
              "      <td>4.07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>COMMERCIAL, OFFICE &amp; HOUSEHOLD EQUIPMENTS</th>\n",
              "      <td>12.20</td>\n",
              "      <td>4.87</td>\n",
              "      <td>2.33</td>\n",
              "      <td>10.41</td>\n",
              "      <td>14.13</td>\n",
              "      <td>25.54</td>\n",
              "      <td>5.42</td>\n",
              "      <td>9.83</td>\n",
              "      <td>12.63</td>\n",
              "      <td>78.98</td>\n",
              "      <td>25.12</td>\n",
              "      <td>29.04</td>\n",
              "      <td>24.33</td>\n",
              "      <td>21.13</td>\n",
              "      <td>33.39</td>\n",
              "      <td>36.68</td>\n",
              "      <td>7.44</td>\n",
              "      <td>353.47</td>\n",
              "      <td>386.27</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>COMPUTER SOFTWARE &amp; HARDWARE</th>\n",
              "      <td>228.39</td>\n",
              "      <td>419.39</td>\n",
              "      <td>314.24</td>\n",
              "      <td>368.32</td>\n",
              "      <td>527.90</td>\n",
              "      <td>1359.97</td>\n",
              "      <td>2613.33</td>\n",
              "      <td>1382.25</td>\n",
              "      <td>1543.34</td>\n",
              "      <td>871.86</td>\n",
              "      <td>779.81</td>\n",
              "      <td>796.35</td>\n",
              "      <td>485.96</td>\n",
              "      <td>1126.27</td>\n",
              "      <td>2296.04</td>\n",
              "      <td>5904.36</td>\n",
              "      <td>3651.71</td>\n",
              "      <td>24669.49</td>\n",
              "      <td>39478.90</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>CONSTRUCTION (INFRASTRUCTURE) ACTIVITIES</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.93</td>\n",
              "      <td>64.06</td>\n",
              "      <td>182.92</td>\n",
              "      <td>172.70</td>\n",
              "      <td>324.56</td>\n",
              "      <td>675.07</td>\n",
              "      <td>386.28</td>\n",
              "      <td>283.89</td>\n",
              "      <td>485.37</td>\n",
              "      <td>870.25</td>\n",
              "      <td>4510.71</td>\n",
              "      <td>1860.73</td>\n",
              "      <td>9817.47</td>\n",
              "      <td>15337.19</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>CONSTRUCTION DEVELOPMENT: Townships, housing, built-up infrastructure and construction-development projects</th>\n",
              "      <td>24.33</td>\n",
              "      <td>51.75</td>\n",
              "      <td>36.10</td>\n",
              "      <td>47.04</td>\n",
              "      <td>152.06</td>\n",
              "      <td>228.71</td>\n",
              "      <td>1392.95</td>\n",
              "      <td>3887.33</td>\n",
              "      <td>4657.51</td>\n",
              "      <td>5466.13</td>\n",
              "      <td>1663.03</td>\n",
              "      <td>3140.78</td>\n",
              "      <td>1332.49</td>\n",
              "      <td>1226.05</td>\n",
              "      <td>769.14</td>\n",
              "      <td>112.55</td>\n",
              "      <td>105.14</td>\n",
              "      <td>24293.09</td>\n",
              "      <td>25122.30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>CONSULTANCY SERVICES</th>\n",
              "      <td>4.25</td>\n",
              "      <td>66.22</td>\n",
              "      <td>25.70</td>\n",
              "      <td>46.20</td>\n",
              "      <td>252.42</td>\n",
              "      <td>47.40</td>\n",
              "      <td>114.68</td>\n",
              "      <td>233.32</td>\n",
              "      <td>256.59</td>\n",
              "      <td>341.31</td>\n",
              "      <td>274.84</td>\n",
              "      <td>289.89</td>\n",
              "      <td>142.32</td>\n",
              "      <td>285.85</td>\n",
              "      <td>458.13</td>\n",
              "      <td>517.47</td>\n",
              "      <td>261.14</td>\n",
              "      <td>3617.73</td>\n",
              "      <td>5174.72</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>DEFENCE INDUSTRIES</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.05</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>3.66</td>\n",
              "      <td>0.41</td>\n",
              "      <td>0.82</td>\n",
              "      <td>0.08</td>\n",
              "      <td>0.10</td>\n",
              "      <td>0.00</td>\n",
              "      <td>5.12</td>\n",
              "      <td>7.32</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>DIAMOND,GOLD ORNAMENTS</th>\n",
              "      <td>18.83</td>\n",
              "      <td>0.36</td>\n",
              "      <td>1.30</td>\n",
              "      <td>1.96</td>\n",
              "      <td>8.58</td>\n",
              "      <td>15.52</td>\n",
              "      <td>61.97</td>\n",
              "      <td>59.15</td>\n",
              "      <td>83.50</td>\n",
              "      <td>31.08</td>\n",
              "      <td>19.59</td>\n",
              "      <td>36.30</td>\n",
              "      <td>52.61</td>\n",
              "      <td>42.56</td>\n",
              "      <td>280.18</td>\n",
              "      <td>58.54</td>\n",
              "      <td>123.92</td>\n",
              "      <td>895.95</td>\n",
              "      <td>1159.93</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>DRUGS &amp; PHARMACEUTICALS</th>\n",
              "      <td>35.94</td>\n",
              "      <td>77.94</td>\n",
              "      <td>40.07</td>\n",
              "      <td>108.91</td>\n",
              "      <td>293.36</td>\n",
              "      <td>172.44</td>\n",
              "      <td>224.20</td>\n",
              "      <td>340.35</td>\n",
              "      <td>4246.76</td>\n",
              "      <td>213.08</td>\n",
              "      <td>209.38</td>\n",
              "      <td>3232.28</td>\n",
              "      <td>1123.46</td>\n",
              "      <td>1279.34</td>\n",
              "      <td>1497.74</td>\n",
              "      <td>754.26</td>\n",
              "      <td>857.39</td>\n",
              "      <td>14706.90</td>\n",
              "      <td>16210.22</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>DYE-STUFFS</th>\n",
              "      <td>1.05</td>\n",
              "      <td>0.18</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.43</td>\n",
              "      <td>1.18</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>5.51</td>\n",
              "      <td>1.17</td>\n",
              "      <td>4.02</td>\n",
              "      <td>5.37</td>\n",
              "      <td>0.58</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>54.89</td>\n",
              "      <td>3.32</td>\n",
              "      <td>10.70</td>\n",
              "      <td>88.40</td>\n",
              "      <td>92.45</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>EARTH-MOVING MACHINERY</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.11</td>\n",
              "      <td>13.77</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.10</td>\n",
              "      <td>50.87</td>\n",
              "      <td>0.99</td>\n",
              "      <td>67.94</td>\n",
              "      <td>2.27</td>\n",
              "      <td>15.62</td>\n",
              "      <td>1.77</td>\n",
              "      <td>16.40</td>\n",
              "      <td>5.10</td>\n",
              "      <td>34.44</td>\n",
              "      <td>30.11</td>\n",
              "      <td>97.66</td>\n",
              "      <td>52.23</td>\n",
              "      <td>389.39</td>\n",
              "      <td>458.96</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>EDUCATION</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.19</td>\n",
              "      <td>1.97</td>\n",
              "      <td>3.16</td>\n",
              "      <td>41.81</td>\n",
              "      <td>43.59</td>\n",
              "      <td>214.52</td>\n",
              "      <td>63.35</td>\n",
              "      <td>37.94</td>\n",
              "      <td>105.62</td>\n",
              "      <td>172.20</td>\n",
              "      <td>262.09</td>\n",
              "      <td>78.86</td>\n",
              "      <td>230.78</td>\n",
              "      <td>160.12</td>\n",
              "      <td>1416.20</td>\n",
              "      <td>2506.52</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ELECTRICAL EQUIPMENTS</th>\n",
              "      <td>79.76</td>\n",
              "      <td>65.76</td>\n",
              "      <td>34.71</td>\n",
              "      <td>73.20</td>\n",
              "      <td>97.40</td>\n",
              "      <td>39.50</td>\n",
              "      <td>76.85</td>\n",
              "      <td>653.74</td>\n",
              "      <td>417.35</td>\n",
              "      <td>728.27</td>\n",
              "      <td>153.90</td>\n",
              "      <td>566.39</td>\n",
              "      <td>195.87</td>\n",
              "      <td>134.31</td>\n",
              "      <td>574.83</td>\n",
              "      <td>444.88</td>\n",
              "      <td>2230.69</td>\n",
              "      <td>6567.41</td>\n",
              "      <td>8180.56</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ELECTRONICS</th>\n",
              "      <td>8.34</td>\n",
              "      <td>12.47</td>\n",
              "      <td>295.88</td>\n",
              "      <td>82.31</td>\n",
              "      <td>88.10</td>\n",
              "      <td>40.91</td>\n",
              "      <td>42.14</td>\n",
              "      <td>136.03</td>\n",
              "      <td>147.51</td>\n",
              "      <td>52.14</td>\n",
              "      <td>59.72</td>\n",
              "      <td>194.41</td>\n",
              "      <td>38.24</td>\n",
              "      <td>132.58</td>\n",
              "      <td>96.84</td>\n",
              "      <td>208.39</td>\n",
              "      <td>83.97</td>\n",
              "      <td>1719.98</td>\n",
              "      <td>2452.85</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>FERMENTATION INDUSTRIES</th>\n",
              "      <td>16.02</td>\n",
              "      <td>11.04</td>\n",
              "      <td>8.07</td>\n",
              "      <td>1.70</td>\n",
              "      <td>139.00</td>\n",
              "      <td>169.83</td>\n",
              "      <td>27.58</td>\n",
              "      <td>270.05</td>\n",
              "      <td>144.70</td>\n",
              "      <td>112.02</td>\n",
              "      <td>57.71</td>\n",
              "      <td>69.70</td>\n",
              "      <td>107.21</td>\n",
              "      <td>814.58</td>\n",
              "      <td>225.38</td>\n",
              "      <td>202.36</td>\n",
              "      <td>110.86</td>\n",
              "      <td>2487.81</td>\n",
              "      <td>2723.98</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>FERTILIZERS</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>16.38</td>\n",
              "      <td>21.58</td>\n",
              "      <td>13.46</td>\n",
              "      <td>4.24</td>\n",
              "      <td>5.01</td>\n",
              "      <td>1.95</td>\n",
              "      <td>133.75</td>\n",
              "      <td>8.20</td>\n",
              "      <td>18.18</td>\n",
              "      <td>32.60</td>\n",
              "      <td>42.55</td>\n",
              "      <td>20.65</td>\n",
              "      <td>225.32</td>\n",
              "      <td>20.93</td>\n",
              "      <td>0.89</td>\n",
              "      <td>565.69</td>\n",
              "      <td>683.18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>FOOD PROCESSING INDUSTRIES</th>\n",
              "      <td>45.75</td>\n",
              "      <td>219.39</td>\n",
              "      <td>36.88</td>\n",
              "      <td>109.22</td>\n",
              "      <td>43.98</td>\n",
              "      <td>41.74</td>\n",
              "      <td>102.00</td>\n",
              "      <td>70.17</td>\n",
              "      <td>102.71</td>\n",
              "      <td>278.89</td>\n",
              "      <td>188.67</td>\n",
              "      <td>170.21</td>\n",
              "      <td>401.46</td>\n",
              "      <td>3982.89</td>\n",
              "      <td>515.86</td>\n",
              "      <td>505.88</td>\n",
              "      <td>727.22</td>\n",
              "      <td>7542.92</td>\n",
              "      <td>9405.09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>GLASS</th>\n",
              "      <td>33.87</td>\n",
              "      <td>8.37</td>\n",
              "      <td>44.98</td>\n",
              "      <td>5.24</td>\n",
              "      <td>8.36</td>\n",
              "      <td>0.81</td>\n",
              "      <td>1.43</td>\n",
              "      <td>11.04</td>\n",
              "      <td>23.16</td>\n",
              "      <td>2.83</td>\n",
              "      <td>7.60</td>\n",
              "      <td>32.22</td>\n",
              "      <td>209.16</td>\n",
              "      <td>43.09</td>\n",
              "      <td>41.82</td>\n",
              "      <td>25.78</td>\n",
              "      <td>51.69</td>\n",
              "      <td>551.45</td>\n",
              "      <td>662.35</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>GLUE AND GELATIN</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.94</td>\n",
              "      <td>5.22</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>2.28</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.27</td>\n",
              "      <td>0.01</td>\n",
              "      <td>5.84</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.97</td>\n",
              "      <td>21.44</td>\n",
              "      <td>0.82</td>\n",
              "      <td>90.60</td>\n",
              "      <td>128.39</td>\n",
              "      <td>146.41</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>HOSPITAL &amp; DIAGNOSTIC CENTRES</th>\n",
              "      <td>0.00</td>\n",
              "      <td>6.93</td>\n",
              "      <td>29.13</td>\n",
              "      <td>24.08</td>\n",
              "      <td>26.19</td>\n",
              "      <td>32.53</td>\n",
              "      <td>38.14</td>\n",
              "      <td>241.76</td>\n",
              "      <td>239.71</td>\n",
              "      <td>135.57</td>\n",
              "      <td>256.00</td>\n",
              "      <td>310.43</td>\n",
              "      <td>256.86</td>\n",
              "      <td>684.58</td>\n",
              "      <td>567.85</td>\n",
              "      <td>742.35</td>\n",
              "      <td>747.38</td>\n",
              "      <td>4339.49</td>\n",
              "      <td>6342.40</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>HOTEL &amp; TOURISM</th>\n",
              "      <td>13.20</td>\n",
              "      <td>32.12</td>\n",
              "      <td>33.75</td>\n",
              "      <td>49.36</td>\n",
              "      <td>37.01</td>\n",
              "      <td>71.78</td>\n",
              "      <td>195.66</td>\n",
              "      <td>421.47</td>\n",
              "      <td>463.92</td>\n",
              "      <td>753.02</td>\n",
              "      <td>308.05</td>\n",
              "      <td>992.86</td>\n",
              "      <td>3259.05</td>\n",
              "      <td>486.38</td>\n",
              "      <td>777.01</td>\n",
              "      <td>1332.69</td>\n",
              "      <td>916.13</td>\n",
              "      <td>10143.46</td>\n",
              "      <td>12966.61</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>MATHEMATICAL,SURVEYING AND DRAWING INSTRUMENTS</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>1.27</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>6.71</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>7.98</td>\n",
              "      <td>7.98</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>MEDICAL AND SURGICAL APPLIANCES</th>\n",
              "      <td>5.42</td>\n",
              "      <td>42.35</td>\n",
              "      <td>21.63</td>\n",
              "      <td>1.97</td>\n",
              "      <td>5.35</td>\n",
              "      <td>1.52</td>\n",
              "      <td>13.43</td>\n",
              "      <td>13.17</td>\n",
              "      <td>75.42</td>\n",
              "      <td>167.35</td>\n",
              "      <td>32.22</td>\n",
              "      <td>141.61</td>\n",
              "      <td>83.02</td>\n",
              "      <td>173.48</td>\n",
              "      <td>145.93</td>\n",
              "      <td>173.26</td>\n",
              "      <td>479.71</td>\n",
              "      <td>1576.84</td>\n",
              "      <td>1833.90</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>METALLURGICAL INDUSTRIES</th>\n",
              "      <td>22.69</td>\n",
              "      <td>14.14</td>\n",
              "      <td>36.61</td>\n",
              "      <td>8.11</td>\n",
              "      <td>200.38</td>\n",
              "      <td>149.13</td>\n",
              "      <td>169.94</td>\n",
              "      <td>1175.75</td>\n",
              "      <td>959.94</td>\n",
              "      <td>419.88</td>\n",
              "      <td>1098.14</td>\n",
              "      <td>1786.14</td>\n",
              "      <td>1466.23</td>\n",
              "      <td>567.63</td>\n",
              "      <td>359.34</td>\n",
              "      <td>456.31</td>\n",
              "      <td>1440.18</td>\n",
              "      <td>10330.54</td>\n",
              "      <td>11372.21</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>MINING</th>\n",
              "      <td>1.32</td>\n",
              "      <td>6.52</td>\n",
              "      <td>10.06</td>\n",
              "      <td>23.48</td>\n",
              "      <td>9.92</td>\n",
              "      <td>7.40</td>\n",
              "      <td>6.62</td>\n",
              "      <td>444.36</td>\n",
              "      <td>34.16</td>\n",
              "      <td>174.40</td>\n",
              "      <td>79.51</td>\n",
              "      <td>142.65</td>\n",
              "      <td>57.89</td>\n",
              "      <td>12.73</td>\n",
              "      <td>684.39</td>\n",
              "      <td>520.67</td>\n",
              "      <td>55.75</td>\n",
              "      <td>2271.83</td>\n",
              "      <td>2651.22</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>MISCELLANEOUS INDUSTRIES</th>\n",
              "      <td>832.07</td>\n",
              "      <td>221.37</td>\n",
              "      <td>218.76</td>\n",
              "      <td>235.48</td>\n",
              "      <td>121.83</td>\n",
              "      <td>164.76</td>\n",
              "      <td>304.87</td>\n",
              "      <td>528.42</td>\n",
              "      <td>1549.70</td>\n",
              "      <td>1147.56</td>\n",
              "      <td>1475.97</td>\n",
              "      <td>813.38</td>\n",
              "      <td>229.49</td>\n",
              "      <td>468.74</td>\n",
              "      <td>765.88</td>\n",
              "      <td>668.77</td>\n",
              "      <td>296.40</td>\n",
              "      <td>10043.45</td>\n",
              "      <td>11334.42</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>MISCELLANEOUS MECHANICAL &amp; ENGINEERING INDUSTRIES</th>\n",
              "      <td>44.50</td>\n",
              "      <td>61.40</td>\n",
              "      <td>45.07</td>\n",
              "      <td>22.73</td>\n",
              "      <td>12.83</td>\n",
              "      <td>51.22</td>\n",
              "      <td>84.44</td>\n",
              "      <td>211.15</td>\n",
              "      <td>142.31</td>\n",
              "      <td>149.59</td>\n",
              "      <td>108.67</td>\n",
              "      <td>1295.34</td>\n",
              "      <td>89.45</td>\n",
              "      <td>288.13</td>\n",
              "      <td>186.69</td>\n",
              "      <td>274.57</td>\n",
              "      <td>245.24</td>\n",
              "      <td>3313.33</td>\n",
              "      <td>3594.59</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>NON-CONVENTIONAL ENERGY</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>1.70</td>\n",
              "      <td>4.14</td>\n",
              "      <td>1.27</td>\n",
              "      <td>1.35</td>\n",
              "      <td>2.44</td>\n",
              "      <td>58.82</td>\n",
              "      <td>125.88</td>\n",
              "      <td>622.52</td>\n",
              "      <td>214.40</td>\n",
              "      <td>452.17</td>\n",
              "      <td>1106.52</td>\n",
              "      <td>414.25</td>\n",
              "      <td>615.95</td>\n",
              "      <td>776.51</td>\n",
              "      <td>783.57</td>\n",
              "      <td>5181.49</td>\n",
              "      <td>8063.07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>PAPER AND PULP (INCLUDING PAPER PRODUCTS)</th>\n",
              "      <td>60.04</td>\n",
              "      <td>16.70</td>\n",
              "      <td>7.36</td>\n",
              "      <td>7.15</td>\n",
              "      <td>2.70</td>\n",
              "      <td>27.38</td>\n",
              "      <td>5.08</td>\n",
              "      <td>31.24</td>\n",
              "      <td>272.51</td>\n",
              "      <td>16.42</td>\n",
              "      <td>6.53</td>\n",
              "      <td>407.35</td>\n",
              "      <td>5.09</td>\n",
              "      <td>26.86</td>\n",
              "      <td>116.21</td>\n",
              "      <td>85.21</td>\n",
              "      <td>197.61</td>\n",
              "      <td>1291.44</td>\n",
              "      <td>1434.83</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>PETROLEUM &amp; NATURAL GAS</th>\n",
              "      <td>9.35</td>\n",
              "      <td>211.07</td>\n",
              "      <td>56.78</td>\n",
              "      <td>80.64</td>\n",
              "      <td>102.78</td>\n",
              "      <td>12.09</td>\n",
              "      <td>87.71</td>\n",
              "      <td>1405.04</td>\n",
              "      <td>349.29</td>\n",
              "      <td>265.53</td>\n",
              "      <td>556.43</td>\n",
              "      <td>2029.98</td>\n",
              "      <td>214.80</td>\n",
              "      <td>112.23</td>\n",
              "      <td>1079.02</td>\n",
              "      <td>103.02</td>\n",
              "      <td>180.40</td>\n",
              "      <td>6856.16</td>\n",
              "      <td>7022.14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>PHOTOGRAPHIC RAW FILM AND PAPER</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.60</td>\n",
              "      <td>0.24</td>\n",
              "      <td>6.16</td>\n",
              "      <td>0.00</td>\n",
              "      <td>2.81</td>\n",
              "      <td>54.86</td>\n",
              "      <td>1.05</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.81</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.75</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>67.28</td>\n",
              "      <td>67.29</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>PORTS</th>\n",
              "      <td>0.00</td>\n",
              "      <td>15.48</td>\n",
              "      <td>2.03</td>\n",
              "      <td>116.36</td>\n",
              "      <td>13.04</td>\n",
              "      <td>0.50</td>\n",
              "      <td>0.00</td>\n",
              "      <td>918.18</td>\n",
              "      <td>493.15</td>\n",
              "      <td>65.41</td>\n",
              "      <td>10.92</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.31</td>\n",
              "      <td>1.90</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>1637.28</td>\n",
              "      <td>1637.30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>POWER</th>\n",
              "      <td>89.42</td>\n",
              "      <td>757.44</td>\n",
              "      <td>59.11</td>\n",
              "      <td>27.09</td>\n",
              "      <td>43.37</td>\n",
              "      <td>72.69</td>\n",
              "      <td>157.15</td>\n",
              "      <td>988.68</td>\n",
              "      <td>907.66</td>\n",
              "      <td>1271.79</td>\n",
              "      <td>1271.77</td>\n",
              "      <td>1652.38</td>\n",
              "      <td>535.68</td>\n",
              "      <td>1066.08</td>\n",
              "      <td>707.04</td>\n",
              "      <td>868.80</td>\n",
              "      <td>1112.98</td>\n",
              "      <td>11589.13</td>\n",
              "      <td>14505.55</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>PRIME MOVER (OTHER THAN ELECTRICAL GENERATORS)</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>2.66</td>\n",
              "      <td>0.74</td>\n",
              "      <td>25.57</td>\n",
              "      <td>40.53</td>\n",
              "      <td>74.88</td>\n",
              "      <td>39.50</td>\n",
              "      <td>166.44</td>\n",
              "      <td>313.75</td>\n",
              "      <td>184.60</td>\n",
              "      <td>212.78</td>\n",
              "      <td>230.70</td>\n",
              "      <td>159.13</td>\n",
              "      <td>286.88</td>\n",
              "      <td>1738.16</td>\n",
              "      <td>2152.84</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>PRINTING OF BOOKS (INCLUDING LITHO PRINTING INDUSTRY)</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>6.30</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.06</td>\n",
              "      <td>9.90</td>\n",
              "      <td>20.04</td>\n",
              "      <td>35.54</td>\n",
              "      <td>31.61</td>\n",
              "      <td>70.51</td>\n",
              "      <td>36.63</td>\n",
              "      <td>47.39</td>\n",
              "      <td>14.34</td>\n",
              "      <td>113.78</td>\n",
              "      <td>72.58</td>\n",
              "      <td>122.81</td>\n",
              "      <td>53.17</td>\n",
              "      <td>634.66</td>\n",
              "      <td>1524.92</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>RAILWAY RELATED COMPONENTS</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.56</td>\n",
              "      <td>2.95</td>\n",
              "      <td>10.75</td>\n",
              "      <td>22.62</td>\n",
              "      <td>25.82</td>\n",
              "      <td>12.41</td>\n",
              "      <td>18.01</td>\n",
              "      <td>34.43</td>\n",
              "      <td>70.66</td>\n",
              "      <td>42.27</td>\n",
              "      <td>29.85</td>\n",
              "      <td>236.93</td>\n",
              "      <td>129.73</td>\n",
              "      <td>73.99</td>\n",
              "      <td>87.57</td>\n",
              "      <td>798.55</td>\n",
              "      <td>977.24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>RETAIL TRADING</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>1.27</td>\n",
              "      <td>0.09</td>\n",
              "      <td>13.73</td>\n",
              "      <td>26.27</td>\n",
              "      <td>31.70</td>\n",
              "      <td>22.31</td>\n",
              "      <td>11.30</td>\n",
              "      <td>168.72</td>\n",
              "      <td>262.24</td>\n",
              "      <td>450.94</td>\n",
              "      <td>988.57</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>RETAIL TRADING</th>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1855.11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>RUBBER GOODS</th>\n",
              "      <td>0.10</td>\n",
              "      <td>46.39</td>\n",
              "      <td>16.42</td>\n",
              "      <td>6.37</td>\n",
              "      <td>40.06</td>\n",
              "      <td>34.09</td>\n",
              "      <td>18.75</td>\n",
              "      <td>15.12</td>\n",
              "      <td>84.88</td>\n",
              "      <td>24.12</td>\n",
              "      <td>17.21</td>\n",
              "      <td>187.37</td>\n",
              "      <td>642.18</td>\n",
              "      <td>370.54</td>\n",
              "      <td>284.51</td>\n",
              "      <td>296.15</td>\n",
              "      <td>262.76</td>\n",
              "      <td>2347.02</td>\n",
              "      <td>2959.41</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>SCIENTIFIC INSTRUMENTS</th>\n",
              "      <td>8.07</td>\n",
              "      <td>2.33</td>\n",
              "      <td>0.19</td>\n",
              "      <td>0.02</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.10</td>\n",
              "      <td>0.07</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.83</td>\n",
              "      <td>0.00</td>\n",
              "      <td>2.49</td>\n",
              "      <td>7.08</td>\n",
              "      <td>73.28</td>\n",
              "      <td>45.08</td>\n",
              "      <td>32.34</td>\n",
              "      <td>6.36</td>\n",
              "      <td>76.66</td>\n",
              "      <td>254.93</td>\n",
              "      <td>277.72</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>SEA TRANSPORT</th>\n",
              "      <td>2.41</td>\n",
              "      <td>19.81</td>\n",
              "      <td>29.32</td>\n",
              "      <td>21.95</td>\n",
              "      <td>36.95</td>\n",
              "      <td>53.63</td>\n",
              "      <td>72.52</td>\n",
              "      <td>128.36</td>\n",
              "      <td>50.21</td>\n",
              "      <td>284.85</td>\n",
              "      <td>300.51</td>\n",
              "      <td>129.36</td>\n",
              "      <td>64.62</td>\n",
              "      <td>20.49</td>\n",
              "      <td>333.22</td>\n",
              "      <td>429.30</td>\n",
              "      <td>735.06</td>\n",
              "      <td>2712.57</td>\n",
              "      <td>4111.67</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>SERVICES SECTOR (Fin.,Banking,Insurance,Non Fin/Business,Outsourcing,R&amp;D,Courier,Tech. Testing and Analysis, Other)</th>\n",
              "      <td>71.38</td>\n",
              "      <td>187.95</td>\n",
              "      <td>296.34</td>\n",
              "      <td>271.15</td>\n",
              "      <td>456.15</td>\n",
              "      <td>548.61</td>\n",
              "      <td>4713.78</td>\n",
              "      <td>6986.17</td>\n",
              "      <td>6183.49</td>\n",
              "      <td>4174.53</td>\n",
              "      <td>3296.09</td>\n",
              "      <td>5215.98</td>\n",
              "      <td>4832.98</td>\n",
              "      <td>2225.10</td>\n",
              "      <td>4443.26</td>\n",
              "      <td>6889.46</td>\n",
              "      <td>8684.07</td>\n",
              "      <td>59476.49</td>\n",
              "      <td>76948.26</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>SOAPS, COSMETICS &amp; TOILET PREPARATIONS</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.89</td>\n",
              "      <td>87.42</td>\n",
              "      <td>6.04</td>\n",
              "      <td>6.38</td>\n",
              "      <td>22.03</td>\n",
              "      <td>24.58</td>\n",
              "      <td>102.90</td>\n",
              "      <td>222.08</td>\n",
              "      <td>160.07</td>\n",
              "      <td>108.44</td>\n",
              "      <td>177.22</td>\n",
              "      <td>193.26</td>\n",
              "      <td>92.60</td>\n",
              "      <td>1203.91</td>\n",
              "      <td>1540.65</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>SUGAR</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>3.97</td>\n",
              "      <td>0.00</td>\n",
              "      <td>2.94</td>\n",
              "      <td>3.00</td>\n",
              "      <td>9.85</td>\n",
              "      <td>10.07</td>\n",
              "      <td>5.01</td>\n",
              "      <td>0.10</td>\n",
              "      <td>0.17</td>\n",
              "      <td>4.44</td>\n",
              "      <td>12.26</td>\n",
              "      <td>3.08</td>\n",
              "      <td>27.77</td>\n",
              "      <td>105.85</td>\n",
              "      <td>15.92</td>\n",
              "      <td>204.43</td>\n",
              "      <td>213.83</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>TEA AND COFFEE (PROCESSING &amp; WAREHOUSING COFFEE &amp; RUBBER)</th>\n",
              "      <td>20.23</td>\n",
              "      <td>0.14</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.32</td>\n",
              "      <td>0.01</td>\n",
              "      <td>1.43</td>\n",
              "      <td>6.20</td>\n",
              "      <td>18.94</td>\n",
              "      <td>37.08</td>\n",
              "      <td>8.15</td>\n",
              "      <td>3.12</td>\n",
              "      <td>5.32</td>\n",
              "      <td>0.27</td>\n",
              "      <td>5.86</td>\n",
              "      <td>1.43</td>\n",
              "      <td>1.12</td>\n",
              "      <td>1.60</td>\n",
              "      <td>111.22</td>\n",
              "      <td>145.71</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>TELECOMMUNICATIONS</th>\n",
              "      <td>177.69</td>\n",
              "      <td>873.23</td>\n",
              "      <td>191.60</td>\n",
              "      <td>86.49</td>\n",
              "      <td>118.33</td>\n",
              "      <td>617.98</td>\n",
              "      <td>476.51</td>\n",
              "      <td>1260.70</td>\n",
              "      <td>2548.63</td>\n",
              "      <td>2539.26</td>\n",
              "      <td>1664.50</td>\n",
              "      <td>1997.24</td>\n",
              "      <td>303.87</td>\n",
              "      <td>1306.95</td>\n",
              "      <td>2894.94</td>\n",
              "      <td>1324.40</td>\n",
              "      <td>5563.69</td>\n",
              "      <td>23946.01</td>\n",
              "      <td>37052.74</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>TEXTILES (INCLUDING  DYED,PRINTED)</th>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3195.58</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>TEXTILES (INCLUDING DYED,PRINTED)</th>\n",
              "      <td>2.06</td>\n",
              "      <td>5.28</td>\n",
              "      <td>54.18</td>\n",
              "      <td>9.34</td>\n",
              "      <td>43.04</td>\n",
              "      <td>94.33</td>\n",
              "      <td>126.90</td>\n",
              "      <td>185.40</td>\n",
              "      <td>157.52</td>\n",
              "      <td>150.27</td>\n",
              "      <td>129.65</td>\n",
              "      <td>164.19</td>\n",
              "      <td>103.89</td>\n",
              "      <td>198.86</td>\n",
              "      <td>197.42</td>\n",
              "      <td>230.13</td>\n",
              "      <td>618.95</td>\n",
              "      <td>2471.41</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>TIMBER PRODUCTS</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.05</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.11</td>\n",
              "      <td>0.07</td>\n",
              "      <td>0.33</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.39</td>\n",
              "      <td>11.27</td>\n",
              "      <td>6.54</td>\n",
              "      <td>1.58</td>\n",
              "      <td>29.60</td>\n",
              "      <td>29.17</td>\n",
              "      <td>6.16</td>\n",
              "      <td>8.97</td>\n",
              "      <td>53.17</td>\n",
              "      <td>10.23</td>\n",
              "      <td>157.68</td>\n",
              "      <td>177.63</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>TRADING</th>\n",
              "      <td>11.49</td>\n",
              "      <td>43.27</td>\n",
              "      <td>38.13</td>\n",
              "      <td>31.12</td>\n",
              "      <td>14.22</td>\n",
              "      <td>28.93</td>\n",
              "      <td>114.65</td>\n",
              "      <td>345.02</td>\n",
              "      <td>643.64</td>\n",
              "      <td>737.95</td>\n",
              "      <td>498.04</td>\n",
              "      <td>731.55</td>\n",
              "      <td>717.80</td>\n",
              "      <td>1343.39</td>\n",
              "      <td>2727.96</td>\n",
              "      <td>3845.32</td>\n",
              "      <td>2338.40</td>\n",
              "      <td>14210.88</td>\n",
              "      <td>24159.53</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>VEGETABLE OILS AND VANASPATI</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>1.69</td>\n",
              "      <td>9.09</td>\n",
              "      <td>12.31</td>\n",
              "      <td>16.22</td>\n",
              "      <td>1.53</td>\n",
              "      <td>42.88</td>\n",
              "      <td>69.74</td>\n",
              "      <td>58.07</td>\n",
              "      <td>65.02</td>\n",
              "      <td>108.39</td>\n",
              "      <td>21.55</td>\n",
              "      <td>148.34</td>\n",
              "      <td>34.22</td>\n",
              "      <td>108.45</td>\n",
              "      <td>697.50</td>\n",
              "      <td>968.23</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>65 rows × 19 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                                       2000-01  2001-02  2002-03  2003-04  \\\n",
              "AGRICULTURAL MACHINERY                    3.64     1.04    13.48    47.54   \n",
              "AGRICULTURE SERVICES                     17.52    14.06    11.01     0.59   \n",
              "AIR TRANSPORT (INCLUDING AIR FREIGHT)     0.00     0.00     3.80     0.94   \n",
              "AUTOMOBILE INDUSTRY                     195.33   235.76   419.96   119.09   \n",
              "BOILERS AND STEAM GENERATING PLANTS       0.00     0.00     0.00     0.04   \n",
              "...                                        ...      ...      ...      ...   \n",
              "TEXTILES (INCLUDING  DYED,PRINTED)         NaN      NaN      NaN      NaN   \n",
              "TEXTILES (INCLUDING DYED,PRINTED)         2.06     5.28    54.18     9.34   \n",
              "TIMBER PRODUCTS                           0.00     0.05     0.04     0.11   \n",
              "TRADING                                  11.49    43.27    38.13    31.12   \n",
              "VEGETABLE OILS AND VANASPATI              0.00     0.00     0.00     1.69   \n",
              "\n",
              "                                       2004-05  2005-06  2006-07  2007-08  \\\n",
              "AGRICULTURAL MACHINERY                    0.00    92.71    25.19     6.72   \n",
              "AGRICULTURE SERVICES                      3.83     9.08    12.53    58.13   \n",
              "AIR TRANSPORT (INCLUDING AIR FREIGHT)     4.11    10.27    62.29    99.08   \n",
              "AUTOMOBILE INDUSTRY                     121.97   139.93   260.72   656.10   \n",
              "BOILERS AND STEAM GENERATING PLANTS       0.54     0.00     3.31     1.51   \n",
              "...                                        ...      ...      ...      ...   \n",
              "TEXTILES (INCLUDING  DYED,PRINTED)         NaN      NaN      NaN      NaN   \n",
              "TEXTILES (INCLUDING DYED,PRINTED)        43.04    94.33   126.90   185.40   \n",
              "TIMBER PRODUCTS                           0.07     0.33     0.00     0.39   \n",
              "TRADING                                  14.22    28.93   114.65   345.02   \n",
              "VEGETABLE OILS AND VANASPATI              9.09    12.31    16.22     1.53   \n",
              "\n",
              "                                       2008-09  2009-10  2010-11  2011-12  \\\n",
              "AGRICULTURAL MACHINERY                    5.57     1.88     0.49     2.77   \n",
              "AGRICULTURE SERVICES                      5.35  1222.22    43.90    49.02   \n",
              "AIR TRANSPORT (INCLUDING AIR FREIGHT)    61.37    23.71   136.60    31.22   \n",
              "AUTOMOBILE INDUSTRY                    1150.03  1236.29  1299.41   922.99   \n",
              "BOILERS AND STEAM GENERATING PLANTS       0.00     3.96     0.63    31.79   \n",
              "...                                        ...      ...      ...      ...   \n",
              "TEXTILES (INCLUDING  DYED,PRINTED)         NaN      NaN      NaN      NaN   \n",
              "TEXTILES (INCLUDING DYED,PRINTED)       157.52   150.27   129.65   164.19   \n",
              "TIMBER PRODUCTS                          11.27     6.54     1.58    29.60   \n",
              "TRADING                                 643.64   737.95   498.04   731.55   \n",
              "VEGETABLE OILS AND VANASPATI             42.88    69.74    58.07    65.02   \n",
              "\n",
              "                                       2012-13  2013-14  2014-15  2015-16  \\\n",
              "AGRICULTURAL MACHINERY                   95.41    48.78    72.35    16.44   \n",
              "AGRICULTURE SERVICES                    161.47    91.01    59.95    84.65   \n",
              "AIR TRANSPORT (INCLUDING AIR FREIGHT)    15.89    45.95    74.56   361.25   \n",
              "AUTOMOBILE INDUSTRY                    1537.28  1517.28  2725.64  2526.82   \n",
              "BOILERS AND STEAM GENERATING PLANTS      20.05     0.17     1.33    77.91   \n",
              "...                                        ...      ...      ...      ...   \n",
              "TEXTILES (INCLUDING  DYED,PRINTED)         NaN      NaN      NaN      NaN   \n",
              "TEXTILES (INCLUDING DYED,PRINTED)       103.89   198.86   197.42   230.13   \n",
              "TIMBER PRODUCTS                          29.17     6.16     8.97    53.17   \n",
              "TRADING                                 717.80  1343.39  2727.96  3845.32   \n",
              "VEGETABLE OILS AND VANASPATI            108.39    21.55   148.34    34.22   \n",
              "\n",
              "                                       2016-17  Sum_upto_16-17  AMOUNT_IN_USD  \n",
              "AGRICULTURAL MACHINERY                   15.19          449.20         540.07  \n",
              "AGRICULTURE SERVICES                     76.43         1920.75        2127.83  \n",
              "AIR TRANSPORT (INCLUDING AIR FREIGHT)    83.40         1014.44        1904.37  \n",
              "AUTOMOBILE INDUSTRY                    1609.32        16673.92       22358.84  \n",
              "BOILERS AND STEAM GENERATING PLANTS      53.91          195.15         263.37  \n",
              "...                                        ...             ...            ...  \n",
              "TEXTILES (INCLUDING  DYED,PRINTED)         NaN             NaN        3195.58  \n",
              "TEXTILES (INCLUDING DYED,PRINTED)       618.95         2471.41            NaN  \n",
              "TIMBER PRODUCTS                          10.23          157.68         177.63  \n",
              "TRADING                                2338.40        14210.88       24159.53  \n",
              "VEGETABLE OILS AND VANASPATI            108.45          697.50         968.23  \n",
              "\n",
              "[65 rows x 19 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7lyN8wmo0DTQ",
        "colab_type": "text"
      },
      "source": [
        "### The first dataframe has data upto 2017 and the second has data upto 2019. So we use these two dataframes to get data from 2017-19 by subtracting 'Sum_upto_16-17' from 'AMOUNT_IN_USD'. Assuming a third od that investment came in the financial year 2017-18 and the rest two third in the financial year 2018-19"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Eb8TKs6a0DTR",
        "colab_type": "code",
        "colab": {},
        "outputId": "603d9d46-c06c-4f93-e5b3-ecc520a9fcea"
      },
      "source": [
        "dataframe['2017-18'] = (2/3)*(data_join['AMOUNT_IN_USD'] - data_join['Sum_upto_16-17'])\n",
        "dataframe['2018-19'] = (data_join['AMOUNT_IN_USD'] - data_join['Sum_upto_16-17'])/(3)\n",
        "dataframe.fillna(0,inplace=True)\n",
        "dataframe"
      ],
      "execution_count": 0,
      "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>2000-01</th>\n",
              "      <th>2001-02</th>\n",
              "      <th>2002-03</th>\n",
              "      <th>2003-04</th>\n",
              "      <th>2004-05</th>\n",
              "      <th>2005-06</th>\n",
              "      <th>2006-07</th>\n",
              "      <th>2007-08</th>\n",
              "      <th>2008-09</th>\n",
              "      <th>2009-10</th>\n",
              "      <th>2010-11</th>\n",
              "      <th>2011-12</th>\n",
              "      <th>2012-13</th>\n",
              "      <th>2013-14</th>\n",
              "      <th>2014-15</th>\n",
              "      <th>2015-16</th>\n",
              "      <th>2016-17</th>\n",
              "      <th>2017-18</th>\n",
              "      <th>2018-19</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Sector</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>METALLURGICAL INDUSTRIES</th>\n",
              "      <td>22.69</td>\n",
              "      <td>14.14</td>\n",
              "      <td>36.61</td>\n",
              "      <td>8.11</td>\n",
              "      <td>200.38</td>\n",
              "      <td>149.13</td>\n",
              "      <td>169.94</td>\n",
              "      <td>1175.75</td>\n",
              "      <td>959.94</td>\n",
              "      <td>419.88</td>\n",
              "      <td>1098.14</td>\n",
              "      <td>1786.14</td>\n",
              "      <td>1466.23</td>\n",
              "      <td>567.63</td>\n",
              "      <td>359.34</td>\n",
              "      <td>456.31</td>\n",
              "      <td>1440.18</td>\n",
              "      <td>694.446667</td>\n",
              "      <td>347.223333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>MINING</th>\n",
              "      <td>1.32</td>\n",
              "      <td>6.52</td>\n",
              "      <td>10.06</td>\n",
              "      <td>23.48</td>\n",
              "      <td>9.92</td>\n",
              "      <td>7.40</td>\n",
              "      <td>6.62</td>\n",
              "      <td>444.36</td>\n",
              "      <td>34.16</td>\n",
              "      <td>174.40</td>\n",
              "      <td>79.51</td>\n",
              "      <td>142.65</td>\n",
              "      <td>57.89</td>\n",
              "      <td>12.73</td>\n",
              "      <td>684.39</td>\n",
              "      <td>520.67</td>\n",
              "      <td>55.75</td>\n",
              "      <td>252.926667</td>\n",
              "      <td>126.463333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>POWER</th>\n",
              "      <td>89.42</td>\n",
              "      <td>757.44</td>\n",
              "      <td>59.11</td>\n",
              "      <td>27.09</td>\n",
              "      <td>43.37</td>\n",
              "      <td>72.69</td>\n",
              "      <td>157.15</td>\n",
              "      <td>988.68</td>\n",
              "      <td>907.66</td>\n",
              "      <td>1271.79</td>\n",
              "      <td>1271.77</td>\n",
              "      <td>1652.38</td>\n",
              "      <td>535.68</td>\n",
              "      <td>1066.08</td>\n",
              "      <td>707.04</td>\n",
              "      <td>868.80</td>\n",
              "      <td>1112.98</td>\n",
              "      <td>1944.280000</td>\n",
              "      <td>972.140000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>NON-CONVENTIONAL ENERGY</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>1.70</td>\n",
              "      <td>4.14</td>\n",
              "      <td>1.27</td>\n",
              "      <td>1.35</td>\n",
              "      <td>2.44</td>\n",
              "      <td>58.82</td>\n",
              "      <td>125.88</td>\n",
              "      <td>622.52</td>\n",
              "      <td>214.40</td>\n",
              "      <td>452.17</td>\n",
              "      <td>1106.52</td>\n",
              "      <td>414.25</td>\n",
              "      <td>615.95</td>\n",
              "      <td>776.51</td>\n",
              "      <td>783.57</td>\n",
              "      <td>1921.053333</td>\n",
              "      <td>960.526667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>COAL PRODUCTION</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.00</td>\n",
              "      <td>9.14</td>\n",
              "      <td>1.30</td>\n",
              "      <td>14.08</td>\n",
              "      <td>0.22</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>2.96</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>-0.006667</td>\n",
              "      <td>-0.003333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>PETROLEUM &amp; NATURAL GAS</th>\n",
              "      <td>9.35</td>\n",
              "      <td>211.07</td>\n",
              "      <td>56.78</td>\n",
              "      <td>80.64</td>\n",
              "      <td>102.78</td>\n",
              "      <td>12.09</td>\n",
              "      <td>87.71</td>\n",
              "      <td>1405.04</td>\n",
              "      <td>349.29</td>\n",
              "      <td>265.53</td>\n",
              "      <td>556.43</td>\n",
              "      <td>2029.98</td>\n",
              "      <td>214.80</td>\n",
              "      <td>112.23</td>\n",
              "      <td>1079.02</td>\n",
              "      <td>103.02</td>\n",
              "      <td>180.40</td>\n",
              "      <td>110.653333</td>\n",
              "      <td>55.326667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>BOILERS AND STEAM GENERATING PLANTS</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.54</td>\n",
              "      <td>0.00</td>\n",
              "      <td>3.31</td>\n",
              "      <td>1.51</td>\n",
              "      <td>0.00</td>\n",
              "      <td>3.96</td>\n",
              "      <td>0.63</td>\n",
              "      <td>31.79</td>\n",
              "      <td>20.05</td>\n",
              "      <td>0.17</td>\n",
              "      <td>1.33</td>\n",
              "      <td>77.91</td>\n",
              "      <td>53.91</td>\n",
              "      <td>45.480000</td>\n",
              "      <td>22.740000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>PRIME MOVER (OTHER THAN ELECTRICAL GENERATORS)</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>2.66</td>\n",
              "      <td>0.74</td>\n",
              "      <td>25.57</td>\n",
              "      <td>40.53</td>\n",
              "      <td>74.88</td>\n",
              "      <td>39.50</td>\n",
              "      <td>166.44</td>\n",
              "      <td>313.75</td>\n",
              "      <td>184.60</td>\n",
              "      <td>212.78</td>\n",
              "      <td>230.70</td>\n",
              "      <td>159.13</td>\n",
              "      <td>286.88</td>\n",
              "      <td>276.453333</td>\n",
              "      <td>138.226667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ELECTRICAL EQUIPMENTS</th>\n",
              "      <td>79.76</td>\n",
              "      <td>65.76</td>\n",
              "      <td>34.71</td>\n",
              "      <td>73.20</td>\n",
              "      <td>97.40</td>\n",
              "      <td>39.50</td>\n",
              "      <td>76.85</td>\n",
              "      <td>653.74</td>\n",
              "      <td>417.35</td>\n",
              "      <td>728.27</td>\n",
              "      <td>153.90</td>\n",
              "      <td>566.39</td>\n",
              "      <td>195.87</td>\n",
              "      <td>134.31</td>\n",
              "      <td>574.83</td>\n",
              "      <td>444.88</td>\n",
              "      <td>2230.69</td>\n",
              "      <td>1075.433333</td>\n",
              "      <td>537.716667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>COMPUTER SOFTWARE &amp; HARDWARE</th>\n",
              "      <td>228.39</td>\n",
              "      <td>419.39</td>\n",
              "      <td>314.24</td>\n",
              "      <td>368.32</td>\n",
              "      <td>527.90</td>\n",
              "      <td>1359.97</td>\n",
              "      <td>2613.33</td>\n",
              "      <td>1382.25</td>\n",
              "      <td>1543.34</td>\n",
              "      <td>871.86</td>\n",
              "      <td>779.81</td>\n",
              "      <td>796.35</td>\n",
              "      <td>485.96</td>\n",
              "      <td>1126.27</td>\n",
              "      <td>2296.04</td>\n",
              "      <td>5904.36</td>\n",
              "      <td>3651.71</td>\n",
              "      <td>9872.940000</td>\n",
              "      <td>4936.470000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ELECTRONICS</th>\n",
              "      <td>8.34</td>\n",
              "      <td>12.47</td>\n",
              "      <td>295.88</td>\n",
              "      <td>82.31</td>\n",
              "      <td>88.10</td>\n",
              "      <td>40.91</td>\n",
              "      <td>42.14</td>\n",
              "      <td>136.03</td>\n",
              "      <td>147.51</td>\n",
              "      <td>52.14</td>\n",
              "      <td>59.72</td>\n",
              "      <td>194.41</td>\n",
              "      <td>38.24</td>\n",
              "      <td>132.58</td>\n",
              "      <td>96.84</td>\n",
              "      <td>208.39</td>\n",
              "      <td>83.97</td>\n",
              "      <td>488.580000</td>\n",
              "      <td>244.290000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>TELECOMMUNICATIONS</th>\n",
              "      <td>177.69</td>\n",
              "      <td>873.23</td>\n",
              "      <td>191.60</td>\n",
              "      <td>86.49</td>\n",
              "      <td>118.33</td>\n",
              "      <td>617.98</td>\n",
              "      <td>476.51</td>\n",
              "      <td>1260.70</td>\n",
              "      <td>2548.63</td>\n",
              "      <td>2539.26</td>\n",
              "      <td>1664.50</td>\n",
              "      <td>1997.24</td>\n",
              "      <td>303.87</td>\n",
              "      <td>1306.95</td>\n",
              "      <td>2894.94</td>\n",
              "      <td>1324.40</td>\n",
              "      <td>5563.69</td>\n",
              "      <td>8737.820000</td>\n",
              "      <td>4368.910000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>INFORMATION &amp; BROADCASTING (INCLUDING PRINT MEDIA)</th>\n",
              "      <td>81.50</td>\n",
              "      <td>4.54</td>\n",
              "      <td>36.50</td>\n",
              "      <td>13.72</td>\n",
              "      <td>9.85</td>\n",
              "      <td>55.93</td>\n",
              "      <td>75.70</td>\n",
              "      <td>288.49</td>\n",
              "      <td>735.04</td>\n",
              "      <td>490.83</td>\n",
              "      <td>412.11</td>\n",
              "      <td>675.96</td>\n",
              "      <td>404.04</td>\n",
              "      <td>428.52</td>\n",
              "      <td>254.96</td>\n",
              "      <td>1009.34</td>\n",
              "      <td>1516.68</td>\n",
              "      <td>1287.246667</td>\n",
              "      <td>643.623333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>AUTOMOBILE INDUSTRY</th>\n",
              "      <td>195.33</td>\n",
              "      <td>235.76</td>\n",
              "      <td>419.96</td>\n",
              "      <td>119.09</td>\n",
              "      <td>121.97</td>\n",
              "      <td>139.93</td>\n",
              "      <td>260.72</td>\n",
              "      <td>656.10</td>\n",
              "      <td>1150.03</td>\n",
              "      <td>1236.29</td>\n",
              "      <td>1299.41</td>\n",
              "      <td>922.99</td>\n",
              "      <td>1537.28</td>\n",
              "      <td>1517.28</td>\n",
              "      <td>2725.64</td>\n",
              "      <td>2526.82</td>\n",
              "      <td>1609.32</td>\n",
              "      <td>3789.946667</td>\n",
              "      <td>1894.973333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>AIR TRANSPORT (INCLUDING AIR FREIGHT)</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>3.80</td>\n",
              "      <td>0.94</td>\n",
              "      <td>4.11</td>\n",
              "      <td>10.27</td>\n",
              "      <td>62.29</td>\n",
              "      <td>99.08</td>\n",
              "      <td>61.37</td>\n",
              "      <td>23.71</td>\n",
              "      <td>136.60</td>\n",
              "      <td>31.22</td>\n",
              "      <td>15.89</td>\n",
              "      <td>45.95</td>\n",
              "      <td>74.56</td>\n",
              "      <td>361.25</td>\n",
              "      <td>83.40</td>\n",
              "      <td>593.286667</td>\n",
              "      <td>296.643333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>SEA TRANSPORT</th>\n",
              "      <td>2.41</td>\n",
              "      <td>19.81</td>\n",
              "      <td>29.32</td>\n",
              "      <td>21.95</td>\n",
              "      <td>36.95</td>\n",
              "      <td>53.63</td>\n",
              "      <td>72.52</td>\n",
              "      <td>128.36</td>\n",
              "      <td>50.21</td>\n",
              "      <td>284.85</td>\n",
              "      <td>300.51</td>\n",
              "      <td>129.36</td>\n",
              "      <td>64.62</td>\n",
              "      <td>20.49</td>\n",
              "      <td>333.22</td>\n",
              "      <td>429.30</td>\n",
              "      <td>735.06</td>\n",
              "      <td>932.733333</td>\n",
              "      <td>466.366667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>PORTS</th>\n",
              "      <td>0.00</td>\n",
              "      <td>15.48</td>\n",
              "      <td>2.03</td>\n",
              "      <td>116.36</td>\n",
              "      <td>13.04</td>\n",
              "      <td>0.50</td>\n",
              "      <td>0.00</td>\n",
              "      <td>918.18</td>\n",
              "      <td>493.15</td>\n",
              "      <td>65.41</td>\n",
              "      <td>10.92</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.31</td>\n",
              "      <td>1.90</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.013333</td>\n",
              "      <td>0.006667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>RAILWAY RELATED COMPONENTS</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.56</td>\n",
              "      <td>2.95</td>\n",
              "      <td>10.75</td>\n",
              "      <td>22.62</td>\n",
              "      <td>25.82</td>\n",
              "      <td>12.41</td>\n",
              "      <td>18.01</td>\n",
              "      <td>34.43</td>\n",
              "      <td>70.66</td>\n",
              "      <td>42.27</td>\n",
              "      <td>29.85</td>\n",
              "      <td>236.93</td>\n",
              "      <td>129.73</td>\n",
              "      <td>73.99</td>\n",
              "      <td>87.57</td>\n",
              "      <td>119.126667</td>\n",
              "      <td>59.563333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>INDUSTRIAL MACHINERY</th>\n",
              "      <td>5.48</td>\n",
              "      <td>32.04</td>\n",
              "      <td>19.40</td>\n",
              "      <td>3.18</td>\n",
              "      <td>8.89</td>\n",
              "      <td>42.80</td>\n",
              "      <td>25.96</td>\n",
              "      <td>119.57</td>\n",
              "      <td>110.54</td>\n",
              "      <td>341.88</td>\n",
              "      <td>467.92</td>\n",
              "      <td>620.66</td>\n",
              "      <td>503.83</td>\n",
              "      <td>477.38</td>\n",
              "      <td>716.79</td>\n",
              "      <td>568.26</td>\n",
              "      <td>329.30</td>\n",
              "      <td>602.493333</td>\n",
              "      <td>301.246667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>MACHINE TOOLS</th>\n",
              "      <td>1.42</td>\n",
              "      <td>4.31</td>\n",
              "      <td>14.17</td>\n",
              "      <td>54.51</td>\n",
              "      <td>11.04</td>\n",
              "      <td>23.00</td>\n",
              "      <td>37.28</td>\n",
              "      <td>56.87</td>\n",
              "      <td>45.66</td>\n",
              "      <td>133.83</td>\n",
              "      <td>11.63</td>\n",
              "      <td>127.87</td>\n",
              "      <td>101.39</td>\n",
              "      <td>64.52</td>\n",
              "      <td>24.06</td>\n",
              "      <td>126.38</td>\n",
              "      <td>23.89</td>\n",
              "      <td>65.286667</td>\n",
              "      <td>32.643333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>AGRICULTURAL MACHINERY</th>\n",
              "      <td>3.64</td>\n",
              "      <td>1.04</td>\n",
              "      <td>13.48</td>\n",
              "      <td>47.54</td>\n",
              "      <td>0.00</td>\n",
              "      <td>92.71</td>\n",
              "      <td>25.19</td>\n",
              "      <td>6.72</td>\n",
              "      <td>5.57</td>\n",
              "      <td>1.88</td>\n",
              "      <td>0.49</td>\n",
              "      <td>2.77</td>\n",
              "      <td>95.41</td>\n",
              "      <td>48.78</td>\n",
              "      <td>72.35</td>\n",
              "      <td>16.44</td>\n",
              "      <td>15.19</td>\n",
              "      <td>60.580000</td>\n",
              "      <td>30.290000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>EARTH-MOVING MACHINERY</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.11</td>\n",
              "      <td>13.77</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.10</td>\n",
              "      <td>50.87</td>\n",
              "      <td>0.99</td>\n",
              "      <td>67.94</td>\n",
              "      <td>2.27</td>\n",
              "      <td>15.62</td>\n",
              "      <td>1.77</td>\n",
              "      <td>16.40</td>\n",
              "      <td>5.10</td>\n",
              "      <td>34.44</td>\n",
              "      <td>30.11</td>\n",
              "      <td>97.66</td>\n",
              "      <td>52.23</td>\n",
              "      <td>46.380000</td>\n",
              "      <td>23.190000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>MISCELLANEOUS MECHANICAL &amp; ENGINEERING INDUSTRIES</th>\n",
              "      <td>44.50</td>\n",
              "      <td>61.40</td>\n",
              "      <td>45.07</td>\n",
              "      <td>22.73</td>\n",
              "      <td>12.83</td>\n",
              "      <td>51.22</td>\n",
              "      <td>84.44</td>\n",
              "      <td>211.15</td>\n",
              "      <td>142.31</td>\n",
              "      <td>149.59</td>\n",
              "      <td>108.67</td>\n",
              "      <td>1295.34</td>\n",
              "      <td>89.45</td>\n",
              "      <td>288.13</td>\n",
              "      <td>186.69</td>\n",
              "      <td>274.57</td>\n",
              "      <td>245.24</td>\n",
              "      <td>187.506667</td>\n",
              "      <td>93.753333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>COMMERCIAL, OFFICE &amp; HOUSEHOLD EQUIPMENTS</th>\n",
              "      <td>12.20</td>\n",
              "      <td>4.87</td>\n",
              "      <td>2.33</td>\n",
              "      <td>10.41</td>\n",
              "      <td>14.13</td>\n",
              "      <td>25.54</td>\n",
              "      <td>5.42</td>\n",
              "      <td>9.83</td>\n",
              "      <td>12.63</td>\n",
              "      <td>78.98</td>\n",
              "      <td>25.12</td>\n",
              "      <td>29.04</td>\n",
              "      <td>24.33</td>\n",
              "      <td>21.13</td>\n",
              "      <td>33.39</td>\n",
              "      <td>36.68</td>\n",
              "      <td>7.44</td>\n",
              "      <td>21.866667</td>\n",
              "      <td>10.933333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>MEDICAL AND SURGICAL APPLIANCES</th>\n",
              "      <td>5.42</td>\n",
              "      <td>42.35</td>\n",
              "      <td>21.63</td>\n",
              "      <td>1.97</td>\n",
              "      <td>5.35</td>\n",
              "      <td>1.52</td>\n",
              "      <td>13.43</td>\n",
              "      <td>13.17</td>\n",
              "      <td>75.42</td>\n",
              "      <td>167.35</td>\n",
              "      <td>32.22</td>\n",
              "      <td>141.61</td>\n",
              "      <td>83.02</td>\n",
              "      <td>173.48</td>\n",
              "      <td>145.93</td>\n",
              "      <td>173.26</td>\n",
              "      <td>479.71</td>\n",
              "      <td>171.373333</td>\n",
              "      <td>85.686667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>INDUSTRIAL INSTRUMENTS</th>\n",
              "      <td>1.01</td>\n",
              "      <td>5.07</td>\n",
              "      <td>1.31</td>\n",
              "      <td>0.30</td>\n",
              "      <td>1.08</td>\n",
              "      <td>0.38</td>\n",
              "      <td>0.00</td>\n",
              "      <td>2.23</td>\n",
              "      <td>17.48</td>\n",
              "      <td>7.61</td>\n",
              "      <td>25.48</td>\n",
              "      <td>3.99</td>\n",
              "      <td>0.58</td>\n",
              "      <td>0.53</td>\n",
              "      <td>0.85</td>\n",
              "      <td>7.42</td>\n",
              "      <td>0.80</td>\n",
              "      <td>7.713333</td>\n",
              "      <td>3.856667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>SCIENTIFIC INSTRUMENTS</th>\n",
              "      <td>8.07</td>\n",
              "      <td>2.33</td>\n",
              "      <td>0.19</td>\n",
              "      <td>0.02</td>\n",
              "      <td>0.03</td>\n",
              "      <td>0.10</td>\n",
              "      <td>0.07</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.83</td>\n",
              "      <td>0.00</td>\n",
              "      <td>2.49</td>\n",
              "      <td>7.08</td>\n",
              "      <td>73.28</td>\n",
              "      <td>45.08</td>\n",
              "      <td>32.34</td>\n",
              "      <td>6.36</td>\n",
              "      <td>76.66</td>\n",
              "      <td>15.193333</td>\n",
              "      <td>7.596667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>MATHEMATICAL,SURVEYING AND DRAWING INSTRUMENTS</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>1.27</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>6.71</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>FERTILIZERS</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>16.38</td>\n",
              "      <td>21.58</td>\n",
              "      <td>13.46</td>\n",
              "      <td>4.24</td>\n",
              "      <td>5.01</td>\n",
              "      <td>1.95</td>\n",
              "      <td>133.75</td>\n",
              "      <td>8.20</td>\n",
              "      <td>18.18</td>\n",
              "      <td>32.60</td>\n",
              "      <td>42.55</td>\n",
              "      <td>20.65</td>\n",
              "      <td>225.32</td>\n",
              "      <td>20.93</td>\n",
              "      <td>0.89</td>\n",
              "      <td>78.326667</td>\n",
              "      <td>39.163333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>CHEMICALS (OTHER THAN FERTILIZERS)</th>\n",
              "      <td>111.14</td>\n",
              "      <td>87.23</td>\n",
              "      <td>128.12</td>\n",
              "      <td>20.24</td>\n",
              "      <td>69.39</td>\n",
              "      <td>387.72</td>\n",
              "      <td>138.85</td>\n",
              "      <td>233.70</td>\n",
              "      <td>651.22</td>\n",
              "      <td>365.94</td>\n",
              "      <td>2354.40</td>\n",
              "      <td>4040.71</td>\n",
              "      <td>292.16</td>\n",
              "      <td>786.76</td>\n",
              "      <td>762.76</td>\n",
              "      <td>1469.95</td>\n",
              "      <td>1392.80</td>\n",
              "      <td>2289.246667</td>\n",
              "      <td>1144.623333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>TEXTILES (INCLUDING DYED,PRINTED)</th>\n",
              "      <td>2.06</td>\n",
              "      <td>5.28</td>\n",
              "      <td>54.18</td>\n",
              "      <td>9.34</td>\n",
              "      <td>43.04</td>\n",
              "      <td>94.33</td>\n",
              "      <td>126.90</td>\n",
              "      <td>185.40</td>\n",
              "      <td>157.52</td>\n",
              "      <td>150.27</td>\n",
              "      <td>129.65</td>\n",
              "      <td>164.19</td>\n",
              "      <td>103.89</td>\n",
              "      <td>198.86</td>\n",
              "      <td>197.42</td>\n",
              "      <td>230.13</td>\n",
              "      <td>618.95</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>PAPER AND PULP (INCLUDING PAPER PRODUCTS)</th>\n",
              "      <td>60.04</td>\n",
              "      <td>16.70</td>\n",
              "      <td>7.36</td>\n",
              "      <td>7.15</td>\n",
              "      <td>2.70</td>\n",
              "      <td>27.38</td>\n",
              "      <td>5.08</td>\n",
              "      <td>31.24</td>\n",
              "      <td>272.51</td>\n",
              "      <td>16.42</td>\n",
              "      <td>6.53</td>\n",
              "      <td>407.35</td>\n",
              "      <td>5.09</td>\n",
              "      <td>26.86</td>\n",
              "      <td>116.21</td>\n",
              "      <td>85.21</td>\n",
              "      <td>197.61</td>\n",
              "      <td>95.593333</td>\n",
              "      <td>47.796667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>SUGAR</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>3.97</td>\n",
              "      <td>0.00</td>\n",
              "      <td>2.94</td>\n",
              "      <td>3.00</td>\n",
              "      <td>9.85</td>\n",
              "      <td>10.07</td>\n",
              "      <td>5.01</td>\n",
              "      <td>0.10</td>\n",
              "      <td>0.17</td>\n",
              "      <td>4.44</td>\n",
              "      <td>12.26</td>\n",
              "      <td>3.08</td>\n",
              "      <td>27.77</td>\n",
              "      <td>105.85</td>\n",
              "      <td>15.92</td>\n",
              "      <td>6.266667</td>\n",
              "      <td>3.133333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>FERMENTATION INDUSTRIES</th>\n",
              "      <td>16.02</td>\n",
              "      <td>11.04</td>\n",
              "      <td>8.07</td>\n",
              "      <td>1.70</td>\n",
              "      <td>139.00</td>\n",
              "      <td>169.83</td>\n",
              "      <td>27.58</td>\n",
              "      <td>270.05</td>\n",
              "      <td>144.70</td>\n",
              "      <td>112.02</td>\n",
              "      <td>57.71</td>\n",
              "      <td>69.70</td>\n",
              "      <td>107.21</td>\n",
              "      <td>814.58</td>\n",
              "      <td>225.38</td>\n",
              "      <td>202.36</td>\n",
              "      <td>110.86</td>\n",
              "      <td>157.446667</td>\n",
              "      <td>78.723333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>FOOD PROCESSING INDUSTRIES</th>\n",
              "      <td>45.75</td>\n",
              "      <td>219.39</td>\n",
              "      <td>36.88</td>\n",
              "      <td>109.22</td>\n",
              "      <td>43.98</td>\n",
              "      <td>41.74</td>\n",
              "      <td>102.00</td>\n",
              "      <td>70.17</td>\n",
              "      <td>102.71</td>\n",
              "      <td>278.89</td>\n",
              "      <td>188.67</td>\n",
              "      <td>170.21</td>\n",
              "      <td>401.46</td>\n",
              "      <td>3982.89</td>\n",
              "      <td>515.86</td>\n",
              "      <td>505.88</td>\n",
              "      <td>727.22</td>\n",
              "      <td>1241.446667</td>\n",
              "      <td>620.723333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>VEGETABLE OILS AND VANASPATI</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>1.69</td>\n",
              "      <td>9.09</td>\n",
              "      <td>12.31</td>\n",
              "      <td>16.22</td>\n",
              "      <td>1.53</td>\n",
              "      <td>42.88</td>\n",
              "      <td>69.74</td>\n",
              "      <td>58.07</td>\n",
              "      <td>65.02</td>\n",
              "      <td>108.39</td>\n",
              "      <td>21.55</td>\n",
              "      <td>148.34</td>\n",
              "      <td>34.22</td>\n",
              "      <td>108.45</td>\n",
              "      <td>180.486667</td>\n",
              "      <td>90.243333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>SOAPS, COSMETICS &amp; TOILET PREPARATIONS</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.89</td>\n",
              "      <td>87.42</td>\n",
              "      <td>6.04</td>\n",
              "      <td>6.38</td>\n",
              "      <td>22.03</td>\n",
              "      <td>24.58</td>\n",
              "      <td>102.90</td>\n",
              "      <td>222.08</td>\n",
              "      <td>160.07</td>\n",
              "      <td>108.44</td>\n",
              "      <td>177.22</td>\n",
              "      <td>193.26</td>\n",
              "      <td>92.60</td>\n",
              "      <td>224.493333</td>\n",
              "      <td>112.246667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>RUBBER GOODS</th>\n",
              "      <td>0.10</td>\n",
              "      <td>46.39</td>\n",
              "      <td>16.42</td>\n",
              "      <td>6.37</td>\n",
              "      <td>40.06</td>\n",
              "      <td>34.09</td>\n",
              "      <td>18.75</td>\n",
              "      <td>15.12</td>\n",
              "      <td>84.88</td>\n",
              "      <td>24.12</td>\n",
              "      <td>17.21</td>\n",
              "      <td>187.37</td>\n",
              "      <td>642.18</td>\n",
              "      <td>370.54</td>\n",
              "      <td>284.51</td>\n",
              "      <td>296.15</td>\n",
              "      <td>262.76</td>\n",
              "      <td>408.260000</td>\n",
              "      <td>204.130000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>LEATHER,LEATHER GOODS AND PICKERS</th>\n",
              "      <td>9.75</td>\n",
              "      <td>0.20</td>\n",
              "      <td>0.01</td>\n",
              "      <td>7.55</td>\n",
              "      <td>0.44</td>\n",
              "      <td>1.11</td>\n",
              "      <td>8.26</td>\n",
              "      <td>7.46</td>\n",
              "      <td>3.32</td>\n",
              "      <td>5.06</td>\n",
              "      <td>9.26</td>\n",
              "      <td>8.30</td>\n",
              "      <td>46.70</td>\n",
              "      <td>6.14</td>\n",
              "      <td>34.21</td>\n",
              "      <td>17.13</td>\n",
              "      <td>2.30</td>\n",
              "      <td>20.386667</td>\n",
              "      <td>10.193333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>GLUE AND GELATIN</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.94</td>\n",
              "      <td>5.22</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>2.28</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.27</td>\n",
              "      <td>0.01</td>\n",
              "      <td>5.84</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.97</td>\n",
              "      <td>21.44</td>\n",
              "      <td>0.82</td>\n",
              "      <td>90.60</td>\n",
              "      <td>12.013333</td>\n",
              "      <td>6.006667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>GLASS</th>\n",
              "      <td>33.87</td>\n",
              "      <td>8.37</td>\n",
              "      <td>44.98</td>\n",
              "      <td>5.24</td>\n",
              "      <td>8.36</td>\n",
              "      <td>0.81</td>\n",
              "      <td>1.43</td>\n",
              "      <td>11.04</td>\n",
              "      <td>23.16</td>\n",
              "      <td>2.83</td>\n",
              "      <td>7.60</td>\n",
              "      <td>32.22</td>\n",
              "      <td>209.16</td>\n",
              "      <td>43.09</td>\n",
              "      <td>41.82</td>\n",
              "      <td>25.78</td>\n",
              "      <td>51.69</td>\n",
              "      <td>73.933333</td>\n",
              "      <td>36.966667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>CERAMICS</th>\n",
              "      <td>4.03</td>\n",
              "      <td>0.78</td>\n",
              "      <td>0.21</td>\n",
              "      <td>1.47</td>\n",
              "      <td>26.79</td>\n",
              "      <td>5.67</td>\n",
              "      <td>122.23</td>\n",
              "      <td>115.11</td>\n",
              "      <td>198.43</td>\n",
              "      <td>7.21</td>\n",
              "      <td>12.00</td>\n",
              "      <td>9.87</td>\n",
              "      <td>4.33</td>\n",
              "      <td>150.09</td>\n",
              "      <td>35.29</td>\n",
              "      <td>51.21</td>\n",
              "      <td>15.40</td>\n",
              "      <td>72.226667</td>\n",
              "      <td>36.113333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>CEMENT AND GYPSUM PRODUCTS</th>\n",
              "      <td>67.72</td>\n",
              "      <td>139.90</td>\n",
              "      <td>21.08</td>\n",
              "      <td>9.58</td>\n",
              "      <td>0.16</td>\n",
              "      <td>452.08</td>\n",
              "      <td>242.47</td>\n",
              "      <td>16.89</td>\n",
              "      <td>724.80</td>\n",
              "      <td>33.80</td>\n",
              "      <td>637.68</td>\n",
              "      <td>267.90</td>\n",
              "      <td>12.38</td>\n",
              "      <td>254.01</td>\n",
              "      <td>208.99</td>\n",
              "      <td>19.69</td>\n",
              "      <td>2130.10</td>\n",
              "      <td>25.353333</td>\n",
              "      <td>12.676667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>TIMBER PRODUCTS</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.05</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.11</td>\n",
              "      <td>0.07</td>\n",
              "      <td>0.33</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.39</td>\n",
              "      <td>11.27</td>\n",
              "      <td>6.54</td>\n",
              "      <td>1.58</td>\n",
              "      <td>29.60</td>\n",
              "      <td>29.17</td>\n",
              "      <td>6.16</td>\n",
              "      <td>8.97</td>\n",
              "      <td>53.17</td>\n",
              "      <td>10.23</td>\n",
              "      <td>13.300000</td>\n",
              "      <td>6.650000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>DEFENCE INDUSTRIES</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.05</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>3.66</td>\n",
              "      <td>0.41</td>\n",
              "      <td>0.82</td>\n",
              "      <td>0.08</td>\n",
              "      <td>0.10</td>\n",
              "      <td>0.00</td>\n",
              "      <td>1.466667</td>\n",
              "      <td>0.733333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>CONSULTANCY SERVICES</th>\n",
              "      <td>4.25</td>\n",
              "      <td>66.22</td>\n",
              "      <td>25.70</td>\n",
              "      <td>46.20</td>\n",
              "      <td>252.42</td>\n",
              "      <td>47.40</td>\n",
              "      <td>114.68</td>\n",
              "      <td>233.32</td>\n",
              "      <td>256.59</td>\n",
              "      <td>341.31</td>\n",
              "      <td>274.84</td>\n",
              "      <td>289.89</td>\n",
              "      <td>142.32</td>\n",
              "      <td>285.85</td>\n",
              "      <td>458.13</td>\n",
              "      <td>517.47</td>\n",
              "      <td>261.14</td>\n",
              "      <td>1037.993333</td>\n",
              "      <td>518.996667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>SERVICES SECTOR (Fin.,Banking,Insurance,Non Fin/Business,Outsourcing,R&amp;D,Courier,Tech. Testing and Analysis, Other)</th>\n",
              "      <td>71.38</td>\n",
              "      <td>187.95</td>\n",
              "      <td>296.34</td>\n",
              "      <td>271.15</td>\n",
              "      <td>456.15</td>\n",
              "      <td>548.61</td>\n",
              "      <td>4713.78</td>\n",
              "      <td>6986.17</td>\n",
              "      <td>6183.49</td>\n",
              "      <td>4174.53</td>\n",
              "      <td>3296.09</td>\n",
              "      <td>5215.98</td>\n",
              "      <td>4832.98</td>\n",
              "      <td>2225.10</td>\n",
              "      <td>4443.26</td>\n",
              "      <td>6889.46</td>\n",
              "      <td>8684.07</td>\n",
              "      <td>11647.846667</td>\n",
              "      <td>5823.923333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>HOSPITAL &amp; DIAGNOSTIC CENTRES</th>\n",
              "      <td>0.00</td>\n",
              "      <td>6.93</td>\n",
              "      <td>29.13</td>\n",
              "      <td>24.08</td>\n",
              "      <td>26.19</td>\n",
              "      <td>32.53</td>\n",
              "      <td>38.14</td>\n",
              "      <td>241.76</td>\n",
              "      <td>239.71</td>\n",
              "      <td>135.57</td>\n",
              "      <td>256.00</td>\n",
              "      <td>310.43</td>\n",
              "      <td>256.86</td>\n",
              "      <td>684.58</td>\n",
              "      <td>567.85</td>\n",
              "      <td>742.35</td>\n",
              "      <td>747.38</td>\n",
              "      <td>1335.273333</td>\n",
              "      <td>667.636667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>EDUCATION</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.19</td>\n",
              "      <td>1.97</td>\n",
              "      <td>3.16</td>\n",
              "      <td>41.81</td>\n",
              "      <td>43.59</td>\n",
              "      <td>214.52</td>\n",
              "      <td>63.35</td>\n",
              "      <td>37.94</td>\n",
              "      <td>105.62</td>\n",
              "      <td>172.20</td>\n",
              "      <td>262.09</td>\n",
              "      <td>78.86</td>\n",
              "      <td>230.78</td>\n",
              "      <td>160.12</td>\n",
              "      <td>726.880000</td>\n",
              "      <td>363.440000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>HOTEL &amp; TOURISM</th>\n",
              "      <td>13.20</td>\n",
              "      <td>32.12</td>\n",
              "      <td>33.75</td>\n",
              "      <td>49.36</td>\n",
              "      <td>37.01</td>\n",
              "      <td>71.78</td>\n",
              "      <td>195.66</td>\n",
              "      <td>421.47</td>\n",
              "      <td>463.92</td>\n",
              "      <td>753.02</td>\n",
              "      <td>308.05</td>\n",
              "      <td>992.86</td>\n",
              "      <td>3259.05</td>\n",
              "      <td>486.38</td>\n",
              "      <td>777.01</td>\n",
              "      <td>1332.69</td>\n",
              "      <td>916.13</td>\n",
              "      <td>1882.100000</td>\n",
              "      <td>941.050000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>TRADING</th>\n",
              "      <td>11.49</td>\n",
              "      <td>43.27</td>\n",
              "      <td>38.13</td>\n",
              "      <td>31.12</td>\n",
              "      <td>14.22</td>\n",
              "      <td>28.93</td>\n",
              "      <td>114.65</td>\n",
              "      <td>345.02</td>\n",
              "      <td>643.64</td>\n",
              "      <td>737.95</td>\n",
              "      <td>498.04</td>\n",
              "      <td>731.55</td>\n",
              "      <td>717.80</td>\n",
              "      <td>1343.39</td>\n",
              "      <td>2727.96</td>\n",
              "      <td>3845.32</td>\n",
              "      <td>2338.40</td>\n",
              "      <td>6632.433333</td>\n",
              "      <td>3316.216667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>RETAIL TRADING</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>1.27</td>\n",
              "      <td>0.09</td>\n",
              "      <td>13.73</td>\n",
              "      <td>26.27</td>\n",
              "      <td>31.70</td>\n",
              "      <td>22.31</td>\n",
              "      <td>11.30</td>\n",
              "      <td>168.72</td>\n",
              "      <td>262.24</td>\n",
              "      <td>450.94</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>AGRICULTURE SERVICES</th>\n",
              "      <td>17.52</td>\n",
              "      <td>14.06</td>\n",
              "      <td>11.01</td>\n",
              "      <td>0.59</td>\n",
              "      <td>3.83</td>\n",
              "      <td>9.08</td>\n",
              "      <td>12.53</td>\n",
              "      <td>58.13</td>\n",
              "      <td>5.35</td>\n",
              "      <td>1222.22</td>\n",
              "      <td>43.90</td>\n",
              "      <td>49.02</td>\n",
              "      <td>161.47</td>\n",
              "      <td>91.01</td>\n",
              "      <td>59.95</td>\n",
              "      <td>84.65</td>\n",
              "      <td>76.43</td>\n",
              "      <td>138.053333</td>\n",
              "      <td>69.026667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>DIAMOND,GOLD ORNAMENTS</th>\n",
              "      <td>18.83</td>\n",
              "      <td>0.36</td>\n",
              "      <td>1.30</td>\n",
              "      <td>1.96</td>\n",
              "      <td>8.58</td>\n",
              "      <td>15.52</td>\n",
              "      <td>61.97</td>\n",
              "      <td>59.15</td>\n",
              "      <td>83.50</td>\n",
              "      <td>31.08</td>\n",
              "      <td>19.59</td>\n",
              "      <td>36.30</td>\n",
              "      <td>52.61</td>\n",
              "      <td>42.56</td>\n",
              "      <td>280.18</td>\n",
              "      <td>58.54</td>\n",
              "      <td>123.92</td>\n",
              "      <td>175.986667</td>\n",
              "      <td>87.993333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>TEA AND COFFEE (PROCESSING &amp; WAREHOUSING COFFEE &amp; RUBBER)</th>\n",
              "      <td>20.23</td>\n",
              "      <td>0.14</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.32</td>\n",
              "      <td>0.01</td>\n",
              "      <td>1.43</td>\n",
              "      <td>6.20</td>\n",
              "      <td>18.94</td>\n",
              "      <td>37.08</td>\n",
              "      <td>8.15</td>\n",
              "      <td>3.12</td>\n",
              "      <td>5.32</td>\n",
              "      <td>0.27</td>\n",
              "      <td>5.86</td>\n",
              "      <td>1.43</td>\n",
              "      <td>1.12</td>\n",
              "      <td>1.60</td>\n",
              "      <td>22.993333</td>\n",
              "      <td>11.496667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>PRINTING OF BOOKS (INCLUDING LITHO PRINTING INDUSTRY)</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>6.30</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.06</td>\n",
              "      <td>9.90</td>\n",
              "      <td>20.04</td>\n",
              "      <td>35.54</td>\n",
              "      <td>31.61</td>\n",
              "      <td>70.51</td>\n",
              "      <td>36.63</td>\n",
              "      <td>47.39</td>\n",
              "      <td>14.34</td>\n",
              "      <td>113.78</td>\n",
              "      <td>72.58</td>\n",
              "      <td>122.81</td>\n",
              "      <td>53.17</td>\n",
              "      <td>593.506667</td>\n",
              "      <td>296.753333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>COIR</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.47</td>\n",
              "      <td>0.59</td>\n",
              "      <td>0.04</td>\n",
              "      <td>0.01</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.25</td>\n",
              "      <td>0.10</td>\n",
              "      <td>0.55</td>\n",
              "      <td>0.15</td>\n",
              "      <td>0.54</td>\n",
              "      <td>1.36</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.006667</td>\n",
              "      <td>0.003333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>CONSTRUCTION (INFRASTRUCTURE) ACTIVITIES</th>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.93</td>\n",
              "      <td>64.06</td>\n",
              "      <td>182.92</td>\n",
              "      <td>172.70</td>\n",
              "      <td>324.56</td>\n",
              "      <td>675.07</td>\n",
              "      <td>386.28</td>\n",
              "      <td>283.89</td>\n",
              "      <td>485.37</td>\n",
              "      <td>870.25</td>\n",
              "      <td>4510.71</td>\n",
              "      <td>1860.73</td>\n",
              "      <td>3679.813333</td>\n",
              "      <td>1839.906667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>CONSTRUCTION DEVELOPMENT: Townships, housing, built-up infrastructure and construction-development projects</th>\n",
              "      <td>24.33</td>\n",
              "      <td>51.75</td>\n",
              "      <td>36.10</td>\n",
              "      <td>47.04</td>\n",
              "      <td>152.06</td>\n",
              "      <td>228.71</td>\n",
              "      <td>1392.95</td>\n",
              "      <td>3887.33</td>\n",
              "      <td>4657.51</td>\n",
              "      <td>5466.13</td>\n",
              "      <td>1663.03</td>\n",
              "      <td>3140.78</td>\n",
              "      <td>1332.49</td>\n",
              "      <td>1226.05</td>\n",
              "      <td>769.14</td>\n",
              "      <td>112.55</td>\n",
              "      <td>105.14</td>\n",
              "      <td>552.806667</td>\n",
              "      <td>276.403333</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>MISCELLANEOUS INDUSTRIES</th>\n",
              "      <td>832.07</td>\n",
              "      <td>221.37</td>\n",
              "      <td>218.76</td>\n",
              "      <td>235.48</td>\n",
              "      <td>121.83</td>\n",
              "      <td>164.76</td>\n",
              "      <td>304.87</td>\n",
              "      <td>528.42</td>\n",
              "      <td>1549.70</td>\n",
              "      <td>1147.56</td>\n",
              "      <td>1475.97</td>\n",
              "      <td>813.38</td>\n",
              "      <td>229.49</td>\n",
              "      <td>468.74</td>\n",
              "      <td>765.88</td>\n",
              "      <td>668.77</td>\n",
              "      <td>296.40</td>\n",
              "      <td>860.646667</td>\n",
              "      <td>430.323333</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>63 rows × 19 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                                                    2000-01  2001-02  2002-03  \\\n",
              "Sector                                                                          \n",
              "METALLURGICAL INDUSTRIES                              22.69    14.14    36.61   \n",
              "MINING                                                 1.32     6.52    10.06   \n",
              "POWER                                                 89.42   757.44    59.11   \n",
              "NON-CONVENTIONAL ENERGY                                0.00     0.00     1.70   \n",
              "COAL PRODUCTION                                        0.00     0.00     0.00   \n",
              "...                                                     ...      ...      ...   \n",
              "PRINTING OF BOOKS (INCLUDING LITHO PRINTING IND...     0.00     0.00     6.30   \n",
              "COIR                                                   0.00     0.00     0.00   \n",
              "CONSTRUCTION (INFRASTRUCTURE) ACTIVITIES               0.00     0.00     0.00   \n",
              "CONSTRUCTION DEVELOPMENT: Townships, housing, b...    24.33    51.75    36.10   \n",
              "MISCELLANEOUS INDUSTRIES                             832.07   221.37   218.76   \n",
              "\n",
              "                                                    2003-04  2004-05  2005-06  \\\n",
              "Sector                                                                          \n",
              "METALLURGICAL INDUSTRIES                               8.11   200.38   149.13   \n",
              "MINING                                                23.48     9.92     7.40   \n",
              "POWER                                                 27.09    43.37    72.69   \n",
              "NON-CONVENTIONAL ENERGY                                4.14     1.27     1.35   \n",
              "COAL PRODUCTION                                        0.04     0.00     9.14   \n",
              "...                                                     ...      ...      ...   \n",
              "PRINTING OF BOOKS (INCLUDING LITHO PRINTING IND...     0.00     0.06     9.90   \n",
              "COIR                                                   0.00     0.47     0.59   \n",
              "CONSTRUCTION (INFRASTRUCTURE) ACTIVITIES               0.00     0.00     0.93   \n",
              "CONSTRUCTION DEVELOPMENT: Townships, housing, b...    47.04   152.06   228.71   \n",
              "MISCELLANEOUS INDUSTRIES                             235.48   121.83   164.76   \n",
              "\n",
              "                                                    2006-07  2007-08  2008-09  \\\n",
              "Sector                                                                          \n",
              "METALLURGICAL INDUSTRIES                             169.94  1175.75   959.94   \n",
              "MINING                                                 6.62   444.36    34.16   \n",
              "POWER                                                157.15   988.68   907.66   \n",
              "NON-CONVENTIONAL ENERGY                                2.44    58.82   125.88   \n",
              "COAL PRODUCTION                                        1.30    14.08     0.22   \n",
              "...                                                     ...      ...      ...   \n",
              "PRINTING OF BOOKS (INCLUDING LITHO PRINTING IND...    20.04    35.54    31.61   \n",
              "COIR                                                   0.04     0.01     0.00   \n",
              "CONSTRUCTION (INFRASTRUCTURE) ACTIVITIES              64.06   182.92   172.70   \n",
              "CONSTRUCTION DEVELOPMENT: Townships, housing, b...  1392.95  3887.33  4657.51   \n",
              "MISCELLANEOUS INDUSTRIES                             304.87   528.42  1549.70   \n",
              "\n",
              "                                                    2009-10  2010-11  2011-12  \\\n",
              "Sector                                                                          \n",
              "METALLURGICAL INDUSTRIES                             419.88  1098.14  1786.14   \n",
              "MINING                                               174.40    79.51   142.65   \n",
              "POWER                                               1271.79  1271.77  1652.38   \n",
              "NON-CONVENTIONAL ENERGY                              622.52   214.40   452.17   \n",
              "COAL PRODUCTION                                        0.00     0.00     0.00   \n",
              "...                                                     ...      ...      ...   \n",
              "PRINTING OF BOOKS (INCLUDING LITHO PRINTING IND...    70.51    36.63    47.39   \n",
              "COIR                                                   0.25     0.10     0.55   \n",
              "CONSTRUCTION (INFRASTRUCTURE) ACTIVITIES             324.56   675.07   386.28   \n",
              "CONSTRUCTION DEVELOPMENT: Townships, housing, b...  5466.13  1663.03  3140.78   \n",
              "MISCELLANEOUS INDUSTRIES                            1147.56  1475.97   813.38   \n",
              "\n",
              "                                                    2012-13  2013-14  2014-15  \\\n",
              "Sector                                                                          \n",
              "METALLURGICAL INDUSTRIES                            1466.23   567.63   359.34   \n",
              "MINING                                                57.89    12.73   684.39   \n",
              "POWER                                                535.68  1066.08   707.04   \n",
              "NON-CONVENTIONAL ENERGY                             1106.52   414.25   615.95   \n",
              "COAL PRODUCTION                                        0.00     2.96     0.00   \n",
              "...                                                     ...      ...      ...   \n",
              "PRINTING OF BOOKS (INCLUDING LITHO PRINTING IND...    14.34   113.78    72.58   \n",
              "COIR                                                   0.15     0.54     1.36   \n",
              "CONSTRUCTION (INFRASTRUCTURE) ACTIVITIES             283.89   485.37   870.25   \n",
              "CONSTRUCTION DEVELOPMENT: Townships, housing, b...  1332.49  1226.05   769.14   \n",
              "MISCELLANEOUS INDUSTRIES                             229.49   468.74   765.88   \n",
              "\n",
              "                                                    2015-16  2016-17  \\\n",
              "Sector                                                                 \n",
              "METALLURGICAL INDUSTRIES                             456.31  1440.18   \n",
              "MINING                                               520.67    55.75   \n",
              "POWER                                                868.80  1112.98   \n",
              "NON-CONVENTIONAL ENERGY                              776.51   783.57   \n",
              "COAL PRODUCTION                                        0.00     0.00   \n",
              "...                                                     ...      ...   \n",
              "PRINTING OF BOOKS (INCLUDING LITHO PRINTING IND...   122.81    53.17   \n",
              "COIR                                                   0.00     0.00   \n",
              "CONSTRUCTION (INFRASTRUCTURE) ACTIVITIES            4510.71  1860.73   \n",
              "CONSTRUCTION DEVELOPMENT: Townships, housing, b...   112.55   105.14   \n",
              "MISCELLANEOUS INDUSTRIES                             668.77   296.40   \n",
              "\n",
              "                                                        2017-18      2018-19  \n",
              "Sector                                                                        \n",
              "METALLURGICAL INDUSTRIES                             694.446667   347.223333  \n",
              "MINING                                               252.926667   126.463333  \n",
              "POWER                                               1944.280000   972.140000  \n",
              "NON-CONVENTIONAL ENERGY                             1921.053333   960.526667  \n",
              "COAL PRODUCTION                                       -0.006667    -0.003333  \n",
              "...                                                         ...          ...  \n",
              "PRINTING OF BOOKS (INCLUDING LITHO PRINTING IND...   593.506667   296.753333  \n",
              "COIR                                                   0.006667     0.003333  \n",
              "CONSTRUCTION (INFRASTRUCTURE) ACTIVITIES            3679.813333  1839.906667  \n",
              "CONSTRUCTION DEVELOPMENT: Townships, housing, b...   552.806667   276.403333  \n",
              "MISCELLANEOUS INDUSTRIES                             860.646667   430.323333  \n",
              "\n",
              "[63 rows x 19 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "1tfGkAZv0DTT",
        "colab_type": "text"
      },
      "source": [
        "## Transforming the dataset"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "btoEW9EC0DTU",
        "colab_type": "code",
        "colab": {},
        "outputId": "e6581703-7f48-4f5b-8e25-543abacf38fa"
      },
      "source": [
        "df = dataframe.transpose()\n",
        "df.index = [x[1] for x in df.index.str.split('-')]\n",
        "new = str('20') + df.index\n",
        "new"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['2001', '2002', '2003', '2004', '2005', '2006', '2007', '2008', '2009',\n",
              "       '2010', '2011', '2012', '2013', '2014', '2015', '2016', '2017', '2018',\n",
              "       '2019'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "WWCz4Etb0DTX",
        "colab_type": "code",
        "colab": {},
        "outputId": "17df2ca3-fd7f-4bf6-b75e-8c4e88859ae4"
      },
      "source": [
        "df = dataframe.transpose()\n",
        "df.index = [x[1] for x in df.index.str.split('-')]\n",
        "df.index = str('20') + df.index\n",
        "df.index = pd.to_datetime(df.index)\n",
        "print(type(df.index))\n",
        "df.tail()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.indexes.datetimes.DatetimeIndex'>\n"
          ],
          "name": "stdout"
        },
        {
          "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>Sector</th>\n",
              "      <th>METALLURGICAL INDUSTRIES</th>\n",
              "      <th>MINING</th>\n",
              "      <th>POWER</th>\n",
              "      <th>NON-CONVENTIONAL ENERGY</th>\n",
              "      <th>COAL PRODUCTION</th>\n",
              "      <th>PETROLEUM &amp; NATURAL GAS</th>\n",
              "      <th>BOILERS AND STEAM GENERATING PLANTS</th>\n",
              "      <th>PRIME MOVER (OTHER THAN ELECTRICAL GENERATORS)</th>\n",
              "      <th>ELECTRICAL EQUIPMENTS</th>\n",
              "      <th>COMPUTER SOFTWARE &amp; HARDWARE</th>\n",
              "      <th>...</th>\n",
              "      <th>TRADING</th>\n",
              "      <th>RETAIL TRADING</th>\n",
              "      <th>AGRICULTURE SERVICES</th>\n",
              "      <th>DIAMOND,GOLD ORNAMENTS</th>\n",
              "      <th>TEA AND COFFEE (PROCESSING &amp; WAREHOUSING COFFEE &amp; RUBBER)</th>\n",
              "      <th>PRINTING OF BOOKS (INCLUDING LITHO PRINTING INDUSTRY)</th>\n",
              "      <th>COIR</th>\n",
              "      <th>CONSTRUCTION (INFRASTRUCTURE) ACTIVITIES</th>\n",
              "      <th>CONSTRUCTION DEVELOPMENT: Townships, housing, built-up infrastructure and construction-development projects</th>\n",
              "      <th>MISCELLANEOUS INDUSTRIES</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2015-01-01</th>\n",
              "      <td>359.340000</td>\n",
              "      <td>684.390000</td>\n",
              "      <td>707.04</td>\n",
              "      <td>615.950000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1079.020000</td>\n",
              "      <td>1.33</td>\n",
              "      <td>230.700000</td>\n",
              "      <td>574.830000</td>\n",
              "      <td>2296.04</td>\n",
              "      <td>...</td>\n",
              "      <td>2727.960000</td>\n",
              "      <td>168.72</td>\n",
              "      <td>59.950000</td>\n",
              "      <td>280.180000</td>\n",
              "      <td>1.430000</td>\n",
              "      <td>72.580000</td>\n",
              "      <td>1.360000</td>\n",
              "      <td>870.250000</td>\n",
              "      <td>769.140000</td>\n",
              "      <td>765.880000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-01-01</th>\n",
              "      <td>456.310000</td>\n",
              "      <td>520.670000</td>\n",
              "      <td>868.80</td>\n",
              "      <td>776.510000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>103.020000</td>\n",
              "      <td>77.91</td>\n",
              "      <td>159.130000</td>\n",
              "      <td>444.880000</td>\n",
              "      <td>5904.36</td>\n",
              "      <td>...</td>\n",
              "      <td>3845.320000</td>\n",
              "      <td>262.24</td>\n",
              "      <td>84.650000</td>\n",
              "      <td>58.540000</td>\n",
              "      <td>1.120000</td>\n",
              "      <td>122.810000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>4510.710000</td>\n",
              "      <td>112.550000</td>\n",
              "      <td>668.770000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2017-01-01</th>\n",
              "      <td>1440.180000</td>\n",
              "      <td>55.750000</td>\n",
              "      <td>1112.98</td>\n",
              "      <td>783.570000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>180.400000</td>\n",
              "      <td>53.91</td>\n",
              "      <td>286.880000</td>\n",
              "      <td>2230.690000</td>\n",
              "      <td>3651.71</td>\n",
              "      <td>...</td>\n",
              "      <td>2338.400000</td>\n",
              "      <td>450.94</td>\n",
              "      <td>76.430000</td>\n",
              "      <td>123.920000</td>\n",
              "      <td>1.600000</td>\n",
              "      <td>53.170000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>1860.730000</td>\n",
              "      <td>105.140000</td>\n",
              "      <td>296.400000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2018-01-01</th>\n",
              "      <td>694.446667</td>\n",
              "      <td>252.926667</td>\n",
              "      <td>1944.28</td>\n",
              "      <td>1921.053333</td>\n",
              "      <td>-0.006667</td>\n",
              "      <td>110.653333</td>\n",
              "      <td>45.48</td>\n",
              "      <td>276.453333</td>\n",
              "      <td>1075.433333</td>\n",
              "      <td>9872.94</td>\n",
              "      <td>...</td>\n",
              "      <td>6632.433333</td>\n",
              "      <td>0.00</td>\n",
              "      <td>138.053333</td>\n",
              "      <td>175.986667</td>\n",
              "      <td>22.993333</td>\n",
              "      <td>593.506667</td>\n",
              "      <td>0.006667</td>\n",
              "      <td>3679.813333</td>\n",
              "      <td>552.806667</td>\n",
              "      <td>860.646667</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-01-01</th>\n",
              "      <td>347.223333</td>\n",
              "      <td>126.463333</td>\n",
              "      <td>972.14</td>\n",
              "      <td>960.526667</td>\n",
              "      <td>-0.003333</td>\n",
              "      <td>55.326667</td>\n",
              "      <td>22.74</td>\n",
              "      <td>138.226667</td>\n",
              "      <td>537.716667</td>\n",
              "      <td>4936.47</td>\n",
              "      <td>...</td>\n",
              "      <td>3316.216667</td>\n",
              "      <td>0.00</td>\n",
              "      <td>69.026667</td>\n",
              "      <td>87.993333</td>\n",
              "      <td>11.496667</td>\n",
              "      <td>296.753333</td>\n",
              "      <td>0.003333</td>\n",
              "      <td>1839.906667</td>\n",
              "      <td>276.403333</td>\n",
              "      <td>430.323333</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 63 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "Sector      METALLURGICAL INDUSTRIES      MINING    POWER  \\\n",
              "2015-01-01                359.340000  684.390000   707.04   \n",
              "2016-01-01                456.310000  520.670000   868.80   \n",
              "2017-01-01               1440.180000   55.750000  1112.98   \n",
              "2018-01-01                694.446667  252.926667  1944.28   \n",
              "2019-01-01                347.223333  126.463333   972.14   \n",
              "\n",
              "Sector      NON-CONVENTIONAL ENERGY  COAL PRODUCTION  PETROLEUM & NATURAL GAS  \\\n",
              "2015-01-01               615.950000         0.000000              1079.020000   \n",
              "2016-01-01               776.510000         0.000000               103.020000   \n",
              "2017-01-01               783.570000         0.000000               180.400000   \n",
              "2018-01-01              1921.053333        -0.006667               110.653333   \n",
              "2019-01-01               960.526667        -0.003333                55.326667   \n",
              "\n",
              "Sector      BOILERS AND STEAM GENERATING PLANTS  \\\n",
              "2015-01-01                                 1.33   \n",
              "2016-01-01                                77.91   \n",
              "2017-01-01                                53.91   \n",
              "2018-01-01                                45.48   \n",
              "2019-01-01                                22.74   \n",
              "\n",
              "Sector      PRIME MOVER (OTHER THAN ELECTRICAL GENERATORS)  \\\n",
              "2015-01-01                                      230.700000   \n",
              "2016-01-01                                      159.130000   \n",
              "2017-01-01                                      286.880000   \n",
              "2018-01-01                                      276.453333   \n",
              "2019-01-01                                      138.226667   \n",
              "\n",
              "Sector      ELECTRICAL EQUIPMENTS  COMPUTER SOFTWARE & HARDWARE  ...  \\\n",
              "2015-01-01             574.830000                       2296.04  ...   \n",
              "2016-01-01             444.880000                       5904.36  ...   \n",
              "2017-01-01            2230.690000                       3651.71  ...   \n",
              "2018-01-01            1075.433333                       9872.94  ...   \n",
              "2019-01-01             537.716667                       4936.47  ...   \n",
              "\n",
              "Sector          TRADING  RETAIL TRADING  AGRICULTURE SERVICES  \\\n",
              "2015-01-01  2727.960000          168.72             59.950000   \n",
              "2016-01-01  3845.320000          262.24             84.650000   \n",
              "2017-01-01  2338.400000          450.94             76.430000   \n",
              "2018-01-01  6632.433333            0.00            138.053333   \n",
              "2019-01-01  3316.216667            0.00             69.026667   \n",
              "\n",
              "Sector      DIAMOND,GOLD ORNAMENTS  \\\n",
              "2015-01-01              280.180000   \n",
              "2016-01-01               58.540000   \n",
              "2017-01-01              123.920000   \n",
              "2018-01-01              175.986667   \n",
              "2019-01-01               87.993333   \n",
              "\n",
              "Sector      TEA AND COFFEE (PROCESSING & WAREHOUSING COFFEE & RUBBER)  \\\n",
              "2015-01-01                                           1.430000           \n",
              "2016-01-01                                           1.120000           \n",
              "2017-01-01                                           1.600000           \n",
              "2018-01-01                                          22.993333           \n",
              "2019-01-01                                          11.496667           \n",
              "\n",
              "Sector      PRINTING OF BOOKS (INCLUDING LITHO PRINTING INDUSTRY)      COIR  \\\n",
              "2015-01-01                                          72.580000      1.360000   \n",
              "2016-01-01                                         122.810000      0.000000   \n",
              "2017-01-01                                          53.170000      0.000000   \n",
              "2018-01-01                                         593.506667      0.006667   \n",
              "2019-01-01                                         296.753333      0.003333   \n",
              "\n",
              "Sector      CONSTRUCTION (INFRASTRUCTURE) ACTIVITIES  \\\n",
              "2015-01-01                                870.250000   \n",
              "2016-01-01                               4510.710000   \n",
              "2017-01-01                               1860.730000   \n",
              "2018-01-01                               3679.813333   \n",
              "2019-01-01                               1839.906667   \n",
              "\n",
              "Sector      CONSTRUCTION DEVELOPMENT: Townships, housing, built-up infrastructure and construction-development projects  \\\n",
              "2015-01-01                                         769.140000                                                             \n",
              "2016-01-01                                         112.550000                                                             \n",
              "2017-01-01                                         105.140000                                                             \n",
              "2018-01-01                                         552.806667                                                             \n",
              "2019-01-01                                         276.403333                                                             \n",
              "\n",
              "Sector      MISCELLANEOUS INDUSTRIES  \n",
              "2015-01-01                765.880000  \n",
              "2016-01-01                668.770000  \n",
              "2017-01-01                296.400000  \n",
              "2018-01-01                860.646667  \n",
              "2019-01-01                430.323333  \n",
              "\n",
              "[5 rows x 63 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "D3QCcNgV0DTZ",
        "colab_type": "text"
      },
      "source": [
        "# FDI in various sectors of Indian economy since 2000"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "I3AXgKkP0DTa",
        "colab_type": "code",
        "colab": {},
        "outputId": "d4d05b18-f6cc-4da7-a368-74072f172972"
      },
      "source": [
        "def plot_data(data=df,x='Year',y='Amount is million USD',t='FDI IN ALL SECTORS OF INDIAN ECONOMY'):\n",
        "    plt.figure(figsize=(8,8))\n",
        "    plt.plot(data)\n",
        "#     plt.legend(data.columns)\n",
        "    plt.xlabel(x)\n",
        "    plt.ylabel(y)\n",
        "    plt.title(t)\n",
        "    plt.show()\n",
        "    \n",
        "plot_data()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "c:\\users\\parik\\appdata\\local\\programs\\python\\python37\\lib\\site-packages\\pandas\\plotting\\_matplotlib\\converter.py:102: FutureWarning: Using an implicitly registered datetime converter for a matplotlib plotting method. The converter was registered by pandas on import. Future versions of pandas will require you to explicitly register matplotlib converters.\n",
            "\n",
            "To register the converters:\n",
            "\t>>> from pandas.plotting import register_matplotlib_converters\n",
            "\t>>> register_matplotlib_converters()\n",
            "  warnings.warn(msg, FutureWarning)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAgEAAAHwCAYAAAA/wLxAAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8QZhcZAAAgAElEQVR4nOzdeXzcZ3Xo/8+ZXfvuRXIs2bGdxc7mOBACIUASSIA0FBoucNuE5f5ob1naphvc25alFwotvWUplEJJCe0tYMKWhECI0ywFkhDZWWxnc2J502JLGkkzGmn25/fH9zuj0Wg0M5JGMyPpvF+veY31ne/MPDOWPWee55zziDEGpZRSSq09jkoPQCmllFKVoUGAUkoptUZpEKCUUkqtURoEKKWUUmuUBgFKKaXUGqVBgFJKKbVGaRCglFJKrVEaBKiKEJFjIjItIpMZl04R6RERk3HstIjcLSLX5rj/NfM89sdF5N8zfjYiclBEHBnH/o+IfLPAGLeISFJEvpLjNiMi23Icf7eI/KKItwAReZWI/EpEJkTELyK/FJHLMh4nkfX+TIpIZ8b93yUivfbxQRH5qf2YX804PyoisYyff2rf1ysifyMiJ+y/hyMi8qciIhmP/6CIhO37jYjID0RkY8btzSJym4gMiUhQRF4QkT/P83oX+pypyytyPFbq98Rl//xN++eXZZyzTURMjscOikhARPaLyEdExJtxzqzfHfuYiMhREXkmxzhSj3lWxrFrRORYnvfBiEgo6zX+WcbtO0Tke/Z7PiEiT4vIrSLiXMT7mHdc9u/ZQRGZsv8e/0lEmrPeDyMiH8663x/axz8uIuvtsb4m65x/FZFvz/c+qOqgQYCqpBuMMfUZl4GM25qNMfXARcB9wA9F5N1LeK5O4B0LvM/NwBjwjswPilIQkUbgbuBLQCvQBXwCiGSc9kjW+5N+j0TkVuDzwKeB9cBm4CvAjcaY30udb9/+3Yz7X28/9veAq4E3Ag3A7wDvB76QNdQP2o+zDagHPpdx2z/Yx84DmoDfAF7K87IX9JwZl0fyPGYmP/B/CpzzQWNMA7AR+GOs34l7Mj9Ac3g1sA7YKnaQliUE/GWRY0y5KOs1/i2AiJwNPAacBC4wxjQBNwF7sN4zKP59zDsuEflj4LPAn2L9/V0OdAP3iYgn49QXgFuy7n6zfRxjzGngj4Cvi0iN/dhXA28CPoyqahoEqKpmjBkyxnwB+DjwWcn4Nr9Afwt8IvXNsUg3A38BxIAbFvm889kBYIz5tjEmYYyZNsb83BjzdKE7ikgT8EngA8aYHxhjQsaYmDHmLmPMnxZx/6uB1wNvM8YcMsbEjTGPAr8NfEByzHAYY8aBHwEXZxy+DPgPY8yYMSZpjHnOGHNHqZ5zEW4HLhSRqwqdaL9nD2IFLq/A+sCazy3Aj4F7mPthCPBF4J0leg2fAH5ljLnVGDNoj/V5Y8y7jDHjC3wf5x2XHYR+AviQMeZn9u/PMeDtWIHAb2ec/jhQKyI77fvuBGrs49hj/DfgeeCTdiDwz8CHjTHDJXhP1DLSIECtFD/A+jZ2zhLuHwDeXczJInIlsAn4DrAXKyAopReAhIjcLiLXi0jLAu77CsAH/HCRz30t8Jgx5mTmQWPMY8AprG+Zs4hIG/BW4MWMw48CnxKR94jI9lI/5yJMYc18fKrYOxhjTgC9wJW5bheRWuC3gP9nX96R9S0ZoB/4OlagulTXADkDKdtC3sd847oC63foB1mPMwn81H6eTP/GzL+BW4Bv5XjM3wPei/Vv5pAx5jt5XoeqEhoEqEr6kYiM25cfFTg3tVTQusjnMlhTo39V5NT+LcBPjTFjwH8A14vIukU+99zBGBMAXmWP6+vAsIjcKSLrM067POP9GReR1FR7GzBijIkv8unbgcF5bhu0b0/5oohMACP28Q9l3PYhrA/GDwLPiMiLInI9uS30OVOv+UD+lzLHPwOb84wjlwHm/716K9YSzc+xlm9c5J41+BvghtS35SIcyPq7fYN9vI353ydY2PuYb1ztzP87lOtx/h1rVsGNtYTy79l3MsacAv4KK5D5n3leg6oiGgSoSnqLMabZvrylwLld9rV/sU9mjLkHOIG1fjovezrzJqwPOOw16RPAuxb73POM51ljzLuNMZuAXVh5C5/POOXRjPen2Rhztn18FGhf4NJGphGsNfFcNtq3p3zYXpe+EGjBmh1JjX/aGPNpY8ylWB9ee4HviUiuD9SFPmfqNe8u6hXNjCkC/LV9ybfOn6mL+X+vbgH22tPuEaxvznOWBOxp73/EWqYpxu6sv9t77eOjzP8+wcLex3zjGmH+36Fcj3MCaxbo08CR7JmIDIeBsdRShqp+GgSoleI3gTNY645L8RfA/wZqCzxXI/AVO2N6COuDotRLAmnGmOeAb2IFA4U8AoSBQoHTfPYBL8/MHAcQK7P+LOA/c4zvIFbS3ZdzJdHZMxufBuqALaV4ziX4V6xEt98sdKI9nkuB/8px2ybgdcBvZ/we/BbwRhHJ/qYM8HfAa+3HW6x9wNsK3L7Q9zHXuB7BmuF4a9bj1AHXA/fneJxvYSVT5loKUCuUBgGqqtnlRx8EPgZ81BiTXMrj2clgB8md4JVyC3AbcAFWItzFwCuBi0XkgozzPCLiy7g4Z4Y967gvx+s6V0T+2P6gSX0YvRNrnb3Qa5jAmnb9soi8RURqRcRt5xb8bRH334f1n/z3RWSniDhF5HKsmY9/MsYcmeeut2PlZfyGPea/FJHLRMRjv8Y/AMbJEagt4TkXzJ7i/jiQr1yx1k4g/DHwa6ykv2y/g5W7cQ4zvwc7sNbe35njeceBvwf+LPu2BfgYcIWI/J2IbLDHuk1E/l1EmhfzPuYal/079AngSyJynf3704NVeXAKKwcg23exkhL3LuH1qSqjQYCqVuMiEsL6wH4jcJMx5rYSPfZfMM8asIh0YSVXfd6uTEhd9gM/Y3bwcBiYzri8xz5+Rdbx6RzTrkHg5cBj9ut8FDiE9U0r5RUyt0/AZQDGmP8L3Gq/lmGskrIPYmXwF+NtwAP2a5rEWuP9BrPX/GcxxkSxMs5TZWcG61v3CNa6+rXAm+zkspI85xJ8m9xr5/8oIkHgNNbSy/eB6+YJLm8BvpL1ezAEfJX5g8gvAIkixvdU1t/r5wGMMS9hJX72AIftfIzvYyUvBu37LuZ9nDMuuyzxf2GVfQaYKU282l76IOv8aWPMPmPMdBGvT60QYowpfJZSSimlVh2dCVBKKaXWKA0ClFJKqTVKgwCllFJqjdIgQCmllFqjNAhQSiml1qjFdhxbsdrb201PT0+lh6GUUkqVxf79+0eMMR25bltzQUBPTw+9vb2VHoZSSilVFiJyfL7bdDlAKaWUWqM0CFBKKaXWqGULAkTkNhE5IyKHMo79nYg8JyJPi8gPRaQ547aP2luRPp+xrSZ2X+vn7ds+knF8i4g8JiJHROS7Ofb4VkoppVQeyzkT8E3guqxj9wG7jDEXYm3M8VEAETkfa4/qnfZ9vmJvjOEEvoy1q9X5WPtZn28/1meBfzDGbAfGgPct42tRSimlVp1lCwKMMQ+TtUe3Mebn9g5fYG2Yktqb/EbgO8aYiDGmD2vf6pfZlxeNMUftzUu+A9xob2X6OuAO+/63s/htVZVSSqk1qZI5Ae8Ffmr/uQtr96qUU/ax+Y63AeMZAUXquFJKKaWKVJEgQET+NxDH2gMbQHKcZhZxfL7ne7+I9IpI7/Dw8EKHq5RSSq1KZQ8CROQW4M3Afzcz+xifAs7KOG0T1v7k8x0fAZoz9mhPHc/JGPM1Y8weY8yejo6c/RKUUkqpNaesQYCIXAf8OfAbxpipjJvuBN4hIl4R2QJsB34NPA5stysBPFjJg3fawcMDwG/Z978F+HG5XodSSim1GixnieC3gUeAc0TklIi8D/hHoAG4T0SeFJGvAhhjDgN7gWeAnwEfMMYk7DX/DwL3As8Ce+1zwQombhWRF7FyBL6xXK9FKaWUWo1kZkZ+bdizZ4/RtsFKKaXWChHZb4zZk+s27RiolFJKrVEaBCillFJrlAYBSiml1BqlQYBSSim1RmkQoJRSSq1RGgQopZRSa5QGAUoppdQC7B3ys/tXh4klV36JvQYBSiml1ALcOzLBQCTGYCRa6aEsmQYBSimlVJGMMTw+EQJgIBKr8GiWToMApZRSqkgnw1HORK1d7DUIUEoppdaQ/YGZve/6wyt/OcBV+BSllFJKAfROhKh1OnAC/atgJkCDAKWUUqpIjwdCXNJQiz8WZ2AVzATocoBSSilVhKlEkmcmp9nTVEen16M5AUoppdRa8VRwiriBPY21dPncDGiJoFJKKbU29NqlgZc21dHl9eCPJZhKJCs8qqXRIEAppZQqQm8gxNk1XlrdLjp9boAVPxugQYBSSilVgDGG3okp9jTVAdDptYOA8MrOC9AgQCmllCrg2HSU0VicPU21AHT5PAD060yAUkoptbr1Bqx8gD2N1kzARp0JUEoppdaG3okQDU4HO+p8AHgdDjo8Ls0JUEoppVa73kCI3Y11OEXSxzq9bvp1JkAppZRavSbjCZ6dDHOpnQ+Q0uX1aE6AUkoptZo9GZwiCVxm5wOkdPrcDERiGGMqM7AS0CBAKaWUyuNxu0nQ7sbZMwGdXg+hRJJAPFGJYZWEBgFKKaVUHr0TU+yo9dHknr3nXle6YdDKzQvQIEAppZSaR9IYDgRCXJaVDwBWTgDAqRW8m6AGAUoppdQ8XpqKMBZPcGlT3Zzb0l0DdSZAKaWUWn2ymwRlWu914xQNApRSSqlVaf/EFM0uJ9tqvXNuc4qwweOmX5cDlFJKqdXn8UCI3Y21ODKaBGXq9Hp0JkAppZRabQLxBC+EwumdA3Pp8rlXdOtgDQKUUkqpHA4EQhjmNgnK1On1MBCOkVyhDYM0CFBKKaVyeHwihAO4pHFueWBKp89N1BhGY/HyDayENAhQSimlctg/McW5dT7qXc55z+myywRX6kZCGgQopZRSWZLGsD8QypsPANDpsxoGrdS8AA0ClFJKqSzPh8IEE8mCQUCqa+BKrRDQIEAppZTKsj8wBeRuEpSpze3E55AV2zpYgwCllFIqy+MTIVrdTrbUePKeJyJs9Lp1JkAppZRaLfYHQuxprEPmaRKUySoT1JkApZRSasXzx+K8OBXhsgL5ACmdPp0JUEoppVaF/RPWpkGXFsgHSOnyehiKxIgnV17DIA0ClFJKqQz7A1M4BS5qrCnq/C6fmyRwOrryZgM0CFBKKaUy9E6E2FlfQ51z/iZBmTrtMsGVuJugBgFKKaWULZ40HAhOFSwNzNRpdw1ciXkBGgQopZRStudC00wV0SQoU5fdNbBfgwCllFJq5epNNwmaf9OgbI0uJ/VOx4osE9QgQCmllLL1ToRY53Fxli9/k6BsnV6PLgcopZRSK1nvApoEZeryuTUxUCmllFqphqMxjk1HF5QPkNLl9WhOgFJKKbVS7Z9YeD5ASqfPzWgsTjiRLPWwlpUGAUoppRTWUoBbhAsbFhEE2GWCgytsNkCDAKWUUgorKfCChhp8zoV/NHalGgZFVlZegAYBSiml1rxY0vDUApsEZUr1ClhpFQIaBCillFrzDk9OM500XNq08KUAgI32csBKqxDQIEAppdSa1xuwdg68bJEzATVOB61up84EKKWUUitN70SITq+bzgU2CcrU5fXoTIBSSim10vQGQly6yFmAlE6fW2cClFJKqZVkKBLjVDjGZYvMB0ixWgfrTAAAInKbiJwRkUMZx1pF5D4ROWJft9jHRUS+KCIvisjTIrI74z632OcfEZFbMo5fKiIH7ft8URba41EppZTCWgoAFl0ZkNLldROIJwnGE6UYVlks50zAN4Hrso59BLjfGLMduN/+GeB6YLt9eT/wT2AFDcDHgJcDLwM+lgoc7HPen3G/7OdSSimlCuoNhPA6hF0NNUt6nJkthVfObMCyBQHGmIcBf9bhG4Hb7T/fDrwl4/i3jOVRoFlENgJvAO4zxviNMWPAfcB19m2NxphHjDEG+FbGYymllFJF650IcVFDLR7H0j4SU10DB8IrJy+g3DkB640xgwD29Tr7eBdwMuO8U/axfMdP5TiulFJKFS2STPJ0cJpLF7FfQLbOFdgwqFoSA3Ot55tFHM/94CLvF5FeEekdHh5e5BCVUkqtNoeC00SNWdTOgdk2eNwIK6thULmDgNP2VD729Rn7+CngrIzzNgEDBY5vynE8J2PM14wxe4wxezo6Opb8IpRSSq0Oj5coKRDA7RA2eFdWmWC5g4A7gVSG/y3AjzOO32xXCVwOTNjLBfcCrxeRFjsh8PXAvfZtQRG53K4KuDnjsZRSSqmi9AZCnOXzsN5ez1+qTq9bZwIAROTbwCPAOSJySkTeB3wGuFZEjgDX2j8D3AMcBV4Evg78PoAxxg/8NfC4ffmkfQzgfwL/Yt/nJeCny/ValFJKrT7GGHonptizwHyAx8Yn+eAzx0mauavQVq+AlTMT4FquBzbGvHOem67Oca4BPjDP49wG3JbjeC+wayljVEoptXb1R2IMRWMLzgf42cgEd5we439t3TinzXCnz819oxMYY1gJ7WuqJTFQKaWUKqt0k6AFBgFD9jf94zmm/bu8bsJJgz+2MhoGaRCglFJqTdofCFHjEM6vW1iToEE7CDg2HZlzW6c3VSa4MvICNAhQSim1Jj0+McXFjbW4HQubtk8FASemc8wEpLoGrpCGQRoEKKWUWnOmE0kOTU4tuDTQGMNQNP9yAKyc1sEaBCillFpzng5OETcLzwcYiyeIJK2qgFzLAe0eF26RFVMhoEGAUkqpNSfVJOjSBc4EpJICW1xOjudYDnCIsNHrZmCF9ArQIEAppdSasz8wxZYaD+2ehVXKp77hv7y5jtFYnMkc2wZ3rqCugRoEKKWUWlOMMfQGQgueBYCZmYDLm+qB3HkBm3wezQlQSimlqtGJcJThaJzLFrFp0GAkigAvs++bu0zQzWAkRiJHR8Fqo0GAUkqpNWWxTYLAKg/s8Lg4u9YLkDMvoNPnIWHgTLT6lwQ0CFBKKbWm9AamqHM6OLfOt+D7DkZibPC6aXK77OTA3DMBAAMroFeABgFKKaXWlN6JELsba3Euorf/UCTGRvtDfnONJ+dMQLph0ApIDtQgQCml1JoRSiR4JjS94CZBKYORGBvt1sA9NV6Oh/PNBFR/cqAGAUoppdaMJwNTJAxcuoh8gOlEkvF4go0e60O+2+fhZDhKPDk7AbDZ5aTW6VgRFQIaBCillFozeiemALi0sXbB902VB26wv+n31HiJm7mbBYkIXSukV4AGAUoppdaM3kCI7bVeWtwLaxIEMx/2nRk5ATBPhYDXsyI2EdIgQCml1JpgjGH/IpsEwdyZgO4au0wwx9p/p8+9IrYT1iBAKaXUmnB0OoI/llhUkyCY2UI4VR3Q6XXjFpm3THA4GieaTC5+wGWgQYBSSqk1IZ0P0LTwfACwgoAGp4N6lxMApwhn+Twcm6dM0DATOFQrDQKUUkqtCb2BEI0uBztqF94kCGAoGksvBaR013hylgl22WWE1Z4XoEGAUkqpNaF3wsoHcCyiSRCkegRkBwHeeRID7V4BVZ4XoEGAUkqpVS8YT/BcKLzopECY3SgopcfnYSKeYDwWn3W805cKAnQmQCmllKqoA4EpDCw6KTBhDGeiuWYCrKAgOy+gzumk2eWkv8q7BmoQoJRSatXrnQghwO5FNAkCGI7GSRhy5ASkygRzVwjoTIBSSilVYb2BEOfU+WiwM/sXKrs8MKXb3izoxDwVApoToJRSSlVQ0m4StNilAIBB+8M8Owioczlpd7s4Nk+vAK0OUEoppSroyFSEQDy5qP0CUuabCQDoybOl8Hg8QSiRWPTzLjcNApRSSq1q+ydCAOxZwkzAUCSGW4S2HHsOdNd4OZZ3S+HqnQ3QIEAppdSq9nggRIvLydl2Et9iDEZirPe6cvYY6K7xMBCOzWkR3GmXE1ZzcqAGAUoppVa13okQlzbVIYtsEgR2jwCPJ+dt3T4vSeBU1jf+LrtXQH8VJwdqEKCUUmrVGo/FOTIVYc8S8gHAWg7ILg9M6U5vKTx7SWCj141AVfcK0CBAKaXUqrU/YG0atJR8AGMMA5FYeo0/W888Wwp7HA46PC5dDlBKKaUqoXcihAO4pGHxMwGBeILpZHLemYB1Hhc+h8xTJujRxECllFKqEvYHQpxfX0PdIpsEAQxG5y8PBHCIsNnnnadhkLuqGwZpEKCUUmpVShjD/sDUkpYCAAbD+YMAsPIC5m0YFIlhjFnSGJaLBgFKKaVWpedDYUKJ5JKTAlMzAfMtB4AVBBwPR+d82Hd5PUwlkkzEq7NhkAYBSimlVqXeEjQJAqsyADKCgFgYRo7MOqenxksokWRkzpbCVuVAf5UmB2oQoJRSalV6PBCi3e1Kb/KzWIORGG1uF16H/ZH56Jfhq6+CyGT6nM3zbCTUZQcO1VomqEGAUkqpVWn/xBR7mmqX1CQI7EZBmUsBxx+BeBhGX0wfmq9MsNNuGFStZYIaBCillFp1+qYiHJ2OcHlT/ZIfa1ajIGNg4ID154wg4Cx7JiA7OXCdx41LYEBnApRSSqny2DvkxwHcuL55yY81EInONAoaPw5To9afM/ICapwONnrdc3YTdIqwwevWmQCllFKqHJLGsHfIz6tbGtjoXVo+QCSZxB9LzMwE9NuzAOKE0dnJgd0+z5zWwWBVCJzSmQCllFJq+f1qfJL+SIy3b2xd8mPNqQzo3w9OL/S8ck6FwGa7TDBbp84EKKWUUuWxd8hPvdPBde1NS36sVBCw0WMHAQNPwMYLYd35MPqSlSNg66nxMhiJMZ3I2lLY52EwEiNZhQ2DNAhQSim1aoTiCe4enuA31jVT61z6R9xgKgjwuSGZgIEnoXM3tG2DWAiCg+lzU6WIJ7MrBLxuYsYwEp3dQ6AaaBCglFJq1bhnZIKpRJK3b1j6UgBkBAEeNww/b33wd10K7dutEzKWBNJlgll5AV3e6m0YpEGAUkqpVWPvkJ9un4eXL7FLYMpQJEaNw0Gjy2nlAwB07YY2OwjISA7cXGN92GfnBXSlewVUX3KgBgFKKaVWhf5wlF+MTXLThtYlNwhKGYjE6PS6rcfr3w/eJmg9Gxo2grsWRmZ6BbS7XdQ5HXNmAjpTMwFVWCHgqvQAlFJKqVK4Y2gMA9y0oaVkjzmrUdDAAei8GFLtg9vOnjUTICJ0+zwcy+oV0Op24nOILgcopZRSy8HYvQEub6qj216bL4XBaNRqGRwLw+nDVj5AStv2OWWC3TXeOQ2DRIROr4eBsAYBSimlVMkdCEzx0nSkZAmBYDUdGkrtGzB0EJJxKx8gpX07jJ+wAgRbd42HE+HInHJAq1dA9S0HaBCglFJqxfvukJ8ah3DDuqW3CU4ZjcWJG7tRUDopMGsmAAP+o+lD3TVewknDmaxywC6fpyobBmkQoJRSakULJ5L8+Mw413c00+Byluxx0+WBXreVD9CwERo7Z05o32ZdZ+4maPcKmJsc6GYoEiOWrK6GQRoEKKWUWtF+PhpgIp7g7SVMCITMIMBjzQR07p59QlsqCJjJC0jlI2QnB3b5PBhgKFpdswEaBCillFrR9g752eh1c2VLQ0kfNxUEdJop69t+V1YQ4G2wZgcyygQ3+dw4gOPhuTMBUH1bCmsQoJRSasUajsZ4wB/gbetbcJaoN0DKUCSGU6B95KB1IDsIAGs2IGMmwONw0Ombu6VwZ7phkM4EKKWUUiXx/aExEoaSVgWkDESirPe4cQ7Y2wd3XjL3pHa7TDCjGqDb552/dbDOBCillFKlsXfIz8UNteyo85X8sdONgvoPWF0Ca3LkHLRtg/A4TI2mD/XUzG0Y1OBy0uhy6EyAUkopVQqHglM8EwqXPCEwZTDVI6D/wOzSwExtczcS6q7xMhKLE4onZp3a6fXQX2W9AioSBIjIH4nIYRE5JCLfFhGfiGwRkcdE5IiIfFdEPPa5XvvnF+3bezIe56P28edF5A2VeC1KKaUqY+/QGG4R3rJ++YKAHQk/BAdy5wNARplgZhBgTf2fyLGlcLV1DSx7ECAiXcCHgT3GmF2AE3gH8FngH4wx24Ex4H32Xd4HjBljtgH/YJ+HiJxv328ncB3wFREpXYGoUkqpqhVLGr5/eozXtzfS6i79NjiT8QSTiSS7Jp61Dsw3E9DcDU7P7JkAX6pMMCsvwKczASkuoEZEXEAtMAi8DrjDvv124C32n2+0f8a+/Wqxtoe6EfiOMSZijOkDXgReVqbxK6WUqqAH/AFGY/FlSQiEmfLAs8cOg8MFGy7IfaLDCa1bZzUMSs0EzKkQ8LrxxxJMJ5LLMubFKHsQYIzpBz4HnMD68J8A9gPjxphUn8VTQJf95y7gpH3fuH1+W+bxHPdRSim1in13yE+b28XrWhuX5fFTQcCGkYOw7nxw18x/ctu2WUFAi9tFk8vJsfDchkGZj10NKrEc0IL1LX4L0AnUAdfnODVVb5Gr8NPkOZ7rOd8vIr0i0js8PLzwQSullKoaY7E4940EeOv6ZtyO0vYGSBmMxBCTpOHM0/PnA6S0bwd/HyRm9gvo9nlytg6G6ioTrMRywDVAnzFm2BgTA34AXAE028sDAJuAAfvPp4CzAOzbmwB/5vEc95nFGPM1Y8weY8yejo6OUr8epZRSZfSjM+NEjVm2pQCwygO3TPfjjEzMnw+Q0rYdkjEYP54+lGtL4XSvgCrKC6hEEHACuFxEau21/auBZ4AHgN+yz7kF+LH95zvtn7Fv/09jjLGPv8OuHtgCbAd+XabXoJRSqkK+N+TnvDofu+rzTNEv0WA0xhVTL1g/FAoC2nOVCXo4GY6SyGgitNFbfV0DK5ET8BhWgt8B4KA9hq8Bfw7cKiIvYq35f8O+yzeANvv4rcBH7Mc5DOzFCiB+BnzAGDO7KFMppdSq8uJUmAOBKd6+oRUpcZvgTIORKK8IPQfuWmg/J//JOTYS6qnxEjNm1vq/z+mgze2qqjLB0tdVFMEY8zHgY1mHj5Iju98YEwZumudxPgV8quQDVEopVZX2DvpxCrxtmXoDpFxhEpoAACAASURBVAxGYlwQeA42XgzOAh+Vta1Q05pVJmhN/R+bjrDJ/jNAl9e95pcDlFJKqQVLGMMdp8d4TUsj6+yp9eUyMj3NlonnCycFprRvn1UhsDnVMCjHlsJrejlAKaWUWoxfjk0yEInx9o3LOwsQSxraxl7AnYgUHwS0bZ81E9Dl9eCSuQ2DOr3uNV8doJRSSi3Y3iE/TS4nb2hrWtbnOR2NcXHwOeuHzmJnArZB6AyEJwBwOYRNPg/Hs1sH+zxMJpIE4tWRwqZBgFJKqao3GU/wk+EJblzXjM+5vB9dQ5EYlwSfJeprgZae4u6U3khoZkmgx+ed2zq4ynoFaBCglFKq6t01PM50MrmsvQFSBiLWTEB0w8VQbAVCqkwwKy8gOyegs8rKBDUIUEopVfX2DvnZWuPl0sbaZX+ukclxzgkdw7lpT/F3atkC4pxTJjgWTzARm+kkmGodPFAlFQIaBCillKpqx6cjPDIe4u0bWpa1N0CKDD2FkyS+swo0Ccrk8kBL95yGQcCsvID1HjcOoL9KegVoEKCUUqqq3TE0BsDbyrAUANAw9CQAUqhTYLa22WWCqV4Bme2DXQ5hQxX1CtAgQCmlVNUyxvC9035e2VzPWRlNd5bT+pGDnKnZAPXrFnbHtm0w+hIkra2Cu2u8QO4ywWrpGqhBgFJKqar164kQx6ajZUkITNk6dpiTbRcs/I7t2yA+DYFTADS4nLS6nZzIUSaoOQFKKaVUAXuH/NQ6Hby5Y3l7A6SY0Ahd0wP4Oy5a+J3b5m4k1FMzt0yw0+tmMBLDZGwuVCkaBCillKpK04kkd54Z500dTdS5nGV5zuCJXgAiGy9e+J1zlAl2+zxzthTe5PMQThpGY5VvGKRBgFJKqar0s5EJgokk/62MSwHhk70kERydlyz8zvXrwdMwZyagPxIllpz51p/qFVANyYEaBCillKpKe4f8dHndXNFcX7bnlP79HKntZl3DIvYnELHyAjJ6BWyu8ZAwsz/wO712r4Aq6BqYNwgQkdeKyA9E5LB9uUNEXlOmsSmllFqjhiIxHvIHuWlDK44y9AYAwBjqzzzFEw3nsnGxuxS2bbcqBGzdPqtCIHNJoMuXmgmofIXAvEGAiLwJuA24C3gX8N+Be4DbROSN5RmeUkqpteiOIT9J4KYNy7tj4CwTJ6mZHuXJhnNZ51lkENC+HSZOQnQKgB67YVBmcmCb24VHpCrKBF15bvtT4C3GmKcyjj0pIr3Al7ACAqWUUqqkjDHsHRpjT2MtZ9f6yvfE/fsBONa6C7djkbMPbdusa/9LsOECNnjdeB0yaybAIUKnz10VZYL5lgM2ZAUAABhjngbWL9+QlFJKrWVPT07zwlS4rL0BAOg/QMzhJth+3uIfo312maBDhM0+D8fD2WWCnqpoHZwvCAgt8jallFJq0fYO+vE6hBvXNZf3ifsPcKRhBx01S9ikqHWrdZ25m6DPO6dMsNNbHTMB+ZYDzhaRO3McF2DrMo1HKaXUGhZNJvnhmTHe0N5EkzvfR1SJJRMw+CRPrHs9G7xLaE/sqYPGTXM2Evr1xCTGmPQGSF0+D0PRGAljcJYr8TGHfO/wjXlu+1ypB6KUUkrdPxrAH0uUfylg5AWITvJo3TlsX2xlQEpWmWBPjYdgIok/lqDNY33sdnrdJAycjsToLNOeCLnMGwQYYx7K/FlE3MAuoN8Yc2a5B6aUUmrt2Ts0xjqPi9e0NJT3ifsPAPBkw7lcudQgoG07PPUdMAZE0hsJHQ9HZgUBAAMVDgLylQh+VUR22n9uAp4CvgU8ISLvLNP4lFJKrRGj0Tj7RgO8dX0LrsVm5y9W/37innperN3MxsWWB6a0b4doECZPA9ZyAMzuFbDJ/uCvdNfAfImBVxpjDtt/fg/wgjHmAuBS4M+WfWRKKaXWlB+eGSNmTFnbBKcNHMDffgFGHGz0LXUmwC4TtPMCNqcbBs1UCKRbB1e4QiBfEJAZnlwL/AjAGDO0rCNSSim1Ju0d8nNBfQ3n1deU94njERg6xMm2XQClmQmAdIVArdPBeo+LYxkzAY0uJ3VOR8UrBPIFAeMi8mYRuQR4JfAzABFxAWX+G1JKKbWaPRea5ungdPkTAgGGDkEyxnPNO2lwOpa+Y2HjJnDVzN5NsMY7q1eAiFhlghWeCchXHfC7wBeBDcAfZswAXA38ZLkHppRSau3YOziGS+A315exTXCK3SnwQP25bKQESXoOB7SdPatMcLPPwyPjk7NO6/J6Kp4TkK864AXguhzH7wXuXc5BKaWUWjviScP3T/u5uq2Rdk8ZewOkDByA+vU842hlY6l6E7Rtg6Gn0z/21Hj5/ukxIskkXoc1Cd/pc3N4dLo0z7dI875aEfkSYDIOGWAEeMAY84vlHphSai5jDO8/fJxr2hr5bxsrMG2q1DJ4eCzI6Wi8MksBYM0EdO5mKBZnR6nyEdq2wbN3QTwKLg/dNR4McDIcZZu9H0KX18NwND4rMCi3fM/aC+zPuBwAJoG/E5E/LMPYlFJZng2FuWt4nFufP8EvxoKVHo5SJbF3yE+Ly8k1bY3lf/LwBIy8QKJzt9W4Z6k9AlLat4NJwFgfYM0EALOSAzvtKoTBCm4pnG854PZcx0Xkq8CvgM8v16CUUrntGw0A1h7l/+PQMX566Q621HorPCqlFi8QT/CzkQneubGtMt+GB54EYHz9hSSHYEOpgoC2jI2EOs6h25fqFTCTHNhltyfuD0fTQUK5LfgdN8ZUdgFDqTVs32iACxtq+PZFW3EI3HzwKIF4otLDUmrR7jwzTjhpuGlDBRICIZ0UeKrVLg8s2UyA3SvAbh/c4XFR43DMahiUmgkYqOBMwIKCABFxich7gFPLNB6l1Dz8sTi9EyGubm2ku8bL13f20Dcd4XcPHyNhTOEHUKoK3TM8zpYaD5c0LGHnvqUYOAAtWzjlqAdKOBPga4K6dTBilQmKCN01s7cU7rRnAipZJpivbXBQRAKZF6AfuB6rfFApVUYP+oMkgWvtddNXtjTwNzs28YA/yCdfGqjs4JRahEgyySPjIV7b2pjeXa/s+g9A16XpdfmSzQSAlRcwq1eAZ9ZMQK3TQavbWdEywXw5AWXevUEplc/9owHa3C4ubpz5xvQ7ne08Nxnmn08Oc06tj3d1tlVwhEotzOMTIaaTSV7TWqGPm+AQBPqhazdDkRhuEdpKuX1x2zZ47u70jz0+Lw/7Z28p3On1VLR1cGVqEpRSC5Iwhgf8AV7X1oAj6xvTJ7Z1cVVLA3/+wikezWpGolQ1e9gfxCVwRXN9ZQZg7xyYmglY73XN+fe1JO3bYWoUpvwAbK7xMJ1MMhyNp0/p9Lor2jpYgwClVoADgSn8sUTOEiqXQ/jnnd1s9nl476E+TmRkHytVzR4cC7KnsY76pbbpXayBAyBO2HAhg5FYeo2+ZNpm7yEwUyaYkRfg86ycxEClVGXsGw3gFObdY73Z7eJbF24hYeDmg31MasWAqnKj0TgHg9O8ulJLAWBVBqw7Hzy1DEVipUsKTGnPKBMkY0vh8Mw3/y6vm4l4glCF/s0WFQSIiFNEOkVkc+qy3ANTSs3YNzrBZY11NOVZrzy71sfXdvZwZCrM7z9zXCsGVFX7r7EghvkD22VnjJ0UuBtjDIOR2NJ3D8zWvBkcrnSZ4Fk+D0LWTEBqS+EKzQYUDAJE5EPAaeA+rI2DfgLcnfdOSqmSGYxEOTwZLqqb2lWtDXxyWxc/Hw3wmaODZRidUovz8FiQJpeTixorVBroPwrhcejazUQ8wXQyWdrKAACnG1q2pGcCvA4HnV73rAqBLt9Mw6BKKGYm4A+Ac4wxO40xF9iXC5d7YEopy/2jVnvga9qLa6n63q52bu5s40snzvC9If9yDk2pRTHG8JA/yKta6nFWqjRw4AnrOqM8sNjlgNCvf03/rbdiksnCJ2eVCW6u8XAi4wM/NRNQqbyAYoKAk8DEcg9EKZXbvtEJurxuzrE3HSlERPjU9k1c0VzPHz93kv0ToWUeoVIL89J0hP5IjKsqtRQAVj6AqwY6zmNogT0Cgvf+nMA9PyV67Fjhk9u2WbMOSWvNv6fGO2s5YKPXWiKoVK+AYoKAo8CDIvJREbk1dVnugSmlrGYqD49Nck3bwpqpuB3Cv+zqYaPXzbsP9VVsqlGpXB70W7NbV1U6KXDjReB0LbhRULTvKADhQ4cKn9y+HRJRGD8OQLfPw5lonKmENYvgdgjrPK6KdQ0sJgg4gZUP4AEaMi5KqWX2yPgkU4nkonZXa3W7+NaFW5lOJLnlYB+hhFYMqOrwsD9IT42H7gptmkMiBoNPQ9dugAUvB0T6jgEQPny48MnpMsGXgJkywePTs9sHV6pXQMHWSMaYTwCISIP1o9FuJEqVyf2jAXwO4ZWLnDY9p87HV3f2cPPTR/nwsyf4+s6e0jZDUWqBYknDL8cnedv6Cm0YBHDmWYhPQ9elAAxFY7S5XXiK2MUwGQoRH7SSbqeLCQIyywS3X8tmu0zwRDjKefU1AHT53DwXCi/ihSxdMdUBu0TkCeAQcFhE9ovIzuUfmlJq32iAVzY3UOtcfEuPa9oa+auzO/nJ8ASfOzZUwtEptXD7AyFCiQq2CgarSRBA5yXWj+FYOkGvkIidB+Bav57IM89iCs2w1baBrzldJtjtm9swqMvroT8cxVSgrLeY/1m+BtxqjOk2xnQDfwx8fXmHpZR6aSpM33SUq9uW/p/l757VwTs2tPJ/j53mR6fHSjA6pRbnIX8QB/DKSrUKBisfwNcMrVsBGIpGi14KiNpLAY1vehPJqanCyYEi1myAXSbY6nbS4Jy7pfB00jBWgYZBxQQBdcaYB1I/GGMeBOqWbURKKcCaBQAWlQ+QTUT47DmbeFlTHX/43AmeDEwt+TGVWoyHxoLsbqzN2/hq2fU/YeUD2Etjg5FY8UmBR4+Cw0Hj9dcDC8gLGM3cUtg7OwhIbylc/ryAoqoDROQvRaTHvvwF0LfcA1Nqrbt/NMCOWh+bS5Q85XU4+MauHto9Lt59sC9dFqVUuYzH4jwZmKpsq+DoFJx5Jp0PEE4k8ccSxQcBx/pwd3XhO+9cxOcrMgg4G4KDELGqIrprPBwPZy4HVK5XQDFBwHuBDuAHwA/tP79nOQel1Fo3GU/wyHioJLMAmTo8br51wVYCiQTvPtjHdKKIZidKlcgvxiZJUsFWwQBDT4NJQKdVGXA6usDKgKN9eLZuQVwufOeeu7DkQHs2oNvn5cR0lKSdA9CZ6hpYjUGAMWbMGPNhY8xuY8wlxpg/MMbooqJSy+jhsSAxY0oeBACcX1/DV87r5qngFH/03ImKJCOptenhsSD1TgeXNFZwRbl/v3WdVR5YzEyASSaJHjuGt2cLAL6dOwkXkxyYKhMcSe0m6CFq71cAsM7jwi1SXcsBIvJ5+/ouEbkz+1K+ISq19uwbDdDocnBZ0/L8Z3ldRxMf3bqRH50Z5wvHTy/LcyiV7UG7VbDbUcEy1f4D0LgJGjYAC+sREB8cxITDeLZaCYW+nTsxxSQHtm4FZKZCIN0rwPrQd4iwweuuyExAvsyMf7OvP1eOgSilLMYY7h8NcFVL47L+Z/mhzet4PhTmM31D7Kjz8caO5mV7LqWOTUc4EY7ye2d1VHYg/fuh65L0j6kgIJWcl0/kqJUO591qzwTssqrlw4cP4z377Pnv6PZZOwpmbSl8LBzhCqwqiS6vu7pmAowx++3rh3JdyjdEpdaWQ5PTnI7Gl2UpIJOI8PfnnMUlDbV84JkTHApqxYBaPqlWwa9pXd7f67ym/DDWl04KBBiKxKh1OmgoohdHtM8KAjxbrCDAu3Vr8cmBGRsJdXk9OAVOzCoT9FRXToCIHBSRp+e7lHOQSq0lqdLA15WgP0AhPqeDb16whWa3k1sO9jEc1YoBtTwe9gfZ5HOzpabwN+5lk24StHvmUCTKRo+7qL05In1HcTQ24mxrA5hJDjxUbJngS2AMbofQ5fVktQ52MxSJpZMFyyXfcsCbyzYKpVTavtEAFzfU0uEp8d7m81jvdXP7BVu48cAR3nOwjx9dsh1XJdds1aoTTxr+ayzIjetaFrQRVsn1HwAEOi9OHxpaSI+AvmN4tvTMeg2+nTsZ/+EPMYkE4nTOf+f2bRALQWAAmrroqfFwLGMmoMvnIWYMw9E464scTynkWw44nu9SthEqtYaMROMcCEwt+1JAtgsbavnUjk30Bqb4xXiwrM+tVr8ng1MEE8nK9gcAKwho3w6+pvShwUis+G6BR4/i3bJ11jHfrl3FJQemNxKaSQ7M1Sug3Dt+5lsOCIpIIMclKCKBcg5SqbXiAX8AQ2m6BC7Ub65roc7p4O4zE2V/brW6PegPIsCVLRVsFWyMnRQ4kw+QNIbT0eJmAhKTIeJnzqTzAVJ8O88Hiugc2LbNuk4lB/o8+GMJgnar4NTeBeXOC8g3E9BgjGnMcWkwxlQws0Op1ev+0QAdHhcXNtSU/blrnA6ubWvknpFx4kntHaBK5+GxIBc11NJSyVbBgX4InZmVDzASjRM3xfUISCcFbp0dBKSSA6cPHcr/AI2d4K6baRiUtaVwqmFQubcUzjcT0Ghft+a6LOVJRaRZRO4QkedE5FkReYX9uPeJyBH7usU+V0TkiyLyop2UuDvjcW6xzz8iIrcsZUxKVVo8aXjAH+Tq1saKbfd7w7pm/LEEj4zrjuGqNALxBPsDocruGggZTYJmZgIGo8U3Cor2HQWsD/1MqeTA8OFn8j+AiNU+OLtM0M4LaHE5qXEIA+EqmQkA/sO+3g/02tf7M35eii8APzPGnAtcBDwLfAS43xizHbjf/hngemC7fXk/8E9gBSfAx4CXAy8DPpYKHJRaiXoDISbiCa6uwFJAymtbG6lxOLhreLxiY1Cry6/GJkkYeHUlWwWDlQ/gcMOGXelDQ+lGQUX0COjrA6cTz1lnzbnNt2sX4WeL6BzYvj2dE9CTmgmwcwBEhE6vh/5qmQkwxrzZvt5ijNlqX6cuW+e7XyH2DMOrgW/Yjx81xowDNwK326fdDrzF/vONwLeM5VGgWUQ2Am8A7jPG+O02xvcB1y12XEpV2r7RAC6Bqyr4janW6eDa9kZ+MjyhSwKqJB4cC1LrdLCnqbayA+nfbwUArpkNuQbSjYKKmAk42odn0ybEMzdgKLpzYNt2GD8JsWkaXU5aXM5ZZYJdPnfZNxEqZgMhRORCEfkNEXlr6rKE59wKDAP/KiJPiMi/iEgdsN4YMwhgX6+zz+8CTmbc/5R9bL7jucb/fhHpFZHe4eHhJQxdqeVz/2iAlzfV0+jKU2ZUBm/uaGY0FufRCV0SUEv3sD/IFc31eBxFfdwsj2QSBp6clQ8A1kyAU6DdUzhXIdrXNycpMCWdHFgoL6B9O2DAby0t5NpSuGqqA1JE5DbgNuBtwA32ZSk9BFzAbuCfjDGXACFmpv5zDiHHMZPn+NyDxnzNGLPHGLOno6PCLSuVyuFUOMqzoXBFqgKyXd3WQI1DuOuMLgmopTkxHeHodKTy+QCjRyAanJUPADAYibLe48ZZIAfHJBJEjx1L7xmQLZ0cWGyFQDo5cPaWwp0+N2eicaLJ8u3uWUxodrn9AXqLMeY99uW9S3jOU8ApY8xj9s93YAUFp+1pfuzrMxnnZy7CbAIG8hxXasW53+4SWMl8gJQ6p5Or2xq5Z2SChO4wqJbg4TFrNilfPkDSGCLL/aHXb3cK7Jo9EzBYZKOg2MAAJhrFs6Un5+3icuE777zCyYFZZYI9NV5OhaPppbcurwfDTK5CORQTBDwiIueX6gmNMUPASRE5xz50NfAMcCeQyvC/Bfix/ec7gZvtKoHLgQl7ueBe4PUi0mInBL7ePqbUirNvNMBmn4fttd7CJ5fBmzuaGY7GeWw8VOmhqBXsQX+AjV533t/rzxwd5JrHn1/eLa3794OnHtp3zDo8VGSjoFR5YHZlQCbfzp2FkwO99dDQOTMT4PMQN6STAVO5CeXMCygmCLgdKxB43i7RO1iCvQM+BPw/+3EuBj4NfAa4VkSOANfaPwPcAxwFXgS+Dvw+gDHGD/w18Lh9+aR9TKkVZTqR5BdjQa5pa6xsS9UM17Y14nOIVgmoRUsYwy/GJrmqpSHv7/Wvxic5MhXh0OT08g1m4AB0XgKO2fk2xc4ERI5aa/jzLQdARnKgHTDMq31beiZgs10mmNpIqCvdK6B8QUAxnRtuA34HOAiUZM7GGPMksCfHTVfnONcAH5jncVL5CkqtWI+MTzKdNFWRD5BS53LyutZGfjI8zqe2d1Wsb4FauZ4OTjMeT+StdkkawzOhMGDNhl3QsAwVBPEIDB2El//erMPBeILJRJKNRZQHRvuO4WxqwtUyfxV6ZudA77Zt8z9Y2zY49H0wJl0meCwc4UoaKtI6uJiZgBPGmDuNMX26d4BSpbdvNECNQ7iiuYItVXO4YV0zZ6Jxfj2hSwJq4R7yW3kuV+bJBzg2HWUqYX23vG90mbrRnz4EiWiOpMAFNAo6ejTvLADYyYE1NUUkB26H8ASERtjodeMWSVcI1LmcNLmcZW0dXMxMwHMi8h/AXUA6jdEY84NlG5VSa4Qxhn2jAV7V0oCviP3My+natka8DuHu4XEur7IARVW/h8aCXFBfk7f87rC9BPCG9kZ+PhJgOBor/e6Z8yQFphsFFfF8kWN91F/56rznFN05sH1mIyFnfQebfR6OZfQKuG/PjrLtIArFzQTUYH34v57SlAgqpWxHpiKcCEeraikgpd7l5LWtDdx9ZqLse5yrlS0UT9A7MVWw8dUzk9M4BT64eT0G+M/RZdjBsv8A1HVA0+xOf6ke/YVmAhKBAInhEbxbc/cIyFRUcmBWhcDmGk86J8D62UtNGb8QFHymjLLA95SoRFApZdtXRaWBudzQ0cxQNEavLgmoBfjV+CQxY7iqQKvgw5PTnF3jY09jLRs8bu4bXYYdLAcOWE2CsvJaZloG5w8C0hsHzdMoKFNRyYHNm8HpnbWl8LFwZHmrI/KorvlHpdaY+0cDnFfnY5OvcHJSJVzb3oRHhLuHdXthVbyHxoLUOITLmurynnd4cpqd9T5EhKvbGnjIHyxto5xIEIafn5MPAFZOQIvLWfBbdyQdBBTull+zaydQYFthhxNat8KIVSbY4/MQiCcZjxfYd2CZaBCgVIUE4gkem5is2lkAgEaXk9e0NnD38LguCaiiPeQPcnlzfd48l/FYnP5IjPPrrW2zr21rIphIljYRdeBJwMzJBwArCCiqR8DRPnC58Jy1qeC5nmKTA9u3zeoaCMxqH1xOGgQoVSEP+YPEDVWZD5DphnXNDERiPBGYqvRQ1AowEI5yZCpScCngmUmrNHCnHQRc2VKP1yHcN1LCKoHU9sGdc4OAoSJ7BET7+vCcdRbiLnyuOJ3FJQe2bYexPkjEZsoEM5IDy6mYvQP+QEQa7Y593xCRAyLy+nIMTqnVbN9ogGaXkz2N+adMK+31bY24RbhTGwepIjw0ZiX3FUwKDFmVAakgoM7l5Irm+nSeTEkMHIDmbqhrm3PTYLTIRkF9hcsDM/l27iT8zDP5kwPbt0MyDmPH2WwvBZ4o88ZBKcXMBLzXGBPAqg7oAN7DTDc/pdQiJI3h/tEAr2ltwOWo7kY8TW4XV7U2cPeZ8YolL6mV4yF/kHUeF+fW+fKed3hymja3i3UZJYTXtDXy0nSEl6bCpRlM/4Gc+QDRZJKRaLzgcoCJx4kdP4F3S0/RT+nbtRMzPZ0/ObBtpkywzuWkw+Oq3pkAZnbreyPwr8aYp8i9g59SqkhPB6cZicWrfikg5c0dTfRHYjwR1CUBNb+kMTw8FuTVBVoFw+ykwJTUv4eSzAZMj8HESdh40ZybTkfjGKyte/OJ9fdjYrGikgJTanYWkRzYdrZ1bZcJdvs8VZ0TsF9Efo4VBNwrIg2UqH2wUmvVvtEAArymdWUEAde1N+EW3V5Y5Xdochp/LFFw6+B40vB8KJxOCkzprvGyo9ZXmiDA/oCl49w5NxVbHpjeM6CI8sCUopIDa1uhtm12mWAVzwS8D/gIcJkxZgrwYC0JKKUWad9ogN2NtXm7qVWTZreLK1vquXt4YnFLAsEhCC9TW1hVNR7yW/kA+bYOBnhxOkwkadL5AJmubW/kkfFJgkstmRt5wbpOdejLUGzL4GjfMYB5txDOJZ0ceKiI9sEjMxUCA5FYacsjizRvECAiqfDpYvt6q4jsBroprt2wUiqH4WiMJ4NTK2YpIOXN65o5GY7yVHCBu72NvgRffjnc86fLMzBVNR7yBzm/zse6Ah+uqcqAXbmCgLZG4gYe9C+xe+DIC+D0WImBWQaL7BYY7TuKs7U178ZBufh27SrcObB928xMgM+LAU6Fy7dnQEq+mYBb7eu/z3H53DKPS6lVK9UadaUFAde3N+ESFra9cHgCvv1OCI/DwBPLNzhVcVN2jf+rCywFgJUP4BFhW+3c5ME9jXU0u5xLXxIYOQKtZ4Nz7nfWwUgMn0Nodjlz3HFGpK9vQUsBKb6d5xeXHBgahulxeuxeAZVYEpg3CDDGvN++fm2Oy+vKN0SlVpd9owHWe1w5vwVVsxa3i1c1L6BKIJmA7/9/4H8Jtrzaao4Sr8y6p1p+j45PEjWmYD4AWHsG7Kjz4c5RGeNyCK9tbWDfaGBpDapGXsi5FABWTsAGr7tg8mL0aF9RewZkKyo5ML2R0Et0270CjlegTFCbBSlVRrGk4UF/gKvbGgv+B1SNbljXzPFwlIOTRSwJ3P9JOHIvXP+3sPsWMImZdVq16jw0FsTrEF7eVHjHycOT05xfP38J4bXtTYzG4jy52AZV8Sj4+6B9R86bB4toFJQYHyfh9+PpWXgQkE4OzJcXkFEmuN7jwueQ6poJUEqV3q8nJgkmkituKSDluvYmnAJ3F6oSeOq78MvPw573wWXvg/XWNyNOF+ikgsH/nwAAIABJREFUplash/xBXt5UV7AX/3A0xploPGdSYMprWxtwAPctdknAf9QKOjvOyXmzFQTkLw9M7xmwiJkAcTrxnXde/pmAlh4QJ4wcQUTY7PPO2k2wXDQIUKqM9o0GcIsUzJ6uVm0eF69srueu4TxLAqf2w50fgp4r4frP2nfcBg43nCmQMa1WpNORGM+FwkX9Xme3C86lxe3isqa6xecF5KkMMMZYywGeAkmBR60gwLuInAAoYlthl8cKBNJlgp7qnAkQkfuLOaaUKuz+0SCvaK6jvkBCUjW7YV0zfdNRDudaEggMwnfeBQ3r4abbwWn/R+t0W1OzOhOwKqVaBReTD5D6vcnuEZDtmrZGDk5OpzP5FyQVBLTNDQJGYwmixtDpKxAEHOsDtxv3psIbB+VSVHJg+0yZYE+Nh+PhaNm7cuYrEfSJSCvQLiItItJqX3qAznINUKnV4sR0hBemwlW9a2AxrmtvwgFztxeOTVsBQCQI7/zO3H7t68+HM8+WbZyqfB72B2lzuwp+sIOVFLjR66bVnb/SPLVkdv/oIkoFR45AYxd45+YnDNlBRaGZgMjRPjzdmxHX4iriU8mB04cOzX9S2zYrcTaZpLvGy1QiyUgsvqjnW6x8MwG/C+wHzrWvU5cfA19e/qEptbqkpjZXaj5ASofHzRXN9dyVWSVgDNz1B9aGLW/92kwOQKZ150PgFEyvjK6DXz85zF+/NMB4mf9TXmmMMTw0FuTVLfU4ikh2PTQ5zfl1hYOFc+t8bPK5uW90ouC5c+SpDCi+UVDfopcCYCY5MO+Ogm3bIB6GiZN0+yqzpXC+EsEvGGO2AH9ijNlqjNliXy4yxvxjGceo1KqwbzTAlhoPZ+eojV5pbljXzEvTEZ4L2Ru9/PIL8PR34XV/Aee9Ofed1p1vXa+A2YDJeIJPHx3gyyfOcMVjz/Kv/SPEk7p5Ui7PhsIMR+MFdw0EiCSTvDgVZmeeyoAUEeHatiYe9k8STiygk54x1kxA+/xJgZC/ZbCJxYieOLGgPQOyFZUc2D5TIZAuEyxzXkDBnABjzJdE5AoReZeI3Jy6lGNwSq0WU4kkvxqfXPGzAClv7LCWBO48Mw4v3Av7Pg473wpX/sn8d1qfCgKqPy/g3pEJppOGz+zYxLl1NXz0hVNc0/s8/7XULnarUKpVcDFBwAuhMHFTOB8g5Zq2RqaT1r+dogUHIRrMOxPgANblWQ6InjwF8fiiGgVlKpgcmMpZGHkxvaXwsWqZCUgRkX/D6hD4KuAy+7Jnmcel1Kryy7Eg4aThmramSg+lJDo8bi5vrudg3xNwx/tgwwVw45ch33Rw01ngbVwRQcCPzozT6XVzc2cb37/4bL6xq4epRJKbnnqJdx88St+UNj1KecgfZEetr2DJHcwkBe5qKC4IeGVzPTUOx8JKBdOVAbl7BAxFY3R4XDkbFaVEj9mVAYsoD8yUTg60NyKao36d9W9i9Ag+p4ONXjfHw+X93Som42EPcL7RjcSVWrR9owFqnQ4ub66r9FBK5q0Nhit+/ifEXV5c7/w2eGrz30EE1p1X9RUCY7E4D/qD/I9N7ek17jd1NHN1ayNfOzXM54+f5qr/n703D2/rPs+074N9Iwiu4KKFIrWRkhfJi2TL8W4nTrzHjt04TTKdtmm6TJvubdJ2+qXppDNts7ZJmnRat7ETJ04sx1tqybIky9ZmW7ZsiZJIkZREiSBIEMS+4/f9cQCKlLAcgABIZc59XbwkAgfAoUQS73nf532eA8f4taUt/N5yJ3WX8KbHfImm0uzzBfnljqbiByOvB5o1Eisyre9imLQabmy0sd3j52+FUGawlU0PzGcUFE0UTQ+Ml5EemAvz+vUARI4cwbgqR2dCkmRdgCcTJLQAkcJKfALeB9qqfSIqKr+oCCHY7vFzY4MNo+YXxJojleRje/6AJdFxnrrp61CvcI2qtVfuBCzia4oXJ3wkhOB+59zQGJNWw/9Y7mTvpl4ecDbM6AWePOchtYi/nmpywBcimhbcpDAS+0gwwlqrGW0Jbpm3N9k5E41zPBxV9oDJE2Cog7rcb1tj8QQdCoyCtM3NaO3zG98ZVqxAslgKiwObZ6cJGhdlEdAMHJUk6b8kSfpZ9qPaJ6ai8ovCsVCUs7HEL8woAICXP49hZBffueLP+BepR/njWtfJYUKBseqd2zx5ZtxLt9nI5Xnm1k6jnq/1LuOlq1bTZTLy+8fPcNebJ9hXytz6F4Rd3gB6SeI6BR0uIQRHg5GCJkG5yOpotk0qHAlMHIeW1XlHU9ncgELEh+a3GZBlJla4kDiwaZW8NRMPsdxswBVPEClFCDlPlBQB/xO4H/hb5iYJqqioKOCVzDzztqZL0yXwIt56HPZ/Gzb/JuarP8XxUJQTIYVXaVlx4CIdCYzHErw+HeS+VkfR1vMGu4WfbVzJt/qWM5lIcv+hQX79yAhnFiAEZqHYNRXgmnorVm3xkchYLIE3mSqYGZCLdqOB9TbzzM9RUSYH8o4CQqkUvmRK0XrgfEcBWYqKA5tXyn96TtKVGZOcruH3kJLtgF25Pmpxcioqvwhs9/hZZ1MmnFr0nNoLL/wB9NwKd3yRu1scADyvNF64dXFvCDw3MY2Ai0YB+ZAkiQecDezZ1MsfdrWxbdLHB/b383dDY4QKZcn/AjART/B+MMJNCi2ws6LAUjsBAHc02TngC+Et5tkQC0DgXMH0QCjsEZD0eklNT5eVGZAL8/p1hcWBTdkiYGCWV0DtxIFKtgMCkiT5Mx9RSZJSkiTNM+hZReX/DaYTSQ76Q78Yo4DpM/DUJ8CxDB76v6DV0WbUc229leeKBQplsTSCrW3RFgFbx730WU2ssZZ2tWrRavjDFW3s2dTLXc31fOXUODfsP8bTrqn5xeEuYl7zyuMPJauBcD4zQOl64GzuaLKTBl4ttqJZTBSooAjIvllXYhwAcicAZHFgThoz47TJQZaZa28YpKQTUCeEsGc+TMBHAdUsSEVFATunAqTEpe8SSDwEP/wlSMVlS2Dz+Svle1oc9IeiDCoVbjn7YHzxBQmdjsR40x/mAYVdgFx0mgx8a10Xz21cRatBx2/3n+aetwd42x+q4JkuDnZNBWjQablM4brfkVCEZSZDWdsUV9otNOl1xQOFihQBLgVGQfGZ9MDyjYJmU1QcaLDI67OeAZr1OqxaTU3XBEuWKgshtgK3VuFcVFR+4dju8dOo17LRXmR9bjEjBGz9LLjelzsALXN/wX6kRe5yFI0XztLaJ4u30ourXf5s5vzva3XM+7muqbfy0lWr+draZZyJxvnwWwP89tFT5YXhLEKEEOyaCvCBxjrFSv8jgdJFgVk0ksRtTXXs8PgLOzdOHgeNDhpzv4HPdAIKGAXFhoaRDAb0HZWJyJkRBxbLEMhECj95eTe/ubS1Iq+tBCXjgAdnfTwkSdKXgV/M/paKSgVJC8GOKT+3NNpLWoladOz633D0Wbjj/4NVd1x0d4fJwNV2C8+VogtIxeTM90XEVreXq+wWlincYS+GRpJ4pL2RNzb18j+WtfLcxDTX7zvGV0dcNVV/V4MT4RiueEKxHiCUSjEUiZUsCpzNHU31TCdTvFmoqzJ5AhpWnE+vvICxWAK7ToO1QDciPjyMYflyJAViR6WY1q8jeuxYAXHgKtkrQAg2OWx0mGqnH1LSCbhn1scHgQBwXzVPSkXlF4F3/GGmEqlLOzXw6M9g59/C5Y/C9b+T97B7Wh0cCUYZUuKkN7MhsHhGAidCUY4Eo/MaBeTDptPy5z0d7L52Lbc21fHlYRc3HjjG2Ut4i2DXlNyWv1GhHuB4MIqgPFFglpsa69BJFB4JFNgMgMx6oKHwG2x8aKhio4As5nXFxIGrIB6EgKuir6sEJZqA/zbr49eEEF8SQrhrcXIqKpcy2zx+NMAtCn9RLjpc78Ezn4HOq+GerxW0BP5IKVsCzWsAaVEFCW11e9Eg6xuqxXKzkX9dv4IfXdHDmWicZ8a9VXutarNrKkiP2chShVesR0LlbwZkseu0bK635bcQTiXBczLvZgDAuViCjkLBQfE48dFRDCu6yj7PXBQVB86sCQ5W9HWVoGQcsESSpGckSXJLkjQuSdJPJElSaA+movL/Lq94/Fxdb6WhSG76oiQ0CT/4OJjq4dEnQF+4jbvEZGCj3aJsS8BgkWe27sXRCRBC8Oz4NNc7bDiL7I9Xghsb61hlMfL6JWouFMsE+ijdCgA4EoxSp9XMhOSUyx3Ndo6HopzOtUI3fQrSieKdgEKiwDNnIJXCWOFOwIw48P083/NN59MEa42SccC/AT8DOoBO4LnMbSoqKnkYjyU4HIxcmlsByTj86JMQcssFQB771Qu5p8XBe8EII0p2nJ19i8Yw6L1ghJORmGJvgEqwpaGO/b4QiUswnvhNX4hIOl1SEXA0GKHPZlbm/V+A7M9TzpHAxHH5z5bcEcLJtMAdTxRcD4xVKDPgQorGCts7QWeesQ+uJUqKgBYhxL8JIZKZj38HWqp8XioqlzSvZGaml1wRIAS89Edw6nW495vQeZXih2a3BBR1A1r7ZGFgIlLumVaMrePT6KTz518LbnDYCKfSvBsI1+w1K8WuqQA6Ca532BQdn87YBZfjD3AhPRYT3WZj7pFANj0wa75zAe54gjRFPAKGR4DKFwEgJwrmFQdqNJkgocXZCZiUJOkTkiRpMx+fADzVPjEVlUuZd/xhHDotvSWaziw4B78Hb/073PA5uPzhkh66zGzkyjqLMl1Aax8gYOJYWadZKdJC8Kzby82N9pqOba7LvIHu8RYxv1mE7PIGuMpuVbzvfyYaJ5hKz0sPMJs7muy8MR282JFxcgBsTjDn1nUo8ggYGkLX2orWpqzAKYXi4sCe8z4HNURJEfArwMcAFzAGPJS5TUVFJQ8D4SirLKZ5tz9ryslX4aU/gdUfglv/oqynuLulnncDkeK2p05ZKLXQI4E3fSHOxhI8UAFvgFJoMujos5ouOV3AVCLJ4UCkRD2A3O2Zz3rgbG5vshNLC/Z4L/i3mzxRUA8wFlfgFljBzIALmREH5tMFNK+SdQ3J2hkFgbLtgNNCiHuFEC1CiFYhxP1CiFO1ODkVlUuVgVCMVdbK7JvXBHe/rANoXg0Pfhc05e1I39Oa3RLwFT6wYQVojQtuH/yMexqTRuKDzbW3dd7SYOOgL0Qsfel4BrzmDSBAsT8AyEWABlhrrUwnYJPDik2rmZsqKESmCMi/GTBWpBMghCA2PFyxzIALOe8cWEAcKNIwNVyV18+Hku2AFZIk/aMkST9Vo4RVVIrjTSSZTCRZZblERgGBcXjiYdCb4bEfg6l8HcNys5HL68zF3QO1OlnAtYBFQDIteM49zR1N9djKsLKdL1scdUTTgrf9l44uYNdUgHqdlivqlDtgHglG6LYYsWhLNqjNiUGj4ebGOrZ7/IhsLkNoQo6obs4tCgS5CDBIEk15xj4pj4e031+xzIALKSoObD4fJFRLlPyvbAVGgG+gRgmrqBRlIBOru9JyCXQC4iH4wSMQ9sDHnwLH0nk/5T0tDg4FwsUjdZ3rFnQc8Pp0UI4AdtZ2FJBls8OKBLx+YVt7kZK1Cr6hwYZOo3zMdSQYrYgocDa3N9lxZVIMgfOiwAKdAFcsgdOoR5NnRDeTGbCisuuBs5kRByZzpCFm1wRrrAtQUgREhRBfF0K8qkYJq6gUZyDjmrd6sYsC0yn4ya/C2LtyJkDHhoo8bTZe+IVi3YDWPgi6IDxVkdctla1uLzathtsaF2aDw6HXcVmdmdenLw1x4MlIjLOxBDeWMArwJ1OcicZZV6FRQJbbmuxIcH5LYKYIyK8JOBeLF1kPzBYB1ekEwHlxYCyXONBkl4WNNTYMUlIEfE2SpL+SJOk6SZI2Zj+qfmYqKpcoA+EoJo3Ekhr6f5fFf30ejr8IH/oyrLmrYk+7wmJkvc1cPEugNWMfvAAjgVg6zQsT09zVUo+pQm3qctjisPGWL3xJZAnsysT43lyiPwAUFgW+cHiMv36uNOOoFoOeDXbLeb+AyQHQW+R9+zy4YoU9AuLDw0hGI/qO9pLOpRRM69cD5E8UbFq1KIuAy4BfA77M+VHA31fzpFRULmUGQjF6LMbFHRq0/zuw/1uw6bOw6TMVf/p7Why85Q8X9sefyRCofRGwcyqAP5nmgdbaGQTlYktDHXEheNO3+KOGd3sDLDcZWF5CwFJ2M2B9gbjhp948w7+9PoI3VFqWwu1Ndg75w0zEE3InoGmlvG+fAyFEUbfA2PCQLN7L8xyVwNDVVVgc2LxyUY4DHgC6hRA3CSFuyXyoUcIqKnnIrgcuWo6/BD//U1jzEfjgl6ryEne3ymr7Fwp1A+raweRYEPvgZ8a9NOq1fKCE1nY12FxvRSux6FcFE2nB697SrIJB7gQ06rW0FYjuPTYmX83vHy5tLHRHkx2BbM/NxIm8ToEA08kUkbQoGCEcHx6peGbAhRQVBzatgshUTUdkSoqAd4GFUc6oqFxiRFJpzkTjrFysRcC5Q/D0r0D7FfDR8lcBi9FjMdFnNfGcu8CqoCTJI4EaBwmFUin+a9LP3S0O9CUI3KqBLaO0X+ziwAO+IMFUuqRRAGREgdb8dsGeYAx3QNbQ7BsqzYNuvc1Mm0HP7vFx8J0umhkA0G7KXQSkYzESo6MYqygKzGJa10e0vz+3OLC59uJAJUWAEzgmSdJ/qSuCKiqFORmWI1MXpUfA9Gl48hGwNMMvPQUGa1Vf7p5WBwf9IcZiRUYC7n55z7tGbJv0E0mnuX+BRwFZtjhsHAqECCXzZM0vAl72+DFIUkn+ACkhOB6KFHQK7B+TdQZ1Rl3JRYAkSdzeZOfM2UwRqcAjIF8nIH7qFKTTVRUFZjGvX4+IRnOLA5tqvyaopAj4K+SRwN+irgiqqBRkMLsZsNg6AVEfPPExSEThsR9BnbPqLzmzJVDIOKi1D2J+8J2p+vlk2er20mbQs9lR3SJIKTc01JEUcGAR6wK2T/rZ0mDDWoKfwlA4RiQtCq4HHnPJo4CHr17KMVeAqRJ1AXc02+kIjsifKOgE5NMEzGQGVMkoaDZZ58Cc4kDHctDoF1cnYPZaYGY1MIlsI6yionIBJ8JRNED3YvIISCVkN0DPADzyH9DaW5OXXWU1sdZqKhwoNLMhUJuRgC+RZIcnwH2tjrz74rXmmnoreklizyLVBZwMRzkZiXFHiWFYWVHgugKbAUfH/LTWGfnI5bIi/8Bwad2AGxpsrI2cJi1poLEn73HnihYB8lW5saurpNcvh4LiQK0ObvlzWHFj1c8jiyIZpCRJV0qS9L8lSRoB/gao7RBPReUSYSAUY7nZgLGKCuOSEAKe/xwM7YR7vgbdN9f05e9pcXDAF5q5EruIbEEyXhtx4IuTPuJC1DQ2uBgWrYaN9sWrC8ja895RorXy0WAEnSQXg/noHwuwtt3O5UvqMeu17D1ZWhFg1WrZnDjLOXMH6PO/jiuWoFmvw5Dn5zI+PIyurQ2NtfrdoRlx4Pvv5z7gA78PK2+r+nlkyfubSpKk1ZIk/aUkSf3AN4EzgJTZDvhmzc5QReUSYiAcXVyiwNf+AQ79J9z4R7DhEzV/+btbHQgKbAmYHWBfUjOvgK3j03SZDVxZYGVtIbjeYeNwIIx/EeoCXvb46bWaWFqi78X7wQirLKa8BXEilWbQHaC3vQ69VsPVXQ3sGypdFb8mcoZ+01JOhqN5jxkr4hEQGxrGWINRQBbz+nX5nQNrTKHLlWPAbcA9QogbhBDfABbfd6iKyiIhmRYMhWOLZz3wvadhxxfhsofhls8XPfzY1DE+s+0zRJKRip3CGquJ1RZT4Xjh1t6ajAMm4gle8wa4v7Vh0aU7bmmwkQb2LbKRwHQiyX5fkDvLCFg6GowWFAWenAiSSAn62uUxw3U9TRwfD+AJlpCil07h8I8waFl23jgoB2MF3AKFEHJ6YFftigDTunX5xYE1plAR8FHk+OBXJUn6riRJtwGL6ydHRWURcSYaJy7E4tgMOLUXtn4Wll0P9/2TvI5XhB2nd/DGuTc4PnW8oqdyd2s9+6ZDuPONBJx9MHFc1i5Ukefc06SB+2ocG6yEq+1WjBpp0fkF7JwKkBKUrAfwxJO44omCosD+jD9Ab6YI2NzdBJToF+A7gyYZJdDQMzdV8AJc8fxGQcmJCdLBIIbu6q8HZikoDqwxeYsAIcQzQohHgLXATuBzgFOSpG9JknRnjc5PReWSYSDTjlzwzQDPSfjhL4FjGTz6BOiUFSWD07Jd6cnpkxU9nXtaMiOByTxbAq3rIJ2oul3qs+5p1lpN9FY4zKYSmLQarrZbeWOR6QJe9vhp0uvYYFeeGgjn7YILdQKOjQUwaDWsaJbn8Jd11mMxaEtbFcyo6J0dfezzBQnkGKdEU2mmEqm8nYD4TGZAl/LXnScz4sB8uoAaomQ7ICSEeEIIcTewBHgH+NOqn5mKyiXGicWQHhjywBMPgaSRY4EtjYofmi0Csn9WirVWE71WE984NY4nnmMGmhUHVlEXMBqNs98X4v5F2AXIsqXBxvvBCN7Ews+JQR5v7fD4ua2prmQL7CMKMgOOjvlZ5bShz2Q36LUarulqLK0ImJC7Vuu7riAp5M7FhbjiGY+AfEXAiFwEGGvYCZC0Wkx9BZwDa0hJEmYhxJQQ4juqbbCKysUMhGO0GnTU58krrzqJqNwB8J2FR38Ajcp/qcVTcU77TwMw5KvsnFKSJL7au4zJeJLf6T9F+kJjoJY1IGmrmiHws8ya4mLaCriQLQ4bAti7SEYCB/0hppMp7mwqXQ9wJBTBadDRUsCmt38sMDMKyLK5u4kT40EmleoCJk+ApYkrnEtx6LRs81zcbZoxCjLmFjbGhoaQzGZ0zup7Z8zGvG5xiAMXyR6Tisqlz4JmBqTTsgbgzH548DuwbFNJDx/2DZMSKSw6S8XHAQBX1Fn461Wd7JgK8M3T7rl36oyyU1oVOwFbx71cWWehq4Twm1qzwW7BrNEsmlXBlyd96CWpZKtgkMcBhfQAE4EYk8EYa9vmPvfmbrlztV/plsDkADSvRqeRuLXJziuewEVFphKjIMOKrqoGB+VisYgDF6wIkCRJK0nSIUmSns98vkKSpP2SJA1IkvSUJEmGzO3GzOeDmfu7Zj3Hn2VuPy5J0gcX5itRUZEVxoPhaMGd6Kqy44tw5Kdw+1/DugdKfnh2BHDLslsYD48TjFf+jejTHU3c1+rgy0NjF8++W3urVgScDEc5HIzwgHPxjgIADBoN19ZbF404cLvHz/UOG7YSXAIB4uk0J0KxwnqAjFNg3wWdgPWd9VhL0QVMnpixC76jyY4nkeQdf3jOIediRcYBQ0M1yQy4kBlx4PsLOxJYyE7A7zLXdOjvgK8IIVYBXuC/Z27/74BXCLES+ErmOCRJ6gMeBdYBHwL+WZKk6qShqKgUwR1P4k+mWbUQeoC3Hoc9/whXfRq2/G5ZT3Fy+iQ6ScetS+VJX6VHAiCPBf5+zVK6zEY+e3REjoDN4lwH3hGIVf4NcOv4NBJwb4l6gC+ePMc/Xdi1qDJbGmwcC0WZzKWdqCHD4RgD4Rh3NJe2FQCydXZCiCKZAXIRsPaCIkCv1XDNikb2KikCwlMQnpyxC765sQ4NsO2CVUFXLI5Vq6FOe/HbXToaJXHuXE0yAy7E0NWFplCscI1YkCJAkqQlwEeA72U+l4BbgaczhzwO3J/5+32Zz8ncf1vm+PuAHwohYkKIYWAQuLY2X4GKylwWbDNg8BXZEbDnNvjwPyhaBczFwPQAy+3LWdu4Fqj8hkCWOp2W767vwpdM8VtHT5HKtm6z9sETxyr6ekIItrq9bHZY886EczEWi/Ot025+OFaag9182eKwAfDGAncDsrP1UlcDYbYosHBwkNNupNF68f/J5u4mBt1BJgJFdAGTJ+Q/m+UI4Qa9jmvrrRf5BWSNgnJ5Q8RPnQIhamoUlEXSajEuAnHgQnUCvgr8MZDOfN4ETAshsuXvKNCZ+Xsnslshmft9meNnbs/xmDlIkvTrkiS9KUnSmxMTE5X8OlRUgFmbAbX0CBg/Aj/6FLSshYf/XfYdL5NB7yArG1bSaevEoDFUpROQZZ3NzJdWLWG3N8hXR8blG52ZIqDC9sFHQ1EGwrGSEwOfGpsiDQxFYkRT6aLHV4or6izYtBr2eC9WuSth7969vPDCC/M+j5cn/ayxmlhehobi/WAEo0aip8Bj+8f8F4kCs5z3CyhSgM0UAefTA29vsvNeMDInuXIslqAtX3pgZh6/EJ0AWBziwJoXAZIk3Q24hRBvzb45x6GiyH2FHjP3RiH+RQhxtRDi6paWlpLOV0VFCQPhGDatJu8vm4rjH5NTAY02ORXQVPoVW5ZwIszZ4Fl6HD1oNVpW1K+o+JrghXy8vZGHnA38/YiL16YC4OgCvaXizoFbx73opPOJhkpIC8GTY1OYNRIpcb7LUwt0GolN9bayOwGHDx/m0KFDpFLlm7v6kyn2+YLcWUYXAGRR4BqrCZ0md1cqnkxzciKYtwhY32HHpiRaePIEaI2yH0aG2zPji9ndAFcsQbsp989lbDjjEVCD4KBcmLKxwicXThy4EJ2ALcC9mTCiHyKPAb4KOCRJyl7KLAHOZf4+CiwFyNxfD0zNvj3HY1RUaspgZjOgJna0sSD84BGIeOHjT0H9knk93bBvGIFglUO+oup2dDM0Xd1fSpIk8Xerl7DSYuSzR08xnkjJHQ135ToB8ihgmhsb6mgyKO+SvOYNcjoa57PLWgHoD9WuCABZFzAYjuUPXcpDKpXC7XaTTCbxeMofY7w65SdZhksgyP/mR4KRgnqAQbdsF3zhZkAWnVbDNV0NxcOEJgfkrRLNeSnYGouccZAtAlJCMB5P0J63EzCMrqMdjXlhDKTOOwcu3Eig5kWAEOLPhBBLhBBdyMK+HUKIx4BXgYeufA6RAAAgAElEQVQyh30KeDbz959lPidz/w4hhMjc/mhme2AFsAo4UKMvQ0VlDgOhWO3sgp/5DLjek0cA7VfM++kGpmXXtZWOlQD01PdwLnSOcCJc6GHzxprRB4RSaX7j6Ajp1r6KegW87Q9zJhov2Rvg++c8NOi0/NayVowaacb9rlZsaShPF+DxeGY6AGNjY2W//rZJP416LVfVl56oNx5PMpVIlbUZMJvN3U2cnAjhDhQowGZtBmSRJInbm+zsngoSSaWZjCdJikLrgcMLshmQZTGIAxeTT8CfAL8vSdIg8sz/XzO3/yvQlLn998m4FQohjgA/Ao4CPwd+SwihBhyp1Bx/MoUrnqiNR4BvFI49L6cCrq6Me/fJ6ZMYNAaW1smNtR6HnMs+7BuuyPMXYq3VzJdXL2HvdIhXdUtktXewMrqdZ9xejBqJu0oIv5mMJ/n5pI+H2xqxarWstpg4FqxtJ2C9zUy9TsvrJeoCXC5Xzr+XQkoIXvH4ubXRXrJLIMwSBVoLbwYYdOftgtPhMAn33C2M63oyuoB8fgHJmLxN0rLmorvuaLITSad5Yzo4YxTUkUMUKoQgNjxc08yAC5E0mgUXBy5oESCE2JmxI0YIMSSEuFYIsVII8bAQIpa5PZr5fGXm/qFZj/+SEKJHCLFGCPHSQn0dKv9vM5hpF9ekCBjaKf/Zd1/FnnJgeoBuRzfaTFs1WwSc9FVnQ+BCHmlv5JfaG/l2PKPXqcBIICUEP3NPc3uTnboS9tx/7JoiIQSPdchvQmttJvpDte0EaCWJzY7S/QJcLhdarZa2trayOwFv+kJ4k6myUgNhdmZA/p+F/rEAq502dFoNQghGP/c5hu9/gHTk/L9zX7udOqMu/6qg5ySI9Mx64Gyud9gwazRs9/gLGgUlx8cR4XBNMwNyYV63fkHFgYupE6CicklyIiMcq8k4YGgnWFvOr9RVgJPTJ2dGAQBL65ai0+iqtiaYiy+tWkKqRc4QmD57eN7Pt3c6iDueLGkrQAjBE2MerrFbWZMxfeqzmhmPJ3NnHlSRGxx1jETijEbjxQ/OMD4+TktLC52dnbhcLsSF9swKeNnjRyfBLWW4BILcCVhi0he0zj7m8tPbJo8Cgq++SmjXblJTU/iefXbmGF3GLyCvODDHZkAWk1bDjY02tnl8nMtsCeQyCooPl58ZkA6FiLz3XsmPy4Vp/boFFQeqRYCKyjwZDMcwSBLLTVUuAoSQi4Dum8v2A7iQQDyAK+SaufoH0Gl0dNm7qi4OnI1Fq+F/b9yIR1/PgYE3SaRLfwObzTPjXqxaDbeXIG7b7wsxGI7xWMf50KXezBVtrbsBWV1AKRbCLpeLtrY22tvbiUajTE9Pl/y62yb9XOewldQ9mU0xUaA7EGUyGKe33U46GmX8S3+LcdVKTOvWMfX4fyDS59cxr+tuYmgihNufYxyTSQ+kaeXF9wF3NNUzGk2wyxtAJ0FzDmFobB7rgZPf+hYjjzxK4tz8tegLLQ5UiwAVlXkyEI6ywmLMuxJVMdxHITQhFwEVInu1n90MyNLj6KnZOCDLSquZdEsfzd4T/K+h8oVt8XSaFyZ83NVcjzmHS1w+vn/OQ51Wwz2znAWzs+3+GusC1lpNNOq1vD6tTBcQCAQIhUK0tbXR1tYGlK4LOBWJcSIcLSswCCCSSnMyHCuiB5C/nrXtdXi+968kzp7F+fkv0PjpTxMfHib02mszx2b9AnKOBCZPQP1SMOQWL97WJHcytk36cRr0OfUN8eERNBYLutZWxV9jlsD2VyCdxv/S/KfQCy0OVIsAFZV5MhCK1cYuOKsH6L65Yk+Z9QOY3QkAeUNgNDBKJFnbK+CWpVewLjLCt067eHny4kQ4JeycCjCdTHFfCTbBvkSS5yemecDZgFV7/iq4xaCjUa+teSdAI0lc57DxujeoqK2ffcNva2vD6XQiSVLJuoCs3W45VsEAx0NR0lB4MyBjF7xSBPF897vYP3wX1s2bsH/og+icTqYef3zm2L4OWRewL5c4cPJETj1AlnajgctsZtIU2AwYGsKwYkXJa72xoWHiIyOg0eB7fv7GTJJGg6mvj+j778/7ucpBLQJUVOZBLJ1mJBKrnSiwadW8fQFmMzg9iFlnpsPWMef2bkc3AsGIb6Rir6WI1l6MyQi3a6f5H/2nOVPCTDzLs+5pGnRabiphrv2TcS/RtOATGUFgFkmS6LOaOVrjTgDIFsJnYwlOK/g3GB+XnRedTid6vZ7m5uaSOwEvT/pYZTGWnbR4XhRYeDOgvd5E7Kt/DxoNrX/8xwBIej0Njz1G6I29RI8fB0Crkbh2RSP7L+wEpNMz6YGFyI6C8gUHxUbK2wwIvrqDUVsLL3zs94n29xM7Of+OmWndOqLHjy+IOFAtAlRU5sFQOEYaqp8emIzDyOsV7QJAxi7YsRKNNPdXQU99bTcEZmiV56N/7/CTEoJff3+EeFq5bW84lealSR8faXFgUBgNmxUEXm4zc3md5aL7e20mjoei53MOasSWBrmIUaILcLlc1NfXY86Y3rS3t5fUCQgkU+ydDpW9FQCyXbBVq2G5OX9GQ/9YgJWGJMHtr9D82c+iz4wuABo+9jCS2czU4/8xc9t1PU0MTYYYn60LCJyDRCinKHA22Y5GriIgHQ6TPDdWVmZA4NVXefLah/hmtI0TjcvwV8CmeSHFgWoRoKIyDwbDcshJ1ccBowflX3zdN1f0aQenBy8aBQAsty9HJ+lqKg4EoFUOMHJOD/CVtcs4FAjzxZPKxVfbPX7CqTT3lxAb/E4gwpFgdGYt8EJ6bWYi6TSnIqV3JebDaouRFoOOPQpWBbOiwCxtbW0zOgEl7JwKkBCiLJfALEeDEXqtJjR52uuxZIqTE0GWvLcPw/LlNH76U3Pu1zoc1N9/H/7nniM5OQmc1wXM2RKY2Qwo3Am4ss7C/a2OnBqH+MgIULooMOn1Mnm4nzfs8uNeu/rD+J5/oaxNjNkspDhQLQJUVObBQDiKBPRUexwwtBMkDXTdULGn9Ea9eKKeOeuBWfRaPcvsy2q6JgiAsU72gncf5e5WB7+6pJnvjk7ywoQypfvWcS9Og47rMml8SnjinAezRsMDeZwFe7PiwBrrAiRJYovDxuveQME3mUQigcfjwel0ztzW3t4OKHcOfNnjo0Gn5Wp76S6BIHdTjoYiBZMDB91BkmnB8jP9OL/weTSGizsGjb/8SUQigfcHPwSgt92O3XRBjkB2M6BIEaCRJL69rosP5BgLzWQGlOgWGNy1iz3t64mhoafFyg57D5Ezo/Oe58+IAxdAF6AWASoq82AgFGWJyYClBBV6WQzthI6NYFZ+hVuMrCjwws2ALD2OnqqmCealdZ28CQH8ZU8HV9ZZ+L3+04xECkfL+pMpXpnyc2+rQ7HbXSiZ4hm3l3tbHdjzrMWtsZqQoOb2wSCvCo7Hk5ws8LW73W6EEBd1AkDZhsCMS2CTvewNlzPROP5kuqAe4P1jowCs71uO7QMfyHmMsXsFtptuwvuDH5COxTK6gKa5OQKTJ8BYD7bSVf1Z4kPDIEkYli8rfvAsgjteZUf3ZlY0W/mTD63Fm5Q41N6H//nnyz4XmCUOVDsBKiqXFgPhGCurPQqI+uDsW1UZBcDFmwFZuuu7OR04TTxV2zY4zj75ai8Zw6DR8C/rlqORJH79/ZGCsb4vTfiIpUVJBkHPuqcJpdIXCQJnY9FqWGE2cqzGQUIAWxzFdQGzNwOymM1mHA6Hok7A2/4wU4nUPEcB8r9NoSLg0Eu7MaQSbPyj3y74XI2f/hSpqamZN9bN3Y2MeMKM+TJF2MRxaFk9L6+M+PAw+s5ONCblHbx0LMbgm+9zuH4ZH93Yyc1rWnFY9OzeeCe+F19EzCO5ERZOHKgWASoqZZIWgpPhKKurPQoYeR1EqiqiwDpDHa2W3FdUPY4e0iJdkwyBObT2yV9vpu27zGzk673LOByM8FeDZ/M+bKvby1KTgY32i8V9+fj+mIfVFhNXF3lMr81Uc68AgBVmA+1GfUELYZfLhcFgwOGY2yVqa2tT1Al4edI3L5dAkE2CJKA3j0A2tP8AxzxRekxpLMuW5jwmi2XzZoxr1sjmQULM6AJmcgQUbAYUIzY8XLIeIHzgADuaZVfL+67sxKDTcPfl7ewxdBDwBggfPDivc1oocaBaBKiolMloNE4kLaq/GTC0E/QWWHptRZ92cFreDMi3J91dL89Laz4SyFoiu88nCn6wuZ7PLm3h8XMeto57L3rIZDzJbm+A+1sdive++4MR3vaHeayjsehjeq1mhiMxQvO82iuV87qA/H4B4+PjOJ1ONBdsQ7S3t+PxeIjFCo9Rtnn8bKq3FbT6LcbRUIQVZiPWHCMVkUjg+pu/YbhhCZetL/7GK0kSjZ/6FLETJwjv3Utfu516s17WBUR9EHQV3QwohEiniY+MlLwZ4H9lBzuWXc2mLgdLG+Wi8YENnUTTsLfrKnzzHAmY1q0HqLkuQC0CVFTKZKBWmwFDO2H59aCr3OsIIWaKgHx01XehkTS1Fwc2rwKNHsbnzkf/vLuDa+xW/uD4GU6G516VvzAxTUqQV9yXiyfGPBgkiYecjUWP7bWZEMCJUOE31GqwpcGGJ5HMOY5Ip9MXbQZkyd6W9RDIxelIjGOhKHeWaRCU5UgwQl+e0CDvk0/iOu3Cp7fQu0SZpsV+90fQNjfjefxxNBm/gL1DHpiUR1jz6QQkXS5EJFKSKFAIwVsH+xm1tfDgVec7GRuXNbCs0cLOdbcQ+K+XScfLH50ZupajsVprrgtQiwAVlTIZyKYHVrMT4DsLk8crPgqYiEzgj/sLFgFGrZGldUtr3wnQ6uVf8rM6AQB6jcS31y3HqJH4tfdHiMzSBzwz7mWVxZi3HX0h0VSap11ePtxST1MOX/kLOW8fvADiwMymQ66RwPT0NPF4PGcRoGRD4OWsS2CZVsEAwWSKkUg8px4gOTHBxDe+ybktcux1b7uyYkNjMNDwS48S2rWb2NAQm7ubOOUJc+6Uss2AQsSGspsByjsB0aNHedm6AqMkuOuy9pnbJUni/g2dvCU14E5Ic2yPS0XSaDD11j5WWC0CVFTKZCAcpVGvpXEebdSiDO+S/+y+uaJPmxUFFioCQDYNqnknAKC1F9z9F93caTLwjd7lHA1F+cKArDY/F42z3xfiAWeD4lHACxPTTCdTBQWBs1luNmDWaGq+JgiyJmKpycAbOcSBuUSBWerq6rBYLAV1Adsn/ay0GOmeRzerP5RfFOj+h38kHYvhukOOvs6mByqh4dFHkQwGpv7jP7huRhcwIXeJGrrKPt/z6YHKiwDvK6+yq3MDt69pxm6aaz70wIZOBLB79ZYKjATW1TxWWC0CVFTKZCAcq74ocGgnWJpnnPQqxaA3UwQ0FCkCHD2c9p8mkUpU9PWL4uwD3xl5BnwBtzXZ+d3lTp4Ym+LHril+5p5GQElbAd8f87DcZOB6hX4CGklirdW0IPbBIHcD9k4HSV+gCxgfH0eSJFpzhOBIklTQOTCYTPHGdHBeWwEgOwUCF3kEhN8+hG/rVpo+/WkGYzo66k3UW3Jb+OZC19SE/d578G19lpWmJPVmPXvHBDR2y92iMokPD6Gx2dA2Nyt+zCsHB/EbrXx088WFw4pmK1cudfBqz3UEd7xKKqjMoCkXpvXrEbFYRayIlaIWASoqZTIYjlZ3FDATHXwTKLTAVcpJ30kaTY00mgrPw7sd3SRFktOB0xV9/aJki54c3QCAP+pq4zqHlT8+Psq/n5vk8jqz4qvZk+Eoe6dDPNbRlNfdLhe9NhP9oci83eHKYUuDDW8ydZFXgcvloqmpCb0+95tiW1sbbrebZI4ry13eAHEh5jUKANk/oV6npXOWPa9IpXD9zRfROZ00/8Zn6B/zKx4FzKbxk59ERKP4f/w0m1Y0ss/XMC9RIGQ2A7q7FXeNEmNj/BwnjdoUH1jVkvOYBzZ0MigsDBkbCe54pexzm3EOfL92IwG1CFBRKYPJeJKpRKq6osCJYxAcr/goAM5nBhRjJkOg1iOBVnkV60JdQBadRuJbfV1YtRpGIvGSugBPjk2hleCRtuKCwNn02cxMJVK447UPecmnC8gnCszS3t5OOp1mYmLiovtenvRTr9NybX15LoFZsqLA2W+q0z/+MbGj/Tj/5I+JG0ycnAiVVQSYVq/Gev31eL//fTYvreN0qpGztvXzOt/40DDGFV2Kjz+77VX2t/Vxd28z+jymYHdf3o5OI7Fr7Y3zGgkshDhQLQJUVMpgIKNOr2p64Ex08C0VfVolmwFZuuq7kJBqXwQ4loGhDsZzFwEgR8R+Z91yNtdbeUjhVkA8neapsSnubKrHmSddLh9rM12fSugC3nG/Q1ooD0bqMBnoNhvZM0sXEIlE8Pl8c+yCLySfc2BKCLZ7/NzaWFe2S2D2efqD0Tl6gKTXy8RXvopl0ybq7rqLQXeQVFqwtr08H4LGT3+K5MQEl518HYB9ifI7AalgiOT4eEmbAc8fGCap1fHwzX15j2myGblpdQuvLrkS/+t7SU7liD9WgKTRsPS7/0LzZ3+jrMeXg1oEqKiUQXYzYGU1xwFDO6GxBxyFzVVKZSw0RjgZzusUOBuzzkynrbP2aYKSlBEH5i8CQE7a27pxFa0K39BfnvQzmUjmDQuazfGp43M2I7IZAvPVBbzpepNffumX2XZqW0mP29JgY9+07L8P51f/CnUCGhsbMRgMF+kC3vGH8SSS80oNBBiJxIik03P0ABNf/RqpYJC2L3weSZLoH5M3EMrpBABYb7gBQ3c3jT99EgcB9vlL6+DMZiY4SKEoMBUM8WLcwQpNlPWdhf+t7t/QiTut572GLvw//3nZ52jZuBFdS+6xQzVQiwAVlTIYCEcxazRz5qAVJZWAkT3VGQVkMwMalF1R9TgWckPgqKyNqBBPjHnoMOoVueP90e4/4k93/+nM500GHU6Dbt6dgJ1ndgJw0FWaw9wWh41AKs17GV1Aoc2ALBqNBqfTeVEn4GWPH+08XQIBjlxgFxx5/wjTP/oRjZ/4BMZV8vdX/1gAk15DV1N5YwdJo6Hxk58kPnSWqxPH2TdW/vdDfFgu6owK1wOPbd/D0cYu7uttKqohuKPPic2oY9e6m/G/8GLZ51hr1CJARaUMBsMxVlmMJQnLSmL0TYgHq1oEKOkEgCwOHPGPkEzXeBbuXAcRLwSKW98q4Uw0zs6pAI+2NxYNGPLFfAz7humf6uds8LxVcZ/NzLF5dgJ2jcprn2+Nv1XS47KbDK97A4BcBFitVmy2whsO7e3tuFwu0unz44dtkz6urbfimOd669FgBK0EaywmRDrN+Be/iLapiebf/q2ZY/rH/Kxx1qGdx9ih/r570Zp1rHOd4cx0lFFvuKzniQ8Pg0aDfvlyRcf/dO9JJCF4+K6rih5r0mu5a30brzWuxvvOYRJn81tcLybUIkBFpQxOhKq8GTC0E5BgRe60tfkw6B2k1dKK3aCsPbvSsZJkOsmZwJmKn0tBZuyDKyOS+sGYnET3S+3FRwGHJw7TkUjSkkyy4/SOmdvXWk2cCEdnWvKlcsZ/hhH/CG3WNganB5mOKotIBmg16lllMc6IA7N2wcWuUNva2ojH43i9st3ymWico6Eod85zKwBkUeBKiwmTVoNv67NE3n2X1j/8A7R1codBCMExV3mbAbPRmM04LjexZkDuSO0bKm/mHhsaRr9kSc4Y4wtJJxK8FK1jI9N0NivrmDywoZOQ0LC/rQ/fi5dGN0AtAlRUSiSUTHE2lqjuZsDQTujYAGblqnelDE4P5o0PzkV2Q2BoeqEyBHKvCZZCSgh+ODbFzY11LDUVfwN4z32I/+sa5589AV45fX7lq9dmJpYWDBWJNc7H7rO7AfjNK34TgEPuQyU9fktDHft9IaKJJG63u+AoIMuFzoHbJmXvhTvmaRUMcidgnc1Myu/H/Q//gHnDBurvvXfm/nF/DG84Me8iACFoWOZmechNvZSUcwTKID48rHgUsPeVg5wzN3J/r3INwubuJtrrTexad8slMxJQiwAVlRIZzLwBrKzWZkDUD6MHqzIKSKVTDPmGFI8CAFbUy780ay4OtDaBzVlwQ0ApOzx+zsUSPKagCwCgP/YinckUa8MBpkf3MxWVrzz7Mt2fC/f1lbJ7dDdd9i4+3P1h9Bo9b7vfLunxWxw2wqk0u0bHSKVSioqAlpYWNBrNjC5gm8dPt9k47+9fbyLJ2ViCPquJiW98k9TUFG1/8QWkWZ4WWVHg2rb5aQ8IjqPXTtOwaQ2XuY6zd/DilcdiiFSK+MiIYrvgn+w9iTEV5957rlf8GhqNxL1XdnDQ0sn40BliAwMln2etUYsAFZUSqXpmwKk3qhIdDDAaHCWWiilaD8xi0VvosHbMaAlqSmtfRcYBT4x5aNbrFAXlpNMpbjh1iGlTHULS8pFAkF1n5Dn+KqsJrUTOMJ9ihBNhDroOcuOSGzFqjVzWfBlvj5dWBGR1ATvG5SthJUWATqejtbWVsbExQskUr3uDFesCAFzhGsX7xBM4Hn0EU9/cNbp+V6YImG8nYPIEAI2P3s9lrhOc9cU4M1WaLiAxNoaIxRRtBsSSKbaFLNyYcFHfpCz0KMsDGzpJIrF7yQZ8L7xQ0mMXArUIUFEpkcFwDK0kZ71XhaGdoDPD0k0Vf+qsXbDSzYAs3Y7u2o8DQC4CJo5DuvwI3/FYgm0eP4+0N2JQ4Lw4dvQn9MaijFz+IKy8jftDUXac2g6AUaOhx2wqqxOwd2wviXSCG5fcCMBVzqs46jlKOKH8zazJoKPPauJgKI5Wq6WpSVlno62tjbGxMXZNZV0C518EHAlGQAjavv4VtHY7rb/7uxcd0z8WoNNhpt48zy2aTBFg2nQb17bJmwj7SuwGnM8MKO4R8PKu9wnoTNy3tvR1xLVtdnrb7ezsvRH/Cy8uiMNkKahFgIpKiQyEo6wwGxW9oZTF0E5Yfh3oK99pyF7Nd9crN0sBWRcw7BsmNY8347Jw9kEyClPDZT/FU64pUgLFowDNvn/Gq9HguPY3kK54lJZknMTJHYQSsie8bB9ceifgtdHXsOqtbGzdCMBG50aSIsnhycMlPc+WBhsn0NHodKLVahU9pr29nXA4zIsuD3adhk31yjITCnEkGOW+Q/tJvvUWLZ/7HFrHxVfMsl3wPEcBAJMDoLeCvYONj92HPRbktddL6xDFh+QiVsk44CdvDNIQ9XPb3TeUdboPbOigX9/I8FSE6OHS/n9rjVoEqKiUyIlQtHpOgf4xmOivyigA5CKg09aJRW8p6XE9jh7i6ficdbmaMM8NgbQQPHHOw3UOq7JsgclB2kYPsbWhiWVNa2HNh0kaLNwV8LHn7B5AjhU+E40TSCoviIQQvDb6Gtd3XI8+E35zZcuVaCRNWSOBpEZDuGOZ4se0tbUhgB3eALc02tHPY10vy8mJKX7l6f/EtG4djoc+etH90USKoYng/EWBIHcCmleBJGG/5RauDI+x/2ygpKvs2PAwmvp6tI2Fr+69oTh7gnpuD5/CvKSzrNO978pOJGBn1zX4nl/cIwG1CFBRKYFEWjAcibGyWpsBVYoOzlLqZkCWbofcOai5aVDLWkAqe0PgdW+QU9E4n1DYBWDfP5GQNBzt2YJG0oDejGbdR7kjFOG1IdkFrtcmF4Cl6AKOTR3DHXHzgc7zK582g401DWtK9gtYrxUgBGfrFX5NZIKE6hxMpeHOCowCEmnBNU8/id07Rdtf/gVSjo7EwHiQtCjfKXAOEyegZQ0AklbLdb2djOtsDL6hvICKDw1j7OoqulL57L5BkpKW+9eUv5njtJvYsrKZV3uuw/fSS4hUjTtoJaAWASoqJTASiZEUVRQFDu0EcyM4L6v4UydSCUZ8IyVtBmSZCRKq9YaAwQKNK2C8vE7AE2MeHDotH2lRIO4KeRDvPMnzVgvdHZtnbtZc+RgWkUZ/4uckUgl6bVn7YOW6gN2j8mrgB5bM9X24ynkVhycOlxTVHPVM0hz0cVyn/HvQaDTiXrICSQhurUARMHi0nwdeeRHvh+/GfMUVOY+p2GZALAj+0TnpgbfcdxMArz6zI9+jLiKeSQ8sxk/2nmSF7xwbP1jeKCDL/Rs6Oaex8H7aSnj//nk9VzVRiwAVlRIYrGZwUBWjgwFO+U+RFElWNijfDMhiM9hwWpwLJw4skiGQC088yYsTPh5qa8CUJ/1tDm/+K1IyyuP1dVzRMuuNbdlmInVO7pye4oDrAEuMeuq0mpJ0AbvP7mZ903qazXMz7Dc6NxJNRTk6pfzrc7lcdE5PcCSWJpJSHkJ0qtFJZ8hHQzkugQEXfO0KOLkDIQTBL3+ZmMFIw+/9Xt6H9Lv8mPValpdpFzyDJ7OV0rx65qY1XS00SEn2j0VInDtX9ClSgQDJiYmieoChiSDvBTXc4T2OaV3+wCAlfGh9GyadhldXbFrUIwG1CFBRKYGBsOwRUBWjoMkTEBir3ijAJ/8yLWU9cDY9jp7adwJAtg+eGoJEaYr8p8eniAuhTBCYiMKBf+G0cy1DBj3rW2bF1UoS+g2/zKZolIPHn0GSJHptZo4p7ARMRad4b+K9ma2A2WRFgqWMBFwuF6sTEeJC8KYvpOgxZ6NxRnUmloyPEomU4XHw5r+BdwRe+0cC27dje/Mgj9/7MVYu6cj7kP4xP2va5mcXDMiiQJhTBEiSxOaeZg439+D5zyeKPsX5zYDCRcAzb55GI9Lcvbqh6NigGDajjjvXtbF76Qamtr9COlaewVS1UYsAFZUSOBGK0mHUY9MpU2WXRJWig7MMegfRSJoZ859S6a7vZtg3XFIEbkVo7QWRllcFFSKE4PvnPGy0W2ba9wV570cQmmBryxK667svslTWXfkYGsBy7AXSIs1aq4mjoYgiYdqes3sQiJxFQJO5iS57V0niwPHxcTZajRP/HeMAACAASURBVGglZiyEi7HNI7fml0+5LgoTKkoqAW/9O2iNpAf34P7SFxlf1sXAXffkFRgKIegfC1ROFChpoHFuK//6dZ1MmB0ce34b6VDhYihbBBQaB6TTgp8eGOFK9wDdt81vFJDlgQ2d+NFzwLKE4O7dFXnOSqMWASoqJTAQjlZPFDi0ExpWQIOycJNSGZweZFndMoza8s6/x9FDJBnhXLB4+7WitK6T/yxhJHDQF2IgHFMmCBQC9v4TwrmepxNuLm+5/OJjGruZal3DbV43h93v0mcz40+mORcrPsvfPbqbJlMTvU29Oe+/ynkVh9yHFBVX8Xgcj8dDl7OVK+osvO5VWARM+llm1OMIBy+KFS5K/3MQdMHdX8FzvJ6Ea4J/fvS/sbbAmqHLH8UXSVRoPfC4/HOhm/t9e12P/H/7jqWd6Z8+U/ApYkPDoNViWLIk7zFvnvJyNiK4bfw9LJs35z2uFD6wqpkmq4FXezbjX6QjAbUIUFFRiBAikx5YBT1AKgHDr1VtFACysr/cUQCcTx0c8tVYF9DYDVpjSeLAJ8amsGo13NeqQBA4uB0mjuHZ8HG88encRQBguepX6EkkOfLeE/QqtA9OpBO8cfYNblxyo7xtkIONzo34435FjoxutxshBG1tbWxx2DgUCBEqsqoYSqXYMx3gQy0O7HV1pXcCDn4PHMuIN1yPp99GXVecQ0s7WGfL/3OQFQVWphMwMGcUkKWnxUazzcCRVVcz9Z//WVCBHx8exrB0KVKB4KCfvD2KKRXnzp56NMbKFPo6rYZ7ruhgf8saXHv2kQoqK9pqiVoEqKgoZCyWIJRKV2cz4OzbEA9UrQiIpWKcDpwuSxSYJWswVPM1Qa0OWlYrXhP0J1P8zO3lQWcDViVjmze+AXXt7GuU59tzRIGzMF3+KAlJg73/edZala0JvuN+h0AikHMUkOUqpxxTq0QXkH0Db2trY0uDjaSAA0V0AXu8QWJp2SUw6xyomPEjcOp1uOZXGfuffw16A84rpnjE9XP6CoxZ+sfkuOM1890MSKdkYWDzxWutkiSxqbuJw03dxE+fJrhzZ96niQ8PFRQFRhMpXnxnlC1nD9Nyy03zO+cLeHBjJ3E0vNa8hsD27RV97kqgFgEqKgqpqihwJjo4/5vFfMjO8ufTCag31tNibql9EQDySEDhOOCn414iacHHlYwCxg7L3gybPsO7U0ex6Cwz65AXYXYwtnQjN3jHcftO0GnUF+0E7B7djU6j47qO6/Ie02HtwGlxKtIFjI+PYzQacTgcXFNvRS9J7CmiC3h50kedVsMmh5X29nYmJydJJBSuJB78HuhMTA1YCe/bj4gnOPXuMj6546esDeSPQe4f87OkwYzdNE+74OlTkIrn7AQAXNfdxHgM3Ct6mfr3x3MeIwcHnSqYGbC9f5xAQnDbmbew3VzZIuCyznq6W6y82nP9ohwJqEWAiopCBjLrgaur0QkY2gntV4CldK9yJQx4ZYX1fIoAyGQI1HocALJ9cGAMwsVz5J8452GdzcSVdQoEgXv/SbajverTHJ48zGXNl6HV5O8e1F/zGRrSaU4e/Ba9NnPRNcHdo7u5ynkVVn3+NTlJktjo3Mjb428XFRq6XC6cTieSJGHVatloL6wLSAvBNo+fmxvtGDQa2TlQCMbHxwu+DgBRH7z7FGLdg0z807+AJOH42McI+E2k9gom7ryToQcfZOLr3yDy3nuI9HlNg2wXXKFRAOQtAjZ3y4Xe4J0PEz54kOjRiwvFxNmziESiYITwM2+fpTkRYtNSO7oijoKlIkkSD1zZyWH7Eobe6SfpKS8GuVqoRYCKikJOhKLU67Q0l7NnXYhYEEYPVFUPMDg9iE6jY5ldudVsLnrqezg5fbL2oSgz9sGFRwKHA2HeC0Z4rL2p+IqX/xy8/zRs/GUiehMnpk7k1QNkqe97EJ/OQMPxn9NnNTEYjhJP5xb0jQZGGfINcWNn8e7O1c6rcUfcjAZG8x6TTqcZHx+fkxx4vcPG4UAYfx5dwOFABHc8OZOe2N7eDqBMF/DuDyERwjPURjoQoO6O22n/q7/kD//huzTfG6fltjY0JjOT3/42Iw9/jIGbbmLsL/6CiZe3MzwZqpBTYGYjJMc4AKCnxUqzzch7LSvRWCxMPX5xNyCWzQzIsxkwGYyx64SbW4b347j15vmfcw7u3yDbD+9svwL/z39eldcoF7UIUFFRyEA4yiqLUdH+sC+R5IDC9S1OvQHpZNVFgV32LvSa+bVnexw9hJNhxsMKriQryUwRUHgk8P1zHkwaiY86FVi+7v+OvHq4+bMc9RwlKZJFiwC0Os6suI6N0266EqdJCjlVMhdZl8CblhZvL8/4Bbjz6wK8Xi/xeByn0zlz25YGG2lgX57vtZc9PjTArY3yG7LD4cBkMhXXBQgBB7+HaNvI5PefBY2Gti9+kWgqzbFYmuObP0ZzyyG6vvk3rHp9Dx1/92UsV12N/8WXeOMv/460gOZnn8T7wx+SKHUbYTaTJ8DakrdDJkkSm7sb2X/aj/3Bj+J78SUSbvecY+LDI0D+4KDn3j1HMo08Crj11vLPtQBLGy1c09Ug2wgvspGAWgSoqChkMBxTLAr8nf7T3HtokPcCCmJih3aCzgTL8s+N50u5mQEXkhUHKlGyVxR7B5jqC24IhFIpfjru5e4WB/XFujWxILz1b9B7DzR0cXhCTnorWgQAjZt+Cz3QevS7QP4Ngd1nd7Pcvpzl9uIrn92ObuqN9QV1AdkW/uxOwNV2K0aNlNcvYPukn6vrrTQZ5H8PSZJoa2sr3gkY3gWTJ5gY7kFEItjvugtdfT0nwlFSAkJXflLe3T/4PXQNDdTfdx9LvvoVVu99A9/vfR6A5SNHcP3Pv2bwllsZeuBBJr7+dSKHD88ZGxQlz2bAbK7racLljxK492FIJvE++eSc++NDQ2gdDnQNuQvDZw6dZVVymlWNJkUJg+Vy/4ZOTpkaeH/ITXy0xkFcBVCLABUVBUwnkkzEk4rWAw9MB3k5Y87ypZMKroKGXoVlm6sSHQwQToQ5GzxbfDMgnZK3FEbfgnPvgOt9uf0+OSA79nlP0aOR0wdPug9DxAtRP8TDkIzLj6/WmECSMvbB+ccBP3NPE0yl+USHAkHgoe/LM+/rfgeAwxOHWVq3lEZT8XlwR8+djJisrBh6Bb0k5dQFhBNhDo4dnBMYVAiNpGFD6wbeducvAlwuF5Ik0draOnObSavhKruVN3LoAsZicQ4HI9xxQVZAW1sb4+PjpAqF2hz4LildE1MvHQCNBufn5Tf2I5mCp6dthVxAHfpP+f8/g2QwMGRpwWLQcsOzT9H9wvO0/uEfoLFamPz2dxj52CMM3HQT577wBQLbt5MOFymSs+mBBcjqAt6KGrHddivTP3yKdPT8/0mhzIBBd4DDoz5uPb4H2623ztslsBB3X9aBXiOxY+lG/C++WLXXKZUKDzdVVH4xUboZIITgb4fGaDXo+G+dzfzdsIvdUwFubMyzKhUYl1vcl3+s0qc8Q1bNXzQ4aO83YdtfFjykAWhc1snQ6/8Hnv2z3AdpdCBp5T81OjkHQaODq38FbvnzMr6CDK198N7TcqGR45f1E+c8rLIY2VRfxKs+nYJ9/wxLN8HSaxBC8O7Eu1zbfq2y85AkRns+wA1Hfs4tyQH6gxeb5uwf2088HS+4GnghVzuvZueZnUxGJi/KGAC5CGhubkavnzvSuaHBxv8ZduFNJOfkAmyblAvRO5vr5xzf3t5OMpnE4/HMKShm8I3C8Rdxn74eER/Cfs896Brlq+ijwQhmjYYVZiNs+gwc3Qrv/Riu+tTMw49m7YK1GrQ9PRh7emj61V8l6fUSeu01gjt3Evivl/E9/RMkgwHL5k04HnoI+513zj2PkAciU0U7Ad3NVlrqjOwb8nDfpz7Fqe2v4Hv2ZzQ8Iv9MxYaH8yr+f/r2WbQS3HT6Tepu/ZWCrzNf6i16bu1tZWfiWn7z+e/T/Ou/VtXXU4paBKioKGAgc7VXbBywYyrAPl+I/7V6CR9vb+SJsf+fvfMOj6rA4vZ7p5f0Se+FAAm9ha6ADRFRWdHdteuKvayK66qrrg3Xvro2XBsqa1kUAbEgHek1QALpISQz6ZNJJtPnfn/cJCRk0gG/79t5nyfPkNvm3pDMPfec3/mdWp4tquDH0MHIfD1lnOHRwXAydd9tOcDeAFteheTpMOUeSaPg9Zx8FU/+O7XoPxQGeGD8/I7bid6W730sqy2ATf+QRgMPn9+/C4nKhD0N0k0qJKHDqqNWG3sszTyZFtvz01zuKqn17MJnATBZTVTbqhkZ3nMpoJXIiXfhOfIj88qW8ZyusxPg5vLN6BQ6xkeN7/Ux288RuCj5ok7rKysrSUhI6LR8akgALwLbzU3MaTctcW2thUSNisGnBK6t5QSj0eg7CNjzES6rgHl7CchkRC56qG3VkSY7GQEa5IIgla+ihsOu92Hs9SAIiKLIUaOFuaM6zxRQhIYSPG8ewfPmIbpcNO/dS9OGjTSuW0f5ffcj/+gj9JMmntyhJk96DR/SxU9MQhAEJqca2F5Yi+aqWWgyM6lbupSQBVfibWzEU1uL2kcmwOsVWbG/nCxvHeEaOdoxY7p9n9PBFWPi+OlIJTvNIgl5eWgGdx/gnA38QYAfP70gr9mOWiaQoOnaccwrijxfVEGSRsU1MWGoZDL+khLDPbnHWVll5nJfYrWijaANheje34D6SoG5ALVcTVxAXNcb7XgH7Ga48BmI7f7DMM1VxpqiNYgTb+99+tTjgo/mwMp7pWsN70erYvsOgVOCgGUVdSgFgQXRvWjv2v4vyYZ26CUAHKw5CMCoSN8mQb5IT5jOnoBgzjFu554kR4encFEU2XJiC1Nip6CU916IOdQwFK1Cy77KfZ2CgObmZhoaGpgwYUKn/cYE6dDKZPxafzIIaPZ42VLfyLWxnbskwsPDUSgUmEwmRp06BtjtgH2fUFkwGLwNBM27FGVLoCCKIjlNNi5tdWEUBMi6FVbdB8e3Q9IUKhrsWOzuHjsDBKUS/aRJ6CdNIuK+eyn+3ZVUPPwwKd+tOFm7r+m+M6A9k1INrDxYQUltM4Ybb6Di4b9g3boVeZB0Hr5q/TuKa6losHND7kYCZpyLoDjzt8OZQyMJUstZnzieC79f839FEODXBPjx0wsKmh2kadXSE1AXrKwyc6TJzsMp0ahaRgHPjwolU6/hhWJj51ay1tHBKedAN73pAz53cwGpwald978310n98hmX9hgAgFRWaHQ1Um2r7v1JyJWw4CPp9avr+zwREJAGCQFUdRQH2j1evjbVMTs8mHBVDx/kx3fCid0w6c62n3l2dTZquZrBob3/QBYEAeOgGUQ6m5lSv4vcppM16Lz6PCqbK/tUCgBQypSMihjl0znQlyiwFZVMRlawvoM4cGt9I3avyAWG4E7by+VyIiMjfXcI5KzEfqKexpwGEAQi7r23bVWFw4XZ7enoFDhigSTY3LUEgNyKFrvgPjgFynQ64l59BU99PcZHHzvZflqTLwlmgztnP05lUqoU/O0oqiNo9mwUERHUffyJNDMA30HAt/vKCVAITCzYRcDMMzO061TUCjmXjIpjW9xIKtf8dPZbbX3gDwL8+OkF+VZ7t6UAl1fkhWIjmXoNV7R74pcLAo+lxVJic/JZxSkmIbUFYCk/o6UAkKYHpod28zT16z/B0QgzH+vV8Vod9frsHBgcD/PflzQQaxb1bV+QMiZBcVDZsU3wh5oG6t2e3gkCt78JmhAYc03bouzqbIYZhvW5fTJ2/EIaBYGrjV+Taz0Z1LS2Bk6P750osD1jo8aSV5+HxWnpsLy9XbAvpoYGcNRqp8bpBqRSQIBcxuQQ3/qImJgYTCZT55vQ7vepPCS1IAZdfHGHgTutosBh7f8OVHoYc51UYrFUcNQknffQPnoEaDIyiFy0iKYNG6j/vEXdX5MHhnRJU9IDKeF6ooLUbC+qRVCpCL3mGqzbttH488+gVHYaHGRzelhzyMhMWR1quYB+2umZGtgb5o+Nwy4o2CyGYTtw4Ky9b1f4gwA/fnrA5vFy3O7stjPgP8ZaSmxO/poa06n2PysskCkhAbxaUklTe1OXMzw6GKDB0UCVraprUWBjpdQvP2LBySftHkgNGcAMgfTz4ZyHJFX5gWU9b38qkRmdOgQ+r6glUaNiemjXU+0AqcMhd7UkUFRJN0enx0lObU6vWgNPZXTsJDYFhXBJ3QEKzSedDDed2ESmIdOnuK8nxkWOQ0TkQFXHm0NlZSV6vZ6AAN/XODVEWr7N3IQoiqytsTAjLLAtI3Uq0dHR2O12zOZ21r/GbJp2H6C5QgoMwu+6s8M+rUFAp5kBE26RNCB7PybX2EhimI4Add9T66HXXUvAuedS9eKL2I8d61VnQCuSX4CBHUW1iKJIyNVXIWg0NG3cKA0OOkVM+XOOCavTw4ycjeizspB38XM9E4xLDCU+WMP6pPFYvv/tuwT8QYAfPz1QZHMgQpcjhJs9Xl4pMZEVrOd8Q+cnIEEQeDwthhqXm3fL2qXQizZCSBKEnbne5NYbdZd2wVtfk7zZZzzS62MaNAaC1cEUNvRzhsCMv0oCxNUPdHqq75HITKlW7JG870tsDraam/hjTJhv4WV7drwjdSlkLWxbdLTuKC6vq19BgEKmwJQ+C73XTWj+agDq7fVkV2f3uRTQyoiIEShkik4lAZPJ1GUWAGBUoI4AuYyt9Y0carJhcrp8lgJa8eUcKO5cQuWBYBAEAs4/H3Vax8DxSJONJI2KgFOHMoWlQvqFsOcjco0NDO3n0CBBEIhZ/Dyy4CDK//xnvNWlENG9KLA9k1INVDc6KKqxtnkXAD5nBnyzr5zYACVDD28jYNbZKQW0IpMJXD42nv3h6RT/shnR7T6r79/pfH7Td/fj5/8BWjsDupoZ8OGJaiqdbh5LjelSKDc2SM/ciGDeKaui2ukCjxuKN5/5UkB3nQENJ2DPB1Jq3NBD+2A7BEEgLTiNInM/ZwjI5PC7D0ATJOkDHH0Yrxo1TApaaqUA5JvKegTgqp4Egc11kjfAiAUQFNO2uNUkqKvJgT0xaOS1nFDImVzyFV5RZGv5VkREzo3v3xAarULLMMOwDqZBbreb6urqboMAhUxgYnAA28xN/FxjQQDO8xGQthIZGSnpGlp1AbZ6GlauxGlWgCgScecdnfbJabIzrKvJgVkLsTWZB2wXrAgLI+7FF3EWl1C5P6jXmQCQhgkBbC+Uym5hN1wPgDqtYwBc1WhnS341s5X1yBAJPEt6gPZcPiYOryCwQZ+EdcfOs/7+7fEHAX789EBesx0ZkKrtnAkwu9y8ebyK88KCmBjSfUrxr6kx2L1eXiuphIr94LCclSBAr9QTrfdxA9n8kvR6zsN9Pm5qSCoF5oL+C5sCo6RAoK5QUpf39jin2AevrDKTFawntpuuDUByB3Q1w+S7OizOrs4mWh9NpM5Hq1wvmBQ7hTWBwUxpOEpFdSlbTmzBoDGQacjs1/FA0gUcrj2M3S0FnzU1NXg8nm6DAJB0AQXNDr4y1TEuSNetSFKlUhEeHt6WCfDuWkrVfjXIZeinT0eT2fH8rW4PxTZH1+OD02ZxLHASIsKAZwboJ0/GcNl0zIV6LId7HhjVSpJBR3SQhh1FUhCgTk0lceknhN14Q4ftVh6owCvCuTkbUWdkoIzt3M7YE/UuN1vrG/u8XyuDIgMYERvE+qQsLN//tjbC/iDAj58eKGh2kKhVoZF3/nN5+3gVDW4Pj6bF+NizI2k6DdfGGFhaUUN9Xstc8ZTTO7b0VArMBaSFpHXOUNQVSU/G427s1G7XGwaFDMLitFBrH8BEtJTpkhjx8H9hz4e92yd8sGREVJVDntXOUav9ZMtaV7idsHOJpL2IHt5h1cHqg33yBzgVjUJDYcq5yADL3s/YWrGVaXHTkAn9/2gdFzkOt9fNoZpDwMnOgPYzA3wxtUUTcdzu7GQQ5Ivo6GgpE+D1UvfRv/HYFODxEn7H7Z22/aC8BhE4pyvdhUxGbvwCADJkZT2+d09EXJCMJsyJ8ZX3cVVU9Gqf1jkCO4rq2oJTfVZWJ7vgb/aVMzJaT+Tuzf3KAri8ItdnF3PlgUK293Y+iA+uGBtPQVAMh37d38Hh8GzjDwL8+OmBfKvdpyiw0uHi/RM1zI8K7TpNegoPJkejFGRUH/1F6pfX90LRPgAKzYW+9QAb/wEyJUx/sF/HbZ0h0O+SQCvTHoBBF8CPj0hWxT2h1Eili8ocVlWZEYC5ET0EAYf/C00mmHJ3h8XVzdVUWCv6pQdoT1bGfParVYQcXkqjw9JvPUAroyNHIyC06QJMJhNyuRyDofvfleEBWoJb6vWnWgX7IiYmhsbGRhp2fEPNHieCUoFu/Hh0Y8d22K7K4eKfpZVcFB5EVjfZrqPK4eixk3Ds4x7fuyeE+gLiLtKC10v5ood7XTeflGqgpslBYbV0c66t3YzTWXPyHE0WcowW5qgt4PX2a2DQS8VGdlusBMplPJ5/Ak8/s2GXjopFLsB6QwZNmzb36xinA38Q4MdPN3hEkSKbw6co8LXSSlyil4dTuk/TtidSreSeaD3JNQeojD+zbUm1tlrq7HWdg4Cqo5D9pWT0Etj7c29Pa7dBv8WBrchkMH8J6CPh6xvAZu55n8hMqMphVbVUCohWd9PaJ4qw7V/SPmnndViVXTMwPUArFyTNYFVAILHWSka4vEyOHdggqGB1MOmh6W26AJPJRFRUFHJ5914SckHgnNBAUrVqhvZi0FVreSHvk08R3QKiy43h9s5ZgH8UG3F6RZ5M68ZsCsitdjA00I7s8NeSBmMg1OShShtK9FNPYtu7l5p33u3VbpPTWnQBRXXYbGUcOHgTOTkn21G/3VeOQiYwLWcTishINMP6VrbZWGfhzeNVXBtj4OWhCRxpsrPM2L9sWESgmunp4WxIGo959ep+HeN04A8C/PjphuM2Jw6v2MkjoNTm4LOKGq6JMZDsQyvQHbdTgEp0s0SZeUbNQlpFgZ2CgI2LpRa5qff3+9gR2ggClYH9axM8FV2YZCTUcAK+u6tnfUBkJmJ9Ccct9T2XAoo2SOZCk+/qNG8guzobhUxBhqF3rZFdEaQKYltUFg5B4GaPlkBV/9Tx7RkbOZYD1QdweVxUVlb2WApo5ZWhCawYM6hXTo6tQUBZJcg0KjTDh6OfOqXDNocbm1lmrOPmuHBSu5mbIYoiuSYLGSkJ4JFcB/uN19s2PTD40ksJvuwyat55h+Y9e3rcNTFMR0ywpAswmr4FoLZuMzU1G/B4RVYcKOfcdAOKXzcSMGtmnwYGVTlc3J1znMF6DU+nxzEvIoRJwXoWFxkxu/qn8L9ibDxVmmB2HDqOp7H/GoOB4A8C/Pjphvzmls6AU8oBLxabUAoCDyT3/UlaV7IZt1zFB/LBbBqAuKgnfAYBxoPS0JdJdw6oFCEIAqkhqacnCABIyIILnoajq6XhPt0RlYmAyBBrSc+lgG3/goAoqSvgFLKrs8kIy0At71sQ54uIyAls1GmZUlfR1r44EMZFjcPmtrHvxD6am5t7FAW2EqSQE9ldZqQdOp2OAJcdhdeL1+4i/PbbOtwURVHkyYIKQpVy/pzcfRBSbrbRaHczNDVJav/c/YHkHdAfLCfAbWvrDIj6299QJsRTvuhhPObuM0Xt/QIqKr4hJCQLnS6F/ILn2ZpfSaXFwSV6K2JzM4F9KAV4RJE7c0qxejwsGZaMTi5DEASeTY+j3uXh1ZLKfl3qhZnR6BQC66NH0Lj2l34dY6D4gwA/frqhdXpg+3JATpONbyrr+VN8BFG9/MDtQNFGZAmTiNQH8myhEe8ZygYUmAsIVgd3NK3Z8LzkmHeKSr4/pIWkUdQwQE1AeybdCUPnSpMMy3Z1vV1Lh8Al3hPdlwIqc6BwnVT2UHS80bu9bo7UHhmwHqDtlNQqVgbo0TmbIX/tgI83Nkqqy28p3gJ07RQ4EGx7dhFsqibaVIk6fVCn+vhPNRZ+NTfxUHI0IcruzX9yjVIwmxETJPkwNJRB3o/9O7G2wUGSjbM8QE/cK6/irqnB+LcnesyeTU41UNvkpLDKxb6PZFA1j+bmIpZt20qgRsHYnK0IOh26iRO7PU573iitZKu5iecGxzOkXVZweKCOa2MNfFheTZ6PkdI9oVXJmT0ili3xY6he/dsYB531IEAQhARBEDYIgpArCMIRQRDua1keJgjCWkEQ8lteQ1uWC4IgvCEIQoEgCNmCIIxtd6wbWrbPFwThhq7e04+f/pJvtROhUnT4EFxcZCRIIeeuxH60lTVVQeVhZGkzeCQ1hsNNNlZU9aIO3g8K6gsYFNIuNVy2W/pgnnovaHt4gu4FqcGp1NnrqLMPsP7biiDAZW9J9sJf3yiNkvVBniqaZpmacz0nuj/e9rdAoYXxt3RalV+fj81tG1BnQHtqLIf5VRtIvVwJB/8z4ONF6iJJCEzgQLUkluxtOaC3iKJI5TOPk1R+nEBLI0E33YTQzl3Q6fXy98Jy0nVqro/t2fkw19hiFxwdCEPmSPbOLfME+kxNvvTaboSwdvgwIu+/n8a1azF/+VW3u09q8Qs4VDoKS1UDxbuOow2cwYYCOXOGheHasJ6AqVORqXuXAdphbuKlYhO/iwrlDz78KP6SEoNOLuOJ/PJ+lffmj43HqlCzobQRd01NzzucZn6LTIAbeFAUxQxgEnCXIAiZwCPAOlEU04F1Ld8DXAykt3wtBN4BKWgAngQmAlnAk62Bgx8/p4v85o6dAbvMTayttXB3YmSPT0c+KW5RAafO4PLIEIYHaFlcZMRx6nChASKKYufOgA3Pgj4Csm47Le/RKg4ccIdAe7QhsOATsFbDtwul+vAprKppJE+fzOCmbt63sRIOfSUZIek6f3C3mQT1YXJgV9jcNo5U78Wh6p5DQgAAIABJREFUSWW1XoOY98PAhXFIuoC85jyCQ4LRaHoW+vWFpnXrsB0rI7auiia9HuspY3Q/PFFDsc3JU4PiUMh6rpsfNVlIMujQqxUgV0jWzEUbofpY30+uJk+aE6HvGHyE3XQj+qlTqVy8GEd+fpe7xwaLhGnM5NWOAMCYf5RjlhtxelSMd6/EXVnZ666AWqebO3JKSdaq+cfgeJ8agnCVgoeSo9lY38jaWouPo3TP5DQDETo5G+LHYPmhn9mTAXDWgwBRFI2iKO5r+XcjkAvEAZcBrWqST4DLW/59GbBUlNgBhAiCEANcBKwVRbFOFMV6YC0w+yxeip//zxFFsSUIULd9/1yRkSiVglviI/p30KIN0tS1mNHIWuyEy+xOPj11uNAAqWyupNHVeDIIKN4ifShPewDUp8cnvfXYp7UkABA7Gma/AAW/wNZXO61eWW2mJmQw6upcHzu3sGuJVJufdKfP1dk12Rg0BmL1XRvFHNu+haL9u3s83V3GXTg8DsINF7AyQI/gccGRb3vcryfGRY3Dhg1F5OkdcSu6XFS98DwKnRu5xUluRgamqqq29bVON6+WmpgZFtit62B7co2NZES323bsDSBXwa73+36C1XktfhAdb7iCTEbsC4uRBQRQ/uBDXfbWV9esZUjoMQocEYQnSZbB3+21EB3gIHH3V5It8rk9t3GKosh9R49T63SzZFhSZ7vkdtwUF0G6Ts2TBeV9DujlMoHLxyWyOzqDsjU/92nf08FvqgkQBCEZGAPsBKJEUTSCFCgArbnWOKC9+8SJlmVdLffj57RQ5XRjcXvbOgPW1TWys8HKn5Oj0fkwDuoRUYTCjR1GB58bGsj00ABeLTHR6O6nkMoHrYK9tJA06X3XPwuBsdIT2mkiSheFTqE7feLA9oy/WRLzbXjuZPYEOGa1c8xqJzB2uJQtaPIxzthpleyQh17SpR3yweqDjIwY2aU63Gapp2DpXznw0TN4exC4bT6xGa1Cy5jYC8jVp3BCGwQHv+j9tXbByDCpVNEQ2DDgY7XH/N//4jxhRKYUUERGUDUss8MMgZdLTFg9Xp4c1DsnvWanm5LaU+yCAyJg2HypNGLv49NxN4ODFBERxL6wGEdeHlUvvuRzG6NxOelqM80yLVGzrkAWncLBOpErxw9Ce0iOZ7AOeWjPSeP3yqr5pdbCU4NiGR6o63ZbpUzg6UFxFNucvF/WhxHbLVwxJh63IOfnegXOsoGbLfWF3ywIEAQhAFgO3C+KYne/Jb7+SsVulvt6r4WCIOwRBGFPdXXf/4P8/G/SvjPAK4osLqogWavimph+qurriiTlc+qMtkWCIPBYaix1Lg9vH6/qcte+0qEzoGAdlO2QpvcpT19aWRAE0kLSBu4V4PvgMPd1MAyC/94ipfehzSBocMo4absqHwOIDiwDWz1MvrvzOsBsN1NqKfUtCvS4pRv4v7K4JOoQswJ2Unb4YJenKYoim8s3MzlmMsODAmnWjeMrrRxO7IKagr5edQeUViUat4YKoXeOeb3B02Sl+s03UYe4cTbIMdxyC5FxcW0zBI5Z7SytqOG62HCG6ntngHXM1IgowtCYU1ojJy4EZ1PfAiJbPVirOugBTiVg+nTCbryR+mXLaFy3rsM6u72C+vrtJNslG+kKbTym5KmICFwcpURZJmLNaKCmpnvx5j6LlWeLKpgTHsxNcb2bBjnTEMSFhiBeK62kytG3DpGMmEAGGzRsSBh71icL/iZBgCAISqQA4HNRFL9pWVzZkuan5bX1E/EE0N7XNB6o6GZ5J0RRXCKK4nhRFMdHRPQzjevnf472nQHfVZk50mTn4ZQYlL2okfqkaIP0esro4NFBOi6LDOHdsuo+f3h0RX59PuHacELVIbD+GWla4ZjrTsux25MafBrbBE9FHSDpAxyNsFwaV7uq2szEYD2hcS038FODAK9HajGMGweJk3we1qdJkMcNB7+EtyfCt7dhtdrJZwQhKjuV67q2NM4352Oymjgn/hwy9FqcuvGs1msRBQGyB5YNqKqqItwezrHmftTVu6D2g3/jqatHpvAgDw4iZMECYmJiqKqqwu1281RBOXq5jEV9aH1t7QzIPHVmQNw46WvXkt7PhmgNnLoJAgAiHvgzmsxMjI8+hqtdFsNo+hZRFPEU1BAqONhd1shuRxjRdhPNa6USjTAxkfyCxXi9Dp/HbnC5uf1IKdFqJa8OTfCZLdpftZ+Xdr+Ey9vx7/WpQXE4vVLZsC8IgsD8rGRyDCnk/nx23QN/i+4AAfgAyBVFsX3BbyXQqvC/Afiu3fLrW7oEJgENLeWCn4ALBUEIbREEXtiyzI+f00K+1U6AXEa4UsE/io1k6jVc3pM5TXcUboDgRGn06ik8khKDS5RGEp8OCs2FUing6GowHpBGBSt6GLLTD9JC0qix1dDgOL0p6zaiMmHuq1CyhWMb3uBY66yAgEjQhnUOAo79IGVcJt/dqabcSnZ1NjJBxjDDMCloaLv5LwSFhtJhi/ikYCSqy17BJWgJKf8Zp93m81ibT0gf2NPjp5MRoMWtTMauj+VocLR03AEIPk0mE1HuKKpsVVQ0DTwb4Kqsou6jj9EngK1GTdhNNyHT6YiOjsbr9fJ9QQkb6hr5c1I0hm6GD51KrtFCgFpBfKiPzEHWQqjNl/QoveGU9sCukKlUxL7yMl6Xi4qH/4Lo8SCKIkbjNyhd47FU1zAmWsO6o1UUmV2M9Jyg6OA+VElJpE5/EpvtOGVlH3c6riiKPHisjAqHk/cyk32Kf080nuCTNxaS+uiHfLTtzQ7rUnVqbo2P4EtTHfstzb275hbmjYpFQOQnjwH7sbw+7TsQfotMwFTgOmCWIAgHWr7mAC8AFwiCkA9c0PI9wBqgCCgA3gfuBBBFsQ54Btjd8vV0yzI/fk4L+c12Buk0/MdUR4nNyaNpsT3PrO8Kr0cS56We6/PmlKJTc11sOJ8ZaylsHtgwEa/opbChkPTgNFj/HBjSYcRVAzpmV7R1CJxucWB7Rv8RxlzHquPFCIiSQZAgSGOFK08JArb/Swq0MuZ1ebjs6mwGh6Sjy10Nb2W13fy5+jPE2zazcaeRiMQUEkdnYR80l1RdFcVbfT9fbD6xmYywDCJ1kYSrFESolQSHTOIzlRcajsPxbf2+bJPJRGaQ5InQOkdgIFS/+Qai2wVuOzKdmtA//hGQZggAfH7kGClaFbfE9y793cpRk4Wh0YG+9RWZl4MuvPftgjXHJEFhSFKPm6pTUoh+/HGad+2i9v33abDsw2YrwWFMB0Fg1pg0nG4vSrnAxYNDMTqa0c6YQXj4OYQbZlFc8jYOZ8eWvKUVtayubuCvqbGMC9Z3ek+b28Yj39/DrG1WiqMFZK9+wJGaIx22+XNyFBEqBY/nn+iTB0hsiJaJicGsTxhHw6qzZyP8W3QHbBVFURBFcaQoiqNbvtaIolgriuJ5oiimt7zWtWwviqJ4lyiKaaIojhBFcU+7Y30oiuKglq+Pzva1+Pn/m3yrg1StmldKTEwM1nNe2ADsYCsOgKOh29HBDyRHoZbJeKFoYNmAiqYKbG4baVYLVOfCzEeltq0zQOsgoTNWEmhlzkusjLmYiZYcouwt7myRmVCVe/Jp+8ReOL4dJt3R5fV6PS4OVe5jZGU+fHOrdPO/6lO4bQtkXEpp9gFqykoZN/cKBEEg4Lz7UchEbNs6q9zNdjMHqw92GBiUqdfSrB3Lz1olboUGDvTPM8Dr9VJZWUlmZCaBysABBwH2vDwavvmW4MwArEY1oddehzxISt+HhYUhKBR46mp5Ii0Wlaz3twVRFDlqbOx6fLBSA+NukDI09aU9H7AmH8LSev37GnzF5QRdcgnVb/4L44b3kcm0mHLNxA7O4NzhUrV41tBIBus0eOQyzCnSsvT0R/F6HRQVvtJ2rCNNNp4oKGdWWCB3JHQuG4uiyJPbnmTk93m8NVfGJ+fLqdeLfPHW3W1jnwECFXIeTY1hr6WZbyrre3UdrczPSqYiIJyikQObP9EX/I6Bfvz4oNHtweR0Ue92U+V082hqTJ98xjvRqgfoZnRwhErJHQkRrKo2s89i7fdbtYkCc3+AqOHS09gZIjYgFq1Ce8aDgKNOyFPHcGntZvj6Jqn9LzIDXFbpiRtg+5ugDoaxPrQPXg9kf03RuxNp8joYKargqqXSzT9znjTICNi9+lsCQsMYOlW6sQvRw7FoU4i37aOxpqOo+NeKX/GK3g5BwNAADaViChptGAcikiWLZmff0sIA9fX1uFwuYmNiGRM1hn1V+/p8jPZUvfIKMr0W0WxCUCoIu/GmtnUWj5dqfTCptkZm92IEcXtO1NtodLi7DgJA6vQQZFLHRk900xngC0EQiH7qSRTRUXhe2kSAazrVpSUMmjCJhDAdj83J4MELhxB0LB+F18vxOklqptOlkBB/PRXGr2lsPILV7WHh4RJCFQreyEjymfFbmrOUw7vWUBMCFQaBoaFDWDZTztjNJt5f90KHba+ODmNUoJZnC41Y+9D1M3t4NGqFjB9tA58/0Vv8QYAfPz5o7QzYabZyviGIid2MUO0VRRshaoTUOtUNdyREYlAqeLbQ2O/hQm1BQE0JzHys7QZ3JpAJMlKCU85sOYCTXQFzx82RlPe/PCWVA0AqCdSXQs530lOnut0HqNcDh/4Lb0+Cb/5EtlL6WYy66kvIvKzDz6aqpIjjhw4w5uJ5yBVKCqubKKhqRJ51M+HqZsp+6ngT23xiM2GaMIaHD29blqHXYBdljI2Zxkdyu6SOP/p9n6+3tWUvOjqasZFjKW4optbWPy8J644dWDdtJnRiHJYyDSG/uwxF2EkDpddKKzHpgwhuNPf5dy6n1Snw1M6A9gTHS+2a+5aCy7e2AgC3E+qKe9QDnIo8MBDtY1cgqxep/4/0M0qfID1J33pOKukGLbbNW4kLDKVo3+62ls/k5LtRKkPJy3uGR/JOUGxz8HZmEuE+9BA7jDt4dc8rXJobwA/jZfw+5Xe8d+ESgjUhvH+xnNA3vmKP8aSnhEwQeC49HpPTxRt96PoJ0ih57erR3DKts27oTOEPAvz48UG+VVION3u9PJoaM7CDOZuhbKekB+iBAIWcB5Kj2GZuYkNd/4YLFdTlEe0RCYgdC0Mu7tcx+kJacNoZzwSsqmpgYrCeqFGXSWKz7f+C+hJpZdUR2Pmu9LQ5sWUUbvub//JbQKaABZ+QPewSglRBJAWndHqPvd+vQKnWMPK82ewtrefSN7dy/qubebhkDE5RgTLny7abpNvrZmv5VqbFTUMmnPwYzQyQxHFxYVPZovBgD4jsl42wyWRCEAQiIiIYFyW1Q+6v2t/n44heL5UvvogyNgbP8SMgk2G4/Z629UXNDj48UUNaXBxul4v6+r6lr48aGxGEFrvg7shaKLX/HV7e9Tb1xSB6IGJIn84BoCZsL7bL9ZRX1hIaHEpI9Mm/WduBA3jMZgZNmIyt0ULFUclkSqkMIi31AVY26Pm6sp4HkqOZEto52C9vKmfRpkXMLg/nq1FNJBDGA1P+QpgmjGfOeZ6yCIFDyQI/vHo/VtfJDN74YD1XRoXyblkVpTbfnQi+mDMihkRD974EpxN/EODHjw8ONEop3CsiQ9o+2PvN8e3gcXZqDeyK62INJGlUPFtY0a/hQgXG3Qxy2GHW410q5E8nqSGpVDZX0uRsOiPHP2q1kddsZ15rZ8aFz0LsGPj+IQiKheM7pKfMYfMhMLrl5j+5w82f23+FYZdzsCbbp0lQY10NR3/dxIhZF5Jv9nDjh7uICFRzz6xBbD1uY519BMnyEjZu3IwoimRXZ2NxWjqUAgDSdRpkgEszHI1Sx+7IVKkUZOlby1hlZSXh4eEolUqGGYahlqv7pQuwfP89jpxcwi4YQUOBgpALp6FsN4zo6cJyVDKB64dLT9+tfgG9JddoIdmgR9dTN0HyNIjIgJ3vdd0u2Gox3IdyAIDDUUlt3VY0C+ZTF6AlvOg4jqKTmanG9RsQlEqGXPl75Eol+bu3t62zBs/jY+E2hgl53JvQuRRic9u4f8P9yBxumpsbqAsSWHzR62gV0mfC9Pjp/H7I71mTJSM5p573Vj3RYf/H0mKQCwJ/Lzh9Xg+nG38Q4MePD36plVre/jLQLABIpQC5CpJ6J/ZRyWT8NTWGHKu9z8Iit91Ckb2adG1kr4OOgZIWLHUInBHTINqVAlrHBivUsOBjyS7M0STZCzubIHLoyZu/IJO2abn5I5PR6Gyk0Fzo0yRo/4+rEb0iQeNncd2HOwnSKll26yQevHAIvz4yC2vWnShlXkpWvMyCd7fz6cEfUQgKpsRO6XAcrVxGmk5NgV1kWtw03hcaQfRKcwz6gMlkapscqJQrGRkxss+6AK/DQdVrr6HJzMR1eAuiKGC4/7G29VvrG/mxxsK9iVEMiYtFJpN1cA7sDbktnQE9IgjSNEdTdtcTIlvbAw19CwJMphWAF3ullN2JcXgkW2GnE4Cm9evRTZyINiKcpBGjKdi9HVEUsXm83JZThl6h5A7vi5SXdSz3iKLI37f/nWN1x7imbjAb053cED6XUdEd5yw8OP5BUvSJvD9HTuySNWwp3di2Lkat4r7EKNbUNLCln5m9M40/CPDj5xRKbA7K7C6SNCqStQOfNU/RBkiYCKrOLUddMS8yhJEBWl4o7ttwobId/8QlCKRl/O6sZAHgDA0SaseqqgYmheiJbD82ODQZLn8XHC1mo0odrHtauuYrP4I7tsGwKzrU/A/XHEZEZFR4x6FBTlsz2b/8QMzoLBZ+W4xGIec/t04iLkR62gtQK7hy/gIaZJHM0R3AWN/ET8UbkLtS2HKsCa+345PtUL2WnCYbMxNmst/biDVqmNQl0MusTnNzMxaLpcP44LGRYzlad7RDurkn6j/7DHeFEcOCC6g/aCVo0lBUSVLrnUcUeSK/nHiNkoUJESgUCiIiIvqUCbA63JTWNncvCmzPyKsl4WZX7YI1+dL0wT7MthBFkQrjNwQHj+X4wXyCIiIZ8tTTOHJzqX7lFRxFxThLSgiYJQXEgyZMxlJdRXVpMU8WlJNrtfOvzDQGR2RRUvoudsfJIOjTnE/5vuh7bo9dwCeafaQ1B3DPxU93OgeNQsM/Zr5MY4CctWNkbH/hoQ6+GbclRJCoUfF4QTlub/90PmcSfxDgx88pvNDi9nVheC8/3LrDWgOmQ73SA7RHGi4Uywm7i4/Lezle1NFIwcGlAAwadPZmacUFxKGSqc6ILqC1FHBphA+TpqFzYHCL5kEb1nLz3w7D5/sUQ2ZXZyMgMCJiRIflhzesxWG1srQxCUEQ+PzWiSjVDfzt17/x8eGPpY0EAWfmVUSpLbw2pgC5xoTclsmdn+/jwtc3882+E7g9UrCWGaCh1O5kfPQ0FIKC7ZFJUqumKbtX19xeFNjK2KixeEUvB6oO9OoY7vp6at59D/255+DY8i2iW4bhwSfb1n9hrCPHaufx1Fi0LXMwYmJiMJlMvRYHHjVJT7a9DgLUAdJUx5wV0Ogj49DHzgCAxsZDNDcXEB4yj9JDBxg0YTJB580i9NprqftkKZWLFwMQOFMKAtLGT0QQZKzesJ6lFbXclRjJLEMQ6YMeQRQ9FBZK8wh2Gnfy6t5XmZUwiwO5G7CpYPHMl1HKlT7PI8OQwT3j7mXXUBnaumbe+/LhtnUauYynBsVyzGrnk4qzPyq4J/xBgB8/7TjSZGNFlRmA0T0MDekVxZuk136k5s8JC+Tc0EBeL6nE0ps2ox3vUiDaERDa+vfPBnKZnJTglDNSDuhUCjiVqz6FeW/C/dld3vxbya7JJjU4lUDVyfS11+Nh1+oV1OjjMKmj+ODGkfxw4mMuXXEpKwpW8Nq+1zhWJ9Wqwy66H7coY0+eFGh9ds1NvPGHMShkAg98dZCZr2zk852lDGrJHlW4VUyInsC/vXWIclWvPQMqKyUfhKioqLZloyNGIxfkvdYF1L77Hl6rlfAb/kDd1hIChkehGT4agCa3hxeKjUwI0nNZOwfM6OhorFYrjY29S1vntnYG9KYc0MqEP4HXDXs/6bhcFKVMQB87A4zGb5DJ1NhM0XhcrraugMhFD6EeMgTrli2oMzJQthgi6YKCMQweSsHuHYwL0vFIirRcq00kMfFmTKYVFJrWsmjTIpKCkshyxrM9uJpbXJPIGDq123O5IfMGxoePYen5chKWbWbtsZOGPxeHBzMtJICXik3Uudx9usYzjT8I8OOnHYuLjOhabiSt0wMHRNFGKQUaM7pfuz+WFkO928NbPbUZ2eph25sUGJKID4xvEy6dLdJC0s5IOWBllblzKaA9CiWMvb5tKmNXtIr5TtUD7N64CWttNdmhI1k4p54Htv2B97LfY1biLP576X8JUgXx/M7nEUUReWAE1QGjOaSsJU4Xw6CQVOaNimXNvdN5//rxhOlUPPbtYZ78TFLxH2ywcl7ieRxprsCaMh0OfS35G/SAyWQiICCAgICTaXGdUkdGWEavdAHOsjLqli0jeP4V2L7/EK9TRvi9D7Wtf6O0kmqnm7+nx3YQSLY6B/ZWF3DUZCFQ04VdcFcY0mDQ+bDnQ6klsJVGIzgb+xQEeL0OTJUriQi/gKK9B9AGBhE7NAMAmVpN3CsvI+h0BM0+mRVzer1sjR2EodbEy+GaDnNAkpPuQKkKZ+ehB3F7XTw6/hHeOPEZmSYlC697rcfzkcvkPH/uP1BotHx9jpycxY9TY5Oe/AVB4Jn0OCxuDy8Wnx5r8NOFPwjw46eFneYmfqm1MD5YygCk6QaoB2gbHTy93459IwN1XBEZwpKyKkzdDRfa9iY4LBRoA6TJgf3A6XGyp3J/v/wJ0kLSqLBW0OzquzFOVxy12shvdjAvsuexrz1xvPE4Zoe5QxBQ3Whn9efLaFDpUU7ZxNtHniVCF8GnF3/Ki+e8yJCwIdw39j72Ve1jdZH0VCdOvoU9WhXjbOq2G6hMJnBBZhQr7prKp7dkMShAC24vz20poKQsGYBfwxOguUaa6NgD7UWB7RkbNZZD1Ydwepw+9jpJ9WuvI8jlGP50C7VrdqNP1qI9Z670c7A5eO9ENVdGhTI2qKNGpTXz0FtdQK6xkYzooL6baGUthCYTHF11clkvZwa0p6ZmA253A5ERl1O0bzdp4yciaxcMqgcNIn3jBgx/uqVt2XOFRjbFSCUHa/aeDseTy/Uc8KQQJbfy7KjLeGv9c3i9Hv4+7EGU+t7pFGICYnhi2t/JjxNoUDj594f3tf09ZQRouSEunKXlNeQ2deOXcJY5M16ifvz8P4YoSpO/olQKQhQK4jVK9PLuny57pL5YcrObeu+ADvNIagyrqxt4pcTES0MSOm/QVA073sU57HKONx/kvNQ5vTquRxTJbbKxo8HKdnMTO/P/hWD5mdSwUbw87UnSQ3tfn23tEChuKGZY+LBe79cdK1tKAZf00cXOF9nVHScH1lud3Pn6J0yymtg+rBaLR8tz055jburcDn3/89PnszxvOa/ufZWZCTMpSErAXihjakV+p/cQBIHp6RFMT49gxrYcKsPgnXVGAlMSeammiAu0BmQH/0NzUwTGJ59EtNkR1GoEtRqZSoWgUuFVq6mOiyWqtJSKvzwirVepENQq0vVGnHonv37yIqPUKcha16nUCGppf09dPZY1azDccTvW5Uvw2MBwy/Vt5/hskREZ+PS+0Gg0hIWF9SoI8HpFjhot/G5cfF//K2DQBZKwc9f7MPx30rKalp9nH4IAo3E5alUUVmMATlszgyZ07r5pVHnRiC40yPm5poH3TlRzc0Y6Ecmp5O/ewfhL57dt+3nu5/y75DCLk6PYU/w1+0Un9xYmMeTWP/bp8i5OuZhNpRtY7v2BB5fvY9XUL5g3+g8APJwSzYrKeh7PL+e/o9MG5kJ6mvAHAX78AL/UWtjVYOUfg+P5rKKWdN1pKgXAgFv1krRqro818HFFDQvjIzqXKX59Hdw2SsZdi3vL3i4zAU6vl0ONNrabm9jRYGVXQxMWtyRmixOLECw/o9KPpMBcyJWrFnBdxrXcMfoO9MqeuxpSQyQNQoG54LQEAaIosqrKzOSQgK5LAX3gYPVB9Eo9qcGpVDZauHLZ84yp2o1dqWL6RVdx69jb0Ck7a0BkgozHJj3GH7//I+8cfAeHx4FalHGew4gldytBGdN8vt8EQyCrPR5W3T2VR9fvpcTzNZ/ZRvLHnNWUvbgfeVgMuvHj8DqdiA4nosOB6HBQ53TgFQSCyk7QbDTidZ1cHytzwP0Ktm9ZRvT2rrM1coOBsOtvoPii6WijQHfFXQDsMjexssrMA8lRxGp8T5SMiYmhvLy8wzKv6CW7Opsdxh1cMegKovRRnKi3YXV6ei8K7PBDlcGEW+Hnx8CYDTEjpUyAKlDyeegFDmcNtXWbSEz4EwUbdqJUa0gacbLkJooiS3OW8vre11HJVWQlXMIP4lyGB+h4Ii2W/RMms+2/y7Ca69GHhLLbtJuX97zMzITziEmZxXcbH2Okxcu1N77crxv1Y1P+xl7jbpaeX83vXnge479nEBMQQ6hSwaKUaB7NL2dNTQOXdKV1OYv4gwA///N4RZHFRUaStSp+Hx3GUwXlTA7p2yQ1nxRugKB4qQ46QO5PjuILUx0vFBv5YHg7tztLhfRENeqPFCCliQeFSkFAs8fLPouVHWYrO8xN7LVYsbW0KKXr1FwWGcqkYD2jAxTcv/ZvuALi+Ojid7guO4+y8qUszVnKD8U/sChrERclXdTth2FCYAIKmeK0iQOPWu3kNzu4Ob5rm2Wb28ZXx75ia/lW/jrxr92KIbOrsxluGM53BWt45teX0HoaSayKY9jcOVw88c5uz2V4+HDmp8/ns5zPMGgNTIgYi6K4lNpfXu0yCMjQa/jU7SE8Qsebl13PpSu+5oRGicLuxpEi8O28J3hgQRaBmo4BTv2BA7AYcuVQAAAgAElEQVRiBaNef42IiI7XLooiaSsu5/jVUaS/vFgKHJxOvA4notPR9r0yMZGmlf/BbXETc8MFCAolXlHkbwXlRKuU3JUY2eW1RkdHc+TIEZqsTRxrOsbPJT/zS+kvVNkkTcqPxT/yycWfkGOU0tn9CgJA6hJY/yzsfp9t0xfzgzuVqPTbiK8yE6tWEqdREaVSopD5/p2rNH2HKHqIjrqcX/Y8Q8rocShUUmBjcVp44tcnWHd8HTMSZhCiNvBpUyYOhQNLyTO84BrFuSnjQBQp3LOTiEmjeHDjgyQGJfL3KX9n4eobUXlgQbobkvt3fYGqQF6Y9TI3/XAjubFeLG/dwaKHv0EmyLg+NpylFbU8VVDBrLCgtu6M3wp/EODnf54VVWZyrHbezUyi0unC5hVJ1w9QD+D1QPFmGDr3tPTrR6iU3JkQyUslJvY2WE+OOd38smRGc+7D5BSuQCbI+aJGxe6ifA40NuMSRQRgWICWa2INTAoOYGKIngjVyZvPa3tfo8RSwnsXvEeMLoivx43mKnkghfXnEmddxqJNi1ges5xHJz5Kig+7XQCFTEFyUPJpEweuqu66FNDsaubLY1/y8ZGPqbPXoZarueWnW/jgog98BgLNrmaO1R/DoAnnye2P4nXGcUP9VFDkcs6lf+jV+dw39j5+LP6Rals1d4y6g4rdB4mo3oLosiMoO2eNMlpcJnOb7MwyJJOMgWzHERyOQELG6Via20DVN4f41x/GdAiuTCYTCoUCg8HQ6ZiCIDA2ehw/FP+AEBqCogsxpOjxUPvvD1CHutBfL5kDLa+s52CjjTcyErssc7m9bixqSfF/3VfXUSArQC1XMy1uGhckXYBeqeeBjQ9w7/p7GSH/C4IAQ6L6OehGGwojr2Jr6VGuCSrAq5+AK1ABOScnDcoFiFZJAUGcWklsy2u8RkVt+XaiAifSUO7Gaq5nUJZUCsitzeWBjQ9gspp4aPxDuOumkxsow+40c3eUlUblYNYUr2G5azkL9An8uPYztjS+hdPj5J8z/8myo8vItRby560qgq/1UlD4D0YMf6Nflzguahw3D7uJD4SPuHNVHl9vW8LVU29HIRN4Nj2OKw8U8l5ZFfcn9y77cabwBwF+/qdxer38o8jI8AAt8yJD2vz6B1wOMB4Eu7nb0cF95faECD4qr+HxwwUsH5mC3VZNyL6l7En7HY8X2Ckt3odMHsWScjOjAnUsTIhgUrCerGA9wUrff+pHao/wyZFPuGLQFW3ud6FKBV+OTmPBAZFc1ePckniQH44tYf7K+dw07CZuHXmrz+6DtJC0TrPV+0NXpQCry8p/jv6HpUeWUu+oZ3LMZG4fdTvB6mBu+ekWn4FAVXMVT/z6BF7RS21zI3bT71g8/SrK33mcodNnoQ/pnegwVBPKxJiJrC9bj1f04hl1DZqDT1O3YQlhF3bWfGS0lGxymmyM+PwTxh6uZsUUOZ7420jc+jJ/n6bl8c1GpqQZuGZiUtt+lZWVREZGIuui1XFc1Di+zvuavPo8MgwZPrdpXP0dzmorcX8YjhAYhdXj4fkiI6MCtVwZ1fF63V43u027WVu6lnXH12G1WpnLXIYohnDbtNuYHj+9Qzno+WnPs2jzIvLrdpJsSEar6r9uZt+IW7lB20iS2MiK7X9Eec6DlI+7jQq7i3KHk/J2r/sszXxf3YCzTbR6NwDnrVvFaJmcZxQGbDs3cdi4gUDlKO6bthhzZTAv7yzENdbApWHBPJ45GphKs6uZzeWb2V7+KRyupzy9jMDAUP596N98X7ia6Ye9XD7rQcxJ1RSXvInZfD0hIeP7dY13jb2Hbcc3s/T8Am5+9V8UD7uIlJAUpoUGcklEMP8sreKq6LAuyzNnA393gJ//aZYZ6yi1O/lragwyQaCgZXrggIOAY2uk15Rzut+uD+gVcm4PUbPfKTJhy0F+Xv4oDgTuiVhAgEKOQTQxIWIIx6aP4Ptxg/lbWiwXhAd3GQC4PC6e+PUJwjRhPDThoQ7rwpQKvho1iBSdlg+axvD4zP8wJ2UO7x96n8tXXM764+s7dRGkBadR3lSOzT0w5XNrKeDSlh72JmcT72e/z0XLL+Kf+/5JpiGTTy/+lCUXLmFs1FjSQtL48KIPEUWRm3+8maKGIuxuO0uylzD327lsN0pe8ZbCe3ju/FuIMx3E7XIyfm7fRiybHWbUcjVLDi0hZNb1WFwaxD0f+9w2RKkgVq1k//Zd1Lz9NjPjZ+AVYHNkHCBwjWYb09PDeXpVDkdN0tO3KIpddga00jpMqKtWQVEUqXnrdVRBLgJv+AsAbx+vwuhw8fdBccgEAZfXxa/lv/LktieZ+dVMFq5dyOqi1WRFZ/H8rOcJCAggS5/F7JTZnfQgs1Nms2j8Iox1cgR1Rb8nXeY22bjmBBhEO1/tXkiY20JgRBpD9VpmGYK4LjacR1JjeDMjiW/GDGLn5ExKzh1J9pRhvBuxhft5jb8lhzDq+DGsyelk26rY0SjSGHw5FYG/55FSWGxvwDUuHEWzh9xfSqlulIb46JQ6ZifPJnn8BORegYu84xkcOpiVhSvx4KUwUcVXmQ0QOhu1Opq8/GcQxd67drZHKVfyj/Nfw6VRsnGEyPKXF+L2Sj4BT6TF4kUSJP+W+IMAP/+z1DrdvFpiYlKwnllhUloz3+ogTCnH0NNAlO6wGGH721IpIDCq5+37QPy6FaSWHmN4+X6uqvwZ8+gb2Xz+LD4fEUeT3cjkyIxedzV8ePhD8urzeHzS4wSpOtc+DSoFX48eRLJWzV15ZuYMe4SPZ3+MTqnjvg33cff6uylrLGvbPi0kDRGRkoaSAV3jyiozMuDcIBnvHnyXi5ZfxBv732Bk+Eg+n/M5717wLqMjO/oupIak8uFFHwJwzffXMOebOby5/00mx0whSMzE6zTw9JzpzB8ZxYGfvidlzHgM8Ym9PqcGRwMHqw9yUfJFVDVX8VHBZ5iCJ2FwFuKuzOu0veh0knK8hFyXl7Bbbuacx98kWh/N9zX7IXUGQvYXvLpgJEFaJXd9vo9mpxuLxYLNZus2CIjWRxOrj+3SNKhpw0Ycx6sxTApBSJpEhd3J28eruMSgx9m0j8e3Ps6ML2dw+y+381PJT0yNm8rrM19n89Wbeencl7gw+UJiYmK67RC4Iu0PiC4DJ5w7+fDwh73+GbZSYnNw9cFCVDKBr6OtRDe3DNfpoTNAJgiEK0XC6pdySXggV8tBXltFpSEP2fE/80RELkXTh7EtaygjyxwE5DZwX2w4H2YmU9vg4OaPd2N1SDfg3abdvGH6GI9WxhTr4LZOmNm7PURGpfBW9jtctnIBr1YF8F35UQ4Wf9TpfHobAKUEp7Bo0l/ITpHhLivni18kz4EkrZrbEyJZXlnP7obe20GfbvxBgJ//SdxekduOlNDg9vBMelxbXTa/2T7wLMD6Z6SpgRc+cxrO9CQ1ZaUUbt/MCyobL5Z/gtsrEDR+IWqZjKKGIkTENlFgTxSaC3kv+z1mJ89mVuKsLrcLVyn4enQaCRo112YX41QP4atLv+Kh8Q+xx7SHK767ok013zpDYCDiQFEUWWkqJ92+mmtXzeWtA28xNnIsX1zyBW+f/7bP4T+t2D12InWRNLmaqLPX8fTkZxCqbqDOXUpm2Aium5xMzpYNNDeYGT/3ij6d17aKbXhEDwsGL2Be2jyW5iylacICvCI0/PRyh229zc2U3XU3iQf2cDwugbAHH0ImkzErYRbbK7bjGD4fzMeJ+PwC1sR9wpz6z/jvp29Rd2wbcjzdBgEgZQP2Vu7tdBOyH8vD+NgjKPVugq+5E4fXyQN7V6Cqfpcjh6/nrnV3sf74emYkzODNWW+y6epNvDD9Bc5LPA+N4uTvfExMDDU1Nbhcvn0p8iqlkllWYhyv73udVYWrfG7nC6PDyYIDhbhFkS9HpxE9dCZPxMSzIDaa3c66Hvevrd2Ey1VHTMx8vv9pKSIiheEW3rvgPe4YdQc6hZJNB4zk5dTw3IQU/jokngtTw3nrmjHkGC3ctWwfZZYKHtr0EPFBCQybOINfSzbzac6nzN4vcJ/8Qj696hvWXrmWh8Y/hEoZysoGFddteZ3r11zLF0e/oNJaw6PfHiLr+XUcLm/o8ZwBrhpyNdPDJ/LVOXKa3/uIo1U5ANybGEm0Sslj+Sf6NTH0dODXBPj5n+TZogq2mpv459BERrSzB85vtjMnfABtOxX74cDnMOVeCDu91r3bl3+BUq0ha1IGmrwCdpmTqPr6W+be93Cbb3/rjbg7PF4PT/z6BHqlnkeyHulx+wiVkuVj0pi/v4BrsotYNjKVG4bdwOzk2by852XePvA2qwtX83/YO+vwKM69/X/WN+7uAoEEggV3d1oKRYq7t1CglBYobSlWrBQrUhyKu7sHSCBIAsTd3TZZm98f24bmBGtPz/t7r/NyX9deye7OPvPMzO7MPV+575kNZyIVSf92cWBBeQErw7aSH70HsaCinVs7xgaOxU/ijC47m5KoO2izstBmZaPN/v2RlYW6vJQrTYxZYxGClZE1k+pO4rfnv/FD8DJy4/ti4lHERwHNEPR6Qk8dxc7TG7eA15OJP3A0+igmMhM6enTkWvI1rBRW1LatjauZK1cSr7Ch/BpflztgH3cKdFqQSNHl55M0fgKqx4+pt3g5e0ViokvLqGlqRHv39ux5vocblrZ0aDMbku5hl/2Q6dIkSDoASfAVYkRHTxscEW2rg52f4WFbvcKAqr5DfU7EniChMAFPC08AVI8fkzhmDCJ9KSnd9WxUhXPlt1aUaUsxlZrS0bMDHT060tSp6Wv17/+Ao6MjgiCQkZGBq2tVHYCINAMJWNBuPAtCoph3ax42ShuauTSrsuyfkaPW0i8shjyNloN1fbEVlzDq4lQeKcXYic0YeXEsH/p+yPQG07FUvvo3mJZ+GJHMhvVRNym9dwMjOxN2frwPBxNDxC02q5glZ5/T1s+OfkEvNTXa1XDghw9r8eWRBww4tgCdpJyf2v2EKiqF70U7cFApGXxDjcPxmYZ9YOLIsIBhDAsYRnjqOXbc/ZQnJfEsuPMjcw6moi32w1gOgzbfZffoxtRyebOWhUgk4vt2S/jwQHeONy6mZNE4vJddwkQqZ46PE5OfJfJbei6fOFUtCP1P4z0JeI//cziSkceGpCxGudjS38m64vVstZZcje7vdwYIApydDca20GrG25f/C8hOjCcy+CaNP+iL8u4qUFggNJvCiyPHCGjVjmhdNDKxDHezt4e4dz/bzePsxyxquQgbo3c76djJZRys61tBBPYGetPI0oEfW//IR9U+YuHdhUy5PAVjqTFPs59W+mxYZhg/P/yZxKLEitekGgHzYh3mxToUJVrSlWXEWmnQSEFjFMSkE88JiryEvvg8Ua+wTVBLodBMQqGZBKNiDS0fCgT4OVLj2yVYBzYkMsaLc8XfYum5F41gEAmKexRKbkoS3SZPf2vvd2x+LPNvz0cmlhFgE8CtlFu0dGmJRCzB1siWSfUmsfjeYmIdGuFRcILyR0cQu7QmafRo1PHxuKxcCc1bwv0XPC8xkID6DvWxUFhwKeUGHdosqliXVlXI15uP4Jt9jdqKTJrYWxj65iPPGnT2/4CFG9hWp6O5I+GFxcQ/2YtZzT6E37yI1TfrKTSC+QP1pFsZY5l+D6lZMwRlQy62+Qgr+btHt/4sH/wqEvAsrRBzpRQPa3NWtV3F8LPDmXZ1Glu7bMXfxv+VYxZpdQx8HENSmZo9gT4YaZP45PwU8sryWN56OS1dW/LLo1/YHr6da0nXmNFwBj29e1Y6Tmp1Li/Sr7C7wIH07MN8XOhK808+qSAAOr3AjAOPkEvELO4TWOUY92/oxv74ZUSp4mhvMQtvC2/mqLZQqtTR76wxzsOHIXNxqTL3AOfODPXrSWTiNdYmLSCmRIejxxWKpPfQp33O4M132T2mMQHObyYCNkY2/NB2KZMuTyI9IZddx75n5Eff08fBim0p2SyMSaOnnSVm0n9TpOwv4j0JeI//U3haVMrnzxNpYmHCfN/KP/h/uygw4igk3oEeq0D576vc/Rl3Du5FrlTSyCUfLp+G9t/QoMlwIu6GcnHLOiJ7yfCy8EIqfvNPOqkwiZ8f/kwr11Z09+r+l+bgoJBxqJ6BCHzyOJZ9dXxoYGFCU+emHOp1iO3h21kTtobgtGA23VpJyzIPrgTvJTs2nObFSgaVm2JcUIZRQRnyUg2FRnCisZhz9UWUy6Hxc4HQOtNxKDGmliqO/AAL0iyUlFkoUf3pr8pCiVYprWi9NBEp6Rtphd3G3WQOGEZIUBuu2bSkR7tvuVz0FRodSEQSQk4cwdTGlupNW751W5eHLkcpVaLWqfkh+Afyy/Np5fqyyLO/X38ORR1inSaDhjkyyk78RP6Njehyc3Hb+AsmTZui1OuRigwdAr0drJCKpbR2bc2VpCto9BpkYsMdudTInM+G9GPFqjSeCA2o13c8CqnE4DOQGwtZLyD7BUJWJOqMJ5jE3+AbnRouLoaLi2lWLqaotZRweylzRWZY1vuGaPtOTHyWwjI/t79EAAAsLS1RKpWvrQt4nlZIDSeDXLCp3JR1HdYx5PQQJlycwK5uu3Azq6xqWarTM+RxLBHFKrbW8kJdHMLQ67MwlZmyres2AmwM4lJTG0ylm3c3vrvzHV/f/Jrj0ceZ02RORbTj2NOV/JgmRSItY6rZYFK4il+jl6Y+m2/E8iAxn1X96+JgXnWbf3vxG1GqK/jKPuLobSssjPdxLOU4zaMskOkssBo5/LX7RGIxhYV3AylQa9g4pBHG+VZcCDXlhP06yjMmMmjTXfaMaYK/85t1BVq5taKfZ2/2cwS33w7xqFEv6rg25PtqrnQNjWRFfDrf+FYlIv9JvCcB7/F/BrkaLSOexmMpk7Kplmcl8xAwpAIAfP+OZ4CmDC7MA4daBkObfxBZCXFE3r1F1061kF+Zbyg4bD4VqVhMx7GT2Tf/SyLScmnq9eaLmyAIzL8zH6lYytwmc/+WEpqjQsbBut4Mu/GQOcfOsdhEhEtONprkZDonJxHtoOS0Xymro3/lULbAqGt6WiSLuOHvSKpCTuta7hQ7mnPIIYFjsnDK0dLRuiljao5C39ufdg+i+bS6K+1HDPhrE2sGuj5DODN7Me6Xj7FNcgfHamOIcnUjriiO0WdH0SbBmF4fjEMiffNpLzgtmOvJ15nWYBo5qhx2ROxALBJXCndLxVK+avQVI86N4Fm2KxbBmaCwwn37NoxqG6yK5WIx1YyVPCspq/hce/f2HI85zv30+xUtmQA2RmJMKeNhqTWLTj9nfq8ANCJ4IdLwQMjnoS6VB9pIck1KEBk74KYX0S26nD4RZchdlVg6l9NCnQ95pQhHJhPiOZhAv7EM/FOk610hEolwdHR8pZGQXi/wPL2oUqjd3tie9R3XM/TMUCZcnMCOrjuwVhrWq9brGf00jrsFJayr6U5K+hFWhK7A38af1e1WY29cWbioulV1dnTdwcHIg6wKXUWf430YVXsUJZoSdkQcxUOpYH23g9xesRYbV3esnAwXzMiMIpafj6RzgAMf1HWuMu+Q9BCW3ltKa9fWrGg9l5HlVzmU8D3u2NL7SiFP3SxJT0rAtUZVtcsHiXmM2vYCvWDJ53XXkB76ITExmYhEInoqmnHK/hdKM8cyaHMwu0e/nQjMaD6b4ORbHGiZgfaHKVT/+Qr1zI0Z4GjN5uRsBjvb4PNPKJa+I96TgPf4PwGtXmB8eDwZ5RqO1vetJJbzB6JKyjESi3H9Oz27wesgPxGGHn+ro91fxZ2De3Ey11EzYyeCQy022X2J7E4CXWo54lqzFtXatSGP7TgKbz7hH4w6yL30e8xrOg9HkzcXn+lLS9GkpKBOSkaTnIwmJRl1cgqapCQ0ycmsLn1pFJQFSKyskLg4Y29nAqJS/JIgzdWI7waV0Ujij+f5AnKEcp51lnE+/xxqvZquXl0ZW3tsheTwkt917bvb/b0oyi+hGSw1bcaoqW0Y/vQkaevXEDddShdlA66VR3CuSTEDG765Al2n17Hs/jKcTZwZVHMQZdoydj3bhanMtEoHRZBjECO0TZDduolICnZjGlUQgD9Q09SIu/nFFc+bOTfDSGrE5cTLlUhAZqZBkc/bV8SeyE08OpxDiupFRbulq6krLVxaUM++HvXt6/N82xo8Dp+hqH5TvIf0RHxmEnT4Dur0J+L414yM2kG/ohAkXpvB4a/LODs6OhISEoJOp0Pyp26TxNxSStU6ajpVFgnytvBmTbs1jD4/msmXJrO502YUUiOmPEvkcm4Ri6s58DBmFUeij9DJoxMLWix4rdOlWCSmn18/2rq15bvg71j/aD0AAUotCxp/io1gTsqzCBr3/hgAjU7P9P2PMFVK+aF37SrkNr0knenXpuNq5sqilouQSSRYuZ9AnFTG6O3lOLjW4JlURfS9O1VIwIWIDKbsfYCDuZIfu3tz9WRdMlQZdOrUCU9PL3bt2kWPvCacsd1CYdYoBm0OZs+YJm9UUjSSGvFjl5/55MQAnloUsWP3LMYNW81X3k6czMrnm+hUdgX+z1mBvycB7/F/Aovi0rieV8yKGm5V3NP+QFRpGb7GCsR/9Q65KANuLAe/7uDd+h+Y7UtkxseSEnqVEQFRiBRmnAhYycJThtz6tyciqOtmSV13b8iF/JtP0LfUVXJS+wPpJemsCFlBI8dG9K3W99WbceUKORs3oU5MRJeTU+k9kZERclcXZC6uGDdqhNzNlQJ7R2YU6Yi2smGEcxYnwleSqcoCoGfvGfT368+G0HVsjdjGo7YStOjRZyfT3bs7Y+uMq6Q+KAgCJ7IMAkGvImhvw5abcSw9+4IP6jrzVb+6SMQdSb2+D23cAvx+u0ejYhnLB8uZcH0yWzpteW0XxfGY47zIe8HSVktRSBTkleWhF/QUqgu5nXq70oW76MoVuq6+R7qZGIt6pSgyToH+J4M2/u+oaaLkcEYeBRotFjIpSqmS5s7NuZx4mbGBYwnLDONh5kNin8bihBO3dZtR2KqIznbmgxo9aeneiHr29SrdMef8uhWvDWd44CPC+oseVDs3F1yCoNlkMjV6erl9xhTb5kx9vBA2toF2c6Dp5L9ETp2cnNBqteTk5GBv/3Ldf2ga1HCsepGra1+Xpa2WMu3qNGZem4nCZSbHMvOZ4WbC1aezCc0IZXyd8UyoM6GSSdPrEFMQw+Osx8jFcpRiEeFlsC0pmh7RVxAEfYVh0PqrMTxJKWDdoPrYmlaO4pXrypl2ZRpl2jK2dt6KmdyM4zHHuZp8mRE5tfFLD2N23U70s4wh+v4dWg8ZVUEidgYn8M2xp9R2sWB6IxMuHNmHTGZB7cCTuHv44ezcnBEjRrBz50665jXknO028rKH8cmmYPaObfLKffQH/G38mRQ4gdWidVS7dJHg5ldo4tuWaZ6OfB+TyqWcQtrb/E1J5r+I9y2C7/Ffj6MZeaxNzGS4i+0bq28jS8qqmvO8Cy5/D9ryf7wlEODuge309niOAhU5vXbw9aUcGnlac/Hz1szs7IdOL7A7/BEAoqgsVq/eSnRmUaUxBEFgQfACtHot85vOr3KnJKjVZCxaTPKEiejy8zFt2wa7qZ/hvGwZnr/tpdrNG/g9CMX7xAncNqzHcc7XWA8bhmeXTnzS0Ix8sYolaZaYmAWyudNmxCIxReoilFIlgc9M6H3ThRZOzWlr04ze15zpV9q8ivzw85IyokvL6WX/1zszdt9N4PuTEXSt5cjyj+sg+T3NE2lr8FJwqtUGzywd324uhqJiRp4ZTnRedJVxSjWl/PzwZwJtA+niafCgv558HTCEvFeErECnN1QpFhw7RvLkKSh9q5G6bDLXFVYYaXLQx1yuNOYf8sHP/5QSaOfejixVFu0PtGf6tekcjDyIWbkZIpmIFV1XsL/rRYSUaUQ8bUc7t44VBEAQBLJWryZz6VJMO3di3QAzQp9uAXUxfLAWDWK+iEyiXK+nZ8tPYGIwVOtkSFNt6w65ce+8T/9oU/zXuoCItCLEIvBzfLVccDv3dnzd+Guup1znePgyhtuquPToU55kPWFJyyVMqjvprQRAL+jZ8GgDY8+PxUphxb4ee/nOTUwPe2dOxp1jatICUvzE2Hl6E55awOpLUfSs40y32pWdETNLM5l7cy5Pc56ysOVCvC29SStOY9HdRdQzq0nnXx8h792XFGtXzhbbUpCZQVZCHIIgsPTsc+YefUrr6nYMcy/g8uljODs7M2HCp3i4exAbuxKNphA7OztGjhyJlbkVnfPqY2e9G5WumIEbg3mRXvSaLTRgZN2x1DGuzsEWYu4snE6RuojRrrZ4Gym49z+oG/CeBLzHfzUiilVMe55EIwsTvvOtmiv8AyU6HSnlGqr91XqAtEfwcBc0HvePGAX9GRmxUVRL3YWDohA+2sSs2yLKtXqW9A3E196USW19OTGlBf2byZCKFGiM/FAFn+TDpafosOIay8+/IDy1gFOxp7iWfI0p9abgZl65aEudlET8oMHkbt+O1aBBeB09gvOCBdiOH49Fj+4Y1a2L1Na2CnEIzwlnzPkxzL8+Ed+iTVjLjYgyHYmpWSDuZu7EFsSSl57Ko/Onad64O6u6rGFFz3XU8m7A7QN7KCsurjTeHwJB3f5iKuBgaDJfH3lK+xr2/DSgHtI/mbE8znqMo7EjkanZpA4bSODASczbrYO8AkYcHciL1MeVxtoWvo0sVRYzG86s2N4byTdwMXVheoPpvMh7wcnYk+Tu2EHqrC8xDgrCffs2+jUZzW0PF1RaKSVXK+vM+/8hH/w7CRAEgcDDT+l6X8/YzAB2d93F7U9uU0NWA3dnd5q7NKemgz0LP6rNg8R8VlwwCBEJej0ZixaRvW49Fn374LpiBbVNnQlVpUGb2ZTbVmd0eBxnswv5xsfFkFM2sQcCzO8AACAASURBVIX+u6D3L5ARDhtaQOh2QxfLW2Bra4tUKq2oCxAEgfSYKCJSC/CyNUEpe31UIVXRihLzDzEqucaFsMmotCq2dtlKt3ewuM4ry2PixYmsDVtLd+/u7Om+B0tdCmhz+DxoOrs77cC4EC74xDHmwlg+O3gBKxM53/UyhPFLNaWcjD3JuAvj6HiwI2fizzCp7iTau7dHL+iZe2suekHPpHMSZKZmeM2cxtYRDYmQuSMAj2/fZvr+R6y7GkOfuo400Tzi8YP7NGvWjKFDh2JmZkb16nPRaPKIj18DGAopR44cib2tPe3yauNsvQ+VroiBm+5UaCq8ChKxhB+7rkEsk3HLR82uXz5FIRZzPqg6s19h9fyfwnsS8B7/tcjTaBnxJA4LqYTNAZ7IX6PHDhBTapAU9f0rBTmCAGe/AmNraDXz351uFeTtnUwNi2x0rb/iWFl9Lj7LZGZnP7xsK6czMsoS8LP25Ytvv8ZIJmGcNAw7Ezlrr0TTY+1Zvrq+ABtpNQJMu1USmCk8e4643h8ZWtpW/4Tj3DmIFW8mQSnFKcy6PosBJwcQmRfJl42+5GzPbZxuWAsjiZiPw6KxM/UgJj+Gm7/tRCyV0vRjgx+7SCSi9ZDRlJUUE3z4t4ox/24q4OjDFGYefETLarasHVQfubTy8X2U9Qg3rS1qVSkNevfDbspkWu09y49prRCVqBh5fDCh+9Yi6HRklmayLXwbnTw6VagRluvKuZt+l5YuLenq1ZVaNrVYdWMRiUsXYdqhPW4bf0FiaopMLGPYh7N5UmSHccoNKMmumIOTQoaFVMKzYhWCIJC5eDGlW3YwId2fDlseYb/hOGJBTEZGRiWRoF51nBnQ0I31V2O4/iydtDlzyduxE+thw3D6/ntEZXnUT40gWi4nrd5ghj+J41x2Ic0lD7kVPpP76ff5fadDnQEw4Ta41IcTn8Ke/oYU1hsgkUiwt7eviAQ8v3WN3V9NIywqhRpvyHdvSc5icWwagRYGB0S1Xs1g/8FvFHn6A2GZYXx84mPup99nXtN5LGyxEGOZMWnph5HJrLCxaYMsoYiutx2Y5D6ChxmPSTf7gbaNH/EsP4Q5N+fQdn9bZt+YTXxBPGNqj+HEhycYX2c8AHuf7+Vu+l2mGHXH/FoYtp99itTKikBXS5YPa0GikRvzQtQcfpjCiAa22MVfJCc7i379+tGpU6eK2ggzswCcnT4mMWkriYlbEAQBU1NThg8fjpurG63ya+JmeZgSTREDNwYT9QYi4GTqxNzm83nhKiLl6V2uPz6O6f9wi+B7EvAe/5XQCQITIxJIK9ewpZbnWz3po36/U/tLGgHPTkDCTWj7NRj9s77gBRdXU0MTTKZVM3IbTGH+iXDqu1syonlVF7/o/Gh8LX2xsHegRb9BqOOe8m0dHfe/7kCjoOsgKiM1ugd91t+l2eLLfHfoIY+mzyZl6lTk3t54HTmMeadOb55PeQHL7i+j55GeXEq8xOjaozn10SkG1RyETCLDw0jBobq+KMRi7pVaUZyYSuSdGwT1+AhTq5cFi/ae3tRq05GHZ0+Sl26Qi332N1IBJx+n8vn+MJp627BpaFCVO9PM0kzSStJQROXjWrMWjj4GWViZoyONF6xlY6PlSEUSPs1Zz9XhPVl5bh5avZapDaZWjHE//T4qrcrQGqjXM/ypDdniEi6NqIXrqlWVCFMzjxY8sKqOBD05t36ueF0kElHTRMmzYhUZC34gd/sOrIYOwfPAfqxHjiRvzx6ily1Do9FUUQr8pmcANW2VxH02jYLDh7GdPBn7L2cZohSnZ1K/2HBxGRZykau5RVQrO0lU3EriCuIYeW4kky5NIiovyjCYpRsMOQZdlkDcNVjXBMKPvnEfOzk5kZ6eTmF2Fpd+XY9eaUa2VoaT8OqL2v70XL6OTMBftYeYpE20dWtLM6dm/PzwZ64kXnntegRBYGfETkacHYFMLGNnt518XP1jRCIRGk0BWVkXcXDoiVgsJ/reHYzNLGjkNYzC+CGYSuw5k7KNcRfHcS7+HF28urC181bO9DnD5HqTK9oLYwtiWRm6kpZOLWi85iqK6tWx6tevYg7+TubcdetMusyWJqb5COFnMDc3Y+zYsfj7V9U+MDb2RiIxJip6IRERM9DpyjAyMmLIkCH4ePvQvKAaPpYnKdIUMGDjnTcSgR7VP6CTTQtONBETsmIOuaq3Kyf+k3hPAt7jvxKLY9O4klvEouquL21334Co0nIkIvA2ekcSoC2H83PA3h/qD/s3Z/svSAzG9OZ8ksusMR+xh3nHIihV61ja15DvTilOISIngvyyfPJUeWSrsvG1NBS61e/2AfaePlzetpGQtMtEFF5nYr3x3P9iCCv61aGlspQGS2cgP3WUUzXbs+XjL7mrUqDRvdogRa1Tsz18O90Od2NHxA66eXXjZO+TfFb/M8zklfPCXsYGIiCWO1P/mQVSU1Ma9qwqz9u8/2AkUik3dm8D4MRfTAWcfZrGZ7+FEeRpzeZhVQkAwJOsJwCYp2hp8AqJ4BqNOrNtwGHkZhZ81TKZkwU36ZnigEPOS2Wi68nXMZIa0dCmLqkzZ+K+7RLNyt044JRErqaqXGyzD2aSWmqG7u6WSiH3miZKInILyN29G+vhw3GYPRuRSIT9zBlYfTKQ+IuXAKqQAIVOzYrHu2mUGMb5NgOwnjjRQAAijkP4Yao1nAwiKbG5YdgXbEOXd5o17ddwts9ZptafysOMh/Q53oc5N+eQVpxmKFhsMh7G3QArDzgwDA6NAVXeK/ezo6MjZWVlnNywGp1WS72JcwAoCD5DWUnldM7prHw+D4/AI28FWdlnGVVrFKvarmJl25X4W/vzxfUvCMsMq7IOQRD4Lvg7lt5fSivXVuzrua+S4FBG5ikEQY2TUx90Wg0xD+4heNsw6uJQjDw2oiIdfxt/rBRWlOnKECGimlW1SnUHWr2Wr298jZHUiM+ivdGmpuHw9deIfm8Vjcoo4qN1tylCQY+MM9TOuIHE1oPRo0dja2tbaa7xBfGcerKAqJjFaHSlgJj0jKOEhPanrCwNuVzOwIED8ff3p1GhBzXNz1OkKWTApjtVanX+jG86LcEaU87U0bN75Zi/bcz0d/CeBLzHfx2OZ+bzc2ImQ51tGOT8bop4UaVleCoVb0wZVELweshPgM4/gOQfbLLJjUO/uz8F5XLS6s/lYryKs+HpTOtQHV97Ux5mPqTHkR70P9mflvta0uFQBwDOxp9lQfACtkZsw6RHfXKLs/n21jdUt6rOqNqjsDCS0T75ASN3zsdXVEralz8Q9/FIDj/JYMiWezT84SIzDjzieqShul8v6DkVe4peR3uxLGQZte1qc6DnARa0WPDG9kJvYwXzJNY45iq5UdubBH3V/WlqZU2jD/oSde82SRFPOJ6ZT7N3TAVciMhg8p6H1HWz5NfhDTF+jdHTo6xHSPQifIw98anf8JXLeFl4sbXXbsqNpIgQUf9GOjE9epKxaBE3oi5wMPIgLR2bkTnlcwpPn8F+xnS+7L+WMm0ZGx5tqDJe7boteKL2wF5XxOMHGwFDLt/l8gVKpDLKJ03GftYXFfUGIpEIhzlzUDVujEivR3LqVMVYuuJiEseMgfvBJI+aykrLINZfjYbSXDj1OVqHQAaYfIBG7o2i5DpexLO3x15aubbCSGrEqNqjOP3RaYb6D+V03Gl6HOnBipAVFJQXgF11GHUB2syGp4dgXTP4l4JGeKkcmBgfR5sho0jVG8i0aV4CV7ZtrFjuem4RE8OCscv8Dk3pc35o8QNTG0xFLBJjLDNmbYe12BvbM/nyZOIKKhcn/vL4Fw5GHqwgDf/ahpmWdghjk2rcy0lj9u4JqEtLOS29S7lOw0ceE7jY9yL7euzjbJ+zjAgYwdHoo/Q62otTsacqLqSbn2zmac5TvvKbjLBxD2ZdumDSuBEAd2Nz6LP+NmVqDR+ax+Oqz0ai1rIl2Y7t9yK5lXKL9WHrGX9xPC1+a8HE090QZ2wlSS1lYboZkeWGduKSkufcu/8B+fkhSKVS+vbtS7169ahX7Ext08sUlhfSf+MdojMrk6c/YC43Z2mX1WRYiXiR85zzt3e+crn/BCTz58//H1vZ/wZs3Lhx/tixY/9/T+M9/kN4Vqxi6JM46pgZsSHAE+k7tvstj8vA10TBhw7v4C9fnAn7h4FPe2j9D9YCqPJhxwdoirI5mtWYuqNmM2b3I6o7mLKkTyBZqkxGnx+NjdKGeU3nUceuDmXaMlJLUrFQWPA4+zHXkq9xNe826dZlFCjKEWWXcCLuGJIfN2G07Rj5Pnak/jAaqyAfutV2YkqbAOq6WaHTC5yPyGDf/SQi8h6wK3YBv73Yi4upCwtbLGRCnQnYGtm+dRP0Oh13168lQ5fDrabu7C90oqOtOdb/Ymfs4FuNiOtXiIl4yiGPWkzycKCuufFrRjXgyvNMxu8KJcDFgh0jG2GmfD1p+OnOCnSZhYxuPglH39drAzzKesTJ2JOYyk0JrqOghXNzwq8fYY7pBTxEtkw7pEF37yGO332L9ZAhWCmtyFZlczDyIJ09O2OlfPl9EYlEpOfpcci8RGR6GM5BY8icO5+8a9c53bwtndq1wtekcm+8SCQiNC0NITsbp81bkFhZIXNzI2nkKMrCw3FZ9iM1hw0gLruE7XfiGZS1HKPsx4yps4RbOmOUBSeQ6gs49MEhnE0rF74qpUqauTSjp09P8srz2P9iPwciDyAWialpG4DUuw1U6whR5w06F6W54NECfvcWKMvP4/6Dh1hbWdNjxBj23U8mKbeUyc1dCDt7AjtPL+JMrRly7zimGUswlwhs6LieNm5tKs3DSGpEK5dWHI0+ytm4s3TxNFgUH40+ypL7S+jl04uvGn9VqfhUEAQeJJ+mIG0rJ3I1rH1xFtfnAuZFMi6a9qOP72i+79qjwupYJpHR1Lkpbd3a8iDzAXue7yEsMwyFRMHie4vp6t2Vnr8loI6Px23tGiTm5px6nMa4naFYKaG1/hHWcjWmjnJ0MfGkNrjN9cJtnIw9SUhGCAqpgrZOdehjnIBCbkVD903UN2nCjrxYcsvy8VFoEQQtqWmHUMjtsLCojZ+fH2q1GnVcHnLjSOJUDpx8lEn7mg5Ym1TVInExc6EkP4djygg8g5No3H7Qa7+3fxXffvtt2vz58ze+6j3R/2TY4X8DgoKChJCQkP/f03iP/wDyNVq6hEZSqtNzPsgPx7fUAfwBrV7A6/pjxrnZMcfn9R0EFTj+qcEkaOJdsH031763QqeF3X0R4q6zP94fz16fslPly7nwdE5OaYmXnYIRZ0eQmJvArtIVWLjYYt7Rg4UPF3Eq9hS3B95GJBJRoinhbNxZ5t+ZT2CyDa0iLaidkIplRjFnW5myvYkK/Z+UEsUiMfbG9jibOONo7MTD1GTS1I+Q6q2Y0WgqA/0/fKee7j/w5PJ5zv+ymsfN9Chr+XFTMQqpCI7Uq4b3v3RePLtxhdNrlnOmbR/2jhz8xkjA9cgsRu8IobqDKbtHN8HC6PXLavQaGu9oSI1US7bPOIdM/uoUj0avoc/xPgiCwKq2qxh7YSwqjQq1tgyHIgnzNhdjoZXhvHxZpZqJHFUO3Y90p7FjY35q91OlMfPSU0lc1JYalhncT2+FzbUojD79jCY1m/CllyNTPatGUZYvX46XhwcNr1yl+NIlpPb26AoKcPlpFWZt2gBQVKZh4coVLCpfyCbvEXzjOgjzzBX0dfXhWMwxNnXaRBOnJq/dJwAvcl+w6sEqbqbcxNHEkUl1J9HTuycSnRoufWcgAja+0PsX9E71+G3+LGJ0Mjyq+zF0+HA+XHsLpUzM7pFB7Pl6BjGCiN9auSPL2Y6XhTfrO6zBxfT1krfh2eGMODcCD3MPxgeOZ8a1GQQ5BrGu/boKU6OU4hROxJzgZOxJaouiaGum5bq0O529P+bpgo1Ei2y5592Ts5+1wkTx6iiQTq9jf+R+fnrwEyWaEuyN7dnlMof8kROxnTwZu8mTWH3lCSvPJWKvLKatEEmxcQZ37O5gWiLQ66YzmS1tCJa7kZHlwKb+H9LQ2YR79z5Crc0g6WJtcuMMYlnuDYO4X7+Y+KzTDLfVoRAJgA4Xl0FUrzYHkUjGjRs3uHz5MtGKYoJLm2CpMGf/uGZ425lW/U7qNAw+3JeO1boxuu64Nx7PvwKRSBQqCELQq957nw743wi9DuKuG7TD3+Od8EchYEqZhi21vN6ZAADEl5WjEYR38wxIewwPdkCjcf8cARAEOPMFxF4hVNKObIk72e6NOPk4jU/bVcPP0YyFdxfyOPsx63XfI4kvp/hmChkrQ4lMfY6vpe/LEDMiNj3ZhIe5B18qOtH8XhQWxQIeW7bw+S/3uTc0lJO9T7Kx40a+bfYtY2qPoZFjI0QiEWFZD9FIUujsNApV3AzWHrcgIvXNvc5/hqa8jNv7d+FUzQ/zAG8yi+M5WNcHjSDQJyya67lFZJRrKsK0fs1akevgRruQi1jqX+ES9DtuR2czZkcIPnam7BrV+I0EACDkxU00Ih2NvZq/lgAAHIo8RFxBHNMaTMPH0odZDWdRrClGg465vX8m4OfNeOzeVaVo0sbIhpG1RnI56TKhGaGV3rNydCbNrAkKkYBPShjK8SPwnDged6W8knzwHygpKaGoqAgHJyfspn+OSKFAm5mJ9aiRFQQAwEwoZr54M+FGXnzv1AeH3J/Z1GIiXzb6ErFIzIOMB2/cJwB+1n6s77CeLZ22YKO0Ye6tufQ90ZfrGfcROi80qF1qymBLR9J+GUJGZASu7u5k5eSg0wu8SC+ihqM5EqmM6qMn8VsDPbKcrTR0asaebjvfSAAAAmwDWNlmJVF5UXx+7XO8LLxY2WYlxZpiDkcdZvjZ4XQ51IW1YWtxMLajnZUJNtYtWdB6NT4qO0rz83gqdefHvnVeSwDA0Ho3sMZAjn94nE9qfMLiZgsJ27iEM+0tWFwzhnorF7DiXCKO0gw6Cs8pcc7EpY0L37f5np3DjmJuZ0/jYi92d5tM40KBw4sXc/ZgO9TaJBIuuGFtG0incZ/SatAIUh6G4bUvnfa2o1mZaUy61lCfkpKymwcPh6LR5NCqVSu6du2Kb7kpzY1CyC8rpP/G28RlV9UCkElk7Pro4D9KAN6G94qB/wZKNCXIxDLkkr8hM/s66PW/32nugoDe8NHmfzbn/F+KH+PSuZxbxNLqrjR8h0LAP+OdOwMEAc59BUZW/2wa4O4GCNlCUc3BXDucQFDfvkw/E02Asznj2/iw/8V+DkUdYr7lTCzvSDFr44ayhhW5hyKJzoumjbwpumI1ElM5qx+uJqU4hWXRjZAe2EmpiyN3bU1x9vLABFBIFHiYe+Bh7vHGKQ0PKGDsjhD6brjN0r516FXn7RGSB6ePU5yXS/eps8goOc/NtFtUMza4D/YNi6bfI4PdsZFYjKeRHGuZlPgmnfnk2GYOHviNZn0H4qKQI/1TpOJubA6jtofgaWPC7tGNsTR++2/t3K39IIMebYa8dpkidRHrwtYR5BBEW7e2PMt5xvw783EwdkAraPni+hds6rQJP2u/V35+iP8Q9r3Yx/KQ5ezutruChAkaDcoMCRk2JhBYxpq6GSwHapoqeVZclQRkZBha9RzUapKGj0CkVCL38iLnl40Y+ftj1sFQ81F0ahZGZdlMqzsHZepWBruPo6WrwTzHz8qvChl5Exo5NWJv972cSzjH6germXRpEkEOQUxrMI3AibdRHZiES8wJRtRyJNbLgh23Chiy+Q4qjY567pZEFuYwJuw7ZGWP8E61Z7pPP0zlVe9qXwVvC2+MpEYUa4op1ZYy+PRgYgoM3wtPc0+m1JtCd+/uKNVxhIUNw9XFUMF/9fxldIhp1qYFTbxfXedTrisnsTCR+MJ44griKh4Hnu9D01aHoJciCnGjKK86/rJMmhql8dFHfQn4XSpY0OvJiIvBxNKKuIchxD0cTSACDq1yMXMtwlg6imHfz0Aik7Hh0QYuFF9g5PTB5Oy5QvbGywzt3If9xbdoIoulkYmWgoIQ7t7rRZ06G2ncuDFKpZKjR48iUT7kuqoe/X65xf5xzau0/L7N6vmfxvury9+EXtDz2ZXPAPip7U8Vual/C4IAZ2cZCIBXawg/AhI5fLj+H9ej/2/Cqax8ViVkMMjJmiHvWAj4Z0T9rhHw1kjA81MQfwO6LTMQgX8CkecMxKJGD85FWWFklscxtRf5pTnsGNmI8JzHLLq3iG7WnWgS6ovMzRjzju6IJGKkYz0oOlyCS7oVGStCiW9Typ64PXSNNMb9SDB2Uz9D0ecjbs+czMXNa+k754d3Ng2q5WLB8SktmLArlE/3PuRZWiEzOvlVqPH9K0oLC7h37AA+QU1wrRGAT0wMWr2WxKJE/C28udm4JmGFpcSryolXqYlXlXO/oIQ8J09eeAegPnuMuZbelJtZ4KaU42kkx1grcDk0FVt3U777IBATo7efrkoL8nmU9QgzJyO8HV99AQfY9GQTeeV5zGg4g+j8aMZeGGtwteuyDa1ey4hzIxh9fjSbO21+JREwkhoxpd4U5t6aW9GaJqjVpEyfjvXtuzxt6UR7x2iSI09yp3pf/E08uZhTSLlej+JPxafp6elY5eai+3I2IrkMj507kDm7kDhqJCnTPsd13TqyTTPwfLqPlW79cTZPwiV/JBsuFtCxWj6BrpbUd6jPochDaHQaREU69Codcqc3n49EIhFdPLvQ3r09hyIPsf7RegadHkRH1/bUfGCEm64hnZxjqB38Kba6flxKzmNeD3/cXMv4+NQo9Op0RtedjX1UKFd//QUP/0BMrV/920spTiE0I5Q7qXc4F38OjV5T8bqLiQuf1f+MJk5NCLAJqPh+Pg1fhlRqjq1NewpVaiLv3abM3I15PeuRo8ohriCu0sU+vjCelOIU9MLLLhcnEyc8jF3p/kCMl6QaJ3wn8zCvmCBpEu2doX//CZgZGxN9P5jYB/eIfRhCSd7L9jy/5q3xaSMmNXsdlxLb87CgJTsbqFl6Zw5n4s9gpbBi9pNv6d6zOy3jO/H89Hm6ubkS3s6DfbnX6GuloVydRUjIx/jXXEKdOr1QKBTsP7AfseIxV0oD6ffLLQ6Ma46n7T9w/fibeF8T8G/geMxx5t2aRw3rGqzvsL5SkdBfhiDAxflwa5VB57vTAoMe/eXvod5g6PlzJU3y9zDgRUkZ3UIj8TNRcqSeb6UT7LtiyrMEbuYV87DZG4xWtOWwtjFIFTD+1j8TnUl/Cr92BhsfUlusYu9383Du+DGzo235tH01Bje3pP/J/phIjNmU8R36jHIcPq2H1MZQXHYn9Q5jL4xlQ8M1eFw1Yoz0K8qFUn46ZofPd3MxDjKkAB9dOM3FzevoMnEaAa3b/6UpqrV65p8IZ8/dRNr62fHTwHqYv6Ig7/LWXwg7f4phy9Zi4+JGeHY4A04NYGWblXTw6FBleUEQaH73Oc4KGT/YyDk1+1OU9ZuQ9+FQ4lTlPCtUEVtShvAnASAR4KyQ4WmkwMtIgYeRHC8jBc5KGQhQLgiEXb3Ir5kL8XAMZHDjH9EIAmq9gFoQ0Oj1lOsFclVpHL43Ejfb1vi69ONG+BeIkFCnxmLEckc0gp4iVSqx0XNAX8Z3LZfT06N5lW3Q6XX0O9mPEk0JR7sdJGv6LIovX8bhq9nczYqhQ8FqLtjYscGjBsOb/MrEZ8lcDKpOLbOXBZBnlq/AZds2jO3scN/6K3IPQ4RGV1BAwvARRKlLCGweRYHUhKPtPmdWg+Hkl2rotvoGcqmYk1NaEJxxlc+vfs62Zluw+00HKi3R7Z0prGWNsUSMUixGKRahlIgxEotRSgzPjX//X/J7Lcn28O08OHAAv2hTwlq0ITXHla90v9BREkqORS2iusxkbOgS9ALMbLqEYb6tyE1NYeesT3Hzr0XvL+cDkFCYQGhGKCEZIYRmhJJWYhAckogk6AU9H1f/mN6+vTkac5R9L/bxRdAXDHTuAVotgl5AqyngVuQHCMqW6OVtOHAjmJrBMUTXEfPIPZMi3cswukIkx0PhiLvMAQ+ZAx5SB9xl9riJbTBCRuGp00RfvcO3feeRUKChuSyWnrXs8TIzJuFRKEnhj9FpNMiNjPGsUx+fBo1wD6zHjpmT8WxqgcLzPHZ2HcmTz2fUrmvYeO+hVBzDtAbTGFxzMBsfb2TLky2YK8wZ4/gJxb/dorSgAM0HNbgtnGG4TRlmEj0iBDzcx+LjM4P4+ER279lNok7HpfIArI3NOTi+OR42/zki8KaagPeRgH8DvXx6YS43Z8a1GQw9M5SNHTfiZPo35R5vLDMQgKCRaNp/w7XES7RsPgWFTgPXFhsiAt1XVHiovwcU/K4IaCwRs6WW598iAGBwD3yrffDdXyAvDgYf/mcIQFGGQblNYQYDf+PW6nUozS34Oc2eGo4mjG3lzvhLoynRlPCrcjm6xBKsB/hVEACAmHxDGLWajTsbCyeT7JTBgoQJWNUPRFfqiKATEElEBLbvQsT1K1zduQWvekEYm7+7NK9cKmZh79r4O5kz/3g4H669xaahQfj8qagpLz2VRxdOU7ttJ2xcDLLEf3gDxOTH0MGjA0lFSZjLzbFQGNYdUVJGrKqc8W52+LnYkt61FyEnjzC6d1+yrOwYeDAYX2M5G0YGoZKJiVeVE6cqJ0GlJk5VzpnsAnI02irzFZnaYFugIlTw5GZEwiu3ySx7LQpEPJM0If7JLEBA5vo1T8vNkWtUyMUiZGJ77L0WkBT3PbOvTmK79zS+q9cPf9OX+18iljC9wXTGXRzHL0sG0ulyNA5z52A9aBDVQ+/yYuceOsrymZ8XQ3T6BaAmESVlFSSg+MYN3LZuRW1hgcee3cj+pBMgsbDg9vxJKG6sxz47j2c1xvJl0AgArEzkrB5YjwEbg/nqyFO++aAeAJdOxbIe9QAAIABJREFUn6KruiOxFhIaXEhlbXw2W73kbz1nyEQilGIRcqEZar9qXFJoEFIEBAsds2vNJiXiJ1w0oZy5/Dn2RubUrj4QD4We2IJYXOxdqNG7G0/3HWHehjHctIkhW2VQTLRWWhPkEMQw/2HcTL3JzZSbLGq5iO5unSl79oyx4Y4kFdjw4/2lxNxajEYKqdaQ7AqZxmL03AZuE5hrDlhRUhpP0/s6nHIEnHNEOOWCVWE5IlEielESAiL0IsMj/vf/00xs+b7TDIoLy+kkjyZAk0Li4fMkApaOTtTt1A3v+o1wqeGPRPqS3Po080LsvA8z0wAC/FcQV5iCU82N5JXnEiidwnD/EYjFIibXm0xHj458c/sblsSvoVXvljSL8CT98APaBDZjuySKLiZJVFPqiE/YSFFRBLVqrWb4sOHs2LWDjsJzLpTWoO+Gmxwc3+I/SgReh/eRgH8AoRmhTL40GROZCRs7bqywRn1n3FkH52ZD4AA0vVbz+fUZXE26SivXVqxqvRLZ1YVwcyU0Hg9dFr8nAoBeEBj6JI6ruYUcqutLY8t3y0n+KwRBoNqNJ/RztGZhdddXL1ScBT/XB/emMGj/vzHr36FRGQxdMp/BiDMkF8rY980sigK7srPEi6MTm3Mk6ScORB5gXfUVeB1XYlzPHut+lcPS82/P51LseeYclfBF93w6EcCiD7eSfzyWsme5yFxMsfqoGnIXU7KTEtg56zNqNGtJ18nTXzmtu8l3uBx6gib1OtLCtQUyceU7/ruxOUzY/QCNTs/qgfVo62cwtjmxagmxD+4x6qdNmFpZI6jVqFNSmLV7KD7FxtjkqCElgwIrGdUGjKZdt4ksTchkdUIGj5vXwlYupaykmF8/G4uRgyurZO0xM5Kxb1xTXCxfbTcLUKTVEa8qJ61cg0QkIvlhCBevbSTMN5x5rTZQx76B4YIuEiEXi5CLRETmPmXk2SEMrDGQq0lXUWlV/Nr5V6pZVas0tjYri8Jz50lKjuFry6skGGXhmxFA2/J6NLe1wsvcFJFMCgJsvP4jSYpSPjf7ELu2HRHJZAgiMTfXzKaNzVNOewayS1xMmvO39HG1Z6qvK6UhIaTO+pI8MzPKvphJu94vBY0EQeDbsP28iMlg79O5xGd5UX5Pjvu2rRgFvIxWrb0SzY/nXrCgWw22R47DpdwOh4BvmBjkgehYHOInOZTVtyW7gytlCJTpBFR6PSq9njKdnjK9gEqnp0yvJzO3hCvnnlJYLEdpIsWxljk5kgvoCs4j0RuEkcz0AmJBoEDyL2RbANsCOTYFcmT+LtRxD6K1a2saOjREKpGy4u6PbH2+g9HqxvS+o6f0YRjl5WqeW3nw0C+Ik24ulGgtADFiwTC2CBEiQcpLDSsRiMQIhtX9JRijpqPoKa5pT3H38sKnfiO8GzTCysnllemxsrI0gu/0RFVYhK/bWrIcjJl+bTpKqZJW5rPYflXH1GZWTK1RBL4dQCxBq9eyK2IXa8LWIBfLGWjRHeHAQzQSgeddlNjKQuhgrkUniDBWulCv7haKi83YtmMbCSVazqlrYG1iyqHxLXG3eXOr7N/BmyIB70nAP4Tnuc8Zf2E8OkHHuvbrqG1X++0fAgjZCiengv8HaHr/wvQbs7iSdIUunl04G3+WTh6dWNpyCZIL8yB4LTSbAh2//z9PBJbGpbEiPoNF1V0Z4fL2/vXXIbVMTf07EW8e58RUeLgTJtwxCK38O9Dr4eAIiDhmMHep2YMD339Fanw8P9v0Y2y7Gnh7P+XbO98yrvoY+lxtgkgqwv7Teoj/VBEt6PUM2NEFktJQmUoptDfhWN9TWCgsEAQB1ZNs8o/HoC/VYNrSFfP27tw+vIe7R/bR9+sFeATWrRirVFPKT/dXkrnnMq5ZRoRWzyM5QEI372709OmJv7V/xckyOa+UsTtCiUrJZU4DC1oIqRw9sofads7UUOlRJySgSU01bOfvUCmg1FrALFuEXAOFNkquNu1AXLvubOjWpmK5cwcO8fTgVm579WLVF4Nxs373k6Gg17P18wkEu6Vyzy6J2wNvYyyr/HlBEBh6ZijxhfGYyEwoVBeypdMWatrUBEBXVETRhYsUnjxJSXAw6PWI5HLU6FjXReBWgJiOD/SMPK9H8g+cNiW1anGgejU++OQTatWqBRiOxbhba7hT3oAbD8ZibWKJ+MODxA8fhVCqwmPnDhTVDIRFrxcYsOMe45I0nDTfxU3rMIIH3UIiliDoBQrPx1N0NRllTWusB9ZALK9aV1Sq1rLhagzrr0Qi6HT0r2OGVbUnHIjaS6nW0AZnJMipmR3AgJp3aByRi1CmZ7WrFQ9MHVEqnJBJFJSUFZGUn4hG+vK4ywQxJmox+QotHhkCdZ9bUGQZSJJZXSI0zpTpxYhFEOhqgaedDDO5MYK+mIz0Q1hZBvEg3YnEjFxqFzzFPaA2rn41EYlEiACxSIRYBGKxCJHo5XOdVktCdBSpSYmU6wVEIqilKKRny4b4BTVBafrmmwWttoTQBwNQqRJ4ccSN9FoeHJHfxsfSh7Xt1+Jg7MCa/8feeYZJVWVt+z6Vc3V1zrmbpqGhyTlLkmRCUDBjRh3HnMc0xjErZlCMgIgSJOcMDTQ0nXMO1aFyrvP9KIYwju/rODO+3w+f66qru7qrztl7n33Oftbaaz3rm7VcWnoviYIZMaYPwuRnQpohgkC9tZ6n9j/F0bajDAzPZ/gJA46iWjrHR9MYcYSrwt3IBJBLlfTt+xZSyQA+XfYp1VYvm7y9CNdpWX3b2H9p7v8a/LEd8DsgJzyH5dOXc/OWm7lp8028OeFNRsSP+J+/dHIFrLsXsqbgu3QJD+x9hB0NO3h02KNclXMVfSP78urRV1HL1Dwz5VkkAS/sfxukSpj0xO/Tsf8P8VNHD6/VtjE/Npzrf0Mg4Pk4FxT4C9sBrUVw7DMYesu/TwAAdv4VitfA5Geg90wai4uoLzpJYfw4UmNNjO/n5NZtzzMybiTzKyfhtnUTfXv/CwiAv7ubpocfomZQMynhRmp0Vt4Y/fRZV7sgCGj6RaHKDKNnQw32XY24TpkZMGsa5Qf3sPXjd7n21XeQK5QUtBXwxJ4nSN/jIq1DS1R6BoPKq8iIjOJ717fs3PMFA7yxjCWLXg4jsuZ23qitx9fSjPCjyO6MeBRKOQmHC3ElxFKfKKcgTUaD0Y8tUqDaKPLigDQyUm6ivmIpR7aVoz/iZcb6dUjXraNmaR7GWbPoHDaWx0t1TFeGM9l+mHjDDb9qOA/XdLG1pI1caSddLU3YR6rIVmf/jAAAbK7bzImOE0SoIujx9PDR5I/opUvHunkz1nXrse/ciej1Ik9KQnb9PHbnBPGmxHBp5qW8q4rkrYI3+ZRlVE0cilW2gA6PQHJrEws0MprUBzhQv4c3xrxKlCIc0eujq6GOhhXPkmdsZ0/v6ayw69EqM3guPR5BJqcmLhbfpk1n5YIbbA1ct/tNilVzebvudWK9XQgLv4GkNFKWLqVu4TXU3XgjqcuXI09J4eOaNq5rDZDuFKk3ZeAO7uOa5T9Q02wkK0ZPTqyelAFhxB3vIOsjL/HX90WqDXl3RFHkx8JmXvyplBaLm1R3BdF5R1kXOE2wJLSQZ2qNTNNZCLNqKbGnU9ldjTtTwsSqTp6q7+RUby9dBgt6TS4aWzIdVRr2VXRh7LEgCnYOZKs4kaJG6oW6KBt1MVZgL7AXFUqS1Qn0ikgj05RGflQ+YxOHUl3zBrW1a/BFXMuKkw3cHdeFWHuIGy6/kfD4f56C6HK5KC0p4ciB/bS1d6ASBDJFH0lxMYyZMpWMrOxfFRArigFOn/4Tdnspfft9wDelS9gn38OY+DG8Mu6VUPB35VYW19yBRabgafc13GbeSswXl0P6eJj8DMlx/flk6id8V/Edrx19jeI0P7OzxxD5QyXq+ByWDW1ljrGNGNwUFt5CetqfuGXRLXz62acI5go22rO4/P3dfPdfIAK/hD88Af9hdDg7uHXrrdRYanhxzItMTZ36zz9YsjakOpcyEt9VX/Hg/qfYWr+Vh4c+zILe55SilhQu4b0T73FVzlU8MuQhhHX3hhalCY/BuAf/a/34/xXlZwIBMzUq1gzIRPWPrsl/ER83dvB4RRMnR/b5eZEhUYTP54TKBd99PFQt8N9B4Tfw/a0w4BqY/TYIAiuefoS66lo+jJ3Ph4tyefb4rSilSj6PfRfP2iaM01PRj0s60xwR8+rP6Hjlb5iFAHfeJkUqSJmYPJHXxr/2i6d1V/XQ830lfrMLMV3Omh2vkjtrGkczO/my+EsuKk0koVogrv8I/C1dpBcdQ93ZidofQDjv+WBXgS1Gjy4tg4ReQ9jW7qCj+hAVKTkEJjo51LYXiQADNTBG68KqyObjxnrWXbKOFGMKgYCL06fv5ZUWFZV1lYwrrGFGuY7IBisBQcKp+BwSZ43l8IEtjL/2ZgbNmPOLfSpqsvDKpjJ2nZE5BogJdONO2cVlA1J5atRjF3zeG/Ay4/sZdLm6kCHhw4i7iNpbhm3zZoJ2O9KICHTTp1IyKIqvhMMcbjtyNpBNEATGJY5jXq95NNgaeOHQC6RZlYw8kcOGqxZTKlUQK7Uh1N3LhKQJvDb+lbPX6+v7b2Sebg3isEUMDRpp1s5k74AMDpR24Woopr2sgEcffZQDLQe489DntIYt4gr7Cd45dn/I6zflubN98FRWUnfNtVhN4bz9xEvM3GthWFeA+rGxXLP/ILrMlwl2XMKE+EupMTuoaLfj9YcWdCmQKJWSmxlBeJiKg9WdVHU4SIoQCciXYDPVAyBBIF8nZYrORoJKQ3TUVLS+HJZ+38B01TGGhVvxVp1EkAWRyUSqZGE0J8jxJYlY/HpKunpR1JpDmbU3XZ5QbYlYg4JRmZH0TRGJibBh87dSZ6ujzlpHvbWeRlsjftFPflQ+U5RV9DJmcvtP1xBrVHFt9waclh5ueG3JBdfT5XJRVlZG0alTVFVXI4oigs+DLuBj4NChjJoxG4XyX6gICpSVP0Nj42ckpz/Gm1XH2NW4i9waPa/M+5Dk3n3hyCew4QGI7o33yq/5uizIkm0lTHNv4D7lGvRBK/SbBxMfh7BkWh2tPHfwOXY17iJHn8WQI1r89WZKp0rJCy9noCaAX4SYyEmkp/2V5V99S0mznZ/8WUzIDePjhRP/pfb/T/hjO+A8/B6KgRaPhbu238WJ9hM8Pvxxrux15YUfqNgKX8+H+AH4Fq7goYPPsqVuy88IAIQeJK8VvMay08tYlLeIe/Lvgh/uhMKv4KK/wOh7/6t9+f8JVn+AiwvK6fEF2DQ4mwTVv6nP4DDz0P7tfC9NpSy6CSFxMBgTz221lG6Ab66C6S/DsH9TvKPuAHw+G5KGhYILZQoaTp9kxTOPsjt8FINnzqRC8gqlXaV8MXQp2s97UKQYiLyxL4JEwF1WRtNTD+M9UYovRWD/NWreDXhRCfBG/3HkJF6JyTQSieSfO/dEXwDrtgZsuxvx4OZ909dsjDzMwtahJO+oJN4ZJNpsxqlSUxsbj8zngoCbuKkXk3fxTNrCpawz72Rd9Tqa7E1oBDWz9sYS8Af4bkw9ComMcQYvo3QesmKnkZJyC7UeWLBhAa8Pfo6c97chDQ8n4u47GVlchsFbyaTgKr5rbSamRcq4gnTmtLQhtrdxNCsRi07D1bfcQ/jYcQjSc27sGrODv20uY93JFowqGSP9FSRU7aRKm05R7FA6/Gr0apFFo3px9bBkovQhD8/7J5aw8ad3GVsMU6t0SLosSLRa9FOm4JwwiDWGSn6oXYfD281AYwRTYzJIUQYIBgPUuD3s7ailwulErkgkq8zJnphuIpThvD9rGbWBSN6pb+dE7TK01h+Ylv82D/YeRZRCzqE1Kwnb/TBZUT7enrWUl0q0hBWbcbpCcyxe6WXwQCcb3TuxRd3GAKWftYdvQipTwm17QX5hTMTewtMsrmrjzzVKJnYEMU9O4OmyFo7Xd6PNfIHepv6suvw9APyBILWdTspabZwu6+DY8RZOBv04EUFwoYpfgUxfGnKnizJSxUjG6CQMSU6nV8p0oqImI22vIPDRLF71X01yAIYcOYavvh6JLEjCxB40Jg9fWyawVDGNSkkopkYtcZIVUUG/yDJ6h5cRr3dgNPbHaBiA0TgQozEfufxcJpUv6GNt1VreLPgbXR4rybJ0KsrnsuraCWx9/HaGzrmC0fOvDVn8paUUFxdTVVVFMBhE4vchtXQSa9QzZtYlZA4ZjuRMOrWnpobODz9CP2Uy+gkT/sfbs6Hxc8rLn0YTPY/Xaiqo6K7g/vx76XjxewZOn8m4qOrQdmzWFLjiU4JyNYGADZ+oZ9n+Wr7ceZIF/u9ZJN+ITCIgGXYrjPkzoiqMjbUbeeHQC9h8Nib584na3EZjfxlkVzLb6CEAGDSp5Pb+kJWrt3O6tpOoPAmPzf3PGXl/kIDz8HvJBrv8Lu7fdT+7G3dz14C7uDnv5pBLqnYvfHE5RGbju/Z7Hj78ApvrNvPgkAe5Jvefi5uIoshzB59jRfkK7h5wNzf3vRFW3wJFq2DqX2HEnf/1/vxfIyiK3FBUw7ZOKyvzMxnxGwMBz6JuP6y6kcvSH8YjUbD++O2hv2ujIXEwxOVDwVJQaOGOg2f11H8Tuqrho0khT8JNW0ATHrISn3qY6upadvZbxOjRB/iuYiWvjnyF/A3RBKweYu4ZBLjpePsdur/6kqAqiGuugZw7v+SRw2+ys3Eni1L6ki8pxe+3olBEEh09g9jYORj0/X7mAnX73Xyx41PS9unJtkVTVvYx4XWlqH1+GmMTkCxcyPgF8yjwBPikrgXlZ2+T1FxD46U3MHfKZEaF6WhztvHWsbeo2LOb4YVh7BjQQXu8g2GaAEpnH4Zm38uVw0PpdHavnRFfj2DBERWX7PYiBoNUZ+Vw092P8UhUA33b/0yhJY7PzWoCimamJE3mAfnFdP2wgZ/qy0g1W+gXkGGYOQP3pBm8XxtgxdEGFFIJ1wyOJWLvMpxNtZjiE+hqrCcoihRGRePMvpKC5gAKqYQZGXqmth1C+ePHxHaDKJdhGD8B9cVTOJDiZV39KmzW42QooZ9eiwkrEFIv1GjSkQhyHM5qRDGU2x4Uoc0vUOSUsd2uRJDIeW30s4xMnsb+zg4Wb7oMlzQWd+zjzI+PZKFOSunjc5meVM4TSR+zulKKoHayZO5Alq/czil/GFafBlEmEJlm4Cv9T/Qqfhdu3AjJ52SAg6LIu/XtvFTdzPNFbsY2+fjMWsKXYUnoVDIen9GbV088hY0y1s7eRNp52Rtef5DP9tfyxtYynH4bmvhVCLoSBAHkQSUa2yAsnROwec5VhYzUyMgIWkipPUJiSxvmzDg0miC9gjKKYgdwVAinpsvCJ7IXGSBU8r5+MTJTInnuXfxFdopuicCT9X6G9tZiiYrAonJj9zUjnje2IVIQIgZabRbHi+7jy8qtbOqRI5PAxYYx6FdVMHLBHTR2W84u/EqpBDrbkHabyczNZejsy0nIOacxELDbMS9ZQtfny8HnA4mEuOefJ+zSS/7p7Wk276Dw5C3YNEN4q74Vp9/Jq+NeZXTCaNb89REG2NeQomiGobfinnA3jc0rqatdiogDuSST3D5PINcN5eM9NWzYd4Q7xBVcJt0NSiOScQ/A0Jvp9jt56chLrK9eT7IygSGH1XjcLhrHdXFZeBdaiYhMoqZvn/fYvLWe/nn9ycv7lXFlvwJ/kIDz8HvWDvAFfTy570nWVa9jYe+FPBA7HskXl4ExEf91P/JwwStsqt3EA4Mf4No+1/6PxwqKQR7f+zhrq9eGPAbZ80IBZiU/hsRrht78u/Tp/wqv1rTyam0rz2UlsCgx6rcfKBiEfW/g2PkqdTGDmJvzLJMjw3jD2AlNx6DxKDQVQGfFue9EZkPCYEgYGCII0X1A9iu9EK4e+GQyODpg0TaIyACgvqiQlc8+xu6I0Yy7JoGl5S9zQ58buLFlDvZ9zYRf2xtvyW7a//Y3At1dOEYHEBfk0n/kJ7R7XMz8fiZSQcrRhUcRRS/mzp20tv5IZ+d2gkEvanUKsTFziI2djUaTRmFHIY/vfRxHfQ1/qswkbUc1Mr+PuqgoTl15MzcsupLIfyijXG+x8u1fn4T6alZNHY/fWInfth+JX2Te7gQUWg+Bae2cCsZR2NNGkCABVxIDwy/itenXIHy2grniEvp2aXl1/nIQ4Kn121meN4Q1y99lZb8EJvRbhUIRTrluFh8Xr0Cv0PP48McRNxRTtGsbI42JrOzSsTZ1JEGJhMvDPNwwMYM9y9/FZbUw9JK57F/5JQOmzWKf+zjCvlrCbEGiIjLYJySzyZiFW6YkzV7FlBQ3M2flcLhzNd09R0iUeYiSh55/gqDAYOhHmHEQxrBBSCUaauveQxCkpKXeheCG+jcfwkkj3olp2GTN2H0OPuhQ0ukXuDpCZFxMNgedaj6uPcXotAXsCIzGio5eVXX4K7toJAppmh5/7EnmyCsxHTZxKM5BYeTlxLR6sTXa8IswKqyHhTMmclFuDHKpBLPXz10ldezotPJOPehKe3hZ6abaE+QiSyV/feJqouOj+OD4ct45+TKK5seYkduXKbmxOL1+/rLuBC32dlQxa5HqQpZ/tiuZaTIVkYKDyVe+jUabQeOxU5zceZTi4joqXAK1hjjqDTF4/kERVSIEyYqwMCRJYFyagQkn30DWdAzvnHe5sXkDpV2lXN/cH9/xdhaOCBBlOQoBDwGJgDUlC0tcPBatiCXQhM/fA4BcbsLns3Kqsw/b264hPmkL+7r3ovRJ6W3tS14wD73fh72sCKnXTZ+xExg881IiEpPPtksMBrH88CPtr/2NQIcZ42WXEXnbrbT+5S849h8g5tFHCL/2wueszVZCwbF5lPqi+KTVQrgqgncmvRPKFrE24/xgOip7LZ35C2jJhI6OLYhiEI07gKFbpDNKgl8uQQhGkpbxJ3SRc1iys5YjB3fzgPQrxkoKCRiSkV70JPS9nN3Ne3nmwDO0O9sZ4cwi/oCd8jFuxic2k64M4hcFemU+REryol8t7PVr8AcJOA+/dwGhoBjklSOv8EXJF8x0ennGq0K4fh2PnHiLjbUbuX/w/VzX59fVo/cH/Tyw6wG21m/lmZHPcGn6TFhxLZRtgFlvwaD/cF37/2M4A0GOWR3s6rLxdn07c2NNvJWT/Ktvjh6f/6w6XY3LQ63NSm1TKbVoaFOeywT4a1YCN55PLBxmeCs/VEyl1wxoOhoiB85Q/jNSJcT1h4RBIVKQMAhMqT/P2Aj44MsroHYfXLsGUkcDIc/Oxw/fR3NDE52XzWWv668MjhnM64nP0/15KapeSuwbX8NVWAg5EXRc0krYoCn0ynmZgo6TvHv8XYo6i8iPyuez6Z9dcEqfz0pHxyZa236gu/sgPlFkuyueylPdXF4gZ0CxBxGBFoOG/Xn9SEyezhRHDIokPabLs5DHnstT9gf9bKzYwDvbX6ZJY0GCArt+AoMqtQwrKKDPojFMGn8bcrmRDmcH66rX8+mJlfQE6pEGYFBlEHOyEUVcHCvnfIcoiow8VEJUdzdPPHwPKq+LwI1TsA3fT1D0oE1+lFeKvqO4s5jJEVNp/cnIMUN/PKKUGWFerj61DlPBfkSgy6ClMymOGiGAOiqK+Q8+xTsf3siwk27iqy0IInRrVWwZpmN1Ul9crtF4vWFEqjqZmLyboQnHiDRlkRozCVPYYPT6PkgkSvx+BzU1b9LQuAyZzHhmTLvQlZnQfu0m5em3z7qWra521pd9zAfFK+n0+Rmt8zPDCK+3heJU/hzl5/uay9laMxKT0srzYe/xxtBX6PB7iSp+npFtI/k+fwy5aal8mh2N7b2prHQP4SvJLJosHqL1SkblxbBNE8Qih4/aZWwuaOY7vMQZVTyeLSX9L3ejzMkheemnVPtauOzHy8gUbuJ0eQY+rEjkPSgityLTViIIIvkaCVcnTyRpw0iMnjhIciLpOIhj5078ra0gCKj7ZKNTnUafKqXrukfZW/U1hXUpFDfkMyZPSu/IcoRAOR5PI4IQRBYMMKyykzCrnb+Ex9Jn5CLGxk5j9bMvoTWauPrJZ5F1nEJStx/q9kLDEUS/C79UwJqYTk98LE1yJw2tcswdqfT0xCEGRLythzmW76RJ24PBLmNEdSyzBsxl0MVzfqZO6Dp1itbnnsNdeBJV/37EPvYY6n79AAh6vTTfdz+2LVuIvPNOIhffiSAIeDxtHD5yKVt6vKzp9JIXmcebE98MVctsOYn41VxEVxdrajJx5QSJH+LD5xRJNbeRWetBEvQTlMhpCdfTlBTAppdDUE1s9DUYEhbxzo4mmo//xKOyr+gt1BKI6Yd06nPYEwfxxrE3+LbsW6Kk4Qw6oqbH5CV+QDNj9T48QUhPupqcXs/+qufcr8EfJOA8/F9UERTbS/lo5Rze1ikYEz0YtSqczfWbuW/QfVzf9/p/6VjegJe7d9zN/qb9vDz2ZaYlTYBvFkDlVrjkPci/+r/Tid8BPT4/hy0ODvY4OGSxU2hz4hdDSnETwvV80jcN9XmBgKIoYvb5qXF6qHV7Qz/Pk6Xt9l9YlCbW20Wqq5HUiDjSkvJIUStJ1yjpq1MjOX8BX/dnKFgGt++H6Jy/nwx66kNegr+/mk+A3xX6vyYiRAYSBp3zGmx7JrSlMOfdkOrjGZQfK2DtS09xInkkTUO2oZDK+WrsctzvVRB092D78WGkYXo88yJp7V2EzTSDIl8EW+u20e3pRiPT4Av4mN97Pg8O+eV9w4KGHaz49BGG7bHQuxE8ail78gaBvR1Pbl8W3LKYFY/ey8De08kI9iXoCqAfn4g40sh3Nav5puwbWh2txKlMZJRBSqUGw0Um7Fs81MRn8MO0BUyPMnJTQhQjwrQIgoB9/352PHcvu9OdbO+vxKsIZV/M7zW+WiGxAAAgAElEQVSf2PBRPNYURmxdN6rSTj5yHUK2aR3kRNF9t4hbaCc54xlePOhnW6EMMaAj3VHNU/NGMG70YEr37WbXay8SZ+4hvtuG1utHlMtR5/XFffIU+P3YY7XoJ2XQnmnhpZ42GtR+hheF0yfWRXl0NiXt06g2m9AopFwxKJHrR6aerebW0bGFsvKn8XhaiI+fR2bGgwQsNoo+mYulfweCQkZyyiJSU25DJjvnOvcEPCzetpiDLQeRChIU+LG7EpG3X4PFYWJi6mkuSf0crcLFcq5nO5N5qP5tOmqzyBhXRB+TEXlHBdKOKiTZF4M+jSNNUbxfFEdjcyglLlsn0GGHHkSuHKjm3onRGDRaXAeP0frQU2h69yPxvQ8Yu+YyfJ3j6LELKCL2IFU3IUckU2LC1zWBZOUoRtTuoaXmJBfpJmGKGoivYT/y8CZ048ej6xuP7MeF+GQSysaNpa1nBzpdLvFxT/DJJxt+ca7J8XE1a0ilkfXyMVRokpDLXSgUbuQKF3K5G4Xcfea9G7nchVR64f1pt5swmzNRKsOg+zRte4zEj2yhXNCyxwRtwW6GxQ7j/iH3kxMeui/9ZjPtr72OZfVqpJGRRN93H8Y5sxH+QThM9PtpefIpLKtXY1q4kMiH7uHw8atY1lDLATtMTZ3Kc6OeQyVT4TyxBNW6x/FKRQr76Dm5sz8KrUDagCryatswWb34M6ZQl3MTaa2bkJz8FnwOLFoDjQki7dEKAsgwaqdgSL6Pd3d1ISlaxYOKFcRjJpBxEdIpz3BUdPGXA3+hzlpHP0sC0WVeXGM7mRNhJ6DOZeaotb843v8q/iAB5+F3JwFd1bD0YggG+Gbi3TxfFCrpfHv/27kj/47fdEiX38XtW2+nsL2Q1ye8zvjYYaFAw5rdcNlHkHfFf7IH/zW0enwc7LFzyOLgYI+dUocbkZCC2QCDhmFGLcPCdORolNS6vRda9WcWe8c5NREkQOIZ3flUtTIkL6uSk1q2ipSdT6IxRMPczyD+XI783+f/We9CWzG8PwqGLIKLX/mfOxDwQXtxiBA0niEGHaVcIGcy6k8w+ekLzvfKXYtxdpk5eZmEBncly6csw/BRC4EeAefuF1DPHM6uoYfYb2+kyGOgx+dELVMzPnE8U1OnkmxI5rIfLwt5g7Iu/Vmz3LYeNrz7IGE/7CWuW8QTE8lPk2ewKTqBGTtWIov2kDK9EU3kMDoadBzfXkTejDmIXQKl7SVsDzuMR/DS35TMSJWZLKkZlaQXpd+HYzfbEEWRac+/wfeiii+aO+n2B8jVqphXdpJhrzyPPikJx8PPcPMeM3btaiRh+5ALcroNl+AyzCCi6S5U+EjQxxEd0GI8WYehxUJD3nAOm8dj9YTTL0lFwLCKodtqUKjVRMek0FNSCUBq/4EMnDUNdVcVtnUb8J2qoindy9spfqb19ZCulvJ+u5wqD2idUqaUJGFsEzHFJzB2wY2443qxdF8dawub8QaCjM00MDFpE4myr9Hpssnp9SxhYYPxd3ZSf8ONeOvqiHrnaVrDd9Patga5PJz0tHuIj5+H5IygUlAM8nrB6yw7vYwwSS8aiucjSH2EJa5n/sA8Yo9aGWpewfbscTwbs5hFp79F7RCYclE1oquDQHclQY2BgEJFp1/BO+KtnBb6kW85gP24kUZPyCsRpujhopRdjE44hF5hB6DdGcmJjr4UmNOopxt52GEkih4MUjkLMiZwedhcmtYewb5jO+rmKvZlJaJ1+1Go08kZMJsEqx5VTjjhU2RIvpxJuwlKsw34Aw7SUu8kJeU2RDFATc127PYG/IFuAv5uAoFuAsFurO5GfIEu9EKAAcU9mHp8lGTraIlVnZnzEAzKCARkBAIKRFEPGIEIBKKwu5RIxD1EapsR1UHEgIClTkdXuZHMKUGCkmaCyDgRzGZNezs2n4vZaTNZWBmL8N5ygh4P4ddeQ+TttyM9owPgsnk5ubOR0v0tmGI1DJiSQkK2kY6XX6Hz82W0PhHBO5JuKjxSbul3C7fl3UhH+3p8e18iubgSu05O26SFRKQsYuc375Kj+5HsWgeCTMuJvo9y68lsOuxeYg0q5uUZWaDeT3TpcjCX45MpaYqR0RSvwKWSopQOQJv4IB/s9pFc9QV3yX9Ahwux/1X4xj/A+9U/sOz0MrSiin4n1TiyHYzvNZcbx//nipT9QQLOw+9KAiyN8Ol08NoIXLeWxyq+ZH31eiSChIywDD646AOiNL9tf9vutXPz5psp7y7n3YveZXhEP/hyLtQfgLlLIfeX06v+LyCKIrUuLwct9rOWfq3LC4BGKmGIQcuwMC3DjTr66dVUOD3s6LKys8tGgdVB4Mw0VQgCyWcXecVZHflUtYIklQLF+RaAswu+vw0qNkHv2TDnHVAZz7bn1LZN7P5yKRqjkcwhI8gcPIy4g48gtByHu0/8tpRAtxVaToS2D2SqkMrjeW3asmUXJz9+hfL+0exPOMIbUXeQuboHIXIkRf7VHBrvZWvPPqwBEaVEzrikCUxLm8bohNGoZWowV7J14z3cG6jntTEvE29Mxua1YfVYcbU2w3c/Eb/1FDqXSG2Skm1jk/gpXYo8YEXh7sInF/FLgr/YfIWgYLxtIJe0TyIsuhTfoCqSM28kImI8zWUlfPPUg0hkMhY8/xrRqem4AkFWVdbxQVElleFRhHk9LEyJ5YbUOOS+INd9uYJG9SuMMtzLBnUfgm47t0VUolBZaHW00mxroapZS2fTSILeGCSqBpRRm5BpKzHJjMTWwrBTYRzO6SLBr2TyBD1qVScBb+u5Niui+cmmY217KxkqGVVuHyCgV+hRy9Ssu2QdzSdPsfuLT+lqbiQpN49x19wEEXF8sHUdqwpFrF49KSYfi8bkMV3WjW/DOmw/bSTo8ZC05D20I0KaH1brKSoqX6Cn5xAaTQaZmQ8RGTERQRCobLex6Ps3MStXoCUZR7CNzPAE6mx1+IN+0nqkTJcZeDr3Le44toPsxHjmXzoLlowEMQh3HGCPPcgdJXXYfH6uDCrYsqseqyfAwjA1WaPUfH/SRkGDD6kEEo0BnH4XPZISZMbjyDTVIEC8MoLbI6Yz9JiIa/tOvHUh+WRF7xz2RWjp9rjwX/oAW+q9lLbamIOc+1Ahk9bQ2ed12mNt6HS5JCXdgMfdTHf3ASzWYwSD3rNjLghyFIoIXKKCEksjBnUio5KnoZIYid6+HEXjaTxTH8XXez5fPfYYqgg/aZeMx2ovJeAtRS3UIBV8+D0S3D1KrLU6ukvikGptJPdpR5HuRqYKoFTGERExDoDOzp10u1rZUaNhhxSkAZHLWpO4/aq/YcrMBcDS4eTQ2hoqj7YjBkUEiYBEIhDwB4lK1pM/OYna6tt5yV9Op0/CowPuJF/dQUvzd6SXt5DU7MaV0g/5vFXYbCoKNtzNQMt6wnt8dGhzeFr/OOtqJfRLNHLV0GS2lbSxo6yDQFAkL97AnWnNTLD+iKLyJxADmMPUNCXK6TTJkYgpKCLu4tODGoY3fcZ1ss1IJDIkI+6gtM90nioIZQdldodzU/Q8Zl7924zEf4Y/SMB5+N1IgL0dlk4HezuBa9bweM0q1lWv456B99Anog/37LiHcFU4H03+iCRDKA+80e1le6eVbV1WCixOYpVysjRKMjUqsrQqsjQh9/XfNfItHgs3bLqBRlsjH07+kHxjJnxxWcgivXI55FwMQNDhwHH4MI69+3Ds24egUGC6ZiHG2bORKP8XzfzfiKAoUupwc+CMpX+ox06bN6T1Hi6XMtQYWvCHhenI06kx+/zsPLPo7+620eULIAD99GomhBsYEaYjXaMkXilH+mtiAhqOwMrrwd4WyqAYevPZPXtbl5nN779FbeExEnP7IpXJaTh9klR1O5cmFVNmnIFy4v0k9cm7QE/834XL6+f5225H4etk87ByHj+ZjqfNxpFxfdkbdpxOqQW5AH01Ui7NvZOpWQvOit74fG7273iMjZU/skmjxHfeGCS3i8w8HGT0aRFJEI70Etg0QsPpZBNeQU2MoMTY0IRWoiF/+EQiDNHo5Xp0cg146rG17sbnOoZOEUQjEZAHFCQ1/Ql1WW+kRgVhl2ahzgkPyQMXHEKp1RH0+5n3lxdR1TfS9MCDBBwOGp75K9+m5/BThwVBgOmRRuZGyLl/83RcPTOx95vHbaYw/pKfCsC+SjMvbyylsNFCepSGhXkSwg6+TmtcGfJEP8og+AsjaD8VTkAmsmp8Ezk6H33UAcx+CZ1BDQFFPG4UVHSHAjnjdfE025uZkTaD9TXreWHMC8xMnwmE1ORObd/M/pVf4rJaiOoNUQMriEwcS1nL1XxxoItSvwqd18m0xgLGxSeQMX4kvecMvCAORRRFzOZtVFa9iNNZg9E4nEM9d/LWDgsahZSrxltZUf8iEkFCIBjgi4u/YG/TXpYdeB+LGuzR73D9wU0Ycg0oJHvxNBXg6D2LA8pRHA/moHN1oTvdRE9nBDlIWKi28VXWV3TYIrH1pOGxZCDRNCA3HkemK0GQ+An61QgSL4Ik5GLXO0X61gsMkqYxsvdUeo2/hBNHD7Dnq2VMX3wfuWNCcQ11nQ4OHT3M4FNvE/DOwh59nOrY4+jVXUgFNyCg1+ViMg3HZBqBWp2MQhGJTGagoK2AW7bcQl5kHh9O+RCnW6Da7KC+rZP8fXeSZjnI25rFrG9JYHLzBmrUybQqYwkPWIgRrei93Ui9Z8orC5A9dBSDp03Du+dtvtvZyqSxnYiDUui0HwNEjKoByLdZkK9ooCVJYPmlUKCQYZKrmaOcT9SJYdg6PGevk86kJC4zjKrj7UilEuQqKW2xX7MmchcEJNz/pY9MdRDrzSIDmmToW5sQRyxGmPwMFceqcR2dT25HFQIytnbnsbkzk82pl7NgeArRehXdTi9jsqJIidCw/mQLq483UtRkRSYRuDRD4BbdbjLrVyE42nEq5TTFy2mOVeGXmBDV1/JtQRwzzMu4RLofj8IEEx5guVrKklMfcXHadJ4dfU4j4t/FHyTgPPwuJMDZBctmQncNgQWreKJhPWur13LXgLu4pd8tAJzqOMXt2+5ARMKw3s9R4Imi7Exd+0SVnBFhOsxeP5VODw3ucwxcAiSrFWRpVGRpVMTKfXxd+BJORxlLp7xNrjYB8fNL8JSUYI++DkdpG85jx8DnQ1Cp0Awdgt9sxlNcgjQigvCFCwibPx+Z6bdVQBRFEXsgSKfPT6vHx1GLg4MWB0csDixn9uTjlXKGh+kYZtQyPExHlkaJTxQ51OM4a+2XnOl7tELGuHA9E8MNjDHpiVT8i6KWoggH3glVZDQkwNxlof35M20t2buT7UvfJ+D3o5l5JWvS+5OmUTNXJzD8m6l43W6WVebj9fhQarSkDxxC5pDhpOYPQqH6ZR37X4MXP/oe+ZaPaI9sISjzcSRLoNMAclHGkMgsMjnFkIgkhuUvRa1OwBf0cbjlMBtLvmVb405sgogeCUZNNFZ3D08XuYg84kbZLMcrF9jWD7ounUpbr9tZa3aSrlbytEGg4rVnkCmVzH/6ZQyR/9zztG3pm9RVfcfAOSPI7H0jOl0vPPVWur+rwN/mxJ7sYv2utxh++VXkjp3At089RNDhYOipSkxJySS+8QbKzEwAGtxeljWZ+bK5kx5/gJjmu1Go+9FkWsSpUX1paLPz8sZi9ld1E6MPsqB/DQNNW/G4ykASIopBPzTti6Wz1ERMlom2im6CwxP5MuIgWrmWScmTUMvUtDhasHltnOo4RZQmikZ7I3cNuCsUdKWO4qsZXyERznli/H4bpadf4viGrXScikAQJWT6JaScrkCGQPXYmaxIHsMeqwAixAckJOtVDB8cR990ExlROhJNamRSCcGgj6OlK3hyXQ+lXakMTTTzt3njSYpKobCjkDu33onFa2FMwhjeHPcm33/yPtXNJ3FIE5GKIjvjdtKp6kQuDac7ajEueSbGmlJ81SqEoJQFohKF0st6XQ9t3UZQNqIKO4bceJKg4EIlVRMty6OrdTAtrUkoZQLDDF2keU5gTnVSLC/D7AmJKcWoojFWusg39uW2G58nUh2Jy1VLR903NNR9jOe8BACZI5aC7mz2mTNp8+QyIjOdqX1iGZ0ViS8QpNbs5FBTCUvK/oQMA1G2+2lu9yHYOgnz9RDmsxDl7+RPERvJUbewpSWTkz3nCqvpwiMwxcYTFhd/9mdMWgaGyFAtiq2fLOH09k3ckXcKud+Oc/Q9VDeewqw4QiBSROJXodfMx9qSzcHyZrYbt9GmryPCEc948wym5o+n9/BMwqJDBLqzyc7WZcXsd+1gV+ZXmAQpk4/fT+/mcvpUfUXKRXYUGjfCjFcJDLieo6tWkN70Z6KsDtqN6dxgvR9dczmDe46xPO0GrIQMJ0EIPW7CtQom5kQzOTeGWIOKDUUtrDneRJvVQ4QKHkiuYIZ3PfrWwwQEgbYoBY0JKqxaLV4uZuOJdOZbvmCktBinLpnW8XdjzL2UCM1vl0P/R/xBAs7Df50EuK0hUZi2YgJXfcOTrdv4sepHFucv5tb+t9Li8bK908b2Liu7W0uRt76IJOgmJf0xZiUPZ2KEgSyN8gLLwxkIUu10U+H0UOF0U+HwUOkMVWHzBEPXz2izMvT0ISZXVtK3qBC1JVT0Q5oSj3HSVHSjR6MeNAiJUokoijgPHaLz009x7N6DoFIRdtllhF9/HbKkJLp9Abp8fjr//vJe+HuXL3DBe+8/zKFMjfLsgj/MqCXpjKhPlcvDzi4bOzpt7O+x4QqKKASBoUYt48P1TIgwkKtV/fbUGFc3rLkjlC2RMzMUkKcOC42hpYetH79HxeH9SFMzWTP2Uko1RrI1Klq9XubVfsuzVe+wcuL7DOw/AypLqDh8gKqCw7htVmRyBcn98skaMoL0QUP/pUp8oiiy+vRBVn7zIK0xPXQaQBYUGEp/RrXmM3i0hhbfq5jChpPb5x1OdlWwsXYjW+q20OPpQRsMMtETYFrfa+mddRXvv3k9Ew46iGh24NHLWD0wwNF+MDT3Xr6VDcceCLI4OZobNPD90w8TDASY//RLmOL+uewqgMfpZNmfb0Oh1tDvoukYoqMxRsVgiIjCc7CTH754CauviwV3v4w2VUXZ/X9mp6sLmUrFVS+8QVhyys+O6QwEWd3awbKDt6MRLRh1C/BVBjjYGI9ebmNG+mbGJ+1DFhSwt8txd6oxReST1f8STm44QtWxI8T0MRPf30zn3rE0t/Yw+sn7eb7kVSq6K5iTMYcHhz5Ip7OT2T/MBmBx/mIA3jnxDsumLWNQzKCz16C9fQPl5c/i9ZoxlsXDsm4qwsJpNulRKZQMmTkXp68fp/e14tHLaO2lochsp7bLiVM4N8flUoGUCC1KmYTyVhuCBC7v08bIiLfRKdwkJ91ISsptNNg7WLB2AfaAnRFdI4izxiHxe7FE6yhK7sePDU+yT53D4l4P47T6SK2yU9tsJ8mgQmbzUiMGEeRmIuOKkOmPYw+2oZQqmZA0gVkZsxgRP+JskafChh6+PFTHj4XNuH3Bs+2M0stQq5z0WItRGmrICq+jl76DXJ0LvdR3dmwM6kwSU2/BwCBsX5gJ2LzUjIrhux4b20rbsbn9KAmg9VoIC7YQpd2E0SVgsqYS5nWg8NguuPYaYxgRcTGMV+4m2ltOS/bNrN1jRpBKuO7Vd1Go1AQCQaqPd3BqZyMOi5feI2LpPTKOLx65ldiMbGbfchPW5xfSvrket1eDZ9KVmHOH0FjlwWMLLfBybQcylYuWtFq2qNfS6feSqwqwICmHQanziI6aisVyktcPPcuP5lbiLZnMbJxP/vAoxNo2hnTej0J0UF+cDY8sp27/i4yyf48gwvvS2fzNNhcRCXE+M1c0rsQ7Yi79J01hQHIYOqWMXeUdbCluY0dpO1a3H6VMwujMSCb1jkGvkrGtpI2Np1tx+4JMNHXwp7A99O1Yj8TvwqKT0RSvojVSjcs/lEOnMljgWE0vSSPtvRYSfdW7v/oZ87/hDxJwHv6rJMDrCAkBNR4heOXnPNV5kO8rf2RmnwfQmyayvcvKaXvI4o1XypkUYWCg2skXBffT5mjh1XGvMj5p/K86lejzYT92nJadu3Dt24eivAwAi1ZDYW4+hdmZLA58S6qkmRv7v0JXwvAz3gMlOpn0zGLuh6pK+v7wHfl7dyEJBtibP4RvLppJSXrWz86pl0qIUMiIkJ95KWSEy8+9j1TI6KdXE6UIPZis/gB7um2hhb/LSqM79NBJVytDi364npEmHVrpzwub/MtoLAi5/20tMOXZ0F78GTJRcXg/mz96F7fDwZHhk9nVZwRDTHruSYlhYrget92M9O2BlITlMi3nRURBYLhRy5Vx4cwM12OpLKXiyAEqjxzEZu5AECQk9M4la8gIMoeOOGvBXHB9RJGSrhI21W5iY9UGml2tSAMiufUwttdULsm6E/+qJjz9yqmO+StW3ThKxXS21m/D7DKjkigY5AuSZu9Cpk9HaDGQcLie3hVu5AHoSQxj+ygdK1NaGJ40m2b/YA6r0hnmqubl3AwSjEl8+9RDuOxW5j31IlEpaf/rENYcP8r6t1/B43Bc8HeZUonf46FP1Bj66kZis5TTVb4K9ZzJ7D9xEG2Ugil3XodEbsPlbsTtasDlbsRqr6OqU0VlTypl3ZmcaM9DKfUyNXU7k1P2oPD7cVsEAi4tpuheJGYNRaWO5dDqjTSfbmDEJYvITIuisPxOHL4gZd9lkNVvCFMfeoz3T77PJ6c+IUIdQbQmmiJzEVdkXcGdA+7k4tUXMzJ+JG9MeAMAp7Wa4qP3YqEIeYME45cStMFkDLNmYpw1i66An41LltDVVAGScJKGXEav2SOobWtDIggkRURStqeDE8fbcOmliJk69rVaMNu9CFxY1S5M5SFc3oaBACqfDIXYTVX8JqzKTm7KuInw9TVUZ2n5IO0Kbm1cwfuxVxJRYcPVaA9VyBNBkNpJCStCmnCadl8FAgJD44YyM30mFyVfhE7xy0JZFpePU40WGrqdtHS14HEeReY6QKKhgmhtKMXV5tVS0pVNSVc6ZbYoOgMiUQYp2dERDElKZ3RUNsafmpC3OTFdkoUzMcjGb76h7ehuhMC58s1yrZbIhCRMsfEXWvax8Sg1Z3Tv/Z7QfVm2ge6B9/LpVwX0GTeDqLRpFO1qwt7twRCpQh+hoqmsBzHYisfyFUNGz8Z04ATNHRK64/PpVicRRI5EIiJIpQQDbqJ7nyK67w58YhmCoMAYMZG9diVfV+/CFfAyQuvjIoOfH3vkHHfJGKGDP2e9z7HVUrpbneRqt5Ifvp7XnTdT2u3iiaSl5HmaaNHquNn+ICXeLCbmRHHb+Az6xhv5/N6biUxK4dKHnvrZuPsCQY7UdLG5uI0txW009bgQBMhPCmNcdhQyicDeCjMHa7rQ4eTP0ce4PPATRkcNXpmEllgljbEqeiTZ1BYlY0yfxsIr/nMB3n+QgPPwXyMBPveZCP1d9Mz+gFttVg5aA6AbhEeUIRNgiFHLpHADkyIM5Jxn8Xa7u7lj6x2UdJXwzKhnmJ0x+5+ewltfj33vXhx79+E8eJCg0wlSKer8fHSjR9HVL4VFdX9FpdDy+kWf4nT4iPtuAc1BKa/lPc7hYBQulx8kIMokyJVSlFIJaokEo99Lck0VCeUlaOw2JJGRSAcPwZjbm0iVgii5DINMiloqQSWRoD7zPZVUQC2RIBEEAqLISZvrZwF9OqmEMSY948NDrxT1r4tD8AV9FLYXsr95P+3OdrJMWWSZsuhl6kWE+kyesCjCwSWw5UnQx4Xc/4kh689tt7Px0yVU7duFOSqetRMup29GJvekxlyoOLj+fjj6Cdy+n2ZDBt+1dfNtaxeVTg9qiYQZUUbmx4UzwqjFXFtN5ZEDVBw+QGdjSG89Oi2DmEH98GQaqaOVos4iisxFWDwWpKKEPrUiI4sDGGxawl9+kKkJM2l98yhFYUdYl/QhJ716un0upIKUSFUEotdGt8dBvxoYWSwypEJE5QOnUUXbiExO9jfyjeQIelUkednPss6iRS2V8KSiiat2LcZjt7CibRwWl8gVjz9PfHbOr57GoijittuwtLdh7Wiju62FIz+uJOj3EpnqwGTUExFhwK8241A2gMbOGZVW7D4NVd2pVFmyqOxJpcaShDcY8gIp5N2MibQySV6AaC9HqnShMkpQm6TI1F6Q2M9uBVzQnoCcgEeJzxGg7YSJnmojMb0cyLQ66gMB1ke00aXyokRgScxDrJftZ2/bXt6b9CZhjWbqS5bSFF6Pza3DVxxOUDkQV1I2Vk0YPa4g7T1+Wtp9WDwCTlGKIygn8At11aSIyBHwiIAAvaJ1DEkLRyoRsNjsNHd00dplw+YXcIgKPJyJJxF8qOK/Rm4oxuQciaGxF8ezhiJpdyHtCm31SaV++qTVg28/9epiAkKQbFM2M9NnMj1tOrHa2P/12nVYKzhStxKf4zS6/9fee0d7chV2np97K/7y7+XYOagVUEYII5JABpMc9izG2GvDMOvxju1xOLaX2fUGPGd2ZpwO9trHM5gZzzIzDAxgAwZsogiSAMlKKHSO7/XrF385VLx3/6hfd79udUtCet1qTd/POfWrfOtb9auq+60b05MQzgGQRhIRbWbrDT/DYivhkQP3stgpEK4McaJwF8faUO8I0vTc8i9loZnRFvmojugf5Y7Nm3nYOsrh9BQ/eu272D5yDYnSJKkajPW580qRKo2KI3527v/ixs59fCT5OT7ZeztaCJyCQ37Iw/IthIB8ClueepiRvkLbO3GsLPtNlG0iV1Fr9Am1zXSpzs1vuZndN2+imLPR0UFOLX6axcXPkSQNEnuSr/en+fLiftTAor2zkrLH+SB71zax5+Rn2bGiebz3LtoyRVe/wW/4H8Uh4Sl3nO/s/yD18e38yD3j7N5TQaVxRMcAACAASURBVEqJlJKH/+YTHLjvm7z3D/4cL1/A8zxyuWdmEWqt2bfY5qsDQ/DEySxVdttogVdtGwY03ztS49hal9c7+/j1yre4qXMfAsXasMP8VI5G9Q7ecM9nnvM/f74YE7COS2EC0iSi9fGfZejIV/iDG/9P/mjoTQAURcS7Jie5e7jM64ZLlO2Lf/F24y6/du+v8f1T3z/TgqDqdul+/0G6991H5/77iI9nkY4zM0Phrrso3PUaCnfeiVUq0YgTDvZCvrl0hL/c/2XwtpAv7GExOlsXVyiF6KXYiSYGhCXwfRvXtdBSEGh1Jnvhh8WXWX3m/mD/0wX63jhc4rZyAUc+vyT+ufYcD5x8gPsX7ufBxQfpxl1GbMGkX+TpTgtNFs5obpTd5W1cs3qM3af2snv61Wz7iX+HU8jyvB996EG+9pE/hXaL7976eqo/+uP86vZpbimf1zPX8l74i9fA7e+Ht//RmcVaax5p9fjkYo3PLtdpJYoZz+Hdk8P8+FiObu8wDx65n4eOPsCB3mGaTpbCIzRMJRX2pONc/0SNm+9f4kR5jJUhn+V37eSaO1/HF7/7GfbJowQyPEeKUJrXH4c3PBGx67CDEygol9BvuJPHbirydXuOLfPjvLZ9K06uytPVMR7Ow8zWIX7pts2M5z2i2gKf+t1fZaXW56euWWT23b+L2n0PSoekaYhSAUoFpCpApQFKhcRRj8VjqyweXabXajA026E41iTlFPOPNjnxzTG23jNPdXuW5GvLKlZnhNXlrRzobOPxTo59zSHWRJaHaYmUae8U43GdoSCk6scUnUHEqhQyDhFRiIxDrCTGUgl2HCKSFrYfURz3yVUFTi7BzsVYuRDLC1C6w8HPbcarRux813G6cZ7j7Wn29orY4SSduEQ7Kg6GAp24SCcuoPSFnzvfCii5nWxwOhRPT7sdinaHot1FWJpOVKQdlVjsTnCyO0ErqGAFZUJt0ZOaiIt3YpWzQhwroKsU7ti92NUHSVrX0194D2iLfPkY1+w8yEL8IL2ky2hS5e0738E7X/ETXDN8zUXDTdOAVutJji1+hbX5r5NvHmU4CMgFigTY5/t8T+TYF9ms9Tyu3XELFT1HMT7CtgRefyJk+t2fhelbztzv880GXzv8GA88+igr+xokvRIT+Z3cZJd4NQ5TSLpo7iPmXhIeJCFap8mSAksKnNNjS2JJAamGIOD/kR/mzfY/8Afx/8Cn09cz7OYoxppiLJiIcsxEeSQCpSMOO3DYgWOOoi2f+53kWpqcHXHT6OPcOfV9dg0dYiWBv6vnuaUY8J397+OJlev5Pfs/8l77G3xL3cyXgp/gF93PscN+lEbJ5qPqLdz5Xw5RTGJ+cOM/oV3eTew06RXmiLwaVq9N/sR++jPbScpZzaFqpczM7CZmZmaYnp5mamoK77zC1qeafb62d5mvPr3Edw+vEqea4YLLzZsqJErz2IkGuWCZf5z/Fu+VX6aQtFiauo6Jf/Ld5zzv54sxAevYSBPw2aU6X16p8Y7v/DZvX/o6/9vOX+dLs6+lXf8GP7NpJ7936/uQg5L8WmtUt4tqt0lbbVSnTdpqZfPtNqrdpt9u8K/y9/Kd4gLvOD7BK+9fQiYJwvPIXXsduRtvIn7FjZyqDjMXJpzoR5zoRxwPI2rx6WpfAleAipZwQ7A7VexGnQ/FH2NPMo96x/+LP3M9j82v8p1Di3z3yBJr3R6WVOyZzvGKTUV2TuawZEp939PUfvAI3UaNqJhD79yO3jxNZAmCNCJSMdFgHKcRSiu2lGe5a/w6bh7dzY7qDkpu6eIXkMz8PLT4EPefvJ8HFh7gRPsEoLm5Msbdw8NsljWIMvNjOyNQeAVLTPHE6hL7577HIUufKSnvSIctua1sfdxn9kCLtUqZ9k/9HL/82jeypzBw7GmcZRk0T2ZVOB/6S1jel/USWHhmt8SJSniqdpBPHXuIb596jJX2Pqx4HjH4wpiQQ+zpldlyUpE/1kK0HPpuHoRACMXxMYtDM0ucHOuTrvvAtBDMFid41dRruW21wJYvfAXnoaOkfQvhuySvvYNHbyzwueJRZldmeEPnFvrK5X4SHoyLdFMboUEInWk5k2etAI0Qp9s/OG2bzs5nd8npMXBmG3BkzJhfY9zpMOVEVL+/j7wKuFkt03j7r3Jk+k4eOdHl4eNr1HvZl3ve7rLFm6M632TWbjAyOUKQqCw7RqU4acjDE4e4Tm3itulXEySKRrNJvV4niiJkv0tuLivdL6+5keHN2xgaGmJ4eJihoSFKlSot7XOkFvDY3/0lpccf4VuTd/GD3Lltq7uyh+N0GEn65FVATvXJ6T5lF6oll7xnAwmiaTPUm8JJcohKj8lX+GzauoWZmS2MjIwjpUO70+Zrn/kkC9//e7zSKs5UijWlmBitY8ks6osin1ZrlFZtC8vNKVb6FWJZxK+MYheq4BVJLJda9yQH1xZY6OfIlfchRr6CCscp5CICXadgF7ireytvXL2NN773p8hvPbeQrg4aBAsPEJy6j2j5MZK1A/idBvkgxQvUORYk0ZkZt4QmUpK5bpXj3SpHelUWtUfoaCInJXQU2rNwcwVy+RLFQhU3tojnV/CXY7ZXbmTb0C2UVRk9uFeOuosI12JzMI6VgLYF9pYSuT0jeLsqNGmxEJ5iPjjJ0dpxDu07SWehgxvaFOISlWCYn/b/lj3eIzzQ/nke7f7k4B5MKKsFRntP0PQXiKcUTfcN6JPbCaXg+MgBnqo8RtNtkVqSWEOibLTyQHnowYByz0wPOyGvHtvP7WP7+fbSdexvjfDh6AvcFpzi65tuZsWb5p2Hv06OkAObKnzv+G/RaF/Pq17nMPSnH0KvrbH207/B/vpWgnZKYdhiZmebvfd+lGoZ3G0+i+4odl8TBgXaOj94vmBsuMr0pq3MzMwwMzPD+Pg4tp09/O0gvmA5gt0TRRKlObJY583iH7j5xhv5n9/zPz7jffRCMSZgHRtpAj74nz7FPQ99lJuXn2Bx4rXsTyOWlvZznbuFLXIM1emgWi3STgfVbmft1l8ADXSKRZZnZjg1Oc4Xr1vgcPX4hmjcaJwEHGnjenlc28exHBzp4A7aF59rz9E/3YoeMFmYZEd1B7uqu9hZ3cmO6g5iFfPw0sPcf/J+Hlt5jEQlFGyft0zu4LaCRSU5RhItAoJC8WZq6atY7pYYsR8ipx5E0EOmmuG2RWXnBwim7uH+1Tm+/v1vc9N3nmYq6dOYqdObaDGhErZomy3aYjyOKIbtc7rHBQHv/DDc9j601pzsnOTJ1Sd5bOUxHl95nAO1A0SD+tGetqnEHrHO0fBLhK6HlfbwwxqaHok1KJAVw1jDx40l9VJMsxRnKQRhmVvr1/Km0jS3vuY1JN94mtbn/4Z4cQWkprFngm/ddSv3b4UbUsn1Ycxix+Gh7hg/qO+gn+RxZMTu4cOUcm2EVkgcLO1gKYuoH5IkKb4s4YocWlsIBEKFSCJEvkiaG6PX1/SaCUkEORFxc/44N1n7uD55iol0gQNyG18Lb+Dh1iy9xOHJ0nXE8mzx8bIXMls4yo7SCba5KV5tmFrXgnad3PwhlJejsOMabrjlNu540z3kCkVe/8nX04pa+JaPQIAAiWRqyef2B31SR3Ds+gqJNUTUH6MbDdFOS9RVnrrOcTqqkzrhvQv/DUdHfOva3Ui5QHNonrc9XOdvX614RznldUN94G5O7NvFyqFj6FYdu9dGUsXJ3410NuH4XW68u8yNb7yFhuPzdDdgb6fP050+T3cDDvcCkljhPb3GrkN7uba3jy2dEwih6e6sYl2TZ3ImYkIcIacXANBaEqcz9LtjLC8VaTSGCYIitu0wOVXmS/LjTB5tc32s+OSszUxLcmt3irfE72FUVuhfu0B+qIXTn0c29+K05/D6ddw4PucZ7NuCVcemoQq0mmXaNY9m7NNMy+gkT1klTORrTBXXmC6uUXGz57EVeZzoDnGsV+VYt0KgLNACgcQWLrOF3WwpXse4vwUpJLXwFMc6TzHfexqlQ3xrhFFvhqncdiZyW7FEFrEJIVBa00w1y7HmZKzoqHPLSgg0vogpWDVeW/4zpt2nqMfTWDKmKNcAjRTnxkUKi8QfpmdXaSQFap0KvWCGfjJOkwKtfIDtPkW5nFB61U9S2LQTZSn6SZ9Ot0dnKaa3kmInx3j7iX/LSLjGx2b3sLm+yJs6dZpFm2/vKPHHvQLe6h7ecPi9FKIKhye+xTu+9UUmVwK+8jM7mBu7g2b/Vk4VR9h66G+ZPbmfP/+FD6Ks7Px9nbAtWGRT6wTD3Sa5XoTsCuxAZYZMCiZHq8xs2cH0zCwzMzOMjIyQap5ZjgCYGcrxrpum+Z23Pv9svOfCmIB1bJgJ0Jojb7uL8GgtmxXQc0GWilRHZrBKJWSphFUuIUtlZKmItW7c91zmej2eWlnl4VaXU16eWqFMLV+ili+RMo9QfUDjJDGlsEc56DFOwvZKiZu3bWGqkn1lp0rx2Fydb+xb5uByG8cS3LFtmJmxJl+Y+xjbKtt4/w3vx+k10N/+fWS/jovEKY7jlGdxqptxqltwhrZzimnuPxHxnQN1Di+FaG1x/dQwb7l+hh8rxRQ//yman/scOo4p3n03I//o/eRuPVuPWmnFQmeBw43DHGwc5FDjEPtq+zjePE6iz83zLTkFri0Nc13eYkrPMyJauNLFzr+Ko51b+ftDO/nuMc3pW3SMOn/o/gW3lPcyn6uAo6imfbxQ4fQF+TDG5tz7ORY2DbvAmuWxhM2q9FmxijRkEfwJlDfCUW+Vw+IEtaROqs9tyvRCFGKLos4h3Qptr0wDgdIxju5jpy1S1Tp9izDactmzMsJt9jTpY4tM1tvMtPsUu32UFBzfOcHBO6bo3STY5swj4oDH167lseVXsL++i1Rb5ESPaU5R6vdQocspZ5zQcrC0QqCQWpHKLGK1VYSNwpY2jvRwpIsjPKS2s699rbBp48kGBdkgL5rYJEggVGWausIhUeUkWXKnrROut04wpZtobXGMYQ4wjR5EyjYpFXqMpn2usyvM9NvU1r7B9Ttneffv/C7pygka+57kKye+zQF7kVzFwy6UiN0KrQOSxoNdVksTLE/PUusW6AVnzYbvRlQLPYa8LkN2jyHRo5IE+MstCocOEYzPEo9cPK9cCIGUMvsKSy36kaReLFIr5VjJeawWq6yVhgjdQfKt0hTWOriLXVQ9Jupn6SVT5R7D4wlSSqZX5pg99AT5Vo3Q9dm780YOX3sNldEWOznALg6wg0P4ZNlDQZKHpSLVg33GDzXJNVOUL+gN21REQLUQ4JWS9e1JoYHAk/RyFnXX5rhtcUDanOjl8I5OUlkpoSONFuAlKdO1NptqLYph/IxrAOAUEgpTIcXJkPxEiOVotILemk+7fQeR83rE8C0IyyXurbJae4LjvYMsOQEdzyfwPLQ1gsMI+cjBEhWErCKsMhLJqC2YcSRTrsAVggB4yhc8UerTzR9id/IYr+o/yJ7eUSSaFEHLLjKUtPns2Bv5F9v/Fxa8MX7pbz7MkOyzcstr2dVdZrq/wmi4zFCyTJU1CjSwdf8Z5xepHJH26NtTtPQ0jf4QrWiMrhpGoHhj+c+RIuWx7ru4sfAlfNni6JYc3/HuIM39M15x0xBtq8Fis87ClyX5wxWapYBHtqcsTk1QSiXVWDMahlx/ap5dxxewpkdwcikLvuZY3udwscz+whAH/QLJIOszr0Jmu4tMdNcodnvYPU2l26MQ9vFswfTYUGYMNm1lenqaU315Jtvgx14xyT99w87nfBc9X4wJWMeGmQCliD7+z0Da/PFEiY/P/Q3vf8UH+PVbf/2CVdya3R73HT7K9xaWeLLR5qTtUSuU6fhn86j9NGGrjtlpw2zU57pKkWsrRdrHj3Fo/z5Ora3Rx8paoFMKR6e0c5M8GE1xJPCZqeb5+Vdv4adfuYlqPnuZfunIl/jgdz7Ia2Zew5+84U9IujXso9/CXTsAq/th9SCsHQa17gVSmoLRXbSK23k8GOery1W+vFRmiSF2T5R41yafu/d/G+vzn0E1m/g33cjI+/8RpXvejLAs4jTm0eVHuX8hS+LfV9sHQMWtsLuyiaqMqAfLzPXqrMSgBonRAomIR3D6FcYil9tsyd12xCvDRQrdE8i0RQp0pKQ1GFasAmuWpp4TNHOCliVpkaefVOklRXrapiN7dKweXatPIp4ZyQst2BxOsi2YZqyXp9qO8WprLEd1ahSpO+MsedPMVwr08yGWt4j0F7D8BYSVvey1BmWNEHvbSd2tKC2ZrLW44ViB21aOc93T+xhfrgPQmxUEr0yJ7kxIi3CiPcuj87fx6OotzAdZ5JtPQ5wkpuPkSAcl72yt2EyPaRHga0WaKtI0pRmH9ElwyCFFgUTYJMIhkR5KSizZxxZ9bNlHiogUQYpFqHPE2ifBI8FB6awzmC1xQiWcY7j3FG+uOuzOH2TS3UdeZmUC+trnqNrKoXAb+9rjPJJMcyQ/w4pfRZ+uk681Q1GLra1VZrs1pnsN+rbHsdI4x4sjzBeGz5yXpVNmk1W20WSH02d3XnLNcJGZcgnbzyFcl0QIGr0e9U6H1VaLQ089TNRvM3GzyzEcDqU9btATTLm78V2Xhp9nzvY4ZBU57lVYKeVp5P0zNUbcJGa0UaO80kLUQ3o9i1qaJx4UChyiy6TV5oZwjlcef4rNx0+Q73RpuUVqfon2cJGkCtpuUrBCqhWX8uQIIk6ptOcYkcv4sktbeTTCPKthgdUwz1qYpxn7cOae13hejJeLcb0EVyc4XYXuWTSTIl2/gNAWbj8kkCmJJbFTxWSjy0hf4jBCLz9Ds7KNbn6KyK+gpAQUQonB57gGNIEr6PqKHf4prhOKkWQWQRFJE8v+Hvuqi3x+cjPfrtyJ7A6xeTVh80rM7FqCO/Dvsa0J3Ailmjj9Uzi9U6i0QZLrUJwO2e1NsznaQT66Bigi6OLIh6k5c+y3HY7Ia5hTu0mVy/+kP8zt3MtX1Hv4kvhRNu37Kw7teTU/uOVu1nyXhne2LIfQmslAc02rww2tZbZ3l5ntLTMarFKMV3HkGq6o4csV8rJ1JtsLoKUq1OIptnr7aPl59l7nsrrwLnoLP4b2LbAtLOGQS2wqsWYk1BSf5VsgViExfaStcFUZua4gqUbR99us+SEnfcHRvM/BQonD+TzzeUHTEeTSgKneKkPdDn43otrrMNxtM0bIzMAY7Lj2RjZt2nRxET8kxgSsYyOzAz6xsMonDn+VJ1Ye5jWTt/P2bffgS0knTVnqBxxerXOk1WE+Uay5ucHDCVKlDDXXmGisMNlaY3R1keqpE5Q7DS5UfM7N5RndvJXRTVvwxyd4arHBk6s97KRPdeCMIyR9zyUcGac/s5VkdJzA9WmnioV+g5UwQFgFFBaWgG05j915n90Fn12+ze60xo7OYfJr+2HlAKwOhrB1RkdkFTghZ3g8mOCwmqbtTLMnTLDrSzQ8i2bF50RxjYPFBVpuj1gE7Gq63Nlxub6Q4E91CCd6IMBdk5T22zjzijUSFkcU81XBsYLgkOswb9vo0y9sBUOpQ0cqutazf6lbGvJC4FspOUtTUJJix6Fc8yivOBT6mkI/pdBLyfcSCv2UEWsH1sQt2MPbKPjjKEtz1J/nsDfHgdwJDnsnWPBWSEWW3G+nMNyG8YZieg1m6orNfZuyM4RteUgBdhKTW2uRm+sjNESbFP3bFb0bLdbSTTywcCePN7cxnwwTCWdQN+zsv1/SmjGlGE4TxlTAOD3GrC6eE2M5KSopEveHCet7SYNHsPxX4uReiyBl1DnIrPsUs+6TTLl7cUSIBhatIY46FQ6JHAvaxiNmMqkymkxRUlPYyRQhVeaSVU4ev5eoMooauQk/HCEXjlCmxqSzj03efqadfZTsrKyG1pJIbaOb7mI+3s4TyQ6+myj26x5td4w1p0w8MAfVJGQ8XKMYL7G1W+NHTi6yuXYCN+0jdIyVJljP453U9hzuu2YTY+0QxypxZGYTR2Y2Z8P0ZgI/a7cerRltReyYP8Lm+cM4qz1akcdJb4RjlWn6dpYKMBG22NlrsqMbsjvuUbX7eF6fgtWgKFYoyBp5u0nObuO5PVwvxBpk/6RaUAtzrIUFloICq0GBWpinnXpnCrIKNPm8wKkqxEiXwmhA0K/SapdoNW2iroMMU/ywh50+s5YEWqOFpO8XWR2eRTtD5JMC5TBPObXxKz3ccpNkaBnh9nGCHDLMk0Z5VJwnlXmqVomtSY6RME+c5vjOmMv3J1qMpw9w08IK1bU89WAHK/EOFDag8IsL+OMHyY0ewfKbeJV5nFwbJ1JU2jGFRUmpphhRHexBxNuIfBZ1mXbhVqz8K8mrKlp0SHM9oomY5lBALdchiNZ41ZPfY+fKGnPDBfrKopsbRqk8OnBQgUMvKdKWQ7ScITq+S9u3aXg2kS1BS3KpoBwLJvowFgqGQ0E50RTSGE8ILBVQlv8VSzQ4MV3lyBaPyad/kdLSK7N3moCWowhln1R00KqDSDqkUUC7K+hGAVFaJ0zqBGmXUPVR56UW5qwSRadC0Rmi4g1TdCsUnDI5WcHj3OqckRWzmouYz1kcyfscy3uczElO5iV1p0+536TcDXibPslv/9yvPudz8Hz579oECCHeCvwJYAEf1Vr/62fbfqNMgNaa67/+t3SSMdw4Qmo1eEjzJOuami2364ytLTFay4ax2hLDjVUCz6dXrNAvlIlKRcJCjrjokxQd4oJF6iicZoRX65JfbVJaqzNUW8OPzpYobxar1IbGiHMFHMumkiQ4lgVCUPcLrBZK9CpD2KPjhHaXp7qPsWd4M3fNvplD/ZAD3azBodPt8gtgk++yM+exzY0Y7S/j1Y/B6lG69TqdXkwYS1TqIJWLm3rIC5aMVpTKq4wMzzFTPsaIblDop3h1m0ILimGfnDxbrlhrSaImSNhCrDcRqxk6ocshtcJR+wRH/CUOVl0Oje+mWZpgqNXj1qeeoNCLGRIOO4eGmaqMM12dpJofw7VLpKpHQz5J03madv4oyooRiU20PMXi0gwH6ps46RepFR3sZAErmSOwVmgUOjQLZ1/C1chnazrGZl1ma08w0+pT6jSwOl3sTojTiLHrGquepSicOSepCcdsDu/ZwhNTN3BQ7+BIOMqadonhTIQvtKasFFNRnYlgnpHgGCPRGjlZwM5vwc5vQdql7N/R2aCVRNp94t4jhLX9TI75bK5aTOuTzNiH8QjReNTkKKfsMRblNMtikkQXEcpFpB6kDmmaI9UeWjuAA9oGJOX2MaxgmZXNVfIji1Qrpyg6bdLuMK2Fm2jXttDrV3DpMeEcYNbfz4yzl2H7ILYYJIMzwlo0wb5an8S6ntLYW3BxmFt6hCO1p9lavIHbR9+CJRxSNAEQK02cQqQ0kU6pi4C5Yp+5XMBCMWapENPIuXT8PH1/iB956AFu2vswf/XuX6E2NE4hCpmsdxmpS8ZbNmP1BLcdc8rSHLNTVu0+JavOBHW2Ume3arKVBlM0KDp1claNsqidScpfTyQ82pRYjio02i7NtkWrZ9FMXdrSO2NYz+aEC6StKM12GLm2QXGme6Yq5QUeF2g7pLUiteMj1BZ8+u0solFWDkkBV0u8Uh9rqItTaeJVOviVCK8S4hTORkpaQ5pY2M6zm2WtQcUeaeSh4hxplCeNc0g0HgGlpM1Eskg+7SNjSTPYxHK4nYK7RjV3HNdrEduCyJF0fZfAh8gVxFhZeQ/n4vGKSG1kXEQFDmEvZfepRbb02kidWaYX2FTYRWlaZfbdYFNzyxx5+C6iVQfZb6F7LdLkmf81gJYO2vKRooikghAFLG1jaxuV1gjUXoryDrBzJHafRISkhAjVQ6gA0j4q7SMRFOwKRbtCwalStKuU3CoFp0rBqmCJs3GFRtNwYuZzFodHl/mVX3z3hl2D/25NgBDCAg4A9wDzwEPAz2itn77YPhtpAm769N+zPJo1h+kHvTMR/WhjlWp7lUJ/ldAN6ORTOvmYXqGP9gPyXkBVRgzrmCoxQ6SUlaaaQDnRFBNFLlEkCCIhiRAECEIBsRYkiUQnFjp0kIGN6FsksU0cW4SJTV96RKJAYpVJvCKptLH6LYqNGoXmCq6O6RTzdEo5WsUc3WKexPPRlpN1haosPCWRIgWRIkQKIkHIkNQO0FaEkAmWSJAyQYusdLqHYoeusTltMhZFjPRTvHVVDgMcFkWFJVFhWVRYZogVUaWmqyBsBD6B7dN0fTpenthyiaSDwkbECYV2jdnjT1AO54lsiPGxSBEiQMoAZcX0fUmj6NIqOLRzFj1PEDkKYfew6KFURKQ1+vxXjdZMJjl2dQQ72ilbmyFTjYhcTWCtCew1EIkEJwdugW5umNWRcdYqY9RyQ6z5FWpOnpp0qUmbFharSIIzX4IwDmxGsA3YRso2mTCFRq5PtVUK0jQbtBp8AQqUEGciGq01DllnSq7MkjKlcAAXhIu4SD335yJBo7TGHXy1azRaxii7h7L7xHaPjt0lcNtEThtl98AK0CJGWSHa7mF5dWy3hnR6aCshtUCfXz1UaSylEQqEEmhtkSqLRLtZ3i55uhToUCQgR09k8z2RByRSS2yt8PoRw198Ajnks2VXRDVukoaCTugQJQKZKPL0qcouFdHBk3F2iaXI/BSCVAoSRxJLSWJLUluQWJLEEqSWIIwl/RWXoO4TBHl04kDsQmKTB/KFFG8UvDELP+fiOjlI8gSrHt0VQdhWSGHh+znK+TJjvkdOp4gkRTmQeoJ2HFLv9mm3Y7TbQw61sYYjZDGFfAdRXETmVxHrO37qu9irDnLNRdd9+u0yjWiUejxMyRlnu7+Jyfww2glo6DkWk32sqCMou4flplieysauwvLOGw/WPx/SSJKGFkmQDWlgkYTrpk8vDy2SwEYFDmPONjYV9jCT34Vn5YhUQDNa9SOpmgAADvtJREFUxbPy5KwCtnRQTofErZF6a8R+jcStETmrxG4N5TbQXhvhZalsDLobF1qjU0Has0h72XEFIK4JaZ0qcOxrU6QBWCpF6hQnTfEThZ9ofOXgqBy2ziNFESULJFaR2C4SukM0K9tInALoFK0TwuZfYHm34uRfl10IrbDSECsNsNIIqWJEGiNUgKaH0n1S+ihClAjQBKQixLEsfCtPwS6fMQkFp0rdPsmb/tD0IvicCCFeDfzfWuu3DOb/OYDW+l9dbJ+NzA649399JyOygacCHBHhEGOLGEsk2CLGFim2SAbjlOdZVf6SoRWoQT6hkBohQFy8ivMLphdKmoFDI7KphTZricNqYtPQ2cs1sSCxIB5Mx4P5M8ttSORgbAkSAQiJowVOKnBTiZ0KHCVxlMBOs7GTSmwlsVMHJ3GwUwtbnR5bWMrK1iuBI8AGXK0pK5uylmB7NHIV6n6Juluk5uSyQXo0hE0di5qS1LVFfIHvFQfFsBUxLAOqVp9Ru8MWp8lmt86M28C1I1KhUTJFCY2WKUoolEzRUqFlCjIzXtm0yuZlNi/EYL3MqgFqsv8yMxDijJHQiDOFKc9Oi3Xbn1Np8Jz1Ao1lxdh2jGXHyGfpcfA0OvEQiY9IcojER8Z5rCSHTPJYcR6RONixRJCQuhGpHaGtAG2HaCsblB2i7WgwHaGseHCez41OZVbN8XnUJ99IROoiEx+Z+s8y9hBp7px5meYQyibxV4kKi0T5RaLCElF+EW2H54Tv9iZwu5M4vUnc7iRubxK3O4GVXLzVQIAo7LLUbXGEPA05aGI3qFNpHaTUOkyhcwwvWEFJSKQkth16fpWeXyXwS4RejjhnQU5hOV2kG2DbPVTsoqIcOixAXMDSHrZwsKWNLWxcmdUWcqSNJxxc6eDJbLktHCxhY8nBWNjn9OtwMbTWKK2ItSZKE2KVkKiYOO2RuGsod43UW0P7dbTfBL+FLnSg0IdchHhiDL55A4ldJXKLxG6JyCkSO3kSO09i+WgJoNBCgVRoFIoELfpoEaBFgEISUwShsdJ5tF7BP224tQCdZVFkz5yF1jZZE1N21gCVGMxrSWZbstoZWSpfCioCHSLSHuW4zwf+8795AXflhXk2E/DCPhmuHGaAuXXz88CrLtfBC6VltiYn6AuXAI8OHn2RI8CjJzwCXPp49MXpcbbs3HXeuWM8AuES4GKhcIhxGBQY4vSQ4ugEl3XLdHpmW4d03ban152dl1qTCIsEixR5diwsEp1Np1jrtjm7XTLYLuXc/RMsYmFzUozRzb+4jnYuhD5/4vw4WK9bptflbzxXvKAhjQVpJFHxhV9I0lLYnsLyFLabUPCibN4dLDs9bWfGKgFWsVmlyn4qwOZ1hzs3Ij4beYuLLzs/El+X7XC6vv+Zc193XcQ5J6/PG59Rc/7lAGy0stChRGuB1mfHSoPm9LwYaDkvFJvn9WYR637RQAwiXr9+0N6BGFQfEypr90BohDjbHoIQ6pxrd+Zc1l/TwbqzV0GcM8/5BmlwzU8f/6wWdaZthtPHFrYCR69rs0GdXSeezchMAJMoZaFSB5XYpKGNUjZp6qDVIP/AHQxVPTgNAYQXCXNwCbQNDA8u72nTWEZwG3D7+st0Hueu0Bddc6G9NGdvR33OI8m6j02hNZoEQTLYfJANcM4OFzra6WUWCAvws3PkmU2cnyEYrN51+nye7YVgDYb1XKydk6mLLN8Y9pyq8YFLeoSzvNxNwIXulGf8y0KIXwR+EWDz5s3P2OGF8sv536QR5J97w2fjQu/m580LTFo4fzfxLOvOoC84ebFNLgU/1NkODIAmqyp2vnlYL1X6YJdBOgrpgnQF0hEIB6QDQmZu/nRknO0vSDQkCMIUdHBe5A5nXL5GnnX8gzIUzzyX9fs92xmLZ9/3uTib7wBotFbZtFZnDixkflBm4UIm4vz5dWNx+pV+gf3OkXjhG+WcpeIC2+gLB3c6BePit9+zH088y57rj/nMfZ/vdddnzAtnjAJoJVFKXsCKDVLonuFJ5aCa59ljn7vnunIJ4uz/sX77i0u88P97vsW7oK1cXxtKrNvznEOKc/Y584BepLOwF59o+mxPiT5n9IKOpxyEWtf14nn367PNnbP8ggfWKJo/rKIXzMvdBMwD6+tRzAIL52+ktf4I8BHIsgM26uAP/eZPb1RQBoPBYDBcdi5BjvBl5SFglxBimxDCBd4DfP4l1mQwGAwGw8uCl3VKgNY6EUL8CvBlssyc/6C1fuollmUwGAwGw8uCl7UJANBafwn40kutw2AwGAyGlxsv9+wAg8FgMBgMLxBjAgwGg8FguEoxJsBgMBgMhqsUYwIMBoPBYLhKMSbAYDAYDIarFGMCDAaDwWC4SjEmwGAwGAyGqxRjAgwGg8FguEoxJsBgMBgMhqsUYwIMBoPBYLhKMSbAYDAYDIarFGMCDAaDwWC4SjEmwGAwGAyGqxRjAgwGg8FguEoxJsBgMBgMhqsUobV+qTVcVoQQK8Dxl1rH82QUWH2pRfyQGM2XB6P58mA0Xx6M5kvLFq312IVWXHUm4OWEEOIftNa3v9Q6fhiM5suD0Xx5MJovD0bzS4fJDjAYDAaD4SrFmACDwWAwGK5SjAm4svnISy3gBWA0Xx6M5suD0Xx5MJpfIkyZAIPBYDAYrlJMSoDBYDAYDFcpxgRcRoQQm4QQ9woh9gohnhJC/Npg+bAQ4qtCiIOD8dBguRBC/KkQ4pAQ4gdCiFsHy28WQnx3EMYPhBA/faVrXhdeWQhxUgjxZy8HzUKIzUKIrwzCeloIsfVloPn3B2HsHWwjrhDNewb3bSiE+K3zwnqrEGL/4Hw+eCn0bqTmi4VzJWteF54lhHhUCPGFl4NmIURVCPFpIcS+QXivfhlo/o1BGE8KIf6rEMK/FJo3BK21GS7TAEwBtw6mS8AB4Drg94EPDpZ/EPg3g+m3AX8HCOBO4PuD5buBXYPpaeAUUL2SNa8L70+AjwN/dqVf58G6bwL3DKaLQP5K1gz8CHA/YA2G7wJvuEI0jwOvBP4l8FvrwrGAw8B2wAUeB667wjVfMJwrWfO68H5z8Ax+4VLo3WjNwP8H/OPBtMuV86672L0xAxwFcoP5/wa871Jd6xc7mJSAy4jW+pTW+pHBdBvYS3bD/DjZjc5g/BOD6R8HPqYzvgdUhRBTWusDWuuDg3AWgGXggg1BXCmaAYQQtwETwFcuhdaN1iyEuA6wtdZfHYTV0Vr3rmTNgAZ8spelBzjA0pWgWWu9rLV+CIjPC+oO4JDW+ojWOgI+MQjjitX8LOFcsZoBhBCzwNuBj14KrRutWQhRBl4H/PvBdpHWunElax5gAzkhhA3kgYVLoXkjMCbgJWKQrHwL8H1gQmt9CrIbkcxhQnYDzq3bbZ7zXjRCiDvIXviHL63iF6dZCCGBPwJ++1LrXM+LvM67gYYQ4q8Hyad/IISwrmTNWuvvAveSpQ6dAr6std57hWi+GM95n18KXqTmi4VzSdkAzR8GfgdQl0jiM3iRmrcDK8BfDZ7BjwohCpdQLvDiNGutTwJ/CJwgewabWutL+uHzYjAm4CVACFEEPgP8uta69WybXmDZmeocgy+//wS8X2t9SR/qDdD8T4Evaa3nLrD+krABmm3gtcBvkSX7bQfet8EyzxXyIjULIXYC1wKzZBHp3UKI12280nVCnr/miwZxgWWXtNrSBmje0HAux7GEEO8AlrXWD2+4uIsf88VeHxu4FfgLrfUtQJcsSf6SsQHXeYgs9WAbWXZtQQjxcxurcuMwJuAyI4RwyG6w/6K1/uvB4qV1SeZTZMn7kH0RbVq3+yyDZKVBMtkXgd8dJAdf6ZpfDfyKEOIYmUv+eSHEv77CNc8Djw6SqRPgs2QvpCtZ808C3xtkXXTIyg3ceYVovhgXvc8vBRuk+WLhXBI2SPNrgHcNnsFPkBnE/3yJJG/kvTGvtT6dyvJprpxn8GK8GTiqtV7RWsfAX5OV1bkiMSbgMiKEEGR5W3u11n+8btXngV8YTP8C8Ll1y39eZNxJlqx0SgjhAn9Dlif8qZeDZq31z2qtN2utt5J9WX9Ma31JHP1GaQYeAoaEEKfLW9wNPH2Faz4BvF4IYQ9eaK8ny9u8EjRfjIeAXUKIbYN7+z2DMDacjdL8LOFsOBulWWv9z7XWs4Nn8D3AN7TWl+QLdQM1LwJzQohrBovexJXzDF6ME8CdQoj8IMw3cYmewQ1BXwGlE6+WAbiLLJnzB8Bjg+FtwAjwdeDgYDw82F4Af06W3/8EcPtg+c+RFUZ5bN1w85Ws+bww38elrR2wYZqBewbhPAH8R8C9kjWTlbT/d2QvnaeBP76CrvMk2ZddC2gMpsuDdW8jK419GPjfr3TNFwvnStZ8Xphv4NLWDtjIe+Nm4B8GYX0WGHoZaP4QsA94kizL1rtU1/rFDqbFQIPBYDAYrlJMdoDBYDAYDFcpxgQYDAaDwXCVYkyAwWAwGAxXKcYEGAwGg8FwlWJMgMFgMBgMVynGBBgMhhfMoJ2C+4QQP7Zu2buFEH//UuoyGAzPD1NF0GAwvCiEEDcAnyJra90iq1/9Vq31C+7PQghh66yVRoPBcAkxJsBgMLxohBC/T9auewFoa63/hRDiF4BfJuvg6gHgV7TWSgjxEbKmX3PAJ7XWvzcIY56soaO3Ah/Wl7g1TIPBkHXOYDAYDC+WDwGPABFw+yB14CeBH9FaJ4OI/z1k/dh/UGtdE1k3q/cKIT6ttT7dFGxXa/2al+IEDIarEWMCDAbDi0Zr3RVCfBLoaK1DIcSbyXpe/Ies+XRynO0u+GeEEB8ge/9MA9dxtj34T15e5QbD1Y0xAQaDYaNQnO2nXgD/QWv9f6zfQAixC/g14A6tdWPQi52/bpPuZVFqMBgAUzvAYDBcGr4GvFsIMQoghBgRQmwm63ynDbQG3bK+5SXUaDBc9ZiUAIPBsOForZ8QQnwI+JoQQpL1evlLZL3BPU3Wu9oR4P6XTqXBYDC1AwwGg8FguEox2QEGg8FgMFylGBNgMBgMBsNVijEBBoPBYDBcpRgTYDAYDAbDVYoxAQaDwWAwXKUYE2AwGAwGw1WKMQEGg8FgMFylGBNgMBgMBsNVyv8PGGjB1HtXhIIAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 576x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eO5VEptq0DTg",
        "colab_type": "text"
      },
      "source": [
        "#### This is a very untidy interpretation of the data. Let us take the top 10 sectors which are most invested in since 2000.\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RnJXsyUo0DTg",
        "colab_type": "text"
      },
      "source": [
        "# Analysing the current top 5 sectors which are the most invested in."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Yorark6G0DTh",
        "colab_type": "code",
        "colab": {},
        "outputId": "8c1eb290-f44f-4cc7-93c6-5a7698b6bed2"
      },
      "source": [
        "def avg_sector(df=dataframe,number=5):\n",
        "    data = df.copy(deep=True)\n",
        "    data['avg'] = pd.Series()\n",
        "    for sector in data.index:\n",
        "        data['avg'] = data.mean(axis=1)\n",
        "        top_df = data.sort_values(by='avg',ascending=False,inplace=False)\n",
        "    top = top_df.head(number).index\n",
        "    top_df.drop(columns=['avg'],axis=1,inplace=True)\n",
        "    return top\n",
        "\n",
        " \n",
        "avg_sector(dataframe)\n",
        "\n",
        "top_sectors = avg_sector()\n",
        "df_top = df[top_sectors]\n",
        "plot_data(data=df_top, x= 'Year', y= 'Amount is million USD',t= 'FDI IN TOP 5 SECTORS OF THE COUNTRY')"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 576x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "HcgpN2G20DTj",
        "colab_type": "text"
      },
      "source": [
        "### These are the top 5 sectors which have received the most foreign investments in the past 19 years. It can be seen that most of these sectors have an 100%+ increment in investments. Few have remained stagnant while some industries like Construction Development has gone down."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KymIoP-60DTk",
        "colab_type": "text"
      },
      "source": [
        "# Does government have anything to do with FDIs?"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3nipkykt0DTl",
        "colab_type": "text"
      },
      "source": [
        "## Analysing how FDIs have changed pre and post Modi government"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "glJ-8ZUI0DTl",
        "colab_type": "code",
        "colab": {},
        "outputId": "fbbb4ea1-b36f-4ac9-9774-befa6d61fb4e"
      },
      "source": [
        "pre = df.loc[:'2013']\n",
        "post = df.loc['2014':]\n",
        "\n",
        "top_pre = avg_sector(pre.transpose())\n",
        "top_post = avg_sector(post.transpose())\n",
        "\n",
        "pre = pre[top_pre]\n",
        "pre.loc['Total',:] = pre.sum(axis=0)\n",
        "# print(pre.loc['Total'])\n",
        "\n",
        "post = post[top_post]\n",
        "post.loc['Total',:] = post.sum(axis=0)\n",
        "# print('\\n')\n",
        "# print(post.loc['Total'])\n",
        "\n",
        "\n",
        "plt.figure(figsize=(20,10))\n",
        "sns.barplot(x=pre.columns,y= pre.loc['Total'])\n",
        "plt.xticks(np.arange(0,5,1),labels=['SERVICES SECTOR','CONSTRUCTION DEVELOPMENT','TELECOMMUNICATIONS','COMPUTER SOFTWARE & HARDWARE','DRUGS PHARMACEUTICALS'], rotation=75)\n",
        "plt.title('FDIs in different sectors before 2014')\n",
        "plt.ylabel('Total amount in million USD')\n",
        "plt.plot()\n"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 1440x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JYL127T70DTq",
        "colab_type": "code",
        "colab": {},
        "outputId": "1b9cb0a0-a14d-405b-b473-fa7e4250b96b"
      },
      "source": [
        "\n",
        "plt.figure(figsize=(20,10))\n",
        "sns.barplot(x=post.columns,y= post.loc['Total'])\n",
        "plt.xticks(np.arange(0,5,1),labels=['SERVICES SECTOR','COMPUTER SOFTWARE & HARDWARE','TELECOMMUNICATIONS','TRADING ','CONSTRUCTION (INFRASTRUCTURE) ACTIVITIES '], rotation=75)\n",
        "plt.title('FDIs in different sectors after 2014')\n",
        "plt.ylabel('Total amount in million USD')\n",
        "plt.plot()\n"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAABJ4AAAM9CAYAAADdPLkkAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjEsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy8QZhcZAAAgAElEQVR4nOzdfdhudVkn/O8piJqKgOxMeREfxafQp1AJnPGlHiwFK6FGGphGsbHQkimPnPGlGcdSsWwepSxfspFE6xEZyyQHY8iXzAoElFQkY6cmCAq2AaESeTnnj2ttvdreL9fe7N+9933z+RzHdVzXOtdvrXWuffOHfo/f+q3q7gAAAADAzna3Xd0AAAAAABuT4AkAAACAIQRPAAAAAAwheAIAAABgCMETAAAAAEMIngAAAAAYQvAEAKyZqjq4qm6uqj120vm6qh42/X5TVb10bt/PVNWXp+vdv6oeV1VXTNvH74zrs5iqekBVfbiqbqqq1+zqfgCAtSN4AoC7qKr6fFX98xTEbP08qKoOmQKdrbUvV9V7q+oHlzj+B7bnmt39he6+T3ffvnPvJunu53b3K6be7p7ktUmePF3vH5K8PMlvTdt/tLOvv5KqelZVfWSNr/lLVfV7a3nNFZyS5CtJ9u7uF4zorapOrqpLquqrVXVVVf1aVe05t3+/qnp3Vf1jVf19Vf27uX0PrKpzqurq6b/9Q5a5xn5Vdd1a/y0BYD0TPAHAXduPTEHM1s/Vc/v26e77JPmeJOcneXdVPWuXdLn9HpDknkkum6s9eJvthc0HGHcVO/meH5zk093dO+Nky/T2bUmen2T/JEcleVKS/zS3//VJvp7Zfxs/keSNVfWIad8dSf4kyb9Z5dKvTnL5jncOAHc9gicAYEXd/aXu/o0kv5Tk1VX1Lf/7oaoeVlV/VlU3VtVXquqdS51rbjbVntP2h6rqFVX1F9NjWP+7qvZfrpeq+s9Vdc00M+U/bLPvrVX1yqp6eJLPTOUbquoDVfV3Sf6vJH88zeK6R1Xdr6reMp3vi9Oxe0znetbU0+lVtWW691TVf6iqy6vq+qo6r6oePHf9rqrnTo/zXV9Vr6+Z70rypiT/arr2Dcvc27Oq6rPTv8Pnquon5vatdN1HVNX5VbVlmp32i1V1TJJfTPJvp2v+9TT2QdPMni1VtbmqfnruPL9UVe+qqt+rqq8meVZVHVlVF0+ziL5cVa9dpvd9p1lx1009vreqDtz6d0lycpIXTr388DK9bfffY153v7G7/7y7v97dX0zy+0keNx1/78xCpZd2983d/ZEk5yR5xnTsl7v7DUkuWur+pnP8qySPTPK7y40BAL6V4AkAWNQfJvn2JP/3EvtekeR/J9k3yYFJfnM7zvvvkvzkdO698i9nqXzDFKb8pyQ/mOTQJEs+5tfdf5tk60yWfbr76O5+aJIv5JszvG5JcmaS25I8LMmjkjw5yU/NneqoJJ+d+jqtZutC/WKSH0uyKcmfJ3nHNpf/4STfm9kssR9P8pTuvjzJc5P81XTtfZa4t3sneV2SY7v7vkn+dZJLp33LXreq7pvkTzObrfOg6V7e391/kuRVSd45XfN7pku9I8lV09inJ3lVVT1prpXjkrwryT6ZBTe/keQ3unvvJA9NcvZS/+aZ/W/K381sZtPBSf45yW8lSXc/azrXr029vHeZ3rbr77FMH/OemG/OcHt4ktun/za2+ut887+TFU0B2OuTnJpkp8zaAoC7CsETANy1/VFV3TB9Vlv3aOtjePstse/WzEKHB3X316YZJYv63e7+2+7+58yCjcOXGffj09hPdfc/ZolZL4uqqgckOTbJ87v7H7v72iSnJzlxbtjV3f2b3X3b1NtzkvxKd1/e3bdlFp4cPj/7KMmvdvcN3f2FJB9c4V6WckeSR1bVvbr7mu7eGpqsdN0fTvKl7n7N9O9+U3dfuMw9H5Tk8UleNI29NMn/yDTrZ/JX3f1H3X3HdM+3JnlYVe0/zRS6YKlzd/c/dPcfdPc/dfdNmQVD37foje/g32Ol8/1kkiOS/H9T6T5Jbtxm2I1J7rtgiz+X5MLuvmTB8QDARPAEAHdtx3f3PtNntTe9HTB9b1li3wuTVJKPVtVl2z4Gt4ovzf3+p8xCgqU8KMmVc9t/vx3X2NaDk9w9yTVbg7ckv53ZbJqtrlzimN+YG78ls3s+YG7MovfyL0xB2r/NbGbUNVX1v6rqOxe47kFJ/m6Ra2T277dlCoa2+vtt+t/2np+d2Wyhv6mqi6bH5L5FVX1bVf12zRbt/mqSDyfZpxZ/e+GO/D2WNM0Q+9XMZo99ZSrfnGTvbYbuneSmrKKqHpRZ8PRfFrk+APAv3eUWygQAdtiPJrk231w/6Ru6+0tJfjpJqurxSf60qj7c3Zt34vWvySxo2ergO3GuK5PckmT/aRbRUrZ9pOrKJKd19+/vwPVWfTyru89Lcl5V3SvJK5P8TpInrHTdadbTSQte8+ok+1XVfefCp4OTfHG5Y7r7iiQn1Wxdrx9L8q6quv8UlM17QWaPYB7V3V+qqsOTfDyzgGyR3nbk7/EtpscxfyfJD3X3J+d2/W2SPavq0OmektnjkIssNn9kkgcm+XRVJcm9ktyrqr6U5IARb2gEgI3EjCcAYEVV9YCqOjXJy5K8pLvvWGLMCVsXk05yfWYhwc7+P+RnZ7bg9WFV9W1TPzuku6/JbE2q11TV3lV1t6p6aFWt9HjYm5K8pKY3oU2LYZ+w4CW/nOTAqtprqZ3Tv/HTprWebslshs7Wf7+VrvveJN9RVc+v2YLp962qo+auecgUGqW7r0zyl0l+paruWVXfndmMpmWDtKr691W1afqbb10Ufam/630zW9fphqraL6v/bbbtbUf+Htv2evR0L/+muz86v28Kyv4wycur6t5V9bjM1rN6+9zx90xyj2nzHtN2krwvySGZPTZ5eJL/llmodrjQCQBWJ3gCAJZzQ1X9Y5JPJnlqkhO6+4xlxn5vkgur6ubM3hb28939uZ3ZTHe/L8mvJ/lAks3T953xzMwWM/90ZmHZuzKb2bLc9d+d5NVJzpoeJ/tUZusSLeIDmc2u+VJVfWWJ/XfLbNbQ1Zk9Svd9SX52tetOM5d+MMmPZPaY3xVJ/t/pnP9z+v6HqvrY9PukzEKUq5O8O8nLuvv8Ffo+Jsll09/1N5Kc2N1fW2Lcr2c2E+grSS7IbLHzlSzV23b9PZbw0iT3S3Lu9La8m6vqfXP7f3bq8drMFln/mbl1tJJZcHbz9Ptvpu109y3Tmx2/NM3suzHJrdNvAGAV1e3FHAAAAADsfGY8AQAAADCE4AkAAACAIQRPAAAAAAwheAIAAABgCMETAAAAAEPsuasbWGv7779/H3LIIbu6DQAAAIAN45JLLvlKd2/atn6XC54OOeSQXHzxxbu6DQAAAIANo6r+fqm6R+0AAAAAGELwBAAAAMAQgicAAAAAhhA8AQAAADCE4AkAAACAIQRPAAAAAAwheAIAAABgCMETAAAAAEMIngAAAAAYQvAEAAAAwBCCJwAAAACGEDwBAAAAMITgCQAAAIAhBE8AAAAADCF4AgAAAGAIwRMAAAAAQwwPnqpqj6r6eFW9d9p+SFVdWFVXVNU7q2qvqX6PaXvztP+QuXO8ZKp/pqqeMlc/ZqptrqoXj74XAAAAABa3FjOefj7J5XPbr05yencfmuT6JM+e6s9Ocn13PyzJ6dO4VNVhSU5M8ogkxyR5wxRm7ZHk9UmOTXJYkpOmsQAAAADsBoYGT1V1YJIfSvI/pu1KcnSSd01Dzkxy/PT7uGk70/4nTeOPS3JWd9/S3Z9LsjnJkdNnc3d/tru/nuSsaSwAAAAAu4HRM55+PckLk9wxbd8/yQ3dfdu0fVWSA6bfByS5Mkmm/TdO479R3+aY5eoAAAAA7AaGBU9V9cNJru3uS+bLSwztVfZtb32pXk6pqour6uLrrrtuha4BAAAA2FlGznh6XJKnVdXnM3sM7ujMZkDtU1V7TmMOTHL19PuqJAclybT/fkm2zNe3OWa5+rfo7jd39xHdfcSmTZvu/J0BAAAAsKphwVN3v6S7D+zuQzJbHPwD3f0TST6Y5OnTsJOTvGf6fc60nWn/B7q7p/qJ01vvHpLk0CQfTXJRkkOnt+TtNV3jnFH3AwAAAMD22XP1ITvdi5KcVVWvTPLxJG+Z6m9J8vaq2pzZTKcTk6S7L6uqs5N8OsltSZ7X3bcnSVWdmuS8JHskOaO7L1vTO9mFHvOf37arW4BVXfLfn7mrWwAAAGAXWpPgqbs/lORD0+/PZvZGum3HfC3JCcscf1qS05aon5vk3J3YKgAAAAA7yei32gEAAABwFyV4AgAAAGAIwRMAAAAAQwieAAAAABhC8AQAAADAEIInAAAAAIYQPAEAAAAwhOAJAAAAgCEETwAAAAAMIXgCAAAAYAjBEwAAAABDCJ4AAAAAGELwBAAAAMAQgicAAAAAhhA8AQAAADCE4AkAAACAIQRPAAAAAAwheAIAAABgCMETAAAAAEMIngAAAAAYQvAEAAAAwBCCJwAAAACGEDwBAAAAMITgCQAAAIAhBE8AAAAADCF4AgAAAGAIwRMAAAAAQwieAAAAABhC8AQAAADAEIInAAAAAIYQPAEAAAAwhOAJAAAAgCEETwAAAAAMIXgCAAAAYAjBEwAAAABDCJ4AAAAAGELwBAAAAMAQgicAAAAAhhA8AQAAADCE4AkAAACAIQRPAAAAAAwheAIAAABgCMETAAAAAEMIngAAAAAYQvAEAAAAwBCCJwAAAACGEDwBAAAAMITgCQAAAIAhBE8AAAAADCF4AgAAAGAIwRMAAAAAQwieAAAAABhC8AQAAADAEIInAAAAAIYQPAEAAAAwhOAJAAAAgCEETwAAAAAMMSx4qqp7VtVHq+qvq+qyqvrlqf7WqvpcVV06fQ6f6lVVr6uqzVX1iap69Ny5Tq6qK6bPyXP1x1TVJ6djXldVNep+AAAAANg+ew489y1Jju7um6vq7kk+UlXvm/b95+5+1zbjj01y6PQ5KskbkxxVVfsleVmSI5J0kkuq6pzuvn4ac0qSC5Kcm+SYJO8LAAAAALvcsBlPPXPztHn36dMrHHJckrdNx12QZJ+qemCSpyQ5v7u3TGHT+UmOmfbt3d1/1d2d5G1Jjh91PwAAAABsn6FrPFXVHlV1aZJrMwuPLpx2nTY9Tnd6Vd1jqh2Q5Mq5w6+aaivVr1qivlQfp1TVxVV18XXXXXen7wsAAACA1Q0Nnrr79u4+PMmBSY6sqkcmeUmS70zyvUn2S/KiafhS6zP1DtSX6uPN3X1Edx+xadOm7bwLAAAAAHbEmrzVrrtvSPKhJMd09zXT43S3JPndJEdOw65KctDcYQcmuXqV+oFL1AEAAADYDYx8q92mqtpn+n2vJD+Q5G+mtZkyvYHu+CSfmg45J8kzp7fbPTbJjd19TZLzkjy5qvatqn2TPDnJedO+m6rqsdO5npnkPaPuBwAAAIDtM/Ktdg9McmZV7ZFZwHV2d7+3qj5QVZsye1Tu0iTPncafm+SpSTYn+ackP5kk3b2lql6R5KJp3Mu7e8v0+2eSvDXJvTJ7m5032gEAAADsJoYFT939iSSPWqJ+9DLjO8nzltl3RpIzlqhfnOSRd65TAAAAAEZYkzWeAAAAALjrETwBAAAAMITgCQAAAIAhBE8AAAAADCF4AgAAAGAIwRMAAAAAQwieAAAAABhC8AQAAADAEIInAAAAAIYQPAEAAAAwhOAJAAAAgCEETwAAAAAMIXgCAAAAYAjBEwAAAABDCJ4AAAAAGELwBAAAAMAQgicAAAAAhhA8AQAAADCE4AkAAACAIQRPAAAAAAwheAIAAABgCMETAAAAAEMIngAAAAAYQvAEAAAAwBCCJwAAAACGEDwBAAAAMITgCQAAAIAhBE8AAAAADCF4AgAAAGAIwRMAAAAAQwieAAAAABhC8AQAAADAEIInAAAAAIYQPAEAAAAwhOAJAAAAgCEETwAAAAAMIXgCAAAAYAjBEwAAAABDCJ4AAAAAGELwBAAAAMAQgicAAAAAhhA8AQAAADCE4AkAAACAIQRPAAAAAAwheAIAAABgCMETAAAAAEMIngAAAAAYQvAEAAAAwBCCJwAAAACGEDwBAAAAMITgCQAAAIAhBE8AAAAADCF4AgAAAGAIwRMAAAAAQwieAAAAABhC8AQAAADAEMOCp6q6Z1V9tKr+uqouq6pfnuoPqaoLq+qKqnpnVe011e8xbW+e9h8yd66XTPXPVNVT5urHTLXNVfXiUfcCAAAAwPYbOePpliRHd/f3JDk8yTFV9dgkr05yencfmuT6JM+exj87yfXd/bAkp0/jUlWHJTkxySOSHJPkDVW1R1XtkeT1SY5NcliSk6axAAAAAOwGhgVPPXPztHn36dNJjk7yrql+ZpLjp9/HTduZ9j+pqmqqn9Xdt3T355JsTnLk9Nnc3Z/t7q8nOWsaCwAAAMBuYOgaT9PMpEuTXJvk/CR/l+SG7r5tGnJVkgOm3wckuTJJpv03Jrn/fH2bY5arL9XHKVV1cVVdfN111+2MWwMAAABgFUODp+6+vbsPT3JgZjOUvmupYdN3LbNve+tL9fHm7j6iu4/YtGnT6o0DAAAAcKetyVvtuvuGJB9K8tgk+1TVntOuA5NcPf2+KslBSTLtv1+SLfP1bY5Zrg4AAADAbmDkW+02VdU+0+97JfmBJJcn+WCSp0/DTk7ynun3OdN2pv0f6O6e6idOb717SJJDk3w0yUVJDp3ekrdXZguQnzPqfgAAAADYPnuuPmSHPTDJmdPb5+6W5Ozufm9VfTrJWVX1yiQfT/KWafxbkry9qjZnNtPpxCTp7suq6uwkn05yW5LndfftSVJVpyY5L8keSc7o7ssG3g8AAAAA22FY8NTdn0jyqCXqn81svadt619LcsIy5zotyWlL1M9Ncu6dbhYAAACAnW5N1ngCAAAA4K5H8AQAAADAEIInAAAAAIYQPAEAAAAwhOAJAAAAgCEETwAAAAAMIXgCAAAAYAjBEwAAAABDCJ4AAAAAGELwBAAAAMAQgicAAAAAhhA8AQAAADCE4AkAAACAIQRPAAAAAAwheAIAAABgCMETAAAAAEMIngAAAAAYQvAEAAAAwBCCJwAAAACGEDwBAAAAMITgCQAAAIAhBE8AAAAADCF4AgAAAGCIPXd1AwC72hde/v/s6hZgRQf/t0/u6hYAAGCHmPEEAAAAwBCCJwAAAACGEDwBAAAAMITgCQAAAIAhBE8AAAAADCF4AgAAAGAIwRMAAAAAQwieAAAAABhC8AQAAADAEIInAAAAAIYQPAEAAAAwhOAJAAAAgCEETwAAAAAMIXgCAAAAYAjBEwAAAABDCJ4AAAAAGELwBAAAAMAQgicAAAAAhhA8AQAAADCE4AkAAACAIQRPAAAAAAyx52oDquq+SR42bV7R3TePbQkAAACAjWDZ4Kmq9kryhiQ/nuTzmc2OOrCqzk7yvO6+dU06BAAAAGBdWulRu/+S5D5JDuzu7+7uRyZ5cJJ7J/mva9EcAAAAAOvXSsHTjyX5qe7+6tZCd9+Y5LnTPgAAAABY1oqLiy+1nlN335Skh3UEAAAAwIaw0uLid0wLi9cS+wRPAAAAAKxopeDp/kkui+AJAAAAgB2wbPDU3QeuZSMAAAAAbCzLrvFUVQdV1d5z20+sqtdU1X+sqruvTXsAAAAArFcrLS7+P5PsnSRV9T1J3p3k2iRHJXn9+NYAAAAAWM9WWuPp27r7qun3v09yRne/uqruluSvx7cGAAAAwHq20oyn+UXFj07y/iTp7juywOLi06N6H6yqy6vqsqr6+an+S1X1xaq6dPo8de6Yl1TV5qr6TFU9Za5+zFTbXFUvnqs/pKourKorquqdVbXX4rcOAAAAwEgrBU9/VlX/f1W9JrM33H0gSarqO5LcusC5b0vygu7+riSPTfK8qjps2nd6dx8+fc6dzntYkhOTPCLJMUneUFV7VNUemT3ad2ySw5KcNHeeV0/nOjTJ9UmevfCdAwAAADDUSsHTzyU5N8mXkjyhu78+1R+U5KWrnbi7r+nuj02/b0pyeZIDVjjkuCRndfct3f25JJuTHDl9Nnf3Z6cezkpyXFVVZjOx3jUdf2aS41frCwAAAIC1sewaT9Mjdb+3RP1j23uRqjokyaOSXJjkcUlOrapnJrk4s1lR12cWSl0wd9hV+WZQdeU29aMym4V1Q3fftsT4ba9/SpJTkuTggw/e3vYBAAAA2AHLzniqquurasvc5x+mdZbeVFX7LnqBqrpPkj9I8vzu/mqSNyZ5aJLDk1yT5DVbhy5xeO9A/VuL3W/u7iO6+4hNmzYt2joAAAAAd8JKj9rtn2TT3Ofbkzw+yd8ledMiJ6+qu2cWOv1+d/9hknT3l7v79mlG1e9k9ihdMpuxdNDc4QcmuXqF+leS7FNVe25TBwAAAGA3sGzwNIVD236u6+7/nuTQ1U48rcH0liSXd/dr5+oPnBv2o0k+Nf0+J8mJVXWPqnrIdI2PJrkoyaHTG+z2ymwB8nO6u5N8MMnTp+NPTvKeBe8bAAAAgMGWXeNpOdMMoz0WGPq4JM9I8smqunSq/WJmb6U7PLPH4j6f5DlJ0t2XVdXZST6d2Rvxntfdt0/XPDXJedN1z+juy6bzvSjJWVX1yiQfzyzoAgAAAGA3sGzwVFVPW6K8b2Yzjv5otRN390ey9DpM565wzGlJTluifu5Sx3X3Z/PNR/UAAAAA2I2sNOPphG22O8k/JHlTd3ukDQAAAIAVLRs8dfcz1rIRAAAAADaWld5qBwAAAAA7TPAEAAAAwBCCJwAAAACGWGlx8SRJVe2V5Pgkh8yP7+5XjWsLAFhvHvebj9vVLcCK/uI//sWubgEA7nJWDZ6SvDvJ15JckuT2se0AAAAAsFEsEjw9uLsfObwTAAAAADaURdZ4uqCqDhveCQAAAAAbyiIzno5K8vGq2pzkliSVpLv70UM7AwAAAGBdWyR4On54FwAAAABsOKs+atfdf5fkXkl+cPrcc6oBAAAAwLJWDZ6q6tQkZyc5ePqcXVU/O7oxAAAAANa3RR61OyXJkd19c5JU1auS/GWSN4xsDAAAAID1bZG32lWSW+e2b51qAAAAALCsRWY8vT3JBVX1B9P2jyY5c1xLAAAAAGwEqwZP3f1rVfXBJE/IbKbTc7v7ouGdAQAAALCuLRs8VdW9u/sfq2rvJJ+ZPlv37d3dX12LBgEAAABYn1aa8fSuJMcmuSxJz9Vr2j54YF8AAAAArHPLBk/dfez0fdDatQMAAADARrHSo3bfvdKB3f2Jnd8OAAAAABvFSo/avX6FfZ3kiTu5FwAAAAA2kJUetXvCWjYCAAAAwMay0qN2T1vpwO4+Z+e3AwAAAMBGsdKjdiessK+TCJ4AAAAAWNZKj9o9Yy0bAQAAAGBjWelRu5O6+x1V9XNL7e/u141rCwAAAID1bqVH7fadvjetRSMAAAAAbCwrPWr3hun7pWvXDgAAAAAbxUoznpIkVXVwklOTHDI/vrt/bFxbAAAAAKx3qwZPmb297m1Jzk9yx9h2AAAAANgoFgmevt7drx3eCQAAAAAbyiLB029W1X9Ncl6SW7YWu/sTw7oCAAAAYN1bJHh6eJKfSnJsvvmoXSd54qimAAAAAFj/FgmefjzJId19y6ojAQAAAGBytwXGfCLJfUc3AgAAAMDGssiMp/sn+ZuqujD/co2nHxvWFQAAAADr3iLB02nDuwAAAABgw1k1eOru969FIwAAAABsLIus8QQAAAAA203wBAAAAMAQgicAAAAAhlh1jaeqemySlyV58DS+knR3P3xwbwAAAACsY4u81e53k7wwySVJbh/bDgAAAAAbxSLB01e7+4+HdwIAAADAhrJI8PSBqvqVJH+Y5Jatxe7+xLCuAAAAAFj3FgmeHr/Nd5J0kifu/HYAAAAA2ChWDZ66+wlr0QgAAAAAG8uywVNVndTd76iqn1tqf3e/blxbAAAAAKx3K8142nf63rQWjQAAAACwsSwbPHX3G6bvl65dOwAAAABsFHfb1Q0AAAAAsDEJngAAAAAYYtXgqaoOXqQGAAAAAPMWmfH0RwvWAAAAAOAbll1cvKoenuS7ktyvqp42t2vvJPcc3RgAAAAA69tKM54ekeTpSfZJcsLc518nec5qJ66qg6rqg1V1eVVdVlU/P9X3q6rzq+qK6XvfqV5V9bqq2lxVn6iqR8+d6+Rp/BVVdfJc/TFV9cnpmNdVVe3IPwIAAAAAO9+yM566+91J3l1Vj+/uj+zAuW9L8oLu/lhV3TfJJVV1fpJnJXl/d/9qVb04yYuTvCjJsUkOnT5HJXljkqOqar8kL0tyRJKeznNOd18/jTklyQVJzk1yTJL37UCvAACw2/izJ37frm4BVvR9H/6zXd0CsE4sGzzN+ZuqemGSQ+bHd/cpKx3U3dckuWb6fVNVXZ7kgCTHJfn+adiZST6UWfB0XJK3dXcnuaCq9qmqB05jz+/uLUkyhVfHVNWHkuzd3X811d+W5PgIngAAAAB2C4sET+/JbEbRR5LcviMXqapDkjwqyYVJHjCFUunua6rq26dhByS5cu6wq6baSvWrlqgvdf1TMpsZlYMP9kI+AAAAgLWwSPB07+5+wY5eoKruk+QPkjy/u7+6wjJMS+3oHah/a7H7zUnenCRHHHHEkmMAAAAA2LlWWlx8q/dV1ZN35ORVdffMQqff7+4/nMpfnh6hy/R97VS/KslBc4cfmOTqVeoHLlEHAAAAYDewSPD03CR/UlU3V9WWqrq+qrasdtD0hrm3JLm8u187t+ucJFvfTHdyZo/yba0/c3q73WOT3Dg9kndekidX1b7TG/CenOS8ad9NVfXY6VrPnDsXAAAAALvYIo/a7b+D535ckmck+WRVXTrVfjHJryY5u6qeneQLSU6Y9p2b5KlJNif5pyQ/mSTdvaWqXpHkomncy7cuNJ7kZ5K8Ncm9MltU3MLiAAAAALuJRYKno5ap/+VKB3X3R7L0OkxJ8qQlxneS5y1zrjOSnLFE/eIkj1ypDwAAAAB2jUWCp5fO/b5nksck+XiS7xvSEUcLJBoAACAASURBVAAAAAAbwqrBU3cfO79dVYckedWgfgAAAADYIBZZXPxf6O7Px+NtAAAAAKxi1RlPVXV6kp4275bkUUkuG9kUAAAAAOvfIms8fWru921J3t3dfzaoHwAAAAA2iEXWeHpLVe2Z5GFTafPYlgAAAADYCBZ51O4JSd6e5ItJKsl3VNUzuvsvRjcHAAAAwPq1yKN2pyd5and/Okmq6rsyC6KOGNkYAAAAAOvbIm+122tr6JQk3X15kr3GtQQAAADARrDIjKePVdVvZzbLKUl+IsnHx7UEAAAAwEawSPD03CQ/l+SFma3x9OEkvzmyKQAAAADWv0Xeave1JL82fQAAAABgIauu8VRVx1TVRVV1bVVtqarrq2rLWjQHAAAAwPq1yKN2v5Xkx5N8MskdY9sBAAAAYKNYJHi6Ksml3S10AgAAAGBhiwRPL0zyx1X1oSS3bC129+tGNQUAAADA+rdI8PTLSW5Nsk88agcAAADAghYJnr69ux8zvBMAAAAANpRV32qX5P1VdfTwTgAAAADYUBYJnn46yZ9W1c1VtaWqrq+qLaMbAwAAAGB9W+RRu/2HdwEAAADAhrNq8NTdt1fV/ZI8NMk953b95bCuAAAAAFj3Vg2equrZSX4hyQFJPpnke5NckOT7h3YGAAAAwLq2yBpPz09yRJLPd/cTkjwmyTVDuwIAAABg3VskePpad/9zklTVXt19WZLvHNsWAAAAAOvdIouLX1NV+yT54yTnTW+0+/LYtgAAAABY7xZZXPxp08+XVtWTktwvyf8a2hUAAAAA694iM56+obvfP6oRAAAAADaWRdZ4AgAAAIDtJngCAAAAYAjBEwAAAABDLLvGU1Vdn6SX2pWku3u/YV0BAAAAsO6ttLj4/mvWBQAAAAAbzrLBU3ffPr9dVfsluedc6epRTQEAAACw/q26xlNV/VBV/W2Sq5JcOH1/YHRjAAAAAKxviywuflqSxyX5THcflOQpST40sikAAAAA1r9Fgqfbuvu6JHerquru85M8enBfAAAAAKxzKy0uvtWNVXXvJB9J8raqujbJHWPbAgAAAGC9W2TG0/FJvpbk+Zk9YvfFJD88sCcAAAAANoBFgqeXdPft3X1rd7+lu1+b5BdGNwYAAADA+rZI8HTMErUf2tmNAAAAALCxLLvGU1U9J8lzkzy8qj42t+u+SS4e3RgAAAAA69tKi4ufneT9SX4lyYvn6jd197VDuwIAAABg3Vs2eOru65Ncn+SEqnpkksdPu/48ieAJAAAAgBWtusZTVT0vs9lPB0+fs6vqZ0c3BgAAAMD6ttKjdls9J8mR3X1zklTVq5L8ZZI3jGwMAAAAgPVtkbfaVZJb57ZvnWoAAAAAsKyV3mq3Z3ffluTtSS6oqj+Ydv1okjPXojkAAAAA1q+VHrX7aJJHd/evVdUHkzwhs5lOz+3ui9akOwAAAADWrZWCp288TjcFTcImAAAAABa2UvC0qap+Ybmd3f3aAf0AAAAAsEGsFDztkeQ+sZA4AAAAADtgpeDpmu5++Zp1AgAAAMCGcrcV9pnpBAAAAMAOWyl4etKadQEAAADAhrNs8NTdW9ayEQAAAAA2lpVmPN0pVXVGVV1bVZ+aq/1SVX2xqi6dPk+d2/eSqtpcVZ+pqqfM1Y+Zapur6sVz9YdU1YVVdUVVvbOq9hp1LwAAAABsv2HBU5K3Jjlmifrp3X349Dk3SarqsCQnJnnEdMwbqmqPqtojyeuTHJvksCQnTWOT5NXTuQ5Ncn2SZw+8FwAAAAC207Dgqbs/nGTRx/WOS3JWd9/S3Z9LsjnJkdNnc3d/tru/nuSsJMdVVSU5Osm7puPPTHL8Tr0BAAAAAO6UkTOelnNqVX1iehRv36l2QJIr58ZcNdWWq98/yQ3dfds2dQAAAAB2E2sdPL0xyUOTHJ7kmiSvmeq1xNjegfqSquqUqrq4qi6+7rrrtq9jAAAAAHbImgZP3f3l7r69u+9I8juZPUqXzGYsHTQ39MAkV69Q/0qSfapqz23qy133zd19RHcfsWnTpp1zMwAAAACsaE2Dp6p64NzmjybZ+sa7c5KcWFX3qKqHJDk0yUeTXJTk0OkNdntltgD5Od3dST6Y5OnT8Scnec9a3AMAAAAAi9lz9SE7pqrekeT7k+xfVVcleVmS76+qwzN7LO7zSZ6TJN19WVWdneTTSW5L8rzuvn06z6lJzkuyR5Izuvuy6RIvSnJWVb0yyceTvGXUvQAAAACw/YYFT9190hLlZcOh7j4tyWlL1M9Ncu4S9c/mm4/qAQAAALCb2RVvtQMAAADgLkDwBAAAAMAQgicAAAAAhhA8AQAAADCE4AkAAACAIQRPAAAAAAwheAIAAABgiD13dQMAAAAwwm+94I93dQuwolNf8yO7uoXhzHgCAAAAYAjBEwAAAABDCJ4AAAAAGELwBAAAAMAQgicAAAAAhhA8AQAAADCE4AkAAACAIQRPAAAAAAwheAIAAABgCMETAAAAAEMIngAAAAAYQvAEAAAAwBCCJwAAAACGEDwBAAAAMITgCQAAAIAhBE8AAAAADCF4AgAAAGAIwRMAAAAAQwieAAAAABhC8AQAAADAEIInAAAAAIYQPAEAAAAwhOAJAAAAgCEETwAAAAAMIXgCAAAAYAjBEwAAAABDCJ4AAAAAGELwBAAAAMAQgicAAAAAhhA8AQAAADCE4AkAAACAIQRPAAAAAAwheAIAAABgCMETAAAAAEMIngAAAAAYQvAEAAAAwBCCJwAAAACGEDwBAAAAMITgCQAAAIAhBE8AAAAADCF4AgAAAGAIwRMAAAAAQwieAAAAABhC8AQAAADAEIInAAAAAIYQPAEAAAAwhOAJAAAAgCEETwAAAAAMMSx4qqozquraqvrUXG2/qjq/qq6Yvved6lVVr6uqzVX1iap69NwxJ0/jr6iqk+fqj6mqT07HvK6qatS9AAAAALD9Rs54emuSY7apvTjJ+7v70CTvn7aT5Ngkh06fU5K8MZkFVUleluSoJEcmednWsGoac8rccdteCwAAAIBdaFjw1N0fTrJlm/JxSc6cfp+Z5Pi5+tt65oIk+1TVA5M8Jcn53b2lu69Pcn6SY6Z9e3f3X3V3J3nb3LkAAAAA2A2s9RpPD+jua5Jk+v72qX5Akivnxl011VaqX7VEHQAAAIDdxO6yuPhS6zP1DtSXPnnVKVV1cVVdfN111+1giwAAAABsj7UOnr48PSaX6fvaqX5VkoPmxh2Y5OpV6gcuUV9Sd7+5u4/o7iM2bdp0p28CAAAAgNWtdfB0TpKtb6Y7Ocl75urPnN5u99gkN06P4p2X5MlVte+0qPiTk5w37bupqh47vc3umXPnAgAAAGA3sOeoE1fVO5J8f5L9q+qqzN5O96tJzq6qZyf5QpITpuHnJnlqks1J/inJTyZJd2+pqlckuWga9/Lu3rpg+c9k9ua8eyV53/QBAAAAYDcxLHjq7pOW2fWkJcZ2kuctc54zkpyxRP3iJI+8Mz0CAAAAMM7usrg4AAAAABuM4AkAAACAIQRPAAAAAAwheAIAAABgCMETAAAAAEMIngAAAAAYQvAEAAAAwBCCJwAAAACGEDwBAAAAMITgCQAAAIAhBE8AAAAADCF4AgAAAGAIwRMAAAAAQwieAAAAABhC8AQAAADAEIInAAAAAIYQPAEAAAAwhOAJAAAAgCEETwAAAAAMIXgCAAAAYAjBEwAAAABDCJ4AAAAAGELwBAAAAMAQgicAAPg/7N1nuGRllbfx+99NzhkEyaDkIDkrKKioKIiOOWHEOKLymh0TjhHDqBjB7OgoKCigKKAEyUiQHEQyTc406/3w7IOHpkEbunrXqXP/rutcXbV3Naz+sE/tvZ71rCVJkgbCxJMkSZIkSZIGwsSTJEmSJEmSBsLEkyRJkiRJkgbCxJMkSZIkSZIGwsSTJEmSJEmSBsLEkyRJkiRJkgbCxJMkSZIkSZIGwsSTJEmSJEmSBsLEkyRJkiRJkgbCxJMkSZIkSZIGwsSTJEmSJEmSBsLEkyRJkiRJkgbCxJMkSZIkSZIGwsSTJEmSJEmSBsLEkyRJkiRJkgbCxJMkSZIkSZIGwsSTJEmSJEmSBsLEkyRJkiRJkgbCxJMkSZIkSZIGwsSTJEmSJEmSBsLEkyRJkiRJkgbCxJMkSZIkSZIGwsSTJEmSJEmSBsLEkyRJkiRJkgbCxJMkSZIkSZIGwsSTJEmSJEmSBsLEkyRJkiRJkgbCxJMkSZIkSZIGwsSTJEmSJEmSBsLEkyRJkiRJkgbCxJMkSZIkSZIGwsSTJEmSJEmSBsLEkyRJkiRJkgail8RTkkuT/DXJ6UlO7o4tkeTIJBd0fy7eHU+SLya5MMmZSZ407r/ziu7zFyR5RR//FkmSJEmSJM1cnxVPT6mqjapq0+79vsDvq2pN4Pfde4BnAGt2P68DvgotUQV8CNgC2Bz40FiySpIkSZIkSf0bpq12uwEHdq8PBJ477vhB1ZwALJbkccAuwJFVNa2qbgSOBJ4+p4OWJEmSJEnSzPWVeCrgiCSnJHldd2zZqroKoPtzme74CsDfx/3dK7pjD3f8IZK8LsnJSU6+7rrrZuM/Q5IkSZIkSQ9nrp7+v9tU1ZVJlgGOTPK3R/hsZnKsHuH4Qw9WHQAcALDpppvO9DOSJEmSJEmavXqpeKqqK7s/rwV+QevRdE23hY7uz2u7j18BrDjurz8euPIRjkuSJEmSJGkIzPHEU5IFkyw89hrYGTgLOAQYm0z3CuDg7vUhwMu76XZbAjd3W/EOB3ZOsnjXVHzn7pgkSZIkSZKGQB9b7ZYFfpFk7P//w6r6bZKTgJ8meQ1wObBn9/nDgGcCFwJ3AK8CqKppST4KnNR97r+qatqc+2dIkiRJkiTpkczxxFNVXQxsOJPjNwA7zeR4AXs/zH/r28C3Z3eMkiRJkiRJeuz6mmonSZIkSZKkEWfiSZIkSZIkSQNh4kmSJEmSJEkDYeJJkiRJkiRJA2HiSZIkSZIkSQNh4kmSJEmSJEkDYeJJkiRJkiRJA2HiSZIkSZIkSQNh4kmSJEmSJEkDYeJJkiRJkiRJA2HiSZIkSZIkSQNh4kmSJEmSJEkDYeJJkiRJkiRJA2HiSZIkSZIkSQNh4kmSJEmSJEkDYeJJkiRJkiRJA2HiSZIkSZIkSQNh4kmSJEmSJEkDYeJJkiRJkiRJA2HiSZIkSZIkSQNh4kmSJEmSJEkDYeJJkiRJkiRJA2HiSZIkSZIkSQNh4kmSJEmSJEkDYeJJkiRJkiRJA2HiSZIkSZIkSQNh4kmSJEmSJEkDYeJJkiRJkiRJA2HiSZIkSZIkSQNh4kmSJEmSJEkDYeJJkiRJkiRJA2HiSZIkSZIkSQNh4kmSJEmSJEkDYeJJkiRJkiRJA2HiSZIkSZIkSQNh4kmSJEmSJEkDYeJJkiRJkiRJA2HiSZIkSZIkSQNh4kmSJEmSJEkDYeJJkiRJkiRJA2HiSZIkSZIkSQNh4kmSJEmSJEkDYeJJkiRJkiRJA2HiSZIkSZIkSQNh4kmSJEmSJEkDYeJJkiRJkiRJA2HiSZIkSZIkSQNh4kmSJEmSJEkDYeJJkiRJkiRJA2HiSZIkSZIkSQNh4kmSJEmSJEkDYeJJkiRJkiRJA2HiSZIkSZIkSQNh4kmSJEmSJEkDYeJJkiRJkiRJA2HiSZIkSZIkSQMx4RNPSZ6e5LwkFybZt+94JEmSJEmS1EzoxFOSqcBXgGcA6wAvSrJOv1FJkiRJkiQJJnjiCdgcuLCqLq6qe4AfA7v1HJMkSZIkSZKAVFXfMTxqSZ4PPL2q9urevwzYoqrePMPnXge8rnv7ROC8ORqoJoqlgOv7DkIaAV5L0uzj9STNHl5L0uzhtaRHsnJVLT3jwbn6iGQ2ykyOPSSTVlUHAAcMPhxNZElOrqpN+45Dmui8lqTZx+tJmj28lqTZw2tJj8ZE32p3BbDiuPePB67sKRZJkiRJkiSNM9ETTycBayZZNck8wH8Ah/QckyRJkiRJkpjgW+2q6r4kbwYOB6YC366qs3sOSxOX2zGl2cNrSZp9vJ6k2cNrSZo9vJY0yyZ0c3FJkiRJkiQNr4m+1U6SJEmSJElDysSTJEmSJEmSBsLEk/QoJUnfMUiSJEmSNMxMPEmPIMmUJIsnWTfJ48afKxukSQOVZI8kr+hez9t3PNIwSrJEkvkf5pwLJJIkqXcmnqRH9lrgt8AXgfcmWTXJXEk2TLJPki16jk8aZXsCd3Wv906y09iJJAv0E5I0dPYFXj2WfEqyfJLVkyzmAokkSRoGc/UdgDTk3gC8BrgP2B34MLAOcF13/nLgxF4ik0bfGsDh3es9gcPGnftGkq9V1bFzPixpqOwC7FpVdyZZHTgIWBq4P8lbq+qIfsOTJEmTnYkn6WEkWQWYu6pO7Q6dmeRO4NnAFVX1t75ik0ZdkicBVNVNSVYGps5wza0FnN5LcNKQSPIE4O6quqKrAnwXcDbwZuA5wIuTHF1Vd/cZp9S3JFOAlYC5qurCvuOR9MiS7EFb4D+jqu7pji1SVbf0G5keLRNP0sNbC1gyyXeAi2lVT8dV1e/6DUuaFFYFFk/yBVr1xg1J5ququ5JsDUyrqlv7DVHq3QLABUkeDzwT2Ax4TVXdk+Qs4D0mnSQAdgWeAvwCuDDJqrSFxL8Cfx57sJU0ND4IvLX7PpsCvAdYIcktwH9X1U39hqdZZY8n6eEdDzwDOBSYCmwDLJPkK0k+kmS1XqOTRlhV/Rx4Gu2h4GraNfh/ST5N2/J6fH/RSf1Lkqo6nXYtHA08F/hidwzaQ7XXidTsAZw1bnv2S2lbuP8T+FyShXuLTNKDJFkRuLeqjk4yF62K91XAmcDjgdckmdpnjJp1VjxJD6Oqbk7y16o6PcnhwCLA8sC6wNbAkrRKKEmzWfdQfTHjrrFu+93WwOLAT/uKTRoGVVVJNgK+Anybth31VoAkGwDbAl/qMURpmGwOvHWG9x+sqj8k+Snt3u6EXiKTNKN1aYuOAFvQto6/o6oOTXIareLps71Fp0fFxJM0E910oM2B1yfZFDiK1kT8p1V1UpKDAUs8pQFIsjTwgiSvBf4AfL6qLu/6rZ2aZImqmtZvlFK/kqwEvB24htYH45IklwIXAWcB7wYu6C1AaUh02+qmzdAb5l3j+gYuD9i3UxoeJ9G2xH4D2JJ2Lzg2KGNDukXJJFOq6v5+QtSsipN2pYdK8gbaNoWf0Bq1bt+9XwXYq6qO6i86abQl+TywGC3h+xTadrtLgb2BO4Arq+oNvQUoDYEkSwE7AEvQvpsWAG4FipZ8OrqqLustQGmIdN8r9wMfHd8bpusZuH9VbdZbcJIeohue8TRakumEqroxSWgtUA6sqp901fEmMyYIE0/STCQ5DnhnVR0/w/FX0Xo97VtV1/cSnDTikhwDvKmqzuren0+r3DgKOB841qaS0oMl2ZWWiFqb1kj5nVX1+X6jkoZDV72+D/B3Wp+Yu4CVadfLeVX13z2GJ6mTZC3glVW170zObUirgPpeVd0xx4PTY+JWO2kGXRO7hYDzuvfz0FaQp1TVd5LsRWtsZ+JJms2SLAGsCCzbNY68kLZK/eqquqbX4KQh0U342R6Yh9b3bGfa1oQNaNvuXg8c1luA0pCpqpOTvAV4Oa3/2f3ACsBX+ecWHkn92w1YCiDJS4F1quq93bmLgVtMOk1MJp6kh5obOJI27eTr40fsdjf7ywNn9BSbNOoWol1/LwXuoT0c3AMsl2QZ4O9WO0k8EzgEuBPYC/g+cFtVXZ1kalVN7zU6aUgk2Qz4DfBb4OfAAWNN+CUNpc2Bz3Wvd6L12B3zRtr3noMzJiC32kkzkWQr4Ou0X3ZH0DLsdwIvANatqj17DE8aeV2D8SfRtkE8AViQlhT+36r6RZ+xSX3rel+8DdgYWI9W7fR74NCqcmFE6nQLhpsDO3Y/qwDTaH1ijqFt3b6vtwAlPaC7Xq8HXkVrr3AksPPYYIAkvwU+XVW/t7/TxGPiSZpBkg9X1YeTrAy8kFaKvTxtC8NBwPdt2CrNWUkWoW0pumKs95MkSLIg8HRale42tO+s51TVr3sNTBpCSRamVQx+AVgW2LuqvtpvVJIAkiwHfAK4GXgcbcDMe2jtTy4BfgVsaVXvxGTiSRqnmxJ0fFWt2b1fBFgJuLeqzjO7Lg1OkvmBVYFrgc2A1YB/0CbcrQfcDXy4qu7tLUhpCCRZHHgurf/gPcBpVXVud24N4NoZRsdLk05XPbEIsB3tO+Uu2oLiubQm4wsDH6uqK3oLUtJDJFkFWJN277cs7Vp9IjB3Ve2QZEpV3d9fhHo07PEkPdhTgL8nmZuWmL0FsLpCmjN2B75Dm1z3GyDA/wOuo219fbxJJ012SbYHXgKsAVxF2za0S5ILgM9W1YV9xicNkWcBvwSOpi1onADsAsxr5bo0fJJ8jlbt9DtaIcCRSeajLURuRBueoQnKxJP0YM+k9ZJ5N3BPkstp/Z0uqarrrXaSBupW4FjgUlovp78kuR5YrKq+BmDVocSbgJOq6vXwQD+0DYF9adWB+/QYmzRM7gR+TVcVCNxO6x14YZIVgWvGD5CR1J9ukvEfadWJbwEWTnI1cDLt3vAnY1vsrHaamNxqJ42T5ETavv+5aavJC9OqLm6m3cB835JsaXCSLEZ7sN4G+BbwEeD1VXVckrlsAqvJLslFwBOqavr47Qbd9rsDgQ/YYFxqD7LddbI6sBUtQfs42rbtu4D9q+r8PmOU1CTZidZPd39gRdq1ug6wLm3b3Z1V9cL+ItRjZcWT1On6YixYVT/q3s8FrEybqLUGbRKKPTOkAaqqm5LsT+u/8RJgUdrELkw6abLr+hCeS+tZ88equr/7rkpV3ZhkTdq1I01qXSL2fUnOo10zv62q73e9BNemLW5c22eMkh5kT1o17/3AZcBlSU4BFgKWAeYBK98nMhNP0j/dBHy0mxB0V/eQe1H3Q5IFquqOPgOURlWSVwFLA9+oqhuB7yU5AXgfcF6Sj1fVt3oNUupRd7N9fZIDgX2S3FZVJ48lZJM8G7ijqqb1G6k0FBahVauvBmwC3JvkOuBC4G/At7ynk4bKpsB34Z/Vil1fzxu7HwBMOk1cbrWTOkk+D5wBHFpV141tYehWzW612kIanCR7AG8HbgAOAX7RJaBI8hLaNXhIjyFKQyHJvLR+TrvTFkzuoF038wA/q6qf9hie1LvxFRFdReBStG12G9ImZC0N/NprRRoOSVam9dT9JW3B/xTacKeraPd/DpYZASaepE6SvwK7VNWVMxzfgnbTcoS/+KTBSrIn8GzgPuAntOuuHJ0rQZJnARdW1d+SLA+sTtsOPhfw07FkrTTZddXrW9KmFd9G+y45tesjuAlwQVU5IUsaAkneSLsuPwu8gDbBbjHgauA84Oiq+kN/EWp2MPEkAUk2B75YVVsmmXt8ginJMsD/AjtX1d29BSmNqG5FejFgnqq6sqsyfBfwCuA44GtV9fs+Y5T61vUh/Awwjdab5gLaBMi/0rYhlJW5EnRJ2XfQFjG+S+vTuQHtenlbVV3VW3CSHiLJV2h9C/933LGlgK2BXYFzqmp/+ztNbPZ4kppFgX+M7+OUZJ5uzO6KwL0mnaSB+TSwPXB2V259KXAUbULXvrQtRCaeNNktA3wKmE6b0LUJ8GTaxNUbaGOoD+8pNmmYvBqYn1Y1MXbvthzt++RrSV5YVXf1FZykhziiqg4ef6Cqrqe1Xjhk3DGTThOYFU+a9Mb1cvoS7UblM8D540ZUfwm4var27TNOaVQleQ7wSuB44IfAArSJkrfQmsPeV1UX9RagNASSHAvsXVVnjju2PK1vzfbAsVV1WF/xScMiyaHAx6vquCRTac+r93fb7L5IG2JxbL9RSgJIsiJt4eQftN5ORwDHVNXtfcal2c/Ek9TpxlDvCyxJa9Y6T3fqGuDzVXVhX7FJoy7JSsBLgZ2As2nVTme4dUiCJIvQelxs3Hcs0jBLMg9wBbDVzBYsugTue008ScMhyeNou7DWBp5Kq+ZdhnYdnwz8pKrO6i9CzS4mnjTpJVkbWK2qDk0yN20LwzK0qSe3V9VBvQYoTQJj0yOBKbTk0y60BNQPHHmtyS7JbsAvaFsOzgAOq6oT+41KGj5JVgW+A1zXHToLOAE4rqpuTfKXqtq8twAlPUiS/wKuqKoDxh1bGdgc2A34U1V9zf5OE5+JJ0163Va6S6vqs0meBtxQVaeOOz+v/Z2kwUjybWBVWoPkZYGVaD2eFqA1hj2gqt7QW4DSEEjyNdo2hOOB3Wnb6xaiTfv5C/CjqvpHfxFKw6HbWrcM7ftkTWB92uTHeWjfL3dW1Xb9RShpvCTPpQ2UuR/4GHDk+CnGJpxGh4knTXpJ/gC8o6pOT3IM8Mmq+k137i207T7H9BqkNKKSrEZ7MLgbuJ32cLA+rfLpZuD4qjqnvwil/nXfTa+sqou79/PSJnVtDTyP1rPmFz2GKA2droo9tCTt6sCTgPOq6o99xiXpwZLMB+xFW1T59YyNxjUaTDxpUuv2Ff+uqtbt3v8Z2L6qpnfvTwFeXFXn9RimNNK6rRHLAKd1kyQldZIsCLypqj6dZArA+NVgSQ+WZBng5qq6O8k6wL20hYwdaQ+1t/UaoKSH6JJPuwP/CVwLvKuqzu43Ks1OJp40qSV5Km389K9pJZ5rVtV63bmptGau2/YYojSyuj38bwU2BpagNZY8D/g88EO3uEqS/l1JdqVNSL0IeBqtb+CVwLbAXcCvquqdvQUo6UG6ZNN8VXVT93qx7tR7gGcCLxrf/kQT21x9ByD1pdsz/LskKwAbAU8BlklyGnAJ7ZffZX3GKI24/WiJpvdU1UlJlqA1knwB7do7yr39muySrAHcRPtO2pz2AH0r7XtrQ+BbVfWH/iKUhsaytIfVrwO7AvcBnwN+XFXvTrJ8n8FJ+qdukBXmAwAAIABJREFUWut/Acsl2RI4EShgO9pz2A207zqNCBNPmrSqqpKsVVV/A37b/Yxt+9kEeCHwox5DlEZWktAemveqqtuTTK2qacB3kiwH7NlNH3JLhCa77wPrAAfTth+sQWu8/wngKtrDtST4X9qD6+uBfavq7UkWBX4GUFVX9hmcpAdZiDZ98gfAPcBywMVVdUG3XfYO7wFHi1vtNGklWQs4ENizqi7vSjw3o/0iPNZfdtLgJNkOeHdVPXvcsSlVdX/XOPlEYNOq8qFak1a3Ivw/wArAz6rqK93xi4G13Y4qPVSSJYF9aFWBOwIrVtW1/UYlabwkL6VV8J5QVVf0HY8Gz4onTWbPAE7skk7LAG+k9Zs5BXhVkjd7oyINzDbArkn2B06mjc+9uju3LnCNSSdNdlV1C/DSJE8DXp1kMdqN+qVd4+QFquqOfqOUhktV3ZDkE7Rt2/cDL07yTRcUpaGyFLAHsF+Sm4DjabtP/lRVN/camQZiSt8BSD3aivZLDtrNyROB51XVzrQb+6f1FZg0CXwJ2J7W+HVP4PAkf07yAdoWInvWSJ2qOhL4NLA08Ba668Okk/RPSdZOslmSeavq1qr6FvBa4PmATcWlIZHk8cC1VbUd8ARaheJdwAeBU5Mc30101Qix4kmT2YnAOkk2Bz5A+6V3SnduKWBaX4FJo66qbgf+1P2Mjb/eBHgybZ//b3oLThoCXR+0LYBLquqaqjo1yRnA6cB7kmwEvK6qbug1UGkIJPkfWmL2DuAo4MBueMwSwGeAc3sMT9KDPR/YAPghre3uH4E/AnSVvVt1/T8dMDNC7PGkSav7xfZ5YBHgb1X1vu74vMAZwAZVdU+PIUojKclCtArDHWkPA4dV1f3jzi9WVTf1FZ80DJJsD+wL7F9Vh3cN+Kd355YCXlNVn+o1SGkIdBOxPg+8HVgceB1wNbAarT/a34Hdqure3oKU9IAkvwBOAz4+9r02k8+YdBoxVjxp0uoebF/VNaGcBg80ct0d+J1JJ2lg3gNsC5wJrA7cmuQi4JXAqsDRwEG9RScNhz2AP3RJp9B61ZBkZeBlwJ/7DE4aIk8DflxVJwIkWQl4M/Deqvp1r5FJmplNgRuBLye5GTiftuj/t64iHpNOo8fEkyatsQla47cpVNUtSQ6jNbeTNBg7Aa8AbqA1Gf9cd/wk4BbaDYg02W0JvKF7nW7i4zxVdVmSFYFV+gtNGiq7AaskWR74Lm3b9vtMOknDp2txchmwH2273eOBtWhby+9Pcg3wX+Mr4TUaTDxp0ppha0+6Y+UkO2lwkqwCLF9VF3SHfpXkAGAHWi8bt0Jo0ksylVb5t3WSM8e2IoyrxN0I+HJf8UnDIsn8tOeZvYDn0hYOVwQ2S7I6cERVndNjiJIebFfazpLzgfOTLAAsS9sWuzq0ZzS32o0eE0+adLomxosx7iF3/C82f9FJA7UcsFS3onUOcCFwUXcDIgmoqulJDgY+BVye5Fjgdlqj5CcAC1TVX/uMURoSOwAXVtUvgV/CAz3Qdu9+9qFVVEgaDkfRvsvGdp/cAVzS/fwpyXzgVrtRZHNxTTpJPgb8A/h2Vd2dZFVgc+DUcVUYkgYoybLA84Cn07bb3QFcDuxbVfaukXigwfhHaQuFZ9IStwsC+1XVUX3GJg2DJF+kVUl8jJacvbiqbus3Kkkz01UoHkSr2D2mqmpswT/Jkk5pHW0mnjTpJPkL8KqqOrsbR70fbQrK6sA7q+rAXgOURtjDVRQmWQt4NnCciSdNdkk+RasGPLSqrkyyNvAk4Czag/WtvQYoDYkkp9Kui6uBqbRhMVcBlwJXABdYOSENhyS7AntX1TPH3w9228tfQquA9x5wRE3pOwBpTkqyAm2Lwtndob2BK6tqC1oj1xcmWby3AKXRN/9YGXWS9ZJslWRpWhXH+d5waLLrro+bgM2Abyb5Ga158t+Ba0w6SU3XTPx+4HXAT4CTu/fr0BYy3gws2luAkmb0LODw7vVc8MB2u+lA0QbPPNB7V6PFHk+abO4HzkjyAmA+2kj353bn7gWWrKob+wpOGmVJXk673pbvmkkeQZtwtzzwG9oW2IP7i1DqX1XdBXyyu/FeDVgP2Bh4PbBcknOq6i19xigNiXWA07pr5pTuhyTLAU8EVqiqm3qMT9KDXU43kbWq7u2+5+YF7gS2om0pBwgtEaUR4lY7TTpJnklr2Hoz8OWq+nF3fG9g06p6VZ/xSaMqyfuB1wBvA06nbY34FnA28Blg3qq6vb8Ipf51fQgXBw4Djq+qad3xBYG1gSlV9ZceQ5SGRpJ5quqebqvO/W6rk4ZX1/j/AOAY4EdVdU13/InAT4EXVNV5PYaoATLxpEklyX+MJZpmOL4aLRn1/aqy4kIakCSvAd5Nm2ry/u7Pl1XVmU6UlCDJzrSV3/WBpWiLJCcChwLnjE1jlfTw/D6RhlOSpwIfAObpDl3b/Xl0VX2un6g0J5h40qSRZD3gs1W1S5JFgadW1c+7c1OAhYDbqur+PuOURl3XR+0NwBrALlXlqGupk2RqVU3vKjjWAh4H7AnsSuvztL3JJ0nSRNYNlVkdWBo4qqou7zkkDZjNxTWZ7EKbEgRtjPtu486tDrzGpJM0GEnmTzJv91B9I22L3TnADUm+mOQJPYcoDYUu6bQ97TtrZ2BfWvP9f9Aa8Jt0kiRNKN0iP0nmS7IScB6t1+cJwGrp9BmjBsvm4ppMtgM+3L3eEjh63LkX0G7sJQ3GJ4DbgOOSnAdcVlWfTfId4NO06qfz+wxQ6luS79K22J0LLAP8lrYN/M6q+lOPoUmS9Kh0U8U/0fV4ugBYjDZc5iZa4mknYLOquqG/KDVobrXTpNBl0KfTfrkdSGtuvMXYWOokBwNfqKo/9BelNLqS7E5L+K5P2z50LHAG7ZqcDpxbVTf3F6HUryRz0XqerUZbBf4prcrpb930n6ndyGlJkiaMbpr4j2iLKb8Efkyr6n0/sG1V3dZjeJpDTDxp0kiyNPBMWnXTpsB9wPG0yUHvBDbwpl4arCQbA18D9qNdj08E/l5VL+k1MGkIdFsRnkC7NrYBlgRuBM4CTqiqQ3sMT5KkWZJkSlXdn2QTWquT22mTjD8J3FpVHxmbTtlroBo4E0+aFJKsTruBP2UsuZRkfeDZwB7AjVX11B5DlCaFJB8C7quqj487tlpVXdxjWFLvkuwALAqcUVWXdccWAbYGngXcXFXv6zFESZJm2QzJp3cCU4GnAptU1aW9Bqc5xsSTJoUkvwIOAn5TVbeNmxrkuF1pwJK8BbgSOBL4GfCuqjqj36ik4ZLk/cCGwC208dIXAadW1am9BiZJ0myU5DnAu2mTWr9QVSf2HJLmABNPGnnd6PajgQ1nTDIl2RZYE/i+k4Kk2S/JgsD/ozXvX5RWZfhxWn+nc6rqmh7Dk4ZK9321EfAkWsP9ZYE7gXdU1bV9xiZJ0mMxVvnUvV4eeC9wfVV92GKA0WfiSSMvyfOA11TVs5LMX1V3jju3JvC9qtqyvwil0db1V1sGeDytcfKywNK0ZNR5VfXJHsOThlaSNWjbEv5cVd/vOx5Jkh6L8QmmJAsDy1XVBSaeRt9cfQcgzQG3ALclWbyqboQ2Paiq7gPWBS7vNTppxFXVdcB1wNnd5K6lgcfRmihbxaFJr0swXT6+uWq3MnxhkhOApwEmniRJE9q4pNOUbrr4reOPa3RZ8aRJIcmXaSPcvwKcWFVXJlkZ+CLw66r6Rq8BSiPu4VayxpddS5NVkoNoVYEXA6cAx1XVud25nwAHV9UPewxRkqRZlmRJ4CZgHmAFYFpVTevOjRUCaBIw8aRJIclCwOuB9YHFaNt9rgV+A3yjqm7pMTxp0ujGxUNb3PILSAKSLAesTevvtDatInBhWmX6X4H3jlXsSpI0ESTZFdgF2AE4j7bL5FbgNNrCvwuPk4iJJ420JE8CVgX+AtwMrAIs0J2+x2lB0uCNVTu5f196qCQb0b6Pzhl37PHAcsDywO+q6o6+4pMk6dFI8hTahNZrgQ1o32lr0BZZ5gO+BRxp1dPkYOJJIy3JC4C9gXuBS4GTgLOBc4FpwJSqmt5bgNIIG9tGNy7xtA/tmvvvJItV1U0mozTZJfkdsCNwBe376TDa1jr7D0qSJqRuqvHyVXXBTM4tAewGbAh8tarOm9Pxac4z8aSRlmSHqjo6yUq0Us+tgZWAu2iJp/dW1d/7jFEaRUnmBj4CfG3sATrJ+sBzaNWHTwY+VlWn9xakNASSvAx4PnAZbYFkK9r1cRdwAfCiqrqmr/gkSZpVSV4ObFxV70iyOrBkVf1lhs9s3h3/TS9Bao5yqp1GVpLlgW8mOYT2gPsN4BvduSfRVpiv6zFEaZTtAmwwQ9XGHcCLgBWB/Uw6SVBV30tyMPA6YEFgn6q6LMmGwO60RRJJkiaSpwO/7V6/Hjif1vqEJDsB91bVMT3Fph5M+dcfkSamqroS2AII8Nsk/5lkme7cqVX1maq6q9cgpdG1AXAmQJItk/w38B3gQ7RKKHvWaFJLknFvbwc+D1wFfCfJ86rqjKr6EGDvC0nSRLMq8H/d622Ak8ed2wtYYo5HpF5Z8aSRlWRqVU1L8i7gecAe3fGvVtWd/UYnjbwfAz/o+tesBXwd2KOqrkvyKeDqXqOTetb1PduLtqVuZWA94HjgTmDvJGdV1QX2QJMkTSRJ1gM2BrZOcg0wdYYq9ycCf+wjNvXHHk+aNJKsCHyZNtnu08BPqureXoOSRlhXYbgDsBRt5es7tJuN9wEvq6q/9Rie1KskCwC30aqc/ofWz2lh4ATgYhdIJEkTUdc8/G3AU4DH07aRfw34HW3H1fuqamcHzEwuJp40kpKsQCvrvBRYE1gXuASYCnwQmF5VK/YWoDTJJPkArbn/tcDRVfXtnkOSepVkfmBPYFPa1tTLgfOAvwHnAFdV1U39RShJ0mPTDZvZljZEY3PaJLv9q+pdY9OPew1Qc4yJJ42kJM8H3gHMDxxDW1V+AnA6re9MqupX/UUoTQ7dltfp3evVgLu6/mvSpJZksbHEUpJ5aTfkOwAbAavTqnL36zFESZJmWZKlgKcBZ1bV2TOcW5D2HHZbL8GpNyaeNJKSLFNV13avF62qm2fyGcs7pQHzOpNmLslJwNm0xZHLgXOr6h/duaWABWaYCilJ0lBLshmwLzAfsDRwQFV9M8kzuo9sV1Xv7S1A9cbm4hpVi3WjOo+vqktn9gEfhqXZL8miwFJVdRE89DqzrFp6oMLpEtrk1QWAW7rj19G22l0IHNdbgJIkPTrPp/UpfFeS1YGPJdmZVsl7D62noQuTk5CJJ42cJLsCbwFWA+ZP8m3aL7kNab00Nq6qPXsMURplL6U1Et8nyROBuavqrLGTJp0kqKq7k/wn8Fra99LRwLm0CZBPBjavqj/3F6EkSY/KVsC7AKrqom7QzJnAi6vqvq7nkwUAk5Bb7TRyknwXOKqqDup+uR0ILEabpvUj4NiqOrzHEKWRleRnwPeq6uAk+wN/qaofdOd2Aq6tqr/2GqQ0RJKsA+wBXAn8tKpuHb9dXJKkiaDr33QqrWL3NOAvwDeBJ1fV9X3Gpv5N6TsAaQC2Am7oejvdS2sq/pOqWr2q3m/SSRqo1YE/dK+34MHbhfahjdWVJrUkKyfZJclWwOLAGsA3gP9MMp9JJ0nSRFNVtwM7AUfSJop/HAiwb5JXJ1m/z/jUL7faaaQkWQK4iDYZaPMkNwDLAMclmb+q7uw1QGmEJdkEWAJYI8kiwNSqumTcR5bin0kpaVLqbrxPpjUWnw/4BfAd2o36+cDd/UUnSdKjk2Rz4F7g/6rqh92xtYBdgT1prRj+an+nycmtdho5SR5HG0u9CrAi7ZfcecB02ljP/+0vOml0JVkVeAetemNxYF7gS8AZtEqovapql/4ilPqXZD3g3cA04DbaVvC/AUfRtqK6HUGSNOEk+QKwHHA1cBlwAXByVV3dnZ+rqu7rMUT1yMSTRkqS99P6y1zWvZ+XttVuXWAdWuLpZz2GKE0KXRJqG2BHYAVa0+SvVtV+vQYmDYEkCwGL0L6X1qANw1gMWBQ4qKoO7TE8SZJmWZK5aN9rm9CevZaltfY5E9i/qu7qMTz1zMSTRkqS04Cdqmpaks8BH6mqm/uOS5oMkqxAa+J/bNdfbcZzt1TVrb0EJw2RJE+iLYqcBlxYVdOTrA1sDBxTVVf0GqAkSY9R13ZhB+CNwCer6tieQ1KP7PGkkdHtK76hSzqtBGxTVTcnCS3b/ltg16q6p9dApRGUZGvgLbRtrosmeR9wEK3SaXlgq6p6f48hSr1LsjLwNtp1MTdtRXh6kp8DH6yqc/uMT5KkR6Mb6vSgxf6qugX4VZLVadNbj7W/0+TlVDuNkl1ojVkBng78FaD75bZ599KkkzQYLwHOrqrVgY2ALYGvA4cAr6X1WZMmu7fT7r1eV1VPq6rlgWfQmvK/FqBbLJEkaSI5IMmPk7w7yXZJFhh3bgfg930FpuFgxZNGyQrAJkk+QEtCHTKuid0zAcs7pcHZAnhbkilVdUXXQPmIqloxyVTA1S2pXSdv7K6R+arqrqo6K8mngE8n+WNVndJ3kJIk/bu6qeIHAI+jVfK+GVgwyT20IRr30gZoYLXT5GXiSaPkTbRmdjvSKp92BbZKchKtvPOV/YUmja4ki9MSS88A1k1yMa1R8hcBqmp6j+FJQyHJfLQb8NsBxpqsJpm7qs5Oshxt+qokSRPJG2k5pU90SajFaNPtHg8sA3y3qm7vM0D1z+biGgld4+LFqurscccWpPXReAawTlW9uK/4pFHWVTRtTkv8rk3bNrQicChwDXBuVR3fX4TScEjyGmBvYB/g9Kqa1h1fA/hlVa3XZ3ySJM2qJIcBn6qqo/uORcPLiieNiv8HXAmcDZBkI+ApwF20KQquIksD0l1fx3c/dJUbawPrA08D5h07J01mVfWtJPMAL6RV5N4DbAhMBX7ca3CSJM2iJPMCGwBLJtkYuI427OnOfiPTsDHxpFGxMfBNgCRjTY2Ppz3wzgd8vr/QpMkhyWLA7VV1dZLrgDOBHwLefGjSS7IFrbH4z4AraBWC8wAn0Kqf/tRjeJIkPRrb0XIKTwUWAK4GLk1yCfAP4Oqqur7H+DQk3GqnCS/JUrQmxk/q3v+c9sC7P21f8UHA7lV1ZX9RSqMpyeOA9wE3AHcD29KaS17TfWQzYNVupK40KSVZmfZd9IaqOnfc8bmBxavq2t6CkyTpUUryVeCcqvpSkm1oVbxrAYvSElJHVNWBfcao4WDFk0ZBAack+R5wC7Am8K6quqmbSj2XSSdpYHakNfa/mNZMfK/uZzdga9oCx139hScNhWcBF1TVuV1PtLEtqvcBOyaZVlVH9BqhJEmz7irgGICq+jPwZ4AkywBb0lqhkCROtJvcTDxpwquqG5J8iDa1bjHg/VV1cXf6tcA5fcUmjbLuJuIHSW6g3VxcV1VXJplOa5R897jPebOhyWx74Nfd67mr6q4kc1XVfUlWp227M/EkSZowkiwAnAIs0r0PbcHx/q6S95Cxz3ofKBNPGgndw+6nxjcR77YAzQ98v7/IpNE17ibiCCDA+7upXVsAWwEkmVJV9/cUojQsTgRWBhhXATj2fbUZ8L0+gpIk6THYDXgB8HJ44L6wkswHrAucUVX39RifhoiJJ42MmUyuuxb4DDY2lgYiySLAbV1i6TfAb5I8D5ibtn3oiqq6qdcgpeHwQ+DwJKvQmoufU1WXJ9kOWBU4ssfYJEl6NHYD/q+qbp2huv1+WqXvUsDhvUWnoTKl7wCkQamq6VV1h6Wd0sC8CbglyUeSbND1rjkU+BjwEuCTvUYnDYEki1TV1cDOwGW0fk+fSHI6sA/wAZvvS5ImoJWAM7rXU9PMU1X30CrfF4cHtuBpknOqnSRplo2tbHUVG88DpgK/rqojx31mlaq6tK8YpWGQ5L3AT6rqoiTL0yqc5gOuAG6sqmvtgyZJmki6ZNI7gEWr6kMzOX8usGNVXTXHg9NQMvEkSXpMkixE2+O/d3foS8DBVXVjf1FJ/UsyD23AxTpVdU+SL1bVW8edXwW4slsdliRpwkiyHvAt4CJay4ULaRPGnwE8taqe7sKKxph4kiTNsiRPADaklVFPB46nbd9+J20r0a+q6tX9RSj1L8mOwOur6oVJNgC+X1UbdOcWAL5ZVS/uNUhJkh6lJAsDr6FV8y4LrE+bZvf1qrrUxJPG2FxckvRovJaWZDoAuBp4CnADcDqwEHBvf6FJQ2NP2jZUgG2AX447tyOwxByPSJKkxyjJz2mLjocCXwcWBe6rquuTTB0b+mTSSWOseJIkPSpJngVsDZwNHNn1qpnL0blSk+Q9wLa06ao7Ar8GPlNVZyX5KHBNVX25zxglSZoVSeamDZjZFtgIuJ2WhDoMONzt45oZE0+SpEctyarAfwA70BJQB1XVGY/8t6TJodtOtySwArAesDawMhBaU/4Nq+qv/UUoSdJjk2QjWpuFPYDjqmrvf/FXNAmZeJIkzZIk6wKPAxakTef6O3A98FJgJ1ofm6/2F6E0fJJMBRamba9bFViuqn7Qb1SSJM0+Sb4H/KiqDus7Fg0XezxJkmbVPsCWwB+Au4DX0x6kL6A9WD+hv9Ck4dT1u7gJuKlrzj+l55AkSZolSeYCnk+bYHdpVV0/w0eWB66Z44Fp6Jl4kiTNqpto24bmB+apqmkASZalfa9M6zE2aSgkWQK4bXyviyRTqup+4HW0hqySJE0kqwI7A5sDdya5GriUVvk+FVi6qk7pLzwNK7faSZL+bUmeBHypqrYZd8yG4tI4SVYADgL+DJwGnEOb/nh7Vd2X5GJgu6r6R49hSpI0S5JMAdag9S5cp/tzXloLhkWB/6mqQ8cttEiAFU+SpFmzM3Dr+ANjSafuZqQcnStxFbAfsB3wKtoW1CuBE5PcC9xt0kmSNNF0yaTzk1xeVX9IshCwEnD1WAX8uM9JD7DiSZL0b0tyJLA6cC9wA3AMcARwYlXd3mds0rBI8jzgsKq6u3u/HLA9bfT0ZsCRVfXBHkOUJGmWJFkYeC9tm91JwPeq6uzu3FrA3E5q1cMx8SRJ+rckmRs4varW7ZpL7gzsCmwNLEDr/bS7lRya7JKcADy9qm5K8jLapMcad97tqZKkCSXJq4HnAgcCG9MSUIfT7gen0Po7bdRfhBpmTlSRJP27VgUOhra9rqoOq6q9q2pjWjXHl0w6abJLsjltK91NSVYH3lpVlWZqkk8CrvpJkiaaJwNfraqfV9X7gcuBZwC/Al4+lnRKkv5C1LCyx5Mk6d/1dFqz5Ad0VVD3VdU1wPeTxB5PmuR2AQ7rXm8OnAGt+VmSbYCNq2p6X8FJkvQobQfMn2RFWqXTysDbq+qs8R/yPlAzY+JJkvTvegnwNoAkbwYOrqq/j/+ANxsSuwGrJCng2cD+485tywzJW0mShl2SBYG9gDWB9YFnAVsAr05yIq3X56X9RahhZ+JJkvQvJVkSuKuqTugOvZI2Ll5SJ8n8tHurvYDnAUsD307yVuBHwJ7A6/uLUJKkR+U/gPmr6stJlgaWoA2bWZu2yPIU4A09xqchZ+JJkvTveDqwSZLVgNWAK6vqlrGTSaY4OldiB+DCqvol8EuAJMsCzwF2Bxavqr/0GJ8kSY/GbsCXAarqOuC6JOcDfwQWp+tdaMsFPRyn2kmS/qUkGwJ70xqMrw9MBz4KnFRVp3Sf8WZDk1qSL9JWgD8G3A5cXFW39RuVJEmPTZILgD2Ai4B7qurenkPSBGPiSZI0S7qqp02Ap9KSUCsDL6qqY3oNTOpZklOBs4CrganANOAq4FLgCuACk7OSpIkkybbAUcCRwI3AacCptCTUDbRWDA7N0CMy8SRJ+pe63jXPAe6mVXJcWFWXJJkKbAScW1V39Bmj1KckywOH0BqIrws8AVgFWJKWhJoKfLCqbuorRkmSZlWS/6YlmD4PvBDYkvYddx9wDfB/VXVIfxFqIrDHkyTpESXZAXgRbZvdvLRqjnmSHAf8z9hWO2mSWwc4raruAk7pfkiyHPBEYAWTTpKkCWhB4KdVdQ/wve6HJOsDzxz7kC0X9EiseJIkPaIkhwB/rKrPde+Xpo3Q3Qf4WTfhxJsNTXpJ5qmqe7pKwPu9JiRJE1mSuYGnVtVvuvdzVdV9PYelCWhK3wFIkobeuuOSTlOr6rqq+jXwJuAZSdbwAVuCbjWYqpo+/ppIkv6ikiTpUXsq8IIkS3XvF0yyeZJ1+wxKE4+JJ0nSw0qyInBxknWgPVAnmatb8TqHtsf/yl6DlIaciVlJ0gS1B3ByVV2fZAXa1NZfAIcl+UKSefoNTxOFiSdJ0kx12+f+TrvB+GSSTbqtRPdV1X1J9gCusam4JEnSSFoPGJtavBewFPBkYA3aVOP1+wlLE43NxSVJMzWuSuPHtJuL/YCrkswLTAcK+HJP4UmSJGlAuvu944ANkkwH3kobNnNJtwC5Cm3anfQv2VxckjRTSaYAK1bVZd37DYC1gPmAhYFfVJXb7CRJkkZQko35/+3dedSedX3n8ffnSUJCIGENiwRZEwhbWVREdlBQoFYLIsVDBcUp1RmV6XQ8M9OiVtvTzijtTE9pz7FSoTMoUsVRtrLIvoiGLRgCYRn2fQkQIJDkO39c12PDdtieO9dz3/f7dU5Onue67iSfnMM5XPlcv9/3B98BngYuraqvt9e3AH5UVTt2mU/9w+JJkvSaknwEOA44oqqeTzIV2APYCPhxVS3qNKAkSZJ6oj1QZln79frAk+3JresD/55mcfwJSUaqanmnYTXuudVOkvR6DgSubkunjYCvAzsC1wFbJPkqHhkvSZI0cFYonSZU1cPt12tV1cNJ/g+wqP2cpZPekMWTJOn17AT8Qfv1cTQznb4E3A6cCnyoqs7rKJskSZJ6IMlM4HDgTuC9SXYG7gAvfqIHAAAVV0lEQVTWSrILcB9wcIcR1WcsniRJr5JkEvAL4PgklwOfBY6tqivb+2sAd3UYUZIkSb2xD/At4Hrgr4ELaYaLrwnsDsyuqiXtCciufNcbGuk6gCRp/Kmql2hOsXsE2BU4tarOAUiyDbBqVd3aYURJkiT1xiXACcACYGlVXQzMBS6oqser6up2tpOlk94Uh4tLkl5l9A1WkjVp/l/xZHt9DeAwYLOq+pNOQ0qSJKlnkhxEM0j8KeAAmjEL1yeZWFVLu02nfuJWO0nSq4y+waqqp15xawlwAe1ASUmSJA2W0WKpqs5J8ivgc8AsYC0ASye9Va54kiS9Lo/IlSRJGj7tqvdF7Qr4EeAI4C+Ai6vqmG7Tqd9YPEmS3jSLKEmSpMGV5AjgIOB+4Myqura9HmAGMLmq7nWwuN4KiydJ0sskmQ3sDKwHnF9VC15xf1I7fFySJEkDIsk6wMXAKTTb6j4MnAjsD0yjmfO0c1Xd2VlI9SWLJ0nSyyS5nGaG0x3AOsB/B9anGSq+OfCHVXV7dwklSZI01pIcBhxYVZ9rvz8Q+A5wNvAvwDVVtbjDiOpTDheXJP1Gkg8AT1bVR9sT7D5L89YrwMnADcBdHUaUJElSbxwC7JTkUOAyYHvg+1X1ldEPuMVOb4fFkyRpRYcCEwCqalGS+cD9VXXI6Hyndo+/JEmSBss/ATfTbK07Ctgd+HmSfYHbq+peSye9HRZPkqQV3Ql8IMn1NEMlZwE/BBgdKu4DhyRJ0mBJsipwC3ANMB1YG9gG2BY4Gtg4ye9W1VOdhVTfcsaTJOll2iNzZ9K85doT2AmYRDP36YiqerTDeJIkSRpjSb4IbFpV/zHJ2sDzwBJgCk0JtVZVzesyo/qXxZMkCYAk+wDbVNVJr7g+GdgSeE9VndJFNkmSJPVOktOAs6rqtCR/B8ytqpO7zqXBMNJ1AEnSuHEkzRstknwlyTEAVbUEuA/4cYfZJEmS1DvbV9Vp7ddzgMuheQGZZEJ3sTQILJ4kSaO2pDnBDuCDwIMr3DsB2GdlB5IkSVJvJZkNbJtkXpLTgdlVtRCaF5BVtazbhOp3Fk+SJJLMBN4LrJFkBrBGVZ23wkf2phk4KUmSpAHRnlp8W1WNAF8GHgAeT7Ioydwk30qydccx1ec81U6SBLA6cAZwDM1JduslOQhY2N5/vqpu7yqcJEmSxl5VLU+yS1XNraqLgIsAkqwOHAJ8DvgdYEGSeLqx3g6Hi0uSSHIUcA/N6SWb0Gy7WxOYDLwfWFhVn+ouoSRJksZakonAHcBawALgXOBHVXVTp8E0UCyeJEkkuRw4qKqeab+fDmwIbARsDVzhA4gkSdJgSrIO8NvA/sB+wDLgEuDCqjq1w2gaABZPkjTkkmwHnFRVe73OfZdVS5IkDZjRZ7wkE6tqaXttK2BV4ESag2UuqKoD21lQyzuMqz7mjCdJ0keAXZP8V+BXwJVVtXj0pqWTJEnS4GlLp08AWyf5CHAj8G7gBeBvgG8BN49+vJuUGgSueJKkIZfkp8BcYDXgg8AawG00wyUvA35p+SRJkjRYkqwNPAbcDpwH/D/g5Kp6qstcGjwWT5I0xJKMADdW1fYrXFsfOBD4EM1qqIOq6tqOIkqSJKkHkkymmem0HTCdZosdwP3Ag8CCqrq+o3gaIBZPkjTEkmwMvL+qzug6iyRJklaeJNsDj1fVA+3BMlsC2wJb0JxyfGlVfc95n3qnnPEkScNtP+BTSWYC1wHXVtXz4FBxSZKkAfdpYL0kjwG30jwLnllVzyZZj3auk8+Deqdc8SRJQ6w90W4XYCuat1urAXcBP6yqy7vMJkmSpN5Jsgkwh2Z108bAujSLUx6mKaL+tyfZaSy44kmShlhV3ZxkATAVWAeYCfwW8Lkkj1bVgk4DSpIkacwl2Q14pqrOS7IKsB6wIc2z4BbAhpZOGiuueJIkvUySacDngU2r6g+7ziNJkqSxleQAYA/gH6vqnlfcmwaMVNWiTsJp4Ix0HUCS1I0k2ydZ8xXXJlTVM8BcmuXWkiRJGjw/BxYD5yb55ySfTrJjkints+Dq7VY86R1zxZMkDakk5wA70uzhvxQ4F5hHs7z6a8DPqup7XeWTJElSbyWZChwBbAPMoHkOfInm2fBW4AcOF9c7ZfEkSUMsyWTgvcDhNCfcLQYWAvOBk6rqqQ7jSZIkqQeShKYPWJ5kVeBdwGRgEc2sp8VVdUuXGTU4LJ4kaQgl2Rw4GDgEuBL4dlUtTjITmF5V8zsNKEmSpJ5YsXTqOouGg8WTJA2hJN8HngDOpymfHgL+rKpeau/HZdWSJEmDL8kEgKpa1n7vc6DGlMWTJA2hJHOB/apqUZK1gZ8Cx1TVwiQjvgGTJEkaPEl2AD4JXAbcUFUPdxxJQ2Bi1wEkSStX+8CxNrBRkkk0AyRXq6qFAJZOkiRJA2tVYBXg48BRSRbRzPe8Cri5qp7rMpwGkyueJGnIJNkK+FNgfWAJsAxYBzgMKODxqlraXUJJkiT1QpKJNC8gpwCzaIaKz6A5ZGYq8MdVNbe7hBpEFk+SNKTa/fw7AbsAewAbAJOAb1bVhV1mkyRJUm+0K963B5YCvw/sAEwDtgF2qKq7O4ynAWTxJElDpH3QOAs4D1jQ/rinqpYlmQbsSbPM+p4OY0qSJGmMJdkb+CPgbpqV7zOA79OM4Lmqqm7oMJ4GmDOeJGm4bErzVmsN4FfAwcAzSe6kKaGurarHuosnSZKkHjmM5jTjO4H/DFxYVU93G0nDwBVPkjREkowA+9K87ZoInEsz52kOsDFweVV9u7uEkiRJ6pUkO9M8C36U5tnvIeBi4BLgIg+ZUS9YPEnSkEry28BGwGVVNT/JpsCEqrqj02CSJEnqmSTTq+rpdgTD3sDhwF7ArlW1qNt0GkQWT5I0RJKsC6wH3APsSnO63c7A0VX14y6zSZIkqTeSrAEcB3wEGH3JeCvw91X1TGfBNBQsniRpSCT5OPDnwGKggH8GnqIpnk6vqms6jCdJkqQeSfID4HbgeuAZYG3gfcAs4E+q6sYO42nAOVxckobHdJoHjbk0c51mAjcBP6yqJQBJUr6RkCRJGhjtjM+dgWOr6tkVrp8DnAB8LMlNPgOqV1zxJElDIsnqwDo0J9vNoimeZgLLaVZAfbuqbussoCRJksZckvcCJ1bVnkmmAEuBZVVVSWYAFwE7VdWyToNqYLniSZKGRFU9m2Q94G7gKpqyaQNgR2A28ECH8SRJktQbDwGPJjmyqk57xb1ZwBNVtSzJiKfaqRcsniRpCCSZDRxFs8x6Z2AZ8Cvg76rqrCRTquqFLjNKkiRpbLVjFO5N8g/AN5PsBpwBXAkcCvwe8H+7zKjB51Y7SRoCSc6gOcHklKq6JcnmwCeADwInVNXVzneSJEkaLO18pw2q6oEkOwFHA/sD6wI/pymdzl5x9pM01iyeJGkIJLmtqma3X/9mGXWSzwMfAL5UVY93mVGSJEljK8k2wL8DFgI305xs9yAwCWD0gBmpl9xqJ0kDrn3geHj0+6panmRCVS2rqpOSfBlY3F1CSZIk9cjGwCM0cz23pjlU5mngTuDh9jS7+zrMpyFg8SRJA66q5ieZn+R/AX8OPDJ6akmS/YEHne8kSZI0kA4AvgY8R1M8zQK2oDlYZh/gMcDiST3lVjtJGgJJtgS+AiwC5gMv0Tx0bAHMraq/6TCeJEmSxliSTYF/qar3vMa9tWjKp5uq6vmVHE1DxuJJkgZYkgCb0SyrngocDGwCLAWmA98DLneouCRJ0mBJcizw2araressGm4WT5I0wJLsC3wG+EZV3dZemwysVVUPdRpOkiRJPdOearwXMIFm1ftFwI+A833pqJVppOsAkqSe+gTNEurbkoy0J9otAZ5N8qkk7+46oCRJknpidlWtX1Xr0ryIfB74n8BjSe5LMqfbeBoWDheXpMG2KzA6v2mkqpa2J9o9m+QAoIDTuosnSZKksZZkM+Cq0e+r6lLg0vbeVOAQ4K5u0mnYuOJJkgZUklWBXwObAlTV0tFb7c/bAr9c+ckkSZLUY+8C5gG0q96TZGKSVNVzVfVDYEm3ETUsLJ4kaUC1J5ScDpyY5DNJtmivL02yPzCpqhZ2GlKSJEm98AVg9STrV9VymvnOS4FVRj/gnCetLA4Xl6QB1b7RqiS/C3wYeAFYk2YF1F3AuVX1gw4jSpIkaYwlmQTcXFVbvca9w2lWvZ9YVYtWejgNJYsnSRoCSTYAdgDWpllWfVNV3dFtKkmSJI21JPsBf1pV+67wInL058nAVVW1S9c5NTwcLi5JQ6CqHgIe6jqHJEmSeu5e4Mkke1TVFfCybXUfBB6BZvZTuw1P6imLJ0mSJEmSBscdwLXAsUmWAvNp5jtvDhwGXNRhNg0ht9pJkiRJkjRgkvwx8EngeWAB8B7gu8CpVfV0l9k0XCyeJEmSJEkaAEn2BI4DfgZcUFWPJ9ka2BC4uqpe6DSghpJb7SRJkiRJGgxPAPOAvYGjkjwH/AI4B3ixy2AaXq54kiRJkiRpQCSZAkwD1ge2ALYFtgS+VVXzu8ym4WTxJEmSJEnSAEoSYB3gWGA28Hm322llG+k6gCRJkiRJemeSrN0WTS9TVY8B3wHmWDqpCxZPkiRJkiT1v/8B3JvklCRHJdm4qirJWsCXgWsBktgDaKVyq50kSZIkSQMgyU7AQcB+wKbAve2P54B/qKrrk6QsArQSWTxJkiRJkjRg2m13uwOTq+qirvNoeLnETpIkSZKkPpZk6yR/lWR+kq8nWacaVwC3Jdmo64waXq54kiRJkiSpjyW5CPg5zba6/YHzgJk02+5eBH5SVX/vNjt1weJJkiRJkqQ+lWRV4Oqq2rH9fjrwEHAqcB0wH/hlVS3pLqWG2cSuA0iSJEmSpLftfcCEJO8BFgGrAbdV1XHdxpIaFk+SJEmSJPWvSTQrm75Ac3rd+sDDSWYDU4A7qmpxh/k05NxqJ0mSJElSn0ryH4CTgVVpVj/NAralWWgyCfjrqrquu4QadhZPkiRJkiT1oSQbAhdW1bavcW8W8H7g7Kp6YqWHk1putZMkSZIkqT/tCzzwWjeqaiGwcOXGkV7N4kmSJEmSpP50ELBDkmuB+4GLgfOrakG3saR/41Y7SZIkSZL6UJLrgEOBAPsDe9DMd1oKPAR8qaru7i6h5IonSZIkSZL6TpLNgQeq6q720p3Ad5JMB+bQFFFPdpVPGuWKJ0mSJEmS+kySOcBWVfWTJBOqalnXmaTXMtJ1AEmSJEmS9JYdATydZHJVLUvyriS7JpnadTBpRa54kiRJkiSpzyRZCLy/qh5PsjVwIrA6MAX4TFXd3GlAqeWKJ0mSJEmS+kiSvYD729JpPeBLwLPAwcB3gS8kSZcZpVEWT5IkSZIk9ZflwGNJZgKfBLYCvlpVzwB3AO+uqkriv/nVOU+1kyRJkiSpv1wLzAPOpllQ8mdVdUt77wDgmq6CSa/kjCdJkiRJkvpQkhnAC+1KJ5JsBnwPOL6qrusymzTKZXeSJEmSJPWJJHsnuSbJfwG2fsXtZ4AvWjppPHHFkyRJkiRJfSLJasBhwO7ADsCqwPXAvwLzgXlVtby7hNLLWTxJkiRJktSn2gHj3wCOACYDR1fVqd2mkv6Nw8UlSZIkSeoD7Sl1M4EPAQH2BjYDLgJ+Avwa+GlnAaXXYPEkSZIkSVJ/OBr4R+Bu4Hbga8D9wOOjA8al8catdpIkSZIk9YEkewFHAouAAqYC84A7gdur6u4kKf+hr3HE4kmSJEmSpD6RZBVgDWAbYCtgc2AaMAP4RlXN6zCe9CoWT5IkSZIk9YG2dPowzZynK2lPsEsyB5gDnFVVL3aZUXoliydJkiRJksa5JHsDxwETgCnAb9GcYncy8NWqeqnDeNLrGuk6gCRJkiRJekNfB84DPl1VH62qTYB9gC2B34PfnHonjSv+RylJkiRJ0jiWZAKwQVWdUlXPJ1mlHSK+APhb4PAkG1XV8o6jSq9i8SRJkiRJ0vi2CXBHkjUAqurF0ZPrqupyYDvg4Q7zSa/L4kmSJEmSpHGsqu4EbgbOSrJXknVH7yU5HLi1qpa61U7jkcPFJUmSJEnqA0mOB7YCHgAmAnsA9wNnVtWPk4y43U7jjcWTJEmSJEnjVJJVaIaIPw3cBuxOs7XuReBe4OqqurezgNIbsHiSJEmSJGmcSvIx4PeBP6iqR1e4PhWYXlUPdRZOehPc/ylJkiRJ0vj1ceC8qno0yYT2hDuAAg5NsluH2aQ3ZPEkSZIkSdL4NQe4ov16pKqWJZlYVc/TzHjavLto0huzeJIkSZIkaRxKMhE4F9gXoKpean9e2n5kO+CybtJJb87ErgNIkiRJkqRXq6qlSc4CTkmyDXA2sAB4AjgMeMrB4hrvHC4uSZIkSdI4lCRVVUk2AT4NzAA2AHYALgS+W1XXjX6uy6zS67F4kiRJkiRpnEsyiaZ0mgY8AjxXVc91m0p6YxZPkiRJkiRJ6gmHi0uSJEmSJKknLJ4kSZIkSZLUExZPkiRJkiRJ6gmLJ0mSpB5K8t+S/DrJTUluSLLrW/z1myY5slf5JEmSemli1wEkSZIGVZLdgEOAnatqSZJ1gVXe4m+zKXAkcNpb+HMnVtXSt/jnSJIkjTlXPEmSJPXOhsBjVbUEoKoeq6oHkuyS5NIkc5P8a5INAZJsmeTCJDcmuS7JFsBfAnu2q6WOTzIlyT8lmZfk+iT7tr/26CRnJPkZcH5Xf2FJkqQVpaq6ziBJkjSQkqwOXAFMBS4ETgeuAi4FfqeqHk3ySeDAqvpMkl8Af1lVZyaZQvOS8H3Af6qqQ9rf84+A7arqmCRb05RMs4EjgG8CO1TVEyv3bypJkvTa3GonSZLUI1X1bJJdgD2BfWmKp28C2wEXJAGYADyYZBqwUVWd2f7aFwDaz6xoD+Bv288sSHI3TfEEcIGlkyRJGk8sniRJknqoqpYBlwCXJJkHfAH4dVXttuLnkkx/k7/lq5qoFSx+WyElSZJ6xBlPkiRJPZJkqySzVri0I3ALMKMdPE6SSUm2raqngfuSfKy9PjnJVOAZYNoKv8dlwKfaz8wG3g3c2vu/jSRJ0ltn8SRJktQ7qwOnJJmf5CZgG+AE4DDgr5LcCNwAfKD9/FHAF9vPXgVsANwELG0Hjh8PnARMaFdPnQ4cPTq8XJIkabxxuLgkSZIkSZJ6whVPkiRJkiRJ6gmLJ0mSJEmSJPWExZMkSZIkSZJ6wuJJkiRJkiRJPWHxJEmSJEmSpJ6weJIkSZIkSVJPWDxJkiRJkiSpJyyeJEmSJEmS1BP/H5Z+6n22f+lAAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 1440x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "z2ipvued0DTs",
        "colab_type": "text"
      },
      "source": [
        "### Computer Software & Hardware and Construction infrastructure activity sectors has gone up in FDIs replacing Construction development and Drugs and Pharamceuticals sector since BJP has taken over."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ufvupsw60DTs",
        "colab_type": "text"
      },
      "source": [
        "# Simple Linear Regression on the sectors"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XcEfPZJT0DTt",
        "colab_type": "code",
        "colab": {},
        "outputId": "6a343207-b9f0-49b3-ec16-e0a7b175eb98"
      },
      "source": [
        "new = df[['SERVICES SECTOR (Fin.,Banking,Insurance,Non Fin/Business,Outsourcing,R&D,Courier,Tech. Testing and Analysis, Other)']]\n",
        "new.rename(columns={'SERVICES SECTOR (Fin.,Banking,Insurance,Non Fin/Business,Outsourcing,R&D,Courier,Tech. Testing and Analysis, Other)':'Services'}, inplace=True)\n",
        "new.head()\n"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "c:\\users\\parik\\appdata\\local\\programs\\python\\python37\\lib\\site-packages\\pandas\\core\\frame.py:4218: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  return super().rename(**kwargs)\n"
          ],
          "name": "stderr"
        },
        {
          "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>Sector</th>\n",
              "      <th>Services</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2001-01-01</th>\n",
              "      <td>71.38</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2002-01-01</th>\n",
              "      <td>187.95</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2003-01-01</th>\n",
              "      <td>296.34</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2004-01-01</th>\n",
              "      <td>271.15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2005-01-01</th>\n",
              "      <td>456.15</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "Sector      Services\n",
              "2001-01-01     71.38\n",
              "2002-01-01    187.95\n",
              "2003-01-01    296.34\n",
              "2004-01-01    271.15\n",
              "2005-01-01    456.15"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "efm-DeDV0DTw",
        "colab_type": "code",
        "colab": {},
        "outputId": "1df04a85-e789-4ffd-ef7a-a5eaa1a72eed"
      },
      "source": [
        "new.plot()\n",
        "plt.show()\n",
        "\n",
        "result = adfuller(new['Services'])\n",
        "\n",
        "print('Test statistic:'+str(result[0]))\n",
        "print('p value:'+str(result[1]))\n",
        "\n"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Test statistic:-0.22235921546115114\n",
            "p value:0.9358034483444051\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NSuwLv450DTz",
        "colab_type": "code",
        "colab": {},
        "outputId": "3cd0cb49-ff44-4053-929f-d6a9c777714d"
      },
      "source": [
        "new_diff = new.diff(1).dropna(inplace=False)\n",
        "plt.figure(figsize=(20,10))\n",
        "new_diff.plot()\n",
        "plt.show()\n",
        "\n",
        "result = adfuller(new_diff['Services'])\n",
        "\n",
        "print('Test statistic:'+ str(result[0]))\n",
        "\n",
        "print('p value:'+str(result[1]))"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1440x720 with 0 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "Test statistic:-4.420722032356825\n",
            "p value:0.00027274595620595786\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LHkmnrPH0DT2",
        "colab_type": "code",
        "colab": {},
        "outputId": "e3bbc7fd-167c-4279-d8fe-e7f63ebd05e4"
      },
      "source": [
        "fig, (ax1, ax2) = plt.subplots(2,1, figsize=(12,8))\n",
        "\n",
        "plot_acf(new_diff, lags=10, zero=False, ax=ax1)\n",
        "\n",
        "plot_pacf(new_diff, lags=10, zero=False, ax=ax2)\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "c:\\users\\parik\\appdata\\local\\programs\\python\\python37\\lib\\site-packages\\statsmodels\\regression\\linear_model.py:1358: RuntimeWarning: invalid value encountered in sqrt\n",
            "  return rho, np.sqrt(sigmasq)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 864x576 with 2 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tOie8lEv0DT5",
        "colab_type": "code",
        "colab": {},
        "outputId": "66c8645a-6a85-4b20-86a6-b41497b2e194"
      },
      "source": [
        "for p in range(4):\n",
        "    for q in range(3):\n",
        "      try:\n",
        "        model = SARIMAX(new, order=(p,1,q), trend='c')\n",
        "        results = model.fit()\n",
        "        \n",
        "        print(p, q, results.aic, results.bic)\n",
        "        \n",
        "      except:\n",
        "        print(p, q, None, None)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "c:\\users\\parik\\appdata\\local\\programs\\python\\python37\\lib\\site-packages\\statsmodels\\tsa\\base\\tsa_model.py:165: ValueWarning: No frequency information was provided, so inferred frequency AS-JAN will be used.\n",
            "  % freq, ValueWarning)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "0 0 333.4474250295873 335.2281685453796\n",
            "0 1 333.52133525096326 336.19245052465175\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "c:\\users\\parik\\appdata\\local\\programs\\python\\python37\\lib\\site-packages\\statsmodels\\tsa\\base\\tsa_model.py:165: ValueWarning: No frequency information was provided, so inferred frequency AS-JAN will be used.\n",
            "  % freq, ValueWarning)\n",
            "c:\\users\\parik\\appdata\\local\\programs\\python\\python37\\lib\\site-packages\\statsmodels\\tsa\\base\\tsa_model.py:165: ValueWarning: No frequency information was provided, so inferred frequency AS-JAN will be used.\n",
            "  % freq, ValueWarning)\n",
            "c:\\users\\parik\\appdata\\local\\programs\\python\\python37\\lib\\site-packages\\statsmodels\\tsa\\statespace\\sarimax.py:961: UserWarning: Non-invertible starting MA parameters found. Using zeros as starting parameters.\n",
            "  warn('Non-invertible starting MA parameters found.'\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "0 2 329.53026890023176 333.0917559318164\n",
            "1 0 335.4670294019618 338.13814467565027\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "c:\\users\\parik\\appdata\\local\\programs\\python\\python37\\lib\\site-packages\\statsmodels\\tsa\\base\\tsa_model.py:165: ValueWarning: No frequency information was provided, so inferred frequency AS-JAN will be used.\n",
            "  % freq, ValueWarning)\n",
            "c:\\users\\parik\\appdata\\local\\programs\\python\\python37\\lib\\site-packages\\statsmodels\\tsa\\base\\tsa_model.py:165: ValueWarning: No frequency information was provided, so inferred frequency AS-JAN will be used.\n",
            "  % freq, ValueWarning)\n",
            "c:\\users\\parik\\appdata\\local\\programs\\python\\python37\\lib\\site-packages\\statsmodels\\base\\model.py:512: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals\n",
            "  \"Check mle_retvals\", ConvergenceWarning)\n",
            "c:\\users\\parik\\appdata\\local\\programs\\python\\python37\\lib\\site-packages\\statsmodels\\tsa\\base\\tsa_model.py:165: ValueWarning: No frequency information was provided, so inferred frequency AS-JAN will be used.\n",
            "  % freq, ValueWarning)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "1 1 332.8522666325143 336.4137536640989\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "c:\\users\\parik\\appdata\\local\\programs\\python\\python37\\lib\\site-packages\\statsmodels\\base\\model.py:512: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals\n",
            "  \"Check mle_retvals\", ConvergenceWarning)\n",
            "c:\\users\\parik\\appdata\\local\\programs\\python\\python37\\lib\\site-packages\\statsmodels\\tsa\\base\\tsa_model.py:165: ValueWarning: No frequency information was provided, so inferred frequency AS-JAN will be used.\n",
            "  % freq, ValueWarning)\n",
            "c:\\users\\parik\\appdata\\local\\programs\\python\\python37\\lib\\site-packages\\statsmodels\\tsa\\base\\tsa_model.py:165: ValueWarning: No frequency information was provided, so inferred frequency AS-JAN will be used.\n",
            "  % freq, ValueWarning)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "1 2 331.4325527086211 335.8844114981019\n",
            "2 0 335.1971053459906 338.75859237757527\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "c:\\users\\parik\\appdata\\local\\programs\\python\\python37\\lib\\site-packages\\statsmodels\\base\\model.py:512: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals\n",
            "  \"Check mle_retvals\", ConvergenceWarning)\n",
            "c:\\users\\parik\\appdata\\local\\programs\\python\\python37\\lib\\site-packages\\statsmodels\\tsa\\base\\tsa_model.py:165: ValueWarning: No frequency information was provided, so inferred frequency AS-JAN will be used.\n",
            "  % freq, ValueWarning)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "2 1 332.28515730986203 336.73701609934284\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "c:\\users\\parik\\appdata\\local\\programs\\python\\python37\\lib\\site-packages\\statsmodels\\base\\model.py:512: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals\n",
            "  \"Check mle_retvals\", ConvergenceWarning)\n",
            "c:\\users\\parik\\appdata\\local\\programs\\python\\python37\\lib\\site-packages\\statsmodels\\tsa\\base\\tsa_model.py:165: ValueWarning: No frequency information was provided, so inferred frequency AS-JAN will be used.\n",
            "  % freq, ValueWarning)\n",
            "c:\\users\\parik\\appdata\\local\\programs\\python\\python37\\lib\\site-packages\\statsmodels\\tsa\\base\\tsa_model.py:165: ValueWarning: No frequency information was provided, so inferred frequency AS-JAN will be used.\n",
            "  % freq, ValueWarning)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "2 2 333.691590392169 339.033820939546\n",
            "3 0 336.57569636053546 341.02755515001627\n",
            "3 1 334.1296497683129 339.4718803156899\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "c:\\users\\parik\\appdata\\local\\programs\\python\\python37\\lib\\site-packages\\statsmodels\\tsa\\base\\tsa_model.py:165: ValueWarning: No frequency information was provided, so inferred frequency AS-JAN will be used.\n",
            "  % freq, ValueWarning)\n",
            "c:\\users\\parik\\appdata\\local\\programs\\python\\python37\\lib\\site-packages\\statsmodels\\tsa\\statespace\\sarimax.py:949: UserWarning: Non-stationary starting autoregressive parameters found. Using zeros as starting parameters.\n",
            "  warn('Non-stationary starting autoregressive parameters'\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "3 2 334.7042137173754 340.93681602264854\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "c:\\users\\parik\\appdata\\local\\programs\\python\\python37\\lib\\site-packages\\statsmodels\\base\\model.py:512: ConvergenceWarning: Maximum Likelihood optimization failed to converge. Check mle_retvals\n",
            "  \"Check mle_retvals\", ConvergenceWarning)\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "U9NwsOBk0DT7",
        "colab_type": "code",
        "colab": {},
        "outputId": "af74b1a9-b8ab-4546-f9f1-db37a5a02f51"
      },
      "source": [
        "model = SARIMAX(new, order=(0,1,2), trend='c')\n",
        "results = model.fit()\n",
        "\n",
        "results.plot_diagnostics()\n",
        "plt.show()\n",
        "\n",
        "print(results.summary())"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "c:\\users\\parik\\appdata\\local\\programs\\python\\python37\\lib\\site-packages\\statsmodels\\tsa\\base\\tsa_model.py:165: ValueWarning: No frequency information was provided, so inferred frequency AS-JAN will be used.\n",
            "  % freq, ValueWarning)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 4 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "stream",
          "text": [
            "                           Statespace Model Results                           \n",
            "==============================================================================\n",
            "Dep. Variable:               Services   No. Observations:                   19\n",
            "Model:               SARIMAX(0, 1, 2)   Log Likelihood                -160.765\n",
            "Date:                Wed, 08 Jan 2020   AIC                            329.530\n",
            "Time:                        18:50:22   BIC                            333.092\n",
            "Sample:                    01-01-2001   HQIC                           330.021\n",
            "                         - 01-01-2019                                         \n",
            "Covariance Type:                  opg                                         \n",
            "==============================================================================\n",
            "                 coef    std err          z      P>|z|      [0.025      0.975]\n",
            "------------------------------------------------------------------------------\n",
            "intercept    396.6681    142.099      2.791      0.005     118.160     675.176\n",
            "ma.L1          0.0037     18.047      0.000      1.000     -35.368      35.375\n",
            "ma.L2         -0.9963      0.349     -2.856      0.004      -1.680      -0.313\n",
            "sigma2      2.693e+06   6.59e-06   4.09e+11      0.000    2.69e+06    2.69e+06\n",
            "===================================================================================\n",
            "Ljung-Box (Q):                         nan   Jarque-Bera (JB):                 0.43\n",
            "Prob(Q):                               nan   Prob(JB):                         0.80\n",
            "Heteroskedasticity (H):               3.21   Skew:                            -0.36\n",
            "Prob(H) (two-sided):                  0.18   Kurtosis:                         3.25\n",
            "===================================================================================\n",
            "\n",
            "Warnings:\n",
            "[1] Covariance matrix calculated using the outer product of gradients (complex-step).\n",
            "[2] Covariance matrix is singular or near-singular, with condition number 3.47e+30. Standard errors may be unstable.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DDWzK1DY0DT9",
        "colab_type": "code",
        "colab": {},
        "outputId": "d8b1155f-e5e2-4724-a867-35c7c1138c3a"
      },
      "source": [
        "one_step_forecast = results.get_prediction(start=-10)\n",
        "\n",
        "mean_forecast = one_step_forecast.predicted_mean\n",
        "\n",
        "confidence_intervals = one_step_forecast.conf_int()\n",
        "# confidence_intervals\n",
        "\n",
        "lower_limits = confidence_intervals.loc[:,'lower Services']\n",
        "upper_limits = confidence_intervals.loc[:,'upper Services']\n",
        "\n",
        "print(mean_forecast)\n",
        "# one_step_forecast\n",
        "# new.tail()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "2010-01-01    5487.041672\n",
            "2011-01-01    3337.650149\n",
            "2012-01-01    4786.459505\n",
            "2013-01-01    5648.053936\n",
            "2014-01-01    4861.459670\n",
            "2015-01-01    3331.156173\n",
            "2016-01-01    7146.660415\n",
            "2017-01-01    6301.490893\n",
            "2018-01-01    9309.534151\n",
            "2019-01-01    9907.225234\n",
            "Freq: AS-JAN, dtype: float64\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Jhx7NQ4g0DUA",
        "colab_type": "code",
        "colab": {},
        "outputId": "1fea99c9-bba4-4577-9f92-772db5a61e92"
      },
      "source": [
        "plt.plot(new.index, new, label='observed')\n",
        "\n",
        "plt.plot(mean_forecast.index, mean_forecast, color='r', label='forecast')\n",
        "\n",
        "plt.fill_between(lower_limits.index,lower_limits, upper_limits, color='pink')\n",
        "\n",
        "plt.xlabel('Date')\n",
        "plt.ylabel('FDI in Services Sector')\n",
        "plt.legend()\n",
        "plt.show()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lLwH4HpH0DUC",
        "colab_type": "code",
        "colab": {},
        "outputId": "3de8712d-6ce4-4a9e-eacb-d6ec0faf4dd7"
      },
      "source": [
        "dynamic_forecast = results.get_forecast(steps=5)\n",
        "\n",
        "mean_forecast = dynamic_forecast.predicted_mean\n",
        "\n",
        "confidence_intervals= dynamic_forecast.conf_int()\n",
        "\n",
        "lower_limits = confidence_intervals.loc[:,'lower Services']\n",
        "upper_limits = confidence_intervals.loc[:,'upper Services']\n",
        "\n",
        "\n",
        "print(mean_forecast)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "2020-01-01    4115.930313\n",
            "2021-01-01    8214.944160\n",
            "2022-01-01    8611.612265\n",
            "2023-01-01    9008.280369\n",
            "2024-01-01    9404.948474\n",
            "Freq: AS-JAN, dtype: float64\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-gbJ-e9V0DUE",
        "colab_type": "code",
        "colab": {},
        "outputId": "7e640e28-9154-4b83-c017-69a871943cbe"
      },
      "source": [
        "plt.plot(new.index, new, label='observed')\n",
        "\n",
        "plt.plot(mean_forecast.index, mean_forecast.values, color='r', label='forecast')\n",
        "\n",
        "plt.fill_between(mean_forecast.index, lower_limits, upper_limits, color='pink')\n",
        "\n",
        "plt.xlabel('Year')\n",
        "plt.ylabel('FDI in Services Sector')\n",
        "plt.legend()\n",
        "plt.show()\n"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "s4rRJwvn0DUG",
        "colab_type": "code",
        "colab": {},
        "outputId": "c33bb46c-6eaa-419f-dcce-5dd117795b47"
      },
      "source": [
        "forcast= results.forecast(1)\n",
        "forcast\n"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "2020-01-01    4115.930313\n",
              "Freq: AS-JAN, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 22
        }
      ]
    }
  ]
}