ML5_Forecasting_20220409.ipynb

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    "colab": {
      "name": "ML5_Forecasting_20220409.ipynb",
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "# Importing Packages"
      ],
      "metadata": {
        "id": "0eoF6ucKskFK"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "gG52jf8Sn0R7"
      },
      "outputs": [],
      "source": [
        "import sys\n",
        "import pandas as pd\n",
        "import math\n",
        "import numpy as np\n",
        "\n",
        "import matplotlib\n",
        "from matplotlib import pyplot as plt\n",
        "from matplotlib import style\n",
        "import seaborn as sns\n",
        "\n",
        "import sklearn\n",
        "from sklearn import preprocessing\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.linear_model import LinearRegression\n",
        "from sklearn.tree import DecisionTreeRegressor\n",
        "from sklearn.ensemble import RandomForestRegressor\n",
        "from sklearn.model_selection import ShuffleSplit\n",
        "from sklearn.model_selection import GridSearchCV\n",
        "from sklearn import metrics\n",
        "import xgboost\n",
        "from xgboost import XGBRegressor\n",
        "\n",
        "import datetime\n",
        "from dateutil.relativedelta import relativedelta"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#python package version information\n",
        "print('Python version: {}'.format(sys.version))\n",
        "print('NumPy version: {}'.format(np.__version__))\n",
        "print('Pandas version: {}'.format(pd.__version__))\n",
        "print('Matplotlib version: {}'.format(matplotlib.__version__))\n",
        "print('Seaborn version: {}'.format(sns.__version__))\n",
        "print('Scikit-learn version: {}'.format(sklearn.__version__))\n",
        "print('XGBoost version: {}'.format(xgboost.__version__))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xaYUMn2QD8MC",
        "outputId": "0e828dae-6602-415a-c6f6-434712b5b3d8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Python version: 3.7.13 (default, Mar 16 2022, 17:37:17) \n",
            "[GCC 7.5.0]\n",
            "NumPy version: 1.21.5\n",
            "Pandas version: 1.3.5\n",
            "Matplotlib version: 3.2.2\n",
            "Seaborn version: 0.11.2\n",
            "Scikit-learn version: 1.0.2\n",
            "XGBoost version: 0.90\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Data Preprocessing"
      ],
      "metadata": {
        "id": "cMERcPar_lpj"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "oildf = pd.read_html(\"https://www.indexmundi.com/commodities/?commodity=crude-oil-brent&months=360\")[1]\n",
        "coaldf = pd.read_html(\"https://www.indexmundi.com/commodities/?commodity=coal-australian&months=360\")[1]\n",
        "gasdf = pd.read_html(\"https://www.indexmundi.com/commodities/?commodity=natural-gas&months=360\")[4]\n",
        "sugardf = pd.read_html(\"https://www.indexmundi.com/commodities/?commodity=sugar&months=360\")[4]\n",
        "oredf = pd.read_html(\"https://www.indexmundi.com/commodities/?commodity=iron-ore&months=360\")[1]\n",
        "copperdf = pd.read_html(\"https://www.indexmundi.com/commodities/?commodity=copper&months=360\")[4]"
      ],
      "metadata": {
        "id": "SmSHA5MxPjGK"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "oildf.drop('Change', inplace = True, axis = 1)\n",
        "coaldf.drop('Change', inplace = True, axis = 1)\n",
        "gasdf.drop('Change', inplace = True, axis = 1)\n",
        "sugardf.drop('Change', inplace = True, axis = 1)\n",
        "oredf.drop('Change', inplace = True, axis = 1)\n",
        "copperdf.drop('Change', inplace = True, axis = 1)"
      ],
      "metadata": {
        "id": "qBSL_5ecArAK"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "oildf.rename(columns = {'Price': 'oil_price'}, inplace = True)\n",
        "coaldf.rename(columns = {'Price': 'coal_price'}, inplace = True)\n",
        "gasdf.rename(columns = {'Price': 'gas_price'}, inplace = True)\n",
        "sugardf.rename(columns = {'Price': 'sugar_price'}, inplace = True)\n",
        "oredf.rename(columns = {'Price': 'ore_price'}, inplace = True)\n",
        "copperdf.rename(columns = {'Price': 'copper_price'}, inplace = True)"
      ],
      "metadata": {
        "id": "Hf6wRw9AAydW"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df = (oildf.merge(coaldf).merge(gasdf).merge(sugardf).merge(oredf).merge(copperdf))\n",
        "df.index = pd.to_datetime(df['Month'], format='%b %Y')\n",
        "df.drop('Month', inplace = True, axis = 1)\n",
        "odf = df.copy()\n",
        "df"
      ],
      "metadata": {
        "id": "OJwVHZWvA2KV",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "16b50ce4-0eb1-4314-8e1f-9d8401a0d17b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            oil_price  coal_price  gas_price  sugar_price  ore_price  \\\n",
              "Month                                                                  \n",
              "1992-03-01      17.60       39.50       1.28         0.18      33.10   \n",
              "1992-04-01      18.95       39.50       1.47         0.21      33.10   \n",
              "1992-05-01      19.90       39.50       1.59         0.21      33.10   \n",
              "1992-06-01      21.15       39.50       1.56         0.23      33.10   \n",
              "1992-07-01      20.25       39.50       1.75         0.23      33.10   \n",
              "...               ...         ...        ...          ...        ...   \n",
              "2021-09-01      74.60      185.69       5.11         0.43     124.52   \n",
              "2021-10-01      83.65      224.51       5.48         0.42     122.91   \n",
              "2021-11-01      80.77      157.48       5.02         0.43      96.24   \n",
              "2021-12-01      74.31      169.65       3.73         0.42     116.96   \n",
              "2022-01-01      85.53      196.95       4.33         0.40     132.53   \n",
              "\n",
              "            copper_price  \n",
              "Month                     \n",
              "1992-03-01       2227.33  \n",
              "1992-04-01       2215.33  \n",
              "1992-05-01       2216.52  \n",
              "1992-06-01       2299.20  \n",
              "1992-07-01       2520.32  \n",
              "...                  ...  \n",
              "2021-09-01       9324.71  \n",
              "2021-10-01       9829.22  \n",
              "2021-11-01       9728.90  \n",
              "2021-12-01       9551.18  \n",
              "2022-01-01       9782.34  \n",
              "\n",
              "[359 rows x 6 columns]"
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>oil_price</th>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1992-03-01</th>\n",
              "      <td>17.60</td>\n",
              "      <td>39.50</td>\n",
              "      <td>1.28</td>\n",
              "      <td>0.18</td>\n",
              "      <td>33.10</td>\n",
              "      <td>2227.33</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1992-04-01</th>\n",
              "      <td>18.95</td>\n",
              "      <td>39.50</td>\n",
              "      <td>1.47</td>\n",
              "      <td>0.21</td>\n",
              "      <td>33.10</td>\n",
              "      <td>2215.33</td>\n",
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              "      <th>1992-05-01</th>\n",
              "      <td>19.90</td>\n",
              "      <td>39.50</td>\n",
              "      <td>1.59</td>\n",
              "      <td>0.21</td>\n",
              "      <td>33.10</td>\n",
              "      <td>2216.52</td>\n",
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              "      <th>1992-06-01</th>\n",
              "      <td>21.15</td>\n",
              "      <td>39.50</td>\n",
              "      <td>1.56</td>\n",
              "      <td>0.23</td>\n",
              "      <td>33.10</td>\n",
              "      <td>2299.20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1992-07-01</th>\n",
              "      <td>20.25</td>\n",
              "      <td>39.50</td>\n",
              "      <td>1.75</td>\n",
              "      <td>0.23</td>\n",
              "      <td>33.10</td>\n",
              "      <td>2520.32</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-09-01</th>\n",
              "      <td>74.60</td>\n",
              "      <td>185.69</td>\n",
              "      <td>5.11</td>\n",
              "      <td>0.43</td>\n",
              "      <td>124.52</td>\n",
              "      <td>9324.71</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-10-01</th>\n",
              "      <td>83.65</td>\n",
              "      <td>224.51</td>\n",
              "      <td>5.48</td>\n",
              "      <td>0.42</td>\n",
              "      <td>122.91</td>\n",
              "      <td>9829.22</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-11-01</th>\n",
              "      <td>80.77</td>\n",
              "      <td>157.48</td>\n",
              "      <td>5.02</td>\n",
              "      <td>0.43</td>\n",
              "      <td>96.24</td>\n",
              "      <td>9728.90</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-12-01</th>\n",
              "      <td>74.31</td>\n",
              "      <td>169.65</td>\n",
              "      <td>3.73</td>\n",
              "      <td>0.42</td>\n",
              "      <td>116.96</td>\n",
              "      <td>9551.18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-01-01</th>\n",
              "      <td>85.53</td>\n",
              "      <td>196.95</td>\n",
              "      <td>4.33</td>\n",
              "      <td>0.40</td>\n",
              "      <td>132.53</td>\n",
              "      <td>9782.34</td>\n",
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              "<p>359 rows × 6 columns</p>\n",
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          "metadata": {},
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    {
      "cell_type": "code",
      "source": [
        "forecast_out = int(math.ceil(0.01 * len(df))) # 1% = 4. \n",
        "df.drop(index=df.index[-forecast_out:], axis=0, inplace=True)\n",
        "df"
      ],
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        "id": "0T12WKd5eF8z",
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      },
      "execution_count": null,
      "outputs": [
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          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            oil_price  coal_price  gas_price  sugar_price  ore_price  \\\n",
              "Month                                                                  \n",
              "1992-03-01      17.60       39.50       1.28         0.18      33.10   \n",
              "1992-04-01      18.95       39.50       1.47         0.21      33.10   \n",
              "1992-05-01      19.90       39.50       1.59         0.21      33.10   \n",
              "1992-06-01      21.15       39.50       1.56         0.23      33.10   \n",
              "1992-07-01      20.25       39.50       1.75         0.23      33.10   \n",
              "...               ...         ...        ...          ...        ...   \n",
              "2021-05-01      68.04      107.04       2.89         0.38     207.72   \n",
              "2021-06-01      73.07      129.97       3.24         0.38     214.43   \n",
              "2021-07-01      74.39      151.97       3.80         0.39     214.14   \n",
              "2021-08-01      70.02      169.58       4.05         0.43     162.16   \n",
              "2021-09-01      74.60      185.69       5.11         0.43     124.52   \n",
              "\n",
              "            copper_price  \n",
              "Month                     \n",
              "1992-03-01       2227.33  \n",
              "1992-04-01       2215.33  \n",
              "1992-05-01       2216.52  \n",
              "1992-06-01       2299.20  \n",
              "1992-07-01       2520.32  \n",
              "...                  ...  \n",
              "2021-05-01      10161.97  \n",
              "2021-06-01       9631.50  \n",
              "2021-07-01       9450.82  \n",
              "2021-08-01       9370.14  \n",
              "2021-09-01       9324.71  \n",
              "\n",
              "[355 rows x 6 columns]"
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              "      <th>Month</th>\n",
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              "      <th>1992-03-01</th>\n",
              "      <td>17.60</td>\n",
              "      <td>39.50</td>\n",
              "      <td>1.28</td>\n",
              "      <td>0.18</td>\n",
              "      <td>33.10</td>\n",
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              "      <th>1992-04-01</th>\n",
              "      <td>18.95</td>\n",
              "      <td>39.50</td>\n",
              "      <td>1.47</td>\n",
              "      <td>0.21</td>\n",
              "      <td>33.10</td>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <th>1992-05-01</th>\n",
              "      <td>19.90</td>\n",
              "      <td>39.50</td>\n",
              "      <td>1.59</td>\n",
              "      <td>0.21</td>\n",
              "      <td>33.10</td>\n",
              "      <td>2216.52</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1992-06-01</th>\n",
              "      <td>21.15</td>\n",
              "      <td>39.50</td>\n",
              "      <td>1.56</td>\n",
              "      <td>0.23</td>\n",
              "      <td>33.10</td>\n",
              "      <td>2299.20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1992-07-01</th>\n",
              "      <td>20.25</td>\n",
              "      <td>39.50</td>\n",
              "      <td>1.75</td>\n",
              "      <td>0.23</td>\n",
              "      <td>33.10</td>\n",
              "      <td>2520.32</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-05-01</th>\n",
              "      <td>68.04</td>\n",
              "      <td>107.04</td>\n",
              "      <td>2.89</td>\n",
              "      <td>0.38</td>\n",
              "      <td>207.72</td>\n",
              "      <td>10161.97</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-06-01</th>\n",
              "      <td>73.07</td>\n",
              "      <td>129.97</td>\n",
              "      <td>3.24</td>\n",
              "      <td>0.38</td>\n",
              "      <td>214.43</td>\n",
              "      <td>9631.50</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-07-01</th>\n",
              "      <td>74.39</td>\n",
              "      <td>151.97</td>\n",
              "      <td>3.80</td>\n",
              "      <td>0.39</td>\n",
              "      <td>214.14</td>\n",
              "      <td>9450.82</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-08-01</th>\n",
              "      <td>70.02</td>\n",
              "      <td>169.58</td>\n",
              "      <td>4.05</td>\n",
              "      <td>0.43</td>\n",
              "      <td>162.16</td>\n",
              "      <td>9370.14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-09-01</th>\n",
              "      <td>74.60</td>\n",
              "      <td>185.69</td>\n",
              "      <td>5.11</td>\n",
              "      <td>0.43</td>\n",
              "      <td>124.52</td>\n",
              "      <td>9324.71</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>355 rows × 6 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-02793664-f3ea-4371-8d13-bfe5e906a641')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
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              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-02793664-f3ea-4371-8d13-bfe5e906a641 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-02793664-f3ea-4371-8d13-bfe5e906a641');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Dataset Analysis"
      ],
      "metadata": {
        "id": "mgqJb-WwEMci"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "df.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "T9K_9Nu6BN11",
        "outputId": "25d7bb70-df63-4eac-fd1f-25f45e672214"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "DatetimeIndex: 355 entries, 1992-03-01 to 2021-09-01\n",
            "Data columns (total 6 columns):\n",
            " #   Column        Non-Null Count  Dtype  \n",
            "---  ------        --------------  -----  \n",
            " 0   oil_price     355 non-null    float64\n",
            " 1   coal_price    355 non-null    float64\n",
            " 2   gas_price     355 non-null    float64\n",
            " 3   sugar_price   355 non-null    float64\n",
            " 4   ore_price     355 non-null    float64\n",
            " 5   copper_price  355 non-null    float64\n",
            "dtypes: float64(6)\n",
            "memory usage: 19.4 KB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YQx0SUQIBUYH",
        "outputId": "a40d945d-ef59-4f3e-dd79-11aa0f58cdde"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        oil_price  coal_price   gas_price  sugar_price   ore_price  \\\n",
              "count  355.000000  355.000000  355.000000   355.000000  355.000000   \n",
              "mean    51.461746   61.197070    3.820028     0.288620   72.615944   \n",
              "std     32.414924   32.769263    2.142240     0.112745   49.475330   \n",
              "min      9.800000   22.250000    1.280000     0.110000   26.470000   \n",
              "25%     21.080000   33.550000    2.300000     0.210000   30.030000   \n",
              "50%     46.840000   52.490000    3.030000     0.270000   62.630000   \n",
              "75%     72.065000   83.690000    4.635000     0.350000   99.810000   \n",
              "max    133.870000  185.690000   13.520000     0.650000  214.430000   \n",
              "\n",
              "       copper_price  \n",
              "count    355.000000  \n",
              "mean    4623.174901  \n",
              "std     2547.912836  \n",
              "min     1377.280000  \n",
              "25%     2030.415000  \n",
              "50%     4694.540000  \n",
              "75%     6861.865000  \n",
              "max    10161.970000  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-986ea909-be86-42ea-80fb-1868cf15a332\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>oil_price</th>\n",
              "      <th>coal_price</th>\n",
              "      <th>gas_price</th>\n",
              "      <th>sugar_price</th>\n",
              "      <th>ore_price</th>\n",
              "      <th>copper_price</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>355.000000</td>\n",
              "      <td>355.000000</td>\n",
              "      <td>355.000000</td>\n",
              "      <td>355.000000</td>\n",
              "      <td>355.000000</td>\n",
              "      <td>355.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>51.461746</td>\n",
              "      <td>61.197070</td>\n",
              "      <td>3.820028</td>\n",
              "      <td>0.288620</td>\n",
              "      <td>72.615944</td>\n",
              "      <td>4623.174901</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>32.414924</td>\n",
              "      <td>32.769263</td>\n",
              "      <td>2.142240</td>\n",
              "      <td>0.112745</td>\n",
              "      <td>49.475330</td>\n",
              "      <td>2547.912836</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>9.800000</td>\n",
              "      <td>22.250000</td>\n",
              "      <td>1.280000</td>\n",
              "      <td>0.110000</td>\n",
              "      <td>26.470000</td>\n",
              "      <td>1377.280000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>21.080000</td>\n",
              "      <td>33.550000</td>\n",
              "      <td>2.300000</td>\n",
              "      <td>0.210000</td>\n",
              "      <td>30.030000</td>\n",
              "      <td>2030.415000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>46.840000</td>\n",
              "      <td>52.490000</td>\n",
              "      <td>3.030000</td>\n",
              "      <td>0.270000</td>\n",
              "      <td>62.630000</td>\n",
              "      <td>4694.540000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>72.065000</td>\n",
              "      <td>83.690000</td>\n",
              "      <td>4.635000</td>\n",
              "      <td>0.350000</td>\n",
              "      <td>99.810000</td>\n",
              "      <td>6861.865000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>133.870000</td>\n",
              "      <td>185.690000</td>\n",
              "      <td>13.520000</td>\n",
              "      <td>0.650000</td>\n",
              "      <td>214.430000</td>\n",
              "      <td>10161.970000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-986ea909-be86-42ea-80fb-1868cf15a332')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
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              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
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              "\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-986ea909-be86-42ea-80fb-1868cf15a332 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-986ea909-be86-42ea-80fb-1868cf15a332');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "continuous_features = [feature for feature in df.columns if df[feature].dtypes != 'O']\n",
        "print(continuous_features)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UkhQDvdzBaI2",
        "outputId": "64ef3516-a9c6-471b-ceaa-b18c61d7edfc"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "['oil_price', 'coal_price', 'gas_price', 'sugar_price', 'ore_price', 'copper_price']\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "style.use('ggplot')\n",
        "df.plot(y = continuous_features)\n",
        "plt.xlabel('Date')\n",
        "plt.ylabel('Price')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "exnD4blwB-zx",
        "outputId": "b20395ce-adf5-496c-fc0b-5e8f6898e3ad"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_min_max_scaled = df.copy()\n",
        "for column in df:\n",
        "    df_min_max_scaled[column] = (df_min_max_scaled[column] - df_min_max_scaled[column].min()) / (df_min_max_scaled[column].max() - df_min_max_scaled[column].min())\n",
        "df_min_max_scaled.plot(y = continuous_features)\n",
        "plt.xlabel('Date')\n",
        "plt.ylabel('Normlaized Price')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Ptrw3dFXzz-i",
        "outputId": "877307f6-8354-409a-f82a-7f677f6427a0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "cor_mat = df.corr()\n",
        "fig = plt.figure(figsize=(7, 7))\n",
        "sns.heatmap(cor_mat,annot = True)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "kH14VHkuEWyG",
        "outputId": "12d05f76-b8f8-43d4-e831-c6370e450827"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 504x504 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(20, 60))\n",
        "plotnumber = 1\n",
        "for feature in continuous_features:\n",
        "    ax = plt.subplot(12, 3, plotnumber)\n",
        "    sns.histplot(df[feature], color = \"red\", kde = True, stat = \"density\", linewidth = 0)\n",
        "    plotnumber+=1\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-feZWrLBEnbI",
        "outputId": "9939c40a-b293-4c76-e3ac-c7c114090601"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1440x4320 with 6 Axes>"
            ],
            "image/png": 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RERERaV3smzZhLyjAm5JC9bXXgsUCgHfYMOybNxOzZQt4vVSNH69BKhExhH7ziIiIiIiItGLW3buJ2bIF78CBVF93XXhwCgCLBe/IkVRdey22PXuwb9liXFARadM0QCUiIiIiItJaVVcTs3YtgS5dqM7IOOc6U760NHz9+2P/5BMs+/dHOKSIiAaoREREREREWq2YTZsweTxUZWTUfnPqTCYTVRkZBF0uYvPywOeLXEgRETRAJSIiIiIi0iqZjh/HVlCA76qrCCYlXbiCzUZ1RgbmEyc01U9EIk4DVCIiIiIiIq2QfetWMJvxDh9e7zqB7t1rpvpt3YrpxIlmTCciUpsGqERERERERFoZU0UFti+/xNe/P6GEhIuqWz1yJJhMxHzySTOlExE5mwaoREREREREWhnb9u0QDOJNS7vouiGnE9/gwVh37sR87FgzpBMROZsGqERERERERFqTYBDbjh0EevYk1LFjg5qoHjoU7HatRSUiEaMBKhERERERkVbEsncv5lOn8A0a1PBG4uLwDRqEdfduTMePN104EZFz0ACViIiIiIhIK2L/4guC8fH4L7+8Ue14U1PBbMa+bVsTJRMROTcNUImIiIiIiLQSJo8Hy969+Pr3B4ulUW2FEhLw9euHbccOqKxsooQiInWzGh1ARERERESkqRUUFLBy5UqCwSAZGRlMmDCh1r+/8847fPjhh1gsFtq1a8cDDzxAp06dAMjKyqJHjx4AJCYmMmvWrIjnbyhrYSGmUAh/375N0p5vyBDsO3Zg27kTX2pqk7QpIlIXDVCJiIiIiEirEgwGWbFiBTk5ObjdbmbPnk1aWhrdunULl+nZsyfz588nJiaG999/n1deeYUZM2YAYLfbeeaZZ4yK3yjWXbsIdOxIMDGxSdoLdupEoGtX7Nu340tJAZOpSdoVETmTpviJiIiIiEirUlhYSFJSEl26dMFqtZKenk5+fn6tMgMHDiQmJgaA3r17U1paakTUJmXyeLAcOoS/T58mHUjyXnUV5uPHsRw40GRtioicSQNUIiIiIiLSqpSWluJ2u8Of3W73eQeg1q5dy+DBg8OffT4fjzzyCHPmzOEf//hHs2ZtSuHpfX36NGm7/j59CMbGYtu+vUnbFRE5nab4iYiIiIhIm7VhwwaKioqYO3du+NiyZctwuVwcOXKEJ554gh49epCUlHRW3by8PPLy8gCYP38+iU00re5iWBwOAMxmMzH79hHq2JHYHj2afirekCFYN2/G4fdDu3bhwzFNeM1Wq9WQ77Ap6RqM19LzQ9u9Bg1QiYiIiIhIq+JyuSgpKQl/LikpweVynVXu888/580332Tu3LnYbLZa9QG6dOlC//792bdvX50DVJmZmWRmZoY/Hzt2rCkvo16cHg8ADqsV8969+K66iupm2HHP1K8fCZ98gj8/H++IEeHj5U14zYmJiYZ8h01J12C8lp4fWt81dO3atV51IjZAdaFdNHw+H7m5uRQVFeF0OsnOzqZz586Ul5ezcOFCCgsLGT16NFOmTAnXmTt3LmVlZdjtdgBycnJo3779OdsSEREREZHWLzk5meLiYo4ePYrL5WLTpk1Mnz69Vpm9e/eyfPlyHn30Udq3bx8+XlFRQUxMDDabjZMnT7Jr1y5uvvnmSF/Cxdu3D1MggL9Xr2ZpPtShA/7LLsP2xRd4hw0Ds1aLEZGmFZEBqvrsorF27Vri4+NZsmQJGzduZNWqVcyYMQObzUZWVhYHDhzg4MGDZ7U9ffp0kpOTax07V1siIiIiItL6WSwWJk+ezLx58wgGg4wZM4bu3buzevVqkpOTSUtL45VXXqGqqoqFCxcCNU/7Z82axTfffMMLL7yA2WwmGAwyYcKEWvct0cpUWEjIZiPQjFl9gwYR9847WA4cINCzZ7OdR0TapogMUJ2+iwYQ3kXj9F/0W7du5fbbbwdg+PDhvPjii4RCIWJjY+nbty+HDx+u9/nO1ZZJW6KKiIiIiLQJKSkppKSk1DqWlZUV/vnXv/51nfWuvPJKFixY0KzZmlwohGnPHvyXXQYWS7Odxt+rF6GYGGxffqkBKhFpchEZoKprF409e/acs4zFYsHhcFBeXk670xbgq8uyZcswm80MGzaMiRMnYjKZ6t1WUy1q+MPChM3JbDbjsFjgu+/g1CmIj6/ZFtfpbPZzN4WWvsib8htL+UVERETOzVxaiqm8nMCwYc17IqsVX9++2HbsgOpqiIlp3vOJSJvSohdJnz59Oi6Xi8rKShYsWMCGDRu47rrr6l2/qRY1/GFhwuZiKi3FkZ+P+auvMAUC4ePmV1+lKjOT8l/+Ev+AAc2aobFa+iJvym8s5TdWfRc1FBEREWNY9u8HqHmDqpn5+vfHvn07tl278F11VbOfT0TajogMUNVnF40fyrjdbgKBAB6PB+cF3g76oY24uDiuueYaCgsLue666xrUVlQKhbDn52P/5JOapxUDB+Lv2ZNQfDymU6cIut043niD2P/5H05NnszJOXP0FENEREREpI2xHjhAqGNHQqct9t5cgklJBFwurDt3aoBKRJpURLZeOH0XDb/fz6ZNm0hLS6tVJjU1lXXr1gGwefNmBgwYcN41owKBACdPngTA7/ezbds2unfv3qC2olIgQOzf/kbMxx/jT04m+MADVGdkEEhOrukUkpM5+eSTHNm4Ec9dd5GwYgWJEydi/u47o5OLiIiIiEikBAJYDh0idPnlkTmfyYS/f3+s336LqawsMucUkTYhIm9Q1WcXjbFjx5Kbm8u0adNISEggOzs7XH/q1Kl4PB78fj/5+fnk5OSQmJjIvHnzCAQCBINBBg0aFJ6ud762WoRQiNgPPsC2cyfVI0bgHT4cR3w81DGVMNShAyfmzaM6PZ0Ov/wl7ttuo2T1aoJJSQYEFxERERGRSDIfOYLJ6yUYqQEqwNevH/aPP8a2c2fEzikirV/E1qC60C4adrudmTNn1ll36dKldR7/z//8zzqPn6+tlsC+adP/Dk6NGFGvOlXjx1OamIjrzjtx//znHHvrLUIdOjRzUhERERERMZJ1/35CAD17QigUkXOGnE4Cl12G7Z//hGAQzBGZmCMirZx+k0QZy759xGzZgm/AALzDh19UXe+wYZS+9BLW/ftx3XsveL3NlFJERERERKKB5dAhgp06QVxcRM/r698f88mT2PPzI3peEWm9NEAVRUweD7HvvUfA7aZq7FhowLpZ3hEjOL5gATGffEK7J59shpQiImI4r1cPIUREBLxeLMXFBLp1i/ip/VdcQchmI+711yN+bhFpnSI2xU8uLGbdOkzV1VTedhvYbA1up/LWW7F9/jkJy5fjvfpqqn760yZMKSIihggGse3Yga2gAPOxY5iAoMOBv18/vGdMoRcRkbbBtn07Jr+fQLduWCJ+chv+K64g7u23OfHEExAbG+kEItLKaIAqSlj278f21VdUDx9OMDGx0e2dnDMH+6ef0uGRRzg6bBjBLl2aIKWISOQVFBSwcuVKgsEgGRkZTJgwoda/+3w+cnNzKSoqwul0kp2dTefOnSkvL2fhwoUUFhYyevRopkyZEq4zd+5cysrKsNvtAOTk5NA+AltzN5Tp1Cni3noLy5EjBJKSatYntFgwHz6M7dNPse3Yge+qq6i89Vajo4qISATFbNkCQODSSw05v69fP2z//Cexa9dSdeONhmQQkdZDA1TRIBgkZu1agh064B06tGnatNkoW7SIzjfcQPvZsylbsaJBUwZFRIwUDAZZsWIFOTk5uN1uZs+eTVpaGt1Om8qwdu1a4uPjWbJkCRs3bmTVqlXMmDEDm81GVlYWBw4c4ODBg2e1PX36dJKTkyN5OQ1iKi/H8dprmE6dovLGG/FfeWWt3+em48eJfe89Ok6bhmXfPipmzNDvexGRNsK+eTMBt5uQw2HI+QM9ehDo3Jm411/XAJWINJrWoIoCth07sJSVUT1qFFibbswwkJzMyf/4D+L+9jdi//KXJmtXRCRSCgsLSUpKokuXLlitVtLT08k/YzHWrVu3Mnr0aACGDx/Ojh07CIVCxMbG0rdv3/BbUi2S30/cX/6CqbISz2234e/b96zBp1CHDlT+7Gd4fvYz2i1YgPPZZw0KKyIiERUIYM/PN+ztKQDMZionTCD2ww8xlZUZl0NEWgW9QWU0nw/7J5/g79oVfzM8yT/1//1/xL3zDu3nzME7cmSTTB8UEYmU0tJS3G53+LPb7WbPnj3nLGOxWHA4HJSXl9OuXbvztr1s2TLMZjPDhg1j4sSJmOp46ygvL4+8vDwA5s+fT2I9f4dardZaZS0NfLJtevddzEeOEPjZz4i94orzlg289BKB+Hicv/sdcQMGEPy3fztnnmgQbZmiLQ9EX6ZoywPRlyna8kB0ZpKmYd21C3NFBYGuXQ3N4Zk4kYQXXiDunXfw3HmnoVlEpGXTAJXBbNu3Yz51iqqbbmqeKRkWC8cXLqTTv/wL7R57jOPLljX9OUREWpjp06fjcrmorKxkwYIFbNiwgeuuu+6scpmZmWRmZoY/Hzt2rF7tJyYm1irr9HguOqPlwAEcn31G9dVX4+3WDS7QRnlpKTz+OO7CQuwPPkjZJZfgGzKkzjzRINoyRVseiL5M0ZYHoi9TtOWByGTqavAASVtl37YNwPABKv+AAfj69CHu9dc1QCUijaIpfkby+bBv3Yq/R49mfTXX36cPFVOn4vjzn7F/v5CiiEhL4HK5KCkpCX8uKSnB5XKds0wgEMDj8eB0Oi/YLkBcXBzXXHMNhYWFTZy8kfx+Yj78kGD79niHD69/PZuN0v/7fwl07kzHBx/EdPJk82UUERFD2bdtq1l/yuhNPkwmKidOJCY/H8v+/cZmEZEWTW9QGci2Ywdmj4eqYcMaVN+5YEH9C/v9BBMS6Pjv/45n0iQwN3xssvzhhxtcV0TkYiQnJ1NcXMzRo0dxuVxs2rSJ6dOn1yqTmprKunXr6NOnD5s3b2bAgAF1Ttf7QSAQ4NSpU7Rr1w6/38+2bdsYNGhQc1/KRbFt346lrAzPLbeAzXZRdUMdOlC2dCmJEyfS/te/5vhzzzVTShERMZLt00/xpaRExcYYlbfcQrvf/Ia4N9+kIjvb6Dgi0kJpgMoowWDNU4+uXQmcthtVs7HZqB41irj/+R9sX36JL8puxkRE6mKxWJg8eTLz5s0jGAwyZswYunfvzurVq0lOTiYtLY2xY8eSm5vLtGnTSEhIIPu0P4ynTp2Kx+PB7/eTn59PTk4OiYmJzJs3j0AgQDAYZNCgQbWm8RnO58Oen1/zdu3llzesiauvpmLqVJyLF+OZOBFuvbWJQ4qIiJFMZWXYvv6ayttvx+T1Gh2HwKWXUj1iBI7XX6fil7+MikEzEWl5NEBlEGthIeaTJ6m87rqI/QL3X3kl/u3bsX/8Mb4+fSAmJiLnFRFpjJSUFFJSUmody8rKCv9st9uZOXNmnXWXLl1a5/H//M//bLqATcy2fXvN27UjRjSqnfLp04n7y1/oMHs2wR//uInSiYhINLB/+ikA3tRUYj75xOA0NSonTqTDr36Fbft2fIMHGx1HRFogrUFlENtnnxFs375Zdu47J5OJ6tGjMVVWErN5c+TOKyIi9eP3N93ahHFxHJ8/H+u+fVh+85umySciIlHB/umnhMxmfD/6kdFRwipvvJFQTAxxr79udBQRaaE0QGUA85EjWL/5Bu+QIY1aC6ohgl264B8wAFtBgRbPFRGJMtbduzF7PHjT0pqkPe+11+K57TbMCxZg/eqrJmlTRESMZ9+2DX+/foTi442OEhZq356qzEzi/vxn8PmMjiMiLZAGqAxg++ILQlYrvv79DTl/9ffTRqLldWAREQFCIeyffUbA5SJw2WVN1uzJxx+H9u1pn5MDoVCTtSsiIgYJBLB99hne1FSjk5zFc9ttWEpKiNmwwegoItICaYAq0nw+bF99hb9PH4iNNSRCqF07fD/6EdadOzGftn27iIgYx1xcjOXIkZp1O5pwbcKgy0XgsceI+eQTYt9/v8naFRERY1j37MFcUYH3jPUZo0H16NEEO3TQND8RaRANUEWYdfduTF4vvoEDDc3hHToUbDbsGzcamkNERGrYduwgZLM1y9u1wXY1HncAACAASURBVHvvxde7N+2efBKiYLcnERFpOPu2bQBR+QYVdjuVP/0pcX/7G6bycqPTiEgLowGqCLPt2EGwQ4fGL37bSCGHA29qKrbCQszFxYZmERFp83w+bLt21bxda7c3fftWKydzcrDu3Uv8yy83ffsiIhIx9m3bCHTsSODyy42OUifPxImYqqqI/etfjY4iIi2MNVInKigoYOXKlQSDQTIyMpgwYUKtf/f5fOTm5lJUVITT6SQ7O5vOnTtTXl7OwoULKSwsZPTo0UyZMgWA6upqFi5cyJEjRzCbzaSmpvKLX/wCgHXr1vHyyy/jcrkAGDduHBkZGZG61HMylZZi/eYbqq+9tkmnbzSUNzUVW0EBMRs3UnnbbUbHERFps6x79mDy+fANGNBs56jOyKD62mtxLlyIZ+JEQh06NNu5RESiwYXuP9555x0+/PBDLBYL7dq144EHHqBTp05Azf3EG2+8AcCtt97K6NGjIx3/nGyffoovJSUq7ifq4ktNxX/ZZThef53Kn/3M6Dgi0oLU+w2q/Px8AoFAg04SDAZZsWIFjz76KIsWLWLjxo0cOnSoVpm1a9cSHx/PkiVLGD9+PKtWrQLAZrORlZXFnXfeeVa7P/nJT/jd737Hb3/7W3bt2sVnn30W/rf09HSeeeYZnnnmmagYnAKw79hByGQybHH0s9jteIcNw3rgAJb9+41OIyKtWGP6kLbA9uWXBNu3b963a00mTvz615hOnMD53HPNdx4RkSbU0P6jPvcfPXv2ZP78+Tz77LMMHz6cV155BYCKigrWrFnD008/zdNPP82aNWuoqKhokutpLNPJk9j27InK9afCTCYqb70V+8aNmqkhIhel3gNUr732Gvfddx8rVqxgz549F3WSwsJCkpKS6NKlC1arlfT0dPLz82uV2bp1a/jJxPDhw9mxYwehUIjY2Fj69u2L/YwpDzExMQz8fh0nq9XK5ZdfTkk0L/gdCGDduRN/r15RtR2s76qrCDqdxHz8sXZ3EpFm05g+pLUzVVRgOXiw5uFFMz8N9w8YgCcri/g//AHLwYPNei4RkabQ0P6jPvcfAwcOJCYmBoDevXtTWloK1Lx5ddVVV5GQkEBCQgJXXXUVBQUFTXdRjWDbsQOo+Rs+mnluvRVTKETcn/9sdBQRaUHqPcXvmWeeYd++fXz00UcsWLCAmJgYRo0axbXXXkvnzp3PW7e0tBS32x3+7Ha7z+pgTi9jsVhwOByUl5fTrl27C2Y7deoU27Zt48Ybbwwf27JlC//85z+55JJLuOuuu0hMTDyrXl5eHnl5eQDMnz+/zjL1YXE4Llxo927MHg+htDQc9Sl/BrPZ3KB69TJ6NJa338Zx4AD063fB4jEN+J6sVmuDv99ooPzGUv6WrzF9SGtn3b0bE+C/8sqInK/84YdxvPUWzt/+luNLlkTknCIiDdXQ/qM+9x+nW7t2LYMHD66zrsvlCg9eGc32xRdA9A9QBXr1wjtkCI41azj17/9udBwRaSEuag2qnj170rNnT+644w6++OILXn75ZV577TX69u1LZmYmI0eOxGyO7LrrgUCA5557jh//+Md06dIFgNTUVEaOHInNZuODDz5g6dKlPP7442fVzczMJDMzM/z52LFjDcrg9HguWCZ2+3ZMsbF4kpKgHuXP5HA48DSgXr0kJ+NwueDvf8fTvTtc4L9heQO+p8TExAZ/v9FA+Y2l/Mbq2rVrk7QTjX1INLDt3k0gMZHg9+smNrdg165U3HsvztxcTt13H75BgyJyXhGRhmru/mPDhg0UFRUxd+7ci67bVA+868uyezehbt1w9e37v8e+f4jdrA+0z+NcD6/Nd92FNTubTsXFhOrZ17SGh3q6BuO19PzQdq/hohdJP3z4MB999BEfffQRJpOJrKwsEhMTee+999iyZQu/+tWvzqrjcrlqTb8rKSkJL2B+Zhm3200gEMDj8eB0Oi+Y5/e//z1JSUmMHz8+fOz0ehkZGeH55Ibx+bB+/XXN9A2LxdgsdTGb8aanE/fOO1i/+gp/tKyRJSKtTkP6kNbMVF6O5dtvqR45MqLnrZg6FceqVbR76ilK/vjHqF1oV0TkBxfbf9Tn/gPg888/580332Tu3LnYbLZw3Z07d4bLlJaW0v8cfx831QPv+uq0dSve/v0pO+08Pzwsb9YH2udxrofX5rFj6WK1UvXii5TPmVOvtlr6Qz3QNUSDlp4fWt811PeBd70HqN577z0++ugjiouLSU9P56GHHqJPnz7hfx82bBj33ntvnXWTk5MpLi7m6NGjuFwuNm3axPTp02uVSU1NZd26dfTp04fNmzczYMAATBf4g/mPf/wjHo+Hfz/jtdGysjI6duwI1Kxt1a1bt/peZrOwFhVh8vsjNn2jIfy9exPo3JmYTZtqckbjQJqItFiN6UNaM+v30018p30XkRBq146K7GzaP/44MevXUx1Fu1OJiJyuof1Hfe4/9u7dy/Lly3n00Udp3759+PjgwYN59dVXwwujb9++nUmTJjXTFdafqaIC69dfU3nGboTRKuh2Uz16NI433qD8kUd0fyEiF1TvAaqCggJuuukm0tLSwk8XThcTE3POJ98Wi4XJkyczb948gsEgY8aMoXv37qxevZrk5GTS0tIYO3Ysubm5TJs2jYSEBLKzs8P1p06disfjwe/3k5+fT05ODnFxcbzxxhtceumlzJo1C4Bx48aRkZHBX//6V7Zu3YrFYiEhIYEHH3zwYr+XJmX96iuC8fHNuztTY5lMVI8ciePNN7Ht2IHvRz8yOpGItCKN6UNaM2thIQG3m9D3D1Ui6dS//RvxL75Iu6ee4rtrr9WNg4hEpYb2H/W5/3jllVeoqqpi4cKFQM3T/lmzZpGQkMDEiROZPXs2ALfddhsJCQnNe6H1YPvyS0yhUIuamu2ZOBFXXh72Tz7Be801RscRkShX7wGq/v37M2LEiLOOv/POO9x0000A/Og8gxopKSmknLEdalZWVvhnu93OzJkz66y7dOnSOo+/9tprdR6fNGlSVDzlAKCqCuu+fTUDPlG+tkqgZ0/8l16KffPmmumIdfwRICLSEI3tQ1qlykos33yDd+hQY85vt3Ny1ixcDz5I3BtvUHn77cbkEBE5j8b0Hxe6//j1r399zvOOHTuWsWPHNiRyswkvkN6CBqiqrr+eYEICjjfe0ACViFxQvUdMXn/99Ys6LjWsX3+NKRDAF8XT+8JMJrwjR2I+dQpblGylKyKtg/qQs1mLijCFQviTkw3LUPWTn+D90Y9w/va3UFlpWA4RkXNR//G/bJ9/TqBLF4LfbwzVIsTFUTV+PLHvvotJ/YyIXMAF36DasWMHULNb3g8//+DIkSPExcU1T7JWwvbVVwTbtyeYlGR0lHoJdOuGv2dPYvLza7avjYkxOpKItGDqQ87N+vXXBBMSjL3RMJs5OWcOiT/7GQkrV1Jh8JR4EZEfqP84m23HDnwDBxod46J5Jk7EsXo1Me+/T9XNNxsdR0Si2AUHqJ5//nkAfD5f+GcAk8lEhw4dmDx5cvOla+FMHg+WAwfwXn11i9ohqXrkSOJXrcK+bRve9HSj44hIC6Y+5BwCAaz79+Pr18/w/sE7ciRVY8eSsGQJp37+c0J17HIlIhJpba3/cC5YcP4CPh/W3bsJdux44bJRxjtiBP5LL8Xxxz9qgEpEzuuCA1Q/rP+Um5vLQw891OyBWhNrYWHN9I2WML3vNMEuXfD17o192zZ8Q4YQaoNPqESkaagPqZvlm28w+Xz4L7/c6CgAnJwzh07XX49zyRJOPv640XFERNR/nMH83XeYQiECLWl63w/MZjw//zntFizAcuAAgR49jE4kIlGq3mtQqWO4eNbCwprpfYmJRke5aN70dPD7sf/jH0ZHEZFWQH1IbZZ9+wiZzQS6dzc6CgD+vn3x/OxnxP/hD1gOHjQ6johImPqPGpYjRwAIdu5scJKG8WRlETKbcfzxj0ZHEZEodt43qGbMmMGiRYsAeOCBB85Z7vTXbuV71dVYDhzAN2SI4dM3GiLoduPv3x9bQQHelBRCTqfRkUSkhVEfcm7W/fsJXHop2O1GRwkrf/hhHG+9hfO3v+X4kiVGxxGRNkz9x9ksR48SdDgIJSQYHaVBgpdeSvXo0ThWr6Z85kyw1nszeRFpQ877m+H+++8P/zxt2rRmD9OaWPfuxRQM4uvd2+goDVY9fDjWr74iZuNGqsaNMzqOiLQw6kPqZqqowPLdd1RH2Xbbwa5dqbj3Xpy5uZyaPLnmAYuIiAHUf5zNfORIzdtTLfDB9w88v/gFrilTiFm7luobbjA6johEofMOUPXt2zf8c//+/Zs9TGtiLSwkGB9P8JJLjI7SYKH27fENGYJt61bMKSkt9pViETGG+pC6WfbvB4ia9adOV/HQQzj+9Cfaz5nDsXfeAXO9VwIQEWky6j/O4PNhLinBm5xsdJJGqcrIINCpE/H//d8aoBKROtX7L8933nmHffv2AbB7924eeOABpk6dyu7du5srW8vl92Pduxd/cnKLfsoBUD10KKHYWGLWr4dQyOg4ItJCqQ/5X9Z9+2oeYETh+oQhp5OTOTnYt2/XOiEiEhXUf4D52DFMoVDLf1hss+HJyiLmww8xFxcbnUZEolC9B6jeffddOn//S/HVV1/lpptuYuLEifzhD39ormwtlmX//prdma64wugojRcbi3fECKwHD2LZu9foNCLSQqkP+V4wWLP+1GWXRe0DjMpbbqF66FCcTz+NqazM6Dgi0sap/6hZfwpomTv4ncHzr/+KKRjUQxARqVO9B6g8Hg8Oh4PKykr27dvHj3/8Y8aOHcu3337bnPlaJFthIaGYmKjZnamxfFddRbBDB2I2bIBg0Og4ItICqQ+pYT5yBFNVFf6ePY2Ocm4mEyeeegrziRO0e/ZZo9OISBun/uP79adiY1vFpkWBnj2puu464l95Bfx+o+OISJSp9wCV2+1m165dbNy4kX79+mE2m/F4PJi1PkVtwSCWr7+uWVvEYjE6TdOwWKgeNQpLaSm2ggKj04hIC6Q+pIZ13z5CgP+yy4yOcl7+AQM4dffdOP7rv/R7X0QMpf4DLEeOEOzSJWrfvL1Yp+6+G8vhw8T+7W9GRxGRKFPv3+x33HEHCxcu5M033+S2224D4NNPP+WK1jCNrQlZvvkGc1VV65jedxp/cjL+nj2J2bQJ8+HDRscRkRZGfUgN6759BJOSIC7O6CgXVP4f/0Gwc2c6/OpX4PUaHUdE2qg233/4/ZhLSgi09PWnTlOdkYG/Wzfi29A0TRGpn/Pu4ne6lJQUfv/739c6Nnz4cIYPH97koVoya1ERIYsluqdvNITJRNWYMcT/13/R7sknOb50qdGJRKQFUR8CVFdjPnwY79ChRiepl1C7dhyfPx/33XeTkJtLxcyZRkcSkTaorfcf5mPHMAWDNW9QtRYWC55/+zfaPf001l278F95pdGJRCRK1HuACmrmgH/77bdUVVXVOj5w4MAmDdWSWYuKCHTrBna70VGaXKhjR7xXX43jrbfw/PzneK+91uhIItKCtPU+xPLNN5hCoRa1PmH19dfjueUWnIsXU3XjjfhP2/pdRCRS2nL/EV4gvRW9QQU1i6U7Fywg/qWXOPH000bHEZEoUe8BqnXr1rFixQpiY2Oxnzb4YjKZyM3NbZZwLY2prAxzWRnewYONjtJsvFdfjeXwYdrPmcN3H3wAMTFGRxKRFkB9CFgPHiRksRC45BKjo1yUk088QcyGDXR4+GGqR4+GJlr3xeJw4PR4ah0rf/jhJmlbRFqPtt5/mI8cIRQTQ6h9e6OjNKmgy0XlT39K3Jo1nJw9u1UsAC8ijVfvAapXX32VmTNnMmTIkObM06JZi4oA8PfqZXCSZmSzceKpp3DfcQfORYsof+QRoxOJSAugPgQsBw/WDE7ZbEZHuShBl4sTTz2F64EHCMXE4B050uhIItKGtPX+w3L0KIFWtED66U7dfTeOP/0Jx5/+xKnJk42OIyJRoN4DVMFgkB/96EcNPlFBQQErV64kGAySkZHBhAkTav27z+cjNzeXoqIinE4n2dnZdO7cmfLychYuXEhhYSGjR49mypQp4TpFRUUsXboUr9fLkCFDuOeeezCZTFRUVLBo0SK+++47OnXqxIwZM0hISGhw9vqyFhURcLtb3ROOM1WPGYMnK4uEpUupuv56fKmpRkcSkSjX2D6kxausxHz0KN4RI4xO0iBVP/0pnr//nbjXXiPQo0eLmqYoIi1bm+4/AgHMx47ha6WDc77Bg/GmpBC/YgWn7rqr9eyALiINVu/39G+++WZef/11gsHgRZ8kGAyyYsUKHn30URYtWsTGjRs5dOhQrTJr164lPj6eJUuWMH78eFatWgWAzWYjKyuLO++886x2ly9fzv3338/ixYs5fPgwBd9vhf3WW28xaNAgFi9ezKBBg3jrrbcuOvNFq6rC8s03rfvtqdOc+D//h8All9AxOxtTZaXRcUQkyjWmD2kNrIcOYQICPXoYHaXBTjz1FKEOHYj9619Bv/dFJELacv9hLinBFAjUvEHVSlXcfz/WffuIff99o6OISBSo9xtU7777LsePH+cvf/nLWW8jPf/88+etW1hYSFJSEl2+/+Wanp5Ofn4+3bp1C5fZunUrt99+O1CzM8eLL75IKBQiNjaWvn37cvjw4VptlpWVUVlZSZ8+fQAYNWoU+fn5DBkyhPz8fObOnQvAddddx9y5c7njjjvqe6kNYt2/H1MwiD85uVnPEy1CTifHFy4kMSsL529+w8knnjA6kohEscb0Ia2B5eBBQlYrgaQko6M0WCg+nsrx43G8+iqx779P1U9/2iqnnIhIdGnL/YflyBGg9S2QfrqqcePwd+9O/AsvUPXjHxsdR0QMVu8BqmnTpjX4JKWlpbjd7vBnt9vNnj17zlnGYrHgcDgoLy+nXbt29W6ztLQUgBMnTtCxY0cAOnTowIkTJ+psIy8vj7y8PADmz59PYmJig67P4nBg2r+fkMNBbK9eTbaA7OnMZjMOh6PJ222ImB++pwkTCDz4IAnLlhFz002EbrzxnHWsVmuDv99ooPzGUv6WrzF9SGtgOXiQwKWXtvjpC8EuXai+9lpi168nmJ+Pd+hQoyOJSCvXlvsP89GjhOx2Qh06GB2l+VitnJoyhfZz52L77DO4/nqjE4mIgeo9QNW/f//mzNFsTCYTpnM84c3MzCQzMzP8+dixYw06h7OigoTCQvy9ep21/W1TcTgceM7Y7cgo5ad/TzNnkrhhA9a77uK7d98lcI4pjomJiQ3+fqOB8htL+Y3VtWvXRrfRUvuQpmA+dgxLSQnV/foZHaVJ+FJSsBw+jP3jjwkkJp7z976ISFNoy/2H5ciRmrenWvnbqp5//VecCxaQ8MILGqASaePq/aqPz+fj1Vdf5aGHHuKuu+4CYPv27bz33nsXrOtyuSgpKQl/LikpweVynbNMIBDA4/HgPM92o+drs3379pSVlQE1UwHP9RZWU7EUF2Oqqmoz60/VEhdH2f/7f4QsFlxTpmCqqDA6kYhEocb0IS2dfdMmAPytZWFxk4mqG24g2Lkzcf/zP5hP64tFRJpam+0/AgHM331HsBWvP/WDUEICnl/8gth334X9+42OIyIGqvcbVC+99BKlpaVMnz6dp59+GoDu3bvz0ksvMW7cuPPWTU5Opri4mKNHj+Jyudi0aRPTp0+vVSY1NZV169bRp08fNm/ezIABA8755hNAx44diYuLY/fu3fTu3ZsNGzaEc6SlpbF+/XomTJjA+vXrufrqq+t7mQ1i+fprQmYz/ssua9bzRKtA9+6UPf887kmT6DBjBmUvvNAsT3qcCxY0eZunM508ieXwYcxlZZjLyjCdOIGpqgqT14spECDJYql5zTo2lmDHjgTdboKJiQS6dm3ybePLH364SdsTMVpj+pCWLmbjRkJ2e+u6ybDZqLz5ZhyrVhH35z/j+dd/JRQXZ3QqEWmF2mr/YS4trVkgvQWsP9XYv9HLH36YismTiV++HMuSJfDII02UTERamnoPUP3jH/9g8eLFxMbGhgeOXC5XeN2n87FYLEyePJl58+YRDAYZM2YM3bt3Z/Xq1SQnJ5OWlsbYsWPJzc1l2rRpJCQkkJ2dHa4/depUPB4Pfr+f/Px8cnJy6NatG/feey/Lli3D6/UyePBghny/BeuECRNYtGgRa9eupVOnTsyYMeNiv5eLYt27l0C3bhAT06zniWbea6/lZE4O7Z94gsC8eZzMyTE60gWZPB4se/di3bcPyzffYD7t7a9gQgLBDh0IduwIdjuW2FgCVVXg9WKqrMRaVIR5xw4AQhYLgR498Pfqhe/KKyE21qhLEolajelDWrqYTZtq1p9qhvUJjRRyOqn6yU+IW7OGuDffxHPbbWC3Gx1LRFqZxvQfBQUFrFy5kmAwSEZGBhMmTKj17zt37uSll15i//79ZGdnM3z48PC/ZWVl0eP7nVcTExOZNWtWE17VhZmPHgVo1Tv4nS546aVU3nILcStWYL7vPoJnzLYRkbah3gNUVqv1rO1dT548ed5peKdLSUkhJSWl1rGsrKzwz3a7nZkzZ9ZZd+nSpXUeT05OZkEdI/ZOp5PHHnusXrkay7J/P5aSEqoGDYrI+aLZqfvuw3rgAAnPP0+wQwcqHnrI6Ehnq6zE9tVX2L76CnNxMSYgGB9PoFs3vF27ErjkEoJu91lvRDkcDqrOWAPM5PFgPnIE6759WPfuJfbDD4lZvx5f3774hgwh2KlTBC9MJLo1pg+50A2Gz+cjNzeXoqIinE4n2dnZdO7cmfLychYuXEhhYSGjR49mypQp4TpFRUUsXboUr9fLkCFDuOeee8771m6DhUKUP/QQMR991PRtR4HApZdSNX48sW+/Tdzbb1M5YUKLXwheRKJLQ/uPYDDIihUryMnJwe12M3v2bNLS0mrtIp6YmMiDDz7I22+/fVZ9u93OM8880zQX0QCWI0cI2WyEvt/4qS2omDoVx5o1xK9YQfl//IfRcUTEAPV+nDt8+HByc3M5+v1ofllZGStWrCA9Pb3ZwrUEsd/vAtgm1586k8nEiSefxHPLLbT7zW9I+N3vjE5UIxjEUlRE7Ntvk/DCC8T+/e/g9+NNT+fUHXdw6r77qBo/vmZQKSmp3tP1Qg4Hgcsvp3rMGE5NnsypO+7A17cvtq++Iv7ll4l9+21Mx48388WJtAwN7UN+uMF49NFHWbRoERs3buTQoUO1yqxdu5b4+HiWLFnC+PHjWbVqFQA2m42srCzuvPPOs9pdvnw5999/P4sXL+bw4cMUFBQ00ZWewWSiMiuLwOWXN0/7UcB/xRVUXX891v37iX3vPTjjRlJEpDEa2n8UFhaSlJREly5dsFqtpKenk5+fX6tM586dueyyy5rnAUUjtZUF0k/n79OH4M03E79yJabycqPjiIgB6v0G1aRJk1i1ahUPP/wwXq+X6dOnk5GRwe23396c+aJeTF4eAZerdW//ejHMZo7/7ndgNtPumWcwl5Zy8vHHDYliKi3F9uWX2HbuxHzqFMG4OHxXXYVv4MBmebsp2Lkz1TfcQPWoUdg/+wz71q1Yv/4a3+DBVI8Y0aangIo0tA85/QYDCN9gnP4EfOvWreF2hg8fzosvvkgoFCI2Npa+ffty+PDhWm2WlZVRWVlJnz59ABg1ahT5+fnhaeJy8fwDB1Lt8RDz8cdgsVB1ww2tbkqjiBijof1HaWkpbrc7/NntdrNnz556n9fn8/HII49gsVi4+eabGTp0aJ3l8vLyyPv+gfX8+fNJTEys9zlOZ3E4/vdDMIj5u+8IpaTgOP34BZjN5osqHy1iTv/OZs/G/Oc/0+mNNwi20DVZrVZrg/8/iBYt/Rpaen5ou9dQ7wGqw4cP07VrV2655RaCwSBDhw4Nz8tuyzx33EHcW28ZHSO6WK0cX7SIoMtFwvLlWPfuhZdfjsy5q6ux7dqF7csvsRQXEzKZat5yGjCg5i23SEw9iY3FO2IEvkGDsH/yCbbPPsNaWEjVv/wLgdayi5fIRWpoH1KfG4zTy1gsFhwOB+Xl5efcwbWuNs+1lklDbzzO7JAtEbhhiDlPtqb6I+e81zF6NEGzGduGDVgsFkI/+cl5B6nqupE63zU0t2j8QzDaMkVbHoi+TNGWB6Iz08Uw6h5k2bJluFwujhw5whNPPEGPHj1ISko6q1xmZiaZmZnhz8eOHWvQ+ZynLSVhPnaMeL+fKpcL/xlLTJyPw+HAcxHlo8bs2eEfLQ4H/h49MD/1FJWHD4P1/Ler0bixUGJiYoP/P4gWLf0aWnp+aH3X0LVr13rVueAAVSgU4vnnn2f9+vW43W46duxIaWkpa9asYdSoUTzwwANR+VpspFSNH4/tq6+MjhF9LBZOzp2LPzmZ9o89BsOGETN/PtVjxjT9uYJBLIcOYfvyS6x79mDy+wm43VSNGoW/Xz9C8fFNf856CCUkUH399fgGDCDur38l7k9/wpeaSvU112iNFmkzWnof0tAbjzP/qHBG4obhtD/wz2RxOKiORIa0NOyBADEbN+Lz+agaN+6cg1R13UiVG/iHWDT+IRhtmaItD0RfpmjLA5HJVN8bj4vR2P7D5XJRUlIS/lxSUoLrIhbe/qFsly5d6N+/P/v27atzgKo5/LBAeqva/fUieIcOxbFmDbYdO/ANHmx0HBGJoAsOUOXl5bFz507mzZvHFVdcET5eWFjIc889xwcffMANN9zQrCGl5fLceSe+wYNJ/OUvcd9xB5U33cTJWbMINHbNrlAI8+HD2HbtwrprF+ZTpwjFxODr3x/fgAE1a0lFyU1vsGtXTt15JzEffYR92zbMxcVU/eQnhg2ciURSY/uQ+txg/FDG7XYTCATweDznXTy3sTctcn7eYcPAZCLm448xeb1Ujh9f77X9Q8xJvgAAIABJREFURER+0Nj+Izk5meLiYo4ePYrL5WLTpk1Mnz69XueuqKggJiYGm83GyZMn2bVrFzfffHOjr6m+LEeOELJaa3aTboMC3bsT6NoV+z/+gW/gwAu+RSUirccFF4jYsGED99xzT62OAeCKK67g7rvv5qNWujORNB3foEH48vM5+fDDxHz4IZ1Hj6bjffcRs2ED+P31b8jrxVJURMz69cSvWEH8q69i276dQFISlePHU3HffVRnZhK85JKoGZwKs9upzsig8sYbsRw9iuO//xvzkSNGpxJpdo3tQ06/wfD7/WzatIm0tLRaZVJTU1m3bh0AmzdvZsCAAed9qt6xY0fi4uLYvXs3oVCIDRs2nNWmNI536FCqMjKwFBXhWLMGKiuNjiQiLUxj+w+LxcLkyZOZN28eM2bMYMSIEXTv3p3Vq1ezdetW4P9n787joiz3/4+/7tmYGRiWGTZRtERNrcwQC8ldslOWa2qWHrP1ZMdy6xzt+M1O5smTqZVkatmimUvl0m4hqaU/T2jZelrM6mSZyCICA7Pevz9QAhUXhLln4PN8PHgwy33P/b5v4LqYz9z3dVUWu/7yl7+wc+dOli5dWjWj+K+//sq0adO47777+Oc//8ngwYNrjH3Y0HR5efjj45vuWH6KgisjA11pKcbPP9c6jRAigE5bjt6/fz8dO3Y86XMdO3YkKyur3kOJRigsjNLJk3GOHk3E0qVYV63C8tZb+KOjcaWn4+nUCe955+G320GnQ3E6UZxO9L/9VnmW1HffYfziCxS/H1Wvx9eiBa5u3fC2aRNSg49727fHGRODZeNGrGvWUH7tted+NpkQQexc+5DqbzD8fj99+vSpeoORkpJCWloaffv2JSsriwkTJhAREcHEiROr1r/77rtxOp14vV5yc3OZMWMGLVq04LbbbmPRokW43W46d+4sA6Q3AM8ll6BaLJjfeaeyvRsyBDUqSutYQogQUR/vQVJTU0lNTa3x2MiRI6tut2nThsWLF5+w3gUXXMC8efPOMnE9UVX0eXl4LrxQm+0HCV9yMt4WLTDl5uK5+GI5E1eIJuK0BSq/34/FYjnpcxaLBb9MJy3Ogj8+niMzZnBkyhTMW7Zg3rQJU24ulnffrXUdX0IC3nbtcHfpgq9lS3xJSSHdSfkTEnDedBOW9euxvP46FVdfjfeCC7SOJUSDqI8+5HRvMEwmU9Wn3sd76qmnTvp4SkqKdm8+mhBvu3aUWyxYXn8d68svU3HddfgCeBaCECJ0NdX3ILqiIhSPB18THX+qiqLgzsjAunYtxs8+wyNnOgvRJJy2QOXz+fjyyy9rfb6xdg6igVksVFx9NRVXXw1QebbU//6HrqgIVBXVakW1WvHFx6NGRwNga0RvJtXwcJzDh2PZsAHzW2/hcrsrPx0SopGRPkT4kpMpu/FGrBs2YHn1VSoyM/FedJHWsYQQQa6p9h/HhoDwx8drnER7vhYt8LZsWXkWVadOYDJpHUkI0cBOW6CKiori6aefrvX52qbxFuJsqFYr3vbttY4RWGFhlA8diuWNNzC//z6oamXnK0QjIn2IAFBjYigbNQrLW29hee893AUFcNVVWscSQgSxptp/6PPyUPV6/A6H1lGCgisjg/DVqzHt2YP7ssu0jiOEaGCnLVDVdnmEEKIeGI2UDxqEZeNGwrKzUU2mpleoE42a9CGiitlM+ZAhhG3dimn3btTCQpSrrkK1WrVOJoQIQk21/9AdPIg/Lq7pDpB+HH9SEt7zzsO0axfuSy4JqbFnhRBnT1o+IbSm11N+3XX4mjfH/O676H/4QetEQgjRMHQ6XH36UHHllfC//2F96SV0v/2mdSohhAgORwdIb/LjTx3HlZGBUlGB6dNPtY4ihGhgUqASIhgYjZQPHow/Lg7Lm29i+vhjrRMJIUSD8Vx8Mf5x40CvrxwAd/duUFWtYwkhhKaUw4dR3G4pUB3Hn5iIJyUF0+7dUF6udRwhRAOSApUQwSIsDOfQoaiRkdjHjUO/b5/WiYQQouEkJlJ20014zz8f89atmN94A6WoSOtUQgihGf3vvwOVMz6LmtwZGeByESYf4grRqEmBSohgYrHgHDIEVafDMWYMSmGh1omEEKLhmM1UDBxIRc+eGPbtIz4zE9OHH2qdSgghNKE/eFAGSK+FPy4O74UXYtyzB6W4WOs4QogGIgUqIYKMGh1N4XPPoT9wAPutt4LLpXUkIYRoOIqCJy0N56hR+MPDib3hBiIfekjaPiFEk6M7eBB/fLwMkF4LV0YGAGHbt2ucRAjRUKT1EyIIebp2pWjBAsI+/pioBx7QOo4QQjQ4f0IC+Zs2UfbnPxOxZAlxAwZg+PprrWMJIURg+P0yQPppqDYb7i5dMH7zDbqDB7WOI4RoAIZAbWjPnj08//zz+P1++vXrx+DBg2s87/F4yMrKYt++fdhsNiZOnEh8fDwA69evJycnB51Ox7hx4+jcuTO//fYbCxYsqFo/Ly+PESNGMGDAANauXcvmzZuJjIwEYNSoUaSmpgZqV4WoFxWDBlHy9dfYsrLwdO6Mc9QorSMJIUSDUi0Wih95hIp+/YieMoW4q6+m9O67KbnnHjCbtY4nhBANRldUhOLx4EtM1DpKUHN37Yrx888J27aN8uuv1zqOEKKeBaRA5ff7WbZsGTNmzMDhcDB9+nTS0tJo0aJF1TI5OTmEh4ezcOFCtm/fzsqVK5k0aRL79+9nx44dzJ8/n6KiImbNmsUTTzxBUlISc+fOrXr9O++8k8suu6zq9QYMGMDAgQMDsXtCNJiSv/0N4+efE3X//Xg6dMDTubPWkYQQosG5MjM59MEHRD74ILYnnsD81lsUz52Lu1o/L4QQjcmxM4JkgPTTCAvD3a0b5g8+wPDDD1qnEULUs4Bc4rd3714SExNJSEjAYDCQkZFBbm5ujWV27dpF7969AUhPT+fLL79EVVVyc3PJyMjAaDQSHx9PYmIie/furbHuF198QWJiInFxcYHYHSECR6+n6Kmn8MXHY7/tNnT5+VonEkKIgPDb7Rx+8kkKVq5EqaggdsgQoqZNk8kjhBCNkv7gQVSjEX9MjNZRgp6nUyd8DgdhW7dCRYXWcYQQ9SggBarCwkIc1WajcDgcFB73D2b1ZfR6PVarlZKSkhPWtdvtJ6y7fft2rrjiihqPbdq0ialTp7Jo0SJKS0vre5eECBjVbqfo2WfRFRURc9dd4PVqHUkIIQLG1bs3h3JyKL3tNqwrV5LQowfhzz4LHo/W0YQQot7oDx7EJwOknxm9Hlfv3uiKi4lYulTrNEKIehSwMagaitfrZffu3dx4441Vj/Xv35/rj16TvGbNGpYvX8748eNPWDc7O5vs7GwA5syZQ2xsbJ0y6K3WOq13NnQ6HdYAbOdMhNXhOBkMhjof32MCcZxrE+jjf8Ix7tMHX1YWYbfdRsITT+B75JGzer36OP5akvxCNG1qeDhH/vlPnEdn+IuaOZPwF1+k+IEHcGVmgqJoHVEIIerO60WXl4enUyetk4QMX6tWeFJSiFi4EOfw4fibNdM6khCiHgSkQGW32ykoKKi6X1BQgN1uP+kyDocDn8+H0+nEZrOdsG5hYWGNdT/99FPOP/98oqOjqx6rfrtfv378+9//PmmuzMxMMjMzq+7n1/HyKZvTWaf1zobVasUZgO2ciZI6HKfY2Ng6H99jAnGcaxPo43/SY3z11USNGUP4/PkcvvRSXH37nvHr1cfx15Lk11ZSUpLWEYQAwNuhA4Uvv0zY5s1EPvQQjptvxpWeTsnkybgzMqRQJYQISYbvv0fxemUGv7Pk6tWL8JUriZw9m8NZWVrHEULUg4CcQ5qSksKBAwfIy8vD6/WyY8cO0tLSaizTpUsXtmzZAsDOnTu58MILURSFtLQ0duzYgcfjIS8vjwMHDtCmTZuq9U52eV9RUVHV7Y8//pjk5OSG2zkhAqj4wQfxdOhA9L33ovv9d63jCCFE4ClK5SDqmzdz+OGHMfz4I7EjRuAYNoywDz4Av1/rhEIIcVaMn38OIAWqs6RGR1P6l79gXb8e0/btWscRQtSDgJxBpdfrueWWW5g9ezZ+v58+ffqQnJzMmjVrSElJIS0tjb59+5KVlcWECROIiIhg4sSJACQnJ9OtWzcmT56MTqfj1ltvRXf02uyKigo+//xz7rjjjhrbe+mll/jpp59QFIW4uLgTnhciZJnNFD39NLFXX03MPfdQsGoV6PVapxJCiMAzGnGOG4dz1Cisq1Zhy8rCMXo0npQUym69lfLrr0cND9c6pRBCnJbps89QTSZUGSD9rJVMmIBlwwai//538rKzwWzWOpIQ4hwEbAyq1NRUUlNTazw2cuTIqtsmk4nJkyefdN2hQ4cydOjQEx43m80899xzJzw+YcKEc0wrRPDytm1L8cMPEzNlChFZWZTee6/WkYQQol7Y5s2r87rOkSMxfPcdpk8+Ifr++4maORNv27Z4OnbEl5xcdflfyZQp9RVXCCHqhfHzzysHSJfLlM+exULxnDk4Ro3CtnAhJffdp3UiIcQ5CPlB0oVoispHjiTsww+xzZuHu1s33JddpnUkIYTQll6Pt0MHvO3boztwAONXX2H89luMX3+N32rF27o13pQUFKcTNUgmHRFCCNxujF9/jeeii7ROErJcPXviHDqUiKeeonzwYLxt22odSQhRRzKPqRChSFEonjMHX4sWRN99N0q1cdeEEKJJUxT8SUm4rryS0jvvpHzAAHzJyRi/+w7rxo0kduhA7HXXYfvXvzC/8w76n3+WcauEEJoqeuopPB07ah0jpB2ZORM1PJyov/9d2nQhQpicQSVEiFJttsrxqAYNInrqVIqefVZODRdCiOqMRrwXXID3ggvA50O/fz++Zs0I27mTiKVLUTweAPwREdCpE1Ft2uBNSak826p1a3wtWoBB/lUSQjQgk4mKq6/G+PXXWicJaf7YWIofeICYyZMJX7aMsttv1zqSEKIO5L8uIUKY55JLODJ9OlEPPYTrhRdwjhundSQhhAhOej2+Vq0omTKFEkApL8fwzTcYv/4a49dfY/n+eywbNqA7cqRqFdVoxNuqVWWx6mjR6tiX/xTjxZzLWFo1Ilut2JzOkz4nY2kJIURN5SNGYHn7bSLnzMHVu7dc6idECJIClThrdfnH+1T/ZIsTndUxVlW8559P1MyZGL/9Fn9c3AmLnOnxlzc8QoimQrVY8Fx6KZ5LLwXAGBtL/qFD6AoLMezbh37fPgzVvsxbt6K4XFXr+8PD8bZpgzstDffll+O+/HL8sbFa7Y4QQghF4fDcucT17Uv0vfeSv3EjGI1apxJCnAUpUAkR6hSFiquuwrpiBea33sJ5003SGQshRF0oCn6HA7fDAV271nzO70d/4AD6H36oKloZ//tfrCtXErFsGaqi4E5Lo+Lqq1GKi1GjorTZByFElT179vD888/j9/vp168fgwcPrvH8119/zYsvvsjPP//MxIkTSU9Pr3puy5YtrFu3DqicUbx3796BjC7qyB8fT/GcOdjvvJOIhQsprWWWeCFEcJIClRCNgGq1UvGnP2F57TXCtmzBdeWVWkcSQojGRafD17w5vubNcffs+cfjbjfGL74gbNs2LO+8Q9RDDwHgPe883J074zvvPNDJnDRCBJrf72fZsmXMmDEDh8PB9OnTSUtLo0WLFlXLxMbGMn78eN54440a65aWlvLqq68yZ84cAKZNm0ZaWhoREREB3QdRNxXXXotz6FBsjz+OOyMDd7XCoxAiuEmBSohGwteqFe6uXQnLzcXXqhXedu20jhT06mucmNM5/hJLuZRSCO3U9ndfH5eiV1x1Fa7LL8f43/9i/PxzrBs24I+KwtWtG9727aVQJUQA7d27l8TERBISEgDIyMggNze3RoEqPj4eAOW48eT27NlDp06dqgpSnTp1Ys+ePXTv3j1A6cW5Kv7XvzB9+ikxd93FoU2bKscNFEIEPSlQCdGIuDMyMPzyC+b336csMRE1MlLrSEII0aSo0dG4u3XDfdllGH74AdPHH2N59118ubm4unfH17q1zLgqRAAUFhbicDiq7jscDr7//vs6rWu32yksLDzpstnZ2WRnZwMwZ84cYus4Fp3eaq3TetXpdDqs9fA6WjrbfQir7XjHxqK++ir67t2JnzgR79tvB2xWVoPBUOffg2AR6vsQ6vmh6e6DFKiEaEz0esqvuYbwl17C/PbblI8YIZ/YCyGEFvR6vO3a4W3bFsP33xO2fTvWjRvxpKTg6tsX1WbTOqEQoh5kZmaSmZlZdT8/P79Or1MfkwlZrVacIT4p0dnuQ8mpjndiIpZHHiFm4kRcf/87JdOn10PC04uNja3z70GwCPV9CPX80Pj2ISkp6YzWkXeuQjQyanQ0FZmZGH77DdPOnVrHEUKIpk1R8LZrR9nYsVT07Inh558Jf/FFjHv2gKpqnU6IRstut1NQUFB1v6CgALvdXqd1CwsLz3hdEVzKhw+n7KabsGVlYXnlFa3jCCFOQwpUQjRC3vbt8Vx4Iab//Af9L79oHUcIIYROhyctjbI//xlfs2aYc3KwbNiAUl6udTIhGqWUlBQOHDhAXl4eXq+XHTt2kJaWdkbrdu7cmc8++4zS0lJKS0v57LPP6Ny5cwMnFg2l+OGHcXXvTvTUqZi2bdM6jhDiFOQSPyEaqYo+fQj/9VfM77yDmpysdRwhhBBUnuVaPnQoxj17CNu2DeuKFVRccw2+agM3CyHOnV6v55ZbbmH27Nn4/X769OlDcnIya9asISUlhbS0NPbu3ctjjz1GWVkZu3fvZu3atcyfP5+IiAiGDRvG9KOXhF1//fUyg18oM5kofOYZYocMwX777eSvX4+3Y0etUwkhTkIKVEI0ViYT5QMGYF21CuXNN2HAABmYVwghgoGi4Ln0UnxJSVjeegvLK6/g6tULz6WXSjstRD1KTU0lNTW1xmMjR46sut2mTRsWL1580nX79u1L3759GzSfCBw1MpKC5cuJGzgQx5gx5K9diy8lRetYQojjSIFKiEbMn5CAq0cPzFu3YkxKwnPcP2lCCCG0409IoGz0aMzvvIN5yxZ0+fm4+vUDvV7raEIIERJs8+ad1fIV/ftjeeUV4q6+mvLrr6f4X/+q9+3rrdYzGvS+ZMqUc9q2EI2RjEElRCPnSU1FveACwrZtQ79/v9ZxhBBCVGcyUTFwIK7LL8f05ZdYXn0VZFwqIYRoEP7Y2MpZrgHL2rUYvvpK40RCiOqkQCVEY6co+K+7DjUyEvNbb6GUlmqdSAghRHWKgvuKKyi/5hr0v/+Odc0alCNHtE4lhBCNkt/hwDliBOj1xA4fTtiWLVpHEkIcJQUqIZoCs5nygQNRXC7Mb70FPp/WiYQQQhzH27495UOHoisrw7pqFeTlaR1JCCEaJTUmBufIkfiSkrCPGUP400+DqmodS4gmL2BjUO3Zs4fnn38ev99Pv379GDx4cI3nPR4PWVlZ7Nu3D5vNxsSJE4mPjwdg/fr15OTkoNPpGDduXNU0r3fffTdmsxmdToder2fOnDkAlJaWsmDBAg4dOkRcXByTJk2SmTdEk+ePjaXiyiuxvPMOYR99hKtXL60jCSGEOI4vORnniBFY1q1D9+KL6AcOxCczsQohRL1To6LIf/11oidNIurhhzF99hmHH3kENSZG62hCNFkBOYPK7/ezbNky7r//fhYsWMD27dvZf9xYODk5OYSHh7Nw4UIGDBjAypUrAdi/fz87duxg/vz5/OMf/2DZsmX4/f6q9WbOnMncuXOrilMAGzZs4OKLL+bJJ5/k4osvZsOGDYHYTSGCnrdDB9ydO2PavRvDt99qHUcIIcRJ+OPicI4aBTYblnXrMHz3ndaRhBCiUVKtVooWL+bI9OmY336b+L59Mb/7rtaxhGiyAlKg2rt3L4mJiSQkJGAwGMjIyCA3N7fGMrt27aJ3794ApKen8+WXX6KqKrm5uWRkZGA0GomPjycxMZG9e/eecnu5ubn0Onp2SK9evU7YlhBNmatXL3zNmmHetAnd779rHSfwPB6Uw4dRiorkUkchRNBSIyPxjx2LPyEB85tvYvzsM60jCSFE46QolP71rxx6+238sbHYb72VmDvvRP+//2mdTIgmJyCX+BUWFuJwOKruOxwOvv/++1qX0ev1WK1WSkpKKCwspG3btlXL2e12CgsLq+7Pnj0bgCuvvJLMzEwAiouLiTl6amZ0dDTFxcUnzZWdnU12djYAc+bMITY2tk77p7da67Te2dDpdFgDsJ2GIvm1dUL+kSPh+eexvv46/nHjICoKgLA6/g00NIPBULe/z5ISlG3b0G3ejPLVVyg//gi//IJS7SxM1WoFux21eXPUVq3g/PPBaKzH9Cce/2A9zkKIIGOx4Bw2DMtbb2HevBnF6cSdng6KonUyIYRodLwXXcSht98mIisLW1YW5k2bKBs9mtJ778UfF6d1PCGahICNQdUQZs2ahd1up7i4mIcffpikpCQ6duxYYxlFUVBq+UcuMzOzqqgFkJ+fX6ccNqezTuudDavVijMA22kokl9bJ+TX6dANGoR19WpYvRrnyJFgMlFSx7+BhhYbG3vmf58VFZg3bcK6ejVhO3ageL34zWa8HTrgTU3FN3gw/pgYUBTMmzahlJSgKyhAv2sXuv/8B9VoxNOhA55LLqm3f0aOP/7Bepxrk5SUpOn2AzmGoRBBx2ik/LrrML//PmH/7/+hOJ24+vTROpUQQjRORiOlkybhvOEGbAsWEL58OdZVqygfNoyy227D266d1gmFaNQCUqCy2+0UFBRU3S8oKMBut590GYfDgc/nw+l0YrPZTli3sLCwat1j36OioujatSt79+6lY8eOREVFUVRURExMDEVFRURGRgZgL4UILf7YWMqvvRbL+vVY3nyT8kGDtI50TnQHDxKxdCnW1avRHT6MNzmZ0jvvxNWzJ+60NDCbT1yn+tmVXi/6X3/F+M03GL/6CtPnn+Nt0QJX9+74NS7QNGXHxjCcMWMGDoeD6dOnk5aWRosWLaqWqT6G4fbt21m5ciWTJk2qMYZhUVERs2bN4oknnkCnq7y6febMmdI/iNCg11Nx1VWoViumXbtQysspueceCAvTOpkQQjRK/mbNKH70UUrvvJOIJUuwvvYa4StX4urRA+eIEVT86U+VZ+ELIepVQMagSklJ4cCBA+Tl5eH1etmxYwdpaWk1lunSpQtbtmwBYOfOnVx44YUoikJaWho7duzA4/GQl5fHgQMHaNOmDRUVFZSXlwNQUVHB559/TsuWLQFIS0tj69atAGzdupWuXbsGYjeFCDm+887DlZmJ4aefML/zTkiOyaT/9Vei/vEPErp1I/yZZ3B1707BqlXk7dhByf334+7e/aTFqRMYDPhataLiqqsoveMOXD16oCsqInz1asxvv41SUtLwOyNOEOgxDIUIWoqCq2dPKnr2xPjddzjGjkUpLdU6lRBCNGq+lBSKH32Ug7m5HPnb39D/9BMxEyaQ0Lkz0ffeWzlOVbWhI4QQ5yYgZ1Dp9XpuueUWZs+ejd/vp0+fPiQnJ7NmzRpSUlJIS0ujb9++ZGVlMWHCBCIiIpg4cSIAycnJdOvWjcmTJ6PT6bj11lvR6XQUFxfz2GOPAeDz+ejevXvVpRuDBw9mwYIF5OTkEBcXx6RJkwKxm0KEJM/FF4PLhXnbNqKmTaP40UdDYnwTpayMiKwsIpYsAb8f54gRlI4fj++88879xS0W3F274r7kEky5uZh27cKwdy+uXr3wdOoUEsensQj0GIbHq+tYhcePmxaIsQpPJRjH0Qu2TMGWB2rJ1LMn/qgoTG+/TcKNN+LduBECNDZKnccDbEDBlinY8kBwZhIi1PjtdkrvvZfSCRMwffwxlldfxfLmm+hKSvCHh+Nt3x5P+/b4jw4xIISom4CNQZWamkpqamqNx0aOHFl122QyMXny5JOuO3ToUIYOHVrjsYSEBObOnXvS5W02Gw888MA5Jhai6fCkpaG4XIS//DKqxcKRf/4zeIswfj+W114j8pFH0B88iHPoUEqmTcPXvHn9b8tkwn3FFXguughzdjbmzZsx/PgjFf37y2ndIe5MxjCEuo9VePy4aYEYq/BUgnEcvWDLFGx54BSZ2rbFvWwZMX/5C7oePShYtQpfcnKD5zmr8QADJNgyBVseCEwmrccqFCJgdDrc6em409MpnjWLmHvvxfjf/2L89FNMu3fjs9tRLr4YJSUFNTpa67RChJyAXOInhAh+7owMSm+/nYhly4ieMgW8Xq0jncC4axexAwcSM3EivqQkDr3+OocXLmyY4lQ1alQU5UOHUtG7N/qff8a6fDn6/fsbdJui0tmMYQic0xiGQoQS15VXUrh6NbrCQmIHDcLw9ddaRxJCiKbFYsF7wQWUDx5M6Z13UpGZiWqxoNu6lYjnnsO6ahXGzz4Dt1vrpEKEDClQCSEqKQpHZs6kZPJkrGvWEHPXXeByaZ2q0v79RP/1r8QNGoT+t98oevxx8l9/HU+XLoHLoCh4UlNx3nQThIVhefVVjF98EbjtN1GBHsNQiFDi7tqV/HXrQFGIHTwY86ZNWkcSQoimyWLB06kT5SNH4pswAVf37uDxYN68mYilSwnLyUFXbZgBIcTJBewSPyFECFAUSqZMwR8VRdTMmehuvJGixYvxB2h8kxPilJcTvngxxqeewuj3U3LPPZT+9a+o4eGa5IHK2Q/LRo3C8tZbmN9/H92hQ7h69wad1PsbQqDHMBQi1Hjbt+fQm29iv/VWYm69lZK//Y3SCROC9zJtIYRo7KKicF92Ge7LLkN34ACmPXswfvEFpj178LZqhbtLF3ytWmmdUoigJAUqIcQJym67Db/DQdTUqcT96U8ULl0a2LOVfD4sr75K5Ny56A8cwDdsGPn33ReQMVbOiNlM+ZAhhH2y3uC9AAAgAElEQVT4Iabdu1FKSqi45howGrVO1igFcgxDIUKRv1kz8l97jej77iPy3//G8O23HH7sMbBYtI4mhBBNmr9ZMyqaNUPp1QvjF19g/OwzrOvW4WvWDHdqKq4+feQDBSGqkY/8hRAnVT5kCPkbN6KaTMQOG0b40qXg8zXsRlWVsJwc4q66ipjJk/ElJJD/2mv4Xn45eIpTx+h0uHr1oqJPHww//IBl3TqoqNA6lRCiqbJYOLxwIUemT8eycSOxQ4dWTn8uhBBCc6rVivvyyym75RYqMjNRSktxjBlD7IABhGVng6pqHVGIoCAFKiFErbwXXcSht9/G1asXUf/8J7EDB2L48sv635CqYtq5E8fIkTjGjEEpL6fw6afJf/NN3Onp9b+9euS59FIqrrkG/YEDWNeuRSkr0zqSEKKpUhRK//pXCp97DsNPPxF31VWY335b61RCCCGOMRjwdOpE2S23cPixx9AVFeEYOxbH8OEytqkQyCV+QojTUGNiKHzhBcyvv07UAw8Qd801lP35z5ROmIA/IeHcXtzrxfzee0T93/+h//13/BYLFX364OnUCeP332OcPx8AvdWKLcimf6/O27495WYzltdfx/LKK5QPH67pOFlCiKbN1b8/hzZtIuauu7DffjtlN9/MkRkzUOWSPyGECA56Pc5Ro3Befz3WlSuxzZtH3J/+hHPYMI78/e/4G3iGaiGClRSohBCnpyhUDBqEq1cvIufMIXz5csJffpnyQYNw3ngj7i5dznyQcFXF+MUXWF57DcvGjegPHcIfFUVFv354OnYM2XGcfOedR/mQIVg2bMCydm1lkSoiQutYQogmyteyJfnr1xP5yCOVM0ht2cLhBQtwX3aZ1tGEECJo2ObN0zaA0Yjz5pspHzqUiKwsIp59Fstbb1Fy992Ujh8PZrO2+YQIMClQCSHOmBodTfGcOZTedRcRixdjefVVrGvX4ktMxNWjB+4uXfC2bYsvPr6yOOPzoT90CN3vv2P46SdMubmY/vMf9AUFqEYjFZmZlF9/feUpzY1gFjxfcnJlkWr9eqxr1+IcPhzVZtM6lhCiqTKZODJzJhWZmURPnYpj6FDKbr2VkmnT5GwqIYQIImpkJCX3349zzBgiZ88mct48rK+9RvGsWbj69tU6nhABIwUqIcRZ87VqRfEjj3Dk/vsxv/ce5nffJSw7G+srr5xyPW9yMq4+fXB160bFVVehxsQAYPzqq0DEDghfixaUDx36R5FqxAiwWrWOJYRowtxXXMGh7Gwi//UvIp59FnN2NocffRT3FVdoHU0IIUQ1vuRkihYvpuzGG4maMQPHmDGUX3MNxQ8+KJf9iSZBClRCiDpTbTbKhw2jfNgwUFX0v/6K4Ycf0OXloZSXg6Lgj4/Hl5CALykJf3y81pEDwte8Oc6hQ7GuW4d17VrUsWPBIM2tEEI7ang4xbNnUz5gANFTpxI7YgTlAwdS/H//hz8pSet4QgghqnH37Mmh998nYskSIp54gvgtWyidNInS224Dkwk498sTS6ZMqY+oQtQrecckhKgfioKvRQt8LVponSQo+JOScA4bhvW111Beegnl+utlTCohhObcGRnkbd5MxNNPY3vqKcLef5/SiRMpvf12CAvTOp4Q9WrPnj08//zz+P1++vXrx+DBg2s87/F4yMrKYt++fdhsNiZOnEh8fDx5eXlMmjSJpKPF27Zt23LHHXdosQuiKQsLo/SeeygfMoTIBx4gcvZsLOvWcXjuXDyXXqp1OiEaROgP+iKEEEHK36wZzqFDobQUyyuvoJSVaR1JCCHAYqF08mTyPvigcvKLRx4hvl8/wt57D1RV63RC1Au/38+yZcu4//77WbBgAdu3b2f//v01lsnJySE8PJyFCxcyYMAAVq5cWfVcYmIic+fOZe7cuVKcEpryJSdT9PzzFD73HLqiImKvu47ImTPB7dY6mhD1TgpUQgjRgPxJSfhvuAHdsSKV06l1JCGEACpn+itatoyCl15C1etxjBuH/cYbMXzzjdbRhDhne/fuJTExkYSEBAwGAxkZGeTm5tZYZteuXfTu3RuA9PR0vvzyS1Qp0oogVXHVVeR98AHOMWOIePZZwpcvR//TT1rHEqJeySV+QgjR0Fq2pHzwYCzr12N55RVKx4/H73BonUoIIQBw9enDoe7dCV++HNv8+cRdeSXO0aMpmTpV2ioRsgoLC3FU+/11OBx8//33tS6j1+uxWq2UlJQAkJeXx9/+9jcsFgs33HADHTp0OOl2srOzyc7OBmDOnDnExsbWKa++HiZU0el0WEN8YpamtA9hdfldiY2FZ57BM3YshhEjsK5bh//ii1GvvPKsJ+U51fYNBkOdf5eDQajnh6a7D1KgEkKIAPAlJ1cWqTZswDFyJAVr1+K327WOJYQQlYxGym69FeeQIdgWLCD8xRexbNhAycSJlI0bVzUorxBNQUxMDIsWLcJms7Fv3z7mzp3LvHnzTlp0yMzMJDMzs+p+fn5+nbZpq4czrK1WK84QP1O7Ke1DSR1/VwBo3x7bTTdh+s9/MOXmwt69uHr3xtu+PSjKGb3EqbYfGxtb59/lYBDq+aHx7UPSGU7IIpf4CSFEgPhatqR80CAMP/6I44YbUIqKtI4khBA1qHY7R2bN4tDmzbi7dCHqoYeI79tXxqcSIcdut1NQUFB1v6CgAPtxHwxVX8bn8+F0OrHZbBiNRmw2GwCtW7cmISGBAwcOBC68EGfCYMB9xRU4b7oJNSoKyzvvYFm/HuXIEa2TCVFnATuDqq6zaACsX7+enJwcdDod48aNo3PnzuTn5/PUU09x+PBhFEUhMzOTa665BoC1a9eyefNmIiMjARg1ahSpqamB2lUhhKiVr1UrCpctwz5uHI5RoyhYvRo1OlrrWEKIEHOu04uficKXXiIsJ4fIf/4Tx7hx+FeswHD//XhrudRJiGCSkpLCgQMHyMvLw263s2PHDu65554ay3Tp0oUtW7bQrl07du7cyYUXXoiiKBw5coSIiAh0Oh0HDx7kwIEDJCQkaLQnQpyaPy4O5w03YNyzh7CPPiL8xRdx9eiB55JLzvhsKiGCRUAKVMdm0ZgxYwYOh4Pp06eTlpZGi2rT0VefRWP79u2sXLmSSZMmsX//fnbs2MH8+fMpKipi1qxZPPHEE+j1esaMGUPr1q0pLy9n2rRpdOrUqeo1BwwYwMCBAwOxe0IIcVZcvXtT+Oyz2G+7DcdNN1Hw8suoUVFaxxJCiBO4+vblUI8ehK9YQeT8+cT174/zppsoue8+GZ9KBDW9Xs8tt9zC7Nmz8fv99OnTh+TkZNasWUNKSgppaWn07duXrKwsJkyYQEREBBMnTgTg66+/Zu3atej1enQ6HbfffjsREREa75FobOr1gwadDk9qKt6UFMzvv485JwfDt99S0b8/akxM/W1HiAYWkAJV9Vk0gKpZNKoXqHbt2sXw4cOBylk0nnvuOVRVJTc3l4yMDIxGI/Hx8SQmJrJ3717atWtHzNE/NovFQvPmzSksLKzxmkIIEaxc/fpRuGQJ9jvuqCxSrVqFevRyAiGECAbHv3ny33ILvpwcrC+9hHXNGlzp6XguvRT0+jpvo2TKlHONKUStUlNTT7iKYuTIkVW3TSYTkydPPmG99PR00tPTGzyfEPVNjYqifNgwDF99hXnrVsKXL8edkYG7SxfQyeg+IvgF5Lf0ZLNoFBYW1rpM9Vk0jl/XbrefsG5eXh4//vgjbdq0qXps06ZNTJ06lUWLFlFaWtoQuyWEEOfE1b8/RYsXY/ziCxyjR8uYAUKI4Gax4OrTB+ef/4yveXPM27YR/uKL6H/4QetkQgghjlEUvBddRNnYsXjPO4+wDz/EumoVukOHtE4mxGmF/Cx+FRUVzJs3j5tvvrlqZo3+/ftz/fXXA7BmzRqWL1/O+PHjT1g3mKaFPZ1Qn3JV8murQae7rQen+xtqbMe/xnEePRpveDjG0aNJuPFGvG+8AXFxGqQUQogz43c4KB8yBP2PPxK2dSvWjRvxtGmDq29fVLkMSgghgoIaEUHFwIF4v/uOsJwcrCtX4u7aFffll4Mh5MsAopEKyG/m2cyi4XA4asyicfy6hYWFVet6vV7mzZtHjx49uPzyy6uWia424HC/fv3497//fdJcwTQt7OmE+pSrkl9bAZnu9hyc7m+osR3/E45zjx6EPfcc9jvuQOnVi4JVq/A3bx7glLU702lhhRBNi+/883G2bInpk08w7diB4YUXcPXsiefii2VgXiGECAaKgveCC/C2bIl5yxbC/vMfDHv3UtG/v9bJhDipgBSozmUWjbS0NJ588kmuvfZaioqKOHDgAG3atEFVVRYvXkzz5s259tpra7xWUVFR1fhUH3/8McnJyYHYTSFCXiBmhRIn5+rXj4KXX8Y+diyxgwdTsHo1vpQUrWMJIcSp6fW4u3bF06YN5uxszNnZGP77XyquvBL1uA8jhRBCaMRioeLqq/FccAHm7Gysq1ahRkRQ8re/oYbwVQqi8QlIgepcZtFITk6mW7duTJ48GZ1Ox6233opOp+Obb75h27ZttGzZkvvuuw+AUaNGkZqayksvvcRPP/2EoijExcVxxx13BGI3hRDinLgvv5z8V1/FceONxA4ZQsHLL+O96CKtYwkhxGmpMTGUX3/9HwPzrliBOz0dd1raOQ2iLoQQov74WrembOxYwj78kIhnnsH83nscfvRR3N27ax1NCCCAY1DVdRYNgKFDhzJ06NAaj7Vv3561a9eedPkJEyacY1ohhNCG96KLyF+3DseoUcQOGULR00/jqnYpshBCBK1jA/Oefz5hOTmEbd+O4bvvqLjqKvzx8VqnE0IIARAWhiszkyMPPED01KnEjhxJ2U03cWTGDNTISK3TiSZO5poUQogg42vThvw33sDbujX2ceOwPv+81pGEEOKMqeHhVFx3HeUDB6I4nVhXrsT00Ufg9WodTQghxFHubt04lJ1N6V/+gnXVKuL79CHs/fe1jiWaOClQCSFEEPInJlKwbh2ufv2InjGDqH/8A9xurWMJIcQZ87ZpUznNeceOhH38MdaXXkL3229axxJCCHGUarFw5P/+j/w33sAfHY3j5puJvvtuOHRI62iiiZIClRBCBCk1PJzCZcsovfNOwl94AcfIkegOHtQ6lhBCnDmzmYqrrsI5dCiKx4N19WrCPvgAPB6tkwkhhDjK07kzh955hyNTpmB56y2MnTtjWbsW/H6to4kmRgpUQggRzPR6jjzwAIWLFmH84gvirr4a08cfa51KCCHOiu+88ygbOxbPJZdg+vRTwpcvR/+//2kdSwghxDEmE6WTJ3Po3XdRU1KImTSJ2IEDMe7Zo3Uy0YRIgUoIIUJAxaBB5L/xBqrFgmPYMGzz5sl4LkKI0GIy4erXD+eIEaAoWF99laj77kM5ckTrZEIIIY7ytm+Pd8sWihYsQL9/P7HXXkvU1Kno8vO1jiaaAClQCSFEiPB26MChd9+lfMgQbPPnEztsmJyBIIQIOb4WLSgbMwZ3WhrW1auJ79MH89tvg6pqHU0IIQSATkf5iBHkffghZXfeifWVV4i/4goi5s9HKS3VOp1oxKRAJYQQIUS12Tj85JMUZWVh+PZb4vr1I/zZZ8Hn0zqaEEKcOaMRV8+elQPzxsRgv/12HKNGYfjuO62TCSGEOEq12Tjyf//Hoc2bcfXsSeS8ecR360b4kiVQUaF1PNEIGbQOIIQQ4uyVDxmC+7LLiJo2jaiZM7Fs3MjhRx/F26GD1tGEEOKMeTp35tC772JdsYLIuXOJy8ykbNw4SqZMQY2M1DqeEEI0WrZ582p9Tm+1YnM6azzmbd+esuhowrZvJ+qhh4h45hlK77oL5w03oIaHN3Rc0UTIGVRCCBGifM2bU7h8OUVPPon+xx+J69+fqH/8A6WwUOtoQghx5gwGnOPGkffhhzhHjSJ82TLir7iC8GeekU/ohRAiiPgTEykfNgzn9dfjTU4m6oEHSOjaFdsjj6D7/Xet44lGQM6gEkKIADvVJ1Z15bzhBsJ27MD64otYV63ClZ6Op1MnMBoBKJkypd63KYQQ9cnvcFD873/jHD2ayNmziXrwQSKWLKFk4kScw4dDWJjWEYUQQgC+li05/MQTGHfvJmLJEiIWLSJiyRLKBw7EecMNuNPTQSfnwoizJ781QgjRGFgslbNjjRmDLzER89athD/3HMZPP5XZ/oQQIcVz8cUUrF5N/po1+Jo1I/rvfychPZ2IhQtRDh/WOp4QQoijPF26ULR0KXkffUTZ6NGYN20idvhw4jMysD32GPqff9Y6oggxUqASQohGxB8bW3nq9fDh+KOjMX/wAeHLlhGxaBFKSYnW8YQQ4oy5u3cn//XXyV+1Ck+HDkTOmUNC165ETZmCcdcumfVPCCGChK9VK448/DAH9+yhKCsL7/nnE/H44yRkZBB79dXY5s3D+Nln4PdrHVUEObnETwghGiFfcjLlI0ag/+UXTB9/jO2RRyj/05/w2WxaRxNCiDOnKLh79qSwZ08MX35J+AsvYNm4kfDVq/G0bYtuxAgMvXtXThChKFqnFUKIJk21WCgfMoTyIUPQ/for1g0bCHv/fSIefxzb/Pn4EhJw9eqF+7LLcHftijclRdpuUYMUqIQQorFSFHwtW1LesiXO4cPxtWypdSIhhKgz70UXUfzYYxx58EEsr7+O5bXXMPzrX8TPno23ZUtc3bvjzsjAlZ6Ov1kzreMKIUSjdqZjqrp79MCTlob+xx8x7NuH5fXXsa5dC4AvJgZPly54Lr4YzwUX4G3fHu/554NByhRNlfzkhRCiCZDilBCisVAjInDeeCPOG28k1ufDuWoVYZs3Y3nzTcJffhkAX1wcnosuwtOhA76WLfElJ+NNTsbXvDmYzRrvgRBCNC2qxYK3Y0e8HTuCqlI+eDCm3FxMubkYd+8mLCcH5ejlf6rJhPf88yvb7aPtty85GV9CAv64OHyxsWCxaLxHoqFIgUoIIYQQQmjiXGc11Vut6J1OvBddhLdjR3R5eeh/+w19Xh7GL74gbOvWqjc9x6hhYX98mc2oJlPlp/U6HapeD0e/VL2+chYqgwFVp6t6vMZyR2+XjxyJajKhNG+O3uNBDQ9HjYhAtVrl8hUhhKhOUbBs3AiAr3nzyg8OPB50RUXo8vMrv4qKMO7ZQ9i2bShu9wkv4Y+IwB8biy8uDjU6Gr/NhhoZWfVd16wZZp3uj8eOtsdqeDh+q7Xyg4o6ts3n2m+d68zaDTEb+JkKxKzgUqASQgghhBChT6fDn5iIPzERz7HH/H6UsjJ0R46gFBdXfi8vR6moQHG5oKICXXExis8H1b4Uv7/yu893Rpu2bthQdTuh2uOqolS+KYqIqHxjdKxwddxtNSKi8n5tt48tFx4uU7cLIRofoxF/fDz++Piaj6tqZTt95EhlW15WhuJ04mnfHv2hQ+gOHUL/228YSkoqlzlypOpDCfspNqfqdFUFK9VqRbVa/2h3j96vaqer3VfDw9H/8AMYjahGI5hMqMduG42VH1wE8kMJrxfF5ars0yoqoNrtqn7O6608Jse+oPLDFYPhjw9kwsJQLZbKD23M5srjERFxToW8upIClRBCCCGEaJx0OlSbrXKCiObNz359Vf3jn/pjBavabnu9hOl0uEtKUDwecLtR3O4/bns86EpLobAQxeOpPCvg6HfF4zl9lmORDIaqN0Mn+378YwarFTvUfM5gqPkGy2Si5O9/P/vjI4QQDUlRwGLBf/SSvmMfGdR6Jo+qojidOAwGDv/8c+UHEyUlKEcLW4rTWVnkqnZfKStDd+x7URHK/v1/LOd0nvQMrtqoOl3NtthkqmxvqxWylMOHaxS8VKu1clmvt7I/8HrB7UYXFoYtPx/lyBF0xz5gOXIEw969fxSlvN5T5wkL++Ns4GPf4Y8PY472XbW9jmowVH5QYrOh2myoikLp5MlnfDzqImAFqj179vD888/j9/vp168fgwcPrvG8x+MhKyuLffv2YbPZmDhxIvFHK6jr168nJycHnU7HuHHj6Ny58ylfMy8vj8cff5ySkhJat27NhAkTMMhAa0IIEZIC2X8IIUQNivLHpX1GI2q1p9STLW+14nU6z347qlpVxKoqbB1fwKpe8PJ4TvxeUYHu2G2vt/L70U/Lz2TUrYilS/n9yy9RG9HYLg3RfwghtHe6y9z0ViuWU7XFBgNqZCRqZCTwR+HrpHy+qra2qr091j5Xu1+jTT56v+qxo4UuxePBsH9/ZYHsNMUlABvgj4zEHxVVebliZCT+6Gg4dqbTsUvVq38dfYywsDM/49bnqyx4HTvD2OlEKS2tLO6VlKArLUX3yy9YX3utcRSo/H4/y5YtY8aMGTgcDqZPn05aWhotWrSoWiYnJ4fw8HAWLlzI9u3bWblyJZMmTWL//v3s2LGD+fPnU1RUxKxZs3jiiScAan3Nl156iQEDBnDFFVewdOlScnJy6N+/fyB2VQghRD0KdP8hhBCaUBQ4Oi4W1FL8qgufD6vBQPmRI7UXto6+uXJ36lT5pqaRaIj+QyeXVwrR9By7DM5srpe2uersL7e76uwt3O4/zrY6eqaVIzGR/JKSE4pMDTIGlV7/x2Xkp8rewMUpgIC0snv37iUxMZGEhAQMBgMZGRnk5ubWWGbXrl307t0bgPT0dL788ktUVSU3N5eMjAyMRiPx8fEkJiayd+/eWl9TVVW++uor0tPTAejdu/cJ2xJCCBEaAtl/CCFEo6PXg8WCarPht9vxJyTga9EC3/nn423XDu+FF+Lp3Bn3ZZdR8o9/NKoB3Rui/xBCiHpjMqHGxFQOFH/++fiaN8efkIDfbke12SpnKgy2ongA+oiAnEFVWFiIw+Gouu9wOPj+++9rXUav12O1WikpKaGwsJC2bdtWLWe32yksLKx6neNfs6SkBKvVil6vP2H542VnZ5OdnQ3AnDlzSEpKqtsOBmgkfVtAttJwJL+2JL+2tM6v9fbrKpD9x8mcSz9RY1kNZ1w5Jhh/B4ItU7DlgeDLFGx5IPgyBVseOLNMwZj7XDRU/3G8YHs/0Rh+jrIPwSHU9yFY859NrpO2Jxr+T1mXY3q2bWKQleQCKzMzkzlz5jBnzhyto5zWtGnTtI5wTiS/tiS/tiR/6KprPxFsxyzY8kDwZQq2PBB8mYItDwRfpmDLA8GZqTEJpvcTjeFnLfsQHEJ9H0I9PzTdfQhIgcput1NQUFB1v6CgALvdXusyPp8Pp9OJzWY7Yd3CwkLsdnutr2mz2XA6nfiOTgt8bHkhhBChJ5D9hxBCiMajIfoPIYQQDSsgBaqUlBQOHDhAXl4eXq+XHTt2kJaWVmOZLl26sGXLFgB27tzJhRdeiKIopKWlsWPHDjweD3l5eRw4cIA2bdrU+pqKonDhhReyc+dOALZs2XLCtoQQQoSGQPYfQgghGo+G6D+EEEI0LP2DDz74YENvRKfTkZiYyMKFC3n33Xfp0aMH6enprFmzhoqKCpKSkmjZsiUfffQRL7/8Mj/99BN33HEHERERREVFUVpaypIlS/joo4+45ZZbSEpKqvU1AVq3bs3y5cvZuHEj4eHh3HDDDVVjUoWy1q1bax3hnEh+bUl+bUn+ugl0/1Gfgu1nHmx5IPgyBVseCL5MwZYHgi9TsOWB4MzU0Bqi/wgFjeFnLfsQHEJ9H0I9PzTNfVBUVa23mWyFEEIIIYQQQgghhDhbTXqQdCGEEEIIIYQQQgihPSlQCSGEEEIIIYQQQghNGbQOIGrKz8/nqaee4vDhwyiKQmZmJtdccw2lpaUsWLCAQ4cOERcXx6RJk4iIiNA6bq38fj/Tpk3Dbrczbdo08vLyePzxxykpKaF169ZMmDABgyE4f/3KyspYvHgxv/zyC4qicNddd5GUlBQyx//NN98kJycHRVFITk5m/PjxHD58OKiP/6JFi/jkk0+Iiopi3rx5ALX+zquqyvPPP8+nn35KWFgY48eP1/z67JPlX7FiBbt378ZgMJCQkMD48eMJDw8HYP369eTk5KDT6Rg3bhydO3fWMv5J8x/zxhtvsGLFCp599lkiIyOD8vhrKVjb7GBrg4OxXQ2GtjLY2r5gbMuCrX2qLc8777zDpk2b0Ol0pKamMnr0aEC7Y/TTTz/xzDPP4Ha70ev13HbbbbRp00ba8Eaqtr4o1Bzfd4Wak/V17dq10zrWWTlZ32gymbSOdUpn05cGq7Ptf4PR2fTXp6SKoFJYWKj+8MMPqqqqqtPpVO+55x71l19+UVesWKGuX79eVVVVXb9+vbpixQotY57WG2+8oT7++OPqI488oqqqqs6bN0/96KOPVFVV1SVLlqibNm3SMt4pLVy4UM3OzlZVVVU9Ho9aWloaMse/oKBAHT9+vOpyuVRVrTzuH3zwQdAf/6+++kr94Ycf1MmTJ1c9Vtsx3717tzp79mzV7/er3377rTp9+nRNMld3svx79uxRvV6vqqqV+3Is/y+//KJOnTpVdbvd6sGDB9W//vWvqs/n0yT3MSfLr6qqeujQIfXhhx9W77rrLrW4uFhV1eA8/loK1jY72NrgYGtXg6WtDLa2LxjbsmBrn06W54svvlAfeugh1e12q6qqqocPH1ZVVdtjNGvWLPWTTz5RVbXyuMycObPqtrThjU9tfVGoOb7vCjUn6+tCSW19Y7A7m740WJ1N/xuszqa/PhW5xC/IxMTEVH2SZbFYaN68OYWFheTm5tKrVy8AevXqRW5urpYxT6mgoIBPPvmEfv36AaCqKl999VXVLFm9e/cO2vxOp5P//ve/9O3bFwCDwUB4eHhIHX+/34/b7cbn8+F2u4mOjg7649+xY8cTPtWo7Zjv2rWLnj17oigK7dq1o6ysjKKiooBnru5k+S+55JKq2UPbtWtHYWEhULlfGRkZGI1G4uPjSUxMZO/evQHPXN3J8uvFh4EAACAASURBVAO8+OKL3HTTTSiKUvVYMB5/LQVjmx1sbXCwtqvB0FYGW9sXjG1ZsLVPJ8vz3nvvMWjQIIxGIwBRUVGAtsdIURTKy8uByr/BmJgYQNrwxqq2viiUHN93hZra+rpQc3zfeKztCGZn05cGq7Ppf4PV2fTXpxI81/iIE+Tl5fHjjz/Spk0biouLqxqI6OhoiouLNU5XuxdeeIHRo0dX/WNUUlKC1Wqt+gOz2+1B+weWl5dHZGQkixYt4ueff6Z169bcfPPNIXP87XY71113HXfddRcmk4lLLrmE1q1bh8zxr662Y15YWEhsbGzVcg6Hg8LCwqDuQHNycsjIyAAq87dt27bquWD9eeTm5mK32znvvPNqPB6Kxz9QgqXNDrY2OBjb1WBuK4O57QuWtizY2qcDBw7wzTffsHr1aoxGI2PGjKFNmzaaHqOxY8cye/ZsVqxYgd/v5+GHHwaC4/dINKzqfVEoOb7vCjW19XVms1nraGfsZH3jJZdconWsOgmV925nqnr/G0pq669PRc6gClIVFRXMmzePm2++GavVWuM5RVHOuAIZaLt37yYqKipkxzPw+Xz8+OOP9O/fn0cffZSwsDA2bNhQY5lgPv6lpaXk5uby1FNPsWTJEioqKtizZ4/Wsc5ZMB/z01m3bh16vZ4ePXpoHeWMuVwu1q9fz8iRI7WOEjKCpc0OxjY4GNvVUGkrg6ntC5a2LBjbJ7/fT2lpKbNnz2bMmDEsWLAAVVU1zfTee+8xduxYnn76acaOHcvixYs1zSMC41R9UTALxr7rbJ1JXxfsTtY3btu2TetY5yyY+tK6CJb+92zVtb+WAlUQ8nq9zJs3jx49enD55ZcDlaeLHzsFu6io6PSDi2nk22+/ZdeuXdx99908/vjj/H/27jwwivr+//hzzySbhJBNCOFSjkRBkCOEAsGDI1oP2iIeKPXiEFsQv4gHVmntrxarIqgQECuH2FK8sQqV2pCmHBEMcqhABURFJBhzYEKuPX9/IFsCSUhCyGyS1+Ov7O7MZ147Ce9h3zufmc8++4yXX36Z0tJSvF4vcPzbO6fTaXDSqsXExBATExP4xnPQoEF8+eWXTWb/f/rpp8TFxdGqVSusVisDBw7k888/bzL7/2TV7XOn00leXl5gufz8/KB9P5mZmXz88cfce++9gQOj0+kkPz8/sEww/j6+++47cnNzefDBB5kyZQr5+fnMmDGDo0ePNqn931iCqWYHYw0OxroazLUyGGtfMNWyYKxPTqeTn/zkJ5hMJhISEjCbzRQXFxta7//zn/8E6tHgwYMDUwtVw5uvqo5FTUVVx6558+YZHatOqjvWNSVVHRv37t1rdKx6aSqf3c6kquNvU1HT8bomalAFGb/fz6JFi+jQoQMjR44MPJ+cnMx//vMf4Ph/OgYMGGBUxBqNHTuWRYsWsWDBAqZNm0avXr2499576dmzJ5s3bwaO/0NLTk42OGnVWrduTUxMDIcPHwaOF+qOHTs2mf0fGxvLvn37qKiowO/3B/I3lf1/sur2eXJyMuvXr8fv97N3714cDkdQTk3YsWMHf//735kxYwYhISGB55OTk8nKysLtdpObm0tOTk7QnYZ/3nnnsXjxYhYsWMCCBQuIiYnhqaeeonXr1k1m/zeWYKvZwViDg7GuBnOtDLbaF2y1LBjr04ABA9i1axcAhw8fxuPxEBkZaWi9dzqd7N69G4DPPvuM+Ph4oOkcQ6VuqjsWNRXVHbuakuqOdU1JVcfGDh06GB2rXprKZ7eaVHf8bSpqOl7XxOQ3+hxkqeS///0vv/vd7zjvvPMCXdJbbrmFxMREnn32WfLy8prErTIBdu3axXvvvcfDDz/Md999x3PPPcexY8fo0qULU6dODVxMNNh89dVXLFq0CI/HQ1xcHJMnT8bv9zeZ/f/666+TlZWFxWKhc+fO/OpXv6KgoCCo9/9zzz3H7t27KS4uJioqiptuuokBAwZUuc/9fj9Llixh586d2O12Jk+eTLdu3YIu/6pVq/B4PIG/k8TERCZNmgQcP1X33//+N2azmTvvvJN+/foZGb/K/Ccu8gkwZcoU/vSnPwVu4x5s+99IwVyzg6kGB2NdDYZaGWy1LxhrWbDVp6ryXHbZZYHrzlitVm677TZ69eoFGLeP2rdvz7Jly/D5fNhsNiZOnEjXrl1Vw5up6o5FSUlJBieru5OPXU1NVce6YP28UJ2qjo3B9JmhKnU5lgaruh5/g1Fdjtc1UYNKREREREREREQMpSl+IiIiIiIiIiJiKDWoRERERERERETEUGpQiYiIiIiIiIiIodSgEhERERERERERQ6lBJSIiIiIiIiIihlKDSqSB/fnPf+bNN98Ejt8q91e/+lWDb2PPnj383//9X4OPKyIixluwYAGvvvpqg4978vFJRETkZE888QSZmZlGx5AWzuT3+/1GhxBprnbt2sX8+fNZtGiR0VFERKSJWLBgATExMdx8881GRxERERFpNDqDSqSJ8Xq9RkcQEZEmxufzGR1BRESCkN/v1zFCgobV6AAiTdWhQ4dYvHgxX331FU6nk7Fjx5KcnFyvb76nTJlCamoq69ev5+jRowwYMICJEydit9sDZ2FdddVVrFmzht69ezN8+PBKZ2bl5eXx8ssvs2fPHvx+P0OGDGHChAkAZGRk8N5773H06FESEhKYNGkSbdq0OSf7RESkJaqqBo8bN45Vq1axbt06XC4Xffv2Zfz48TgcDgDmzp3Lnj17cLlcdO7cmYkTJ9KpU6dab/PEseHKK69kzZo1hIaGcvPNN3PppZcCx8/Cstvt5OXlsXv3bh588EE2bNhQ6fiUnZ3N66+/Tm5uLq1atWLChAn07duX0tJSli9fzvbt2zGZTAwbNoybbroJs1nfa4qInI0DBw6waNEijhw5Qt++fTGZTLRr146RI0eSlpbGvn378Pl8XHjhhdx1113ExMQAkJmZyZtvvklRURGRkZGV6n1VMjMzWbduHZ07d2b9+vVER0czYcIELr74YgB+//vfc+GFF7J7924OHDjAnDlzWLRoEZdeeikjRowAID09nTVr1pCfn09MTAxTp06la9euFBQUsHTpUvbs2UNoaCjXXnst11xzzbnfedIi6H8aIvXg8Xh46qmn6N27N4sXL2b8+PHMmzePw4cP13vMjRs38uijjzJ//nxycnJ4++23A68dPXqUY8eOsXDhQu6+++5K6/l8Pp566iliY2NZsGABixYtYsiQIcDxDx+rVq3i/vvvZ/HixXTv3p3nn3++3hlFRKSy6mpwZmYmmZmZPPbYY6SlpVFeXs6SJUsC6/Xt25d58+axePFiunTpwrx58+q87aNHj1JcXMyiRYuYMmUKf/7znysdhzZu3Mh1113H8uXL6d69e6V19+/fT1paGrfddhvLli3j//2//xf48mLBggVYLBbmzZvH008/zc6dO1m3bl0995CIiMDxzw/PPPMMQ4cOZenSpQwZMoSPPvoIOH4W09ChQ1m4cCELFy7EbrcHjhnl5eUsW7aMRx55hFdeeYU//vGPdO7c+Yzb27dvH23btmXJkiXcdNNNPPPMMxw7dizw+vr165k0aRKvvPIKsbGxldb98MMPeeONN5gyZQrLly9nxowZREZGBo55nTt35sUXX+R3v/sd//jHP9ixY0fD7Shp0dSgEqmHffv2UV5ezqhRo7BarfTq1YukpCQ2btxY7zF/+tOfEhsbS0REBNdddx2bNm0KvGYymbjpppuw2WzY7fZK6+3fv5+CggJuu+02QkNDsdvtgQ8i//rXv7juuuvo2LEjFouF6667jq+++orvv/++3jlFROR/qqvBGzduZOTIkbRt25bQ0FDGjh1LVlZWYJr28OHDCQsLw2azceONN/L1119TWlpa5+2PGTMGm83GRRddRL9+/cjKygq8NmDAALp3747ZbD7t2JGRkcGwYcPo3bs3ZrMZp9NJhw4dOHr0KNu3b+fOO+8kNDSUqKgorr322krjiohI3e3duxev18vVV1+N1Wpl4MCBJCQkABAZGcmgQYMICQkhLCyM0aNHs2fPnsC6JpOJgwcP4nK5iI6OrtUZtyfqt9VqJSUlhfbt27Nt27bA60OHDqVTp05YLBas1soTqzIyMvjFL35BQkICJpOJ+Ph42rRpwxdffEFRURE33HADVquVtm3bMmLECB0jpMFoip9IPRQWFhIbG1tpukObNm0oKCio95gnf3Nx6litWrU67cPFCXl5ebRp0waLxXLaa99//z3Lli3jlVdeCTzn9/spKCjQND8RkQZQXQ0uLCysVGdjY2Pxer388MMPtG7dmpUrV7J582aKioowmUwAFBUVBaYA1kZ4eDihoaGBx23atKGwsDDw+MTUkKrk5+fTr1+/Kt+P1+tl0qRJgef8fn+NY4mIyJkVFhbidDoDNR/+V6crKipYvnw5O3bsoKSkBICysjJ8Ph+hoaFMmzaN9957j0WLFnHhhRdy++2306FDhxq3d+q2Tv18UVNdz8vLo23btqc9//3331NYWMidd94ZeM7n89GjR4+a37xILalBJVIP0dHR5OXl4fP5Ak2qvLw82rVrV++zk/Ly8ir97HQ6A49PPricKjY2NvCB4tQPSLGxsYwePbrGOeoiIlJ/1dXg6OjoSseDvLw8LBYLUVFRbNy4ka1bt/Lb3/6WNm3aUFpayrhx4+q87ZKSEsrLywNNqry8vErfqtd07IiJieHIkSNVPm+1WlmyZEmVX3yIiEj9REdHU1BQgN/vD9Tn/Px84uPjee+99zh8+DBPPPEErVu35quvvuKhhx7C7/cDx6eF9+3bF5fLxauvvsqLL77IH/7whxq3d+q28vLySE5ODrx+ps8X3333XZXPx8XF1WtaukhtaIqfSD0kJiYSEhLCu+++i8fjYdeuXXz88ceBaz/Vxz//+U/y8/M5duwYb7/9NoMHD67VegkJCURHR7NixQrKy8txuVz897//BeCKK67gnXfe4ZtvvgGgtLSUDz/8sN4ZRUSksupq8JAhQ1izZg25ubmUl5ezcuVKBg8ejMVioaysDKvVSkREBBUVFaxcubLe23/99dfxeDzs2bOHbdu21frYMXz4cDIzM/n000/x+XwUFBTw7bffEh0dTZ8+fXjllVcoLS3F5/Nx5MgRdu/eXe+MIiICF1xwAWazmbVr1+L1esnOzmb//v3A8etM2e12HA4Hx44d44033gisd/ToUbKzsykvL8dqtRIaGlpjc+mEH374gffffx+Px8OHH37It99+W+WZs1UZPnw47733HgcOHMDv93PkyBG+//57EhISCAsL45133sHlcuHz+Th48GDgfYicLZ1BJVIPVquVGTNmsHjxYlatWoXT6eSee+4546m2Nbnkkkv44x//SGFhIcnJyVx//fW1Ws9sNjNjxgyWLl3K5MmTMZlMDBkyhO7du/OTn/yE8vJynnvuOfLy8nA4HFx88cW1/gAjIiI1q64G33nnnRQWFvLYY4/hcrno06cP48ePB+Dyyy9n586d/OpXvyIiIoIxY8bwwQcf1HnbrVu3JiIigrvvvhu73c5dd91V6+NQQkICkydPZvny5eTm5hIVFcWECRPo0KED99xzDytWrGD69OmUlZXRtm1bfvGLX9Q5n4iI/I/VauWBBx5g0aJF/O1vf6Nfv370798fq9XKlVdeybx585gwYQJOp5ORI0eSnZ0NHJ9mvXr1atLS0jCZTHTu3Jm77rrrjNtLTEwkJyeHCRMm0Lp1a6ZPn05kZGStsg4ePJji4mKef/55CgoKiIuL45577qFNmzbMmDGDV155hSlTpuDxeGjfvj1jxow5q30jcoLJf+K8QRExzJQpU7j77rvp3bu30VFERKQJ2LVrF/Pnz2fRokVGRxERkXp65JFHuOKKKxg2bFiDjpuZmcm6det4/PHHG3RckXNNU/xEREREREREzrHdu3dz9OhRvF4vmZmZfP311/Tt29foWCJBQ1P8RBpBXl4e9913X5WvPfvss42cRkREmoK3336bVatWnfZ8jx49NOVORKQJOnz4MM8++yzl5eW0bduW+++/n+jo6HqN9ec//5kNGzac9vyll17KBRdccLZRRQyhKX4iIiIiIiIiImIoTfETERERERERERFDqUElIiIiIiIiIiKGUoNKREREREREREQMpQaViIiIiIiIiIgYSg0qERERERERERExlBpUIiIiIiIiIiJiKDWoRERERERERETEUGpQiYiIiIiIiIiIodSgEhERERERERERQ1mNDiAiIiIiInLCjh07WLZsGT6fjxEjRjBq1KhKr7vdbtLS0jhw4ACRkZFMmzaNuLg4AFatWkVGRgZms5lx48bRt2/fGsd84YUXOHDgAH6/n3bt2jFlyhRCQ0PJzMzkL3/5C06nE4CrrrqKESNGNOJeEBFpedSgEhERERGRoODz+ViyZAkzZ84kJiaG3/zmNyQnJ9OxY8fAMhkZGYSHhzN//nw2bdrEihUruO+++zh06BBZWVnMnTuXwsJCHn/8cZ5//nmAase84447cDgcACxfvpy1a9cGmlcpKSlMmDCh8XeCiEgLpQbVSQ4fPlzj67GxseTl5TVSmsbXnN+f3lvT1ZzfX1N5b+3btzc6QtA403HiVMH8Ow7mbKB8ZyOYs4HynY1gzdaQx4n9+/cTHx9P27ZtgeNNouzs7EoNqq1bt3LjjTcCMGjQIJYuXYrf7yc7O5uUlBRsNhtxcXHEx8ezf/9+gGrHPNGc8vv9uFyus85f1+PEuRSsfy9G0f6oTPujMu2Pyhp6f9T2OKEGlYiIiIiIBIWCggJiYmICj2NiYti3b1+1y1gsFhwOB8XFxRQUFJCYmBhYzul0UlBQEBinujEXLlzI9u3b6dixI7fffnvg+S1btrBnzx7atWvHHXfcQWxs7Gl509PTSU9PB+DJJ5+schmjWK3WoMpjNO2PyrQ/KtP+qMyo/aEGlYiIiIiItFiTJ0/G5/OxdOlSsrKyGDZsGP3792fIkCHYbDb+9a9/sWDBAh577LHT1k1NTSU1NTXwOJjOwNAZIZVpf1Sm/VGZ9kdlRp1Bpbv4iYiIiIhIUHA6neTn5wce5+fnBy5UXtUyXq+X0tJSIiMjT1u3oKAAp9NZqzHNZjMpKSls2bIFgMjISGw2GwAjRozgwIEDDftGRUTkNGpQiYiIiIhIUOjWrRs5OTnk5ubi8XjIysoiOTm50jL9+/cnMzMTgM2bN9OzZ09MJhPJyclkZWXhdrvJzc0lJyeHhISEasf0+/0cOXIEOH4Nqq1btwa+5S8sLAxsb+vWrZWugSUiIueGpviJiIiIiEhQsFgsjB8/nlmzZuHz+Rg2bBidOnXitddeo1u3biQnJzN8+HDS0tKYOnUqERERTJs2DYBOnToxePBgpk+fjtlsZsKECZjNx7+Pr2pMn8/HggULKC0tBeD8889n4sSJALz//vts3boVi8VCREQEkydPNmaHiIi0IGpQiYiIiIhI0EhKSiIpKanSc2PGjAn8bLfbmT59epXrjh49mtGjR9dqTLPZzOOPP17lOGPHjmXs2LF1jS4iImdBU/xERERERERERMRQalCJiIiIiIiIiIih1KASERERERERERFD6RpUctYi58xp8DGL77+/wccUETHKuaiTtaFaKiLSNJyL44TF4SDyxwvAV0fHCREJJjqDSkREREREREREDKUGlYiIiIiIiIiIGEoNKhERERERERERMZSuQSVBqaHn4Z+Yg6959iIiIiIiIiLBR2dQiYiIiIiIiIiIodSgEhERERERERERQ6lBJSIiIiIiIiIihlKDSkREREREREREDKUGlYiIiIiIiIiIGEoNKhERERERERERMZQaVCIiIiIiIiIiYig1qERERERERERExFBqUImIiIiIiIiIiKHUoBIREREREREREUOpQSUiIiIiIiIiIoZSg0pERERERERERAylBpWIiIiIiIiIiBhKDSoRERERERERETGU1egA55LP5+Phhx/G6XTy8MMPGx1HqmEqKsKcn4+pvBx/WBi+2Fj8ERFGxxIRERERERGRRtKsG1T/+Mc/6NChA2VlZUZHkVO53dh27cK2cyeW/PzTXva2bYtrwAA8iYlgMhkQUEREREREREQaS7NtUOXn57Nt2zZGjx7N6tWrjY4jJ7F89RWh6emYi4rwxsdTfvnl+OLj8YeFYSorw/Ltt1h37yZs9Wq87dtTdvXV+KOijI4tIiIiIo1gx44dLFu2DJ/Px4gRIxg1alSl191uN2lpaRw4cIDIyEimTZtGXFwcAKtWrSIjIwOz2cy4cePo27dvjWO+8MILHDhwAL/fT7t27ZgyZQqhoaE1bkNERM6NZtugevnll7n11ltrPHsqPT2d9PR0AJ588kliY2NrHNNqtZ5xmaasvu/P4nDUbkGfD1NGBubNm/HHxOD95S+hc2dsp54hlZgIl12G79NPMX/wAeF//Su+G26ALl3qnO0Es9mMw+EgpBn+/vR32XQ15/cmIiJSHz6fjyVLljBz5kxiYmL4zW9+Q3JyMh07dgwsk5GRQXh4OPPnz2fTpk2sWLGC++67j0OHDpGVlcXcuXMpLCzk8ccf5/nnnweodsw77rgDx4//l12+fDlr165l1KhR1W5DRETOnWbZoPr444+Jioqia9eu7Nq1q9rlUlNTSU1NDTzOy8urcdzY2NgzLtOU1ff9RZaWnnkht5uw1auxfPklrj59qLj8crBaoabpl4mJmOLiCHvnHcyvvkrZyJF4u3Wrcz4Ah8NBaWkpxc3w96e/y6arqby39u3bGx1BRERaiP379xMfH0/btm0BSElJITs7u1KDauvWrdx4440ADBo0iKVLl+L3+8nOziYlJQWbzUZcXBzx8fHs378foNoxTzSn/H4/LpfrjNsw6dITIiLnTLNsUH3++eds3bqV7du343K5KCsrY968edx7771GR2uZXC7CVq3C8u23lKem4u7du9ar+qOiKL3pJhxvv03Y6tWU3ngjPn1YFhEREWmWCgoKiImJCTyOiYlh37591S5jsVhwOBwUFxdTUFBAYmJiYDmn00lBQUFgnOrGXLhwIdu3b6djx47cfvvtNW6jVatWlbLUdUZGdWo9I6EOTswgqElznF1QHZ25Xpn2R2XaH5UZtT+aZYNq7NixjB07FoBdu3bx3nvvqTllFI+HsL//Hcvhw5Rfey2eCy+s+xhhYZSNHo1j5Uoc77xDydix+Fu3bvisIiIiItLiTJ48GZ/Px9KlS8nKymLYsGG1XreuMzKqU6sZCXV0YgZBTZrj7ILqNJUz1xuL9kdl2h+VNfT+qO2MDHODbVHkVH4/oe+/j/Wbbyj/6U/r15w6MVRYGKXXXQd+P2Fr1oDX24BBRURERCQYOJ1O8k+6w3N+fj5Op7PaZbxeL6WlpURGRp62bkFBAU6ns1Zjms1mUlJS2LJlS43bEBGRc6fZN6h69uzJww8/bHSMFsm+ZQu2ffsov+wyPBdddNbj+aOjKb/ySizffUfIhg0NkFBEREREgkm3bt3IyckhNzcXj8dDVlYWycnJlZbp378/mZmZAGzevJmePXtiMplITk4mKysLt9tNbm4uOTk5JCQkVDum3+/nyJEjwPFrUG3dujXwLX912xARkXOnWU7xE+NZvvgCe1YW7h49cPfv32DjehITcfXpg23bNjyJiXg7dGiwsUUkONX3duOffPIJK1aswOPxYLVaue222+jVqxcABw4cYMGCBbhcLvr168e4ceP0wUNEJAhYLBbGjx/PrFmz8Pl8DBs2jE6dOvHaa6/RrVs3kpOTGT58OGlpaUydOpWIiAimTZsGQKdOnRg8eDDTp0/HbDYzYcIEzObj38dXNabP52PBggWBaXDnn38+EydOBKh2GyIicu6oQSUNzlxQQNj77+OLi6M8NRUa+ENfxaWXYv3yS0I++IDS2247fjdAEWmWzuZ245GRkcyYMQOn08nBgweZNWsWL774IgAvvfQSd999N4mJifzpT39ix44d9OvXz6i3KSIiJ0lKSiIpKanSc2PGjAn8bLfbmT59epXrjh49mtGjR9dqTLPZzOOPP17lODVtQ0REzo1mP8VPGpnbTeh77+G3WCj7+c/BZmv4bdjtlKemYiksxP7xxw0/vogEjZNvN261WgO3Bj/Z1q1bGTp0KHD8VuCfffYZfr+fLl26BK4x0qlTJ1wuF263m8LCQsrKyrjgggswmUxcdtllp40pIiIiIiKNSw0qaVAhGzZgyc+n/Oqr8Z9yG96G5O3cGXdiIvYtWzAVF5+z7YiIsaq63fiJW4ZXtczJtwI/2ZYtW+jatSs2m61WY4qIiIiISOPS3ChpMJYvv8S+Yweufv3wdu58zrdXcfnlWA8cIGTDBsqvueacb09EmqZvvvmGFStW8Oijj9Z53fT0dNLT0wF48skniY2NrdP6VquV2NhYLA5HnbfdEEJqyHsiW7BSvvoL5mygfGcjmLOJiIicLTWopEGYSksJ/ec/8cbEUHHppY2yTX+rVrj698f+0UeYf/ITfPoPm0izU5fbjcfExJx2K/D8/HyeeeYZpkyZQnx8fK3HPCE1NZXU1NTA47y8vDrlj42NJS8vj8gfL8Db2IpryHsiW7BSvvoL5mygfGcjWLOduPOdiIjI2dAUP2kQIenpmCoqjp/J1IgXLXf17w92O/asrEbbpog0nrO53XhJSQlPPvkkY8eOpXv37oHlo6OjCQsLY+/evfj9ftavX3/amCIiIiIi0rh0BpWcNev+/dj276fikkvwtWnTuBsPC8PVvz8hH36I67vv8LVt27jbF5Fz6mxuN7527VqOHDnCm2++yZtvvgnAzJkziYqKYuLEiSxcuBCXy0Xfvn11Bz8REREREYOpQSVnxVRcTEhGBt7Y2ONnMxnAlZSEfds2QrKyKLvuOkMyAL+gcgAAIABJREFUiMi5U9/bjV9//fVcf/31VY7ZrVs35syZ07BBRURERESk3jTFT85K5OzZmI4do/yKK8BiMSZESAiuAQOwfvkl5sOHjckgIiIiIiIiIvWmBpXUm23HDsKXLsXdpw++du0MzeLq2xdfWBghH35oaA4RERERERERqTs1qKR+PB5aP/QQvrg4Ki65xOg0YLfjTkrC+vXXmL//3ug0IiIiIiIiIlIHalBJvYQvWYJt1y5+ePxxCAkxOg4Art698Vut2LdtMzqKiIiIiIiIiNSBGlRSZ5ZDh4icPZvy1FTKr7nG6Dj/ExaGu1cvrHv2YDp2zOg0IiIiIiIiIlJLalBJ3fj9RD3yCJhM/PDEE2AyGZ2oEldSEvh82HbsMDqKiIiIiIiIiNSSGlRSJ6Fr1hC6bh3FDzyAt0MHo+Ocxt+6NZ7EROw7d4LLZXQcEREREREREakFNaik1kxFRUT97ne4evWiZMIEo+NUy9W/P6aKCmy7dhkdRURERERERERqQQ0qqbVWTz2F+fvv+eHpp8FqNTpOtXzt2+Nt1w779u3g9xsdR0RERERERETOQA0qqRXbxx/jWL6cknHjcPfpY3ScM3L17Yv56FEsBw8aHUVEREREREREzkANKjkzt5vWM2bga9uW4oceMjpNrXgSE/GFheli6SIiIiIiIiJNgBpUckYRL72Ebc8efpg1C39EhNFxasdqxd2rF9YDBzAVFxudRkRERERERERqoAaV1Mhy8CARc+ZQdtVVlF91ldFx6sTduzf4/dg++cToKCIiIiIiIiJSAzWopHp+P1GPPAIWCz/84Q9Gp6kzf1QU3q5dsX36KXi9RscRERERERERkWqoQSXVCn33XUL//W+KZ8zA16GD0XHqxdWnD+bSUkyff250FBERERERERGphhpUUiXTDz8Q9dhjuPr0oeTOO42OU2/ezp3xRUVh+vhjo6OIiIiIiIiISDWsRgeQ4NTqiScw5+eT/9e/gsVidJz6M5lwX3wxIRs3YiosNDqNiIiIiNRgx44dLFu2DJ/Px4gRIxg1alSl191uN2lpaRw4cIDIyEimTZtGXFwcAKtWrSIjIwOz2cy4cePo27dvjWPOmzePL774AqvVSrdu3Zg0aRJWq5Vdu3bx9NNPB8YdOHAgN9xwQyPuBRGRlklnUMlpbNnZhP/1r5RMnIinVy+j45w190UX4TeZsH32mdFRRERERKQaPp+PJUuW8Mgjj/Dss8+yadMmDh06VGmZjIwMwsPDmT9/Ptdeey0rVqwA4NChQ2RlZTF37lweffRRlixZgs/nq3HMSy65hOeee45nnnkGl8tFRkZGYDs9evRg9uzZzJ49W80pEZFGogaVVOZ20/rhh/F06EDxAw8YnaZB+CMiIDER2+7d4HYbHUdEREREqrB//37i4+Np27YtVquVlJQUsrOzKy2zdetWhg4dCsCgQYP47LPP8Pv9ZGdnk5KSgs1mIy4ujvj4ePbv31/jmElJSZhMJkwmEwkJCeTn5zf2WxYRkZNoip9UEvHCC9j++1/yly3DHx5udJwG4+vbF8vevYRmZFD+058aHUdERERETlFQUEBMTEzgcUxMDPv27at2GYvFgsPhoLi4mIKCAhITEwPLOZ1OCgoKAuPUNKbH42HDhg3cedJ1V/fu3cuDDz5IdHQ0t912G506daoyc3p6Ounp6QA8+eSTxMbG1uOdg8XhqNd6NTGbzTjOMG5IPfM2RVartd6/n+ZI+6My7Y/KjNofalDJ/+zdS+Rzz1E2ciQVV15pdJqGlZCALzwcx8qValCJiIiISMDixYvp0aMHPXr0AKBLly4sXLiQ0NBQtm3bxuzZs5k3b16V66amppKamhp4nJeXV68MkaWl9VqvJg6Hg9IzjFtcz7xNUWxsbL1/P82R9kdl2h+VNfT+aN++fa2W0xQ/Oc7nwzplCv7QUH54/HGj0zQ8sxl3z56ErFuHOSfH6DQiIiIicgqn01lpml1+fj5Op7PaZbxeL6WlpURGRp62bkFBAU6n84xjvvHGGxQVFXH77bcHnnM4HISGhgLHpwF6vV6Kiooa9s2KiMhp1KASAByvvop5/XqKfvtbfD/esaS5cffsicnnw/HGG0ZHEREREZFTdOvWjZycHHJzc/F4PGRlZZGcnFxpmf79+5OZmQnA5s2b6dmzJyaTieTkZLKysnC73eTm5pKTk0NCQkKNY65bt46dO3cybdo0zOb/fSw6evQofr8fOH5dLJ/PR2RkZOPsBBGRFkxT/ATzd9/R6vHH8V1+OaU332x0nHPGHx1NRUoKjldf5dg994BZ/VkRERGRYGGxWBg/fjyzZs3C5/MxbNgwOnXqxGuvvUa3bt1ITk5m+PDhpKWlMXXqVCIiIpg2bRoAnTp1YvDgwUyfPh2z2cyECRMCTaeqxgR46aWXaNOmDY8++igAAwcO5IYbbmDz5s188MEHWCwW7HY706ZNw2QyGbNTRERaEDWoWpjIOXNOey70vfcwlZTg69mTyLlzDUjVeErHjiX6nnuwZ2XhuuQSo+OIiIiIyEmSkpJISkqq9NyYMWMCP9vtdqZPn17luqNHj2b06NG1GhPg1VdfrXKcq666iquuuqousUVEpAHoFJIWzvLFF9j27cM1aBCcMse/OSq7+mp8rVvjWLnS6CgiIiIiIiIi8iM1qFqyigpC163DGxuL65T5/c1WaCilo0cT9o9/YPrx1sMiIiIiIiIiYiw1qFqwkI0bMR07RvkVV4DFYnScRlN6882YXC4cq1YZHUVEREREREREUIOqxTIfPoxt507c/frha9fO6DiNytOzJ64+fXD87W/w4x1aRERERERERMQ4alC1RB4PoR98gD8ykoohQ4xOY4jSW27B9t//Ytuxw+goIiIiIiIiIi2eGlQtkD07G0tBAeWpqWC3Gx3HEGWjRuELCzt+FpWIiIiIiIiIGMpqdIBzxeVy8dhjj+HxePB6vQwaNIibbrrJ6FiGM+fnY//oI9wXXoi3Sxej4xjGHxlJ+c9+Rtjf/07R73+PPzzc6EgiIiIiIiIiLVazPYPKZrPx2GOPMXv2bJ5++ml27NjB3r17jY5lLJ+PkH/9C2w2KoYNMzqN4UrGjsVcUkLYu+8aHUVERERERESkRWu2DSqTyURoaCgAXq8Xr9eLyWQyOJWxHH/9K9bDhym//HL8DofRcQznTk7GnZiIY8UKo6OIiIiIiIiItGjNdoofgM/nY8aMGRw5coSf/vSnJCYmVno9PT2d9PR0AJ588kliY2NrHM9qtZ5xmaD17bfYnngCf+fO2JOTsVfRrDObzTiaaePqxHsLOeX3Z7rrLmwPPUSbI0fw9+plULqz06T/LmuhOb+/5vzeRERERERE6qJZN6jMZjOzZ8+mpKSEZ555hoMHD3LeeecFXk9NTSU1NTXwOC8vr8bxYmNjz7hMsIqePBmr203p8OH4y8qqXMbhcFBaWtrIyRrHifdWfMrvz3z11bSdOZOKhQsp+sMfDEp3dpry32VtNOf311TeW/v27Y2OICIiIiIizVyzneJ3svDwcHr27MmOHTuMjmKI0PffJ2ztWo5Nn46/dWuj4wQVn9NJ+VVX4XjrLSgvNzqOiIiIiIiISIvUbBtURUVFlJSUAMfv6PfJJ5/QoUMHg1M1PlNREVEzZ+K+6CKOTZpkdJygVHLLLZiPHiXs/feNjiIiIiIiIiLSIjXbKX6FhYUsWLAAn8+H3+9n8ODB9O/f3+hYtRY5Z06DjBOybh3m776jfPhwIufNa5AxmxvXJZfgOe88HH/7G2XXXWd0HBE5xY4dO1i2bBk+n48RI0YwatSoSq+73W7S0tI4cOAAkZGRTJs2jbi4OIqLi5k7dy779+9n6NChTJgwIbDO73//ewoLC7Hb7QDMnDmTqKioRn1fIiIiIiLyP822QXX++efz9NNPGx3DUObDh7Ht3Ik7KQlffLzRcYKX2UzpzTfT6umnsXz5Jd4uXYxOJCI/8vl8LFmyhJkzZxITE8NvfvMbkpOT6dixY2CZjIwMwsPDmT9/Pps2bWLFihXcd9992Gw2xowZw8GDB/nmm29OG/vee++lW7dujfl2RERERESkGs12il+L5/US+q9/4Y+MpCIlxeg0Qa90zBj8FguOV181OoqInGT//v3Ex8fTtm1brFYrKSkpZGdnV1pm69atDB06FIBBgwbx2Wef4ff7CQ0NpXv37oGzpEREREREJHg12zOoWjp7djaW/HxKR40CfTg7I198POUjRuB47TWKH3gAbDajI4kIUFBQQExMTOBxTEwM+/btq3YZi8WCw+GguLiYVq1a1Tj2woULMZvNDBw4kOuvvx6TyXTaMunp6aSnpwPw5JNPEhsbW6f8VquV2NhYLA5HndZrKCE15D2RLVgpX/0FczZQvrMRzNlERETOlhpUzZCpoAD7li24L7gAb9euRsdpMkrHjiXsgw8I/eADyq+91ug4InIO3XvvvTidTsrKypgzZw7r16/n8ssvP2251NRUUlNTA4/z8vLqtJ3Y2Fjy8vKILC0968z1UVxD3hPZgpXy1V8wZwPlOxvBmq19+/ZGRxARkWZAU/yaG7+f0PR0sFqpGDbM6DRNSsXw4Xg6dCD8lVeMjiIiP3I6neTn5wce5+fn43Q6q13G6/VSWlpKZGTkGccFCAsL45JLLmH//v0NnFxEREREROpCDapmxrprF9ZDh6i47DL84eFGx2laLBZKb7uNkI0bserDqkhQ6NatGzk5OeTm5uLxeMjKyiI5ObnSMv379yczMxOAzZs307Nnzyqn653g9XopKioCwOPx8PHHH9OpU6dz9h5EREREROTMNMWvOSkrI3T9ejwdOuDu1cvoNE1S6S23EDlnDo5XXqHoD38wOo5Ii2exWBg/fjyzZs3C5/MxbNgwOnXqxGuvvUa3bt1ITk5m+PDhpKWlMXXqVCIiIpg2bVpg/SlTplBaWorH4yE7O5uZM2cSGxvLrFmz8Hq9+Hw+Lr744krT+EREREREpPGpQdWMhGzaBBUVVIwYATWcPSDV88XGUjZyJI433qD44YfxG3RhYxH5n6SkJJKSkio9N2bMmMDPdrud6dOnV7nuggULqnz+qaeeariAIiIiIiJy1jTFr5kwHzmC7ZNPcPfrh093dzkrpbffjrmoiLB33jE6ioiIiIiIiEiLENQNquzsbLxer9Exgp/fT2hGBn6Hg4rBg41O0+S5BgzA3aMH4S+/DH6/0XFEmgXVcxGRlkM1X0RE6iOop/i9/vrrLFq0iJSUFC677DISExONjhSUrLt2YTlyhLKrroKQEKPjNH0mEyW3307r3/wG29atuAcMMDqRSJOnei4i0nKcbc3fsWMHy5Ytw+fzMWLECEaNGlXpdbfbTVpaGgcOHCAyMpJp06YRFxcHwKpVq8jIyMBsNjNu3Dj69u1b45jz5s3jiy++wGq10q1bNyZNmoTVasXv97Ns2TK2b99OSEgIkydPpmvXrg2wd0REpDpBfQbV7Nmz+e1vf4vdbmfOnDn83//9H2+99Ra5ublGRwse5eWEbNiAp317PD16GJ2m2Si7/np8UVFEvPSS0VFEmgXVcxGRluNsar7P52PJkiU88sgjPPvss2zatIlDhw5VWiYjI4Pw8HDmz5/Ptddey4oVKwA4dOgQWVlZzJ07l0cffZQlS5bg8/lqHPOSSy7hueee45lnnsHlcpGRkQHA9u3bOXLkCPPmzWPSpEksXry4gfeSiIicKqjPoALo3LkznTt35tZbb+XTTz/lL3/5C6+//jrdu3cnNTWVIUOGYDYHdZ/tnArJysJUXk7F8OG6MHoD8oeHU/LLXxKxaBGWb77Bq1vQi5w11XMRkZajvjV///79xMfH07ZtWwBSUlLIzs6mY8eOgWW2bt3KjTfeCMCgQYNYunQpfr+f7OxsUlJSsNlsxMXFER8fz/79+wGqHfPkm3AkJCSQn58f2MZll12GyWTiggsuoKSkhMLCQqKjo8/NDhMRkeBvUAEcOXKEDRs2sGHDBkwmE2PGjCE2Npa1a9eyZcsWHnjgAaMjGsL8/ffYdu7E3bs3vh9Pa5aGU3LnnUS8+CLhS5dS9NhjRscRaRZUz0VEWo761PyCggJiYmICj2NiYti3b1+1y1gsFhwOB8XFxRQUFFSaTuh0OikoKAiMU9OYHo+HDRs2cOeddwa2EXvSjYdiYmIoKCg4rUGVnp5Oeno6AE8++WSlderCcg7uHG02m3GcYdyQFnRzJavVWu/fT3Ok/VGZ9kdlRu2PoG5QrV27lg0bNpCTk0NKSgr33HMPF1xwQeD1gQMHMnHiRAMTGsjvJ+Q//wG7nYqUFKPTNEu+Dh0oGzkSx8qVFN9/P/6ICKMjiTRZquciIi1HU6z5ixcvpkePHvSo4yUzUlNTSU1NDTzOy8ur1/YjS0vrtV5NHA4HpWcYt7ieeZui2NjYev9+miPtj8q0Pypr6P3Rvn37Wi0X1A2qHTt2MHLkSJKTk7HZbKe9HhIS0mK/bbd89RXWgwcpHzoUwsKMjtNsldx1F46//x3Ha69RMmGC0XFEmizVcxGRluNsar7T6QxMswPIz8/H6XRWuUxMTAxer5fS0lIiIyNPW7egoCCwbk1jvvHGGxQVFTFp0qRK2zj5w1lVOUREpGEF9cU+LrroIgYPHnzagW316tWBn/v06dPYsYzn8xGyfj2+qCjcLfH9NyJ3v364+vcnfMkS0O2SRepN9VxEpOU4m5rfrVs3cnJyyM3NxePxkJWVRXJycqVl+vfvT2ZmJgCbN2+mZ8+emEwmkpOTycrKwu12k5ubS05ODgkJCTWOuW7dOnbu3Mm0adMqXRMrOTmZ9evX4/f72bt3Lw6HQ9efEhE5x4K6QfXWW2/V6fmWwrZrF5b8fCouvRQsFqPjNHvHJk3C+vXXhP7jH0ZHEWmyVM9FRFqOs6n5FouF8ePHM2vWLO677z4GDx5Mp06deO2119i6dSsAw4cP59ixY0ydOpXVq1fzy1/+EoBOnToxePBgpk+fzqxZs5gwYQJms7naMQFeeuklfvjhBx599FEefPBB3nzzTQD69etHXFwc9957Ly+++GLQTUkUEWmOgnKK32effQaA1+sN/HzCd999R1hLntLmcmHPysLbvj2eky4CKedO+dVX4+nalYi0NMpHjtTdEkXqQPVcRKTlaKian5SUVOnuegBjxowJ/Gy325k+fXqV644ePZrRo0fXakyAV199tcpxTCaTmlIiIo0sKBtUL7zwAgButzvwMxw/ULRu3Zrx48cbFc1w9u3bMZeUUPKzn6lR0lgsForvuYfo6dMJycigYsQIoxOJNBmq5yIiLYdqfhBwubB+/TWWb7/FXFJCWHk5/tBQfDExeDt2xNuhgz5DiEjQCsoG1YIFCwBIS0vjnnvuMThNECkvx751K+5u3fDV8ir40jDKRo8mcs4cIufNo2L4cB3YRWpJ9VxEpOVQzTdQWRkhW7Zg++wzTC4XfqsVoqMxWSyYjx7F+vnnmABfVBSufv1w9+4N1qD8KCgiLVhQVyUd2Cqzb90KFRW4UlKMjtJkRc6ZU+91PRdeSGhGBq3vuw/vj9ctACi+//6GiCbSrKmei4i0HKr5jcu6ezeh//43uFx4LrwQ98UX423fHkdkJKWlpccXKi/H+uWX2D75hNDMTOzbtlF+xRXGBhcROUXQNajuu+8+nn32WQB+/etfV7vcyacNtwSm0lLs27fjufBCfG3aGB2nRXL37Il982bsW7ZQdlKDSkSqpnouItJyqOYbwOMhdN06bLt24enQgYoRI/DFxla9bGgonh498HTvjuXgQUIzMnC89RY+p5OimTN1NpWIBIWgq0R333134OepU6camCS42D/6CDweKgYPNjpKy2Wz4erfn9ANGzAfPqxpliJnoHouItJyqOY3MpeLsHffxXrwIBUDB+IaPBjMtbhBu8mE9/zzKbn1VkI2bCDipZew7dpFweLF+KOizn1uEZEaBF2Dqnv37oGfL7roIgOTBA9TcTG2nTvxXHQRfqfT6DgtmrtPH+wff0zIxo2U3XijrkUlUgPVcxGRlkM1vxG53YStWoXl8GHKrroKT332t81GxfDhlNx5J60ffJDYG24g/29/00wNETFULdrsxlm9ejVfffUVAHv37uXXv/41U6ZMYe/evcYGa2T2rVvB76di0CCjo4jdjmvgQKyHDmH5+muj04g0GarnIiIth2r+OeTzEbZ6NZZvv6X8mmvq15w6SdmNN1Lw8stYvvySmDFjMBcUNFBQEZG6C+oG1Zo1a4iLiwNg5cqVjBw5kuuvv56XX37Z2GCNyFRSgu2TT/D06KHTboOEu3dvfK1aEbJxI/j9RscRaRJUz0VEWg7V/HMnZP16rF9+SUVqKp4LL2yQMSuGDqXg5Zexfv01zrFjMZWUNMi4IiJ1FdQNqtLSUhwOB2VlZXz11VdcffXVDB8+nMOHDxsdrdHYPv4YfD4qfvITo6PICRYLFSkpWHJzseqbQJFaUT0XEWk5VPPPDevu3di3bcOVlIS7d+8GHdt1ySUUvPgitl27aD11Kvh8DTq+iEhtBHWDKiYmhs8//5xNmzbRo0cPzGYzpaWlmGtzAcDmoKwM+86deC64AH90tNFp5CSe7t3xxsQQsmkTuN1GxxEJei2+nouItCCq+Q3PVFBA6Lp1eDp2pOKyy87JNipSUyn6/e8J++c/iXzqqXOyDRGRmgTdRdJPduuttzJ37lysViv3338/ANu2bSMhIcHgZI3Dvn07Jrcb18CBRkeRU5nNVFx6KY533iF8+XJKJk40OpFIUGvp9VxEpCVRzW9gXi9h//gHfouF8quvrt3d+uqpZPx4rHv3EpmWhich4fhNgUREGklQN6iSkpJ48cUXKz03aNAgBrWEi4VXVGDfvh13t274YmONTiNV8Hbpguf884l85hnKfvEL3fVEpAYtup7XwFRUhOXgQcxFRWA242vVCu955+GPiDA6mohIvanmNyz7xx9jyc2l7Gc/wx8ZeW43ZjLxwx//iPXLL2n90EO4e/TA06vXud2miMiPgrpBBcfnsB8+fJjy8vJKz/dq5oXS9umnmCoqdPZUMDOZKB82jPAVK2j1pz9xdO5coxOJBLWWWs+rYs7JIWTjRqzffAOAHzCd9LrnvPNwDRqEt2NHQ/KJiJwt1fyGYTp6FPuHH+JOSMCTmNg4G7XZKFy0iDapqURPmULe++/jdzgaZ9si0qIFdYMqMzOTJUuWEBoait1uDzxvMplIS0szMNk55nZj374dT8eO+OLjjU4jNfA7nZRMnEjECy9QcuutuJOSjI4kEpRabD0/lddLyIYN2Ldtw+dwUDFkCJ6EBHytW4Pfj7mwEOsXX2DbsQPH66/jvugiyocOhdBQo5OLiNSaan4D8fsJTU8/foOeYcMaddM+p5PC558n5pZbaPXYY/wwe3ajbl9EWqagblCtXLmS6dOn069fP6OjNKqwNWswFxdTPny40VGkFoqnTSPs7beJmjmTvNWrz+l1AUSaqpZazytxuQh75x2shw7h6tOHiksvhZM+uAH42rTB1aYNrv79sX/0EfaPPiL8228pGzUKX0yMQcFFROpGNb9hWPfswXrwIOUjRpz7qX1VcF16KcemTCEyLY2KSy+l/Oc/b/QMItKyBHWDyufz0adPH6NjNC6/n/BFi/BGR+Pt2tXoNFIL/ogIimbOJHrqVMJffpmS8eONjiQSdFpkPT+Zy0XY229jycmh7Kqr8Fx0Uc3L22y4hgzB06ULYe++i2PlSsquuw5vhw6Nk1dE5Cy0+JrfEMrLCfnPf/C2a4e7d2/DYhQ/8AAhmzbResYMcgcMwNeunWFZpGmInDPHkO0W/3hDBmnagvpUj1/84he89dZb+Hw+o6M0GvuHH2L/9FPc/fuDyXTmFSQolF13HeXDhxP5xBNYvvrK6DgiQacl1vOAH+++ZMnJofzaa8/cnDqJr317SseOxR8efrzBdejQOQwqItIwWnTNbyD27GzMZWWUjxhh7GcCm43C+fPB5aL1ww+D329cFhFp9oL6DKo1a9Zw9OhR3n33XSJOuaPRCy+8YFCqcyvixRfxxsTg7tHD6ChSFyYTR596irjhw2n9wAPkv/66pvqJnKQl1vMTWv3pT1gPHKB8xAg8F1xQ5/X9rVpReuONhL35JmF//zulN9+s6X4iEtRacs1vCKbiYuzbtuHu3h1fXJzRcfB26ULxQw8R9Yc/EPbOO5Rdd53RkUSkmQrqBtXUqVONjtCoLPv3E5qeTvH06UZHkXrwtW9P0WOP0fqBB3C88gqld95pdCSRoNHS6nlAWRn2jRtx9emD+yymu/gjIigbPRrH3/5G2DvvUHrLLbqjkogErRZb8xuIPSsLgIohQwxO8j8lEycStno1UTNnUnHJJfjatDE6kog0Q0HdoLqoDtMgmoPw5cvx2+2U3HEH4cuXGx1H6qH05psJfe89Ws2aRcXll+Pt0sXoSCJBoaXV84CwMPJXrSJi/vyzHsrfqhVlo0bheP31402qG28Em60BQoqINKwWW/MbgDkvD9vu3bj79cMfFWV0nP+xWDg6dy5trrySqEcfpfDPfzY6kYg0Q0E9B8ntdrNy5Uruuece7rjjDgB27tzJ2rVrDU7W8EzHjuF4/XXKfvYzfLGxRseR+jKZODp7NtjtRP/611BRYXQikaDQkur5qfxhYWCxNMhYvvh4yq+5BvORI4T+61+6FoiIBKWWXPPPVsiGDWC3UzFwoNFRTuNJTKT4vvsIW7OGkPR0o+OISDMU1A2q5cuX880333Dvvfdi+vHigJ06deKDDz4wOFnDC3vzTczHjlGiaWFNnq9DBwqffRb7p5/S6o9/NDqOSFBoSfX8XPMkJOAaMgTbf/+L7dNPjY4jInIa1fz6MefkYP3yS1wDBkBYmNFxqnTsV7+h5BUtAAAgAElEQVTCnZBA1G9/C2VlRscRkWYmqKf4ffTRR8ybN4/Q0NDAwc3pdFJQUFDjenl5eSxYsICjR49iMplITU3lmmuuaYzI9eP3E/7yy8evUdKvn9FppAFUXHklxyZOJGLxYlyDB1MezH9/Io2gvvVcqub6yU+wHDpEyL//jbddO10LRESCimp+/YRs2YI/NBRX376Nts3IOXPqvI67b18cb75JzK234kpJqfP6xfffX+d1RKRlCOoGldVqPe32tEVFRURGRta4nsVi4bbbbqNr166UlZXx8MMP07t3bzp27Hgu49abfdMmbPv2Ufjss8beRlYaVNGjj2LPzqb1/ffzfY8edboeVV3+s2BxOIgsLa3VsvoPgRilvvVcqmEyUX711Tj+8hdCV6+m9Je/BLvd6FQiIsDZ1fwdO3awbNkyfD4fI0aMYNSoUZVed7vdpKWlceDAASIjI5k2bRpxP97pbtWqVWRkZGA2mxk3bhx9f2z0VDfm2rVrWbNmDd999x2LFy+mVatWAOzatYunn346MO7AgQO54YYbzm6nnIE5NxfrgQNUpKQEfT33nnce7gsvxJ6djbtHD/zR0UZHEpFmIqin+A0aNIi0tDRyc3MBKCwsZMmSJaScoVMfHR1N165dAQgLC6NDhw5B/Y1N+Msv442OpuznPzc6ijQku53CRYvAbMY5bhymoiKjE4kYpr71XKrndziOX4/q6FFCMzKMjiMiElDfmu/z+ViyZAmPPPLI/2fvvuOjqPM/jr92tm/6bkhCCUJCRxBCQAmKNBEBpQqnIop4dyqiiOJZ8CyI5RTRE9GfvaFSPAUBOUFANBEOBPQACxE4QUpINoSQ3WyZmd8fCxGUnjIpn+fjsY9kNzOz75lsJruf+RamT59OdnY2u3btOmaZ5cuXExUVxfPPP8+AAQOYNWsWALt27SInJ4dnnnmG+++/n9deew1N0066zZYtW/LAAw9Q7zitUFu3bs1TTz3FU089VenFKQDbmjXoNluVtp4qj8DFF4PZjGPFChkPUQhRYap1gerqq68mOTmZO++8E5/Px2233UZCQgJXXnnlaW8jLy+P7du306xZs0pMevbMv/6K49//jlz9djiMjiMqmNq4Md6XX8ayfTsJ48aBqhodSQhDVMT5XPyRmppKsEsXrFu2YMnNNTqOEEIAZ3/Oz83NJSUlheTkZCwWC1lZWaxdu/aYZdatW0ePHj2ASCFs06ZN6LrO2rVrycrKwmq1kpSUREpKCrm5uSfdZtOmTctaSRnJ8uOPWLduJdixY435PKBHRxPIysKyY4f8/xFCVJhq3cVv7969NGjQgCFDhqBpGl26dKFx48anvX5paSnTpk3j+uuvx+Vy/eHny5YtY9nhGSieeOIJEk8xe57FYjnlMmfKPHMm6Dr28eOxH7Vt83HyVjZFUY57nGqDytw3+6leE4MGoT77LI5bbyV5+nTUJ5445TbP5Pd/Jvt2yqzVUGX83VUXtXnffq+853NxYsELLsCyfTv2pUtRGzRAr6XncSFEzXG253yv14vH4ym77/F42Lp16wmXMZvNuFwuiouL8Xq9NG/evGy5o8e8OtU2j+enn35i0qRJJCQkcO2115Kamnrc5c7088TxmO+8E91qxdKtG5YKPIdX+nv7rCz0LVtwfPEFWuvWp9010aj3o3XpfdfpqKzjYcTnWCj/60peH8cy6nhUywKVruu8+OKLfPHFF3g8HhISEvB6vcybN4/u3btz8803lw24eCLhcJhp06Zx0UUXcf4Jpmnt06cPffr0Kbufn59/0m0mJiaecpkzoqokv/46gYsvxhsdDUdt+3THFKpILpcLnwHPWxUqc9+KT+c1MWQIsd98Q/T06RQnJeEbPfqki5/J7/9M9u20slYzFf53V43UlH1r0KDBWa9bEefzsx2PpLi4mGeeeYbc3Fx69OjB2LFjy9bZtm0bL7zwAsFgkI4dOzJmzJhT5qi2zGZK+/XDNWsW9qVLKb3iChnPUAhhiIo451cHTZs2ZebMmTgcDtavX89TTz3FP//5z+Mue6afJ35P8XpJ/ugjQuedRwCgAt+vVsV7e6VXL6I++IDwihUEL7rotNYx6v1oTXnfVVUq63gY8TkWyv+6ktfHsSr6eJzu54lqWaBatmwZW7ZsYerUqcd0zcvNzeW5555j6dKl9O3b94Tr67rOSy+9RMOGDRk4cGBVRD4r9pUrMe/ZQ9HDDxsdRVSBgw89hGXnTuLuuw/N46F0wACjIwlR6cp7Pj8ydsjkyZPxeDzce++9ZGZmHjPpxdHjkWRnZzNr1izuuOMOrFYrI0eO5JdffmHnzp3HbPeVV17hr3/9K82bN+fxxx9n48aNdKzBs6hqiYkEunXDsWoV4S1bCLdta3QkIUQdVN5zvtvtpqCgoOx+QUEBbrf7uMt4PB5UVcXn8xETE/OHdb1eb9m6p9rm7x3d6igjI4PXXnuNgwcPlg2iXpE0t5u8VauIevPNCt92VdAaNCDUpg229esJnXuuDJguhCiXajkG1apVqxgzZswfxo1q1qwZ119/PV9++eVJ1//xxx9ZtWoVmzZtYtKkSUyaNIn169dXZuSz4nrvPVSPh9JLLjE6iqgKFguFL71EKCODhFtvxZaTY3QiISpdec/n5RmPxOFw0KpVK2y/63JQWFiI3++nRYsWmEwmunfv/odt1kShjAzCDRviWLFCJmUQQhiivOf89PR09uzZQ15eHuFwmJycHDIzM49ZplOnTqxcuRKA1atX07ZtW0wmE5mZmeTk5BAKhcjLy2PPnj00a9bstLb5ewcOHEA/PPB3bm4umqZV6qyzaqNG6E5npW2/sgUuvBAUBccXXxgdRQhRw1XLFlS7du2iTZs2x/1ZmzZtmDFjxknXb9WqFXPmzKmMaBVGycvDsXQpJX/5S7WfSlZUHN3ppOCtt0gcMgT3DTdQMGcOofbtjY4lRKUp7/m8POORnOhK9/G2eaKZXss7tsiR/vtVNh7D4MHwyitELV2KNmrUScdjqO5jLUi+s1eds4HkK4/qnA3Kf843m83ccMMNTJ06FU3T6NmzJ6mpqcyePZv09HQyMzPp1asXM2bMYPz48URHRzNhwgQAUlNT6dq1KxMnTkRRFMaOHYuiRK7FH2+bAIsXL2bBggUcOHCASZMm0bFjR2666SZWr17NZ599htlsxmazMWHChBrRNdEoenQ0gQsuwPHll5i3b0dt2tToSEKIGqpaFqg0TcN5gqsITqcTTdOqOFHFc82Zg0lVKbnqKqOjiCqmJyRQMGsWicOG4bnqKvLnzJHuOKLWqunn8/KOLXKk/36Vjcdgt2O9+GIcS5cSys7Ge5K81X2sBcl39qpzNpB85VFdsx0ZW6QizvkZGRlkZGQc89jIkSPLvrfZbEycOPG46w4dOpShQ4ee1jYB+vfvT//+/f/weL9+/ejXr98ps4rfhDIysG3ahGPlSkoaNwaz2ehIQogaqFoWqFRVZdOmTSf8eXX/QHNKmobr/fcJXHABanq60WmEAbSGDSmYM4fEoUPx/OlPFMydS7hVK6NjCVHhyns+L894JOXZZk0WOvdcLLm52L/8EktuLuHfdbURQojKUuvfw4sTM5spvfhiXB9/jHXDBkKn6EYphBDHUy0LVHFxcbz44osn/HllDFBYlWxff41lxw6KT3D1R9QNauPG5M+dG2lJNXIkBR9+KB8kRa1T3vP50WOHuN1ucnJyuO22245Z5sh4JC1atDhmPJITSUhIwOl08tNPP9G8eXNWrVpVu66Um0yU9u2L6623iL/1VvIXLJCu5EKIKlHb38OLk1PT0gg3bYp99WrCrVujR0UZHUkIUcNUywLVCy+8YHSEMxIzbdoZLe9YtAjdbseydesZrytqF7VpUwrmzMEzfDieESPInzcPNS3N6FhCVJjyns/LMx4JwLhx4/D5fITDYdauXcvkyZNp1KgRN954IzNnziQYDNKhQ4caPYPf8ehRUQQuuQTnJ58QM20axffea3QkIUQdUNPew4uKV9qjB1FvvYX9q68ovfRSo+MIIWqYalmgqtX8fiy5uYTatQOr1eg0ohoIN2tGwezZeK68ksQrryR/7lyjIwlRrZRnPJITfVhKT09nWi2/QBBu3pySa64h+oUXCFx8McGsLKMjCSGEqOX0hASCnTphX7uWYPv2aPXrGx1JGEHXMfn9mHw+UNXfHnY4Ii3rLFKGEMcnr4wqZv3+e0yqGilQCXFYuGXLSJFqxAgSr7wS/2WXoSckGB1LCFHDHXzoIexff03CbbeRt2wZeny80ZGEEELUcsHzz8e6ZQuOFSvwXXUVyAyItZrJ58O2ejXWb7/FumkT9q+/xlRcjOkkY87pDgeqx4OWnIyanIyamooeHV2FqUV1JQWqqqTrWDdtQk1ORqtXz+g0opoJt24d6e43YgSuuXPxXXmlFKmEEOWiu1wUzphB4hVXEP+3v1H40kvyQUEIIUTlstkIXHQRziVLsGzZIrNV10LKvn04FyzAvnw59jVrMAUCAITT0iKfdVu0QI+KitwOt5YyHWlVVVKCqbgYc34+1m+/xXa4hZWanEw4LY1Qq1byGagOkwJVFVL278ecn09p795GRxHV1JEiVeLll+OaMwffiBFyghZClEvovPMonjSJ2Mcfp3TuXPwjRhgdSQghRC0Xbt0a9dtvsX/5ZWQSILvd6EiivIJBnIsX45w7F/uqVZg0jVCLFpRcdx2Bnj0JZmSgR0ef2RjLmoaSn49l+3Ys27Zh+/pr7F9/TbhxY0Lt2xNOTwezufL2SVQ7UqCqQtbNm9HNZkItWhgdRVRj4dat8Q8fjnPePClSCSEqxKGbb8a+ciVxkycTzMhAlRlDhRBCVCaTidKePXG99x721asJXHyx0YnEWTJ5vUS9+y5Rb76Jed8+wo0acejWW/EPG1b+GcgVBS0piWBSEsHzz8dUXIx182as//0vzoUL0eLiCHbpQqhNGylU1RFSoKoqqorlhx8Ip6WB02l0GlHNafXq4b/ySpxz50qRSghRfmYzhc89R73LLsP95z+T/8knkJhYaU9XETPUml0uYny+016++M47y/2cQgghKo6WkkLo3HOxbthAqF07NLfb6EjiDJi8XqJfeomo119H8fsp7d6dA08/TaBHD1CUSnlOPSaG4AUXEOzSBfP27dhXr8axdCm2NWsIdOtGuFUrGaqglqucV5b4A/OOHSh+f6T6K8Rp0BIT8V95JWgarjlzMBUWGh1JCFGDaQ0bUjhzJpbcXOInTgRdNzqSEEKIWi544YVgsWBfuVL+79QQppISYp5+muSuXYmeOZPSfv3I+/xzvO+/T6BXr0orTh1DUVDT0/FdfTW+wYPRHQ6cn36Kc84clLy8yn9+YRgpUFUR6+bNaE4napMmRkcRNYgUqYQQFSl44YUcvO8+nIsWoUyfbnQcIYQQtZzuchHo2hXLjh2Yt283Oo44GV3H+fHHJHXvTsz06QQuvpj9n3/OgRkzIi2XjGAyoaal4bvmGkovuQTF68U1axb2L76AUMiYTKJSSYGqKvj9WLZtI9y6tfSdFWdMilRCiIpUctNN+AcMwHz//diXLjU6jhBCiFou1KEDqtuNY8UKCIeNjiOOw7JpE55hw0gYNw61Xj32f/wxhS+/TLhlS6OjRZhMhNq1o2TMGELt2mH75hui3n0XZfduo5OJCiYFqipg/fHHyCwH0r1PnCUpUgkhKozJxIHp09E7dCDhppuwrl9vdCIhhBC1mdlMoGdPlKIibPI/p1ox+XzE/v3v1LvsMixbt3LgH/8gf9EiQp07Gx3t+BwOAn364Bs+HMJhXLNnY8vOBk0zOpmoIFKgqgLWLVtQExPRkpKMjiJqMClSCSEqih4VRfjjj9GSk3Ffdx3mbduMjiSEEKIWU885h1B6OrY1a1D27jU6jgBMq1ZRr08fol97Dd+oUeR9+SW+a66pET1+1MaNKRk9mnCbNtjXrME5bx7Kvn1GxxIVQApUlUzxejHv3UuobVujo4haoKxIpaq4PvwQU3Gx0ZGEEDVVcjIF774LgGfUKJRffzU4kBBCiNoscPHFoGnETp1qdJQ6zVRSQuzkyVgvuQSA/LlzKXr8cfT4eIOTnSG7ndJLL8V/6aWY9+6lXt++2HJyjE4lykkKVJXMsnkzuslk3MByotbREhPxDx2KqbQU54cfwhlMwy6EEEdT09Lwvv02itdL4rBhmH/5xehIQgghaik9Pp5gZiauf/0L69q1Rsepk6zffEO9Pn2IevNN1FtvZf+yZQSzsoyOVS7htm3xXX01Wnw8nquuwjVrltGRRDlIgaoyaRrW779HbdIEPSrK6DSiFtFSUvAPGoRSVITy/vsQCBgdSQhRQ4U6dqRgzhyU4mIShwzBnJtrdCQhhBC1VLBLF9SUFOL+/ndQVaPj1B2aRvTzz5M4ZAhoGgUffog6bRq6y2V0sgqhJSaS/8knBC68kPi77yb2wQdlQP4aymJ0gNrMvHMnyqFDkeasQlQwNTUV/+WX41ywAOf8+fiHDAGr1ehYQogaKNS+Pflz5+K56ioShw2j8NVXCVbXAVKFEELUXFYrBx94gIRx43DNno3v6quNTlRrxUybBoDp0CEcS5Zg+eUXQi1bUtq7N/avvsK8fj0xtagnhh4bi/ett4h95BGiX30Vy88/UzhzJnpsrNHRxBmQFlSVyLplC7rdTjg93egoopZS09LQr7gC865dOBculCtRQoizFm7ThvwPP0SPjsYzfDiuN98EXTc6lhBCiFrGP2gQgS5diHn8cUxFRUbHqdXM27bheucdzLt34+/bl9L+/cHhMDpW5bFYOPjIIxx48knsX35J4qBBMsZmDSMFqsoSDGLZupVQy5ZgkYZqovLo555LoE8fLNu341iyRD5QCiHOmtqsGfsXLybQvTvx999P/MSJmA4dMjqWEEKI2sRkomjKFJQDB4h55hmj09ROwSD2FStwffwxenQ0JaNGET73XDCZjE5WJXyjRlEwaxbm3btJHDwYiwxfUGNIgaqSWH76CVM4TKhNG6OjiDog1L49gQsvxPrjj9hXrJAilRDirOlxcXjfeoviCRNwzp1LvZ49sX/+udGxhBBC1CLhc8/Fd/XVRL3xBpYffzQ6Tq2i7N5N4vDh2DZsINixI76rrkJ3u42OVeWCF15I/ocfYgoG8QwejHXDBqMjidMgBapKYt2yBS0+Hq1+faOjiDoi2KULwU6dsG3ciO0//zE6jhCiJlMUiidNIv/jj9GjovCMHk38LbfILH9CCCEqTPHf/oYeE0PcPfeAphkdp1awffUV9fr1w/LDD/gHDiTQs2ed7s0TPvfcyHuZmBg8I0ZgX7XK6EjiFKRAVQlMRUVYdu0i1LZtnWlGKaqHQPfuhFq3xp6djfW//zU6jhCihgtlZrL/3/+meOJEnEuWkHTRRcTdfbeM5yCEEKLcNLebor//Hft//oPrnXeMjlOz6TrRL7yA56qr0Nxu8hcvJtyihdGpqgW1aVPyP/4Y9ZxzcI8ejWPRIqMjiZOQAlUlsH7/PQCh1q0NTiLqHJOJ0r59CTdpgn3ZMulvLYQoP7ud4jvvZF92Nr5rrsE1Zw7JWVkk3HQTtuxs6VIshBDirPlHjCBw0UXEPvYYyu7dRsepkUwHD5Jw443EPvYYpQMHkr9oEeFmzYyOVa1oycnkf/ghofPOI+Hmm3HMn290JHECdbe9X2XRdaxbthBOTZUpLYUxzGb8l1+Oa+5cHIsW4R82DLVRI6NTCSFqOK1+fYoee4xD48YR9fLLuObNw/nJJ4TT0vAPGoR/wADCrVpJy2EhRLlt3LiRN954A03T6N27N4MHDz7m56FQiBkzZrBt2zZiYmKYMGECSUlJAHz00UcsX74cRVEYM2YMHTp0OOk2lyxZwqJFi9i3bx+vvvoqsYffv+u6zhtvvMGGDRuw2+3ccsstpKWlVeFRqCNMJg48+ST1evcm/r778L7xhvwfOQOW77/H/ec/Y965k6KHHqLkxhvl+J2AHhdHwaxZuK+7joRbb+VAOIx/2DCjY4nfkQJVBVP27EE5cIDA+ecbHUXUZVYr/iFDcH7wAc758/GNGIFWr57RqYQQtYDasCEHH36Yg/fcg/OTT3DNmUP0c88RM316pFg1YACK14uWlCRvkoUQZ0zTNF577TUmT56Mx+Ph3nvvJTMzk0ZHXWxbvnw5UVFRPP/882RnZzNr1izuuOMOdu3aRU5ODs888wyFhYVMmTKF5557DuCE22zZsiUZGRk8/PDDx+TYsGEDe/fu5Z///Cdbt27l1Vdf5bHHHqvSY1FXqOecQ/GkScQ98giOBQsoHTTI6Eg1gvNf/yLu7rvRY2IomDuXYJcuRkcyVMy0aae1XLBzZ8y//kr8bbfhWLgwMrshYHa5iPH5zug5i++884xzipOTLn4VzLp5M7rFQrh5c6OjiDpOdzrxDxuGbrXi/Ne/MB08aHQkIURt4nTiHzGCgnnz2Ld+PQcefxy1QQOiX3iBqFmziHrlFeyff455xw5QVaPTCiFqiNzcXFJSUkhOTsZisZCVlcXatWuPWWbdunX06NEDgAsuuIBNmzah6zpr164lKysLq9VKUlISKSkp5ObmnnSbTZs2LWt99fvn6N69OyaTiRYtWlBSUkJhYWGl739dVXLjjQQ7diT+vvtQ9u41Ok71FgwSO3kyCePHE2rfnv1LltT54tQZsVrxDx6Mes45OD/7DOt33xmdSBxFWlBVpHAY608/RYpTNpvRaYRAj43FP3QortmzcX34IYduvx2tDk4zK4SoXFq9evhGj8Y3ejSK10vcXXdhyc3Funkztm+/RbfZCDdtSjg9nXDTpmC3Gx1ZCFFNeb1ePB5P2X2Px8PWrVtPuIzZbMblclFcXIzX66X5UReJ3W43Xq+3bDsn2+bxciQmJh6zjtfrJSEh4Zjlli1bxrJlywB44oknjlnnTJhdrrNa72QURcFVCdstL/uJjtHbb2Pq0oWke+8lvGBBhbfCtVgsZ/37qTZ278Zy9dUoX3+NetttmB57DLfVetxFT/Waqq6vjypz1VXo8+bhWLYMm8WCqUuXMz4eJ3wt1wJG/b1IgaoCWX7+GVMgQKhNG6OjCFFGS0zEP3gwznnzcI8eTcHs2ehRUUbHEkLUUprbTbhtW8Jt20IohPmXX7Dk5mLZtg3rjz+iKwpqairhFi0ItWghxSohRI3Wp08f+vTpU3Y/Pz//rLZzpl2LTofL5cJXCdstr+ITHSO3G9fkycTffz++Z5/Fd+21Ffq8iYmJZ/37qQ5sX39Nws03Q0kJ3hdfpPSKK6Co6ITLn+o1VV1fH1Wqf38cixZhXbIETdPwHe7ud7pO+FquBSr676VBgwantZx08atA1i1b0KKjUVNTjY4ixDHUhg3xDxyI9dtvSfjLXyAUMjqSEKIusFpR09MJXHopJX/9K76RIwllZKAUFeFYupTo//s/HJ9+innXLpkNUAgBRFo9FRQUlN0vKCjA/bvW30cvo6oqPp+PmJiYP6zr9Xpxu92ntc3j5Tj6w9nprCPKzzd6NKXduxP78MOYt283Ok71oOtEvfwynpEj0WNiyF+0KFKcEuVnsVA6cCChZs1QPvsM6/r1Rieq86RAVUFMJSWYd+wg1Lo1KHJYRfWjpqdT9I9/4Fi5kviJE0HTjI4khKhLFAW1YUMC3btTMmYMJX/6E6E2bbBs24Zrzhxcs2Zh2bwZwmGjkwohDJSens6ePXvIy8sjHA6Tk5NDZmbmMct06tSJlStXArB69Wratm2LyWQiMzOTnJwcQqEQeXl57Nmzh2bNmp3WNn8vMzOTVatWoes6P/30Ey6X6w/d+0QlUBQOTJsGNhsJt9wCgYDRiQxlKikh4ZZbiHv4YUr79mX/4sWEW7QwOlbtYjZTOmAAeqtWOFaulCKVwaSLXwWx/PADJl2PdGkQdcrpzhhRHfiuugpl/35in3wSzePh4IMPyixbQoiqZzKhNWhAoEEDAhdfjPX777Fu2IDz3/9Gy84m2LkzyGy4QtRJZrOZG264galTp6JpGj179iQ1NZXZs2eTnp5OZmYmvXr1YsaMGYwfP57o6GgmTJgAQGpqKl27dmXixIkoisLYsWNRDl84Pt42ARYvXsyCBQs4cOAAkyZNomPHjtx000107NiR9evXc9ttt2Gz2bjlllsMOyZ1jdagAQeeeQb32LHEPvooB6dMMTqSIcw//4z7z3/GsnUrB++7j0O33CLv2yuL2Yw2ZAjavHk4Vq4EXSfUqZPRqeokKVBVEOuWLagpKTIAtaj2Do0fj5KfT/Qrr6AmJ1Ny881GRxJC1GVWK6H27Qm1a4f5f//DtmYNjhUr0NeuxdqlC6F27cBsNjqlEKIKZWRkkJGRccxjI0eOLPveZrMxceLE4647dOhQhg4delrbBOjfvz/9+/f/w+Mmk4kbb7zxTKOLClLarx+HbryR6FdfJXjBBZQOGGB0pCrlWLKE+NtvR7fZKHjvPYIXXWR0pNrPbKa0f39YvBjHF18ASJHKANIXrQIo+/dj3r9fBkcXNYPJxMGHHsJ/xRXEPfoozjlzjE4khBBgMqE2aYJ/5Eh8V14JbjeO5ctxvfMO5m3bZIwqIYSoYw7efz/BDh2Iv/NOzDt2GB2naoTDxDz+OO6xYwk3a0b+kiVSnKpKh4tUoebNcXzxBdZvvjE6UZ0jBaoKYN28GV1RCLVsaXQUIU6PolD47LMELrqI+Lvuwn54emQhhKgO1NRUtGuvxTdoECZdx/Xxxzg//BBl/36jowkhhKgqNhuFL70EZjPusWMxFRcbnahSKbt34xkxgpgZMyi55hry//Uv1IYNjY5V9xwpUrVoESlSrVtndKI6RQpU5RUOY/nhB8JpaeB0Gp1GiNNnt+N99VVCbduS8Ne/yslXCFG9mEyo6emUjB5NaQt75H0AACAASURBVI8emPftw/Xuu9i/+AKCQaPTCSGEqAJqaireF1/EsnUrCePGgaoaHalS2Jcto17fvlg3baLw+ecp+sc/wG43OlbdZTZTetllkSLVqlXyOakKyRhU5WRfuRLF5yMg3ftEDaRHR+N95x0SBw3Cc9115H/0kcwMIoSoXsxmQhkZhFq3xp6dje2bb7Bs3Uppr16oaWlGpxNCCFHJgt27U/TII8Tffz+xjz3GwQceMDrSGTnphEqqiv2rr7B98w1qvXr4Bg/Gsn17jZqEqdY6MiYV4Fi1KjJweufOBoeq/aQFVTm55s1DczoJN21qdBQhzoqWmEjB+++j22x4rr4a5ddfjY4khBB/5HQS6NMH38iR6BYLro8/xrFoEaaSEqOTCSGEqGS+66+n5PrriX7pJVzvvmt0nAphKirCNXs2tm++IXjeefiuugo9IcHoWOJoihLp7teyJY4vv8S2dq3RiWo9aUFVTqHWrVG8XplhSNRoauPGFLzzDonDh5M4ciT5c+ei1a9vdCwhhPgDtWFDfKNGYVu7Ftt//oP5f/8j0KeP0bGEEEJUsqKHH8b8yy/E3XMPWkwMpYMGGR3p7Og6lu+/x7FiBeg6/oEDpQdDdaYolF52GQD2L78EXSfYpYvBoWqvWtuCaubMmdx4443ceeedlfo8h26/neD551fqcwhRFcLnnkvBO++g7N9P4vDhmKUllRCiurJYCHbtim/UKPS4OJwLFxJ/662YCguNTiaEEKKyWCwUvvwywfPPJ+G222rkJD8mnw/HwoU4lyxB9XgoGTVKilM1weEiVahly0iXzP/8x+hEtVatLVD16NGD++67z+gYQtQooc6dKXj/fRSvF8+wYZh37jQ6khBCnJDm8eD7058IdO2K85NPSOrTB/vy5UbHEkIIUUl0pxPvm28SatsW91/+gn3VKqMjnTbzzz/jevttLNu2EbjoIvwjRqDHxxsdS5wuKVJViVpboGrTpg3R0dFGxxCixgllZFDwwQcoxcWRItWOHUZHEkKIEzObCXbtSv7ChWhxcXiuvZa4u+/GdOiQ0cmEEEJUAj0mhoJ33yWcloZ79GgcCxYYHemkTD4fjk8/xTV/PrrLhe/qqwl27gxKrf0oXnsdKVK1aoX9q6+Ifv55oxPVOjIGlRB1yJnMCOIfOBDnvHnUu/RS/MOGoXk8x12uuJK70QqxceNG3njjDTRNo3fv3gwePPiYn4dCIWbMmMG2bduIiYlhwoQJJCUlAfDRRx+xfPlyFEVhzJgxdOjQAYBx48bhcDhQFAWz2cwTTzxR5fslKlaoXTv2L15MzLRpRL/4IvYvv+TA9OkEL7jA6GhCCCEqmO52k//hh7jHjCHhllsoKijAN2aM0bGOpWm43n+fqDfegFCIwPnnR4aGschH8BpNUSjt1w+A2CeeAF3n0G23GRyq9qjTfx3Lli1j2eG+y0888QSJiYknXd5isRx3GbPLVSn5qpqiKLhqyb78nuzbWWjSBP3aa1Hefx/X7NloI0ZA48Z/WMx+ir+b8jrR311tUJv3raJomsZrr73G5MmT8Xg83HvvvWRmZtKoUaOyZZYvX05UVBTPP/882dnZzJo1izvuuINdu3aRk5PDM888Q2FhIVOmTOG5555DOXzF8sEHHyQ2NtaoXROVweGg+P77CfTtS/ztt+MZPpySv/6Vg5MmgcNhdDohhBAVSI+Lo2DWLBLGjSN+8mQsO3Zw8P77wWYzOhqWH34g7p57sK9dS7hhQwJ9+pzwYq+ogQ4XqUJt2hD75JORItXttxudqlao0wWqPn360OeomX/y8/NPunxiYuJxl4nx+So8mxFcLhe+WrIvvyf7dpZiYjCNHInzX/9CmTWL0ssu+8NAjsWn+LsprxP93dUGNWXfGjRoYNhz5+bmkpKSQnJyMgBZWVmsXbv2mALVunXruPLKKwG44IILeP3119F1nbVr15KVlYXVaiUpKYmUlBRyc3NpIYOR1nrBzp3Zv3QpsVOmEP3SS9hXrODAc88RatfO6GhCCCEqktNJ4csvoz7yCNGvvopt/XoKX3oJtWFDQ+IoeXnETJuG6/330WJjKXzmGSw7d4LJZEgeUYkUhQPPPgtA7D/+8VuRSn7X5VKnC1RCiFPT4+Lw/elPuD7+GMfChQS7dYtMrSonX1EFvF4vnqOuOHo8HrZu3XrCZcxmMy6Xi+LiYrxeL82bNy9bzu124/V6y+5PnToVgEsuueSYixVHO9OWtr93pJWcUS1tT9bCsTJb8FXE/p5p69A/7GtiIrz6KqHhw7HcdBOJAweiTp6MNmlShXSvqM4tIKtzNpB85VGdswlhGIuFg488QrBzZ+Lvuot6ffty4LHHKL3iiip7v2o6cIDo114j6qWXMAWDlFx3HYfuuAPN7T6jITZEDWM2R4pUJhOxTz2FcvAgBx94QD4nlUOtLVA9++yzbNmyheLiYm666SZGjBhBr169jI4lRM3kdOIbPhzHZ59hz85Gycuj9NJLq0UTaiHOxpQpU3C73RQVFfHoo4/SoEED2rRp84flzrSl7e8daSVnVEvbk7VwrMwWfBWxv2faOvSE+5qZiWnpUuLuvx/XQw8RnD+fwmefRW3WrFz5qnMLyOqcDSRfeVTXbEa2tBXiiNLLL2d/27YkjBuH+5ZbCLz3HkVTpxIu5/n+ZJT9+4l65RWi3noL5dAh/P37c/Dee1HT0irtOUU1c7hIpcXGEv1//4dSWMiBp56SscbOUq09ahMmTDA6ghC1i9VKaf/+qElJ2L/6CldhIf6BA41OJWo5t9tNQUFB2f2CggLcbvdxl/F4PKiqis/nIyYm5g/rer3esnWPfI2Li6Nz587k5uYet0Alagc9IYEDM2dSeumlxN93H/UuvZSDkyfju+46mUVJCCFqETUtjfyFC3G98w6xTz5JvT598I0cyaG//CXSsrYi6Dq2NWtwvfsuzkWLIBSidOBAisePJ9y2bcU8h6hZFIWDU6agud3ETpuGqaiIwpkzZfzLsyDvyoQQp89kItS5M/4hQ1AOHSLq3Xdxvfce6LrRyUQtlZ6ezp49e8jLyyMcDpOTk0NmZuYxy3Tq1ImVK1cCsHr1atq2bYvJZCIzM5OcnBxCoRB5eXns2bOHZs2aUVpait/vB6C0tJTvvvuOxseZAEDUPqWDBpH3+ecEs7KInzwZz4gRmLdtMzqWEEKIimQ247v+evK+/BLfyJG45s4l6eKLsQwbhmPJEkxn08pX07CuW0fMY4+RdNFFJA4bhuPzzym55hryVq6k8KWXpDhV15lMHJo4kQNTp+L47DM8o0ZhOnjQ6FQ1Tq1tQSWEqDxqkyaUXHstjiVLiJ80CfuKFRQ9/jiajIshKpjZbOaGG25g6tSpaJpGz549SU1NZfbs2aSnp5OZmUmvXr2YMWMG48ePJzo6uqwFbWpqKl27dmXixIkoisLYsWNRFIWioiKefvppAFRV5cILL6RDhw5G7qaoQlpKCt6338b13nvEPvooSZdcQvHEiZGr61ar0fGEEEJUEC0xkaInn6T4rruIeustot95B/fCheh2O4Fu3QhmZBBu3pxws2Zo8fHoNhvYbJiKijDv34953z4smzdj27AB68aNmL1edIuFYNeuFI8fT+kVV6A7nUbvpqhmfNdfjx4fT/ztt5M4ZAjet982bND+mkgKVEKIs6LHxOAfPhwtKorYJ5/EnpMT6TLzpz/JwICiQmVkZJCRkXHMYyNHjiz73mazMXHixOOuO3ToUIYOHXrMY8nJyTz11FMVH1TUHCYTvmuuobR3b+IeeIDYxx7DOX8+B55+mlD79kanE0IIUYG0evUovusu7FOmcHDxYhxLl+L4/HMcy5efcl3dZCLcogWBPn0IdO9Oaa9e6HFxVZBa1GT+wYNRPR7cf/4ziZdfjvfNN+X9xWmSApUQ4uyZTJTcfDOBPn2I+9vfiL/rLpxz53LwoYfkJCyEqPa0lBQKX3kF/+LFxE2eTOKAAfhGjeLgpEnovxvrTAghRA1ntUZmo+7WjYMPPYTJ78f8889Yc3MxHTyIKRiEUAg9JgY1KQktKYlws2bo0dFGJxc1UPCii8ifPx/3tdfiGTqUwpkzCfTta3Ssak8KVEKIcgs3b07BvHm4Zs8mZupU6l12Gb5Bgyi++27UJk3OeHtHT8drdrkqZEaw4jvvLPc2hBC1U2n//gS6dSNm2jSi3nwT54IFHLz7bnyjRoHZbHQ8IYQQlUB3Ogmfey7hc881OoqopcItW5K/cCHu66/HPXYsBx9+mJIxY6S3yUlIgUoIUTEUBd9VV+EfMIDoF18k6uWXcS5ahH/wYA7ddBPh1q2NTiiEqMWOLmyfLT0uDt8112BfsYL4++4jZvp0AhdfjHqcQfSPFM+l+C2EEEKIE9GSkiiYN4/4W28l7oEHsGzZQtHUqWC3Gx2tWpJZ/IQQFUqPjaX4b38jLzubkuuuw7FoEUl9+uAeNQrHv/8NoZDREYUQ4oS0xET8w4fjHzgQUyCAa948nHPnouzebXQ0IYQQQtRAustF4auvUnz77US9/z6Jw4ej7N1rdKxqSQpUQohKoaWkcPCRR9i3di0H774b6+bNuG+4geQuXYiZOhXrd9+BrhsdUwgh/ujwoLgl119PaY8eKAUFRH3wAc6PPkLZt8/odEIIIYSoaRSF4rvvxvvyy1h++IF6l12Gdd06o1NVO9LFTwhRqfSEBA7dfjuHxo3Dvnw5rvffJ/r//o+YmTMJN2pEab9+lPbvTzAzU8Z6EUJULxYLoYwMQu3aYduwAdvatUTNmkW4cWPIyoL69Y1OKESttHHjRt544w00TaN3794MHjz4mJ+HQiFmzJjBtm3biImJYcKECSQlJQHw0UcfsXz5chRFYcyYMXTo0OGk28zLy+PZZ5+luLiYtLQ0xo8fj8ViYeXKlbzzzju4D0+Y0K9fP3r37l2FR0FUNPOUKRUyrqkQ5VE6YAD56em4x44lcfhwih56CN9118m4VIdJgUoIUTUsFgJ9+xLo2xeT14tj6VKcn35K1DvvEP3qq2jx8QS6diVw4YUoXi9aQoKcqIUQ1YPVSrBLF4Lt22P77jusGzagfPABLrcbNTkZ/7Bh6C6X0SmFqBU0TeO1115j8uTJeDwe7r33XjIzM2nUqFHZMsuXLycqKornn3+e7OxsZs2axR133MGuXbvIycnhmWeeobCwkClTpvDcc88BnHCb7777LgMGDKBbt268/PLLLF++nL6HZ9rKyspi7NixhhwHIUTtFW7Viv2LFpEwfjzx99+PPTubA08/jR4XZ3Q0w0mBSghR5XS3G//IkfhHjsR06BD2FSuwf/EF9q++wvnppwBoUVGojRtjatYMU1KSnLCFOAsnGzi8ombIrFMcjkihqlMnonbsgNWrib/nHmIffRT/5ZfjHzGCYOfOVVJcN+p3K4PCi8qWm5tLSkoKycnJQKRItHbt2mMKVOvWrePKK68E4IILLuD1119H13XWrl1LVlYWVquVpKQkUlJSyM3NBTjuNhs2bMjmzZu5/fbbAejRowdz584tK1AJIURl0ePj8b71FlEvv0zs449T79JLKZw5k1BGhtHRDCUFKiGEofToaEovv5zSyy8HwPy//xH3979j3rkT844dKN9/TzSgxcaipqYSTk1FTU1Fj4kxNrgQou4ym9HbtcOXlkage3dcH3yAc/58ot5/n3DDhpRedpl0XRbiLHm9XjweT9l9j8fD1q1bT7iM2WzG5XJRXFyM1+ulefPmZcu53W68Xm/Zdn6/zeLiYlwuF+bDf6dHLw+wZs0avv/+e+rXr891111HYmLiH/IuW7aMZcuWAfDEE08cd5nTYa6EVpiKouCqhq077Wd5jMqruh4Po8jxONbZHI8KeS1Pnky4b18so0aROGQI6iOPoN1xByjGDhdusVjO+nxWruet8mcUQoiTUM85h1D79oTatwddx1VSQmjrVsw7d2L5+WesmzcDoMXFlRWr1MaN0aOiDE4uhKhzTKZIi6ouXTBNmYJj0SKcixYR9fbbka7LcXEEunUjcOGFBM8/n3Dz5lKwEqKG6NSpE926dcNqtbJ06VJeeOEFHnzwwT8s16dPH/r06VN2Pz8//6yerzJaPbpcLnzVsKVs8Vkeo/JK1rRqeTyMUl1fH0Y5m+NRYa/ltDRMixcTP2kSzvvuI/DJJxyYPh01NbVitn8WEhMTz/p8djwNGjQ4reWkQCWEqL5MJkhKIhQdTahjR9B1lPz8SOuqnTuxbt2KbdMmANTkZMJNmxJOS0NLTpbxq4QQVUqPisI/YgT+ESMiXZeXL8e+ahX2VatwLl4MgOZyETrvPEKtWxNOS0NNT498bdDA8CulQlQXbrebgoKCsvsFBQVlA5X/fhmPx4Oqqvh8PmJiYv6wrtfrLVv3eNuMiYnB5/Ohqipms/mY5WOOaqndu3dv3n333UrZXyGEgEiXv8KXX6Z0zhzi/v536vXuzcGHH8b3pz/Vqc81UqASQtQcJhNavXpo9epF+mdrGsr+/Vh27MCyfTu2NWuwr16N5nKhNmlCOD2dcJMmYLUanVwIUYfo0dGUXnEFpVdcAbqOeccObOvXY92wAdvGjbhmz0YpKflteasVzeNB83hQExPRPB706Gh0uz1yczgi5zFdB00DXcf29deR+7p+eCOR7026jsliwR4M/vbzI8soCrrZDBYLWCzoFgu6w/HbzemMtEa12Qw4akJEpKens2fPHvLy8nC73eTk5HDbbbcds0ynTp1YuXIlLVq0YPXq1bRt2xaTyURmZib//Oc/GThwIIWFhezZs4dmzZqh6/pxt2kymWjbti2rV6+mW7durFy5kszMTAAKCwtJSEgAImNeHT0GlhBCVAqTCf/IkQS7dSN+wgTi77oLx6efcuAf/0BLSTE6XZWQApUQouZSFLTkZILJyQTPPx+T3495xw4s27ZFugNu2YJutRJOSyPUsiWB3r3RnU6jUwsh6hKTCbVpU/xNm+IfNizymK6j5OVh+flnLNu2Yf7lF8z5+SgFBSgFBVi2b8dUUoIpEIjcQqETbl4//By/v1mPfA/oh783aRqEw5hU9aSRdYcDLSYGLTYWPSYGze2O3DyeSLGrDl3JFVXPbDZzww03MHXqVDRNo2fPnqSmpjJ79mzS09PJzMykV69ezJgxg/HjxxMdHc2ECRMASE1NpWvXrkycOBFFURg7dizK4daJx9smwDXXXMOzzz7LBx98QNOmTenVqxcAn376KevWrcNsNhMdHc0tt9xizAGphU42yUOlkvGWRA2hNmpEwZw5RL3+OrGPP05Sz54cvO8+fNdcU+tbXJt0/chlNbF79+6T/vxE/TANO8lWsNrcD1n2rfJUxoxOR/9NnfX+aRrmXbuw/PQTltxcFJ8Pzekk0KsX/ssvJ9Cnj+HFqoru211ZTrfPeF1wqv8Tv3fkd1wd/08Yfe44lZqSr0pmtQuHIRSKvClVFDCZiHn22cjPjlMsOuWx03VQ1Ujhq7QUU2kpJr8fU2kpyqFDmIqLUYqLMR08iFJUdEyBTIuLI9SmDaF27Qi1b0+wXTvUtLQzesNc3c991Tlfdc0m/yd+c6b/J46ojP8T1f08WtXkeBxLjsexzmoMqip4D2Deto34e+7Bnp1NoEsXiv7xj8iYlpVMxqASQoiKpCiojRujNm5MoFcvAt264Vy4EMfixTgXLUJzuSi99FL8V1xB4OKLwW43OrEQQhzf4S55xyhPKyaTqayLH04nJ71SqeuYDh1C8XpRCgpQGzXCunkzUW+/jam0FAAtOprQuecS6tCBYMeOBDMy0KRgIYQQQpSbmpZGwezZOOfMIe6RR6jXty+Hxo2jeNw4qIU9Q6RAJYSo/RSFYFYWwawsiqZMwbZmDc7583EsWoTro4/Q4uLwX3YZpYMGEcjK+uMHQSGEqKtMJvSYGNSYGNRzzvntanEohGXrVqz//S+2b7/F+t13RL3+OtHBIABqSgrBjh0JHS5Yhdq3l9lWhRBCiLNxeGyqQO/exD74IDHTp+OcO5eDDzxA6YABtarrvXwKE0KUS3XsunRSZvNvxapHH8X+1Vc458+PTA3/wQeoHg+lAwbgHzSIYJcutb6ftxBCnBWrlXCbNoTbtME/cmTksUAA65Yt2DZsiAwIv349zk8/BUBXFMItWxLMyEDp3h1L8+aRLgpyjhVCCFFDGfE5SE1LI3/uXOL+/nfcf/0rgawsih55hHDr1lWepTJIgUoIUXdZrQR69iTQsyeUluJYuTJSrJozh6i330ZNScF/+eX4Bw0i1KFDrbo6IYQQZ+N034yrTZrgb9IEk9+PsmcP5r17Me/Zg2vePEyzZpEE6DYbakpK5Fa/PlpKyglbWVXJWF9CCCFEDRDMymL/kiW43n2X2Keeot6ll1IyejTFd96Jfnj20ZpKClRCCAHgcFDarx+l/fphKinBvmwZzvnziXrrLaJfeYVw48b4r7gC/6BBkSsUUqwSQohT0p1O1LS0yEDqALqOq7SU4PbtmPfswbxnD7Z16yIzDAJabCxq/fqoycloHg+a240eG2vgHgghhBDVy9EXi0quugp7Tg5Rb75J1HvvETj//MiF9XIOWWJ2uYj53aDxVXGxSApUQgjxO3pUFKWDBlE6aBCmoiIcS5bgXLCA6BdfJGbGDELNm+MfNAj/5ZejNmtmdFwhhKg5TCbweAg7nYTbtIk8FgphzstDOdzKyrx7N9YffyxbRbdYcHz2GaFmzVDT0wk3aoR65NagAVitBu2MEEIIYTCnk0Dv3oTat8e+ahWOVauwbdhAICsrclG9hnWllwKVEEKchB4Xh3/kSPwjR6IUFOBYtAjnggXETJtG7NNPEzz3XEqPFKtSU42OK4SoYjVuHL7qyGpFbdgQtWFDQocfMvn9ZTMHKl4vWlwctvXrscyff8yquqKgJSdH1q9XD61evcjXxES0pCTUw1+1evXQz2K2IyN+v9KdUQghxJnS6tXDP2wY5l9+wf7llzj//W/UdesIXHQRatOmNab3hxSohBDiNGkeD77Ro/GNHo2yZw/OhQtxzp9P7NSpxE6dSjAjI9KyauBAtJQUo+MKIUSNpTudZUUrOKpoEwhg3r0b865dWHbtwnzktns3lp9/Rlm9GnNh4XG3qUVHRwpYSUmR4tWRr/XqRYpch7/idlfVbgohhBAVSm3cGN/VV2PZuhX7V1/h+vhjwg0bEuzaNXIxvZoXqqRAJYQQZ0GrX5+SP/+Zkj//GfMvv+BcsADn/PnEPfggsQ89RPCCC/APGkTpZZehJSYaHVcIIWoHux21aVPUpk0JnmiZUAglPx9zfj5KXl7k+7w8lP37y75aN23Cvn8/yqFDf1hdN5tJatAAtXFjTEVF6PHxaHFxkVtCAtjtlbqLQgghRLmYTIRbtCCcno510yZsq1fjmjfvt0JV48ZGJzwhKVAJIeqEquimUdqvH8HOnbH8+COWH34g/uuv0e+5B61+fcLp6YTT0tA8nrIrF8cbfBCke4cQQpSL1YpWvz5a/fqnXNTk86Hk5WHevx9l3z6U/fuJKS4muHUrlv/9D8u2bSi/O09rMTGRAdwTEyNdCD2eyLm9nAPSCiGEEBXKbCZ03nmE2rbF+t//YvvPfyKFqkaNfmtRVc3If1IhhKhAmsdDMCuLYNeuKPv3Y/n5ZyzbtmH/6ivsX32FFhtLOC2NcHo6tGhhdFwhhKjTdJcLtUkT1CZNyh5zJSZyID8fOHxxIxRCKSpCOXDgt3Gx8vOx7tyJTVUj21GUSPfBlBTUlBS0lBQ0t7vad6UQQghRB1gshDp2JNSu3W+FqrlzIy2qOneuVmNUSYFKCCEqg8mElpREMCmJYNeumA4dwrJtG5Zt2yL/GDZuRLfZcJxzDuH0dNSmTc9qAF8hhKgLqnKw8j+0brVaI4Ou/767tqZhOnAg0pVw3z7Me/di/f57bN9+C4Bus6HWr//bjIPJydLKSgghhHGOLlR99x22detwffwxamIiwcxMwi1bgtlsbERDn10IIeoIPTqaUPv2hNq3j0yp/ssvOH75BfNPP2HduhUd0FJSCDdpQtyePZGBeitwWljpNiiEEBVMUdDdbsJu928tYnU90spq717Me/di3rULe3Z25Edm87EFq/r1wWo1cAeEEELUSRYLoYwMQuedh+WHH7CtW4dzyRK07GyCnToRatfOuGiGPbMQQtRVVitqejp6u3b4evRA2bcv0rpqxw5sq1djX70a3eEgfM45hJs2RT3nHPSoKKNTCyGEOBWTqWxMqnDbtpHH/H4sv/4amW3w11+xrVmDafVqdEWJFKxSUyO3+vWlhZUQQoiqYzYTbtuWcJs2mLdtw7Z2LY6VK7F//TV6x46Y2rZFj4ur0kjyX1AIIYxkMqGlpBBMSSGYlRX5IPO//2HZsQPzjh1Yf/wRADUpifDhcVLU+vUNb34rhBDiNDmdhJs1I9ysWeR+IIB5927MO3di2bnzt4KV2YzasCG61UogK4vQeedJCyshhBCVz2RCTU/Hn56O+ddfsa5fj2XNGqJWryacnk6oY8cqG1BdClRCCFGdOJ2EW7Ui3KpVpKvI/v2RYtX27djWrsX0n/+g22yEGzdGbdqUcJMm6DExRqcWQghxuux21KZNUZs2JQhQWor511+x7NyJeedOYp98EgAtKorg+ecT6NaNYFYWoSMtsoQQQohKojZsiNqwIa5QiPCaNVj/+1+sP/+M6najJibiu/pqsNkq7fmlQCWEENXVUQOt06ULBAJYfvkF8/btWHbswJqbC4Dq8aA2aRJpYdWwoXQREUKImsThQE1PR01PB6BkzBhsX3+NPTsbW3Y2ccuXA6DFxUH37kR17kwgKysymG0FjlUohBBClImLI3jhhQQvuADLjz9i27iR6FdewTd6dKU+rXyKEUKImsJuJ9y8OeHmzQnoOkpBwk7G/wAAH65JREFUAeYdOyLFqo0bsX3zDbrFgtqoUVl3QC0hodpMGyuEEOLUNLeb0gEDKB0wAABl3z7sOTnYcnJwff01cZ98AkQuTgS7diXQrRuBrKxIgUvO90IIISqSxVI2TlXJ9ddX+oURKVAJIURNZDKVTXseysyEYBDzrl1YDhesHCtXAqDFxBBu0oRQq1YEevZEd7mMzS2EEOKMaMnJ+IcMwT9kCNbERAo3bsSWnY09Jwd7djbOhQsBUFNSCGRllXUJVBs3Nji5EEKIWuPwZ4/KJgUqIYSoDWw21LQ01LQ0AoCpqOiYgdbdf/kL+1atKutCIoQQomZSGzXCP3Ik/pEjQdcx79iBPTs7clu1Cte//gVAuGFDQh07EuzYkVDHjoTatZOLFEIIIao1KVAJIUQtpMfFETrvvMgsUKpKaa9eqGlpRscSQghxCjHTpp3wZ2aXixif77g/CzdrRjg9PdL9e+dOzL/+in3VqrIWVrrJhObxoKakoNWvj5qUhObxlI1bWHznnRW/M0IIIcQZkAKVEELUdmZzpBugEEKI2u3o7t8dO0Ye8vlQ9u7FfPhmzc3FtGkTALqioCUkoCUloUVF4Rs9WlpZCSGEMIwUqIQQQgghhKildJerrAt45AEd04EDmPfvR9m/H3NeHuadO4l98klKbrjB2LBCCCHqNClQCSGEEEIIUVeYTOgJCYQTEqBFi7KHD914I9hsBgYTQghR19XaAtXGjRt544030DSN3r17M3jwYKMjCSGEOAunOp+HQiFmzJjBtm3biImJYcKECSQlJQHw0UcfsXz5chRFYcyYMXTo0OG0timEEHWNHhdndIQyVXnez8vL49lnn6W4uJi0tDTGjx+PxWI56XMIIYSoHIrRASqDpmm89tpr3HfffUyfPp3s7Gx2/X979x4XVZ0/fvw1F1ARRO6IpoaiqT3UEpO8LYa1XawtH1tZu5q5RQlmVqZmN/fRTc3biri4eQPXWvVRaFmru17QRbQQxRDMQLwGiTBoXBxhZj6/P/wxX0ZFUC5nwPfzr5lzzpzz/nzOZz6fM5/5fM45c0brsIQQQtygutTnO3bsoG3btsTExPDII4+wdu1aAM6cOUNKSgoLFizg7bffZsWKFdhsNmkjhBDCiTV1vf/Pf/6TRx55hJiYGNq2bcuOHTuuewwhhBCNp0V2UOXk5BAYGEhAQABGo5HBgweTmpqqdVhCCCFuUF3q8/379xMeHg5AWFgYhw8fRilFamoqgwcPxsXFBX9/fwIDA8nJyZE2QgghnFhT1vtKKTIzMwkLCwMgPDzcfqyajiGEEKLxtMgpfiaTCR8fH/t7Hx8fsrOzr9pu27ZtbNu2DYDZs2cTFBRU676vuc11Hgfc3HhoHUAjkrQ1Xy05fU2Vtuaah3Wpz6tvYzAYcHNzo6SkBJPJREhIiH07b29vTCaTfT/X22eVm2knrhQUFOS07YSzlwuJ7+Y5c2wg8dVHY8XmLGluynq/pKQENzc3DAbDVdvXdIx27do5xNIQ7QTQaO2Es5xXZyH54Ujyw5Hkh6Mr86Mp8qdFjqCqq5EjRzJ79mxmz55dp+1nzJjRyBFpqyWnT9LWfLXk9LXktLUUN9pOXMmZz7EzxwYSX304c2wg8dWHM8d2q6pvO9GYpLw4kvxwJPnhSPLDkVb50SI7qLy9vSkqKrK/LyoqwtvbW8OIhBBC3Iy61OfVt7FarZSXl+Ph4XHVZ00mE97e3tJGCCGEE2vKet/Dw4Py8nKsVqvD9tc7hhBCiMbTIjuounXrRn5+PgUFBVgsFlJSUggNDdU6LCGEEDeoLvX5gAEDSEpKAmDfvn306dMHnU5HaGgoKSkpVFZWUlBQQH5+Pt27d5c2QgghnFhT1vs6nY4+ffqwb98+AJKSkuzHqukYQgghGo9h1qxZs7QOoqHp9XoCAwOJiYlhy5YtDBs2zH7zw/oKDg5ukP04q5acPklb89WS09eS09YQaqrP161bh9lsJigoiM6dO5OcnMznn3/OiRMniIyMxN3dHU9PT0pLS1m2bBnJyclMmDCBoKCgRm0jrsWZz7EzxwYSX304c2wg8dWHM8fWEJq63g8ODiYhIYFNmzbRtm1bxowZg8FgqPEYzU1LLy83SvLDkeSHI8kPR1rkh07J4yiEEEIIIYQQQgghhIZa5BQ/IYQQQgghhBBCCNF8SAeVEEIIIYQQQgghhNCUUesAnFF6ejqrVq3CZrMRERHB448/7rA+KyuL+Ph4Tp48yZQpUxr13iUNrba0bd68me3bt2MwGGjXrh0TJ07Ez89Po2hvXG3p+89//sPWrVvR6/W0bt2al156iU6dOmkU7Y2pLW1V9u3bx4IFC/jkk0/o1q1bE0d5c2pLW1JSEmvWrLE/WefBBx8kIiJCi1BvWF3OW0pKChs2bECn09GlSxdeffVVDSIV9VFYWEhsbCznz59Hp9MxcuRIHn74YdavX8/27dtp164dAM888wx33323JjFGR0fTunVr9Ho9BoOB2bNnU1paysKFCzl37hx+fn689tprTX6Plby8PBYuXGh/X1BQwFNPPUVZWZlmebd06VIOHDiAp6cn8+fPB6gxr5RSrFq1ioMHD9KqVSuioqIa/Z4N14pvzZo1pKWlYTQaCQgIICoqirZt21JQUMBrr71GUFAQACEhIURGRjZ5fNf7LiQmJrJjxw70ej3PP/88/fv3b9LYFi5cSF5eHgDl5eW4ubnx6aefapJ3NdUlzlT+hHYasnwkJSXx1VdfATB69GjCw8M1TFn92Gw2ZsyYgbe3NzNmzKCgoIBFixZRUlJCcHAwr7zyCkajkcrKSpYsWUJubi4eHh5MmTIFf39/oGnrocZUVlZGXFwcp0+fRqfTMXHiRIKCgm7Z8rF582Z27NiBTqfjtttuIyoqivPnz98y5aOhrmdqKg+5ubnExsZSUVHBXXfdxfPPP1//h0ko4cBqtapJkyapX3/9VVVWVqqpU6eq06dPO2xz9uxZdeLECRUTE6P27t2rUaQ3ri5py8jIUGazWSml1NatW9WCBQu0CPWm1CV9ZWVl9tepqanqww8/bOowb0pd0qaUUuXl5eq9995TM2fOVDk5ORpEeuPqkradO3eq5cuXaxThzatL2vLy8tSbb76pSkpKlFJKnT9/XotQRT2ZTCZ17NgxpdTl7+HkyZPV6dOn1bp169SmTZs0ju6yqKgodeHCBYdla9asUYmJiUoppRITE9WaNWu0CM3OarWqF154QRUUFGiad5mZmerYsWPq9ddfty+rKa/S0tLURx99pGw2mzp69Kh66623NIkvPT1dWSwWe6xV8Z09e9Zhu6ZwrfhqOp+nT59WU6dOVRUVFers2bNq0qRJymq1Nmls1cXHx6sNGzYopbTJu5rqEmcqf0I7DVU+SkpKVHR0tCopKXF43Vx98803atGiReqTTz5RSik1f/58lZycrJRSatmyZWrr1q1KKaW2bNmili1bppRSKjk52f47p6nrocYUExOjtm3bppRSqrKyUpWWlt6y5aOoqEhFRUWpS5cuKaUul4udO3feUuWjIa5nrlceZsyYoY4ePapsNpv66KOP1IEDB+ods0zxu0JOTg6BgYEEBARgNBoZPHgwqampDtv4+/vTpUuXZveo2bqk7c4776RVq1bA5X8KTSaTFqHelLqkz83Nzf7abDY3m3NYl7QBrFu3jj/84Q+4uLhoEOXNqWvamqO6pG379u38/ve/t49a8fT01CJUUU9eXl72f5natGlDx44dm0X9mZqayu9+9zsAfve732n+3cvIyCAwMFDzkbu9e/e+aiRZTXm1f/9+hg8fjk6no0ePHpSVlVFcXNzk8fXr1w+DwQBAjx49NC1/14qvJqmpqQwePBgXFxf8/f0JDAwkJydHk9iUUuzdu5chQ4Y02vFrU1Nd4kzlT2inocpHeno6ffv2xd3dHXd3d/r27Ut6erpm6aqPoqIiDhw4YB9Zr5QiMzPTPsMlPDzcIT+qRn6EhYVx+PBhlFJNXg81lvLyco4cOcJ9990HgNFopG3btrd0+bDZbFRUVGC1WqmoqKB9+/a3VPloiOuZmspDcXExFy9epEePHuh0OoYPH94g15Eyxe8KJpMJHx8f+3sfHx+ys7M1jKjh3GjaduzY0WyGL0Ld07dlyxa+/fZbLBYL7733XlOGeNPqkrbc3FwKCwu5++67+frrr5s6xJtW1/P2/fffc+TIETp06MBzzz2Hr69vU4Z5U+qStqppJe+++y42m40nn3yyWX3vxNUKCgo4fvw43bt356effmLr1q3s3r2b4OBgxo0bp+ljyj/66CMA7r//fkaOHMmFCxfw8vICoH379ly4cEGz2AD27Nnj0DngTHlXU16ZTCaH+sjHxweTyWTfVgs7duxg8ODB9vcFBQVMmzaNNm3aMGbMGHr16qVJXNc6nyaTiZCQEPs23t7emnWuHTlyBE9PTzp06GBfpmXeVa9LmlP5E02jPuXjyusTLb939bV69Wr+/Oc/c/HiRQBKSkpwc3Ozd9hXT1v1dBsMBtzc3CgpKXGqeqg+CgoKaNeuHUuXLuXkyZMEBwczfvz4W7Z8eHt78+ijjzJx4kRcXV3p168fwcHBt2z5qNJQ5eFav3MaIl9kBJW4pt27d5Obm8tjjz2mdSgN7sEHHyQmJoY//elPfPnll1qH0yBsNhsJCQmMGzdO61AaxYABA4iNjWXevHn07duX2NhYrUNqMDabjfz8fN5//31effVVli1bRllZmdZhiZtkNpuZP38+48ePx83NjQceeICYmBjmzp2Ll5cXCQkJmsX2wQcfMGfOHGbOnMnWrVvJyspyWK/T6TQdVWqxWEhLS7P/q+lMeXclrfPqer766isMBgPDhg0DLo+4WLp0KXPnzuW5555j8eLFlJeXN3lcznw+q1zZQapl3l1Zl1TnzOVPNA0pH5elpaXh6ekp9137/6xWK8ePH+eBBx5g7ty5tGrVio0bNzpscyuVj9LSUlJTU4mNjWXZsmWYzeZmOxKssThjeZAOqit4e3tTVFRkf19UVGS/MXNzV9e0/fjjjyQmJjJt2rRmNVXsRs9dc5pKVlvazGYzp0+f5q9//SvR0dFkZ2czd+5cjh07pkW4N6Qu583Dw8NeFiMiIsjNzW3SGG9WXdLm7e1NaGgoRqMRf39/OnToQH5+flOHKhqAxWJh/vz5DBs2jEGDBgGX/5nS6/Xo9XoiIiI0/U5WlT1PT08GDhxITk4Onp6e9ulAxcXF9htYa+HgwYPcfvvttG/fHnCuvANqzCtvb28KCwvt22l53ZCUlERaWhqTJ0+2X3C6uLjg4eEBQHBwMAEBAZrUMTWdzyvrSZPJpEn+Wa1WfvjhB4eRZ1rl3bXqkuZQ/kTTaIjy4Szfu/o6evQo+/fvJzo6mkWLFnH48GFWr15NeXk5VqsVcExb9XRbrVbKy8vx8PBoMfnh4+ODj4+PfbRPWFgYx48fv2XLR0ZGBv7+/rRr1w6j0cigQYM4evToLVs+qjRUeWisfhPpoLpCt27dyM/Pp6CgAIvFQkpKCqGhoVqH1SDqkrbjx4/z2WefMW3atGZ3L5y6pK/6heWBAwcchvE7s9rS5ubmxooVK4iNjSU2NpaQkBCmTZvWLJ7iV5fzVv1+Gvv37282T16sS9ruueceMjMzAfjtt9/Iz88nICBAi3BFPSiliIuLo2PHjowaNcq+vHrZ/eGHH7jtttu0CA+z2Wyf/mA2m/nxxx/p3LkzoaGh7Nq1C4Bdu3YxcOBATeKDq0evOEveVakpr0JDQ9m9ezdKKX7++Wfc3Nw0mV6Vnp7Opk2bmD59uv1eknC5XrHZbACcPXtWszqmpvMZGhpKSkoKlZWVFBQUkJ+fT/fu3Zs8voyMDIKCghymK2iRdzXVJc5e/kTTaKjy0b9/fw4dOkRpaSmlpaUcOnSoWd5e4NlnnyUuLo7Y2FimTJnCnXfeyeTJk+nTpw/79u0DLnfcV117DRgwgKSkJODyU6/79OmDTqdzmnqovtq3b4+Pj4/99hEZGRl06tTpli0fvr6+ZGdnc+nSJZRS9vy4VctHlYYqD15eXrRp04aff/4ZpRS7d+9ukH4TnVJK1XsvLcyBAweIj4/HZrMxYsQIRo8ezbp16+jWrRuhoaHk5OQwb948ysrKcHFxoX379ixYsEDrsOuktrR98MEHnDp1yv4Ptq+vL9OnT9c46rqrLX2rVq0iIyMDg8GAu7s7EyZM0PxHT13VlrbqZs2axdixY5tFBxXUnrbPP/+c/fv328/bCy+8QMeOHbUOu05qS5tSioSEBNLT09Hr9YwePVrTG/SKm/PTTz/x3nvv0blzZ/vIlWeeeYY9e/Zw4sQJdDodfn5+REZGavLj8ezZs8ybNw+4/K/g0KFDGT16NCUlJSxcuJDCwkKHRw03NbPZTFRUFEuWLLFPV4mJidEs7xYtWkRWVhYlJSV4enry1FNPMXDgwGvmlVKKFStWcOjQIVxdXYmKimr0uvda8SUmJmKxWOznLyQkhMjISPbt28f69esxGAzo9XqefPLJRv/j7VrxZWZm1ng+v/rqK3bu3Iler2f8+PHcddddTRrbfffdZ/9z54EHHrBvq0Xe1VSXhISEOE35E9ppyPKxY8cOEhMTgcuPjR8xYoRm6WoImZmZfPPNN8yYMYOzZ8+yaNEiSktLuf3223nllVdwcXGhoqKCJUuWcPz4cdzd3ZkyZYq907kp66HGdOLECeLi4rBYLPj7+xMVFYVS6pYtH+vXryclJQWDwUDXrl15+eWXMZlMt0z5aKjrmZrKw7Fjx1i6dCkVFRX079+fCRMm1HvKoHRQCSGEEEIIIYQQQghNyRQ/IYQQQgghhBBCCKEp6aASQgghhBBCCCGEEJqSDiohhBBCCCGEEEIIoSnpoBJCCCGEEEIIIYQQmpIOKiGEEEIIIYQQQgihKemgEqIFKywsZOzYsdhsNq1DEUIIoZHXX3+dzMxMrcMQQgjRAkibIhqTTimltA5CCCGEEEIIIYQQQty6ZASVEE5EKdVgo52sVmuD7EcIIUTDa4qRrdIOCCGEaKi2QNoU0RSMWgcghLPZuHEj//73v7l48SJeXl688MIL7N69Gx8fH8aMGQNAZmYmMTExxMXFAZCbm0tcXBy//vor/fv3R6fT0aFDB8aMGUNpaSlLliwhOzsbm81Gz549efHFF/Hx8QFg1qxZ9OzZk6ysLHJzc5k/fz6BgYHXjG3WrFn06NGDjIwM8vLy6NOnD1FRUbi7u1NQUMCkSZN4+eWX2bBhA/7+/kRHRzNp0iS++OILDAYDpaWlJCQkcOjQISoqKujVqxfTpk0DIC0tjX/961+cO3eOTp068eKLL9KlS5cmyHEhhGg5zpw5w/Llyzlx4gTe3t48++yzhIaGEhsbi6urK4WFhWRlZfHmm2/SqVMnVq5cyZEjR2jdujWPPPIIDz/88HX3v379ek6fPo1er+fgwYN06NCBiRMn0rVrVwCio6O5//77SU5OJi8vjzVr1jB58mReeukl+vbti81mY+PGjezcuZMLFy7QoUMH3nzzTXx9ffnll19YuXIlubm5tGvXjqeffprBgwc3Qa4JIUTzVlhYyOrVqzly5AhKKYYMGcLzzz9PYmIi27dvp6Kigv79+zNhwgTc3Nzs1+2RkZFs2LABpRSjRo3iscceA2qv600mU43tR9VnXVxcSEtLY9y4cURERFwzbmlThLOREVRCVJOXl8fWrVv55JNPSEhI4O2338bPz++6n7FYLMybN4/w8HBWrlzJkCFD+OGHH+zrlVKEh4ezdOlSli5diqurKytWrHDYx+7du4mMjCQhIQFfX9/rHm/Xrl1MnDiRZcuWodfrWblypcP6rKwsFi5cyNtvv33VZ2NiYrh06RLz58/ns88+Y9SoUQAcP36cv//970RGRrJy5UpGjhzJ3LlzqaysvG4sQggh/o/FYmHOnDn07duX5cuXM2HCBBYvXkxeXh4AycnJPPHEE8THx9OzZ0/mzJlD165dWbZsGe+99x7fffcd6enptR5n//793HvvvfY259NPP8VisdjX79mzhxkzZrB69WoMBoPDZzdv3syePXt46623iI+PZ+LEibRq1Qqz2cyHH37I0KFDWb58OVOmTGHFihWcOXOmYTNJCCFaGJvNxpw5c/D19SU2Npa4uDiGDBlCUlISSUlJvP/++yxZsgSz2XzVb4DDhw/zt7/9jXfeeYdNmzbx448/2tfVVNdXHe967cf+/fsJCwtj1apVDBs27LrxS5sinIl0UAlRjV6vp7KykjNnzmCxWPD3969xNFOVn3/+GavVykMPPYTRaGTQoEF0797dvt7Dw4OwsDBatWpFmzZtGD16NEeOHHHYR3h4OLfddhsGgwGj8foDG4cPH07nzp1p3bo1Y8aMYe/evQ5TRZ588klat26Nq6urw+eKi4tJT0/nxRdfxN3dHaPRSO/evQHYtm0bI0eOJCQkBL1eT3h4OEajkezs7DrlmxBCCMjOzsZsNvP4449jNBq58847ufvuu0lOTgZg4MCB3HHHHej1ek6dOsVvv/3GH//4R4xGIwEBAURERJCSklLrcYKDgwkLC8NoNDJq1CgqKysd6uuHHnoIX1/fq9oBgO3btzNmzBiCgoLQ6XR07doVDw8PDhw4gJ+fHyNGjMBgMHD77bczaNAg9u7d23AZJIQQLVBOTg4mk4mxY8far8HvuOMOkpOTGTVqFAEBAbRu3Zpnn32WlJQUh6lyVdftnTt3ZsSIEezZs8e+rqa6/tixY7W2Hz169OCee+5Br9dfsy2oTtoU4Uxkip8Q1QQGBjJ+/Hg2bNjAmTNn6NevH+PGjbvuZ4qLi/H29kan09mXVU3fA7h06RLx8fGkp6dTVlYGwMWLF7HZbOj1+qu2r031bX19fbFarfz222/XXF9dUVER7u7uuLu7X7WusLCQXbt2sWXLFvsyi8WCyWSqc1xCCHGrKy4uxtfX1163A/j5+dnr0ur187lz5yguLmb8+PH2ZTabjV69etV6nOr70ev1+Pj4UFxcbF92vZG4RUVFBAQEXLX83LlzZGdnO8RjtVoZPnx4rfEIIcStrLCwED8/v6tGFxUXFzvMxKi6br9w4YJ92ZXX9adOnbrmuivr+traj5v9bSFtitCadFAJcYWhQ4cydOhQysvL+cc//sHatWtp06YNly5dsm9z/vx5+2svLy9MJhNKKXsnVVFRkX3k1TfffENeXh4ff/wx7du358SJE0ybNo3qD9Cs3rlVm6KiIvvrwsJCDAYD7dq1o7Cw8Lr78vHxobS0lLKyMtq2bXvVutGjRzN69Og6xyGEEMKRl5cXhYWFDn9AFBYW0qFDB86dO+dQP/v6+uLv78/ixYtv+DjV2wGbzUZRURFeXl51+qyPjw9nz56lc+fOVy3v3bs377777g3HI4QQtzJfX18KCwuxWq0OnVReXl6cO3fO/r7qut3T09NejxcVFdGxY0f7+up1eU11vcFguOn241qkTRHORKb4CVFNXl4ehw8fprKyEldXV1xdXe3DVQ8ePEhpaSnnz5/nu+++s3+mR48e6PV6tmzZgtVqJTU1lZycHPt6s9mMq6srbm5ulJaWsmHDhnrF+L///Y8zZ85w6dIl1q9fT1hYmMO/9TXx8vKif//+LF++nNLSUiwWC1lZWQBERETw3//+l+zsbJRSmM1mDhw4wMWLF+sVqxBC3EpCQkJo1aoVX3/9NRaLhczMTNLS0hgyZMhV23bv3p02bdqwceNGKioqsNlsnDp1yqH9qElubi7ff/89VquV7777DhcXF0JCQuoUY0REBOvWrSM/Px+lFCdPnqSkpIQBAwaQn5/P7t27sVgsWCwWcnJy5H4hQghRi+7du+Pl5cXatWsxm81UVFTw008/MWTIEL799lsKCgowm8188cUX3HvvvQ6dWF9++SWXLl3i9OnTJCUlOdxEvKa6vj7tx7VImyKciYygEqKayspK1q5dyy+//ILBYKBnz55ERkbi7u5ORkYG0dHR+Pn5ER4ezubNmwEwGo1MnTqVuLg4Pv/8c+666y4GDBhgv5fUww8/zOLFi/nLX/6Ct7c3o0aNIjU19aZjHD58OLGxseTl5dGrVy+ioqLq/NlXXnmF1atX89prr2GxWOjTpw+9e/emW7duvPTSS6xcuZL8/Hz73Pm6TDURQghxmdFoZPr06SxfvpzExES8vb2ZNGmS/d/x6vR6PdOnTychIYHo6GgsFgtBQUE8/fTTtR4nNDSUlJQUYmNjCQwM5I033qj1/oVVqu4v8uGHH1JSUkLHjh2ZOnUqHh4evPPOO8THxxMfH49Sii5duvDcc8/dcD4IIcStpKo+X7lyJVFRUeh0OoYMGcL48eMpLi7m/fffp6Kign79+jFhwgSHz/bu3ZvJkydjs9l49NFH6devn33d9er6m20/rkXaFOFMdKr6PCMhRIOYOXMm999/PyNGjGjQ/c6aNYthw4bV+KhYIYQQLdv69ev59ddfmTx5stahCCGEuEkFBQVMmjSJL7744qp7V0HT1fXSpghnI1P8hGgAWVlZnD9/HqvVSlJSEidPnqR///5ahyWEEEIIIYQQQjQLMsVPiAaQl5fHwoULMZvNBAQE8MYbb9T55oJXGjt27DWXz5w5sz4hCiGEaCY+/vhjjhw5ctXyJ554QoNohBBCNGfSpojmRKb4CSGEEEIIIYQQQghNyRQ/IYQQQgghhBBCCKEp6aASQgghhBBCCCGEEJqSDiohhBBCCCGEEEIIoSnpoBJCCCGEEEIIIYQQmpIOKiGEEEIIIYQQQgihqf8Hjjv6S/QpkR0AAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(20, 60))\n",
        "plotnumber = 1\n",
        "for feature in continuous_features:\n",
        "    ax = plt.subplot(12, 3, plotnumber)\n",
        "    sns.boxplot(x = df[feature])\n",
        "    plt.xlabel(feature)\n",
        "    plotnumber+=1\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3NlIh_7kFAUH",
        "outputId": "9485d5ab-7d07-4e9a-fcf0-edcc3443f50e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1440x4320 with 6 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Selecting Best Model"
      ],
      "metadata": {
        "id": "oZ9SyKNhs3Y3"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def find_best_model_using_gridsearchcv(x, y):\n",
        "    algos = {\n",
        "        'DecisionTreeRegressor': {\n",
        "            'model': DecisionTreeRegressor(),\n",
        "            'params': {\n",
        "                'criterion': ['squared_error','friedman_mse'],\n",
        "                'splitter': ['best','random']\n",
        "            }\n",
        "        },\n",
        "        'RandomForestRegressor': {\n",
        "            'model': RandomForestRegressor(),\n",
        "            'params': {\n",
        "                'n_estimators': [10, 50, 100, 130],\n",
        "                'criterion': ['squared_error'],\n",
        "                'max_depth': range(2, 4, 1),\n",
        "                'max_features': ['auto','log2']\n",
        "            }\n",
        "        },\n",
        "        'XGBRegressor': {\n",
        "            'model': XGBRegressor(),\n",
        "            'params': {\n",
        "                'objective': ['reg:squarederror'],\n",
        "                'learning_rate': [0.5, 0.1, 0.01, 0.001],\n",
        "                'max_depth': [2, 3],\n",
        "                'n_estimators': [10, 50, 100, 200]\n",
        "            }\n",
        "        },\n",
        "        'LinearRegression': {\n",
        "            'model': LinearRegression(),\n",
        "            'params': {}\n",
        "        }\n",
        "\n",
        "    }\n",
        "    scores = []\n",
        "    cv = ShuffleSplit(n_splits = 5, test_size = 0.2, random_state = 0)\n",
        "    for algo_name, config in algos.items():\n",
        "        gs = GridSearchCV(config['model'], config['params'],cv = cv, return_train_score = False)\n",
        "        gs.fit(x,y)\n",
        "        scores.append({\n",
        "            'model':algo_name,\n",
        "            'best_score': gs.best_score_,\n",
        "            'best_params': gs.best_params_\n",
        "        })\n",
        "    return pd.DataFrame(scores, columns = ['model', 'best_score', 'best_params'])"
      ],
      "metadata": {
        "id": "pMRg7BDzBCKq"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Price Predictions by Combined Dataset"
      ],
      "metadata": {
        "id": "T0JYwJN1Frrk"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "target = 'oil_price' #oil_price, coal_price, gas_price, sugar_price, ore_price, copper_price"
      ],
      "metadata": {
        "id": "K_Ye0fMLFrKc"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(cor_mat[target])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "sJV4BrLDTolw",
        "outputId": "25883ede-7dd4-4dcd-b9b0-c4fc0612e26a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "oil_price       1.000000\n",
            "coal_price      0.820015\n",
            "gas_price       0.381916\n",
            "sugar_price     0.697577\n",
            "ore_price       0.855380\n",
            "copper_price    0.886648\n",
            "Name: oil_price, dtype: float64\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(20, 60))\n",
        "plotnumber = 1\n",
        "for feature in continuous_features:\n",
        "    ax = plt.subplot(12, 3, plotnumber)\n",
        "    plt.scatter(df[feature], df[target])\n",
        "    plt.xlabel(feature)\n",
        "    plt.ylabel(target)\n",
        "    plotnumber+=1\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 528
        },
        "id": "Rjd1P_VHTqzD",
        "outputId": "0d597864-4c2f-48f7-92c6-17cb8d2bb468"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1440x4320 with 6 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df['Y'] = df[target].shift(-forecast_out)\n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 455
        },
        "id": "63NFu5qkcVsl",
        "outputId": "4fbb8d04-4db7-4a0c-e0b6-00faa739b15c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            oil_price  coal_price  gas_price  sugar_price  ore_price  \\\n",
              "Month                                                                  \n",
              "1992-03-01      17.60       39.50       1.28         0.18      33.10   \n",
              "1992-04-01      18.95       39.50       1.47         0.21      33.10   \n",
              "1992-05-01      19.90       39.50       1.59         0.21      33.10   \n",
              "1992-06-01      21.15       39.50       1.56         0.23      33.10   \n",
              "1992-07-01      20.25       39.50       1.75         0.23      33.10   \n",
              "...               ...         ...        ...          ...        ...   \n",
              "2021-05-01      68.04      107.04       2.89         0.38     207.72   \n",
              "2021-06-01      73.07      129.97       3.24         0.38     214.43   \n",
              "2021-07-01      74.39      151.97       3.80         0.39     214.14   \n",
              "2021-08-01      70.02      169.58       4.05         0.43     162.16   \n",
              "2021-09-01      74.60      185.69       5.11         0.43     124.52   \n",
              "\n",
              "            copper_price      Y  \n",
              "Month                            \n",
              "1992-03-01       2227.33  20.25  \n",
              "1992-04-01       2215.33  19.75  \n",
              "1992-05-01       2216.52  20.25  \n",
              "1992-06-01       2299.20  20.30  \n",
              "1992-07-01       2520.32  19.20  \n",
              "...                  ...    ...  \n",
              "2021-05-01      10161.97  74.60  \n",
              "2021-06-01       9631.50    NaN  \n",
              "2021-07-01       9450.82    NaN  \n",
              "2021-08-01       9370.14    NaN  \n",
              "2021-09-01       9324.71    NaN  \n",
              "\n",
              "[355 rows x 7 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-a8e13b46-b080-4ff2-a3f1-3b933d345787\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>oil_price</th>\n",
              "      <th>coal_price</th>\n",
              "      <th>gas_price</th>\n",
              "      <th>sugar_price</th>\n",
              "      <th>ore_price</th>\n",
              "      <th>copper_price</th>\n",
              "      <th>Y</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Month</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>1992-03-01</th>\n",
              "      <td>17.60</td>\n",
              "      <td>39.50</td>\n",
              "      <td>1.28</td>\n",
              "      <td>0.18</td>\n",
              "      <td>33.10</td>\n",
              "      <td>2227.33</td>\n",
              "      <td>20.25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1992-04-01</th>\n",
              "      <td>18.95</td>\n",
              "      <td>39.50</td>\n",
              "      <td>1.47</td>\n",
              "      <td>0.21</td>\n",
              "      <td>33.10</td>\n",
              "      <td>2215.33</td>\n",
              "      <td>19.75</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1992-05-01</th>\n",
              "      <td>19.90</td>\n",
              "      <td>39.50</td>\n",
              "      <td>1.59</td>\n",
              "      <td>0.21</td>\n",
              "      <td>33.10</td>\n",
              "      <td>2216.52</td>\n",
              "      <td>20.25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1992-06-01</th>\n",
              "      <td>21.15</td>\n",
              "      <td>39.50</td>\n",
              "      <td>1.56</td>\n",
              "      <td>0.23</td>\n",
              "      <td>33.10</td>\n",
              "      <td>2299.20</td>\n",
              "      <td>20.30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1992-07-01</th>\n",
              "      <td>20.25</td>\n",
              "      <td>39.50</td>\n",
              "      <td>1.75</td>\n",
              "      <td>0.23</td>\n",
              "      <td>33.10</td>\n",
              "      <td>2520.32</td>\n",
              "      <td>19.20</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-05-01</th>\n",
              "      <td>68.04</td>\n",
              "      <td>107.04</td>\n",
              "      <td>2.89</td>\n",
              "      <td>0.38</td>\n",
              "      <td>207.72</td>\n",
              "      <td>10161.97</td>\n",
              "      <td>74.60</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-06-01</th>\n",
              "      <td>73.07</td>\n",
              "      <td>129.97</td>\n",
              "      <td>3.24</td>\n",
              "      <td>0.38</td>\n",
              "      <td>214.43</td>\n",
              "      <td>9631.50</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-07-01</th>\n",
              "      <td>74.39</td>\n",
              "      <td>151.97</td>\n",
              "      <td>3.80</td>\n",
              "      <td>0.39</td>\n",
              "      <td>214.14</td>\n",
              "      <td>9450.82</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-08-01</th>\n",
              "      <td>70.02</td>\n",
              "      <td>169.58</td>\n",
              "      <td>4.05</td>\n",
              "      <td>0.43</td>\n",
              "      <td>162.16</td>\n",
              "      <td>9370.14</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-09-01</th>\n",
              "      <td>74.60</td>\n",
              "      <td>185.69</td>\n",
              "      <td>5.11</td>\n",
              "      <td>0.43</td>\n",
              "      <td>124.52</td>\n",
              "      <td>9324.71</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>355 rows × 7 columns</p>\n",
              "</div>\n",
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          "metadata": {},
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    {
      "cell_type": "code",
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        "X = np.array(df.drop(['Y'], 1))\n",
        "X = preprocessing.scale(X)\n",
        "X_lately = X[-forecast_out:]\n",
        "X = X[:-forecast_out]\n",
        "X"
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      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:1: FutureWarning: In a future version of pandas all arguments of DataFrame.drop except for the argument 'labels' will be keyword-only\n",
            "  \"\"\"Entry point for launching an IPython kernel.\n"
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    {
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      "source": [
        "y = np.array(df['Y'])\n",
        "y = y[:-forecast_out]\n",
        "y"
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              "        17.6 ,  16.8 ,  15.9 ,  16.4 ,  17.2 ,  15.96,  16.63,  17.08,\n",
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              "        12.01,  11.88,  13.36,  12.56,  10.92,   9.8 ,  11.06,  10.2 ,\n",
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              "       114.44, 123.07, 114.46, 113.76, 116.46, 110.08, 110.88, 109.47,\n",
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              "       109.24, 102.88, 103.03, 103.11, 107.72, 110.96, 111.62, 109.48,\n",
              "       108.08, 110.67, 107.42, 108.81, 107.4 , 107.79, 109.68, 111.87,\n",
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              "        62.57,  64.21,  68.99,  65.42,  66.45,  71.63,  76.65,  75.19,\n",
              "        74.44,  73.13,  78.86,  80.47,  65.17,  56.46,  59.27,  64.13,\n",
              "        66.41,  71.2 ,  70.53,  63.3 ,  64.  ,  59.25,  62.33,  59.37,\n",
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              "        42.81,  44.26,  41.09,  40.47,  43.23,  49.87,  54.55,  61.96,\n",
              "        65.19,  64.77,  68.04,  73.07,  74.39,  70.02,  74.6 ])"
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        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.2, random_state = 0)\n",
        "pd.set_option('display.max_colwidth', 100)\n",
        "find_best_model_using_gridsearchcv(X,y)"
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              "                   model  best_score  \\\n",
              "0  DecisionTreeRegressor    0.915205   \n",
              "1  RandomForestRegressor    0.903620   \n",
              "2           XGBRegressor    0.940797   \n",
              "3       LinearRegression    0.856345   \n",
              "\n",
              "                                                                                    best_params  \n",
              "0                                            {'criterion': 'squared_error', 'splitter': 'best'}  \n",
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              "3                                                                                            {}  "
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              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "clf = XGBRegressor(learning_rate = 0.1, max_depth = 3, n_estimators = 200, objective = 'reg:squarederror')\n",
        "clf.fit(X_train, y_train)\n",
        "confidence = clf.score(X_test, y_test)\n",
        "print(confidence)"
      ],
      "metadata": {
        "id": "3_GbYSOFXhvO",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "b5631359-a283-423d-9ddc-228e690cd3e4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "0.9607251677811108\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "forecast_set = clf.predict(X_lately)\n",
        "df['Forecast'] = np.nan\n",
        "forecast_set"
      ],
      "metadata": {
        "id": "S26tW5Detbu7",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "4b579980-2571-4982-e526-944c490d5bb4"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([83.33231 , 60.84204 , 58.734276, 61.01791 ], dtype=float32)"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for i in forecast_set:\n",
        "    next_date = df.iloc[-1].name + relativedelta(months=1)\n",
        "    df.loc[next_date] = [np.nan for _ in range(len(df.columns)-1)]+[i]"
      ],
      "metadata": {
        "id": "ExbPgEcBteBp"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 455
        },
        "id": "fdXHQMJjjTlj",
        "outputId": "06ce5ccd-c312-4d11-ad35-e8ca7b2a16fa"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            oil_price  coal_price  gas_price  sugar_price  ore_price  \\\n",
              "Month                                                                  \n",
              "1992-03-01      17.60       39.50       1.28         0.18      33.10   \n",
              "1992-04-01      18.95       39.50       1.47         0.21      33.10   \n",
              "1992-05-01      19.90       39.50       1.59         0.21      33.10   \n",
              "1992-06-01      21.15       39.50       1.56         0.23      33.10   \n",
              "1992-07-01      20.25       39.50       1.75         0.23      33.10   \n",
              "...               ...         ...        ...          ...        ...   \n",
              "2021-09-01      74.60      185.69       5.11         0.43     124.52   \n",
              "2021-10-01        NaN         NaN        NaN          NaN        NaN   \n",
              "2021-11-01        NaN         NaN        NaN          NaN        NaN   \n",
              "2021-12-01        NaN         NaN        NaN          NaN        NaN   \n",
              "2022-01-01        NaN         NaN        NaN          NaN        NaN   \n",
              "\n",
              "            copper_price      Y   Forecast  \n",
              "Month                                       \n",
              "1992-03-01       2227.33  20.25        NaN  \n",
              "1992-04-01       2215.33  19.75        NaN  \n",
              "1992-05-01       2216.52  20.25        NaN  \n",
              "1992-06-01       2299.20  20.30        NaN  \n",
              "1992-07-01       2520.32  19.20        NaN  \n",
              "...                  ...    ...        ...  \n",
              "2021-09-01       9324.71    NaN        NaN  \n",
              "2021-10-01           NaN    NaN  83.332314  \n",
              "2021-11-01           NaN    NaN  60.842041  \n",
              "2021-12-01           NaN    NaN  58.734276  \n",
              "2022-01-01           NaN    NaN  61.017910  \n",
              "\n",
              "[359 rows x 8 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-0dcd10f7-3580-415a-849a-d8be961ab8ac\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>oil_price</th>\n",
              "      <th>coal_price</th>\n",
              "      <th>gas_price</th>\n",
              "      <th>sugar_price</th>\n",
              "      <th>ore_price</th>\n",
              "      <th>copper_price</th>\n",
              "      <th>Y</th>\n",
              "      <th>Forecast</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Month</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>1992-03-01</th>\n",
              "      <td>17.60</td>\n",
              "      <td>39.50</td>\n",
              "      <td>1.28</td>\n",
              "      <td>0.18</td>\n",
              "      <td>33.10</td>\n",
              "      <td>2227.33</td>\n",
              "      <td>20.25</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1992-04-01</th>\n",
              "      <td>18.95</td>\n",
              "      <td>39.50</td>\n",
              "      <td>1.47</td>\n",
              "      <td>0.21</td>\n",
              "      <td>33.10</td>\n",
              "      <td>2215.33</td>\n",
              "      <td>19.75</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1992-05-01</th>\n",
              "      <td>19.90</td>\n",
              "      <td>39.50</td>\n",
              "      <td>1.59</td>\n",
              "      <td>0.21</td>\n",
              "      <td>33.10</td>\n",
              "      <td>2216.52</td>\n",
              "      <td>20.25</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1992-06-01</th>\n",
              "      <td>21.15</td>\n",
              "      <td>39.50</td>\n",
              "      <td>1.56</td>\n",
              "      <td>0.23</td>\n",
              "      <td>33.10</td>\n",
              "      <td>2299.20</td>\n",
              "      <td>20.30</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1992-07-01</th>\n",
              "      <td>20.25</td>\n",
              "      <td>39.50</td>\n",
              "      <td>1.75</td>\n",
              "      <td>0.23</td>\n",
              "      <td>33.10</td>\n",
              "      <td>2520.32</td>\n",
              "      <td>19.20</td>\n",
              "      <td>NaN</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-09-01</th>\n",
              "      <td>74.60</td>\n",
              "      <td>185.69</td>\n",
              "      <td>5.11</td>\n",
              "      <td>0.43</td>\n",
              "      <td>124.52</td>\n",
              "      <td>9324.71</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-10-01</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>83.332314</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-11-01</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>60.842041</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2021-12-01</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>58.734276</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2022-01-01</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>61.017910</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>359 rows × 8 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-0dcd10f7-3580-415a-849a-d8be961ab8ac')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-0dcd10f7-3580-415a-849a-d8be961ab8ac button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-0dcd10f7-3580-415a-849a-d8be961ab8ac');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "odf[target].plot()\n",
        "df['Forecast'].plot()\n",
        "plt.legend(loc=4)\n",
        "plt.xlabel('Date')\n",
        "plt.ylabel('Price')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 286
        },
        "id": "3Rh_hPUptiAu",
        "outputId": "11684551-082d-476f-e40a-2c1a71eeefda"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "odf.tail(forecast_out+1)[target].plot()\n",
        "df.tail(forecast_out)['Forecast'].plot()\n",
        "plt.legend(loc=4)\n",
        "plt.xlabel('Date')\n",
        "plt.ylabel('Price')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 294
        },
        "id": "7u-_rCsn-C8s",
        "outputId": "5908c75a-5254-4341-abdb-4e2e1906750f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(df['Forecast'])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7c10MC-MkwxW",
        "outputId": "f3791c1c-3f1f-4a1f-a7ac-3629f54405bc"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Month\n",
            "1992-03-01          NaN\n",
            "1992-04-01          NaN\n",
            "1992-05-01          NaN\n",
            "1992-06-01          NaN\n",
            "1992-07-01          NaN\n",
            "                ...    \n",
            "2021-09-01          NaN\n",
            "2021-10-01    83.332314\n",
            "2021-11-01    60.842041\n",
            "2021-12-01    58.734276\n",
            "2022-01-01    61.017910\n",
            "Name: Forecast, Length: 359, dtype: float64\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(odf[target])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "a6exiqFYlxbG",
        "outputId": "306548de-b1c5-41b0-c9f1-d85d7fadfc2e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Month\n",
            "1992-03-01    17.60\n",
            "1992-04-01    18.95\n",
            "1992-05-01    19.90\n",
            "1992-06-01    21.15\n",
            "1992-07-01    20.25\n",
            "              ...  \n",
            "2021-09-01    74.60\n",
            "2021-10-01    83.65\n",
            "2021-11-01    80.77\n",
            "2021-12-01    74.31\n",
            "2022-01-01    85.53\n",
            "Name: oil_price, Length: 359, dtype: float64\n"
          ]
        }
      ]
    }
  ]
}