Weighted_combinations.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Weighted_combinations.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyNS13Ildl07PjmYoCRp2GgG",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/gaditi123/Technical-Indicators-FA-Project/blob/main/Weighted_combinations.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fYSw_nK2bZs5",
        "outputId": "f318688b-9d7b-49ea-9454-f1d763709ac5"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Collecting yfinance\n",
            "  Downloading yfinance-0.1.70-py2.py3-none-any.whl (26 kB)\n",
            "Collecting requests>=2.26\n",
            "  Downloading requests-2.28.0-py3-none-any.whl (62 kB)\n",
            "\u001b[K     |████████████████████████████████| 62 kB 1.3 MB/s \n",
            "\u001b[?25hRequirement already satisfied: multitasking>=0.0.7 in /usr/local/lib/python3.7/dist-packages (from yfinance) (0.0.10)\n",
            "Requirement already satisfied: numpy>=1.15 in /usr/local/lib/python3.7/dist-packages (from yfinance) (1.21.6)\n",
            "Collecting lxml>=4.5.1\n",
            "  Downloading lxml-4.9.0-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_24_x86_64.whl (6.4 MB)\n",
            "\u001b[K     |████████████████████████████████| 6.4 MB 11.4 MB/s \n",
            "\u001b[?25hRequirement already satisfied: pandas>=0.24.0 in /usr/local/lib/python3.7/dist-packages (from yfinance) (1.3.5)\n",
            "Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.7/dist-packages (from pandas>=0.24.0->yfinance) (2022.1)\n",
            "Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.7/dist-packages (from pandas>=0.24.0->yfinance) (2.8.2)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.7/dist-packages (from python-dateutil>=2.7.3->pandas>=0.24.0->yfinance) (1.15.0)\n",
            "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests>=2.26->yfinance) (1.24.3)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests>=2.26->yfinance) (2.10)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests>=2.26->yfinance) (2022.5.18.1)\n",
            "Requirement already satisfied: charset-normalizer~=2.0.0 in /usr/local/lib/python3.7/dist-packages (from requests>=2.26->yfinance) (2.0.12)\n",
            "Installing collected packages: requests, lxml, yfinance\n",
            "  Attempting uninstall: requests\n",
            "    Found existing installation: requests 2.23.0\n",
            "    Uninstalling requests-2.23.0:\n",
            "      Successfully uninstalled requests-2.23.0\n",
            "  Attempting uninstall: lxml\n",
            "    Found existing installation: lxml 4.2.6\n",
            "    Uninstalling lxml-4.2.6:\n",
            "      Successfully uninstalled lxml-4.2.6\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "google-colab 1.0.0 requires requests~=2.23.0, but you have requests 2.28.0 which is incompatible.\n",
            "datascience 0.10.6 requires folium==0.2.1, but you have folium 0.8.3 which is incompatible.\u001b[0m\n",
            "Successfully installed lxml-4.9.0 requests-2.28.0 yfinance-0.1.70\n"
          ]
        }
      ],
      "source": [
        "!pip install yfinance"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install pandas_ta"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hg0W-lHhdQGm",
        "outputId": "87a2750a-d483-4760-e92b-715361c8c618"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Collecting pandas_ta\n",
            "  Downloading pandas_ta-0.3.14b.tar.gz (115 kB)\n",
            "\u001b[K     |████████████████████████████████| 115 kB 5.2 MB/s \n",
            "\u001b[?25hRequirement already satisfied: pandas in /usr/local/lib/python3.7/dist-packages (from pandas_ta) (1.3.5)\n",
            "Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.7/dist-packages (from pandas->pandas_ta) (2022.1)\n",
            "Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.7/dist-packages (from pandas->pandas_ta) (2.8.2)\n",
            "Requirement already satisfied: numpy>=1.17.3 in /usr/local/lib/python3.7/dist-packages (from pandas->pandas_ta) (1.21.6)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.7/dist-packages (from python-dateutil>=2.7.3->pandas->pandas_ta) (1.15.0)\n",
            "Building wheels for collected packages: pandas-ta\n",
            "  Building wheel for pandas-ta (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for pandas-ta: filename=pandas_ta-0.3.14b0-py3-none-any.whl size=218923 sha256=8134b38a16d3e010d6c59867ea4462eb3510169aad9f0528215cda386f705b27\n",
            "  Stored in directory: /root/.cache/pip/wheels/0b/81/f0/cca85757840e4616a2c6b9fe12569d97d324c27cac60724c58\n",
            "Successfully built pandas-ta\n",
            "Installing collected packages: pandas-ta\n",
            "Successfully installed pandas-ta-0.3.14b0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import yfinance as yf\n",
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "import pandas_ta as ta\n",
        "\n",
        "plt.style.use(\"seaborn\")\n",
        "plt.rcParams[\"figure.figsize\"] = [14, 8]"
      ],
      "metadata": {
        "id": "5p8WG2UtdP6X"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df = yf.download(\"HDFCBANK.NS\", start=\"2015-01-01\", end=\"2019-12-31\")\n",
        "df[\"Adj Close\"].plot(title=\"HDFC's stock in 2021\");"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 495
        },
        "id": "VkHd3N3tdjHq",
        "outputId": "3a813725-b0b3-4439-b27c-d5452992ce34"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\r[*********************100%***********************]  1 of 1 completed\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1008x576 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "CustomStrategy = ta.Strategy(\n",
        "    name=\"Weighted Strategy\",\n",
        "    description=\"SMA 50,200, BBANDS, RSI, MACD and Volume SMA 20\",\n",
        "    ta = [\n",
        "          {\"kind\" : \"sma\", \"length\" : 10},\n",
        "          {\"kind\": \"sma\", \"length\": 30},\n",
        "          {\"kind\": \"rsi\"},\n",
        "          {\"kind\" : \"obv\"},\n",
        "          {\"kind\": \"macd\", \"fast\": 8, \"slow\": 21},\n",
        "          {\"kind\": \"bbands\", \"length\": 20}\n",
        "    ]\n",
        ")\n",
        "# To run your \"Custom Strategy\"\n",
        "df.ta.strategy(CustomStrategy)"
      ],
      "metadata": {
        "id": "ydTLmrDidr_F"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df['OBV_EMA'] = df['OBV'].ewm(span=14).mean()\n",
        "df = df.iloc[30:, :]\n",
        "df.head(200)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 797
        },
        "id": "wBC7CMmJd4of",
        "outputId": "4c71d847-7426-438d-fd87-faf32b6368cf"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \"\"\"Entry point for launching an IPython kernel.\n"
          ]
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              "                  Open        High         Low       Close   Adj Close  \\\n",
              "Date                                                                     \n",
              "2015-03-31  519.950012  519.950012  507.424988  511.350006  484.978485   \n",
              "2015-04-01  513.049988  518.424988  506.500000  516.625000  489.981415   \n",
              "2015-04-06  517.500000  518.424988  509.899994  515.974976  489.364960   \n",
              "2015-04-07  516.625000  519.099976  511.825012  516.375000  489.744324   \n",
              "2015-04-08  520.025024  521.224976  515.025024  517.775024  491.072174   \n",
              "...                ...         ...         ...         ...         ...   \n",
              "2016-01-14  525.075012  528.700012  519.750000  524.875000  501.547607   \n",
              "2016-01-15  524.000000  527.724976  519.049988  521.075012  497.916534   \n",
              "2016-01-18  517.825012  520.724976  510.500000  512.924988  490.128723   \n",
              "2016-01-19  513.599976  518.775024  513.150024  517.900024  494.882660   \n",
              "2016-01-20  512.500000  554.000000  503.950012  509.149994  486.521454   \n",
              "\n",
              "             Volume      SMA_10      SMA_30     RSI_14         OBV  ...  \\\n",
              "Date                                                                ...   \n",
              "2015-03-31  2981128  518.640002  527.315007  42.777334  22766994.0  ...   \n",
              "2015-04-01  1922098  517.125000  526.743339  46.549342  24689092.0  ...   \n",
              "2015-04-06  3575586  516.112500  526.029171  46.145670  21113506.0  ...   \n",
              "2015-04-07  3098536  514.954999  525.245003  46.453413  24212042.0  ...   \n",
              "2015-04-08  2053072  514.345001  524.620003  47.582372  26265114.0  ...   \n",
              "...             ...         ...         ...        ...         ...  ...   \n",
              "2016-01-14  3139592  531.137494  532.677496  42.410586  -6940536.0  ...   \n",
              "2016-01-15  2708630  528.807495  532.100830  39.499564  -9649166.0  ...   \n",
              "2016-01-18  3247694  526.574994  531.549996  34.094328 -12896860.0  ...   \n",
              "2016-01-19  3202606  525.244995  531.114164  39.533804  -9694254.0  ...   \n",
              "2016-01-20  4781794  522.804996  530.598331  34.189140 -14476048.0  ...   \n",
              "\n",
              "            BBL_20_2.0  BBM_20_2.0  BBU_20_2.0  BBB_20_2.0  BBP_20_2.0  \\\n",
              "Date                                                                     \n",
              "2015-03-31  505.203787  524.535004  543.866220    7.370801    0.158971   \n",
              "2015-04-01  505.361044  523.282504  541.203965    6.849631    0.314259   \n",
              "2015-04-06  504.798594  522.448752  540.098910    6.756704    0.316609   \n",
              "2015-04-07  505.933328  521.140002  536.346677    5.835927    0.343325   \n",
              "2015-04-08  505.783686  520.553754  535.323821    5.674752    0.405934   \n",
              "...                ...         ...         ...         ...         ...   \n",
              "2016-01-14  523.761230  534.439996  545.118763    3.996245    0.052149   \n",
              "2016-01-15  521.669386  533.487497  545.305608    4.430511   -0.025147   \n",
              "2016-01-18  517.582638  532.308746  547.034854    5.532920   -0.158143   \n",
              "2016-01-19  515.550204  531.318747  547.087290    5.935625    0.074510   \n",
              "2016-01-20  511.664662  530.114998  548.565334    6.960881   -0.068147   \n",
              "\n",
              "                 OBV_EMA  Signals_SMA  Signals_RSI  Signals_OBV  \\\n",
              "Date                                                              \n",
              "2015-03-31  3.345554e+07            0            0            0   \n",
              "2015-04-01  3.227456e+07            0            0            0   \n",
              "2015-04-06  3.077306e+07            0            0            0   \n",
              "2015-04-07  2.989146e+07            0            0            0   \n",
              "2015-04-08  2.940470e+07            0            0            0   \n",
              "...                  ...          ...          ...          ...   \n",
              "2016-01-14 -5.044430e+06            0            0           -1   \n",
              "2016-01-15 -5.658395e+06            0            0            0   \n",
              "2016-01-18 -6.623524e+06            0            0            0   \n",
              "2016-01-19 -7.032954e+06            0            0            0   \n",
              "2016-01-20 -8.025367e+06            0            0            0   \n",
              "\n",
              "            Buy_Sell_Signal  \n",
              "Date                         \n",
              "2015-03-31                0  \n",
              "2015-04-01                0  \n",
              "2015-04-06                0  \n",
              "2015-04-07                0  \n",
              "2015-04-08                0  \n",
              "...                     ...  \n",
              "2016-01-14                0  \n",
              "2016-01-15                0  \n",
              "2016-01-18                0  \n",
              "2016-01-19                0  \n",
              "2016-01-20                0  \n",
              "\n",
              "[200 rows x 23 columns]"
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              "      <th>Date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2015-03-31</th>\n",
              "      <td>519.950012</td>\n",
              "      <td>519.950012</td>\n",
              "      <td>507.424988</td>\n",
              "      <td>511.350006</td>\n",
              "      <td>484.978485</td>\n",
              "      <td>2981128</td>\n",
              "      <td>518.640002</td>\n",
              "      <td>527.315007</td>\n",
              "      <td>42.777334</td>\n",
              "      <td>22766994.0</td>\n",
              "      <td>...</td>\n",
              "      <td>505.203787</td>\n",
              "      <td>524.535004</td>\n",
              "      <td>543.866220</td>\n",
              "      <td>7.370801</td>\n",
              "      <td>0.158971</td>\n",
              "      <td>3.345554e+07</td>\n",
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              "      <th>2015-04-01</th>\n",
              "      <td>513.049988</td>\n",
              "      <td>518.424988</td>\n",
              "      <td>506.500000</td>\n",
              "      <td>516.625000</td>\n",
              "      <td>489.981415</td>\n",
              "      <td>1922098</td>\n",
              "      <td>517.125000</td>\n",
              "      <td>526.743339</td>\n",
              "      <td>46.549342</td>\n",
              "      <td>24689092.0</td>\n",
              "      <td>...</td>\n",
              "      <td>505.361044</td>\n",
              "      <td>523.282504</td>\n",
              "      <td>541.203965</td>\n",
              "      <td>6.849631</td>\n",
              "      <td>0.314259</td>\n",
              "      <td>3.227456e+07</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <th>2015-04-06</th>\n",
              "      <td>517.500000</td>\n",
              "      <td>518.424988</td>\n",
              "      <td>509.899994</td>\n",
              "      <td>515.974976</td>\n",
              "      <td>489.364960</td>\n",
              "      <td>3575586</td>\n",
              "      <td>516.112500</td>\n",
              "      <td>526.029171</td>\n",
              "      <td>46.145670</td>\n",
              "      <td>21113506.0</td>\n",
              "      <td>...</td>\n",
              "      <td>504.798594</td>\n",
              "      <td>522.448752</td>\n",
              "      <td>540.098910</td>\n",
              "      <td>6.756704</td>\n",
              "      <td>0.316609</td>\n",
              "      <td>3.077306e+07</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "    <tr>\n",
              "      <th>2015-04-07</th>\n",
              "      <td>516.625000</td>\n",
              "      <td>519.099976</td>\n",
              "      <td>511.825012</td>\n",
              "      <td>516.375000</td>\n",
              "      <td>489.744324</td>\n",
              "      <td>3098536</td>\n",
              "      <td>514.954999</td>\n",
              "      <td>525.245003</td>\n",
              "      <td>46.453413</td>\n",
              "      <td>24212042.0</td>\n",
              "      <td>...</td>\n",
              "      <td>505.933328</td>\n",
              "      <td>521.140002</td>\n",
              "      <td>536.346677</td>\n",
              "      <td>5.835927</td>\n",
              "      <td>0.343325</td>\n",
              "      <td>2.989146e+07</td>\n",
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              "      <th>2015-04-08</th>\n",
              "      <td>520.025024</td>\n",
              "      <td>521.224976</td>\n",
              "      <td>515.025024</td>\n",
              "      <td>517.775024</td>\n",
              "      <td>491.072174</td>\n",
              "      <td>2053072</td>\n",
              "      <td>514.345001</td>\n",
              "      <td>524.620003</td>\n",
              "      <td>47.582372</td>\n",
              "      <td>26265114.0</td>\n",
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              "      <td>505.783686</td>\n",
              "      <td>520.553754</td>\n",
              "      <td>535.323821</td>\n",
              "      <td>5.674752</td>\n",
              "      <td>0.405934</td>\n",
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              "      <th>2016-01-14</th>\n",
              "      <td>525.075012</td>\n",
              "      <td>528.700012</td>\n",
              "      <td>519.750000</td>\n",
              "      <td>524.875000</td>\n",
              "      <td>501.547607</td>\n",
              "      <td>3139592</td>\n",
              "      <td>531.137494</td>\n",
              "      <td>532.677496</td>\n",
              "      <td>42.410586</td>\n",
              "      <td>-6940536.0</td>\n",
              "      <td>...</td>\n",
              "      <td>523.761230</td>\n",
              "      <td>534.439996</td>\n",
              "      <td>545.118763</td>\n",
              "      <td>3.996245</td>\n",
              "      <td>0.052149</td>\n",
              "      <td>-5.044430e+06</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
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              "    <tr>\n",
              "      <th>2016-01-15</th>\n",
              "      <td>524.000000</td>\n",
              "      <td>527.724976</td>\n",
              "      <td>519.049988</td>\n",
              "      <td>521.075012</td>\n",
              "      <td>497.916534</td>\n",
              "      <td>2708630</td>\n",
              "      <td>528.807495</td>\n",
              "      <td>532.100830</td>\n",
              "      <td>39.499564</td>\n",
              "      <td>-9649166.0</td>\n",
              "      <td>...</td>\n",
              "      <td>521.669386</td>\n",
              "      <td>533.487497</td>\n",
              "      <td>545.305608</td>\n",
              "      <td>4.430511</td>\n",
              "      <td>-0.025147</td>\n",
              "      <td>-5.658395e+06</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "    <tr>\n",
              "      <th>2016-01-18</th>\n",
              "      <td>517.825012</td>\n",
              "      <td>520.724976</td>\n",
              "      <td>510.500000</td>\n",
              "      <td>512.924988</td>\n",
              "      <td>490.128723</td>\n",
              "      <td>3247694</td>\n",
              "      <td>526.574994</td>\n",
              "      <td>531.549996</td>\n",
              "      <td>34.094328</td>\n",
              "      <td>-12896860.0</td>\n",
              "      <td>...</td>\n",
              "      <td>517.582638</td>\n",
              "      <td>532.308746</td>\n",
              "      <td>547.034854</td>\n",
              "      <td>5.532920</td>\n",
              "      <td>-0.158143</td>\n",
              "      <td>-6.623524e+06</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "    <tr>\n",
              "      <th>2016-01-19</th>\n",
              "      <td>513.599976</td>\n",
              "      <td>518.775024</td>\n",
              "      <td>513.150024</td>\n",
              "      <td>517.900024</td>\n",
              "      <td>494.882660</td>\n",
              "      <td>3202606</td>\n",
              "      <td>525.244995</td>\n",
              "      <td>531.114164</td>\n",
              "      <td>39.533804</td>\n",
              "      <td>-9694254.0</td>\n",
              "      <td>...</td>\n",
              "      <td>515.550204</td>\n",
              "      <td>531.318747</td>\n",
              "      <td>547.087290</td>\n",
              "      <td>5.935625</td>\n",
              "      <td>0.074510</td>\n",
              "      <td>-7.032954e+06</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2016-01-20</th>\n",
              "      <td>512.500000</td>\n",
              "      <td>554.000000</td>\n",
              "      <td>503.950012</td>\n",
              "      <td>509.149994</td>\n",
              "      <td>486.521454</td>\n",
              "      <td>4781794</td>\n",
              "      <td>522.804996</td>\n",
              "      <td>530.598331</td>\n",
              "      <td>34.189140</td>\n",
              "      <td>-14476048.0</td>\n",
              "      <td>...</td>\n",
              "      <td>511.664662</td>\n",
              "      <td>530.114998</td>\n",
              "      <td>548.565334</td>\n",
              "      <td>6.960881</td>\n",
              "      <td>-0.068147</td>\n",
              "      <td>-8.025367e+06</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "\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-3f821a30-c9a1-4073-8db7-c90c097ec510 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-3f821a30-c9a1-4073-8db7-c90c097ec510');\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": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.columns"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Ol6XdeGpGw8A",
        "outputId": "05dcd268-cc4e-4638-fe53-2b5a2f639188"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['Open', 'High', 'Low', 'Close', 'Adj Close', 'Volume', 'SMA_10',\n",
              "       'SMA_30', 'RSI_14', 'OBV', 'MACD_8_21_9', 'MACDh_8_21_9',\n",
              "       'MACDs_8_21_9', 'BBL_20_2.0', 'BBM_20_2.0', 'BBU_20_2.0', 'BBB_20_2.0',\n",
              "       'BBP_20_2.0', 'OBV_EMA', 'Signals_SMA', 'Signals_RSI', 'Signals_OBV',\n",
              "       'Buy_Sell_Signal', 'Signals_MACD', 'Signals_BB'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 40
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.plot(df['SMA_30'], label='SMA', color='green')\n",
        "plt.plot(df['Open'], label='SHARE PRICE', color='black')\n",
        "\n",
        "#add legend\n",
        "plt.legend(title='Group')\n",
        "\n",
        "#add axes labels and a title\n",
        "plt.ylabel('SHARE PRICE', fontsize=14)\n",
        "plt.xlabel('Time', fontsize=14)\n",
        "plt.title('TA', fontsize=16)\n",
        "\n",
        "#display plot\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 519
        },
        "id": "RSvkN1imd6op",
        "outputId": "0b94c00c-80e5-4760-e509-0dc91b3dea2b"
      },
      "execution_count": 97,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1008x576 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.plot(df['RSI_14'], label='RSI', color='red')\n",
        "\n",
        "#add legend\n",
        "plt.legend(title='Group')\n",
        "\n",
        "#add axes labels and a title\n",
        "plt.ylabel('RSI range', fontsize=14)\n",
        "plt.xlabel('Time', fontsize=14)\n",
        "plt.title('RSI', fontsize=16)\n",
        "\n",
        "#display plot\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 519
        },
        "id": "XMkM2dWAeq8R",
        "outputId": "440ecb04-eeb0-4ce0-d070-b8e07afbd806"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1008x576 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.plot(df['MACD_8_21_9'], label ='MACD', color ='red')\n",
        "plt.plot(df['MACDs_8_21_9'], label = 'MACD signal', color = 'green')\n",
        "\n",
        "#add legend\n",
        "plt.legend(title='Group')\n",
        "\n",
        "#add axes labels and a title\n",
        "plt.ylabel('MACD deviation range', fontsize=14)\n",
        "plt.xlabel('Time', fontsize=14)\n",
        "plt.title('MACD', fontsize=16)\n",
        "\n",
        "#display plot\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 519
        },
        "id": "kIfTGYkwMQgg",
        "outputId": "8719f950-488a-429e-aa96-f7afa61584a7"
      },
      "execution_count": 94,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1008x576 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.plot(df['BBL_20_2.0'], label ='BB Lower', color ='red')\n",
        "plt.plot(df['BBM_20_2.0'], label = 'BB Middle', color = 'yellow')\n",
        "plt.plot(df['BBU_20_2.0'], label = 'BB Upper', color = 'green')\n",
        "plt.plot(df['Adj Close'], label = 'Close Price', color ='blue')\n",
        "\n",
        "#add legend\n",
        "plt.legend(title='Group')\n",
        "\n",
        "#add axes labels and a title\n",
        "plt.ylabel('BB deviation range', fontsize=14)\n",
        "plt.xlabel('Time', fontsize=14)\n",
        "plt.title('BB', fontsize=16)\n",
        "\n",
        "#display plot\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 519
        },
        "id": "e1bJPiRCM46L",
        "outputId": "4a29dbe0-b062-458b-e13d-c59e947e15e8"
      },
      "execution_count": 96,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1008x576 with 1 Axes>"
            ],
            "image/png": 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WhBBCCCGEOEF8qo/nFj3NC4tG4fQ4/9V7zdv9M0kRSXSqcW6FbVol6kUe1uasrrCNw+Ngbc5qmiW0wGSo/MS0ZcsCWaW4OJWDBzVMplWYTKdPUTEJloQQQgghhDhB/sj4jfQV43hrxevcPOM6Sn2l/8p9PD4PWcWZtEhohdFgrLBdqyS9yMN9v9yNx+cJOuf2uXlu0dOkTaqNqqm0SGgZtg9FySMmpg+xsVdiMq0C9JIIMTGB0gjJyTvJy8snPv4i4uMvAzYc3wOeIBIsCSGEEEIIcYJsP7jV//PSrMWMXPDEv3Kfg+6DAMRYY4/YrjyzBLBw34Kgc+OWvUb6inEk2hLpkNKRvs36h1xvtX5OQkJ7rNafsVgWEh9/EXFx3TEa1+F06muU3n33HmrW3EtOThIOxwCKitKBJsf5hCeGBEtCCCGEEEKcILsLdwPw7XU/UjOqFjO3f/+v3KewVF8gFGeNO2K7GGssvRtdD8DCfcEV8cqDp79u+Yc5fX7jorqX4PFASoqdwYNtKEoOdvvDgIrD8SyFhZNwu7tjNi8jIeF8FOUlABITHSQktEDTDCxZMoG33hqE23161Jk7PUZ5BsnM3Mdtt/WjWbPmKIqC2+1myJAHadeuPT/9NIP333+X2rX13ZTNZjMjRz5HQkLwJmI333wt1157IwMGDPQfe/vtN5k/fx5Tp85gypSP6dChI61bt/Wfdzqd3Hbbf5g6dUZQX+np40hL0zew3b59G0OHPvQvPbkQQgghhNiYp++n2SS+GU3im/Fnxm+UeEuIMEVU630KyoKl2KMESwDjLk3nx+0/8Oby18kpyWXerjk0iW/Gwn0LSI1pQIIt8F30wAE9WzRtmplPPx2GopRQXPwkJSUPAFBa2heLZTZRUaNwli3JUtVHSE6OAeCRR2ysXGmkd2+oVas6n/jfIZmlk6B+/VTS0ycyfvx7DB58P5Mnv+8/1717T9LTJ5KePpG2bdvz448/hFyfkJDIggW/+z9rmubfyBZgwICBQYGSEEIIIYQ4+fYWZfB7xnzaJ3cgJTKFetH1/Mermz9Yshx5Gh6A3RJDl1pdUTWVKes/IrN4H39kzAege/3LAMjLg1dftbBvX6D8948/avTvPxOH475DelNwu68iP38xubkjALDZmpOSoq9fWrnSSJ06Kq1bc1qQzNJJlpeXR1JScoXnWrZsFXLcbDYTGRnFjh3badgwjdWrV5Ga2pDMzH0AjB49im7detC+fQeefPIx3G43bdu2918/Z85PfPbZZJKTa2C1Wv2ZpXLTpn3NvHmzURQDF13Ujf79b63GJxZCCCGEODtN2fAxqqZye6tBANS168HSnqLdNI6v3jU8haX6mqVY29EzSwCf9vqKf/YvpdRXSlZxJhGmCGpF1eb82hcAMGRIBL/+auLXXwPhQ58+0wC45RYnXbr4QvosLtYDq8hIjZQU9ZDrPBgM1mN7sBPsrA6WoqKewmr9rhItFRIStKM3A0pLr6e4+IUjttm9exdDh96N2+0mJyebsWPH+8/9+utcNm5cz8GDBURGRnHffQ+G7ePSS3swd+5s7r57CL/8ModLLrmUv//+K6jNnDmzSEtrxAMPPMIvv/zMvHlz0DSN9957mw8+mILdHsOgQcGB0L59e/ntt194550PABg8eBCXXnoZNWvWrNTzCyGEEEKcyfYWZZAUmYzVePQv+3muXD7f8CnbCrawJPNvthRsJsYSy/VNbgICwVKGY0+1j7O8wENlMksA0RY73ep1r/D8okV6Rb3Vq0Mnpl17bSRZWUUYDjtVPg0vIgJq1Ah8l+7TxwucHsGSTMM7Ccqn4U2c+DFvvPE2zzwzHK/XCwSm4U2Z8jU33NCHV18dHbaPCy+8hD/+mI/P52PFimV06HBOSJudO7fTunU7AP/5gwcPEhkZRXx8AiaTiTZt2gVds2HDOjIy9nD//fdw//334HQWk5W1rzofXwghhBDitLO9YCs3fHc1Haa05P5f7qnUNXfOuZ3nFo3ksw2fsKtwJ62T2vJW9wlEmaOAQLC0t6j6g6UidxEAdou9Wvqz2fT/ejxK2PPr1oWGFSUlh2aWAsFS06ZqSNtT1VmdWSoufuGoWSCA5GQ7eXlF/8oYUlMbYLVaOXBgf8i5bt16MGnShLDX2e12atWqzVdffU6rVm0wmUL/KjUNDAb9JVVVreyY5j+mHw9+WU0mM+effwGPPfbkMT+TEEIIIcSZZsSCx/irrFrcrB0/4vA4iDZHh227YO8fDJ57J/udWaTGNODDKz+laXyzkGxU3ejyaXjVHyw53IWAvh6pOphMGhA+UAL486nf6dLqB4pffNV/rLhY/29kpIbZHGirVNzNKUcySydZYeFBcnNzSU5OCTm3fv1a6tdPrfDaSy+9jE8//ZhLLgmfMq1fP5WNG/UNv5Yv/weA2NhYHA4HRUVFeL1e1qxZFXRNs2YtWL58GS6XC03TGDfuNUpLXcf6eEIIIYQQp70lmYv5fY9emGFI+wco9ZWyJntV2LaapvHw/KHsd2ZxeeqVfNP7e9oktQ07ba9WdG0AMourfxZPYTUHS+Xrjyoyb5GdyPffw7A3UKyisFC/JiZGn4Y3cWIJCxYUV8t4TpSzOrN0spSvWQJwu908/PAwzGXhdvmaJQBFUXj00eEV9nPRRd2YMGE8557bOez5K6+8mhEjHuXBBwfTtm17FEXBYDBwxx13M3To3dSqVSukuEPNmjXp27c/9913FwaDgYsv7obVaquOxxZCCCGEOC2N/OtxNDSe6foCB5z6bKCVB1b4ix8canX2SnYV7qRP0//wzmWTjtiv1WglKSKZfY691T7m6piGp6rg9cLnn5v9G8xWZBHnU0Q01pnf47z7PnbtUsjPV4iK0iifAHX99d5jHsvJomiaVrnKBaeh7OzqmTqXnGyvtr7E2UveI1Ed5D0Sx0veIVEdzqb3yKf6aDCpJi0SWvLzzb+zvWArXT7vyI1Nbubdnh+EtJ+wMp1nFo5gwmXvc1PTvkftv8fXF7G1YDM778pCqcb5abfPuoVZO2ay8Y4dQfskVcXjj1v56CNLhed/+aWYp5+2krO5gE3ZSaynBc1is3jkihWM+7oBAHXqqKxYEZpNOpXeoeTkigNKmYYnhBBCCCFEBXYX7aLUV0rj+KYANIhNw26J4Y+M+Uzd/BV/7f2TQ3MPS7L+BuC8Wl0q1X/t6NqUeEs4WLYvUnVxlGeWzMc+De/wQMlg0MuD33ijh507i2jTRuXbb4q4UfkWgF23PIpSVMiK6YFMWXT06Z2XkWBJCCGEEEKICvy6ex4AbZP1CsIGxcCQ9veTU5LDkHl3ccP3V/NHxm+Avl5padZiakbV8hdvOJpaUfq6pX3VuG7J54P8PIUIUwRmo/noF1RS3bpFzJjhZOxYF5GR+rHI8W9Q68BqAPZ2v4Xi4SPxHDLbbtMmI7jd1TaGE02CJSGEEEIIISrw9abPMSpGbmjcx3/skU6P88vNf5IUkQTAlvxNAMzZOYsDzv10rX1hpafUlQdLmdW4bmnMGAtrH5+PLef8Y+4j3EKdTp0i6NzZR1RU4Jht8ockRpUAkJOjUHLvUArsgUCxATuIeP+9Yx7HySbBkhBCCCGEEGFszNvAigPL6V7/MmpE1Qw61ya5HZ9c9SUAGY4McktyGfb7QxgVI/8757FK36O8It5f+xagatWz/9Bbb+nT59Rltx9zH8WHLDO68cbvmDp1I6+8cliGyOHAuG8vyY30NT979ypgtVJgr0v9+iqTX93FT1F9iHr5eQx7dh/zWE4mCZaEEEIIIYQIY9b2mQD0afqfsOfLN5XdmLeeu36+nf3OLP7b+k6aJjSr9D3Or30BUeZo0leMY8Sfw45/0EDz5nrQpeU1POY+HA49M9aixXomTdrMxRfXIeaw5U/mtfr0uzZtVRRFY9kyI6CXDLfbNa66PYG6z96O4nIRf2V3bB+8R8Q747FO+1qfK3gakGBJCCGEEEKIMP7OXAjARXW7hT1fI7Im7ZI78OvueSzY+wetEtvw/AUvV+keqTEN+LPfYtJiG/HR2vfJdmYf77CxWPVgyYANVYXFi41hp9WF4/Ho5cIdDv1z166L0LQbwraNePtNAGzXdKNpU5XVq41s367gcCiUluptXAMG4njhZZTcHOzDhxE96kliBt8Jmzcf1zOeKBIsnWCZmfvo2fNihg69m/vvv4d77vkvq1atBOCnn2Zw441XM3Sovg/Sww/fR15ebkgfV1/dI+jz8uX/8NRTlU/3CiGEEEKIo1ufu4569vr+tUmHUxSFd3u+7/88sPUgjAZjle9T116PW1oMQENjwd7fj3m8/nGVVa0zqlYmTDDTu3ekf2re0XTrFknTptE4nXsAiI5OQlVrhrQz7NmN5efZeDqeg6f7ZTRqpOJwKLz2mr75rrV8D15FoeTuIRTM+gXH6DEcfH8yBd/9BM2bH/dznggSLJ0E9eunkp4+kfHj32Pw4PuZPDnwj6x7956kp08kPX0ibdu258cffziJIxVCCCGEODs53EXsd2bRKK7xEds1imvCTzfO43/nDOPmpv3YuVNh1ixTle/XsUYnADblbTim8R7K7dEzSyUHajNzpl4N70hjslo/Iy6uJ4qSxZYtRhwOBZdrDQARETXCXhP18gsomkbJwDsBSEvT7zl1qn6/0aNLg9p7O5xDyV2DcV97A56uF0I17in1b6r636SoVnl5eSQlJVd4rmXLVlXqr0+f3lx11TUsW7YUs9nMCy+8wp9//sbixQspLi4mO/sAffvewtVXX8uqVSt47723MZlMpKTU4PHHn2LNmlV8+eWnOJ1Ohg59mObNW1THYwohhBBCnFa2FWwFIC220VHbdqp5Hp1qngfAtddGkpVlYOnSW2nVKori4uFo2tE3hS0vNb6naM9xjFrnKCvO4MxNYlnZJKXS0opaO7HbBwPg9V4PrAOguPh7oC8REWkhV1hm/4Ttmy/xtO9AaR99PdcNN3hJT7f623TufHqsSTqaszpYGrXwKWZs++6o7QwGBVWt3ETP3o2uZ1TXF47YZvfuXQwdejdut5ucnGzGjh3vP/frr3PZuHE9Bw8WEBkZxX33PVip+x4qNbUBgwbdw/jxbzBr1kyio6PZsWM7H374GQ6Hg4ED+3PVVdcwbtyrvPnmBGJiYnnnnTeZP38eSUnJbNu2lS++mI7FUrl0rRBCCCHEmWZd7loAWiRW7RfXWVn6xK05c1Lp1OlFDIb9FBZ+Ahw5k1I7ug4KChmO4w+WnM7Qe1W01ZHNNoWXX36CceMe4qWXnvUfX7r0IgCiomIAj/+4Zc4sYm/rB0DRW++CSQ8n2rRR2batiOuvjyQuTsNY9dmIp6SzOlg6Wcqn4QHs2rWTkSMf58MPPwP0aXhDhz4EwOzZP/Lqq6MZOfL5SvQa+EfRqVNnAFq3bsOyZf/QsmUr2rfviMlkIi4uDrvdTkFBPhkZexgxQq+64nK5iI2NIykpmcaNm0igJIQQQoiz2upsfU1526R2lbzCRWnpN8AQAKZPf5jHHpuJ1fo9kZGjKSm5H02LrfBqi9FCzahaZFRDZslVEhqplJaGC9bc2GxvMWKEXtb7/vvf9p957bV7AYiODiQMlNxc7PcO0u9x4834DpuBZLfDzz87MZxBC33O6mBpVNcXjpoFAkhOtpOdXfSvjCE1tQFWq5UDB/aHnOvWrQeTJk0IOW42W1BVFUPZm1hQUEBSUmDhoVZWo1/T8G+IdmhmTD9uICkp2R+0lVu+/B/M5urb6VkIIYQQ4nS0Jmc1RsVYycySj9jY61m/vpjyYGnt2kTy8r4mKekyoqJeITLyTRyOMbhc/6WiLFOd6LqsOLAMn+o7pkIR5VxO/drEujnkZujfEcNNw7Nav+Hvv1P9n8NlpNq3D0ynix7xKIZiB8VPPIXz/ofD3vtMySiVO4PivtNTYeFBcnNzSU5OCTm3fv1a6tdPDTnerl175s37GQCv18vs2TPp3Lmr//yqVSsAWLduNQ0aNPT/7PP5KCgowOksJjZW/83Gjh3bAZg69Uu2bt1SvQ8nhBBCCHEaKiw9yLqctTSNb47NZDtiW7N5HnFx3bFYFrJ16+X+4263ws6ddSgomJyzIusAACAASURBVENx8WNoWjR2+0NERz8KhF/eUc9eD5/mI6s485jH7vWCx22EBr/Srf+SoPEczmL5hS++6F9hX7fd5iYtTQNVJfKl57B9Ow3POefifPAROEt+uX5WZ5ZOlvI1SwBut5uHHx7mz+aUr1kCPSv06KPDQ65/6KHHGDv2ZX74YTper5fu3Xty/vkX+M9v2rSRb7+dCigMGnQPv/32KzVr1mbkyCfYu3cPd989BIPBwBNPPM2LLz6L2WwmKSmZa6+9kbVlm4sJIYQQQpytnln4JE5vMdc3vvGI7YzGLcTG9gE0Vq4cyqJFTwLQurWPtWuN7NxpIC2tHk7nU7hctxEb24+IiEmoak2cztANaOvZ9V+Sb8hbRx173WMau9NZ9oPFQZ0GgXRSuMySqmbwzTc3Y7FoIcHUhRd6ee01/SLL/HlEvfEamslEUfq7Z1766AgkWDrBatWqzdy5f4Q916tXb3r16n3UPuLj43nhhTEVnh8w4L9ERkYGHatTp65/LVS5du3aM2nS5KBjHTt2omPHTkcdgxBCCCHEmeiuOQP5ftt0Wie1ZWiHh8K2MRpXY7c/gNm8HID9+9+nQ4dB/vOdOunB0oEDgQBEVetTUPAt8fHdy9Yw/RdNC96/6cqGvXhrxet8sv5jLku94pjGX1xcdk+Lg/ppXv/xcAUe5s9vQE5OMoMGufngA329elycRkGBQkJCIPtlmTMLgMJ3P8DXqMkxjet0JdPwhBBCCCGEAIrchXy/bToAT3UZhdkYbqqZRmzsAMzm5Xi9TXA4XiI7u29Qi44d9XU+ubnB2RpNq4HL1R9FUTGZVoT0fE6Nc2mf3IGfd85id+GuY3qGQGapmIS4QAbI61XIz4euXSOZPt2EohQxa5Y+M+m66wJB1ezZxVxxhTewT5KqYpn3M2psHO5K/FL/THNCg6XNmzdz2WWX8emnnwKQmZnJwIEDufXWWxk4cCDZ2dkA/PDDD9x0003cfPPNfPPNNwB4PB4eeeQR+vfvz6233sqePcdfKeRMNHXqjJCsUq9evUOySkIIIYQQItiuQwKUS+v1CNvGaNyK0biD0tLryc9fRknJfYFsTplGjfRiWzk5oV+1vd4OAJjNq0LOKYrCoDb3oGoqH619/5ie4dDMUqQ5gg4dAgUavvrKzNatRu69NwKjcSO7d9cHoFkzH4sWOZg7t5i0NI0pU0qoUUPPLFlm/4QxYw/uq672lwk/m5ywYMnpdPL8889z/vnn+4+NGzeOvn378umnn9KzZ08++ugjnE4nb7/9Nh9//DFTpkxh8uTJFBQUMHPmTGJiYvjiiy+49957GTt27IkauhBCCCGEOAuUZ3OeOf8Ff0Xhw5nNiwBwuy/2Hzs8WEpK0gONwzNLAF5vewBMppVh+7++yU3YLTHM3vljFUd/2FgsDmzGCH780Unfvp6Q8fz5p4MZM67FavUSFweNGmm0a6cGd6ZpRL7+CpqiVFj97kx3woIli8XCpEmTSEkJVH175plnuOIKfT5mfHw8BQUFrFq1ijZt2mC327HZbHTs2JHly5ezaNEievbsCUDXrl1Zvnz5iRq6EEIIIYQ4C+wu2glA/ZjQasTlTKbFAHg8XfzHfN/OCmpTw7ENgJyc0GBJVWujqskVBktWo5X69lSyirOqNPZy/ml45mJsJhsmE8TG6sFbYWFgPNdddy0ApaUmKogLMa1Yhnn1Skp7X4+vSdNjGs/p7oQFSyaTCZstuPRiZGQkRqMRn8/H559/Tu/evcnJySEhIcHfJiEhgezs7KDjBoMBRVFwV7QVsRBCCCGEEFVUnllKPSxYmj3bSFHZlptm82JU1Y7PV7Yha2kpns+n+9sqqNQaPhirVQubWQIFj6c9RuNuFCU37DhSIlMo9jhweBxVfoZDM0vRZrv+o167AZcrdDypqd6QYwCoKvFXdgfA3fPYik2cCU76xEOfz8djjz1Gly5dOP/885kxY0bQeU0LX4e+ouOHio+PxGSqntKGycn2aulHnN3kPRLVQd4jcbzkHRLV4Ux8j7JK9wLQsWFr4iP055s/H267Dbp0gUWLcoHNwGUkJ8fpF036Eleey9/H/I6PYlmyiBTDPvL2JVTw53QeMJekpC1Ag5Cz9RPqwh5QbU6SE2pV6RkM5akQi4MmdeuTHGUnrmyoqhooWFGr1n4yM2swdaop/BgzMvw/xnS7AP6Fv+/T4R066cHS8OHDSU1NZejQoQCkpKSQk5PjP3/gwAHat29PSkoK2dnZNG/eHI/Hg6ZpWMrD5Ark5zuPeL6ykpPtZGcXVUtfAHv27Oatt8ZSUJCPz6fSpk1b7rvvIXJzc3jqqcf54IMp1XYvgKFD78blcmGz2fD5vDRs2IhHHnkC42E18p944n+8/PLr1XpvEVDd75E4O8l7JI6XvEOiOpyp79HGA5uItcbhKTKS7dCfb/FiM2Dj77/hn3+W4HBcQmJiT2rWLAJNI+HFlygydgMfvP66i7ZNe6H1mUCyK4uN++Mo+OpbPN0vC7qPxdKS2FhwOBZSUtIlZByxhkQA1u3ZQowvJeT8kezfr48XSzHeIhPZziK8XgtgpaDAS/nXf4cjgnbttpCaWpOyGmtBzEtXEQf4atUmr0YqVPPf96n0Dh0paDuppcN/+OEHzGYzDzzwgP9Yu3btWLNmDYWFhRQXF7N8+XI6derEBRdcwOzZswGYP38+nTt3PlnDPi4+n4+nnnqMW265jUmTPvEHRh99NOlfve+IEU+Tnj6RCRM+xOv1Mm/enJA2EigJIYQQ4mxV4i1h+8FttEhoGVTcYcuWwNflc8+9iksv/Y22bR9jzx4FJTcX484dFDbtCEBUlIb3vM7k7Mgkvm0dnEThnTE35F7lFfEslt/DjqVBbEMAdhzcXuXnKJ+GZ4tQ/aXPzWUJpcLCQDuHI5qoqIpnYBm36+uuioePrPIYziQnLLO0du1axowZw969ezGZTMyZM4fc3FysVisDBgwAoFGjRowaNYpHHnmEQYMGoSgK9913H3a7nV69erFw4UL69++PxWLh5ZdfPlFDr1ZLly6mfv0GdOhwDqCXiBwy5AEUxUBubiCjtnz5P0yc+A4mk4nk5BSGD3+avLw8nn9+JAaDAZ/Px9NPP09ycgqvvDKaffv24vV6ufPOeznnnHOPOIaWLVuRkbGH5cv/4csvP8XpdDJ06MM88shQfvzxFzZv3sjYsWMwGBRat27Hffc9yI4d23njjVdQFIXIyEhGjBiF3X7qp06FEEIIcebSNI03l4+lyF3EI50eJ9IcefSLKrAxdz2qptIqqbX/2IYNBr78MtxeS3DttZFMea6Ep1hAa58+Dc9uL1smYjSS0DgWVkPexhziD7tWVevi8ZyPxTIfo3ELPl/wRq+N4/TPWwu2VPk5iov1/8bYA0Ge1aqPq6AgEARqmgGbrSbgIxzjDj1Q8zVsVOUxnElOWLDUunVrpkyp3PSyK6+8kiuvvDLomNFo5KWXXqrWMY0aZWXGjKP/ERgMoKpRleqzd28vo0aVVnh+9+6dNDmsmojVagtp99prL/HGG29To0ZNXn99DHPnzqaoqJBzz+3MwIF3smnTRnJycli5cjmJiUkMH/40BQUFPPjgvUye/GWF9/f5fCxevIjevW8AYNu2rXzxxfSgKY3jxr3GsGEjaNy4Cc8//zRZWZmMG/cqw4aNoF69+kyf/g3Tp3/N7bcPqug2QgghhBD/um82f8mLi58DYJ9jLxN6HtveRADrctcC0Cqxjf/YJZdU/P1v714Dg55swA5asnCzfiwtLVB6OzFFz9rkb8wh3usN2aPI6byX2NhFRES8h8PxWtC5RscRLDmdekAUEx24X/nXvEODJYCoKDP+YElVMWTuA1VFcTgwL9Wr/vnSJFgSJ5SCqqpHbFFYeBBFUahRoyYAHTt2YuXK5Vx77Q2MGDGMoqIiLr20B61bt2X27JmsWrWC1av18pOlpaV4PB7M5uDfgrz44nPYbDY0TaNz5/Pp2vVCli//h8aNm4Ss/dq9exeNG+v/SEeO1P8HtH79OsaMeQHQNwhu0aLl8f9RCCGEEEIcoz1Fuxn+5zBMBhPR5mimbfmatLhGDDt3+DH1ty53DSweyuI9vbm1kr+fz8wNfIeyWjVSUwMFyMr3WsopjqDZor/wXHRJ0LVu9zWoahIWy09AcLCUFJFErDWObflVD5YOFunBT7w98F2w4mCp7AeXi7ibr8O8eFHQeTUxES0pqcpjOJOc1cHSqFGlR8wCldMXoBVXyz1TUxswbdrXQcfcbjcZGbuJiChPHStB1f48Hg+KYiAtrTEff/wFS5b8zbvvpnP11ddiMpm57bY76NkzOBN3uBEjniYtrXHI8cODKtBLsx/OZrMxfvx7FW7QJoQQQghxIv1v/v0UuQt589J3uLhuN677vhevLn2Ja9Kuo0Vi1X+puy5nLcz6i6+At14MLjwQFeWiuDh0JpDLE/gqfccdHg6tnZWUpP9yPJtkIiZNwNnlEiZMsNCvn4eUFA0w4/W2xGz+E3ABgf4VRaFxXGNWZ6/Cq3oxGSr/lf2gwwNEkBAbCOQsFv17ZUnJ4cGSfjzyrdcxL16Ep9N5+GrXQXGV4LnwYjwXXESFmzCdJU5qgYez0bnndmb//kwWLPgDAFVVmTBhPL/8Elj8FxMTg6IoZGXpm5GtXLmc5s1bMG/eHLZv38rFF3fjrruGsGnTBlq2bM2CBfriwPz8PN577+3jHmODBg1Zt05PRb/00nPs3LmDxo2b8PffCwGYN28O//yz5LjvI4QQQghxLFxeF39k/Eb75A70a/5/1LHX5f4ODwGwKntFlfvTNI31uesC/buCiyH06/eF/+c77gjd5/PjJ1by7LPBv4BPTNQDkfciHmLHzzt499ZlvPCClcGDA0GRz9cQRdEwGneF9JkW2xiP6mF34c4qPcvBIn3fpKSYwPotqzV824sv1rNQ1h++RYuMpOCb7yl6fzKFn35Nyb1D8bZpV6V7n4nO6szSyWAwGBg7Np1XXhnNRx9Nwmw2c+65nfnvf+9i//7ATs2PPfYUzz77JEajkTp16tKjx+Vs27aV1157kYiISAwGAw89NIy6deuxfPlS7r33Dnw+H3fccfdxj/HBBx/ltdf0/HOrVm1o0KAhDz74KK+8MprPPpuMxWJl1KgXjvs+QgghhBDHYlfhTjQ0WiW18c96aZHQCiAo6DmSNTmrmb3jR5IjUjAZTBS6AtFRYaFCYWEgo/LOO/eQkdGJLl2aMGSIh5cHb+Guztv5Xu3NTc1X0+vhtJD+y/c2+rukPS1YT9/5XwGQkRHIVfh8etU7o3E7Pl+zoOsPLfKQFhc6O6giRQ49SEuODQRLYSYSkZyscsUVXnA6MW3ehPuibofMyxPlJFg6CZKSknjllTdCjteqVdtfSrxdu/ZMmPBB0PlmzZozadInIdc98cSRSzqmp08Me7xjx0507NjJ//nHH38BoFGjxiH3btCgIe+8c+yLJoUQQgghqkt5Se2GsYEgpfznPUW7j3r9rsKdXP9dL4rch6SPXIGadYWFCu+/r0cYw4e/hMkUz2efmVFVDwD2l55liFrA9/SmRZ9moIRmm/yV8crkKUmgQYI90PbQYOlwjeP1YGlbwbajPs+hSkp9oHhJjIrzHyuvhneo0aNLMRjAmLVPH0vdulW6z9lCgiUhhBBCCHFa2evYA0A9e33/saSIJCwGC5mOvUe8dk32Kv4z8waK3IV0r38Z3ep1563lr1NUUJPyiXQHD8Lff+sLkB58cByFhZNR1Tr+PsxLF9Ojhpu5Uxw0bRYaiADExAQfn6f10MdZsBVIBUBV9QDPaNwRcv2xVsTz+nygqMRZA8Gf2RwYS3R0KQsXeqhZUz9myMzUx1KrVpXuc7aQNUtCCCGEEOK0kunQv+DXig4EMIqiUCu6NvuK9x3x2omrJ5BTksNzF7zIF1dP4952Q1l9+2a+7P6Hv83YsVY2bjRw0UV/EBfXGY/ngqA+DLm5qCk1aNdeIyIi/H0OD5bKReZk+H8uzywZDKHBUsPYNBQUtlUxWPKUBUvxtkCwFBGx6ZCfzf5ACdDLhQNqzdpVus/ZQoIlIYQQQghxWtlXrGePakcFf8GvHV2H/cVZeHyeCq/dWbgDg2JgUOt7/OudTAYTxYWBKgi//GJC0xRatVqHy3VzcAelpSjOYrSEhCOOMTo68PNjj5Vy/vl64YVip4KSlwuApsWgqolhM0sRpgjq2etXObPk8aplwVJgfNHRgZLghwd3gcySBEvhSLAkhBBCCCFOK5kOPRtSMyp46litqNpoaOx3ZoW7DNDXK9WJrovZGFz1IC8vtER206Zb8Xi6Bx0z5OcBoB4lWDp0J5Z+/Tx8910JJoMPB9GYVgYq9vl8Dcuq4flC+kiLa8QB5/7gtVVH4fWpYPARbw2Mr0aNQNVlp/OwcZatWZJpeOFJsCSEEEIIIU4r+4r3khSRjMVoCTpeJ1ovUrDPEX4q3gHnAbKKM2kUprpcuGCpUSMzmhYTdEzJLcsKxR85WAoaVx0NRYEom48i7JhXLPOf8/nSUBQPBkNGyHXlFfG2FWyt9L28vuDMkqLk0qTJDB57TC8SZgn+I8O4r6zAQ606iFBS4EEIIYQQQpw2NE0jqziTJvHNQs7Vjtanku0q3MF5tTqHnP8jYz4AF9XtFnIuPz80WKpb9z8hxwKZpcSjjvXLL52oamBf1+gYhUJnDKaVy/1tAhXxdqCqqUHXJ0ekAJDnyjvqvcp5fRooKrHWWADM5gUoisrIkVuJj3fRpIka/DxZ+9DMZrTEoz/P2UiCJSGEEEIIcdooKM2nxFsSsl4JoFON8wAYtfAp1uWupW50XQpKC1i2fynxtgQOOA8A0K1e95BrD88sWSxeatcOzUCVrzc62jQ8gO7dg6fWxcQb2Lc/HvPyZaBpoCiHBEub8Xi6Bbe36lmtqkzDU1U9WDIZ9BSSyaSvefL52jJoUOhaLkNmJmrNWsHzBoWfBEtCCCGEEOK0sSRrMRAorX2odikdePicR3lj2Wu8s/KtsNe3SmxDq8TWIcfLg6WICBclJTYaNvRiNIZeb8jTszxVmYZXLi5OY4MWi5adg5Kfh5aQiMfTFU1TsNk+w+W6CwgEbXaLHiwVVilYAsUQyB4ZDLsA8PkahDb2+TDsz8J7yL6bIpgES0IIIYQQ4rTx7ZapAFzb6Pqw54d3fpoOKZ3YnL+RhrGNAIg2R/PBmvfontqT/zS7BYMSmkUJTMPTA41GjYxAmExMFabhHS42Vi/ZfZBYlMJCtIREVLUBbndvrNYfMJv/wuO50N8+xqJPpSssrUqwpKAYAqXBjcbyzFK90GfJyUbx+fBJJbwKSbAkhBBCCCFOC06Pkzk7Z5Ea04D2KR0rbHdlw15c2bBX0LFL6+ubwpaUwPY9Cmlpwfsg5ecrxMW5KCiIBCA1Nfw+Sf6y35WYhne4+LKtj/KJJ76oyH/c6RyK1foDNtsnhwVLZdPwPFUMlhR97EbjZiyWhXg85wKRIW39eyxJJbwKyeREIYQQQghxWvg9Yz7FHgfXN77Jv0dSVd17r40uXaLZtCn4a3BenkJiYo7/s90ePlgylFXDU49hGl55ZimPBAxFgQDI6z0PVY3GZFoV1N5evmapCpklTQNDWWYpIiIdAKfzgbBt/XssyYa0FZJgSQghhBBCnBaWlq1XujhMNbvKmjVL319p/frA12BNg7w8jaSkQPnuyMgKgqUDepEINaVGle8dF6f3mU88yiGZJTDg87XCaNwMuALtrXEA5LpyK9W/pmlo/ml4Pmy2r/H5UnG7rwn/LPv0zX0ls1QxCZaEEEIIIcRpYfn+f1BQaJ/S4bj7yskJZKZ8vj14PEbs9lL/scjQWWsAGPZnosbFgc1W5XuWZ5b0YCk4W+T1tkZRfJhMm/zHakfVIdIUyfrctZXq3626QTNgMIDBsAdFceLxdAbCVKoAjFllmaXassdSRSRYEkIIIYQQpzyf6mPlgRU0S2jurxJXVV5v4OedO8Fg2I3BsB2z+R4ALJbAPkdWawWZpf1ZqDVqHtP9gzJLhaHBEoDRGAiMjAYjrZLasDFvA/N2zTlq/yUeJ6hGFAWMRn0jW58vtPx5OX8Z9KTkqj3IWUSCJSGEEEIIccrbXbQLp7eYNkntjrmP3NxANmnv3qUkJrYmMbE9Xq9eMc5sDmRYTOHKoLlcGAoKUFOOL1jKIwHDwYKgc+XBkskUnEV6svMzADy36Gkc7iKOxOVzgWbAaNQO2V8ptMR6OcXpBECLiKjCU5xdJFgSQgghhBCnvNwSvfhCjajKBCpOoqKeIj6+M/HxnYiOfhhwULbcCICdOxPw+erict1AXp5eAOHQmXVmc2ivhgP7AVBrVH29EhyWWco+EHTO52sJhAZLXetcyB2t72Jj3gbumDMATQvOeGmaxvaCrXy3ZRpPLnjcPw2vUpmlUn3aoWat+pTCs4WUDhdCCCGEEKe8vLIiBwm2I+9vpCjZ2O2DsVp/RtMiUJQSTKbN2GyfUlLyH2AyANu3Nyc3dx2KopCXp+cPbLZAIBIus2TYnwVQLdPwjPv3B53TNDteb1PM5n/QizwEApgXLhzDjoPbmb/nF3pOvYSf+/zGb3t+Zermr1idvZLN+YF1Too2iWir2R8seb2NKh6Qq0S/9zGsvzpbSGZJCCGEEEKc8vJc+mawCbaKS3YbDPuIj78Aq/VnPJ7zycnZTm7uCkpKbgcUDhyI9rd1uYzs369/FS5LsByWWQpds2TYf3yZpVh9j1nySfBnqQ7ldvdCUYqJjHw16LjJYGLMxa8DsDp7JV0+60C/mTcydfNX/kCpZWJrvrh6KrGWeGKs0RiNW/H5agHRh9/GT3GVVd6TaXgVkmBJCCGEEEKc8gLBUsWZJZvtfYzGLJzO/1FQ8BMQhao2wuEYT05OJtu36wFH8+Y+AHbu1L8Kl5Toa5kiIjT/HkUJCaHBknG7nq1Rax5bqW3/PkvmFH+W6lBO50P4fA2IinoVi+XHoHMNYhuy6raNNIprzM7CHRgUA2Mufp2swQVk3JPDLzf/SY/Uy9E0AwaDitG454jrlQCUkhI0sxmM4avlCZmGJ4QQQgghTgN5JUebhqdhs01F06IoLn6M0HLZRrKz9aDovPN8bNxoZONGA126+ChPsFit8OefTn7/3UinTmrw5T4fEVM+RrNacV94yTE9g9kMUVEaeb5k/35NQU+gJXDw4GfEx/cgKuop3O6rg87Xiq7Nwv7LcPlcaJpGpFmvb24xWvxtVBWMRnfZkNOOOB7F5ZL1SkchmSUhhBBCCHHKK1+zlBgRfhqe0bgOo3EnpaW9gPCbJJUHSzfcoNcQ//13PaAqD5ZsNo0mTVTuvNODogRfa/l5NsZdO3Hd3A8tKemYnyM+XiOfOBRnMYojtLqdz9cGj+dCTKZtKEroZrSKohBhivAHSqHXg8HgAUBVj7J/UqnrmPaLOptIsCSEEEIIIU55uWXBUnwFa5bM5qUAeDwXV9jHgQN6BHTuuT7i4jS2bi1fs6QfP1LcYP1uKgAld9xdtYEfJjZWo8Cr7xMVbt0SULaRLFgsR99b6XCaFsgsqeqRC1EoLpeUDT8KCZaEEEIIIcQpL9+Vh0ExEGuJY9MmA/PnG8nNVXj1VQu5uV4iIiYC4PF0rbCPLVsM1K6tYrFArVoqe/eWr1nSz0dEhN+IFsC0cSNqVDS+Vq2P6zni4jSKvBF4MPkLRhzO5eqLpilERHxY5f5VFQyGygZLJVIJ7yhkzZIQQgghhDjl5blyibfGYzQYueiiKADat/excqWRmJg/ue++vdhsA/1FDTSPF/Oq5SguF95WrclyJ7J/v4ErrtCn4NWpo7Fhg0JhYaDAQ1DcoGkYt27B1zANSksxbtuCt1VrQubnVVF5kYeDxGLJ3Be2jao2xO2+DKt1LibT33i9XSrdv88HRqOz7Oe6R25c4kKrKcHSkUhmSQghhBBCnNI0TSPbeSCkuMPKlfqao5EjLyMhIZ+cnOcAWL7ARc06sSzs9TpxN15DzH9vZe1a/WtvmzZ6JbzatfUCDnv3Gigo0AOg8n2QACLHvUbCBZ2IfvwRIj7+AMXtxn3ZFcf9LNFllbyLsGPIzAw65/NBVpY+FqdzGABRUS9WqX9VBZMpH1VNwedrccS2iqtE1iwdhQRLQgghhBDilLanaDf5rny0eS+ydGnFX19//VUvvDDlqV1oGLjZMA1vwzQsCxew+fnvAWjbpBjQM0sAW7cayCuroxAfpwdQSkE+Ee+mAxAx5SOin30KNSqakjvvOe5niY7W75vGDjI2lwSd++wzMx06RLF5swGvtwtud3cslt8wGldXun9VVTAaXZSWXsURv+qXlqL4fGiRUcfwFGcPCZaEEEIIIcQpbWnWYsjswNaZN3H11YEv919/7QxqN2OGCaWokKStSwAoUW0U3vswAKvXmwG46LlrwOmkVi09MBo0KIJ9f+wAoPY374CmYb//Xgz5+bj69sfV7//wdDyHovHvosVXvCFuZdntgezV1MUNg87t2GHA51P8WTCX6z8AWCx/Vapvraxrg0HF7b7qiG0Vh0O/JrriTWuFrFkSQgghhBCnuKVZi0ENfG01GjU6dFDp1s1H+/Y5rFypZ5R+/tmE1uQT9rkb+dv+3uQOLlnUlWXXNCKxsJDUvYtwfDGFhHpD/G1+2NAcgLofvYzSIw3rnFm4L+pG0ZvvVPuGrYfGJjt3KeB0QqReBry8hHl54QmPR1+rZLHMpaRkcIV9Tp5sJilJ5YorHIAdgwHc7m5HHEd52XIJlo5MMktCCCGEEOKU9s/+pZi9gb2NfD6FmBg9jXLzzYv9x4uKFN5PV9luaOw/9uuvRvKSmrAzN5Y255rBYsH2+ad07erj3HN9QfeJVfOJevJxAJzDnqj2QAnAcMi37/W+5lgW/un/XB4sQgm+TQAAIABJREFU7dunr1tS1YZ4PJ2xWOZhNG4N05sPs/kbhg2z8d//RpKYqBd0UJQIKtprqpxklipHgiUhhBBCiCrw+Dykr3iTNTmVX0cijl2xp5h1OWuob20bdLw8WOra9Q8AIiL0aXWrHI1YpbWlVSsfNpvGL7+YmDJFn4LXuqMBb4dzMK1bQ+0HBvw/e/cdHkW1PnD8OzNbk01vEAgtdAJI7wIiKthRFHvDdr3X3tvPhohd1HvtIthBEBAVkC5KkQ6hB0iBkF52N1tnfn9MspslCQld8HyexyfJzJmZM5NV5817zntYLg9iQeIY+rOcu9MWIwGGPRlosoy3W48Tcz+O4Pdb6YBx/rzAz1VV+XJypGrb9HWdzOZvyc2VAkPtJCmP6Ojz8PsfCbR1uTpU7ouqtx9SeVVmKeLobuQfQgRLgiAIgiAIR2BOxixe+PMZhn0/kLl7fznV3TnjZZdn4df8JMptQ7anpenB0cCBM/jll1HMmaPPX1rK2fg0AwMH+unXz8/WrQovvKBXfOvQQcV12SgkVcX800yMK/9kaPF0lja/nhd+aIm/UWMA1PgEMJtPyP14PMHvS4ihaOGmwM9V6z3t3y9Xa38BmmZk6tQCunSx8csvfwEubLZHMRpXk5l5XaBtero+t0nTWtXbD9khhuE1hAiWBEEQBEEQjsDCrN8C37+2enzIPk3TWLH/D974awI55dknu2tnpGJ3MQBGb7C4wiWXeLnnHg/gQlF2M2xYLikpesrlAMkA9O7tZ9gwX8i5kpM1XLfdSf6eAxT+tYn8PQcoyC6gaPVGtJhYKsbeBYD70stP2P38619e+vb1MWSI3red+yyBdJPLpWeUqobhAWhaBOXlH/DQQ28A8OOPJSQkJGKxTMfr7UlGRrC0+OLF+rwuWa5/+GDVMDxVBEuHJQo8CIIgCIIgNJDX72XBvvnEWxNoFZXKXwdXUeIqxqAY+Sr9C2bsnMbavDUAzN3zMzMv/xWrwXqKe316K3HpwZLiiQFg4sQKrr7ahySBouxEklR8vo41lgvq1ctPZTwQkJSkZ6MID0cNr1kyu+I/9+M9ezC+zl2P+31UiY/XmDWrgu++M7B4sYHPuYXX07cj9eoemLNUUCDjcgWXQHK7R2OzhVNUBD5fCzyeoSxc2Ieysju5557g3KTJk/XhhoqiHXrZGoJzlsQwvMMRwZIgCIIgCEIDTFz7Jt9u+4r8ijxuTbudZFsTVuWu4JzvB1LkKsLp07MDw5ufT2bZPtbnr+M/C+7io/M+R5bEYJ6jVewqAqDsgD5Erls3Faky8WI262sn+XydMJlAQkVDJiXJRaNGWmB+T5VGjeoJIiQJ31ndj2v/69K2rR64TeFGlJe28OrMYGYJ9OxSq1bB/ppM+ve7d3dhzZpZjBgRzAiNHu1l5045sEivFDxNnaRiPQg9HuXQz2QiWBIEQRAEQahHZtk+XlrxHBbFwsWpl/FEn2fwa35+3DWdzQUbaRbZgktSb+fyNlfSOb4Lbr+bK2ddwqzdM3DMsfPxeZOwmcRf8I9GsbsYnLFsXdGCRo3UQJChKDsIC3sbvz8Zt/sqJAm0yhkmPc9yA3KNoOHvNOKsTRs18P3mXaGlw0Gft9SqVbBaX3m5fjMFBRJlZcEbmzDBxS23ePnmGwP33adnMeUGxOZy5Uq8aqwIlg5HBEuCIAiCIAj1WJy1EID/6/8it3W+M7B9/pVL2O/IoaktBanam7lZMTPpgq+5fd5NLMiczwcb3ufhXo+f9H6fCYpdRTDvNZzlJh59yBUIgGy2R5AkD3b762haZMgxPXrXPM9nn1WchN42nM0GsqyhqhKyS++b0xn8DFWviAfBYKmwUArJQA0cqAdU8fHBLFRDgiWpMljS4uKO7gb+IUROWBAEQRAEoR4zd00HYHjzC0K2K7JCSkSzkECpSpw1jskjvyXGHMPHG/+H3Wuv0Uao3/5cP6y/ldR2Tu64w1u51Y7RuBivtzcez0U1jmnaylhjW0MCiJMtPd2OCTfFTr3yXvXM0rJlhsAwQp8vGEipqkR2dvDz1qKFnqGKqJa4bMjyUMHMkgiWDudv+LERBEEQBEH4+8gqz+T3nKX0btSXZpHNj+hYm9HG7V3upthdzJQtk05MB89wB/P0r336eTBUjokyGLYiSRpeb+1rIcUn1Jyb5PXW0vAUi42F1PBcivxRSAUFuFwSRqPe9++/NzJqlJV9+yQWLAiNfl59VQ+unnzSjbEyLrTZjiyzJBcWoikKWlT08bmZM5QIlgRBEARBEOqwOncll/04Eg2NGzvdclTnuK3zHYQZwpmS/vlx7t0/Q3GJnjlJjAmue2QwbAHA7+9U6zEJ1YKlm2/WFzY66yx/rW1PtZgoP8XEIG/dissVzBQBLF9uoFcvGzfcoM9pqqpyl5mpv8I3ahRsWz1YakiBBznvIGpCYsMa/4OJYEkQBEEQBKEODyz6N/vtOTzQ42FGtx1zVOeIscTSPrY9mWX70A4tzybUq6RUf2Yx0cGXekXRgyWfr2OwYbVnWz1YGj/eTUZGOc2b/z2ffUISqCjk/pmJ2y2F9P1QN9/s5bbbgqvaVi9YUX0YXr2ZJU1DPpiL2qjRUfb6n0MES4IgCIIgCLWwe+3sLN5Bv+QBPNHn2VrnJTVUo/BkPKqHQlfhcezhP0N5mT4ELSoqGEQYDOlomoTP1yHY0OHgWZ7n7Oj1VF9CSVH+XlXwDtVtkL6Y0tK5+jhBiwW+/trJxIk1C1JERGjcfHNwPGF4uAaahmHNapLefSGwvb45S1JpCZLLhZokgqX6iGBJEARBEAShFlsLt6Ch0Sku7ZjP1dimrxF0wLH/mM91IuWUZ//tClHY9+jZo8hAwTsNg2ELqtoCCEZFckkxz/Mcc4eNP61Glp01NAqAv7brN2i1apx7rp8xY3w12kZEQLt2Kv376/siC/YQ260jMSOGEfPf1wLtZNQax1an7NsLgJrU+HjcwhlNBEuCIAiCIAi12FywCYBO8Z2P+VxNbCmAvl7T35HT62T0rEvpNqUj/5o/9lR3J8Dtd+NbdTsQzCwpym5kuSh0CB4glZQAoEWfXgULUlvr97XRo2fJLJbgvri40KAnIkJv++KLbm4ZU8qQcReh7M/BM2AQpZO/DbQz7tx62Guap30PgHfQ2cfc/zOdCJYEQRAEQRBqURUspcV3qaOFhsk0m7CwcVgsHyPLe+s8V8c4vRDBlspz/t0sylrAkuxFAMzfNxen13nCruVX/ewq3onb7663bYmrOPC9XqBBw2Z7FAC3+4qQtnKpHiypp1l1t8REjQiLhw10BfTMUpW5n+wIaVsVLHXurPJui9ex7N+L45EnKJ0xB88FI5Flfb+huKDuC7pcWL7/GjU+AfeImmXXhVAiWBIEQRAEQahFeuEmjLKRtjHtat1vsXxBVNR1hIdPICLiIWJju2Myza21bdVQvvTCLSesv8fir9xVAHRL7I5f87PiwHKWZS9h3IrnWXNw9TGdW9WC2ZFdxTu5aMZw+n/Tg35fdWdv6Z7DHltYUQSSn8T2O4mIAJNpHibTb3g8Q2sES1KxHlhpMTHH1N+TTZIgtZUfD3q1v+qZpVTfDp5kXODnmNxtmH/4HtOsGVg/eA/NbKbirnsC+1VVH38YoxXVeT3T/LnIxcW4rrkeTKbjfDdnHsOp7oAgCIIgCMLfjV/1k164hbYx7TEptb1Qalgsn6JpMuXlnyFJBdhsT2CzPUBJyXxUtUlI68SwJMIMYWSW/z2H4f11cBWyJPNAj0e58ZcxTNr8KX8e+INSdwm/5yzllysW1Dim1K1ncqLMdWdyJqwax8S1bzKi5UUYZIVZu3/Ep/poFN6YbHsWg7/ry3vDPuTi1MtqPb7QUQKagqWyarjV+iEAdvtLQOjEpNM1swTQqr3C+nT9e4slmFlSsrOwEiz0kPz8vUTye+Bn1yWXo0UEJnMFRPvqLiRi2LENAM+AQcfa7X8EESwJgiAIgiAcIqN0NxW+CtJqna+kER7+FEbjBtzu83C7RwEgy7mEh79OTMxAiosXVRYg0EmSREpEM7LKM0/ODRwBj9/Dhrx1dIjtxPDm59MhthO/7v05sH9r4RZUTUWWZDRN4521bzB15zfsLNpJuNHG7Mvn1vGcYMbOaXhVL7N2zwCgfWwHHuv9NCNbXsTXW6fw6NIHmLj2LS5OvYyN+euxGW20im4dOP5AqZ4tslgkZDkXo3EBXm8f/P6a1wvOWTq9MksAqanBAEnTqpVI37YVK8H1pcLaNKb8lleRNA1cblw33lzr+WyeujNLcnYWAGpKs2Ps9T+DCJYEQRAEQRAOseLAHwB0iq9ZCa+i4mduvfU8HnmkgE6dngtsdzqfAcIID3+BsLD3sNtfDzmuWWRzthdvo9hVRIwl9kR2/4hsKdiEy++iV6PeKLLChLPf4LGlD3J7l7tZceAPvt/+DdfPuYouiWeRGJbEyytfwKyYSQ5vwn5HDi/8+QwP9nyMtPjOFDjzeWXVS7SIbEF64RYySnczrNlwnun3AhU+J90TewZKsF/X8Uam7viWP/b/zllfdGC/I4doczR/XLuWeGs8ALsL9Bf7qHAzBsNKJEnD4xlW633IJXpgpZ6GwVLr1sGhivv2VAZOXi/mGdMwW24AV+XOrz/F1bzu83zwQQXj7ynkar4D7q21jZKpB+z+Jk2PQ8/PfCJYEgRBEARBqGZH0Xb+b/lTWBQLw5uff8hela++2s9PPz3I4sUjycioXghBwum8F4tlMhbLJ7hcY/D5egb2to1pz/x9c9letI2+yf1Pyr00xF8H9flKPRv1BqBvcn+WjFkBwNCUYWSVZ/Jb5jx+y5wXOGbWNbPobOvFOd8PYHHWQhZnLaz13GnxXXiu/zjaxbavdf91HW7kj/2/s9+RA0CJu4Sl2YsY1WY024q2smTvnwDE2sJQFH2cms/XqdZzKdv1CnBqs9MvY5KSEgyWHr4uE2iEaf5clLyDGAalwTJ9Xy0j7kKMGuXj1vcvwrA7g7pKPMjZmajxCRAWdlz6fqYTwZIgCIIgCEI1r6x6Cbu3nP+d+wmp0W1C9plMcygs1F9s7fbaVv40UV7+DtHRl2K1fkh5eTBYqqqIN23H9/Rp3O+YFrk9nlbnrgSCwVJ1TSKaMuPSOWwtTGdr0RZ+z16KIhsY2mIoJUUufrp8Hr/u/ZmVB1YwJf1zAK5qdw29GvWhZ1LvWjNz1V3Z9mqa2JoSY4ml1FPKJTPO5675t/G/9e+xIX8dFOpD8uJs4RgMenGMQ0uGA6CqGFf+ib9Zc9TkJjX3/8117qwyOGUn12dNoKvtSrxaEtZPPgBAGdwvGCxF1H8uLSEBadMGpPKymvOZVBUlJxtfp2NfO+yfQgRLgiAIgiAIlTx+Dwsz55Ma3ZpRbUYHtrvdcPfdJZx//kYyM7sHtmsaNRZA9XqH4Pc3x2yeitfbH5frFgCGNz+fllGtmJz+GS5/BW8NeQ+jYjwp91WXCl8Fi7IW0ii8MS0jW9XaRpZkOsWn0Sk+jSvbXg1Q2W8XkeYormp3DVe1u4aXBr6CT/USYaon/VGNJEn0bzIw0JeOcWmkF25mQ/46Wka14vqWr/EiYLXKGAzpaFoYqtqyxnmU7dv0Cm/DLzjiZ/B3YDbD7P/MIeLRT/Hf+TPes4dg+n0pnnPOxdYxOFzO0IA3d39L/feo7MnA1+WskH1yfh6Sx4Pa9PTLvp0qIlgSBEEQBEGotLlgI06fk0FNBodkfqZPr+Cnn1L46adXOPvsYEW7vDyJpCTtkLNIlJV9QVTUlURE3IfP1wGfry/RlhjmjPqN6+eM5vvt39A5vgt3dr2HU2nWrhmUuku4NW3sMWe6rAYrYD2m4xdf/QeaFnye69bp2TurdR8Gw2Y8nsHUtvKNcYU+x8zb9+8zvPFI+dvri9IquQdQvv8GzWzG/tw4WpnUeo485DyHCZaULfo6X77U1jWOE2on1lkSBEEQBOEfzev38vKKF/grdxU/ZcwCoFejPgDcd5+FkSPDWL06WIo5Nzf4l/6bb7aiHRorAT5fd8rKpqBpEpGRNyJJ+QDEW+OZPPI7AObtq31NppNpSvokJCSu7XDjqe5KgCRJgX/cbj2Ai4z8FU1TcDheqvUY48rTP1jy9umH/enncI69k/I336Vk2mz87TvQrFktH7DD8LdKBUDJ2F1jn2mRPrfMO2jwsXf4H0JklgRBEARB+Edbkr2Qt9e+zttr9ep1VoOV81row7m++UYfJvfXXx0C7XfsCM5VWrNGIfOlb2lxx1C0pKSQ83q9A3A6nyQ8fBwWy5dUVDwAQGJYIm1j2rHu4Bo0TQtkdNx+N6XuUlYdWMHG/PU80PORymzNieH1e1mVu4KeSb1pHtniuJ1XUbYjy/l4vX2AYxtm6KqsAhcWlovLdRM+X9far7knA81sxn86Z0wkiYp7H6yx2WCA115zER3dsKCpembpUKYlC9GsVry9+x5bX/9BRLAkCIIgCMI/QrGriN0lu9hTmkG40Ubvxn2Jt8azPCe4yOfYzndyZduriTJH4/XWfS6LRcPl0oMc77ufEffpA5S9/xGeCy8OaVdRMZawsLcID5+A19sfn0/PWHWI7cSO4u1k27NoYmtKfkU+V826jK1FWwLHhhvDua/HQ8fxCYQqduulthvbko/6HLKchdn8PbJciKomA37Cw8cjSU58vtZUVPwLl+s2Dl1AtqHcbv2rxeLC4zm37n4UFaHGxtWcQHaGuOmmw3wYD+FPaY6mKDUyS8rmTRi2bcV9/gh9kpTQICJYEgRBEAThjObyubjpl2tYlLUgZLvNGMF/z/2Y77Z/RaQpio03bSfMGCynnJcX+uL9wgvf8eyzeoGDAQP8LFigv0blRrRBUzcT+a+xFC9ajr9VMLuhaXGUlX1GZOR1REbeRlHRRkCma2I3Zu6eTo8pNauSGWUjXtXLr3t/PrHBkktfuDTGfDRrPhVjNC4hMvJWZLm4xl5NM6Aoe4iIeBBNi8Ttvuqo+lhRoX+1WPx4vXUPHZOKi1GbphzVNc44JhNq05QamSXr5M8AcF1/8yno1OlLzFkSBEEQBOGMNm7l8yzKWkDn+K7c2fUeJpz9Jnd0uRu7t5wbfxlDQUUBj/Z6IiRQAjhwQA+WxozZzJw5I7nwwuC+Ll38vDpUn9+UOeYBHC+9glRRgXnWjzWu7/GMxO2+GkXJxGBYDcBtne9gUNMhgTZmxcyLA8az87ZMtt+6ly4JZ7G5YCM+1Xecn0ZQVWYp9ogWyNUICxsHNCI6+nJkuRiH4xGKi3+jvPxdysvfp7BwGwUFRRQX6/OILJavQs6gKLswmWagKDvruIYXWc7AaFyI368/T7O5PZpWR91srxe5rBQ19u+z0O+p5m+Vqle+Ky/TN9jtmKd9j79JUzznnndqO3eaEZklQRAEQRDOSFnlmYxb8RzTd06jdXQbZl3+K+HGcAA0TeOv3FWszVvDk32e5Y6u/6px/IED+t+Ue/eexogRc8nLeyuwr107leQVG4BLOGhsgnvEhdge/A/GRQvg/odrnMvtHoXF8jVm83R8vj5YDVa+HPkds3bNYEizYRgkA3HWuED7tLjObMxfz66SnbSP7VDjfMdDILNUb7Dkx2p9h7Cw1wEzslwIpOB0Xo7X2wuP5xJAwucLXafJ7++A19sXk2kRNtsDaJoVk2kuBoMeJGmagst1A07no6hqUyQpj6ioazAY1iBJegU4n+/fwLUYDEPr7J1UrAd9WowIlqr4W6XCogUoe/fg69wV47o1yPZynDfdCkpt64MJdRHBkiAIgiAIZ6T/rp/I9J3TaBvTjk/OnxwIlECvuPbNRT+wPm8dQ1LOqfX4/fv1zFKzZptwOh9ClpPp3t3P2rUK553nI/f9vQAU+yPRYq34unXHuHolUmEhWlxcyLk8niGoajRm8484HOMBGavBytXtr6312lWLuW4p2HQSgqWYOtuYTPOIiLgLWS5AVSNQ1Wh8vvaYTN/hcNS/nlJ5+VtERV2B1fopAJoWhtt9ET5fZyyWL7FaJ2E2/0RFxV2YzV9jMGTg87XH5+uG39+coqJLATCbUwB/rdeQi/X7UEWwFBAo8pCxG1/nrig7tgHgS+t8Krt1WhLD8ARBEARBOCPllGcDMPvyubUGHDGWWIY2G1bn+kIZGfr2xo19OJ2PAfDtt07S0+3YbBBdoq+3VFauv065r7gKyefD+tH7tZzNhNt9MYpyAJNpXr197xSnv9SuOPBnvW2PVlEDMkthYeOQpGIqKm6hqGgdBQXreP75BWRmNqm1vcsFr95XQO7MvwDw+ztRVLSGkpJfKSmZTUHBXsrKvsbpfIKioo243ZciywWEh7+EwZCB0/kgxcUrKS//EKfzScrKulX2o+77kAv0suxqQsLRPIYzUqB8eOW8JcOmjQD42nc8ZX06XYlgSRAEQRCEM9IBxwHMiploc92Zk7r4fPDDDwomk5sWLZoAJgCioyE+Xi/hHFukv4iWlelBVcV1N6HGJ2D95COk0pIa53S7rwEgMvJqrNbaAqqgLolnkWBN5Istn/La6vFH3P+GqK/AgywfwGhch9c7ELv9HTQtkalTDbz8spmzz679nBMnmnj9m5bcf7tK2NuvV24Nx+vtX1mgwVKttUJZ2WeUln5HWdmnFBam43A8R/XKeRUV+vdWa91lswPBUrwIlqpUzywBmJYvQ42KDix8KzScCJYEQRAEQTgj7Z47gsiMG+vMHB1OYaFEWZmBkSN/xmbrVmO/dPAgMQ49c1VaWnn+sDAqbrsDubwM08Lfahzj9Q6kpGQ6mhZLWNh4JKm0zuvbjDZmX/4rzSNb8Nrq8czcNf2I76E+JfUUeDCZ5lJUFENpabAcelVguE9PqiEVFBD+5CNEjxhGXOsUVr2+AoADNCbstfEY//i9xnknTTLy1VdV6y8Z8XhG4HaPRlWb1mjrdOpfD5dZkkRmqYZA+fA9GcjZWSj79uLt11/MVzoKIlgSBEEQBOGMo2ka9lnjyP/8o6M6vqBADwqSk/fj9Q6qsd8yfSomvIQZvZSVSfz+u0Lv3uHsbqnPfzJs2Vzreb3ec3E6/4Msl2GxfHbYPrSKbs3XF04D4NttXx227dGobxjeJ58YiIsrYvjwuwPbjIesMRvx4H8I++RDDBvW4YpPZo3UCwA5JgqAyBvGIOdkB9qXlcFTT5l59lkzWgPWWK3KLIWFHSazlK8HS5rILAVVlQ/P2I1pySIAvANqfo6F+olgSRAEQRCEM47L7zqi9j/+aODjj4ORQFGRntKIi5NR1UPm52galm+/RDMaiYyRKC2VGDUqjL17Zabu0LNQhrV/1d03162oagRW638Bx2H71SamLU1tKWwq2HhE99MQB7JNMPVbCnNqDlN0OJw8+KAeJG3YEEzrVGV6AKSyUkxzf8bXqTMFew7QuGALDk1vmys3xvHY08jlZRiXLQkcM3++Aa9XorxcIjv78Bk/lysYtFqtdbeTCwoAMQzvUL4OHZHz8wgf9xwA7vNHntoOnaZEsCQIgiAIwhmn1FV+RO3vuMPKU09Z0DTw+1WKi38GIDa2ZiED86wZGLam4zl/JPGJEgcPBl/6pfAwvN17YPxzOVJJzcVaATQtGpdrLIpykJiYc5Hl/YftW9fEbuQ5D7KnNOOw7Y5U5oo+sOVqBvaPOrSHbNv2Ra3HlJQE71XZuQNJ0/AMHIRqNAeG6IE+XM/bqw8Ahh3bA9t/+SVYiDk9Pfga6vfDt98asBd5MKz9C/t/v6V/msrChQYkSSM8vCFzluLrv+l/EO9AfWKZXFCA68qrUVu0PMU9Oj2JYEkQBEEQhDNOaYU98H1DhnsFjiuF1q0tjB17EwCNG3cP2a/s3EHE3WMBcN7xLzp3VgNDxQDy8iQ8F1yI5Pdjmj+3zus4HE9SUXEzBsMWrNaJh+1TVWnzV1a+eFwXqbV7g3OmcnOD92Ay/cKePXtC2i5cqJCYGME775gD29ZOWMIm0vC3ace0aXoQ1KuXn6FDfXi9EvaUdgAou/R1lZ56ysysWUYkSf+FbNkSnD8zd66Be++1Mq3P/4i54BxWPreA7LIo0tjEh8Z7CPOV1XkfckE+mqKgRR95IY8zmeuqa/C174DnnHMpf+u9U92d05YIlgRBEARBOOOUVQSHtzkOP9KNiorg93v2ZONw6AFBmzYeBg8OzbpYpkxC8vmwP/8yvr79GDgwNHjJyZHwDBsOgHHFH4e5qhm7/TVU1YbZPJu61hACuLLt1fRI6sWMXT/w+nGqjOf2u3FVBF8DZ84MZnxMpp/Zvr1dSPsxY2pWWDh38fN0YRPrGp3P22/r1QJ79fITGakHQ6XGODSzGTl3Px4PfPyx3mbgQP1eqzJL+/ZJLFigB077SqPxJzUi63J9keAnu83hds//MP6xvM57kQryUePiQRavtdVp0TEUL/6T0m+ng9lc/wFCrcSnShAEQRCEM05pRXByTfXhYbUpKAhmLTIzg3+Bv+cef0jxMOOfy7F8+QWqLYKKW28H4IorfDRpogbaLFxooCSlI5rFgmnhbyjbth7mymbc7qtQlCwiIm4DnLW2CjeGM/XiH7EoFubu/fWw99JQec6D4Aku0jt9enC+ltH4O1u36ovi9utXM5N1LvNDfh58fTs0TX/G993nJiJCD5bKyyXUpMbIubls2xZ85Xz+eTdRURrp6TKaBr162ZgyRQ+ksmlKxb/v42ArfQhfxMi+ACjb0uu8Fzk/XxR3qIsIII+ZeIKCIAiCIJxxqg/Dqz7PpiaNsrJgpbn09LMAiInRGDMmGChIRYVEXjsaye2i/J33A3+pl2X49Vcno0Z5GTzYh9Mp8dd6CxU33YqSk030iGHIB3PrvLrD8Qxebz8slulER49Akmqfa2UzRdAtqQfphZtxeOtJlTVAnvMgePVgyWrV2LRJZuZMA8XFBzEYMtjYGUo4AAAgAElEQVS+PY3ERJVmzWqOYTz73Jrlp3fvlklKUomJgYgIfVtZmYTauDFy3kE2rNN/BxMmuEhLU+nY0U9GhszmzaGvolmk4G/ekvnz9UxXTMtIgLqfocuFXF4mijsIJ4wIlgRBEARBOCNomoaq6VmeUlcwoCgqqitYchAVdRnFxX8GtqxadQsAjz3mDvmjvPnH6cgOO44nnsVz8WUhZ0lK0vjgAxe33+6pPIeC48VXsD/zArLDjvWDygVoVRXs9pBjNS2OkpJZuFxXYjSuw2KZUuf9tYtpj4Z2XAo95DnzApmlJk1UfD6J22+3MmpULBUVFjIzk2jdWiU1vubiurd90YsVKyAlRQ3Znp+vP+eqYXgHD8r4W7ZCUlW2fKJXBxyw/n+Ej3uerp7VqKrE7M9D15rKpik7YnuzcaMekMWk6vOQlIMHa70PubCqEp4o7iCcGCJYEgRBEAThtOZTfTz/xzP0mJJG609SmLVrBgv3LA7sLyysPViyWj/HZFpEdnZw/ZnVq/WX9Li40IyKcYU+Z8Y98qI6+9Grlz4XZ+VK/RwVY+/En9IM68f/w7B6JdHnDyWhVTJxHVOxfDW52pFm7PZX0DQJk2lOnedPjW4NwO6SnXW2aaiDjlzw6vOQGjcO3uuWLbEMGrQMTZNITVU5a/v3IcfNmuXEaIQ+feCKK7wAXHqp/rUqozRggP4cvvvOgPM/D+AJj+bn7W2IoYhe3zxG2Dtv0GPNpwAs+zK0EmAeScxakRz4ObZNDJosI+ceqPU+ZLEgrXCCiWBJEARBEITT2uzdP/L++nco85Rh95Yzdt5NzMsIzqupWqsnlB+r9QM0LYyXX743sNXj0dtWzbupYly9CjU+HrVlqzr7ERMD7dr5WbNGweeDSd9F0sG1nqWevrhG38mbG4bjQ0EqKyXsnTdCyvRpWiI+XxeMxlVIUmGt528f2xGAzQWb6n0m9ak+DC86OvRe16zpCYCiQFrF6sD2iy/20rdvsBDFY495mD/fwUcfuRg3zsVXX+lzrvr29ZOaqrJ4sQFHSltmvraRXBpz+ZACHLN+onj2PHq+NwZZUllDzxp9mzxZnz+1aZMdxaSgJjdBzsqs9T6CZcNFsCScGCJYEgRBEAThtDZ3r74m0pxR8/n0/Mn0SOrF6DbXB/aHZpY0DIbV2GwPoCiZ/PnnY+TmGjiUzRYMIOScbJScbLy9+oJ0+GIRvXv7cTol1qxReO45MzvzY/hSup7Rzi94nAmMf7YE9wUXouzdQ/hTjyIVFwWOdbuvRZLchIVNqPXc3RK7IyExdfu3fJU+mQpfRa3tGmJj/vrAMDyvt/Y2Y8d6aeXcQjj60MH4+NCgSlGga1cVSYLbb/fSu3dwWN6FF3pxOiWmTzfw7W+NALjikSb4+vbD16cvTa7qw+Wjaq8AmJkp0727n6Qk/Xr+1m1Qcg8glZXWaGueOUNv06r1Edy9IDScCJYEQRAEQTit/ZW7mlhLLG1j2nFx6mX8csUC7jvricD+wkJ9eFtU1Cji4loQEzMMq3USqprI66/rWaXbbvMEhtEB2GzB8xu2bgHA1/Wsevty0UV6UYjHHjPjdOqB1epWV7PGoFd3y8414bnoEgDCPvmQ2O5pGDauB6Ci4jb8/pZYrR9hMPxV49yR5iguTr2M/Y4cHlj8byZt1oeylblLUTWV7UXb+HHnD7j97sP2Mb1wC/P2/UoYiVgsWqBaYGpqcC7U5Zd7adtWxVCYT0ejPuzv0GDpcG691YvBoPHBByYWLTLQtKlKz56hc5weeMATvLdIjYcfDvZ7+PBgcQ1f29D1mqoYNq7H/N3X+Dqm4TnM8EhBOBYiWBIEQRAEoU4ZpbvJKc8+1d2o00HnQTLL99EjqRdStayPr1rF66KiMiIjr8Nk+g1Ni8LluorS0m9IT9/ArFlRdOzo5+WX3bRuHXyZrz4MT96rL9DqP8wQvCpDh+pD0NLTgxXj0jMjcPn0oWV+P7gvvgznv+9HjY5Gdtgxz/qxsqWJ8vL3kCSViIi7qW3tpQ+Hf8bUi2cC8PHG/zF27k20+6wFHT5ryaBve3PH/Fv4btvXh+3jxLVvAmDzpxAdrXHppfrDeuqpFwNtGjXS718uyCfNtheoOY/rcJKTNS65xMe2bQrFxRJpaf4aSbm2bYPPe/VqO127Bu/3vPOCv0B/67YAKDu2hxwf/vwzSJqG/YWXCanxLgjHkQiWBEEQBEGo1aLMBfT9qhvdpnTkylmX8tZfrzF1+7e8v24it8+9mXsX3s3agzUzICfT+ry1AHRPCp374q8WZxQXH0SSVEpLv6KoaCPl5Z/g8VxIRkYkfr/E8OE+JAlSU4Mv79WH4SkZu/VztmjZoD4NGhR80T/nHB9ebzBKyM2VcPsU7M+8QPEifdFaOWtfYL/XOwiX62oMhu0YDGtqnFuRFQanDOW6DjeSbc9i1u4ZyJKMIivEmPXKcWsOrq5xXJWN+ev5cdcPdIxLw2O3EROjcfPNXjZseIJbbpkUaBcXpyGVFCM5nfRopM8XatFCreOstevdO/hLaNeu9mPnznXw5psuYmL0AAsgOVklLS3Y3l+ZWTJUW7NKKirEtGwJnr798Z495Ij6JQhHouYgXUEQBEEQBPTCCQARpkiWZi9iafaiGm1+zviJP65dQ2JY4snuHgAZJXog0y6mQ8j26vNwCgvB50vF4wkdqlW1/lJMjP6SHhosVX7j8WCePRPVFoGvTbsG9WnwYD+TJlGZtfGycGHwdWvdOoWUlAjuvdfN0080RjMaUTL3hRzvdl+GxfIdJtOv+Hy9a73Gm0PeZUz767F7yhiSMgxFVvCrflI/acKG/PV19m3i2rdQNZWnej3H9aXQoYOGJEHHjj+iacFFaqOiNJTduwC4YeBuksc5A1XuGqrquQLExtaelerWTaVbN/25t2ql0qSJyrXXekOyUL60zqjhNiyTP6fipltRW7bCtHQxgAiUhBNOZJYEQRAEQajV2rw1hBnC2HzzTp7u+xwDkgfxVJ//48Phn7H6+o082edZyjylvLrq5VPWx6xyPdBoHtk8ZHv1YXj5+fG4XDcDoePASiqXEKp6qa8+DMyoj5rD/OMPKAdzcV13Y+hEpsO44AIfb77pYtkyB127BgOwhASV/fv1V6+JE82gKPibt0DZuTOkMp7HMxhNM2M2z63zGpIk0adxX4Y1Pw9F1oegKbJCp/jObC/aqpdPz5zPpvwNLMlahN1TTrGriMVZC2lqS6FH9HA0TSIqSkOSCjEYtuH1BgOz6GgtMEdIatOKgQNrDqOrT/VgyWqtv314OKxb5+Dhhz0h27XIKOyvvolsLyfyrluRszKx/u9dANyXjjqyTgnCERKZJUEQBEEQatA0jb2le2gZlYrVYOXe7g9yb/cHQ9r8p9sDTN7yOTN2TeO5/i9iM0Wc9H5mlOqZpZSIZiHbfb7gm31eXhIzZtzLsGHBIAiCmaWoKP3npk013nzTRWm1omvWTz5Ak2Uqbr+rwX1SFLj+ej21FR+vMWaMl0GDfEydamTxYj1YSk7WgyhfWmcsP05H3rcXNTDMz4bXOxCTaQGynImqNqvtMrXq1agPq3NXMnbeTSHbz246lCa2JpR5Srmvx0OUlOj9iIkBo3EFAF5vv0B7i0VDSdczS/7WbRp8/epCg6WGz3eqLShzjx6Da8kiLN9/Q1yPNH3bBRfib9P2qPomCA11UjNLO3bs4Nxzz+XLL78E4MCBA9xwww1ce+213HfffXg8+l8SZs2axRVXXMHo0aOZOnUqAF6vl4ceeohrrrmG66+/nqysrJPZdUEQBEH4RymoKMDpc9A8skWdbRRZ4YaON1PuKePZ5U+evM5V2lu6hyVZi+gQ25Eoc3TIPp8v9OX8xhsjmTDBFLLt0GF4oAc599yjBzrKls0Y16/DM3QYarPQzFVDKQpMnOhi9GgfnToFs0xy5RuYt99AACIeuT8ku+R26xmT6OiLsVg+BJwNut7DvR7no+Gf89KAV3ik1xPc0PFmzIqZpdmL+Gbbl3SO78rdXf9Nfr7egdhYDaNRnzvl9fYP6Z9hV2WwlHp0Zbmrr98UFnZUpwhhf+kVPAPPxj38fOz/9xLl73947CcVhHqctGDJ6XTy4osv0q9f8K8WEydO5Nprr+Xrr7+mefPmTJs2DafTyfvvv8+kSZOYMmUKX3zxBSUlJfz0009ERkbyzTffcNddd/HGG2+crK4LgiAIwj/OvjK9AtzhgiWAe7rdR1p8F77c+gXrDtYsSHAivb9+In7Nz73dHwyphAegqgdrtJ840Rzy86JF+gCbWufTqCrhr+rDC1233XFc+vvvf3u49FK9pHZ2tkyHDuFs7n8bnnPOxbRkEcbFCwNtXa6rcLsvRZb3ERHxCDbbww26hs1o47I2V3BH13/xSK8neGPIRB7u+Xhg/xtD3sEgG8jO1p9XSoofk2kemmbE6+3JLbfof7ju0kVF2bkdNdyG2qjxUd1v9ed6JJmlumjRMZRO/4myr6ZScc+9aBGRx3xOQajPEQdL3rpWLquHyWTi448/JjExOAF05cqVDBs2DIChQ4fy559/smHDBjp37kxERAQWi4Xu3buzdu1a/vzzT4YPHw5A//79Wbt27VH1QxAEQRCE+u0r2wtA86gWh21nUkzc3lkforalcPMJ7lWQqqlM2/EdTW0pXNq65rwVTdtRY1vLlsHMjscD69crNG+u0raNH2XHdiyTPiXy1huI7daRuNSmmH/5CV+nzniGnXdc+hwXp/Hxx65AoYTCQpn/fmjB8dhTgD7kL8hMWdkUioq24fc3x2z+ETi6RWgvbn0ZoA9VPCuxOwBZWforYGrq7xgM23G7rwTCeOUVNzk55STZ7Cg7tuNP61zvQrx1qT7FqyFzlgTh76hBwZLH4+Gtt95i4MCBdO+u/0tmt9t5/PHHcTgcDbqQwWDAYrGEbKuoqMBk0lPicXFx5OfnU1BQQGxsbKBNbGxsje2yLCNJUmDYniAIgiAIx1dmWWXhhIj6h581iWgKwH57zgntU3VZ5Zk4vHZ6N+6LQa45BVuSltQ8Jktiwwb91cdu17d1lTcRO6QvsQN7EfHoA5h/momSk43k9+G6+lpKP//yqIOFulRfr2jZMgPes3rg7dkb8/y5yPv2hrRV1Ua43Vcgy3Ysli+P6nqtolJZMHoZ0y/9KbBt3z79ntq2fRtNU3A4HgP0WzUawfzzbCRVxdu9Z63nbIjqj+14ZJYE4VRoUIGHcePGsWXLFv7v//6Phx56CABVVSkuLubll19m3Lhxx9wRTav9X6Ij3V5dTEwYBsPxWaQsIeHkT1oVzjzicyQcD+JzJByrhnyGdpSnA9C9ZWcS4g7fvrOsl9Qu8uWdtM/niqK9AHRv2rWWa/6IJOmV3IYPh/nz4dZb4bPPJIYPD2fiRLj4Yr1lzJ51GKhcv2fcOBg9GtxupNhYLMnJWDj+/vUvmD5d/37fPpmsrAgSb7gO/lpF3M7N0LPzoUcAnxER8TAREc2BK474muckDAz5ee9ekGWNdu1+Q5IuIC6ua3CnwwEvPw9mM2GPPkhYHb/TI/ldN2kSTkLCEXdbOMOdDv8/a1CwNG/ePGbMmEGjRo0CY4IjIyMZP348l1xyyVFfPCwsDJfLhcVi4eDBgyQmJpKYmEhBQUGgTV5eHmeddRaJiYnk5+fTvn17vF4vmqYFslJ1KS5u2GTI+iQkRJCfX35cziX8c4nPkXA8iM+RcKwa8hnKc+Yxa/ss2sd2INrfqN72Zq9eTm53wZ6T9vn8ees8ANrZOodcU1HSiYm5Fo/nKgCGD3fx0UdewsPB7zfzxRcm7r0XWrRwAmFEUkbJ1Jn6ej2HZpBO0L106QKrV0usXatw551WZs92kZrWgmjA8dd6nOcG14NyOECWE4mImEV09Dn4fC9RUnJswwI1DdLTbbRs6cRs9uB0tsPhCN6r5espROTk4LzvIRzhcbU+h4b/tyii8j7s5OeL7JIQ9Hf6/9nhgrYGDcPz+/0k1PLnAJPJ1OBheLXp378/c+fqawjMmzePQYMG0bVrVzZt2kRZWRkOh4O1a9fSs2dPBgwYwK+//grAokWL6NOnz1FfVxAEQRCEun2zdQpe1ctNnW6rUTihNmHGMGLMMSdtGJ5P9fHT7pmEG230adwvZF94+HgkqYKystsBMBj09XsAXn3VHWj31FN6sYcIyvH27X/ch9rVp3lzjcREPXiw26VACeyqhWCrjBgRRv/+4RQUnIXHMxSjcT2yvPuYrl1QIFFcLNGuXS4APl9oaXA5KxMAz3Fc8PUkP15BOG4alFnq1KkTH3/8MXfdFVxjwOFw8Morr9ClS5cGXWjz5s1MmDCBnJwcDAYDc+fO5fXXX+fxxx/nu+++Izk5mcsuuwyj0chDDz3Ebbfp/4G+5557iIiIYOTIkfzxxx9cc801mEwmXnnllaO7Y0EQBEEQ6uRX/UxJn0SYIYzRba9u8HHJtqbsKc1A07QGBVjH4u01r5Ntz+KWtLFYDMGBcibTbMzmmTgcvbn77gEAxMcHizpU79amTfowfVuMAcyhVfJOlrAwPVj6/HMj+/a24lvFiJIdXBqlsFBi2za9n2++aWbChFGYzfOxWH7A6Xw00E5RNmO1forP1x2X62rg8CNvdu7U/1bevn1laXB/u5D9cn4+AGpCIsdq6lQnS5cqtGghskrC6alBwdITTzzB2LFjmTx5Mh6PhwsvvJCcnBwSEhL473//26ALpaWlMWXKlBrbP//88xrbLrjgAi644IKQbYqiMH78+AZdSxAEQRCEo7Mhfx2Z5fu4pv31RJqjGnxcE1sTthRuotRdQrQl5oT175utX/Lq6pdpYmvKwz2fIC9P4oknjLz22n20a/chmmZl9uxPAu2Tk0Nf0hcvdjBkSHjgZ1vScVgA6ChVZbyKimSm/WAiI7kPrfZnBPanpwcHAOXlSXg8F6Fp9xEe/hJW63s4nY/j96cQEfEfZLkI+BSL5SNKShZxuFe8HTv083bsuB4Avz90YVc5Ty+7riYee7A0eLCfwYP9x3weQThVGhQstW3blnnz5rFo0SKysrKwWCw0b96cgQMHoijHp4CCIAiCIAin3o7i7QD0bNT7iI5LDEsCoNBVcFyCpcyyfYxb8RySJHN7l7vokdQLgE82fYhZMTPtkpkkhCVwzyNmZs82UlY2hgUL5mK3v0pOTnBY2aHBUseOKh9+WMGdd+q1rGNTTl1N66rMUpWdUT1ovW05uFxgsYQESx4PaFoUZWUfY7V+itG4HJstuH5SRcUNyHIuZvN8jMZFeL3Da71maSlMmmQEoFOnBfj9KWha6HpFcn4emsGAFn3igl5BOF00KFgCsFgsjBgx4kT2RRAEQRCEU2xXsV5FrnV0m3pahqoKkIpcRaQeYx9+2TOHm365JvBzmbuUry+aRp4zj00FG+iW2J3Uyv6VV84PX7JkCEVF84GkwDAzCC3TXeWSS3y8/nQRBflwzuBTtwzJocHSjoQBjNz6DqaFv+EZeRHp6cE/SHu9+hhCj+dyPJ7LkeUsLJYvkCQHbveV+HzdMRr/wGyej9n8S63BkqZBmzbBiewdOqzE6x1Wo52cn68PwZOPeDlOQTjjNChY6tu3b53jj2VZJikpicGDB3PXXXdhPkXjfgVBEARBOHa7SvRgKfUIg6UYi74WYomr+Jiur2kaH23Qh/hf0GIkG/M3sDDrN/aUZvDUMn2eTlWWCcBgKAH0IlQrViTTt68/ECxt3WqvtbCAadtmfrfeg5eDmM77BbVmk5Mi7JARgDsS+gNg+eH7ymApNLNUnaqm4HQ+HbLN6+2NqkZiMs0FNPRFbM2AHnS9/74xpH1UVBnl5YNCT6xpyPkH8bUJncckCP9UDfqTwQMPPICiKAwZMoR7772X+++/n6FDh2K1Wrn77rs5//zzmTNnDq+99tqJ7q8gCIIgCCfQrpIdRJqiSLAe2aI4MeZgZulYfLb5Y5bvX0b/5IFMHvktV7S9ClVT6fPVWfyWOY92Me15vv/LgB5Y7d9fFjg2N1ePjHbulElMVEOySlJ5GeZp3xFx793EXDCUxMx1xNwzGrVFy2Pq77E49O/LGeWJ+Fq2wrhoAT6Xj23bZDp10uf7eL3Bdtu3y/TsGc6aNYe+xhnxeoeiKFkkJESRkNCIuLg2REWNoqRkPW++GXpBv78xbvflIdskhx2pouK4zFcShDNBgzJLCxcu5JVXXmHgwOCCZldffTXLly/nhx9+4M0332TEiBFcf/31PP3004c5kyAIgiAIf1c+1cee0gy6JHQ94op20ZXBUrH76IOlzLJ9PLP8ceKt8bw77AMAnu77HG6/i482/o+mthTeG/YhRkXPkCxfPom1a+8NHJ+TI+FwQFaWzMABPpSt6fjbtQePh+gLh2PYpi8+q8YnUPbB23guvPio+3o8VH/EBoPGnr0y3rOHYv3iU/IWbsXt7k+7dirbtsm43cHGv/xiIDNTZskSAz16hKacHI5HADeynIckuZGkYkym3/j66/7Y7YO48cYvmDz5Js49dwvFxSvQtNB5SYHiDsehEp4gnAkalFlatWoVvXvXnOjZq1cvlixZAkBycjJ2u/349k4QBEEQhJMms2wvXtV7xEPwABqFNwJgb+meo77+lPRJ+FQfz/Z7kZSIZgBIksQLA8az9oYtrLlhM10TuwGgKDt4+eV+SJLK++/rpa6zsmQyMiorveUtJnZwX0xzZmGeNQPDtq24zx9B8YJlFG7eecoDpUOlpans3Svj6n82AI5lGwGIjdUwmUIzS+vX6/d44IDE/PkKI0eGUVqq7/P7u1BW9j0lJYspLv6ToqJtOBxPs2ePnkF74olFLFy4ho8+alYjUAKQ8vRnqSUmnahbFYTTSoOCpaSkJN544w1KSkoC2+x2O++++y5RUVGoqsobb7xBhw4dTlhHBUEQBEE4sarmK1UVd/jjD4Vff21Y1dsuCWcRZgjj95ylR3Vtj9/DV1snE22O5tLWo0L2yZJM04iUkGyX2fwqa9d2p3fvAi680ILZrLFihcKuXfqrTdrOmQAYtqZj/mkWAI7nx+Hr3PVvVbhgzhwHc+c6aNVKxeOR2NtqCADO1dsAiIzUg6Xqc5Y2bNB/J7m5MtddF8Zffym89FLdc8adzocpKBgKgKK8S1paW2y22tvK+VWZpSMbhikIZ6oGDcN79dVXufvuu5k8eTJWqxWj0Uh5eTlhYWG88847gD5U76233jqhnRUEQRAE4cRZc3A1AB3iOuF2w2WX6RUIDh4sr7VQQnUmxUS/5AEsyJzPfnsOybYmR3TtnzNmU1CRz51d78FqqLuctyQVYLM9TWnpYlRVITExhrAwF/36+Vm82MDGjXog0YQcAOQD+zEuX4a/RUv8rVofUZ9Ohl699PISrVvrX39bl0jnDh1xbNP7HxmpYTRqgcxSfr5ETk4ws1Tliy9MjB/vxlDrm51MSYn++4iIqG1/tZZ5eQCoIrMkCEADg6UuXbqwaNEiNm3aREFBAaqqEhcXR1paGmGVpVzmzp17QjsqCIIgCMKJ9cueOVgUCwObnM1jjwQzFfn5EomJNUtwH+rspkNZkDmfpdmLGdP+ugZfV9M0PtjwHgA3d7r1sG0jI2/CZFrGli1XAAT6NXSoj8WLDUybpr/aJKK/9Ftm/IDkdFBx+ZUN7s+pcMUVXl591czSpQr/7taDUn16FZGRVGaW9MBo48ZgViw7OzSCLSmRiI+v/fdUWioRHq5R3/KYwcySmLMkCNDAYXgAJpOJli1b0rlzZ7p27UrTpk0pKSlh//79J7J/giAIgiCcBBklu9hWtJUhKecQZgjn669NgX05OaXYbPcTFXU5ERG3EB7+KAbD+hrnGJyiD/Vamr34iK79856fWJu3hktSLz/sfClF2YTJtAyPZzC7dk0CgsHSOefoVeMOHtRfbWLaxqKZzUhOBwDuiy45oj6dbE2b6vdRWirhb9ueUqKAqsxScM5SVeZMUTSKikJf44qL607/lZVJREXVH/DK+fqcJZFZEgRdgzJLP//8My+88AKlVbMHK2mahiRJbN269YR0ThAEQRCEk+OXPT8DMKJl6Po+AKWlz2C1fh6yLSzsA9zuCykvfxtN01+sO8R2JMGayNLsxYF3hIZ4ddXLKJLC471rr6irKNuxWt/FZFrA7NkXsWzZKzRurL/CNGqkD19r21YlNVVl92697xG3X4HzYCfC3noN++vv4B1yTgOfxKlhNOqL1JaWSvg6pVGKE4CE+d9hyRuK06DPISos1J9paqrKjh164GQ2abg9EsXpudCm9oxQWZkUeFaHE6yGJ+YsCQI0MFiaMGECo0ePZvjw4VitdY8jFgRBEATh9LSpQM8UDWx6NjM+118PBg0qZ9myCOx2Iw7H07hcVwEyBsNWwsJex2yeg6ZFUV6ul/mWJIn+yQOZuXs62fasQEW7w9lZvIOtRVsY0fIiWsfUzCopymaioy9BlgvQNCOXXDIbgM6d9UxSixZa5bXh4ou9vP22PnwwfGAXnK0up+Jf/0Gz1TNR528iKkpj40aF9VGD2GkoBx+0/u5VzHTDQxTK9p1UVHQFoF27YLB0duxG5ud2xfPwi0hnP48WExtyXp8PysqgXbuGZJby0EwmtKjo43+DgnAaatAwPLvdzv3330+XLl1o06ZNjX8EQRAEQTi9HXAcQEKiUVhjFixQkCSNyy7TK9sVFd2A0/koqtoCVW2Gx3M+JSVz8fubYzbPBIJLh7SKbgXoayY1xNTt3wJwYavaSnlrRET8B0kqxG5/mYKC4ND/TZv0QKFly2C2pPq8KrVlK5Ck0yZQAgLziYaeF8Of8RcTaXCQ/P5DKCmNKSUa3xU3M2WKPjxy7E3OwHFDyvRqfwWlRmyPP1TjvAUFEqoq0ahRA4KlvDx9CN4RrrMlCGeqBgVLw4YNY+XKlbVO5XgAACAASURBVCe6L4IgCIIgnCIH7PtJCEvEaTeyapVC9+4qLVr8AYDdXtvSIDIu1xgkyYHZPCuwtVlEC6BhwVK+M5//bXgXq8HK8ObnH7K3gsjIGzEa1+DxnEdFxb8BM5GRoS/8SUnBn2Nt7mrd+/uUB2+o7OxgnzPyI2jT1YJ39FWsy9KH1iXlbQns7z+2O+PlJ7lG+Z7znHqZ9NWx5+kFLUpLQs6bm6sHPvUGSz4fcn6eGIInCNU0aBheamoqTzzxBF26dKFp06Y1xiA/+uijJ6RzgiAIgiCceJqmkes4QLvYDmzZouD3S/Tv7yEqah0ADocN8NQ4zuW6hvDwCVgs3+B2XwtAarRennv6zqlc2fZqjIqxzuv+sX8Zbr+bB3o8TIwldOiY1fo5ZvNMvN6+2O1vAnqp7LKy0HeQ6q8ktn1bgb5Hevt/GwMG+Fi+/P/Zu+/oqIr2gePfu303m0ZIQkjovXdQOihSlaIUEQRFAUFFBBTBgqKi2H6oiAXFBorwAooCUkWa9N4JkEAgCSGkZ/v9/bGSsKQQNUGQ53OOh92ZuffOzbvnvfvszDzj/WrmditERha8xsiaEsezurdwV6tOdrNWmOd72Kq5HfDuLRVXuRXvv2+gf39nTrAUHl74miXDyhUodjuuho2L6Y6EuPkVKVjauHEj5cuXJyUlxWdjWqDIizeFEEIIcWNKsV/C5rYR4RfBuXPe53r58jFYrRcByMrK/1nv8VTG4WiJwbAeq/UJMjLeoXnEbTQvcxvrz66j4mdlaBzelDaR7ehZtQ8VAyuxPX4ra2JWMbj2EN7Z8SYAPSr3zHNuo3E+qqolNXUuquod6Xj7bUOedkpGuneqnapi3bKWmzlY+uKLbJ54wszKld6vZxER3pGgPn2cLFrkG3Rmrl1Het26Oe8r71SJPhGOCpxaeoTGn3lH6j791MC779oACA0tfGTJ/MVnAGQ/9Gix3I8Q/wVFCpa++eabAuuOHTtWbJ0RQgghRMlIzEpk1ekVLI1ZxMBqQ7inau+cuvOZ5wGwH+jGqLe9iZyiov7AYvGui8nOLvi8GRnvERDwMGbzV7hcTbHZhjCr02ze2/EWuxN3sT1+K1vPb+HtHW/4HPf1oTmkO9IYWmcY9UIb+NRptUfQ63djt3fOCZQAYk94kzos8HuQec5+DHF8RqnmW7ANeAD91i302L6dUf5RdPvu3r//h/oXBQdDu3auK4Il70jQrFk2zGaVuXNzg0XPFYESeLPjHTyo57SpJgNnd/Gpu7gnDqhCoMUJ5B/4amJOY/h9HY6WrXHXzG/apRC3piIFS5clJSXhcOQOwyckJDBs2DB27dpV7B0TQgghxD+z7fxW5h7+iuOXjrEjYVtO+abYTYT7RVDWWpZy/uWJzzwHHoV1b4/OaVO58keYzd6MAwWNLAG43bVITf2OkJD6GI2LsdmGUM6/PO92+ACANHsqC47NZ++F3ZxKPUn14BpsitvAydRoKgdW4aWWr+Y5p8n0PaoKS5eOp2VLMMUexzxrJhe2P0sgYdyb+Q19Sv2CJjkZT7YVy4f/B4DjtpZMnV4Td81rp8i+UUVGXrEGq1Rupr+OHd3MnVvwcZUre+954V0fceSnGj51a79OAKpQ9o3xKG1fyDfTnf4P7/o0+915R/mEuJUVKVjas2cPY8aMITExMU9dq1atir1TQgghhPhnzqafYcDPfchwpgNg0poYWGsw6Z4UFhxawN2L70Kn0bG67wa+PfQ1HPPNRle5cioXLnhnlhQ2sgTg8VTE6WyEXr8eRbmEqgbn1AUYAxlWb7hP+yXH/8ekjROYeeen+On9rqhRMZk+wWz+hG++eYQhQ+5kwAAnX2hnYJz7DdHMpC4HSP3fUpxt2gGg276VoD49cJevQOq8hWC1/s2/2I2hXLncQC8wMLe8TRtXocddDpZ2WVoD0LlNKucvmth3yMgWWgIQcnwbwe1uJ/3jz3He1tLneP2uHQC4Gjf9x/cgxH9JkYKl119/nbvvvpuuXbsyYMAAFixYwIEDB1i1ahXTpk0r6T4KIYQQ4i9QVZXBywaQ4UznjbbvcH/NQQCYdWaCSpmo6FeVjXG/s+XcJl7aNIlN5zZgOTGXrCvOode/hsnknY5V2MjSZQ5HF/T63ej1v+Fw9C60ba9q99KrWt6pcgbDSvz9n2Hv3pYMGeJdP/P993q+Lb+eM9Za2DNMVGwciLN19ZxjXM1acHHfUVSDEfz88pzzZnNlUoegIPWK1zBihINPPsm7bgtyg6X9+70Z9Rq3NjFkiIOaNY05bfQjBqOZ/SwBD/Qjbe4PPgGTbtdOVIMBV23f6X1C3OqKlFczOjqap59+mjp16qAoCjVr1uS+++7joYceYtKkSSXdRyGEEOKmkOFIJzYtBpen8FGAkrY1/g8OXtzPXRW68FCdRzDrzJh13rVIeq2eCc2eY3HPXwg1h7H+7DpcHhflFG9ihA0buhAT0xCH4w7MZtDrVS5eLEqw1BUAf/8x6PWb/0av3fj5vYiqamjYcJPvuWMTONK4PwAV2pfPsweQGlzqPxEogXfd0mWBgb4JGaZOtfPqqzZmzsw71Fe5srftwYPeqZN+fiqlSvnuQ6V/ejgZ099DycoksG9PDMt+BkBJT0N3cD+uevXBaMxzbiFuZUUKliwWC+np3mF8Pz8/EhISAGjatCnbtm0r7FAhhBDilnAw6QANvq5F02/r0XJeE746+AXxfyZOKMzexN3sSdxFljOLFNslEjLjiU2LIS79LKp67U1EwTuSFJN2ml9PL2d7/FaGrRgMwCP1RxaYtVajaBjbZDwAjzV4Ak1GJIGB2bRu/SulS7cDdGi13i/bJ05ouFZXXK6GpKV9jKJkEBjYG0VJKFLfL9u791c+/7wNaWkP5qnbRCv+qHw/ADVq3LzrkYriyv+5rhxZumz4cCd9++YNxkNCVJ89qKxW7+smTdw5Zf7+YBs81DtdUasjYNhgb2KH1StRXC4cHTsV450I8d9QpGl4HTp0YODAgSxYsIBmzZrxzDPP0L9/f/bu3UtISEhJ91EIIYS44c3cM4N0Rxrl/MtzOu0UE9Y/xbO/P02vqn34oOMn+e43tP7MOvouLXhBfZWgqjxc91GG1nkkz/Gp9hTe2TGds+ln2JWwg3OZcT71r7eeTvtyHQvt8yP1R9KlUncirVHUSrBTtuxp3O4IsrNz1xhVrerh2DEtiYmKzwaw+bHbB6LRJGO1TsJk+oHs7CcKbX+ZyfQFnTqNAfqj1cblqX9FmYIuphIALVu689T/1xiNKna7km+wVBBF8U7F27Pn8siSt7xxYzcLF3o/O7o/v/U5O9xBxpRX8X9mLMZfl6Hf7B3Js3e7O895hbjVFWlk6fnnn6d79+6YTCYmT56M0+nk2WefZePGjUydOrWk+yiEEELc0NweNytPr6Ccf3l2DNrP+v5/8Hrr6dQIrsWi4wuZc+CzPMdkOjP5fP8nAERZy9Gx/J10qdSdXlX70K/G/TQNb05M2mkmb3yWadvyPmtHrHqYj/d+yM8nfyTZdpG7q/Ti0XojAagTUo9h9UYUqe9R/uWABJKTLYSFXSIl5Tc8nvI59dWqeUdyTpwo0lcGbLb7UVUDZvNn6HRb0en2AvlPS9y5U0O/fjp27VqaUzZ+fFmfNgFKGhvU1qxbp6N6dfc1A7b/gp07M1m3LhOL5a8dd3ndEnin4QE0auT2+fcyR5duqFot1ucnYly2FGe9Brhr1/lnHRfiP6hII0uJiYmMGjUKgPDwcObNm1einRJCCCFuJgeS9pHmSOXuKj1RFIVaIbWpFVKb3tX6ctu8Rry14w0u2pK4s0JnygdU5JXNL7AyZgWp9hRqlarDqr7rMWjzLtxPyk7irgXt+HTvRzxSbwRlrZEAxGeeZ23sapqEN+XLrt8RaAjEpDMB3tEiP721SJvGazSnsVonY7dvBpIwm0PweCJ82lSt6v0Cfvy4hlatrj2qo6ohZGcPx2L5kOBg77Qutzscu/0+srNH4fGUA1RA4e67LbhcCl265AZLqanefr/+uo3WLR181+FbZuH9DnIrjCoBhIWphIX99aDQN1jy/tukiYf587No0MD3b+cpE4Hjrq4Yl3vXLaV/9FmetWBCiCKOLN1zzz14PP/tOcJCCCHE37Xp3EYAWpZt7VMeYg7hpdunkmZP5b2db9N9USfqfVmNBce+J9WewpjG41hx39p8AyWA0ubSjGwwGofHwfoz63LK18WuAaBX1XsJt4TnBEoAlQIrE2YJu2afFeUigYH3YjQuJSOjIgAGQ6U87S6PLEVHF21kCSAzcyppaZ+SlfUYNlsfFMWBxTKTkJA6hIREUrp0aYKCWuNyeb+c22xmn+Nvu83FI484qaM7hl3NTThQr558FynMlQFRcHBusNWhg5tSpfK2zxr3DM4GjUj9/BvcNWpejy4KcdMp0v/zPfDAA8yYMYOMjIyS7o8QQghx0/nl5E8AtI5sm6duUO0h7B1yhFl3zkav0RNuKUP5gIq82fZdJt/2Uk6WuoLcXta7n+GqmF8BcLgdzD/qneHRodydf6O3FwkM7EVISE10uuNkZT1JXNxvAFgseb8WXDmyVHRa7PYBZGa+SXr6l1y8eJyMjNdwuarj8YTh8USiqocLPHrevGxwOPB/ciS9WAKATqfSv7/zL/Th1nPXXW5mzsxm5szsIiXCcNVvSMqq9ThkI1ohClSkaXirV68mKSmJzz77DKvVilar9anfsmVLiXROCCGEuNHtT9rH9vitdCx/JxHWsvm2KeMXwb3V+9Ei4nZKm0N9RoKupU7pejQIbcTPJ3/k070fsSFuPZvPbaRDuTuoFlz92ifw4QEewWBYi9tdEZttEFlZ48jO9o7wmM15p34FBEB4uKfQYCk7G1av1tG9uwtNvs0MZGc/cUXCB5V9+zJ9WvTp46RxYzelSqlYrWBc/BP6XTvpdG8/tj2TToWKMkvsWhSFfDPlCSH+viIFS8OHD792IyGEEOIWNGe/N3nDsLrXflZ6kyn8NRpFwyd3fUGPRXfx/KaJALSL6sCcLnOvuS5Jo4nBYPgdRUlBo7mATrcT2IDD0YbU1B/RnIolYHJ/3M2eAHpgLmCQq0IFDzt3anG74arfSwGYNMnI3LkGpk2zMWxYUUZ/FPbtC/YpiYryMHx47rH69d5ph9mPPU7FvLMDhRDiuihSsNS7d+E7cQshhBC3qlUxvxJuKUPH8iW3R03lwCq8dPtUnljrzXb3Tbf51xidUjGbP8DP73UUJeuqujqkpX0N6DDNn4tx9UpY7QB6YDHnP3WrTBkVt1shKSn/9OGrV3u/Tmzdqi1isAR79/oOQV19Xt3+fahmM6469Yp0PiGEKAl/ZQKyEEIIIa6Qak8hISueOqXrotXkM+RSjDpX7Er5gIq8ePvUQgMlne4PgoObY7U+j6rqyciYRmrqN6SmziUp6QSwD1X17pGo37kDFXiMjwHwP3Ug33NGRHgDmZSXZoLDkc81vf+mpytgt2P++EM0CfGF3s/+/Vr0+twA6cqEBHg86E4cw1WlWv5DWUIIcZ1IsCSEEEL8TccuHQWgWnCNEr9WkCmYHYP28XijMTllGk0sOt0OtNrjKEo6JtNXBAb2Q6c7is12L5cubSM7ezQOR08cjrtR1TByHv0eD7rdu9gV2Z2jePvvPnM+32tHWC4BkLxoE6FRpQludxvag97AyumECxe80wETEhQs772F9cVJWMePyfdcqgpr12rZtUtLzZq5I1lXBkuamNMo2dm4q//VNVlCCFG8ijQNTwghhPgvO5V6kuiU47Qvdwc6TdEfjccvHQOgRnBJpF12AzbAL99ai+VV/Pym5ylXVRNpaZ9ht/cv9OzaE8fRpKWyp0ZXiPOWnYrJ/94j9q0BBnKBUFSLH7rDhwh8oC8pK9ZyKi0Sh+PPYCkezHO8a7iMvy7HMu0VNBcu4K5eg+xhI0Cv548/tAwY4N1ttUEDN/v3e0eOgoJygyX9jm0AuBo3LfQehBCipMnIkhBCiFva6dRTdJjfioG/9OWpdaNxe4q+8WlJjSxptccJDm5B6dJlCQzsiUZz2qfeYFiBn9903O6KZGU9gdN5O253OTIzJ5OcvAO7vT9Hjmg4e7bgBBC6XTsAOGhpllM2NuNVuGpfRU1CPGW2LwMgdtxbJJ2MI23yy2jPxRF43z0c2Za7rcjFiwrqpVScDRuharX4vfc25m+/wvriJErd3hj9ujU++zWFBeeubwoKUsFmw++FiQSM9ibLcNzuu2+VEEJcb0X6+ez48eN88MEHREdHY7PZ8tSvWbOm2DsmhBBClLSErAT6/9ybLJc3jfUPR78jOuUEX3T+psA04Fc6mRoNQJWgqsXSH43mJFbrZAyGtShKNi5XZQyGdfj7jyQ11RuwBAQMxWhcgqpqSEv7Cper0Z9Hq4A3OMrIgLZt/fD3V4mOzrtHounrOfi9+RoAhx1VADjTfRhRv2wmZdMGnG3a/XlKFf/hDxGa5g0gP/gimHbdsujz4Qv0qnknc460Ivr7vcBdBAV6SEnVcNa/Fn4Lf0KTkIDu0AGOXgjh6PIzDNowiqD+vblUZhbgTVQx/PchvMtCAPy0dvyfGo1p0QIAHK3b4q5Xv1j+rkII8XcVKVgaP348AQEB9O7dG3NBeUWFEEKIm8wbW6dyKvUkTzUez4gGo3luwziWnFhEn596sHHA9msmbTibfgaLzkKIKaSQVk4MhnUoSgoOxx05yRW87JhM89Fq96PX70Cn24+iOHC5qpOV9TR2+0ACAh7AaFyKn9+LgAajcQlOZyMyM1+5IlCCy4ESwMcfGwBvwoUvvtDTurWbESNMfPihjfb+O/EfPwbVZCLzqfEcWRJM6dIe/EYPRF3+Jf5jnyD5t81gtaI5dRLDlk34NxsM2+HSJYUhQ8ykpip8ldqSuTgw7vCODvVocJpvf6/M7o5jaBUQiDsgEHe16jQP8weg6ct+1HxpCAnx3n7uD25Djb0bWV+mL7vsdajX/GXvX6thI1K/XYBaunSR/jcUQoiSVKRgKTY2li1btmAyFX0TPSGEEOJG5lE9rIr5ldLmUCa2eN67n1GnORi0Rn44+h3rzqzmzgqdCz3H2fRYovzLFbLfkYuAgEEYjcu91/SUxmYbiEaThEaTiE63C40mGQBV1eNy1SU7ewR2+8CcM2RkTEev34TF8v6f7UykpX3HpEmVKFPGw+OP+6bqXrpUx/Tpxpz3EyeaiIz0EBen4cMPDfyarvAc/vDmm8zVD+X0aQ0tW7pwNW1O9uNPYXn/XUq1v51Lazei3+rddN7auTls//Oez2qIjPRQq5aH1av1uDx6ANoH7+FbKvP20Z6Ui1UoX943FXjynfdyYWQvYvp4YBOY1i8i+93naPvl57T9c3TJ2aQpqd8vQg0MKvTvLoQQ10uR1izVqlWLxMTEku6LEEIIcd0cTNpPYlYCHcrdgUbxPg4VReHRet4pYu/veg+Xx1Xg8RmOdFLsKQVsNKtiMPxIUFBnjMblOBxtsNn6o9EkYbG8z8qV6Tz7bDdcLgPffvsGsbFLSUo6R0rKep9ACcDjiSQ5eRvp6f+H3d6J9PRZJCWV5dNPDbzySt4fMTds8I6GlS6du/YoLs57f//7n543VjbmKf4PV4NGjBrlnS0SFuYNbDInPIezUWO0sTEE9rmbgDGjALB2aOJzjYEDncyalZ3z3qDzcK+6gE6sZNORMLp2tZCVBdu25X7NSE2FFb/q+HVTEBaLSkC4iYzXppM9+CGyHh1J0sk4UpavlUBJCHFDKdLI0tChQ5kwYQJ33303kZGRaDS+MVa7du1KpHNCCCFESdl0bgMA7ct19ClvENaILpW6s+LUL0ze+AyvtnoTvVaf5/gz6WcAiLKW9ynXaM7j5zcRk2kxAHZ7N9LTP0NVrdhsQwE3PXt2B8BmG83HHxuYNs1W6GauqhqGzfYwNtvDAOzcWfD0wIwM7yjX4MFO3n/fQO/eLhYu9O3/HB4m40N7zvuctN1GIylLlhMw6lGMv/wEgCc0DLVObaZMsTFlijc4q1/fTWAgBJgdpGUbCDJkErDmZ5ZFbaZPwxMs/VlPbKyGHj1yM/mlpCg8+KA3C154uIqiAHo9Ge/MKPBehBDi31akYOnJJ58EYO/evXnqFEXh8OHDxdsrIYQQooTtu+B9pjUOb5Kn7sOOH9P1f3cw58BsVpxaxp0V7qJ75bvpWL5TTpuz6bEAlPMvx8yZehYv1rN69XSCg99Bo7mIy1WbtLQvcbtz04o7na18ks198YU3iElNLThrXX62b88NljIzwe9yTKKq2DbvAZox4fTjPPdVd5SK5Vm4sHGecyxY6J2qFxCgMnFibuCE2UzanG8xrFyOfstmbIMeBI2GgIDcJg0aeG+iShUPuw+AkpWJhgxsj4yggttb9+OPvl8x9u7N7XNEhG/GPSGEuFEVKVg6cuRISfdDCCGEuK4OXzyERWehUmCVPHUBxkB+6bOK6dtfZ+Gx+Xxz6Eu+OfQl77R/n8G1hwJwOu0UAMFqZca/7B1xOXlyCSEhTrKyxpGZ+TzgOwKkqvDYY7lT5y7vT+RwFK3P8+frWLVKx44duee9cEHBz887MqTb+gdZ5/6chrf4S/SLZ1++cp5zdenipEsXFwMH5j/V0HFXVxx3dc157++fe47wcO/r7r0Udh+ABMrgrFuf7IceodQib9077xh9zndlgHflBrRCCHEjK/I+S6qqsnfvXpYtW8ayZcs4dOhQSfZLCCGEKDGqqhKTdpoKAZVy1itdLcgUzOtt3uLwQ6dY0nMZFp0fb22fxsXsiwCsivkVgOjVd+Ucs3r1naSk/Epm5ktcHSiBdyRp8eK8U/qcBc/A8/HEE2Z++knPuXMaFLyjM+f7TiRg2IMoaan4vfsm6fhj1LvJ/uBDsocNJ3vQEH6983Xm3P4RrUNzZ4J8/bWtwEApP1f28XI+i549vYVVKjlJWbsRT9lISpXyDYQWLswCYO3a3N9nJbGuEOJmUaSRpRMnTjBy5EjOnj2L359j/ZmZmdSoUYPZs2cTGhpaop0UQgghilOyLZkMZzoVAipcs61Wo6VlZGuG1h3GR3vep+6XVXmj7TtsOLuexmFNWPFVWE7bWbOe4tFHTRSUHG/NGt/Hbv36bvbt0+aMMBUmPT33tQY3v9GetmxgSUxj7omZScrSzfTjE7bTnJAAD/b+A7H39yaLaPTnf13csGMHmEyZ17ze1WrV8gZngwfnDoNVqKCyfHkmERG5AVJwcO4x993npGVLN3fc4fK5d7NZRpaEEDeHIo0svfbaa7Ro0YLNmzezc+dOdu7cyfr166lWrRqvvvpqSfdRCCGEKFbb4v8AoEpQtSIf81yLF3jx9qkoisKE9U/hVt2UP/kSp05paN48lo4d1xAXF0piYsGBT1oaaDQq586lM2NGNtOmeTd6z28anpKYiH7dGpT0NAD2rb6YU9e0Vjq1fnuHqHA7P/gN5XyFZjRiNz/SC7hiDdNVtFro0SN3zdFfUaeOh127Mpg+3e5T3qSJh7Jlc4OfsLDcc0+caEeng88/z/Y5xug7Q08IIW5YRQqW9uzZwwsvvECpUqVyysLDw5kyZQo7duwosc4JIYQQJeHrg18AcG/1fkU+xqg18nijMXSp2D2nbMnbdwPQsOFyWrXyPg8PHSr40ZqeruDvDzod3H+/i5AQb5CRZxpeVhbBndoS1L83IbUqY50wloPPLwHAqrfx8Vwdau1a9HsAMjM1DKm0nvOUzTncai2ZkZuoKBVt4fv0+uyvVLq097XF4tvmkUeKuEhLCCH+ZUUKlvz9/cnKyspT7nQ6C9mITwghhLjxxKSdZm3sapqGN6du6Xp/+fjHG41Br9FzR5neOWUvv/wGZct6g6gzZwp+tKalKQQE5AYTBoP3X7s991m6f78G9xfz0J4/h6tadVAUjF99wdcXumLUONm+K5uoKO85BgzwRlmrfvNdBHQ5CPs3XA6QwDdI2rYtg3nzskhMTKdyZZmGJ4S4ORRpzVKrVq146qmnGDt2LFWqeLMGRUdHM2PGDJo1a1aiHRRCCCGK05rYVaioDKj5wDXbarVH0Ol24XbXwuWqD2hpHN6UfUOOcfJIAGuAUaNmEhDQi4iIygCcPZvPj4hOJ5q4s6Sl1aNcudxpanp9TjUAv/+u5b77LMBY2miaMWhEDfpFbWTjm9s4trsG/fs6CQnPfXRXrKhSrpwnT4BWpsy/F4woCnTq5MLt9i2vWFGlYkV3/gcJIcQNqkjB0qRJk5g8eTIDB+buKq6qKu3ateOFF14osc4JIYQQxS0m9TQAtUJqF9hGqz2C2Twbk2kOiuKNZJzOJqSnz8Dtrk+IOYQNMd4ApVq1GLKyxhAZ6Q2Crg5c9OvWEPDwYMjMJAMXAX4ub3Sk0+WMLF1es7T2k9OAt18bPK3ZMB66n72T2d/1gN3w8MN5p69FRuYNlv7tfYzmzs2+diMhhLgJFClY8vf35/333yctLY24uDgcDgflypXzWcMkhBBC3Axi02MAKB9QMd96nW4vQUF3oih23O5wbLZH0Om2YTSuIji4DS5XczIzXyQ21gK0p1KlcFQ1hMhIFbNZ5fBh38DF9MN3aDIzSDGXQc3WUHr7SkIj78FZtz6uYWOBobguZeJ6ZipfrnoFHU76dkjgu3VRAPzvfzpOntRgsag0bJg3CLoyucJlkZEyzU0IIYpDgROro6Ojc16fOHGCEydOkJiYiF6vx8/Pj+Tk5JxyIYQQ4mYRl34Go9ZImDksn1oVP78XURQ76ekzSE4+RFbWs6Sl/Y+UlP/hcrVAp9tOUFB3Tp06C0C5cp0Ab9KGBg3cHDmiyU3zraroN2/EUzqUmIXrAfAP8c690x/YR+mxjwLg2bKdUV+2Jgs/ejY7w4z5gezalYHFojJliomDBzWEh6v5piSPisoNkjfOCAAAIABJREFUoIYPd9Cxo4vevYu4cZMQQohCFTiy1Lt3b/bt2wdAjx49UBQFVc39perye0VROHz4cEGnEUIIIW4oF20XKW0OzSdBkQeL5XUMhnU4HB2x2R7yqXU6O5GS0gm9/jes1skcOXIbBoOHsmUr5bRp1szNH3/o2LVLS7t2bqLXneXk+Sga9IwixS8SANM9HbkwLQXd7p3of10O/wepShCrVW/Q1fCesoCTqCiVZ56xM2WKCYDw8PzX+1w5sjRxoh2r9R/+gYQQQuQoMFhasWJFzus1a9Zcl84IIYQQJe1idlK++yv5+4/CZJqH212W9PSZBR7vdLYnOXkTx49bqVTJ45NKu2lT7yjP5s1aPv9cz4oVtdGxkWP1PyctzRucBQSooNHgatIMV5NmGD/ysN2RmyypYsXckaI773QzZYr3dXh4/lPrrhxZujpFtxBCiH+mwGl4Zcvm7tcwceJEIiMj8/wXGBjIyJEjr0tHhRBCiH8qy5lFliuLEHOIT7lWewiTaR5OZ30uXdqExxNZ6HmSkhTS0hQqV/ZdQ9S0qXf05733jKxYoceo2HGh5/VDfejb15ve29/f91x6Q+4IV69eTu66K3cE6crAqW7d/JM2XBlEaYq0IYgQQoiiKjTBw/79+9m3bx+7d+9m3rx5PtPwAM6cOcPZs2dLtINCCCFEcUm2XQSglCmEefN0xMRoeO45B2azdyQpK2syqhpS2CkAiN6bCVipUsU3gAkNValQwUPMn5nyequL+J77mf2/3PVRV28Yq7viSfzii3afdUkGA7Ru7WLjRh1t27ry7Uv9+h5eftlGx46SllsIIYpbocFSdnY2GzZswOVyMXv27Dz1JpOJMWPGlFjnhBBCiOIUn3kegFBLGE895R3pad06g169FuF2V8Dh6OzT3vzJTMwz30e1WnE1aMTlSCZhUQDwKVUr5Q1gmjVz5wRLwyqtYVlSf9LSc4d8MjN910r5+6ukpHjL8sti9/332Rw9qqFevfxHlhQFHntMEjoIIURJKDRYat68Oc2bN2f48OF8+umn16tPQgghRImITjkBP/zAl9PvySm7994QKlQ4wJIli4iMzA1qNGfP4PfSZBSPN0jRnTieU3ecNwCodXwp0N3nGg2qpbMQ79YaDWcO4niTTDweiIjwzr8LDPQNiCZMsPPkk2Zat3blm+3OYKDAQEkIIUTJKtLs5oICJYfDQfv27YuzP0IIIUSJOZl6Ag71xZ5l9CmPianIL78MASArCzIywO+1l1E8HtJmfMSlpSvJHjiYlO8XkTJ/Mcc6elN+1/5+KkrKJZ9zVd6/NOe12rQJigJaLRw5ks6rr9p44AHfUaABA1ysWpXJZ5/ZSuCOhRBC/BNF2pQ2KSmJN998kwMHDuBw5O4enpaWRmBgYIl1TgghhChOJ1IK3hvw5El/wE7btn7ExmpQ+QFn/YbY+w4AnY7Uprehqt41Rhfe907hC085hm3JImxDhwGgiT9PpV2LgSF5zl+qFAwfnv90uQYNZORICCFuREUaWXrxxRdJSEigf//+JCQkMGTIEJo0aUKlSpWYO3duSfdRCCGEKBbRVwRLY8akM2LEx7z22ofeumgNqgqxsd5HYzpW4ka/RJbD+7vivfeaadvWm5v74kWFoAAXelwYVi4HQElLJahzB8qf2349b0kIIUQJKtLI0s6dO1mzZg1Wq5X33nuPBx98EIAffviBOXPmMHHixBLtpBBCCPFPpTvSiE45jsaUTliQHy+//CuBgY+RmTmeDz7wcOqUhqSk3EVDR6t0odmIXlSv7mblyiw2b/Y+MhMSFJKSFEqHgSuyDoYN61HS0zB/8hHa8+cIHvUkb1XKlnVGQgjxH1CkkSVFUTCZvDuI6/V6MjIyALjnnntYvHhxyfVOCCGEKCY/HP0eu8uO6rAQFaWi128AwOlsQ5UqHs6cUTh0KPexuKvKvQAcO6bl8OHc8h07tFy8qBASomLrcx+K3Y7l3bcwfzwTT+nSZI6fyJAhLho3lmBJCCFudkUKlho2bMjkyZOx2+3UrFmTmTNnkpSUxIYNG9DIDnhCCCH+BSm2S3y05wOmbX2FWXs+5HzGuQLbujwuPt33EXrViurRYrF4gyVV1eN0tqBaNQ+qqvDdd/qcY3arDXNed+3ql/P67bcNqKpC1aoebEOH4fEPwDJzBpr0NLIeHwtWa8ncsBBCiOuuSNPwJk+ezAsvvICiKDz11FOMGDGCL7/8Eo1Gw4QJE0q6j0IIIUQOVVX5KXoxj64c6lP+1vZp9Krahycaj6VSYGVUVWV7/Da2xm/hs32ziM88T8+oYfwI+Pk50On24nTeBljo08fFl18aWLQoN1jal1g23+sfPKgFoF07N2pgEKlzF2D5bBY4HWT/mehBCCHEf4OiqmreHfCuIS0tjZMnT1K2bFnCwsKufcC/5MKF9GI5T2iof7GdS9y65HMkisOt/jk6lnyUt7ZP48foRQAEGYP4uuv3bIvfyoe73yPFnoJF50f/mvezO2Eney7szjm2YkAlvm61gbYtIhkwYA3ffXcnGRmvk539OFlZULGiv8+1/Pw8ZGZqeP55O6++6k01Hh7uISHBO6Pi1Kl0/Py46dzqnyFRPORzJP6pG+kzFBrqX2BdgSNL0dHRVKlSBYATJ/KmWrVaraSlpZGWlkbVqlWLoZtCCCFEwVLtKXRf3IlUewrl/StQP7Qhw+oN57ayLbmtbEtGN3ySxScWMmnDBOYcmI2CQvfK93BXhS4kZiXQp3pf7Ane7S78/aOx2zuRnf0YABZL7nVmGcfwkvMFEjNLAxAUlPub4sCBTt57z0j37s6bMlASQgjx1xQYLPXu3Zt9+/YB0KNHDxRF4cpBqMvvFUXh8OHDJd9TIYQQt7RlJ38m1Z7C/TUH8Xqbt/DT+0YrWo2W+6r3547ynTiZGk05/wqEWXxnP/y+2zsqVLp0EpmZrwPanLo337RxenMCI358H8/tjRm9xbtXUkSEhzJlPMTHa+jb10mbNm4aN3aX7M0KIYS4IRQYLK1YsSLn9Zo1a65LZ4QQQoj8qKrK8lM/AzCyweN5AqUrBZtK0cRUKt+67du9wVLTptG43dV96h56yIklcRYKcP8wHXMVF0lJCu3bu1m1KoujRzVUrapStaoESkIIcasoMFgqWzZ3Yeu4cePo0aMHXbt2JSQk5Lp0TAghhLjs8/2fsOL0MhqGNqJmqVp/+zw//ujEYFBo3twIKL6VNhumb77E42fF3aE9C7tlo6qg10N4uEp4uARJQghxqylS3u8WLVowb9482rZty9ChQ1mwYAFpaWkl3TchhBACl8fF61unEmIKYU6XuSiKcu2D8nHpko0jR/zp0GEdfn598tSbvp+LNjEB20OPoPoHoNN5AyUhhBC3riIFS2PHjmXZsmX8+OOPtGjRgu+++45WrVoxcuRIfv7555LuoxBCiFvYwaT9ZDjT6Vb5biL9o4p0jKKko9PtxGKZTkDAQAIDexIf/zAAtWtfwuVqkecY07dfoRoMZI0YXaz9F0IIcfMq0j5Ll1WtWpWqVavy2GOPceDAAd544w0mTJhAjx49Sqp/QgghbnHLT/8CQKvINtdomYnBsAaz+TMMhvV5ag8dehqASpU65z3Ubkd36ACuBg1Rw8P/aZeFEEL8R/ylYOnMmTOsWbOG1atXs2fPHurVq8dzzz1XUn0TQghxi/OoHhYenY+f3krnit0KaoXF8ioWy4coig0Ap7MpLldjnM5mOBwdAD27dnmDoOrVjYDH5wy6o4dRXC5cdRuU3M0IIYS46RQpWHr//fdZvXo1x48fp0GDBnTp0oV33nmHcPn1TQghRAn649xmYtNjGFDzgXwy4GVjsXyAwfALev1u3O5y2Gz9sdt74XbX92mZkgJffmkAoHp1D1fTHdgPgKte/Tx1Qgghbl1FCpY2btxI79696dKlCxERESXdJyGEEIKEzHjG/vY4APfXHJSn3s/vZSyWj1BVBbu9E+npn6Gq+acMHzHCjNPpTQxhteat1+3bA4Crbr1i6r0QQoj/giIFSz/88ANut5s//viDTZs2cd999wGQkZGBNb+njhBCCPEPTdwwnlOpJ3mq8XhuL9vqqloXJtP3eDyhJCdvRVVLF3qudesKf9zptm9DNRpx1ZFgSQghRK4iZcM7cuQInTp1YuzYsUyZMgWAuLg4OnTowJ49e0qyf0IIIW5BTreT386spXJgFZ5r8UKeer1+CxpNMnZ7z2sGSgBly3qn3k2aZM9Tp2Skozu4H1fDxmA0/vPOCyGE+M8oUrA0depUevXqxR9//IFG4z0kMjKS8ePH8+abb5ZoB4UQQtx6difuItOZQduo9vnuq2QweLetsNvzZmPVnIzG8vYbWCeOI7BPD0rVr4HxfAzhhks8df/ZPO31WzaheDw4W9xe/DcihBDiplakaXiHDh1izpw5aDQan4fWfffdJ8GSEEKIYrf53AYA2kS1y1OnKBcwGheRkVGG7OzW6K58kmVlEdSrG9r48zlFjnKVOK+WoY7jIEEDHyHl55VgNgOgOXsG67gxANjv6lpyNySEEOKmVKSRpeDgYFJSUvKUnzx5EqNMWRBCCFHMDl88CEDDsMZX1TgJDOxHSoqTsmVP0b59EKqaW+s3/XW08efJHjqMi2s3s37xGbbO3Y8NM7UrZKDfvxfrS5Ny27/xKtr482S8/Dqu5nk3qhVCCHFrK1Kw1LFjR5588knWr1+Pqqrs37+fBQsWMHLkSNmQVgghRLE7knwEP72VKGs5n3K9/nf0+p20a7eL9HQTx45pufxbnmH5L5hnfYCrUmXSJ7/M2DlNaN87irZtvSnH6w5vgqtqNUzffoUm7iy43RhW/4q7TATZI0df71sUQghxEyhSsPTMM89Qr149nn76aRwOB3379uXdd9+lZ8+eTJgwoaT7KIQQ4hbi8riITjlO9eDqedYrGY2/kJwczMGDFXLKEhM1GH/4jsAh94NeT8a7H/Dz76X45htDTpsHH3Qw8EHIevJpFJcL09dfoNu1A01yMo5OnSGfdVFCCCFEkdYsGQwGJk+ezKRJk7h48SImk0lShgshhCgRp1NP4fA4qFGq1lU1KgbDclav7uRTeiFBxe/tN1BNJlJ+WUV2zQa80d6ARqMyd242tWt7iIjwztVz9LgHnnwM/fZtOQGSo2MnhBBCiPwUGCytX7++yCdp1y7vAlwhhBDi79iRsA2AmqVq+5TrdHs4fdrIhg33A1CunIczZzRc/HU32tOnyH7gQVz1GvDFJ3qOH9cydKiDO+5w+5xDtfrjqlIVw8bfMWz8HVWvx9lWnmFCCCHyV2CwNGLECJ/3iqKgXrmKFtBoNJjNZnbu3Pm3Lp6Zmcmzzz5LamoqTqeT0aNHExoamrOXU40aNXj55ZcBmD17NitWrEBRFB5//HEJ0IQQ4j9q/pF5AHSr5LsmdvXqaPr1iwZAUVTeeCWdBx4K5MvZWtwMx1r/Ge4Cvv9ej9msMnFi3j2VADKmvY3l3ekoTgfZDz2K6h9QovcjhBDi5lVgsHTkyJGc16tXr2b58uWMHDmSSpUq4fF4OHHiBJ9++indunX72xdfvHgxlSpVYty4cSQkJDBkyBBCQ0OZNGkS9evXZ9y4caxfv57KlSuzbNkyvv/+ezIyMhg4cCCtW7dGq9X+7WsLIYS48ZxOPcWmcxtoVbYNFQMrXVGzg9mzo3Le1azpoeeRt+hLfRao/dhES3gWBh9wcPCglqZN3ZQqlf81nO07ktq+Y8neiBBCiP+EIiV4ePPNN3n55ZepVq0aOp0Og8FA7dq1mTJlyj/aZ+nKlORpaWkEBQURFxdH/fr1AejQoQNbtmxh69attGnTBoPBQKlSpYiMjOTEiRN/+7pCCCH+ffGZ5zmdegq3J3eq3E/RSwAYUPOBK1q66d3bj5Urc9cWNazrwPzpR8wIfMHnnJeTOtSr5zv9TgghhPg7ihQspaSkkJmZmafcbreTmpr6ty/evXt3zp07R6dOnRg0aBDPPPMMAQG50yFCQkK4cOECSUlJlLriJ8JSpUpx4cKFv31dIYQQ/66fTiym0de1aT63AX2X9swJmE6leqfZNQlvltNWp9vEtm0NqVgxkU6dXAA80OIomkuXCLq3HUuWZOU5f+3anutwF0IIIf7ripQNr23btjz00EP079+fqKgo3G4358+fZ8GCBbRq1epvX/zHH3+kbNmyfP755xw5coTRo0fj7++fU3/1GqlrlV8tONiCTlc8U/VCQ/2v3UiIa5DPkSgON/vn6GzaWcatfxKtRkukNZKNcb+zOXktfWr14YIjHoAGlWpi0VsASElZjdPZnXr1FP73Px2nTkH1vccBMNevQ8+eFk6ehCVLYM0a+OUXuOsuE6Ghpn/tHm90N/tnSNwY5HMk/qmb4TNUpGDp1VdfZdasWcyfP5/4+HgcDgdhYWG0bduW8ePH/+2L79q1i9atWwNQs2ZN7HY7Lpcrpz4hIYGwsDDCwsI4depUnvJruXQp76+Nf0doqD8XLqQXy7nErUs+R6I43Oyfo/0X9jJy1TBS7am83W4Gzcq0oN382/hq57e0Kd2JUxdPE2wMJjPFTSbpgIvk5E0AWK0BpKSkExwMGQeOYgVSg8NxXEjHaoVBg6BvX4iO1hAR4UEmIOTvZv8MiRuDfI7EP3UjfYYKC9qKFCyZzWaefvppnn766WLrFECFChXYu3cvnTt3Ji4uDj8/PyIjI9mxYwdNmzZl5cqVDB48mIoVKzJnzhyeeOIJLl26RGJiIlWrVi3WvgghhChZTreTgb/0JSErnpENHmdw7aEAlDaXZk/iLlRVJS4jjspBVXKO0et/IznZO0MgJCT3XNrY0wC4y+duTgtgNMoUPCGEEMWnSMFSSenfvz+TJk1i0KBBuFwupkyZQmhoKC+++CIej4cGDRrQsmVLAPr168egQYNQFIUpU6ag0RRpuZUQQogbxOrYlSRkxTOs3nBeafV6Tnn90IasjV3NqbSTZLkyibRGAqDVnsDf/wliYrwzEEJCcqdga87EAuApX/463oEQQohbzb8aLPn5+TFjxow85fPmzctTNnjwYAYPHnw9uiWEEKIELD6+AICBtR70Ka8RXIu1sav57cxaAMpaI/F4IDPzZYzGS7zwwkwA2rXLzXCnjY3BExwseyQJIYQoUTI8I4QQ4rrYEb+d0uZQ6obU8ymvFlwdgE/3fgRAef+KjBnjpFKlJVitmZw4EcLDDzuoW9c7vc6wZiW648dw1ax9fW9ACCHELUeCJSGEECVu+alfOJtxhqbhzVAUxaeuTVQ7IvzKcjI1mkqBlbmwbDTz5+duF9Gvn5Pnn7d732Rk4P/4CFSjkYxX//4+f0IIIURRXHMaXmpqKnFxcdSoUQOtVsuGDRuYO3cuNpuN3r1707Nnz+vRTyGEEDepwxcPMWr1o1h0FiY0n5SnvkJARXYM2s+GuPWc33E7Y2cE5dR165bNhx/mZknVHdiP5uJFsh4dibte/evSfyGEELeuQoOlDRs2MGrUKJxOJ9WrV+f5559n3LhxdOvWDfCmFHc6ndx3333XpbNCCCFuPm/veINMZwafd/6aeqXzD3D0Wj0dy9/JqDe8eyNt2tSSkJDGWCzTfNrpjh0BwFWvQcl2WgghhOAawdKsWbMYPXo0ffv25fPPP2fChAlMnz6d9u3bA9CtWzemTp0qwZIQQogCHbp4gGBjMD0qX3smwv796QQEaGne/AhpaW/hdvvWa48eBsBdo2ZJdFUIIYTwUeiapejoaB5++GFCQkJ47LHHSEhIyEnlDdCsWTPOnj1b4p0UQghxc3K4HZxOPUXV4Op51ipdTVGSSExUKFcujrS01bjdeUehdEePAuCuVr1E+iuEEEJcqdBgyWazYTAYAPD398doNOa8B1AUBY9HNv8TQgiRv/jM87hVNxUCKhbaTqs9TlDQnWRnmzAaA3G7q+Xf7uhh3JFRqNaCd1sXQgghiotkwxNCCFFiErLiAQi3lCmwjUZziqCgO9BqT2KzmTEYwvNvdy4ObUI8rvoNS6SvQgghxNUKXbPkdDoZM2ZMge8BXC7X1YcJIYQQACRmJQIQZsk/AAIwm79Co0nhwoXpf77Pv51+0wYAnE2bF28nhRBCiAIUGixdnRY8vzTh99xzT/H2SAghxH9GzsiSX8HBksHwE6pq4dKlIQCYTGqeNkrKJSwfzgDA0aVbCfRUCCGEyKvQYGnatGmFVQshhBCFSsxKAAoeWdJqj6PTncBu74HNZgHyH1kKeGgQusMHyX7wYUnuIIQQ4rq55qa0V7tw4QJLly7FZrPRtWtXKlWqVBL9EkII8R+QmOkNlgpas2QwLAfAbu+Ga+N2oAPmzCTAmtNGe/AAhk0bcLTtQMb0d0u6y0IIIUSOQhM8xMTEcO+999KkSROmTJlCQkIC99xzDwsXLuTnn3+mT58+7Nix43r1VQghxE0md2QpLJ9aN0bjYlRVwX28OvrRTwJgPXPUp5Vp4XwAsoc8DBrJSySEEOL6KfSp89ZbbxEREcHUqVOJjY1lzJgxPPTQQyxbtoxly5Yxfvx4ZsyYcb36KoQQ4iaTkJWASWsiwBCYp85qfQa9ficOR2d0r37GA8wFwHLpXG4jmw3Td9/gCQrC0anz9eq2EEIIAVxjGt6ePXv46aefKFWqFI0aNaJjx47Mnj07p75v374SLAkhhChQYlYCoYYoVFXhyj1ptdojmM2f4XLVJmvvRNYtmcF+vJvQ+iWdAY8HNBoM69agSU4m67EnwGT6l+5CCCHErarQkaWMjAxKlSoFQEREBDqdDqs1dx65wWDAbreXbA+FEELclDyqh8TUDM48e5yRI30DHaPxJwCyssah3R3NPAbm1DmdKrq9u9Ht2YX/2NEA2Hvfe/06LoQQQvyp0GBJVX3Tt2pkrrgQQogiSrYl406OAmDJEr1PnTdduAG7vTNx0XaWcjcAIVYbHVhH4IA+BN/VHiUlhfR33sfVsPF1778QQghR6DQ8t9vNvHnzcoKmq99fLhNCCCGulpiVAJmheco1mlPo9fuw2zvx1VchTHjrMQBeGnyEUW9HYv6mO5rxKwGw9x2AbfDQ69ltIYQQIkehwVJYWJjPGqWr318uE0IIIa4WmxYDGRF5yo3GnzhypAZr1kzk9deNOeUD+2ahKGB78CE8EREYFy0k44VXrmeXhRBCCB+FBktr1669Xv0QQgjxH7MzYTukl8157/GA0bgaP7/XqVUrK6f8jtK7mZfUGU2VP7g8b8HRqQuOTl2uc4+FEEIIX7IISQghRInYHr8VUnI3Lh861Mi0abE4ndqcsnHj7CwrP4JQbTJqSMi/0U0hhBCiQIWOLAkhhBB/h9PtZHfiTvwyXiMT0OlUVqwwsGLFGNq0yV33OnasA+38eDzhZWTDWSGEEDcceTIJIYQodgcv7ifbmY1yoRZBQSpbtmTm1D3//MMAPP64HYPOgyb+PJ6IvGubhBBCiH+bBEtCCCGK3c6E7XD2NjIuhNKxo4tq1ZayZUsHAPbuDUCvV+nc2Y1y8SKKy4UnXIIlIYQQNx6ZhieEEKLYnUo9CQn1AOjceTGBgQNp0ULDK69sJC6uOSNGOIiKUtHsPw8gI0tCCCFuSBIsCSGEKHax6bGQ3A6AWrW+x+MJIiVlNSNHVgfsOe208ecAcEeUze80QgghxL9KgiUhhBB/2YpTy9hw9jcqB1WhW6W7ibD6BjunU0+iTR6JG6hV63eczja43dXznEcTHw/gTfAghBBC3GAkWBJCCPGXHL90jCHL70f9c1ekSRueoXVkW9pGtcfutpPmSOVI8mEsqfUwBNkICblIRkbbfM+lOe8dWfLIyJIQQogbkARLQggh/pId8dtQURlSZxi1Qmqz6NgCNsStZ0Pc+pw2oaYILiWVo07DEygKOJ3t8z2XJuHPkaUysmZJCCHEjUeCJSGEEEXmdDv5/exvAPSrMYBmZVrwcN1HiU2LYUfCNkqbQ3F5nJTObsGdTg3Vq+/B7Y7MdwoeXDmyJMGSEEKIG48ES0IIIXwcTDrAoYsHqBxUhSj/8oRbwgF4Y+tU/m/XO3hUD5HWKOqWrp9zTPmACpQPqJDzfu1aLQA1auzH4egAKPleSxMfj2rxQ7X6l9wNCSGEEH+TBEtCCCFybD3/B/f9dDd2tzdjnYLCu+0/INI/ind3vkWgMYguFbvxdNNnMOvMBZ4nJuYUUIeqVWOx2R7Jt42SfBHdiWO4K1cFJf9gSgghhPg3SbAkhBCCLGcWY9aO4qfoxQA8UOtB/A0BfHXwc6ZseR6tokGraFl0z1LqhTYo4Cw29Ppt6HT7ycxUgDpYrSNxuerm29r07VcoNhu2AQNL5qaEEEKIf0iCJSGEELyz401+jF5Eg9BGPNt8EndW6AxApDWSFzY9B0DbqA4FBkoazXkCA+9GpzsGQHr6/wFgNtcHPHkPcLsxf/EZqsUP2/2Div+GhBBCiGIgwZIQQtzinG4n3xyaQ6g5jJ96r/CZXje8/igCDIHM2vsBj9Yfmc/RKhbLa5jNn6HRXMJm64fD0YELFwYAYLWq+V5Te+wo2nNx2PrdjxoYVBK3JYQQQvxjEiwJIcQt7vez60ixp/BovZF51iEpisL9tf6fvfsMjKroGjj+v9tbeqGHGnoLIEXpihRp0jsqoj4qNlQQ0RfFBgooAooiIiCKogLSpUvvvYZek5C+STbb7vthMWFNQFSqOb8vJjPnzp27Lgtnp/WhZ6X8R3/M5s+xWkfj9UZgt79NVtbzgILdbgLAZsv/nrp9ewBw1Yy5Yc8hhBBC3GiSLAkhRAGW4cpg1JZ3AehQrvN1X6fRXMRiGYnZPAOvN4Tk5HV4vbnbf9vtvg0brNb8R5Z0+/cB4KlaPd96IYQQ4k6gud0dEEIIcXt4VS9PLnuUXQk76VGxN/cUrnudV7o5d+7CyhunAAAgAElEQVQ5NJrZuN2VSUlZlJsoZWZiWL6UjEPnUBQVqzX/FnT79vpaqlzl3z+IEEIIcZNIsiSEEAXUjrhtLDu1hIbFGjOmyXiU69y+e8eOFdSosZjHHltOcvJ6PB5fwmOePJHwCiUJ6tWVzLPJBCj2/HcEV1V0+3bjKVkKNTDoBj6REEIIcWNJsiSEEAXUwaQDAHQp3x29Vv8X0R5MpikEBz/Ivn2bAJg1qxHgO3xWt3sn1hHDUQMCyRz0IsmacIK8yWjOnc3TkvZ4LJqkJFy169zIxxFCCCFuOEmWhBCigDqU6EuWKoZW+otIlcDAPgQEvIROtxW9Pu/udebJk1A8HtImTCZ5yFucVYtSipMYFi/IE6vbugUAV53rnfYnhBBC3B6SLAkhRAF1KPkQAOVDK14zzmyeiNG4EJerDomJh3G5XvarN/7wHaY5s3GXKYuraXNOndLgVTWUVU5gnvYVqP6bPBjWrALALcmSEEKIO5wkS0IIUUAdSjxAiYAobPqr7O8NGAzLsNmG4fEUIS1tKqoaicuVW68kJRIw+Dm8QcHsfmcOaXYN06f7pvRVqAq6I4fRb1iXE2/8/ltMP/2Au1w0btkJTwghxB1OkiUhhCiAMlwZJGTFUyao7DXjTKaZAEyb9hvTp0f7rs3I3bVBWbyMM9mRHO3/Bvf0rkGrVhbWrtWi0aj0GVoIAOP8X3zBLhe2N1/DGxRM2szZoJPTK4QQQtzZ5G8qIYQogOIyLwJQxFb0GlGZGAzLSE2txuOP+3a8697dhd2eG/HQiEZs5jTmyV5UVSE21rfhQ+XKHoxN6+K12jD8thRGOtFv3ogmJYWsAU/gKVPuZj2aEEIIccPIyJIQQhRAF+0XAChsKXLVGINhOYqSyWefvZtT9ttvOr+Rpc2pvs0hsrJ9f50MGpRNVJSX9u3doNeT3aMX2rNnCC9dhICXBgGQ3eqhG/48QgghxM0gI0tCCFEAXcg4D0BhW/7Jkk63CZvtZdLSAvjww1Y55R99ZKBaNS8AIwt/yucXH6ZqjJZuzwaj1UKbNm7eeMOZE5/5v0GYZkxDcTrRnjqJu3wFXPc2vIlPJoQQQtw4kiwJIUQBtCNuGwAVQ/JuG67VHiU4+CHAw9SpC0lK0jN4cDZffGHgwAENXocLBS0vXhzK4F5bsY+bAIo73/t4o0qSvGoDSmYGit2Oq0YM6P/qTCchhBDiziDJkhBCFECrz6zEorNSp3De7btNpm9RFBfp6RNZtOgBAPrufY3gMnV5Y3cPDsSaqMhBTIUCSRo9DhQlTxtX8kSXvynPIIQQQtxssmZJCCEKmLPpZziadBTDN5t4/52AP9V6MBp/wOsNZOvWHvz2m44IWybVln3MI7tfRsE3BS+GnaR/+jkYDLf+AYQQQohbRJIlIYQoYNacWQUXa5JytCoTJ/onOwbDIrTas2Rnd+bHH33nL70V9gkaVAI/eZ2m1RIAiH6zE66mzW9534UQQohbSZIlIYQoYLZe3AynG+Up1+m2Y7O9DsDmzYOZMkVPkQgn/U+NxNm4Gdk9+/Dk6wGEh3t54AHPre62EEIIcctJsiSEEAXMibTjEF815/f0dFCURIKC2qHVniQ5eQhPP10Rt1thUpu5WMjC0bkrAM2bezhwIIOKFb23q/tCCCHELSPJkhBCFCCqqnIi9TiGpJicspUrdbhcM9Bo7Njt77BgwZscPKilZ08XD+pXAuCpUvVqTQohhBD/WZIsCSFEAfLdoZlctF/AG5+7ZfjAgWaKFn2DZ56ZTGbmYznrmPr0caI9fQoAT1TJ29JfIYQQ4naSZEkIIQqAxKxEBq9+ntd+fxmboyLuTCtt2rgYPdpBs2aJAEya9AS7dgWyebOORo3c1KnjRXvqJN7AINTgkNv8BEIIIcStJ8mSEEL8x6U70+i1sDMzDnxNoCGIZ4p/DkDFil4effQiixd3okSJ0wB89plvVKlvXxeK6kuWPKVK37a+CyGEELeTJEtCCPEflpqdQtf5HdgZv4MeFXuzq99BbCn1AKhYMZWQkEYYjWt5+unFAMydq8dgULn/fjea+DgUh0OSJSGEEAWWJEtCCPEfle3Jpuv8DuyI307X8j0Y13QCWo2WEyd8H/2VKi1Dqz1LZuaTNG/eC4NBxWJRGTfOQUAAaE+eAMAryZIQQogCSne7OyCEEHcCVVWZc2Q2FzIuUMhSiO4Ve+Ubdzb9DOvOraV8SAViImujKMot7un1W3JiIbsSdvJwuc6Mb/4ZWo0WgIwMX5/DwlYDkJX1LKVLw4oVmQQEqBQtqgKguZwseUqWuuV9F0IIIe4EkiwJIQSw7NQSnlnxRM7vlcIqUz2ipl9MXMZFOsxtzZl03/qejuU6MbbZBGx62y3t6/X6+egcAF6o/UpOogTgcPj+Gxi4CY+nGF6vb6e7ChX8z076Y2RJpuEJIYQoqCRZEkIUOFnuLPZd2oPL4yLCEsnC4/P5Ys8kAFqXbsviEwtoOacZFUIrERVYksphVUjLTmVu7E9cyrrE/VEtSHIkMjf2Z+Iy45jXcfFtfqK8nB4nq04vp0JIRSqFVfary8ryjSzZbGdwuR7Iv4HsbIzzf0FVFDzlK9zs7gohhBB3JEmWhBAFiqqq9FjQiY3n1/uV6zQ6XqrzKk/XGMRDP8dyLDWW2OQjHEjcx5ITCwEINYUyrN6bPF9rMG6vm+4LHmbdubVsu7iFOoXr3o7HuarDSQdxeBzUK3JvnrqsLN9/zeYsnM56+V5vmTQeXexRsgY8gbdQ4ZvZVSGEEOKOJcmSEKJA2XB+HRvPrycmsha1CtVhzZlVDKj2JJ2juxJs8p0l9HvPLXi8HjSKhgOJ+0nNTkFFpU7huhi1RgD0Wj0Dq/+PdefW8trvr7Csy+o7av3StritANSMjMlT53C40WpBq7XgcHTJU6/ExWEZ9yGeyEJkvPbGTe+rEEIIcaeSZEkIUWCoqsq47R8B8F6jD6ld6J6rxv6xxqdKeNWrxrQu/VDOtL2x20fTsFgT6haud9WkKTErkTfWDyUhM557izbk+dqD0Sg3Z1PSP0bD7ivWKE+d05mA2RxMZuZwVDUiT71+53YUhwPHi6+gBgbdlP4JIYQQdwPZOlwIUWCM3zGWtWdX0aR4s2smSuAB1Otqc1DMCxg0BkZteZd2vzzIJzvGXPP+c47MZs3ZVby/ZSRzjsz+ew9wnX49NpdVZ1ZQt3B9SgeVyVPvcLgxm7NwOPrne7326BEA3BUr51svhBBCFBSSLAkhCoRlJxfz7ua3KGYrzoT7J181TqM5RmhoZcLDCxEWVpLQ0OoEBAzEah2GyfQNWu0Rv/g6heuyrudWJj3wJeHmcCbs/ITErMQ87Z5JP82cI7Ox6Cys6rYBvUbP/60fRooj+YY+p9vr5rXfX8GsM/NJ84n5PN9xsrI0WCxewJRvG7pDBwDwRJe/oX0TQggh7jaSLAkhCoTJu3273U1v8z2FrPltWKBiNM4iKKgLWu0FVFWP11sIRUnGZJqNxTKBgIBBhIbWISioA4qSmxCVCipNl/LdeabmC6Q5U2n1UzOOpx7LqY/PjKfr/A4kZMUzpO5wqoRXZXCdISQ6Emn1U3N2xm2/Yc+56cIG4jPj6F6hF2WDo/PUm81fk5VlxmjMP1EC0G/ZhDc4GE+ZsjesX0IIIcTdSJIlIcR/XrIjiQ3n11ErsjbVwqvnG2MyzSAw8Cm02uNkZT1BYuJZkpO3kJh4gsTE3SQnLyc9fTxOZyMMhlUEB7dDq431a+N/NZ/lxdovcyrtJO9sHJFTPmBpX46nHuP5WoP5X81nL8cOok+l/pxIPc7La164Yc+66PivADxUpn2eOp1uC2bzFDIzrRiN+Z8Npbl4Ae2pk7jq1geN/BUhhBCiYJMNHoQQ/3mrz6zEo3poXbptvvVa7RGs1mF4vQGkpKzG47lyREaH11sar7c0bnddHI5+2GyvYDZ/SUhIbRyOR7HbxwEKGkXD0LpvsPL0ChYcn0fkpEBCjCEkZydzf1QLhtV7M6dVs87M2GafkuhIZPGJBexJ2JXnENx/YvOFTZh1Zu4t2tCvXK//naCgDiQlBZKZaSEoyJPv9fqNvi3VXXUb/Ou+CCGEEHc7+dpQCPGft/fSHgDqFqn/pxovNtsLhIQ0QKNJw24fi8cTjW73TvS/rwFVBbf7T9dosNvHkJr6DR5PNGbzVAyGRTm1iqIwuM4Qv99DjCEMq/dmvrvk9a7UF4AfD3//r59TVVWOpx6jVGAZ9Fr9lTVYrcNRFDdz5y5GVRUaN84nWXK5MM38BgBns/v/dX+EEEKIu52MLAkh7ip2ZzoTdn7MD4e/p6itGF+1mkEhS6Grxqc709hyYRMAFUMr+dWZTN9gNk/F7S5LZuZgsrO7o7l4gZAWTXJiVK0Wd526eEqWIvOZ5/FU8u0Q53Q+jMdTmZCQBgQEPEdGxiVcrlp4PNVoVboNy7qspkRASUJNobi97j8lL7malrifAEMgy08vYyQf/KvXJj4rngyXPc8OeLt37yM6OpFChR5m794aANxzz5+SJVUl8MnHMPy+BmejJniqVvtXfRFCCCH+C2RkSQhxV3l93RDGbv+Qs/YzbLm4iWrToin/VRS/HJ2TJ/a9TW9TdkpxtlzcRNXw6oSYQgHQamMJDOxGQMDzqKqF1NT5xMb2pWxZG9M+Ss+53lW3Pp4KldBv3ojph+8IeaARxu9m5tR7PBWw2z9Ao0m4vPnDfZjN4wGoGVmLMHMYiqJcNVECMGgNlA+pwKm0k3i8+U+Nu1574ncCUDGs0uX+Qf/+Jlq0uJeuXX8kI+MRFi70fUcWHe31u1Z7+BDGBfNw1b6H1Onfwx10wK4QQghxu0iyJIS4a5y3n2POkdmUC47m2ONn6V2pH8VtJUjJTmH4uqE4PU5UVWXfpb28vfFNPt7xEYUshWlVqg3vNhx1uZUsgoI6YTQuwelsSErKYrzeEsyerSc9XeHl6bUBSP1qBikLlpG8egMJZxJInTEbNSCAgFdeQHP2TE6fHI4nSE5eS3r6BDyeYthswwkKaoNOtw1FSUZRkgDnNZ+rZGBJ3F435zPO/ePXZt25tby5YRgA9Qr71ht9/LGBxYt9idrWrXXp0aM1sbFaYmI8RET4nyNlXDDP9+o8/iRYrf+4H0IIIcR/iUzDE0LcNb7Y8xkur4tnaj5PgCGQcc0mAPDGuqFM3jOJ4pPD/eKNWiMz28ymRmQMoKLXr+PcuW/xeLIIChqI3f4R4BtBOXw497ujI0QTXvqKqWxGI86WrbG/9R6Bg57CMmYU9nETcqrd7pq43TVxuepis72AwbAOg6F5Tr3XG0Jq6mzc7j+vmfIpFVgagEOJBygREPW3X5eLGRd4ZHFvMlx2HqkygMbFm6KqMGqUEYC6dTezZUs9li/XU66ch9mzM/MMHBkXzEc1GHA+2Opv318IIYT4r5KRJSHEXSE+M57p+78m0lKILhW6+9W9WOcVOkV3pX6RewkxhlAjIobxzT9jQ6/tlxMlsNlewunsT9WqM2nRYj12+/uAwjvvGJg2Tc/pU7nZQwWOkFLMf30TQHaX7rgrVMT03Uy0sUfz1Hs8FUlNXUJKys+4XPXJzm5BdvaDKEoKwcEdMJvHAGqe65qW8G2msOjEgn/02ozfMZY0ZyrvNfqQ0U3GodVoSb7irNuXXlqX8/O4cdkEB/tfrz0ei+7APpxNmqEGBP6jPgghhBD/RTKyJIS443lVL8+tfAq7K53X67+JUWv0qw81hfF5i68A8Hg9KIpvG29FSUSvX4hWu5Pjxzcyc+Y7AOzbVxaXKx23G8aPz20rnAQuEQHAlGkWXnzxT9PntFoyhr5B0KO9sYx6l/Qvp+XbX5frAVJSHsj53Wj8Gat1CDbbW7jddXC5mvjF1y1Sn0KWwiw6/iujG4+75hqnP/N4Pcw/NpdQUyh9Kz9CdjYsX64jOzs3pnHj6vTv72TvXq3/xg6qin7dWiwTPwEgu22H676vEEIIURBIsiSEuOMtOr6AlaeX06zE/TxadeA1Y7UaFybTj+h02zAa56LRJDNzZm/69t3vF1enjpXZs7P8yuqZ99DxnWoMHBzJ0aMaBg82kpKiMGWKI2famrNNW1w1YzDN+xklw467Vh0yX3gZdFf/OM3O7oTHE0VISHMslo9ITfVPljSKhrZl2/PV3i9Yd24tzaKuf9vudefWEp8ZR9/Kj6DT6HjmORO//JKbbP3f/72PTvcUH36Ymz2ZZkzDNGs66PToN28EwF2xEs6H2l33fYUQQoiCQJIlIcQdb27sTwC82WAkGiXv7GGdbidW6wgUJQmt9gIaTTwAXq+NzMzBLF3aO881Fy5oGDXKAEAF8ymOZRXliccdxHQ1w2CYMyc34XjzTZXkZIURI7IJDwf7+x8R1KcbxuXLMC5fhm7fXrI7dsJdtTqectHg9WJYOB81OAS0WnC5cDVphtPZDINhFTrdFtzuun79aVGyFV/t/YLNFzZcd7Lk9roZsWE4AL0un9d05dorgMKFg7nyo15JS8U2dDCKy+VrI7o89o8+wVWvAWhkZrYQQghxJUmWhBB3NLfXzeozK4kKLEXlsCp/qlUxGJYQGPgoipKJ12sDjGRmPofD0R2PpzxgJDLSkHPFunUZbNqkZcQIIwsX+hKi/2WNZUD9PWQN+wW0EByskpKSu4Zp8mTf9ZUre3j6aRfu2veQuC8W7dEjhLRsinHRrxgX/Qr4DnNVEhJYsa8I5TlCGU4AkLRyPZkxr2IwrCIwsB/p6Z/jcjXNuccfZ0DFpsRe92vz3aGZ7E/cS4+Kvald6B7ffZIUSpb00qvXYg4dyqZt2wi/a/RrVqG4XGQ+8zzOB1vhql5Tdr8TQgghrkK+RhRC3NF2xG0nzZlKsxL3o/xpCzebbTBBQd0BB6mp35CYeJ7ExBNkZLyDx1MN8K1HSkvzXbdiRQbly3vp18/FgAG565EKtahM1rx5vlEgwGr1bcIQFeVlxAgH5cv71vls3HjF90taLZ6KlUhevJL0sZ+S8fJQvOHhGFatIGvfCVqzhLIcJyuiOADGBXNxue7Dbh+BRpNAYGAfFCV3F4Yi1qJYdFZiU/JuHHE1c2N/BuC1um8AoKq+ZCky8jTvvdeWOXOexGj0n/JnWL4MgOwOD+NqcJ8kSkIIIcQ1SLIkhLijrTi9FICmJZr7lWu1hzGZvsLtLk9KyiqczocB0Jw4ju3FZwm5tzYhTe/F9uqL2DcdBHwjRn/o0sWd83O5PrX9DmGtW9eXHLVu7ebpp12sW5dJqVJeNm7U4rm8P8IHHxj49VcdnspVcPTpT+arw0jcF0vi9n0cWXUkp61f3toGgG7vHgCysl4iI+P/0GjSMJtztx9XFIWyweU4nhKLV/U/MDY/Lo+LLRc2UiWsGkVsRQHIyACnUyEyct/l12URYMq9R0ICxl/n4SlcBHf1mn95DyGEEKKgk2RJCHHHcrgd/Hh4NhadJU+yZLGMQlFUMjLexp1dHfP4sQQ8+Shh9Wpi/nY6mosX0R4+iHnaV6Tv8x0iG2LN3eSg6rmlOT8Xb1Her+1RoxwMH57N0KG58ffe6yYtTWH/fg2XLimMHWtkwAAzO3Zc8TGq0eAtEUWKOyCn6JeVoXiKl0C/ZTPY7QBkZT2Gx1MEi2UcOt3GnNjokGgcHgdn03MPvb2aI8mHyfZkExNZK6csMdGXZIWFpZGaOg+Pp2LuBVlZBPXrgcaeTtYzz8n6JCGEEOI6yN+WQog71oSdH3PWfoa+lR/Bqs+dLmYwLMRo/AmXqwZOZ2uMc2Zje2cEpl98G0FkPvk0Fw+cZkD3FBaO30diSDm0uIkc8wZKXByGRQsI6teT87oS7Ji2Ca3Of3pfcDA895zTb4bavff6hpS++MLAuXO58S++aCI5GXbu1BAb6ytPTc2tX7JER3LXR9GkpmCeMe1yqQ27fRSK4iYkpCUWy4cARIdUAOBw0sG/fG32XtoNQNWI6jll6elbAAgJCcPrLeYXb54+Ff32rTg6dyPriaf/sn0hhBBC3AHJ0vz582nfvj2dOnVi9erVXLhwgb59+9KrVy+ef/55nE5nTlznzp3p2rUrP/74423utRDiZktxJPPJjjEUthbh1brDcspNpq8ICuoJ6MjIeBtQMKxeCUDqN9+RuOsgGSM/YNtOA1/PstH2uSrsc0YToknF+uVnhFUvT9AjvUCnxzxrAsXb/HnTiPy1auUmMFDlhx/0tGiRm0UdPKilQoUAWra0cu+9Nk6fVnKSJYtFxW5XWFDmGbxWG+ZJ4+HyLnROZ0dSU3/A4ymGxfI+Wu1RakT4psbtjN/xl/3Zf2kvANXCfcmS0TiLrKxPAQgKKp8n3jj7O1SdDvvID/ymHAohhBDi6m5rspScnMzEiROZNWsWn3/+OStWrGD8+PH06tWLWbNmUbJkSebMmUNmZiYTJ05k2rRpzJgxg2+++YaUlJTb2XUhxE22M34H2Z5selbsTYAh8HJpNhbLaLxeG8nJv+NyNfMdrLr+d7zh4ThbteGQvQSjRhnYuzf3482eoSUwKoj0D8bgrl4TVVHIeG04rqbN8795PgIDoVcvl19ZWFju2qLISN/PderYGDDADEDv3r74BatDyO7wMNq4i2iPHM65xulslTPCZLW+Qa1CddAqWj7fPZFp+77C7kwHfIfyTtr1KUPXDmbE6hEcTT7Cloub0CgaKodVRaM5TUDAiyQk+NYuBQcX8eun9thR9Pv24Ly/BWp4+HU/sxBCCFHQ3dZkaePGjTRo0ACbzUZkZCQjR45k8+bN3H+/74yRZs2asXHjRnbv3k21atUICAjAZDJRq1Ytduz4629ehRB3r+1xWwGoFp67EcGWLet5+eVXGD36GzyeyowZY6B0KStlLm5ke5U+oCg8+aSJMWOMDB9u8msvOFTB8dhAUn5bw6VziWQ9+czf7tM993hyfm7a1M0zz+TuqNexoztPfIsWbmw2lf37Nbir+UaAdAf2+cU4ne1wuephNC6iUMAuBlR7ArsrnVfXvkiVaeVo8n19Cn8WzIgNrzN135e8teYt7vuuDjvjd9CwWBNwWpk8eRtpaXrOn+8PQGio6ncP3Tbfa+n8G8mhEEIIIW7zOUtnz57F4XDw1FNPkZaWxqBBg8jKysJg8J1pEhYWRkJCApcuXSI0NDTnutDQUBISEm5Xt4UQf8Px1GMYNAaCTSEYNUb0Wv1fXpPsSGLqvi+x6Kw0LNYIgN273bRt2yEnZtYsD3v3+rb6zqAkE7z/4yMgIyN3itnEiVl8+aWBXbtyd7EDQPfPPvrq1Mlt5LHHnH6z2WJiPH6xL7yQTZMmHipW9LJrl4as6GoEALoD+8n2i1TIyHiToKCHCQrqygdNf+SRKo8z/cDXLDw+n/MZ5wEIMATy+QNTiPec46d9v1DEWpSnaz7DW28dZtq0/kyc2JoOHYKAvMmSfpfvyyV3zVoIIYQQ4vrd9kNpU1JSmDBhAufPn6dfv36oau5f8lf+fKWrlf9ZSIgFnU57Q/oZERHw10FC/IWC8j46n36eZxc9y4mUE+y6uMuvrknJJrxy7yu0KtcKrSb/P5/T1n/OpawE3mn2DtElooAkVq+eDzySE/NHotSYNaylCZds5YiI0BAeDidPQnIyBAebOXgQdu2C3bu1//r1j7jifNfy5S0EBeX+/sQTZhYsgIULYdYs6NnTCBipVg22bYPUkvWJBCzHDmPJ0482wDKgOSEhw2gQsocG5T8FfGuQTqacxKg1UiTAN73uhfovXL7uBdr/9DYA589H8tlnvs0pGja0EBJyRfP7doNOR0jTe8HkP+ImCqaC8lkkbi55H4l/6254D93WZCksLIyYmBh0Oh1RUVFYrVa0Wi0OhwOTyURcXByRkZFERkZy6dKlnOvi4+OpWfOvzwhJTs68If2MiAggISH9hrQlCq6C8j7yeD20/6UD2+N85wvFRNaiVGBp7C47SY5E1pxaw5pTazBqjTxdcxCv3DMMnSb3o+hA4n5Grn0Hk9ZEl9K9SUhIx2h8jB9+GJ0T8/LL2aSmKuybtpu3bWNpldWYc+dVEhLSOXfOSlQUuFwZJCRA69YaJkyw0qWLi4QEx79+viJFrFy4oEGvtxMYqFKypJXWrd0kJmbz9dfg8fjOtv1j8DsiwgAY2XlcT5mixWDPXpLyfR/Uwmbrh9k8jYyM13A4+uH1RgEarISBSyXBkXb5fWRHVXfSvXsH0tMD/VoZMSILt9udc3/t3j2EbN+Ou2o1UtJdkO7Ke2tRoBSUzyJxc8n7SPxbd9J76FpJ221Nlho2bMjQoUMZOHAgqampZGZm0rBhQ5YuXUqHDh1YtmwZjRo1okaNGgwfPpy0tDS0Wi07duxg2LBhf30DIcQt5VW9jN76LtvjttGmdDsmPzgVo9boF7M3YTfPrniSg0kHGLf9I6bs/YJBMS8QYgpl68XNzIv9mWxPNp+3+IpQUxiZmWuJjJwLQKNGbho39tC7t4sIQwrhX9bFWaM54bEqu3drWbFCy4ULGho1yl0/dM89XtauzaBEib8+6PV6rFyZydGjGkqU8I1wb92a4Vev/dNgWVSU775nzmjwRJVEv2UTOJ1webrxlTIzX8No/AWr9SOs1o9QVQseT2FUNQyt9igajW9jm9DQksyZ05DVq2cC8N57DrZs0RId7aVnzyvWTjmdBP5vAIrbTcbQ4Tfk+YUQQoiC5LYmS4UKFaJly5Z069YNgOHDh1OtWjWGDBnC7NmzKVq0KB07dkSv1zN48GAGDBiAoig888wzBATc+cN2QhQ0H259n3HbP6KotRjvNhyVJ1ECqBZRg0WdVzAv9mc2nF/H/NhfeG/z2zn1gYYgRjceR6foLmzfPo/Wrfvk1D37rJNmzXxrg/SL1wHgqlkLYn31PXtaAKhXz3/9UMWKNyZRAggLUwkL8/x14GXFi/uSqnPnFKe0rwoAACAASURBVLzFS6Bs2oDm/Dm8pUrnifV6i5CcvBqT6We02oNotUfQai+iKCfwegvjdFbFYFBRlEOcPl0Z8G068eijLh5/PO+IkX7DOnRHDpPVux+u5i3+4RMLIYQQBddtX7PUo0cPevTo4Vf29ddf54lr1aoVrVq1ulXdEkL8AwuOzcOis7K82++Em6++RbVVb6VXpb70qtSXwXWGsPL0bwQZg/F4PdQr0oBSQaXJzPyJzp275lzTrp0rJ1EC0K9bA4Dz/gd5obiTNWu0lCihcv68Qs+ed85Us0KFfIlafLyCJyoKAO3JE/kmSwBeb1kyM1/5U6kH3+alChERASQmpnPqlC8RfestR57RrD/oN/oSSmfb9v/2MYQQQogC6bYnS0KI/4YkRyKHkw/RuHizayZKPi602oN4vSUoHVSGAdWe9KvV6baRnDyRzMxHcsquTJTAt6ucqii4q1WnXz0X/frdOQnSlSIjfSNLcXEa3K3rAGBYu/r6znhS1csHyObNhuLjFb/2814DhvXrULVaXHXr//MHEEIIIQowSZaEEP9YujONFad+o26R+uxJ2A1AvSLX+oe5A7P5C0ymqeh0x1FVI253dTye8ng8UaiqEYNhGQbDBnbubAZA+/YuQkNVunS5IhnyeNDt24unVGmwWG7iE/57NhuYzSrx8QrO+xrjDQ3F/MUkstu2x12rjn+ww0HggL7od2zDG1kY7YljeIOCQa/HE1USZ7P7QXUREHuC5DVDgBpEROQmS6avp2B99y2y27bH2a4Dum1bcMfURg3w3wRCCCGEENdHkiUhxD+S4cqg+6+d2Ba3hTBTGBGWSADqF7nXL06jOYnZ/DWKkoZOtw29fjeqqsfpbI5Gcw6dbid6/daceFVVcDqbcPq0bx1TgwYeBgzwHzXSr1uLJjWF7LtgepmiQIkSXmJjNaR7regnTSGoZ2cCXnyW5DWb/GLN06Zg/G0pqsmE7qBv5EzxuFHiLrL9bGEqbhgLpGMC4hlCIGmYPRmADcsHI7GO/dDXzqwZmGfNAJCNHYQQQoh/QZIlIcTf9uPh73lmxRMAFLYW4VJWAomORABqFfKNlmi1sZhM32I2T0JRsnKuzcrqS0bGSFT1j4OmXWi1J9FozqIoWbjdVcnOjmLqVDMAISH+08x0u3YQ+FhfVEUhu3O3m/ykN0bnzm7ef9/IDz/oGTDgAZwtWmJctgTNmdN4S/jWMaGqmKZ9hWoykbj7EOh0qHoDGI3M/kHPoEFmGleJZ/XEQySZg7jQtDSFsi5ie3s0rgb3YR37Ie4yZUmb+QOGpYvRnjyBq8G9uJo0u70PL4QQQtzFJFkSQvwtG8+vz0mUOpbrxMT7v+RoyhFGb3mPSmGVseqtaDRnCQ5ujkaTgtcbhN3+AS5XXUCLx1MBUK5oUY/HE43HE51TMnKkkd9/9308hYb6J0vW/3sdTXoaaZOn4mrY+CY/7Y3Rp4+LMWMMjBljoF07N/oWD9Fj2RM0fWwDD8+P4sMPDaTuOs2Xx8/g7vIwakio3/VbtvjWLK3dH8lPCZE0bJhOYraNCsaDmKd9hXnaVwDYR4/DUy6arHLRefoghBBCiL9PkiUhxHU7mnyEp5cPREFhbNNP6VWpL4qiUDmsCtNaf3s5SiUg4Bk0mhTs9v8jK+tJwObXjmnql5i//AxP5ap4ihVHycpCtdnwBgejOJ0s/v5VwHcOUa1q2fzxUaXbtgXDxvU4mz9A9sNdbtlz/1sRESpt27r5+Wc906fr6dqpL3MJYu5ueKHkH1HRNDIMoPNzj+S5Pj5ek/PzkCHw4INGvF6FkGbVSG/yEfod23A2fwBX46a34nGEEEKIAkOSJSHEddl3aS8d57YhzZnK8Ppv0btyv3yi7FitIzEYVuF0PkBW1kv4jyIBbjeWT8ehPXcW3bHYPC2kEMQp3qMMx1hDE8KH1CVzyOt4ypTFMn4cAJnPvnDjH/Ame/XVbH7+Wc/o0UaCgtR8Y74sNoKOFc15yuPiFIxGlfr1PaxZo+Pzzw2YzSqt2ik4uj6BY8ATN7v7QgghRIEkyZIQ4rp8sWcSac5U3m/0EQOq5f+P88DAgRiNC/F4SpGePo48iZKqYnvlBbTnzuLo0ZuMIa+juXAe1WpDybCTdj6DBoPvh1ToXH43RS+ko5n/C6b5v6DqdChuN66YWrjua3TzH/gGi4rKTZBef92Ub8zWE5H06eNm5sysy3FGsrNh/34NhQurNG3qZs0a38f24sWZVK584w7bFUIIIURekiyJO1aKI5kgYzCKovx1sLip7M50fj02j+K2Ejxa9fF8Y/T6lRiNC3G5GpCSMhfIO0JinP8L5m+n46oRw6+tPkaJtdCkSfGc+g/eNHIh1Tf9rurrrUlscRLjzz9iWLUC7dEjeCpVJuPFV3LOEbqb6PL5tB00KJvESwqzvjPklC1bpiMmxorL5T/9rmVLF926ufnyS6hc2U3FipIoCSGEEDebJEvijrTi1DJ6L+pGn0qP8FHTj293dwq86QemkeGyMyjmBTSKxq9OUdKxWMZiMn3Jd9/15LvvxjN2rJGgoNwYzdkz4HJhGTMKVaMhffJXdKvvO7g2Li6dkSMNxMR4uXgxNwmqVcsDOh3Z3XqS3a3nLXnOW61aNS/16nk4eEjLe+85eOUVE/v2aTl3TpMntmNHFxERKufOQUJCVj6tCSGEEOJGk2RJ3HSqqhKfGYdZZ2Z3wi5qFaqDRWe56oiRqqq8t3kkXtXL9ANTWXF6GWWDo5ncYiph5rBb3Hvxxe5JjNjwOjZ9AL0r/XmdkkpAwECMxkVkZRWiV69ZAPz6K0yZkkX79m7069YS1LMzSnY2AFm9+5EdVS6nhUOHNEyYYMxz30KF8l/X81/Qv7+T6Ggv7dq50Wph6dJMAHr3dvHaa1q0WhWPx//PR6VKMpIkhBBC3GqSLImbSlVV3lz/GpP3TPIr12l0vFT7VV6+ZyibL2wiMesSLUq2RK/Vs+zUEvZe2k254Gi0ipbDyYc4Zz/LpzvHMeLed25Jv72ql8NJh9get5WitqI0j2pxS+57p1FVlU92jCXYGMzcjospZC3sV28yTcFoXITT2ZiNG3/xq3v8cTNJs+cR+FgflOxsXHXq4g2PIGPoG1y6lJsI7N6ddxRl3bqMm/NAt5lOp+J2KwQEqDzxhCtP/SOPuGjRwk2JEirx8Qovv2xi4EAnAQEqAQG3ocNCCCFEASfJkrhpVFVlxIbhTN4zieK2EgSbQnC4sygeUIL9l/bx4db32XRhI2vPrgKgiLUoD0d3YcmJhSgoTG01kwohFbmUdYkHfmzElD2fExVYkseqDryp/V50fAFvbRzOidTjOWXNox7giepP0zzqgZt67zvNWfsZErLiaVumA5XDqvjV6fVrsVpH4PUGk54+hf37fWuUhg/P5p13fCNF9bpXwstORj99mEYjfGciHTum8O67uSNJGzf6PoZGj3bw6qsmChXyUr78f3MUpWFDD6tX6yhdOv9RM602dyOIQoVUZsyQ6XZCCCHE7STJkrgpvKqXV9a8wIwD04gOLs+c9vMpYiuaU7/14mb6LOyWkyjZ9AEkO5KYtGs8AO3LPkzF0EoARFgimPjAFzy+tB9D1w6mengN6hSu+4/7tunCRvYm7GJ3wi42nd9AdEh56he5lxqRMexJ2M07m/4PnUZHp+iu3FO4Hj8e/o6Vp5fz+9k1bO2zh6K2Yv/ilbm7zI39GYCGxf0Pf9Vq9xAU1AFQSE+fhNdbmIsXfSNEVat62DDnKG26hHOU8gBMOVGSutkOSpTIOzyyfr3vwNXOnV0UKeL9T083+/LLLBYv1tGtm/t2d0UIIYQQ10GSJXHDeVUvY7aNYsaBaVSPqMn3bX8m3BzuF3NP4Xrsf/QYWe5MVFUl0BhEujON9zePJCEzgbfue9cvvmGxxoxp+imPLunNitO//a1kSVVVtsVtYdOFjZxOO8X0/VNRyf1m/3T6KVac/i3nd4PGwPQ23+VMvRtQ7Qm+3jeFIWtfovP8dqzoug6L3vJPXpq7zpozvmS2Y7lOfuUWywQUxcP06WuIiqpNlSpeMo5cAEoRYFOp9ckgTrCJef1n88g3LTl+XMPx43mn2wGcPq2hdGkvAQHQsqXnZj/SbRUUBD16SKIkhBBC3C0kWboFvKoXp8eJSZf/2Sr/JUtOLOLdTSM4nHwIgBmtv8+TKP1Bp9ERYAjM+T3AEMh7jT68atuNijXGorPw/aFvebnOULQa7V/2Z+HxX3lrw3BOpp3IKQs0BPFaveFUCq1Czcha2F12Np1fz/7EvRS2FqVNmXYUshTya+eRKgPYk7CLbw9OZ+nJRTwc3eUv732386pedsXvoGxwOUJNuRtrKEoCRuPPnDrVkP79fSNOlzbtwjlnA/A0JdvWxcgBlEZNaTO6AVGrvBw+rKVJE2tOGytXZvDxxwbmz9cDcO+9kkAIIYQQ4s4jydItMHrLu4zfOY6WpdowpO7rOdPL/mvWnFlF/8W+LZ6L2YrzQu2X/abeXUlREjGbv0ZRkgAtDkdfPJ7y12w/0BhE5/LdmHFgGpsubOC+Ytc+mHT/pX08s3wgme5MupbvQavSbShuK0HpoDIEm0Jy4ix6C+3LPUz7cg9ftS1FUXiqxrN8d2gmb64fRoOi91HYWuSa97/bnUg9RpozlQdLtfIrN5u/QVGcLF8+JKfM+tLzpOM7fymQNNzR5UkfOx4UhZEjs+nfP/fMpb59nVSt6mXsWAflynlZv15Lv355NzsQQgghhLjd8p8XI26oplEPUCGkEguPz6fJ9/X5fPeE292lG+68/RyPLOmNisrXrb5lZ78D9K/yWJ44s/lTQkPLExYWjdX6NhbLBCyWTwgJaYjN9hIGw2Lg6ltGP1iqNQCbL2z8yz59vP0jMt2ZTLz/CyY+8AXtynYkplBtv0Tp76gQWpE3G4wkLvMir6558R+1kR+7y85vJ5eQ4bpzdoA7l36Wtza+CUBMZK2ccqPxWyyWURw7VoVXXmmdU35+wxlSIqMB8M6eTvLvW/CWLAVA69Zudu6058S2aOEbRQoMhKFDnfz6axYxMf/ddUpCCCGEuHtJsnQL1C/SgJXd1vFVy+mYdCbeXD+M51b+j4k7x+P0OLE709kZt52EzARUNf9EQVXVq9bdCX44/B0ZLjv/1+Ad2pRpm2+M0fgDNtvrKIoDt7sWdvu7JCevIi3tS1TVhtk8haCg7thsr3C1hCk6xDf6dDz12DX74/F6WHN2JcVtJehSvvs1Il0YDAswmz/GYJiPRnP6qvcG+F+NZ6kVWZtlp5ZwNv3MNftwPfYm7Kb+tzH0XtSN+2bV4buDM2/7/+cVp5ZRf1YMS04spFp4DTpFdwNAq91LQMDTxMWVoFy5fSQn506DjKUcKUUrA2BsXAc0/h8txYqpLFiQwUsvZdO8+X97XZIQQggh/jtkGt4toigK7cp2pEJIJXot7ML3h74FYMvFTeyO38n5jHMABBuDCTGFUiaoLPcUrscTNZ5Gg4aeCzuz+cJGqoXXYEGnZRi1eQ/xvF02X9jEmG2jsOkD6Fmpd556RbmE1fo+JtN0vN5AUlJ+w+OpkFPvdtcmO/th9Ppt2GyDMZu/QFW1ZGSMBAx+bUUFlESn0XEo6eA1+7Q9bhsp2Sm0K9vxqoff/nGgqsn0s1+p1xuGw9EPp7MxbnddVDV3BzdFUehX5TF2rHqGvot6MOmBL6kUVjmnPsmRyIHE/cQmH2Xvpd1oFC3pzjQ2nl9PcnYSNr2NNqXbUzqoDHsv7WJe7C94VA+BhiCSHIk8v+ppDicfumXnSV1JVVU2nl/P4NXP4/K6+KjJJ/Sp3B+NogHUy4muSvv2m/Nc24olmI8oWCwq2qssJatb10vdus6b+xBCCCGEEDeQot7ur7FvooSE9BvSTkREwA1rCyAhM4GXVj/L0pOLc8oqhlaiREAUq86swO11+5UbtSZ2J+zMKRvf/DN6VMyblNwOqqpSf1YMp9NO8e1DP+ZzDpGT4OCH0Os34/EUIj19Mi5Xc1BVDEsXo0mIB1Ulu2Mn1MAgNJqzBAW1R6eLJStrIHb7mDz37P7rw6w6s4KFnX7jnsL18u1Tl/nt+f3cGr5v+/NVz0YyGOYTFNQHlyuGzMyX0Gpj0en2YjAsQ6OxX27LSlra1ziduet2nB4nT/72GAuPzwegekRNws3hZLgy2HZxCx41/5GTqpFViUuPJyErPqcsKrAU79z3AS1Ltea8/Rzdfu3I0ZQjLO28iphCta/52t9Iqdkp9FzQhW1xWwB4re4bvFjnlcu1DiyWj7Fa3yMjoyU225Kc64a228WHv1bFc/l7lxIlvGzffudMJ/wvutGfR6LgkfeQuBHkfST+rTvpPRQRcfWT32Vk6TaIsEQwo81sdsZtx+FxUCa4XM7ua3aXHbPWTJIjicFrnmPJiYUAKCjM7biIDnNbM3rLexxPOUaX8t0pH1rhWre66XbEb+NE6nE6luuUb1JiMk1Fr9+Mw9GJ9PQp/PGWMyxeSNAjvXLiNOfOkPnam3i9xUlJWUNISANMpllkZIzwG9kBeKH2y6w6s4Jx2z5kVts5ee7589Ef+f3cGlqUbEmzEvfn02svZvN4LJYxqKqB9PQpeDzRObWKkopevxG9fiNm8yQCAx8lI2MI2dmd8XpLYNAa+KrldBYen883+7/OOSsKfAfrdi3fg3Ih0VQMrYRJZ2bj+fWUDS5H55h2XIxLYdOFDeyI30618Oo0Lt708sgNFAsozsiG79NjQWc+3fkxX7WcnmdUbPLuifxw+HuCjcFUDa/OfcUa0jyqBTrNP/ujbHfZWXx8ARN2fszBpAPcV7QRw+q/eUUSqjJr1izi4qz06XMP99//KwAREV5+/DGLBm+/QlcSmdJtEQs3RfL669n/qB9CCCGEEHciGVm6Drcr8/WqXg4nHWJPwi4iLJE0j3qAIWtfYvr+r/GoHiqGVmJtj7xTom6lJ5c9yi+xPzGn/XwaF296RY2K2TwRq3UEqmokKWkXqhqRUxvYtzvGpYvJfPxJLFMm4w0MIn3iF7irVMVbvAQWy/tYre+Tnj4Bh6Nfnvu2mtOMHfHbOfb4Wb/tx72ql5jplUl2JPF7zy2UDCyV51qr9S0sljF4vcHY7aPIzu551eczGH4lMPAJFCUDrzeI9PQvcDpb+8WcTD1BiCkEq96GVtFeddrf9byPPF4PbX95kO1xW3m34SgGVv8fAJeyLvHqmhdZcHxenmveaziax6s/dc1287P+3O8MWNqXJEcSAA+WbMUXD07zO0NKr/+dkJA2ea6dPMlO/0V9MC6Yh6t2HVIWr/zb9xf/zJ30TZy4O8l7SNwI8j4S/9ad9B661siSbPBwB9MoGiqFVaZ7xV45ozajGo/l6IDT1CvSgENJB9kdv/MvWrl5PF4Pq8+spJitOI2KNfGrMxgWYbMNQ1UDSUubkZMo6VetIKRJA4xLF+OOLk/Gu6NxdO6GJi2VoL7dCW1QC+PPP+Jw9EFVFUym6fneu1ahOgAcT/Hf6GFn/HYuZJynU3TXfBMlk2k6FssY3O4yJCXtJDu7J9ojhwl4eiCmryaD3e4X73S2IzFxLxkZr6Mo6QQFdScwsAd6/Qr+2AiiVFBpgozB6DS6a6yPuj5ajZavWk4n3BzBm+uHsfH8egDe3zySBcfnUSMiho29tnN0wGleqvMqAN8enIFXvfZucj8e/p6q06KpNLU0FaeWotO8tjw87yGSHcl0r9CLTb12MPOhH/IctjtzZv5rw5p4V/kSpVq1SZv45b96ZiGEEEKIO5UkS7eBXr+WgICBGAyLrij1XPHfaw/22QwBtCndDoAWc5rQd1F3xmwbRUJmwk3p79XsSthBcnYyTUs0z5MkmExTAUhOnudbowTgdBIw6Cl0B/fjbNiYjBHvgKJgf3cU9ndHkTF0OKregG3w86hpwbhczdDrt2A2TwT8k4GyweUAiE056le+/NQyAB4o2TJPf63WIQQEPIvXG0Ra2g+oahj6jesJaX4fpjmzCXjtFcKqlcf40w9+16lqOJmZQ0hOXo/LFYPRuIjg4IcJCamLxfIeGs3FK6KdKEocOt1ujMbZGI0/YjDMx2T6EnidoKCHCA2NJiwsirCwsphMX/Pn/99FbcX4qqUvSewwtzXvbXqb2Ye+JcIcyZLOKykbHE2QMZihdYfTKboL+xP35mwYkh9VVflw6/vEZ8aR5c4iyZHEunNrKRtcjkWdl/Pp/Z9T5vLr+QdFScdieZtBgwbn22bxM74RzczBQ/CWKXvVewshhBBC3M1kzdItpRIQ8Dgm048AmEyz8XhKAR602jN4veEoSgpebzFcrvtwuRrgcPTkzzvCAQys/hSXshKYd+wXlp5czNKTi5lzZDbTW3+fs732zbT27Gqe+s13jtKfExON5iyzZhXj5ZeTSU8PwuVSWLo0g7rZ23DGpxLf40Us49/KiVdDw8ga6JtuhsuFdcwoDCt+I6PzMHS6ndhsr6GqRhyOx3OuKRPk+8f9sZRYv3uvOLUMvUZPkxJN/cq12oNYLJ/hdpcnLW0WHk95VBVS3v6MAKebjPGfoT15HPMXnxP4v8dJCQ3D1cx/vZPHU4WUlNXodDuwWMZgNC5Ap/sAk8m3AYRGk4zBsBxFybzq62YwgMdTGq83Aq32BAEBz2MyTSMtbRZeb7GcuAZF7+PdRqN5d9NbfLzjIwDalm2PVuO/1dybDUay5MQi3t30Ft0r9MpT/8drdDLtBO3LPszkFlP55sBUwk3htCnT7qprnQICnsFonAt86Fdusah88okD/be+c65c1WOu+qxCCCGEEHc7GVm6hYzGHzCZfsTliiEtbRJudzQazUUUJROXKwavNwiPpySKkoTJNIuAgEGEhtbBan0NRUnza0un0fFGg7fY1mcPO/rup1/lxziWEkuj7+vyyfa8O8jFZVzkl6Nz/vIMH7vLzopTy0hyJF41xulx8r/fHiclO8V3rlJp/3OVTKYZPPbY1yQlBeNy+UacWra0snLcQYpwgWpzR5GQkP90NWfrhwAwLF+G212X5OT1qKoOk2maX1y5EN+GDMcujyxdsJ9nyNqX2JWwk/pF7vVbxwRgsYwFICNjBG53eaZN0zNkYCalt8/jndJTyO7Rm8yhb5A2czYA5ulfQ76vlYLbXZu0tFlcunSMjIxhaDSXMJu/wWicj6pqyM7ucHknv1Gkp4/Dbv+A9PSJwFoSEw+RlLSb5OQNJCevJTu7PXr9TgID+wD+22o/VnUge/ofZkC1J6gVWZunaz6XpzdFbcVoV7YjCVnxeUbZAFweF/+3YRgAzUrcj1aj5bGqA/n/9u46wIrqbeD4d27f7QRBOqQlVxpBFClRQBQRBF8sRBAUC5AQAxBQEVTS+KmEhHQIEtKpqEgoHbvEdty9MfP+MexdLnsJXWAX9vn8Azt5zswR59lzznPalWt/2UDJZNqK1fojCQmNvNsmTsxg69ZUDh9O5ZHmCZg3bcBVrTpa4cJ+ryGEEEIIcTuQnqWbQsNqnUFw8Mtomp3k5C9R1TJkZna9zPEejMaD2O2TsNlmEBAwEbN5E0lJi9C0kBxHFwsuzof3fkTzkg/w6to+jNr+HmXDypPuTuP3c3tA05ix7zuSnUmku9J5snLOhAkAu+N28uzKHhxLOUqZ0LJseGK73w/q7bFbOZtxhu5VetK7pu8HvNn8M3b7pxQr9iInThTz2ddxTT/9Lw5YutRD9+6u7CekgaKAu+rdqFHRmNesBk1DVYvhdLbEal2M0bgHj+duAO4MKobdZOfXs7tRNZX/W9GVnXE7uDOoGK/dM9DnvkbjAazWH3C7q+J0tmbTJiOvv24DbADMyXyIFy8c66rXAHeValiXLCTo9VdIfed9sNv9Pi9NiyY9/U0yMnphMMSiaYGoapT3upcKDg5GVbMnMno85UlO/h/Bwc9hs80iOPh50tPfwOOp6D0m0BzIB43H+L1elurRNZi1/3t2n9lJhYiKPvs+3P4BPx1dQbPizelUofMVr2My7cJm+w6rdSaapnD0qN7717mzi06dstPZm9euQXE6cbZoeblLCSGEEELcFqRn6Saw2z8iJOQFwERS0veoapmrnGHE46lIaupHnDt3DIfjSczm3URGliYkpDOQMz2zoii0Kt2GMfeOx626+b8VXXlp9fNM+m0ik/Z8RrIzCYDhmwdfdm5TvzUvcSL1OKHWMA4l/UPjmfcwftdHOY57d8swAO4v2cJnu8EQS2hoZxTFhcMRRblyOdcbMhn1uUcLF2YHYQ4HxMQE8vbbVjAYcDZrjvFMHMY//7iwX19Tymb7NvteioE2ZdpxOOkQwze9zc64HTQtfh/bu+6hXpH6aBr89ZcBk+knwsJaoigqn302lfHjbcyd6xsA7ouLJDZWyaoEibN/xF2pMvavpxF+f2OUxIScD0vTvD1PmhaKx1MBVS3G5QKlLEpqCrapXxDerCGB7w4Dt4eUlI9wuyths80lPLwugYFDudq8tYvVLdoAgF9OrPPZ/uuZXUz49WPuDCrGtJb/w2LMOZwzi8WygrCwZtjtUwAbR49+y6lTevrwqKiL5otpGtbFPwJIsCSEEEKI255x2LBhw/K6EDdKerrz6gddg8BAa66uZTAko2k2kpO/xOPR53gYDv2DFhqmd6dckRGnswWgYjCcwWLZgtF4BDCiqkUAq8/R5cPvolah2pQIKUHtwjG8VLMfL9V8mS6VulE+vALLjywh0ZFAy9JtfM6Ld5xn2KZBNC7WlBlt57A9dgt7z//J+hNriXecJ8waRoozhRn7vmXmvu9oXKwpb93ztk9iB7t9HEbjBl55ZTNr1pSgUiWV48f1eNxGBm7M1K6jUqSIxpYtJjZtMhIfr7BggZm1a03s3GmkY0cXEbZ0rEsW4SleEnfd+ng8pbHbp2My7SEzs5O3d61sWHn+qqckwwAAIABJREFUt/crtsVuAeDt+sOpFFkZgK+/NvPkkwGULPklMTG/kJj4Ls2adWb9ehN79ujzenrwJeZgGycc0URGatSteyG4CwzE8dgTGONisaxfi2ax4mrUJPuN/L6H8OaNCfh4DNYf56IWK4YnK8mBpoHDgZKUhOH8OQznz2KIi0PxeAhwpGG9txG2eXMwnD2DeetmtIBA3HWb4HB0w+2uism0B6t1KWbzDkDB47kLyDkP6WLR9mi+/nM6R5IP06vGS953MmTjW+w9/yeTHphGxYjKlzk7jeDgPgQGDgNMpKRMYfr0KbRoURu7HXbvNtK6tZuYGBU0jeBePbHNm4OnRCnS3h5+De1XXG+5/fdICGlD4nqQdiRyKz+1ocBA62X3yTpL1+B654G3LPqR0J5P4Xi4AykTJoH1wgtSVSxLFuGuURO1eIkc5ylKMuHhjS4ES3qigNTUD3G5aqNpkVe9r0f1UO/7mpzLOMdfTx/CZsruBfn81wkM3TSQwfWG07dWfwD+OPc7Ty7pxOm0Uz7XKRxwB7Memk/lyCrebQZDLOHhtXn22c+YPl0fXtili5NXyi/kn+GzKdOiFK13j2TsWAcHDxoZMcJ/o+zY0cWkYUeIrHYXmS3bkPzNDADs9s8ICnoTt7s8iYlrvAHTr2d2MWH3JxQOKMw7DT/wJjho1CiAAweMNG++ikWLZrJ378fUqRPkvU8LVrC49mCOTJxL5UbFqVpVZeXKSxIzpKURVbkMakQkyV9Mx12rNpa1qwl6rT/GUyfxFCqMISEe3G4cXbqB2Yx1wTwMCTl7ohIJJZQkFMDRviOObk8T1qEtnkKFid++xzvUT1HiCA194kKwBKoajMtVj4yM/rhcjXJcN0vvVc/xw4GZrHlsE1WiqrIjdhvtfmxJ+bC7WPv45sukNPcQEtIFq3UZbncVUlPfx+VqRrFiQTid2cd/9lkGjz7qxrRlM+HtHsR1dw2Sp32DWrLUZcsjbpz8tC6FuDVJGxLXg7QjkVv5qQ1daZ0lmbN0s7lcBI0YCoBtwTxsC+ahhoahFiqEIS4OQ3ISmsVCxvO9cdVvgCumrt4DBWhaCAkJGzGZtmK3T8ZqXU5o6KMAqGoh0tLexuHoftlbGw1G2pRpx2e/jmfDyXU+WezmHJiF2WCmW+Xs86tGVWNTl51M2fM5CY4EzmacwWa08UbdwRQOuHhivweH4yM6dPiGBQseAaBECZXXqi+n2if9qGU+Q/x7O/mzZBoAwRe1x8qVPezdm91zsmiRidGjChMeGITx6GHv9oyMXhiNhy7UeyYOx3MA1ChUi6kPfp2jrmfP6j1aq1ffz6hRpSlbVv+5b59Mnlz1LJX/mkfKp+sJKxNOo0Ye1q41sXmzkfr1Lxo6GBhIxnMvEvDJWMIfyh5yqBmNpA59l4zefbGsWEbwi89i/+4b7z5n46ZooaFodjua1cruhNI0XDKUT6tNokeHc2T0egkMBtL7vkLA+HEEjhtN2qChF95xYRITf8ZoPIDdPhmL5Ses1p+wWNaRmLgEt7uu33dbt0h9fjgwk11ndmAymHh04cNomsZbdYf4DZQU5TxBQa9htS7D6WxGUtIcNM3Mjz+avIFS2ehEmofu4JH1PxK0JQPrj3MBSBs8TAIlIYQQQhQI0rN0Da5n5Gv7ejrBr/XDXaWa/jFtD8Bw7gyGM3EYzufMQKcpCu6YuiRN+98lmcdULJbFmM3bMRr3YzZvwmBIxuHoQGrqODQtwu/9t57ewkPzW9Ctcg/GNh1PijOZ0ds/YNJvE3mwVCv+13rWv6yRRnDw0/Tvfz9ffKGn/+7Z08mY1isJ66ivBZX2+kDSB7zpPSM1FerWDeThh908+6yTunX1Hp8771Q5edLApEkZPP1pPUyH/ubc4dPeoV6KEkdkZFVUNZr4+B2A7wKqWeLjoWJF/78h+Kj9avrNv9+n1+p//zPz6qt6L9v48Rl07uz2Ocf8809YVyzDvHkjnjQn07osZfaWMnz1VQaBgaAkJ2HauQMtJIS/PBUoXSsE00W/hnjzTSvTp+vzhc6cuagdpaYScW89DKdPkbB+K55y5f2W2WJZQWhoJzIzHyQ5+Qe/x/x57g+azW5A0cA7CbOFs/f8H3zcbCJdKnXzc3QmERExGI1HcLlqkpS0EI8nlF69bMyfb8Zu15h5/xe0W/Siz1lqSCip744ks/OTfssgbo789Js4cWuSNiSuB2lHIrfyUxu6Us+SJHi4yQImfIwWEEDizHkkLl1F/OyFLPlgO5NGHOfsyfOcPXmec/+cIHHmPNL6D8Bdqw7mbVsIem/YJVcy4HS2Iy1tBMnJs0lMXI3LVRubbR4hIc+QvcitrzqFY4iyR7Ps8BIy3Bl0XtyRSb9NJNpeiIF1h/7r+lgsSzl48ACTJz/n3VakiIZ1wXwAkr7/wSdQAggKgj170nj33UwiIrJj9W7d9Ox4S5aYUEuVRklPx3Amzrtf0wqTkdEbo/EEdvuXly3Trl1/AdC9+1eUK5fos6/H8q6oYWGkjspOr96uXXZWvr597eze7fufheu+B0gdNY7fv99GxPmD9B51F+vWmfjqK7NerpBQXM2as8lTl4Zt7+SVV2ycP6+QlAQTJ5q9gRJA4sXFCQoidegIFLcb25dTLlsfp/NBXK57sFhWYrV+h7/kD1WiqjKw7hDOZMSx9/wfBFtCaF/+Ub/Xs1oXYjQeweF4ksTEVWhaKLt2GZg/38zdd3tYsyaVNjvfQw0PJ2XUODLbtCNxwTLO7/1HAiUhhBBCFCgSLN1EytGjrDxakaTGrby9RF272nnkkQBefNHOgcNWMJvRgkNw3Xc/6W8NIXHxStwVK2Gd9T1KctJlr+3xVCAxcTVO5/1YLKsICXkci2Up4DsPx2gw0rJUa85lnKXRjBi2x27lkXId2N51jzc5wjXXRzlDUNAbDBz4AaqaPZSuaBEPlhVLUSMjcTZt7vdcoxEMBgi5KBN68+ZuypRRWbXKREZxfdFZw+HDPuelp/dB08wEBIy+UD9fBsNpdu/+BYCOHe1s2mRg7lz9GTwZuZSwjFhSxnyCWqSo95zQUIiLS6FVKz1omj/f7HPNhATIzITffjOSnp49pG3iRN/scjt36s9g5kwzlSoFUb58MMOH+2bHW7PGd+Srs1VbtIAALBvW+31OWdLShqJpgYSE9MJuH+f3mH61B7Di0bW8WKMvsx+aj93kP+W5xTKfvXsrkZb2MqDX9c8/9bI/2sFJxQNLMZ46ibPZ/TiefobkL7/FVb+hvqKuEEIIIUQBIsHSTTRj7Dlas4zXEvR1gNLTYfXq7I/nX37xk/XMaMTZ7H4UTcP4119XuYOB5OQvcTobYrWuJDS0MxERNbDZvsRgOO49qkfVngRbQjiecowoezRj7v2EALP/IW06B5AGqBeK9AehoS2JiiqH0XiMLVvupVSp7PTSd0eewBgXi7NJU3zGo/lx8XSaKlVUYmI8pKcrHA6ppt/ryCGf4zUtktTUj1GUDEJCnsRo/FuvueEf7PaxpKT04sMPXwWgatXWgELjxh5WzTzG5+cfx9mkGc527f2WY/JkByEhGosWmVAvVOfAAQO1agXRtGkgW7bo72fatAwaN3Zz7pyB9Iti0fj4nHODBg7MpE0bFy+/rKd7f+cdKxkZFx1gNuOqUQvjvr9Q4i+/ELDL1ZiEhC14PEUJDHwXk2mz3+OqRd3NsAbvUrtwjN/9ipLC11+XoEqVvVStWpvBg60kJsJrr+lBXdkP+xD6lL4ek/PBVpctjxBCCCFEQSDB0k301YriAEzbXpP0dH0doItd2uuQxV1Zzzpn3r3jqvfQtFCSkpaQkLAKh+NxjMZYgoNfJjy8HgbDUQDujq7BHz0OMv/hJax5fBMh1lC/11KUBIKDXyAqqijR0UWIjCxFRER1IiIaYLFswuWqy/ffz+DcuWCKFFF58kknLVu6qOr+FQBPpSp+r3upqVMzmD49A5NJTwwBcCigKgCm33/LcbzD0Y3k5MkoioeQkCcIDBxCeHgzgoKGM3JkJwAqVPAQlJ38jjqZmwgmFVeDhpcth9UKrVq5OXnSwM6d+rv56ScjaWkK//xjYNIkvWelaFGVO+/Uh8Lt3m3Ec2HE44ED+jkDB+qBUf36bvr1c/Lllw4GDtRTY548aaBrV7s3GANw3qcHw/bpU8DtBk3DsmgBYW0eIKpEIaJK3UHQWwNQPcVJSZkKaISFtSU4uBdwceR1dRbLAj76qA8AsbEGJk+2MH5MdpAXZUslo9vTJH0zk8yHO/yrawshhBBC3G4kG95NkJgIkycq7ErQ1+LRNIV77w2kRQvfRAIbNhjJzMzOJJ7F2bQ5mtFI4PvvYFn9E+n9BoCiYFmzGjU4GFBwV62Kq2GTCycbcLvvISXlHjIynsdiWUpg4BiCgt4kOflCKm6TnYZ3NvZbXoPhNCEhnTGbdwPgdpdDVUtiMv2KoiTgdN7H2bM9MRrb8OSTeqB15IiBBQv0D3fjJ3v18+6qeE3Pp1277OeQFSwdNt+FZrFg2bSRND/nOJ0Pk5n5EFbrIkym/WiagdTUkWzapGfzW7DAd/iheZM+NM91T70rluX++93MmmVm+3Yj69ebGDVKfxkdOrhYvNhEUJBG+fIqd9yhl7N9e71H7t13HWzfbqRoUZW+fZ2EhWk89FB2vRQFAgL03sRffjFRsmQQVauqfPddOlGPPk7ghx8QOPp97BPHY0hL5X3eIpTaPF8+AUNsLPZpk3E89gSumo1ITv6WwMBh2Gzf4XLVwuF49qrPWM9+NxCbbQYZGUd89k2YnB1Vhi/6gtRyV17XSQghhBCioJBg6SYYNcrKtGkWAkhj0eNf0v+vXuzZY2TKFN85IOnpCtu2GWnc2MO2bQY+/tjK559nEFq4MCnjPiVw9PtY1q3Bsm6N3/u4K1UmeeIUPFWrZW9z18Htro3Fsg6rdQkm03bcbv9DtED/qA4O7o3ZvBuXqxZOZ1vS0/uhNxW9N8XlUqhZM5AiRbITDbRqlR0YmHds0+9dq/a/fVSULKlf89hpC84mTbGuWol5zWpczS6d+6SQnPwdBsNhzpw5g8VyByEhJYmLs1KqlErEJckALevXotntuGL8p97OUrmyHgQtWmT2zkECvbdowgQHqqpP3bn7btXnvMGD9WFsnTq5MBigRw8Xl9q3D0pcWD4rM1Nh504jn3xiZfjwO0maMRfrnFlYVq1kQ1p1BvE+AEvLuxjx9FJqDXwE8/q1uGvWxulsi8t1D5GRlbHbP8fh6MnVOon//PMLChfexR131OXYsZI0buymYUMPI0fqweBzldfz9ITKlCp3+UXZhBBCCCEKGhmGdxO89HQCM8Je4Ii5PNUH3Mv06dlDp8xmjYkTM3jvPQcA06eb8XigbdtAVq0y8f33+gT8zCe6Ev/LNlIHDyf9pX44Hu5AwjN9OT51PknfzMTRoROmv/YSfn9jzGt/vqQECmlpbwEQFtYKmy3nukQAAQFjiIysgMWyCqezEYmJP5OePoDsmFoBFM6eVTh71sCePXowce+9boYM0YeemdesxvLTCtzlyqPeUeRfP6uSJfUg5OhRAxl9+qNZLIQ+1RnT7p1+jx89ugKVK99PuXJV6djRzrlzCoUL+wYyhrhYTH/txVWvQc5uu0uULq1SooTqEygBREVpmEzZOQ7atHHz+++pOc7v0ePyK1EXLw5vv51J9+7Zx8TG6kPgXI2akPrxROI37eSV8gu9+5cuNdN75n0AGI8d9W7XtEJkZnbEZPobs3nDFWqkoarLadp0JJUq7WP6dL1tVKig0rvWBu5hK3dZD/PyrBqUrSqBkhBCCCHExSRYugnKL55A58RJBPTpilqyFEWLZvfIVKyo0qmTm65ds9Jmm+ndOzuD2tChNo4fvzCnJCiIjL79SRvyDilTvuLB38ZR4plHSGvempQvppH0zUwUVSXkuR6YL8mu5nLdT1LS92haIEFBb2AwnPDZb7EsIyBgBJoWRGrqSJKSfuByzWPPHn27waDXo3t3FwEBQGoqIb16gslEyvjP/9OzKlxYw2rVOHbMgKt+Q1I+/QIlMxPr4oU5jj140MDo0dkf+L/8YkJVFQoX9k2tbb7QE+ds0uyq9zeZYMmSdPr1y/TOPQJ9CN3FFIUc92nb1kVMjG+gdqk+fZyMGpV93WPHfJ/x8aRQth/07RY7cDwQAOPRoz7bsxYgtts/5XKp4gMD3+TQoezsea++qlfkPuVnij7fia3UY8u8f4gunDM5hRBCCCFEQSfB0k3gKV6CzFZtSe+rZ2m7OEFcxYr6x7XdDjEx+gfvvHm+qav797fhb+ng7dv13o+TJ/UPXWfL1qQOGoqSkkJop4cJ7tsLQ+xp7/FOZ1vS0kagKOmEhnbAav2WoKA+RERUITT0cQYM+IgWLfaTnv4iEOi3LpoGTz2lf3D36eNk0qQMWrbUh+BZly7CEB9P+ksv465zz798SjqDAYoV0zh27EKdml7oVdn7R45j//nH9wO/alUPZcqo3HffRUMCf1lH0MDX9Ws1f+CaylC4sMbAgU769XOyZk0aixf7mzWlW7FC31ekiOoTBF2JwQADBujH/vmnAdeFEXsbNhgZNEgP/rLSmAPEJxg4GB6D8dgRn+u4XPVxuepgta4gJKQbl66/ZLEsJSDgc1aufAKAFi3cPPOMk25PpNF+ekdwuUkZNQ73VYYmCiGEEEIUVBIs3QSZnTqT/PX3ObsngEKFsj9wv/46g8jI7J6JceMcVK/uYf16E1u3Xn7S/ZEj2a8x4+VXSZ72PzwlSmKb+R1Br/f3Odbh6IbD0RmTaR8hIS9it3+NomTgdDZn3LiXWb06yudehhPHCa9Xk4haVQjt+BD735nn3WexQPv2bm/wZ/n5J72+j/hfDPValSypEh9vIDUVtPAIPEWKYtr75xXrDdCxo4stW9Lo0uVCsKRpBL/aF8WRQfKnX+CpWOlfl6VKFZV77rl8b1HNmipnzqTw229pREf7iWgv4/XXnfTs6cThUBg1ysKhQwodOgSwfLkeKDds6OGLLzLo1Usfsrc8qCOGkyfwpt4DQCEpaf6FVPGLsdm+9e6xWJYTHNwHTbMwf35PzGaNzz7L4P33Mxnf+RdsnnQc3XrgePqZf/dAhBBCCCEKEAmW8oiiaD5/gj4vpk0b/UP///7PSdeuLu/HctbQtywXp54eM8binfsC4GzdloTNu3BVr4ll5XLMWzZddIJCSspEkpJmkJLyCUlJszl//m/i4uZ7z8+aJ4WmEfTGK5gO/YPxxHEsv6xjycTsnqruT2ZnnFPOnsWyYjmeonfiqXBtWfAuJysj3tGjep3dlatgPH0KJSHe57hLg6VLl3QyHtiP8chhMlu1JfPxLrkq042QlS1v/Hgr9eoF+ewLCdHo0MHtnQO1Vm2M4nJhOH3K5zhNCyU1dTyqGkpQUB+Cg58mJORJQkMfQ1HO8+OP3/Hbb4E0bOjxLgBs2qXP//ovCTiEEEIIIQoSCZbySNOmeg9BuXK+vRZvvOFk3DgHI0bow7SqVtX3b95s5MMPLbRoEcCJE3qShSzbtpno08fmcx0MBjJ6PoeiqoS1a0lY2xb6Gj4AmHE62+BwPI3T2RIw8NJL2ecvXGgiLQ3Ma3/G+tMKnA0bc/Z0AvE/rWdWRC+ClFTSsVPm0zdRzpzBOn8OYZ0expCWSnqf/r4rzf4HWcHS0qUmeva00efMME5zB+btW32OO3JYv081s75Yb9W9c7EsnE/WSrFZSSFc9S+/tlJeqlvXd55RQIDGww/rw+9q1tSfQalSGqGhGr+nlwfAkiN5B3g85UlK+hFNi8Rmm8vRo/uoU2c3BoOHDh30Xr7WrbOHJnqfS41a171OQgghhBC3E0XT/M2GuT2cPZtyXa4THR183a6VJSkJli838dhj7ivGFpoGTZsGsH+/AVXNeeArr2SyY4e+JtDMmencd5/H52TLimUETPwE89bNJH3/A877H/R7n0KFgn1+/nl5PPW/eBbbj/NIWLQSd916/PqrgRYtAunYOoVZO8pjPBOXfSuDgcyH25Py6aTslHH/0aJFJnr2tPtsG8srvNjpNCkTJ3u3NaiQSWKCxr7gOmzOqElb9wLvvvS+r2D5aTmmv/aSsHIt7nwQGPhrR61aBXgz77Vt62LaNAexsYpPWvZHHrGzebORVGsk1jAb8Vt2+x3Sqapu0tJOU7Zs5Rz7tm9P9aZlD29YB0NcHOcPHst1YCtuvhvx75EoWKQNietB2pHIrfzUhqKjgy+7T3qW8khoKDz++JUDJdC/ZStUUHMEStWqeWjXzkXv3k4GD9Z7od5/35rjZGfL1qS99TYA5vXrclz/998NbNuWsxmoPV/G9uM8PEWK4q5dB9CzzQG0bG8iceVa0t56m8wHHiTjia7Eb9lNyqQvcx0oQXbP0sXO2YtjXrcG1eHE4YBR7yr8nRBFWfMxtF0bqL9rNMmTppP5gB4MBowfp6cLr1Ydd/WauS7TjfL999lDGRs18qAo+ARKAGXLqmiawp+dBmKMPY3th5k5rhMbq1CjRijt2lXwbps2LTtFfYkSF67p8WA8egRP2bISKAkhhBBCXIUsSnsLCA31/XguU0Zl9ersj+waNVTuvtvD/v0GPB4wXpILwlWjFprJ5F0sNsvKlUa6ds3uoShVSqVDBxfjxllJPplKZqu2pA5/zzsZ6MgR/eO6QgUVteidpPd/7XpW0+vioYmKoqFpCudL1sC4L443Wuzn630NvPs9EVFooWFooWFktn+UzBatsM2djRoZheLIwNmseb4OCsLDoWtXJ99+a6FdO7ffY0qV0t//gWrtieE1zBvX4+j+fz7H/PCDmdhYA7Gx+s8dO7po29aNzaZRpYrqfQSGkydQnE48pcvcsDoJIYQQQtwupGfpFhAWlh0sBQRoTJ2akeOY8uVVMjMVb0DjIyAAT+kyGA8ewJuD3O1m7zb9OpUqeejQwcWCBeneRWEPU5r0Xn04YihDQoJ+yuHDBhRFo1SpK68llFuBgTB5sl62/v31BAeT9zVjUdFnfAIlgIc65DzZ8dTTONs8RGbHx9AiIm9oWa+HUaMy+fvvFKKi/I+I9S7U67wTNboQ5i2buTSX/JYteoTcpIkbu13j7bczURQ4cCCVBQuyA2vj4UMAeEqXvRFVEUIIIYS4rUiwdAvI6lkKDdU4dCjVm/ThYvXr63OV3nrLRps2ASxd6ttp6Cl3F4akRAJGvUdI18eIKlOU+PGzAfiy9QymDPidIkU0QkP1419lHN/sqUWdOkE0aaKvuXT4sIGiRTVsl+SSuBEeecTNtm2pvPSS07ut3akp3r+/qHzGmme/4rkhEX7OvrWYzXgz1fkTEqK//5RUBVe9BhhjT2M89LfPMb/9ZuDOO1XmzMngwIFU78LHNpvvyEjjoX8A8JSRYEkIIYQQ4mokWLoFhIXpf9ar58FwmTfWoYOLoCCNtWtNbN9u5L33LKRcNGfOdU89AALHjca6cjknAu/iC3oBUGHsS0Q0qE1o5w5EHdruPaff4CgA4uIMtG4dwMmT+gf5zVKqlEagn7Vxu4Qs5P3vC1PlvY45hhzejgID9cAnLQ0yW7UBIODDD7zp4N1uOHPG4O2Bslr9XwdNw7JmFYAMwxNCCCGEuAYSLN0CshIeNG3qf04LQFAQPPaYy/vzwYNGKlYMYtkyE6oKaf/3POl9XyGja3fSn32B2S+t9h5rHP4G7spVsfy8iph3/C8ou2OHHpU4nTd3/o+/6UaR3R/E2bzFTS1HXsoKGNPSFDI7dMJVrTq2eXMIe7gVpKWRkKA/pIiIKye2DHz/HazLl+KqHZMvsgMKIYQQQuR3EizdAho39rBwYTo9eriueNwLLzgxGDSio1WeesqJy6Uwc6aJHj1sNHkgnNRBw0gd9ylp743m5+36eLtly9Jw9HqJhOU/kzLuU4L/7xG+aT+Lke+m+iSWsFr1vw8dmnnjKnoZ7dr51js6+rbNdu9Xds+SAgYDf4+fx/4GXVG37sS6eAHx8VcJllQV6w8zCfhkLO4yZUn6dnbOFXyFEEIIIUQO8sV0C1AUfQje1ZQqpfHnn2lYrfrwtQULzCxbZvbuP3tWoVAhDbdbTwNesqRK7doXhtXZbDi6dgegJQAaHR5LZcAAG243TJrkuPzwrhvs888d3Huvh1df1SdLFSpUsIKloCD9z9RUOH9eoVar0jgc/yOECexa+joJJbsBEBl5yXNxuQh5pjvWZYsB0KxWkr6fgxaZ/5NeCCGEEELkBxIs3WYu/mAuVkwlKSl7Us/hwwbGjzcxebI+479Dhyv3VIWFwdSpjhtT0H/BbIZu3VzeYOni7IAFwcU9SwcPGnA4FMxmjWRXKPv2eDh37kLPknoO+/ipWDasR72jCMaDBzDv3I6nRCnUO+4g8+H2qJLYQQghhBDimkmwdBt76ikXb7xhpEgRldOnDbz3noUtW7JfeadOVw6W8psNG9L47jszjRtfvZftdmK1gtGokZamcOyYHhhVq6aya5eRM6dUjv3tAuxU+nwAQU7fBWszW7UlZeIktKDLr0wthBBCCCH8k2DpNta9u4uKFVWSkuCppwJ8AqV33nFwzz03L7Pd9XDXXSrDh9/8OVN5TVH0JA/btxs5dUofC1mrlkcPlrRojuxOBkK4y/kHaf0HkNHzBYynT6JGF0ItemfeFl4IIYQQ4hYmCR5uYwaDvv5S1po7F7ta5jSRvzRooGdCPHnSQIUKHtq21X8+TRG2/5yOAQ+lo1JI7/sqWqFCuKvXlEBJCCGEECKXpGepAChcOGdg5C8lt8i/Ro7MpE4dlfvuc1O5skpsrP4Cp/As6ZmBPKHMwD3xY/wuTCWEEEIIIf4TCZYKgKio7GCpbFmVs2cV7ruvYM37udUVLarRt6/T+3PWO00nEEXR6PPt3bialcir4gkhhBBC3Jbrks7AAAAKlklEQVRkGF4BYMxOiMfLL2fy99+pOdNMi1uKxYJ3HaxatVTKPSCBkhBCCCHE9SbBUgETEpLXJRDXi+HCf71Fi95aiTqEEEIIIW4VEiwVMJp0KN02FEV/mXZ7HhdECCGEEOI2JcFSAZG1kGtwsERLt4syZfR3mZAg2TqEEEIIIW4ECZYKiNWr0xgzxlHgFnS9nU2YkEH16h7eeqvgrT0lhBBCCHEzSDa8AqJ4cY2nnnLldTHEdVSmjMZPP6XndTGEEEIIIW5b0rMkhBBCCCGEEH5IsCSEEEIIIYQQfkiwJIQQQgghhBB+SLAkhBBCCCGEEH5IsCSEEEIIIYQQfkiwJIQQQgghhBB+SLAkhBBCCCGEEH5IsCSEEEIIIYQQfkiwJIQQQgghhBB+SLAkhBBCCCGEEH5IsCSEEEIIIYQQfkiwJIQQQgghhBB+SLAkhBBCCCGEEH5IsCSEEEIIIYQQfkiwJIQQQgghhBB+SLAkhBBCCCGEEH5IsCSEEEIIIYQQfkiwJIQQQgghhBB+KJqmaXldCCGEEEIIIYTIb6RnSQghhBBCCCH8kGBJCCGEEEIIIfyQYEkIIYQQQggh/JBgSQghhBBCCCH8kGBJCCGEEEIIIfyQYEkIIYQQQggh/DDldQHy0ujRo9m5cydut5vnn3+eatWq8frrr+PxeIiOjubDDz/EYrGQlJTEK6+8QmBgIOPHjwdg3rx5fPLJJ5QoUQKABg0a0KtXr7ysjsgjuWlHANOmTWPhwoWYTCaGDh3K3XffnYe1EXklN+3o888/Z9OmTQCoqsq5c+dYsWJFXlZH5IHctKG4uDgGDhyI0+lEVVXeeustqlatmsc1EnkhN+0oPT2dN998k3PnzmG32xk5ciTR0dF5XCORF661HS1dupTp06djMBioX78+/fv3x+Vy8eabb3Lq1CmMRiMffPABxYsXz7O6FNhgacuWLRw8eJBZs2aRkJBA+/btqV+/Pl26dKFVq1aMGzeOOXPm0KVLF4YOHUrt2rXZt2+fzzVat27NG2+8kUc1EPlBbtvRwYMHWbJkCXPnzmX//v2sXr1agqUCKLftqFevXt5f1syfP5/z58/nVVVEHsltG/rqq6944IEH6Ny5M7t27eKjjz5i2rRpeVgjkRdy245mz55N8eLFGT9+PDt27GD8+PGMGDEiD2sk8sK1tqP27dszZswYFi5cSGBgII899hgPPfQQv//+OyEhIYwdO5YNGzYwduxYPv744zyrT4EdhhcTE8Mnn3wCQEhICBkZGWzdupXmzZsD0KxZMzZv3gzAu+++S+3atfOsrCL/ym07WrNmDa1atcJkMlGlShX69u17cysg8oXr9e+R2+1mxowZdO3a9eYUXOQbuW1D4eHhJCYmApCcnEx4ePhNLL3IL3Lbjo4cOeL9hV+dOnXYuXPnTSy9yC+utR3Z7XYWLlxIUFAQiqIQFhZGYmIimzdv5oEHHgD0kVu7du3Ks7pAAQ6WjEYjAQEBAMyZM4cmTZqQkZGBxWIBIDIykrNnzwIQFBTk9xrbtm2jZ8+edO/enb17996cgot8Jbft6OTJk5w+fdrbji7tvRQFw/X49whg5cqVNGrUCJvNduMLLfKV3LahHj16sHTpUlq2bMngwYN5+eWXb17hRb6R23Z01113sW7dOkD/Rjp16tRNKrnIT/5LO9q/fz8nT56kevXqnDt3joiICAAMBgOKouB0OvOgJroCGyxlWbVqFXPmzGHIkCE+2zVNu+J51atXp0+fPkybNo1+/frJcLwC7r+2I03T8Hg8TJ06lT59+jBo0KAbWUyRz/3XdpRl7ty5dOjQ4UYUTdwi/msbmjp1Kq1atWL58uWMGDGCUaNG3chiinzuv7ajRx99FLPZzBNPPMHGjRu9H7yiYLrWdnTkyBEGDBjA2LFjMZvNOa5zrf8PvFEKdLD0yy+/8MUXXzBlyhSCg4MJCAjA4XAA+mTXQoUKXfbcsmXL0rRpUwBq1qxJfHw8Ho/nZhRb5DO5aUdRUVHExMSgKAp16tTh5MmTN6vYIp/JTTsCfWJ1bGwsxYoVuxnFFflQbtrQrl27aNy4MQANGzbkjz/+uCllFvlPbtqRxWJh+PDhzJgxg+eee87buyAKnmttR7GxsfTu3ZuRI0dSqVIlAAoVKuTteXK5XGia5u2VygsFNlhKSUlh9OjRTJo0ibCwMEAfF5mVQWrlypXe/3H4M2XKFBYvXgzAgQMHiIiIwGg03viCi3wlt+2oSZMmbNiwAYB//vmHIkWK3PhCi3wnt+0IYN++fZQpU+aGl1XkT7ltQyVLluS3334DYM+ePZQsWfLGF1rkO7ltR+vWrfNOxF+4cOFV/90St6d/044GDRrEsGHDqFKlivf8hg0bsnz5ckCf2123bt2bXANfipbXfVt5ZNasWXz66aeULl3au23kyJEMHjyYzMxMihYtygcffIDBYKBHjx4kJycTFxdH+fLlefHFFyldujSvvfYamqbhdrsZOHCgZDErgHLbjurXr8/48ePZuHEjAG+++SY1a9bMq+qIPHI92tGKFSvYtGkTw4cPz8OaiLyS2zZUtmxZBg0a5P3N76BBg6hYsWJeVUfkkdy2o5o1a9K3b18SExMJDQ1l3LhxBAcH52GNRF641nZ04sQJHnnkEZ/v5x49etC0aVMGDx7MkSNHsFgsjBw5Mk9/mVxggyUhhBBCCCGEuJICOwxPCCGEEEIIIa5EgiUhhBBCCCGE8EOCJSGEEEIIIYTwQ4IlIYQQQgghhPBDgiUhhBBCCCGE8EOCJSGEELeVatWqsW7durwuhhBCiNuAKa8LIIQQQvwbgwcPZsGCBQBomobL5fJZ3X369OnExMTkVfGEEELcRmSdJSGEELesNWvW8MILL7B///68LooQQojbkAzDE0IIcVupUKECa9asAaBbt25MmDCBvn37UqNGDVq2bMn+/fsZNWoUMTExNGnSxGfI3v79++nRowcxMTHUrVuXIUOGkJmZmVdVEUIIkcckWBJCCHFbmz17Nk8//TQbN24kKCiIZ599lhIlSrBx40YaNWrEmDFjAMjIyOCZZ54hJiaGjRs3Mn/+fP744w8mTJiQxzUQQgiRVyRYEkIIcVurUaMGNWvWJDAwkHr16uHxeOjcuTMWi4UmTZpw5MgRANauXYvL5aJ3795YLBaKFi3KCy+8wPz58/O2AkIIIfKMJHgQQghxWytSpIj371arlUKFCqEoivdnp9MJwPHjx0lMTKRatWo+56uqitPp9EkiIYQQomCQYEkIIcRtzWDwHUSRFShdymq1Urp0aZYtW3YziiWEEOIWIMPwhBBCCKBkyZKcPHmS1NRU77akpCRSUlLysFRCCCHykgRLQgghBNCoUSOio6N5//33SUlJIT4+ntdee40RI0bkddGEEELkEQmWhBBCCMBkMvHZZ59x/PhxGjVqRNu2bYmMjGTIkCF5XTQhhBB5RBalFUIIIYQQQgg/pGdJCCGEEEIIIfyQYEkIIYQQQggh/JBgSQghhBBCCCH8kGBJCCGEEEIIIfyQYEkIIYQQQggh/JBgSQghhBBCCCH8kGBJCCGEEEIIIfyQYEkIIYQQQggh/JBgSQghhBBCCCH8+H9lTcy0thDC7gAAAABJRU5ErkJggg==\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "weights = {\n",
        "  'SMA' : 0.25,\n",
        "  'RSI' : 0.5,  \n",
        "  'OBV' : 0.35,\n",
        "  'MACD' : 0.3,\n",
        "  'BB' : 0.25\n",
        "}"
      ],
      "metadata": {
        "id": "J8U1YSaVhoVi"
      },
      "execution_count": 110,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df['Signals_SMA'] = 0\n",
        "\n",
        "def calculateSignalsForSMA(alreadyBrought,alreadySold):\n",
        "  for i in range(len(df)) :\n",
        "    if df['SMA_10'][i] > df['SMA_30'][i] and alreadyBrought == False:\n",
        "      df['Signals_SMA'][i] = 1\n",
        "      alreadyBrought = True\n",
        "      alreadySold = False\n",
        "\n",
        "    elif  df['SMA_10'][i] < df['SMA_30'][i] and alreadySold == False:\n",
        "      df['Signals_SMA'][i] = -1\n",
        "      alreadySold = True\n",
        "      alreadyBrought = False\n",
        "      print(\"SellingSMA\")\n",
        "\n",
        "    else:\n",
        "      df['Signals_SMA'][i] = 0\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "H5p5_qd_jj_1",
        "outputId": "d92b1be1-13f1-40fa-ecd2-8a11d40df91a"
      },
      "execution_count": 111,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \"\"\"Entry point for launching an IPython kernel.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df['Signals_RSI'] = 0\n",
        "def calculateSignalsForRSI(alreadyBought, alreadySold):\n",
        "  for i in range(len(df)) :\n",
        "    if df['RSI_14'][i] < 25 and alreadyBought == False:\n",
        "      df['Signals_RSI'][i] = 1\n",
        "      alreadyBought = True\n",
        "      alreadySold = False\n",
        "\n",
        "    elif df['RSI_14'][i] > 70 and alreadySold == False:\n",
        "      df['Signals_RSI'][i] = -1\n",
        "      alreadyBought = False\n",
        "      alreadySold = True\n",
        "      print(\"SellignRSI\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IZ8NWCCnlnJ0",
        "outputId": "f40d76d9-df76-4e69-b405-656bcfa9aa99"
      },
      "execution_count": 112,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \"\"\"Entry point for launching an IPython kernel.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df['Signals_OBV'] = 0\n",
        "\n",
        "def calculateSignalsForOBV(alreadyBought,alreadySold):\n",
        "  for i in range(len(df)) :\n",
        "    if df['OBV'][i] > df['OBV_EMA'][i] and alreadyBought == False:\n",
        "      df['Signals_OBV'][i] = 1\n",
        "      alreadyBought = True\n",
        "      alreadySold = False\n",
        "\n",
        "    elif df['OBV'][i] < df['OBV_EMA'][i] and alreadySold == False:\n",
        "      df['Signals_OBV'][i] = -1\n",
        "      alreadySold = True\n",
        "      alreadyBought = False\n",
        "      print(\"SellingOBV\")\n",
        "\n",
        "    else :\n",
        "      df['Signals_OBV'][i] = 0"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PzXg-CDZmfCu",
        "outputId": "8748c075-b780-4eab-9349-69f5ecf838b8"
      },
      "execution_count": 113,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \"\"\"Entry point for launching an IPython kernel.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df['Signals_MACD'] = 0\n",
        "\n",
        "def calculateSignalsForMACD(alreadyBought,alreadySold):\n",
        "  for i in range(len(df)) :\n",
        "    if df['MACD_8_21_9'][i] > df['MACDs_8_21_9'][i] and alreadyBought == False:\n",
        "      df['Signals_MACD'][i] = 1\n",
        "      alreadyBought = True\n",
        "      alreadySold = False\n",
        "\n",
        "    elif df['MACD_8_21_9'][i] < df['MACDs_8_21_9'][i] and alreadySold == False:\n",
        "      df['Signals_MACD'][i] = -1\n",
        "      alreadySold = True\n",
        "      alreadyBought = False\n",
        "      print(\"SellingMACD\")\n",
        "\n",
        "    else :\n",
        "      df['Signals_MACD'][i] = 0"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "z8ZHUswUEnTO",
        "outputId": "a5f30baf-a5b8-489d-979e-05854eaf19d6"
      },
      "execution_count": 114,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \"\"\"Entry point for launching an IPython kernel.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df['Signals_BB'] = 0\n",
        "\n",
        "def calculateSignalsForBB(alreadyBought,alreadySold):\n",
        "  for i in range(len(df)) :\n",
        "    if df['BBL_20_2.0'][i] > df['Adj Close'][i] and alreadyBought == False:\n",
        "      df['Signals_BB'][i] = 1\n",
        "      alreadyBought = True\n",
        "      alreadySold = False\n",
        "\n",
        "    elif df['BBU_20_2.0'][i] < df['Adj Close'][i] and alreadySold == False:\n",
        "      df['Signals_BB'][i] = -1\n",
        "      alreadySold = True\n",
        "      alreadyBought = False\n",
        "      print(\"SellingBB\")\n",
        "\n",
        "    else :\n",
        "      df['Signals_BB'][i] = 0"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "y3bplevtFwTU",
        "outputId": "fdbb5e9f-4445-43cb-a525-786062d62700"
      },
      "execution_count": 115,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \"\"\"Entry point for launching an IPython kernel.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "calculateSignalsForSMA(False, True)\n",
        "calculateSignalsForRSI(False, True)\n",
        "calculateSignalsForOBV(False, True)\n",
        "calculateSignalsForMACD(False, True)\n",
        "calculateSignalsForBB(False, True)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EG7giy2vn0Qm",
        "outputId": "ae726561-ce49-46dd-938e-fde0ce44ee90"
      },
      "execution_count": 116,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:6: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:17: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:11: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  # This is added back by InteractiveShellApp.init_path()\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "SellingSMA\n",
            "SellingSMA\n",
            "SellingSMA\n",
            "SellingSMA\n",
            "SellingSMA\n",
            "SellingSMA\n",
            "SellingSMA\n",
            "SellingSMA\n",
            "SellingSMA\n",
            "SellingSMA\n",
            "SellingSMA\n",
            "SellingSMA\n",
            "SellingSMA\n",
            "SellingSMA\n",
            "SellingSMA\n",
            "SellingSMA\n",
            "SellingSMA\n",
            "SellingSMA\n",
            "SellignRSI\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:5: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \"\"\"\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:10: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  # Remove the CWD from sys.path while we load stuff.\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingOBV\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingMACD\n",
            "SellingBB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 693
        },
        "id": "XDJiwan5pHtL",
        "outputId": "33189ba7-891e-4889-9aa6-e0282646abd1"
      },
      "execution_count": 117,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                   Open         High          Low        Close    Adj Close  \\\n",
              "Date                                                                          \n",
              "2015-02-13   540.599976   541.000000   531.799988   532.900024   505.417145   \n",
              "2015-02-16   537.900024   542.500000   531.250000   533.775024   506.246979   \n",
              "2015-02-18   533.775024   541.474976   528.525024   537.400024   509.685028   \n",
              "2015-02-19   537.000000   542.450012   531.900024   539.900024   512.056152   \n",
              "2015-02-20   541.500000   544.950012   534.250000   536.525024   508.855133   \n",
              "...                 ...          ...          ...          ...          ...   \n",
              "2019-12-23  1299.000000  1304.000000  1288.800049  1302.400024  1281.883057   \n",
              "2019-12-24  1298.599976  1301.099976  1286.949951  1289.150024  1268.841797   \n",
              "2019-12-26  1289.699951  1291.849976  1264.650024  1270.449951  1250.436279   \n",
              "2019-12-27  1272.000000  1279.000000  1270.000000  1275.000000  1254.914673   \n",
              "2019-12-30  1282.000000  1288.750000  1274.050049  1282.150024  1261.952026   \n",
              "\n",
              "             Volume       SMA_10       SMA_30     RSI_14          OBV  ...  \\\n",
              "Date                                                                   ...   \n",
              "2015-02-13  3857250   531.907495   511.523333  59.815652   36787422.0  ...   \n",
              "2015-02-16  3694358   531.204999   513.227500  60.270091   40481780.0  ...   \n",
              "2015-02-18  2690846   531.740002   515.188334  62.178376   43172626.0  ...   \n",
              "2015-02-19  2253502   532.345007   517.480835  63.481122   45426128.0  ...   \n",
              "2015-02-20  3103012   532.172510   519.615002  60.453780   42323116.0  ...   \n",
              "...             ...          ...          ...        ...          ...  ...   \n",
              "2019-12-23  5097891  1273.439990  1267.870003  67.172380  436711588.0  ...   \n",
              "2019-12-24  3589604  1277.404993  1268.683337  59.681157  433121984.0  ...   \n",
              "2019-12-26  7474879  1279.574988  1269.113334  51.031270  425647105.0  ...   \n",
              "2019-12-27  3546496  1280.714990  1269.150000  52.822954  429193601.0  ...   \n",
              "2019-12-30  4667095  1282.544995  1269.291667  55.573750  433860696.0  ...   \n",
              "\n",
              "             BBU_20_2.0  BBB_20_2.0  BBP_20_2.0       OBV_EMA  Signals_SMA  \\\n",
              "Date                                                                         \n",
              "2015-02-13   552.491119    9.935473    0.625372  3.319909e+07            1   \n",
              "2015-02-16   551.493358    8.899494    0.622928  3.418018e+07            0   \n",
              "2015-02-18   550.370369    7.782982    0.685420  3.538994e+07            0   \n",
              "2015-02-19   550.267673    7.168855    0.727761  3.673849e+07            0   \n",
              "2015-02-20   549.010332    6.180250    0.620659  3.748812e+07            0   \n",
              "...                 ...         ...         ...           ...          ...   \n",
              "2019-12-23  1301.791263    5.528411    1.008693  4.221179e+08            0   \n",
              "2019-12-24  1303.681982    5.712435    0.799293  4.235852e+08            0   \n",
              "2019-12-26  1302.969349    5.664486    0.546918  4.238601e+08            0   \n",
              "2019-12-27  1303.606740    5.686364    0.603117  4.245712e+08            0   \n",
              "2019-12-30  1304.395823    5.752431    0.694998  4.258098e+08            0   \n",
              "\n",
              "            Signals_RSI  Signals_OBV  Signals_MACD  Signals_BB  \\\n",
              "Date                                                             \n",
              "2015-02-13            0            1             0           0   \n",
              "2015-02-16            0            0             0           0   \n",
              "2015-02-18            0            0             0           0   \n",
              "2015-02-19            0            0             0           1   \n",
              "2015-02-20            0            0             0           0   \n",
              "...                 ...          ...           ...         ...   \n",
              "2019-12-23            0            0             0           0   \n",
              "2019-12-24            0            0             0           0   \n",
              "2019-12-26            0            0             0           0   \n",
              "2019-12-27            0            0             0           0   \n",
              "2019-12-30            0            0            -1           0   \n",
              "\n",
              "            Buy_Sell_Signal  \n",
              "Date                         \n",
              "2015-02-13                0  \n",
              "2015-02-16                0  \n",
              "2015-02-18                0  \n",
              "2015-02-19                0  \n",
              "2015-02-20                0  \n",
              "...                     ...  \n",
              "2019-12-23                0  \n",
              "2019-12-24                0  \n",
              "2019-12-26                0  \n",
              "2019-12-27                0  \n",
              "2019-12-30                0  \n",
              "\n",
              "[1198 rows x 25 columns]"
            ],
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              "  <div id=\"df-ecea99bd-173e-4f19-a34e-a964bdadd6d1\">\n",
              "    <div class=\"colab-df-container\">\n",
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Open</th>\n",
              "      <th>High</th>\n",
              "      <th>Low</th>\n",
              "      <th>Close</th>\n",
              "      <th>Adj Close</th>\n",
              "      <th>Volume</th>\n",
              "      <th>SMA_10</th>\n",
              "      <th>SMA_30</th>\n",
              "      <th>RSI_14</th>\n",
              "      <th>OBV</th>\n",
              "      <th>...</th>\n",
              "      <th>BBU_20_2.0</th>\n",
              "      <th>BBB_20_2.0</th>\n",
              "      <th>BBP_20_2.0</th>\n",
              "      <th>OBV_EMA</th>\n",
              "      <th>Signals_SMA</th>\n",
              "      <th>Signals_RSI</th>\n",
              "      <th>Signals_OBV</th>\n",
              "      <th>Signals_MACD</th>\n",
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              "      <th>Buy_Sell_Signal</th>\n",
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              "      <th></th>\n",
              "      <th></th>\n",
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              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2015-02-13</th>\n",
              "      <td>540.599976</td>\n",
              "      <td>541.000000</td>\n",
              "      <td>531.799988</td>\n",
              "      <td>532.900024</td>\n",
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              "      <td>3857250</td>\n",
              "      <td>531.907495</td>\n",
              "      <td>511.523333</td>\n",
              "      <td>59.815652</td>\n",
              "      <td>36787422.0</td>\n",
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              "      <td>552.491119</td>\n",
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              "      <th>2015-02-16</th>\n",
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              "      <td>531.250000</td>\n",
              "      <td>533.775024</td>\n",
              "      <td>506.246979</td>\n",
              "      <td>3694358</td>\n",
              "      <td>531.204999</td>\n",
              "      <td>513.227500</td>\n",
              "      <td>60.270091</td>\n",
              "      <td>40481780.0</td>\n",
              "      <td>...</td>\n",
              "      <td>551.493358</td>\n",
              "      <td>8.899494</td>\n",
              "      <td>0.622928</td>\n",
              "      <td>3.418018e+07</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <th>2015-02-18</th>\n",
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              "      <td>541.474976</td>\n",
              "      <td>528.525024</td>\n",
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              "      <td>509.685028</td>\n",
              "      <td>2690846</td>\n",
              "      <td>531.740002</td>\n",
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              "      <th>2015-02-19</th>\n",
              "      <td>537.000000</td>\n",
              "      <td>542.450012</td>\n",
              "      <td>531.900024</td>\n",
              "      <td>539.900024</td>\n",
              "      <td>512.056152</td>\n",
              "      <td>2253502</td>\n",
              "      <td>532.345007</td>\n",
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              "      <th>2015-02-20</th>\n",
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              "      <td>532.172510</td>\n",
              "      <td>519.615002</td>\n",
              "      <td>60.453780</td>\n",
              "      <td>42323116.0</td>\n",
              "      <td>...</td>\n",
              "      <td>549.010332</td>\n",
              "      <td>6.180250</td>\n",
              "      <td>0.620659</td>\n",
              "      <td>3.748812e+07</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-12-23</th>\n",
              "      <td>1299.000000</td>\n",
              "      <td>1304.000000</td>\n",
              "      <td>1288.800049</td>\n",
              "      <td>1302.400024</td>\n",
              "      <td>1281.883057</td>\n",
              "      <td>5097891</td>\n",
              "      <td>1273.439990</td>\n",
              "      <td>1267.870003</td>\n",
              "      <td>67.172380</td>\n",
              "      <td>436711588.0</td>\n",
              "      <td>...</td>\n",
              "      <td>1301.791263</td>\n",
              "      <td>5.528411</td>\n",
              "      <td>1.008693</td>\n",
              "      <td>4.221179e+08</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-12-24</th>\n",
              "      <td>1298.599976</td>\n",
              "      <td>1301.099976</td>\n",
              "      <td>1286.949951</td>\n",
              "      <td>1289.150024</td>\n",
              "      <td>1268.841797</td>\n",
              "      <td>3589604</td>\n",
              "      <td>1277.404993</td>\n",
              "      <td>1268.683337</td>\n",
              "      <td>59.681157</td>\n",
              "      <td>433121984.0</td>\n",
              "      <td>...</td>\n",
              "      <td>1303.681982</td>\n",
              "      <td>5.712435</td>\n",
              "      <td>0.799293</td>\n",
              "      <td>4.235852e+08</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-12-26</th>\n",
              "      <td>1289.699951</td>\n",
              "      <td>1291.849976</td>\n",
              "      <td>1264.650024</td>\n",
              "      <td>1270.449951</td>\n",
              "      <td>1250.436279</td>\n",
              "      <td>7474879</td>\n",
              "      <td>1279.574988</td>\n",
              "      <td>1269.113334</td>\n",
              "      <td>51.031270</td>\n",
              "      <td>425647105.0</td>\n",
              "      <td>...</td>\n",
              "      <td>1302.969349</td>\n",
              "      <td>5.664486</td>\n",
              "      <td>0.546918</td>\n",
              "      <td>4.238601e+08</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-12-27</th>\n",
              "      <td>1272.000000</td>\n",
              "      <td>1279.000000</td>\n",
              "      <td>1270.000000</td>\n",
              "      <td>1275.000000</td>\n",
              "      <td>1254.914673</td>\n",
              "      <td>3546496</td>\n",
              "      <td>1280.714990</td>\n",
              "      <td>1269.150000</td>\n",
              "      <td>52.822954</td>\n",
              "      <td>429193601.0</td>\n",
              "      <td>...</td>\n",
              "      <td>1303.606740</td>\n",
              "      <td>5.686364</td>\n",
              "      <td>0.603117</td>\n",
              "      <td>4.245712e+08</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-12-30</th>\n",
              "      <td>1282.000000</td>\n",
              "      <td>1288.750000</td>\n",
              "      <td>1274.050049</td>\n",
              "      <td>1282.150024</td>\n",
              "      <td>1261.952026</td>\n",
              "      <td>4667095</td>\n",
              "      <td>1282.544995</td>\n",
              "      <td>1269.291667</td>\n",
              "      <td>55.573750</td>\n",
              "      <td>433860696.0</td>\n",
              "      <td>...</td>\n",
              "      <td>1304.395823</td>\n",
              "      <td>5.752431</td>\n",
              "      <td>0.694998</td>\n",
              "      <td>4.258098e+08</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "  </tbody>\n",
              "</table>\n",
              "<p>1198 rows × 25 columns</p>\n",
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            ]
          },
          "metadata": {},
          "execution_count": 117
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sellTotal = 0\n",
        "buyTotal = 0\n",
        "df['Buy_Sell_Signal'] = 0\n",
        "\n",
        "\n",
        "for i in range(len(df)):\n",
        "  sellTotal = 0\n",
        "  buyTotal = 0\n",
        "  if(df['Signals_SMA'][i] == 1):\n",
        "    buyTotal = buyTotal + 1*weights['SMA']\n",
        "  if(df['Signals_SMA'][i] == -1):\n",
        "    sellTotal = sellTotal +1*weights['SMA']\n",
        "  if(df['Signals_RSI'][i] == 1):\n",
        "    buyTotal = buyTotal + 1*weights['RSI']\n",
        "  if(df['Signals_RSI'][i] == -1):\n",
        "    sellTotal = sellTotal +1*weights['RSI']\n",
        "  if(df['Signals_OBV'][i] == 1):\n",
        "    buyTotal = buyTotal + 1*weights['OBV']\n",
        "  if(df['Signals_OBV'][i] == -1):\n",
        "    sellTotal = sellTotal +1*weights['OBV']\n",
        "  if df['Signals_MACD'][i] == 1:\n",
        "    buyTotal = buyTotal + 1*weights['MACD']\n",
        "  if df['Signals_MACD'][i] == -1:\n",
        "    sellTotal = sellTotal + 1*weights['MACD']\n",
        "  \n",
        "\n",
        "  if buyTotal == 0.5 : \n",
        "    df['Buy_Sell_Signal'][i] = 1\n",
        "    print(\"Buy\")\n",
        "  elif sellTotal == 0.5:\n",
        "    df['Buy_Sell_Signal'][i] = -1\n",
        "    print(\"Sell\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Lt4qlO1ztcmS",
        "outputId": "48a28614-e17c-447a-cbc2-b65009da4dff"
      },
      "execution_count": 118,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Buy\n",
            "Sell\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:3: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  This is separate from the ipykernel package so we can avoid doing imports until\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:28: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "/usr/local/lib/python3.7/dist-packages/ipykernel_launcher.py:31: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df"
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          "height": 693
        },
        "id": "hhmKI4iZvlV8",
        "outputId": "47eebc34-fe89-4deb-b3b0-ac67866eaa54"
      },
      "execution_count": 119,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                   Open         High          Low        Close    Adj Close  \\\n",
              "Date                                                                          \n",
              "2015-02-13   540.599976   541.000000   531.799988   532.900024   505.417145   \n",
              "2015-02-16   537.900024   542.500000   531.250000   533.775024   506.246979   \n",
              "2015-02-18   533.775024   541.474976   528.525024   537.400024   509.685028   \n",
              "2015-02-19   537.000000   542.450012   531.900024   539.900024   512.056152   \n",
              "2015-02-20   541.500000   544.950012   534.250000   536.525024   508.855133   \n",
              "...                 ...          ...          ...          ...          ...   \n",
              "2019-12-23  1299.000000  1304.000000  1288.800049  1302.400024  1281.883057   \n",
              "2019-12-24  1298.599976  1301.099976  1286.949951  1289.150024  1268.841797   \n",
              "2019-12-26  1289.699951  1291.849976  1264.650024  1270.449951  1250.436279   \n",
              "2019-12-27  1272.000000  1279.000000  1270.000000  1275.000000  1254.914673   \n",
              "2019-12-30  1282.000000  1288.750000  1274.050049  1282.150024  1261.952026   \n",
              "\n",
              "             Volume       SMA_10       SMA_30     RSI_14          OBV  ...  \\\n",
              "Date                                                                   ...   \n",
              "2015-02-13  3857250   531.907495   511.523333  59.815652   36787422.0  ...   \n",
              "2015-02-16  3694358   531.204999   513.227500  60.270091   40481780.0  ...   \n",
              "2015-02-18  2690846   531.740002   515.188334  62.178376   43172626.0  ...   \n",
              "2015-02-19  2253502   532.345007   517.480835  63.481122   45426128.0  ...   \n",
              "2015-02-20  3103012   532.172510   519.615002  60.453780   42323116.0  ...   \n",
              "...             ...          ...          ...        ...          ...  ...   \n",
              "2019-12-23  5097891  1273.439990  1267.870003  67.172380  436711588.0  ...   \n",
              "2019-12-24  3589604  1277.404993  1268.683337  59.681157  433121984.0  ...   \n",
              "2019-12-26  7474879  1279.574988  1269.113334  51.031270  425647105.0  ...   \n",
              "2019-12-27  3546496  1280.714990  1269.150000  52.822954  429193601.0  ...   \n",
              "2019-12-30  4667095  1282.544995  1269.291667  55.573750  433860696.0  ...   \n",
              "\n",
              "             BBU_20_2.0  BBB_20_2.0  BBP_20_2.0       OBV_EMA  Signals_SMA  \\\n",
              "Date                                                                         \n",
              "2015-02-13   552.491119    9.935473    0.625372  3.319909e+07            1   \n",
              "2015-02-16   551.493358    8.899494    0.622928  3.418018e+07            0   \n",
              "2015-02-18   550.370369    7.782982    0.685420  3.538994e+07            0   \n",
              "2015-02-19   550.267673    7.168855    0.727761  3.673849e+07            0   \n",
              "2015-02-20   549.010332    6.180250    0.620659  3.748812e+07            0   \n",
              "...                 ...         ...         ...           ...          ...   \n",
              "2019-12-23  1301.791263    5.528411    1.008693  4.221179e+08            0   \n",
              "2019-12-24  1303.681982    5.712435    0.799293  4.235852e+08            0   \n",
              "2019-12-26  1302.969349    5.664486    0.546918  4.238601e+08            0   \n",
              "2019-12-27  1303.606740    5.686364    0.603117  4.245712e+08            0   \n",
              "2019-12-30  1304.395823    5.752431    0.694998  4.258098e+08            0   \n",
              "\n",
              "            Signals_RSI  Signals_OBV  Signals_MACD  Signals_BB  \\\n",
              "Date                                                             \n",
              "2015-02-13            0            1             0           0   \n",
              "2015-02-16            0            0             0           0   \n",
              "2015-02-18            0            0             0           0   \n",
              "2015-02-19            0            0             0           1   \n",
              "2015-02-20            0            0             0           0   \n",
              "...                 ...          ...           ...         ...   \n",
              "2019-12-23            0            0             0           0   \n",
              "2019-12-24            0            0             0           0   \n",
              "2019-12-26            0            0             0           0   \n",
              "2019-12-27            0            0             0           0   \n",
              "2019-12-30            0            0            -1           0   \n",
              "\n",
              "            Buy_Sell_Signal  \n",
              "Date                         \n",
              "2015-02-13                0  \n",
              "2015-02-16                0  \n",
              "2015-02-18                0  \n",
              "2015-02-19                0  \n",
              "2015-02-20                0  \n",
              "...                     ...  \n",
              "2019-12-23                0  \n",
              "2019-12-24                0  \n",
              "2019-12-26                0  \n",
              "2019-12-27                0  \n",
              "2019-12-30                0  \n",
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              "[1198 rows x 25 columns]"
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              "    </tr>\n",
              "    <tr>\n",
              "      <th>Date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2015-02-13</th>\n",
              "      <td>540.599976</td>\n",
              "      <td>541.000000</td>\n",
              "      <td>531.799988</td>\n",
              "      <td>532.900024</td>\n",
              "      <td>505.417145</td>\n",
              "      <td>3857250</td>\n",
              "      <td>531.907495</td>\n",
              "      <td>511.523333</td>\n",
              "      <td>59.815652</td>\n",
              "      <td>36787422.0</td>\n",
              "      <td>...</td>\n",
              "      <td>552.491119</td>\n",
              "      <td>9.935473</td>\n",
              "      <td>0.625372</td>\n",
              "      <td>3.319909e+07</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-02-16</th>\n",
              "      <td>537.900024</td>\n",
              "      <td>542.500000</td>\n",
              "      <td>531.250000</td>\n",
              "      <td>533.775024</td>\n",
              "      <td>506.246979</td>\n",
              "      <td>3694358</td>\n",
              "      <td>531.204999</td>\n",
              "      <td>513.227500</td>\n",
              "      <td>60.270091</td>\n",
              "      <td>40481780.0</td>\n",
              "      <td>...</td>\n",
              "      <td>551.493358</td>\n",
              "      <td>8.899494</td>\n",
              "      <td>0.622928</td>\n",
              "      <td>3.418018e+07</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-02-18</th>\n",
              "      <td>533.775024</td>\n",
              "      <td>541.474976</td>\n",
              "      <td>528.525024</td>\n",
              "      <td>537.400024</td>\n",
              "      <td>509.685028</td>\n",
              "      <td>2690846</td>\n",
              "      <td>531.740002</td>\n",
              "      <td>515.188334</td>\n",
              "      <td>62.178376</td>\n",
              "      <td>43172626.0</td>\n",
              "      <td>...</td>\n",
              "      <td>550.370369</td>\n",
              "      <td>7.782982</td>\n",
              "      <td>0.685420</td>\n",
              "      <td>3.538994e+07</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-02-19</th>\n",
              "      <td>537.000000</td>\n",
              "      <td>542.450012</td>\n",
              "      <td>531.900024</td>\n",
              "      <td>539.900024</td>\n",
              "      <td>512.056152</td>\n",
              "      <td>2253502</td>\n",
              "      <td>532.345007</td>\n",
              "      <td>517.480835</td>\n",
              "      <td>63.481122</td>\n",
              "      <td>45426128.0</td>\n",
              "      <td>...</td>\n",
              "      <td>550.267673</td>\n",
              "      <td>7.168855</td>\n",
              "      <td>0.727761</td>\n",
              "      <td>3.673849e+07</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-02-20</th>\n",
              "      <td>541.500000</td>\n",
              "      <td>544.950012</td>\n",
              "      <td>534.250000</td>\n",
              "      <td>536.525024</td>\n",
              "      <td>508.855133</td>\n",
              "      <td>3103012</td>\n",
              "      <td>532.172510</td>\n",
              "      <td>519.615002</td>\n",
              "      <td>60.453780</td>\n",
              "      <td>42323116.0</td>\n",
              "      <td>...</td>\n",
              "      <td>549.010332</td>\n",
              "      <td>6.180250</td>\n",
              "      <td>0.620659</td>\n",
              "      <td>3.748812e+07</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-12-23</th>\n",
              "      <td>1299.000000</td>\n",
              "      <td>1304.000000</td>\n",
              "      <td>1288.800049</td>\n",
              "      <td>1302.400024</td>\n",
              "      <td>1281.883057</td>\n",
              "      <td>5097891</td>\n",
              "      <td>1273.439990</td>\n",
              "      <td>1267.870003</td>\n",
              "      <td>67.172380</td>\n",
              "      <td>436711588.0</td>\n",
              "      <td>...</td>\n",
              "      <td>1301.791263</td>\n",
              "      <td>5.528411</td>\n",
              "      <td>1.008693</td>\n",
              "      <td>4.221179e+08</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-12-24</th>\n",
              "      <td>1298.599976</td>\n",
              "      <td>1301.099976</td>\n",
              "      <td>1286.949951</td>\n",
              "      <td>1289.150024</td>\n",
              "      <td>1268.841797</td>\n",
              "      <td>3589604</td>\n",
              "      <td>1277.404993</td>\n",
              "      <td>1268.683337</td>\n",
              "      <td>59.681157</td>\n",
              "      <td>433121984.0</td>\n",
              "      <td>...</td>\n",
              "      <td>1303.681982</td>\n",
              "      <td>5.712435</td>\n",
              "      <td>0.799293</td>\n",
              "      <td>4.235852e+08</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-12-26</th>\n",
              "      <td>1289.699951</td>\n",
              "      <td>1291.849976</td>\n",
              "      <td>1264.650024</td>\n",
              "      <td>1270.449951</td>\n",
              "      <td>1250.436279</td>\n",
              "      <td>7474879</td>\n",
              "      <td>1279.574988</td>\n",
              "      <td>1269.113334</td>\n",
              "      <td>51.031270</td>\n",
              "      <td>425647105.0</td>\n",
              "      <td>...</td>\n",
              "      <td>1302.969349</td>\n",
              "      <td>5.664486</td>\n",
              "      <td>0.546918</td>\n",
              "      <td>4.238601e+08</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-12-27</th>\n",
              "      <td>1272.000000</td>\n",
              "      <td>1279.000000</td>\n",
              "      <td>1270.000000</td>\n",
              "      <td>1275.000000</td>\n",
              "      <td>1254.914673</td>\n",
              "      <td>3546496</td>\n",
              "      <td>1280.714990</td>\n",
              "      <td>1269.150000</td>\n",
              "      <td>52.822954</td>\n",
              "      <td>429193601.0</td>\n",
              "      <td>...</td>\n",
              "      <td>1303.606740</td>\n",
              "      <td>5.686364</td>\n",
              "      <td>0.603117</td>\n",
              "      <td>4.245712e+08</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2019-12-30</th>\n",
              "      <td>1282.000000</td>\n",
              "      <td>1288.750000</td>\n",
              "      <td>1274.050049</td>\n",
              "      <td>1282.150024</td>\n",
              "      <td>1261.952026</td>\n",
              "      <td>4667095</td>\n",
              "      <td>1282.544995</td>\n",
              "      <td>1269.291667</td>\n",
              "      <td>55.573750</td>\n",
              "      <td>433860696.0</td>\n",
              "      <td>...</td>\n",
              "      <td>1304.395823</td>\n",
              "      <td>5.752431</td>\n",
              "      <td>0.694998</td>\n",
              "      <td>4.258098e+08</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>-1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1198 rows × 25 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-bf2bf9fb-93c9-4ade-9396-d8fd863e298b')\"\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",
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              "      \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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              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\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",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
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              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-bf2bf9fb-93c9-4ade-9396-d8fd863e298b 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-bf2bf9fb-93c9-4ade-9396-d8fd863e298b');\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",
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              "          element.appendChild(docLink);\n",
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              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 119
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import math"
      ],
      "metadata": {
        "id": "pqSuf2ZA1wiJ"
      },
      "execution_count": 120,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "initial_capital = 10000\n",
        "current_capital = 10000\n",
        "shares = 0\n",
        "\n",
        "for i in range(len(df)):\n",
        "  if(df['Buy_Sell_Signal'][i] == 1 and current_capital >= df['Adj Close'][i]):\n",
        "    current_capital = current_capital - math.floor(current_capital/df['Adj Close'][i]) * df['Adj Close'][i]\n",
        "    shares = math.floor(current_capital/df['Adj Close'][i])\n",
        "  elif df['Buy_Sell_Signal'][i] == -1 and shares > 0:\n",
        "    current_capital = current_capital + shares * df['Adj Close'][i]\n",
        "    shares = 0\n",
        "\n",
        "print(\"Final Capital is : Rs \", current_capital)\n",
        "print(\"Percentage of profit = \",((current_capital-initial_capital)/initial_capital)*100, \"%\" )"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "frAMl2iz09dh",
        "outputId": "6a1b5850-0a4d-4172-8751-962a9bff8677"
      },
      "execution_count": 121,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Final Capital is : Rs  347.8603515625\n",
            "Percentage of profit =  -96.521396484375 %\n"
          ]
        }
      ]
    }
  ]
}