Time_Series_Forecasting.ipynb

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      "cell_type": "markdown",
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        "<a href=\"https://colab.research.google.com/github/sakuna47/Customer_Segmentation_with_Clustering/blob/main/Time_Series_Forecasting.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
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            "\u001b[?25hInstalling collected packages: setuptools, pip\n",
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            "    Found existing installation: setuptools 75.1.0\n",
            "    Uninstalling setuptools-75.1.0:\n",
            "      Successfully uninstalled setuptools-75.1.0\n",
            "  Attempting uninstall: pip\n",
            "    Found existing installation: pip 24.1.2\n",
            "    Uninstalling pip-24.1.2:\n",
            "      Successfully uninstalled pip-24.1.2\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",
            "ipython 7.34.0 requires jedi>=0.16, which is not installed.\u001b[0m\u001b[31m\n",
            "\u001b[0mSuccessfully installed pip-25.0.1 setuptools-75.8.0\n"
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            "Collecting pystan==2.19.1.1\n",
            "  Downloading pystan-2.19.1.1.tar.gz (16.2 MB)\n",
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            "  \u001b[31m╰─>\u001b[0m See above for output.\n",
            "  \n",
            "  \u001b[1;35mnote\u001b[0m: This error originates from a subprocess, and is likely not a problem with pip.\n",
            "  Building wheel for pystan (setup.py) ... \u001b[?25lerror\n",
            "\u001b[31m  ERROR: Failed building wheel for pystan\u001b[0m\u001b[31m\n",
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            "Failed to build pystan\n",
            "\u001b[31mERROR: Failed to build installable wheels for some pyproject.toml based projects (pystan)\u001b[0m\u001b[31m\n",
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          ]
        }
      ],
      "source": [
        "# Upgrade pip, setuptools, and wheel\n",
        "!pip install --upgrade pip setuptools wheel\n",
        "\n",
        "# Install pystan (required dependency for Prophet)\n",
        "!pip install pystan==2.19.1.1\n",
        "\n",
        "# Install Prophet (fbprophet is now deprecated)\n",
        "!pip install prophet\n",
        "\n",
        "# Install other necessary libraries\n",
        "!pip install pandas numpy matplotlib statsmodels tensorflow scikit-learn\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Import necessary libraries\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "from statsmodels.tsa.arima.model import ARIMA\n",
        "from prophet import Prophet\n",
        "from sklearn.metrics import mean_squared_error, mean_absolute_error"
      ],
      "metadata": {
        "id": "ZgKLyTUdb-lS"
      },
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Load the dataset\n",
        "url = \"https://raw.githubusercontent.com/jbrownlee/Datasets/master/airline-passengers.csv\"\n",
        "df = pd.read_csv(url, parse_dates=['Month'], index_col='Month')\n",
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 237
        },
        "id": "0WZg8NIwcSqy",
        "outputId": "83a67edb-8e5d-4b04-9bef-795f9029529e"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            Passengers\n",
              "Month                 \n",
              "1949-01-01         112\n",
              "1949-02-01         118\n",
              "1949-03-01         132\n",
              "1949-04-01         129\n",
              "1949-05-01         121"
            ],
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              "      <th></th>\n",
              "      <th>Passengers</th>\n",
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              "      <th>1949-01-01</th>\n",
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              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-92d8f421-7aa9-416d-9b9f-838b37f0c7d0 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-92d8f421-7aa9-416d-9b9f-838b37f0c7d0');\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",
              "\n",
              "\n",
              "<div id=\"df-55385448-b650-4398-8cb0-6503c965fd62\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-55385448-b650-4398-8cb0-6503c965fd62')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-55385448-b650-4398-8cb0-6503c965fd62 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 144,\n  \"fields\": [\n    {\n      \"column\": \"Month\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": \"1949-01-01 00:00:00\",\n        \"max\": \"1960-12-01 00:00:00\",\n        \"num_unique_values\": 144,\n        \"samples\": [\n          \"1958-10-01 00:00:00\",\n          \"1950-08-01 00:00:00\",\n          \"1955-11-01 00:00:00\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Passengers\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 119,\n        \"min\": 104,\n        \"max\": 622,\n        \"num_unique_values\": 118,\n        \"samples\": [\n          293,\n          340,\n          121\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Explore the dataset\n",
        "print(df.info())\n",
        "print(df.describe())\n",
        "\n",
        "plt.figure(figsize=(10, 6))\n",
        "plt.plot(df.index, df['Passengers'], label='Passengers')\n",
        "plt.title('Monthly Airline Passengers')\n",
        "plt.xlabel('Date')\n",
        "plt.ylabel('Number of Passengers')\n",
        "plt.legend()\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 876
        },
        "id": "eSVKiL_hcbl5",
        "outputId": "099624e3-3b6e-4dfb-a063-e4393268438c"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "DatetimeIndex: 144 entries, 1949-01-01 to 1960-12-01\n",
            "Data columns (total 1 columns):\n",
            " #   Column      Non-Null Count  Dtype\n",
            "---  ------      --------------  -----\n",
            " 0   Passengers  144 non-null    int64\n",
            "dtypes: int64(1)\n",
            "memory usage: 2.2 KB\n",
            "None\n",
            "       Passengers\n",
            "count  144.000000\n",
            "mean   280.298611\n",
            "std    119.966317\n",
            "min    104.000000\n",
            "25%    180.000000\n",
            "50%    265.500000\n",
            "75%    360.500000\n",
            "max    622.000000\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x600 with 1 Axes>"
            ],
            "image/png": 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8PBxzzDFYvXo1/ve//+Guu+5qs7fGGxMnTgQA3H///bj00kthMBhw7rnnygVWdyQnJ+PMM8/EsmXLEBcXh1mzZnX5NUuXLoVOp+vw2j/96U+4//778eGHH7Ybid2TTjnlFNx000148sknsXXrVsyYMQMGgwH79+/HsmXL8MILL3S4381b55xzDpYvX44LLrgAs2bNQm5uLl577TWMHDkS9fX18nXXX389qqqqcPrpp2PAgAHIz8/HSy+9hHHjxsl76EaOHIlTTz0VEydOREJCAn7//Xd8/PHHreLKFy9ejClTpmDMmDG44YYbMGjQIJSWlmLjxo04cuQItm3b5tP6U1NTceedd2LRokX405/+hDPPPBPbtm3DypUrkZSU1KrLds899+Dzzz/HOeecg2uuuQYTJ05EQ0MDduzYgY8//hh5eXkdjkAKM2bMQFpaGk466SSkpqZi9+7dePnll1sFlxAR9RQWUkRECqHVavH555/joYcewn//+18sWbIEWVlZ+Ne//oW7777br8c89thj8dhjj+G1117D119/DafTidzc3IAUUoBrvG/FihW4+OKLYTKZOr3WZrNh2bJlOPHEE5GQkNDuNaNHj0Z2djbef//9kBdSAPDaa69h4sSJeP311/H3v/8der0eWVlZuOKKKwIScHDNNdegpKQEr7/+OlatWoWRI0fi/fffx7Jly1odQnzFFVfgjTfewCuvvIKamhqkpaXhkksuwcKFC6HVuoZL7rjjDnz++edYvXo1mpubkZmZiccff1w+lBlwFVu///47HnnkEbzzzjuorKxESkoKxo8fj4ceesiv1/DUU08hIiICb775Jr755htMnjwZq1evxpQpU1qN2kVEROCHH37AE088gWXLluG9995DTEwMhg4dikceeQSxsbFdPtdNN92EpUuX4tlnn0V9fT0GDBiAO+64Aw888IBfayci6g6N5M+OUSIiIgD/+9//cP7552PdunU4+eSTQ70cUoiamhrEx8fj8ccfx/333x/q5RARBQX3SBERkd/efPNNDBo0CFOmTAn1UihEmpqa2tz2/PPPA3BF2hMR9VYc7SMiIp99+OGH2L59O7788ku88MILQU0HJGX773//i3feeQdnn302oqKisH79evznP//BjBkzeL4TEfVqHO0jIiKfaTQaREVF4ZJLLsFrr70GvZ5/l+urNm/ejHvvvRdbt26F2WxGamoqZs+ejccffxxRUVGhXh4RUdCwkCIiIiIiIvIR90gRERERERH5iIUUERERERGRjzjUDsDpdKKoqAjR0dHcME1ERERE1IdJkoS6ujr069dPPquvPSykABQVFSEjIyPUyyAiIiIiIoU4fPgwBgwY0OH9LKQAREdHA3B9s2JiYkK8GiIiIiIiChWz2YyMjAy5RugICylAHueLiYlhIUVERERERF1u+WHYBBERERERkY9YSBEREREREfmIhRQREREREZGPuEfKSw6HAzabLdTLoB6k0+mg1+sZiU9EREREbbCQ8kJ9fT2OHDkCSZJCvRTqYREREUhPT4fRaAz1UoiIiIhIQVhIdcHhcODIkSOIiIhAcnIyuxN9hCRJsFqtKC8vR25uLoYMGdLpgWxERERE1LewkOqCzWaDJElITk5GeHh4qJdDPSg8PBwGgwH5+fmwWq0ICwsL9ZKIiIiISCH4J3YvsRPVN7ELRURERETt4btEIiIiIiIiH7GQIiIiIiIi8hELKSIiIiIiIh+xkOqlrrnmGmg0Gmg0GhiNRuTk5ODRRx+F3W4P9dKIiIiIiFSPqX292JlnnoklS5agubkZX331FebOnQuDwYAFCxaEemk9zmq18iwoIiIiIgoYdqR8JEkSGq32kHz4eiCwyWRCWloaMjMzccstt2D69On4/PPP8eyzz2LMmDGIjIxERkYGbr31VtTX18tfl5+fj3PPPRfx8fGIjIzEqFGj8NVXXwEAqqurMWfOHDkOfsiQIViyZIn8tYcPH8bFF1+MuLg4JCQk4LzzzkNeXp58/zXXXIPzzz8fzzzzDNLT05GYmIi5c+fCZrPJ1xQXF2PWrFkIDw9HdnY2PvjgA2RlZeH555+Xr6mpqcH111+P5ORkxMTE4PTTT8e2bdvk+xcuXIhx48bhrbfeQnZ2thxd/vHHH2PMmDEIDw9HYmIipk+fjoaGBp++r0RERERE7Ej5qMnmwMiHVoXkuXc9OhMRRv9/ZOHh4aisrIRWq8WLL76I7OxsHDp0CLfeeivuvfdevPLKKwCAuXPnwmq1Yt26dYiMjMSuXbsQFRUFAHjwwQexa9curFy5EklJSThw4ACampoAuM7cmjlzJiZPnowff/wRer0ejz/+OM4880xs375d7gitXbsW6enpWLt2LQ4cOIBLLrkE48aNww033AAAuOqqq1BRUYHvv/8eBoMB8+fPR1lZWavX8uc//xnh4eFYuXIlYmNj8frrr2PatGnYt28fEhISAAAHDhzAJ598guXLl0On06G4uBiXXXYZnn76aVxwwQWoq6vDjz/+6HOBSkRERETEQqoPkCQJ3377LVatWoXbb78dd911l3xfVlYWHn/8cdx8881yIVVQUIDZs2djzJgxAIBBgwbJ1xcUFGD8+PGYNGmS/PXCf//7XzidTrz11lvyuVtLlixBXFwcvv/+e8yYMQMAEB8fj5dffhk6nQ7Dhw/HrFmz8O233+KGG27Anj178M033+C3336Tn+Ott97CkCFD5OdZv349fv31V5SVlcFkMgEAnnnmGXz22Wf4+OOPceONNwJwjfO99957SE5OBgBs3rwZdrsdF154ITIzMwFAfo1ERERERL5gIeWjcIMOux6dGbLn9sWKFSsQFRUFm80Gp9OJyy+/HAsXLsQ333yDJ598Env27IHZbIbdbofFYkFjYyMiIiJwxx134JZbbsHq1asxffp0zJ49G2PHjgUA3HLLLZg9ezY2b96MGTNm4Pzzz8eJJ54IANi2bRsOHDiA6OjoVuuwWCw4ePCg/PmoUaOg03leS3p6Onbs2AEA2Lt3L/R6PSZMmCDfn5OTg/j4ePnzbdu2ob6+HomJia2ep6mpqdXzZGZmykUUABxzzDGYNm0axowZg5kzZ2LGjBm46KKLWj02EREREXlIkoQ/Cs0YkhqFMB/fi/Z2LKR8pNFoujVe15NOO+00vPrqqzAajejXrx/0ej3y8vJwzjnn4JZbbsE//vEPJCQkYP369bjuuutgtVoRERGB66+/HjNnzsSXX36J1atX48knn8SiRYtw++2346yzzkJ+fj6++uorrFmzBtOmTcPcuXPxzDPPoL6+HhMnTsTSpUvbrKVlQWMwGFrdp9Fo4HQ6vX5d9fX1SE9Px/fff9/mvri4OPmfIyMjW92n0+mwZs0abNiwAatXr8ZLL72E+++/H7/88guys7O9fn4iIiKivmL9gQpc+fav+NMx/fDiZeNDvRxFYdhELxYZGYmcnBwMHDgQer2r+Nu0aROcTicWLVqEE044AUOHDkVRUVGbr83IyMDNN9+M5cuX4+6778abb74p35ecnIyrr74a77//Pp5//nm88cYbAIAJEyZg//79SElJQU5OTquP2NhYr9Y8bNgw2O12bNmyRb7twIEDqK6ulj+fMGECSkpKoNfr2zxPUlJSp4+v0Whw0kkn4ZFHHsGWLVtgNBrx6aeferU2IiIior5mb0kdAODLHcUoq7OEeDXKwkKqj8nJyYHNZsNLL72EQ4cO4d///jdee+21VtfcddddWLVqFXJzc7F582asXbsWI0aMAAA89NBD+N///ocDBw5g586dWLFihXzfnDlzkJSUhPPOOw8//vgjcnNz8f333+OOO+7AkSNHvFrf8OHDMX36dNx444349ddfsWXLFtx4440IDw+X911Nnz4dkydPxvnnn4/Vq1cjLy8PGzZswP3334/ff/+9w8f+5Zdf8MQTT+D3339HQUEBli9fjvLycnn9RERERNRabZMrWdnhlLB8c2GIV6MsLKT6mGOOOQbPPvssnnrqKYwePRpLly7Fk08+2eoah8OBuXPnYsSIETjzzDMxdOhQOYjCaDRiwYIFGDt2LKZOnQqdTocPP/wQABAREYF169Zh4MCBuPDCCzFixAhcd911sFgsiImJ8XqN7733HlJTUzF16lRccMEFuOGGGxAdHS1HmGs0Gnz11VeYOnUqrr32WgwdOhSXXnop8vPzkZqa2uHjxsTEYN26dTj77LMxdOhQPPDAA1i0aBHOOussX7+NRERERH1CTaPniJqPfjvMtOMWNBK/GzCbzYiNjUVtbW2bN/wWiwW5ubmtziKinnXkyBFkZGTgm2++wbRp03r0ufnzJyIior7s9v9swRfbPNtAlt08GcdmJYRwRcHXWW3QkjpSE6hP+e6771BfX48xY8aguLgY9957L7KysjB16tRQL42IiIioTxGjfdFhetRZ7Pjvb4d7fSHlLY72keLYbDb8/e9/x6hRo3DBBRcgOTlZPpyXiIiIiHpObaMVADDneNcZnF9uL0adxdbZl/QZ7EiR4sycORMzZ4bmrC4iIiIi8hAdqWkjUrB6VwkOlTdgxfZiXHbcwBCvLPTYkSIiIiIionbVuAupuHADLpmUAQD472+HQ7kkxWAh5SVmcvRN/LkTERFRX+V0SnJHKjbcgAsnDIBeq8HWwzXYV1oX4tWFHgupLuh0OgCA1WoN8UooFBobGwGA+7OIiIioz6lrtkP8TTkm3IDkaBNOH54CgF0pgHukuqTX6xEREYHy8nIYDAZotaw9+wJJktDY2IiysjLExcXJBTURERFRX1HrPkMq3KBDmMH1XuiSYzOwelcpPt1SiL+dORxGfd99b8xCqgsajQbp6enIzc1Ffn5+qJdDPSwuLg5paWmhXgYRERFRj6tpck1kxYZ7JnNOGZqMlGgTyuqa8c3uUpw9Jj1Uyws5FlJeMBqNGDJkCMf7+hiDwcBOFBEREfVZYn9UXISnkNLrtLho4gC88v1BrNhexEKKuqbVahEWFhbqZRARERER9YiaRk/QREtjB8QCAErNzT2+JiUJ+VBjYWEhrrjiCiQmJiI8PBxjxozB77//Lt8vSRIeeughpKenIzw8HNOnT8f+/ftbPUZVVRXmzJmDmJgYxMXF4brrrkN9fX1PvxQiIiIiol6jZWJfSzFhrs/NTX37YN6QFlLV1dU46aSTYDAYsHLlSuzatQuLFi1CfHy8fM3TTz+NF198Ea+99hp++eUXREZGYubMmbBYLPI1c+bMwc6dO7FmzRqsWLEC69atw4033hiKl0RERERE1Cu0N9oHuBL8AMBs6duFVEhH+5566ilkZGRgyZIl8m3Z2dnyP0uShOeffx4PPPAAzjvvPADAe++9h9TUVHz22We49NJLsXv3bnz99df47bffMGnSJADASy+9hLPPPhvPPPMM+vXr17MvioiIiIioF6hpdOUDxEUYW93u6UjZe3xNShLSjtTnn3+OSZMm4c9//jNSUlIwfvx4vPnmm/L9ubm5KCkpwfTp0+XbYmNjcfzxx2Pjxo0AgI0bNyIuLk4uogBg+vTp0Gq1+OWXX9p93ubmZpjN5lYfRERERETk0eFoX7irF9Nkc8Bqd/b4upQipIXUoUOH8Oqrr2LIkCFYtWoVbrnlFtxxxx149913AQAlJSUAgNTU1FZfl5qaKt9XUlKClJSUVvfr9XokJCTI1xztySefRGxsrPyRkZER6JdGRERERKRqHYVNRId5Pq/rw+N9IS2knE4nJkyYgCeeeALjx4/HjTfeiBtuuAGvvfZaUJ93wYIFqK2tlT8OH+bJzERERERELdV00JHSaTWINrm6UrV9OHAipIVUeno6Ro4c2eq2ESNGoKCgAADkg1BLS0tbXVNaWirfl5aWhrKyslb32+12VFVVdXiQqslkQkxMTKsPIiIiIiLyMHcQNgG0DJzou/ukQlpInXTSSdi7d2+r2/bt24fMzEwAruCJtLQ0fPvtt/L9ZrMZv/zyCyZPngwAmDx5MmpqarBp0yb5mu+++w5OpxPHH398D7wKIiIiIqLeR4z2xYUb29wXHebqSPXlCPSQpvbNmzcPJ554Ip544glcfPHF+PXXX/HGG2/gjTfeAABoNBrcddddePzxxzFkyBBkZ2fjwQcfRL9+/XD++ecDcHWwzjzzTHkk0Gaz4bbbbsOll17KxD4iIiIiIj91FDYBMAIdCHEhdeyxx+LTTz/FggUL8OijjyI7OxvPP/885syZI19z7733oqGhATfeeCNqamowZcoUfP311wgLC5OvWbp0KW677TZMmzYNWq0Ws2fPxosvvhiKl0REREREpHoWmwNNNgcAILa90T5GoIe2kAKAc845B+ecc06H92s0Gjz66KN49NFHO7wmISEBH3zwQTCWR0RERETU54iRPa0GcrBES7HsSIV2jxQRERERESmPGOuLCTdAq9W0uV+cJcXUPiIiIiIiIjcRfR7Xzv4ooOVoHwspIiIiIiIiAC0O441om9gHMP4cYCFFRERERERH6SyxDwBiGH/OQoqIiIiIiFqrabQC6Hi0j2ETLKSIiIiIiOgootMU1070OdBitI8dKSIiIiIiIpeaLkf7XLfX9uFzpFhIERERERFRK3LYREeFlDv+nKN9REREREREbl2GTbhvt9qdsNgcPbYuJWEhRURERERErcjnSHUQfx5l1EPjPqe3r3alWEgREREREVErtSK1r4OwCa1W0+JQ3r65T4qFFBERERERtdLVaB/AfVIspIiIiIiISOZ0SnIh1dE5UkDL5D4WUkRERERE1MfVW+1wSq5/jvGikOqrZ0mxkCIiIiIiIlmtO/o8zKBFmEHX4XWe0T7ukSIiIiIioj5OnCEVF95+Yp/AjhQREREREZGbvD+qg8Q+QQRRMGyCiIiIiIj6vJomV/R5Z/ujWt7P+HMiIiIiIurzPKN9XRRSYe49UhztIyIiIiKivs6bM6SAFh0pjvYREREREVFf5+0eKYZNEBERERERuYn487iILlL75I4U90gREREREVEf523YhJzax44UERERERH1dV6HTcgH8togSVLQ16U0LKSIiIiIiLpJkiQUVDb2ioLC1z1SNoeEJpsj6OtSGhZSRERERETd9MgXuzD1X2uxamdJqJfSbd6m9kUYddBpNQD65llSLKSIiIiIiLphd7EZ723MAwDsKjKHdjEB4Bnt6zxsQqPReM6S6oMR6CykiIiIiIj8JEkS/vHlbjjdE321Kg9eaLY75DG92C5G+4AWyX0qf93+YCFFREREROSntXvLsP5Ahfy52qPARSGo0QDRJn2X18f24UN5WUgREREREfnB5nDiH1/uBgD0jwsHoP6OlLnF/iite/9TZzyH8qq7gPQHCykiIiIiIj/859cCHCxvQEKkEXdOHwJA/SNuYn9UV0ETgohAV3sB6Q8WUkREREREPqptsuG5NfsAAPPOGIoBvaQj5e0ZUoKnI6Xu1+0PFlJERERERD5avPYAqhttyEmJwmXHZnhCF1S+V0iOPo/oPLFP6C2v2x8spIiIiIiIfJBf2YB3fsoDANw/awT0Oq08Cqf6jpSXZ0gJctgE90gREREREVFn/m99LqwOJ04ekoRThyYD8HRmLDYnmu2OUC6vW2obrQB8Ge3jOVJEREREROSFw9VNAIBZY9Kh0biS7aJNerj/UdXdGdFRi/PiDCmAo31EREREROSlqgZX1yYh0rOPSKvVyOcuqXm8z9fRPhE2oebX7C8WUkREREREPqhubFtIAb2jO1PrayHljj9XcxfOXyykiIiIiIh8IDpS8UcVUr0hcEKOP/c2tS9M/cWjv1hIERERERF5yWp3os7i6r4kHt2R6gVnKvnakfKk9tkgSVLQ1qVELKSIiIiIiLxU4x7r02o8hZPQsqhQK3/DJpwS0GBVb1qhP1hIERERERF5qcpdSMVHGKHValrdJ+8Xsqhzv5DTKcmForcdKZNeC6POVVKouYD0BwspIiIiIiIvdbQ/ClD/Hql6qx1O93Set4WURqORC0i1vm5/sZAiIiIiIvJSdYOrWEhoJ4xB7Xukat1BE2EGLcIMOq+/Tu2v218spIiIiIiIvFTV0AwAiI9s27GJjVB3R8rXoAkhWo59V+dIo79YSBERERERealKdKQiTW3uU3sUuDy26GX0udAbQjb8wUKKiIiIiMhLnsN42+lIqXyPVFmdq9uWHN22SOxMTJgI2VDn6/YXCykiIiIiIi911rWRU/ua1DniVlZnAQCkRIf59HUxckdKna/bXyykiIiIiIi85OlI9b7UvjKzqyOVEuNrR0rdr9tfLKSIiIiIiLzUWfy5KCjqLDY4RY64ing6Uj4WUuEc7SMiIiIiok6IQqrd+HN3R8opuc5kUhvRkUqN8XG0j/HnRERERETUEUmSPIVUOx2pMIMORr3r7bUaiwoRNuFrR0pO7WNHioiIiIiIjtZkc6DZ7gTQfiEFqHeflCRJDJvwEQspIiIiIiIviG6UUa9FhFHX7jVyFLjKioq6ZjssNleR6HvYBPdIERERERFRB6rFYbwRRmg0mnavUWtHSuyPig7TI8zQfpHYkRiVvubuYiFFREREROSFqsaOE/uEGJXuFyoz+5fYB3jCJuqb7apMK/QXCykiIiIiIi9UNbi6NomdFFJy8ILKujMiaMLXxD7AE38uSa4Rwb6ChRQRERERkReq3KN9nXakVBoF7u8ZUgBg0usQZlBvWqG/WEgREREREXmhWj5DytDhNWrfI5XiR0cKaFFAqmyksTtYSBERERERecG7PVIiwU5dI27+niEl9MUIdBZSREREREReqO7kMF5BtR0p92hfsr+FlDsCXW2vuztYSBEREREReaHSXUjFR/TGPVKiI+XnaJ9K0wq7g4UUEREREZEXREfKm9Q+tXVmPHuk/OtIqTWtsDtYSBEREREReaG6l54j1Wi1o94dW+5P/DnQMmyCe6SIiIiIiMjN6ZRQ3egqjnrbHinRjYow6hBl0vv1GHLIhoped3exkCIiIiIi6kKdxQ6HUwIAxHUSfy46MxabE812R4+srbu6m9gHMP6ciIiIiIjaIaLPo0x6mPS6Dq+LDtNDo3H9s1qiwD2H8fo31ge0jD9nIUVERERERG5VDa6uTXxkx90oANBqNfJ4nFq6M2K0L9nPoAnAM+5Y7u5u9QUspIiIiIgoKCrrm7FiexGc7pE4NatqEPujui421LZPqlTuSPlfSA2IDwcAHKluCsia1ICFFBEREREFxc3vb8JtH2zBt3vKQr2UbpMP4+1kf5SgtrOkys3dO0MKAAbERwBwnbXV0KyOkcbuCmkhtXDhQmg0mlYfw4cPl++3WCyYO3cuEhMTERUVhdmzZ6O0tLTVYxQUFGDWrFmIiIhASkoK7rnnHtjtfeOHR0RERKRUWwqq8VteNQDgSHVjiFfTfVVeRJ8LautIibCJ1G6M9sWGGxAT5hppLKzpG12pkHekRo0aheLiYvlj/fr18n3z5s3DF198gWXLluGHH35AUVERLrzwQvl+h8OBWbNmwWq1YsOGDXj33Xfxzjvv4KGHHgrFSyEiIiIit7fX58r/rJbQhc54OlJdF1JyFLhKzlQKRNgEAGQkuLpSh6vUXzh7w7+g+EAuQK9HWlpam9tra2vx9ttv44MPPsDpp58OAFiyZAlGjBiBn3/+GSeccAJWr16NXbt24ZtvvkFqairGjRuHxx57DH/729+wcOFCGI1d/6ITERERUWAV1jRh5R8l8ud1Kgld6Exlg+8dKbWM9snx593oSAGufVI7i8x9Zp9UyDtS+/fvR79+/TBo0CDMmTMHBQUFAIBNmzbBZrNh+vTp8rXDhw/HwIEDsXHjRgDAxo0bMWbMGKSmpsrXzJw5E2azGTt37uzwOZubm2E2m1t9EBEREVFgvLchTz5zCVBPel1nREcq0YtCSuyRUsNoX7PdgRr3QcPdCZsAgIz4vtWRCmkhdfzxx+Odd97B119/jVdffRW5ubk4+eSTUVdXh5KSEhiNRsTFxbX6mtTUVJSUuP7CUVJS0qqIEveL+zry5JNPIjY2Vv7IyMgI7AsjIiIi6qMamu344FfXH8ZPHZYMoHeM9vmzR0oNHSkRV27Ua+V1+0se7esFe+K8EdLRvrPOOkv+57Fjx+L4449HZmYmPvroI4SHhwfteRcsWID58+fLn5vNZhZTRERERAGw7PfDqLPYMSgpEueN64fv95ajrln5BUVX5D1S3nSkVBQ2USrOkIoyQSNOEvZTX4tAD/loX0txcXEYOnQoDhw4gLS0NFitVtTU1LS6prS0VN5TlZaW1ibFT3ze3r4rwWQyISYmptUHEREREXWPwylhyYY8AMC1J2UhLtxVdPSKjpTYI+VF2ITckVLBSGO5CJro5v4ooO+FTSiqkKqvr8fBgweRnp6OiRMnwmAw4Ntvv5Xv37t3LwoKCjB58mQAwOTJk7Fjxw6UlXnOJlizZg1iYmIwcuTIHl8/ERERUV/27e5S5Fc2IjbcgNkTByA6TKTXKb+g6IzN4ZQT+LzrSLletxo6UnL0eTcT+wBPR8pssavitXdXSAupv/71r/jhhx+Ql5eHDRs24IILLoBOp8Nll12G2NhYXHfddZg/fz7Wrl2LTZs24dprr8XkyZNxwgknAABmzJiBkSNH4sorr8S2bduwatUqPPDAA5g7dy5Mpu5X1URERETkPRF5ftlxAxFh1MsjbmrYK9SZavf+KI0GXu0j8uyRUn4nrswcmMQ+AIgw6uUwjt5wdlhXQrpH6siRI7jssstQWVmJ5ORkTJkyBT///DOSk10bE5977jlotVrMnj0bzc3NmDlzJl555RX563U6HVasWIFbbrkFkydPRmRkJK6++mo8+uijoXpJRERERH3SH4W1+CW3CnqtBlefmAnAk15XZ7FDkqRu78EJleoGVyEYH2GETtv1a1BTap/nDKnANCEGJESgssGKw1VNGNUvNiCPqVQhLaQ+/PDDTu8PCwvD4sWLsXjx4g6vyczMxFdffRXopRERERGRD/69MR8AMGtsOtJjXSNeYsTN7pTQZHMgwhjyI0z94tkf5V2qnehI1VlscDolaL0ovkJFPkMqAKN9gGu8b9vhmj7RkVLUHikiIiIiUqddxa5zOWeNSZdvCzfo5A6OGsbcOiJG+7zZHwV4UvucElBvVfbrFqN9yQEY7QM8Z0n1heQ+FlJERERE1G3Fta4RsX5xniNsNBoNYtyBE3UqDpzwJbEPAMIMOhj1rrfZSt8fFujRvowE18+/LyT3sZAiIiIiom6xOZyobHB1NtJiW4+IxagoCrwjvpwhJahhn5Td4USl+7WlxgRqtI8dKSIiIiIir5TVNUOSAINOg4SjujZyBLqKR/tEsRHvQyEVG678111Rb4UkAXpt25+bvzLcEeiHqxshSVJAHlOpWEgRERERUbeU1Lq6D6kxYW2CFURnRtUdKfceqURfOlLhyu9IibG+pChTwAIx+rsLqUarQx6J7K1YSBERERFRt5TUusf62hkP8xRSyu3MdMXXPVJAi7OkFFxABvIMKcGk1yHV/Xi9fbyPhRQRERERdUuJ2dXZSI1tW0h5RvuUW1B0xdfUPqBFAang1+2JPg9cIQV4kvsO9/IIdBZSRERERNQtYrQvvb2OlAo6M12RD+T1aY+U8gupUncBnBygM6SEjAR3IVXFjhQRERERUYdKzO0n9gGezkydikf7RCKhL4EM4jBiZe+RCk5HaoB7n1RvP5SXhRQRERERdUvLsImjqX20r8nqgMXmBADERxq8/jrPHinlFpDl7rCJQEWfC57RPnakiIiIiIg6JPZIpbfXkVJBQdGZKvf+KKNOiyiT3uuvU8M5UuxIdQ8LKSIiIiLymyRJKHWn9rXX2Yhxd6TqVLpHqlo+Q8oAjcb7iHA17JEKRmof4NkjdaS6CU5n7z1LioUUEREREfmtqsEKq8M1+tb+aJ/yC4rO+BN9Dij/HCmnU0JFvehIBXa0Lz02DDqtBla7E+Xu5+iNWEgRERERkd/EWF9SlBFGfdu3liJ0Qa2jff5EnwPKP0eqqtEKu1OCRuP62QWSXqeVzxTrzeN9LKSIiIiIyG8iQrujwAJPap8yC4quVNaL0T4fO1IK3yMlfm6JkUbodYEvCTISXPukenMEOgspIiIiIvJbcW3HQROAp6Cw2Jxotjt6bF2BIsbfEv3sSCn1dX+zqwyAZz9ToMnJfVXsSBERERERtVFa23lHKirMk3SnxrOkimpcHZV+ceE+fV3L121uUtbrLq9rxuvrDgIArpuSHZTnGBDvCZzorVhIEREREZHfREcqrYNCSqfVINqk3rOkCt2FVH8fCymdVuM5Q0thY40vfrsfjVYHjhkQi1lj0oPyHPJoXy/eI+V9GD4RERERdUt+ZQO+/qMEFpsTt52eA53W+zhtpRJhE2kdjPYBrgS7uma7SjtSrtfna0cKcI011lnsitondai8Hv/5tQAAcN9ZI3yKdPdFX+hIsZAiIiIiChJJkrC/rB4rd5Rg5R/F2FNSJ983bmAcThmaHMLVBUapF4WUUjszXbE7nHKhKA6Z9UVsuAGFNU2K6sT9a9Ve2J0STh+egsmDE4P2PKIjVVTTBIdT6hV/NDgaCykiIiKiIFn4+U68uzFf/lyn1SDcoEN9sx2FveQv9V2N9gGewAml7RXqSmldMxxOCQadBslRvh9aK6LfldKR2lxQjZV/lECrAf525vCgPldqdBgMOg1sDgnFtU1yh6o34R4pIiIioiBZ+UcJAODkIUl4+qKx+P3+6Tj3GNeelLI6SyiXFhCNVs+4Xuejfa6CQm0R6CJoIj02HFo/Oiqes6RCX0BKkoQnv9oNAJg9YQCGpUUH9fm0Wo28r6y3jvexkCIiIiIKgkarHWV1rujsly4bj4snZSA+0ojkaFfBIe5TsxJ3NyrSqEO0u+vUHnGf2kb7RNewX1zHRWJnRCFV6z7UN5S+2V2G3/KqYdJrMX/G0B55ThGt3lsj0FlIEREREQVBgfvNY2y4AXERnjOIUqJdI2JlZvV3pEQh1Vk3CgBixB4plY32eRL7/BtLS3b/rEvNoS2anU4JT329BwDwlynZSI/1fb+XP8Q432F2pIiIiIjIW3kVrkIqM7H1m3Bx3lKv6Eh5ETQBuFL7APWN9nkKKf86UmnugqUkxEXzwfJ6HCirR7hBh5tPGdxjzyu+b8U1LKSIiIiIyEv5lQ0AgMzEyFa3ezpSvaeQ6ugwXsGT2qeujpTYI9Xfj8Q+wBPAITp3oXKowvW7mJMSJY8b9oQkd0BHZUPoRxuDgYUUERERURDku0f7so7qSKXEuN5cVtQ3w+mUenxdgSQKhPQuR/tEap/KOlLyHqluFlIh7kjlugup7KTILq4MLLmQqlf/Hw3a43Mh1dTUhMZGz4ax/Px8PP/881i9enVAF0ZERESkZqIjNTChdSGVFGWCRgPYnRKqFBBC0B0lXkSfA57RPjWFTUiS5OlI+VtIuQvMivpm2BzOgK3NV7nloSmkEqNcewMr6tX9e94Rnwup8847D++99x4AoKamBscffzwWLVqE8847D6+++mrAF0hERESkRmKPVNZRb14NOi0S3OETah/v83W0r05Fo321TTY0WB0A/O9IJUYaYdBpIEmh3ROX6y7qByWHpiNVUd8MSVJ397U9PhdSmzdvxsknnwwA+Pjjj5Gamor8/Hy89957ePHFFwO+QCIiIiK1abY7UFzr6mYcHTYBeNLc1H6WlGe0r/NCQ42jfSJoIinKiDCDzq/H0Go1SIkO/T4pMdqXlRiajlSz3SkXpb2Jz4VUY2MjoqNdB3itXr0aF154IbRaLU444QTk5+d38dVEREREvd+R6iY4JSDCqEOy+6/yLcnJfSruSNkcTpS7976kxrZ9jS3FKOhgWm91d3+UIMb7SkO0T6rOYkO5uxt2dHc02CKMekQYXUVob9wn5XMhlZOTg88++wyHDx/GqlWrMGPGDABAWVkZYmJiAr5AIiIiIrUpqHSN9Q1MiIBGo2lzf0ov6EiV1zVDkgC9VoOkyM4LKTHaV99sh0MlARvd3R8liP1jxSHqSIkR06QoY48m9gmefVIspPDQQw/hr3/9K7KysnD88cdj8uTJAFzdqfHjxwd8gURERERqk1fZ+SiVSO5T81lSLfdHabVti8WWRCEFAPUq6UqJ0T61d6Ryu/hdDDbPPqneFzih7/qS1i666CJMmTIFxcXFOOaYY+Tbp02bhgsuuCCgiyMiIiJSo/zK9g/jFcS+GTWP9pXWikKq824UAJj0OoQZtLDYnDBbbIiN6PnOiK+KalyvT+0dqVAl9gmJkSICvY8XUjabDeHh4di6dWub7tNxxx0X0IURERERqVVHh/EKvWG0r9jLoAkhOswAi61ZNRHoRwLdkQpVIVVRDwDI7uHEPiGJo30uBoMBAwcOhMPR+1I3iIiIiAJFdKSOPoxX6A2jfaVeRp8LMe7xPnOTOkb7xB6pAfGBKaRCdShvrvt3cVCIOlK9+VBen/dI3X///fj73/+OqqqqYKyHiIiISNUcTgmHq91hE12N9tWp93wd0ZFK6yKxT1DTobzNdoecdNftjlSMp5Dq6Z+1JEnILXd1pHo6sU+QwyYa+vhoHwC8/PLLOHDgAPr164fMzExERrb+oWzevDlgiyMiIiJSm6KaJtgcEow6bYdjb+IcKavdidomG+LcB/SqieiwpHk52qems6SK3fujwg06xHdzP5foPlrtTlQ32pAQ2XM/66oGqxw5H6qwiUQRNqHi7mtHfC6kzj///CAsg4iIiKh3EGN9GQnh0HWQZhdm0CE23IDaJhvK6ppVWUiJ0b40L0f7RHJfnQpS+4rk/VFh7cbX+8Kk1yEx0ojKBitKai09WkiJg3j7x4X7fahwd4k9UpXsSAEPP/xwMNZBRERE1Ct0FX0upESbXIWUuRlDU6N7YmkBI0mSZ7TP2z1SKhrtE0ET/ePbH830VVpsmKuQMjdhZL+eO3dVFFKhSuwDuEeqjZqaGrz11ltYsGCBvFdq8+bNKCwsDOjiiIiIiNSmoKrz/VGCJ3BCfcl9NY02WO1OAJ7X0RXPaJ96OlL947wrErsi75Oq7dliQhRSWUmBKQj9kejuwFU32mBzOEO2jmDwuSO1fft2TJ8+HbGxscjLy8MNN9yAhIQELF++HAUFBXjvvfeCsU4iIiIiVcir8LYj5QmcUBuxPyoh0uj1yJhntE/5HanCalFIdS9oQkgVyX21TQF5PG95OlJRPfq8LcVFGKHVAE4JqG6wIsXLDqYa+NyRmj9/Pq655hrs378fYWGeb8TZZ5+NdevWBXRxRERERGrT1WG8gnyWlAoP5S3xcawPUNdoX1FtYM6QEtJjQhOBLgqpUEWfA4BOq0GC+1Deil52KK/PhdRvv/2Gm266qc3t/fv3R0lJSUAWRURERKRGkiQhv6rzw3gF8Zd5NY72eRL7fCikVHSOVNA6Uj1YNDudkme/XggLKaD3HsrrcyFlMplgNpvb3L5v3z4kJycHZFFEREREalRW1wyLzQmdVtPlm3C5I6XC0T4RNOHtYbyAZ49UXbOyO1JOp4Qi9+sLWEcqBKN9JWYLLDYn9FpNtw8V7q5EOblPfb/rnfG5kPrTn/6ERx99FDab618CjUaDgoIC/O1vf8Ps2bMDvkAiIiIitchrETdt1Hf+Nssz2qe+jlR5nSikvAuaAICYcHV0pCoammG1O6HV+NZx64wnbKLnftZirG9gQgQMOr/y5QLGk9zXx0f7Fi1ahPr6eqSkpKCpqQmnnHIKcnJyEB0djX/84x/BWCMRERGRKuRXebc/Cmg52qe+v9KLvS7iYGFvyKl9Ct8jVVTj6bYFqgARo31mix2N1p4pJA8pIPpcSHTvkSrvYLRvV5EZP+4vV92Yq8+pfbGxsVizZg3Wr1+P7du3o76+HhMmTMD06dODsT4iIiIi1civFPujvCik3EVIo9WB+mY7okw+vy0LGXEmkHiD7I1oMdpnsUOSpG4fdBssYn9UoMb6ACDapEekUYcGqwMltRYMSg5+ip6cHqmEQkqM9nXQkVr6Sz6W/lKAuacNxj0zh/fk0rrF739jp0yZgilTpgRyLURERESqludO7Osq+hwAIlu8uS4zWxDVA2+uA6WywfWGWIQIeEOM9jmcEhqtDkQqtHD0nCEVuEJKo9EgNTYMh8obUGLumUJKCYfxCsldHMqb78O/N0ri82/wiy++2O7tGo0GYWFhyMnJwdSpU6HTeXemABEREVFvUeB+QzgwwbsDUFNjwnCoogFldc098uY6UERnITHK+45UuEEHvVYDu1OC2WJTbCFVWBP4jhTgCpw4VN7QY/uklBB9LiTKqX3td6SUVPT5wuff4Oeeew7l5eVobGxEfHw8AKC6uhoRERGIiopCWVkZBg0ahLVr1yIjIyPgCyYiIiJSIknyPW46OdokF1JqYbG5RhEBzxtkb2g0GkSH6VHdaIO5yY702GCtsHtEIdU/wEl3qT14lpTN4cRh93697OTQFyeJnXSkmu0O+dyuro4MUBqfd9A98cQTOPbYY7F//35UVlaisrIS+/btw/HHH48XXngBBQUFSEtLw7x584KxXiIiIiJFqm60oc7iKjC87UjJgRMqSu4TY31GnRbRPnaVxKG8dQoOnPCcIRWYxD5BJPeV9kBH6kh1E+xOCWEGLVKjA/s6/CGfI9VghSRJre47XNUISQKiTHqfRkWVwOeO1AMPPIBPPvkEgwcPlm/LycnBM888g9mzZ+PQoUN4+umnGYVOREREfYoImkiLCUOYwbstDmo8S0oOmogy+hwYoYbkPtEd6R/nXTHsLXGWVHEPFFK5FfUAXHuOtNrQh3qIUBKr3Ym6Zrv8ewAAeRWepEulBpB0xOeOVHFxMez2trGNdrsdJSUlAIB+/fqhrq6u+6sjIiIiUgmxYd6bxD5BjWdJefZH+d49iA5T9llSDc121DS6irx+Ae5IidG+0h74WR8qd++PUsBYHwCEG3WINLr+uHB0cp+v47BK4nMhddppp+Gmm27Cli1b5Nu2bNmCW265BaeffjoAYMeOHcjOzg7cKomIiIgUTn5D6MM+j5QY9XWkKvyIPhdiwpQ92icS+2LC9HJce6Ckx7r2XPXEHil/fheDLSm6/X1SnrUGtgPYE3wupN5++20kJCRg4sSJMJlMMJlMmDRpEhISEvD2228DAKKiorBo0aKAL5aIiIhIqeTEPh/eEIr9K2oqpMQeKX86UiIC3WxRZkcqWIl9AJAa6z6Utq4Zdocz4I/fkhJT8BIjRXLfUYVUhTqjzwE/9kilpaVhzZo12LNnD/bt2wcAGDZsGIYNGyZfc9pppwVuhUREREQqIDoNvoyEyR0pVY32ud4IJ/kQfS7Ie6SalNmREoXUgAAn9gFAUqRJjn8vr2+WO1TBkKuw0T7Ak9x3dAS6mkf7/A7wHz58OIYPV8/Jw0RERETBVO7uKqX4kJKW7L7WbLHDYnN4HVIRSvIeqUh/9kiJsAlldqREARLIw3gFrVaD1JgwFNY0objWErRCqsnqQJE70CI7STlnk4lEvpZ7pJrtDnmcsk90pBwOB9555x18++23KCsrg9PZujX53XffBWxxRERERGpR4UenJiZMD5Nei2a7E+V1zcjwMjY9lCoafD+MV/CM9imzI/VrXhUAYEJmfFAePzXGhMKaJr8j0B1OV3S4rpMkvgNlrsS+uAgD4iMCu8+rO5LkjpRntO9wVROcEhBp1Kku+hzwo5C688478c4772DWrFkYPXq06mIKiYiIiALNanei2p32lhztfYGh0WiQEmPC4aomlJotqiikWsaf+0rJo31miw1/FNYCAI7PTgzKc7i6UDV+BU5IkoRb3t+EX3KrsOquqUiLbb/zue1IDQBgTP9YRb1PFx3MygZPIZVX4RnrU9JaveVzIfXhhx/io48+wtlnnx2M9RARERGpjnhzqNdqEBfuWxcgJToMh6uaVBM4IUazkvxI7ZPjzxU42vd7XhWckiugoaMipbtEBHqJHx2pH/dXYPWuUgDAd3vKcPnxA9u9bru7kBo7INa/RQZJe3uklJgu6AufU/uMRiNycnKCsRYiIiIiVaqo8yTZ+XoAqprOkpIkSS4a/UvtU278+c+HXGN9x2cnBO050tzJfb52pCRJwqLVe+XPf3OPILZn+xFXV23sgDjfFxhE7Y32eYImlN+JbY/PhdTdd9+NF154AZIkBWM9RERE1Mu9/N1+XP/u76hV4HiXv8rrXW+MfRnrE0SXQg0dKbPFDpvD9R4wwY+wCc9on/I6Uj8fqgQAnDAoOGN9AJAmzpLysSP1ze4ybHMXSADwa277hVSj1Y59pXUAgGMUV0i1DZvwHGKtzo6Uz6N969evx9q1a7Fy5UqMGjUKBkPr9vXy5csDtjgiIiLqXZxOCS99dwDNdifu/mgr3rhyks8dHCUSiX3JfgQwiOJLDYWU2B8VbdL7lTDoGe1TVhHdan/UoCB2pMRonw8dKafT0426enIm/v1zPgprmlBU09TmvKudRWY4JVeXM1jjif4So321TTZY7U4Y9VpFnnflC587UnFxcbjgggtwyimnICkpCbGxsa0+iIiIiDpSWNOEZrsr8feb3WV4bd3BEK8oMMS+D3/OVkpRUyHVjcN4Ac9on9XuhMXmCNi6ukvsj8pKjAjq+U7psZ49Ut5Od331RzH2lNQh2qTHvDOGYlQ/1/vt9sb7th2uAaC8sT4AiAs3yGmDVQ3WVtHnmT4cYq0kPneklixZEox1EBERUR9wyP0XaKNeC6vdiWdW7cW4AXE4MScpxCvrHrkj5cdoX4oY7VPBHilPYp/vrxNwdbI0GkCSgDqLXTHnZon9UcEc6wM8BzA3252oabQhvovxSLvDiWfX7AMAXH/yIMRFGHFsVgJ2FNbi19wqnDeuf6vrxf6oYxQWNAG4ztFKiDSivK4ZFfXNqG+2y9Hn/nRylcDnjhQA2O12fPPNN3j99ddRV+eawywqKkJ9fX1AF0dERES9y0H3GTenDUvGnycOgFMCbv/PFr9SzJSkvL4bhZSKOlIV3TiMF3C9mY4yKm+8ryf2RwGASa+T95Z5M973v61FOFTegLgIA/4yJQsAcFy264yr9jpSO9zjiWMz4gKz4ADzRKBbke8OmshMVGf0OeBHIZWfn48xY8bgvPPOw9y5c1FeXg4AeOqpp/DXv/414AskIiKi3uNQhauQGpQchcfOH42R6TGobLDi1qWbYHWP/KmR6Eh1Z7SvqsGq+O+BCArwtyMFtEzu69nAiaoGa7vjdD21P0pI8zIC3eZw4vlvXd2om08ZjGh3UMekLNca95XWo6bRE9xQ22ST9xyN7a+8jhTg+UNDZX2z6vdHAX4UUnfeeScmTZqE6upqhId7ZkgvuOACfPvttwFdHBEREfUuh8pdb54GJ0chzKDDa1dMREyYHpsLavDkyt0hXp3/Krox2hcfYYRB5/qLfMtoaCUS0edJfu6RAloETvRgauOm/CpMeGwN7v14e9v78qp7ZH+UIAIijrj3B3Vk2e9HcLiqCUlRJlw1OVO+PSnKhEHJruLj97xq+fYd7rG+gQkRXY4MhoroSFXUN7dI7FPn/ijAj0Lqxx9/xAMPPACjsfUPKCsrC4WFhQFbGBEREfU+opASbwQHJkbg2YvHAQCW/JQn/5VabcRonz8dKa1WI+8RUfp4X2U3R/uAFhHoPTjatzm/BgCwbNMR/LCvvNV9Yqzv+OzgjvUJonAoqOz8d33JT7kAgFtPHYwIY+tYg+PcXamW433bFHoQb0uik1lZb21xhlQf6kg5nU44HG1TVo4cOYLo6Gi/F/LPf/4TGo0Gd911l3ybxWLB3LlzkZiYiKioKMyePRulpaWtvq6goACzZs1CREQEUlJScM8998BuV97ZBERERH1dfbNd3hcyOClKvn36yFSMcY8iHShT335ri80hj6n505ECgGT3uFepwgMnyrsZNgEAsRGuQqq6wdrFlYFT0eApUB/87I9WiYHy/qjBwR/rAzyFVJ67I9Mem8Mp/1Hh7DHpbe4/1l1I/dqikNruLqSUdn5USyLtsaJlIaXSM6QAPwqpGTNm4Pnnn5c/12g0qK+vx8MPP4yzzz7br0X89ttveP311zF27NhWt8+bNw9ffPEFli1bhh9++AFFRUW48MIL5fsdDgdmzZoFq9WKDRs24N1338U777yDhx56yK91EBERUfDkurtRSVFG+c20MCDePe5U3fGbS6US+6OMei1iwnwORAYApLnT3JSe3OdJ7fO/I9VfjLZVdz7aFkgVdZ6iraCqEYvXHgAA1FlsckBDT3WkBiaIjlTHv+tFNU2wOyWY9Fp5D11Lx2W7CqkdR2rRZHUVhSKxT8kdKdGxLa5tQqH755+V1IdG+xYtWoSffvoJI0eOhMViweWXXy6P9T311FM+L6C+vh5z5szBm2++ifj4ePn22tpavP3223j22Wdx+umnY+LEiViyZAk2bNiAn3/+GQCwevVq7Nq1C++//z7GjRuHs846C4899hgWL14Mq7Xn/spBREREXZODJlp0owRRSBX24JvrQBH7mpKjTH6nj/lzUGsoiHOk/BlhFORCoqrnimaxt2v6iBQAwGs/HMSBsnr87t4flZkY0eZw22DJdHdgCqoaOzxLKq/F/qH2DqweEB+OtJgw2J0SthyuRlmdBcW1Fmg1wGiFBk0Anr1124/Uqj76HPCjkBowYAC2bduG+++/H/PmzcP48ePxz3/+E1u2bEFKSorPC5g7dy5mzZqF6dOnt7p906ZNsNlsrW4fPnw4Bg4ciI0bNwIANm7ciDFjxiA1NVW+ZubMmTCbzdi5c2eHz9nc3Ayz2dzqg4iIiIJLRJ+L/VEtiS5FYRcb8JVITuzzc6wP8JwlVVKr3D1SNofr7COge3ukQlFIiWL38uMHYtrwFNgcEu7/dAc2irG+HupGAa7fdZ1WgyabQ/7dOVpBi2jw9mg0Ghzr7kr9lluN7Ydd3aiclChEmvzrivaExEjXvyP1za5RWDVHnwN+HMgLAHq9HnPmzMGcOXO69eQffvghNm/ejN9++63NfSUlJTAajYiLi2t1e2pqKkpKSuRrWhZR4n5xX0eefPJJPPLII91aOxEREfnmYIUnse9oA+Jdb657ctwrUMpbdKT8laaCPVJiT5NWA8RFdKOQSvSMtkmS1CNvpEVIRlKUCQv/NAo/HazAL7lV8jhcT+2PAlwjoP3iwnC4qgl5lY1yEd2S3JFK6Hjs7biseHyxrQi/5VXB4XTF5o9V8P4ooO0fG9Q81gf40ZF699138eWXX8qf33vvvYiLi8OJJ56I/Px8rx/n8OHDuPPOO7F06VKEhbX9BQqmBQsWoLa2Vv44fPhwjz4/ERFRX3R0Yl9L/ePV25ES+2+So/0vLtJilT/aJw7jTYg0QtfOuJm3MtxFc12zHbU9EIEuSVKr868yEiJw57ShAIAmd+hET+2PEjITXP8O5HeQ3CcfVttJop3oSG0uqMbmghoAyt4fBbTtZKo5aALwo5B64okn5POjNm7ciJdffhlPP/00kpKSMG/ePK8fZ9OmTSgrK8OECROg1+uh1+vxww8/4MUXX4Rer0dqaiqsVitqampafV1paSnS0tIAAGlpaW1S/MTn4pr2mEwmxMTEtPogIiKi4HE6JeS2OIz3aKKQqmqwotGqrvTd8npX8dOdjlSq6Eh1cUhrKIl9RmI8y1/hRp2cbtgT431mix1Wh6tjI97IX39yNoamun4Pe3J/lCB35Tp4/eKMpaxOzlgamhKN2HADGq0O/HSwAoDyO1JhBh2iWowe9rlC6vDhw8jJyQEAfPbZZ7joootw44034sknn8SPP/7o9eNMmzYNO3bswNatW+WPSZMmYc6cOfI/GwyGVof87t27FwUFBZg8eTIAYPLkydixYwfKysrka9asWYOYmBiMHDnS15dGREREQVJU2wSLzQmDToOM+LZvWmPCDHLindoCJ8q7cRivIDpSdc12NDQrs5D0dHW6f9hrT+6TEkmD0SY9wgw6AIBBp8XTFx2D9NgwXHlCZmdfHhRiZC+/neQ+p1NCfpUY7eu40NBqNZiU6QpqkyTAoNNgRLr/RxH1lJaHOav5DCnAjz1SUVFRqKysxMCBA7F69WrMnz8fABAWFoamJu//wxcdHY3Ro0e3ui0yMhKJiYny7ddddx3mz5+PhIQExMTE4Pbbb8fkyZNxwgknAHBFsY8cORJXXnklnn76aZSUlOCBBx7A3LlzYTKpNwGEiIiotxFjfZmJkdDr2v87bv/4CJiLzThS3YQhqcp/QyhU1Hc/yS7KpEeUSS+ftdXePrJQqwjAGVJCZkIENuVX90wh1dB+ATguIw4bF0wL+vO3R4RI5Lfz+kvMFljtTui1GvSL63z7y7HZCfh2j6uhMDwtBia9LvCLDbDEKJO8B6yzjpsa+FxInXHGGbj++usxfvx47Nu3Tz47aufOncjKygro4p577jlotVrMnj0bzc3NmDlzJl555RX5fp1OhxUrVuCWW27B5MmTERkZiauvvhqPPvpoQNdBRERE3XOwXESfd/wX6AHx4dhdbMYRle2TCkRHCgBSY0yoL7ejtFaZhZRckHQjsU/IcHdkDvdAIVVRF7gCMFDEobzt7ZESXaqMhIgO/+ggiIN5AeXvjxLE709EixFPtfK5kFq8eDEeeOABHD58GJ988gkSE12b8zZt2oTLLrusW4v5/vvvW30eFhaGxYsXY/HixR1+TWZmJr766qtuPS8REREFlydoouMCwXNQq7oO5ZXPkermm8K02DAcLG9AaZ0y90mJEbkklY32VchnX3V/3YEiXn9Now21TTbEhnsOqBbF1cBOEvuEMf1jEWbQwmJz4hiF748SRHKf2qPPAT8Kqbi4OLz88sttbmecOBEREXVEHMY7uJ3EPkGNh/I2NNvRaHUlv3VntA/wBE4o9Syplsl33dVV2EIgVQZwJDFQIk16JEWZUFHfjILKRoxp0U3yZezNqNfizxMz8M3uUpw6PDlo6w2kJHdHSu1jfYAfYRNff/011q9fL3++ePFijBs3Dpdffjmqq6sDujgiIiLqHQ6Wdd2REoWUms6SEmN9EUZdtw9CVfpZUhUBHO0T3ZaiGgts7kS9YBEdw6QArDuQ5PG+qtbjfQVVnR/Ge7THzh+NjQumISW6Z48T8tfZY9MxYWAcLj9+YKiX0m0+F1L33HMPzGYzAGDHjh24++67cfbZZyM3N1cOniAiIiISGtwBCkBXHSnXG0s1nSUlv0kPQLfD05FSZiEVyM5OcpQJJr0WDqeEoiD/vOXDeBW2H8ezT6p1Vy6vorHV/b3N8LQYLL/1JJw8RB0dtM74/KeT3NxcOVr8k08+wTnnnIMnnngCmzdvloMniIiIiITcCtdf2BMjjYiL6LgrIPZIldc1w2JzyFHVShaooAmgRSGl0I6UXJAEYK+RVqtBRkIEDpTVo6Cq0evuiz/kkcRunn8VaO0dyitJkjzuGMzvCQWGzx0po9GIxkbXD/ibb77BjBkzAAAJCQlyp4qIiIhIkBP7OulGAUBchAGRRlfxFOwuRaCUi6CJAHRpxFlSShzta7Ta0WRz7QUL1F6jngqc8MS2K3S0r0VHqrLBivpmOzQaICOhZw8JJt/53JGaMmUK5s+fj5NOOgm//vor/vvf/wIA9u3bhwEDBgR8gURERKRuB0ViX1Lnkd4ajQb948Oxr7QeR6qbOt1PpRQiWjspuvtv0sUeqbK6ZjicEnRa5SSaia6OSa+Vi93u6ulCKhDjl4HUXuCG6E71iw1XxZlQfZ3PHamXX34Zer0eH3/8MV599VX0798fALBy5UqceeaZAV8gERERqdshd0dqcErXo0pq2yfl6Uh1f6N/UpQRWg3gcEryfiSlaFmMBCqyuifOkmq2O2C22AEoK/4ccB1KDADFtRZY3N0+0Z3qrfujehufO1IDBw7EihUr2tz+3HPPBWRBRERE1Lsc8rIjBajvLKlA7pHS67RIjjah1NyMErMFKTHKSWHzRJ8HrhjpiY5UlTtpUK/VtDqrSQkSIo2INulR12zH4apGDEmNlqPPWUipg88dqZYsFgvMZnOrDyIiIiLB6ZTkM6S62iMFqO8sqfIABjAAnvE+pSX3VTa49xkFMEJcFAsFlcErpFoWgEo7/FWj0cjjfaITJUb7GDShDj4XUg0NDbjtttuQkpKCyMhIxMfHt/ogIiIiEorNFlhsThh0GnmUqzP9VXaWVEUAO1KAJ7lPaYETFQE8jFfIcI9xmi121DbaAva4LYnRS6Ul9gmes6REIeX9YbwUej4XUvfeey++++47vPrqqzCZTHjrrbfwyCOPoF+/fnjvvfeCsUYiIiJSKbE/amBCBAy6rt92qGmPlCRJnj1SASqkPMl9ytojFYzRvnCjTv6+BWu8T6lnSAkD3RHoBe5OlOhIidtJ2XwupL744gu88sormD17NvR6PU4++WQ88MADeOKJJ7B06dJgrJGIiIhU6mCZGOvzLoFP7JEqMVtgtTuDtq5AMFvs8hoDlQin1LOkxGhfUoA7O8HeJyVCO5ICOJIYSKIjlVfZiNomG6rdnTnukVIHnwupqqoqDBo0CAAQExODqqoqAK5Y9HXr1gV2dURERKRqh9yH8XqzPwpw7TUy6bWQJOXtEzqaCJqIDtMH7PDgNIWO9gWjIwUEv5BS6hlSQmaLCHSxVyw52oRIk895cBQCPhdSgwYNQm5uLgBg+PDh+OijjwC4OlVxcXEBXRwRERGpW667kBrsRWIf4DlLClB+cl9FgMf6gBYdKYUVkZ6CJLAdqYygd6REGIgyR/tEqMSR6kY5lCXTi72EpAw+F1LXXnsttm3bBgC47777sHjxYoSFhWHevHm45557Ar5AIiIiUi+RvudN0IQg9kkdUfg+KdGRCuSb9LRY12Mpb7TP3ZEK8IjcwCCfJVXREPiQjEBKiwmDUaeFzSHh50OVAJjYpyY+9w3nzZsn//P06dOxZ88ebNq0CTk5ORg7dmxAF0dERETqJUkSimpdxVB6rPdnInnOklJHIRWMjlSdxY5Gqx0RxtCPeDmdknweUyBfK+AppPKrGgL6uIJIVVTqaJ9Oq8GAhHAcKm/Aun0VAJjYpyZe/9vpdDrxr3/9C59//jmsViumTZuGhx9+GJmZmcjMzAzmGomIiEiFaptssNhcYQxpPhRSajlLSh7tC2C3IzrMgEijDg1WB0pqLV6HdARTbZMNDqcEAIiPCE5HqqjGApvD6VWyoy9ESEYgf0aBlpUYiUPlDXJS5UAWUqrh9W/rP/7xD/z9739HVFQU+vfvjxdeeAFz584N5tqIiIhIxYrd+3wSIo0+hTEMUMkeqWB0pAAgNVZZyX2iGIkNN8CoD2yhkxJtglGvhcMpobgmsK/X6ZSCFpIRSAOPGnvN4mifanj9b8N7772HV155BatWrcJnn32GL774AkuXLoXTqexoUiIiIgoNEZggkui8JXeklL5HKggdKUB5yX0VQSxGtFoNMtw/70AHTpgtNtjdnbQEhcafA22jzllIqYfXhVRBQQHOPvts+fPp06dDo9GgqKgoKAsjIiIidRP7o/rF+VZI9Y9zvbEsrrXA7lDuH2zFaF9SdGDfpKfJyX3KOJRXTr4L8BlSgghXCHQhJQrAmDA9TPrAxNMHQ8tCKjbcgNgIQwhXQ77wupCy2+0IC2v9H0KDwQCbzRbwRREREfU1DqcEm4KLBn/IHSkf9kcBrnEvg04Dh1NCaZ0yion2yKN9Ub69vq6I0T6ldKTEaF+wxuOCdZaUXOgqeH8UAAxM8HSgGDShLl6HTUiShGuuuQYmk+eX0WKx4Oabb0ZkpOcXYPny5YFdIRERUS9XZ7Hh9EU/ICc5Ch/ccDw0Gk2olxQQYo9Uemy4T1+n1WrQLy4c+ZWNOFLVKKf4KYnTKckdj0DvkepLo32AJxo/0BHoatgfBQAZCeHQaABJYvS52nhdSF199dVtbrviiisCuhgiIqK+aFeRGeV1zSiva8b2I7U4JiMu1EsKiGL3aJ+ve6QA1z6p/MpGxe6TqmmRZBfoN+ryobxBLqSarA58svkIzhmbjrhO0viOuAucxCCN9gWrIyU6aUrvSJn0OvSLDUdhTVOb/VKkbF4XUkuWLAnmOoiIiPqsluclfbqlsBcVUu6OlI97pADlnyUlxvriIwwBj+xOjXG98S+tDW4htfSXfDz+5W6s21eON66a1O419c12rNpZAgA4YVBiUNYRtNE+hZ8h1dLglCgU1jQhJyX0cffkvcD+m09EREQ+a9l1+WJbUa/YKyVJkrxHytfRPgAYEO96c63Us6TkM6QCPNYHePaUldU1w+nuegXD/tJ6AMCa3aXIq2j/QNwvthWhwerAoKRInDAoISjryEhw/X7UNtlQ2+j73vt/rtyDW97fhGa7o9XtFe5DhIPVSQuk+88egXvPHIaZo9JCvRTyAQspIiKiEGtZLFQ2WLFuX3kIVxMY5iY7Gq2uN7b+jPbJHakaZZ4lJTpSwRgbS44yQasB7E4JFQ3BC9s47D6nS5KAdzbktXvNf34tAABcdtzAoO3dizDq5e+jr12pyvpmvPbDQaz8owRr95S1uQ8AkoJQ7AbasLRo3Hpqjk/nrVHosZAiIiIKMdGRSnG/4Vu+uTCUywmIYrPrNcVHGBBu9P3NoXyWlEI7UsE6jBcA9DqtXFiUBjEC/XCLA48/+v0waptad4P+KKzF9iO1MOq0mD1xQNDWAXi6Ur4ewrzhYKX8z19sK251X4Uc26780T5SJxZSREREISbePN44dRAA16jV0W9q1aZYjj73L3Gvv7uQKqqxBHW87WiHqxrxxFe7u3xDXxGkw3gFMd4XrMAJu8OJ4hrPgcmNVgc+dHefBNGNmjk6LegH2ma4RzkP+1hIrd9fIf/zt3tKUd9slz9XU0eK1MmrQmrChAmorq4GADz66KNobFRmm52IiEhtnE4JRe43tDNHpWFoahSsdidW7iju4iuVzbM/yr8zltJiwqDTamB1OFFe33NnSb29PhdvrDuEv7zzGxqt9g6vK3K/vmC9SQ92cl+J2QK7U4JBp8Fd04cAAN7dkCcfgNzQbMf/thYBAC47LiMoa2hJdCB9CReRJAnrD7gKKYNOA4vNiW93l8r3y/Hn7EhRkHhVSO3evRsNDa5NiI888gjq6+uDuigiIqK+oqK+GVaHE1qNqwtxwXjXCNXyLeoe7yt2jyv6W0jpdVp5b5Wv417dIcYs95XWY8HyHZCktt2wtXvK8OV2V5ExLDU6KOuQz5IKUnKfKFj6x4Xj/PH9kRRlRFGtBSv/cCX0fbGtCPXNdmQnRWJykNL6WhLhIr4UUrkVDSisaYJRp8U1J2YBcK0bACw2B+rc3alEhcefk3p5FX8+btw4XHvttZgyZQokScIzzzyDqKj24xkfeuihgC6QiIioNztc7TlryaDT4vzx/fD0qj34NbcKh6sa5cNK1aa4mx0pwNWlKKxpwpHqJkzMDNTKOlfWogP0v61FmJgZj6smZ8m37Soy47YPNsMpARdPGoBThyUHZR3BHu0Th99mJEQgzKDDnOMz8cK3+/HW+lycMza9RchERo8cEC32SPlyKK/oRk3MjMfFkzLw5o+5+GFfOWobbah3dxONOi1iwrw+7YfIJ151pN555x0kJiZixYoV0Gg0WLlyJT799NM2H5999lmQl0tERNS7iA6I2BOUHhsudwD+t1W9XSlRAPi7RwrwfE968iypUrNrjPC8cf0AAI+t2IXNBdXu+yy47t3f0GB1YPKgRDx+/pigFRlitK80SIWU+J6KkborTsiEUafFtsM1eP/nfGw7UguDToPZE4IbMiG07Ei11wVsz4/u/VFThiRhSGo0hqdFw+aQsGpnSaszpHqiEKS+yasSfdiwYfjwww8BAFqtFt9++y1SUlKCujAiIqK+oFB+Q+vpPF0wvj82HKzE8i2FmHtajirfCBZ1c7QPaHGWVE3PFFIOpyTvx1pw1gjXXrU/SjB36WZ8dNNk3LJ0E4prLRicHInXrpgIoz54mV1pQS6kRKiD+B4nR5tw/vh++Oj3I1j4xS4Arj17PTUW1y8uDBoN0GRzoKrB2uXz2h1O/OxO7Dt5SBIA4Nxj+mFPyV58vq0If4nOAqCOw3hJvXz+L4DT6WQRRUREFCCF7nOSxLlJAHDWmHSEGbQ4VN6AbUdqQ7U0v0mSFJjRvrie7UhVNjTD4ZSg1QBJUUY8fdFYDEqKRHGtBTOeW4c/Cs1IiDRiyTXHITbCENS1pMW6ComSIO+REh0pAPjLlGwAroISAC4/fmBQnrs9Jr0OqdGu35XDXvy8tx2pQV2zHXERBozqFwsAOGdsOgBgw8EK7CmpAxCcc76IBL/+lHLw4EHcfvvtmD59OqZPn4477rgDBw8eDPTaiIiIej1503+LN7RRJj1mjkoDAHy6+UhI1tUddc0tDuPt5h4pACjsobCJMrPnkF29TovoMANevWIiwg06NNkcMOq1ePOqiRiYGPx9aynujpTZYkeT+3sZSEda7JEShqfFYEqOq7uTlRjRIyETLXmS+7r+eYuxvpMGJ0GndXVsMxMjccyAWDglYOnPrj1eiZEspCh4fC6kVq1ahZEjR+LXX3/F2LFjMXbsWPzyyy8YNWoU1qxZE4w1EhER9VqF7XQGANd4HwB8uaPE6z0jSiHOJ4oNNyDC6P9Gf1FcFtZ4v2+mO8QYndifBADD0qLxwqXjMDI9Bi9eOh4TMxOCvg4AiDbpEek+yLi4NrAdOavdKe9hO/r37t4zh2FIShTuO2t4j4+U+hKBLs6POsld+AnnHuPa2ybGQZM42kdB5PN/3e677z7MmzcP//znP9vc/re//Q1nnHFGwBZHRETUm0mS5AmbiGv9hvaEQYnQalzx6OV1zXKHQg3EG//ujPW5vj4cGg1gsTlR2WAN+piWCJpIjWn9PDNGpWGGu0PYUzQaDTISIrCnpA75lY0YlNx+WrI/imub4JQAk17b5kDhsQPisGb+KQF7Ll+I7lhXyX11Fhu2HK4B4NkfJcwam47Hv9wtf87RPgomnztSu3fvxnXXXdfm9r/85S/YtWtXQBZFRETUF1Q32uQRuH5HFVJhBh2ykyIBALvd+z3UoruH8QpGvVbeN9MT+6RER0opReugZNfP/1BFQ0Aft+X+KCUFmXjbkfr5UBUcTgmZiRFtjgdIjw3HcVmeriHDJiiYfC6kkpOTsXXr1ja3b926lSEUREREPhBjfcnRJoQZdG3uH54WAwDYW2Lu0XV1V1Ft96PPBc8+qeAXUmV17tG+aGUUUlmJrkIqL8CF1OF29kcpgScCvfOO1Pr95QAg7+c62rnHpMv/zMN4KZh8Hu274YYbcOONN+LQoUM48cQTAQA//fQTnnrqKcyfPz/gCyQiIuqt2kvsa2lYWjS+3FEsJ5CpRUmARvsA1z6p3/OrvQog6K6ORvtCRXQkc4PYkVKSjKPOkuqoWyYO4j16rE84a0w6Fn6xCw6n1GZ0kSiQfC6kHnzwQURHR2PRokVYsGABAKBfv35YuHAh7rjjjoAvkIiIqLdqL7GvpeFp0QCAPcXqKqQCEX0uDGgROBFs7YVNhJIY7fO1kGqyOvDWj4cQbtTh+pMHtblfnCGVEa+sjlR6XBi0GqDZ7kR5fTNS2ukMFtc24WB5A7QaYPKg9guppCgTHpw1AnmVjRiRHh3sZVMf5nMhpdFoMG/ePMybNw91da7/sEdH85eUiIjIV3JnoIOOlBjtO1BeD7vDCb0ueAfABpJnj1T3Ox794zxdimATHakUhXSkxGhfYU0TLDZHu+OfR9twsAILlu9AfqWrWJoxMq1NXLsY7RugsELKoNMiPTYchTVNOFLd1G4hJWLPxwyI6/Qsr2tOyg7aOomEbv0XOTo6mkUUERGRn0SXpaMRqwHx4Ygw6mC1O5FXGdjxrmAqlvdIBbAjFeRCyuZworJBjPYpoyOVEGlETJjrb96iMOpIbZMN932yHZe/+Uura39w7ydqSRSlGQnKGu0DPN3ZjgpnEXt+cgf7o4h6kjr+tEVERNQLFXYx2qfVajA01fUHy90qGe+rs9hQ32wHELg9UoArgCCYZ0lV1DdDkgC9VoOECGUkvWk0GmS7Y89zK+o7vO77vWU449kf8OFvhwEAV5wwELecOhgA8MPe1oWUxeZAWZ2rYFRaRwrwFM7tRaBLkoQNB12F1JQO9kcR9SQWUkRERCEiAhTE+Fp7xB6PvSoJnBBjfTFhekSa/D+MVxBBHA1WB2qbbN1+vI7IY33RJmi1yokEz3aP5XUUgV7fbMetSzejrK4Zg5Ii8d8bT8Dj54/BrDGu5LoNBytgtTvl60UXNNKoQ3wno3Gh0jJw4mh5lY2oqLfCqNNi/MC4Hl4ZUVsspIiIiEKgzmKD2eLq3HTUkQKAYe6OlFqS+4oCuD8KcJ2nJQ5VDeY+KaWdISVkJ7k7UuXtF1K7isxotDqQGmPCV3eejOMHJQIARqbHICnKhEarA7/nV8nXt9wfpaQzpIQBLTqQR9tSUA0AGNU/BiZ91/vFiILNp0LKZrNh2rRp2L9/f7DWQ0RE1CeIzkBchAFRnXRuhomzpErVcZaUHH0eF7iCxNuDWrujTE7sU0bQhJDtTu7raI/cH4W1AIAx/eNahVFotRpMHeoaf/thn2e8T8n7o4CWZ0m1/VlvdhdSEwbG9+iaiDriUyFlMBiwffv2YK2FiIiozzhS5d4f1UFinyAi0A9XNcl7j5QskNHnQv8eiED3nCGlrI7UoC7OktpZ5CqwR/ePaXPfKUOTAbTeJyWiz5W4PwrwFHiF1U1wOlvviducXwOAhRQph8+jfVdccQXefvvtYKyFiIioz+gqsU+IjzTKXRI17JMqrnEn9sUEruPR2bhXoCjtDCkhy11IVdRb290jtrPI1ZEa1S+2zX0nD0mGRuMaCxWvT6mH8QppMWHQaTWwOlxnSQkNzXbsKXEVjRMy40K0OqLWfN4Farfb8X//93/45ptvMHHiRERGRra6/9lnnw3Y4oiIiHorUUh1FjQhDEuLQam5HHtL6jAxU9l/jS82B74jJc7ZCmYEemmdJ2xCSaJMeiRHm1Be14y8igYckxEn32exObC/zJXm115HKiHSiLED4rDtcA1+2FeOiydl4IhCz5AS9Dot0mPDcKS6CYerGuXCdtuRGjgl1+9VoPbfEXWXzx2pP/74AxMmTEB0dDT27duHLVu2yB9bt24NwhKJiIh6n66iz1sakSYCJ5S/Tyo4e6SCfyhvmUI7UgCQndT+Pqm9JXVwOCUkRBqR1sG65fE+9z4ppe+RAtpP7ttSUAOAY32kLD53pNauXRuMdRAREfUpR+S9Kl2/oR2Wpp7kPjHap749UgoupBIj8WtuFQ4dldwn9keN6hfTYQLfKUOT8eK3+7F+fwXMFhsqG6wAlNuRAtof5RSJfYw9JyXxO/78wIEDWLVqFZqaXP9RC+YheURERL2NZ7TP+0Jqb0mdov//ts5iQ507ECMtgONX4ntU22RDnSXwZ0k12x2obnQ9rtJS+wBPct/RgRN/dLI/SjhmQCxiww2obbLhq+3FAFxnfMWGK+8MKUEUeYerPO8xN7s7UuPZkSIF8bmQqqysxLRp0zB06FCcffbZKC52/Ut53XXX4e677w74AomIiHobi82BinrRGei64MhJiYJOq0Ftkw0l7s6JEomuTnSYvtNId19FmvTy4bHB6EqVuRP7jHqtIguM7A6S+zpL7BP0Oi2mDHHFoL//Sz4AZXejAM/Y4ZEaV0cqv7IRVQ2ug3g7e61EPc3nQmrevHkwGAwoKChARITnX8RLLrkEX3/9dUAXR0RE1BuJvR+RRp1Xb9xNep0cg63k8b5gRJ8L8j6pqiAUUnUiaTBMkYfUip99XkWD3JG0O5zYUyxG+zruSAGefVJ/FLquV/L+KKDtnrjNPIiXFMrnQmr16tV46qmnMGDAgFa3DxkyBPn5+QFbGBERUW/liT6P8PqNe8vxPqWSo8+DkKomxvuC0ZHynCGlvLE+AMhIiIBGA9Q12+VO5sHyBjTbnYgy6ZGZ0HmHSRRSgtI7UqJLW1TTBIdTYtAEKZbPhVRDQ0OrTpRQVVUFk0mZ/wEiIiJSEl8S+wRxMK/oQiiR3JEKQmBDMM+SEiOJKQoMmgCAMINOLiTFeJ84P2pkegy02s6L8dSYMPn3BwAyFHqGlJAaEwaDTgObQ0Kp2SJ3pFhIkdL4XEidfPLJeO+99+TPNRoNnE4nnn76aZx22mkBXRwREVFvVOje++FN0IQwPM21N0TJo30l5sBHnwvBTO6TO1LRyiykgJb7pFznRokxvVFe7hk6ZZinK6X0jpROq0E/978b+0rr5N95JvaR0vi8E/Tpp5/GtGnT8Pvvv8NqteLee+/Fzp07UVVVhZ9++ikYayQiIupVxN4Pb4ImBDHad7C8HjaHEwad38G7fpEkqdMxRKdTwv5S15v8oO6RCsJZUp4zpJQ7WZOdFIkf91cgt8JVhO/0IrGvpVOGJuP1Hw4BcI0KKt2A+HDkVzbiqx3FcDglpMWEycUVkVL4/F/h0aNHY9++fZgyZQrOO+88NDQ04MILL8SWLVswePDgYKyRiIioV/FntG9AfDiiTHrYHFKb9LZg+/fP+Rj7yGo8t2Yfmu2ONvc3Wu24Zekm/J7vGsEa0z8u4GuQ90gFoZAqrVPuGVJCy46U0ylhV4szpLwxKTMBA+LDkRpjQmai8gspcSjvyj9KAAATMuNCuBqi9vmVTRobG4v7778/0GshIiLqE3w5Q0rQaDQYmhqFzQU12F1sxtDU6K6/KEC+2l6MOosdL3y7H1/tKMZTF42V96sU1TTh+nd/x65iM4w6LZ68cAxGevnm3hei6KxssKLRakeE0fe3MJsLqhFt0mPIUd87MdqXovCOFODaI3W4uhF1zXYY9VrkpER59fVGvRZf3DYFgGvPldKJbm2dxXUuGfdHkRL5VUhVV1fj7bffxu7duwEAI0eOxLXXXouEhISALo6IiKi3sdqd8llQvnSkAGB4egw2F9T0eHJfXqWrAxZm0GJ/WT1mv7oB15yYhTNGpOKOD7eior4ZiZFGvHHVREzMDM57gdhwA6LD9Kiz2FFU04ScFN8KyQ0HKzDnrV8QbdLjp/tOR3SYJ3a+1Kz8jtSgJFfBlFfZiO1HXGN9w9OifRrxjI80BmVtwXD0Pi4exEtK5PNo37p165CVlYUXX3wR1dXVqK6uxosvvojs7GysW7cuGGskIiLqNY5UN0KSgHCDDslRvnVAhocgAr3J6pDT+L6642RcOKE/JAlY8lMeLn/rF1TUN2N4WjT+d9tJQSuiBPHm+rCP431miw33LNsOSQLMFjv++9th+b5Gq13ueii5kOoX50qys9qd+GZ3KQDv90epUcuzrngQLymVz4XU3LlzcckllyA3NxfLly/H8uXLcejQIVx66aWYO3duMNZIRETUa+RXucICMhO9P0NKGOYeSevJ5L78Klc3KiZMj+ykSDx78Ti8+5fj5LHE6SNS8PEtJ/ZIEpy/+6Qe/WIXCmuaYHR3b97ZkAeH03WwbZl7rC/SqEOUya9BnR6h12kx0B0SsWaXKKR6b3HR8vdpZD8exEvK5HMhdeDAAdx9993Q6Ty/0DqdDvPnz8eBAwcCujgiIqLepqDSVUgN9CM5TST3FdY0oaHZHtB1dSTPHWyRnRQpF36nDE3GmvlTsfzWE/HGlZN6rADxnCXlfSG1amcJPt50BBoN8H/XHIv4CAOOVDdh9U5XiIEaxvqEbPd4X6PVFfgxun/v7UglR5lg1LvepnJ/FCmVz4XUhAkT5L1RLe3evRvHHHNMQBZFRETUW+VXejpSvoqLMCIpyrXP5VB5zyT3ibjtLHfYgRBh1GPCwPguD4MNpAE+niVVUd+Mvy/fAQC4aepgTBmShDnHZwIA3lqfCwAorVN+0ISQneT5ndFpNa0O2e1ttFqNfHAwE/tIqbz6E9L27dvlf77jjjtw55134sCBAzjhhBMAAD///DMWL16Mf/7zn8FZJRERUS+R7w5uyEyM7OLK9g1KjkJFfRUOltdjzIDgdyTEAbBZfq43kDwdqcYur5UkCQuW70BlgxXD06Ix74whAICrJmfi9XUHsSm/GlsP17Q4Q0o9HSkAyEmOUkX6Xnf8/ewRWH+gAjNHpYV6KUTt8qqQGjduHDQaDSRJkm+7995721x3+eWX45JLLgnc6oiIiHqZlnuk/JGTEoVfc6twoKw+kMvqUJ67I5WdFPpCqn+c63vmzR6pTzYXYs2uUhh0Gjx78Th5j01KTBjOHdsPy7cU4u31uUhzd6LUUUh5fga9eX+UMG1EKqaNSA31Mog65FUhlZubG+x1EBER9XpOp4QCUUgl+FeYDE52dSUOlvdMIZXr7qAdPdoXCqIjVVbXDIvN0WFHps5iwyOf7wQAzD9jWJtzrf4yJRvLtxTiqx3FmDAwDgCQEq2G0b4WhVQv3h9FpBZeFVKZmZnBXgcREVGvV1pngdXuhF6rQb84/zogg5Ndb6Z7opCqb7aj3L2HKFsBo31xEQbEhhtQ22TDofKGDg/+/aPQjLpmO/rFhuHGqYPa3D+6fyxOGJSAnw9V4be8agDq6EilxpgQYdSh0eroEx0pIqXzOWwCAIqKivDRRx/h5Zdfxosvvtjqwxevvvoqxo4di5iYGMTExGDy5MlYuXKlfL/FYsHcuXORmJiIqKgozJ49G6Wlpa0eo6CgALNmzUJERARSUlJwzz33wG7vmSQjIiIiX4igif7x4dD7cJBqSzkpro5UbkUD7A5nwNbWHpHYFx9hQGyEoYurg0+j0cjJhXtKzB1et6/UFQ8/sl8sdB2EYVw3pXWBpYZCSqPR4J6ZwzB7wgBMymSSHVGo+ZxX+s477+Cmm26C0WhEYmJiqzMwNBoN7rjjDq8fa8CAAfjnP/+JIUOGQJIkvPvuuzjvvPOwZcsWjBo1CvPmzcOXX36JZcuWITY2FrfddhsuvPBC/PTTTwAAh8OBWbNmIS0tDRs2bEBxcTGuuuoqGAwGPPHEE76+NCIiUpBGqx23vL8ZJwxKxC2nDg71cgKiu0ETANAvNhxhBi0sNicOVzcFde9SXqUn+lwphqdF49fcqk4PJd7rLqSGpUV1eM204SnISoxAnru4TVVBah8AXHtSdqiXQERuPv857MEHH8RDDz2E2tpa5OXlITc3V/44dOiQT4917rnn4uyzz8aQIUMwdOhQ/OMf/0BUVBR+/vln1NbW4u2338azzz6L008/HRMnTsSSJUuwYcMG/PzzzwCA1atXY9euXXj//fcxbtw4nHXWWXjsscewePFiWK1WX18aEREpyI/7K/DDvnI89fUerN1bFurlBIQcfe7HGVKCVqvBIHd628EgB06IjpQS9kcJno5Ux4XUfnchNTS143hwrVaDv0zxFCUp0crvSBGRsvhcSDU2NuLSSy+FVuvfSEJHHA4HPvzwQzQ0NGDy5MnYtGkTbDYbpk+fLl8zfPhwDBw4EBs3bgQAbNy4EWPGjEFqqifRZebMmTCbzdi5c2eHz9Xc3Ayz2dzqg4iIlKXlHqC/fbwdNY3q/wNZdxP7BDHedyDI+6TEGVJK2B8lDE9z7Q3qqCMlSZJ837Auzlm6aOIAjOkfizNGpiLc2LujxIko8Hyuhq677josW7YsYAvYsWMHoqKiYDKZcPPNN+PTTz/FyJEjUVJSAqPRiLi4uFbXp6amoqTEdRp5SUlJqyJK3C/u68iTTz6J2NhY+SMjIyNgr4eIiAKjZbx3WV0zHvxfx38gU4sCd0dqYDc6UkCL5L5gd6QUlNgniOKoxGxpt7guNTfDbLFDp9V0OZIYYdTji9un4M2rJgVlrUTUu/m8R+rJJ5/EOeecg6+//hpjxoyBwdB68+mzzz7r0+MNGzYMW7duRW1tLT7++GNcffXV+OGHH3xdlk8WLFiA+fPny5+bzWYWU0RECnOw3PUm/uZTBuPNHw/hi21FOGNkKv50TL8Qr8w/kiTJhUl39kgBwOCUnknuE6N9StojFWXSY0B8OI5UN2FPSR1OGJTY6n6xPyo7KVI+O4qIKBj8KqRWrVqFYcOGAUCbsAlfGY1G5OTkAAAmTpyI3377DS+88AIuueQSWK1W1NTUtOpKlZaWIi3NdcJ1Wloafv3111aPJ1L9xDXtMZlMMJnUsamUiKgvkiRJ7rbMntAfRr0WL367Hw9+9geOz05QRcLa0WoabaizuFJlu9uRkkf7yuohSZJf///bFbPFhsoGV8dHSR0pwBU4caS6CXvbKaT2ibG+TvZHEREFgs+jfYsWLcL//d//Yffu3fj++++xdu1a+eO7777r9oKcTieam5sxceJEGAwGfPvtt/J9e/fuRUFBASZPngwAmDx5Mnbs2IGyMs8m5DVr1iAmJgYjR47s9lqIiCg0yuqaUd/sGs/KTIzE7afnYHT/GNQ22XDvx9shSVKol+gzsT8qNcbU7f04WYmR0GgAs8WOivrg7B0T3aikKBOiTD7/3TWoxD6p9iLQ93oRNEFEFAg+F1ImkwknnXRSQJ58wYIFWLduHfLy8rBjxw4sWLAA33//PebMmYPY2Fhcd911mD9/PtauXYtNmzbh2muvxeTJk3HCCScAAGbMmIGRI0fiyiuvxLZt27Bq1So88MADmDt3LjtOREQqJrpRmQkRMOq1MOi0eO7icTDqtfhhXzk++LUgxCv0nRx9ntD97k6YQYeMeFdXK1jjfbnyWF/3umfB0Fly334vos+JiALB50LqzjvvxEsvvRSQJy8rK8NVV12FYcOGYdq0afjtt9+watUqnHHGGQCA5557Dueccw5mz56NqVOnIi0tDcuXL5e/XqfTYcWKFdDpdJg8eTKuuOIKXHXVVXj00UcDsj4iIgoNkUY3KNnzZnhIajTunekaK3/9B9+O21ACOWiim4l9QsvxvmDIcyf2ZSkosU8Y7i6k9pXUwen0dCedTgn7Sl3fjyHsSBFRkPncq//111/x3XffYcWKFRg1alSbsImWhU5X3n777U7vDwsLw+LFi7F48eIOr8nMzMRXX33l9XMSEZHyiY6UCFUQ/jwxA49/uRsFVY0wW2yICTO09+WKJEefd3N/lDA4ORLf7QleR0qJiX1CdlIkjDotGqwOFNY0IcP9PT1S3YQmmwNGvTZg32cioo74XEjFxcXhwgsvDMZaiIiIAHgS+3KSW49nxUYY0C82DEW1FuwprsNx2QmhWJ5fREcqM0CFiehIie9VoOUqMLFP0Ou0yEmJwq5iM3YXm+VCSuyPykmOgl4X2PMuiYiO5nMhtWTJkmCsg4iISHZA7ki13ecyIj3GVUiVmFVVSMnR5wHrSAX3LCm5I6XA0T7ANd63q9iMvSV1mDHKldS7r9S7g3iJiAKBf64hIiJFqW+2o8RsAeApFloake5KbNtd3DaxTamarA6U1TUDADIDtEdKfG8Ka5rQaLUH5DGFmkYrahptAIAsBYZNAC0CJ0o9gRP7mNhHRD3I545UdnZ2p+dVHDqkvg3ARESkHKLDkhxtQmx42z1Qw9Ndb5J3FbdNbFOqAvf+qJgwPeIijAF5zPhIIxIjjahssOJQeQNG948NyOMCnrG+tJgwRBiVFX0uDHcX1HtaFNR7S0QhxcQ+Igo+n//reNddd7X63GazYcuWLfj6669xzz33BGpdRETUR4nwhMHJ7Y+UiY7UvpI6OJwSdNrAH0YbaHL0eYDH5AYnR6GyoQoHy+v9LqQOltdjYEIEDC32FHmCJpTZjQI8yX15lY2w2BzQaTU45N4vxo4UEfUEnwupO++8s93bFy9ejN9//73bCyIior7NU0i131XISoxEmEGLJpsD+ZUNrSLSlUp0pAI11icMTonEr3lVfu2TkiQJT67cgzfWHcL4gXH44PoT5IOCc93R50oMmhBSok2IizCgptGGA2X1CDNoYXU4EWnUoX9ceKiXR0R9QMD2SJ111ln45JNPAvVwRETUR4mgiZx2giYAQKfVYFhqxweyKpEcNBHoQirZv+Q+p1PCws934o11rnH8LQU1uP0/W+Bwn8mUV6HsoAkA0Gha/x7sLfGcH6VVQZeSiNQvYIXUxx9/jIQE9aQnERGRMomioKOOFKC+wIl8EX2eEODRPj8O5XU6Jdz/2Q68uzEfAHDdlGwY9Vp8s7sUD3/+ByRJkvdIKfEMqZbE78HeErMcfT6MY31E1EN8Hu0bP358q7AJSZJQUlKC8vJyvPLKKwFdHBER9S02h1PeT9Re9Lkg9seopZASo30DA9yREuds5VY0eLVfzOGUcM/H27B8cyG0GuDpi47BRRMHYFJmPG79YDPe/7kA6bHhckdKyaN9QIvkvpI6RJlcb2mGMGiCiHqIz4XU+eef3+pzrVaL5ORknHrqqRg+fHig1kVERH1QQVUjbA4JEUYd0mPCOrzO05FS/mif3eFEYXUTgMCPyvWPC4dJr0Wz3YnDVY2ddpDsDifmfbQNX2wrgk6rwXOXjMOfjukHADhrTDoeOmckHvliF/61ai8AQKMBBgbozKtgEYXU3pI6RIXpW91GRBRsPhdSDz/8cDDWQUREJIcmDEqO7HSfy/A0VyFVWNOE2iZbuzHpSlFUY4HdKcGk1yIl2hTQx9ZqNRiUHIXdxWYcLK/vtJBa+UcJvthWBINOg5cum4AzR6e1uv/ak7JRXGuR9031iw1HmEEX0PUGmhjjK6trRnl9c6vbiIiCjQfyEhGRYhzoIrFPiI0wyMlsexQ+3ieCJgYmRAQlBEHExIu0w47scn+fLp6U0aaIEu47czjOdXephqugsxNp0stdM0kC4iIMSA5wsUpE1BGvO1JarbbTg3gBV4KO3R7Y09WJiKjvOFjmKjpyvIg0H5EejcKaJuwpqcPxgxKDvTS/5Qcp+lzI8TJwIteLEA+tVoNFfz4GU4ck4QQFf09bGpYWLe9BG5oa3eV7FSKiQPG6kPr00087vG/jxo148cUX4XQ6A7IoIiLqm+QzpDoJmhCGp8Xgm91lig+cKJA7UsEJbhCFUVeFlOiMdRUgYdRr8edJGYFZXA8YnhaNNbtKAQBDGTRBRD3I60LqvPPOa3Pb3r17cd999+GLL77AnDlz8OijjwZ0cURE1LVmuwMf/X4EJ2QnYIiK94dIkiTvkepqtA9QTwS6iD7PSgp+R0qSpHY7Mk6nJ9Jc6Ul8vhL75QDujyKinuXXHqmioiLccMMNGDNmDOx2O7Zu3Yp3330XmZmZgV4fERF14ZEvduHBz/7A/Z/9EeqldEt5XTPqmu3QarwrOkakuxPbSuvkg2SVSI4+D1IC3qDkSOi0GpgtdpTVNbd7TYnZgma7E3qtBgPiw4OyjlBpmdI3lIUUEfUgn1L7amtr8cQTT+Cll17CuHHj8O233+Lkk08O1tqIiKgLH286gg9+KQAA7CyshdMpBSXQoCeI0bSBCREw6btOi8tMjESYQQuLzYm8ygavuljBZnM4caCsHvtK61r9L+BabzCY9DpkJkbgUHkD9pXWIbWd2HhxLtTAhAjodb0rZyorMQKpMSY0NjswPD2m6y8gIgoQrwupp59+Gk899RTS0tLwn//8p91RPyIi6jm7isy4/9Md8ucNVgcKa5qQofCzfzoi9kfleLE/CgB0Wg2GpcVg2+Ea7CmuC1khZbE58OP+Cqz8oxjf7CqF2dI2dKlfbFhQO0FDU6LdhVQ9Th6S3Ob+Q+5CqrN4dLXS67T4+OYTYXU4FR2DT0S9j9eF1H333Yfw8HDk5OTg3XffxbvvvtvudcuXLw/Y4oiIqH21TTbcsnQTmu1OnDI0GaVmC/aU1GF3sVnFhVTXqXJHG5EWjW2Ha7C72IxZY9ODtbR2bcqvxpKfcrF2TxkarA759miTHkPTojE0NQo5Ka7/HZcRB0MQO0FDU6Pw9U5gf2n7BxSLjlSgDwRWCrX+zhORunldSF111VWMFCUiUgBJkvDXZduQX9mI/nHheP6ScXhsxS7sKanD3pI6zBjV/hlBSnfAh6AJIZSBE3OXbkaJ2QIASI8Nw8xRaThrdBomZSVA18PjlTnuvUH7Oiik5KCJ5N5ZSBERhYLXhdQ777wTxGUQEZG3Xl93CGt2lcKo0+LVKyYgPtIob7jf08EbaTXwJfpcEIXUnpKefd2V9c1yEfXJLSdiwsC4kP6xUcR+7+8guS9XRJ/30o4UEVEo9K4dp0REvdyuIjOe/noPAGDhn0Zh7IA4AJ7ksj0KjwLvSH2zHcW1rsJksA9dE/G6C2uaUNtoC8ra2iO6ZxkJ4ZiYGR/yiY3sJFdyX53FjlJz6+Q+u8OJw+7kQHakiIgCh4UUEZGKfLG9CE4JmD4iBZcd5zk0VXRm8iobYbE5OvpyxdpV5CoAU2NMiIswev11seEG9I9zhTjsLum5InK/u5AakqKMuG2TXoesRNc+oaPH+wprmmBzSDDptUhvJ9GPiIj8w0KKiEhFvt9bDgA4Z2y/Vl2QlGgT4iIMcDgluVuiJtuP1ACA3GHzhThPqie7cSLUYYgPY4jBNrSDfVJif1RmYoRqo/GJiJSIhRQRkUqUmi3YXWyGRgNMHdo64lqj0WCY+4303h7eLxQI24/UAgCOGRDr89d6Aid67nWLjpS3Ue09YYj757+/tHUhLQdN9MLocyKiUGIhRUSkEj+4u1FjB8QhIbLt+NtwsU+qB0fcAkV0pMb41ZFyF1KhGO1LVcZoH+Dpju0ra11Q5vXiM6SIiEKJhRQRkUp8v68MAHDq0LYHrgLA8BAl2HVXbaMNeZWuMISx/f3vSO0pqYPN4Qzo2tpT02hFeZ0r0EFJHSkx2neg1JXcJ+S6v7eDWEgREQUUCykiIhWwO5z4cX8FAODUYe0XUiLBTm2jfdsLawAAAxMiEN9Op60rmQkRiDbpYbU724y1BYPYg9YvNgxRJq9PEQm67KRI6LUa1DXb5Wh2AMitcK23tx7GS0QUKiykiIhUYHNBDeosdsRHGDoMZBAdibK6ZlQ1WHtwdd0j9keN9WN/FABotRqM6u/qSv1RWBuwdXVE3h+loLE+ADDqtfL43j53Qdlsd6CwugkA90gREQUaCykiIhX4fq9rrG/q0GToOkheizLpMTDBFYGtpn1SYn/UMX7sjxLGuEcCd/REIVUqos+VM9YnyAfzupP7Dlc1wikBkUYdkqNNoVwaEVGvw0KKiEgFROx5R2N9ghrH+7rbkQI8IRU9UkiVKS/6XBDnWokI9NwK1/6orKTIkB8aTETU27CQIiJSuFKzBbtE7PmQzgup4SorpMrqLCiutUCjAUb5ETQhiI7U7mJz0AMnDigwsU8Y4u5IidE+JvYREQUPCykiIoWTY8/7xyIxqvPxLNGR2q2SQmqHuxuVkxzVreAGETjRHOTAiTqLDcW1riAHJSX2CXJyX5krue+Qu5BiYh8RUeCxkCIiUjgRe37KsJQurx2e5gpd2F9aB6dT6uLq0Nsmj/XFdetxeipwQnSjUmNMiA03BO15/JWV6Eruq2+2o7jW4ulIMbGPiCjgWEgRESmYN7HnLWUlRsCo16LR6sDh6sZgL6/b5KCJDP/H+oSeCJzwBE0ob6wPcCX3ZcvJfXXIq3QVUtnJLKSIiAKNhRQRkYK1jD33JtVOr9PKIQi7i5U93idJUougibhuP97oniik3EETShzrE8R43/YjtfIYYjY7UkREAcdCiohIwUTs+clDOo49P5pakvuOVDehqsEKvVYjh2R0R8vACXuQAif2y0ETyi2kxNrW7CoFAMSGG/w66JiIiDrHQoqISMG8jT1vaYR7n9TeUmWfJSU6R8PToxFm0HX78bISIxElAifKghM4ofTRPsCzNvH95UG8RETBwUKKiHqtklpL0DoTPaGk1hV7DrgO4vWW6EjtUXhHapt7f1QgxvoAd+BEP1cR2d3xvsNVjZCk1mEdDc12FNY0AVDmGVLC0KO6ZSykiIiCg4UUEfVKK7YX4YQnv8Uzq/eFeil+++CXfADAsVnxSOoi9rwlMSaXV9EAi80RlLUFwvbDrmLnmG4cxHs0Md7XneS+j34/jJOfXou/f/pHq9sPlru6UUlRRkWPymUlRcKg84yBspAiIgoOFlJE1OtY7U489fUeAJ49RmpjsTnw/i8FAIBrTsz26WuTo02IjzDAKSGoZyp1h9MpycVOoDpSADBmQPcCJ2wOJ174Zj8A4D+/FmD1zhL5PvG9VHLQBAAYdNpWxRMP4yUiCg4WUkTU6yzbdBiHq1wjWAfK6tFsV25XpiOfbilEVYMV/ePCMXNUqk9fq9Fo5POk9pQoc5/UoYoG1DXbEWbQBnRMbnQ3Ayf+t7VIHt8DgAXLd6CivhlAi6AJBe+PEoaketbIxD4iouBgIUVEvYrF5sBL3x6QP7c7JcV2ZToiSRL+b30uAOCaE7Og1/n+n2ql75PaUVgDABjVL9av19eRbHfghMXmxIFy337uDqeEV753/e7MP2MohqVGo7LBivs/3QFJknDAHX1+9B4kJRraotjLSooI4UqIiHovFlJE1Kt88EsBSswWpMeGYWJmPADIgQ2hcqCsHj/uL0dRTVObAIP2rNtfgf1l9Yg06nDJcRl+PedwuZBSZkdq22Ex1he4/VHAUYETR3wb71u9swSHyhsQE6bHtSdl4dlLjoFBp8GqnaVYvrlQ7kjlqKIj5Sr2kqJMiA4zhHg1RES9kz7UCyAiCpRGq13uKNwxbQgOlNVjU341dhWFrpgwW2w47+X1aLC6xgsjjTrkpERhcEoUZoxMw5mj09p8zdvubtTFx2Ygxs83wWLEbdvhWjicktdnUHXX+v0VqLPYcNaY9E6v2+5O7PPmkGFfjekfi19yq/BHYS3+PMm7QlSSJLzy/UEAri5gdJgBo/rF4q7pQ/GvVXux8POdqLfaASj7DCnhpJwkjB0Qi+kjfBsLJSIi77EjRUS9xrsb8lFRb8XAhAhcNHEARqa7OhOh7EgdLKtHg9UBnVYDvVaDBqsD247UYvnmQtz8/ia5aBL2l9Zh3b5yaDTAtT6GTLQ0PC0akUYd6pvtPXYwr83hxA3v/Y5blm7Gp1uOdHid1e7ETndxG+iOFOAJnNjuQ+DEj/srsKOwFuEGHa45yfN9v2nqIEwYGIe6ZjskCYiPMCBRwYl9Qmy4AZ/fNgV3TBsS6qUQEfVaLKSIqFcwW2x47QdXR+Gu6UNg0Gkx0j3itbvI7NVIXTAUVDUCACZlxmPXo2dizbypeHXOBFx6rKtT8tiKXa2Kqf/7yfXPM0amYmCi/3tb9Dotxg90jTZuyq/y+3F8UVJrQZM7bn3B8h3tjhVKkoQHPtuBZrsTSVEmZAUhCMGfwInFa12dzMuPH4iEFoWSXqfFoovHIdx9YPCQlGhoND3T3SMiImVjIUVEvcLbP+aitsmGwcmROG9cfwDA4OQoGHVa1DXbcaS6qYtHCI68ClchlZUYCaNeiyGp0ThrTDqevHAMbj89B4CnmKpqsGL55kIAwHVTBnX7ucUesd/zq7v9WN5omXZnsTlxy/ubUWextbrm1R8O4qPfj0CrAf510VhogzBy6GvgxO95VfgltwoGnQbXn9y2C5idFImFfxoJjQaYOjQp4OslIiJ1YiFFRKpX3WCVuzrzzxgm7wdyFS6u/Sw7Q7RPKr+yAQCQeVRymkajwfwzhuK20zzF1F/e+Q3NdifGDojFsVnx3X7uSe7H+D2vhwopd7E6ql8M+sWGIbeiAfcs2y53A7/cXoynv94LAFj4p1E4bXhKUNah1WrkbqQ3gRNib9TsCQOQHhve7jWXHDsQWx48A3PdPy8iIiIWUkSkem/+eAj1zXaMSI/BWUeFN4gEt1Dtk8oThVRC2xE2jUaDu2d4iqmth2sAANdNyQ7I+Nj4gfHQalydopJaS7cfrytF7o7UyPQYvHLFRBh0Gny9swRv/ZiLzQXVmP/RVgDAtSdl4arJWUFdyxj3eN8fXeyT2lVkxnd7yqDVADedMrjTa+MijBzrIyIiGQspIlK1qgYr3t2QBwCYN31Im1ExOXAiRB0psUcqs4P9TkcXU/1iw3B2F4l33ooy6eWDeX/vgX1SYrSvf3w4xmXE4aFzRwEA/vn1Hlzn7rZNH5GCB2aNDPpaRIiFKE478r+trlHKs0anIzuJB9cSEZH3WEgRkaq99eMhNFgdGJkegzNGto16HtnPEzzQ0+osNlTUWwF0XEgBnmLq3b8chw9uOAGGAB5Q25PjfaKQ6hfnGo+74viBuGB8fzicEqobbRjVLwYvXDq+R6LYxf6wnUVmNLpjy9sj9o8Fa8yQiIh6LxZSRKRa1S26UXdNH9Lu2NXwdNfhqYU1TahptPbk8pBf6epGJUUZuzwUVaPR4JShycgKcFdEFBSbeiBwQoz2DXAXUhqNBv+4YDQmD0rE8LRovH31sYg09czxhQPiI9AvNgx2p4QtBTXtXmOxOeQ9VJMyu78njYiI+hYWUkSkWm+t77wbBQAxYQYMTHB1g3p6n5QopMTzh8KkrAQArtfe0NxxZ6a7JElq05ECgAijHh/ccDxW3nky0mLDgvb87Tk22/Xaf81tf6zxj8JaWB1OJEUZO+0YEhERtYeFFBGpUnWDFe/8lAcAuLODbpQQqn1S+VWuoIlgnJXkrf5x4UiPDYPDKWFbF/uFuqO60QaLzXVmU3pc64JJo9GEJKThWHcR+Vte+4WUGOubmBnPEAkiIvIZCykiUqWW3agZHXSjhJEhSu7LrxBBE6ENMeiJ86RE9HlytAkmvS5oz+OL49wdqS0FNbC1czCv2Dc2KTOhR9dFRES9AwspIlIdX7pRQOg6UiL6PCsptGNjk3qikGpnrC/UcpKjEBdhQJPN0SYGXZIkbC5wd6QCcGYXERH1PSykiEh13l6fiwarAyO86EYBno7UgbJ6NNsdwV6eTAl7pADPPqkt+dVwOKWgPEfhUUETSqDVauRu09HjfYcqGlDVYIVJr8Vod7IjERGRL1hIEZGq1DRa8Y47qe/OaV13owAgPTYMcREG2J0S9pfWB3mFLhabAyVm1yG4odwjBQDD06IRYdShrtmOfaV1QXmOIrkj1bOBEl05LtvVbfo1t3U3bpN7rO+YAXEw6vl/hURE5Dv+vwcRqcqP+ytQ32xHTkqUV90owBV2II/39dA+KXEQb0yYHnERnUefB5tep8X4gXEAgjfeJ/ZI9VdQRwrwBE78nl8FZ4tunDigmGN9RETkLxZSRKQqe0pchdCxWfHQ+nCwa0/vk8qrEPujIhWRCDfRPeK2qYMEu+4qqlXeHikAGN0/FuEGHWoabThQ7ulGioKS50cREZG/WEgRkarsLXGNpg1Ljfbp63o6uU8p+6MEUTBsKghyRypeWYWUoUU3TpwnVdVgxaFyV6E7kYUUERH5iYUUEanKHlFIpcX49HWikNpdZIYkBSdwoSU5sS/E+6OE8QPjoNUAh6uaUObeuxUoFpsDlQ1WAMob7QPanie1yd2NykmJQlyEMWTrIiIidWMhRUSqUWex4Yi78zE8zbeO1ODkKBh1WtQ12+XHCCaxRyozURkdqegwg1x8BnqflEjsizTqEBse2v1g7RHnSf3m7kiJ/VEc6yMiou5gIUVEqiES51JjTIiP9K2TYNBpMTQtCgCwswf2SXnOkFJGRwpocZ5UXmALqaIWZ0gpYT/Y0cYPjINeq0FRrQVHqhvlxL4JLKSIiKgbWEgRkWr4O9Yn9FRyn9XulPcMZSpkjxQAea/Q9iM1AX1cUUgpbX+UEGHUY1R/11lRPx2owHb34bzsSBERUXewkCIi1RBBEyN8HOsTRCG1JUiBC8KR6kY4JSDcoENytCmoz+WLMe5iYmeROaAH84qiUWmJfS0d5445X/JTHqx2JxIjjchWULeQiIjUh4UUEanGnmLRkfKvkJo6NBkAsPFgJWobbQFb19HyW+yPUtKo26DkKEQYdWiyOXCwPHAHExfWuMIrlBg0IYjACdHVnJAZr6ifDRERqQ8LKSJSBUmS5DOk/C2kBiVHYXhaNOxOCat3lQRyea3kVygrsU/QaTUY5U4v3HGkNmCPW1jjKhyVXEhNchdS8ucc6yMiom5iIUVEqlBitsBssUOn1SAnJcrvxzlrdDoAYOUfwSuk8iqVldjX0mj3eN+OQt8Kqcr6ZqzeWQKbw9nmviLRkVLoHikASIg0tvq9mZTFQoqIiLonpIXUk08+iWOPPRbR0dFISUnB+eefj71797a6xmKxYO7cuUhMTERUVBRmz56N0tLSVtcUFBRg1qxZiIiIQEpKCu655x7Y7faefClEFGRirG9QUiRMep3fjzNrbBoA4Mf95TBbgjPel+9O7MtUWEcK8OyT+sPLQqrUbMFjK3bhpKe+w43/3oRFq/e1ut/plFBcq/w9UoBnvM+o18oFJRERkb9CWkj98MMPmPv/7d1peJNV+j/wb5LuS7rvG5RSKLQgaynIXqEsjoyOC4KIw8Co4LjO/IaR0dFZ+OuMqDiMzrjhiKjgAiMKyiogpbRl6wJlK7SFLtAtXZMmOf8XaUIL3UKzNfl+risvmuc8yTk5tubm3Oc+y5fj8OHD2LlzJ1paWjBjxgw0NDQY2jz99NP45ptvsHnzZvz444+4cuUK7r77bsN1jUaDOXPmQKVS4dChQ/joo4+wfv16vPDCC9YYEhGZyfWKfbeW1qcXF+yNgcFeaNEI7Mov7/6GW3CpdUWqnw2uSPW04ERJdSNWbcnBxFf24v2DhWhu0a1Ebcoqhkp9fVXqar0SLRoBmVSCEBsqrNGR2+MCAejS+noTjBMREQFWDqR27NiBxYsXY+jQoRg+fDjWr1+PoqIiZGdnAwBqa2vx/vvvY82aNZg2bRpGjRqFDz/8EIcOHcLhw4cBAD/88APy8/OxYcMG3HbbbZg1axb+/Oc/Y926dVCpVNYcHhGZUEHr/ihjD+LtyKwkXXrfdzmmT+/TaAWKq1tT+2ywKlzbghMXOik4sbegAlP+vg8bDhdBpdFidIwfPlw8BiFyV1Q1qLD71PUAVH+4cajcDU4y284Wn50Uijfuvw2v3DPM2l0hIiI7YFP/16ut1aWa+Pvr0i+ys7PR0tKC1NRUQ5vBgwcjOjoa6enpAID09HQkJSUhJCTE0GbmzJlQKBTIy8vr8H2USiUUCkW7B5G9qWtuwXc5pdh6/HK7x97TFdCasPS1pehXpAbf4hlSbc1O0qX37T97FXUmTu+7UtOEFo2Ai0yKULmbSV/bFGRSiaEMfGf7pN47cAFqrcDoGD98tmwcNj+agqmDg/GLUZEAgM+zig1trx/Ga3tjvZFEIsG8ERGIsqGzvYiIqO9ysnYH9LRaLZ566ilMmDABiYmJAICysjK4uLjA19e3XduQkBCUlZUZ2rQNovTX9dc6snr1arz00ksmHgGRbXlhax6+Pna5w2t/npeIh8bFWLhHt65FozWU6+5tah8ADArxRmyQJy5cbcCe0xW467aIXr+mnj6tL8rfHTKpbZbXTozwQdalauRcrsXdIyPbXWtQqpFZqDtn69VfDENs0PUCDfeNjsK6veex/8xVlNY2IczHHZf1h/Ha+P4oIiIiU7OZFanly5cjNzcXn332mdnfa+XKlaitrTU8iouLu7+JqA9p0WgN+39Gxfhh/IAAjB8QYFiJ+OjQRQjRd1alLlxtQItGwMvVCZEmqAwnkUgwO1Gf3lfa69dr62KlbZY+b6urghOHzldCpdEi2t/jpgNrYwI8MS7WH1oBfJFVAqDtihQDKSIiciw2sSK1YsUKbNu2Dfv370dk5PV/HQ0NDYVKpUJNTU27Vany8nKEhoYa2hw5cqTd6+mr+unb3MjV1RWurra9KZqoN45eqkadUg0/D2ds+nWKYWWkrrkFyX/bjXMV9Th8oQopAwKs3NOe0Z8fFR/iZbJDVGclheKfe89hX8FVNCjV8HTt+Z9DRXML9pyqwPbcUhwtqmmXKtmo0gCwzYp9ekmR7QtOtF0521dQAQCYMiiow8/6/jFROHyhCpuyi7F8apwhkLLl0udERETmYNUVKSEEVqxYga+//hp79uxB//79210fNWoUnJ2dsXv3bsNzBQUFKCoqQkpKCgAgJSUFOTk5qKioMLTZuXMn5HI5hgwZYpmBENmYfWeuAgAmxQe1+5Ls7eaMeSN0aWwbDl+ySt9uRYF+f1RY7/dH6Q0JkyMmwANKtRZ7Tld02765RYPPM4uw+MMjGPXnnXjq8+P4Pq8cV+uUqGxQGR5NLbpAKjnWv5tXtJ4BQV5wd5ahUaVB4bXrBSeEENhXoPtvZ8qgoA7vnZUYBm83JxRXNSH9QqWh2ARXpIiIyNFYdUVq+fLl2LhxI7Zu3Qpvb2/DniYfHx+4u7vDx8cHS5YswTPPPAN/f3/I5XI88cQTSElJwbhx4wAAM2bMwJAhQ/DQQw/h1VdfRVlZGVatWoXly5dz1YkcVldfhhcmx2BjRhG+zytDhaIZwVYqiLAzvxxhPm49Os/neqGJ3u+P0pNIJJidFIa3953H9txS3Dk8vMv2L32Tj0+PFBl+jgv2wqzEUEwZFAxvt/Z/Sr3dnBDmY7uBhUwqwdBwuWGfVFyw7nM9f7Uel2ua4OIkRUpsYIf3ujnLcNdt4dhwuAifZxYbVqQiGUgREZGDseqK1Ntvv43a2lpMmTIFYWFhhsfnn39uaPP6669j7ty5uOeeezBp0iSEhobiq6++MlyXyWTYtm0bZDIZUlJSsHDhQixatAgvv/yyNYZEZHXlimacKlVAIgEmDbw5kBoSLsfoGD+otQKfZVpnf2D6+Uos/W8W5r97GDWN3R9ToF+RGhRiukAKgGGf1N7TV9Go6vwQbyEEdrWW/P7V7f2x65lJ2PXMZDw7YxBGxfghPsS73cOWgyg9fQB7suT6Pqm9p3UBeHJ/f7i7dH7O0v2jowEAO3LLoGjWfW5ckSIiIkdj1RWpnmx2d3Nzw7p167Bu3bpO28TExOC7774zZdeI+qwfW1ejhkX4IMCr41XZheNikHWpGhszivD4lAEWP//nvQMXAAB1zWq8e+ACfjtzcKdtFc0thspwpih93lZihByRfu4oqW7CjwVXDedL3aigvA5X65Rwd5bht2mD7OIw144KTuw7o98fFdzlvYkRciSEyXGqVLd3zdfD2ag9ZkRERPbAZqr2EZFp6L8MT+7iy/CspFD4e7qgTNGMXae63x9kSuev1mN3mz1JH/50EdfqlZ22169Ghfm4wcfD2aR90af3AcC3XVTvO3j2GgDdvid7CKKAmwtOtC173tn+KD2JRIL7R18vDBTeB1bgiIiITI2BFJEdUWu0OND6pb+rL8OuTjLcNzoKAPBJhmWLTnxwsBAAkJoQjGGRPmhUafDOvvOdttfvjzLF+VEd0QdSe05XoLm1UMSN9rd+phM7SJXsq24sOKEvex7l747YwO4rDs4bEQEXJ93/Qlixj4iIHBEDKSI7crSoBnXNurLnwyN9u2y7IDkaEglw4Ow1XLha32VbU6lqUOHLo7rzh341MRbPzhgEAPj48CWU1TZ3eE9Ba+lzcwVSwyN9EO7jhkaVBj+2Vjtsq7lFg4wLlQCAiQM7LsDQF8mkEgwJ16VK5lyuvV72PD64RyXmfT1cMHOo7oiJaH8P83WUiIjIRjGQIrIj+i/DEwe2L3vekSh/D0xtTf/7JKOoy7amsjHjEppbtEiMkCO5vz8mDQzEmH5+UKq1WLf3XIf36FP7Eky8P0pPIpEY9kZ1dDhv9qVqKNVahMhdMTDYyyx9sBb9PqmcEkW3Zc878sc5CVg6sT+W3N6/+8ZERER2hoEUkR0x9svwwnG66mtfZJegSdVxWpupKNUafJSuSyP81e2xkEgkkEgkhlWpzzKLUFzV2O4eIYTZU/uA6+l9u0/dnN63/6zuM504sOMDavsyfeW+73JKdWXPZVKjDmkOlrvh+TlDWLGPiIgcEgMpIjtRoWhGfmsVtUnxPQukJscHI9LPHbVNLdie23mxBVP45kQprtYpESp3MwQuADAuNgC3xwWiRSPw1p6z7e4pqmpEXbMaTlIJBgSZbzVoRJQvQuVuqFeqDYUl9A6c0e+Psp+0Pr1hrQUnyhS6tMrkWH94uLD6HhERUU8wkCKyE/ta9/cMi/RBYCdlz28kk0rw8xERAIC9BTfvDzIVIYSh5PnD4/sZihToPTMjHgDw5dHLyL1ci63HL2Ppf7Nwx+v7AegKI9x4jylJpRKkJer2+7RN77tapzQEpxPi7C+Q0hec0JvcwwCciIiIGEgR2Q39+VFTjPwyrK9E99O5a9Bquz/b7VYcOl+J02V1cHeW4cGx0TddHxnth+mDg6HRCsx96yCe/Ow4duaXQ6XWIjbIE8/NHGSWfrWlXyXbeaocSrWmtd+61aih4fIeB6d9SduCE0D350cRERHRdczhILIDurLnukCqq/OjOjIi2heeLjJUNaiQX6ow7JsxFSEE3m4tb37f6MhOz4J6ZkY8fjxzFWqtQGygJ+YMC8PspDAMDvW2yN6k0TF+CPZ2RUWdEofOVWLq4GDsP2N/Zc9vlBThg+xL1Yj0c8eAoO7LnhMREZEOV6SIbIQQAseKqg2rIcY4VlwDRbMavh7OuC3K16h7nWVSpAzQpa3pCyuY0hfZJTh47hqcZRL8sovqbkPDffDtbybi+6cmYfezk/HsjEFICJNbrMBD2/S+b3NKIYQwBKf2uD9KLy0xFBIJMH9stN0V0yAiIjInBlJENmLbyVL8/F+H8MctuUbd16TS4PWdZwD0rOx5R/SBwo2FFnqrpLoRL32TDwB4+o54xAR0veIxKNQbgyy0AtWRWYm69L4f8sqQd0WBijol3JylGBXjZ5X+WMK42ACcejkNj08ZYO2uEBER9SkMpIhshD6I+frYZVyrV/bonnqlGg9/eASHzlfCw0WGpRNv7TwffSCVdbEajSr1Lb3GjbRagec2n0C9Uo1RMX749STb/6I+tr8/Ar1coGhW49XvCwAAyf0D4NamIIM9cnOWcTWKiIjISAykiGxEzuVaAECLRuDzzOJu2yuaW7Do/QwcKayCt6sTPl4yFsMifW/pvfsHeiLC1x0qjRYZhVW39Bo3Wn/oIg5fqIK7swyv3Tv8llbKLE0mlWDmUF163/4z9p/WR0RERLeOgRSRDWhu0eBMeZ3h540ZRdB0UUGvplGFhe9l4GhRDXzcnfHJ0mSMivG/5feXSCSYFK8LGPTnJvXGuYo6vLLjNADg+TkJ6BfYd4oYtD3jCrDvQhNERER06xhIEdmAgrI6qLUCvh7O8PVwxuWaJuwrqOiwbVWDCvPfzcDJklr4e7pg49LkW16Jauv2OF3AcPBc7wpOtGi0eGbTCSjVWkyKD8KC5JvLnduy5P7+8GutLBjs7Yr4EPMdBExERER9FwMpIhtwsjWtb1ikL+4dFQkA2HD40k3thBB4dtNxnCpVINDLFZ8tG4eh4aYpVz4hLgASCXCmvB5ltc239BpCCKzZeQYnS2rh4+6MV+8Z1uf23jjJpIbqfRMHBvW5/hMREZFl8Bwpciibs4rx/sHCm9Lm/D1dsHb+CITI3azSr9wSXSCVFCHHvaOi8O6BQuw7cxVFlY2IDvAwtPvy6GXsLbgKF5kUG341FvEh3ibrg6+HC4ZF+uJEcQ0OnL2Ke0dHGXW/Uq3BH7fkYlNWCQDgz/MSEepjnc+zt56bMQg+7i5YPL6ftbtCRERENoorUuQwhBD4xw8FOF1Wh7MV9e0eGYVVWPPDGav1TV9oIinCB/0CPTEpPghCAJ8cub4qVVbbjJe+yQOgKyU+OFRu8n5MjGstg37OuH1S5YpmPPCfw9iUVQKpBHh+dgJ+Njzc5P2zlAAvV/x+1uA+GwgSERGR+TGQIodxqrQO5QrduUAbf5WMT5eOw6dLx+G1e4cDAL44WoLCaw0W71fbQhOJEbo0vYWt+4o2Z5WguUUDIQT+8HUO6prVGB7le8tlzrvT9jwpbRfFLto6WlSNO986iGOthS/WPzIWSyfFmqV/RERERLaCqX3kMPad0RVvGD8gEOPj2pe0/janFHtOV+DNXWfwxgMjLNovfaEJPw9nRPi6AwCmDQ5GuI8brtQ2Y3tuKTRaYM/pCrjIpPjHL4bBSWaefwMZEe0HTxcZKhtUyC9VGAK7zvzvxBU8t+kEVBot4kO88O6i0d0euktERERkD7giRQ5jX4GuGt2UQTeXs37mjngAwNYTV9qVIbcEfVpfYoSPobCBk0yKB1tXpf794wVDSt9TdwzEQBPui7qRi5MUKQMCAAAHznad3qdUa/CHr3Kg0mgxc2gIvnp8AoMoIiIichgMpMghKJpbkH2pGgAwJT74puuJET6YlRgKIYDXd1p2r1Rum/1Rbd03JgpOUglOl9XpUvoifbBsovlT5m437JPqugx6xoUq1CvVCPZ2xdsLRsHLlQvcRERE5DgYSJFD+OnsNWi0ArGBnu2q4LX19B3xkEiA7bllhuDGEk6WdBxIBXu7Gcpwu8ik+Me9w82W0tfWxHjdil1mYTWaVJpO2+0+VQ4AmJ4QDKmUJcKJiIjIsTCQIoegT+ub3EFan158iDfuaq0099oPBRbpV0eFJtp6YtpAxAV74eW7hpo1pa+t2EBPRPi6Q6XRdlq9TwiB3ad1e86mDQ6xSL+IiIiIbAkDKbJ7Qgj8eEa/P+rmtL62nkyNh0wqwd6Cq8i+VGX2vrUtNBHp537T9UGh3tj1zGQ8MDba7H3Rk0gkmNW6ErY5q7jDNmfK61FS3QRXJ6khFZCIiIjIkTCQIrt3uqwOZYpmuDlLkdzfv8u2/QM98YuRkQCA1yxwrlRHhSZswf1jdIfx7jldgat1ypuu72pN6xs/IADuLjKL9o2IiIjIFjCQIrunT+tLiQ2Am3P3X/qfmB4HZ5kEh85XIuuieVelOis0YW0DQ7wxItoXaq3AV0dLbrq+pzWtb3oC0/qIiIjIMTGQIru3r0D3pb+7tD69SD8PzE4KAwBDSqC55NhoIAUA94/WrUp9nlUMIa4fzltZr8TRIl0FxOkJPftMiYiIiOwNAymya3Vty553UWjiRimxurOUMgrNtyLVXaEJa5s7PBweLjJcuNpg+AwBYG/BVQgBDAmTI8zn5n1dRERERI6AgRTZtZ/OXYNaK9A/0NOow2LHtO6lOl5cA6W68xLgvVFQVocWjYBvJ4UmrM3L1QlzWlfmPs+8XnRiz2nd/qhUrkYRERGRA2MgRXbNUPY8vuerUYCuBHiglwtUai1ySsxzplTbtD5bKjTRlr7oxLc5pahXqqFSa7H/jK4kOvdHERERkSNjIEV2SwhhCKSMSesDdCXAx/TTrUqZK70vt03FPls1KsYPsUGeaFRpsO3EFWQUVqJeqUaQt6tN7usiIiIishQGUmS3Csp1Zc9dnaQY17rnyRj6QCrTDJX7hBA4UWK7hSb0JBJJu6ITu0+1HsI7KBhSqW2uohERERFZAgMpsluGsucDelb2/EZjW/dJZV+shkYrumndc80tGjz1+XGcKlVAKgFui/I12Wubw90jI+EkleBYUQ2+PnYZADCN+6OIiIjIwTlZuwNkff/3xUlsyi6GuCFWCPdxw5ePj++zldkOntXt5TF2f5ReQpgcXq5OqFOqcapUYZIUvMs1Tfj1x1nIvayATCrBSz8binBf2/58g7xdMW1wMH7IL0dtUwtcnKSYODDQ2t0iIiIisiquSDm4/CuK1nOCbr52pbYZa3eftXynTECp1hhS8m6Pu7Uv/TKpBKNi/ACYJr0v40IlfvbWQeReVsDf0wUbliRj4biYXr+uJeiLTgDA+AEB8HDhv8EQERGRY2Mg5eDePXABADArMRSZz6caHv/95VgAwKasEly81mDNLt6SY0U1UKq1CPRyRVyw1y2/jj69rzeBlBACH6dfxIL3MlDZoMKQMDn+t2ICUgYYv2/LWibHByHY2xUAMH0w0/qIiIiIGEg5sJLqRvzvxBUAwONT4hDk7Wp4TIoPwtRBQdBoBd7sg6tSh85XAtCtnvSmtLg+kDpSWAXR0bJdN5RqDVZ+lYM/bs2DWitw5/BwfPnYeET6edxyn6zBSSbFa/cNx8MpMbh3dFT3NxARERHZOQZSDuyDgxeh0QpMiAtAUuTN+3+euWMQAGDL8cs4W15n6e71Svp53f6o8b1c9RkW6QMXJymu1atQaOTKXIWiGfP/cxifZRZDIgF+P2sw1j5wG9xdjC98YQsmDgzCS3cl3lLhDiIiIiJ7w0DKQdU0qvBZZhEA4NeTBnTYJinSB2lDQyEE8PquM5bsnkGLRosjhVVQqbU9vqdRpcaxohoAwPgBvSuK4OokM1TVMya971hRNe7850EcLaqB3M0JHy4eg0cnD7DZg3eJiIiIyDgMpBzUhsOX0KjSICFM3mUFtqfviIdEAnyXU2Y4QNaS/v3jedz373Qs+iADDUp1j+7JvFgNtVYgwtcdUf69r4g31siDebcev4z7/30Y5Qol4oK9sHXF7ZgyiPuKiIiIiOwJAykH1NyiwfpDFwEAj06O7XKVZFCoN342PBwA8PpOy65KabUCnx4pBgAcvlCFRR8cgaK5pdv7DrVJ6zPFCtAYIwpONKrU+N0XJ6HSaJGaEIKvHx+P/oGeve4DEREREdkWBlIO6MujJbhWr0KErztmJ4V12/7J6QMhk0qw+3QFjhZVW6CHOocLK3G5pglerk6Quzkh+1I1HnovA7WNXQdT6fpCE3GmqYo3KsYPUglQXNWE0tqmLtseL9ZVCwyVu+E/D42Ct5uzSfpARERERLaFgZSD0WgF3t2vK3n+q4n94Szr/j+B2CAv3DMyAgCw5gfLrUp9kV0CALhzeDg2Lh0HPw9nnCipxfx3D6OqQdXhPbWNLYYUxJRY0xwa6+XqhKHhumIcR7pJ78u+qAs0R/fzg1TK/VBERERE9oqBlIP5Ia8MFysb4evh3O6Q1e48MW0gnGUSHDx3zSKrUg1KNXbklgEAfjEqEokRPvhsWQoCvVyQX6rAA/9Jx9U65U33ZRRWQiuA2CBPhPq4maw/PT1PKutSayDVepAvEREREdknBlIO5j+tB/AuGhcDDxenHt8X5e+BucN0e6W2HLtslr619V1OKRpVGvQP9MTIaF8Auv1any1LQYjcFWfK6/F/X5686b6250eZ0pjWghOZhZ0HkVqtMASZo1vbExEREZF9YiDlQLIvVeNYUQ1cZFI8lNLP6Pvvuk0XSH17shQtmp6XI78VXx7VpfXdMzKiXcGIuGAvfLwkGc4yCfacrsCu/PJ29xn2R/Wy7PmNxvTTrTAVlNehupO0wjMVdahrVsPDRYbBod4mfX8iIiIisi0MpPqgL7NLMOxP3+O5zSdw4Wp9j+/74GAhAF1AFOTtavT73h4XiABPF1Q2qHDw3DWj7++p4qpGHL5QBYkE+PnIyJuux4d4Y8ntsQCAl7bloblFAwC4WqdEQevBweNiTbsiFeDlikEhuuDoxzNXO2yT1bo/akS0L5x6sPeMiIiIiPouftvrYzRagTU7z0DRrMYX2SVIXfMjnvj0GE6XKbq8r6S6EdtzSwEASyb2v6X3dpJJMXeYrsrf/45fuaXX6ImvjupSB8cPCECEb8fnQD0xLQ5hPm4ormrC2/vOAwAOX9CtRiWEyeHv6WLyfs0YGgIAhs/xRtmt+6NGxTCtj4iIiMjeMZDqYw6cvYrLNU3wcXdGakIwtAL45sQVpL1xAMv+m4WKuuYO7/vo0EVoBTAhLgCDQ+W3/P4/u01Xve/7vDI0qTS3/DqdEUK0Seu7eTVKz9PVCavmDAEAvP3jeRRVNpptf5TerERdELmv4GqHhwNnXdIVomChCSIiIiL7x0Cqj9mYUQQAuHtkBN57eAy++81EzBkWBokE+CG/HI9tOHrT/qV6pRqftR5s+6vWlLhbNTLaF5F+7mhUabDrVHn3Nxgp82I1iqoa4ekiQ1piaJdtZyeFYkJcAFRqLV76Jg/pbQ7iNYeEMG/EBHhAqdZiX0H79L4KRTOKq5oglehS+4iIiIjIvjGQ6kPKFc3YfboCAPDg2GgAwJBwOdY9OBLf/WYivFsPrf3HDwXt7tucVYw6pRqxQZ6YHB/Uqz5IJBJD0YmtZkjv+7L17KjZSWHdVhWUSCR46WdD4dR6WPDFykbIpBJDqXJTk0gkhuDuxvQ+fdnzQaFyHsJLRERE5AAYSPUhm7OKodEKjOnnh4Eh7avCJYTJ8fdfDAMA/PvHC9hzWrdapNEKfPjTRQDALyf0N8khsXe1pvf9eKYCNY0dV7C7FTWNKnybowtQfjGq87S+tuKCvdvt+UqK8DFrIDO7Nb1vz+kKQ5EL4HqhCab1ERERETkGBlJ9hFYr8Glret781tWoG6UlhmHx+H4AgGc3ncCVmibszC9HUZXuAN6u9hwZIz7EGwlhcrRoBL7LKTPJawLAW3vOoV6pxuBQb8O5TT3xm2kDESrXHb5rrrQ+vWGRPojw1aU27m9TvS9bvz+qHwMpIiIiIkfAQKqPOHDuGi7XNEHu5oTZSWGdtls5ezCSInxQ3diCJz49hvdaD+B9cGw03F1kJuvP9fQ+0xzOW3itAf9NvwgAeH5OglErZ56uTli3YCTm3RaOxRP6maQ/nWmf3qcLIptUGuRd0VVNHMUVKSIiIiKHwECqj9iYcQkAcPfISLg5dx4QuTrJsO7BkfB21e2XyrpUDWeZBA+3rlSZyp3DdYHUkYtVuFLT1OvX+3/bT6FFIzB1UBAmDjR+H9eoGD+88cAIBHu79bov3ZnVGkjtOlUOlVqL48U1UGsFQuVunZZrJyIiIiL7wkCqD6hQNGPXqdYiE8kdp/W1FR3ggVda90sBwNxh4QiRmzbAiPB1x9h+/hAC2Hayd0UnDl+oxPd55ZBJJfjD7AQT9dB8Rkb7IdjbFXXNavx0/pohrW9UPz9IJL3fg0ZEREREto+BVB+wObsEGq3A6Bg/xN9QZKIzs5PC8JtpcYjwdcfyqXFm6dfPWtP7thy79UBKqxX4y7f5AHTphzcW0bBFUmmb9L6cUkPFPhaaICIiInIcDKRsnEqtxadHdGdHdVZkojPPzBiEn34/DXHBXuboGmYnhcFJKkF+qQL5rXuEOiKEwHsHLmDt7rOorFe2u/b1scvIvayAt6sTnkodaJZ+moM+kPohvxxHDYGUecquExEREZHtYSBlw5pbNHh0QzZKqpvg6+HcZZEJa/D3dMGMoSEAgE9a93B15EhhFf7y7Sms2XkGt7+yF3/elo9yRTMaVWr8/XvdmVcrpsUhwMvVIv02hbH9/BHg6YKaxhYomtXwcJEhIcz2V9OIiIiIyDQYSNmoJpUGv/ooC3tOV8DNWYq35o8wadU9U1k4LgaAbmWprrmlwzYftVbj83J1QlOLBu8fLMTEV/biwXczUKZoRpS/u8mLYZibk0xqCCIB4LYoXzjJ+OtERERE5Cj4zc8G1SvVePjDIzh47ho8XGRY/8jYW6pkZwkpsQEYEOSJRpUGXx+7uRT6lZomfJ+nOxz4i8dS8NEvx2J0jB9UGl21OwD4fVpCl5UIbVVa4vUVQpY9JyIiInIsDKRsjKK5BYvez8CRwip4uzrh4yVjMS7WvIfM9oZEIjGsSm04fAlCiHbXNxy+BI1WYFysPwaHyjE5PgibH03Bp0vH4Y4hIViUEoPZSaHW6HqvjR8QAB93ZwAw6gBhIiIiIur7nKzdAbquplGFRR8cwcmSWvi4O+PjJWMxLNLX2t3q1t0jI/HqjgKcKa/HkcIqJLcGfs0tGkOhjMXj+xvaSyQSpAwIQMoA2w0Qe8JZJsXa+SOQe7kWt8cFWrs7RERERGRBXJGyIceKa5B7uRb+ni74dOm4PhFEAYCPuzPmjdCVQt+QUWR4/n8nrqC6sQURvu5ITQi2VvfManJ8EJZPjYNUyvOjiIiIiBwJAykbMnVQMNbOH4HPl43DkHC5tbtjlAXJuvS+HbmlqKhrhhACHx26CAB4KCWGhRiIiIiIyK7w262NmTssvE8cSnujxAgfjIj2RYtGYFNmMbIuVSPvigJuzlI8MCbK2t0jIiIiIjIp7pEik3loXAyOFdVgY0YR8loP6J13WwR8PVys3DMiIiIiItPiihSZzOykMPh5OONKbTO255YBQJ87H4qIiIiIqCcYSJHJuDnLcN/o62l8yf39kRDWt/Z6ERERERH1hFUDqf379+POO+9EeHg4JBIJtmzZ0u66EAIvvPACwsLC4O7ujtTUVJw9e7Zdm6qqKixYsAByuRy+vr5YsmQJ6uvrLTgKauvB5GhIWgvYPTKhn1X7QkRERERkLlYNpBoaGjB8+HCsW7euw+uvvvoq1q5di3feeQcZGRnw9PTEzJkz0dzcbGizYMEC5OXlYefOndi2bRv279+PZcuWWWoIdIOYAE88PzsBv5zQH3cM6ZsH7RIRERERdUcihBDW7gSgO6T166+/xrx58wDoVqPCw8Px7LPP4rnnngMA1NbWIiQkBOvXr8cDDzyAU6dOYciQIcjMzMTo0aMBADt27MDs2bNRUlKC8PDwHr23QqGAj48PamtrIZczFY2IiIiIyFH1NDaw2T1ShYWFKCsrQ2pqquE5Hx8fJCcnIz09HQCQnp4OX19fQxAFAKmpqZBKpcjIyOj0tZVKJRQKRbsHERERERFRT9lsIFVWpqv6FhIS0u75kJAQw7WysjIEBwe3u+7k5AR/f39Dm46sXr0aPj4+hkdUFM85IiIiIiKinrPZQMqcVq5cidraWsOjuLjY2l0iIiIiIqI+xGYDqdBQXaGC8vLyds+Xl5cbroWGhqKioqLddbVajaqqKkObjri6ukIul7d7EBERERER9ZTNBlL9+/dHaGgodu/ebXhOoVAgIyMDKSkpAICUlBTU1NQgOzvb0GbPnj3QarVITk62eJ+JiIiIiMgxOFnzzevr63Hu3DnDz4WFhTh+/Dj8/f0RHR2Np556Cn/5y18wcOBA9O/fH3/84x8RHh5uqOyXkJCAtLQ0LF26FO+88w5aWlqwYsUKPPDAAz2u2EdERERERGQsqwZSWVlZmDp1quHnZ555BgDw8MMPY/369fjd736HhoYGLFu2DDU1Nbj99tuxY8cOuLm5Ge755JNPsGLFCkyfPh1SqRT33HMP1q5da/GxEBERERGR47CZc6SsiedIERERERERYAfnSBEREREREdkqBlJERERERERGYiBFRERERERkJAZSRERERERERmIgRUREREREZCQGUkREREREREZiIEVERERERGQkBlJERERERERGYiBFRERERERkJAZSRERERERERnKydgdsgRACAKBQKKzcEyIiIiIisiZ9TKCPETrDQApAXV0dACAqKsrKPSEiIiIiIltQV1cHHx+fTq9LRHehlgPQarW4cuUKvL29IZFIrN0dh6FQKBAVFYXi4mLI5XJrd4dMhPNqnziv9otza584r/aJ82oZQgjU1dUhPDwcUmnnO6G4IgVAKpUiMjLS2t1wWHK5nH8M7BDn1T5xXu0X59Y+cV7tE+fV/LpaidJjsQkiIiIiIiIjMZAiIiIiIiIyEgMpshpXV1e8+OKLcHV1tXZXyIQ4r/aJ82q/OLf2ifNqnzivtoXFJoiIiIiIiIzEFSkiIiIiIiIjMZAiIiIiIiIyEgMpIiIiIiIiIzGQIiIiIiIiMhIDKeqV/fv3484770R4eDgkEgm2bNnS7np5eTkWL16M8PBweHh4IC0tDWfPnm3XZsqUKZBIJO0ejz76aLs2RUVFmDNnDjw8PBAcHIzf/va3UKvV5h6ew7LEvJ44cQLz589HVFQU3N3dkZCQgDfffNMSw3NYlvp91ausrERkZCQkEglqamrMNCoCLDu369evx7Bhw+Dm5obg4GAsX77cnENzaJaa18zMTEyfPh2+vr7w8/PDzJkzceLECXMPz2GZYl4BID09HdOmTYOnpyfkcjkmTZqEpqYmw/WqqiosWLAAcrkcvr6+WLJkCerr6809PIfCQIp6paGhAcOHD8e6detuuiaEwLx583DhwgVs3boVx44dQ0xMDFJTU9HQ0NCu7dKlS1FaWmp4vPrqq4ZrGo0Gc+bMgUqlwqFDh/DRRx9h/fr1eOGFF8w+PkdliXnNzs5GcHAwNmzYgLy8PDz//PNYuXIl/vnPf5p9fI7KEvPa1pIlSzBs2DCzjIXas9TcrlmzBs8//zx+//vfIy8vD7t27cLMmTPNOjZHZol5ra+vR1paGqKjo5GRkYGDBw/C29sbM2fOREtLi9nH6IhMMa/p6elIS0vDjBkzcOTIEWRmZmLFihWQSq9/tV+wYAHy8vKwc+dObNu2Dfv378eyZcssMkaHIYhMBID4+uuvDT8XFBQIACI3N9fwnEajEUFBQeLdd981PDd58mTx5JNPdvq63333nZBKpaKsrMzw3Ntvvy3kcrlQKpUmHQPdzFzz2pHHH39cTJ06tbddph4w97z+61//EpMnTxa7d+8WAER1dbUJe09dMdfcVlVVCXd3d7Fr1y5zdJu6Ya55zczMFABEUVGR4bmTJ08KAOLs2bMmHQPd7FbnNTk5WaxatarT183PzxcARGZmpuG57du3C4lEIi5fvmzaQTgwrkiR2SiVSgCAm5ub4TmpVApXV1ccPHiwXdtPPvkEgYGBSExMxMqVK9HY2Gi4lp6ejqSkJISEhBiemzlzJhQKBfLy8sw8CrqRqea1I7W1tfD39zd9p6lbppzX/Px8vPzyy/jvf//b7l9HyTpMNbc7d+6EVqvF5cuXkZCQgMjISNx3330oLi62zECoHVPN66BBgxAQEID3338fKpUKTU1NeP/995GQkIB+/fpZZCx0XU/mtaKiAhkZGQgODsb48eMREhKCyZMnt5v39PR0+Pr6YvTo0YbnUlNTIZVKkZGRYaHR2D/+H47MZvDgwYiOjsbKlStRXV0NlUqFV155BSUlJSgtLTW0e/DBB7Fhwwbs3bsXK1euxMcff4yFCxcarpeVlbULogAYfi4rK7PMYMjAVPN6o0OHDuHzzz9n2oGVmGpelUol5s+fj7///e+Ijo62xlDoBqaa2wsXLkCr1eJvf/sb3njjDXzxxReoqqrCHXfcAZVKZY2hOTRTzau3tzf27duHDRs2wN3dHV5eXtixYwe2b98OJycnawzNofVkXi9cuAAA+NOf/oSlS5dix44dGDlyJKZPn27YS1VWVobg4OB2r+3k5AR/f39+dzIh/oaQ2Tg7O+Orr77CkiVL4O/vD5lMhtTUVMyaNQtCCEO7tl+ck5KSEBYWhunTp+P8+fMYMGCANbpOXTDHvObm5uKuu+7Ciy++iBkzZlhsLHSdqeZ15cqVSEhI6DJoJssy1dxqtVq0tLRg7dq1ht/TTz/9FKGhodi7dy/3SlmYqea1qakJS5YswYQJE/Dpp59Co9HgH//4B+bMmYPMzEy4u7tbY3gOqyfzqtVqAQC//vWv8cgjjwAARowYgd27d+ODDz7A6tWrrdZ/R8MVKTKrUaNG4fjx46ipqUFpaSl27NiByspKxMbGdnpPcnIyAODcuXMAgNDQUJSXl7dro/85NDTUTD2nrphiXvXy8/Mxffp0LFu2DKtWrTJrv6lrppjXPXv2YPPmzXBycoKTkxOmT58OAAgMDMSLL75o/kFQh0wxt2FhYQCAIUOGGNoEBQUhMDAQRUVFZuw9dcYU87px40ZcvHgRH374IcaMGYNx48Zh48aNKCwsxNatWy0yDmqvu3nt6HcRABISEgy/i6GhoaioqGh3Xa1Wo6qqit+dTIiBFFmEj48PgoKCcPbsWWRlZeGuu+7qtO3x48cBXP9DkZKSgpycnHZ/EHbu3Am5XH7THxGyrN7MKwDk5eVh6tSpePjhh/HXv/7V3N2lHurNvH755Zc4ceIEjh8/juPHj+O9994DABw4cIBlsm1Ab+Z2woQJAICCggJDm6qqKly7dg0xMTHm6zR1qzfz2tjYCKlUColEYmij/1m/8kHW0dm89uvXD+Hh4e1+FwHgzJkzht/FlJQU1NTUIDs723B9z5490Gq1hmCaTMCalS6o76urqxPHjh0Tx44dEwDEmjVrxLFjx8SlS5eEEEJs2rRJ7N27V5w/f15s2bJFxMTEiLvvvttw/7lz58TLL78ssrKyRGFhodi6dauIjY0VkyZNMrRRq9UiMTFRzJgxQxw/flzs2LFDBAUFiZUrV1p8vI7CEvOak5MjgoKCxMKFC0VpaanhUVFRYfHxOgpLzOuN9u7dy6p9FmCpub3rrrvE0KFDxU8//SRycnLE3LlzxZAhQ4RKpbLoeB2FJeb11KlTwtXVVTz22GMiPz9f5ObmioULFwofHx9x5coVi4/ZEfR2XoUQ4vXXXxdyuVxs3rxZnD17VqxatUq4ubmJc+fOGdqkpaWJESNGiIyMDHHw4EExcOBAMX/+fIuO1d4xkKJe0X9JuvHx8MMPCyGEePPNN0VkZKRwdnYW0dHRYtWqVe1KlhcVFYlJkyYJf39/4erqKuLi4sRvf/tbUVtb2+59Ll68KGbNmiXc3d1FYGCgePbZZ0VLS4slh+pQLDGvL774YofvERMTY+HROg5L/b529J4MpMzLUnNbW1srfvnLXwpfX1/h7+8vfv7zn7crm02mZal5/eGHH8SECROEj4+P8PPzE9OmTRPp6emWHKpD6e286q1evVpERkYKDw8PkZKSIg4cONDuemVlpZg/f77w8vIScrlcPPLII6Kurs4SQ3QYEiHa7EgkIiIiIiKibnGPFBERERERkZEYSBERERERERmJgRQREREREZGRGEgREREREREZiYEUERERERGRkRhIERERERERGYmBFBERERERkZEYSBERERERERmJgRQREREREZGRGEgREZFdWbx4MSQSCSQSCZydnRESEoI77rgDH3zwAbRabY9fZ/369fD19TVfR4mIqE9jIEVERHYnLS0NpaWluHjxIrZv346pU6fiySefxNy5c6FWq63dPSIisgMMpIiIyO64uroiNDQUERERGDlyJP7whz9g69at2L59O9avXw8AWLNmDZKSkuDp6YmoqCg8/vjjqK+vBwDs27cPjzzyCGpraw2rW3/6058AAEqlEs899xwiIiLg6emJ5ORk7Nu3zzoDJSIiq2EgRUREDmHatGkYPnw4vvrqKwCAVCrF2rVrkZeXh48++gh79uzB7373OwDA+PHj8cYbb0Aul6O0tBSlpaV47rnnAAArVqxAeno6PvvsM5w8eRL33nsv0tLScPbsWauNjYiILE8ihBDW7gQREZGpLF68GDU1NdiyZctN1x544AGcPHkS+fn5N1374osv8Oijj+LatWsAdHuknnrqKdTU1BjaFBUVITY2FkVFRQgPDzc8n5qairFjx+Jvf/ubycdDRES2ycnaHSAiIrIUIQQkEgkAYNeuXVi9ejVOnz4NhUIBtVqN5uZmNDY2wsPDo8P7c3JyoNFoEB8f3+55pVKJgIAAs/efiIhsBwMpIiJyGKdOnUL//v1x8eJFzJ07F4899hj++te/wt/fHwcPHsSSJUugUqk6DaTq6+shk8mQnZ0NmUzW7pqXl5clhkBERDaCgRQRETmEPXv2ICcnB08//TSys7Oh1Wrx2muvQSrVbRfetGlTu/YuLi7QaDTtnhsxYgQ0Gg0qKiowceJEi/WdiIhsDwMpIiKyO0qlEmVlZdBoNCgvL8eOHTuwevVqzJ07F4sWLUJubi5aWlrw1ltv4c4778RPP/2Ed955p91r9OvXD/X19di9ezeGDx8ODw8PxMfHY8GCBVi0aBFee+01jBgxAlevXsXu3bsxbNgwzJkzx0ojJiIiS2PVPiIisjs7duxAWFgY+vXrh7S0NOzduxdr167F1q1bIZPJMHz4cKxZswavvPIKEhMT8cknn2D16tXtXmP8+PF49NFHcf/99yMoKAivvvoqAODDDz/EokWL8Oyzz2LQoEGYN28eMjMzER0dbY2hEhGRlbBqHxERERERkZG4IkVERERERGQkBlJERERERERGYiBFRERERERkJAZSRERERERERmIgRUREREREZCQGUkREREREREZiIEVERERERGQkBlJERERERERGYiBFRERERERkJAZSRERERERERmIgRUREREREZKT/DwkxUR0QsHfzAAAAAElFTkSuQmCC\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Preprocess the data\n",
        "df.index = pd.to_datetime(df.index)\n",
        "df['Passengers'] = df['Passengers'].astype(float)\n",
        "\n",
        "train_size = int(len(df) * 0.8)\n",
        "train, test = df.iloc[:train_size], df.iloc[train_size:]"
      ],
      "metadata": {
        "id": "iG-zNjk6cjPJ"
      },
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Build and evaluate ARIMA model\n",
        "model = ARIMA(train['Passengers'], order=(5, 1, 0))\n",
        "model_fit = model.fit()\n",
        "print(model_fit.summary())\n",
        "\n",
        "predictions = model_fit.forecast(steps=len(test))\n",
        "\n",
        "mse = mean_squared_error(test['Passengers'], predictions)\n",
        "mae = mean_absolute_error(test['Passengers'], predictions)\n",
        "print(f\"MSE: {mse}, MAE: {mae}\")\n",
        "\n",
        "plt.figure(figsize=(10, 6))\n",
        "plt.plot(train.index, train['Passengers'], label='Training Data')\n",
        "plt.plot(test.index, test['Passengers'], label='Actual Data')\n",
        "plt.plot(test.index, predictions, label='Predicted Data')\n",
        "plt.title('ARIMA Forecasting')\n",
        "plt.xlabel('Date')\n",
        "plt.ylabel('Number of Passengers')\n",
        "plt.legend()\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "9GI7DUGfctU5",
        "outputId": "89d4c519-046f-4e72-8393-d89665ab6fdc"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.11/dist-packages/statsmodels/tsa/base/tsa_model.py:473: ValueWarning: No frequency information was provided, so inferred frequency MS will be used.\n",
            "  self._init_dates(dates, freq)\n",
            "/usr/local/lib/python3.11/dist-packages/statsmodels/tsa/base/tsa_model.py:473: ValueWarning: No frequency information was provided, so inferred frequency MS will be used.\n",
            "  self._init_dates(dates, freq)\n",
            "/usr/local/lib/python3.11/dist-packages/statsmodels/tsa/base/tsa_model.py:473: ValueWarning: No frequency information was provided, so inferred frequency MS will be used.\n",
            "  self._init_dates(dates, freq)\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "                               SARIMAX Results                                \n",
            "==============================================================================\n",
            "Dep. Variable:             Passengers   No. Observations:                  115\n",
            "Model:                 ARIMA(5, 1, 0)   Log Likelihood                -524.549\n",
            "Date:                Mon, 10 Feb 2025   AIC                           1061.098\n",
            "Time:                        15:20:53   BIC                           1077.515\n",
            "Sample:                    01-01-1949   HQIC                          1067.760\n",
            "                         - 07-01-1958                                         \n",
            "Covariance Type:                  opg                                         \n",
            "==============================================================================\n",
            "                 coef    std err          z      P>|z|      [0.025      0.975]\n",
            "------------------------------------------------------------------------------\n",
            "ar.L1          0.3558      0.092      3.854      0.000       0.175       0.537\n",
            "ar.L2         -0.2644      0.109     -2.422      0.015      -0.478      -0.050\n",
            "ar.L3          0.0847      0.078      1.089      0.276      -0.068       0.237\n",
            "ar.L4         -0.3179      0.088     -3.621      0.000      -0.490      -0.146\n",
            "ar.L5          0.0748      0.106      0.704      0.482      -0.133       0.283\n",
            "sigma2       578.0868     98.904      5.845      0.000     384.239     771.935\n",
            "===================================================================================\n",
            "Ljung-Box (L1) (Q):                   0.01   Jarque-Bera (JB):                 4.12\n",
            "Prob(Q):                              0.94   Prob(JB):                         0.13\n",
            "Heteroskedasticity (H):               5.78   Skew:                             0.29\n",
            "Prob(H) (two-sided):                  0.00   Kurtosis:                         2.27\n",
            "===================================================================================\n",
            "\n",
            "Warnings:\n",
            "[1] Covariance matrix calculated using the outer product of gradients (complex-step).\n",
            "MSE: 6506.6720690672255, MAE: 67.3835005901074\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    }
  ]
}