ComparingTradingVolume.ipynb

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              "                        Date        Open        High         Low       Close  \\\n",
              "0  2022-02-01 00:00:00-05:00  174.009995  174.839996  172.309998  174.610001   \n",
              "1  2022-02-02 00:00:00-05:00  174.750000  175.880005  173.330002  175.839996   \n",
              "2  2022-02-03 00:00:00-05:00  174.479996  176.240005  172.119995  172.899994   \n",
              "3  2022-02-04 00:00:00-05:00  171.679993  174.100006  170.679993  172.389999   \n",
              "4  2022-02-07 00:00:00-05:00  172.860001  173.949997  170.949997  171.660004   \n",
              "\n",
              "    Adj Close    Volume  \n",
              "0  173.602448  86213900  \n",
              "1  174.825348  84914300  \n",
              "2  171.902313  89418100  \n",
              "3  171.613632  82465400  \n",
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        }
      ],
      "source": [
        "import pandas\n",
        "\n",
        "aapl = pandas.read_csv(\"aapl.csv\")\n",
        "\n",
        "aapl.head()"
      ]
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    {
      "cell_type": "code",
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        "aapl.tail()\n"
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              "                          Date        Open        High         Low  \\\n",
              "246  2023-01-25 00:00:00-05:00  140.889999  142.429993  138.809998   \n",
              "247  2023-01-26 00:00:00-05:00  143.169998  144.250000  141.899994   \n",
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              "250  2023-01-31 00:00:00-05:00  142.699997  144.339996  142.279999   \n",
              "\n",
              "          Close   Adj Close    Volume  \n",
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              "        document.querySelector('#df-ece947ff-a318-4150-bd96-0930926168c7 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-ece947ff-a318-4150-bd96-0930926168c7');\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-a5a3cd42-f5e9-4808-9114-6589590bd485\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-a5a3cd42-f5e9-4808-9114-6589590bd485')\"\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-a5a3cd42-f5e9-4808-9114-6589590bd485 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "amzn = pandas.read_csv(\"amzn.csv\")\n",
        "\n",
        "amzn.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "sR2HnReRlmHz",
        "outputId": "b3f06b7d-4d6b-4f85-960b-956bfd26e5be"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                        Date        Open        High         Low       Close  \\\n",
              "0  2022-02-01 00:00:00-05:00  150.000000  151.707993  147.627502  151.193497   \n",
              "1  2022-02-02 00:00:00-05:00  155.050507  155.074997  148.863495  150.612503   \n",
              "2  2022-02-03 00:00:00-05:00  141.737503  144.247498  138.332993  138.845505   \n",
              "3  2022-02-04 00:00:00-05:00  155.606506  161.199997  150.608002  157.639496   \n",
              "4  2022-02-07 00:00:00-05:00  158.520004  162.690994  157.250000  157.935501   \n",
              "\n",
              "    Adj Close     Volume  \n",
              "0  151.193497   59220000  \n",
              "1  150.612503   87330000  \n",
              "2  138.845505  225532000  \n",
              "3  157.639496  253456000  \n",
              "4  157.935501  102624000  "
            ],
            "text/html": [
              "\n",
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              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "\n",
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              "\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date</th>\n",
              "      <th>Open</th>\n",
              "      <th>High</th>\n",
              "      <th>Low</th>\n",
              "      <th>Close</th>\n",
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              "      <th>Volume</th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2022-02-01 00:00:00-05:00</td>\n",
              "      <td>150.000000</td>\n",
              "      <td>151.707993</td>\n",
              "      <td>147.627502</td>\n",
              "      <td>151.193497</td>\n",
              "      <td>151.193497</td>\n",
              "      <td>59220000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2022-02-02 00:00:00-05:00</td>\n",
              "      <td>155.050507</td>\n",
              "      <td>155.074997</td>\n",
              "      <td>148.863495</td>\n",
              "      <td>150.612503</td>\n",
              "      <td>150.612503</td>\n",
              "      <td>87330000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2022-02-03 00:00:00-05:00</td>\n",
              "      <td>141.737503</td>\n",
              "      <td>144.247498</td>\n",
              "      <td>138.332993</td>\n",
              "      <td>138.845505</td>\n",
              "      <td>138.845505</td>\n",
              "      <td>225532000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2022-02-04 00:00:00-05:00</td>\n",
              "      <td>155.606506</td>\n",
              "      <td>161.199997</td>\n",
              "      <td>150.608002</td>\n",
              "      <td>157.639496</td>\n",
              "      <td>157.639496</td>\n",
              "      <td>253456000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2022-02-07 00:00:00-05:00</td>\n",
              "      <td>158.520004</td>\n",
              "      <td>162.690994</td>\n",
              "      <td>157.250000</td>\n",
              "      <td>157.935501</td>\n",
              "      <td>157.935501</td>\n",
              "      <td>102624000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-8baed9f8-8278-4432-b089-ef1823791aae')\"\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 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .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-8baed9f8-8278-4432-b089-ef1823791aae 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-8baed9f8-8278-4432-b089-ef1823791aae');\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-90c5f582-386b-4a2d-b52c-2a083354c4d5\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-90c5f582-386b-4a2d-b52c-2a083354c4d5')\"\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-90c5f582-386b-4a2d-b52c-2a083354c4d5 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "amzn.tail()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "8EFokBWnltST",
        "outputId": "214192bf-2ee3-4fdf-ab0a-836539b544e9"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                          Date        Open        High         Low  \\\n",
              "246  2023-01-25 00:00:00-05:00   92.559998   97.239998   91.519997   \n",
              "247  2023-01-26 00:00:00-05:00   98.239998   99.489998   96.919998   \n",
              "248  2023-01-27 00:00:00-05:00   99.529999  103.489998   99.529999   \n",
              "249  2023-01-30 00:00:00-05:00  101.089996  101.739998   99.010002   \n",
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              "\n",
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          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "csco = pandas.read_csv(\"csco.csv\")\n",
        "\n",
        "csco.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "1MmZoJ4FlyIP",
        "outputId": "6fe68cab-f15f-413f-bed2-e76cbbe87ea5"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                        Date       Open       High        Low      Close  \\\n",
              "0  2022-02-01 00:00:00-05:00  55.450001  55.500000  54.740002  55.369999   \n",
              "1  2022-02-02 00:00:00-05:00  55.230000  56.320000  55.169998  56.169998   \n",
              "2  2022-02-03 00:00:00-05:00  55.869999  56.150002  55.060001  55.200001   \n",
              "3  2022-02-04 00:00:00-05:00  54.889999  55.619999  54.389999  55.150002   \n",
              "4  2022-02-07 00:00:00-05:00  55.330002  55.529999  54.700001  55.169998   \n",
              "\n",
              "   Adj Close    Volume  \n",
              "0  53.573200  22438500  \n",
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              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
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              "          + ' to learn more about interactive tables.';\n",
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              "<div id=\"df-909f3f31-d2a7-436e-a793-75881bc2c135\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-909f3f31-d2a7-436e-a793-75881bc2c135')\"\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",
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              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
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              "    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-909f3f31-d2a7-436e-a793-75881bc2c135 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "csco.tail()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "dD35HmDLl7cs",
        "outputId": "acf94407-5411-46d5-f18d-5f350112e838"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                          Date       Open       High        Low      Close  \\\n",
              "246  2023-01-25 00:00:00-05:00  47.980000  48.080002  47.230000  47.980000   \n",
              "247  2023-01-26 00:00:00-05:00  48.150002  48.470001  47.830002  48.340000   \n",
              "248  2023-01-27 00:00:00-05:00  48.099998  48.730000  47.970001  48.509998   \n",
              "249  2023-01-30 00:00:00-05:00  48.139999  48.500000  48.119999  48.220001   \n",
              "250  2023-01-31 00:00:00-05:00  48.119999  48.689999  48.049999  48.669998   \n",
              "\n",
              "     Adj Close    Volume  \n",
              "246  47.980000  14638700  \n",
              "247  48.340000  12952700  \n",
              "248  48.509998  13414200  \n",
              "249  48.220001  19261900  \n",
              "250  48.669998  16821600  "
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              "<table border=\"1\" class=\"dataframe\">\n",
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              "      <th>Date</th>\n",
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              "      <td>2023-01-25 00:00:00-05:00</td>\n",
              "      <td>47.980000</td>\n",
              "      <td>48.080002</td>\n",
              "      <td>47.230000</td>\n",
              "      <td>47.980000</td>\n",
              "      <td>47.980000</td>\n",
              "      <td>14638700</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>247</th>\n",
              "      <td>2023-01-26 00:00:00-05:00</td>\n",
              "      <td>48.150002</td>\n",
              "      <td>48.470001</td>\n",
              "      <td>47.830002</td>\n",
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              "    <tr>\n",
              "      <th>249</th>\n",
              "      <td>2023-01-30 00:00:00-05:00</td>\n",
              "      <td>48.139999</td>\n",
              "      <td>48.500000</td>\n",
              "      <td>48.119999</td>\n",
              "      <td>48.220001</td>\n",
              "      <td>48.220001</td>\n",
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              "      <th>250</th>\n",
              "      <td>2023-01-31 00:00:00-05:00</td>\n",
              "      <td>48.119999</td>\n",
              "      <td>48.689999</td>\n",
              "      <td>48.049999</td>\n",
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              "      <td>48.669998</td>\n",
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              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
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              "      border-radius: 50%;\n",
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              "      margin-bottom: 4px;\n",
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              "    [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-130f65fa-54b3-4c44-abfe-9fbd88534d21 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-130f65fa-54b3-4c44-abfe-9fbd88534d21');\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",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
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              "      --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",
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              "      --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",
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              "    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",
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              "    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",
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              "    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-0a35edf7-b109-45d8-80d5-013b74d1b124 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ford = pandas.read_csv(\"ford.csv\")\n",
        "\n",
        "ford.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "kFsv68jOl9nn",
        "outputId": "641c7922-ddbd-4419-eb53-57b0018409f0"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                        Date       Open       High        Low      Close  \\\n",
              "0  2022-02-01 00:00:00-05:00  20.610001  20.850000  19.920000  20.660000   \n",
              "1  2022-02-02 00:00:00-05:00  20.809999  21.049999  20.180000  20.629999   \n",
              "2  2022-02-03 00:00:00-05:00  20.170000  20.620001  19.870001  19.889999   \n",
              "3  2022-02-04 00:00:00-05:00  18.520000  18.590000  17.520000  17.959999   \n",
              "4  2022-02-07 00:00:00-05:00  17.730000  18.120001  17.700001  17.889999   \n",
              "\n",
              "   Adj Close     Volume  \n",
              "0  20.110569  117651800  \n",
              "1  20.081366   95377600  \n",
              "2  19.361046  103016000  \n",
              "3  17.482370  211100500  \n",
              "4  17.414232   84610000  "
            ],
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              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "      <th></th>\n",
              "      <th>Date</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",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2022-02-01 00:00:00-05:00</td>\n",
              "      <td>20.610001</td>\n",
              "      <td>20.850000</td>\n",
              "      <td>19.920000</td>\n",
              "      <td>20.660000</td>\n",
              "      <td>20.110569</td>\n",
              "      <td>117651800</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2022-02-02 00:00:00-05:00</td>\n",
              "      <td>20.809999</td>\n",
              "      <td>21.049999</td>\n",
              "      <td>20.180000</td>\n",
              "      <td>20.629999</td>\n",
              "      <td>20.081366</td>\n",
              "      <td>95377600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2022-02-03 00:00:00-05:00</td>\n",
              "      <td>20.170000</td>\n",
              "      <td>20.620001</td>\n",
              "      <td>19.870001</td>\n",
              "      <td>19.889999</td>\n",
              "      <td>19.361046</td>\n",
              "      <td>103016000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2022-02-04 00:00:00-05:00</td>\n",
              "      <td>18.520000</td>\n",
              "      <td>18.590000</td>\n",
              "      <td>17.520000</td>\n",
              "      <td>17.959999</td>\n",
              "      <td>17.482370</td>\n",
              "      <td>211100500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2022-02-07 00:00:00-05:00</td>\n",
              "      <td>17.730000</td>\n",
              "      <td>18.120001</td>\n",
              "      <td>17.700001</td>\n",
              "      <td>17.889999</td>\n",
              "      <td>17.414232</td>\n",
              "      <td>84610000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-c2db738a-f287-4a04-a373-afa2067a30ce')\"\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 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .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-c2db738a-f287-4a04-a373-afa2067a30ce 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-c2db738a-f287-4a04-a373-afa2067a30ce');\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-f06a231b-d517-4079-bf3d-159ce3d976ad\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-f06a231b-d517-4079-bf3d-159ce3d976ad')\"\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-f06a231b-d517-4079-bf3d-159ce3d976ad button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ford.tail()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "TH8-w9r8mEhg",
        "outputId": "b8444c56-0873-4e96-bb18-b06a72f87abe"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                          Date   Open   High    Low  Close  Adj Close  \\\n",
              "246  2023-01-25 00:00:00-05:00  12.60  12.85  12.49  12.79      12.79   \n",
              "247  2023-01-26 00:00:00-05:00  12.99  13.07  12.71  12.92      12.92   \n",
              "248  2023-01-27 00:00:00-05:00  12.88  13.37  12.87  13.27      13.27   \n",
              "249  2023-01-30 00:00:00-05:00  13.01  13.20  12.86  12.89      12.89   \n",
              "250  2023-01-31 00:00:00-05:00  13.39  13.57  13.25  13.51      13.51   \n",
              "\n",
              "       Volume  \n",
              "246  37739000  \n",
              "247  48970900  \n",
              "248  62066500  \n",
              "249  64512600  \n",
              "250  83093300  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-a1cdcf2f-5db4-4486-a0dd-d1a62480397f\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date</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",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>246</th>\n",
              "      <td>2023-01-25 00:00:00-05:00</td>\n",
              "      <td>12.60</td>\n",
              "      <td>12.85</td>\n",
              "      <td>12.49</td>\n",
              "      <td>12.79</td>\n",
              "      <td>12.79</td>\n",
              "      <td>37739000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>247</th>\n",
              "      <td>2023-01-26 00:00:00-05:00</td>\n",
              "      <td>12.99</td>\n",
              "      <td>13.07</td>\n",
              "      <td>12.71</td>\n",
              "      <td>12.92</td>\n",
              "      <td>12.92</td>\n",
              "      <td>48970900</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>248</th>\n",
              "      <td>2023-01-27 00:00:00-05:00</td>\n",
              "      <td>12.88</td>\n",
              "      <td>13.37</td>\n",
              "      <td>12.87</td>\n",
              "      <td>13.27</td>\n",
              "      <td>13.27</td>\n",
              "      <td>62066500</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>249</th>\n",
              "      <td>2023-01-30 00:00:00-05:00</td>\n",
              "      <td>13.01</td>\n",
              "      <td>13.20</td>\n",
              "      <td>12.86</td>\n",
              "      <td>12.89</td>\n",
              "      <td>12.89</td>\n",
              "      <td>64512600</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>250</th>\n",
              "      <td>2023-01-31 00:00:00-05:00</td>\n",
              "      <td>13.39</td>\n",
              "      <td>13.57</td>\n",
              "      <td>13.25</td>\n",
              "      <td>13.51</td>\n",
              "      <td>13.51</td>\n",
              "      <td>83093300</td>\n",
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              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-a1cdcf2f-5db4-4486-a0dd-d1a62480397f')\"\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 -960 960 960\">\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .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-a1cdcf2f-5db4-4486-a0dd-d1a62480397f 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-a1cdcf2f-5db4-4486-a0dd-d1a62480397f');\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-88459ed6-906e-4883-8202-955f68d62f15\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-88459ed6-906e-4883-8202-955f68d62f15')\"\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-88459ed6-906e-4883-8202-955f68d62f15 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# New Section Comparing trading volume of stocks with NumPY\n"
      ],
      "metadata": {
        "id": "7s3Uvi9umVxp"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "aapl_volume_average = aapl[\"Volume\"].mean()\n",
        "print(aapl_volume_average)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YK7Wvw4Hmn6-",
        "outputId": "090807cf-2a7d-4e5e-b20b-68f12ea1e1ae"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "85259773.70517929\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "amzn_volume_average = amzn[\"Volume\"].mean()\n",
        "print(amzn_volume_average)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "jyJ8mAW-otdX",
        "outputId": "e1f62603-c86b-43b0-d547-adac70d09fca"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "76075050.59760956\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "csco_volume_average = csco[\"Volume\"].mean()\n",
        "print(csco_volume_average)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "eWn-oOX_o79F",
        "outputId": "3b658be7-9557-4079-c0f6-73f026b1ad35"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "20673897.609561753\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ford_volume_average = ford[\"Volume\"].mean()\n",
        "print(ford_volume_average)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dNenuO9YpHpj",
        "outputId": "3be9844c-19e2-4e56-a6d1-c138e6340725"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "65473899.20318725\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy\n",
        "\n",
        "volume_averages = numpy.array([aapl_volume_average,\n",
        "                               amzn_volume_average,\n",
        "                               csco_volume_average,\n",
        "                               ford_volume_average])\n",
        "\n",
        "print(volume_averages)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZDnOvpn-pbwA",
        "outputId": "cc7c0489-ab67-42c4-e9b2-774408c65988"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[85259773.70517929 76075050.59760956 20673897.60956175 65473899.20318725]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [],
      "metadata": {
        "id": "34uep-sbrv-v"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as pyplot\n",
        "\n",
        "labels =[\"Apple\",\"Amazon\",\"Cisco\",\"Ford\"]\n",
        "\n",
        "\n",
        "pyplot.pie(volume_averages,labels=labels,autopct = \"%.2f\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 621
        },
        "id": "sWYZ64UDp6Bw",
        "outputId": "58b10af2-1939-4d97-f060-ee825497aca2"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "([<matplotlib.patches.Wedge at 0x7d150b8630a0>,\n",
              "  <matplotlib.patches.Wedge at 0x7d150b862fb0>,\n",
              "  <matplotlib.patches.Wedge at 0x7d150b863d90>,\n",
              "  <matplotlib.patches.Wedge at 0x7d15096b0460>],\n",
              " [Text(0.5162243538966687, 0.9713456729938973, 'Apple'),\n",
              "  Text(-1.0999301106459403, 0.01239966509263741, 'Amazon'),\n",
              "  Text(-0.3812342189610647, -1.0318238562337794, 'Cisco'),\n",
              "  Text(0.7414388325668605, -0.8125690478734044, 'Ford')],\n",
              " [Text(0.28157692030727377, 0.5298249125421257, '34.45'),\n",
              "  Text(-0.5999618785341492, 0.006763453686893133, '30.74'),\n",
              "  Text(-0.20794593761512617, -0.5628130124911523, '8.35'),\n",
              "  Text(0.4044211814001057, -0.44321948065822053, '26.46')])"
            ]
          },
          "metadata": {},
          "execution_count": 15
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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eO0LKlWO24LHlu2F3cA3JlmA5KZm1GvjkTsDifWt8aSrzsDxhjegYRK2y9VgxZnzNCRItwXJSsi8mAvn7Radwm6TTX+CJxGOiYxC1yvtbsvDZ7tOiYygOy0mpfnkPOPCp6BRu92jlHCT714iOQdQqT3+2HwdzOUGiOVhOSlRwyKsmQFyIuroIH8UpfxYi+bZauxOTP97DFSSageWkNPZa4LMHALvvHE3E56zHc8kZomMQtcqRwkq8uv6w6BiKwXJSmo0vAQUHRKfwuPvK5qK90SI6BlGrLN2WhZ+OKGtpMVFYTkpy7Adg2zzRKYRQW4rxYfTHomMQtYokAVNW7UNZNVdBuRiVJElcpVAJqkuA+QOBCt++tcSHsc/i+RNdRcdQrIrfvkbFb1/DXlYAANBGJMJ0+e3wT+3TYDtJklC4ahpqTuxC5M3PIqDDgCbtv/ibuajcswGhQx9A8GU31T9+ev59cJQXNtjWdOU9COl/WyvfkTJd1yMW8+64RHQMWfMTHYCa6Mt/+nwxAcCdpfPwcdAsHKwwio6iSJqgcIReeQ/8QuMAAJUHNqLws+mIHf8WdJFJ9dtV7FwLqJq37+rMrajNzYAmMKzR74cMuhNBPa+p/71K59/8N+AlvtqXh6s6n8bNvRNER5EtDuspwZ4VQDrXmwMAdY0ZH0QsEx1DsQLa9YN/6mXQhsVDGxaP0L/dDbXOgNrcsxNOrAXHUb5jDSJGTm7yfu0VZ1Dy3XuIuP5JQN34Z161LgCawND6L7XO0Nq3o2gvrD2IHDPPo54Py0nuqoqBb54RnUJWwvM2Y2aKcldflwvJ6UDVoc1w2mqgj+8EAHDaanDmy1kIG/4wNIGhTduP5MSZdW8guN8tDY6+/qrsl1XIfut25L4/CWW/rIbk9O1p1RU1djyxcg94ZqVxHNaTu++e98rliVrrtuJ3sDx4NvaUB4qOojjWoizkf/gkJLsVKp0/om5+FrqIRABA6cZF0Md3RkD7/k3eX/n2T6FSaxB06Y3n3Sb40hugi0mF2hCE2px0mDcvhaOyBGHDHmj1+1Gy7cdL8Mmv2fh730TRUWSHR05ylvUzsOcj0SlkSVVbgffDloqOoUjasHjE3jsHMXe/gaDeI3HmqzdhPXMK1Ud+Qc2pvQhtRmHU5h9F+a4vEH7tZKhU5z9JFdz3ZhgSe0AX1RZBva9F6NAJqNi9DpKds9Ze3XCYq5c3grP15MpuBd4dCJzJFJ1E1tbGP4l/HuOsp9Yo+PhZ+JliofLToWLXl8CfS0ZyAio19AldEHPHq+c8t/zXtSj936JGn6MJikDCw4sbfU1r0UnkLX4Ucfe/C204JwWMviQBs8f0FB1DVjisJ1db32IxNcGNRfPxkWk2dpiDRUdRLEmSIDlsMA26E4E9hzf4Xt7ixxA69H74t+vb6HON3YbAkNzwh2rhyhdg7DoUgd2vOu9rWguPAyo11EZTq/N7g9W7T+O2PgnonxIuOopscFhPjkqOAz++LjqFIqisVVgU8j5UKg4ANEXp5iWoyT4Ae1kBrEVZKN28BLWn9sPYZTA0gaHQRSY3+AIAv+BIaE0x9fvIWfgQqjO3AgA0/sHnPkftB40xtP6IqDYnHeW/roW18Dhs5nxUHvwBpf9bBGPXwdAYeM7wDy+sPcB7P/0Jj5zk6KsnfWrtvNYKLvgF76T+ioePNv7pns5yVJXhzLo34KgqgVpvhC4yGVFjXoJ/295N3oe95DSctdVNf1GNFlXpP8K8ZTngsMEvJBrBfW5C8GU3t+AdeK/Mgkp8uP0k7h3YVnQUWeA5J7lJX1d3A0FqFkkbgLu0s/FzSYjoKEQtFmzww6YpQxBm1ImOIhyH9eTEYQe+f1F0CkVS2arxbuAiaFQcFiHlKq+xY9Y3XLkcYDnJy673geKjolMoVmDhLixst110DKJW+eTXbBzKLRcdQziWk1zUlAObzp2qS80zJHchhoXzomVSLqcEvPk9Z+qynORi6xyg+ozoFIqnctTibf8F0Ks5vEfK9d2hAuw7bRYdQyiWkxxUFgHb54tO4TUCzuzDotSfRccgapXZ3/r20RPLSQ5+mg1YK0Wn8CqDchdjZCSPREm5NmcWYddJ3x2iZjmJZs4Gdja+xAu1nMphxZu6d+Gv8e2Vr0nZfPnoieUk2s9vAo5a0Sm8kqH4EJakbBYdg6jFth4rxrZjxaJjCMFyEqmyiKuOu1nfnCW4Jbrw4hsSydQb32VcfCMvxHISacd7XKbIzVROO/6jng+jH4f3SJl+zSrFj5lFomN4HMtJlNpKYMdC0Sl8gr40Ax+23Sg6BlGLzdl4RHQEj2M5ibJ7KVBjFp3CZ/Q+/SHGxuaLjkHUIjtPlmL/6TLRMTyK5SSCwwZse0d0Cp+ikhx4WZqLEK1ddBSiFnl/6wnRETyK5STC/k+B8tOiU/gcnfk4Pkr+RnQMohZZty8PZyp9Z2Yvy8nTJKluqSISomv2ctwTlyM6BlGzWe1OLP/llOgYHsNy8rTjm4DCQ6JT+CwVJDxnn4twnU10FKJm++iXk7D5yN1yWU6etnup6AQ+T1t+EsuTvhYdg6jZCspr8fX+PNExPILl5EnVJcDhr0SnIAAdslfiHwm+M0RC3mPp1izRETyC5eRJe1cADqvoFIS64b1/1b6NGD3/f5Cy7D5l9onbabCcPGn3h6IT0J/4VeRgeeIXomMQNdsH206KjuB2LCdPyd4BFKWLTkF/kZL9GSYm+tb1I6R8Gw7ko8bm3UtysZw8ZRcnQsjV5Oq5iDf4zvUjpHyVtXZ8n14gOoZbsZw8obYCOLhGdAo6D01lHpYn8P8PKcvaPbmiI7gVy8kTDq4BbFWiU9AFJJ3+Ak8mHRUdg6jJNmcUoczivdfrsZw84eDnohNQEzxS8TaS/XkLE1IGq8OJ9V58zRPLyd0sZuDEj6JTUBOoq4vwUdxK0TGImsybh/ZYTu6WsR5weu+ht7eJz9mA55J9886jpDy/nChGQbl3Hu2znNwt/UvRCaiZ7iubi/ZGi+gYRBfllIAv93rn0RPLyZ1qK4FjvAOr0qgtxVgWvUJ0DKIm8dahPZaTOx35FrB75yG3t4vO/R7TUw6KjkF0UftzypBf5n0/Z1hO7pTOpXGU7M7iuegaxEsASP5+PFIkOoLLsZzcxVYDHPlOdApqBVVtGT6IWCY6BtFF/ZjJcqKmOrkFsFaKTkGtFJ63GTNT94qOQXRBPx89A6dTEh3DpVhO7sJrm7zGbWfewSUh/KBB8mWutmFfTpnoGC7FcnIXlpPXUNVWIC10KVQq7/pkSt7F24b2WE7uUFMG5HEoyJuE5m/BW6m7RccgOi+WE11c1hZA8u57rfiiGwreRT9TuegYRI3ak21GeY33rEbDcnIHDul5JZWtCgtDFnN4j2TJ7pSw9egZ0TFchuXkDiwnrxVcsAPzU3eIjkHUqJ+OsJzofKrOAIWHRKcgNxqRvwB/CzOLjkF0jj3ZZtERXIbl5GpZPwHgsI83U9kteMe4CH4qp+goRA1kFlSgxuYd57tZTq6W+5voBOQBgUW7saDdNtExiBqwOSSk53nHpB2Wk6txCrnPGJK7CMPCS0THIGpg32nvuBiX5eRqeftEJyAPUTlq8bb/AujVHN4j+dh72iw6gkuwnFzJfAqw8JO0Lwk4sw9pqT+JjkFUj0dOdC4O6fmkgTmLcW2k90zhJWU7XlSJylq76BitxnJyJZaTT1I5bXhD9y78Nd4xS4qUzSkBB7xgEViWkyuxnHyWofgQlqZsEh2DCACwzwvOO7GcXImTIXzaZTlLcUt0oegYRDiYq/zp5CwnV6kqBirzRacggVROO/6jfgdGPw7vkVgni6tFR2g1lpOrlJ4QnYBkQF+aiWUp34uOQT7uVAnLif5QmiU6AclEr+wP8ffYPNExyIeVVFkVP2OP5eQqPHKi36kkJ16S5iFEq+wfDqRsJ4urREdoFZaTq/DIif5EZz6Oj5I3iI5BPuyUws87sZxcpSRLdAKSma7ZK3BPXI7oGOSjTir8vBPLyVV45ER/oYKE5+xzEa7znltnk3IofcYey8kV7FagIld0CpIhbflJLE/6SnQM8kGnSnjOicynAIkrU1PjOmSvwoMJp0THIB/DIyfiURNdkAoSptS+jRi9VXQU8iH5ZTWiI7QKy8kVqnmbDLowv4ocLG+zVnQM8iF2p6Toa51YTq7AezhRE6ScXoN/Jh4XHYN8iLlauUfrLCdXsJSKTkAKMalqLhIMtaJjkI8osyh3pijLyRU4rEdNpKnKx/KEz0THIB9RVs1y8m0Ws+gEpCCJp7/Ev5KOiI5BPoBHTr6Ow3rUTA9VvI2UAGXPpiL5M7OcfBwnRFAzqavPYFnsStExyMv53JHTtm3boNFocN1117k6jzLxyIlaIC5nA55ve1h0DPJiZgWfc/JryZPS0tIwceJEpKWlITc3F3Fxca7OpSxW+S8TMv9XK+bvtCLLXLeSRdcoDV74mw4j22sBADV2CU98U4OPD9pRa5cwop0f3rnWgOjA839+Uf278VtBz7xKjykD9Q0eq7VL6LeoCnsLnPjtQSN6xWhc9M6U7V7zXHxinIXMKn/RUcgL+dSRU2VlJT755BM8/PDDuO6667BkyZL6723atAkqlQrffPMNevfuDX9/fwwdOhSFhYVYv349OnfujODgYNxxxx2orj67tMaGDRswaNAgmEwmhIeH4/rrr8exY8fqvz9t2jSoVKpzvv547draWkyaNAlRUVEwGAwYNGgQfv3113Nybdy4EX369EFAQAAuv/xyZGRktOCPrBEO+V9LkBCswqtX6bHrH0bs/IcRQ5M1uOljCw4W1t1S/P821ODLTDtW3eaPzeONyK2QcMtKywX3mfdEYIOvxTcaoAIwuov2nG3/9V0t4oI4ivxXaksJlkUvFx2DvFSVL12Eu3LlSnTq1AkdO3bEuHHjsHjxYkiS1GCbadOmYe7cudi6dSuys7MxZswY/Pe//8Xy5cvx1Vdf4dtvv8Xbb79dv31VVRUef/xx7Ny5Exs3boRarcbNN98Mp7PuU/6TTz6JvLy8+q/XX38dAQEB6NOnDwDgX//6F1avXo2lS5di9+7daNeuHUaMGIGSkobngp599lnMnj0bO3fuhJ+fH+67775m/4E1SgHldENHLa5tr0X7cA06hGswY5gBgTpg+2kHymokpP1mwxsjDBja1g+Xxmnw/k0GbM12YPvp8//ljglUN/ham2HHkLYapIQ2/Gu1/ogN3x634/Xh+vPsybdF5W7EjJQDomOQF3L85WezkjS7nNLS0jBu3DgAwDXXXIOysjJs3ry5wTbTp0/HwIED0bt3b0yYMAGbN2/G/Pnz0bt3b1xxxRW49dZb8cMPP9RvP3r0aNxyyy1o164devXqhcWLF2P//v04dOgQACAwMBAxMTGIiYlBVlYWnnvuObz//vvo1q0bqqqqMH/+fMyaNQsjR45Ely5dsHDhQvj7+yMtLa1BrhkzZuDKK69Ely5dMHXqVGzduhU1NS6YMeVQ1qGzwynh4wM2VNmAAW002JXngM0JXJVydpS3U4QGiSEqbMt2NGmfBZVOfHXEjgm9dec8/sCXNfjwZn8EaFUufR/e5I7ieegaJP/hYVIWp9NHyikjIwM7duzA7bffDgDw8/PD2LFjzymBHj161P93dHQ0AgICkJKS0uCxwsLC+t8fOXIEt99+O1JSUhAcHIzk5GQAwKlTDVdyPnXqFEaNGoUnn3wSY8aMAQAcO3YMNpsNAwcOrN9Oq9Wib9++SE9PP2+u2NhYAGiQo8Wcyjh03l/gQOAr5dBPr8BD6yxYM9YfXSI1yK+UoNMAJkPD8og2qpBf2bS/3Ev32hCkA27pfLbgJEnC+LUWPNRHhz5xPMd0IaraMnwQsUx0DPIyTgUfOTVrQkRaWhrsdnuDCRCSJEGv12Pu3Ln1j2m1Z885qFSqBr//47E/huwA4IYbbkBSUhIWLlyIuLg4OJ1OdOvWDVbr2eGyqqoq3HjjjRgwYABeeuml5sQ+by4ADXK0mEJul9ExQo09DwWirEbCp4dsuOfzGmwe75rzQIt/s+HO7loY/M4W3Ns7rKioBZ4epLvAM+kP4Xmb8XpKfzx5vKfoKOQlHMr40dSoJpeT3W7HBx98gNmzZ2P48OENvjdq1CisWLECnTp1anaA4uJiZGRkYOHChbjiiisAAD///HODbSRJwrhx4+B0OvHhhx/WFwsApKamQqfTYcuWLUhKSgIA2Gw2/Prrr5g8eXKz83gznUaFdmF1f3aXxmnwa64Db223Ymw3LawOwFwjNTh6KqiSEBN48aG4n07akVHsxCe3Npxx9r8TDmw77YB+ekWDx/ssqMKdPbRYOooz1P6qo/Qbvj64Q3QM8hJa3SUA+oiO0SJNLqd169ahtLQUEyZMQEhISIPvjR49GmlpaZg1a1azA4SGhiI8PBwLFixAbGwsTp06halTpzbYZtq0afj+++/x7bfforKyEpWVlQCAkJAQGI1GPPzww5gyZQrCwsKQmJiImTNnorq6GhMmTGh2Hl/ilIBaB3BprAZaNbDxuL1+pl3GGQdOlUkY0Obiw3Fpv9lwaawaPf8yPXzOSAOmDz07rJBbIWHEsmp8cqs/+iVwmO+vckMTsd7uhxuOcHIEuYahTbzoCC3W5HJKS0vDVVdddU4xAXXlNHPmTOzbt6/ZAdRqNT7++GNMmjQJ3bp1Q8eOHTFnzhwMHjy4fpvNmzejsrISl19+eYPnvv/++xg/fjxeffVVOJ1O3HXXXaioqECfPn3wzTffIDQ0tNl5vNXT39dgZHs/JIaoUVErYfl+GzZlOfDNOD1CDCpM6K3F49/WIMxfhWC9ChPX12BAggb9E/40SWJuJf4zTI+bO58dHi2vlbDqkA2zhxvOec3EkIZDhoG6ujGG1DA1EoI5rfzPnCo1nklqj35H+edCLqRW7iQklfTXeeDUfK/EA9ZK0SkuaMJaCzaesCOvUkKIXoUe0Wo8NVCPq1PryuePi3BXHLCh1gGMSPXDO9cZEPOni3BV/y7H+zcZML7X2XNIC3ZZMXlDDfKeCEKI4cL/ELLMTrR9q5IX4TZiYc+RmFN+EC+c7I1uy3+9+BOImiDo6quR8PYc0TFahOXkCq93BCrzRacghToY3x3jDFWwO+1449AlSFjLc07kGsHXX4/415t/ukUOOIbgCjqj6ASkUNU6I6aGGmH//XKEoEplXJZAyqA2KvdnE8vJFfSBohOQQs3sNhhZVbn1v/cvl/9qI6Qc6kCWk2/TBYlOQAq0sf0VWF26v8FjOjNXiSDX4ZGTr+OwHjVTUXAM/q02n/O4urTxld6JWkLDcvJxHNajZpCgwnOp3VFqLWvwuAYqOM1l53kWUfOpA5X7s4nl5Ao65f4FIM/7qPsIbDWfe7uWeEcIYOeECHIdDuv5Oj3POVHTZEZ3wpvVRxv9XhsrP+SQa6mNyv07xXJyhYAw0QlIAawaPaZGRcDqbHxGXrxNuT9ISJ78IsJFR2gxlpMrBCeITkAK8GaPq3Gk8tR5vx9dw9XbybX8oqNFR2gxlpMrBMddfBvyaVtT+uMj8/4LbhNe3aw72BBdkEqrhUbB64uynFyB5UQXUGoMx3P6Gki48EphpiquJEau4xcV1eD2QkrDcnKFYOUuS0/uN63jZSiqKbnodoGVDg+kIV/hFxUlOkKrsJxcQWsA/Dkpgs71ader8L/SQ03a1r+81s1pyJco+XwTwHJynRAePVFDJyNSMNOa3eTttVy6iFxIG80jJwI4tEcN2NV+mBrfBha7pcnPUXHpInIhv5hY0RFaheXkKiwn+pN3eozAgfITTd5eI6kglZrdF4h8jq5tsugIrcJycpXwdqITkEzsSrwUaeUHm/WcNo4QwOl0UyLyRfrUVNERWoXl5CpRnUUnIBmoMITgmUAVnFLziibRFuymROSLVHo9tPHKHs1hOblKVBfRCUgGpncZiFxLYbOfF2cNcEMa8lW6pCSo1Mr+8a7s9HISFA0EKHcdK2q9rzoNwdelB1r03GiL3sVpyJfpUlJER2g1lpMrRXJoz1flhiZihrOgxc8Pt2hcmIZ8nZ7lRA1EdRKdgARwqtR4OqkdKmyVLd5HCJcuIhfikRM1xEkRPimtxzXYXdb4PZqaKrCSNxkk1zF0Vv4HZZaTK3FShM85EN8d71QebvV+DGU1LkhDVHdrdh45UUNRXQAodxVgap5qnRFTQ42wO1t/1KM1V7sgERFg6NZN0auR/4Hl5Er+JiCig+gU5CEzuw3Gyapcl+xLVVrmkv0Q+XfvLjqCS7CcXC2xv+gE5AEb21+B1aUXvnlgU+kkDSQzy4lcw9CD5USNSRwgOgG5WVFwDKapzS7bX6I9BJA4W49cw79HD9ERXILl5Go8cvJqElR4LrU7zFbXHem0sXPpInINv6goaBV+H6c/sJxcLawtEKTsperp/JZ1H4Gt5gyX7jO21uDS/ZHv8u/ZU3QEl2E5uUObfqITkBtkRnfCf6tbdz1TY6JruHQRuUZAf+/52cNycgeed/I6Vo0eU6MiYHVaXb7vsGouXUSuYRxwuegILsNycgeed/I6b/a4CkcqT7ll3yYuXUQu4BcbC31KW9ExXIbl5A4x3QGDSXQKcpGtKf3xkbllq403hbHC5rZ9k+8w9veuD8UsJ3dQa4B2V4lOQS5QagzHc/oaSHDf0Y2hvNZt+ybfYbzcu04nsJzcpeNI0QnIBV7seBmKakrc+hp+pS1fzZzoD8YBLCdqinZXAWo/0SmoFT7tejV+KD3k9tfh0kXUWvoOHeAXESE6hkuxnNzF3wS08a4xYF+SFZmKmVb3TID4M4PkB6m8wu2vQ94tcMgQ0RFcjuXkTh2vEZ2AWsCm1mJqXAIsdovbXyvJbuLSRdRqQVdfLTqCy7Gc3KkDy0mJ5vcYjoPlJzzyWgn2QI+8DnkvbXw8/Lt1FR3D5VhO7hTRHghLFZ2CmmFX4qVIKz/osdeLq/H32GuRdwq6yjtnBrOc3I2z9hSjwhCCpwMBp+T02GtGcekiaqWg4d43pAewnNyv2y2iE1ATTe8yEHmWIo++Zlg1/wlSy2kiI+Dfu7foGG7BfxnuFn8p746rAOs6DcHXpe5bBeJ8Qrh0EbVC0LBhUKm988e4d74ruekxVnQCuoDc0ES84iwQ8tpcuohaI/jaa0VHcBuWkyf0GAtAJToFNcKpUuPppHaosIlZpcFQViPkdUn5tImJCLjsMtEx3Ibl5AmmNkDyINEpqBGLelyD3WWuv0dTU/mZuXQRtYzp5lFQqbz3Qy/LyVN6/l10AvqLA/HdMb/isNgQJVy6iFpArUbIqFGiU7gVy8lTutwE+PGaFrmo1hkxNdQIu2QXliHAqYVUwaWLqPmM/ftDGxsrOoZbsZw8RR8EdLpOdAr63cxug3GyKldohmSHSejrk3KFjPb+S1RYTp506T2iExCAje2vwOrS/aJjIMHKpYuo+dQhIV67KsSfsZw8qe3fgCjvWwNLSYqCYzBNbRYdAwAQaw0QHYEUKOT666HWe//KIiwnT+v/kOgEPkuCCs+mdofZKo9JCFEWregIpDQqFULH3Sk6hUewnDyt+xggIFx0Cp+0rPsIbDNniI5Rj0sXUXMZBw2Cvm1b0TE8gv86PE1rAC69V3QKn5MZ3Qn/rRZ3PVNjgis9t8AseYewu+8SHcFjeB9xEfo+AGx5C3By6RpPqPUz4KmocFgrs0VHacBYIW4ae2stKC7G95UVOF5rhUGtQi9/fzwRGYm2uobnQvZYLHjrTBH2WSxQq1TopNdjYUIbGJqwHtzC4mK8eaYId4WG4umoaJftV6l07VJhHOQ7F/OznEQIigG6jgL2rxKdxCf8t8dVOFq6T3SMc+jLqkVHaLGd1dW43WRCN4M/HJKE/54pwv3Z2fiybQoCfi+IPRYL/nE6Gw+EheOZqGj4qYDDNbVNGq7Zb7FgZZkZHRs58d+a/SpZ+PjxXr0ixF+pJIn3iBYiZxewcKjoFF5vS0p/PCzlQYL8/pqvWhYNKTtHdAyXKLHbMejYUXzQJhF9AupmIf79ZBYuNxoxKSKyWfuqcjpxa9YJPB8dg/eKz6CTwdDgyKml+1UyTUQE2v1vI9Q6negoHuPtHzbkK/5SIPFy0Sm8WqkxHM/pamRZTACAErPoBC5T4aw7fxai0QAAiu127KupQZhGgztOnsQVR4/g7lMnsav64keL0wvycWVgIC43Gs/5Xmv2q2Rhd93lU8UEsJzEuvJfohN4tRc7XoYztSWiYzQqyKmHVFUlOoZLOCUJrxYW4BJ/f7T/fRjutK3ufOq8M2dwqykE7yW0QReDAfedzkaW1XrefX1dXo5DNbX4v/McFbV0v0qmMZkQeqdvTB//M5aTSKlDgDb9RafwSqu6Xo0fSg+JjnFeyfYQ0RFc5uWCAhyprcXrsXH1jzl/P1odYwrFLSEmdDEYMDUqGm21OnxWZm50P3k2G/5TWICZsbHQn2diQ0v2q3Rh990HTeC5R5HejhMiRBv8FPDhzaJTeJWsyFTMqj0pOsYFJdiCREdwiekF+dhcVYkP2iQiRnv2ouJITd2PltS/DEWl6HXIszU+S/FgTQ2KHQ7cejKr/jEHgJ0WC5aXlmJPh44t2q+SaUJDEXbnHaJjCMFyEi11aN3RU/Z20Um8gk2txdS4BFjKT4iOckExNQbREVpFkiTMKCzA95WVWNImEQl/KYt4rRZRfn7IsjUcasuyWnGFsfE1BQcYA7A2ueEFps/m56GtTof7w8KhUalatF8lC59wH9SNnHvzBRzWk4Nhz4tO4DXe6TEcB2VeTAAQVaPsk9svFxbgy/JyzIqNg1GtRpHdjiK7HTW/T4xQqVS4LzQMy0pL8U1FOU5arZhzpggnrFaMDjk7pHlv9il8VFoKADCqNWiv1zf48lepYNJo6s9lNXW/3kATHu6T55r+wCMnOUgeBKQMAY7/IDqJou1MuhSLyw+KjtEkodXKvl7lY7MZAHBP9qkGj8+IicHNISYAwN1hYaiVJLxWWIgyhwMd9QYsSmiDxD8dZWVbrSh1NG84rin79QbhEyZA7e+794DjdU5ykbMbWDhEdArFqjCEYHRKO+RZikRHaZJ3fuuFiA07RccgmfKLiUHqhvVQG5Q9/NsaHNaTi/hLgC6jRKdQrJe7DFRMMQGAsYJLV9H5RT3xuE8XE8Bykpfh03kr9xZY12ko1pceEB2jWfRlFtERSKb8e/ZE8PXXi44hHMtJTkxtgEH/JzqFouSEJeIVZ77oGM2mMVeKjkBypFIh+pmnfWoNvfNhOcnNwH8CpiTRKRTBodLgmcR2qLAp8Ad9canoBCRDwddfD/+ePUXHkAWWk9xoDcCIV0SnUIS0HiOwu0xe92hqihCnAZKFw3rUkMrfH1FPPC46hmywnOSo8/V1F+fSeR2I7475FYdFx2iRZJt3XY9DrhE+YQK0MTGiY8gGy0murnkNUGsvvp0PqtYZMTXUCLukzOVqvGXpInIdXXIywh+4X3QMWeFFuHIV2QHo9yCwba7oJLIzs9tgnCzd36RtJaeEwjWFMG8zw15mh5/JD6GDQhF5Y+R5TzpXZVahYGUBavNq4bQ6oQ3XImxIGCJGRNRvU7CmAEVrG05d18Xo0OHVDhfNFFvr21OE6S9UKsS+/BLUjdxY0ZexnORs8NNA+peAWd6LmHrSxvZXYHUTiwkAir4qQskPJUi4PwH6eD0sWRbkpOVAE6BB+NXhjT5HrVcj7KowGNoYoNapUX2kGjlLcuoeHxxWv50+Xo/kKcn1v1dpmjbDKrKGR8R0lum22xBw2WWiY8gOh/XkTB8I3DQPAKeVAkBhSCymqc3Neo7lqAVBvYMQ1CsIukgdQi4LQWDXQFQfP//N6fyT/GHqb4Ih3gBdpA6my00I6h6EqoyG919SqVXQmrT1X35BTfusF1rF/59Uxy8qClFTnhQdQ5ZYTnLX9gqg7wOiUwgnQYXnUrrBbC1r1vP82/mj6lAVavNrAQCWUxZUHalCUPemn/exnLSg+kg1jJ0arg5dW1CLw5MPI2NKBrLfzYa1uGk3uwuqdDb9DZBXi3nxBWiCeA6yMRzWU4Kr/g0c/R4oOS46iTAfdh+Bbebm3zww8rpIOC1OHHn6SN1HMScQPToapstNF33u4f87DEeFA5JDQtSoKIRdeXZILyA1oG6oMFYPm9mGwrWFOPHKCbSb3g4af80F9xtQ7p13bKXmCRoxAkHDhomOIVssJyXQBQA3vQMsuRaQfO9Td0ZMZ7xV3bLrmcp2lMG83YyEBxNgiDfAcsqC/OX59RMjLiTlmRQ4a5yoPlaNglUF0EXrYOpvAgAE9Tj7adfQxoCAlABkPJmBsh1lDUqsMfpyXuPk6zRhYYh5/jnRMWSNw3pKkTQA6Pew6BQeV+tnwNTIMFidLTvayF+Zj8hrI+vOIbUxIHRgKMJHhKNo3cUXidVF6mBoY0DY4DCEjwhH4eeF591WY9RAH6OHtfDiOTWlFc16D+R9YmdMh19ExMU39GEsJyUZ9gIQ3l50Co96s/swHK3MbvHzpVrpnL/lKrUKaO6NYiRAsp3/SY4aB6yFVmhNTZiJV2Ju5ouTNwm94w4EDeHtcS6Gw3pKojUAN78HLB4BOL3/lgtbUvpjubl1q40H9QpC0ZdF0IXpoI/Xo+ZUDc58cwahV5wd0stflQ97qR0J/0gAABR/XwxtuBb62LrrTqoyqnBm/ZkGU8/zPs5DcK9gaMO1sJvtKPi8AFADIf0uvPpDuDMAUk15q94TKZe+fXtEPfUv0TEUgeWkNAmXAle/BHzztOgkblVqDMdzupq6I59WiB0Xi8LPCpH7YS7s5XUX4YYNDkPkTZH129jN9oYz7SSg4NMCWIusUGlU0EXpED0musE1TvYSO7LfzYaj0gFNkAbG9kakPJ8Cv+AL/5NKtocAYDn5IpVej7jZr/Ni2ybinXCVauXdwKG1olO4zcTe12BTC2bnyd2NFe0xbm666BgkQPTzzyHszjtFx1AMnnNSqpvmAeHtRKdwi1Vdr/bKYgKAmFp+avZFgUOHspiaieWkVPogYMwHXnfn3BORqZhV673LNUVYuHSRr9ElJyPutVdFx1AclpOSRXcFrpstOoXL2NRaTI2Nh8VRIzqK24RWc+kiX6I2GpEwby5XgWgBlpPS9b4T6D1OdAqXeKfncByqyBIdw62CKx2iI5CnqFSIm/ka9KmpopMoEsvJG1w7G4jtJTpFq+xMuhSLyw6KjuF2XLrId0Q8/DCXJ2oFlpM30BqAOz4BghNEJ2mRcv8QPGMEnD6wNJOu7PyroZP3CBwyBBETHxMdQ9FYTt4iKAa4cxWgDxadpNmmdx6IPMvFlxPyBmouXeT1dKmpiJs187w3s6SmYTl5k+guwJilgFo511Z/2WkI1pe2bhUIReHSRV7NLzISiQvegyYwUHQUxWM5eZvUocD1b4pO0SQ5YYl4xZkvOobHRDmNkKw85+St1IGBaLNwAbTx8aKjeAWWkze65G5g0OOiU1yQQ6XBM4ntUGmruvjGXiLJduF190jBtFokvD0Hhk6dRCfxGiwnbzXsBaDbaNEpzmtRjxHYXdayezQpVbzVePGNSHlUKsS9MgPGAQNEJ/EqLCdvpVIBo+YDKYNFJznH/oQeeLfisOgYHhdTaxAdgdwg6onHEXLDDaJjeB2Wkzfz0wO3fwwkXyE6Sb1qnRFTQ/xhl+yio3hcRLVyJqpQ04SNH4/w++8XHcMrsZy8nda/7hqoRHkMObzWbTBOVeeJjiEEly7yLqF334XoqU+JjuG1WE6+QGesuwYqvo/QGBvbX4HPSvcLzSBSEJcu8hqhd96JmGeeER3Dq7GcfIU+CBi3WtgyR4UhsZimNgt5bbnw59JFXsF0+98R8/xzomN4PZaTL/E3AXetAaK7e/RlJajwbEo3mK1lHn1dudGZfWfavLcy3XYbYl54QXQMn8By8jUBYcDda4Hobh57yQ+7j8B2c4bHXk+u1GYuXaRkIbeORsxL/+ayRB7CcvJFxnBg/FdA4uVuf6mMmM54q9q3rmdqjEoCJC5dpFhh99yN2JdfZjF5EMvJV/0xxNfxOre9RK2fAVMjw2B18lxLjDMIsNlEx6AWiJg0EdFPP81i8jCWky/TGoCxH9Ytd+QGb3a/Ckcrs92yb6VJsilvtXifp1Yj+oXnEfnII6KT+CReFejr1BrgxrcBYxTw0+su2+3PqQOw3Oy708b/Kt7GVaqVRKXXI27mTASPGC46is/ikRPVGfY8MHIWoGr9X4kSYwSe11ogQXJBMO8QbdGLjkBNpA4ORuKihSwmwVhOdFa/fwCj0wC/1q0B92KHPjhTW+KiUN4hwqIRHYGaQJeUhOSPVyDgsstER/F5LCdqqNstwH0bWnzL95Vdr8Ym8yEXh1I+Ey9xkj3jwIFIXrUS+pQU0VEILCdqTFxv4B+bgKSBzXraichUvF570j2ZFC6oyik6Al1A2D13o82C96AJlv/ElU2bNkGlUsFsNouO4lYsJ2pcYGTdxbqXPdCkzW1qLabGxsPiqHFzMGXyL+OfixyptFrEzphRN1Vc0/qh1/Hjx0OlUp3zdfQor/VrLpYTnZ9GC1z3OnDTPEBz4RP683oOx6GKLM/kUiBdWbXoCPQXmogIJC5dCtPoW1y632uuuQZ5eXkNvtq2bdvs/Vitvn19IMuJLq73OODe9UBQXKPf/jWpD94vO+jhUMqiKikXHYH+JGBAf6Ss+QwBl/R2+b71ej1iYmIafGk0GmzevBl9+/aFXq9HbGwspk6dCrv97H3NBg8ejMceewyTJ09GREQERowYAQD4+uuv0aFDB/j7+2PIkCHIyspyeWY5YjlR0yRcCjy4GUgZ0uDhcv8QPGuU4JR4TuV8VBIgmX170VvZ0GgQOfmfSExLg19kpMdeNicnB9deey0uu+wy7N27F/Pnz0daWhqmT5/eYLulS5dCp9Nhy5YtePfdd5GdnY1bbrkFN9xwA/bs2YP7778fU6dO9VhukXgRLjVdYFTdkkdb5wAbXwacNkzvPBB5pQdEJ5O1BEcIYC8WHcPn+cXGIv71WQi49FK3vs66desQGHj2ouuRI0eiQ4cOaNOmDebOnQuVSoVOnTohNzcXTz31FF544QWo1XXHCe3bt8fMmTPrn/vMM88gNTUVs2fPBgB07NgR+/fvx2uvvebW9yAHLCdqHpUKGPhPIPkKfLt7PtaXbBedSPYS7cEAWE4iBQ4dirhXZkBjMrn9tYYMGYL58+fX/95oNOLRRx/FgAEDGqzPN3DgQFRWVuL06dNITEwEAFz6l+JMT09Hv379Gjw2YIA87mrtbiwnapn4SzAo6i3ctvN1rMpcJTqNrMVZA0RH8Fkqf39EPf44wu4a57HXNBqNaNeuXYufS3V4zolaLEAbgBcGvIB5w+Yhwj9CdBzZiq7h0kUiBPTti5Qv1nq0mM6nc+fO2LZtGyTp7JJeW7ZsQVBQEBISzn/Be+fOnbFjx44Gj23f7hujFSwnarW/JfwNa25cg5HJI0VHkaWIai5d5EnqgABEv/A8Epcuga5NG9FxAACPPPIIsrOzMXHiRBw+fBhr167Fiy++iMcff7z+fFNjHnroIRw5cgRTpkxBRkYGli9fjiVLlnguuEAsJ3IJk8GEmVfOxLtXvYvEoETRcWTFVM37AHmK8fIBaPvFFwi74w5Z3X8pPj4eX3/9NXbs2IGePXvioYcewoQJE/Dcc89d8HmJiYlYvXo1Pv/8c/Ts2RPvvvsuXnnlFQ+lFksl/fk4k8gFah21WLR/ERbvX8wbDQJYtKMHgjfuFh3Dq6lDQhD1xOMIHTNGdBRyER45kcvpNXo82utRfHbTZ+gf2190HOH8y2pFR/BeajVMY8YgdcN6FpOX4ZETud3Xx7/GrJ2zcMZyRnQUIVZ+mgAcyRIdw+v49+6N6OeehX/XrqKjkBuwnMgjKqwVmPvbXKzMXAm7037xJ3iRVQuCIRXz/lau4hcZiagnn0DwjTfK6rwSuRbLiTwquzwb8/bOw/oT631iySMNVFgx0wk4HKKjKJ7KYEDYXeMQ/uBD0ATyeiBvx3IiITJLMzFn9xxsPr1ZdBS3SrKbMGuWbw5nuopKq4XpttsQ/tCD0EZFiY5DHsJyIqH2FO7BW7vfws6CnaKjuMUVNYmY+OZx0TGUSaNByI03IuLRR6FLiBedhjyM5USysCVnC97a/RbSS9JFR3GpseZOGD2fC+M2i0qFoBEjEDlpIm+Z7sO4th7JwsD4gbg87nL8kP0Dlh5cit2F3nFdUHQtly5qMq0WIdddh7D77oWhQwfRaUgwlhPJhkqlwtDEoRiaOBQHzhzABwc/wHcnv4NdUu7svnAuXXRR6sBAmMaOQdjdd0MbHS06DskEh/VI1vKr8vFR+kdYnbkaFbYK0XGa7a2DlyD2ix0X39AH+cXEIOzuu2Eacxs0f7r/ERHAciKFqLZV47Mjn2FZ+jLkVOaIjtNkadu6I2jTb6JjyEpA374wjRmD4BHDodJqRcchmWI5kaI4nA78lPMT1hxZgx9zfpT9Bb0ffdsB2l2HRMcQThMeDtPNo2C69VbokpNFxyEFYDmRYhVbirHu+Dp8fvRzHDUfFR2nUSs/iQeOnxQdQwy1GsbLL4fpttsQNHQIj5KoWVhO5BUOlxzGumPrsP7EehRaCkXHqbfq3UBIpWbRMTzK0KULgq+7FsEjR0IbFyc6DikUy4m8ilNy4tf8X7EhawN+PP0jCqvFFZVO0mDZTBvg9P5lmvSdOiF4xHAEXXMN9G3bio5DXoDlRF4tvTgdm09vxo+nf8SBMwcgwXN/3VPtYfjPLPkcxbmUVouAnj0ROPhKBA0fDl0ibzBJrsVyIp9RbCnGTzk/4cfTP2Jr7lZU2arc+nqDLUl45L/H3PoanqRNSIBx0EAEDhqEgP4DuPgquRXLiXySzWHDb4W/YVfhLuwt3It9Rftcfh3VHWWdMeqd/S7dpydpwsPh36sXjP36wXjFIA7XkUdxhQjySVqNFn1j+6JvbF8AgCRJOGo+ij1Fe7CncA/2Fu3FyfLWzbKLsuhcEdUzNBroO3ZAQK/e8O/dC/69ekHXpo3oVOTDeOREdB6lNaXYW7QX6SXpOFF2AifKTuBk+UlY7JYmPf/lE5eg48fyWx1CHRwMfbt2dV/t20PfsQP8u3WDOiBAdDSieiwncgmVSoU1a9Zg1KhRoqO4lSRJyK3KxXHzcZwoO4HjZXW/ZpVnoaSm4d1u5+zvjZh1vwrJqQ4IgF9cLLSxcdDGxkLXtm1dEbVvx/XrSBFYTtQk+fn5mDFjBr766ivk5OQgKioKvXr1wuTJkzFs2DDk5+cjNDQUer3vrsJtdVhRZClCUXURCqoL0C6jEkHp2XCUlMJRWgKHuQxOiwXOGgskSw2cNTWQLBY4a2vPvVOuSgVoNFCp1XW/+vlBHRgITXAwNEFBUIeEQBMUBE1IMNRBwdCEhUIbEwttXCy0sbHQhISI+UMgchGWE11UVlYWBg4cCJPJhJdeegndu3eHzWbDN998gwULFuDw4cOiIyqeZLVCkqSzZaRWi45EJBT/BdBFPfLII1CpVNixYwdGjx6NDh06oGvXrnj88cexfft2AHXDep9//jkAwGq14rHHHkNsbCwMBgOSkpLwn//8p35/ZrMZDz74IKKjo2EwGNCtWzesW7eu/vurV69G165dodfrkZycjNmzZ3v0/Yqg0umg1uuh0mpZTETgbD26iJKSEmzYsAEzZsyA0XjudS0mk+mcx+bMmYMvvvgCK1euRGJiIrKzs5GdnQ0AcDqdGDlyJCoqKrBs2TKkpqbi0KFD0Gjq7nu0a9cujBkzBtOmTcPYsWOxdetWPPLIIwgPD8f48ePd+VaJSEZYTnRBR48ehSRJ6NSpU5Ofc+rUKbRv3x6DBg2CSqVCUlJS/fe+//577NixA+np6ejw+91OU/50K+433ngDw4YNw/PPPw8A6NChAw4dOoRZs2axnIh8CMcP6IJackpy/Pjx2LNnDzp27IhJkybh22+/rf/enj17kJCQUF9Mf5Weno6BAwc2eGzgwIE4cuQIHH+dNEBEXovlRBfUvn17qFSqZk16uOSSS3DixAm8/PLLsFgsGDNmDG699VYAgL+/v7uiEpEXYTnRBYWFhWHEiBGYN28eqqrOXYvObDY3+rzg4GCMHTsWCxcuxCeffILVq1ejpKQEPXr0wOnTp5GZmdno8zp37owtW7Y0eGzLli3o0KFD/XkpIvJ+LCe6qHnz5sHhcKBv375YvXo1jhw5gvT0dMyZMwcDBgw4Z/s33ngDK1aswOHDh5GZmYlVq1YhJiYGJpMJV155Jf72t79h9OjR+O6773DixAmsX78eGzZsAAA88cQT2LhxI15++WVkZmZi6dKlmDt3Lp588klPv20iEkkiaoLc3Fzp0UcflZKSkiSdTifFx8dLN954o/TDDz9IkiRJAKQ1a9ZIkiRJCxYskHr16iUZjUYpODhYGjZsmLR79+76fRUXF0v33nuvFB4eLhkMBqlbt27SunXr6r//6aefSl26dJG0Wq2UmJgozZo1y5NvlYhkgBfhEhGR7HBYj4iIZIflREREssNyIiIi2WE5ERGR7LCciIhIdlhOREQkOywnIiKSHZYTERHJDsuJiIhkh+VERESyw3IiIiLZYTkREZHssJyIiEh2WE5ERCQ7LCciIpIdlhMREckOy4mIiGSH5URERLLDciIiItlhORERkeywnIiISHZYTkREJDssJyIikh2WExERyQ7LiYiIZIflREREssNyIiIi2WE5ERGR7LCciIhIdlhOREQkOywnIiKSHZYTERHJDsuJiIhkh+VERESyw3IiIiLZYTkREZHssJyIiEh2/h8ITfXUWu1gewAAAABJRU5ErkJggg==\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "aapl_closing_average = aapl[\"Close\"].mean()\n",
        "print(aapl_closing_average)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7Wp1iptDq8Mv",
        "outputId": "baac8867-f1b6-4f57-8234-c46caf934227"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "152.11932260581696\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "amzn_closing_average = amzn[\"Close\"].mean()\n",
        "print(amzn_closing_average)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Mq5o5cC4rIP3",
        "outputId": "2f13960f-0904-4b58-90fd-7f4e612eb99b"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "121.21775516950751\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "csco_closing_average = csco[\"Close\"].mean()\n",
        "print(csco_closing_average)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2W99qy1brPF_",
        "outputId": "365dc4fd-0596-4b49-9e59-b85bc0d55c43"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "47.648884503489946\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ford_closing_average = ford[\"Close\"].mean()\n",
        "print(ford_closing_average)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YNYBv6F-rVWL",
        "outputId": "8de99435-1373-4df6-c3ce-fd0603168eed"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "14.090318721604062\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "closing_averages = numpy.array([aapl_closing_average,\n",
        "                                amzn_closing_average,\n",
        "                                csco_closing_average,\n",
        "                                ford_closing_average])"
      ],
      "metadata": {
        "id": "0YnoUClury02"
      },
      "execution_count": 20,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "pyplot.pie(closing_averages,labels=labels,autopct = \"%.2f\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 621
        },
        "id": "l5lpyTQXsSRt",
        "outputId": "0b87d23b-6461-460d-c931-deae27d18a9b"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "([<matplotlib.patches.Wedge at 0x7d150977cb50>,\n",
              "  <matplotlib.patches.Wedge at 0x7d150977ca60>,\n",
              "  <matplotlib.patches.Wedge at 0x7d150977d840>,\n",
              "  <matplotlib.patches.Wedge at 0x7d150977ded0>],\n",
              " [Text(0.1584661948210632, 1.0885258219715934, 'Apple'),\n",
              "  Text(-0.7281430650801606, -0.8245045037934415, 'Amazon'),\n",
              "  Text(0.8335096960110228, -0.7178172376417362, 'Cisco'),\n",
              "  Text(1.0904150611782353, -0.14489649531878204, 'Ford')],\n",
              " [Text(0.08643610626603447, 0.5937413574390509, '45.40'),\n",
              "  Text(-0.39716894458917845, -0.44972972934187716, '36.18'),\n",
              "  Text(0.4546416523696487, -0.3915366750773106, '14.22'),\n",
              "  Text(0.5947718515517646, -0.07903445199206292, '4.21')])"
            ]
          },
          "metadata": {},
          "execution_count": 21
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Find lowest risk stocks with Python (Using MarketCap)"
      ],
      "metadata": {
        "id": "hAlC5sF_ZG4D"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "aapl[\"Market Cap\"] =aapl [\"Open\"]  * aapl[\"Volume\"]\n",
        "\n",
        "aapl.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "AgNfnlg5NaiV",
        "outputId": "7c7fb26c-6e66-4b71-b96b-a91255dd9192"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                        Date        Open        High         Low       Close  \\\n",
              "0  2022-02-01 00:00:00-05:00  174.009995  174.839996  172.309998  174.610001   \n",
              "1  2022-02-02 00:00:00-05:00  174.750000  175.880005  173.330002  175.839996   \n",
              "2  2022-02-03 00:00:00-05:00  174.479996  176.240005  172.119995  172.899994   \n",
              "3  2022-02-04 00:00:00-05:00  171.679993  174.100006  170.679993  172.389999   \n",
              "4  2022-02-07 00:00:00-05:00  172.860001  173.949997  170.949997  171.660004   \n",
              "\n",
              "    Adj Close    Volume    Market Cap  \n",
              "0  173.602448  86213900  1.500208e+10  \n",
              "1  174.825348  84914300  1.483877e+10  \n",
              "2  171.902313  89418100  1.560167e+10  \n",
              "3  171.613632  82465400  1.415766e+10  \n",
              "4  170.886917  77251200  1.335364e+10  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-a4e1e8c4-8ce0-4465-a705-296ccf23beed\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date</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>Market Cap</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2022-02-01 00:00:00-05:00</td>\n",
              "      <td>174.009995</td>\n",
              "      <td>174.839996</td>\n",
              "      <td>172.309998</td>\n",
              "      <td>174.610001</td>\n",
              "      <td>173.602448</td>\n",
              "      <td>86213900</td>\n",
              "      <td>1.500208e+10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2022-02-02 00:00:00-05:00</td>\n",
              "      <td>174.750000</td>\n",
              "      <td>175.880005</td>\n",
              "      <td>173.330002</td>\n",
              "      <td>175.839996</td>\n",
              "      <td>174.825348</td>\n",
              "      <td>84914300</td>\n",
              "      <td>1.483877e+10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2022-02-03 00:00:00-05:00</td>\n",
              "      <td>174.479996</td>\n",
              "      <td>176.240005</td>\n",
              "      <td>172.119995</td>\n",
              "      <td>172.899994</td>\n",
              "      <td>171.902313</td>\n",
              "      <td>89418100</td>\n",
              "      <td>1.560167e+10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2022-02-04 00:00:00-05:00</td>\n",
              "      <td>171.679993</td>\n",
              "      <td>174.100006</td>\n",
              "      <td>170.679993</td>\n",
              "      <td>172.389999</td>\n",
              "      <td>171.613632</td>\n",
              "      <td>82465400</td>\n",
              "      <td>1.415766e+10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2022-02-07 00:00:00-05:00</td>\n",
              "      <td>172.860001</td>\n",
              "      <td>173.949997</td>\n",
              "      <td>170.949997</td>\n",
              "      <td>171.660004</td>\n",
              "      <td>170.886917</td>\n",
              "      <td>77251200</td>\n",
              "      <td>1.335364e+10</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-a4e1e8c4-8ce0-4465-a705-296ccf23beed')\"\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 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .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-a4e1e8c4-8ce0-4465-a705-296ccf23beed 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-a4e1e8c4-8ce0-4465-a705-296ccf23beed');\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-c4ebe4e4-584c-4381-a095-d59edc72ed93\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-c4ebe4e4-584c-4381-a095-d59edc72ed93')\"\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-c4ebe4e4-584c-4381-a095-d59edc72ed93 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "amzn[\"Market Cap\"] =amzn [\"Open\"]  * amzn[\"Volume\"]\n",
        "\n",
        "amzn.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "OPO4fghTPALj",
        "outputId": "a2ef8319-26d6-46fe-eef1-c9371b2630f8"
      },
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                        Date        Open        High         Low       Close  \\\n",
              "0  2022-02-01 00:00:00-05:00  150.000000  151.707993  147.627502  151.193497   \n",
              "1  2022-02-02 00:00:00-05:00  155.050507  155.074997  148.863495  150.612503   \n",
              "2  2022-02-03 00:00:00-05:00  141.737503  144.247498  138.332993  138.845505   \n",
              "3  2022-02-04 00:00:00-05:00  155.606506  161.199997  150.608002  157.639496   \n",
              "4  2022-02-07 00:00:00-05:00  158.520004  162.690994  157.250000  157.935501   \n",
              "\n",
              "    Adj Close     Volume    Market Cap  \n",
              "0  151.193497   59220000  8.883000e+09  \n",
              "1  150.612503   87330000  1.354056e+10  \n",
              "2  138.845505  225532000  3.196634e+10  \n",
              "3  157.639496  253456000  3.943940e+10  \n",
              "4  157.935501  102624000  1.626796e+10  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-69f15933-7501-4e42-9cdd-4eea14cb743c\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
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              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Date</th>\n",
              "      <th>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>Market Cap</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2022-02-01 00:00:00-05:00</td>\n",
              "      <td>150.000000</td>\n",
              "      <td>151.707993</td>\n",
              "      <td>147.627502</td>\n",
              "      <td>151.193497</td>\n",
              "      <td>151.193497</td>\n",
              "      <td>59220000</td>\n",
              "      <td>8.883000e+09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2022-02-02 00:00:00-05:00</td>\n",
              "      <td>155.050507</td>\n",
              "      <td>155.074997</td>\n",
              "      <td>148.863495</td>\n",
              "      <td>150.612503</td>\n",
              "      <td>150.612503</td>\n",
              "      <td>87330000</td>\n",
              "      <td>1.354056e+10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2022-02-03 00:00:00-05:00</td>\n",
              "      <td>141.737503</td>\n",
              "      <td>144.247498</td>\n",
              "      <td>138.332993</td>\n",
              "      <td>138.845505</td>\n",
              "      <td>138.845505</td>\n",
              "      <td>225532000</td>\n",
              "      <td>3.196634e+10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2022-02-04 00:00:00-05:00</td>\n",
              "      <td>155.606506</td>\n",
              "      <td>161.199997</td>\n",
              "      <td>150.608002</td>\n",
              "      <td>157.639496</td>\n",
              "      <td>157.639496</td>\n",
              "      <td>253456000</td>\n",
              "      <td>3.943940e+10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2022-02-07 00:00:00-05:00</td>\n",
              "      <td>158.520004</td>\n",
              "      <td>162.690994</td>\n",
              "      <td>157.250000</td>\n",
              "      <td>157.935501</td>\n",
              "      <td>157.935501</td>\n",
              "      <td>102624000</td>\n",
              "      <td>1.626796e+10</td>\n",
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              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
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              "            style=\"display:none;\">\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
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              "\n",
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              "      background-color: #E8F0FE;\n",
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              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .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-69f15933-7501-4e42-9cdd-4eea14cb743c 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-69f15933-7501-4e42-9cdd-4eea14cb743c');\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-193136d4-d0a3-4b1e-a93b-82c734533baf\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-193136d4-d0a3-4b1e-a93b-82c734533baf')\"\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",
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              "    </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",
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              "\n",
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              "    border-bottom-color: var(--fill-color);\n",
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              "      border-bottom-color: var(--fill-color);\n",
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              "      border-left-color: var(--fill-color);\n",
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              "    }\n",
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              "\n",
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              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
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              "      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",
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              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
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              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "csco[\"Market Cap\"] =csco [\"Open\"]  * csco[\"Volume\"]\n",
        "\n",
        "csco.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "sw4u0arMPJfL",
        "outputId": "c2eef665-211f-4c05-c293-293fc6a028a5"
      },
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                        Date       Open       High        Low      Close  \\\n",
              "0  2022-02-01 00:00:00-05:00  55.450001  55.500000  54.740002  55.369999   \n",
              "1  2022-02-02 00:00:00-05:00  55.230000  56.320000  55.169998  56.169998   \n",
              "2  2022-02-03 00:00:00-05:00  55.869999  56.150002  55.060001  55.200001   \n",
              "3  2022-02-04 00:00:00-05:00  54.889999  55.619999  54.389999  55.150002   \n",
              "4  2022-02-07 00:00:00-05:00  55.330002  55.529999  54.700001  55.169998   \n",
              "\n",
              "   Adj Close    Volume    Market Cap  \n",
              "0  53.573200  22438500  1.244215e+09  \n",
              "1  54.347244  23316700  1.287781e+09  \n",
              "2  53.408722  19260500  1.076084e+09  \n",
              "3  53.360340  19675900  1.080010e+09  \n",
              "4  53.379692  14450200  7.995296e+08  "
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              "      <th>1</th>\n",
              "      <td>2022-02-02 00:00:00-05:00</td>\n",
              "      <td>55.230000</td>\n",
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              "      <th>2</th>\n",
              "      <td>2022-02-03 00:00:00-05:00</td>\n",
              "      <td>55.869999</td>\n",
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              "      <td>2022-02-04 00:00:00-05:00</td>\n",
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              "      <td>2022-02-07 00:00:00-05:00</td>\n",
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              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-c347874d-30a0-4361-97c6-cf73050c1f73');\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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              "  .colab-df-quickchart:hover {\n",
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              "\n",
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              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
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              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
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              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
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              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
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              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
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              "      border-bottom-color: var(--fill-color);\n",
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              "\n",
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              "    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",
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              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
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              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ford[\"Market Cap\"] =ford [\"Open\"]  * ford[\"Volume\"]\n",
        "\n",
        "ford.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "SaOhwB1SPOZ2",
        "outputId": "37446361-0aef-4f88-88b7-bc9da6d9d9d7"
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "                        Date       Open       High        Low      Close  \\\n",
              "0  2022-02-01 00:00:00-05:00  20.610001  20.850000  19.920000  20.660000   \n",
              "1  2022-02-02 00:00:00-05:00  20.809999  21.049999  20.180000  20.629999   \n",
              "2  2022-02-03 00:00:00-05:00  20.170000  20.620001  19.870001  19.889999   \n",
              "3  2022-02-04 00:00:00-05:00  18.520000  18.590000  17.520000  17.959999   \n",
              "4  2022-02-07 00:00:00-05:00  17.730000  18.120001  17.700001  17.889999   \n",
              "\n",
              "   Adj Close     Volume    Market Cap  \n",
              "0  20.110569  117651800  2.424804e+09  \n",
              "1  20.081366   95377600  1.984808e+09  \n",
              "2  19.361046  103016000  2.077833e+09  \n",
              "3  17.482370  211100500  3.909581e+09  \n",
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              "      <td>2022-02-03 00:00:00-05:00</td>\n",
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              "      <td>19.361046</td>\n",
              "      <td>103016000</td>\n",
              "      <td>2.077833e+09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2022-02-04 00:00:00-05:00</td>\n",
              "      <td>18.520000</td>\n",
              "      <td>18.590000</td>\n",
              "      <td>17.520000</td>\n",
              "      <td>17.959999</td>\n",
              "      <td>17.482370</td>\n",
              "      <td>211100500</td>\n",
              "      <td>3.909581e+09</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2022-02-07 00:00:00-05:00</td>\n",
              "      <td>17.730000</td>\n",
              "      <td>18.120001</td>\n",
              "      <td>17.700001</td>\n",
              "      <td>17.889999</td>\n",
              "      <td>17.414232</td>\n",
              "      <td>84610000</td>\n",
              "      <td>1.500135e+09</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-9e99734f-5f72-45c9-a9e8-aa20099e8cf9')\"\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 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .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-9e99734f-5f72-45c9-a9e8-aa20099e8cf9 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-9e99734f-5f72-45c9-a9e8-aa20099e8cf9');\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-838b52e5-8c65-45aa-a62d-b1cfa568bcc5\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-838b52e5-8c65-45aa-a62d-b1cfa568bcc5')\"\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-838b52e5-8c65-45aa-a62d-b1cfa568bcc5 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "aapl[\"Market Cap\"].plot(label=\"Apple\",figsize=(20,5))\n",
        "amzn[\"Market Cap\"].plot(label=\"Amazon\",figsize=(20,5))\n",
        "csco[\"Market Cap\"].plot(label=\"Cisco\",figsize=(20,5))\n",
        "ford[\"Market Cap\"].plot(label=\"Ford\",figsize=(20,5))\n",
        "\n",
        "pyplot.legend()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 478
        },
        "id": "Kh8qBcWQQAc4",
        "outputId": "2fb2406d-d9fe-4417-cab3-29e8ff78213f"
      },
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.legend.Legend at 0x7d15088aece0>"
            ]
          },
          "metadata": {},
          "execution_count": 30
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 2000x500 with 1 Axes>"
            ],
            "image/png": 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uwJo1a7SvrVu3DpIkYe3atViwYAFycnJw0UUXobm5Gf/6178wY8YMWK1WfPGLX0Rvb692u7feegvnnnsuioqKUFpaiiuvvBKHDx/Wvv7AAw9AkqRBb+J7OxwOfP3rX0dFRQUsFgvOPfdcfPrpp4O2691338Xpp5+O3NxcLF68GPv374/t7xUFQ8K/A6Um0Q6rcDRwHKwEISIiIiIiIiIiouzl6gV+Pio53/v7JwFTXsRXf+mllzB9+nRMmzYNN910E+6++26sXLkSkiRp13nggQewatUq5Obm4rrrrsN1110Hs9mM5557Dj09Pfj85z+P//f//h/uvfdeAIDdbse3vvUtzJ07Fz09Pbj//vvx+c9/HrW1tdDpdPjOd76D2267Tbv/v/71r7j//vtx+umnAwC++93v4uWXX8bTTz+NcePG4Ve/+hWWLl2KQ4cOoaSkRLvdD37wAzz88MMoLy/Hbbfdhi9/+cv4+OOPh/sbDIshSLYS7bCso5X3rAQhIiIiIiIiIiIiSnmrV6/GTTfdBABYtmwZurq6sH79elxwwQXadX7605/inHPOAQDccsstWLlyJQ4fPoyJEycCAP7zP/8T77//vhaCXHPNNQHf48knn0R5eTn27NmD2bNnIz8/H/n5+QCATZs24b777sPTTz+N2bNnw26347HHHsOaNWtw+eWXAwCeeOIJvP3221i9ejXuuece7X5/9rOfYcmSJQCA733ve7jiiivQ398Pi8WSgN+UgiFINpLlwSEIK0GIiIiIiIiIiIgoWxlzlYqMZH3vCO3fvx+bN2/GK6+8AgAwGAy4/vrrsXr16oAQZO7cudrHlZWVyM3N1QIQcdnmzZu1zw8ePIj7778fn3zyCVpbW+H1egEA9fX1mD17tna9+vp6LF++HN/5zndw3XXXAQAOHz4Ml8ulhS4AYDQaceaZZ2Lv3r0B2++/XdXVyrzq5uZmjB07NuLfQbQYgmQjR7cv9CgUlSAMQYiIiIiIiIiIiChLSVJULamSZfXq1XC73Rg1yte6S5ZlmM1mrFq1SrvMaDRqH0uSFPC5uEwEHQBw1VVXYdy4cXjiiScwatQoeL1ezJ49G06nr4OQ3W7Hf/zHf2DRokV48MEHY9r+gdsFIGA7EoGD0bORGIpuzAUsRcrHHrbDIiIiIiIiIiIiIkpVbrcbzzzzDB5++GHU1tZqb5999hlGjRqF559/Pqb7bWtrw/79+3Hffffh4osvxowZM9DR0RFwHVmWcdNNN8Hr9eIvf/lLwPyRSZMmwWQyBcz2cLlc+PTTTzFz5szYftg4YiVINhKtsPLKAINZ+ZiVIEREREREREREREQp6/XXX0dHRwduueUWFBYWBnztmmuuwerVq/HrX/866vstLi5GaWkp/vSnP6G6uhr19fX43ve+F3CdBx54AO+88w7+/e9/o6enBz09PQCAwsJC5OXl4fbbb8c999yDkpISjB07Fr/61a/Q29uLW265JfYfOE5YCZKN7C3K+7xyQG9SPmYlCBEREREREREREVHKWr16NS655JJBAQighCBbtmzBjh07or5fnU6HF154AVu3bsXs2bPxzW9+c1CYsn79evT09GDx4sWorq7W3l588UUAwC9+8Qtcc801+O///m8sXLgQhw4dwtq1a1FcXBzbDxtHkizLcrI3Yig2mw2FhYXo6uqC1WpN9uakv61PA//8OjB1GXDx/cBji4HcMuC7h5O9ZUREREREREREREQJ19/fj7q6OkyYMAEWiyXZm0MhhPs7RZobsBIkG4lKkNwyQK+2w2IlCBERERERERERERFlGIYg2ShgJojaDoszQYiIiIiIiIiIiIgowzAEyUa9IgQp96sEcQCp3xmNiIiIiIiIiIiIiChiDEGykTYY3a8SBAA8ruRsDxERERERERERERFRAjAEyUb+7bBEJQigVIMQEREREREREREREWUIhiDZyO7XDsvgF4K4ORydiAgA0HVCeSMiIiIiIiIiorRmSPYG0Ajzen0zQXLLAJ0ekPSA7GElCBERoLQG/OO5gKQDvr0f0POlkoiIiIiIiIgoXUVVCfLYY49h7ty5sFqtsFqtWLRoEf71r3+FvP6aNWsgSVLAm8ViGfZG0zD0dwJet/JxXpnyXlSDuBmCEBGh3wb0tSuBsbMn2VtDRERERERERETDENXy1jFjxuAXv/gFpkyZAlmW8fTTT+Pqq6/G9u3bMWvWrKC3sVqt2L9/v/a5JEnD22Iant425b250Bd+6E2AqxfwsB0WERHc/b6PXX1ATlHSNoWIiIiIiIiIiIYnqhDkqquuCvj8Zz/7GR577DFs2rQpZAgiSRKqqqqi2iiHwwGHw1eVYLPZoro9hWFvUd7nlfouYyUIEZGPfwji7kvedhARERERERERxUiSJLzyyitYvnx5sjcl6WIejO7xePDCCy/Abrdj0aJFIa/X09ODcePGoaamBldffTV279495H0/9NBDKCws1N5qampi3UwaSAtByn2X6dUQhJUgRERK9Uewj4mIiIiIiIiIUkRjYyPuuusuTJw4EWazGTU1Nbjqqqvw7rvvAgBOnTqFyy+/PMlbmRqiDkF27tyJ/Px8mM1m3HbbbXjllVcwc+bMoNedNm0annzySbz22mt49tln4fV6sXjxYhw/fjzs91i5ciW6urq0t4aGhmg3k0Kxq0PR/UMQg0l5z0oQIqLA50JXf+jrERERERERERElwdGjR3Haaafhvffew69//Wvs3LkTb731Fi688ELccccdAICqqiqYzeYkb2lqiDoEmTZtGmpra/HJJ5/g9ttvx5e+9CXs2bMn6HUXLVqEFStWYP78+ViyZAn+8Y9/oLy8HI8//njY72E2m7Xh6+KN4kSEILl+7bC0ShCGIEREAS2w2A6LiIiIiIiIKCvIsoxeV29S3mRZjmpbv/a1r0GSJGzevBnXXHMNpk6dilmzZuFb3/oWNm3aBEBph/Xqq68CAJxOJ+68805UV1fDYrFg3LhxeOihh7T76+zsxFe/+lVUVlbCYrFg9uzZeP3117Wvv/zyy5g1axbMZjPGjx+Phx9+ePi/8BEU1UwQADCZTJg8eTIA4LTTTsOnn36KRx99dMhgAwCMRiMWLFiAQ4cORb+lFB/B2mGJShCPa+S3h4go1QwcjE5EREREREREGa/P3YeznjsrKd/7ky9+glxjbkTXbW9vx1tvvYWf/exnyMvLG/T1oqKiQZf97ne/w//93//hpZdewtixY9HQ0KB1X/J6vbj88svR3d2NZ599FpMmTcKePXug1+sBAFu3bsV1112HBx54ANdffz02bNiAr33taygtLcXNN98c8888kqIOQQbyer0BQ8zD8Xg82LlzJz73uc8N99tSrHqDtMPSczA6EZHGxRCEiIiIiIiIiFLToUOHIMsypk+fHvFt6uvrMWXKFJx77rmQJAnjxo3TvvbOO+9g8+bN2Lt3L6ZOnQoAmDhxovb13/zmN7j44ovxwx/+EAAwdepU7NmzB7/+9a8zMwRZuXIlLr/8cowdOxbd3d147rnnsG7dOqxduxYAsGLFCowePVorpXnwwQdx9tlnY/Lkyejs7MSvf/1rHDt2DF/5ylfi/5NQZLSZIGW+y7RKEA5GJyJiJQgRERERERFR9skx5OCTL36StO8dqWhbZwHAzTffjEsvvRTTpk3DsmXLcOWVV+Kyyy4DANTW1mLMmDFaADLQ3r17cfXVVwdcds455+C3v/0tPB6PVjGSyqIKQZqbm7FixQqcOnUKhYWFmDt3LtauXYtLL70UgJIo6XS+MSMdHR249dZb0djYiOLiYpx22mnYsGFDyEHqNAKChSCsBCEi8vEPQTgThIiIiIiIiCgrSJIUcUuqZJoyZQokScK+ffsivs3ChQtRV1eHf/3rX3jnnXdw3XXX4ZJLLsHf//535OREHsCkq6hCkNWrV4f9+rp16wI+f+SRR/DII49EvVGUQEFngnAwOhGRxr/6w781FhERERERERFRkpWUlGDp0qX4/e9/j69//euD5oJ0dnYGnQtitVpx/fXX4/rrr8d//ud/YtmyZWhvb8fcuXNx/PhxHDhwIGg1yIwZM/Dxxx8HXPbxxx9j6tSpaVEFAgC6oa9CGcPrAXrblI9z/StB1HZYbrbDIiIKbIfVm7ztICIiIiIiIiIK4ve//z08Hg/OPPNMvPzyyzh48CD27t2L3/3ud1i0aNGg6//mN7/B888/j3379uHAgQP429/+hqqqKhQVFWHJkiU4//zzcc011+Dtt9/WKkbeeustAMC3v/1tvPvuu/jJT36CAwcO4Omnn8aqVavwne98Z6R/7JgxBMkmfR0A1J5xuaW+y1kJQkTkE9AOi5UgRERERERERJRaJk6ciG3btuHCCy/Et7/9bcyePRuXXnop3n33XTz22GODrl9QUIBf/epXOP3003HGGWfg6NGjePPNN7XRFi+//DLOOOMM3HDDDZg5cya++93vwuPxAFBaab300kt44YUXMHv2bNx///148MEH02YoOhBlOyxKc6IVVk4JoPf707MShIjIx8VKECIiIiIiIiJKbdXV1Vi1ahVWrVoV9Ov+A9RvvfVW3HrrrSHvq6SkBE8++WTIr19zzTW45pprYt/YJGMlSDbR5oGUBV7OShAiIp+AdlisBCEiIiIiIiIiSmcMQbKJvVV57z8UHfCrBGEIQkQU2A6rL/T1iIiIiIiIiIgo5TEEySZaCBKqEoTtsIiIAtthMQQhIiIiIiIiIkpnDEGyiWiHlTsgBNGrIQgrQYiIAqs/2A6LiIiIiIiIiCitMQTJJr0h2mEZ1HZYrAQhIgoMhDkYnYiIiIiIiIgorTEEySahBqOzEoSIyMe/BZablSBEREREREREROmMIUg2CTkTRFSCMAQhImIlCBERERERERFR5mAIkk3sIdphaZUgbIdFRMSZIEREREREREREmYMhSDbR2mENnAmihiCsBCEiCgw+/AMRIiIiIiIiIiJKOwxBsoXHBfR3Kh/nDpwJorbDYiUIEVHgHBAXQxAiIiIiIiIiyi7r1q2DJEno7OxM9qbEBUOQbNHbpryXdEBOceDXWAlCROQTEIKwHRYRERERERERpY6bb74ZkiQNejt06FCyNy1lGZK9ATRCRCus3DJANyD7YiUIEZGPf/UHB6MTERERERERUYpZtmwZnnrqqYDLysvLQ1w7NKfTCZPJFK/NSlmsBMkW2jyQssFfYyUIEZGP2++5UPYo7QSJiIiIiIiIKKPJsgxvb29S3mRZjmpbzWYzqqqqAt70ej3Wr1+PM888E2azGdXV1fje974Ht9ut3e6CCy7AnXfeibvvvhtlZWVYunQpAODNN9/E1KlTkZOTgwsvvBBHjx6N56826VgJki3sajusYCGIXg1B3AxBiCjLyfLgYeiuPkBvTM72EBEREREREdGIkPv6sH/haUn53tO2bYWUmzus+zhx4gQ+97nP4eabb8YzzzyDffv24dZbb4XFYsEDDzygXe/pp5/G7bffjo8//hgA0NDQgC984Qu444478L//+7/YsmULvv3tbw9rW1INQ5BsoVWCBCmLMqglTx62wyKiLOdxAbI38DJXH2CxJmd7iIiIiIiIiIgGeP3115Gfn699fvnll2Pq1KmoqanBqlWrIEkSpk+fjpMnT+Lee+/F/fffD506ImHKlCn41a9+pd32+9//PiZNmoSHH34YADBt2jTs3LkTv/zlL0f2h0oghiDZordVeZ/LShAiopD8h6JLeqUd1sDKECIiIiIiIiLKOFJODqZt25q07x2NCy+8EI899pj2eV5eHu644w4sWrQIkiRpl59zzjno6enB8ePHMXbsWADAaacFVrvs3bsXZ511VsBlixYtivZHSGkMQbJFb7vyPrd08NdYCUJEpPAPQSxWoK8jcFA6EREREREREWUkSZKG3ZJqpOTl5WHy5Mkx3zbbcDB6thAn8YxBUkVWghARKUQIYrAARnWngCEIEREREREREaW4GTNmYOPGjQFD1j/++GMUFBRgzJgxYW+3efPmgMs2bdqUsO1MBoYg2cIdLgRRK0G8LsDrHfx1IqJs4fIPQSzqZQxBiIiIiIiIiCi1fe1rX0NDQwPuuusu7Nu3D6+99hp+9KMf4Vvf+pY2DySY2267DQcPHsQ999yD/fv347nnnsOaNWtGbsNHAEOQbOF/Ym8g0Q4LYEssIspuIjA2WHyhMWeCEBEREREREVGKGz16NN58801s3rwZ8+bNw2233YZbbrkF9913X9jbjR07Fi+//DJeffVVzJs3D3/84x/x85//fIS2emRwJki2EC1ewrXDAgCPw7f6mYgo24i2gEYLYFCfL139oa9PRERERERERDSCwlVpLFmyZFBrK3/r1q0LevmVV16JK6+8MuCy//mf/4ll81ISK0Gyhdbn3jz4a3q/ShA3K0GIKIuJ1leGHF9ozHZYRERERERERERpiyFItvA/sTeQTgfojMrHHg5HJ6Is5h8Ysx0WEREREREREVHaYwiSLbR2WCFaXYkKETdDECLKYv6tAw0cjE5ERERERERElO4YgmQLbTB6kEoQwNcSi4PRiSibac+VFsCYq17GEISIiIiIiIgoU8mynOxNoDDi8fdhCJItws0E8b+clSBElM1E6yuDxVc55+ZgdCIiIiIiIqJMo9frAQBOJxeFp7Le3l4AgNFojPk+DPHaGEpx/i1egmElCBGRLwg2+leC9CZve4iIiIiIiIgoIQwGA3Jzc9HS0gKj0QidjvUCqUSWZfT29qK5uRlFRUVaaBULhiDZwuW3ujkYVoIQEfk9V/rPBGElCBEREREREVGmkSQJ1dXVqKurw7Fjx5K9ORRCUVERqqqqhnUfDEGygdcDeF3KxyErQdQQxMMQhIiymAiCDWZfOyxWghARERERERFlJJPJhClTprAlVooyGo3DqgARGIJkA/+hviErQdR2WG7+wxNRFhMzQYw5vnZYnAlCRERERERElLF0Oh0slhDnTCkjRNXo7LHHHsPcuXNhtVphtVqxaNEi/Otf/wp7m7/97W+YPn06LBYL5syZgzfffHNYG0wx8G9xFSoEYSUIEZGv9ZXB4tcOqy/09YmIiIiIiIiIKKVFFYKMGTMGv/jFL7B161Zs2bIFF110Ea6++mrs3r076PU3bNiAG264Abfccgu2b9+O5cuXY/ny5di1a1dcNp4iJFY2601AqAE/rAQhIvJVfRj8B6MzBCEiIiIiIiIiSldRhSBXXXUVPve5z2HKlCmYOnUqfvaznyE/Px+bNm0Kev1HH30Uy5Ytwz333IMZM2bgJz/5CRYuXIhVq1bFZeMpQtrK5hDzQABWghARAb4QxGjxzQRhOywiIiIiIiIiorQVVQjiz+Px4IUXXoDdbseiRYuCXmfjxo245JJLAi5bunQpNm7cGPa+HQ4HbDZbwBsNg9bjPkxvO60ShCEIEWUxUfVhsPiCYw5GJyIiIiIiIiJKW1GHIDt37kR+fj7MZjNuu+02vPLKK5g5c2bQ6zY2NqKysjLgssrKSjQ2Nob9Hg899BAKCwu1t5qammg3k/yJYMNgDn0drRKE7bCIKItpz5cWZTg64KumIyIiIiIiIiKitBN1CDJt2jTU1tbik08+we23344vfelL2LNnT1w3auXKlejq6tLeGhoa4nr/WUdb2RymHZYISFgJQkTZTKucy/ELQVgJQkRERERERESUrgzR3sBkMmHy5MkAgNNOOw2ffvopHn30UTz++OODrltVVYWmpqaAy5qamlBVVRX2e5jNZpjNYaoWKDr+Pe5D0avtsFgJQkTZTJuhZPaFIJwJQkRERERERESUtmKeCSJ4vV44HMGrBxYtWoR333034LK333475AwRShBWghARRUYEHoYcv5kgDEGIiIiIiIiIiNJVVJUgK1euxOWXX46xY8eiu7sbzz33HNatW4e1a9cCAFasWIHRo0fjoYceAgB84xvfwJIlS/Dwww/jiiuuwAsvvIAtW7bgT3/6U/x/EgqNlSBERJHxf75kOywiIiIiIiIiorQXVQjS3NyMFStW4NSpUygsLMTcuXOxdu1aXHrppQCA+vp66HS+4pLFixfjueeew3333Yfvf//7mDJlCl599VXMnj07vj8FhaetbA4TgrAShIjIr3LOLwTxugCPG9BH3UGSiIiIiIiIiIiSLKozOqtXrw779XXr1g267Nprr8W1114b1UZRnLkiCEH0agjiYQhCRFlMBMEGS+BzprsP0BckZ5uIiIiIiIiIiChmw54JQmnAra5sNoabCaK2w3KzHRYRZTH/50v/EIRzQYiIiIiIiIiI0hJDkGzAShAiosholSBmQKfzPW+KcISIiIiIiIiIiNIKQ5Bs4PbrcR8KK0GIKNvJst8MJbVyThuOzhCEiIiIiIiIiCgdMQTJBmJls5GVIEREIbn9Wl6J50sDQxAiIiIiIiIionTGECQbiJN3hnAzQdQQxM0QhIiylH8IIirnRBjCEISIiIiIiIiIKC0xBMkG4sRe2EoQtR2Wh+2wiChLiflJkh7QG5WPjbnKe84EISIiIiIiIiJKSwxBsgErQYiIhhZsfpKBlSBEREREREREROmMIUg2EMGGCDqCYSUIEWW7YPOTOBidiIiIiIiIiCitMQTJBmJ1szGCShCGIESUrYJVzYnnTf95IURERERERERElDYYgmQD0efeEG4miGiHxRCEiLKUCDr8q+bYDouIiIiIiIiIKK0xBMkGEVWCiHZYnAlCRFlKhCD+z5ViMDpDECIiIiIiIiKitMQQJBu4gqxuHkjPwehElOWCVc0ZWQlCRERERERERJTOGIJkA63FSySVIGyHRURZyh0sBFErQdwMQYiIiIiIiIiI0hFDkGygtXiJZCYIK0GIKEsFe67UZoJwMDoRERERERERUTpiCJINXJFUgqghiOwBvJ7EbxMRUaoRLa+CVYK4ekd+e4iIiIiIiIiIaNgYgmQDbTB6uEoQk9/1WQ1CRFlIPPcFmwniZiUIEREREREREVE6YgiS6bwe35wPQ5gQxH9ouochCBFloWCBsdYOi5UgRERERERERETpiCFIpvOv6ggXgugMACT1NhyOTkRZKFjrQK0dFitBiIiIiIiIiIjSEUOQTOffwsUYZiaIJPmqQVgJQkTZSDxf+lfGiaoQMS+EiIiIiIiIiIjSCkOQTCdO3OmMgE4f/rp69cQfK0GIKBuJEMQYpBLEzRCEiIiIiIiIiCgdMQTJdNrK5jCtsASDOhydlSBElI1EaOxfCaLNBGE7LCIiIiIiIiKidMQQJNNpK5sjCEG0ShCGIESUhcRzX8BMEPVjDkYnIiIiIiIiIkpLDEEyXbBBv6FolSBsh0VEWUi0vPIPjUUI4mYlCBERERERERFROmIIkumCndQLhZUgRJTNXEHaBxpYCUJERERERERElM4YgmS6YCf1QmElCBFls2AzlLR2WKwEISIiIiIiIiJKRwxBMp2oBIkkBGElCBFlM22GUpCZIB4H4PWO/DYREREREREREdGwMATJdCLQiKQdlkENQTwMQYgoC2mVIGbfZf4BsgiV04zbw/CGiIiIiIiIiLIXQ5BM5xKVIBEMRter7bDcbIdFRFlIax8YpBLE/+tp5EhLD+b9+N/4xb/2JXtTiIiIiIiIiIiSgiFIptPau7AShIgorGDPlzq9LyBOw+HoHx1qhd3pwUeHWpK9KUREREREREREScEQJNNFVQliVN6zEoSIslGwweiArxrEnY6VIHYAQFefK8lbQkRERERERESUHAxBMl2wHveh6FkJQkRZzBUiBBEhchpWghxpVUOQXoYgRERERERERJSdGIJkOq29SwSVIAYxE4QhCBFlITH4fODzpfg8TWeCAEC3ww2vV07y1hARERERERERjTyGIJku1MrmYLRKELbDIqIs43EDXrfycch2WH0ju03D1O/y4ESnss2yDHT3u5O8RUREREREREREI48hSKYLtbI5GNEyi5UgRJRt/Od9DGqHpX7uSq8Q5GibHbJf8Yetny2xiIiIiIiIiCj7RBWCPPTQQzjjjDNQUFCAiooKLF++HPv37w97mzVr1kCSpIA3iyWCqgSKD1c0M0HUdlisBCGibBMuBDHmKu/TLAQRQ9EFDkcnIiIiIiIiomwUVQiyfv163HHHHdi0aRPefvttuFwuXHbZZbDb7WFvZ7VacerUKe3t2LFjw9poioI2GJ2VIEREIYnnSr0J0A14aTSmZyWImAciMAQhIiIiIiIiomxkiObKb731VsDna9asQUVFBbZu3Yrzzz8/5O0kSUJVVVVsW0jDow1Gj2QmiKgEYQhCRFnGFSYwTtOZIEdaWQlCRERERERERDSsmSBdXV0AgJKSkrDX6+npwbhx41BTU4Orr74au3fvDnt9h8MBm80W8EYxEiuXo6oEYTssIsoy7jCtA8Xzp6t/8NdSmGiHpddJABiCEBEREREREVF2ijkE8Xq9uPvuu3HOOedg9uzZIa83bdo0PPnkk3jttdfw7LPPwuv1YvHixTh+/HjI2zz00EMoLCzU3mpqamLdTIqqEkQ9+cdKECLKNuGeK9OwHZYsy1o7rOlVBQAYghARERERERFRdoo5BLnjjjuwa9cuvPDCC2Gvt2jRIqxYsQLz58/HkiVL8I9//APl5eV4/PHHQ95m5cqV6Orq0t4aGhpi3UzSKkEiCEEMajssVoIQUbYJVzUnBqOnUTusNrsTtn43JAmYO6YIAEMQIiIiIiIiIspOUc0EEe688068/vrr+OCDDzBmzJiobms0GrFgwQIcOnQo5HXMZjPM5iAtSSh6Ysh5JCEIK0GIKFtpz5XB2mGlXyWIaIU1uigHFQXKz8QQhIiIKPUcbOpGZ58LZ4wP32KaiIiIiGIXVSWILMu488478corr+C9997DhAkTov6GHo8HO3fuRHV1ddS3pRiIlcvGSGaCsBKEiLJUuOdKUQmSViGI0gprQlkeCnOMAAAbQxAiIqKUs+LJzbjhT5vQbucxGKWm5u5+7DzelezNICIiGpaoQpA77rgDzz77LJ577jkUFBSgsbERjY2N6OvznRhasWIFVq5cqX3+4IMP4t///jeOHDmCbdu24aabbsKxY8fwla98JX4/BYUmBvmyEoSIKLRwz5VpOBOkrlWpBJlUnq+FIKwEISIiSi1ujxenuvrh9spo6eYxGKWmr/5lK65a9RGOtdmTvSlEREQxi6od1mOPPQYAuOCCCwIuf+qpp3DzzTcDAOrr66HT+bKVjo4O3HrrrWhsbERxcTFOO+00bNiwATNnzhzellNk3NHMBFFDEDd3wIkoy7jDhCBiTkgazQQ5rLbDmljOShAiIqJU1d3v1j7ucbjDXJMoeQ43KxXGx9p6Ma40L8lbQ0REFJuoQhBZloe8zrp16wI+f+SRR/DII49EtVEUR2J1szGSShC1HZaHpdhElGXcYZ4rRYss8XyaBo60KgerE8vyYTIoCxNYCUJERJRa/EMQO0MQSkFujxc29XHKfUkiIkpnMQ1GpzQhy77WVoZIZoKwEoSIspRodRXsuVILQXpHbnuGweXxor5N2daJ5XnaCRYeuBIREaUWW7/vtZkhCKWiTr/9R+5LEhFROmMIksncfquWWQlCRBSaCH9FGOxPhCDu9KgEaWjvhdsrI8eoR5XVAp2k/Gy2fjdkWYYkSUneQiIiIgICQxC2w6JU1GH3nRtgCEJEROksqsHolGb8h/iyEoSIKDQx78MY5LnSkF6D0Y+o80DGl+VBp5O0mSAer8wTLERERCmE7bAo1XX0shKEiIgyA0OQTCZWLUt6QB9B0Y9eDUFYCUJE2SZsJUiu8j5dQhAxD6RcGVxpMepg0nMuCBERUarhYHRKde3+lSC93I8kIqL0xRAkk2mDfiOoAgEAg9oOi5UgRJRtws4EUStB0qQdVl2rUgkyqUwJQSRJglWtBrH18QQLERFRqrD1+bfD8iRxS4iC6+hlOywiIsoMDEEymUs9YWeIYB4I4FcJ4lCGqhMRZQstNA7yfGlIr8Hoh9V2WBPL87XLCnOUakAevBIREaUOtsOiVMcQhIiIMgVDkEwWrsd9MKISBAA83MEhoiziDhMai+dQV3pUghzRQpA87TIxF4QHr0RERKmj228wOkMQSkUcjE5ERJmCIUgm0ypBgvS4D0bvdz0PW2IRURYJVzknQhB3X8pXydn6XWjtUZ6/J5QNDkFsPHglIiJKGbZ+/3ZYDEEo9XAwOhERZQqGIJnMHabHfTD+YYmbw9GJKIuEq5zzvyzF54KIKpDyAjMKLEbtcisrQYiIiFJOQDssJ0MQSj2sBCEiokzBECSTiQHnwXrcB6PTA5Je+ZiVIESUTcTzZbDKOf8gWQxQT1FHWnoAABP9qkAAtsMiIiJKRf4hCAejUypq95sJ0uNww+3xJnFriIiIYscQJJOJk3WRDkYHfCcA3QxBiCiLuMJUzukNgM4QeL0UVdc6eCg6wBCEiIgoFdk4E4RSXGdv4L6jrZ+PUyIiSk8MQTKZaNsS6WB0ANCrw9E9bIdFRFlEe74MERobcwOvl6JEO6xJ5awEISIiSnUB7bAYglAKarcHnhfgviQREaUrhiCZTFvZHOFgdP/rshKEiLKJO8xgdP/LXb0jsz0xOizaYQ0IQTgThIiIKPV0czA6pTC3x6tVK+UYlbbZnb1cLElEROmJIUgm007qRVMJooYgrAQhomziGiIEERV1rtStBPF6ZRxtU9thlQVvh+XfdoOIiIiSy9YXWAkiy3ISt4YoUFefC+IhObYkV7uMiIgoHTEEyWRDtXcJxqC2w2IlCBFlE7daOReqfaAWgqRuJcjJrj70u7ww6iWMKQ78OdgOi4iIKLX0uzxw+g2Z9spAv4tDpyl1dKhVH1aLASV5ynkC7ksSEVG6YgiSyVzDqQRhCEJEWUQEv6HaB4oKkRSeCSLmgYwtyYVBH/jyrlWC8MCViIgoJYjqTElS3gCg28HXaUodHepQ9OI8E/cliYgo7TEEyWRaO6xoZoKIShC2wyKiLCHLfjOUQlWCqIPRxfVSUF2r2gqrPH/Q1/wrQdhqg4iIKPnEUPR8swF5JgMAwO7wJHOTiAKIoejFuSZWFRMRUdpjCJLJXEO0dwmGlSBElG08LgBqMBAqNBZtBVM4BDkSYig64BuM7vLI6HPxBAsREVGyiRDEajEiz6wMnbZzODqlEDEEvSTPhKJco3oZQxAiIkpPDEEymdbeJZaZIKwEIaIs4fYLNkLOBMkdfN0Uc0StBJlUNrgSJM+kh16n9NrgCj4iIqLkE22FCiwG5JmVSpAehiCUQtrtymO0KNeoLajhfiQREaUrhiCZbKhBv8FolSAMQYgoS4j5SZAAvSn4dQzpUAki2mENrgSRJIltDIiIiFKIfyVIvlm0w2IIQqlDDEafpGvCdPunALgfSdnF4fbgq3/Zgmc3HUv2phBRHDAEyWTaYPRoKkHYDouIsozb77lSTCYdSITJKRqC9DrdONGpbFuwmSCA31wQtjEgIiJKuu5+XyVIPitBKAV1qDNBrj16Py7echsmSScYglBW2XqsA2t3N+HxDw4ne1OIKA4YgmQyUQkSTQiiZzssIsoyIgQxhnmuFCGIuG6KEVUgJXkmlOQFr2YRbQxs/TzBQkRElGw2NQSx5hi1dljpMhj91e0ncN+rO+H2eJO9KZRAohKkuK8eAFAttTMEoazS1qP8D3Tz+IkoIzAEyWSuCE7sDcRKkEF2nejCT1/fwx0+okwlqjsMYVoHpng7rEPNylD0ySGqQACwHRYREVEKESfV/CtB0qUd1q/X7sezm+rx4aHWZG8KJVC73QkLHDB6egEA+ejjfiRlFREEdve7IctykreGiIaLIUgm01q8RDMThJUgA/3u3YP480d1eGPHqWRvChElglsNfUUIHIwYjD7MEMTrlbHjeCdccV45ebhFCUEmVTAEISIiSgf+IUieWQ8gfdphtattkmrrO5O7IZRQnb0ulEld2ucFUi/3IymriOc6j1dGv4uVb0TpjiFIJoukxctArAQZ5FRXv/o+NVeAE9EwidaBassrp9uLh/61F4++c9B3HWN8KkFe2tKA/1j1MR5fH9++sqISZFKQoehCYY6yypQHr0RERMlnU1+PrRb/dlipH4L0uzzocyltu2obOpO7MZRQ7b1OlMMXguSjD71OT9wX8xClKhGCAL45TkSUvhiCZDLXcGaCMAQRmruVEKTZxt8JUUZy+Qaj9zrd+MozW/D4+iN45J0DOKJWWGiVIO7hhSCf1LUDAD48GN/2EVo7rAgqQWwMQYiIiJLOplWCGJFvUkMQZ+qHIP6LKT473skWMRnK45XR1RdYCZIPZT+YC2ooWwSEIGkQUhNReAxBMpnbd2IvYlolCNthAUrrmlZ1GJYIQ4gow6jPlW6dCTf9+RN8cKBF+9Lbe5qUD+I0E0SEKntO2uD1xuekgdvjxdE2ZTB6uBDEamE7LCIiolQhVhUr7bCUEKQnDQajix75gNIu6WhbbxK3hhKlq88FWQZKJZt2WYnRoX2NKBv4P99xODpR+mMIkslcgS1eIqJXQxBWggBQXvQ86onK5m7+TogykhqC1DY6sK2+E4U5Rlx3+hgAfiGIeB4dRggiyzIOtyhhRbfDjYaO+Jw0ONbeC5dHRo5Rj1GFoZ/vOROEiIgodYhKEGuOMa0Go3f2Bu5H1DZ0JGlLKJHECvjRxm7tshK9cjw88DFAlKnaenwhSA9DEKK0xxAkk2nDfqOpBFHbYbESBEBg8JFOIUi/y4ONh9vYr5UoAm2dygq3docOFQVmvPTVRbj7kqkAgK31HWjtcfhCEHfsFWEt3Y6Agae7T9rCXDty2jyQijzodFLI6zEEISIiSh1BK0HS4CTboBCEw9EzUqe6An60wReCFOmV/WC2VqVsEVgJwsc9UbpjCJKpZHnQsN+IsBIkQItf8NHW49CqQlLdqvcO4YYnNuHFTxuSvSlEKe1QczeeWr8XAKA35eDl2xdjWlUBRhXlYM7oQsgy8O7eJsAgKkFir94QVSDCrhNdIa4ZHW0eSHnoVlgAZ4IQERGlEtFaxWoxIM+sB4CAxRKpSpwc16sLLzgcPTOJSpAKvW/RjlWnhCBcUEPZQJblAYPRU//5mYjCYwiSqfxDDDHnIxJaJQhDECAwBPHKShCSDvacUnZWDzR1D3FNouz26LuH4HYowcbi6WNQU5Krfe3SmZUA1JZYWjus2CtBDosh66p4VYKI+w03DwRQ2m0APHAlIiJKNlmWtVXFVotfO6w0GIzeqe5HnDa2GIBy3NHvSv1ZJhQdUfFTBg5Gp+zU43DD5fEtguVgdKL0xxAkU7n9+tYbYqkEYTssYHALrHRpiXVcnTXQ2MVh7kThNLT3wgzlQC4nJzfga5fNUkKQDw+2oh9KgDCcmSBH1EqQM8YrJw12n+yCLA+/uuywaIcVYSUID1yJiIiSy+70QBSYF1iMWjusdJgJItrDzB5diNI8E1weOW4LOyh1tKt/52LZF4LkMQShLNJhD3ycsx0WUfpjCJKpRCWIpAP0xshvJ6pGWAkCILASBACau1M/VJBlGcc7lB3UJlvqby9RMrX2OGCR1NB3QGA8rbIANSU5cLi92HJC/V9yxx6CiIqNz82phl4nobXHOWSwuvVYB052hv6e/sPWh6oEKcxVXgscbi9XbBIRESWRaE1p0EmwGHVaJUg6tMPqUisEinONmF9TBIAtsTJRh9oGyOrxDb7PkZWFdgxBKBu02QOP09JhZhMRhRdVCPLQQw/hjDPOQEFBASoqKrB8+XLs379/yNv97W9/w/Tp02GxWDBnzhy8+eabMW8wRUisVjbkAFLoQbmD6NV2WKwEATA49GiypX441NHrQq9TOcGZDttLlCyyLCshCNTnO6Ml4OuSJOGymVUAgHV1aiurYbTDOtKq3MfMaismlecBCD8XZOfxLvznHzfg1me2hLxOo60fPQ439DoJ40rzwn7/fJMBYm4654IQEREljzYPJMcISZK0EKTf5YXb403mpg1JVIIUMQTJaB29ThjhRo7H117Z4lFCENEqiyiT+Q9FBzgThCgTRBWCrF+/HnfccQc2bdqEt99+Gy6XC5dddhnsdnvI22zYsAE33HADbrnlFmzfvh3Lly/H8uXLsWvXrmFvPIXhVk/URTMPxP/6rAQB4KsEEQcmzWkQKohWWADQkkbD3IlGmt3pQb/Lq7XDgsEy6DpiLsi6w+oBoKsXiKGFVb/Lo1VoTarIx+xRhQDCzwV5e08jZFm5zqmu4NUgYij6uNJcmAzhX9J1OolzQYiIiFKAaKtSYFGOMUQ7LEDZP0ll4gR4Ua4J88cWAQBqGzrC3ILSUbvdhVIELtYxeXoAyNyPpKzQ1hMYgqRDpR4RhRdVCPLWW2/h5ptvxqxZszBv3jysWbMG9fX12Lp1a8jbPProo1i2bBnuuecezJgxAz/5yU+wcOFCrFq1atgbT2GIShBjFPNAAF/rLFaCAFBCBACYOcoKID3aYYkTrQDg8Sor3YlosFY15MzThw5BTh9XjOJcI5r6xMulDHiif3482maHLANWiwGleSbtOSVcJcj6Ay3axxsPtwW9jghBJg8xD0SwWhiCEFEKatoNvPo1oLM+2VtCNCJsfkPRAcBk0MGkV/Y1Un0uiC8EMWLumCIAQEN7H9p4zJFROnudKJPU/VSTsp+pl90wwzUiFcXxmJtHNByiEkSrpOdMEKK0N6yZIF1dyotiSUlJyOts3LgRl1xyScBlS5cuxcaNG0PexuFwwGazBbxRlLRKkMEn9cLSsxLEX4ta+TFLC0FS//dyoiNwxTjnghAFJwJCq0FdcRkkNDbodbhoeiX6YfJd6OoddL2hHG5WKiYnVeRDkiTMHh2+EqTd7sQOv4Dk40PBQxAxZ2SoeSACh6MTUUra/ARQ+1eg9vlkbwnRiBBtVUQlCADkmfUA0iAE6VMHZueaUJhj1PZB2BIrs7T7hyDFE7TL89GX8P3INR/XYcFP3g67WIgo0drVweiji5VjRFaCEKW/mEMQr9eLu+++G+eccw5mz54d8nqNjY2orKwMuKyyshKNjY0hb/PQQw+hsLBQe6upqYl1M7OXCEGirQQR7bDcqX+yP9H6nB50qy90s9TWNekQgvi3wwKAxq70CEH6XR68s6cp5Q/8KHOIECRfrz7mQrQPvGxWJVzQwy1eMmOYC3JEDSsmliknCkQlyInOPm3wpL+PDrVClqGtCt14uDXoijitEoQhCBGls7525X1v8MCXKNPYgoYgqT8cXZZldKiVIGKfgnNBMlOH3YlyEYIUVAKmAgBAvpT4EGTt7iZ09rqw6QhfEyh52tXB6ONKlLmLnAlClP5iDkHuuOMO7Nq1Cy+88EI8twcAsHLlSnR1dWlvDQ0Ncf8eGc8VayWIuto5hnYvmUbMAzEbdNoQ45Y0qKo4HksliCf5L+jPfVKPrzyzBb9//1CyN4WyhDbzRwtBgofG500pg9mgR7+sPj/GUgmihiCTKpTnEqvFiHGluQCAPacGV4Os36+0wrr+jBqY9Dqc7OrHsbbB3/eQqDCJsB2WOGHBwehElFL6OpX3/Vz1S9lBvA6LdliAbwah3ZG6M0H6XV443crg9uI8Zb+IIUjm8XiVuR9lUPdR8yoAsxqCoE+rBkqUJrUFNRftUDKJSpCx6jFbD0MQorQXUwhy55134vXXX8f777+PMWPGhL1uVVUVmpqaAi5rampCVVVVyNuYzWZYrdaAN4qSWz0RHm0IwkoQTUuPsvNVYTWjwmpRL3OkfH9SEYKMV1+sG4cKQdoOA7+aALzzQIK3LLxjbcrJ3J0se6YR0qIOu8uV1AMsY/Dny1yTAedNKfe1xHLHUAnSqjy+RSUI4GuzN7DUX5ZlfHhQCUGWzqrCAnXo6IYBc0G6el1aNcukCCtBfIPRuRNPRClEhB/9nUndDKJo7TrRhVe2H4/6dr52WL4QJB0qQUSPfINOQp5Jad+lhSD1nfB6U/s4iSJj63PBK8PXDiu/XAtBCqQ+9Lu8cLgTF9Y1qZ0MxOONKBl8lSDKeZVuzgQhSntRhSCyLOPOO+/EK6+8gvfeew8TJkwY8jaLFi3Cu+++G3DZ22+/jUWLFkW3pRQdUQkS4qReSKwE0YhV4uX5ZpTnK+GQy+MrAU9Fsixr7bBOG6fM6mmyDRFoNWwGHDbg8HuJ3ryw2tSWQEda7EndDsoeIkCwSKEHowuXzfSbCxJlOyxZlnFYa1uVp10u2uwNnAuyr7Ebzd0O5Bj1OH18MRZPKgMAfHy4NeB6h1q6AQDVhRZt9ehQ2A6LiFKSCEFERQhRmvjaX7fhmy9+hj0hZnyFIk6mpVs7LN9QdBMkSZkWPL2qABajDt0ON4609iRz8yhORPhQpVf2Nf0rQQokZcFdovYlexxu2J0edTu4v0rJIx5/onrf7vTAw6CXKK1FFYLccccdePbZZ/Hcc8+hoKAAjY2NaGxsRF+fr/3OihUrsHLlSu3zb3zjG3jrrbfw8MMPY9++fXjggQewZcsW3HnnnfH7KWgwVoIMm5j/UVFggcmgQ3GuUb08dVtidfa6tJ3GheOKAETQDkv0307yiYd2NQQ52dWHflfqtgGgzNEqWt5BDX3DPF9eNKNCa4fV2tER1fdp7nbA7vRAr5MwtsQ/BFErQU4GVoKsP6BUgZw9sQQWox6LJ5cCADYdbgtYYRntPBCAIQgRpSitEoTVoJQ+Grv6Ud+uLD4SFc2REjNBRIUmAOSnwWD0TvXkeFGub7sNeh3mjFYWdmyv70zGZlGciRCkUi/aYfkqQcqNytcS1VrVf55lJytBKInE+YkatRIESO2QmoiGFlUI8thjj6GrqwsXXHABqqurtbcXX3xRu059fT1OnTqlfb548WI899xz+NOf/oR58+bh73//O1599dWww9QpDkSIEe1gdL0agnhdgNcb321KM1olSIHyO6koUE6QNg9VWZFEohVWWb5ZG+A15GB0MYw0RUIQWQbqWlkNQoknKkFMIgQJ83xZlm+GzqTsANfWNUb1fcQ8kLEluTAZfC+7ohKkrtUecMLjAzUEOX9qOQBg3pgi5Jr0aLM7caC5W7ueCEEinQcCMAQhohQky2yHRWlpe71vUcSQ7WcHCFoJYkqDShB1/6HYLwQBOBck04hZCMHaYZUZlf3nRO1LNvv9L3XYub9KyeHyeLXHeHVhjnYMl8rPz0Q0tMj6Z6gimYWwbt26QZdde+21uPbaa6P5VjRcrlgrQUy+jz1OQBfl7TPIoBDEasb+pm6tQiQVnehUVqONKc5BVaGy3RFXgji6AK8H0OkTuYkhiRAEUFpizajmLCBKrFZ1JojBq/5Pi0q4EHLy8oEu4NCJZlwSxfc53CLmgeQFXF5eYEal1YwmmwN7T9lw+vgS2B1ubDmqnFRZooYgJoMOZ4wvwfoDLdhwqA3Tq6wB9xtLJchID0aXZRlurwyjPqZRZESUyZx2QFYrQNkOi9LItmGFIGolSJB2WKlcCSIqBApzTAGXz68pBlDHECRDiL9ziayGIHkVgFnZ/yxVQ5DOBLWq8v9fYiUIJYt4fEuScvxUYDagze1UA+woFxoTUcqIKgShNCIG90Ybguj9TgJ6HNHPFMkgvnZYyu9EhCGp3A5LVIKMKc5BpTrM3dbvRp/TgxxTiHCj12/Ycn8XkFuS6M0cRJblgMF3R1rYT5gST1SCGDwiBAm/Q2uy5AJdQE9PdI9P8XieWJ436GuzRxWiydaM3SeVEGTTkTY4PV6MKc7BBL/QZPGkUiUEOdyKL5+rzOOKpR2WNUd52U9kJcjWYx3Yeqwdxzv6cKKjT3nf2Yc+lwe/umYurjltTMK+NxGlIf8WWO4+pZp5iFCaKBVs82v91DRU5fUAYjGC1W8wuqgKSeUQRJwYHFQJMrYIgDLXLOxxB6WFDrsTeniQ7xWVIL6ZIMX6xFaC+M+z5EwQShaxQLMoxwi9TkKBxYA2uxM9/an7/ExEQ2MIkqlEJUisg9EBwJ3dKy/SuR3WmOJc5JsNyDXp0ev0oNHWH3BCNUBvu+/jvo6khCDdDjdcHl+l2RG2w6IE63W60avOz5E8kVWCmHKU/6He3uhCEFGxEaxt1axRVry7rxm7TigHmf6tsMTAUQDacPRPjrTD7fHC7ZXR0NEb8n5DSXQ7rFNdfbju8Y0hhwa+9tlJhiBEFGjgHJD+LuWEG1EKc7q92HnC99iNtRKkwC8E8Q1GT93ZeGL/oWhACDKq0ILyAjNauh3YdbILZ4wf+eMJip+OXhdK0A0dZEDSAbmlWghSqFMe64kLQXz/S30uD/pdHliMDNVoZIkQpCRPOT+Wr4bU3QxBiNIaQ5BM5Y5sZfMgOh2gMyozQType7J/JIiKD18IorxvSeF2WMc7fO2wJElCldWCI612NHaFC0H8K0E6E7+RQbT3BAZurAShRGvtVh5zOUa/EGSIGUoWNQSRnb2wO9zayYqh+CpBBocVM9W5ILtPKoMnPzjYCsDXCst3PSusFgNs/W7sOmmDSa+DLCuhRll+YEuKcLR2WP2JOXD99GgHPF4ZVVYLPr9wNMYU52BMcS76nG7c9uw21NZ3wOuVodNJQ98ZEWWHgSFIXydDEEp5e07Z4HT75ic2RblIyhZsJkg6tMMSq6NzA/c9JEnC/JoivL2nCbX1nQxB0lyH3YlSSR2KnluqtEtWQ5ACnbLobiRCEPF9GILQSNNawqkhSIE5scdQRDQy2Jw7U7ljrAQBfKuh3al7sj/RvF5ZmxcgKkAqrOnVDguA1hIr7Db7hyBJ6sXdph5QifOiR1rtEc0gIopVi9oKa1Se38vgEO0DjWYlxLDAhROdfRF9n36XR7vupGDtsEYr/ZUPNHXjUHMP6lrtMOgkLJ5UGnA9vU7CIvWyDYdbcajF1wrLv2JkKCIE6XV64PJ4h7h29GrV1iBLZ1Xi3mXTceNZ47BkajkunlEJi1EHW7+blV5EFChYJQhRihND0UWry8au/oj3Xd0er1aNas3xVVTkm5UTvXZn6oYgnSEqQQBggdoSa3tDx6CvUXpp73X6hqLnqaG0GoLkI7EhyMCqqg7OBaEkaAtRCcLB6ETpjSFIpnLFOBME8LXE8mTvDkdHrxMerwxJAkrVVdZaO6wUrQSRZTmgHRYAVBUq29wYqk+x1xvYDitJlSBiVdnUygJIklJm2tqTvY8/SjwxD6Q6zy9AGOr5Ug2VLZIDJzoiC0HqWu1axYbYifY3uigHhTlGuL0y/vzhEQDAwnHFAe0xBNESa+PhNt88kChaYQGBbTcScfAqTnwsGFsccLlRr8Pc0UXKdep5coSI/AwKQTqTshlE0RDzQC6fXQVAadtji7BNiv9JtIBKEFPqn2QTg6qLcwfv0yxUX/s/ONCa0pXzNLTOXifKIEIQZf9ThCB5stJ5oCtB8zoGztfpsHPlPY28jgEhSAHbYRFlBIYgmSrWwegAK0HgCzpKck0w6pV/E9EOq9nmSMkqha4+l3bQJCpBRPVKyD7Fji5A9us73Jeck5Oi52ZVoUXbdrbEokQSB+dVuer/ss4A6Idob6U+n1rgxPEIK0EOq4/jSeV5QSs2JEnSqkFe3nYcwOBWWIKoDvn0aDv2nlJaFEQzFB2ANtgPiH8I4nR7tbZe82uKBn3dt0K0M67fl4jSXLB2WEQpTgT6iyaWaVWWA9v4hGLrU/bXc4x67TgDAPLToB2WGIxelDN4scYZ40swZ3Qhehxu/PKtfSO9aRRH7Xa/ShDRntCs7K9avGoIkoDFNF6vrB2Hjy5Sjgk7WQlCSSDOT4jAt0DMbGIIQpTWGIJkKm0wepQzQQBWgmDwUHTAFyj0uTwpuUJLVIGU5Zu0vqlV1iGGuftXgQBJb4dVkmfCxDLlpC5b5lAiiUoQLQSJZH6SUamwyoEz4kqQI+pQ9GDzQIRZ6lwQl0fZlvOnBA9BJlfko7zAjH6XF+v2N2uXRStRw9H3qv3Ri3ONGFeaO+jrWgiirp4lIgLAShBKO83d/Tje0QdJAubVFGr72yErrwcINg8E8J8JkrqD0TtECBKkEkSvk/Djq2cBAP6+9Ti2sfIzbXX0ukK2w7J4lX3bRIQgbXYn3Go3himV+dq2EI20gYPRRTV9N2eCEKU1hiCZShuMzkqQWAQLQXJNBm2FViq2xBIhyOhi38lH7aAs1Mq0gSFIstphicFjuSatt3I6V4L8f2v34+yfv4uTEVYL0MgTIUiZeIo0mENfWTD6KkEinQniqwQJF4JYtY9L80wBn/uTJN+sEBGYpFIIIlbFzq8pClr1Ilpk7W+0pfQqVyIaYQP3PRiCUIoTYf60ygIUWIyoLBxif3sA0U4lVAiSioutAKX1blefGIw+uBIEUFpiXbNwDADggf/bDa839arnKTyvV0ZnrxPlWiWIujhHnY1ndCcuBBHVVGX5ZpTlK/vmnAlCyTBoMLpoh5Wiz89EFBmGIJnKPZxKEPVkoCf1TvSPlOYgIQgQ2BIr1RzvUEqTRTspAKgYamWa/1B0IHmVIOr8j5J8k7ZiXqygTzfd/S488eERNNr68eHBlmRvDoXQ2q085spz1OHgkTxXikoQyYET6v/bUHyVIIOHoguiEgQAzptSBp0u9KBz/4HpZoMOo4qif44XIYgtzgevtWqbq/k1xUG/Xmm1YFShBV4Z2HGcg4+JSMV2WJRmRIWDqHCsUqvFB84yCEVUglgHtJTK9wtBUrH1rt3p0RZhBJsJItx7+TTkmw3YcbwLL21pGKnNozix9bvgleE3EySwEsTgUhb4JDIEqbSaUawGbWyHRcmgnZ8YMBidM0GI0htDkEylDUaPYHXzQAZ1p9advTscwSpB/D9v7o7sIGck+Yai+06KisHozd39wQ+mBoUgyZoJovy+S/NMmFSmVoKkaTusf+9ugsOtnFg/1hbZiXIaeaISpMQs2mFFUDVnUgK6fPRFVAkiy7JW0RSuEmRCWR5yTUoLu/NDzAMRxHB0QGmxpQ8TmIRitSSoEkQNQcRJoWBENYgYoE5EpIUgBdWBnxOlKFEJIl7Thqy8HsBXCRIYguSZlX0Bj1fW9iVTiTgZbTLoYDGGPo1QUWDB3ZdMAQD8au3+hA3QpsQQ7afKdd3KBQNmgug8/TDAjc6EhCBqu1qrRWu5xnZYlAyDK0GU52vOBCFKbwxBMpWoBImkz/1ArATRQo6KgsATo6KyoiWF22GN8WuHJSpXXB5Z62sZQIQgYg5Mkk48tKs7tyV5Zq0SpL69F84UPAAcyqu1J7SPj7UzBElVIgQpNqp9tyMJQXJLlNtIPWjudgz5+GyyOWB3eqDXSRhbMnhGhqDXSbhtySScM7kUl82qCnufNSW5WtAZSyssIDGVIO12pxb6zQsyFF0QAUkt54IQkSD2PYrGqZ93Jm1TiIbi8nix43gnAGCh+pom2mFFOhi9O9RMEJPv81RsiSWGohfnGoO2vfT3pcXjMbkiH+12Jx5558BIbB7FiThmLNeJShB1AY7Jt9+Zh3443V70u+I7v0YEiRVWi1Zt1MkQhEaYLMvazNKBg9G7HXw8EqUzhiCZSszzMMYyE4SVIKEqQbR2WCkZggxuh2XU61CWr/w9g65OEyFI8QTlfZJaUIhKkJI8IyqtZuSZ9PB4ZdSnUIggyzLcnvAnvZu7+/HxoVbt83pWgqSsVrXEuUiEIJE8V+YqrahKpG7IMnCqK3w1iKgCGVeSC5Mh/Mvt1y+egr9+5WytFUY4F0xTqkXmji4c4prBFebGvxLkM7UKZGJ5nhayBKMNR2/oTMlWH0SUBFoIMlZ5z3ZYlML2N3aj3+WF1WLAxDLlpHC0lSC2PiXgsA6oBNHpJK0yNBVnZ4mT0UU5oVthCUa9Dg9cpQxJ/8umY9jXaEvotlH8dNidkOBFsTygHZbBpC0aKtQpj/V4VxU3q/9DSiUI22FRcvQ6Pdpit9L8wJkgrAQhSm8MQTKVi5Ugw9GirhIvzw81EyT12mGJ9jw1xYF/80prmNVpIgQpnaS8T9Lqy3at56YZkiRhQooNR3e6vbjskQ9w+aMfos8ZesXTGztOwSsrbb0A4Fhberb0ynT9Lo+2wtJqiqISJEepBCmRlL/riY7wIYgYih4wD6TuA+D/mwbseS3Krfa5d9l0PHztPKxYPC6m2ydiMLoYir4gxDwQYdaoQhj1Elq6HREPlyeiDCdCkOJxgZ8TpSAxD2T+2GJthlelNoMvsmMnUQlitQxe+JDKw9FFe5jCEEPRBzp3Shkun10Fj1fGj17bzcUPaaKj14lC2GGAuo+c59eqVZ0LUmVWHgvxDkEag4QgHIxOI01UQ5kNOuQYlWCaM0GIMgNDkEzljsdMkCwOQdR+pBXWASGINTUrQbr6XNoL8uiiwLY7VVoIEmSbxQyQkomBn4+gfpcHdjVYED03xcq6VJkLsuVYOw429+Bgcw/+suloyOu9WnsSAHDLeUplja3fzdVLKUhUepkMOuRA/ftE0Q4rH3bo4dFa0IVyWB2KHjAPZPerQE8jsOOlqLdbKLAYcc1pY2A26GO6vTURIYgYih5mHggAWIx6zKxWekpvZ0ssIgLYDovSinjtWuj3eidm8LXZHXANUTUM+M8EGRyCiJYrdkd82wzFg5gBURxhCAIAP7hiBixGHT6pa8fa3Y2J2jSKo45eJ8ok9XnZUuQ7NwBoIUhlgkKQJr9jcLbDomQRIUhpnklr/SdmgnSnYEBNRJFjCJKJZNlXCWIcTiVIdp687XN6tBe3we2wxKDx1ApBRCus0jwTckyBJ0ZFn+LGrnCVIJOV984ewDOyO5pidY9BJ2kr4sTK+bqW1AhB1u9v0T7+4/ojQVfnHW2147OGTuh1Eq49rUZ77HA4eupp9av0kkRgHEk7LEsRAGVHuAg9OD5EJUPQSpC2g8r7pt3RbHJcxbsSxOuVUSuGooeZByLMV6/DECQ1dfW58LM39mDPSbYuoREgy4PbYbEShFKYqAQRQ9EBoCTXBKNegixHdoxgE5UgQdpH5mkhSOqdaOtUTwxG0g5LGFOciy+foywOemnL8YRsF8VXR68L5SIEEUPRBTUEKTcpj4V4BxSic0FVod9MkD4Xq4hoRLWr5yeK83zPdaJlsdPthcOdeiE1EUWGIUgm8jgBqDsKkaxuHkhUj2RpJYhYJW4x6rTVWEKqtsPyDUUfHHpVFkTQDqtkgu+yET750Nbj28kQKy3EcPQjranRDmudGoIYdBLa7U48veHooOu8plaBnDO5DOUFZowvVSpyOBw99Yh5IGX5Jt/zXCTPlXoDYFHmcBRL3UO2wzoSrBKkVQ1BOuoAR3d0Gx4nvhAkPidYjrTa0d3vhsWow/SqgiGvL04cbW8Y+cozGtrftjTgiQ/rsOr9g8neFMoGzh5AVk8maO2wbIB36NX0RCOttcehLW6Z7xf663SStlAq6KKjAcJVguSZlcVMqdgOS1SCFOVFXgkCAF9YOAYA8MGBFlZIp4EOuxNlGDAPRDAr1bylRmX/OZ6VIA63R1uBX1nga4fl8cqwsQURjSBfq+7BIQjAuSBE6YwhSCZy++18x1QJoj7ZZ2klSEuP8vsrLzBrJ+UFcYBj63ej35U6KwB8IUjuoK9VFSrBTdgQJK9C26kd6ZZYohKk1G8nY2KZmAmS/EqQk5192N/UDZ0E3HfFDADA4+sPB+z0y7KM1z47AQC4et4oAMDYEuVnqOdckJQjgs6yfLPf/KQIA2O1JVYxenCiM3TA1ef0aDMvRKiHfhvQfcp3pea90W14nIgQxBanA1cxD2Tu6CIY9EPvVojh6LtP2LiSKgXtOK6c+DjZmVphP2UosfBCZwQKqtULZcDBahBKPbVqBePkinzttVQQLbGC7m8PIGaCFJgHhwn5KVwJIvbZo6kEAZTf14xqK9xemS2x0kC73YlSSa0GzS8P/KJaCVKij38I0mzztastyjXCYtRr8xgYntFIEs91/iGIXichT+24wbkgROmLIUgmcomdb8kXaESDlSAABg9FBwBrjgEmgy7geqlAtMMKWgkihjUOnAni9fgCj9xStdUPgL7OBG1lcGLFjyh5BoAJagjSZneiK8l9YNcfUKpA5tUU4b8XjceUinzY+t1Y/VGddp1dJ2w40mKH2aDD0tlVAIBxohKE7bBSjtYOq8DsC40jDYzV4ejFUnfYwd6HmpUqpuJco28Hum3AyvqmXZFvdBzFux1WbYTzQISxJbkoyTPB6fGy5VIK2nVSOfmcSq9xlMFECGIpVPY/DTmBlxOlENEKa2GQ17sqa+SVIGJVe7h2WKlYCSL2yaOZCSJcOVcJOf/52akhrknJ1tnr8s0EyQseghQZlMd5PEMQESBWWn0LEYu14eicC0IjJ9j5CcBvLghDEKK0xRAkE7n9VjYPqGSISAIrQfpdHjSkeHsg0ctXVH34kyTJ1xKrO3VWyYZth2UNsTKtvwuQ1XYTuSVATpF6eWeCtjI40Q6rJN+3k5FnNmgHk4eT3BJr3f5mAMAFUyug10n45qVTAQBPflSHDnUH6bVapQrkkpmV2gq+cWyHlbJECFKW7xeCGAaHnkHllgIAiqQenOrsh8cbvEfxzhPKwePs0YV+3/hQ4JUakxOCiNk7PQ433BEMcB2KFoJEMA8EUJ5HF3AuSErqcbhR16pUr7X0ONiDmxLPPwQBfPsiI7wggygSvqHoxYO+FnJ/OwitEiRoO6zUH4xeFEMIctVcpVJ6w+FWbT+MUlN7b7h2WEoIUigpj/N4VRUDvqHo4hgQAIq04eisBKGR4z8Y3V+++pzd7WAoR5SuGIJkIlEJEsmg32ASVAkiyzJufWYLzv/1+/hMPWmWirRKkILgJ0V9c0FSZwf+RLh2WOqOZLvdGdh6RrTCMhfCIxkgJ+nEQ7B2WIBvmHQyW2I53V58dLAVAHDBNGUl1LJZVZhRbUWPw40/fXgEHq+M//tMmQeyfP5o7bZjS5S/RT0rQVKOLwQx+Z4vDRFWgqjtsMqkHri9csgwVKymDwxBDijvRdVVkoaj+688He5Kpj6nB/saldkmCyKsBPG/7vYUfi2IiiwD7/8c2P7XZG/JsOw5aYPIPZxuL3twU+INDEHE8+MIL8ggGorb48VnxzsBBA5FF0T72cYIQhBbX+iZIFo7LGfqPf9q7bByo+80MLY0F/PGFMIrA//ayWqQVNbZ6/RVgoRoh1Ug9WnXjRfxv1MREIIY1e/Dk840crRKkLyBlSBqCML9Y6K0xRAkE2mVIDHMAwEAvXry3xPfk/zv7WvGhwdbIcvAO3ub4nrf8dSiVYKECkGUHbPmFGoVEq4dVlGuUWvhFRDcqCGI01yEWT96C3va1aeDEZ4J0hai3NQXgiSvEmTLsXbYnR6U5pkwRz2ZrdNJ+JZaDbLm46N4fcdJNHc7UJhjxJKpvgOFcaXK9jfa+lNqfgwBrd3qYPSAdlgRhsZqO6zRFuV5NtRw9N2iEmRUkBBkxlXK+6bdSRn+a9TrtJ62w21jsPNEFzxeGZVWM6oLI3/N0Yaj14/wcPTWQ8BHjwDOOIerrQeA9b8E3rwHSOPqiV0nAlsQsSUWJdygEKQw8HKiFHGgqQe9Tg8KzAZMqcgf9PXKCNth9bs8cKpVmEHbYZlSvx1WLJUgAHClWg3yzx0MQVKV1yujI6AdVvBKkDwo+7/xnQmi/O/4V4KI48OOOIYth1t6IqrYouwlQpCSgZUgol0hQxCitMUQJBOJCo6YK0HUJ3t3/HY2PF4Zv3prv/b5J0fa43bf8dY8VCWINbXaYXX1ubTVuqODhCCSJKHSGmQ4eq/yN2jx5KPf5cWudrV12givvmxX22GV5g8IQcqUA8xkVoKs36/MA1kytRw6na+13CUzKjBvTCH6XB7c+/IOAMDn5lRrYROg9LAtUHeUUr0FXLYJ3g4rusHo1UblbxpsLojL48VetTpi9mir3zdWZ4JMv0JpO+jsBrrqY/gJhi9ec0FEiLGgZvCq2HDmjimEJCmt/Eb0ufS9B4F3HgDe+1l877f9iPLeZU/rk7cMQWjEsR0WpYntDcrr3byaooB9QqEqwnZYYgWxJAH5pmDtsJRFCql2kk2WZa0d1sCFS5G6Qp0L8unR9ohmp9DI6+53w+OVUaYNRh8Ygij7tbmysh8czxCk0W8miFAU55kg7XYnLv/th7j2jxvZ8pNCag8yGB0ArNpMEFYmEaUrhiCZyOU3EyQWCagEeXX7Cexv6oZZPUlc29CZsqvj060dlliJXpJnQm6QgynAb1hjQAiiVII09Ctf65DVVW0jPRg9xE6GVgmSxJkg60QIMi2wFFySJHzrsmkAgH6Xsppv+fxRg64zlsPRU1KLfwgS7fOlGoJU6JVw7niQSpCDTT1wur0osBi0tmjweoD2w8rHFTOAcuXxk+yWWMM9eI12KLpQYDFiaoWymrB2JOeCdBxT3m9ZDdhOxvF+j/o+7kndSsehiDZuevUEX6qE/ZTBRAgiwg+2w6IUJRblzKguCPr1qkLfvna4k6s29eRZvtkQNEzR2mGlWCVIt8OtzUErDFLBEolRRTk4fVwxZBl4gy2xUpJScSGjHOEHo1u88Q9BfIPRB1eCxKvtVl2rHU6PF/XtvUH34YkAaHM/B56fKLCkbqUeEUWGIUgminZl80BxrgRxuD34zdtKG5i7L5mK8gIznB5vyg7EFSd9gg1G9788VdphhWuFJfiGNQ5uh3XCqZyk7ZKV0MHdG75K59Oj7dh6LH6VPFq56YBVZZPKlVDmaFtvyOHTA7X2OPDMxqNxOXA82dmH/U3d0EnA+VPKB339/CllOH2csvp9VKEFZ4wvGXQdDkdPPf0uj7YKszzfDNiVmS9i4PmQ1HZYxZISzgWrBNHmgYwqhCSpJzg6jwEep/K8XFgDVM5WLk/ScPR4VYJEOxTdX1LmgnQ3Ku/d/cCHD8fvfkW4AqRtCNLn9OBQs/K4Pk19bmMlCCUc22FRmhAnaKtCtH4U+9r9Lq828yMYsQ8iVhQPJAajhzrJ9o9tx3Hpb9bj7T0j+1rTaVf2F3KMeliM+pjv56p5yqKh13fEcSECxU17rxP56INZUvcPQ4QgJo8SCnaFeaxHK/hg9PhWgrT4Le7YeYKvMzSYx+uregvVDoszQYjSF0OQTCRWNhtTYybIs5vqcaKzD5VWM25ePB5nTVBOIm6uS72WWF6vjFa1PVOoSpByrR1WapwcOq4NRQ/99w5aoq+GIO1yAc6cUAJdbhEAoLEx9Mqs3Se7cP3jG/HFJz6J28ofLQQZ0A5rVFEOTAYdnG5vyLkLAz3y9gHc/9purPzHzmFv1/oDShXIvJqiQUPRAKXS4/6rZmJMcQ7uvGhK0NV8Y0uUYOlYW/JaelEgMYPGpNfBmmPwnbAuqIrsDtRKkAKv0iYg2GNTtBQK2gqrdDKg0/tCkKbkhCBiZZ1oDRaLxq5+nOrqh05S2ltFSwtBRmouiMcN2Jt9n299OjC8GA7/SpDu9AxB9pyywSsrr31ilk3LMB4fRBFRKz4OdOlwzi/ewwmHuu/FdliUYkQFuH+rHn8Wo147YRtuOLpooxJsKDow9GD0Fz5twMHmHvzvX7bg9+8fGrGWPp19Yih6bFUgwuVzqqCTgO31nWwXm4IChqKb8gFTbuAV1BDE6FYWTXT1OePyGJRleUQqQfyP3z873hmX+6TM0tnr1Mb7FQ2oeisQ7bBYCUKUthiCZCIxEyTmShBz4P0MQ3e/C79//xAApQokx6THWROVFdef1LUN+/7jraPXCY9XhiQNnlEhVKqVIC0p0ibEF4LkhrxO0GGNasVHh1yAy2ZWYuG0icrnbS1Bd2a9Xhn3v7YbXhlwuL345Mjw/34er6zt1A5caaHXSZhQGl1LrC1HlZOp//fZSWw8PLztW7dfOVl6wdSKkNeZO6YIH917Eb541tigXx/Hdlgpp1U9+CnNNylVGj3qSfGBPY9DUStGLG7lADFoJYgWggQZil46WXlfOUt5n6QQZIJoNzeMmTu1an/0aVXWkK34whHD0Xcc74q42mtY7C2A7AUkPTDhfMDrAj74VXzuu9O/EqQxPvc5hP2N3XFdTLBbq2CyaosAWAlCCadWfGxu9OJEZx92J2k+GdFQGoOcoB0oaPvZAUSVSKhKkHyLaIcVvG3w0VbldVuWgV+v3Y+7nt+OPmfiWwx3aEPRY5sHIlQUWHDWBGVfii2xUk+73YWyUK2wAC0E0buUYzOXR0ZfHFpcdzvc6FUfxwEhSJ7yf9IZp0oQ/wWBO4+zEoQGEws0C3OMMOgDT5eK52dWghClL4Ygmcg9zEoQk3JyDA7bsDfliQ+OoN3uxMTyPFx72hgAwNlqJci2+g443d5hf494EqtDSnJNMOqD/3uIwehtdifcnuRv/4nOCNphFQ4+KHP1KJUO7SjAJTMqcdasSQAAo8sWNED4x/YT2HrMt2J7wzBDBkBpxSPOfRbLXcD7Pwc6G7SvT4ziRG2Pw40Dzd3a5z/6v11wxfj3cbq9+PiQ8vNdMC3IAUCExqnzIOq50i1lBAxFd3Qrg6wBIC/CEERth2V0dkKCUqXkHxq6PV7sOaU8dwaGIGolSNlU5X3VHOV9ex3gGPm5N1MqlHZzB/3+Z6IlWhouiHIeiDC5PB8FZgN6nZ6RaUnQrZ5sya8ELrpf+bj2eaD10PDuV5ZHfCaI1yvjxj9/ghue2BS3oMI/vKtgCEIjRQ1BjnQr7XWanJaAy4lSQcAq9RDtcgG/9rNhhn4PVQmSZwrdDsvucGvHKisvnw6DTsLrO07h2sc34GSQRRnxJBYtDVwZHQvREuufn7ElVqrpsDtDD0UHtMHokqNHmx8Wj+4Azer/l9ViQI7J125NhG4d8aoEsTkwTapHNdqw83gXvCOxCIfSighBSoN0gtBmgnAwOlHaYgiSiVxiJkjwcu0hFY9X3rfXAcMob23pduDPH9UBAO65bJqWpE+uyEdJngn9Li92pFgZ6lBD0QElIDHoJMgytNZZyRRNO6xmvxCku105UWcqKMP4sjzkFyqrsgolO57acDTg9l19LvziX3sBAGeMV1ZvbzjcOuS2Pb+5Hl98YhO6Qqzeabcrv2+rxQDj1ieB9b8ENvxO+3o0w9F3Hu+CLCsnt0vyTDjQ1IOnB/wckdp6rAM9DjdK80yYMzr6Nj+CGIx+vCPyuSaUWAH/46IKxJQPmPMjuwO1HZYke1GAXvS5PAF9io+02tHv8iLPpNcqmQAMDkHyypST8ZCBln3D+ZFiMkUdSi5mQMRCtBGIZR4IAOh0EpaoIeNLWxqGuHYciBDEWg3UnAFMXQbIHmD9L4Z3v/ZWwOUXdI5AO6yGjl609jjg8co43BKfEG3nCV94x0oQGjEiBOlRTiwc71dPOrAdFqUQW58bDnXhVkWIdlhAZJUgYgXxkO2wgoQgR9X2qsW5Rnx1yST89StnoSTPhF0nbPiPVR8HLFaKN7ESX6zMH45ls6ug10nYfdKGI3F6DaP4qG/v9bXDClMJIjm7UWRRwop4hCCNXeo8kMLAkFGEbvGqBOntbMY/TT/A86afotvh1v6niAQRuAVrh13AmSBEaY8hSCYSlSCGGCtBiicAkJRKEPvQJ7pD+X/vHUSv04N5NUVYNtvXb1+SJJypDpH+JMXmgjRHEILodJKyihy+IerJFFk7LGV7G2392qp1d4/yt50yYbxyJUsRAKAIPXhnbxPq/Vo4PfL2AbT2ODGpPA+//+JCAMCBpp6wJ8jcHi9+9dY+bDjchn/vCd4epl0dsliabwbaD6sX1mlfn1CmnJiOpBJEnJA9c0Ix7l02DQDw23cOBgQ/kRKtsJZMLQ866yNS1YU5MOoluDxywlfoUWR8lSAm34r9/MrI78BgVkITAJPylZ1k/7kgYjX9rFGFgY8d0Q6rbIrvMtESq3H4M2yiNalCCWhae5zaiqdoif/LaZUFMW/HjWeNAwC8tv1EyCGwcSNCkIJq5f2F31fe7/w70LQn9vv1rwIBRqQd1p6TvkrN4xHOTAqn3+XBwSalKoghCI0oNQSxedX2kXb1pAPbYVEKaVL394tyjWGHggervB7Ipq4gtoaoqMgzK/ff6/QMWqVep7bCmlCmvIafNbEUr91xDqZXFaC1x4Fbnv4U/XFoTRSMOAldmDO8dliA0gL33MllAIDXd7AlVirZVt+BchGCBK0E8e3zVecoj7VBi92ObQCeugJojLzla6h2c2ImSI/DHZcOEnpbA0ySB+N1TchDH3awJRYNIOZHDmzVDfhmgiT8mIWIEoYhSCYSlSDGGGeCGC1AodK6SjsxHaX6tl4890k9AODeZdOU3vt+zpqYmiFIJJUggG8VmBiSmCy2fpe2+mZ0UZh2WOoOZb/LC1ufG26PFyZnJwBg3pQJypVylAqPHMkJo+zCMxuPAlBOtomPf/wfs1FhtWBmtVIKvTHMXJCtxzq0FfJHWoOHGKISpDjXCHTWqz/UCe3r0bTD+qxB/XnGFOHa02owv6YIPQ43fv7m3iFvO9C6/UqrsCXDaIUFKHNNaorZEiuViOqtsnxzbCEIoLXEmiJCkE7f31a0dZrlPxS9tx3oVQNlMRME8BuOvju67x8HuSaD9pwRSzVIr9PXkmO8f8VLlM6eWIKJ5XmwOz14dfuJoW8wHN1qOFGghvLV84CZVwOQgXU/j/1+RQiiU1f19jSHvGq87D3lC0HiMVj2QFM33F4ZxblGjCq0aK+B7b3OmNsKEkVEDUG6oDyPHOs1BlxOlAoiaYUF+CpBwrfDCl8Jkmf2XT5wOLqYBzK+zPe6W1OSi5dvX4yyfBM6e10Jay+prY4e5mB04cq5yoKE13ewJVaq6HW6sa+x228mSJAQxGDR9ncqzcpx3qBKkK1PA8c+ArY8GfH3DjYUHVDCQnEaobNv+B0YZHuL9vFoqZUhSBjZ2sWgQ4QgQeYfcSYIUfpjCJKJ3KIdVowhCACUKvMh0BZbCPLGzlNwe2UsnlSKxZPKBn1dDMTberQ9JeZqCBGHIAWiEiS5IYg4+VWcaww4aBrIYtSjSD1oaerux7ajrbDKyoHUzMlqCGK2AlD2Mgthx4tbGtDjcOP+13bBKwNXzKnGuVOUv+XiScrfb8Oh0JVCb+/xtYQ5HOIkq2+lhdkXgnQd174+Sa0EabT1B20L4K9WhCA1RdDpJDx49SxIEvBq7UlsimKI+8nOPuxv6oZOAs6fMrwQBPC1xOJw9NTQ4j8TRLQtinQoupCrBIbjc5XnWv+V+LtFS6FRfm3U2tSZE9bRgW23tBAkOcPRp1TGPhfkaKvvuadwGCdEJEnSqkH++kl9wHyVuNMqQXyVibjg+wAkYO8/gZO1sd1v51HlfdVc9fuMQCWIfwjSMfznlp1+80AkSUJJrgl6te1jrJVCREOSZV8liKy8VnZ61ZO7fZ3DaslKFE+NaqgRrhUWAFQV+iqvQ7FpM0GCv3aaDToY1ErSgcPR69TX3gkDFh/kmQ04fZyyQCNRLbHEie6iOIUgl82qglEv4UBTD46xJVFK2HG8Cx6vjNFG9bgtb/AxPCRJqwapMCv7B50DQxCxoK3hk4i/ty8ECfwf0+skFMapJZbL44Wh3/f/oYQgncO6z0z1rZdqcdbP383KfUBxfiJoOywtBOFMEKJ0xRAkEwUJQbYe68Adf92mrSAaUokIQWIbGLvrpHJQe16Ik8jTqgpgtRhgd3qw6+TwB7DHi2hvVTHESq9y9etNMbRaiqeP1RBi5ijrENf0rV5r7OrHht2HoJOUkwuGPCXQgE4HWJQTt7NKPOjud+N/n9mCLcc6kGPU4wdXzNDua/FkNQQJMRxdlmX82z8ECdHvV6y0qMyRfScoHTbtpEhhrlEbSnagKfSJ2iZbP0519UMnQZvhMXdMEb545lgAwI9e2x3xaub1B5QVQvNqioLu/ERLDEc/1s4DvFTQqgaXZQXDrwSpsSj//yfUVmder4zd6nPfnDH+Q9GDtMICfO2wmnYn5WSfGI4eSyWIOGExbhhVIMI1C0fDbNBh7ymbFmYmhFYJUu27rGI6MPc65eP3fxbb/YpKkLFnK+/7O30VmQmy95Tv+TAe7bB2+c0DAUTbR+X5jy2xKGGcPYCsvDbb1EoQURECrytw1g5REolFTwNXqQ+kDUYPF4L0KYt6rCFCEEmStIVNA1uuiPkF/pUgwmnjlAUaiQpBRCVIUZDV0bEozDFiprpgJKGv/RSxbfXKY6fGrO4XhlokpIYg5Ubl/8I2MAQRC9qadkc830n8z1QF+R8TLbE6hnlCvrXHgRLJt/80WmrF7pO2lFqQmQo8Xhlv7DiF1h6H1mkhm3SEG4zu99yc0IVbRJQwDEEykUs9IaK2w6prtePLaz7FGztP4ZdvRTiAV1SCxNgOS/QrnxXi5LxeJ+HMCcqJxM11ka/ST7ThVoK8t68J/736E+1EeqKt3a2cxF02q2qIawb2Kd6x/wgAwGksBPR+FSRqS6zrZiknR0XIcdfFkzHKr93WmRNKoddJqG/vDdqK5UBTD+rbeyFGIhxr6w0aQoiVFmMNAw7Y/KpBFqoHdR8dDF11InbQplYWBFTE3LN0Gopzjdjf1I1nNh4LeXt//96tnCi9YGqU1QEhjFVPEtezEiTu6lrtWPmPnfjfZ7bgv/60EZ979EOc+8v3MPeBtVj++4+D9sUOnAmiti0qiDIEyVVCwGqj8jcVM0Hq2uywOz2wGHWY6H+CQgtBpgbeT9lUQGdUgr+uERgMPsBwhqMfVR/P40tDzyKKVFGuCVfOHQVAqQZJGJsStH7YaAws8V9yr/L+4L8BewyvRx3qc0v1PECvvnb0NIW+/jB19jq14A0AjsehHZYW3o32hXecC0IJpy54cMIAB4zINxvQCzO8kj7g60TJFu4ErT/x9dYeZ8j5Bd1aJUjoCu5Qw9GPDpgJ4k/sL2871pGQk3NiFX5RiFkmsZinLhhhS6LUsO1YJwCgTFIXKAZrhwWo3QOAEoOyfxDQDkuWAZtocSYDx7dE9L0b1RbTFUH+x0T1UccwK0GabQ4U+4UgEwxt6HN5cCjEYr1sVd/eC4f6/HU8C2datquPs+CVIMpj0SsDdmdi5i8RUWIxBMlEWiVIDrr6XLjl6U+1nZO1uxsj6x+uVYIcifrbd/e7tMF9oUIQwNcS65MjqTMXRLTKqYhwJkiLWjnS3e/CvX/fgS+v2YIPD7bix//cnfDVAc22fm2112URhCBV6jZvrmtHd7tygk6fXxp4pZwiAMCF48zaSoeJZXn4yrkTA66WbzZoBy4bg1SDiCBhydRy5Jr0cHvloI87UWJbIw0IjfxCkIumKzvg7+0P3We/1m8eiL+iXBO+u2w6AGW4+1AriI539GKdGmBdOa867HUjpVWCxCkE+dfOU9jfGH37okz0g1d24vnN9fj3niZsOtKOPadsON7RB1u/G7UNnQEt2QQxE6R8ODNBcpUAt0yvHDSJlfhiKPqMaisMer+X19aDyvvSAZUgBhNQPk35OIrhkfEyWbTDaoohBAnSl3w4vniWUrX1z89ODh6wGS9qtdlPPujAa7V+80dKJwHFalvAphiG1IsQpHiC77GUwLkgogpEnEA7Zesf1rBQp9uLfep9+rdxK88XYX9yKx4pg4l5IHIuAAnnTC4FIMFhUAfvRriCmCjRQrXqGagkzwST+vof6rlzqJkggG84un8lSFefS1s8FOy1d/ZoK0x6HdrszoTMoRPHkvGokhbmqvvtbEmUfLIso7ZBOa7Md6nH5kNUggQNQXrbAI/f4omGTRF9/+YIKkG6hjkTpMnWjxL4OlDMyFFegxjCBdrf6PsdnYhDtXG6ETNLg1WCWIw66NVVnj2cC0KUlqIOQT744ANcddVVGDVqFCRJwquvvhr2+uvWrYMkSYPeGhsT3zM7a6mVIB69GXc9vx1HWuyoLrRgwdgieGVoQ67DEsN7249E3aZFnKCpLrSgND/0wYIYjr75aHvKDN5qsUVaCaLsoDV3O7DhcCuW/fZDvLilAZIEGHQSjrTYEzaYUFirnuBdOLZoyPJ8wLdT+fqOk1opsH5gr1dLEQAgx9ONOy6aDKvFgJ9/YQ5MhsFPFWLWy4bDgys03t6rbNvSWVXaarXDQYabixCkyjvgZLXfqvgL1OHktQ2dIfuSfqYePM2rKRr0tetPr8GMait6HG48tzn8KvMXP22ALAOLJpZiUnl+2OtGalypbzD6cIOxzXXtuP2v23DL059mfQlubUMnNhxug0En4YGrZuJ3NyzA018+E698bTG+tEiZMRFwohvKyV5xoKYMRldfh2Jsh1UEJTwQq/J3qxVw/qvpAfhCkIHtsICkDkefXOGbuWOLsret1pIjDu2wAOV5bHpVARxuL17ednzoG0TL7QD6lIP6JrlYq1bUVKvzPE7tiO5+PS7Apm5v8TjfCYOexO3jiKHoZ08shcWogywrs4xidbC5G06PF1aLATUlvoo/VoJQwqkhh03OQ01JjvacZNepIUh/Z3K2i2iAcKvU/UmSpC2UCtUSS7zeWsNUVARrhyUWH5QXmLVKEX9mgx6zRyuLzxLREktrh5WASpBdJ9KnJdEf1h3Cf6/+ZMhZhemmob0PrT1OFOid0LvVY7a8ELMR1RCkSK88xgNCEFvgvjfqhw5BPF5Z665QVRikEiQnTpUg3Q6USL6FP+P0yjEsQ7hA+xt9v6MTWVgJ0mEPHfhKksS5IERpLuoQxG63Y968efj9738f1e3279+PU6dOaW8VFfFpNUNBuJWdiNf3dOKDAy3IMerxxIrT8fWLlBNwL3zaMKjH7CDF4wBJD7jsUQ95FauhZ40qDHu9mdVW5JsN6O53ayd1kqnP6UG3+nuJtB3WnpM2fPGJT3Cisw9jinPw/K1n43NzlAqCf2w7Ee4uhm3tLuXvsmz20FUggO/Ard/l9ZUC5wavBEFfB25bMgk7HliKsycOuI5KzAX5+HBbwAn5U1192HG8C5IEXDyjUgsTgs0FEaFGqXvAY6zL97urLszBjGorZBlYf2Dw6mqvV8aOBuUxNz9ICKLTSfjf85VV3ms2HIXDHbx01eXx4oVPlfDlprPHBb1OLGrUSpAeh3vYw+XeV6thjnf0aSfcs9Uf1ymt+q6ePxo3nzMB/zFvFJZMLceCscXa32/d/paA6p82dWWPQQxZFKv1ox6Mrjz2873K36Crz4Uehxs71ZVkAUPRPS6go075eGA7LMBvLkgMFQjDZLUYtVWt0bbEEpVN4+LQDgtQB6SfLQakH4t/yKe+jjlkI7qQp4U4mqo5yvvGKP8OXQ3KTAODRQnTxND1BA5HF0PRZ1ZbMaZY+f0PZy7Ibr95IJIkaZczBKGEUytBupGLaZVWre2mGJLOdliUKpq1SpDIFx01dgV/7hSVINYo22GJ162BQ9H9JWouiNcr+w1Gj18lyMTyfOSZ9OhzeYIulkpFf/6wDh8ebMW7+xJX8ZkMYh7I2ZVqGGWwaGHHIOrlBZLyfxEwsFwcw5nVfeETW5V94TDa7A54vDJ0UvDV9+IxJ4K4WDV3B7bDKnUri/B2shIkgP8czuMd2dfOWRwvloR4rtNCkAwLQomyRdQhyOWXX46f/vSn+PznPx/V7SoqKlBVVaW96XTsxDVcL289jtdqT2g75hq1HdY7BzsBAL+5bh5mjy7EkqnlmFiWh+5+N17eOsRKW70RKFLak0Q7HH33EPNABINep+2sb64b2ZZYT3xwBHc+tw1/+uAwthxtR7/Lo53osRh1WiuoUMQqL7dawXLDmTV46+7zcfbEUnx+wWgASluXSIdxR6uz14mNR5Q2VEsjaIUFBJYXF6sr2EVbH406EySSFhQLxxbDZNChpdsREHC8o1WoFKO8wOwLQYKcZBWhgNWhDkUXK/K7Ah+fF6rVIO/tGzxr5UhrD7odbliMOkytDF69ccWcUaiyWtDS7cA/PzsV9Drv7GlCS7cDZflmXDozysqAMCxGvfa7PzbM9gQfHvT9/MFaPWWLQ809WLtHOcl825KJg74+pbIAM6utcHtlvLnL9/du7VZDt3wTdPACdvX3mR/Z/5BG/b8x9HcoYQqUg4Rd6lyFWaP9nvva6wCvGzDmAdZRg+/Lfzh6EmhzQaJoidXn9KBRfd0J1pc8Vsvnj0KuSY/DLXZ8Eu/XBDWUaJKLAEg40jowBFErQaINQUQrrKJxgCSNUDssNQQZZUVNsXLSuGEYB6mianH2gAomUfEo2kQSxZ0actjkXEyryseoQuXx3OFVQxC2w6IU4PVbpT5UOywgcAbfQLIsa6uHQw1GB4A80+AQpE5rQxl68UGiQhBbv0trDFAYx0oQvU7SXns+S4PV+H1Oj3bsEqwdcDoTIchZ5epjLq9c2a8JRgtBlH2PoJUg488FLIWAq3fIfaumLl8nhoB2sqpidSZIp314K+9buvtRAt8JfoujFWY4sfdU97Daimaa/X4hSLa1w+pzetDvUh4LJfnBQ5B8s/J47GY7LKK0NGJJxPz581FdXY1LL70UH3/8cdjrOhwO2Gy2gDca7NF3D+IbL9TizJ+/i0t/sx4/em0X3trViC7199UPE7516VRcrlYm6HQS/uec8QCApz6ug3eoFlQxDkcXA1YHnlAJRrTE+mQEh6Ov29+Mn725F6/vOIWfv7kP//nHjZjzwFrc/NRmAMoOmBRqp09VUWDBtMoCVBda8NT/nIGHvjBXW7V13pQylOaZ0GZ34qNDoYd5D8c7e5vh8cqYXlWAcRG2o/EvL56Qqx6YDQxB1HZYkbSgsBj1OF092Pr4kO/v92/15LwIEiaWK9s38KSjLMvagUSuXQ09xi1W3g8IQcRckA8OtAwql69t8A30DbbjDAAmgw5fWjweAPDnD48EXWUuBjJff8aYoO2/hmOsaIk1jLkgbT0O7Drhey58Z2/2hiCPrz8MWVYeY1Mqg69SW75ACRxe235Su6ylR3nclxeYlZ7FsheQdMDAtnBDEWFhbztGqyuXNx1uQ3e/Gya9DlP9t0kbij45+MGkqEBoOww4R361lWg/E81QyGPtyv9yYY4xritCCyxGXD1fCZGfi/eAdHUeSBOUv11De2/gc4n4O7Qe0FpKRqTjqPK+eLzyXgtBElMJ4vJ4tRku/pUgEc36CkEL7wYsXGAlCCWcCEGQh2lVvkqQFrfalo3tsCgFtNmd8HhlSJJvVlI4YuFLsHZYdqcH4vCrIEwIkm8R7bB81cuRzOJaOFZ5jdvf1B3XVi1ipX+eSR/3fWTRyjYdWhKd6vLtH2w6klkhyPb6TgDA3GL1cROqFRaghSB5svL7aPVfLCFCkMIxQM1ZyscNn4T93k1DVFoV5cWnEqTJ5kCJFHheaVqODU6Pl/MWVQ63RwtcAaV6JlQXhUzUrj7GTHod8kz6oNcRlSCcCUKUnhIeglRXV+OPf/wjXn75Zbz88suoqanBBRdcgG3btoW8zUMPPYTCwkLtraamJtGbmXZcHi+WzqrErFFWSBJwsLkHT288htue3YqTrcpKjnkTqnDXRZMDbveFhWNgtRhwtK0X7w1VxqsNR488BOl3eXBQXfE/VCUI4BuOvrmufehQJg7sDjd+8IoygPiCaeW4bGYlyvLNcHlk7SS9OKkZjl4n4Y2vn4uP770IF04LbKVj0Otw1TzlBOwrCWqJ9VaUrbAAX/UKAEwvVHciQ7bD6ozoPs+ZHDgXxNbv0g4KLlNDEFEJcqi5JyB86HV64FBX3Rh7RAhyjvJ+QAgyv6YIhTlGdPW5sL0hcNs+Uz8P1grL3xfPHItckx77GrsDQhtAWV330aFWSBLwX2eMHeKnjl48hqOLQK2mJAc6Sam4Gs4cgFQWrhXSyc4+vKrO+rj9gkkhr3fVvFGQJGXmkCjlFpUgZflmX7ui3DJAF3wnNyQRHva1Y7S6En/tbiWUml5dAKN/GNcm5oEEaYUFKK248soByEDz3ui2Iw6maMPRIz/4O9qq/D7Hx6kVlr8b1QHp/9p1KvCgepg6mpSKjWa5BCa9Di6PHNjnuKBaeSzIHqB5TxR3fFR5X6y20CtQQ5DuxISUh1t64PR4UWA2YExxjjbDI9Z2WG6PV6ssGTjLRoQgzQxBKEFkNeSwybnKwpIi5QRYmxaCsEUJJZ84QVuWH3yV+kC+dliDQxARTBh0EizG0PcVrB1WnboPGa4dVoXVgpqSHMiyMjstXrR5IHFc+CCI1550GE59stP3N61rtQf9G6ejPqdH2xeYkqfuT4RrFWtWjvFLDQ5IkrIPooV+NnXxkXWULwSp3xj2+zcOEYJolSDDnAnSarNr8/zEgqbFZcr/VTpUIo2EIy12eLwyCiwG5BiV46NTnZnxOI9Ee4/yXFeSZwq5KFZ0DOFMEKL0lPAQZNq0afjqV7+K0047DYsXL8aTTz6JxYsX45FHHgl5m5UrV6Krq0t7a2hoCHndbGXU6/CDK2bija+fh233XYo/3rQQKxaNw+SKfJigPCHfeuGsQU/eeWYDbjhTOcn05Md14b+J/3D0CB1o6obHK6M414jqIIPNBpozuhAWow4dvS4tPEmkX6/dr83v+MONC/GnFafj0x9cjA+/eyEe/a/5uOPCSbjvipkR3ZdBr4NOF/zFUbTE+veexqHnr0TJ7nBrbZGiCUHK8swwqQdvNWZ1B3dQCCLaYUVWRr9oknL7TUeU4fbr9rfA5ZExqTwPE9XwY0JZHiRJKZX2n4mhtcIyuKGzq4GcqASxnQC8vlUnBr0OS6YqK5LeHxDehRuK7q8w14jrTlcC1Sc+DHxMP/eJcoL0gqnl2gyPeBJzE8QK+lh8dFAJQS6fXa21O3g3A6tBfvjqLpz/6/dD9uf984d1cHlknD2xRFvxGEx1YQ7OmqCEFaIFmmjrowxFF/NAYmh9Jv5vetsxWn2eE9Vsg2YhtQ4RggB+LbF2Rb8twyTaYUXz/KsNRY9jKyxh9uhCzBtTCJdHxt+HatsYhRMN6uudtVprJeK/0g2SFNtckE61HZZWCaI+J/ck5n9TDHSfUW2FJEmoEZUgMbbDOtxiR7/LizyTftCQe7HimZUglCg9XcrzZo+UhwllebBajCgwG9AF9bHIdliUAnyr1IeuAgHCt8Oy9anzQHKMYavO88zKyUdxDCHLMurUis2hXntPGxv/llid2jyQ+LXCEuaNKQKgtHpM9RXnJ7sCFxxkSjXIjuOdcHtlVBSYUeRVHzcRVIKYPHbMrFYCEe130eVXCTL2bOXj+k+AMAuchvofK47TTJA+Wwf0krod1fMAAPMLlEVAnAuiEBUx06sKtIVe2TQcXVSCBBuKLmiVIJwJQpSWkjKY48wzz8ShQ6HnTJjNZlit1oA3Cq04z4Rls6vx4NWz8c63lmBCofJnNecEr2hYsXg89DoJGw63hR9IXqr22o+iEmRXiAGroZgM/nNBErsjua2+A09vPAoA+Pnn5yBX7bcrSRJqSnJx9fzRuGfp9IjaeA1l7phCTCzPQ7/Lq1VtxMv6Ay1wuL0YX6qsnIyUTifhvitn4KtLJqJI9EMdGIJE0Q4LAOaOLkS+2YCuPhf2nLRpcyou85tTkmPSa9U1/kMPRQgyK0f9XqYCoHw6oDMoq7EHDBYWLbH8K5j6Xb6VS+IgKpwvnzMBkqT8DsXQt36XB39TT7beeFb8BqL7G6ueXIy1HZYsy/hQDUHOm1KGS2YoJ+7/nWFzQdweL17a0oCG9j588YlN2HI0cC5Eh92J5zcrbZJuv2BysLsIsFxtrfSaWjnSGhCCqL+7aIeiA0COWgnicWC8+vIkCtkGrqb3tcOaEvr+Kmcr75MQgoh2WMc7+tDrjGxn/pgagkTaii9a4v/wxU8b4jYgvbtZWUxRXDlWO9l/dNBckBhCkEHtsNTHU4JCEP95IAD82mHFdoC664RohVU4KNQXlSC9Tk/AamSieOnuVPb7DLnFWoud6iILumT1uYXtsCgFNNnUeSAFQy/uAsK3wxIrhwvCDEUHlEVrgK8SpKPXBZvaemVgYD2QOK7aprY3CkaWZXiiqMDvFCcGE1AJUlOSg+JcI1weGftOpXZLooEV2JkyF0Q8VhaOLYakzcsLs0hIDEx3dOPsib4FcQAAm7qAxToKGLUQ0BmVFqFi0UgQ4n+lKlQ7LDV86xhGJYjHK8PbqxxLec1WoEQ5zzHFrIQ+rARRiHkgUysLtOP3bBqO3i6GoucN3a7QlkHtsP6w7hD+e/Un6HOmdhBNFA9JCUFqa2tRXV2djG+dFXQedafbEDwEGV2Uo1UQPBWuGkS0w2o/AngjGxYm5oHMjKAVliBaYm1K4HB0p9uL7728A7IMfGHhaJw/NczqljiQJAmfV0/Avro9vi2xRKiydHZVREGTvxWLxmPl5TMg9ao77cNsh2XQ67TV9usPNGOdGlAMHCwuqkKO+M0dECHIVIv6dy8ep7QlEsOjbYG/t/OnlkOSgH2N3VpP3j2nbHB5ZJTlmzCmeOg2ZmNLc7F0pvLYX/2h8tj/165T6Ox1YVShBRdOj+GEeAS0dlgx9u0/1NyDRls/zAYdzhhfgkvU3++mI20ZVYp7uMWutUjrdrjx36s342O/uTpPbzyKPpcHs0ZZcf6Uoed4XD67Gia9Dvsau7Gv0YbWHtEOy+Q7SV0Q5VB0ADDlAXrlRMC4nMCTHLP9h6LLsi8EKY0kBBn54egleSaUqqudDjdHVqmUyHZYAHDF3GpYjDrUtdqx++TwZ4I53B5I6oyOseMmasPc6+IxHN1/MDrgezz1NAdUs8XLnlOiEkQ5ASHaYbX2ONDviv777QozwyvPbND6IbMahBKhv1t5/c8v9O2LjCrKgQ3qcwvbYVEK0FapR1DhDgS2wxoY5ItBukOFIFo7LHVxgni9qi60ICdEn3phoRqCbD/WEbLV8I//uQfzH/w3XtkeWcWlaENUmIBKEEmSMEddyJTqc0FEW6AFY4sAABtjrASx9bvQYR9eVUM8bVeHoi8cV+S3SCi6EOSTujZlv1drhzUaMOVqFReoDz0XpFENGitCtsNS9lO7+pwxL45p63GgWFb2oaS8MqBQ6Q5QDeXY9WBzD08AAzigVoJM868EyaLh6O125bmuJC905Z+Y55RJM0Ge+OAIPjzYGnDcTZSpog5Benp6UFtbi9raWgBAXV0damtrUV+vrM5duXIlVqxYoV3/t7/9LV577TUcOnQIu3btwt1334333nsPd9xxR3x+AhrMpZ6UM4beWf/yORMAAK/Wngzdd72wRlm94XH4VnUMYZd6wmr2wJYwYYiT6JsTGII8tu4wDjT1oDTPhB9G2O5quJarLbE+Ptwat56xDrdHq4RYNiuGk7dCr/q7HmYlCOBrifXnj+rQ7XCjvMCM+QOqMiapw9EP+4UgberO/wSDegBRpM7isI5R3ncFtsEryTNhgdry6v19yiolMQ9k3piiiAOhW89XHvuvbD+Blm4H/rpJee664cyx0IdobzZcoh1WS7cj4tX2/j5Qq0DOnFACi1GPSeX5mFiWB5dHxgcHMmdnRYSo88YU4rwpZehzefA/az7Fe/uaYHe4sWbDUQDKLJBI/t6FuUZcME0JPF/dfhKt6onc8gL/dlgxBF+SpP3vjLH4DgwMOilwKLq9VT2JJwGloeeXoMqvEiROlQ/R8A1Hj2wFZiLbYQHKyXdR+fXPHSeHuPbQthztQJmsPOeNrpngC0EGVmZVixBkV2QBRr8N6PMLcQEgrwKApFSz9cZ3hagsy9irrpKdobafKMwxar2JY1mpJypBAsI7P9pw9DjOZyES3L2dAICiUl+oXV2Y46sEYTssSgHN3WoIEmEliJjB53B70dUXuFDFpi5csYYZig4AeabAwejaUPQIKjCnVRYg16RHt8MdtNXlwaZurNlwFN39bnzzxc/wu3cPDnliWazAL05ACAIo+31A6s8FEe2wrp43CnqdhPr23qhbBXm9Mq7740Zc/Jv1KbGQSZblgEqQiPaP/UKQM8eXQJKUWRItTccBjxOApMxaA3wtsRo2hby75ggrQVweGfYYg4rmbgdKJGUfSsot1Y47c3pPorzADI9Xxp5Tqf34GwlBK0GyqB2WCCdLwjzX5WfYTBBbv0t7jo/H4jOiVBd1CLJlyxYsWLAACxYsAAB861vfwoIFC3D//fcDAE6dOqUFIgDgdDrx7W9/G3PmzMGSJUvw2Wef4Z133sHFF18cpx+BAsgy4FZfqEJUggDAwrFFmFdTBKfbq50EHkRvAEqUE8aRtMRye7zYp65SjWQoujBH3fFt6XagLQEnWg42dWPV+0pf/h/9x6ywPR7jqaYkF2eML4YsA//3WXyqQTYcakOPw41Kqzmi9k9BeVyAQ93JE219BP+ZIBGejBXD0cUqsUtmVA5qqyKGo/u3wxI7GTWSehJfhCCFIgQZHLyJIfQiCBJDH4eaB+Jv4dhizK8pgtPjxQ9f3YUtxzqg10m4/oyaiO8jWkW5JljVVX/1MVSDfKTOgDnPr/pBVNu8k0FzQUQ7vQVji/HnL52OS2dWwun24n+f2YpvvliLzl4XxpXm4vLZkVcSijDyn5+dHDATRG23FstMEED736k0+P6eUysLYDH6rdAUVSBFYwFjmEqlsqlKG7j+LuDRecD/Ow34/VnAHxYDj58PfPrn2LYxQr7h6EPPBel3eXBKDXUjORkTqyvnKhVhb+w4NeyWWOsPtKBSUlY5StbRWnhT1zrg5y2drLxuuuxA+xAzswBfa4fcUt8JAb0ByFP/T+PcEqvJ5kC73Qm9X9gmSZK2Ui/allger6zNGAnVBlIbjm5jCELxp1P3RcrLfM/Do4ssvpkgbIdFKUBrhxXhTBCLUa+FBQPngthCVYL0tvtmKWBwO6xoFh8Y9DrMV/eLg80F+cM65ZhO/Dy/efsA7n15B1ye0FX/XWIwek5ijqHmapUgqX0SWrTDmlJZoLU/jbYl1v6mbuxr7Ea73RlwXJQsxzv60NrjgEEnKfsCkbSLVQejw9GNwlwjZlQpn+/Zv893W4P6WNGGo4erBAk/GD3HqNdaJsZaQdPc3Y9iSd3vyy3VKkGkzuOYOzo9QrhE63G4cVyt+phWWaB1WcimShCxSDNcJYg1w2aCNPidmxALEokyWdQhyAUXXABZlge9rVmzBgCwZs0arFu3Trv+d7/7XRw6dAh9fX1oa2vD+++/jwsvvDBe208Ded2ArO7EhqkEkSQJXz5nPADgL5uOhX4S11piDR2CiFY2wQashpNrMmgtPQ5EcBIuGl6vrO7Yy7h4egWumhtDGzZXH3Bye0wrtMUJ2H9si08IorXCmlUVcij7kLSh55Kv/ZUgPvc4lZ87AtMqC1DiFyxdNnPwSWVfCDK4EqRKVne2RTuZcCGIujr840OtcLg9WiXI/ChCEEmScOt5Sh/Yt3Y3atscqgQ7XsT8hGNRzgVxuD1an93zpvjauImWWO/taw574JpOdvu15jEb9PjDjQvxH/NGwe2VtfknXz1/UlQVOxdNr0CB2YATnX04pK6IDByMHmMLtFwlBCnw2mAx6tTtHhD+avNAwgxFBwCDGRh3jvJx5zGg7RDQsg9o3g2c+gx458cJaa0kRDMcXYR4BRZDwlaEAkrgmWvS43hHnxZ2xuqTfUdRIKnPZwWVmKieRDrR0Qen2+9/R6cHKtVKwcYdQ9/xwHkgggjWuuMbgoh5IBPL8gLCtpqS2Iajbz3WAbvTA6vFoP1OBtIqQbrjU81IJLg8XpjdynPOqCpfZWt1YQ5s2kwQHoxnm8MtPdq+XaoQ1dyhTtAGU+nXEsufbybIgNfPJ5cCq87QHvP5A0IQ0Q5rQllkbSjFXJCBIUh9Wy/+7zOlwvLPK87AT5bPhk4CXtpyHP/z1KdapcpAYpVwIgajA75KkIPN3TFVTI8EWZZxUm2HNaooR6uEj3Y4un+7mcau5J9c3qa2wpo1yqrsW2j7x5G0w1L2S0RLrPo6ZdGh1toY8FWCNO8JWt3X7/JoC+lCVYJIkqTtc3bGOBek2eZAif9MzCJ18ZvtBOaNVo5Tsz0EOahWgVQUmFGcZ9IqQbJpMLpWCRLBTJDuDGmHFRiCsBKEMl9SZoJQAvmfuDaE31n/3JxqjC7KQWuPA9/9+2fBV9uKFi5tR4b81v7zQKI9QT9VOwkX34F4L25pwLb6TuSbDfjp52dHPUMDALD2+8CfLgD2/yvqm145Z5Q2kyDsEPoIuD1evK2u+h9eKyx1Zz2nWDnp58+UD0jqZRGuwNTpJCxSd37zTHrtoMCfaIfV0N4Lh1s5mSsGj5W51RX5EVSCzBplRUWBGX0uD9bubsJRNVCYOya6YfZLZ1VqO3ZA4gai+xurtsSKdjj61mMd6HN5UJZvxvQqX6ulhWOLUZxrRFefC1uODl7pl268fqvSRSWZUa/DI9fPx/WnKwcqFQVmfGHh6Kju12LUY+nswP+XgJkg+TH+L6khiNTXoT2WBq2mb1UPBsMNRRdu/Btw6/vALW8D//MW8KXXgf9+RVlt57BFdlI+Rlo7rAhCEN+JmLzYnk8jlGPS45IZygH46ztOxXw/Jzv7YGtRQmjZlA+YC1BeYEaeSQ+vHKQyK5rh6EOFIKLaKE72DBiKLtSow9GPR7lSb60aAl88oxIGffDdwfJ8tsOixDjaakcBlOeT8nJfGD2qKMdXCcJ2WFmlx+HGNY9twH/+ccOgAdTJJNphVURYCQIAVYXBh6Pb+pSTZgHtsNwOZdGEyw50KtX5eWZlX1ycZKuLoh0W4JsLIk5wC4+tPwyPV8b5U8sxZ0wh/vvscfjzl05HrkmPjw614ro/bgz6u+/sEyFIYipBKqwWVFkt8Mq+quBU09XnQp86e6u60KKd+I+2EsQ/BBGhSjJtV1thLRhbDDh6AKe6LxhhOyzIMs6eqOwTt59Sq2itfvvq+RVA8QQAMnD800F3JSpNLUYdrDmhZ+WIuSAdvbFVgjTZHCiR1MdWbqmy/68zArIHp5co25DqM2kS7UCTbx4IAIxR9y9PdfXDnaYL7mRZxk9e34PVH0VQ4Q3fzNJwnUMKzMrzd3eGVIL4L9A80dmHzhj/x4jSBUOQTOP225kaIgQx6nX43Q0LYNRLeHNnI/70QZCgo0RZMY+2Q0N+a7HTOiuKeSDCVPXFdn9jfEOQl7cqJ9LvumgyqguHHpwdlNhhO7kt6psW5hpx4XQxk2B41SCfHu1Au92JolwjzpxQMvQNQgk1FB1QZh1EORwd8LVmWjq7KrAdkKq8wIwCswFe2fdCKwaPFToGhiDqypwBM0GUzZO0lli/e1c5wTyhLC/qgzKDXocvn6u0ehtfmovFQYKbePMNR4+u9P0jdR7IeVPKAk4663USLpqeOS2xGjp60e1ww2TQaSflAeXnfOgLc7Dqiwvwl1vOCvr4Gsry+b6DMb1OUg6kIlnpFo5oJdfXjqvnj8aoQgsunjHgvtqiCEEMZmD0QqDmTGDcImDCecCki4Bxi5WvH/0otu2MwBT1932szT7kcO1jakuOcQlshSVcqVbuvbHjVMjhrkMJaIWl9qeWJMmvJVao4eiRVIIMGIouaMPR4/t/6RuKPiAEKRHtsCIPWGVZ1kKQpWFCdVEhx8HoFG/7G7tQAOUxq/OrSh1VZPHNBHHZlRaelBVe3nocnb0uuDwyPkqR4awujxetPWrlchSVIL7h6Mpzp8cr4y8bj+K5T5TXjYCKCrvfz6rO7PMfjC7LsjYTZGJ5hCFIjRKC1LXatVbDjV392nHRnRdO1q570fRKvPTVRagoMGNfYzdueGLToH0BcVIskRWgc7W5IJ0J+x7DIVbDl+aZYDHqcfq4Yhh0Ek509kX8+uvyePGJ3wzMUylUCbJwXDFgV/eNjbnKwrhQRAgiewB3P86coMwFMdnVRStiQZugVoOsfetVzPvxv7H4oXdx6W/WY/nvP8ZdL2wHoFRPhVtcI/5nYg1Bmrv7tZkgyC0FdDptO2flKQs5j7TaM2bOQyz2NfrmgQDK4jOjXoLHK6MpTfcDd5+0YfVHdfjZG3siarveqi7SLAkTgvgqQTLjsTJwQdgeVoNQhmMIkmlEJYjBopzQHsJp44px/5VK+49fvrUPGwYedJRG3g5LVIJEMw9EmBpFT/pIddid2o7dlfNGDXHtEGTZVwUjVv1G6fNqS6zXak/CE+OJPMC3avfSMKt2IxIuBAEC54JE6Or5o/DcrWfhwatnB/26JEmYqJ5oPayuNm+3O5CDflic6sGAFoKoJ6y7godGIlQSq9ajaYXlb8Wicbjvihn4w42nxd5aLApiOHq07bA+9AtBBrp0phIIvbO3adhzE5JNhKjTqwpgHPD41ukkXDl3lLYyKVqLJpVqbX1K80zQufu0Ev7htsNCbzu+fvEUbFh5cUB1EYDI22GFM/5c5X0CQ5DyAjOsFiWkHBQKDCCqr8aXRtaSYziWTCtHgdmARls/ttbHVu20fn8LKqDetsB3sl+EIEdDhiDDqQRRH1MJaoc1c0AIIlbqRdMOa/dJG4539MFi1GHJ1PKQ19MqQdL04JdSV92JJugl9XXL4ls8U1VoQTf8nl/YEitAr9Odtityw/F6ZTy94aj2+aYoV9cninjuM+olbSV6JLR2WLZ+bD3Wjqv+30f44Wu7Yet3Y0a1VTs2AADYW3wfq/vo/jNBWnocsDs90Em+9odDKcw1agscxEr/P31wBE6PF2dOKBm0mGr26EK8csc5qC604FhbL/64PvC4rzPB7bAA33y/z1K0JdEptWqjukj52+aZDdo2R1oNUtvQiV6/wd6nupJbCdLv8mgnPBfUFAE96mMxvyL8eQRjHgD1645uFOWaMKPKiipJPaazDjjuVueCWJu3oavPhZNd/TjY3IPahk6t/d3k8jChC3yVIDG3w+p2oNi/HRagtcQqdDRidFEO5BSuRBoJWiWIGoLodJK2iDRd54KIVtxeGXh/f0vY6zZ29eNIix2ShIAFeQMVZFg7LBGCiHbTbIlFmY4hSKYRlSBDVIH4u+nscfjCwtHwysCdz28PLIMuVVcKdRwFPKGf6ANb2URfCSJ60h9o7o7bydwPDrbAKysv5INOTkaqp0lZiQjEHIJcOL0CVotyIs//AC8axzt68Y9tyuqtcKt2IzJUCGIpUt5HMZBUkiQsnlSmrVwLRrTEEjsj7XYnxoih6JZCXwWKWD3U1w44B5+QPWdyGYx63475vChbYQlGvQ5fOW/ioNYyiTK2RPn59zV2R7xirK3HgV1quHju5MEhyHlTymEy6HCsrTeieQ6pzBeixvb3DEf//7N3leFtXGn3zIjMjDHGHHLsxGGGJmnatGnKzMy8bbfb9tvylre8ZWZKIQ03zAwO2DHGzJYtnu/HnTsz4pEsO7ar8zx+JEsz0kgauPc97zmHZbCID9omeSB8cVoZKHazeQqqBOlyMvE16kSlgC9IkPJNvZYLwjAMsvkJjztLrDIPLTl6Ao1SgdNG8JZYvIe5JzCaLdh4vFFQgiBUzISiGRiltiRI/HAADNlH3JEYNBg90kYJQi3WfGiH1WUwCQSVMyWIJ3ZYy3lSfUZOLALVztVVQiaI3w7LDx+jupbsgyZWbZVhp1EqEBUSiHaOH7f5LbEEHKvrQMETK/D40oOnelN8jvXHG63Ox5tKmvpFcwcNbI4LDfCoYYbaYf269yTOfWszDtW0IyxAif87ewSW3jbFmszokjSgdZMiMiVBjGZOaBAbEhEIjVK+GlbIBaloQVOnHl9sI9csqQpEiqSIQDxyxjAAwFtrS6zGqrT7vrfssAAIQeP9VQlykldtDJE4C1A7YLm5INQKK5i/7p5qEmRfVRtMFg6xoRoSgi1YxbpRSbOstSUWSC7IEIb/HqR2WACQOgkAUMAex9n5cfj51in44roJePfysXj5wtF4dskoPL1klMu3jOihHVZ9h40dFgCE8w14rRUeKZE4jpC228ua3S47kHCklpxrciRNZ2IuiGdNfP0F0nnNykOux/UrDpFxSWFKBOJCndfSqJ1h5yAhQei5njpj+MPR/Rjs8JMggw1ekCAMw+Dpc0ZheGIYmrUG3Pz5LiG3AaFDyGtZTEBbhdPXEKxsFCyy4113cjhCVlwIWIZ0d/iq43R1MZH00jBtr9Ak6YRqluclaQuNUoEbZxBFzf/9egif81J4uTCaLbjjy91o15kwOiUCM3Odd+3KgkCCOLHU8sIOSw5oOHppA5nkEhKE78igKhCAECIavsjnQA0SGqDCuHRx20d7qQTpawxPDEN4oAoNHXrMeekvPLes2K2MdmNJEziOqCMcBbcHa5SYwg9YVrgZ2PV3HLDJA/E1rpiUhqSIQJyRnyhaYYXGy1LMOQSdQHU7mQA1lwDgAE04ENyDYzYhv2e5IGYTsOl1t8oG2jHqjkyjSqZ0meGsPQUlr34/UOuxkm5XeQs69Cakq/nBfJhIglASx04Jog4Wyf86F9+ZxSKSXLZKkFCaCVLv0fa6wpHaDnAcIfEoMUFBlSCtXUbZ0vxlMqywAJEEoZ7d/RWdehPu+XoPVg0Ca8C/C+oayPFhUduf85MiAtBOc0E8aMgY7Fh3rBEGswW/7avpFwSBL/HRRjLGvnh8KtQKFrXtOkF56AtwHIed5S1o87CLvJ6SIB7kgQCiHRb1jL+wKAVr7puJKyal26u5reywCGkvbSo6UE2uYUNjPGs+GCMJR/9g4wnojBbkJ4c7VBZTnDEqEZMyoqE3WfDUb4cBkExC2vEcEdj7dljlTV390pNeGopOQXMQN5fKI+0oCXIGb/dZe4pJkN3UCis1glhRCSSIjLmzTTj6hIwoJIAqQaxJkDpNKlq5YAQyBtwxvBujUyIwOSsG80Yk4JzCZFw0PlVQTzlDz4PRdWIwejB/DNBw9LYK5CdHACBqHXfYeLwJj/1yEPd9u9erbemPaOrUo5FveMmR1HKSIgeHEgQgDbKubH//PEj2/3luxsb0/NxtNMM4wJWZJrNFaKJawGdo+pUgfgx2+EmQwQYDP2FQeaZ8CFAp8M7lYxEeqMLeylY8/ssh8gTLSnJBnFti0ZNlrgMrG7nvTz3mj/rAEsts4fDXUVJgnzOsBySI1Aasq1HodvEUt8zMxPXTSAbFIz8ewNfbnRNKtnhpxVHsqmhFaIASr19c2DMrLEDwG3ZOgnhuhyUHUiWI0WxBu84kIUFsOqmFcHT7XBAAmM0TWyoF02dKjp4iPEiFr26YiEkZ0TCYLHhrbQlm/mctPt9a7tTaYsMx8v24mrDOHT7wc0E4jsNBfpJvFy7uI6THBGPjP2bj1llZ8jvdXEFih+UQDcXkNjbXe6IFAFiF0EHnlSXWro+B5Y8Av97jcjExHN35OU5nNAudkH2RCQIQ5RclD7ee8MwehV4Dhofw10WJEsRpJggAJPKWWDUuSKfOOsCsBxgFEGbjfU33qw7fKUGchaIDZDJGiwOVze4nqScatTha1wkly2BOnutjgJIgTVpDj+wcexsrD9Xhh93VeGnF0VO9KX7IQJfBhK42cjyzQRF2zyeGB6Kd85MgtqDFnJYuo8fWmn2BP/bX4JnfD3tcFDrRqMWaIw1gGODG6RkoTI0A4HngtCv8tKca5761CbNeXIuf91TLJpHqeAI43kVXsCOMTolAbKgGBSkR+PGWyXjuvHxEhzghUqR2WHxjhYJlEMhnoO3nx0eeKjCpEmRvZSs+2URI+1tnZbnMXWAYBo+fNQIKlsGyg7XYcKwR7ZJu5/BeJEEigtSCdSz9zP0J1ClhSIS4L4xJjYRKwaCmTef2mNTqTYI12XljSfG9tl13Sq+tQh5IKj/3o80bwZ6QIGTcOCE9QrDDalRaz1s+31qJnRaiis7sPuDVtkYIJIjnBJnFwqGhQ49Ihq8xCEoQngRprRSOlx3lLW7PD9v48Wh5Uxe6Db2j0u5r0PpLalQQgtQiCUuVIJ6ojfsTpEqQLoMZm52ottq6jIKiy12DEM0EAchxPZBR06aDycJBrWCF+kpJQ+eg2a/98MMR/CTIYAMtGtvKUGUgJSoIr11cCIYBvtxWIXRlySFBDggFTO8L0rQTmfpR9gS7K1rQ2mVEeKCKeJx6C9tAeC8tsRiGwcMLh+HqKekAgH/8sB/f8eGErrDuaAPeWku+9+fOzZftBewSvWCHJQdUCVLSoEWLlgxgU92SII6/o4WjEhERpMK8EQkeWQOcagxLDMMX10/Ae1cUISMmGE1aAx758QAWvrYeKw5Z53pwHCfJA3GuJKBFzD2Vrajv8L6jrF1nxJoj9aeku7SuXY8mrQEKlkGel7kfHsGTTjdnCHRHghwht7G53r8HhZALstHzdfd8QW5r97m0NKQkiKtcpsrmLnAcKbpHuwgM9CXUShYL+MnIr/tqPFp3Le/9m6LiiymSTBBqh1XbrrMf6Cfwlgyu1DP0WhCeDChsbAApCdJZR3KlfIDDQii64+ODXhuqZOSC0HypSZnRCHfj7x4drAbDkMYCby0o+gKUzDpe39mvyRo/CI7VdQqh6EpJKDrFkIhAMRzdb4cloERSzNld6dtGFV/giaWH8M66Uvy6zzP7QmoVOys3DukxwUJ3/aYS34Wj/7CLKIubtQbc+dUeXPPRdiHo2hXqeCUItbeSi6hgNbY+NAc/3ToFhbTA7AwOgtEB0RKLNpqle6gEyYgJRkSQCnqTBR16E3LiQ3DaMPfNH7kJobh8IhmXP770oKDQDw1Q9rwRyw1oN/6+fpgLQkPMEyV2WIFqBQr5EHpnxVWKbSeaYbJwSIkKxNi0SChYEjjdeIrsJjmOwy6elBH2UU+ahGxIkAiuHRrGBAvHYGuDOEbUm8z4YluFQIKgcotX2yvaYXmuBGnpMoC1GBDK8Mc8bWSiTgRtlchPDodKwaChQ++24C/NqSttHNh2xBS0/kJD0SmSqRJExvmyv8FktgjjQ5p/58wSa1VxHUwWDjnxIW5VdyoFiwAVORcO9FwQaoWVHBWIhLAAxIRoYOGAw7V+NYgfgxd+EmSwgRZmotK9Wn1GTizuPY0MUh5fegiP/XwA5ij34eh0gD68B37+NPTYFyQItcKakRPbswG7LfHjJQkCECLkX2cOxxWT0sBxwP3f7cWPu50TIfXtOtzzzR4AwKUTUrFwVKLTZT2CoARxFoweQW59XHhIjQ4CyxDbksO15DcequQnDFI7LEAkQdodh6MPiQjE9kfm4r8XFfp0G/sCDMNg7vB4/Hn3dDy+aDgiglQ4WteJ6z/ZgbPf2Ig1xYSIKGnoRE2bDmolaxdgKUVCeADyk8PBccDi1zfi1s934a21JdhwrFG27QPHcbjxk524+sPt+GKbfJWSr0C9RzNjgxGg6gNSy5dKEGd2WIISJM/796DwNhek8RhQvYPcN+mApmNOF6WZICcatU67eMskVliuOkl9jTNHk3PfsgO1sgOB69t1OFTTDoYBIs38eUaiBIkMVgsdrWVNtuHoHpAgtlZYgEi2GLu8Vg/agmZu2YaiU6QI4ejuJ6nLDhASxJ3cHwCUClYgvPpzOHo5/xvqTZYBa9nwd8KRug6EgT/uAuzHjUMiAtDmhR3W19srMP35NT4ZR/ZHSG099vDFy/4CndEs5Gd8s919kw9Fp94kNAVdNTkdgDRnodknjRlt3UZBVXLlpDSoFSzWHGnAvJf+wsebylwSp1QJ4qkdFgD5GSJWJIhYSA/RkPEQLeJleEiCMAwjdviDqEDkbtPdp+UgOliN4/WdeHUVUdh5EgzvLWjO314ZlkR9DUd2WAAwMVNeLgi1wpqSGQMFyyCOV1qePEXF5YrmLjR06KFkGSGPRVCCeGSHxZ9v+TlbA8KxuUwsoP62rwaNnQacCBrJv/EWrxpExGB0zxsyrELRGQWxqgUkdlhVCFCyQi7hznLnJLPJbBEUPYBo8zzQUczPzXMTrG3NB7IdVmVLN4xmDoEqBa6cTIjdlYfrHF5X/pRpE0sRyueCDHQShIaip0aRuR21pfZbYvkxmOEnQQYbaG6Fo8KMTNw6Kwt3zc0GAHy8uRzvHuAHzE6UIBzHSUKNe6AEifc9CTK7J3kgANBcSm6pRVQPSBCATEieOGsELp2QCo4D7v1mL97fcEJQRlCYLRzu+noPGjsNyEsIxaNnDu/R+1rhFClBNEoFUvlu5R18kFwqy0/8bEkQqmRyogQBSBeGJyGV/Q0qBYurpgzFX/fNwk0zMhGkVmBfVRuu/mg7znlzE95aS/a98elRbomByyemgWWAk206/La/Bs8tK8Zl72/F6P9bjovf3YJON1Ld5YfqhA62Dzac6HM1CB1ojeyFUHSHEEgQeQNdh6AkiKETMDmYkAlKEB+QIEIuSJvbbA8rUBUIhYt1h4QHIFitgMnCCQVlW9DH+8oKi2JSRjSig9Vo1hqwSYY9CsdxeJL3Ms9PCodCy//eoda/91BnllgJvB1W03HA4GRy6ywUHSC5Imq+OOCDXBCLhRMmp85IENqpJw2ydYTaNh32VLaCYYD5w+WRgDG8hUt/JkFOSGxIjjcMzgL4YMKR2g6EMfxv5pAECUQ7xytfdfI7wr/eXomK5q4Bn5HlCK1dBjR2itcaOb71fQmpCm1zaRMqZNp1fb+zCp16EzJigzE1i1joFKRGIEDForFTb2Vl4i3WHqmHycIhKy4ET5w9Er/fORVFaZHQGsx47JeDuOjdzU6tP6gSxFM7LI/gwA4LEJUgFJ4qQQDREistOghneNBMFR6owgMLiJL19/2kOBjhRjnoC/RXJYjZwgkkn9QOCxBJu80lrnNBNlAShN/PE3l10anKBaFz5bFpkQjkg9p7ogShOY41XBS2lJL9mOM4fMQrvUZPmA0o1OQ9Vj3hMRFCbT+9UYKQUHR+O4Oiid03QOabDEsahbQNwvHiigQpru1Al+R8MVhIEKdKkAhyLa5u7R5wWVT0+pERG4zJmTEIUitQ167HgWrrAn+3wSxY6MomQfjzs9wsvv6Kcn7ekMbXaGgt75A/HN2PQQw/CTLY0EJJkKFevwTDMLhrbg7eu6IIoRol1jSQi6G+3nEXcX2HHo2dBrAMMCzBexKEhnAdq+vs0UW2urUbxbUdYBlR+ugVLBaRBMmYRW69DEeXgmEY/PvskbhoXAosHPDvXw9h7JMrcN5bm/Dm2uM4UtuBN9ccx6aSJgSqFHj9kjG+7Y53R4L0UiYIIFpibTtBBseJHD/Yti0kUo9WJ5kggwnhQSr84/Q8rHtgFm6YnoEAFYs9la34fhchgFzlgVCcX5SC3f+ahy+um4B/nJ6HM/ITBcJpc2kTnl9W7HRdg8mCZ/8Qny9p0MoqNPsS1E6vz/JdPOl0cwZNOJk4AfZqELNRJI1jc7x/DwqF0vNcEIsF2Pc1uR/Ok4w1zgMcGYaR5II4LjpRsiA9um9C0SmUClYI65Njs/LOulL8svcklCyDR+cMIZNbwEoJArggQULieIKMA+oO2r3+zvIWHDrI54U4azig+1Znz3NBypu70GUwQ6NknUr0k2XaYa04RLanMCUCcW5CSCmEcPR+TIJIiTtfFE396F0cretAuAslSGK4RAkiU5XKcZzgaS5VTAwW0M9ELTgO1bS7DHjta1TYELDf7XQ/frNYOMEK66rJ6UJji0apQFEaaTTwxXhE7PAlhd2suFB8c+Mk/PvsEQhWK7C9rAW/7HWsPBZIEJnnS6/Q5doOCyAZIZTs9gSXTUjDhUUpeOXCAo+V8eePTRGUGYBoR9SbGJkUBpYhVpU0lL4/oL6DZHcQBYf1vlCYGgG1kkV9hx6ljnLGADR26oVmhsm8coTaap08RSTIqsNkLDxXapFGCTmPSBC+oNxOxmc1XDSO13eioUOP3ZWt2FfVBrWSxfkTs4G5j5NlN7wM/HKbS5tWW4h2WJ4rQeradYiUkiAUCpU4NmytQJEkF8QZaCMfxWC43nAch6P8/plnU8tJCA8AwxClrZSIHwigv01mbAgCVApM5+2lV9jkaJLAdAuSIgJlN/SG8rkg7hoN+zvotTtFIEHIOd+vBPFjMMNPggw20CJ9lPckCMXc4fH4+bYpQDSxw1K2V+LrLSV2BAUtYGbGhoidJF4gIyYESpZBh96Emh4MCNfwnS2FqZGI7IlvfcdJUjxjlcDQ6eSxHipBKFiWwdPnjMJDp+dhWGIYLBwZcD2/7Ajmv7IOL/Lhrv9ePFIoTPoMp8gOCwAy+c+yp7IVIehCKMcPSCnpQeEmE2QwIiZEg4cXDsO6B2bh2qlDoVGyUCtZnCazWzs8UIXJWTG4aUYm3rhkDNY9MAufXjseAPDJ5nJsdSLT/3xrOU40ahETosa5Y8j3TosSrlDe5Nw2yVMISpBeCkW3Aw2s7okdFsuKhGGXzXfbfAKwGAFVsH1otrcQckFkkiBl64g1QUA4MOUO8pgbFUlWHJnQOssFoaGfnoaz+gJn5g8BQKycDCbn+92aI/V4jif9Hls0HEVR/LUkMApQWtuZOCVBAIklln04+gPf7UVHHU9y2eYZUVDViQ/C0WkeSG5CqNMiVkqkvODKZR7K/QGRBOmvSpDWLgNaJZ2hrnJt/OgfKJahBKGZIBaZY5GTbTqhGFEySDpzpSipJ5+pKC0KMSFqGM1cvypSUOVHCF+4/25nldt8nnXHGlDaqEWoRoklY6yvlTQXpKfh6DqjWciHmjdcPO+xLIPLJ6Xj6ilkvrS11LG1pUiCeG6HJRtOlCAhEhIkJTIQKi/sfcODVHjuvHz3uSQOwLIkJJ0iohdD0SmC1Epk82ORvf1IDUKtsBLCAqCwUaEHqBQYkxoBwPn+Ssm8YYlhiObVlaISpO9thtp1Ygj0nGF80wbHeZaZp+GLxYIdFpmz6QIJqbD1RBM+2lgGADh79BDyuSfdCpz1X9JEtPsz4OtLAYM81RhVgnToTLKtUSkaOvSIggMSBJCEo1dgDE+CHKltd9rhTwmSfJ4gHAyZIDVtOnToTVCyjF2zjVrJCko4Oblz/Qm0KYbWUubyc2rbXBBKlM8bEe/Y7tdiAVb9Gzi6XHiIhqMPdDusSokdFiAqQYprO3w2z/fDj/4GPwkymGDoErtOe6AEkSIjNgQf3HYmdEwgFAyHd39ehcVvbsLyg7Ww8JMbXxUw1UpWkHr3xBJrja+ssGgoemQ6EEPswQSljQ/AsgxunJGJP+6chk3/mI0nF4/E7Lw4aJTksDx3TDLOG+ujAiqFSQ8Y6CDQSc5EL9lhAaKfsd5kQRLDd74FRgIBNl0XAglSTQYefyPEhQbg0TOHY/NDc7DqnhnIiJWQYBwH7PgAqNwu67WmZcfi4vFkcP/g9/vs7B7auox4dRVReN1zWi5unkkIz5WH61wOdL/eXoEZ/1mLJ5bad8l7ihatQQjbG1BKEECcSNmGowt5IDmi5L6n8DQXZM+X5HbkuUByEblfu9+l/YAQju6kk55mZ3hjydFTjB8ahdhQDdp1JnyyuUy4/khR2tCJO77cDY4DLh6fgssmpgEdfJh6qL0NCP0cZS5JEGviqKqlCyUNWqQy/D7k7ForhKP33A6L5oG4UlrSDi4SXu/4N27tMggWFYOJBCm3sd05Pgi6MgczmrUGNHToXWaCxIZooGX58UKnk9wlG9AuVgAore+Zorg/gu7XWXEhKEiJAADsrvC9Ytdb0DyiJWOSEBagxMk2ndtgc2qTc35RilXBHwAm0lyQE00Oz/dysfF4I7oMZiTy+Wm2mJBBxsJbT9jnj3QbzGjnC1zxHgajewRpJoiuTeiOlypBTsV1FyANZRcUkTE5LZL1NujvtK+qtU/eTw5oKLqtFRbFpAyi2nYWjr5JyAMRC/AJ/D51KpQg6442wGThkBETLM4zdK2Ame/09yoThChBgmOJ+viXPSfx+34yBruSz/sBAIy5Arjwc0AZABxdBnx6jv042gHCJSRcW7dnFkT17TpEMTxpbDv/jRDdB+LDApAcGQgLB+ytdEzCUausC4rIeqUN2gF/vTnC110yYoOhVtrPW5IGaDg6JUGoE8Ws3FiwDFFS0s9iNFsEVZTTsXHlFmD9C8AfDwgPhWp4Um6QKEFSeZV/alQQQjRKGEyWQaFy8sMPR/CTIIMJ1KNcEy52KPsAIQEqaOIJCZCtrMfeylbc8OlOLHh1HX7cXSWE1/UkDwStlUBXs5UlljfQGc3YyE+6ZuX2lAThO32jMkXLk9YKz4KJZWJIRCAum5iGD64ahz3/modfbpuC58/Ll7dyxVagZA3Q2eB+WTrIZFgxFM4Wgh1Wq7z3dwWLBTCKA6ZMiaolmeG31zYPBADChgBgALPe2ibgb4SoYLVQ2BRQuRX49W7SOSVzP3xo4TAkhAWgrKkLL688avXcf1cfQ2uXETnxIbigKBlZcSGYmhUDCwd8tsVxQHpDhx5P8XkL3+yossuz8RSH+C73tOgghAX0fpchLBZAyxemQ+UXgh0i0Ek4ui/zQCg8yQXRdwCHfyH3R18CxA4jirbuZiG40hGyXZAgepNZCO9M62M7LIBYgVBS+MnfDuOctzZZWRK064y4/pMd6NCZMDYtEk+cNZJ0c1ElhoPfeiivaLELRgeckiAbjjVCAwPiQSbBnKPzFyAhQXquBNnFFzpHOSjgUSTxQa1ag9mpX/aqw/UwWzjkJYR6VFCj1h8Nnf2TBKG/XxSv/Dw+CAvggwnvrCNjqwQNvz85IEFYlhEaMoyd8gr9RyTNMx16U78l7bxFiVDMCRa6+vtTLggtpGTFhWBxIcl1+2aHczXviUYt1h5pAMMAV0yyV9TlJ4cjWK1Aa5cRh2u9V7wIHb7DHXf4jk2LhJJlUN3abaekoyqQQJVC8H/3OQxawGjTdMLb0dJgdODUKDAp/r14JP57cSFumJHRJ++Xz5N8ztQ5pwJ0/GMbik4xlbeuXXagFhuO2c9bhDwQicUtfa1TkQlCi76CCgQQmzYCwu2Usw7hJBMkLpk0VC0/VAeThcO49Ej7Rsm8hcDlP5H3qtwCfLhQWN8ZlAoWYXz3vaNxDrUscwSrTJBgG5thOo5rJRZ+oiWW/f5X3dqNmjYdFCyDRaOHQMEy6DKYhbyYgQraRGCbB0KRPADD0TmOE4r4tMkrOkQj5L6s4i2xtp1oRlu3EVHBaoxLd9IgSp1W2iqF+beoBBm4mSBt3UZBSZ0SSeZ2LMsI+YMHq/uP2tQPP3wJPwkymCBYYaUDjqR8PQDDW2K9MDsEt8zMRKhGiaN1nbj7671YxSsvRngTamw2AqufAl4dDXwwX7j4HvFSCbK5tAk6owWJ4QEYluj4Qi4bNA8kOhMIHULC3CymXrdoClQrkJ8cYSe3doi6Q8AH84BPFwMvZAEv5ACfLgGWPwoc+tleRUFtewKjnHeoC3ZYLR6H1tnh17uA5zOAGmIpkylRNaQIJIgDOxmFSixa/o0ssdyC/x7RWQdUbpO1SliACk+dMxIA8N76UqFoUt6kxcebywAADy8cJtjs0GLE19srHPqNP/P7YaEz0mCy4FsZvt+uQO30ekSieoLuFnIcA0BwDzKDALGbzKkSJLdnry+FJ7kgh34hRZWoTKICUQUAMfy2uCBQsnkSuqShE+02g/rK5m5YOCBYrUBsSC/agrjA3XNzcP/8XASrFdhb2Yrz3t6MWz7fibJGLe7+ag9KGrRICAvAW5eNETvZXCpByIC/sdNg93mROJrc1h208qxef6wRSUwjWIZDJxeASp0TQiiUJ0E6ehbQbDBZBBJkwlAnkzMQO444XrHhTMW1TJD7e0b+iUqQ/jnJp0qQ6dkxYBliTTDYCuCDBT/vqcY7f5Gx1bBIfnzhgAQBAHUI2d8tXfJIEFsF8WBTBAne5hIlSH8iQSolvuK0Q/rPg7VodeDfz3EcXviTNAvMyo1zSMqqFCzG8ec8by2xTGYLVrrp8A1SKwXlwRabLn6pFZZDixRfgKpAFBrxWOAbK4LVIvGSEXvqSBCNUoFFo4f0TaMKgJk5sVCwDLaVNfebfZzaYdEcD1uMSY3AksIkmC0cbvl8J0ol55+Kpi5UtXRDyTIYLymyUjusmj7urjeZLVhzxEEeiCeh6IADJQghMTIysq0Ws1KBSJE2Cbh6GRmfNRwGPltCSEEXoLkgtueV3/bVYMLTq/D8n44zEOvadYh0Z4fF51C6Ckenjw1PDEN4oEoIk6Z2hQMVtO6S64QEoY02A0kJ0tChR4fOBJYRx/uAuM+v4C2xKFE+d1ic89oLrUVYTAJZKGSCDGA7LHrdjgnRWCkPqTNDf7Lc9MMPX8JPggwm+CAU3SmiCAkSoi3HAwvysOEfs3H//FxE852XagXruZVNwxHgvbnAuucBzgw0HsWICHIhOeYlCUKtsGblxfV8wiIoQTIIYUCL9T7KBfEJqnhbJIUaAEMGsCWrgE2vAd9cAax41Hp5d6HogGiHxZkBQw+KCN0twJ4vSDF246sASKcu9XR1qQQB/pa5IG7RcFi8f3ip7NXmDIvHOYVJsHAkz0BvMuO5ZcUwmjlMy47BTIlqas6weCRFBKKly4ile61DqDeXNOGH3dVgGODi8eR3+3xrRY+sKugAyysS1RvQzvygaEK29QQCCWJToGnklSAxPiRBACB9Crl1R4Ls5a2wCi4WCXEnygYpUiKDMDQmGAaTBU//dtjqORo8nRYd3HvFIDdQK1ncOisLa+6fiYvHp4JlgN/312LWi2uxqrgeGiWLd68Yax1a6kIJEhqgQgxP6NhZYkUOJZkuJp1gjWi2cNhwvFGwwqrk4rD5hJPiXAj/fp09I0H2V7dBZ7QgKljtNh9KtMSyn6R2GUxYd5Sccxd4SoKE+C4Y/attFbj/W3IO8hWoEiQ7PhRpfLe0M0s3P04dDlS34YHvCJF/88xMxCj5/ZSOOWwQGErOr4xe3iSckiDUUnQw5YLojGZRaREbgvzkcDAMyQDqD4Qfx3EiCRIZhBFDwjAsMQwGkwW/2IwjAJI79tv+GihZBrfPznL6upOoJZYTiyF32FnegmatAeGBKoFQcYQJ/PtsPWHd0FDHf7dxvRmKTkmQ4FhRXco3VljZYZ1CJUhfIyUqCIsLiJrov7xl66kGVYIkObHDYhgGTy8ZhTGpEWjXmXDdxzvQxndYUxXImNRIq9+UEip1HXq3+Tm+xK6KVrR2GREeqBIK/gAkVrFekCAWi2CHFRafjrwE8lxCWIBr+8344cC1y8mYqaGYqN1dNODROaRUCaI3mfHMH4fBccBPu6sdKkGtlCC2c2Bqh8UrQWguyJ6KVrvfZSevQKbfGyUnB3ouyBFeCZKb4IQEGYBKEGqFlRoVBI1SVNXRXJAtpU1o1xmx/CAZp7vcT9sk7gg82UfVgQM5E0SwwoqyJndHCCRI/8ll8sMPX8JPggwm0OI8tW7yJXglCC0GhQeqcOusLGx4cDaePy8f/7uyyMqr0yUsFmDL28A704GaPWQCzE+ChylIwftYfafHhVWO47Ca5oH01AoLAJp5EoR+dvq99icSpJ4vVI6/AXioCrh2JXDmy0Dh5eTxLW8C1TvF5altjysSRBXIkyromSXW4aUkHBoADv0kFCOp92wyzQRxFizsJ0HsUS/pcCpe6pFS519nDkdMiBpH6zpx6+e78fv+WrAM8MgZw6yWU7AMLufVIB9vLhMmEwaTBY/+fAAAIUAePXMYQgOUKG/qEiZ43uDAyT5Wgnja6eYKgh2WpFvMYgYa+Um7L5UggLxckJZyoGw9AAbIv0h8PJG316vZ6/TlWZbBs0sIWfLV9kqhaA4AZTQUPabvrbBsERcagGeWjMIfd07HtOwY4TB49txRyE+OsF6YKkHC7JUggJhTZBeOzrJAAlFQUeLoQHUb2rqNyFKTglwlF+u8Q5kqQXpIgmzji3Lj0iPdkk/UrqDSgRLkryMN0JssSIkK9Fgl6atMEJPZgn//egjf7qzCmmIZ9o0yQQms9OhgQW14/G9EguhNZrRoDWjm/5o69Wjq1NtlQJ1KNHbqccMnO6A3WTAzNxb3zcsl2QeAUyVISCSxLFEZ3U/CzRZOsFGdkUMUfiWDaB8ob+qChSOdp7GhGoQGqAT7wv7QKd/SZYSW39+SIwPBMIyQI/HNDmu16M7yFjzJk+wPLRzmMrCbhqNvLW12GIRstnACQe8If/LFrTnD4lyGik8USBDr83l9uxiG3Wuglq/B0eLYnB+rS3NSbMOKBztunZUJlgFWFdcLiuFTiZo210oQgCgy37m8CEkRgSht1OLWL3bBaLYINs2Ts6znXrGhGihYBmYL5/H1leM4PPDdXtzz9R6PCZSVvA3QrNxYQQUOwLNQdEASjN5O9mOLEQADhCZgHl9ovm7aUJfHHgDSDHfeBwCjAPZ9Dez8yPmivBKkRaIE+XJrhWBlV9eut3OT4DiOkCBOlSB8M15bJcBxyEsIQ7BagQ69yU5hSEPRi9LJeYuOOUoHMOlutnBC44hTEoRXgthaBvZn2FphUWTGhiAjJhhGM4fXVx9HbbsOwWoFpmTFOHoZglbJdYyvS4TyyrjOAZwJUmETik5BGxMP1bT77WX9GJTwkyCDCYIdVi8oQaL5Tq2mUquHA9UKXFCUIkw63aK9BvjsHGDZg6TDNnM2cMtmweYlUX8CagWLLoPZY8nl8fpOVLV0Q61k7QaaHsNiFr9P+tnp9+rDcPQeo/4QuY0bBmhCgJRxQNE1wNmvA6POBzgL8MudxHYMkChBnHfEgWHEXJCehKPv/45/PZbIR3d8CID4WQNAihAs7CdBZIHjrJUgrRVA7T7Zq0cGq/F/Z5OiLp0AXTguBXkOwpYvLEqBRsniQHU7dvMFlvc2lOJ4fSeig9V4cH4egtRKnDuG/EafbSn36iNp9Sah+Nx3ShAfhaIDju2wWsvJuU2h8T0hnTAaUIe6zgXZ9zW5HTpN7G4DZClBANIRexVvXfCP7/cJNlHSQnN/QW5CKD69dgK+umEiPrp6HM4pTLZfyIUdFiCSOnYkCCB+Z9veBba+i5LtfyIMnRgfTjrTK7g4bC5tcjxBoCQbVaJ4iW18UW78UPfXNOrn68gO69ud5Dy6YESCx0oeSoJ06EwOLfLk4sDJdqFQutlNYLInKJcQdHSy+3chQbaXNWPSM6tR+O8VGMP/jX1yJcY+uRKjn1iOnQ48zfsaBpMFt3y2CyfbdMiICcarFxUSywk3JEh4FDlHB5g77a09bVDR3AW9yYIAFSsoGwdToKc03JUev3LC0bsMJhgdkAe+Bi2kxIdpEKAiHbeLC5KgVpBxBO0mbezU49bPd8Fk4XBGfiKumZLu8nVHDAlHaIASHXqTnS1Hl8GEi97djBn/WYs31x63W5fjOMHmxGWHL0hXt4JlUNncbTX3kNph9Rq0PCEcHGunLqWe82oF6zSLYrAiIzYEZ40eAgB4zQs1SHVrNy57bytWF/esEYHCXSYIRWyoBv+7oghBagU2HG/E/y09JISiT7UpsipYBvH89ZUGr8tFeVMXvtlRhR92V+PnPa6zNGxB5wBzhtk0A/VECULnaqEJgEKF22Zn45fbpuDaqTJrEulTgDn/Ivf/eAA4ucfhYlQJQu2wtHoT/ruaHP/BanLu+euIdZNFe7cJBpPFuRKEzjf17YCuFQqWEchZqSVWp96Ew3yOYVEaOVapEmQgX2/Km7Qw8NdPOo60RbIkGH2gFMWF66YDFTVVg7y/gdR0ZubGCdcuh5DWIqgSZBBkgtDxsy0Jkh0fArWCRYfO5FBd7ocfAx1+EmQwoQ/ssNBeZRV07RE4DvjmcqB0LaAMBBa+AFz2AwnBjiMBworGI8KAwrb7wh2oCmRSRjSCJD66XqG1gnS0KDRAGD846s9KkLhh9s/Nf4YobOr2E0UIIBZrXSlBANGeotv55NolOur4bnSIg9qdHwImg9A1494Oy9qj9W+PznryezAskHUaeezwrx69xMJRiTh9JCkGBKsVuPu0HIfLRQarhcnnJ5vKUNncJUxCH144DOH8JOSyieS3W3m4TpggeoLDNe3gOFJgoIXWXofQ6dbDUHRAYl0h6R6loegxOQDrYkDtDRRK4qEMOLbE4jjRCmv0JdbPxfOqhtZytwqvBxbkIjUqCCfbdHjmd3KOoZZDViRIdytQe8DDD+F7TMyItrJ0s4ILOywAGBpDzkd2dliAmMFStQ34434s2XcD9gXcgDntPwIAaph41LXrUepoXbp/dTcDJntPfDkwWzjsKHOfB0KRwsvZbScsfx6sxerieihZBheOS3G0qkuEBSgFi6GeqEGkljabvPT4t0W7zogmLfl+06KDhe74Y/XeWWoOJDR16nHbF7vQrHW8fxnMFizdW9PHW2WPJ5YexLayZoRqlHj3Cl41bLEAOr6o7YQEiY0hzTUsOMDg+vekVh7ZcaHIiR/4nbm2cNTR6i4cvVNvwoJX1qPoyZX4Y3/v7geVDrpJI4PVOI0vNH27owpmC4c7vtyN2nYdMmOD8dy5+W4JWQXLYAJPAG+WnD90RjNu+GQntvPnx+eXHcGyA9aE88GT7ahu7UaAisX0bNeNWiEapRDcvFXyPrXt5HwX36t2WBISxIkdVkpUoLycwEGG22ZngWFIwDYtPsvFJ5vLsOF4I5789XCPi7Y6o1m4zgxxYoclxfAhYXj5wgIAwKdbytHSZUSwWoHRPHEpRSJPqtR4GI6+T6KOeXH5UdkWkycatSht0ELJMpiRa3NceNokJCVB+MIwwsjcQa1kkZ8c4VnTxeQ7gNyFgNlALJ0dzEFFJQgpPH+w4QSatAakRwcJc5q/jlqTIHV8nlk064QEUQcBQTxBZWOJtUtCguypaIWFI6qIBD7PZTAoQWi9JSc+FKyT8wwl/zr1JrR3DwzlA80Fk+aRUtBcEKqimjfCBfFnsdiQIMT2jZLU7QPYDku4dts0uKkULHISyPfmt8TyYzDCT4IMFljMxAYF6B0lSFCUOFFt9lIJUbaBZFgoA4Ab/wLGXy/61ccNJ7cNxcjmQ7mO1nnWVSFYYeX50AoraqgYIE7JJW8/v6+hbQS0/IA1Ns/++ZBYYP5T5P6aZ8h2y8kEASTh6K3ebdvBH4kKJXkcMOk20oXdWQcc+hmZsSEIgxbhDN+tHO6kKOdXgliDqkAi04nKB/AoF4TiycUjcdboIXjuvHzr7AQb0CDD3/bX4L5v90JntGDC0CgsGZMkLJMVF4qJGVGwcMTr31PQzs6RfaUCAcSgap8oQaytKwD0Tii6FIIl1kb75yq3As2lJMti2CLr54KiRMl/nWviIkitxPPnEfusL7cRWyzaLZQWLekW+vlW4O0pQMVWrz5Kr8NikZAgjpUgQ10pQUYsAS7+Cph2H0xZC1DFkUmygiMTHkMc+Y4cWmIFRgIsbxFJz9Me4nBNOzr0JoRolBiW6N4uLpnv4JPaYXXojHjs54MAgBtnZCArzjMrLIB4nQuWWJ3ekyDS4uKx+k7U+yBovaJJDHUM0SglSpCBW5CQA4uFw73f7kVdux6ZscE48MR8lD69EKVPL8SJZxbizUvHAPA+UNpX+HJbBT7fWgGGAV69uEAs4hs6ALgORo+PioCO448hN2MRaRGHFjyqW7v7lSVYT1DioJhDlSD7qtoc2uF8ubUCFc1daOs24ubPd+HhH/f32vdRIckDkeI83hLr5z3VePaPw9hU0oQgtQJvXzbWyurJFaglFiVOjWYLbv9yNzYcb0SQWoH5fPHqnm/24JBELbKcD72dnh2LQLX7hoSJGYSA2FoqXs+pEqRPMkGCokUlCD+mKEqLRGpUEM4d60Dl+DdAVlwoFo4i1+7XV9urfVxh3VHyvZY2antsGUcJiiC1Qrb18/wRCbh/vjgOnJAR7dAWihbTPW0kklqEVbd24/Mt8sbgq3gVyISMKPug+54Eo/OFYYQlOV/eHVgWWPwmaY5rLQd+usXO9jdSEozerDXg3XXEoeLeebmCsmV7WTO0Eoui+nY9AA4RzuywALEhj2+8K+JJkB0SEmQHr6ykVliAaPFc3dqNLsPALIbv5/elHCeh6ACZF9Ac2KpWe7VxfwQNq3eUpzcmNUJQFakUDGa5qh1pGwCzZOxra4c1gEkQZ3ZYADAikYzN/OHofgxG+EmQwYL2k0S5wKp6NgBxBoYR1SBu7FScYtNr5LbgEvsCIS3i1x9CbpznSpC2bqMwUPEJCUJtv+hnBvqfEqReUhRXO7GoKbgUSJ8GmLqB3+6RTLbcdBVTJYi3dlgHeCuskeeR8Omia8j/295BbkIokhjJpE/jJOyX7se0u+jvDpoHEjsMyJkHsEpCjDR6NjGMDtHgtYsLcWb+EJfLjUwKx5jUCBjNHLaeaIaSZfDk4pF2XV2XTSR2Zl9tr/TYdoNO4vosDwTwbSaIIzssqgRxREz6AlISRJoLom0ktk0AMPxsx8eVTEssgKgrpLZY1GJJ8CXnOOAEr/Y69qenn6Jv0NUIcGaingp2fF2gSpATjVr7blGWBXJPB+Y8irVjXsNU/Ws4I+gz4Oo/gKv/QPSwaQCsO5St1qVEGyXePATNAylKj5TVBSzaYXULmVovLj+K2nYd0qODcPvsbK+2A+h5LohU1UItBHxRoBcVSuSzU9uDxk69YJcxGPHehlKsPdIAjZLFG5eOQYhGCZZlwLIMGIYRMg6O1HWgsQfEVU9BQ43vPS0Hs/Mk51xqhaUMAFSOC8xDIgLRBnK+0XW4tvWiHvC5CSGIDFYjii/WDPSwWgrRDksc6+XEhyJIrUCn3mRn/6Y3mfHeBjKOpeHiX2ytwFmvb0Bxre8LGvT6kGJTSJmeHYuEsAC0dBnxv/Wkgei5c/OFZic5mMyTIDvKmqE3mXHft3ux4lAd1EoW711RhDcuGYNp2THoMphx3cfbhXPUcplWWBQTecXJFkkuCM0Eie9NpaqLYPQhEYFY98As3DLTeXj8YMfts8ln//1ADY7JnBfWt+uslCM/7u7ZPKKGJygSwwM8UjbcMjNTsI2lZI4thvAkSK2nSpCqVgBisf71Ncdl2fIIVlh5DsbAVAniZLxkB0qCmHTi3LinNYjASOCCT0g25ZHfxdoBj8hgaodlxFtrj6NDb8KIIWE4Y1Qi0qODkBoVBKOZsxpf1HfoEIJuqMEXqx2SINbh6AWpEWAYUiSmDRvUGqtIEiYfFawWiukOm2kGAFYdJr87Pdc6w0AKR+/QGVHLn78dKUGUClYgPiZnxtgTglLYNmPydQlK5HfoB6YdlslsEewfHZIgSf5wdD8GL/wkyGABtcKKSPW9BQtF2mRyu+xBMfhXLuoPA8eWA2CIMsAWMTmkUNXdghERZALjCQnywy4itc+ND7WbhHkFIRQ9Q3yMZlfoWr23ifIlBCus4c6XYRhg0avE1qtkNXB0GXncrRKEH+B58zlbyojih2GBEeeQx8ZeRQa0VduR0n0YT87gB87OQtEBUSHSWQeYTl0Rp9+AKkFic8nvM3Q6+b/YczWIXFA1CABcPz3DYeFi3vAExIRoUN+hx4pDnhV7aXfJiKQ+VIL0SjC6IxLEsdVYj0FzQXRtwPJHiWXAy6OA/2QCB74ny4y+yMm6PAlSIy9LRmqLZeGAQJVCtC1rrSDZJED/VYLQPJDgOGIl5gBU2dKuMzm1FQKA9ceIvUJhTjq5FqZNFoqLW93lgnR6lwtCSZDxMqywACAxIgAsQzIYGjv12FPZio83lwEAnjpnlGu/YzeIDSG/e72XJMihk0TVEhqgxAVF5NzuCxJEVCiR4nCIRikUlQZrLsiuihY8v4ycZx4/a4TDXKeoYDXy+IDTLY5Iuj5Aa5cBJ/nCnvRaAsBtHghAbNg6eRKkqcm1muporagEAYCMGOrT3rtFqQ6dEe+uK+lVosli4QSrFWlHq4JlkJ9Mvr89ldZjtZ92V6OuXY+EsAB8dM04fHbtBMSGanCsvhNnvb4Rn24u86mvu7NuUgXL4NyxYlH06inpWDTadQOGLXLjQxEZpEKXwYwr3t+Gn/echJJl8PZlYzA5KwZKBYvXLx6DjJhgnGzT4cZPd+BoXQeKazugYBnMGSavoFuUHgmWIeeU2jYdOI5DHW+HRbv1ewWOMkH6wxyjnyAvIQzzR8SD40ihXw7WHSPEUhCvAPpl70kYTN5n41TLzAOxBcMweOH8fKx/YBbOHeOYHEgI99wOy2LhcLCajJ8fWzQCGTHBaNYaBKLRGdq6jIKF3FzbPBDA82B0tWROQFXQ4T5oxBxSCCx4ltxf+YTVmJXaYR2p68DHm4kDxv3zc4UGAJpRKrXEqu/QI5LmgaiCiP2VLWwsmMMCVMjlrye7ylthtnDYXdEKQLTKoqBqEFfXm7+ONuDjTWX9Ti1S0dQlnCvdNZEOpHB0+lvEhmqcqrdum5WFOXlxuG+eG+V+G6+yUvLHfxshQcL4hp6BqgQ52aqD2cJBrWQR54Dopw2KB/xKED8GIfwkyGBBb4aiU8x6BEgqIoPzz5Z41t266b/kdtiZQHSm/fOqACCKEA55LLm4HK/vdCjxt4XJbBGCra6Y7KKo7gmaKAki6b5SB4tFrf6gBpGGortCdCYw4wFy38AXhXrTDosWYtOnAaH89xUSJxIiW9/F2HB+MOosDwQgk0E64PCrQUQlCP29884ktx7mgniC00cmYlRSOEYMCcMdTrrI1UoWF/E5A59ulh+QrjeZBaKzb5UgfDEt1BdKEGqH1UpUGRzX+0oQaS7IljeAQz+LA/ToLEIyp09zvG4isW+Sq+YLUivx3Ln5wv9p0UFiF6T0Nap3eJd7wXHA8n8CH50JaHuhUNtOQ9GddwIHqBRC0ZyqChxhPV9UmSbxli9IjUCAikVjpwHHHBXc6ft2eq4E4TgO28oICSInDwQgHr6JfEHlRKMW//h+HzgOWFKYhCk2gayeoqdKEFqIH5cehanZZFt8kQtCs1zSJTZtmYM4HL2ty4jbv9gNk4XDotFDhHOvI1AboVNliUVzOpIiAgXbCAEySBCGYaBTkiJUW3OD0+X0JrPQgZvLEz+087Okl/eBp347jKd/L8Yzvxf32nucbOtGt9EMlYKxIxkKUkgxjhbnAKK6eucvogK5btpQaJQKTM2OwbI7p2FWbiwMJgse/fkg3lxb4rNtFOywHDQhXTw+FaEBSkzJisZDp7sZrzoAy4rKpq0nmsEywCsXFVgpi8KDVHjvyiKEBSixq6IVl79PiPkJQ6OEoqk7hAaoxFyQE01o15nQbSRqS1fWoT1GF1WCxNgFo/tBQFWMS/eeRKmMAOp1fAH8ysnpiAvVoLXLiLVHvLOlBESCYki45+H0DMMgJSrIqYKEjj88CUYva9KiQ2+CRskiLzEU9/G2W++tL3V5jV57tB5mC4fsuBCkRtscqxazuC/KbRJSKAmpAIhzFF+5URRdA2TOIWreklXCwxF8Qbu0gYR5TxgaJRAfAIT7a4/WC0RvXbsOUa6ssABxPtoq2oqNTaPh6M04UtuBTt6e1LbxgCr0nO2bXQYTbvhkBx775SDmvPgXft13st+Eiy8/RJp0xqe7P1dSEqTaiwzIvga99mc5UIFQZMSG4P2rxmFUsptGPF4dhOQicttZC5hNQiZIh87Ub35PTyBtXnCUBZOXEAaGIeN+X9jX+uFHf4KfBBks6M1QdAp1EHDJ14SsaK0AvrgA0MuYYLafBPZ9Q+5Pucv5cnzRMF5XCo2Shd5kEU7QrvD7gVpUtXQjOlgtyI57jCa+2yjKhrDpT5ZYcpQgFJPvsF5ObjC6N3ZY+3kSZNR51o+Pv5HcHvwBqN5J7rsiQRjGnwtCwXESJQhfXM87AwBDCtDUi9fHUCtZLL19Kn69fapLT+2LJ6SCZYgtkNzC47G6TpgsHCKCVMLAuk9Au/J9ogSh3WAcIULaqgCjlliVRWW4WrNnmHw7MGQMsb2a+wRwxS/APyqA23eSHCDWyaWdKkEaimWTFpMyo3HlJEIuD5fmUkhzRUw6oGav559jy1uEIC9bD/z5kOfruwNVgjjJA6EYyk9gTzQ6vt5UtXShtFELBcsIhWUA0CgVKEojRatNxxvtV+yBHVZJQyeatQZolCxGJUXIXi+Ztyt4+vfDKK7tQGSQCo+c4Xnh0Ra0COgtCbKVt5iZmBGFcelRULIMKpq7hFBGb0GJq7QY0SYom889GWwkCMdxuP+7vahu7UZadBCePsfenlCKyZmEbHJo19YHoBZVVJFiBRkkCAAYVeR5bauD44vHiUYtTBYOoQFKJPDZDZlxVAnSe/tAQ4ceP/A2O6uK62ByYwdptnB4bdUxj4uxtKM1PToYSptMgcLUCADW4ejLD9aitFGL8EAVLhovjrGiQzT44KpxuGMOKSj/vMc3zSUmswUnW0mBxJGlRnJkEHb+8zR8es0EqJXeTTul591nl+Q7tPPMiA3Bm5eOhYJlBAWHXCssCko4byltEqywwgKUsjJFvIZWQoLY2GH5QTAyKRxz8uJg4YA31rgm7ywWDhv46/Gs3DicXUD2lR92eb+/n/RSCSIHCQIJIr/ISDMchg8Jg0rB4vSRCRidHI4ugxmvr3bu1LCStz2a40gFom0kWY4MS/ZFuaCWWB0+yASRgmHEorNkzh1pU6h/YEGe1XVwUmY0VAoGlc3dKOOVolZKEGd20DZKEEBKgrRgJ58HUpgaIdqTWsg5350SZNPxJuh5JVJNmw63fbEbl/xvq9AocCpBFfynDXc/JxpIdlhCKHqcE7twT0BrEEljiO08ZwE6aoTmDpOFE37fgQRXeSAAEKxRChbI/lwQPwYb/CTIYAEdINAifW8hOAa49DtSRK/ZA3x7FWB2IwPc+jbJK0mdLA5oHIHvcGcbigXJvztLLI7j8O46MiC+YlJ6j+w+BJiNYieIrWqlv4Sjc5yEBJFR4FKqgUWvAeAHbu4KwIIdVqtn21V/GKg/SAYJtsHMyWOBpLGA2SCqRSLdKHf8JAhBRy0pGjEssY4DSJd5ynhyv/i3Xn17dx7ISRGBQlfm51vdq0FatAZ8toUsN2JImEceyz2CUScW33wRjK5QAhq+iNfdLKpAorNIFk5vYeh04IY1xDd56l1Axgy3xUQAZJIXEEHOx5RUk4FHzhiOVy4swD9Ol6hbBCUI/9tVbpH9egCAE+uICoRi39fAsZWevYY7CKHorgth6dGUBHFcMN3Aq0AKUiLsfIOFbntHheYQqgTx3A5rK2+FNSY10qPCIe3E3ltF9vOHFw5DdEjP/ex7ogQxWzjB2mvC0GiEaJQYzYc691SlQIscQ6PFiS4dPzhU5wxQ1LR144XlR7D8UB3UChZvXDLGXl1hg/FDo8AypGOWBjz3JYpraU6H9yQIF0CI124XmSC0kJQbHypcSzJl2JP0FJ9uKRcsdlolNjPOsOxALV5acRT3fLNXyOyRAzEPxL6jtZA/jo7WkS5ljuPw1l9kTHzlpDS78HGGYQRS+2hdp09yc2raXFtqAKShwlGnqVwsLkzCGaMS8eL5o3GBC/XT1OwYPLaINPwwjLzCnhSC4qS0WSBS4nszFJ3jnNhh+UkQW9zOk3c/7alGuQvV5oGTbWjWGhCiUaIwNQJL+Oa41cX1Xu/v1NYvMcL3+wIlVuo79G6JVIr9/PV9FK9cYhgGDy4g47MvtlWgosm+ucBotggE7FxHFnFanpwNivHMVltjc373hR0WBa1pSObcEUHide+04fECUUERrFFiXDo5jv7iP29Dux7RghLECcEjZILYK0EOVLcLylXh/VorgReygR9uEM7NzpQga/jtuKAoGXfNzYZGyWJzaRMWvrYeTyw9KCvLpTfQrDVgO684lkWCDDIliGxQYiwiFQjjCfj2agSpFKDT13YZv6HZwuGzLeWys416G+5IEAAYMYScYw75SRA/Bhn8JMhgQV/YYVFEZwKXfEOsio6vAH69iwzkHUHXDuz4kNyfcofr1xXC0Q8Lvs7uLhSbS5twoLodASoWl0/ykRVWSzmR36qC7DuI+4sSpP0k8eNnlUC0zLDblHHAeR8AC18QB3vOINhheehLvJ8PRM+aK+mSl4CqQcDvL64yQQBxMN0fSBCT3jvLH1+AFqwjh1qHyFKi6XDv5YLIxWUTScfpdzur8NfRBrR12Q8IK5q68NjPBzD52dX4ajsZVNJchT4BneQpNKLaqacI4vfzrmbREznWjb/sqQLDeBSOTqFWslhcmIQ4aTGIrp81l9xWeECCtFYQAp0zA6MvBibcTB7/9S556kK5kKsE4TudypwoQUQrLPvJs9Smxa6wSS3XvFCCeJoHQkHD0QFybJ031jfqSIEE8SL74HBNO9p1xEaCWt/RAM5NJc47/N1BqzcJpIzU2iOrH9phHa3rwJ8Ha2VbJjRrDfhtXw0e+XE/Zr+wFpOeWS10QD+8ME+w7XGF8ECVMIE9FZZYR3xAgrD8OMKodV4Ups0yOZL3oUWpE42dHhEOcqEzmgUin9rZuMvEWrqXdEo3aw044EHQKFWzSPNAKOLCAjAkPAAWjgQlbyppwr6qNgSoWPscFh7RIRrBvmWHG+JGDqiaKzkysEdEhyuEBajwxqVjcK6M89kVk9Lx/Ln5eOXCAo8794vSo8AwQGmjVui271USRN9BGoMAUpwVLDZbnM+r/qYoSInA9JxYmC0cPtxY5nQ5aoU1OTMaKgWLYYlhGJYYBoPZgl/31Xj13lQJ0huq5ZgQDZQsA7OFk3193VdtTYIAwOSsGEzLjoHRzOHFFUfs1tle1owOnQlRwWoUpjqYn3mblyclQRhWbP7wBWjjoWTOHROigUbJgmHgNMvBNhekvkMnUYI4mXNQJUhXE2AgJFtqVBBiQjQwmC1Yzp/fqfoXOz8i9mEHf0RGFCGbSxu0dtcbjuOw9gjZjtNHJuKuuTlYec8MzB8RL+zLD/0gfzzuS6wuroeFA4YlhsnKU03mx5cDgQQ5Llw3HYw/PAW1wwpPsWrOZFlGaDSQkwvy0aYy/POnA7js/a1o6z71YeoVzWQ/d/Xb0zG7PxydoNtgxpbSJtmEtR/9F34SZLCgL+ywpEguIgV1hgV2fwqs/rcgC7XCzo8AfTvpXs+e7/o1qV1TQzFy+MnekTrXRYx31xHf4/PHpiAqWJ7vr1vQUPSoDMC2Q10gQU6xEoSqQKKziMpDLkYuAcZf7345b+ywOA44wJMgtlZYFCMWk243Cld2WIBEnnyKSRCDFnhzIvDWpFMT0m6bB0JBc0HKNpxy+4Tp2bFIjQpCh86EKz/YhtH/txxzXlyL+77di082l+HWz3dh5gtr8PHmcnQbzRieGIZXLyrAzTOz3L+4p9j+HrDiMeJxLAXNAwmJtz+2vQWdUHU1AY38xDOmn5IgAJDgWS6IQ+jagVZe8UPPJxWb5RVtDF3AV5eS7yuxADjzZWD2P4HwVNJttfpJ77fLFlQJEiaPBClttO8uNUusNaR5IBT5yeEIUivQ2mXE4VqbTilBCeIZCcJxHLaWepYHQpESRYo0aiWLp9zYJXkCgQTxQlFAVS1j0yIFOx9q1bSpxEmovAzQUPSoYLVV8GU2P36obu3uFyGkHMfhmo+248ZPd+L3/e5VQd9sr8S4p1bi1i924fOtFSht1IJlgNHJ4fjnGcOcFrcd4VTlgnAcJ4SVOwpul0uCqELI/s+5UKUeqSXjRBpiC5CCvFrBQme04KQHXvty8f2uKjRrDUiODMQ/zyRj1xWHnZNcHTojVktssNYddZ5xYgva0erM1oMWNPdUtuItPufjonGpLhVgtFOadgH3BEIeSKT7Ilpf4YJxKTi7wPOO9PBAlWD7+AtPWvUqCUJVIKpgYjlM7bAsJjJ38sMK100lc9zvdlY57Z6nhe/pkpyIJYVkX/hxt+eWWBzHoYYv+iaG+35fULCMsI/JscQioejk/JmfHGH1HFWD/LznJN75qwTv/FWCl5YfwRNLD+K5ZWR8Ois3TrRzkkIYH3uokpaSICEJRCHtK9A5d1sVcWkAEKhW4L0ri/DpNRMcE+wAZuSS335zaRN0RjPq2vWIckeCBEaIym5+zskwDMamRQAgY0GWIVlwsJiBvV+SZc0GpBlPQMky6DaaUWszRjpW34nq1m5olKzQNJMSFYR3Li/Cm5eOAUDICOMpKKouP0jGI/NkKuaoHVaz1tAvxlbOYDBZhPGhb+ywJCQItXvjs0pDNWIuiCt0G8zC9bmuXY9nfpevxu8t0Gt3mgsShBKtm0qa0KI9RY2g/QRHajuw6PUNuOjdLfhoU9mp3hw/egg/CTIY0NUsTih72w5LiryFRFUAAOtfBD6YD9QdFJ83GYjnO0A87J351FNEZxFlg74do8JIMcqVEuRIbQfWHmkAw5DwR59BCEV3EOAeZd+VckogNxTdW3gTjF69i3wvqiAg93THyyg1wNirxf/D3ShS+osd1u7PgeZSkhVzfJX75X0N2zwQiqihQPwo0lF/dFnfb5cELMvgvxcXYnHBECGkuKRBi+92VuFfPx/Eb/trYOHIxPTz6ybgtzum4uyCJMeTsZ6guxX4/X5g4yui7RqF0OnmAyssikCJfYUQit6PSRAajl6zz/vXoOf5sCQgYxagDCCkBs1ScgaOA5beCdTuI12vF34GqAIBTQiw6GWyzNa3gaod3m+bFNSjWqYS5ERjp52dwf7qNrR1GxEaoMRoB+GJKgUrqDXsCs20o9JDEqSqpRu17TooWcZxx6YLnDY8HvNHxOM/5+ULPtW+gFQJ4ilpsbWU5oGIxYfC1AholCzqO/ReWxZRS5Q0m4DXyGA1ovmmiJL63rNDkouDJ9tRxXtoP7vsMPQms9Nl69t1eGLpQZgtHHLiQ3D1lHT874oi7P7XPPx821RcNy3DI2KLkiCbSr1X3HiD6tZudOhNUCkYZMQ6KELIJEECQ6Osl3cAQQkiIUGUClbYL3xtiWWxcHh/A2mEuXrKUMzMjYVGyaKyuVvIQbHFikN1gnUWIBZq5UBQgsQ6LvgV8JZY3+2owobjjVCwjNsxMSVBtvmABKlscW+pMZBAz1OHawgJER/WcztBp5DmgQBE6UuDpv3h6HaYlh2DzNhgdOpN+H6n/bygXWfEropWALAKyz67YAhYhmQ7lDlodnCF9m4TtAZyzu6NTBBAJFdqWt2TIKWNWmgNZgSoWEHRRTEyKRyLRhO7nmf+KMYzfxTjtdXH8eHGMuzlc4Pmj3BS8PZ2fKyRkNzUKshXCE0g40vObJXVMS07FlMdKHMpcuNDER+mgc5owZrienQbzYh0F4wOSCyx7HNBAKKYCNEogdI1QhEcAJQndwlq1FKb682aYkIuTcyItssWWjAiARFBKnQZzDhQ3bed9t0GM9YdI9chubaB4YEqoejfn3NBKpq1MFs4hGjEnDCvoe8QG0LDkyUOFTwJwtuSdupdkyCfby1HY6deaNj9anulYLXrC9S26bD2SL1H43Nqm5ca7fzaPX5oFHLjQ9HaZcQzf7gnbnRGc78myLzFNzsqcfYbGwSFOW2S8GPgwk+CDAbQgnxIPOkk6kuMu5Z08qpDgaptwNvTgOWPks75A9+TIlRIPJB/ofvXUqqFIPJchgxAShu0Trsj/reeqEAWjEhAWrQPmH4KZ6HogHVXyqmyRgI8C0X3BtTKyhMlCFWB5J4OqF38HuOuJQXQ5HHu99f+QIJYzMCWN8T/93/b99vgTAkCAMN4NUg/sMQanRKBVy4qxNr7Z2HnP+fig6uKcPvsLEzPicUFRcn4485p+OSa8ZiSFdN7OSAn1pHQOgBY+4zQPQZAVAb4IhSdgnp4dzVJ7LDynC9/qiG1w3Kk3pMDqiKJH0nO20ljyf/uLLG2vAXs/wZgFMD5H1nb8mXNBfIvAsABv9zum/OrzEyQ1KggpEUHQWe0YOFr6/HplnJhIrGeL1ZOyYyxCyWmoJZudiRIqIQE8eC7psqJ/ORwjwN5QwNUeOfyIq+6oF0hJoRM3IxmziMZv8XCCYXWCRmiqiVApUBROrnObPbSEovmgaQ7uP5nUkushlPvvbzqsKgAqGzuxiebnOcmPbusGFqDGQUpEVh253Q8tmgEThseb6V08QTj0qOgYElIbFVLz0LoPQG1wsqMDYHK0XEjkwQJjSCFLrWx3eHkvstgEroZc+KtST8hF8THtmhrjtSjtEGL0AAlLhyXgiC1ElOzyHauOOiY8KQT5nP5fIJdFa2yPMRbuwxo7CTnQodkEsRwdKpkO3v0EMG2xBkocXugug3dBueknBxUNJNiGFWhDXTYqu96VQnSRUkQicpQCEfvuVXZYAPDMLiKV8J9srncznpo0/EmmC0cMmKCrSxe4sICMJVXcv7goRqEKsmigtW+yZ10ADEc3X1heX91KwDi1e9oTPLIwmE4Y1Qi5g2Px5LCJFwxKQ03z8zE/fNz8epFBc4L3r5QgvgyDwQgim0HuSDuV2MEEuxbniyLU/BjgWAXJIjgPiDNBYmS3Ofnxrs/J7dK/pxXvVOSQ2V9vaFWWLNy7ZXELMsIhDQd9/UVNhxvhM5oQVJEoGB5JAdUDVLVjy2xxByt4J7PNSkhFhAOBITZKUFCAqgSxPn1vMtgwtt8VteDC3JxBW/f/o8f9kHrhjyRi9u+2IWrPtyOpTIt/1q7DGjn1SuuVJwqBYunl4wEAHyzo0poanKExk49Tn91PaY9t2bQqEa6DCbc880ePPDdPuiMFkzOjAbDAPuq2gaELZwfzuEnQQYD+toKyxZF1wC3bQOGnUW6NTa9BrwxEfjrWfL8hJuIAkAO+CJvdHcpgtQKGMwWhwF4de06/LyHXIBumJ7hk48hoNmFEiQkngx6OItVV0qfo7eVINQOq7vVvnhnsZAChlEn2t9YzMCBH8j9kU6ssChCE4A7dgNX/e5+O6R2WKfKH7n4V0I0KvmJ8JE/fJtb4A4c57q4TnNBSlb37Xa5QXSIBrPz4nHvvFx8cs14PH/eaAxLlD/QtkNbtbzPV7JavN9cKkrWAe8nea5Au8rqD4vh9dG9YPHlK8TkkEwUQ4doaeUp6ngShBIqqRPJrSsSpGKLGIQ+/2lg6DT7ZRY8QwjS+kNEydMTmI2i1YgbJYhSweLL6ydicmY0dEYLHv3pAK7+aDvq23ViHkiO865D2m2/7USztU9sML+fWUwe5SvRScb4oX2Yl+MGGqVCCCT1JBz9SF0HWruMCFIrrPzLAWtLLG/gTAkCiJZY/SEXZFUxKYxTsuy11cfQ7GCCuLO8BT/sIuOaJ84a4ZN8hRCNEvnJfZ8L4jIUHZBNgoRFkcJRCNcpkAFSHOMtU2NCNHb2T9QGw7Yo1VPQBpxLxqcKfuC0sLjisD0J0qw1CB2ft8zKxNCYYJgtHDYdd/970G0fEh6AYJuQc4qRSeFQSvaVG2c4GLvaIDkyEPFhGhjNHPbwHeLeolJGuOpAwvihUVZumb2rBKGh6JLrC80Z84ejO8SSMckI1ShR2qgVOtkp6P9SKyyKc8dQS6wqj7qlaR7IkF4IRaegChM5dlj7q4hCyfZ6SpEQHoA3Lh2Dd68owksXFuD/zh6JBxfk4dZZWTi7IMl5UdgXmSBhPiZBAEkuiGc21DNyyPiLhsHHKflaghwlCHWEADAyKQxqnmwamxZJ3DeKfyVPTr+X3FbvEEhqqZq4Q2cULAdn5jqed1DS1VVxuTew4hBpEjpteLxHRIEQjt4PlCCVzV0OM79EEsQXoeh8E2Y4b99t05wZKpAgzsmMTzeXo7HTgNSoICwZk4wHFuQhKSIQVS3d+M+f9vk9nqKmrRs7yskc4+21JbLOb7R5JDZU47bZamxaFC4eTz7/Iz8dsFK1UuhNZtz06U6caNSiSWvA7we8y1/qTzhS24GzXt+IH3ZVg2WA++fn4rNrJwjE5Z8H3Nvb+tF/4SdBBgP6MhTdGcKGABd+Clz8NSlct1WQwrE6hJAkcsEX9dmGI0IR46iDXJAPN5bBaOYwLj3SY7sQt2giE1yHShBpV8qpssSymEXbnV5TgkTwdzhrX+KTu4H/FgLPpgJPxQNPRAD/jiX/d9aSgkbWHPevHxAmL8uESquNWs9D2n0BjgM2vkbuT76d7BOmbuCIDALHV+ioIb8BowBisu2fjxtOJgkmHXB8Zd9tV1+ibAPw6mjgCzeKMo4DSni7soxZ5Pav58UcFzrJc6MM8Ai0a7N8E7m1Da/vb1CoRPK01ktLrNoD5DaBdAchhZIgm52vs+4/hCQfdT4w4UbHywRFAac/Jy7f0IPJAf2tWZX4G7nAkIhAfHbtBDx65nColSzWHmnA/FfWYVcFOe9Md5AHQjFiSDhCA5To0Jtw8KTkfKlUi+/dKX+wLCgnPMwD6W3E8kXmSg8UBXRiPzYt0k4RIORVlDZ5FV59gu98d6QE6S/h6PXtOuyrIgX/Vy4qwLDEMHToTHht1TGr5SwWDo//Qmzmzh+bjNG8xZEv4FSp1ItwGYoOiFabbkgQdTAZ34WhC985sL+h9lO5CfbFDmeduT3Bgeo2bClthpJlrLJZ5gyLF7oDa20KmcsO1MJk4TBiSBgyY0MwnbdxsS3gOgK1c8t0EIpOEaBSCA0Gc4fFOf/OJWAYxme5IGIw+uAgQSKC1FY5NnF9kQliRYLQnDE/CeIIwRolzi8ixWqpLzvHcULWznQHTQvzhicgWK1AZbNYMKTrbS1twj++34cPN9oX2k/yx3NieO8pnahlj+25wxGoEsQZCeI1pJl5nqDXSZB0cuvhnHtqVgxYBqBDC7eZIACQMoHc7voU6CT7kkapwJWT0zAqKZwQGQe+B8wGYkU8lq9vNB1HXjhR1EntFzceb4SJVyalxzhW8lH7vR1lLTB7MQ7yBmYLJyhU5eaBUFAlyKnugl95qA7Tnl+DGz/bafe90d/A1XVTNqgqiBJktpkgvB2WMxJEqzfhHT6/9vbZWVApWIRolHhmCWki+3hzGXb08Bq84pDYfHGoph0bZTRYyMkDkeIfC/IQE6LG8fpOvLuuxOo5juPw0A/7rc6rP+8Z2HZRde06nPvWJhyv70R8mAZfXj8Rt87KAssyWDCC1BCWHfSTIAMZfhJkMEBQgqSf0s0AAOQuAG7dCky+gwT9zXhQUlCXAdrpXn8I2by/839XH8f/1pXiaF0HOI5Dp96Ez7eSDuYbprvvePMIRp2o8HCkBAEkuSCnKBy9pYwU4pUBvfebKzWiLzG1xNr7NfDBAvuBqNkAGPgiQ8Fl8lU/cqAKFG0CfrsHaK1wvbyvUbkVqN5BOufH3yAGvvelJRa1PovKcPzdMgyQs4Dcd1WEHqjQdwA/3QxYjED5BqLucIbmUrKPsCrg3PeJAqCtEtj1CXm+V5QgPAlLVRX9OQ+EQmqJ5SnMJlGJFs+/Tso4AAxR0XXW26/TXCpm6cx62HUo/chzgez55Lzyyx3eK8CkVlju8qh4sCyDa6cOxa+3T8XwxDC0dBlhsnBIiw6ystawhYJlBMJis203HyXcOuQNlmvbdChv6gLDAGPTfUzw9xA0e+D5ZUegM8qz0KEWD9I8EIr8pHCEaJSOQ+VlgAZfOlKCUBLk2CkmQVbzfuCjUyIQHxaAf55BCMjPtpRbdYx+u7MS+6vbEKpR4oEFvrXTo4qbzaXeh9B7iiNCKHrPlCB0/BjOaPH+hlK7/Y6Gr0vzQChEEsR3mSDv8SqQM/ITrfIBYkM1KOSPD1s1yFLeCot69dPQ3nVHG9z+Hscb5HW0XjU5Hbnxobh/vvx9h1pi9YQE0epNaOJVTa58xQcapAR0jz3lXUHrwg7LrwRxiismpYFhiNUQJcNLG7WoaumGWsE6vN4EqhU4fRRRhf6wqxodOiM+2VyG+a+sw4XvbsFX2yvxxNJDWG9DTlIlSFIv5YEAosrkpBs7LLOFExot8h1klPUIvrDD8nUmCCDOuT2wwwKA8CCVVZNkOMePMVyRICOWAIkFgL4NWP1v4eFHzhiOpbdPJbaUuz8lDxZeRqy1+Hn4CJDCsPS6vqaY7EszHFhhUQxLDEOohjTR0Byi3sauihY0aQ0IC1BinIfNNsnUDusUK0G+3UlqNSsO1eHF5dYNU7T5JcsXJAi1w6IKEHqrbQBMeqE56NMt5Q4tRz/ZXI5mrQHp0UE4p1AkCafnxOL8scngOOCB7/fJHlM7wnLehpPmjby73sU8mUeFhwrO8CAVHj2TNN6+tvq4VbbSO+tK8cOuaihYBs+fS3Int5c1y7L3669Yf6wRnXoTMmOD8dsd0zBBck2ZP5LM67aXNXukjPejf8FPggwGtPDFt1Nlh2ULdTAw79/Aw9XAlDs8W5cqGxqOYEa2GE741O+HMe/ldZj0zGpc/eE2dOhMyIgNxpw8HxYzAb7Az5Ggt2Ang5ZTrQShRfHYXIDtHX9aAKIllrYJ+PMR4McbiNogZwFwfynwj0rgvuPA3QeB23cBt+0E5j3p++0oupbcHvwR+G8RsOIxlyGpPsWm/5Lb0ReSiQG1+ipZTb6XvgC1wopzUdygRW0aWD2YsOJf1uTXoZ+dL0utsFInksnJ9PvI/+v+Axi6xG58X2aC2KoMBgQJwoeje0OCNJeQ84AqWJycBkaK5+7Krfbr7PgQAEdyP6Lc2BcyDHDmS+T1K7cAe7/yfBuNOmD9i+Q+tdTzADnxofjp1im4ZWYmVAoG549NdrvOJFpodhqO7oAccgCqAhmeGIawAO9yIHoLD55OOsGKazvw0oqjbpfnOE4gQRypWpSuQuXdoNtgRm076ZodGhNMrPK+uxY4TGwqsuNIYaa8qcuhdL+vsJLvtqRjlSlZMZidFweThcMzf5Bze1u3Ec8vI5P4O+dmCyH0vgJR4TCo4Qm23obBZBHUF7mSjnorCCRIhOsX458PZ7Ro7NTj2x3WNqSCEsQBCULtSRo69B7l2DhDTVs3fuX9tq+ban8eO204mRhLuzLr23XYcoLs22fwBdiJGdFQK1hUtXQLBVxnoHkm7jpazx2bjD/vni5LBUJRxHvd7ypvsbbx8wBUFRYRpOp356ueYKIkv8jXx6MVKAkSJFWCSHLG/HCI9JhgzObthT7m1SBUBVKUHokgtWPruCWFoiXWhKdX4V8/H8TRuk4EqhRCLsJDP+y3Cvat4UkQGl7eG0jgVSbulCClDZ3oMpgRpFYgwxdWP1L4wg4r3P1YyWMIc27P7VtpLggLC4LNVAni3NoULCuqkXd9AtTstX6+dj95jFURVTMAJBUBAFK6SHPQyTYdugwmcByHtUfJ9X+WEyssgDTR0Hy0LX1kibWc72CfMyzecWaXCyRFkKJ5X2aM2aLbYMZfR0Wy8s21JUKzgcXCCeMP39ph8XOJwEgxC6a9GldPSUdSRCBONGpx7lubcLROzKHr1JsE1cTts7PtMnz+ecZwxIZqUNqgxas26mDZm9dlFPabVy8qAMuQc6E7Qo2Gortq8LLFWaOHYGpWDAwmCx79+QA4jsOKQ3V4bhkZyz62aDguGJeCcemR4Djg170D1xJrL28TOjsvDjE2VqtJEYHITw4HxwErHVig+jEw4CdBBgP6gx2WI3gTRhWVASjUgFGLRWlmrLp3Bh49czhm5MRCo2RR267D9jIit7t+WoZPPLOtIISiZzjffi9C2nyK3g5Fp6AKnu+uAja/Tu5Pvx+46EtSYA4IA0JiyaA3OhOIyZLdce0RZj0E3PAXkD4NMOtJVsBrhcDWd61Dr32NphKg+Ddyf9Jt5DY2hxSQLSbg0E+9995SCKSXi/yXeH5fqD906rJTegMlq4EdH5D7dMLhkgRZQ24zeSuswiuIj2tnHbDjfe/l/q5g21XWn0PRKRJ5EqTGCzssIRR9uDUJ6ywXxKgDdn9G7lNC0x3Ck4EZ95P7Kx4VrXPkQN8BfHE+saxTBgAzH5S/rgRqJYsHFuTh4BMLcNtsBzZ0NpjMWzttON4o+P8DkJAg8pQg207QPJD+ZYUFkNyFZ5aQfed/60vdTtiP1XeiWWtAgIpFfnKEw2Xo9+ZpLgjtYgsPVCEiSE1I8gPfASsfA0B8/EM0SpgtnMNcMVt0G8x4ZeVRTHx6FT7Y4Jtru85oxsbjZF+YM0wsgjy8MA8KlsGKQ3XYUtqEV1ceQ5PWgMzYYFwxKd0n7y1FoFqBwhQ+hL4PiiyljZ0wWTiEBigxxFnhUK4ShH9eDRM0MOLtv0phlBTsacEhx0HxPzRAhTi+gF3qA0usjzaWwWThMGFoFEY56MKmuSCbSxqFkNRf99WA44AxqRFCsSFIrRSKXuuOurbEEos5jq1UeoLchFCEBiihNZhxuKbD/QoOIBRSBokVFsWkzBgMCQ/AxIwoj4uEHkGww3IUjO5XgrjCVVPSAQDf7axCh84oscJy3nU/MSMaQ8IDoDNa0GUwIysuBI8vGo6tj8zBNzdOEnz6X/hTJPlPthJiYkhvKkH482Rdu84lIUmtFUcMCYPCl/Nfk15U/XusBJEQ3b2dCeLh/IaSIBHoBAN+3UA3CtvUiXzDGwf88Q/r96SB6HkLxYD1pLHkZev3Cp34pQ1aHK7pQF27HoEqhdvxHO0y74twdI7jsJwn6k/z0AoLEK0n91S2YnfFKbCpBvDX0QbojBYkRwbiRj4X9v7v9uJAdRtq23XoMpihZBmHKmGPQd1BqB0Ww4iKp7ZqpEQF4fubJyM7LgR17Xqc//Zm7ORtoT7eVIaWLiOGxgTj7AJ7lVR4kApPLSa2wu+uK/VKCbT6SB1MFg658aGYlh0rqN3+50YN4qkSBCA2mk8uHgm1ksX6Y414cflR3PnVbnAccNnEVGH8elYBOQ/8snfgWmLtrWoFAKfWtPOpJZY/F2TAwk+CDHSY9IIvYb9RgvQECiUQzRec6g8jMzYEXei+mwAA9MZJREFU104dio+vGY+9j83Dx9eMx7VTh+K6qUNx7phe6DhxFYpOIQzIvAwV7il6OxSdgnZotlaQruwLPgFm/7N3iA53GFIAXLmUZM7E5JAOuT/uB766tPeK/pvfAMAR5Yu0u58W4w983zvvaws5SpDYPBLI3dUku+O830PXBvzMk0/jrgfmP0M+48ndjo89sxE4sY7cz5xNbpVqsQi+4WXvO91cIWgAKkHiRwBggI6TYieqXAgkyEjrxwUSxMaS7dBPxNYjPAXImS//fSbeSq4F2gZg7TPy1ulqBj5ZTPYDdQhw6XdAxkz57+kAaqW8811eQigWFwyB2cLh5s934hjtBgvl97W2almvs01QTrgJRdc2Aj/cSM6BZueBjF7DyXn1tOHxuLAoBRwH3PvNXqHY6wjSPBBn3yPNBdla2mRV3HaHsiaaB8JP4Oh+2XQc0DaBYRihe96VJRbHcfh5TzXmvLgWr6w8htp2HZ7+/bBPbCk2lzSh22hGYngAhieKhaKsuFBcPJ5MqB/6YT8+2VwGAHhs0QjZ+5unmOQB2cRxHNYcqccFb2/G1OdWC5kPciHkgcSHOg5ctVjErDF3JIgmlORhAcgM1qO6tRu/8F7TrV0G1LUTK4JsJ0oJ2gla2gNLLJPZgm92VOLzrUSReP00x2q2rLgQZMQEw2jmhC7VpfusrbAoaKF23THn51+d0SwUKnxi62EDBcugKI0UBL21xKrkLVEGSyg6RXigCmvvn4UvrpvYu28k2GE5UIL47bBcYmpWDDJjg9GpN+HLbRXYUkq+L1f5XSzL4MULCnDV5HR8dcNErLh7Oq6aMhRhASoEa5R46hwyrvlw0wkhD4xaVPUmCRIdooGSZWDhgIZO5/Yq+6sJCTKyt/JAFGr36jxbUCUIw/p2bE0RkQqAIbbLHqqjRiWFIypYjUiaBxIQQeoM7nDaE6Tbv2ITcPAH8pjJAOz7mtwvvFxcNpkoQVC9Axn8eKS0UYs1fCD7lKxoBKhcuzZMkFgTepOP5gmO1XeivKkLaiXrkjB0hqy4UCwpTALHkfGLJ+M2X4EqWeaPSMADC/IwIycWOqMFN3yyA1v5RqK06CDfENiCHZZEVR5unQuSEB6Ab2+ahMLUCLR1G3HZe1vx676TAhFxx5wsOxUIxbwRCThteDzMFg7fO8g9c4c/D9Txr0OOvRv48ckve066tKMSMkE8JIrSY4Jx+6wsAMDra46jy2DGlKxoPLZohLDMwpEJULAM9le3+aQBpa+hM5qFOcBoJw1cC3hLrE0ljT5RGvvR9/D47LBu3TosWrQIQ4YMAcMw+Omnn9yus3btWowZMwYajQZZWVn46KOPvNhUPxyipRwAR4rUwS4kngMJtLjfcNjq4QCVAjNyYvHomcPxTz681udo4kkQR6HoFII01/OuFJ+gr5Qg1Ms+Mh24biUw/OzefT93YBiSOXPzZuCMl0hOx7E/gdK1vn8vbSOwh+/4mXy79XMjzwXAAOUbRZlsb4HjxHBoV0oQVaBoM1R3oHe3qa+w7GEywIwcSiYkIbFA2hTy3OFf7Jev2gEYOkgXZcJo8fH8i4DoLDJ5MhPvcp9mgtjaYcXk+O61ewuaUHF/8dQSi+5f1IKNgpIgNXuJ9RjF9vfJ7dgrPbPvU6qBhf8h97e96347O+qAj84kGT6BkcCVvwBDp8l/vx6CYRg8e24+itIi0aEz4eqPtqOxUy9aj1Vucf0CAJq1BhytIxOGca7yQI6tAN6cBOz7Cij+FajZ44NPIEH5JuDJeGDjqw6ffnTRcKREBaK6tRtPLD3k9GVoUcoVoTMsIQwRQSpoDWahy1XWJvIkSBoNRZee96q2AxAL487C0fdWtuK8tzfjzq/24GSbDkkRgRibFgmThcOD3+/z2iKIgsrkZ+fF2ZEBd83NQahGiRONWpgsHE4bHu9VQUIuhBD6Eue5IBYLh2UHarDo9Q24+sPt2FbWjKqWboeB5K5Q7C4UXd8O0K5caRexIzCMcE69O4cQC2/9VQKLhROOlaSIQCGc1BaZcWT/8CYc3WLh8Mvek5j38jo88N0+dOpNGJ0SgdkubFhpZ+2KQ3WobO7C7opWsAzJEJGCFmo3lzRBb3LsBV7e1AULB4QGKAXfcV9jXA9zQYRQ9KjeKxCfKqiVrO/V5rbockSC+IPR5YBhGFw1OR0A8NKKo+g2mhEbqsGwRNeWcJMyo/H4WSMwMSPa7rw8MzdOKPA++B3x6acWVTS3ozegYBnE89kzVHniCJQE6bU8kOA4z10cKJEdmiiPYPAUqgCx895DBwaWZXDnnGxMiOevN67yQKQITwam3UPuL/8XGdMe/YMQk6GJYqMVQMbCrBLQNmBsBBmXlNR3Yi1Pgsx0YYVFMTIpHEFqBVq7jDha750qTy6oXeOUzGiEaLz7vR45YxgiglQoru1wq5yta9f5tBBuNFuEsdUCvtj+2sWFyIgJxsk2HR76gcwVfNI4YDYCHbylk5QECeObcCU1gIggNT6/bgJm5MSi22jGbV/sRmuXERmxwThrtGuFFM0KWVXsWROjzijags3j7ThHp0RgwtAomCwcPtpY5nA9o9kiZB1508Bww4wM4fvNiAnGm5eMtSKcokM0mJpFrmkDUQ1yuKYdRjOH6GC1kIFji8zYEOTEh8Bo5rC62G+JNRDhcRVZq9Vi9OjReOONN2Qtf+LECZxxxhmYNWsW9uzZg7vuugvXXXcd/vzzT4831g8HoLkUUUO9s5/qj6Ad7/XF8tfpbiGh3R8vAvZ8QfzBvQENXXalBOlBV0qPYTIATbxvZG8rQWb/Ezjt/4Dr14h2S/0BCiUw7lqg6Bry/5qnfE9GbX+f5B4kFoiFd4rwJCBtMrnf22qQ9mpSMGKVpJDvCnESS6yBjqN/Ans+A8AAi98iOUOASMQ5ssSieSCZs6zVSgolMPMh8f+ACMcB895CqgQJTxW3tb9jSCG5LV3j2XqUjLAlQcJTiBWCxQRU7ySP1ewDqrYR/+TCKzzfxsxZ5DfnLMDv9zs/zlvKgQ/mA/UHgZAE4Oo/BIuCvkSASoF3ryhCWnQQqlq6cf0nO6BL5s8Vtfvd5ghtKiEFsey4EEQ7Knoau8n38Pl5gFYyWare5auPQLDxNWI9SK0fbBCiUeKlCwrAMMSKxJEcnOSBkM/rKKSWgmUZTMqgBXr5qqQTjaT4mh4dRPaLWgkJwufSZDkhQdp1Rjzw3V6c/cZG7CxvQZBagfvm5WDVvTPw1qVjEBqgxL6qNnyw0XtbLI7jhFD0ucPsu2NjQjS4he+mUytZPHpG715jC1MjoFGyaOzU2xECBpMFP+2uxvxX1uGmz3bhQHU7AlUKwapslYcTPNmh6MoAUuByh7yFAICZ3HaEBihxvL4Tyw/ViXkgLnIwxHB0+WNCjuOw/GAtFr62Hnd8uRuljVpEBqnw8MI8fHX9RJeFcUqCrC6ux0+7SZfoxIxoxIVaf85hiaGIDdWg22jGzjLHliLScFeHihofYFy6SIK4C2l3hEovLDX84GGx+IPRe4glY5IRqlFCZySE9fTs2B4fK4+eORzRwWocq+/EE0sPwmThoGAZu2PY16CZI866t01mCw7xoeijkiJ8++aCStqLBqGkIhIoPsM761FZEBwYyjxe9crJ6Xh6Hk9Ce9IsOvl2Mq5trwI2vSbauo6+2LqhRxXIq6uBIhVppNxd2SpYIs10EYouvISCxVhelbe1tHePe6qimMfb+XiD6BANHl5IahAvrzzqVC26vawZs19Yi7kv/YVf9/mmGL6ltAntOhNiQtQYwwffhweq8O4VRVbnAp+QIO3VADjSdCk9R9soQSiC1Eq8d2WRlfXVnXOy3VrXTcuOgUrB4ESj1qOxyvpjjeg2mjEkPAAjk8SGkht4i7AvtlY4VGtXt3TDwgEaJetV5pVGqcCbl47BJRNS8dHV4xEeZN+Echavfv1l70mvxhanEjQPZHRKhMvryQIfW2J9t7MKX2+vcL+gHz6BxyTI6aefjieffBLnnHOOrOXffvttDB06FC+++CKGDRuG2267Deeddx5efvllp+vo9Xq0t7db/fnhBC38JJ2qEwYDaMe7J8Xc/d8RG5YT64CfbgZeyAF+vJn8b+G7OY06Uiyr3A4cXkqKpiaD9etQJYirgrO0K6U3wtFP7gbemQEcW2n/XNNxUmTUhPWO96oU0ZnAlDvt7X76C6beTeTKVduBY8t997rGbtJ5DpBBsKML4Cg+IH3/d45f49hKYNW/ex7gTonAqEzSGe8K1J6oboCTIF3NwC93kPuTbgXSJonPDTsLAEN+c1sVjkCCzIYdRiwRSSJfy/VVgYCKLwANBCssiuFnkdv934vnSHfobOAny4y9Eo1hgJQJ5D7NBdnBq0CGLRJtoTzF/KfJ91uxWbQioLBYyMT03ZnkWhiRBlyzrPcJYheIClbjg6vGITxQhd0Vrbjvj1pw9JpWtt7lumuPkI6uGY4UATX7yHWBnpvG30jOzwC5ZvgKHXXi+bTxCPnNHWBcehRumkGaBR7+cT/qO6y7V0satGjsNECjZDE6xXXXKi22/7qvBq1dBpfLUlgpQdoqAb3kXFu5DQCQFWtvh7W5pAmnv7Ie3+wg548lhUlYfe9M3DY7GwEqBeLCAgRC4sXlR1HmJrjaGQ7VtKOmTYcAFSuoMGxxzdR03Dg9Ay9fUIBUX3hXu4BGqRCKLNQSq7q1Gy/8eQSTn12Nu77eg2P1nQjVKHH77Cxs/MdsvHZxIRgGOFDd7jawVwrBDsttKLrMbua8MwAAqtJVuHoCmXS+ufY4jtSSuUGOg1B0CkqCVNY3yzrPWSwc7vhqD274dCeKazsQGqDEvaflYP2Ds3HD9EwEql2r2QpTIxEdrEaHzoS3/iLjSVsrLIB0sU/LJgW5v5zkgvg03NUJ8pPDoVayaOw0uA1pdwRqqTHYMkH6BLpWgONVQFbB6LwK0K8EcYtgjRIXjBM7tKfn9NwRITJYjcfPIkXtL7cRK5yEsADfZnA4QGKE63D0kgYtuo1mBKsVyIjxcbNNT6xilWrg/A+J2re3IHVg8Aa0YVGuEgQgY/t5/yb3N7wMHOfn5AWX2i/Lh6PnGEmWzLqjDbBwpKElWea5kVpibevFXJDGTj32VrWBYaxzyrzB+WOTMWFoFHRGMSRbis0lTbji/W3QGsywcMCdX+3BnwfdF4vdFcxpwfm04QlWx2RWXIgwZgF8dN0UrLCSrJvraP3Fgc2tSsHi5QsK8M8zhuGO2Vk4M9/++m+L0ACV0Cy0yoOgbSmhJS3Wz8qNQ1ZcCDr0JnzFn8OkkOaBeEsa58SH4ulzRjkdu84bEQ+NkkVpgxYHTw6sOi5VpbtT3M3nLbH+OtqALkPPbIlr2rpx37d78eD3+/HtDvvfzA/fo9fN/Tdv3oy5c+daPTZ//nxs3rzZyRrAM888g/DwcOEvJSXF6bJ/e/TXUPSegBawGo8CFsc2AXagneGZs4nNi1EL7P2CKENeyAaeTQWeigdezQfenwt8fRnw6TnAC1mELDmyjEw4OvhOBWoV4wy9GY6+4wNib/LTTfaBwNI8kMGi/PEWofHA+OvJfV+qQfZ+RSwKwlOA4YsdLzN8MVFn1O4DGsQARVgswNpngc/PBda/AHxyds8mstQSzlUeCIUQjn7Q+/c71TB0AT/dQkKko7OJGkmK0HhRhXNIYonV1Qyc5LvhM2bZvy7LAnMfB8CQfBlfg3ZuDiQSJHs+IVPbq+xzPJyhjleBRGUAGgcTjFSesKrYTAqd+74h/4+TGYjuCOHJwHQ+JH35o2IBte4Q8NFC4OdbScdswihCgPSDa2FmbAjevmwsVAoGv+6rwS4Fb4l14i+n61gsYo7ALFu7naN/Av+bTUiJkHjg0u+Bhc8DqfyxQPd9X2Df12JhDiC2f05w99wcDEsMQ7PWgLkv/oWiJ1ci//E/MezRZZj/CsnnIQoE14XjucPjEaRWoLi2A2e8tkHownKFcj6QOT0mSFSBaPgJS/VOwGxEdjzNg+hEt8GMp347hEve24Lq1m6kRgXhu5sm4aULC5BgE959flEypmRFQ2+y4MHv93nl0b3qMFGBTM2KdeoHrlEq8NDCYXZWSb0FSjb9sKsa1328A9OeW43X1xxHY6cesaEa3DcvBxsfmo175+UiKliNmBANCvhQSLlqkHadEdW8zUKuM3Kilc90CpZZhEksBEKHAIZOXJtUhQAVi31VbVi6l9hU0KBWARwHNB4D9nyBsfv/D7+rH8LS9gvAvTnJbX7Oq6uOYenek1ArWNw6KxPrH5iF2+dky7YNUbCMUFyi4awLnHTcUrLTHQnSG3kgFBqlAgW85/UOJ4oUZ+A4DpUtfiWI16AqEE24dZOLPxjdI1wxKQ0sA6gUDKa5yAPxBGfmJ1op+HrTCouCKkGc2WHt44N6RySF+96mTcufg3xpFetLRKWTW28bDwUSxMOmvuGLiRuASUcUyamTgBgHTZK88jiuw9qO2G4s5wJiOLpzy8qeooRvCEmJDOqxsolhGDy9ZBTUChZrjzTgt/01wnPrjzXg6o+2odtoxrTsGJxTmASzhcNtX+xyah10srUbN366A2OfXOmUCLJYOMHOa/4Ie8JuVl4cXjhvNBaMSOiR0kUAbbYLt6lDhvN2WO32JAhAFM7XTcvAPfNyZZOnc/h9ZeVheZZYJokt2Dyb74JlGVw/jcyFPth4Qsht4TgOh2va8cMu8rl8EhzvBKEBKmEsNNAssfa4CUWnGJ4YhpSoQOiMFqxzMo6Ti/WSfLh//nQAB6p72ETrh1v0OglSW1uL+HjrgzM+Ph7t7e3o7nYs+XzooYfQ1tYm/FVW+hkxpxiMSpDIdGKTYNLJG/B01ouFmjNfBm7fBVyzHBhzJSnydTWKhTOFhljWJBWRYpKujZAlX14IvMSTL4GR7gdKPZDmukXVDnKrbSDFfSmEPJBT1+ncrzDlLhKAXLOXeOP7Ars+JrcTbnLubxsUBWTOIfcP8GoQfSfw7RViiLMqiHRof7zIaTe1W1AliKs8EAramd9wRD552J/QfAJ4fx7x3WWVxAZL5cCL05El1ol1ZIISmyfKlG2RMx+4fSc5R/ga9HwRK4Os6i9QBfDKGgD7v5G3jmCFNdLx8zQXpHIbsSU0dpHvxNZSzlNMuo2o87T1wIrHgBX/At6ZRsgWVRBw2r+JbV+Y+46rvsKkzGg8s4SQH29X8PvkiXVOlz9U046GDj2C1AoU2eaBrHsBsBiB7HnAzZuAbL6xhFqaNRzx3gJSCo4Ts5Co9L98k9PF1UoWr1xYgAAVi3adCY2derTrTOg2mmG2cGAY0evYFRLDA/HtTZOQFh2E6tZunPf2Jny6ucxpIUBnNAthtenRweJ+mXs6UReYuoHa/UiODIJayUJvsmD+K+vwv/UnwHHAxeNT8Med01CU7vg6zzAMnjknH4EqBbaeaMZX2z0fg64SrLD6T1GJKlL2VLZi5eE6WDhgUkY03rhkDDb9YzZum52NMJtsDVoIXCVzYn6UV4Ekhgc4tEgAINiVCYGy7sCy5LcFEF6+HBeNSwUAIYzSSgmy92vg+aHA60XATzcjeP8nGM6WQ8FwYBqLXTYJ/LG/Bq+uInajT54zEvfPz0NEkBsFpgOcNlwsvkzLjkFksOPXmJoVA4YhGSr17faFT2qH1ZtKEADC+Wabh7kgDZ166IwWMEzvhkYPWtDCs61FDx1PmLqJMtkPl0iLDsbH14zHR1ePR5STY81TMAyDJxePRChPfiaG9/7+TUmQ2nbHvzktio3ydSg60DMlSF+Azrm9bTykhKInShCANBsueJaEvgOOVSCAcC0LaNiPAIWoOJRjhUWRnxzOW1YaUNLgnQLVHSp8bF+YGRuCW2YRRfATSw+hrduINUfqce3HO6AzWjA7Lw7/u6II/zkvH2fmJ8Jo5nDTZ7uw/pg4JzaZLXhvfSnmvvQX/jxYh2atAQ/9sA8Gk71yc3dlK+o79AjVKDE507Hq69yxyXj78rFe551YoY0f+0XYkCCCEsR3uaBz+LHWzvIWWYroHeUtaOkyIiJIhfEOxrKLC5MQG6pBTZsOL684isd/OYipz63B6a+ux097CCkxLNFNJlsPQS2xlu496VUz0alAW7cRpfzx5ywUnYJhGJ9ZYm3gSZBAlQJ6kwU3f74TbV3+wPXeRK+TIN5Ao9EgLCzM6s8PJ6BF+MhT3/3qM7AKMVyYFv1d4fBSUgAdUkgIFIYBUicAZ70G3HcUuHYFcOs24MEy4J91wN37getXAfccJt7x428kQWcmfhIqp+DcU2muM+jarD/z9veAk3vE//sqFH2gIDgamHgzub/mafm2Ps7QVEKIC0YB5F/oelnBEutbchx+MJ/siwo1cPYbwPWryYSi7gDpWG+vcflyDuGJEiRyKCkIm3Rits1AwbGVxNKobj+xhbj8JyBlnONlhy0it5VbgHa+u4RaYTlSgUgRndk7mR2FlwOJownRMpCQfz65PfiTvTWgI9CO+/hRjp+PHwGoQ0lA/dpnyWNF1/ZctaZUA6c/T+7v/JAEdltMQN6Z5Nw+5Q5A4aTgegpx3thk3DA9A1stw2AGS+wMHcjnAQghmlOyYqyVE62VJFcFDLDoNeuCWWg8PxnjCBHcU5zcBTQUkyaE2Y+Sx1woQQCSx7D2vln45bYp+OPOaVh5zwysf2AWtjw0B3v+NQ8X8gVrdxgxJBxLb5+KBSMSYDRzePTng7jjqz3Q6u0796tausBxQKhGSYpeVKGUMApIHs8vtB0KlhEKyBXNXYgOVuN/VxThmSX5CHYzQU6NDsJ984my65nfDzv1aXeE+g6doGZxFaLd18hPjkBeQihCA5S4eko6Vt4zA1/eMBFn5CdahVpKQTv5Nh5vRLfBPblOQ9FdWVShgidBqH2eHPCWWCj+HddPS4eS765kGQlJYNIDKx4lGXHKANK1O/l2PBn8MLZa+Gsob5Vmi8M17bjnG3IMXT0lHRcUea9An5oVgwAV+T7PKnBOzEaHaDByCClorpN0AeqMZjz60wHBQsKposZH8DYcvbKZHBNDwgOhVvbL6WT/hkCC2BRKNWGkEQTwq0FkYlp2LKZk9dwKS4qE8AD8e/FIBKoUfXIed6sE6a1QdKBnmSB9AaHx0FsShD+/BnmxjyTmAwueI1kgdN5ni+hsQBMGxtSN6eHkuA7RKFGUJl95olEqUJgaAQBCnpqvUdlCztkpUb4j9W6emYmM2GA0dOhxwyc7cOMnO2EwWTBveDzevmwsAlQKKBUsXr6wAPNHxMNgsuD6T3ZgS2kT9lW14uw3NuLJ3w6jy2BGURqxkyxp0OLjTWV270XttGYPi+uba04rn89gpwThSRBdK2DwDWGVEhWE3PhQmC2cYI3rCssPkmN2Tl48lA7GbxqlAldNTgcAvLm2BB9tKkN1azc0ShZzh8XhuXNH4bbZbrJGe4iZuXEI1ShR06bDjnLPlKanCvt5K6zUqCBZpPoC3hJr1eF6h8SdHFgsHDYeJ+eoVy4qQEpUICqbu3HX17sHDHk0ENHrZ5CEhATU1VlL3+rq6hAWFobAQH/nUI9gsVgHow8mUKVDgwwShHaEO7IuUgUCKeOJTU1gpHUxjlUQa52FzwN3HyLqkdmPAme84P496fftayVI9S4AHPG2H3kuIXd+u1cs7kvtsPwgmHQrsROoPwQc/KFnr3WAXz9jBhDipoMndyHJJGkuBd6aSsiO4Djgqt+AwsvIb3T1H6RI2XgU+PB0cUAlBxxHOrwBecQcy4pKhLoDrpftL7BYgL/+Q4Keda1EUn7jOmDoNOfrhA0Ri2eHfyXfUwkf7u0oD6QvMOEGst39dQLpDOnTSJC4rhU4vsL98nS/sg1Fp2AVInmlawVUwcBoN2SiXGTNEVVA4anAxV8BF31u36HVz3DdtKHoZIKx35JOHnBiibWGn/TYdQ4e/JHcpk0BwhzYJlE1iC8ssWgQ+rBFQuc96g66LcQlhAcgPzkCwxLDkBUXgpSoICSEByA80DNiKixAhbcuG4N/njEMSpbB0r0ncdbrG4QwWIoyPhQ9LYb3M66V7Jf03MCrDYr4HIy5w+Lx593TheBqObhqcjoKUiLQoTfhkR8PoFkrL69kDa8CyU8OR1yYD21U9J09KoqqFCz+uHMa9v5rHh5bNEKWzVJufCiSIgKhN1mw4bj74Hq3oehGHbH7BMjYTC7Sp5HisLYeSZ0HBYVRekywaDd28EdSzAtNBB4sJ/Z4855EXfI8bDITj39Ubbd76WatAdd/sgPdRjOmZsXgkYU9G18FqhV4fNEIXFCUjNNHurY6oxkG1ErheH0HFr+xEZ9uIZZhd8zJ7vW8mLFpkWAYYjHnSJHiDDQM15cFtQGL6p3Ani89W4cWZm2VIAwjscTqnWKoH/KwuDAJB56Yj8UyFI09BVWbOMoEsQ5F7w0ShFf69dcxLG087KjxTh3lTSaIFBNuAM5527E6HSDzL34sNi2IzPOmZEV7XKifMJRsX2/lgojnbJnXlNYKp40DFBqlAk+fQ+YEW080w2C24IxRiXjj0jFWn1+lYPHfi8dgdl4cdEYLrvxgGxa/sREHT7YjLECJZ5aMwjc3TsKDC8g89tVVx6yuRxzHCSTIfE+trjiONGbRMa5cOLPDCggnDV+A2IznA9Cmk5VuckGk34WtFZYUl01IQ1p0EGJC1LiwKAX/u6IIe/41D+9dOQ4Xjkt1a1XbUwSoFEJuxi97HTeAycXq4jpc/v5Wp/ahclDbpsNTvx1CBW+n6wh7ZVphURSmRCI2VIMOvQmbStyPkR3hcG07mrQGBKkVmJUbh7cuHQuNksWaIw14fc1xr17TD/fodRJk0qRJWLVqldVjK1aswKRJk5ys4YdsdNaSrm9GYX+CHuigRX5qB+QM2kYxbJYWyLwByxL1yPT7SDezO/RWJgidoKeMB+Y9RS6y1TuA3Z+SbgNKuviVICICI0mAOUAGOW48v13iwPfkdqSTbh8pNCFA3kJy39ABJBYAN6y1LuxEZwJX/05IrZYTwIcL5as02ioBQyfAqsjryAHNBRkI4ej6TpLNs+ZJABww9ipCGjmzs5JCaonVXAq0VZDvKb2Htkt/N7AKQrYCRNHkCkadSMo5s8MCxFwQgChN5IYfy8E57wKXfAvcukUs0vdzxIUGYEpWDDZZ+O/MgSVWa5cBuytIl9TMXJsiBCV2R57j+A0EEqSH4ehGnWjtV3ApKYZEZwPgxKD7PgDDEC/lr26YiPgwDUoatDj7jQ14ffUxmHhf4zJpKLq+Q+wOTRglnn/5ifujZw7Hn3dNx/+uGIuYEI1H26JgGTx/Xj5UCgari+sx5t8rMOHplbj6w234z5/F+HXfSSH/QgpqHTUnz8fWIh8tBF4f1yMihGEYj/zkGYYRLL3kBHYeqaOh6E5IkJq9gNlAut/dZa9JoVQTOzgAKP4Vd87NxuiUCFzNdzqC44DNb5D7468ndn88MmODsYvLJv9QKy4eRrMFt3y+E1Ut3UiLDsLrlxQ67Kr0FBeNT8Xz5412mgdDMZ3PMNhwvBFfbavAov9uRHFtB2JC1Pj4mvG457ScHm+LO4QFqJDHh9hv9yAXxB+KzsNiAb66lOT4Ve2Uv57WCQkCiJZY3X4lyKmGQ09/k97nKp1EPnekvkMnXOsojtV3Qm+yIESjJBaQvkZ/t8MKiiIkOAC0lHu+fk9JEDngc0GmB5cjVKPEFZPSPX6JCRnkuN9a2twruSCVntphfXUpcTmodd1YNzEjGpdOIKrfswuG4NWLChyqS9VKFm9eOgbTsmOgN1lg4YDFBUOw6t6ZuHh8KliWwXljkzE6JQKdehOe/UOsARXXdqC8qQsaJSvkaclG/SFiVb30TjLWlQtndliAOFftBUusv442CDkejnCoph3Vrd0IULHCGMIRwoNU+Ov+Wdj+yFw8d14+Thsej0B17xIftqCWWL/tq3H5maygbRKuj1q9CQ//uB/XfLQD64814unfZDRHOwDNpPnf+hP492/OayR7eBX3aJmKO5ZlhHwaSkx5CmqFNWFoFNRKFiOTwvHkYjJnfHnlUcEpACCqkbJGLX7bV4PnlxV71LjihzU8Hul3dnZiz5492LNnDwDgxIkT2LNnDyoqCPP90EMP4YorrhCWv+mmm1BaWooHHngAxcXFePPNN/HNN9/g7rvv9s0n+DuDFuDDk/ulFUiPQDvf3dlhFf9K1BKJo/tWDUOluR0nPe/+cgVKgiSPI12/sx4i/698DCjfDIAjxQNHk6a/MybeRDrnmo5Z5xtYLMRObNN/SQeIq0Fl3SGiPFKoResNdxh/A1GDjL6YdJ06KuBHppPifnQWGVB9eg6ZQLkDJQCjs+Qf33E8gVc/AEiQZQ8CR34j3/ei14BFrwJKmUVKmmVRvhHYyx9/qRN7x+pqsINaYh35A9C1O1+uoZgEZgdEiH64jkBzQQBiheVLqAKAnHkD7ndeXJCEjRZybHKlf9mdh9Yda4SFA3LiQ5Ak9dYX7PlYYJgTkj9pDLmt7qESpPhXYscYlgwMnU4eo6SiG0us3kBRehR+u2Ma5g2Ph9HM4YXlR3HuW5twvL5TIEHSo4NEwjd0CCmUJI0l31dbJdBWDbWSRW5CKFGMeIGc+FC8cP5oIUCyrl2PNUca8MaaEtz2xW5MeXY15r70F5789RDWH2tAu84oBBzO8WUeiLaREAhdjX3+e9CJ+ariepfSfI7jBCWIUxKkkifUUiZ4bpNHmw6Kf0dyZBB+vnUKLqeFpvJNQO0+cj0ee7XVapmxIdhjyYIFDGkk6WyA2cKhRWvAE0sPYktpM4LVCvzviiKvMkB6gjFpkQjRKNGsNeAfP+wX1Ci/3znN80JPDzCezwXxxBLL44LaYEX9QdKhDgC1HtgSOrPDAvzh6P0dX18OvJJPrtE+QkywBioFAwsH1HdYzxGoRcvIpDDfh6JzXP9XgjAMEJlG7nvjwNAXJAifC5LWXYz9T8z3yp6tMCUSKgWD2nadQDL7Eh4R17o2ck3lLGKzqQs8uXgkVt07A69cWOCykSBApcC7lxfh4YV5+OK6CXjlokLEhopzP5Zl8H9njQDDAD/srsbOcnIOpAXmadmxbu1M7dDAz6ctRvlOCRznXAkCiPMgJ+Ho3qAgJQLRwWp06EzY7kIN9CdvhTU9O1YWqeHt+NcXmJwZjZgQNVq6jLLUxDDqgLcmA29MwL4jR3HGa+vxxVZSY2YZ0mhD89I8wUebygRLrrVH6h0quzmOE0iQAplKEACC4nfp3hrc+dVuPLH0IF5ffQyfby3HsgO1aNe5zvag38s0CaF1flEKLh6fCo4D7vp6Dx7/5SAueHsz8p9YjpkvrMWtX+zCm2tLhO31w3N4TILs2LEDhYWFKCwk3Yf33HMPCgsL8a9//QsAUFNTIxAiADB06FD89ttvWLFiBUaPHo0XX3wR7733HubPH2De6f0Rg9UKCxAzEJqOue7sP/gTue2JCsQbBEcD464n93+6iWR39BQcJyFB+MDQ8TcC8SOJx/Uvt5HH/FZY9tCEAlPuJPfXPgts+x9RGfwnA3h3BrD8n8DPtzi1ogEgdkFnnQYERsh739SJwMPVrmXSACFHrvqdWA+1lAE7PnD/2p7kgVBQFVOd8/DXfoGKrcDuz8j9S78Dxl7p2foRKUBSEQAO2PgaeexUWWENdCQWkI5/k44Uwp1BaoXlakCdMhHIWUDOj4n5Pt3UgYr5IxNwUJEHPacE03HSrnBCu3zsVSC8FdZQF/Z8iQXktuUEuU54CxqIXnAxUQgBQNpUcnsKSBAAiAnR4J3Lx+KlC0YjNECJvVVtOOO19YIXclp0sCQPhFfaaELINRPgs1R6jrMLkvDX/bNw4In5+O6mSfj32SNw8fhU5CeHg2VIgPV7G07g8ve3Ycz/rUC30YyEsACMGOLDPLsGsSOyL5U5AOlODVYr0NChx37el94R6tr1aOs2QsEyzq22qLWGJ1ZYFFmnEcVf0zGg4aj1c1veJLejLxK76HlkxoagA0E4zpGixR0vvIPMh39H4b9X4LMtFWAY4JWLCl3nmPQSVAoWk/nAegXL4IEFufjkmvGIC/WhjZoMeJMLUuGptcpgBc0kA9yr16WgShBHOQV+JUj/hcUMlK4lCvCdH/rsZVmWQTxvnyjNoDKaLVjBq/Dy3QT1egVDJ2DkC+7B/ZQEAXqWC6LlSZDg3leCoP4wUah6gUC1Qghj3lrq22NfZzQL5Jos4lo6j3RjiQWQQntmbIisgnugWoEbpmdishOiaHRKBC4YS4iHf/18EGYLJwRP0wwGj9B4TLxfLVOtp23ks2IZx41fghLEdySIgmWEecDKw/VOl1suWGF58V30MZQKFgtHEZLg2x2V7ldoOEycbroaceCzB1HW1IXE8AB8ft0ETOcbQ5Yd8CxjtaxRi//8Sa7NQWoFjGYOv+6ztzGrbdehoUMPBctgxBD5Lgbjh0YhLlSDTr0JP+85iQ83luGF5UfxyI8HcNNnO3Hr586b1HRGs2B/Ny3b+nh4/KzhGJ0cjtYuIz7aVIZtZc3o1JugVrLITw7HxeNThGuGH57DYxJk5syZ4DjO7u+jjz4CAHz00UdYu3at3Tq7d++GXq9HSUkJrrrqKh9suh/CQGAwhaJThKcSP3mzwbl9UFezaC3iKA+kt3H688AEPpT7t3tJWG9P0FQiBnrS4GGFEjjjRXKfdpr5rbAcY/z1ZADfWg78fh8JKe9uAdQhQBRvJ7X2WcdqEI6TWGEt8ex9WZnS0tB4YOY/yP11/3HddQ+Ik2k5eSAUlARpKSN2U/0RZhPw+73kfsFlJH/FG1Di08x3zPlJEO/AMMAoXg3iyhKrVhI+7QpKNXDJ1/Kylf4mCNEoMW14GnZZeGubE2uF5ywWDn+5ywNxdU4KihLHAN5aYrVVibk6BZeIj6dNJrc1e92fr3oJDMNgyZhkLL97OqbnxEJvsggT+fToYHG/pMQHYGeJ5SuEaJQoSo/C5ZPS8cySUfjltqnY/eg8vHHJGFxQlIz4MA1MvFJi/oh433bfWZEgm333ujKgUSqEDjVXlljFtWQfGRoT7NhrmuNEO6qUifbPu0NAmHi9kBK2zSeA4t/I/Qk32a2WERuMsAAldpiJJdZwk/hdhgeq8MRZIzzKivE17pybjXMKk/DNjZNwy8ws33d6y8C4dFJ0P1zTjk3HG1Fc246Trd3o0Bmd2rJUCSG7fhJEgJwcQwo5dlhdAyNM9m+Ftipx3Ln3K8DsusvXE9Bw9Bo+F6SmrRsXv7sFKw6R8+4s20YJX4CqQNQhpImgv4LaUHuqBDF2A0Y+vLo3lSChCURJC444EHgJwRLLx7kgVS2E6ArRKBERJMNdoGafZOUdPt0WOXhgQS7CApQ4eLIdzy8rRnFtBxSsaM/pEaiVLyBfNd3GN3SHJpB5jS3Cksltu+/ssACI9qPFdQ6vvRVNXcJ3MSevH5OWElxQlAKGAX7fXyucy5zBUC3udxeya3Bzng7L7pqOKVkxWMgrLn7fL992ymLh8MB3+6AzWjA5Mxr3zssFAHy/0/5321tJmnxy4kM9sg1TKVh8f/NkvHj+aDyycBhunpmJC4tScNrweChYBuuPNeJYnWNidEdZC/QmC+LDNHbNQxqlAm9fPhZLCpNw7dSheOmC0fjzruk4+MR8/HLbVDyzJF92dokf9uj1TBA/ehHUDosODAYTWJaEmQPOrX2KfyX2LPGj5Gcm+BIsCyx4Bph+P/l/xb+A1U+5tlxyBaoCSSywvuCmTiQe7RR+JYhjqIPJ7xEUQ+xcZv8TuHYF8GAZCStXaEjxqHSt/bond5GBtSqod7MGCi8n9lZdTcDm150vZ7GIBU1PlCDBMXwnF2ddNOtP2PE+KVwGhAOnPeH96ww/S7wfFA0k+FUHXmMUn4FTuhbocDJAlYZP++ExFhcMESyxLCWiIu3AyTY0aQ0IVitQlCbpYG84QtQ3rBLIO9P1i/fUEmvvlwA4Er4uzWkITyLjC87ic0LBUySGB+Ljq8fhmSWjEKxWIFClQG58qGS/lJIg1uHovYnwIBXOyE/E8+eNxpaH5uCPO6fhlQsLcP8CD87bciCdxNfsJRlhfQgxsNN5d6JbK6zmUmIBpFATC1NvQK0qj/wuPrbtXQAckDnH4fUyQKXAL7dNRcEkkilyZUo9dvxzLo49dTr2PjbPK+92X2LEkHC8fGEBxqZFnrJtiA8LQGpUECwccMl7W7HglfWY/OxqjHp8OTIf/h0XvL1ZyC0CAIPJgpNtlAT5GwejG7p4q1oe7ix8pZBlh+UPRu93aJIE1WobgKN/+uylaTh6TasOa4/U44zXNmBHeQtCNUq8dekYTMrshSJ+f7fCoqCuF55mcVJLOVYp5or0FoSxmAfZQDag4ehbT/j22K9sFklrWQ0atMEEIIRAh3d5B94iOkQjZGK9s440w04YGuWdZaVUCXJSLgniwgoL6BUlCABMy4mFWsGivKkLJQ3WzYwmswX/9ytR6IxPj0JkcN/ad3qLkUnhuH4amVs89MM+NHY6tgTnOA6bN5H5kRkMFAyHB9lPEB5A7M8oqXCoph1ljfLGwJ9sJgqKILUCz52bj7MLhkDJMthb1Ybj9dbEBA1FL0jxPMsyJSoI545NxvXTM/Dggjw8d14+/ndFkUBqfbrFcZbR+uNkHDA1K9bhcZkYHoiXLizAo2cOx5IxychNCHWYt+OH5/B/iwMZVAkyGO2wALHY76z4cuhncjuij62wpGAYUmyf+zj5f93zwJ+PeEeEUOuOlHH2z819QgwYpkG4fthj1HnAAyXAlUsJOZUynuRphCUCRbxPuCM1yH5eBZJ7eu/mDSiUwOxHyf1NrwOdDY6XW/8i6ShUBogFPbkQwtH7oSVWZz2w+klyf86/epZtE5kuWgFlzCKkpB/eITqT2ItxFjGIWwqOE22HpB33fsjG9JxYHFCTwq+5dB0hOgGs5VUgU7NjoFZK9uED/O+QOdvO3scOcsLRde3A8ZX2Ng0cB+z5gtyXku0UaTQXZIPrbegDMAyDi8enYsODs7H6vhkID2DFJol4CTlHlSA1+0gXaB9u37DEMCwuTEKIp57V7iAltS2mHhVZvMGsvDgwDAnkPOkgDB4QSZA8Z7ZSdCyXWGAVXO4RcvgmhartpCijawd2fUoem3iL09XSY4IxfPxcAEBgw17EBDD+iaQN7p+fi9HJ4UiPDkJ0sBoqBZmQWzhgW1kzznlzE+75eg/q2nU42doNjgMCVCxiQ2RmeQ1GlG8iqgAaKK1tEK133KHLH4w+ICElQQBg96c+e2mqBPlkSxmu+nA7mrUGjEwKw693TMXpvKWMz9HfQ9EpvFWCSPNAejsbgVpZV3uvnBiTFgkFy6CqpRvVTq613kDMA5FJWtvmG9FGzT7EZRPTkCdpqvDKCstiIRaaFI3H5CmbW3nrpvBkx8/3QiYIQJQ6VA0kbTrhOA6P/nwQKw/XQ6Nkcd/8XJ++b2/jntNykBsfisZOAx76Yb9Dlcv7G05A00TG9DX5t5GGmdK1AtEcGazGpAxCEv5xwD0pV96kxXPLSAPRQ6fnISUqCDEhGkF1/8Mu699urxCKHuHNR3SIyyemC+/Vqbe396eh6LZWWH70PvwzgIEMOhAYjHZYAJAxk9xueRPY/531c13NYkf/qbDCssXUu4GFvP3LljdIEdtTSEPRbRESS8K1L/jE+w7Kvzum3k1IhcotQOka8XGLpPA78tze347hZ5OipVFLbLFsUbIGWPMUuX/GS0SK6wn6czj68kcBfTv5/DbhtV5h2r0kEHn89T1/rb87XFlitVWSkERWKSr0/PAIKgWLtPxp6OQCoDK0CqTSGkd5IBzn2TlpCN996IoE+flW4LNzgRdygZ9uJd3LHEfyJZpLif2ko2wtSoKUnZpcEEeIDFaTjtnmE8TLXBlorQaNSCMFHYuxR7YU/QrUHpEqdcr71hIrJkSDQl52v6rYsRqk2G0oOq/MSfWQ2JciLJHPgwJRg+z5nHjzx+QCWXNcrxudBQRGEp/vuv2ul/0bYtHoIfj5tqlYe/8s7Hz0NBx98nQU/3sB/rp/Js4bSwpBP+yuxqwX1uI/f5LCQkqkzK7iwQpqhZUzH4hIJfflWGKZTWKHuj8YfWCBkiBUoXlsOdDumUe9M1AShHbtXzYxFd/dNJnkX/UWqBLE0X7YnyBkgpQJTSSyQMlGR9k7vgbNBfFWlQtSBB+ZRJoeXdlPUnAch90VLdA6KLBKUcmTILLyQEwGccyRMYt/gb5XAysVLB4/i8xpGQaYN9wLEqStglzzFWqeuOCAmj0y1uNJkAhnShCeHPGxEgQA5g4jhORqCQny+urj+HIbyTB79aLCU6oc9QYBKgVevrAAKgWDFYfq8K2NHdWm44145o/DGMYQxUTypPPFxpblj5B9EsDpo8g+4C4XxGLh8OD3+9BtNGNiRhQunZAmPLdkDPntftxdDQtvYWuxcNhXReywfGYxxXGYbN6O8VE6dOpN+Gm39b7S1KnHwZOEkJuSFQNUbj8l1nN/V/hJkIGMq5cBl3wDxGSf6i3pHYw6nw8f54AfbwSOrRCfO/IH6YaMG9F/Pv/460lOCADs+NAzNYhBK3buOyJBAJL30NcB8IMJoQli4V2qBqnYTPJWNOFA1tze3w6GEZVDOz6w7mpqPwl8fx0AjlhnFTrozHaH/qoEKdsI7PsKAENybuRmqbjC8LOAew8Tyzg/eoaRSwBGQTrMpcHdDUeAdTzBG5sHKP/GXb89xFljUrHVQhSOhuNr0aw1YA/feWSVB1J3AGg8Siz8che6f+HEfAAM6UhzZGfWViVmKBi1wJ7PgA8XAK8XAX8+RB4fcY5jP3CaC3JyF7F+6U8Q1EnDrc8nDCPJBel9S6xeR1czoOUnw2OuILd9nAsCAHP4ibmjwozJbMFx3rohL8GJ5YiQB9IDEgQQLbEO/QJseYvcn3iT+y5flhXHV5V939U60MAwDAJUCqRFB+OF80fj51unYExqBLoMZvy2nxQgZBXUBjMoCZI5W8xvk2OJ1d0MgAPAiISHFH4lSP8FJUFyTyfZRpyFt5TsObLiCIEcrFbgtYsL8eTiUQhQ+WCs7AoDRQkSnkzGqGY9CU6WC0okulPU+gKJBQDDkrFYD4ixxQVDAAD/XX3cLbnx3voTOOfNTXjmD9fnHUEJIuec3VBMmkgCwsVGnFNUnJ2YEY3XLi7Em5eMQUK4FwpSaoUVlSlR6shQ0rqzwwojvxEMHaRJzIeg9qM7ypvRojXgmx2VeHHFUQDAE2eN8E4R0w8wfEgY7jmNNNL939JDAjFX1dKF277cjXhLI8KZLnCsksw3p91LyNmm48RKG4QIYxlgb1WbkHPjCJ9vLceW0mYEqhR4/tzRVllrs/PiEBagRE2bDltKiVKstLETnXoTAlUKZMc5mAt5gyN/gP3qIrymJvbnn20pt1LAbCwh752XEIpYtgP46Azgw4V9bj33d4WfBBnIiM0h3UeqQerHyzCEVBh5HiE8vr6cdK0CohVWfyMFxlxJwuXaqzzrBKneRQbSYcnihdUP32PqXbwaZKs4eaWB6MMW9V2BN2Mm6a6xGIE1T5PHzEbg26tJ11LCKGChA5WIHNBw9LqDnhFxtPPH20wbVzAbSVg9AIy9UuyW8qP/ICROVN9texfY/AbwzgzgjfHAro/J41QV4IdXGJMaicMBRMnXcmAF1h9rAMeRATD1AgcgWmFln0bCoN1BEyoqdBypQXZ9Qq4vaVNJ80TBZST/qOm4uLwzwjUynXTPWUyiZWNfobuFNBQ4s7SieSCOLNqEXJBTm2XiE9A8kPBUkaiv2k66yfsQtDtxU0kTugzW713WpIXBZEGQWoFkR3Yb3a1icbjHJAjfgV26BmgtJ+qO/IvkrZs8gMixk7uJMrSfYHRKBL6/eTJevahA6FgfltjLHvv9Ge0nedUHAwydIVr4ysljo6HogZHEJtUWNMDZrwTpf6AkSHQWUHgZub/7M5+MnadkRePdy8di2V3TcdboPpoLDhQSRKESu/I9yQWR2mH1NjQhIhnaA0usSyekIS06CA0derzL52E4wsnWbrzEF8e3lro+V1S2kHGULOKa5oEk5IsNJSd3k7ncKcBZo4d4bwfXSL4fxOaIqmk59ZlWPhjdGQmiDgYCIsh9H6tBkiODkJcQCgsHPPX7YTz0A/k9bp6ZecozzHqKG6ZnYFx6JDr1Jtz7zV50GUy46bOdaNYasCCW2AMzMTmkHhMQBsx6hKy49lmgqxmxoRqMH0oIzWVOLLEqm7vwzB/kOvyP0/OQGm29zweoFDiTP79+z1ti7eFD0UclhUPpK6vU4t8AAAmtu5CqakVxbQd2lIvZahuOkc87LTuGKJvNevK3+zPfvL8fLuEnQfzo32BZYPFbQNZpgKkb+OIC4sFLC9gjFp/SzbODKoAQUwBw6Cf56wlWWEU+3yQ/JAhNAIquJffXPksGdPR3Grmkb7dl7mPkdt83pJi38nFi1aUJJ7Zn3pKbsXmkE6m7WZzcuENrBfC/WcCbE4DvrvZ5Vwu2vUvsuQKjgDmP+fa1/fAdqCXW1reBPx8mknFWCeQsAM59H5j/1CndvIEOhmEQNpwUscPrt2N98UkALqywRpwj/8Wd5YKYTYQEAYBx1wBpk4DFbwD3HQXO+i+QPo1kgaROcrbRklyQTfK3xxf46Rbg17uAlU84fr6OhqKPsn9OGo7eG8RuX4IWVWNzgbjhJNzV0Cl+frkwGYD3TgPem+tVVkpOfAiSIwNhMFmwnvcxBoik//f9tfwyoVYddwKqdwDgiKVJTwN4Y3OAaIkCeOzVgFqmIoEWdE6Bv7lHMJuAT88hf7Ue/s69CIZhcHZBElbdOwMfXj0Ot87KOtWbdOpACaqkMaTLnJIg9XJIEBeh6IDfDqu/wtgtZgVEZ5FrtCoYaC7xiTqPYRjMG5Egr1vfVxgoweiAd7kgfUmCAKLd4/J/el0cVytZPDA/DwDw7rpS1LfrHC73f0sPodtoBgCUNmqh4+/bguM4oes+JUrG3FIgQUaRa21AOKnBeDrm6A+gTSQxOWJwvSvrWAp3dliAaInl41wQQFSDfLezCmYLh3MKk/DAAMsBcQQFy+DF8wsQrFZgW1kzFr66Hgeq2xEVrMadI/nAdGlj05gryP+6VlK3AbCQJ8R+32+vtuI4YoPVZTBj/NAoXD4xzW4ZADh3DMl0+eNADboMJjEPxItQdIfgOJLDyOOeFEKef7q5XNhOmgcyNTsWOPyruO6ujz2z/PPDK/hJED/6P5RqUhROmUCKsx8vIh30sXn9059+2Fnk9vAv8osvrvJA/PAtptxJPOSrtgErHiMD5KAY0snXlxhSyBc5OeCbK4DNRC6JxW+Kvu/eQBUori/HEqtiC/DuLHFwe/BHogCQM0iUA20jsOYZcn/u430jSffDOww7EwjmJ8LJ40nO0b1HgUu+BkadRzrx/OgRJk+egSYuFAGcDvXFhFSwssI6uZtM8FVBxG5DLoRcEJsOt6PLiN1fUAyQt0h8XBNKJhdX/UrOOa6shKglVl/mglTtJJ1RAJkQOCoG0om6IyVI4mjiAd3VSDJPbGE2CR7D/R50Eh+bS2y/KMFDlbFyceB7ct2r2g6sf8njzWAYRlCDvLuuFHd8uRvTnl+NsU+uFLpRhw9xogyo8JEVFkUebxPHKoFx18lfL2ksaRJoqySd/P0V9YeIEgqcT4OXfYUgtRKzcuMQqO5lq57+jJJV5DZzNrmNJUVL1B9yP/Z3R4LQcZK+rc8VX364QPMJABwpCgdFk87/kXyzwq7+d5zKwkBRggCSXBAPlCBUdRXcR8HD0+8nZE1LGfDxmV5fZxaOSkBhagS6jWbh+irFmuJ6LDtYCwXLIFClgNnC4Xh9p8PXau0yCqHMyZFylCD7yG1CPmlGpTlcA9FGktphxeQQuzIw5Prf2eB8HX0nf/2FcyUIIIajU+ssH4LajwLA1KwYPHdu/qDJ30qNDsK/FhHr7rKmLihYBq9fUojwNn6smyAZ07MKsQFv+3tA7QHMH0HswHZVtKKmzbqh54ttFdhU0oQAFYvnz8133JQDosxPjw5Cl8GMPw/WYl9VKwAg31eh6HUHrWz75jJElf7HgRo0dOhR2qjFyTYd1AoW4xNVYlatMoA0ppau9s12+OEUfhLEj4EBdRApxMWNILYcQP8IRHeE7NNIkb2lTBxIuALHiSQI7VL0o/cQGg+M49UgW94gtyMWO7Yk6G3MfpR43DbzGQyTbyeF6J4ijs8FcReOvutT4KMzeQuufODCz4nlSssJ4P15wNZ3et5FvfkN4pmaOJrknPjRf6EJBW7ZDNx9ELhuBck5Cu6j7rm/CbLiw3BYQyyxCoz7EKpRWgccUnu+nPlEbi8XSRKZv/SY3fkhuS28jDQUeIP0qeS2ajtgdNyR6HOseVK8b+wCtr9v/XxXs9h9Ry0ApVBq+Akv7Lv+S/8CXh4BvD7WMUHS3yAoQfgiK81AqvBAmcNxItEOABtfARqPe7wptDtxZ3kLftl7UgjwzYoLwYVFKbhlZqbjFYU8EB+NcQovJ1YUE24CwpPkr6cJIeNIoH9bpUmtVPZ9DZj0p25b/LCHxSIqQTLnkNuYHAAMUeFqXRTYALE73VlhltqsAGIxzo9TD8EKK1tsHCjkc5oO/QTo2k/JZvUIdF8dCEqQKJ4E6a92WACxtL7yVyAilYwvPl7kVT4IwzB4ZCFRl32zoxJHajuE53RGMx77hTS5XTt1qNC9frjG8f5H80DiQjXuM2Y4zloJAgwcBaUjUDusmBxirxSTQ/63bRiSgpIamnDXlrR07NELSpCC5AjMyYvDtOwYvHXZGKiVg6tke0FRCs7gFR2PLByGyZkxzi1uM2YCOacDnBl4ZxrifzwfD8ZuRRg6rSyxqlq68PRvxHb1gfl5SI9xPodiGEYISP9yayUO8cdOga9C0Y/zOca8PV7Iyc2YlqyA0czh6+0VggqkKD0SgeWrALOB5NaMuZKst/Mj32yHH04xuI4oPwY3AiOBy38gnSAKtWjd0t+gDgayed9uml3iCq3lZBDKqkgh2o/eB1WDUNDgt75GdCbJyACIHY2vrKKEXBAnJIjZBCx7GPjlNqKqGn42cM0yQsDctI54rpsNwB8PAF9fRjqZtE1ENt9+ktgBtFW7J0i6W4Bt/yP3ZzxIOor86N8IjhEl3n70DnjV2RTFAUzNjoFKwZJj5eQe4OBPZJkRHtrzxY8kXfFdjeIErqUMOM53K9PzjDeIziIKIbPe9cTRV6CWl6wSmP1P8ti2d6wtnKhyLSLN+STVNhzdYgbWPgd8cjbp0GqtAD4+u1e6+HwKQQlCSRDeuqxii3ySunQN+c5UwcQCzWwAfr/XY5J7UkY0LhqXgjl5cbj3tBx8du0E7Ht8HlbeMwPPnZfvuMvUbBKDSCmB01PEZAP/KPfOom8gFHSqJMGt3S1A8a/Ol/Wj71G7l5Ad6lDRxlYdJNr1uAtHF5QgTkgQhVIkQvzh6P0HTXxXebTEBi5lPCFFjF2ileVAgcUiscMaCEqQdHL7/+yddXgU596G71mJbNwdAgnuUtxdW9rSlrbUaKl7eyrfaXtO3fXUqbsrBQoFinsIHjQh7i7r8/3xZncT4iEQoO99XXvtZmd29t3N7Mw7P3me+uSwbFahpb/s/+C7a4Ts4ys9hSoDnL4kCAgJpWsWiy6CgiMiEdIKs+PBsYFM6xWOXaWW8fk7fx8ltbCScF8P7prYhe7hYg6UVCNRUpO0agPpZvmBFKWAqVTEWRxqGw6VitPtC3eyVBaKOTGIOQPUKBhqxBy9OVJYUKMTpO2TIBqNwofXnsfn1w/Fx+Pc68JXFNH9sfnhiSwY1QnMFa6ipPokbme+BB1GCH/D5LXcUvY6291voc/am2D/b6h2Ow//tIcKs43zYgO4dkRsk2O4cID4/21NKcRiUwn0cqvf0641OK69Bi8QhTeqjbtiRMHrV1tSWXNIzAFGdQl2SWH1mAWDrxOPk5ZIg/RTjIxISc4ufMLhlg1w504IPoO1iB1dKvt/bTrI4GgvjegrPEUkpx7vUFc3iG8UxLRRYKY1TH1G+N5c/k3byQ05O0HqkcMyV8DXl7m6YMY9DHM/cVWdewbAZV/A9BfEJDhpMbzSA17sDC91EY9f6w2v9nSZnTfElvdEF0hYb1HFIZFI6DFCdHsNVA7zTO5t8FwHeD4W3h8Lpeng5i06CluC3sP1u3ckKnZ8CqhCruVkJPYU5fRJYqkqrKoObA+4CkbeLQIJFXmw62vXeo6KsfoulhzUNEcvz4MvLoa/nwFU4YMSGAclqfDp+VDWTP+k042xBMqq5TRCqisYowaKoonynObLgmz8n7gfeDWc/4ZouT/2t6vzqJnotBqeu7gvH157HndM7MKoLsH4NnWBnrtPeJi4+7oSOe2JMzl2Bgd0HJ0gjsKYs1Vq51zF4UvYaUzteVtzzdGbksMClySW9AU5cyio7tqumQRRFBhY3eV8thnaGotFIRQ0vi+eKTQmh/Xn/8Gvt4lrm/2/iCR3aYYImnqFnH6lhYCOQm7UN1okzz6d7Uo4NYXV5OzqfXB6d3Qahb8P5rH+cD7J+RW8s0bsh4/N7omXu46eEY4kSOOdIM3ymnF0gYT2cB3bogaJ+6KUxmWkzjQcXSB+Ma5r3OaYozuSII1JYUENT5AzvJDmDEVRFML9quNeOfsBVRRc1deV5hcNC5bCXbtg4mNYgnvgptgYbNoC311Fwg/Ps+5wPu46DS/M7degDFZNYgINTpN1gH7Rfm0jOWYqc3lExU90KnwMqNhAoJcbmSVGViWJY8GYTr5wuLprpMf54ncXM0x0vZxt55OzDJkEkZx9uHmd+ZXKXaaIAHLBkaYrwpx+IFIK67Qy5l9CImbmK+3boaD3hP5XgKd/223T0QmSd7C2nrTdBj8uFGZdOk+45FMY91Ddz68oMPQmuH45BJ/gu6PRgdZdPN72gQik1YexFDa/Ix6Pvk92gUgk1QR16EGhexR6xUZA6QER6AZxoR41GGa8KI4LLaWmObrV7JpAD7ru5AftNEc/ySRI0hJY/YxIxtZH8ho4vl4cY8b8S1yED79NLNv4pjiGQeOm6A4cQY+cffDeaNENoTfAnHeFD8o1vwn5v8KjojukouDkPtupIK/6It4nUujQg9g3HNWMzfEFyd4rgraKBobdLBJio+8Ty/78P9f+d6pwJBuiBwt95/bGUdWalXjyMlNWE+z9CcyVJz0sJ8ZSV/fPzGrvlmN/i84lyZmBUwprfO3nnb4gTXWCNMOnwGmOfgYel/6pOOWwTpD96ztPSNumb4PcJhJgDsrzWmbwfSpwVMP7RLZeLvN04ugEqSyoLT12bI3oFgXhETXtOeElesMquDcJ7jso5KlONwGxcO3votgu/5AouDDV79vhRFXhmytg0Xg48Budgr2YX23u/PSSAzz2617MVjujuwQzvbfwRuge4QPAgawy1HoKLx2ylc1Lgjj8QGrMrTz9Xce2M7mD8kScUlhdXM85zdETGi5SLXYkQZqINZ3CTpB/HDkOCbZ6PP5qEhALo+9Df/tm7gh4hy+sQo6yz76X6KWk8K+p3ejUiAzWiTgM0gH6tZUUVvJaId0f2FmcK7qLJIj22CquHOA65wcY9PQ07hTFoj4RrgTdoGvFvTRIP6XIqJREcirw8HXpBDtacRsivUaAQHL68PSHC96CbtPaeyRtT0AnEeyzGmtr3v/1Xzj4hwgwXv2L8EJpjMgBcNsWeCQPHiuC/5bAYwXwaK7LjPa3O+sPaG77QFSZBXURclsSiUSgKARe/5Mwnr/8G7h1M/xfJvzrCCxcKZKiraGmL8jBP6AiF7zDW2aw3hCx1UmQtK1gs7RuG4f+hG+vhDXPw2dz6lY4qyqsqvYCGXydS2/Z4f9QeBSS/hDPNWaK7sAnXMhloQpz+OBusHAV9L9cLPeLhmt+FRcfeQfgiwuhqrh1n+1U4fQDOSEZ7fQF2dT0NjZVd/31vMAVRBp5l+iEKc9xdd6cDGlb4Z1R1d1HJy5z+IG0Y8dlTQI7gyFYSIJl7Tq5bW14A364Dv64t23GBtWdXKoI2sWcJ7oNUGHnl233HpLWYyp3JR8dpugOmt0JUp0EMTSSBHF0gkg5rDMHp8lyl9rP+4RB1+priZ3N6Noqy4F3hsPbI5rfHXAqcMhvdp/ZfmNoCR6+LlkrRwLJWCo6QEAUfMx8GYbdIs530YPAN6J9k++BneGa38VcLO8A/NWE7HHiV6JQDUSCHbhzYhd83HUcyCpl3eF83LQanrigt7NqvWuYDxoFCivM5JXVTeynOTpBmiP14/QD6Vf7eUeM4mxKgjiKCRw+IFAtHasXibSGCguaK4dV0xPkZP0z/+k05AfSCL37D+UR6wJW2Abhplh53/AW153XSEdbwVH46/Fa//fpfSJwr/Zb6ddWpuiOzo74amn88D5iPmet4prQI047qRHxwWgOVkthdZ/pKhbtNUcUPUmD9FOKTIJIJKeKnueL+8Z8QSxVrgmHNEWXtBUaTY2KxGpJrITPYOMb4vEFbzVfm11RRIXYiZ0ck/4rWoWLj8PKJ2svM1e4THjH3H9mVP9KJGcSod2F8Xy36SJw1hIT9IZwdoIkuozEB17VNjJ7IT2EVJ6lonUXwdl74YcFQpoCRST/P55eu4Lu8AqxbZ0njKoRVHb3diVdN7wukjCOIGNTVWNdpoj7PpeKBIgjSOkgsDNc/ZsIRmbtgi8vabpS83Ryoim6A4cvyPEmkiClmbDne/F4xB2u53XuIlgEsG2R2GdOhr+fFZV8v98Jyx+tXb2W2sam6CeLorSdJNbB6qTc7u/arlMjvVoKK6o66OQwXk780tUJJWk/UtYLCSH/jnVlBh3Hl9wDjQfFmiOH5ewEkUmQM4LKQldCqj55SYck1rYPXQG9+lBV+PVWsQ9YKlxdRacbqxmSfhePe13YPmNoDSf6gvz5sAha+3eEKU+116gaJygOLnxXPN72gUtO70TKcsTncXB0FdgsBHq5cet4lwTbzePialW7e+i1zr8P1OML0iJPkKx6OkHApVZxNiVBnEnLGkkQvYdLLaEhXxCHT1xTcliOThCrUR6nT5bmdHefwPTeEYDCvyw3kq0GEmXLQLvswfpXTtsqfILWvyIUMarPz74eep6a05v5wzowuksjRQnNRVVdfiCOJIiiCKkrIDh9BVN6Cv+lKT2CRXc8OLtFANHt3a+6WGv7xyc/Jkm9yCSIRHKq6DZdSAfl7nediE8ka5domfMOa/pkK5G0hLBqf4Cc/aI1c/E94u+xD0HfS05+++4+MPs18XjLu7WDSTs+FVU2/h2h99yTfy+JRNI0oT2F14OpBFLWCfmjgSdhiF4TjcZV6brh9Za9tiwHvp4nfCE6jYGb1lR3XyTBh1OE5JOqwqrqZOqQhaKytiZDbxIdbBnbRYu4zSw8Jvw7Nv7e056F23fARe+LZEp9hHQVnXEe/iI546gqPRNoqBPE4XdScNhVVV4fW94TAduOI1263g7ixkPvi0ViavE9rQ+wFx2vHcjb+AZ8f42QiCrNFL4riubM6nZ1SGI5ulRaQ3mekJ4Dod/skH88WRxJEMf31WOWqAosSWtYflJy+nAEMOMnwon64UFdxL5uLBZdVg3hlMNqzBOkuuL9VHWC/PU4vNILdn1z5lUxVxWJpHljRWSnG4cfiG9U/UULXaaKoJe1Cr67quGuwm0fuCr9of1+08f+FlKI3uHNL4o6E6jpC3JwWbXspyKSDA2d488E4sbDeQvF419vr1+Gcsn94vmIfuL3byp1dp1dNzKWfjH+9I/x59ZxcXVe2r3aF+RAVm1fEJtdJaOomXJYFfkuD7ITC0wc58yMhNoyy2cyTjmsrrWfrymJdSKlma6ikMBOjW9f5+46hktfkNZjtwvZWmhRJ0iHIAP9Y/wpxoctA54X597EL0VRSk0OLBaePI5zadpmOLzcufiSwTE8NacPOm0zwuKqKvaRhsg/LOa8WneIHeV63pHkOLSMly/uxRfXD+X8gDSozBfXHjXXBZck1sGl0iD9FCGTIBLJqcIzADqNFY8bmsg7tbLPq3sxJZGcDKHVlS6Hl8O3V4lkW++5wgOkrYifBP2uAFQxqbeawGJ0BUlH3wtaXdu9n0QiaRitvnYVVfzkptv5W8Lo+4Xu+aFlkNbMakBLldC3LkkTZrKXfiYu8K9fLgKGpenw0VRY/bTQonbzFmboJ+Id6pKxWvFfcR/Wq+nzplYPwfFNrxfeB678QXy+/b+4qrPaG4ecw4mdIIZA0Z0DDfuCmMpcVWQ1u0BqMvUZkUzKTIAdraw42/kFoIr5zkWLhB/agd/g01ku+bKwXiJxfqbgSCKlb6sdAK4oEMHhH65v2ivlWHXix636c+34VARvTwZVdZmiOzpB9J6ikwmaJ7XzTyFrN3x/Hbw5pPk+DG2BIwlyohQWiCpjR5dAQ74gVrNIVEPjniCGAHF/KiqM07eLitjSdPj5JpFwONl9ty3Z9iHs/RGW/OvM6X4qqC5mO9EPxIFGI45/fjFChvaXW+sml3KTYPkj4rEjKJa8pn2SUPt+Fvc9Lzi7urUdnSAZCaLzEIRvWMcR7TakZjP5cZHEKc2AZQ/XXrb/V3He1OhEt378ZPF8dbDWQ6/l19tG8sttI/HQ1/1/9QgX56GkE5IgWSVVWO0qbloNYb4ejY/P4QcS2Lnu+Tqku5grWCqErNeZjsUolAqgbhLEaY6+s+7rVj4pEpkxwyCif9PvI31BTp7iFFEkpXWrKzXYBG9eMYB35w9k9vmXwJgHxJOL73Elrbcugm/ni26drtNgyI3i+ZVPts5vY/XT8EqPhotejlRLYXUcUTtZHjNEJMyMJXhnbWJUl2CUpGoprK7T6nbsS4P0U45MgkgkpxKHJFZDviBOU/TzTs94JP8cHJ0gWYmiKjH6PDGxbutk29SnwSsU8g/Cmhcg8QsozxYTw36t9DaQSCStwyGJBTB4QdtuOzjelYhY9WTj64K4wPjlVhHU9QyAK74T9yD0cRf8KS5Gqwph7Yvi+WG3gFdQ/dsbfgegCBNBaFHFWLOIOc+VLPjjvtrGq+2BqcylTX1iJwg07QuS8LkItgZ1EVXK9eETDhOqg3J/Pd54hVt92KyuC7RB10DfS+HqX4WUT8YOUdkKrqTDmULkABFsKssS0hcVBcIz67U+Iji894f6/U1q4qjmPu96sS9aKlwydK2lOFXI5Gh0ENHX9bxDaifpjzNbdiN1C2z/6NSaeR7fJGTr3hsN+34Sc4/Nb52696tJcaoIhitaiB1d/zpNmaNXVneBKFpRAdoQp0oOy26HpdXBotBeYhz7fhKePsnr2va9WoOqwu5vxePyHCE/dibgNEVvJEhnCIRLPxXBvIN/wIbXXMusZvjpBhGMi5/kShiXZri2fbqwml0J6qa8Ac80HNX5+38R+0dwN5jwaLsOqdm4eVXLYimiYt1RbFFVBH9UnytH3i2KMrpWS3nWqFhvjB7VnSBJJ8hhpVb7gUQFeKLVNHH95/QD6Vt3mUbj6qA4WRnJ00HhUdHl6uEnimhq4vgcWYm1k6yZO2HXV+Lx1Gead73sME8vkZ0grcYhHxjSvcXyvdEBBqb1jkCjUWDMv6DDCJFQ+WGBkGZdcj+gis6Ky76EcQ+LZF7OHnHeawlFKa4iz7/+60q01MQxL3RIYTnQaKHbDPH4wO/iPHegOgnSY3b97ycN0k8pMgkikZxKus8S7XlZu6Awue5yp+yBTIJI2hhHJwiAXweY95WoUmxrDIEw8yXxeP2r8Pdz4vHIu4WXiEQiOX04qsd9o6HL5Lbf/tgHhalk8hohs9cYa54TFxkaPVz2Rd0KWq8gYRjaebz4291PVHQ2RHB8bQPXFmgHN5txD4lKzbJMWPlE22+/JTikHLzDXCbJNXH4gtTXCWKzuirVht9W19OpJufdIKSyTKWi8rolHPlLfFeega7K5o4j4Ia/hPG6gzMtCeJmcCXRFt8Nr/cV5y9LhUjqg0iENITd7tJ97jJZGM2DkIa0GFs/LkcXSFhv0QHiIKKfCEzZzK4A8ZmG3S5kgBbfA9tPMhl0IjYLHPoTPpoOH08TgUFF40pE7P9NBHZPNY6u7ujB4Olf/zpOc/QGkiBOP5Dgxn+XrTFGT1oiAiyNsfsbkaB084arfhJdeQGdRFfIp7NFcOd0fJcNkbnTdewDl6dRe+NMgsQ3vl7UIJj+gni88gnXeXL10yLI7BkoCpLcDK7j4umWxDq2WiTIvcNFtfHZhKMTBEQC78J3T821zamiwzBXscXvd4oE/J+PQEWu6FgYU30OjpsgPl9ekpCcbAKHHNaR3HJMVldgP72wmVJYUCMJ0sDcyukLsr3pbbU3NaWwTkxmhHQHvZcIljvkylUV/vy3eNznUog+QT60IUKrCw63vic6nyUtpxV+IPWi1cHFi0RxQVaiywd1wiMw6zWx3BAII6o7yFY/LeYWzWXlk2IOhiKS2b/dWTs5Ya6ElA3i8YlJEHD6gpC0RIyvJFV4INbXVQq1DdIb8hGStBqZBJFITiVewUKLG1wXJnabuJD6YJIIHihaiOzfbkOUnKN4h4gqa89AuOLbupUwbUnPC8TJXbWJC3yvUFflqkQiOX30uhBG3QMXf3BqJC78O7iqk1Y91bCMx84vYM3z4vHs1+rq3Tpw9xYdIjNegqt+dnWKNIQj2AxNm6K3Br2ny+to2wcuU+/2wCmFVU8XCLg6QbISwVzhet5ug63viwssQzD0m9f4+2i0cP7/RPdB0mIRUG4uCdXdEv2vEPrYDoLiRCIkbqJIyMVNbP42TxeOAOSRv0QwJLwvXP4N3LpJzMuydkF+AxXaWYmiot/NR2yn14VCBqciD3Z93foxpVcbtdZXGDOw2iA94fMzz8MBxHfi8MFY+SSU557c9qqKYc8PQprsxTj46lJI3SiSqgOvgdu3i64j7zDR7XqqgwTHN4luKRBeOg3h7ARpQKLL4QdiaMKEtaWdILkHhPTgt/Nhxyf1r2MqE0kOEMFWn3CR0Ll5PQy4ClBFMvD5jvDGQPh4hqio/fPfwl/odEhmOfTcHd4PB34TUqvtjaPqt6kkCIhzZL8rRCX6Dwtg9/euCuLz3xDfO0Dnasnk5DVtPtxGcUhh9ZrTeCLuTMSxXwCMud9V1X82Mf7f4jhRkQdfXCg66FHEediR0PEMcJ2jmtENEunnga+HDqtd5Wiuaz7g6ASJCahOqqdtFT5s9eEwRY/oV/9yx3kp/SzoBMmrkQQ5EY3W9Rkd5uhJi+H4BuGrN+k/zX+f4beKZGLBEVcRoKRlODpB2qK72y8a5rwtHmt0MOcdca6rmQgbdouQpio81nypqYwd1YUxCsz7EvQGOL4eEj5xrXN8A9hMYi5Y37y90xjRhVKe7ZpLxE8UCfH6qGmQ/vNNsPenM3Pud5Zylp35JJKzkJ4XiPu9Pwptwv8Ngu+uFlJYWjeY/ET9JnsSycly/Qq4Z69LGutUMuMll7TDyDtrV7FKJJLTg84NJv0XOg4/de8x5n5xoZi2pbbBq4M9P8Bv1ZWOI++CAfMb357OTZihN6fyLmYIDL0Zes6B8AYu1E+WzuOg/3xAFZWa7RWAc5qid69/uX8H8IkUfk8ZO4QB/dqX4PX+8Ge13viQG5t3LA7rJZJnIOQDGjL1rUlplqjOB1eAviaGQFFpfs/ehiXO2pPeF4tkR3gf0Sl501roNl0Ur8RVdyc1JJfg6ALpPFbIN2j1ri6mjf9rvY+BoxOkPhP5PnOF2WbuvvoNXdubmscCU4nL+6AlqKo4fnw6WyQ+frxeBB6MJcIoeNhtcPduEUgOihPBrF4Xitc21rlzshQmw7dXgt0i5vQOg+P6cHaCJNUfsHCaojeRBGmpMfqaF4Dq91t8j0vuqCZrXxKJqsDOIhDkwN0bLngTLv1cvK+lUsjJHN8grl02vSkktD6ZdWrl2GxW1/9x2rPgEyH+947fW3tht7uSIMHNSIIoCsx8GcL6iED3TzcAqkg01ZQ+cXRBJq89fd4nVlMNKawLT897tiW+kSIw2OtC4VN2NqL3EB0sjmQ7iHP1iQb1Dkksx3m2ERRFcXaDJGW7pDzTikQSpEOgQchdfjwdFo2vK+VjrnT53jTYCVJ9Xio4cmbLMkLDpugOapqjW01COglEl45D4qo5eAbArFfE443/E141LSV1s5COPdO/0+ZQWdhyWdUcRwdSGxU2dZ8J1y2Fm9aJAp0Tcfd2HTvWPN90B4+quvaPfpeL7U98TPy9/DGXH8zhaj+Q+In1S6np3KBL9W/a4SnXkBSWg1H3CmWPynz44TrRbVuW0/hrJM1CJkEkklNNj9mAIqrkltwPRcnipDnmX3D3Xhhxe3uPUHKuotWdvgSbTxhc+b1oOx1y0+l5T4lEcvrxCRdJCxDeIDUDfft/g59uFBWwg66FSY+3/ftPf75ad13X9tt2MOVJUSmWlwTrXzt179MYTXWCKIor2fX73fBqT/H/KEkVc4yRd7sSG81h9P1C7748B1Y81vT6iV+I7r+YYQ2P0THOM5EOQ+GRHHGh3H1m7XE6Kv33/FB/ILs+3ecBV4lCgMKj9Qegm8JmcQXEoupJgngGuHzmElphkF5VJMb99/Pw40JI29bybTSGIwAw8BpAEbJdLfGYMFfCr7eJxEfyWpHcC+ku9uMFy+H+wzDtGREErUnvueI+aYnYRltjLIGv50FlgTDKnfNu49XzQfEiuGkqrT8Y5JTDCmn8fQ01OkGaqv7MO+iq7u8yxdWBcLyGX1DBUdhcXSE79ZnanVsOep4P9x6AOxLg2iVw8Ycw5WkRGPQKFbIlX84VHSUNYbeL/X/HJ+L3c+hPIRGSmdi0bv7RVeL7MQSL31avi8Tz7S2JVZohzJI1eiEv2xzcDOI85e4n/g7oBNNOqBSP6C8qg40lrt/+qeboarFv+kS65I3OJhRFJBAu+eTsltyNHOCSvvKLcQVVa+Lw8kpZ16xjm8Mc/UANc3RnJ0igQfwG7VbR+fjj9bVl73L3i+OGV4jorqsPQ6DLE6emJFbhMTFP+v462PSW+LshLEbxO1/9rKsL41TQVBLE4Z+XkSAKVIuSxeceeXfL36v7TDFnUG3w6+0tlxP8437hEbPlvZa/95mEqQzeGwP/G1y/BHx9GEuE3BO0rc9fxxGNF4AOvk787sqyxP+/MQ4ucXUJOTz0htwoOqPMZaLoQFUb9gOpSY9ZrscaHXRtwK/PgU8Y3Pg3jH1IrH/gd3h7KOz6VnaFnCQyCSKRnGp8wl16fwGxomL+nn3iQOrTwERDIjkbiRkiJvVn84WJRCJpmpH3CE35rF0uqcdDf4rAm2oTUiAzXz1zA+BNYQh0BazWveRKSJxOmuoEAZcvSOFREdyIHgIXvicCmZMfb9mxWO8Bs6slWxI+bdyQ2G53BeIHXdP89zjT0Orr30e7zxSduvkHRXCoJlVFLjmQ+BoyX+7ewl8FhCFyzQtUU7mQw3m9Hyy+t/6x5OwVOtMe/nX9cxwMqJaZ3POD2GZTJC0RScn/DYLnY+GLi+HvZ2DPd65uobagstDVxTL2QRi8QDz+477mBYQKjsKHk0UgSNGIhNydO+G2LWI/7jC0YXm/6MGiK8pSAYeWts3ncWCzimNaXpLoSrj864alKxzo3F2SSfX5gjiM0ZvqBHHIYak2EShqjLUvAarw5Zn3NXSdLvalry+DnOr9989/Cz3zuInQdVoT44+D2JGi+2jE7TDlKSE95hkgApdfzas/KFuSDp9fIGS5fr9LBFq/uhQ+mQHvj4VXe8G2Rvxidn8j7vvMFb/NPtXJyINLm7e/nyocfiCBnVqWfA+Kg8s+E92Fl34qjhE10epcvjanyxfEkSzrecHZJ4V1rjH2AZFUvfrXuvsGiK4yvxjxW05pOqHcvR5z9LRqT5AOgYbax6PMnaJowkF2tRRWeN/G520OSawDv8HaF+Hd0fDGAPjrP6Jz8s//E3+/NVRI/qRtE74bm9+FL+aK89DnFwrPuM8vFGbTbY3d7vL6aKoTJGdvdRcdMOHR+v8PzWH6C6KLLnefkBRsLvmHXZ0QzZA9O6NZ/yqUpIlz8d/PNu81OfvEvW9U/d53pwqdu/AABFj/ChhL61/PZoEV1fJow24FvyjxWKOF898U88TDf4pzcOFRkajoNLbh942fLDp6QcgENyUBDGIeP/5hkQwJ7yvmoD/fKIozWtp1I3Eiz34Syelg7odw/V+iumrIQil/JZFIJJKzF68gcUEAwlzwyF/w7VVCLqb3xUJa5WwPsPS+WFRV28wioFfTALGtqCysP0hsrnSZoTaWBOlzCXSbKYLON6+HG1YID5DWyhHGjoRB14nHv93ZsMl38hooPi6qnHvOad17ncl4+LlkC/b+WHvZsTWiYja4mwi+12ToTeICN2MHHN8oKiPXvSKM11c8JgI+2z+s38zeUVkbNajhIFTsaCFlZC6rO64TKTgqJJx2f1sjiNvZ1eWSvh3KshvfRnM5ukp8J6E9RZBg4mOiojj/IGz6X+OvPbAY3h8nglFeISIgOPFRMdbmoCiuz7S3Afmy1vLn/4ljm85TJEBO7EJpiNAGfEHMFa4x+ndsfBt6D6E7Do1LYuUfcUlIjX1ABNbnfiT8BIwlIvG141ORINLohMxUa5LTYT1h/k/CB+f4eiHr6zh2qarw8nh7hOji0RtEFXvsaNHtENRFdJKA+B3U1xFiLHV1UPW9TNxHDhQdFNYqkQhpL5pril4fnceJfbohn4XT6QtiMYqqZjg7pbDONTRa6H95w0lvRXGdh5ohidWjOglyIEskQSrNVvLLhZxnTIDBdTzqMELcb3zD5aXk8ANpypw6pjoJsvNz4QuXvVt0vnUaKxLgnca4DN3XvwIfToI3B8OyB+HICvFb9g4Xxz9jiZg3NjTPaC2l6a7OrYDY+tcJ6CQC0DazkG8M61O/dFJz8QoWiRAQyaGc/Y2v76DmOSsz4eS9tE4GVW29/GtxKmx80/X37u+a9x20pR9IS+k7TyTJqoqE5GN9JHwqZOIMQTDq7trLQru7urlWPyXuY4aBh2/D7+nuDd2qixAa8xarj/A+sHCVmF9p3eDQMtj3S8u2IXFyll+hSiRnCZ4BYuJwKoxqJRKJRCI53Qy/TVSt5yWJCj+bSVQiX/jeuXGuUxSY+QrovSB1U8P+EK3BbhdVcy/Gw8fT6iZCCg4Dqrjwaqxi3NMfLv8KZr3adPCiuUx+XAQpCo/C2hfqX8dhiN73kqYr489WeldL8ez9sXZXR2OSB96hrkDK73fBa31g5eNCSimgk6vqe+UTdaUMHEmQ+vxAHGg0QmYOGja/drDlXZGYiD4PrvwBHkgW3RVzP6qW21JdAdGTxamFXf2dePoLGSWANS+6Eno1ceiwf3ulkOeJGSZ8WTqNafn7OySxDi9vnp9Nc9j2AWytlie56H2XfEpzCKn2Bck9oRNk5ZMieegXAwOvano7TnP0RgzJ170k/s9dp7sC7W4GuPwbkUAtyxTeRiAkPBqTrmuKqIFw5XciKXRkhej0KM8TWuU/LRTBxKhBQmLuyu/g2sVw0xq4Yzvcd1AkZszlQv7lxP3/wO+i4j2oi+u7VhSR6IXWeb5UFLRN8vpkkiBN0XmcuE/d3PbB4BM5ukr81nyjXBX9kjMbRxLk8PIm5W+6hnmjKJBfbiKvzER6kegC8fXQ4WfQuzpBRtwOg68Xj3++WfyGs6u7ESL6Nj6euAni96/Ri+P9+f8TUoXX/Abj/w+u+R0eOCqk9HpdJOTetG4iSTL5CbhlI9yXBNctEce37N2w9F8Nv19RCnw4BT6a5vJeaAqHKXpQXMOdW4oikqwOpj598vPW3heLohS7RUg72qxNv8Yxr1Sq37s9/Y++ngcvdhGSeS1lxX/ENUDsaOhxPqCKJFlTtLUfSEvQ6mD8v8Xjjf8TCfqs3a7fmbFUyLaBkKPy8Ku7jZF3C88OBzW7gxti1muiY3NAM+YAdcash9H3iXPs4OtF4Y2kVcgkiEQikUgkEomkZXj6w8jq4BqqqPyd+7GYpJ8r+McIc3cQmtdtocFbWShkav76r5C6ydghzBlr4qjYbKwL5FTh4SdMfUFIOC15QFSbO6jIF9X7UO3/cI7SdZqoaC9KcRmRq6orSNHQxe6IOwBFJLKqikTg9ML34Pbt4l7rLvSlTwx2OOSk6vMDqUn/K0UAKjOhYR+BqiLY+YV4POER6DK5ttRE95nivjXeJSdit7sSQ46AHUDfS0VAxFoFSx8Uz1mMLomuF+NFJTIIw/NrFze/0+JEwnqJ34rNDEmLW/9ZHKRuFvs9CIkUhxdLc3F0gtSUn0ndLBJTIGTn3H2a3o7jf9ZQJ0jBUVFxC6IL5MTXzv9RBLxBJFTHPti88TdGxxEw70sR2Dzwm5C42vezCOKN/7fwb6nPPFyjEZ9boxddKQd+q73cIYXV77LanSp9qhNcR/5qmXFw0hJ4MU7I9DSH7L31J+vg1CZBgruKpLPVCGlbWvbanV+IZF1zgq0A+38R9z3nnP2dmv8UOo0RXgQlaS6JzAYwuOmIDRJKE0nZpaQW1PADsdtcyYGQ7iLoH9JDeID9cotLlii8iSRIQCzcsxf+dUQcXwZeLTqDa+IZIH63l3wsku8PZ4gkyci7xLFaUYT5+NwPAQUSPnOdr2pyfCMsmiB+F6mb4IOJro6VxnD6gXRpfL2O1R0x3Wa4OrJOBkURcyd3P3F+3vxW4+vn7Bf/U60bnFedlGovSazULaKzwFQiJAwdMrfNfe2+nwBF+E1NeETIWh78o2nvsfbsBAEhCxg7GiyVYr773mh4a4jwTvvrv0K+MjBOeIjUh84NLvif+LxQew7UEIZA6D7j5OSCQ7vDrFfOjYKzdkKeASUSiUQikUgkLWfozeICoteFcOln56Yf0JCFohskZ8/JV+mlbRMa2oeXi2C4o6p//Su1jUadfiAnUbV9MvSYBf0uFz4jW9+DNweJbp/Df0HiV6LSMXJA01WjZzNuXtBtunjskKzIPSAq63We0HFk/a8LihNa0x2Gw0WL4LatQqJMqxNSUUMWivVW/tdVpV5V5Aq0NtYJAqIzqMds8Xj7x/Wvs+MTcVEf1rt+feru1eacx9Y07TfRFFmJIlDg5gMdhrmedwSEHEHvL+aKxMc3lwuJLoc58yWfCsPzk0meKoqrG2RPKzoGalJZ6PI26n2xqLpsKY5OkLyDInFmMQrDXFToP7951aJQwxy9oP7l614R4+wyxaVxXxO/aLjqZ5HQm/OOSFy3BfEThTG1ohXVv0Fd4Ia/XHJcDRHaA0bdIx4vecDVtVOSAcnVngd9Lq39mpBuQqrGboX9vzZvfKoqZBpRhQdJQ3rvDvIPC0m2RRPq/z04/AVORRJEUVzdIC3xBUn8SlSb/3Gf8FxpyojYkYAE6DWnFQOVtAtuBlcHYbMksURyNSmrjLQikQTpEGgQ+4fNJBIqAbFCMnPuh2Ie4pCp0ns1T4bQK7j5xxKtruF5YdwEVyX+H/fVTnDs/BI+PV8c+yL6VXe1ZcHH011J94ZwJkGamD8Nu1V4slz0fvM+S3PwjRDnM4DVz9Qv/efAIWkZP9nV8XZ0ZfOTmm2JoyDBw08UE3x3DSR+3fTr7HaXv9iA+WJOGNJN+AICrHqikdfaXN2SbdXJ3FIURSTzLv1MdLBo3cX+8/czQroUYNJ/G5+fRA2CSz8XXVHt0dEiaRUyCSKRSCQSiUQiaTluXqKC+5JPhIb9uYgh0FUF1hzDS6tJBJxqyrCoKmx6S0hflaaLyrKFK0VldJ9LhZzNzze5zIYdRuzt0QniYM47rgAqigiUfHkxrHhULB94dfuN7XRR02uiZsdD7KjG9/dxD8GCZaIb4sRKvVH3ioRB9h7YX21SnLFD3Ad2bp45qGN/3PN9XcNoqxm2VMs4Db+t/mrDkK6iAt1ucUlZtRbH6zuPrRsoCOlW3RmD2H/MZSLxMfQWWPAn3LOv7QKyDvmy5DVC3qU1qKqoii7NEL/R2a+3rlozKE4kf8zlooJ7zXOiM8g7HKY2QyLEgVMOq54OiKIU2FUdpBrzQN3lDkK6wRXfQtepzX/f5tB9Jlz9i5A9u2lt/UmY+hh9n0gmlGcLqTgQ+zGqSCwG1OOV4jBIb8oHx8GRv4THDAiT3qaktLa8J34Llfmw6e3ay6wmoXcPpyYJAi33BcnZD4vvFY81OlEp/+5okRhpqFvx6Erx+/ONbrrbTHJm4fjtNqNLoHu4wxeklNTCGp0gjq604K6uc1JYL9ER4iCs1+mvLB99n0jiWo3w3VXiWLf8Ufj1VvGb7HkBXLdMnC9iR4tj6peXCp+jhnAmQRowRXfgZhCeLM3pymsJ/a8UxzKrURhm14equqSwel8kAumeASIJm95E90Rbk3fI1RW64E+RqFdt8MvNsKWJBNGe78X8xc1bdE06GPeQ6HBJXtuwvFbBUZF803k23wPsVKBzF/vZZZ/Dvw6LuW/cRJHkj5/sKjppjB6z/hlz4nMImQSRSCQSiUQikUgaYtitIqh5fD2kbW14vcSv4OlweDoMngiAxwPgqTB4JkqYLNutomvmxr9dlW8zXgCfCNEJ4AgKtncnCIjgb9wEEUC9Y4f4DtyrDR/dvF2V9+cy8ZOEtEVZJqRtFoF8x/OtxSvIlRhY9TTYLJBenQRpbnAydrQI0pvL6wZ49/8iKma9wxo33nRKYp2kfJTjO+kyuf7lY/4F590gJK8WLBeJj+nPia6RtpTkCYoTGu+q3SX7U5OqItj8rivBWB+b3hSSIFp3uPTT1gfHtHpXwHzXN7Chusp21isi0NVcGpPDcnSBxE1wmRWfbjqNEf4CLfEF0nuI5BLA9o/g+CbRGQQiaVgfjv04ZT2UZjb9Ho5ktUMKbPvHDScHjKWuZBKIZHXNpFNhMqCKY593aNPv3Roc3VqZO5v2tDGVw/fXiOBh5/FCZq/DCJHg+OUWscwx/pIM0Rm1+B5YUu270GuOlMI623AcW1M3i+NYI3QPF8esA9llpBUKT5CYwBqm6KE9a7/gvBuEjwVAzJA2G3Kz0WiETKRfB5HY/d9AV1fC2Adh7ifi+OLpD/N/EmbWqk34HNXnrQXNl8M6VSiKKyGw83PxuU4kaxcUHhMJgK7TRPLJMa843HTHT5uy6X+AKmTBQnuIjoaht4hlS/8ljN7r+57NFUIyCmD0veAT5lrmH+PynWno/+TwAwnreebIOnn4CV+3q36C/8sU89+Tka2SnLHIs6BEIpFIJBKJRNIQflFCqx6EN0h95B4Q1blqzQ4Qu6gGtFSIqrgZLwnfFA9f1zqeAXD+m+LxlndFZX1RtbRJe3aC1CQoDqY9C/fuFwGLq3+t/RnOVXTuosIPhG758U3icUMB/+Yy/FYwBAvz+Z1fuPxAmpLCcqAoLim1mpJYqioC+SBkt3TuDW+je3V14+EVotq9NVQWumTc4hv4TtwMQhZr2jPQYeipDcA6guUnSmIdWg5vDYNlD8K7o2Ddy3UlR9K2uQI60549eXmO0GpJrNXPuKS1HImn5tJQJ0hxqki4gjBsPduIHeUyhf3+WsjdLxJPPefUv75/B4gZBqguabqGSN0iPHc0erjiO7Hd7N0uX58T2fW1SCYGdxV+COay2h1/Tj+QuFMXDPOLEpJiql0kehpCVUVCI/+QSJxftAgCO4luzAmPiq6Q/b/C28PgtT7wak9hXr/9I9HdpHUXAT7J2UVArJB2Um1Nmlb3iBDn5SO5ZRzLF12CMQGerk6Q0BPmFIoCF38gzutj7m/rkTcPQyBc9pmYI1UVCcmuiz8URus1zxc6N7jwXZe30bqX4dv5tY+PlYVQUd0J2FQnyKmk43CRoLZbYc2LdZc7ukC6TgF3b/HY4Sdxst2ZLaEsWyTqweV/p9GIc+C4apmrVU/B15eLuUbhMVdCY+P/RIGIXwdR5HAio+8TEmuZCXWLLaxml/xfe/mBNIXe48xJzkjaHJkEkUgkEolEIpFIGmPEXYAizB4dVZUOLFXw/XWiOjduAjyUCv86BvcdhLv3wB0JcP9hEZiuL5DWZRIMqpY4+v46EQzz8BfV/GcS7j7C36K5wfpzAYfM0q6vhTxHQOzJSze4+7i8JtY875K/aIlMTf8rRdAoK1FUkIMI/mbtEtWljirMhogcIAKp5nLhDdIajq4CVAjtJQK57U3viwBFdO0UpwlpkV9vg68uEfJL7tV65yufgA8nu37HVUXCB8TRqTV4wcmPxZEEQRWm5NNfaPk2DNWGwzl7RfL1p5uE7NGb54l9sdNYkVg6G5n8BHiFiP8LQLdpjfsMOAzSm5K22vCauO83T+iz97xA/L3jk7rr2u2wtVruZciNwtAXYOsiERwEIWMGp04Ky0FzfEESPoU93wmZlrkfgXeIeF6jFQHs61dUS43liESZooGI/iJAedkXcF+SkDySnH10dQTIG5fEig7wxMddh8WmciyvAqj2BHEc6xx+RTVxM4jfS0u61NqayAFin+4yFa5d4vq9n4iiiOTIBW+LRGfSYnFMPL5RLHf49/hGuZIL7YXD72TX10L6yYGqwr5qKcxeF7mej5sIKOJ4X5Jxesa45T1xTowZWtfTa9xDMPVZ8fehpbD4bnhjALzWF365TRiJA0x+vH55UO8QUfABIpFis4r/0+93wUtdRGEJQGT/U/XpJJIGkUkQiUQikUgkEomkMUK6uroCHBd/DpY9LCotvUJFRaWHn5A98gkXVcxBcU0biU55Cvw7ikpkEF0gsg2//ek01hWMBiFZ0Rb/l8ELwC9GSFdVFYmERktMNb2CXFrVjgDvprfEff8rmvYW0WhOXhLLEZDrchLyYG2Jb6TLsP6v/8DbI0SnDYoIBN+XJPS+3f1Edep7Y0TV/y+3QUkqBHSC2W+0zf+3ZhfX9BeEmXBLcfwP07aIz7P7G9HVYDWKY8zE/5z8ONsLQyBMe871d995ja/fc44I/mfudAU6TyT3ABxcAiiuqmZHx9SeH+sapB9bJTo93KqTu12miGCgtcql5e/sBDnF0jqOJEhDviBZu4WZPMDEx6DjiLrrRA0U/iwXfSCkgx5KhZvWiC6sHrOb5zckOTPpUu0Lsv83WP4IZCbWKzGkKArdI3xq/A1RvjpXMu/ETpAziR6z4crvIHpQ0+sOuBJu+EvIQpamwycz4e/nanuftDfRg8X/TbWJsTnI2CGSlG7eru4PEOd0R4HJkdPQDWIqg23V5t8j7qx/neG3wo1rRFdIhxEi8VSSColfgKVSdOj1urDh9xhxhyjoyUsSiY+Pp4v5irFYeGSNuBP6XtbGH0wiaRqZBJFIJBKJRCKRSJpi5D3ifs93otIcYN8vsKNakuii91qvG+/uLaQeqA7AtqcfiMSFVu+qJoeT8wOpid5DVFo6iOjXuHxVfTi6h/b8IIJiB5eKv4fd2rzXO5IgB5eA3day97bb4chK8bghKaz2oKaJdmm66Ny5bokIBLsZRILots0i+GQzCQmsg3+IJNQln7SdzFunMaJDZvCCxr1ZGqPzOKHhH9pTbGP8I3DZl6Kz7IHk5gULz2R6XwzDb4c+lzQtMecdIrrsAL65Akqz6q7jSE73mO3yA+g4QkgJWSqqDdhr4DD9HXCl6M6qqeW/4xMoOu6q4A6Ka/HHaxGxo0TnRv6hur4nVcXC68NmEv4BDQUsAdy8oO8lED+x7Q2fJe1Hh2Giy8dSIWSI3h8rOsL+fg7yj9Ra1WGODhDu64F76XFR7a83COmic4XI/iLJ1+8K0T3797OiIAXOjCQIiK4VEMceRzeOQ9Kv2/S6fkqOZNfpkMTa8SmYSsR+1W1Gw+tF9hdzlQVL4aHjcOWPIrnRbabwD2msaMDDD0ZVz5urCoW3Uv/5QlL13v0w5UlxzJJITjMyCSKRSCQSiUQikTRF9CAR3LRbRdV90XH4rTogNeoeV5CutXQcIYykoe2C7ZKTxxHE1roJU/K2ou88V7CmJVJYDmJHiQCGuVwEhlGh63QIbqZ0T8dRoiuiIs8lydVcsnZCZb6ooq8po9He9JwjKmwBzlsIt2ysWzXvGyn8Ii54SwRlAKY83bayHJ7+cOtGmPVq6ztLvEPh1k3iNvcjGPsv0Y0WFHduaJUrCkx9WngSaPVNrz/jBfCNFomCT2ZASbprWXGqK8kx6u7a7+HoBtlRwyC98Jirk+m8ha71O40WySe7Bda84Oo6OdVyWJ7+QhIIxOfY+yMsfQgWTYAX48V4/WJEJ5M0Nv/nodXDzRvg0s9FUl7nIbo7/n4W3hxUy6usZidITIBBdEiB6E471/Yddx+48B3hj+PmLboToP1M0U8ksj90nwWo4n9lt9cvheXAkQw+9nfrvbqag9UMm98Wj0fc2fz9ws1LdH5OeQou/0p0SDfF8NtFN+Qln8D9h2DOW+IYey6cwyRnLefYkVAikUgkEolEIjlFOKraEj4V1bmmEog+z6X/fLJM+Dc8lAY9z2+b7UlOno4jYfKTolOnLXXGtTohn9bzAhh2c8tfXzPAW1qtIT68HoPShtC5QdfqytOWSmId/kvcx41rXgD7dGEIhIWr4JZNMPOlhqtMFQUGzBddFdf/BUNvPL3jlLScwM6iq8e/g0gKfDxDJKJBJKXtViFfF3VCh0y/edUG6XtcBunbPgRUkWw+MWk44TFxv+srkeiDU98JAmLsACseEx41W94R0jl2i6jgv/QzKWn1T0bvIeYFl34mPMYufM+VlN/5uXM1hzk6QEygQUgRQQ2fonOQvpcKKbjIgeK33mlMe4/Ixfj/AxTY/wts/1CYibv7iW6tEwnvK7zgzOWQuunUjWnvj2LO4B126uWotDoYepOQzdJ7ntr3kkiaSauSIG+99RaxsbF4eHgwdOhQtm7d2uC6n3zyCYqi1Lp5eNRjniORSCQSiUQikZzJdB4vpIsslUKf3t0PLv6wbQPBbSXJI2kbFAVG3tl6WaPGiBoogloBsa17fb8rRIcKiABK7KiWvd4hiXVgcb0a8w3i0Cw/k6SwHIR0g7CezVvXOwRizju145G0HQEd4bqlIiFSfFwkQtK2CWkXcCWpa2IIhF5zxOPtH4O5whU0HnJT3fWjBwl5GNUu/vaJOD3SUr0uFL4nGp0wNB9yo/D3uGsX3L1bHCskEhBzhH7zYN5XYn8pOAKFyQB0C6vRCRLoWbsT5FwmKE4kwB9MPrPkRMN6uXwzlj4o7rvPrF/+UqNxnVMPLT8141FV2PiGeDz0pvpNzSWSc5wWJ0G+/fZb7r33Xv7zn/+QkJBAv379mDp1Krm5uQ2+xtfXl6ysLOft+PHjJzVoiUQikUgkEonktKMotQNt578uAnMSSXvgFSR8LgDG3N9y6aX4SaJytijZFSxzoKqQsh4O/A6pm4U/grEUKgogfbvr9RLJ6cQvGq5dIqTkStPhoynCzDyiv8tg/EQcHVN7f4RtH4CxBAI6Nbz/jv83Tn+mUy2F5SCiL/zriOgEvGkNzHhR+HsExLZeUk1ybuPhK8ypAY4KjyYvdx0dg4TXREzAP6QTxIGinJkeE+MeEp4/arX3VmMFFQ5JrMOnKAmy/xfI3S/kwwYvODXvIZGc4bQ4CfLKK6+wcOFCrrvuOnr27Mm7776LwWDgo48+avA1iqIQHh7uvIWFhZ3UoCUSiUQikUgkknahx/kw8i6Y9pyrwk8iaS+mvwh3JtY2cG8u7t4QN148dkhiWc2Q+DW8MwI+mQnfzoePpsL/BsJzMfByV0AVxt9+UW31KSSS5uMbAdf+IUzjHR0bo+5pOFnQYXi1QXol/PW4eG7Iwoa18MN7Q+9qzf7TGTw2BNY1S5ZIGsMhq3RkpfOp60d1ol+MP+Pi/USXCJz7nSBnMiHdoM8l4rFnIHQe2/C6ceOru3sOC9m/tuTwX/BTdffb4AXgGdC225dIzhJalAQxm83s2LGDSZNcVRMajYZJkyaxaVPDunXl5eV07NiRmJgYLrjgAvbt29fo+5hMJkpLS2vdJBKJRCKRSCSSdkejhclPwLBb2nskEonw9gjs1PrXd58l7vf/ChvfhDf6wy83u6pFo88T1ej66gpbu1Xc9zkF8mASSXPxDoVrFgsvja7ToMfshtet6Z+j2kBvgP5XNr79mS/DxP/A6PvabMgSSZvj6GY6tkYksIGrh8fy620jCTKmieO1m4/ooJK0HxMehZihwvetMflUDz+RtAWX91ZNrOaWSVc6OPQnfHM52EzQbaYYj0TyD0XXkpXz8/Ox2Wx1OjnCwsJISkqq9zXdunXjo48+om/fvpSUlPDSSy8xYsQI9u3bR3R0/QfjZ599lscff7wlQ5NIJBKJRCKRSCQSSUvoNl1IdeTsheX/Fs95hYok3+AF4OnvWtdcARV5YKkSlfUSSXviFQTX/Na8dfvNg7/+K4KA/ebV3q/rwzMARt97siOUSE4t4X2EwXV5DqRtrm0KnlctcRjaXUqqtTf+MXB9MyWuukyGlHWQ+CVUFQm5ysJkcV+eIzpFPAOqb4Hi3j9GHNeiBtXd3sGl8O1VYLeIZPHFH4niCYnkH0qLkiCtYfjw4QwfPtz594gRI+jRowfvvfceTz75ZL2vefjhh7n3Xteko7S0lJiYmFM9VIlEIpFIJBKJRCL55+AVLKqJDy8X/gcj7oS+l9VvmOrmdWZqrkskTWEIFEmN3d+KfVwiORdQFIibCLu+giN/1U6C5FYXKUsprLOLLlNgxWOQlShuJ2K3imKEirzaz299HyIHCqm/XheJc/iB3+H760QCpOccuPiDxjtRJJJ/AC1KggQHB6PVasnJyan1fE5ODuHh4c3ahl6vZ8CAARw5cqTBddzd3XF3d2/J0CQSiUQikUgkEolE0lIu/kAYn0f0b9gnQSI52xn3kLhJJOcS8Y4kyEoh1enA2QnyDzBFP5cI6Q7DboPs3RDQEQI6CcnLgE7g3wFsZqgshKpC0SlSWQipm2Dfz5CZAL/cAn/+G7rNgN3fiKRJ74vhwvdBe8pr4CWSM54W/Qrc3NwYNGgQK1euZM6cOQDY7XZWrlzJ7bff3qxt2Gw29uzZw4wZM1o8WIlEIpFIJBKJRCKRtCEefhA1sL1HIZFIJJKWEjcBUISkYWkW+EaI52UnyNmJosC0Zxpfxzey9t+Dr4MpT8POz2H7R1CSBolfiGV9LoU578gEiERSTYtLfe69914WLVrEp59+yoEDB7jllluoqKjguuuuA+Dqq6/m4Ycfdq7/xBNPsHz5co4dO0ZCQgLz58/n+PHj3HDDDW33KSQSiUQikUgkEolEIpFIJJJ/CoZAlxfE0ZXi3mKEwmPicWjP9hmX5PTiHSIk/+7aBfO+hu6zYMQdcOG7MgEikdSgxb+Gyy67jLy8PB577DGys7Pp378/y5Ytc5qlp6amoqnRRl1UVMTChQvJzs4mICCAQYMGsXHjRnr2lAdjiUQikUjONUw2ExpFg14jNWclEolEIpFIJJJTSvwkyNgufEEGzIeCw6DaRJefT/Nk6yXnCBotdJ8hbhKJpA6Kqqpqew+iKUpLS/Hz86OkpARfX9/2Ho5EIpFIJJJ6KDGVcOGvFxLlHcVn0z9DUZT2HpJEIpFIJBKJRHLukrYNPpwEHv7wr6PCH+KnGyBmGFz/Z3uPTiKRSE45zc0bSOc7iUQikUgkbcLa9LXkVeWRmJdISmlKew9HIpFIJBKJRCI5t4kaKBIgxmJhju00RZd+IBKJRFITmQT5h1OVmEj5mjXtPQyJRCKRnAOsTV/rfLwxc2M7jkQikUgkEolEIvkHoNFWG6QjJLGcpug92m9MEolEcgYikyD/YOwVFaQuuJ60m2/BnJLS3sORSCQSyVmM1W5lQ+YG598bMjY0srZEIpFIJBKJRCJpE+Inifsjf9XoBJFJEIlEIqmJTIL8gylbtRp7ZSWoKuUbZcWuRCKRSFpPYm4iZeYypyH69pztmGymdh6VRCKRSCQSiURyjhM/UdxnJEBhsngskyASiURSC5kE+QdTumSJ83Hlps3tOBKJRCKRnO2szRBSWFNipxDiGUKVtYqEnIR2HpVEIpFIJBKJRHKO4xMOYb0BVdw8A8ErpL1HJZFIJGcUMgnyD8VWUkL5+vXOvyu2bEG12dpxRBKJRCI5m1mXvg6AsdFjGR45HJC+IBKJRCKRSCQSyWnB0Q0CogtEUdpvLBKJRHIGIpMg/1DKVqwAiwX3LvFovL2xl5Zi3H+gvYclkUgkkrOQjPIMjhQfQatoGRE5gpGRIwFqeYRIJBKJRCKRSCSSU4TDFwSkFJZEIpHUg0yC/ENxSGH5zpqN4bzzAKjYvKk9hySRSCSSs5S16UIKq39of/zc/RgeORwFhcNFh8mtzG3n0UkkEolEIpFIJOc4McNA7yUeh3Rv37FIJBLJGYhMgvwDsebnU7F5CwC+M6bjNVzIlkhfEIlEIpG0BkcSZEz0GAACPALoFdQLkJJYEolEIpFIJBLJKUfnBoOuATef2l0hklajqipfHfhK+hxKJOcIMgnyD6R02Z9gt+PRry9uMTF4DR8GQGVCAnazuZ1HJ5FIJJKziSprFduytwEwJmqM8/kRUSMA2JAhJbEkEolEIpFIJJJTztRn4OE0COzU3iM5J9iQuYFntz7L/Wvux67a23s4EonkJJFJkH8gDiksvxkzAHCLj0cbEoxqNFK1M7EdRyb5J1NhqeDz/Z9TZCxq76FIJJIWsDVrKyabiUivSOL845zPO3xBNmVtwma3tdfwarE+Yz13rLxDSnRJJBKJRCKRSM49FEUaorcha9LWAJBXlcehokPtPBqJRHKyyCTIPwxLZiZVCQmgKPhMmw6Aoih4DRXdINIXRNJevJP4Di9se4FHNzza3kORSCQtYE26uDgYHT0apcZFV5+QPnjrvSkxlbC/YH97Dc+Jqqq8sO0F/k7/my8OfNHew5FIJBKJpMXYKyup2ruvvYchkUgk5zyqqrIuY53zb9ndLpGc/cgkyD+M0qVLATCcdx76sFDn805JrI0yCSI5/dhVO0tTxL65Jn0N+wrkxZ1EcjagqmodPxAHeo2eoRFDAdFK3t4cKjpEckkyACuPr0RV1XYekUQikUgkLSP76adJmTuXkt9+a++hSCQSyTlNcmkyGeUZzr+lz6FEcvYjkyD/MEr/EFJYvtVSWA4c5uhVe/diKy8/7eOS/LPZmbuzljzNu7vebcfRSCSS5nKo6BA5lTl4aD0YEj6kzvIRkcIX5Ey4aPgz5U/n49SyVI4UH2nH0Zy5FFQV8NiGx0jMTWzvoUgkEomkBnazmbJl4lxW8PEnMpkvkUgkp5B16aILJNY3FoCE3AQqLZXtOCKJRHKyyCTIWUzVrl2Ur1vf7PVNyckY9+8HnQ6fqVNqLdNHRqLv2AFsNiq3bqv39fnvvc+hYcOp2LL1pMYtcWHJysJWWtrew2h3liUvA2BQ2CA0ioa/0/4+I+RzJBJJ4zhaxIdGDMVD51Fn+cgo4QuyO283peb2O9apqsqyFHGc8dZ7A7AydWW7jedM5u3Et/n5yM88vulxGWCTSCSSM4jKLVuxV1QAYDpwgKrExPYdkEQikZzDOK5zLu12KVHeUVjtVrZl1x8rk0gkZwcyCXKWYq+oIONfD5C2cCHZTz6Fvaqqydc4DNG9RgxHFxBQZ7nXMNENUp8viPHAAfLeeANbcTGZDz4oA/dtQMXWrRyZMpWjU6dhOnasvYfTbtjsNlYcXwHA9b2vZ0Yn0aX0zq532nNYEomkGTQkheUgyjuKWN9YbKqNLVlbTufQarG/cD9pZWl4aD24fcDtAKxKXdVu4zlTKTYW89tRIbFypPgIiXmJ7TsgiUQikTgpX1193tKIS/iir75ux9FIJBLJuUuFpYIdOTsAcZ0zMlIUdp0JEr8SiaT1yCTI2YpWi/fo0QAUffklyRfPpWrP3gZXV1W1QSksB05fkE2ba7/WZiPrsf+AzQaANTub7KeeOumP8E/GnJ5Bxl13g8WCraiI1AXXY8nMbO9htQvbc7ZTYCzAz92PYZHDuLHvjbIbRCI5Cyg2FrMrbxcAo6NGN7ieoxukPc0E/0wW8iFjoscwvdN0NIqGA4UHaun8SuCHwz9gtBmdf39/8Pt2HI1EIpFIHKiqStmq1QAE33YrAGXLlmEtKGjPYUkkEsk5yeaszVjtVjr4dKCjb0dGRJ05Er8SiaT1yCTIWYrGw4PwRx8hZtEidCEhmI8dI+Xyy8l/5x1Uq7XO+sZ9+zEfO4bi5obPpEn1btMwVBjYmg4fxpqf73y+6OtvMO7Zg8bbm6j/vQEaDaW//U7psj/r3Y6kcewVFaTfdhu2oiI8evbELS4Oa3Y2qdffgLWwsL2Hd9pZmiwM0Sd1mIReo6eTXyemd5oOSG8QieRMZn3meuyqnS4BXYjwjmhwvZq+IO0hr1RTCmtap2kEegQyMHQgILtBamKxWfj6gKgqntdtHiB8VEpMJe05LIlEIpEAxv37sWZnoxgMBN1wAx59+6JaLBT/8GN7D00ikUjOORx+IKOjRaHX0PCh6BQdx0uPk16W3p5Dk0gkJ4FMgpzleI8eRafffsVn2jSwWsl7/Q2OXzmfgg8+IOvRRzl+1dUcHj2GlLlzxfpjx6L19q53W7qAANx79ACgYrOQLbHk5JD36qsAhN53L76TJxN040IAsv/7Xyy5ufVu60yh2FjM3vy92FV7ew8FANVuJ/Ph/8N08CDa4GCi336LDh9+gC4yAnNyMmk33oStvKK9h3nasNgt/JX6FyCCkw4c3SCr01ZzoOBAew1P8g9AtdulvF8r+TvtbwDGRNUvheVgcNhg9Bo9WRVZJJcmn/qBncCuvF1kVWRh0BmcHSuTOopiAOkL4mJZyjJyq3IJ8QzhgfMeoFtAN8x2s1MeSyJpC1S7ncIvv6Riq/SXaytKTCWsz1iPzW5r76FITiHlK0XS3nvkSDTu7gRcfjkARd9+g2qT/3uJRCJpK1RVdfqBOK4dvN286RvSF5DdIBLJ2YxMgpwD6AICiHr1FSJffAGNjw9Vu3aR+9LLFH//A5XbtmHNyxPrhYUReN21jW7La3i1L8gmcWDPeeop7BUVePbrh/9llwEQcuutuPfsga24mKxHHz2jjFOzyrNYfGwxT2x6gjm/zGHCF6N44fXL+O83C6kwlbf38Mh/5x3Kli8HvZ7oN95AHx6OPjycDh98iDYgAOPevaTffjt2k6m9h3pa2JK1hRJTCYEegQwOG+x8vrNfZ2c3iPQGkZxKsp94gkPDhlP88y/tPZSzikNFh5xePpM7Tm50XYPewKCwQUD7dF78mSK6FsfFjHOat0+ImQBAQk4CBVVSSkRVVT7f/zkA87rPQ6/Vc0nXSwD47uB3Z9R5XnJ2U/LzL+Q8+RSp199A+bp17T2cs55CYyHzl8znlr9u4eUdL7f3cCSnkLJV1UmQCeL85TtjOlp/f6yZWZSvWdOeQ5NIJJJzikNFh8itzMVD68HgcFeM4kyQ+JVIJCeHTIKcIyiKgt/s2XT+9Rf8Lr4I35kzCb71ViJffIHY77+j69YtdFnzN4aBAxvdTk1fkLKVKylb8RfodIQ/8QRKtQmf4uZG1PPPo7i5UbFmLcXft79meEZ5Bhf/djFTfpzCw+se5vtD33O0+Ah3/2rn4e/tXP74Rg4NHcqRq64k9+WXKV2+vNkaupacXEpXrMBuNp/UGEtXrCD/f28CEPGfxzAMHOBc5t65EzGLFqExGKjcvJnM++9HtVhO6v3OBpYlC4mayR0no9Poai2T3SCSU03Fxo0Uf/Mt2O1kPfaYrExuJqqq8uK2F7GrdiZ3nEyv4F5NvmZSB9F58U7iOyTmJp7iEbqwq3aWpywHcCZWASK8I+gZ1BMV1dnR8k9mR84ODhQewF3r7kx+zOw8E0+dJymlKWzP2d7OI5ScC9hNJvLeFPMgLBbS77iTyh072ndQZzEVlgpu/etWUkpTAPh8/+esSZPB8HMRS0YGpqQk0GjwHjcWAI27O/5zLwag6Muv2nN4EomkEb4/9D1vJLwhi27OIhxdIEMjhuKudXc+7zBH35K9BYv93I/VSCTnIjIJco6hj4wk8umniXr5JULuvAO/2bPx7NMHra9vs15vGDQI9HosmZlk/fsRAIKuuxaPbl1rrefepQshd98NQM5zz2NOTW1y2+b0DDIfephj519A0fff1+td0hpKTCXc8tctHCo6hFbR0juoN1f3vJr3K+Zy3mEVVavFrAMPox3LtgQKFn1Axp13cWTceHKeex5bcXG927WbTOS/+x5Hp08n4447Sb7oIioTdrZqjFWJiWQ++BAAAfPn418tT1YTz969iH77bRS9nrIVf3Fo6DBSF95I/vuLqEpMbFFSRFXVM17ix2wzO6vCp8VOq7O8s19n5/OvJ7zOpsxNrE1fy8rUlSxLWcYfx/4guyL7tI5ZcvZysPAgly2+jLcT30ZVVexVVWQ99h8AtIGBYLGQccedmFNS2negZwHrMtaxOWszeo2eewbd06zXzO06l3Ex4zDbzdy1+q7TZkiekJNAblUuPnofpzeJg4kdJgJSEgtwdoHMjptNgEcAINr+Z3SaAYgLeInkZCn66musWVnowsPxGjMa1Wgk7aabqdq3r72HdtZhsVm4e/Xd7CvYR4B7ANNjRZL3kQ2PyLnROYjDEN1z4AB0AQHO5/3nzQNFoWLDBkzJp19uUiKRNM5Hez/iiU1PsGjPImb+PJNFuxdRZa1q72FJmsDpB1ItheWgR1APAtwDqLBUsDtvd3sMTSKRnCSKehZoHJSWluLn50dJSQm+zQzmS1pPyvz5VG0XlXn66Gg6//4bGk/POuupdjup11xL5bZtuMXHEbTgenwmT0Lr41NrPWtREQXvvU/Rl1/WCuS7depEyF134jNlirPLpKWYbWZuXHEjO3J2EGYI44sZXxDuFY7pyBGSL56LajIR+tCDVJw/lqe+vgnDkQy65WgZVRSKLlkE4TS+vgTfuJCA+fPReHigqirlK1eS8/wLWNLSxBvpdWCxgqIQcPnlhNx7L1pvr0bHZsnKonTJEkp+XyyqtwDDsGF0WPQ+il7f4OvKVq0m65FHsJ1gkq4YDHj26YN7fDzu8XG4dY7DPa4z2qAg7BUVGHfvpmrXLioTEzEm7sJWUkLQTTcRcvddKIrSqu/3VPJ32t/cseoOQj1DWXHJCjRK3X3gWMkx5vwyB5X6D1Peem9eGfcKwyOHn+LR4gzSePZquuo9uyKbfQX7GBc9Dq1G26r3U+12zEePYkpOxpycgjklBXNyMubUVBR3d/RRkbhFRaOPikIfFYVbbEc8Bwxo9W/pXCarPIsrl1xJXpWQBrx30L3MWJJP4UcfoQsPp9OPP5B2660Yd+3GLTaW2G++Ruvv376DPkOx2C1c/NvFJJckc12v67h38L3Nfm2lpZJrll1DUmES8f7xfD79c7zd6veoaiue2vwU3x78lgviLuCpUU/VWna0+Chzfp2DXqNn7WVrT/lYzlRSS1OZ9fMsVFR+veBXOvt3di7bV7CPeYvnodfo+euSvwj0CGzHkUrOZmxlZRydPAVbcTERTz+F74wZpC5cSNX2HWgDAuj45Re4d3bte3aTidI/llD01VeoFgsRTz+NZ++mz7//BOyqnYfWPsTSlKV46jz5aOpHdA3oyvwl8zlQeIBBYYP4YMoHdTpsJWcvqQsWULFxE6EPPEDQgutqLUu76WbK16wh8JprCHv4oXYaoUQiOZHvD33PE5ueACDaO5r0cmGmHWoI5Y4BdzC78+xWXydKTh0lphLGfjsWm2pj2cXLiPKOwl5VheLhgaIoPLD2AZYmL2Vhn4XcOfDO9h6uRCKpprl5A5kEkdQh7823yK+WK4hZ9D7eo0c3uK45PYPkiy7CXt11oLi54T1+PL6zZuI1ZAhF335HwaJF2MvKAJEE8Bo2lMJPP8NWVASAR8+ehNxzD16jRrYoWG9X7Ty49kGWpSzDW+/Np9M/pWtAV+xmMymXXoYpKQmvkSOJWfQ+ikZDiamEe/6+h23Z29Cg8B/tHPp8txProSMA6MLDCbr+espXr6Ji4yYArEG+LJkezPLwPP6T0ImQVbud64b/5zF8xo8HwFZejjU7G0tODubkFMqWLaNyew35EJ0On/HjCX/i8VoVXA2h2u2YDh2icus2KrdtpXLrNmwlJfWuq/HxwV5eDg38lP3mXkzEf/+LojuzLoYfWvcQfxz7g/k95vPgkAcx7t9P4aef4tm/P74zZzq7l97b9R5/JP+BTqNDr9HjpnFDr9WTX5VPckkyOkXHY8Mf48IuF56ysZYs/oPMBx4AVSX0/vsIXLCgwX31SNERFvy5gCJTEZM6TOLZ0c86fQiai62sjLSFN1KVmNii13kOGEDEk0/gHh/fotedy5SYSrhm6TUcLTlKoEcghcZCOmWpPPeZHcWuEv3O2/iMH481L4/kyy7DmpmFYehQkax0c2vv4Z9xfHXgK57d+iwB7gH8cdEf+Lj5NP2iGmRXZHPlH1eSW5XLyKiRvDnhzVMWqLParUz8fiKFxkLemfQOo6JG1Vquqirn/3I+KaUpvDjmRaZ1qtuR9k/g2S3P8lXSV4yMGsm7k96ts/yyxZexv2A/9w66l+t6X1fPFuqyv2A/i3YvIso7in6h/egX0o9QQ2hbD11yFpH7+usUvPMubp070/m3X1F0OmxlZaRecy3G/fvRhYcT++UXoNNR9PXXFH/7nXOeCKDo9YQ++CABV15R7/nXVlxM/rvvUbFlCx5du+A5eDCGwYNxi409IwtBWouqqjy/7Xm+PPAlOo2Otya8xYgo0eV2vPQ4l/5+KZXWSm7pdwu39r+1nUcraS5GqxGj1Yi/h3+dZbbSUg6NGAlWK3HLluIWG1trefmaNaTddDMaX1+6rPm73sI1iURyelmWvIwH1j6Aisr1va/nzoF3sjR5KW8kvEFmRSYA3QK68ejwR+kX0q+dR1uXpMIkjhQfYXrs9H9comZZyjL+teZfxPnF8cucX6hKTCT1hoXowsOIfP55lrsf4ZENj9ArqBffzPqmvYcrkUiqkUmQfyCqqlJlraLMXEagRyB6bcPdBo1hSk4m5dLL8Js9i/DHHmtyfUtWFiW//ELJ74sxHztW7zru3bsTet99zkSHrbycwk8+pfCjj7BXVgLg0asXPtOm4jtlCm4dOzb5vq/seIWP936MTtHxzuR3GBYh/Exynn2Owk8/RRsQQKdff0Ef6gq8WGwWHt/0OL8e/RUArapwRWo0U/7Mx72gzLmeTadh2TA3vhlqweTmunieV9aTub/kY08Xkxd9TAy2ggLnZzgRw3nn4TtrFj5TJjcr+dEQqt2O6fARjHv3Yjp2FPORo5iOHcOSnu5MfugjI/Hs3x+lTw9yOvlRcWAvQf/7Aex2vCdOJOrll9B4tCwYfzLYSkoo+PhjTEkHCb7tNjz79HYuM1qNjP12LJXWSj6f/jmdtmaQ9e9/o1YbwitubvhMmoTfRRfhNXwYitY1+VJVFVtxMVWZ6byQ9jG/5Ahz5hv73sjt/W9v82BH6ZIlZNz/L7Dbnc/5XXgh4Y//F80JQfJjJcdYsGwBBUaX5uvA0IG8MeEN/Nz9mvV+9ooKUm9YSNXOnSju7rh37YpbbCxunWJx79QJt44dUc1mzBkZWDIysaSnY8nIoHLnTtTKStDrCb7pJoJuXFhnfI2RV5lHobGQLgFd6u3KORup2SkWagjlyxlf8tmuj+n98Gd0ygHLhKH0ffsT5/rGgwc5fvkV2CsrRfLwySfP6uCZqqqULl5M7quv4tmrN6H/uh+3Dh1avb0SUwkzf55JiamER4Y+wmXdL2vVdvYV7OO6ZddRZa3i8u6X839D/6/W8jJzGUeLjxJqCCXSO7LV492ctZmFyxfi7+7PqktXodfUPSe+tuM1Ptz7IVNjp/LS2Jda/V5nK6XmUiZ9P4kqaxXvTX6vjmQYwA+HfuDxTY/TwacDv1/4e5PHh4ScBG5deSsVlopaz0d4RdAvpB/nhZ/H7LjZeOpkoO6fgjUvjyNTpqJWVRH1vzfwnTzZtaywkOPzr8J87BjagAAh5WmzAaCLjCDg8supStxF+UohW+czeTIRTz/lLJSwm80UffEl+e++6yzIqYk2OBjD4MF4jxmD76yZLTovnoks2r2IN3a+AcDzo59nRucZtZYvPraYh9c9jEbR8MGUDzgv/Lz2GKakBRwuOsyNK26kylrFJ9M+oXtg91rLS/74g8z77sctLo64PxbXeb1qt3N06jQsaWlEPPVkvZK79b1GtVrP+t9DSzEfP07V7t34Tp0qC10kp4y16Wu5a9VdWFUrl3a9lEeGPeK8njDZTHx14CsW7V5EmaUMT50nb01864w6Vh8sPMhVS6+iylrFqKhRPD/meXzd/jkxuH+v/ze/Hf2Na3tdy50x80meOxdbXr5YqNdjuPk6Zhs+BI2GNZetccrISiSS9kUmQf4BPLTuITLKMig1l1JiKqHUXOo0aPJx82FCzASmxE5heMTwFidEVLsdFKVFAUBVVTElJVGyeDGlfyzBmp2NPiqKkLvvwnfmzHpleqyFhUIq6+uvUWsYj7t364bPlMn4TJ6Me5cudcbxTdI3PL3laQCeHvU058edD0D5+g2k3XADgLPCu75xfp30NT8e/pFDRYcA0FtVpu1QmbUNDkWofDFBQ06AQoRXBBd3uRiD3sDrCa9jspkI1wTy/OEBeP6wolZg3GzQk+tlJd8b9nXS4j9jJldPuPeUVr+aK8vZuv039llT2UsGhwoPOatLAIYdVrjzFxs6qx3PQYOIeeftOv4wjqSC1te3VrKhtdgrKyn8/AvyP/gAtboDSNUoBF57LaF33onGw4MVx1dw79/3EukZzmdp0yhc9AEAhsGDsZWWYjp0yLk9XXg4XkOHYM3Lx5KVhSUrC9VoBERlaPbADnwSk0xiZ4Wp8TN5cuSTuGnb5sKmdNkyMu67H2w2/C66CI8ePch57jmw2fAcPIjoN95AFyjkYY6XHue6ZdeRV5VH98Du3NzvZh5d/yhlljLi/OJ4Z9I7RHhHNP7dVeujV27ZgsbXl46ffoJHjx7NGqslK4vsx5+g/O+/AXCLiyPiyScxDBxQ7/pGq5GE3AQ2ZW5iQ+YGDhcdBoQB3BMjnjip4POZQEOdYnmLFpH/8iuUecCjt/nxv7mf0TXA5XlU9vffpN96G9jtBN95B8E33dTq38W+/H3sK9hHdkU2WRVZZFVkkV2RTbGpmL7BfZnUcRITOkwg2DO4TT6zyWYivSyd46XHycw4SOjbPxOzLc21gl5P0LXXEnTTTU3K+dXHi9te5LP9nxHnF8cP5/9wUh0cK4+v5J6/70FFZUHvBXjoPDhUeIikwiSnXABAl4AujI0ey9josfQJ7uOsRis3l7O/YD/7CsR3bLPbOC/8PIZFDqOTbycUReG/G//Lj4d/ZG7Xufxn+H/qHceevD1cseQKDDoDa+etrWV+eCaTW5nL+7vfp9hUzPlx5zMqalSrkpef7P2El3e8TLx/PD+d/1O95/xKSyUTvp9AhaWCRVMWOQsO6mNj5kbuWnUXRpuRAaEDiPePZ1feLo4UH8Guus6XwZ7BXN/7euZ2ndviTjnJ2Uf2E09S9NVXePTrS+w339TZzyzZ2Ry/4kosmWL+YjjvPAKumo/PhAkoOh2qqlL0+efkvPgSWCzoo6KIeuVlzGnp5L36KpYMIW/q3rUrgddeizktlapt26navbvW3FIXEkLgNVfjf9lldaRbHdjKyrDm5+MWE3NGddDuyNnBu7veZXPWZgAeGvIQV/a4st51H93wKL8c+YVQz1C+P/97KWN3iqnavRvz8eP4TJ2Kxs0NVVU5WnyUPfl76B7YnR5BDc/jDhQc4MYVN1JsKgYgxieGb2d9W6vLMuPe+yhdsoSghQsJva9+CcqCDz8i98UX0UdHE3TD9XiNHIlbTEytdVSbjaqdOyldvpyy5Suw5ubiOXAAPuMn4D1hPO6dOp38l3EGU7VvH6nXLcBeWopHv75Ev/IK+qio9h6W5DSTU5HDoj2LKDQWEmYII9wrnDCvMMIN4eKxIeykCqC2Z2/n5r9uxmQzMb3TdJ4b/Vy987NiYzEPrnuQjZkb8dR58vbEtxkcPvhkPlqbUGQsYt7iebXiCbG+sbwx4Q06+Z3bxwgQ14/jvxtPobGQD8e+Q8j9r2Pcu1cUJXbsSNkKUXyZ0snAi9NM3D/7hTrFCJLTg/HAAar27MHv/PNPa6Gv5MxFJkH+Acz8aSapZXUNyRWUWh4KPm4+TOwwkfEx4/Fx88Gu2lFRxb2qEu4VTpx/XKvHUWIqIbM8E7PdjNlWfbMYsWVlURXghVljx2QzYbFbMNlMVFgqyK/KJ68yj7yqPHIrc1GKShh3zMDkZG9CknJQbK5giTYoCM8B/TEMGEhVjw6s9c7g+cRXsKt2bu9/Ozf1uwkQCZVjF1yALS+fgCuuIPyxR5sce1Z5FmvT17I2Yy1bsrZgspnQKlrGRo9lbte5jIgc4Qy6HS46zANrH+BIsZDPujl4DoPVWH4pWcuKyh3OjpEIrwiyKrIA8NB6cEWPK1jQe0GzOwGaQ5GxiB8P/8i3B7+t1wAz3Cscb703R4qP0CNV5cEfbBhMUNExhODnnsKvyIx1/0GMe/dStXcvtvx8dJER+F0+j5IpQzhky+BQ0SHyq/LpGtCVfiH96BnUEzetG9aiIuylpWh8fdF6ezv9TVSzmeNffEjp+x+iLxYVwKnBkBWoMPSQ2B9LQg0U3nM5i32Osf3oWl5cFUnoLhGkDVp4AyF33w0aDcZ9+yn56SdK/vgDe0MyYH5+tZaVGGB9T4Wc0d2JHjQGkyr2RZPNhMlmwlvvTe/g3vQO7k2cX1yTrb2lfy4n4957wWbDNn0sG67uj06nZ3xWIJZ/P4u9rAx9VBTR77xNfoSBa5ddS05lDvH+8Xw09SMCPAI4VHSIW/66hdzKXDrbg3je4wqiIrriPWoUik6H0WrkWMkxsiqy6OnTBcsDT1Gxbh0aLy86fPwRnn371hqTqqqklqXi7+5f7/6kqiplS5eS/fQz2AoKQFHwnT0LrxEjsPXozH7PIvYU7iMxN5GE3ARMNpPztQoKWo0Wq92Kl96L+wffz8VdLj5rOyFe3v4yn+z7BJ1Gx7uT3mVoxFDMx49z7PwLUE0mFl/eic9i02p5CTko/Owzcp55FgB9bCyaq+eSPaoL6VXZ5FflMyxiGAPDBjb43iWmEl7c9qKz46wxFBT6h/ZnYoeJDAgdgNlmptJaKW4WcVMUBTetG24aN3GvdQMV0svTSS1N5XjZcVJLU8muyEZFpf9RO7f8YSegAqwa+H2oQqds6J8sfoea4CDC7rsfvwvOb7aHzPHS48z5dQ5Wu7VeaanW8NHej3h1x6v1LgvxDKHAWFArcB7gHkC/kH4cLztOSklKg15BYYYwhkUMY3XaakrNpXww5QOGRgwFwFpQQNWePXiPGIHi5oZdtTP5h8nkVuby1sS3GBM95qQ/16nEaDXy2f7P+GDPB7WMNWN8YpjXbR5zusxpslqv0lLJlqwtrM9Yz9LkpZRZynh8xONc1OWiBl/j8FaZ0nEKL497ud51VqWu4v4192OxWxgZNZJXx73q7PaosFSwJ38PibmJ/Hz4Z+fFdYhnCDf0uYGLu1580gkos82M1W7FTesmvRDOIMypqRydMROsVjp8+ileQ4fUu54pI53Mn74lfNIMPBtI/lft2UPGPfeKLtga6EJDCbnrTvzmzKmVtLabTBj37KFiyxaKv/sea04OABpvbwIun0fAVVehms1UJSRQmZBAVcJOTIcPg6qKTszu3fDo2ROPHj3w6NkLjZcBW3ExtqJicV9cjL2iArfYWDx698KtY8c29eVSVZXtOdt5Z9c7bMveJj6rouPW/reysO/CBl9Xaalk3h/zSC5JpmdQT6bHTqdvSF96BvXEXeuOJSMDXUgIGvfW/eaMViM7cnYQ7BlMnH9cm/7eVFVFRT0rOlJtxcXkvvwyxd//AIA51J/N0zvwdWwWBWYh5aagcGWPK7lz4J11ut/25u/lxhU3UmYuo1dQL4qMRWRWZDIhZgKvjX8NRVFQzWYOjRyFvayMjl9/hWFA/YUt1qIijk2bXks6V9+hA14jhmMYMICqXbsoXbHCVc1cD26xsXhPmIBHz55oDJ5oPD3RGAwonp5ovb3RRUS0ak5otpn5/tD3bMzcSP+Q/syOm11rzlUfqqqiVlZiKyvDVlKKvaxUdIkpCl4jRrR43zXu38/x6xbUum7Q+PkR+dyz9RbMtQVGq5EvDnzBmrQ1XNTlIi6Iv+CM2q+tRUWU/PwLlvR0VIsZu8mEaragms0oWg1+F110yr6b9sBit/DVga94O/FtKq31KzgAxPvHM6vzLGZ2ntnkfloTs83M8uPLeXrz05RbyhkTPYbXxr9WbxeyA5PNxJ2r7nQmQt6Z9A6Dwga16HO1JRa7hZtW3MS27G3E+MTw2PDHeHTDo2RXZOOt9+aFMS8wOrphmfQzkUNFh3h317tY7BbGRo9lXMy4RovP9uXvY94f8/DSGfh+52jKF/+B1t+f2B++Rx8VRclPP5Pz9NPYKyupdIPEKwex4J6PWt1ZllaWxt78vUzqMKnVKi7/NFSrlYJFi8h78y2w2XCLjyPqxRebXTh6NqNarZT99RfFP/5E9GuvovFqeVHjuYxMgvwDWJW6Crtqx8/dD183X+e9u9adxLxE/kz5kxXHV5Bf1fCE18HgsMFc3fNqxsaMbdYEzWQzsTptNYuPLmZDxgasqrUtPhIAXlUqk1L9mJTiTejeLBSzpdZysxbSg8EQGEqXmP5ofH3Q+vhStXs3VTt24N4lntjvv29xRrjKWsX+gv3E+MQ02L1htBp5aftLfHvw21rPKyiMjxnP1b2uZmDoQHbk7OD1hNdJzEsEwEfvw0VdLkKn0VFuKafCUuG8eeg8CDOEiZtXmPOxQW/AXevuvGk1WpIKk/jqwFcsSV7iDGAHegQyNnos3QK70TWgK10DujoD5AcKDvDj4R/ZtfFX7vmynIDa6iT1f0Y9rO2tsHSwhoxgBXezSs9UlX6pGgam6QnPrKq1vsVNi8lDi2Kz4VUhJCxy/OG70Royhncm1r8z1rWbuGJxGYHl4jV/9VfokaoSVQiKuzsRTz2F3+xZdcZiN5spX7Uac0oKurAw9BER6CMj0IWHo3Fzw5iURMkvv1KyeDG2fNd+btRDShgkhykkhyskhylUukNkgUpkIXQo0hJf6klIsYoaHIC9e2d0vXti6NePgE7dqFr1N5UPPYFis7OxrxuvT7ehalwXfmOsnbnh81w8sovBy8Df/bTsD6jA1imaJ674iOBAUVlmPn6czKW/sv+XT+iYUoXjl1Xh586mAZ782r2cnADQ2lTu+cXOkEMqNjcdhv89R+exM5373NbsraxNX8ua9DVkV2SjU3QMjxzO9E7TGR8zvo6hs7Ewn2NP/wflj1W1ni/3gCMRCoejILGzhpL4UEZEjWRk5EiGRgyl1FzKoxseZWfuTgBGRI7g8RGP13sRoKpqqxMkBVUFLEtZxuaszQR7BhPvH09nv87E+8cT7Blc73btqkimmqwmjDahnW2ymZwSgOWWcud9amkqPx7+EYBnhz3JVO/zsOblkfvyK1Ru24bXiOH4vv0KVy+7muSSZGJ9YxkUNogqa1W1LncVvVemMGJ5BoYqEYTP9YNfh2lY3VfBqlMYETmC2/rfRt+Q2omqFcdX8PTmpykwFqCgMCJqBDHeMYR7hRPhFUGEdwSeOk82ZGxgZepK9uTvQbGrhBZDUJmKuwXcrOBmAXcruFvAu0rFrxL8KsC3UsWvAjzNkOcLWUEKmYEKmUGQHaAwbbeW8TtE5XN5VAAF/7oS9549+WL/59jWb+HqlXYiqmX23Xp0x3P8WMq6RZLd0Yd0tZD0snRUVFER5x1OuEGM+5ktz7AqbVWDvhGNYTeZKF28mLJVq/GdNhXfWbNEcEdVeS3hNTZlbqJLQBe6BXSjW2A3ugV0w9/Dn2JjMesz17M2bS3rM9ZTZimrtd0Irwh6B/emV1AvVFQ2Z24mITfB2REJEOQRxMpLVqKx2Sn84kvy33oLe3k5bvFxhD/2GF5DhvDMlmf4Oulr5sTP4b/D/3tGah+rqsry48t5ZfsrZFZkorWpzM3pSK9SXw4UJWG0m1EV0Gp19AjuhX/nbpjio7CFBqJoNGgUDUXGItZnrGdHzg7nd+RuVunq1ZmP5n6Dh5uhwfc/WHiQub/PdQZgB4UNondwb2fX3R/H/uDf6/+NTbUxueNknhv9XIMdeRabhZ+P/MyiPYucSfxQQyjnx51Pr6Be9AzqSYRX84NtqqryzcFveHXHq87EkE7R4aZ1w0PnIe61te8DKhXi3KI4f8yNxPjGNLp9k81EiankrPI0ySjPILkkmUFhg9pFdsyu2jleepykwiQCn/sU3zW78Bo1ig4fLKqzbqWlkl+P/sqXB77keOlxJsRM4LHhjxHkGVTvtm2lpWQ98ihly5ejMRgIvOF6gq69Fo2h4f0XRKFGye+LKfjwQ5d0q6LU66emuLs75TlbgsbHB49evfDs0xuP3n3w7N0LXWRki8+VdtXOpsxNvL/7fRJyEwDQaXRcGH8h1/e5nijvpqvXDxYe5MolVzrniopdZeRBDZdu1RKeaUQN9CdswfX4z7u8RZ2Ba9LW8OzWZ8koF903njpPegT2oHdwb/oE96F/aP8mA4emo0cp+vJLKnckYBg0CL/zZ+PRrx87c3fy5OYnKTIWcX2f67m026W4a90xp6ZSsWUL9pIS7GYzqtksgrUWCyjg3qkT7l274h4fj9av9QVHdrMZS0aGkBlNT0fr749h2LA6craqqlL6++9kPvsMFImgeqkn+FZPj9OD4KfxHhQO7cL+wgOASFQ/MeIJZ6V3Ym4idy69GZ/cckZYOnCt92SKNUZudvuOYncr9w26j2t7X0vFxo2kLrgebVAQXdatbTTJZk5Pp3TxYirWb6AyMRGsda/NND4++EyYgM/UqbjHdaZ8/XrKV62mYutWsFjqbrQGusgIfCZOwmfiRAyDB4FWi8lmcnbzWbKzqdq1G+OB/eiCgvEcM4q/rHt4K/Et5/4C4pppSMQQLoi7gIkdJmLQu367lpxccj/5iLIff0ItLaszBhASd4Hz5xNw+bxm/b+NBw6Qeu112EpK8OzXj/AnHifrkUcx7tkDQOCCBYTec7ezqKsx8irz+HDvh6SXpTM2ZixTOk6pU5Rks9v47ehvvJn4JrmVuc7n+4b05d9D/03PoJ5Nvk9jqKrKqtRVvLf7PaqsVczoNIPZcbOJ9olu1uuNhw5R9PnnlPz2e5PHOd8Z0wn7v/9DF9w2Hcvm1FRsxcV49OrVqi5ri91Cdnk2nnrPJruoHXPPii1bKCzIIDknCbWyEncL+Nrd0IWHk9krjINdPNgfaCTHmEtORY4zpqGgMDh8MLM6z2Jih4kNFjMeKz7GD4d/4Pejvzs7ugaHDeadSe80q9PVaDVy56o72ZS1CU+dJ+9OerfRQqtTydObn+abg99g0Bn4csaXxAfEk1+Vz31/30dCbgIKCvcMuodre117xhfJVVoqeXfXu3y2/zNsqs35vIJCn5A+jI8Zz5joMfi7+9d63ZcHvuSjvR9x38E4hv50ELRaOnz4IV7DhjrXMaelcfDuW9HtE4Wx6HW4x1afh7p2xb1bVzz79nWqRdRHiamE93e/z1dJX2G1WxkXPY5Xxr1y1iZC8qvy2Z69Hb1Gz9iYsaesGMmclkbmAw9StVPEKhRPT9SqKtDrCb37LgKvvRabolJmLsNit4ibTdw74qZBnkH1JidLTCUcKT7CkaIjpJSmEOcfx6zOs86IjnVrURHF3/9A0VdfYc0W105hjz1K4BVXtPPIzixkEkQCiIlYQm4Cf6b8yY6cHc7ApaIoKIiT17HiY84TfgefDszvOZ8L4i6oNSm12q2Um8s5XHyYP479wZ8pf1JuKXcuD/IIcgYb3LXuTvPqOo+1bnjqxMQl1BBKiGcIIZ4hBHkGsTd/L0uTl7IqbZVTS1xnVemcDd3SVbplqHRLF8HAhlDc3Ij9/js8unU7Bd+mi1Wpq/jPxv9gspm4MP5C5veYXyeQoqoqa9PX8vrO151SQyeDTqPDandd0PQM6smVPa5kauzUJitoKy2VrNr8Nf7/9z8C8kxkBsHRCEXcwkUAdcghlenb7cS65utURAfikVmE1l77MGHUg0c910pFXrBlWgf8585lXOdJzrZZm93GvpSt5L30MpGr9rk+U3g40W++iWfvXq34RlyoVisVGzaQ8d2XWNZtRGu2Nf2iBij1BIMJdHZY10vhzVkafDz8GBoxlApLBVuytmBTbXhXqtz3s41eJzZjKQr6DjEoOj3mo0drLUoOg6BS14UywIFOehR3N7onVWDWwvOXaNjTSUO8fzwRXhFsy96G0WZ0rn/ifuCmcWNM9BhGRI0gtTSV3Xm72V+wH6PNSLc0lSGH7HTJFL8jtxOuh/UxMfjOmonfrFm4x4luMJvdxpcHvuSNnW84O2hmdp5JqbmUgqoCcTMWUGoupU9wH2Z1nsXU2KkN6qHazWYq1q3DVFHGLu9CfjVvZW3u5loT0pr4uvkS5hGCvsyIrrQSjzIT7mUmPMst6GygKtU3xL2iiv+Xt1GtvgeDUSQLIo0e6MuMtbaveHjQ+fffcIuJIaM8g/lL5jeYKPYwqUzZqTJ7qx2/6gRihZ87WzpZOR6skhoC0f1GcN3ouwn1DOWZLc+wOnkFgWXQW43ghrAL6eARiaLVgFaLotWh6LSoNjvmlBRMR45QcegAluQUNOa2SyQDBF5zNSH33ONMBquqysbMjfxv6yt0Xp7ExRvsGFwqMdgRyeXDUQr7YxQS4hUqPGtf4GgVLT/M/oH4gHhMR49S8tvvWNJS8ezXD8Pw4XWkC60FBRR9/Q1FX38tOpOq8ezfn7B//x+effo0+/NY7BYScxM5UHCAWL9YegX1qjdIWmWtYmfuTjZnbmZP/h4u6nIR47MDyXnmWdfvUadzBof8LriA9Gsmcv02l8SIgoJOo0OnEYH0aO9ougR0oYt/F3Ef0KXNJMxOxK7aKTIWiW7JqjzyKvPIr8pnfcZ6EnIT8KtQuWCvgWm7FHQFdf0PTqTUUxzrj4WLJFlwKYQXqXQodSOiWMGjtPr3oShofX3R+vuj8fdD5x+Ae9cuePbrh0ffvuhDQ7l66dXOBCmAu9adPsF96OjbkZ8O/4SKyvlx5/P4iMebdfFjtpn5+bBIhuRU5tRa5u/u7wyszomfQwff+r1sys3l/Gfjf1h+fHmT7weiyOLiDXam7VDR2SHfFwr6RNNl0ly6TZmLLkjsU3bVTkJOAr8f+53lKcspt5Rzba9ruWPAHW0mt9hS8qvyMdvMDSaIrHYra9LXiIrrjI2oqPi7+3NF9yuY131eg8doW3k5xt27ce/SBV1ISKvGVmYuY1XqKvYV7COpMImkwiSqrFV0zFF58SNxrF90b3d6j5jNxA4T6ejbkeyKbL5O+pofDv1Aqbn2vhzgHsBjwx9jUsdJ9b6fqqpU7UzELbZjo0GGel9rt1O6ahUZ776JsvcgqlaLR88eeA0chOfAgRgGDkAbFIQlNRXj/v01bgdQLRa0AQFo/f3RBgSg+nqRby/DkJqHcuR4vQFFbWAgHr174dm7Dx69e6MPD0Nxdxc3NzdR0a7VYi8poSwvi/UHlrL14EqMhXl4V4GfUaGnNobOSgi6sirsZWV4DhhA0PULcO/SpdHPmlKSwupjyzEtXk6PpUmEFtZz3vXxJviqqwm4an6j3nWZ5Zk8t/U5VqetJrxQZexRDxSrFaNqQVXArgG7AkZ3hbj+47hk6r2Eh3Wu9b2Xr1lD0edfULFxY53tl4X5sKRrBet6KZR4Qc9UlRGpngxL9cA9q6DO+g2hCwtzeqnpw8PRR4Sji4hAHxGBLjgYa2GhSHKkpWFOT8eSJhIe5vR00Sl04mWxouDRo4foqBg+nHIfHcef+i++u1MASAuG96dpSY9045qkEEauzEFfIfYDjz59KOwTw+aUtViqKnCzQhdDB0JtXhQfOUBwscqJKQ2bh56lfawsHarnhbkfEr1oGUVffonf3IuJfOqpej9zianEKW2qVbRM6TiFwb69MG1PoGLDRqp278a9Szy+U6fiNWxYrYplm93GsZJj7EvdRv7fK/HaeoCQMojQBuJpVbBXVmGvqhJdGDWSKjYfAwlxCkf8quibb6Bzhg3P4qo6Y0sPgp1xCkd7BtBv0mVsy9/J9pztzuUGnYGeQT3RZ+QzZHUmQ3ZWoq+xm6paDTo/f7Q+Pmh8fbHm5jo7uhSDgYBLLiHwmqvRR9Yv4WpMSiL1mmuxlZTg0a8vHT74AK2PD6rZTM5LL1H02eeAmJdEvvB8g75p5eZyPtn3CZ/t/6xWF6Zeo2ds9FhmdZ7F6OjRbMrcxGsJrzlVAyK8IpjUcRI/HvqRSmslCgqXdruUOwbc0SqFgF15u3h5+8u1zsUOhoQP4YL4C5jUYVKta3i73Y6pvJjCzesp+exLlO27ncvyO/qR0ycKb+9A/L2D8fcJJtAvHDU5jcIvvgCbDY2fH2EPPIDfRRe2OvBtPn6cvDffonTxYlBVdKGh+M6Yge+sWXj06llru+XmctLK0jhenExmQQqp1lzSy9JJL08nqyLL2SHcNaArIyNHMjJqJANCBzjPzdb8fAq//prCr75CLSpu1vi0QUF4jRyBdshAEjXp/F20ja3l+6h0h6rqS+xosw/xtiA6mL2JNHoSUKmwyy2HH0KPY3QX4w8zhHFRl4u4tte1tf4HTVEzEWLQGXh38rsMCK2/6+tU4fB/A3h9/OuMCx6GtbAQt+hoLDYLz2x9hh8Oia63MdFjuHPAnXQLPLXxltayOnU1z2591qnMManDJHoE9WB16mr2Fuxt8vUDjth56AcVRVUJe/QRAq+sKz1pMlXywl3DmbbZjLex7jYUd3eCbrqRoOuvr9W5ZrFZ+Pbgt7y7+11KTCUElqrE5SgkdFYZ32kyL4x9odHuoVNFqbmUo8VHKTOXiaJCczllljJRsKv1INgzmBCDiNmFeIag1+hJyE1ga9ZWtmZvdR7zQCT9b+x7I7M6z2qzZIiqqpT88is5Tz2FvaICjbc34Y89iteoUWQ9+pjTN66kVwzPTC4j2bO80e0FuAcQbAgmxDPEKWGZW5VbZ71Aj0Dm95jPZd0vO62+OHkVufyw8zMSE/9k7DYjfROK0FrEyVETGEDgvHn4z5tXy/tYIpMgkhbguBD9/tD3lJlF1Y2Pmw9hhjBKzaWUm8vrbRsN9wpnVudZzO48m87+nessby1Gq5F1GetYmryUHTk7nFXag8MG0zekL26Z+ZhSUrCXlWErK8NeWoatrBR7eQXe48aettZdxyS4qSpLu2pnWfIytuVsw0PrgbebN146L7zcvPDSeVFprSSnMoecihznfW5VLkarsVZFM4jq1skdJ3NFjyvoF9KvxZNR1WIRQWm9rVZAu8hYRIghhC7+XQg8kEnR519QvnKVy3Q9Kgp1cF8yugeyPdpEoYcNP503/jZ3/M16fC06fOxudBs6jZDAxiuRKjZtIuuZZ9CHhhL1/PNtVl3k/IxWK+aUFGfQwnjgAMb9+1GNRtxiO6KPjaUi3I/0QJVDniXYM7PxP5ZHaEoJEVkmdNUXX3sHBpJ//xWMiBlF76DezurwQmMhfx3/i6XJS0nM3M7w/Xb6FXozwRKPejQFW2GhazA6HV5DzsN7wkTcx47ks4Kl5JVmMvCQnQ5/H0S/Y7/rglunJeWhy/g5NI1t2dtqdVeFe4UzNnosY6LHMCR8CJkVmSxLXsbS5KWklKbU+z34uPnQN7gvfUL60De4L739euBxPIeqXYlU7dhB2d9rhJF6Ne49ejh/O/aKCkqKs9l9fCumsmJKDJAYp7Crk0KlR919TqfoGBU1iplxMxkeMZwCYwHZSTux/rwEv5UJuNVIRNgVyPaH0khffDt3xVZVhbkgD6W4FLdSI76V4F1FncDASaHXow8JQRcWRtCNC2sdI9LL0ll8bDEaRYOH1gMPnQeeOk88dZ74ufsR4xNDsOJD6Y8/U/DBB86L75oUG6DER4NfuR3/ZnRb1Yfi7o4+MlJIT3h4oPHwEPfu7mj9/dAGBaELCkIbGIguOBiNpyfm9HTMySmYk5OdN21wMOGPPoLXsPp9GxzHo4/WvUqn7Zl0yVDpnqkQUmyvvZ5GITXOh+3dNKyOrSTPx86NkZdwRUYHSn/7HeP+/XW2rQ0OxmvYMAxDzsO4Zy8lv/7q1OPXhYfjPXYsJb//7tzv/C64gJB770UfdmomcOb0dHKff56yFX+J8QUGEnrfvXhPmEDe669T/O13oKpofH34dZIPX3TJqdXx1RihhlBmdJrBnPg5LZaTLDWXklGWQXp5Oull6WSUZzjvM8oz6hz3AeIzVGYkwIgkFY1V/K+0wcF4jxuLotGCake12cmvzCO9KAXvzGICM8rrJLBbiy4iAm3v7hyJ0bOmu5X1VXspNBbWWueybpfxf0P/r8VyH2abmSXJS0jMTWR/wX4OFx+ulejVKBqmxk7lhj431PLvSSpM4r6/7yO1LBWdouOeQfcwt+tcLHYLRqsRs82M0VZ9b6qA35bj8fEvaErFj9SmUep8P+bOkRREeLFHl0OyZzl5fpDnp5DvCxa9QvfA7jw/+vlmz3ksNgtpZWkklyRTai4lwCOAAI8AAj0CCfQIxKAzOLuirKrVKeFYairlYNFBkgqTOFB4gKSCJAqMIhDso/ehW2A3p9dAB58OrMtYx8+HfyavKg/FrtIjTaVHkYFj3pWkhihUBHhwYdeLuLrn1UT7RGMrLaV89WpKl/1Jxfr1oqJep8Nn/Hj8L70ErxEjmlWlm12RzRf7v+CHwz84i1dQVTplw4jDGsbuV/AvMrOhh8Lrc1zb6+DTgczyzDoFOD0Ce/Dk5iedfm2zOs/ioSEPtYmcaKGxkI2ZG9mYsZENmRsorCogqBTKDCI5PihsECMiRzAicgTx/vGNzq/q+9xeuDPaEsvgQn86ZdnxPpoNR1NRbK0vymgK73HjCFp4A54DB9Yar72qiqo9e6jctq2WDJji50PR7JEs7W+ncPVK5myyEeX4GXt6EjB3Lj4TJ+A5YIAzaGOxWfh0/6e8l/guXY5WMXM7DDxiP3Eo9WIM9MKvex8MsaLjwJJaXTWiKHhPmIDPpEkcWfEjunU7cLe4fot2nRaN1fW92TRg7tWZ4E490XsYUNzcqm96VLMF09EjmA4dxpqVdRLfpkBjMKCPjkYfFUVV+nFsh4/Vu55ZBz+N0pI/ZyTTu85mQswEDHoDtrIyCj76iMJPP6s1x2rw/Xx9cO8ch1unThgPHMCUlAQIKcttfT0YmemDPTeP6LffxmdC9RxNtXO46DDrMtaxLn0diXmJtaQjQQR4JneczLRO0xgYOhCNoiGvKo+UkhRSSlNILknmcNFh9hbsdf12T2BI+BAW9l3I0PChqEYj5Rs2cOi3L2H9Nrwq6+7XNgVSQyE90p3AAhPd00Bb4xCrGAzoIyOwBfqR4VHJPjJJdSune7rK0CRXQigpCn4drmFvRwWTHkZGjeL+wfcTHxCParFQunQpBR986PQPVLUaSvt1orRjEEVRvuRHGsgLdsMjPY/pr2zBrdwIPbvS6aOP8fB3JU2NViMpv32D7ek30FSIazpLdCj6IQMJGjWeoBFjsPt48d3Bb/lm/Tv4ZhQTkw/9ygKI1AWxPbCEDQH5JIeDVafgrnV3dl75uvlyY98bmdd9Hm4aN3Irc3l5x8ssTV7q/P9c3PVi7KpdSJ9aK6myVlFprSTII4hY31hi/WLp6NuRDj4dyK3M5bWE11hxXPgReGg9uKrnVXT278yvR35ld8pmumTY6Z6m0jVbg1+VgofRjqfRjpcRNDX+D3YFtnRTWHKehoNRiI64EwjyCKJzjsK8XwqJyRTzuEOdPfh9RiAV3jrQKKiKBlUBtBo6R/bi4m6XMChsUK1jkSU7m/y336H4p5+cSTSNwYC9xm+jMsKfI4PCKbCXocspwK/ARGixSnCpKEg7Fga7OiskdtZwKAr0bp6YbKZakqjeigeTrF3psyad7jty0VdPIfJ9YXUfhWIfhb4xQ5jW80K8fYPQeHhgOnSI8nXrqdi8ucnfqp2Gr0vMOkjrHULIzAsYeOGN6L1dfj6q3Y6toABLdjYaT0/c4uIaPLcYrUbuWHUHm7M246ZxI8onCg+t65rEU+dJjE8MEzpMoG9I31ZJqzkq4k9M0CTkJHD98uux2q3c3v925lf1I/OBB7Hm5uLeJR6fKVPxmTqFX+wJPL/1eee5e3LHydzc7+Zac7P6UFWVUnMpmeWZZJZnkl2ZjYKCQW/AoDNg0Bvw1Hmi1+idXrfOm7kEnaIjwjuCKO8oIrwiiPSOxMfNx7ndYlMxRcYiioxF/HzkZ1anrQYg0iuSR0OvofOSPdgrynGLi8MYHUKiVz7L1b1sKUwUc25VdOJ7GxXCiuzc/4MNT5Md/0suIfyJxxv8n936162sS19LcCkMLA9mYFkQnfI1BBwvglTR/abERMI9C6ka3I30snTe2/0ex0uPE5WvMj/Bi4GJFSg2G8nhCm/M1tBn8HSeHf3saZF1NdlMrElbwx/H/mBdxrp6rz9aQreAbuRV5TmvD6K9o0UyJG5WqxI79ooKTMeSMScfo2zFCuf1nOegQUQ+/zxu0aIr1mQ1sfqdfxO2aAkeZpUKd/hppIb9sVoyw93Q6dycHTYlppIGCzFB7DPxAfFEe0fzd9rfTvleg87AJV0v4aqeVxHmFdbiz1IfqqpiOnyYys1bqNy2FXNaOqbiAswlxeiqLHWOOcfCYOlgDZt7aYkI6Mh9g+9jXMy4NhnLuYJMgkhaTKWlkl+O/MKXB76s12sEwM/djwkxE5gdN5tBYYPOKG3TcxGb3YbJZnIGcwx6w2nLQpvT0zHu3YtHr151zBXPNlRVFRrfTWh1200mqg4cwJKXi9+EiU0GgXIrc9mavZXhEcOdVenWggJMhw5hKy/Ha8iQRlv1zekZlPz0ExUbN4rg/IQJgDhBr01fS6GxkGERw+ga0LXeCZiqqhwsOsjS5KXszttNZ7/OIukR0pdY39hGf5/2ykrKVq2mdPFiytevr1c2oc77aTTY+nTBbdRw3EcNZ2PFXlYlr+BY4WE0KmjsEJurMmmnSp/jrlNLgY+4EOlQoOBpbN4pR1UU8PVG4++HJjAAXUAgWncPNIoGRVWrW0GqPS58vNH6+qH1FZWCWh9R0a4LDUUXGoLW379N2rbtZjPlf/+NKSkJ46FDVCTtx56RhXJi4aibaLPXh4aiGDzBZke12cBqFfeqij4mBvf4eNzj43CPj0cfHd1qA/bWYLFbSCtNI8gzCD93P6z5+UJScOdOytesdQYXHGg7dsCWlg726kCLTof3qFF49O1DVcJOKrdvRzXWLYXy6N2bwOuuxXfKFBS9HktOLnmvvELJr8IvRVRyzkUbEIii1wkjYp0ORa/HLToajz59GjQwrolqsWA6coSq3Xuo2rMb4+49mI4cEePVagmcfyXBt92GtsYcomr3brL/+7gzoaONjETfqzuabnFo4jthj4/FGGggtSyVw0WHxa34MKmlqbUuvvuG9GVO/BymxU7Dx80Hi81CVkWWs3LxxGTHiVXv9RHoEUiwRxAD0/SMXJ5J2CFXt5Jnv34EzJ+P79QpjWoQ200mTAcPYty3j6q9e7FkZqKPiMStQwfcOnZA36EDbh06oHF3x1ZSIjwOqu+t+fnidbt2Oz0SnOh0eI8bh2n6KBI7w86C3XTx78I1va5x/s5UsxlLVha28nLUykrszlsVil6He3w8bnFx9eq6m21mDhcdZl/BPlanrWZ9xnrnsnEx41jYZyFJhUk8v/V5zHYzUR7hvBBwHeF7skGrQRcSgi40VCQ+Q0IwHUsm94XnMR0WVWpucXGEPfQghsGDObT6V/Yu+xKvxKPE5jZ+bCr1Usj1VSnw19Kp2xD69J6APjIKfVQU+qhISnRmEnIS2JW3i+SSZFKKjmHOyCA830pkoejESwuG46EK+X7iGOemcUOjaOoEdOpDowhZs5oJIucyu5CtHHvYnWGHwL20dkV2hTukhUBaiIZYozedD5Whtbner9LXDUOpqzWsItBA8pg4ssZ1J7hjd2J8YojxiSHKOwq9Vs/BwoN8su8TliUvw6pa0VtVxhaFM/m4H9GJmejzip3b0gYG4vPxm6xVD7EydWWtJL9DinVM9BhnoYHZZubdXe/y4d4Psat2Qg2hXN/7emyqjWJTsTMwUmouRVVVZ9eW46ZRNFRZqup4K2VVZNX6jg06A/1C+nG05GgtyRoQAcBewUKarUdgD3oG9STMEEZSYRKf7v+UP5P/dH6GSK9IUTBkqVt1qLeqdMyBuGyVuCyVTtkq3kbQW6tlD62u4KRFC2WeYPZywzs4gpCIzrgHivNXzZui01L8w4/CnLX6d+nZvz9+cy7AnJxMZcJOjAcO1Dqn60JDCVxwHQGXXOLUjz5YeJA3tr+GafVaLtxop3ON/L5VryEtzpekzm7siDIRklbGjO12Ymo0TXqNGoU+IgLVbgOb3ZmILco5TsWhJHxL6gZTVG8DVdNHkjd9MEWBetZnrGdt+lrczSoz0oK5JDkU3Y59YLeji4wgs084PwYeY1NEubPS2kPrgb+HPwHuIqHo7+6Pl94Lg86Ar0VHUFYFfuklGI+nUJ6RgntBGUGlEFgmAvJ2RcxHcvwVyoMNeMfGEdi5B/kBWlK9TaRqisipyiW7IptiUzF+5Sp9U1T6pKj0TVYJLIcj3Xww3nUV44df3mBXoDU/n6JvvsVWXIzGwx3F3YNUczZLM1eSq5YS0rUv9130Cp4h4a7jpqpSsX49ue+/h2nbDtfGPNzJ++El9pQfZE/eHnbn73YWrTmI949nVNQoqqxVLE9ZTpGpyLkswD0As93cYLLDU+dJr6Be9AnpQ8/AnmzK2sRvR35z7uN9g/syO242Px/5mf0F+9HYVQbkGLgqvysdLX7kx/iyL9zMWkM6u8sPYVWtuGvdubrDxVxa3BX7hm2Ur1tXu0ioHtQRg/BaMJ/goaOx2q21pGI0ioa5XeayoM8CkkuS2Zq5hYI1K+m/IoXex+seO60akTxzt8KRcHjqci1mg55Y31iCPINIK01zHhNCi1RuWmqn1/HanTl2ICdEi0+Zrd5Kb+d6Og0pEVr2RVhRdVoGajsRZw2E/EKseXnYSkrEnDQ4iAofN/bY00h3K6fCQ8FWPU6bRnRT2TTi+OBhBg+LiodZyJ/qbQomnYpJr9AxtAuDOo7Exy8ES0YGlQk7MCUddM3PGqDcAzYP8mL/uFg8ooVMa6ghFKPV6PSWSy1LpcRUwzfFrjJjm8pla+24N3KZYNVAgS9UBHji1yGejl0Ho680U/z9985imPx+Hfhjsh+bPTLodKCYkftVBh9WG93uiSjeXngNH4E9JIC840lUZaahyy/Bt8xe6393OAKWDNVxfEAEnYLiuaXfLfQJqb/7WDWbqdyZSMX6dVRu34GtpMRZaFlrXqvVYAvwxRRgoNxHT4mnStSxMgxZrt+a4umJ15Ah2KuqsGRlYc3OFkUG1bjFxeE7cwZ+M2fi1rFjnbFUWau4a9VdbMra1Oj3EOIZwviY8UzsOJHzws9rMsBcUFXAZ/s/45ukb6i0VuKp8yTII4hgz2CCPYNJyE2g0FjIlOiJPJAYQ+EHH9YrFekWF4dt7Hn86XGUNWUJlHpCuSeM6DaF6/peDwrORIfjllGRQWZ5ZoPHn9Zi0BmEF1w9kuw6RcctQXOYtqqEiiXL6v0sKAq6sDBUsxlbWVkdOUDPQYPo+HHjXh8JOQk8teUpjhQdqT2HU1VGHFC5eqXdKQW+qbvCpxM1BJXCpVu19DvomnM5JDjNWvhqnAbNpbN5avTTbS7Pq6oqRaYikgqSWJqylL+O/1Vr7hLhFUGARwA+eh98dF6E/n97dx4fVXn/C/xzZp9JZiaZbJMJ2VgjhEWWhLhA7zVlcWmt9haRVupVWit6XVrbalVqX/1dKra3vGr9lVd7b7W/tqjl/qq9pWKLUaFKkJ0AgQRCYkKSyT6ZNbOc89w/DhkcSCCxQBY/79frvCbMOTN5Tki+c87zfZ7v49Mgs1tGNNKHbtmHLsWLTtmLTrkXEY2CicYczLYWoThpEqaa8mCOadAX8mNfyx5UNu9CMBqARgCphhTkZRfBkp6FpAwXUpx5SHNORKotE6KzC7HWVsit7ZDdbsitbQg31CNW/zF0nZ6E9ssa4OAXitDz5cXItecj15qLJl8TfnX4V2gNtCKrW+Dbb2lR0HTuZ6tJSoL52mthmTcXplmzAK0GPm8nej3t8Pu6EPB2QdZpkD59DgpmL4ItPTv+2qgSxdv1b+PlYy/jZHctkvoAWxDosWsQ02shSVL82lyCWmlHA03C8w6TAznJOXAlu5CT5EJerx5p1a3AgSPQHjwOjWfgso/9FJMBoflFOPJf8/FRei9O9NTEB0X9+vO/Rpmr7DL8ZowfTILQpyYrMg51qJlxq8EKm96GZEMykg3JIzI9j4iurFhPD3x//wdChw5BMhmhTU6GJilJ3SwWhOtOw79jx7k66kOgSEDT9DS0ls+C5voFKM6ahTkZc6B0diFSV4fwqTpEzzRBk5Sszm5wpELrSIPWkQqdw3G2s2f0L26sBIM4fXgnWptO4NrpN8HkyoE2NXXU18q9lMjHH8NX8S58FRUIHTiQ0Nlm+8JtsC1fnlA6RYlEEDp0CIHKSoT27lNrdn/tqxeMUO4XqqpC27/9T4QOH754QyQJhokTYZ41C+ZZM2GcOhWx7m7EWloQaW5GtKUF0ZYWRE7XD5iESbquDFlPPjlo2Rghy+h59TV0bNwIxX9hJ6bWblfrzcqxeDJLyDJkSaDbLqHBHESHTaDDLqE31QCt1YqecA8UocTLtgGAXj631oshBqRIFiQnO6BMzodl2jXIceRjQvIE5FhzkGHOQKRyLzr//d/Vnz0ASa+H7eabkfrVr8I8s/jiP7PLTPYH0Hf0KEKHD8P/7rsJ/2e6rCzY7/gSDDk5CNfXI3L67KykpibgUiPgtVoYCgtgOltDWWOxQOkLQ/SF4o9CVuBJ1aNCVGNbrAqtqQJRvQRdTO2U/GKzE8XHg1CGUPJCa7cj/X88jNQVKy6ILe6AG1t2/wZnPvgHpgRtmClnI8srQWl1I9rckjBqdTB+k9q56kmSkO4VyPIgoazLJ4UMwMcZQFOmBK9ZjZdCktSyQpJa9tCpSUGWZEc6kmBXTEiOagBZQQgR+JQQvEoQHtmHUDiA6Q0yLIFPzJ6x22G59lpEm88gXN8wYJK7KR3YXSRhd5EGTelAbidw0yEFi46KhA4/d4paJq/WJaFuggb+/Az0etsx9YzA9CaBBW3JyGkKQYqe+x6SxYLkG26A9fPlSF68OCH56I14sc+9D65kF4ocRYP+PA93HMbTHzw96GzHT2Na6jRcn3M9bsi5AXMy5kCv1UMIgdO9p/Fh84fY1boL+937E0pQ9rMZbAkJzBJnCVbPWI0bcm4AoJaeOtJ5BEc6j6CqowpdoS61s96UGu+wTzWmIhQLoT3UjvZgOzqCHejwuxGLhHFdwWLcPX0VSp2lQ/r8iDQ0oOu3L6P3zTfjnYyfpMvMhHnuXCTfeCNst90KzSAdOXvde/Hzff8Lmj1VuKFa/btyDFJFQmOxwH7HHXB8dRUMBQWDtk0IgfeOb8Ub//gFtA0tcHULtKRJ+GC6hLAh8dx0Gh3un3k/7p95P4xaI2JdXVCCQXVggCQhGA3iD8f/gN9X/z5eb384NJIGs9Jn4brshZhvnIZauQX/bNuFfe598VH7g5EgocBegKLUIkx1TEVR6jRMNeYhM+PCzsuhCkaDONJ5BHOz5l70nurUh2+hcsP3MLcmhu3XSvg/yxI7w0xaE0qzS3Fjzo24YcINCevExJQY9rj34O36t/FO4zvxhIlG0mBC8gQU2AtQYCvARPtEFKcXD7i4fau/FS8fexl/PvnnhJ+TWWfGPdPvwT0z7hlwUFYwGkRtTy0mWCckJIiEoiBSX6+Ws2pvR7S9HbH2DsTa26FNSUHqqrthmnrhaPJGbyN+vv/neKfxnUF/VtcHXChpS0aGuw+OZh9szeooWgDoLnDgd2vycSRcP2Ci0mqwotBWiHxbPrT+EHSHa5FR3YrJp0MJST+h0cBQkA/T5Clq6U+DAaHDhxE6eBByT88F7zsS9BMmwDx3LvzTJkA406C3p8JoT4XBlgpTShrMyfYhrTfQG+5Fs78ZMSUW79gVzW7oNr4CzYFjatJTUdQBSUNQnQu8uliLmtzEv/1McyYmGVwordNg6lEPzBYbkvImwjGxCMn5k2CYMAGSXo9AZaU6Y+ODDy76s1b0WgRLpkN395eQVbIYmUmZ//JoehGNQvb7AUVRr+3PG0wnhED4xAl4t70N77ZtiDY1XfgmkgRdRgZkjychVpuKi2G7+WaYZsyANjUFurOlFqHToaanBr6IL75WYf8soUPth7DzzM6E32WrwYrrXNdhYfZClLnKEmJBR7ADLx97GVtqtqifa/3/ZwN8xiyUC/D9t4yIHFXLVqd85StIX7sWgcpd8L39dwQ+/DAhoXM+v0ndfGbAZ5YQMKtfhwz9CT4JRoMZySY7ks02RJKM6DULdFsUdJmi6DTFEJKisBltsBvssBltSDGmwGawIaJE1KSKrxl9rc1IOdMLVzcQNKrXXUGHBXJGKqy2dEyLpGHFbi3E1nfi16HWpUthmXstwnWnET5dh8ipOsgez4UnoddDa7PBdM01cP1k/ZCrVXgjXhzpOILDHYdxqP0QjnQegT/qhyUMrPxQg/K9EWgVIKaVoJPP/R9Yy8uRtuZ+6LKcaP3BDxD4QB30cyRfwqkHl+H7X/gpZCGjzlOH413HcaK1Cp0f18AZs6BASkeOYkdmzAJrnwTh9SHW60G4pwvhni7IvR4Inx99ViPOFCThWI7AnkwvGpKC5/7/hcBkKRNf0C9AmZwPR3sIkYYGdfu4ccBri6vNkwQ0pwHNaRIq5mhQ7xz4+ijTnIlvzv4mbi+4Df4//Sf8O3cidPDggPd2F6NzOmGcMgXGyZMhYjF1nbDmZoSaPoYmeO7asNMKtDoktDrUx3Y74LVI8FrU3/uAWb2uz/AIzGgUKG5QH9POy3mEdcCJCRKOFkhoyARCZg1mF16HL85dhZkFCwe8dusMdaKmuwazM2ZfsC7sZx2TIEREdFlFmprg37ET/h07ENyzR7040ukgaTTqLAadDhqbFfZbb0Pqf/sy9DmXXryVRr9YZyeCBw/CNG3aoPWyPw0hBHzbtiGwd696YxWNQcRiENEoRDiMcF0domfODPn9NFaruiDxTDVhYpo5c8i1UmWfD6GqKnWWz4kahE8cR/h0/aU78i8HvR7GKZNhnjEDhkmT4N22DX2H1ZrdksGAlK98BWn33we98+KLDV8t4ZMn4fm//4nev/xl4JvIsySzGVqbDRqLJb5JFjNEMIS+2loovb2DvvZiOmxAUlhdC6if1m5H8uc+B02SBbGODrVzrUPdACD17pVIf/DBT7VoshACSm8voi0tCJ85g48ObsXRY+/B4ZGR0SuQ0QtYBxslbDTAmF8AQ0EBJJMR4ZOnEDl16qIdCZ+WNiUF1s+Xw7pkKZIWlsYX+RWRCML19QjX1sJ9ZA88mj74y4oRzs1ATMQgKzKiShSykBFTYpBDIaTuPoHMdw4j5XjLBd8nolVLlGjOu3vQZqQjedEiWMvLkVRWFl+P6F8RioXwm6rfoLqrOt4xYjfa1Y4Row0SJMSUGGIipj4qMShCgVlnjpfZ6P86JzlnSGv5hOUwqruqUd1VjeNdx1HdXY3TntOQhayut1CwBKtnrMaMtH9tLbN+QgjIQv7UnXWxjg50//4PCB04AOPUqeqIx7nXDmtBdiEE3m16F3vde2HVJ8PZHkPWMTesVQ3QV9VCn5aOtK+ugv2OO4Y0My/eNiWGN0+9id8e/S18ER+sBmt8sxlscJgcWFm0ckglBYUQCMVC6O7rhifsiT/29PXEZ/wEogEEY+qjw+SIdwwOVE4tFAthr3sv/nnmn2j0NSLdnA5nkhPOJCeyLFlwJjkxIXnCsOr6X25vN7yNH7zzBKJagfyUQszKmIWZ6eps3ympU4Y0MC0qR3G06yjsBrW853AX3e0MdeI/qv8Du5p3YYFzAe6fef+A63Fdafvc+/DCvhdQ3VUNV5ILpdmlKMkuQYmzBJmWxM95IQRira2INKprlmnMZggh4A64cdJzEj19Pci15qLAXoBU48CDVvwRP5oaquA/WoUpU8tgm3rNgJ1RQghEGxsRPHgQfVVHAI1GnYV8diaiLjMDWnsK5F4P5M5OxDo7EevsQqyzE4rPp84OlmMQMTn+tWQwQmMxq5+ZZgvCRglRLWATJiihIEQoFF+rRZuSAsu8uTDPnQt91uUp0TJUQghAUQeHyF1d6G2sw75D21Bz4gPA3QFzBNhZrJbSLbAXYk7mHMzJmIPi9GLkWnOH/bclZBl91dVqMsTvh96Zra7548yG3pkFrcNxyRn/V5IQAn3HqhE6sB/aVAf02U51LaLMTEh6PWSfD753KuD9298QqKwc9PpSY7NBl5oKXVYWdM4s6LOc0GVlqeeYlgYlyYzD4TpUdO9GhXvnBaVJ86x58dHhb5x8AxElAlNY4J6aTPyXyiB0fVFIeTmI5mYi4EpBd6YZsseDyX/8ECIYgsZuR/aPfgTb0iUJ7yv7fPC/9x5871Qg2tKizh72eIbdyXwxGqtVHQiXlgZdmgNah/oo+/zxWfgXu3bUpqRACQTi11hJi25ExiOPwDzjws/rWHc3oo2N6rWq3Q6tzQbJbL48lQOEgrAchklrgiRJ6DtxAu7nfqQu5q3Xw/6F25B2330wTvzEullCwPPaa2j5yU+gCUcQNAIH51ih9wSQ1qsg3YuLros7VN3JQEuOCdnRJDjaQ5D8g7+ppNdDn5cHjckEEQlDCUcgwmF1i0YhmdU4pfnEo2QwqOtgaiRA0kCGAnfAjYi3F5peH3S+EMy+CPQx9SKyfxZZp01C19nNl26Gku+CedIUZGVPQp41D9lJ2egJ96DJ24Qm37lNQGBl0UqsmLbiggXMhSwjXFuL4P4DCB3Yj77q44BOC43ZopadtpihMVugBAMInzqFWMulS2pKJtOAg+4uoNEAFhNw3s83ppXQkGdA/aRkNE6xo7MwBTqTGSatCRPtE7GiaEVCIpOGh0kQIiK6YoQQY362A41+sa4utUxXVRX6Dlch0tAAbXo69C5XwmYoKIChIP+y3gAr4TAiDQ0QsRiks8k+dYF7LZRwGLHW1nMzUZpb4GusgxIKQa/RQYf+UbvqJZakN5xd68UIyWCEZDJB8XrRd+wY5AFu6CSTCakrVsBx338ftYveKZEI/BUV6P1/f4UI98EwcRIMhQUwTpwIw8SJ6o3/IDFCCIFYezvCNTUI19YifPKkekNlMp9bD+dsJ3rkTBMiH3+MSH0DFO+5kfi6jAy10//zn4dl/vx4p//53weyfNlnldX21OKne3+KQDSAazOvxXzbDMyIZsHc5UOsowO6LCcMhYXQu7IvHDkajarrVtXUIlxbq84yUWQIRQEUoZYVEkK9SUuyQGNRZ+RpkpIg6XRnE4UR9SY/pnaema4pgqWk5LKfp+z1qiXmDh9C6NBhBA8fgvCqw9j0ubmwzJ8Py/x5sMyfD31e3rj9TOiL9aHOU4d0c/plqwU9VvCzfmS1+FuQpE+6LOvijHVCCPijflgNQ0/E0dUnhEBVZxX2ufeh8Gzyw2FyXPqFnyGxri54//53+N+pQNTthtzTow4qGWa3nGQ0Qkk2o3OiA3sLZPwtqxUd1nNl0cx9AveeyMKiD3qh8V26HJVlwQK4NjwPfXb2JY/tJ6JRyF4vYj09UHp71bKqPZ5zSZJgUC2bGE/0yede090Fuasbse7uC8pRDUqng7GwEIbJk6AEAoi1uhFtaYESOHd+lvnzkfHYo7DMmzfk87jShKIguGcvDIUFF01YRhoacOyRb8JUM3BpesVkQMRmRsAsoccQQ5e+D71GGX4z4DdJCJgkaOw2GFPSkOTIRL7fhPyGIBy1bdCfbLpwZrAkQZ+dffY+6uxWWKi2Mzv7ipRqFkJABIOIBQPQpTqgGSWVH2SfD+GTpxA+eRLhU6egMRrOlrw9u7lc0JjNiPX0nJ0t87H6WN+AmNuNmKcHcncPFN8npntotTDPnAnLwlIklZaqa65dhkFCNLArmgR56aWX8MILL8DtdmP27Nl48cUXUVJSMujxW7ZswTPPPIOGhgZMmTIFzz//PG6++eYhfz8mQYiIiGi8EUIg2tyCvmPH0HfsGMK1tTBOmQzH6tVDnob/WSGEgOzxIFJfD0lvgGnG9BEd9flZ1D/qWTKZoc8anck5IiKisUbIMmSvF3JPjzpjqK0dsTY3ou42xNraziVLfD51QMggXXjRQhfqp6cihChm7TgTH+lvyM9H2gMPwDyzWC1fWt+AyOnTCNefhtzdg5Q770Tamvuv6vqE/YQQULxexLq6IXd3JTzGujqhMZpgLJqmzkifNGnAWVmyz4fo2ZH8xqlTxnTyXsRiOPLyRoQa6pFeWISMwukwnB30pbHZEs5NVmS0BFrQ3deNTHMm0i3pg84SVPr60HfkCPpqaqHLyFATHvl57JS/zEQkgtjZJKDelQNtctJIN+kz44olQV5//XXcc8892LRpE0pLS7Fx40Zs2bIFNTU1yBxgtOKuXbuwaNEirF+/Hrfeeis2b96M559/HgcOHEBx8dDqWjMJQkREREREREREn1VCUaAEAlC8XkTb2xHcvRv+HTvVNdvO69ozTJqE9AcegO3m5SOS4CAiulquWBKktLQUCxYswC9/+UsAgKIoyM3NxcMPP4zvf//7Fxy/YsUKBAIBbN26Nf7cwoULMWfOHGzatGnA7xEOhxEOnyv27PV6kZubyyQIERERERERERHRWbGeHgQ+3AX/jh2Qe3qQ8uU7YV2yhLNmiegzYahJkGFFxEgkgv3796O8vPzcG2g0KC8vR2Vl5YCvqaysTDgeAJYuXTro8QCwfv162O32+JabmzucZhIREREREREREY17utRU2G+9BTkvbEDe//4NbMuWMQFCRHSeYUXFzs5OyLKMrPMW88nKyoLb7R7wNW63e1jHA8CTTz6J3t7e+NbU1DScZhIREREREREREREREUE30g0YiNFohNFoHOlmEBERERERERERERHRGDasmSDp6enQarVoa2tLeL6trQ1Op3PA1zidzmEdT0REREREREREREREdDkMKwliMBgwb948VFRUxJ9TFAUVFRUoKysb8DVlZWUJxwPA9u3bBz2eiIiIiIiIiIiIiIjochh2OazHH38cq1evxvz581FSUoKNGzciEAjg3nvvBQDcc889yMnJwfr16wEAjzzyCBYvXoyf/exnuOWWW/Daa69h3759+PWvf315z4SIiIiIiIiIiIiIiOgThp0EWbFiBTo6OvDss8/C7XZjzpw5ePvtt+OLnzc2NkKjOTfB5LrrrsPmzZvx9NNP46mnnsKUKVPw5ptvori4+PKdBRERERERERERERER0XkkIYQY6UZcitfrhd1uR29vL2w220g3h4iIiIiIiIiIiIiIRtBQ8wbDWhOEiIiIiIiIiIiIiIhorGAShIiIiIiIiIiIiIiIxiUmQYiIiIiIiIiIiIiIaFxiEoSIiIiIiIiIiIiIiMYlJkGIiIiIiIiIiIiIiGhcYhKEiIiIiIiIiIiIiIjGJSZBiIiIiIiIiIiIiIhoXNKNdAOGQggBAPB6vSPcEiIiIiIiIiIiIiIiGmn9+YL+/MFgxkQSxOfzAQByc3NHuCVERERERERERERERDRa+Hw+2O32QfdL4lJpklFAURS0tLTAarVCkqSRbs6o4fV6kZubi6amJthstpFuDhGNQ4wzRHSlMc4Q0ZXGOENEVxJjDBFdaYwzgxNCwOfzweVyQaMZfOWPMTETRKPRYMKECSPdjFHLZrPxD4CIrijGGSK60hhniOhKY5whoiuJMYaIrjTGmYFdbAZIPy6MTkRERERERERERERE4xKTIERERERERERERERENC4xCTKGGY1GrFu3DkajcaSbQkTjFOMMEV1pjDNEdKUxzhDRlcQYQ0RXGuPMv25MLIxOREREREREREREREQ0XJwJQkRERERERERERERE4xKTIERERERERERERERENC4xCUJEREREREREREREROMSkyBERERERERERERERDQuMQlCRERERERERERERETjEpMgY9hLL72EgoICmEwmlJaWYs+ePSPdJCIag374wx9CkqSEraioKL6/r68Pa9euRVpaGpKTk3HnnXeira1tBFtMRKPdzp07cdttt8HlckGSJLz55psJ+4UQePbZZ5GdnQ2z2Yzy8nKcPHky4Zju7m6sWrUKNpsNKSkpuO++++D3+6/iWRDRaHapOPP1r3/9guubZcuWJRzDOENEg1m/fj0WLFgAq9WKzMxM3H777aipqUk4Zij3SY2NjbjllltgsViQmZmJJ554ArFY7GqeChGNUkOJM5/73OcuuJ554IEHEo5hnBkaJkHGqNdffx2PP/441q1bhwMHDmD27NlYunQp2tvbR7ppRDQGzZgxA62trfHtgw8+iO977LHH8Ne//hVbtmzBjh070NLSgjvuuGMEW0tEo10gEMDs2bPx0ksvDbh/w4YN+MUvfoFNmzbho48+QlJSEpYuXYq+vr74MatWrcKxY8ewfft2bN26FTt37sQ3vvGNq3UKRDTKXSrOAMCyZcsSrm9effXVhP2MM0Q0mB07dmDt2rXYvXs3tm/fjmg0iiVLliAQCMSPudR9kizLuOWWWxCJRLBr1y787ne/wyuvvIJnn312JE6JiEaZocQZAFizZk3C9cyGDRvi+xhnhkHQmFRSUiLWrl0b/7csy8Llcon169ePYKuIaCxat26dmD179oD7PB6P0Ov1YsuWLfHnjh8/LgCIysrKq9RCIhrLAIg33ngj/m9FUYTT6RQvvPBC/DmPxyOMRqN49dVXhRBCVFdXCwBi79698WO2bdsmJEkSzc3NV63tRDQ2nB9nhBBi9erV4otf/OKgr2GcIaLhaG9vFwDEjh07hBBDu0966623hEajEW63O37Mr371K2Gz2UQ4HL66J0BEo975cUYIIRYvXiweeeSRQV/DODN0nAkyBkUiEezfvx/l5eXx5zQaDcrLy1FZWTmCLSOiserkyZNwuVyYOHEiVq1ahcbGRgDA/v37EY1GE+JNUVER8vLyGG+I6FOpr6+H2+1OiCt2ux2lpaXxuFJZWYmUlBTMnz8/fkx5eTk0Gg0++uijq95mIhqb3n//fWRmZmLatGn41re+ha6urvg+xhkiGo7e3l4AgMPhADC0+6TKykrMnDkTWVlZ8WOWLl0Kr9eLY8eOXcXWE9FYcH6c6ffHP/4R6enpKC4uxpNPPolgMBjfxzgzdLqRbgANX2dnJ2RZTvgFB4CsrCycOHFihFpFRGNVaWkpXnnlFUybNg2tra147rnncOONN+Lo0aNwu90wGAxISUlJeE1WVhbcbvfINJiIxrT+2DHQdUz/PrfbjczMzIT9Op0ODoeDsYeIhmTZsmW44447UFhYiLq6Ojz11FNYvnw5KisrodVqGWeIaMgURcGjjz6K66+/HsXFxQAwpPskt9s94PVO/z4ion4DxRkAuPvuu5Gfnw+Xy4Wqqip873vfQ01NDf785z8DYJwZDiZBiIg+45YvXx7/etasWSgtLUV+fj7+9Kc/wWw2j2DLiIiIiD6du+66K/71zJkzMWvWLEyaNAnvv/8+brrpphFsGRGNNWvXrsXRo0cT1k0kIrqcBoszn1yrbObMmcjOzsZNN92Euro6TJo06Wo3c0xjOawxKD09HVqtFm1tbQnPt7W1wel0jlCriGi8SElJwdSpU3Hq1Ck4nU5EIhF4PJ6EYxhviOjT6o8dF7uOcTqdaG9vT9gfi8XQ3d3N2ENEn8rEiRORnp6OU6dOAWCcIaKheeihh7B161a89957mDBhQvz5odwnOZ3OAa93+vcREQGDx5mBlJaWAkDC9QzjzNAwCTIGGQwGzJs3DxUVFfHnFEVBRUUFysrKRrBlRDQe+P1+1NXVITs7G/PmzYNer0+INzU1NWhsbGS8IaJPpbCwEE6nMyGueL1efPTRR/G4UlZWBo/Hg/3798ePeffdd6EoSvzCn4hoOM6cOYOuri5kZ2cDYJwhoosTQuChhx7CG2+8gXfffReFhYUJ+4dyn1RWVoYjR44kJFy3b98Om82G6dOnX50TIaJR61JxZiCHDh0CgITrGcaZoWE5rDHq8ccfx+rVqzF//nyUlJRg48aNCAQCuPfee0e6aUQ0xnznO9/Bbbfdhvz8fLS0tGDdunXQarVYuXIl7HY77rvvPjz++ONwOByw2Wx4+OGHUVZWhoULF45004lolPL7/fHRSYC6GPqhQ4fgcDiQl5eHRx99FD/+8Y8xZcoUFBYW4plnnoHL5cLtt98OALjmmmuwbNkyrFmzBps2bUI0GsVDDz2Eu+66Cy6Xa4TOiohGk4vFGYfDgeeeew533nknnE4n6urq8N3vfheTJ0/G0qVLATDOENHFrV27Fps3b8Zf/vIXWK3WeG19u90Os9k8pPukJUuWYPr06fja176GDRs2wO124+mnn8batWthNBpH8vSIaBS4VJypq6vD5s2bcfPNNyMtLQ1VVVV47LHHsGjRIsyaNQsA48ywCBqzXnzxRZGXlycMBoMoKSkRu3fvHukmEdEYtGLFCpGdnS0MBoPIyckRK1asEKdOnYrvD4VC4sEHHxSpqanCYrGIL33pS6K1tXUEW0xEo917770nAFywrV69WgghhKIo4plnnhFZWVnCaDSKm266SdTU1CS8R1dXl1i5cqVITk4WNptN3HvvvcLn843A2RDRaHSxOBMMBsWSJUtERkaG0Ov1Ij8/X6xZs0a43e6E92CcIaLBDBRfAIiXX345fsxQ7pMaGhrE8uXLhdlsFunp6eLb3/62iEajV/lsiGg0ulScaWxsFIsWLRIOh0MYjUYxefJk8cQTT4je3t6E92GcGRpJCCGuZtKFiIiIiIiIiIiIiIjoauCaIERERERERERERERENC4xCUJEREREREREREREROMSkyBERERERERERERERDQuMQlCRERERERERERERETjEpMgREREREREREREREQ0LjEJQkRERERERERERERE4xKTIERERERERERERERENC4xCUJEREREREREREREROMSkyBERERERERERERERDQuMQlCRERERERERERERETjEpMgREREREREREREREQ0Lv1/Oh9NDG375Q4AAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#Find most traded stock with Pyplot"
      ],
      "metadata": {
        "id": "zO1F_w-3RMaT"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "aapl[\"Volume\"].plot(label=\"Apple\",figsize = (20,5))\n",
        "amzn[\"Volume\"].plot(label=\"AMAZON\",figsize = (20,5))\n",
        "csco[\"Volume\"].plot(label=\"CISCO\",figsize = (20,5))\n",
        "ford[\"Volume\"].plot(label=\"Ford\",figsize = (20,5))\n",
        "\n",
        "\n",
        "pyplot.legend()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 478
        },
        "id": "r-S8MT_GRSm-",
        "outputId": "04ff6249-c63d-45d9-f54b-d3c3156a49cb"
      },
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.legend.Legend at 0x7d150839bf70>"
            ]
          },
          "metadata": {},
          "execution_count": 36
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 2000x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#Find Stock trends with moving averages\n"
      ],
      "metadata": {
        "id": "7WhhizYpTA8x"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "aapl[\"MA50\"] = aapl[\"Close\"].rolling(50).mean()\n",
        "\n",
        "aapl.tail"
      ],
      "metadata": {
        "id": "YKPvh5gTTD3t",
        "outputId": "9b09ce3b-e4d0-48d3-cce7-c0eeb49deac9",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<bound method NDFrame.tail of                           Date        Open        High         Low  \\\n",
              "0    2022-02-01 00:00:00-05:00  174.009995  174.839996  172.309998   \n",
              "1    2022-02-02 00:00:00-05:00  174.750000  175.880005  173.330002   \n",
              "2    2022-02-03 00:00:00-05:00  174.479996  176.240005  172.119995   \n",
              "3    2022-02-04 00:00:00-05:00  171.679993  174.100006  170.679993   \n",
              "4    2022-02-07 00:00:00-05:00  172.860001  173.949997  170.949997   \n",
              "..                         ...         ...         ...         ...   \n",
              "246  2023-01-25 00:00:00-05:00  140.889999  142.429993  138.809998   \n",
              "247  2023-01-26 00:00:00-05:00  143.169998  144.250000  141.899994   \n",
              "248  2023-01-27 00:00:00-05:00  143.160004  147.229996  143.080002   \n",
              "249  2023-01-30 00:00:00-05:00  144.960007  145.550003  142.850006   \n",
              "250  2023-01-31 00:00:00-05:00  142.699997  144.339996  142.279999   \n",
              "\n",
              "          Close   Adj Close    Volume    Market Cap        MA50       MA200  \n",
              "0    174.610001  173.602448  86213900  1.500208e+10         NaN         NaN  \n",
              "1    175.839996  174.825348  84914300  1.483877e+10         NaN         NaN  \n",
              "2    172.899994  171.902313  89418100  1.560167e+10         NaN         NaN  \n",
              "3    172.389999  171.613632  82465400  1.415766e+10         NaN         NaN  \n",
              "4    171.660004  170.886917  77251200  1.335364e+10         NaN         NaN  \n",
              "..          ...         ...       ...           ...         ...         ...  \n",
              "246  141.860001  141.860001  65799300  9.270463e+09  139.268399  139.268399  \n",
              "247  143.960007  143.960007  54105100  7.746227e+09  139.153599  139.153599  \n",
              "248  145.929993  145.929993  70492800  1.009175e+10  139.106599  139.106599  \n",
              "249  143.000000  143.000000  64015300  9.279658e+09  138.965799  138.965799  \n",
              "250  144.289993  144.289993  65874500  9.400291e+09  138.875799  138.875799  \n",
              "\n",
              "[251 rows x 10 columns]>"
            ]
          },
          "metadata": {},
          "execution_count": 40
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "aapl[\"MA200\"] =aapl[\"Close\"] .rolling(200).mean()\n",
        "\n",
        "aapl.tail"
      ],
      "metadata": {
        "id": "xGVHrUxNTWWK",
        "outputId": "30c171a4-f6e8-47ee-ed01-d35062c66bd7",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<bound method NDFrame.tail of                           Date        Open        High         Low  \\\n",
              "0    2022-02-01 00:00:00-05:00  174.009995  174.839996  172.309998   \n",
              "1    2022-02-02 00:00:00-05:00  174.750000  175.880005  173.330002   \n",
              "2    2022-02-03 00:00:00-05:00  174.479996  176.240005  172.119995   \n",
              "3    2022-02-04 00:00:00-05:00  171.679993  174.100006  170.679993   \n",
              "4    2022-02-07 00:00:00-05:00  172.860001  173.949997  170.949997   \n",
              "..                         ...         ...         ...         ...   \n",
              "246  2023-01-25 00:00:00-05:00  140.889999  142.429993  138.809998   \n",
              "247  2023-01-26 00:00:00-05:00  143.169998  144.250000  141.899994   \n",
              "248  2023-01-27 00:00:00-05:00  143.160004  147.229996  143.080002   \n",
              "249  2023-01-30 00:00:00-05:00  144.960007  145.550003  142.850006   \n",
              "250  2023-01-31 00:00:00-05:00  142.699997  144.339996  142.279999   \n",
              "\n",
              "          Close   Adj Close    Volume    Market Cap        MA50       MA200  \n",
              "0    174.610001  173.602448  86213900  1.500208e+10         NaN         NaN  \n",
              "1    175.839996  174.825348  84914300  1.483877e+10         NaN         NaN  \n",
              "2    172.899994  171.902313  89418100  1.560167e+10         NaN         NaN  \n",
              "3    172.389999  171.613632  82465400  1.415766e+10         NaN         NaN  \n",
              "4    171.660004  170.886917  77251200  1.335364e+10         NaN         NaN  \n",
              "..          ...         ...       ...           ...         ...         ...  \n",
              "246  141.860001  141.860001  65799300  9.270463e+09  139.268399  139.268399  \n",
              "247  143.960007  143.960007  54105100  7.746227e+09  139.153599  139.153599  \n",
              "248  145.929993  145.929993  70492800  1.009175e+10  139.106599  139.106599  \n",
              "249  143.000000  143.000000  64015300  9.279658e+09  138.965799  138.965799  \n",
              "250  144.289993  144.289993  65874500  9.400291e+09  138.875799  138.875799  \n",
              "\n",
              "[251 rows x 10 columns]>"
            ]
          },
          "metadata": {},
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "amzn[\"MA50\"] = amzn[\"Close\"].rolling(50).mean()\n",
        "\n",
        "amzn.tail"
      ],
      "metadata": {
        "id": "uP_tALAoThn9",
        "outputId": "f8bd0a8c-6e48-421d-a384-0d2a6d5e7515",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<bound method NDFrame.tail of                           Date        Open        High         Low  \\\n",
              "0    2022-02-01 00:00:00-05:00  150.000000  151.707993  147.627502   \n",
              "1    2022-02-02 00:00:00-05:00  155.050507  155.074997  148.863495   \n",
              "2    2022-02-03 00:00:00-05:00  141.737503  144.247498  138.332993   \n",
              "3    2022-02-04 00:00:00-05:00  155.606506  161.199997  150.608002   \n",
              "4    2022-02-07 00:00:00-05:00  158.520004  162.690994  157.250000   \n",
              "..                         ...         ...         ...         ...   \n",
              "246  2023-01-25 00:00:00-05:00   92.559998   97.239998   91.519997   \n",
              "247  2023-01-26 00:00:00-05:00   98.239998   99.489998   96.919998   \n",
              "248  2023-01-27 00:00:00-05:00   99.529999  103.489998   99.529999   \n",
              "249  2023-01-30 00:00:00-05:00  101.089996  101.739998   99.010002   \n",
              "250  2023-01-31 00:00:00-05:00  101.160004  103.349998  101.139999   \n",
              "\n",
              "          Close   Adj Close     Volume    Market Cap     MA50  \n",
              "0    151.193497  151.193497   59220000  8.883000e+09      NaN  \n",
              "1    150.612503  150.612503   87330000  1.354056e+10      NaN  \n",
              "2    138.845505  138.845505  225532000  3.196634e+10      NaN  \n",
              "3    157.639496  157.639496  253456000  3.943940e+10      NaN  \n",
              "4    157.935501  157.935501  102624000  1.626796e+10      NaN  \n",
              "..          ...         ...        ...           ...      ...  \n",
              "246   97.180000   97.180000   94261600  8.724853e+09  91.3290  \n",
              "247   99.220001   99.220001   68523600  6.731758e+09  91.2976  \n",
              "248  102.239998  102.239998   87678100  8.726601e+09  91.3726  \n",
              "249  100.550003  100.550003   70691900  7.146244e+09  91.4048  \n",
              "250  103.129997  103.129997   66527300  6.729902e+09  91.5250  \n",
              "\n",
              "[251 rows x 9 columns]>"
            ]
          },
          "metadata": {},
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "amzn[\"MA200\"] =amzn[\"Close\"] .rolling(200).mean()\n",
        "\n",
        "amzn.tail"
      ],
      "metadata": {
        "id": "TMfHNmzOTmdo",
        "outputId": "a4887039-2969-44bb-ade1-b2c3543b0f85",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": 42,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<bound method NDFrame.tail of                           Date        Open        High         Low  \\\n",
              "0    2022-02-01 00:00:00-05:00  150.000000  151.707993  147.627502   \n",
              "1    2022-02-02 00:00:00-05:00  155.050507  155.074997  148.863495   \n",
              "2    2022-02-03 00:00:00-05:00  141.737503  144.247498  138.332993   \n",
              "3    2022-02-04 00:00:00-05:00  155.606506  161.199997  150.608002   \n",
              "4    2022-02-07 00:00:00-05:00  158.520004  162.690994  157.250000   \n",
              "..                         ...         ...         ...         ...   \n",
              "246  2023-01-25 00:00:00-05:00   92.559998   97.239998   91.519997   \n",
              "247  2023-01-26 00:00:00-05:00   98.239998   99.489998   96.919998   \n",
              "248  2023-01-27 00:00:00-05:00   99.529999  103.489998   99.529999   \n",
              "249  2023-01-30 00:00:00-05:00  101.089996  101.739998   99.010002   \n",
              "250  2023-01-31 00:00:00-05:00  101.160004  103.349998  101.139999   \n",
              "\n",
              "          Close   Adj Close     Volume    Market Cap     MA50       MA200  \n",
              "0    151.193497  151.193497   59220000  8.883000e+09      NaN         NaN  \n",
              "1    150.612503  150.612503   87330000  1.354056e+10      NaN         NaN  \n",
              "2    138.845505  138.845505  225532000  3.196634e+10      NaN         NaN  \n",
              "3    157.639496  157.639496  253456000  3.943940e+10      NaN         NaN  \n",
              "4    157.935501  157.935501  102624000  1.626796e+10      NaN         NaN  \n",
              "..          ...         ...        ...           ...      ...         ...  \n",
              "246   97.180000   97.180000   94261600  8.724853e+09  91.3290  113.688355  \n",
              "247   99.220001   99.220001   68523600  6.731758e+09  91.2976  113.412153  \n",
              "248  102.239998  102.239998   87678100  8.726601e+09  91.3726  113.167743  \n",
              "249  100.550003  100.550003   70691900  7.146244e+09  91.4048  112.916555  \n",
              "250  103.129997  103.129997   66527300  6.729902e+09  91.5250  112.654500  \n",
              "\n",
              "[251 rows x 10 columns]>"
            ]
          },
          "metadata": {},
          "execution_count": 42
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "csco[\"MA50\"] = csco[\"Close\"].rolling(50).mean()\n",
        "\n",
        "csco.tail"
      ],
      "metadata": {
        "id": "rOfgTQSvTrYD",
        "outputId": "39303434-d0fd-4622-febe-09f422d4de55",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<bound method NDFrame.tail of                           Date       Open       High        Low      Close  \\\n",
              "0    2022-02-01 00:00:00-05:00  55.450001  55.500000  54.740002  55.369999   \n",
              "1    2022-02-02 00:00:00-05:00  55.230000  56.320000  55.169998  56.169998   \n",
              "2    2022-02-03 00:00:00-05:00  55.869999  56.150002  55.060001  55.200001   \n",
              "3    2022-02-04 00:00:00-05:00  54.889999  55.619999  54.389999  55.150002   \n",
              "4    2022-02-07 00:00:00-05:00  55.330002  55.529999  54.700001  55.169998   \n",
              "..                         ...        ...        ...        ...        ...   \n",
              "246  2023-01-25 00:00:00-05:00  47.980000  48.080002  47.230000  47.980000   \n",
              "247  2023-01-26 00:00:00-05:00  48.150002  48.470001  47.830002  48.340000   \n",
              "248  2023-01-27 00:00:00-05:00  48.099998  48.730000  47.970001  48.509998   \n",
              "249  2023-01-30 00:00:00-05:00  48.139999  48.500000  48.119999  48.220001   \n",
              "250  2023-01-31 00:00:00-05:00  48.119999  48.689999  48.049999  48.669998   \n",
              "\n",
              "     Adj Close    Volume    Market Cap     MA50  \n",
              "0    53.573200  22438500  1.244215e+09      NaN  \n",
              "1    54.347244  23316700  1.287781e+09      NaN  \n",
              "2    53.408722  19260500  1.076084e+09      NaN  \n",
              "3    53.360340  19675900  1.080010e+09      NaN  \n",
              "4    53.379692  14450200  7.995296e+08      NaN  \n",
              "..         ...       ...           ...      ...  \n",
              "246  47.980000  14638700  7.023648e+08  47.8664  \n",
              "247  48.340000  12952700  6.236725e+08  47.9374  \n",
              "248  48.509998  13414200  6.452230e+08  48.0128  \n",
              "249  48.220001  19261900  9.272679e+08  48.0792  \n",
              "250  48.669998  16821600  8.094554e+08  48.1648  \n",
              "\n",
              "[251 rows x 9 columns]>"
            ]
          },
          "metadata": {},
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "csco[\"MA200\"] = csco[\"Close\"].rolling(200).mean()\n",
        "\n",
        "csco.tail"
      ],
      "metadata": {
        "id": "z00xJcXiTx9l",
        "outputId": "26c41f96-8f63-4839-e03c-fe350db01293",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": 44,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<bound method NDFrame.tail of                           Date       Open       High        Low      Close  \\\n",
              "0    2022-02-01 00:00:00-05:00  55.450001  55.500000  54.740002  55.369999   \n",
              "1    2022-02-02 00:00:00-05:00  55.230000  56.320000  55.169998  56.169998   \n",
              "2    2022-02-03 00:00:00-05:00  55.869999  56.150002  55.060001  55.200001   \n",
              "3    2022-02-04 00:00:00-05:00  54.889999  55.619999  54.389999  55.150002   \n",
              "4    2022-02-07 00:00:00-05:00  55.330002  55.529999  54.700001  55.169998   \n",
              "..                         ...        ...        ...        ...        ...   \n",
              "246  2023-01-25 00:00:00-05:00  47.980000  48.080002  47.230000  47.980000   \n",
              "247  2023-01-26 00:00:00-05:00  48.150002  48.470001  47.830002  48.340000   \n",
              "248  2023-01-27 00:00:00-05:00  48.099998  48.730000  47.970001  48.509998   \n",
              "249  2023-01-30 00:00:00-05:00  48.139999  48.500000  48.119999  48.220001   \n",
              "250  2023-01-31 00:00:00-05:00  48.119999  48.689999  48.049999  48.669998   \n",
              "\n",
              "     Adj Close    Volume    Market Cap     MA50     MA200  \n",
              "0    53.573200  22438500  1.244215e+09      NaN       NaN  \n",
              "1    54.347244  23316700  1.287781e+09      NaN       NaN  \n",
              "2    53.408722  19260500  1.076084e+09      NaN       NaN  \n",
              "3    53.360340  19675900  1.080010e+09      NaN       NaN  \n",
              "4    53.379692  14450200  7.995296e+08      NaN       NaN  \n",
              "..         ...       ...           ...      ...       ...  \n",
              "246  47.980000  14638700  7.023648e+08  47.8664  45.83005  \n",
              "247  48.340000  12952700  6.236725e+08  47.9374  45.80035  \n",
              "248  48.509998  13414200  6.452230e+08  48.0128  45.77850  \n",
              "249  48.220001  19261900  9.272679e+08  48.0792  45.76050  \n",
              "250  48.669998  16821600  8.094554e+08  48.1648  45.74310  \n",
              "\n",
              "[251 rows x 10 columns]>"
            ]
          },
          "metadata": {},
          "execution_count": 44
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ford[\"MA50\"] = ford[\"Close\"].rolling(50).mean()\n",
        "\n",
        "ford.tail"
      ],
      "metadata": {
        "id": "3vvvZt3bT9E0",
        "outputId": "4e3c6ce7-d565-41c9-abc7-56925f411569",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<bound method NDFrame.tail of                           Date       Open       High        Low      Close  \\\n",
              "0    2022-02-01 00:00:00-05:00  20.610001  20.850000  19.920000  20.660000   \n",
              "1    2022-02-02 00:00:00-05:00  20.809999  21.049999  20.180000  20.629999   \n",
              "2    2022-02-03 00:00:00-05:00  20.170000  20.620001  19.870001  19.889999   \n",
              "3    2022-02-04 00:00:00-05:00  18.520000  18.590000  17.520000  17.959999   \n",
              "4    2022-02-07 00:00:00-05:00  17.730000  18.120001  17.700001  17.889999   \n",
              "..                         ...        ...        ...        ...        ...   \n",
              "246  2023-01-25 00:00:00-05:00  12.600000  12.850000  12.490000  12.790000   \n",
              "247  2023-01-26 00:00:00-05:00  12.990000  13.070000  12.710000  12.920000   \n",
              "248  2023-01-27 00:00:00-05:00  12.880000  13.370000  12.870000  13.270000   \n",
              "249  2023-01-30 00:00:00-05:00  13.010000  13.200000  12.860000  12.890000   \n",
              "250  2023-01-31 00:00:00-05:00  13.390000  13.570000  13.250000  13.510000   \n",
              "\n",
              "     Adj Close     Volume    Market Cap     MA50  \n",
              "0    20.110569  117651800  2.424804e+09      NaN  \n",
              "1    20.081366   95377600  1.984808e+09      NaN  \n",
              "2    19.361046  103016000  2.077833e+09      NaN  \n",
              "3    17.482370  211100500  3.909581e+09      NaN  \n",
              "4    17.414232   84610000  1.500135e+09      NaN  \n",
              "..         ...        ...           ...      ...  \n",
              "246  12.790000   37739000  4.755114e+08  12.9234  \n",
              "247  12.920000   48970900  6.361320e+08  12.8918  \n",
              "248  13.270000   62066500  7.994165e+08  12.8760  \n",
              "249  12.890000   64512600  8.393089e+08  12.8478  \n",
              "250  13.510000   83093300  1.112619e+09  12.8400  \n",
              "\n",
              "[251 rows x 9 columns]>"
            ]
          },
          "metadata": {},
          "execution_count": 45
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "ford[\"MA200\"] = ford[\"Close\"].rolling(200).mean()\n",
        "\n",
        "ford.tail"
      ],
      "metadata": {
        "id": "nKrV35MNUB8F",
        "outputId": "fc0f58a9-71fb-4e81-a1cd-866efe7220b2",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": 46,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<bound method NDFrame.tail of                           Date       Open       High        Low      Close  \\\n",
              "0    2022-02-01 00:00:00-05:00  20.610001  20.850000  19.920000  20.660000   \n",
              "1    2022-02-02 00:00:00-05:00  20.809999  21.049999  20.180000  20.629999   \n",
              "2    2022-02-03 00:00:00-05:00  20.170000  20.620001  19.870001  19.889999   \n",
              "3    2022-02-04 00:00:00-05:00  18.520000  18.590000  17.520000  17.959999   \n",
              "4    2022-02-07 00:00:00-05:00  17.730000  18.120001  17.700001  17.889999   \n",
              "..                         ...        ...        ...        ...        ...   \n",
              "246  2023-01-25 00:00:00-05:00  12.600000  12.850000  12.490000  12.790000   \n",
              "247  2023-01-26 00:00:00-05:00  12.990000  13.070000  12.710000  12.920000   \n",
              "248  2023-01-27 00:00:00-05:00  12.880000  13.370000  12.870000  13.270000   \n",
              "249  2023-01-30 00:00:00-05:00  13.010000  13.200000  12.860000  12.890000   \n",
              "250  2023-01-31 00:00:00-05:00  13.390000  13.570000  13.250000  13.510000   \n",
              "\n",
              "     Adj Close     Volume    Market Cap     MA50     MA200  \n",
              "0    20.110569  117651800  2.424804e+09      NaN       NaN  \n",
              "1    20.081366   95377600  1.984808e+09      NaN       NaN  \n",
              "2    19.361046  103016000  2.077833e+09      NaN       NaN  \n",
              "3    17.482370  211100500  3.909581e+09      NaN       NaN  \n",
              "4    17.414232   84610000  1.500135e+09      NaN       NaN  \n",
              "..         ...        ...           ...      ...       ...  \n",
              "246  12.790000   37739000  4.755114e+08  12.9234  13.38000  \n",
              "247  12.920000   48970900  6.361320e+08  12.8918  13.36935  \n",
              "248  13.270000   62066500  7.994165e+08  12.8760  13.35930  \n",
              "249  12.890000   64512600  8.393089e+08  12.8478  13.34695  \n",
              "250  13.510000   83093300  1.112619e+09  12.8400  13.33695  \n",
              "\n",
              "[251 rows x 10 columns]>"
            ]
          },
          "metadata": {},
          "execution_count": 46
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#Visualize stock moving average with PyPlot"
      ],
      "metadata": {
        "id": "w7tUVcBpUY1I"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "figure, axes = pyplot.subplots(2,2, figsize=(20,10))\n",
        "\n",
        "aapl[\"MA50\"].plot(ax = axes[0,0])\n",
        "aapl[\"Close\"].plot(ax = axes[0,0])\n",
        "\n",
        "amzn[\"MA50\"].plot(ax = axes[0,1])\n",
        "amzn[\"Close\"].plot(ax = axes[0,1])\n",
        "\n",
        "\n",
        "csco[\"MA50\"].plot(ax = axes[1,0])\n",
        "csco[\"Close\"].plot(ax = axes[1,0])\n",
        "\n",
        "\n",
        "ford[\"MA50\"].plot(ax = axes[1,1])\n",
        "ford[\"Close\"].plot(ax = axes[1,1])\n",
        "\n",
        "\n",
        "\n"
      ],
      "metadata": {
        "id": "9U_-IwI0UcRD",
        "outputId": "d20c4ff2-3ab4-40b3-879e-af45aec61a25",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 848
        }
      },
      "execution_count": 52,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 52
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 2000x1000 with 4 Axes>"
            ],
            "image/png": 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11VeVkJCgrKwsZWVlqbjY3NyTlJSkGTNm6M4779SXX36pNWvW6LrrrtPo0aN16qmnBnj2DWRdc9irpIqSwM4FAAAAIY1Aib9YgZKOg6T2jqySujIVqiqlYz+a5e4NDJQUHpVkl2zhriwSSYqIkqIdafXVy285S29lSMldzXLOHjPW1Z9EkpK7SeFR5iLGyh4pzZfKC13nrqzwfqxkgivv3WyyWDqfIo25rV4/ps99Sja9Y8Zh013rhk+Xrv1QSupqMmck6YLHTLCksrT+2TAAAABAE3jqqaeUm5urM888U+np6c7HG2+4+uz94x//0Pnnn69LLrlE48aNU1pamt55550AzrqRImJdy+XFgZsHAAAAQl5EoCfQaliltzoOktr3lg6ur9ms3V3ObqmqXIqIkTqPNOsKj5gskfDI+r2mVXYrLlUKC/fc1qadCUgUZUtyZG3Y7Z6BkghHL5D6BkrCws3Pdvh706ekbTdXNokk2StNI0YrAFPdtk+lnUukyDbS1Kel8Hr++lkZJUX1CJQUHZMOrDXLmed5but+mnTTN9LXj0oxSaY/yjePS0c2m54lbbvXbz4AAACAn9nrUXoqJiZGTz75pJ588slmmFEzCI8wN2JVljlKALc74SEAAABAUyCjxB8KDjvKQtlMM/L2jsBEXRklRx3b2vVyBDocwRErWFHf15WkBC+BDWdD92zXuuLjrh4kiZ1cAY38A6afSl2N3C3teprRKitWfb51ld86vNmM/S9wZd3Uhy+lt35cJMkudRjg2eDeEpMojb9fGnuHKetllf6qK6gFAAAAoGlEtjFjWVFg5wEAAICQRqDEH6yyW+17SVFt3AIlO2o/xvpiPqW3FBbm+lLfl4budWWAeAuUWNkkbdpLkTEmIBIRY2oC5+0/cUaJZHqbSK4slOrzzamjhJX1+kmda9/HG18CJTu+MGOvs+t37vZ9zFi9QT0AAACApmcFSsoJlAAAACBwCJT4Q5bVn2SgGevTo8T6Yt76ot4ZKPGhT4kzsOElA6SuQElihhltNrc+Jbvrl1GS7AiUWD093Etvua/3pvrr15f1s5yoR4ndLu340iz3Oqt+505x/PcnowQAAABoflEESgAAABB4BEr8wb0/ieTKKCk4JJXkeT/GCpSkVA+U+JBRkm8FSryUmPIaKNlvxsROrnXuDd2tnifeSlZZnBklVqCkeumtugIl+2q+fn3UN6Mke7t5jfBoqeuY+p3bmVFSR1ALAAAAQNOIdDR0J1ACAACAACJQ4g/RCaZclRUoiUmS4hxZGce8lN/6/j1p99dmOW2wGRPSzdigjBIvpbJi25qx+Jhr3QkDJfUovVVbRknbHo71dfQocWaUNFGgxCq71W206860E7Gyf/IPSKUFvs0LAAAAQOM4S28VB3YeAAAACGkESvzhvEeku7dK/Sa71tXWp2T/GumdX5rlU25wletqUI+SOkplOTNK3AMlXkpfeQRK6lF6K8mxf8EhqbzElYXS+WTHeWrJKKkodQU6GhwoOUHpLV/7k0hSm3au/1Z1lUrzIreo3Kf9AQAAAFRDM3cAAAAEgYhAT6BVsdlcy+17SXuWSh//Rtq7QuowQDq+S1r3qlRRLPU+V5o427V/gzJK6iiV5WvprWM7XYGMujJK2rQzFzPlRZ4N4DudLG2cazJK7HbP/xaSK0gTEWPO4Yu4FDMWHvF+bkmqKJN2fmWWe9azP4mlfR/z3yl7u5QxrF6HlJRX6pxHF6t/eoJ+cXpPjeuTIpu3eQEAAACoHc3cAQAAEAR8yii5//77ZbPZPB6ZmZnO7WeeeWaN7TfeeGOd57Tb7brvvvuUnp6u2NhYjR8/Xtu2tYLG2kOnmWBF0VFp5bPSB7dL3zwmFR42QZOf/lcKd4tT+ZpRYrfXM6OkjmbukpTc3YxZGyV7lSSb1Cal9te12dz6lLhloXQ6yYzlhVLx8ZrHub+2rwEFK1BSUSKV1VIea/N889pxqa4SaPWV4sj+OVr/37vVu47rWGGpvtp2VNf8d6UmPrZE32w/QcYLAAAAAE9RlN4CAABA4PlcemvgwIE6ePCg8/H11197bL/++us9tj/88MN1nu/hhx/W448/rqefflorVqxQXFycJk6cqJKSEl+nFly6nybdtUWa/pY0bLrUZ4IptTX5Yem6j6SYRM/9fc0oKStw3XXlLQOkeqDEbpdyHRklSZ1d+1kZJRWOC5O4FM8AjjdWn5Ljblkoyd1cfVm8NXT3ls1SX1FxUmScWfZWfuvAOmn+rWZ5+FVSmI+/1lZD9+z6B0rG9knR4lln6een9VBcVLi2HirQ9P+s0P3zv1NJeaVvrw8AAACEKmcz98LAzgMAAAAhzefSWxEREUpL81LqyaFNmzZ1bndnt9v12GOP6Q9/+IOmTJkiSXrppZfUsWNHvfvuu7riiiu8HldaWqrS0lLn87y8PB9+gmYUHin1Odc8TsTKKCk+bnp/RMbUvX++o+RVVIIJJFRnBUqKc6TKCkdgxXHxYQVlJBMYiYh1BUri6/HeWRklB9aaLBRbmDlPUmeTMZOzV0of6nlMYwIlkhTXXsopNIGSdj1c63P3S69dYYJGvc6RzvqD7+dOcQRKfMgokaQu7drovgsG6LbxffS3T3/Qy8v3aM7SXVq89Yj+cF5/nZ3ZgXJcAAAAQF1o5g4AAIAg4HNGybZt25SRkaGePXtq+vTp2rNnj8f2V155RSkpKRo0aJDuueceFRXVXmt2586dysrK0vjx453rkpKSNGrUKC1btqzW42bPnq2kpCTno0uXLr7+GMEnJtn075BcvUfqYvUGqa3xemxbx4JdKslxlb6KbetKb5dMGSwrq6Su87mzMkr2rTFjmxQpLNy1PndfzWOsbBb3sl++cDZ0P+K5ft4vTRZOan/p0hdOnA3jjTOjZIfJvPFRUmykHrposOZcN1IdEqK182ihZry4Wj97fqXW7c3xfT4AAABAqKCZOwAAAIKAT4GSUaNGac6cOfrkk0/01FNPaefOnTr99NOVn58vSbryyiv18ssv68svv9Q999yj//3vf7rqqqtqPV9WlgkIdOzoWTqqY8eOzm3e3HPPPcrNzXU+9u71UuqppbHZfOtT4gyU1NJ4PTzCBF8kU37L2SPES0aHR6CkjkbuliTH/kc2ex5jZZp4Lb3leP2khmaUeAmU5O6Tdn0lySZNe1WKSWrYudv1kGzhJuPGW5Cnns7s10EL7jpDN57RS1HhYfp6+1Fd9OQ3uvyZZfrsuyxKcgEAAADV0cwdAAAAQcCn2+8nT57sXB4yZIhGjRqlbt266c0339SMGTN0ww03OLcPHjxY6enpOuecc7Rjxw716tXLb5OOjo5WdHS0384XNBLSpeO7XGWq6mIFShLqCGy0aWeySYqOSXmOAMAJAyU+ZJTYqzznUGegpLGltxwN3d0DJVs+NmOXUVK7ng07r2RKpKUNkg6ul3YvlZIvb/CpEmMi9dvJmZo+qqseW7BN89fv14qdx7Ri5zHFRobrtN4pmjwoTRMGdlRCTGTD5wwAAAC0Bs4eJZTeAgAAQOD4XHrLXXJysvr27avt27d73T5q1ChJqnW71cvk0KFDHusPHTpU7z4nrUrb7mY8tvPE+54oo0TybOjuzCjxUvqqbTfXcr0ySqqVOrOOsQIoOU0RKLEyStyauW/5yIz9Jtfc31c9zzTjzsWNP5dM/5K/XzZUS359ln45rqfSk2JUXF6pBZsP6a6563XyQwv0q9fWan8OF4QAAAAIYVFklAAAACDwGhUoKSgo0I4dO5Senu51+7p16ySp1u09evRQWlqaFi5c6FyXl5enFStWaPTo0Y2ZWsvUvrcZs70HljwUHDZjXRkg7oGS3DoCFe4ZJXVlqDj3SZPC3LIhrDkkdTbjsR3S9/Olw5tNz4+KUlcmSKMDJY7zlORKO78yy5nnNeyc7nqcYcYfFzWoT0lt0pNidc9P+mvpb8/Wh78aq9vH91HPlDiVVlRp/voDmvSPJXpz9V7Z/fiaAAAAQItB6S0AAAAEAZ8CJXfffbcWL16sXbt2aenSpZo6darCw8M1bdo07dixQw8++KDWrFmjXbt2af78+br66qs1btw4DRkyxHmOzMxMzZs3T5Jks9l0++2366GHHtL8+fO1ceNGXX311crIyNBFF13k1x+0RfApUGJllNSReWMFSnL2uLIvOmTW3M/XHiVh4Z69Rqw5JHeTbGEmiPHmz6R/nyp985grmyUixpQDa4jqgZLtC6WqctOIPaVPw87prutoKTzKZL5k7zDrqqqkyorGn1vmd31gRpJuH99XC+86Q+/NPE0ndU1WfmmFfv3WBl3+7HJ9uOGgyiur/PJ6AAAAQIvgDJSQaQ0AAIDA8alHyb59+zRt2jRlZ2crNTVVY8eO1fLly5WamqqSkhItWLBAjz32mAoLC9WlSxddcskl+sMf/uBxji1btig3N9f5/Ne//rUKCwt1ww03KCcnR2PHjtUnn3yimJgY//yELYkvgZL8+pTecgQlVj1nghftekp9vZSpSvax9JZkym8d3+U4xpFREpssTX1G2vqpySY5/J206nmp08lme2KGaVrfEFaPkqJsM/qz7JZkUv47nyLt/lrauUhK6S29/XMTkLn+S/PcT2w2m4Z2SdbcG8fo2SU/6h+fb9XKnce0cucxpSZE64qRXTTtlK7KSI7122sCAAAAQckKlJQVBnYeAAAACGk+BUpef/31Wrd16dJFixefuL9D9RJDNptNDzzwgB544AFfptI6WQ3Ji4+bBux1ZV84M0rqUXqrxBGYGvdrKdzLW96mvZSaKRXn1Ow/UpvaslCGXGYe5SXSI31NY/cNb5htDS27JUlt3Jq5V5ZL2z4zz/1RdsvS80wTKPlxsekX853JfNKKp6XzHvHf6ziEh9l005m9NGVYhl5buUevrdyrI/mleuKL7Xryy+2aODBNd5zbV307Jvj9tQEAAICgQDN3AAAABIFG9SiBn0W1kRIdfT7qyiqpqpSKHE3NE+pReksyQZjBl3rfz2aTfrlEunWNFFnPTB73gIq3OUTGSIOmmuX1jgBbYwIl7qW33viZCf60SZE6j2z4Oavr6ehTsnOJ9Nm9rvXrX5dK8/33OtVkJMfqrgn9tPS3Z+tfVw7XqT3bqcoufbwpSxMfW6LbX1+rXUe5ww4AAACtEM3cAQAAEAQIlASb9r3MWFegpPCIZK8y/UDcgyHVuW8bN8t7NoklIlqKjq//PJPdAiW1ZbUMnWbGqnIzJmbU//zVxaWYBvL2Kmnrx2bdwItMvxR/yThJikqQSnKkw99LMckms6QsX9rwpv9epxZREWE6f0iGXr9htD65/XRNGpgmu116d90BnfPoYt3zzkYdzOVOOwAAALQiNHMHAABAECBQEmzq06fEKrsVl1p3oCClrySbaXg++DK/TVGSK6Mkso0UVUuApcsoVzkxybMBvK/CI6WL/i2dPEM690HpitekCX9u+Pm8vkaE1P001/MzfiOd8kuzvPq/UrWycU0pMy1RT/9shN6/ZazO6Juqyiq7Xlu5R2c/slhvrt5bo4QdAAAA0CJRegsAAABBgEBJsKlXoOSwGU/UeD2lj3T9F9J1H9edTdIQGcOkhAypz4TaG7TbbK6sEqlxpbck0/vk/Eel034lZf6k/mXCfNHrbDO27SGN/IU0bJoUESsd2iTtXeH/1zuBwZ2T9OLPT9HcG0drRLe2Ki6v1K/f2qDbXl+n/JLyZp8PAAAA4FeRcWasKDElhgEAAIAAIFASbKxAyVEvgZKlT0hv/Vxa+Zx5fqJAiSR1OkmKT/Xf/CwxSdIdm6RL59S935DLXcuNDZQ0h5Oukc78nTTtNSkiSoptKw2+xGxb9XzApjWyezu9+cvRmjWxn8LDbJq//oAuevIb/XikIGBzAgAAABrNyiiRyCoBAABAwBAoCTZWj5JjO6SqKtf6wmzpsz9Im96Wtn1q1tXVyL05hIXXnk1iadtNOusP0rCrpI6DmmdejREZI535G6lDf9c6K9gTgIwSd+FhNs08q7fe/OWpSkuM0Y4jhbroyW+0ZOuRgM4LAAAAaDACJQAAAAgCBEqCTXI3KSzCpJ7n7XetP77TjDHJ0ojrpIFTpVNvCsgUfXbGLOmiJ6WwFvrrltzNjPlZzdqnpDYjurXT/FtP00ldk5VXUqFrX1ip99btP/GBAAAAQLCx2dwauhcGdi4AAAAIWS30m+tWLDzC9MeQPPuUHN9lxo4DpQseMyWvOg5s5smFKCtzp7JUKj4e2Lk4dEiI0Ws3nKqLh3dSlV264411en/9gUBPCwAAAPAdDd0BAAAQYARKglFKHzN6BEocGSVtuzf7dEJeRLTUpr1Zzj8Y2Lm4iY4I1yOXDtWlIzqryi7d/sY6vb1mX6CnBQAAAPjGauheVhTYeQAAACBkESgJRlafkuwdrnVWRgmBksBISDdjEAVKJCkszKa/XDJEl5zUWZVVdt01d71uenmNjuSXBnpqAAAAQP04M0oIlAAAACAwCJQEo/a9zeiRUbLbjARKAsMKlOQFV6BEMk3eH/7pEP3qnD6KCLPp401ZOvcfi/Xeuv2yB0FPFQAAAKBOlN4CAABAgBEoCUbOQMk21zoySgLL6lOSnxXYedQiPMymO8/tq/duOU390xOVU1Su215fp+tfWqPDeSWBnh4AAABQuyhH6S2auQMAACBACJQEo9T+Zjy+SyrJlSrKpFxH7wkCJYHhLL0V3A3TB2Ykaf4tp+mO8X0VGW7Tgs2HNPGxJfpyy+FATw0AAADwjowSAAAABBiBkmAU115K6mqWD26QcvdKskuRbaS41IBOLWQlWoGS4MwocRcZHqbbxvfR+7eO1YD0RB0vKtd1L6zS7I83q7yyKtDTAwAAADxFtjEjPUoAAAAQIARKglXGUDMeWCsd32mW23aXbLaATSmkOXuUBHdGibvMtES9c/MYXT26myTpmcU/auYr36qsgmAJAAAAgogVKCkjUAIAAIDAIFASrDKGm/HgOvqTBIOElpNR4i4mMlwPTBmkJ688SVERYfrs+0O66eU1Kq2oDPTUAAAAAIPSWwAAAAgwAiXBKn2YGQ+sI1ASDKxASeFhqbIisHNpgPOGpOs/V5+s6IgwLfzhsH7x4moVlLa8nwMAAACtEM3cAQAAEGAESoKVlVFybIfpUyIRKAmkuBTJFi7Zq0ywpAUa1zdVL1w7UrGR4fpq21H99Kml2p/DXXsAAAAIMDJKAAAAEGAESoJVm3ZSsqOh+66vzUigJHDCwqWENLOcfzCwc2mEMb1T9NoNpyolPlo/ZOVryr++0do9xwM9LQAAAIQyZ6CEHiUAAAAIDAIlwcwqv2V39JMgUBJYVqAkr+UGSiRpWJdkvXfLacpMS9DRglJd8exyvb++5TSpBwAAQCsT6Si9RTN3AAAABAiBkmBmld+yWBkmCAxnQ/eWHSiRpE7JsXrrpjEa37+DSiuqdOtra/X4wm2y2+2BnhoAAABCDaW3AAAAEGAESoJZxjDXcnya6wICgdGKAiWSFB8doWd+drKuP72HJOnRz7fq8YXbAzwrAAAAhBxnM3cySgAAABAYBEqCmVV6S6LsVjBItAIlWYGdhx+Fh9n0+/MG6L7zB0iS/rFgq/63fHeAZwUAAICQQo8SAAAABBiBkmDWpp2U3M0sEygJPCujJK/19fP4+dgeuu2cPpKk+97bpHfX7g/wjAAAABAyKL0FAACAACNQEuysPiXtegR2HnA1c29FGSXubh/fR1eP7ia7XbrjzXWa883OQE8JAAAAocDZzL0wsPMAAABAyIoI9ARwAuPulqITpOE/C/RMkJBhxlbSo6Q6m82m+y8YKEl6adlu3f/+9zqcX6pZE/vJZrMFeHYAAABotcgoAQAAQICRURLs0gZLU/4lJXUK9ExgZZSU5DTsIq6qUlr5nHRkq1+n5U9hYTb96cKBmjWxnyTp34t26M8fbpbdbg/wzAAAANBqOZu5EygBAABAYBAoAeorJkmKbGOWG5JVsu0z6aO7pZemSKUF/p2bH9lsNs08q7f+b+pgSdJ/vt6pRz8P3uAOAAAAWjhnRkkdpbeqKinNBQAAgCZDoASoL5vNlVWS14BAyVFHsCH/gLTkYf/Nq4lcOaqrHphiSnE98cV2PfLpFlVWkVkCAAAAP7MCJVUVUmW5933e/oX09/7S8V3NNi0AAACEDgIlgC8S0s3YkIySnL2u5WVPSke2+GdOTejq0d31u59kSpL+9eV2XfbMMu3O5k4+AAAA+JHVzF2Syou877PjC6k0V/ru3WaZEgAAAEILgRLAF0mdzZizx/djcx2Bksg4c7fcR3dLLaD3xw3jeumRS4cqPjpCa3Yf1+R/fqUPNhwI9LQAAADQWoRHSrZws1zmJVBSkmv6BErSts+bbVoAAAAIHQRKAF+07WHG4zt9P9bKKJnwgBQRI+1cIu3+xn9za0I/HdFZn9x+ukb1aKeiskrd8upaPbZgK03eAQAA0Hg2m6sXoLeMEvfM7D3LTOAEAAAA8CMCJYAv2jkCJccaECixMkq6ny71PMssH205TdI7t22jV68/Vb8Ya/4bPLZgm2a9tSHAswIAAECrEFVXoMQtm9teKe34snnmBAAAgJDhU6Dk/vvvl81m83hkZpr+BceOHdOtt96qfv36KTY2Vl27dtWvfvUr5ebWfbfPtddeW+OckyZNavhPBDQlZ0bJLt+OK86RSvPMclJnKdHqdZLlr5k1i/Awm/5w/gD95eLBigiz6a01+7R0x9FATwsAAAAtndXQvby45rbcvZ7PKb8FAAAAP4vw9YCBAwdqwYIFrhNEmFMcOHBABw4c0COPPKIBAwZo9+7duvHGG3XgwAG99dZbdZ5z0qRJeuGFF5zPo6OjfZ0W0Dzadjdj7j6polSKqOfvqnVx16a9FBXXuKbwQeCKU7pq88E8vbhst/7x+VaN7tleNpst0NMCAABAS2U1dK8royRtsJS1Udr+uVRVJYVRIAEAAAD+4XOgJCIiQmlpaTXWDxo0SG+//bbzea9evfTnP/9ZV111lSoqKpwBFW+io6O9nhMIOvEdzEVceaG5YEvpU7/jrLrKSV3MmOD4fW9hGSXubj6rt15btVerdh3X19uP6vQ+qYGeEgAAAFoqK6PEWzP3nN1mHHK5KYFbcEjKWi9lDG+++QEAAKBV8/kWnG3btikjI0M9e/bU9OnTtWfPnlr3zc3NVWJiYp1BEklatGiROnTooH79+ummm25SdnZ2nfuXlpYqLy/P4wE0C5vNlVXiS/ktK6Mk2QqUtOyMEknqmBijq0Z1kyT9/TMauwMAAKARnKW36sgoad9b6nmmWa6t/FZFqbR3lVRV6fcpenj7F9ILP5Eqy5v2dQAAANAsfAqUjBo1SnPmzNEnn3yip556Sjt37tTpp5+u/Pz8GvsePXpUDz74oG644YY6zzlp0iS99NJLWrhwof76179q8eLFmjx5siora/9gO3v2bCUlJTkfXbp08eXHABqnIQ3drYu7pK5mbAUZJZJ045k9FRMZpnV7c/TFD4cDPR0AAIAWa8mSJbrggguUkZEhm82md99912N7QUGBbrnlFnXu3FmxsbEaMGCAnn766cBMtilE1VV6yy07u88Es7zjC+/n+erv0vPjpVcvl8oK/T9PyQRhNs6Vdn8jHfmhaV4DAAAAzcqnQMnkyZN16aWXasiQIZo4caI++ugj5eTk6M033/TYLy8vT+edd54GDBig+++/v85zXnHFFbrwwgs1ePBgXXTRRfrggw+0atUqLVq0qNZj7rnnHuXm5jofe/furXVfwO+cGSU+BEpqyygpPNKi70LrkBCja0Z3lyQ9+MH3Kilv4jv3AAAAWqnCwkINHTpUTz75pNftd955pz755BO9/PLL2rx5s26//Xbdcsstmj9/fjPPtInU1sy9NF8qPmaWk7tInUaY5SNbvJ/nwDozbv9cmnO+VHjUc/u7N0tPjmpcEKWswLV8dGvDzwMAAICg0ajud8nJyerbt6+2b9/uXJefn69JkyYpISFB8+bNU2RkpE/n7Nmzp1JSUjzOWV10dLQSExM9HkCzaVBGSbUeJbHtpDDHv42CQ/6bWwDMPLu3OiREa1d2kf79Ze3/bgEAAFC7yZMn66GHHtLUqVO9bl+6dKmuueYanXnmmerevbtuuOEGDR06VCtXrqz1nC2qZHFkGzNWzyixPkfHJEsxSVK7nuZ58TGp6FjN81iZ3LZw6cC30ktTXGW4KsulDW+YLJCsTQ2fa6lbRYWj2xp+HgAAAASNRgVKCgoKtGPHDqWnm7vj8/LyNGHCBEVFRWn+/PmKiYnx+Zz79u1Tdna285xA0GnrCJQ0JqMkLKzVlN9KjInU/RcOlCQ9tXiHth+uWYoPAAAAjTNmzBjNnz9f+/fvl91u15dffqmtW7dqwoQJtR7TokoWW4GS6s3cnZ+jHSVso9pIiZ3NcvYOz33tdleg5IpXpfBo6dAmV2/B47ukqgqznH+g4XP1CJSQUQIAANAa+BQoufvuu7V48WLt2rVLS5cu1dSpUxUeHq5p06Y5gySFhYV6/vnnlZeXp6ysLGVlZXn0G8nMzNS8efMkmUDLrFmztHz5cu3atUsLFy7UlClT1Lt3b02cONG/PyngL1ZGyfFdUlWVWa6rfFZ5sSmxJbkySiS3QEnLbehumTwoTWdndlB5pV2/m7eJxu4AAAB+9sQTT2jAgAHq3LmzoqKiNGnSJD355JMaN25crce0qJLFMY4qAT98KOW7ZVxbgQ8rUCJJ7R1ZJdnVspmLsqVyR0mtXmdJqX3NstVHxD2o0ZiblUrcMnMIlAAAALQKPgVK9u3bp2nTpqlfv3667LLL1L59ey1fvlypqan69ttvtWLFCm3cuFG9e/dWenq68+H+gXzLli3Kzc2VJIWHh2vDhg268MIL1bdvX82YMUMjRozQV199pejoaP/+pIC/JHUxqfwVJVJBlrRmjvRgqrmo88YqFxAVL8W2da23+pS08IwSSbLZbHpgykDFRoZr5c5jmrtmX6CnBAAA0Ko88cQTWr58uebPn681a9bo73//u2bOnKkFCxbUekyLKlk8bLrUJkU6/J30/LmubJGc3Wb0CJT0NmP1QIm1b0K6FBEtpfY3zw9vNqN7UCPPXxkl2103TwEAAKDFivBl59dff73WbWeeeWa97iJ33yc2NlaffvqpL1MAAi880pTQOr7LXGx9OVuSXdr6iZR5Xs39cx13wSV1kWw213pnoKTlZ5RIUue2bXTnuX3154826/8+2qxzMjuofTwBTwAAgMYqLi7W7373O82bN0/nnWc+bw4ZMkTr1q3TI488ovHjxwd4hn7Qvpc04zPp5UtMidv/TpJuWVVLRokjUHKsWukt577dzNgh04xW43f3fiKN+Qxe6pZRUlEs5e3znB8AAABanEb1KAFCltWn5Ot/mKwSqWaNZEtOtf4kllbSo8Tddad1V//0ROUUlevPH20O9HQAAABahfLycpWXlysszPPyLTw8XFWtKZuhfS9pxudSu15S4WFp9X/dPkvXI6PkeLXsk1QrUOIlo6Q+n8ErK7yvdw+UVD8vAAAAWiQCJUBDtO1uxh8XudbVFiip3oDSUj2jpKxQ2r6wRafuR4SHafbFg2WzSe98u1/fbD8a6CkBAAC0CAUFBVq3bp3WrVsnSdq5c6fWrVunPXv2KDExUWeccYZmzZqlRYsWaefOnZozZ45eeuklTZ06NbAT97f4VOmMX5vl5U+Z7BLJs9dfu15mzN5hGrhbqmefWIGSo9ukqkrfSm8tfUL6c0dp99Ka29xLb1nnBwAAQItGoARoCKuhuySFR5mxIKvmRZPkugsu6QQZJZ/dK718sbThDf/OtZkN65Ksq0815Q5+8/YGFZTWciceAAAAnFavXq3hw4dr+PDhkqQ777xTw4cP13333SfJlEEeOXKkpk+frgEDBugvf/mL/vznP+vGG28M5LSbxqBLpMTOJquk+LhZ537TUdtupmdgeZFnCS0rUNLWUXqrbXcpIsb0Fty3SirJde2bf9AzyFLdts+kqgrp25dqbqsRKCGjBAAAoKUjUAI0RFu3QMnQK6S4VLPsLaskt7bSW24ZJXa7tNXRr+fAt/6dawDMmpSpzm1jte94sf784feBng4AAEDQs3o+Vn/MmTNHkpSWlqYXXnhB+/fvV3FxsX744Qfdeeedsrn3wGstwiOl0Te7nkcnSbHJntutDG/38lvVG7+HhUspfczy9/PNGO+4Wam8qGYJLXe5+8y47fOaGd9WoCSxkxlbYkZJVZW09mXpCEEeAAAAiUAJ0DDterqWR93klv6/vea+x3eZMal66S3HRVrxcXMXWp7jYuzYTr9ONRDioyP0yKVDZbNJr63cqy9+OBToKQEAAKAlOelqEyCRvDdKd/YpcdyoZLd7b/ye2t+Mm983Y/oQKcZx3rxaGrrb7VLufrNcdFQ6uNZze4kjwNLpJDO2xIySXV9J782U5t8a6JkAAAAEBQIlQEN0GCCNuFY683dSxwGuC7VjP3ruV3DYUQ7AJnXI9NwWkyRFxJrljW+51lc/Rwt1as/2mnGaybz59VsbdbywLMAzAgAAQIsRnSCNnGGW2/equb19tRuVCo+YEluymbJdltR+Zsx1BFFS+koJGWY5v5Y+JYVHpcpS1/Ntn3tutzJROo0wY8EhqTjnRD9RcLEyZrI2tugeiQAAAP5CoARoiLAw6YJ/Smf+xjyvfqFmObDOjCl9zMWeO5vNlVWyca5rfc5uqbJ19PW4e2I/9e4Qr6MFpfrLxz8EejoAAABoSc74jTThz9L4P9bc1t6tobskHXeU3UrsJEVEufbr0N/zuJS+UqJVAjfL++tamd6WbZ95PrdKbyVkuIIu3jLLg5nV+6W8UMrbH9i5AAAABAECJYA/OFP/q10gHVxnxvRh3o+z+pQcdyu3VVVR8+KshYqJDNdfLh4sSXpj9V6t3HkswDMCAABAixEZI425xbPsraX65+/q/UksqdWyut0zSvJqySixym5ZpXP3fysVHHFttzJKohNcPVBaWvmtYrfP5Ue2BG4eAAAAQYJACeAP7hdqdrtrvZVRkjHc+3FWRokkhUVISY6G740pv7XiGemRftLh4MjgOLl7O007xfxcv5+3UWUVpPYDAACgkazP38d3mmxsb/1JJNP0PSLG9Tylr+szeH4tPUqsslQZw6T0oZLs0vYFru1WRklMojmf1PKCDVZGiSQdbWFzBwAAaAIESgB/aGd6cagkVypyuzvrgKPxY8Yw78dZGSWSlHGS1HGgWW5MQ/fv50sFWaZBY5D4zaRMtY+L0rbDBXp2yY5ATwcAAAAtXUKGCYBUVZj+I7VllISFu7I+YttJce3rX3orqbPUZ4JZdi+/ZQVKohPcehW2sM+47tcsR4LjBisAAIBAIlAC+ENkrCsbxEr/LzjsaBBpk9KGeD/OPaOk+1hXWYHGZJQUOsoCFAVPmavkNlG69/wBkqTHF27XtkP5AZ4RAAAAWrSwMKmdo0/JwfWujJK23Wrum+roU2Jlf9S79JZboGTHF67M8RK30ltJnRznqiU7JVi5Z5S0tGwYAACAJkCgBPCX6g3dnY3c+0rR8d6Pcc8o6X6a1NaRmXJ8V8PnYQVK3C9+gsCUYRk6O7ODyiqrdNfc9aqopAQXAAAAGqH7aWb88C4pa5NZrp5RIrmyu9NM77x6l95K7OTK+C7JMZkkVZWmAbokRSe5gi61nStYVe9R4l4+GAAAIAQRKAH8pXpDyROV3ZJcF2m2cKnLqY3PKKksd130FAdPRokk2Ww2zb54sBJjIrRhX66eWdKIrBkAAADgnD+aHiJF2VLhYbPOW6BkxHXSlH9LZ95jnic6ghsFh0x/k+ryrIySLlJUnBTluOmp8Iir7JZkboZyL+NVVdn4n6m5FOe4lktyTDY8AABACCNQAviLlfpv1Sc+uM6MtTVyl6ROI6TOI6VRvzQXWlavk2M7G3ZXV1G223JwBUokqWNijO6/0NyV99iCrfohKy/AMwIAAECLFR0vXfmmqwSuLVxK7Fxzv6g20vDppj+JJMWlmn3tVa5sbEtlhSs7xCqrFZdqxoJDrkBJeLQUES3FdZBsYZK9Uio86t+frylZ1wrh0WakTwkAAAhxBEoAf3FmlDgCJVZGSfqw2o+JaiP9YoE0abZ5ntTFXLRVFNfeXLIu7hd6QZZRYpk6vJPG9++o8kq77p67XuWU4AIAAEBDJaRJ0+dK8WlS7/FSeMSJjwkLdyu/Va1PSf5BE0AJizRBEEmKd4wFh6VSx40+MYlmDI9w7Vf9XMGqotRVPqzTCDMe3Rq4+QAAAAQBAiWAv7j3KNnyieNONJurFnJ9RERJyY474hpSfss9ZT4IM0okU4Lr/y4epOQ2kdq0P09PLdoR6CkBAACgJevQX7pjk3TlG/U/xgqUVG/CbpXdSswwDeMlV6DEvfRWdILrGKv8Vktp6G71MrSFSZ1PNstklAAAgBBHoATwl+RupqFjRYn02uVmXWq/2hu518bZ0H2n73NwT/cPsmbu7jokxOhPjhJcjy/cpu8PUIILAAAAjRAeKdls9d8/weotUi24YTVyt8p5Sa6MEffSW+6BktrOFays64SYZKnDALN8ZEvApgMAABAMCJQA/hIeIV33kTTkCik8yqzrdprv52lMQ3f30lsluUHdUPLCoRmaOLCjKqpMCa6yCkpwAQAAoJlYDd1rDZR0cq1zL71VkmuWoxNd21taoMTKPG/TztzYJREoAQAAIY9ACeBPaYOki5+R7twsXf6KNP6Pvp/DvaG7rzyaUdql4hzfz9FMbDabHrposNq2idT3B/P05JfbAz0lAAAAhIraSm85AyVuTeG9lt5yC5S01NJbsW2llL5mufBw0JbuBQAAaA4ESoCmEJci9T9fikny/Vh/ZZRIQdvQ3ZKaEK0HLxokSXryy+3atD83wDMCAABASEh0ZIzk7PFc7+xR4pZREufezN1b6S0rO6WFNHO3rhFi25kywVaZMbJKAABACCNQAgQbZ6Bkp2S3+3ZsjUBJ8PYpsZw/JEM/GZxGCS4AAAA0n7TBZjywVqqscK2vK6Ok1kCJIzslP6tp5upv7hklktShvxmzNgZmPgAAAEGAQAkQbJK7mrE0Vyor8O3Y6oGSFpI+/+CUQWofF6UfsvL1xBfbAj0dAAAAtHap/aXoJKm8UDq0ybW+ztJbh6XSPLMc4156y5FRktdCMkrce5RIUqcRZty/OjDzAQAACAIESoBgExUnRcaZ5YLDvh1b4AiUWCW/grz0lqV9fLQecpTg+veiHdqwLyewEwIAAEDrFhYmdRlplveuMGNZkevzs7fSWxUlrtJcHhkljh4lJTlSeXGTTdlvqmeUdD7ZjPsIlAAAgNBFoAQIRvGpZqyeIVIXu921f0o/M7aQjBJJmjw4XecPSVelowRXaUVloKcEAACA1qzLqWbcs9yMVhAkKsGz12BUGykq3ixn7zCje6AkJkmKiDXL+S2gobuzR4kjUGJllBzb0aKuHwAAAPyJQAkQjJwNIw+51lWWS2WFtR9Tmi9Vlprl1L5mbCEZJZYHpgxSSnyUth4q0D8XUIILAAAATajrKDNaGSU/LjJjSh/JZvPcN85xI9OxH80Y7RZIsdmkREdWSV5LCJTkmNEKlMS2ldr3MctklQAAgBBFoAQIRu4NIy3/nSQ9NlgqraVviZVNEhXvKhXg72buR7ZKC/7UZHeatYuL0kMXmcaaTy/eoTW7g78ZPQAAAFqoTiMkW7jJJMnZK6150awfcnnNfeM7mrGixIzuGSWSlODoUxKIjJKqKunNa6RP7qnf/tV7lEiu8lt+7lNyKK9E98//TmUVVX49LwAAgL8RKAGCkbNhpCP4UV5iLlqKsl13sVVn7RuXIsU6Lnr8HdD46hHp60eljW/597xuJg1K08XDO6nKLt355joVllY02WsBAAAghEXFSelDzPKKp6VDG6XwaGnIZTX3tUrjWmoEStLMGIhASfY26ft3peX/dmWL1KV6jxLJrU/JKr9Nq7LKrmnPLdecpbv0l49/8Nt5AQAAmgKBEiAYxVXLKMk/4NpWWEuDd2egJNV1d5i/S2/l7q97Dn5y/5SB6pQcq93ZRXrow++b9LUAAAAQwro4ym8tf8qM/S/wzLSwWJ/PLTGJns8DWXrr+G7X8qFNJ97f2aPEPaPE0dh+3xqToeIH4WE23TO5vyTpv9/s1CebWkBZMgAAELIIlADByLpjzQqU5LkHSo56P8Y9UOLMKPFz6SorQFKS69/zVpMYE6lHLh0qm016beVeff79oRMfBAAAAPjKCpTYK8044hrv+1mltyy1lt46oGaX4xYoObih7n3Li13lw9wzSjoMNA3pS3Ol7O1+m9q5AzrqhnE9JUmz5m7Q7uw6ei4CAAAEEIESIBhZF2KFXgIlBbVkcxS4Z5Q4Lnr83aPEeu36pPQ30uhe7fWLsT0kSXe9uU57soua/DUBAAAQYrqe6lpu20PqNtb7fjVKb1XLKHGW3sry39zq6/gu13LWCQIlVmnesAjPYE94hJQx3Cz7sfyWJM2a2E8nd2ur/NIK3fzKtyopr/Tr+QEAAPyBQAkQjKqX3srb79pmZY5U55FRYgVK/Fh6q6JMKskxy02cUWK5e2I/DeuSrLySCt348houqgAAAOBfiRlSUlezfNLPpLBaLpGrl96qnlGS6MgoyQtERske1/KJMkqcZbfaSjab57Ym6FMiSZHhYXriyuFqFxel7w7k6cEPKK0LAACCD4ESIBhZd6xZwQ+P0lv1CZQ4Sm+VF5lG8P7g/rpWwKSJRUeE66mrTlL7uCh9fzBPf3h3k+x2e7O8NgAAAELEufdLg34qnTyj9n3i3QIlEbFSeKTn9gRHj5L8LKm5P6+6l9468kPdn/+djdy99GFxBkpW+29uDulJsXrs8mGy2aRXVuzRe+v2n/ggAACAZkSgBAhG1h1r5UVSaUE9AyWO3iVxKVJMkmQLN8/9lVVS4NYnpJkySiRzUfXEtOEKs0lvrdmn11bubbbXBgAAQAgYdIn00+el2OTa93EPlFTPJpFcpbcqS13lrZrKoe9cZXclz2bu9krpyObajy1yyyiproujDNmhjVK+/3sEjuubqlvP6i1Juuedjdp2KN/vrwEAANBQPgVK7r//ftlsNo9HZmamc3tJSYlmzpyp9u3bKz4+XpdccokOHar7A5bdbtd9992n9PR0xcbGavz48dq2bVvDfhqgtYiOlyLjzHLBoXqW3nKU6YrvYNLorYsff12oub9uM/QocTemd4pmTTR/a+6f/53W723e1wcAAECIcy+9FZNYc3tEtNSmvVluyobuWZukp0+X3rjKPC/JdWV7dx5pRqv81vFd0pEtnsdbGSVtvGSUJHR09SnZ9qk/Z+102/i+GtOrvYrKKnXNf1dqf05xk7wOAACAr3zOKBk4cKAOHjzofHz99dfObXfccYfef/99zZ07V4sXL9aBAwd08cUX13m+hx9+WI8//riefvpprVixQnFxcZo4caJKSvxULghoqdzLb3k0c69H6S3JdfHjr4bu7k3kmzGjxHLjGT01cWBHlVVW6aaX1+hYYVmzzwEAAAAhKqqNFBVvlr1llEhSvCOrpMD/2RhOP3xgskb2rpBK813ZJG3aS11Hm+WsDVJhtvTMGdKzZ3neOFVcR0aJJPWdbMYtnzTJ9MPDbPrXlSepd4d4Hcgt0c+eX6HsgtImeS0AAABf+BwoiYiIUFpamvORkpIiScrNzdXzzz+vRx99VGeffbZGjBihF154QUuXLtXy5cu9nstut+uxxx7TH/7wB02ZMkVDhgzRSy+9pAMHDujdd99t1A8GtHjWXWt5+z2DFIVHatY9rix3BUSsQIm/G7oXus2holiqaN4LGpvNpr9dOlQ9UuJ0ILdEv3ptrSqr6FcCAACAZmKV36o1UGLd6HS06eawfaFjwW4yR6z+JMndpLQhZvngBumbf5hMk/JCae9K1/HOHiW1BEr6TTLjj1/6r9dhNe3iovS/GaeoU3KsfjxSqCueXa7PvstSFZ/tAQBAAPkcKNm2bZsyMjLUs2dPTZ8+XXv27JEkrVmzRuXl5Ro/frxz38zMTHXt2lXLli3zeq6dO3cqKyvL45ikpCSNGjWq1mMkqbS0VHl5eR4PoNWxLsQObpBkl8IizPOq8prN1K2LMVuY66LHatDor9Jb1TNZApBVkhgTqaevGqHYyHB9vf2oHv18y4kPAoCWrjBb2vCmCYoDAALHupEp2kvpLfft7jc5+VPxcWm/W6P1A9+6MkradpPSHYGSrA3Syudc++1b5VouOkGgJG2IlNjJ9ErcucR/c68mPSlW/5txilLio7TtcIFu+N8aTXhsieau3quyiqome10AAIDa+BQoGTVqlObMmaNPPvlETz31lHbu3KnTTz9d+fn5ysrKUlRUlJKTkz2O6dixo7Kysryez1rfsWPHeh8jSbNnz1ZSUpLz0aVLF19+DKBlsAIlB9aaMbGT66Ks+l1q2Y6+Pm1SpDBHE3dn6a0myCiRmr1PiaVfWoL+cslgSdKTX+7Q5983YWkDAAg0u93UoX/nemnR7EDPBgBCm5UxUlugxPr8Xv1zs7/8uEiyuwURDqyVcsyNi0ruJrXvLUW2kSpKzCM8ymxzD67U1aNEMr0O+040y1s/9uv0q+uZGq+Pbxunm8/spYToCG0/XKBZb23QGX/7Uv/56keVlFc26esDAAC48ylQMnnyZF166aUaMmSIJk6cqI8++kg5OTl68803m2p+Xt1zzz3Kzc11Pvbu3dusrw80C+uOtIPrzZjYyVVWy7pL7cA66ZXLpBcvdOyT4TreWXqrCXqUSAHJKLFMGdZJ147pLkm684112pNdFLC5AECT+m6etGepWV72bym/9htJAABNLO4EpbfiTFnqWnsKNtb2BWbsOMiM+791K73V1dww1XGga/8JD5lx3xqpyhF0OFGPEsnVp2TrpzVL/vpZakK0fj0pU0vvOVv3TM5Uh4RoHcwt0UMfbta4h7/U/5btIsMEAAA0C59Lb7lLTk5W3759tX37dqWlpamsrEw5OTke+xw6dEhpaWlej7fWHzrkeUd4XcdIUnR0tBITEz0eQKtj3bFmldlKzHAFSqzG7e/NlLZ9Ksku9TpbOv9R1/HWXWJFfgqUFFYvvZXjn/M20O9+0l8jurVVfmmFbn9jrSoquYAC0MqUFUmf32eWI2JMf6jFfw3snAAglGX+REpIl/pM8L7dCqRU/9zsD3a7tP0Ls3z6nWY8vtNRplem9JYkpQ8zY6+zpZNnSJFxUlm+dHSr59xia8kokaQe40xmSt5+6e0Z0ksXSYv+4s+fpoaEmEj98oxe+uo3Z2n2xYPVKTlWh/NLde973+nip77RgZziJn19AACARgVKCgoKtGPHDqWnp2vEiBGKjIzUwoULndu3bNmiPXv2aPTo0V6P79Gjh9LS0jyOycvL04oVK2o9BggZ1oWWJTHDrUHkEamiTDryg3l+/RfSz+ZJnUa49vd3M3cro6SN4065AGaUSFJURJj+ecUwJURH6Ns9OXryyx0BnQ8A+N3SJ6TcvVJSF+mKV8y6NS9K2fy9A4CA6D1euusHqc9479ubsvTW4c1S/gEpIlbqd57UtodZn3/AjMndzTj2Dmn0LdKF/5LCI6ROJ5n1+1ZLh3+QsrdLtnCpQ//aXysyxgRaJGnT26ax+6LZUknT9waNjgjXtFO66ou7z9CDUwaqXVyUNu3P04X/+kZrdvvpBjAAAAAvfAqU3H333Vq8eLF27dqlpUuXaurUqQoPD9e0adOUlJSkGTNm6M4779SXX36pNWvW6LrrrtPo0aN16qmnOs+RmZmpefPmSZJsNptuv/12PfTQQ5o/f742btyoq6++WhkZGbrooov8+oMCLU68Z+8ej9JbhUekYz9KVRVSVIKUcVLN4/3ZzL2y3BVwSelrRn+V9GqEzm3b6MGLTOmBx7/YprV7Aj8nAPCLwqPS1/8wyxMeNF/O9Zkg2SulLx4M7NwAAN45y+T6MaOk4Ih0ZIu06S3zvPtpJpDRyf3zv01KdvTtTOokTfyzGSXXjVT7Vklr/2eW+05yBXVqM/5P0ik3SGf81mSXSE3XpN6L6Ihw/Wx0d82/5TRlpiXoaEGppj27XC8u3SV7E5cDAwAAocmnQMm+ffs0bdo09evXT5dddpnat2+v5cuXKzXVfCD8xz/+ofPPP1+XXHKJxo0bp7S0NL3zzjse59iyZYtyc113ov/617/WrbfeqhtuuEEjR45UQUGBPvnkE8XExPjhxwNaMCt7xJKY4ZnOb2WTpPYzTRer82czdytF3xYutXPcvRbgjBLLRcM76cKhGaqssuvON9fT9BFA65C1wZTaatdTGnCRWXfOH8343bvS8d0NP7fdLq1+Qdq2oLGzBAC4c7+pqcoPZWH3r5H+3ld68hTpq7+bdb0d2SwZw137JaRLEdHez9F5pBl3L5XWv2aWT7r6xK+d0lv6yd+ks+5x9UEsOFT3MU2gc9s2evumMZo0ME1llVX64/zvdMP/1iinqKzZ5wIAAFo3nwIlr7/+ug4cOKDS0lLt27dPr7/+unr16uXcHhMToyeffFLHjh1TYWGh3nnnnRq9Rux2u6699lrnc5vNpgceeEBZWVkqKSnRggUL1Ldv38b9VEBrUKP0Vie3BpGHzZ1lkpSa6f14K6OkoRdqVZWu9Hrr7rG4VFdJrwD3KHH34EWD1DExWjuPFupfX2wP9HQAoPGspu1tu7uC4WmDpB5nSLJL615p+Ll3fCF9cLv0xnT/ZB0CAAwrUGKv9M9n5Z1LJHuVFB5tPoN3GCANvNhsc88oT+5a+zk6n2zG7G1SUbYJqvSupXRYbaxM9wAESiQpLjpCT111kv54wQBFhYfp8+8PafI/v9LKnfw/DAAA+E+jepQAaELR8a40d6laM/ejnhkl3rTrIUUnmRJZ38+ruX3/t9KjA03dYW8+miX9rbeUtcmVURKfKsUkm+UgySiRpKTYSP3pQlOC6+nFO7QlKz/AMwKARso/aMZ4zxtOnHcBr33ZBLQbYuWzZqwokb59sWHnAADUFBHl+qzsjzJV2Y4bgE6/U/rNLunmZVKCI2iRPlSSI5BuNXL3JiHN9LqyDL/K9C7xhVWmqxlLb1Vns9l03Wk99M7NY9QjJU4Hc0t0xbPL9M8F21RZRSkuAADQeARKgGBmXZTYws1yvHvprRNklETFSWNuMctfzpYqKzy3r5kj5e2T1r3q/fgfF0mVpdL377pllHSQYpLMcnGO7z9PE5o0KE0TBnRURZVdv31ng6q4YALQkuU77tpNqBYoyTzf3FWct99khvjq2E5p66eu56uer/n/BwBAw/mzoXv2DjO2711zW3S864ap5DoCJZKrT4lkAiW+sjLdA5RR4m5QpyS9f+tYXTy8k6rs0j8WbNVPn16q7YcLAj01AADQwhEoAYKZdVGSkC6Fhbs1iDxk0uel2jNKJGnUjaYEV/Y2aeObntt2f2NGK+Dizm43X8JJJuXfutCL7yDFJpvlIMoosfxpykDFR0do7Z4cvbZqT6CnAwANZ2WUJKR7ro+MkYZcYZYbkg2y6j+S7FL3083/H3L3Sls/adRUAQBunJ/X/RAoOer4vO8tUCJJfSaYscuous/TbYwZe55lSjr6KggyStzFR0fo0cuH6e+XDlWC47P/Tx7/Ss9/vZNG78DxXVJ5SaBnAQAtEoESIJhZFyVWA0XrwqusQKosM6W53FPpq4tJlMbebpYX/UWqcDQ9zD/kSuXP3SuVVrsDq+iYKckimSaSx3a6Xt/KKAmiHiWW9KRY3TXB9Dh65NMtyi0qD/CM0KS2L5Be/qmUuz/QMwH8z+pRYpVYcXfSz8y45WPfvrQqK5TW/s8sj7nVVcZr5TMNnycAwJN7qdzGKD4uFTnOUVugZPyfpDs3S31O0HNkxHXS5L9JFz3VsLlYPUr8kSXjR5eM6KxP7xincX1TVVZRpQc/+F6/f3eTKiob0J8RaA3WvSb9c6j04V2BngkAtEgESoBgZl1oWYGSmCQpPMq1PaWvFHaCf8YjrzeZKTm7pfWvmXVWNonFyk6x5O1zLVdVSD98aJbjOwRljxJ3V53aTX06xOt4UbkeW7g10NNBU1r1vLT988Y1tQaCVYEVKEmvua3jQKnTyebv84Y3a26vzYY3zd/utt2l3udKI2dItjCTOXh4s1+mDQAhr67SW7n7pIIj9TuPVXYrId2U2fImLMx1nVCXiChp1A1Sopf/p9RHgJu51yUjOVYvXjdS950/QDab9OqKPfrl/9aoqIyykggx2Tukj+42yw0pzwoAIFACBLUO/c3YcaAZbTZX8ESqvT+Ju6g20mm/Msur/2vG6oGSI9UCCtXv0LfuZgviHiWWyPAw3XfBAEnSS8t2a9shGru3WiV5Zty3OrDzAPzNbnfLKEnzvs/Ai8y4Z1n9z/vdPDOePMN8uZbcVeo72az7fn6DpgoAqCauljJVeQekJ0dJ/xggfXi3lHew7vNY2d+1ZZM0pyArvVWdzWbTz8f20FPTRyg6IkwLfzisa/+7SgWlBEsQIirLpXduMJUnJCn/QND+ewWAYEagBAhmJ/9cuvZDacyvXOviUlzLdfUncTf0SiksUjq4Tjq4Xtq91KyPd3wBd7Ran5JcR0ZJeLTnevceJaV5UlVwprWf3idV4/t3VGWVXQ988D21ilurMkcQbP9q88Uy0FoUHzflFSXXXbzVZQw348EN9T/v4e/N2H2sa12nk8x4fJdPUwy43cukRwdK614N9EwAwJP1Wb2wWubIj4td5XNXPSc9Pqzumz1O1J+kObkHSoL0878kTRqUplevH6WEmAit3HVM1/53pfJLKMWLELDkb+aaKDpJSnBkmfnyGREAIIlACRDcwiPNF1qRMa51vmaUSFJce6n/+Wb568dcX5YNv8qM1Ru6W6W3+k32XB/vllFir3J9UR2E/nBef0WFh+mrbUe1cDN307RKpY7fv6LslvclL1AXK5sktp0UEe19n7TBZszdY/pKnUjBEceXdjbP/3ckdzNjzp4GTzcgvv6H+X/VB3fUzIoEgEBylt6qFijZu9yMfSdJ6UNNP8BVz9d+HiujJKWP/+foK+v6w14pFdfj/zkBNKJbO73yi1FKjInQ6t3H9bPnV+pYYVmgpwU0newd0ld/N8vnPyp1P80sH1wXsCkBQEtFoARoaax0fqn+GSWSq2nvd+84js2Uuo0xy0drKb3VaYSU4vYacR2kyFhXpkmQ9imRpO4pcfr52B6SpIc+/F6lFZUBnhH8rtQtULd/TeDmAfhbvqMci7f+JJaYJKmt+Rung+tPfM4jjh4k7XqYkoyW5K5mbEmBksKj0vYFZrmiRJp3gyk5AQDBwFl6q1qgZM8KMw7/mXTuA2b5x0W1Z8UGU+mt8EipTXuzHIR9Sqob0jlZr15/qpJiI7Vub44u/vc32nm0MNDTAprG5/eZvnW9x0uDf2oCsVL9Ph8CADwQKAFaGiudPzzaNOStrx5nSkldXc+7neYKtBz70fNLpjxHoCSpk9RjnFm2hUlt2pllq/xWkPYpsdxydm+lJkRrV3aR5nyzK9DTgb+VFriW960K3DwAf3P2J6ml7JbFlwthq1l7hwGe661ASd5+qbKF1HLf9La5qzmlrwkYHVjrupMSAAIt3pF9UXjYFQQpznEFrLuMMo/waNNHwCqx5a6qytXMPRgCJZJbQ/eWkak9qFOS3rpxtDolx2pXdpEu/vc3WrUruLNhAJ/t+kb64QNzrT7hIbOOQAkANBiBEqClsdL5U/pKYeH1Py4sTDrpZ67n3cZIiZ2kqHhzB8qxH13brIySxM5SzzPMclyq6/Ws8ltBnFEiSfHREfr1RBMMeuKL7TqcXxLgGcFvKsulimLXcxq6ozUpsAIldWSUSHVfCL9/u/ToAFfQxSq52KG/537xHc2XdfZKV5A82G14w4wnz5B+4giQLP6rtPK5wM0JACxWmaqKElf2q3VDR7ueJpASGSt1PdWs+3FRzXPk7Tefc8IiXSUSAy3IG7p706djgubNHKOhnZN0vKhc059bofnrDwR6WoB/VFVJn/3eLJ90teszXtoQM+bsNn3vAAD1RqAEaGmsBr5Wpocvhk2XbOHm0X2sZLO56h5bfUqqKs3dbZLJKOkzQRp8mTRulus8MclmLMlpyE/QrC45qbOGdE5SQWmFHvl0y4kPQMtQWq0/TtYGqaI0MHMB/M2ZUZJW9361BUqqqqQNb5ov2ja/b9Y5M0qqBUrCwqTkLma5JZTfOrrdlNqzhUuDLjYlJkZca/pmfXS39MGdlOECEFhRcVJknFm2+pTscfQn6XKqa7+eZ5rRW6DEKrvVrocUHtEUs/Sds6RYE5beqvJ/qdwOCTF6/YbRmjCgo8oqq/Sr19bqX19sU1VVLSXPgJbih/dNVm1UvHTW713rY5NdlSeshu5VVc09OwBokQiUAC1N97HSXVtcqbW+SOokXfmmdMUrri/grB4kRx1BhILDJsPEFibFp5lGwpc8J51yves8LSSjRJLCwmz64wUDJUlz1+zThn05gZ0Q/KPMUXYrPNo0vK4sk7I2BXZOgL9YPUri6xkoObZDKslzrc/ZJZU7arHv+MKUfqmt9JbUsvqUWNkkvc42dzfbbNL5j0nn/FGSTVr9vPT5HwM5QwBwK7/lCJTsdfQn6TrKtY8VKNn1Vc3Sh8HUn8QS38SBkj3Lpf/rJC18wO+njo0K11NXjdAMR//CRz7bqkueXqpN+4P/Wgao1bbPzDjiWte/T4v7zTRHt0l/7ye9fb0AAHUjUAK0RAlp5i7ghugzXuo32fU8ta8Zjzgauufuc7xGRu13sLWQHiWWEd3aaurwTrLbpfvnfyd7bU0z0XJYGSUxiVKnEWaZPiVoLfIdX0KdKKMkLsWUSJSkrI2u9Ye+dy3vXCId3yWV5pkSLu161TyPM1Cyu8FTbhaVFa5AydArXOttNun0O6ULHjPPt33a7FMDAA9xbmWqKstdJULdM0rSh5os7dI86eA6z+ODMlDSxD1Ktnxkyo199Xdp41t+P314mE33nj9A/zd1sOKiwrV2T44u/NfX+uN7m5RbTCYiWqC9jmuf7mNrbrMCJQfWSu/dYnombXpLKqJPDwDUhUAJEOqqZ5TkOQIlSZ1qP6YFZZRYfjMpU7GR4fp2Tw61iVsDq5F7VLzUeaRZ3k+fErQS+fXsUSJ5L7916DvXclmB9O1LZjmljxQRVfMcLSWjZOUzJpgTk+wZ8Lf0dazL3iGVFTXr1AB/WLJkiS644AJlZGTIZrPp3XffrbHP5s2bdeGFFyopKUlxcXEaOXKk9uwJ8n+7oci6u7vwsKM8aLH525XS17VPWLirlO6PX3oebzV4D8pASRNllFg3bUnS/Fs9/1/mR1eO6qqFd52p84ekq8ouvbhst875+2K98+0+bqZCy1F0zHX9bl0LubM+H37/rrTXUfrPXmUyjQEAtSJQAoS6VEeg5MhWU7vU2ci9rkBJshlbQI8SS1pSjGaeZe6knv3RDyoqqzjBEQhqVkZJdILU2cooIVCCVsBud2vmfoKMEqmWQImjDJ0t3Iyr/2vG6v1JLFaj4GAOlOTslb74s1k+90+mB0B1CR0dTZTt0pHNTT8nu136cra065smqauP0FNYWKihQ4fqySef9Lp9x44dGjt2rDIzM7Vo0SJt2LBB9957r2JiYpp5pjihuBQzFh6V9jjKbnUZVTMjvOcZZvxxsef6bEegxOolGAycwZ8jTXP+Iz+YMamLVF4kvXGVVF7cJC+VlhSjf115kl6eMUo9U+J0tKBUd765Xje/8q3ySsguQQuwf40Z2/Vy/b1xl+b4fGh39CZp19OM2z5v+rkBQAtGoAQIdW17mHIsFcXmTt08R6CklWWUSNIvTu+pzm1jlZVXoqcW7Qj0dNAYpY5+DNGJUvpws3x8J3eRo+UrPm567kiuu3fr4i1QcthRemvgVDNaQe1aAyVBnlFit0sfzTJ9V7qOloZfXfu+HU1Pqqa6E9nDoe+kxX+RXr64yb7MQ2iZPHmyHnroIU2dOtXr9t///vf6yU9+oocffljDhw9Xr169dOGFF6pDhw5e90cAWaW3sjZKa182y+79SSw9zzLj3hVSmaO3VH6W4++xrfa/24HQlD1KyotNmUhJmj7X/P/v2I81A0h+NrZPij6+/XTdPaGvIsNt+nhTls5//Gt6lyD47V1pxi6neN8en+q68bHbadIF/zTL2z+nsTsA1IFACRDqwiNcPR6+m+fqUWLVvfemhfUoscREhuv3PzEXnM8s+VF7j/GleotlNXOPjpfatHNlOR37MWBTAuql4Ii06C+usirVWY3c27T3XiarOitQcnSL+ZKtrMiUnpKkMbd47uutkbvkyijJ229q6Qebze9LWz82Qf0L/ll3j66Og8zYHIGSze+bsdc55m8R0ISqqqr04Ycfqm/fvpo4caI6dOigUaNGeS3P5a60tFR5eXkeDzQDK6jwwwfS4e+k6CRp4MU192vX02RQVJZJe5aZdbuXmjFtkBTbtnnmWx9W8L4o2///r8jeLsluPs+lZkq9zzXr96307+t4ER0RrlvO7qO5N45R57ax2nOsSJc/s4xgCYKb9W/DW9kty6hfSmmDpQufMDeaRCeaf78H1jbPHAGgBSJQAkA6yXF37rcvugIlrTCjRJImDUrT6J7tVVZRpdkfN0NpFjQN99JbNpvU3tGg2mp+CgSjynLp9SulRbOlOee7Sh2686U/iWTKcyV3NaUVtn3uKF1il9qkSBnDXX2opNrvTI7vIEXEmHPkeZlTIFWUSp/93iyPvd1VLrI2VkZJ1ib/z2PZv6UD61zrrEBJ/wv8+1qAF4cPH1ZBQYH+8pe/aNKkSfrss880depUXXzxxVq8uPa77mfPnq2kpCTno0uXLs046xAWl+paThss/XKR1K5Hzf1sNrfyW4vMuPsbM3Y7rSln6LvYdq6Sjv4uv3XE0WshNdP8N+ni+PJ3b9MHSizDuiTrw1tP16k926mwrFLXvrBSu7MLm+31gXqrqpT2OUpv1ZZRIkmn3Sbd+LW5TgqPlHo5Mti2fdb0cwSAFopACQBTniU6yaS8W3eYtLIeJRabzab7LhigMJv00cYsLd1xNNBTQkNYgZIox13cVrPTY5RUQxBbcL/rDsCCLOnVy6XSAs99rEBJfcpuSeYLpUGXmOWNc12ZFFbAoNfZZoyIlZK7136OJMeXp8FWfmvls2ZOCenS2DtOvL8zo2STKdnlD3a7NP9X0qf3mEBXRanJ2jn8nRQWIfWd6J/XAepQ5SiVMmXKFN1xxx0aNmyYfvvb3+r888/X008/Xetx99xzj3Jzc52PvXv3NteUQ1v3002weuT10ozPXf0BvLHKb1llpnYFaaAkLKzpym9Z/UmsYHhnx5e/+9dIlc3XVzCpTaSeu/pkDUhP1NGCMl3935U6kl/abK8P1MvhzVJZvrkOqi1b2Js+E8xYn0DJsR+l5ydKmz9o2BwBoIUiUAJAimojDb3c8cTxxVJSHaW3WnBGiST1T0/UlaNMTf7753+nsgrqtLY47hklkmlkKEnZlN5CkNr8vrTsX2Z58sOmfv2hjdLbMzxrRVult+qbUSJJgy8147bPXCVbrIBB5k/M2GVk3SWrrD4lx3fX/3WbWtExacnfzPLZ93pv4F5daj9zx3NJjpR3wD/zWPKItOF1s5y3X1r7P2nzfPO8++mm/B/QxFJSUhQREaEBAzy/FOvfv7/27Kk9wBkdHa3ExESPB5pBXHvphkXSeY9IkbF179tjnBmzNkhHtkpHHBnP3cY06RQbxBkoOezf81YPlKRmmjJB5UUmKN2MEmIiNefnI9WlXax2ZxfpujkrVVDafMEa4ISsm246jZDCwut/XO/xZjzw7Yn/DW94U9q7XFr1XMPmCAAtFIESAMaIa13L4dGmbEttWmiPEnd3ndtP7eKitPVQgZ77ii/XWxxnoMTxhQ+ltxDMKstNRoIkjb7F1Iye9popd7X1E2nLR659rbt0E9Lqf/6OA80dhZVl0oY3XOsk8wXc1fOlqc/UfY5gbOi++GETkO84WBp6Rf2OiYiWUvqaZX/0Kdn0tvTlQ2a555lm/OpRadM7ZnnAhY1/DaAeoqKiNHLkSG3ZssVj/datW9WtW7cAzQp+Ed9B6uD4m734L2ZMzZTi6vgsHihWtqPfAyVbzWgFSsLCpM4nm+VmLL9l6ZAQo5d+Pkrt46K0aX+ebvzfGm6sQvDYu8qMdZXd8iYhzdXbbseXde97cIMZs8nWBxBaCJQAMDoOdKW5J2bUfedxlOMu/opizzuhW5C2cVH6w3mmXv/jC7dpTzaN3VsUZ6DEKr3lCJRQegvB6MgWqfiYCeyNv9+s63yydOpNZtnKNJHcMkp8CJRI0uCfmtFeacaObned9zzD/F2vS1vHF63BEigpOOK6i3HCg77dMZnmVn6rMSpKpY9+bZZPnSlNe8Nk+uTtN3d+yyb1O69xrwG4KSgo0Lp167Ru3TpJ0s6dO7Vu3TpnxsisWbP0xhtv6LnnntP27dv1r3/9S++//75uvvnmAM4afmEFYq0gbDBmk0gmG1Lyb+mtijLX57fUTNd667pk3yr/vZYPeqTE6YXrRqpNVLi+3n5Ud89dr8oqP5V0BBrD2cjdx0CJ5AqUHN9Z935ZG82Yu1cq4zoZQOggUALA5ZTrzXiiWqfhka7lqvKmm08Tmzq8k8b0aq/Siir94b1Nsvurnj2aXpmjr0P10luFR1psSTi0YlmOu/LSBnv+/Tzll1JYpLRnmbRvtVSYLe1ZYbbV1SfKG6tPiSTZwjy/bKqPYMsoyd4mVVVIyd1czUfry8qmaWygZPP7UtFRKSFDOvcBKTLGs09K11OlhHr2kgHqYfXq1Ro+fLiGDx8uSbrzzjs1fPhw3XfffZKkqVOn6umnn9bDDz+swYMH6z//+Y/efvttjR07NpDThj9YgRKrBG6w9SexWKW3rH5a/nDsR/P3Pire8/99AWjoXt2Qzsl6+qoRigizaf76A5pFsASBVpjtyqC3sq58Ee+4Eaeuf8NFx6Rct8+Dx6i+ACB0ECgB4DL4UunKudJ5f697P/cv+irLmnZOTchms+nBiwYpKjxMS7Ye0by1+wM9JdRX9R4lMYmuuxxJEUewscoXpA3xXJ+Y7uovsvRx6b2ZUuFhUzrK1+BA2+5Sl1FmuX3vE9fEry45yDJKrMwaXwNGkltD90aW3lozx4wn/UwKj3AsX+P8kqEq83y9sWqP5q6mOTb848wzz5Tdbq/xmDNnjnOfn//859q2bZuKi4u1bt06TZkyJXAThv90GyOFRbg9D9JAiZXBa/UU8YejjnJyKX0lm821vpPjS+DjO02WYYCM65uqx6cNV3iYTe+s3a8731ynisqWmVGPFmLV89ITJ3sPUOxZZsbUzIb1SLNu8KgrK8zKJrFkb/P9dQCghSJQAsDFZpP6TjBf3tUlPMq1XNlyM0okqVdqvH51Tm9JprH7obySAM8I9WIFSqLiXeuc5be46wlBxrrgTBtcc9uYW8z4/XvS1o/N39ef/tf3QIckDf+ZGbue6vuxVkZJ3n6ptMD34/0tvwG9WixWRsnRbVJ5A/+mH90m7frKZOecdLVrfWSMdOkcHR44Q5evydRv3t6oBz/4XtkFpQ17HQCQTClRq4xOu54n/iweKM6Mve8kf2ViH3EESqpnQsYmS6mmTK6z1FCA/GRwuv41bbgiwmx6b90BPfjB9wGdD1q5b180wYltn9fcZgVKuo5u2Lnrk1FiZUJb6AEJIIQQKAHgu7BwSY47vlp4oESSbjyjlwZ3SlJeSYV++/YGSnC1BNWbuUuu8ltklCCY2O2uQEn6kJrbOw6Uep3jen7uA94DKvUx/CrTuP3cB30/Ni7V8W/I7moIH0jOXi0N+LIwIV2KbWf6tTT0rmcrm6TPBCmps3P19sP5um1ZjE5Zc45W7S9VfHSEfnVOHyXGRno/DwDUV98JZux1dmDnUZfU/iaAXHzM9Xe6say/01Yjd3dBUH7LMnlwup6YZsrivbhstxZvDVyWC1qxqirpyFazfHxXze1WoKShfYysG1DqyiixMqGjk8x4lEAJgNBBoARAw1hZJS249JYlIjxMf79sqKLCw/TlliOau2ZfoKeEE6leektyZZRw1xOCSc5uqTTX/M2srW/IuFmm5Erm+dKoGxv+Wjabadwem9ywY60+VSuf89+dwg1l3enYkB4gNpvrv3VD/h6Ul0jrXjXLI66VJP2QlaeZr36rc/+xRO+tOyBJuvikTvrirjP0i9N7KjKcj9QAGmn0LdIlz0vn/DHQM6ldZIzUvo9Zbmx5Q4szo8RLoMTKstm/xj+v1UiTB6frmtGmVOWsueuVU9Tyr4MQAEe2So8Nlr79X81tuXukimKzXD1QUlYoHVxvlhuSPSxJ8W6lt6pqKSFn3eDT/wIzcm0FIIRwVQegYaw+JS24mbu7vh0TdOeEvpKkB9//XgdyigM8I9TJGSjxVnqLjBIEEeuuvA79Pfs7ues2Wrp7m3TZ/zzrsze3YVdKkXHSkc2m7FRTy94hbVvgfVuBFShpYPkZq5RYbgP6h6z6j7lbOrGTvos7RTf+b40mPfaVPtxwUHa7NGFAR71/y1g9etkwdUiMadj8AKC68Ehp8E9N37VgluboA1W9j0FDlOabUoeS90BJhwFmDKIvan87ub96psbpcH6p/vDuJjLR4bvv3zM94VY8XXOblU0i1QyU7FslVVVIiZ1dn3N8ZQVKqirMZ53qyoulo445DJpqxuxtgb+BBgCaCYESAA1jfeHXCkpvWa4/vaeGd01WfmmFfkMJruBVUeoK0LlnlLRzyyjhvUOwsOo8n6icVpt2UliAP5bFJElDrzDLK55p2teqKJVevEB65RJp55Ka250ZJQ3oUSJJyV3MmONjoGTb59Ln90qSXom8WOf9a7k++S5LNpt03uB0fXzb6Xr26pM1uHNSw+YFAC1dR0eg5NCmxp9rwxtSZanJUmnbo+b2do51+QfNF7hBIDYqXP+4bJjCw2z6YMNB/euL4AnioIWwAn+HvpOKqgUr3EuGHt/teU2zZ7kZuzWwP4kkRUSZ8qSS9z4lh743pUvbpEjdTpNkk0pypaLshr8mALQgBEoANIyz9FbrCZSEh9n0yKVDFR0Rpq+2HdVrKxtwJzKanpVNInk2c2/X04wluTUvOoBAcTZyHxrYedTXKTeYcctH5m7HprLuFdM4XpLWvlxzu3XxHt/AQEmSFSip/8+wZ/Nqlb5+jWSv0hsVZ+r3+09VmE26cGiGPr19nJ6cfpL6pwf5nd4A0NScgZJGlt6y26VV/zXLI2d4z6iMbevqk+CtX0OADO2SrN//xDSa//vnW/Wfr34M8IzQojgzpOyuniMWqxSdJJUXSoVHXc93LzVjQ8tuWZx9SrwESrIcpb3Sh0iRsa7PU9ac7XZuSAPQqhEoAdAwYVZGSeuqzdsrNV6zJprU/z9/+L32HisK8IxQgxUoiYyTwsJd66PaSImdzDLltxAoVVXSB3dIS/5mLiSt0lveGrkHow6ZUo9xkr1KWv1C07xGZbn09T9czze/7xkALSuUSvPMcoMzSupfemt/TrF+88ZqVb1+paIrC7WscoD+ZJ+hi4d31ud3nqHHpw1X344JJzwPAIQEq/TW0W2mp1ND7VkuHf5OioiVhk7zvo/NJrXrbpaP7Wz4azWBn4/toTvPNWV7H/pws15evjvAM0KL4V5Kzgp+WI5u8XxuBQgry03pLUnq2sBG7har/Fa+l4bu1ufWNMfnVqu08dFt0uEfpL90k969qWmCJZUV/j8nAPiIQAmAhmmFpbcs153WQyO7t1VhWaV+/dYGVVVx10xQ8dbI3eJs6E6gBAFy+Dtp9X+lLx4yJZzyD0iySR0HBnpm9Xfyz824cW7tjT4bY+NbJtOjTYrJBCsvkr6f79puZZNExnn/d14fVqAkZ4/Xi3m73a61e45r1tz1OuuRRapYP1fdbYeUE95Ox87/j5bfO1mPXj5MvVLjaxwLACEtId1ketgrPcsE1UdlhVRVaZZXP2/GwT+VYpNrP8YqyXU8uAIlknTr2b31yzNMRvMf3t2kF5fuCuyEEPyKjkklOa7nu752LdvtroySNilmtAIlWRvM56WYZCk1s3FzsPq/ec0ocWRCWzf4pPQxY/Z2adH/SaW50vrXpO/mNW4O1R3ZIj3aX3pvpn/PCwA+IlACoGFaWTN3d+FhNv3tp0MVGxmuZT9m6+UV3CEWVLw1cre0723G/aubbz6AO/dST0ufMGO7ng3/wj8Q+k6SohJMNsbeFTW3Z+8wwY6G3E1YVSV9/ahZHj1TGjbdLK9/zbWPsz9Jx4Y3t7eyy8qLnKX4yiurtGxHtmZ/tFnn/mOJpv57qeau2afyigrd0eYjSVLyWbfpvFEDlRgT2bDXBYDWzmZrWJ+SomPS48Okv/WSPrzLNLSWTNmtulh9SoIso0SSbDabfjspU9efbub4x/nf6bkllOFCHaxskijH58KsDVKJI4s2/6DJqLWFS73ONuusQMluR4murqc2vqddQi0ZJSV5rn/TVslY69pq66eeN7V8NMt/pY6rKqV3b5YKD5vXAYAAatRf2L/85S+y2Wy6/fbbJUm7du2SzWbz+pg7d26t57n22mtr7D9p0qTGTA1AU3P2KGldpbcs3VPi9NvJ5m6d2R/9oF1HCwM8IziVFZjR2xfPmeebce0rnjV9geZiNQ+3/kZKLafsliUyVup/gVneWO3zW2WF9PIl0tszam6rj6X/lI5uNY3jR/5CGnK5JJu06yvTtFRy3eFo3fHYEJExzv4mC5ev1k0vr9FJD3yuac8t1zNLftT2wwWKjgjTxSd10mc/KVLnij1SdKJ08nUNf00ACBUN6VPy9T9MAL74uLTqP+YaIuMkKWN43cdZPeiOBWcAwmaz6Xc/6a+ZZ5ms5j9/tFk3vbxGWbmNKEuG1ssKlHQabrKl7FWum1KsbJJ2PaUUU9bNFSix+pM0opG7Jb6WHiWb3pYqSqSUfq4sfStQcmSzJLu5mSa1v1R0VPrkt76/tt0ubf5Aevmn0jePm8+VK5523eRWeJQSXAACqsGBklWrVumZZ57RkCGui/8uXbro4MGDHo8//elPio+P1+TJk+s836RJkzyOe+211+rcH0CAhUWYsRV/kPnZqd00umd7FZdX6u6561VJCa7gUFfprV5nmwvuimJp+b+bd16A5OqJcfIMqfe5Zrn72MDNp6GGXGrG7+Z5lljc8Iar/MmKp70fW5wjlRfXXP/V36UF95vlM34jxSRKyV2kHqe7zi25ZZQ0sD+JpH3Hi7TPbspWzF24VB9vylJ+aYXaxUXp4uGd9Pi04Vr5+/F69NKh6rP1P+agk39uAjgAgLpZfUqsMj0nkndQWvmsWT7rD9LAqVJiZ+mce098bBCX3rLYbDbNmpip30zKVHiYTR9vytL4Rxfr9ZV7TnwwQosVKGnfW+p2mlne/Y0ZrUBJaj+pbXezfHyXybjY7SjRZX1maozaMkq+fcmMJ13tyui1AiWWM++Rpjwp2cLM5zb30mEnsm+N9OyZ0hvTpe2fmxK1z50pLXzQbSe7ySwBgABpUKCkoKBA06dP13PPPae2bds614eHhystLc3jMW/ePF122WWKj6+7xnN0dLTHce7nra60tFR5eXkeDwDNrJVnlEhSWJhND/90iOKjI7R693H964vtJz4ITc9q8hzlJVBis0mn322WVz5nvrAFmpNVeqttd2naa9KMBdJJ1wZyRg3TfZwU10EqPibt+NKsq6wwTeot+9eYi17JBEbWvCi9eKH0cA/p2bNcdeglc9zCB8zymb+TTr3Ztc1q4rvZUdIh/6AZ430PlOw8WqhZc9frzL8t0to889lzUFyObjunj96deZpW/368Hr18mC4cmqGk2EhpzzJp30rz/7RTb/L59QAgJFl9tw5tql8Zxq8eMXeqdxkljbtbunSOdOd3rvJCdbFKb+XsCfobtG46s5fev2WshnVJVkFphX77zkbd++4mlVc2Qb8vtExWH8X2vaXujkDJLitQ4uj5Uz1QkrVRKsk11z5WSazG8JZRkrVROvCtFBYpDb3CtT6pixQebZb7TJQyhkmdR0jDf2bWrZlTv9e026U3fyYdXGd60J10jem3krXR3ODW/XTXvPK99E4BgGbSoEDJzJkzdd5552n8+PF17rdmzRqtW7dOM2acoO6opEWLFqlDhw7q16+fbrrpJmVnZ9e67+zZs5WUlOR8dOnSxeefAUAjWYGSVtijxF2Xdm300EXmrrl/LtyqVbv8VIsVDVdaR+ktSer3E5MSXppngiVAc8rdZ8bkLqaXU5eRUnhEYOfUEOER0qCLzfLGN13j8Z2mwWj/C826lc+YIMn/pkrv/0raudiUkTiyWdq3yuxTeFT6crZZHn+/dOZvPHuP9DzTjIe+k8oKXXc4+pBRsu1Qvm57fa3O+fsizV2zTxVVdtkdDd1vHh6tO87tq2FdkhUWVq3nyca3zDjk8kZlsABASEntb/ooFB93Bbdrc3yX68vUc+7zvfdUQob5oraqQsrb15DZNqsBGYl6+6YxmjWxn2w26X/Ld+vaF1Yqt6h1XzOhntwDJd3GmOUD35rPP0e3muepma5ASd5+acdCs9xtjH8+U7pnlFiBzm//Z8bM86S4FNe+YWGO140yn98sJ11jxs0fuHqs1CV3r/lZwiKk29ZJFz4u3bLa3CyTMVy68AnX57CCQ3WeCgCaks+Bktdff13ffvutZs+efcJ9n3/+efXv319jxoypc79JkybppZde0sKFC/XXv/5Vixcv1uTJk1VZWel1/3vuuUe5ubnOx969e339MQA0lvUhrbL1f+i/aHgnXXxSJ1XZpdteW6ucotabRdMi1NXMXTIf6Mc5skqW/1sqK2qeeQGSq/RWUiu4iWOwo/zW5vel+bdKixyf/U77lTT2drO86R3p9ekmMyM6STrnj+aOQ+s4yWSK2CvNhfDYO2q+TmKG+SLMXiUdWOv60q0ePUq+O5Crm19ZowmPLdF76w6oyi6dndlBb980RheOGyVJCsut43PigbVmrM9dzQAAIzJGSuljlrPqaOheXiK9f5sJcvQ8q2GlKMPCpLbdzHIQNnT3JjzMppln9dYzV41Qm6hwfbM9W5c+s1QHc72UpUTrVpwjrXjWZITY7dIxR6CkXS8puZuU1NX8+3j7eunwZrMttZ8JVkS2kWSX1jnK0vurlKuVuVFRbG4sKy+WNrxu1p10dc39L/+fdOsaqdMI17pOJ5leJhXF0vfvnvg1D643Y4f+UnwHxzxSpalPSzcsMpljCWSUAAg8nwIle/fu1W233aZXXnlFMTExde5bXFysV199tV7ZJFdccYUuvPBCDR48WBdddJE++OADrVq1SosWLfK6f3R0tBITEz0eAJpZCJTecvfAlEHq3r6NDuSW6IaX1qi4zHsgF82grh4lloFTzcVH8THX3fBAUysvlgqPmOWkzoGdiz90GiF1GGjKpXz7kil70qa9acLeaYTU6WSTVbhjobnbd9pr0ul3SsOuNMf/8KH5UuC7eeb5wKm1v1bnk824b7Vbj5KOte6+fm+OfvHiKp33+Nf6aGOW7HZp4sCO+uDWsfrvtSM1oltb8+WDJOXUEiipLHc1Is4YVr//JgAAw738ljcVZdLca6QfF5kvfCc86H2/+mgBfUq8mTAwTW/dOEYdE6O19VCBLvn3Um07lB/oaaE5LX9K+niW9OHd5kaQ8iKTjdW2m8muOu8R8xlqy4fmukU2qX0fs83KKsneZkZ/9CeRpKg2UrTjO7T8Q46skFzzuannWTX3j06QHFm6TjabNMxROnXdqyd+TStQkl5H6bB4x+c+MkoABJBPgZI1a9bo8OHDOumkkxQREaGIiAgtXrxYjz/+uCIiIjwyQN566y0VFRXp6qu9RKRPoGfPnkpJSdH27fQDAIJWWKQZQyCjRJLioyP07+kjlBAToZW7jummV9aorIJ6wwFRVo9ASVi4dMr1ZnnFs6608j3LpdUvNO38ELqssltR8VJs7b3WWgybTfr5x9LlL0tj75T6nWcaeEbFme2n3ODYL0z66fOuWtu9x5uL/uM7TSkuq9HngItqfy0rULLfPVBSM6Pk2z3HdfV/V2rKk99owebDstmkC4Zm6NPbx+mZn52sQZ3cmrFbF/W5tTTTPbxZqiw1DdytL+EAAPXT0dHQ3VugpKpKeus6aesnUkSMdOUbUtrghr+W1aekhWSUuLNKcfVMjdOB3BJd+swybdqfG+hpobkcdTRo/+4d1+ehtt1NeVZJ6jtRuvpd81lEMqVbo9q49rNEJ0lpQ/w3L2dQIkva5ChDOmyayeCqryGXm8+Ae5ZJx36se19noGRY7fuQUQIgCPgUKDnnnHO0ceNGrVu3zvk4+eSTNX36dK1bt07h4eHOfZ9//nldeOGFSk1N9XlS+/btU3Z2ttLTT1xyAUCAhIdWoEQyFzovXDtSMZFhWrTliO6au15VVfVoYAn/sjJKvDVzdzf8KnMH4+HvpN1LzZeiL02RPrjd9WEd8CerkXtSF99rsAermCSp/wXS+D9K016V+k12bRv8U9OY/fKXzT6W6Hipl+OOxPdvNyW1Oo1wlU7xppMjULLrG1cw1K1nyNGCUt09d70u/vdSLdl6ROFhNl1yUmctuPMMPTFtuPqlefl7kOwof1aSax7VWWW30oe1nvcLAJqLM1DyXc1tWz+RfvjAlW3YY1zjXquFZpRYOrdto7dvHKOhXZKVU1SuK59brvV7cwI9LTQHK6u1qkJa+IBZbt/bc59uY6Sff2oamo/5lWu9e6Ck2xhzI5i/WJ+xjm6Tdnxhlgde7Ns5EjNcfebWv173vvUJlJBRAiAI+BQoSUhI0KBBgzwecXFxat++vQYNGuTcb/v27VqyZIl+8YtfeD1PZmam5s0zZRgKCgo0a9YsLV++XLt27dLChQs1ZcoU9e7dWxMnTmzEjwagSVmBklbezL26k7u309NXjVBkuE3vrz+gv322JdBTCj31Kb0lmTv6h1xmlpc+Ib01w5QQklrkHYloAaxeGMmtoD9JfYSFm8aemefV3JZ5vhmtL7XqKrslmdJXtnBH2QlJkXFSdILKK6s055udOvuRRXprjcnYuXREZ31515n6+2VD1Su1ll5Fksl8iW1nlr2V3zq4zvXaAADfpDmu/49uM71I3G1624wjf+GfHlAtOKPE0jYuSi/POEUnd2urvJIKXfWfFVq581igp4Wm5t4nzVquHiiRTO+Oaz9wZcRLnoESf/UnsVhBiW9fNKW0U/pKHTJ9P8+w6WZc9qS06nmTTVZdfpYJftjCXCX7vCGjBEAQ8LmZe33897//VefOnTVhwgSv27ds2aLcXHNnX3h4uDZs2KALL7xQffv21YwZMzRixAh99dVXio6OborpAfCHEOtR4u7Mfh308E9N6vNTi3bozVV1NAqG/5UWmPFEgRLJVRpo68cms8RiNYsG/MkqvdUaGrk3Vr/J5oLYMmBK3ftHxUkdBzif2hPStHDzIU18bInuf/975ZVUaGBGot65eYz+dulQdW3fpn7zcJbf8vJ32j2jBADgm4R0c1OKvVI6stm1vqxI2vKxWR7k4x3qtWnrFigpL5a+elTa+pl/zt2MEmIi9eLPT9EpPdopv7RC0/+zXHNXcx3RalWUurIj2rR3rW/fs37HuwdK/NWfxGIFJaxMj/4XNuw8/S+Quo2VygqkD++U5vxE2rZAqnLr53lgnRlT+rnKinljNZknowRAADU6ULJo0SI99thjHuv+7//+T3v27FFYLfUN7Xa7rr32WklSbGysPv30Ux0+fFhlZWXatWuXnn32WXXsWHsDTwBBwFl6qyKw8wiQqcM761dnm7uBfjdvo5buOBrgGYUQZ0ZJHXeSWzoONB/eLVZt37wD/p8XkBNiGSV1iUuRuo42y51H1mwC6o1VfkvSDwVxmvHiav14pFDt46L00EWD9N7M03RSVx97v1jvRU61PiUVZW6N3If7dk4AgClZ6K381rbPpPJC83e/0wj/vFbbbpJs5rzPjJMW/kl69yZXD7oWJC46Qi9ed4omD0pTeaVds97aoNkfb1Yl5XxbH+sGmohYacytrvXeMkq8Sc00N53Ed3T9W/OX+Grft53ohpbaRERL18yXJj9ssoH3LJNeuUR6bLDpEynVr5G7JCW4ld7ylpkCAM2gSTJKAIQAZzP30Msosdxxbl9dMDRDFVV23fi/NdpxpCDQUwoNZT5klEjSGb82v6/jZpmeCv/P3nmGR1Wtbfiekt57D51QQu9VEBQRe8EKdsXejnr8jnqKeuzl2LvYuyiKDZAqLZTQOwRCegjpPTPfjzU7M4HUySQzSd77unKtPTN79l6BZLL3et73eUBauoW2QetakI4SxZh56ndv3O3N2j3Dz2rHsL/MB3eDnltO68myB6Zw9dhuGA12XLYGWASak4WSnN3q75dnYN2KTUEQBKH5aIu3mTaB7ju/V+PACx2X/2T0gIBYtZ27T42luVDSMQuVvNwNvH7lcO60FF29veIQt3yyieKKrlmA1mmxtWQdfg24+6rrorD+zXt/UDe4+nv15ch8EqiTA0dQd4gcZP+x9AYYcwvcvh5G36I6zQrT4NcHVP5Jc4USn3A1mqqtVqyCIAjtjAglgiDYRxe23tLQ6XQ8d8lghscHUlhezfXzk8gr6br/Hu1GRaEaPfybt3/P0+CRLDj9EfCLVs+J9ZbQFuSLUFKHAefBY7lN5pMczi3h+vlJzPndWj3oExLL0vtP4+GZ/fH3dLN/DoENCCW1tltDJMhdEATBXrSckiyLUFJRbLXEamkwdFNo2QZxY6zXczl7HHuOdkSv13H/mQn87/KhuBv1LNmdxSVvruHYiVJnT01wFLbXhd7BcN2vqvvCrwXuKb2mWn/PHIltR0n/8xxzLRQYB2c/C/ftUcIQwC8PQPpmtd2UUGJ0t1qUSVGbIAhOQoQSQRDsw2BUo6lrVz55uhl4Z+5IYoO8OHK8lFs+2UhFdU3TbxTsw2y2Wm+5N8N6S0OrwvKPUqNYbwmOpqZaVc+BWG81kxqTmXdXHuKsl1fy555sDhNNmd4HgGmjhxAX3MwcksZoyHpL88uWIHdBEAT7ibARSsxm2PcbVJdBcM+mF0VbyqwX4ZIP4dpF1mN3YKFE4/yhMXx181hCfT3Yk1nEhW+sYfuxAmdPS3AEBSdZskYNhm7jnTcfW2w7SgZc4Nhju3nCmY+rDpHjB6wFas3pWqnNKRGhRBAE5yBCiSAI9iEdJbWE+nrw4bWj8PM0kpRygr9/tx1zB/RM7hBUlYHZUnXeXOstW/wsQklRRof0tRZcmOJMFWird7Pe5AkNkltcwZXvruPJX3ZTUW1iQu8QFt83Fa/elrDS4F6OOZFWgZy5HUptbBwyktUo+SSCIAj2E9YPdAYoO6HyGDbNV88PvMjx3XoBMSoc3uAGYX3Vc5oNVwdnWHwQP94xgX6RfuQUVTD77bUs3S2B1h0eLaNEs41zJYJ6KKGz20SIGe7443sGKLFEI7gXeDbDDUDrtimSn39BEJyDCCWCINhHbUZJlXPn4SL0ifDjzatGYNDrWLAljVeWHnD2lDoXe35RrdvH91ue0IG7T8uPowklVaVWCy9BcAS19goxoJfLq8bYkVbAea+uZv3hPHw9jDx10SA+vWEMPcN84ZyX4NL50HeGY06m+W6ba2DPIvVcdYU1eDhqqGPOIwiC0BVx84TQPmr7m2shZRUYPGDIFW173rB+auwEHSUaMYFefD1vHJP6hFJWVcNNH2/kk3VHnD0toTVo3axaXporYXSHW/+Ca39uOwvSwZdB/Di13dwOM+koEQTBycidvCAI9mEQoeRkJvYJ5YkLlAXBS0v28WNympNn1ElI+Qu+ngMb3oEPz1bPefjZd1Hv7q0qnAAKJadEcCAS5N4sFm5N55K31pBeUE6PUB9+uH08V4yOR6f9PvtHq0wTR4aWDjhfjbt+VOPOH1Q3pF+UBLkLgiC0Fq1zL22jGi98E0J7t+05wxLUmLPX/mPUVMPv/1DFOC6Cv6cbH1w7iktHxGIyw6M/7OC/v+zGZJIu6A7JydZbrkhb5rTpdHDh2zBsDkz+W/PeIx0lgiA4GRFKBEGwD816yyRCiS1XjI7n5sk9AXjgm21sTMlr4h1CoxQcg6/nqiwcN2+oLFbP22O7pVEb6C45JYIDqa0adOGbYSdSYzLzzG97uOuLLZRXmTitbxg/3D6B3uGt+F1uLpr39qHlyh5m7avq8agbJchdEAShtUTYBE1P/zckXtz25wy1WG8VZ6nPdXs4sBjWvga/Pui4eTkAN4OeZy8ZzP1nqO/xnZWHuPWzTRSWyz1Xh8JkggJL0VxXvjYM6gbnv2YVVJtC6ygpamZBm0myQQVBcCwilAiCYB+1HSWSUXIyD53VjzMHRFBZY+LmTzZx9Hips6fUsVj+NLw9Gb66Gj69GEpzlXXOPTtg6NVqn8Bu9h+/NtBdOkoEB9IRqgadRGF5FTd+lMSbyw8CMO+0Xnxw7SgCvNzaZwKhfSB8gBL2f3tY5ZW4ecPI69vn/IIgCJ2Zfueo0Obxd8KEu9vnnB5+4G/JfcixM6ckc7saC1KhLN8h03IUOp2OO6f14aXLhuBm0PH7zizOeWU1O9Ik5L3DUJyprjt0Bqv1r9A0WkdJcTM6SlL+gqdiYf07bTsnQRC6FCKUCIJgH2K91SAGvY6XLx9KYow/eSWVXDd/g1SBNZeqMljxLGRshd0/Ke9pr2C47DPwCYELXocbl8Lsj+0/R21HiQglggMptHQouWJgpxM5mFPMBa//xbK9OXgY9fzv8qH8fWY/DPp27uTQ7Le2fqHGYVeDd3D7zkEQBKEzEtYX/rYPznyifbv0au237Mwpydxm3XbRrJMLh8XyzbzxxAR6cTSvlIveWMPXSanOnpbQHLQgd/9oMBidO5eORG1HyUkZJVk74YsrrBlzAGteUbmTh1e03/wEQej0iFAiCIJ9SJh7o3i7G3n/mlFE+ntyMKeEx3/a5ewpdQwyd6jQZa9gOOsZVZ0453vVtq0ROxJ8w+w/h18LW7oFoTmUWmz2vEOcOw8XYtnebC54/S8O5ZQQFeDJt/PGc/7QGOdMRhNKAHR6GHurc+YhCILQGXGGjeHJOSUpq+Houua/X+soAch23ev0oXGB/HLXJKb3V93qD363jX8t3ElVjcnZUxMaQyxZ7cO2o8Rsk83z5xOw9xf4xWKVV5wN+xer7cqS9p2jIAidGhFKBEGwDy2jRKy3GiTC35NXrhiGTgffbDrGkl0SStck6VvUGDsSxs5T1YnRwxx7jva03jKboaK47c8jOJ9yix2GZ4Bz5+ECmM1m3lpxkOvnJ1FUXs2o7kEsvGMig2Kd+G8T1s/qad/vHAju6by5CIIgCK1HE0py9yrR46Nz4aPzoOR40+8tL4QTKdbHWa4rlAAEeLvxzpwR3GfJLZm/JoU5768nu6jcyTMTGkQsWe1D6yipLrdeW5flw4ElavvIaji2EbZ9rYrrQHWVCIIgOAgRSgRBsA+thdhU7dx5uDijewRz48QeAPz9++2cKBFhqVE0ocTR4ogt7Rnm/ucT8Ew3OLq+7c8lOJfyfDV6BjpzFk6nqsbEPV8l8/SvezCb4YrR8Xx241jC/DycOzGdDqb+A2JGwumPOncugiAIQusJ66fG7D3wxyNgNkFNBexe2PR7be17ALJ3O35+Dkav13HXtD68PWcEPu4G1h3K4+z/reavA7nOnppQH/kWoUQ6SlqGuzd4WAprtJySvb/ULc78639WK1WAShFKBEFwHCKUCIJgH9JR0mzuPzOB3uG+5BZX8OiPO5w9HdemPYSS9uwo2blAiYnpm9v+XILzMJutQbBegc6ciVOpqjFx1xdb+DE5HaNexxMXJPLURYNwN7rI5ebAC+CmpcpPXxAEQejYaF2Chcfg0HLr8zu/b/q9mu2Wv8UOMntnXZsfF2bGwEh+vGMiCRF+5BZXcPX763l92QHMHWT+XQato0Sy61qOZr+l5ZTssPxOD7xQjbsXQpbNPXWVWG8JguA4XOTOVRCEDketUCIZJU3h6WbgxdlDMOh1/Lwtg5+2tkMnQ0ekoljZJ0Abd5RYhJKSbKhpw46o4hzIO6i2tdZxoXNSVQomy2dhF+0oqbZ0kvy6IxN3g553rxnJ1WO7Nf1GQRAEQbAH72DwCbc+1hZRU1ar/ILGyNpufY9OD2UnrNXrHYDe4b78cPsELhsZh9kMz/2+l/u+3kp5VY2zpyZoaGHuYr3VcnwtQsmJwyoD8NAy9XjK/0GfGdb9gnupUTpKBEFwICKUCIJgH3qL9ZYIJc1icGwgt0/tDcCjP+4QT+H6yNyubBP8oq2B622BTxjoDOpcJU3cSLeGYxus2yKUdG60bhK9Edx9nDoVZ1BZbeLur5JZtC0DN4OON68eztSE8KbfKAiCIAitQcsp8QqGc16GmBHq+m7Xj42/T+soiR1lXWw92Y7LxfFyN/DMJYN5/PyBGPQ6FmxJ44p318k9hitgNttYb8U7dy4dkaghavzjUVj2pOrOj0hUHcET7rbuN+pGNTYjo6SkopqMgjLS8stIzSvl6PFSUnJLyC4sp8Yk3ViCIFgxOnsCgiB0UMR6q8XcMbU3S3dnsTO9kIe/285714xEp9M5e1quQ3vYbgHoDUqIKUxT9lv+0W1znqPrrNvaQrrQObENcu9iv9PlVTXc/tlmlu7Jxs2g442rRjCtf4SzpyUIgiB0BXpNhZRVcMa/lfXlwIsgbZOy6hl9U/3vqam2hrdHDoLw/nB8v8op6T2t3abuKOaM607PMF9u+2wzW47mc8Frf/HO3JEkxgQ4e2pdl/J8qCxS22K91XKm/kPdFx75C5LeU89pHWPdxsPom1UXWP9z4PeHobJEiVM21+AV1TX8dSCXFXtz2JBygj2ZhQ266xn0OiL9PRnbM4SZiZFM7BOKp5uhjb9JQRBcFekoEQTBPgxuajRJR0lzcTfqeWH2ENwNepbuyebjtUecPSXXor2EErDab7VloHuqTYC7dJR0brpokHt5VQ03fJTE0j3ZeBj1vDt3JGcMEJFEEARBaCcm3Av374Phc9XjgReo8ehaKGzgGu/4ARX67u4LQT0gYqB6PntXm0+3rZjQO5Qfbp9AzzAf0gvKufSttfy2ox2y+IT6KUhTo1ewCicXWoa7N1z5FcSNsT6XeJEadTo4+zm4+D3w8FfPmWugpooak5kV+3K464stjHh8CdfP38hHa4+wO0OJJO4GPR5GPV5uBnzcDfh6GNHroMZkJi2/jO82H+PGjzcy5r9Lef73veQUVbT/9y4IgtORjhJBEOxDE0rEeqtF9Iv058GzEnhi0W7+8/MueoX5MrFPqLOn5TwytgI6iBrcvkKJfxSkYQ0JdDTVFdbvB0Qo6ex0wSD36hoTd36xhb8OHMfH3cD7145ibM8QZ09LEARB6Ero9dbgZ1DV+3FjIXUd7PwBxt126ns0262IRPX+8P7qcQcWSgB6hPqw4LYJ3PH5Zlbtz2Xep5u5/4y+3HF6b+lgb28KLUJJQIxz59GR8fCDq76Fn+6CgDgI7nnqPm5WEeqtJdv5aEs+GQVW67kIfw/OHBDJ2J4hjOoeRLi/5ymHqK4xkVtcyaGcYv7YlcXvOzPJKCjntWUHeGfVIWYmRnLu4Ggm9w3D3Sh15oLQFRChRBAE+9CLUGIvN0zswa70Qr7fksZtn23ixzsm0iO06+UaUFkKH8xUvrJTHla2BwDRQ9v+3FpHSUPVhq0lPbmuLZ0IJZ2bLtZRYjabefTHnSzelYW7Uc8H145ijIgkgiAIgiuQMFMJJanrGhBKtqkxMlGN4VpHyR4w1SiL1g5KgJcbH147iicW7Wb+mhReWLyPfdnFPHXRIHw9ZOmn3dCC3P3FdqtVePrDpfMbfLmgSocvBgzUMH/5TjIJIcDLjQuGRnP+sBiGxgai1zcuEhoNeiIDPIkM8GR871AePWcAi3dl8daKgySn5vNjcjo/JqfjYdQTG+RFTJA3fh5GdDrwdDMwIMqfofGBDIz2x8PYcT87BEGwIn8tBUGwD8kosRudTsd/LxrE4eMlbDmazw0fJbHgtgkEeLk5e2rty4kUqCpR28v/q8aAePBphw6bWuutNrIlSF1nPU9RhgglnZ0u1lHyytIDfLHhKDodvHL5UBFJBEEQBNdBE0Cyd9f/etYOy36D1BjcA4yeUF2mrk1DerX5FNsSo0HPv84bSN8IPx77cQc/bU0nOfUEL80eysjuwc6eXtdAOkranKPHS7n+oyS+N3vgrytlcIQbD08dyoyBka3KFzHodZyVGMmMgRFsPVbAwuR0ft6WTnZRBQdzSjiYU1Lv+0J83Ll2fHfmjOtGoLe73ecXBMH5iFAiCIJ91GaUVDt3Hh0UTzcDb88ZwQWv/cWhnBLu+HwzH147CqOhC7X05lsyWjwCVOCh2QTRQ9rn3FqAe/YuMJmU9YIjSd2gxj5nwuaPRCjp7NR2lHT+4NQvNxzlpSX7APjPeQM5KzHKyTMSBEEQBBvCLFZaxw8qK1Sjh/W1mipITVLbmtWr3gBhCcoONntXhxdKNK4cE0/vcF/u/SqZ1LwyZr+9lrum9eGu0/s0WWUvtBIto8RfhJK2YGNKHjd/som8kkrKPT3xp5S3L+uHLtpx/946nY6hcYEMjQvkH7P6k5pXSlp+GWknyiivrsFkMlNQVs22Y/lsSc3neEklLyzex5srDvLYOQO4fHS8w+YiCEL70oVW5ARBcCi1GSVt2FFiNkPaZqjunF0r4X6evDN3JF5uBlbtz+WJRQ1UvnVWTqSosddU5UHbcwqMrccioS2IHwsGD3VTvOJpxx7bbIajlo6SvjPUWFGg7ByEzokmhHVy660lu7L4vwXK2/2Oqb2ZM667cyckCIIgCCfjH62KcMw1kLu/7mvHNqriHO8QiBhkfT5ysOX1pPabZzswukcwv94ziYuGx2Ayw8tL9nPzJ5soKhfr5DaltqNErLccidls5pN1R7ji3XXklVQyKCaA4MBAAHRVZW12XoNeR/dQHyb0DmX2qDjmjuvOtRN6cPf0Prx/7SjW/980/nf5UAZE+VNaWcPfv9/OU7/sxmQyt9mcXJKUv+CFfrD3V2fPRBBahQglgiDYR3tYbyV/Bu9OhWVPtN05nExiTAAvXaa6KOavSWH+X4edPKN2RBNKgrpB72kw90foNr59zh3UHc79n9pe8Qzs/slxx847BKW5SojpMdn6fEWh484huBZdwHprw+E87vhiMyYzXDoilvvP7OvsKQmCIAjCqeh0EN5PbefsqfvaoWVq7HFa3W7ibhPUeGRN28+vnfH3dOPF2UN5/tIhuBv1LNmdxQWv/0VGQdstLHd5ajNKpKPEUZRX1fC3b7bx6A87qKoxM2tQFF/dMhajpyXns7LUaXNzM+g5f2gMi+6ayD3T+wDw9spD3PbZZsqrulCh3MYPlOV08mfOnokgtAoRSgRBsA8tzN1sartKeW3xetePbXN8F+GsxCj+Zll0/NdPu/g6KdXJM7KT1S/BJxdZF42b4oTFeiuoe1vNqHGGXgFjblXbC+ZZhZvWsnuhGuNGg4cfGL3UY7Hf6liYW1AF1snD3Dem5HHthxsorzIxNSGM/140CJ1ObDsEQRAEFyXcYr+Vvavu8wctQkmvqXWf724RStK3QGX9GQQdnUtGxPLNLeOI9PfkYE4J132YJJ0lbYHZDIXpalsyShxCSUU11364ge82H0Ovg/87ux+vXTkMb3cjuFmEkirnCSUaOp2Oe6b35eXLhuJu0PPbzkxu+ngjZZVdQCwxm+HIX2o7a1fj+wqCiyNCiSAI9mGwCR6vacVF9okjUJJ76vM11ap9E9QCdl7n7rS4fWpvbpjYA4CHvt/Gj8lpTp6RDflHoSir8X3MZlj1IhxcChvfb95xNWEisFurptcqznwcYkdDZTFs/bL1xzObYetXanvwbDVquRUilDiWvMPw+z+sVXuO5MBSeK437P65eft34o6STUdOcM0HGyitrGFi71DevHoEbl0pS0kQBEHoeIQPUGO2TUdJWT6kbVTbPU8SSgLjISBOZS+mrm+XKTqDIXGBfDNvHKG+HuzJLOL2z7dQVWNy9rQ6FyW5UFMB6MAv2tmz6fAUV1Rz3YdJrDuUh6+HkU9vGMPNk3tZC3bcvdXoAkKJxgXDYvjo+tF4uyt77Ws+3EBxRSfPdT1xWHWTgHJX6KSCs9A1kDtdQRDsw1YoMdkplBRlwhvj4MOzT63ezkhWHsIah5bX8/4s2L/EvnO7GDqdjkdm9eeqMfGYzXDvV8m8t+oQ5pZUtbcFZfnwxnh4ayKU5jW8X/4Rq7XUhnebFs/MZmuYu7M6SkD9HA+fq7b3/tL642Vuh5zdynar/3nqORFK2oY1r8La1+CrOUpYdST7/1D2aTu/b97+nTTMfctRJZKUVNYwvlcI784diaebwdnTEgRBEITGCbNYb9l2lKSsUp3wIb0hMO7U93Ri+y1b4oK9+eBalZG4cl8Oj/6ww/n3G52JQksBj284GN2dO5cOTn5pJXPfX8+GlDz8PI18csNoxvcOrbuTm0UocbGF+XG9QvjkhtH4eRjZcDiPq99bT0FpJ+7g0gpcATDXFakFoYMhQokgCPZhsLnws7ej5PAqqCqB3L2nhi0eXlH38clCSXUFzD8bPru4fhGlA6LT6Xj8/ESuGhOPyQxPLNrN/y3Y7txKr+zdSrAqyYbljYSeZ+6wbhdlNG2XVpKjKn90elXB50z6ngXoVLB7a7sTtlm6SRLOsnYXiFDSNmgdSembYfWLjj221uWWs7d5+3fCMPetqfnMfV9VwI3tGcx714zEy11EEkEQBKEDoHWUnEixZhdotlsnd5NoaDl5dRb8OieDYwN59Yph6HXwZVIqbyw/6OwpdR4KLK4Akk/SKlLzSrnozTVsPpqPv6eRz24cw7D4oFN3dHO9jhKNEd2C+fymsQR6u5Gcms8V767jeHGFs6fVNpwsMGfvdM48BMEBiFAiCIJ96A1qkRvsF0pS11m3U1bWfe2w5XHiJZbHK8BkIxiseRWOH6i7bydAr9fxxAWJPDKrPzodfLEhlVs/3ew8sUT7NwZIek8JJ/WRZRFKNAFt7euNZzxoi9z+Mc6vtvINg7gxanvvr/Yfx1QD279R24Mvtz6vCSYilDgWW1FrxTNKeD20AjZ/DCXHW3fsUotQkruved0qncx6a/PRE8x5fz1FFdWM7h7MB9eOUj7QgiAIgtAR8A0D7xDArAqywBrkfnI+iUb3iWpM2whV5W0+RWczfUAE/zx3IADP/b7XtWx/OzKFln9HySexm23H8rnwjTUcyikhOsCTb+aNZ3BsYP07a9ZbTgxzb4xBsQF8efNYQn092JVRyOXvrCO7sBN+vhxZrcYwSz5UlkUoMZth10IoznbOvATBDkQoEQTBfrRA95pK+95v6wF8eJV1u7oCjlpElIn3gLsflJ2AzK3qufyjsPJ5m+NssO/8LopOp+PGST15b+5IPIx6luzO4qFvt2EyOaEtPs+mwsxcA789XL8AogklY29TYkn6ZjiW1PBxnR3kfjL9zlZja+y3Di2H4izwCobe063Pax0lzQ25F5rGbIaCVLUdM1J5in90Dnx8Hiy8E5Y92brja0JLTaVV1GuI6gqoLlPbnaCjZNG2DK54Zx2F5dWM6h7Eh9eJSCIIgiB0QGxzSk4cUb75OoNVEDmZ4J7gG6H+9mtZJp2ca8Z350ZLRuID32xjY0ojNrtC89AKefxjnTuPDsqyPdlc9vY6cosr6Bfpx/e3TSAh0q/hN9SGubuW9ZYt/SL9+eqWsUT6e7I/u5jZb68lLb/M2dNyHPmpan1GZ4CR16nnNKFky6fw9Rz45QHnzU8QWogIJYIg2I/WPWCPUFJRZP0DCpCy2roAfywJqsvBJxwiEqHHJPW8ZrH128NqYTK4p3qctllV83cypvWP4I2rhmPQ6/h+Sxr/+XlX+3sIax0lY25V/9+HlsFfL5/6761Zb/WaCoMsIebr3mj4uNric5ATg9xtSbAIJYdX2d/5odluJV5Ut0tGrLccT9kJa4v9ZZ9Y7du8LC356Vtad3ytowRU5kyjc8m3bOjAw79153UiZrOZt1Yc5PbPN1NRbWJ6/3DmXzcaHw8RSQRBEIQOiG1Oybo31XbsyIbzxHS6LpNTYsv/nd2fswZGUllj4vbPN5PbWa2B2gvpKLGbLzYc5caPN1JWVcOkPqF8M28ckQGejb/JxTtKNHqF+fLNvHHEBnmRcryU2W+t5chx1xV3WoT2eRk9FOJGq+2snWptZ8e36vHRdfW+VRBcERFKBEGwH4NlAc1kR5DysSQVqOgfA0YvtTCp2TppVlo9Jqublp5T1ONdC+G7m2DPz6piYfYnqtukqqRuWGMnYlr/CF64dAgA89ek8NB329rXhuu4paOk9zSYcI/aXvIveG8aZGxTjyuK4MRhtR0xCMbcorZ3/2zNejgZTSgJ7O74OdtDaB8I6QOmKjiwpO5raZsgPbnx95fmWXNZbG23QISStkDrJvEJB/9ouH09PHAIrv9dPZ+7r3Hrt8Ywm+v+3OY0EUZYG+TuD/qOeVlVVWPi/xbs4Olf1fd67fjuvD1npIgkgiAIQscl3GIBs+N7WG8RSibd3/h7anNKVrfdvFwMvV7HC7OH0Dvcl6zCCu7+cgs1zuhi7yxIRoldfJV0lIe/306NyczFw2P54NpR+Hm6Nf1GF84oOZm4YG++mTeOnqE+pOWXMfvttRzILnb2tFqPZrvVbYISqHV6KMtTazuaa0hxJhRlOm+OgtACOuYdvSAIrkFrOkqOWmy3uk2AeEs+hHZTYiuUgDV0MX0zbP9abZ/+CEQmQsxw9bgxm6cOzgXDYnj6okHodfD1xmNc92ESheV25sK0BJNJ2RQAhPSCKQ/DrBfBI0BV7H84U/mNZllEKr8o8AmBqMEQPUyJDlu/rP/Y+S5mvQU29ls2OSWlefDhLJh/DlQ2UvWT/LnqgooYpKoVbRGhxPHkW4SSQEsnibuP+tkL7gl6I1QWWyv6Wkp5gfrZ1chuSijp2EHuReVV3PDRRr7YcBSdDh47ZwD/Om8gBr3O2VMTBEEQBPvRhJJCixXSqJug74zG36MJJWmb7C+46ID4eBh56+rheLsb+OvAcV5avM/ZU+q41HaUiPVWc1m2J5v/W6DcCW6Z3JPnLx2Mm6GZS5XumvWW6wslAFEBXnx5y1gSIvzIKqzgsrfXsjuj0NnTah1aR0m3CeDmBcG91OOVzyrrbg2tyFIQXBwRSgRBsJ/ajBI7Fu21IPf4MdDdYq2VshJSk6yZI5pQEtoHQhPUdvdJcPNymHSfeqy1d6Z2XqEE4PLR8bx/zSi83Q2sPpDLle+uo6CsjcWSwjS1+K93g4B4VS0/6ga4YwOED1SL0Vs+haztav+Igdb3Dp+rxs0f13+j6WrWW2C139r/hzXAO2WVsnmrLGr44s5kgo0fqO1RN6guKFtEKHE8mv/zyTehBjfrxXlTnSANUXpSEHzO3sb378BB7sUV1VzzwQZW7svBy83A21eP4HqLV7kgCIIgdGg06y1Q9xFnPt70ewIt16WVxeqrC9E73I+nLhoEwGvLDvDdpmNOnlEHxFQDhelqWzpKmsXW1Hxu+2xzbSfJ32f2Q3fyvVRjuHUM6y1bwv08+eLmsSTG+HO8pJLL31nHpiMnnD0t+yjLt1p1x49Vo7YmsPMHNeoMaszY2p4zEwS7aZVQ8vTTT6PT6bjnnntqn5syZQo6na7O17x58xo9jtls5rHHHiMqKgovLy+mT5/O/v37WzM1QRDaA4OdQompBo5ZQhLjxlgFkcMr4aurVeXBgPMh2LJgp9PB3B/h5hVwzU+qW0EjdpQaO3FHicbUfuF8fcs4Qnzc2ZFWyHUfbqCkwg7bs+aiXfQE97DarAH4RcK429X25o+sAkJEonWfxEvUhWvuXqvwpVFdaa22cqWOkhiLb3V5gepeAmu7MFifO5nDy1XovbsfDLr01Ne1ToPyAkwmMzvTC/hkbQov/rGXfyzYzn1fJ5/y9fD323jxj718sjaFvw7kkl9qR9dWZ0az3tKySWwJs4iqOXZWQ2q2WwYPNebuazwDqdZ6K9C+8zmJssoabpifxOaj+QR4ufHlzWM5c2Cks6clCIIgCI7BOxiihqiw54vfU5XOTeHhC+6+ars4u23n54KcPzSGWyarDMiHvtvGyn05Tp5RB6M4S93H6gzqfklolB1pBcz9YENtJsnTFw9qmUgC1oySDtJRohHs485nN45leHwgBWVVXPnuOv7Y2QGtqTQ7Lc8Aa9FYbfGkpVhy2NVqzEhux4kJgv3YbT6dlJTE22+/zeDBg0957aabbuI///lP7WNvb+9Gj/Xss8/yyiuv8NFHH9GjRw8effRRZsyYwa5du/D0bCK8SRAE56FZb5laKJRk7VRVWh7+ED5AZZW4+Vgq7gsgrD+c/3rd9/hHqa+T0YSS4/uVTZJ3cIu/jY5EYkwAn9wwhsvfWcvmo/nc8FESH147Gi93g+NPViuU9Dr1tYEXwm8Pq84QbWE5cpD1dU9/tU/yZ7DlY6u9GqhFbrNJCSk+YY6ft70YjMrmbdcPcGCp6lZKsRVKGggIT3pfjUOvUDfYNlTXmDhUqKcvkJ6ZwXn/XWp3SGZskBeJ0QEkxvgzJC6QYfFB+HbVDIlGhZJ+sHthKzpKLD/PEQOU7VZ1mfo5D6nn9wA6ZEdJZbWJmz/ZyPrDefh5GPn4+tEMiQt09rQEQRAEwbFc96uqNPdtwfWmbzjkFSuhpKG//Z2Yh87qR2ZhOT8mp3Prp5v46pZxJMYEOHtaHQMtn8QvCvRtcG/WidiRVsBV762noKyKYfGBvHn1iObbbdlS21HS8YLRA7zc+PTGMdzx+Rb+3JPNvE838fgFiVw1xoUcF5qixCIo+4Rbn7N1mQjrB4Nn1y2utAezGXL3q8/kpn63CjPUPbmHn/3nE7o0dnWUFBcXc9VVV/Huu+8SFBR0yuve3t5ERkbWfvn7+zd4LLPZzMsvv8wjjzzC+eefz+DBg/n4449JT0/nhx9+sGd6giC0F7UdJS2sdk+15JPEjlR/6Axu0G2ces4zAC7/rPl/2LyDrQv5aZtaNo8OyoBofz6+YQy+HkbWHcrjmg83UNQWmSW2+SQn4+4NQy5T25o1gW1HCVjtt3Z8D78+BAtuhY0fQp4l+D2w26k2Vc6m9zQ1HlyqbpBtF9vT6ukoKUiDvb+o7ZE31D5tMplZuDWdM19ayf0LLXksFQXkFlfg7W5gSkIYV4+N5+5pfXh4Zj/+7+y6X/dO78ucsd04Y0AE8cHqBuDYiTJ+25nJ83/sY877Gxj8r98559VVvLp0Pym5He/moFU0ZL0F1o6S3FZ2lPhGQFhftZ29u+H9aztKOsYigtls5u/fb2PV/ly83Q18eN0oEUkEwUVYuXIl5557LtHR0eh0ukbvhebNm4dOp+Pll19ut/kJQofD3adlIgmov/+gugO6IHq9jucuGcKE3iGUVNZw3fwkUvM6VrW+09DycALEdqsxth3LryOSfHz9aPuLvzpQmHt9eLsbeWfOCK4YHYfJDP9YsIN3Vh509rSaj9Z552sjlIQPsG73P89aTFlwVBW2NsXeX+H1sbD0cSg7odYkPj4fXh8FS//d+Htz9sIrw9T+XShnSnAsdn0a3X777cyaNYvp06fzxBNPnPL6Z599xqeffkpkZCTnnnsujz76aINdJYcPHyYzM5Pp06fXPhcQEMCYMWNYu3Ytl19++SnvqaiooKLCWpFbWNjBw48EoaNSK5S00P5JE0ribLoMxt4GJTlwxn9aXr0VN1pZH6VugD5ntOy9HZShcYHMv24U132YxIbDeVz93nrmXzeaIB93x51E6ygJ6V3/6yOuhQ3vqG2Dx6n7xY2B0L5qwXr9W+q5rZ+Dd6jadiXbLY1eFqEkbRPs+VltB8SrC7u8g6p7wLZzYNcPqjsmfjyE96OovIofk9P5ZO0R9mYVATDQUxULhBrL+XzuGEZ0C8LD2LIqs4LSKnZmFLAzrZDtaQVsPnqCYyfK2JFWyI60Ql5YvI8BUf5M7RfG1IRwhscHoe/MYdzNEUqyd6sL5JaKcVpHiXeoEj8ytirBrP859e/fwcLc/7d0P99vTsOg1/HGVcMZ2b1zd+EJQkeipKSEIUOGcP3113PRRRc1uN+CBQtYt24d0dHR7Tg7QegiaN3OXdB6S8PdqOfNq0cw+6217Mks4poPNvDtreMJduR9RmdE6yiRfJIGWXvwODd9vJHiiupakcTP083+A2ph7h0oo+RkjAY9/71wEME+7ry+7CD//WUPpZU13D2tT8utyNobrcDM1iUisJu6jyrNhYEXqPup4J5K8MjYCr2mNny84mxYME8VouXshg3vqqLc6jL1+v4lar2oIda+rvZN26TOFT20ld+g0BVpsVDy5ZdfsnnzZpKS6s8DuPLKK+nWrRvR0dFs27aNhx56iL179/L999/Xu39mpvK0i4iIqPN8RERE7Wsn89RTT/HvfzehJAqC0Pbo7ewoybZU6UcNsT7Xe5q1mr+lxI6ErV90iZwSW0Z2D+bzm8Yy94P1bD1WwNXvr+fbeeMdZ8PVlFASMRBiR8OxDRDer26OCagF6gvfVv832kXs+retC9GuKJQExKgW4Zw9sOI59Vy/WaprJP+Ist+yvbg7tByAvYETeeurZH7fmUlppcqz8PMwctPknlw/fCT8D9xrShnfPRAMLf//CfB2Y3yvUMb3Cq19LquwnBX7cvh5WwZ/HchlV0YhuzIKeX3ZQaIDPLloeCyXjIile6iPvf8arklVubXKMzD+1NdDegM6dYFdklO3wqk5lFjC3H1CrOLHyTZeaZsgc4fqmupA1lsLthzj5SUqA+7x8xOZktDCfxtBENqUmTNnMnPmzEb3SUtL48477+T3339n1qxZTR5TCswEoYV08Y4SDX9PNz66fjQXvbGGQ7kl3PhREp/dOLZt7H47C1oGo3SU1MvS3Vnc+tlmKqtNjO8VwjtzR7beRri2o6Rjd9frdDoemNEPb3cjz/2+l5eX7Ccjv5x/nz8QTzcX/p0rqaejRK+Hq75W3SOaDVfUkPqFkqoyyNqlMmj1evjlb+oeLjRBOY9k71L7xY2F1HXqcXmhsvk+mdI82PaV9fH2b0QoEeyiRZ9Kqamp3H333SxevLjB7JCbb765dnvQoEFERUUxbdo0Dh48SK9ejvH4fPjhh7nvvvtqHxcWFhIXV49PuSAIbYuWUdISocRstrF0amABvqXEjlZj2iYwmdQf2S7CoNgAvr5lHJe/s46d6YU8+N02Xrl8aOurT2qq4ITFMqqxDp8Jd8NXV0GfGfW/HjNcfWkMm6OqRI5tUJ1ArkivaWphvChdPe4xCVNRJvr8I2xZ9ydrjsZRUlFNVn4xj+9fhTdwX1IgO83q5qhnmA9Xjo7nkhGxBHq71+24qih0WI5OhL8ns0fGMXtkHMeLK1ixL4fle3NYtjeb9IJyXlt2gNeXH+DcwdHccXpv+kZ0Ep9W7SbUzRu8TrX/xM1LiXAnDqv26xYLJZbgUu9Q62eUrVBydD18fB5Ul6uOlg4S5r4zvYC/f7cdgFtO68mVY+oRmQRBcGlMJhNz5szhgQceYODAgU2/ASkwE4QWI0JJLRH+nnx0/SguflNlI975xRbeuno4RnuyJLoChdJR0hCfrjvCPxfupMZk5owBEbx6xTDHCABamHsH7iix5fapvfF2N/Cfn3fx1cZUdmcW8sZVw4kNajz32WkU15NRAhAzou7jqCGwc4ESSjTKTsBH50HmNmXX1edM2PUj6Axw8bsQMUgVK5prlIXXy4OVy0Papvq7UjbNV/dnbj5KONv+reo+kbwgoYW06C/cpk2byM7OZvjw4RiNRoxGIytWrOCVV17BaDRSU1NzynvGjFHWOgcOHKj3mJGRkQBkZdW9EMnKyqp97WQ8PDzw9/ev8yUIghPQOghMLbDeKspUf7h0etWW6QjCB6g/iBWFkLvXMcfsQPSJ8OONq4Zj1Ov4aWs676w81PqDnjiiLkrcvFUgYUP0Pwfu3wdT/t6844b0gut/h3t3QmLDtiLOwmQyUxQ7ufaxGR03rXDnhR2qKyNrz1qe+30vbyw/SMrWlXhTRp7ZlwL/BG6Y2INv541j6X2nceOknkokAfV74m4JedcW1R1MiK8HFw2P5ZUrhpH0j+m8duUwTusbhtkMC7emM+PllTzwzVZOlLSw+8sVsbXdakgQ1Oy37Al01zqefEJVpxRAzj7IPaC64T6frS7CAfb/0SE6SgpKq7j1081UVJuYmhDGQzP6OXtKgiDYwTPPPIPRaOSuu+5q9nsefvhhCgoKar9SU1PbcIaC0AnQCiy6sPWWLb3D/XjvmpG4G/Us2Z3FYwt3Yhbv//opsqxp+dW/jtUVMZnMPPXLbh75YQc1JjOXjIjljauGO65Lws3SOV9dpgomOwHXTejBR9eNJsjbjW3HCjj/tb/YkVbg7GnVj1Zg1lQWVORgNWpCSXkBfHKREklAdYr89bLanniPElb0erXWMOB8dc8XN0q9Xp+LSE0VJL2ntmc8qQrYijMhZZWd35jQlWmRUDJt2jS2b99OcnJy7dfIkSO56qqrSE5OxlCPnUhycjIAUVH1L7T16NGDyMhIli5dWvtcYWEh69evZ9y4cS2ZniAI7Y09HSWanVNgNzA6yOfWYLR2LXQx+y2NMT1D+Oe5Kjjtmd/28PXGVi6E1Npu9Wo648EvomWVGnp9/dkSTiK3uIJvNx3j9s82M+Q/fzDy0zLKzcpWboepG4sPV7KxqgcAo9xTuHRELNeO786DfZU9pEefqaz6+zQePWcAI7sH19/NowV9a4vqbYinm4FzBkfz0fWj+eWuSZw9KBKzGb7ZdIzpL65gwZZj1Jg68A1urVDSSCdpawLdS2wySgK7gbsf1FTAayPgndOU2KXl7Oxf7PJh7iaTmfu/SeZoXimxQV68dNnQzp1fIwidlE2bNvG///2P+fPnt6hrVArMBKGFaB0lJSKUaIzqHmzpWIfP1x/l9WX1F8F2eYot1vG+IpSAKtS58eONvG0p4rvvjL48d8lg3BzZkeRu02mh5Vh0Aib3DeOnOycyIMqf4yWVXPHuOjYdaUYQenvTUEfJyWiW63kHYcm/4cNZkL4ZvILhul9h0t9UYWH0cJj8YP3H0PJtUzec+trun1RHl08YDLlCZaMAbPumxd+SILToE8rPz4/ExMQ6Xz4+PoSEhJCYmMjBgwd5/PHH2bRpEykpKSxcuJC5c+cyefJkBg8eXHucfv36sWDBAkB58d1zzz088cQTLFy4kO3btzN37lyio6O54IILHPrNCoLgYGqFkqrmvyfvoBpbGtjeFLEj1VjfH84uwtVju3H5qDhMZnjw223c//VWSitb0O1jS1P5JB0Yk8nMtmP5vLxkH+e/tppRTy7hb99sZdH2DIrKq6nAnU0o0Sk3dAxPXpjIE7ddhRkdITU5PDczin+dN5Ax7ADAp9/pTS9aaYvo5e1bDTQg2p83rhrBd7eOp2+EL8dLKrn3q61MfX45H6w+TGF5C353XYUCiwjYmNgW2pqOEpuMEr0BLvsEep+h2sCryyG0L9y0FPRG9Xmm/a541mMD5mTMZjP/+XkXS3Zn427U89bVI6ydToIgdChWrVpFdnY28fHxtZ39R44c4f7776d79+7Onp4gdB46YkeJ2QyfXwbzz6lr+epAzkqM4l/nKsu/5//YxzetLcrqbJjN1o6Sltq+dkJ2pBUw69VV/LknGw+jnpcuG8JdbRFObvSybncS+y2N2CBvvrxlLKO6B1FUXs3V721g9f5cZ0+rLrUdJU38zPuEWovcVr8IWdtV18fcH6HbeJj2KDx0BG5YDG71xzwQq3WUbKjbPWQ2w5pX1PbI69X7B81Wj3cvVPmWgtACWpmcVBd3d3eWLFnCyy+/TElJCXFxcVx88cU88sgjdfbbu3cvBQXWxaIHH3yQkpISbr75ZvLz85k4cSK//fZbgzkogiC4CHrLR0hLhJLjFqEk2NFCiSXv4thGxx63A6HT6XjywkHEBHrx0pJ9fLf5GFuP5fP6lcNJiGxhPkVeG/0/OZGC0ireWH6A7zankVtcUee1xBh/Tk8IZ0q/cAZG++OREwtrXmPqGf8Gf0tHZFiCWnhP2ww9JllFuR6nNX1yJwklGiO6BfHznZN4d9Uh3l11iKN5pfzn5108/dseTk8I59wh0UzsHUqAt5tT5tciaoWSxjpKNMusZljxFRxT+/WcqrqnbDtKQHng9pqqQt5TVkH3SUpEiRsLR1Zbbbhc0HrrpSX7mb8mBYDnLhlMYoxrdr0IgtA0c+bMYfr06XWemzFjBnPmzOG6665z0qwEoRNiK5R0lOzDvEOw7ze1nb3TWr3tYK4Z353MwnLeXH6Qv3+/nTA/D6YkiCgAQEWRtaOhi1tvLduTza2fbaK8ykR8sDdvXDW87a5B9XolllSXWQLdm7CA6mD4e7rx8fVjuPmTjazan8v185N47cphnDnQBX7GzGabjpJm/Luf+YQKW/eLgsB41fUR1N36uqGJ5enIQer/urwAju+3OgjsWQTpW5QN26ib1HPx48A/FgqPwf7flX2XIDSTVgsly5cvr92Oi4tjxYoVTb7nZE9LnU7Hf/7zH/7zn/+0djqCILQnWkeJyQ6hxNGdClqFQc4e9cfTRW1w2hqDXsed0/owqkcwd3+5hQPZxZz/+mr+fd5AZo+MQ7fsv8ob9JwXG6/I1xaYQ/u2z8TbkMpqE5+uO8Irf+4nv1T9rPq4G5jUJ4yp/cKYkhBOhP9JwnzUEBUiZ0v0cPXztf0blbFjqoKAeAju2fQknCyUALgb9dw+tTfXT+jB91uO8dGaFPZlFfPbzkx+25mJTgcDo/2Z3j+CK8fEE+7nosUKmvVWYCNCSWgfNRZnqaDAk0PfS/OU0LX5Y9j3K5hNcP4bMOA8ZbMFqvLJFp8Qaxs3QO9pSijRcLEw9/dXH+aVpfsB+M/5Azl/qASLCoKrU1xcXCfX8fDhwyQnJxMcHEx8fDwhISF19ndzcyMyMpKEhIT2nqogdF60BT9TlcVuM9ip02kWR9dZt9OT20woAXhwRgKZBeUs2JLGbZ9t5r25IxnfO7TpN3Z2ii3dJO5+4O7j3Lk4kR+2pPG3b7ZSbTJzWt8wXrliGAFebVyI5e6thJJO1lGi4eVu4L1rRnL3F8n8tjOTWz/bzAuXDuGCYU6+tq8otN43NaeLauAFde+lWorBDaKHwdE16j4uLAFMNbDsSfX62HnWrBS9HhLOUrklxzaKUCK0iA5QHiEIgstisFz0tCSjpNZ6qxmLyy3BN8xSkWCGtE2OPXYHZGzPEH65axKT+4ZRXmXioe+2c9+HSzCvel5VVbwztWGbMrMZspStFBED2m/SDsZsNvPbjkxmvLyS//y8i/zSKvpG+PLu3JFseexM3pozgstGxZ8qkjSEdmG341v47ka13XNy0xkuYF1Ed6JQouHlbuCqMd34/Z7J/HLXJG45rSc9w3wwm2FHWiEvL9nPhKf/5N6vkknLd0Gv3/xmWG95+qsqIoCsXdbnt38L/xsKz/aALy6DvYuUSAJweKW1fdzNu+mb3D5nnHRO1xFnv96YyuM/q+/7/jP6Mndcd+dOSBCEZrFx40aGDRvGsGHDALjvvvsYNmwYjz32mJNnJghdCKOHtcBCW/x2dVJthJKM5DY9lU6n45mLBzOpTyillTVc+2ESP29Lb9NzdgiKLPkkfhHOnYcT+XhtCvd8lUy1ycyFw2J475qRbS+SgDXQvapzCiUAHkYDr105jIuGx1BjMnPv18l8uu6IcydVbLlvcvcDN6/G93UUcTb2WwA7vlNB8J4BMP7Ouvu2xGFAEGxwqPWWIAhdjFqhpJkdJaYayDusttvC0il2FJxIgdQk6HW644/fwQjx9WD+taN4c8VBXlq8D/eDv6NzsywKl2TD/Flw3qsw5PK6byxMUwv6emOH7SjZdiyfJxbtZsNhFXoX6uvOfWckMHtkLEZ7AwT7zoBLPoAfboMKi+DRY0rz3usCHSUno9PpGBDtz4Bofx6e2Z+swnJW78/l8w1H2XTkBAu2pPHnnmxeuHQI0we4yE2f2WwT5t6IUAKqmrLwmOqg6j5BPbf8KTihfQb1VNkjwT3gt7+rQMESSz6JdzMqIyMSVVhncaYKH2yqXbyd+G1HBn//bhsAN07swR2nd76cIUHorEyZMuWUzvvGSElJabvJCEJXxjdCdaQWZ0F4f2fPpmmOrrdup2+pfx+TSRX3OCAjwt2o5925I7n3q2R+3ZHJnV9s4XhxJdeM797qY3dYNFHN10WumduZt1Yc5OlfVTbgteO789g5A9DrHZxH0hBaoHtlSfucz0kYDXqev2QIvh5GPl57hEd+2EFxRTXzTnOSVXaJxXbLtx3tzmwD3XMPwLL/qsfj7zrVQUATSnJFKBFahnSUCIJgP/oWCiUFx1R7pt5N+VI6mtqAryTHH7uDotfruH1qb369exKX+6obp9eqz2ed+zjVCbTgFlj8z7qBaFoFfmhfVVXXgThyvIR7v0rmvNf+YsPhPDyMeu6Y2pvlD0zlyjHx9oskGokXw3W/gl80ePg3X5BzQaHkZCL8Pbl4RCzf3TqehXdMYEhsAAVlVdz48UaeXLSLqhpT0wdpC8ry1U3/po/g6zmWFm8d+DfRbh49VI3agkFpnjV4/Z4dcNcWOPtZSLxEPZe73yqi+NS1t6kXnQ56W/ICXMR2a/X+XO76IhmTGWaPjOUfs/o7PjRTEARBEDo7HSnQvTSv7kJg1k6oPqnbP3sPPBUDvz3ssNN6uhl47crhXD02HrMZ/rlwJ8//vrdFYm+noosKJWazmZcW76sVSe46vTf/PLcdRRJQneDQqTtKNPR6Hf8+byC3T1XiyNO/7uHZ3/a0/e+d2awKXrd9DTn71HO1+STtmFOk5dLm7IHXRqh7N58wGDPv1H01oeTEkU5ryya0Da5R/igIQsdEyyhprvVWbUB4D9AbHD8fW6Gko4QvthN9/GswV20F4HfjVF4oDOXvHpHcolsAf70Muftg9seqS0iz3QrvOLZb+7KKeGPZARZuTcdkuU68aFgMf5uRQHSgg1uBY4arRfbqslMrVxqiVijJd+xc2ojBsYF8M288T/+6hw/+Osy7qw6z8cgJXr1iGLFB3u0ziZJceP9M6+eGLT1Ps3a0NUTUUDVqFhRpm9UY3LNuvolvmAqGL0iFA0vVc83pKAFlv5X8qUuEdm46coKbP9lIZY2JmYmRPHXRYBFJBEEQBMEetMVuVxVKaqrUwqXR3WqlG9JbXTuV50PO7ro5Jdu+UovIG9+HKQ81//q1CQx6HY+fn0i4nycvLt7Ha8sOkFNUwZMXJra+OKmjUWu95fxrwvbCbDbz1K97eGflIQAePCuB26Y4oZPZvfNbb9mi0+l4YEY/fD3ceOa3Pbyx/CDHiyvb7vdu76/wy4NQcFQ9Du6p7oU1y+L27CjxDVOfbRlb1VpU7GiY9ih4+J66r08oeAVDWZ4Kf2/D7Cahc9HF/noJguBQtIVKU3Xz9teC3NvCdguUFY7RU90g1Le42pXZ/wc6UxWE9ePNuy9jVI9Qnqq4lLsrb6MSN9j7C+xeqPbN2qnGiIHOm28zOXK8hHu+3MKMl1fyQ7ISSU7rG8ZPd0zkxcuGOl4k0XDzbNlNZgfoKDkZd6Oex84dwNtzRuDvaWTL0ReX32MAAHK2SURBVHxmvbKapbvbya/74J/W32PfCOg2AaY8DDcsgau/b/r9WkdJ7n6oKIK0jepxzMh69lV5ABxYosaTg9wbov95cNYzqjPFiezOKOS6DzdQWlnDpD6hvHz5UAztWcknCIIgCJ0JrULa1TJKTDWw7i14pju8fwZUV1jzSeLHWhcCT7bfOmgpBKmpVJ7+DkSn03HXtD7898JB6HXw1cZU7vxiC5XVTupEdha1HSXtWF3vREwmM4/+uKNWJPnnuQOcI5KAtaOki3UN3DqlF09dZP29m/fpZsqrahx7kuoK+PF2JZLoLXX2eYdUPokzOkpA3Qde/wf8/Shct0h99tWHTqcC30FySoQWIUKJIAj209Iwd00oCWkjocTobl3wbCiovKuiiSD9zyU2yJsvbhrLv84dwJ9uU/iw+kwAtiz9moLSKhWIBi4tlGQVlvOPBduZ9sIKfkhOx2yGswZG8vOdE/no+tEMinWdYG2gQwolGjMGRrLorkm1Vlw3fLSRFxfvw2Rq4xZvTbAbeT38bR9c9wtM+bsK8WtOR5pvuMWeywyZ2+GYRSjROs9siRmuxtJcNXo3w3oLVNfa2HkQM6J5+7cBafllXPPBBgrLqxkeH8jbc0bgYWyDjj1BEARB6Cq4ovVW/lHVafvbQ1BZrDpm17xqzSeJG2NjO5psfV9xjqq+1kj+ok2md+WYeN64agTuBj2/7sjk5k82On7R1pWpFUo6f0eJ2WzmHz9s59N1R9Hp4JmLB3HdhB7Om5B717HeOpkrRsfz5tUjcDfqWbI7iznvr1f3845i149QelzZTj+UYi14zdxmk1HSzkKJTyjEj2legLwIJYIdiFAiCIL91FpvNfOPcV4bCyUA0ZYFz8xtbXeOjkZlKey3VMr3PxdQrfLXTujB0vtPo7rHNABi89Zy1vN/YNJ8R11IKDGbzaTmlfLL9gz++eMOJj+7jM/WH6XaZGZKQhg/3zmRt+aMIDHGxQQSDa9ANXZAoQQgLtibb+aN55px3QB4Zel+rv8oifzSZoqk9uCIziZNOE3bbO0oia1H1NA+NzSa21HiZIrKq7j+wySyiypIiPDjw2tH4+0urqqCIAiC0CpqrbdcqKPkj0fVtYyHPwy9Sj238nlI26S248Zar3s021FQHboAQd1BZ1DHyN3fJlM8KzGS964ZiaebnuV7c5j7wQbHLtq6MkWWnxW/zp9R8tzve/liQyp6Hbw0eyiXjWqD7NGW4Gax3urkYe4NMWNgJJ9cPxo/TyNJKSeY/fZaMgvKHXPwpPfVOOJa8PCDqMHqceY2JcKCyghxVbSckpw9zp2H0KEQoUQQBPvR2i+bK5S0tfUWQOQgNWZub91xVr8Mz/ZS4Yf1cSJFBZq5OmYzJL2n8jQC4yFycJ2Xw/09uf2aOdQYvQnTFTChYgV6czUlel9y9e2/WFxdY2JfVhG/7cjkw78O88TPu7jqvXUM/c9iJj27jNs+28xHa49QUW1iZLcgvr5lHPOvG+26AolGB+4o0XA36vn3+Ym8OHsIHkZ1A3zua6vZlV7YNifUOpvCWyGUaDklOxdA2QkweEDEoFP30yowNVz5gt9CVY2J2z7bzN6sIsL8PPjgulEEeDeR2yIIgiAIQtO4YkeJVgR26Ydw/uvQbaK6vq+pUD78oX2s1z22ge6a7dbAC1W2GkDy5202zcl9w/jkhjH4eRjZcDiPi99aQ2peF6j0L7ZklHTyjpL3Vh3ijeXqnv6/Fw7igmExTp4R1s6CLthRojGmZwhf3zKOcD8P9mYVce5rq1l36HjrDpq1U1n76QwwfK56TltLyHBiR0lLCO2rxtZ0lOQfhU3zu5y1W1dGyg4FQbCfloS511QpcQFU2GBbYSuUmM3Km9Iekj9TNjzbvoLp/6z7WnUFvDtNfd93bnLdi4OS4/DzPVbbrSFX1v/vYXTH0GsK7P2FhwMWQynsqI7ltpdXMe+0XlwxJh5fD/v/XFRWmziaV8LBnBLKKmvQ63WYzWZKK2soKq8ip6iC9PxyUk+UsjeziIoGPI3dDDoSIv0YFBPAmQMjmdI3rOOEVWverUUZsO0bGHypc+fTCi4aHktCpB/zPt1Eal4ZF735F4+fn8glI2Id9/9RdgIK09R2eH/7j6MJIFo3SdRgZdF3Mp4B6nPp+AH1uLlh7k7CbDbzz4U7WbU/Fy83Ax9cM4qYtsrjEQRBEISuhiM6SoqywNO/efYwTVFdYb2PCh+orudnPQ9vTgBzjbLd0ulU14hnoMprzN6lFjUPWISS3tOVkLLvN9j6JZz+SPOsTO1gVPdgvp43jus+TOJAdjEXvrGGD64dyeDYwDY5n9OprlDXrmD92emEfL/5GE8s2g2o4PbLRzu5k0TDvWtmlJxM/yh/vrt1PNfPT2J/djFXvruO+89M4NbTeqG3J7tQ6ybpfw74R6lt244SrVjWlX/mtY6SvENKPK7vPrAxygvgw1kqo2Xvb3D5Z232uSm4DiKUCIJgP7Vh7s3oKMk/qi7kjV7gF9V2cwrtqwScikLIP6JuGFpKZYm1JT1l1amvFxyzZhls/BCmPGT3dNsMUw18dC5k71SdP1P+DhPubXj/3tNh7y+ElKpAvizPXhwvrOTJX3bz6p/7ueW0XtwyuSdGQ+ONiJXVJjYdOcFfB3LZk1nEoZxijuSVUtOCPAsfdwO9I/yICfQk0t+LvhG+JMYE0DfCD3djB22E9I+CUTdB0ruw4BYwesCA85w9K7sZGB3AT3dM5O4vk1mxL4cHvt3Gin05PHnBIMd0NWSrmzD8Y622ZfagVVZq1BfkrhE93CqUuLj11rurDvH5euUL/b/Lh7peJo8gCIIgdGS0IqjS41BTDYYmlk3yj6rFQqOHelyUCf8boq4trv+19fPJOwxmE7j7gp+lYyG8P0y8F1Y9rxYyQYklUUPg8AproHtprnpf7GjArISUonR1j9NzSuvn1gD9o/z54fYJXDc/id0ZhVz29jpeu3IY0/q78KKqvWidR3o38A527lzaiD/3ZPHAt6qr6YaJPbj1tDZ0iGgpmvVWVde03rIlLtibH++YwCMLdvD9ljSe+30vSSl5vDR7KEE+LRAJKopUwSjAyBusz2sdJccPWteCXLkT3z8a3P2gskjZwLe0AG/R35RIArDvV/jt7zDzWfuLcbsySe+pv2UDL6rfCtuFEKFEEAT7qQ1zb4ZQsvN7NYb2UQHIbYXRXVUOZG5TXSX2CCVZOwHLwn7aZnWh4OFnfT3/qHU76T2YeI/1xshVKM5SIonOADcuPdVa6GR6T6/z8Oxp0yjTD+LtFYc4lFvCc7/vZdmebF6+fCixQd519jWZzPx1MJdvNh5j6e4sSipPDW70cTfQM8yXAC83TGYzZjP4eBjx8zQS5O1OTJAXMYGeJET60y3Y276qF1dn5rNKhNv6OXx7PVy7SAXRdVACvd354NpRvLXiIC8t3sfP2zLYfOQEL142lLE9mxmG3hC1+SQDWncc3zAlthQeU49jGxFKYobD9q/VdnPD3J3Ar9sz+O8vyhLwkVkDOHNg57Z4EARBEIR2xzsEdHolTpTmWsWJ+sjYCm9PhsRL4BJLBfaxJKguV/khrelw1zhuKeAK7VP3WKc/orIDAmKtz0UPU0LJimetOW89TrNWUg84HzZ/BLt/alOhBCAywJOvbxnL7Z9vYeW+HG76eCP/Pj+ROWO7tel5253aIPeITrmAujElj9s+20yNycyFw2L4x9n9XaurXzpK6uDtbuSF2UMY0zOYx37cyfK9Ocx6ZRWvXjmMEd2aKeTt/gkqiyGkD/SYbH3eN1zZyxVnWl1FXNVdA9TvY1hf9Vmcs6dlQsm2r9W9oc5gEaVfgA3vQHBPGHtr2825s7JrofrbFJEoQokgCJ2Y5oa5Hz8IK55T2+PuaNs5gap00IQSS3h5i8jYat0218DRdVZPX6grlJRkw47vYegV9s+3LSjKUKNfZNMiCUBQN9WNk6uC3I3Rg7gsLp5LRsSxYEsa/1q4k41HTjDzf8qO6/JRcRgNer7ccJSP1x4hLb+s9lChvu5M6hPGsPhAeoX50ivMlwh/D9e6oHYGej2c/5qyQ9j7C2z5pEMLJQAGvY7bp/ZmQu9Q7vlyCynHS7ni3XXcelov7j2jL25NdCA1SG0+SSuFElA//80RSmwD3V20o2TL0RPc81UyAHPHdeP6Cd2dOh9BEARB6JToDapKujhLfTUmlGjFHYdXWp/T/PBrLJZMre0y0DrdQ/rUfV6ng8C4us+NvE5Vghelqy+A3qdbX+93jhJK9vwCM59r2wI2wM/TjfevGckjC3bw1cZUHv1hB/klldxxeu/Oc29QpOWTuPCCsZ38mJzGQ99to7zKxNSEMJ69ZLDrFbS5WYSSLpxRcjI6nY7LRsUzKCaQ2z/fzOHcEi59ay3XTejB/Wf2xdu9iaXgPYvUOOiSU8W/qMGw3/Iz7+YD7j6O/wYcSVg/i1DSgpySoixYdL/aPu1B5c7hGQCLH4U/n4TRt7T5Z2enQ1tDC3QRy75GkP9ZQRDsR691lDSSUWI2w8/3qhuFnlNh8Oy2n1drA91rhRLLRYHtjQ9YP+S1i7J1b6jv05Uosqlsai62XSWWaguDXsclI2L55a5JDI0LpKi8mud+38u4p/9k3FNLeerXPaTll+HnaWTO2G4suG08G/5vOi9dNpS547ozoXcokQGenedGqLXoDTBsjto+ttG5c3EgQ+MCWXTXJGaPjMVshjeWH+Ts/63itx0ZmO353ciyCCURia2fnCYUeodCYCMVjFFD1IVb5GBlUeFipOaVctPHG6moVjeqj50zQH6vBEEQBKGtaG6ge2meGkuyocRizWu7IKcVL7WGXJuOkqYI6g53bYEZ/1Vij1cQJMyyvt5jsrrOKUqHjC2tn1szcDPoefriQdw9Tc3/hcX7eHLRbvuuEV0RraOkMUGtg1FdY+LJRbu4+8tkyqtMTEkI442rRthfBNWWaAv1IpScwoBofxbeMYGLhsVgMsP7qw9z5ksr+ToplfKqU10gANWZo2Ub9Zt16uua/Rao7n1XJyxBjS0RSnYvVFbukYNg0t/Uc+NuB4OHsvHKT3H4NNuF9GR4Y5zKW2lPTDXKvh5Uga6L44KfcoIgdBhqM0qqG95n21eqxc7oCee82D7tyM0RSrJ3w/MJ1pAyWzKV/2rthcHJOSUFqWocdaPKXMncBkfWtG7Ojqa2o6QFeTB9z1JjaN+6VmNAfIg338wbx4uzhzA4NoDKahOllTX0i/Tj2YsHk/SP6Tx+QSLD4oNcr8rI1dC6GnL2QHmhc+fiQHw8jDx7yRDevGo4gd5u7M8uZt6nmznn1dX8mJxGVY2peQcym60ZJa213gL1c613g4EXNP754+YJd26Gm/50OduEgrIqrp+fRG5xJf2j/Hn1yuFN5gUJgiAIgtAKmhvoXpZn3dY6YnP2WJ8rdIBQollvhfRu3v5uXmpR777dcO9OaxAzqOsdrThKqxpvB3Q6Hfee0ZfHzlHXdu+tPsxjP+7sHGJJsR0Fai5MZbWJu79M5t1VhwG4bUov3r9mFF7uLhpi7SbWW43h5+nGi5cNZf51o4gJ9KL0RBZ7f3iaQ0+O4OD/ZlFSVl73DYeWQXWZKiCrr2gtykYo8ekAXVRaoHtLhJKDf6px4IXWjCq9wSq6aPeqHY2Vz6m/U1s/b9/zFmWoXGO9sW3zih2E3GULgmA/hiY6SsxmWPak2j7tQeXn2B5EWv6gF6Raq7xOZtePylvzr//V7QaprrRWs2s2YRlbobzAuo/WURI1BIZcprbb+49NU2gt4C2pbOp5Glz0Hlxcj3iEqga7aHgsP94+gZ/vnMiC28bz692TmD0qDk83F71wdkV8wyEgHjBbgzY7ETMHRbHigancdXpvfNwN7Ewv5O4vk5n4zJ+8vuwAeSWNdKCBqjapKFAXUidbTNhD5CB48CCc9UzT+xrcrJ9rLkJVjYnbPtvE/uxiIvw9+ODakfh6iHOqIAiCILQp2qL3mtdg+TOQvaf+/WzvNbJ3g8lk7QABq/2VvZjNNh0lfVv2XoNb/bY4/Szh7+0olGhcP7EHz14yGJ0OPll3hOd+b8Hipatiz32Xi1JeVcO8TzexaHsGbgYdr14xjAfP6ofBlQvhtIwSCXNvlCkJ4Sw9I4skrzt41O1TBnCYXidWc/sLH7Fwa7pVtNQ+F/qdU3/xWJ2Oko4glFjEjdx9kLOv6f2rK62OIifluNbmPmnrRR2JklzYZ+kkKWzl36WWoq2fBcQqwcnFEaFEEAT7qc0oaWDhM3WD+lB094Wxt7XfvDwDrBY7WTvq30er9Mo/UrfqK2ePUrs9AyB+rBJ3zKa6HSP5lo6SwG7QZ4baTtvs2O+htdjTUQIw+NK6VSL1oNPpSIwJYFh8kFj/2IsWYJbWeey3bAnwcuO+MxNY9dDp3Du9L2F+HmQVVijbtqeW8tC320jNa6DqS6vGDO1rDR5tLZ4B1mqgDoTZbOaRBTv468BxvN0NvH/NKKICvJw9LUEQBEHo/HQbr8ac3bD8v/DOFKgoOnU/246SrJ1QcFRVY2toi+j2Unpc5duhg5BerTuWRp8zVEFKzh7IPeCYY7aA2SPjePIC5QDwxvKDvLn8YLvPwaFo9mwdYdG4EUoqqrnuwyT+3JONh1HPu3NHcu6QaGdPq2mko6R55O7H89d7MZirMUcNochPfZ70KNvOXV9s4fJ31rE7LQ/2/qr2r892C5S9n4e/2vbpANZbgd2g+yS1xvPV1fV/jtuSul4F2fuEQcSguq9pYfDZHVAo2f6t1QnGWUJJB8gnARFKBEFoDXrLwmNNA9Zb279RY79zVAt4e9KU/ZZtNYF2MQBW263IwaqCovsk9ThltRqrK62VYYHxED3Mcrw9UOlCVSydqLKpUxJjsd/qRDkl9RHs487d0/vw10On89JlyratotrEVxtTmfbiCl5avO9Uf1wtFNURQe4dnDdXHOSrjanodfDqFcNIjAlw9pQEQRAEoWsw7GplyXnOS+ARoMSP+qqRT+4oOdnepbULUrmWcwbEOe5+yivQeo+zt/27SgCuHBPPwzOVJc4zv+1h0TYHWJQ5i2ItzL3j3ncVlFUx5/31rD10HB93Ax9dP5opCR1E+JEw96aproTvblSfYz1OQ3fTcvxGXwXAlVEZeLrpWX84j3+//gGU5WHyCoa4sfUfS6ezrrV0BHFQp4NLPlAFpLl74cc7Gs+XPbBEjb2mnRrYHm7pKOmIQomtA0pRRsNreG3BiSNqbCwv1IUQoUQQBPtprKOkphp2/aC2B13SblOqRWsJrU8oqam2ev2CtQURrEHuUUPU2GOyGrX2y8I01WFi8FBVBv5R6qLYbLI/PL4tqBVKXN8DsksSO0qNxzY2fqHWSXA36rlwmLJt++7WcYzvFUJltYn/Ld3P1OeX8+byg5zQLLm0C09H5JN0YD5dd4Rnf1OLLf88dyDT+ncO32tBEARB6DCE9IKR11sXBY/X031RdsK6nb3b6l2vsyy1tDbMvdZ2q5n5JM1FqxZ3gv2Wxi2n9eKmST0AePDbrRzIbqLS21Up0sLcO+a1WnZhOVe8s47NR/MJ8HLjs5vGMrZniLOn1Xw0eznpKGmY5f+FjGTwCoIL31ICQNwYAPpU7GTJvZOZmRjJGXpVxPdz+RC+2pyOydTAferAC1UGbbcJ7fQNtBLfcLj0I1Xou+sH2DS/4X0PWoLse0879TWto+T4AaiucPQs246snWqdS+8GOoNau2oqf6s17Psdlj6uQtzBpqNEhBJBEDo7mlBiqjr1tcMroCQHvIKh55R2nRbQeEfJiRQl7ugtWQSpG5RnI0CGTUcJWP/4Z+1QwdtakHtgnLXCIGa4Gl0pb6LWeqvjVjZ1aqIGqwu1kmzrz1QXQKfTMaJbMJ/dOIbXrxxOVIAnGQXlPPPbHsZaLLnKj1l+B7WKnS7Ix2tTeOQHZRt48+SeXDO+u3MnJAiCIAhdGU2ksC200rDtKKkssi6yaV3nrRVKaoPcHZDbZkvPqWrM2KpyVZzEQ2f1Y2zPYEoqa7jlk00UV7RjlbMjMJnU9Tx0uDB3s9nM95uPccZLK9mVUUiorztf3jyWoXGBzp5ay3CTjJJGyU+F1S+r7fNeBX+LnVr0cHU/WpRBrC6XN68cylX+yQD8VDGMh77bzoyXV/L1xlQqqk9yABh9EzycpjJOOwrxY2DaY2p79UvWRXxbirIs60c66HX6qa/7R6sOQ1N13SwqVyfZ0k3Sd4b1/7+t7LfMZlh4J6x6Hg5Y/h7max0lYr0lCEJnR/P8r6lHKNnxnRoHXuCccGQtZyN716kt8LmWxxEDLIKKGfb/oS50NWFFe79/lPpAN5sgbZNNEFWc9XjajZCrCCXVlVBqEX6ko8Q1cfOCiES13cntt+pDp9Mxa3AUy/42hecuGczAaH8qqk38sPEgxjx10fnVsUDS8suaOFLnosZk5vVlB3jsR2U/dvPknrW2FIIgCIIgOIkQTShppKNE8+zX7Hq1QrHC1naUWM4Z6mChJKi7WiStLm994HwrMBr0vHrFcCL8PTiYU8Lfvt7acBW7K1KWZ/X99+kANkQWNqbkMfeDDdz39VYKyqoYGO3P17eMo3+Uv7On1nK0MHdTdf3rEl2dvb8CZogfB/3PtT7v7m110UhdD4eW4VmagdkzkHFnzMbPw8j+7GIe/HYbk55ZxhvLD1BQZvPv2wHzHxl1E3gGqoV7W1cRjYN/qjFqCPiEnvq6Tmd1PdC6B10dk8lqiT/0SvCPUduFaW1zvvwj1m6VtE2W5yxraEHSUSIIQmen1nrrpAuSqnLY/ZPaTnSC7RZAQCwknK0Ejt8ermtvpIW3hyZA35lqe++vsPcXVYli9KxbtWVpS1Xh9FpHiY0a7kihxGyGVS/C7/+AKjsXibU/THo38A5u/ZyEtiG2a+SUNIanm4FLR8bx850T+XbeOG7sU4pRZyLH7M9Di3OZ8PSfnPvqal77cz/7s4owd2KbstS8Uq54dx3P/a6E3Hmn9eLhmf3Q6XROnpkgCIIgdHG0+4KTg8+ryqzB7fHj1Gi2dGdoHRslOa1bvNU6ShwtlBiMSiyB+gWgdiTMz4M3rhqBu0HPbzszef6PvU2/yVXQ7I69Q8Do7ty5NIM1B3K5+M01XPLWWlbtz8XdoOeBGQn8cPsEeob5Ont69uHmY912pcxQV2GfJY81Yeapr2k5JEfXweaPAdANuZzrp/bnr4dP5+GZ/Yj09yS7qIJnf9vL+KeW8tSvuyko7aCClLs3jLhWba97s+5rJhPs+lFt12e7pWGx3yo9to3SymrXvz89fkCtDxm9oPcZbd9Rkppk3U7fomzvC46pxx2ko6QDSoCCILgMmnXVyRklBxZDRaFSq7WbBmdw5hOwf7Fqgd//h2o1BGsQY1gC9JoKK5+F3QvVF6hwQ9sKibgxSoVPXW9tqbb9kI8aqsbc/cqey7MVlTirXoA/H1fbWTvg8s+tvqvNxTbIXRZZXZeYkZD0HhzbACXHoTzfKuj5hoFn1wnu1ul0jOwezMjB5ZAK5aGDGO0WQtKRPLanFbA9rYDn/9hHz1AfzhwYyYXDYkiI9HP2tB2C2Wzm642pPP7zboorqvFxN/DoOQO4bFSciCSCIAiC4ApoHSV5B9Vimma/q9lu6Y0QNwr2/64e6wwQN1rdK5mq1CJVQGzLz1tdCXmHLXNwsFAC6vs6fkB9OcMq2YYR3YJ46qJB3P/NVt5YfpAeoT5cOjKu6Tc6G60q2y/aufNogsyCcp5YtIuft6kOJ3eDnotHxHDz5F70CG3hvaarYXRXv4OmahXo7hXo7Bm5DhVF1i63vvUIJfFjYN3rav1G634bNgcAf083bjmtF9dN6MFPW9N5d9Uh9mQW8faKQ3y5IZXbp/bigmExhPt5ttM34yBG3wRrXoWUVZC5AyIT1Wf5gnnWz3Atw8nCsROlLN+bw4p9OQw4ZuReYM3aVdy48neMeh0hvu7EBXkTHeiFyWymrLKG0soayqpqKK+qwcOox8/TjQBvN6L8PYkK9CI6QI0xgV6E+Xm03febvlmNUUPU70qtUNJGHSXHNtQ9d2EamGvU30PfjmELL0KJIAj2o1lqnVwltf1bNQ680Hoj4QxCesG42+Cv/6mukp5T1R8HraMkLAGihil7qqIMFdA+fC6c9lDd49gGb0dYchNshRLfMGXFVZAKmdug+0T75rtzgVUkMbjDoeXw2aVw5Vfg0YJF4WIboURwXWp/rpLguZ51X3P3hTs3db3/w4ytAMQNGMvX08aRW1zBkl1Z/L4zk78OHOdQbglvrTjIWysOcs7gKO6Z3pfe4R20+g3ILirn4e+2s3SP8rYe1T2IFy4dSnyIt5NnJgiCIAhCLUHd1EJsVam6ZwiwWJeUWYQSr6C62WohvcDooa7jClLVAqQ9QsmJFLXA5OZjXdxyJLWWYgcdf2w7uHhELIdzS3ht2QH+b8F24oK9XT9U3Da/0gUxm818vuEo/120m5LKGvQ6uHpsN+44vXfHW+BuDDcfqCiQQPeTOfinKmoN7ll/V5rWUaJZI8WMUMKBDe5GPRePiOWi4TH8uSebZ37bw76sYv77yx7++8se+kX6MbpHMP0i/ekX5UdidADuRhc2LwqIVRZku35Qay/hA1RRbEGqWg+a9YL6dwD2Zhbx3192s2JfTu3bC3QR3OsB/fTqd7/aZCarsIKswgo4csKuKUUHeDKsWxADovyJC/YmLsiL2CBvQn3dW184p7meaC4obW29lbreul2So7qVoG7Gr4sjQokgCPajCSW2Ye4VRVa/x0FOst2yZdLfIPkLVQG28X0YfYs1eCusn/qwnv0JHF0Lg2fXvzAdkahC4ioK1KI2nNo2GD1U/XFN32KfUJKxVVUxAIy5FRIvgk8vhiN/wW9/h/Nfb/6xikQo6RCE9FIZOVoujrsv6A2qZbyyGA6vgsGXOneO7Y1FKNH8ckN9Pbh8dDyXj46nqLyK5Xtz+GlrOn/syuLnbRn8sj2DmYlR3Dy5J0M6WPDkom0ZPPLDdk6UVuFu0PO3GX25YWJPDHrpIhEEQRAEl8Lgpmyqjh9QVliaUKJ1lHgFW33rQRVjgSrGKki1PwMkx+KBH9qnbbrEQ3qp0UWEEoD7zujL4dwSFm3PYN6nm1hw2wTX7njQbJkDXE8oSc0r5aHvtrHm4HEAhsUH8vj5iSTGdMKudTcvda+evgVCezt7Nq7DXsu6TN+Z9X+G+EWoz7YTKerx8LkNHkqn0zGtfwRTEsL5btMxPl6Xwo60QvZkFrEns6h2Px93A+N7hzKhVwgDYwLoF+mHn6cTMmsbY+xtSijZ95t17SqoO8z+GKKGkF1UzkuL9/FVUiomM+h1quttSkI4oyP6wdePE6vLZdc/xlFg8iK7sILUE6Vk5JdjNOjwcjPg5W7A292Ip5ueiioTRRVVHC+uJLOgnIyCcjIKysgoKCersJz0gnLSt2WwaFvdTCtPNz1hfh54Gg14uhnwdNPjYVTH9nE34ONhVF/uRnw8bB+rbW93A70OJ+EDHPFMID81n8DqQLpB21hvVZaoLh1Q3SPFmerfGSCwY+STgAglgiC0htqMEhvrrT2/qFDA4F5WSypn4ukPUx+Gn++FtW9A37NUDoneDYJ6qH3iRqmvhjAYVVVByiqrKHSKUDJM5bLYm1Oy7k3179b7DJjxpFowv+wT+Ph82PE9nPV087tKiix/YCXI3bXR6eDmFSoE1DPAKjwu+hskvQsZyV1LKKmuhOxdalsLFrTBz9ONc4dEc+6QaHZnFPLi4n0s3pXFou0ZLNqewdC4QM5KjOTMAREu7bGcV1LJv3/ayY/J6uJ0YLQ/L84e2mmsxARBEAShUxLS51SbKq2jxDsYAuJVVXtVicpBBPC3XIvbG+iesU2NkYPsnnajNBZS7yT0eh0vzB7Csfwytqbmc8P8JL6/bTyB3i6a/+GCHSUmk5nP1h/hqV/3UFpZg6ebngdn9OOa8d07b0FOUDe1KPv9jbD5IzjnJcfn+nQ0TDVWK6mEsxreL26sEkrcfCDx4iYPa9DrmD0qjtmj4jheXMGag8fZnlbAnswidqYVcLykksW7sli8K6v2PWN7BnP5qHjOSozE083Qym/MAcSNhsGXqW6HbuOV9fqA8yjVefHe0v28teIgpZU1AMxMjOShs/rR3VawtTiSeOcfwDtuNFEBXnYX7ZVUVLP1WD6bj5zgUE4JqSdKOXaijMzCcsqrTKTm2ZlbCxipZofHNtDBtX/UcPj3vxiqy+EHD8hIPcj9764j0t+TcH9PEiJ9GRYXRLcQb/u7WNK3qC5Iv2joc4b6XTywRL3WQfJJQIQSQRBagyaUmE3qD7HeoNoWAQZd6jr5GEOugD+fgIKjsPpF9VxI77o5JE0RN0YJJVC/v2L0cDXaI5SYzXBwmdoef6f6dwTocZrVO3jXQhh2VfOOJx0lHQe9AXxC6z6ntcWmJ7f7dJxKzh4lunoGNFlx0j/Kn3fnjmR3RiHvrTrMwq1pJKfmk5yaz9O/7mFwbACXj4rnvKHR+Hq4xqWOyWTmm02pPP3rHk6UVmHQ67h9Si/uOL2Pa7enC4IgCIJg7b6wDXS37SjR65WgkbrO2l2iFS0V2SmUZFqEknoKSBxCsOV7OpGirJQNrlH17elm4N25I7jw9TUcyi3h5k828dF1o/Fyd4EF1pOp7Sixw1qtDTh6vJQHv9vKukPqZ3N092CevWRw3UXezshln8KKZ2HTfHXP/v3NcPMyZ8/KuRzbCKXHwSOg8dzYhJmw7UsYPqdldt9AiK9HbSEbqPudXRmFrNiXw+YjJ9iVUUhGQTnrDuWx7lAe/j8auXBYDJeNimdAdCtyXVuLTgcXvVP7MLOgnE+Wp/D5+qOcsATVD40L5JFZ/RnZPfjU94cPUJ/r2buU6NIKfDyMjO8VyvheddcEKqprSM8vJ6+kkoqqGiqqTZRX1VBerfJPSitqKKmspqSimuKKGkprt6sprayhuKKamPIDeFZVUYw3Vf7didHpqaqOhGoINZ9g3cEcTNS9Dw31defMgZGcMyiKMT1DWiauplrySeJGqTWNzR9Zi6pFKBEEoUugt/kIqamCsnw4ZLkgcQXbLQ03Lxh5Pax8DjZ/rJ7TWuKbi+0fwIDYU/0Vo4eqMe8QFGWpNtbmkr1bVcAYvSB+rPV5nc4i8jwOW79oWCgpL4S3J6v8lMs/k46Sjo72s5SxtW5gaGfH1narmSJr/yh/Xpg9hIfOSuD3XVn8sTOTtQePs+1YAduObefJRbu4bFQ8103oTlyw83I/9mQW8siCHWy0+Nb2i/Tj6YsHM7SD2YUJgiAIQpdFq0637b6o7SgJUuPMp2H/Yuh3rnrcWqGktqNksH3vbwq/KGUvXFUKJ464lGVRuJ8n710zkkvfWsuGw3nM+3QT78wdgYexncSS3P3w090w+QHoNbXh/bSOkgDnLgKaTGY+WXeEp3/dQ1lVDV5uBv4+sx9zxnZD31m7SGzxDYdZz8OYefDaCBUi3dJ78s7Gvl/V2OeMxkXQAefDbetU11wr0et1JMYE1LF3S8sv47tNx/gqKZW0/DI+WnuEj9YeYXBsALNHxnHe0Gj829maq7yqhtX7c1l9IJeklDx2ZxRiMqvX4oK9eGBGP84dHNVwZ0VoHzi4VK39tBEeRgM9Qn1aZz246Qj8BL49RrL6munqOVMN5sdvxY0aXjsvhqNVAWTkl7E9rYAd6YXkFlfy+fqjfL7+KKG+7pyVGMnZg6IY0S2o6c9fTSiJHQ0xw+u+JtZbgiB0CQw2LdCmKuU/aKpWF/Ou1uo68gZY/bLVOqulQkmsjTVXfa3VXkFqgTdjK3x/E1z9ffM7Vg7+qcbuE1Twoy2DL1PdMCmr1A1MUD1/YI6ugxOHLV8p0lHS0QlNUKJZZZHK1nG136W24qR8kpYQ7u/JnLHdmDO2G7nFFXy/+RhfJqVyKKeED/46zPw1hzm9XziXjozj9H7huBnaXnwqr6rhUE4JPySn8f7qw9SYzHi7G7jvjL5cO747xnaYgyAIgiAIDkJbRDy+3/pcWb4avSwVx9HDrJ3BYA1gt8cLvjhbFVKhU8VQbYFer7pKsrZbrjldRygBVRDz4XWjmPv+Blbsy+HOz7fw+lXD2+U6jrWvqazIX7Lh9g31Fy5VV1rvu5xovXXkeAkPfLuNDYeVcDe2ZzDPXjyE+BDnFQk5jdDeyv47I1ndYw+9wtkzcg7VlSqnFaDf2Y3vq9NBeP82m0pMoBd3TevDHVN789fBXL7ckMofuzIthW0FPLFoF7MGRXP56DhGdgtqfXh5AxSWV7FsTza/78xk+d6cWmstjdHdg7l+Yg/OGBDRdBeFb7gaS463yVwdRvpmNdr+XdIb0PlFQmEaZ8ebIbZX7UuV1SbWHz7Oom0Z/LYzk9ziSj5dd5RP1x3F3ahnaGwgiTEB9AjzoVeoD8O7BVmt1MxmOKZ1lIxRXTcGD6ipUM/Vt47loohQIgiC/dhWJtRUwY7v1LYrdZNo+EepgPRtX6nHLRVKvIMhtC/k7mu4bfCCt+C96XB4BSz5p8oaaQ6aUNLr9FNfC4yDHpPg8Eo199MePHUfbYEZYO+v0lHS0TEYITIRjiUp+60uJ5QMbdVhQn09uHlyL26a1JOV+3N5b9UhVu3PZcnubJbszsbf08iAaH8SIvxIiPQnIdKXvhGtDxksLK9ia2o+K/bmsPpALvuyimorkwDOGhjJY+cOIDrQq1XnEQRBEATBCWh5HvlHobpCFTeV2mSU1EdtR0lmy8+n2W6F9AKPNsxeC7EIJccPADPa7jx2Mqp7MO9dM5Lr5ifxx64s5n2yideuHN62Nlxms+oMAiWMHfwT+kw/db/CNMAMRk/wCWu7+TSAyWRm/poUnv19D+VVJrzdDTw8sx9XjekiXSQN0XuaRShZ2nWFkl0/KqHVN8La4eZk9Hodk/qEMalPGMeLK1iwJY0vk1I5kF3Md5uP8d3mY4T6utM/yp9+kX70i/SnX5QfvcN97eokM5vN7MksYtX+HFbtz2XdoeNU1VhvzqIDPDm9fzhjeoQwukcwEf6ezT+49vtektPiebUrmi189EndHf7R6vOrMA0YUfu0u1Ff+3/0+AWJ/HUgl0XbMli2N5vc4ko2pOSxISWvdn8/TyNnJ0Zx4fAYxgTkoys9roqpowartcLIQZC2Ue0s1luCIHQJ9AbQ6VVGSVWZ6mwA6O8af4xPYeytVqEktIVCCaiQr9x9ENZAxUXEALjwLfh6jqpCih7WtGhUVa6qlaB+oQRgyJVKKNn6hWr/PrnKIiPZur3jexUODurCSOiYRA+zCCVbukagu6kGMrerbQf5cOt0Ok7rG8ZpfcM4kF3MN5tS+X5zGjlFFbU+ubbEBHqREOmHQa8jNa+UrMJyvN2NBHi54WbUU15ZQ1mV8oQtr1IVSME+7gT5uJNdWE5GQfkpc/D3NNI/yp+bJ/dkWn/5fRQEQRCEDotvOHj4Q0Uh5B2G8H5W6y2vpoQSO6y32tp2S8MFA91PZkLvUN6eM4JbP93E0j3ZXPXeOt6/ZhRBPm0U8J69y7KAaGH9m/ULJQU2+STtnM15OLeEB7/dSlKKuu8b3yuEZy4e7FSrWZeh93RY9YISuLqSjbEt699U48gbwNhGvyetIMTXgxsn9eSGiT3YfDSfr5KO8tPWDHKLK1m1P5dV+3Nr9zXodfQK86FfpD8jugUxrlcIfcJ96+08yS4sZ/WB3Npj5BZX1Hm9d7gvMwZGMGNgJINiAuzvXukIQklVOWTtVNsn22D5xwBJjXY7uhn0TEkIZ0pCOGazmZTjpSSl5LEvs4iU4yVsTysgq7CCrzam8tXGVO4PWMadQHnYINz17ir5JGa4EkoMHuAT3kbfqOMRoUQQhNahd1PtdAWpYK5RuSWu6j8YPQwm3AOluaoVsKVM/6fKjxg0u+F9BpwHk/4Gq56HRfdDz6ngE9Lw/kfXQnW5upEK61f/Pv3PVcfKOwQb3oUxN9d9XbuRAmu7o8FD2YEJHROtq8JWBOvM5O6H6jJw97UGizqQ3uG+PDyzPw+cmcCezCL2ZhaxN8syZhaRWVhOWn4Zaflldd53orTqlOdsKa6o5mheae3j6ABPJvQO5bSEMEZ1Dybcz6PN2scFQRAEQWhHdDrVfZG+RYkK4f2a7ijxtwgllcUqU9CzBeHFtUHubS2UWK67XFgoAZiaEM5nN47h+vkb2Xw0n4vfXMM7c0fQO7xl4dPNYv8faowYBFk74MASyNkHYX3r7lcb5N5+tlsV1TV8tCaFF/7YR0W1CR93A/83qz9Xjo6Xa06N2FFK1Cw9ru6lTl4k7uykJkHaJlXZP/J6Z8+mUXQ6HSO6BTGiWxD/Pi+RvVlF7MkoZE9mEbszCtmdUUhheTX7sorZl1XMwq1qYT/Mz4Np/dQiflF5FduOFZCUkseezKI6x/dyMzC2ZzAT+6jiud7hDurOqxVKchvfz5lk7VC2+N4hp35G+ceo0VYQbgSdTndKXorJZGb94Tx+TE5j5da9XFX+BejgqdREvvv3HwyLD+SO4G6MAeWS0oEESxFKBEFoHQZ3JZRoQVb+MarTxFU549/2v9czAIbPbXq/KQ/Dvt9VG/vSf8F5rza8r2a71XNqw5VIHr5w2gOw5F/w64Oqom3gBeq10jwoOKq2A7tB/hG17RfZ7pVNggPpaoHu2mJARGKbfq9Gg/6UgEGAgtIqJZxkFYHZTGywN1EBnpRXmcgvraSqxoyXmwEvd0PtaDabySup5HhJJSE+7vSJ8CPAq32DCAVBEARBaEdC+liEEktOSW1HSQPFSe4+4BEAFQXqfaueV4tWl3xovU4vOa6KpgJi6r633TtK2i6U2FGM6BbMN/PGcc0HGziUW8L5r/3FC7OHclaig3MZNdutEdeoe7W9v8Dql6DvmerafOCFqgO64JjaLyDWseevB5PJzM/bM3ju9z2k5qkinom9Q3n64kHEBkkXSR0MbtBjMuz5GQ4s7RpCSXmh6oTyi4J1r6vnBl0Kvu1vCWcvXu4GhsYFMjQusPY5s9lMZmE5ezKK2J5WwPrDx9mYcoKcogq+TErly6TUOsfQ6SAxOoBJfUKZ1CeM4d0C7bLtahKfUDWW5CirPldcd7G13Tp5frX5Wc0TSupDr9cxrlcI43qFUGV8H7ctxRwxdueb6jMprahm1f5ckongDfchJJefxtaPkgj39+SiYTGM7N5AcYGLIEKJIAitQ8sp0YSSdqyocVkMRpj1PHwwAzZ/DMPmQtyo+vc9uEyNDdluaUy4R1UtbXxfhcX7hEL3idZch+Ce6qJ91QvqseSTdGxqA92LVYXfyRVsnQ3t86Ol2UEOIsDbjdE9ghndo2UXbT07zr2HIAiCIAitRRMVci1CSWkT1lugipcqCuCLy6HK0oU6/V8Q1F0tsM0/W9mf3LXFuvhWUaTC1cFhlqQNon1PhcegshTcXXvRvW+EHwvvmMgdn29m/eE85n26ifvP6Msdp/d2TEdFWb7VTrrPGSqjcu8vsPVz9QVwaAXcvMymWK3tvPdrTGZ+3pbOG8sOqoIeINzPg7/NSODSEbHSRdIQvacroeTgUlVw2Nn59jrV+WTLmHnOmYsD0el0RAV4ERXgxdR+4UAfKqpr2HA4j6W7s/nrQC5BPu4MiQ1gaJyy5QpuK0s+W7SOkuoyqCxp2xwpezCblSU7QOzIU1+vFUoatt6ql7xDyrnEVthP24Tblo8A6DbnTbbFjmV/djF/7slmwZY05mQ/BMeB49kAjOoe5PJCSavKNp9++ml0Oh333HMPAHl5edx5550kJCTg5eVFfHw8d911FwUFBY0e59prr0Wn09X5Ouuss1ozNUEQ2otThJK2r6jpEMSPhaFXqe1F98Hxg6fuU3JcdZ0A9JzS+PF0Ojj7Oeh/HtRUwsK71B/A2gDsIZAwy7q/n4Mrq4T2xWBU4WfQNey3TqSoMai7M2chCIIgCILQMBED1ZixTXX8luerxw1Zb4HVfqvKatVJapIajx+EnD0q9+TYRuvrmq+8X7RVPGkrvIOtHTF5rt9VAsp259Mbx3DDxB4AvLB4H/9auBOTydzEO5vBoWXKTjo0QV2X9pgM8ePVa5p1c/oWlQnZhtZbJpOZhVvTmf7iCu7+Mpm9WUX4ehi574y+LH9gCrNHxolI0hi9p6kxdQOUN74e2eGpKlfiHShbdIC+Z7W9bZ+T8DAamNQnjH+dN5DF953G17eM4x+zBjBrcFT7iCSgugXdLKKyK+aUHFwKR9coUWPYnFNfb6H1FqB+j96aBK8Ohy2fqucyd8CCeYAZBl8G3cZjNOjpH+XP7VN7s/jeySy+dzLvzR3Jkxcmcve0Pgw6ydnBFbG7oyQpKYm3336bwYOtv3zp6emkp6fz/PPPM2DAAI4cOcK8efNIT0/n22+/bfR4Z511Fh9++GHtYw8PD3unJghCe2Kw/DHKO6zGQOkoqWX6v2H3z8pW6NXh6mJ78gMw7Gr1utYOGdK7eW2xegNc8KZqAc87qELgbYWS6GHgGwnFmdJR0hmIHqoyZ9KTYXAjuTidARFKBEEQBEFwdTRr1JzdUJwFZpN63FhHSUgfOLRc2Z+E9oFtX0Hqehh8qVrI0sjcBgmWYtFa261Bjv4O6ie4lwrcPX4AIhPb55ytxM2g59FzBhAX5MW/f97FR2uPkFtSyfOXDMHLvRVWO5rtVt8z1ajTwTU/KaHL0x9eGwW5+yBltTXM3cH3vxtT8njsx53syihUh/d24/oJPbhmXHcCvMXmtVkExqtuIO3/qt+spt/TUcnYCqYq8A6Fv+1X2SzejWSkCo7BJxTyj6qckuAezp6NFbMZlj6utkfdeKqtI9h0lGQ03+Y7PVm5XQD8eDts/VLl7Zqq1c/eGf855S06nY4+EX70iWiDLKk2xK6OkuLiYq666ireffddgoKsfpyJiYl89913nHvuufTq1YvTTz+dJ598kp9++onq6upGj+nh4UFkZGTtl+1xBUFwYfQWvVVrD5eOEiu+YXD5Z9B9kqruOJECfzyi/hiBtVNAC+5uDh6+kHix2t78cV2hRK+HQZeox+11YyW0HbWB7ludOo12oVYo6ebUaQiCIAiCIDSIf4xaEDJVQ8oq9Zy7LxgbqWKe+n9w8ftw7c+qyhtUIQxYLZ6g7vVepnZ9304V4cE91ahdj3Ugrp3Qg/9dPgw3g45F2zK46M01HDleYt/BqiutQe59zrQ+bzAqkQSgx2lqPLQcCizV2A7qKDGZzLy14iCXvbOOXRmFtR0kqx86nbum9RGRpKXEWqyvM3c4dx5tTep6NcaNUesBvmGdP9/SFagNdHexjpLdP6l1JndfmHRf/fv4RYJOrwS2/JTmHVf7G+UXDejU30BTNfQ/F+at7lSOJnb99tx+++3MmjWL6dOnN7lvQUEB/v7+GI2NN68sX76c8PBwEhISuPXWWzl+/HiD+1ZUVFBYWFjnSxAEJ6F1lGgtrSKU1KXHJHVj9OAhlTlRdkJVa4GNUNJC7+Hh16hx5w9WgSrScoxp/4TrfoUhl7d25oKzCe+nRi0wtLNSVQZFGWo7yIWqcQRBEARBEGzR6VQHN1hzBhvrJgFlbTXoEmXVEjdaPZe5Q/naHzmpo0QjPVmNbR3kruEbrsbS3PY5n4M5b0g0n9wwhlBfd3ZnFHLuq6v5fWdmyw+08X216OkbAXFj69+np0Uo2fUj1FSoxUatOrsV5JdWcvMnG3n61z3UmMxcMDSalQ9O5a5pffD1kGhhuwiz3Evl7HbuPNoaTXhtKBNVaBtcUSipqYZlT6rtsbc2bN1ocFP2ggDvTlPdIeYmrAs1oWT0TTD3ByWQXPap+vLvXG4mLRZKvvzySzZv3sxTTz3V5L65ubk8/vjj3HzzzY3ud9ZZZ/Hxxx+zdOlSnnnmGVasWMHMmTOpqampd/+nnnqKgICA2q+4OLH6EQSnYTipsiWg7cLsOjSe/hAzXG1rFzPplj82Wht/c4kZDuED1cU5qComH0t7rdEduo1XNl1Cxya4lxqLs1SoZ2cl3xKE6eFv9cgWBEEQBEFwRbTr9oN/qtG7BdcuAbGqGtdcA3t/hROHAUvORP5RVVBVnANZlgr4+AYW6x2NtphW0nCxqqsztmcIP905kWHxgRSWV3PLJ5u476tkCsqqmneAshOw4hm1PfX/Gu4S6jYB0FkXR/2iTr0fbiFbU/OZ9cpqluzOxt2o578XDuKly4a2X95CZ0XLlMnuxEKJ2WzNPIod7dy5dDVqPzddSChZ9YLKvfIMhHF3NL7vxe+qNaWyPFhwC/z5eOP72zqZ9JyiBJL+5zpi1i5Hi4SS1NRU7r77bj777DM8PT0b3bewsJBZs2YxYMAA/vWvfzW67+WXX855553HoEGDuOCCC/j5559JSkpi+fLl9e7/8MMPU1BQUPuVmprakm9DEARHcopQUo8HoqDQ2n9T10NpHhRYFohbWi2m08HwudbHLe1IEToGXoHK3gFU2GdnxdZ2S0IpBUEQBEFwZTRr1GJLx0JTHSUno1V9r3lFjZGJKk8BIHM7HLaEMkckWjs92hpvF1zws4OoAC++unkct5zWE70Ovt+SxoyXVrL2YDMEoJXPK7EkfED94cca3sF1771aYbtVYzLz/urDXPrWWtLyy+gW4s33t47nyjHxEtTuCGq78w8oW7XOSEGq+izSG63dbkL7UNtR4iKdeKkbrGLv2c+rtYTGiBwEt6yAyQ+qxxs/UB0p9VFRZHVF6QJrTy0SSjZt2kR2djbDhw/HaDRiNBpZsWIFr7zyCkajsbYDpKioiLPOOgs/Pz8WLFiAm1vLFPaePXsSGhrKgQMH6n3dw8MDf3//Ol+CIDgJg02li1ewaisX6idujBpTN1htt4J6NP1HrD4GzwaDh9ruAn+suiwhlq6SvK4glHR35iwEQRAEQRCa5uRO8JZ2w2pV31p1bvx4a9FUxjarpVfPKfbOsOVoldEd1HrLFnejnodn9uebeePpEepDZmE5V763jhf/2Et1jan+N+UdgvVvq+0zH2+6M1+z3wK7g9wPZBcx++21PP7zLiprTMwYGMFPd04kMSbAruMJ9eAfozrWTdXWRd7ORqrFqSJyELh7O3cuXQ1Xst4qL4TvblTdioNmw+BLm/c+gxuc9pDqQCk7YXU+OZnMHYAZ/GMbtvPqRLRIKJk2bRrbt28nOTm59mvkyJFcddVVJCcnYzAYKCws5Mwzz8Td3Z2FCxc22XlSH8eOHeP48eNERXUunzNB6JTobYRQOy8UuwyaL3HOHji8Um231HZLwzsYRl6vqke0YEih86HZbx0/5Nx5tCUilAiCIAiC0FHwj7EukIG6Jm8JcSfZ48SPtQolmdvgkEUo6TXV/jm2FO+Ob711MiO6BbHorolcOiIWsxle+fMAV7y7jrT8slN33vCeCjXudTr0bjqHtzbQHezqKPlyw1HOfmU1m46cwNfDyBMXJPLW1SPw95Swdoei03X+nBJNKBHbrfbHlYSSZf+F/CPKBn/W8y17r8EIfc5U23t/rX8fW9utLkCLhBI/Pz8SExPrfPn4+BASEkJiYmKtSFJSUsL7779PYWEhmZmZZGZm1skb6devHwsWLACguLiYBx54gHXr1pGSksLSpUs5//zz6d27NzNmzHDsdysIguOxtd5qRetxl8AnFIJ7qu3NH6tRa9+3hxn/hYfTIKqdgh6F9kfrKOmsVVAgQokgCIIgCB0Hna7u9XtLrbeihtTtyI8fZ72W3/cbFKap1+PHt3qqzcYVvfYdgLe7kecuHcL/Lh+Kr4eRpJQTnP2/Vfy246Sgd+06e8D5zTtw/FhrsWALCgWrakw89uMO/v79diqrTUxJCOOPeydz9dhuYrXVVoT3V2NnzSmpDXIXoaTdqf3cdIFOvL2L1DjzafC0oystwVJ4u++3+l8XocR+Nm/ezPr169m+fTu9e/cmKiqq9ss2R2Tv3r0UFBQAYDAY2LZtG+eddx59+/blhhtuYMSIEaxatQoPDw9HTk8QhLagjlAS67x5dBQ0+61SS8VWa/7Y6PXg1vKuPaEDIdZbgiAIgiAIroVtR3hLO0qMHlahJag7+EdZO0rK1RoJ8WPb10ZHW/CrLoPKkvY7bztx/tAYFt01kSGxARSUVTHv0008+sMOyqssxbz5ltzI5hb9uftYKrB1ED28WW/ZnVHI5e+s4+O1RwD425l9+fDaUUQHerXwuxFaRFsJJfsXw+eXW392nEFVmco1AhFKnIGrdJQUpKmfQ50eeky27xi9pyunktx99WejdjGhxNjaA9gGrk+ZMgWz2dzke2z38fLy4vfff2/tNARBcBa2FVHSUdI0caNh6xfWx13kj41gJ7XWW51UKDGb4YS6YSSwu1OnIgiCIAiC0CxsQ5Nb2lECSgg5tgG6TVSP/aPBO8RaSNWzHW23ANx9VfZhTYWqju6EmZPdQnz4Zt54XvhjL2+vPMQn646QlJLH/y4bSoK22B3YrfkHvPAtKEy3BoY3QGF5FS/+sY+P16ZgMoOPu4GXLhvKmQMjW/HdCM2mLYSSyhL44TYoyQajO8z+2HHHbgnpW1T+im+krMM4A00oKc0Fk0kVsTqDo2vVGDkYPPzsO4ZnAHSbAIdXqK6ScbdbX6sqU9bx0GXWrpz0PykIQqdBb6O3SkdJ02gdJQCB8S2vQhO6FppVW1kelOY5dy5tQUkuVJUAOsk4EgRBEAShY2BrvWXPtfzEe2HyA3D6I+qxTmftKoH2zSfRzm+76NdJcTfqefjs/nx0/WhCfd3Zk1nEla8sslyL0rJ7WU//JkWSpbuzOOPFFcxfo0SSWYOi+P3eySKStCdhFqHkxGG14OsINryjRBKAXT9CerJjjttSUlarMW60+h0W2hfvEDWaTSoI3VloQkn8uNYdJ2GmGk/OKcnaqULifcLBr2t8dolQIghC65COkpYR1g/cLUp/a/JJhK6Bhy/4RantvDYOdC/Ng4/Og5/va9vz2KLZbvnHKCsKQRAEQRAEV8c/2np9Zs/CkXewEkn8o6zPRQ5So1cwRDqhatfHsujnCn77bcxpfcP45e5JnDkggmjU95tlDmTuJ9v4aWs6ZZU1TRyhYQpKq/gxOY2bPt7IDR9tJKuwgh6hPnx24xhev2o4sUHtaKkmgG+4+p0ym5StUGspL4DVL6vtgHg1/vlE649rDweXqbHnFOecv6tjcAOvILXtTPutIxahpFsrhZK+lpySo2uhLN/6fEayGqOGdBlBrtXWW4IgdHFshRKpCG8avQHiRsHBP+u27QtCQwT3gqIMFTQZO7JtzlFdCV9dDUf+Ui23E+9tn99nyScRBEEQBKGjodPBRe+oStuIRMccs8+ZsOYVSLzYORYu3i4UTNwOhPt58s7ckRxZtR+WwjFzGCv35bByn1rwDPX1IDrQk6gAT6IDvQjydqfGZFZfZjXqdBDs7U6AlxuHcktYfziPHWkF1JiU1bxeBzdN7sm90/vi6WZw5rfbddHplP3Wkb8ge0/rrYPWvAbl+ar48bLP4PXRcGCxWqxu7UJ1S6gosga5t3cHmmDFJ0x1k5TkAI13mLUJZScge5fabm1HSXAP9XOdswf2/Q5DLlPPp21WYxex3QIRSgRBaC0Gy8eIwcN6gS00zhn/UYvfo25w9kyEjkBILziyuu1ySsxm+OludQOhsfdXGHOz489VVQarXoCtX8KUh5W3M4hQIgiCIAhCx6LHZPuDc+s93iS4Zwf4RjjumC2hC1hv1Uc3g/p+ExIGcGdYb77fnEZafhm5xRXkFlew7VhBi4/ZN8KXaf0jOG9INP2j/B09ZaGl1Aolu1p3nNI8WPeG2p76DwjtDcPnwKb58OfjcO2i9qu4T/lL5ZMEdrNaNQvtj0+Y6lRyVkdJ6gbArNaWfMNbf7z+5ymhZOcCJZRUV8LeX9Rr3Se2/vgdBBFKBEFoHVpHSUCM8wKsOhqRg2DW886ehdBRCLEEuue1kVCy4R3Y+jnoDNB3hroY2rvI8UJJympYeKfVQmzhnRCWoLZFKBEEQRAEoavjzO58H62jxIkWMs7AEuTuG9GT+6cncN8ZfckvrSItv4yMgnLS88tILyijsKwKg16HUa+3jDqqTWZOlFZyoqSSCH9PxvQMZnSPEGICvZz8TQl1CLNU+muB1PaSvgUqiyGoB/Q/Vz03+UFI/lwJMSmrleDZHhyy2G5JN4lz8XFyJ96RNWp0VDdT4kWw8lk4sETZbx1Zo7pWfCMdWxjg4ohQIghC69C7qVHySQShbQjprcbjB9rm+Bs/UOMZ/4aEs5VQkrJaefB6BjjmHCXH4dNLoLpMeXqH91f2c1pllwglgiAIgiAIzkMLJi457tx5tDcWoYRAlTeh0+kI8nEnyMedxBgHXQcLziV8gBqzdrbuOJqIGNTd2jkSEAPD5sDG99UCc3sJJbX5JCKUOBWtE89ZAvPRdWqMH++Y44X3h7D+kLMb9ixStnJgsYTsOvaBUv4tCELrMIhQIghtSrClo+T4IWWT5UgK0izVVToYepXqXgntq1q59y923HkOLFYiSWgC3L4Brviy7gWdCCWCIAiCIAjOQ6uMPtl6q7wQvr4GPj4faqrbf15tTX6qGi1CidAJiRoMOj0UpKp7H3vRFsO1xXGNifeA3giHV8LR9fYfv7kUpEHuXkDXpar8XRJnCiVV5ZBuyQ+JH+u44yZepMYtnyg7boDBlzru+B0AEUoEQWgdfc5Q7acDL3T2TAShcxLUHdBBZZHjL8IOLVdjzHDwDlbbCWerUfMjdQT7flNj/3PB0x+MHnDZp6oV3jdCVa8IgiAIgiAIzqF2wc9GKCnKhPlnw64f1DVjW3U3Owuz2aajpJtz5yK0HR5+1iBqzarIHoqz1XhyFkRgPAy9Um2vfNb+4zcX7f4tepj1/k1wDs60LDyWBDWV6l7akTk1Ay1CydG1UF0OIX0gaqjjjt8BEKFEEITW0X0i3J0MfaY7eyaC0Dlx87R6Vjv6BvXgn2rsdbr1uX6z1Lh/sQpway01VXDAcp6+Z1mf9wmBeavhnu3g4dv68wiCIAiCIAj24X2S137BMXj/DMjcbt2nLK/959WWlJ1QhUgAAbHOnYvQtnSboMYjq+0/hva7oS2O2zLxPpX3eGAJpG2y/xzNQfJJXIf6BOb2Ys/Paux1utUKzhGE9laZuhqDZzv2+B0AEUoEQRAEwdXRvHVbUwV1MiaTzYW2jVASM1Jd9FUUqmDC1nJ0HVQUKO/rmOF1XzO4qe4SQRAEQRAEwXn4WDJKNOutdW+qbovgntZq5dJOll+idZP4hIObBLB3amqFknrupVKT4H9DYO9vjR+jxNJR4hN+6mvBNg4buxbaP8+mMJuVxRdIPokr4CzrLZPJ+nM24HzHH1/rKgEYdInjj+/iiFAiCIIgCK6O1uWx60fHHTNzm7rhdfeF2FHW5/V66DNDbaesav159v+uxj5ndqkQOEEQBEEQhA6DtuBXVQqVJZC+RT2e/IDKmIPOK5RIPknnp9s4QAe5+6wWWhrr3oATKbD9m8aP0VBGiUbUYDUWZbZmpnXJPQB5h6yPi7PUl04PMSMcdx7BPpzVUZK2CYrSwd2vbQSzIZerIsd+5zjW1quDIEKJIAiCILg6CbNUO3fmtroXy61B6ybpPkl1dtgS1leNWsBla9hnI5QIgiAIgiAIroe7LxgsXb7F2ZCxVW1HDbXmIJR2MuutAgly7zJ4BUHEQLVt2zFfUw0Hl6rtwvTGj1GsCSX1WG+BtdOkOMv+edpybBO8OQ7ePV0Fd4PVCi+kN7h7O+Y8gv1oPwsVBVBd0X7n3W0pnuw7Q9l0Oxr/aPjbfpj9ieOP3QEQoUQQBEEQXB2fEJUHBM1v5847DBnbGn69vnwSDf8YNRamNX+O9c7hkKrc0hvrP48gCIJQy8qVKzn33HOJjo5Gp9Pxww8/1L5WVVXFQw89xKBBg/Dx8SE6Opq5c+eSnt7Ewo4gCEJz0Omsi36pG6CyGNy8IbSvjVAiHSVCB6Y++61jG6C8QG03dt9jNls7Sk4Oc9fQnj+5Y8UeSnLh6zkqrLvshFUg0UbbDAnBeXgGqq4OcFwxY1OYzVaXiQHntd159AblNNEF6ZrftSAIgiB0NDT/0ebYb5nN8PH58N70+qujKktUdgjUL2AEWMLjC1rZUbLvDzXGjwOvwNYdSxAEoZNTUlLCkCFDeP311095rbS0lM2bN/Poo4+yefNmvv/+e/bu3ct557XhTbIgCF0Lb0tOyYHFaowcBAaj9fmyE/Yf22SClL8gc0fr5uhIaoWSOOfOQ2gfuo1XY4pNR8n+P6zbhenq57Q+yvPBVKW2vRvoKPGNUGNJK4WSmmr49rq6ws2xJDWKUOJa6HQQYckSba/Ptoyt6rPLzRt6n9E+5+xiGJ09AUEQBEEQmkH/c2HR/ZC+WV0cNVb9VpgO+UfUdtom1T5rS9pmVaHkHwshvU59f4DWUZIOphr7s0WOrlVj72n2vV8QBKELMXPmTGbOnFnvawEBASxevLjOc6+99hqjR4/m6NGjxMdLRbQgCK1E89s/YLEiihqqRq9WdJSUF8La1yH5cyg4CkYvuGdbw1X57UmtUNLNufMQ2getoyR7p7KR8w6G/TZ/V01VUJpb/8+mlkHhEdCw1VGtUJKrxA6Dncuta15Rge1uPtD/HNj2lVUoybIsxkeIUOIyRCRC6nrL/82lbX8+rWiy93SxX2sjpKNEEARBEDoCvuHWC/ym7Leyd1m3tcojW7Qbw9A+qhLmlHNFqkwUU3Xr2sdPpFjOk2D/MQRBEIR6KSgoQKfTERgY2OA+FRUVFBYW1vkSBEGoF816q8ySRRI9TI1aR4k9QsnKZ2HF00okAagua153dHuQLxklXQrfMGUlB3B4BRSkWRa3deDhr55vyH5Lux9qKJ8ElPCiMwBmJbjYQ001bHhXbc98GoZeqbaPbYTKUjh+QD2WjhLXQcu+yWqnjpK9v6pRc5sQHI4IJYIgCILQUai13/qh8f2ydlq36xNKNDsurXPkZAxGaxdKwbEWTbEOmlAS1N3+YwiCIAinUF5ezkMPPcQVV1yBv79/g/s99dRTBAQE1H7FxYnFjCAIDXCypVD0UMvzmlBiR5h7erIaJ94Lpz+itncusGd2jqUkVwUwg9VyVuj89J6uxp/vgzWvqu3YUSocHRoOdG8qnwRUB74mpNgb6H5wKRSlq9+5wZdB9HBAp4TGQ8vBbFKh8X4R9h1fcDyaaGV7/91WlByHnN1qu+fUtj9fF0WEEkEQBEHoKPQ/R43HNkJxTsP7NdVRUmgRP/wbEEpsXyu0Uygpy1d+viCVeoIgCA6kqqqK2bNnYzabefPNNxvd9+GHH6agoKD2KzW1ldlTgiB0Xmyr5bUgd7A/zN1sti4eDrgAhlyhto+sgcKMVk21VVSWwNfXqO3gXmJf05WY8nclPpTlwXrL388+Z9a1Ha4PTShprKMEWh/ovvljNQ65Aowe4OkP4f3Vc5s+VGNkon3HFtoG7f+nKEMJGW1JqiVjNDQBfELa9lxdGBFKBEEQBKGj4B8NkYMBszVosz6ybISSgtRTKwALLG3ljQklAbGWfe0USrSMFJ8w8PC17xiCIAhCHTSR5MiRIyxevLjRbhIADw8P/P3963wJgiDUi+0icORga0ad1lFSnq+sgZpLcbZakNbpISxBXVvGjQHMTXdHtxVVZfDFFXBktbJbuvhd58xDcA6eATDne8v9lIW+Z1rviRq676kVSprI1tFySuzpKCnKstoqDZtjfT5mhBq1PBWx3XItPPwgqIfazqqnQNGRHFmjxm7j2vY8XRwRSgRBEAShI9H3LDXu+63+12uqIGeP2nbzUePJnqlNWW/ZvmavUCK2W4IgCA5FE0n279/PkiVLCAmRakJBEByIrfWWZrsF4Blo3da6hZtDtqWbJLgnuHmp7YEXqXHH93ZM0AEs+ZfKp3D3hau+tS5CC10HryCY+yN0nwQJZ6tgdM1yuKGOktqMkrDGj90aoWTr52CuUWJieD/r87GjLBtmNdiKPIJrUJtT0sb2W0fXqjF+fNuep4sjQokgCIIgdCT6zlDjwWVQXXnq68cPgKlK3QD2sniXnmy/1RzrLc2v2W6hxNJREtjNvvcLgiB0MYqLi0lOTiY5ORmAw4cPk5yczNGjR6mqquKSSy5h48aNfPbZZ9TU1JCZmUlmZiaVlfX8LRAEQWgpth0lUUOt2wajVSxpif1WtsVLP3yA9bkB5wM6OLbBGqbenhxeqcZzXob4Me1/fsE18A6Ga3+GK74Avd7GcripjJKmhBLNeqsRi+T6MJuttlvD59Z9LXZk3ccRYr3lcmhdPpltGOheWQIZW9V2/Ni2O48gQokgCIIgdCiih6uKv4pCa1WJLVolS3h/iBqitm2FkopiKLeEVzYno0Q6SgRBENqFjRs3MmzYMIYNGwbAfffdx7Bhw3jsscdIS0tj4cKFHDt2jKFDhxIVFVX7tWbNGifPXBCEToFPAx0lYF+gu2YFayuU+EdBtwlqu71D3WuqVUERQNyoxvcVuha1Qkla/a/XWm+1UUfJgSWQdwjc/VSejy1h/VQBHIDR0xo8L7gOmnh1souDIzm2EUzV6mdV8j/bFBFKBEEQBKEjoder0EGA/X+c+roW5B4x0Ka6xUYo0SqlPPxVQGBDaBklDd0wNIWWURIkHSWCIAjNYcqUKZjN5lO+5s+fT/fu3et9zWw2M2XKFGdPXRCEzoBfNHgFq65iLchdw55A99pr0gF1nx94gRr3/W7XNO0m/wjUVKrFZq1zWhCgrvWW2Xzq683NKNGElMbC3E01sP5t6/2Z2QwrnlHbI645NdtRb4CY4Wo7fIDq8BJcC816K2ePssHWKMmFTy6EbV+3/hy1tltjQadr/fGEBhGhRBAEQRA6Gpr9Vn05JbXVezZCSc4eqK5Q27W2W9GNn0MTSkpyVPBlS5GOEkEQBEEQhI6DmyfckQTzVlmD3DVqO0qaKZSYTNbMvPCThJJep6sxdb3qdG4vcvaqMaTPqd+f0LXxi1JjTUX9XVPFDuwo2f4t/PogzD8H8g7DoeVwLEkJeOPvqv89WiaFZOq4JoHdVDdQTaW1aw1g6xdw8E9Y/XLrz1ErlEiQe1sjQokgCIIgdDR6TQW9UV2IHT9Y9zUtODNigGrN9QpSbbrazWqBpUOkMdstUO9z81bbDfn1NoTJBPlH1bYIJYIgCIIgCB0Dn1B1DXgyXpaOkrJmWm/lp0BVKRg8VJi7LcE9lXWMqQqOtKN1YK5FKAnr2/h+QtfD6G7tFik8yXa4qgwqi9R2kxklmlDSSEfJjm/VWJ4PX8+B5U+rx8OvAb+I+t8z4W446xmY8nDj5xecg15v7ZyzzSk5vEqNx/cr6z97qamG1CS13U2C3NsaEUoEQRAEoaPhGWC9SPrsEti1ULVtVxRZBYrwAaot92T7LU30CGhCKNHprF0lzckpKUhTFgpmMxRlqIoavbFpQUYQBEEQBEFwbVpqvaV1OIclnNq9odNBz/9v786jo6zy/I9/KmRhyQaEbEIgQSSDYVHEmFaQlgxL090oOCKm2+X4k9GODrgPPS3YnJ6DQ8+xHbqZttvTP21/7YAyA6i4dCObPyREZZFNImA0KCQoGJIAISG588dNVaUgS1USUqSe9+ucnPtUPU89ucWtPOTm+9zvd7zd/nxDh3TPL998ZtuEoZ33PdF1NE6/1Zg77Va3SJu6uCXuYu5nT0q11RfuP33CrjCQpKg4Oz87vNWe+/o5zZ83sqd03f1Sr76tvw8Eh6dOScOcu+6cdxVIXY30XXHbz/3VR1LtKfs3gH5/175+olUESgAA6Ipumm+Xf5/43N6N9MJN0v9/1u6LSfFOaJNH2NYTKHGn3urf+vcIpKD7W49K/3WbtO91b9qtuAGkNgAAAOjqPKm3vvPv+GOf2tadu/98Gd+37aE2BEp2vSZ98B/eVdL+YkUJWtJcfcbG9Ulaqw3RPc6uopKkU02sKtm/xq70T8qSZv4/ydXwJ9lRea3fxIZLW/9rbPvZ3+yNg6WfSGcrvPvd18RA1NdJhX+0N0ZK0qCxdvUKLir+hQEA6IoGjJH+aYc07gkpvId0ZLu0uSFQ0jgXdMpI237VsFzXk3qrlRolUmAF3d0FOz9ZRiF3AACAUBLoihJ3KtjEZu5+zhgvySV986lUcdT/flSWSStnS2vnS89lSX+51d401BpjpG8P2G1WlKApza0o8dQnSWj9HC6Xd1VJU+m39vyPba+8Rcq4Ufrx76TLc6Xx/9y2PuPSMfQHdmXQN59KZXukLzb77nenwfZXbbX0l+nSO49LNVXSgGxp8qKO6y+aRaAEAICuKipGuulfpLm7pJt+4V0lcnmu9xh3iq4jO6XqCm/Qw5+7ljyptw63fJw73ZYkHXxP+nq73aY+CQAAQNcXaDF3993Tic2sKOnZx3szz+cb/e/Hic8lGcnVTTL10sG13hXVLakstXd3u8KkvoP9/35wjtZSb7kDIK3xBErOK+he9Y1U/L7dzppu26vypJ/8jxSTHHh/cWnpES9dMclu73rNW5/EnaEhkEBJfb20+gF7bYzoJf3g36V73rW1nXDRESgBAKCri06Uxj0uzfnErjLJ/kfvvrj+Uu90ydRJJVu9v/z7k3rLEyhpZUXJ6eM296pkl5Pv+IvdJlACAADQ9QVSzL222rt6o7kVJZI0uCH9ViB1StzpXdPHSre+aLfddQAkqeaU9N7TUtE7vq9zp93qnS6FR/n//eAc7j9oX5B6q2FlSK9WCrm7eQq6l9maJG89ZoN5W5bY4F7KKKlPRod0GZeY4bfZdvd/e69L19xj22MBBErWL5T2rpTCIqRZy6Rr7yPlVifiXxoAgFDRLdz+4n1+XZBBN9i26C1vrtRAUm+1VqPk/Duvzp2xbTyptwAAALo8f1eU1J2TVv2jvUEnOqnl3zfddUo+32hXJ/vDHSjpPagh0OKSjh/0pjna+ntp82+kZbdLr/7UriSRvIXc+5F2C81wf1bPv0Hs1Le29TtQ0ij11vv/Ln30grTulzZQInlXkyD0DJkoRcVJlUdsuqzu8VLWDLvv+AF7fWzN/rfsNUySfvxbm6INnYpACQAAoS59nG33rrJt9zgpKrr118U2CpS0NIF1B0piUiU1KnLIihIAAICuzx0oOVNuCww3pb5OWn2/tG+1vRN62tKWi1+nXWfr7FWV+Z+Wxh0oiR8o9ejtrcvnvnv7wFrvsZ++If3nddLxQ94VJQlD/Ps+cB7PipIjvvOeqjauKCk/bGs3SlLa9+wfzXv1k0bM7JDu4hIU0V0a9mPv40E3SPGDpIieNvvCd8Wtn8N9DRt9jzRq1kXpJlpGoAQAgFA3aKxtq0/a1p+0W5K3jkntqZZXlVQ2BEpSR0kDr/c+T6AEAACg6+vRu2HD2GCJmzH2Dug3HpKWXCXtXiGFhUu3vSwN+fuWzxkeJV12td1217drTeMVJZINtkg2vezpE9JXH9rHs5ZLSVnSme+k1x+UvnEHSlhRgmbEpNj23Bn7uXELtEaJO6Cyb7VNVReTKt29RnqiWHr0M+qRhLoRt3m3B421KbMSrrCP3bWbWuK+xvUf0+Fdg38IlAAAEOpiU6S+lzd67EfaLUmK6OENfOx6tfnjPHVPUqUR/2C3o2IbTaoBAADQZXULtyuSJd/0W8XvS8vvkLa/LJV/aVeI3Pp/pcwf+HfelFG2PbrTv+PPD5QM/J5tv9wiHVpva0AkDpOGTpFu/y9bCLlki/RFQ2FlUm+hORHdvcGSsr22NUb6tiFtm3tfa9wrSmqqbHvVT2xa5LAw6kw4wcAbbC0kVzfp8gn2OXetJnfAtiXnX+PQ6dr1U/rMM8/I5XJp7ty5nueqq6uVn5+vvn37Kjo6WjNmzFBZWVmL5zHGaP78+UpJSVGPHj2Um5urAwcOtKdrAACgMfeqEsm7UsQfo/Jsu/OV5tNveVJvpdg8rIMnSDkPtpxuAQAAAF1HUwXdd71m20FjpTtekx77TBo2zf9zpo6y7ZGdrR9bc1qqaqg54llRkmPb0l3eFLPulSy9B0q5T/ueg9RbaEnGeNse+Jtty/ZIlUdt6iR/7/B3B0okSS4bKIFzhIXZFUT3rfNeb9wB2m9aWVFSd046edhuEygJmjYHSj766CP94Q9/0IgRI3yef/jhh/Xmm29qxYoV2rRpk44cOaLp01suVrR48WItWbJEzz//vAoLC9WrVy9NmjRJ1dXVbe0eAABoLL1RoMTf1FuSnexG9JJOfO7N/3w+z4qSy6SoGOmnK6XxT7a9rwAAALi0nF/Q/VyNtP9Nu33jk9IVk6TusYGdM/Uq25bubr3QcXmJbaPivKuW4y6T4tLsSpL9a+xzQyZ6XzPm/0gDGtJzxaR4V8UATXEH2dx1Ij77q23Tb7QrTvzROEVXxngbsIOzxPX3XtskqV/DipJjDbWY6uuarvVU8bVUf07qFun/CiZ0uDYFSqqqqpSXl6cXXnhBvXt702qcPHlSf/rTn/Tss8/qpptu0ujRo/Xiiy9qy5Yt2rp1a5PnMsboueee0y9+8QtNmzZNI0aM0Msvv6wjR45o9erVTb7m7Nmzqqio8PkCAAAtaLyixN/UW5It+p51i93e8UrTx3gCJfxCBwAAEJLOD5R8vsHWv4tO8qbAClSfwVJkjK0L8W0raWk8KWkG+q5aHpjj3Y6KkwZkex+Hhdmi8n2HSFf9tG19hHMMvklyhdk7/8tLvAGT1urtNNY4UHL1nR3bP3RNiZm2PX5A2vyctGiAtGzWhdkayr+0bfxA0rQFUZv+5fPz8zV16lTl5ub6PL9t2zbV1tb6PJ+Zmam0tDQVFDR9F2pxcbFKS0t9XhMXF6fs7OxmX7No0SLFxcV5vgYMGNCWtwEAgHNEJ0opI+22+5c1f41qWDK+d5V0turC/ZVHbRsbQEovAAAAdB09G1JvnW5IvbVnpW2H3WxrMLRFWJiU0pClxJ1+a9cK6dWfSFXHfI9tLnd/WqNAyeDvS90ifPcnXC499LF007+0rY9wjh69vYG2Xa9KX31otwMJlET2kkbcLmV8X8qc2vF9RNcTl2bTt9XVSO8tkGpPSQf+aoPNjVGf5JIQcKBk+fLl2r59uxYtWnTBvtLSUkVGRio+Pt7n+aSkJJWWljZ5PvfzSUlJPs+39Jp58+bp5MmTnq/Dhw8H+jYAAHCef/izzR992ejAXpd2nb3jr/aUtG+1777qCulsw8pOlggDAACEpsYrSmqrpf1v2cdZLadab5U7Rc3RnVLtGentx6RP35TWPOx7x7U/gZLGabeAtnAHRTY/Z1O69fs7KT4tsHNM/4N052opPKqje4euKCzMW9C9e5wt+C5Jm37te1zjVXMImoACJYcPH9acOXP0yiuvqHt3P/PzXQRRUVGKjY31+QIAAK3ok27zRwfK1agQ4Yd/9J20uleTRMXZNF0AAAAIPe66IN8USXv+W6qptKuJ+1/bvvOmjLLtkZ12lUp1uX28f43vDTrutDTnB0r6DbWptbrHEShB+7k/QzUNq+iv4DOFDjD536Sxj0n5H0kzXrB1SEq2SF9s9h7DipJLQkCBkm3btunYsWO6+uqrFR4ervDwcG3atElLlixReHi4kpKSVFNTo/Lycp/XlZWVKTk5uclzup8vKyvz+zUAAKCTjb7bLhk++onvMmFPfZIA6p4AAACga3GvHD7wV+n1fLt95S3tz6XvKei+y96QI0l9Mmz79uPeVF/N3W3tckn3/k36WaEU3a99fQGSsnxXyRN8Q0cYMEaa8JQUk2Tnze6aSZsWe48hUHJJCOh/tAkTJmj37t3auXOn5+uaa65RXl6eZzsiIkLr1q3zvKaoqEglJSXKyclp8pzp6elKTk72eU1FRYUKCwubfQ0AAOhkPft4CxJufs77PIXcAQAAQt+waVLOgzYVkSSFhUsjZ7X/vH0yGgq6V9v0W2ER0l1rpH6Z0qlvpHfn2dXMnj8ipl94jp59+F0UHcPl8qbfior11iwBOtINc+01tHiTdLihFg6BkktCQIGSmJgYZWVl+Xz16tVLffv2VVZWluLi4nTvvffqkUce0YYNG7Rt2zbdc889ysnJ0XXXXec5T2ZmplatWiVJcrlcmjt3rn71q1/pjTfe0O7du3XnnXcqNTVVN998c4e+WQAA0A45+d5f6L7ebp+rZEUJAABAyIuKlib9q5S/VXrsgDTnEyk5q/3nDQuTUkZ6Hw+bJsVdJk1bKskl7VouFb0j1Z62j+MGtP97Ai0ZMVOSSxp+q9QtIti9QSiKT5OG32a3P1lu636ePt6wjxolwdTONZIX+s1vfqMf/vCHmjFjhsaNG6fk5GStXLnS55iioiKdPHnS8/iJJ57QQw89pNmzZ2vMmDGqqqrSu+++G9Q6KAAA4DzxaVLWrXb7g+ds61lRcllQugQAAIBOFp0oxfXvuPOljvJuj7nXtv2v8a5YefOfbBvXXwqP7LjvCzRl0A3SI5/auhLAxZI1w7b735K+K7bbPftK3anDHUzh7T3Bxo0bfR53795dS5cu1dKlS5t9jWlcBFZ2VcnChQu1cOHC9nYHAABcTNfPsXf27XtDOn5Iqmgo5h5DugMAAAC0wYBsqeB3UuKVUlqjFOwTnpL2rrIpuCRS0qDzkMoNF1v6WJt2sKpU2tOwwIBrXNB1+IoSAAAQwpKGSUMmSTLSB/8hVXxtn2dFCQAAANoi84fSj38n3f6KrRHhFpsqfe8h7+PzC7kDQFcVHuWth7PtRdsSKAk6AiUAACAwN8y17SfLpBOf223uugIAAEBbhIVJV/9U6tNEofbr50jRSXabPyICCCWZU21b3VCegmtc0BEoAQAAgUnLsSkS6mqkmir7HCtKAAAA0NGioqXpf7Qrmt01SwAgFAz5eykswvuYQEnQESgBAACBcbmk6+d6H4d3l3r0Dlp3AAAAEMIyxkt5r3VsAXkACLbucVL6OO9jAiVBR6AEAAAE7orJUr9Mux2T4ptPGgAAAAA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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#Calculate stock volatility with Python"
      ],
      "metadata": {
        "id": "ebuKrd1RZUtO"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "aapl[\"Returns\"] = (aapl[\"Close\"]/aapl[\"Close\"].shift(1)) -1\n",
        "amzn[\"Returns\"] = (amzn[\"Close\"]/amzn[\"Close\"].shift(1)) -1\n",
        "csco[\"Returns\"] = (csco[\"Close\"]/csco[\"Close\"].shift(1)) -1\n",
        "ford[\"Returns\"] = (ford[\"Close\"]/ford[\"Close\"].shift(1)) -1"
      ],
      "metadata": {
        "id": "Dzo7O8MpZYP0"
      },
      "execution_count": 57,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "aapl[\"Returns\"].hist(bins =100, label =\"apple\")"
      ],
      "metadata": {
        "id": "2Cqt9uTdZzRP",
        "outputId": "b014698d-f2a5-493c-f843-552fc4ec441c",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 448
        }
      },
      "execution_count": 54,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 54
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [],
      "metadata": {
        "id": "fifGKt0aZUmh"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "figure , axes = pyplot.subplots(2,2, figsize = (20,10))\n",
        "\n",
        "aapl[\"Returns\"].hist(bins = 100,label = \"Apple\", ax= axes[0,0])\n",
        "amzn[\"Returns\"].hist(bins = 100,label = \"Amazon\", ax= axes[0,1])\n",
        "csco[\"Returns\"].hist(bins = 100,label = \"Cisco\", ax= axes[1,0])\n",
        "ford[\"Returns\"].hist(bins = 100,label = \"Ford\", ax= axes[1,1])\n",
        "\n",
        "pyplot.legend()"
      ],
      "metadata": {
        "id": "qdJxKdTKdtza",
        "outputId": "5f2897bd-544f-4c23-a1a1-c40d5c110e03",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 848
        }
      },
      "execution_count": 60,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<matplotlib.legend.Legend at 0x7d150260f340>"
            ]
          },
          "metadata": {},
          "execution_count": 60
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 2000x1000 with 4 Axes>"
            ],
            "image/png": 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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#Calculate correlations between stock features"
      ],
      "metadata": {
        "id": "Le7jJGIAfefA"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "aapl.corr()"
      ],
      "metadata": {
        "id": "cmitJTTnfhhm",
        "outputId": "fcb5d218-ea1a-4a40-b32b-b1ac8579cb67",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        }
      },
      "execution_count": 61,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-61-549a9badf061>:1: FutureWarning: The default value of numeric_only in DataFrame.corr is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning.\n",
            "  aapl.corr()\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                Open      High       Low     Close  Adj Close    Volume  \\\n",
              "Open        1.000000  0.992154  0.991682  0.977003   0.976693 -0.081043   \n",
              "High        0.992154  1.000000  0.992645  0.990535   0.990102 -0.049436   \n",
              "Low         0.991682  0.992645  1.000000  0.991665   0.991615 -0.126822   \n",
              "Close       0.977003  0.990535  0.991665  1.000000   0.999882 -0.089830   \n",
              "Adj Close   0.976693  0.990102  0.991615  0.999882   1.000000 -0.094738   \n",
              "Volume     -0.081043 -0.049436 -0.126822 -0.089830  -0.094738  1.000000   \n",
              "Market Cap  0.234814  0.263423  0.187170  0.218601   0.213563  0.947355   \n",
              "MA50        0.404927  0.419157  0.370321  0.379224   0.369884  0.440725   \n",
              "MA200       0.404927  0.419157  0.370321  0.379224   0.369884  0.440725   \n",
              "Returns    -0.077002  0.004500  0.012110  0.106319   0.108005 -0.074883   \n",
              "\n",
              "            Market Cap      MA50     MA200   Returns  \n",
              "Open          0.234814  0.404927  0.404927 -0.077002  \n",
              "High          0.263423  0.419157  0.419157  0.004500  \n",
              "Low           0.187170  0.370321  0.370321  0.012110  \n",
              "Close         0.218601  0.379224  0.379224  0.106319  \n",
              "Adj Close     0.213563  0.369884  0.369884  0.108005  \n",
              "Volume        0.947355  0.440725  0.440725 -0.074883  \n",
              "Market Cap    1.000000  0.548997  0.548997 -0.098775  \n",
              "MA50          0.548997  1.000000  1.000000 -0.130187  \n",
              "MA200         0.548997  1.000000  1.000000 -0.130187  \n",
              "Returns      -0.098775 -0.130187 -0.130187  1.000000  "
            ],
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              "      <th></th>\n",
              "      <th>Open</th>\n",
              "      <th>High</th>\n",
              "      <th>Low</th>\n",
              "      <th>Close</th>\n",
              "      <th>Adj Close</th>\n",
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              "      <th>Open</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.992154</td>\n",
              "      <td>0.991682</td>\n",
              "      <td>0.977003</td>\n",
              "      <td>0.976693</td>\n",
              "      <td>-0.081043</td>\n",
              "      <td>0.234814</td>\n",
              "      <td>0.404927</td>\n",
              "      <td>0.404927</td>\n",
              "      <td>-0.077002</td>\n",
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              "      <th>High</th>\n",
              "      <td>0.992154</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.992645</td>\n",
              "      <td>0.990535</td>\n",
              "      <td>0.990102</td>\n",
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              "      <td>0.419157</td>\n",
              "      <td>0.004500</td>\n",
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              "      <th>Low</th>\n",
              "      <td>0.991682</td>\n",
              "      <td>0.992645</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.991665</td>\n",
              "      <td>0.991615</td>\n",
              "      <td>-0.126822</td>\n",
              "      <td>0.187170</td>\n",
              "      <td>0.370321</td>\n",
              "      <td>0.370321</td>\n",
              "      <td>0.012110</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Close</th>\n",
              "      <td>0.977003</td>\n",
              "      <td>0.990535</td>\n",
              "      <td>0.991665</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.999882</td>\n",
              "      <td>-0.089830</td>\n",
              "      <td>0.218601</td>\n",
              "      <td>0.379224</td>\n",
              "      <td>0.379224</td>\n",
              "      <td>0.106319</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Adj Close</th>\n",
              "      <td>0.976693</td>\n",
              "      <td>0.990102</td>\n",
              "      <td>0.991615</td>\n",
              "      <td>0.999882</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.094738</td>\n",
              "      <td>0.213563</td>\n",
              "      <td>0.369884</td>\n",
              "      <td>0.369884</td>\n",
              "      <td>0.108005</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Volume</th>\n",
              "      <td>-0.081043</td>\n",
              "      <td>-0.049436</td>\n",
              "      <td>-0.126822</td>\n",
              "      <td>-0.089830</td>\n",
              "      <td>-0.094738</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.947355</td>\n",
              "      <td>0.440725</td>\n",
              "      <td>0.440725</td>\n",
              "      <td>-0.074883</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Market Cap</th>\n",
              "      <td>0.234814</td>\n",
              "      <td>0.263423</td>\n",
              "      <td>0.187170</td>\n",
              "      <td>0.218601</td>\n",
              "      <td>0.213563</td>\n",
              "      <td>0.947355</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.548997</td>\n",
              "      <td>0.548997</td>\n",
              "      <td>-0.098775</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>MA50</th>\n",
              "      <td>0.404927</td>\n",
              "      <td>0.419157</td>\n",
              "      <td>0.370321</td>\n",
              "      <td>0.379224</td>\n",
              "      <td>0.369884</td>\n",
              "      <td>0.440725</td>\n",
              "      <td>0.548997</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.130187</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>MA200</th>\n",
              "      <td>0.404927</td>\n",
              "      <td>0.419157</td>\n",
              "      <td>0.370321</td>\n",
              "      <td>0.379224</td>\n",
              "      <td>0.369884</td>\n",
              "      <td>0.440725</td>\n",
              "      <td>0.548997</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.130187</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Returns</th>\n",
              "      <td>-0.077002</td>\n",
              "      <td>0.004500</td>\n",
              "      <td>0.012110</td>\n",
              "      <td>0.106319</td>\n",
              "      <td>0.108005</td>\n",
              "      <td>-0.074883</td>\n",
              "      <td>-0.098775</td>\n",
              "      <td>-0.130187</td>\n",
              "      <td>-0.130187</td>\n",
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            ]
          },
          "metadata": {},
          "execution_count": 61
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(aapl.corr())"
      ],
      "metadata": {
        "id": "sRN5SCIVflqS",
        "outputId": "b9539255-cbc2-4aa7-b315-f63652e90265",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": 62,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "                Open      High       Low     Close  Adj Close    Volume  \\\n",
            "Open        1.000000  0.992154  0.991682  0.977003   0.976693 -0.081043   \n",
            "High        0.992154  1.000000  0.992645  0.990535   0.990102 -0.049436   \n",
            "Low         0.991682  0.992645  1.000000  0.991665   0.991615 -0.126822   \n",
            "Close       0.977003  0.990535  0.991665  1.000000   0.999882 -0.089830   \n",
            "Adj Close   0.976693  0.990102  0.991615  0.999882   1.000000 -0.094738   \n",
            "Volume     -0.081043 -0.049436 -0.126822 -0.089830  -0.094738  1.000000   \n",
            "Market Cap  0.234814  0.263423  0.187170  0.218601   0.213563  0.947355   \n",
            "MA50        0.404927  0.419157  0.370321  0.379224   0.369884  0.440725   \n",
            "MA200       0.404927  0.419157  0.370321  0.379224   0.369884  0.440725   \n",
            "Returns    -0.077002  0.004500  0.012110  0.106319   0.108005 -0.074883   \n",
            "\n",
            "            Market Cap      MA50     MA200   Returns  \n",
            "Open          0.234814  0.404927  0.404927 -0.077002  \n",
            "High          0.263423  0.419157  0.419157  0.004500  \n",
            "Low           0.187170  0.370321  0.370321  0.012110  \n",
            "Close         0.218601  0.379224  0.379224  0.106319  \n",
            "Adj Close     0.213563  0.369884  0.369884  0.108005  \n",
            "Volume        0.947355  0.440725  0.440725 -0.074883  \n",
            "Market Cap    1.000000  0.548997  0.548997 -0.098775  \n",
            "MA50          0.548997  1.000000  1.000000 -0.130187  \n",
            "MA200         0.548997  1.000000  1.000000 -0.130187  \n",
            "Returns      -0.098775 -0.130187 -0.130187  1.000000  \n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-62-f8ecaf2385d8>:1: FutureWarning: The default value of numeric_only in DataFrame.corr is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning.\n",
            "  print(aapl.corr())\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import seaborn\n",
        "\n",
        "seaborn.heatmap(aapl.corr())"
      ],
      "metadata": {
        "id": "LqxtobbxgvjO",
        "outputId": "7a654d02-64df-4d88-b7ac-572f13567c50",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 575
        }
      },
      "execution_count": 65,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-65-e2333e336341>:3: FutureWarning: The default value of numeric_only in DataFrame.corr is deprecated. In a future version, it will default to False. Select only valid columns or specify the value of numeric_only to silence this warning.\n",
            "  seaborn.heatmap(aapl.corr())\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<Axes: >"
            ]
          },
          "metadata": {},
          "execution_count": 65
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    }
  ]
}