Lab6 - Polynomial Regression - ML.ipynb

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      "cell_type": "markdown",
      "source": [
        "# Polynomial Regression"
      ],
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        "id": "fXT_Jf4xm_TV"
      }
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        "id": "Yr5s0Qf1kURB"
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      "source": [
        "# Usual imports\n",
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "\n",
        "random_state = 42"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Dataset preparation"
      ],
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        "id": "FGeFZ_T0ndEX"
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    {
      "cell_type": "code",
      "source": [
        "# Load the dataset\n",
        "df = pd.read_csv('power_demand_vs_temperature.csv', index_col = 0)\n",
        "\n",
        "# And show the first five rows\n",
        "df.head()"
      ],
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              "              demand  temp\n",
              "date                      \n",
              "2015-01-01  1.736065   1.7\n",
              "2015-01-02  1.831672   2.2\n",
              "2015-01-03  1.714934  14.4\n",
              "2015-01-04  1.628577  15.6\n",
              "2015-01-05  2.045394   0.0"
            ],
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>demand</th>\n",
              "      <th>temp</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>date</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2015-01-01</th>\n",
              "      <td>1.736065</td>\n",
              "      <td>1.7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-01-02</th>\n",
              "      <td>1.831672</td>\n",
              "      <td>2.2</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-01-03</th>\n",
              "      <td>1.714934</td>\n",
              "      <td>14.4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-01-04</th>\n",
              "      <td>1.628577</td>\n",
              "      <td>15.6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2015-01-05</th>\n",
              "      <td>2.045394</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
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              "                                                     [key], {});\n",
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              "\n",
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              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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              "  "
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      "cell_type": "markdown",
      "source": [
        "As we can see, the target is influenced only by a single feature."
      ],
      "metadata": {
        "id": "6zFLzeuioRj_"
      }
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      "cell_type": "code",
      "source": [
        "# Show a quick description of the dataset\n",
        "df.describe(include = 'all')"
      ],
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          "height": 300
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      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            demand         temp\n",
              "count  1096.000000  1096.000000\n",
              "mean      1.831796    16.927737\n",
              "std       0.329434    10.791581\n",
              "min       1.316033   -15.000000\n",
              "25%       1.581654     8.900000\n",
              "50%       1.731479    18.900000\n",
              "75%       2.024869    26.100000\n",
              "max       2.804025    33.900000"
            ],
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              "      <th>demand</th>\n",
              "      <th>temp</th>\n",
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              "  <tbody>\n",
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              "      <th>count</th>\n",
              "      <td>1096.000000</td>\n",
              "      <td>1096.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>1.831796</td>\n",
              "      <td>16.927737</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>0.329434</td>\n",
              "      <td>10.791581</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>1.316033</td>\n",
              "      <td>-15.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>1.581654</td>\n",
              "      <td>8.900000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>1.731479</td>\n",
              "      <td>18.900000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>2.024869</td>\n",
              "      <td>26.100000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>2.804025</td>\n",
              "      <td>33.900000</td>\n",
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              "  </tbody>\n",
              "</table>\n",
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              "                                                     [key], {});\n",
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              "\n",
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              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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      "source": [
        "# Check for null rows\n",
        "\n",
        "print(f\"The dataframe has {df.shape[0]-df.dropna().shape[0]} invalid rows\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
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        "outputId": "4545ba0f-fa5c-4258-eeed-07abaae08943"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "The dataframe has 0 invalid rows\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Create X and y\n",
        "X = df.drop('demand', axis=1)\n",
        "y = df['demand']\n",
        "\n",
        "print(f\"X has shape{X.shape}\")\n",
        "print(f\"Y has shape{y.shape}\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "52NYuA7ioFPQ",
        "outputId": "72ac7523-7842-4bac-d85c-c104367bb68b"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "X has shape(1096, 1)\n",
            "Y has shape(1096,)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Plot the distribution\n",
        "\n",
        "import warnings\n",
        "warnings.filterwarnings(\"ignore\")\n",
        "\n",
        "plt.scatter(X,y)\n",
        "plt.xlabel(\"Temperature\");\n",
        "plt.ylabel(\"Demand\");\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 449
        },
        "id": "W6Sx3eQroazL",
        "outputId": "9a40bffa-7654-4879-ac4f-d9ef248f5853"
      },
      "execution_count": 20,
      "outputs": [
        {
          "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": [
        "Split the dataset"
      ],
      "metadata": {
        "id": "ZxG4X8m8omBN"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.model_selection import train_test_split\n",
        "X_train, X_test, y_train, y_test = train_test_split(X,y,random_state=random_state, train_size=0.7)\n",
        "print('Training set and test set have {} and {} elements respectively'.format(X_train.shape[0],X_test.shape[0]))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DfPoME5DoonW",
        "outputId": "45535f06-2452-4df2-d595-2b3696e7fd32"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Training set and test set have 767 and 329 elements respectively\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Create an evaluation function to compute, print and return the metrics: rmse, r2, f-statistic, and p-value.\n"
      ],
      "metadata": {
        "id": "IgxhyycQotsZ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import scipy.stats\n",
        "\n",
        "# Computation of F-statistic and p-value for the regression\n",
        "# http://facweb.cs.depaul.edu/sjost/csc423/documents/f-test-reg.htm\n",
        "def f_test(y_true, y_pred, n_var, n_obs, sn=.95):\n",
        "    y_true = np.array(y_true)\n",
        "    y_pred = np.array(y_pred)\n",
        "    n = n_obs\n",
        "    p = n_var+1 # number of regression parameters (coefficients + intercept)\n",
        "    y_true_m = np.mean(y_true)\n",
        "    SSM = np.sum((y_pred-y_true_m)**2)\n",
        "    SST = np.sum((y_true-y_true_m)**2)\n",
        "    SSE = np.sum((y_true-y_pred)**2)\n",
        "    DFT = n - 1\n",
        "    DFM = p - 1 # degrees of freedom for model - numerator\n",
        "    DFE = n - p # degrees of freedom for error - denominator\n",
        "    DFT = n - 1\n",
        "    MSM = SSM / DFM\n",
        "    MSE = SSE / DFE \n",
        "    MST = SST / DFT\n",
        "    F = MSM / MSE\n",
        "    # f = np.var(x, ddof=1)/np.var(y, ddof=1) #calculate F test statistic \n",
        "    p = 1-scipy.stats.f.cdf(F, DFM, DFE) #find p-value of F test statistic \n",
        "    return F, p"
      ],
      "metadata": {
        "id": "Swlw-nWwo1uS"
      },
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "And a function which prints the evaluations above."
      ],
      "metadata": {
        "id": "HNS-ALuBo8-B"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.metrics import mean_squared_error, r2_score\n",
        "\n",
        "def print_eval(X, y, model):\n",
        "    pred = model.predict(X)\n",
        "    F, p = f_test(y, pred, X.shape[1], X.shape[0])\n",
        "    print(\" Mean squared error: \\t{:.5}\".format(mean_squared_error(y,pred)))\n",
        "    print(\" r2 score: \\t\\t{:.5}\".format(r2_score(y,pred)))\n",
        "    print(\" f-statistic: \\t\\t{:.5}\".format(F))\n",
        "    print(\" p-value: \\t\\t{:.5}\".format(p))\n",
        "    return mean_squared_error(pred, y), r2_score(pred, y), F, p"
      ],
      "metadata": {
        "id": "OEHCV7bbpAgO"
      },
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## First Experiment:\n",
        "\n",
        "*Linear model*"
      ],
      "metadata": {
        "id": "fo_glG2IpMZ4"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.linear_model import LinearRegression\n",
        "\n",
        "lmodel = LinearRegression()\n",
        "lmodel.fit(X.temp.values.reshape(-1,1), y)\n",
        "lin = print_eval(X_test, y_test, lmodel)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "C2afTi8CpTBH",
        "outputId": "aa99d346-2c71-4dbd-d6d0-aeb7f9bdea77"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            " Mean squared error: \t0.10016\n",
            " r2 score: \t\t0.1803\n",
            " f-statistic: \t\t53.273\n",
            " p-value: \t\t2.2197e-12\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Visualize the prediction of the model\n",
        "\n",
        "lpred = lmodel.predict(np.arange(min(X.temp), max(X.temp)).reshape(-1,1))\n",
        "plt.plot(np.arange(min(X.temp), max(X.temp)),lpred, label = \"lin\", color = \"red\")\n",
        "plt.legend()\n",
        "plt.scatter(X,y)\n",
        "plt.show();"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 430
        },
        "id": "4LOAdvMzpfBm",
        "outputId": "1870d521-07db-4894-94ef-e001dab620d0"
      },
      "execution_count": 19,
      "outputs": [
        {
          "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": [
        "Clearly, it does not represent well the distribution."
      ],
      "metadata": {
        "id": "8GwV4ZjUprXm"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Second Experiment:\n",
        "\n",
        "*Polynomial Regression*\n",
        "\n",
        "Polynomial degree = 2"
      ],
      "metadata": {
        "id": "jOWpWweypvcc"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.preprocessing import PolynomialFeatures\n",
        "\n",
        "polFea = PolynomialFeatures(2,include_bias=False)\n",
        "print(\"Polynomial degree = 2\")\n",
        "X_poly = polFea.fit_transform(X_train.values) #.reshape(-1,1))\n",
        "model = LinearRegression()\n",
        "model.fit(X_poly, y_train);"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VujIS-ddp5z2",
        "outputId": "6caa21bf-aec0-42b1-8b99-67f8ba40287b"
      },
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Polynomial degree = 2\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pol = print_eval(polFea.transform(X_test), y_test, model)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Z8Q5LnDUqSOV",
        "outputId": "c2a01530-d597-4b31-de21-877b47aa0f34"
      },
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            " Mean squared error: \t0.033456\n",
            " r2 score: \t\t0.72619\n",
            " f-statistic: \t\t384.89\n",
            " p-value: \t\t1.1102e-16\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Visualize the prediction\n",
        "\n",
        "pred = model.predict(polFea.transform((np.arange(min(X.temp), max(X.temp))).reshape(-1,1)))\n",
        "plt.plot(np.arange(min(X.temp), max(X.temp)),pred, label = \"poly\",color=\"red\")\n",
        "plt.legend()\n",
        "plt.scatter(X,y)\n",
        "plt.plot();"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 430
        },
        "id": "Mx1H9axXqUhL",
        "outputId": "85f332c6-ebac-493b-8f32-5c32c6e510a4"
      },
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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Hssdr18qUWQmCIAhCC75uTmY7lqW68XKFnBFjMW4cUL8+8PgxsGOHpa0hCIIgrB0z+gSW6sbLFXJGjIWjIzBrluzxV18B1l+kRBAEQViQzELTtxKJ7N0UO6eG4ty8PlbriADkjBiXd98F3N2BGzeAI0csbQ1BEARhxZgykZTND5nTv6VFu/FyhZwRYyISAe+8I3u8apVlbSEIgiCsGl29ZAyBgfXmh6iDnBFjM2sWYG8PnDoFXLpkaWsIgiAIK0Wxm29th5wRYxMQAIwZI3tM0RGCIAhCC4NCxHinRxCMHcBgpd9tpccNOSOmgC3z/fNP4P59y9pCEARBWC3Rien48UwKjO0zMADS80pxISXbuDs2EeSMmIK2bYEBAwCplOThCYIgCLVwkYM3FGuUflcHOSOm4sMPZf/+8guQlWVZWwiCIAirg48cvL5Yo/S7OsgZMRV9+wLt2gHFxcCGDZa2hiAIgrAyMvJKTLp/oQDo2NjLpMcwFuSMmAqBoCo68t13QKlthMoIgiAI85BdZNrWIVIGiH+QY9JjGAtyRkzJa68BjRoBT58CW7da2hqCIAjCivCuY/reNJQzQgAODsCcObLHX38tS2glCIIgCAB+7qZ3RmpkzkhUVBQ6deoEd3d3+Pn5YdSoUbh9+7bO7XJzcxEREQGxWAwnJye0aNEChw8f1ttom+LttwFPT+DOHWD/fktbQxAEQZgJiZRBbHIW9iU8QmxyVnXNDxOW0bBy8J2DvE13ECNiz2fw6dOnERERgU6dOqGyshKffPIJBgwYgKSkJLi5uandpry8HP3794efnx/+/PNPNGjQAA8ePICnp6cx7Ld+6tQBpk8HoqJkImijRlnaIoIgCMLERCemY8mBJKVqGbHIGYuGB8sb1j01UaM8Vj/NluTgBQyjf3vZZ8+ewc/PD6dPn0aPHj3Ujtm4cSNWrVqFW7duwcHBQa/j5OfnQyQSIS8vDx4eHvqaaznS04HAQKC8HIiJAbp2tbRFBEEQhImITkzH9O2XqwU+WLdgdr8WCPR1xaXUbGyLSzP68VWdHkvCdf7mFRlRJS8vDwDg7a05DLR//36EhYUhIiIC+/btQ926dTFu3DjMmzcPdnZ2arcpKytDWVmVx5ifn2+ImZZHLAYmTAB+/lkWHdm719IWEQRBECZAm5AZ+9zqY3eMdjyhAJjSLQh9WtXD04JS+LnLlmZsJSLConcCq1QqxezZsxEeHo6QkBCN4+7fv48///wTEokEhw8fxoIFC/D111/jiy++0LhNVFQURCKR/C8gIEBfM62H99+X/btvH3DrlmVtIQiCIEyCOYTMFGEY4KezKcgrKcfIdg0Q1tTH5hwRwABnJCIiAomJidi1a5fWcVKpFH5+fvjxxx/RsWNHvPHGG/j000+xceNGjdvMnz8feXl58r+HDx/qa6b10Lo1MHKk7JuzYoWlrSEIgiBMgLlLadloiy01xVOHXs5IZGQkDh48iJMnT6Jhw4Zax4rFYrRo0UJpSaZ169bIyMhAebl6wRcnJyd4eHgo/dUI5s+X/bt9O/DggWVtIQiCIIyOrxm0Q1SxtaZ46uDljDAMg8jISOzduxcnTpxAUFCQzm3Cw8Nx7949SBU0Nu7cuQOxWAxHR0f+FtsyXbrIZOIrK4GvvrK0NQRBEISxsWBwQjEqo7Os2Mrg5YxERERg+/bt2LFjB9zd3ZGRkYGMjAyUlFTp60+cOBHz2QgAgOnTpyM7OxuzZs3CnTt3cOjQISxbtgwRERHGexe2xCefyP796SfgyRPL2kIQBEEYlcwi05TrcoEVOItOTEe3FScwdlMcZu1KwNhNcei24gSiE9MtZpsueDkjGzZsQF5eHnr16gWxWCz/+/333+Vj0tLSkJ5e9YYDAgLw999/4+LFi3jxxRfx3nvvYdasWfj444+N9y5sid69ZRGS0lJgzRpLW0MQBEEYEUsonioKnLFlxapJtBl5pZi+/bLVOiQG6YyYC5vXGVFl/35ZMqu7O5CWJlNoJQiCIGweiZRBtxUnkJFXapYVGwFkK0Nz+jVHI29XLD10U2MDPgEAf5Ezzs3rY7aKG67zN/WmsQTDhgEhIUBBAbB+vaWtIQiCIIyEnVCARcODAVSJnJkSkasDPF0dsPrYXcz546rWTsDWnOhKzoglEAqrKmvWrAGKiixqDkEQBGE8BoWIsWF8B/iLlJdsxCJnfD+uPXZODcXaMe0wo2dTvfa/YGhrrB3TDnP6tUBecQVyiyt4bW+NnXwNUmAlDOD114EFC4D792XJrLNmWdoigiAIwkgMChGjf7A/LqRka1RG/bngPq99ssssk8NllazdVpzQaynIGjv5UmTEUtjbA/PmyR6vWiXrW0MQBEHUaBRLbrO0LKmowrowC4a2xoWUbKw+eoe30qs1d/KlyIglmTQJWLwYePQI2LYNmDLF0hYRBEEQRiA6MR2L9ychI7/KYfB0cQAE4L2sAsgiIiPairH00E295OatvZMvRUYsiZMT8MEHssfLlwMSiWXtIQiCIHRSXinFz2fvY+G+RPx89j7KK6VKr0cnpmPa9stKjggA5Jbwz+9gKSmvxA9nUvTue+MvcsaG8R2sopOvOqi019IUFgKNGwPZ2cCuXcAbb1jaIoIgCEIDUYeTsOlsChQFTYUCYGr3IMwfEgyJlEHHL47q7XQYEzcnO3wxqg38PSzXyZdKe22FOnWqkleXLZM10iMIgiCsjqjDSfjhjLIjAgBSBvjhTAqiDich7n6WVTgiAOBoJ8SItvVtopMvOSPWQGSkzCm5dg04fNjS1hAEQRAqlFdKselsitYxm86mIOZuppks0k1OcYVVaoqog5wRa8DbG5g+Xfb4yy8pOkIQBGFlbItNrRYRUUXKAFf/yzWLPVyxRk0RdZAzYi3MmSNLaI2NBU6ftrQ1BEEQhAIPsos5jXN1tK5p1Ro1RdRhXWetNiMWV5X2LltmWVsIgiAIJRp7u3Ia1znIF56uDia2RjfWrCmiDnJGrIkPPwTs7ICjR4GLFy1tDUEQBPGcCWGB0JUDKhQAk7oGYvnoNuYxSgsMrFdTRB3kjFgTgYHAm2/KHn/+uUVNIQiCIKpwtBeib2s/rWP6tvaDo70Qg0LE2Di+A/w9nJRe9/dwUupNE9nb0N40zfXa3hohBVZr47PPgO3bgYMHgUuXgJdesrRFBEEQtR6JlEHio3ytY+If5GDvlUfw93BG/2B/9GlVD9tiU/EguxiNvV0xISwQjvZVMYDY5CysO5nMyw5PVwel3jSaEABYciAJ/YP9bSI6Qs6ItdG8uSw6sm0bsGQJcOCApS0iCIKo9VxIydapfppdVIE5vycAgDxvRFFz5KdzKVg0PFiugto5yBtikTMvVdUKiZSTPQyA9LxSXEjJRtjPXwOtWgHjxsn6olkhtExjjXz2GSAUyqIj8fGWtoYgCKLWw7dENre4uvR7Rl4ppm+/jOjEdACAnVCAEW35ybMXlUkQdz+Lsz3F1xKBFStkvdASE3kdy5yQM2KNtGhRlTuyZIllbSEIgiCMUiLLypQsOZAEiZSBRMpg/9V03vuJTc7ibM+LW74DpFJgxAigXTvexzIX5IxYK2x05MABio4QBEFYmM5B3kYp2VVcPuGy9KNpL1zs6VCUDt8De2T/WbxYj+OYD3JGrJUWLWTrewBFRwiCIGoYRxLTce7eM722DWviy2nc1FO/QcAwwKhRQPv2eh3LXJAzYs0oRkcuX7a0NQRBELWWCynZRm2AtzX2AdbzrKQBACd7IUKb+ui0p/mzBxiY+FzN28qjIgA5I9ZNy5bA2LGyxxQdIQiCsBjW0uOlXCKFRMrotGfWv7sgBIPHfQYDbduayTr9IWfE2mGjI/v3U3SEIAjCQlhLjxeGkTXt02ZPi2epGHLrHADg2dyPzWWaQZAzYu20alUVHSFVVoIgCIvAaoJYg3zYg+xidGzspVGe/r0YWVTkSMuuaD2wm3mN0xNyRmwBNjqybx9w5YqlrSEIgqh12AkFWDQ8WK9tRS7GbZzX2NsV8Q9yIGWqv9byWSqG3ZZFRdaEj0P8gxyjHttUkDNiC7RqBYwZI3tMuSMEQRAWYVCIGO/0CNLZME+VvBLjJb4KBLKmfZpyRmad2wEAONiyG27X1TzO2iBnxFZYsED2LaToCEEQhEWITkzHj2dS1EYkzIWjnRB2QoHanJHWT+9jyJ1/IYUAa8Nly/vWkuuiC3JGbAXKHSEIgrAYEimDJQeSYEE/BABQVilFXHKW2hyWWTE7AQCHWnXDvbqNIRY5o3OQt2UM5Qk5I7bEZ5/JoiN//UXREYIgCDOiv1qq8Ym9n6mUwyIAEPzkPgbdiYUUAnz7PCoyplMjHLz2GLHJWZBYMpzDAXJGbInWratyRyg6QhAEYTasK/dCFg8ZFCLGhvEd4C9yxqyY57kirbsjs1FTiFwdsPrYHczalYCxm+LQbcUJeYM+a4ScEVuDzR356y8gIcHS1hAEQdgkEimD2OQs7Et4xClyYE25F2FNfeSPB4WIcW6AFwbejQMjECD3/Y+Rw6FjsLVhb2kDCJ6w0ZGdO4FFi2QJrQRBEARnohPTseRAktKyi1jkjEXDgzEoRKx2G1bXw9KrHV6uDght4qP0nN3nsipLZsxYbHjqCKB6FIeBLJ6y5EAS+gf7w45vSZCJ4RUZiYqKQqdOneDu7g4/Pz+MGjUKt2/f5rz9rl27IBAIMGrUKL52EoosWlSlyhoXZ2lrCIIgbIboxHRM3365Wv6HrsiBJl0PcxM1uo2yIxEfL5sLhEJc/b+ZWvNaFDsGWxu8nJHTp08jIiICcXFxOHr0KCoqKjBgwAAUFRXp3DY1NRUffPABunfvrrexxHNatgQmT5Y9/vRTi5pCEARhK2iriGGfW3IgSe2SjaVzRsQiZ2wc36F65IZtgjduHNLqBnDal6Xfizp4LdNER0cr/X/Lli3w8/NDfHw8evTooXE7iUSCN998E0uWLMHZs2eRm5url7GEAgsXAtu3AydOAMePA337WtoigiAIq0ZXRYxi5EAxLwOwbM7IjF5N8f6AltWXVi5eBA4elEXKFyyAnx03G60p/4XFoATWvLw8AIC3t/Y65s8//xx+fn6YMmUKp/2WlZUhPz9f6Y9QoXFj4N13ZY8/+UTWPYkgCILQCNeIwJHE9GpJrZ2DvOHpalxZd650b15XfY7HJ5/I/h0/HmjRQmf/HAFgtdojejsjUqkUs2fPRnh4OEJCQjSOO3fuHH7++Wds2rSJ876joqIgEonkfwEB3EJPtY5PPgFcXYELF4ADByxtDUEQhFXDNSKwNfaB1ZTDanQejh8Hjh0DHBzkbUJUtUcUYf+/aHiw1SWvAgY4IxEREUhMTMSuXbs0jikoKMCECROwadMm+Pr6ct73/PnzkZeXJ/97+PChvmbWbPz9gVmzZI8//RSQSi1rD0EQhBXDt/NuRl4ppm2/jLXH7mD10dvVymXNwYi24urOA8NURUXefRcIDJS/pKg9ooi/yBkb1OWcWAkChuEf34+MjMS+fftw5swZBAUFaRyXkJCA9u3bw87OTv6c9PmEKRQKcfv2bTRt2lTn8fLz8yESiZCXlwcPDw++5tZscnKAoCAgLw/47Tdg3DhLW0QQBGG1sNU0ACwu7c4FscgZ5+b1UXZI9u4FRo8G3NyA5GSgXr1q20mkDC6kZONpQSn83GXRFUtERLjO37wiIwzDIDIyEnv37sWJEye0OiIA0KpVK1y/fh0JCQnyvxEjRqB3795ISEig5Rdj4OUFfPSR7PHChUCF+T13giAIW0FT5MBaqVaKK5HIWoMAwOzZah0RQLZkE9bUByPbNUBYUx+rXJpRhFc1TUREBHbs2IF9+/bB3d0dGRkZAACRSAQXFxcAwMSJE9GgQQNERUXB2dm5Wj6Jp6cnAGjNMyF48t57wNq1Mg9582bgnXcsbRFBEITVMihEjP7B/riQko0jienYGvvA0iZpRSnxdvt2IClJdiP6wQeWM8rI8IqMbNiwAXl5eejVqxfEYrH87/fff5ePSUtLQ3q6dcrN1ljq1KnSG/n8c6CkxLL2EARB2AgezpapkOGDPPG2rEwmegkAH38MPL+5rwnolTNibihnhANlZUDz5sDDh8DXXwNz51raIoIgCKtEnRy8KZnesym2xqWiqEzCazsBZImn8pyR776TRcLFYuDePVk1pZVjkpwRwopxcqpS4ouKAgoKLGoOQRCENaJJDt5UeLk6YE7/FnCw4zfdVivFLSwEvvhC9uTChTbhiPCBnJGaxMSJQIsWQGYmsGaNpa0hCIKwKrTJwZuK119qiPgHObzLgquV4q5ZAzx9CjRtCnAUELUlqGtvTcLeXpYzMmYM8NVXwIwZgI+P7u0IgiBqAbrk4E3Bb+cfoqic2/JMZO+maF7PvXopblYWsGqV7PHSpTKhsxoGRUZqGq+9BrRtC+TnAytXWtoagiAIq8ESDeIKyyqxPS6N09jwZnXVl+KuWCG7prdtC7zxhokstSzkjNQ0hELgyy9lj7/7Dnj82LL2EARBWAnW2CCOxcvVQb3s+6NHsms5ILu2C2vmtF0z31VtZ8gQoGtXWYkvm/BEEARRy2kX4GlpEzRSWiFB3P0s7Et4pNykb+lSoLQUCA+XXdvVIJEyiE1Ws60NQaW9KliLhK7BnD4N9OoF2NkBN24ALVta2iKCIAiL8vPZ+1h66KalzeCEWOSMFW1d0GNkT6CyEjhzBujevdo4dWXKYpEzFg0Ptoo+NFznb0pgVcDaP1Re9OwJDBsGHDwIzJ8P7NljaYsIgiAsyoPsYkubwJmMvFLkfLBU5ogMHqzREZm+/XK16qCMvFJM337ZqhvjqULLNM/RVHvOfqiWbiOtFytWyNYX9+4Fzp2ztDUEQRAWpbE3N22OQB8XE1uim1ZP72PkzdMAAMkXX1Z7XVuZMvvckgNJNrNkQ84Iat6HKic4uKoe/cMPZW2nCYIgaikTwgKha9VdKADGdm7MaX8vt6uPnVND8f249vD3cDKChVXMP7kZALC/dQ9cEDWq9rquMmUGaprsWTHkjKDmfahKLFkiazMdFwf873+WtoYgCMJiONoLMbW79m7zQ9qI4VvHCQIOTsuKV9sirKkPhrxYHzEf98XOqaEY36W648CXHvfj0SP1CsqF9ljVY6LakmSuZcqWKGfWB3JGUPM+VCXE4qrOjh9/DJSXW9YegiAICzJ/SDDe7RFULUIiEACujnY4eC0d7+++qjOQPLV7EBztq6ZQO6EAYU19MPTF+gbZJ5RK8MnJXwAAv3Ychoee/sgsKKsWmedapmzN5cyKkDOCmvehVuODD4B69YDkZGDjRktbQxAEYVHmDwnGraWDsWBoa0wMa4xXOzQAwwDFHJVS+wf7Yf6QYLWvdQ7yhlik/1zx6vXjaJX5ALnOdbAuTCZwtvTQTXRbcUIpd5E9jqYAjgCyAgy12iVWCDkjqHkfajXq1JEt1wAyufjcXIuaQxAEYWkc7YWY0r0JFg1/ATHJWZy3EwA4mvQUa4/dUavrYScUYNHwYAgAjXOKJlzLS/D+ue0AgO+6jkGei7v8NdViCvY4rE2qNgIKTfZsAHJGUPM+VLVMmQK0aiXrcbBihaWtIQiCsAr49qth3Y7Vx+5i1q4EjN0UVy1qMShEjHd6BOnMO1HlnQt7UK8wGw88/bGt/VC1x1UsphgUIsaG8R3grxKJqdZkzwYg0TMFapTOiDr27wdGjgScnYE7d4CAAEtbRBAEYRHKK6XYFpuKU3ee4ezdTIP2xfocrAOgSf9DG34FWTi16R24VpRhxsiPcbhVN41jd04NRVjTqiao1izWSaJnejAoRIz+wf5W+6EazPDhQI8eMiW/zz4Dfv3V0hYRBEGYnajDSdh0NgXGUmtgd/Pp3kQUlUnw5WH1UhHamHvuN7hWlCG+fiscbhmudaxqMQWbPGvL0DKNCuyHqrZzoq0jEABffSV7vG0bkJBgUXMIgiDMTdThJPxwxniOiCJZReV4f/dVZBdV8Nqu1dMUvH7tKADgyz5ToGt9x2aLKbRAzkhto1MnYMwYmQDaRx9Z2hqCIAizUV4pxaazKZY2oxrzT22GEAwOtuyGyw1aax3rqam7r41Dzkht5MsvAQcH4OhR4O+/LW0NQRCEyVDsaLv04A2TREQMocf9ePRMuYxyoT1W9pykc3wNitUrQTkjtZEmTYDISGD1aplMfL9+su6+BEEQNYjoxHQs3p+EjHzrFKwUSiWYf0om+761w1CkeekulMgprsCFlGybzxFRhSIjFkDRU1etUTfbPj/7DPD0BK5fl+WPEARB1CCiE9Mxbftlq3VEAOCVxONo/SwVeU5u+K7rGM7b2aQauA4oMmJmTFE+rGmfC4a2hpebk/rKIG9v4JNPZHkjn30GvPaarIcNQRCEjSORMvh4z3VLm6EV1/ISfHBWJnD2rYrAmS4ogZUwCLb2XFVgR1VZzxj7TM8rxYwdVzB2U5xGYR7MnAkEBgKPHpEQGkEQNYa4+1nILeZX0WJupl7Yi3qF2UgT1cO2DsMAAPMHt4Kni4PGbWxeDVwL5IyYCYmUwZID6mvP1SnrGbpPdVRzepydga+/lj1etQpITeV8bIIgCGslloe8uyWoW5iNdy/Iuqiv6DkZ5fYyB6SgtALLX2mjVkq+xqiBa4CcETOhS3KYgSyacSEl22j7VHcMQMXpeflloHdvoLRUlsxKEARh8xi/ZOalxl5G29f7Z7fDtaIMV8QtcUhJaVWgU+K9f7C/0XMOrQHKGTETXBOO+CQm6ZPEpOj0hDX1kYnrrFkDtG8P/PkncOoU0KuX2m2tWXKYIAiCJayJL9adTDbqPi89yDHKftqk35ULnC3t87aSwBlbIaNJDfxoUga6rThRI1uWkDNiJrgmHPFJTDIkiUnJkXnxRWDaNOD774FZs4D4eMBe+atR4/v2EARRYwht6gNPVweryxsRMFIsPvYDhGCw54XeuNywSuDMy9UBYIB9CY/kzodi+a6mfjfs8rutNcZThZZpzETnIG+IRc4aBWv0SUzStU9tVHNkPv8c8PICrl0DfvpJ6SVTJN4SBEGYCjuhAMtHt7G0GdUYdeMUOj6+hSIHZyzvOVnpNQbAmz+fV1twYIqcQ2uDnBETw+p/HLz2GGM6NQJgvMQkO6EAi4YHq92nJjQ6PT4+wJIlsseffQbk5Mjtr+k/AoIgah6DQsTYOL4D/D2cLG0KAMCtrFgucLau6xt46i6Leni5ypJXVaM4ijd7psg5tDZomcaEqFva8FTzxfM3YLmDTXZSPY46dDo906cDP/wA3Lghc0zWrOH1I6hpioAEQdg2g0LE6NOqHrbFpuJBdjGkUgbbz6dZxJaZsb/DrygHqZ5iuH30AdbW94JvHSe8/0eC2vEMZNfsJQeS8NGgVpyOYctiaLyckaioKOzZswe3bt2Ci4sLunbtihUrVqBly5Yat9m0aRO2bt2KxMREAEDHjh2xbNkydO7c2TDLrRxN63t5xRVgAMzp1xyBvm5GSQRVl+yUU1SOpYeUHRSdTo+9vSyZtX9/YN064J138LRcxMkGW/4REARRM1F3Q2gJArMf4a2L+wAAWV8sR+SQEACyEuSM/DKN27E3e9mFmscoYstiaLyckdOnTyMiIgKdOnVCZWUlPvnkEwwYMABJSUlw06DeeerUKYwdOxZdu3aFs7MzVqxYgQEDBuDGjRto0KCBUd6EtaFraUMAYNfFhzg3r4/RqlHshIJqkYmBIdWzsXUer18/YORIYN8+YPZs+H2/g9PxbflHQBBEzUPTDaG5mdOvOd74fDUcpZVgBg1GxxkT5K9xvYnzdnOEWOSMjLxSte9HANnNpi2LoQkYhtH7s3r27Bn8/Pxw+vRp9OjRg9M2EokEXl5eWLduHSZOnMhpm/z8fIhEIuTl5cHDw0Nfc81GbHIWxm6K0zlu59RQ61zaSE4GgoOB8nJI/tqHbkluOn8ExnSsCIIgDEEiZaqVwFoCAYDR6Qn4eutnsk7p169D0ryF/CYxs6AMSw/d1LmfnVNDkVdSjunbLwNQVlFhr7rWWk3Ddf42KGckLy8PAODtzd0bKy4uRkVFhdZtysrKUFZWFZbKz8/X30gLYApNEbPStCkwdy6wfDns3p+LxX8cw7Q/bkAA9T+CmqoISBCE7SGRMtgSk2IUR0Rdjh8fHCorEHHge9l/Zs1CdIUHlqg4SQIBoC0k4OnqII9qq8sPNCTn0JrQ2xmRSqWYPXs2wsPDERISwnm7efPmoX79+ujXr5/GMVFRUVjCVnbYIKbQFDE7n3wC/PorkJyMgcf+wIbxE2rsj4AgiJqBsXJEZvRqgu7N/eTLHhdSspGRV4KP/ryGCh6Vg/8Xvw9Nch6j1Kcuzr4yVe2yka61CcXbPE1iaDXhZlDvZZrp06fjyJEjOHfuHBo2bMhpm+XLl2PlypU4deoUXnzxRY3j1EVGAgICbGaZhg0R2vzSxtatwKRJQJ06wN27kPjVq5E/AoIgbB9j5ohE9m6KDwYqV7CUV0rRcsERnc4DS93CbJzc9C7qlJfgzvLvMEnaWm8nyWqX9DnAdZlGL52RyMhIHDx4ECdPnuTsiHz11VdYvnw5/vnnH62OCAA4OTnBw8ND6c+W0Kb/YVNLG+PHA507A4WFwCefyJNkR7ZrgLCmPtZvP0EQtQK+TUN1U/3ati02lbMjAgAfn96COuUluFK/JZ6MfM2gaI3VLukbEV7OCMMwiIyMxN69e3HixAkEBQVx2m7lypVYunQpoqOj8dJLL+llqK2hq9mRTSxtCIXAt9/KHm/eDMTpTsolCIIwN3ybhuqii5qqlAfZxZy37/DoJl5JPAEAWNTvXZx/kGuQPVa9pG8keOWMREREYMeOHdi3bx/c3d2RkZEBABCJRHBxcQEATJw4EQ0aNEBUVBQAYMWKFVi4cCF27NiBwMBA+TZ16tRBnTp1jPlerI4asb7XpQsweTKwZYtMFO3ixWp9awiCIMyNYuPOu08KjbpvoZprdGNvV07bsv1nAOD3Nv1xTdwCPQyI2fBtE2Kr8JpVNmzYAADopdLVdfPmzZg8eTIAIC0tDUKhUGmb8vJyvPrqq0rbLFq0CIsXL+ZvsY2hTv/D5li5UqY7kpAga6b33nuWtoggiFqMqcXMMhVExlinx9PFQWflCwC8du0YXsy4h3xHV6zqKZOv6BLog/+JHmnMI9TGiLZi27qB1RNezgiXXNdTp04p/T81NZXPIQhrpG5dICpK1tn3s8+AV18F6te3tFUEQdRAFCMe6qLJ5hAzu/ukALHJWcgpkumAcHV6RCUF+OjMrwCAteFjkenmBQAQ2snyCKdvv1xNIkEX+6+m46NBrWu8Q0LxdoIbU6fK8kbOn5dpkOzaZWmLCIKoYaiLeIgVJASMn6iqnnUnk7HuZDLv7ead3gLf4jzc8WmErR2HyZ9/WlCGl9s34NxHTJHa0vuLnBGCG0IhsGED8NJLwO+/A1OmyHrYEARBGAFNEQ+2e+2G8R0gcnG0uKqqJjr8dxPjrv4NAPh04AxU2DnIX2N7y6jmEd59UsDJ6aFqGoJQpH17YOZM2eMZM4DSmv8DIQjC9Ojq5wXIutdm5JVw2t+MXk3g6eKge6CRsJdUYtnf6wDIklYvBigLgXq7OcofK0okhDery2n/taGahpwRgh+ffw6IxcC9e7LEVjMhkTKITc7CvoRHiE3OgoSHCiJBENaNrtJctnttJsfuteFN62L5K20ggDrFEOPz1qV9aJX5ANkuHljea3K11/1FLmq36xzkDbFIu6NB1TQEoQ4PD2D1amDMGGDZMkjGjMUFO2+Tli7rWkcmCMK24boMcSElh9sOBVVaT6asugGABnlPMTtG1t18We+3kOMqUnpdmzNhJxRgRFsxfjiTonH/VE1DECrIs9xbhKNneC94xpzCxWHjMPblRbJuT5D98BYMbQ0vNyejOChc1pEVHRJdmfgEQVgfXJchjt58wmlcpoYcDa5dcjnDMFhydANcK8pwPiAEf4b0rTbkpcaeOHjtsdrrkUTKYP/VdK2HoGoaolajOqmrlrgFBo/F33HnEHr3EgbfjsGRVt0AyEKpM3ZcUdqXvlEMXevIAsjWkfsH+8NOKKAICkHYKOxyhT46HOrwreMkf6yo9VReKcUXh2/yknXXxsC7seiXfBHlQnt8MiBCflOmyIFrGThwTSb26e/hjMUjqq5HXJRja0s1DeWMENWITkxHtxUnMHZTHGbtSsDYTXGYseOK0o8m1bsBNnZ5DQCw8PgmuJVplkpmoxjRidrvAFThuo58ISVbHkFRHa/vsQmCMB/a+nnphQZn42JqttEcEbeyYiw69iMA4Mcuo5HsG6Bzm4z8UkxTuB5xXZ6iahqi1qFpUlfH92GvIdVTDHFhFuac+03jOMVseC6Jp2yy6hGODkRGXgmnTHxjJr1SQi1BGBdN/bz0IbNIfaJrbHKWwftmmR2zA/ULMvHA0x/fhb3Ba9v5e65DImU4L0/VhmoaWqYh5PAVFCqzd8TC/tOwdfciTI4/gP+16Yubfk3UjlWMYmgLN+oj85xdVM45gmKMUCctBxGEaVDM8TiSmI6tsQ/02o+myVvKSA0xT07wk/v4v0v7AQAL+09HmYOTji2UySmuQNz9LIQ28dG6PCWArLlqbaimocgIIUefzpdnmnTEwZbdYM9I8cXf30Og48euLdzIJyoDyH6oYpEzvOtwuxAYI9RJy0EEYVrYHI/Bejj27DVBcfJWjGLml1QabJ9QKsGyv9fBnpHiYMtuON2ko177iU3O0ro8xf5/0fDgGp+8ClBkhFBA38l6ad+30SslHh0f38LYq39jR7vBGsdqumPhG5VR/KGKXBy1jtV1bK7wTag1FVQxRNQG2gV48t6GAbBgaLD895GaWYydF9KQkW+8nItxV/9Gu/Q7KHB0wed9pxqwJ9mVRFMJsn8ti7aSM0LI8eUYYVDlibsvvu4+HouOb8LHJzfjRJNOyPDwrTZOKAA6NvZSuw++URl/lX4V5gh18kmoNVXmOy0REbWFHef1W6L55K/ryC2uMLI1MuoW5uCj07JGeF/1mIin7vr/zsOaVF0jVUuQa+NNBi3TEFUYkIP5a4dhuFy/JTzKi/HFP+vV9tmWMkD8A/WiRVyjMhPDGmPn1FCcm9dHPvmaK9Rp6cx3WiIiahMPsjVX6GnDVI4IAHx24id4lBXhmn8zbGs/RO/9eLo6IFTlhkVRJj6sqU+tckQAckYIBTRloHNBKrTDR4NnoczOHv2SL2L4zTNqx2maqLkuoQwOEav9oWrKxPcXOVcTRtMXS2a+c+3dQVU9RE2hsberpU1QolfyJYy8eRoSgRCfDIyEVGiHjo089drX8tFtap2zoQtapiHkGDqJ3vNthHVhb+D9c79h8bEfEBPYDtkq0siajqFL9IjLUoupQ53GsFFfrGGJiCDMyYSwQHx5+Caswb92LyuSN8Lb0nE4Ev2bAQAEakTOtOHv4YTFI16gJVU1UGTESrAG3Qp2sjVk6t4Y+ipu1g2ET0k+Fh7/Uf68ALIfopRh1L5HYy21mDLUacnMd0svERGEuXG0F2Jq9yBLmwEAmH9yM+oXZCLVU4xVPSbIn2/oWfP1P8wFOSNWgDrF024rTpgkB0Cb02MMFcQKOwfMG/weJAIhRiWdRp97FyCA7M69tFKKN386r/E9mmOpxVAsZSOJIxG1kflDgvFujyCYe0VjZNv68sddUxMw7mo0AODjwTNR6lD1G3u5Q0Netj3JL6P8Lg0IGMZY4rimIz8/HyKRCHl5efDw8DDKPq2lPFJTIzjWEmNOcJoqMVQb26n2odGH+Sd/wbsX9iC9jg9enbkJj6TVy281vUdDPhtzfa7m/v5IpAy6rTihc4no3Lw+tBZN1DjKK6XYFpuKB9nFKC6T4M/L/8lvckzB9F5NsPH0fbiUlSD6l0g0ynuCbe2HYMGAGfIxAgDTejbBhtP3ee27tv1Wuc7ftdIZsZbySHaC0TTpG/NLq8npUYfMQQmGl5ujvFZ/zbE7ALj/+J0rShG7ay68HqdhT+dhmNt7mtpxxn6P1vC5mgr2MwSUPwdTOK4EYU3oatwJyCpUcosrjOKkjGpXH38lPMaiYz/g/+IP4D+Puhj41noUORkvqXbn1NBakd/Fdf6udQmsfFvSmxJzJSXyFRTLyCtFxA7ZuRjZrgEAoKV/Hc4y7QIAXr6e8Ni2BejbB6MvHMQfTbsirtGL1cay73H10dsIb1ZXY4RBVyTCmj5XU0HiSERtRHNEt+qGib0mHE3K4N1OQh1ikTNe+u8GJsUfBADMHzTTqI4IoH9+l7VE9Y1NrXJGrEVBk8VcSYl8BcXUnQvVSpXUzGKsfh4tUbf9ouHBsAsRI+WV8Qj633ZERX+Hwf/3ndJ6qyLrTiZj3clktZGM6MR0LN5/Axn5VaXHilnppv5crenHT+JIRG1C202G6g0TUPX7eP+PBPyV8Fjv42Y+y8WKI99CCAa/t+mPs0Ed9N6XJvTJ76rJ0d9alcDKJxJhDsyVlKiPM6PuXChWqrT0r8NpP88++xzpdXwQlJOO2ed26ByvKuAVnZiOadsvKzkiAJCRXyZvxW3Kz9WcycWqaEo2ru3iSETtQF9tHTuhAK+9FGDQsZt+/zWaZj/Ckzre+LLPFIP2pYq6/jlcqOmih7XKGbG28khdpbT6fmlVMcSZUXcu2IuEJthIhETKoOOLgfh69BwAwNSLf6FN+l2tx1O8yJRXSvHxnutax3+85zrnvhN8P1dL/vgt6QQRhDVgyE1GaBMfeLo66HXcto9vY+qFvQCATwdEIN+Z240XF/SVAKgNooe1yhmxtvJIc+lWsE6PPqg7F3wuEnZCAfp9+Bb+Cu4JO0aKlUfWwkGiXa6Z3f7Xf1N0SjvnFlcgs4Cbcqyuz1UxEhFzLxOL99+wyI+/pt8BEQQXDLl5tBMKsHx0G97HdKyswMoja2HHSPFXcE8ca96F9z76t/bDzqmh+H5c+2rXXX0lAKwtqm8KalXOiCUVNDVhjqREO6EAI9qK8cOZFM7baDsXfC8Sg0LEOL5hHXIGd0PrZ6mYEbsba7uN07n9xVT1fWxUySkuM/hzVbcWqw1TKZ5aW14TQVgKQ28eB4WIsXF8Byzen6QUPfVydUCOhqqbiNjf0TIzDZmuIizp+45edncO8pFfEwaGiI2S32VtUX1TUKucETYSMX375WpfRFMraGrD1EmJEimD/Ve5302z52ZMpwAcvPa4mj36XCT69giBdNMG4M1xeC/uDxxv1lkuqawJN0c7TscRCoR6fa5sYuqxpAz8HJPK6ViqGPvHT7LvBCGDy82jt5sjMvJKEJucJb9GqSacn/moN+If5Oisugl+ch8z4nYDABb2n44clVYWXPF1r+p+zuZ3GYq1RfVNQa1yRgDrLY801pdWHXyraUTP11pXH6vK71DM2NY3wiQcOwb4ay/sdu/GusPfYOCE1ShzcFKzB9nxRndoiL0cMuLDmvogvJkvr8+VbyREE8b+8deGOyCC4IK2m0c8/39WUTnm/HEVgOyaMaKtGPsS0pUiIf4ezlg8Irha1U3PFn5YdjgJCQ9zcTMtW7aELJXgSIuuONwyXG+7/T2M7xBYY1Tf2NQ6ZwSofeWRXCeuiWGN4ePmhDXH7ujU69ArwiQQABs2AOfOITA9DfNO/4rP+6kPhY5oK0bXZr5yISNNeLk6ILSJzIkbFCJGn1b15EqNjb1dMSEsEI72yqlRfATgNGGqH39tuAMiCK5ounlUR3peqdql6Iz8UkzbfhkbFXI1og4nYdPZFHkTvlmxfyDkSTJynN2xsP902bVKD7zdHJCRX6oUqTEG1hrVNya1KoFVkdpUHsl14hoY7I9dF9M4JW3q3aPFxweSTT8BAN6K34+uqQlqh7HLSrqS0KIUWnFHJ6aj56qTWHroJrbGPsDSQzfRc9VJpYRPvgJw6jDlj99cFVYEYSsMChHj3Lw+2Dk1FKvfaAdvN/2qZN7ffRUSKYOow0n44UyVI9Lu8W3M/HcXAGBR/3fxrI6X3rZmF1Vgzu+mqX6zhd5dhlArIyO1Da4hPgjAK19B3wjThVZdkNxuMMYnHMFXh9dg0FvrqpXPscfRlISmKvTDVYGV75KVOky5pFcb7oAIgi/szWNschayi7RX2GmiqEyC07efYdPZquiJS3kpvjn4NewZKfa37oH9wb2MZLFp1J9rclSfnBEbQx81UK4TXGYhtxJZxWUffXJdnhaUYlnvt9AtNQGBuelYdOwHvD/sfY3H0fUD5FOBwjfXgnXUvnq1LTKLyuTHBoDY5CyTXBCsNa+JIAzBGA0wjxgYafjm6G0oVuN/dvInNMl5jMfuvvhMoQmeMTBV9Zsp8wstCS9nJCoqCnv27MGtW7fg4uKCrl27YsWKFWjZsqXW7Xbv3o0FCxYgNTUVzZs3x4oVKzBkyBCDDK+NGCIFzGWCi03O4mSHofkKfu7OKHZ0wdxhc7H7t3l45cZJHG0eimiVpDHF42j7AfKpQOFju6KjFt7cV/68OSSZa/IdEFH7MOQ3Y6xkcwDIK6mKqvS5dwFvJkQDAD4YMtuo4mYsVP3GHV45I6dPn0ZERATi4uJw9OhRVFRUYMCAASgqKtK4zb///ouxY8diypQpuHLlCkaNGoVRo0YhMTHRYONrE8YQwlJce107ph12Tg3FuXl95BcDY+UraJIxZ2GPc6VBa2wIfRUAsOzv9ahbmM3rOCx8KlD4CMCpW4s1pyBZbcprImoufH8zitePtcfuqt1WX1r4uQEAfIpkvWcA4KeXRuLfwHZG2b8mqPpNN7wiI9HR0Ur/37JlC/z8/BAfH48ePXqo3Wbt2rUYNGgQPvzwQwDA0qVLcfToUaxbtw4bN27U0+zaBddlCHcnB6WlBL6TlzHyFbjcASke59vwseh1Px4hT5Kx4si3mPLqIkAg4JUXwacChYsAXN9WdfF296bVziEJkhEEP/j+ZowZBVFHh0ZeOHn7GZZHf4e6xbm45dsYq3pOMsmxFKHqN90YlDOSl5cHAPD21nwHGxsbi7lz5yo9N3DgQPz1118atykrK0NZWVX+Qn5+viFm2jxclyHe/Pm8/Dl1LbZzisqx9JB2R8GQfAVNSaTpahK5FI8zZ+hcHPx1Nvrcv4R37xxHu6Uf8Vru4FODz0UALim9QK0zR4JkBMEPPr+ZvJJyg0vudbHq6F28ef0o+t87jzI7e8wZ/j7K7B1NdryaoP9hLvR2RqRSKWbPno3w8HCEhIRoHJeRkYF69eopPVevXj1kZGRo3CYqKgpLlizR17Qahz4hvvS8UszYcVnnOHUZ3/rkK+gqmWVQPWpQdZx2uOv5BCHffI55RzdB8FWk2v1rsoeNtEzbrv79MqiK6MQmZ3HSK1DnUJAgGUHwg+tvISO/FCujb+nliHRv7guGYXDunu6ct8Y5j/HJ0R8BAF93n4Cbfk30OCI3qPqNH3o7IxEREUhMTMS5c+eMaQ8AYP78+UrRlPz8fAQEGNYS2pYxZYhP0/IC34xtLiWz6iZ5+XFWLQLiT0Nw+jQwaRJw+jRgJ5ODj05Mr1bay6oq8k0YNcShIEEyguAH199CdmGZ3kszZ+9mchpnJ5Vg9cGv4VZRiriAEPzUaZTGsQOC/fBP0lO97GGh6jd+6CV6FhkZiYMHD+LkyZNo2LCh1rH+/v548uSJ0nNPnjyBv7+/xm2cnJzg4eGh9Feb0ZVYaijG6PiYkVdi2DihEPj1V8DdHYiJAVauBCBzRKZtv6zkiABVqorRienyqIwmWGdLImUMcihIkIwg+MH1N+PtZrqlEpYZsX+gw+PbyHd0xftD50Iq1Nz7qkU9/eYcbzcHrH6jenEAoRtezgjDMIiMjMTevXtx4sQJBAUF6dwmLCwMx48fV3ru6NGjCAsL42dpLYZdhgBgMocEMGx5Ibuo3PBxjRsD38oy3LFwIST/xuLjPde17m/+nuuI07H0ouhsGeJQaPsc2P+P6dQIB689VltFRBC1DS6/mUXDg+EvcjGpHS+m38GsmJ0AgIUDpuORyE/r+LCmPnrdAGYXVcDfw5mq3/SAlzMSERGB7du3Y8eOHXB3d0dGRgYyMjJQUlJ1tztx4kTMnz9f/v9Zs2YhOjoaX3/9NW7duoXFixfj0qVLiIysnhdAaEaTFLAxMWR5wbuO+oZ3vMdNmgS8/jpQWYmKN8ZAmp2jdXhOcQX+TeYWpj2SmI4LKdlYMLQ1AO0XR00XEk2fg6erA0SuDlh97A5m7aqSgz58LV1rmbO1oqs821aOQVgeLjLmnYO84emqn8y7LlzKS7H6ucrqwVbd8ZcWlVX2ZiS0iY/eN4CUM6YfAoZhOF8BBBqaB23evBmTJ08GAPTq1QuBgYHYsmWL/PXdu3fjs88+k4uerVy5kpfoWX5+PkQiEfLy8mr9ko1iIqe3qyMm/nLBKNnnYpEzzs3rozNJVVMSaczdTKVqHk38NqWLkoCYWvLygA4dgPv3cahlOCJGfqy1cdXL7epz6u7Lwnb33H81XW/hMsVzkZpZpNThWNexVaucrE3MzByibuY4BmFdaLt+SKQMOn5xVGtTTDcnO4xu3xDb4h7oPFbXJl74977sRmZZ9DqMuxqN9Do+GPTWOuS5uKvdhv0FKibzq8tX08XOqaFUTacA1/mbVwIrF7/l1KlT1Z577bXX8Nprr/E5FKEBxcTS2OQso5XBjWgr1ks/hJ1YuUYnuNxmSNw9cOOrjQh+bQiG3o7BvwlH8Ft7zc5rfS8XiEXOnBPgMvJK8eOZFKwf10HJKejY2AvxD3KwL+GRTieB/RwkUgbdVpzgdFxAfZWTNU3CXHv8WPsxCOtDl4qyNkcEkPWWaeTNbTmnrFL27RqRdBrjrkZDCgE+GDpHoyMCaEs45XaVpTJew6DeNDaMMcOB+6+m46NBrdVOvtr0Q7iUDyui2v9G9W6pSgulHFN6TMKCkz9j4fFNiG/QGrf81OcodW3ii0qJVKuQmSJsBdHSQ0nyaBDb8ZfrnTprd8y9TIMFmiw9CbPvJSO/FEsP3jCpqBsJxxHq4Hot0+WwsDg72CEo+xGW/b0OALAu7HXEqFFZDanvgQ6NvdDY2xUTwgLhaF+VuaDpuqcOKuM1HHJGrBhdjaWMWUKanleK1UfvILyZL+cmdPqgaLMutcWfO41C17Rr6Jt8Eev2rcDwSWtQ4lg9V6NTkDc++PMqLzu4iC1pchL0Cd3qssVSkzAfxUtjiLqRcByhDq7XsjtPCjiNa1vXGZ/uW4465SWICwjB2m7j1I5LfJyPxMcyUc2fzqXIbz74Xvf8Rc5YMLQ1RC6OnCKrRHXIGbFSuKyp61Ie5cu6k/ew7uQ9peNw0Q/hgmoIk9Ndh0CAD4bMxuHN76FZ9n/4/OhGfDh0ttKQ5aPbIP5Bjt42ZuSVYOXftzXeqQPV5ao1iasZAjsJb4lJga+7k1kuZnzu/BQxJCJHwnE1H32683K9lh29yU37o+fGZQh+moJMVxHeG/4hJFrKeFkUbz5ELo6crimRvZsivFldTurWhHb00hkhTAvXxlKmKvlVPI4xJgXVECafu44cVxFmjfgQEoEQryUew6gbJwEA/h5O2Pg8YmFoSTJXsTaJlNFZamwoSw/dVKrGMWbjPUUMiXj5cqycUgcJx9VsohPT0W3FCYzdFMfre6x4LTOUYTfPoMvfuwEAc4fOxVN3bhE2xZsPrrpJzeu5I6+kHBE7zNM8syZDzoiVoWtNHagS8AJMU/KreBxfN/0nHhbV7rd8oy0XAkKwNnwsAGDFse+xt58vYj7uK9+fPhMXW8Ln5cpNbCkjvxRx97M4r1kbA1NezAyKeBkQhiPhuJqLrpuow8/1dxRLuRXLu0Uujni7eyAMCQY2znmMqOjvAADJU9/DmSYdeW3PRigzC7npJnm7OPK6XhOaoWUaK0OfNXXFXjJ/XEzjVeaq6zgQQO+loMjezarloAD6heDXhb2O0LTr6Jp2DS3emwpcOg+4yjLr+S5XKUZqHuVwuwPKLixD8tNC3nYbgilySdgQ+hEDHJzMojLdgzRgjM7QhPXB5SYqcucVKM7JrK6IsRx8p8pyrN+3Au7lJXjWvjMmNRoKFOq37wupuvvcAMCtJwWUA2UkKDJiZei7ps6WzfVoqV1ZkC+ZhWW8l4LYu9s5/VuoVSLUJ5IhFdph9rD3kekqgtvN69jTd6zey1WKkRquMtSycea/uzFEql9VVOzwtcfyEPrWWN1aDZowdAmFiwgWYVtwibSpBgdyiyuMGmn89MTPCHmSjCwXDxz79Bv8p6cjAgBHOfaleZhTzGkc5UDphiIjVoaha+r+Hty2H9WuPv7iEEHxc5dJG28Y34FT1QWXu1t9E2+fuvvg/aFz8evuRXgtbh/eXfgC8HkkBoWI5ROcNi0UdQl1XGWo/UUu8HN3xrqTyTwsrmJGr6bo3rwuTtx6gp/PpVS7MOuC78WMT5UMV4ypo6BPZ2jCerH0ZDvk1jlMvHIIALDwlY/QL6gxcDHX5Mdt7O3KaRzlQOmGnBErQ9dErWtCYLfXNgmJRc5Y+WpbnNdxN6O4dq9u8sgpKsPSQzeV9sGlU6W2UL0uTjfpiI2dR2PahT1YeXgtpjRphf4rx8NOKNBrguN6vtjz4OnqoNfdXHgzX+SVlOOnsyl6xVf4XMz0rZLRhimWUPh2hiasF0tOto1y0rHiyFoAwPehr+JkUEeM43hTpi/sdXhCWCB+Opei9/WaqIKWaawMro2ltCmDLhoeDIGG7QXPt3e0F2JEW+3hcFVVVnbyGNmuAcKa+mDIi/Vxbl4f7JwairVj+HWq1BSqF4uc8f249tg5NRSRvZup3farHhNxuX5LiMqKsHTrQly68VCjjWz1jqYeKIrnSx3s+bITCmAnFGD56DY635s6nuaX6lW9wjeh0xi6MF6uDtX6hNASCqEN1qk3N46VFVi/bzncy0twsUEwvu4+AcXlEkgljMl63Shehx3thQZdr4kqKDJihWhacuASdeC6vUTKYP9V7UmM2lRZWQy5u9UVydAU+q20s8f0UfNx8NfZaP0sFdcipiH2l63o3KR6foo6gTJ/D2csHlF1HrUt8aie7ytp2hv3aYJLCbEq+lzMDKmSmRjWGIOfNy1j90VLKAQX7IQCjGgr5qyCbCw+PfkT2jxJRo6zO94bUaUn8u/9TJSUS0xyTNXrsKHXa0IGr0Z5lqK2NsrTRzyI6/axyVkYuylO5z4s2fRJl42dHiZix65P4SCVYGmft3G43xilH78ugbKNKnf6us53eaUUrRYc4Z3v4e3mgKFt6nNq8KWIPqJJ+xIeYdauBH4GPocafBH6wvZoMmaOki5evX4MXx1eAwD4v1cX4WTTTvLXQsTuSEznptbKlRm9mqB7cz+N12FDr9c1FZM0yiPMi6Fr6tq2twUlTF35MxcDQvBFn7ex5NgPmH/yF9yo1wTT80qxYXwH9A/21ylQNn/PdaWSWU3ni73I/H4xjbcjAgDZRRWcHZEFQ1sbpMCqr+YKrWsThmAspWautH18G1/+vR4AsCZ8rJIjAsDojggAhDerK78+aHI8yJnXH3JGaim2oITJJdH11w7D0Db9DkbfOIl1+1ZgxKQ1WHIgCW6O9joTTXOKKxB3PwvhzXw1jjFFVYo6WIdgcniQQXdT+miuMADGdArAwWuP6Y6O0At9blr01RmpW5iDjXuXwUlSgaPNusgFEU0N2+STS6sOgj/kjNRSOgd566wM8XJ1sPjdsqb1WDkCAT4ZGIGWzx7ghaf38f1fy/DGuBXYc/k/TvuPTdbsjJiiKkUdxkx041upJHo+Iaw+dlf+HF1YCb5wvWlRjfwBeN79+hmnsnkHSQW+/ysK4sIs3PNuiDnD3gcjME8dxt0nBVh77C7WHLvDuakmwR2qpiE0Yi3JRINCxPKqnYlhjau9XurgjHdHf4ocZ3e0S7+LJUc3oqiskuPe1b9LY3cr1oaxK1W0Vyp1kFc/zenXAnlqhKeopwbBFy7VNOLnkT/FSjd2aWNO/5Za2wSwLDy+CZ0eJSHf0RVTX1mAQiduOh/GYN3JZKxW44gAJP1uDCgyUku5kJKtMzyaW1xhNTLGiuux6tRD/xPVw8wRH+HX3Ysw5to/aHC9O/6xb69zv2FN1EdFzLEG3r25L3q1qIsJYYFwtDfufYGuSiU24VDThdXYMvREzYZLNY2qVIDq9roiemMSojHhymFIIcCsER8ixbuBcYw3EiT9bhgUGaml2EICqzq0NVo7F9Qeq3pMBAB0+/Zz9Mi6q2ZUFZ6uDgg1MMHXEM7ezcTSQzfRc9VJk0Qh1GmusPDpgUQQuuAqFaAtaqCt6WeHRzfx+dGNAICvu49XSliN7N0ME0Ib6Wm58bG2a6atQM5ILYMVALv7hFu2ubXJGOsShfuhyyvI6D8UgooKrN8bhbqFmnVB3nipocY7Na7vO6S+4aXm6RZYFrFVZ5SwTrhEErk4t4pLsuOfOxh+BVnY8FcUHKWVONyiK9aHva60TW5JOTycjStwNqpdfb23tbZrpq1AzkgtIjoxXd4oTVeymDW3ctfaaG1CR/j/byeY4GC4Zz3F+n1RcJCoX47SdqfGtdX9yHbGCRUzMO96sy1UUxG2gzGdWzai19jbDY6VFdj41zLUK8zGLd/G+GDoHECg/KvcHpeG9af06xmliWI9BNOs+ZppC1DOSC2BT2WILcgY68qJSFj7C5oO7YPO/yXhi7+/x7zB71W7iGlb3+Xa6r6olGuirG7S80qxJSbFIJ0RrvDtyWNOSDzK9jCmc8t+/hdSMrHk6AZ0eHwbeU5ueGf0Zyh25NbY0lCyi8p4jbeFa6a1Q85ILYBvZYilZYy5TkbaRIbSfBti7YgP8fP/luKN60eR6l0fG0JfqzZO250aF5nnn8/e1+MdambpoZtVx/FwwtjOjRDo62a0SVnx3HZs7IWD1zQvDWlLODQVpOFgmxja4JMlOjEdi/bdwJOCMrx55TDGXvsHEoEQM0d8hDQv833+lx7k8hpv6WtmTYCckVoA18qQyN7NEN7M16J3olx6yXDBz90Zp5p2wpK+U/H5sR8w7/SveOApxuFW3aqN08agEDF6tvDDssNJSM0qRqCPKz4ZEgwXR1kPDO86TjzeHT8y8suMqv/BV8CNS28iY6IpekcaDtYN6+AODvHHLzGpWiOJqt8lRec4NbMYq4/dAQB0S7mCxcd+AACs7DkRZ5p0NP0b4Qj7/ub0a27UG4XaDjkjtQCu67nN69WxaEmapl4yGfmlmLb9crVeMtpg79S2dRyOoJzH+L/4A/jm0Dd47FEXCfVbQgCgnocTpAyDfQmPNF5Qog4nYdPZFLkM/Nm7wG/n0zC1exDmDwmGv4lblStiyKSsj4CbOcsUtUXvakupsS0uT6lzcAUCQLHjmaaogSbnuOWzVHz/VxQcpBLsDe6FHzq/wtuukPoeSHycz3s7LlAUxDSQM1ILsIVkRYmU4d1LRtN+2Av6mE4BWH3sLr7o8zYCcjPQL/kiNv1vKV6e+DX+E9VDaaUUb/50Xr6tauQh6nCSWt0EKQP58x8Naq1TydZY6DspGyLgduR5hY+pJ0Y+pcY1UcPBFpenNDm4rOM+JTwQ/YL91X53NG3rV5CFX3YvgUd5Mc4HhGDe4FnVcr24UF4p5b2NLiJ7N0V4s7o24STaIlRNUwvgWhliySzwuPtZnHvJaCI6MR3hy2XVQrN2JWD1sbvwdHWAex1nvDfiI9zwa4K6xbn49X9L4F5WpFV5tLxSik1ntbdD33Q2xSQXPW3w0f9gy7hXH72jt4Db1tgHGLspDt1WnDBp6XFtLjVmJ2bVz8ialXB1ObgCAIcTM6oJ7cUmZ2Hv5f/wyd7Eatu6lRVj859L0KDgGZK9G+Kdlz9Fub1+Jbt3nhbqtZ02mtdzr6bXQxgPckZqAbq0OQDLZ4HHJmt2MriMY5d4FHNNAJmKbG5xBd4d0hb/bd2FMj9/NH2WhvV/LYe9RLkSRlHS+dd/U3R26JUywLLDSWaJiqiia1JWLuO+Z/DxTD0x2kL0zhToWp4CrFNinK9onuL3cc4fV5FdVK403k4qwXf7V+KFp/fxzNUTk15bjDwXd1O+Bd7UtO+etUHOSC1BqzaHVSQGcr3YVh/HZYln09lkFPvVx5FlP6LIwRk9Uq/IFB0Z5f2xF9GLqZrF0hRJzSrmNK5bM184Oxjv56btwqjpTtsQTD0x2kL0zhTYkhIuG9nYl/AIMfeecdrmaUGp7u8jw2DJ0Y3oc/8SSuyd8PYrC/Cfp78RLTeMmvrdszYoZ6QWoUubw5KENfHl1LVTXS8ZLks8hWUSzPk9AYAQfUd8iB/3fIlxV6OR4lUfm7qMrjbe7Xm1jC4CfVxxVrvqPADg3L1MTvvTha4SSVM2+NOUt2GMxEuuui7W8F01JrayPMW3EovF180JH/x5Vev38Z0LezA+4Yis58zwD3C1fkvDjDUiNfm7Z21QZKSWoa1fiSUJbeoDT1ft68Oaesmcu8vtLo3leLMu+KLPFADA/FObMfDOv9XGtBZ76OwgKhQALzYQwdvNUedYY8DlwmhIg78BwfU4jVOcGBXD77N2JRiUX2L90TvjYwvLU/pG2jxdHJCUnq91u6E3z+KTU5sBAEv7vo1/WoTxtq9NAw90M1FSc03+7lkbFBkhrAI7oQDLR7dRW9rLsnx0G7WT8LX/8ngfb3PHEQjMeYxJlw9hzYGvMWasj9Id2bIjt+DmaIciLbLQUgb48H/al4f40q2pD5r41UFxmQRn7z7Dk4IqJUi2pLB/sD9ik7PkkYiOjb0Q/yAHTwtKOfccUkeLenXwT9ITnePYiVGbLsi07ZfxVngg+muoptDEoBAx+rSqh22xqXiQXYzG3q4m6WpsLRhLLMxUGBJpyy2pwJeHb2p8veN/Sfjm0DcAgM0dh2PzSyP1svH6I+OX8FqD5lJtg7czcubMGaxatQrx8fFIT0/H3r17MWrUKK3b/Pbbb1i5ciXu3r0LkUiEwYMHY9WqVfDxqXkleoT+DAoRY+P4Dli8/wYy8hUmYQ8nLB7xgsa7E1eOSypKCAT4vO87aJSbgd7347Fl92K89uYK3POt6v7J9qfQ1NLcFJxLzsK550m6/h7OmNOvBQJ9XeXLH0eTMhC+/LjS+TGWfWFNfPG/y484TYxcEi9/iUnFLzGpvEpU1S0H/HQuxapLXA3B2penDIm0aSMw+xE27fkCTpIKHG3WBUv7vG30Y+gD+x2f078FOSFmhvftRlFREdq2bYv169dzGh8TE4OJEydiypQpuHHjBnbv3o0LFy5g6tSpvI0laj6DQsSI+bgvdk4Nxdox7bBzaihiPu6rdSLqFKjfXaNEaIeIkR8jQdwCXqUF2Pb7AjTMq4oMsLoe/iJnfDqkFSaENoa7sx6Oj548yS/F6mN3cPVhLgDgb3nFkHLfDGM4It5uDnhaWIYxnQLk71sR1YmRzyTFtRLHFktcjYE1L09xzVWJ6NUUni7cynB9inKx+c/F8C7Jx1X/5nhv+IeQCs33u9IGA8oPsRS8IyODBw/G4MGDOY+PjY1FYGAg3nvvPQBAUFAQ3n33XaxYsYLvoYlagraeM+poLfbQ+1iv9GiJyZLF+OO3j9EiKw3bfv8Mr725EpluXgCqkjZDGngipIEntsU90PtYfFGNMJjy8phdVPE8wRfy3B3FpGBV1Uk+CZVcxNpquwKrtSaXc81VyS+tQG6J7hJ3j9JCbPtjAYJy0vGfhx+mvLoQJY7c82HaNPAwybIMYXlMvhAbFhaGhw8f4vDhw2AYBk+ePMGff/6JIUOGmPrQRC0hu7hc9yAV2HK9Do28kOvigQlvfI6HonoIyknH1j8WwqNUWTQp5t4zuRqppTDXUlFecQXyiivwaocGmBjWGAuGtsbpD3sr3aHzTajUVaJqSyWupsIak8s7NvYCFzO2xaXpHONaXoLNuxcj+GkKnrl5YvwbS+VOP1ea1q3Da7w+fLznutXputQGTO6MhIeH47fffsMbb7wBR0dH+Pv7QyQSaV3mKSsrQ35+vtIfQWiC78SouOTgL5K1JH/i7ovxbyzFMzdPBD9Nwc9/fg7niqrJcd3JZGyNNV9UxNSMD20EbzdHta8xz//+vPwIW2MfYOmhm+i56iQOX3ss15molEj1itRoiqjYSolrbSP+QY5O8T8uOFWW48c9X6Dj41socvPAhNeXItW7Aa99CAXAKx0aGm6MDnKLKxDHUYSRMB4md0aSkpIwa9YsLFy4EPHx8YiOjkZqaiqmTZumcZuoqCiIRCL5X0BAgKnNJGwYXYJZqiiuxStu+8CrPia8vhR5Tm7o9CgJG/6KgoPE/Oqq5iDIx62aCqY20vNKMWPHFXkJ74RfLugVqdHkOHJ1KO8+KUBschYkUkZJhIt9jjAuxnD+7CWV+G7/SnR7cBWMmxsc/47GnXpBvPfTt7Ufujbz5fVb15dfY1PpO2VmBAzD6H22BQKBzmqaCRMmoLS0FLt375Y/d+7cOXTv3h2PHz+GWFw9OausrAxlZVVJevn5+QgICEBeXh48PPTPDyBqLmzyI1C9IkFXu2/VbsEd/ruJ337/DC6VZTjQqjtmDf/AahLsjIFQAKx6tS3e333VbMdkE4HPzeujdvmhvFKKVguOcL4LV5fXYunGcrbYdVcXsclZGLspTu/tBYwUqw9+jVFJpyFxdIJd9BGgd2+NTSi14eXqgEuf9cfRpAy1v3VTYOnvVE0gPz8fIpFI5/xt8shIcXExhELlw9jZyS7smvwgJycneHh4KP0RhDa0VSRsHN8Bs/q1qLYWz95Zq+YhXG7YGtNe/gTlQnsMv3VWrWy8LSNlgLM8heIMgUuJKt/lALbnkCKWrLoxpvibNcE36qgEw2DpPxswKuk0pPb2sPvfn0Dv3gCA+UOC0T/Yj9fu2EaZmn7rYpEz3u0RBLGa5+f0a4G1Y9rh0yGteR1T03eKonLGh3dkpLCwEPfuyRpvtW/fHt988w169+4Nb29vNGrUCPPnz8ejR4+wdetWAMCWLVswdepUfPvttxg4cCDS09Mxe/ZsCIVCnD9/Xtuh5HD1rAiC690pF3nrYTfP4Nv9qyAEg3Vhr+OrHhOrjZkY1hjZReU4eM22Jx1TwuXucl/CI8zalWDwsXRFYEyBJvE39uiWLs81FE1RR60wDD4+tRnTLuyBVCDAtZXfo90HVUvzms6ZLiJ7N8MHA2XihJp+66rPK4oC+ro5IWLnZV7NLVW/U+quHRRB0QzX+Zt3ae+lS5fQ+7l3CwBz584FAEyaNAlbtmxBeno60tKqMqsnT56MgoICrFu3Du+//z48PT3Rp08fKu0lLAbXC+HB1j3gUVaEZX+vR2TsHyhwcsUPXV5VGjPwBX+EN/NFWeVFHE16arBtIfU9kPi45iRsTwhthAXDXoCjvVCro2gsuXNN/XNMRW0oSWYjEapihEIBNEazImL/wLQLewAA8wfOxB+ZAdiQmI5BIWID+ydVbcVFAuBCShbm/H5FyW5dbSfUHZH9TuWVlGtUHZ6+/bLNO56WhLcz0qtXL43LK4AsEqLKzJkzMXPmTL6HIghecLlj4Xsh3NFuMESlhZh3+lfMP7UFQobBhtDX5K//ey8Tl1KzjeKIAKhRjgggK/k8dvMpRrQVY//VdI2fjS5ZdL6YsupG0anKLCjjVJK8JSYFvu5ONp5Lomyzh7MDcksqqinHTr60Hx+e3QYAWNrnbfzedoCSU2aIqmuXIO3OB5eIZ97zqIiniwMnbRSWjLwSrPz7do12PC0J9aYhagTa+qQo3rHocyHcEPoaHCSVmHvuN8w7/SvspBKs6zoGALD+lO5Ow+bG1UGI4gqppc2Qk55XqjZZUfWz0SSLrg+maiynb/fapYeqerTYWkhf028r7/lELnJ1kC97jE2IxuLjPwIAVoePw8+dRgFQji4Y4igKBZonea4RT/b1PB6OCABkF5Vz1sIxR1SuplEzu08RtQoufVKWHEiCRMrofSH8NnwsVnWfAAD44Ox2zD73m9UmtZZWWo8jog3Vz0ZTYiIfWDE7qZQxenKhvt1rVeGaaGsNSZJclqGc7YWI6N0Uky/tR9Tf6wAAmzqNwtrwsdW2ibmXidsZ+jdzzCyqWm5RPD8x9zKxeP8NXk4s17Hsd8q7jhOn8aSFox8UGSFsHj7qnYbcMa/v+gYq7eww/9QWzI7ZCaFUim+6jwe03K1ZAltK7Fe9m1Tt2nvnSQHi7nNTXWUjKiUVErz5c1VyvDEiEYblOSjDJaRvLUmSXH5bGfll6LV3Mzo9j4hs7PIKlvecrPZ3se7kPYPsUewYrU+ESl8WDQ+GyEW9SKAqporK1XQoMkLYPFzvRI4kpkMqZeDvob9o0g9dXsXS3lMAAO/F/o55p3/VK0Li7eaA1W+0Q2TvZnpaUrOIufcMEimD6MR09Fx1EksP3cTW2AecHRFAvfYIYJxIhLG712qTt7eWhoESKYOYe5naBzEMZp3bgU4/rAQArAkfq9ERMQQ2OtE5yNtoESouCAXA290DIXJxREZ+KbzdNCe/KtqoD9YQCbMkFBkhbB6udyJbYx9ga+wDeLo68LrDVa0a+Lnzy5AI7bD4+I+Yfv5P2EklWNb7LV4X4OyiCiQ/LYQXz8z+msq6k8nYfj6NV8klS2TvZghr6oP3/0hQ+7qmSIRiImpqZhF2XkhTqrpQjESYKvSuul9rqc7hFHlgGMw7/Sumn/8TAHB84mysEfczSs5PtUNBFp0AYLQIFRekDLDpbCo2nU3VOo6Llo42rCUSZknIGSFsHr6VGHwnPCkDLBjaGjnF5Vh3UpawuuWlEZAIhVh6dCPeubgX9lIJPu87lZdDwoastZVIaiLA0xkPc2vW2rQ+jggANK9XB0KBQMmRUEV1OYjLZKuYYMvV4V0wtDV83Z2QWVCmlLSqCdX98llyNFWSJKdEUIbBouM/4v/iDwAAPu8zFb+I+wGQ/QRMlU5l7AiVsVDtas0Hrsn3NR1apiFsHjuhQH7XZKp7RV93J8zp31JJo2Bbh2GYPzASAPBW/H4sOaafUqs+0dixXRrx30iB5nXdDNremvBzd+bVaI9rmF8xwbZjYy+tSqRsiH5yeBBGtmuAyeFBnMarhvQt3TCQS26MgJFi2d/r5Y7IpwNm4JdOI+Wvs9/nKeGBGNWuvlHsYiNCGfnW4YgIAPi4OWL1622xc2oozs3ro5fDwCf5vqZDzghRIzBGJYY2NN0Z72w3CB8Ofg9SCDDp8iEs+3s9hFKJXsfgGlRxc7KDvcCwn+4rHRtWk802FZpkuo2Bt5sDMvJleh9c8K3jxCvMz0YitsWmYkiIv8bt2GUENkSvzUHWFtLnGoExVZKkrsiDnVSCrw6vwbir0ZAIhPhgyGz81n5ItXECAIcTM9DAy8UodrGfQ6aVVKowALKKyuEvclFqMcEXPpGwmg45I0SNYVCIGOfm9cHOqaGYGNbYKPtUvIO9kJKtdilh94sD8OGQ2ZBCgHFXo7Hhryg4VXCbHBVhGODTIa3xVnig1nFfv9YW/+WV8N6/Io9yS/FSY0+D9sGFCaGNcPrD3pg/JBjn5vUxesJudlEF5vyewGlJRCgApBJGrzD/0kM38XNMKq9ttPVL0hR619ULxtAkSV1oi7jYSyqx9sBXeCXxBCRCO8we9j7+bNNP7Vh2EvXkWIHSvzW3PjX6LuWZCkMjVJaOhFkT5IwQNou67HNWInqwEddY2TvYDC0OwP/a9EXEyHkos3PAwLtx+O33zyAq4a+nkFdSgYXDX8DG8R3g71G94dfG55NYY29X3vtWZFvcAxy4lmHQPrgdJw09VsoaxtkJBQhv5mvyY2pCygDnU7NMtv/5e65XC6crOshrx7TTGdLXN6JiLDRFXFzLS/Djni8w7NZZlAvtsWX2ChwI7qlzf54u3NISx3XiuOxoXVX0BkeoLB0JsyYogZWwSXRlnxtDXlwoAKZ2D5JPHNlF5VrHH2nVDVluntiy70u89Ogm/rf9Q0x6/XM8EvHpTiqzdlCIWC6dra6Xy4SwQHx5+KZNaIpk5Jdh2vbL2Di+A/q0qqdXwi4A1HGyx5LhwfjyyC2dn4VmTDebsV1lVR0u1R4qrBOtqZkjG1FR/X5rSpLk2hySC+p+N3ULs/HLn0vQ5kkySu0dMX3UfJx0aMVpf1f/y+U07qeY6gq96uAaaTE1bPM8QyNUuq5TxjqOLUDOCGETKJdhFmPNsTs6s88NlRdnGODHMylo38gLg0LEnBQYLwSE4N8tf6HfnElo9t9/+Ou3DzHplUVIqteE0zHDmlRNZNoagTnaCzG1e5BamXVr5eP/XUNE7+Z6O1CFZZXILakwwBEBwpr64H+X/zNaDxxVYpOrOyOKcC3h1OWM8t2fNlSdmQVDW2PGjisAgGaZadiyexEa5j9DlosH3n5lIa404OaIAMAtjmqrMcncIlapWUWcj20qjBmhYiNh6q5T5oiEWRMCRlvXOyuBawtiombCR22Ra7tvdY3bdO3vQko2xm6K02lDZO+m6O1WgQ7Tx0GQmIhy1zr4bd43WFHREKVaesZ4ujog/rP+vC48UYeTsOlsik1ESIzBhNBG2BaXpnugGjxdHLD+zQ7IKy5HxPPJ1tinLbJ3U3wwUP1kramEk/20+ZZwGmN/6n4fns97zYSmXcOPe76ER1kR7nvVx+TXliDNq+aXmAJARO+m6NasLnKKyrH0kOn1P2qyzgjX+ZucEcKq4dr8SpWdU0PlUQVNYWyJlMGWmBROyY87p4aic5A3uq04wTkBMkBQhm92LUGn1GsoF9rjg6GzsT+4l8bxG/XUEyivlMrl05OfFiAmueZm3hvijLDwcUb58tuULghvXj0yIpEyOr87YgUnWhe69qfqlKtD229r5I2TWHV4LRyllbjYIBjvjP4UOa4inXbZArp0ULxcHXBJ4abAmMtg2jDXccwN1/mblmkIq8WQfiCK2eealjvshAL4unNvfqUYUgV031U/ZJzw5itL8M2hbzDs1ll8e+Ar+Bdk4cfOo5XqeFVzU3Sh7qI1pbtsGSjmbiZiks/r2AN3wpv6oEldN9jbAb/+m2bRCIxAALRt6IltMMwZycgrxY9nUrB+XAf8EpOCSw9yjGKfp6sDQtV8z1inV5fjw0fMzFBxNI2/LYZBROwf+PDsNgDAwZbd8P6wuSizt45cDUMQANj6VmcUlFbIl6HUETW6jZIToG251JiY6zjWCjkjhNViiNqisbPU2XGDQsR4p0cQNp1N4aRvVm7vgJkjPkRGHW+8fWkfPjm1GeKCTCzt8zakQjsA1XNTtBGdmI7F+28oqY36ezhh8YgXMChEjNCmPvIwuzGISc7ivJ5vahhGliTKhU+HtML6k8nIVdMmnv3Ylh5KQpdAL1x6YBz7lqtMYgD/hm5cRb24lnrG3MtUe6et7rdlL6nE0n++x9hr/wAAfug8Gst7TQZjoKaNtfBOjyB0b1EXALBRKMDi/coiajVlWcRWIWeEsFr0qa3nm33ON5s9OjEdP55J4deqXCDEF32nIt3dFwtO/oz/iz+Apln/YeaIj5Dn4s6550h0YjqmPY/KKKJYrTIoRIzlo9uoHVcTyCkuh1jkrHO5I7i+SK0jokh6XilaiT2Aq4Y1nlN0BhXRZ4kxu7DKydS2vMhV5E2xS67iZKvq9LiVFeP7fcvRM+UyJAIhFvd7B9s6DONhufXTvpGX/DHXBGHCfJAzQlgtfGvr9ck+55PNbmgb+Z87v4x0j7r46vBq9Ei9ggO/zsa7oz/FTb8mnMLqH++5rnX/c/+4CncnB/QP9sfG8R2qRVC04eFsjyEv+uP3C/+ZrQmZfjAal8oUP6+nHCfr/JJKg6x5uV19fPV6u2rfN32/K95usuUQQxOv1aFYbabo9DTOeYyNe5eh9bNUlNg7YeaIj3CseRfO+zVFYzxTMH/PdSVnv7Yvi1gbNSP+RtRIdKlRqqJN2VIbXJUyjdGk63Crbnh5wtd44OmPRnlPsGfbhxiedFr+uqZoUFxyls6ll+JyCd78+Ty6rTgBAIj5uC92Tg1FZO+mOu3KL62Eg1Bo9ZOKp7OjfKlMVT5fIJCF4geFiJUmW208NlDJtoGXi1KiIyvCxyVHRB3+IheNvXPS80rxwxn99gso9zrxdJU5PX3vnceBX+eg9bNUPHPzxBvjong5Ior7tXZYHRjCOqHICGG16IpaMADm9GuOQF83g8OsXMK2xmrSdbtuIEZMXI1vD6xCz5TL+O7AKoQ8ScbKnpM0RoNi72dy3r+q3grX5a7UrGLOx7AUeWUVGpfKpAq5N2yEQRf1PQ1TtmR1YfjmhqhDLHJGx8Ze6LnqpMkmeDYCl5NfjPfPbMPM2N8BAJcatEbEyHl44m45hVxzoEsHhrAcFBkhrBptUYuN4ztgVr8WGNmugUHNqljYsK2m/XG92+ZCnos7/u/VRVgf+hoA4N0Le7Brz2J0dtekQ8L9val2++S63BXoY5jEvLnQtfyx5EASfDkI1AGySIuni4Pugeq2fV49w7ULsDYEkC0vxT/IMXq5sSpexXkImzlR7ohs7jgcY8cuU+uIjDewO7Q5mBjWmEd3YFuJ49Q+KDJCWD3WkmzG9W6bK1KhHVb1nIQb9Zpi1eE16JR8BejcCdi7F2jfXmlsWFMfpWREXSjmoLDLXbqSPucNam2whoc29JWBV8TTxYFTSStX5c9l0bf0tmX56DYAdDtHulBMLN175ZEBe9JNm/S72PDXMjTMf4ZiByd8PGimVu2bjoHeOH7rqckUa43BwBf8AQb4K+GxzrGKCseEdUHOCGETWEOymb+IWzv0yN7NEN7MFzlFZfj8YJJSEqmniz0gECjlf1zp0g9XJg9Etw+nAvfuAV27Aj/9BLz5pnxMp0BvvRIFWX2UkAYeWidxd2d7zP0jgefeucG6jOvGtoeXm9NzSf8i7LyQpnRudL0/T1cHzhGPtGzjyYar2qVYPRObnGVQJGPB0NaYHB4kT5COTzWdYN0bV//G50c3wElSiRQvMaa9/Clu1w3Uuo2/h7PBbRVMDgN0CtL9+xBANo6lpoqM2SrkjBAER7hGGOb0byG/qA0MEVe74AFQfxHsdVHmgBw+DIwfD5w6BaxeDdSpg4up2XpNBH7uziivlOL4zadax915Uog7Twr1OIJu2AZvbHQLADoH+WB6r2aIf5AjPw85RWVaxaiWj24DkQUapTGQOQ2+7k7VJi1D84h83Z3kbQv4VD/xwamiDJ8f3Yg3rh8FAPzTPBTvD52DAic3rdt5uTrI3+uG8R2q6XLwRZfyqb5kFpUh/kGOzt8HAyD+QQ7Cni+t1VT5dVuFnBGC4IidUIARbcVam9ONaCvmpN6oNsrj6QkcOAAsXgx88YUsOnLqFPDbb4jN4SfFraiPsiXGsr1rpFIGV9JyNIq1jWzXQP6cTIxKs6hbeaVU53KPUAC82NATMFCpVRFfdye5nYpddy8/MCySkVlQhsPX0jFjh2l0YZpmPsTag18h5EkyJAIhvu4+HhtCX+UkZFb9FOv/JRIAqOfuhCndmuBiajb+SXqi975U8XN35pyk/bSgVKP+i2riN2FeyBkhCI5IpAz26xDI2n81HR8Naq1/uFcoBD7/HOjTB5g4Ub5sEzpuBjb494PkuWqrNlT1UR5km6ZKxsvVATnFFTrD408KytQ6cKpibYDu/KD4Bzk6HSspA6Mp0LKwScDGqJpRZOmhmzxSk7kjYKT4v0sHMO/0FjhJKpDl4oH3RnyEmMB2nPeRW1yBxfsT8TC7GKfucK/mUgcD2ecd0kAEPw8nozgjig43G3HTxdP8Mvx87r7a7ytX8UHCNJAzQhAc4aIzoipcpve6dK9ewNWrwIwZwK5d6LbtO/xR/yhmD/8ADz39tW7qrxJubuxtmioZJ3sh3u0RZHDDubl/XIW7swNCm8gqmLTlB3G9A84tLtfbHkUEAOp5OEHKMFh64AZ+jkk1yn4VMXbQqkHeU3x1eDXC0mQieaeDOuCjwe/pVbZr7IRm9ndgKKoON5clVAD48rD2ppi6xAcJ00HOCEHogHUojiRykw1nJ0yD16W9vICdO4Fhw8DMmIGOj2/hyOaZWNzvXfwZ0heqql+ujnbYNPEl+aTOMiEsEF8evmn0pZon+WXyhnOPckt0Xug1UVwuwZs/ned0brhOZI9yDRMzY2EAlFZK8eZPxms+aDIYBq8mHseiYz/AvbwExQ5O+LL3FPzWbnC174ql8HOXaakYWlml6nBzWULlgz6tKAjDIJ0RgtBCdGI6uq04gbGb4rA1lltHNT93Z43aE+y6dDRHxwYA8OabEFy7huwOXVCnvARfHV6D9fuWw7MkX2nY2E4BEKqZdBzthZjaPYj78RQY2VassaSZef639FAScowQidB2btg8jce5JZyWNbiUeXLF2Es+psCnKBc/7v0SXx1eA/fyElxq0BqD/+87/NZ+iNU4IkIBUFkpxbfH7+jtiET0aoqdU0Nxbl4fJaeVyxIqH7hWbRHGgyIjBKEBvo3O2DVsbSqa7HOf7L2Okgop/D04Lt00bgzvCzG4/f4CNP1uJYbejkHHRzcxf9BMnGraCQyAn2NS8XNMqtoIw/whwQCATWe5J7MKBcCrHQOwT8dFPj2vFFcf5nLbqRY0rdkbO0+jpjHgTiyW/b0OvsV5KBfa45vu4/Fj55fhUccZsCJHSsoAEzZfMGgfLfzd1S6fGKNVgxJWWcNcsxEwjCmKrYxLfn4+RCIR8vLy4OHhYWlziFqARMqg24oTnC9wrCuxYXwHiFwcMXZTHOdj8S0plFy8hPIxY+FyXyaCFt0iDEv6voN0j7pKtqwfV6XrwearSKQMtsWm4kF2Me5mFCBWS+LfsBfF8HJ1xLY4bhEhY7Jzaqi8BJNv59vagmdJPj478TNeTTwOALhZNxBzh81FbvNgpVJqVtdl9bG7FrbYcCJ7N0V4s7rVHPh9CY8wa1eC0Y6zdkw7pSovQn+4zt8UGSEINfC901Jcw96XwE9Fk29JoV2nl+B4NQHbh7yFN2L+h0F3YtE95QrWho/FLy+NRKWd7GcdufOKUhSEdXqmdG8ify7qcFK1aIlAALg42OHgNeOFvfnytKDU4C7JNRWhVIIx1/7Bh6e3wqu0ABKBED90GY014W+i3N4B9aSylgJsIjDrWNcE1p1MxrqTydUceGMkxSpi7P0RuuGdM3LmzBkMHz4c9evXh0AgwF9//aVzm7KyMnz66ado3LgxnJycEBgYiF9++UUfewnCLHBNYJsY1rjaGjbfC5lqLxkuXHhSis+6TsTQyWtxoWEw3CpK8cmpzTi4ZRZe+u8GgOoJgupyMuYPCcatpYOxYGhrTAxrjFc7NATDyJJKLYmfu7PxQ+81gPaPbuGvbe9j2d/r4VVagJt1A/HauBVY2XMyyu1lPXaeFJRjmsLnXBPPo+p3mW+Hb00IIHPaOysotRLmgbczUlRUhLZt22L9+vWct3n99ddx/Phx/Pzzz7h9+zZ27tyJli1b8j00QZgNrg7F4BBxtaZ6+lwYFUsKucA6S3fqBuKNccvx4eBZyHbxQKvMB/jzt3lYdWgNvIvzqh0DqO70ONoLMaV7Eywa/gJikg3TkzAUxcnAVioazJEe6lOUi5WH12Dv9g/wYsY95Du5YVG/dzFs8lpcbtha7TYf77kOiZRBRp5xKousCTZ5mv0usx2+DYmiqZYLE+aF9zLN4MGDMXjwYM7jo6Ojcfr0ady/fx/e3jJvMzAwkO9hCcKssA6FpgZhioJLqrAXRn36eXCdgBWdJUYgxO4X++No8y746PSvGHf1b7yWeAz978Vhec/J+L3tALnipjYdBUvfQatOBrYSKjflMpKdVIIJlw9h7rnf4FEm67fzR5t+WNlzEjLdvLRum1tcgbjkLGQXGUdzxRoxRBNEtbzYX+SMBUNbQ+TiiH0Jj6hfjZkxec7I/v378dJLL2HlypXYtm0b3NzcMGLECCxduhQuLuobj5WVlaGsrEoOOj8/X+04gjAV2hwKLndQg0LE2DC+A+8qEC4TsETKQMow8HRxQG5JVbVErosHPhk0E3+26Ycv/vkewU9TsPzvdRh3NRpfd5+A00Ed5GWeRxTC2+x7sHQkQlU7QpdDWNPp/DARS45uROtnqQCA6/WaYmH/6bjSoBXnffxxMQ0erg4mstA6yMiX5Rd9vOc6p/FVjRs7wMvNUaE3UjmWHqJ+NZbCoGoagUCAvXv3YtSoURrHDBo0CKdOnUK/fv2wcOFCZGZmYsaMGejduzc2b96sdpvFixdjyZIl1Z6nahrC3BgqXMYKpmXklWDpoZvIKSrXGmk5N6+P1jsxrmWudlIJJsUfxNxz21GnXBamv9AwGF/1mIgLASFq30tschavKiBj8VZ4IPoH+6u9C2WraYDaU235wpNkzIrZiQF3ZZ9FjrM7VvachN9f7A8ph3YAtY0FQ1ujldiDszCdut+vpqotxSo5ckj0g2s1jcmdkQEDBuDs2bPIyMiASCRr9rVnzx68+uqrKCoqUhsdURcZCQgIIGeEsAjGajWuaWLlesHTp8zVpygX0+N2Y8KVw3CSyKIoZwLb46seE3BN3ELp2P2D/dFtxQmzRSK4OnW1RWck+Ml9zIrZgYHPnRApBNjRbhC+6jEBuS503dPE6tfbIvlZEdadvKdz7Mvt6uOr19sp/X51lfFzvVEg1GM1pb1isRgNGjSQOyIA0Lp1azAMg//++w/Nmzevto2TkxOcnEgBj7AOtPVK4YOmpRvV5Ql16FvmmuXmiS/6TsVPnV7GzNhdeP3aUfRIvYIeqVfwd/NQfN19PO7WDZQLjS0aHoxp203TQVYVrvdBqs3zjiVl4MC1DBNbZz7UOSH7gntiXdc3kOwTYGHrrB9/kQuSnxVyGqvuG6crV4r61ZgHkzsj4eHh2L17NwoLC1GnTh0AwJ07dyAUCtGwYUNTH54grApdXWk1YWhyaYaHLz4dGImNXV7F7JgdGHXjFAbejUP/u+exP7gH1oSPw4WUdriSlqP3MfjyJL+Ms76KombG8iO3zGShaWn99D5mxezEoDuxAGROSHK/4ZgWOJicEI54ujqgc5A3pFIG604m6xz/V8JjnE/JVnL+ueZKWTqnqqbDu7S3sLAQCQkJSEhIAACkpKQgISEBaWmy7o7z58/HxIkT5ePHjRsHHx8f/N///R+SkpJw5swZfPjhh3jrrbc0JrASRE2GnVhHtmtQrSxYE/peCCN7N8PEsMby/z/09Mf7Q+di4FvrcKhlOIRgMCrpNE5smobAyW/g5tb/AWYSZdZUasz2odmX8AixyVlKr1m64scYtEm/iw17l+HI5vcw6E6sLBLSuicGvP09/lvzIzkiPGB/OaFNfeDJMVFXVaOEa9WWrVR32Sq8IyOXLl1C79695f+fO3cuAGDSpEnYsmUL0tPT5Y4JANSpUwdHjx7FzJkz8dJLL8HHxwevv/46vvjiCyOYTxA1B225KfpeCL00XKDv+TZCxKj5+D7jHuac+w39ki9CfO44tuI4kr0b4tcOQ/G/kL4ocnLV+/1wQTUErith2FbvTp0rSjEi6QzGJxzGixmy3AYpBDjYuju+7ToG93wbAQB++tc4XWdrCznFFfLvzvLRbTgtMar2QDKkjJ8wHtSbhiBMCNfkV12TMJtkxye5lGubdgGAzuXPMPvOUYQc3Qv359U3BY4u+LNNP/zaYRhSvU3bp2PtmHZwshfqrGjg2/fH0jTNfIjxCYfxSuIJuU5ImZ09DrXqjg1dXsXduo2Vxgf5uiIls9gSptosin1kohPTsXj/DWTkl+nYSoZqDyRAv+RyQjNmqaYxF+SMELYI17JgbVUyAlRdCE1R5qp4sX2UU4Jv9sTjlcTjmHT5EJpm/ycfdyqoI37tOAxnA9vLe98Yk9+mdMEHf17VWdFw+sPe6LnqpFVrjzhIKjDwTizGXzmM0IeJ8ucfePpjR7tB2N2mP7JdRVr2QPCBdShYJFIGq4/e5pRDEtm7GZrXq0M6IyaEnBGCsCBcdQu4dAcWK5QVGrvMVfFiW1IuQeuF0TI7GSm6pSZgcvwB9E6+BOHzd5Lj7I7oFmE43KobYhu9aLBjwjoZX73WlpNOxM6pocgrKbc67REBI0W7x3cw8M6/eOXGCdQtygUASARCHG/WGdvbDcbZoPZyJVxT4eogRHGF1KTHsBa0ldzqo5kjfq7Aqtrpmsp5DcNqSnsJorahrQxXdb2aS0KmYk7FoBAx+rSqh6UHb2BbXJrW7bShrhV7wsPcKjsFQpwN6oCzQR3QKCcdEy8fxKikU/AtzsPYa/9g7LV/kO3igb+bh+rtmCgq2WYWcgurPy0oxch2DfRStzU2DpIKhKZdx8A7seh/7zzqFVb1FXpSxxu7XhyIXW0HIN2jrtlsqk2OCKBZBVkf9d6MvFJE7LiCDeM7yJd9CPNBzghBGBk+ugVcm5ix44wVGWlez72aZoKm5NA0LzG+6DsVUb3fQueHiRh66xwG3flXo2NyoeELKHPgphP0To8guforF9hEXtUS6cyCMiw9dJPTPgzBtbwEPVIuY+CdWPRNvijPAwFkOTYnm3bCoZbdcLxZZ5MsZ9VGvFwdwEDWa4dFlzaPPv2hVG8UKCJiXujXQhBGho9uAdcmZtlF5XopsGpCXXWOroodidAOsY3bIrZxWyzqPw2dHyZi2K2zGHgnVskxKbOzxzX/FrgQ8AIuBIQgvkFrFKqpymEA/HAmBe0beaF/sD/EImedy1WKFQ2KYnQSKYPvTt5TmrCMgUt5Kdpm3EGHR7fw0n9J6Jp2Dc6VVZ/ZM1dPHG3eBf80D8O/jdui3L5m94ExF3P6NUegr5t8qQQAb20effpDkcCZ5SBnhCCMDB/dAi7VLgDg5eqolwKrKurKFOX9c/JL4e3mgOwi3RO6RGiHuOeOycL+09El7TqG3j6HfvcuoF5hNjo9SkKnR0mIiNsNiUCIJL8gXAgIwYWGL+BiwAtKCZwf77mO/sH+GNFWjB/OaC5tHdFWXE3Gm52gfOs4Ga6PwjAIyHuCDo9uosPjW+j46BZaPU2BPaO89JEmqoe/W4Th7xZhuFy/FfWLMSJCATC1exBm9WtR7TV9nAPVCNrdJwWcEltttYTcliFnhCCMDB/dggsp2WpGVCenuNzgpRl16+yGLPuw700itMO/ge3wb2A7fDqAQePcdHR+eANdHyeh77Nb8Hj8EG2eJKPNk2RMubQPAJBRxxsp3g2Q4tUA973r41bdp0i4WwkHO09U2KmPLuy/mo6PBrU2OJHXqbIcDfKeolFuBhrmPUGj3AwE5TxGu8e3Ubc4t9r49Do+KO7QCTvsGuDfwLa4WTdI3v2Y4I6rox2KyyVax0gZ4Mfn0TJjVbAoRtBik7M4OSMkcGZ+yBkhCCOjbb1a1SFgHRddyxPebo6cjy8WOWNEWzH2X03X2gPHmMs+cgQCPPCqjwde9bH7xf4Y1a4+Ys9eQ+eHN9DpvyR0fpiIVpkP4F+YDf/CbISlPW/7fvIX/A6gUiDEQ896SPFqgCd1vFHo5IpCR1cUOLmhwMkF99zTkO/ojB/OPoabkysChXZwriyHc2U5XCrK4FxZBueKMrhUlj3/fzk8SovQMC8DAc8dD/9CzQ5gudAeN+o1xeUGrXC5fitcbtAK6R518VJjT1x6kGvMM1VrEECWG/TRoNbyCNzSgzc0RuAYcMvb0KeBJQmcWS/kjBCECeDaFE/RcQE0Oy7uTtxyET4d0gpvdWsCO6FAfvFXd7HW1XhPAMDbzRGfDGmNLw8ncVq6UUdRWSWeuPviQHBPHAjuCQDwKC1Ek+xHCMp+hMCcx2iS/QhtS57C5/EDuFWUIignHUE56ep3eET2z169rKmi0NEFD0X18NDTH2nP/71erxlu+DdFmX11xy+/1LBclPFdGuHKwxzceFxg0H5sjfFdGmHh8BfgaC+Uy/onPy3U+X3SlbfBVcNHFT43CoR5IWeEIEwE16Z4XByXmHuZnI4ZXF8k37+2bsNcKn6yisqRW1yutyMCAPU8qoe7853rIKF+SyTUbyl/7tMhrfHloST4FWajSc4jBGU/hk9xLuqUFcO9vBh1ykpQp7wYL7gB2RmZqFNWjDrlJXCQVKDUwQkl9k4otXdCiYMTSh2cUGrviJLnzxc7OuM/UT08FNVDmqc/HorqIcfFg9dSy50nRboHaWH7ef3LsG2ZTkHecLQX6rWspqnSTFNEj+05o0st1ZDu2YTpIGeEIEyINodAEV2OC1cdDj56HVx4kG2YNHn7AE8cvJ6utcrFy9UBk7oG4peYFGQIfPDU3QdxjV5UGsOGzz8a1Apzfk8wyCbCfPi5O+u9HKiu0oyPho+26Ia+3bMJ02FaOUCCIDijrZuvsTuLch3X2NuwRnn1vVyxfHQbrWOiRreBo70Qi4YHA6gKl7Mohs/91URaCOtDANmyScfGXnpXgXnXqa5Vw0fDRxf6dM8mTAc5IwRhA3QO8tbZIt3L1YFz4h2byKfp8stOJhPCArWO0warCzIoRIyN4ztUcyTEImdsVAips+Fzf5HyOH+Rszz0rstuc9PCz83SJlgdis5j/IMcvavA1DmefDR8CNuClmkIoobA5+6TSyLfmE6NcCQxHWM6BWD1sbuclSzZfSgmArIy9ttiU/EguxiNvV0xISwQjvbK90O6wue67GYAeLo6KC0Lce1erA8ltUR+nQ+KuRf7Eh7ptQ9VgTsWY0f+COuBnBGCsAEupGTrVBfNLa7gpRypKZHP87n89upjd5SeY4/BorGE2MMJYzs3QlmlFLHJWegc5I2jSRnVjvPTuRS1CYO68mx0JSCyzszRpAz8EpNqMkcEAB7mcJPzr8mIRc746tW2yCwqq+Y88nUKDO05Q6W5tgs5IwRhA5gqPK0aiUjNLMLqY3erjct77oTM6dcCgb6uSpOOYglxamYxdl5IU9qHaqSChWv1A1BdU6J/sL/WCErnIG/M/SOB17mozfi4OeKzoa2RWViGLw/f4rSNouMQ3txX7Ri+DesM6TlDpbm2DTkjBGEDmDI8zUYiJFIG3VacUDuGrVTYdTGtWst2dvvoxHSsOXan2qSjKaLDtfpBk6bEgqHB8NIgBselGzIhQwDgy5dDeJWQA9xKYbk4D7PVOLiqqDqj68e1x9JDN41emquPkBphHMgZIQgbwBzhaT6VCqrLKLpE1PTZJ6BZUyI9rxQzdlxWek5R9IoSGLmhKhTGtTQ8sndTzOnfktNEbaiuhy5n1FiOg75CaoRxIGeEIGwALombg0Nkyxb6XpQNWQoyNBKhuE954768Eiw9dJOzg6O47GNtCYwdGnniclqupc2QE9m7KcKb1a32XeF63sKb1eX1HdNX10ObwFnEDtlnPbJdA8526HMcrkuJhGFQaS9B2AiaSl9ZIdFfYlIxdlMcuq04gehEDXLqWvBVo+vAZZxEyiDm3jPex1OEnQSjE9PRbcUJjN0Uhzl/XFUrfKUJdiJZciAJHRt7cSpd/nRIK4Ps5oqLg/V09hWLnDGnf0u12hodG3tBl48hFMjG8YWvrocugTNA9llLDMxQNtdxCO2QM0IQNsSgEDHOzeuDnVNDMSU8EED1slX2bo63Q8L1WqswjnUeuHRC1YSnqwOkUgaHrz3G9O2XDYqwsMs+8Q9yOImovdWtiVl0S1wdrccZ6djYCwevPUZscla1CTb+QY7O6iMpIxvHIpEyiE3Owr6ER2r3qe+41UdvG03gTBvGFFIj9IeWaQjCxmC7/WqqFuEji61IZhFHyfnn44zV9Te3uAJv/nweQgE/rRRtPC0oxch2DTjlKiwaHoxp2y9r2pXBeLk6YOAL/jh686nOsSNeFGP/Nf5RLT4cvJaOg8+PoZoTwXepjmueBde8j5yiciw9xK+HjaH5QSSkZh2QM0IQNoghyaaa4FOxwydhVZMYmSrGjIKz70VbrgKbm2LqO14GgFjkwmnsay8F4MD1dDBmWhFQzYnwdeO4VOfmxDnPgk8Ssj4Ymh9EQmrWATkjBGGDmOJujk/FDp+EVUUxsrj7WYj47TJyS/TvBKwNrlVF+nSR1Zfc4gpAIIsEaDueWOQMoUBgNkcEqB5F47peJWV051l8vOc63BzssXi/fr1pdGEsgTMSUrMOyBkhCBvEFHdzfASluDo5kb2bYU7/FvKlIqFAYFJHRNFGQL3ToStCYwoyC8vk5xbQfG65LpUpwn5Wb4UHokIixba4NF7bK0bRuJb2nufgjOYWV2DC5gu8bOGKYsuCg9ceG1Taq/i91wQJqZkeSmAlCBuEa6M7vndzXJrVAXxKQH2VLuKGrLt7uzlg9RvtsHNqKL4f175aIzVVG9nlAdVJ09yOCCA7X1zOLddlEkVYx+ZIYgbaBfCvcmFhl7H4HdUyeLo6QOTigNXH7mDWrgSM3RSH8OX6VZEBsu/9Oz2CqlUSCQXAOz2CqKzXDFBkhCBsEFPKYnPRhNA3tK3Pujt71GUvt1FyNFQnREZhfUNfETZNhDf1QUxyFu/tVM+DznNrwM13el4pcou5l0KrwtrC5XMNa+JrUAWVvkT2bgYHO4HalgUZ+aWYtv2yUidorkQnpuPHMynV3jPDAD+eSUH7Rl7kkJgYiowQhI3CNYqhD7o0IVhnCNBeOqu6na6IDoBqd6eaIh4Z+cpLCk/yyzB9+2UcvpaOLTEpRskHYSNMbQNEem0LAAuGynr3sCWtADSe26cF/JdpFPFydYRYxM/hU4yicf1cQ5v6yJsnmgtPVwe817c5Nv+bqnXc/D3XeWmCkM6IdUCREYKwYfRVtjTWsfnKfHOJ6Kwb20GjzDeXiSNy52WjVOYoTr7uTg74/tR9Xtv7P+9qrNpDRZvE+DMDHaic4nJepcrqHEd2yWLT2RSlZFqBAJjaXbZkYYmJWQDg/P0snctsOcUViLufhfBm6pv3qWKKyjSCP+SMEISNw0YxLIE+zpAhvUq4VPEYa55UtEciZXQmvopc7PH9mx2RWVgm18yI2MFdYlwiZXDqjm4tEm14a2gcqAl151zTkoVUYclC5OJo9tybnOIK/O/yf5zGxiZzd0ZIZ8Q6IGeEIAiD0McZ0jeiY44JYUp4IPoF+yvZYycUYPnoNlojDiteeVE+AbIdkDVFcFRF6YxVauzn7owP/ryqdYy3mwMWDHsB/h5VuSyxyVl4WlAK3zpOWLz/hsZcG+a53R8NMo+MvirF5ZUcR3L3SElnxDrg7YycOXMGq1atQnx8PNLT07F3716MGjWK07YxMTHo2bMnQkJCkJCQwPfQBEHYMOras/N1YowxIWgSYdPVoXVQiBjv9giqFjUQoHrFBZ/Qf15JuVGUbIUCmf6HLocmu6gC/h7OCGvqg+jEdCzen4SMfO5OUHpeKbI5lgBzZVS7+vgr4bHOcZ0CffBPku7oUVgTblERgHRGrAXezkhRURHatm2Lt956C6NHj+a8XW5uLiZOnIi+ffviyZMnfA9LEIQNY6z27LomDi4oirDxicxoWr4AqldccI3gZOSXYmX0LaNU/UgZ4HwKt4qfpwWliE5M11sG39PFweDPQZGeLerifEq2TodgUtdArD91T+sSkaerA0J5OLmmrEwjuMO7mmbw4MH44osv8PLLL/Pabtq0aRg3bhzCwsL4HpIgCBtGk96HPg39tFV7cGHB0NY4N68PBoWIeXWR5VtxwTWCk11YZmQVWG5nxdfNCR/vua73UXJLKgz6HFTxF7lwquJxtBdi+eg2Wve1fHQb3o6DKSvTCG6YpbR38+bNuH//PhYtWmSOwxEEYSWYomxS08Shbf5hy1cnhwfpdYfLt7Nr5yBvnaWvXq4OvBNOddGFQ+m0t5sDYu5lGpSA6l3HSePnwAfFsmKuDsGgEDE2ju8Afw9lgTh/Dye9NEZYFDtirx0jE9djHVfC9Jg8gfXu3bv4+OOPcfbsWdjbcztcWVkZysqq1iTz8/NNZR5BECbEVGWT6hJgc4rKELHjiny/LMYItZui4oIB9whKv1Z1cezWM53jhALd0ubZRRX4/rRhgmWs+i37OXz9zy3epc/qJN37B/ujT6t62BabigfZxWjs7YoJYYFwtFe+bzZVSbslK9NqOyZ1RiQSCcaNG4clS5agRYsWnLeLiorCkiVLTGgZQRDmwJRlk+omjg1CgV4lw4D6BFt2cuNbcXEhJVtn5EGxgZ6uXIkhbepzckaeFpbh5fYN5DohppADUW0zYCcUoHtzP97OiKerAxgAq4/dUXoOUJbs/+lcitrPjxyHmoVJnZGCggJcunQJV65cQWRkJABAKpWCYRjY29vjn3/+QZ8+faptN3/+fMydO1f+//z8fAQEBJjSVIIgTADXSTyzoAwSKWPwna2+d8y6Emw7NvZ6Xq2ieR9CAdCxsaw3DFfnim2gpymRlIEsovMop4TT/rILyxCdmI4fzqRwGs8HLsq62qJg/h5O+Pr1dsgsLENqZpFaSXd1DpwmXRaiZmFSZ8TDwwPXrysnSX3//fc4ceIE/vzzTwQFBandzsnJCU5O/BtGEQRhXXCtfll66KbGO2C+8L1jZhNstYmTiVwcdUYZpAwQ/yAHYU19eEVS8kp095Phmlvi6eJgUGKqNrgq62qK8Cwe8QLCm/nKNVi4ok6Xhah58E5gLSwsREJCglwnJCUlBQkJCUhLk7Wtnj9/PiZOnCjbuVCIkJAQpT8/Pz84OzsjJCQEbm5uxnsnBEFYHXyqX/SprjEUrgm2XHU42IgI167KHRt7YcmBJI37YydhztU5xRVGVUYd36UR52ROrp1vuajoqqKaIEzUPHg7I5cuXUL79u3Rvn17AMDcuXPRvn17LFy4EACQnp4ud0wIgiDYKol6HtqjnZZoSsY1wfbyA26TIOs0cG04F/8gh9Px2dwSbYhFzsjlEGXhw9OCMk6lz0CVDovqR8d2vmWdTENUdEmSvebC2xnp1asXGIap9rdlyxYAwJYtW3Dq1CmN2y9evJjUVwmiVqI7vG7uO2Cuk9u2OO03WIolqixVTpjmUlW+uSXaIi2LhgfzUUHnhKujnfyxRMogNjlL3n1Y0WHkU8JtiIouSbLXXKg3DUEQJkVTToY2jHkHbIwqGW3oLh1WfueMQitcPrklYU191DYYVEy0fZhdzNd8rbzSviEA3Qm+fEq49VHRJUn2mg85IwRBmAxtd8zaMNYdsK5J1Jjy8qr5FJqcsCf5ZfLE2P7B/jqrUBQjLrqqhXyNGDlwdbRD1+a+nBJ8yyqlnPb5tKBUq/y6OkiSvXZgFgVWgiBqJ3yTFdUtd+gLFxl6Q+XlAeVIBwvXZQsAGNFWe/XQiLZipUlYm4y9vwc3ZySydzPM6ddc65hvXm8rt1PX+3iaz61xHutkalJb9XR1qKZcS5LstQOKjBAEYTL4LLcY8w5YlzOgWCrKVoFsOpsCNX6FThQjHVwrRthli7jkLOy/qr16aP/VdHw0qDWnc8LK0OtqJDenfwvYCQVo6e+ORfsS8aSgKvG1nrsjlowMwaAQMWKTszi9jy8P39Rpm6IOC6A5ygPA6MqqhPVDzghBECaDz3ILV6VULvDJYcgrKdfYjZcL6nQwuDphsfczdUaOdMnlK+bE+Lrp1mdSnNZ1LfsYM3dHUYeFRZMmDCmr1j7IGSEIwmRwycnwdHXA+rEdEMqhfJQrXCfRjPxSrIy+ZXARimqPHe5OGLf3G3MvU22EQF1OjC5yiiuUnBttInHGrl7R17nRloRM1AwoZ4QgCJOhS29DAFnL9/DmvkadXDiLhBWW8Rbg0gZf0TOuEYB1J++h24oTSoJwmnJi+NipCy7dh/mgj3MTnZiObitOYOymOMzalYCxm+KqnQvC9iFnhCAIk8K1Nbwx4eoMcJVZ5wpf0bPQJj5a7VREMfFW3yolVTvNhb6JyVySkImaATkjBEGYnEEhYpyb1wc7p4Zylhc3BK7OgL/IhdP+Ph3SGp4umiME2kTPtDlhfKp5FKtX4u5rTyzlY6c2uHQf5nJMgH9iMh8hNcL2oZwRgiDMgrlbvrPOgGpOhWKibHmllFM33kldAxHg7YLpz7vrKg7XNtly6SKsyU51sLkpsclZXE6BEvo4BcZIYNU3MZlPEjIlvNo+5IwQBFFj0eUMxD/I4dyNl4tzow4uThhr5+qjt7HuZDKHd8Y/GqCPU2DIcs6U8ED0C/bXO9mUqyNE/WpqBuSMEARRo9HmDPCd8LhEOgyxM7xZXU7OSFgTX/zv8iONVUoCAPU8nPD16+2QWVimt51cqqFUI0tiI5Vo85HKJ2wfckYIgqi16DPhmXK5Sdfkz/ZoCW3qo1FSnXU3Fo94AeHNfA2yR5t0O3ucdWM7wMvN0ejOGddzQf1qagaUwEoQRK2Fa9WNuSY8rom3dkKB2aqUdB1nyItijfL0hsDnXBC2j4BR11jBysjPz4dIJEJeXh48PDwsbQ5BEDUItnwUUH/nb4m+KLoa/CliLkEwSwmP8TkXhPXBdf4mZ4QgiFqPNU54pDpaBZ0L24WcEYIgCB7QhEcQxofr/E0JrARBEDC/DgpBEFVQAitBEARBEBaFnBGCIAiCICwKOSMEQRAEQVgUckYIgiAIgrAo5IwQBEEQBGFRyBkhCIIgCMKikDNCEARBEIRFIWeEIAiCIAiLQs4IQRAEQRAWxSYUWFnF+vz8fAtbQhAEQRAEV9h5W1fnGZtwRgoKCgAAAQEBFraEIAiCIAi+FBQUQCQSaXzdJhrlSaVSPH78GO7u7hAIqHFVfn4+AgIC8PDhQ2ocaCbonJsXOt/mhc63ealN55thGBQUFKB+/foQCjVnhthEZEQoFKJhw4aWNsPq8PDwqPFfZGuDzrl5ofNtXuh8m5facr61RURYKIGVIAiCIAiLQs4IQRAEQRAWhZwRG8TJyQmLFi2Ck5OTpU2pNdA5Ny90vs0LnW/zQue7OjaRwEoQBEEQRM2FIiMEQRAEQVgUckYIgiAIgrAo5IwQBEEQBGFRyBkhCIIgCMKikDNiY3z55Zfo2rUrXF1d4enpqXZMWloahg4dCldXV/j5+eHDDz9EZWWleQ2tQaxfvx6BgYFwdnZGly5dcOHCBUubVGM4c+YMhg8fjvr160MgEOCvv/5Sep1hGCxcuBBisRguLi7o168f7t69axljbZyoqCh06tQJ7u7u8PPzw6hRo3D79m2lMaWlpYiIiICPjw/q1KmDV155BU+ePLGQxbbPhg0b8OKLL8rFzcLCwnDkyBH563S+qyBnxMYoLy/Ha6+9hunTp6t9XSKRYOjQoSgvL8e///6LX3/9FVu2bMHChQvNbGnN4Pfff8fcuXOxaNEiXL58GW3btsXAgQPx9OlTS5tWIygqKkLbtm2xfv16ta+vXLkS3377LTZu3Ijz58/Dzc0NAwcORGlpqZkttX1Onz6NiIgIxMXF4ejRo6ioqMCAAQNQVFQkHzNnzhwcOHAAu3fvxunTp/H48WOMHj3aglbbNg0bNsTy5csRHx+PS5cuoU+fPhg5ciRu3LgBgM63Egxhk2zevJkRiUTVnj98+DAjFAqZjIwM+XMbNmxgPDw8mLKyMjNaWDPo3LkzExERIf+/RCJh6tevz0RFRVnQqpoJAGbv3r3y/0ulUsbf359ZtWqV/Lnc3FzGycmJ2blzpwUsrFk8ffqUAcCcPn2aYRjZuXVwcGB2794tH3Pz5k0GABMbG2spM2scXl5ezE8//UTnWwWKjNQwYmNj0aZNG9SrV0/+3MCBA5Gfny/3xglulJeXIz4+Hv369ZM/JxQK0a9fP8TGxlrQstpBSkoKMjIylM6/SCRCly5d6Pwbgby8PACAt7c3ACA+Ph4VFRVK57tVq1Zo1KgRnW8jIJFIsGvXLhQVFSEsLIzOtwo20SiP4E5GRoaSIwJA/v+MjAxLmGSzZGZmQiKRqD2ft27dspBVtQf2+6ru/NN32TCkUilmz56N8PBwhISEAJCdb0dHx2q5aHS+DeP69esICwtDaWkp6tSpg7179yI4OBgJCQl0vhWgyIgV8PHHH0MgEGj9o8mPIAhjERERgcTEROzatcvSptR4WrZsiYSEBJw/fx7Tp0/HpEmTkJSUZGmzrA6KjFgB77//PiZPnqx1TJMmTTjty9/fv1q1B5ud7e/vr5d9tRVfX1/Y2dlVy25/8uQJnUszwJ7jJ0+eQCwWy59/8uQJ2rVrZyGrbJ/IyEgcPHgQZ86cQcOGDeXP+/v7o7y8HLm5uUp36/R9NwxHR0c0a9YMANCxY0dcvHgRa9euxRtvvEHnWwGKjFgBdevWRatWrbT+OTo6ctpXWFgYrl+/rlTtcfToUXh4eCA4ONhUb6FG4ujoiI4dO+L48ePy56RSKY4fP46wsDALWlY7CAoKgr+/v9L5z8/Px/nz5+n86wHDMIiMjMTevXtx4sQJBAUFKb3esWNHODg4KJ3v27dvIy0tjc63EZFKpSgrK6PzrQJFRmyMtLQ0ZGdnIy0tDRKJBAkJCQCAZs2aoU6dOhgwYACCg4MxYcIErFy5EhkZGfjss88QERFBHSL1YO7cuZg0aRJeeukldO7cGWvWrEFRURH+7//+z9Km1QgKCwtx7949+f9TUlKQkJAAb29vNGrUCLNnz8YXX3yB5s2bIygoCAsWLED9+vUxatQoyxlto0RERGDHjh3Yt28f3N3d5XkJIpEILi4uEIlEmDJlCubOnQtvb294eHhg5syZCAsLQ2hoqIWtt03mz5+PwYMHo1GjRigoKMCOHTtw6tQp/P3333S+VbF0OQ/Bj0mTJjEAqv2dPHlSPiY1NZUZPHgw4+Liwvj6+jLvv/8+U1FRYTmjbZzvvvuOadSoEePo6Mh07tyZiYuLs7RJNYaTJ0+q/T5PmjSJYRhZee+CBQuYevXqMU5OTkzfvn2Z27dvW9ZoG0XdeQbAbN68WT6mpKSEmTFjBuPl5cW4uroyL7/8MpOenm45o22ct956i2ncuDHj6OjI1K1bl+nbty/zzz//yF+n812FgGEYxvwuEEEQBEEQhAzKGSEIgiAIwqKQM0IQBEEQhEUhZ4QgCIIgCItCzghBEARBEBaFnBGCIAiCICwKOSMEQRAEQVgUckYIgiAIgrAo5IwQBEEQBGFRyBkhCIIgCMKikDNCEARBEIRFIWeEIAiCIAiLQs4IQRAEQRAW5f8BkCZK8TFN750AAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Better, but not good enough."
      ],
      "metadata": {
        "id": "a-7NM43HqcYr"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Third Experiment:\n",
        "\n",
        "*Polynomial Regression*\n",
        "\n",
        "Ploynomial degree = 3"
      ],
      "metadata": {
        "id": "ov4hebqxqevb"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "polFea = PolynomialFeatures(3,include_bias=False)\n",
        "print(\"Polynomial degree = 3\")\n",
        "X_poly = polFea.fit_transform(X_train.values)#.reshape(-1,1))\n",
        "model = LinearRegression()\n",
        "model.fit(X_poly, y_train);"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EibcNBvQqk8B",
        "outputId": "af067331-a953-4c8e-83d8-83e1507bcc17"
      },
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Polynomial degree = 3\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pol3 = print_eval(polFea.transform(X_test), y_test, model)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "q-Rbusvzqx7r",
        "outputId": "83ece757-f003-42b4-b848-669d47b87dbb"
      },
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            " Mean squared error: \t0.021749\n",
            " r2 score: \t\t0.822\n",
            " f-statistic: \t\t502.32\n",
            " p-value: \t\t1.1102e-16\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Visualize the prediction\n",
        "\n",
        "pred3 = model.predict(polFea.transform((np.arange(min(X.temp), max(X.temp))).reshape(-1,1)))\n",
        "plt.plot(np.arange(min(X.temp), max(X.temp)),pred3, label = \"poly\",color=\"red\")\n",
        "plt.legend()\n",
        "plt.scatter(X,y)\n",
        "plt.plot();"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 430
        },
        "id": "7wedJh81q0gY",
        "outputId": "190c0efc-e0e7-4f2b-ca03-3f22ca9057e4"
      },
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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x3Y2+LwGgkHuhT0yQ9QdpQAQ1ytu7dy8SExPRu3dv1NfX44033sCIESOQkZEBX19fo9vU1tZi+PDhCA0NxW+//YaWLVsiJycHAQEBYoyfIAiCIJwSpYrDkaxiXC+vRqifl0Hn3OvWdu3lOAzKMp0v4oq9aQQZI8nJyTqvV65cidDQUBw7dgyDBg0yus3333+P4uJiHDp0CB4eHgCA6Oho60ZLEARBEC5AcnoeFm7J0CndVci9sGBcrKZnTLGVxkjUzTxElBagVuqOwxFxBu+H6R3HFRBkjOhTWloKAAgKMu0G2rx5M+Lj45GYmIhNmzahefPmmDx5MubOnQs3NzdbDk8QBEEQTgevqqofhckvrcbzq49j1rD2iA7xQZGV1TQDb3tFjrXqBP+QAPz33lgE+spMemBcAauNEZVKhVmzZiEhIQFxcYaWGc+lS5ewa9cuTJkyBdu3b8fFixfxwgsvoK6uDgsWLDC6TU1NDWpq7liMZWVl1g6TIAiCIBoMc6qq/LIlO8/bdIxBt0t690d3ByCBVCpBfJtgm/bpaKyupklMTER6ejrWrVtndj2VSoXQ0FB888036NmzJx555BG8+eab+Oqrr0xuk5SUBLlcrvmLiIiwdpgEQRAE0WDYqqpqCXdlPeJzTgBQ54sUlKm9La7UodcYVhkjM2fOxNatW7F79260atXK7LoKhQLt27fXCcl06tQJ+fn5qK017qKaN28eSktLNX+XL1+2ZpgEQRAE0aBY2/COlW555+BXW4Vib3+cbtFa421xpQ69xhBkjHAch5kzZ2LDhg3YtWsXYmJiLG6TkJCAixcvQqVSaZadP38eCoUCnp6eRreRyWTw9/fX+SMIgiAIZ8fapFRW+HyRA9HdNBLwrtah1xiCjJHExESsXr0aa9asgZ+fH/Lz85Gfn4+qqjv6+tOmTcO8efM0r59//nkUFxfjpZdewvnz57Ft2za8//77SExMFO9TEARBEIQTEORr/CFbLPiSXnW+iC7aaqtKFYeUzCJsSruKlMwip/eaCEpgXbZsGQBg8ODBOstXrFiB6dOnAwByc3Mhld6xcSIiIvDnn39i9uzZ6NKlC1q2bImXXnoJc+fOtW3kBEEQBOFkhMm97bZveVU5uuRfAGDcGOHVVlnKip0NQcYIx1m2rPbs2WOwLD4+HqmpqUIORRAEQRAuR5+YICjkXnZJYu2fcwJunArngyOR7x+iWS6BWlukT0yQxbLiZY/1cEqDhHrTEARBEIRIuEklWDAuFvZQ+eC79GpLwEugzhl5tHcENqddxRsb0s2WFTtroisZIwRBEAQhIqPiFFj2WA8o5LpN6gJ8PBDg42HdTrUk4LVDNPLb+1yy8wJm/3ICxWaE1Jw50dUmBVaCIAiCIAwZFafA8Ngwg940ADTLzuWV48u9mUz7iym5hlZl11Hj5o4hMx7A/aGByC6sxKc7zwvut6ed6OoskDFCEARBEHbAzYQyKr/su/JLzPsaeLtL76moznhs2F0AgAGLd1nV+JdPdHUmyBghCIIgCAcgpAyYl4BvNm40jmQV4+DFQsFJstqJrs4GGSMEQRAEYQdq61VYlZKNnOJKRAX5YGp8NNykEk2Yxlx+hzYeyjrE554CACQpI7B3ufDqVD6hdsG4WKdsokfGCEEQBEEIQKniDHJB9Cf4pO0ZWL4/C9qFK+9uOwMfTzdU1CoFHa/7tXPwra1CoY8c+3xaWjXmsMakM0IQBEEQTZnk9Dy8s/k08svuyL6H+cvwzvi7NBN90vYMfL0vy2BbDhBsiADGJeBZ8JW54d0JnRHmb9xgciaotJcgCIIgGEhOz8Nzq4/rGCIAkF9Wg+dud86trVdh+X5DQ8QWBmark1f3R/cQtJ2nmxTju4Yjvk2wUxsiABkjBEEQBGERpYrD6+tPmV3n9fWn8MOhbIipKRZQVYYueRcBAPujuwnatqSyzik1RYxBxghBEARBWCA1swg3K+vMrnOzsg5HsopEPW5C9glIweFsSBSu+xmWCVvCGTVFjEHGCEEQBEFYIOVSIdN6lVbkhJjDmAS8EJxRU8QYZIwQBEEQhEXYci66tJJDtPQMjtMkrxrr0msOCdSdep1RU8QYZIwQBEEQhAWMKakaY0C75pgxMEaUY7YpvoKW5TdQ4+aBIxF3CdqWg/NqihiDSnsJgiAIwgL9WgcjwMfDbN5IoI8H+rUORkLbEAAw0BmRAIJ0RnivyJFWd6Ha4064Zf7YTgjxkyG7sAJLdl4Q/mGcEDJGCIIgCMICblIJHunVyqh+CM/DvVppPBHzxsTi5REdzSqwFpbXYNG2Myb3ZyxfRCH3wvQEtedlwOJdJreVAFi4JQPDY8NcwjtCxghBEARBWECp4rD5RJ7ZdX49dgUdFXIdkbHYcDlC/GQI9fOCm1Si0zxPqeLw7YEs5JdWGzS886yvQ3zuSQC6xkhcS3+4SSVIySwy25uGA5BXWo0jWcXMISZHQsYIQRAEQVjgSFaxxcZ0xRV1mP1zGgAgwMcDAHTCOgo9SXY3qQQLxsXiudXHDfbV49oZ+NTV4IZvAM42j9Ys//vMddTWq5hLdqm0lyAIgiAaCUIn9ZuVdQb5Jfml1Xj+tlKrJe6+xKuudteRgFdxwKqUbOaSXSrtJQiCIIhGghiTOh+KWbglA0oVB6WKw8ItGUbXvefiEQDA7ta9DN7LKa5En5ggKOTmx0SlvQRBEATRiOgTE6QJvdiCdi6HqdBPxM18tC/KRb1Eir2texq8HxXkAzepBOO7mu/AO76rwiWSVwEyRgiCIAiiwfkjPQ8HLt4w+h7vFfkn4i6UeTXTeU8qAabGRzMl1G4+kQelmI1y7AglsBIEQRCEBY5kFVvsTSOEH1NyTL43NPMfAMDfbXobvBfX0h+e7lKL1TSAa1XTkGeEIAiCICzQUFUpzWoq0S9X3R3477Z9Dd5Pv1pG1TQEQRAE0RRpqKqUgVnH4amqx6XAcGQFtTR4n6ppCIIgCKKJwlev2Dsd9B4+RNO2j8l1coor0TMq0GJDPqkE6BkVKObw7AYZIwRBEARhAV6gDGDt33uHMH8Z03pSlRJDbhsju9qYNkaignxwLKcElnJTVRxwLKeEeZyOhIwRgiAIgmBgVJwCyx7rgRaMxgVPflkN03rd8s4juKoMZTJf/NMq1ug6ktvVNJQzQhAEQRBNGvsEa/iS3j2te6LezXixq4+HG9ykEsoZIQiCIIimSHJ6Hp5ffRz5ZfbxNpgr6eWpqFXiSFaxxRwWCUiBlSAIgiAaFbx0u70kxFqWXkenG9lQSqTYY0QCXpv80iqzOSz86wXjYkmBlSAIgiAaCyxde21haKY6RHO0ZSeUevuZXbe4ohbAnRyWML0eNWFyLyyd3ANyb09sSruKlMwip1diJQVWgiAIosmhVHE4klWM6+XVCPVThzPMeRHsnQg67Ha+iLmSXp6gZncSaEfFKTA8Nkzns5RU1GDRtgwd40kh98KCcbEYFWe+n42jIGOEIAiCaFIkp+dh4RZhk7U9E0F9ayrRL/ckAOBvMyW9PGH+umNxk0o0ku/J6XlIXPOvQTgpv7Qaz68+jmWP9XBKg4TCNARBEESTgU9C1Q+58JN1crrx5nMsImPWMiAnDTJlPbIDFMgMbmV2XXNJqebyWvhlC7dkOGXIRpAxkpSUhN69e8PPzw+hoaGYMGECzp07x7z9unXrIJFIMGHCBKHjJAiCIAibsGWyZhEZsxa+pHdXm95qIREjSG7/mUtKtZTXwuFO8zxnQ5AxsnfvXiQmJiI1NRU7duxAXV0dRowYgYqKCovbZmdn45VXXsHAgQOtHixBEARBWIstk7W9ckYknApDMo8CAHaayRcJk3tZDLG4shCaoJyR5ORkndcrV65EaGgojh07hkGDBpncTqlUYsqUKVi4cCH279+PmzdvWjVYgiAIgrAWWyZre+WMdM27gOaVN1Hm6YN/Iu4yus4Lg9vg5REdLJbpurIQmk05I6WlpQCAoCDzoir/93//h9DQUDz11FNM+62pqUFZWZnOH0EQBEHYAuskfKGg3KActk9MEAJ8PEQf09DbIZp9MT1Q52Z8/wPbNWfSC3FlITSrjRGVSoVZs2YhISEBcXFxJtc7cOAAvvvuOyxfvpx530lJSZDL5Zq/iIgIa4dJEARBEADYO+9+sTsTk5anYsDiXSYTWsViWKb5kl4hxoMrC6FZbYwkJiYiPT0d69atM7lOeXk5pk6diuXLlyMkJIR53/PmzUNpaanm7/Lly9YOkyAIgiAACO+8q11hcySrGDcr60QdT3jZdcRez7qtutrT6DrjuyoEGQ/mhNCctawXsFJnZObMmdi6dSv27duHVq1MlyFlZmYiOzsb48aN0yxTqVTqA7u749y5c2jTpo3BdjKZDDKZsK6IBEEQBGEJfrLW1xkxBh+keWPDKYztHC76WIbeTlw9Ht4RJT5yo+tsPpGH10Z1EmyQ6AuhWRJ1czSCjBGO4/Diiy9iw4YN2LNnD2JiYsyu37FjR5w6dUpn2VtvvYXy8nJ89tlnFH4hCIIgGhztyfrgxUJ8sfui2fWLK+qwKjVH9HHcc/EwAGBXW9ON8fjqHl7UjBVtITRXQJAxkpiYiDVr1mDTpk3w8/NDfn4+AEAul8Pb2xsAMG3aNLRs2RJJSUnw8vIyyCcJCAgAALN5JgRBEARhT/jJ2lFlrt611eifo1Zd3WlBddUZS3HFRpAxsmzZMgDA4MGDdZavWLEC06dPBwDk5uZCKiVhV4IgCMJ54XvTXCi45ZDjq1VX63BZ3gIXQiLNruuMpbhiIzhMY4k9e/aYfX/lypVCDkkQBEEQomKsN409mdI3En+k56G44k4CLF/Su7NtH7Oqq2FOWoorNuTCIAiCIJoMpnrT2JN7u4TjoZ53ij0knAr3ZP4D4LYEvBGcvRRXbMgYIQiCIJoE5nrT2IsAHw/0jArE5hN39Eri8jMRWlGCW57eOBzRGQAMmvA5eymu2FhV2ksQBEEQroal3jT2oE6pwj96xx3Gq65Gd0etu1p1VcUB88d2QoifzCVKccWGjBGCIAiiSeCIqpSKGiVWHMrSWTbiQgoAYJee6mqInwz3dWvZYGNzJihMQxAEQTQJHFWVsvPMdc3/Y4qvotONbNRJ3bCjbV+d9ZpC1YwpyBghCIIgmgQ9owKZZODtyehzBwEAKZFdUOrtp1ke6OPRJKpmTEFhGoIgCKJJ8E9WcYMmrxqDN0a2dRygs7y6TonUS0UovFUjOGeE10xxFel3Y5Axokdj+FIJgiAIQ1IuFTr0+BE389G5IBP1Ein+atdP572qOhWmfHtY81oh98KCcbEWq2mMaaawbutMkDGiRWP5UgmCIAhjOPbBkveKpEZ2NtkYj4fvGGyuvJfXTNH39rBs62xQzshtTAnhaLeQJgiCIFwX1sZx/Vuz5W5M6KrA2hn98OXk7gjzt9xpfsxtY+SPDgkW1+UNjIVbMqBUGQaXzGmmWNrWGSFjBI3vSyUIgiAM6dc6GAE+HmbXCfTxwHfT+1j0oUgAfPhQN8S3CcaYLuE4+Po9WDujHxJMGDwtS6+jW955qCDBn+3jmcbL4U7XXn0saaaY29YZIWMEje9LJQiCIAxxk0rwwcTOZteZ3j8Gf2XkY2wX8+GNZwbFwNP9zhTKdwF+oEcro+uPuu0VORJxFwp9AwWN25g+Cqtmiqt0/KWcETS+L5UgCIIwzqg4Bb56rAfe2ZyB/LI79/RAHw9wAJbsPK9Z5uPphspapcE+nh0Ug3ljYo3uXxHgbXQ5H6LZzhCi0aewvAZKFadTTMGqSeIq2iVkjKDxfakEQRCEaUbFKTA8NkxTOZldWIElOy8YrGfMEAnz90L3SNOejT4xQVDIvXS87WFlheh57SwAILl9f8HjXbTtDL49kKVTTMEfJ7+02miKgat1/KUwDe58qaZihBKoq2pc5UslCIIgzMOHVe7tEo51/1xm3q6grBrPrT6Oz3aex6a0q0jJLNLJJ3STSrBgXCwkuFO7M+r8IQDAPy1jcd2PLYlWH/1iCv44gGGNkCt2/CVjBI3vSyUIgiDYENo8jzc7luy8gJfWpWHS8lQMWLxLp+JyVJwCzwyKgeT2lDFaQBWNpeNqF1OMilNg2WM9ECbX9dq7YsdfCtPchv9S9XVGwkhnhCAIotEiRi6gvq5HcnoevtmXBQ5A81vF6H0lAwDwRwfhIRpttIsp+DJl/ZCTq4p1kjGiRWP5UgmCIAjz1NarsColG4dFqJLkoPaiv7khHRU1Sry3/Y5UxMjzKZCCw/HwDsjzb27zsQBDA4oPObkyZIzo0Ri+VIIgCMI0SdszsHx/FsSUjuIAFFXU4uVfT+gst6WKxhSNsZiCjBGCIAiiyZC0PQNf78tqkGMFV9xE38vpAIBkkYyRxlpMQQmsBEEQRJOgtl6F5fsbxhABgBEXUuHGqXAirB2uyFuIss/xXRWNMnWAPCMEQRBEo0W7E/vR7GJRQzOWEKOKRp/NJ/Lw2qhOjc4gIWOEIAiCaJQkp+cZKK02FIGVpeifo84fsbWKRhv9aprGAhkjDkDbUherYsce+yQIgnBVktPz8Nzq4w47/vALh+HOqXA6tDVyAsNF3XdjbE1CxkgDk5yeZ6BlorBRy8TUPueP7YRAXxkZKARBNCmUKg6vrz/l0DHYo4qGh6ppCJtITs/D86uPG/QR0BfMEWOfeaXVeGHNvzrLbDV6CIIgXIHUS0W4WVnnsOP7V99CQk4aAGH5IvNGd8SyPZm4WWV87K7Wb0YIVE3TQChVHBZuyTDa0MiYzK+t+zSGfm8DgiCIxkhKZpFDjz/8wmF4qJQ40zwal4JbMW9XXl2HDx7orNPXhqextyYhY6SBsNT/QFvmV6x9GjsGINzoIQiCcC3Ev791bunPvO7ocwcAWFNFI7HYb2Z4bBhSMouMNulzZShM00CwJhwJSUyyJonJWG8DVihJliAIVyC+dQi+2J0p6j5PXS1jWs+vpgIDs9UhcqH5Ipb6zezIyMeAxbtEzTl0FsgYaSBYE46EJCbZksQk1JCxR+ItQRCEPejXJhgBPh4OyRsZevEIZMp6XAiOwMWQSObtAn08AA7YlHZVY3xoPzDaI+fQmaAwTQPRJyYICrmXQRyQRwLhMr+W9mkOIYYMfxHoh4QoB4UgCGfETSrBBxM7O+TY1lbRcACmfHcYL61Lw6TlqRiweJfm3mqPnENng4wRO6NUcUjJLMLWk9fwaG+1lSxWYpKbVIIF42KN7tMUQo2epnAREATR+BgVp8BXj/VAmL+swY7pX30Lgy8dA8CeLxLo4wEABl4c7Yc9e+QcOhsUprEjxkIbAUZ+eGE2hDv4ZCf94xjDGqNHyEXQ2BQBCYJwbUbFKTC0YwusSslGTnElVCoOqw/n2u14o88dhExZh3MhkTjbPNrgfQnU98zZw9ohOsQXIc1kePmXNKP74m6vv3BLBl4b1ZHp+K4shkbGiJ0wFd8rrazT+TGKkQhqLNmppKIWi7bpGijWGD32SLwlCIJoCIw9ENqTiad3AwA23DUUkBje0/XvwSmZRcgvqzG5P/5hr/iW6XW0cWUxNEHGSFJSEtavX4+zZ8/C29sb/fv3x+LFi9GhQweT2yxfvhw//vgj0tPVbZR79uyJ999/H3369LFt5E6MpdCGBMC6fy7jwNyholWjuEklBp6JkXGG2dhCj2ePxFuCIAh7Y+qB0F60Ki1A38vpUEGCjbGDNcvNPXiyPsQF+XpCIfdCfmm10c/TGMTQBOWM7N27F4mJiUhNTcWOHTtQV1eHESNGoKKiwuQ2e/bswaRJk7B7926kpKQgIiICI0aMwNWrV20evLPiLPE93kC5r1tLxLcJtsrwsUfiLUEQhD0RKggpBved3gMASInqjHz/EAB3Hjzv7RKuuQfzeYSb0q6isJzN4xEm9zaZH9hYxNAEeUaSk5N1Xq9cuRKhoaE4duwYBg0aZHSbn376Sef1t99+i99//x1///03pk2bJnC4rkFjCm3wSbLPrz6uiXfyNJaLgCCIxoNSxWHlwSxRQjPGcvyMwnG6IRp+MXRz6oyFjaQSwFz+P/+w5yaVGM0PtCXn0JmwKWektLQUABAUxP5UXFlZibq6OrPb1NTUoKbmjsVYVsYmNuMsNLbQhqkk2cZyERAE0TgQI0fEy12KpImdESb31nh8j2QVI7+0CvM3ncatmnqDbbrkX0Cb4iuocpfhj/b9Dd6/Xl5tMmxkqRBxfFeF5mHPlBhaY3gYtNoYUalUmDVrFhISEhAXF8e83dy5cxEeHo5hw4aZXCcpKQkLFy60dmgOhw9tNKb4XmO+CAiCcH3EyhGprlch1M9LJweP///29DzsyLhusM39t70if7XrhwqZj8H7Ib4yvPLbCavGtvlEHl4b1UlzrzWWH9gYsFpnJDExEenp6Vi3bh3zNh988AHWrVuHDRs2wMvLtFdg3rx5KC0t1fxdvnzZ2mE6BHP6H64c2hAjB4UgCEJsxM4RSblUaLCstl6Fv88YGiLuynqMO7MPALDhriEG76vDMJzV3hpX1w9hxSpjZObMmdi6dSt2796NVq3YOhL+97//xQcffIC//voLXbp0MbuuTCaDv7+/zp+rYanZEYU2CIIgxEFo01BLGAudrErJNrp8UNZxhFSW4oZPAPbHdDe6r8M2GhOukF9oK4LCNBzH4cUXX8SGDRuwZ88exMTEMG334Ycf4r333sOff/6JXr16WTVQV4RCGwRBEPZH7Mk60MfTYFlOcaXRdfnE1S2dBkEpdTOxR9t8Nq6SX2gLgoyRxMRErFmzBps2bYKfnx/y8/MBAHK5HN7e3gCAadOmoWXLlkhKSgIALF68GG+//TbWrFmD6OhozTbNmjVDs2bNxPwsTkljje8RBEE4Eu0u4qwlsqyE+BlKyEcFGeaC+NVUYPiFVADA+rihBu/z9I0Oxu/yqybzCM3RVKQTBBkjy5YtAwAMHjxYZ/mKFSswffp0AEBubi6kUqnONrW1tXjwwQd1tlmwYAHeeecd4SMmCIIgmjTWlMgKIcz/jieCN3oCvD0gkQCc1jFG3ZZ/vxAcgfQWbUzuT+pmWiLBEtrVNI0ZwWEaS+zZs0fndXZ2tpBDEARBEIRJrC2RZSXY1xP5pVVIySxCSUUNFm07YzIf5Y62yBCj8u88hbdqcF+3lkYlEiwZUfrVNI0V6k1DEARBOA3a4Rf9PDuWqhlbPSRFFbWY/csJi+uFl11HfO4pAMDGuwabXTekmTrso59HWFiuNnbM0VQakZIxQhAEQTgFxsIvCi1xRZaqGRUHTO0XiVWp9uvOCwATePn3yM645h9qfmUt40g7j3BTGltblKZQTWO1zghBEARBiAUfftE3NvJLq/H86uNITs9jnpR7RAaa7allMxynETpbb0RbRJ/CCuMJto1NrdsWyBghXALt5lIpmUVQihUgJgjC4VjqdA4AC7dkIMjbsOTWGKF+XiaFJ8UgriAT7Youo9rdE390GMA0HmPwat3moGoagmDAXHxXLCy5bgmCcG1YO53//u8Vth1KTPfUEoOJ6bsAADva9sUtI/Lv2pgzJtykEozvqsDX+7JMbk/VNAShh77hUVJRi0XbDI2E+WM7IdBXJoqBYipznnfd6qvZNoRxRBCEuLCGXzamXWNar/CWOixiTcKoJdxUSo38uzltEZ5eUQHYevKa0fuRUsVh84k8s9tTNQ3RpDE0PMyXuPHklVbjhTX/6iyz1othyXUrgdp1Ozw2DG5SCXlQCMJFETsnQnt/2gmjShWH/+2+iJuVdVbve2DWcTSvvIlCHzn2RxvKv+uz5WQ+tpxUi33q349YEnKpmoZosojRhlsbU14MS7C6bo9kFaO0qlaQB4UgCOfBUqdzIUglQM+oQJPv19arbNq/tvx7vZuwKVT/fsTqEaJqGqLJYSqj3Ra0E9CEJJ6yXoD5pVVMyW9iJr1SQi1BiIe5TudCUXHAsZwSo++lXipCZa3S6n03q6nEiNvy78Y69FqCu/3H34+omuYO5BkhNIjdhlsbbS+GJXcjHyK6UFDOtO/iilpmD4oYrk4KBxGE+IiZcGrqQebgxUKb9jvq/CF41dciM6gVToa1s3o//P3IkkdIAnWnd6qmIZoUYrfhNoYlb4eQEBF/oQY1M2xqZc2xWRCaUEsQBDvaCacHL97AF7szrdqPtidBO//txOWbNo3v/tPqKpr1FuTfWcgvq9Z4hIz1rOH3vmBcbKNPXgXIGCG0aIi4pDl3o6mJ3hjaF6pcgPaALQhNqCUIQjh8wmmfmCB8fzBbUFhF35MgZv5beNl1xOeo5d83WZB/Z6FYq+LHmEcorIl5W8kYITSEMHoYrMVcYpnQEJH2hapUcQ3i6hSSUGvPzHcqXyaaAkoVh6o6YfkdHID5Y2NxJKsYOzLy8f3BbNHG88iJvyAFh0ORXXBF3sLm/QX53nmI0i9BborXNRkjxB3snIPJJ5YZm6hZQ0Qzh7RFQtsQnQu1oVydzpD5TvkqRFNhVUo2GBrFG/DGxlM2le4aw11Zj0dP/gUA+KnbaFH2GSb31nmtXYLcFKFqGkKDqf4JlniwRysMbBfCtK6piZp1Am/Xohni2wQbGBa8qzNMT1o5TO4lWh6HozPfWXp3EERjIae40qrtxDZEAOCezCNocasYN3wC8Ff7fjbvr6lIvAuBPCOEBmsn0d+OM0o0mzmGGBO9vV2djsx8p3wVoqkRFWReZr0hmZyWDAD4rfMw1Ll5aJb3jAzAsdybgvYlQdNJShUCeUYIDfxka49LRALzTwOWjm1pex7e1Xlft5ZGPSi2YE4Lwd6Z70LyVQiiMTA1PhrOMF9H3MzHwCy1qvSabqN03msV6G1sE5MoRPTUNjbIGHESnEFES0zhIW34fc0f2wlHsoqNfkZHTvRCaIhwkDGcIV+FIBoST3cpZgyMafDjBvt6YkrfSM3rSSeSIQWHfdHdcTkgTGfdVozemxGxoZg/thP2vjqEDBETUJjGCWjIpERLlRj26HQZJvfC+K4Kg942+p/RVUrcHJH57uh8FYJwBPPGqB9Qlu/PQkM9nxVV1KJ1iC8AwENZh4dO7gQA/NTdMHG1X0wwlu3JtDi2vzKu46+M6/j2QJZT3cucCQnHWZOv3LCUlZVBLpejtLQU/v7+ouzTWcojTWlr8CMR82lbiNHDn5/80ios2nYGJRW1gottpsVHYXScAiUVtUhcw/4ZbflunOV7FRulisOAxbss5qscmDu0UXxegtCmtl6FVSnZyCmuRGWNEr8dv2JQOScm/32wC177/SRGZ+zH0s2LUdAsCAnPfa/Ti0YqAX54og+mfn+Eeb/2uK87O6zzd5P0jDhLeWRDJiWaUw59bvVxzB7WDtEhvjoTOF9m5u3pZrRs1hKj4xToExOEAYt3CfqM1pa4Ocv3ag9IqZFoyni6S/HUwNaa18NiQw2u9QAfD9ysrBPFSDlx5SZUHDD5xB8AgJ87DzdoiqfigFWp2YL2S8nmpmlynpGG9ERYIiWzCJOWp1pcb+2MfjbVn/NP1axhF2MTuDUy7QfmDsWRrGKmzzhzSBsktG1utSfDmb5Xe9KYDS6CMIUxjycAg2U7MvJFCTFP6RuBQ3+kYvfyZ6GUSDHwuW9xzT9UjI+iwdr7uqt5f8kzYgRnK49sqKREoT1njPVZ0c+TyC6sxKc7z5t8AuGf0lnH/sXuTHyxO9PkxKrtpo0K8sHU+Gh4uqvzr53te7UnpNRINDWEGOD89fHyL2nYmHbN6mPmFFVi0u1y3j2te4puiADW3dcb88NIkzJGnEXOm6ehkhKF/uhZwyeVtXUGiWVSCTBjYIzmwhA6dmOGUNL2DIPjvLf9DGYMjMG8MbF2/16d7UmkqSs1Ek0HaxpTukkleKhXhE3GyD9n8/B5+t8ADMt5xULovbGxN+lsUsaIs5VHNpSIljXGjKUJPDk9D9/syzIYN8cB3+zLQvfIQIy6nTNi7jMaO662IfRh8hl8vS/LYD0VB83y2HA502dytScRZzOCCKIhscXj2a91sCaHxBpGnj+EoKoyXPVrjt2te1m1D1NYc19vCt7fJqUz4mzlkQ2lrWGLmJmxCdzShQGoLwylirNKu4Q3hA5dLMTy/YaGiDbL92chyMc+XXsdKb+enJ6HAYt3YdLyVLy0Lg2TlqdiwOJdJPlONBlsEfpzk0rwwcTOVh97yr+3E1e7joBK6iZo2+GdQjF7WDsA4t3Xm4LoYZPyjDhSztsUomlr1NYCV68CublATo763ytXAKUSbh4eWFtWi7/OF6PezQ11UnfUubmjXuqOOqkbin3kyApqiazAcJR6++ns1tgELjQsYq12ye/Hr1is31dxwNn8MlG+V21PREgzGd7ZfNohTyKN3R1LECzY6skeFafAV4/1wDubM5BfdmedQB8PlJjxmLQtzEXfK6dRL5Hi5y7DhQ0agK/MHS8Na48OYX6iaSY5m1ffHjQpY8RZyyMFJSXeugXs3QscOABkZ98xPK5dg7kWl9EAnmEYS7G3P7ICw5EV1BKF4VHoc6wSqOgAtGsHeKulj625MLQ/48GLhfhi90WL21fW1jMd53JJlc3fq5BqIcB++UVNwR1LECxY68nWD2/ue20IjuWUMFfd8H1o/m7bBwV+bA1AtWl5WyJezGRzZ/Pq24MmZYwAzqvyaTIpsb4eOHoU2LkT2LEDSEkB6kxY9Z6eQGQkEBWl/jcyEvDwgKq2Fj/uu4jqymp4qJTwUNbDXVUPD6USHqo6hN4qQUzxVShuFSGoqgxBVWXoee0skA7gr+8BAJyHByTx8cCwYWjdsRfclfUGdff66F8Y/GfsExOE349fMTvxK+Re6B0djL8yrps9BqBuqGXN98rftHZm5OO7g9kWj2MMsZ9EnC3JmiAcBYsnO8jXE/mlVUjJLDJpZPA5Xvd1a6lZpvtwdANf7M4EAMjqavCAJnHVUHGVhf5t7hgwYiWbO6NXX2yanDECOHl5JMcBmZlqw2PHDmDXLqC0VHedmBjgnnuAjh11jY/QUEBqmAZ0OLMI79RY1vrwqa1CdEke7qosQFThFSiuX0ZM8VXEFF9DYHU5sG8fsG8fOgM4IfNBSkQcDkZ1xYGobrgQEglI1OfP0oXhJpVgfFeF0cRUnvFdFXi8fzSS/jhjNlQjlagbagHCvlehnhBTiP0k0hTcsQTBgjlPNm6/LqqoxexfTgCAyYRVU+FNpYpDxrVS3Kyqg5+XO25V1+Peswcgr6nAZXkL7IvpLnjMgT4e6Nda/IcEZ/Xqi0mTNEYAJyyPrKkBfv4Z+Pxz4Ngx3fcCAoChQ4Hhw9V/bdoI2jXrxPXg3R0R7NtVrR+i3Z+K4xB1Mx8JOWl4kcuF4uhB+BYXY9jFIxh2US2FfN03EAeiu2Frp0HYF9PD7IWhVHHYfMJ8IubmE3l4bVQnzBgYY9ZomTEwRqM3woqpnAwh2OtJpCm4YwmCFSH5ZqYqZ7ST6vnwpjG5AACYnKZOXF3bdSQ4ifD6jun9o7H15DW7POA6q1dfLJqsMeI0XLsGfPUV8PXXwPXbIQkPD6B/f7XhMWwY0KsX4CYso1sb1olrZGwYXvnthOEkLZEgJ1CB3EAFdsu9cGDbBridPIFzq9ejZGsyumalI7SiBBNP78bE07tRExQCWf1U4PHHga5dDY7DIsLGhyJMNcri9Uz49wG2MlxzORms2PNJpCm4YwlCCNoez/yyaizaehrFFcJLdvl7yp5zBUYfcDpez0LPa2dRJ3XDr52FJ64CwJKdFzT/t4cEgFN79W2EjBFHcfiw2gvyyy/qvBAAaNUKSEwEnn4aCBGeOGUK1gkOErDlK+TcRHyPHujQoweU/12Ef87mof7QQbQ5+DfCtq2H7MYNYMkS9V+XLmqjZMoUoEULAMJDEfPGxOLlER1NKrAC7BUoQtVojWHPJ5Gm4I4lCKHwnuyUzCKrDBGey8WVJuUC+MTVP9vF40azQKuPwWOv6jen8+qLBBkjDUltLfDbb8BnnwFHtDo9DhgA/Oc/wIQJaq+IGawRwmKd4Apv1TB9DG1jwk0qQb/YcCD2IeDph4C6/wHJycAPPwBbtgAnTwIvvwy89howciTw+ONoETeA6TjaHh39RlnaCKlAEZprwRtq/32wKworanT6YqRkFtnl6aSxu2OJpokY3bj/sFFn5+d/co3moPnUVuH+07sAiKe4StVvwhBkjCQlJWH9+vU4e/YsvL290b9/fyxevBgdOnQwu92vv/6K+fPnIzs7G+3atcPixYsxZswYmwbucmzeDLz0krocF1BXvkyaBLz4ItCzJ9MubFEDZZngUjKLmMZhNuzj4QGMG6f+Ky5W58H8+COQmgps3w5s346+4eF4pctYfN1xOMplPga7EBqKEFKBIiTXQttQS2h3x1PVEKqsjdkdSzQ9bLlmxEo2B4DyGuNyAfef3g2/2ipkBSqQEtXF5uPwUPUbO4KMkb179yIxMRG9e/dGfX093njjDYwYMQIZGRnw9fU1us2hQ4cwadIkJCUl4d5778WaNWswYcIEHD9+HHFxcaJ8CKfm0iW1EbJ1q/p1WBjwwgvAM89owhYsiCGEZWmCEytfQecJaMTD6PPsc3C7cB5YtQpYsQKSa9cw89pyTNu9Bqu7j8aKnuNxo1mQ5hiAsFCEkLDPvV3CoZB7Md3YjHkiGlKQrLG6Y4mmhdBrRvv+Yakhp1AiA71xvuCWzjIJp8JT/2wEAPzY416rElctQdVvlpFwnBmlLAvcuHEDoaGh2Lt3LwYNGmR0nUceeQQVFRXYyk/GAPr164du3brhq6++YjoOawtip6K6GvjwQyApSf1/d3d1uGL+fMCE4WYKpYrDgMW7TE6gvJFwYO5Qm5+c+RsHYDycY2mytfgEVFsL/PST+tycPQsAqHFzx+9x92B5n4mojmkj2MOQklmEScstly7zLbuTtmeYrdC5p2NzPD2wjYEnoiG/B4JoDAi9ZsT0ghjj1eHt8PHOCzqhmuEXUrF8/bsolfmi//MrUGHEW2sr/L2nKcI6f9tkApbe1r8ICjL9pJySkoJhw4bpLBs5ciRSUlJMblNTU4OysjKdP5fijz+AuDhgwQK1ITJ0qDp34oMPBBsiAHsYYuXBLGxKu4qUzCIoTYhzKFUcUjKLTK7Hh3PC5LrhjDC5F5MhYqyXS552LxdPT+CJJ4DTp4FNm8D17w+Zsh6TT/yJXd8+h0NHl2FU5WULZ0QXS713JFAbRH1igpjKijPyyo2GRJpCfwiCEBMh14yp+4eYfLTjAtzddKe9p49sAAD81H206IaI9r2HMI/VCawqlQqzZs1CQkKC2XBLfn4+WuiFI1q0aIH8/HyT2yQlJWHhwoXWDs1x5OQAs2YBGzeqX4eHA598Ajz8sEYQzBpYXXyLtp3R/F8h98L8sbEI9PXUhGRKKmqxaJvluK01+QqWSmY56CVySaXA+PGQjB+vlrb/8ENItmwB1v+u/hs+HFi8GOhuWXiIT9B97rZHx9ix+bBPSmYRc1mx/pMMCZIRhDBYr4X8smp8mHzWqnDMwHYh4DgOBy6y5bzV1qs0/+927Rz6XjmNWqk7VvYYZ8XRTUPVb8Kw2hhJTExEeno6Dhw4IOZ4AADz5s3DnDlzNK/LysoQEREh+nFEQ6kEPvoI+L//A6qq1Jogs2apPSN+fhY3t4Q1Ald5pdV4YY3xyVkbU3FbofkKQrRDDPY7YID67/Rp4L//BVavVqvP7typLgl+910oIyJFSea0xaAgQTKCEAbrtVB8q8Zqj8j+C4VWbQfc8Ypsih2M63537ksjYkOZWlGYg6rfhGGVMTJz5kxs3boV+/btQ6tWrcyuGxYWhoKCAp1lBQUFCAsLM7mNTCaDTCazZmgNT1ERMHky8Ndf6teDBgFLl6rDNCJhKbHUFsQqP8svrbJ9vbvuAlasAN5+G3jrLWDNGmD1aqh+/gVr+96HD3s+gDKvZgCAMH8vvDNefaHzXhlTaH8+WwwKEiQjCGGwXjNBvp4NPTRE3MzH6POHAADf9pmg8177Fv5WGSNBvh6Yf+9dCPOn6jehCMoZ4TgOM2fOxIYNG7Br1y7ExMRY3CY+Ph5///23zrIdO3YgPj5e2EidkePH1WW5f/0F+PgA338P7NkjqiEC3AlDADCZF2ELYuQ6FFfUirdeTIw6yfXoURT1SYC0rhaPHfgV+796CjMOr4esvhb5ZdV47nYeipC4tJD8En3MfQ/860d7R2LryWtm83YIoqnAcs0sGBeLMLl3g44LAJ48uglunAp7Y3rgXPNonffi2wSbvU+YoriiDmH+XohvE0yGiEAEGSOJiYlYvXo11qxZAz8/P+Tn5yM/Px9VVXeedqdNm4Z58+ZpXr/00ktITk7Gxx9/jLNnz+Kdd97B0aNHMXPmTPE+hSP44QcgIUGdJ9KmjVpH44knbMoNMYepxFIxsSXXIagZmyeLdT0AUHbvgXvGzMf0B9/B2ZAoyGsq8Oae7/H38mcx4fRuSDgV5q0/xeyVuV5ezXxzNHUjMfU9BPh4QO7jgSU7z+OldWmYtDwVAxbvwvaTeWYThp0VS4nOBMEKS1J8n5ggBPiYF3wUE3lVOR4+uQMA8E2fiZrl/MNIv9bBVj8AUs6YdQgK0yxbtgwAMHjwYJ3lK1aswPTp0wEAubm5kGp1ju3fvz/WrFmDt956C2+88QbatWuHjRs3uq7GSG2tOh/k9rnA2LHqHIeAALsfWj+x9HpZDd7bfsbyhozYkusQ5s+2Let6AJB6qQg3q+qxp00v7Ivpjomnd+PlfavQquwGPt36MZ76ZyPeGvECCm+1ZdrfhYJypGQWYXhsmE0Kp/rfQ3ZhhU5PCh5jeTvGEoudzZ3bEKJugG2KnIRrIYaIn6/MDRO7t8Kq1ByL647rHIYtp0wXSUxJ+wO+ddXICI3BwSh1/yz9hxHeiHpncwbyy9gNDMoZsw5BxgiLJMmePXsMlj300EN46KGHhBzKObl6FXjoISAlRe0BeecddW6DVHyRHFNoJ5YetCFxS58AHw9hYmZ6N5OeUYGQSmBUaplHKlGvZwn+OD8cytYsU0nd8FvnYdjacQCeOLYFz6f8is4Fmdiw6hWcKDmKdt0fwcVad7M5NV/szsQXuzM1E+uBuUOtvjny3wOvo8CKKQPFWRLdGkrUraEMHsJ5MJcUfySr2GTXXZ6KGiWig9lKb0vM7Muzvg7Tj20BACzvfb/Gm236YYTNK0g5Y7ZBvWlY2bdPXaJbUKD2gqxerfaKOJDCCrZeMixYmoJNTR78U/7BizfMGiKA2lA5llNitkrHkuhRtYcXlvV7CL90Ho43dn+HB07vRveta7E1ZSde7T8dmzsNshgqM6f8KLTfjBiN9+zVUEsoQnr82OLBaEgVW8I1YA1tBHh7QCIBzD0XSySAl6fpLuf3ZexBaEUJ8poFI2/kOHw2sJ3R693U79ToMW//S2W81kPGiCU4Tt1d9+WX1SW8nTsDGzao80QcjJjuwJLKOizZcR4JbUOYL0rW8mFt9G861ko/F/kG4OV7X8ZvnYfju8PfwyfrIj7f8hEePLUTbw9/DtlBLU1ua2xiFfqkLlbjLlPjaUj4z3LwYiFzIrC1apINZfAQrgVzCXBlnVlDBFDfslv4mchN4zg8/Y+6nHdFr/Fo28q4F8OSbpI+VMZrO2SMmIPjgDlzgE8/Vb+ePBn45hurVFStwVJMXeyS3y92X8QXuy/qTMJCL0pLaN90xJB+PtOpJ9y/nYWvJ7yA6bt/wqDsf/Hn9zOxNP5hfNX3QdS6G0+K055YS6tqBT2pJ6fnCY4jW8JRDbWs+Q5sSdATUvnUVOWzmyIs97IgXw8cyWITNvPzMu5BuTvrODoU5qLc0xtru41C+eHLWH1Yrfisfd9j9XjOHNIGCW2b272Td1OAjBFTcJy6o+7SperXH38MzJ5tt2oZfVie1PnKkOdXH4cErJFNy2hPwnJvT1HkmfXjqUJcoOb4YGJnHMuvRFLPB7GmdX8s+msZBmX/izkHfsJ9GXswf/jzOBTdzeT2+aVV+PDPcyaf1AFDD4oppVcxOHjxRoPdzKz9DmzxyJGKbePHmsRklntZcUUddpxh0/7IL6vGMwNjDHpQzTiyHgDwc5cRKJfpPlRq3/dqtFRazdGuhR/i2wRTDpQINFzmpSuhUqk76y5dqjY+vv1W7SFpQEPEWI8G/mJJ1goN2KPkV3sSZi2bNYd+PFUMb0uYvwxf3fZY8BNXTmA4pj38f0gcPxfXfQPRpvgq1vz8Ft5P/h98ayqN7qe4opZZOVap4vD6+lM2jNoyX+zO1CkNThYhDGQMa78D1iRkU5CKbeMmOT0PAxbvwqTlqYJ/x/y9rIW/7YKXYXIZ5o2JxfDYUM2yuwoyMSDnBOolUqzodZ/BNtr3vRBftjGE+nkJul8TpiFjRB+VCnj2WeCrr9TGx4oVwFNPNdjhLcXUAfXFoq37MCpOgQNzh2LtjH6Y2i9SlHHw7nJWMTNz6DfZsyXpc+aQNlg7ox8Ovn6PZn86E5dEgm2dBuKeGV/hhx7qBOPJJ/5E8ooX0S/35J3VoH5yCfRhU37ML6tWlxpbyPgXE3vezKz9DvgkZGuxRXSOcG4sTcrbb4sBamvX6OvZqFR85pBtBPuqjYSdWiqqvPT7to4DcVUeanQ7/r6n4jhYckpKJUC3iADB92vCOBSm0UapBJ5+Gli5Ul2u++OP6t4oDYi1MXW+bC7jWqmo4wlqJrM6L2XmkLZGE2KtccHzYZ7ZwzsYuHyNxZvLZb5YMPx5/NEhAR9t/wwRpQVYt/YNrOg5Dh/e/TiqPdQu1KslbJ6f4ls1yLx+S/C4bcEeCZ1iJN7aEkIx546nigTXheUhaubaf3Uq7niRM3sY+MG+njrjUZTdwLgz+wAAy/vcb3H7w1nFTNWBaw7nUA6USJBnhKe+Hpg+XW2IuLmp+6I0sCEC2B5TZ1U4Hd6pheWVoBYpE6pEyD/dzh7e3qgsslAXvCWpdXOqqqmRXTDqif/hp26jAABPHNuCP394CWvjlBgVp2DuiaFez/qnm5lD2mLtjH74cnJ3hAlwQ9si1a//1Ln95DWNC/3HFMvCUaawNYTCoshJuBYsnjb9yf1mZZ3dPI0llbrh1+nHtsCdUyElsjPSwyyLJJ4vKGM6Tk6x8fCvPpQDZRnyjABqQ2TqVGDdOsDdHVi7FnjwQYcMxdaYOqvC6fT+0Ui/VsrU9M1NKjGqWGoMlqdboVVAAT4e4AAs2Xles0w/OYyf4IxrofRA4MyhOPRnMnr+36uILLiKyMfvB069AsXj/2EYARAm90aonxe+2J3JtL42Ugnwn3vawdNdejvkYr9uwzxiVCrpI6aokxiKnITz4EyTbaCPh85Dhl9NBSan/QFAV/rdHKxN8qKC2ETYKAfKMmSM1NWpPSC//gp4eAA//wzcb9mNZy9s7QzLb29uElLIvdCvTbDGXW4KbYPC2ORRUlGDRdvOCJZUt+Sq5wDMHtYO0SG+JqXWjZXdWpzgXpgCTB4LvPSSOgT34Yfou3UrBg+ZiT3NTOfaaOcwBPh4CH6a4/MsTJUQsyDkZiZWpZI29gihmFPkJFwLZ5psa+pVCNV6KHs07U/41VbhQnAE9rTuKcox+Pvw1PhofHsgizp5i0DTDtPU1gKPPKI2RDw9gd9/d6ghArB3uTQ1IfDbS0xsL4Fu74VnBsUYJGpJJcAzg2IMDAp+8rivW0vEtwnGmC7hmsTZzx7thrUz+uHA3KFMbnZzrvqvHuuBl4a1x71dwrHun8tGtzeVHKY/RoPzFBCgbnK4cSMQGgpJRga+/+pFzDz0M6QqpcFxtM+Xm1SCDyZ2tvjZjJFfWmVV9YrQhE4xKpUCfTwMmpZRCIUwB/8Q5AxU1iqhUnII8PGAT20Vnj3yOwDgmz73g5PYPuVp34c93aU23a+JOzRdz4hKpe4zs3kzIJMB69cDY8Y4elQATIcchDRyY9k+OT0P3+zLMpi4OA74Zl8WukcGWjyWLU+3ljwZYglkGdU9uO8+ddflF16A9Ndf8cr+VRhy5SReGD0bBX4hAIzrBKjHHIodjG5cHpYSYn2suZnZUqk0LT4Ko293UOX3RSEUggU3qQTjuyoMdD0cxaFL6r5djx/fipDKUmQHKLDhrqGi7Fv/Pmrr/ZpQ03SNEakUGDAA+Osv9VPyyJGOHpEOtsbULW3vLLLc5owZ1jg0Xxli7PwYU0sN8/fCO+Nv3yR+/hm4917ghRfQM+sEDqyZjeMLPoZq3Hij+0vaniHIEOHdtKyJxdpYczOzJXY/Ok6h811QCIVgRanisPmE8+hp7L9QiPqSUjxzWC1y9nnCo6h3s226e6xfJMZ2Djd6X6AcKNtpusYIALz6qrr5XVSUo0diFFtj6pa6ZDp7SRprHPrHlBz8mJJj4MkwpZaaX1aN51Yf14imYdo0oF8/YNIkeBw/jr6znwQyZwIffQR4eWk8K9dKKvHNfmFPfhyAR3tHIPN6OdP688d2QoifzOqbmTWxe4prE7YiRsNIMUm/Vob/HN2EwOpyZAa1wsbYwTbvMybYV3MvNKUySwa89TRtYwRwWkPE3riCLLfQqhvtpNbhsWEW1VLnrT91x/PTvj1w6BDwxhvAJ58AX3wB7N2L/Yv+h9cy6m260RpLwNWHNwimJ8TY9DQl9JzxCcOP9o7A1pPX6ImOsApr7hP21Bnxr76Fp//ZCAD4NGESVFLTXXxZ4b2bJP1uH8gYaaK4giy30N472uElX093ize5kso6pF4qQkJbdY4IZDJ1D6Jhw4DHHwdOnUKvB0fi7ntmYF3XkXZrByBmopvQcya/PSFoG0x0YyWEwnqf0Pf8AbjdMfqGVWXzpphxZAP8aypwNiQKWzsNFGWfYf5eJivVTDXVJNhp2tU0TZg+MUEGFRP6BPp4ONx1L7T3Dh9eWn/8CtP6KZlGuoCOHg1l2gkcbtsT3vU1+ODPL7B00wfwr7aPAqvYlSqmzplC7oUvJ/fQVD/NHtYepUaEp6inBiEUlmoaxW3Pn3alGx/amD28g9k2AUIIrCzFE8c2AwCWDJgiSgVNsK8nrpVU4o0N6ST9bifIM0KYxFkuKe3ksD/S85jUQytqDct0jWP8Ux6p8sTkiQsw48gGvLrvR4w9dxBd8i/i+QnzmBQcWTAlly8GLAnMAxbvcngCM9E4YKmmGd9VYVGSQIwO5M8eWY9mtVVIb9EGf7aPt2FPdyiqqMXLv500u44z5Nm5MuQZaaIcySq2GMa4WVlnlQy5PeCfoEYzeg96R7N1lo1vHWJ0+fXyanASKb7p+wAeeOwj5MpbIKK0AL+vfgVT/t2urn+2kbJq+zbdM6e5IiSBmSAswVJNs/lEnlmvgbUdyGcOaatpEBpSUYJpx7cCAD4ZMKXBOq1r40xqtK4EGSNNFFdIYDUGa9fXx/vHwMfTfNKar6cb+pl4gtGOgZ9UtMe90z/DjrZ9IVPW472/vsSSrR/Dp5atyZ4pfkzJEdRiXUxc9fsnnBOWahoW41a7A/m0eLbigrLqOvh7qUPOz6f+Bp+6Gvyr6IBdbXqzDd4IiUPaIMjXfBjbFM6kRutKkDHSxOCbp10oYCs1dbYLS4hCrae7+Z+3h5n39Y2eMq9mmDHxLbw/+AnUS6S4P2MPtqyag4d82M6jOfIckKPhCgnMhOsgpnHLe/RGxoYx7fPHlBws3ZOJFuWFeOzf7QCATwba7hUprhDmuRSqlkzoQsZIEyI5PU/TtdVS5rozX1gsXV9tDUMZNXokEnzT9wFMnvQ+CpoFoU3hZbz/wVMYn7HHxk+kDos0ZPIbq4fJGb9/wvmwh3GrEhgKTUz5FTJlHY60isX+6O6CttXnaokwrydJv9sOJbA2EYQ0T3OFC8tSgqYYT2qmZJ4vx/XC6Rm70WLRbHjs2oXPt/wXva9kYNHQGah1t861C6g9JCsPZtkkesYKb2wZE4UD1MaRo75/U4JShPNia4NPbfjvf1Wq5UR1npal1/HoiT8BAJ8MfMxmr0hFjTCvCEm/2w4ZI00Aoc3THH1hsU5G5hQPxXpSM2v0DPwL/z75Err/uBRT/92OLnkXkDjhdVyRt2A6tjEWbTuj+X+YvwyT+kQiOsRXtElZ+9xmF1batC97QIJSromlTtwAm3GbnJ6HBZtOo6C8RtDxZx5aB09VPQ5GdUFqZBdB2xpjx5kbFtcJ8vXA/HvvQpg/GcxiQMZIE4BVqtmepaasWOwlw4jYT2oZ10qRU1yJqCAf9IwKVJ8fNzdkz5qHzyqbY8nWj9E1/wK2rnwJ/xn3KvaJ0Ko8v6xGVDEyYxO9KRxR2kuCUq4Jb+DW1Kswa1h7rD2Sq3v9mvnd6hvHS3aeF3z8yJI8PHRqJwDg4wFTAQDDOjXHTgaDwhr4q+H9+zvT71FEyBhpArCGLNq1aObQ+njmXjIMsDypzR/byaIHJml7Bpbvz4J2Ksd7289gxsAYzBsTizB/L+xp0wtjn/gMX25MQre8C1j56zv476Cp+LLfQ6KWFtoyKQsJ0wENr5ngLI0bHYkrhqeMGbhh/jLMHtbOokdPiHFsjv8cWgd3ToU9MT1xvFWn20vtd94c7TlurJAx0gRwhcoJpYoT1kvGzH60b+hLJ3fHom1nDFp7j++qMFiu73lI2p5hVMRJxUGz/LVRnRDg44FrCMXDkz/Ewh3LMOnkX3ht34/okn8Br4yZjVsyH0HnwhTWTspCw3TamOuILCau0LjRnrhieMqUgVtQVoNPd17Assd6mPyuhBrHpmhddAX3n94NAFgyYLJmeXFFrY17NmTmkDZIaNvcJYxEV4SMkSaAmCELe5F6qUh4Lxk9TIV43r43FoG+nhoDpaSiFolrzIcDhnZsgeUWOvQu35+FWcM6aF7Xuntg3uj/4ISiPRbu/AqjzqegbeFlPDvxTWQGR5g/AYwImZR5w+zgxUKrnz5NdUQWm6ase+KK4SlbPFm2GMf6zD7wE9w4FXa07YMT4XeuxeO5N0XYuy7tWvg1SkPYWaDS3iaAEG0OR2G0R4yA9fgQj7YhAqhDPC+sOY7Sqlrc160l+sQEYdE20zdRQH0T/eGQbmjGGCoOeH97hoERta7bKDwyeTHymgWjbfEVbPxxDkaeP8T0+VixNCnrlnFftPl49u5X4wreO3tgaVIHnLPfiTUKvrzG0ZId52wOzQBAzysZGHd2P1SQYMmAx2zenyUa22/P2SBjpInAos3hWIRkM+jCGuLhPQUsN9F/skuYRpNdZLwiJS28A8ZN/xSHI+LgV1uFrze8jzcOroJUxdozxzzmboz8k7YYN3wee0+MTVX3xFVl+YV6soRoHLEgVSmxcOfXAIB1XUcgo0Vrm/dpisb623M2KEzThLCkzeFI4luHMN2kjPWSYQ3xfLLjHHNam68FKXme6GAf7L9g/L1C30BMeeRdzNuzAk8d3YRnDvyMDlcv4D/jXkWptx/jSHSxFFIT0wWuj6kQkRiJl2KVhroarhSe0v6eCxlLb0P9vETLD9Hm4ZM7EFeQiTKZL/47aJqIe9alMf/2nA0yRpoY5rQ5HEm/NsEI8PEwa1QE+HgY7SVz4AJbCd9SAU9kE3u0wqYT18yGaqQS4I0xsdh55rrJfJx6N3csumcGTijaYfEf/8PdWcex5YdZeHbimzgTKuxpjuXGyFrGrY+vzA0Tu7diEprSnhjFTLw0JTLXmKsXXCU8Zex7lkpg9voI8PZAvVKFdzaLaxz7V9/Cq/t+BKBOWu3Vqx18PN2xMe2aiEdR05h/e84GGSOEU+AmleCDiZ1NKoICwAcTOxudhE9eKRV1LAE+HpBKJHhqQDSW7882ud6Yzgr8lZGPR3tH4tOd5822Pt8cOxjnQ6Lw9Yb3EHUzH7+vfhWvjp6FbZ0G6qx3f7dwDO4YiuzCSpN6DcNjw5CSWaTxRPSMCsSxnBJcL69m7jmkT0WNEtHBbFU//MRoj8TLUXEKDO3YAqtSsjW6LlPjoy32GXJVXCG53NT3bClad7OqDlO/PyL6eGYf+AnBVWU4HxyJbQMmYF7ncBTfqhHVGJkWH4XRcQqn8Rw3BSQcJ0IvdDtTVlYGuVyO0tJS+Pv7O3o4hB1RV8ScRn7ZHTdwmL8M74y/y+TENuOHf7DjzHXRx6KQeyGupT/+PnNd58YrkQDeHm6orL2T/xHgo5aBtxQukleV43+bP8Sg7H8BAEv7PYSPBz4GlVQdFnpzTCeE+ssMjAw+/LEjI1/wEyorSx7uig//PGdxYjwwdygAYMDiXWa9MAE+Hlg6qQf6tQlmvqG7YomrrfCTPWA8POXInC6lirP4PYv1+2Oh3Y0c/LHiRbhzKkx55F0cjO6meU8iAcSazdbO6OeUHmRXhHX+Fvy4sW/fPowbNw7h4eGQSCTYuHGjxW1++ukndO3aFT4+PlAoFHjyySdRVMRWPUE0LUbFKXDw9XuwdkY/fPZoN6yd0Q8HX7/H7M24T4x9bhr5pdXYmXEdnz3aHfPHdsK0+Cg82KMlOA46hgigNkIsGSIAUOrthyceegdf95kIAEhM/RXf/f5/8K++BYlELaj20ro0TFqeirs/2q2pAopvE4wdGflGE1PFmgjC5N7MVVcs4aCblXWY8t1hDFi8i6kKx1Tirb0reRyNMyeXs3zPKk5tRAd4W9+XiQmOw4K/v4E7p0Jy+3gdQ+T226JAyaqOQbAxUlFRga5du2Lp0qVM6x88eBDTpk3DU089hdOnT+PXX3/FkSNHMGPGDMGDJZoGfF4LPwlbeqp+rF+U1cdKHNLG5E2Uv7e9v/0MpifEYMG4u3CQsQTZHEqpG5KGPIn/jHsF1e6eGHLpGDb+OAetb1zWWS+/VK08+39bTuPgxUK8s/m0XRJTAXWfjfyyasi9PbF0cneLE6OQhEoWY8JVS1zFYlScAgfmDtUxwg/MHepwbxDr91xaVYebVcKaywll5IUUDMg5gRp3D7w75Cm7HWd8VwWFZhyA4JyR0aNHY/To0czrp6SkIDo6Gv/5z38AADExMXj22WexePFioYcmCKOkXb5p9bZBPp5mb6L6pZVilstujh2MzKBW+GbDe2hdcg0bV83BnHtfxo52/TTHBoDvD2bj+4PZoh3XGMUVdZj9cxoA9ZPh/LG6QnH6sXMhCZUsyrFNXYEVcM7kctbv+UqJfZsuyupq8Nau7wAAX/eeiCsBYXY71uYTeXhtVCcySBoYu2eFxcfH4/Lly9i+fTs4jkNBQQF+++03jBkzxuQ2NTU1KCsr0/kjCFNYU/bIawcE+XoyrX/w4g2NNLoY+Hu5Y2q/SPSYMBTjpy1B6m09kuXr38V/Dq6FhFOJdiyh5JdWI3HNcbPaFn1igjR5MixY0stwpRLXpkTPqECwzMn2qGTRZsY/GxBRWoDKFgos6/eQXY/ljLouTQG7V9MkJCTgp59+wiOPPILq6mrU19dj3LhxZsM8SUlJWLhwob2HRjQShJY9auc/yL3ZjBExhJq0Kauux6rUXPUL3wA89si7eHP3d3ji2BbMOfAT7irIxJyxc1AhUl8bfR7rF4ntp/KN9vDgPTLaHVTV3pJOCPSV4Xp5NUKayWBN7rspY8JVSlybGsdySkTJSZIAaOEvw8cPd0P+zSq88vtJ5hwPRdkNJKb8CgC4Mm8hqvLs/xvIL62y+zEIXezuGcnIyMBLL72Et99+G8eOHUNycjKys7Px3HPPmdxm3rx5KC0t1fxdvnzZ5LoEYUm9Ux/t/Aeh29qLejd3LBz2LF4d/RJq3Nwx8kIq1q9+BVEl9nnijAn2FdRMLK+0Gi+s+ReTlqfipXVpmPLtYZRW1Qs+riljgsXT0kzmjvzSKqRkFkGp4jTy4pvSrmqWEeIihieKv7beGX8XEtqG4IFeEXhmYAzz9vP2rIB3fQ2OR8Uh+oUnG+R63Xv+Bv2mGhi7e0aSkpKQkJCAV199FQDQpUsX+Pr6YuDAgXj33XehUBgmaMlkMshkMnsPjWgkWFLv5ACTLc35bc3pmzQkv3YZjgshkfh6w3voUJiLzT/Mxsz75mJ/TA/RjiGVAAE+bB4hsRBDL+NWTT1m/3ICgPFSakeXAIuhROtsiOGJMiYcNm+Mumpr+X7zPaD6XE7H+DP7oJRI8daQZ/BmTonFa11fPFEh98KjvSMRHeKD8/nlWLrHspdzY9o1bEy75vDfVFPC7sZIZWUl3N11D+PmptZUcAGJE8JFsEa9k588nC0+nBbeAeOmLcFXG99Hj2vnsPLXd/DB3dOxvM/9ajEFG1FxwM1K8Vusm4JVOZalNJrH2LqO7HLbWPVRLImyWWJCt3B8+GBXo6J188bEYtawDnh/ewb2nLuByyW6oRGpSol3bvefWdt1JDJatEZKZhFeGdnB7LVuruVFSmYRkzHCY+o31RgNT0cj2Bi5desWLl680wU0KysLaWlpCAoKQmRkJObNm4erV6/ixx/Vcr3jxo3DjBkzsGzZMowcORJ5eXmYNWsW+vTpg/DwcPE+CdHkEdJ7x9jkYQ3T4qMQ7CvTya8Qg+t+wXh00gdY9NeXeOTUDry553vEXr+E10e9iBoP272G2UUVaCZzx60a4aEWobBIaosRDmCp2rEH9lCidRbMeR1Z2Jh2DYezio1+/5auwUkn/kTs9SyUynzx8UC+K696BJaudf3eSbxicYivDGH+XgbdvU1h7DfVWA1PRyPYGDl69CiGDBmieT1nzhwAwOOPP46VK1ciLy8Pubm5mvenT5+O8vJyfPHFF3j55ZcREBCAoUOHUmkv4TDEbNw18q4wJLQNQWVtnUWXMwsJbYI1Wia17h6YO/o/ON2iNd7+eznuz9iDNsVX8Oz9byLPv7lNx9Ekz9qZ+WM7YXpCDNykErNPk2IlpjZ0CbAlfRRHGEdiw3sd9ZWRWZVXjRlllq7BkIoSvLJvFQDg44GPocRHDkC3USZLKbQxw4EP8bEaV9q/qdKq2kZreDoawcbI4MGDzYZXVq5cabDsxRdfxIsvvij0UAQhCJYnFrG72h66WIij2cX4el+WKPtr7qfn9ZBI8GPPcbgQEoWlmz5Al/yL2PzDbDx//zwcbXWXKMe0FxIA7VuouxNb+m5sDQfo01AlwKz6KCsPZiHET+biLn3dMft7eeBmVZ3FSV3fKMPt/5vchuPw/p9LEVhdjtOhrfFT9zGao/dmyDnijd6dGfn4zog+T+ntEJ/cQmNOffJLq/Dhn+cateHpSKg3DdEoMPWkpd/fIyWzCJOWpzb08JiwdFNvVVqAb9a/i9jrWaiVuuOd4c9iTTdDAcIAb3fctKLSxV6Y6sas/92Y6tFiDfbsLaLt4blQcAtf7L5oeSMtXM2lb+7aMpYwao61M9SCfuauwfvTd2HJtk9QK3XH+MeX4GzoncobS9+rkPCr0LDT/LGdsGjbGYvrUV8bXezWm4YgnA0hUuLOLJpl6cZ4Rd4CD0z5CFs7DoSnqh7v/7kU7/35BTyU+hOBcz2VmZqo9L8bUz1ahMCL2dmrt0hyeh4GLN6lKXEWaogArtVrhyUM5eUuReKQNkz7O3ixENtOmS5Xb1FeiIW3k1Y/HTBZxxABdD1e+qXd209eM9rbyBSshohGILEZW66WM99jnBm7V9MQhL0RIiXujKJZQp7Qqjy9MHP8azjdojVe3fsjpqQlo8ONHDw/YR5uNFNPwPbuESIm+jkeo+IUGNqxBValZCOnuBKVNUr8dvwK0754E2z+2Fi7VDqIlWvE6tJ3hooNlmsrv6wGQYyl4maNN47D4j/+B/+aCqQp2uPrvg8YrMJfv8Y8IFKJ7R41fawRSHTGe4wrQMYI4fIIkRK/t0u4qLkJ1hLk64H5996F4ls1TK5fHSQSLOv3EM40j8HnWz5Cr6tnsOWHWXh+whv4t2VH+wzYzhy8eAN9YoKwIyPf6iqnMLkXxndVYNE28SsdxM41spRo6ywVG6zXVpCvp83X1SMn/8LgrGOocfPAy2NmQyl107ynrVNjyii0hz5ZC38Z3hl/F0bFKaBUcWY/o61aOs5gfDoSCtMQLg/rk8iFgnIcySrG/LGxgvZvj/tBcUUdwvy9EKKfsCqAPW16Yfy0T3A+OBJht4qxbu3rePjEXyKOsuH4Yncmer67A88JcLMDaqNuySPqLrfzx3bCN/uyDLZnDYuYU3S15CGwFmOTPT/ZWvs5xEKp4lBYXmN5RQDFFbUYHRem8foIpVVpAebv+hYA8NGgqcgMidB5n4PaOwFYSH4VHQlUt38XW09ew6O9I4x+RhYtHXPoh/8mLU/FgMW7XCKUJxbkGSFcHtZKjC92Z+KL3ZlQyL0wLDYUf5+5zvQ0peLUyWsllbWi9qj5Iz0PUUHW9Z4J85chv6wG2UEtcf/U/+Lj7Usw6nwKPkz+HHEFmVh0z9Ooc2NvZOcMCKls4OGNuj4xQRiweJegSgftJ9HswgqsPZKrU7qq7Ylg9RDMHNIG7Vr4obCczeOlb0g7S6mwkERQqQQ6n1UiAXPfGQCQcCp8uP0zNKutwj8tY/F9r/tMrmsvo9AU+WXqNgjaGFP/ZdHSMUVj1qkRAhkjhMsjVJgpr7Ra8A0txE+G6Qkx+P34VdFuhj+m5ABg12vQZlinFlh9WK0VUiHzwfMT5iEx5RfM2f8Tpv27DR1vZOGFCfNQ6Bsoylidmevl1YLyhuLbBDNNttqTAav3LaFtc8S3CYZSxeHbA1mCXfpCP4c9EJobo//b5V8/lRANLw83i4qnU49vQ//ck6j0kOGVsbOg0grP8PBG2GujHB+G5EuDZw9rj+gQH5tCKs5ifDoDFKYhGgViVGKYI9TPC25SCcZ3Ff8JRaghIpEAr47UvSlzEim+6P8onn5gPso8fdDnSga2rJyFLnnGlWHv6dgcQb6eDVJ3wx/DUiM8awn18xKUN2QqDKKPdrVPz6hAsw3a9Kt4eAOZf09/XcC4S1/I57AHQnJjzM2NEgDb0/Mt9kCKKrmG1/euBAB8cPd05AQaV+XmjbBCJ6hU4c/Nun9ycW+XcMS3CbbaUBBifDZ2yBghGg2j4hQ4MHco1s7oh5lD2oqyT+1JRqni8PNRtsoOq47FeD97ZmAMfjtmvJP1rrZ9MGHaJ7gY1AqKW0X49ae5ePDUToP1+rUOwfv3xzVI7D1M7oWvHuuBY28NF+174Qny9UB+WTWuM8p7B/l4Cso54CeDVSnZGHM7J8LUevrGhSkDWbtrtD6sHhh7VWywhkGm9os0a0Tz581cDySpSon/bvsUPnU1ON2hJ1b1GGvxuNaE8uyBWEaCo41PZ4LCNESjgpeIFrP1OT/JHLxQaNebIccBb47phFB/GXZkFGD7qTydG75UAswYGIN5Y2Lx9qZ0k/u5FNwKE6Z9giVbP8bwi4fx3+2fotu1c/i/e55BrbvaO5FbXImTV0rs9ll4pvaLxPx779I0SktoG2KVNocpiivqMPvnNOb1z+aXWxVmY8n/+De3xMDAENIvCbCc/yRG92NzsF43EkbL2dxqTx7dhN5XM1Du6Y30//sE3PFy0Y7bUNh6n3G08elMkGeEcFnMVT+IcfG28JfpPMGmXCpk2m54pxYI8rUuJFFaVYf7urXEF5N74Oyi0Zg/thOmxUdh/thOOLtotKb1uqXE11syHzwz8U18MmAKVJDgsbQ/8POa1xFWpv4Mq1JzsOVkvlVjFMKq1FwM+vBOVUCfmCC7hWtYuFxSabd9L9+fhdp6lcFy3kC+r1tLiy59a8M7YsF63bAKd/eONG40tSm8jFdv9555d+jTGHVvvMWqNakE6GsnI8xabL3P8MYna/ivMUPGCOGSWCqFs3SRs2FqOjBPhzA/vH9/Z0iYt9Dmzk3e012Kpwa2xv/dF4enBrbWacM+NT7a4s2bk0jxecIkPPngApTKfNE97xy2/vAS4nNOCh6VLeSX1eA5EUpSg3098fGDXdBMZr1D19rqJRZUHLAqJdvieuaMaEB4eMfS/oTAet2wNFqUSoBz1w29HW4qJT7e/glkyjrsbt0TP3cZgRd+OmYxd0rFAVKJxKHGLI9YRoKjjU9ngowRwuVg0WEwd5GzUlCmq+vAWr3AK4lak1Cr3ZXUHJ7uUswYGGN5Raj1SO6d/hlOh7ZGSGUpVv/8Fp45/Luw+ksReP33k/j+QJbVoa6iiloUV9bhVo3wvjv85DE1PloEI9U0OcXmPS+sehLa+U+fParWUTkwd6iBISK2PgV/3Yjxy1BxwF8Zht63ebu/R7e8CyiV+eL1US8CEommU7Ulkk/no7pWKcLorEdsI8Ga3KLGCDXKI1wCXhMiv7QKi7adQXGF8cQ4PqZ+YO5QuEklJpUsx3dVYPOJPIv5A9r7A4Ce7+4wO5kG+njg6FvDDbQs8kurMH/TabMTaYCPB45pbctC0vYMLN+fxVSR41VXjff++hIPpO8CAGzrkIDXRr+ECpn9vAViMyI2FH9lXLdq26cSojEsNgwlFTVIvK0dIfbNb/7YTnhqYGuj77E2c2RFrP3pK3+WVNQYaGuIxfiMPfh8y38BAM9OeAN/duhvl+PYSuKQNhjQtjlKKmrtouhrjMaqwMo6f5MxQjg9QgSYeLQ7Z5q6yJUqDisPZgnqxJmcnofnbneWNYa+9oBSxTH3WfnKyqeg2nqV5hiZ18txMNNMhj/H4bG0P/D2zm/gqarHxaBWeHbim8gMjjC9jRMxoVs4NqaZbrRmDH0dFyHGqNDjnF00WiecxqNUcRiweJfZ4ym0jGhLWNqfvlFuClM9XuwhrR5bcAm/r34V3vU1+CL+Yfx30DTxD8KAJVE2Uw8Ujc1IaChY52+qpiGcGmubk2lnufMJhPq4SSXMcuz8/kbFKfDVYz3wzuYM5GuVk/Jx7CU77+h6+Hq6obJWabL1Og9fJcNqiBi7OfJP4wcvFOJg5mHTG0skWN19DDJCY/DlxiS0Lb6CTT/OwStjZiG5Q4LOqm5SddgoJsQH7m7AD4dy7TJJsSKRAPd3a8lkjLw5phPySqvw/cFsgzHnl1bjm31ZWDq5B74/mIWjOeJUFc0YGGPSEFl50FCmXh8hYmZiiKM1ZI+XgKoyfLXhPXjX12BvTA98MmCK+AexgI+nG5ZP64XSylqznp+kiZ11jA1T9w9CXMgYIZwWW5qTiV0yZ7ie7qiMhW4qTMS29T8PxwHf7MtC98hAiwZJcnoe3tl8Wke2PEyrmVe/NsEI8PGwmJdxvGUn3Dv9M/xv84eIzz2FrzYm4fue45E05AmNjLxSBRy4WIgD4lXi2gTHAVKpxOLnC/TxwOP9o3H3R7uN7+f2v4u2ZaBvdCCO5tg2Lu2Sa32EevXyGfVSWEtKD14sNPpEL3bjP3NIVUp8vvkjRJYWICcgDP8Z96pRlVV788nDXZHQVp2T9ZVUYvBA4YhGhMQdyBghnBZr+lAI1WEQqusgVht5bVhln02FiPhqFT7M88HEzmZDSTyFvoF47JF38ereH/DckfV48thm9Lh2FjPvm4sr8hY2fir7cDir2OLnS5rYGcdySpg8ER0V/sAJ66t8HusbgbfHxRn1iFjzWym+dcfINBceYDWitTVdtCdbMXu8WAp7vLpvFQZl/4tKDxmevf9NlHr7iXJcWxCq/0LYH6qmIZwWoYJC1mS5Cymts+fTpCVFR6WKw+vrT5ndx5xfTuDghUIMjw3DV4/1QJi/5RCUUuqGD4Y8iVmTF6LWX45ueeexbcV/MOyCmVCPA1FxKk2oLMxfd0JW3FZ6HRWnYPYwlFUJr8zRJsBHZjI0Y81vJchXLZ9urkpGqeKgUnEI8BZW4qpdbcZ6fljwl7lhch/jOUdjzh7A84d/AwDMHfUfnA1lqwCzBwu3ZOiUPQvRfyHsDxkjhNMiVFDI2lI41tK6hugYasoAS80sshh6qaxVYsp3hzFgsbpa5uDr99yWxm9j8bgbI3ri849+RpqiPeQ1Ffh2/SK8ses7uCttm6zFJtBH28DSneq1c/G1PQzmuFZaZeOI7hxTW++DJUfEGGFyb7Ol68+tPo6e7+7AlO8O42aVsBJp7V47heVs54eF0mol1hwxbE/Q/kY2Ptr+KQDg6z4TsSX2btGOaQ1NpceLq0JhGsJpsRRCAdS9Sebfe5emjby1TzcsblsxnyZNYcoAY1V/BQxbj7N6mE64BeDrKYvx+p6VeOroJjzzzwb0vHoGM++bizz/5szHtyfBvp4mwx8FZTWaz817GCwRHmCbgiavC2NNxZc+CrkXekYF4u6Pdpvs4grY1p+F98AVVYhnjBjDv/oWvt7wHnzrqnEgqis+vPtxux6PlYa4hgnrIM8I4bRYCqFIALx/f2fc310cN6slty3r07Y1WFZ0ZP9s2k/AShXH7GGKDvZBnZsHFt0zA8/e/wbKZL7oee0stq/4DwZn/sN8fHtSVFFrtuU6oP7cIc3YqqTiY0KsFkEL8PFAv9vl3ixdgM0hgTocyJLrIgZHs9k8BMM7hQret4RT4dMt/0VMSR6u+IfixfGvQWnHhNVp8VGY2i+SaV17XsOEbZAxQjg1zqROyPq0LRSWXBehpYXaOSi8h8kcCrkX3hgTq2ls9mf7/hgz/TOcCGuHwOpyrPxtIebuWWlT2EaMkHxJZS1TSevZfMtN1wDgbEG52W685vhgYmcAsDmPSKH1W26oJ/ejOTeZ1hsdpxBsrM06sAZDLx1Ftbsnnr3/DZT4yK0aIysj7wpDj8hApnXtdQ0TtkNhGsLpcZbM9zC5t6D1fWVuqKzR1RmRQK13oF32G8ZQUtivdTB89bZj4Xp5NdykEsS19Dc7ibcM8ELy6Xx4uklRc7vZ25WAMDw05UPM2/M9nji2Bc8f/g3xuSfx0rhXkBMYzjwG/lv6YlJ3BPrKcL28GtmFFVh7JFenRJkF1q+ctSHee9stC97Jvd1RqpXoql1KnZJZZLUnw8fTDcun9kK/2144pYrD8RznymlQBHhjwbhYPL/6uIE+jjHGntmPlw6tAwDMGzkTp8Pa2n2M4NivTaHXMNFwkDFCuATOIDzEexjMTT76OSzaCqxRQT6YGh8NN6nEKsPKWr2V2noV/j5jXkL9aM5NHM1JM1he6+6BhcOexeGIOCz+43N0yzuP7Sv+g3eGPYtfOw8z3yP+NqaMrZlD22nOQ0gzGV7+Jc2scaKQeyG+dQi+2J1p8ZgRgeJI3EsAeHu44cspPVF4q8bg+7KlhXxlrRJSqUTTtkBfP8bR8GFDN6kEyx7rYTEnZujFI/h0q1rqfUXPcdgQN1TnfUslwNZSWFGD0XEKi8qxUgnQM+qOB4WUVZ0LMkYIghE+h8WcxsX793fWmXTdpBKjvUqEGlapl4pQKcAroq2PsvIgW+8acyR3SMAJRXss2fox+l1Ox0d/fIa7Lx3DG6NmosyrmcntpvaLxPx774Knu9TozV/7PLwz/i6Tuhx8TgWLqFuAjwc6homjZcFBreMilUhwX7eWAO5UzVwvr8Z1G42H6+XVFlsMOIrxXRWayXlUnAJDO7bQGNYKuQyLk++oDSdkp2HZxiR4qJTYGHs3Fg19WmdfEgAt/GR4akBr5BRX4PdjV1FVJ07Du1A/LxzLKWHq+nssp0TT1sFYzyoSPXMcZIwQhAuQwtjVFDDMQbHUSZaVPP/mmPzoe3j2yHrM2b8a9547gB7XzmLOvXOQGtnF6DarUnOxI+M67uumwKa0ayaVY4E7+UHmJgklg1UlAVAocqIi7wERo2pGZ79l1VjK4OlxBJtP5OG1UZ1MNpzk6XklA8vXL4JMWYc/2/XDK2NmGyis8kZdXEs54lrKsTo11+bxaRvcW0+y9SvijT9jRq9+FRrRsJAxQhCM8EJWpmBRUbUedteGflgkKki8rry+Pp64NesVbJ8yAfe8OwfhuVlYs/ZNfN33AXwycIpGSl6b/LJqfL0vy8hyXeVYwHJ+0JGsYoulrSWVdSi8Zbyrs7WE+nnZRX33ve1nRdybuOSVVuOdzem4XFyJPeeNl5Z3zruAFb++A5+6GuyL7o4Xx89FvZvpacWWsJY2+gY3a8XY9bIafHfgkslqLPtew4Q5qJqGIBgR0pyMR1sIKyWziOnJ3hi8noUl3hzTCQfmDtV5spsaHy1KJQsAlFcrsSo1By9lemD8E58jbeQDkILD84d/w++rX0VM8VXB+5zzywkcvFioOTfmSqxZJ7ObleIYIxKoPTj1ShVe//1Ug/RycSZWpeaaNETa38jGj7+8Df/aShyOiMMzE99Erbt5VdhQPy/BYobG0K+mY6kYA9QJy+byciwpIRP2gzwjBGEBPtfhj3S2HibmXPrWxqVZcyWeHBBj8ETn6S7FjIExRr0TtpBVLcH93Z7A7yNGIfadV9Al/yK2rfwP3h/8JH7qPhqchO1Zp7JWiSnfHmY6N6wT2dWbtiqrquEAVNerMPX7I6Lsr7EQU3wVP/38FgKry5GmaI8nH3gb1R7mv5sAHw9NUrelZFNjSCXARw90QXigj0GyqZtUgvFdFaL9xsXy4BDskGeEIMyg3SPkxxS29q7aLn1jkt58fxAhuEklGl0LUzzQvSWOZBUb9b7MGxOLZwfFCPaQPHd3jEltBu72X2JNDL5fuhEHo7rAp64G7+5YhjXr3kRkibDPaO7c8B6mazermDQvNqax5RCwYIviqSOxV5ShVWkBflr3JppX3MSZ5tF4/KGFqJBZDgVKoG5r8Pnf561KqFZxQHigj1FBQqWKw2YbGh7qwyqaR4iHhOPsUWwlLmVlZZDL5SgtLYW/v7+jh0M0EYTmCPAJdXtfHYK7P9ptMqTDr3dg7lDBcWljJaD6+g/mPAy19SqsSslGdlElfj12GdV1KpPHCvDxwNLJPTDlW8tN8xLaBOPQxRuYdnwb5u5dCZ+6GlR6yPDRoGlY2XMcs5fE2LkRO2m0scP/opZO1tV1WbLzgs37Di0vwq9r5iLqZj4yg1rh4ckfoMg3wOb9svLZo900VU3apGQWYdLyVNGO89NTfZHQji00SpiHdf4mzwhBGEFo11XthDpLkt58XHrJjvOC80hGxSk0DfCeTIjW7E8b3sOw/eQ1g3wVT3cpnhrYGosmxOHTR7qZPdYT/aORnJ7PNK6DmUXgJFL80HMcRj65FIci1V6SBX8vxy8/vc6cS6IfsxdDar2hcJZ0Rz6fYkyXcE3uTQcRSp2DKkvx089vIepmPnLlLTD50Xcb1BABgAsF5UavGbHDKoV27t1DGEI5IwRhBKEderUrWDalsU28X+y+iC92XxScR+ImlaBPTBDm/JJm9H3+Nj1z7b867nD944yKU+Crx3oYeFrk3u6QSCRWP0lfDgjDlEffxeS0ZMzbswK9r2bgjxUv4uMBj+G73vcZlH0a43p5tWCD0FHwRshnD3fDP7nFyC6qRGVNPY7l3nTIeFQqXW+XpSowFqKLr+K73/8PbYqvIq9ZMCY/+h4K/Brec/DF7kx8sTvT4LcsRlKsNmLvj7CMYM/Ivn37MG7cOISHh0MikWDjxo0Wt6mpqcGbb76JqKgoyGQyREdH4/vvv7dmvATRILA+aU2Lj8LaGf10KliE3sisySNhMZb0HS7GjqPtafns0W6YPaw9yqrqbc6T4CRS/NR9DEY8tRT7orvDq74Wb+75Hr+vfg1tCg3bzesT6ucl2CB0FGFyLwyLDcWsX9OwKjUX+y8UOswQAYCC8lo8p/U923oe+1xOx4ZVr6BN8VVc9WuOKY++hysBYWIN1yr0f8t8NY2t3inLDSsJeyHYGKmoqEDXrl2xdOlS5m0efvhh/P333/juu+9w7tw5rF27Fh06dBB6aIJoMFgNitFxCoOEOqE3Rv0uuyxY45Y2dRy+lPbeLuFY90+uqJ6Ia/6hmPbw/+HV0f9BmcwX3fPOYfvKF/HiwbWQ1RuW32pPBs5e0SBzl+LNMR0xprMCOzKu26xya464cOG5cq+vPwWlikN+qfWVRQ+c+hur192pmpkw7RNcCm5l9f7EQv+3rN3h21pYGlYS9kNwmGb06NEYPXo08/rJycnYu3cvLl26hKAgtbUZHR0t9LAE0aDwBkV+abVJefIwE09Q/I2RtbkYoJsrwSIVb60b2dxx7OaJkEjwa5cR2BfTA+//uRT3ZP6Dlw/8hAfSd2HhsGewu01v9Wq3VxcqZOUoaupVDSZaln6tTPA2NyvrkJpZhOIK4ZorEk6Fl/evxsyUXwAAWzsMwMtjZ6PGw3mqTPR/y6PiFBgWG4odGeb7MPHolxeHyb0wf2wnyL09sSntKvWraWDsnjOyefNm9OrVCx9++CFWrVoFX19fjB8/HosWLYK3t/EOijU1NaipuRPDLisTfiEShC2YMyhYnqBMSZtbgtUbYMlYssQfWu5tMZq+sVDgF4KnHngb957dj7d2fYvom3lY8dtC7GzTGwuHPYv6qGidPABbPyMB/PJPLvx9zAuR6eNVV42Pty3B2HMHAQD/i38EnwycwlwR1dDwv9uk7RlMhsidLtI9EOjrqVH6LamoxaJt1K/GUdj913Xp0iUcOHAA6enp2LBhAz799FP89ttveOGFF0xuk5SUBLlcrvmLiIiw9zAJwgDeoAjTU3bUV380t/2BuUOxdkY/zBzShumYLN4AXoRtTFyY1ZP0jyk5mLQ8FQMW79LE3RvEEyGRYGunQRg642t81fcB1EndMCzzH+xdkYiDVXsxqrVcs6q2652eTa1j08k8rBLQB6b5rRKsWzsPY88dRK3UHS+PmY2PB011WkMEUGuC1NarsHw/m+DZnWojhabaqLSqFolrxNMFIoRjk86IRCLBhg0bMGHCBJPrjBgxAvv370d+fj7kcvWNZv369XjwwQdRUVFh1DtizDMSERFBOiOEQxCj1bhSxWHA4l0Wwz6WtEfE1tzgj7TssR4YHhtmdoxio5B74cO7PDDwf4uAnTvVC6OigE8/Be67T91zHqQz0lB0vJ6F7377P7Qsv4ESLz88O/FNHImIc/SwLPLTU31xNr8Mi7adsbju1H6ReGd8nM41xl+b9tAFIpxIZ0ShUKBly5YaQwQAOnXqBI7jcOXKFaPbyGQy+Pv76/wRhKMw1ytFyD5MPeWzJs7ZQ3NDOxGQH0NDwXEcKlq3A/76C/jtNyAiAsjJAe6/HxgzBjh3DoCuh2nJI90Q5Css7EBY5p6Lh/HbT6+hZfkNZAa1xIRpH7uEIQKoNUFYO1NLJBKDa8yanlOE+NjdGElISMC1a9dw69YtzbLz589DKpWiVSvHZ2UTRENhS9jHGs0NVptJ+2bLJwE2BAVlNWoX+Ol84IEHgDNngDffBDw9geRk4K67gBkzgMuXNQbh/d1b4qGejfe+MW90w1YZ+lffwkfbPsV3vy9Cs9oqHIrsgvunfoycwPAGHYcthPp5MXem5jjOasE0Z6/ucnUEGyO3bt1CWloa0tLSAABZWVlIS0tDbq46Ljlv3jxMmzZNs/7kyZMRHByMJ554AhkZGdi3bx9effVVPPnkkyYTWAmisaL9lP/Zo90MNEpMYU2li4oD5o/thGnxUUzrXy+vZk4CFAODUmNfX+Ddd4H0dODeewGlEvj2W6BtW2DWLKCgQPQeJM6EBMCjvdm+KzG45+Jh7PjuBTyUvhMqSPBtr/vw+MMLUebVrMHGYCt88z3WztSrUnN18qQA9lwpZ6/ucnUEGyNHjx5F9+7d0b17dwDAnDlz0L17d7z99tsAgLy8PI1hAgDNmjXDjh07cPPmTfTq1QtTpkzBuHHj8Pnnn4v0EQjCtbAm7GPtU1mInwyjGSsBgrw9mZMAxcKYC1zZpi1SPl2JfSs2orRPf6C2FvjsM6B1a+TNfBkVBcZb2rs6HIBXfk2z+3HkVeX4ZOvH+O73RWhxqxiZQS3x0JTFePeeGahzc60QGH/l8J2pWRAqmEZCaA2D4NLewYMHw1zO68qVKw2WdezYETt27BB6KIJoUphLlLX2qaywvAYqDgjy9UBxhXFVVT5B72xBuV2Fu8zBG1u6yaruwOB5GH9XBv7vn7UISE9Dq2VLsF/mi6/7PoCVPceh0rNxeVdzS6wXKGNh5PlDePevL9G84iaUEim+7T0BnwyY4lT6IUIoqazT6IzMG6POd1q+P8vs75iD+je/cEsGhseG2VzGT4gDde0lCDvCWoljrGJEW+PAUjWOMfRFnYyhXU1zKLMIP6bkMO5dXNbO6IfSqlqjXZIlAMBx+D38Ojp++V/4nFdXTdzwCcBXfR/Auq4jmVrYuwI9IwPsIiUfVFmKhTu+wriz+wEAF4Ij8OqYWUgLd30lbP1OvrX1KizaepqppHntjH4a8T9L1yBhHazzNzXKIwg7wXpz46tk9CfhvNvuZD65VaiqK4uXQ7vB3+Vi+z6VG4P3yvSMCsTdH+02+rk4qKsgEiujsPfkCSyYtgBP/LUS0TfzMH/3d3jp4Fr82mU4VvYch8sO7pliK7YaIgp/D+SV3fGASTgVxp3Zj7f//gYhlaWol0jxdd8H8HnCJNS4e9o4WudA32vo6S5Fr+ggJmPk4MVCzYPC8NgwDI8Ns7mMn7AOMkYIwg6YMjDy9QwMS1UyHO64k61VddVGAiDI1xNvje2EMLm3zs22Ywvb28wLHQugdoEfyylhKq88dqUM8fNfxPDIvnjw1E48/c9GtCm+gqeObsITRzdjZ7u++L7XeKRGdNbolDQlVJz6M0tVSow9ewCJKb+gY6Ha23U2JAqvjJ2N9LC2jhyiaJhrycAa1vxi90XN/8kL4licV1aPIFwUcwaGfgUJS5WMdoLnqDgF9r46BFP7RVo1Ng5AUUUtwuTeBsmzxVXCe5jYgnZJs5DyylFxCvzv8T7Yc/cEDHv6Szz+0ELsjekBKTiMuJCKdWvfwB8rXsRDJ3cYbcbXmCm6WYkHT+3Ezm+fx/+2fISOhTko8/TBJwOmYNz0TxuVIQKYzuWwposvqa06FvKMEITICBFRYu2oyq8nlhqpscnfnqWLEgAt/L1wT6fmyC2uQnSwD94YEwtvTzdBx+bXGxWn0HKp94C77wu4//ONeODAekw8vQudbmTjoz8+w9y9K7G26yhsuGuIU3SbtRey+lo8dGonnkv9Da3K1KXZJV5++K73ffixx70uVa6rT6CPBzioG//xhFnwYljbrFI/sZVoOMgYIQiREfKUz9pRtbii1mToxxqMTf72akzHTwYFZdX46fBlAMD+C8BPh3MxY2AM5o2J1RzbnJGlX17Jl0jz7BvdH2/5KvDh3Y/j0RN/4vFjW9Gy/AZeTPkZL6b8jIzQGGztOBDbOg4QJOolkQDOmubvXVuNySeS8cyR9WhxS+09u+EbgG96T8RP3Ue7bLXR7GHtEB3iq8nbACA4l8OasKbQ7tmEeJAxQhAiI+Qpn7WUNtDHU7ACqzGMxdm1K34e7R2BJTsvMD1N+srcUFGjtHhMn9vr6e9PxQFf71PrmswbE4vxXRWa18YY31Vh0FOEH3dIMxk2pV0DAJR5NcM3fR/Ad70nYMT5FDx8agcGZKch9noWYq9n4bV9P+JUizbY2mkgtnUYgCsWkl69PaSY2L0VVh9mbzhnTzyUdeifcxIjzx/CqPMpCKpSdzW/5heCr/o+gJ+7jHDZUl2pBJgxMAYvDWtv8J41xoGuB60aFwrK8cXuTIvbkdpqw0PGCEGIjCUPg7ZBwNrvoqSy1ubQjLE4u7GwT8DtlvPabvFAHw+oOA6lVfWaZZUWDJEAbw989mg3TF/xj9n1lu/PwqxhHSwqq24+kYfXRnWCm1TCFK5SSt3wR8cB+KPjAARUlWHE+VTce3Y/+uecQOeCTHQuyMS8PSuRpmiHbR0G4kBMN5wLiYJK6qazn8paFe7pEIo1R3IdpsPiXVuNu7OOYdT5Qxh68R/4197pxZITEIYv+z2E9XFDnVq0zMfTDZW15n8zKg74Zl8WukcGipZIqu1BS8ksYjJGSG214SFjhCBERoiIEmt4IsiXvQxTIffC+K4KbD6Rp7Nf/Ti7qbBP6W0jZPaw9ogO8UF2YQWW7LxgcBxL8/LNqjrsPFNgcT0VB7y/3bIrnXefm9IjMTsWb3/80nUEfuk6AkGVpRh5PgX3nt2Hfrnp6JZ3Ad3yLgB7gHJPb/wb3hHHWnbCsZad8G94B1TIfPDdQfNCWvZAXlWOezKPYNT5FAzKOg4vrWTc676B+LN9PP5sF4+UqC5Q6hlQzoQEwDODYvDaqE7qPKmyaizaetqkCJ92BZm5UIw13bSFPCgQDQsZIwRhB0zFq/UNAm3DBTBtuMi92YyR+WM7YXpCDNykEs3N39jN2lLFjwTAun9ysffVIbj7o93CPrwWWYUVTOtlF7F1Xc0vrcKHf56zKVxV7CPH2m6jsLbbKIRUlGDU+RSMOJ+CHtfOwq+2CoOy/8Wg7H8BAEqJFOeaR+F8my4IDm6LCyFRyPMLRom3v6DS4TfHdELqpUL8ffaGwXuy+lrEFF9Fu8JctC26jPaFuWhXmIvokmtw51Sa9XICwpDcvj/+bBePf1t2ACdx/mLIN0Z3xPSEGHi6q8ca3yYYKZlFJg0RHkt5G9YKlJHaqvNCxghB2An9eLWppzcWw6W2XmVRUVUqAabGR2v2r5/gqQ1rxc+qlGybwkPeHmxP7NHBPthv6HwxoLjC9nCVNoW+gVjdfQxWdx8DqUqJjjdy0OPqGfS6moFeV86gVdl1Ta7JBK3tatw8kO8XjHy/EORp/g1Bvl8wbnn6wENZB09lPdxVSngo69Cq9gSiL1zHtOpqeCjrEVhdrjE+okvy4KZldGhzpnm02gPSPh5nmse4nHZK51YBGkOE92RsP3WNaVtTlWasGj6mYH1QIBoWMkYIwo6YMwi0sWS4HMspsRgmUHHq9ViOx5qgl1PM5rEwxYi7wvD32esWjag3xsRi55nrFt3nQc3sl5ipkroho0VrZLRojdU9xgIAWpQXoufVs+h59Qx6XD2LVqUFaF55EzJlHaJu5iPqZj7z/kebea9U5osLIZE4HxKJi8GRuBASgXMhUbju59oVHcZ7DrFhrNKMxaPHEuJhfVAgGg4yRgjCSTBnuAgpF2aBNUEvKsi2ni+tAn0wY2CM2SqZGQNj4O3pxuQ+Zw1XiUWBXwi2dxyA7R0HaJZ51tch9FYRwm4VQVFWiLDyIijKC9HiVhHCywrhXVeNWncP1EndUefmjlo3D9RL3VDn5o46Nw/UurmjwtMbmUGtcD4kEhdCInHDN9DlvB4shPp5WV2SbszwFKLhY8koZ31QIBoGMkYIwgUQKgpmCdZEvqnx0fj2QJZV2iO8Lgh/w9fvpsqXcfLdVlnc50oVZxctFCHUunvgSkCYxZLgpgxLzyFLhPkb/pbFNsoJ54GMEYJwAfrEBCHAx0On3FafQB8P5ioAlkS+R3tH4o/0PEHaI9r70E4EnDcmFi+P6IhVKdnIKa5EVJAPpsZHa/IJeCy5zy2NmwMMzlOYvwwD2jaHj8wNrQK8kfTHWdEMmVYB3rhys+EbDDozQnoOmUJf4I5HbKOccB7IGCGIRoLQCdaUJyLgtvz2kp3ndZYButojpkqITVU1uEkliA2XI8RPhlA/L5PxeUvuc0seFG1jJruwEmuP5OK341fYTopAfGTOX9HS0Gh7sjalXRW0LWvPGSrNbXxIOM5ZhY7vUFZWBrlcjtLSUvj7+zt6OATR4KRkFmHS8lSL662d0U9wHFxbr8GUpgg/Lcy6rT2i7bHQ13voGRWIYzklOp6NHRn5VpViso7bWAKimPL5TYGZQ9oAkOh0smVBIffCfx/sisKKGoPvgfV3q70vS78J/nsFjHv0LFXTEA0L6/xNnhGCcAHsGSvnPRFKFYcBi3cZXUdbe+TA3KE6k762JyM5PQ93f7TbwNNiLLzEWooJmDY8TBle5qouCEMUci/MHt4BqZlFzMaIthcjoV2I0XVYPBlBvp54a2wnhMm9beo5Q6W5rg0ZIwThAjRErNzWSgVTnghTeS6spZimBK7mj41FoK+nUc+Ipc9C3EEnv0dAQQ/L5M+Sm/Te/XGCjdHhsWFUmtvIIGOEIFyAhoiV2+J9sdYTYa2Bk1dajRfWHNdZpu3ip2oKNvTDIoW3api2mzmkDWYP78A0+dvqybBWbdUarJGYJ8SBjBGCcAFYqkhGx6mfFK29gdrifbHVE6FtPPATQn5pFRZtO8Ns4GiHfZytmiIu3B/p18ocPQwNM4e0QULb5ga/FdbzltC2uaDfmLUiY7aqrQqhIY0ewhBKBScIF4F/wgyT604YvFbW9wezMWl5KgYs3oXkdPMdcI3RMyoQluYXqUS9njZKFYeDFw17rgiBnwST0/MwYPEuTFqeitm/nDCqwmkKfsJauCUDPaMCoZB7mYw6SKCeaN4c09GmcbOi/505Ej4/JL5NsIExYO1vgAU+x+e+bi2NHlsfS2qrgPq7VorQwZA3evQNat7oseZ6IoRBxghBuBCj4hQ4MHco1s7oh6cSogEY9qux9gYqRHKehzceWNqymyLAxwMqFYftJ68ZnRCEwId9juWUYME4tZia/pSnnXj55IDWZo0WsTAm4OUoekYFYuvJa0jJLDKYyK35DShVHFIyi7Ap7arRfVq73pId55hzmGyhIY0ewjQUpiEIF8NNKkGfmCDM+SXN6PtCenRoIzRnRKzS2ZuVdZjy3WFIJcK1Ukxxvbwa93VryZSroN012R4E+nige2QgVh/OtbjuhG7h2JjG1kjOWraezMPWk2pDVT8MYc1vgCW0wZqEXFJRi0XbhPWwsTU/SEyJecJ6yBghCBfEHjdQITkjQhJWTSmj6iPmgyf/WVhyFUbFKfDMoBgDuXqx4MDuGXmgRytsPnHNLuMwhn7uRYgvWyPCEF8Zcz6HkCRka7A1P4gk5p0DMkYIwgWxxw1USMWOkIRVbWXU1EtFSPzpOG5WmTZKbEFIVRGfKLsjIx/fH8y2y3iA26XNErUnwNw5U8i9IJVIBBsiQmT69dH3orHGq1Sc5dDG6+tPwdfDHe9sto/ei1hqqyQx7xyQMUIQLog9bqAsmhC8HgWrkTNzSFvMHt5e44mQSiR2NUS0xwiYDg8Yk7G3J4W3anTCQabObWEFW2mtNi38vTCpTySiQ3xwvawa720/K2h7bS8aa2nvYQZj9GZlHaauOCJoLKxYko0XAknMOweUwEoQLgh/A7VULSL0BmqqYidM7qVTRsleAhqiM1nY4uoO8vXAkke6Ye2MfvhycneD0If+GE1VSOSVVuPrfVkNKooW6ufFdG6tefouKKvGpzvPQ+YuRWy43Oox8mEsNhybzBkm98Lnk7rjakkV3t6Uju/2X0JtvcqqffFGuKlPxEEco4cwD3lGCMIFEeLFEApLnoW1T5PWTLb8Ud+/v7OOoaE/IWq32RJbDr5XVACO5twUvJ3+ebB0bntGBUIiAYR0DNOu+HhtZAfBY+Thx8Lyvca3DrGpgspaZg5pi4S2Idh1Nh8vrftXJ6T13vYzmDEwBvPGxDb4uAjbIc8IQbgorF4Ma7CkCcEbQ4D50ln97Sx5dAAY6FyY8njkl+mGFArKajQlzWLLwbcK9BG8janzYO7c/pNdLMgQ0SavtFqQLov2OHkvGuv32q9NMBQNrJ2i1kdpjz3nCrB8f7ZBbo2KA77el4Wk7RmC9ssbrqbgc2qotNe+kGeEIFwYa5UtxTq2UJlvFo/OF5N6mOw5Y0kTgp84JnZvKcpn5D0BD3RvJbjkVjtxNyWziOn7OXSx0KbxBvp4mvVs6GPMYNKuLtI2jCQSYMbAGM33Or6rAl/vy7JpvEIY31UBpYrD8v3mj7l8fxZeHtERnu5sz9pU2usckDFCEC6Oue619sYaY8iWXiWsE8fSPbaHELQn6v7tQiyWJsu93fHllJ4ovFWjOQ87MvIxYPEuZonxqyVVNo25pLIWC8bF4jlG3RRj5zw5PQ/f7MsyMGZUHPDNvix0jwzE8NgwbD7RsKqkm0/kIaSZjEmUbVVKNp4a2Jppv1Ta6xyQMUIQhE1YYwxZ69FpyAlBf6L+YGJns5P84ge6IKFtiOa10L4qShWHGzZ+viBfT4vrzB7WDtEhvkbPOUuuzcItGfDz8mjwrsh5pdX4J7vE8ooAcoormfdLpb3OARkjBEE4BGuMmIaYEJ5KiMaw2DCj4mhfPdYDCzalo6D8Tm5GCz9PLLwvzsCwYAkn8Qq5xkqQrSHUzwuv/HbC5PsSAOv+uYwDc4fqhL54o7CwvIbJ85SSWWTTOPUZEdsCf2UUWFzP19ONaX9RQew5PlTa6xwITmDdt28fxo0bh/DwcEgkEmzcuJF524MHD8Ld3R3dunUTeliCIFwc1t4k5mBJgLWEQu6FZwfFGCRgKuRe+OqxHpg/7i6zjdwkEqnZ14CwPARTJchCkUrUYmRC+rkkp+ch4QN1Y8KX1qVh0bYzjEcTN5mzfYtmTOtN7NGKqZHf1Pho5mNbm4xNiItgz0hFRQW6du2KJ598EhMnTmTe7ubNm5g2bRruueceFBRYtoAJgmg8iNWe3VwCLAszh7TB7OEd4CaV4LVRnQSFiUyFXQrKDMMurOGk/LJqfJh8VpSpXcUBh7PYPBbXy6uRnJ7HnFuiT9/oYPwuv8qcKGuJ+NYh+P246f3x3on+bUMwY2CM2cTZGQNjmJNXeWzJYyLEQbAxMnr0aIwePVrwgZ577jlMnjwZbm5ugrwpBEG4NkJzJyxhauJgIaFtc43BISRMJDTswhpOKr5lPiwiHLan9xBfGRLXWt8XRupmm1HIwxsZ/doEM+vm8Doi+r2EpLerfazVGXFkZRrRQDkjK1aswKVLl7B69Wq8++67DXFIgiCcAKGTOCv6E0dIMxle/iUNBWU1don7Cy3/7BMTZLH6JtDHgynhVAh9Y4Lw+3Hzpb1Bvh44eLHQ7NgsUXirxmRXZFb0jQwh3ol5Y2Lx8oiOWJWSjZziSkQF+WBqfLRgj4g+jqxMa+rY3Ri5cOECXn/9dezfvx/u7myHq6mpQU3NHUGjsrIyew2PIAg7Yk8NB/2J453xd9lFkRawT/knB/aE3Cl9I/DT4csW15NK7ngsTFFcUYcv99pW+qzfFfnjv87iyz2XBO3DmJExKk6BoR1bMBkZnu5S5vJdwvmxqzGiVCoxefJkLFy4EO3bt2feLikpCQsXLrTjyAiCaAgaUsPB1ri/dlWJvoteaPnnkaxii54H7W6+lnIlekUHMxkjhRVqjwUvWia2aKgxD5ObVIKB7UKZjJH5YzshxE+mOb8AdAThSipqsWib7vf37YEsyttoAtjVGCkvL8fRo0fx77//YubMmQAAlUoFjuPg7u6Ov/76C0OHDjXYbt68eZgzZ47mdVlZGSIiIuw5VIIg7EBDazhYG/e3lGDbMyrwdrWK6X1IJereMgC7ccV38zWVSMo3afPz8mDaX0gzGZLT8+yijMoi82/OC6aQe2F6QozZjsrGsDa3iHAt7GqM+Pv749SpUzrLvvzyS+zatQu//fYbYmJijG4nk8kgk8nsOTSCIBoASxoOABDg7QEVx0Gp4kRJFhQa92dJsJV7ezIpfx7LKUF8m2BBRlhpFUM/GUYPh0rJ4fX1pyyvaAWsMv+mPDzaRoypc24MW3KLCNdBsDFy69YtXLx4UfM6KysLaWlpCAoKQmRkJObNm4erV6/ixx9/hFQqRVxcnM72oaGh8PLyMlhOEETjg6UU92ZVHaZ8e9iqUl9bYU2wfW1UR6b98R4RViGtnlGBuPuj3Sb3pzk+Yzfe1KwimxJT9XmsbyR6xwQxy/wbCw/xVS7892pNR2XqD9P4EZx6fPToUXTv3h3du3cHAMyZMwfdu3fH22+/DQDIy8tDbm6uuKMkCMJlMdVdWB/eE5Gc3nA9T1gTbItv1ZhcRxveI8IqpHUsp4Tt+IzdeK/dtK23jT7Xy2tMdm7Wh+9po+9B4m73tOG/V1s6KlN/mMaLYGNk8ODB4DjO4G/lypUAgJUrV2LPnj0mt3/nnXeQlpZm5XAJgnBFRsUpsPfVIXhzTCf4eBiX9ObnsIZs1846uRVV1CDA23TehgTqnAjtxE7eCGvhr2uEhcm9NPkPrMcPaiYzqzzLHz9M7s20P1Z8tOTXzSnoWvIwAXe+V1sMCuoP03ih3jQEQdgd1mTFhnbHs05u5ipFLJcO607RHHfnNevxw/y9mETBLgtoEMfCA91bAbCc4CukhNsag4L6wzR+bFOIIQiCsIA1vVfEdMebe6IXo9eNtqdDG/5z55fphngKymo04Sj++ObgPS6mwl3axw8R0XPg4+mG/u1CTH5/2mE1ISXcQs859YdpGpBnhCAIu2FNsiIgnjve0hO9Lb1ufDzdMHtYezze31CUS4jy7PiuCrOluOO7KjSTsKXS5TB/tvM2c0hbeLhJsGTnBZPrfPJwV+D2OC19jv8+1JXpuKF+XoLPOfWHaRqQMUIQhN0QmqwopjuetScO73F4Z3MG8svYx1pZq8R728/g+4OGolysYYvUzCJsPmE+YXfziTy8NqoTU08dFhn6AB8PzB7eHm5SCTqE+WHBpnQUlN9JkG3h54mF98VhVJwCKZlFTJ8j/epNi4aFtg6LKYE6hdwL88d2QqCvjPrDNDHIGCEIwm4ICbeI6Y63rieOdUmzxkS5WD93yqVCi8aa2Dk02mfWkqeF9XMk/XHO4jraOiwsxyaaFmSMEARhN4SEW8R0xwtJqCytqmUW4DK1L2u79rJ22TVnFGjL2BeW11jUGSmprNMxbsx5WsSuXtH/HNSYjuAhY4QgCLvBpMDq44Glk3qgH4OWBSusT/T5ZdX4MPms1YYIj7GuvSyiZ/FtgvHF7otG1tClsLzGqEIta5WSPqznh0XmXQjWGjfm+gYRjQOqpiEIwm5YEv+SAPhgYmcktAsRdXJhnfSKb9WINtECdyZ5VtGzfq2DmSpLFm07gwGLd+kIwllTpcTDen7cpBKM72q7p8qYDgsryel5GLB4FyYtT8VL69IwaXmqwbkgXB8yRgiCsCssJaliY6l8lJ8cg3w9RT2u9iTP8rnNGS36aJfSWlulJNQoUKo4iwm2LMcErMsFYikrJhoHFKYhCMLuNHSyornyUe3JUe7NZoy8OaYTlu6+iJtVxvMxTFUBsXxuU5Ul+mjnpvh5eQj2iFhjFNgi3c5jbS6QdUnIhKtCxghBEA1CQycrmprktSfH2noVpBKY7cgrlQCP949GRJA3nl99HIBp48bYpMjyuXmjZeXBLCzadsbkenxuSkpmkdn9GcMao8AW8bkAbw8sndID/VpblwskJAmZkmBdHzJGCIJotFjyTBzLKTFriAB3SlJZjBtbcJNKEOInY1ybLUAzf2wnhPjJrPZEWSvdDgAfPNAZCW1DBG/PI0TVlXB9yBghCKJRY84zIXTCs3e4iXXyj28dgt+PX7VYrTM9IcamsbFUQ+l7lsQyzljPBTXPaxyQMUIQRJPFmgnPnuEm1pLgfm2CmXJibDWSWHJvvpjUA4G+nqIbZ6zngprnNQ6omoYgiCYLa9VNQ014rCXBblJJg1UpWTrOmC4KxLcJxn3dWiJeRK0YIeeCcH0knHY/ayelrKwMcrkcpaWl8Pf3d/RwCIJoRPDlo4DxJ397lR9bGpO5Bn/aNJQgmKOEx4ScC8L5YJ2/yRghCKLJ44wTHqmO3oHOhetCxghBEIQAaMIjCPFhnb8pgZUgCALUtI0gHAklsBIEQRAE4VDIGCEIgiAIwqGQMUIQBEEQhEMhY4QgCIIgCIdCxghBEARBEA6FjBGCIAiCIBwKGSMEQRAEQTgUMkYIgiAIgnAoZIwQBEEQBOFQXEKBlVesLysrc/BICIIgCIJghZ+3LXWecQljpLy8HAAQERHh4JEQBEEQBCGU8vJyyOVyk++7RKM8lUqFa9euwc/PDxIJNa4qKytDREQELl++TI0DGwg65w0Lne+Ghc53w9KUzjfHcSgvL0d4eDikUtOZIS7hGZFKpWjVqpWjh+F0+Pv7N/ofsrNB57xhofPdsND5bliayvk25xHhoQRWgiAIgiAcChkjBEEQBEE4FDJGXBCZTIYFCxZAJpM5eihNBjrnDQud74aFznfDQufbEJdIYCUIgiAIovFCnhGCIAiCIBwKGSMEQRAEQTgUMkYIgiAIgnAoZIwQBEEQBOFQyBhxMd577z30798fPj4+CAgIMLpObm4uxo4dCx8fH4SGhuLVV19FfX19ww60EbF06VJER0fDy8sLffv2xZEjRxw9pEbDvn37MG7cOISHh0MikWDjxo0673Mch7fffhsKhQLe3t4YNmwYLly44JjBujhJSUno3bs3/Pz8EBoaigkTJuDcuXM661RXVyMxMRHBwcFo1qwZHnjgARQUFDhoxK7PsmXL0KVLF424WXx8PP744w/N+3S+70DGiItRW1uLhx56CM8//7zR95VKJcaOHYva2locOnQIP/zwA1auXIm33367gUfaOPj5558xZ84cLFiwAMePH0fXrl0xcuRIXL9+3dFDaxRUVFSga9euWLp0qdH3P/zwQ3z++ef46quvcPjwYfj6+mLkyJGorq5u4JG6Pnv37kViYiJSU1OxY8cO1NXVYcSIEaioqNCsM3v2bGzZsgW//vor9u7di2vXrmHixIkOHLVr06pVK3zwwQc4duwYjh49iqFDh+K+++7D6dOnAdD51oEjXJIVK1ZwcrncYPn27ds5qVTK5efna5YtW7aM8/f352pqahpwhI2DPn36cImJiZrXSqWSCw8P55KSkhw4qsYJAG7Dhg2a1yqVigsLC+M++ugjzbKbN29yMpmMW7t2rQNG2Li4fv06B4Dbu3cvx3Hqc+vh4cH9+uuvmnXOnDnDAeBSUlIcNcxGR2BgIPftt9/S+daDPCONjJSUFHTu3BktWrTQLBs5ciTKyso01jjBRm1tLY4dO4Zhw4ZplkmlUgwbNgwpKSkOHFnTICsrC/n5+TrnXy6Xo2/fvnT+RaC0tBQAEBQUBAA4duwY6urqdM53x44dERkZSedbBJRKJdatW4eKigrEx8fT+dbDJRrlEezk5+frGCIANK/z8/MdMSSXpbCwEEql0uj5PHv2rING1XTgf6/Gzj/9lm1DpVJh1qxZSEhIQFxcHAD1+fb09DTIRaPzbRunTp1CfHw8qqur0axZM2zYsAGxsbFIS0uj860FeUacgNdffx0SicTsH01+BEGIRWJiItLT07Fu3TpHD6XR06FDB6SlpeHw4cN4/vnn8fjjjyMjI8PRw3I6yDPiBLz88suYPn262XVat27NtK+wsDCDag8+OzssLMyq8TVVQkJC4ObmZpDdXlBQQOeyAeDPcUFBARQKhWZ5QUEBunXr5qBRuT4zZ87E1q1bsW/fPrRq1UqzPCwsDLW1tbh586bO0zr93m3D09MTbdu2BQD07NkT//zzDz777DM88sgjdL61IM+IE9C8eXN07NjR7J+npyfTvuLj43Hq1Cmdao8dO3bA398fsbGx9voIjRJPT0/07NkTf//9t2aZSqXC33//jfj4eAeOrGkQExODsLAwnfNfVlaGw4cP0/m3Ao7jMHPmTGzYsAG7du1CTEyMzvs9e/aEh4eHzvk+d+4ccnNz6XyLiEqlQk1NDZ1vPcgz4mLk5uaiuLgYubm5UCqVSEtLAwC0bdsWzZo1w4gRIxAbG4upU6fiww8/RH5+Pt566y0kJiZSh0grmDNnDh5//HH06tULffr0waeffoqKigo88cQTjh5ao+DWrVu4ePGi5nVWVhbS0tIQFBSEyMhIzJo1C++++y7atWuHmJgYzJ8/H+Hh4ZgwYYLjBu2iJCYmYs2aNdi0aRP8/Pw0eQlyuRze3t6Qy+V46qmnMGfOHAQFBcHf3x8vvvgi4uPj0a9fPweP3jWZN28eRo8ejcjISJSXl2PNmjXYs2cP/vzzTzrf+ji6nIcQxuOPP84BMPjbvXu3Zp3s7Gxu9OjRnLe3NxcSEsK9/PLLXF1dneMG7eL873//4yIjIzlPT0+uT58+XGpqqqOH1GjYvXu30d/z448/znGcurx3/vz5XIsWLTiZTMbdc8893Llz5xw7aBfF2HkGwK1YsUKzTlVVFffCCy9wgYGBnI+PD3f//fdzeXl5jhu0i/Pkk09yUVFRnKenJ9e8eXPunnvu4f766y/N+3S+7yDhOI5reBOIIAiCIAhCDeWMEARBEAThUMgYIQiCIAjCoZAxQhAEQRCEQyFjhCAIgiAIh0LGCEEQBEEQDoWMEYIgCIIgHAoZIwRBEARBOBQyRgiCIAiCcChkjBAEQRAE4VDIGCEIgiAIwqGQMUIQBEEQxP9vQMFoY2QUjIJRMApGwSgYBQMKAPLJWAR/sqroAAAAAElFTkSuQmCC\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Fourth Experiment:\n",
        "\n",
        "*Polynomial Regression*\n",
        "\n",
        "Ploynomial degree = 4"
      ],
      "metadata": {
        "id": "PfbQrWz3q_JE"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "polFea = PolynomialFeatures(4,include_bias=False)\n",
        "print(\"Polynomial degree = 4\")\n",
        "X_poly = polFea.fit_transform(X_train.values)#.reshape(-1,1))\n",
        "model = LinearRegression()\n",
        "model.fit(X_poly, y_train);"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "iMVo-JlzrDuI",
        "outputId": "0fb3966c-fce2-4acf-a16e-1d129b18093c"
      },
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Polynomial degree = 4\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pol4 = print_eval(polFea.transform(X_test), y_test, model)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "stZItvz9rGft",
        "outputId": "7cfb58ad-d0c5-4320-94fc-fcf6c35e1ccf"
      },
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            " Mean squared error: \t0.021334\n",
            " r2 score: \t\t0.8254\n",
            " f-statistic: \t\t390.05\n",
            " p-value: \t\t1.1102e-16\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Visualize the prediction\n",
        "\n",
        "pred4 = model.predict(polFea.transform((np.arange(min(X.temp), max(X.temp))).reshape(-1,1)))\n",
        "plt.plot(np.arange(min(X.temp), max(X.temp)),pred4, label = \"poly\",color=\"red\")\n",
        "plt.legend()\n",
        "plt.scatter(X,y)\n",
        "plt.plot();"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 430
        },
        "id": "cq8XCysDrIvQ",
        "outputId": "92c41418-7fbd-4390-ec95-320debc5754c"
      },
      "execution_count": 38,
      "outputs": [
        {
          "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": [
        "Much better."
      ],
      "metadata": {
        "id": "W3KOSboyrNAF"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Compare the performances of the four models"
      ],
      "metadata": {
        "id": "41qjBGOqrPqY"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "performance = {\"linear \": [*lin],\n",
        "                \"polynomial d = 2\": [*pol],\n",
        "                \"polynomial d = 3\": [*pol3],\n",
        "                \"polynomial d = 4\": [*pol4] }\n",
        "res = pd.DataFrame(performance, index = ['rmse'\n",
        "                     , 'r2'\n",
        "                     , 'f-statistic'\n",
        "                     , 'p-value'])\n",
        "res"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        },
        "id": "3YA9JguyrTCb",
        "outputId": "03929cf1-2f5d-4a81-d808-c25b498948e7"
      },
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                  linear   polynomial d = 2  polynomial d = 3  \\\n",
              "rmse         1.001591e-01      3.345625e-02      2.174942e-02   \n",
              "r2          -5.366169e+00      5.756325e-01      7.843318e-01   \n",
              "f-statistic  5.327309e+01      3.848865e+02      5.023183e+02   \n",
              "p-value      2.219669e-12      1.110223e-16      1.110223e-16   \n",
              "\n",
              "             polynomial d = 4  \n",
              "rmse             2.133387e-02  \n",
              "r2               7.923317e-01  \n",
              "f-statistic      3.900454e+02  \n",
              "p-value          1.110223e-16  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-611c40ac-4c72-4a08-8a01-1c21edfe0c67\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>linear</th>\n",
              "      <th>polynomial d = 2</th>\n",
              "      <th>polynomial d = 3</th>\n",
              "      <th>polynomial d = 4</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>rmse</th>\n",
              "      <td>1.001591e-01</td>\n",
              "      <td>3.345625e-02</td>\n",
              "      <td>2.174942e-02</td>\n",
              "      <td>2.133387e-02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>r2</th>\n",
              "      <td>-5.366169e+00</td>\n",
              "      <td>5.756325e-01</td>\n",
              "      <td>7.843318e-01</td>\n",
              "      <td>7.923317e-01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>f-statistic</th>\n",
              "      <td>5.327309e+01</td>\n",
              "      <td>3.848865e+02</td>\n",
              "      <td>5.023183e+02</td>\n",
              "      <td>3.900454e+02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>p-value</th>\n",
              "      <td>2.219669e-12</td>\n",
              "      <td>1.110223e-16</td>\n",
              "      <td>1.110223e-16</td>\n",
              "      <td>1.110223e-16</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-611c40ac-4c72-4a08-8a01-1c21edfe0c67')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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            ]
          },
          "metadata": {},
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "As the degree of the polynomial grows, the *rmse* decreases and the R2 (the *Coefficient of determination*) is much much closer to 1, which represent the best case scenario."
      ],
      "metadata": {
        "id": "yVTxJ6uXrhm0"
      }
    }
  ]
}