handwritten_detection.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "lpb5ow8R6cUq"
      },
      "outputs": [],
      "source": [
        "import gzip\n",
        "f = gzip.open('/content/drive/MyDrive/Widya Wicara Test/train-images-idx3-ubyte.gz','r')\n",
        "\n",
        "image_size = 28\n",
        "num_images = 100\n",
        "\n",
        "import numpy as np\n",
        "f.read(16)\n",
        "buf = f.read(image_size * image_size * num_images)\n",
        "data = np.frombuffer(buf, dtype=np.uint8).astype(np.float32)\n",
        "data = data.reshape(num_images, image_size, image_size, 1)"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "len(data)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "DzT2y4XCjGcG",
        "outputId": "d0df80a7-3cc8-43e2-f073-fee4176a65ba"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "100"
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "image = np.asarray(data[99]).squeeze()\n",
        "plt.imshow(image)\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 430
        },
        "id": "T_zAkFvND3yS",
        "outputId": "4a95139b-e56f-49b5-cef7-012cecaa89e7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "f = gzip.open('train-labels-idx1-ubyte.gz','r')\n",
        "f.read(8)\n",
        "for i in range(0,50):\n",
        "    buf = f.read(1)\n",
        "    labels = np.frombuffer(buf, dtype=np.uint8).astype(np.int64)\n",
        "    print(labels)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GfjXaB2kTAap",
        "outputId": "d9926678-ce83-49f4-ed81-c312c802d2fc"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[5]\n",
            "[0]\n",
            "[4]\n",
            "[1]\n",
            "[9]\n",
            "[2]\n",
            "[1]\n",
            "[3]\n",
            "[1]\n",
            "[4]\n",
            "[3]\n",
            "[5]\n",
            "[3]\n",
            "[6]\n",
            "[1]\n",
            "[7]\n",
            "[2]\n",
            "[8]\n",
            "[6]\n",
            "[9]\n",
            "[4]\n",
            "[0]\n",
            "[9]\n",
            "[1]\n",
            "[1]\n",
            "[2]\n",
            "[4]\n",
            "[3]\n",
            "[2]\n",
            "[7]\n",
            "[3]\n",
            "[8]\n",
            "[6]\n",
            "[9]\n",
            "[0]\n",
            "[5]\n",
            "[6]\n",
            "[0]\n",
            "[7]\n",
            "[6]\n",
            "[1]\n",
            "[8]\n",
            "[7]\n",
            "[9]\n",
            "[3]\n",
            "[9]\n",
            "[8]\n",
            "[5]\n",
            "[9]\n",
            "[3]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import os\n",
        "import gzip\n",
        "import struct\n",
        "import urllib.request\n",
        "import numpy as np\n",
        "from skimage.feature import hog\n",
        "from sklearn.svm import SVC\n",
        "from sklearn.metrics import accuracy_score, precision_score, recall_score\n",
        "import matplotlib.pyplot as pl"
      ],
      "metadata": {
        "id": "zfnY54UsevRw"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "def download_mnist(url, filepath):\n",
        "    if not os.path.exists(filepath):\n",
        "        urllib.request.urlretrieve(url, filepath)\n",
        "\n",
        "\n",
        "def read_mnist_labels(filepath):\n",
        "    with gzip.open(filepath, 'rb') as f:\n",
        "        magic, size = struct.unpack(\">II\", f.read(8))\n",
        "        labels = np.frombuffer(f.read(), dtype=np.uint8)\n",
        "    return labels\n",
        "\n",
        "\n",
        "def read_mnist_images(filepath):\n",
        "    with gzip.open(filepath, 'rb') as f:\n",
        "        magic, size, rows, cols = struct.unpack(\">IIII\", f.read(16))\n",
        "        images = np.frombuffer(f.read(), dtype=np.uint8).reshape(size, rows, cols)\n",
        "    return images"
      ],
      "metadata": {
        "id": "jJCMmNN5ewZC"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Download dataset training\n",
        "train_images_url = \"http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz\"\n",
        "train_labels_url = \"http://yann.lecun.com/exdb/mnist/train-labels-idx1-ubyte.gz\"\n",
        "download_mnist(train_images_url, \"train-images-idx3-ubyte.gz\")\n",
        "download_mnist(train_labels_url, \"train-labels-idx1-ubyte.gz\")\n",
        "\n",
        "# Read training images and labels\n",
        "train_images = read_mnist_images(\"train-images-idx3-ubyte.gz\")\n",
        "train_labels = read_mnist_labels(\"train-labels-idx1-ubyte.gz\")\n",
        "\n"
      ],
      "metadata": {
        "id": "ZdL3NaIme1wh"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Menampilkan beberapa gambar dan label\n",
        "num_images_to_display = 5\n",
        "\n",
        "fig, axs = plt.subplots(1, num_images_to_display, figsize=(10, 3))\n",
        "\n",
        "for i in range(num_images_to_display):\n",
        "    image = train_images[i]\n",
        "    label = train_labels[i]\n",
        "\n",
        "    # Menampilkan gambar\n",
        "    axs[i].imshow(image, cmap='gray')\n",
        "    axs[i].axis('off')\n",
        "    axs[i].set_title(f\"Label: {label}\")\n",
        "\n",
        "plt.tight_layout()\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 241
        },
        "id": "5x4TWqhJh3Cv",
        "outputId": "2a3497a4-617e-4d40-bde9-badb63664652"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x300 with 5 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Menampilkan beberapa gambar dan label\n",
        "num_images_to_display = 50\n",
        "num_rows = (num_images_to_display + 4) // 5\n",
        "\n",
        "fig, axs = plt.subplots(num_rows, 5, figsize=(10, 3 * num_rows))\n",
        "\n",
        "for i in range(num_images_to_display):\n",
        "    row = i // 5\n",
        "    col = i % 5\n",
        "    image = train_images[i]\n",
        "    label = train_labels[i]\n",
        "\n",
        "    # Menampilkan gambar\n",
        "    axs[row, col].imshow(image, cmap='gray')\n",
        "    axs[row, col].axis('off')\n",
        "    axs[row, col].set_title(f\"Label: {label}\")\n",
        "\n",
        "# Menghapus subplot yang tidak digunakan\n",
        "if num_images_to_display < num_rows * 5:\n",
        "    for j in range(num_images_to_display, num_rows * 5):\n",
        "        axs[j // 5, j % 5].axis('off')\n",
        "\n",
        "plt.tight_layout()\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "K-X4y50Qg4AL",
        "outputId": "0e03d66a-5b24-484f-c693-4c90d2b3eecb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x3000 with 50 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Extract features using HOG on training dataset\n",
        "hog_features = []\n",
        "for image in train_images:\n",
        "    fd = hog(image, orientations=9, pixels_per_cell=(3, 3), cells_per_block=(2, 2), visualize=False)\n",
        "    hog_features.append(fd)\n",
        "X_train_hog = np.array(hog_features)\n",
        "y_train = train_labels"
      ],
      "metadata": {
        "id": "ejeaxPlRiCtH"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Memilih salah satu gambar\n",
        "image_index = 0\n",
        "image = train_images[image_index]\n",
        "\n",
        "# Ekstraksi fitur HOG\n",
        "hog_features, hog_image = hog(image, orientations=9, pixels_per_cell=(3, 3), cells_per_block=(2, 2), visualize=True)\n",
        "\n",
        "# Menampilkan gambar asli\n",
        "plt.subplot(1, 2, 1)\n",
        "plt.imshow(image, cmap='gray')\n",
        "plt.title(\"Original Image\")\n",
        "plt.axis('off')\n",
        "\n",
        "# Menampilkan gambar hasil HOG\n",
        "plt.subplot(1, 2, 2)\n",
        "plt.imshow(hog_image, cmap='gray')\n",
        "plt.title(\"HOG Image\")\n",
        "plt.axis('off')\n",
        "\n",
        "plt.tight_layout()\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 356
        },
        "id": "G08Xx0ydkSpd",
        "outputId": "855e9b20-449f-4c45-d837-37dff1df7b32"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 2 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Train SVM with HOG features\n",
        "svm = SVC(kernel='linear', decision_function_shape='ovr')\n",
        "svm.fit(X_train_hog, y_train)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 74
        },
        "id": "AO2YKGG7l5I6",
        "outputId": "709221de-a521-4d77-b039-faa08442cb3f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "SVC(kernel='linear')"
            ],
            "text/html": [
              "<style>#sk-container-id-1 {color: black;background-color: white;}#sk-container-id-1 pre{padding: 0;}#sk-container-id-1 div.sk-toggleable {background-color: white;}#sk-container-id-1 label.sk-toggleable__label {cursor: pointer;display: block;width: 100%;margin-bottom: 0;padding: 0.3em;box-sizing: border-box;text-align: center;}#sk-container-id-1 label.sk-toggleable__label-arrow:before {content: \"▸\";float: left;margin-right: 0.25em;color: #696969;}#sk-container-id-1 label.sk-toggleable__label-arrow:hover:before {color: black;}#sk-container-id-1 div.sk-estimator:hover label.sk-toggleable__label-arrow:before {color: black;}#sk-container-id-1 div.sk-toggleable__content {max-height: 0;max-width: 0;overflow: hidden;text-align: left;background-color: #f0f8ff;}#sk-container-id-1 div.sk-toggleable__content pre {margin: 0.2em;color: black;border-radius: 0.25em;background-color: #f0f8ff;}#sk-container-id-1 input.sk-toggleable__control:checked~div.sk-toggleable__content {max-height: 200px;max-width: 100%;overflow: auto;}#sk-container-id-1 input.sk-toggleable__control:checked~label.sk-toggleable__label-arrow:before {content: \"▾\";}#sk-container-id-1 div.sk-estimator input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-label input.sk-toggleable__control:checked~label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 input.sk-hidden--visually {border: 0;clip: rect(1px 1px 1px 1px);clip: rect(1px, 1px, 1px, 1px);height: 1px;margin: -1px;overflow: hidden;padding: 0;position: absolute;width: 1px;}#sk-container-id-1 div.sk-estimator {font-family: monospace;background-color: #f0f8ff;border: 1px dotted black;border-radius: 0.25em;box-sizing: border-box;margin-bottom: 0.5em;}#sk-container-id-1 div.sk-estimator:hover {background-color: #d4ebff;}#sk-container-id-1 div.sk-parallel-item::after {content: \"\";width: 100%;border-bottom: 1px solid gray;flex-grow: 1;}#sk-container-id-1 div.sk-label:hover label.sk-toggleable__label {background-color: #d4ebff;}#sk-container-id-1 div.sk-serial::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: 0;}#sk-container-id-1 div.sk-serial {display: flex;flex-direction: column;align-items: center;background-color: white;padding-right: 0.2em;padding-left: 0.2em;position: relative;}#sk-container-id-1 div.sk-item {position: relative;z-index: 1;}#sk-container-id-1 div.sk-parallel {display: flex;align-items: stretch;justify-content: center;background-color: white;position: relative;}#sk-container-id-1 div.sk-item::before, #sk-container-id-1 div.sk-parallel-item::before {content: \"\";position: absolute;border-left: 1px solid gray;box-sizing: border-box;top: 0;bottom: 0;left: 50%;z-index: -1;}#sk-container-id-1 div.sk-parallel-item {display: flex;flex-direction: column;z-index: 1;position: relative;background-color: white;}#sk-container-id-1 div.sk-parallel-item:first-child::after {align-self: flex-end;width: 50%;}#sk-container-id-1 div.sk-parallel-item:last-child::after {align-self: flex-start;width: 50%;}#sk-container-id-1 div.sk-parallel-item:only-child::after {width: 0;}#sk-container-id-1 div.sk-dashed-wrapped {border: 1px dashed gray;margin: 0 0.4em 0.5em 0.4em;box-sizing: border-box;padding-bottom: 0.4em;background-color: white;}#sk-container-id-1 div.sk-label label {font-family: monospace;font-weight: bold;display: inline-block;line-height: 1.2em;}#sk-container-id-1 div.sk-label-container {text-align: center;}#sk-container-id-1 div.sk-container {/* jupyter's `normalize.less` sets `[hidden] { display: none; }` but bootstrap.min.css set `[hidden] { display: none !important; }` so we also need the `!important` here to be able to override the default hidden behavior on the sphinx rendered scikit-learn.org. See: https://github.com/scikit-learn/scikit-learn/issues/21755 */display: inline-block !important;position: relative;}#sk-container-id-1 div.sk-text-repr-fallback {display: none;}</style><div id=\"sk-container-id-1\" class=\"sk-top-container\"><div class=\"sk-text-repr-fallback\"><pre>SVC(kernel=&#x27;linear&#x27;)</pre><b>In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. <br />On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.</b></div><div class=\"sk-container\" hidden><div class=\"sk-item\"><div class=\"sk-estimator sk-toggleable\"><input class=\"sk-toggleable__control sk-hidden--visually\" id=\"sk-estimator-id-1\" type=\"checkbox\" checked><label for=\"sk-estimator-id-1\" class=\"sk-toggleable__label sk-toggleable__label-arrow\">SVC</label><div class=\"sk-toggleable__content\"><pre>SVC(kernel=&#x27;linear&#x27;)</pre></div></div></div></div></div>"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Download dataset testing\n",
        "test_images_url = \"http://yann.lecun.com/exdb/mnist/t10k-images-idx3-ubyte.gz\"\n",
        "test_labels_url = \"http://yann.lecun.com/exdb/mnist/t10k-labels-idx1-ubyte.gz\"\n",
        "download_mnist(test_images_url, \"t10k-images-idx3-ubyte.gz\")\n",
        "download_mnist(test_labels_url, \"t10k-labels-idx1-ubyte.gz\")\n",
        "\n",
        "# Read testing images and labels\n",
        "test_images = read_mnist_images(\"t10k-images-idx3-ubyte.gz\")\n",
        "test_labels = read_mnist_labels(\"t10k-labels-idx1-ubyte.gz\")"
      ],
      "metadata": {
        "id": "npNpp1ihmuRm"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Extract features using HOG on testing dataset\n",
        "hog_features_test = []\n",
        "for image in test_images:\n",
        "    fd = hog(image, orientations=9, pixels_per_cell=(3, 3), cells_per_block=(2, 2), visualize=False)\n",
        "    hog_features_test.append(fd)\n",
        "X_test_hog = np.array(hog_features_test)\n",
        "y_test = test_labels\n",
        "\n",
        "# Prediksi kelas menggunakan SVM\n",
        "y_pred = svm.predict(X_test_hog)"
      ],
      "metadata": {
        "id": "5AcvpmQpmwKu"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.metrics import confusion_matrix, precision_recall_curve\n",
        "\n",
        "confusion_mat = confusion_matrix(y_test, y_pred)\n",
        "\n",
        "# Display confusion matrix\n",
        "plt.figure(figsize=(8, 6))\n",
        "plt.imshow(confusion_mat, cmap='Blues')\n",
        "plt.title('Confusion Matrix')\n",
        "plt.colorbar()\n",
        "tick_marks = np.arange(10)\n",
        "plt.xticks(tick_marks, np.arange(10))\n",
        "plt.yticks(tick_marks, np.arange(10))\n",
        "plt.xlabel('Predicted Label')\n",
        "plt.ylabel('True Label')\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 564
        },
        "id": "_UHNjwAZm7oM",
        "outputId": "90857ea9-b2db-4c91-e885-740d4fe586f7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x600 with 2 Axes>"
            ],
            "image/png": 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Nm+IyZ63aBAUF6YorrtCaNWvc50pLS7VmzRolJCRYGBkAAIA9WL4pblpamlJSUtSlSxddddVVmjVrlgoLCzV06FCrQwMAAN4W4Dh1eLtPP2Z5sjZo0CD9+OOPmjhxonJzc9WpUyetWrWq3KIDAACAC5HlyZokjRo1SqNGjbI6DAAAUN14kbtptkjWAADABYJ3g5rm36koAABADUdlDQAA+A7DoKb599MBAADUcFTWAACA7zBnzTQqawAAADZGZQ0AAPgOc9ZM8++nAwAAqOGorAEAAN9hzpppJGsAAMB3GAY1zb+fDgAAoIajsgYAAHyHYVDTqKwBAADYGJU1AADgQ9UwZ83Pa0/+/XQAAAA1nF9U1r575U6FhYVZHYYp9a4cZXUIVXI46wWrQwAA1GTMWTONyhoAAICN+UVlDQAA1BAORzXss+bflTWSNQAA4Dtsimuafz8dAABABTZs2KB+/fopNjZWDodDK1as8LhuGIYmTpyomJgYhYSEKDExUXv27PFo88svvyg5OVlhYWGKiIjQ8OHDVVBQ4NHm888/1zXXXKPg4GDFxcVpxowZpmMlWQMAAL5TtsDA24dJhYWF6tixo+bOnVvh9RkzZmj27NmaP3++tmzZojp16igpKUnHjx93t0lOTtauXbuUkZGhlStXasOGDRo5cqT7usvlUu/evRUfH6/t27frL3/5iyZPnqwFCxaYipVhUAAAcMHp06eP+vTpU+E1wzA0a9YsPf744+rfv78k6e9//7uioqK0YsUKDR48WF9++aVWrVqlrKwsdenSRZI0Z84c3XjjjXrmmWcUGxurpUuXqri4WK+88oqCgoLUrl07ZWdna+bMmR5J3blQWQMAAL5TNmfN24dOVbJ+exQVFVUpxH379ik3N1eJiYnuc+Hh4eratasyMzMlSZmZmYqIiHAnapKUmJiogIAAbdmyxd2mR48eCgoKcrdJSkrS7t27dfjw4UrHQ7IGAAD8QlxcnMLDw91Henp6lfrJzc2VJEVFRXmcj4qKcl/Lzc1Vw4YNPa7XqlVLkZGRHm0q6uO396gMhkEBAIDvVOOmuDk5OR6b5DudTu/exyJU1gAAgF8ICwvzOKqarEVHR0uSDh065HH+0KFD7mvR0dHKy8vzuH7y5En98ssvHm0q6uO396gMkjUAAOA71ThnzVuaNm2q6OhorVmzxn3O5XJpy5YtSkhIkCQlJCToyJEj2r59u7vN2rVrVVpaqq5du7rbbNiwQSdOnHC3ycjIUKtWrVSvXr1Kx0OyBgAAfMcmW3cUFBQoOztb2dnZkk4tKsjOztb+/fvlcDg0ZswYPfHEE3r33Xe1Y8cO3XXXXYqNjdWAAQMkSW3atNENN9ygESNGaOvWrfrPf/6jUaNGafDgwYqNjZUk3XHHHQoKCtLw4cO1a9cuvfHGG3r++eeVlpZmKlbmrAEAgAvOtm3bdN1117k/lyVQKSkpWrRokR555BEVFhZq5MiROnLkiK6++mqtWrVKwcHB7u8sXbpUo0aNUq9evRQQEKBbbrlFs2fPdl8PDw/Xhx9+qNTUVF1xxRW6+OKLNXHiRFPbdkiSwzAM4zyf1zIul0vh4eE69HO+x4TCmqDelaOsDqFKDme9YHUIAIAqcrlciqofrvx83/+5WfZndnC/F+SoHeLVvo0Tv+r4e6MseS5fYBgUAADAxhgGBQAAPuNwOOSopq07/BWVNQAAABujsgYAAHzH8b/D2336MSprAAAANmZpsrZhwwb169dPsbGxcjgcWrFihZXhAACAalY2Z83bhz+zNFkrLCxUx44dNXfuXCvDAAAAPkKyZp6lc9b69OmjPn36WBkCAACArdWoBQZFRUUqKipyf3a5XBZGAwAAzGLrDvNq1AKD9PR0hYeHu4+4uDirQwIAAKhWNSpZGz9+vPLz891HTk6O1SEBAAATmLNmXo0aBnU6nXI6nVaHAQAA4DM1KlkDAAA1HJvimmZpslZQUKC9e/e6P+/bt0/Z2dmKjIxU48aNLYwMAADAHixN1rZt26brrrvO/TktLU2SlJKSokWLFlkUFQAAqC6sBjXP0mTt2muvlWEYVoYAAABga8xZAwAAPuNwqBoqa97tzm5I1gAAgM84VB1bbfh3tlaj9lkDAAC40FBZAwAAPsMCA/OorAEAANgYlTUAAOA7bIprGpU1AAAAG6OyBgAAfKca5qwZzFkDAACAVaisAQAAn6mO1aDe37fNXkjWAACAz5CsmccwKAAAgI1RWQMAAL7D1h2mUVkDAACwMSprAADAZ5izZh6VNQAAABujsmaRw1kvWB1CldT7w2yrQ6iyw+8+aHUIAHDBo7JmHpU1AAAAG6OyBgAAfIbKmnkkawAAwGdI1sxjGBQAAMDGqKwBAADfYVNc06isAQAA2BiVNQAA4DPMWTOPyhoAAICNUVkDAAA+Q2XNPCprAAAANkZlDQAA+AyVNfNI1gAAgO+wdYdpDIMCAADYGJU1AADgMwyDmkdlDQAAwMaorAEAAJ+hsmYelTUAAAAbo7IGAAB8xqFqqKz5+XJQSytr6enpuvLKKxUaGqqGDRtqwIAB2r17t5UhAQAA2Iqlydr69euVmpqqzZs3KyMjQydOnFDv3r1VWFhoZVgAAKCalM1Z8/bhzywdBl21apXH50WLFqlhw4bavn27evToYVFUAACg2rAprmm2mrOWn58vSYqMjKzwelFRkYqKityfXS6XT+ICAACwim1Wg5aWlmrMmDHq3r272rdvX2Gb9PR0hYeHu4+4uDgfRwkAAM4Hw6Dm2SZZS01N1c6dO/X666+fsc348eOVn5/vPnJycnwYIQAAgO/ZYhh01KhRWrlypTZs2KBGjRqdsZ3T6ZTT6fRhZAAAwJvYFNc8S5M1wzD0wAMPaPny5Vq3bp2aNm1qZTgAAAC2Y2mylpqaqmXLlumdd95RaGiocnNzJUnh4eEKCQmxMjQAAFANHI5Th7f79GeWzlmbN2+e8vPzde211yomJsZ9vPHGG1aGBQAAYBuWD4MCAIALx6nKmrfnrHm1O9uxxQIDAABwgaiGYVB/3xTXNlt3AAAAoDwqawAAwGfYusM8KmsAAAA2RmUNAAD4DFt3mEdlDQAAwMaorAEAAJ8JCHAoIMC7pTDDy/3ZDZU1AAAAGyNZAwAAPlM2Z83bhxklJSWaMGGCmjZtqpCQEDVv3lzTpk3z2KzfMAxNnDhRMTExCgkJUWJiovbs2ePRzy+//KLk5GSFhYUpIiJCw4cPV0FBgTd+Jg8kawAAwGfKtu7w9mHG008/rXnz5umFF17Ql19+qaefflozZszQnDlz3G1mzJih2bNna/78+dqyZYvq1KmjpKQkHT9+3N0mOTlZu3btUkZGhlauXKkNGzZo5MiRXvutyjBnDQAAXFA2bdqk/v37q2/fvpKkJk2a6LXXXtPWrVslnaqqzZo1S48//rj69+8vSfr73/+uqKgorVixQoMHD9aXX36pVatWKSsrS126dJEkzZkzRzfeeKOeeeYZxcbGei1eKmsAAMBnqnMY1OVyeRxFRUUVxtCtWzetWbNGX3/9tSTps88+08aNG9WnTx9J0r59+5Sbm6vExET3d8LDw9W1a1dlZmZKkjIzMxUREeFO1CQpMTFRAQEB2rJli1d/MyprAADAL8TFxXl8njRpkiZPnlyu3WOPPSaXy6XWrVsrMDBQJSUlmj59upKTkyVJubm5kqSoqCiP70VFRbmv5ebmqmHDhh7Xa9WqpcjISHcbbyFZAwAAPlOdr5vKyclRWFiY+7zT6ayw/ZtvvqmlS5dq2bJlateunbKzszVmzBjFxsYqJSXFq7F5A8kaAADwC2FhYR7J2pmMGzdOjz32mAYPHixJ6tChg77//nulp6crJSVF0dHRkqRDhw4pJibG/b1Dhw6pU6dOkqTo6Gjl5eV59Hvy5En98ssv7u97C3PWAACAz9hhNeixY8cUEOCZAgUGBqq0tFSS1LRpU0VHR2vNmjXu6y6XS1u2bFFCQoIkKSEhQUeOHNH27dvdbdauXavS0lJ17dq1qj9PhaiswZTD7z5odQhVVu/Wl6wOoUoOvzXC6hCq5Lf7FdU03h6iwdnxzwp8rV+/fpo+fboaN26sdu3a6dNPP9XMmTM1bNgwSaf+dx0zZoyeeOIJtWzZUk2bNtWECRMUGxurAQMGSJLatGmjG264QSNGjND8+fN14sQJjRo1SoMHD/bqSlCJZA0AAPiQHV7kPmfOHE2YMEH333+/8vLyFBsbq3vuuUcTJ050t3nkkUdUWFiokSNH6siRI7r66qu1atUqBQcHu9ssXbpUo0aNUq9evRQQEKBbbrlFs2fP9tZjuTmMGvyfNC6XS+Hh4Tr0c36lxqhxYaOy5ls1+P9aqJb4GP+s+I7L5VJU/XDl5/v+z82yP7M7PPauAoPreLXvkuOF2vHUHyx5Ll9gzhoAAICNMQwKAAB8xg7DoDUNlTUAAAAbo7IGAAB8pjo3xfVXVNYAAABsjMoaAADwGeasmUdlDQAAwMaorAEAAJ9hzpp5VNYAAABsjMoaAADwGeasmUeyBgAAfIZhUPMYBgUAALAxKmsAAMB3qmEYVP5dWKOyBgAAYGdU1gAAgM8wZ808KmsAAAA2RmUNAAD4DFt3mGdpZW3evHm67LLLFBYWprCwMCUkJOiDDz6wMiQAAABbsbSy1qhRIz311FNq2bKlDMPQ4sWL1b9/f3366adq166dlaEBAIBqwJw18yxN1vr16+fxefr06Zo3b542b95cYbJWVFSkoqIi92eXy1XtMQIAAO9hGNQ82ywwKCkp0euvv67CwkIlJCRU2CY9PV3h4eHuIy4uzsdRAgAA+JblydqOHTtUt25dOZ1O3XvvvVq+fLnatm1bYdvx48crPz/ffeTk5Pg4WgAAcD7KhkG9ffgzy1eDtmrVStnZ2crPz9c//vEPpaSkaP369RUmbE6nU06n04IoAQAArGF5shYUFKQWLVpIkq644gplZWXp+eef14svvmhxZAAAwNtYYGCe5cOgpystLfVYRAAAAHAhs7SyNn78ePXp00eNGzfW0aNHtWzZMq1bt06rV6+2MiwAAFBNWA1qnqXJWl5enu666y4dPHhQ4eHhuuyyy7R69Wpdf/31VoYFAABgG5Ymay+//LKVtwcAAD7GnDXzLF9gAAAALhwMg5pnuwUGAAAA+P+orAEAAJ9hGNQ8KmsAAAA2RmUNAAD4jEPVMGfNu93ZDpU1AAAAG6OyBgAAfCbA4VCAl0tr3u7PbqisAQAA2BiVNQAA4DPss2YeyRoAAPAZtu4wj2FQAAAAG6OyBgAAfCbAcerwdp/+jMoaAACAjVFZAwAAvuOohjlmVNYAAABgFSpruGAcfmuE1SFUycV3LLI6hCr5adkQq0NADVGTV/IZhmF1CKbYIV627jCPyhoAAICNUVkDAAA+4/jfX97u05+RrAEAAJ9h6w7zGAYFAACwMSprAADAZ3jdlHlU1gAAAGyMyhoAAPAZtu4wj8oaAACAjVFZAwAAPhPgcCjAy6Uwb/dnN1TWAAAAbIzKGgAA8BnmrJlHsgYAAHyGrTvMq1Sy9vnnn1e6w8suu6zKwQAAAMBTpZK1Tp06yeFwyDCMCq+XXXM4HCopKfFqgAAAwH8wDGpepZK1ffv2VXccAAAAqEClkrX4+PjqjgMAAFwA2LrDvCpt3bFkyRJ1795dsbGx+v777yVJs2bN0jvvvOPV4AAAAC50ppO1efPmKS0tTTfeeKOOHDninqMWERGhWbNmeTs+AADgRxzVdPgz08nanDlz9NJLL+nPf/6zAgMD3ee7dOmiHTt2eDU4AACAC53pZG3fvn26/PLLy513Op0qLCysciBPPfWUHA6HxowZU+U+AACAvZXts+btw5+ZTtaaNm2q7OzscudXrVqlNm3aVCmIrKwsvfjii+zRBgCAnwtwVM/hz0y/wSAtLU2pqak6fvy4DMPQ1q1b9dprryk9PV1/+9vfTAdQUFCg5ORkvfTSS3riiSdMfx8AAMCfmU7W7r77boWEhOjxxx/XsWPHdMcddyg2NlbPP/+8Bg8ebDqA1NRU9e3bV4mJiedM1oqKilRUVOT+7HK5TN8PAABYh9dNmVeld4MmJycrOTlZx44dU0FBgRo2bFilm7/++uv65JNPlJWVVan26enpmjJlSpXuBQAAUBNV+UXueXl52r17t6RTGW2DBg1MfT8nJ0ejR49WRkaGgoODK/Wd8ePHKy0tzf3Z5XIpLi7O1H0BAIC1/LwQ5nWmk7WjR4/q/vvv12uvvabS0lJJUmBgoAYNGqS5c+cqPDy8Uv1s375deXl56ty5s/tcSUmJNmzYoBdeeEFFRUUeW4NIp1acOp1OsyEDAADUWKZXg959993asmWL/vWvf+nIkSM6cuSIVq5cqW3btumee+6pdD+9evXSjh07lJ2d7T66dOmi5ORkZWdnl0vUAABAzcfWHeaZTtZWrlypV155RUlJSQoLC1NYWJiSkpL00ksv6b333qt0P6GhoWrfvr3HUadOHdWvX1/t27c3GxYAAECl/fDDD7rzzjtVv359hYSEqEOHDtq2bZv7umEYmjhxomJiYhQSEqLExETt2bPHo49ffvlFycnJCgsLU0REhIYPH66CggKvx2o6Watfv36FQ53h4eGqV6+eV4ICAAD+yQ77rB0+fFjdu3dX7dq19cEHH+iLL77Qs88+65HHzJgxQ7Nnz9b8+fO1ZcsW1alTR0lJSTp+/Li7TXJysnbt2qWMjAytXLlSGzZs0MiRI731U7mZnrP2+OOPKy0tTUuWLFF0dLQkKTc3V+PGjdOECRPOK5h169ad1/cBAIC92WHrjqefflpxcXFauHCh+1zTpk3df28YhmbNmqXHH39c/fv3lyT9/e9/V1RUlFasWKHBgwfryy+/1KpVq5SVlaUuXbpIOvVKzhtvvFHPPPOMYmNjvfBkp1QqWbv88ss9fog9e/aocePGaty4sSRp//79cjqd+vHHH03NWwMAAPCW0/dfPdPCxHfffVdJSUm69dZbtX79el1yySW6//77NWLECEmnXq2Zm5urxMRE93fCw8PVtWtXZWZmavDgwcrMzFRERIQ7UZOkxMREBQQEaMuWLbr55pu99lyVStYGDBjgtRsCAIALl+N/h7f7lFRuO69JkyZp8uTJ5dp/++23mjdvntLS0vSnP/1JWVlZevDBBxUUFKSUlBTl5uZKkqKiojy+FxUV5b6Wm5tbbp/ZWrVqKTIy0t3GWyqVrE2aNMmrNwUAAPC2nJwchYWFuT+fabuv0tJSdenSRU8++aSkUyOIO3fu1Pz585WSkuKTWM0wvcAAAACgqgIcjmo5JLl3qSg7zpSsxcTEqG3bth7n2rRpo/3790uSe07+oUOHPNocOnTIfS06Olp5eXke10+ePKlffvnF3cZbTCdrJSUleuaZZ3TVVVcpOjpakZGRHgcAAICdde/e3f0WpjJff/214uPjJZ1abBAdHa01a9a4r7tcLm3ZskUJCQmSpISEBB05ckTbt293t1m7dq1KS0vVtWtXr8ZrOlmbMmWKZs6cqUGDBik/P19paWkaOHCgAgICKhwXBgAAKONwVM9hxkMPPaTNmzfrySef1N69e7Vs2TItWLBAqamp/4vRoTFjxuiJJ57Qu+++qx07duiuu+5SbGysex5/mzZtdMMNN2jEiBHaunWr/vOf/2jUqFEaPHiwV1eCSlVI1pYuXaqXXnpJDz/8sGrVqqXbb79df/vb3zRx4kRt3rzZq8EBAAB425VXXqnly5frtddeU/v27TVt2jTNmjVLycnJ7jaPPPKIHnjgAY0cOVJXXnmlCgoKtGrVKo/3mS9dulStW7dWr169dOONN+rqq6/WggULvB6v6X3WcnNz1aFDB0lS3bp1lZ+fL0m66aabznufNQAA4N/ssM+adCpvuemmm87a59SpUzV16tQztomMjNSyZctM39ss05W1Ro0a6eDBg5Kk5s2b68MPP5QkZWVl8ZJ1AAAALzOdrN18883uCXcPPPCAJkyYoJYtW+quu+7SsGHDvB4gAADwH3aYs1bTmB4Gfeqpp9x/P2jQIMXHx2vTpk1q2bKl+vXr59XgAACAf/ntVhve7NOfnfc+a7/73e+Ulpamrl27ujeXAwAAgHd4bVPcgwcPssAAAACcFcOg5vEGAwAAABszPWcNAACgquyydUdNQrKGC0ZpqWF1CFXy07IhVodQJS1Gr7A6hCrb+/wAq0NADVHTkoSaFi9OqXSylpaWdtbrP/7443kHAwAA/FuAvD8Hy9/ndFU6Wfv000/P2aZHjx7nFQwAAAA8VTpZ+/jjj6szDgAAcAFgzpp5zFkDAAA+43BIAV7Orfw8V/P7YV4AAIAajcoaAADwmYBqqKx5uz+7obIGAABgY1TWAACAz7DAwLwqVdb+/e9/684771RCQoJ++OEHSdKSJUu0ceNGrwYHAABwoTOdrL399ttKSkpSSEiIPv30UxUVFUmS8vPz9eSTT3o9QAAA4D/K5qx5+/BnppO1J554QvPnz9dLL72k2rVru893795dn3zyiVeDAwAAuNCZnrO2e/fuCt9UEB4eriNHjngjJgAA4KccDu/vi+bnU9bMV9aio6O1d+/ecuc3btyoZs2aeSUoAADgnwIcjmo5/JnpZG3EiBEaPXq0tmzZIofDoQMHDmjp0qUaO3as7rvvvuqIEQAA4IJlehj0scceU2lpqXr16qVjx46pR48ecjqdGjt2rB544IHqiBEAAPiJAHl/k1d/3zTWdLLmcDj05z//WePGjdPevXtVUFCgtm3bqm7dutURHwAAwAWtypviBgUFqW3btt6MBQAA+DkWGJhnOlm77rrrzrpT8Nq1a88rIAAAAPx/ppO1Tp06eXw+ceKEsrOztXPnTqWkpHgrLgAA4IcC5P3VmwHy79Ka6WTtueeeq/D85MmTVVBQYKqvyZMna8qUKR7nWrVqpa+++spsWAAAAH7Jay9yv/POO3XVVVfpmWeeMfW9du3a6aOPPvr/AdXi3fIAAPgr5qyZ57XMKDMzU8HBweYDqFVL0dHR3goDAADYWHW8y9Pf3w1qOlkbOHCgx2fDMHTw4EFt27ZNEyZMMB3Anj17FBsbq+DgYCUkJCg9PV2NGzeusG1RUZH7xfGS5HK5TN8PAACgJjGdrIWHh3t8DggIUKtWrTR16lT17t3bVF9du3bVokWL1KpVKx08eFBTpkzRNddco507dyo0NLRc+/T09HJz3AAAQM3hcMjrCwwYBv2NkpISDR06VB06dFC9evXO++Z9+vRx//1ll12mrl27Kj4+Xm+++aaGDx9erv348eOVlpbm/uxyuRQXF3fecQAAANiVqWQtMDBQvXv31pdffumVZO10ERERuvTSSyt8UbwkOZ1OOZ1Or98XAAD4BgsMzDP9Oq327dvr22+/rY5YVFBQoG+++UYxMTHV0j8AAEBNYzpZe+KJJzR27FitXLlSBw8elMvl8jjMGDt2rNavX6/vvvtOmzZt0s0336zAwEDdfvvtZsMCAAA1QNlqUG8f/qzSw6BTp07Vww8/rBtvvFGS9Ic//MHjtVOGYcjhcKikpKTSN//vf/+r22+/XT///LMaNGigq6++Wps3b1aDBg1MPAIAAID/qnSyNmXKFN177736+OOPvXbz119/3Wt9AQAA+3P87y9v9+nPKp2sGYYhSerZs2e1BQMAAPwbm+KaZ2rOmsPfl1sAAADYjKmtOy699NJzJmy//PLLeQUEAAD8F5U180wla1OmTCn3BgMAAABUH1PJ2uDBg9WwYcPqigUAAPg5h8Ph9WlV/j5Nq9Jz1vz9hwAAALAj06tBAQAAqoo5a+ZVOlkrLS2tzjgAAABQAVNz1gAAAM4HL3I3j2QNAAD4TIDDoQAvZ1fe7s9uTL/IHQAAAL5DZQ0AAPgMCwzMo7IGAABgY1TWAACA71TDAgNRWQMAAIBVqKwBAACfCZBDAV4uhXm7P7vxi2SttNRQaWnNesNCgL/PhrQhfnPf2jOrv9UhVFnM0KVWh1AlBxcmWx0CgGrgF8kaAACoGdgU1zySNQAA4DNs3WEeCwwAAABsjMoaAADwGV43ZR6VNQAAABujsgYAAHyGBQbmUVkDAACwMSprAADAZwJUDXPW/HxTXCprAAAANkZlDQAA+Axz1swjWQMAAD4TIO8P6/n7MKG/Px8AAECNRmUNAAD4jMPhkMPL45be7s9uqKwBAADYGJU1AADgM47/Hd7u059RWQMAALAxkjUAAOAzZS9y9/ZxPp566ik5HA6NGTPGfe748eNKTU1V/fr1VbduXd1yyy06dOiQx/f279+vvn376qKLLlLDhg01btw4nTx58rxiqQjJGgAAuGBlZWXpxRdf1GWXXeZx/qGHHtJ7772nt956S+vXr9eBAwc0cOBA9/WSkhL17dtXxcXF2rRpkxYvXqxFixZp4sSJXo/R8mTthx9+0J133qn69esrJCREHTp00LZt26wOCwAAVBOHl4+qKigoUHJysl566SXVq1fPfT4/P18vv/yyZs6cqd///ve64oortHDhQm3atEmbN2+WJH344Yf64osv9Oqrr6pTp07q06ePpk2bprlz56q4uPg8oirP0mTt8OHD6t69u2rXrq0PPvhAX3zxhZ599lmPHwwAAPiPsjcYePuQJJfL5XEUFRWdNZbU1FT17dtXiYmJHue3b9+uEydOeJxv3bq1GjdurMzMTElSZmamOnTooKioKHebpKQkuVwu7dq1y0u/1imWrgZ9+umnFRcXp4ULF7rPNW3a1MKIAABATRUXF+fxedKkSZo8eXKFbV9//XV98sknysrKKnctNzdXQUFBioiI8DgfFRWl3Nxcd5vfJmpl18uueZOlydq7776rpKQk3XrrrVq/fr0uueQS3X///RoxYkSF7YuKijyyZJfL5atQAQCAF1Tnprg5OTkKCwtzn3c6nRW2z8nJ0ejRo5WRkaHg4GCvxlIdLB0G/fbbbzVv3jy1bNlSq1ev1n333acHH3xQixcvrrB9enq6wsPD3cfpGTQAALhwhYWFeRxnSta2b9+uvLw8de7cWbVq1VKtWrW0fv16zZ49W7Vq1VJUVJSKi4t15MgRj+8dOnRI0dHRkqTo6Ohyq0PLPpe18RZLk7XS0lJ17txZTz75pC6//HKNHDlSI0aM0Pz58ytsP378eOXn57uPnJwcH0cMAADOR0A1HWb06tVLO3bsUHZ2tvvo0qWLkpOT3X9fu3ZtrVmzxv2d3bt3a//+/UpISJAkJSQkaMeOHcrLy3O3ycjIUFhYmNq2bWsyorOzdBg0Jiam3AO1adNGb7/9doXtnU7nGbNkAACAyggNDVX79u09ztWpU0f169d3nx8+fLjS0tIUGRmpsLAwPfDAA0pISNDvfvc7SVLv3r3Vtm1b/fGPf9SMGTOUm5urxx9/XKmpqV7PVSxN1rp3767du3d7nPv6668VHx9vUUQAAKA61ZQXuT/33HMKCAjQLbfcoqKiIiUlJemvf/2r+3pgYKBWrlyp++67TwkJCapTp45SUlI0depUr8diabL20EMPqVu3bnryySd12223aevWrVqwYIEWLFhgZVgAAOACs27dOo/PwcHBmjt3rubOnXvG78THx+v999+v5sgsnrN25ZVXavny5XrttdfUvn17TZs2TbNmzVJycrKVYQEAgGri7Q1xq+PF8HZjaWVNkm666SbddNNNVocBAABgS5YnawAA4MJRU+as2QnJGgAA8JmqbLVRmT79mb8/HwAAQI1GZQ0AAPgMw6DmUVkDAACwMSprAADAZ6pjqw3/rqtRWQMAALA1KmsAAMBnHI5Th7f79GdU1gAAAGyMyhoAAPCZADkU4OVZZt7uz25I1gAAgM8wDGoew6AAAAA2RmUNAAD4jON/f3m7T39GZQ0AAMDGqKwBAACfYc6aeVTWAAAAbMwvKmsBAQ4FBPh5Wm0ThmFYHUKV1dQX/dbU37ym/t6SdHBhstUhVEm9AXOtDqFKDq9ItToE+JCjGrbuYM4aAAAALOMXlTUAAFAzMGfNPJI1AADgMyRr5jEMCgAAYGNU1gAAgM+wKa55VNYAAABsjMoaAADwmQDHqcPbffozKmsAAAA2RmUNAAD4DHPWzKOyBgAAYGNU1gAAgM+wz5p5JGsAAMBnHPL+sKWf52oMgwIAANgZlTUAAOAzbN1hHpU1AAAAG6OyBgAAfIatO8yjsgYAAGBjVNYAAIDPsHWHeZZW1po0aSKHw1HuSE1NtTIsAAAA27C0spaVlaWSkhL35507d+r666/XrbfeamFUAACgujjk/X3R/LywZm2y1qBBA4/PTz31lJo3b66ePXtaFBEAAKhOAXIowMvjlgF+nq7ZZs5acXGxXn31VaWlpclxhv8Ri4qKVFRU5P7scrl8FR4AAIAlbLMadMWKFTpy5IiGDBlyxjbp6ekKDw93H3Fxcb4LEAAAnDdHNR3+zDbJ2ssvv6w+ffooNjb2jG3Gjx+v/Px895GTk+PDCAEAAHzPFsOg33//vT766CP985//PGs7p9Mpp9Ppo6gAAIDXscLANFtU1hYuXKiGDRuqb9++VocCAABgK5ZX1kpLS7Vw4UKlpKSoVi3LwwEAANWI102ZZ3ll7aOPPtL+/fs1bNgwq0MBAACwHctLWb1795ZhGFaHAQAAfKEaXjfl54U165M1AABw4WB9gXmWD4MCAADgzKisAQAA36G0ZhqVNQAAABujsgYAAHyGrTvMo7IGAABgY1TWAACAzziqYesOr28FYjNU1gAAAGyMyhoAAPAZFoOaR7IGAAB8h2zNNIZBAQAAbIzKGgAA8Bm27jCPyhoAAICNUVkDAAA+w9Yd5lFZAwAAsDEqawAAwGdYDGoeyRouGIZhWB1ClTj8vb4Przm8ItXqEKokOuVVq0OosoOLkq0OwZSa+v+DFzqSNQAA4DuU1kwjWQMAAD7D1h3mscAAAADAxqisAQAAn2HrDvOorAEAANgYlTUAAOAzrC8wj8oaAAC4oKSnp+vKK69UaGioGjZsqAEDBmj37t0ebY4fP67U1FTVr19fdevW1S233KJDhw55tNm/f7/69u2riy66SA0bNtS4ceN08uRJr8dLsgYAAHzHUU2HCevXr1dqaqo2b96sjIwMnThxQr1791ZhYaG7zUMPPaT33ntPb731ltavX68DBw5o4MCB7uslJSXq27eviouLtWnTJi1evFiLFi3SxIkTq/CjnB3DoAAA4IKyatUqj8+LFi1Sw4YNtX37dvXo0UP5+fl6+eWXtWzZMv3+97+XJC1cuFBt2rTR5s2b9bvf/U4ffvihvvjiC3300UeKiopSp06dNG3aND366KOaPHmygoKCvBYvlTUAAOAzjmr6S5JcLpfHUVRUVKmY8vPzJUmRkZGSpO3bt+vEiRNKTEx0t2ndurUaN26szMxMSVJmZqY6dOigqKgod5ukpCS5XC7t2rXLK79VGZI1AADgF+Li4hQeHu4+0tPTz/md0tJSjRkzRt27d1f79u0lSbm5uQoKClJERIRH26ioKOXm5rrb/DZRK7teds2bGAYFAAA+U537rOXk5CgsLMx93ul0nvO7qamp2rlzpzZu3OjdoLyIyhoAAPCZ6lxfEBYW5nGcK1kbNWqUVq5cqY8//liNGjVyn4+OjlZxcbGOHDni0f7QoUOKjo52tzl9dWjZ57I23kKyBgAALiiGYWjUqFFavny51q5dq6ZNm3pcv+KKK1S7dm2tWbPGfW737t3av3+/EhISJEkJCQnasWOH8vLy3G0yMjIUFhamtm3bejVehkEBAIDv2GBX3NTUVC1btkzvvPOOQkND3XPMwsPDFRISovDwcA0fPlxpaWmKjIxUWFiYHnjgASUkJOh3v/udJKl3795q27at/vjHP2rGjBnKzc3V448/rtTU1EoNv5pBsgYAAC4o8+bNkyRde+21HucXLlyoIUOGSJKee+45BQQE6JZbblFRUZGSkpL017/+1d02MDBQK1eu1H333aeEhATVqVNHKSkpmjp1qtfjJVkDAAA+89utNrzZpxmGYZyzTXBwsObOnau5c+eesU18fLzef/99U/euCuasAQAA2BiVNQAA4DPVuXWHv7K0slZSUqIJEyaoadOmCgkJUfPmzTVt2rRKlScBAAAuBJZW1p5++mnNmzdPixcvVrt27bRt2zYNHTpU4eHhevDBB60MDQAAVAMbLAatcSxN1jZt2qT+/furb9++kqQmTZrotdde09atWytsX1RU5PGeL5fL5ZM4AQCAl5CtmWbpMGi3bt20Zs0aff3115Kkzz77TBs3blSfPn0qbJ+enu7xzq+4uDhfhgsAAOBzllbWHnvsMblcLrVu3VqBgYEqKSnR9OnTlZycXGH78ePHKy0tzf3Z5XKRsAEAUIPYYeuOmsbSZO3NN9/U0qVLtWzZMrVr107Z2dkaM2aMYmNjlZKSUq690+n0+q7AAAAAdmZpsjZu3Dg99thjGjx4sCSpQ4cO+v7775Wenl5hsgYAAGq4ati6w88La9bOWTt27JgCAjxDCAwMVGlpqUURAQAA2IullbV+/fpp+vTpaty4sdq1a6dPP/1UM2fO1LBhw6wMCwAAVBMWg5pnabI2Z84cTZgwQffff7/y8vIUGxure+65RxMnTrQyLAAAANuwNFkLDQ3VrFmzNGvWLCvDAAAAvkJpzTTeDQoAAHyGrTvMs3SBAQAAAM6OyhoAAPAZRzVs3eH1rUBshsoaAACAjVFZAwAAPsP6AvOorAEAANgYlTUAAOA7lNZMo7IGAABgY1TWAACAz7DPmnkkawAAwGccqoatO7zbne0wDAoAAGBjVNYAAIDPsL7APCprAAAANkZlDQAA+AyvmzKPyhoAAICNUVkDAAA+xKw1s0jWYIqjBteaDcOwOoQqqalx12Q19Z/zmvrPysFFyVaHUGUX37HI6hBMMU78anUIqAKSNQAA4DPMWTOPZA0AAPgMg6DmscAAAADAxqisAQAAn2EY1DwqawAAADZGZQ0AAPiM439/ebtPf0ZlDQAAwMaorAEAAN9hOahpVNYAAABsjMoaAADwGQpr5pGsAQAAn2HrDvMYBgUAALAxKmsAAMBn2LrDPCprAAAANkZlDQAA+A4rDEyjsgYAAGBjVNYAAIDPUFgzj8oaAACAjVmarB09elRjxoxRfHy8QkJC1K1bN2VlZVkZEgAAqEZl+6x5+/BnliZrd999tzIyMrRkyRLt2LFDvXv3VmJion744QcrwwIAANXG4fW//H0g1LJk7ddff9Xbb7+tGTNmqEePHmrRooUmT56sFi1aaN68eVaFBQAAYCuWLTA4efKkSkpKFBwc7HE+JCREGzdurPA7RUVFKioqcn92uVzVGiMAAPAuXjdlnmWVtdDQUCUkJGjatGk6cOCASkpK9OqrryozM1MHDx6s8Dvp6ekKDw93H3FxcT6OGgAAwLcsnbO2ZMkSGYahSy65RE6nU7Nnz9btt9+ugICKwxo/frzy8/PdR05Ojo8jBgAA8C1L91lr3ry51q9fr8LCQrlcLsXExGjQoEFq1qxZhe2dTqecTqePowQAALCOLfZZq1OnjmJiYnT48GGtXr1a/fv3tzokAABQDdi6wzxLK2urV6+WYRhq1aqV9u7dq3Hjxql169YaOnSolWEBAADYhqXJWn5+vsaPH6///ve/ioyM1C233KLp06erdu3aVoYFAACqyf/fG827ffozS5O12267TbfddpuVIQAAAB9i6w7zbDFnDQAAABWztLIGAAAuLNXxcig/L6xRWQMAALAzKmsAAMB3KK2ZRmUNAADAxqisAQAAn2HrDvOorAEAANgYlTUAAOAz7LNmHpU1AAAAG6OyBgAAfIbFoOaRrAEAAN8hWzONYVAAAAAbI1kDAAA+46imv6pi7ty5atKkiYKDg9W1a1dt3brVy0/rHSRrAADggvPGG28oLS1NkyZN0ieffKKOHTsqKSlJeXl5VodWDskaAADwmbKtO7x9mDVz5kyNGDFCQ4cOVdu2bTV//nxddNFFeuWVV7z/0OepRi8wMAxDknTU5bI4EtQEZf+8AOfiqKGbNvHPuO8ZJ361OgRTyuK18p8VVzX8mV3W5+l9O51OOZ3Ocu2Li4u1fft2jR8/3n0uICBAiYmJyszM9Hp856tGJ2tHjx6VJLVoGmdxJAAA1BxHjx5VeHi4T+8ZFBSk6OhotaymP7Pr1q2ruDjPvidNmqTJkyeXa/vTTz+ppKREUVFRHuejoqL01VdfVUt856NGJ2uxsbHKyclRaGio1/9L2OVyKS4uTjk5OQoLC/Nq39WppsYt1dzYidu3iNv3amrsxF2eYRg6evSoYmNjvdpvZQQHB2vfvn0qLi6ulv4NwyiXC1RUVauJanSyFhAQoEaNGlXrPcLCwmrUv+RlamrcUs2Nnbh9i7h9r6bGTtyefF1R+63g4GAFBwdbdv8yF198sQIDA3Xo0CGP84cOHVJ0dLRFUZ0ZCwwAAMAFJSgoSFdccYXWrFnjPldaWqo1a9YoISHBwsgqVqMrawAAAFWRlpamlJQUdenSRVdddZVmzZqlwsJCDR061OrQyiFZOwOn06lJkybVuPHumhq3VHNjJ27fIm7fq6mxEzfOZtCgQfrxxx81ceJE5ebmqlOnTlq1alW5RQd24DBY6w0AAGBbzFkDAACwMZI1AAAAGyNZAwAAsDGSNQAAABsjWTuDuXPnqkmTJgoODlbXrl21detWq0M6pw0bNqhfv36KjY2Vw+HQihUrrA7pnNLT03XllVcqNDRUDRs21IABA7R7926rw6qUefPm6bLLLnNvXJmQkKAPPvjA6rBMeeqpp+RwODRmzBirQzmnyZMny+FweBytW7e2OqxK+eGHH3TnnXeqfv36CgkJUYcOHbRt2zarwzqrJk2alPu9HQ6HUlNTrQ7trEpKSjRhwgQ1bdpUISEhat68uaZNm1Yj3pt69OhRjRkzRvHx8QoJCVG3bt2UlZVldViwAZK1CrzxxhtKS0vTpEmT9Mknn6hjx45KSkpSXl6e1aGdVWFhoTp27Ki5c+daHUqlrV+/Xqmpqdq8ebMyMjJ04sQJ9e7dW4WFhVaHdk6NGjXSU089pe3bt2vbtm36/e9/r/79+2vXrl1Wh1YpWVlZevHFF3XZZZdZHUqltWvXTgcPHnQfGzdutDqkczp8+LC6d++u2rVr64MPPtAXX3yhZ599VvXq1bM6tLPKysry+K0zMjIkSbfeeqvFkZ3d008/rXnz5umFF17Ql19+qaefflozZszQnDlzrA7tnO6++25lZGRoyZIl2rFjh3r37q3ExET98MMPVocGqxko56qrrjJSU1Pdn0tKSozY2FgjPT3dwqjMkWQsX77c6jBMy8vLMyQZ69evtzqUKqlXr57xt7/9zeowzuno0aNGy5YtjYyMDKNnz57G6NGjrQ7pnCZNmmR07NjR6jBMe/TRR42rr77a6jDO2+jRo43mzZsbpaWlVodyVn379jWGDRvmcW7gwIFGcnKyRRFVzrFjx4zAwEBj5cqVHuc7d+5s/PnPf7YoKtgFlbXTFBcXa/v27UpMTHSfCwgIUGJiojIzMy2M7MKQn58vSYqMjLQ4EnNKSkr0+uuvq7Cw0JavKjldamqq+vbt6/HPeU2wZ88excbGqlmzZkpOTtb+/futDumc3n33XXXp0kW33nqrGjZsqMsvv1wvvfSS1WGZUlxcrFdffVXDhg0r96Jsu+nWrZvWrFmjr7/+WpL02WefaePGjerTp4/FkZ3dyZMnVVJSUu69mSEhITWigozqxRsMTvPTTz+ppKSk3A7GUVFR+uqrryyK6sJQWlqqMWPGqHv37mrfvr3V4VTKjh07lJCQoOPHj6tu3bpavny52rZta3VYZ/X666/rk08+qXFzYbp27apFixapVatWOnjwoKZMmaJrrrlGO3fuVGhoqNXhndG3336refPmKS0tTX/605+UlZWlBx98UEFBQUpJSbE6vEpZsWKFjhw5oiFDhlgdyjk99thjcrlcat26tQIDA1VSUqLp06crOTnZ6tDOKjQ0VAkJCZo2bZratGmjqKgovfbaa8rMzFSLFi2sDg8WI1mDbaSmpmrnzp016r8iW7VqpezsbOXn5+sf//iHUlJStH79etsmbDk5ORo9erQyMjLK/Re83f22MnLZZZepa9euio+P15tvvqnhw4dbGNnZlZaWqkuXLnryySclSZdffrl27typ+fPn15hk7eWXX1afPn0UGxtrdSjn9Oabb2rp0qVatmyZ2rVrp+zsbI0ZM0axsbG2/72XLFmiYcOG6ZJLLlFgYKA6d+6s22+/Xdu3b7c6NFiMZO00F198sQIDA3Xo0CGP84cOHVJ0dLRFUfm/UaNGaeXKldqwYYMaNWpkdTiVFhQU5P6v3iuuuEJZWVl6/vnn9eKLL1ocWcW2b9+uvLw8de7c2X2upKREGzZs0AsvvKCioiIFBgZaGGHlRURE6NJLL9XevXutDuWsYmJiyiXvbdq00dtvv21RROZ8//33+uijj/TPf/7T6lAqZdy4cXrsscc0ePBgSVKHDh30/fffKz093fbJWvPmzbV+/XoVFhbK5XIpJiZGgwYNUrNmzawODRZjztppgoKCdMUVV2jNmjXuc6WlpVqzZk2NmItU0xiGoVGjRmn58uVau3atmjZtanVI56W0tFRFRUVWh3FGvXr10o4dO5Sdne0+unTpouTkZGVnZ9eYRE2SCgoK9M033ygmJsbqUM6qe/fu5baj+frrrxUfH29RROYsXLhQDRs2VN++fa0OpVKOHTumgADPP9oCAwNVWlpqUUTm1alTRzExMTp8+LBWr16t/v37Wx0SLEZlrQJpaWlKSUlRly5ddNVVV2nWrFkqLCzU0KFDrQ7trAoKCjyqDPv27VN2drYiIyPVuHFjCyM7s9TUVC1btkzvvPOOQkNDlZubK0kKDw9XSEiIxdGd3fjx49WnTx81btxYR48e1bJly7Ru3TqtXr3a6tDOKDQ0tNx8wDp16qh+/fq2nyc4duxY9evXT/Hx8Tpw4IAmTZqkwMBA3X777VaHdlYPPfSQunXrpieffFK33Xabtm7dqgULFmjBggVWh3ZOpaWlWrhwoVJSUlSrVs3446Jfv36aPn26GjdurHbt2unTTz/VzJkzNWzYMKtDO6fVq1fLMAy1atVKe/fu1bhx49S6dWvb/9kDH7B6OapdzZkzx2jcuLERFBRkXHXVVcbmzZutDumcPv74Y0NSuSMlJcXq0M6oonglGQsXLrQ6tHMaNmyYER8fbwQFBRkNGjQwevXqZXz44YdWh2VaTdm6Y9CgQUZMTIwRFBRkXHLJJcagQYOMvXv3Wh1Wpbz33ntG+/btDafTabRu3dpYsGCB1SFVyurVqw1Jxu7du60OpdJcLpcxevRoo3HjxkZwcLDRrFkz489//rNRVFRkdWjn9MYbbxjNmjUzgoKCjOjoaCM1NdU4cuSI1WHBBhyGUQO2dQYAALhAMWcNAADAxkjWAAAAbIxkDQAAwMZI1gAAAGyMZA0AAMDGSNYAAABsjGQNAADAxkjWAAAAbIxkDbjADBkyRAMGDHB/vvbaazVmzBifx7Fu3To5HA4dOXKk2u5x+rNWhS/iBICzIVkDbGDIkCFyOBxyOBwKCgpSixYtNHXqVJ08ebLa7/3Pf/5T06ZNq1RbXycuTZo00axZs3xyLwCwq5rxZl7gAnDDDTdo4cKFKioq0vvvv6/U1FTVrl1b48ePL9e2uLhYQUFBXrlvZGSkV/oBAFQPKmuATTidTkVHRys+Pl733XefEhMT9e6770r6/8N506dPV2xsrFq1aiVJysnJ0W233aaIiAhFRkaqf//++u6779x9lpSUKC0tTREREapfv74eeeQRnf464NOHQYuKivToo48qLi5OTqdTLVq00Msvv6zvvvtO1113nSSpXr16cjgcGjJkiCSptLRU6enpatq0qUJCQtSxY0f94x//8LjP+++/r0svvVQhISG67rrrPOKsipKSEg0fPtx9z1atWun555+vsO2UKVPUoEEDhYWF6d5771VxcbH7WmViBwArUVkDbCokJEQ///yz+/OaNWsUFhamjIwMSdKJEyeUlJSkhIQE/fvf/1atWrX0xBNP6IYbbtDnn3+uoKAgPfvss1q0aJFeeeUVtWnTRs8++6yWL1+u3//+92e871133aXMzEzNnj1bHTt21L59+/TTTz8pLi5Ob7/9tm655Rbt3r1bYWFhCgkJkSSlp6fr1Vdf1fz589WyZUtt2LBBd955pxo0aKCePXsqJydHAwcOVGpqqkaOHKlt27bp4YcfPq/fp7S0VI0aNdJbb72l+vXra9OmTRo5cqRiYmJ02223efxuwcHBWrdunb777jsNHTpU9evX1/Tp0ysVOwBYzgBguZSUFKN///6GYRhGaWmpkZGRYTidTmPs2LHu61FRUUZRUZH7O0uWLDFatWpllJaWus8VFRUZISEhxurVqw3DMIyYmBhjxowZ7usnTpwwGjVq5L6XYRhGz549jdGjRxuGYRi7d+82JBkZGRkVxvnxxx8bkozDhw+7zx0/fty46KKLjE2bNnm0HT58uHH77bcbhmEY48ePN9q2betx/dFHHy3X1+ni4+ON55577ozXT5eammrccsst7s8pKSlGZGSkUVhY6D43b948o27dukZJSUmlYq/omQHAl6isATaxcuVK1a1bVydOnFBpaanuuOMOTZ482X29Q4cOHvPUPvvsM+3du1ehoaEe/Rw/flzffPON8vPzdfDgQXXt2tV9rVatWurSpUu5odAy2dnZCgwMNFVR2rt3r44dO6brr7/e43xxcbEuv/xySdKXX37pEYckJSQkVPoeZzJ37ly98sor2r9/v3799VcVFxerU6dOHm06duyoiy66yOO+BQUFysnJUUFBwTljBwCrkawBNnHddddp3rx5CgoKUmxsrGrV8vzXs06dOh6fCwoKdMUVV2jp0qXl+mrQoEGVYigb1jSjoKBAkvSvf/1Ll1xyicc1p9NZpTgq4/XXX9fYsWP17LPPKiEhQaGhofrLX/6iLVu2VLoPq2IHADNI1gCbqFOnjlq0aFHp9p07d9Ybb7yhhg0bKiwsrMI2MTEx2rJli3r06CFJOnnypLZv367OnTtX2L5Dhw4qLS3V+vXrlZiYWO56WWWvpKTEfa5t27ZyOp3av3//GStybdq0cS+WKLN58+ZzP+RZ/Oc//1G3bt10//33u89988035dp99tln+vXXX92J6ObNm1W3bl3FxcUpMjLynLEDgNVYDQrUUMnJybr44ovVv39//fvf/9a+ffu0bt06Pfjgg/rvf/8rSRo9erSeeuoprVixQl999ZXuv//+s+6R1qRJE6WkpGjYsGFasWKFu88333xTkhQfHy+Hw6GVK1fqxx9/VEFBgUJDQzV27Fg99NBDWrx4sb755ht98sknmjNnjhYvXixJuvfee7Vnzx6NGzdOu3fv1rJly7Ro0aJKPecPP/yg7Oxsj+Pw4cNq2bKltm3bptWrV+vrr7/WhAkTlJWVVe77xcXFGj58uL744gu9//77mjRpkkaNGqWAgIBKxQ4AlrN60hwAzwUGZq4fPHjQuOuuu4yLL77YcDqdRrNmzYwRI0YY+fn5hmGcWlAwevRoIywszIiIiDDS0tKMu+6664wLDAzDMH799VfjoYceMmJiYoygoCCjRYsWxiuvvOK+PnXqVCM6OtpwOBxGSkqKYRinFkXMmjXLaNWqlVG7dm2jQYMGRlJSkrF+/Xr399577z2jRYsWhtPpNK655hrjlVdeqdQCA0nljiVLlhjHjx83hgwZYoSHhxsRERHGfffdZzz22GNGx44dy/1uEydONOrXr2/UrVvXGDFihHH8+HF3m3PFzgIDAFZzGMYZZhoDAADAcgyDAgAA2BjJGgAAgI2RrAEAANgYyRoAAICNkawBAADYGMkaAACAjZGsAQAA2BjJGgAAgI2RrAEAANgYyRoAAICNkawBAADY2P8DShLNpBsHZFQAAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.metrics import confusion_matrix, precision_recall_curve\n",
        "\n",
        "confusion_mat = confusion_matrix(y_test, y_pred)\n",
        "\n",
        "# Display confusion matrix\n",
        "plt.figure(figsize=(8, 6))\n",
        "plt.imshow(confusion_mat, cmap='Blues', interpolation='nearest')\n",
        "plt.title('Confusion Matrix')\n",
        "plt.colorbar()\n",
        "\n",
        "tick_marks = np.arange(10)\n",
        "plt.xticks(tick_marks, np.arange(10))\n",
        "plt.yticks(tick_marks, np.arange(10))\n",
        "\n",
        "thresh = confusion_mat.max() / 2.\n",
        "for i in range(confusion_mat.shape[0]):\n",
        "    for j in range(confusion_mat.shape[1]):\n",
        "        plt.text(j, i, format(confusion_mat[i, j], 'd'),\n",
        "                 horizontalalignment=\"center\",\n",
        "                 color=\"white\" if confusion_mat[i, j] > thresh else \"black\")\n",
        "\n",
        "plt.xlabel('Predicted Label')\n",
        "plt.ylabel('True Label')\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 564
        },
        "id": "Dp8IcvSkpoSt",
        "outputId": "2105989b-f450-4865-cae8-ef6bebb3213c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x600 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.metrics import precision_recall_curve\n",
        "from sklearn.preprocessing import label_binarize\n",
        "from itertools import cycle\n",
        "\n",
        "# Convert labels to binary format\n",
        "y_test_binary = label_binarize(y_test, classes=np.arange(10))\n",
        "y_pred_binary = label_binarize(y_pred, classes=np.arange(10))\n",
        "\n",
        "# Compute precision and recall for each class\n",
        "precision = dict()\n",
        "recall = dict()\n",
        "precision_curve = dict()\n",
        "recall_curve = dict()\n",
        "\n",
        "# Compute precision and recall for each class\n",
        "for i in range(10):\n",
        "    precision[i], recall[i], _ = precision_recall_curve(y_test_binary[:, i], y_pred_binary[:, i])\n",
        "    precision_curve[i] = precision[i][:-1]\n",
        "    recall_curve[i] = recall[i][:-1]\n",
        "\n",
        "# Plot precision-recall curves for each class\n",
        "plt.figure(figsize=(8, 6))\n",
        "colors = cycle(['navy', 'turquoise', 'darkorange', 'cornflowerblue', 'teal', 'red', 'green', 'purple', 'pink', 'yellow'])\n",
        "for i, color in zip(range(10), colors):\n",
        "    plt.plot(recall_curve[i], precision_curve[i], color=color, lw=2, label='Class {}'.format(i))\n",
        "\n",
        "plt.xlabel('Recall')\n",
        "plt.ylabel('Precision')\n",
        "plt.title('Precision-Recall Curve (One-vs-Rest)')\n",
        "plt.legend(loc='lower left')\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 564
        },
        "id": "72TdndN3ne7e",
        "outputId": "875a4a8b-3563-4b21-f803-8670c44327fc"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x600 with 1 Axes>"
            ],
            "image/png": 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PtCcrDvz+BMWqVasCWAjQ+7ly5Qrx8fFUq1bNYv5BnyFzwazX66lZsybTpk3LcW3p0qUB6Nu3r0US3LBhw5g9ezYlSpSgZcuWRERE8MEHH7B7926uXr3K5MmTLa4zdepUhg8fzrJly1i7di1vvvkmkyZNYvfu3ZQqVeqB18+iVKlSxs9yt27dKFy4MK+//jpt27alb9++j/Va3N3d2bp1K5s2bWLlypWsXr2a8PBw2rVrx9q1ax/pdw/Ez6py5cqPtFYisTdSzEokeYyKFSuyfv16mjdvnqM4MV8HcPz48YcKjZxwcXGhR48e9OjRA71ez2uvvcbPP//M+PHjc7xW2bJlAThz5oxx2zOLM2fOGB9/HObOnUtKSopxXKFChYeu//DDD/n111/56KOPjAluFStWJDEx0SgUHkTFihVZs2YN0dHRD/TO/vPPP6SlpbF8+XLKlCljnP+vrerHoUePHuzatYtFixYxaNCg/1zv7++fLckoPT2dW7duPdbzhoSE8Oeff7JhwwZOnTqFqqoWSUVZ772zs/N/vpc5UaZMGdzd3Y2VOrIICgoiKCiIpUuXMmPGjBzDDbJqnT7zzDOP/bwVK1bkyJEjtG/f/qFexqlTp1oI7RIlShiPQ0JCeO211zhz5gzh4eF4eHjQo0ePbNeoWbMmNWvW5KOPPmLnzp00b96cn376ic8///yh18+Jl19+menTp/PRRx/Rp08fFEV55NcCoNFoaN++Pe3bt2fatGl8+eWXfPjhh2zatIkOHTr85/mZmZlcu3aNnj17PnSdROIoyJhZiSSPMXDgQHQ6HZ999lm2xzIzM43iplOnTnh7ezNp0iRSU1Mt1t2/3WvO/R2XNBoNtWrVAnhgOaMGDRoQGBjITz/9ZLFm1apVnDp1iu7duz/SazOnefPmdOjQwfjvv8Ssn58fL7/8MmvWrDF2Nho4cCC7du1izZo12dbHxsaSmZkJQL9+/VBVlU8++STbuqz3KsujZf7excXFMWvWrMd+bQ/ilVdeoXjx4owePZqzZ89mezwqKorPP//cOK5YsaIx7jeLX3755bFLnHXo0IGAgADCw8MJDw+nUaNGFiEJgYGBtGnThp9//jlHoXznzp2HXt/Z2ZkGDRpYlDnL4uOPPyYmJoZXXnklm90HDhxg8uTJ1KhRw1jJ43EYOHAgN27c4Ndff832WEpKCklJSQDUr1/f4rNm7gXu168fWq2W+fPns2DBAp555hk8PT2Nj8fHxxs/R1nUrFkTjUZj/F142PVzwsnJidGjR3Pq1CmWLVv2WK8lOjo62+NZjRGy7Mmy/0HVFk6ePElqairNmjV7qJ0SiaMgPbMSSR6jdevWvPzyy0yaNInDhw/TqVMnnJ2dOXfuHAsWLGDGjBn0798fHx8fpk+fzsiRI2nYsCHPPvss/v7+HDlyhOTk5AeGDIwcOZLo6GjatWtHqVKluHLlCv/73/+oU6eOcVv4fpydnZk8eTLPP/88rVu3ZtCgQURGRjJjxgzKlSvHO++8Y823xMhbb73Ft99+y1dffUVYWBjvvvsuy5cv55lnnmH48OHUr1+fpKQkY93Sy5cvU7hwYdq2bcuQIUOYOXMm586do0uXLuj1erZt20bbtm15/fXX6dSpk9Fj/fLLL5OYmMivv/5KYGDgY3tCH4S/vz9LliyhW7du1KlTx6ID2MGDB5k/fz5NmzY1rh85ciSvvPIK/fr1o2PHjhw5coQ1a9ZQuHDhx3peZ2dn+vbtS1hYGElJSUyZMiXbmu+//54WLVpQs2ZNXnzxRSpUqEBkZCS7du3i+vXr/9n+tFevXnz44YfEx8dblOF67rnn2LdvHzNmzODkyZM899xz+Pv7c/DgQf744w8KFSrEwoULcXZ2fqzXBDBkyBAiIiJ45ZVX2LRpE82bN0en03H69GkiIiJYs2bNf4b6BAYG0rZtW6ZNm0ZCQkK2kl4bN27k9ddfZ8CAAQQFBZGZmcmcOXPQarVPJMCzGD58OB9//DGTJ0+md+/ej/xaPv30U7Zu3Ur37t0pW7YsUVFR/PDDD5QqVYoWLVoA4ibIz8+Pn376CW9vbzw9PWncuLHxBmbdunV4eHjQsWPHJ7ZfIrEp9iqjIJEUVB7UAex+hg0bpnp6ej7w8V9++UWtX7++6u7urnp7e6s1a9ZU33vvPfXmzZsW65YvX642a9ZMdXd3V318fNRGjRqp8+fPt3ge89JcCxcuVDt16qQGBgaqLi4uapkyZdSXX35ZvXXrlnHN/aW5sggPD1fr1q2rurq6qgEBAepzzz1nLDX2X69rwoQJ6qP8SXpQB7Ashg8frmq1WvX8+fOqqqpqQkKCOm7cOLVSpUqqi4uLWrhwYbVZs2bqlClT1PT0dON5mZmZ6jfffKNWqVJFdXFxUYsUKaJ27dpVPXDggMV7WatWLdXNzU0tV66cOnnyZPWPP/5QAfXSpUvGdU9amiuLmzdvqu+8844aFBSkurm5qR4eHmr9+vXVL774Qo2LizOu0+l06vvvv68WLlxY9fDwUDt37qyeP3/+gaW5HvaZW7dunQqoiqKo165dy3HNhQsX1KFDh6rFihVTnZ2d1ZIlS6rPPPOMunDhwv98TZGRkaqTk5M6Z86cHB9funSp2rFjR9Xf3191dXVVK1WqpI4ePTrHElOtW7dWq1evnm3+/s+yqoqycZMnT1arV6+uurq6qv7+/mr9+vXVTz75xOK9fBi//vqrCqje3t7ZytxdvHhRfeGFF9SKFSuqbm5uakBAgNq2bVt1/fr1j3RtcugAlsXEiROzlcD7r9eyYcMGtVevXmqJEiVUFxcXtUSJEuqgQYOyladbtmyZWq1aNdXJySnbZ7Nx48bq4MGDH8l+icQRUFT1IfuNEolEIpHkEiNGjODs2bNs27bN3qZIHsDhw4epV68eBw8eNIYnSCSOjhSzEolEIrEJV69eJSgoiA0bNtC8eXN7myPJgdDQUPR6fY6dzyQSR0WKWYlEIpFIJBJJnkVWM5BIJBKJRCKR5FmkmJVIJBKJRCKR5FmkmJVIJBKJRCKR5FmkmJVIJBKJRCKR5FkKXNMEvV7PzZs38fb2/s+WfhKJRCKRSCQS26OqKgkJCZQoUQKN5uG+1wInZm/evEnp0qXtbYZEIpFIJBKJ5D+4du0apUqVeuiaAidmvb29AfHmmLdUlEgkEolEIpE4BvHx8ZQuXdqo2x5GgROzWaEFPj4+UsxKJBKJRCKRODCPEhIqE8AkEolEIpFIJHkWKWYlEolEIpFIJHkWKWYlEolEIpFIJHkWKWYlEolEIpFIJHkWKWYlEolEIpFIJHkWKWYlEolEIpFIJHkWKWYlEolEIpFIJHkWKWYlEolEIpFIJHkWu4rZrVu30qNHD0qUKIGiKCxduvQ/z9m8eTP16tXD1dWVSpUqMXv2bKvbKZFIJBKJRCJxTOwqZpOSkqhduzbff//9I62/dOkS3bt3p23bthw+fJi3336bkSNHsmbNGitbKpFIJBKJRCJxROzazrZr16507dr1kdf/9NNPlC9fnqlTpwJQtWpVtm/fzvTp0+ncubO1zJRIJBKJRCKROCh5KmZ2165ddOjQwWKuc+fO7Nq164HnpKWlER8fb/FPIpFIJBKJRJI/yFNi9vbt2xQtWtRirmjRosTHx5OSkpLjOZMmTcLX19f4r3Tp0rYwVSKRSCQSiURiA/KUmH0Sxo0bR1xcnPHftWvX7G2SRCKRSCQSiSSXsGvM7ONSrFgxIiMjLeYiIyPx8fHB3d09x3NcXV1xdXW1hXkSiUQikUgkEhuTpzyzTZs2ZcOGDRZz69ato2nTpnaySCKRSCQSiURiT+wqZhMTEzl8+DCHDx8GROmtw4cPc/XqVUCECAwdOtS4/pVXXuHixYu89957nD59mh9++IGIiAjeeecde5gvkUjyCZn6TJacWmJvM/I1qqoSl5pqbzMkBQSdqvJ3XCQfR13m0ztX7G2OxMrYVczu37+funXrUrduXQBGjRpF3bp1+fjjjwG4deuWUdgClC9fnpUrV7Ju3Tpq167N1KlT+e2332RZLolE8sREJUXRcU5H+kb0Zc6ROfY2J1+y/+ZNWsyaRcjChaiqam9zJAUAraLwT8I9tqXEsTslHp383OVrFLWA/WWJj4/H19eXuLg4fHx87G2ORCKxAXqdnpToFDyLeGZ7bM6ROQxdKnaA3Jzc2PHCDuoVr/fwC6oqKIo1TM13ZOr1VP7f/7gcGwvA8tBQegQH29coiU3R6fQcOHCLtWsv0LFjBRo3LmWT5/34zmW2JccBMLtEMGWd3WzyvJLc4XH0Wp6Kmc2bJAMb7W2EJC+Slm5vC/IFqXGphPUMY06HOaQnZn9Ph9Qewkv1XhJrM1PpG96Xu8l3H3zB7duhcWOIirKWyfkKJ42GyWb1wd9Zs4a0zMyHn5QUCetegRs7rGydxBYsXXqaxo1/Y/z4TUREnLDZ8wa7mBLDz6Ql2+x5JbZHilmr8w7QHhgNSHEieURuRMHe4xArm3w8LUuHLuXcv+eIPBrJkqFLUPXZN6Nmdp1Jk1JNALgSd4VBiwaRqc9BcC1cCG3awL598OyzoNNZ2fr8wYBq1WhdtiwAF2JimLFnz4MXRx2G3yvB0Z9h8yhQ9bYxUmI12rYtj0YjdjLWrr1os+cNdvEwHp9Oz7kWvSR/IMWsVdkK/GI4ngY0A87ZzxxJ3uBeLJy/Cno9HDsPMVLQPg0dJnfA1UeU5zu95DSbP9mcbY2rkysLBywk0DMQgPUX1/Phhg+zX6xFCwgUa9iwAT75xFpm5ysURWFGly5oDKEZn23dyq2EhJwXF64BPkL4cnsvnA63kZUSaxEQ4E6DBiUAOH48ips3H/Czz2XMPbNn06VnNj8jxaxVaQnMAFwM4wNAPUAmmUgegr8PBPiKY70ejp2D6Dj72pSHKVylMP3C+qEYPENbP93KiQXZtzpL+pRkwYAFOGlE+e2vd37NghMLLBcVKwZhYaDVivFnn8GqVVa1P79Qu1gxXqonYpET09MZd1+ZRSMaJ2g9xTTePg4yZRWEvE6nThWMx+vWXbDJc3prnSjhJL5/z6WnyCSwfIwUs1ZFAd4EdgNBhrlEYKjhn23uTiV5DI0GqleEwn5irKpw/DzcjbWnVXmayl0r0+FrU9zm0mFLuXXwVrZ1rcq2Ymqnqcbx88ue50TUfcK3VSv48kvTePBgMKu6Yg9UVWXn6TRikxx7S/6zdu3wcxNJOH8eOcKe69dzXli+C5TtJI7jr8DBGTayUGItOnWqaDy2R6hBuqpyKUPeFOVXpJi1CXURXtnnzebmILy0B+xikcTB0WigagUo4i/GqgonL8CdGPvalYdpOqopdYbXASAzJZOwXmEk3k7Mtu6NRm8wuNZgAJIykugT3ofY1FjLRWPGQM+e4jg6GgYOhHT7xMQnpOj5YXUiszYm8eemJIcufVXYw4NP27Qxjt9cvRr9g+xtPQUUw1fUni8gWSbc5WWaNCmFl5fwkq5ffxF9DrHr1qCKq0wCKwhIMWszvIA/gHmAt2HuPNAUmAo4tkdFYgeyBG1ggBhnCdqoaPvalUdRFIXuP3WnVFNRFij+ejzhfcPJTMvMtu7nZ36mTrE6AJyLPseQJUPQmyciaTQwezaULy/Ge/bAu+/a4FXkzMXb4jUcv5rBlhNpdrPjUXilQQOqFSkCwN4bN5hz5EjOC4vUhBojxHF6AuycaBsDJVbB2VlLu3bi9yUqKomjRyP/44zcIcgsCeysTALLt0gxa3MGAYeBRoZxBjAG6A5Iz4PkPhQFqpSHooVMc6cuQuQ9+9mUh3FydSJkcQg+pUTNwuu7rrPylZXZvJkezh4sCVlCgLu4kVhxdgWfbfnM8mL+/qK6gatILmPmTIiIsPpruB9vdw3D25nq5y7YmUxkrONWWXDWapnRpYtxPHbDBhLSHiDAm38Kzl7i+OgvcO+kDSyUWAvzuNm1a20TN1vZxZ2sitCnZRJYvkWKWbtQAdgOvG82txqoDay3i0USB0ZRILgcFCtsmjt9CW4/pBaq5IF4FfMidFkoTu4i0evw7MPsnr4727pyfuUI6xeGxrDVPXHLRFacXWG5qF49mGEWzzliBJw5YzXbH0TNsi60qiZEdXom/LEhEZ2NtnGfhA4VKtC7ShUAbicm8vnWrTkv9CwGjcaKY1UHW+zn/ZY8PZZxs7YRs54aLaWdxO/GxfRU0mWpt3yJFLN2wxn4ClgLFDXM3QY6AWMRHluJxICiQFBZKFHENHfmMty6YzeT8jLF6xWn9+zexvG6d9dxblX2snkdK3bki3ZfGMeDFw/m3L371r30kkgCA0hMhH79ICnJGmY/lAHNPSjiI/6kX4zUsfqgYye7TO3UCVdDVYjpu3dz7t4DdhvqvwNeho5Rl/6FK/KGP69SqVIAZcuKSi3btl0lOdk233PBriLUIBOVS+mO/XsheTKkmLU7HYEjQGfDWAUmAy0A22V8SvIAigKVykDJQNPc2SuiwYLksak+sDotP2oJgKpXWRS6iLuns3u732/+Pv2q9gMgLi2OPuF9SEw3SxxTFPjpJ6heXYxPnIDXXhMxzjbEzVlhRAdPY5fdf/ancOXOf3TasiMV/P0Z3bQpABl6PaPWrs15obMHtDSrHrFlNOgdN4xC8mAURTF6Z9PTdWzdesUmz2teb1aGGuRPpJh1CIoC/wJTEB5bgL2IKghh9jJK4ogoClQsDaWKmubOX4XrtkmmyG+0/aQtVfqI7e60+DTm95xPSoxlkoiiKMzqNYtqRaoBcOLOCUYsH2EZZ+vpKeJnPQ2xq3/9Bb//bpPXYE7FYs50rStKX+n08Pv6JDIyHTfcYFzLlpTwFgmxK86eZfX58zkvrPocFK0vju8chROzbWOgJNexR6iBeSewM2kyCSw/IsWsw6BBtLzdCVQyzMUjEsZeAGy/bSlxUBQFKpSCMsVMcxeuwbXb9rMpj6JoFPr81YeitcTNQfS5aBaGLESfaRlX5+3qzZKQJfi4isSxiBMRTNk5xfJiVarAb7+Zxq+/DocOWdX+nOjR0J0yhcX2/a0YHYv3OK4nysvFha87mOr/vr16NRk5tQhWNNBmmmm84yNIz15WTeL4tGtnam27bp1tdh8rubgbxc4Z6ZnNl0gx63A0AA4Cg83mZgH1EVUQJBKEoC1XEsqWMM1dvA5XbtrPpjyKi5cLoctC8SgsvDcX111k7bvZt7yDCgUxp4+pe9/YDWNZf/G++M3QUPi//xPHaWnQvz/ExlrL9Bxx0iq80METJ0OTsvVH0jh9w3Fj8J+tWZNmpUsDcObePb7buzfnhaVaQaXe4jjpNuz7xjYGSnKVgAB3Gja0bWtbN42Gcs5ix+JyRiqpepkElt+QYtYh8UY0VfgLyCq5cwZoDMxExNVKCjyKAuVKCFGbxeWbcPmGzeM18zp+5fwYuGggGifxJ3HPt3s49Ed2r2rP4J6MbzUeAL2qJ3RhKJdjL1sumjoVGjYUxxcvwvDhNv95lAxwok9jU5zgrA1JJKc55he4oijM7NLFWD5p4pYtRD0oga7V16LdLcD+byDhhk1slOQu5qEGtmptmxVqoAfOy3qz+Q4pZh2aIcAhRKcwgHTgLaAnIMsySQyULS7CDrK4cgsuSUH7uJRtVZZuP3Qzjle8soKr27O3qZ3YZiLdKot191Lu0S+iHykZZl+Orq6wYIGoQwuwbJkQuDamQ203gksI4RedqGf+NsfdXq1fogQv1K0LQHxaGh9u2JDzQv/KUMfg+c5MgR0f2shCSW7SsaN5vVnbhBpYdAKToQb5DilmHZ7KiDjaUWZzKxA1aTfZxSKJA1K6mEgMy+LabRF2IAXtY1H/xfo0ekM0NNFn6AnvG07slViLNRpFw999/qaiv/AuHbx1kFdXvmqZEFa2LPz9t2k8dixs325t8++zU+H59p64uwif5+6z6Ry4YJ+Wu4/CF+3a4WNoQPH7oUMcuPmAkJkmH4Ornzg+8RdE2j4uWfJ0mLe2Xbfugk1a21okgUnPbL5Ditk8gSui5e2/QFad0ZtAe2A84LjldyQ2pFRRqFzGNL4eKRLDpKB9LDpP60yFDsJzlHwnmbBeYaQnWYpAf3d/loYuxcNZfEH+eeRPftj3g+WFunWDDw2eQ50OBg6ESNtWnSjkrSW0helL/O8tScQmOWa4QVEvLz5u1QoQgVRvrV6drTMbAO4B0GS8YaCKUl3yM56nMG9te+dOMkeOWD95tbyLG06GYJYzadIzm9+QYjZP0RVRkzYr+1cFPgdaA7ap1ydxcEoEiuYKWdyIEqW75Jf9I6Nx0tA/vD8BlUQr28gjkSwdthT1Pu9RjcAazOo1yzh+e83bbL96n/f1k0+gbVtxfOsWPPusELY2pGmwC/UqiJJ/iakqf21KylkkOgBvNG5McCHRunnHtWvMP34854V1/g/8DHGX1zbBhX9sZKEktzBvbWuLqgYuioaKLiIJ7FpmGkmyVnG+QorZPEdxYA2ie5ghEYKdQB1goZ1skjgUxYuI9rdZ3Lwjmis4qIBxRNwD3AldHoqrj9j2PrXoFFs+3ZJt3cDqAxnTdAwAmfpMBiwYwM0Es+1xrRbmzYPixcV440aYONHa5lugKAqDW3vi4y68UseuZrDtZJpNbXhUXLRapnfubBy/t24dSek5hEY4uULLyabx1ndB57gVGyTZsWe9WRU4J0MN8hVSzOZJNMD7wDagnGEuFhgAvAzILZQCT7HCUKW8aXz7rmh/KwXtI1OkahH6ze9HVpr9lk+2cGLBiWzrJnWYRLvy7QC4nXib/hH9SdeZCbBixSAsTAhbgM8/h1WrrG2+Bd7uGoa19TSOI3YkExXnmJ6prpUr071yZQBuJCQw6UGxxpX7QskW4jjmLBz92UYWSnKDSpUCKFfOD7Bda9sgs05gMtQgfyHFbJ6mCaL2bIjZ3C9AQ+CYPQySOBJFC0E101Yekffg9CUpaB+Dyt0q0/Hrjsbx0mFLuXXolsUaJ40TYf3CKOMr4pV3Xd/F26vftrxQq1YwaZJpPHgwXM1eKcGa1CrnQstqwtOclgl/bEiySeLNkzC9c2ecNeLracrOnVyMicm+SFGgtVmViJ0TITXWJvZJnh7R2lb8fbJVa9sqrjIJLL8ixWyexxeYD/wOZP2ingQaAT8ia9IWcIoEQPWK4osfICoaTl4EWTT8kWk6uim1htQCIDMlk7BeYSRGWnafKuJZhMUDF+OqFWLxx/0/MuvQLMsLjRkDPXuK4+hoGDAActpCtyIDm3tQxEf82b9wO5PVh1Jt+vyPSuVChXi7SRMA0nQ6xqzN3sQCgOKNoMqz4jj1Huz5wkYWSnKDjh1tG2pQztkNF8PfQlmeK38hxWy+QEG0vD2AKNkFkAq8BvQDou1kl8QhKOxvKWjvxkhB+xgoikKPX3pQqomo5Rt/LZ6IvhFkpllWEalfoj4/PfOTcfzqylfZf3O/+YVg9mwobwj/2LtXCFwb4uas8EJ7T+NHYfm+FK7eccxqKB+1akVRTxEaseT0aTZcfECSUMsvwXATwaGZEGubuqWSp8e8ta0txKxWUahsCDW4mZlOvM4xP/uSx0eK2XxFFWA38IbZ3BJEctg2exgkcRQK+UGNSmD44uBeLJy4IAXtI+Lk5sTAxQPxLukNwLWd11j56spsVQGG1xnOaw1eAyBNl0bf8L5EJUWZFvj7w8KForECwP/+B+HhNnkNWVQq7kyXOiKrW6eH39YnkZHpeDs4Pq6ufNWhg3H89po1ZOb0efUpC/UNdbh16bBtrI0slDwt5q1tT5y4w40b8VZ/TvN6s2dlqEG+QYrZfIcbouXtcqCQYe4a0Ab4BHDMpA+JDQjwhRqVwRCLSHQcHD8vFI3kP/Eu7k3o0lCc3EQVkcOzDrNnxp5s66Z3mU6z0s0AuBZ/jZCFIWTqzTxA9erBzJmm8ciRcOaMVW2/n56N3ClVSCSk3YrRsWSPY36pD61dm0YlRbvm41FR/LR/f84LG40Fj0BxfHYB3NhpIwslT4t5VYP1663vVQ92kZ3A8iNSzOZbeiBq0rYxjPXARKAdQtxKCiT+PlDTTNDGxMPxczavfZpXKdGgBL1m9zKO145ey/k15y3WuGhdWDBgAcW8igGw+fJm3l/3vuWFXnwRhgwRx4mJ0K8fJCVZ1XZznLQKIzt44mT4GKw/ksqZG45X2kqjKMzs0sU4/njTJu4l5yBAXH2g2SemsWykkGewLNFlAzFrngSW5pg3cZLHR4rZfE1JYD3wGWAoC8RWRNjBMjvZJLE7ft5QqzJoDb/+sQlw7BxkSkH7KNQIqUHLD1sCoOpVFoYs5O6ZuxZrSniXYOGAhThphBd32u5phB0PMy1QFPjxR6heXYxPnIBXX7WpACtZyIk+TYSXSkVUN0hOczwvfeNSpRhaW+QCxKSmMn7TA9p41xwJhaqJ41u74UyEjSyUPA2NG5fE29t2rW1LObniroi/fdIzm3+QYjbfowU+ArYAWa1Oo4HewOuAvDMtkPh6Q60gU+3TuEQ4dlYK2kek7adtCe4VDEBaXBphPcNIjbWsDNC8THNmdJlhHI9YPoKjkUdNCzw9RfysIcmJOXPgt9+sbrs5HWq7EVRCCO7oRD1h2x3zy31S+/Z4OosuZj8fOMCR2zm0P9U4QesppvG29yHTMas1SEw4O2tp29Z2rW21imKsNxulyyBaNtvIF0gxW2BojqhJ289s7nugMaKUl6TA4eMFtYPAySBo45Pg6FnIlBm+/4WiUegzpw+BNUSc5r2z91gYuhB9pqVn89UGrzK8znAAkjOS6RPeh5gUs5qpVapYCtg33oCDB61tvhGNIqobuAmdyK4z6Ry8aNtyYY9CCW9vPmrVCgC9qvLW6tU5t+Qt1wXKGuoCx1+BgzOzr5E4HOatbW1R1UCGGuQ/pJgtUPgDC4CfEIliIJorNAB+RdakLYB4e0LtYHAytEZOSIIjZyFDCtr/wtXbldDloXgUFl+MF9ZcYN176yzWKIrCj91/pH7x+gBcjLnIc4ufQ2feFz40FF5/XRynpYn6s7GxtngJABTy1hLa0tQdbM7mJOKSHS/c4J0mTajo7w/AlitXWHgyh5vwrEYKhm1k9nwByXdsaKXkSbB53KxZEthZGWqQL5BitsChIFre7gdqGOZSgJcQncRi7WOWxH54eUCdYHA2CNrEZDhyBtLl9tt/4V/enwELB6AxZFLtnr6bQ38csljj5uTG4pDFFPYoDMCq86uYuHmi5YWmTIFGjcTxxYswfLhN42ebBbtQp7xwzyamqvy1KSlnz6cdcXVyYlrnzsbxmHXrSM7I4TNapCbUeEEcp8eLzmASh8a8te327dZvbWtenkt2AssfSDFbYKkO7AVeNZtbgEgO22UPgyT2xNNdeGhdDPvNSSki5EAK2v+kXOtydPu+m3G84pUVXN1h2aq2jG8ZwvuHozF4DD/f9jlLTy81LXB1hYgIUYcWYNkymDoVW6EoCkPbeOLtLuoQH72SwfZTaTZ7/kelR1AQnSoKL97VuDi+2bEj54XNPwNng7f56M9w75SNLJQ8CbZubVvCyQUvjQivOp2W7HA3bpLHR4rZAo078AOwCPAzzF0BWgJfImvSFjByErRHzkCa48VQOhr1X6pPw/9rCIA+Q09E3wjirsZZrGlXvh2TO0w2jocuGcqZu2b1ZcuWhb//No3HjoVttmt24u2uYVhbU7hB+PZkouIc62+Aoih827kzTobScpN37OBqXFz2hZ7FoKGhHJqqg63v2dBKyZNgGWpg3bhZRVGMoQYx+kzuyiSwPI8UsxKgL6ImbQvDWAd8CHQEbtrLKIk98HATIQeuolQOyalS0D4inad3pnw7kZWdFJVEWK8w0pMs37fRTUcTUj0EgIT0BPqE9yEhLcG0oFs3+PBDcazTQUgIREbaxH6A2uVcaFlVdCdLy4RZG5KsXirpcalapAivNxQ3DimZmby3bl3OCxuMBi/RcIGLK+DKBhtZKHkSbN3aVoYa5C+kmJUYKANsAj7G9LHYBNQCVtjLKIk9cDcIWjeDoE1Jg8NnINXxtp0dCa2zlv4R/fGvKEIFbh++zbLhy1DNxKCiKPze83dqBIp49VN3TzF82XDLbc5PPoF27cTxrVvw7LM2bWoxsLkHhX3E34DztzNZc9jxyltNaNOGIh5CjISfOMHWKzlsSzt7QIsvTeMto0HvWJ5miQl/f9u2tg12NSWBnU6TSWB5HSlmJWY4IVrebkQ0XAC4h+gm9jYgxUyBwc0ValcR/4MQsofPCGEreSAehTwYtHwQLoYi8CcXnmTr51st1ni6eLIkZAl+bn4ALD61mK+2f2VaoNXCvHlQvLgYb9wIEyfawHqBm4so16UYxsv2pnD1rmNVt/Bzc+OLLMEPvLlqFTp9DhUYqg2GwHri+M4ROPmXjSyUPAnmoQbr1lm3qoGlZ1aK2byOFLOSHGiNCDvoZTY3A2gKnLWLRRI74OYiPLTuhjJuaelw5LQIPZA8kCLVitBvfj+y1ODmCZs5uciyjFSlgErM7TsXxbDow40fsub8GtOCokUhPNzU1OLzz2HVKluYD0Dl4s50rit+7jo9/LE+iYxMxwo3eKFuXeoWEy2Dj0RG8ltO9XkVDbQxS6Tb/iGkJ9rIQsnjYsu42UCtM/6GDn1n01NkElgeR4pZyQMoBCwBvgMM3jkOAfWA2ciatAUEV4Og9cgStBkihjZZxpg9jKDuQXT4qoNxvHToUm4ftuxs1K1yNya2mQiAisqgRYO4GGPmjWrZEiZNMo0HD4acttOtRM9G7pQqJMT0jWgdS/c61s9cq9Ewo0sX4/jDjRuJScnBxtJtoKLhxjzpFuyfkn2NxCEwb227fv1Fq8ZrK4pCkCHUIF6v43amzAvIy0gxK3kICvB/wB6gimEuCXgeeA6wbkyTxEFwcRZVDjwNMWbpGSLkIMmxxI2j0ezdZtQaXAuAjOQMwnqFkRSVZLHmo1Yf0TO4JwAxqTH0De9LcobZlueYMdDLIMSio2HgQEi3zZeus1ZhRAdPDCV0WXc4lTM3HCvru2XZsoTWEPHH91JSmLh5c84LW30t2t0C7PsGEm7YxkDJY+HsrKVdO9u1tjUPNTgtk8DyNFLMSh6B2ogmCyPN5uYDdRG1aiX5nixB62X445+RKTy0iTLW7EEoikKPX3tQspGIP4+7GkdEvwh06aYkJI2i4a/efxFUKAiAI5FHeOmfl0xbnooCs2dDefEFz969QuDaiFKFnOjdWNzEqMCsjUmkpDvWrszXHTrgbuhg9/2+fZyIisq+KCAIar8mjjOTYcdHNrRQ8jjYMtSgioybzTdIMSt5RDwRLW/DAV/D3EWgOfA14HjtLyW5jLMT1AoC7/sEbULSw88rwDi5ORGyNATvEt4AXN1+lZWvrbSIz/N182VJyBK8XLwAmHtsLjP3zDRdxM8PFi4UjRUA/vc/EU9rIzrWdqNycSEW7yXoCd/uWD/v0r6+jGshygrqVJW316zJOf6x6cfg6ieOT/wJUYdtZqPk0enYsYLx2NqtbYPM29qmSc9sXkaKWcljMhA4DDQxjDOB94GugHW3hCQOQJag9TEU18/UiU5h8TKp5kF4F/cmdFkoTm5CEB76/RB7Zu6xWFOtSDVm95ptHI9eO5otl7eYFtSrBzPNBO7IkXD6tDXNNqLRiOoGboZeGjtOp3PoomPFF45p1oxyfn4ArL94kWVnzmRf5F4ImmR5ZFVRqksm/Tgc97e2TUqy3metkJMzhbXig302PRm9/DzkWaSYlTwB5YCtwAcYU7ZZiwhHWPOAcyT5BicnqBkEPsKTaBS0cVLQPogSDUrQ84+exvHaUWu5cN8War9q/RjbfCwAOlXHwIUDuR5/3bTgxRdhyBBxnJgI/ftDkm28pIV9tIS2MHUH+2tzEvHJjrMb4+7szJSOHY3jUWvWkJqZQzmxOq+Dr8Hzd3UjXFxpIwslj4qtW9tWMXhnk1Q91zNl6cG8ihSzkifEGfgCWAcY6mESBXQB3gUcy3MjyWWctFCrMviJ7XN0ejh2FmITHn5eAabmoJq0GCe2w1W9ysKQhdw7e89izeftPqdjBSHKopKi6BfRj7SsL1hFgR9/hOrVxfjECXj1VZt5F5tVcaFOeeHFSkxV+WtzkkOVM+pbtSpty5UD4FJsLNN27cq+yMkVWplaCrNlDMhWpg6HTevNuprFzcpQgzyLFLOSp6Q9oiZtN7O5KYhY2vN2sUhiI7RaqFEJ/H3EWKeHY+cgRla5eBDtPm9HcM9gAFJjU5nfcz6psaa6vVqNlvn95lPOrxwAe2/s5Y1Vb5gu4OkJixaBl8ErPmcO/PabTWxXFIUhrT3xdhe7MUcuZ7D9lOPctCqKwowuXdAowr4vt23jRnwOn8XK/aBEc3EccwaO/mJDKyWPgi1b25rHzcoksLyLFLOSXKAIouXtdITHFkT1g7rAXHsZJbEFWYI2wJAUqNfD8XMQHWdfuxwURaPQ5+8+BNYIBODemXssGrQIvc60ZV/IoxCLBy7GzUnU9v314K/8euBX00WCgy0F7BtvQE4NA6yAj4eGoW1M4QbhO5K4E+c4LWJrFi3Kqw0aAJCUkcHYDRuyL1IUy0YKuyZCaqxN7JM8Gv7+7jQyVAGxdmtb2QksfyDFrCSXUBAtb3cDlQ1zicBgYJjhWJIv0WigekUo5CfGehWOn4d7sfa0ymFx9XYldHko7oWER+j86vOsf3+9xZq6xevyaw+TgH191evsuW6WNBYSAq+/Lo7T0kT8bEyM1W0HqFPeheZVRGH7tAz4Y2OSVYvbPy6ftm1LgLt4b/8+epRd165lX1S8MVQZJI5T7sKeL21ooeRRyIqbBeuGGvhqnSjuJD7P59NT0TlQ6Izk0ZFiVpLL1AMOIgRsFn+ZzUvyJRoNVKsAhf3FWFXhxAW4axuBldfwL+/PwIUD0Rg6EuyauovDfx62WDO41mDebPQmAOm6dPpF9CMyMdK0YMoUaNRIHF+6BMOH2yx+NqSFJ4W8he3nb2Wy9ojjtDgOcHfns7ZtjeM3V6/OOUu95STQGsqdHZoBcZdsZKHkUejY0Xb1ZrNCDVJVPVcyHOezLHl0pJiVWAEvRMvbvwFDghDnEOW8piNb4eZTsgRtkQAxVlU4eRHuSEGbE+XalKPr/7oaxyteWsG1nZZexCmdptCyTEsAbiTcYMCCAWRkJSy5ukJEBAQY3u/ly4XAtQHuLqJcV1Ytk6V7Urh2N4fqAXbipfr1qRkoQjn237zJ7MOHsy/yKQv13hbHunTYNs5m9kn+G/PWtuvWWbe1rWWogUwCy4tIMSuxIs8Bh4AGhnEGMAp4BlH5QJLvUBSoWh4CzQXtBYiKtq9dDkqDVxrQ4DXx+6FL1xHeN5y4a6Z4Y2etMxEDIijhXQKAbVe38e66d00XKFsW/v7bNB43DrZts4ntQSWc6VRHxPXq9PD7+iQydI5xo+qk0TCjSxfjeNyGDcSl5uBxazwO3IuI4zPhcDOHCggSu2De2vbuXeu2tq1iUdFAxs3mRaSYlViZisAORLmuLP5F1KTNITlDkvdRFKhSHooVMs2dugiR9x58TgGmy7ddKNe2HABJkUmE9QojI9lULqqYVzEWDVyEs0YkV87YM4O/j5oJ2K5d4SNDMwCdTsTTRpqFI1iRXo3dKRmgBeBGtI5lexzHq9W2fHn6Va0KQFRSEp9t3Zp9kasvNPvENN48SjZScCBs1dq2sqxokOeRYlZiA1wQLW/XAIGGudtAR0TjBVnnMd+hKBBUDooXNs2dvgS37trNJEdF66xlwIIB+FcQ8ca3D91m2fPLLGq4NinVhO+6fWccv/TPSxy+fdh0kYkToV07cXzrFgwaJIStlXHWKozs4Ikh9Je1h1M5e9Nxfp+ndOqEm5PovDZjzx7O3M3h81frRQgQopdbu+HsAhtaKHkYlmLWeklgXhotpZ1E/PSF9FQyVMdpCCJ5NKSYldiQTsBRw/8gYmcnAS0BmXyR71AUqFwWSgSa5s5ehpt37GaSo+JRyIPQ5aG4GGIET0ScYOvnlp7El+q/xMi6IwFIyUyhT3gf7iUbvN1aLcybB8UNDUw2bYIJE2xie6nCTvRqLDxbKvDHhiRS0h3Du1nOz493mzUDIFOv5501OXQo1DhBa7NY463vQ6ZMAnIEKlb0p3x5P8D6rW2DXcVnOAOVS+ny55/XkGJWYmOKAqsQnlonw9weoA4QbiebJFZDUaBSaShZ1DR37grcsM02eF4isHogfef2NXaI3vzxZk4tOWWx5rtu39GopKhgcDn2Ms8ufhad3uCBLVoUwsOFsAX44gtYtcomtneq7Ubl4uL3+V6CnvDttmmz+yi837w5pXxEY49V58+z8uzZ7IvKd4UyHcRx/GU49D/bGSh5IIqi0LGjbVrbmieBnZZJYHkOKWYldkCDiKHdCWTVEowHQoGRgON8EUpyAUWBiqWgdDHT3PlrcM16CR15leAewbT/sr1xvGTIEiKPmoS/q5MriwYuooiHSFpae2EtH238yHSBli3hq69M48GD4Yp1e9sDaDQKz7f3xNXQM2XH6XQOX3KM7mCeLi5807GjcfzOmjWk3x+CoSgG76zhTmLPF5AsQ2IcAVvFzQabxc2elXGzeQ4pZiV2pCGi2sGzZnO/I6ofHLGLRRIroShQviSUKW6au3gdrt6yn00OSvP3m1PzuZoAZCRlML/nfJKiTDd4pXxKsWDAArSK8MB+teMrFp1cZLrA6NHQq5c4jo6GgQNFYwUrU8RHS0hzU3ewvzYnEZ/sGLGHIdWr07JMGQDORUczc8+e7IsCa0ONF8RxWhzs+iT7GonNsWxta7242Uou7kZBJCsa5D2kmJXYGR9EPdrZQNYX4WmgMfAdsiZtPiJL0JYrYZq7dAOu3LSfTQ6Ioij0+LUHJRqK9ynuShwR/SPQpZu8ia3LtWZKJ1Oc5/Blwzl552TWBWD2bCgvyhqxdy+MGWMT21tUdaF2OeGeTUhRmbMlySKRzV4oisKMLl2MdXE/3bKF24k5dCVs/hk4G/4OHfkR7p22mY2SnDFvbXvypPVa27prtJR1FqXmLmakkqZ3jBsxyaMhxazEAVAQHcMOAnUNc2nAG0BvQJZ0yleULSFEbRaXbwpR6wCix1FwdncmdGkoXsW9ALi67Sor/2+lhTB8q/FbPFtT7GokpifSJ7wPcamGGrV+frBwoWisAPDddyKe1sooisLQNp54uwvZePhSBjtPO0a4Qd3ixXmxXj0AEtLT+WBDDqUBvYpDw/fEsaqDre/Z0ELJg7BVa9usUAM9cCFDxs3mJaSYlTgQQcAu4G2zueWImrSb7WCPxGqUKS7iaLO4eksK2vvwLuFN6NJQtK4inODQb4fY+91e4+OKovBrj1+pXbQ2AGfvnWXo0qHos8oK1asH/zNLZBo5Ek5b39Po46FhSGtTuMH87Uncibd+mbBH4fN27fA1CPxZhw+z78aN7IsajAYvw83WxX/g6kYbWijJCZvFzVo0T5BiNi8hxazEwXBFtLxdAWTVKL0BtAM+BhynZabkKSlVDCqVMY2v3YYL16WgNaNko5L0+qOXcbzmnTVcXG/yTHk4e7A4ZDH+bqJG7fIzy/li6xemC4wcCUOHiuPEROjfH5Ksn2BZt4ILzauIMmNpGTBrQ5JV25E+KkU8PZnYpo1x/Obq1ejv/7w5e0ILs/dw82jQO4YYL6g0alQSHx9xE2LN1raWbW1l3GxeQopZiYPSHZEEZigEjwp8BrQBrtrJJkmuUzJQ1KLN4kYknL8qBa0ZNZ+tSfOxzQFQdSoLBizg3jlT6E0F/wrM7zcfxRAROmHzBP499694UFHghx+genUxPnECXnnFJu9vSAtPCnmLr5hztzJZd8Qxanf+X8OGVC0sbpR3X7/O3KNHsy+qNgQCDSFPdw7DyTm2M1CSDWdnLW0NXfLu3k3m8GHrVEKp6OKGobAdp6WYzVNIMStxYEoAa4EvwfgnZgci7GDRg06S5DVKFBHdwrK4eUfUopWC1kj7L9oT1CMIgNTYVMJ6hpEaZxKHnSt15vN2nwOgovLc4uc4H31ePOjpCYsWgZeIv+Xvv+HXX61us7uLwgvtPY1JV0v3pHD9rv13Vpy1Wr7t0sU4fn/9ehLur/agaKD1VNN4x4eQIUsG2hNbhBq4KBoqGOJmr2akkSI98nkGKWYlDo4WGAdsA7I8eLFAf+AVQMY15QuKF4Yq5U3jW3fhzGUpaA0oGoW+f/elSHVRX/bu6bssGrQIvc6UcT2uxTj6VOkDQGxqLH3D+5KUbhBgwcHw22+mC77xBhw8aHW7g0o407GOyBDP1MPvG5LI0Nn/Z9qpYkV6BgcDcCsxkS+3bcu+qExbqNhTHCfehH1Tsq+R2AxzMWuLJDAVOCebJ+QZpJiV5BGaAoeBgWZzPyNq1R63h0GS3KZoIahqylom8h6cviQFrQFXH1cGLR+Ee4D4sj2/6jzrx643Pq4oCrN7z6ZK4SoAHIs6xojlI0wVEEJChIgFSE8X8bMxMVa3u3cjd0oGiJ2V6/d0LN/rGAJhWqdOuBi6pU3bvZvz0dHZF7X6WrS7Bdj3tRC1Ertgq9a2shNY3kSKWUkewg8IA34Dsrq1nEAI2p+QNWnzAYEBUK2iiPUEiIqGU5dA1nwEwL+CPwMWDkDRivdn15RdHP7zsPFxH1cfloYsxdvFG4DwE+FM2zXNdIEpU6BxY3F86RIMH271mwVnJ4URHTzRGr5t1hxK5dytDKs+56NQMSCAUU2aAJCu0zF67drsiwKCodYr4jgzGXaMt6GFEnMURTF6Z63Z2jbY1dQJTDZPyDtIMSvJYyjACOAAUMswlwq8CgwArO9pkliZIv6WgvaOFLTmlG9bnq4zuxrHK15awfXd143j4MLBzOljSlh6b/17bLxkKC/l4gIRERAQIMbLlwuBa2VKF3aiVyPT9u0fG5JITbf/zecHLVtS3BBLvPzMGdZeyCEWs+kEcPUVx8dnQdRh2xkoscAWcbPlnd1xNkR6y7a2eQcpZiV5lKrAHuB1s7lFiOSw7XaxSJKLFPaD6maC9m4MnLwoBa2Bhq81pP4r9QHQpesI6x1G/HVTZ6ReVXrxUcuPANCrekIWhnA1zlAFpEwZkQSWxbhxsHWr1W3uXMeNSsXElv3deD0RO+wvFLxdXZncoYNx/Pbq1WTo7kv68SgMjT8yDFTYMkaGvtgJW7S2dVIUKhniZq9nppMok8DyBFLMSvIwbsD/gKWAwdPENaA18Ckg/wjlaQr5QY1KYPjy4l4snDgvBa2BrjO7Uq5NOQCSIpMI6xVGRrJp+35im4l0qSSy9u8m36VveF9SMw0VELp2hY8MAk2ng9BQiIy0qr0ajcLz7T1xNYSgbjuVxuFL9u8O9lytWjQpJRp4nLp7lx/27cu+qO4b4GtIULy6AS79a0MLJVn4+blZtLa9bnYDl5vIUIO8hxSzknxAL0RN2laGsR6YALQHrj/oJEleIMAXalQGjeFPVXQ8HD8vBFgBR+usZcCCAfgZkmJuHbzFsheWGRO+tBot8/rOo4K/SKo7cOsAr618zZQQNnEitDPUcb51CwYNsvr7GuirJaSFKcHmr81JJKTY9+ZEoyjMNCvVNWHzZu7c31jCyRVaTjaNt4wBnf3jfgsilq1trRNqYJ4EdlYmgeUJpJiV5BNKARsRHtmsj/UWRNjBcnsZJckN/H2gZmWMGUQx8XBMCloAj8IeDFo+CBcv0W3rRPgJtn1pKjPl7+7PkpAleDiLL+dZh2fx0/6fxINaLcyfDyVKiPGmTTBhgtVtblHVldrlnAFISFH5a3OSSWDbiYYlS/J8nToAxKWl8dHGHFrYBvWHEs3EcfRpOGb9Wr2S7NiiRJdlRQPpmc0LSDEryUdogfEIEVvaMBeN8Ny+gUgUk+RJ/LyhZpAQYABxCXD0HGRKQRtYI5C+c/uS1Z1g00ebOL30tPHxWkVr8XvP343jt1a/xc5rOw0nB0J4uOl9/eILWLnSqvYqisLQNp54uQmDD1/KYOcZ+4cbfNm+Pd4u4qbg14MHOXTrluUCRbFspLBzAqTF2dBCCdimtW0ZZ1fcFCGPZJhB3kCKWUk+pAWiJm0fs7nvgMbAKXsYJMkNfL2gVmVwMgiv+EQ4ehYy7d9Vyt4E9wym3RftjOPFgxcTedQUAxtaI5RRTUYBkKHPoF9EP24lGMRaixbw1Vemiw0ZAlesU/YoCx8PDUPaeBrHYduSuBtv3xuTYl5ejG8lQpVU4M3Vq7N7jEs0geBQcZxyF/ZMsq2REpydtbRrJ+KXrdXaVqsoBBmSwCJ1GcTq5N8YR0eKWUk+JQBR3eBHRKIYwFGgAfA7siZtHsXHC2oFmQRtQpIQtBnyy6bF2BbUGFQDgIykDOb3nE/SHVPs5+SOk2lTrg0AtxNv039Bf9J1Bo/o6NHQu7c4jomBAQPg/havuUy9Ci40DRae0NQMmLUxCb2dww3eatKEyoayZduvXiX8xInsi1pOAq3wDHJwOsRdtp2BEsAybtZaJbqyxCzAGRlq4PBIMSvJxyiIlrf7gGqGuWRgJDAIkFuEeRJvT6gdDM6GtPiEZCloEdv3PX/vSYkGIgY27kocC/ovQJcuPJ5OGifC+4dTykdk7u+8tpNRa0ZlnQyzZkEFg0jYtw/GjLG6zaEtPAjwEl9DZ29msv6IfUOBXLRapnfubBy/u24dSen3hUD4loN6b4ljXTpsG2c7AyUAdOxo/Xqzwa6muNkzaTIJzNGRYlZSAKiBELQvm82FA3WA3fYwSPK0eHlYCtrEZDhyBtILdoa5s7szIUtD8CouGgFc2XqFf9/417hdHugZyOKBi3E1eBa/3/c9fx7+U5zs5wcLF4Krwev43XcQFmZVez1cNbzQ3jMr3Jclu1O4cc++NyXdg4LoWqkSANfj45m8Y0f2RY0/APfC4vhMGNyUf0dsiS1a21YxSwKTnlnHR4pZSQHBA9HydiGiLS7AZUR87SREOS9JnsLTHeoEg4vIjCcpRQpawKekDyFLQtC6ilCMg78cZN/3ptqpDUs25IfuPxjHL694mQM3D4hB3brwv/+ZLjZyJJyybpx5cElnOtQWoUCZevhtfRIZOvuGG0zv3BknQzm4b3bu5HJsrOUCV19o9olpvHmUbKRgQ8xb22Zk6K3S2raEkwueWUlgUsw6PFLMSgoY/RDJYc0NYx3wAdAJuGknmyRPjIe78NC6GgRtciocPg1p9s+OtyelGpei5289jePVb6/m4gZTGaMX6r7AK/VfASBNl0bfiL7cSbojHhw5EoYOFcdJSdC/v/jfivRp7E6JACG+r9/T8c9e+27rBhcuzFuNGwOQmpnJu+vWZV9U6yUIqCKOb+2CswttaKHE2q1tNYpCkCHU4J4uk7uZBfsm2dGRYlZSACkLbEaU8cra4NyAqEkrO/vkOTzcoHYVcBXJRKSkweEzkGrdBCZHp9bgWjR7T9RFVXUqCwYsIPp8tPHxGV1n0LRUUwCuxl0ldFEomfpMET/7ww9QQySTcfIkvPKKVT2Pzk4KI9p7GksJrz6cyvlb9hUP41u1ItBTVFxYePIkmy5dslygcYJW35jG296HzIL9mbMltmhtW0UmgeUZpJiVFFCcEA0WNgKGovHcBboDowD5pZSncHcVIQduhnjP1DQRclDABW37L9tTuXtlAFJjUpnfcz6pcSLJykXrwsKBCynqWRSAjZc2Mm69IZnJ01PEz3qJ2Fv+/ht+tW6TgDJFnOjZUIgHVYU/NiSRmm6/rXtfNzcmtW9vHL+1ejWZ97dSrtAdyhjWxF2CQ/9DYhv8/Nxo3Ni6rW2DLeJmZRKYIyPFrKSA0wbRCreH2dx0oBlw1h4GSZ4UN4Ogdc8StOnCQ5tScJtlaLQa+s3rR+GqIlnp7qm7LH5uMXqdEGUlvEuwcOBCnDQikW7KrilEnIgQJwcHw++mZgu88QYcOGBVe7vUdaNiMWHLnXg9ETvt6w0bXqcODQwd0o5FRfHL/a/f2EjBsMOz53NIvmtbIwswHTtat7WtZUUD6Zl1ZKSYlUgoDCwDZgKGrWoOAvWAv5A1afMQri4ihtbDUFs4zSBokwuuoHX1cWXQ8kG4+Yv35NzKc2z4YIPx8RZlWjC983Tj+IVlL3A86rgYDBwoRCxAerqoPxsTYzVbNRqFF9p74mooUrHtZBpHLtsv/lmjKMzs0sU4Hr9pE9Ep93noAmtD9eHiOC0Odn9qOwMLOJZxs7kfalBU64yvRsRyn0lPtnvbZcmDkWJWIgGEZ+UNYC8QbJhLAoYBQ4Dc38KSWIksQetpiHdLzxAhB0kFd5swoFIAAxcORNEKD+LOr3dyZM4R4+P/1/D/GFpbJH0lZSTRJ7wPsamx4sEpU8CQDMWlSzBsGNy/3Z6LBPpqGdjc5BH7a1MSCSn2qzbStHRpnqtZE4DolBQ+3rQp+6IWn4OTweYjP0L0GRtaWHAxb227fn3ut7ZVFMUYahCn1xGpk0lgjordxez3339PuXLlcHNzo3Hjxuzdu/eh67/99luCg4Nxd3endOnSvPPOO6SmFlyviyS3qQ0cAF4wm5uL8NLuy/EMiQPi4gy1g7IL2sSCu1VYvl15uswweRn/efEfru+5Dogv7Z+6/0S94vUAOB99nucWP4de1YOLC0REgKEzFv/8IwSuFWlZzZWaZUWFivgUlb+3JNnVKza5Qwc8nYU9P+7fz7HISMsFXiWg4XviWJ8JW9+zsYUFE1u0tg12NUsCk6EGDotdxWx4eDijRo1iwoQJHDx4kNq1a9O5c2eioqJyXD9v3jzGjh3LhAkTOHXqFL///jvh4eF88MEHNrZckr/xRLS8nQ/4GOYuIOJopyBr0uYRnJ2Fh9bL4DHLyIQjZwu0oG34WkPqv1wfAF2ajvDe4cTfELsO7s7uLB64mELuhQD499y/fLLZUEu1TBmYO1fEiAJ88AFs3Wo1OxVFYVhbT7zcxPMdvJjBrjP2Czco6ePDBy1bAqBXVd5avTq7uG44RohagAvL4dpmm9pYULF2a9tg2TwhT2BXMTtt2jRefPFFnn/+eapVq8ZPP/2Eh4cHf/zxR47rd+7cSfPmzXn22WcpV64cnTp1YtCgQQ/15qalpREfH2/xTyJ5NEKBQ4Bhi5VM4F2gGxD5oJMkjoSzk/DQeosSS2RmCg9tgnXrpjoqiqLQdWZXyrYqC0Di7UTCe4eTkSK2T8v6lSWsfxgaQ7H4T7d+yvIzy8XJXbrARx+JY50OQkLgdu57wrLw9dAwuLWncRy2PZl7CTqrPd9/MappUyr4+wOw6fJlFt/fTMLZE5p/YRpvHgWqvPG1NtauNysrGuQN7CZm09PTOXDgAB06dDAZo9HQoUMHdu3aleM5zZo148CBA0bxevHiRf7991+6dev2wOeZNGkSvr6+xn+lS5fO3RciyedUALYBYzHVpF2DCEdYay+jJI+DkxPUCgKfLEGrEx7a+ET72mUntC5aBi4aiF85PwBu7r/J8heWGz2NHSp0YFL7Scb1Q5YM4ew9Q2WPCRMgq1zV7dvw7LPiBsFK1K/oQpMgkZSZkq4ya0MSejuFG7g5OTG1UyfjePTataRk3BdDWX0oFKkjjqMOwck5tjOwgFKxYgAVKoibDGu0ti3s5EwhrchIPJOWbLfPn+Th2E3M3r17F51OR9GiRS3mixYtyu0H3O0/++yzfPrpp7Ro0QJnZ2cqVqxImzZtHhpmMG7cOOLi4oz/rl27lquvQ1IQcEa0vF0LFDPMRQKdgfeAgt1tKk/gpBWC1tdQN1Wng6NnIS7BvnbZCY/CHoQuD8XFSwjF42HH2T5pu/Hxd5u9y4BqAwCIT4unT3gfEtISQKuFefPAUK6KTZuEwLUig1p6EOBlaCt6M5P1R+yXI9ErOJgOFcS29pW4OKbs3Gm5QNFAm6mm8fYPIUNuTVubrBJdGRl6tmzJ/da2Wd7ZJFXPzUz5994RsXsC2OOwefNmvvzyS3744QcOHjzI4sWLWblyJZ999tkDz3F1dcXHx8fin0TyZHRA1KTtajb3DdACEVMrcWi0WqhZGfy8xVinh6PnILZgCtqiNYvS5+8+xvHGDzdyetlpQIQj/NHrD6oXqQ7AyTsneWH5C8J7GxgI4eHi/QT48ktYudJqdnq4ani+vSncYMmeFG5EW88b/DAURWFGly5oDbHDk7Zv51pcnOWiMu2ggqFudeIN2D8ViXWxbaiBvDlxROwmZgsXLoxWqyXyvqzQyMhIihUrluM548ePZ8iQIYwcOZKaNWvSp08fvvzySyZNmoTeiqViJBITgcAKYCrCYwuiykFdYJ69jJI8Klot1KgM/oabWr0ejp2DmIIZS1+lVxXaft7WOF4yeAmRx8TfZC8XL5aELMHX1ReAhScX8vWOr8XCFi1g8mTThYYMgSu57xEz2lnSmQ61RQmmTB38vj6JTJ19tnurFSnC/zVsCEBKZibvr1+ffVGrr0ExiP19kyHxlg0tLHiYt7Zdty73682aVzQ4LSsaOCR2E7MuLi7Ur1+fDRtMxbv1ej0bNmygadOmOZ6TnJyMRmNpstbgHZDFjCW2Q4NoebsLqGSYSwCeA54HCmYsZp5Bq4EalSBAiDT0ejh+DqLjHn5ePqXlBy2pEVoDgPTEdMJ6hpF8V3xhVy5Umb/7/m1c+8HGD1h3YZ0YjBoFvXuL45gY0VAhzXrtg/s29qC4v/h7f+2ujn/22S8ZZ2KbNhRyFwJn/vHjbL961XJBoSpQ+xVxnJEEO8bb2MKChbVb25p7Zs/KJDCHxK5hBqNGjeLXX3/lzz//5NSpU7z66qskJSXx/PPPAzB06FDGjRtnXN+jRw9+/PFHwsLCuHTpEuvWrWP8+PH06NHDKGolEttRH9EpbKjZ3GzD/CF7GCR5VDQaqF4RCvmJsV6F4+fhXqw9rbILiqLQ8/eeFK9fHIDYy7FE9I9Aly4qBzwT9AwTW08EQK/qCV0UyqWYS6JM16xZYIghZd8+GD3aanY6OymM7OCJ1vCttepQKudv2aeIvb+7O1+0a2ccv7lqFbr7dwebTgAXww7A8T8g6ggS62EeapDbrW39tE4U1YqduLPpKeik88zhsKuYDQkJYcqUKXz88cfUqVOHw4cPs3r1amNS2NWrV7l1y7Q989FHHzF69Gg++ugjqlWrxogRI+jcuTM///yzvV6CpMDjDfwJzAEMyUWcBZoA3yJb4TowGg1UqwBFRCY0qgonLsBd67VrdVScPZwJXRqKVzHxGb6y5Qqr3lplfHx86/E8E/QMANEp0fSN6EtyRjL4+cHCheAqQgD4/nsIC7OanWWKONGjgfCIqir8sSGJ1Az7/I6NrFeP2obvqkO3b/PHoftuYD2KQBNDKTNU2DJGGC2xCtZubRvsKryzqaqeqxnW24GQPBmKWsD25+Pj4/H19SUuLk4mg0lymfOI2rQHzOa6A7OAInaxSPIIqCqcvgRR0aa5qhUgMMB+NtmJ67uvM7vNbHRpwivb7ftuNHxNxIfGpsbS6NdGnIs+B8CQWkP4s/efKIoCv/0GL74oLuLpKby0VataxUadXuXrJfFcjBQ2tqrmypA2nv9xlnXYeuUKrWfPBqCwhwfn3ngDPzc304LMVJhVFeIvi3GflVDhwaUkJU9OZqaeQoW+Jj4+jUKF3ImKetcYR5sbzIuL5NdYUWnp/UKl6eJV8P4+2JrH0Wt5qpqBROLYVAJ2AuZbrSsRNWk32sUiySOgKFClPBQtZJo7dREi79nPJjtRqkkpevzawzhe9eYqLm28BICfmx9LQpbg6SyE45yjc/hu73di4YgRMGyYOE5Kgv79xf9WQKtRGNHBCxdR+pOtJ9M4dsU+5ZJalS3LwOqi4sPd5GQ+2bzZcoGTG7T8yjTeMka0u5XkOk5OGmNr23v3Ujh0KHeT7izjZmUSmKMhxaxEkqu4IFrerkJUPgC4hSjr9SFgnxg/yX+gKBBcDooVNs2dvgS379rNJHtRe0htmr3bDABVp7JgwAKiLwivdfXA6szqNcu4dtTaUWy7sk28fz/8ADVEIhknT8LLL1ttWz3QV8vA5iZxMXtjEgkp9qlo803Hjrg7CWX93b59nLpzx3JB8EAo3kQcR5+Co7/a2MKCgzVb2wa5mFc0kElgjoYUsxKJVeiCqEnb0TBWgS+B1sBlO9kkeSiKAkFloYRZSMiZy3DrzgNPya+0n9Seyt0qA5ASnUJYzzDS4kWc4IDqA3iv2XsAZOoz6b+gPzfib4CHh4if9TLEjs+dC7/8YjUbW1VzpWYZkZQTn6Ly95Yku1S1KePry/vNmwOQqdfz9po1lnYoCrSZZhrvnABpBbMUnLWxTALL3bhZb60TJZ1Ek5Hz6SlkFqwITYdHilmJxGoUA1YDkwHDnii7gDrAAjvZJHkoigKVykDJQNPc2StwM8p+NtkBjVZD33l9KVxVeKrvnLzD4ucWo9cJ7+cX7b+gQwXRijwqKYp+Ef1Iy0yD4GD4/XfThd58Ew4cyHb93EBRFIa29cTLTcRFHryYwe6z9gk3eLd5c8r4ilJvay9c4J+zZy0XlGgKQQPFccod2DsJSe5j7da2WaEGGahczrBfJzpJdqSYlUisigbR8nY7UN4wFwcMBF4EZOyVw6EoULE0lDJrtX3uKlyPfPA5+RA3XzcGLR+Em79IaDq74iwbPxSx304aJ+b3m09Z37IA7Lmxh7dWvyVOHDhQiFiA9HRRfzbGOhUi/Dw1DG5tSv6avy2Zewk6qzzXw/BwdmZKx47G8ag1a0jLvC82ttVXoBWePQ5Mh3jrNZkoyGSFGlijtW1WRQOAM7J5gkMhxaxEYhMaI2rPDjKb+w1oABy1i0WSh6AoUKEUlDHrRnjhGly7bT+b7EBApQAGLBiAohXezx2Td3B0rvi8FvYozOKQxbg5CbH784Gf+f2gwSv7zTfQuLE4vnRJJIdZqUtj/YouNAkSIjElXWXWxiT0dtgC7l+tGq3LCnF/ISaGb3fvtlzgWx7qGgS/Lg22jUOS+1iztW2wedysTAJzKKSYlUhshi8wF1GqK+sO/xTQCPgeWZPWwVAUKFcSyhY3zV28DlcKVmvSCu0r0Hl6Z+N4+Yjl3Nh7A4B6xevx8zOmOt+v/fsae2/sBRcXiIiAAEP5on/+gSlTrGbjoJYe+HuKr7MzNzLZeNT2dUAVRWFm165oFCH8P9+2jVsJCZaLGn8AboaqGafnw629NrYy/9O2ram1rTWSwLKKfZ2RncAcCilmJRKbogDDEZ3D6hjm0oDXgT5AwSsH5dBkCdpyJUxzl2+IfwUoAaTR642o92I9AHRpOsJ6hxF/QyQxDa09lNcbvg5Aui6dfhH9iEqKgjJlRBKYQdzxwQewZYtV7PNw1fB8e1O4waLdydyMtn24Qa2iRXm5fn0AEtPTGWvWrh0ANz9o9olpvHlUgfoc2QLz1ranTt3N1da27hotZZxFg5BL6amkq/apoCHJjhSzEoldCAZ2A2+ZzS1DCNyt9jBI8jDKlhBhB1lcuVWgBK2iKHT7rhtlW4lt9MRbiYT3DicjRZSam9Z5Gi3KtADgevx1Bi4YSIYuA7p0gY8MXbB0OggNhdvWCdWoWsqZ9rWE0MjUwe8bEsnU2f7n81nbtvgbGif8deQIe65ft1xQ6yXwDxbHN3fAuUU2tjD/Y83WtllJYJmoXEiXSWCOghSzEondcEW0vP0HyCrYfx1oC0wEZHF1h6J0MZEYlsXV2yLsoIAIWq2LlgELB+BbVmTt39x/k39G/oOqqjhrnVkwYAHFvURIxpYrW3hvnSjfxYQJ0L69OL59G559Fu5Pjsol+jbxoLi/+Fq7ekfHP/ttvxVcyMODT9u2NY7fWLXKMoZX6wytvzGNt74PmbI9am5izda2VcyaJ5yRcbMOgxSzEondeQZRkzbrC1APfAK0A67ZyyhJTpQqKkp3ZXE9UiSGFRBB61nEk0HLB+HsKeq7Hpt3jB2TdwBQzKsYiwYuwlkjHvt2z7fMOzYPtFqYNw9KGEI1Nm0SAtcKuDgpjGjvhdbwzbbqYCoXbtu+UckrDRpQvYioV7zv5k3+OnLEckGFZ6C04fc97iIc/t7GFuZvGjUqiY+P8NKvW3cBvT73fj+DXU1JYLKigeMgxaxE4hCUBNYBXwBaw9w2RCvcJfYySpITJQNFc4UsbkTB+asFRtAWrVWUPnP6GMcbPtjAmX/OANC0dFNmdp1pfGzk8pEcuX0EAgMhPFwIW4Avv4SVK61iX9lAJ55pIASHqsIfG5JIy7Dtz8ZJo2FGly7G8dj164lPM/O+Kgq0ngpZ6US7P4MUGS+fWzg5aWjf3jqtbSs6uxuFk0wCcxykmJVIHAYt8AEiZjZLLMUAfYHXAPmH02EoXkS0v83i5h3RXKGACNqqfarS9jODZ1GFxc8uJuq4aCzxcv2XeaHOCwCkZKbQJ7wP0SnR0KIFTJ5susiQIXD5slXs61rPjQpFhXCOitOzYKftPWjtK1SgT5UqAEQmJfH51vti4YvWherDxHFaLOz61LYG5nM6drROa1tXjYbyziIm+kpGKil62ycaSrIjxaxE4nA0Aw4D/c3mfkSU8DphD4MkOVGsMFQpbxrfviva3xYQQdvyw5ZUH1gdgPTEdOb3nE/yvWQUReH77t/TsERDAC7FXuLZRc+i0+tg1Cjo3VtcICZGNFRIy/14Ua1G4YX2XrgYGu9tOZHGsSu27w42tVMnXA3e6G937+bsvfu8r80/BydDDOaRHyD6vs5hkifGqnGzhuYJeuC8TAJzCKSYlUgcEj8gAvgFyIrROg40NMwVDMHk8BQtBFVNHiAi78HpSwVC0CqKQq9ZvSheTyR9xV6KZUH/BegydLg5ubFo4CKKeIi40TUX1vDxpo/F9vqsWVDRIDT274fRo61iX1E/LQOamZJ1/tyURGKqbUsplff3Z0yzZgBk6PWMWrPGcoF3SWj4rjjWZ8LW92xqX37GvLXtjh2529o2SCaBORxSzEokDouCaHm7H6hpmEsBXka0w7VOi1DJYxIYANUrmuqpRkXDqYtW63jlSDh7OBOyNATPoqLG6+XNl1n91moASvuWJrx/OFpFeCa/3P4lS04tAT8/WLgQXEWCDt9/D/PnW8W+1tVdqVFGJKTFJav8vSUZ1cY3GuNatKCktzcAK8+dY9W5c5YLGr4LnobGHBeWwTXr1OItiFirta15JzApZh0DKWYlEoenGrAHETebxUJETdqd9jBIcj+F/aGamaC9EwMnC4ag9S3tS8iSELQuQrTu/3E/+37cB0Db8m35uuPXxrVDlw7l9N3TUKcOfPed6SIvvginTuW6bYqiMKytJ56u4udy4EI6e87ZNtzA08WFrzt2NI7fWbOGdJ1ZnKWzpwg3yGLzKJDF+HMFa7W2reDihrMhee9MmsxlcASkmJVI8gTuiJa3SwB/w9xVoBXwOSCTEOxOYT+oUckkaO/FwokLBULQlm5ammd+ecY4Xv3mai5vvgzAO03eIbRGKACJ6Yn0DutNfFo8jBgBwwwJUElJ0K8fJCbmum1+nhqea23aFp63NZnoBNv+vgyqUYPmpUWN4jP37vHd3vva2FYfBkVqi+Oog3Bqrk3ty6+0bVserTb3W9s6KxoquogksGuZaSTKJDC7I8WsRJKn6I2oSdvSMNYB44EOwA072SQxEuALNSuDxvCnNToOjp8HXf4XtHWG1aHp6KYA6DP1RPSLIOZiDIqi8FuP36hVtBYAZ+6dYdjSYehR4YcfoKYhhObUKXjlFavEGzes5Eqjyi4ApKSrzNqYZNnIwMooisLMrl2zCnHxyZYtRJoLd43WUKrLwLZxkCG3r58WPz83GjUytba9di0u165tHjd7TpbosjtSzEokeY7SwEZEl7CsX+HNiJq0/9jHJIkJfx9LQRsTD8fPiXau+ZwOkztQqWslAFKiU5jfcz5p8Wl4uniyeOBi/Nz8AFh6eimTtk0CDw8RP2uIKWXuXPjlF6vY9mxLD/w9xc/k9I1MNh61bdetesWLM6JuXQDi09L4cONGywVl20OF7uI48QYcmGZT+/Irlq1tc6+qQVZFA5DNExwBKWYlkjyJEzAB2ASUMszdA3oCbwGyXIxd8fOGWpUxtqKKTYBj+V/QarQa+s3vR6Fg0Z75zok7LB68GFWvUjGgIvP7zUcx+CfHbxrPqnOrICgIfv/ddJE334QDB3LdNk83Dc+39zSOF+9O5la0bX8eX7Rvj48h8e2PQ4c4cPOm5YJW34AhYY69X0HSbZvalx+xVtyseRLYaZkEZnekmJVI8jStEGEHvc3mZgJNgdP2MEiSha831Aoydb2KS4Sj5yAzfwtaN183Bv0zCDc/EVN49p+zbPxIeCG7VOrCZ20/A0BF5dnFz3Ih+oKoN/vmm+IC6enQv7+oQ5vLVC3lTPuaQkxm6OD3DYlk6mwXbhDo6cmE1q0BUVzvzdWrLasrFKoKtV4WxxlJsGO8zWzLr5i3tl2//mKutbYt6+yGqyE+/qwMM7A7UsxKJHmeAGAxIkHMUO6Iw0B94A9kTVo74uMFtYPAySBo4xPh6FnIzLSvXVamUOVC9I/oj2JIvtk+aTvH5h0DYFzLcfQK7gVAbGosfcL7kJSeBN98A40biwtcvgxDh1olea5vUw+K+Ymvvit3dKw8YFsh8nqjRgQXEp7rndeuMe/YMcsFzSaCi484Pv4H3LnvccljYa3WtlpFobLBO3srM504Xf7+nXZ0pJiVSPIFCqJ01z6gqmEuGRgBPAvkXuKD5DHx9oRaweBkaEeVkARHzkJG/v7yq9ixIp2ndTaOl49Yzo19N9AoGv7q8xfBhYIBOBZ1jBf/eRHV2RkiIsAg9FixQgjcXMbFSWFEBy9jBMi/B1K5GGm7n4WLVsu3XboYx++tX09iulm5MI8i0PhDcazqYcvoAtGEw5pYL9TAFDcrvbP2RYpZiSRfURPRZOFFs7kwoC6iVq3ELnh7CA+ts0HQJibDkTOQkWFfu6xMozcaUXeESHrKTM0kvHc4CTcT8HH1YUnIErxcvACYf3w+3+7+FsqUgb//NpU3+/BD2JL7TQTKBTrRvb7wqulV+H19ImkZthOMXSpV4pmgIABuJiQwads2ywX13gSfsuL4yjq4vNpmtuVHrNXaNlh2AnMYpJiVSPIdHoiWtxGAr2HuEtACmIzoKC6xOV4eUDsYXERHKpJShIc2Pf8KWkVR6P5Dd8q0KANAws0EwvuEk5GSQdUiVfmr91/Gte+ue5dNlzZBly4w3hArqtNBaCjczv1EqG713SgfKMI/ouL0LNxlWzEyrVMnnA0VL6bu2sVF8xhhJzdo+ZVpvGWMaHcreSIqVPC3aG2bmJg7jTOCXc06gcmKBnZFilmJJN8yAJEc1swwzgTGAp2B3Ikbkzwmnu45CNozkGbbrlS2ROuiZeCigfiWETdWN/be4J8X/0FVVfpU7cMHLT4AQKfqCFkYwrW4a/Dxx9Chg7jA7dswaFCuxxlrNQovdPDCxeAs33w8jeNXbfdzqFyoEO80aQJAmk7H6LVrLRcEh0BxQwzxvZNw7HckT45la9vLuXLNUk6ueChCRp2RYQZ2RYpZiSRfUxbYAnwIxpLt6xE1aVfZy6iCjYcb1AkGV1HEn+TUfC9oPQM9CV0eirOHEPHH5h5j5zeiFfOnbT+lc0URW3sn+Q59I/qSqmaImrMlSogLbN4sBG4uU8xPS/+mpq3i2RuTSEy13c7FR61aUcxLhFosPX2a9RfNtsAVBVqb1ZrdMR7S4m1mW37DGvVmNYpCkCEJ7I4ug2hd/t1lcXSkmJVI8j1OiJa364Hihrk7QDdgNJB/RZTD4m4QtG4GQZuSBofPQKptC/nbkmK1i9FnTh/jeP3Y9ZxdcRatRsu8fvMo7ycyzvff3M//rfw/1CJFREJYVmmzSZNg5cpct6tNDVeqlxYiOy5ZZe6WZMtyWVbE29WVr9q3N47fXr2aTPMKDiWbQdAAcZxyR9SelTwR1mptG2zRPEF6Z+2FFLMSSYGhHXAUeMZsbhoiDOGcXSwq0Li5Qu0q4n8QQvbwGSFs8ylV+1alzSdtxECFRc8uIupEFAHuASwJWYK7k/By/XH4D3458As0bw5ff226wJAhomxXLqIoCsPbeeLhKoTO/gvp7D1nuxu8IbVr06ikaLl64s4dfty3z3JBy69Aa7jpOTAN4q/YzLb8hJ+fG40biwYzudnaViaBOQZSzEokBYrCwHJgBmD4guQAUA+YYy+jCi5uLsJD624QtGnpcOQ0pOTfDm6txrei2oBqAKQnpBPWM4zke8nULlab33r+Zlz3xqo32HVtF7zzDvQxeHRjYkSDhbTcFfx+nhoGtzKJknnbkolOtE24gUZRmGlWquvjzZu5m2wmivwqQF1DQwldGmz7wCZ25Uey4mYh90INZCcwx0CKWYmkwKEAbwK7gSDDXCIw1PAvwU52FVBcXaBOFRFLC5CWITy0yflzy1JRFHrN6kWxusUAiLkYw4IBC9Bl6Hi25rO83fhtADL0GfRf0J/bSZHwxx9Q0RDzuH8/jBqV63Y1rOxKo8riBi85TWX2xkT0Ngo3aFyqFMNq1wYgNjWV8Rs33rfgQ3Az1N89PQ9u7bWJXfmNjh1zv95scScXfDQiFOZsWorNQlQklkgxK5EUWOoivLLPm83NQXhpD9jFogKLi7OocuBp8PKkGwRtUv4UtC6eLoQuDcUz0BOAy5sus+adNQB83fFrWpcVLV9vJtxkwIIBpHt7wMKF4GrwYP/wA8ybl+t2PdvSAz9PEW5w6nomm47ZLuRjUvv2eLkIMf3LwYMcMS9H5uYHTSeYxrKRwhNh3tp23bqL6HRP731XzJLAYvSZ3JFJYHZBilmJpEDjhWh5Ow/wNsydB5oCU5E1aW1IlqD1Mmx3Z2SKKgeJ+XPr0reMLyFLQtC6CK/Wvu/3sf/n/ThrnYkYEEFJbxFHuv3qdkavGQ116sD335su8NJLcOpUrtrk6abh+XZexvGiXcncitHl6nM8iOLe3nzUsiUAelXlzdWrLb18tV8Bf8NOyo3tcH6JTezKT5i3to2OTuHQodypX2weNytDDeyDFLMSiQQYBBwCGhrGGcAYoDsQZS+jCh7OTlArSHQMA5OgTUiyr11WonSz0jzzsykhcdXrq7i8+TKBnoEsDlmMiyHx6bt93/HXkb/ghRdg+HCxOCkJ+vWDxMRctalaaWfa1hTeuwyd6A6WqbONF/TtJk2oFBAAwNYrV1hw8qTpQa0ztDJr77v1PdDJSiSPi2WJrtwJNZAVDeyPFLMSicRARWA78L7Z3GqgFrDOLhYVSLIErY/YgidTB0fPQnz+FLR1htehySjRPECfqSeifwQxl2JoVLIR33czeWJfXvEyB28fEt7ZmjXF5KlT8Morub7l3q+JB8X8xNfjlTs6/j1gG4Hi6uTEtE6djOMxa9eSbN7yuGIPKN1GHMdegMPfI3k8rNHatopZEthZ6Zm1C1LMSiQSM1yAr4C1QFHDXCTQCSFyZTyYTXBygppB4GPY8s4StHG564V0FDpO7kjFzkJkpNxLIaxnGGkJaYysN5KX6r0EQGpmKn3D+3KXZBE/620Ii5k7F37+OVftcXVWeKG9FxpDn5GVB1K5FGmbdrLPBAXR2ZDsdi0+nq937DA9qCjQeirGBii7P4OUaJvYlV+oUMGfihVzt7VtYa0z/hrRSu5MukwCswdSzEokkhzoiGiF29ls7mugBZA73gzJf+CkhVqVwc8g2nQ6OHYWYvNftQmNk4b+Yf0pFCwy9qOOR7FkyBJUvcrMrjNpUkp4bq/EXWHQokFkVqoAv5u1d33rLVHlIBcpX9SJ7g2Ex02vwu8bEknLsL5IURSFb7t0wUkjvp4n79jBldhY04Ki9aD6UHGcGgO7P7W6TfmNLO9sbrW2VRSFYFfxWUnQ67iZKcM/bI0UsxKJ5AEUBf4FpgDOhrm9iCoIYfYyqmCh1UKNSuDvI8Y6PRw7BzH5r62pm58bg5YPwtVXxKueWXaGjeM34urkysIBCynqKXYK1l9cz4cbPhT1Zt96S5ycni7GMTG5alO3em6UCxQJapGxehbtss0WcpXChXmjUSMAUjMzeW/9essFzb8AQ4MJDn8PMbLpyePQsaOp3mxuleiqIpsn2BUpZiUSyUPQIFre7kTE1ALEIxLGXgDyZxynQ5ElaAMMglavh+PnIDp3Ohg5EoWCCjEgYgCKYX9/+5fbOTb/GCV9SrJgwAKcDFu5X+/8mgUnFojuYE2E15bLl2HoUPH+5BJOWoUR7b1wEU/LpuNpnLhqm1Cbj1u3poiHEEgRJ06wxbzzmXdJaDBGHOszYev72S8geSCWrW1zZ6cpyELMyiQwWyPFrEQieQQaIKodDDabmwXUBw7bw6CChUYD1StBIV8x1qtw/Dzci7WrWdagYqeKdJpqSoJa/sJybu6/ScuyLZnaaapx/vllz3Mi9hxEREAhQ0OBFSvgm2/uv+RTUcxfS7+mJqEye1MiSanWL1nn5+bGl+3bG8dvrV6NzlyoN3wPPEXjCc4vgWtbrG5TfsG8te3p07nT2jYrzADgTJr0zNoaKWYlEskj4o1oqvAXYMi05wzQGJgJyKQHq6LRQLWKUNhPjFUVTlyAu7m7te4INH6rMXVeqANAZmomYb3DSLiVwBuN3mBwLXFDlZSRRJ/wPsQW8Ya//xbJUQAffACbN+eqPW1quFKtlHDPxiapzN1qG7HyfJ061CteHIAjkZH8evCg6UEXL2j+uWm8ZTSosi70o5LbrW0DtM4EakU41tn0FJt1j5MIpJiVSCSPyRCEl7aeYZwOvAX0BO7ay6iCgUYDVStAEZGNjarCyYtwJ38JWkVR6P5Dd0o3Lw1Awo0EwvuEo0vT8fMzP1OnWB0AzkWfY8iSIeg7d4Lx48XJej2EhsLt3CmID6BRFIa388LDVQjmfefT2XvO+t3BtBoNM7t0MY4/2riRmBSzLezqw6FILXEceQBO5X5XtPyKZYmuXKo3awg1SFH1XM+0Xfc4iRSzEonkiaiMiKMdZTa3AqgNbLKLRQWGLEEbKIrrC0F7AaLyV4kmJ1cnBi4aiE9pESt8Y88N/nnpH9yd3FkSsoQAd/H6V5xdwWdbPoOPP4YOHcTJkZEwaBBk5l45LX8vDc+2MoUbzN2aTEyi9T2hzcuUYVCNGgDcS0lhgrnXWaM1lOoysG0cZMgt7kehYcOS+PrmbmvbILNQg9My1MCmSDErkUieEFdEy9uVQBHD3E2gPTAesE1dzgKJokCV8lCskGnu1EWIvGc/m6yAV1EvBi0fhLOH2L49OucoO6fspJxfOcL6haFRxFfYxC0TWXFhFcybByVFG1w2bxYCNxdpXNmVhpVEV7LkNJXZGxNtsp38dceOeDiL9+CHffs4HmXWla9sByjfTRwnXocD061uT37AyUlDu3a529q2ikwCsxtSzEokkqekG6ImbVayigp8DrQGrtjLqPyPokBQOShe2DR3+hLczl+hHsXqFKP3X72N4/Xvr+fsyrN0rNiRL9t9aZwfvHgw5zSxEB4uKkAATJokksJykedaeeDnKcINTl7PZPNx628nl/LxYVyLFgDoVJW3V6+2LMzf+htQDK9571eQlHshFvmZ3A41CDLrBCbLc9kWKWYlEkkuUBzRNewrwFDHiJ2IsIOF9jIq/6MoULkslChimjtzGW7esZtJ1qBav2q0nthaDFRYNGgRd07d4b3m79Gvaj8A4tLi6BPeh8SGtUXJriyGDIFLl3LNFk83DcPaehrHi3YlcztGl2vXfxCjmzalnJ8fABsuXWLp6dOmBwtVg1qiUxoZibBzgtXtyQ/ktpj10TpRwkl47s+np6CTSWA2Q4pZiUSSS2gQLW+3AeUMc3HAAOBlQHoqrIKiQKUyUDLQNHfuCtyIevA5eZDW41tTtV9VANIT0pnfYz6pManM6jWLakWqAXDizglGLB+B+vbb0KePODE2FgYOhLTc86DWKONC2xoi3jI9U3QHy9RZV7i4OzsztZOpZNnotWtJNY8JbjYRXAzd4o79BnePW9We/IB5a9udO6/lSmvbrCSwNFXlckbqU19P8mhIMSuRSHKZJojasyFmc78ADYFj9jAo/6MoULE0lC5mmjt/Fa7nn+1mRaPQ+8/eFKsjXmPMhRgWDFyAh8aDJSFL8HEViWIRJyKYsmsqzJoFFQ2et/37YdSoB136iejX1IOifuIr9HKUjn8PWl+49KlShXblRZznpdhYpu7caXrQIxAafSCOVT1sGWN1e/IDud3aNliGGtgFKWYlEokV8AXmA78DWUkRJ4FGwI/ImrRWQFGgfEkoU9w0d+E6XL1lP5tyGRdPF0KXheJRRHymLm24xJpRawgqFMScPnOM68ZuGMv6e/tg4UJwcxOTP/wgEsRyCVdn0R3M0KyMlftTuBRp3aRHRVGY0aULWkNN3S+3b+dGvFlr4/pvg09ZcXx5DVxabVV78gO5HWoQ7GqWBJYmk8BshRSzEonESiiIlrf7EbGzAKnAa0A/IH+VknIIsgRtuRKmuUs34MpN+9mUy/iW8SVkSQgaZ/H1te+7fRz45QA9g3vycStRvUCv6gldGMrlcn7w3Xemk196CU6ezDVbyhd1olt9N8Nzwh8bEknLsO6NWo3AQF5t0ACA5IwM3l+/3vSgkxu0mGQabxkj2t1KHkjbtuVytbVtZRd3DPc30jNrQ6SYlUgkVqYqsBt4w2xuCULgbrOLRfmesiWEqM3i8k0havNJQkqZ5mV45qdnjON//+9frmy9woQ2E+hWWZSpupdyj77hfUkZMgiGDxcLk5Kgf39ITMw1W7rXd6dsEVFJ4HasnsW7rS9gPmnblkLuYjt77rFj7Lx2zfRglVAo1kgc3zsBx/+wuj15GV9fy9a2V68+XWtbT42W0k4invpCeirpsiubTZBiViKR2AA3RMvb5UBWbdTrQBvgE8D62eAFjjLFoUIp0/jqrXwlaOu+UJfGbzcGQJ+pJ6JfBPFX4vm7z99U9Bdbx4duH+KVf19F/e47qFlTnHjqFLz8cq69D05ahREdvHA2VMbaeCyNk9cycuXaDyLA3Z3P2rY1jt9ctcpU71ZRoM000+Id4yE9war25HUsW9vmXqhBJiqX0mUSmC2QYlYikdiQHoiatIYyS+iBiUA74NoDzpE8MaWLiUoHWVy7DRev5xtB2+mbTlQ0xDwm301mfs/5eOo8WRq6FA9nISj+OvIXP5yYLeJnvQ3Z/vPmwc8/55odxf219GtqipWctTGRpFTreuReql+fWkWLAnDg1i1mHTpkerBkcwjqL46To0TtWckDMY+bXbfu6UMNZL1Z2yPFrEQisTElgQ3AZ4DBncVWoA6wzE425WNKBopatFlcj4Tz1/KFoNU4aegX1o9CQcLbH3UsiiVDllC9cHVm9ZplXPf2mrfZ7hYFf5htub/1lqhykEu0relK1VKixnJsksq8bdYVMVqNhhlduhjHH2zcSFyqmRew5VegEV3DODAN4uXN4oPI7da2shOY7ZFiViKR2AEt8BGwBcjyHEYDvYHXAfkFkKuUKCK6hWVxMwrOXc0Xgtbd353Q5aG4GsTI6aWn2TRhEwOrD2RMU1GeKlOfyYAFA7jZuZkQsQDp6SJ+Njp3EhE1isLwdl54uIr0n73n0tl3zrrdwdqUK0f/aqLGblRSEp9u2WJ60K8i1DXEqWemwvYPrGpLXsbJSUP79iLUIDda21ZycTeKq9Np0jNrC6SYlUgkdqQ5oiZtP7O574HGiFJeklyjeGGoUt40vnUHzl7OF4K2cHBh+of3RzHUydr2+TaOhx9nUodJtC8v2izfTrxN/4j+pE/6HJo0ESdeuQLDhoE+d0ICArw0PNvS5JX7e2syMYnWDTeY0rEjbk7CIzxz715O3zVrZ9zkI3ALEMen/obb+6xqS17GPG72aUt0uWk0lHMWVS4uZ6SSmkufL8mDkWJWIpHYGX9gAfATIlEMRHOFBsCvyJq0uUjRQlDVTNDevgenL+ULQVupcyU6TuloHC97fhlRh6KY328+ZXyF93/X9V28teFdiIiAQoZExBUrLNvfPiWNKrvQoKJoaZqcpvLnpiRUK76/Zf38eK9ZMwAy9XreWbPG9Hxu/tDUrLXt5tH54mdtDTp2zOV6s4ZQAz1wIUPuNFkbKWYlEokDoCBa3u4HqhvmUoCXEJ3EYu1jVn4ksBBUqyCy3gGiouHUpVzzTtqTJm83oc7wOgBkpmQS3jsc9wR3Fg9cjKtWhCH8dOAn/ri7DubONb0HH34Imzfnig2KojC4tQe+HuLaJ65lsPmEdcMN3m/RgtI+ogPa6vPnWXnunOnB2q+Af2VxfGMbnF9qVVvyKve3tk1IeLqfWbCrKQlMhhpYHylmJRKJA1Ed2Ae8aja3AJEctjOnEyRPQpEAS0F7J38IWkVR6P5Td0o3Kw1A/PV4wvuEUzugNj8985Nx3WsrX2N/zUIwfryY0OshNBRu5U63NE83DcPbeRrHC3cmczvWeuXnPJyd+aajySv9zpo1pGUamiVoXaDVN6bFW98DXbrVbMnLWLa2vfJU1wqWSWA2RYpZiUTiYLgDPwCLAD/D3BWgFfAFsiZtLlHYH6pXNAnauzFw8mKeF7ROrk4MXDwQn9LCU3l993VWvLyCYbWH8VqD1wBI06XRN7wvUaNfgQ4dxImRkTBoEGTmTsesGmVcaFNdeIPTM+GP9Yno9Nbb4h9YvTqtyoqqFeejo5m5Z4/pwYo9oZShHF7seTj8g9XsyMtYluh6ulCDCi5uOBl6gZ2V5bmsjhSzEonEQemLqEnbwjDWISogdATyT3tWu1LID2pUAkPiFPdi4cSFPC9ovYp6EbosFCd3kRh15K8j7Jq2i+ldptO8dHMArsVfI2TJs2T+/ReUNHRL27LF5K3NBfo38yDQV3zNXorSseqg9QroK4rCjC5d0BhuTj7bupXbWZ3OFAXaTDUt3v0ppMh20veTm61tXRQNFVxEDsDVjDSS9fIm3JpIMSuRSByYMsAm4GNMf642AbWAFfYyKn8R4As1KoPG8P5Gx8Hx86DL21++xesWp/efvY3j9e+t58raKywYsIBiXsUA2Hx5M+8fngLh4WCoCMBXX4mksFzA1VnhhfZeRuf3iv0pXI7KHc9vTtQpVowX69UDICE9nXEbNpgeLFofqg0Vx6kxsOdzq9mRV/H1daNJk9xrbZsVaqACZ2WogVWRYlYikTg4ToiWtxsRDRcA7iG6ib0NWDe5pkDg7wM1zQRtTHy+ELTVB1Sn1cetAFD1KotCF+F03YmFAxbipBHiddruacz3uWpZ0WDIELh0KVdsqFjMie71hYdOp4ff1yeSnmm9cIPP2rbFz0083+zDh9l744bpwRZfgJMhMenQdxBz3mp25FVyM9Qg2KwTmAw1sC5SzEokkjxCa0TYQS+zuRlAE+CMXSzKV/h5Q60g0Bq+FmIT4Ng5yMzbgrbNhDZU7VsVgLT4NMJ6hlHPqx4zuswwrhmxfARHB7WDvn3FRGwsDBgAablzo9S9vjtli4hud7dj9SzeZT1hU8TTk4mtWxvHb65ahT6rHJd3KWgwWhzrM2Db+1azI6/SsaN5vdmnCzUIdjVLAkuTnllrIsWsRCLJQxQClgDfAa6GucNAfWA2sibtU+LrZRC0hjbDcYlw7GyuJUXZA0Wj0PvP3hStVRSA6PPRLAxZyMt1XmZ4neEApGSm0CeiLzE/TIOKBs/cgQPwzju5YoOTVmFEey+cDW/rhmNpnLyWkSvXzonXGjakWpEiAOy5cYO/jx41PdjwffAUYRacWwzXt1nNjryIeWvb9eufrrVtOWc3XAwxJqelZ9aqSDErkUjyGArwf8AeoIphLgl4HngOiLeTXfkEHy+oHQROBuUVnwRHz0JG3hW0Ll4uhC4PxaOI8JRdXH+RtWPW8mP3H6lfvL6Yi7nIc+tfRbcgHAzb9Pz4I8yblys2FA/Q0reJyVM3e2MSyWnWSbRz1mr5tnNn4/j99etJyPIyu3hBs89MizePAjVvJ/zlJrnZ2tZJUahsCDW4mZlOgi7v/g45OlLMSiSSPEptRJOFkWZz84G6wF67WJRv8PaE2sHgbEiKSkjO84LWr6wfIYtD0DiLr729M/dycvZJFocsprBHYQBWnV/FxJil8P33phNfeglO5k5r5Xa1XKlaSrynMUl65m21nreuY8WK9AoOBuB2YiJfbDPzwNZ4HgrXFMeR++H0fKvZkRfJzda2QWb1ZmUSmPWQYlYikeRhPBEtb8MAH8PcRaA58DWimaTkifDysBS0iclw5AykW2973NqUaVGG7j92N45XvrYS9ahKeP9wNIr4Ovx82+csbRYAzz8vFiUlQf/+kFXm6inQKArD23ri7iK2nvecS2f/ees1MJjaqRMuhpCR6bt3cz7aUI5Lo4XWU0wLt40D2XLViHkS2NOKWfMkMBlqYD2kmJVIJPmAEETsbBPDOBN4H+gCPPk2YYHH0x3qBIOLsxgnpeR5QVtvRD0avdkIAH2Gnoh+EdTT1GNyh8nGNUOXDOX0J29ATYP38tQp4aFVnz4mO8Bby7MtTd66v7ckEZtknZuuigEBjG7aFIB0nY5Ra9aYHizXCcp3FccJ1+DgdKvYkBcpX96fSpUCgKdvbSs7gdkGKWYlEkk+oTywFfgADJ13YB0iHGHNg06S/Bce7sJD62oQtMmpcPgMpOXdlqidp3amgiFrPflOMmE9w3ij5huEVA8BICE9gT7LnyVh/mzw9hYnzZ8PP/30gCs+Ho2DXKhfUbyfSWkqf25KQs0FoZwTH7RsSQnDa/jn7FnWnDcrx9XqGzB4pNkzCZIirWJDXiSrqsHTtrYt7eyKu+E9PpsmPbPWQopZiUSSj3BGtLxdBxQ3zEUhPLTvAnlXgNkVDzeoXQVcXcQ4JVV4aFPz5vupcdLQP7w/AZWF9y3yaCRLhy3lt2d+o0ZgDQBO3z3N8BNfoP7+u+nEt9+G/fuf+vkVRWFwa098PcRN1/GrGWw5YZ16yV4uLkzOatkLvL1mDRlZ9YMLV4eaL4rjjETYOcEqNuRFcivUQGuWBBapyyBGl3d3NRwZKWYlEkk+pD2iJm03s7kpiFhaWSj+iXB3FSEHblmCNg2OnIbUvNm0wt3fnUHLB+HqI8ownV5ymn2T9rEkZAl+bn4ALD61mK+KnRciFiA9XcTPRj99K1gvNw3D2noaxwt2JhMZa52avs/VrEnTUobOVnfv8v2+faYHm30CLgbv87Ff4e5xq9iQ1zBvbbtu3VPWm5WhBlZHilmJRJJPKYJoeTsd4bEFUf2gLjDXXkblbdxcoU4VIWxBeGYPnxGe2jxI4SqF6RfWD0UjRMvWT7eStiGNuX3nohhCVT7c+CFrXm4PhthTrlyBYcNA//RxrjXLutC6ungv0zPh9w2J6PS5H26gKAozu3Y1Bt9M3LyZO0lJYuBZFBqNE8eqHra8m+vPnxfJzda2VVxNSWBnZKiBVZBiViKR5GMURMvb3UBlw1wiMBgYBiTYx6y8jKuLiKH1MNRiTTMI2uS8KWgrd61Mh69N2/BLhy2lbkJdPmnzCQAqKoOWDeXir19DoUJi0YoVlu1vn4IBzTwI9BVfxZcidaw6aJ33sUGJEjxfpw4AcWlpfLhxo+nBem+DdxlxfHk1XF5rFRvyGrnV2lZ6Zq2PFLMSiaQAUA84iBCwWfyF6Bx2wC4W5WnuF7TpGSKGNilvflE3HdWUOsPrAJCZkklYrzDeCnqLnsE9AYhJjaHvttdJ/ut3MHR04sMPYfPmp35uV2eFF9p7GS+7Yn8KV6KsU8/3i/bt8XYRYSK/HTzIwVu3xAPO7tBykmnhltGgz9ttjHMDy7jZJw81KOHkgpdGlEg7k55stWS/gowUsxKJpIDghWh5+zdgiBHkHNAUEYogv2AeCxdnIWg9DVuoeVjQKopC95+6U6qp2FaOvx7Pgn4L+KPrHwQVCgLgSOQRXkyNQP14vDhJr4fQUMgShE9BxWJOdK0nbgx0ehFukJ6Z+5/HYl5efNy6NSA+7W+uWmUSVlVCoVhDcXz3OBz/I9efP6/RoEEJ/PzEz+VpWtsqimKsNxuty+Su7ASW60gxK5FIChjPAYeABoZxBjAKeAZR+UDyyGQJWi/DNmpGpgg5SMx7cYFOrk6ELA7Bp5RovnF913W2v72dxQMX4+XiBcC8Y/OY2dkPOnYUJ0VGwqBBkPn04qRHA3fKFBbeu1sxepbsts57+GbjxgQZwiV2XLtG2HFDwpeigdbTTAt3jIf0gh2G4+SkoV278oBobXvw4JPfuFiGGuS93w9HR4pZiURSAKkI7ECU68riX0RN2g12sSjP4uwEtYP+n73zDovq2vrwe2boHSsWFFHAXoIaW1QUeyzRqBijpphygxprNFGj3ptmmtFEU7wmfik3mmg0xhiNYu/YsSEixYYFBKTDzHx/7GEGInUYGcD9Ps88Ye9z9tnrDJH5zTqriBa4IITd6XC4n2pZu0zAycOJoN+DsLIXXc9OrT5F8o/JrB662nDOjO2z2PNhMNSrJyb27IH588u8t5Va4cVAJ6yEnmXHmUwuXDN/GScbtZol/foZxrO2byc1S19irX438Bkhfk67BaHmiQuuzJirta2vjUwCe5hIMSuRSB5RbBAtb7cCtfRzcUAfROMFWQ+yxFhZQWsfcMkVtBo4fQmSy94Ctryp81gdhq0eZhhvn7Wd1jGtmdN1DgAanYZRO17m2vdfiPsG+OAD+OOPMu9dt5qa4Z2MHrzVO1NJyzR/d7CBPj4M9BEJkdfv3+eD/fuNB7svBpW++sexjyH5qtn3r0zkTwIzPW62qa1MAnuYSDErkUgecfoBZ4C++rEOeB94AoiylFGVDysraOULruKRPBoNnLkESZXvUXWLUS14Yt4TAOi0OtYHrWdq3an08RbhBbdTbzPiyvtkLn7PuGj8eIgq+/8vvVvb4ldPiOSEFC0/73s4Xrwl/fphrRIS4KODB4m6d08ccGsM7SaJn3My4MDch7J/ZcFcrW1rqa1xU4nfq0wCMz9SzEokEgm1gb8Qnlq9t40jQFtgrYVsqoRYqaGVD7jpE+w0WjgTAYmVT9AGLAqg6VNNAchMzuSXYb/wXa/v8HLzAuDo9aNMahIOw4eLBYmJMHIkZJSttJZKUXi+lyP2NqK8weFLWRyPNH+nNd/q1Xn98ccByNRomLl9u/Fgp/lgJwQc53+AuLJ3PavM5IYalKW1bd4ksGSthricytk9r6JicTG7fPlyvLy8sLOz4/HHH+fo0aNFnp+YmEhwcDB16tTB1tYWX19ftmzZUk7WSiSSqosKEUN7EMiNk0sGgoCJQOWLAbUIajW09AF3kUiFVgthEXAv2bJ2lRJFpfDU909Ru3VtABIiEtj5/E7WDV+HnZXIcP/vyVWsnNYDmjQRi44fh+nTy7x3dWc1Y54wPpb+YXcqianmDzeY36MHtR1FaMhvFy6wM9ezbOcOnd82nrhnBjzCnkRztbb1k6EGDw2Litm1a9cyffp0FixYwIkTJ2jTpg39+vXj9u2CM4qzsrLo06cP0dHRrFu3jvDwcFauXEm93EB8iUQiKTMdENUOnskztwpR/eC0RSyqdKhV0LIJVHMVY60WzkZAguldlCyBjZMNQb8H4VBDiJAr269w59M7rBy80nDOpN2zOPLNArDT19z98kv4qewd5jr52vCYt4hdTc3U8X+7Us3+aNrF1pb3e/c2jF/fupWc3M5mbf4FbnqRfm0vXP7drHtXJnr2NLa2LZOYzZsEJisamBWLitlPP/2Ul156ieeff57mzZvz1Vdf4eDgwLffFlzf7ttvvyUhIYGNGzfStWtXvLy86NGjB23atClnyyUSSdXGBVGPdjWgT2riIvA48AWyJm0JUKmgRWOo7ibGWh2cvQzxiZa0qtS4ebkxav0oVFbi4/LIZ0docawFUzpOASBLk8WIk3O4tSxP/OzLL8P582XaV1EUnu3hiIu9EFFnY7PZe960eM2imNC2LR3q1hV73L7N18f0IQVqG+iep5rBvjdA82g+Gs/b2jY8PN7k1rb5ynNlSs+sObGYmM3KyuL48eMEBhrbCKpUKgIDAzl06FCBazZt2kTnzp0JDg6mdu3atGzZkvfeew+NpvBOJZmZmSQnJ+d7SSQSSfEoiI5hJ4B2+rlMYDIwDIi3jFmVCZUKmntDTXcx1ungXCTcvWdZu0pJw+4NGbhioGG8+dXNvO7wOt0bdgfg+v3rjLTaQPbz+g5zaWkwYgSklK2ag7O9igkBjobxLwfSuJ1k3s5cKkVhaf/+hvH8XbuIT9N7DZsMg/riHrkXAae/NOvelQlztLatbmVNDbXwtl/KSkP7CIdumBuLidm7d++i0WioXbt2vvnatWsTFxdX4JorV66wbt06NBoNW7ZsYf78+XzyySe88847he7z/vvv4+rqanh5enqa9T4kEklVxxc4BEzNM7cJUZN2twXsqWSoVNDMG2rpE4p0Ojh/Be4kWNauUuL/kj8dJ3cEQJutZf3I9azquIq6zsKruS92HzOfcoDWrcWCixeFh7aMgqW1lw3dm9sCkJUD3+5IRaM1rwjq7OnJs3q772Vk8PauXeKAokCPT4wnHvo3ZFSuLyLmwlytbXNDDVJ1Wq7LJDCzYfEEsNKg1WqpVasW33zzDf7+/owePZq5c+fy1VdfFbrmzTffJCkpyfC6evXRrpknkUhMwRbR8nYzUEM/dx3oBbwNyPaURaIo0LQR1BadpwyC9lbl8m73+7Qf3oEiOTDtTho7ntnB2ifXYq2vy7rsxJf8+NE4cNZXc/j5Zyji86mkjOzqQE0X8XEdeSuHrSfLVjGhIBYHBuJoLe7jq+PHOXPrljjg0R6aPSt+zkiAw4U7j6oy5mptmzfU4KJsnmA2TBKzGo2GVatW8cwzzxAYGEivXr3yvUpCjRo1UKvV3Mr9B6Pn1q1beHh4FLimTp06+Pr6olarDXPNmjUjLi6OrKyCv+HY2tri4uKS7yWRSCSmMQiRBJb7d04H/AfoCZhWsueRQVHAzws8ahjnLkZB3F2LmVRaVFYqnl77NNX0dUdvnb7Fjbdu8Hn/zw3nvBQ6n5Mr8nQEmzoVQkPLtK+dtcILvR1RRPgsf4SmE3vHvF+g6jo7M/cJUVtXq9Px+tatxoSzbu+BvoIDJz+HRNOToCorVlYqevcue2tbP1tjEtglmQRmNkwSs6+//jqvv/46Go2Gli1b0qZNm3yvkmBjY4O/vz8hIcbWkVqtlpCQEDp37lzgmq5du3L58mW0WuM3okuXLlGnTh1sbGxMuRWJRCIpJXWBv4H3gNwv1gcQNWnXW8imSoKigG9DqFPTOBceDTfvWMyk0mJfzZ6gTUHYuohH/xfWX8DvTz8mtpsIQEZOBsPjVxA/7RWxICtL1J9NKFtYRZM61vRvJwSlRgv/3ZFKdo55ww2mde6Mt7uIb94dHc36CxfEARdP8J8hftZmw97ZZt23smCOEl35ksBkeS6zoehMqPVRo0YNvv/+ewYOHFj8yUWwdu1aJkyYwNdff03Hjh357LPP+OWXX7h48SK1a9dm/Pjx1KtXj/fffx+Aq1ev0qJFCyZMmMDkyZOJiIjghRdeYMqUKcydW7IuJcnJybi6upKUlCS9tBKJpIwcAsaQ3yv7CiIkwb7AFRJEmEHkVbiepwyjTwOoW6vwNRWMiC0R/O/J/xkKWwz7eRgvp7zM0euiVnrfRoFs+SoF9aHD4oRBg2DTJhFDbCI5Gh3vrU/m6l2RBBbYxpbRXR2LWVU6fr94kWFrRaOQhq6uXAgOxt7aGrLuwyofSNM/TR29D+p3M+veFZ2oqHt4ey8DoHv3huzZ85xJ1xlz7QJxmizsFBWbPVuiznW5S/JRGr1m0r8qGxsbmuQWiS4Do0eP5uOPP+btt9+mbdu2nDp1iq1btxqSwmJjY7l50+jK9/T0ZNu2bYSGhtK6dWumTJnC66+/zpw5c8psi0QikZSezsApYFSeua8RtWrPWsKgyoGiQGNPqJ8nATgiFq7dKnxNBcNnoA+Bi43VeDa/sJmv/b6mlqMQ5H9H7WDerMeghj6s4s8/YfHiMu1ppVZ4MdARK/0DgR2nM7l4PbtM1/wnQ/z86OMt4oJjkpL46OBBccDGGbr+x3jinhmgM38jh4qMuVrb5oYaZOi0xGabP/75UcQkz+wnn3zClStX+OKLL1Aq2TcK6ZmVSCTmR4dorDAFyH10aIfw0L6CKPMleQCdDqKuw9U8FWy864NnwXkTFQ2dTsfGCRs588MZAFw8XWi5viUD/hqARie8p+t85zFi7LviXlUqCAmBnj3LtO/fp9L59aD4/6yak4oFo11wsDVfPvf5O3do/eWXaHQ67K2sCJ80CU9XV9Bq4Ie2cFf/RW3gT9DsmSKvVdUIDv6TFStELd4//hjDk0/6lvoaPyfd5ptE4aibXd2T/k7VzGpjVeGhe2b379/PTz/9ROPGjRk8eDDDhw/P95JIJJJHCwXR8vY4oC/NRAbwL+BpoHKVoSo3FAUa1YOGdYxzV65BrGnJNeWNoigM/mYw9fUF9ZOvJnN16lU+6vmR4Zznoj/j/Nv/EgOtFoKC4GbZ7i+wjR1+da0ASEjRsma/eROJmtesyaSOogxZek4Ob+zYIQ6o1NDjY+OJ+96E7Ecr7tM8cbPGECRZ0cA8mCRm3dzceOqpp+jRowc1atTIV8fV1dXV3DZKJBJJJaEZcASYlGfuN0Ry2H5LGFTxURTwqgdedY1zUdch+kaZa7SWB1Z2Voz6bRTO9UQ5rqsHr+L9nTfPtBQey5SsFJ6qvoOk/j3Fglu3hKDNMb0agUpReL63I/Y2wuN/KDyLE5HmrVm6sGdPajiIZKU1Z8+yL0YfF+7VD7z0TRbux8KJpWbdt6ITENCozK1tfW1lEpi5MSnMoDIjwwwkEkn58DvwAkavrApYAMzFWAVBko/Ym0LI5tKgjhC5lSCc7caxG3z3xHfkZAiRGvBxAFMcp3D61mkAhnj1Z8PcM6iu3xALZs+GDz4o054HL2by3c5UAJzsFBYGueLqYL5wg2+OH+eVzZsBaOvhwbGXXkKtUsHdc/B9axEza+MML14Gh8qTvFdWnnjiO/bvjwUgOvp1GjZ0K/U1xl+/yNWcTKxR+LNBS6yVSlX2v1x46GEGudy5c4f9+/ezf/9+7typPKVVJBKJ5OEzFFGTVt8OFC1CzPYGrlnKqIpNgzoiMSyX2Jsi7KAS+Fzqtq/L0NVDDePdb+zmixpf4G4nSl1tit7Kux8MBCsRHsDixfDHH2Xas7OfDe0aiUYHKRk6/m9XKub0T73Yrh1t9XXfT8XFserkSXGgRgtoJUqRkXUfDi4w256VgT59vA0/b99uWjcwX32oQTY6orJkElhZMUnMpqam8sILL1CnTh26d+9O9+7dqVu3Li+++CJpaTL+QyKRSAT1gZ3AIox/bvcgWuFuspRRFZv6taFJA+P42i1RxqsSCNqWo1vyxFzReECn1bF/4n6+bfctij4BcEHkKra897xxwfjxEBVl8n6KojCupyMu9uL6YTHZ7LtgWoZ9QahVKpb1728Yz925k3vp+sfiXf4N1k7i5zPfCG/tI4JZ4mZlqIFZMUnMTp8+nT179vDHH3+QmJhIYmIiv//+O3v27GHGjBnmtlEikUgqMWpEy9s9QK7XMQHhuZ2MSBST5KNeLdFcIZfrt+FybKUQtAH/DsBvqB8AmUmZXJt8jXc6iBawOnQ8o/mFy2P6iZMTE+HppyHD9P8HnO1VjA8w1pr9ZX8at5M0Jl/vnzzRsCGjW7QA4G5aGov27BEHHGvD42+Kn3Va2DvLbHtWdPK2tg0JiTKptW3TPElg4bITWJkxScyuX7+eVatWMWDAAEOL2IEDB7Jy5UrWrVtnbhslEomkCtANUZP2qTxzXwCPAxcsYVDFpk5N0f42lxt34FJMhRe0ikrhqR+eolZLEUMafymeBssa8JSP+L0nZSbxVJerpPrpH1WfOAHTppVpzzZeNjzRXHQky8yBb0NS0WrN9z591KcP9vrwiC+OHuV8bljhY9PAWf8FLeoviN5utj0rMuZobdvExt4gwMJlRYMyY5KYTUtLMzQ2yEutWrVkmIFEIpEUSjVEy9svEXVoAc4A7RF1aiu2UCt3PGpA00bGcdxd0f62ggtaW2dbgjYF4VBDPEqO3BbJ80eep2mNpgCcjT/PizN90NkJAcpXX8FPP5Vpz1FdHajpIj7SI+Ny2HrSfB5/T1dX5nQT3b40Oh1Tt24VsbnW9tDtPeOJe2aIWrSPAGUNNbBXqWlgLf4GRGVnkKl9tBpQmBuTxGznzp1ZsGABGXkejaSnp7No0SI6d+5sNuMkEomk6qEArwKhQHP9XBqiTu0YIMlCdlVQaleHZsaEG27Fw8WoCi9o3Ru5M3LdSFRW4mP2xLITfJrzKc42ooTX2uvb+PQDY8IYL78M58+bvJ+dtcILvR0NhR82haYTe9f08l//ZFaXLjTUl97cfuUKm8LDxYFmz0Dt9uLnu2FwbrXZ9qzI5E0C+/tv05LAckMNNEDkI1av19yYJGaXLl3KgQMHqF+/Pr1796Z37954enpy8OBBli59tGrOSSQSiWm0RAjaV/LMrUXUpD1sCYMqLrWqQfPGxhJdtxPgwhXRhKAC49XDi4HLBxrGx2Yd48uGXxrGbyStY+e/9AlWaWkwYgSkpJi8X5M61vRvK7x9Gi2s2pFKdo55RL+9tTUf9+1rGE//+28ycnJAUUHPT40nHpgHWabfQ2WhUSN3fHzK1tpW1ps1HyaJ2ZYtWxIREcH7779P27Ztadu2LR988AERERG00AeKSyQSiaQ4HICvgF8BN/1cNCK+9n1EOS8JADXd8wvaO/cqhaD1f9mfDsEdANBma7k57SbzfOeJsU7LaK9jxD4uwg+4eBFeeqlMXuchHe2pX13UMb6RoGHjEfOJpBHNmtHTywuAK/fu8dlh/Zeu+k9AE30seGochH5otj0rMrne2ZwcLbt3R5d6fd5OYDJutmyYXGfWwcGBl156iU8++YRPPvmEiRMnYm9vX/xCiUQikfyDpxHJYV31Yw3wFtAXuGEhmyogNdygRROjoL2bCOciK7yg7bekH416idjf1Nup1PuwHoPqDwLgbvpdho+1It1dX+ZqzRr48svCLlUsVmqFiYGO6KMb2H46g/Dr2WWyPxdFUVjavz8q/fv/zt693Lh/XxzsvhhUouYtxz6G+1W/lnJZ42ab2Ngb2qdIz2zZKLGY3bRpE9nZ2Yafi3pJJBKJpLQ0BHYD84HcjlchiJq0WyxkUwWkuiu08gGV/uMrIQnOXhbP1Ssoams1T//yNO6NRQOFW6duMebPMXi7Cs/e8YSzvLaggzH9b+pUCA01eb961a0Y9rhwLumA73amkp5lnnCD1rVr86q/PwCp2dnM2bFDHHD3gbbB4uecdNg/1yz7VWTytrY1pXmCjaLCW++djc3OIP0RSZ57GJS4na1KpSIuLo5atWqhUhWugRVFQaOpuL8Q2c5WIpFUfHYDY8nvlZ2GCD2wtYRBFY/EZAi7bPTKujlDyyagrritgu+cv8N/O/2XrPtZADSb1Yzn3Z4nLVs8Yl6R3ot/Ld4pTm7YUJTtqlbNpL20Wh2fbLrPpRsiCaxLUxue7+VU9psA4tPS8Pn8c+7pk8APvfginerXh/QE+LYJZNwTJz57HGo/ZpY9KyplbW37cfxV/kwRLa+X1m5Mazvz/I6qAg+lna1Wq6VWrVqGnwt7VWQhK5FIJJWDnohWuIPzzC0BugCXLGFQxcPNBVr7gFr/MZZ4H8IioAJ/BtVsXpMRP48wON4vfHSBz+w/Mxx/3XEfBwe0FIOYGNEhzMQQCpVK4flejtjpn/wfvJjFiStZZbDeSHUHB/4TEGAYT/nrL7Q6HdhXg05vG0/cM6PCV50oK337lq21bVMbmQRmDkyOmf0niYmJ5rqURCKRSKgB/A4sA2z0cyeAx4DvkTVpAVdnaO1r9MYmpcCZCMipuILWd5AvgR8EGsZ35t1hZs2ZAGRrsxnR8zY3G+i9sX/+CYsXm7xXDRc1QU8Yu4P9sDuVpDTzhGO80r49LfUOrtAbN/i/U6fEgbavgVsT8fPV3RBZtUMPyxo362crk8DMgUlidvHixaxdu9YwHjlyJNWqVaNevXqcPn3abMZJJBLJo42CaHl7FPDTz6UCE4BxQLKF7KpAuDhBG1+w0gva5BQ4cwlyzFdj1dx0mdWF1s+2BiA7LZu6i+vSt5ooexWXfpunX/cgKzdaYt482LXL9L38bGjbSLhnUzJ0fL8rlRJGFxaJlUrF0v79DeM3Q0JIzswEtY1IBstl7xugMU8CWkUkb2vbHTuulLq1rZe1HdZ6V71sa2s6JonZr776Ck9P0cJu+/bt7Nixg61btzJgwABmzXp0+jNLJBJJ+dAGOA68kGfuJ4SX1vREoSqDsyO09gN9y1XupwpBm10xBa2iKAxeOZh6HesBkBybzIifR9DQoSEAB++fZ9p8Uc4LrRbGjIGbpW+ZmrvX+J6OONsLwXQmJpv9F0pfE7UgejVqxPBmzQC4lZrKf/bsEQeaPAX1nhA/37sEp78yy34VEbXa2Nr23r0Mjh8v3e/JWlHRWJ8Edi0nixSZBGYSJonZuLg4g5jdvHkzo0aNom/fvrzxxhuEliEDUyKRSCSF4YhoefszkJsMEYmIo/2YR74mrbOD8NBa5wraNDgTDtkV0ytoZWfF6I2jca4rOoLdPHST+SfmY6sSCX4rCGX1WH3d9lu3ICjIZG+zs72KCQHGcIO1B9K4k2Qe0fRxnz7Y6sM8lh45wqX4eFE6LW8jhUMLjUlhVZC8oQbbt5c+1KBpnlCDSzLUwCRMErPu7u5cvXoVgK1btxIYKOJ/dDqdTACTSCSSh0oQcBJ4XD/OAWYBA4FbljKqYuDkAG38jII2JR1OX4Ksiilones4E/R7EFZ2wt5ra66xONn4iP7Vppc53kbEpbJ3rwg5MJE2XjZ0ayaEcmY2fBuSilZb9nCDRu7uzOrSBYBsrZZp27aJAx7todlY8XNGAhx+t8x7VVTK2trWTyaBlRmTxOzw4cN55pln6NOnD/Hx8QwYMACAkydP0qRJE7MaKJFIJJJ/4g3sA+ZgrEm7DWgN/G0poyoGjvbQtinY6NP4U9PhdDhkmieT39zUbV+XId8OMYyTPk1iijIFgExNJsPHKNxx0QfQLl4MZajlPrqrAzVcxMf+5bgctp3KMN3wPMzp1o36+tJJWyIi2BIRIQ50ew+sRDwppz6HxNILvcpAWVvb5usEJuNmTcIkMbtkyRImTZpE8+bN2b59O05Ooi7azZs3ee2118xqoEQikUgKwhpRd/ZvwEM/dxvoB7wBVEzxVi442EFbP7DVV4FIy6jQgrbVmFZ0e7MbADqtjrpL6tLbqjcAsRm3CJrlTU7up/WECXDFNFFoZyPKdeV+/fn9aDpX75Y9rtjRxoYPA40VGqZt20aWRgMuDcB/upjUZMG+OWXeq6KSG2pgSmvbBtZ22CniFxyeKT2zpmCSmLW2tmbmzJksXbqUdu3aGeanTZvGxIkTzWacRCKRSIojEFGTdkCeuY+AboiY2kcUezsRcmCnF7TpmXAqHDLMk/xkbnq90wu/IaJiRUZiBk/+35M0UDcAYKcmgjf/5SNOTEyEkSMhwzSvqm9da/q2E95SjRZW7UglO6fs4QZBLVvSrYGw91J8PJ8fOSIOdJwDDvpQiUu/wvUDZd6rIlKWEl1qRcFH752N02SRqKmYiYsVGdnOViKRSCo9tYDNwCcIjy2IKgftgP9ZyijLY2+rF7T6rmkZekGbXvEEraJSeOrHp6jVUgi/pIgkZu2YhbX+9/lxzQjWBuo98CdOwLRpJu81tKM99auL0IXrCRo2Hi27N1BRFJb172/w+v57715upaSAjTN0+bfxxCraSKFnTy9Da1vT4mbzJIHJUINSI9vZSiQSSZXiOCJJ7HKeueeAz4FHtFVmZpYIM8gVsbY2ovKBvZ1l7SqAe1H3WNlhJenxQmDaPWPHHF/xeN5BbceRr7W0vKYPl/jhB3j2WZP2uRafw7u/JpOjFVHXM4Y641fPuth1xfHyH3+w8sQJAF5o25ZVQ4eCNge+bwvx58RJg36GpkFl3quiUZbWtjtS7/HuXbH2BVcPxrnVfhgmVipkO1uJRCJ5ZPFHdAobn2dutX7+pCUMsjy2NiIpzEEvXjOzhIc2zTwJUObEvZE7o9aNQmUlPp4z/pfBa/EiFyVNk8FTr7qRmKvBX3kFzp0zaZ/61a0Y9rjwBuqA73amkp5Vdo/pu7164WorPOHfnTrFsRs3QGUFPT42nrRvDuRUvPe+rJSltW3eigYXpWe21Jitna1EIpFIKgrOwP8BP2D0xl4COgGf8Ui2wrWxFiEHjvrHuVnZcOqiqHZQwfDq6cWAz40x0HW+rkPvNJEQdjnnNmNfr49WAdLSYMQIuH/fpH36tLHDp44oCxZ/X8va/alltr2moyMLevQAxP9lU/76S3Qca9QfGoouZyTHwImlZd6rolGWuNl6VjY46pPAZJhB6TFJzE6ZMoVly5Y9MP/FF18wderUstokkUgkErPwLMIb668fZwHTgMHAHUsZZTlsrEV4gZNe0GbniPCDlIonHtq/2p72r7UHQJOloc/qPjTMFB3CtthfY9EofVJVeDi8/LJJcagqlcLzvR2x1UcXHLiYxamosld8mNSxI01r1ADg0LVr/BQWJg70+Bj0go0j70Ha7TLvVZEoS2tblaLgayu8s3c1OdzNqZi1kSsqJonZ9evX07Vr1wfmu3Tpwrp168pslEQikUjMRRPgIDAjz9yfiBa5Oy1ikUWxthatb531j3VzBe39snslzU3/z/rjFeAFQMbtDCZtmoRNtqjO8O9mt9nUVi/K16yBL780aY+aLmqCuhm7g32/O5XktLJ1k7NWq/msXz/DePaOHaRkZUHNVtDyRTGZlQwHF5Zpn4qGWq0iMFCEGpjS2lYmgZmOSWI2Pj4eV1fXB+ZdXFy4e/dumY2SSCQSiTmxQbS83QLU1M/dRJT1mgs8Yl4gayto7QvOehGXo4EzlyC5YglatbWakb+OxN3bHYDUc6nMPzTfECUybrhCeHX9yVOnwtGjJu3TtakNbbyEe/Z+uo7vd6dSwtzwQunXpAmDfX0BuHH/Pu/t26ff7N9grQ99OfMNxF8o0z4VjfzdwEoXapA/brbihb9UZEwSs02aNGHr1q0PzP/11194e3sXsEIikUgklmcAcAboox/rgPeA7kC0hWyyEFZ6QeuiF1a5gjYpxbJ2/QOH6g4EbQrCxll4ZDU7Nbx2QSSEJWvTGP5aNe7bANnZov5sfHyp91AUhfE9HXG2F6WlTkdnc+Bi2cMNPu3XDxu1KAH2yaFDRCYkgKOHqD0LoNPA3lll3qciURYx29TWKGYvZUrPbGkocWmuvHz77bdMmjSJWbNm0atXLwBCQkL45JNP+Oyzz3jppZfMbqi5KGmpB41GY6irKyl/rK2tUev/CEokEnOjRXhq5wK5BdpdgZXASEsZZRk0Ggi7DEn6JCq1Clr6gJuzZe36B+F/hLNm6BqDV/bASwfYXm87AE/HVeeXr+JFjdeBA+GPP6CIEpqFcSoqi+V/CTFvaw0LRrlS07Vsf4fn7NjB4gOiUcJQPz82BgVBdhp86wcp18RJT2+HhoFFXKVy4ev7ORERCVhZqUhIeANnZ9sSrdPpdAy7do5krQY3lRW/1W+OoijFL6yilKY0l0liFuDLL7/k3Xff5caNGwB4eXmxcOFCxo8fX8xKy1Lcm6PT6YiLiyMxMbH8jZPkw83NDQ8Pj0f6H7NE8nA5AowBovLMTQSWAg4FrqiSaDRw9jIk6gWtSgWtmoBbxapFvv+D/YS8GQKAlaMV3734HZHVhPfvg4MOzP5b781791146y2T9li9M8XglW1Sx4pZQ51RqUz/G3w/MxO/L77gZooQyX8/+yx9GjeG8z/AX3q9ULM1PHsCVFXDgTFp0haWLw8FYNOmIAYP9ivx2jduXSE0Q/x/+HO9ZnhY2TwUGysD5SJmc7lz5w729vY4OVWOYtzFvTk3b94kMTGRWrVq4eDgIIWUBdDpdKSlpXH79m3c3NyoU6eOpU2SSKowScC/gJ/zzDUD1gCtLWKRRdBq4dxlSEgWY5UKWjSGag/mh1gKnU7HhnEbCPtJVAewqWfDu2PeJdUpFRUqtv6gpU8kwvYdOyAgoNR7pGfpWLQ2ifj7IglsRGd7+rezL2ZV0Xx/+jQTNm4EoHnNmpx65RWsVQr81BFuHRcn9V0FrV4o0z4VhU2bwhk6dA0AkyZ14PPPB5Z47beJN/khSVR5WFijIT0c3R6GiZWCchGzOTk57N69m8jISJ555hmcnZ25ceMGLi4uFVrYFvXmaDQaLl26RK1atahevXohV5CUF/Hx8dy+fRtfX18ZciCRPFR0iMYKk4DcWD1bRHvc14BH5Eu9VgvnIyE+SYwVBVo0geoVR9Bmp2ezusdqboSKp6K0hv8M+Q8aKw3VsOfYZ+k0SgRq1YKTJ6Fu3VLvcelGNh9vvI8OsFLB3KddqF/DymSbtTodXVat4sj16wAs7d+fKY8/Dtf2wlpRkxZHD3ghAmwqrn4oKcnJmVSv/iE5OVp8fasTHj6pxGv3pyUx/040AM+41OIl90fXmfNQOoDlJSYmhlatWjF06FCCg4O5c0fUK1y8eDEzZ8405ZIVgtwYWQeHR+jxWgUm9/cgY5clkoeNAjyP6BzWVj+XiRC3TwGlTyqqlKhU0Lwx1HATY51OeGvvJlrSqnxY21sTtDEIpzq5FQHg1QOvgg4SSGf4RGfSrIHbtyEoCHJyirxeQfjWtaZvW1EvNUcL/92RSrbG9Ie4KkVh2QBjE4gFu3dzJzUV6neHJsPEZGochH5k8h4VCRcXWzp1qg/ApUvxREcnlnit7ARmGiaJ2ddff5327dtz79497O2Njx+eeuopQkJCzGacpZChBRUD+XuQSMobP+Aw8Hqeud8RAnevJQwqf1QqaOYNNUU5LHQ64a29c8+yduXBua4zQRuDUNuKJ1Y1d9Vk0NlBAJxyus+roxxEnti+fTB3rkl7DH3cnnrVxPWvJ2j4/WjZSkV1rFeP59q2BSAxI4P5u3aJA08sFu1uAY59BPevl2mfikL+1rYlr2pQQ21FNbV4P8Iz08pcIu1RwSQxu2/fPubNm4eNTf7AZC8vL65frxr/I0okEsmjiS2i5e0fQG641TUgAFiIsfpBFSZX0NaqJsa5gvZ2gmXtykO9jvUY+u1Qw7jjxo40j2kOwA8+aXzRSf/x/uGHsGlTqa9vrVZ4MdARtf4yf5/M4NKNsj0le69XL5z0uuGb48c5FRcH1XyhbbA4IScdDswr0x4Vhbytbbdvv1LidYqi0FTvnU3VabmRU/YSaY8CJolZrVaLRqN5YP7atWs4O1esciaS/CiKwkZ9IL5EIpEUzpPAaaCnfqwFFgG9gKsWsqkcURRo2ghq58mfuHAFblWckItWz7Si6xzRjVOn0RG0Pohq8UKAT+8P+xroT5wwAa6UXFDl4lnDiqEdxdNXHfDdzlQyskz3FNZxdmZ+9+6G60356y/heez0Nti6iZPO/R/cOmnyHhWFsrS29c3TCUyGGpQMk8Rs3759+eyzzwxjRVFISUlhwYIFDBxY8qw9iXmJi4tj8uTJeHt7Y2tri6enJ4MHD64woR86nY63336bOnXqYG9vT2BgIBEREZY2SyKRFEo9YAfwDpCbhLkP0Qp3g6WMKj8UBfy8oE4N49zFKIirOJ0ue73TC98nRactbbKWSRsnYZthSw5anh5ny3VnIDFRNFTIyCj19fu1taNJHfHY+26ylrUHyiauXn/8cZpUE4J7X2wsv5w7B/bVoNN8/Rk62DNDeMMrMWVpbeuXp3lCeKbsBFYSTBKzH3/8MQcOHKB58+ZkZGTwzDPPGEIMFi9ebG4bJSUgOjoaf39/du7cyUcffURYWBhbt24lICCA4OBgS5sHwIcffsiyZcv46quvOHLkCI6OjvTr148ME/7ASiSS8kKNaK6wF2ion7sHDEdUOqjiH7aKAj4NoW5N41x4NNy4YzGT8qJSqxj+03BqthD2qa6qeGXLKyhahdvWmYyYYEemGjhxQrS8Le31VQov9HLEVnS7Zf+FTE5Fmf7o29bKiiX9+hnGs7ZvJy07W4QauOkfzV/dBVc2m7xHRSFv3GxpuoH55fHMhkvPbIkwScx6enpy+vRp5s6dy7Rp02jXrh0ffPABJ0+epFatWua2UVICXnvtNRRF4ejRo4wYMQJfX19atGjB9OnTOXz4cKHrZs+eja+vLw4ODnh7ezN//vx81QNOnz5NQEAAzs7OuLi44O/vz7FjxwBR1WLw4MG4u7vj6OhIixYt2LJlS4H76HQ6PvvsM+bNm8fQoUNp3bo133//PTdu3JBhDxJJpaALcAp4Os/cl0BH4JwlDCo/FAWaNIB6eT7fImLg+m3L2ZQHWxdbxmwag301IYKqnanG8H3DAThSI4MpT+q96l9/DT/+WOrr13RVM7qro2H8/e5UktNK/tj8nwzy8aF/kyYAXE1OZvH+/WBlK5LBctkzEzSVu5JNnz7GuNnSiFl3tTW11eLbw6WsdDSV3EtdHpRazGZnZ9O4cWMiIiIYO3YsH374IStWrGDixIn5KhtIyo+EhAS2bt1KcHAwjo6ODxx3c3MrdK2zszOrV6/m/PnzLF26lJUrV7JkyRLD8bFjx1K/fn1CQ0M5fvw4c+bMwdpa/CMLDg4mMzOTvXv3EhYWxuLFiwutMRwVFUVcXByBgcaWha6urjz++OMcOnTIxDuXSCTlixvwC/ANkPv3/izQQT9XhT90FQUae4Knh3Hucixci7OcTXlw93Zn5LqRKGpRBabVrla0D2sPwDftNPz3Mf2Jr7wC50r/5aNbMxvaeIm//ffTdfywJ9XkTHtFUVjSrx9W+pa7Hx48SExiIvgMh3rdxEn3LsGZr026fkXBy8sNHx8RUnHo0DWSkzNLvNZXH2qQodNyNbvk6x5VSl0F2dra+pF7LNy+/TfExaWU+74eHk4cO/ZyseddvnwZnU5H06ZNS73HvHnGzFEvLy9mzpzJmjVreOONNwCIjY1l1qxZhmv7+PgYzo+NjWXEiBG0atUKAG9vbwojLk78wa9du3a++dq1axuOSSSSyoACvAR0BUYjxGw68AqwHSFq3S1m3UNFUaBRPfHfWH0MZOQ10OqggeWL2zcKaMSAZQPYEiyekD256Uni3OK45nmN4MEqWt/S0vF6GowYAaGhUIqEbUVRGN/TkYVrk7ifruNUVDYHL2bRtZmtSbY2rVGDKR078unhw2Tk5DBr+3Z+GTkSenwC/3tcnHRwITR7FuzcTNqjItC3b2MiIhLIydGye3c0Q4aUrLVtUxt79qWJ5h3hWWl42dg9TDMrPSaFGQQHB7N48WJyTCjGXBmJi0vh+vX75f4qqYAuSx26tWvX0rVrVzw8PHBycmLevHnExsYajk+fPp2JEycSGBjIBx98QGSk8VHJlClTeOedd+jatSsLFizgzJkzJtshkUgqG82Bo4i42VzWIWrSHrCEQeVDrqBtmKezVtR1iLlhOZvy0OG1Dvi/6i8G2fDC+hdwSXIhS9EyYqw1tx2B8HB4+eVSJ1m5OKgY18P49G/N/lTuJj9Y2aikvN2jB7X0TxN/PX+e3dHRUKcjNH1GnJARD0feNfn6FYH8JbpKEzebJwlMxs0Wi0liNjQ0lN9++40GDRrQr18/hg8fnu9V1fDwcKJePedyf3l4lKytn4+PD4qicPHixVLd16FDhxg7diwDBw5k8+bNnDx5krlz55KVZQzuX7hwIefOnWPQoEHs3LmT5s2bs2GDyGKeOHEiV65cYdy4cYSFhdG+fXs+//zzQt5D8Wju1q1b+eZv3bplOCaRSCob9sBy4DeM3thYoAeiAoLpQqfC41VXiNpcom8IUVsB4hsHLBuAV08vAFSJKib+NhHrLGuuOWQzKkhNtgpYswZWrCj1tdt529ClqagVm5EtynVptabds6udHe/16mUYv751KzlaLTzxHqj1Ht+TyyApyqTrVwR69vTCykpIrb//Lnl5tLzluWRFg+JRdCa49Z5//vkij3/33XcmG/SwKarXb0ZGBlFRUTRq1Ag7u8rl0h8wYABhYWGEh4c/EDebmJhoiJtVFIUNGzYwbNgwPvnkE1asWJHP2zpx4kTWrVtHYmJigfuMGTOG1NRUNhVQhPvNN9/kzz//LNBDq9PpqFu3LjNnzmTGjBmA+F3UqlWL1atXExQU9MCayvz7kEgePa4CYxGlu3LpCfyIKPFVRbkaB1euGceeHsZQBAuSdjeNlR1XkhiVCEBk20h+GPoDKDD1ECzZBlhbw/790LFjqa6dnqVj0dok4u+LJLCnO9vTr51pOTNanY6OK1dy/KYI21gxcCD/6tAB9r0FR98XJ/mOgsFrTbp+RaB79+/Yt0888YyKeh0vL7cSrXv2+gWu52Rhoyj86dkKq0esK2ZReu2flMozq9VqWbx4MZcuXeLs2bPUqlWLFStW8N133+V7Scqf5cuXo9Fo6NixI+vXryciIoILFy6wbNkyOnfuXOAaHx8fYmNjWbNmDZGRkSxbtszgdQVIT09n0qRJ7N69m5iYGA4cOEBoaCjNmjUDYOrUqWzbto2oqChOnDjBrl27DMf+iaIoTJ06lXfeeYdNmzYRFhbG+PHjqVu3LsOGDTP7+yGRSMobT2AnoktY7kfLbkRN2j8sY1J54OkBTTyN41xxa2EPrUMNB8ZsGoONk/CiNj7VmJ77ewLwWWf4XysgO1vUn40vXSMIexuF53s5kiutNh5J51q8aWGHKkVh2YABhvG8XbtISE+HjnPAQV894tIvcP2gSdevCJQ11CBLpyM6+9HKVSotpRKz7777Lm+99RZOTk7Uq1ePZcuWVZgapo863t7enDhxgoCAAGbMmEHLli3p06cPISEhfPnllwWuGTJkCNOmTWPSpEm0bduWgwcPMn/+fMNxtVpNfHw848ePx9fXl1GjRjFgwAAWLVoEgEajITg4mGbNmtG/f398fX1ZUcRjqzfeeIPJkyfz8ssv06FDB1JSUti6dav0ukokVQYrYAGwC6ivn4sHhgCvA1X0A7lebfBpYBxfuwWRVy0uaGu1rMXwn4aTqzp7hvSk6QWRzDtxmIrTtYHYWBg/HrSlK7XlV8+aPm3E3+4cLazakUq2xrT77eLpyTP6ROKE9HQW7NoFti7QZZHxpErcSKFPn7z1ZkseauBnmzfUQMbNFkWpwgx8fHyYOXMmr7zyCgA7duxg0KBBpKeno1KZFH5b7lTVMIOqiPx9SCSVmXhgIrAxz1wbYA1Q+sorlYKbd+FStHFcp6YQuRZ+PLzv/X3sfGsnAFo7LV8/9zW3PG7RKEnFsa+0VEsH3n0X3nqrVNfNztHx7rpkrieI2Oj+7ewY0dmhmFUFcy05Gb8vviAtOxu1onDq1VdpWaMafN8G4s+LkwatgaajTbq+JdFotNSo8RGJiRm4u9tx584s1OriNdPpjBSm3hKe3MFO1ZlevX4xK6oWDy3MIDY2Nl+72sDAQBRF4caNipHFKZFIJJKKQnVEYthyILd802nAH/iWKlmTtk4N0f42l5t34FKMxT2K3eZ0o+WYlgCoMlRM+HUCDqkORLlqeWYEaBRg/nzYubNU17W2Ungh0JFcXbbtZAYRN01rdFDfxYW3uokasxqdjte3bkWnqKHHx8aT9s2BnMrn3Te1ta2Pjb0hlENWNCiaUonZnJycBzxk1tbW+TpGSSQSiUQiUBClu0KB3Hj6NOBF4BkgyUJ2PUQ8akDTRsZx3F3R/taCglZRFIasGkLd9qKcmEO8A2PXjUWdo2ZbE3g7ABFmMGYMlNI51aCGFUM7isfhOuDbkFQysky71xldutBIn6y8MyqKDRcvgld/aNhHnJAcDSeWmXRtS2NKa1sHlZoG1uKL4JWsDLJ0pnddq+qUSszqdDqee+65fGW4MjIyePXVV6t0aS6JRCKRlIVWwDFEs4Vc1gDtgCMWseihUrs6NPc2hhfciocLURYVtNb21ozeOBqnOqLkY72oegz8ayDo4L3usKEpcPs2BAVBKWvI92trRxMP0YPpbrKWXw6Y5kW0s7Lik759DeMZf/9Nek6O3jurfy+PvAtpd0y6viUxtbVtbhJYDjquZFU+r3R5USoxO2HCBGrVqoWrq6vh9eyzz1K3bt18cxKJRCKR5McB0R3sFyD3cyIK6AYsBqqY16lmtfyC9k4CnL9S6kQrc+JSz4XRG0ajtlUD4H/cn45HRVmu8cMVLtQA9u2DuXNLdV2VSuH53o7Y6nuK7ruQyenorKIXFcKwpk3p3Uh4tqMTE/nk0CGo2RpavShOyEqGQ4uKuELFxMvLDV/f6kDpWtv65a03K0MNCsWkOrOVGZkAVnmQvw+JpKoSjQgzOJRnLhD4HrB8W1izEp8I5yKNXtnqbkLkWjBp+syPZ9gwTpRh1Kl0fP/s90R5R+F3F46uBJdMYONGGDq0VNfdez6DH3YLweVsr7AoyBVn+9Lf57nbt2nz1VdodDocrK0JnzSJ+uo0WNUEslNBUcOEMKhecCnIisrkyVv44otQAH7/PahErW3PZaYyKe4yAP0d3Zldo0ExK6oODy0BTCKRSCSSsuMF7AXmYnh8zA5EtYO/LGTTQ6K6G7RsAir9feaKWwt6aFs/25oub3QBQNEqjFk3hmrx1QivAROGgVYBJkyAKyUvIwXwRDNbWje0BuB+uo4fdqea1G69Ra1avNahAwBp2dnM3rEDHD2gw2xxgk4De98o9XUtjSmhBo2t7Q1C7VKW7ARWGFLMSiQSicQCWCFa3u7A6I29AwwEZgCmPaaukFRzhZY+Rm9sQhKcvQwaywna3u/1xmeQDwA2aTaMXTsW2wxbNjaD97sBSUnw9NOQUfI4TUVRGB/giJOdEO4no7I5FG7a73FRz55UtxeP2P8XFsaB2FhoPwOc9N3krmyGmBCTrm0p8re2LZmYtVOpaGQtnkxGZ2eQYcEvQRUZKWYlEolEYkF6AWeAJ/PMfQp0ASIsYtFDwd0FWuURtPeS4WwEaDQWMUelVjHifyOo0awGANVvV2fE+hEoWoX5veCvJsDJkzB1aqmu6+qgYlwPY0v1n/elcje59Pfobm/PO716GcZTtm5Fo7aDbu8ZT9ozA7SWef9MwcXFls6dRa3YiIgEoqMTS7TOz1YkgWmBCOmdLRApZiUSiURiYWoAm4DPABv93HHgMeAHC9n0EHBzhta+GAqzJt6HsAjIsYwgs3WxZcymMdi5C8+fb4QvvUN6o1Pgmach0h34+mv4oXS/g8ca29DZT/weM7Lhu52paE0IN3jpscdoXbs2ACdu3uS7U6eg+bNQ6zFxwp3TcP77Ul/XkpjS2lYmgRWPFLOPGIqisHHjRkubIZFIJP9AQbS8PQz46udSgPHAOOC+hewyM65OekErKgqQlAJhl0pdDstcVGtSjVHrRqGoRWhAtwPdaH26NYl28FQQpFoDr74KZ8+W6rpB3Ryo5iQkxqUbOew4XfqyUmqVimX9+xvGb4WEkJiZBT0/MZ60f65ICqsk5BWzJW1tm1ueC2TcbGFIMVuFiIuLY/LkyXh7e2Nra4unpyeDBw8mJKRixBX99ttv9O3bl+rVq6MoCqdOnbK0SRKJpMLRDuGVfT7P3I8IL+1xi1hkdlycoI0vWOkFbXIqnImAbMsI2ka9GtF/qVE0Dv1jKPWu1SOsNrw0BHRpaSJ+9n7Jv1A42Kp4obejIb1vw+F0rseX/v56eHkxsnlzAO6kpfHvPXvAsyc01ldaSL0JoR+V+rqWwt+/Du56T/iOHVfQlCBuupGNHdb6d/JipvTMFoQUs1WE6Oho/P392blzJx999BFhYWFs3bqVgIAAgoODLW0eAKmpqXTr1o3Fixdb2hSJRFKhcUK0vP0f4Kyfuwx0Bj6hStSkdXaENn5grS/Oej8VzlyymKDt8FoH/F/xB0Cdo2bM2jE4Jzvzcyv4rBMQHg4vvVSqxg9+9awJbCOEW44W/rsjlRxN6cMNPurTBzsr8T59fvQoF+7cge4fgkr/3oV+BCml61xmKdRqFb17i25giYkZHDtWvN02igpvG/E+Xs3JJLUSxQmXF1LMVhFee+01FEXh6NGjjBgxAl9fX1q0aMH06dM5fPhwoetmz56Nr68vDg4OeHt7M3/+/HztiU+fPk1AQADOzs64uLjg7+/PsWPHAIiJiWHw4MG4u7vj6OhIixYt2LJlS6F7jRs3jrfffpvAwEDz3bhEIqnCjAFOAh3042xgJjAIuG0po8yHk0N+QZuSBqfDIav8W8QrisKAZQNo2L2hMO2+E0FrgrDKtmJWX9jlBaxdCytWlOq6Tz1uT91qwgN9LV7DptDSPyZv6ObG7K5dAcjRapm2bRs6dx9o85o4IScN9s8r9XUthSmtbfOGGsgksAeRYrYKkJCQwNatWwkODsbR0fGB4276XtcF4ezszOrVqzl//jxLly5l5cqVLFmyxHB87Nix1K9fn9DQUI4fP86cOXOwthZ1BIODg8nMzGTv3r2EhYWxePFinJyczH5/EonkUaYxsB/IW1d0K9Aa2G4Ri8yKoz209QMb8XeV1HSLCVq1jZpR60fh5uUGQL0b9Rj6+1A0CoweCVddgGnT4OjREl/T2krhxd6Ohpy3rSczuHyz9Pf2RteueOoL52+LjGTzpUvQ+W2wFbZybjXcPlXq61qCvPVmt28vYdysrTEJTIYaPIiVpQ2oDLxy8xIJmvJ/9FNNbcXXdXyLPe/y5cvodDqaNm1a6j3mzTN+m/Xy8mLmzJmsWbOGN94QHxyxsbHMmjXLcG0fHx/D+bGxsYwYMYJWrVoB4O3tjUQikZgfG0TL296IhLBb+ldfhMh9B7C2mHVlxsFeeGjPhENmNqRlCEHb2hdsbYpfb05TajgQtCmIVZ1XkZ2aTauzrbhd6zb7uu9j+GjY9102diNHwokTUL16ia7ZoKYVgzvYs/FIOjodfBuSytujXbGzVopfnGuXtTUf9+3L6HXrAJi2bRt9X3sN207zYM9MQCdKdT29w9hCuIKS29r20qV4Q2tbFxfbItfk9czKigYPIj2zJSBBk8NdTXa5v0oqoMvSkXjt2rV07doVDw8PnJycmDdvHrGxsYbj06dPZ+LEiQQGBvLBBx8QGWl8JDJlyhTeeecdunbtyoIFCzhz5ozJdkgkEknx9AVOA/3yzH0IdANK162qwuFgB22aGsVrrqDNKP/mEbVb1Wb4j8MN4947e+N30Y9j9SB4IOhiY2HcuFJ1Mevfzo7GtYX/7E6yll8PlF6QjWzenB4NRRhE5L17LD1yBNpOAle9IyV2J1z5s9TXtQS5oQY5OVp2744u9nwvazts9SJdVjR4EClmS0A1tRU11Nbl/qqmLpnj3MfHB0VRuHjxYqnu69ChQ4wdO5aBAweyefNmTp48ydy5c8nKMv7xXLhwIefOnWPQoEHs3LmT5s2bs2GD6Ok9ceJErly5wrhx4wgLC6N9+/Z8/vnnpbJBIpFISkdtYAvwMUZv7FFEFYQ1ljLKPNjbipADO72gTc+E0xchI7PcTWk6rCkB7wQYxsN/G06tW7X49jH4xh/46y94//0SX0+tUngh0BFb/cfa3vOZnIkunVBXFIWl/fuj0ou6/+zdy830LOieJ6l47yzQlH+IRmnJX6Kr+LhZtaLQRF9v9kZOFskWeFpckVF0ZXHrVUKSk5NxdXUlKSkJF338TS4ZGRlERUXRqFEj7OzsLGShaQwYMICwsDDCw8MfiJtNTEw0xM0qisKGDRsYNmwYn3zyCStWrMjnbZ04cSLr1q0jMTGxwH3GjBlDamoqmzZteuDYm2++yZ9//lmshzY6OppGjRpx8uRJ2rZtW+h5lfn3IZFIyoNjQBCQVww8D3wOPJg/UGnIyBIhB+l6EWtrI8IQ7It+FG1udDodvz3zG2fXiBqz99zusfKllWTbpbHnO+h8QwXbt0OeTl3FsedcBj/uEV5ZF3uFhUGuONuXzq/2r82b+eq4KNM2oU0bVg8dCmuegBsHxAm9voB2FaOKT2Hcv59JtWofkpOjxcenGpcuTS52zecJ1/nt/l0APqzlTQd752JWVG6K0mv/RHpmqwjLly9Ho9HQsWNH1q9fT0REBBcuXGDZsmV07ty5wDU+Pj7ExsayZs0aIiMjWbZsmcHrCpCens6kSZPYvXs3MTExHDhwgNDQUJo1awbA1KlT2bZtG1FRUZw4cYJdu3YZjhVEQkICp06d4vz58wCEh4dz6tQp4uLizPhOSCSSR4f2wAlgbJ657wB/4JQlDDIPdrniVf8lPjMLTl0UoQfliKIoDFk1hDr+dQBwT3Rn1C+j0KDi6VEQ56CFMWPgRsnLYnVvbkurBsKjnpyu48c9qaUOlftPr1646R0c/3f6NEeuX8/fSOHQQshMKtU1yxtn5/ytbaOi7hW7pqmMmy0UKWarCN7e3pw4cYKAgABmzJhBy5Yt6dOnDyEhIXz55ZcFrhkyZAjTpk1j0qRJtG3bloMHDzJ//nzDcbVaTXx8POPHj8fX15dRo0YxYMAAFi1aBIBGoyE4OJhmzZrRv39/fH19WVFE2ZZNmzbRrl07Bg0aBEBQUBDt2rXjq6++MuM7IZFIHi1cEE0VvsfojQ0HHgeWAZX04aOtjQg5cNAL2qxsEUObWr7xktYO1gRtDMLJQ1Sq8YrxYsBfA7jhAiNHQlb8bRg9GrJL9mhfURQm9HLEyU6ECpy4ks2h8NKFG9RwcODfPXsaxlO2bkXr0RGajhET6XfhyHuluqYlyN/atviY77wVDS5lyrjZvMgwgzzIx9oVC/n7kEgkpSMCEXZwIs/ckwhvbQ2LWFRmsrJFM4VcEWttJby2jvZFrzMz1w5fY3XP1WgyRcH+Pwf+SWjHUCYdgc//AmbNgg8/LPH1jkdm8dW2FADsbRQWjHahurO6xOuzNRrafv015+/cAWD10KFM8HaHb/1AkwlqG3j+Irg2KvlNljNHj17n8cf/C8DTTzfn119HFnm+Vqdj8NWzpOm01FRb80v95uVhpsWQYQYSiUQieQTxAQ4C0/PMbQbaALssYlGZsbEW4tVJ/4g5OwdOhYsGC+VI/U71GbxysGE8YOsAGl1pxBePw/dtgI8+gt9/L/H1/Bvb0MlXJLqlZ+n4bmcq2lL41qzVapb2N7bgnRMSwn1bD3hsqpjQZMG+N0t8PUtQ2ta2KkXBV58EdkeTTUIlSHQrL6SYlUgkEkkVwhbR8vZPoKZ+7gaiRu18oBJmgVtbQRtf0QIXICdHhBzcTy1XM9qMa0OXWV0AUGlVjPx1JO4J7rzyJJyoA0yYAFdKXiJtzBMOVHMSMiT8eg4hZ0pXtSHQ25th+hrocSkpvLN3Lzz+Jtjrf+/ha+HGoVJdszxRq1UEBpauta2fbZ64WRlqYECKWYlEIpFUQQYiatL21o91iOYK3YFoC9lUBqysoLUPuOQKWg2cvgTJKeVqRu/3e+MzUDTPcUh3YMzPY9BpbBk+Gu5mJ8HTT0NGyRLVHGxVPNfLWHXit8NpXE8o3ZeNT/r2xVYtwhOWHD5MREoOdFlkPGH3dKjA0ZSlLdGV65kFmQSWFylmJRKJRFJFqQP8DbwP5MZjHgLaAussZFMZsLKCVr7gqm8brtGIeNqk++VmgkqtYvj/hlOjmYhBrnWnFsN/G06si8KYEZBz+iS8/nqJr9esvjWBrUXJsRwNfLsjlRxNycWnt7s7M/QVe7K1Wqb//Te0fgmq6Svr3DwMl34t8fXKmz59jJ0z//67BElgsqJBgUgxK5FIJJIqjAqYA+wHvPRzScBI4BWgkgkCKzW08gE3fY1RjRbOREBi+QlaO1c7xmwag50+3tPvkh+9Q3qzozHM7QV88w388EOJr/dUJwfquAs5EntXwx/HSvf4/M0nnqCus3g/Nl+6xNYr0dDjY+MJ++ZATvmWNSspDRuK1rYAhw5dJTm56FCLulY2OKvEF7PwzPQydQCtSkgxK5FIJJJHgE6I2rOj88x9A3QAwixhkOmo1dCyCbjrM7y1WgiLgHvJ5WZCtSbVGPnrSBS1KLHV7UA3Wp1pxYfd4NfmwKuvwtmzJbqWjZXCi4FOqPWK5K8TGVy+WfLkJicbGz4MDDSMp27dSnaDvtBAP5cUBScrbnfK3Na2Go2u2Na2iqLgpw81uKfN4Y5MAgOkmJVIJBLJI4Mr8DOwCsh9XHse6Ah8SaWqSZsraKu5irFWC2cjIKH8mgV49/am35J+hvHQ34dS71o9nh8GZ53SRPzs/ZJ5jBvWtGJweyHSdDr4NiSVjOyS/z6eadWKLp6eAITHx/NFaKjeOyvENkfehbS7Jb5eeVL6uNm8oQYyCQykmJVIJBLJI4UCvIBohdtaP5cBvAaMABIsZJcJqFTQojFUdxNjrQ7OXob4xHIzoeOkjjz20mMAWGmsCFoThCrDmeGjITEmHCZOLHECVv/H7PCuLR6h30nW8uuBkoeAKIrCsv79c6UrC/fs4bZjE2j5vJjITIJDiwpdb0l69vTCykrIsZKI2ab5KhpUsjCZh4QUsxKJRCJ5BGkGHAEm55nbgKhJu88iFpmESgXNvaGGuxjrdHAuEu4W3x7VHCiKwsAvBtLgiQYAOKc4E7QmiCgXK8Y9Bdpff4Hly0t0LbVKhBvYWInx3vOZhMWUvDuYf926vNCuHQDJmZnMDQmBrv8Ba33FhNNfQvzFkt9cOeHsbEuXLsKrXJLWtn6yosEDSDH7iKEoChs3brS0GRKJRFIBsEO0vN0EVNfPXQN6AosAjWXMKi25grZWNTHW6eD8FbhTPl5mtY2aUetH4dpQhDzUu1GPIZuGsNkX/tMdmD4djhwp0bVquaoZ2cXoefy/XancTy+6mUBe3u3VCxdbUR1h1cmTHE8GOrwhDuo0sPeNEl+rPMmNm4XiW9vWVFvjrhKKPzxLJoGBFLNViri4OCZPnoy3tze2trZ4enoyePBgQkJCLG0a2dnZzJ49m1atWuHo6EjdunUZP348N24UXyRaIpFIHi6DETVpe+jHWmAh0Au4aiGbSomiQNNGUFsvynMF7e34ctnesaYjYzaNwdrRGoDWYa3ptr8bCwNgc6NsGDUK4ktmS48WtrRsIK6TlKbjp72pJRZstZ2ceLt7d0BEQL++dSs6/+ngVFeccOUPiK143eD69Cl53KyiKPjZCu/sfa2Gmzkl915XVaSYrSJER0fj7+/Pzp07+eijjwgLC2Pr1q0EBAQQHBxsafNIS0vjxIkTzJ8/nxMnTvDbb78RHh7OkCFDLG2aRCKRAPWAEODfGD8a9yJq0m60jEmlRVHAzws8ahjnLkRBXPkkPtVuXZunfnjKMO4d0hvfcF+eHQ4RKbEwbpxIVCsGRVGYEOCIo62IgD0emc2RSyUXbJMffxy/6kLUH7h6lZ/Do6Dbe8YTdk8HbcXyuudtbRsSElVsa9u89WYvylCDiiFmly9fjpeXF3Z2djz++OMcPXq0ROvWrFmDoigMGzbs4RpYCXjttddQFIWjR48yYsQIfH19adGiBdOnT+fw4cOFrps9eza+vr44ODjg7e3N/Pnzyc42lvo4ffo0AQEBODs74+Ligr+/P8eOHQMgJiaGwYMH4+7ujqOjIy1atGDLli0F7uPq6sr27dsZNWoUfn5+dOrUiS+++ILjx48TGxtr3jdDIpFITEKNaHm7F2ign0sAngKCgUqQOa4o4NsQ6tQ0zoVHw8075bJ9s6eaEfCfAGEKCiPWj8AmuSbDgiAl5C94//0SXcfNUcWzPYzdwf63L434+yUToDZqNUv6GassvLF9O6lNRkMtEU/LnVNwvuR1cMuD0ra2zStmL8mKBpYXs2vXrmX69OksWLCAEydO0KZNG/r168ft27eLXBcdHc3MmTN54oknysnSiktCQgJbt24lODgYR0fHB467ubkVutbZ2ZnVq1dz/vx5li5dysqVK1myZInh+NixY6lfvz6hoaEcP36cOXPmYG0tHv8EBweTmZnJ3r17CQsLY/HixTg5OZXY7qSkJBRFKdI+iUQiKX+6ImrSjsgztwJ4HFHKq4KjKODTAOrVMs5dioEbRX+umosn5j5Bi1EtALDNsmXMz2OIcrLnhaGge3s+lDD0rX0TGx73sQEgPUvHdztT0ZYw3GCAjw+DfETb3ev37/P+gYPQ4xPjCQfmQnZqKe7q4VOaEl25YQYgKxoAWFnagE8//ZSXXnqJ558X5TO++uor/vzzT7799lvmzJlT4BqNRsPYsWNZtGgR+/btIzExsdDrZ2Zmkplp7KiRnGxCUekf20NqXOnXlRVHD3j2WLGnXb58GZ1OR9OmTUu9xbx58ww/e3l5MXPmTNasWcMbb4gg+djYWGbNmmW4to/+j0PusREjRtCqVSsAvL29KSkZGRnMnj2bMWPG4OLiUmq7JRKJ5OHiDvyKaKwwFVG+KwxoDywFJmKoYVoRURRo7Cn+e+2WmIuIFeW76td+yFsrDP1uKAmXE7h54ibV7lVj1C+j+GHcD3zcScusZ56Bkyehbt1ir/VMdwcu3cjhXqqW8Os57DyTSWAbuxLZsaRfP/6OjCRbq+Xjgwd5oV0w3o2HQOQmSLkBxz6Bzm+X9XbNxj9b286f36PQc6upramptuaOJptLWelodTpUSgX+//EhY1HPbFZWFsePHycwT+cOlUpFYGAghw4dKnTdv//9b2rVqsWLL75Y7B7vv/8+rq6uhpenvqhyqUiNg5Tr5f8qoYAuSybj2rVr6dq1Kx4eHjg5OTFv3rx8j/2nT5/OxIkTCQwM5IMPPiAy0vhtccqUKbzzzjt07dqVBQsWcObMmRLtmZ2dzahRo9DpdHz55Zcm2y6RSCQPFwXR8vYY0EI/lw68jOgklmgZs0qKooB3ffD0MM5FXoWrD985Y+1gzeiNo3GsLZ4WNopuxIC/BjAnEHY43YbRoyG7+O5VDrYqnu9tfOK4/nAaNxJKFm7gU706Uzt1AiBTo2Hm339D9w9BXwmAo4uFqK0gNGzohp9fyVvb5pboStNpuZZT9LlVHYuK2bt376LRaKhdO/+3xNq1axMXV/A/tv3797Nq1SpWrlxZoj3efPNNkpKSDK+rV03ITHX0AKd65f9y9CjeNoS3VFEULl4sXf28Q4cOMXbsWAYOHMjmzZs5efIkc+fOJSvLGGi/cOFCzp07x6BBg9i5cyfNmzdnw4YNAEycOJErV64wbtw4wsLCaN++PZ9/XnTLwFwhGxMTw/bt26VXViKRVAJaAKHAq3nmfkUkhx20hEElR1GgUT1oWMc4d+UaxN586Fu7eroyesNo1DaiEUKHYx147Hh7gp6G6LP7Ye7cEl2nWX1rercW5bZyNLAqJIUcTcmcOPO6d6e2Pvxuw8WLhCRaQ2v97zEnDQ7ML+VdPVxyvbMajY5du6KKPNcvX/OERztu1uJhBqXh/v37jBs3jpUrV1KjRo3iFwC2trbY6mvOmUwJHvVbkmrVqtGvXz+WL1/OlClTHoibTUxMLDAu9eDBgzRs2JC5ef6gxMTEPHCer68vvr6+TJs2jTFjxvDdd9/x1FMiY9XT05NXX32VV199lTfffJOVK1cyefLkB64BRiEbERHBrl27qF69eoHnSSQSScXDHtHyNhARYpAIxADdETVp5yASyCogigJe9cR/o/WeyKjrIuTAq/hH/WXBs7MnT37zJL8/9zsAA/4awA817jJ8dDQHlnyEfZcuUIIk7uGdHDh/NZub97TE3tGw+Vg6wx53KHadi60tHwQG8vzvYv+p27Zxctx8rC78ILqCnf0O2k2BWm3KdJ/mom/fxnzxRSgg4maHDi08fNAvX1vbNPrg/tDtq6hY1DNbo0YN1Go1t27dyjd/69YtPDwe9EpGRkYSHR3N4MGDsbKywsrKiu+//55NmzZhZWWV7xH4o8by5cvRaDR07NiR9evXExERwYULF1i2bBmdO3cucI2Pjw+xsbGsWbOGyMhIli1bZvC6AqSnpzNp0iR2795NTEwMBw4cIDQ0lGbNmgEwdepUtm3bRlRUFCdOnGDXrl2GY/8kOzubp59+mmPHjvHTTz+h0WiIi4sjLi4unydYIpFIKjYjEDVpu+nHGmAe0AeoOI+sC6RhXeGlzSXmhhC1D7noftsJbek8Q3wOqbVqRv0yimhbd159EnTPTYASfHbbWCm82NsJtV61bDmRQWRcTon2H9+mDR3rifs+e/s2X52Phsdz80V0sGfGQ38PSkre1rbFNU/wzdMJ7FEvz2VRMWtjY4O/v3++ov5arZaQkJACBVjTpk0JCwvj1KlThteQIUMICAjg1KlTpsXDVhG8vb05ceIEAQEBzJgxg5YtW9KnTx9CQkIKjUsdMmQI06ZNY9KkSbRt25aDBw8yf77xkYtarSY+Pp7x48fj6+vLqFGjGDBgAIsWif7WGo2G4OBgmjVrRv/+/fH19WXFihUF7nX9+nU2bdrEtWvXaNu2LXXq1DG8Dh6s4I/pJBKJJB8NgF3A2xg/RncBrYHNljKqZDSoIxLDcom9WS6CNnBxIE0GNAHAId2BMT+PYW1TW1b4JsPIkZCRUew1Gtay4sn2QsDpdPBtSAqZ2cXbrVIUlvbvbxi/vWsX8X4TwbWRmIgNgaiCy0qWN6VpbeuqtqKulaj2cDkrHU0FEeSWQNFZuA/a2rVrmTBhAl9//TUdO3bks88+45dffuHixYvUrl2b8ePHU69ePd4vpDbdc889R2JiYolbtCYnJ+Pq6kpSUtID8ZoZGRlERUXRqFEj7OxKli0peXjI34dEIqn47AHGAtfzzL0OLAbKGOL2MLl+Gy7nqfFdr5ax+sFDIiMpg/8+/l/iw0UnsHDfcH4dtYZd3+vo1v9l+PrrYq+h0epYvCGZqFsiCaxnC1vG9nAsZpVg/IYN/KBPVP5X+/asaJIGm0eJg9WawYQzxuQwC/Luu3uZN090Kfv66yd5+WX/Qs9ddCea3WlJAKyq44t3Hm9tZacovfZPLF5ndvTo0Xz88ce8/fbbtG3bllOnTrF161ZDUlhsbCw3bz78QHWJRCKRSEpPD0TYQd5uhkuBTkC4RSwqEfVqgU9D4zhX3D5E/5adqx1j/hiDnZtwTvhd8qPH7l6MHAk3fv4Gvv++2GuoVQov9HbCRq85d5/LJCymZKFqHwQG4qivk/718eOcdukGdbuIgwkX4EzJEssfNqWqNys7gQEVwDNb3kjPbOVB/j4kEknlQYdorDADyC2T5Ah8AUygwtakjbsrOoTlUqeGELkP0UMbuT2Snwb8hE5fkWD98PU4uYexe40dNoeOgr52eVHsOpvB//YK8ebqoLAwyBUnu+L9cx/s38+b+tDGHg0bsquPH8oavaC1rwEvXgZbVxPvzDxoNFpq1fqYhIR03NzsuHNnliGO9p+czEhh+i0heIc4VWda9frlaepDpVJ5ZiUSiUQiqfwoiJa3R4DcDPRU4HlEGIIJDXvKA48a0LSRcXxTL24fop+rcZ/G9PvU2G52yKYhxKjq8nrPDHj6abh/v9hr9GxhSwtP4WVNStPx4560EtVcn9apE43dRdb/npgY1iW6gN9ocTD9LhwpWbvdh4laraJ3b/E7Ka61bd4ksEuPsGdWilmJRCKRSMxGG0SThYl55n4G2gFHLWJRsdSuDs3ydHC8FQ8Xox6qoO04uSPtXmwHgHWONUFrgvjJz5lvHS/BxInF7q0oCs/1csTRVniQj0dmcSSi+HADWysrPu1nFNIzt28nrdM7oNbHN5/4DJKiTbonc5I31GD79sJDDRxVajythO2RWRlk67QP3baKiBSzEolEIpGYFUdgJbAGyH08egXoCnwIVEDBUasaNG9sDC+4nQAXroD24diqKAqDVgyiQbcGALjcd2H02tFM6WtF6P5fYPnyYq/h5qhibA9jzOj/9qaRcL/47mCDfX3p21iIxdikJD46ew0ee10c1GTCvjdNuCPz8s/WtkXhZyu8s9nouJJVfFWIqogUsxKJRCKRPBRGA6cQyWAAOcBsoD/w8FvKlpqa7vkF7Z17D1XQqm3UjFo/CtcGIka1/vX69NsyhBGj4Pa8aXDkSLHX6NDElo4+ojxVepaO1btS0ZbAq/tZv35YqYQEWnzgALFNJ4mYWYDwNXCz+L0fJqVpbZu/ecKj2QlMilmJRCKRSB4ajYC9wFsYk8C2I8IRtlnKqMKp4QYtmhgF7d1EOB/50AStYy1HgjYFYe0g4l9bh7WmwdmujB6WQ86opyE+vthrPPOEA26Owt4L13LYFVa48MulWc2aTOrQAYD0nBze2HsEuiwynrB7usUbKeSGGhTX2vafncAeRaSYlUgkEonkoWINvIsQsXX0c7cRHtpZQAXrgljdFVo2AZVe0MYnwdnLoHk4gtajjQdP/fCUYRy4I5AbWb7MbnoNnn22WCHtaKfi+V5OhvH6Q2ncTCg+3GBBz57UdBBCcO25c+x17Q/V9Ml7Nw7CpXUm3I35KGmJriY2dgYxF54pxaxEIpFIJJKHRm9ETdqBeeY+RsTSXraIRYVSzRVa+oD+UTz3kuFsBGiKF4mm0Gx4M3ou6gmAgsKI9SP4oUlNfr62Fd57r9j1zT2t6dVKJEJla2BVSAo5mqI9q252drzbq5dhPGXb32i6fWg8Yd9syCney/uw6NGjoaEkV1Fxs/YqNV7WonxlVHYGmQ/Ji16RkWL2EUNRlBJ3S5NIJBKJuamJaHm7BOGxBVH9oB3wk6WMKhh3F2jlA2q9VEi8D2GXH5qg7T6/O81HNgfANsuWMT+PIbiPPWeWvw152t4XxvBODni4CVtj7mj483jx8aMvtGtHOw8PAE7fusV/k+pAg97iYFIUnPrCxLspO3lb216+XHRr29wSXVrgcvajFzcrxWwVIi4ujsmTJ+Pt7Y2trS2enp4MHjyYkBL8ESgPFi5cSNOmTXF0dMTd3Z3AwECOlCDAXyKRSKoWCjAVOAz46OdSgGcRDRaKr7Nabrg5QytfUKvFOOk+nImAHPMLWkVRGPrdUDzaCXFZ7V41hmwYxfARCveeD4Lr14tcb2stuoPlRkdsOZ7BlVs5Ra5Rq1Qs7d/fMJ67cyf3Or2PIb758H8g7a7J91RW+vY1VjXYvr1w76yfbZ642Ucw1ECK2SpCdHQ0/v7+7Ny5k48++oiwsDC2bt1KQEAAwcHBljYPAF9fX7744gvCwsLYv38/Xl5e9O3blzt37ljaNIlEIrEAjwEnEAI2l+8Bf+C4RSwqEFcnaO0LVnpBm5wCZy5BTtFC0RRsHG0I2hiEQy0hzhpFN8LvaH/Gdr+LJmg0ZGcXub5RbSuebK/3Uupg1Y4UMrOLDjd4omFDglq2BCA+PZ2FZ+9Ci+fEwcwkOPzvst1UGShp3GzTR7yigRSzVYTXXnsNRVE4evQoI0aMwNfXlxYtWjB9+nQOHz5c6LrZs2fj6+uLg4MD3t7ezJ8/n+w8fyxOnz5NQEAAzs7OuLi44O/vz7FjxwCIiYlh8ODBuLu74+joSIsWLdiyZUuhez3zzDMEBgbi7e1NixYt+PTTT0lOTubMmTPmeyMkEomkUuEErAZ+BJz1cxFAZ0QoQgXpOO/iCK39jIL2fqoQtNnmF7SuDVwJ2hCEykZIlI6hHbmd5M9C6wPw1lvFrh/ob0ejWsLO20la1h0q3lP5YWAg9lZWACwPDeVc0+lgpReIp7+EhEsm3k3ZeOyxOlSrJsR5SEgUOTkFx8N629hhpfcmP4oVDaSYrQIkJCSwdetWgoODcXR0fOC4m5tboWudnZ1ZvXo158+fZ+nSpaxcuZIlS5YYjo8dO5b69esTGhrK8ePHmTNnDtbWIs4rODiYzMxM9u7dS1hYGIsXL8bJyamwrfKRlZXFN998g6urK23atCndDUskEkmVYyxwEmivH2cD04EnEZUPKgDODtDGD6yF6ON+GpwJL9ZbagqeXTx58qsnDeOBWwbyYwMvNm7+GIrJ+1CrFF4IdMJGb+bus5mcjS26YoSnqytvdusGgEanY+q+k+javyEOanNg7xsm30tZUKtVBAaKUIOiWtvaKCoa2YgksNjsTNK0DyeuuaJiZWkDKgPv/JpEUlr5Zwe6OqiYN9K12PMuX76MTqejadOmxZ77T+bNm2f42cvLi5kzZ7JmzRreeEP8w42NjWXWrFmGa/v4+BjOj42NZcSIEbRq1QoAb+887RALYfPmzQQFBZGWlkadOnXYvn07NWrUKLXdEolEUvVoDBwA5gEf6ee2IGrS/oiohmBhnPSC9nS48MqmpMPpSyIMwca6+PWloN3z7bgddpvDSw6j1qoZ9csoJj33DU2njaNpq1PQuHGhaz3c1Dzd2YH/7RNeytU7U1kUZIWjXeE+vJlduvDtqVNEJyay48oVfm83lGFO30DKDYj8Ha7uBs+eZr3HktC3rze//HIOEKEGnTrVL/C8pjYORGSlowMistJpY1cy51JVQHpmS0BSmpbEVF25v0oqoHVlKOy8du1aunbtioeHB05OTsybN4/Y2FjD8enTpzNx4kQCAwP54IMPiIw0xuxMmTKFd955h65du7JgwYIShQsEBARw6tQpDh48SP/+/Rk1ahS3b1cQr4NEIpFYHBtEy9utQC39XBzQB3gT4bG1MI720LapUbympgtxm2n+erl9PuxD435CtDqkOzBk/RhG9skiOegpSC86NrRnS1uaewqfXVKajp/2Fv343d7amo/79DGMp4fsIaPTf4wn7J4BuvJ3bPXpU7K4WT99RQN49OJmpZgtAa4OKtwclXJ/uTqU7Nfj4+ODoihcvHixVPd16NAhxo4dy8CBA9m8eTMnT55k7ty5ZGUZ/yAtXLiQc+fOMWjQIHbu3Enz5s3ZsGEDABMnTuTKlSuMGzeOsLAw2rdvz+eff17kno6OjjRp0oROnTqxatUqrKysWLVqVanslkgkkqpPP0RN2r76sQ74AHgCKLwbVLnhYAdt/cBWtJIlLeOhCFqVlYqn1zxNNd9qANS+XZuWe4fznPdZdK9PKXKtoig8F+CEg62IJQ29nMWRiKLrxg5v1owALy8AohIT+TSpMdRsKw7ePgHnfyzT/ZhCgwauhta2hw9fK7S17aNc0UDRlcWtVwlJTk7G1dWVpKQkXFxc8h3LyMggKiqKRo0aYWdnZyELTWPAgAGEhYURHh7+QNxsYmKiIW5WURQ2bNjAsGHD+OSTT1ixYkU+b+vEiRNZt24diYmJBe4zZswYUlNT2bRp0wPH3nzzTf78889SJXQ1btyYcePGsXDhwgeOVebfh0QikZgHLfAJoh1ubrKVC/ANMNpSRhlJz8wvYu1soY2v+K8Zib8Uz9cdviY7WXim9z6xl0DdTt586f9g/Pgi1x6NyGTl9lQAHGwVFox2pZpT4c6isFu3aPv112h1OhytrQl/qh31tugbXTjVgxcugbVDoesfBlOm/MXnnx8FYOPG0Qwd+mBYYY5Ox6CrYWTpdNSzsuHHes3K1UZzU5Re+yfSM1tFWL58ORqNho4dO7J+/XoiIiK4cOECy5Yto3PnzgWu8fHxITY2ljVr1hAZGcmyZcsMXleA9PR0Jk2axO7du4mJieHAgQOEhobSrJn4BzJ16lS2bdtGVFQUJ06cYNeuXYZj/yQ1NZW33nqLw4cPExMTw/Hjx3nhhRe4fv06I0eONP8bIpFIJFUCFaLl7UEgNy8hGQgCJgKpFrJLj72t8NDmitcMvbhNN2/nrOq+1Rn962iDaum+rzv/q92SbYtfgrCwItd29LGlQxPhQU7L1PF/O1PQFuHHa1W7Nv9qLxLxUrOzmXMxA7z1yWgp1+HYJ2W/oVJSkhJdVopCE2sRanA9J4v7GvNXmqioSDFbRfD29ubEiRMEBAQwY8YMWrZsSZ8+fQgJCeHLL78scM2QIUOYNm0akyZNom3bthw8eJD58+cbjqvVauLj4xk/fjy+vr6MGjWKAQMGsGjRIgA0Gg3BwcE0a9aM/v374+vry4oVKwrcS61Wc/HiRUPZsMGDBxMfH8++ffto0aKF+d8QiUQiqVJ0QFQ7eCbP3CpE9YPTFrHIgJ1e0NrnCtosvaDNMOs2jfs2pt8n/Qzjob8P5fX2NbgyYQjcL7rRxNjuDrg5inCD89dy2BVWtNj+d0AA1eyFMPzxzBkO+cwGRV+WLHQxpNwsw52Unp49vbC2Lr61rZ+tMW720iMUNyvDDPIgH2tXLOTvQyKRSP6JDtFYIRijV9YG+BiYhKFzlSXIzBK1Z9P0ItbGWlQ+cDDf32+dTsemFzdx6rtTACQ7J7N/2DfsyuqLw8/rQCn8/s9fzWbJH0L0Wqth/ihX6rirCz1/RWgowfra6e3r1uVIo9OoTi8XB1u+CP3+a56bKiE9e65mz54YACIjp+Dt7f7AOdtSEvgg/ioAL7l58Ixr7XK10ZzIMAOJRCKRSKokCqJj2HGgnX4uC5gCDAPiLWMWiGSwNn6i2gFAVrbw0Kaaz0OoKAqDvhxE3c51AXC570LrnUG8nLEJXTEJyM09rQloJbzH2RrRHSxHU7g/72V/f1rVEhUljt24wWrnUWCjF1Vnv4U75dvwp0+fvK1tCw418HtEO4FJMSuRSCQSSaXDDzgETM0ztwlRk3a3BezRY2MtEsCc/iFoU8yXXW9la8WYDWOwryf2qH+9PmlRg1m6ZhocOVLk2hGdHPBwE9In5o6GLccLF3xWKhVL+/c3jN/cd5Qk/7n6kU5fqqv8Hm7nj5stONTA09oWO0Xc36NU0UCKWYlEIpFIKiW2iJa3m4Hc5jPXgV7A2xirH5Qz1tai9a2T3kuYnSMaK9w3n7hyqu3E+M3jUexFWEGbM21Y79iJPZMHQ3zh3mlba4UXejuh0kcj/Hk8g6hbhb9PAY0aMUKf2Hw7NZX/JLcEFy9xMHYHRP1llvspCXlb2+7cWXBrW7Wi4KuvN3tLk809TQWoS1wOSDErkUgkEkmlZhAiCayXfqwD/gP0BGIsY5K1lfDQOutLRebkiNa3yearvuDR1oOnf3jaMO69ow+z6rtx7YWnQVt4c4NGta0Y5C/ieLU6WBWSQmZ24R7Wj/v2xc5KNF9YGnqc8DaLjAf3zBTtbsuBkra2zRtq8KgkgUkxK5FIJBJJpacu8DfwLpCb1HQAaAust4xJVlaiza2Lvq1qjkYkiCWlmG2L5iOa031BdwAUFAL/fJrx1mfJfPffRa4b6G9Pw5rifbqVqGX94cK9xl5ubszq0gWAHK2WaRFqqNNJHEy4AGHllwjWt68xbrawEl15KxpcfERCDaSYlUgkEomkSqBGNFfYBzTUzyUCTwOvAhbw0lmpobUPuOoFrUYDYZcgqehSWqWh59s9aTxMxJPaZtnSauczTD74IezYUYRZCi8GOmGt1/27wjI5f7XwR/Kzu3alvj6j/q/Ll/nT+03jwQNvQ2Zy2W+kBJSkta30zEokEolEIqnkdAZOAaPyzH2NqFV7tvzNUauhlQ+4OYuxRgtnIiDRPAJQUSmM+nEULi2E2Kx2rxqZ4SP5+t8j4Pr1QtfVcVczorNR+H23M4XUjILDExxtbPioTx/DeFpoDFlN9O9v+h04+r4Z7qR4GjRwpWlTER99+PA1kpIerOVbz8oGx9wksCzpmZVIJBKJRFIpcQPWACuB3MfO5xCC9itEXG05olZDSx9w15e20moh7DLcM4+gtXG04YUtL6ByF7LGO8qbPzK6cvjlgZBduMc1oJUtzeqLeNjEVB0/7S1c/I1u0YInGjQAICIhgWXO40AtOotxfAkkl098cm6JLo1Gx65d0Q8cVxQFP1sh0uM1OdzJqfpJYFLMSiQSiURSJVEQLW+PA631cxnAvxChBwnla45aBS2bQHVXMdZqISwCEpLMcnnXBq5M+GMCOish1DuEPs68LGtuzX290DUqReG5Xk442IryBqGXszgaUXB3MEVRWNq/v6Etxb+PhBHXfKoYaDJh31tmuY/iyFuiq/B6s8a42UfBOyvF7COGoihs3LjR0mZIJBKJpNxoBhxBdA3L5TdEctj+8jVFpYLmjaGGmxjrdHD2MtxNNMvlG3RtwJNfPmkYd9k5kJfObiH7t18LXVPNScUz3Y3hBj/tTeNeSsHhBu3q1OGlxx4D4H5WFm+ltAe76uLgxf/BzaNmuIuiKUlr2/xxs1LMSioRcXFxTJ48GW9vb2xtbfH09GTw4MGEhIRY2rQHePXVV1EUhc8++8zSpkgkEskjgB3wBbARqKafuwr0AP4NaMrPFJUKmnlDTX07Vp0OzkfCnXtmuXz7ie1pFdwKALVWTdM9o3jjy2CILNiLCfC4jy0dmoiQgbRMHat3paArpCHCO7164WorOol9F3ae0GbzjAd3T3/ojRScnGzo0sUTgMuXE7hy5cH3LTfMAOBiZtVPApNitooQHR2Nv78/O3fu5KOPPiIsLIytW7cSEBBAcHBw8RcoRzZs2MDhw4epW7eupU2RSCSSR4yhiJq03fVjLbAA6A1cKz8zcgVtLb2wzhW0t80T+jDss2FU7y48po5pjmSeeZrvJ/WF9MKF3djuDrg5iiCC81dz2H224HCDmo6OLOzZ0zCecsUJrZufGNw4ABG/meUeiqK4UIPaamtcVaJUQ3hWWqHCvKogxWwV4bXXXkNRFI4ePcqIESPw9fWlRYsWTJ8+ncOHDxe6bvbs2fj6+uLg4IC3tzfz588nO0+w/OnTpwkICMDZ2RkXFxf8/f05duwYADExMQwePBh3d3ccHR1p0aIFW7ZsKdLO69evM3nyZH766Sesra3Nc/MSiUQiKQX1gZ3AIowyYA+iFe7v5WeGokDTRlC7unHuwhW4VXgHr5KislLx4sYXUXuK+6t9uzbbrnTgxIyxha5xtFMxIcDRMF53KI24ewV7rIM7dKBZDX1VgevX+anBHOPBvW9ATsFC2FwU19pWURSa6kMNkrUablXxTmBSzFYBEhIS2Lp1K8HBwTg6Oj5w3M3NrdC1zs7OrF69mvPnz7N06VJWrlzJkiVLDMfHjh1L/fr1CQ0N5fjx48yZM8cgQoODg8nMzGTv3r2EhYWxePFinJycCt1Lq9Uybtw4Zs2aRYsWLUy/YYlEIpGUETWi5e1uwFM/lwAMAyYjEsXKAUUBPy/wqGGcuxgFcXfLfGl7d3te3f4vtPZCkPpeasY7xxOJ/3Z5oWtaNrChZ0sRQpCVA9+GpKDRPujVtFar+ax/f8N49pl47tcNFIOkK3Cq8D3MQbt2HobWtiEhVwpsbeubJ9QgvIo3T7CytAGVgfbffENcivk6lpQUDycnjr38crHnXb58GZ1OR9OmTUu9x7x5xlgfLy8vZs6cyZo1a3jjjTcAiI2NZdasWYZr+/j4GM6PjY1lxIgRtGolYpO8vb0pisWLF2NlZcWUKVNKbadEIpFIHgZPIGrSTgQ26Oe+APYiSns1e/gmKAr4NgSVAjfuiLnwaNFrtm7NMl26hl8NgtaNYe2Ta1B0Ktoc7cFku6/4oX1X1K3bFrjm6c4OnL+aze0kLVG3NWw5nsHgDvYPnNe3cWOG+PmxKTycmykpvOf4HO8TAujg8H+gxQSwr/7gBmYgt7XtL7+cIykpk9DQ63Tu7JnvnLwVDS5mpdHD0e2h2FIRkJ7ZEhCXksL1+/fL/VVSAV2WWJi1a9fStWtXPDw8cHJyYt68ecTGxhqOT58+nYkTJxIYGMgHH3xAZJ4A+ilTpvDOO+/QtWtXFixYwJkzZwrd5/jx4yxdupTVq1ejKEqh50kkEomkvKmGaHn7JSJRDOAM0B5YRbnUpFUUaNIA6tUyzkXEwPXbZb50s4HN6PRuZ8PY++BQ5s8IguSCa9zaWovuYCr9R9XmY+lE3cop8NxP+/bFRi1iUz89E8Xlxi+KA5mJcKjolrplJW9r2+3bHww1yFvRILyKdwKTYrYEeDg5Uc/ZudxfHkU8ss+Lj48PiqJw8eLFUt3XoUOHGDt2LAMHDmTz5s2cPHmSuXPnkpWVZThn4cKFnDt3jkGDBrFz506aN2/Ohg3i2/vEiRO5cuUK48aNIywsjPbt2/P5558XuNe+ffu4ffs2DRo0wMrKCisrK2JiYpgxYwZeXl6lslsikUgk5kZBtLwNBZrr59IQHtsxgHlqwRZtggKNPaF+bePc5Vi4dqvMl+43px8ew4WX1zrHmoyjA1nzypBCKw9417ZioL8Q9lqdCDfIzH7w3MbVqjG9UycAsjQaZqR0ASu9iDy9AhIuldn2wiiutW0NK2tqqMUD+EuZaWircBKYoqvqKW7/IDk5GVdXV5KSknDR91nOJSMjg6ioKBo1aoSdnV0hV6iYDBgwgLCwMMLDwx+Im01MTDTEzSqKwoYNGxg2bBiffPIJK1asyOdtnThxIuvWrSMxMbHAfcaMGUNqaiqbNm164Nibb77Jn3/+WaCHNj4+nps3b+ab69evH+PGjeP555/Hz8/vgTWV+fchkUgklZc0YDqiBW4uXsDPQKeHv71OB9E3IDbPZ4Z3ffD0KNNlczJz+KDdO2guCJfrjbpXmTS1Fq1mvVfw+RodH/yWTMwdEXPbq5UtY554MC/lfmYmfl98wU3909Rtj+noe2mRONhkGAzd8MAac9Gs2XIuXryLWq0QH/8Grq75Pyvn3o7iYLrwQH9ftyme1rYPzRZzU5Re+yfSM1tFWL58ORqNho4dO7J+/XoiIiK4cOECy5Yto3PnzgWu8fHxITY2ljVr1hAZGcmyZcsMXleA9PR0Jk2axO7du4mJieHAgQOEhobSrJmIoZo6dSrbtm0jKiqKEydOsGvXLsOxf1K9enVatmyZ72VtbY2Hh0eBQlYikUgklsIB0fL2V0RbXIBooBvwPqKc10NEUaBRPWiYp3zjlWsQc6NMl7WyteL1nTPIdhPJbXVvePLxtxdI3Lu94PPVItzAWkQRsDMsk/NXH6wK4Gxry+LAQMN4akx1sh3qicHljXB1T5nsLorcUIPCWts2zRdqUHWTwKSYrSJ4e3tz4sQJAgICmDFjBi1btqRPnz6EhITw5ZdfFrhmyJAhTJs2jUmTJtG2bVsOHjzI/PnzDcfVajXx8fGMHz8eX19fRo0axYABA1i0SHzj1Gg0BAcH06xZM/r374+vry8rVqwol/uVSCQSycPmaURyWBf9WAO8BfQFyiYsS4RXXfCqZxxH34Do62VqSuDs4cyL214mx0qIUu+LbZk18x20dwqOza3jrmZEZ6Mg/G5nCqkZD4r5sa1b06l+fQAuxCewwmOW8eDu6aB7OF8A8pfoejDUwM82T1vbKlzRQIYZ5EE+1q5YyN+HRCKRVARyEDVp38WYDFYD+D9g4MPf/mqc8Mzm4ukhPLdlSCbe9d/t7H3pIABaRYs6cDdvb90lmjn8A61Ox2d/3OfCNZEE1tHHhpf6PJjTEnr9Oh3/+18AXG1tiaj9GzUTQsXBAd9D83Em21sYKSlZVKu2mOxsLY0bu3P5cv5qQYmaHJ66dg6AVraOLPNoYnYbHhYyzEAikUgkEomZsAL+g2i0kPvo/y4wCBFb+3AbBODpIRLDcskVt2XwxQVM7EO9F0X3MZVORfreLqx/fWKB56oUhecCHLG3EeL5aEQWoZcfvOcO9erxfNu2ACRlZjLP7kXjwX1vQbb5PaN5W9tGRt57oLWtm9qK2mpRGz4iKx1NFfVfSjErkUgkEomkBPREtMIdnGduCSIM4eFl7QOiwoFPA+P42i2IvFomQfviN5NQ/IXAtMu0Y99PTpz737cFnlvNWc0z3Y3hBj/uSSMx9cHQgfd698bZxgaAlZfiOFlnpDiQcg2Of2qyrUVRXGvbpvrmCRk6LbHZD/mLh4WQYlYikUgkEkkJqYFoebsMsNHPnQAeQ4QdPETPX91aorlCLtdvQ0SsyYJWUSnM3vVv0msnAuB+rzrL5+wh+XLBZS4f97HBv7G457RMHat3pj5Q593DyYn53bsD4p2YktIDHfoMsqMfQGqcSbYWRXGtbf0egSQwKWYlEolEIpGUAgXR8vYIkFuNJhV4DhgHFNyMwCzUqSna3+Zy8w5cijFZ0No62zJpzzQyHFIBqH3Vm3lPvYkuT731XBRF4dkeDrg6iHCDc1ez2X3uQU/n65064VNNhDDsv3mXtXX1cazZqXDgbZPsLIp27TyoXr3w1ra+eTqBSTErkUgkEolEYqAtcBx4Ic/cTwgvbejD29ajBjRtZBzH3RXtb00UtPX9GjBoVQAalagnW/1sWxYPm1DguU52Kp7rZaw1u+5gGnGJmnzn2KjVLOnXzzCedbMuqdZC3HJ2FdwJM8nOwshtbQsYWtvmxc82j2c2s2p2ApNiViKRSCQSiYk4Ilre/gzkZpxHIuJoP+ah1aStXR2aexsrGtyKh4tRJgvabkED8HrN6MFM2+bDhnmLCjy3ZQMberYQzQeycuDbHSlotPn3HeTry4AmonLAtfupLK42TRzQaWHPTJNsLIo+fYytbf9ZostJ9qCTIQAATbtJREFUpaa+lQiPuJyVTvZDKhNmSaSYlUgkEolEUkaCgJPA4/pxDjALUbqr7O1oC6RmtfyC9nYCnL8CWtPE2gufv4m2q+g6ptaqObwklfNb/y7w3Ke7OFDLVUioqNsa/jqR8cA5S/r1w0pf6uujGIVohxbiQMzfELXVJBsLI39r2wfjZn31cbPZ6IjOftDWyo4UsxKJRCKRSMyAN7APmJ1nbhvQGihYFJaZGu7QorFR0N69VyZBOy9kGUkNrwLgkObIf8f9TtKNB5O2bK0VXujtZNh287F0Ym7n5DvHr0YNXn9ciPuMnBxm2TxvPLhnBmjzn18WGjRwpWnTGgAcOXKNpKT8grVpFQ81kGJWIpFIJBKJmbAGPkCIVw/93G2gH/AG8GBiVZmp7gYtm4BKryzjE+FcpEmC1trWhlnbZ5PsHg+A691avNtzLlrNg9dq7GHFwMdEQx+NFv67I4WsnPzhBvO7d6eWo4ixXXcthV2uA/Q2noewVaW2ryiKam3rlycJ7GIVTAKTYvYRQ1EUNm7caGkzJBKJRFKl6YOoSTsgz9xHQDdETK2ZqeYKLX2MHbwSkuDsZaEyS0kdHx+Gf9GJTFvh3XSMaMAnT04v8Nwn29vToKYovRWXqOW3w/mFoqudHe/37m0Yv57Wmxyd3saDb0Om+So/FNXa1sfG3iD4LmVJz6ykAhMXF8fkyZPx9vbG1tYWT09PBg8eTEhIiKVNA+C5555DUZR8r/79+1vaLIlEIpE8FGoBm4FPEB5bEFUO2gH/M/927i7QKo+gvZcMZyNAoyl6XQF0feYZvCdmoFWEGE7b6s6GhV8+cJ6VWuHF3k5Y6UvJhpzJ5MK17HznPNe2Le3ris5pYfdS+KaavtNY2m1Re9ZM9OjhhbW1uPd/ill7lZoG1sKLfCUrnawqlgQmxWwVITo6Gn9/f3bu3MlHH31EWFgYW7duJSAggODgYEubZ6B///7cvHnT8Pr5558tbZJEIpFIHhoqRMvbQ0AT/dx9YCyiLm2Kebdzc4bWPqDWy5vE+xAWATmlF7QTv1hCVvezhvHxd68Ttu3wA+fVraZmRCdjTOp3IamkZRrFokpRWJbHcTP/jhcJir7yw4klkBxbatsK4p+tbSMjE/Idzw010ACRWVUrCUyK2SrCa6+9hqIoHD16lBEjRuDr60uLFi2YPn06hw8/+I8vl9mzZ+Pr64uDgwPe3t7Mnz+f7Gzjt8rTp08TEBCAs7MzLi4u+Pv7c+zYMQBiYmIYPHgw7u7uODo60qJFC7Zs2VKknba2tnh4eBhe7u7u5nkDJBKJRFKB8Ud0ChuXZ+7/9PMnzbuVqzO09gW13l2alAJhl0wStP/+czVxTYWgtc6x5n8j15FwLf6B83q1tqVpPSsA7qVq+d/e/OEGnT09GduqFQAJGVm87TxJHMjJgP1vldquwsjf2jZ/VYO8ncCqWtysFLNVgISEBLZu3UpwcDCOjo4PHHdzcyt0rbOzM6tXr+b8+fMsXbqUlStXsmTJEsPxsWPHUr9+fUJDQzl+/Dhz5szB2lo8LgoODiYzM5O9e/cSFhbG4sWLcXJyKtLW3bt3U6tWLfz8/PjXv/5FfPyDfxQkEolEUhVxBr7Xv3I/Ky4BnYDPMGsrXBcnaOOL4fl/ciqcuQQ5pasgYO3ozNs/Ted2HVHhwO6+M592fYeczPzXUSkKz/VyxN5GJKEdicji2OX8yW6LAwNx1H9+fnnTljArX3Hgwk8QZ54mE0WKWVtjEtilzKolZq0sbUCloH17iDN/P+Vi8fAAvRe0KC5fvoxOp6Np06al3mLevHmGn728vJg5cyZr1qzhjTfeACA2NpZZs2YZru3j42M4PzY2lhEjRtBK/23T29uboujfvz/Dhw+nUaNGREZG8tZbbzFgwAAOHTqEOvcbtEQikUiqOOOAzojatMcRFQ6mATuA74Ca5tnG2RHa+MFpvYi9nyp+bu0L1iWXP3Ue68yY+fvZMPsmLvddsY5147MB/2FGyEKU3NpcQHVnNc884cCqENEa98c9qTSpY4Wbo/Ab1nNx4a0nnmDuzp1odTpeV48nJHueKO+1ezqM3mssMWYiua1t4+PTDa1trazE/o2t7VEjwgzCq1gSmPTMloS4OLh+vfxfJRTQOhM7ngCsXbuWrl274uHhgZOTE/PmzSM21hi/M336dCZOnEhgYCAffPABkZHGoPIpU6bwzjvv0LVrVxYsWMCZM2eK3CsoKIghQ4bQqlUrhg0bxubNmwkNDWX37t0m2y+RSCSSykgT4CAwI8/cn0AbYKf5tnFygLZ+RvGakganwyEru+h1/6Dbv2bh83QM2VZiXeouFetm//DAeY/72uDfWHhfUzN1/N+u1Hyf0dM7d8ZbH163Kz6H3+z0lQ6u74fLG0p7dw9QVGtbW5WKRvoksJjsDNK1pQ+7qKhIMVsSPDygXr3yf3l4FG8bwluqKAoXL14s1W0dOnSIsWPHMnDgQDZv3szJkyeZO3cuWVnGRyMLFy7k3LlzDBo0iJ07d9K8eXM2bBD/4CZOnMiVK1cYN24cYWFhtG/fns8//7zE+3t7e1OjRg0uX75cKrslEolEUhWwQbS83YLRG3sTCATeAkonOAvF0V54aG30FRVS000StK9+vYbU7rsN47MfR3L8t/zhAYqi8GwPR1wdhIf1bGw2e85lGo7bWVnxSd++hvGMjN6k6/RCe+8boCl7Hd6iSnT56ZsnaBGtbasKUsyWhGPH4Nq18n+VIMQAoFq1avTr14/ly5eTmpr6wPHExMQC1x08eJCGDRsyd+5c2rdvj4+PDzExMQ+c5+vry7Rp0/j7778ZPnw43333neGYp6cnr776Kr/99hszZsxg5cqVJXtPgWvXrhEfH0+dOnVKvEYikUgkVY0BwBmEiAURO/s+0B2INs8W/xS0aRlC0GaWQjxaW7N49Y9EPrYPAJVOxcZnNnLrQv52vU52KiYEGPNXfj2Yxq1Eoxd0qJ8fgfqwvJjULD62HysOJEbCqeUm3Fx++vQxhvz9s7Vt3iSwqhRqIMVsFWH58uVoNBo6duzI+vXriYiI4MKFCyxbtozOnTsXuMbHx4fY2FjWrFlDZGQky5YtM3hdAdLT05k0aRK7d+8mJiaGAwcOEBoaSrNmzQCYOnUq27ZtIyoqihMnTrBr1y7DsX+SkpLCrFmzOHz4MNHR0YSEhDB06FCaNGlCv379zP+GSCQSiaQS4YFofbsYYzrPYaAt8Kt5tnCwEyEHtjZinCtoM0ouaG08vXh/0USuNLkAgFWmDSt6LiX9Xn5h2KqhDd2b2wKQlQPfhqSg0YpwA0VRWNq/P2p9fOz7iY25qnUVCw//B9Lzl9QqLZ6ehbe2zdcJrAolgUkxW0Xw9vbmxIkTBAQEMGPGDFq2bEmfPn0ICQnhyy8fLPQMMGTIEKZNm8akSZNo27YtBw8eZP78+YbjarWa+Ph4xo8fj6+vL6NGjWLAgAEsWrQIAI1GQ3BwMM2aNaN///74+vqyYsWKAvdSq9WcOXOGIUOG4Ovry4svvoi/vz/79u3D1tbW/G+IRCKRSCoZKkTL2/1AI/1cEjAKeAkwg/iy1wtaO72gTc+E0xchI7PodXmo92QQzwe5cKuWyGtR3bbli75L0Obkb0QwsqsDNV2EzLpyS8PWE0ZR2bxmTYI7dBAm5GiZbf+SOJBxTwjaMlJYa9tGNnZYI0R0VeoEpujKkj1UCUlOTsbV1ZWkpCRcXFzyHcvIyCAqKopGjRphZ2dnIQslucjfh0QikTyqJAH/AvI21mkGrAFal/3yGVlwJlyIWRDe2jZ+YF9C54pWy7JRj3PtrwAc00RIQZOJjRi7cny+0yLjslm84T46nejj8OYIFxrW1NejTU/H5/PPiU8XonKf04904zKorOC58+Dug6n8+eclnnxSvHf/+ld7VqwYZDj2r5sRhjqzf3i2xElVMasJFaXX/on0zEokEolEIqlguAI/Ad8CuXGeF4COwHLKXJPWLle86h0lmVnCQ5tWws5YKhWTv/qLpC6b0KhEPOzl/0Zx4OsD+U5r7GHNgHZiD40WVu1IIStH2O5ub8+7vXoZzp2ijEWjU0CbA3tnl+n2imptmzfUoKrUm5ViViKRSCQSSQVEAZ5H1KJto5/LBCYBTwFlbLpjayNCDhxyBW22iKFNK9njd6VGDT779zeEdfvTMPd38N9E74vOd97gDvY0qCG8nzfvadlw2CggJz72GG1q1wbg5H2Fb1U9xYHLG+DaXtPuC9HatmvXBsCDrW1zKxpA1UkCk2JWIpFIJBJJBaYpIhns9TxzvyOSw0wXfICobtDGT1Q7AFGu61S4KN9VAuw7d+ez4UM5/dgRAFQaFauf/I7EmETDOVZqhRcDnQzNyHacyeTCNVEWTK1SsWzAAMO5b2UGkKjTi+vd00GXPw63NOTGzUL+bmBN83hmw6tIW1spZiUSiUQikVRw7BAtb/8AquvnrgEBwEKgdG1q85EraJ30HsvsHOGhTSmZ0Gs4ZT7/apXOlUbicb6SrOKbfl+RlWqsklC3mprhnYwe0dU7U0nLFEK1e8OGjGrRAoC7WVoWqUeIk24dhwv/M/m2+vQpuN5sA2s77BQh/8IzpWdWIpFIJBKJpBx5EjgN9NSPtcAioBcQW8iaEmBtJdrcOv9D0N5/sHb7AygKfT7fRIumu4ivJkIf0sMz+SHoB3RaY2xv79a2+NUTyV8JKVp+3mcUyx/16YO9lTj2xX1fLmhFaS32vQnZpnlPc1vbAoSERJGjr7agVhSa2Ajvb5wmiyRNGb4IVBCkmJVIJBKJRFKJqAfsAN4BcjPx9yHCDsrQEjZX0LroGx7kaOD0JUhOKX6tszOzPvyLhMd/IcNWJJFd23yNv9/+23CKSlF4vpcj9jaiNNbhS1kcjxTe2waurszu2lVsq9MxVTUOnQ5IuQbHl5h0O3lb2yYn529t2zRf84TKH2ogxaxEIpFIJJJKhhqYi4iZbaCfuwcMB14DTHx8bmUFrXzB1UmMNRo4cwmSihe0SsuWfDX6P4QGrkenr7Zw+N3DnPvlnOGc6s5qgroZheSPe1JJTBUe01ldu9LAVTRP+DvFlT+0+iZERz+A1DiTbqew1ra+ecVsFQg1kGJWIpFIJBJJJaULcAp4Os/cl4gSXucKWlA8Vmpo5QNuzmKs0ULYJUi8X+xSpwkv8WWDx9gXsN0wt278Om6evGkYd/az4TFv0VY3JUPH97tS0el0OFhb83GfPobzputGkKlTQ3YKHFxg0q0U1trWz7ZqJYFJMSuRSCQSiaQS4w78AnwD5Iq0s0AH/ZwJNWnVamjZBNz1xfo1WgiLgHvJxS71+XQ1U23iON36tJjIhNWDVpNyS3h3FUXh2R6OuNiLcIOw2Gz2nRfNG55u3pweDRsCEJlhxWfaHuIaYf+Fu2dLfRuenq40a2ZsbZuYKEIg6lvZ4pibBFYFynNJMfuIoSgKGzdutLQZEolEIpGYEQXR8vYY0FI/lw68gmiHe6/0l8wVtNXEo3+0WjgbAQlJRa+zs2Pwiu20qbWNq/WvApB1M4vvh3xPTqZItnK2VzEhwNGwZO2BNG4naVAUhWUDBqBShNB9J6s7N7VOokTXnpmlvweMoQaitW0UIOJ3c0MN7mqyic/JNunaFQUpZqsQcXFxTJ48GW9vb2xtbfH09GTw4MGEhIRY2jQDFy5cYMiQIbi6uuLo6EiHDh2IjS1DBqpEIpFIJAaaA0cRcbO5rEMkhx0oaEHRqFTQojFUdxNjrQ7OXob4xKLXeXszf9JPJLRfS7Kz8ObeOXqH31/5HZ1OeIpbe9nQvblon5uVA9/uSEWj1dG6dm1e8fcHIEUDc3RDxTWjt4lXKckfapAnbrYKhRpIMVtFiI6Oxt/fn507d/LRRx8RFhbG1q1bCQgIIDg42NLmARAZGUm3bt1o2rQpu3fv5syZM8yfPx87OztLmyaRSCSSKoM9ouXtb4gQBBBlu3ogKiBo/r+9O4+LquofOP4Zhn1XURFFBQJR3DF91MxI3DI19dEyUsu0nwmZ4pYpmZWplfmkuZTlkpa4a2WhheKKC+K+AiKoCeaCKDsz9/fHxQESFE2W0e/79ZpXzLnn3HvumSt8O3OWBzudiQk0cAenvHMpCpyIg6v37u016fkSiz0Hs7trKDmmas/n8aXH2fu/vYY8fdtaU9VeDcXiknMJO6QOA/jYz49KeX8bf8jwZJ+uplogYrS63e0DKLi1beHNEx6fncAkmH1MDB8+HI1Gw/79++nTpw9eXl74+PgQHBzM3r17iy03fvx4vLy8sLa2xt3dnZCQEHJy8r9uOHLkCH5+ftjZ2WFvb4+vry9RUVEAJCQk0L17dypVqoSNjQ0+Pj789ttvxV5r4sSJvPDCC3z22Wc0a9YMDw8PevToQbVq1R5dQwghhBCAuuXtYaBd3nsdEAL4A5eKKVOMOwFt1crqe0WBk+fg7+v3LOYw9Qu+T3Xm9xc3GNK2jNlC7OZYACzNNAzuYEPeqAJ+OZBB4t+5VLG25iM/P0OZd/R90SsauHYCji96oKoXt7VtvcdoJzAJZh8D169fJywsjMDAQGxsbO467ujoWGxZOzs7lixZwsmTJ/nqq69YuHAhs2blr2kXEBBArVq1OHDgAAcPHuS9997DzEydhRkYGEhWVhY7duzg2LFjzJgxA1tb2yKvo9fr2bRpE15eXnTu3Jlq1arRqlUrGb8rhBCiFNUGtqLuEnYn5IkAmqDuJvYANBqo7wbV83YguxPQXrlWfBkzM3y+/4X3ki+wo13e1rt6WNl3JVfPXAXgqRpmdGmm9sLq9PDdn2nk5CoMa9ECn6pVATiQ5cgPuU3U8rtDIPv+KysUVNTWts6m5tibqOv0nsnKMAx/MEam5V0BY9Di2xYk3X64Nd7+DWdbZ6LeirpvvtjYWBRFwdvb+4GvMWnSJMPPdevWZcyYMYSGhjJu3DgAEhMTGTt2rOHcnp6ehvyJiYn06dOHRo0aAeDu7k5xrly5wu3bt5k+fTqffPIJM2bMICwsjN69e7Nt2zbat2//wHUXQggh7s8UmIy69W0A6ja414AewAhgBup2uSWg0UC9uup/k9RglFPx6oIJd4Lcf3Jxoe/UDUR92oHT9arhfcab3Fu5LH9xOcMODMPS0ZIeT1txPDGHC1d1XL6hY/2+DPq1tearLl3wX7YMgPd03ehtegr79CuwfwY880mJW6BTJw/ef38roI6bHTasBRqNhnrm1hzIvEWKPpcruhyqm5qX+JwViQSzJZB0O4lLtx7wK4ky9G/+b2rlypXMnj2buLg4bt++TW5uLvb29objwcHBDBkyhGXLluHv70/fvn3x8FBnRo4YMYK3336bLVu24O/vT58+fWjcuHGR19Hr1UWhe/bsyahRowBo2rQpe/bsYcGCBRLMCiGEKGXPog47eBPYmJc2G9gOhAIl7BDSaMCrjvrfy3+raafj1clhNZyKLuPnx9TdH/Liiakk33iT6leqczP2JqteXsVrm17D1NSENzvY8MnqVHL18OeRTJrUNaODuzu9vL1Zf/o0yblmfGLyHJ+Zb4aDM6Hx/4G9a4mq3KxZDapUseLatQzD1rampibUM7fiQKbay3smO91og1kZZlACzrbO1LSrWeYvZ1vnEtXP09MTjUbD6dOnH+i+IiMjCQgI4IUXXuDXX3/l0KFDTJw4kezsbEOeDz/8kBMnTtCtWze2bt1KgwYNWL9e3S5wyJAhnDt3jgEDBnDs2DFatGjBnDlziryWk5MTpqamNGjQoFB6/fr1ZTUDIYQQZaQK6pa3cwGLvLQjgC+wiBKvSavRgGdtqFlgzsfZ8/DX38UWMX1/Ej+mtWNHtxWkWacBEL8lnj/GqRss1KxiSq//qONYFWBReBrpWXpmduqEhVYdDvC/nP9wVl8FcjNh1/slqytgYqIptLXt/v1qB109i8djJzCNYsyDJB5CamoqDg4O3Lx5s1APJEBmZibx8fG4ubkZ3Qz7rl27cuzYMc6cOXPXuNmUlBTDuFmNRsP69et56aWXmDlzJvPmzSMuLn+pjiFDhrBmzRpSUlKKvE7//v1JS0vj559/vuvYhAkT2LRpE0ePHi2ybJs2bfDw8GBZ3lcmAL169cLKyoqffvrprvzG/HkIIYSo6I4CrwCnCqS9AiwAHEp2CkWBcxfhYnJ+2lOuULN60fmvXSO6Y0Ne8bHglZ8GotWrQWqP73vQbHAz9IrCzI23OPuXumJB63rmDO5gy6StW5m6cycA3czi+dViqXq+gAPg3KJEVV206BBvvqn+7Z48uT0ffvgcf+dm0++Sev++lrZ8Ud3jXqcoU/eK1/5JemYfE3PnzkWn09GyZUvWrl1LTEwMp06dYvbs2bRu3brIMp6eniQmJhIaGkpcXByzZ8829LoCZGRkEBQUREREBAkJCezevZsDBw5Qv766X/TIkSPZvHkz8fHxREdHs23bNsOxoowdO5aVK1eycOFCYmNj+frrr/nll18YPnx4sWWEEEKI0tEYdZOFoQXSQoFmwL6SnUKjAfda4Frgm9TYC3ChmHk2VarQfMFGJp28yG8v5K/+88uwX0jcnYiJRl3dwFKdZ03kmWyi47KZ8Mwz1LRTt9fdlOPG77lPqRkigtWAugQKrjd7ZxKYk9aMylp1xOmZbOOdBCbB7GPC3d2d6Oho/Pz8GD16NA0bNqRjx46Eh4czf/78Isv06NGDUaNGERQUZBi/GhISYjiu1Wq5du0aAwcOxMvLi379+tG1a1emTJkCgE6nIzAwkPr169OlSxe8vLyYN29esXXs1asXCxYs4LPPPqNRo0Z89913rF27lmeeeebRNoYQQghRItaoW96uIr83Nh54BpgO6O9/Co0G3GpC7Rr5aecuQuLlovO3bMnAwV/RWneQ/U/vB0DJUQjtFcrNxJtUsdPSv13+N6zLtqeRm2vKZx07GtJG5XYnW9HCpZ0Qu6FEd1rU1rZ3JoEB3Nbr+Cs3+16nqLBkmEEB8rV2xSKfhxBCiLJzHngViCyQ5g/8ANQoqsDdEv6C83/lv6/jAnVd7s6nKOS8+godLNbgtuM13OPVXtPqTaszeNdgzKzNmB92m0Px6rrvjeqYEdTVhmeXLGH3BXWL3Jnmmwk2jwTHp+D1E6C9/+StkSPD+Oortdd53bp+9OpVn6UpSSy5qQ6TCHGqzfM2le51ijJjdMMM5s6dS926dbG0tKRVq1bs37+/2LwLFy6kXbt2VKpUiUqVKuHv73/P/EIIIYQQ91cXdWWD94G8XQz4E3VN2t9Ldoo6Lmov7R0Jf0H8pbuHAmg0mH37HasOu7Gzy2quV1I3Mkg+nMzG19WVFgY8Z4O9lVqPYwk57DqdzeyuXQ01m5LbgWS9DaTEwpGiv4H9p06d8sfE3tnattAkMCPdCazcg9mVK1cSHBzM5MmTiY6OpkmTJnTu3JkrV64UmT8iIoL+/fuzbds2IiMjcXV1pVOnTly6VHGXzhJCCCGEMTADpqIGsXd6Y/8GXgBGAyX4Gr52DfColf8+8XLRAa2dHc4/buTHP/SsfnkFWeZZAJxcc5IdH+/AzsqEgX75ww1W7UqnlnU13mzWDIBUvSkTszuoByOnQMa9dyMDaN++jmFr2y1b1HGzXgV2AjudZZw7gZV7MPvll18ydOhQ3njjDRo0aMCCBQuwtrZm0aKit2v78ccfGT58OE2bNsXb25vvvvsOvV5PeHh4GddcCCGEEI+n51FXO3ixQNqXQBsg5v7FaznDU7Xz319IgriLdwe0Pj60/mAhkw/8zZr/rkHJWxosYnIEJ9eepEldc9rVV5cQy8qFxeFpfOz3PPYWatqi3GYc1NWAzBuw7/6bKNjY5G9te+6curVtZa0Z1bTqjLOY7Ax0Rjj6tFyD2ezsbA4ePIi/v78hzcTEBH9/fyIjI+9RMl96ejo5OTlUrly5yONZWVmkpqYWegkhhBBC3JsT8DPwP+DOeNSDQHNgWTFlCqhZDTzr5L+/lAyxiXcHtAMG8FaLt2h3O4Y//f80JK8fuJ6kw0n0a2uNk70arsUm5XIoRsvkvI2GFDSMyO6mnvLQ13Aj9r7VKmpr2ztDDTIUPRdzs+5/bxVMuQazV69eRafTUb164fXYqlevTlJSybaPHT9+PC4uLoUC4oKmTZuGg4OD4eXqWrLdMoQQQgjxpNMA7wJ7Aa+8tNvAQGAAcOvexV2qqtvf3vHX3xCTcFdAq/nfV8z9qynZdXdzpPERAHLTc1nRcwW6lHQGd7AxjJXduD+DHu7NqVdF3T53j64WP+U2An0O7Bx/3zsqctyskQ81KPdhBv/G9OnTCQ0NZf369cXOdp8wYQI3b940vC7kzQIUQgghhCiZZqi9sq8XSFuO2kt78N5FnZ3A2y3//eWrcOZ84YDW0hLLlWtZ+7sdkR1+4WLNiwCkJqayqs8q3KuY0LmZGufo9LB8WyZfdOxsKD4upzO3FXOIWQcXd977TvK2tgUMW9veWZ4LjHMSWLkGs05OTmi1WpKTkwulJycn4+x8761cv/jiC6ZPn86WLVto3LhxsfksLCywt7cv9BJCCCGEeDC2wGLgR8AuLy0WaA3M5J5r0lavAvXzv94n+Rqcji8c0Lq74zpvOSvW57K6XyipduqwyMRdiWwavonuT1tSq4q6Y9il6zoyrtbkRS+1t/gvvS3TsvPWbN8+GpTi62JioqFjR7V39s7WtgV7Zs9mS8/sAzE3N8fX17fQ5K07k7mK27UK4LPPPuPjjz8mLCyMFi1Kto2bEEIIIcS/9ypwCHg6730OMAboBiQXVwiqVYYGHuomCwBXrsOpc6AvEHj26MFz/cYxOfI2oa+EkmOqrjN76PtDRM/dzxB/G0zzIrc/jmQS1OR5zEzUhJk5bTmnrwRJB+D0inveQcFxs1u2xGGnNcXFVB0XHJOdQa6RTQIr92EGwcHBLFy4kKVLl3Lq1Cnefvtt0tLSeOONNwAYOHAgEyZMMOSfMWMGISEhLFq0iLp165KUlERSUhK3b98ur1sQQgghxBPFA9gFjCuQFoa6Ju0fxRerWqlwQPv3jbsD2qlTGWnejvbX/2Jjz42G5C3BW8g8mMBLrdReVAXYdtCCd1r+B4AstIzO6qRm3jkBcoofLnCnZxYKjptVhxpkKwrnczLvce8VT7kHsy+//DJffPEFH3zwAU2bNuXw4cOEhYUZJoUlJiZy+XL+lnDz588nOzub//73v9SoUcPw+uKLL8rrFoyKRqNhw4YN5V0NIYQQwsiZAzOAzcCdiezJQCdgPGqPbRGcHMGnQEB7NQVOxuUHtKamaEJXsjCyKiZVj7PzGXUMrKJXWPPyGppbpeHlYgrAtVt6PDS+ONvaArBBV58/c93h1gWI/l+xNa9Vy77A1raXSEnJxNsif6jBGSObBFbuwSxAUFAQCQkJZGVlsW/fPlq1amU4FhERwZIlSwzvz58/j6Iod70+/PDDsq94BZOUlMQ777yDu7s7FhYWuLq60r179wqzBq9Goyny9fnnn5d31YQQQoiH1Ak4AnQukPYZ8AxwrugiVRyh4VNgkhfQXrsJJ2LzA9oaNbBZvpJ1qzUcbLOV0/VOA5CZksnKl0J5tbkWS3VpWA7FwtuN2xtOPTK7C7mKCez7FNKKH/ZwZ1UDvV5h27Z4vApMAjtrZJPAKkQwK/698+fP4+vry9atW/n88885duwYYWFh+Pn5ERgYWN7VA+Dy5cuFXosWLUKj0dCnT5/yrpoQQgjxL1QHfgO+QN1FDGA/6ioIoUUXqewADT0hb8wr11PheCzodOp7Pz88gj9hxTqF9b3WcaWqujPqtTPXiPi/DbzcOr8n9XqiO741XAA4oa/G/JwWkHMb9kwutsb/XKLLy9zKsPzXaSObBCbB7GNi+PDhaDQa9u/fT58+ffDy8sLHx4fg4GD27t1bbLnx48fj5eWFtbU17u7uhISEkJOT/9XIkSNH8PPzw87ODnt7e3x9fYmKigIgISGB7t27U6lSJWxsbPDx8eG3334r9lrOzs6FXhs3bsTPzw93d/diywghhBDGwQR1y9s9qGNqAVKB/sBgIO3uIpXsoZEnaPPCsRupcKxAQPvee3TxeoGQ3dms6L+CdCs1yIwNiyVt8Q6auqmBc1oWPOeY3zv7Qc7zXFWs4dhCuHqiyNr+c2tbaxMttc3UncXOZWeSfY8VESoa0/KugDH4tsW33E4q+wlmts62vBX11n3zXb9+nbCwMKZOnYqNjc1dxx0dHYsta2dnx5IlS3BxceHYsWMMHToUOzs7xo1TB7UHBATQrFkz5s+fj1ar5fDhw5iZqf94AgMDyc7OZseOHdjY2HDy5Els88bt3E9ycjKbNm1i6dKlJcovhBBCGIcWQDQwHHUZL1CX9NqD2kvbtHB2Rzto5AXHYtQg9uYtOBqjBrmmWli2jAnNmxHlksiqfqsYsGwAWr2WvV/upVO9asRZ1eVWhsLNq050qdOQsITjpCiWhGT5Md9yE+wYC73v7miysTHnmWdqs23becPWtl4O1iTkZJGLQnx2pmFnsIpOgtkSuJ10m1uX7rPLRzmKjY1FURS8vb0fuOykSZMMP9etW5cxY8YQGhpqCGYTExMZO3as4dyenp6G/ImJifTp04dGjRoBPFAP69KlS7Gzs6N3794PXGchhBCiYrNH3VShE2pQmwacAVoBnwPvgOFLfcDBFhp7qgFtrg5Sb8PRs2pa5cqYrFrN0ufb0vKN8/ze9Xde3PQiAOHvbOLFH19lRYYjAM6ZLbExO0taTjbf5voyTBdFk/jf4fwWqNvprlp26uTBtm3nAXWoQb2AuvyRdgNQhxoYSzArwwxKwNbZFruadmX+snUuWS+n8i/Wg1u5ciVt27bF2dkZW1tbJk2aRGJiouF4cHAwQ4YMwd/fn+nTpxMXF2c4NmLECD755BPatm3L5MmTOXr0aImvu2jRIgICAorduU0IIYQwfgNRe2mb573PRt0etwdwtXBWe1to7KX2xgLcSlMD2pxcaNkS+xn/Y30onG4cxf6n9wOgy9YRHbSO/1TJAsBUb0O7Ki0B0GPCiKyu6r4M28eAXndX7Tp2LLje7LnCO4FlGc8kMOmZLYGSfNVfnjw9PdFoNJw+ffqBykVGRhIQEMCUKVPo3LkzDg4OhIaGMnPmTEOeDz/8kFdffZVNmzbx+++/M3nyZEJDQ+nVqxdDhgyhc+fObNq0iS1btjBt2jRmzpzJO++8c8/r7ty5kzNnzrBy5cqHul8hhBDCeHihDjF4H/gyL+1X1DVplwN++VntbKBJvfwg9lY6HD2jBrnDh1N/1y5+WB/Kf/uGUfXvqriddyMtOQ3bGb/gFNiLq1laauQ2xsXmOH+lpbBDX5fVuT70u3oMji+GxkMK1ezO1rbXrmWwdWs8y0wsMEHdy+yMEU0Ck57Zx0DlypXp3Lkzc+fOJS3t7gHmKSkpRZbbs2cPderUYeLEibRo0QJPT08SEhLuyufl5cWoUaPYsmULvXv3ZvHixYZjrq6uDBs2jHXr1jF69GgWLlx43/p+//33+Pr60qRJk5LfpBBCCGG0LFC3vN0EVM1L+wvoAIQAuflZba3VgNYsr7/xdgYcyQtuv/2WXnjz3m49q/qt4nql6wAkH7qM18ZtaBQFrUZLI7NnDKcbk92JdMUMdk+C7MJDJv+5te3RqMvUNVO/MT2fk0mm3jgmgUkw+5iYO3cuOp2Oli1bsnbtWmJiYjh16hSzZ88udmtgT09PEhMTCQ0NJS4ujtmzZ7N+/XrD8YyMDIKCgoiIiCAhIYHdu3dz4MAB6tevD8DIkSPZvHkz8fHxREdHs23bNsOx4qSmprJ69WqGDBlyz3xCCCHE4+cF1DVpO+S9V4BPgGeB8/nZbKygqTeY5y3zlZYBR86AhSWsWcNH+6x49q8MVvRfQZa5OsQg8ZdTND1yCIBapnXxsK4DwAXFgc+y20J6Mhz47K4a/XNr2ztDDfRArJGsNyvB7GPC3d2d6Oho/Pz8GD16NA0bNqRjx46Eh4czf/78Isv06NGDUaNGERQURNOmTdmzZw8hISGG41qtlmvXrjFw4EC8vLzo168fXbt2ZcqUKQDodDoCAwOpX78+Xbp0wcvLi3nz5t2znqGhoSiKQv/+/R/dzQshhBBGowawBZgG5I2PJRJ1lYM1+dmsLaFpPbAwV9+nZ8Lh0/CUJ9oF3/LTWrAz/Zu1fdaioM6d+XvhbmrFxaPRaGhm8QxajRrmzchpS4LeAaJmQuqFQrX559a2hXYCM5KhBhrl38weMkKpqak4ODhw8+ZN7O3tCx3LzMwkPj4eNzc3mZhUAcjnIYQQ4vG2F3Ud2vMF0t4CZgF5k7EystRe2axs9b2lBTTxgpHvcmTDN7QeAr57n8E/3B8AU2szkkb9l0wXJ/be3snxjMMA9DM9zkrLNdBgAHT9oVAtfHzmcfLk35iYaNiXPIKxaeqQw442lXjfqXYp3fu93Ste+yfpmRVCCCGEKBf/AQ4DLxdI+xZ4GjimvrWyUHtoLdUNDcjMC25nfEaTms357mfY9cwujjZSVxTKTc/BZdEmTG6l08y6JdYmak/rqtyGbNfVgZPLIPlgoVrcWdVAr1eI3/kXpnnLhp3JMo6eWQlmhRBCCCHKjQOwAvgeQ28sJ1ED2nmAogayTeupgS1AZjacOg8rVvLqBUdG7oWfe/zMJZdLAGRfTqXWD2FY6E1pbp0/b+bdrK7oFA1EjIYCX8wX3No2fPM5PMzVb0Mv5GaRVsSSXhWNBLNCCCGEEOVKg7rlbRTQOC8tCwgE+gDX1bGzTeqpY2lBHXZwLQ2WLeezP6DtpVxCXwnllq26YoH+5CWqrI7Ay8KbKqbqCgpH9M4szPWFi9shdqPh6gW3tv3jj/z1ZhUgxggmgUkwK4QQQghRIdQH9qHuEHbHetQ1aXfmB7Q2eZO0snOgSi3MPvyYVavBQblF6Cuh5GrVpb6sdp3EbsdxWts+azjbpKznuaFYws5xoFPH4d7Z2hbg3LkbVLqZvySXMQw1kGBWCCGEEKLCsARmAxuBynlpF4HngClgbqJOALMtENB2eJFqXfuxdhX87XyJjT3ze10rrd1JnbhcPCy8ALiGNZOz/eBGDBxZYMhXcKjB5T1XDD+fkZ5ZIYQQQgjx4HoAR4H2ee/1wIfA82CWBI3rqRssgLqhwojxtKz5H+ZtgmONj7HzmZ15xRScvg+jbVpDTPM2fp2X8zTHddUgcgpk3gAKB7P71sdhrsmbBGYEy3NJMCuEEEIIUSHVBMKBj8gP2XYATcDsV7WH1s5GTdbrYcZs3sxowFtRsPX5rZzxOgOAJj0L14Xb8NU0BUCHCSOzu6BkXIe9nwDQtKkzTk5qcLztz3ieMlXH5v6Vm02qrsAOZRWQBLNCCCGEEBWWFnXL2x3AnTVfbwC9wPRdaOwK9rZqskYDX3/HnPMNaXVJYV3vdVypqg4ZMEu+QfuVV7DDDoBwnTsbdN5waA6kxGFiosHfX12iKzU1C4fr+eNmz1bwoQYSzAohhBBCVHhtUdek7V0gbR6YtoHGOeCQF9CammE+cz4/H2+CY24WK/qvIN1KHSpgfTKRlyOcDKVHZ3UmU6fAzveAwlvb3jh03fBzRR9qIMHsE0aj0bBhw4byroYQQgghHlgl1C1vF6BOFAM4BtpW0Hg7OOYFtBaWVJ0yhy1Hm3PL4Qar+q1Cr1F7WmtFxNP+eCUA4pVKzMxpDWfXwMVdhba2Pbox3vDzmSzpmRVlJCkpiXfeeQd3d3csLCxwdXWle/fuhIeHl3fVALh9+zZBQUHUqlULKysrGjRowIIFC+5fUAghhBB5NMD/oa5J65OXlgEmw6BRCFTJS7K0onHwV6yOa8l5t/P83vV3wxnar79JrQvqz59mt+OS3g62j6ZWTVsaNFDXpN27IQ5LjGMSmASzj4nz58/j6+vL1q1b+fzzzzl27BhhYWH4+fkRGBhY3tUDIDg4mLCwMJYvX86pU6cYOXIkQUFB/Pzzz+VdNSGEEMLI+AAHgGH5SSZrwOe/UCtOfW9pSc/Xv+SzlNYcaHmAAy0OqNl0egJWmmJ/E9IxZ3x2R0jaD6dXGoYa6HUKVdT9F7iiy+G6Lqfsbu0BSTD7mBg+fDgajYb9+/fTp08fvLy88PHxITg4mL179xZbbvz48Xh5eWFtbY27uzshISHk5OQ/sEeOHMHPzw87Ozvs7e3x9fUlKioKgISEBLp3706lSpWwsbHBx8eH3377rdhr7dmzh0GDBvHcc89Rt25d3nrrLZo0acL+/fsfXUMIIYQQTwwrYD7q0ANHNUmTAO4B4P0ToENjbsGYF75ghKYdv3f9nfi66vABq9u59A/VYJYNP+Y2Zo/OFXa+Rxf/moazp5+8afi5Ig81MC3vChiFgyfVRYnLmrkZ+Da4b7br168TFhbG1KlTsbGxueu4o6NjsWXt7OxYsmQJLi4uHDt2jKFDh2JnZ8e4ceMACAgIoFmzZsyfPx+tVsvhw4cxMzMDIDAwkOzsbHbs2IGNjQ0nT57E1ta22Gu1adOGn3/+mcGDB+Pi4kJERARnz55l1qxZ971HIYQQQhSnD/A08CqwGzQ6qD4LbCPh6AdoqMr/2szgxtH3Wd13NUMXDqVSSiVqXFbouRHW/BfeyerGgdRv8GvwM+bmWrKzdZzdfIGqrdShDGez02ltbV+eN1ks6Zktieyc8nuVQGxsLIqi4O3t/cC3NmnSJNq0aUPdunXp3r07Y8aMYdWqVYbjiYmJ+Pv74+3tjaenJ3379qVJkyaGY23btqVRo0a4u7vz4osv8uyzzxZ3KebMmUODBg2oVasW5ubmdOnShblz596zjBBCCCFKojYQAXyAIbyz2QtPB0DlnWjMzFjSdBrd67RhRf8VZJlnAdDwBLTbCdF6ZxbnNsX80Ay6+TkAEPfnJcPZK/JOYBLMloS5Wfm9SkBRlIe+tZUrV9K2bVucnZ2xtbVl0qRJJCYmGo4HBwczZMgQ/P39mT59OnFxcYZjI0aM4JNPPqFt27ZMnjyZo0eP3vNac+bMYe/evfz8888cPHiQmTNnEhgYyJ9//vnQ9RdCCCHEHabAFGAr6oYLgOkNaBQMHjMxMdXzU4NP8G/UnHW916Fo1Pihw1bwPgXjsrtyMyubSc+rE8czE9Mxy1HznM5K/1fxRmnSKBW1ZqUkNTUVBwcHbt68ib194e7yzMxM4uPjcXNzw9LSspgzVDzXr1/HycmJqVOnMmHChHvm1Wg0rF+/npdeeonIyEjatWvHlClT6Ny5Mw4ODoSGhjJz5kxSUlIMZc6ePcumTZv4/fff2b59O6GhofTq1QuACxcusGnTJrZs2cKvv/7KzJkzeeedd+66bkZGBg4ODqxfv55u3boZ0ocMGcLFixcJCwu7q4yxfh5CCCFE+bsGDAYKTLK+5QWnpqJPr80bpz/i3Jqb+If7A5BtBt+/CX1dDzHb4hd8Ph/GqeRq+G/uSG49dQjjqpr1qWpqXia1v1e89k/SM/sYqFy5Mp07d2bu3LmkpaXddbxgYFrQnj17qFOnDhMnTqRFixZ4enqSkJBwVz4vLy9GjRrFli1b6N27N4sXLzYcc3V1ZdiwYaxbt47Ro0ezcOHCIq+Vk5NDTk4OJiaFHzmtVotery+yjBBCCCEeVhVgAzAHsFCT7M6C70BMnDex2DsE775OHGt4DADzHOi/ApakNOO0vjJf9doKwMWdSYYzVtShBhLMPibmzp2LTqejZcuWrF27lpiYGE6dOsXs2bNp3bp1kWU8PT1JTEwkNDSUuLg4Zs+ezfr16w3HMzIyCAoKIiIigoSEBHbv3s2BAweoX78+ACNHjmTz5s3Ex8cTHR3Ntm3bDMf+yd7envbt2zN27FgiIiKIj49nyZIl/PDDD4ZeXiGEEEI8ShogCNgH5M2r0WaA90eY1J/MQp93qRGo5ZKLOjbW8Sb8dxUMTn8df4/T+HvGcfXAVcPZTmdVzPVmJZh9TLi7uxMdHY2fnx+jR4+mYcOGdOzYkfDwcObPn19kmR49ejBq1CiCgoJo2rQpe/bsISQkxHBcq9Vy7do1Bg4ciJeXF/369aNr165MmTIFAJ1OR2BgIPXr16dLly54eXkxb968YusYGhrK008/TUBAAA0aNGD69OlMnTqVYcOGFVtGCCGEEP9WE9RNFobkJ1XfDL6vMaflC1R+P4dbduqisnUTwOkXW37StWFm982kHa/429rKmNkCZIxmxSKfhxBCCPGorQTlLdCkqm/1Wjg/nE826sgaVxnTXHXV1ohupvz23BSCVncl7tsQNI5m2Jto2VDLB41GU+q1lDGzQgghhBCiCC+D5jDoW6lvTXTgPodJgw5Sd2b+JgnP/pbLmDPBfNJlKxnRFwFI1eu4nJtdDnW+NwlmhRBCCCGeKG5gshNuvwN35mBX3sebw36k7VJ1IriJAnY/WhGb1ZSA88sMJSviJDAJZoUQQgghnjhmYDsbjn4BN6zUJPPr+A9czKsROzExy8UqAzYs7kx/k204pScDFXPcrASzQgghhBBPqqajYekoOFjDkOTZPpwRscup5HEN+ys6FqwcwRtRs2ltZYe7WcWbwyLBrBBCCCHEk2zExzC5GXzfBPTqBDCH2ucJPL6QRgFH0J/ScHtxZd5OTKCTbeVyruzdJJgVQgghhHiSmZjAD8vg4xR0wW1R0l0B0Fpm0nv5enouWU/cgVqcmTUPKuAiWBLMCiGEEEI86SpXhtWr0c6P5PYbDVCS8reebzroCG8d/IZzsZW5uDa0HCtZNAlmhRBCCCEEPP00zJqF3arNxAfloj/5IeRaA1DF6zpv7vyOuFOLUZSKtQ29BLNCCCGEEEL19tvQvz/uazez47Od5B5cAqnqVvVacz2WvcxRt8mtOCSYfcJoNBo2bNhQ3tUQQgghREWk0cC330L9+jy3NJxFK+aRHb0ALgyA9NrciBlYwUJZCWYfK0lJSbzzzju4u7tjYWGBq6sr3bt3Jzw8vLyrBkBycjKvv/46Li4uWFtb06VLF2JiYsq7WkIIIYQoyNYW1qwBa2te/zqCSVsnkhU7DA4uZ8+1fVS0KWCm5V0B8WicP3+etm3b4ujoyOeff06jRo3Iyclh8+bNBAYGcvr06XKtn6IovPTSS5iZmbFx40bs7e358ssv8ff35+TJk9jY2JRr/YQQQghRQIMG8O23mL/2GqNm7eINmzG4VfemVbuX0GgqVt+s9Mw+JoYPH45Go2H//v306dMHLy8vfHx8CA4OZu/evcWWGz9+PF5eXlhbW+Pu7k5ISAg5OTmG40eOHMHPzw87Ozvs7e3x9fUlKioKgISEBLp3706lSpWwsbHBx8eH3377rcjrxMTEsHfvXubPn8/TTz9NvXr1mD9/PhkZGaxYseLRNoYQQggh/r2AABg2jBq3YeScSAbOCaeHc/vyrtVdpGe2RFoASeVwXWcg6r65rl+/TlhYGFOnTi2yh9PR0bHYsnZ2dixZsgQXFxeOHTvG0KFDsbOzY9y4cQAEBATQrFkz5s+fj1ar5fDhw5iZmQEQGBhIdnY2O3bswMbGhpMnT2Jra1vkdbKysgCwtMzfOcTExAQLCwt27drFkCFD7nufQgghhChjs2bBgQO0PHgQLiXC4MHqEIQK1DsrwWyJJAGXyrsSxYqNjUVRFLy9vR+47KRJkww/161blzFjxhAaGmoIZhMTExk7dqzh3J6enob8iYmJ9OnTh0aNGgHg7u5e7HW8vb2pXbs2EyZM4JtvvsHGxoZZs2Zx8eJFLl++/MD1FkIIIUQZsLSE1auheXPIyIAuXcq7RneRYLZEnCv0dZV/sRvHypUrmT17NnFxcdy+fZvc3Fzs7e0Nx4ODgxkyZAjLli3D39+fvn374uHhAcCIESN4++232bJlC/7+/vTp04fGjRsXeR0zMzPWrVvHm2++SeXKldFqtfj7+9O1a9d/VX8hhBBClDI3N1i5EqpWhWbNyrs2d5ExsyUSBVwsh9f9hxiA2luq0WgeeJJXZGQkAQEBvPDCC/z6668cOnSIiRMnkp2dbcjz4YcfcuLECbp168bWrVtp0KAB69evB2DIkCGcO3eOAQMGcOzYMVq0aMGcOXOKvZ6vry+HDx8mJSWFy5cvExYWxrVr1+7ZoyuEEEKICqBTpwoZyIIEs4+FypUr07lzZ+bOnUtaWtpdx1NSUoost2fPHurUqcPEiRNp0aIFnp6eJCQk3JXPy8uLUaNGsWXLFnr37s3ixYsNx1xdXRk2bBjr1q1j9OjRLFy48L71dXBwoGrVqsTExBAVFUXPnj1LfrNCCCGEEAVIMPuYmDt3LjqdjpYtW7J27VpiYmI4deoUs2fPpnXr1kWW8fT0JDExkdDQUOLi4pg9e7ah1xUgIyODoKAgIiIiSEhIYPfu3Rw4cID69dWdQEaOHMnmzZuJj48nOjqabdu2GY4VZfXq1URERHDu3Dk2btxIx44deemll+jUqdOjbQwhhBBCPDFkzOxjwt3dnejoaKZOncro0aO5fPkyVatWxdfXl/nz5xdZpkePHowaNYqgoCCysrLo1q0bISEhfPjhhwBotVquXbvGwIEDSU5OxsnJid69ezNlyhQAdDodgYGBXLx4EXt7e7p06cKsWbOKrePly5cJDg4mOTmZGjVqMHDgQEJCQh55WwghhBDiyaFRnrDZN6mpqTg4OHDz5s1CE50AMjMziY+Px83NrdASUqJ8yOchhBBCPJnuFa/9kwwzEEIIIYQQRkuCWSGEEEIIYbQkmBVCCCGEEEZLglkhhBBCCGG0JJgtwhM2J67Cks9BCCGEEPcjwWwBZmZmAKSnp5dzTQTkfw53PhchhBBCiH+SdWYL0Gq1ODo6cuXKFQCsra3RaDTlXKsnj6IopKenc+XKFRwdHdFqteVdJSGEEEJUUBLM/oOzszOAIaAV5cfR0dHweQghhBBCFEWC2X/QaDTUqFGDatWqkZOTU97VeWKZmZlJj6wQQggh7kuC2WJotVoJpoQQQgghKjiZACaEEEIIIYyWBLNCCCGEEMJoSTArhBBCCCGM1hM3ZvbOQvypqanlXBMhhBBCCFGUO3FaSTZQeuKC2Vu3bgHg6upazjURQgghhBD3cuvWLRwcHO6ZR6M8YXuG6vV6/vrrL+zs7Crchgipqam4urpy4cIF7O3ty7s6RkXa7uFJ2z08abuHJ2338KTtHp603cMr67ZTFIVbt27h4uKCicm9R8U+cT2zJiYm1KpVq7yrcU/29vbyj+whSds9PGm7hydt9/Ck7R6etN3Dk7Z7eGXZdvfrkb1DJoAJIYQQQgijJcGsEEIIIYQwWhLMViAWFhZMnjwZCwuL8q6K0ZG2e3jSdg9P2u7hSds9PGm7hydt9/Aqcts9cRPAhBBCCCHE40N6ZoUQQgghhNGSYFYIIYQQQhgtCWaFEEIIIYTRkmBWCCGEEEIYLQlmH6G5c+dSt25dLC0tadWqFfv37y82b05ODh999BEeHh5YWlrSpEkTwsLC7sp36dIlXnvtNapUqYKVlRWNGjUiKirKcPz1119Ho9EUenXp0qVU7q80Peq2q1u37l3totFoCAwMNOTJzMwkMDCQKlWqYGtrS58+fUhOTi61eywt5dF2zz333F3Hhw0bVmr3WFoeddvpdDpCQkJwc3PDysoKDw8PPv7440J7iyuKwgcffECNGjWwsrLC39+fmJiYUrvH0lIebSe/74puu1u3bjFy5Ejq1KmDlZUVbdq04cCBA4XyyHP38G33ODx3O3bsoHv37ri4uKDRaNiwYcN9y0RERNC8eXMsLCx46qmnWLJkyV157vd5lNnfWUU8EqGhoYq5ubmyaNEi5cSJE8rQoUMVR0dHJTk5ucj848aNU1xcXJRNmzYpcXFxyrx58xRLS0slOjrakOf69etKnTp1lNdff13Zt2+fcu7cOWXz5s1KbGysIc+gQYOULl26KJcvXza8rl+/Xur3+yiVRttduXKlUJv88ccfCqBs27bNkGfYsGGKq6urEh4erkRFRSn/+c9/lDZt2pT27T5S5dV27du3V4YOHVoo382bN0v7dh+p0mi7qVOnKlWqVFF+/fVXJT4+Xlm9erVia2urfPXVV4Y806dPVxwcHJQNGzYoR44cUXr06KG4ubkpGRkZpX7Pj0p5tZ38viu67fr166c0aNBA2b59uxITE6NMnjxZsbe3Vy5evGjII8/dw7fd4/Dc/fbbb8rEiROVdevWKYCyfv36e+Y/d+6cYm1trQQHBysnT55U5syZo2i1WiUsLMyQpySfR1n9nZVg9hFp2bKlEhgYaHiv0+kUFxcXZdq0aUXmr1GjhvL1118XSuvdu7cSEBBgeD9+/HjlmWeeued1Bw0apPTs2fPhK14BlEbb/dO7776reHh4KHq9XlEURUlJSVHMzMyU1atXG/KcOnVKAZTIyMh/cztlqjzaTlHUYPbdd9/9d5UvZ6XRdt26dVMGDx5cbB69Xq84Ozsrn3/+ueF4SkqKYmFhoaxYseJf31NZKY+2UxT5fXdHwXZJT09XtFqt8uuvvxbK07x5c2XixImKoshzV9CDtp2iPB7PXUElCWbHjRun+Pj4FEp7+eWXlc6dOxve3+/zKMu/szLM4BHIzs7m4MGD+Pv7G9JMTEzw9/cnMjKyyDJZWVlYWloWSrOysmLXrl2G9z///DMtWrSgb9++VKtWjWbNmrFw4cK7zhUREUG1atWoV68eb7/9NteuXXtEd1b6Sqvt/nmN5cuXM3jwYDQaDQAHDx4kJyen0HW9vb2pXbt2sdetaMqr7e748ccfcXJyomHDhkyYMIH09PR/eUdlp7Tark2bNoSHh3P27FkAjhw5wq5du+jatSsA8fHxJCUlFbqug4MDrVq1euKfu/u13R3y+65w2+Xm5qLT6e6ZR567fA/adncY83P3MCIjIwu1NUDnzp0NbV2Sz6Ms/85KMPsIXL16FZ1OR/Xq1QulV69enaSkpCLLdO7cmS+//JKYmBj0ej1//PEH69at4/Lly4Y8586dY/78+Xh6erJ582befvttRowYwdKlSw15unTpwg8//EB4eDgzZsxg+/btdO3aFZ1OVzo3+4iVVtsVtGHDBlJSUnj99dcNaUlJSZibm+Po6Fji61Y05dV2AK+++irLly9n27ZtTJgwgWXLlvHaa689kvsqC6XVdu+99x6vvPIK3t7emJmZ0axZM0aOHElAQACA4dwPct2KprzaDuT3XVFtZ2dnR+vWrfn444/566+/0Ol0LF++nMjISEMeee4evu3A+J+7h5GUlFRkW6emppKRkVGiz6Ms/86aPtKziRL76quvGDp0KN7e3mg0Gjw8PHjjjTdYtGiRIY9er6dFixZ8+umnADRr1ozjx4+zYMECBg0aBMArr7xiyN+oUSMaN26Mh4cHERERdOjQoWxvqoyUpO0K+v777+natSsuLi5lXNOK51G13VtvvWX4uVGjRtSoUYMOHToQFxeHh4dHqd5DeSlJ261atYoff/yRn376CR8fHw4fPszIkSNxcXEx/Jt9Ej2qtpPfd0W33bJlyxg8eDA1a9ZEq9XSvHlz+vfvz8GDB8ux5uXvUbXdk/jcGRvpmX0EnJyc0Gq1d83QS05OxtnZucgyVatWZcOGDaSlpZGQkMDp06extbXF3d3dkKdGjRo0aNCgULn69euTmJhYbF3c3d1xcnIiNjb2X9xR2SmttrsjISGBP//8kyFDhhRKd3Z2Jjs7m5SUlBJft6Ipr7YrSqtWrQCe+Odu7Nixhh7GRo0aMWDAAEaNGsW0adMADOd+kOtWNOXVdkWR33cqDw8Ptm/fzu3bt7lw4QL79+8nJyfHkEeeu4dvu6IY23P3MJydnYtsa3t7e6ysrEr0eZTl31kJZh8Bc3NzfH19CQ8PN6Tp9XrCw8Np3br1PctaWlpSs2ZNcnNzWbt2LT179jQca9u2LWfOnCmU/+zZs9SpU6fY8128eJFr165Ro0aNh7ybslVabXfH4sWLqVatGt26dSuU7uvri5mZWaHrnjlzhsTExPtet6Ior7YryuHDhwGe+OcuPT0dE5PCv1a1Wi16vR4ANzc3nJ2dC103NTWVffv2PfHP3f3arijy+64wGxsbatSowY0bN9i8ebMhjzx3D992RTG25+5htG7dulBbA/zxxx+Gti7J51Gmf2cf6XSyJ1hoaKhiYWGhLFmyRDl58qTy1ltvKY6OjkpSUpKiKIoyYMAA5b333jPk37t3r7J27VolLi5O2bFjh/L8888rbm5uyo0bNwx59u/fr5iamipTp05VYmJilB9//FGxtrZWli9friiKoty6dUsZM2aMEhkZqcTHxyt//vmn0rx5c8XT01PJzMws0/v/N0qj7RRFnVlZu3ZtZfz48UVed9iwYUrt2rWVrVu3KlFRUUrr1q2V1q1bl9p9lobyaLvY2Fjlo48+UqKiopT4+Hhl48aNiru7u/Lss8+W6r0+aqXRdoMGDVJq1qxpWF5q3bp1ipOTkzJu3DhDnunTpyuOjo7Kxo0blaNHjyo9e/Y0yiWSyrrt5Pdd8W0XFham/P7778q5c+eULVu2KE2aNFFatWqlZGdnG/LIc/dwbfe4PHe3bt1SDh06pBw6dEgBlC+//FI5dOiQkpCQoCiKorz33nvKgAEDDPnvLM01duxY5dSpU8rcuXOLXJrrXp+HopTd31kJZh+hOXPmKLVr11bMzc2Vli1bKnv37jUca9++vTJo0CDD+4iICKV+/fqKhYWFUqVKFWXAgAHKpUuX7jrnL7/8ojRs2FCxsLBQvL29lW+//dZwLD09XenUqZNStWpVxczMTKlTp44ydOjQQg+SsSiNttu8ebMCKGfOnCnymhkZGcrw4cOVSpUqKdbW1kqvXr2Uy5cvP/J7K21l3XaJiYnKs88+q1SuXFmxsLBQnnrqKWXs2LFGt86sojz6tktNTVXeffddpXbt2oqlpaXi7u6uTJw4UcnKyjLk0ev1SkhIiFK9enXFwsJC6dChQ7HPaEVW1m0nv++Kb7uVK1cq7u7uirm5ueLs7KwEBgYqKSkphfLIc/dwbfe4PHfbtm1TgLted9pr0KBBSvv27e8q07RpU8Xc3Fxxd3dXFi9efNd57/V5KErZ/Z3VKEqB7VWEEEIIIYQwIjJmVgghhBBCGC0JZoUQQgghhNGSYFYIIYQQQhgtCWaFEEIIIYTRkmBWCCGEEEIYLQlmhRBCCCGE0ZJgVgghhBBCGC0JZoUQQgghhNGSYFYIIZ5gGo2GDRs2AHD+/Hk0Gg2HDx8u1zoJIcSDkGBWCCHKyeuvv45Go0Gj0WBmZoabmxvjxo0jMzOzvKsmhBBGw7S8KyCEEE+yLl26sHjxYnJycjh48CCDBg1Co9EwY8aM8q6aEEIYBemZFUKIcmRhYYGzszOurq689NJL+Pv788cffwCg1+uZNm0abm5uWFlZ0aRJE9asWVOo/IkTJ3jxxRext7fHzs6Odu3aERcXB8CBAwfo2LEjTk5OODg40L59e6Kjo8v8HoUQojRJMCuEEBXE8ePH2bNnD+bm5gBMmzaNH374gQULFnDixAlGjRrFa6+9xvbt2wG4dOkSzz77LBYWFmzdupWDBw8yePBgcnNzAbh16xaDBg1i165d7N27F09PT1544QVu3bpVbvcohBCPmgwzEEKIcvTrr79ia2tLbm4uWVlZmJiY8PXXX5OVlcWnn37Kn3/+SevWrQFwd3dn165dfPPNN7Rv3565c+fi4OBAaGgoZmZmAHh5eRnO/fzzzxe61rfffoujoyPbt2/nxRdfLLubFEKIUiTBrBBClCM/Pz/mz59PWloas2bNwtTUlD59+nDixAnS09Pp2LFjofzZ2dk0a9YMgMOHD9OuXTtDIPtPycnJTJo0iYiICK5cuYJOpyM9PZ3ExMRSvy8hhCgrEswKIUQ5srGx4amnngJg0aJFNGnShO+//56GDRsCsGnTJmrWrFmojIWFBQBWVlb3PPegQYO4du0aX331FXXq1MHCwoLWrVuTnZ1dCncihBDlQ4JZIYSoIExMTHj//fcJDg7m7NmzWFhYkJiYSPv27YvM37hxY5YuXUpOTk6RvbO7d+9m3rx5vPDCCwBcuHCBq1evluo9CCFEWZMJYEIIUYH07dsXrVbLN998w5gxYxg1ahRLly4lLi6O6Oho5syZw9KlSwEICgoiNTWVV155haioKGJiYli2bBlnzpwBwNPTk2XLlnHq1Cn27dtHQEDAfXtzhRDC2EjPrBBCVCCmpqYEBQXx2WefER8fT9WqVZk2bRrnzp3D0dGR5s2b8/777wNQpUoVtm7dytixY2nfvj1arZamTZvStm1bAL7//nveeustmjdvjqurK59++iljxowpz9sTQohHTqMoilLelRBCCCGEEOJhyDADIYQQQghhtCSYFUIIIYQQRkuCWSGEEEIIYbQkmBVCCCGEEEZLglkhhBBCCGG0JJgVQgghhBBGS4JZIYQQQghhtCSYFUIIIYQQRkuCWSGEEEIIYbQkmBVCCCGEEEZLglkhhBBCCGG0/h8CoH3YgzLldAAAAABJRU5ErkJggg==\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Select random test samples\n",
        "num_samples = 50\n",
        "random_indices = np.random.choice(len(test_images), num_samples, replace=False)\n",
        "sample_images = test_images[random_indices]\n",
        "sample_labels = test_labels[random_indices]\n",
        "\n",
        "# Extract HOG features for sample images\n",
        "hog_features_sample = []\n",
        "for image in sample_images:\n",
        "    fd = hog(image, orientations=9, pixels_per_cell=(3, 3), cells_per_block=(2, 2), visualize=False)\n",
        "    hog_features_sample.append(fd)\n",
        "X_sample_hog = np.array(hog_features_sample)\n",
        "\n",
        "# Make predictions on sample images\n",
        "y_pred_sample = svm.predict(X_sample_hog)\n",
        "\n",
        "# Visualize sample images with predicted labels\n",
        "num_rows = (num_samples + 4) // 5\n",
        "fig, axs = plt.subplots(num_rows, 5, figsize=(12, 3 * num_rows))\n",
        "\n",
        "for i in range(num_samples):\n",
        "    row = i // 5\n",
        "    col = i % 5\n",
        "    axs[row, col].imshow(sample_images[i], cmap='gray')\n",
        "    axs[row, col].axis('off')\n",
        "    axs[row, col].set_title(f\"True: {sample_labels[i]}, Pred: {y_pred_sample[i]}\")\n",
        "\n",
        "for j in range(num_samples, num_rows * 5):\n",
        "    row = j // 5\n",
        "    col = j % 5\n",
        "    axs[row, col].axis('off')\n",
        "\n",
        "plt.tight_layout()\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "SMa5ZPannrWa",
        "outputId": "3d2ebe31-282b-4b55-b6c2-cef8d884023c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x3000 with 50 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Perhitungan akurasi, presisi, dan recall\n",
        "accuracy = accuracy_score(y_test, y_pred)\n",
        "precision = precision_score(y_test, y_pred, average='weighted')\n",
        "recall = recall_score(y_test, y_pred, average='weighted')\n",
        "\n",
        "print(\"Akurasi: \", accuracy)\n",
        "print(\"Presisi: \", precision)\n",
        "print(\"Recall: \", recall)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CzLRZowhn-E4",
        "outputId": "d6f74d69-e2fe-4362-ae78-78199195ff9f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Akurasi:  0.9817\n",
            "Presisi:  0.9817047703649084\n",
            "Recall:  0.9817\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import os\n",
        "import gzip\n",
        "import struct\n",
        "import urllib.request\n",
        "import numpy as np\n",
        "from skimage.feature import hog\n",
        "from sklearn.svm import SVC\n",
        "from sklearn.metrics import accuracy_score, precision_score, recall_score\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "\n",
        "def download_mnist(url, filepath):\n",
        "    if not os.path.exists(filepath):\n",
        "        urllib.request.urlretrieve(url, filepath)\n",
        "\n",
        "\n",
        "def read_mnist_labels(filepath):\n",
        "    with gzip.open(filepath, 'rb') as f:\n",
        "        magic, size = struct.unpack(\">II\", f.read(8))\n",
        "        labels = np.frombuffer(f.read(), dtype=np.uint8)\n",
        "    return labels\n",
        "\n",
        "\n",
        "def read_mnist_images(filepath):\n",
        "    with gzip.open(filepath, 'rb') as f:\n",
        "        magic, size, rows, cols = struct.unpack(\">IIII\", f.read(16))\n",
        "        images = np.frombuffer(f.read(), dtype=np.uint8).reshape(size, rows, cols)\n",
        "    return images\n",
        "\n",
        "\n",
        "# Download dataset training\n",
        "train_images_url = \"http://yann.lecun.com/exdb/mnist/train-images-idx3-ubyte.gz\"\n",
        "train_labels_url = \"http://yann.lecun.com/exdb/mnist/train-labels-idx1-ubyte.gz\"\n",
        "download_mnist(train_images_url, \"train-images-idx3-ubyte.gz\")\n",
        "download_mnist(train_labels_url, \"train-labels-idx1-ubyte.gz\")\n",
        "\n",
        "# Read training images and labels\n",
        "train_images = read_mnist_images(\"train-images-idx3-ubyte.gz\")\n",
        "train_labels = read_mnist_labels(\"train-labels-idx1-ubyte.gz\")\n",
        "\n",
        "# Extract features using HOG on training dataset\n",
        "hog_features = []\n",
        "for image in train_images:\n",
        "    fd = hog(image, orientations=9, pixels_per_cell=(8, 8), cells_per_block=(2, 2), visualize=False)\n",
        "    hog_features.append(fd)\n",
        "X_train_hog = np.array(hog_features)\n",
        "y_train = train_labels\n",
        "\n",
        "# Train SVM with HOG features\n",
        "svm = SVC(kernel='linear', decision_function_shape='ovr')\n",
        "svm.fit(X_train_hog, y_train)\n",
        "\n",
        "\n",
        "# Download dataset testing\n",
        "test_images_url = \"http://yann.lecun.com/exdb/mnist/t10k-images-idx3-ubyte.gz\"\n",
        "test_labels_url = \"http://yann.lecun.com/exdb/mnist/t10k-labels-idx1-ubyte.gz\"\n",
        "download_mnist(test_images_url, \"t10k-images-idx3-ubyte.gz\")\n",
        "download_mnist(test_labels_url, \"t10k-labels-idx1-ubyte.gz\")\n",
        "\n",
        "# Read testing images and labels\n",
        "test_images = read_mnist_images(\"t10k-images-idx3-ubyte.gz\")\n",
        "test_labels = read_mnist_labels(\"t10k-labels-idx1-ubyte.gz\")\n",
        "\n",
        "# Extract features using HOG on testing dataset\n",
        "hog_features_test = []\n",
        "for image in test_images:\n",
        "    fd = hog(image, orientations=9, pixels_per_cell=(8, 8), cells_per_block=(2, 2), visualize=False)\n",
        "    hog_features_test.append(fd)\n",
        "X_test_hog = np.array(hog_features_test)\n",
        "y_test = test_labels\n",
        "\n",
        "# Prediksi kelas menggunakan SVM\n",
        "y_pred = svm.predict(X_test_hog)\n",
        "\n",
        "# Perhitungan akurasi, presisi, dan recall\n",
        "accuracy = accuracy_score(y_test, y_pred)\n",
        "precision = precision_score(y_test, y_pred, average='weighted')\n",
        "recall = recall_score(y_test, y_pred, average='weighted')\n",
        "\n",
        "print(\"Akurasi: \", accuracy)\n",
        "print(\"Presisi: \", precision)\n",
        "print(\"Recall: \", recall)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PYCu4rVnLDNi",
        "outputId": "f3f4ab88-c5bd-4cf3-adf8-6bb457a6cc55"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Akurasi:  0.9575\n",
            "Presisi:  0.9575080711229844\n",
            "Recall:  0.9575\n"
          ]
        }
      ]
    }
  ]
}