{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "import tensorflow as tf\n",
        "from tensorflow.keras.models import Sequential\n",
        "from tensorflow.keras.layers import Dense\n",
        "from tensorflow.keras.utils import to_categorical\n",
        "from sklearn.datasets import load_iris\n",
        "from sklearn.model_selection import train_test_split\n",
        "import matplotlib.pyplot as plt"
      ],
      "metadata": {
        "id": "tRLElg03Gftp"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "iris = load_iris()\n",
        "X = iris.data  # Features\n",
        "y = iris.target"
      ],
      "metadata": {
        "id": "cGllboBDGfv9"
      },
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "y_encoded = to_categorical(y)"
      ],
      "metadata": {
        "id": "LeS5-HnXHEUX"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "X_train, X_test, y_train, y_test = train_test_split(X, y_encoded, test_size=0.2, random_state=42)\n"
      ],
      "metadata": {
        "id": "x3UeXZN0HEZR"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model = Sequential([\n",
        "    Dense(8, input_shape=(4,), activation='relu'),\n",
        "    Dense(3, activation='softmax')\n",
        "])"
      ],
      "metadata": {
        "id": "G1E9dC0lHEb9"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model.compile(optimizer='adam', loss='categorical_crossentropy', metrics=['accuracy'])"
      ],
      "metadata": {
        "id": "0rq5eknXHMHW"
      },
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "history = model.fit(X_train, y_train, epochs=100, batch_size=8, validation_split=0.2, verbose=0)\n",
        "\n",
        "# Step 6: Evaluate the Model\n",
        "loss, accuracy = model.evaluate(X_test, y_test, verbose=0)\n",
        "print(f\"Test Accuracy: {accuracy * 100:.2f}%\")\n",
        "\n",
        "# Step 7: Predict and Display Probabilities\n",
        "sample = np.array([[5.1, 3.5, 1.4, 0.2]])  # Example flower features\n",
        "prediction = model.predict(sample)\n",
        "predicted_class = np.argmax(prediction)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "VYBhUeQQHMJ5",
        "outputId": "ed5c4fb2-0d8f-46ac-c4c3-5b2c36450a2a"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Test Accuracy: 90.00%\n",
            "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 82ms/step\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "print(\"\\nPredicted Probabilities (Softmax Output):\", prediction)\n",
        "print(\"Predicted Class:\", iris.target_names[predicted_class])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fheRWibnHSB5",
        "outputId": "7dbcf4f9-0f6d-4f1d-dd11-cebaf541e0fd"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Predicted Probabilities (Softmax Output): [[9.6107572e-01 3.8675901e-02 2.4836522e-04]]\n",
            "Predicted Class: setosa\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "plt.figure(figsize=(10,4))\n",
        "\n",
        "plt.subplot(1, 2, 1)\n",
        "plt.plot(history.history['accuracy'], label='Train Accuracy')\n",
        "plt.plot(history.history['val_accuracy'], label='Validation Accuracy')\n",
        "plt.title('Model Accuracy')\n",
        "plt.xlabel('Epochs')\n",
        "plt.ylabel('Accuracy')\n",
        "plt.legend()\n",
        "\n",
        "plt.subplot(1, 2, 2)\n",
        "plt.plot(history.history['loss'], label='Train Loss')\n",
        "plt.plot(history.history['val_loss'], label='Validation Loss')\n",
        "plt.title('Model Loss')\n",
        "plt.xlabel('Epochs')\n",
        "plt.ylabel('Loss')\n",
        "plt.legend()\n",
        "\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 407
        },
        "id": "wmXUfaqqHSE1",
        "outputId": "ea66af4e-466e-43ef-b56c-434f14159eb2"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x400 with 2 Axes>"
            ],
            "image/png": 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8vKIoipKamqq8++67SlBQkOLg4KDY2dkpQUFByg8//JBnjEKUFipFeaTvpRBCiDwFBwfj6upKSEiIqUMRQgghhBAlnIzpFkKIQjh06BChoaEMGjTI1KEIIYQQQohSQFq6hRCiAE6ePMnhw4eZNm0asbGxXLx4UT/bqhBCCCGEELmRlm4hhCiAlStXMnToUNLT0/n9998l4RZCCCGEEAUiLd1CCCGEEEIIIYSRSEu3EEIIIYQQQghhJJJ0CyGEEEIIIYQQRmJu6gCKm1ar5caNGzg4OKBSqUwdjhBCCJGFoijcvXsXb29v1Oon+7dxuWYLIYQoyQp6zX7iku4bN27g4+Nj6jCEEEKIPF29epWKFSuaOgwApkyZwurVqzlz5gw2NjY0b96cr776imrVquVaZ+HChQwdOjTLPisrK1JSUgp8XrlmCyGEKA3yu2Y/cUm3g4MDoPtiHB0dTRyNEEIIkVVCQgI+Pj7661VJsGPHDkaPHk2jRo3IyMjgww8/5JlnnuH06dPY2dnlWs/R0ZGzZ8/qXxe2tVqu2UIIIUqygl6zn7ikO/OC7+joKBdwIYQQJVZJ6k69YcOGLK8XLlyIu7s7hw8fplWrVrnWU6lUeHp6Fvm8cs0WQghRGuR3zX6yB4sJIYQQotDi4+MBcHV1zbNcYmIivr6++Pj40L17d06dOpVn+dTUVBISErJsQgghRGknSbcQQgghCkyr1TJ27FhatGhB7dq1cy1XrVo15s+fz19//cVvv/2GVqulefPmXLt2Ldc6U6ZMwcnJSb/JeG4hhBBlgUpRFMXUQRSnhIQEnJyciI+Pl65qQgghSpySfp169dVXWb9+Pbt37y7URG/p6enUqFGDAQMG8Nlnn+VYJjU1ldTUVP3rzLFyJfW7EEII8WQr6DX7iRvTXVAajYb09HRThyGEwVlYWGBmZmbqMIQQpdCYMWP4559/2LlzZ6FnVrewsCA4OJgLFy7kWsbKygorK6vHDVMI8QSSe3dhDIa6b5ak+xGKohAVFUVcXJypQxHCaJydnfH09CxREzUJIUouRVF4/fXX+fPPP9m+fTv+/v6FPoZGo+HEiRN06dLFCBEKIZ5Ucu8ujM0Q982SdD8i8x+tu7s7tra2kpSIMkVRFO7du0dMTAwAXl5eJo5ICFEajB49mqVLl/LXX3/h4OBAVFQUAE5OTtjY2AAwaNAgKlSowJQpUwCYPHkyTZs2pUqVKsTFxfHNN99w5coVRowYYbLPIYQoe+TeXRiLIe+bJel+iEaj0f+jLVeunKnDEcIoMm+QY2JicHd3l67mQoh8/fjjjwC0adMmy/4FCxYwZMgQACIiIlCrH8zPeufOHUaOHElUVBQuLi40aNCAvXv3UrNmzeIKWwhRxsm9uzA2Q903m3T28p07d9KtWze8vb1RqVSsWbMm3zrbt2+nfv36WFlZUaVKFRYuXGiweDLHgdja2hrsmEKURJl/x2XskxCiIBRFyXHLTLhBd31++Jr83XffceXKFVJTU4mKimLdunUEBwcXf/BCiDJL7t1FcTDEfbNJk+6kpCSCgoKYPXt2gcpfunSJrl270rZtW0JDQxk7diwjRoxg48aNBo1LuqWIsk7+jgshhBCirJD7GmFMhvj7ZdLu5Z07d6Zz584FLj9nzhz8/f2ZNm0aADVq1GD37t189913dOzY0VhhCiGEEEIIIYQQRVKqxnTv27eP9u3bZ9nXsWNHxo4dm2udnNb8FAXj5+fH2LFj8/x+hRCl2J3LsOY1aP46VCvAD6AnVsK2L0H7UPcqe0/ovxTs3fKuqyjwz1ugUkPXaVDYX41vhcOKIZAS92CfuTV0/hoqt81e/tSfEPLZI7F63I/VPXv5jR9B2NrCxfQoz7rQf8njHUMYh1YLvzwNty/B6APg4GHqiIQQwuDk3r3kMmn38sKKiorCwyPrhdLDw4OEhASSk5NzrDNlyhScnJz0m4+PT3GEWqxUKlWe26RJk4p03IMHDzJq1CiDxPj7779jZmbG6NGjDXI8IYQBHJgLV/bAjq8LVn73d3A7HOIiHmzXDsDJVfnXjTkNhxfAoXkQe67wsR5ZBFHHs5479hzsy2V40q7pOcR6EE6syF42KRb2zcpatihbYnThP5coHmq17s85JQ7irpg6GiHEE64k37u3adNGknYjKFUt3UUxfvx4xo0bp3+dkJBQ5hLvyMhI/fPly5czYcIEzp49q99nb2+vf64oChqNBnPz/P/o3dzyabkqhHnz5vHee+/x008/MW3aNKytrQ127MJKS0vD0tLSZOcXosS4uF33eOMo3LsNtq65l02MgeiTuueD/wYLOzi1WpesXtwGTV/J+1zh27I+d6tWuFgz67ebCP6tIf4qrBis+9EgIxXMrR6UTYrVJegAg/4CSwc4/Sfs/V53nGaP/PiX+T24VYfuPxQurodZ2hW9rjA+Z1/d35s7V8CnsamjEUI8wUrDvbswrFLV0u3p6Ul0dNaWhOjoaBwdHfXTuT/KysoKR0fHLFtZ4+npqd+cnJxQqVT612fOnMHBwYH169fToEEDrKys2L17N+Hh4XTv3h0PDw/s7e1p1KgRW7ZsyXJcPz8/ZsyYoX+tUqn45Zdf6NmzJ7a2tgQGBrJ2bf7dMS9dusTevXv54IMPqFq1KqtXr85WZv78+dSqVQsrKyu8vLwYM2aM/r24uDhefvllPDw8sLa2pnbt2vzzzz8ATJo0iXr16mU51owZM/Dz89O/HjJkCD169OCLL77A29ubatV0N/uLFy+mYcOGODg44OnpycCBA/Xr8GU6deoUzz77LI6Ojjg4ONCyZUvCw8PZuXMnFhYW+rVqM40dO5aWLVvm+50IYXIPJ9EocGln3uUzE1PPuuDfCio2gLp9dfsu7wZNPjN6XtyW8/OCeDiJDn5Rd+6a3cHODdLvwdUDOcfqURsC2tyPtb9uX2aSnlNsVdrryhZ1c69euM8lipeLr+7xzmWThiGEECX93j0vq1at0t+z+/n56efayvTDDz8QGBiItbU1Hh4e9O7dW//eypUrqVOnDjY2NpQrV4727duTlJT0WPGUFqUq6W7WrBkhISFZ9m3evJlmzZoZ7ZyKonAvLcMkm6IoBvscH3zwAVOnTiUsLIy6deuSmJhIly5dCAkJ4ejRo3Tq1Ilu3boRERGR53E+/fRT+vbty/Hjx+nSpQsvvPACt2/fzrPOggUL6Nq1K05OTrz44ovMmzcvy/s//vgjo0ePZtSoUZw4cYK1a9dSpUoVALRaLZ07d2bPnj389ttvnD59mqlTpxZ6jbyQkBDOnj3L5s2b9Ql7eno6n332GceOHWPNmjVcvnw5y/I3169fp1WrVlhZWbF161YOHz7MsGHDyMjIoFWrVgQEBLB48WJ9+fT0dJYsWcKwYcMKFZsQJnFxxyOvt+dT/v77AW0e7POoA7blIC0Rrh3KvW5GKlzZ++B1QZL0h126H6t7rQfjsVWqB7E8GntmEv1wrO41HyTp1w4+2K8oEH6/fkAOY8NF2eF8P+mOu2zSMIQQxmWqe3dD3reDae/dc3P48GH69u1L//79OXHiBJMmTeKTTz7RLxd56NAh3njjDSZPnszZs2fZsGEDrVq1AnSt+wMGDGDYsGGEhYWxfft2evXqZfDvraQyaffyxMRELly4oH996dIlQkNDcXV1pVKlSowfP57r16/z66+/AvDKK68wa9Ys3nvvPYYNG8bWrVv5448/WLdundFiTE7XUHOCYZckK6jTkztia2mYP6LJkyfToUMH/WtXV1eCgoL0rz/77DP+/PNP1q5dm6WV+VFDhgxhwIABAHz55ZfMnDmTAwcO0KlTpxzLa7VaFi5cyPfffw9A//79efvtt7l06RL+/v4AfP7557z99tu8+eab+nqNGjUCYMuWLRw4cICwsDCqVq0KQEBAQKE/v52dHb/88kuWbuUPJ8cBAQHMnDmTRo0akZiYiL29PbNnz8bJyYlly5ZhYWEBoI8BYPjw4SxYsIB3330XgL///puUlBT69u1b6PiEKHaZial7Td1467xanxXlQffuhyctU6t1Xb1PrdbV983lB9CrB3TJrp07aDMg+bYuSc+t/KNyOjfokuQTK3TnbvfJQ7Fuf/D+w7EGtNGVD98Gfk/p9t8Kh4RrYGYJvs0LFo8onfQt3TKmW4iyzFT37oa8bwfT3bvnZfr06bRr145PPtFdc6tWrcrp06f55ptvGDJkCBEREdjZ2fHss8/i4OCAr68vwcHBgC7pzsjIoFevXvj66v4/rlOnTqFjKK1M2tJ96NAhgoOD9X8Y48aNIzg4mAkTJgC6P5yHf73x9/dn3bp1bN68maCgIKZNm8Yvv/wiy4UVQMOGDbO8TkxM5J133qFGjRo4Oztjb29PWFhYvr+W1a1bV//czs4OR0fHbF2yH7Z582aSkpLo0qULAOXLl6dDhw7Mnz8fgJiYGG7cuEG7du1yrB8aGkrFihWzJLtFUadOnWzjuA8fPky3bt2oVKkSDg4OtG7dGkD/HYSGhtKyZUt9wv2oIUOGcOHCBf777z8AFi5cSN++fbGzk3GdooR7OIluMx7U5rout7cv5Vw+9hzcvQFmVlDpkUQ5MxEOzyNpf7jlOaB11n0FiVXfyv5I0p157htHIfmO7nleSXRm/Zy6uvs0AUvbgsUkSid9S7ck3UKIks9U9+55CQsLo0WLFln2tWjRgvPnz6PRaOjQoQO+vr4EBATw0ksvsWTJEu7duwdAUFAQ7dq1o06dOvTp04e5c+dy586dIsVRGpm0pbtNmzZ5dinI7KrwaJ2jR48aMaqsbCzMOD3ZNEm9jUXhulDn5dFE8J133mHz5s18++23VKlSBRsbG3r37k1aWlqex3k0AVWpVGi12lzLz5s3j9u3b2cZc6/Vajl+/DiffvpprmPxM+X3vlqtzvZ3KD09e7fVRz9/UlISHTt2pGPHjixZsgQ3NzciIiLo2LGj/jvI79zu7u5069aNBQsW4O/vz/r169m+fXuedYQoER5OogM7QMVGELFPl4C6+mcvn5lQ+zYDi0f+XWQmstcPQ0o8WDvlXr9yW1238lN/6va1/TD/WG+F6ya/MrPM3jLu6A3lq0HsWbi0C2o+l3cSndndPDNJt3HJvRVdlD2ZLd3x10GTAWZlfi5ZIZ5Iprp3N+R9O5ju3v1xODg4cOTIEbZv386mTZuYMGECkyZN4uDBgzg7O7N582b27t3Lpk2b+P777/noo4/Yv3+/vvdrWSZXnHyoVCqDdhUpKfbs2cOQIUPo2bMnoPv17PLlywY9x61bt/jrr79YtmwZtWrV0u/XaDQ89dRTbNq0iU6dOuHn50dISAht22a/6a1bty7Xrl3j3LlzObZ2u7m5ERUVhaIoqO6v+xsaGppvbGfOnOHWrVtMnTpVP5v9oUNZx6TWrVuXRYsWkZ6enmtr94gRIxgwYAAVK1akcuXK2X79E6JEymw5zkyiA9reT7q3Q8Mc5iTIaTx3JmcfcK2sW57r8m6o3jXr+8l3dEluZn1thu55Xkl6lnM/nETn0IskoI0u6b64TZd0hz/Uqv4opwpQvqruR4dLu6BaF7i8K/fyomyx99T90KRJ1fWGcPEzdURCCCOQe3fjqVGjBnv27MkWV9WqVfXzLZmbm9O+fXvat2/PxIkTcXZ2ZuvWrfTq1QuVSkWLFi1o0aIFEyZMwNfXlz///DPLSlNlVamaSE0YTmBgIKtXryY0NJRjx44xcOBAg//qtXjxYsqVK0ffvn2pXbu2fgsKCqJLly76CdUmTZrEtGnTmDlzJufPn+fIkSP6MeCtW7emVatWPP/882zevJlLly6xfv16NmzYAOh6Pty8eZOvv/6a8PBwZs+ezfr16/ONrVKlSlhaWvL9999z8eJF1q5dy2effZalzJgxY0hISKB///4cOnSI8+fPs3jx4ixLOnTs2BFHR0c+//xzhg4daqivTgjjejQxzWzlvbgDtJqsZTXpumQacp9oLK8u5pd2AoquRdrRG5wr6ZJ0RfPguHnJK+F/9NyajAdJdG4t1w93Mb9+GFITwNoZvOrlH4so3dRq3Y9EIOO6hRClTnHcu2e6efMmoaGhWbbo6GjefvttQkJC+Oyzzzh37hyLFi1i1qxZvPPOOwD8888/zJw5k9DQUK5cucKvv/6KVqulWrVq7N+/ny+//JJDhw4RERHB6tWruXnzJjVq1DDKZyhpJOl+Qk2fPh0XFxeaN29Ot27d6NixI/Xr1zfoOebPn0/Pnj31LdAPe/7551m7di2xsbEMHjyYGTNm8MMPP1CrVi2effZZzp8/ry+7atUqGjVqxIABA6hZsybvvfceGo0uMahRowY//PADs2fPJigoiAMHDuj/4efFzc2NhQsXsmLFCmrWrMnUqVP59ttvs5QpV64cW7duJTExkdatW9OgQQPmzp2bpdVbrVYzZMgQNBoNgwYNKupXJUTxySmJ9q4PVo6QEgeRoVnLXzsEaXd1s5R71iVHOY2VzpRT9+2CjAMHXRKduZRZbkm031P3x6Rf0nVbzy+J1v/AsP2hhL41qA3bLVCUUDKuWwhRShXHvXumpUuX6ufdytzmzp1L/fr1+eOPP1i2bBm1a9dmwoQJTJ48Wb/6j7OzM6tXr+bpp5+mRo0azJkzh99//51atWrh6OjIzp076dKlC1WrVuXjjz9m2rRpdO7c2SifoaRRKU/KPO33JSQk4OTkRHx8fLY1u1NSUvSzaltbW5soQlHaDB8+nJs3bz72uofFSf6ul05arcI7K44RGZ/Ct32DqOCcdXz1lVtJvLEslAvRd3M9RkP1WRYxAcXGFdW74brWP4DfB8LZdfD0J9BK98PVvN2XMN8xhcHpy6FWL+izIOeDpsSjfOWHStHSXvmBSKWc/q31qjeopIrmNe177KABAO04wEz1NC4pXjyrzMg11mD1eX7jYxRrZ1TvXcw9MZ7fCSL2cV3lQQUlWreGd99fcy6behem+upa2l384M5lUjpN483z9Yi5m8rM/sH4uGYdC3719j3eWHaUc1G5f68AQT7OLB3ZNM8yBZHXdepJY/Dv4p+34NB8aPnOgxnvhRClltzPiOKQ19+zgl6npKVbiCKKj49n9+7dLF26lNdff93U4YgnwL8nI1l99Dr7Lt6i9497uRCTqH8vLDKB3nP2cexqHElpmly34IxQAI6Y1SXt4V5pD7UAK4rCVxvO8Nk/p6mVqhuPvZfcl/W4iy3nzXVzLgRnhOrP5Zp+g0qqaNIVM3akVdPv355WHY2iwl8ViVNadO6xputiPWpel9RcetApisIebW0AXcIN7FXyWILEykE3cRzoZmwHRv/nxMZT0RyNiOP5H/dy7qEfLc5F36X3nL0cjcj7e01K05CcrsnhhKJEkZZuIYQQJlD2ZhkQoph0796dAwcO8Morr2RZR1EIY0jXaPl2o24+AWsLNZHxKfT9aR+LhjYmTaNh6IKDJKRkUN3TgRn962FrkfN/73a/fQ134I87gcz89RBzXmyAjaWZvou4cnU/k1YfYtHBGBy4R7D6AgDvHnalv+t5xjxdJcuQkdtJaQxZcIB2yTWoan6Gdypf5/XuumPZnVwM20Dj3YD1vbtkiSNjRX3Mog7zd9cMkmrm3HXcduk0uAUr7wTy3aJD/PRSgyyT42i1ChPWnuR0eAVaWD2o935oOZ4vd4432wXmOLyFym3hqm6pvxsqT0KibHG1s8TVzpILMYn0/WkfC4Y0QqVSMWTBAeLupVPVw54Z/YKxt8r9smlpLr9jl3iZk6fJmG4hhBDFSJJuIYpIlgczIkXRjSVOKto6ksVJURQibifj4WiFdQGWC0nXaLl6JxnfcraY5ZQQ5mLP2ZsE3rlCfVtzxneuwU87w7ly6x4/z92PVqvQRKOlsoc9rz9dBbu4XTkfRJsBcScAOKQOIvzcTV6at5+RrQJQKXa0tPXG5t4N7I78zDNmFRlTMwWz81ruWFfieoob0zafI+ZuKi0Dy+sOpyh8s/Es4TeTcLMNBu2feMT+Bzfvj9W+9DcA1tXaU6ncI8t3VW0HUYcpd2kt5dw8c4hVA3eO6WI1C+Lc+Vhe/GU/L7euTOa3tvbYDf45Hom5qjJp5vZYZiQSZ12BqykezNhynpt3U2ld1S3boZ1UdWly//m29Fp4O1mzeEQTytlZMmTBQUKvxvHCL/tRAUlpGoJ8nFk4pBEudpYF/eMSJZWLtHQLIYQofjKm+yEyLkQ8KUr83/VLO2FRN1NHUXa5VuZw9y361vFMX5n/TD/z7dnLNxrBfKcxTP7ndI6H83KyZvGQ+lRZUBvSErMXGL4ZfBpn3Xd5Dyzskr3so1z8ONJzO0MXHCQ+OT3b2+ZqFdP71eO50+/oxqQ3GMoC1zf59O+cYwUwQ0Oo1SgcVMlMtH6fUa+8pR8fn5SawajFh9hz4RYAzSuX4+dBDfNs4TY0GdP9gMG/i3u34ev768F+FJV93XkhRKlS4u9nRJlgiDHd0tIthCh5Ys/pHm1coFygaWPJhRaFK7fucTspTb/PwkxNoLs9Njm0eKdptFyIScwy7tfB2pzKbvb5tnhHJqRwIy4ZK3M1Nb0dUd9v69UqCtfjklEB3i42+v15UptB09do4OvK8peb8e3Gs9y5p/sMezL6UzMpAV8HBUfr+7P0W9lDk1cYVt4fd0crFu+7QrrmwQBrTydrPuxSg4outvDM53Dsd11PBX2BOlChYfY4KjWFBkMh+lTesTZ5hfqVXPjj5WZ8s/FMlu/bxtKMl1tVplVVN/AYryv/1FiGuvjh7mDNr/suZ4n1YQuSX6OB2TleH/o65Z0eJF52VubMH9KIrzecRVHgvU7VCtSDQZQSNi66mfpTEyAuAtyqmToiIYQQTwBp6X6I/FomnhQl/u/6zm9h62cQ/CJ0n23qaLJJSdcwZukRtoTFYK5W8XHXGizZH8H5mERcbC1YOLQxQT7O+vJXbiXx4rz9XL3fDX1s+6p8/s/pAnVdvp2URquvt5GYmsH/+teje70KxfQphalIS/cDRvkufnwKok/AwBVQ9RnDHFMIYRIl/n5GlAnS0i2EKJuS7+gerZ2Ncvi/Qq+z8VRUketfvJnEmai7WJmr+fHF+jxd3YPu9SowZOFBjl2NY+Dc/2hV1Y3MBuwDl+4Qm5iKbzlbfhveBB9XW2p6OTJkwQGOXY2jxw97qOWd83/U1+4kk5iaQS1vR7rV9S5yzEKI+1x8dUm3jOsWQghRTCTpFkKUPClxukcbZ4Mf+urte7yz4hjpmsfr5ONgZc4vgxvSJEC3JrWLnSVLRjRh1K+H2Bt+i/Unsyb11T0d+HVYY9wddb+QBvk488fLzXhp3gGu3LrHlVv38jzf+52qo1YXfOI1IUQuMpcNu79knBBCCGFsknQLIUqe5DjdoxFauqdvPke6RiG4kjO9govWVVulUtG6qhs+rlln5La3MmfB0EZsPBVN/L2Hxx6b07GWBw6Z46TvC/Rw4O/Xn2JLWDQZuYw9BqjoaqsbtyyEeHwuknQLIYQoXpJ0C702bdpQr149ZsyYAYCfnx9jx45l7NixudZRqVT8+eef9OjR47HObajjiDIiJV73aONS5EMoipJtjebTNxJYE3odgM+616Z2BaciHz83VuZmPBdU8G7gbg5WDGhcyeBxCCFy4SzLhgkhyga5dy891KYOQDy+bt260alTpxzf27VrFyqViuPHjxf6uAcPHmTUqFGPG14WkyZNol69etn2R0ZG0rlzZ4OeKzfJycm4urpSvnx5UlNTi+WcopAeo6U7XaNl/OoTNPh8C+uOR2Z57+uNZ1AU6BbkbZSEWwhRCuhbuiNMG4cQ4okl9+4Fs3DhQpydnY16juIiSXcZMHz4cDZv3sy1a9eyvbdgwQIaNmxI3bp1C31cNzc3bG1t8y9oAJ6enlhZWRXLuVatWkWtWrWoXr06a9asKZZz5kZRFDIyMvIv+KTJnEitkC3dKekaXv3tCL8fiOB2Uhqv/36EZQd0N9Z7w2PZfvYm5moV7zxT1dARCyFKC+f7PUtS4x/8XyOEEMVI7t2fPJJ0lwHPPvssbm5uLFy4MMv+xMREVqxYwfDhw7l16xYDBgygQoUK2NraUqdOHX7//fc8j+vn56fvrgJw/vx5WrVqhbW1NTVr1mTz5s3Z6rz//vtUrVoVW1tbAgIC+OSTT0hPTwd0v1Z9+umnHDt2DJVKhUql0sesUqmyJMAnTpzg6aefxsbGhnLlyjFq1CgSExP17w8ZMoQePXrw7bff4uXlRbly5Rg9erT+XHmZN28eL774Ii+++CLz5s3L9v6pU6d49tlncXR0xMHBgZYtWxIeHq5/f/78+dSqVQsrKyu8vLwYM2YMAJcvX0alUhEaGqovGxcXh0qlYvv27QBs374dlUrF+vXradCgAVZWVuzevZvw8HC6d++Oh4cH9vb2NGrUiC1btmSJKzU1lffffx8fHx+srKyoUqUK8+bNQ1EUqlSpwrfffpulfGhoKCqVigsXLuT7nZQ4RZhI7W5KOkMWHGBLWDRW5mra13BHq8AHq08wZ0c4X204C8DAJpXwLWdn+JiFEKWDpR3Y3Z8j4Y50MRdCFD+5dy/cvXtuIiIi6N69O/b29jg6OtK3b1+io6P17x87doy2bdvi4OCAo6MjDRo04NChQwBcuXKFbt264eLigp2dHbVq1eLff/8tciz5kTHd+VEUSM97VmGjsbAFVf6zFZubmzNo0CAWLlzIRx99pB/HumLFCjQaDQMGDCAxMZEGDRrw/vvv4+joyLp163jppZeoXLkyjRs3zvccWq2WXr164eHhwf79+4mPj89xvIiDgwMLFy7E29ubEydOMHLkSBwcHHjvvffo168fJ0+eZMOGDfqE0skpexffpKQkOnbsSLNmzTh48CAxMTGMGDGCMWPGZPnPadu2bXh5ebFt2zYuXLhAv379qFevHiNHjsz1c4SHh7Nv3z5Wr16Noii89dZbXLlyBV9fXXfD69ev06pVK9q0acPWrVtxdHRkz549+tboH3/8kXHjxjF16lQ6d+5MfHw8e/bsyff7e9QHH3zAt99+S0BAAC4uLly9epUuXbrwxRdfYGVlxa+//kq3bt04e/YslSrpWmUGDRrEvn37mDlzJkFBQVy6dInY2FhUKhXDhg1jwYIFvPPOO/pzLFiwgFatWlGlSpVCx2dSmnRIu/+f9P3u5WkZWraeiSE+OS3Xakv2R3D8Wjz2mbOK+7vy9caz/Lg9nKnrzwBga2nG608HGvsTCCFKOmdfSLqpG9ftXc/U0QghDMlU9+4FvG8HuXcvzL17Xp8vM+HesWMHGRkZjB49mn79+ukbu1544QWCg4P58ccfMTMzIzQ0FAsL3aS2o0ePJi0tjZ07d2JnZ8fp06ext7cvdBwFJUl3ftLvwZcmWhv3wxu6X+QLYNiwYXzzzTfs2LGDNm3aALqk6/nnn8fJyQknJ6csCdnrr7/Oxo0b+eOPPwr0D3fLli2cOXOGjRs34u2t+z6+/PLLbGM5Pv74Y/1zPz8/3nnnHZYtW8Z7772HjY0N9vb2mJub4+npmeu5li5dSkpKCr/++it2drrPP2vWLLp168ZXX32Fh4cHAC4uLsyaNQszMzOqV69O165dCQkJyfMf7vz58+ncuTMuLrpuyx07dmTBggVMmjQJgNmzZ+Pk5MSyZcv0/yirVn3QFfnzzz/n7bff5s0339Tva9SoUb7f36MmT55Mhw4d9K9dXV0JCgrSv/7ss8/4888/Wbt2LWPGjOHcuXP88ccfbN68mfbt2wMQEBCgLz9kyBAmTJjAgQMHaNy4Menp6SxdujRb63epkDmJGoC1E/fSMnh58WF2nY/Nt6qrnSWLhjamTkXdBeH9TtVxsrHQJ90jWgbg5iBdoYR44rn4wvVD0tItRFlkqnv3Qty3g9y7F/TePTchISGcOHGCS5cu4ePjA8Cvv/5KrVq1OHjwII0aNSIiIoJ3332X6tWrAxAY+KDhJSIigueff546deoAWe+rjUGS7jKievXqNG/enPnz59OmTRsuXLjArl27mDx5MgAajYYvv/ySP/74g+vXr5OWlkZqamqBx32EhYXh4+Oj/0cL0KxZs2zlli9fzsyZMwkPDycxMZGMjAwcHR0L9VnCwsIICgrS/6MFaNGiBVqtlrNnz+r/4daqVQszMzN9GS8vL06cOJHrcTUaDYsWLeJ///ufft+LL77IO++8w4QJE1Cr1YSGhtKyZUt9wv2wmJgYbty4Qbt27Qr1eXLSsGHDLK8TExOZNGkS69atIzIykoyMDJKTk4mI0I1HDg0NxczMjNatW+d4PG9vb7p27cr8+fNp3Lgxf//9N6mpqfTp0+exYy12mZOoWToQn6owdOEBjkTEYWtpRtOAcuT2G7KTjQWjn65CZbesv1K+0royvq62hF6L49XWlY0auhCilHDx0z3KDOZCCBORe/f8793zO6ePj48+4QaoWbMmzs7OhIWF0ahRI8aNG8eIESNYvHgx7du3p0+fPlSurLsXfOONN3j11VfZtGkT7du35/nnny/SOPqCkqQ7Pxa2ul+uTHXuQhg+fDivv/46s2fPZsGCBVSuXFmfpH3zzTf873//Y8aMGdSpUwc7OzvGjh1LWlru3XULa9++fbzwwgt8+umndOzYUd9iPG3aNIOd42GPJsYqlQqtNve1jjdu3Mj169fp169flv0ajYaQkBA6dOiAjY1NrvXzeg9ArdZNkaAoin5fbuNUHv5PCeCdd95h8+bNfPvtt1SpUgUbGxt69+6t//PJ79wAI0aM4KWXXuK7775jwYIF9OvXr9gm0zCo++O5NdbO9Pt5H2ei7uJkY8GCoY2oX6loS4h1ruNF5zpeBgxSCFGqZS4bJi3dQpQ9prp3L+R9O8i9e3737o9r0qRJDBw4kHXr1rF+/XomTpzIsmXL6NmzJyNGjKBjx46sW7eOTZs2MWXKFKZNm8brr79ulFhkIrX8qFS6riKm2Ao4LiRT3759UavVLF26lF9//ZVhw4bpx4js2bOH7t278+KLLxIUFERAQADnzp0r8LFr1KjB1atXiYx8sATTf//9l6XM3r178fX15aOPPqJhw4YEBgZy5UrWGxpLS0s0Gk2+5zp27BhJSUn6fXv27EGtVlOtWrUCx/yoefPm0b9/f0JDQ7Ns/fv310+oVrduXXbt2pVjsuzg4ICfnx8hISE5Ht/NTTcxz8Pf0cOTquVlz549DBkyhJ49e1KnTh08PT25fPmy/v06deqg1WrZsWNHrsfo0qULdnZ2/Pjjj2zYsIFhw4YV6NwlQUq6hnF/hNL/531MXb0XgAt3zTkTdRc3ByuWv9y0yAm3EEJk4yJrdQtRZpnq3r2Q9+0g9+6PI/PzXb16Vb/v9OnTxMXFUbNmTf2+qlWr8tZbb7Fp0yZ69erFggUL9O/5+PjwyiuvsHr1at5++23mzp1rlFhBku4yxd7enn79+jF+/HgiIyMZMmSI/r3AwEA2b97M3r17CQsL4+WXX84yu19+2rdvT9WqVRk8eDDHjh1j165dfPTRR1nKBAYGEhERwbJlywgPD2fmzJn8+eefWcr4+flx6dIlQkNDiY2NzXGd7BdeeAFra2sGDx7MyZMn2bZtG6+//jovvfSSvntKYd28eZO///6bwYMHU7t27SzboEGDWLNmDbdv32bMmDEkJCTQv39/Dh06xPnz51m8eDFnz+pmvp40aRLTpk1j5syZnD9/niNHjvD9998Dutbopk2bMnXqVMLCwtixY0eWcTJ5CQwMZPXq1YSGhnLs2DEGDhyY5Zc/Pz8/Bg8ezLBhw1izZg2XLl1i+/bt/PHHH/oyZmZmDBkyhPHjxxMYGJhjF6KSKiQshtVHrvPfxdvciIoC4FaGDT6uNqx6pTnVPQvXzUkIIfKU2dIdF6GbdEkIIUxA7t3zp9FosjWYhYWF0b59e+rUqcMLL7zAkSNHOHDgAIMGDaJ169Y0bNiQ5ORkxowZw/bt27ly5Qp79uzh4MGD1KhRA4CxY8eyceNGLl26xJEjR9i2bZv+PWOQpLuMGT58OHfu3KFjx45ZxnB8/PHH1K9fn44dO9KmTRs8PT3p0aNHgY+rVqv5888/SU5OpnHjxowYMYIvvvgiS5nnnnuOt956izFjxlCvXj327t3LJ598kqXM888/T6dOnWjbti1ubm45Ln1ga2vLxo0buX37No0aNaJ37960a9eOWbNmFe7LeEjmxA45jcdu164dNjY2/Pbbb5QrV46tW7eSmJhI69atadCgAXPnztV3hxk8eDAzZszghx9+oFatWjz77LOcP39ef6z58+eTkZFBgwYNGDt2LJ9//nmB4ps+fTouLi40b96cbt260bFjR+rXr5+lzI8//kjv3r157bXXqF69OiNHjszyiyLo/vzT0tIYOnRoYb8ikwq9qlsr9+nq7oxspGvRDvCpwLo3WlKpXCnsIi+EKNmcKoLKDDJS4G5k/uWFEMJI5N49b4mJiQQHB2fZunXrhkql4q+//sLFxYVWrVrRvn17AgICWL58OaBrjLp16xaDBg2iatWq9O3bl86dO/Ppp58CumR+9OjR1KhRg06dOlG1alV++OGHx443NypFMe1PvLNnz+abb74hKiqKoKAgvv/++1xn5EtPT2fKlCksWrSI69evU61aNb766is6depU4PMlJCTg5OREfHx8tkkCUlJSuHTpEv7+/lhbWz/W5xLCFHbt2kW7du24evVqnr8slrS/633m7OXg5Tt82yeI3om/w7bPIfgl6P74/1kLUdrkdZ160hj1u5gZDLcvwuC/wb+VYY8thCgWJe1+RpRNef09K+h1yqQt3cuXL2fcuHFMnDiRI0eOEBQURMeOHYmJicmx/Mcff8xPP/3E999/z+nTp3nllVfo2bMnR48eLebIhShZUlNTuXbtGpMmTaJPnz6P3ZWnOKVrtJy4rlsmrJ6Ps34iNWycTRWSEOJJUK6K7vHWBdPGIYQQoswzadI9ffp0Ro4cydChQ6lZsyZz5szB1taW+fPn51h+8eLFfPjhh3Tp0oWAgABeffVVunTpYrQZ9oQoLX7//Xd8fX2Ji4vj66+/NnU4hXI26i4p6VocrM0JKG/3YMkwG5k4TQhhROXur9caK0m3EEII4zJZ0p2Wlsbhw4dp3779g2DUatq3b8++fftyrJOampqtSd/Gxobdu3fnep7U1FQSEhKybEKUNUOGDEGj0XD48GEqVKhg6nAKJfRqHKBr5VarVZCsG9+NtbPJYhJCPAHK6dZqlZZuIYQQxmaypDs2NhaNRpOtG6yHhwdR92cvflTHjh2ZPn0658+fR6vVsnnzZlavXp1lKvxHTZkyBScnJ/328ALqQgjTezjpBqR7uRCieJS/39J963ze5YQQQojHVKpmL//f//5HYGAg1atXx9LSkjFjxjB06FDU6tw/xvjx44mPj9dvD6/lJoQwvWxJd2b3cmnpFkIYU+aY7jtXICPNtLEIIYQo00yWdJcvXx4zM7Ns681FR0fj6emZYx03NzfWrFlDUlISV65c4cyZM9jb2xMQEJDreaysrHB0dMyy5efh9ZGFKItKyt/xhJR0wm8mAtLSLYQoZg5eYGEHigbuXDZ1NEKIx1BS7mtE2WSIv1/mBoijSCwtLWnQoAEhISH6Nee0Wi0hISGMGTMmz7rW1tZUqFCB9PR0Vq1aRd++fQ0Wk1qt5saNG7i5uWFpaYlKpTLIsYUoCRRFIS0tjZs3b6JWq7G0tDRpPMevxqMo4ONqQzl7K91OaekWQhQHlUo3rjvquG5ct1tVU0ckhCgkuXcXxmTI+2aTJd0A48aNY/DgwTRs2JDGjRszY8YMkpKSGDp0KACDBg2iQoUKTJkyBYD9+/dz/fp16tWrx/Xr15k0aRJarZb33nvPIPGo1Wr8/f2JjIzkxo0bBjmmECWRra0tlSpVynNoRnEIvaqbNK2ez/2ZyjPSID1J91xmLxdCGFv5wPtJt4zrFqI0knt3URwMcd9s0qS7X79+3Lx5kwkTJhAVFUW9evXYsGGDfnK1iIiILB8uJSWFjz/+mIsXL2Jvb0+XLl1YvHgxzs7OBovJ0tKSSpUqkZGRgUajMdhxhSgpzMzMMDc3LxG/BOc6iRqAtVNxhyOEeNLIWt1ClHpy7y6MyVD3zSZNugHGjBmTa3fy7du3Z3ndunVrTp8+bfSYVCoVFhYWWFhYGP1cQjypFEXJfRI1KydQm5kiLCHEk0TW6haiTJB7d1HSlarZy4UQZce1O8nEJqZhYaailvf9CQ71k6hJK7cQohjIWt1CCCGKgSTdQgiTyGzlruHliLXF/VZtmURNCFGcMruXJ8VASrxpYxFCCFFmSdIthDCJbF3L4aGWbplETQhRDKwdwV43j4y0dgshhDAWSbqFECaRY9KdrJvNXNboFkIUGxnXLYQQwsgk6RZCFLt0jZaT13VdObMm3XG6R+leLoQoLjKuWwghhJFJ0i2EKHYhYTGkZmhxtrXAv7zdgzf03cudTRGWEOJJVP5+S7es1S2EEMJIJOkWQhSrDI2WbzaeAeDFJr5Z1z2Ulm4hRHGTtbqFEEIYmSTdQohiterINcJvJuFia8Go1gFZ35SWbiFEccsc030rHLRa08YihBCiTJKkWwhRbFLSNXy3WdeFc3TbKjhaW2QtkNnSLbOXCyGKi4svqM0h/R7cjTR1NEIIIcogSbqFEMVm4d7LRCWkUMHZhheb+mYvkDl7uXQvF0IUFzMLcPHTPZdx3UIIIYxAkm4hRLGIv5fOD9t0YybHdaiKtYVZ9kLSvVyIEmnKlCk0atQIBwcH3N3d6dGjB2fPns233ooVK6hevTrW1tbUqVOHf//9txiiLQIZ1y2EEMKIJOkWQhjFrcRU9l6I1W9T1oeRkJJBNQ8HegRXyLmSTKQmRIm0Y8cORo8ezX///cfmzZtJT0/nmWeeISkpKdc6e/fuZcCAAQwfPpyjR4/So0cPevTowcmTJ4sx8gLKTLplrW4hhBBGYG7qAIQQZY9Wq9Dt+93ciE/J9t57naphplZlr5SRChnJuufS0i1EibJhw4YsrxcuXIi7uzuHDx+mVatWOdb53//+R6dOnXj33XcB+Oyzz9i8eTOzZs1izpw5Ro85Jwkp6ThYmWddNQGkpVsIIYRRSdIthDC4iNv3uBGfgplaRRU3e/3+pgGuPF3dPedKma3cqMDKyegxCiGKLj4+HgBXV9dcy+zbt49x48Zl2dexY0fWrFmTa53U1FRSU1P1rxMSEh4v0PsyNFpaf7Od63HJHPiwHe6O1lkLyFrdQgghjEiSbiGEwZ2J0t0o1/By4J/XWxaskn4SNSdQy8gXIUoqrVbL2LFjadGiBbVr1861XFRUFB4eHln2eXh4EBUVlWudKVOm8Omnnxos1kzmZmoszHSt2xdiErMn3ZnLhsVFQHoyWNgYPAYhhBBPLrmzFUIY3JmouwBU93QseCWZRE2IUmH06NGcPHmSZcuWGfzY48ePJz4+Xr9dvXrVYMeu4q7rdXM+JjH7m/buYFsOFC3EhBnsnEIIIQRI0i2EMIIzkZlJt0PBK8kkakKUeGPGjOGff/5h27ZtVKxYMc+ynp6eREdHZ9kXHR2Np6dnrnWsrKxwdHTMshlK5ftJ94Wckm6VCjzut9pHl8CJ3oQQQpRqknQLIQzuQfdyaekWoixQFIUxY8bw559/snXrVvz9/fOt06xZM0JCQrLs27x5M82aNTNWmHkKdNf9CJhj0g3gWUf3GCVJtxBCCMOSMd1CCINKSs3gyu17gLR0C1FWjB49mqVLl/LXX3/h4OCgH5ft5OSEjY1u/POgQYOoUKECU6ZMAeDNN9+kdevWTJs2ja5du7Js2TIOHTrEzz//bJLPkGf3cgCPWrpHaekWQghhYNLSLYQwqHPRd1EUcHOwopy9VcEr6lu6XYwSlxCi6H788Ufi4+Np06YNXl5e+m358uX6MhEREURGRupfN2/enKVLl/Lzzz8TFBTEypUrWbNmTZ6TrxlTZTc7AGITU4m/l569wMPdyxWlGCMTQghR1klLtxDCoB5MolaIVm54MHu5dC8XosRRCpCEbt++Pdu+Pn360KdPHyNEVHgO1hZ4OVkTGZ/ChZt3aeD7yHJnbtVAbQ4p8RB/DZx9TBOoEEKIMkdauoUQBnW2yEl3nO5RupcLIYykSl6TqZlbQflquufSxVwIIYQBSdIthDCosEjdJGqFWi4MZCI1IYTRVXa7P647OrfJ1O53MZfJ1IQQQhiQJN1CCINRFOVB93IvaekWQpQsgR73W7pv5jaZWua47hPFFJEQQogngcmT7tmzZ+Pn54e1tTVNmjThwIEDeZafMWMG1apVw8bGBh8fH9566y1SUlKKKVohRF6iElKIT07HTK3Sd+MsMGnpFkIYWRW3PLqXg7R0CyGEMAqTJt3Lly9n3LhxTJw4kSNHjhAUFETHjh2JiYnJsfzSpUv54IMPmDhxImFhYcybN4/ly5fz4YcfFnPkQoicnInUtXJXdrPDytyscJUzW7pl9nIhhJFk/hh47U4y99IyshfwuL9W9+2LkJZUjJEJIYQoy0yadE+fPp2RI0cydOhQatasyZw5c7C1tWX+/Pk5lt+7dy8tWrRg4MCB+Pn58cwzzzBgwIB8W8eFEIV3+kYCH/55gpiEgvckCYvSjeeuVtjx3PBg9nLpXi6EMJJy9la42FoAcPFmDkm1vRvYuQMKRJ8u3uCEEEKUWSZLutPS0jh8+DDt27d/EIxaTfv27dm3b1+OdZo3b87hw4f1SfbFixf5999/6dKlS67nSU1NJSEhIcsmhMjfpL9PsXR/BBPXnipwnSLPXJ6eDJpU3XPpXi6EMKJAd93/T/l2MZdx3UIIIQzEZEl3bGwsGo0GDw+PLPs9PDyIiorKsc7AgQOZPHkyTz31FBYWFlSuXJk2bdrk2b18ypQpODk56TcfH1l3U4j8XLtzjwOXbgOw/mQURyPuFKheZvfyGkWdRE2lBstC1hVCiEKofL+L+fmYuzkX0E+mVvAfHIUQQoi8mHwitcLYvn07X375JT/88ANHjhxh9erVrFu3js8++yzXOuPHjyc+Pl6/Xb16tRgjFqJ0WnvsRpbXX204g6Io2cpptQ/2pWZoCL8/I3CBlgvTaiD1rm67e/981k6gLlX/LQkhSpk81+oG8Lw/rlsmUxNCCGEg5qY6cfny5TEzMyM6OjrL/ujoaDw9PXOs88knn/DSSy8xYsQIAOrUqUNSUhKjRo3io48+Qp3DzbqVlRVWVlaG/wBClFGKorDm6HUA3mwXyI87wvnv4m12nLtJm2ruACSlZvDmsqMciYjju371aF3VjfCYJDK0Co7W5ng5Wed9kuQ78ONTkHAt634Zzy2EMLLA/JLuh1u6tVr5IVAIIcRjM9mVxNLSkgYNGhASEqLfp9VqCQkJoVmzZjnWuXfvXrbE2sxMN0NyTq1wQojCC4u8y7noRCzN1Qxv6c/gZr4AfLXhLFqtQty9NF74ZT9bwmK4nZTGiEUHWXc8kjP3J1Gr7uWISqXK+yTnt2RPuAGqdzX0xxFCiCwyW7ov37pHWoY2e4HygWBmCWl3Ie5KMUcnhBCiLDJZSzfAuHHjGDx4MA0bNqRx48bMmDGDpKQkhg4dCsCgQYOoUKECU6ZMAaBbt25Mnz6d4OBgmjRpwoULF/jkk0/o1q2bPvkWQjyeNaG6Vu72NdxxtLbgtTZVWHbgKmGRCfyy+yIrD1/jXHQizrYWBPs4s+3sTV7//Yh+xvICTaJ2cbvuseloaDdB91ylAnPplSKEMC4vJ2vsLM1IStNw5VYSgR6P/J9lZgFu1SHqOESfBFd/0wQqhBCizDBp0t2vXz9u3rzJhAkTiIqKol69emzYsEE/uVpERESWlu2PP/4YlUrFxx9/zPXr13Fzc6Nbt2588cUXpvoIQpQpGq3CX/eT7u71KgDgYmfJK20q883Gs3z57xkAPBytWDy8CZXd7Pl4zUl+PxBBWOT9lu78xnMrClzcpntepR1Y5NMVXQghDEilUlHF3Z5j1+K5EJOYPekG3bjuqOO6cd01uhV/kEIIIcoUkybdAGPGjGHMmDE5vrd9+/Ysr83NzZk4cSITJ04shsiEePLsv3iL6IRUnGwsaFPNTb9/WAt/Fu29TMzdVHzL2fLb8Cb4uNoC8GXP2jjZWDBnRzhQgJnLY89DwnUwswLf5kb7LEIIkZvKDyXdOfKopXuMlsnUhBBCPD6TJ91CiJLjz/sTqHWp44WV+YMhGzaWZswd1JB1JyIZ8ZQ/7o4PWqdVKhUfdK5OgJsd127fo56Pc94nyexaXqkpWNgY+BMIIUT+quiXDctnMrUoWatbCCHE45OkWwgBQEq6hvUnowDoGVwh2/tBPs4E5ZFQ923oU7ATZXYtD2hTyAiFEMIwAt11PXJyben2qqt7jLsC926DrWsxRSaEEKIskqRbiCfUyevxTN98jvjkdEC3DFhiagYVnG1o6OtinJNq0uHSLt3zym2Ncw4hhMhHZkt3+M1ENFoFM/UjKy7YuICLP9y5BJGhUPnp4g9SCCFEmSFJtxBPoP8u3mLEokMkpmZke69Pw4qoH70BNZTrh3XL8Ni4gGeQcc4hhBD58HGxwdJcTWqGlojb9/Avb5e9kHewLum+ESpJtxBCiMciSbcQT5iQsGheW3KE1AwtTQNcGdriwXI4NhZmNKtczngnzxzP7d8aHlqZQAghipO5mZpqHg6cuB5PWGRC7kn3qdVw42jxByiEEKJMkaRbiFIkNUNDTEJqkevvu3iL8atPoNEqtK/hwayBwVhbFOMa9+H3x3NL13IhhInV9HLUJ91d6nhlL+AdrHu8EVqscQkhhCh7JOkWopRISdfQ+X+7uBSb9NjH6hVcga9718XcrBhbm1MS4NpB3fMASbqFEKZV09sRgNM3EnIu4HV/CEx8BCTFgl35YopMCCFEWSNJtxClxII9l7kUm4SZWoWVedGSZXO1ioFNfHmvYzXjjdvOzZU9oGjANQBcfIv33EII8YgaXveT7shckm5rRygXCLfO61q7A9sXX3BCCCHKFEm6hSgF4u6l8eP2CwB8/Xxdnm9Q0cQRFUG4LBUmhCg5qnvplg2LjE/hTlIaLnaW2Qt5B99Puo9K0i2EEKLIZCYjIUqBH7eHk5CSQXVPB3rksIZ2qaBfn1u6lgshTM/R2oJKrrYAhOXW2q0f1y2TqQkhhCg6SbqFKOFuxCWzYO9lAN7rVC37erKlQfx1iD0HKjX4tzR1NEIIAegmU4M8uphL0i2EEMIAJOkWooSbseUcaRlaGvu50raau6nDKZrMpcK86+vW6BZCiBIg33HdnnUAFdy9AXejii8wIYQQZYok3UKUYOej77Ly8DUA3u9cHZWqFLZyw0Ndy9uYNAwhhHhYvjOYW9mDWzXdc1k6TAghRBHJRGpClBBarcLMref5+9gNFEW3Ly45Ha0Cz9T0oIFvKW0h1moftHTL+txCiBIkM+m+EJNIaoYGK3Oz7IW8g+HmGV0X82qdijlCIYQQZYEk3UKUABkaLe+vOsGqI9eyvWdprua9TtVMEJWBxJyCpJtgYQcVG5s6GiGE0PN2ssbJxoL45HQuxCRSy9sph0LBcOx3GdcthBCiyCTpFsLEUtI1vP77UTafjsZMrWJit5r6cYYAXk7WVHSxNWGEjymzlduvBZjnsCSPEEKYiEqlooaXA/9dvM3pGwm5J92gS7oVBUrrMB8hhBAmI0m3ECaUmJrByEWH2HfxFpbman4YWJ/2NT1MHZZhyfrcQogSrKaXky7pzm0yNY/aoDKDpBi4GwmO3sUboBBCiFJPJlITwkTuJKXxwtz/2HfxFvZW5iwa2rjsJdzpKXBlr+65rM8thCiBMsd157pWt6UtuNfQPZcu5kIIIYpAkm4hTCAqPoW+P+3j2LV4XGwtWDqyCc0qlzN1WIZ3dT9kJIO9x4ObViGEKEH0a3XfSEDJnMXyUd71dI+SdAshhCgCSbqFKGaXY5N4/se9nI9JxMvJmhWvNKNuRWdTh2UcmeO5A9rIOEghRIlUxd0eCzMVCSkZXI9LzrlQ5rju60eKLzAhhBBlhozpFuIhiqKw4tC13Mf2GcA/xyOJTUzFv7wdi4c3Lt2TpOVHvz63dC0XQpRMluZqqrg7EBaZQFjk3Zz/T67QUPd47SBoMsBMbp+EEEIUnFw1hLhPo1X4cPUJlh+6avRz1fRyZNGwxrg5WBn9XCZz7zbcCNU9l0nUhBAlWE0vR8IiEzh9I4EOOc2t4VkHrJ0gJR6ijkGFBsUfpBBCiFJLkm4hgNQMDWOXhbL+ZBRqFbzY1BcHa+P883C2saRfYx8crS2McvwS49JOQAG3GuDoZepohBAiVzW9HVl1BE5HxudcQG0Gvi3g7L9waZck3UIIIQpFkm7xxEtKzeCV3w6z63wslmZqZg6oR6fakiQ+touyVJgQonSo4eUAQFjk3dwL+bXUJd2Xd8FTY4snMCGEEGVCiUi6Z8+ezTfffENUVBRBQUF8//33NG7cOMeybdq0YceOHdn2d+nShXXr1hk7VGEACSnpvPTLfq7cvmfqUABIy9ByL02DraUZP7/UkKcCy5s6pLIhc33uyjKeWwhRstXycgIg4vY94u6l4Wxrmb2Qf0vd45V9oEkHszLeW0kIIYTBmDzpXr58OePGjWPOnDk0adKEGTNm0LFjR86ePYu7u3u28qtXryYtLU3/+tatWwQFBdGnT5/iDFs8hr9Cb3DsWi5d+EzE1c6SeYMbElzJxdShlA23L0LcFVBb6LpkCiFECeZka4F/eTsuxSYRejWONtWy33/gXgtsXCH5tm7pMJ+cGweEEEKIR5k86Z4+fTojR45k6NChAMyZM4d169Yxf/58Pvjgg2zlXV1ds7xetmwZtra2knSXImuOXgfg9aer0L2et4mj0angbIuNpZmpwyg7MpcK82kMVvYmDUUIIQoi2Mc576RbrQa/FhD2t27OCkm6hRBCFJBJk+60tDQOHz7M+PHj9fvUajXt27dn3759BTrGvHnz6N+/P3Z2djm+n5qaSmpqqv51QoLxloIS+Yu4dY/DV+6guj9ZmYejtalDEsYQLuO5hRClS71Kzqw+ep3Qq3G5F/JrpUu6L++CVu8UW2xCCCFKN7UpTx4bG4tGo8HDI+vyHB4eHkRFReVb/8CBA5w8eZIRI0bkWmbKlCk4OTnpNx8fn8eOWxTdX6G6Vu4WlctLwl1WaTX3Zy5H1ucWQpQa9XycAQi9GoeiKDkXyhzXHbEfMlJzLiOEEEI8wqRJ9+OaN28ederUyXXSNYDx48cTHx+v365eNf4azCJniqKw5n7S3SO4gomjEUZzIxRS4sDKCbyDTR2NEEIUSHVPR6zM1cTdS+fyrVwm+nSrDnZukJEM1w8Xb4BCCCFKLZMm3eXLl8fMzIzo6Ogs+6Ojo/H09MyzblJSEsuWLWP48OF5lrOyssLR0THLJkzj5PUEwm8mYWWupmMtj/wriNIpc6kw/5ZgZvJpI4QQokAszdXUrqCbxfxoxJ2cC6lU4PeU7vmlXcUUmRBCiNLOpEm3paUlDRo0ICQkRL9Pq9USEhJCs2bN8qy7YsUKUlNTefHFF40dpjCQP+9PoNahpgcO1rLUSpmVOYmajOcWQpQyD3cxz5Xf/S7mlyXpFkIIUTCFTrr9/PyYPHkyERERBglg3LhxzJ07l0WLFhEWFsarr75KUlKSfjbzQYMGZZloLdO8efPo0aMH5cqVM0gcwrgyNFr+Pn4DgJ7StbzsSkuCiP90zys/bdpYhBCikAqUdPu30j1ePQDpKUaPSQghROlX6KR77NixrF69moCAADp06MCyZcuyzA5eWP369ePbb79lwoQJ1KtXj9DQUDZs2KCfXC0iIoLIyMgsdc6ePcvu3bvz7VouSo694be4eTcVF1sLWlV1M3U4wliu7AVtOjhVAtcAU0cjhBCFElzJGYDTNxJISdfkXKhcFbD3BE0qXDtQfMEJIYQotYqUdIeGhnLgwAFq1KjB66+/jpeXF2PGjOHIkSNFCmLMmDFcuXKF1NRU9u/fT5MmTfTvbd++nYULF2YpX61aNRRFoUOHDkU6nyh+mWtzP1vXGwuzUj1/n8iLvmt5a93YRyGEKEUqONtQ3t6KDK3CqRvxORdSqR7MYi7juoUQQhRAkbOf+vXrM3PmTG7cuMHEiRP55ZdfaNSoEfXq1WP+/Pm5L7chnjgp6Ro2ntItASezlpdxmetzV5alwoQQpY9KpdJ3MT8aEZd7wcxx3eFbjR6TEEKI0q/ISXd6ejp//PEHzz33HG+//TYNGzbkl19+4fnnn+fDDz/khRdeMGScohQ7HZlAUpqG8vZW1L/fdU+UQXejIeYUoAL/NiYORgghiiazi/nRvMZ1B97vaXf9sO7/PiGEECIPhV7P58iRIyxYsIDff/8dtVrNoEGD+O6776hevbq+TM+ePWnUqJFBAxWl15nIuwDU9HZEJV2Oy65LO3SPXnXBTiY4FEKUTsGZk6nl1dLt6A3ewXDjKJxbDw2GFEdoQgghSqlCJ92NGjWiQ4cO/Pjjj/To0QMLi+xLP/n7+9O/f3+DBChKvzNRCQDU8HQwcSTCoBJj4OIOULS618eW6h5lqTAhRClWp6ITKhVcj0sm5m4K7g7WORes1lWXdJ+VpFsIIUTeCp10X7x4EV9f3zzL2NnZsWDBgiIHJcqWzJbuapJ0ly0rh+W8Tm2AjOcWQpReDtYWVHV34Gz0XUIj4nimlmfOBat3gW2f6yaQTEsCS7tijVMIIUTpUegx3TExMezfvz/b/v3793Po0CGDBCXKDkVR9C3d1T0dTRyNMBhFgcjjuueVmuvW5K78NDR++cEatkIIUUoVaL1u95rg7AsZKTKhmhBCiDwVOukePXo0V69ezbb/+vXrjB492iBBibIjMj6FhJQMzNUqKrtLK0CZkXwHUu8vp/PiKnjpT93W5WtQm5k2NiGEUezcuZNu3brh7e2NSqVizZo1eZbfvn07KpUq2xYVFVU8AT+GepmTqeU1rlulgupddc/P/Gv0mIQQQpRehU66T58+Tf369bPtDw4O5vTp0wYJSpQdma3cld3ssTKXZKzMuHNZ92jvAZa2Jg1FCFE8kpKSCAoKYvbs2YWqd/bsWSIjI/Wbu7u7kSI0nPqVXABdS3dKuib3gtW66B7PbQBNRjFEJoQQojQq9JhuKysroqOjCQgIyLI/MjISc/NCH06UcWH3x3NX95Lx3GXKnUu6Rxd/08YhhCg2nTt3pnPnzoWu5+7ujrOzs+EDMqKqHva4O1gRczeVg5dv0zLQLeeClZqBtTMk34ZrB8C3ebHGKYQQonQodEv3M888w/jx44mPj9fvi4uL48MPP6RDhw4GDU6UfmeiZBK1MimzpdvFz5RRCCFKgXr16uHl5UWHDh3Ys2ePqcMpEJVKReuqukR7+9mbuRc0M4eqHXXPz6wrhsiEEEKURoVOur/99luuXr2Kr68vbdu2pW3btvj7+xMVFcW0adOMEaMoxc7qlwuTSdTKFEm6hRD58PLyYs6cOaxatYpVq1bh4+NDmzZtOHLkSK51UlNTSUhIyLKZSptqum7wO87lkXTDgy7mZ//VTTIphBBCPKLQ/cErVKjA8ePHWbJkCceOHcPGxoahQ4cyYMCAHNfsFk+u1AwN4TeTAOleXubcvt+93FW6lwshclatWjWqVaumf928eXPCw8P57rvvWLx4cY51pkyZwqefflpcIebpqcDymKlVXIhJ5Nqde1R0yWX+iirtwMwSbl+Em2fBvXrxBiqEEKLEK9IgbDs7O0aNGmXoWEQZcyEmEY1WwcnGAk9Ha1OHIwzpzhXdo7R0CyEKoXHjxuzevTvX98ePH8+4ceP0rxMSEvDx8SmO0LJxsrGgfiVnDl6+w/azN3mxqW/OBa0cwL81XNgMZ9dJ0i2EECKbIs98dvr0aSIiIkhLS8uy/7nnnnvsoETZcCbywXhulUpl4miEwWSkQcI13XOZSE0IUQihoaF4eXnl+r6VlRVWVlbFGFHe2lRzzz/pBt3SYRc2w8k/oeXbxRegEEKIUqHQSffFixfp2bMnJ06cQKVSodwfv5SZVGk0eSytIZ4oZ/TjuaVreZkSfxUULZjbgH3JX/pHCGEYiYmJXLhwQf/60qVLhIaG4urqSqVKlRg/fjzXr1/n119/BWDGjBn4+/tTq1YtUlJS+OWXX9i6dSubNm0y1UcotNZV3fhm41n2hseSmqHJfenLmt3h33ch+gREnwKPWsUbqBBCiBKt0BOpvfnmm/j7+xMTE4OtrS2nTp1i586dNGzYkO3btxshRFFaZc5cXt1LJlErU/TLhfmB9GAQosS7evUq165d078+cOAAY8eO5eeffy7UcQ4dOkRwcDDBwcEAjBs3juDgYCZMmADolg6NiIjQl09LS+Ptt9+mTp06tG7dmmPHjrFlyxbatWtngE9VPGp5O+LmYMW9NA2HLt/JvaCt64NZzI8vL57ghBBClBqFTrr37dvH5MmTKV++PGq1GrVazVNPPcWUKVN44403jBGjKKX0Sbe0dJctMomaEKXKwIED2bZtGwBRUVF06NCBAwcO8NFHHzF58uQCH6dNmzYoipJtW7hwIQALFy7M8uP7e++9x4ULF0hOTubWrVts27aNtm3bGvKjGV3WpcNi8i5ct5/u8fgK0GqNHJkQQojSpNBJt0ajwcFBl0SVL1+eGzduAODr68vZs2cNG50otWITU7l5NxWVCqp6SNJdpshyYUKUKidPnqRx48YA/PHHH9SuXZu9e/eyZMkSfcIsctemWgHW6wYIfAasneDuDbiS+2RxQgghnjyFTrpr167NsWPHAGjSpAlff/01e/bsYfLkyQQEBBg8QFE6nb3fyl3J1RY7qyLP1ydMKeI/+H0gxF/Lul+SbiFKlfT0dP3kZFu2bNFPeFq9enUiIyNNGVqp0LKKG2oVnI9J5Hpccu4FLayhZg/d82PSxVwIIcQDhU66P/74Y7T3u01NnjyZS5cu0bJlS/79919mzpxp8ABF6RQWqZtETbqWl2JbP9ctf7Pvh6z79Um3dC8XojSoVasWc+bMYdeuXWzevJlOnToBcOPGDcqVK2fi6Eo+J1sL6ldyAWBHfq3dQf11j6f/gvQ8EnQhhBBPlEIn3R07dqRXr14AVKlShTNnzhAbG0tMTAxPP/20wQMUpdNZ/XhumUStVEq7B1f3655f3PZgv6JIS7cQpcxXX33FTz/9RJs2bRgwYABBQUEArF27Vt/tXOQts4v5tvzGdfs0BadKkHYXzv5bDJEJIYQoDQqVdKenp2Nubs7Jkyez7Hd1dZV1mEUWmZOo1fCSlu5SKWIvaNJ0z2NOw91o3fN7tyAtEVCBcyWThSeEKLg2bdoQGxtLbGws8+fP1+8fNWoUc+bMMWFkpUebarrlEXefjyUlPY+lUdVqqNtX9/z4H8UQmRBCiNKgUEm3hYUFlSpVkrW4RZ4yNFrOReuS7mrS0l06hW/L+vridt1j5szljt668YtCiBIvOTmZ1NRUXFx0XaSvXLnCjBkzOHv2LO7u7iaOrnSo5e1IBWcbktM17Dofm3fhzKT7whZIyqesEEKIJ0Khu5d/9NFHfPjhh9y+fdsgAcyePRs/Pz+sra1p0qQJBw4cyLN8XFwco0ePxsvLCysrK6pWrcq//0oXrpLkbPRdUjO0OFiZ4+tqa+pwRFFkJtmu9ydHzOxiLl3LhSh1unfvzq+//grorqFNmjRh2rRp9OjRgx9//NHE0ZUOKpWKZ2p5ALDxVFTehd2qgVc90GbAyVXGD04IIUSJV+ike9asWezcuRNvb2+qVatG/fr1s2yFsXz5csaNG8fEiRM5cuQIQUFBdOzYkZiYnMdMpaWl0aFDBy5fvszKlSs5e/Ysc+fOpUKFCoX9GMKIQq/GAVDXxwm1WoYdlDqJMRB9fwhJ2490jxe3PzKeWyZRE6K0OHLkCC1btgRg5cqVeHh4cOXKFX799VeZALUQnqnpCUBIWDQZmnzW4a43UPd4aL7u/04hhBBPtEKv5dSjRw+DnXz69OmMHDmSoUOHAjBnzhzWrVvH/Pnz+eCDD7KVnz9/Prdv32bv3r1YWFgA4OfnZ7B4hGGERsQBUM/H2aRxiCK6uEP36FkHqj8L5tZwNxJunoU797uXS0u3EKXGvXv3cHDQza+xadMmevXqhVqtpmnTply5csXE0ZUejfxccLG14M69dA5evkOzynnM/B7UH7Z8CjfPwOVd4N+q+AIVQghR4hQ66Z44caJBTpyWlsbhw4cZP368fp9araZ9+/bs27cvxzpr166lWbNmjB49mr/++gs3NzcGDhzI+++/j5mZmUHiEo8vs6W7no+LaQMRRZPZlTygrW7ctm9zCN+q2y/dy4UodapUqcKaNWvo2bMnGzdu5K233gIgJiYGR0eZd6OgzM3UtKvhwcrD19h0OirvpNvaSZd4H5oHB36WpFsIIZ5whe5ebiixsbFoNBo8PDyy7Pfw8CAqKufxUhcvXmTlypVoNBr+/fdfPvnkE6ZNm8bnn3+e63lSU1NJSEjIsgnjuZuSzoWbiQAE+TiZOBpRaIryYBK1ym11jwFtdI/h2x5MpOYq3cuFKC0mTJjAO++8g5+fH40bN6ZZs2aArtU7ODjYxNGVLh1r6bqYbzoVjZJft/HGI3WPZ9ZB/DUjRyaEEKIkK3TSrVarMTMzy3UzJq1Wi7u7Oz///DMNGjSgX79+fPTRR3kueTJlyhScnJz0m4+Pj1FjfNIdvxaPokAFZxvcHWR261In9jzcvQFmVlBJd2NOwP3k+/Ju3XsgLd1ClCK9e/cmIiKCQ4cOsXHjRv3+du3a8d1335kwstKnZWB5bCzMuB6XzKkb+fyI714D/FqCooVDC4onQCGEECVSobuX//nnn1lep6enc/ToURYtWsSnn35a4OOUL18eMzMzoqOjs+yPjo7G09MzxzpeXl5YWFhkSe5r1KhBVFQUaWlpWFpaZqszfvx4xo0bp3+dkJAgibcRPeha7mzSOEQRZXYtr9QULGx0zz1qg215uHd/6RtLe7DNo1ulEKLE8fT0xNPTk2vXdC2uFStWpHHjxiaOqvSxtjCjdVU3NpyKYtOpKGpXyKdHV+ORujHdhxdC6/fA3KpY4hRCCFGyFLqlu3v37lm23r1788UXX/D111+zdu3aAh/H0tKSBg0aEBISot+n1WoJCQnRd317VIsWLbhw4QJa7YNZQ8+dO4eXl1eOCTeAlZUVjo6OWTZhPEdlErXS7dGu5QBqNQS0fvDaxR9UMiu9EKWFVqtl8uTJODk54evri6+vL87Oznz22WdZrqeiYB4sHRadT0mgWldwrKD70fLUGuMGJoQQosQy2Jjupk2bZkmgC2LcuHHMnTuXRYsWERYWxquvvkpSUpJ+NvNBgwZlmWjt1Vdf5fbt27z55pucO3eOdevW8eWXXzJ69GhDfQzxGBRFedDSXcnZpLGIItCk67qQw4Mu5Zkefu3iW3wxCSEe20cffcSsWbOYOnUqR48e5ejRo3z55Zd8//33fPLJJ6YOr9RpV90DM7WKs9F3uRyblHdhM3NooLun4cDPxg9OCCFEiVTo7uU5SU5OZubMmYVeL7tfv37cvHmTCRMmEBUVRb169diwYYN+crWIiAjU6ge/C/j4+OhnXq1bty4VKlTgzTff5P333zfExxCP6UZ8CrGJqZipVdT2lknUjCL5jm7pLmOIPQdpd8HGFTzrZn0vczI1kEnUhChlFi1axC+//MJzzz2n35d5DX3ttdf44osvTBhd6eNka0HTAFf2XLjFptNRjGpVOe8KDQbDjq/g+iG4fhgqNCieQIUQQpQYhU66XVxcUD3UtVRRFO7evYutrS2//fZboQMYM2YMY8aMyfG97du3Z9vXrFkz/vvvv0KfRxhf5vrc1T0dsLGUJdwMTquFOa0gPsK45wloretS/jBnHyhXBW5dkEnUhChlbt++TfXq1bPtr169Ordv3zZBRKVfx1qe7Llwi3XHI/NPuu3doVZPOPEH7Pkf9P21eIIUQghRYhQ66f7uu++yJN1qtRo3NzeaNGmCi4usy/wkC716B5Dx3EZzN/J+wq0C1wDjnMPSFpq+lvN77SbAkV+hVi/jnFsIYRRBQUHMmjWLmTNnZtk/a9Ys6tatm0stkZcudbyY/Pdpjl2L53z0XQI9HPKu8NRbuqT79F8QfRo8ahZPoEIIIUqEQifdQ4YMMUIYoiyQmcuN7M79NbJd/OCNI8V//prddZsQolT5+uuv6dq1K1u2bNFPVLpv3z6uXr3Kv//+a+LoSqfy9la0re7O5tPRrDh8jQ+71Mi7gkdNqPEchK2Fnd9AH1lCTAghniSFnkhtwYIFrFixItv+FStWsGjRIoMEJUqfdI2WE9fjAQiWSdSM485l3aN07xZCFELr1q05d+4cPXv2JC4ujri4OHr16sWpU6dYvHixqcMrtfo0qAjA6iPXydAUYBb41u/pHk/9aby5OYQQQpRIhU66p0yZQvny5bPtd3d358svvzRIUKL0ORt1l5R0LQ7W5gSUtzd1OGWTJN1CiCLy9vbmiy++YNWqVaxatYrPP/+cO3fuMG/ePFOHVmq1re5OOTtLYhNT2XHuZv4VPOtA9WcBRdfaLYQQ4olR6KQ7IiICf//ssxf7+voSEWHkCZ5EiZXZtTyoojNqtazhbBS373cvl9nDhRDC5CzM1PQI1q3asvLwtYJVymztPrkKYs8bKTIhhBAlTaGTbnd3d44fP55t/7FjxyhXrpxBghKlj4znLgbS0i2EECVK7/tdzLeERXM7KS3/Cl5BULUzKFrYNc3I0QkhhCgpCp10DxgwgDfeeINt27ah0WjQaDRs3bqVN998k/79+xsjRlHCKYrCkSsyc7nRSdIthBAlSg0vR2pXcCRdo/BX6PWCVcps7T7+B9wKN15wQgghSoxCz17+2WefcfnyZdq1a4e5ua66Vqtl0KBBMqb7CRUSFsPF2CSszNU09JNl44wi9S7ci9U9l6RbCFEAvXrlvbxfXFxc8QRSxvVp4MPJ66dYefgaQ1sUYPhPhfoQ2BHOb4TNE6D/EuMHKYQQwqQKnXRbWlqyfPlyPv/8c0JDQ7GxsaFOnTr4+voaIz5Rwmm0Cl9vPAPA0Bb+ONtamjiiMiqzldvGFaydTBqKEKJ0cHLK+/8KJycnBg0aVEzRlF3PBXnzxbowTt1I4PSNBGp6O+ZfqcNkuLAFzvwD4dugclvjByqEEMJkCp10ZwoMDCQwMNCQsYhS6M+j1zkXnYijtTmvtq5s6nDKrsykWyZRE0IU0IIFshZ0cXCxs6R9TXf+PRHF8oMRfNq9dv6V3KtD45Gwfw5s+ABe2QNmRb4lE0IIUcIVekz3888/z1dffZVt/9dff02fPn0MEpQoHVLSNUzfpFtrdHTbKjjZWpg4ojIsc+Zy6VouhBAlzoDGlQBYcfgacfcKMKEaQJsPdL2Xbp6BQ7J0mxBClGWFTrp37txJly5dsu3v3LkzO3fuNEhQonT47b8r3IhPwcvJmsHN/UwdTtkmk6gJIUSJ9VSV8tT0cuRemobF+64UrJKNC7T7RPd82xeQdMt4AQohhDCpQifdiYmJWFpmH7drYWFBQkKCQYISJV9CSjqztl0A4K32VbG2MDNxRGXcncyWbuleLoQQJY1KpeLl1gEALNx7mZR0TcEq1h8MHnUgJV6XeAshhCiTCp1016lTh+XLl2fbv2zZMmrWrGmQoETJ99OOcOLupVPF3Z5e9SuYOpyyT1q6hRCiROtax4sKzjbcSkpj5eFrBaukNoPO94fsHV4AN0KNFp8QQgjTKfSsHZ988gm9evUiPDycp59+GoCQkBCWLl3KypUrDR6gKJn+OR4JwNj2gZibFfq3G1EYWg3EReieS9IthBAlkrmZmpEt/Zn092nm7rrIgMaVMFOr8q/o1wJq94aTK2HNazBqG5hbGT9gIYQQxabQ2VK3bt1Ys2YNFy5c4LXXXuPtt9/m+vXrbN26lSpVqhgjRlECxSSkAlDbW5avMrr4a6DNADNLcPQ2dTRCCCFy0beRD862Fly5dY8NJ6MKXrHzV2BbHmJOwY6vjRegEEIIkyhSE2XXrl3Zs2cPSUlJXLx4kb59+/LOO+8QFBRk6PhECZSUmkHy/fFq5R3k13ijy+xa7lxJ1xVRCCFEiWRrac6gZn4AzNkRjqIoBatoVx6ena57vvs7uH7EOAEKIYQwiSL3C965cyeDBw/G29ubadOm8fTTT/Pff/8ZMjZRQsUm6lq5rS3U2FlKEmh0Mp5bCCFKjcHNfLG2UHPiejz7wgsxI3nN7lCrFygaXTfzjFTjBSmEEKJYFSrpjoqKYurUqQQGBtKnTx8cHR1JTU1lzZo1TJ06lUaNGhkrTlGCZCbd5e2tUKkKMF5NPB6ZuVwIIUqNcvZW9G3oA8C3m84WvLUboMu3YOcGN8Ng+1QjRSiEEKK4FTjp7tatG9WqVeP48ePMmDGDGzdu8P333xszNlFCxSamAbqkWxQDaekWQohSZXTbKthYmHEkIo71hRnbbVcOut7vZr5nBlzaZZT4hBBCFK8CJ93r169n+PDhfPrpp3Tt2hUzM+lW/KR60NKdfb12YQS377d0u0pLtxBClAYejtaMaqVbt3vq+jOkZWgLXrnmcxA0ABQtrBgC8deNE6QQQohiU+Cke/fu3dy9e5cGDRrQpEkTZs2aRWxsrDFjEyVU7F1p6S5W0tIthBClzqhWAbg5WBFx+x6/7rtcuMpdp4NHHbgXC3+8JOO7hRCilCtw0t20aVPmzp1LZGQkL7/8MsuWLcPb2xutVsvmzZu5e/euMeMUJcjDY7qFkSXfgZQ43XNnX5OGIoQQouDsrMx555mqAHy/9QJx99IKXtnSFvotBmtnuH4Y/n3XOEEKIYQoFoWevdzOzo5hw4axe/duTpw4wdtvv83UqVNxd3fnueeeM0aMooSR7uXFKLOV284drOxNGooQQojC6d3Ah2oeDsQnpzNr64XCVXb1h+fnASo4sggOLzRGiEIIIYpBkZcMA6hWrRpff/01165d4/fffy/ycWbPno2fnx/W1tY0adKEAwcO5Fp24cKFqFSqLJu1tXWRzy0KT590yxrdxiddy4UQotQyU6v4sGsNABbtu8yVW0mFO0Bge3j6Y93zf9+FiP0GjlAIIURxeKykO5OZmRk9evRg7dq1ha67fPlyxo0bx8SJEzly5AhBQUF07NiRmJiYXOs4OjoSGRmp365cufI44YtCktnLi5Ek3UIIUaq1rupGy8DypGsUPvnrVOGWEAN4ahzU6AaaNFj+IsRfM06gQgghjMYgSffjmD59OiNHjmTo0KHUrFmTOXPmYGtry/z583Oto1Kp8PT01G8eHh7FGLGIvStjuouNzFwuhBCl3qTnamFprmbnuZv8FXqjcJXVaugxBzxqQ1IM/D4A0grZYi6EEMKkzE158rS0NA4fPsz48eP1+9RqNe3bt2ffvn251ktMTMTX1xetVkv9+vX58ssvqVWrVnGE/MRLSddwNzUDALfCJN0ZabpZWEXhxJ7XPUpLtxBClFqV3ex5s10g32w8y+R/TtOqqhuudoWYF8XKHvovhbltIeo4rHkN+iwElcpoMQshhDAckybdsbGxaDSabC3VHh4enDlzJsc61apVY/78+dStW5f4+Hi+/fZbmjdvzqlTp6hYsWK28qmpqaSmPlhqIyEhwbAf4gmTOZ7b0kyNo00B//qkJ8P3DSFBusQVmSTdQghRqo1qFcDfx25wJuoun/9zmun96hXuAC6+0O83WNQNTq+BHV9Dm/eNEaoQQggDM3n38sJq1qwZgwYNol69erRu3ZrVq1fj5ubGTz/9lGP5KVOm4OTkpN98fHyKOeKy5db98dzl7C1RFfQX9piwBwm32ly2wm4edcCrnnH+QIUQQhQLCzM1U5+vi0oFq49eZ8e5m4U/iG9z6DpN93z7l3B0iWGDFEIIYRQmbekuX748ZmZmREdHZ9kfHR2Np6dngY5hYWFBcHAwFy7kvBTH+PHjGTdunP51QkKCJN6PoUhrdGdOBubTFIZvNHxQQgghRClQz8eZoc39mb/nEh+uPsGmt1phZ1XIW7EGQ+BWOOydCWtfB1tXqNbZKPEKIYQwDJO2dFtaWtKgQQNCQkL0+7RaLSEhITRr1qxAx9BoNJw4cQIvL68c37eyssLR0THLJoquSGt0ZybdMhmYEEKIJ9zbz1SlgrMN1+OSmbj2VNEO0v5TCBoAigZWDJGlxIQQooQzeffycePGMXfuXBYtWkRYWBivvvoqSUlJDB06FIBBgwZlmWht8uTJbNq0iYsXL3LkyBFefPFFrly5wogRI0z1EZ4oRVou7M79GbhlXLIQQognnJ2VOdP6BqFWwcrD11hx6GrhD6JWw3PfQ2BHyEiBpX11Q7mEEEKUSCZPuvv168e3337LhAkTqFevHqGhoWzYsEE/uVpERASRkZH68nfu3GHkyJHUqFGDLl26kJCQwN69e6lZs6apPsIT5WbmcmEOReheLkm3EEIIQdOAcozrUBWAT/46ybnou4U/iJmFbgZznyaQEge/dofoIracCyGEMCqVoiiKqYMoTgkJCTg5OREfHy9dzYtgzNIj/HM8kk+ercnwpwrYXfy7OhAfAcM2QaUmxg1QCCFKOblOPVCWvwutVmHwggPsOh9LFXd7/hrdovDjuwHu3YZFz0H0CbB2hhdXQ8UGBo9XCCFEdgW9Tpm8pVuULoUe052R9mDmcmnpFkIIIQBQq1XM6FcPD0crLsQk8smakxSpHcTWFYb8DRUb3W/xfg4u7TR4vEIIIYpOkm5RKIUe0x1/FRQtWNiCvbsRIxNCCCFKl3L2Vnw/oD5mahWrj15n6YGIoh3IxgVeWgP+rSEtEX7rDWfXGzRWIYQQRSdJtyiUQi8Z9vAkagVd11sIIYR4QjT2d+XdjtUAmLT2FEci7hTtQFb2MPAPqP4saFJh+UsQ9o8BIxVCCFFUknSLAkvXaIm7lw4Uonu5TKImhBBlws6dO+nWrRve3t6oVCrWrFmTb53t27dTv359rKysqFKlCgsXLjR6nKXRy60C6Fzbk3SNwmu/HdFPWlpoFtbQZxHU7g3adFgxGE6vNWywQgghCk2SblFgt5N0XcvN1CpcbAuYdN+W5cKEEKIsSEpKIigoiNmzZxeo/KVLl+jatStt27YlNDSUsWPHMmLECDZu3GjkSEsflUrFN32CqOxmR1RCCmOWHiFdoy3awczMoedPUKcvaDN063ifWmPIcIUQQhRSEabJFE+qzF/eXe0sUasL2FVc39JdwJnOhRBClEidO3emc+fOBS4/Z84c/P39mTZtGgA1atRg9+7dfPfdd3Ts2NFYYZZa9lbm/PRSQ3rM3sP+S7eZ8u8ZJnQr4nKoZubQcw6o1HB8GawcBun3oN5AwwYthBCiQKSlWxRYocdzA9y5onuUlm4hhHii7Nu3j/bt22fZ17FjR/bt22eiiEq+Ku72fNsnCID5ey6xYM+loh9MbQY9foCggaBoYM2rsPYNSE82ULRCCCEKSpJuUWAPZi4vYNdyRXkwkZqrtHQLIcSTJCoqCg8Pjyz7PDw8SEhIIDk558QvNTWVhISELNuTplNtT8Z1qArAp3+fZuXha0U/mNoMus+C1u8DKjiyCOa2g9jzhglWCCFEgUjSLQoss6XbraAt3fdu6ZYuQQVOPsYLTAghRJkwZcoUnJyc9JuPz5N57Xj96SoMa6H7sfq9lcfYcDKy6AdTm0HbD+GlP8HODWJOwU+tZZy3EEIUI0m6RYHF3h/TXd6hoMuFXdY9OnrrZlQVQgjxxPD09CQ6OjrLvujoaBwdHbGxscmxzvjx44mPj9dvV69eLY5QSxyVSsUnz9agb8OKaBV4/fej7Dx38/EOWrktvLIb/FpCepJuZvO93+t6pQkhhDAqSbpFgT0Y013Ymcula7kQQjxpmjVrRkhISJZ9mzdvplmzZrnWsbKywtHRMcv2pFKpVEzpVZcudXRLiY1afIjd52Mf76AOnjDoL2g8Svd608ew/n3Qah4/YCGEELmSpFsU2IMx3YVs6ZZJ1IQQotRLTEwkNDSU0NBQQLckWGhoKBEREYCulXrQoEH68q+88goXL17kvffe48yZM/zwww/88ccfvPXWW6YIv1QyU6uY0S+YttXcSEnXMmzRQbaeic6/Yl7UZtD5a3jmc93rAz/B8pcgLenxAxZCCJEjSbpFgRV69vI7ska3EEKUFYcOHSI4OJjg4GAAxo0bR3BwMBMmTAAgMjJSn4AD+Pv7s27dOjZv3kxQUBDTpk3jl19+keXCCsnSXM2clxrQoaYHaRlaXl58mA0nox7voCoVNH8d+iwEMys4uw5mN4Vzsoa6EEIYg6zTLQqsyC3dMnO5EEKUem3atEHJY/zvwoULc6xz9OhRI0b1ZLAyN+OHF+ozdnko645HMnrpEb7rV4/ngrwf78C1eoKDF6waAfERsLQv1OgGnb4CpwqGCV4IIYS0dIuC0WgVbicVcky3dC8XQgghDMLCTM3/+tWjV3AFNFqFN5cdZeHjrOOdqVJTGL0fWrwJKjMI+xtmN4ZDC2SSNSGEMBBJukWB3LmXhlbR9UhztStA0p2eAgk3dM9lIjUhhBDisZmbqfm2TxAvNq2EosCkv08zdf2ZPHsgFIilHXSYDK/sAp8muuU+/xkLv/eHxBiDxC6EEE8ySbpFgWSO53axtcTcrAB/beIiAAUsHcDW1bjBCSGEEE8ItVrFZ91r884zVQGYsyOct/84RrpG+/gH96gFQzdAxy91Y73PbYAfmkLYP49/bCGEeIJJ0i0KJPZu5njuInQtV6mMEpMQQgjxJFKpVIx5OpCve9fFTK1i9dHrDF1wkLh7aY9/cLUamo2GUdvBow7cuwXLX4DVL0Pyncc/vhBCPIEk6RYFUuSZy139jBOQEEII8YTr29CHXwY3xMbCjN0XYuk2azdhkQmGObhHTRgZAi3GgkoNx5fpZjg/u94wxxdCiCeIJN2iQAqfdF/WPcokakIIIYTRtK3mzurXmuPjasPV28n0+mEvfx+7YZiDm1tBh09h2CYoFwiJUbpx3qtHQdxVw5xDCCGeAJJ0iwK5Wdik+7as0S2EEEIUhxpejvw95ilaBpYnOV3D678f5ct/wwwzzhvAp5FukrXmb9xv9V4OM4Ph7zfhzhXDnEMIIcowSbpFgejHdDsUdky3zFwuhBBCGJuzrSULhzbm5dYBAPy88yID5/5HVHyKYU5gYQPPfAbDN4NfS9Cmw+GF8H19WPsGJEQa5jxCCFEGSdItCqRQ3cu1WuleLoQQQhQzM7WK8Z1r8OML9XGwMufg5Tt0mbmLXedvGu4kFRvCkH9g6HoIaAPaDDiySJd8b/sSUhMNdy4hhCgjJOkWBXIhRncRrehik3/hmFOQkQwWduBcyciRCSGEEOJhnet48ffrT1HTy5HbSWkMmn+A6ZvOotE+5nreD/NtDoP+gmEbdWt7p9+DHV/pku/Di0CrMdy5hBCilCsRSffs2bPx8/PD2tqaJk2acODAgQLVW7ZsGSqVih49ehg3wCfczbupXI9LRqWCOhWc8q8Qvk336NcCzCyMG5wQQgghsvErb8fq15ozoHElFAVmbr1g2O7mmSo11SXefRbperclRsPfb8Ccp+DCFsOeSwghSimTJ93Lly9n3LhxTJw4kSNHjhAUFETHjh2JiYnJs97ly5d55513aNmyZTFF+uQKvRoHQKC7PQ7WBUiiL27XPQa0NVpMQgghhMibtYUZU3rV4X/962Fnacb+S7fpMnMX287mfY9VaCoV1OoBow9Axy/B2hliTsNvz8PiXhB10rDnE0KIUsbkSff06dMZOXIkQ4cOpWbNmsyZMwdbW1vmz5+fax2NRsMLL7zAp59+SkBAQDFG+2Q6GnEHgHo+zvkXTk+BK3t1zytL0i2EEEKYWvd6FfjnjZb67uZDFxzkkzUnSUhJN+yJzK2g2Wh44yg0HQ1qCwgPgTktYMUQuHnWsOcTQohSwqRJd1paGocPH6Z9+/b6fWq1mvbt27Nv375c602ePBl3d3eGDx9eHGE+8TJbuuv5uORf+Op+3Xhue09wq27cwIQQQghRIP73u5sPbuYLwOL/rtBu2g7WHruBohhwrDeArSt0+hLGHIBaPXX7Tv0Js5vAqpFw85xhzyeEECWcSZPu2NhYNBoNHh4eWfZ7eHgQFRWVY53du3czb9485s6dW6BzpKamkpCQkGUTBafRKhy/Fg8UsKX74v3x3AFtdN3NhBBCCFEiWFuY8Wn32iwZ0YSA8nbcvJvKG78fZdD8A1yOTTL8CV0DoM9CeGUPVH8WUODEHzC7ESzqBqf/Ao2BW9uFEKIEMnn38sK4e/cuL730EnPnzqV8+fIFqjNlyhScnJz0m4+Pj5GjLFvCbyaSmJqBjYUZVT3s86+QOZ5bupYLIYQQJVKLKuVZP7Yl4zpUxdJcza7zsTwzYyeztp4nLUNr+BN61ob+S2DUdqjWFVDBpZ3wxyD4rjbs/AZS4g1/XiGEKCFMmnSXL18eMzMzoqOjs+yPjo7G09MzW/nw8HAuX75Mt27dMDc3x9zcnF9//ZW1a9dibm5OeHh4tjrjx48nPj5ev129etVon6csCo2IA6BORSfMzfL563LvNtwI1T0PaGPMsIQQQgjxGKzMzXijXSCbxraiZWB50jK0fLvpHF1n7uLg5dvGOal3MAxYCmOPQ8u3wc4NEqNg6+cwow5snwrJd4xzbiGEMCGTJt2WlpY0aNCAkJAQ/T6tVktISAjNmjXLVr569eqcOHGC0NBQ/fbcc8/Rtm1bQkNDc2zFtrKywtHRMcsmCu7o/fHcwQXpWn5pB6CAWw1wyP6jiRBCCCFKFr/ydvw6rDH/61+PcnaWnI9JpM+cfYxffYL4ZCN1/XauBO0mwFunoefPUL6qrqV7+xSYURc2fgS3sjekCCFEaWVu6gDGjRvH4MGDadiwIY0bN2bGjBkkJSUxdOhQAAYNGkSFChWYMmUK1tbW1K5dO0t9Z2dngGz7hWE8mETNOf/CmetzS9dyIYQQotRQqVR0r1eB1lXdmLr+DMsOXuX3AxGEhEXz6XO16FTbE5Ux5mkxt4SgflCnt258985vdEuN7Zul2/xbQ8NhUL0rmBVgyVIhhCihTJ509+vXj5s3bzJhwgSioqKoV68eGzZs0E+uFhERgVpdqoaelxn30jI4G6WbeK5eJee8CyvKQ5OoSdIthBBClDbOtpZMfb4uPYMrMH71CS7GJvHqkiO0r+HBJ8/WwLecnXFOrDaD2r2gZg84vwkOzdc9Xtqh2xwrQJOXof5gsHE2TgxCCGFEKsXg60SUbAkJCTg5OREfHy9dzfOx/+It+v38Hx6OVuz/sH3ehW9fhJnBujU5378MVgWYdE0IIUQ2cp16QL4L00lJ1/DDtgv8uCOcdI2ChZmKF5r48vrTVShnb2X8AOIi4PAiOLIIkm7q9lnYQfCLULefbny4NMoIIUysoNcp+d9K5KpIXct9GkvCLYQQQpRy1hZmjHumGuveaEnrqm6kaxQW7r1M62+2MzPkPPfSMowbgHMlaPcJjD0J3WeDey1IT4IDP8EvT8P0GvD3m3BuE2SkGTcWIYR4TJJ0i1w9SLpd8i8sXcuFEEKIMqeqhwOLhjVm6Ygm1KngRGJqBtM3n6PV19tZvO8y6RojLDH2MAtrXev2q3vgpTW6LuiWDrpZzw8vhKV94NtAXQJ+eQ9ojRyPEEIUgcnHdIuSq8At3VqNbr1NkKXChBBCiDKoeZXy/DW6Bf+ciGTaprNcuXWPT/46xS+7L/H2M9V4to4XarURJlvLpFLpJmqt3BYyUuHybjj7L4T98yABP7wQHLyh8tPg30q3OXoZLyYhhCggGdMtchSdkEKTL0NQq+DEpI7YWeXx+8y1w7quXlZO8N5FMJPfcoQQoqjkOvWAfBclU1qGlmUHI5gZcp7YRF3X7moeDoxtH0jHWp7GTb4fpdXoEvATf8DpvyE1Puv7bjWg5nNQqye41yi+uIQQT4SCXqckOxI5OhoRB+i6leWZcANc3Kp79G8pCbcQQghRxlmaqxnUzI/n61dk3u5LzN11kbPRd3l1yRFqeDnyZrtAOtT0wKw4km+1GQS01m1dpsGV3bredxd3QOQxuBkGO8Jgx1f3E/DuuiXIPOvoWs+FEKIYSIb0GDacjGLuroumDsMoouJTgIJOorZd9yjrcwshhBBPDDsrc95oF8jgZn7M232R+XsuExaZwCu/Hca/vB3DnvKnd/2K2FiaFU9AFtZQpb1uA7h3Gy5sgZOrITzkoQR8Kjj5QLXOUKMb+D4lM6ELIYxKupc/hsX/XeGTNScNFFnJ9P2AYLoFeedeIC0JpvqCNh1ePwLlKhdfcEIIUQZJl+oH5LsoXe4kpfHL7oss3neFhBTd7OYutha81NSXIS38cbWzNF1wyXFwdj2c+QcuhEBG8oP3nCpBvYFQbwC4+JkqQiFEKVTQ65Qk3Y/h6u17nI5MMFBkJY+TjQWN/VzzHpt1fjMs6a27YI09Ll21hBDiMUmi+YB8F6VTUmoGfxy6yvw9l7h6W5fc2liYMaBxJUa28sfLyca0AaYnw8XtugT89FpIfeherlIzXQt41c5QPlDua4QQeZKkOxdyATewDR/Cf7Oh/iB47ntTRyOEEKWeXKcekO+idMvQaNl4Kpofd1zg5HVdYmthpqJ7vQoMa+FPTe8S8GeanqybAT30N904cB66LXYN0CXf1buAT1OZt0YIkY0k3bmQC7iB/dAMYk5D7wVQu5epoxFCiFJPrlMPyHdRNiiKwq7zsczedoH9l27r9zcLKMfQFn60q1FMk67lJ+6qrgv6ufW6GdE1aQ/es3GFqh0h8Bnd8qi2riYLUwhRckjSnQu5gBvQ3WiYVhVQwbvhYFfO1BEJIUSpJ9epB+S7KHuORNxh/u5LrD8ZhUaruwWt4GxD7wYV6dOwIhVdbE0c4X2pdyF8m24t8P+3d+fhVZd33sff52Q552Q92TcSQgg7sgYQ1LZWFNDpFMe26kWVOjP6qOjo0JkK44g6XoqOXpYZtVh9Rvu0Llg7aq0LaqO4sssOCUsgCSQne3JO9nDO7/njR06IBAghyUnI53Vd95Xkt+X+3Y39ni/3tn8tNNWcdNICqVPN/cCz58KwGeoFFxmilHSfhgJ4L9rxBrx9G6RMhv/zRaBrIyJyQVCc6qC2uHCV1Dbx+/WFvL6piLqmNsCcPn3JyHhumJnOVeOTCQ0eICuKe49D8QbI+wAOfWqugn4yu9NMvkfPM7+qF1xkyNA+3dL3Cj4zv2ZpqzARERHpvlSng2ULxnLv3FF8tMfFH7cU8/XBKr46WMlXByuJCw/lJznDuHFGBpnx4YGtbFAwZF5qFgB3ibkQ28FccyuyphrY/SezWKyQPstMwEfPh4SxWoxNRNTTLT1kGPD0OPCUwk3vaI9uEZFeojjVQW0xtBRXN/LHLcX8cUsxZe4W//GZI2K5dmoaV1+UQrQjJIA17IL3OBzbYg5B3/8xlO/pfD48ATIuhow55tfkiyBogL2DiPSYhpefhgJ4LynPg9/MgmA73FcIIfZA10hE5IKgONVBbTE0Hff6+DSvnNc3FbFufwXtn1RDg63MHZfItVOH8f3RCQNn+PnJaotg/0dmOfwFeFs6nw+2Q/IkSJsOw3LMRDx6WGDqKiLnTUn3aSiA95INq2HtMnNo+c3vBLo2IiIXDMWpDmoLKa1r4s/bS3j722Pkl3n8x51hIfzNpBSunZrGtIwYLANxCHdbM5Ruh8JvoGiDOS+8ue7U65wZMPwSc1h6yiRIHA8hAd7LXES6RUn3aSiA95LXrjeHUs19GC69N9C1ERG5YChOdVBbSDvDMNhb6ubtb4/x7o4Syj0dPchpTgdXX5TMNZNSmTwsemAm4GBOzasugGNb4egWOLoJSneC4e18ncUKcdnmQrWZl0LmZeae4QP1vUSGMCXdp6EA3kueGgP1LviHv0L6jEDXRkTkgqE41UFtIV3x+gzWH6ri7W3HWLu7lIbWjqQ1zelg3oRk5k1IIiczdmDs/30mLR4o3mT2hh/bAq7d0Fh56nVRaeZQ9MTxkDQBEsdBdAZYB+AQe5EhREn3aSiA94LWRngsxfz+V4e1NYaISC9SnOqgtpCzaW7z8vn+Ct7fWcpf95XReFICHhceytxxScybmMQl2fHYgoMCWNNuMgyoLzOT76ObzXnhRzeDr+3Ua+3OjlXVMy+FxAlKwkX6mZLu01AA7wXl++A3F4M9GpYVBbo2IiIXFMWpDmoLORdNrWYC/vFeF7n7yv37fwNE2IL5wZgE5k1I5nujEwbeKuhn0toIxRvN+eFle83PYZX54G3tfF2QDWJHQOxIiMuClCnm0PTIpEDUWmRI0D7d0ndqjphfYzIDWQsRERERP0doEPMnJjN/YjJtXh+bDlfz0R4XH+1xUeZu4b2dpby3s5Qgq4UZmTH8cGwiPxybyMiEiIE7DxwgNMzcmvXk7Vm9bVC6A458CUe+Mhdqa62HijyznCx+DIy4zEzAMy+F8Pj+rb+IqKdbeqB95fLxP4af/T7QtRERuaAoTnVQW0hv8PkMdhytZe0eswf8YHl9p/NpTgffGx3P90cnMCc7nij7IOoFb+c9DnXFUH0Iqgqg6oCZiLt2Ad/5qJ843kzA02dC6lSIGaFh6SI9pJ5u6TvVh82vMSMCWw8RERGRs7BaLUzNiGFqRgzLF4yjqKqRT/PKyM0rZ+Phao7VNvH6pmJe31SM1QKT051cmh3PpdnxTM2IGZj7gX9XUPCJoeUjIPuk443VUPg1HP7S7BUv39tRNv3WvMYWDamTzQQ8dRqkTYPodK2WLtKL1NMt5+7Vn8GBj+BvVkHOLYGujYjIBUVxqoPaQvpaU6uXDYer+Dy/gi/2V1BQ2dDpfFhoEDNHxHJpdjyXZMczNjlyYA9FP5uGSnM4euHXcOxbsyfc23LqdWHxMGyG2RuePtNMxkPD+r++IgPcoOrpfu6553jyySdxuVxMnjyZZ555hpkzZ3Z57VtvvcVjjz3GwYMHaWtrY9SoUfzyl7/kpptu6udaD2E17T3dmQGthoiIiMj5cIQGcfmYRC4fkwjA0ZpGvjlYxZcHK/nmYCVVDa2sy69gXX4FAM6wEKZnxDA9M4bpGTFMTndiDxkEq6K3C4+HCQvNAubc8PJ9UPItlGwzE/Hyvea2Zfs/NAuAJQjiR0PKJEieBKlTIG06hDgC9CIig0vAe7rfeOMNbr75Zp5//nlmzZrFqlWrePPNN8nPzycxMfGU69etW0dNTQ1jx44lNDSU9957j1/+8pe8//77zJs376y/T/9qfp58Png02fxX0Xt2KPEWEellilMd1BYSSD6fQZ7Lw9cHK/nqYCWbDlfT1ObtdE1osJUp6U4uHhHLrKw4pqQ7CbcNiD6tnmtrMnvAizfB0U3mV0/pqdcFhUJaDmReYu4hnjQRIpI0LF2GlEGzZdisWbOYMWMGzz77LAA+n4/09HTuvvtuli1b1q1nTJs2jWuuuYZHHnnkrNcqgJ8ndwk8PQ6swXB/mTmHSEREeo3iVAe1hQwkrcd97C11s+VINVsLa9hSWEOFp/PQbKsFxiRHMTXDydR0JzMyYxkeFza4h6Qbhpl0l+4E105z1fSjW6Dedeq1jhhzobaEsZAw5kQZq2RcLliDYnh5a2srW7duZfny5f5jVquVuXPnsn79+rPebxgGn376Kfn5+TzxxBN9WVVp176IWnS6Em4REREZMtp7taekO/nHy8zPoYcrG9h4uJqNBVVsOlxNSV0z+0rd7Ct189rGIgASI23MGBHLzMxYpmY4GZscNTgWZ2tnsUBUqlnGzDePGQZUF3SeH159CJpqzJ8Lv+78DEcMJF9kDk1PvghSJpvD1a2DaGi+yHkIaNZUWVmJ1+slKSmp0/GkpCTy8vJOcxfU1dWRlpZGS0sLQUFB/OY3v+HKK6/s8tqWlhZaWjr+FdLtdvdO5Ycq7dEtIiIigsViISshgqyECG6cmQGAq66Z7cU1bCuqZWthDTuP1lHuaeH9naW8v9Mcoh0abGVCahSThzmZnB7NpGFORsSFY7UOop5giwXiRppl+mLzWFszVO4354RX5J8oeeZaQE01cPgLs7QLCTsxP3yq2SPuzDA/X0YPg2BbQF5LpK8Myq7KyMhItm/fTn19Pbm5uSxdupSsrCx+8IMfnHLtypUrefjhh/u/khcqJd0iIiIiXUqOtjM/OoX5E1MAaG7zsr24ls2Hq9lSWMOOo7XUNraxraiWbUW1/vsi7cFMTI3momHRTEyLZmJqFJmDLREPsZsLraVM6ny8rRkq808anr7TnDPe1gDFG8zSicXsCR+zAEbPN7/X0HQZ5AKadMfHxxMUFERZWVmn42VlZSQnJ5/2PqvVSna2uQnhlClT2LdvHytXruwy6V6+fDlLly71/+x2u0lPT++dFxiK2lcuj9Ue3SIiIiJnYg8J4uKsOC7OigPMIemFVY1sL65le3EtO4/WsqfEjaf5OOsLqlhfUOW/N8IWzPiUKCakRTEhNZqJaVFkJ0QQHDSIhqbDiWR8slna+bxQeQBKt0PJdnOoem0R1BZCW6N5vHQ7rFsJkanmQm2pUyBlivkchzMALyLScwFNukNDQ5k+fTq5ubksXLgQMBdSy83N5a677ur2c3w+X6ch5Cez2WzYbBqi0mvU0y0iIiLSIxaLhcz4cDLjw1k4NQ2ANq+PA2X17DpWy+5jbnaX1LG3xE19y3E2Halm05Fq//32ECvjU6K4KC2aCanRjE2JZFRiJI7QQTY32hoEiWPNMvmGjuPti7Yd+hTyP4RDn4GnBPa8ZZZ2YXHmcHRnBjiHm4u1JY4zh6mHhvf/+4icRcCHly9dupTFixeTk5PDzJkzWbVqFQ0NDdxyyy0A3HzzzaSlpbFy5UrAHC6ek5PDyJEjaWlp4YMPPuAPf/gDq1evDuRrDB3V2qNbREREpLeEBFkZnxrF+NQorp9hHjvu9XGoooHdx+rYU+I+8bWOhlYv3xbV8u1JQ9OtFsiMC2dsSiTjkqMYmxLFuJRI0pyOwbdqevuibVN/bpa2Zihaf2If8e1m73dtETRWmaVk23cfALFZkHkpZP3ALGGx/f4aIt8V8KT7+uuvp6KighUrVuByuZgyZQpr1671L65WVFSE1doxjKahoYE777yTo0eP4nA4GDt2LK+88grXX399oF5h6GjxQGOl+b2SbhEREZE+ERxkZUxyJGOSI7luunnM5zM4XGUm4ruO1rHP5WZfqYfqhlYKKhsoqGzgg10d23hF2oMZlxLF+BNlTHIk2YkRg2sf8RA7jLzcLO2a604MRT9RqgvMBdvK90FDhbmKevUh+Pb/ARZInmhuYxY/2uwRjx9tfo4NDg3UW8kQFPB9uvub9vw8D67d8Pwl4IiF+w4HujYiIhckxakOaguRMzMMg4r6FvJKPeS53OSVetjn8nCw3EObt+uP+MNiHIxJMhP6sSlRjE+JJDMufPDNFe9KfYXZ+12wDgo+M1dS74rFaq6SHpsFcdnm0PT2/cXVMy7nYFDs0y2DjBZRExEZ0p577jmefPJJXC4XkydP5plnnmHmzJldXvu73/3OP1Wsnc1mo7m5uT+qKjIkWCwWEiPtJEba+d7oBP/x1uM+DlXUs7fE3DN8b6mb/WX1VNa3cLSmiaM1TeTmlfuvDw22MjIhgtFJEYxOimRUYgSjkiLJiA0jaDCtoB6RAKOvMguAxwVHN3dsYVaZD5UHzZXT23vKC9Z1fkZMJmRfCaOuMoeph4b191vIBUhJt3SfFlETERmy3njjDZYuXcrzzz/PrFmzWLVqFfPmzSM/P5/ExMQu74mKiiI/P9//86CbXyoySIUGWxmXEsW4lM49bzUNrewv87C/zOwRzyt1k+fy0NjqZV+pmaB/9zlZ8eFkJ0YwKjGSUUkRjEqMIDM+nJDB0DMemQzjfmSWdoYB9eXmsPTqQyf2Ft8H5XlQV2R+3t38olmC7RA/CmzRYIs0izMdkiaaJW6kuSicyFko6ZbuU9ItIjJkPf3009x6663+3uvnn3+e999/n5deeolly5Z1eY/FYjnjFqAi0r9iwkOZlRXHrBNbmIE5V7y4ppH9ZfX+hHx/WT0FFfW0HPeR5/KQ5/IApf57gq0WhseFkZ0YwciEiBPJeCQjEyIG/krqFgtEJpll+OzO55rroPAbOPAx7P8Y3EfNPcVPJ9hhbmWWMRuGXwLpM8GuqTByKiXd0n3+lcs1vFxEZChpbW1l69atLF++3H/MarUyd+5c1q9ff9r76uvrGT58OD6fj2nTpvHYY48xYcKE017f0tLSaQtQt9t92mtFpHdYrRaGx4UzPC6cK8cn+Y97fQbHapo4UO7hQHk9B8vrOVBmft/Y6uVQRQOHKhqAMv89Fgukx4T5h6ePbk/GE8MJCx0EaYc9GsYsMIthmEPS645Ci9tcULi5zuwdd+0254u3NZqrqxeth6+eNueKp0yBrO/DiO+b+4uHOAL9VjIADIK/fhkw1NMtIjIkVVZW4vV6/TuLtEtKSiIvL6/Le8aMGcNLL73EpEmTqKur46mnnmLOnDns2bOHYcOGdXnPypUrefjhh3u9/iJy7oKsFjLiwsiIC+OKcR3/7RuGQUldM4fK6zlUcSIZP5GUVze0UlTdSFF1Y6c54wAp0XZGxIf7S2acuV95RmwYocEDcKi6xdKxl3hXfF5ziHrRBrN3vOgb87Nyybdm+erXEBRqDnEPi4fwBIhIhORJMCzHHJ6uFdSHDCXd0j0+r7nYBCjpFhGRs5o9ezazZ3cM3ZwzZw7jxo3jt7/9LY888kiX9yxfvpylS5f6f3a73aSnp/d5XUWk+ywWC2lOB2lOR6fF2wCq6lvYX1bPwXKPf7j6gRPJeGldM6V1zXxzqKrTPVYLpMeGkRUfTlaCOVw9Mz6MEfHhJEXasQ7UhdysQeZ87/hRMO0m81jdMTj8hbk42+HPwVPasWDbdwXZIGVSxzZm8aPNldSd6RBs69dXkb6npFu6x30MfG3mv9hFpQa6NiIi0o/i4+MJCgqirKys0/GysrJuz9kOCQlh6tSpHDx48LTX2Gw2bDZ92BQZrOIibMyOsDF7ZFyn4zUNrRyuauBwRQMFlfUcqWzkcGUDR6oaaGz1UljVSGFVI5/lV3S6zx5iZXhsOCMTw8lOiCA7KZLshAiGx4UNzP3Go9Ngyo1mMQyoKwZPmbl/eGMl1BabveBHt0Bzrbmy+tHN33mIBSJTwJlhbmsWkQjhJ3rK47Ih/WKwDsCRAXJGA/CvVQak9qHlzgyt0igiMsSEhoYyffp0cnNzWbhwIQA+n4/c3Fzuuuuubj3D6/Wya9curr766j6sqYgMRDHhocSEhzItI6bTccMwqPC0UFDZwKGKegoqzK9HKhsormmiuc1HfpmH/DLPKc+MjwglPTaMjFizV9zsJQ8nK36ALOZmsZifm50Zp54zDHNoesk2qDxgrqBeeQCqDsLxJvCUmKW4i+c6h8PUn8PkG81ecRkUlHRL92gRNRGRIW3p0qUsXryYnJwcZs6cyapVq2hoaPCvZn7zzTeTlpbGypUrAfiP//gPLr74YrKzs6mtreXJJ5+ksLCQf/zHfwzka4jIAGKxWEiMspMYZefirM69421eH8dqmjh8IiFvnzt+qKKe2sY2KutbqaxvZVtR7SnPTYy0kRkXTkZcGJlxYQyPM+eRD48LI9Ie0k9vdwYWi7ndWNzIzscNAxqroLbQHJJed8zsJW+oMLc5K95onvvsUfjsMUieCGFx4IgxS1uTufCb+xi4SyFmOFz0U7PEDA/MuwqgpFu6S4uoiYgMaddffz0VFRWsWLECl8vFlClTWLt2rX9xtaKiIqwnDXmsqanh1ltvxeVyERMTw/Tp0/nmm28YP358oF5BRAaRkCArmfHmYmuXj03sdK6uqY3i6kaKqxsprG6koKKeQxUNFFTUU9PYRrmnhXJPC5uOVJ/y3LjwUHOBuNiOkpUQzoj4CGLCQrBYAjiH3GI5MZQ8HtKmn3q+tRH2/QW2/QGOfHnm7cwAKvLg00fMkjEbRs+DYTMhdSqEhvXNO0iXLIZhGIGuRH9yu91ER0dTV1dHVJT20eu2N2+BPW/BVY/CnO4NJRQRkXOnONVBbSEi56qmoZXC6kYKqxooqmrkSFUjR6oaOFLZQFVD6xnvjXaEkBEbRkq0nVSng1SnnZRoh//7xEg7QQNlYbeaQnNLs6aajhIcClHDzLnlEclQvAF2vgGHvwROSvmswZB8kbm3eNYPzITcFhGoNxnUuhun1NMt3dP+L2lx2YGth4iIiIjIabTPH5+S7jzlnLu5jaKqRv+2ZoVVjRRVmwu8ldQ1U9fUxq5jdew6Vtfls4Os5srtJ299NjIhgtFJESRE2vq3lzxm+NmHjMdnm/O/3SWw98/m1mbFm6DeZc4nL9kG658Fa8iJ3u9w8LaBt8W8P30WjLoSMuZoe7PzpJ5uObu6o/DrCWCxwq8Og8MZ6BqJiFywFKc6qC1EpL80tXo5UtXA0ZomSuuaKKltpqS243uXuxmv7/RpU7QjhFGJEWTEhTHM6SAtxsGwmDCGxZg95SFBA2TF8fZV1Ys2mNuaFXwBdV1saXay0AgYeTlMvA5Gz4cQR//UdRBQT7f0nkOfmV/TpivhFhEREZELjiM0iHEpUYxL6Tpx8voMyj3NFFY1cqSygcOVDRRUNnCwvJ7CqgbqmtrYUljDlsKaU+61WiAluj0RdzDM2ZGQj0gIJznK3n+95Cevqj7pZ2YSXnPY3MbMMCAoxNwnvLURCj6DAx+bC7nt+4tZbFEw/sdm8u07Ds11ZmkoN4e8ty8CZ7FC1uXmPPKRV0B43NnrdgFTT7ec3Z/+Hnb/L3zvV/DD+wNdGxGRC5riVAe1hYgMBs1tXgoqGjhQ7uFoTRPHaps4VtPE0ZpGjtY00XLcd8b7HSFB5nD1hHDSY8JIjzWT8jSng+RoOxGB3JPc54PS7bDvXdj5JriP9uAhFnP++Jy7YNS8zvuMN7vhUK6ZzI/4npn0DyLq6Zbe4fNBwefm9yMvD2xdREREREQGGHtIEONToxifemrSZRgGFfUtFFd3JOHtiXnxibnlTW1e9pa62Vvq7vL54aFBJEXZSYqyk+K0kxrtIMVpJyM2jNFJkST25XxyqxXSppnlhyug6BvYsQZKtpuLr9mjzeKINeeYO0/MNW+ugwOfmKVsFxR+ZZaEcXDJPWCPgp1/hP1r4Xiz+bvC4mD8QrjoJ5B+cefkfJBTT7ecWelO+O1lEBIO9x3RIgoiIn1McaqD2kJELnRtXh9F1Y0crmjwzykvrm70J+b1LcfP+owoezCjkiJJjrYTFhJEWGgQYbZghsU4mJTmZExyJKHBAUxga4th84uw+SVo9Zx6Pi4bmmqhsbLzsdl3weQbIcTeb1U9V+rplt5RcGI+d+alSrhFRERERHpRSJCVkQkRjEzoesuuhpbjlHtaKHM3+xd1a/96pNJM1N3Nx9naxVzydqFBVsalRJKdGElGbBjD48JIjw0j1WknIcJGcF8v8uZMhyv/Ay77JWx5CTb9XzB8MPHv4KKfQspk8Hnh8DrY9b/m3PGqg/DevfDZozDjVohKAU8ZeErNOeYYYAkCaxAEOyDr+zBmAdgi+/Zdekg93XJmv19oJt7zH4eL7wh0bURELniKUx3UFiIiZ9bc5uVwZQMHyuupqm+hsdVLU6uX+pbjHKqoZ+fROuqa2k57v9UCCZE2kk8MX0+ONktKtDl8PTMunNjw0P7dDq3FA9/+ATb8xlxpvbuC7TDqKphwLWReBhEJfVfHE9TTLeevrRmK1pvfZ2k+t4iIiIjIQGIPOfOq64ZhUFTdyK5jdRypbPDvT15c3UiZpwWvz6DM3UKZuwXoen/ySHsw6TFh2EOshARZCQ22Eh4azKT0aKZlxDB5mBNHaFDvvZQtEmbfCTNvNfcX3/6auRp6ZBJEJENEovmz4TN7yBsqzIXeqg6aX/e9az4nNsucG542zVytPSoVIlMhLNZcxb0fqadbTq9gHfz+xxCZAkv39fsfp4jIUKQ41UFtISLSd7w+g6r6FlzuZkrrmilzN+OqM/ckL6ltoqiqkZK65rM+J9hqISshHKcjlEh7MJH2YBIibYxKimRsciSjEiP9SblhGLR6fYRYrVitvZhbGAa4dsGetyB/LVTsO/21QTb46e9g7NXn/WvV0y3nr31/7qwfKOEWEREREbmABFktJEbZSYyyM2lY19c0t3kpqm7kWG0Trcd9tHnNUulpZVtxDVsLayhzt7C/rP60v8digQhbMK3Hff7t0yJtwUzJcDI13cnU4TFMSIki4XxWYbdYIGWSWeY+BE015t7jxRvNZNxdYpbGSvC2gCOmZ7+nh5R0y+m1L6KmoeUiIiIiIkOOPSSI0UmRjE7qeoEywzA4VttEQUUDnubjeJrb8DQf51htE/vLPOwv81BZ34qnufMq7J6W43x5oJIvD3SsWB5pC2ZEQjhZ8eEkRdmJcoQQ7QjBGRZCekwYWQnhRNq7uY+3IwZGXWmWkx1vMRdji0g6p3Y4X0q6pWsNVeZ2YWD2dIuIiIiIiJzEYrEwLCaMYTFhp72msr6FuqY27CFB2ILNeeFHaxr5tqiWbUU1bC+q5UhVA56W4+w8WsfOo13PLQdIirKRFR9BitNOYqSdxEgbiVE2hsWEkREbRkxYyJl7y4NtEJN5Hm/cMwMi6X7uued48skncblcTJ48mWeeeYaZM2d2ee2LL77I73//e3bv3g3A9OnTeeyxx057fZ9qqoH6iv7/vf2hYB1gQOJ4c9ECERERERGRcxQfYSM+wtbpWLQjmgmp0dx08XCgYxh7QUU9BZUNVNe3UtfURl1TG7WNbRypajixdVr7om9dizixP3ly9ImEPNJOQqQNZ1h7r3ko0Y4QUqLt2EN6cfG3swh40v3GG2+wdOlSnn/+eWbNmsWqVauYN28e+fn5JCYmnnL9unXruPHGG5kzZw52u50nnniCq666ij179pCWlta/ld/9v/D+L/v3d/Y3DS0XEREREZE+dLZh7ADu5jYOlddTUGEm4OWeZjMRr2umuKaRMncL9S3HyXN5yHN5zvj7Xrw5hyvH91/HYsBXL581axYzZszg2WefBcDn85Gens7dd9/NsmXLznq/1+slJiaGZ599lptvvvms1/fqSqjf/gE+/vfze8ZA5nDCDa9D0vhA10REZMjQit0d1BYiItJdzW1ejtY0UlzTRIW7hTK3mZRXeFr8vebt5eVbZjAjM/a8f+egWL28tbWVrVu3snz5cv8xq9XK3LlzWb9+fbee0djYSFtbG7Gx599o52zaTWYRERERERGRgLGHBJGdGEl24ul7ywMloEl3ZWUlXq+XpKTOXftJSUnk5eV16xn33XcfqampzJ07t8vzLS0ttLR0jPt3u909r7CIiIiIiIjIObAGugLn4/HHH2fNmjW8/fbb2O32Lq9ZuXIl0dHR/pKent7PtRQREREREZGhKqBJd3x8PEFBQZSVlXU6XlZWRnJy8hnvfeqpp3j88cf5+OOPmTRp0mmvW758OXV1df5SXFzcK3UXEREREREROZuAJt2hoaFMnz6d3Nxc/zGfz0dubi6zZ88+7X3/+Z//ySOPPMLatWvJyck54++w2WxERUV1KiIiIiIiIiL9IeBbhi1dupTFixeTk5PDzJkzWbVqFQ0NDdxyyy0A3HzzzaSlpbFy5UoAnnjiCVasWMFrr71GZmYmLpcLgIiICCIiIgL2HiIiIiIiIiLfFfCk+/rrr6eiooIVK1bgcrmYMmUKa9eu9S+uVlRUhNXa0SG/evVqWltb+clPftLpOQ8++CAPPfRQf1ZdRERERERE5IwCvk93f9OenyIiMpApTnVQW4iIyEDW3Tg1qFcvFxERERERERnIlHSLiIiIiIiI9BEl3SIiIiIiIiJ9REm3iIiIiIiISB8J+Orl/a193Ti32x3gmoiIiJyqPT4NsXVOu6SYLSIiA1l3Y/aQS7o9Hg8A6enpAa6JiIjI6Xk8HqKjowNdjYBSzBYRkcHgbDF7yG0Z5vP5KCkpITIyEovFct7Pc7vdpKenU1xcrO1MzoHarWfUbj2jdusZtVvPnU/bGYaBx+MhNTUVq3VozwLrzZitv+eeUbv1nNquZ9RuPaN265nzbbfuxuwh19NttVoZNmxYrz83KipKf+A9oHbrGbVbz6jdekbt1nM9bbuh3sPdri9itv6ee0bt1nNqu55Ru/WM2q1nzqfduhOzh/Y/oYuIiIiIiIj0ISXdIiIiIiIiIn1ESfd5stlsPPjgg9hstkBXZVBRu/WM2q1n1G49o3brObXdwKP/TXpG7dZzarueUbv1jNqtZ/qr3YbcQmoiIiIiIiIi/UU93SIiIiIiIiJ9REm3iIiIiIiISB9R0i0iIiIiIiLSR5R0n4fnnnuOzMxM7HY7s2bNYtOmTYGu0oCycuVKZsyYQWRkJImJiSxcuJD8/PxO1zQ3N7NkyRLi4uKIiIjguuuuo6ysLEA1Hpgef/xxLBYL9957r/+Y2q1rx44d4+c//zlxcXE4HA4uuugitmzZ4j9vGAYrVqwgJSUFh8PB3LlzOXDgQABrPDB4vV4eeOABRowYgcPhYOTIkTzyyCOcvOSH2g6++OILfvSjH5GamorFYuGdd97pdL47bVRdXc2iRYuIiorC6XTyD//wD9TX1/fjWwxditlnpph9/hSvz41i9rlTvO6+ARezDemRNWvWGKGhocZLL71k7Nmzx7j11lsNp9NplJWVBbpqA8a8efOMl19+2di9e7exfft24+qrrzYyMjKM+vp6/zW33367kZ6ebuTm5hpbtmwxLr74YmPOnDkBrPXAsmnTJiMzM9OYNGmScc899/iPq91OVV1dbQwfPtz4xS9+YWzcuNEoKCgwPvroI+PgwYP+ax5//HEjOjraeOedd4wdO3YYf/u3f2uMGDHCaGpqCmDNA+/RRx814uLijPfee884fPiw8eabbxoRERHGf/3Xf/mvUdsZxgcffGDcf//9xltvvWUAxttvv93pfHfaaP78+cbkyZONDRs2GF9++aWRnZ1t3Hjjjf38JkOPYvbZKWafH8Xrc6OY3TOK19030GK2ku4emjlzprFkyRL/z16v10hNTTVWrlwZwFoNbOXl5QZgfP7554ZhGEZtba0REhJivPnmm/5r9u3bZwDG+vXrA1XNAcPj8RijRo0yPvnkE+P73/++P4ir3bp23333GZdeeulpz/t8PiM5Odl48skn/cdqa2sNm81mvP766/1RxQHrmmuuMf7+7/++07G/+7u/MxYtWmQYhtquK98N4N1po7179xqAsXnzZv81H374oWGxWIxjx471W92HIsXsc6eY3X2K1+dOMbtnFK97ZiDEbA0v74HW1la2bt3K3Llz/cesVitz585l/fr1AazZwFZXVwdAbGwsAFu3bqWtra1TO44dO5aMjAy1I7BkyRKuueaaTu0DarfTeffdd8nJyeGnP/0piYmJTJ06lRdffNF//vDhw7hcrk7tFh0dzaxZs4Z0uwHMmTOH3Nxc9u/fD8COHTv46quvWLBgAaC2647utNH69etxOp3k5OT4r5k7dy5Wq5WNGzf2e52HCsXsnlHM7j7F63OnmN0zite9IxAxO/j8qz30VFZW4vV6SUpK6nQ8KSmJvLy8ANVqYPP5fNx7771ccsklTJw4EQCXy0VoaChOp7PTtUlJSbhcrgDUcuBYs2YN3377LZs3bz7lnNqtawUFBaxevZqlS5fyb//2b2zevJl/+qd/IjQ0lMWLF/vbpqv/bodyuwEsW7YMt9vN2LFjCQoKwuv18uijj7Jo0SIAtV03dKeNXC4XiYmJnc4HBwcTGxurduxDitnnTjG7+xSve0Yxu2cUr3tHIGK2km7pF0uWLGH37t189dVXga7KgFdcXMw999zDJ598gt1uD3R1Bg2fz0dOTg6PPfYYAFOnTmX37t08//zzLF68OMC1G9j++Mc/8uqrr/Laa68xYcIEtm/fzr333ktqaqraTmQIUszuHsXrnlPM7hnF68FLw8t7ID4+nqCgoFNWnywrKyM5OTlAtRq47rrrLt577z0+++wzhg0b5j+enJxMa2srtbW1na4f6u24detWysvLmTZtGsHBwQQHB/P555/z3//93wQHB5OUlKR260JKSgrjx4/vdGzcuHEUFRUB+NtG/92e6l//9V9ZtmwZN9xwAxdddBE33XQT//zP/8zKlSsBtV13dKeNkpOTKS8v73T++PHjVFdXqx37kGL2uVHM7j7F655TzO4ZxeveEYiYraS7B0JDQ5k+fTq5ubn+Yz6fj9zcXGbPnh3Amg0shmFw11138fbbb/Ppp58yYsSITuenT59OSEhIp3bMz8+nqKhoSLfjFVdcwa5du9i+fbu/5OTksGjRIv/3ardTXXLJJadsb7N//36GDx8OwIgRI0hOTu7Ubm63m40bNw7pdgNobGzEau0cDoKCgvD5fIDarju600azZ8+mtraWrVu3+q/59NNP8fl8zJo1q9/rPFQoZnePYva5U7zuOcXsnlG87h0Bidk9XQVuqFuzZo1hs9mM3/3ud8bevXuN2267zXA6nYbL5Qp01QaMO+64w4iOjjbWrVtnlJaW+ktjY6P/mttvv93IyMgwPv30U2PLli3G7NmzjdmzZwew1gPTyauhGobarSubNm0ygoODjUcffdQ4cOCA8eqrrxphYWHGK6+84r/m8ccfN5xOp/HnP//Z2Llzp/HjH/94SG6j8V2LFy820tLS/FuQvPXWW0Z8fLzxq1/9yn+N2s5coXjbtm3Gtm3bDMB4+umnjW3bthmFhYWGYXSvjebPn29MnTrV2Lhxo/HVV18Zo0aN0pZh/UAx++wUs3uH4nX3KGb3jOJ19w20mK2k+zw888wzRkZGhhEaGmrMnDnT2LBhQ6CrNKAAXZaXX37Zf01TU5Nx5513GjExMUZYWJhx7bXXGqWlpYGr9AD13SCuduvaX/7yF2PixImGzWYzxo4da7zwwgudzvt8PuOBBx4wkpKSDJvNZlxxxRVGfn5+gGo7cLjdbuOee+4xMjIyDLvdbmRlZRn333+/0dLS4r9GbWcYn332WZf/n7Z48WLDMLrXRlVVVcaNN95oREREGFFRUcYtt9xieDyeALzN0KOYfWaK2b1D8br7FLPPneJ19w20mG0xDMM49/5xERERERERETkbzekWERERERER6SNKukVERERERET6iJJuERERERERkT6ipFtERERERESkjyjpFhEREREREekjSrpFRERERERE+oiSbhEREREREZE+oqRbREREREREpI8o6RaRfmOxWHjnnXcCXQ0RERE5A8Vrkd6lpFtkiPjFL36BxWI5pcyfPz/QVRMREZETFK9FLjzBga6AiPSf+fPn8/LLL3c6ZrPZAlQbERER6YritciFRT3dIkOIzWYjOTm5U4mJiQHMoWSrV69mwYIFOBwOsrKy+NOf/tTp/l27dvHDH/4Qh8NBXFwct912G/X19Z2ueemll5gwYQI2m42UlBTuuuuuTucrKyu59tprCQsLY9SoUbz77rv+czU1NSxatIiEhAQcDgejRo065UOHiIjIhU7xWuTCoqRbRPweeOABrrvuOnbs2MGiRYu44YYb2LdvHwANDQ3MmzePmJgYNm/ezJtvvslf//rXTkF69erVLFmyhNtuu41du3bx7rvvkp2d3el3PPzww/zsZz9j586dXH311SxatIjq6mr/79+7dy8ffvgh+/btY/Xq1cTHx/dfA4iIiAwCitcig4whIkPC4sWLjaCgICM8PLxTefTRRw3DMAzAuP322zvdM2vWLOOOO+4wDMMwXnjhBSMmJsaor6/3n3///fcNq9VquFwuwzAMIzU11bj//vtPWwfA+Pd//3f/z/X19QZgfPjhh4ZhGMaPfvQj45ZbbumdFxYRERmEFK9FLjya0y0yhFx++eWsXr2607HY2Fj/97Nnz+50bvbs2Wzfvh2Affv2MXnyZMLDw/3nL7nkEnw+H/n5+VgsFkpKSrjiiivOWIdJkyb5vw8PDycqKory8nIA7rjjDq677jq+/fZbrrrqKhYuXMicOXN69K4iIiKDleK1yIVFSbfIEBIeHn7K8LHe4nA4unVdSEhIp58tFgs+nw+ABQsWUFhYyAcffMAnn3zCFVdcwZIlS3jqqad6vb4iIiIDleK1yIVFc7pFxG/Dhg2n/Dxu3DgAxo0bx44dO2hoaPCf//rrr7FarYwZM4bIyEgyMzPJzc09rzokJCSwePFiXnnlFVatWsULL7xwXs8TERG50Cheiwwu6ukWGUJaWlpwuVydjgUHB/sXP3nzzTfJycnh0ksv5dVXX2XTpk38z//8DwCLFi3iwQcfZPHixTz00ENUVFRw9913c9NNN5GUlATAQw89xO23305iYiILFizA4/Hw9ddfc/fdd3erfitWrGD69OlMmDCBlpYW3nvvPf+HCBERkaFC8VrkwqKkW2QIWbt2LSkpKZ2OjRkzhry8PMBcqXTNmjXceeedpKSk8PrrrzN+/HgAwsLC+Oijj7jnnnuYMWMGYWFhXHfddTz99NP+Zy1evJjm5mZ+/etf8y//8i/Ex8fzk5/8pNv1Cw0NZfny5Rw5cgSHw8Fll13GmjVreuHNRUREBg/Fa5ELi8UwDCPQlRCRwLNYLLz99tssXLgw0FURERGR01C8Fhl8NKdbREREREREpI8o6RYRERERERHpIxpeLiIiIiIiItJH1NMtIiIiIiIi0keUdIuIiIiIiIj0ESXdIiIiIiIiIn1ESbeIiIiIiIhIH1HSLSIiIiIiItJHlHSLiIiIiIiI9BEl3SIiIiIiIiJ9REm3iIiIiIiISB9R0i0iIiIiIiLSR/4/XY3HL1N/IaIAAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "mXXoP63rHMMz"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}