ECT - MMF2 - Experimento 4 - Aceleração Variável

mmf2_exp4_aceleracao_variavel.ipynb

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      "source": [
        "# ECT3403 - MODELAGEM DO MUNDO FÍSICO II\n",
        "## Atividade Experimental 4:  Aceleração variável\n",
        "> Utilização de corrente como contrapeso e verificação do comportamento da velocidade e aceleração do carrinho sobre trilho.\n",
        "\n",
        "**Bancada**: 2 <br>\n",
        "**Integrantes**:\n",
        "1. Eduardo Eudes Prazeres Lopes\n",
        "2. José Fabiano Costa de Lima\n",
        "3. Nelis Nelson Arruda da Cruz Júnior\n",
        "4. Taise de Azevedo Souza\n",
        "\n"
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      "source": [
        "# @title Bibliotecas\n",
        "# Bibliotecas\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n"
      ],
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        "# @title Dados iniciais\n",
        "# Dados iniciais\n",
        "x_max = 1.760  # @param {\"type\":\"number\",\"placeholder\": \"Altura máxima\"},\n",
        "x1 = 1.180     # @param {\"type\":\"number\",\"placeholder\": Posição onde a corrente toca o chão\"},\n",
        "x2 = 0.700     # @param {\"type\":\"number\",\"placeholder\": Posição onde o fio distensiona\"},\n",
        "a0 = -0.3430   # @param {\"type\":\"number\",\"placeholder\": Aceleração inicial\"},\n",
        "delta_t = 0.010 # @param {\"type\":\"number\", \"placeholder\": Intervalo de tempo a ser incrementado\"},\n",
        "\n"
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        "# @title Cálculos\n",
        "\n",
        "# Tempo em segundos\n",
        "# t_total = 2.56  # fixo\n",
        "t_total = np.sqrt(2 * x_max / abs(a0))  # Simplificado para aceleração média\n",
        "tempo = np.arange(0, t_total, delta_t)\n",
        "\n",
        "# Inicialização das variáveis\n",
        "posicao = [x_max]\n",
        "velocidade = [0]  # Velocidade inicial é 0\n",
        "aceleracao = [a0] # Aceleração inicial\n",
        "x_atual = x_max\n",
        "v_atual = 0\n",
        "a_atual = a0\n",
        "\n",
        "for t in tempo[1:]:\n",
        "    # Condições para a aceleração\n",
        "    if x_atual > x1:\n",
        "        a_atual = a0\n",
        "    elif x_atual >= x2 and x_atual <= x1:\n",
        "        a_atual = a0 * (x_atual - x2) / (x1 - x2)\n",
        "    else:\n",
        "        a_atual = 0\n",
        "\n",
        "    # Atualizar velocidade\n",
        "    v_atual = v_atual + a_atual * delta_t\n",
        "    velocidade.append(v_atual)\n",
        "\n",
        "    # Atualizar posição\n",
        "    x_atual = x_atual + v_atual * delta_t\n",
        "    posicao.append(x_atual)\n",
        "\n",
        "    # Atualizar aceleração e adicioná-la à lista\n",
        "    aceleracao.append(a_atual)\n",
        "\n",
        "# Criar DataFrame\n",
        "dados = pd.DataFrame({\n",
        "    \"Tempo (s)\": tempo,\n",
        "    \"Posição (m)\": posicao,\n",
        "    \"Velocidade (m/s)\": velocidade,\n",
        "    \"Aceleração (m/s²)\": aceleracao\n",
        "})"
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        "# @title Exibir a tabela formatada\n",
        "from IPython.display import display\n",
        "\n",
        "# Visualizar os dados\n",
        "display(dados)\n"
      ],
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              "     Tempo (s)  Posição (m)  Velocidade (m/s)  Aceleração (m/s²)\n",
              "0         0.00     1.760000          0.000000             -0.343\n",
              "1         0.01     1.759966         -0.003430             -0.343\n",
              "2         0.02     1.759897         -0.006860             -0.343\n",
              "3         0.03     1.759794         -0.010290             -0.343\n",
              "4         0.04     1.759657         -0.013720             -0.343\n",
              "..         ...          ...               ...                ...\n",
              "316       3.16     0.212660         -0.750009              0.000\n",
              "317       3.17     0.205160         -0.750009              0.000\n",
              "318       3.18     0.197660         -0.750009              0.000\n",
              "319       3.19     0.190160         -0.750009              0.000\n",
              "320       3.20     0.182660         -0.750009              0.000\n",
              "\n",
              "[321 rows x 4 columns]"
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              "    <path d=\"M7,19H8.4L18.45,9,17,7.55,7,17.6ZM5,21V16.75L18.45,3.32a2,2,0,0,1,2.83,0l1.4,1.43a1.91,1.91,0,0,1,.58,1.4,1.91,1.91,0,0,1-.58,1.4L9.25,21ZM18.45,9,17,7.55Zm-12,3A5.31,5.31,0,0,0,4.9,8.1,5.31,5.31,0,0,0,1,6.5,5.31,5.31,0,0,0,4.9,4.9,5.31,5.31,0,0,0,6.5,1,5.31,5.31,0,0,0,8.1,4.9,5.31,5.31,0,0,0,12,6.5,5.46,5.46,0,0,0,6.5,12Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_47b880c5-1bae-4c05-8cf5-7150e21aa65e button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('dados');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "dados",
              "summary": "{\n  \"name\": \"dados\",\n  \"rows\": 321,\n  \"fields\": [\n    {\n      \"column\": \"Tempo (s)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.9280894353455383,\n        \"min\": 0.0,\n        \"max\": 3.2,\n        \"num_unique_values\": 321,\n        \"samples\": [\n          1.73,\n          1.32,\n          1.97\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Posi\\u00e7\\u00e3o (m)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.49248541218950487,\n        \"min\": 0.18265985298683876,\n        \"max\": 1.76,\n        \"num_unique_values\": 321,\n        \"samples\": [\n          1.2437507000000008,\n          1.4589146000000002,\n          1.091239099937699\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Velocidade (m/s)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.24900709131701862,\n        \"min\": -0.7500093598502874,\n        \"max\": 0.0,\n        \"num_unique_values\": 253,\n        \"samples\": [\n          -0.6998260043553223,\n          -0.02058,\n          -0.2709699999999996\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Acelera\\u00e7\\u00e3o (m/s\\u00b2)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.1462218219841786,\n        \"min\": -0.343,\n        \"max\": 0.0,\n        \"num_unique_values\": 70,\n        \"samples\": [\n          -0.24048083140948706,\n          -0.343,\n          -0.10151059217061827\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# @title Gráficos\n",
        "plt.figure(figsize=(10, 8))\n",
        "\n",
        "# Posição\n",
        "plt.subplot(3, 1, 1)\n",
        "plt.plot(tempo, posicao, label=\"Posição (m)\")\n",
        "plt.title(\"Posição vs. Tempo\")  # Título do gráfico\n",
        "plt.xlabel(\"Tempo (s)\")\n",
        "plt.ylabel(\"Posição (m)\")\n",
        "plt.legend()\n",
        "\n",
        "# Velocidade\n",
        "plt.subplot(3, 1, 2)\n",
        "plt.plot(tempo, velocidade, label=\"Velocidade (m/s)\", color=\"orange\")\n",
        "plt.title(\"Velocidade vs. Tempo\")  # Título do gráfico\n",
        "plt.xlabel(\"Tempo (s)\")\n",
        "plt.ylabel(\"Velocidade (m/s)\")\n",
        "plt.legend()\n",
        "\n",
        "# Aceleração\n",
        "plt.subplot(3, 1, 3)\n",
        "plt.plot(tempo, aceleracao, label=\"Aceleração (m/s²)\", color=\"green\")\n",
        "plt.title(\"Aceleração vs. Tempo\")  # Título do gráfico\n",
        "plt.xlabel(\"Tempo (s)\")\n",
        "plt.ylabel(\"Aceleração (m/s²)\")\n",
        "plt.legend()\n",
        "\n",
        "# Título geral para todos os gráficos\n",
        "plt.suptitle(\"Análise do Movimento no Experimento do Trilho com Carrinho\", fontsize=16)\n",
        "\n",
        "# Ajuste do layout para mais espaço entre os gráficos\n",
        "plt.subplots_adjust(hspace=0.5)  # Aumenta o espaço entre os subgráficos\n",
        "plt.show()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 573
        },
        "cellView": "form",
        "id": "CWMZ7xtQ95Zc",
        "outputId": "f0eb8638-dc78-463e-a0c7-70a12ddd5c0b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x800 with 3 Axes>"
            ],
            "image/png": 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bi8OHDxuMp3HjxmXmM/Z+ycnJkX6oGDt2rMjOztYrz8jIENu3b69xDHe/z+8998fGxkrnqWbNmomBAweK3Nxcqfzo0aPC3NxcyOXyMt8PynPlyhVpfXv37q3063G3zZs3i1u3bpWZfvDgQWFrayssLCzEjRs39MpKj4XSz+jMzMwy8xvrHFTVY6e6n4cjRowQAES7du309lt2drbo27evAHQ/DpIOk6x64uWXXxYAxNChQ/Wmv/vuu+V+IAjx74fC448/brC8T58+903SDDl79qwAINq0aVOmrCpJ1pEjR6STc2WcO3dOyGQy4enpKX1hu1e/fv0EgDInjfK8+eabBr+0lZo5c6bBD/u7W/oMnRQ3bNggAAgbGxuRn59fqVjuTbJKkx5ra2vpw+vLL78UAMTChQuFEKLcJOuNN94QAESrVq0Mruv999+Xvvze7dVXXzX45V0IXesRAPHEE0/oTa9MkrVp06Yyy/vwww+lX9rOnDlTpvy5554TQNlWqdIP9Q0bNhjctnXr1hl8r5Qem7NnzzY4X+kPFvd+CFeUZNXGsVD6mspkMr0v76UOHz4sAIhGjRrpTa/ufq9MLBU9HnvsMYPzl7Z+jhgxQhw/flwolUphYWFhMJG/e12//vprmfLExESpNf3AgQPS9NLEbcCAAQZjyM7OFq6ursLc3FzvV/XSLyGOjo5lWrlKVeYLjqEv3L/88st9j/8PPvjAYOJX+iXm/fffNxhP6Xnz3n1c3XN9RUnWvn37BAChVqvF7du3y5T//fffAoCQy+VlErjy1KXz7r0qk2T16NGj3PlrkmTd3UOgVEFBgfTDSXx8vDS9NvZL6Tk+PDy8Uj9UVjeGu89vhs79M2bMEICut8q9P6YKIcTAgQMN/tBQntLzJQBx/vz5Ss1TFfPmzTN4Hig9FiwsLMSVK1cMzmusc1BVjh0hqvd5GBcXJ+RyuZDJZOLUqVNl5rlx44b0A8nd5+dHGa/JqgfuHgBh4sSJemVjx46Fubk59u7diytXrpS7jIEDBxqcHhISAgDlXudw6dIl/PDDD3j33XexaNEiLFy4EGvXrgUAXLhwocrbcrfg4GDY2Nhg8+bN+O9//4tr167dt/7mzZshhEDfvn3LHeWwtJ/zwYMHKxXD7t27AeiugTKkvCGrS+cbOXIklEplmfLHH38cDg4OyM7OxrFjxyoVy73kcjnGjRuHnJwc6VqaZcuWQS6XV9jfvzS+8uKfNGkSAN3+vXXrljS99Nq5tWvXlulLX3p92L3HYEXMzc3Rq1evMtNLb2jt4+OD0NDQcsvvji8lJQVHjhyBpaVlucd0RcdAdd8L5anNY8HHxwdhYWGVjrW6+72yxo0bV+6jR48eBudZtmwZGjVqhLVr16J79+4oLCzE22+/jfbt25e7Hnt7ewwaNKjMdFdXV2lY7dJtBYBNmzYBgHSd6r1Kr/cpKSkxOFBQVFRUjQbl6devX5lppcdvRcf/3ftBq9VK17yUty2tW7eGtbU1Tpw4YfDa2No6vvv06QM3N7cy5a1atUJYWBi0Wi327NlTpWXWxfNuZTzxxBO1slxD+06pVKJRo0YA9PddbeyXLVu2ANCdJ8zMzCqsX9MYKjr3t2rVCq6uruWWV+ccVhOpqan4/vvv8dJLL2HKlCkYP348xo8fL21bed+JWrRoIe3D8tT0HFSVY6ei+QDD54u9e/dCq9WiRYsWaN68eZl5GjRogN69ewPQXedFHMK9Xti0aRNu376tdwCXcnNzQ79+/fD7779j2bJl+O9//2twGeWN/FY6us69H9a3b9/G2LFjsX379nLjysrKqspmlGFjY4Ply5djwoQJeOWVV/DKK6/Aw8MD7du3R58+fTB69GhYW1tL9a9evQpAN9DH/Qb7AHQDd1TGjRs3AAB+fn4Gy8ubXnriKa9cJpPBz88P6enpVf5Sc7cJEybgzTffxLJly9C2bVscOXIEUVFR8PX1ve98FcVnb28PR0dHpKWl4caNG9LIkY0aNULXrl2xe/dubNy4URq98MSJEzh16hQ8PT0NfmG8Hw8PD5iblz3VlO7b8o7N0kT67mPz2rVrEEIgPz/f4Jesu5V3DFT1vVCR2jwWKoq1sLCwSrGUt98rqzpDWtvZ2eGHH35Ax44dkZmZiX79+mH27Nn3nad0kBJDSret9L0L/HtuePLJJ/Hkk0/ed9mGjoua3uTT0H4qPb7LO/4NHd+pqanSedXb27vC9aampqJBgwYVxgLU3vENAP7+/jh16lSlj++6ft6tSG3dmLoq+6429ktcXBwA3Q+glVHTGMrb3up8NtyPi4uL9H9SUhKCgoIqNd/dvvnmGzz//PP3HYypvO9ElTleauMcBFT8vq+NY+7uuo86Jln1QGlCUVBQgK5du5YpLz2YV6xYgddff93gL1ByedUaLYcOHYqDBw9iwIABeOmll9CkSRPY2trCwsICRUVFFX7Brcp6oqKi8Pvvv2Pfvn04cOAANm7ciI0bN+K1117D9u3b0axZMwC6X3kB3c0gDf26f7d27doZJT5T8/PzQ7du3bBr1y7MmzcPQNVbkqpq4sSJ2L17N1asWCElWaWtWGPHjq3UL5x3q+jYq8qxWXoMWFtbY+jQoVWKozrrM7X6FOv9/PDDD9L/MTExyMzMrPHtHMRdI+WVHhfl/aJ+N0M/UFhaWtYolvvtp+oc30Dlbvxs6Dz8sBwzdVlNj5fyPGr7zpifDffTsGFD6celo0ePonPnzlWa/9ixY3j66adhZmaGd955BwMHDoSPjw/UajVkMhm+/vprPP300wZHagYqd7zU5jmoNuajymGSVcclJCRIQ3CmpqbiwIED5da9desWtmzZgv79+9donZcvX8bBgwfh6uqKjRs3lvkV1tg36bOzs9P7Bfr69et47rnn8Ntvv2H69OlSU3zpL7sdO3bEp59+apR1N2jQAOfPnzc4VDyAcqeX/npc+gu6IaXdH+/9pbmqJk6ciF27duGPP/6Ag4MDhgwZUuE8pdtVXnyZmZnS8On3xjd06FBMnz4d0dHRuH79Otzc3LB69WoAupY1Uyo9BmQymdR10tQe5LFQmViqu99ry5o1a/Dll1/Czc0NrVu3xqZNmzBx4kT8/PPP5c5T3vvu7jIvLy9pmre3N86fP49JkybVWleuB8HZ2RmWlpbIz8/H+++/D2dnZ1OHVKnju7SsssdUfTjv1nW1sV98fHwQExOD8+fPIyoqyiQx1Aa5XI6BAwdi5cqV+P777ytsSb/X+vXrIYTAc889h5deeqlMeV26cXFtqi/7uy4x/TcUuq8VK1ZAo9GgXbt2ELqBSgw+St/4FXWjq4zSe7d4enoa7OZS3n1ajMXb21u6d8vJkyel6X379gUA/P7771Xu8lKe0pbBVatWGSwv714Rpdf9rF271mAsGzduRHp6unS/kJoYOnQofH194eTkhAkTJkClUlU4T2l85d3MuPReNIGBgWVOhmq1GiNGjIBWq8X333+PP/74A6mpqejYsSMaN25co22pKU9PTzRv3hzZ2dnS9QO1TaFQAEC592V5kMdCRWqy32vDxYsX8dRTT0Eul2PVqlVYvXo1/P398csvv+CTTz4pd76MjAz88ccfZaYnJydL+/3u+7KVnhse1H3AaouZmRl69uwJ4MFtS2WP7y1btiAxMbFM+YkTJ3Dy5EnI5fIy9xYqT30479Z1tbFfSq93XLZsWaXuN1YbMdSWl19+GRYWFjh16hSWLFlSYf19+/ZJ/5f+MGWoFbygoOC+Pxg9TLp06QK5XI6TJ0/i1KlTZcoTEhKk83P37t0fdHh1EpOsOq70S1FFXUfGjh0LQHez2Mpej1SegIAAyOVynDlzRu/icgD4448/8NFHH9Vo+aVOnDhhcICF0vUA+ie1Fi1aYOjQobh+/Toef/xxg7925ubmYtWqVQZP+IZMmjQJ1tbWOHToUJkvfbt37zZ4I1UAGDZsGHx8fHDr1i3Mnj1b7wvKtWvXMGfOHADAc889V6mk6H4sLS0RGxuLlJQUfPDBB5WaZ8qUKbC1tcXx48fx1ltv6XVjOHHiBN58800AwIsvvmhw/tIuiStWrJCOQVO3YpUqjX3ChAkGv4gLIfDXX39h27ZtRllfaYvJP//8Y7D8QR4LFanpfjemgoICDBs2DNnZ2Xj11VcRGRkJW1tbrFu3DkqlEi+++KLBQShKzZkzR++6q8LCQkybNg25ublo27YtOnbsKJU99dRT8PX1xfr16/Hyyy8jOzu7zPJu376Nb775xrgbWQsWLFgAhUKBF198EStXrtTrQljq7Nmz+OWXX4yyvoqO706dOqFdu3bIz8/H008/rXdT55SUFDz99NMAdINRVOY6MqB+nHfrutrYL5MnT4aXlxdOnDiBKVOmlLn+KCsrS+/Gu7URQ20JCQnBhx9+CACYPXs25s+fb/A8cfHiRYwaNQozZszQmxfQ/Xh19zwFBQV49tlnKxy062Hh4+ODYcOGQQiBp59+GqmpqVJZbm4unnrqKRQUFKBDhw7o0KGDCSOtQx78gIZUWbt37xYAhFKprNQNBUvvSXH30L+lQ87u2rXL4DzlDd/77LPPSkOvdu3aVYwaNUpa/iuvvGJweF0hqjaE+8aNGwUAYWlpKTp27ChGjhypd2NhhUIh/ve//+ktJysrS0RGRkrlbdq0EcOHDxfDhg0Tbdq0kW5GGxMTU+HrVeqnn36SborZrFkzMWrUKNGlSxchk8nE888/X+623n1TTF9fXzFixAjRr18/o92MuDLudzPiP/74Q++GpqNGjRKRkZHC3Nzc4NDR9woJCZG23crKqsw9U0pV5mbEVZnv3m27dyhkIYT4+OOPpe0ICAgQ/fv3F6NHjxY9e/aUbvT68ssv681T3rFZqryh2k+dOiXkcrmQy+UiKipKTJgwQUyaNEn89ttvUh1jHwsVvTZCiHKPy5ru9/JiKd0X93vcfd+ayZMnS8NdazQavWUuXbpUALobV6anp5dZV0REhGjXrp1Qq9ViwIABYvjw4cLT01MAEK6urgaHYT579qx0nyR7e3vRpUsXMXr0aDF48GDRpEkTIZPJhJubm948lblHVGWGT67qfHdvq6F9vG7dOmmoei8vL9GrVy8xZswY0bdvX+k+cCNGjNCbp7rn+tu3b0s3Oe7YsaMYP368mDRpkli2bJlU5+4bzrq6uoonnnhCPPbYY8LW1lYA1bvpbV05796rMkO4l/caC1GzIdzLU956a2O/HD9+XLi7u0vvo/79+4sRI0aIDh06VHgz4srGUJNzvxCVe9+WZ9myZdLxrlKpRJcuXcSoUaPEkCFD9D7zRo4cKc2Tnp4ubaOTk5MYPHiwGDp0qHB1dRU2NjbSLQfujbei7ajsttTGsVPdz8OUlBTpRsd2dnZi8ODB4oknnhAuLi7SOZ03I/4Xk6w67MknnxRA2fsSlaf0HhchISHStOp+8Go0GvHNN9+Ili1bCmtra2FnZyc6deok1qxZI4Qo/41dlSQrISFBvP3226Jfv37Cz89PqNVqYWtrK5o0aSKmTZtW7v0sNBqNWL16tejXr59wc3MTFhYWwsnJSYSGhooJEyaIjRs36t2ksjL27dsnevfuLWxtbYVarRYtWrQQX3311X23VQgh4uPjxbRp00SjRo2EQqEQNjY2IiIiQnzxxReiuLi4SjEYO8kSQndvsXHjxgkvLy9hYWEh7O3tRffu3aX9eD+l92Cr6EPCFEmWEEKcOXNGPPXUUyIwMFCoVCqhVqtFo0aNRO/evcUnn3wibt68qVe/uh8qQuh+EOjYsaOwsbERMpnM4HvGmMdCTZIsIWq238uLpTKPEydOCCGE+PHHHwUA4ebmZvBG40II8cQTTwgAYsiQIQa3OycnR7z44ovCz89PKBQK4ebmJsaPH1/mfi93y8rKEu+++66IiIgQ9vb2wsLCQnh4eIg2bdqIF198URw8eFCvfl1Nskrnf/7550VoaKiwsrISKpVK+Pr6im7duom3335bXL58Wa9+dc/1Qgixd+9eERUVJRwcHIRcLjf4vktNTRXz5s0TISEh0vutRYsW4u233y5zw9LKqgvn3XvVpyRLiNrZL8nJyeKVV14RzZo1E1ZWVsLS0lI0atRIjBgxQmzZsqXGMZgyySrdvjfffFN07txZuLi4CHNzc2FtbS1CQ0PFU089VeYm96XzPPvss8Lf318olUrh6ekp/vOf/4hLly6VG+/DmGQJobvB++LFi0V4eLhQq9VCpVKJkJAQMX/+/Con9Q87mRDlDIdCRET0AO3evRvdu3eXbiNARERUX/GaLCIiIiIiIiNikkVERERERGRETLKIiIiIiIiMiNdkERERERERGRFbsoiIiIiIiIyISRYREREREZERMckiIiIiIiIyIiZZRERERERERsQki4iIiIiIyIiYZBERERERERkRkywiIiIiIiIjYpJFRERERERkREyyiIiIiIiIjIhJFhERERERkRExySIiIiIiIjIiJllERERERERGxCSLiIiIiIjIiJhkERERERERGRGTLCIiIiIiIiNikkVERERERGRETLKIiIiIiIiMiEkWERERERGRETHJIiIiIiIiMiImWUREREREREbEJIuIiIiIiMiImGQREREREREZEZMsIiIiIiIiI2KSRUREREREZERMsoiIiIiIiIyISRYREREREZERMckiIiIiIiIyIiZZRERERERERsQki4iIiIiIyIiYZBERERERERkRkywiIiIiIiIjYpJFRERERERkREyyiIiIiIiIjIhJFhERERERkRExySIiIiIiIjIiJllERERERERGxCSLiIgeOJlMhoULF1Z5vgMHDsDNzQ3NmjXDkSNH8NZbb2HWrFlGj4+IiKgmmGQRET3iVqxYAZlMJj1UKhUaN26M6dOnIzEx0dTh6fn444/Rv39/tG/fHp06dcJ///tfjB492tRhVdvu3bv1Xvv7PYiIqP4wN3UARERUN7z++uvw8/NDQUEB9u/fjy+++AKbN2/G2bNnoVarjbqu/Px8mJtX/SNoyZIlcHBwgKWlJd59912Ym5vDxsbGqLE9SCEhIfjhhx/0ps2bNw/W1tb4v//7PxNFRURENSUTQghTB0FERKazYsUKTJgwAUePHkXr1q2l6XPmzMGHH36I1atXY9SoUSaM8NESGhoKZ2dn7N6929ShEBFRNbG7IBERGdSjRw8AwLVr1wAAJSUleOONN+Dv7w+lUomGDRti/vz5KCws1Jvv77//Ru/eveHs7AxLS0v4+flh4sSJenUMXZN18+ZNTJo0CZ6enlAqlfDz88MzzzyDoqIiAEBKSgrmzJmD0NBQWFtbw9bWFn379sWpU6fKxJ6UlIRJkybBzc0NKpUKYWFhWLlyZYXbPGDAADRq1MhgWUREhF4Sun37dnTq1An29vawtrZGUFAQ5s+fX+E6qiMjIwOzZs2Ct7c3lEolAgIC8M4770Cr1Up1YmNjIZPJ8P777+Ozzz5Do0aNoFar0atXL1y/fh1CCLzxxhvw8vKCpaUlHnvsMaSlpemtp2HDhhgwYAC2bduG8PBwqFQqNGnSBL/88kuZmK5evYphw4bB0dERarUa7du3x6ZNm2pl+4mI6ht2FyQiIoOuXLkCAHBycgIATJ48GStXrsQTTzyBOXPm4K+//sLixYsRExODjRs3AtAlN7169YKLiwvmzp0Le3t7xMbGGvySfrdbt26hbdu2yMjIwFNPPYXg4GDcvHkTGzZsQF5eHhQKBS5fvozffvsNw4cPR8OGDZGYmIgvv/wSXbt2xblz5+Dp6QlA1xWxW7duuHz5MqZPnw4/Pz+sX78e48ePR0ZGBmbOnFluHCNGjMDYsWNx9OhRtGnTRpoeFxeHw4cP47333gMA/PPPPxgwYACaN2+O119/HUqlEpcvX8aBAweq/4KXIy8vD127dsXNmzfx9NNPw8fHBwcPHsS8efOQkJCAJUuW6NVftWoVioqK8NxzzyEtLQ3vvvsuhg8fjh49emD37t14+eWXcfnyZSxduhQvvPACli1bpjf/pUuXMGLECEydOhXjxo3D8uXLMWzYMGzZsgU9e/YEACQmJqJDhw7Iy8vDjBkz4OTkhJUrV2LQoEHYsGEDhgwZYvTXgYioXhFERPRIW758uQAgduzYIZKTk8X169fFmjVrhJOTk7C0tBQ3btwQJ0+eFADE5MmT9eZ94YUXBACxc+dOIYQQGzduFADE0aNH77tOAGLBggXS87Fjxwq5XG5wPq1WK4QQoqCgQGg0Gr2ya9euCaVSKV5//XVp2pIlSwQA8eOPP0rTioqKREREhLC2thZZWVnlxpWZmSmUSqWYM2eO3vR3331XyGQyERcXJ4QQ4qOPPhIARHJy8n23szqaNm0qunbtKj1/4403hJWVlbh48aJevblz5wozMzMRHx8vhNC9FgCEi4uLyMjIkOrNmzdPABBhYWGiuLhYmj5q1CihUChEQUGBNM3X11cAED///LM0LTMzU3h4eIgWLVpI02bNmiUAiH379knTsrOzhZ+fn2jYsGGZ/URE9Khhd0EiIgIAREVFwcXFBd7e3hg5ciSsra2xceNGNGjQAJs3bwYAzJ49W2+eOXPmAIDUTcze3h4A8Oeff6K4uLhS69Vqtfj1118xcOBAve54pUpH1lMqlZDLdR9bGo0GqampUje948ePS/U3b94Md3d3vevILCwsMGPGDOTk5GDPnj3lxlLaBXHdunUQd12yvHbtWrRv3x4+Pj562/nbb7/pddmrDevXr0fnzp3h4OCAlJQU6REVFQWNRoO9e/fq1R82bBjs7Oyk5+3atQMA/Oc//9EbbKRdu3YoKirCzZs39eb39PTUa4mytbXF2LFjceLECdy+fRuA7jVu27YtOnXqJNWztrbGU089hdjYWJw7d854LwARUT3EJIuIiAAAn332GbZv345du3bh3LlzuHr1Knr37g1A111OLpcjICBAbx53d3fY29sjLi4OANC1a1cMHToUixYtgrOzMx577DEsX768zHVbd0tOTkZWVhZCQ0PvG59Wq8VHH32EwMBAKJVKODs7w8XFBadPn0ZmZqZULy4uDoGBgVJCViokJEQqv58RI0bg+vXrOHToEABdt8ljx45hxIgRenU6duyIyZMnw83NDSNHjsS6detqJeG6dOkStmzZAhcXF71HVFQUAF0XzbuVJoKlShMub29vg9PT09P1pgcEBJQZMr5x48YAdNd9AbrXMCgoqEyslX2NiYgedrwmi4iIAABt27Y12JJ0t4ru1ySTybBhwwYcPnwYf/zxB7Zu3YqJEyfigw8+wOHDh2FtbV3t+N566y28+uqrmDhxIt544w04OjpCLpdj1qxZRk1uBg4cCLVajXXr1qFDhw5Yt24d5HI5hg0bJtWxtLTE3r17sWvXLmzatAlbtmzB2rVr0aNHD2zbtg1mZmZGi0er1aJnz5546aWXDJaXJkClylt3edMFBxkmIjI6JllERFQhX19faLVaXLp0SWqtAHQDIGRkZMDX11evfvv27dG+fXv897//xerVqzFmzBisWbMGkydPLrNsFxcX2Nra4uzZs/eNYcOGDejevTu+++47vekZGRlwdnbWi/X06dPQarV6rVnnz5+Xyu/HysoKAwYMwPr16/Hhhx9i7dq16Ny5szSwRim5XI7IyEhERkbiww8/xFtvvYX/+7//w65du6RWJmPw9/dHTk6OUZd5P5cvX4YQQi+hvnjxIgDd6IOA7jW8cOFCmXkr+xoTET3s2F2QiIgq1K9fPwAoM5Ldhx9+CADo378/AF3Xs3tbRsLDwwGg3C6DcrkcgwcPxh9//IG///67THnp8szMzMose/369WWuKerXrx9u376NtWvXStNKSkqwdOlSWFtbo2vXrvfbVAC67oC3bt3Ct99+i1OnTul1FQRQZujz8rbz/PnziI+Pr3B99zN8+HAcOnQIW7duLVOWkZGBkpKSGi3/Xrdu3ZJGiwSArKwsfP/99wgPD4e7uzsA3Wt85MgRqUslAOTm5uLrr79Gw4YN0aRJE6PGRERU37Ali4iIKhQWFoZx48bh66+/RkZGBrp27YojR45g5cqVGDx4MLp37w4AWLlyJT7//HMMGTIE/v7+yM7OxjfffANbW1spUTPkrbfewrZt29C1a1c89dRTCAkJQUJCAtavX4/9+/fD3t4eAwYMwOuvv44JEyagQ4cOOHPmDFatWlXmvlZPPfUUvvrqK4wfPx7Hjh1Dw4YNsWHDBhw4cABLliyBjY1Nhdvbr18/2NjY4IUXXoCZmRmGDh2qV/76669j79696N+/P3x9fZGUlITPP/8cXl5eeoNBhISEoGvXrjW6sfCLL76I33//HQMGDMD48ePRqlUr5Obm4syZM9iwYQNiY2P1WvJqqnHjxpg0aRKOHj0KNzc3LFu2DImJiVi+fLlUZ+7cufjpp5/Qt29fzJgxA46Ojli5ciWuXbuGn3/+ucz1cEREjxomWUREVCnffvstGjVqhBUrVmDjxo1wd3fHvHnzsGDBAqlOafK1Zs0aJCYmws7ODm3btsWqVavg5+dX7rIbNGiAv/76C6+++ipWrVqF5ORkeHt7Y9CgQVCr1QCA+fPnIzc3F6tXr8batWvRsmVLbNq0CXPnztVblqWlJXbv3o25c+di5cqVyMrKQlBQEJYvX47x48dXaltVKhUGDRqEVatWISoqCq6urnrlgwYNQmxsLJYtW4aUlBQ4Ozuja9euWLRokd7IfsagVquxZ88evPXWW1i/fj2+//572NraonHjxrWyvsDAQCxduhQvvvgiLly4AD8/P6xdu1YaBAUA3NzccPDgQbz88stYunQpCgoK0Lx5c/zxxx9SqyYR0aNMJnjFKxER1TGTJ09G27Zt8dRTT5k6lEdKw4YNERoaij///NPUoRAR1Wtszyciojpn4MCB+PHHH00dBhERUbWwuyAREdUZmzZtwq1bt/Dnn38iJyfH1OEQERFVC5MsIiKqM27cuIHZs2fDxsYGX3zxhanDISIiqhZek0VERERERGREvCaLiIiIiIjIiJhkERERERERGRGvyaqAVqvFrVu3YGNjA5lMZupwiIiIiIjIRIQQyM7Ohqen531vvM4kqwK3bt2Ct7e3qcMgIiIiIqI64vr16/Dy8iq3nElWBWxsbADoXkhbW1sTR0NERERERKaSlZUFb29vKUcoD5OsCpR2EbS1tWWSRUREREREFV5GxIEviIiIiIiIjIhJFhERERERkRGxu2A9Eh2TiGKNFjKZDDIAcpkMcrmuuVJ+9zSZbppMVv5z+Z3nZnIZzOVyWJjJYG4mh4Vc99fcTAYLue6vuVzGkRWJiIiIiCqJSVY98tKG00jNLTLJus3lMv3Eq5yETGEuh9JcDqW5GVQWur9KczmUd/9vbgalhRwqczmUFndNu7eehRxqC3OolWZQK8ygMjeDXM5kj4iIiGqPEAIlJSXQaDSmDoVMwMzMDObm5jVuYGCSVY+Ee9sjM78YWiGgFYCA7kSgFQJaLaAVAgCkcq3QVbr7uRCl8wAaIaDVChRrtCjRCpRoBIq1WtxZjJ4SrUCJVqAA2ge70fdQK3QJl6XCDFYKc1jeea5WmEtlpf/fW8dKYQ4blTmsVeawUVnAWmkOa6U5zJi4EREREYCioiIkJCQgLy/P1KGQCanVanh4eEChUFR7GTIhDH2lplJZWVmws7NDZmbmIzO6oEYrUKLVokTzb+JVork7GdOiWKOrU6zRPS+5k6wVlWhRKD00KCzW/V9QrPl3Won2znSNVFcqL9ZIyygo1iCvSIP84tr9JclKYaaXeNmo7jyUFnem65IxW5X+cxuVBezVFrCztICFGS9vJCIiqs+0Wi0uXboEMzMzuLi4QKFQ8HKJR4wQAkVFRUhOToZGo0FgYGCZGw5XNjdgSxaVYSaXwUxuBmUdOTq0WoGCEg1yCzXIL9Igr7jk3/+LSpBXpLnz+Pf/fAPTc4tKkFNQgpzCEmQVlKCoRNcql1ukQW6RBolZhdWO0VppDjtLXcJVmnjp/iqk/+0tLWAnlSlgb2kBtcKMJ3AiIqI6oKioCFqtFt7e3lCr1aYOh0zE0tISFhYWiIuLQ1FREVQqVbWWU0e+RhOVTy6X3ekCaNzDtbBEIyVd2QWlj2JkS9OKkX2nLOdO2d11s/J15QCQU6ib52ZGfpViMJfL7krKFHC0UsDJSvfX0UoBJ2sFHK2UcLJSwOFOmcrCzKivAxEREf3r3pYLevQY4xhgkkWPLKW5GZTWZnCyVlZ7GSUaLbILSpCRX4yMvCJk5hcjM78YGXn//s3IL0KW9H/p9KI7XS4FUnKKkJJTBCC3UutUK8zuScaUcLJWwEF91zRrBVyslXCxUTIpIyIiInrAmGQR1YC5mRwOd1qZAKtKzyeEQH6x5t9ELK8Y6XlFSMv995GaW4S03EKk5vw7rUQr7nSBzMeN9Mq1mtkozeFiq5SSLulxz3MnKyUHASEiIiI9u3fvRvfu3ZGeng57e/tKzTN8+HAcPnwYP/30E7744gvMnDkTbdq0qXEsr776KhITE/H1119Xexnnzp1Dr169cOHCBVhZVf67W1UxySIyAZns3y6QHnaWlZpHCIGsgpI7CVch0nKLdUlYbhHScu5OzHSP5JxCFJVodV0ek0twNfn+LWVyGeBkXX4y5margoedCq62SijN2TpGRERUV4wfPx4rV64EAFhYWMDHxwdjx47F/PnzYW5es6/7HTp0QEJCAuzs7CpVPysrC7Gxsfjhhx8wa9Ys2Nvbo2XLljWKAQBu376Njz/+GGfOnKnRcpo0aYL27dvjww8/xKuvvlrjuMrDJIuonpDJZNLgGn7OFf/yUpqUJWcX6h45hf/+f8/z1NxCaAWk50i4/7IdrRRS0uVmq4K7rQrudqWJmCXcbVWwtaz5PSaIiIiocvr06YPly5ejsLAQmzdvxrRp02BhYYF58+bVaLkKhQLu7u6Vrm9ra4sjR44AAI4ePVqjdd/t22+/RYcOHeDr61vjZU2YMAFTpkzBvHnzapyElodJFtFD6u6kLMDV+r51SzRapOUVlZuEJWUXIjGrALczC1BYopVay2ISsspdpspCfif50iVhbnf+liZmDewt4Wyt5A2miYiIjECpVErJ0DPPPIONGzfi999/x7x585Ceno6ZM2fijz/+QGFhIbp27YpPPvkEgYGBAIC4uDhMnz4d+/fvR1FRERo2bIj33nsP/fr1M9hd8MCBA/i///s/HDlyBEqlEm3btsWaNWvg4OCALVu24M0338TZs2dhZmaGiIgIfPzxx/D395diPXPmDGbOnIlDhw5BrVZj6NCh+PDDD2FtXf73lTVr1uCZZ57Rm9atWzc0a9YMZmZmWLlyJRQKBd58802MHj0a06dPx4YNG+Dm5oalS5eib9++0nw9e/ZEWloa9uzZg8jISGPtAj1MsogI5mZyuNqo4Gpz/2FKhRDIzC9GQmYBbmcVIPHO39t3/U3MKkB6XjEKirWITc1DbGr5N3RUmMnhYa9LuDzvPLzu/G3gYAkPOxUH7iAiIpMpvYb6QbO0qPktXiwtLZGamgpA153w0qVL+P3332Fra4uXX34Z/fr1w7lz52BhYYFp06ahqKgIe/fuhZWVFc6dO1duwnPy5ElERkZi4sSJ+Pjjj2Fubo5du3ZBo9G9Trm5uZg9ezaaN2+OnJwcvPbaaxgyZAhOnjwJuVyO3Nxc9O7dGxERETh69CiSkpIwefJkTJ8+HStWrDC4zrS0NJw7dw6tW7cuU7Zy5Uq89NJLOHLkCNauXSslmEOGDMH8+fPx0Ucf4cknn0R8fLw0NL9CoUB4eDj27dvHJIuITE8mk+nu8aVWIMSj/BvwFRRrpJavu5OwxKwCXYJ2Jxkr0mgRl5qHuPskYs7WSjSwV6GBgyU87XTJl6e9JRrcedirLdgtkYiIakV+sQZNXtv6wNd77vXe1b51jRAC0dHR2Lp1K5577jkpuTpw4AA6dOgAAFi1ahW8vb3x66+/YtiwYYiPj8fQoUPRrFkzAECjRo3KXf67776L1q1b4/PPP5emNW3aVPp/6NChevWXLVsGFxcXnDt3DqGhoVi9ejUKCgrw/fffSwNPfPrppxg4cCDeeecduLm5lVlnfHw8hBDw9PQsUxYWFoZXXnkFADBv3jy8/fbbcHZ2xpQpUwAAr732Gr744gucPn0a7du3l+bz9PREXFzc/V/MGmCSRURGp7Iwg6+TFXydyr92rFijRWJWAW6m5+NWZj5upufjZkYBbmbk41aG7nl+sQYpOYVIySnEqRuZBpejVpjB094SPo5q+Diq4eWg+9/7zsO6rtxVm4iIqBb9+eefsLa2RnFxMbRaLUaPHo2FCxciOjoa5ubmaNeunVTXyckJQUFBiImJAQDMmDEDzzzzDLZt24aoqCgMHToUzZs3N7iekydPYtiwYeXGcenSJbz22mv466+/kJKSAq1WC0CXKIWGhiImJgZhYWF6I/t17NgRWq0WFy5cMJhk5efrRlQ2dGPgu+M0MzODk5OTlCwCkJaXlJSkN5+lpSXy8sr/kbem+O2DiEzCwkwOLwc1vBzUBsuFEMjIK8bNjHy9xOvuhCwlpxB5RRpcTsrB5aQcg8txslLA604C5uNoCW8HtZSEedipYG7Gm04SEZFhlhZmOPd6b5Ost6q6d++OL774AgqFAp6enlUa0GHy5Mno3bs3Nm3ahG3btmHx4sX44IMP8Nxzz5WNzfL+oyIPHDgQvr6++Oabb+Dp6QmtVovQ0FAUFRVVeZtKOTs7AwDS09Ph4uKiV2ZhYaH3XCaT6U0r7e1SmuyVSktL07tOzNiYZBFRnSSTyaR7kIU2MDxsbEGxBgmZBbiRnofrafmIT8vD9fQ8XE/LQ3xaHjLyipF6Z2j7U9czysxvJpehgb0lvB3vav1yUMPXSQ1fJyvYWVqUXSkRET0ySm+5Uh9YWVkhICCgzPSQkBCUlJTgr7/+kroLpqam4sKFC2jSpIlUz9vbG1OnTsXUqVMxb948fPPNNwaTrObNmyM6OhqLFi0qU1a63G+++QadO3cGAOzfv79MPCtWrEBubq7UmnXgwAHI5XIEBQUZ3DZ/f3/Y2tri3LlzaNy4cSVfkfs7e/YsnnjiCaMsy5D6cdQQERmgsjCDn7NVuUPaZxUU43pa3p3Hv0lYfFoebqTlo0ijRfydhOwAUsvM72ilQEMnNRo6W8HPyQq+d/42dFbDRsUEjIiI6r7AwEA89thjmDJlCr766ivY2Nhg7ty5aNCgAR577DEAwKxZs9C3b180btwY6enp2LVrF0JCQgwub968eWjWrBmeffZZTJ06FQqFArt27cKwYcPg6OgIJycnfP311/Dw8EB8fDzmzp2rN/+YMWOwYMECjBs3DgsXLkRycjKee+45PPnkkwa7CgKAXC5HVFQU9u/fj8GDB9f4NYmNjcXNmzcRFRVV42WVh0kWET20bFUWaOpph6aeZVvCtFqBpOxCXeJ1J9Eq/RuXlofk7EJpqPrj8Rll5ne2VsDXyQoNnazg56xLxBo6WaGhsxWvAyMiojpl+fLlmDlzJgYMGICioiJ06dIFmzdvlrrVaTQaTJs2DTdu3ICtrS369OmDjz76yOCyGjdujG3btmH+/PkICwsDAPTu3RujRo2CXC7HmjVrMGPGDISGhiIoKAiffPIJunXrJs2vVquxdetWzJw5E23atNEbwv1+Jk+ejClTpuDdd9+FXF6zrv4//fQTevXqZZR7bpVHJoQQtbb0h0BWVhbs7OyQmZkJW9vyR1MjoodLTmEJYlNyEZeah9jUXFxLyUVsSi5iU3ORknP/fuXO1kr4Oeu6HPo5W6GRsxX8Xa3h66SG0pxD0hMR1UUFBQW4du0a/Pz8DA6wQGVdv34dTz75JHbv3l3r6xJCoF27dnj++ecxatSoai+nqKgIgYGBWL16NTp27Giwzv2OhcrmBvy5lYjIAGulOUIb2Bm8Hiy7oBhxqXlS4nUtNVdKyFJzi6QREY/GpuvNJ5cBPo5q+LtYw9/VGv4uVrr/XazhYKV4UJtGRERUY5cvX0ZhYSGOHj2K9PR0ODg41Or6ZDIZvv76a5w5c6ZGy4mPj8f8+fPLTbCMhUkWEVEV2agsyk3AMvOLESe1fOlawa6m5OJKUo6udezODZqjz+sPJetopdBLuvxddf97OahhJud9wIiIqG556623sGrVKvTq1Qv29vYPZJ3h4eEIDw+v0TICAgIMDhBibPWqu+DevXvx3nvv4dixY0hISMDGjRvve/Hb7t270b179zLTExIS4O7uXql1srsgERmDEALJ2YW4nJyDK8m6pOtKcg6uJufiZkZ+ufMpzOXwc7KCv6sVAqQWMGsEuFpDVY0hfomIyDB2F6RSj1x3wdzcXISFhWHixIl4/PHHKz3fhQsX9F4EV1fX2giPiKhcMpkMrrYquNqq0MHfWa8sr6gEV5NzcaU0AUvOwZWkHFxNyUVRiRYXErNxITFbbx65DPB1skKgqzUau9kg0E33t5GLFa/7IiIiMrF6lWT17dsXffv2rfJ8rq6uD6wZk4ioqtQKw9d/abQCtzLyda1fSf+2gF1MykZGXjGupei6JW47lyjNYyaXoaGT+k7iZYPGd5IvP2crWPDGy0RERA9EvUqyqis8PByFhYUIDQ3FwoUL73uhW2FhIQoLC6XnWVlZDyJEIqIyzOQy3Q2SHdXoHvRvC7wQAsk5hbiUmIOLidm4mJiDS3dau7ILSu60huXif2dvS/OYy2Vo5GKlS7xcdclXoJsNGjqpYc7ki4hIUo+upKFaYoxj4KFOsjw8PPDll1+idevWKCwsxLfffotu3brhr7/+QsuWLQ3Os3jxYoN3sCYiqitkMhlcbVRwtVGhY8C/XQ+FEEjMKryTeGXrkrAk3d+cwhJcTMzBxcQcbEKCNI/CTI4AV2uEeNgixMMGwe66v07WSlNsGhGRyZTeMyovLw+WlpYmjoZMKS8vD8C/x0R11KuBL+4mk8kqHPjCkK5du8LHxwc//PCDwXJDLVne3t4c+IKI6i0hBG5lFtxJvP5t+bqYmIP8Yo3BeVxslLrEy90GwR42CPGwRSNnayjM2epFRA+vhIQEZGRkwNXVFWq1GjIZR3d9lAghkJeXh6SkJNjb28PDw6NMnYdy4AtjaNu2Lfbv319uuVKphFLJX3CJ6OEhk8nQwN4SDewt9bodarUCN9Lzcf52FmISsu/8zUJcWh6SswuRnJ2MvReTpfoWZjL4u1ijiYctgqVWL1u42PCcSUQPh9LRp5OSkiqoSQ8ze3v7So9EXp5HLsk6efKkwayUiOhRI5fL4OOkho+TGr2a/vthkltYgouJ2XqJ1/mEbGQXluD87Wycv50NnPh3Oc7WCqmbYbC7LZo2sEWAizWv9SKiekcmk8HDwwOurq4oLi42dThkAhYWFjAzq/kovfUqycrJycHly5el59euXcPJkyfh6OgIHx8fzJs3Dzdv3sT3338PAFiyZAn8/PzQtGlTFBQU4Ntvv8XOnTuxbds2U20CEVGdZ6U0RwsfB7TwcZCmCSFwMyNfl3glZCHmti7xupaai5ScIuy/nIL9l1Ok+kpzOYI9bNHU0xahnnZo6mmLIHcb3tuLiOoFMzMzo3zRpkdXvUqy/v77b72bC8+ePRsAMG7cOKxYsQIJCQmIj4+XyouKijBnzhzcvHkTarUazZs3x44dOwzeoJiIiMonk8ng5aCGl4MaPZu4SdPzinQDapxP0LV4nUvIwrlbWcgt0uDU9Qycup4h1TWTyxDoao2mnnYIbWCLpp52aOJpC2tlvfooIiIiqlC9HfjiQansxW1ERKSj1QrEpeXh7M1M/HMrC//cysTZm5lIzyvb9UYmAxo6WelavBroWryaetrB0UphgsiJiIjur7K5AZOsCjDJIiKqOSEEEjIL8M+trDvJly4BS8gsMFjf006Fpg3sEOpph+ZeugeHlSciIlOrE0mWVqvFnj17sG/fPsTFxSEvLw8uLi5o0aIFoqKi4O3tXVurNhomWUREtSc1p1CXeN1Juv65mYnY1DyDdRvYWyLM2w7NGtgjzMsOoV52sFVV/x4mREREVWXSJCs/Px8ffPABvvjiC6SlpSE8PByenp6wtLREWloazp49i1u3bqFXr1547bXX0L59e2OHYDRMsoiIHqzsgmKcu5WFs3davU7fyMCV5FyDdRu5WKF5Azs097JHmLcdmnjYwVLBi9WJiKh2mDTJ8vb2RkREBMaPH4+ePXsavFtyXFwcVq9eja+++gr/93//hylTphg7DKNgkkVEZHrZBcU4czMTp29k4syNTJy6kYEb6fll6pUOrhHmZY/m3nYI87JHYzcb3kSZiIiMwqRJVkxMDEJCQipVt7i4GPHx8fD39zd2GEbBJIuIqG5KzSnE6Zu6pOv0jQycupGJ5OzCMvUU5nKEeNgizEuXdLXwsYefsxVkMpkJoiYiovqsTlyT9TBgkkVEVD8IIZCYVYhTNzJw+kYGTt/QtXxl5pcd1dBebYFwb3u08HZACx97hHnbw86S13cREdH91akkq6CgAKdPn0ZSUhK0Wq1e2aBBg2p79TXCJIuIqP4SQiA+LQ+nbmTi9PWMOwlYJgpLtGXq+rtY3bkJsy75auxmDXMzdjMkIqJ/1Zkka8uWLRg7dixSUlLKrlwmg0ajqc3V1xiTLCKih0uxRovzCdk4cT0dJ+IzcCI+3eCIhmqFGZp72ekSL297hPvYw9VGZYKIiYiorqgzSVZgYKA0iqCbm1ttrqpWMMkiInr4peUW4aSUdGXg5PUM5BSWlKnn5WApJV0tfOzRxNMWSnOOZkhE9KioM0mWra0tTpw4UWcHtqgIkywiokePRitwJTkHJ+L/TbwuJmXj3k9MhbkcYV52aOXriNa+Dmjl6wAHK4VpgiYiolpX2dzAvLYDeeKJJ7B79+56m2QREdGjx0wuQ2M3GzR2s8GINj4A7gwjfyMTJ67ruhgej89AWm4Rjsam42hsujSvv4sVWvs6olVDB7Rp6IiGTmqOZEhE9Iip9ZasvLw8DBs2DC4uLmjWrFmZe2bNmDGjNldfY2zJIiIiQ4QQuJaSi7/j0nEsNh1/x6UZvGmyk5UCrXwd0LqhA1r5OiK0AbsYEhHVV3Wmu+B3332HqVOnQqVSwcnJSe/XPJlMhqtXr9bm6muMSRYREVVWWm4Rjsel6xKvuDScupGJontGMmQXQyKi+qvOJFnu7u6YMWMG5s6dC7m8/g2FyySLiIiqq7BEg7M3M/F3bGnilY603KIy9QJcrdHaV9e9sK2fI7wd1SaIloiIKlJnkixHR0ccPXq03l6TxSSLiIiM5d4uhkfj0nDVQBfDBvaWaOunS7ja+TnCz9mK13UREdUBdSbJev755+Hi4oL58+fX5mpqDZMsIiKqTWm5RTgWl46/Y9NwJDYNZ25kokSr/9HsbK1EOz9HtGukS7wau9pALmfSRUT0oNWZJGvGjBn4/vvvERYWhubNm5cZ+OLDDz+szdXXGJMsIiJ6kPKKSnA8LgNHrqXir2tpOHE9o8x1XXaWFmjT0BHt7yRdTTxsYW5W/7rkExHVN3UmyerevXv5K5fJsHPnztpcfY0xySIiIlMqKNbg9I1MKek6FpeOvCKNXh1rpTla+TpI3QubedlxBEMiolpQZ5Ks+o5JFhER1SXFGi3+uZWlS7qu6roYZheU6NVRmsvR0scB7Rs5oUOAE8K87KEwZ0sXEVFNMckyEiZZRERUl2m0AhduZ0stXUeupSH1nhEMLS3M0LqhAyL8ndDB3xmhnuxeSERUHSZNsqZOnYpXXnkFXl5eFdZdu3YtSkpKMGbMGGOHYRRMsoiIqD4RQuBKci4OX03FoaupOHwltUzSZaM0R1s/R0T4OyHC3wkh7rYcSIOIqBIqmxuY18bKXVxc0LRpU3Ts2BEDBw5E69at4enpCZVKhfT0dJw7dw779+/HmjVr4Onpia+//ro2wiAiInrkyGQyBLhaI8DVGv9p7wshBC4m5uDglRQcupKKw1dTkVVQgujzSYg+nwQAsFdboL2f052WLicEuFpzyHgiohqote6CiYmJ+Pbbb7FmzRqcO3dOr8zGxgZRUVGYPHky+vTpUxurNxq2ZBER0cNEoxWISciSkq4j19KQe89AGs7WSrRv5IgO/s6I8HdCQyc1ky4iItSxa7LS09MRHx+P/Px8ODs7w9/fv96crJlkERHRw6xYo8WZm5k4dCUVh66k4u+4NBQU6w8Z72GnQoS/EzoFOKNjgDPcbFUmipaIyLTqVJJVnzHJIiKiR0lhiQYn4zNw6GoqDl5Jxcn4DBRp9JOuxm7W6BjgjE4BzmjXyAnWylq5+oCIqM5hkmUkTLKIiOhRll+kwbG4dBy4koIDl1Nw5mYm7v7mYC6XoYWPPToFuKBToBOae9nDgiMXEtFDikmWkTDJIiIi+ld6bhEOXU3Fvku6pCs+LU+v3FppjvaNnNApwAmdAp3h78JBNIjo4cEky0iYZBEREZUvPjUP+y/rEq4DV1KQkVesV+5uq0LHAGd0DnRGhwAnuNrwei4iqr+YZBkJkywiIqLK0WgFzt3Kwv7LKdh/ORlHY9NRVKJ/PVewu43ueq5AZ7T3c4KlwsxE0RIRVV2dS7KSk5Nx4cIFAEBQUBBcXFwexGprjEkWERFR9RQUa3A0Nk1q6Tp7M0uvXGEuR9uGjujS2BldGrsgyM2GXQuJqE6rM0lWbm4unnvuOfzwww/QaHT34TAzM8PYsWOxdOlSqNXq2lx9jTHJIiIiMo603CIcvJKC/ZdSsO9SCm5m5OuVu9kq0TnQBV0au6BzgDMcrBQmipSIyLA6k2Q9/fTT2LFjBz799FN07NgRALB//37MmDEDPXv2xBdffFGbq68xJllERETGJ4TAleRc7LmYjL0Xk/HXtVS9+3PJZEDzBnbo2liXdIV728OcoxYSkYnVmSTL2dkZGzZsQLdu3fSm79q1C8OHD0dycnJtrr7GmGQRERHVvtKuhXsvJmPvxRRcSMzWK7dRmaOjv65bYZfGzvByqNs9YYjo4VTZ3KDWfxLKy8uDm5tbmemurq7Iy8szMEf59u7di4EDB8LT0xMymQy//vprhfPs3r0bLVu2hFKpREBAAFasWFGldRIREVHtU1mYoXOgC/6vfxNsfb4LDs+LxLtPNMeA5h6wV1sgu6AEW/65jfkbz6DTO7vQ44PdWPj7P9h1Pgn5RRpTh09EpKfWb9EeERGBBQsW4Pvvv4dKpRu2NT8/H4sWLUJERESVlpWbm4uwsDBMnDgRjz/+eIX1r127hv79+2Pq1KlYtWoVoqOjMXnyZHh4eKB3797V2h4iIiKqfe52Kgxv7Y3hrb2h0QqcuZl5p5UrGSeuZ+Bqci6uJudixcFYKMzkaOPngC6BLugaxAE0iMj0ar274NmzZ9G7d28UFhYiLCwMAHDq1CmoVCps3boVTZs2rdZyZTIZNm7ciMGDB5db5+WXX8amTZtw9uxZadrIkSORkZGBLVu2VGo97C5IRERUt2TmF+PQlZQ713OVHUDDw06FbkEu6Bbkio4BzrBW1vpvykT0iKhsblDrZ53Q0FBcunQJq1atwvnz5wEAo0aNwpgxY2BpaVmr6z506BCioqL0pvXu3RuzZs0qd57CwkIUFhZKz7OyssqtS0RERA+enaUF+oR6oE+ohzSAxt6Lydh7KRmHr6YiIbMAPx25jp+OXIeFmQxtGjqiW5ALuge5IsDVmq1cRFTrHshPO2q1GlOmTHkQq9Jz+/btMteDubm5ISsrC/n5+QaTvMWLF2PRokUPKkQiIiKqAZlMhgBXawS4WmNiJz8UFGtw+Goqdl9Ixu4LSYhNzcPBK6k4eCUVb20+jwb2llIrVwd/J1ixlYuIasEDO7OcO3cO8fHxKCoq0ps+aNCgBxVCpcybNw+zZ8+WnmdlZcHb29uEEREREVFlqSzM0C3IFd2CXAE0xbWUXOy+kITdF5Jx6GoqbmbkY9Vf8Vj1VzwUZnK09XOUki5/Fyu2chGRUdRKknXs2DG0bNkSMpkMV69exZAhQ3DmzBnIZDKUXgJWehIrvUFxbXB3d0diYqLetMTERNja2pbbVVGpVEKpVNZaTERERPTg+Dlbwc/ZDxM6+iG/SNfKtetCEnZdSML1tHzsv5yC/ZdT8OamGHg7WqJbY1d0D3ZBRCNnWCrMTB0+EdVTtZJkLVmyBMnJydiyZQtmzpwJPz8/REdHw8/PD0eOHEFqairmzJmD999/vzZWL4mIiMDmzZv1pm3fvr3KoxoSERFR/WepMEP3YFd0D3aFEAJXU3Kx63wS9lxMxl9X03A9LR8/HI7DD4fjoDCXo30jJ3S/08rl52xl6vCJqB6pldEFDx48iFmzZuHIkSNwdnbGzp070bx5c9jZ2eHIkSMICgrCzp07MWfOHJw4caLSy83JycHly5cBAC1atMCHH36I7t27w9HRET4+Ppg3bx5u3ryJ77//HoBuCPfQ0FBMmzYNEydOxM6dOzFjxgxs2rSp0kO4c3RBIiKih19uYQkOXdG1cu2+kFxmxEJfJzW6B7miW5AL2jdygsqCrVxEjyKTji44evRo/PDDDwB03QFtbGwAAM7Ozrh16xaCgoLg6+uLCxcuVGm5f//9N7p37y49L712aty4cVixYgUSEhIQHx8vlfv5+WHTpk14/vnn8fHHH8PLywvffvst75FFREREeqyU5ohq4oaoJm4QQuByUg52X0jGrgtJOBqbhrjUPKw4GIsVB2NhaWGGjgFO6BHshh7BrnC3U5k6fCKqY2qlJWv48OGIj4/H4cOH0blzZ8yZMweDBw/G6NGjkZ6ejldeeQVff/01jh07pncPq7qILVlERESPtpzCEhy4nKJLus4n4XZWgV55Ew9bRIbouiGGednDTM7BM4geVpXNDWrtZsTZ2dmwsbHB1q1bkZubi8cffxyXL1/GgAEDcPHiRTg5OWHt2rXo0aNHbazeaJhkERERUSkhBGISsrHzfCJ2nk/CiesZuPublJOVAt2CXNEj2BWdGzvDVmVhumCJyOhMnmTdT1paGhwcHOrFMKlMsoiIiKg8qTmF2H0hGTsvJGHvhWRkF5ZIZeZy3Y2QI0N0SVcjF2sTRkpExlBnkqzMzExoNBo4OjrqTU9LS4O5uXmdT1yYZBEREVFlFGu0+Ds2HTvPJyL6fBKuJufqlTd0UkvXcbX1c4TCXG6iSImouupMktW3b18MHDgQzz77rN70L7/8Er///js2b96MzMxM2NnZ1WYY1cYki4iIiKojNiUXO8/r7sl1+GoqijX/fuWyVpqjU4AzeoS4onuQK1xseI9OovqgziRZjo6OOHDgAEJCQvSmX7hwASEhIejWrRuOHDmCqKgo/Prrr7UZSrUwySIiIqKayikswf5LKXeu5UpGSk6hXnmYl53UytXU0xZyDp5BVCeZdAj3uxUWFqKkpKTM9KKiIgDADz/8gIyMDLRu3bq2QyEiIiIyCWulOfqEuqNPqDu0WoGztzIRHaNr5Tp9IxOn7jw+2nERrjZK9Lhz0+ROAc6wUtb61zUiMrJab8nq3r07QkNDsXTpUr3p06ZNw+nTp7Fv3z5cuXIFb731Fr777rvaDKVa2JJFREREtSkpqwC7LiRh5/kk7LuUgrwijVSmMJOjvb8TokJcERnihgb2liaMlIjqTHfBAwcOICoqCm3atEFkZCQAIDo6GkePHsW2bdvQuXPn2lx9jTHJIiIiogelsESDI9fSEB2jS7ri0/L0yoPdbRAV4obIEN09uditkOjBqjNJFgCcPHkS7733Hk6ePAlLS0s0b94c8+bNQ2BgYG2vusaYZBEREZEpCCFwJTkH0TFJiI5Jwt9xadDe9a3N2VqJHsEuiAxxQ+dAZ6gV7FZIVNvqVJJVnzHJIiIiorogPbcIuy8mYce5JOy5mIycu+7JpTCXo4O/EyJD3BAV4goPO3YrJKoNJk2ysrKypJVmZWXdt25dT1yYZBEREVFdU1SixZFradgRk4jo84m4npavV97EwxZRIa6IauKGUE87diskMhKTJllmZmZISEiAq6sr5HI5ZLKyb2whBGQyGTQajYEl1B1MsoiIiKguE0LgUlKOLuGKScLx+HTc/e3O1UaJyBBXRAa7oWOAMywVZqYLlqieM2mStWfPHnTs2BHm5ubYs2fPfet27drV2Ks3KiZZREREVJ+k5hRi14VkRMckYu/FZOTeNVqh0lyOTgHOiLwzeIabrcqEkRLVP7wmy0iYZBEREVF9VViiwV9X06RWrpsZ+t0KmzWwQ2SIK6JC3NDU09Zg7yMi+ledSbK2bNkCa2trdOrUCQDw2Wef4ZtvvkGTJk3w2WefwcHBoTZXX2NMsoiIiOhhIITA+dvZiI5JxI6YJJy6kaHXrdDdVoUeIa7oGeKGCH8nqCzYrZDoXnUmyWrWrBneeecd9OvXD2fOnEHr1q0xZ84c7Nq1C8HBwVi+fHltrr7GmGQRERHRwyg5uxC7zidhR0wi9l1KQX7xv90KLS3M0CnQGVEhruge7ApXG3YrJALqUJJlbW2Ns2fPomHDhli4cCHOnj2LDRs24Pjx4+jXrx9u375dm6uvMSZZRERE9LArKNbg0NVU7DiXiJ3nk5CQWaBXHuZtj6hgV0SGuCHEw4bdCumRVdncoNbvWqdQKJCXp7tb+Y4dOzB27FgAgKOjY4XDuxMRERFR7VNZmKF7kCu6B7lCCIF/bmXpboJ8PhGnb2Ti1PUMnLqegQ+2X0QDe0v0CHZFZIgrIvydoDRnt0Kie9V6S9agQYNQVFSEjh074o033sC1a9fQoEEDbNu2DdOnT8fFixdrc/U1xpYsIiIiepQlZhVg5/kkRMckYv/lFBQUa6UytcIMnQN1oxX2CHaFs7XShJES1b46010wPj4ezz77LK5fv44ZM2Zg0qRJAIDnn38eGo0Gn3zySW2uvsaYZBERERHp5BdpcPBKCnbEJGHn+UQkZhVKZTIZEO5tj6gQN0SFuKGxmzW7FdJDp84kWfUdkywiIiKisrRaXbfC7TGJiI5JxD+39C8D8Xa0RGSwLuFq6+cIhbncRJESGU+dSrI0Gg1+/fVXxMTEAACaNm2KQYMGwcys7vfhZZJFREREVLGEzHzddVwxiThwJRVFJf92K7RRmqNLkAt6hrihW5AL7NUKE0ZKVH11Jsm6fPky+vXrh5s3byIoKAgAcOHCBXh7e2PTpk3w9/evzdXXGJMsIiIioqrJKyrBvkspiI7RjVaYklMklZnJZWjt64CoEDdEhriikYu1CSMlqpo6k2T169cPQgisWrUKjo6OAIDU1FT85z//gVwux6ZNm2pz9TXGJIuIiIio+rRagZM3MnQ3QT6XhAuJ2XrljVysdAlXsCta+TrA3IzdCqnuqjNJlpWVFQ4fPoxmzZrpTT916hQ6duyInJyc2lx9jTHJIiIiIjKe62l52BGTiOiYJPx1LRXFmn+/itqrLdA9yBVRIW7o0tgZNioLE0ZKVFaduU+WUqlEdnZ2mek5OTlQKNgfl4iIiOhR4u2oxoSOfpjQ0Q9ZBcXYezEZ0TFJ2Hk+CRl5xdh44iY2nrgJCzMZ2jdyQuSdmyB7O6pNHTpRpdV6S9bYsWNx/PhxfPfdd2jbti0A4K+//sKUKVPQqlUrrFixojZXX2NsySIiIiKqfSUaLY7FpSP6fBJ2nEvE1ZRcvfJgdxtEhugSrnAve8jlHB6eHrw6010wIyMD48aNwx9//AELC12Tb0lJCQYNGoQVK1bAzs6uNldfY0yyiIiIiB68K8k5uuu4YpLwd2watHd9Y3W2VqJHsAuiQtzQKdAZakWtd84iAlCHkqxSly9floZwDwkJQUBAwINYbY0xySIiIiIyrfTcIuy+mIQdMUnYeyEZ2YUlUpnSXI6OAc66Vq5gN7jbqUwYKT3sTJ5kabVavPfee/j9999RVFSEyMhILFiwAJaWlrWxulrDJIuIiIio7igq0eLItTTsiEnEjphE3EjP1ytv1sAOkSG6wTOaetpCJmO3QjIekydZb7zxBhYuXIioqChYWlpi69atGDVqFJYtW1Ybq6s1TLKIiIiI6iYhBC4m5kgJ18nrGbj7m62HnQo9gl0R1cQNEY2coLIwM12w9FAweZIVGBiIF154AU8//TQAYMeOHejfvz/y8/Mhl9ef+x8wySIiIiKqH5KzC7HrfBJ2xCRi36UU5BdrpDK1wgydA50RGeKGHsGucLZWmjBSqq9MnmQplUpcvnwZ3t7e0jSVSoXLly/Dy8urNlZZK5hkEREREdU/BcUaHLqSKrVyJWYVSmUyGdDC2x6RIW7o2cQNga7W7FZIlVLZ3KDWmpRKSkqgUulfeGhhYYHi4uIaLfezzz5Dw4YNoVKp0K5dOxw5cqTcuitWrIBMJtN73BsTERERET18VBZm6B7siv8OaYbD8yLx53OdMDMyEKENbCEEcDw+A+9tvYBeH+1Fl/d2YeHv/+DA5RQUa7SmDp0eArU23qUQAuPHj4dS+W9TbEFBAaZOnQorKytp2i+//FLpZa5duxazZ8/Gl19+iXbt2mHJkiXo3bs3Lly4AFdXV4Pz2Nra4sKFC9Jz/kpBRERE9GiRyWQIbWCH0AZ2eL5nYyRk5iM6JgnRMYk4cCUV19PyseJgLFYcjIWN0hxdg3TDw3cLcoG9WmHq8KkeqrXughMmTKhUveXLl1d6me3atUObNm3w6aefAtCNYOjt7Y3nnnsOc+fOLVN/xYoVmDVrFjIyMiq9jnuxuyARERHRwyuvqAT7LqUgOiYRO88nISWnSCozk8vQ2tcBUSFuiGriBj9nq/ssiR4Flc0Naq0lqyrJU2UUFRXh2LFjmDdvnjRNLpcjKioKhw4dKne+nJwc+Pr6QqvVomXLlnjrrbfQtGlTo8ZGRERERPWTWmGO3k3d0bupO7RagZM3MrDjXCKiY5JwITEbf11Lw1/X0vDfzTFo5GKFniFuiAxxQ0sfe5ib1Z/B3OjBqje3x05JSYFGo4Gbm5vedDc3N5w/f97gPEFBQVi2bBmaN2+OzMxMvP/+++jQoQP++eefcgffKCwsRGHhvxdGZmVlGW8jiIiIiKjOkstlaOnjgJY+DnipTzCup+VhR4wu4Tp8NRVXk3PxVfJVfLX3KuzVFugR5IrIEDd0aewMG5WFqcOnOqTeJFnVERERgYiICOl5hw4dEBISgq+++gpvvPGGwXkWL16MRYsWPagQiYiIiKiO8nZUY0JHP0zo6IesgmLsvZiM6Jgk7DyfhIy8Yvxy4iZ+OXETFmYytG/khMhgXdLl7ag2dehkYrV2TZaxFRUVQa1WY8OGDRg8eLA0fdy4ccjIyMBvv/1WqeUMGzYM5ubm+OmnnwyWG2rJ8vb25jVZRERERAQAKNFocSwuHdHnk7DjXCKupuTqlQe72yAqxA2RIa4I87KHXM6B1x4WJr8my9gUCgVatWqF6OhoKcnSarWIjo7G9OnTK7UMjUaDM2fOoF+/fuXWUSqVeiMiEhERERHdzdxMjnaNnNCukRPm9wvBleQcRMckYkdMEv6OTcP529k4fzsbn+66DGdr5Z0WLld0CnSGWlFvvn5TDdSblixAN4T7uHHj8NVXX6Ft27ZYsmQJ1q1bh/Pnz8PNzQ1jx45FgwYNsHjxYgDA66+/jvbt2yMgIAAZGRl477338Ouvv+LYsWNo0qRJpdbJ0QWJiIiIqLLSc4uw+2ISdsQkYc+FZOQUlkhlSnM5OgY4S61cbra8f2t989C1ZAHAiBEjkJycjNdeew23b99GeHg4tmzZIg2GER8fD7n831Fe0tPTMWXKFNy+fRsODg5o1aoVDh48WOkEi4iIiIioKhysFBjSwgtDWnihqESLI9fSsCMmETtiEnEjPR87z+uu6cJGoFkDOynhauppy/u5PkTqVUuWKbAli4iIiIhqSgiBi4k5UsJ18noG7v4W7mGnQmSIbuCMiEZOUFmYmS5YKldlcwMmWRVgkkVERERExpacXYhd55OwIyYR+y6lIL9YI5WpFWboHKjrVtgj2BVO1hwvoK5gkmUkTLKIiIiIqDYVFGtw6EoqtsckIjomEYlZ/450LZMBLbztEdXEDVEhbgh0tWa3QhNikmUkTLKIiIiI6EERQuCfW1nYfi4R0ecTcfZmll65j6MakSGuiApxQ1s/R1iYyctZEtUGJllGwiSLiIiIiEwlITMf0TFJiI5JxIErqSgq0UplNipzdG3sgp5N3NCtsSvs1BYmjPTRwCTLSJhkEREREVFdkFtYgv2XU7DjXCJ2XUhCSk6RVGYml6G1rwN6NnFDZIgb/JytTBjpw4tJlpEwySIiIiKiukarFTh5IwM7ziUiOiYJFxKz9cr9XazuDA/vhpY+9jBnt0KjYJJlJEyyiIiIiKiuu56Whx0xuoTr8NVUlGj//YrvoLZA9yBXRDVxQ+dAZ9io2K2wuphkGQmTLCIiIiKqT7IKirH3YvKdboXJyMwvlsoszGRo38hJugmyl4PahJHWP0yyjIRJFhERERHVVyUaLY7FpUutXFdTcvXKg91tpIQrzMsecjmHh78fJllGwiSLiIiIiB4WV5JzEB2TiB0xSfg7Ng139SqEs7USkcG6boWdApxhqTAzXaB1FJMsI2GSRUREREQPo/TcIuy+mIQd55Kw52IycgpLpDKluRydApwReaeVy81WZcJI6w4mWUbCJIuIiIiIHnZFJVocuZaGHTGJ2BGTiBvp+Xrlzb3sEBmsS7iaetpCJns0uxUyyTISJllERERE9CgRQuBCYjaiY5KwIyYRJ69n4O6MwdNOhR4hrogKcUOEvxOU5o9Ot0ImWUbCJIuIiIiIHmXJ2YXYdT4J22MSsf9SCvKLNVKZWmGGLoEuiAxxRY9gVzhZK00Yae1jkmUkTLKIiIiIiHQKijU4dCUV22MSER2TiMSsQqlMJgNa+jggMsQVPUPcEOBq/dB1K2SSZSRMsoiIiIiIyhJC4OzNLN3w8OcTcfZmll65j6MaUSFuiApxRRs/R1iYyU0UqfEwyTISJllERERERBVLyMxHdEwSomMSceBKKopKtFKZjcoc3YJcERXiim6NXWGntjBhpNXHJMtImGQREREREVVNbmEJ9l9OwY5zidh5PgmpuUVSmZlchjYNHe60crmhobOVCSOtGiZZRsIki4iIiIio+jRagZPXMxAdk4jomCRcSMzWK/d3sUJUE13C1dLHAWbyunsdF5MsI2GSRURERERkPNfT8qT7cf11NQ0l2n/TEQe1BboH64aH79LYBdZKcxNGWhaTLCNhkkVEREREVDuyCoqx92IydpxLxK4LycjML5bKLMxkaN/ICVEhupsgezmoTRipDpMsI2GSRURERERU+0o0WhyLS7/TypWEaym5UlljN2tse76rCaPTqWxuULfa34iIiIiI6JFkbiZHu0ZOaNfICf/XvwmuJOcgOiYRO84loV0jR1OHVyVMsoiIiIiIqM7xd7GGv4s1nurij/rW+a7+3xGMiIiIiIgeajJZ3R1x0BAmWUREREREREbEJIuIiIiIiMiImGQREREREREZEQe+qEDpRXZZWVkmjoSIiIiIiEypNCeoaCAOJlkVyM7OBgB4e3ubOBIiIiIiIqoLsrOzYWdnV245b0ZcAa1Wi1u3bsHGxsbko5pkZWXB29sb169f542R6xHut/qJ+61+4n6rn7jf6i/uu/qJ+636hBDIzs6Gp6cn5PLyr7xiS1YF5HI5vLy8TB2GHltbW74h6iHut/qJ+61+4n6rn7jf6i/uu/qJ+6167teCVYoDXxARERERERkRkywiIiIiIiIjYpJVjyiVSixYsABKpdLUoVAVcL/VT9xv9RP3W/3E/VZ/cd/VT9xvtY8DXxARERERERkRW7KIiIiIiIiMiEkWERERERGRETHJIiIiIiIiMiImWUREREREREbEJKuO+eyzz9CwYUOoVCq0a9cOR44cuW/99evXIzg4GCqVCs2aNcPmzZsfUKR0t6rstxUrVkAmk+k9VCrVA4yWAGDv3r0YOHAgPD09IZPJ8Ouvv1Y4z+7du9GyZUsolUoEBARgxYoVtR4n6avqftu9e3eZ95tMJsPt27cfTMAEAFi8eDHatGkDGxsbuLq6YvDgwbhw4UKF8/EzzrSqs9/4GWd6X3zxBZo3by7daDgiIgL/+9//7jsP32vGxySrDlm7di1mz56NBQsW4Pjx4wgLC0Pv3r2RlJRksP7BgwcxatQoTJo0CSdOnMDgwYMxePBgnD179gFH/mir6n4DdHdYT0hIkB5xcXEPMGICgNzcXISFheGzzz6rVP1r166hf//+6N69O06ePIlZs2Zh8uTJ2Lp1ay1HSner6n4rdeHCBb33nKuray1FSIbs2bMH06ZNw+HDh7F9+3YUFxejV69eyM3NLXcefsaZXnX2G8DPOFPz8vLC22+/jWPHjuHvv/9Gjx498Nhjj+Gff/4xWJ/vtVoiqM5o27atmDZtmvRco9EIT09PsXjxYoP1hw8fLvr37683rV27duLpp5+u1ThJX1X32/Lly4Wdnd0Dio4qA4DYuHHjfeu89NJLomnTpnrTRowYIXr37l2LkdH9VGa/7dq1SwAQ6enpDyQmqpykpCQBQOzZs6fcOvyMq3sqs9/4GVc3OTg4iG+//dZgGd9rtYMtWXVEUVERjh07hqioKGmaXC5HVFQUDh06ZHCeQ4cO6dUHgN69e5dbn4yvOvsNAHJycuDr6wtvb+/7/rpEdQffb/VbeHg4PDw80LNnTxw4cMDU4TzyMjMzAQCOjo7l1uF7ru6pzH4D+BlXl2g0GqxZswa5ubmIiIgwWIfvtdrBJKuOSElJgUajgZubm950Nze3cq8duH37dpXqk/FVZ78FBQVh2bJl+O233/Djjz9Cq9WiQ4cOuHHjxoMImaqpvPdbVlYW8vPzTRQVVcTDwwNffvklfv75Z/z888/w9vZGt27dcPz4cVOH9sjSarWYNWsWOnbsiNDQ0HLr8TOubqnsfuNnXN1w5swZWFtbQ6lUYurUqdi4cSOaNGlisC7fa7XD3NQBED1qIiIi9H5N6tChA0JCQvDVV1/hjTfeMGFkRA+foKAgBAUFSc87dOiAK1eu4KOPPsIPP/xgwsgeXdOmTcPZs2exf/9+U4dCVVDZ/cbPuLohKCgIJ0+eRGZmJjZs2IBx48Zhz5495SZaZHxsyaojnJ2dYWZmhsTERL3piYmJcHd3NziPu7t7leqT8VVnv93LwsICLVq0wOXLl2sjRDKS8t5vtra2sLS0NFFUVB1t27bl+81Epk+fjj///BO7du2Cl5fXfevyM67uqMp+uxc/40xDoVAgICAArVq1wuLFixEWFoaPP/7YYF2+12oHk6w6QqFQoFWrVoiOjpamabVaREdHl9uHNiIiQq8+AGzfvr3c+mR81dlv99JoNDhz5gw8PDxqK0wyAr7fHh4nT57k++0BE0Jg+vTp2LhxI3bu3Ak/P78K5+F7zvSqs9/uxc+4ukGr1aKwsNBgGd9rtcTUI2/Qv9asWSOUSqVYsWKFOHfunHjqqaeEvb29uH37thBCiCeffFLMnTtXqn/gwAFhbm4u3n//fRETEyMWLFggLCwsxJkzZ0y1CY+kqu63RYsWia1bt4orV66IY8eOiZEjRwqVSiX++ecfU23CIyk7O1ucOHFCnDhxQgAQH374oThx4oSIi4sTQggxd+5c8eSTT0r1r169KtRqtXjxxRdFTEyM+Oyzz4SZmZnYsmWLqTbhkVTV/fbRRx+JX3/9VVy6dEmcOXNGzJw5U8jlcrFjxw5TbcIj6ZlnnhF2dnZi9+7dIiEhQXrk5eVJdfgZV/dUZ7/xM8705s6dK/bs2SOuXbsmTp8+LebOnStkMpnYtm2bEILvtQeFSVYds3TpUuHj4yMUCoVo27atOHz4sFTWtWtXMW7cOL3669atE40bNxYKhUI0bdpUbNq06QFHTEJUbb/NmjVLquvm5ib69esnjh8/boKoH22lQ3vf+yjdV+PGjRNdu3YtM094eLhQKBSiUaNGYvny5Q887kddVffbO++8I/z9/YVKpRKOjo6iW7duYufOnaYJ/hFmaJ8B0HsP8TOu7qnOfuNnnOlNnDhR+Pr6CoVCIVxcXERkZKSUYAnB99qDIhNCiAfXbkZERERERPRw4zVZRERERERERsQki4iIiIiIyIiYZBERERERERkRkywiIiIiIiIjYpJFRERERERkREyyiIiIiIiIjIhJFhERERERkRExySIiInqALly4AHd3d2RnZ1dY99y5c/Dy8kJubu4DiIyIiIyFSRYREdVpMpnsvo+FCxeaOsQqmTdvHp577jnY2NhUWLdJkyZo3749PvzwwwcQGRERGYtMCCFMHQQREVF5bt++Lf2/du1avPbaa7hw4YI0zdraGtbW1qYIrcri4+MREBCAa9euoUGDBpWaZ9OmTZgyZQri4+Nhbm5eyxESEZExsCWLiIjqNHd3d+lhZ2cHmUymN23NmjUICQmBSqVCcHAwPv/8c2ne2NhYyGQyrFu3Dp07d4alpSXatGmDixcv4ujRo2jdujWsra3Rt29fJCcnS/ONHz8egwcPxqJFi+Di4gJbW1tMnToVRUVFUp3CwkLMmDEDrq6uUKlU6NSpE44ePXrfbVm3bh3CwsL0Eqy4uDgMHDgQDg4OsLKyQtOmTbF582apvGfPnkhLS8OePXuM8XISEdEDwJ/EiIio3lq1ahVee+01fPrpp2jRogVOnDiBKVOmwMrKCuPGjZPqLViwAEuWLIGPjw8mTpyI0aNHw8bGBh9//DHUajWGDx+O1157DV988YU0T3R0NFQqFXbv3o3Y2FhMmDABTk5O+O9//wsAeOmll/Dzzz9j5cqV8PX1xbvvvovevXvj8uXLcHR0NBjvvn370Lp1a71p06ZNQ1FREfbu3QsrKyucO3dOr2VOoVAgPDwc+/btQ2RkpDFfPiIiqiVMsoiIqN5asGABPvjgAzz++OMAAD8/P5w7dw5fffWVXpL1wgsvoHfv3gCAmTNnYtSoUYiOjkbHjh0BAJMmTcKKFSv0lq1QKLBs2TKo1Wo0bdoUr7/+Ol588UW88cYbyM/PxxdffIEVK1agb9++AIBvvvkG27dvx3fffYcXX3zRYLxxcXFlkqz4+HgMHToUzZo1AwA0atSozHyenp6Ii4urxitERESmwCSLiIjqpdzcXFy5cgWTJk3ClClTpOklJSWws7PTq9u8eXPpfzc3NwCQkprSaUlJSXrzhIWFQa1WS88jIiKQk5OD69evIzMzE8XFxVKSBgAWFhZo27YtYmJiyo05Pz8fKpVKb9qMGTPwzDPPYNu2bYiKisLQoUP14gUAS0tL5OXllbtcIiKqW3hNFhER1Us5OTkAdC1IJ0+elB5nz57F4cOH9epaWFhI/8tkMoPTtFptrcfs7OyM9PR0vWmTJ0/G1atX8eSTT+LMmTNo3bo1li5dqlcnLS0NLi4utR4fEREZB5MsIiKql9zc3ODp6YmrV68iICBA7+Hn51fj5Z86dQr5+fnS88OHD8Pa2hre3t7w9/eHQqHAgQMHpPLi4mIcPXoUTZo0KXeZLVq0wLlz58pM9/b2xtSpU/HLL79gzpw5+Oabb/TKz549ixYtWtR4m4iI6MFgd0EiIqq3Fi1ahBkzZsDOzg59+vRBYWEh/v77b6Snp2P27Nk1WnZRUREmTZqEV155BbGxsViwYAGmT58OuVwOKysrPPPMM3jxxRfh6OgIHx8fvPvuu8jLy8OkSZPKXWbv3r0xefJkaDQamJmZAQBmzZqFvn37onHjxkhPT8euXbsQEhIizRMbG4ubN28iKiqqRttDREQPDpMsIiKqtyZPngy1Wo333nsPL774IqysrNCsWTPMmjWrxsuOjIxEYGAgunTpgsLCQowaNUrvxsdvv/02tFotnnzySWRnZ6N169bYunUrHBwcyl1m3759YW5ujh07dkgDcWg0GkybNg03btyAra0t+vTpg48++kia56effkKvXr3g6+tb420iIqIHgzcjJiIiusf48eORkZGBX3/91ejL/uyzz/D7779j69atFdYtKipCYGAgVq9erTfIBhER1W1sySIiInqAnn76aWRkZCA7Oxs2Njb3rRsfH4/58+czwSIiqmfYkkVERHSP2mzJIiKihx+TLCIiIiIiIiPiEO5ERERERERGxCSLiIiIiIjIiJhkERERERERGRGTLCIiIiIiIiNikkVERERERGRETLKIiIiIiIiMiEkWERERERGRETHJIiIiIiIiMiImWUREREREREbEJIuIiIiIiMiImGQREREREREZEZMsIiIql0wmw8KFC2tl2bGxsZDJZFixYkWFdcePH4+GDRsadf21uW1ERPRoY5JFRPQQGDRoENRqNbKzs8utM2bMGCgUCqSmpj7AyKg2rFixAjKZrMKHsRNTIiKqHHNTB0BERDU3ZswY/PHHH9i4cSPGjh1bpjwvLw+//fYb+vTpAycnJxNEWJavry/y8/NhYWFh6lDqnS5duuCHH37QmzZ58mS0bdsWTz31lDTN2tr6QYdGRERgkkVE9FAYNGgQbGxssHr1aoNJ1m+//Ybc3FyMGTPGBNEZJpPJoFKpTB1GvdSoUSM0atRIb9rUqVPRqFEj/Oc//zFRVEREVIrdBYmIHgKWlpZ4/PHHER0djaSkpDLlq1evho2NDQYNGgQAyMjIwKxZs+Dt7Q2lUomAgAC888470Gq1Fa7rxIkT6Nu3L2xtbWFtbY3IyEgcPny4TL2MjAw8//zzaNiwIZRKJby8vDB27FikpKQAKP+arF9//RWhoaFQqVQIDQ3Fxo0bDcbx/vvvo0OHDnBycoKlpSVatWqFDRs2lKlXWFiI559/Hi4uLtJrcOPGDYPLvHnzJiZOnAg3NzcolUo0bdoUy5Ytq/A1CQ0NRffu3ctM12q1aNCgAZ544glp2po1a9CqVSvY2NjA1tYWzZo1w8cff1zhOqqjMtuze/duyGQyrFu3DosWLUKDBg1gY2ODJ554ApmZmSgsLMSsWbPg6uoKa2trTJgwAYWFhXrLkMlkmD59OlatWoWgoCCoVCq0atUKe/fuLRNTZY8fIqL6jC1ZREQPiTFjxmDlypVYt24dpk+fLk1PS0vD1q1bMWrUKFhaWiIvLw9du3bFzZs38fTTT8PHxwcHDx7EvHnzkJCQgCVLlpS7jn/++QedO3eGra0tXnrpJVhYWOCrr75Ct27dsGfPHrRr1w4AkJOTg86dOyMmJgYTJ05Ey5YtkZKSgt9//x03btyAs7OzweVv27YNQ4cORZMmTbB48WKkpqZiwoQJ8PLyKlP3448/xqBBgzBmzBgUFRVhzZo1GDZsGP7880/0799fqjd58mT8+OOPGD16NDp06ICdO3fqlZdKTExE+/btpYTBxcUF//vf/zBp0iRkZWVh1qxZ5b4uI0aMwMKFC3H79m24u7tL0/fv349bt25h5MiRAIDt27dj1KhRiIyMxDvvvAMAiImJwYEDBzBz5sxyl18dVd2exYsXw9LSEnPnzsXly5exdOlSWFhYQC6XIz09HQsXLsThw4exYsUK+Pn54bXXXtObf8+ePVi7di1mzJgBpVKJzz//HH369MGRI0cQGhoKoPLHDxFRvSeIiOihUFJSIjw8PERERITe9C+//FIAEFu3bhVCCPHGG28IKysrcfHiRb16c+fOFWZmZiI+Pl6aBkAsWLBAej548GChUCjElStXpGm3bt0SNjY2okuXLtK01157TQAQv/zyS5k4tVqtEEKIa9euCQBi+fLlUll4eLjw8PAQGRkZ0rRt27YJAMLX11dvOXl5eXrPi4qKRGhoqOjRo4c07eTJkwKAePbZZ/Xqjh49usy2TZo0SXh4eIiUlBS9uiNHjhR2dnZl1ne3CxcuCABi6dKletOfffZZYW1tLc07c+ZMYWtrK0pKSspdVnVZWVmJcePGSc8ruz27du0SAERoaKgoKiqS6o0aNUrIZDLRt29fvfkjIiLK7AsAAoD4+++/pWlxcXFCpVKJIUOGSNMqe/wQEdV37C5IRPSQMDMzw8iRI3Ho0CHExsZK01evXg03NzdERkYCANavX4/OnTvDwcEBKSkp0iMqKgoajcZgFy8A0Gg02LZtGwYPHqx3PZCHhwdGjx6N/fv3IysrCwDw888/IywsDEOGDCmzHJlMZnD5CQkJOHnyJMaNGwc7Oztpes+ePdGkSZMy9S0tLaX/09PTkZmZic6dO+P48ePS9M2bNwMAZsyYoTfvva04Qgj8/PPPGDhwIIQQeq9L7969kZmZqbfcezVu3Bjh4eFYu3atNE2j0WDDhg0YOHCgFKu9vT1yc3Oxffv2cpdlDNXZnrFjx+oNQtKuXTsIITBx4kS9eu3atcP169dRUlKiNz0iIgKtWrWSnvv4+OCxxx7D1q1bodFoqnT8EBHVd0yyiIgeIqUDW6xevRoAcOPGDezbtw8jR46EmZkZAODSpUvYsmULXFxc9B5RUVEAYPCaLgBITk5GXl4egoKCypSFhIRAq9Xi+vXrAIArV65IXcQqKy4uDgAQGBhYpszQOv/880+0b98eKpUKjo6OcHFxwRdffIHMzEy9Zcrlcvj7+993ecnJycjIyMDXX39d5nWZMGECgPJfl1IjRozAgQMHcPPmTQC6a52SkpIwYsQIqc6zzz6Lxo0bo2/fvvDy8sLEiROxZcuW+y63OqqzPT4+PnrPSxNdb2/vMtO1Wq3e6wwY3m+NGzdGXl4ekpOTq3T8EBHVd7wmi4joIdKqVSsEBwfjp59+wvz58/HTTz9BCKE3qqBWq0XPnj3x0ksvGVxG48aNH1S41bZv3z4MGjQIXbp0weeffw4PDw9YWFhg+fLlUoJZFaUDfvznP//BuHHjDNZp3rz5fZcxYsQIzJs3D+vXr8esWbOwbt062NnZoU+fPlIdV1dXnDx5Elu3bsX//vc//O9//8Py5csxduxYrFy5sspxG3N7SpPwe5U3XQhRgwiJiB5uTLKIiB4yY8aMwauvvorTp09j9erVCAwMRJs2baRyf39/5OTkSC1XleXi4gK1Wo0LFy6UKTt//jzkcrnU6uHv74+zZ89Wafm+vr4AdC1t97p3nT///DNUKhW2bt0KpVIpTV++fHmZZWq1Wly5ckWvBeXe5ZWOPKjRaKr8upTy8/ND27ZtsXbtWkyfPh2//PILBg8erBcfACgUCgwcOBADBw6EVqvFs88+i6+++gqvvvoqAgICqrXuexlje6rK0H67ePEi1Go1XFxcAKDSxw8RUX3H7oJERA+Z0lar1157DSdPnixzb6zhw4fj0KFD2Lp1a5l5MzIyylxrU8rMzAy9evXCb7/9pnfNV2JiIlavXo1OnTrB1tYWADB06FCcOnXK4PDr5bWAeHh4IDw8HCtXrtTrirZ9+3acO3euTCwymQwajUaaFhsbi19//VWvXt++fQEAn3zyid70e0dQNDMzw9ChQ/Hzzz8bTA6Tk5MNxnyvESNG4PDhw1i2bBlSUlL0ugoCQGpqqt5zuVwutSiVDoteXFyM8+fPIyEhoVLrNMRY21MVhw4d0rvO6/r16/jtt9/Qq1cvmJmZVen4ISKq79iSRUT0kPHz80OHDh3w22+/AUCZJOvFF1/E77//jgEDBmD8+PFo1aoVcnNzcebMGWzYsAGxsbHlDrH+5ptvYvv27ejUqROeffZZmJub46uvvkJhYSHeffddvXVs2LABw4YNw8SJE9GqVSukpaXh999/x5dffomwsDCDy1+8eDH69++PTp06YeLEiUhLS8PSpUvRtGlT5OTkSPX69++PDz/8EH369MHo0aORlJSEzz77DAEBATh9+rRULzw8HKNGjcLnn3+OzMxMdOjQAdHR0bh8+XKZdb/99tvYtWsX2rVrhylTpqBJkyZIS0vD8ePHsWPHDqSlpVX42g8fPhwvvPACXnjhBTg6OpZpRZo8eTLS0tLQo0cPeHl5IS4uDkuXLkV4eDhCQkIA6O5tFRISgnHjxpW5h1hVGGN7qiI0NBS9e/fWG8IdABYtWiTVqezxQ0RU75luYEMiIqotn332mQAg2rZta7A8OztbzJs3TwQEBAiFQiGcnZ1Fhw4dxPvvv683jDfuGeZcCCGOHz8uevfuLaytrYVarRbdu3cXBw8eLLOO1NRUMX36dNGgQQOhUCiEl5eXGDdunDSkuKEh3IUQ4ueffxYhISFCqVSKJk2aiF9++UWMGzeuzLDh3333nQgMDBRKpVIEBweL5cuXiwULFoh7P9ry8/PFjBkzhJOTk7CyshIDBw4U169fN7htiYmJYtq0acLb21tYWFgId3d3ERkZKb7++uv7vNr6OnbsKACIyZMnlynbsGGD6NWrl3B1dRUKhUL4+PiIp59+WiQkJEh1Sl+Xu4djr4x7h3Cv7PaUDuG+fv16vXmXL18uAIijR4/qTS99jZOTk6VpAMS0adPEjz/+KO2TFi1aiF27dpWJs7LHDxFRfSYTgleuEhERUfXJZDJMmzYNn376qalDISKqE3hNFhERERERkRExySIiIiIiIjIiJllERERERERGxNEFiYiIqEZ4eTcRkT62ZBERERERERkRkywiIiIiIiIjYnfBCmi1Wty6dQs2NjaQyWSmDoeIiIiIiExECIHs7Gx4enpCLi+/vYpJVgVu3boFb29vU4dBRERERER1xPXr1+Hl5VVuOZOsCtjY2ADQvZC2trYmjoaIiIiIiEwlKysL3t7eUo5QnnqXZH322Wd47733cPv2bYSFhWHp0qVo27ZtufXXr1+PV199FbGxsQgMDMQ777yDfv36VXp9pV0EbW1tmWQREREREVGFlxHVq4Ev1q5di9mzZ2PBggU4fvw4wsLC0Lt3byQlJRmsf/DgQYwaNQqTJk3CiRMnMHjwYAwePBhnz559wJETEREREdGjQibq0c0t2rVrhzZt2uDTTz8FoBuUwtvbG8899xzmzp1bpv6IESOQm5uLP//8U5rWvn17hIeH48svv6zUOrOysmBnZ4fMzEy2ZBERERERPcIqmxvUm5asoqIiHDt2DFFRUdI0uVyOqKgoHDp0yOA8hw4d0qsPAL179y63fp0Xvx64vRPQFJk6EiIiIiIiKke9uSYrJSUFGo0Gbm5uetPd3Nxw/vx5g/Pcvn3bYP3bt2+Xu57CwkIUFhZKz7OysmoQtREJARx7Hsi/CZhbA+49gQb9AY++gNrT1NERERERVZsQAiUlJdBoNKYOhR5xZmZmMDc3r/Gtm+pNkvWgLF68GIsWLTJ1GGWV5ALuUUDC/4CCJODGRt0DABxaAJ79dA+ndoDczLSxEhEREVVSUVEREhISkJeXZ+pQiAAAarUaHh4eUCgU1V5GvUmynJ2dYWZmhsTERL3piYmJcHd3NziPu7t7leoDwLx58zB79mzpeekwjSZnYQ1ErACEFkg7BtzarHukHgXST+ge//wXUDgCHn3utHL1BpROpo6ciIiIyCCtVotr167BzMwMnp6eUCgUNW5BIKouIQSKioqQnJyMa9euITAw8L43HL6fepNkKRQKtGrVCtHR0Rg8eDAA3RszOjoa06dPNzhPREQEoqOjMWvWLGna9u3bERERUe56lEollEqlMUM3LpkccGqjezRboGvVurUFuLUJSNgKFKUBcat1D5lc17Ll2V/XyuUQDvDERURERHVEUVGRNJCZWq02dThEsLS0hIWFBeLi4lBUVASVSlWt5dSbJAsAZs+ejXHjxqF169Zo27YtlixZgtzcXEyYMAEAMHbsWDRo0ACLFy8GAMycORNdu3bFBx98gP79+2PNmjX4+++/8fXXX5tyM4xL5Qo0Gqt7aEuAlEO6hOvWZiDjjO55yiHg9CuApce/3QrdowALjpZIREREplfd1gKi2mCM47FeJVkjRoxAcnIyXnvtNdy+fRvh4eHYsmWLNLhFfHy83ovSoUMHrF69Gq+88grmz5+PwMBA/PrrrwgNDTXVJtQuuTng2ln3CH8byL3+b7fC2zuA/ATgyne6h9wCcOn8b9JlG8xWLiIiIiIiI6hX98kyhYfmPlmaAiBpry7hurkJyLmsX27lp0u2GvQHXLsB5pYmCZOIiIgeHQUFBbh27Rr8/Pyq3S2LyNjud1w+dPfJohoyUwEevYBWS4BBl4ABF4GWH+mGgpcrgNxrwKXPgN39gJ8dgd39gYufAzmxpo6ciIiI6KHTsGFDLFmy5IEuTyaT4ddff63RehYuXIjw8PAaLQMAUlNT4erqitjY2Bovq7KKiorQsGFD/P3337W+LiZZjyrbQCB4FtBjGzA0FejyKxDwFKD20rV63doM/D0N+N0P2NQUOPEikLgL0BabOnIiIiIikxk4cCD69OljsGzfvn2QyWQ4ffr0A44KOHr0KJ566qkHvt7q+u9//4vHHnsMDRs2NMryJkyYgFdeeeW+dRQKBV544QW8/PLLRlnn/dSra7KollhYA16P6R5C6AbMKL2WK+UgkHlO94h5XzdYhnvPOyMW9tENpkFERET0iJg0aRKGDh2KGzduwMvLS69s+fLlaN26NZo3b/7A43JxcXng66yuvLw8fPfdd9i6datRlqfRaPDnn39i06ZNFdYdM2YM5syZg3/++QdNmzY1yvoNYUsW6ZPJAIfmQNO5QM+9wNBkoOMaoOGTgNIZKM4Crv8M/DUR2OgJ/K8VcPo1IOUwoOVd2omIiKgGhABKck3zqOQwBQMGDICLiwtWrFihNz0nJwfr16/HpEmTAAD79+9H586dYWlpCW9vb8yYMQO5ubnlLjc+Ph6PPfYYrK2tYWtri+HDh5e53+sff/yBNm3aQKVSwdnZGUOGDJHK7u0ueOnSJXTp0gUqlQpNmjTB9u3by6zz5ZdfRuPGjaFWq9GoUSO8+uqrKC7W77X09ttvw83NDTY2Npg0aRIKCgrKLOfbb79FSEgIVCoVgoOD8fnnn5e7nQCwefNmKJVKtG/fXpq2e/duyGQybN26FS1atIClpSV69OiBpP9n777Dori6MIC/S+9NuqKoWMCKvcUGCogFS1BjYq9RE6PRaIpojPolJrFEozGxxN4L9l4Re4lGJBYUFRCV3mH3fn+sLq4UF1xYyvt7nnlw79yZOcu44uHOPTc6GgcOHICrqyvMzMzw0Ucf5Vi4+ty5c9DV1UXTpk2RkZGBcePGwcHBAQYGBqhSpYqi8jgAWFpaonXr1ti0aVO+Mb4vjmRR/vQsgSp95ZuQAS8vZ5eIj7kMxF6Vb7dmyZMwB295AQ0HL0DfStPRExERUWkiTQG2mGjm2v5JgI7xO7vp6Ohg4MCBWL16Nb755hvF4slbt26FVCpF//79cf/+fXh7e+OHH37AypUr8fz5c4wbNw7jxo3DqlWrcpxTJpMpEqxTp04hKysLY8eORd++fXHy5EkAwL59+9CzZ0988803WLNmDTIyMrB///5cY5TJZOjVqxfs7Oxw4cIFxMfHK60b+5qpqSlWr14NR0dH3Lx5EyNGjICpqSmmTJkCANiyZQtmzJiBJUuWoE2bNli7di0WLVqEatWqKc6xfv16TJ8+HYsXL4a7uzuuXbuGESNGwNjYGIMGDco1vjNnzqBx48a57psxYwYWL14MIyMj+Pv7w9/fH/r6+tiwYQOSkpLQs2dP/Pbbb0qP/AUGBqJbt26QSCRYtGgRAgMDsWXLFlSuXBmPHz/G48ePla7RrFkznDlzJtfrqwuTLFKdRAuwbibf6s8EUp8BkQfkCVfkISD9BfBwnXyTaAHWLV+ViPcFLOqzRDwRERGVCUOHDsW8efNw6tQptG/fHoD8UcHevXvD3NwckyZNwoABAxSJTY0aNbBo0SK0a9cOS5cuzVGx7tixY7h58ybCwsLg5OQEAFizZg3q1KmDS5cuoWnTppg9ezb69euHmTNnKo5r0KBBrvEdPXoUd+7cwaFDh+Do6AgAmDNnDnx8fJT6vTmHydnZGV9++SU2bdqkSLIWLFiAYcOGKUbnfvjhBxw9elRpNCsgIAC//PILevXqBQCoWrUqbt++jT/++CPPJOvRo0eKuN72ww8/oHXr1gDkj2ZOmzYN9+/fVyR2ffr0wYkTJ5SSrN27d2P+/PkA5COCNWrUQJs2bSCRSFClSpUc13B0dMSjR49yvb66MMmiwjO0A6oNlm+yTOD5uVdzufYB8f8Cz4Pk241vAMOKbyyE7AHommo6eiIiIipptI3kI0qauraKateujVatWmHlypVo37497t27hzNnzuD7778HANy4cQP//PMP1q9frzhGCAGZTIawsDC4uroqnS8kJAROTk6KBAsA3NzcYGFhgZCQEDRt2hTXr1/HiBEjVIrv9fneTGRatmyZo9/mzZuxaNEi3L9/H0lJScjKylIqSx4SEoLRo0crHdOyZUucOHECAJCcnIz79+9j2LBhSrFlZWXB3Nw8z/hSU1PzLNn/5nw2Ozs7xaOMb7ZdvHhRKcaIiAh4eHgAAAYPHoxOnTqhVq1a8Pb2RteuXdG5c2elaxgaGuZ45FDdmGSRemjpAnbt5Jv7j0Dyo1drcu0Hnh0DUp8C9/+Ub1q6gG277KTLtCZHuYiIiEj+/wEVHtkrCYYNG4bx48djyZIlWLVqFapXr4527doBkM/PGjVqFD777LMcx1WuXLlQ1zM0VO8apsHBwRgwYABmzpwJLy8vmJubY9OmTfjll19UPkdSkjwh/vPPP9G8eXOlfdra2nkeZ21tjdjY2Fz36erqKv4skUiUXr9uk8lkiteBgYHo1KmTImlr1KgRwsLCcODAARw9ehT+/v7w9PTEtm3bFMfExMQUeaGQAidZISEh2LRpE86cOYNHjx4hJSUFNjY2cHd3h5eXF3r37g19ff2iiJVKE+MqQI0x8k2aBjw7mT3KlfQAiDoq365OBEyqZydcdu3la3oRERERlWD+/v74/PPPsWHDBqxZswZjxoxRzM9q1KgRbt++DRcXF5XO5erqqpg79Ho06/bt24iLi4ObmxsA+QjPsWPHMGTIEJXPFxkZCQcHeSXo8+fPK/U5d+4cqlSpgm+++UbR9vYjdK6urrhw4QIGDhyoaHvzPHZ2dnB0dMSDBw8wYMAAld4rALi7u2PdunUq98/P7t27c5SuNzMzQ9++fdG3b1/06dMH3t7eiImJgZWVvF7ArVu34O7urpbr50XlJOvq1auYMmUKzp49i9atW6N58+bo2bMnDA0NERMTg1u3buGbb77B+PHjMWXKFEyYMIHJFslpG8jLvTt6A2IhkPhfdon46FNA0n3gv9/km7YhYOcBVPSVJ13GhfttDxEREVFRMjExQd++fTFt2jQkJCRg8ODBin1fffUVWrRogXHjxmH48OEwNjbG7du3ceTIESxevDjHuTw9PVGvXj0MGDAACxYsQFZWFj799FO0a9cOTZo0ASCf++Th4YHq1aujX79+yMrKwv79+3Nd88nT0xM1a9bEoEGDMG/ePCQkJCglU4B8nlh4eDg2bdqEpk2bYt++fdi5c6dSn88//xyDBw9GkyZN0Lp1a6xfvx7//vuv0uN7M2fOxGeffQZzc3N4e3sjPT0dly9fRmxsLCZOnJjr987LywvTpk1DbGwsLC0tVf6evy06OhqXL19GYGCgou3XX3+Fg4MD3N3doaWlha1bt8Le3h4WFhaKPmfOnMGsWbMKfV2VCBU5OzuLJUuWiNjY2Hz7nTt3TvTt21fMnj1b1VOXaPHx8QKAiI+P13QoZVNGghDhO4U4P1yIHY5CrIfytreOEFenCBF1UghphqajJSIiIjVKTU0Vt2/fFqmpqZoOpVDOnTsnAIguXbrk2Hfx4kXRqVMnYWJiIoyNjUX9+vWV/n9cpUoVMX/+fMXrR48eie7duwtjY2NhamoqPvzwQxEVFaV0zu3bt4uGDRsKPT09YW1tLXr16pXn+UJDQ0WbNm2Enp6eqFmzpjh48KAAIHbu3KnoM3nyZFGhQgVhYmIi+vbtK+bPny/Mzc2Vrjl79mxhbW0tTExMxKBBg8SUKVNEgwYNlPqsX79eEZelpaVo27at2LFjR77fu2bNmolly5YpXp84cUIAUMo1Vq1alSOegIAAxfX/+usv0bp1a6X9y5cvFw0bNhTGxsbCzMxMeHh4iKtXryr2nzt3TlhYWIiUlJQ8Y8vv76WquYFECNUWBcjMzMzxTKQ6+5dUCQkJMDc3R3x8vNJEQCoCQgBx/2SXiH8RLC8b/5quOeDQ+VWJeB954Q0iIiIqtdLS0hAWFoaqVavmWQiByqZ9+/Zh8uTJuHXrFrS0Crd0b/fu3dGmTRtFNURV9O3bFw0aNMDXX3+dZ5/8/l6qmhuo/LjguxKmuLg4pWG4spBgUTGTSADLBvKtztdA+ksg8vCrEvEH5K/Dt8o3ALBqkl0ivkITedl4IiIiIirxfH19cffuXTx9+lSpqmJBtGnTBv3791e5f0ZGBurVq4cvvviiUNcrCJVHst70448/wtnZGX379gUgn/i3fft22NvbY//+/XnW7C+NOJJVQsikQMylVxUL98kXQH6Tvg3g6PNqlKuzfBFlIiIiKtE4kkUlkTpGsgr1q/9ly5YpMs4jR47gyJEjOHDgAHx8fDB58uTCnJIof1ragHULoP73gM8VoGcE0HwF4NQb0DEF0p8DYWuAoH7AdhvgSFvg3/8BcTfljyESERERERWTQq2TFRUVpUiy9u7dC39/f3Tu3BnOzs45auQTFQlDB6D6UPkmzQBeBGVXLIy/DTw/I99uTAOMKmU/VmjXEdA10XT0RERERFSGFWoky9LSEo8fPwYAHDx4EJ6engDkK1lLpVL1RUekCm09wK4D4D4P8P0X6P4AaLJEnlRpGwApT4B7y4HTPYDtFYDjnYE7C4GEu5qOnIiIiCD/PyRRSaGOv4+FGsnq1asXPvroI9SoUQMvX76Ej48PAODatWsqL7pGVGRMqgI1P5VvWalA9En5PK6IfUDyQyDqiHy7OgEwcclek8u2HaDNtd2IiIiKy+tCaSkpKTA0NNRwNERyKSkpAN6vkF+hkqz58+fD2dkZjx8/xk8//QQTE/njV5GRkfj0008LHQyR2ukYviqI4QOI34CE0OwS8dGngaR7QOhC+aZtBNh7vnq0sAtgXLhKN0RERKQabW1tWFhYIDo6GgBgZGQEiUSi4aiovBJCICUlBdHR0bCwsIC2tnahz1Wg6oLTp09Hjx490Lhx40JfsLRhdcEyLDMBiDqaPZcrNVJ5v0W97Llc1i0BrUL9ToKIiIjyIYRAVFQU4uLiNB0KEQDAwsIC9vb2uSb8quYGBUqyhg4dir1790JPTw/dunVDjx490LFjR+jp6RXuHZQCTLLKCSGA2OuvEq59wIvzAN74aOhaAA5er5Iub8DAVkOBEhERlU1SqRSZmZmaDoPKOV1d3XxHsIokyQIAmUyGoKAg7NmzB7t370ZkZCQ6deqEHj16oGvXrrCysirI6Uo8JlnlVNoLIPLQq4WQDwIZMW/slAAVmmaPclk14kLIREREROVAkSVZbwsJCVEkXFeuXEGzZs3QvXt39O/fHxUrVnyfU5cITLIIMinw8kL2Y4Wx15T3G9gCDj7yAhr2nQA9C42ESURERERFq9iSrDdFR0djz549CAwMxAcffIAvv/xSXafWGCZZlENKBBB54NUo12EgKyl7n0QbsGmTXTzDvA7ACbxEREREZYJGkqyyiEkW5UuaATw/m12xMOGO8n6jytkJl31HQMdYM3ESERER0Xsr0iQrLS0Nv/32G06cOIHo6GjIZDKl/VevXi14xCUUkywqkKQHwNNXjxVGnwCkadn7tPQBu/byeVyOXQDT6hoLk4iIiIgKrkiTrAEDBuDw4cPo06cP7OzscpQ3DAgIKHjEJRSTLCq0rBTg2YnsioXJj5T3m9aUJ1wVuwA2H3AhZCIiIqISrkiTLHNzc+zfvx+tW7d+ryALIiYmBuPHj8eePXugpaWF3r17Y+HChYqFkHPrHxAQgMOHDyM8PBw2Njbw8/PDrFmzYG5urvJ1mWSRWggBJIQAT189Vvj8LCCysvfrmLyxELIPYFRJc7ESERERUa5UzQ0KtbpqxYoVYWpqWujgCmPAgAGIjIzEkSNHkJmZiSFDhmDkyJHYsGFDrv0jIiIQERGBn3/+GW5ubnj06BFGjx6NiIgIbNu2rVhjJ4JEApi7yTe3yUBGPBB1JLtiYdoz4Mku+QYAFg3kCVdFX6BCcy6ETERERFSKFGok68CBA1i0aBGWLVuGKlWqFEVcSkJCQuDm5oZLly6hSZMmAICDBw+iS5cuePLkCRwdHVU6z9atW/Hxxx8jOTkZOjqq/aeVI1lU5IRMXhb+9VyulxegtBCynuWrhZB95V8NbDQWKhEREVF5VqQjWU2aNEFaWhqqVasGIyMj6OrqKu2PiYnJ48jCCQ4OhoWFhSLBAgBPT09oaWnhwoUL6Nmzp0rnef3NyC/BSk9PR3p6uuJ1QkJC4QMnUoVEC7BqLN/qfQekPX9rIeRY4NEm+QaJfGTLsYt8LpelOxdCJiIiIiphCpVk9e/fH0+fPsWcOXNyLXyhblFRUbC1tVVq09HRgZWVFaKiolQ6x4sXLzBr1iyMHDky335z587FzJkzCx0r0XszsAGqfizfZFnyka3Xc7nibgAvz8u3m9MBA3v5HC7HLq8WQlZ9viERERERFY1CJVnnzp1DcHAwGjRo8F4Xnzp1Kn788cd8+4SEhLzXNQD5aJSvry/c3NwwY8aMfPtOmzYNEydOVDrWycnpvWMgKhQtHcCmtXxrOAdIeQJEvFoIOeoIkBYFPFgl3yQ68oWQK74qEW/myoWQiYiIiDSgUElW7dq1kZqa+t4XnzRpEgYPHpxvn2rVqsHe3h7R0dFK7VlZWYiJiYG9vX2+xycmJsLb2xumpqbYuXNnjkcb36avrw99fZbSphLKqBLgMkK+SdOB52dezeXaByT+B0SflG/XJgPGztkLIdt1AHSMNBw8ERERUflQqMIXhw8fxsyZMzF79mzUq1cvR+Ki7gIRrwtfXL58GY0bN1bE4O3tnW/hi4SEBHh5eUFfXx/79++HkVHB/5PJwhdUaiTey65W+OwkIMueWwhtA8C2Q3bFQpOqGguTiIiIqLQq0nWytLTkE+3fnoslhIBEIoFUKi3oKd/Jx8cHz549w7JlyxQl3Js0aaIo4f706VN4eHhgzZo1aNasGRISEtC5c2ekpKRg586dMDY2VpzLxsYG2traKl2XSRaVSlnJQNTx7IWQUx4r7zer/WqUy1f+iKG2nmbiJCIiIipFirS64IkTJwodWGGtX78e48aNg4eHh2Ix4kWLFin2Z2ZmIjQ0FCkpKQCAq1ev4sKFCwAAFxcXpXOFhYXB2dm52GInKnY6xkClbvJNCCD+3+xRrudngYQ78u3Or68WQu4kH+Fy8AGMVFsSgYiIiIhyV6iRrPKEI1lU5mTEyYtmPN0HRB4A0pTnO8LSPXsuV4XmgJZqo75EREREZZ3aHxcMDw9H5cqVVQ7g6dOnqFixosr9SyomWVSmCRkQc1X+SGHEfuDlJSgvhGwFOHi/GuXyAvQraCxUIiIiIk1TNTdQeRXTpk2bYtSoUbh06VKefeLj4/Hnn3+ibt262L59e8EiJqLiJ9ECKjQB6gUAXheAXlFAi7+Byn0BXQsgIwZ4tAE4NwDYYQscbgXcmg3EXJM/hkhEREREOag8kvXy5UvMnj0bK1euhIGBARo3bgxHR0cYGBggNjYWt2/fxr///otGjRrhu+++Q5cuXYo69mLBkSwqt2RZwIvg7OIZcTeV9xs6ZD9WaN8J0DXVTJxERERExaTIqgumpqZi3759OHv2LB49eoTU1FRYW1vD3d0dXl5eqFu37nsHX5IwySJ6JflxdvGMqKOANCV7n5YuYPNBdsVCs1pcCJmIiIjKnCIt4V6eMMkiyoU0DYg+LU+4nu4Dku4p7zeuKp/H5dgFsG0P6BhqJEwiIiIidWKSpSZMsohUkHA3e5Qr+iQgy8jep20I2HXMfrTQxFlTURIRERG9FyZZasIki6iAMpOAZ8ezKxamPFHeb+6WnXDZtJE/akhERERUCjDJUhMmWUTvQQgg/pb8kcKI/cCLc4CQZu/XNZMXzXD0BRy95cU0iIiIiEooJllqwiSLSI0yYoHIw68eLTwApD9X3m/ZKHsul1VTLoRMREREJQqTLDVhkkVURIQMeHk5u0R8zGXl/frW8oWQHbu8WgjZSjNxEhEREb1S5EnW2rVrsWzZMoSFhSE4OBhVqlTBggULULVqVfTo0aPQgZc0TLKIiknqMyDygDzpijwEZCZk75NoAdYts0vEW9RniXgiIiIqdqrmBlqFOfnSpUsxceJEdOnSBXFxcZBK5XMsLCwssGDBgkIFTETlnKEdUG0w0GYL0PsF4HEScJ0CmNeRj3o9DwJufAMcaAjscgIujAQe7wIyEzUaNhEREdHbCjWS5ebmhjlz5sDPzw+mpqa4ceMGqlWrhlu3bqF9+/Z48eJFUcSqERzJIioBkh/J53BF7AeijuVcCNm2XfYol2kNjnIRERFRkVA1N9ApzMnDwsLg7u6eo11fXx/JycmFOSURUd6MqwA1Rss3aRrw7NSrEvH7gKQHQNRR+XZ1ImBSPTvhsmsHaBtoOnoiIiIqZwqVZFWtWhXXr19HlSpVlNoPHjwIV1dXtQRGRJQrbQPA0Uu+iYVA4t3sNbmiTwFJ94H/fpNv2kbyhZBfVyw0rqzp6ImIiKgcKFSSNXHiRIwdOxZpaWkQQuDixYvYuHEj5s6di7/++kvdMRIR5U4iAcxqyrfaX8jnZ0Ude1WxcD+Q+hSI2CvfAMC87hsLIbfiQshERERUJApdXXD9+vWYMWMG7t+/DwBwdHTEzJkzMWzYMLUGqGmck0VUSgkBxP2TXSL+RbC8gMZruuaAQ+dXJeJ95IU3iIiIiPJRbOtkpaSkICkpCba2tu9zmhKLSRZRGZEeIy8NH7FfXio+/aXyfqsm2XO5KjSRl40nIiIiegMXI1YTJllEZZBMCsRckidcT/cBsVeV9+vbAI4+r0a5OgN6lpqJk4iIiEoUtSdZ7u7ukKhYFvnq1avv7lRKMMkiKgdSI4GIg69KxB9+ayFkbcC6lTzhqugrn9fFEvFERETlktpLuPv5+Sn+nJaWht9//x1ubm5o2bIlAOD8+fP4999/8emnnxY+aiIiTTB0AKoPkW+yTPnCx68rFsbfBp6fkW83pgFGld4oEd8R0DXRdPRERERUwhTqccHhw4fDwcEBs2bNUmoPCAjA48ePsXLlSrUFqGkcySIq55IeZlcrfHYckKZm79PSe7UQ8qsS8WY1NBYmERERFb0inZNlbm6Oy5cvo0YN5f9Q3L17F02aNEF8fHzBIy6hmGQRkUJWKhB9MnsuV3KY8n7TGtkl4m3bAdr6GgmTiIiIiobaHxd8k6GhIYKCgnIkWUFBQTAwMCjMKYmISj4dw1cFMXyAxouAhNDsEvHRp+ULI4culG86xoCdh3wel4MPYOyk6eiJiIiomBQqyZowYQLGjBmDq1evolmzZgCACxcuYOXKlfjuu+/UGiARUYkkkQDmteWb60R5sYyoo28shBwJPA2UbwBgUS/7sULrloBWof75JSIiolKg0CXct2zZgoULFyIkJAQA4Orqis8//xz+/v5qDVDT+LggERWYEEDs9TcWQj4P4I1/anUtAAevV48WegMGZXOdQSIiorKmzK2TFRMTg/Hjx2PPnj3Q0tJC7969sXDhQpiYvLuylxACXbp0wcGDB7Fz506lSonvwiSLiN5b2gt5afin+4DIg0BGzBs7JUCFptkVC60acSFkIiKiEqpI52RpwoABAxAZGYkjR44gMzMTQ4YMwciRI7Fhw4Z3HrtgwQKV1/giIlI7A2vA+SP5JpMCLy9ml4iPvSZ//fIicHOGfFTLwUc+l8u+E6BnoenoiYiIqIAKNZIllUoxf/58bNmyBeHh4cjIyFDaHxMTk8eRhRMSEgI3NzdcunQJTZo0AQAcPHgQXbp0wZMnT+Do6JjnsdevX0fXrl1x+fJlODg4cCSLiEqWlAgg8oA84Yo8AmQlZu+TaAM2bbIrFprX4ULIREREGqRqblCoZ1JmzpyJX3/9FX379kV8fDwmTpyIXr16QUtLCzNmzChszHkKDg6GhYWFIsECAE9PT2hpaeHChQt5HpeSkoKPPvoIS5Ysgb29vUrXSk9PR0JCgtJGRFRkjByB6sOAD7YDvV8AHY8BtScBZrUBIQWiTwHXvwL21wN2OwMXxwBP9gBZyZqOnIiIiPJQqCRr/fr1+PPPPzFp0iTo6Oigf//++OuvvzB9+nScP39e3TEiKioKtrbKE8N1dHRgZWWFqKioPI/74osv0KpVK/To0UPla82dOxfm5uaKzcmJZZeJqJho6wH2HYFGPwNdQ4Du94Emi+WPD2obACnhwL1lwOnuwLYKwAlvIPQ3IPG+piMnIiKiNxQqyYqKikK9evUAACYmJorFh7t27Yp9+/apfJ6pU6dCIpHku925c6cwISIwMBDHjx/HggULCnTctGnTEB8fr9geP35cqOsTEb03k2pAzbFAh/1A75dAu71AjU8B4yqALB2IPARc+QzY4wLsqQVcmSgvIy9N13TkRERE5VqhCl9UqlQJkZGRqFy5MqpXr47Dhw+jUaNGuHTpEvT19VU+z6RJkzB48OB8+1SrVg329vaIjo5Was/KykJMTEyejwEeP34c9+/fh4WFhVJ779698cEHH+DkyZO5Hqevr1+g90BEVCx0jOTFMCr6AmIxkBAin8f1dB/w/CyQ+B8Q+h8QOh/QMQHsPbPnchlV1HT0RERE5UqhCl9MnToVZmZm+Prrr7F582Z8/PHHcHZ2Rnh4OL744gv873//U2uQrwtfXL58GY0bNwYAHD58GN7e3nkWvoiKisKLFy+U2urVq4eFCxeiW7duqFq1qkrXZuELIirxMuJfLYS8D4g4AKS99Ri1RQN5cubYBajQnAshExERFVKxrpMVHByM4OBg1KhRA926dXvf0+XKx8cHz549w7JlyxQl3Js0aaIo4f706VN4eHhgzZo1aNasWa7nkEgkrC5IRGWbkMkXQn76qkT8ywtQWghZzxJw8JYnXA7e8vLyREREpJJiXSerZcuWaNmypTpOlaf169dj3Lhx8PDwUCxGvGjRIsX+zMxMhIaGIiUlpUjjICIq0SRa8gWNrRoB9b6TL4QcefBVifiDQEYs8GijfINEPrLl2AWo2AWwdOdCyERERGqg8khWYGCgyift3r17oQMqaTiSRURlhixLPrL1ei5X3A3l/Qb2gKOPPOmy7wTomWsmTiIiohJK7Y8Lamkp/3ZTIpHg7UMlrxbJlEqlBY23xGKSRURlVspTecIVsR+IOqK89pZER74Q8uu5XGauXAiZiIjKPbUvRiyTyRTb4cOH0bBhQxw4cABxcXGIi4vDgQMH0KhRIxw8eFAtb4CIiIqYUUXAZQTQdqe8RHzHI0CtLwCzWoDIAqJPAtcmA/vqAIHVgEtj5SNgWXwsm4iIKD+FKnxRt25dLFu2DG3atFFqP3PmDEaOHImQkBC1BahpHMkionIp8Z68UmHEPuDZSfm6XK9pGwC2HV7N5fIFTFSr1kpERFTaFWnhi9zWnwIAc3NzPHz4sDCnJCKiksTUBag1Xr5lJQPPTmRXLEwJByIPyLcr4wGz2oDjq8cKbdoA2nqajp6IiEijCjWS1bZtWxgYGGDt2rWws7MDADx79gwDBw5EWloaTp06pfZANYUjWUREbxACiL/9ak2u/fKFkMUb83B1TAGHTq9KxPsARjnXMSQiIiqtinSdrHv37qFnz57477//4OTkBAB4/PgxatSogV27dsHFxaXwkZcwTLKIiPKREScvmvG6gEZatPJ+S3d5wuXoC1RoBmhpayRMIiIidSjyxYiFEDhy5Aju3LkDAHB1dYWnp6eiwmBZwSSLiEhFQgbEXH2VcO0DXl6C8kLIVvIFkCv6Ag5egH4FjYVKRERUGEWeZJUXTLKIiAopLRqIeL0Q8iEgMy57n0QLqNDi1ShXF8CyIUvEExFRiaf2JGvRokUYOXIkDAwMsGjRonz7fvbZZwWLtgRjkkVEpAayLOBFcPZjhXH/KO83dMhOuOw7AbqmmomTiIgoH2pPsqpWrYrLly+jQoUKqFo173K9EokEDx48KHjEJRSTLCKiIpD8WF6d8Ok+IOooIH1j7S0tXcDmg+y5XGa1OMpFREQlAh8XVBMmWURERUyaDkSfzq5YmHhXeb9xVfk8LscugG17QMdQI2ESERExyVITJllERMUs4W72Y4XRJwFZRvY+bUPArmP2o4UmzpqKkoiIyqEiTbJ69+6NZs2a4auvvlJq/+mnn3Dp0iVs3bq14BGXUEyyiIg0KDMJeHY8u2JhyhPl/eZu2Y8V2rSWP2pIRERURIo0ybKxscHx48dRr149pfabN2/C09MTz549K3jEJRSTLCKiEkIIIP6WPOF6ug94cU55IWRdM3nRDEdfwNEHMLTXXKxERFQmqZob6BTm5ElJSdDT08vRrquri4SEhMKckoiIKH8SCWBRT765fQVkxAKRh1+Nch0A0p8Dj7fLNwCwapz9WKFVUy6ETERExUarMAfVq1cPmzdvztG+adMmuLm5vXdQRERE76RnCVTpC7T8G+gVBXS+ANQNAKyayPfHXAFuzQIOtwR22gPnPgEebgLSYzQbNxERlXmFGsn67rvv0KtXL9y/fx8dO3YEABw7dgwbN24sU/OxiIiolJBoAdbN5Fv9GUDqMyDyoHweV+RhIP0F8HCdfJNoAdYtXz1W2AWwqM8S8UREpFaFri64b98+zJkzB9evX4ehoSHq16+PgIAAtGvXTt0xahTnZBERlXKyTPlCyE9flYiPv6W837DiGwshe3AhZCIiyhNLuKsJkywiojImOTy7RHzUsZwLIdu2y65YaFqDo1xERKRQLEnWlStXEBISAgCoU6cO3N3dC3uqEotJFhFRGSZNA56dyi4Rn3Rfeb9J9eyEy64doG2gmTiJiKhEKNIkKzo6Gv369cPJkydhYWEBAIiLi0OHDh2wadMm2NjYFDrwkoZJFhFROSEEkHg3O+GKPiV/1PA1bSP5QsgVX83lMq6suViJiEgjijTJ6tu3Lx48eIA1a9bA1dUVAHD79m0MGjQILi4u2LhxY+EjL2GYZBERlVOZifLHCV8/Wpj6VHm/ed3suVw2rbgQMhFROVCkSZa5uTmOHj2Kpk2bKrVfvHgRnTt3RlxcXIEDLqmYZBEREYQA4v7JHuV6EQwIWfZ+XXPAobP8sUIHb8DQTnOxEhFRkSnSxYhlMhl0dXP+xk5XVxcymSyXI4iIiEoxiQSwbCDf6kyTr7UVefhVifiD8hLx4VvlGyBfq+t1ifgKTeRl44mIqNwo1EhWjx49EBcXh40bN8LR0REA8PTpUwwYMACWlpbYuXOn2gPVFI5kERFRvmRSIOayPOGK2C9fBPlN+jaAo4884XLoLF9EmYiISqUifVzw8ePH6N69O/799184OTkp2urWrYvAwEBUqlSp8JGXMEyyiIioQFKjgIgDr0rEHwYyE7L3SbQB61byhKuir3xeF0vEExGVGkVewl0IgaNHj+LOnTsAAFdXV3h6ehYuWhXExMRg/Pjx2LNnD7S0tNC7d28sXLgQJiYm+R4XHByMb775BhcuXIC2tjYaNmyIQ4cOwdDQUKXrMskiIqJCk2UCz4Oy53LF31beb+SUXTzDriOgm//PNCIi0qwytxixj48PIiMj8ccffyAzMxNDhgxB06ZNsWHDhjyPCQ4Ohre3N6ZNm4Zu3bpBR0cHN27cQI8ePaCvr6/SdZlkERGR2iQ9BCIPAE/3Ac+OA9LU7H1aeq8WQn41l8ushsbCJCKi3Kk9yVq0aJHKF//ss89U7quKkJAQuLm54dKlS2jSpAkA4ODBg+jSpQuePHmimBf2thYtWqBTp06YNWtWoa/NJIuIiIpEVioQfVI+yvV0H5AcprzftEb2KJdtO0BbtV8OEhFR0VF7klW1alWVLiyRSPDgwQPVolTRypUrMWnSJMTGxirasrKyYGBggK1bt6Jnz545jomOjoadnR0WLVqEjRs34v79+6hduzZmz56NNm3aqHxtJllERFTkhAASQrMfK3x+RnkhZB1jwM5DPo/LwQcwdtJcrERE5ZjaS7iHhYW9u1MRiYqKgq2trVKbjo4OrKysEBUVlesxrxO9GTNm4Oeff0bDhg2xZs0aeHh44NatW6hRI/fHMNLT05Genq54nZCQkGs/IiIitZFIAPPa8s11orxYRtSx7IqFqZHA00D5BgAW9bIfK7RuCWgVakUWIiIqIu+1cEdGRgZCQ0ORlZVVqOOnTp0KiUSS7/a6sEZBvV6va9SoURgyZAjc3d0xf/581KpVCytXrszzuLlz58Lc3Fyxva6eSEREVGx0zQCnnkDzvwC/p4DPNaD+D/LKhBItIO4mcPt/wNG2wHYb4Gw/4MEaIO25piMnIiIUcjHilJQUjB8/Hn///TcA4L///kO1atUwfvx4VKxYEVOnTlXpPJMmTcLgwYPz7VOtWjXY29sjOjpaqT0rKwsxMTGwt7fP9TgHBwcAgJubm1K7q6srwsPD87zetGnTMHHiRMXrhIQEJlpERKQ5Eglg2VC+1f0GSH8JRB6Sj3BFHpS/Dt8s3yABKjR9NZfLF7BqxIWQiYg0oFBJ1rRp03Djxg2cPHkS3t7einZPT0/MmDFD5STLxsYGNjY27+zXsmVLxMXF4cqVK2jcuDEA4Pjx45DJZGjevHmuxzg7O8PR0RGhoaFK7f/99x98fHzyvJa+vr7KlQeJiIiKnX4FwPkj+SaTAi8vZs/lir0mf/3yInBzBmBgl70Qsn0nQM9C09ETEZULhSrhXqVKFWzevBktWrSAqakpbty4gWrVquHevXto1KhRkcxj8vHxwbNnz7Bs2TJFCfcmTZooSrg/ffoUHh4eWLNmDZo1awYAWLBgAQICArBixQo0bNgQf//9N37++WfcunUL1atXV+m6LHxBRESlRkqEfHQrYh8QeQTISszeJ9EGbNpkj3KZu3EhZCKiAlJ74Ys3PX/+PEchCgBITk6GpIj+wV6/fj3GjRsHDw8PxWLEb5aVz8zMRGhoKFJSUhRtEyZMQFpaGr744gvExMSgQYMGOHLkiMoJFhERUali5AhUHyrfpBnA87OvRrn2AwkhQPQp+Xb9K8CosjzhqugL2HWQVzAkIiK1KNRIVtu2bfHhhx9i/PjxMDU1xT///IOqVati/PjxuHv3Lg4ePFgUsWoER7KIiKhMSHoARLxaCDn6BCBNy96npQ/Ytc+uWGjKX0YSEeWmSEey5syZAx8fH9y+fRtZWVlYuHAhbt++jXPnzuHUqVOFDpqIiIiKiEk1oOZY+ZaVAjw7+apE/D4g+ZG8mEbkIeDKZ4BpTXnCVbELYPMBF0ImIiqgAo1k3bp1C3Xr1gUA3L9/H//73/9w48YNJCUloVGjRvjqq69Qr169IgtWEziSRUREZZoQQMKd7DW5os8A4o2lWXRMAHtPeQENe095skZEVE6pmhsUKMnS0tJC06ZNMXz4cPTr1w+mpqZqCbYkY5JFRETlSmaCvGjG67lcaVHK+42dAXsPwM5DPpfLMPelVIiIyqIiSbLOnDmDVatWYdu2bZDJZOjTpw+GDRuGDz74QC1Bl0RMsoiIqNwSMiD2unweV9Rh4MV55VEuADCvI0+47D0A23aAnrlGQiUiKg5FkmS9lpycjC1btmD16tU4c+YMXFxcMGzYMAwaNCjPxYFLKyZZREREr2QmAc/PAFHHgGfH5AnYmyRagFUTedJl2xawaQXo8mcnEZUdRZpkvenevXtYtWoV1q5di6ioKHh7eyMwMPB9TlmiMMkiIiLKQ9oLeaXCqOPypCvxrvJ+iRZg6S4vnmHbVr5Ol4GNZmIlIlKDYkuyAPnI1vr16zFt2jTExcVBKpW+7ylLDCZZREREKkoOB54dB56dkBfQSA7L2cfc7Y2k6wPA2Kn44yQiKqRiSbJOnz6NlStXYvv27dDS0oK/vz+GDRuGFi1aFPaUJQ6TLCIiokJKeSJPtqJPyx8zjP83Zx9jZ8C6JWDdQv7VogGgrVfsoRIRqaLIkqyIiAisXr0aq1evxr1799CqVSsMGzYM/v7+MDYue6vFM8kiIiJSk7QXwPOz2UlX7FV5cY03aRsAVo2BCi2yky+jipqJl4joLUWSZPn4+ODo0aOwtrbGwIEDMXToUNSqVUstAZdUTLKIiIiKSGYi8PIC8DwYeHleXr0wIyZnPyMnebJVoQVQoYl8npdu2V9GhohKHlVzA52CnFRXVxfbtm1D165doa2t/d5BEhERUTmmaypf4NjeU/5aCHnxjBfB8oTrRTAQfxNIeQyEPwbCt746UAKY1QQsG78a9WLiRUQli1oKX5RlHMkiIiLSoMwkIOaSPOl6eQGIuSKf65XDW4mXVSPAoj6gb1XsIRNR2VWs1QXLMiZZREREJUxatDzZenNLeZx7X8OK8mTLsj5gXk/+1bQWi2sQUaEwyVITJllERESlQFo0EHMViLksT7pirwHJj3Lvq6ULmNWWJ18W9eTJl7krYFQZ0OJ0CCLKW5HMySIiIiIqkQxsAUdv+fZaRjwQfwuIuwnE/ZP9NTPh1Z9vKp9D2wAwrSlPwMxc5V/Na8vbdIyK9/0QUanGJIuIiIjKJj1zwKa1fHtNCCAl/K3E66a84IY07VXbPznPZVxFnnSZ1gJMqwMmrzdneXJGRPQGPi74DnxckIiIqByQSYHkh0DCHSAh5NXXO0B8SO5l5RUk8nW8TKq9kXi9/nNVQN8akEiK610QURHjnCw1YZJFRERUzqW9yE66EkOBpAdA4n0g6T6QlZT/sdoG8nW+jCq9+vrGZvzqq645EzGiUoJzsoiIiIjUwcAaMGgD2LZRbhcCSH8hT7qS7ssTr+TXCdgDIPWp/BHExLvyLS86xvIkzMAeMLCTfzW0e/Vnu+w2A1tAW79o3ysRqQWTLCIiIqLCkEgAAxv5Zt08535pujzRSn4sLzH/envzdUYMkJUMJITKt3fRtZAnW3pW8jXA9Cxfbbn8Wd9K3l/XBNA2ZuVEomLEJIuIiIioKGjrv5qfVS3vPlkp8sWVU54Aac+Ut9Qo5dciC8iMk2+FisdQPmqmY/LG1zf/bARo6QNaevJ1xCS62X/WenPTle9TPOL41tc329/Zh0hFBnbKRWxKOCZZRERERJqiYwSY1ZRv+RECyIgF0qLka4JlxL6xxci/psfkbMuMA4RMfg5pqnxLf1Hkb4tI7Ry8gA4HNR2FyphkEREREZV0Eon88T99K8DcTfXjhJDPC8tKkj+WqPT17bZkQJYByDJffX1jk771Wpb5+gLKX8Wbr3Nre/MrUQGY19F0BAXCJIuIiIiorJJIAB1D+QYbTUdDVG5oaToAIiIiIiKisoRJFhERERERkRoxySIiIiIiIlIjJllERERERERqxMIX7yBeVcRJSEjQcCRERERERKRJr3MCIfKvkskk6x0SExMBAE5OThqOhIiIiIiISoLExESYm5vnuV8i3pWGlXMymQwREREwNTWFRMOrkyckJMDJyQmPHz+GmZmZRmMh1fG+lU68b6UT71vpxPtWevHelU68b4UnhEBiYiIcHR2hpZX3zCuOZL2DlpYWKlWqpOkwlJiZmfEDUQrxvpVOvG+lE+9b6cT7Vnrx3pVOvG+Fk98I1mssfEFERERERKRGTLKIiIiIiIjUiElWKaKvr4+AgADo6+trOhQqAN630on3rXTifSudeN9KL9670on3reix8AUREREREZEacSSLiIiIiIhIjZhkERERERERqRGTLCIiIiIiIjVikkVERERERKRGTLJKmCVLlsDZ2RkGBgZo3rw5Ll68mG//rVu3onbt2jAwMEC9evWwf//+YoqU3lSQ+7Z69WpIJBKlzcDAoBijJQA4ffo0unXrBkdHR0gkEuzateudx5w8eRKNGjWCvr4+XFxcsHr16iKPk5QV9L6dPHkyx+dNIpEgKiqqeAImAMDcuXPRtGlTmJqawtbWFn5+fggNDX3ncfwZp1mFuW/8Gad5S5cuRf369RULDbds2RIHDhzI9xh+1tSPSVYJsnnzZkycOBEBAQG4evUqGjRoAC8vL0RHR+fa/9y5c+jfvz+GDRuGa9euwc/PD35+frh161YxR16+FfS+AfIV1iMjIxXbo0ePijFiAoDk5GQ0aNAAS5YsUal/WFgYfH190aFDB1y/fh0TJkzA8OHDcejQoSKOlN5U0Pv2WmhoqNJnztbWtogipNycOnUKY8eOxfnz53HkyBFkZmaic+fOSE5OzvMY/ozTvMLcN4A/4zStUqVK+N///ocrV67g8uXL6NixI3r06IF///031/78rBURQSVGs2bNxNixYxWvpVKpcHR0FHPnzs21v7+/v/D19VVqa968uRg1alSRxknKCnrfVq1aJczNzYspOlIFALFz5858+0yZMkXUqVNHqa1v377Cy8urCCOj/Khy306cOCEAiNjY2GKJiVQTHR0tAIhTp07l2Yc/40oeVe4bf8aVTJaWluKvv/7KdR8/a0WDI1klREZGBq5cuQJPT09Fm5aWFjw9PREcHJzrMcHBwUr9AcDLyyvP/qR+hblvAJCUlIQqVarAyckp398uUcnBz1vp1rBhQzg4OKBTp04ICgrSdDjlXnx8PADAysoqzz78zJU8qtw3gD/jShKpVIpNmzYhOTkZLVu2zLUPP2tFg0lWCfHixQtIpVLY2dkptdvZ2eU5dyAqKqpA/Un9CnPfatWqhZUrV2L37t1Yt24dZDIZWrVqhSdPnhRHyFRIeX3eEhISkJqaqqGo6F0cHBywbNkybN++Hdu3b4eTkxPat2+Pq1evajq0cksmk2HChAlo3bo16tatm2c//owrWVS9b/wZVzLcvHkTJiYm0NfXx+jRo7Fz5064ubnl2peftaKho+kAiMqbli1bKv02qVWrVnB1dcUff/yBWbNmaTAyorKnVq1aqFWrluJ1q1atcP/+fcyfPx9r167VYGTl19ixY3Hr1i2cPXtW06FQAah63/gzrmSoVasWrl+/jvj4eGzbtg2DBg3CqVOn8ky0SP04klVCWFtbQ1tbG8+ePVNqf/bsGezt7XM9xt7evkD9Sf0Kc9/epqurC3d3d9y7d68oQiQ1yevzZmZmBkNDQw1FRYXRrFkzft40ZNy4cdi7dy9OnDiBSpUq5duXP+NKjoLct7fxZ5xm6OnpwcXFBY0bN8bcuXPRoEEDLFy4MNe+/KwVDSZZJYSenh4aN26MY8eOKdpkMhmOHTuW5zO0LVu2VOoPAEeOHMmzP6lfYe7b26RSKW7evAkHB4eiCpPUgJ+3suP69ev8vBUzIQTGjRuHnTt34vjx46hateo7j+FnTvMKc9/exp9xJYNMJkN6enqu+/hZKyKarrxB2TZt2iT09fXF6tWrxe3bt8XIkSOFhYWFiIqKEkII8cknn4ipU6cq+gcFBQkdHR3x888/i5CQEBEQECB0dXXFzZs3NfUWyqWC3reZM2eKQ4cOifv374srV66Ifv36CQMDA/Hvv/9q6i2US4mJieLatWvi2rVrAoD49ddfxbVr18SjR4+EEEJMnTpVfPLJJ4r+Dx48EEZGRmLy5MkiJCRELFmyRGhra4uDBw9q6i2USwW9b/Pnzxe7du0Sd+/eFTdv3hSff/650NLSEkePHtXUWyiXxowZI8zNzcXJkydFZGSkYktJSVH04c+4kqcw940/4zRv6tSp4tSpUyIsLEz8888/YurUqUIikYjDhw8LIfhZKy5MskqY3377TVSuXFno6emJZs2aifPnzyv2tWvXTgwaNEip/5YtW0TNmjWFnp6eqFOnjti3b18xR0xCFOy+TZgwQdHXzs5OdOnSRVy9elUDUZdvr0t7v729vleDBg0S7dq1y3FMw4YNhZ6enqhWrZpYtWpVscdd3hX0vv3444+ievXqwsDAQFhZWYn27duL48ePayb4ciy3ewZA6TPEn3ElT2HuG3/Gad7QoUNFlSpVhJ6enrCxsREeHh6KBEsIftaKi0QIIYpv3IyIiIiIiKhs45wsIiIiIiIiNWKSRUREREREpEZMsoiIiIiIiNSISRYREREREZEaMckiIiIiIiJSIyZZREREREREasQki4iIiIiISI2YZBERERWj0NBQ2NvbIzEx8Z19b9++jUqVKiE5ObkYIiMiInVhkkVERCWaRCLJd5sxY4amQyyQadOmYfz48TA1NX1nXzc3N7Ro0QK//vprMURGRETqIhFCCE0HQURElJeoqCjFnzdv3ozp06cjNDRU0WZiYgITExNNhFZg4eHhcHFxQVhYGCpWrKjSMfv27cOIESMQHh4OHR2dIo6QiIjUgSNZRERUotnb2ys2c3NzSCQSpbZNmzbB1dUVBgYGqF27Nn7//XfFsQ8fPoREIsGWLVvwwQcfwNDQEE2bNsV///2HS5cuoUmTJjAxMYGPjw+eP3+uOG7w4MHw8/PDzJkzYWNjAzMzM4wePRoZGRmKPunp6fjss89ga2sLAwMDtGnTBpcuXcr3vWzZsgUNGjRQSrAePXqEbt26wdLSEsbGxqhTpw7279+v2N+pUyfExMTg1KlT6vh2EhFRMeCvxIiIqNRav349pk+fjsWLF8Pd3R3Xrl3DiBEjYGxsjEGDBin6BQQEYMGCBahcuTKGDh2Kjz76CKampli4cCGMjIzg7++P6dOnY+nSpYpjjh07BgMDA5w8eRIPHz7EkCFDUKFCBcyePRsAMGXKFGzfvh1///03qlSpgp9++gleXl64d+8erKysco33zJkzaNKkiVLb2LFjkZGRgdOnT8PY2Bi3b99WGpnT09NDw4YNcebMGXh4eKjz20dEREWESRYREZVaAQEB+OWXX9CrVy8AQNWqVXH79m388ccfSknWl19+CS8vLwDA559/jv79++PYsWNo3bo1AGDYsGFYvXq10rn19PSwcuVKGBkZoU6dOvj+++8xefJkzJo1C6mpqVi6dClWr14NHx8fAMCff/6JI0eOYMWKFZg8eXKu8T569ChHkhUeHo7evXujXr16AIBq1arlOM7R0RGPHj0qxHeIiIg0gUkWERGVSsnJybh//z6GDRuGESNGKNqzsrJgbm6u1Ld+/fqKP9vZ2QGAIql53RYdHa10TIMGDWBkZKR43bJlSyQlJeHx48eIj49HZmamIkkDAF1dXTRr1gwhISF5xpyamgoDAwOlts8++wxjxozB4cOH4enpid69eyvFCwCGhoZISUnJ87xERFSycE4WERGVSklJSQDkI0jXr19XbLdu3cL58+eV+urq6ir+LJFIcm2TyWRFHrO1tTViY2OV2oYPH44HDx7gk08+wc2bN9GkSRP89ttvSn1iYmJgY2NT5PEREZF6MMkiIqJSyc7ODo6Ojnjw4AFcXFyUtqpVq773+W/cuIHU1FTF6/Pnz8PExAROTk6oXr069PT0EBQUpNifmZmJS5cuwc3NLc9zuru74/bt2znanZycMHr0aOzYsQOTJk3Cn3/+qbT/1q1bcHd3f+/3RERExYOPCxIRUak1c+ZMfPbZZzA3N4e3tzfS09Nx+fJlxMbGYuLEie917oyMDAwbNgzffvstHj58iICAAIwbNw5aWlowNjbGmDFjMHnyZFhZWaFy5cr46aefkJKSgmHDhuV5Ti8vLwwfPhxSqRTa2toAgAkTJsDHxwc1a9ZEbGwsTpw4AVdXV8UxDx8+xNOnT+Hp6fle74eIiIoPkywiIiq1hg8fDiMjI8ybNw+TJ0+GsbEx6tWrhwkTJrz3uT08PFCjRg20bdsW6enp6N+/v9LCx//73/8gk8nwySefIDExEU2aNMGhQ4dgaWmZ5zl9fHygo6ODo0ePKgpxSKVSjB07Fk+ePIGZmRm8vb0xf/58xTEbN25E586dUaVKlfd+T0REVDy4GDEREdFbBg8ejLi4OOzatUvt516yZAkCAwNx6NChd/bNyMhAjRo1sGHDBqUiG0REVLJxJIuIiKgYjRo1CnFxcUhMTISpqWm+fcPDw/H1118zwSIiKmU4kkVERPSWohzJIiKiso9JFhERERERkRqxhDsREREREZEaMckiIiIiIiJSIyZZREREREREasQki4iIiIiISI2YZBEREREREakRkywiIiIiIiI1YpJFRERERESkRkyyiIiIiIiI1IhJFhERERERkRoxySIiIiIiIlIjJllERERERERqxCSLiIjei7OzMwYPHqzpMPKVkZGB9u3bw9LSEj/99BMeP34MCwsLTYdFRERlFJMsIqIy5vfff4dEIkHz5s01HUqJcfToUURFRWHq1KlYsGABqlSpguHDh2s6rPfi7OwMiUTyzm316tWaDpWIqNyRCCGEpoMgIiL1ad26NSIiIvDw4UPcvXsXLi4uRXo9Z2dntG/fvkT/Zz4xMRGpqamwtbVFZmYmXr58CXt7e02H9V527dqFpKQkxev9+/dj48aNmD9/PqytrRXtrVq1QrVq1TQRIhFRuaWj6QCIiEh9wsLCcO7cOezYsQOjRo3C+vXrERAQoOmwVJaVlQWZTAY9PT21ntfU1BSmpqYAAF1d3VKfYAGAn5+f0uuoqChs3LgRfn5+cHZ21khMREQkx8cFiYjKkPXr18PS0hK+vr7o06cP1q9fn2u/uLg4fPHFF3B2doa+vj4qVaqEgQMH4sWLF4o+6enpCAgIgIuLC/T19eHk5IQpU6YgPT39nXHExcVhwoQJcHJygr6+PlxcXPDjjz9CJpMp+jx8+BASiQQ///wzFixYgOrVq0NfXx+3b99GRkYGpk+fjsaNG8Pc3BzGxsb44IMPcOLEiRzXkslkWLhwIerVqwcDAwPY2NjA29sbly9fVvRZsWIFOnbsCFtbW+jr68PNzQ1Lly7NNfbff/8dderUgb6+PhwdHTF27FjExcXl+363bdsGiUSCU6dO5dj3xx9/QCKR4NatWwDkydCQIUNQqVIl6Ovrw8HBAT169MDDhw/f+X0tjHXr1qFx48YwNDSElZUV+vXrh8ePHyv1ad++PerWrYt//vkH7dq1g5GREVxcXLBt2zYAwKlTp9C8eXMYGhqiVq1aOHr0qNLxM2bMgEQiwZ07d+Dv7w8zMzNUqFABn3/+OdLS0pT6ZmVlYdasWYr77ezsjK+//lqlv1dERKUFR7KIiMqQ9evXo1evXtDT00P//v2xdOlSXLp0CU2bNlX0SUpKwgcffICQkBAMHToUjRo1wosXLxAYGIgnT57A2toaMpkM3bt3x9mzZzFy5Ei4urri5s2bmD9/Pv777z/s2rUrzxhSUlLQrl07PH36FKNGjULlypVx7tw5TJs2DZGRkViwYIFS/1WrViEtLQ0jR46Evr4+rKyskJCQgL/++gv9+/fHiBEjkJiYiBUrVsDLywsXL15Ew4YNFccPGzYMq1evho+PD4YPH46srCycOXMG58+fR5MmTQDIE6cGDRqge/fu0NHRwZ49e/Dpp59CJpNh7NixinPNmDEDM2fOhKenJ8aMGYPQ0FDF9zAoKAi6urq5vmdfX1+YmJhgy5YtaNeundK+zZs3o06dOqhbty4AoHfv3vj3338xfvx4ODs7Izo6GkeOHEF4eLjaR6Bmz56N7777Dv7+/hg+fDieP3+O3377DW3btsW1a9eUin/Exsaia9eu6NevHz788EMsXboU/fr1w/r16zFhwgSMHj0aH330EebNm4c+ffrg8ePHitHB1/z9/eHs7Iy5c+fi/PnzWLRoEWJjY7FmzRpFn+HDh+Pvv/9Gnz59MGnSJFy4cAFz585FSEgIdu7cqdb3T0SkMYKIiMqEy5cvCwDiyJEjQgghZDKZqFSpkvj888+V+k2fPl0AEDt27MhxDplMJoQQYu3atUJLS0ucOXNGaf+yZcsEABEUFKRoq1Klihg0aJDi9axZs4SxsbH477//lI6dOnWq0NbWFuHh4UIIIcLCwgQAYWZmJqKjo5X6ZmVlifT0dKW22NhYYWdnJ4YOHapoO378uAAgPvvsszzfixBCJCcn59jv5eUlqlWrpngdHR0t9PT0ROfOnYVUKlW0L168WAAQK1euzHGON/Xv31/Y2tqKrKwsRVtkZKTQ0tIS33//veI9ABDz5s3L91yFMW/ePAFAhIWFCSGEePjwodDW1hazZ89W6nfz5k2ho6Oj1N6uXTsBQGzYsEHRdufOHQFAaGlpifPnzyvaDx06JACIVatWKdoCAgIEANG9e3ela3366acCgLhx44YQQojr168LAGL48OFK/b788ksBQBw/fvy9vgdERCUFHxckIioj1q9fDzs7O3To0AEAIJFI0LdvX2zatAlSqVTRb/v27WjQoAF69uyZ4xwSiQQAsHXrVri6uqJ27dp48eKFYuvYsSMA5PrY3mtbt27FBx98AEtLS6VjPT09IZVKcfr0aaX+vXv3ho2NjVKbtra2Yl6WTCZDTEwMsrKy0KRJE1y9elXpvUgkklznnb1+LwBgZGSk+HN8fDxevHiBdu3a4cGDB4iPjwcgr0CYkZGBCRMmQEsr+8fjiBEjYGZmhn379uX5ngGgb9++iI6OxsmTJxVt27Ztg0wmQ9++fQEAhoaG0NPTw8mTJxEbG5vv+d7Xjh07IJPJ4O/vr3Qf7O3tUaNGjRz30MTEBP369VO8rlWrFiwsLODq6qpUqfL1nx88eJDjmm+OCgLA+PHjAciLcrz5deLEiUr9Jk2aBADv/B4TEZUWfFyQiKgMkEql2LRpEzp06ICwsDBFe/PmzfHLL7/g2LFj6Ny5MwDg/v376N27d77nu3v3LkJCQnIkP69FR0fne+w///yj8rFVq1bNtd/ff/+NX375BXfu3EFmZmau/e/fvw9HR0dYWVnlGQ8ABAUFISAgAMHBwUhJSVHaFx8fD3Nzczx69AiAPLl4k56eHqpVq6bYnxdvb2+Ym5tj8+bN8PDwACB/VLBhw4aoWbMmAEBfXx8//vgjJk2aBDs7O7Ro0QJdu3bFwIED1V6M4+7duxBCoEaNGrnuf/vRx0qVKiklpgBgbm4OJyenHG0Ack0S375W9erVoaWlpZhv9ujRI2hpaeWoeGlvbw8LC4t3fo+JiEoLJllERGXA8ePHERkZiU2bNmHTpk059q9fv16RZKlCJpOhXr16+PXXX3Pd//Z/vN8+tlOnTpgyZUqu+18nHK8ZGhrm6LNu3ToMHjwYfn5+mDx5MmxtbaGtrY25c+fi/v37Kr8PQJ6IeXh4oHbt2vj111/h5OQEPT097N+/H/Pnz1cqxvE+9PX14efnh507d+L333/Hs2fPEBQUhDlz5ij1mzBhArp164Zdu3bh0KFD+O677zB37lwcP34c7u7uaokFkN8HiUSCAwcOQFtbO8d+ExMTpde59cmvXaiwAszbSdu72omIygomWUREZcD69etha2uLJUuW5Ni3Y8cO7Ny5E8uWLYOhoSGqV6+uqHSXl+rVq+PGjRvw8PAo8H+Iq1evjqSkJHh6ehbouDdt27YN1apVw44dO5Su//ZjgdWrV8ehQ4cQExOT52jWnj17kJ6ejsDAQFSuXFnR/vbjclWqVAEAhIaGKq0rlZGRgbCwMJXeT9++ffH333/j2LFjCAkJgRBC8ajg23FPmjQJkyZNwt27d9GwYUP88ssvWLdu3Tuvoarq1atDCIGqVavmSGyLyt27d5VGGu/duweZTKYo6FGlShXIZDLcvXsXrq6uin7Pnj1DXFyc4h4QEZV2nJNFRFTKpaamYseOHejatSv69OmTYxs3bhwSExMRGBgIQD4H6saNG7lWcns9OuHv74+nT5/izz//zPV6ycnJecbj7++P4OBgHDp0KMe+uLg4ZGVlvfM9vR49eXO05MKFCwgODlbq17t3bwghMHPmzDzfS27nio+Px6pVq5T6e3p6Qk9PD4sWLVLqu2LFCsTHx8PX1/edcXt6esLKygqbN2/G5s2b0axZM6WkIyUlJUdJ8+rVq8PU1FSphHlkZGSOxyQLqlevXtDW1sbMmTNzjDoJIfDy5ctCnzsvbyf5v/32GwDAx8cHANClSxcAyFFh8vWIqSrfYyKi0oAjWUREpVxgYCASExPRvXv3XPe3aNECNjY2WL9+Pfr27YvJkydj27Zt+PDDDzF06FA0btwYMTExCAwMxLJly9CgQQN88skn2LJlC0aPHo0TJ06gdevWkEqluHPnDrZs2YJDhw4pyqO/bfLkyQgMDETXrl0xePBgNG7cGMnJybh58ya2bduGhw8fwtraOt/31LVrV+zYsQM9e/aEr68vwsLCsGzZMri5uSEpKUnRr0OHDvjkk0+waNEi3L17F97e3pDJZDhz5gw6dOiAcePGoXPnztDT00O3bt0watQoJCUl4c8//4StrS0iIyMV57KxscG0adMwc+ZMeHt7o3v37ggNDcXvv/+Opk2b4uOPP37nvdDV1UWvXr2wadMmJCcn4+eff1ba/99//8HDwwP+/v5wc3ODjo4Odu7ciWfPnikVnZg2bRr+/vtvhIWFFbqse/Xq1fHDDz9g2rRpePjwIfz8/GBqaoqwsDDs3LkTI0eOxJdfflmoc+clLCwM3bt3h7e3N4KDg7Fu3Tp89NFHaNCgAQCgQYMGGDRoEJYvX464uDi0a9cOFy9exN9//w0/Pz9F0RYiolJPM0UNiYhIXbp16yYMDAxyLVP+2uDBg4Wurq548eKFEEKIly9finHjxomKFSsKPT09UalSJTFo0CDFfiGEyMjIED/++KOoU6eO0NfXF5aWlqJx48Zi5syZIj4+XtHv7RLuQgiRmJgopk2bJlxcXISenp6wtrYWrVq1Ej///LPIyMgQQmSXcM+tnLlMJhNz5swRVapUEfr6+sLd3V3s3btXDBo0SFSpUkWpb1ZWlpg3b56oXbu2ACAACB8fH3HlyhVFn8DAQFG/fn1hYGAgnJ2dxY8//ihWrlypVPL8tcWLF4vatWsLXV1dYWdnJ8aMGSNiY2PzuwVKjhw5IgAIiUQiHj9+rLTvxYsXYuzYsaJ27drC2NhYmJubi+bNm4stW7Yo9Rs0aFCuseXn7RLur23fvl20adNGGBsbC2NjY1G7dm0xduxYERoaqujTrl07UadOnRznrFKlivD19c3RDkCMHTtW8fp1Cffbt2+LPn36CFNTU2FpaSnGjRsnUlNTlY7NzMwUM2fOFFWrVhW6urrCyclJTJs2TaSlpan8XomISjqJECrMXCUiIioFzp49i6+++gpBQUGaDqVceb2I8/Pnz985SklEVB5wThYREZUZbdq0QUhISK5rOBERERUXzskiIqJS7/nz51i5ciUAeVGLN+dtERERFTcmWUREVOpJpVIsWrQIsbGx+Pjjj1G/fn1Nh0REROUY52QRERERERGpEedkERERERERqRGTLCIiIiIiIjXinKx3kMlkiIiIgKmpKSQSiabDISIiIiIiDRFCIDExEY6OjtDSynu8iknWO0RERMDJyUnTYRARERERUQnx+PFjVKpUKc/9TLLewdTUFID8G2lmZqbhaIiIiIiISFMSEhLg5OSkyBHyUuqSrCVLlmDevHmIiopCgwYN8Ntvv6FZs2Z59t+6dSu+++47PHz4EDVq1MCPP/6ILl26qHy9148ImpmZMckiIiIiIqJ3TiMqVYUvNm/ejIkTJyIgIABXr15FgwYN4OXlhejo6Fz7nzt3Dv3798ewYcNw7do1+Pn5wc/PD7du3SrmyImIiIiIqLwoVetkNW/eHE2bNsXixYsByItSODk5Yfz48Zg6dWqO/n379kVycjL27t2raGvRogUaNmyIZcuWqXTNhIQEmJubIz4+niNZRERERETlmKq5Qal5XDAjIwNXrlzBtGnTFG1aWlrw9PREcHBwrscEBwdj4sSJSm1eXl7YtWtXUYZKREREVC5FJEbg5rObkAkZZEIGAaH4s0zINB0elWJ2xnZoXbm1psNQWalJsl68eAGpVAo7Ozuldjs7O9y5cyfXY6KionLtHxUVled10tPTkZ6ernidkJDwztiEEMjKyoJUKn1nXyJN0dbWho6ODpciICKiInHw3kH4bfJDujT93Z2JCsiruhcOfnxQ02GorNQkWcVl7ty5mDlzpsr9MzIyEBkZiZSUlCKMikg9jIyM4ODgAD09PU2HQkREZcj+u/vRc3NPZEgzUM2yGiwMLKAl0VJsEkggkUggAX/RR4VTx6aOpkMokFKTZFlbW0NbWxvPnj1Tan/27Bns7e1zPcbe3r5A/QFg2rRpSo8Yvi7TmBuZTIawsDBoa2vD0dERenp6HCWgEkkIgYyMDDx//hxhYWGoUaNGvgvoERERqWrff/vQa0svZEgz0Nu1Nzb23ghdbV1Nh0WkUaUmydLT00Pjxo1x7Ngx+Pn5AZAnOceOHcO4ceNyPaZly5Y4duwYJkyYoGg7cuQIWrZsmed19PX1oa+vr1JMGRkZiuIbRkZGKr8XIk0wNDSErq4uHj16hIyMDBgYGGg6JCIiKuX2hO5B7y29kSnLRB+3PtjQawMTLCKUoiQLACZOnIhBgwahSZMmaNasGRYsWIDk5GQMGTIEADBw4EBUrFgRc+fOBQB8/vnnaNeuHX755Rf4+vpi06ZNuHz5MpYvX67WuDgiQKUF/64SEZG6BIYGos+WPsiUZeJDtw+xvtd6JlhEr5SqJKtv3754/vw5pk+fjqioKDRs2BAHDx5UFLcIDw9X+k9kq1atsGHDBnz77bf4+uuvUaNGDezatQt169bV1FsgIiIiKvV239mND7d+iExZJvrW6Yt1vdZBR6tU/beSqEiVul9rjxs3Do8ePUJ6ejouXLiA5s2bK/adPHkSq1evVur/4YcfIjQ0FOnp6bh16xa6dOlSzBGXT6tXr4aFhYWmwwAAxMXFoXbt2mjdujUiIiLg6uqqtnO3bdsWGzZsUNv5Cuv27duoVKkSkpOTNR0KERGVcTtDdqLPVvkIVr+6/ZhgEeWi1CVZpD7BwcHQ1taGr6+vpkMpUufOnUP79u0xcuRItGvXDr169VLLeQMDA/Hs2TP069dPLef7+++/0aZNm3z7nD9/Hp6enmjdujUaNWqEy5cvAwDc3NzQokUL/Prrr2qJhYiIKDc7QnbAf5s/smRZ6F+3P9b2XMsEiygXTLLKsRUrVmD8+PE4ffo0IiIiNB1ODpmZmWo5T5cuXbBs2TIMGjQId+/exezZs9Vy3kWLFmHIkCFqm+e0e/dudO/ePd8+jRo1wtGjRxEUFIRevXph69atin1DhgzB0qVLkZWVpZZ4iIiI3rTt9jb4b5UnWAPqDcCanmuYYBHlgUlWOZWUlITNmzdjzJgx8PX1zfGYJQDs2bMHTZs2hYGBAaytrdGzZ0/FvvT0dHz55ZeoWLEijI2N0bx5c5w8eTLfa+7evRuNGjWCgYEBqlWrhpkzZyolBBKJBEuXLkX37t1hbGyM2bNnQyqVYtiwYahatSoMDQ1Rq1YtLFy4MMe5V65ciTp16kBfXx8ODg5KFSd//fVX1KtXD8bGxnBycsKnn36KpKQkpeO3b9+uON7Z2Rm//PJLvu/l+fPnOH78OLp166bULpFI8Mcff6Br164wMjKCq6srgoODce/ePbRv3x7GxsZo1aoV7t+/r3RcWloaDh8+rEiyfv/9d9SoUQMGBgaws7NDnz59AECxvtWlS5dw+PBhTJ48WXGOTp06ISYmBqdOnco3diIiooLa+u9W9NvWD1IhxSf1P8Hffn8zwSLKj6B8xcfHCwAiPj4+x77U1FRx+/ZtkZqaKoQQQiaTiaT0JI1sMpmsQO9rxYoVokmTJkIIIfbs2SOqV6+udI69e/cKbW1tMX36dHH79m1x/fp1MWfOHMX+4cOHi1atWonTp0+Le/fuiXnz5gl9fX3x33//CSGEWLVqlTA3N1f0P336tDAzMxOrV68W9+/fF4cPHxbOzs5ixowZij4AhK2trVi5cqW4f/++ePTokcjIyBDTp08Xly5dEg8ePBDr1q0TRkZGYvPmzYrjfv/9d2FgYCAWLFggQkNDxcWLF8X8+fMV++fPny+OHz8uwsLCxLFjx0StWrXEmDFjFPsvX74stLS0xPfffy9CQ0PFqlWrhKGhoVi1alWe378dO3YIY2NjIZVKldoBiIoVK4rNmzeL0NBQ4efnJ5ydnUXHjh3FwYMHxe3bt0WLFi2Et7e30nF79+4VNWvWFEIIcenSJaGtrS02bNggHj58KK5evSoWLlyo6PvXX3+JXr16iZiYmBxxNW/eXAQEBOQZ99t/Z4mIiN5l081NQnumtsAMiIE7B4osaZamQyLSmPxygzdJhBBC1YRMJpPh1KlTOHPmDB49eoSUlBTY2NjA3d0dnp6eeS7aW5olJCTA3Nwc8fHxMDMzU9qXlpaGsLAwVK1aFQYGBkjOSIbJXBONxJk0LQnGesYq92/dujX8/f3x+eefIysrCw4ODti6dSvat28PQF6ZsVq1ali3bl2OY8PDw1GtWjWEh4fD0dFR0e7p6YlmzZphzpw5WL16NSZMmIC4uDjFPg8PD0ybNk3Rf926dZgyZYriUUWJRIIJEyZg/vz5+cY+btw4REVFYdu2bQCAihUrYsiQIfjhhx9Ueu/btm3D6NGj8eLFCwDAgAED8Pz5cxw+fFjRZ8qUKdi3bx/+/fffXM+xYMEC/PbbbzlGpCQSCb799lvMmjULgHwOVcuWLbFixQoMHToUALBp0yYMGTIEqampiuNGjhwJc3NzzJs3Dzt27MCQIUPw5MkTmJqaKp1/586d+PDDD9G4cWNIJBJ07NgRc+bMUezv1asXzM3NsWrVqlzjfvvvLBERUX423dqEATsGQCZkGNRgEFZ0XwFtLW1Nh0WkMfnlBm9SaZw3NTUVv/zyC5YuXYqYmBg0bNgQjo6OMDQ0xL1797Br1y6MGDECnTt3xvTp09GiRQu1vRFSv9DQUFy8eBE7d+4EAOjo6KBv375YsWKFIsm6fv06RowYkevxN2/ehFQqRc2aNZXa09PTUaFChVyPuXHjBoKCgpTmQ0mlUqSlpSElJUWxmHOTJk1yHLtkyRKsXLkS4eHhSE1NRUZGBho2bAgAiI6ORkREBDw8PPJ8v0ePHsXcuXNx584dJCQkICsrS+m6ISEh6NGjh9IxrVu3xoIFCyCVSqGtnfOHSWpqap5JSv369RV/fr28QL169ZTa0tLSkJCQADMzMwghsGfPHmzZsgWA/LG/KlWqoFq1avD29oa3tzd69uwJIyMj9OzZM985V4aGhkhJSclzPxERkao23NyAT3Z+ApmQYUjDIfiz259MsIhUpFKSVbNmTbRs2RJ//vknOnXqBF3dnAvNPXr0CBs2bEC/fv3wzTff5Pkf9LLMSNcISdOS3t2xiK6tqhUrViArK0tpFEoIAX19fSxevBjm5uYwNDTM8/ikpCRoa2vjypUrORIQE5PcR/KSkpIwc+bMXCv7vZmsGBsrj8Zt2rQJX375JX755Re0bNkSpqammDdvHi5cuAAA+cYJAA8fPkTXrl0xZswYzJ49G1ZWVjh79iyGDRuGjIwMRXJXUNbW1oiNjc1135ufD4lEkmebTCYDAFy8eBFZWVlo1aoVAMDU1BRXr17FyZMncfjwYUyfPh0zZszApUuX3lkWPyYmBtWrVy/UeyIiInpt3T/rMGjXIMiEDEMbDsWf3f+EloRT+YlUpVKSdfjw4XeuLVSlShVMmzYNX375JcLDw9USXGkjkUgK9MieJmRlZWHNmjX45Zdf0LlzZ6V9fn5+2LhxI0aPHo369evj2LFjGDJkSI5zuLu7QyqVIjo6Gh988IFK123UqBFCQ0Ph4uJSoHiDgoLQqlUrfPrpp4q2Nx/RMzU1hbOzM44dO4YOHTrkOP7KlSuQyWT45ZdfFFUAX48Yvebq6oqgoKAc161Zs2auo1iA/HsQFRWF2NhYWFpaFug9vW337t3w9fVVupaOjg48PT3h6emJgIAAWFhY4Pjx4+8sP3/r1i1FkQwiIqLCWHNjDQbvGgwBgeHuw/FHtz+YYBEVkEpJVkEWb9XV1eVv0kuwvXv3IjY2FsOGDYO5ubnSvt69e2PFihUYPXo0AgIC4OHhgerVq6Nfv37IysrC/v378dVXX6FmzZoYMGAABg4ciF9++QXu7u54/vw5jh07hvr16+e67tb06dPRtWtXVK5cGX369IGWlhZu3LiBW7du5TuXqkaNGlizZg0OHTqEqlWrYu3atbh06RKqVq2q6DNjxgyMHj0atra28PHxQWJiIoKCgjB+/Hi4uLggMzMTv/32G7p164agoCAsW7ZM6RqTJk1C06ZNMWvWLPTt2xfBwcFYvHgxfv/99zzjcnd3h7W1NYKCgtC1a1dVv/25CgwMxPfff694vXfvXjx48ABt27aFpaUl9u/fD5lMhlq1auV7nocPH+Lp06fw9PR8r3iIiKj8WnVtFYYFDoOAwKjGo/C77+9MsIgKQ9VKGleuXBFTp05VVDT75ptvCl+WoxQpSHXB0qBr166iS5cuue67cOGCACBu3LghhBBi+/btomHDhkJPT09YW1uLXr16Kfq+rvrn7OwsdHV1hYODg+jZs6f4559/hBA5qwsKIcTBgwdFq1athKGhoTAzMxPNmjUTy5cvV+wHIHbu3Kl0TFpamhg8eLAwNzcXFhYWYsyYMWLq1KmiQYMGSv2WLVsmatWqJQAICwsLMX78eMW+X3/9VTg4OAhDQ0Ph5eUl1qxZIwCI2NhYRZ9t27YJNzc3oaurKypXrizmzZv3zu/llClTRL9+/ZTa3n4PYWFhAoC4du2aou3EiROK69+7d0/o6+uLpKQkxf4zZ86Idu3aCUtLS2FoaCjq16+vVE0xL3PmzBFeXl759imNf2eJiKh4/HXlLyGZIRGYATFm7xghlUnffRBROaP26oJNmjRBz549ceTIEezevRs+Pj44d+5cEaV+JUdBqguS5m3cuBG3b99WVPcrSlFRUahTpw6uXr2KKlWqFOocv/76K44ePYr9+/e/VywZGRmoUaMGNmzYgNatW+fZj39niYgoN8uvLMeovaMAAOOajsMin0WKOcRElE3V6oIqj/8aGBjgm2++wbx58zBs2DComJsRFZt///0XQggEBgYWy/Xs7e2xYsWK95qDWKlSJaWy9oUVHh6Or7/+Ot8Ei4iIKDe/X/pdkWB93vxzJlhEaqDyUt2vq7g1bdoUPj4+GDNmTJEFRVQYPXr0QEREBL799ttiu6afn997He/v76+WOFxcXApcVISIiGjxxcUYf2A8AGBii4n4ufPPTLCI1EDlJOuHH35AVlYWdHR0MGzYsDzXQyLSlHv37mk6BCIiolJj4fmFmHBoAgBgcqvJ+NHzRyZYRGqi8uOCzZs3h45Odk72+jf4CQkJ2LVrF0JCQtQeHBERERGp36/BvyoSrKmtpzLBIlKzAtfk9Pf3x+LFiwEAqampaNKkCfz9/VG/fn1s375d7QESERERkfrMC5qHSYcnAQC++eAbzPGYwwSLSM0KnGSdPn1asQDtzp07IYRAXFwcFi1alO96R2UZi4BQacG/q0RE5dv/zv4PU45OAQBMbzsdszrMYoJFVAQKnGTFx8fDysoKAHDw4EH07t0bRkZG8PX1xd27d9UeYEmmq6sLAEhJSdFwJESqef139fXfXSIiKj9mn56NacfkFW1ntp+JmR1mMsEiKiIqF754zcnJCcHBwbCyssLBgwexadMmAEBsbGy5W3dHW1sbFhYWiI6OBgAYGRnxHysqkYQQSElJQXR0NCwsLKCtra3pkIiIqBh9f+p7BJwMAAD80OEHfNP2Gw1HRFS2FTjJmjBhAgYMGAATExNUqVIF7du3ByB/jLBevXrqjq/Es7e3BwBFokVUkllYWCj+zhIRUdknhMDMUzMx89RMAMBcj7mY2maqhqMiKvskohCTNC5fvozHjx+jU6dOMDExAQDs27cPFhYWZW4xVFVXdZZKpcjMzCzGyIgKRldXlyNYRETliBAC009Mxw9n5HPmf/L8CZNbT9ZwVESlm6q5gcpJ1gcffIAePXqgR48eqFGjhtoCLelU/UYSERERlRRCCHx97Gv8L+h/AIBfOv+CiS0najgqotJP1dxA5cIXI0aMQHBwMBo1agRXV1d89dVXCAoKYrUyIiIiohJECIGvjn6lSLDme81ngkVUzAr8uGB6ejqOHTuG3bt3Y8+ePZBKpfD19UX37t3h5eUFQ0PDoopVIziSRURERKWFEAJfHv4Sv57/FQCwyHsRxjcfr+GoiMoOtY9kvaavr48uXbrgjz/+QEREBAIDA+Hg4IDvvvsOFSpUQNeuXREUFPRewRMRERFRwQgh8MWhLxQJ1pIuS5hgEWlIoQpf5OX+/fsIDAyEk5MT+vTpo67TahRHsoiIiKikE0Lg84Of47eLvwEAlvkuw6gmozQcFVHZo/bCF7lJSkqCTCZTaitriQiTLCIiIirJZEKG8fvH4/fLv0MCCZZ3W47hjYZrOiyiMqnIHhcMCwuDr68vjI2NYW5uDktLS1haWsLCwgKWlpbvFTQRERERqU4mZPh036eKBGtF9xVMsIhKgAIvRvzxxx9DCIGVK1fCzs4OEomkKOIiIiIionzIhAyj9ozCX9f+ggQSrOqxCoMaDtJ0WESEQiRZN27cwJUrV1CrVq2iiIeIiIiI3kEqk2LEnhFYdX0VtCRa+Nvvb3xc/2NNh0VErxT4ccGmTZvi8ePHRRFLvmJiYjBgwACYmZnBwsICw4YNQ1JSUr7HLF++HO3bt4eZmRkkEgni4uKKJ1giIiKiIiKVSTE0cKgiwVrbcy0TLKISpsAjWX/99RdGjx6Np0+fom7dutDV1VXaX79+fbUF96YBAwYgMjISR44cQWZmJoYMGYKRI0diw4YNeR6TkpICb29veHt7Y9q0aUUSFxEREVFxkcqkGLx7MNb9sw7aEm2s77Uefev21XRYRPSWAlcXPH/+PD766CM8fPgw+yQSCYQQkEgkkEql6o4RISEhcHNzw6VLl9CkSRMAwMGDB9GlSxc8efIEjo6O+R5/8uRJdOjQAbGxsbCwsCjQtVldkIiIiEqCLFkWBu4ciI23NkJboo2NvTfiwzofajosonJF1dygwCNZQ4cOhbu7OzZu3FhshS+Cg4NhYWGhSLAAwNPTE1paWrhw4QJ69uxZ5DEQERERaUqmNBMf7fgI225vg46WDjb32Yxerr00HRYR5aHASdajR48QGBgIFxeXoognV1FRUbC1tVVq09HRgZWVFaKiotR6rfT0dKSnpyteJyQkqPX8RERERAWRnpWOvtv6Ynfobuhp62Hrh1vRvVZ3TYdFRPkocOGLjh074saNG2q5+NSpUyGRSPLd7ty5o5ZrqWru3LkwNzdXbE5OTsV6fSIiIqLX0rLS0GtLL+wO3Q19bX3s6ruLCRZRKVDgkaxu3brhiy++wM2bN1GvXr0chS+6d1f9gz9p0iQMHjw43z7VqlWDvb09oqOjldqzsrIQExMDe3t7la+nimnTpmHixImK1wkJCUy0iIiIqNilZKbAb5Mfjjw4AkMdQwT2D4RnNU9Nh0VEKihwkjV69GgAwPfff59jX0ELX9jY2MDGxuad/Vq2bIm4uDhcuXIFjRs3BgAcP34cMpkMzZs3V/l6qtDX14e+vr5az0lERERUEEkZSei2sRtOPjwJY11j7PtoH9o5t9N0WESkogI/LiiTyfLciqKyIAC4urrC29sbI0aMwMWLFxEUFIRx48ahX79+isqCT58+Re3atXHx4kXFcVFRUbh+/Tru3bsHALh58yauX7+OmJiYIomTiIiI6H0lpCfAZ70PTj48CVM9Uxz6+BATLKJSpsBJlqasX78etWvXhoeHB7p06YI2bdpg+fLliv2ZmZkIDQ1FSkqKom3ZsmVwd3fHiBEjAABt27aFu7s7AgMDiz1+IiIioneJS4uD1zovnA0/C3N9cxz55AhaV26t6bCIqIBUWidr06ZN6Nevn0onfPz4McLDw9G6ddn4B4HrZBEREVFxiEmNQee1nXEl8gosDSxx5JMjaOzYWNNhEdEbVM0NVBrJWrp0KVxdXfHTTz8hJCQkx/74+Hjs378fH330ERo1aoSXL18WPnIiIiKicuZFygt0/LsjrkRegbWRNU4MOsEEi6gUU6nwxalTpxAYGIjffvsN06ZNg7GxMezs7GBgYIDY2FhERUXB2toagwcPxq1bt2BnZ1fUcRMRERGVCc+SnsFzrSduRd+CnbEdjg08hjq2dTQdFhG9B5UeF3zTixcvcPbsWTx69AipqamwtraGu7s73N3doaVVaqZ4qYyPCxIREVFRiUiMgMcaD9x5cQcOJg44Pug4alvX1nRYRJQHVXODApdwt7a2hp+f3/vERkRERFTuPY5/jI5rOuJezD04mTnh+KDjcLFy0XRYRKQGBU6yiIiIiOj9PIx7iI5/d0RYXBicLZxxfOBxVLWsqumwiEhNmGQRERERFaP7MffRcU1HhMeHo7pldRwfdByVzStrOiwiUiMmWURERETFJPRFKDzWeOBp4lPUqlALxwYeQ0WzipoOi4jUjEkWERERUTG4/fw2PNZ4ICopCm42bjg28BjsTew1HRYRFYH3SrJeFyaUSCRqCYaIiIioLLr57CY81njgecpz1Lerj6OfHIWNsY2mwyKiIlKomutr1qxBvXr1YGhoCENDQ9SvXx9r165Vd2xEREREpd61yGvo8HcHPE95jkYOjXB84HEmWERlXIFHsn799Vd89913GDduHFq3bg0AOHv2LEaPHo0XL17giy++UHuQRERERKXRpaeX0HldZ8SlxaFZxWY49PEhWBhYaDosIipiBV6MuGrVqpg5cyYGDhyo1P73339jxowZCAsLU2uAmsbFiImIiKgwzjw6A98NvkjMSEQrp1Y4MOAAzPT5fwmi0kzV3KDAjwtGRkaiVatWOdpbtWqFyMjIgp6OiIiIqMw5+uAovNZ5ITEjER2cO+DQx4eYYBGVIwVOslxcXLBly5Yc7Zs3b0aNGjXUEhQRERFRabX3v73ouqErUrNS4e3ijX0f7YOJnommwyKiYlTgOVkzZ85E3759cfr0acWcrKCgIBw7dizX5IuIiIiovNj671Z8tOMjZMmy0LN2T2zsvRH6OvqaDouIilmBR7J69+6NCxcuwNraGrt27cKuXbtgbW2NixcvomfPnkURIxEREVGJt/bGWvTb3g9Zsiz0r9sfm/tsZoJFVE4VuPBFecPCF0RERPQuy68sx+i9oyEgMMx9GP7o+ge0tbQ1HRYRqZmqucF7LUaclpaGjIwMpTYmIkRERFSeLDi/AF8cki9hM77ZeCzwXgAtSaGWIiWiMqLA/wKkpKRg3LhxsLW1hbGxMSwtLZU2IiIiovJi9unZigTrq9ZfYaH3QiZYRKRakuXm5obp06cDACZPnozjx49j6dKl0NfXx19//YWZM2fC0dERa9asKdJgiYiIiEoCIQS+OfYNvj3xLQBgZvuZmOsxFxKJRMOREVFJoNKcrMjISLRv3x6hoaGoXLky1qxZg/bt28PMzAxXr16Fi4sL1q5di40bN2L//v3FEXex4ZwsIiIiepMQAhMPTcSCCwsAAPM6zcOXrb7UbFBEVCzUuhixv78/vv1W/puamJgYVKtWDYB8/lVMTAwAoE2bNjh9+vT7xk1ERERUYsmEDGP2jVEkWEu6LGGCRUQ5qJRkPX/+HMHBwQCAatWqISwsDABQu3ZtxdpYe/bsgYWFRdFESURERKRhWbIsDN41GH9c+QNaEi2s7L4Snzb9VNNhEVEJpFJ1wQsXLuDcuXMAgCFDhuDGjRto164dpk6dim7dumHx4sXIzMzEr7/+WqTBEhEREWlChjQDA3YMwLbb26At0ca6XuvQr24/TYdFRCXUe6+T9ejRI1y5cgUuLi6oX7++uuIqMTgni4iIqHxLy0pDny19sO/uPuhp62FLny3oUbuHpsMiIg0olnWyAKBKlSqoUqXK+56GiIiIqMRJzkiG32Y/HH1wFAY6BtjVdxe8XLw0HRYRlXAFXsjhs88+w6JFi3K0L168GBMmTFBHTEREREQal5CeAO/13jj64CiMdY1xYMABJlhEpJICJ1nbt29H69atc7S3bt0aa9euRUBAANzd3fHjjz+qJUAiIiKi4haTGgPPNZ44G34W5vrmODrwKNo7t9d0WERUShQ4yXr58iXMzc1ztJuamiI2NhZubm6YPHkyZs2apZYAiYiIiIpTZGIk2q1uh0sRl1DBsAKODzqOFpVaaDosIipFCpxkubi44ODBgznaDxw4gNq1a6Nv375o2LAhHBwc1BIgERERUXF5GPcQH6z6ALeib8HBxAGnh5xGI4dGmg6LiEqZAidZEydOxJQpUxAQEIBTp07h1KlTmD59OqZOnYovvvgCAODm5oa7d++qNdCYmBgMGDAAZmZmsLCwwLBhw5CUlJRv//Hjx6NWrVowNDRE5cqV8dlnnyE+Pl6tcREREVHZcOfFHbRZ2Qb3Y++jqkVVnB16Fm42bpoOi4hKoQJXFxw6dCjS09Mxe/ZsxSOBzs7OWLp0KQYOHKj2AF8bMGAAIiMjceTIEWRmZmLIkCEYOXIkNmzYkGv/iIgIRERE4Oeff4abmxsePXqE0aNHIyIiAtu2bSuyOImIiKj0uRp5FV7rvPAi5QXcbNxw+OPDqGhWUdNhEVEp9V7rZD1//hyGhoYwMTFRZ0w5hISEwM3NDZcuXUKTJk0AAAcPHkSXLl3w5MkTODo6qnSerVu34uOPP0ZycjJ0dFTLL7lOFhERUdl2NvwsfDf4IiE9AY0dGuPgxwdhbWSt6bCIqARSNTco8OOCb7KxsSnyBAsAgoODYWFhoUiwAMDT0xNaWlq4cOGCyud5/c3IL8FKT09HQkKC0kZERERl06F7h9B5bWckpCegbZW2OD7oOBMsInpvhVqMeNu2bdiyZQvCw8ORkZGhtO/q1atqCexNUVFRsLW1VWrT0dGBlZUVoqKiVDrHixcvMGvWLIwcOTLffnPnzsXMmTMLHSsRERGVDttvb0f/7f2RKcuEj4sPtvlvg5GukabDIqIyoMAjWYsWLcKQIUNgZ2eHa9euoVmzZqhQoQIePHgAHx+fAp1r6tSpkEgk+W537twpaIg5JCQkwNfXF25ubpgxY0a+fadNm4b4+HjF9vjx4/e+PhEREZUsf1//G/7b/JEpy8SHbh9iV79dTLCISG0KPJL1+++/Y/ny5ejfvz9Wr16NKVOmoFq1apg+fTpiYmIKdK5JkyZh8ODB+fapVq0a7O3tER0drdSelZWFmJgY2Nvb53t8YmIivL29YWpqip07d0JXVzff/vr6+tDX11cpfiIiIip9frvwGz47+BkAYJj7MPzR9Q9oa2lrOCoiKksKnGSFh4ejVatWAABDQ0MkJiYCAD755BO0aNECixcvVvlcNjY2sLGxeWe/li1bIi4uDleuXEHjxo0BAMePH4dMJkPz5s3zPC4hIQFeXl7Q19dHYGAgDAwMVI6NiIiIyhYhBGafmY3vTnwHAPiixRf4pfMvkEgkGo6MiMqaAj8uaG9vrxixqly5Ms6fPw8ACAsLw3sUKsyXq6srvL29MWLECFy8eBFBQUEYN24c+vXrp6gs+PTpU9SuXRsXL14EIE+wOnfujOTkZKxYsQIJCQmIiopCVFQUpFJpkcRJREREJZMQAlOOTFEkWDPazWCCRURFpsAjWR07dkRgYCDc3d0xZMgQfPHFF9i2bRsuX76MXr16FUWMAID169dj3Lhx8PDwgJaWFnr37o1FixYp9mdmZiI0NBQpKSkA5AU4XlcedHFxUTpXWFgYnJ2diyxWIiIiKjmkMik+3fcpll9dDgCY7zUfE1pM0GxQRFSmFXidLJlMBplMpiiDvmnTJpw7dw41atTAqFGjoKenVySBagrXySIiIiq9MqWZGLhrIDbd2gQtiRb+7PYnhroP1XRYRFRKqZobFCjJysrKwpw5czB06FBUqlRJLYGWdEyyiIiISqfUzFT4b/PH3v/2QldLF+t7rceHdT7UdFhEVIoVyWLEOjo6+Omnn5CVlfXeARIREREVlfi0ePis98He//bCQMcAu/vtZoJFRMWmwIUvPDw8cOrUqaKIhYiIiOi9PUt6hvZ/t8epR6dgpm+GQx8fgk+Ngq3lSUT0Pgpc+MLHxwdTp07FzZs30bhxYxgbGyvt7969u9qCIyIiIiqIh3EP0WltJ9yLuQdbY1scHHAQ7g7umg6LiMqZAhe+0NLKe/BLIpGUufLonJNFRERUOtyKvgWvdV6ISIyAs4UzDn98GDUq1NB0WERUhqiaGxR4JEsmk71XYERERETqFvw4GL4bfBGbFou6tnVx6ONDcDR11HRYRFROFXhO1pvS0tLUFQcRERFRoRy8dxCeaz0RmxaLlpVa4tTgU0ywiEijCpxkSaVSzJo1CxUrVoSJiQkePHgAAPjuu++wYsUKtQdIRERElJeNNzei28ZuSMlMgbeLN458cgRWhlaaDouIyrkCJ1mzZ8/G6tWr8dNPPyktPFy3bl389ddfag2OiIiIKC9LLi7BgB0DkCXLQv+6/bG7324Y6xm/+0AioiJW4CRrzZo1WL58OQYMGABtbW1Fe4MGDXDnzh21BkdERET0NiEEZp6ciXEHxkFAYFzTcVjXax30tPXefTARUTEocOGLp0+fwsXFJUe7TCZDZmamWoIiIiIiyo1MyPD5gc+x+NJiAMCMdjMwvd10SCQSDUdGRJStwCNZbm5uOHPmTI72bdu2wd2d61AQERFR0ciQZuDjHR9j8aXFkECCxT6LEdA+gAkWEZU4BR7Jmj59OgYNGoSnT59CJpNhx44dCA0NxZo1a7B3796iiJGIiIjKueSMZPTZ2gcH7x2EjpYO1vitQf96/TUdFhFRrgo8ktWjRw/s2bMHR48ehbGxMaZPn46QkBDs2bMHnTp1KooYiYiIqByLSY1Bp7WdcPDeQRjqGGJP/z1MsIioRJMIIYSmgyjJVF3VmYiIiNQvIjECXuu8cCv6FiwNLLHvo31o6dRS02ERUTmlam5Q4McFiYiIiIrDfy//g9c6LzyMewgHEwcc/uQw6trW1XRYRETvpFKSZWlpqfKk0piYmPcKiIiIiOjCkwvw3eCLl6kv4WLlgsMfH0ZVy6qaDouISCUqJVkLFiwo4jCIiIiI5Pbf3Y8Pt36IlMwUNHVsir0f7YWtsa2mwyIiUplKSdagQYOKOg4iIiIirL6+GsMDh0MqpPB28cbWD7fCRM9E02ERERVIgasLAsD9+/fx7bffon///oiOjgYAHDhwAP/++69agyMiIqLyQQiBuWfmYsjuIZAKKQY2GIjAfoFMsIioVCpwknXq1CnUq1cPFy5cwI4dO5CUlAQAuHHjBgICAtQeIBEREZVtUpkUnx34DF8f/xoAMLX1VKzusRq62roajoyIqHAKnGRNnToVP/zwA44cOQI9PT1Fe8eOHXH+/Hm1BkdERERlW1pWGvpt74fFlxZDAgkWei/EXM+5KhfcIiIqiQpcwv3mzZvYsGFDjnZbW1u8ePFCLUERERFR2RefFg+/zX44+fAk9LT1sMZvDfrW7avpsIiI3luBR7IsLCwQGRmZo/3atWuoWLGiWoIiIiKisi0iMQJtV7fFyYcnYapnigMDDjDBIqIyo8BJVr9+/fDVV18hKioKEokEMpkMQUFB+PLLLzFw4MCiiJGIiIjKkDsv7qDlipb459k/sDexx+khp9GxakdNh0VEpDYFTrLmzJmD2rVrw8nJCUlJSXBzc0Pbtm3RqlUrfPvtt0URIxEREZUR55+cR+uVrREeH46aFWoieFgwGto31HRYRERqJRFCiMIc+PjxY9y8eRNJSUlwd3dHjRo11B1biZCQkABzc3PEx8fDzMxM0+EQERGVWnv/2wv/rf5IzUpFs4rNsO+jfbA2stZ0WEREKlM1Nyhw4YvXnJyc4OTkVNjDiYiIqBxZfmU5Pt33KaRCii41umBLny0w1jPWdFhEREWiwI8L9u7dGz/++GOO9p9++gkffvihWoIiIiKiskEIgW+OfYNRe0dBKqQY0nAIdvXdxQSLiMq0AidZp0+fRpcuXXK0+/j44PTp02oJioiIiEq/DGkGPtn5CeacnQMAmNFuBlZ0X8FFhomozCtwkpWUlKS0CPFrurq6SEhIUEtQuYmJicGAAQNgZmYGCwsLDBs2DElJSfkeM2rUKFSvXh2GhoawsbFBjx49cOfOnSKLkYiIiOTi0uLgvc4b62+uh46WDlb1WIWA9gFcZJiIyoUCJ1n16tXD5s2bc7Rv2rQJbm5uagkqNwMGDMC///6LI0eOYO/evTh9+jRGjhyZ7zGNGzfGqlWrEBISgkOHDkEIgc6dO0MqlRZZnEREROVdeHw42qxsgxMPT8BUzxT7P9qPwQ0HazosIqJiU+Dqgnv27EGvXr3w0UcfoWNH+ZoWx44dw8aNG7F1fwZT7AAAFDVJREFU61b4+fmpPciQkBC4ubnh0qVLaNKkCQDg4MGD6NKlC548eQJHR0eVzvPPP/+gQYMGuHfvHqpXr67SMawuSEREpLprkdfgu8EXkUmRqGhaEfsH7Ed9u/qaDouISC1UzQ0KPJLVrVs37Nq1C/fu3cOnn36KSZMm4cmTJzh69GiRJFgAEBwcDAsLC0WCBQCenp7Q0tLChQsXVDpHcnIyVq1ahapVq+ZbFTE9PR0JCQlKGxEREb3bwXsH0XZ1W0QmRaKebT2cH36eCRYRlUsFTrIAwNfXF0FBQUhOTsaLFy9w/PhxtGvXDrdu3VJ3fACAqKgo2NraKrXp6OjAysoKUVFR+R77+++/w8TEBCYmJjhw4ACOHDmS65yy1+bOnQtzc3PFxjL1RERE77bi6gp03dAVSRlJ8KjqgTNDzqCSWSVNh0VEpBGFSrLelJiYiOXLl6NZs2Zo0KBBgY6dOnUqJBJJvtv7FqoYMGAArl27hlOnTqFmzZrw9/dHWlpanv2nTZuG+Ph4xfb48eP3uj4REVFZJoTA9BPTMXzPcEiFFAMbDMT+AfthbmCu6dCIiDSm0IsRnz59Gn/99Rd27NgBR0dH9OrVC0uWLCnQOSZNmoTBgwfn26datWqwt7dHdHS0UntWVhZiYmJgb2+f7/GvR6Rq1KiBFi1awNLSEjt37kT//v1z7a+vrw99ff0CvQ8iIqLyKEOageGBw7H2n7UAgOltp2NG+xmsIEhE5V6BkqyoqCisXr0aK1asQEJCAvz9/ZGeno5du3YVqrKgjY0NbGxs3tmvZcuWiIuLw5UrV9C4cWMAwPHjxyGTydC8eXOVryeEgBAC6enpBY6ViIiIssWnxaP3lt44FnYM2hJtLO+2HEPdh2o6LCKiEkHlxwW7deuGWrVq4Z9//sGCBQsQERGB3377rShjU3B1dYW3tzdGjBiBixcvIigoCOPGjUO/fv0UlQWfPn2K2rVr4+LFiwCABw8eYO7cubhy5QrCw8Nx7tw5fPjhhzA0NMx1MWUiIiJSzeP4x2izqg2OhR2DiZ4J9n20jwkWEdEbVB7JOnDgAD777DOMGTMGNWrUKMqYcrV+/XqMGzcOHh4e0NLSQu/evbFo0SLF/szMTISGhiIlJQUAYGBggDNnzmDBggWIjY2FnZ0d2rZti3PnzuUookFERESqufT0Erpv6o6opCg4mDhg/4D9aGjfUNNhERGVKConWWfPnsWKFSvQuHFjuLq64pNPPkG/fv2KMjYlVlZW2LBhQ577nZ2d8eaSX46Ojti/f39xhEZERFQu7AjZgY93fIzUrFTUs62HvR/tRWXzypoOi4ioxFH5ccEWLVrgzz//RGRkJEaNGoVNmzbB0dERMpkMR44cQWJiYlHGSURERBoihMBPQT+h95beSM1KRZcaXRA0NIgJFhFRHiTizeGfAgoNDcWKFSuwdu1axMXFoVOnTggMDFRnfBqn6qrOREREZVGGNAOf7vsUK66tAACMbzYev3r9Ch2tQhcoJiIqtVTNDd5rnaxatWrhp59+wpMnT7Bx48b3ORURERGVMLGpsfBe540V11ZAS6KF33x+wyKfRUywiIje4b1GssoDjmQREVF5dD/mPnw3+CL0ZShM9Eywuc9mdKnB6rxEVL6pmhvwV1FERESk5Gz4Wfht8sPL1JdwMnPC3o/2or5dfU2HRURUarzX44JERERUtqz7Zx081njgZepLNHVsigvDLzDBIiIqICZZREREBCEEAk4E4JOdnyBDmoHerr1xcvBJOJg6aDo0IqJSh48LEhERlXNpWWkYunsoNt6SF7H6qvVXmOMxB1oS/i6WiKgwmGQRERGVY08SnqDvtr449/gcdLR08EfXPzDUfaimwyIiKtWYZJUi+/7bh3RpuqbDICKiMkAIgZMPT2L51eXIkGbAwsACO/x3oEPVDpoOjYio1GOSVYoMDRyK6ORoTYdBRERlzAeVP8DybstR27q2pkMhIioTmGSVIs0qNkNsaqymwyAiojLC2sganzX/DB2cO0AikWg6HCKiMoNJVimyp/8eTYdARERERETvwLJBREREREREasQki4iIiIiISI2YZBEREREREakRkywiIiIiIiI1YuGLdxBCAAASEhI0HAkREREREWnS65zgdY6QFyZZ75CYmAgAcHJy0nAkRERERERUEiQmJsLc3DzP/RLxrjSsnJPJZIiIiICpqanG1xBJSEiAk5MTHj9+DDMzM43GQqrjfSudeN9KJ9630on3rfTivSudeN8KTwiBxMREODo6Qksr75lXHMl6By0tLVSqVEnTYSgxMzPjB6IU4n0rnXjfSifet9KJ96304r0rnXjfCie/EazXWPiCiIiIiIhIjZhkERERERERqRGTrFJEX18fAQEB0NfX13QoVAC8b6UT71vpxPtWOvG+lV68d6UT71vRY+ELIiIiIiIiNeJIFhERERERkRoxySIiIiIiIlIjJllERERERERqxCSLiIiIiIhIjZhklTBLliyBs7MzDAwM0Lx5c1y8eDHf/lu3bkXt2rVhYGCAevXqYf/+/cUUKb2pIPdt9erVkEgkSpuBgUExRksAcPr0aXTr1g2Ojo6QSCTYtWvXO485efIkGjVqBH19fbi4uGD16tVFHicpK+h9O3nyZI7Pm0QiQVRUVPEETACAuXPnomnTpjA1NYWtrS38/PwQGhr6zuP4M06zCnPf+DNO85YuXYr69esrFhpu2bIlDhw4kO8x/KypH5OsEmTz5s2YOHEiAgICcPXqVTRo0ABeXl6Ijo7Otf+5c+fQv39/DBs2DNeuXYOfnx/8/Pxw69atYo68fCvofQPkK6xHRkYqtkePHhVjxAQAycnJaNCgAZYsWaJS/7CwMPj6+qJDhw64fv06JkyYgOHDh+PQoUNFHCm9qaD37bXQ0FClz5ytrW0RRUi5OXXqFMaOHYvz58/jyJEjyMzMROfOnZGcnJznMfwZp3mFuW8Af8ZpWqVKlfC///0PV65cweXLl9GxY0f06NED//77b679+VkrIoJKjGbNmomxY8cqXkulUuHo6Cjmzp2ba39/f3/h6+ur1Na8eXMxatSoIo2TlBX0vq1atUqYm5sXU3SkCgBi586d+faZMmWKqFOnjlJb3759hZeXVxFGRvlR5b6dOHFCABCxsbHFEhOpJjo6WgAQp06dyrMPf8aVPKrcN/6MK5ksLS3FX3/9les+ftaKBkeySoiMjAxcuXIFnp6eijYtLS14enoiODg412OCg4OV+gOAl5dXnv1J/Qpz3wAgKSkJVapUgZOTU76/XaKSg5+30q1hw4ZwcHBAp06dEBQUpOlwyr34+HgAgJWVVZ59+JkreVS5bwB/xpUkUqkUmzZtQnJyMlq2bJlrH37WigaTrBLixYsXkEqlsLOzU2q3s7PLc+5AVFRUgfqT+hXmvtWqVQsrV67E7t27sW7dOshkMrRq1QpPnjwpjpCpkPL6vCUkJCA1NVVDUdG7ODg4YNmyZdi+fTu2b98OJycntG/fHlevXtV0aOWWTCbDhAkT0Lp1a9StWzfPfvwZV7Koet/4M65kuHnzJkxMTKCvr4//t3f/MVVXfxzHX1fgdrmXH0kSZApDUQJmyCQW9sM2LKStreXWso1hAgWDkFW3UWsQuVZZSc7MOVfRWmWs0rVsoaKSubFRQUGXWYJAtbQ20aEwMDjfP77r891V0C964UI8H9tnu/d83ufs/blnZ5+9OdzPLSws1K5du5SUlDRqLGttYgT6OwFgpsnIyPD6a9Ly5cuVmJio7du3a8OGDX7MDPj3SUhIUEJCgvV++fLl6ujoUHV1td5//30/ZjZzFRcXq62tTd98842/U8E4/L/zxj1uakhISFBLS4vOnDmjTz75RLm5uWpoaBiz0ILvsZM1RcyZM0cBAQE6efKkV/vJkycVHR09ap/o6OhxxcP3rmTeLhQUFKTU1FQdO3ZsIlKEj4y13sLCwhQcHOynrHAl0tPTWW9+UlJSoi+++EIHDx7UvHnzLhnLPW7qGM+8XYh7nH/Y7XbFx8dr2bJleumll5SSkqLNmzePGstamxgUWVOE3W7XsmXLVF9fb7WNjIyovr5+zP+hzcjI8IqXpH379o0ZD9+7knm70PDwsFpbW3XDDTdMVJrwAdbbv0dLSwvrbZIZY1RSUqJdu3bpwIEDiouLu2wf1pz/Xcm8XYh73NQwMjKiwcHBUc+x1iaIv5+8gf/ZuXOnueaaa0xNTY3xeDzm0UcfNddee605ceKEMcaYnJwcU15ebsUfOXLEBAYGmtdee820t7ebyspKExQUZFpbW/11CTPSeOetqqrK1NXVmY6ODvPdd9+Zhx56yDgcDvPTTz/56xJmpL6+PtPc3Gyam5uNJLNp0ybT3Nxsuru7jTHGlJeXm5ycHCu+s7PTOJ1O43a7TXt7u9m6dasJCAgwX331lb8uYUYa77xVV1eb3bt3m19++cW0traa9evXm1mzZpn9+/f76xJmpKKiIhMeHm4OHTpk/vjjD+vo7++3YrjHTT1XMm/c4/yvvLzcNDQ0mOPHj5sff/zRlJeXG5vNZvbu3WuMYa1NFoqsKWbLli0mJibG2O12k56ebhobG61zK1asMLm5uV7xtbW1ZvHixcZut5vk5GSzZ8+eSc4Yxoxv3srKyqzYqKgoc++995rvv//eD1nPbP882vvC45+5ys3NNStWrLioz9KlS43dbjcLFiww77777qTnPdONd95eeeUVs3DhQuNwOExERIS56667zIEDB/yT/Aw22pxJ8lpD3OOmniuZN+5x/rdu3ToTGxtr7Ha7iYyMNJmZmVaBZQxrbbLYjDFm8vbNAAAAAODfje9kAQAAAIAPUWQBAAAAgA9RZAEAAACAD1FkAQAAAIAPUWQBAAAAgA9RZAEAAACAD1FkAQAAAIAPUWQBADCJjh49qujoaPX19V021uPxaN68eTp37twkZAYA8BWKLADAlGaz2S55PP/88/5OcVyeeeYZPf744woNDb1sbFJSkm699VZt2rRpEjIDAPiKzRhj/J0EAABjOXHihPX6448/VkVFhY4ePWq1hYSEKCQkxB+pjVtPT4/i4+N1/Phx3Xjjjf9Xnz179qigoEA9PT0KDAyc4AwBAL7AThYAYEqLjo62jvDwcNlsNq+2nTt3KjExUQ6HQzfddJPeeustq29XV5dsNptqa2t1xx13KDg4WLfccot+/vlnNTU1KS0tTSEhIcrOztZff/1l9Vu7dq3uv/9+VVVVKTIyUmFhYSosLNTQ0JAVMzg4qNLSUl1//fVyOBy6/fbb1dTUdMlrqa2tVUpKileB1d3drfvuu0+zZ8+Wy+VScnKyvvzyS+v83XffrVOnTqmhocEXHycAYBLwJzEAwLT1wQcfqKKiQm+++aZSU1PV3NysgoICuVwu5ebmWnGVlZV64403FBMTo3Xr1unhhx9WaGioNm/eLKfTqQcffFAVFRXatm2b1ae+vl4Oh0OHDh1SV1eXHnnkEV133XV68cUXJUlPP/20Pv30U7333nuKjY3Vxo0blZWVpWPHjikiImLUfA8fPqy0tDSvtuLiYg0NDenrr7+Wy+WSx+Px2pmz2+1aunSpDh8+rMzMTF9+fACACUKRBQCYtiorK/X666/rgQcekCTFxcXJ4/Fo+/btXkXWU089paysLEnS+vXrtWbNGtXX1+u2226TJOXl5ammpsZrbLvdrnfeeUdOp1PJycl64YUX5Ha7tWHDBg0MDGjbtm2qqalRdna2JGnHjh3at2+f3n77bbnd7lHz7e7uvqjI6unp0erVq7VkyRJJ0oIFCy7qN3fuXHV3d1/BJwQA8AeKLADAtHTu3Dl1dHQoLy9PBQUFVvvff/+t8PBwr9ibb77Zeh0VFSVJVlHzT9uff/7p1SclJUVOp9N6n5GRobNnz+rXX3/VmTNndP78eatIk6SgoCClp6ervb19zJwHBgbkcDi82kpLS1VUVKS9e/dq5cqVWr16tVe+khQcHKz+/v4xxwUATC18JwsAMC2dPXtW0n93kFpaWqyjra1NjY2NXrFBQUHWa5vNNmrbyMjIhOc8Z84c9fb2erXl5+ers7NTOTk5am1tVVpamrZs2eIVc+rUKUVGRk54fgAA36DIAgBMS1FRUZo7d646OzsVHx/vdcTFxV31+D/88IMGBgas942NjQoJCdH8+fO1cOFC2e12HTlyxDp//vx5NTU1KSkpacwxU1NT5fF4LmqfP3++CgsL9dlnn+nJJ5/Ujh07vM63tbUpNTX1qq8JADA5+HdBAMC0VVVVpdLSUoWHh2vVqlUaHBzUt99+q97eXj3xxBNXNfbQ0JDy8vL03HPPqaurS5WVlSopKdGsWbPkcrlUVFQkt9utiIgIxcTEaOPGjerv71deXt6YY2ZlZSk/P1/Dw8MKCAiQJJWVlSk7O1uLFy9Wb2+vDh48qMTERKtPV1eXfv/9d61cufKqrgcAMHkosgAA01Z+fr6cTqdeffVVud1uuVwuLVmyRGVlZVc9dmZmphYtWqQ777xTg4ODWrNmjdcPH7/88ssaGRlRTk6O+vr6lJaWprq6Os2ePXvMMbOzsxUYGKj9+/dbD+IYHh5WcXGxfvvtN4WFhWnVqlWqrq62+nz00Ue65557FBsbe9XXBACYHPwYMQAAF1i7dq1Onz6t3bt3+3zsrVu36vPPP1ddXd1lY4eGhrRo0SJ9+OGHXg/ZAABMbexkAQAwiR577DGdPn1afX19Cg0NvWRsT0+Pnn32WQosAJhm2MkCAOACE7mTBQD496PIAgAAAAAf4hHuAAAAAOBDFFkAAAAA4EMUWQAAAADgQxRZAAAAAOBDFFkAAAAA4EMUWQAAAADgQxRZAAAAAOBDFFkAAAAA4EMUWQAAAADgQ/8BkDe+fRsmC+oAAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# @title Exportar para CSV\n",
        "\n",
        "nome_personalizado = \"nome da tabela csv\"  # @param {type:\"string\"}\n",
        "dados.to_csv(f\"{nome_personalizado}.csv\", index=False)\n"
      ],
      "metadata": {
        "id": "QP4I57_S8lLf",
        "cellView": "form"
      },
      "execution_count": 74,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# @title Salvar dados numa planilha Google.\n",
        "\n",
        "import numpy as np\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "from IPython.display import display\n",
        "from google.colab import auth\n",
        "auth.authenticate_user()\n",
        "import gspread\n",
        "from google.auth import default\n",
        "creds, _ = default()\n",
        "gc = gspread.authorize(creds)\n",
        "\n",
        "from google.colab import userdata\n",
        "\n",
        "\n",
        "# Salvar os dados em uma planilha Google\n",
        "planilha_id = userdata.get('planilha_id_secret')\n",
        "planilha = gc.open_by_key(planilha_id)\n",
        "\n",
        "worksheet = planilha.sheet1\n",
        "worksheet.clear()  # Limpa a planilha antes de inserir os dados\n",
        "worksheet.update([dados.columns.values.tolist()] + dados.values.tolist())"
      ],
      "metadata": {
        "id": "YndWpI06JsuG",
        "cellView": "form"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}