{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "source": [
        "from IPython.display import HTML\n",
        "\n",
        "HTML(\"\"\"\n",
        "<div style=\"\n",
        "background: linear-gradient(135deg,#020617,#0f172a,#1e3a8a);\n",
        "padding:50px;\n",
        "border-radius:30px;\n",
        "color:white;\n",
        "text-align:center;\n",
        "box-shadow:0px 10px 40px rgba(0,0,0,0.5);\n",
        "font-family:Arial,sans-serif;\n",
        "\">\n",
        "\n",
        "<h1 style=\"\n",
        "font-size:50px;\n",
        "margin-bottom:10px;\n",
        "color:#ffffff;\n",
        "text-shadow:0px 0px 20px #60A5FA;\n",
        "\">\n",
        "📊 MODELO GJR-GARCH(1,1)\n",
        "</h1>\n",
        "\n",
        "<h2 style=\"\n",
        "color:#93C5FD;\n",
        "font-size:32px;\n",
        "margin-top:0;\n",
        "\">\n",
        "Extensión del modelo GARCH\n",
        "</h2>\n",
        "\n",
        "<hr style=\"\n",
        "border:1px solid rgba(255,255,255,0.2);\n",
        "margin-top:25px;\n",
        "margin-bottom:25px;\n",
        "\">\n",
        "\n",
        "<h2 style=\"\n",
        "font-size:34px;\n",
        "color:#FBBF24;\n",
        "margin-bottom:10px;\n",
        "\">\n",
        "UNIVERSIDAD CENTRAL DEL ECUADOR\n",
        "</h2>\n",
        "\n",
        "<h3 style=\"\n",
        "font-size:28px;\n",
        "color:white;\n",
        "margin-bottom:5px;\n",
        "\">\n",
        "FACULTAD DE CIENCIAS ECONÓMICAS\n",
        "</h3>\n",
        "\n",
        "<h3 style=\"\n",
        "font-size:26px;\n",
        "color:white;\n",
        "margin-top:0;\n",
        "\">\n",
        "CARRERA DE ESTADÍSTICA\n",
        "</h3>\n",
        "\n",
        "<div style=\"\n",
        "background:rgba(255,255,255,0.08);\n",
        "padding:18px;\n",
        "border-radius:15px;\n",
        "margin-top:25px;\n",
        "\">\n",
        "\n",
        "<h2 style=\"\n",
        "color:#60A5FA;\n",
        "margin-bottom:5px;\n",
        "\">\n",
        "SERIES DE TIEMPO\n",
        "</h2>\n",
        "\n",
        "<h2 style=\"\n",
        "color:white;\n",
        "margin-top:10px;\n",
        "\">\n",
        "MODELO GJR-GARCH\n",
        "</h2>\n",
        "\n",
        "\n",
        "<h3 style=\"\n",
        "color:#E5E7EB;\n",
        "font-weight:normal;\n",
        "margin-top:15px;\n",
        "\">\n",
        "\n",
        "</h3>\n",
        "\n",
        "</div>\n",
        "\n",
        "<div style=\"\n",
        "margin-top:30px;\n",
        "padding:20px;\n",
        "background:rgba(255,255,255,0.05);\n",
        "border-radius:20px;\n",
        "\">\n",
        "\"Volatilidad asimétrica de los ingresos por exportaciones petroleras de las empresas públicas del Ecuador mediante un modelo GJR-GARCH\".\n",
        "<h2 style=\"\n",
        "color:#FBBF24;\n",
        "\">\n",
        "👥 INTEGRANTES\n",
        "</h2>\n",
        "\n",
        "<p style=\"\n",
        "font-size:24px;\n",
        "line-height:2;\n",
        "\">\n",
        "\n",
        "🔹 Melany Arboleda<br>\n",
        "🔹 Angie Hernández<br>\n",
        "🔹 Marley Mansilla<br>\n",
        "🔹 Bryan Moncayo\n",
        "\n",
        "</p>\n",
        "\n",
        "</div>\n",
        "\n",
        "</div>\n",
        "\"\"\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "0DUeToJMQfAN",
        "outputId": "adb8a792-6ceb-4d66-b69e-30a16d8c83d0"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "\n",
              "<div style=\"\n",
              "background: linear-gradient(135deg,#020617,#0f172a,#1e3a8a);\n",
              "padding:50px;\n",
              "border-radius:30px;\n",
              "color:white;\n",
              "text-align:center;\n",
              "box-shadow:0px 10px 40px rgba(0,0,0,0.5);\n",
              "font-family:Arial,sans-serif;\n",
              "\">\n",
              "\n",
              "<h1 style=\"\n",
              "font-size:50px;\n",
              "margin-bottom:10px;\n",
              "color:#ffffff;\n",
              "text-shadow:0px 0px 20px #60A5FA;\n",
              "\">\n",
              "📊 MODELO GJR-GARCH(1,1)\n",
              "</h1>\n",
              "\n",
              "<h2 style=\"\n",
              "color:#93C5FD;\n",
              "font-size:32px;\n",
              "margin-top:0;\n",
              "\">\n",
              "Extensión del modelo GARCH\n",
              "</h2>\n",
              "\n",
              "<hr style=\"\n",
              "border:1px solid rgba(255,255,255,0.2);\n",
              "margin-top:25px;\n",
              "margin-bottom:25px;\n",
              "\">\n",
              "\n",
              "<h2 style=\"\n",
              "font-size:34px;\n",
              "color:#FBBF24;\n",
              "margin-bottom:10px;\n",
              "\">\n",
              "UNIVERSIDAD CENTRAL DEL ECUADOR\n",
              "</h2>\n",
              "\n",
              "<h3 style=\"\n",
              "font-size:28px;\n",
              "color:white;\n",
              "margin-bottom:5px;\n",
              "\">\n",
              "FACULTAD DE CIENCIAS ECONÓMICAS\n",
              "</h3>\n",
              "\n",
              "<h3 style=\"\n",
              "font-size:26px;\n",
              "color:white;\n",
              "margin-top:0;\n",
              "\">\n",
              "CARRERA DE ESTADÍSTICA\n",
              "</h3>\n",
              "\n",
              "<div style=\"\n",
              "background:rgba(255,255,255,0.08);\n",
              "padding:18px;\n",
              "border-radius:15px;\n",
              "margin-top:25px;\n",
              "\">\n",
              "\n",
              "<h2 style=\"\n",
              "color:#60A5FA;\n",
              "margin-bottom:5px;\n",
              "\">\n",
              "SERIES DE TIEMPO\n",
              "</h2>\n",
              "\n",
              "<h2 style=\"\n",
              "color:white;\n",
              "margin-top:10px;\n",
              "\">\n",
              "MODELO GJR-GARCH\n",
              "</h2>\n",
              "\n",
              "\n",
              "<h3 style=\"\n",
              "color:#E5E7EB;\n",
              "font-weight:normal;\n",
              "margin-top:15px;\n",
              "\">\n",
              "\n",
              "</h3>\n",
              "\n",
              "</div>\n",
              "\n",
              "<div style=\"\n",
              "margin-top:30px;\n",
              "padding:20px;\n",
              "background:rgba(255,255,255,0.05);\n",
              "border-radius:20px;\n",
              "\">\n",
              "\"Volatilidad asimétrica de los ingresos por exportaciones petroleras de las empresas públicas del Ecuador mediante un modelo GJR-GARCH\".\n",
              "<h2 style=\"\n",
              "color:#FBBF24;\n",
              "\">\n",
              "👥 INTEGRANTES\n",
              "</h2>\n",
              "\n",
              "<p style=\"\n",
              "font-size:24px;\n",
              "line-height:2;\n",
              "\">\n",
              "\n",
              "🔹 Melany Arboleda<br>\n",
              "🔹 Angie Hernández<br>\n",
              "🔹 Marley Mansilla<br>\n",
              "🔹 Bryan Moncayo\n",
              "\n",
              "</p>\n",
              "\n",
              "</div>\n",
              "\n",
              "</div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# PROYECTO GRUPAL\n",
        "\n",
        "---\n",
        "\n",
        "# MODELO GJR-GARCH\n",
        "## Volatilidad Asimétrica de los Ingresos por Exportaciones Petroleras de las Empresas Públicas del Ecuador\n",
        "\n",
        "---\n",
        "\n",
        "### Variable de Estudio\n",
        "\n",
        "**Ingresos por exportaciones petroleras de las empresas públicas del Ecuador**\n",
        "\n",
        "- **Unidad de medida:** Miles de dólares (USD)\n",
        "- **Frecuencia:** Mensual\n",
        "- **Periodo de análisis:** 2007–2026\n",
        "- **Fuente de información:** Banco Central del Ecuador (BCE)\n",
        "\n",
        "---\n",
        "\n",
        "## Objetivo General\n",
        "\n",
        "Aplicar el modelo GJR-GARCH a los ingresos por exportaciones petroleras de las empresas públicas del Ecuador, con el propósito de analizar la volatilidad asimétrica generada por las fluctuaciones del mercado petrolero internacional, evaluar el impacto de las noticias negativas sobre la volatilidad y pronosticar el comportamiento futuro del riesgo.\n",
        "\n",
        "---\n",
        "\n",
        "## Pregunta de Investigación\n",
        "\n",
        "**¿Las noticias negativas del mercado petrolero internacional generan un mayor incremento en la volatilidad de los ingresos por exportaciones petroleras de las empresas públicas del Ecuador que las noticias positivas?**\n",
        "\n",
        "---\n",
        "\n",
        "## Formulación de Hipótesis\n",
        "\n",
        "### Hipótesis Nula (H₀)\n",
        "\n",
        "🔴 No existe un efecto asimétrico significativo en la volatilidad de los ingresos por exportaciones petroleras; las noticias positivas y negativas tienen el mismo efecto sobre la volatilidad.\n",
        "\n",
        "### Hipótesis Alternativa (H₁)\n",
        "\n",
        "🟢 Existe un efecto asimétrico significativo en la volatilidad de los ingresos por exportaciones petroleras; las noticias negativas generan un incremento mayor en la volatilidad que las noticias positivas.\n",
        "\n",
        "---\n",
        "\n",
        "## Metodología\n",
        "\n",
        "1️⃣ Obtención y revisión de la base de datos del sector petrolero ecuatoriano.\n",
        "\n",
        "2️⃣ Limpieza y preparación de la información.\n",
        "\n",
        "3️⃣ Análisis exploratorio de la serie temporal de ingresos por exportaciones petroleras.\n",
        "\n",
        "4️⃣ Cálculo de los retornos logarítmicos.\n",
        "\n",
        "5️⃣ Verificación de estacionariedad mediante la prueba ADF.\n",
        "\n",
        "6️⃣ Aplicación de la prueba ARCH-LM para detectar heterocedasticidad condicional.\n",
        "\n",
        "7️⃣ Estimación del modelo GJR-GARCH.\n",
        "\n",
        "8️⃣ Análisis e interpretación de la volatilidad condicional y del efecto asimétrico.\n",
        "\n",
        "9️⃣ Pronóstico de la volatilidad futura y construcción de un Índice de Riesgo Petrolero.\n",
        "\n",
        "🔟 Simulación de escenarios de riesgo ante variaciones en los ingresos por exportaciones petroleras.\n",
        "\n",
        "1️⃣1️⃣ Interpretación de resultados, conclusiones y recomendaciones."
      ],
      "metadata": {
        "id": "VBxeX3TX0KR6"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **Descripción de la Base de Datos**\n",
        "\n",
        "La base de datos proviene del **Banco Central del Ecuador (BCE)** y contiene información mensual del sector petrolero ecuatoriano durante el período **2007–2026**. La información está organizada como una serie temporal e incluye variables relacionadas con las exportaciones, precios e ingresos de las empresas petroleras públicas y privadas del país.\n",
        "\n",
        "**Variables principales de la base de datos**\n",
        "\n",
        "- Fecha\n",
        "- Exportaciones de empresas públicas\n",
        "- Precio del petróleo de empresas públicas\n",
        "- Ingresos de empresas públicas\n",
        "- Exportaciones de empresas privadas\n",
        "- Precio del petróleo de empresas privadas\n",
        "- Ingresos de empresas privadas\n",
        "\n",
        "**Variable de Estudio**\n",
        "\n",
        "Los **ingresos por exportaciones petroleras de las empresas públicas y privadas del Ecuador**, medidos en millones de dólares. Estas variables representan los ingresos generados por la comercialización de petróleo en los mercados internacionales y constituyen la base para analizar la volatilidad mediante el modelo **GJR-GARCH**, permitiendo evaluar si las noticias negativas producen un mayor impacto sobre la variabilidad de los ingresos en comparación con las noticias positivas.\n"
      ],
      "metadata": {
        "id": "Nm_nLA8nE5PV"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **DESARROLLO DEL CODIGO**\n",
        "## **1: Importar librerías**"
      ],
      "metadata": {
        "id": "fSk29eK3CP5Z"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#!pip install arch -q"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1ccyyy-swJvi",
        "outputId": "505f4ca9-81e3-4b1f-fe97-4f868298a103"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[?25l   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/981.3 kB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m981.3/981.3 kB\u001b[0m \u001b[31m32.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 1. IMPORTAR LIBRERÍAS\n",
        "\n",
        "\n",
        "# Manipulación de datos\n",
        "import pandas as pd\n",
        "\n",
        "# Operaciones numéricas\n",
        "import numpy as np\n",
        "\n",
        "# Gráficos\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# Estilo de gráficos\n",
        "import seaborn as sns\n",
        "\n",
        "# Modelo GJR-GARCH\n",
        "from arch import arch_model\n",
        "\n",
        "# Prueba ARCH\n",
        "from statsmodels.stats.diagnostic import het_arch\n",
        "\n",
        "# Configura tamaño de gráficos\n",
        "plt.rcParams[\"figure.figsize\"] = (12,6)\n",
        "\n",
        "# Estilo visual\n",
        "sns.set_style(\"whitegrid\")"
      ],
      "metadata": {
        "id": "0AUWTfvYv7YE"
      },
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 2: Cargar la Base de Datos"
      ],
      "metadata": {
        "id": "0ce6regzwDK9"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 2. CARGAR LA BASE DE DATOS\n",
        "\n",
        "\n",
        "# Permite subir archivos desde el computador\n",
        "from google.colab import files\n",
        "\n",
        "# Abre el explorador de archivos\n",
        "uploaded = files.upload()\n",
        "\n",
        "# Lee el archivo Excel\n",
        "df = pd.read_excel(\"Petroleo.xlsx\")\n",
        "\n",
        "# Muestra las primeras filas\n",
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 470
        },
        "id": "QzFtdUH-wHtc",
        "outputId": "8fcc08b2-8087-4208-d09e-f6643745af8f"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "\n",
              "     <input type=\"file\" id=\"files-2355e830-93a3-492f-9ff9-e4ed54ab1232\" name=\"files[]\" multiple disabled\n",
              "        style=\"border:none\" />\n",
              "     <output id=\"result-2355e830-93a3-492f-9ff9-e4ed54ab1232\">\n",
              "      Upload widget is only available when the cell has been executed in the\n",
              "      current browser session. Please rerun this cell to enable.\n",
              "      </output>\n",
              "      <script>// Copyright 2017 Google LLC\n",
              "//\n",
              "// Licensed under the Apache License, Version 2.0 (the \"License\");\n",
              "// you may not use this file except in compliance with the License.\n",
              "// You may obtain a copy of the License at\n",
              "//\n",
              "//      http://www.apache.org/licenses/LICENSE-2.0\n",
              "//\n",
              "// Unless required by applicable law or agreed to in writing, software\n",
              "// distributed under the License is distributed on an \"AS IS\" BASIS,\n",
              "// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
              "// See the License for the specific language governing permissions and\n",
              "// limitations under the License.\n",
              "\n",
              "/**\n",
              " * @fileoverview Helpers for google.colab Python module.\n",
              " */\n",
              "(function(scope) {\n",
              "function span(text, styleAttributes = {}) {\n",
              "  const element = document.createElement('span');\n",
              "  element.textContent = text;\n",
              "  for (const key of Object.keys(styleAttributes)) {\n",
              "    element.style[key] = styleAttributes[key];\n",
              "  }\n",
              "  return element;\n",
              "}\n",
              "\n",
              "// Max number of bytes which will be uploaded at a time.\n",
              "const MAX_PAYLOAD_SIZE = 100 * 1024;\n",
              "\n",
              "function _uploadFiles(inputId, outputId) {\n",
              "  const steps = uploadFilesStep(inputId, outputId);\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  // Cache steps on the outputElement to make it available for the next call\n",
              "  // to uploadFilesContinue from Python.\n",
              "  outputElement.steps = steps;\n",
              "\n",
              "  return _uploadFilesContinue(outputId);\n",
              "}\n",
              "\n",
              "// This is roughly an async generator (not supported in the browser yet),\n",
              "// where there are multiple asynchronous steps and the Python side is going\n",
              "// to poll for completion of each step.\n",
              "// This uses a Promise to block the python side on completion of each step,\n",
              "// then passes the result of the previous step as the input to the next step.\n",
              "function _uploadFilesContinue(outputId) {\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  const steps = outputElement.steps;\n",
              "\n",
              "  const next = steps.next(outputElement.lastPromiseValue);\n",
              "  return Promise.resolve(next.value.promise).then((value) => {\n",
              "    // Cache the last promise value to make it available to the next\n",
              "    // step of the generator.\n",
              "    outputElement.lastPromiseValue = value;\n",
              "    return next.value.response;\n",
              "  });\n",
              "}\n",
              "\n",
              "/**\n",
              " * Generator function which is called between each async step of the upload\n",
              " * process.\n",
              " * @param {string} inputId Element ID of the input file picker element.\n",
              " * @param {string} outputId Element ID of the output display.\n",
              " * @return {!Iterable<!Object>} Iterable of next steps.\n",
              " */\n",
              "function* uploadFilesStep(inputId, outputId) {\n",
              "  const inputElement = document.getElementById(inputId);\n",
              "  inputElement.disabled = false;\n",
              "\n",
              "  const outputElement = document.getElementById(outputId);\n",
              "  outputElement.innerHTML = '';\n",
              "\n",
              "  const pickedPromise = new Promise((resolve) => {\n",
              "    inputElement.addEventListener('change', (e) => {\n",
              "      resolve(e.target.files);\n",
              "    });\n",
              "  });\n",
              "\n",
              "  const cancel = document.createElement('button');\n",
              "  inputElement.parentElement.appendChild(cancel);\n",
              "  cancel.textContent = 'Cancel upload';\n",
              "  const cancelPromise = new Promise((resolve) => {\n",
              "    cancel.onclick = () => {\n",
              "      resolve(null);\n",
              "    };\n",
              "  });\n",
              "\n",
              "  // Wait for the user to pick the files.\n",
              "  const files = yield {\n",
              "    promise: Promise.race([pickedPromise, cancelPromise]),\n",
              "    response: {\n",
              "      action: 'starting',\n",
              "    }\n",
              "  };\n",
              "\n",
              "  cancel.remove();\n",
              "\n",
              "  // Disable the input element since further picks are not allowed.\n",
              "  inputElement.disabled = true;\n",
              "\n",
              "  if (!files) {\n",
              "    return {\n",
              "      response: {\n",
              "        action: 'complete',\n",
              "      }\n",
              "    };\n",
              "  }\n",
              "\n",
              "  for (const file of files) {\n",
              "    const li = document.createElement('li');\n",
              "    li.append(span(file.name, {fontWeight: 'bold'}));\n",
              "    li.append(span(\n",
              "        `(${file.type || 'n/a'}) - ${file.size} bytes, ` +\n",
              "        `last modified: ${\n",
              "            file.lastModifiedDate ? file.lastModifiedDate.toLocaleDateString() :\n",
              "                                    'n/a'} - `));\n",
              "    const percent = span('0% done');\n",
              "    li.appendChild(percent);\n",
              "\n",
              "    outputElement.appendChild(li);\n",
              "\n",
              "    const fileDataPromise = new Promise((resolve) => {\n",
              "      const reader = new FileReader();\n",
              "      reader.onload = (e) => {\n",
              "        resolve(e.target.result);\n",
              "      };\n",
              "      reader.readAsArrayBuffer(file);\n",
              "    });\n",
              "    // Wait for the data to be ready.\n",
              "    let fileData = yield {\n",
              "      promise: fileDataPromise,\n",
              "      response: {\n",
              "        action: 'continue',\n",
              "      }\n",
              "    };\n",
              "\n",
              "    // Use a chunked sending to avoid message size limits. See b/62115660.\n",
              "    let position = 0;\n",
              "    do {\n",
              "      const length = Math.min(fileData.byteLength - position, MAX_PAYLOAD_SIZE);\n",
              "      const chunk = new Uint8Array(fileData, position, length);\n",
              "      position += length;\n",
              "\n",
              "      const base64 = btoa(String.fromCharCode.apply(null, chunk));\n",
              "      yield {\n",
              "        response: {\n",
              "          action: 'append',\n",
              "          file: file.name,\n",
              "          data: base64,\n",
              "        },\n",
              "      };\n",
              "\n",
              "      let percentDone = fileData.byteLength === 0 ?\n",
              "          100 :\n",
              "          Math.round((position / fileData.byteLength) * 100);\n",
              "      percent.textContent = `${percentDone}% done`;\n",
              "\n",
              "    } while (position < fileData.byteLength);\n",
              "  }\n",
              "\n",
              "  // All done.\n",
              "  yield {\n",
              "    response: {\n",
              "      action: 'complete',\n",
              "    }\n",
              "  };\n",
              "}\n",
              "\n",
              "scope.google = scope.google || {};\n",
              "scope.google.colab = scope.google.colab || {};\n",
              "scope.google.colab._files = {\n",
              "  _uploadFiles,\n",
              "  _uploadFilesContinue,\n",
              "};\n",
              "})(self);\n",
              "</script> "
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Saving Petroleo.xlsx to Petroleo.xlsx\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     Periodo  \\\n",
              "0 2007-01-01   \n",
              "1 2007-02-01   \n",
              "2 2007-03-01   \n",
              "3 2007-04-01   \n",
              "4 2007-05-01   \n",
              "\n",
              "   EXPORTACIONES DE PETRÓLEO DE EMPRESAS PÚBLICAS (miles de barriles)   \\\n",
              "0                                           5713.873                     \n",
              "1                                           5656.911                     \n",
              "2                                           5137.830                     \n",
              "3                                           5169.221                     \n",
              "4                                           4509.777                     \n",
              "\n",
              "   Precio (USD por barril)  \\\n",
              "0                39.109373   \n",
              "1                46.630391   \n",
              "2                48.669201   \n",
              "3                53.308112   \n",
              "4                54.572039   \n",
              "\n",
              "   Ingreso por exportaciones de petróleo de Empresas Públicas (miles de USD)  \\\n",
              "0                                       223465.98871                           \n",
              "1                                       263783.97315                           \n",
              "2                                       250054.07994                           \n",
              "3                                       275561.41457                           \n",
              "4                                       246107.72458                           \n",
              "\n",
              "   EXPORTACIONES DE PETRÓLEO DE COMPAÑÍAS PRIVADAS (miles de barriles)  \\\n",
              "0                                         4590.43209                     \n",
              "1                                         3553.46539                     \n",
              "2                                         5167.00802                     \n",
              "3                                         4145.32441                     \n",
              "4                                         4714.12562                     \n",
              "\n",
              "  Precio (dólares por barril)  \\\n",
              "0                   41.604827   \n",
              "1                   45.754273   \n",
              "2                   48.073291   \n",
              "3                   51.279615   \n",
              "4                      53.028   \n",
              "\n",
              "   Ingreso por exportaciones de petróleo de Compañías Privadas (miles de dólares)  \n",
              "0                                       190984.13301                               \n",
              "1                                       162586.22547                               \n",
              "2                                       248395.08028                               \n",
              "3                                       212570.64012                               \n",
              "4                                       249980.65544                               "
            ],
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            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 233,\n  \"fields\": [\n    {\n      \"column\": \"Periodo\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": \"2007-01-01 00:00:00\",\n        \"max\": \"2026-05-01 00:00:00\",\n        \"num_unique_values\": 233,\n        \"samples\": [\n          \"2014-01-01 00:00:00\",\n          \"2025-01-01 00:00:00\",\n          \"2026-04-01 00:00:00\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"EXPORTACIONES DE PETR\\u00d3LEO DE EMPRESAS P\\u00daBLICAS (miles de barriles) \",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1924.4425829718314,\n        \"min\": 1710.9530399999999,\n        \"max\": 13923.75622,\n        \"num_unique_values\": 233,\n        \"samples\": [\n          10217.95665,\n          10626.672709999999,\n          8893.828300000001\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Precio (USD por barril)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 22.40768082809142,\n        \"min\": 14.03742579453826,\n        \"max\": 118.80247365415559,\n        \"num_unique_values\": 233,\n        \"samples\": [\n          91.63051411815925,\n          67.30156019302242,\n          89.44645422826638\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Ingreso por exportaciones de petr\\u00f3leo de Empresas P\\u00fablicas (miles de USD)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 234006.66650438122,\n        \"min\": 68798.94323,\n        \"max\": 1336204.8010128327,\n        \"num_unique_values\": 233,\n        \"samples\": [\n          936276.6210765643,\n          715191.6530436137,\n          795521.4059500103\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"EXPORTACIONES DE PETR\\u00d3LEO DE COMPA\\u00d1\\u00cdAS PRIVADAS (miles de barriles)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1549.8598475153574,\n        \"min\": 0.0,\n        \"max\": 6208.9651,\n        \"num_unique_values\": 92,\n        \"samples\": [\n          1633.9419100000005,\n          2636.30296,\n          8.499029999999038\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Precio (d\\u00f3lares por barril)\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 93,\n        \"samples\": [\n          65.42228061216693,\n          48.217138858224665,\n          101.41999999999999\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Ingreso por exportaciones de petr\\u00f3leo de Compa\\u00f1\\u00edas Privadas (miles de d\\u00f3lares)\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 109079.04699064446,\n        \"min\": 0.0,\n        \"max\": 520050.74529000005,\n        \"num_unique_values\": 85,\n        \"samples\": [\n          16411.31079,\n          190984.13301000002,\n          28635.19058424\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 3: Estructura de la Base"
      ],
      "metadata": {
        "id": "7yYh76X9widh"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Muestra las últimas 5 observaciones\n",
        "df.tail()\n",
        "# Muestra el tamaño de la base (filas y columnas)\n",
        "df.shape\n",
        "# Muestra el nombre de todas las variables\n",
        "df.columns\n",
        "# Muestra el tipo de dato de cada variable\n",
        "df.info()\n",
        "# Obtiene estadísticas descriptivas de las variables numéricas\n",
        "df.describe().T\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 848
        },
        "id": "2kD5P8pawk9s",
        "outputId": "eb9c7c1f-ec90-4e5c-e5fc-c09d87a1f53c"
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      "execution_count": 6,
      "outputs": [
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          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 233 entries, 0 to 232\n",
            "Data columns (total 7 columns):\n",
            " #   Column                                                                          Non-Null Count  Dtype         \n",
            "---  ------                                                                          --------------  -----         \n",
            " 0   Periodo                                                                         233 non-null    datetime64[ns]\n",
            " 1   EXPORTACIONES DE PETRÓLEO DE EMPRESAS PÚBLICAS (miles de barriles)              233 non-null    float64       \n",
            " 2   Precio (USD por barril)                                                         233 non-null    float64       \n",
            " 3   Ingreso por exportaciones de petróleo de Empresas Públicas (miles de USD)       233 non-null    float64       \n",
            " 4   EXPORTACIONES DE PETRÓLEO DE COMPAÑÍAS PRIVADAS (miles de barriles)             233 non-null    float64       \n",
            " 5   Precio (dólares por barril)                                                     233 non-null    object        \n",
            " 6   Ingreso por exportaciones de petróleo de Compañías Privadas (miles de dólares)  233 non-null    float64       \n",
            "dtypes: datetime64[ns](1), float64(5), object(1)\n",
            "memory usage: 12.9+ KB\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                                    count  \\\n",
              "Periodo                                               233   \n",
              "EXPORTACIONES DE PETRÓLEO DE EMPRESAS PÚBLICAS ...  233.0   \n",
              "Precio (USD por barril)                             233.0   \n",
              "Ingreso por exportaciones de petróleo de Empres...  233.0   \n",
              "EXPORTACIONES DE PETRÓLEO DE COMPAÑÍAS PRIVADAS...  233.0   \n",
              "Ingreso por exportaciones de petróleo de Compañ...  233.0   \n",
              "\n",
              "                                                                             mean  \\\n",
              "Periodo                                             2016-08-31 04:19:34.248926976   \n",
              "EXPORTACIONES DE PETRÓLEO DE EMPRESAS PÚBLICAS ...                    8954.704297   \n",
              "Precio (USD por barril)                                                 66.751987   \n",
              "Ingreso por exportaciones de petróleo de Empres...                  594784.218799   \n",
              "EXPORTACIONES DE PETRÓLEO DE COMPAÑÍAS PRIVADAS...                     777.488976   \n",
              "Ingreso por exportaciones de petróleo de Compañ...                    51455.01831   \n",
              "\n",
              "                                                                    min  \\\n",
              "Periodo                                             2007-01-01 00:00:00   \n",
              "EXPORTACIONES DE PETRÓLEO DE EMPRESAS PÚBLICAS ...           1710.95304   \n",
              "Precio (USD por barril)                                       14.037426   \n",
              "Ingreso por exportaciones de petróleo de Empres...          68798.94323   \n",
              "EXPORTACIONES DE PETRÓLEO DE COMPAÑÍAS PRIVADAS...                  0.0   \n",
              "Ingreso por exportaciones de petróleo de Compañ...                  0.0   \n",
              "\n",
              "                                                                    25%  \\\n",
              "Periodo                                             2011-11-01 00:00:00   \n",
              "EXPORTACIONES DE PETRÓLEO DE EMPRESAS PÚBLICAS ...           7811.72599   \n",
              "Precio (USD por barril)                                       51.924284   \n",
              "Ingreso por exportaciones de petróleo de Empres...        437221.046865   \n",
              "EXPORTACIONES DE PETRÓLEO DE COMPAÑÍAS PRIVADAS...                  0.0   \n",
              "Ingreso por exportaciones de petróleo de Compañ...                  0.0   \n",
              "\n",
              "                                                                    50%  \\\n",
              "Periodo                                             2016-09-01 00:00:00   \n",
              "EXPORTACIONES DE PETRÓLEO DE EMPRESAS PÚBLICAS ...           9084.47768   \n",
              "Precio (USD por barril)                                       64.743564   \n",
              "Ingreso por exportaciones de petróleo de Empres...        548905.963246   \n",
              "EXPORTACIONES DE PETRÓLEO DE COMPAÑÍAS PRIVADAS...                  0.0   \n",
              "Ingreso por exportaciones de petróleo de Compañ...                  0.0   \n",
              "\n",
              "                                                                    75%  \\\n",
              "Periodo                                             2021-07-01 00:00:00   \n",
              "EXPORTACIONES DE PETRÓLEO DE EMPRESAS PÚBLICAS ...          10172.24363   \n",
              "Precio (USD por barril)                                       83.530452   \n",
              "Ingreso por exportaciones de petróleo de Empres...         736706.17382   \n",
              "EXPORTACIONES DE PETRÓLEO DE COMPAÑÍAS PRIVADAS...            275.41425   \n",
              "Ingreso por exportaciones de petróleo de Compañ...           17627.6223   \n",
              "\n",
              "                                                                    max  \\\n",
              "Periodo                                             2026-05-01 00:00:00   \n",
              "EXPORTACIONES DE PETRÓLEO DE EMPRESAS PÚBLICAS ...          13923.75622   \n",
              "Precio (USD por barril)                                      118.802474   \n",
              "Ingreso por exportaciones de petróleo de Empres...       1336204.801013   \n",
              "EXPORTACIONES DE PETRÓLEO DE COMPAÑÍAS PRIVADAS...            6208.9651   \n",
              "Ingreso por exportaciones de petróleo de Compañ...         520050.74529   \n",
              "\n",
              "                                                              std  \n",
              "Periodo                                                       NaN  \n",
              "EXPORTACIONES DE PETRÓLEO DE EMPRESAS PÚBLICAS ...    1924.442583  \n",
              "Precio (USD por barril)                                 22.407681  \n",
              "Ingreso por exportaciones de petróleo de Empres...  234006.666504  \n",
              "EXPORTACIONES DE PETRÓLEO DE COMPAÑÍAS PRIVADAS...    1549.859848  \n",
              "Ingreso por exportaciones de petróleo de Compañ...  109079.046991  "
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              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>count</th>\n",
              "      <th>mean</th>\n",
              "      <th>min</th>\n",
              "      <th>25%</th>\n",
              "      <th>50%</th>\n",
              "      <th>75%</th>\n",
              "      <th>max</th>\n",
              "      <th>std</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Periodo</th>\n",
              "      <td>233</td>\n",
              "      <td>2016-08-31 04:19:34.248926976</td>\n",
              "      <td>2007-01-01 00:00:00</td>\n",
              "      <td>2011-11-01 00:00:00</td>\n",
              "      <td>2016-09-01 00:00:00</td>\n",
              "      <td>2021-07-01 00:00:00</td>\n",
              "      <td>2026-05-01 00:00:00</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>EXPORTACIONES DE PETRÓLEO DE EMPRESAS PÚBLICAS (miles de barriles)</th>\n",
              "      <td>233.0</td>\n",
              "      <td>8954.704297</td>\n",
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              "      <td>7811.72599</td>\n",
              "      <td>9084.47768</td>\n",
              "      <td>10172.24363</td>\n",
              "      <td>13923.75622</td>\n",
              "      <td>1924.442583</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Precio (USD por barril)</th>\n",
              "      <td>233.0</td>\n",
              "      <td>66.751987</td>\n",
              "      <td>14.037426</td>\n",
              "      <td>51.924284</td>\n",
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              "      <td>118.802474</td>\n",
              "      <td>22.407681</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Ingreso por exportaciones de petróleo de Empresas Públicas (miles de USD)</th>\n",
              "      <td>233.0</td>\n",
              "      <td>594784.218799</td>\n",
              "      <td>68798.94323</td>\n",
              "      <td>437221.046865</td>\n",
              "      <td>548905.963246</td>\n",
              "      <td>736706.17382</td>\n",
              "      <td>1336204.801013</td>\n",
              "      <td>234006.666504</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>EXPORTACIONES DE PETRÓLEO DE COMPAÑÍAS PRIVADAS (miles de barriles)</th>\n",
              "      <td>233.0</td>\n",
              "      <td>777.488976</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>275.41425</td>\n",
              "      <td>6208.9651</td>\n",
              "      <td>1549.859848</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Ingreso por exportaciones de petróleo de Compañías Privadas (miles de dólares)</th>\n",
              "      <td>233.0</td>\n",
              "      <td>51455.01831</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>17627.6223</td>\n",
              "      <td>520050.74529</td>\n",
              "      <td>109079.046991</td>\n",
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              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "        const element = document.querySelector('#df-97ecea22-afb9-40cc-9341-a2b42744ee7e');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
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              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
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              "        await google.colab.output.renderOutput(dataTable, element);\n",
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              "\n",
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              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 6,\n  \"fields\": [\n    {\n      \"column\": \"count\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": \"233\",\n        \"max\": \"233\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"233\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"mean\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": \"1970-01-01 00:00:00.000000066\",\n        \"max\": \"2016-08-31 04:19:34.248926976\",\n        \"num_unique_values\": 6,\n        \"samples\": [\n          \"2016-08-31 04:19:34.248926976\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"min\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": \"1970-01-01 00:00:00\",\n        \"max\": \"2007-01-01 00:00:00\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          1710.9530399999999\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"25%\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": \"1970-01-01 00:00:00\",\n        \"max\": \"2011-11-01 00:00:00\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          7811.72599\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"50%\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": \"1970-01-01 00:00:00\",\n        \"max\": \"2016-09-01 00:00:00\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          9084.477680000002\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"75%\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": \"1970-01-01 00:00:00.000000083\",\n        \"max\": \"2021-07-01 00:00:00\",\n        \"num_unique_values\": 6,\n        \"samples\": [\n          \"2021-07-01 00:00:00\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"max\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": \"1970-01-01 00:00:00.000000118\",\n        \"max\": \"2026-05-01 00:00:00\",\n        \"num_unique_values\": 6,\n        \"samples\": [\n          \"2026-05-01 00:00:00\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"std\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": 22.40768082809142,\n        \"max\": 234006.66650438122,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          22.40768082809142\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 4: Verificar valores faltantes"
      ],
      "metadata": {
        "id": "-b0dQxtywyN6"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 4. VALORES FALTANTES\n",
        "\n",
        "# Cuenta los valores faltantes de cada variable\n",
        "df.isnull().sum()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 304
        },
        "id": "-E_Sv9fRw1Sc",
        "outputId": "48ff9f16-f799-4ecf-ed88-246ac1feaeb0"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Periodo                                                                           0\n",
              "EXPORTACIONES DE PETRÓLEO DE EMPRESAS PÚBLICAS (miles de barriles)                0\n",
              "Precio (USD por barril)                                                           0\n",
              "Ingreso por exportaciones de petróleo de Empresas Públicas (miles de USD)         0\n",
              "EXPORTACIONES DE PETRÓLEO DE COMPAÑÍAS PRIVADAS (miles de barriles)               0\n",
              "Precio (dólares por barril)                                                       0\n",
              "Ingreso por exportaciones de petróleo de Compañías Privadas (miles de dólares)    0\n",
              "dtype: int64"
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              "      <td>0</td>\n",
              "    </tr>\n",
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              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>EXPORTACIONES DE PETRÓLEO DE COMPAÑÍAS PRIVADAS (miles de barriles)</th>\n",
              "      <td>0</td>\n",
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              "    <tr>\n",
              "      <th>Precio (dólares por barril)</th>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div><br><label><b>dtype:</b> int64</label>"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "La base de datos no presenta valores faltantes, por lo que no fue necesario realizar procesos de imputación o eliminación de observaciones."
      ],
      "metadata": {
        "id": "j1sy68Bww8t9"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 5: Renombrar las Variables"
      ],
      "metadata": {
        "id": "Bk41am0zxF5P"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 5. RENOMBRAR VARIABLES\n",
        "\n",
        "# Cambia los nombres largos por nombres cortos\n",
        "df.columns = [\n",
        "    \"Periodo\",\n",
        "    \"Export_Publicas\",\n",
        "    \"Precio_Publicas\",\n",
        "    \"Ingreso_Publicas\",\n",
        "    \"Export_Privadas\",\n",
        "    \"Precio_Privadas\",\n",
        "    \"Ingreso_Privadas\"\n",
        "]\n",
        "\n",
        "# Muestra los nuevos nombres de las variables\n",
        "df.columns"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "33zh7l6JxI5J",
        "outputId": "f4a83c08-8cf1-4aba-c0af-e7026c87438f"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['Periodo', 'Export_Publicas', 'Precio_Publicas', 'Ingreso_Publicas',\n",
              "       'Export_Privadas', 'Precio_Privadas', 'Ingreso_Privadas'],\n",
              "      dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#6: Convertir la Fecha"
      ],
      "metadata": {
        "id": "VEjCbEf7xNCe"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 6. CONVERTIR LA FECHA\n",
        "\n",
        "# Convierte la columna Periodo al formato de fecha\n",
        "df[\"Periodo\"] = pd.to_datetime(df[\"Periodo\"])\n",
        "\n",
        "# Establece la fecha como índice de la base\n",
        "df.set_index(\"Periodo\", inplace=True)\n",
        "\n",
        "# Muestra las primeras observaciones\n",
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 344
        },
        "id": "wpglP0JhxP8R",
        "outputId": "00ab9e11-2d41-4c3c-9fbb-f188839967e9"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            Export_Publicas  Precio_Publicas  Ingreso_Publicas  \\\n",
              "Periodo                                                          \n",
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              "2007-02-01         5656.911        46.630391      263783.97315   \n",
              "2007-03-01         5137.830        48.669201      250054.07994   \n",
              "2007-04-01         5169.221        53.308112      275561.41457   \n",
              "2007-05-01         4509.777        54.572039      246107.72458   \n",
              "\n",
              "            Export_Privadas Precio_Privadas  Ingreso_Privadas  \n",
              "Periodo                                                        \n",
              "2007-01-01       4590.43209       41.604827      190984.13301  \n",
              "2007-02-01       3553.46539       45.754273      162586.22547  \n",
              "2007-03-01       5167.00802       48.073291      248395.08028  \n",
              "2007-04-01       4145.32441       51.279615      212570.64012  \n",
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              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-64e396e4-3314-4ad8-9f8e-7dc3b462227a button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-64e396e4-3314-4ad8-9f8e-7dc3b462227a');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 233,\n  \"fields\": [\n    {\n      \"column\": \"Periodo\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": \"2007-01-01 00:00:00\",\n        \"max\": \"2026-05-01 00:00:00\",\n        \"num_unique_values\": 233,\n        \"samples\": [\n          \"2014-01-01 00:00:00\",\n          \"2025-01-01 00:00:00\",\n          \"2026-04-01 00:00:00\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Export_Publicas\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1924.4425829718314,\n        \"min\": 1710.9530399999999,\n        \"max\": 13923.75622,\n        \"num_unique_values\": 233,\n        \"samples\": [\n          10217.95665,\n          10626.672709999999,\n          8893.828300000001\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Precio_Publicas\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 22.40768082809142,\n        \"min\": 14.03742579453826,\n        \"max\": 118.80247365415559,\n        \"num_unique_values\": 233,\n        \"samples\": [\n          91.63051411815925,\n          67.30156019302242,\n          89.44645422826638\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Ingreso_Publicas\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 234006.66650438122,\n        \"min\": 68798.94323,\n        \"max\": 1336204.8010128327,\n        \"num_unique_values\": 233,\n        \"samples\": [\n          936276.6210765643,\n          715191.6530436137,\n          795521.4059500103\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Export_Privadas\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1549.8598475153574,\n        \"min\": 0.0,\n        \"max\": 6208.9651,\n        \"num_unique_values\": 92,\n        \"samples\": [\n          1633.9419100000005,\n          2636.30296,\n          8.499029999999038\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Precio_Privadas\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 93,\n        \"samples\": [\n          65.42228061216693,\n          48.217138858224665,\n          101.41999999999999\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Ingreso_Privadas\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 109079.04699064446,\n        \"min\": 0.0,\n        \"max\": 520050.74529000005,\n        \"num_unique_values\": 85,\n        \"samples\": [\n          16411.31079,\n          190984.13301000002,\n          28635.19058424\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#7: Estadísticas descriptivas"
      ],
      "metadata": {
        "id": "qwNVesITxV7G"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 7. ESTADÍSTICAS DESCRIPTIVAS\n",
        "\n",
        "\n",
        "# Calcula estadísticas descriptivas\n",
        "estadisticas = df.describe().T\n",
        "\n",
        "# Redondea los resultados a dos decimales\n",
        "estadisticas = estadisticas.round(2)\n",
        "\n",
        "# Muestra la tabla\n",
        "estadisticas"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 226
        },
        "id": "tvTdBRF4xZrh",
        "outputId": "cc01b50f-4066-4ff9-c41d-0e44c5acdd05"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                  count       mean        std       min        25%        50%  \\\n",
              "Export_Publicas   233.0    8954.70    1924.44   1710.95    7811.73    9084.48   \n",
              "Precio_Publicas   233.0      66.75      22.41     14.04      51.92      64.74   \n",
              "Ingreso_Publicas  233.0  594784.22  234006.67  68798.94  437221.05  548905.96   \n",
              "Export_Privadas   233.0     777.49    1549.86      0.00       0.00       0.00   \n",
              "Ingreso_Privadas  233.0   51455.02  109079.05      0.00       0.00       0.00   \n",
              "\n",
              "                        75%         max  \n",
              "Export_Publicas    10172.24    13923.76  \n",
              "Precio_Publicas       83.53      118.80  \n",
              "Ingreso_Publicas  736706.17  1336204.80  \n",
              "Export_Privadas      275.41     6208.97  \n",
              "Ingreso_Privadas   17627.62   520050.75  "
            ],
            "text/html": [
              "\n",
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              "        vertical-align: middle;\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>count</th>\n",
              "      <th>mean</th>\n",
              "      <th>std</th>\n",
              "      <th>min</th>\n",
              "      <th>25%</th>\n",
              "      <th>50%</th>\n",
              "      <th>75%</th>\n",
              "      <th>max</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Export_Publicas</th>\n",
              "      <td>233.0</td>\n",
              "      <td>8954.70</td>\n",
              "      <td>1924.44</td>\n",
              "      <td>1710.95</td>\n",
              "      <td>7811.73</td>\n",
              "      <td>9084.48</td>\n",
              "      <td>10172.24</td>\n",
              "      <td>13923.76</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Precio_Publicas</th>\n",
              "      <td>233.0</td>\n",
              "      <td>66.75</td>\n",
              "      <td>22.41</td>\n",
              "      <td>14.04</td>\n",
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              "      <td>83.53</td>\n",
              "      <td>118.80</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Ingreso_Publicas</th>\n",
              "      <td>233.0</td>\n",
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              "      <td>68798.94</td>\n",
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              "      <td>736706.17</td>\n",
              "      <td>1336204.80</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Export_Privadas</th>\n",
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              "      <td>6208.97</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Ingreso_Privadas</th>\n",
              "      <td>233.0</td>\n",
              "      <td>51455.02</td>\n",
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              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0.00</td>\n",
              "      <td>17627.62</td>\n",
              "      <td>520050.75</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
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              "\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-97f594b2-69cc-4002-8523-133d756d8153 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-97f594b2-69cc-4002-8523-133d756d8153');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "  <div id=\"id_1c89649b-d206-4fec-96e1-b6eda1d624d2\">\n",
              "    <style>\n",
              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('estadisticas')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
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              "  </svg>\n",
              "    </button>\n",
              "    <script>\n",
              "      (() => {\n",
              "      const buttonEl =\n",
              "        document.querySelector('#id_1c89649b-d206-4fec-96e1-b6eda1d624d2 button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('estadisticas');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "estadisticas",
              "summary": "{\n  \"name\": \"estadisticas\",\n  \"rows\": 5,\n  \"fields\": [\n    {\n      \"column\": \"count\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.0,\n        \"min\": 233.0,\n        \"max\": 233.0,\n        \"num_unique_values\": 1,\n        \"samples\": [\n          233.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"mean\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 260009.35767728576,\n        \"min\": 66.75,\n        \"max\": 594784.22,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          66.75\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"std\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 103246.78037836302,\n        \"min\": 22.41,\n        \"max\": 234006.67,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          22.41\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"min\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 30583.88771730435,\n        \"min\": 0.0,\n        \"max\": 68798.94,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          14.04\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"25%\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 194681.27436245876,\n        \"min\": 0.0,\n        \"max\": 437221.05,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          51.92\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"50%\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 244486.79315389055,\n        \"min\": 0.0,\n        \"max\": 548905.96,\n        \"num_unique_values\": 4,\n        \"samples\": [\n          64.74\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"75%\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 326399.52004057076,\n        \"min\": 83.53,\n        \"max\": 736706.17,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          83.53\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"max\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 581350.3079845697,\n        \"min\": 118.8,\n        \"max\": 1336204.8,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          118.8\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 8: Análisis Exploratorio de Datos (EDA)"
      ],
      "metadata": {
        "id": "oWdKLh2MxnrC"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# LIMPIEZA DE VARIABLES NUMÉRICAS\n",
        "\n",
        "\n",
        "# Reemplaza los guiones por valores faltantes (NaN)\n",
        "df = df.replace(\"-\", np.nan)\n",
        "\n",
        "# Convierte todas las columnas a valores numéricos\n",
        "for columna in df.columns:\n",
        "    df[columna] = pd.to_numeric(df[columna], errors=\"coerce\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cmGfaMQMyLg5",
        "outputId": "54e766c4-db69-46f2-edd6-d291f5dd396d"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/tmp/ipykernel_709/812336716.py:6: FutureWarning: Downcasting behavior in `replace` is deprecated and will be removed in a future version. To retain the old behavior, explicitly call `result.infer_objects(copy=False)`. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)`\n",
            "  df = df.replace(\"-\", np.nan)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 8.1 Serie Temporal de los ingresos"
      ],
      "metadata": {
        "id": "j-lYMTgr0lWn"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "# 8.1 SERIE TEMPORAL DE LOS INGRESOS\n",
        "\n",
        "\n",
        "# Crea una figura\n",
        "plt.figure(figsize=(15,6))\n",
        "\n",
        "# Grafica la serie de ingresos\n",
        "plt.plot(\n",
        "    df.index,\n",
        "    df[\"Ingreso_Publicas\"],\n",
        "    linewidth=2,\n",
        "    color=\"red\"\n",
        ")\n",
        "\n",
        "# Agrega el título\n",
        "plt.title(\"Ingresos por Exportaciones Petroleras de Empresas Públicas\")\n",
        "\n",
        "# Nombre del eje X\n",
        "plt.xlabel(\"Periodo\")\n",
        "\n",
        "# Nombre del eje Y\n",
        "plt.ylabel(\"Miles de USD\")\n",
        "\n",
        "# Activa la cuadrícula\n",
        "plt.grid(alpha=0.3)\n",
        "\n",
        "# Muestra la gráfica\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 356
        },
        "id": "R-JbKGDp0h9l",
        "outputId": "17780e07-2d05-4af1-82db-c6d702054fbc"
      },
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1500x600 with 1 Axes>"
            ],
            "image/png": 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l1KhRSmVlpev8119/XcnOzlaWLFniOm/8+PHK+PHjXafV10/+7Rs3bpzSp08ft+9d4+fCaM2aNUp2drayaNEi13kjR45UJk2a5OspISKiALGdk4iI/GKsVjrmmGN07SXLli1DvXr1cMEFF7jOi4uL01UN+brNL7/8EqmpqRg0aBAKCgpc/7p164akpCSsWrUKAFyVCEuXLkVVVZXpbf/444+Ij4/HhAkTdOdfccUVUBTF1Y6nVox8++23cDqdXp8DM3369EH37t1dp1u1aoVTTjkFP/30E2pqalBTU4Ply5dj2LBhaNOmjet6zZo1w1lnnYXffvsNJSUlutu84IILEB8fb3kdLrzwQsyZM8ftX+fOnV3XadiwIWbMmIGtW7di3LhxWLp0KaZNm4ZWrVpF5WNSKxMBMTh4QUEBjjvuOOzcudPV0rV8+XKUlpZi0qRJbmMPeasOsfreUA0cOFA32HuXLl2QkpLiqm5RFAVff/01hg4dCkVRdO/dwYMHo7i42NVKmJaWhr179+Kvv/6y/FzIZs6ciQEDBmDQoEGYMGECduzYgdtvvx2nnnoqNmzYgG3btuHss8/GwYMHXetQVlaGAQMGYPXq1Zbf48cee6zu/ePPa67yZ70uuugit9uR3xMVFRUoKChwVb/JrZppaWn4888/kZeXZ+mxqo/vp59+wrBhw3SfiU6dOmHw4MG6637zzTdwOp04/fTTda91kyZN0K5dO9f3lC/33nuv22f29ddfd7veaaedpqu+Uqv2Ro4cqRu0vmfPnqiqqnJ73M2aNcPw4cNdp1NSUnDuuedi/fr1yM/P113X+DldsWIFioqKcOaZZ+oea1xcHHr16uV6rA0aNEC9evXwyy+/eG1zlF9DtRKvX79+OHz4MP7991/X+gHATz/9hMOHD3u8LU/U99WAAQMwfPhwPP300+jduzdefPFF27eluvDCC3VjK44dOxYJCQn44YcfLN9GQUEBVq9ejfPOO8/te1f+vpKfo6qqKhw8eBBt27ZFWloa1q9f77osLS0NmzdvxrZt2/x4REREZBXbOYmIyLb69evrWr0AID09XbeztHv3bjRt2tTVaqLyNNNcQkICWrRooTtv+/btKC4uxoABA0z/5sCBAwCA4447DiNGjMALL7yAuXPn4rjjjsOwYcNw9tlnIzExEYAYV6ZZs2auHTJVp06dXJcDwBlnnIEPP/wQd999N5566inXjtdpp52GuDjfx57atWvndl779u11LZaHDx9Ghw4d3K7XqVMnOJ1O7NmzB0cddZTrfLMZ+3ytw8CBA31e75hjjsHYsWPx7rvvYvDgwTj//PM93p5RuB/Tb7/9hpkzZ+KPP/5w25EuLi5Gamqqq5VRvh8rrL43VC1btnS7jfT0dBQVFQEQO8dFRUX44IMP8MEHH5jep/q8XXXVVVixYgXGjBmDdu3aYdCgQTjrrLNwzDHHWFr3Cy+8EKeddhocDgfS0tJw1FFHud7z6s60pxZqQDx36enpPu/H+HoVFBTYfs1V/qyX2fvl0KFDeOGFF/D555+7vgvkv1fdfvvtmDp1Kk466SR069YNQ4YMwbnnnqsL/4wKCgpQXl5u+t7v0KGDLizZtm0bFEXBqaeeanpbVmdj7Nmzp6WJBYzvPzVQ83R+YWGh7rG2a9fOLVRu3749APFeb9q0qet84/OuvnaXXnqp6bqpn6HExETcfvvteOyxxzBo0CD06tULJ510Es4991zd7W/evBnPPvssfv75Z7fQVX0N27Rpg8svvxxz5szB4sWL0a9fPwwdOhQjR4601MpZv359vPLKK671at26tdtvjV3G90VycjKaNm3q9l3hjRq6qy3xnpSXl+PVV1/FwoULkZeXpxunUX6f33jjjbjuuuswYsQIZGdnY/DgwTjnnHPQpUsXy+tERES+xXSItnr1asyePRt///038vPz8eKLL2LYsGG2bkNRFLzxxhuYP38+cnNz0ahRI1x88cW49tprQ7TWRESRZ6eCyKrExES3kMrpdCIzMxNPPvmk6d+oQZ7D4cDzzz+PP/74A99//z2WLVuG6dOnY86cOfjggw+QnJxseT0aNGiAd999F6tWrcLSpUuxbNkyfP755/jggw/wxhtvhOSx+xKqGd0qKyvxyy+/ABA7dIcPH3YLPUPFzmPasWMHLrvsMnTs2BFTp05Fy5YtUa9ePfzwww+YO3euXxWDgfD0HlB3btX1GTlyJEaNGmV63ZycHAAicPryyy9d77Wvv/4a7733Hq6//nrceOONPtfFW2Cqrs+dd96Jrl27ml7H6myLcjVMoPxZL7P3y80334w1a9Zg4sSJ6Nq1K5KSkuB0OnHllVfqgoYzzjgD/fr1wzfffIPly5dj9uzZeP311zFz5sygTNThdDrhcDjw+uuvm743gj2jpaf3n6eQXzFMjmGH8XlXb+vxxx/XhWFm63bZZZdh6NChWLJkCX766Sc899xzeO211/Dmm2/i6KOPRlFREcaPH4+UlBTceOONaNu2LerXr49169bhySef1H2up06dilGjRuHbb7/F8uXL8fDDD+PVV1/F/PnzfQZi8fHxlg4qmDFOcBAJDz30kGu8wN69eyM1NRUOh0M3PiAgqkW/+eYb13P0f//3f3jzzTfxwAMPYMyYMRF8BEREdUtMh2hlZWXIycnBeeedhxtuuMGv23jkkUfw008/4c4770R2djYKCwt9zs5DRBQLWrVqhVWrVrkFM2q1kBVt27bFypUr0bdvX0s78b1790bv3r1xyy23YPHixbj99tvx+eefY8yYMcjKysLKlStRUlKiqzhSW4aysrJc58XFxbnaf6ZNm4ZXXnkFzzzzDFatWuVzZ2z79u1u523btg0NGzZ0hX4NGzbEf//953a9f//9F3FxcaaVTqHw/PPPY+vWrZgyZQqefPJJPPXUU7j77rvdrheux+Sp5fK7775DZWUlXn75ZV3bk7FNTq1y3Lx5s2kFkSd23htWNG7cGMnJyXA6nZZ23pOSknDGGWfgjDPOQGVlJSZPnoxXXnkFV199dUABqlp9lJKS4nM97AyGDojH6O9rbme9PCksLMTKlSsxefJk3Tacp1a2Zs2aYdy4cRg3bhwOHDiAUaNG4ZVXXvEYojVu3BgNGjQwfe8bH3Pbtm2hKApat25tWpkXbbZv3w5FUXSvufq8+Xqvq69dZmampdeubdu2uOKKK3DFFVdg27ZtOPfcc/HGG2/gySefxC+//OKqJjz22GNdf2OcdVKlzhp73XXX4ffff8fYsWMxb9481wD8gZArSVWVlZVu7a2q7du3u2bCBYDS0lLk5+fjxBNPtHyf6nP5zz//eL3eV199hXPPPVc3S2hFRYXpzKQZGRk477zzcN5556G0tBTjx4/HzJkzGaIREQVRTI+JNmTIENxyyy26cSFklZWVeOyxx3DCCSegd+/eGDNmjG6DfevWrZg3bx5eeuklnHLKKWjTpg26d+/OGXCIiAAMHjwYVVVVmD9/vus8p9OJd9991/JtnH766aipqcFLL73kdll1dbVrp6ewsNCt2kKtcKmsrAQAnHjiiaipqXG7/7lz58LhcLh2fg4dOuR2X8bb8mbNmjW68Zj27NmDb7/9FoMGDUJ8fDzi4+MxaNAgfPvtt7qdxf379+PTTz/FMccc49ZWGAp//vkn3njjDVx66aW44oorMHHiRLzzzjuuyrRIPCY1bDXuHKrVLcY2pgULFuiuN3jwYCQnJ+PVV19FRUWF7jJv1ThW3xtWxcfHY8SIEfjqq69Md5DlGRgPHjyouywxMRGdOnWCoigex/ezqnv37mjbti3eeOMNlJaWel0PT8+9J4G85nbWy9v9m3nzzTd1p2tqatweU2ZmJpo1a+b18xwfH4/BgwdjyZIl2L17t+v8rVu34qefftJd99RTT0V8fDxeeOEFt/eZoihur3Gk7du3TzdzcUlJCT766CN07drVtLpMdsIJJyAlJQWvvvqq6ftTbu82fgbbtm2L5ORk1/OuVs7Jz1llZSXee+893d+VlJSgurpad152djbi4uIsfSdb0aZNG/z666+68+bPn++xEu2DDz7QPf558+ahurra1ndF48aNceyxx2LBggW69xigf07M3utvv/2227oZ32fJyclo27Zt0J4jIiISYroSzZcHH3wQW7ZswTPPPINmzZrhm2++wZVXXonFixejffv2+O6779C6dWssXboUV155JQBgwIABuOOOO/yeMpuIqK4YNmwYevbsicceeww7duxAx44d8d1337mqda1Uvhx33HG48MIL8eqrr2LDhg0YNGgQ6tWrh23btuHLL7/EXXfdhdNOOw2LFi3CvHnzMGzYMLRt2xalpaWYP38+UlJSXDs1Q4cOxfHHH49nnnkGubm5yMnJwfLly/Htt9/i0ksvdVUxvfjii/j1118xZMgQZGVl4cCBA3jvvffQokULS+NUZWdnY+LEiZgwYQISExMxb948AMDkyZNd17n55puxYsUKXHzxxbj44osRHx+PDz74AJWVlbjjjjtsP9dG69evx8cff+x2ftu2bdGnTx9UVFRgypQpaNeunauKY/Lkyfj+++8xbdo0LF68WNeCFq7H1K1bNwDAM888gzPOOAP16tXDySef7Hrdr7nmGlx00UUoLS3Fhx9+iMzMTF2lSEpKCqZNm4a7774b559/Ps466yykpaVh48aNKC8vx2OPPWZ6v1bfG3bcdtttWLVqFS644AKMGTMGnTt3RmFhIdatW4eVK1e6wsqJEyeiSZMm6Nu3LzIzM/Hvv//inXfewZAhQwIOU+Pi4vDwww/jqquuwllnnYXRo0ejefPmyMvLw6pVq5CSkuIaK8rTc++tFdHf19zOenmSkpKCY489FrNmzUJVVRWaN2+O5cuXu1UxlZaWYsiQIRgxYgS6dOmCpKQkrFixAmvXrtVV9piZPHkyli1bhnHjxmHs2LGoqanBO++8g86dO2PTpk2u67Vt2xY333wznnrqKeTm5mLYsGFITk7Grl27sGTJElxwwQWYOHGi1/sCxAQXavWjrG/fvl7Hb7Orffv2uOuuu7B27VpkZmZiwYIFOHDgAGbMmOHzb1NSUnD//ffjzjvvxOjRo3HGGWegcePG2L17N3744Qf07dsX9957L7Zt24bLLrsMp512Gjp37oz4+HgsWbIE+/fvx5lnnglATFiSnp6OqVOnYsKECXA4HPj444/dgsiff/4ZDz74IE477TS0b98eNTU1+Pjjj11hdTCMGTMG9913HyZPnoyBAwdi48aN+Omnn9CoUSPT61dVVeGyyy7D6aefjv/++w/vvfcejjnmGJxyyim27vfuu+/G2LFjMWrUKFx44YVo3bo1cnNzsXTpUtd3+EknnYSPP/4YKSkp6Ny5M/744w+sWLHCbV/jzDPPxHHHHYdu3bohIyMDa9euxVdffYXx48f79ZwQEZE5hmge7N69GwsXLsT333+P5s2bAxAbusuWLcPChQtx6623YufOndi9eze+/PJLPP7446ipqcGMGTNw44034q233orwIyAiiqz4+Hi8+uqreOSRR7Bo0SLExcVh+PDhuP766zF27FjLbWoPPvggunfvjvfffx/PPPMM4uPjkZWVhZEjR6Jv374ARNi2du1afP7559i/fz9SU1PRs2dPPPnkk66dz7i4OLz88st4/vnn8fnnn2PhwoXIysrCnXfeiSuuuMJ1f0OHDkVubi4WLFiAgwcPolGjRjjuuOMwefJkS4NYH3vssa6Z33bv3o3OnTtjxowZusGdjzrqKLz77rt46qmn8Oqrr0JRFPTs2RNPPPGEa3bBQHz66af49NNP3c4fNWoU+vTpg6effho7duzA+++/73odEhMT8eijj+LCCy/E448/jvvvvz/sj6lnz5646aab8P7772PZsmVwOp349ttv0bFjRzz//PN49tln8dhjj6FJkyYYO3YsGjdujOnTp+tuY8yYMcjMzMRrr72Gl156CQkJCejYsSMuu+wyj/dr9b1hR5MmTfDhhx/ixRdfxDfffIN58+YhIyMDnTt3xu233+663oUXXojFixdjzpw5KCsrQ4sWLTBhwgRcd911ft2v0fHHH48PPvgAL730Et555x2UlZWhadOm6NmzJy688ELX9Tw9995CtEBec6vr5c1TTz2Fhx56CO+99x4URcGgQYPw+uuv44QTTnBdp0GDBhg7diyWL1+Or7/+GoqioG3btrjvvvtw8cUXe739Ll26YPbs2ZgxYwaef/55tGjRApMnT0Z+fr4uRAOASZMmoX379pg7d65r1scWLVpg0KBBGDp0qKXH8/zzz5ueP2PGjKCHaPfccw8ef/xx/Pfff2jdujWeeeYZ3fPmzdlnn41mzZrhtddew+zZs1FZWYnmzZujX79+GD16NADx2M8880ysXLkSn3zyCeLj49GxY0c8++yzruCrUaNGeOWVV/DYY4/h2WefRVpaGkaOHIkBAwboQsecnBwMHjwY33//PfLy8tCwYUPk5OTg9ddfR+/evYPynFxwwQXYtWsX/u///g/Lli3DMcccgzlz5nj83rj33nuxePFiPP/886iqqsKZZ56Ju+++23ZbdJcuXTB//nw899xzmDdvHioqKtCqVSucfvrpruvcddddiIuLw+LFi1FRUYG+fftizpw5rgP4qgkTJuC7777D8uXLUVlZiVatWuHmm2+2FOASEZF1DiWQ0UbrkJycHN3EAkuXLsXVV1/ttvFYWVmJ4cOH49lnn8U999yD+fPn48svv3SNgbFu3TqMHj0aX3zxBTp27Bj2x0FEFO2WLFmC66+/3nXkvi7JycnBuHHjcO+990Z6VYKmLj4molg1dOhQHHXUUXj11VcjvSpERES1EivRPCgrK0N8fDwWLFjgNhaBGqw1bdoUCQkJukFkO3XqBECMF8MQjYhiXXl5uW5CgJqaGrz99ttISUlxtY8RERERERHVBgzRPOjatStqampQUFCAfv36mV6nb9++qK6uxo4dO1zjpaizG8mzhxERxaqHHnoI5eXl6NOnDyorK/H1119jzZo1uPXWWy3NtklERERERBQtYjpEKy0txY4dO1ynd+3ahQ0bNiA9PR0dOnTA2WefjTvvvBNTp05F165dcfDgQaxcuRI5OTk46aSTMHDgQHTr1g3Tp0/H9OnT4XQ68eCDD2LQoEG1YopzIqJQ69+/P+bMmYOlS5eioqIC7dq1wz333MOBjomIiIiIqNaJ6THRVq1ahUsuucTt/FGjRuHRRx9FVVUVXn75ZXz00UfYt28fMjIy0Lt3b0yePBk5OTkAgLy8PDz88MP46aefkJSUhBNPPBFTpkzh7JxERERERERERHVITIdoREREREREREREVsRFegWIiIiIiIiIiIiiHUM0IiIiIiIiIiIiH2JuYgGn04nq6mrExcXB4XBEenWIiIiIiIiIiCiCFEWB0+lEQkIC4uI815vFXIhWXV2NtWvXRno1iIiIiIiIiIgoivTo0QOJiYkeL4+5EE1NFHv06IH4+PgIrw35oigKioqKkJaWxspBohDh54woPPhZIwoPftaIwoOfNapLampqsHbtWq9VaEAMhmjqhzs+Pp4hWi2gKAri4uIQHx/PL2aiEOHnjCg8+FkjCg9+1ojCg581qot8vZc5sQAREREREREREZEPDNGIiIiIiIiIiIh8YIhGRERERERERETkA0M0IiIiIiIiIiIiHxiiERERERERERER+cAQjYiIiIiIiIiIyAeGaERERERERERERD4wRCMiIiIiIiIiIvKBIRoREREREREREZEPDNGIiIiIiIiIiIh8YIhGRERERERERETkA0M0IiIiIiIiIiIiHxiiERERERERERER+cAQjYiIiIiIiIiIyAeGaERERERERERERD4wRCMiIiIiIiIiIvKBIRoREVGsKiwEpk8H5s6N9JoQEREREUW9hEivABEREUXIrFnAjBliecAAICcnsutDRERERBTFWIlGREQUq3bs0JbXr4/cehARERER1QIM0YiIiGJVZaW2vHt35NaDiIiIiKgWYIhGREQUq+QQLTc3cutBRERERFQLMEQjIiKKVaxEIyIiIiKyjCEaERFRrGKIRkRERERkGUM0IiKiWFVVpS2znZOIiIiIyCuGaERERLGKlWhERERERJYxRCMiIopVcoh26BBQVhaxVSEiIiIiinYM0YiIiGKVHKIBrEYjIiIiIvKCIRoREVGsYohGRERERGQZQzQiIqJYJU8sAHByASIiIiIiLxiiERERxSpWohERERERWcYQjYiIKFYxRCMiIiIisowhGhERUawyhmhs5yQiIiIi8oghGhERUaxiJRoRERERkWUM0YiIiGKVcWIBhmhERERERB4xRCMiIopVZu2cihKZdSEiIiIiinIM0YiIiGKVMUQrLwcOHYrIqhARERERRTuGaERERLHKGKIBbOkkIiIiIvKAIRoREVEsUhT3MdEAztBJREREROQBQzQiIqJYVF1tfj4r0YiIiIiITDFEIyIiikVmrZwAQzQiIiIiIg8YohEREcUiOURr3FhbZjsnEREREZEphmhERESxSA7ROnTQllmJRkRERERkiiEaERFRLJJDtDZtAIdDLDNEIyIiIiIyxRCNiIgoFskhWlIS0Ly5WGY7JxERERGRKYZoREREsaiqSltOTARatRLLe/cCNTWRWSciIiIioijGEI2IiCgWyZVocohWUwPs2xeZdSIiIiIiimIM0YiIiGKRMUTLytJOc1w0IiIiIiI3DNGIiIhikadKNIAhGhERERGRCYZoREREsUgO0erV04donFyAiIiIiMgNQzQiIqJYZJxYgO2cREREREReMUQjIiKKRWznJCIiIiKyhSEaERFRLPIWorGdk4iIiIjIDUM0IiKiWGQM0Zo0EWOjAaxEIyIiIiIywRCNiCjWvfYaUgcMAP7v/yK9JhROxokFHA6tGo0hGhERERGRG4ZoRESx7t57Eb9xI/Dww5FeEwon48QCgDa5wP79QEVF+NeJiIiIiCiKMUQjIopligIcOCCW1f8pNhjbOQH9uGh79oR3fYiIiIiIohxDNCKiWFZRAUdNjVguLY3sulB4+QrR2NJJRERERKTDEI2IKJbJwRlDtNhiFqKp7ZwAZ+gkIiIiIjKIaIi2evVqXHPNNRg8eDBycnKwZMkSr9f/+uuvcfnll6N///7o27cvLrzwQixbtixMa0tEVAdJwZmjqko/ThbVbaxEIyIiIiKyJaIhWllZGXJycnDfffdZuv7q1asxcOBAvPbaa1i4cCGOP/54XHvttVi/fn2I15SIqI4qKdGfZjVa7JAD03r1xP8M0YiIiIiIPEqI5J0PGTIEQ4YMsXz9u+66S3f61ltvxbfffovvvvsORx99dLBXj4io7jOGZmVlQEZGRFaFwoztnEREREREttTqMdGcTidKS0uRwR0+IiL/GEM0VqLFDrZzEhERERHZEtFKtEDNnj0bZWVlOP30023/raIoUBQlBGtFwaS+TnytiEKkuBgO6aRSUgLw8xYbKipcr71Sr5543VNSgJQUOEpKoOTm8r0QZPxNIwoPftaIwoOfNapLrL6Pa22ItnjxYrz44ot46aWXkJmZafvvi4qKEBdXqwvxYoKiKCgrKwMAOBwOH9cmIrvq5ecjWTpdkpeHmsLCiK0PhU/DkhLUP7JcUlnpet1TmzVDfEkJlLw8FPG9EFT8TSMKD37WiMKDnzWqS5xOp6Xr1coQ7bPPPsPdd9+N5557DgMHDvTrNtLS0hAfHx/kNaNgU9Pg9PR0fjEThYLhiEuKwwGkp0doZShSUho10l735s2Bf/9FXGEh0pOStEkHKGD8TSMKD37WiMKDnzWqS2pqaixdr9aFaJ9++immT5+Op59+GieddJLft+NwOPhBryXU14qvF1EIGMZAc5SVAfysxYbqateio3597XVv2lQ7/8ABoGXLcK9ZncbfNKLw4GeNKDz4WaO6wup7OKIhWmlpKXbs2OE6vWvXLmzYsAHp6elo1aoVnnrqKeTl5eHxxx8HIFo4p06diunTp6NXr17Iz88HADRo0ACpqakReQxERLUaJxaIXWYTCwC6EA379jFEIyIiIiI6IqIh2t9//41LLrnEdXrGjBkAgFGjRuHRRx9Ffn4+9uzZ47p8/vz5qK6uxoMPPogHH3zQdb56fSIisokhWuzyFKI1a6YtHzlYRUREREREEQ7Rjj/+eGzatMnj5cZg7O233w71KhERxZaSEv1phmixw0olGkM0IiIiIiIXTk9JRBTLWIkWu+QQTZ48gCEaEREREZEphmhERLHMGJodmaacYkBVlbbsbUw0IiIiIiICwBCNiCi2sZ0zdnmqROOYaEREREREphiiERHFMrZzxi41RIuPF/9UbOckIiIiIjLFEI2IKJaxEi12qSGa3MoJMEQjIiIiIvKAIRoRUSxjJVrdVVkJfPYZsGuX58sB9xCtfn0gNVUsexoTbeVKYMQIgLNmExEREVEMYYhGRBTLGKLVXY89Bpx1FtC/v34SAZV6njwemkodF81TJdpddwFffw1cfz3gdAZnfYmIiIiIohxDNCKiWMZ2zrprxQrxf24usGeP++WeKtEAraXz4EHzAO6ff8T/xcXiHxERERFRDGCIRkQUy1iJVncdOqQtl5e7X24lRAOAAwf0l1VX60O5wkK/V5GIiIiIqDZhiEZEFKtqaoDDh/XnMUSrO+QQzfg6A9ZDNOO4aLt361s4GaIRERERUYxgiEZEFKvKyqydR7WTHG7ZrURTx0QD3MdFM05UIId1RERERER1GEM0IqJYZVZ1xkq0usNXJZq3iQXkSjRjiLZzp/40K9GIiIiIKEYwRCMiilVmgVlZGaAo4V+XusKs4isSKiv1wZlxvRTFejsnQzQiIiIiIgAM0YiIYpdxZk5AhCtmVUvk20UXAenpwDvvRHpN3IMt42taXa0t2x0TjSEaEREREcUohmhERLHKU+smWzrtO3gQ+OADUd310kuRXhv3ccqMlWhqFRoQ+JhoDNGIiIiIKEYwRCMiilUM0YLnwAFtedOmyK2HyhiiGSvRfIVobOckIiIiInLDEI2IKFaZtXMCDNH8cfCgtlxQAOzfH7l1AexVonFiASIiIiIiSxiiERHFKiksU+LiTM8ni+QQDYh8NZqvMdHUmTkB80q0Bg2AlBSxLI+JVlkJ5OV5vy8iIiIiojqKIRoRUaySQ7TMTNPzySJjiLZxY2TWQxXomGiANi6aXIm2e7f77K0M0YiIiIgoRjBEIyKKVVI7p9KkiXY+QzT7oq0SLdAx0QCtpbOgQJvN09jKCTBEIyIiIqKYwRCNiChWSWGZUx4Dq6wsAitTyxlDq0iHaMZgy59KNPk9oU6cwBCNiIiIiGIYQzQiolglt3PKgQkr0eyL9nZOb5VoZhMLAOaTC5iFaMb7IiIiIiKqoxiiERHFKrmdkyFaYIwh2r//6gfvDzdfY6L5mlgA0MZEA7TJBXbtcr8eK9GIiIiIKEYwRCMiilVyOyfHRAuMMUSrrhZBmhnjwPyhEMwx0QDzSrSsLPF/cTFQU+PXahIRERER1SYM0YiIYpXczilXHTFEs88YogHmLZ1vvw1kZAC33hra9Qn2mGjGEC0uDujSRbu8uNi/9SQiIiIiqkUYohERxSqpnZOVaAEyC9HMJhd46CGgqAh47jmgoiJ06xPqSrRWrYDGjbXL2dJJRERERDGAIRoRUazixALBYyVE27MH2LxZLDudwP79oVsfX2OiWQnRjGOilZdrYVqbNkB6unY5QzQiIiIiigEM0YiIYtWRsExJSICSkeF2PtmghmgtWmjnGds5ly3Tn1YH6w8FY6hlrESTJxawOjtnbq52miEaEREREcUghmhERLFKbedMTobSsKF2PkM0e5xOLURq00YbcN9Yifbjj/rToQrRampEy6gsGGOiyZMKtG7NEI2IiIiIYg5DNCKiWKWGZSkpQHKy+/lkTVGRNuNmo0ZATo5YPnBA/FOFK0QzBmiAf2OiNWyovS+MIRor0YiIiIgoBjFEIyKKVWpYlpwMJSlJO7+sLDLrU1vJ46HJIRqgVaMVFABr1+r/LlQhmnE8NMC/SjRAGxdt3z5g1y7tfIZoRERERBSDGKIREcUqqZ0TiYlQEhLEaVai2SOHaBkZQJcu2ml1XLSffnL/u7y80KyPWaDlTyUaoLV0FhQA27Zp57dpIx6ryiy4IyIiIiKqYxiiERHFospKoLpaLKekiP/V1j2GaPZYqUQztnICka1EszKxAKCFaIoC/Pmndj7HRCMiIiKiGMQQjYgoFslBmRqeMUTzT20I0QKtRAO0EC0hAWjenCEaEREREcUchmhERLFIbeUEGKIFyhiitW0LNGggTm/cCBQXA7//Lk536QLEHfnpDVWIZhZoVVdrlYeA/THRAK2aLSsLiI9niEZEREREMYchGhFRLJKDMrZzBsYYosXFAdnZ4vTWraIKraZGnD75ZKBJE7Eczko0QN/S6U8lmqpNG/E/QzQiIiIiijEM0YiIYpEclKkzc6ohWlWVfsws8k4OrRo1Ev+rLZ3V1cCbb2qXn3iifsZLRQnt+sTHa8vBCtFatxb/p6Vp5zFEIyIiIqIYwBCNiCgWeWvnBFiNZoexEg3Qj4v20Ufa8gknaCFaRYVo9Qw2OURr3lxblsdFszuxgEytRKtXTwtgGaIRERERUQxgiEZEFIvM2jnVQMR4OXnnK0RTA6tOncR4YnKwFYqWTjnQatFCW5ZDNH/GRFOpIRqgtXQyRCMiIiKiGMAQjYgoFnmbndN4OXlnFqJ16eJ+vRNPFP/LwVQoQjS5Eq1lS2052GOiAQzRiIiIiCimMEQjIopFZu2cciVaWVl416c2U0M0h0MbJ0ydWEAWSIi2fTvw1Vf6GTY9kUO0QCvRvI2JBmghWnGxNnkCEREREVEdxRCNiCgWeZud03g5eaeGaOnpYmZOQIRpchUY4H+IVloKHHMMcNppwAsv+L6+WhWWkAA0bqyd708lWlKSPlwF9JVoGRnacijGdyMiIiIiiiIM0YiIYhHbOYNHDdHUVk6V3NKZlQV06CCW7YZomzYBBw6I5e++8319tRItIwNo2FA731MlmreJBQD9+iYm6qvT1Eo0+X6JiIiIiOoohmhEROFUUgI89xzw/feRXw8VQzT/KYoWHhlDNHlygRNPFO2egP0QraBAW96xw/f11fVJT9eHaHIlmjw7p7dKNEAfmrVurVXbqfeh4rhoRERERFTHJUR6BYiIYsrTTwP33QfUrw/s3Gk+5lQ4sJ0zOEpKtLHAjCFat27astrKCdgP0dQqNMB3iKYoWpiVkQE0aKBd5s+YaIB7iCZjiEZEREREMYQhGhFROP32m/i/ogLYuDFyIRor0YLDbGZO1YQJwEcficD0kku08wOpRDt4UIw9lppqft3SUi3UM7Zz+jMmGqB/j8rjoQEM0YiIiIgopjBEIyIKp127tOW8vMitB8dECw5vIVp6OrBkifvfJCeLcOvwYfuVaICoRpOr3GTyuGRWK9HsjInGEI2IiIiIYhhDNCKicJJDtL17I7cewWjn/OILEZxceKE23le0q6kB3nxThFc5OWLw/06dfFdjeeItRPPE4RDB1Pbt9ivRAOshmrcx0dQQLT5e/POGlWhERERERAAYohERhU9lpT40iWQlmrGd0+m0F6KtXg2ccYZYLi4Grroq+OsYCm+/DUycqD8vPh4YNAiYPx9o3tze7ckhWkaG9b9TQ7T9+0Ww5y3IMlaibd/u+bpykOWtEk2dWMBXFRoADB8ugr+4OLEsY4hGRERERDGEs3MSEYXL7t3609FSiZaUpP8fAMrKvP/94sXa8hNPiBCuNlixwv28mhrgxx+B996zf3v+VKIBWoukoriHZEZmlWieGNs5fVWiWanA690b2LoV2LYNOOoo/WUM0YiIiIgohjBEIyIKl9xc/eloCNEaNtSqoOxUoi1dqi1v3gx89llQVy9k5CquqVOB007TTsuttlYFGqIBvls6zcZE88TYzulrTDSrbawdOrjPzKneh4ohGhERERHVcQzRiIjCxRjSREM7pxycWQ3RDh8GVq3Sn/fss0FbtZBSQ7SkJOB//9Ovtz+vhxxahSpEi3QlmjdyCytDNCIiIiKq4xiiERGFizFEi4ZKNH9CtJ9/1s/uCADffQf8+Wfw1i8UFEULoNq10wb4V1kZ5N8oHJVoxhAtGGOiBStEYyUaEREREcUQhmhEROFibOfMyxPBTiSoIZk6MydgPUT74QdteeBAbTnaq9Hy87UgqV078X9Ghja4fjSGaIriHqLl5gLV1ebXtzo7p52JBbxJSzO/byIiIiKiOoghGhFRuBgr0SorIxM8OJ3mlWhy4OItRJPHQ5s1S2vpe++9yLao+iJXcKkhmlyNFo0hWlGRmPhAVlMD7Nljfn1jO2eoK9ESErT3ECvRiIiIiKiOY4hGRBQuZgPXR6KlUw5T5BAtLk6bodNTiFZeLto5ATHYfNeuwFVXidOVlcDLLwd/fYPFLEQDtEArP9/+LKNyiCa3NvpiNUTzNHOnp3HRjO2coR4TDdAeN0M0IiIiIqrjIhqirV69Gtdccw0GDx6MnJwcLFmyxOffrFq1CqNGjUL37t0xfPhwLFy4MAxrSkQUBMZ2TiAylVtyQCa3cwJaqOYpRFu1CqioEMtDhoj/J0/WZvh86SV9WBNNfIVo1dX2KwPVEC01VVRlWWU1RJNbOR0ObdnTuGjeJhZQw1NFYYhGREREROSHiIZoZWVlyMnJwX333Wfp+jt37sTVV1+N448/Hh9//DEuvfRS3H333Vi2bFmI15SIKEBOJ7B7t/v5kahEU2fmBPSVaPJpTyGa3Mp50kni/zZtgPPPF8v5+cC8ecFYy+CTg6f27bXlQCYXUEM0O62cANCkibX7lCvRcnK0ZU+VaGqI5nCIYK9+fe0yNdyUx1MLZohWUuLeekpEREREVIdENEQbMmQIbrnlFgwfPtzS9d9//320bt0aU6dORadOnTB+/HiMGDECc+fODe2KEhEFat8+88HgIxGiyQGZ3RBNnlRArUQDgJtv1pZfeCGg1QsZX5VogL3KQEXxP0RLTNT+xmolWu/e2rKvEC0tTbTnxsVpQZpaiaZOKgAEPrEAoG9jLSoK/PaIiIiIiKKUjd6TyPvjjz8wYMAA3XmDBw/G//73P9u3pSgKlEjNikeWqa8TXyuq9XbuhNqMp3TuDMeWLWJ5797wz9BZUqKtS3Ky/nOWlCQuKyuD4nTqWwgrKoCVK+EAoLRrJ4Iodd2PPx7o2hWODRug/PmnqLyT/zYabN8u1r1ePaBFC23dmzbVng87M6aWlcFxJJBSGjWy/zo2awbHwYNQ9u3z/Lf792vr1rs3HO+/L5Z37DD/m8JC8RgzMrTLGzSAo6ICSnm5OK+iQrvNxMTA33/p6drtHTqkTTRBbvibRhQe/KwRhQc/a1SXWH0f16oQbf/+/Wgit8AAaNKkCUpKSlBeXo4G8ixkPhQVFSEujvMqRDtFUVBWVgYAcETbDjmRDfX++QdqzVdVjx5IPBKiVe7cicNhHksqIS8P6khoFQkJOFxY6PqcpdSvD7U2qXDvXm2iAQDxK1Yg9UhLYNXAgSgzrHdyixaot2EDHDU1OLRzp72B9sMg/b//AADOrCwUFxe7zq+XluZ6bQ5v345Ki6+HY/duqI+wKiXF7fnwJaVxYyQAcBQX49Devfrxy46ov2cP1HNL27ZFcv36cFRUwPnvvyg2ub/0I5VozpQU1+VpDRrAUVgIpbQURYWFcOzf71rvaocDpQG+/xo2bAi1abR41y447VblxRD+phGFBz9rROHBzxrVJU6LE4zVqhAtmNLS0hCvDoRNUUtNg9PT0/nFTLWbNItjvQEDgEWLAACJBw8iMYJhU/3GjV33n56eDoe0LukJCfog7NdfXYv1hg1DunG9pbbI9Jqa6ArRCgvhONJqGNehg37dpdbOhsXFaGh1vXfudC3Wa9rU/fnwpVUr12J6ZaWojjOSxq9LbtdOjD+3ZQvicnPd76+8HI4jkz7EZWZqlx8J5xyVleI8KUBMSE62v95G0sGtVKczul73KMPfNKLw4GeNKDz4WaO6pMbi2L61KkRr0qQJ9u/frztv//79SElJsVWFBoiknB/02kF9rfh6Ua0mzczp6NVLzGZZUwPH3r3hb3s8csQQABypqYD0GXNIY6Q5ysr06/bjj9plJ5/svt6NG2uXFxQAHTsGf939JY0h5mjXTr/uzZtrl+XnW389pJkwHY0b238dpdDRkZ+vH6dNJYWvjsxMoG1bYMsWEQgWFXkcj8yRkaGtjxqiHT4szpPGRHMkJgb+/pMqzxxFRdHXxhtl+JtGFB78rBGFBz9rVFdYfQ/Xqn7G3r174+eff9adt2LFCvSWB1smIopGu3Zpy23aaMFNtM7OCegnF6isBFasEMtt2+pnt1RlZmrL8oD40cDTpAKA/7NzSgGX7YkFrN6v/DyqIZpKfkyALtTTjUumHmRSZ+esrNQuC/bEAvI6EBERERHVMREN0UpLS7FhwwZs2LABALBr1y5s2LABu3fvBgA89dRTuPPOO13Xv+iii7Bz5048/vjj2Lp1K95991188cUXuOyyyyKx+kRE1kmVaMjK0lr39u0Tg/CHk5XZOY3XW71am91xyBDzaiOpEq1WhWhNm2rL/oZo/gymbyVEO3BAfx/yuhtn6JQDLDnYUsdaq6oCamr0s3MmJtpZY3PyfYV5fD8iIiIionCKaDvn33//jUsuucR1esaMGQCAUaNG4dFHH0V+fj727NnjurxNmzZ49dVXMWPGDLz11lto0aIFHn74YZxwwglhX3ciIlvUSrTUVCAtTatEq6kRQYkc5ISaHI6lpOgv8xSiLV2qLZ90kvntyiGaHP5EA28hWoMG4jUpKoreSrT0dCAhQV+J5i1EM6tEA0Q1mlyJxhCNiIiIiMiyiIZoxx9/PDZt2uTx8kcffdT0bz766KMQrhURUZApilaJ1rq1+F8eRH7v3vCGaP60c/7wg7Y8ZIj57dbWdk5ABFpFRUBenvXbDEeIpoaR6nPrLUSTAyw5RJNn/Tx8mCEaEREREZGfatWYaEREtdKhQ9pg/llZ4n85RLMT3ASD3XZOpxNYuVIsZ2V5njCgNlSiORxiTDojtTKwsBA4MsOlT3LlVyhCNKdTC+rU59bqmGhysMVKNCIiIiKioGCIRkQUavKkAmolmjQjZNgnF7Dbzrlzp1a91rev59kXa8OYaC1bmgdHcqCVn2/tNkNdiXbokKhiBLRKNDkAtNrOyUo0IiIiIqKgYIhGRBRqxkkFgMhWollt51Sr59av1847+mjPtxut7Zzl5dpzbNbKCfg3Q2egIVpGhhjnzNN9ys+hGlA2bKitq9V2TmMlmjyxQLBn52SIRkRERER1GEM0IqJQM6tEM46JFk7e2jmTktyvd2QGZQBA166eb1cOkqKpnVMOm6IpRIuL08bCM7tP+TmUA0q1pXP3bn0gFqlKtLQ0bZkhGhERERHVYQzRiIhCTa5Eq43tnHKI5q0SLSFBC1TsVKJddZWoZnrvPet/Y4evSQWAwEK05GT/K7rU+923T2vdVJlVogFaiOZ06t9bkRoTLSFBe98wRCMiIiKiOowhGhFRqMmVaNHUzhkXB9Svr7/MLEST2zm7dPF+22rFlNUQrbAQmDVLzIw5aZL7YPnBIN9m+/bm1wkkRJOrvuxS77eqyj2Akp9DuRJNDgLlKrtIVaLJ98cQjYiIiIjqMIZoRETBsmYNMHIkMHeu/nyzds70dC3AilQlWnKy+yQBxhBNUbRKtNatgdRU77etVkwVFIhKKV/kQfxLS4HrrnOvyArUtm3aspVKNKuhphqi+dPKaXa/xvBObuc0q0QD9CGaHGCFsxJNvj+GaERERERUhzFEIyIKlvvuAxYvBiZOFDNaqtSWu8REoEkTsexwaC2dkQrRjK2cgHuItm+fFhZ5a+VUqWGP0ymqy3wxjp32+efA++/7/js7rLRzyu21ZpVoU6YAw4ZpgWJ5ufgHhC5E81SJZhaiKYr290lJ+vZSYyVasCcWALQQraQEqK4Ozm0SEREREUUZhmhERMGiBmdOJzBnjna+WomWlaWv/FJbOvfvD2/woLZzGicVMJ5XWqpv5fQ2qYDK7gydZhMQ3HRTcCcmCHRMtD//BB5/HPj2W2D0aBGeya2TkaxEUx/b888DmzeL5Y4d9bcjV6KFqp1TrnyzEp4SEREREdVCDNGIiIJFDlZmzwZqaoCyMq2SS23lVKkhmqLo2xpDTW7nNDKGaFYnFVDJYY+VIEwO2tSZQfPzgdtu8/23VqlBU2am+WMGRBAWHy+WzUI01caNwD33BD4zp8pqJZr8vBrHRFu+HLj9du28Rx7R345ciRbqdk6ALZ1EREREVGcxRCMiChY5WNmxQ1QuybMnqpMKqOQWwnBNLlBVpYUoVto5w1mJ9sADWhjz5pvAkiW+/96X6mrtNfBUhQaISRaaNhXLxjBLfg4A4KmngE8/1U4HEqLJ7wH5vQLonxv5eW3SRKsuW7cOuOACrZJxyhQxLp8s3JVoDNGIiIiIqI5iiEZEFAw1Ne7hwaxZ5pMKqOQZOsM1LppahQaYV2XVq6eNk2WsRLMSoskVU3ZDtO7dgSee0E5PmiQq+QKRmyteG8B7iAZoVWH79uknN5CfA0Bcdtdd2ulAQrTsbG3ZGNapz5/DoQ+pHA6tpXPnTmD3brF80knAww+73wcr0YiIiIiIgoIhGhFRMJgFBx99BPzxh3baWyVatIRo8vllZVqA1LSpNimCN3bbOY3VVhMnAieeKE7/9x/wySe+b8MbK+OhqdQQrbJSP66XGm4lJQH9+4tleXD+QEK0jh21kGvtWv1l6nMjt5qq5HHRAKBlSzEhQ0KC+30YK9FCObEAwBCNiIiIiOoshmhERMEgt3KqqqpE65/KWyVauNo55RDNrJ0T0MYm27NH/AOsVaEBgbVzZmaKtso77tDO+/tva/friZ0Qzay9trwc+PdfsdylCzB3rj6UAgIL0eLjtbHmtmwRIZdKff7kYFIlP5aEBODDD/XrL2MlGhERERFRUDBEIyIKBjlEGzZMW5bHuYqGdk51Zk7AdyVacbF2ntUQzW47p9ng+fJ9bdxo7X498acSDdDGRfvnHzHbKiDCrpwc4H//0/9dRkZg69i9u/hfUbTKv+pqbaIKOZhU9emjLT/+ODBokOfb55hoRERERERBYdL3QUREtskh2nHHiSq0H37QXycaJhaw084pszIzJ+B/O2d8vBbEtG8vwp3KysiHaPI4ZepzcNNNwKJFwLJl4rQxHLWrRw9tee1aoG9f/UyvZpVoV14prpOVBVx6qffbN1aiycFZsEI0OUhkiEZEREREdRRDNCKiYJBDj0aNRMghh2hxcfrKM8B7JdrSpSKY6N07uOtppZ3TLEQLdTtn48ZiwHxABGpHHSVmnty8WUwMYBwTzKpAQzSziRXi4sT4Y7feCnToAPTq5d+6qdRKNEBrX5WfO7NKtPr19ZMbeGOsRJOxEo2IiIiIyDK2cxIRBYNcidaoEXDeefpgoXlz90HcU1K0wEoO0d57Dzj5ZFGRtGVLcNfTTjunzGolmlyRZCdEMwZFXbqI/ysrgW3brN23GTVES042r+iSWa1EA4BWrUSQNmOGFv75y1iJBuir+Hytty/hHhPNSgUiEREREVEtxBCNiCgYjCFaw4bA+PHaeZ5a/tSWTrWd0+kEHn5YLCsK8MsvwV1Pf9o5U1NFaGRFQoIWqPgKUyortVDPU4gG+N/SqSjAjh1iuV0732GXtxAtMVHMpBkKLVtqkxNYrUSzIxyzc7ZuLSr0AOCDD7TnnYiIiIioDmGIRkQUDHKIplZjXXWVdp6nAEZt6SwoACoqgK++0rcQqmFOsMiVaFbbObt2tVdtpYY+virRzCYVUOXkaMv+hmh5eaLyCvDdygm4h2hVVaKdFACys0VAGAoOh1aNlpsr3ku1rRItMxOYNEksl5YC114rQkwiIiIiojqEIRoRUTAYK9EAMVbWjBnA0KHAtGnmfyePi7ZvH/DMM/rLgx2i+VOJZrWVU6WGPgcPajNbmpGDolBUosmtmJ07+76+MUTbulWr2rL7HNhlHBfNW8BoVzhm5wSARx/VKhY//1y0uxIRERER1SEM0YiIgsEsRAOAqVOBb7/1PPi8PEPnkiXAN9/oL4+GEM3qpAIqNfRxOr0PMu8tRJMr0TZtsnf/qj/+0JatTNCQlKRV5+Xl6UM4u8+BXcYQzdtzY1dcnBaWhaoSDRBtvC++qJ2+6SaOj0ZEREREdQpDNCKiYPAUovkiV6Ldd5/75dHQzmm3CsvqDJ3egqK0NK2qyd9KtDVrtOU+faz9jVqNtm+fvq021JVoxskFglmJBmjVaKGsRAOAc88Vk2oAQH4+cNttwb19IiIiu/LzgbKySK8FEdURDNGIiILh0CHxf1ycGIjfKjlE27lT/C/PdBjsEE2eBdRTOJOUpD/tbyUa4D1E8xUUqdVo+fn+VTSplWgJCdZDMDVEKygA/vxTOz/UIVq3btpysCvRAG1ctPLy0EwsIJs5U3sPv/mme3UlERFRuPz0k5jAp0MHoKgo0mtDRHUAQzQiomBQK9EyMrRZCq2Q2zlVkyZpwUmwQzS1RTE+3vM4YXIlWv36QPv29u5DDsS8hV++giJ5XDS7LZ2HD2uVZN26icdhhTwu2o8/iv/j4oCjjrJ3/3Y1aqTN4Lp2bXAnFgDMK9Hi4sT7INhatgSeeEI7fc01QHV18O+HiIjIlw8/BGpqxPaU+rtORBQAhmhERMEgh2h2yJVogAg1Jk/WtxUGS02N1hrZubPnVj45ROvSxX7QEox2TvW+VXZbOv/+WzxewNp4aCo5RMvLE/937mw9hAuEOi7aoUNi/QHx3MuVif6SK9HUEC3YrZyyiROBQYPE8r//AuvWhe6+iIiIPPnvP22Z43QSURAwRCMiCpTTqbVz2hkPDXCvRBszBmjTRgtzSkv1kwEEYvt2EaIA3tsT5RDNnwH1rbZzhrISTZ5UwOp4aIA+RFOFelIBlTwumtp226gR4HAEfttmlWihDNHi4oAzztBO+zs5BBERUSC2bdOW9++P2GoQUd3BEI2IKFDFxSJIAwIP0W65Rfwvhzn5+f6vm8zqbJNydZynWUW9sdrOKQdsZiGaPEOn3Uo0fyYVAMzba0M9HppKnqFTFYzx0ACtEq2qSgtSQxmiAcGZYZWIiMhfisJKNCIKOoZoRESB8ndmTkCEG2qgNXQocNxxYtmsrTBQcojmLRg64QTguuuA888X41nZ5U87p9m4X23aaOFPICGanSDQrBItXCGaXImmCsZ4aIBWiQZoAyuHYlIBGUM0IiKKpIIC/azkDNGIKAgSIr0CRES1ntrKCdgP0QDg88+BL78UoZVKrogK1rho6kD7gPdKtLg44MUX/b8fuxMLNGyohWXG9cjJEa2ZW7eKNkQr1VM1NcBff4nljh3tjSkWyXbOLl3EY1arGoHgV6IBQGGh+D/UlWidO4tWVEVhiEZEROEnV6EBDNGIKChYiUZEFKhAKtEAMfvlNdcATZpo58lhTrBCNLUSzeHQjzcWbHbHRPMWFKnrWVMjBqi3YvNmoKxMLNtp5QTMQ7RQPleyhg3dZ0wNRSWaOlNmqEO0Bg20mV03bRJhGhERUbjI46EBDNGIKCgYohERBSrQEM1MsEM0RdEq0dq3B5KSAr9NT+TnwFOIpijWQjR/xkWTWzntzMwJuIdo7drpJ1oINWNLZ7BCNLNKv1CHaID2+hUXa5MlEBERhYOxEo0TCxBREDBEIyIKlByiZWQE5zaDHaLl5oogAwh9e2J8vPY8eDrqW1oqBrkHvAdFchWY1RDN35k5ARHoxUk/jeEaD01lnFwgWO2cciWaKpwhGsCWTiIiCi+2cxJRCDBEIyIKVG2oRLM6qUCwqMGYp0o0eUPWSjsn4F8lmt0QLT5e31Yb7hAtnJVooZ5YAGCIRkREkWPWzsmhBYgoQAzRiIgCVRtCNHlSgXAEQ2owdvCgfqB8ldUQLTtbW7YSwiiKVonWtCnQsqXvvzGSn/twTSqgYiUaERFRcBgr0SorRSV8rLvvPjEb/K+/RnpNiGolhmhERIEKRYiWlqaFHMGuRAtHMKRWUCmKfvZSldUQLSkJaNtWLG/c6PsI8u7dQH6+WO7TR0yiYJccooW7Eq1zZ6B+fe10XRkTDWCIRkRE4aMo7pVoAMdFy88HHnoIWL0aePrpSK8NUa3EEI2IKFBySBSsEM3h0MKc2hyiAeYtnfJ5vqqt1JbOQ4d8PxeBTCqg6ttX/N+okXt7ZajFx+uDu9peidaqFZCSIpYZohERUbjk5QHl5e7nx/q4aPv2aQck1YOORGQLQzQiokCFohIN0EK0/HzzlkirFEUL0Vq1AtLTA183X+TwxyxEkzdifVVb2RkXLZBJBVT33gu89BKwZIkWAIVT//7i/3r1tCq8QEWqEs3h0Fpy//sPqKgI/X0SERGZVaEBDNEKC7XloqLIrQdRLcYQjYgoUHKIFsyASg3Ramo8D9BvRX6+9vfhak+UgzGzDVar7ZyAPkTzVc0UyKQCqtRU4NprtYq0cLv3XuCGG4C33tJPchCISFWiAVpLp9MJbN0anvskIqLYJo+H1qqVtswQTVtWZ20nIlsYohERBUoN0dLSRDtesDRvri0H0tIZ7pk5Ad/tnHZCNHlcLV+VaGqIlpQkxherjVq0AGbOBC66KHi3GanZOQGOi0ZEROEnh2jHHKMtx/qYaAzRKBgOHgSGDQPOOy8mJ+tgiEZEFCg1RAtmKycQvBk65Zk5wzXbpJ12TjuVaN5CtEOHtI3mXr2CG2jWdtFQiQYwRCMiovCQ2zn79dOWY70STR7Hl+2c5K8XXwS+/RZYuFDfBRIjGKIREQVCUaI/RIt0JZrZBqudiQVathQtloD3EObPP7Vlf1s566pIjYkGMEQjIqLwkyvRjj1WW471EE2uRCsp8T3rOZGZFSu0ZbldOkYwRCMiCkRpKVBdLZYZomnstHNmZHi/LYcD6NhRLO/YIcaIMxOMmTnrqkhWoqkTCwAM0YiIKDzUSrTUVOCoo7TzGaJpy04nUFYWuXWh2snpBH7+WSw3awZ06BDZ9YkAhmhERIGQy+KjNURT2zmbNAneQPW+WG3nzMgAEhJ83576A11dDeTmml8nGDNz1lWRrERLTgZatxbLDNGIiCjUamqA7dvFcvv2+m0SjommP81x0ciuzZu1Lpz+/cXB7hjDEI2IKBDyzJzRGKIdPAjs2SOWw1WFBlifndNXK6dKPsolt2jI1q4V/8fFAd27W7vdWGFWiRauiQUAraWzoIA7MEREFFp79gBVVWK5Qwcxc7o6TmqsV6LJB38BjotG9qlVaIAI0WIQQzQiokDIIZqvtkS7ghGiRWJSAUA8F+qRKWMlWk2NthFnNURr315bNgvRFAXYskUst2tnHhrFskhWogEcF42IiMJH3k5o314cXFMP7sV6iMZKNArUypXaMkM0IiKyLZSVaE2basvBCNHCWYkWH6+FisYQ7dAhbSBbuWLNG1+VaAUF2tHUTp3srGlsiOSYaABDNCIiCh95O0HdflAP2jFE059miEZ2qZVocXH6STtiiIWBaNwVFBQgNzcXDocDWVlZaBTsHUciotoilCFa/fqiBaGwEMjL8+82IjGpgKpxY/H8GDdY5dP+tHPK09ar/v1XW1YnISANK9GIiChWyNsJaiW7ur1RUgJUVIhtrFhkDNHYzkl2lJRow6f06AGkpER2fSLEVoi2efNm3H///fj999915x977LG4//770ZE7LkQUa0IZogFA8+Zig8ffSjQ5RAtnOycgQrStW0XlWU2N+XgkwWrn3LpVW2YlmjtWohERUawwq0STJ1Y6cABo1Sq86xQtWIlGgfj1VzE7JxCzrZyAjRAtPz8f48ePR+PGjTF16lR07NgRiqJg69atmD9/PsaNG4dPP/0UmVZ3iIiI6oJQzs4JiHHR/vlHHCksL7c/1pfazpmWFv4NRvX3QFHERpvZeCRWfzNSUsQG8P795iEaK9G8M6tEC+fEAm3bivdueTlDNCIiCi1vlWhAbIdoxokFGKKRHfJ4aAMGRG49IszymGhz585FVlYWPvroI1x66aU44YQTcOKJJ+Lyyy/HokWL0LJlS8ydOzeEq0pEFIVCXYkmTy6Qn2/vb/ft06Z4P/ro8E9B7WmGTnmMNDsHXtSjybm5ohVDxko07yJdiRYXBxx1lFjeuhWorg7ffRMRUd3w99/A999rlTCeqAfbGjUSw2IA7iFaLHI63UMztnOSHZyZE4CNEG3FihW48sorUd+kf7xBgwaYOHEifvrpp6CuHBFR1AtniGa3pXPOHG15yJDgrI8dcogmB2fyxqvViQUALURTFGDnTv1lrETzLj7evfIsnCEaoLV0VlWZVxMSERF5smMH0Ls3MHQocOaZnseKrarSthHk8VQZookATZ3YST6PyApF0UK0Ro20g6MxyHKItnPnTnTr1s3j5d27d8dO404NEVFdJ4do6myUweRviOZ0Aq+9pp2+6qrgrZNV8garpxDNn0o0wD2EUSvRMjO1o86kZ6xGi1SIBrClk4iI7Pn1VzG+KgB8+SXQqxfw9dfu19u1S6tUk8dTlbc39u8P2WpGNeN4aABDNLLuv/+0fZH+/UWXQYyy/MhLS0uR4mX2heTkZJSVlQVlpYiIao1orURbskSrzjr11Mi0OHpq5wx2iFZRITaaAVaheWMcF40hGhER1RbywThAVKKNGAHccQdQWamdbzapAOA+sUAsMo6HBrCdk6xjK6eLrdk5S0tLTds5AaCkpASKsTyUiKiuU0O05OTQDNTub4j2yiva8jXXBG997PDUzunvmGieZujctk1rT+B4aJ4ZK9HCObEAwBCNiIj8Jx+0bNtWtHcCwJNPAsuXA998I7bF5EkF2M6px0o0CgRDNBfLIZqiKBgxYoTXyx1+DFr97rvvYvbs2cjPz0eXLl1wzz33oGfPnh6vP3fuXMybNw979uxBo0aNMGLECNx2220ewz0iopBSN+pCUYUG+Bei5eYCn3willu1As46K/jrZYWVdk5/xkQD9BvJHA/NmmiqRNu8Obz3TUREtZu8HTF7tphk4M47xRhoK1cC48YBCxboD7J5audkiKZhiEZWqTNzOhzA8cdHdl0izHKI9tZbbwX9zj///HPMmDEDDzzwAHr16oU333wTEydOxJdffolMk+qExYsX46mnnsL//vc/9OnTB9u2bcPUqVPhcDgwbdq0oK8fEZFPaml8NIVos2dr44ZceWX4K45UckCWm6stqxuvCQlAaqr122vXTvxwK4p+I5kzc1oT6THR0tPFfVZW6isKiIiIfJF/NzIzgZtvBgYPBk45RbQkfvwxMHUqsHevdj1PlWgcE03DEI2sOHwY+OMPsdy1a8yPP2w5RDvuuOOCfudz5szBBRdcgPPOOw8A8MADD2Dp0qVYsGABJk2a5Hb9NWvWoG/fvjj77LMBAK1bt8ZZZ52FP//8M+jrRkTkU3m5+AeEJ0TzNBOVrLoaeP11sRwXJ0K0SOnSBahfX4xZ9tFHwIsvihBFDdEyM0UoZlX9+qKyLjfXc4jGSjTPIl2JBgApKaKaoKQk/PdNRES1l1yJpm5z9esH/N//AaefLg4ePvmk/uBcu3basqdxWmMJx0Qjf/3+u9jHAGK+lROwEaJVV1fD6XQiUdro3r9/P95//32UlZVh6NCh6Nevn+U7rqysxLp163D11Ve7zouLi8PAgQOxZs0a07/p06cPPvnkE/z111/o2bMndu7ciR9++AHnnHOO5ftVKYrCMdxqAfV14mtFUamgAGoEpDRq5D5teDBkZAAJCXBUV0PZt8/3fXz2GRxHBtlXzjoLaN3a59+E7HOWlgaMGgXH++8D+/dDWbwYGD0aOHAADgBKZqb956x9ezhyc4F9+6CUlIjxT/79V3sdOnYMzetQFzRoADmyVOrVC/9zlZoKR0GBeO1i8HXibxpRePCzVgcdPKj91mdkaL8hw4YBM2fCcd114vSRyiqlWTMgKUm7XkICkJ4OR2EhlAMHYvI3CIcOwXjoUikuDui54GctRqxYoX3+jj++zn5+rL6PLYdo99xzD+rVq4cHH3wQgJhI4Pzzz0dFRQWaNm2KN998Ey+99BKGDBli6fYOHjyImpoat7bNzMxM/CuPbyM5++yzcfDgQVx88cVQFAXV1dW46KKLcI0fg2YXFRUhLoanZa0tFEVxzfrqz5h7RKEUt2MH0o4sVyUlocysTD4I0po0gWPvXih5eSjycR/JL7wAtXmzdPx4VFtYp1B+zhLGjEHK++8DAKpfew2lgwYh48h91aSno8Tmc5aUlQX1UE7x33/D2aULUv/5B/EAlMREFCYnm7crEJITEiA39pZUVqImzM9VasOGiAeA4mIUxuDrxN80ovDgZ63uSdm/HwkAlPh4FCqK/rd+7Fg0+PtvNHjpJddZNW3auG1jpDZqhPjCQij79/vcnqqLGuzbB8PADlCKigJ6LvhZiw1JP/2kbX937w5nHf38OJ1OS9ezHKL9/vvvuOeee1ynP/74Y9TU1ODrr79GamoqnnjiCcyaNctyiOaPVatW4dVXX8V9992Hnj17YseOHXjkkUfw4osv4vrrr7d1W2lpaYiPjw/RmlKwqGlweno6v5gp+qhlzQDqNWuG9FCND9C8ObB3Lxz5+UhPS/PcAvnff8C33wIAlPbtkTxqFGDhey6kn7ORI6G0aQPHzp1IWLIE6Ueq5AAg3p/nLDvbtZi6f7+odtu+XZzRoQPS7UxUEGsM48+lNGoU/jEtjtyfo6wM6Skplt6fdQl/04jCg5+1Okjdac/IQHpGhvvlzz0HZedOOBYvBgDEH3WU+zZG06bAtm1wHDoUk79BriFIIMJIR00NHMXF3rctfeBnLUb8/jsAQElNRepxx9XZz06NOqa0D5ZDtLy8PLST+spXrlyJESNGIPXIRvmoUaOwcOFCyyvYqFEjxMfH44ChJ/3AgQNo0qSJ6d8899xzGDlyJMaMGQMAyMnJQVlZGe69915ce+21tirLHA4HP+i1hPpa8fWiqCONLeFo3NjvDRCfjoyL5qiqEmNXGDced+4E3nsPeOMNV3m1Y9Ik0bpgUcg+ZwkJwKWXAg8/DIfTCTz3nHafdsdEA3Rjnjm2bRPjxB0+LE537Bi616AuMIyJ5qhfP/zPV0qKdv+HD9ubWKKO4G8aUXjws1bHHJlYwOP2VkKC2Ba6+GLg11/hmDzZ/XpH9jEdiiK24Tzsc9ZZUvWQo1UrYOdOOKqrxYQ/xsmHbOBnrY4rLgaOHAR39Opla/+itrH6HracOtWvXx8VFRWu03/88Qd69uypu1wt5bQiMTER3bp1w0p1qlSI8rmVK1eiT58+pn9TXl7uFpSp1WTswyaisJMHaA3VxAKA5xk6v/kGGDpUDJw7dSrwzz/i/MRE4PLLQ7c+dl12mbZ8pLUTgH6mLKvkmbb++w+Q2/85M6d30TCxgByacXIBIiKyoqbG2mzoKSnAJ5+ICYgGDnS/XN7uiMXJBeQWvDZttGXO0EneyBN4HXVU5NYjilgO0bp06YKPP/4YAPDrr7/iwIED6C/NzLBjxw40k3f0LLj88ssxf/58LFq0CFu3bsX999+Pw4cPY/To0QCAO++8E0899ZTr+ieffDLmzZuHzz77DDt37sTy5cvx3HPP4eSTT2ZrJhGFnzzderhDtJUrgdNOA77/Xj+456BBwMKFQIsWoVsfuzp1AtRWf6kF1q8QrX17bXnbNs7MaYfxKHOkZudUcaOdiIiskMMfK8M2eKomYYimLbdurS1zhk7yZvNmbblz58itRxSxXIt3/fXX46qrrsIXX3yB/Px8jBo1SheaffPNN+jbt6+tOz/jjDNQUFCA559/Hvn5+ejatStmzZrlaufcs2ePrvLs2muvhcPhwLPPPou8vDw0btwYJ598Mm655RZb90tEFBSRCtFqaoDJkwF18MvOnYEJE4Dx46M3SLr8cuCHH/Tn+TN+WevWYhyGmhpWotkVDZVocojGSjQiIrKioEBbDmR7Sw7R9u/3/3ZqKzVES07WDw3Cg1rkzZYt2jIr0QDYCNGOO+44LFiwAMuXL0fTpk1x2mmn6S7v2rWrrr3TqvHjx2P8+PGml7399tv6lU1IwA033IAbbrjB9v0QEQWdHKKZDXIbLMYQ7Y03gN9+E6d79BCDfUb7+ATnnw/ccIM+OPGnEi0hAWjbVgRo//3HSjQ7jJVo9eqZXy+U2M5JRER2ydtbgUwgJI+BFouVaGpLbHq6mJhJxRCNvGElmhvrI/ED6Ny5My699FKcccYZbmOTXXjhhejatWtQV46IKKpFohJt0yZg+nTt9MyZ0R+gAeKo54UX6s/zJ0QDtHHRDh1yzRYEgCGaL9FWicaNdiIisiIUlWixGKJJM5zqDmrV1nbOV18FevYEjgw5RSEiV6IxRANgoxLtrbfeMj0/NTUV7du39zgZABFRnRWuEK15c235xReBqiqxfNFF2lhjtcEVVwCzZ2un/Q3R5HHR1q8X/7doASQl+b1qMSHaxkRjJRoREVkRrO2tWA7RqquB0lKxnJ6uD9Fq60GtKVNEMPjQQ8A550R6beoutRKtefOYnFXdjOUQbe7cuabnFxcXo7i4GH369MHLL7+MjFC2NBERRZNIVKKpAVpSEvDEE6G7z1AYMADIyRHVdADQtKl/tyPP0KnieGi+yZVocXFibLlwY4hGRER2BaudM5ZDNLnarC60cx4+rFXW5edHdl3qspISYO9esczx0Fwsh2jfffedx8t27tyJO+64A88++yzuv//+YKwXEVH0U8eWaNDAvconmMzCprvv1s+sVBs4HCL4u+QSYORIfYWdHWYhGls5fZPfo5GoQgM4JhoREdnHiQUCp26zAnWjEk0OQeVZR2sDRfE8g2y0YSunKVtjonnSpk0b3HbbbVi+fHkwbo6IqHZQj4yGsgoNEFVncgVPp07ArbeG9j5D5eyzxcbwm2/6fxusRPOPXIkWiUkFAI6JRkRE9rESLXBy0FQXxkSTg9WiIhFMmdm2DXjwQWDt2rCslk+7d4tJwQYOBMrKIr02vnFmTlNBCdEAoGXLltgfa4k+EcWurVuBXbvEcqtWob8/uWrr2WeB+vVDf5+hEujRN1ai+ScaKtHYzklERHYFqxItKUk7oBTLIVokK9EUBZg4EejfXx/Q2CW/JxRFG+/N6Prrgfvuc5/cKlLmzwfWrQNWrgS++SbSa+MbZ+Y0FbQQ7Z9//kGrcOxIEhFFA3mA/AsuCP39XXGF+P/yy4Gzzgr9/UWz5s3dQ0RWovkmV6IxRCMiotoiWJVogFaNFushWqTGRPvxR+CNN4BVq4DnnvP/doyvn6eWzg0bxP+bNnmuVgsn+b3sKfiLJnKIxko0F8tjopV42NgtLi7GunXr8Oijj+Lcc88N1noREUWv6mpgzhyxnJAAXHpp6O9z+nTg5pv1QUisiosTM3SqExQArESzIhoq0TgmGhER2RWsSjRAhGi7dokx0WrT2FSB8laJFs52zlWrtOW//vL/duT3BCAeQ1aW+/XUx+10AuXlkd+Olrd91MnCohnHRDNlOUTr168fHB6+ZBwOB84//3xMmjQpaCtGRBS1Pv9cm6kmkAHy7UpKCs/91AYdOmghWlJS+F6D2izaKtE4JhoREVmhVu80aBB4CNKkifi/ulr8DskVWXVZtEwssHq1tvz33/4HmWYhmpGi6M8vLmaIZpdaida8uf49E+Msh2hvvfWW6fkpKSlo164dkpOTg7ZSRERRbdYsbfnKKyO3HrFMHhetY8fYOZIcCLkSLRomFmAlGhERWaEGJsGYyMk4uUCshGjeJhaIVIhWUCAOSrdsaf92rLRzHj4swlJVSQnQrJn9+womedunsjJy62FFSYlWNMAqNB3LIdpxxx0XyvUgIoou778vxlG4+Wb9RltuLvDZZ2K5dWvg1FMjsnoxr317bZnjoVkTbZVoDNGIiMiKYM6GbgzRzCYrqouM7Zz164ttgcrK8LVz5ucD27frz/v7b/9CNCuVaMZgLRq2O2pTJRpn5vQoaBMLEBHVGdu2AePGiSmxzzxTHMlSzZ0rxlUAxGD/8fGRWEMyVqKRb9EwJlpCgrYe0bAxS0RE0a2iAigrE8uBTioA6EO0/fsDv73awhiiAVo1Wrgq0eQqNNXff/t3W1ZCNON50TCMRG0N0ViJpsMQjYjIaPNmLShbuVJMHOB0in/qrJwOhzZjJoXf8OFifIZ69cIzO2pdEA2VaIBWjRYNG7NERBTd5NkMg1GJpo6JBsTWDJ3GMdEArZW1LoRoZu2crEQLDGfm9IghGsWmxx8HmjYFnnwy0mtCqmiYdlolb7ABwIcfitkxv/8e+O8/cd6ppwLt2oV/3UjIyBAVg3v3Av37R3ptaofkZK1yMpKDw6ohWjRszBIRUXSTt8mCXYkWSyGacUw0oHZXohlfu9rSzik/19EeorESzSOGaBR7Fi8GpkwRJdzTpgG7d0d6jeiTT4BWrYDbb4/0mgjGEA0AHntMP4kAJxSIvAYNgrNBHSsaNgSmThWtsDfeGLn1UDfao2FjloiIoptccRSKMdFihRooORza77D6f3l56AMdRdFCtEaNtKE41q3Tuj/s8KedMxq2O2rTxAJyJRpDNB2/QrTq6mqsWLEC77//PkqOvBHy8vJQWloa1JUjCrrdu4HLL9dOV1cDL70UufUh4ZlnREXR008D0fA9Iodop5+uLW/bJv5v2hQYOTKsq0QUFA8/DPz7L3DaaZFbB7USzThrFhERkVEoK9FicUy01FQgLk5bVoW6Gm3nTmDfPrHcrx/Qo4dYLi11n2zACn/aOaNhGIna1M6pVqI1axY7s9haZDtEy83Nxdlnn43rrrsODz74IA4e+WJ7/fXX8dhjjwV9BYmCpqYGGD/e/ajTK6/oB46n8Nu5U/yvKOZVYOEmjxtxxx3AbbfpL7/00siOKUVUm8kzdEZDaE5ERNEr2JVosT4mmjoeGqAPRkIdMMmtnMceC3Tvrp1eu9bebZWVieo5WW2sRIvmEK2kBNizRyyzCs2N7RDtkUceQffu3fHLL7+gfv36rvOHDx+On3/+OagrRxRUjz8uxrQCgNatgbPOEssHDgDvvBO59Yp1iqJvqZUDrEgxDmL7+OPA6NHidGIicNVVkVkvorpADtGiYYOWiKw7eBB47jngt98ivSYUK0JZiZabG/jt1RZqVZY6Hhqgr0QzC6GCyVuIZndcNGMVGlA7xkSrrNQHZ9Ecom3dqi1zUgE3tkO03377Dddeey0SDVUYWVlZyMvLC9qKEQXVypXAPfeI5bg4EZrdf792+bPPRtfA9rGksFBfCWhWjh1u8gZbRoZ4z7z/PvDmmyKIzc6O2KoR1XryRnukN2iJyJ677wZuvhkYMcK9EoQoFII9O2daGtC2rVhevlwfFtRVlZXa51WuRAtnO2eoQ7Ta0M5p3OaJ5jHROB6aV7ZDNKfTCafJ4H979+5FcnJyUFaKKKgKC4GLLxbtnIDYABwyBDjmGGDwYHHe+vXA119Hbh1jmXFih2isRAOAevWASy4BBg6MzDoR1RVyJVqkN2iJyJ7ly8X/Bw7ERvhAkRfsdk6HA7jmGrGsKMCLLwZ+m9FODpMi0c7pdGrVqy1bAllZ4oB0QoI4z26IZtaGWxvaOY33H82VaPLMnKxEc2M7RBs0aBDefPNN3XmlpaWYOXMmhgwZErQVIwqaN97QBoQfNEirSAOAW27Rlp99NpxrRSpjiBYNlWhqkBcXpz9KR0SBYzsnUe2kKPodK3XbiiiUgt3OCYhhORo0EMuzZ9f93yL5ALWnSrRQtnNu2aJt3x97rPg/MRHIyRHLGzfaC5TC0c759NNiv3HlSut/40ttCtFYieaV7RBt6tSp+P3333HGGWegsrISt99+O4YOHYq8vDzcfvvtoVhHosD8+6+2/Oij2lEPADjnHKB9e7H85ZfAhg1hXTVCdFeiqa2cRBQ8DNGIaqe9e/WTgfz3X+TWhWJHsCvRADG5wLhxYrmoSAzXUZfJYZKnMdFCWYlmbOVUqS2dVVX60MYXf9s5rW5zFBSIicVWrAD+9z/r6+VLbQrR5AMmDNHc2N47bNGiBT7++GNcffXVuPTSS9G1a1fcfvvt+Oijj5ApD9RIFC3kL9oWLfSXxccDN96onWY1WvhFYyWaGqIFa2ONiDQcE42odjLu5LISjcIh2GOiqSZP1pZnzhQth3VVpNs5fYVogL2WTrN2zuJi99fQWJ1m9TGuW6fd1s6d1tfLl9oUoqnf902b6t8zBMCPEA0AEhIScM455+DOO+/E/fffjzFjxqCBWhJLFG18/fhOnKjt1L31VmxNdx0Noq0SzenU1kE+WkdEwcEx0YhqJ7kyAWAlGoWHejA8NVXfTRKoXr3EGMkAsGkT8M03vv/mgw+Axx6L7gHhzXgK0cLVzimHaP36acv+hmhygUT9+tqyMaTytxJt3TptOT/f+nr5Ytzmidb3UWkpsGePWOZ4aKYsfRN9++23lm/wlFNO8XtliEJC/qI1C0XS0kSQ9uyzYuaa998Hrr8+XGtH0VaJJh/JYiUaUfCxnZOodmIlGlmxdq1oj7zkEqBnz8BvTz0YHqzx0GQ33QT88INYfv55MeusJxs3AhddJJadTmDatOCvT6hYGRMtVAe1qquBNWvEcseOgNy5FowQrV074J9/xHJhob66zt+JBeR1yc8X40E6HNbXz5PaUonGVk6fLIVo1xsCBYfDAUVR3M4DgA0cU4qijfrjm54u2jfNXHKJ1sr51VcM0cIp2kI0eUODIRpR8LGdk6h2MoZorEQjM1dcAfz6K/D999qMjP5SFC0wCcU22dlnixBm+3bg88/Fe9xT5c0ff2jLH35Yu0K0ULZz5ueLGew9WbcOOHxYLMutnADQoQPQsKG43N92zg4dtBDNGJoZ9ynstHOqqqrE7QajpbE2hmisRDNlqZ1z48aNrn9vvPEGunbtitdffx2//vorfv31V7z++us4+uijMWvWrFCvL5F9Vo5g9e6tjZf23XdARUXIV4uOiLZ2zlCNvUFEAivRiGonYzvnwYORP/BF0WfjRvH/33+LECwQpaWikgkITSVaQoL+wPnMmZ6vK4+NtWZNcMfKCrVQTSxw991wNG+OJG/FB55aOQFR3HD00WJ5yxYtbPNFrkRTJ4gD9CFadbV+IhTAv3ZOIHgtnbUlROPMnD7ZHhPtf//7H6ZPn44TTjgBKSkpSElJwQknnIBp06bh4YcfDsU6EvnP6hEsh0Mr4S4tBZYvD/26kXh9oq0SjSEaUWhxTDSi2kdR3EM0gC2dpFdZqQUFlZX6bSp/hGObbOJEUQ0FAHPmeB4bbMcO/elPPzW/3hNPAGeeCURTd1aoxkR7+20AQL333/d8ENzTpAIqtaVTUaw/Z+q+XYMGQPPm2vny4zTbvigt9T2BRH6+e2gWqhAtWsdEk9/rHTtGbj2imO0QbceOHUiTSz+PSElJQW5ublBWiihoSkqAmhqx7OsI1mmnactffhm6dSLNgQPuR2GiqRKNEwsQBR8r0Yhqnz173Ks6AIZopGecnMt4oNQuueIoVCFa48ZiWBdA/CZ9/LH59Ywh2iefuF9nzRrgzjtFa+gTTwR3PQNhJUSze1DL6XS9vg5FAX76yfx6v/wi/nc4gL593S+Xx0Vbu9bafavvi8xM/eORg0Czg/KK4rvazViFBsReJZr8PLKgwJTtEK1Hjx549NFHsX//ftd5+/fvxxNPPIGewRg8kiiY7Pz4Dh+uDRrJEC08zDauWIlGVLeFa0y0BQvEzGuffRa6+yCKFXIVmjwwOMdFI5kxRFNn+POXvE0WinZO1ciR2vKmTebXMYZo333n/hsmD20UTcUlniYWaNhQGy/aboi2b5/WagsAP/5ofr9//imWu3fX//6revTQlq2Mi6Yo2vuscWPPEwl4qqzz9TgZoumfI7PXjPxr58zPz8dJJ52E4cOHY/jw4TjppJOQl5eHRx55JBTrSLFs7drAply2E4hkZgLHHafdbzT9+NVVZiFapCvROLEAUWiFq53z9tvFRv0dd4TuPohihTxGzrBh2jIr0UgW7BAtHJVoANCpk7a8dav5dYwhWmUl8PXX2unDh4F339VOB9rKGkyexkRzOLSQxO7+1q5d+tNmIdqPP2rj4p18svnt2J2h8/BhbexqY4gmP05PB+V9HbwzC9Gk4qGA1JYQTV5PeZuNXCzNzilr164dPvnkEyxfvhz//vsvAKBTp04YOHCga4ZOoqCYNQuOq65CWuvWYtYVdbwCO+QfXytHsE47DVi1Six/9ZWYYYhCxyxEKysTPyreZvoJJVaiEYVWcrK2HKpKNEXRNvD//Td409MTxSq5Em34cOCDD8QyK9FIVlsr0dq3F78RiiJ+M4xKSvTjcJWXi+VPPgFGjxbLCxbog5tIHxSWqesVH6//DQZEiHbokP2DWsZig99+E7chVy59/7227ClEa9VKBHuHDlkL0eR9O7vtnIDv7Q6zdYjVSjSHA0hKiuy6RCnblWgA4HA4MHjwYFxyySW45JJLMGjQIAZoFHzffAMAiNu1SysFtstuIMJx0cJLDtHipK+jSLZ0MkQjCq34eO2gSKhCtJISrc2koiK6KgKIaiO5Eu3EE7UDXaxEI5kccAC1Y0w0AKhfH2jdWiybVaLJM3GefbZWnfPZZ9rYy3IrJxBdvzvqdnVamvsBJbWSy26IZqhEc9TUACtW6K+zdOmRCx3ie8OMwwF066bdpq/1kINaq+2c8oF5b7evKFolmvw8xdrEAup6Jifr98/Ihc8KRS/5i0beeLPDbiXascdqP9LffKPv9afgkzeu5NlfoiVE48QCRKGhHqkOVYhm3JELtBqCKNap22EJCUCHDkC7duL0f/9p7VpEtbUSDdC2Qw8ccN8OlVs5jzoKOPVUsbx/P/Dzz+Lz8cMP+r85dCh6PhtqVZxctaVSf49LS7VA0AqzYW/k56CgQCuC6NXL++vXoYO2LAeWZoz7dlbaObOytGVv2x15edrt9+6tnR+sEM0Y4EV7JRrHQ/OIIRpFL/mL5p9//LsNu1VF8fHaD+OhQ9qMMhQacoh29NHaciRL4FmJRhR66lH8UI2JFuxqCKJYpihaO2eHDlqQBojPcDRV3FBk1dYx0QD9wVxjm7IcorVtq5+IYPFi4I033G+vutp8RttwUxQtUDI7OOzvZD/GMdEAfYhmZTw0VZs22rKdEM1qO6fVEE0eD+2EE7RqtFht52SI5hFDNIpe8heNPBaHHf4cwWJLZ/ioO7YOB5CdrZ0fyUo0OcBjJRpRaKghWrgq0RiiEflvzx4xXikgqnAAMYaUiuOikao2V6J5m1xADnbatgXOOEMLWBYtAubOFcsJCcDgwdp1o2FctPJyLawxq0STK7nsHNiSKtGcLVuKhdWrte8KK+OhqeyEaP60c7ZqpS1bDdF69NBmIo6lEE1RtPXkpAIeMUSj6CV/kQejndPqEawRI7Rlhmihpe7YNm8ONGminR8NlWhpadq030QUXOrRzYqK0GxEGitj2M5J5D95G0wN0eT2K46LRiqzEC2QlsZwdgfIlWjGyQXkSrQ2bYCmTYGBA8Xpf/4B9u4VyyNH6g8KR0OVpnxg2ls7J2AvRDtSiaakpKBq+HBxXlUVsHKlWFbHQ4uLE1Vd3vhbida4sQh61EDTUzunOt4d4P0xyiFat27idQZia0y08nKtrZeVaB7ZDtHWrVuHTZs2uU4vWbIE1113HZ5++mlURuMbgWov45ho/vwI+/Pj27Kl6N0HgF9/Dd4XJ+nV1GgbHa1a6X/Yo2FMNFahEYWOfHQzFO0urEQjCh65G6BzZ/E/K9HIjDFEKyvTVwTZpX6Xx8WFfofeWyWasZ0T0Ld0qq68Ur+/EQ2VaPI6+ArRrL5WiqJVorVujWo1UARES+f+/cBff4nTffr43qYOpJ1Tfm94qkTzp53z6KO1EK2sTKuwC0RtqEST15GVaB7ZDtHuvfdebDtyxGnnzp249dZb0bBhQ3z55Zd44okngr1+FMukIwWOoiL/wiy7Ewuo1JZORXHNEkpBlp+vHelQp7dWRSpEUxQtRON4aEShI2+YhWJcNIZoRMHjqxKNIRqpjCEaEFglsLxNFupZAq1UoqWna+2DZ5+tv07r1mJcZXl7tq5WohUWagfAsrJQPWiQdtkPP+jHRvPVygkE1s4JaK+JpzHRrLRzyjNztmkjnis1RAMCL6qoqhLV97KaGs9FIv7u+wZKfg+wEs0j299G27ZtQ9euXQEAX3zxBY499lg89dRTmDFjBr7++uugryDFKKfTvTrBn5ZO9ccrPt5ems5x0UJP3qk1VqJF6shdWZl2VIghGlHoyN/HoRgXjSEaRaPDhyO9Bv4xC9HkSjS2c5Iq2CGa+l0ejm2yzEwtNJBDNKdTC3bUKjQA6NJFq8wEgMsvF/sb0VaJJodJZhVh/oyJJs/M2bo1lNatoajB+qpV+n0nKyFao0ZAUpJYttvOCWiPIZDZOXfv1l6vbt3E/8EM0TxV3ZtVo+3bJ4K8Vq2ANWsCu1+7GKJZYjtEUxQFTqcTALBy5UqceOKJAICWLVviYDSk7VQ3mJXM+hOiqV+0jRtr/fJWDByo7eR99VX0TFFdl3gL0SJViSZv7DBEIwodf2cDs8oYonFMNIq0GTPEdsVtt0V6TexT2zkTErQQoXlzoEEDscxKNALEtrLxuxfw//u3pkbbHgz1pAKA2E9QWzq3bxezawIi0FCHLJJDNIcDGDtWLDdoAFxxhViWg6poC9GC1c4ph2hqldeQIeL/igrg7bfFcny8fqIFTxwOrRpt507v+13eQrTSUq3LRX0siYn6cZc9BYXG8dCA4IZonrZ1zEK0ZcvE+ldXA598Etj92sV2Tktsh2jdu3fHyy+/jI8++girV6/GSSedBADYtWsXmshvUKJAmH3BBVKJZjcQSUwEBgwQy/v2mR9Zo8AYQ7Ro2OgI5wC2RLEsEpVoPBhCkTRrlqhoeeGF6BwHxxNF0UK0jh1FkAaInV61Gm3bNn6+SNvpN/I3RCss1N5X4domU1s6q6u1iiiz8dBU06cDr78uZqJUPw/R1s5pZ0w0q5VoRyYVAKBVeR0prAGgtS0ec4y+0s0bNUQrK/P+vKn7ZA0bin+A/nGpj0END9PSrB24i1SIZjamfHl58O7XLlaiWWI7RJs+fTrWr1+Phx56CNdccw3atWsHAPjqq6/Qp0+foK8gxSizLxq7IVqgR7COvLcB6H8sKDiisRJN/tHmxAJEoRPqMdGMG+CVleYVEkThsn+/+L+yUszmZ2btWuCcc4DZs8O3Xr7s2aN1B6itnCq1fevwYXHAkWKb/B3booW27G87vfw9Ho5KNMB8cgFvIVqDBmIygf79tfOiuZ3TLEQLQjsnAK0STWallVNldVw0uctIJT8GtQJNfdzp6dYO3EVTJZocrIX7u1VeT4ZoHiXY/YMuXbpg8eLFbuffeeediAv1gI8UO4JRiRZoa548HXJuLtC7t/3bIM9YiUYUu8JdiQaIMCAzM/j3ReRLVZW+Teqvv7SdNNm0acBnnwGffgqMGKHfDvGmsBDYuBHo10+0TwWTvO0lj/8EuI+L1rx5cO+bahe5a6N7d20Gdn8r0eTv8XBXogHauGjeQjQz0VaJ5mtMNH/aOc0q0dq3F0GYHIAFEqL16uV+HbllWP49l0M0tYJRfSxpaUBysna5lXbOo48W/wczRPN0v75CtEhWorGd0yO/Uq+ioiJ8+OGHeOqpp3DoyM7uli1bUMCjvBQsnirR7LQLBHoESx6EkpVowWcM0ZKStI1/jolGVLeFe0w0gJMLUOQYd6T/+sv9OooC/PKLWHY6gf/7P++3qSjAzz+LwcxbthSVMNdeG5z1lZlNKqDiDJ0kk0O0Hj20ZX9DtEhUopmFaHIoJAc9ntS2SjR/2jnNKtEcDn1LZ0ICIM/a6Yt80MBTJdrhw1qrqPyekB9XUZG4ntpanJ4uhulJTBSnzbY5FAVYv14st2unhUeRqkSTZ/EMdyUa2zktsR2ibdy4Eaeeeipef/11vPHGGyg+8kR//fXXeOqpp4K+ghSjzL7ES0u1o1pWBHoES/4yZ4gWfOoObXy8+JFyOLQjZKxEI6rbQt3OyRCNoolxXFWzEG33bv1O2vz5nm/vrbdElcaAAcDcudqsn998E/CqulHHQwPcQzTO0Eky+X3etq32PR+MEC1c22R22znNRFslmq8x0fxp51T3i+rV0wdNckvnscfaq2Sy0s4pv8e8tXPKFXXqY1YDIbMwa9cu7W/kKuFIjYkWyUo0Tixgie0Q7dFHH8Xo0aPx9ddfI1FNdAEMGTIEv/76a1BXjmKY9AFWEqSuY0/jiJgJ9MdXrkSTj7hQcKg7tC1bAmoruPpDFw1jojFEIwqdULZzVlSYz/DMEI0ixRjqmoVoa9boT69cqd95V737LnDppWL8NKO8vOAP8O+tnZOVaCQzBhwtW4rl2tTO2battk1qbOeMi9NmovSmYUOgfn2xXNsq0ezOztmqlfZ8AcBpp2mP/dxzba2mpRBNfk94a+eUH7N6mbrdYbbNIbdydu+uLcuTJgYzRHM4tGVflWj792szjoYDK9EssR2irV27FhdddJHb+c2bN0d+uJNSqrukD7CzSxftfDvjoplNgWwHK9FCp6pKK0+WN0jkSrRIzPTFiQWIwiOU7Zzy51geo8nfHTmiQBkr0Xbtcq9QMYZoAPDhh/rTigL873/a6f79gTlztJapw4eDX9mpbnfVq+dehcNKNJLJ7/PMTC1EKyoS3SR2LVmiLcsVQaEkv8+3bhWfOTVEa9VKXG6Fug0ZDZVocjugrzHRrHx/lJdrE6XIBQeACMKWLhXfSzffbG897YZo3to5zYJDNUQze4x//60ty5Vo9eppz5n6mP0lb+vI6+trTDR5HLhw4MQCltgO0RITE1FissG7bds2NA5XvzrVfdJ7rLpnT+18OyFaoFVFGRlinC6AlWjBJh8tl0M09Uelpsa8kiTUWIlGFB6hrESTNzbljWFWolGkGEM0wL2S7I8/3K9jbOn8+mtt3J7Bg0W12mWX6cOtvLxA1lRPUbR2zo4dxRhHssxM7bPMSjQyhmjy9p3dgxjffw8sXCiWmzUzn/kxVNSWzsJC8buhhlBWWjlV6jZkpCvRjGN9NWzofp3kZK0yykqIJv+Wmk1+0r+/+F6SOtYsSUvTqsY8FS8Eo52zrMy9sstsZk6VGuAGsxJNXndfIRoQ3nHROLGAJbZDtKFDh+LFF19ElfSC7969G08++SROPfXUoK4cxTDpA1wjz84Szko0h0M7wsJKtOAyTiqgivQMnZxYgCg8Qjkmmvzdr86wBTBEo8gxqyIwtnSqlWjJydqg7L/8oq/weuYZbfmWW7RlueIymCHa7t3aeGvGVk5AbCep1Wjbt4sJESh2eapEA+yFaNXVwE03aadnzAhvRYw8ucCPP2rLdkI0dXu2uFgb4D4SPI31JYuLM6/S2rMHeOcd9+1xs5k5g0WtRtu1y7wjJRjtnID7gXq5dd449qMaohUWmo9fZpUcosn7GL7aOYHIhWisRPPIdog2depUlJWVYeDAgaioqMCECRNw6qmnIjk5GbfIP+hEgZC+aJw5OVDU8ulwVqIB2hGWoqLQDH4dqzyFaHJ5cyTGRWMlGlF4hKsSrUULbQOY7ZwUKWaVaHKIduiQVsnVqxcgD5uitnSuWwd89ZVY7tABOOcc7TotWmjLwQzRvE0qoFLHRaustPcZUxTgzTfdW1ap9gpWiPbaa1qlZr9+oqopnOTJBb7/Xlv2pxINiNw4v4D3CiuZGpaogdv69SLMnzABuOYa/XXNZuYMFjVEq6gwr/yy2s5pVonm7eCdel/167sHR/K4aIG0dHoK0XxNLCCvXzhwYgFLEnxfRS81NRVz5szBr7/+ik2bNqGsrAzdunXDwIEDQ7F+FKukLzclPV0cFdq0SWzQOZ36QSw9CbQSDXCfXEAen438Z6USLZIhWlKS/TJ0IrIulGOiGb/7W7YUG6C7d4sdd3lAX6Jw8FWJJrdy9ukDXHABcNdd4vT8+cAddwDPPqtd56abxMzWKrkSzc4s5r7I1RnyJAIy47hoVitTXntN2zlfsULMNEq1m/o+j4sT23NyiGa1ErigALjnHu30889b2+YPJrkSbelSbdmfSjRAhORy1VQ4eRow30j9TS4uFhMqDBumhaKLF4tqKbWgQQ7RQlWJBohx0Zo1019utZ3TVyWacbtDrfRq1sx9G8E4Q6eVySXM1MZKNIZoHvn9rdSvXz+MGzcOV111FQM0Cj55ds6UFO0IaHm59fHJglmJBrClM5isVKJFop1Tfc9wUgGi0FLHmwRCG6I1aqR9x1RVmVcEEXlTXQ38/LPY/vCX/L5TxyT6+2+t/VEO0Xr3Fq2TffuK07/+Ku7/7bfF6bQ04Ior9LcfqnZOuerCuDOr8meGzupq4NFHtdOrV9tfN5WiAJMmifBRDgwo/NT3eaNG7jNZWq1Eu/de7Tt8/PjIhKtyiCZ3wMgBjy/yfkckJxfwNGC+kRo0FRcDp5yif73KyoA//9ROh6OdEzCfXMCfdk7jmGiAfrvD6dS+68wmsDCGaP4KZEy0SFSiNWzoPg4muVh6Zt566y3LN3jJJZf4vTJELnIlWnKyfiyOzZut/ZAxRIte4WznXLECeOopsdNx5pner6u+Z9jKSRRacXFi7KfS0uC3ysvf/Y0b679jdu/Wt2YQ+XLTTcBLL4kdS3m2QDvkHb9Bg8TtlJaK0KlTJ/3MnH36iP8vuAD4/XdtWa1MuOoq93ajcIRonipp/Jmhc/58/XX//dfmiknWrQNef10sP/00MHu2/7dFgVFDNPW9Yredc+1a4OWXxXJysj5oDSe5nVMWSCVapKjBssMBdO3q+Xrqd4qiaJ/NxEQtzFm+XLTWAuFp5wR8h2iBtHPKgdbBg9pEA2YHC4IVosnbOrVhYgFWoXllKUSbO3eupRtzOBwM0Sg4PFWiASJEGzrU922oX7QNGwINGvi3HsZ2TgqOcE4scOutwKpVwLffijYXT++FigptAGWGaEShl5IigoRQt3MaqyHkGZ+JfPniC/H/d99ZH07CSA0XEhNFZY0axv31lz5ES0jQWq7GjAGmThXL6s5kXBwwebL77YdqTDS5gs5T+Gw3RFMU4LHH9OcFEqLJ98lKtMD884+oXDrrLPtDWlRVacGFvyHaLbdo1ZnTpwe/ysmqjAyxHWisIPM3RItUJZrTqc3M2bGjvgLcyBjMd+oEPPeceC8AIkRTJ3uQiwr8bW30xFeI5qmdU51hVFGstXPKgZYcjIWrEk1+f5iNiWZs5wxnJZr63HBSAa8shWjfffddyFbg3XffxezZs5Gfn48uXbrgnnvuQU8vG7hFRUV45pln8M033+DQoUPIysrC9OnTMSScUx9T6MlfbsnJ7iGaFcGoKmIlWmioIVpioucjScGqRFM3zgsLRZDmqRqNM3MShVdqqtjhD8eYaCrO0El2KIr2nlEU8V6V24asUt+TjRvrQ9y//gJOP13b0T36aDGwNSB2evv1E+2cqvPOA9q1c799eScvmGOiWalE87XTa/Tll+4zk1ptAzUjf6Y3bOC4h/76+GMR3FZViQqwKVPs/b1Zm116ujhwWV7uO0TLyxPbaIBoEb71Vnv3H2ydOuk/e8nJ9rYN5etGqhJt+3ZxoArw3soJ6L/XsrJE0N+6tVYxvny59tlSiwqaNRPb8WazaPrLaiVaUpL+oLjDIR6D2spp1s7pqRJNrvIKZSWa3CYpr3u0VaKp68lKNK/CPFKj3ueff44ZM2bg+uuvx6JFi9ClSxdMnDgRBzyMWVJZWYnLL78cubm5eO655/Dll1/ioYceQnO5jJ3qhiMfYCU5WRx59SdEkzda/SWHaKxECx51o7dVK/3GbrAr0ZxO/VGrhQs9X5czcxKFl7qBFux2Tm+VaAzRyI4DB/QVAf4e3JHb3Iwh2rp1WitR7976v7vwQv3pW24xv/169bTgItyVaJmZ2jhvVkI0uQpNnRzh33/93xGXP9NFRZyF1x8LFwLnn6/tzMszUlplViHkcGgHMXx998qfrcGD/e8gCRZ5XDRAVKHZCWejoRLN6sycgDbbb+vWIkBr315UxvbvL87fvVtMNFJTo72WoagUlPe7vIVoZvt2ahDoqZ3T05ho4a5ES0nRJmkAomtigaoq7b5ZieaVpUq0GTNm4KabbkJSUhJmzJjh9brTpk2zfOdz5szBBRdcgPPOOw8A8MADD2Dp0qVYsGABJk2a5Hb9BQsWoLCwEO+//z7qHXnztQ52LzZFB2M/dps24uhsRYW1EK28PDitec2aiR+R6mpWopn55x9g7lyxod+rl7W/qajQNraMZeDBrkQrKNBaAwBxpPXVV80HypQ3cjixAFHoqd/vVVXiqGuwZsRVN7LVI9P+DG5NBLjv+B86ZG9wcUBsj5SVieXGjUWFS8OGYhvlr7/Mx0NTjRkjKoKcTuD4470Pst68ufhtzcsLXjWWWonWoIHnVjCHQzwn//wjdrK93ffPPwM//CCWc3JEVd3XX4vnJz/f8+QF3hhfow0bgt9iVpd9+CEwdqwW5ALAli32b0cO0eSqxVatRKXhwYPis+ApHJMn7oh0gAaYh2h2REMlmtWZOQFR5bprlwjL1WpYQIzhqFYILl8OnHyy9l4JxT54UpJ4/xw44B6iKYr2PjML0dLTxd8Y2znVbQ1P7ZzhrkRLSdFv70TTxAJyuMgQzStLlWjr169HdXW1a9nTvw0bNli+48rKSqxbt043s2dcXBwGDhyINfIGheS7775D79698eCDD2LgwIE466yz8Morr6BG/uKnukH9EKsf4Lg4bXKBrVv1P/ZmjANL+0ueXYghmrtJk4AZM8Sgx1bJO7HGDd1gV6IZf3QOHACWLTO/LivRiMLL23TzgZBb+ePi2M5J/jNWoPtzcMfY5hYfr+3Qbt0K/PSTdrkxRGvXDpgzB7joImDePO/3o46Ldvhw8D5P6g6rr8k41IChtNT7b7dchXbnnfoB3P0dF834GtnYF4l577+vD9DU8HP7dnHw2A5PIZr8/eut1TjaQjTj5AJ2Q7RoqESzOjOnKitLH6ABIkRTLV8e2pk5VeqBitxc/f5eWZkWLpm1l6uVaGVl2vsxNVWrePW0zRHpSjSzMdGM5xUUmIdtwSaHi2zn9MpSJdrb6rTahuVAHDx4EDU1Ncg0fAgyMzPxr4cf0p07d+Lnn3/G2Wefjddeew07duzAAw88gOrqatxwww227l9RFCjB7OGm4CouhgMAUlK01+qoo+BYtw6orISyfbt+WnWjggKox0GVRo0C69fPyoJjxw4gPx9Kebn7D0ws27hRPM///ANl7179DGGe5OZqr03LlvrXJi1Nu6ywMPBxFvbtg/F4uLJgAXDSSe7XPXhQu++MjOCO8RDl1M8YvxMprFJTtc9ccXHwwusj3/9K48bic9y8uXY/u3dH9LPNz1ots2uX7jdEOXjQ/vvnwAH37ZEePeBYvRpQFCgLFmiX9+rlfvsTJoh/gPf7lt/ne/YEvgOkKMD+/eKzlJnp/b5bt9bue8cO82ruDRvg+OgjcZ1WrYCLL9Y/N//+K6rt7Nq9W/8arV8vntdY/qyVlYkJlfr311ptjRYvBsaNg+NItb5y+eXAoUNwLFoEVFeL7WxjNZY3R94rgPTdCwAtWui/f83G9AOAw4e169WvH/ltsA4d9O+rNm3srVNGhvZ4Dh2KzONZt058fuPigOxs/9bh+OOBuDg4nE4oK1YAw4ZpjysrKzSftTZt4PjjD6CmRnyXqWGd/H0hv8dU8j7Eke9uJS1Nu15Kin6bQz0/L087v2lT99tt0ABIToajtBRKfr5/z2NNDRxHOqSUlBQgIUG7z8pK99usqHDff9m/Xz+JTCgUFWnrlZIS+c9hBFh9H1sK0aKFoijIzMzEQw89hPj4eHTv3h15eXmYPXu27RCtqKgIcf7MsEShV1mJjCNpe3XDhig70gbRsE0bqMemSv/4A9VeKszid+yAWoRakZyM8gBaA5OaN4dadFu8aROcnjYAYo2iIF06wl66YgWqLcyaWm/LFiQfWS5v3BgVhtcm48j/Nfv3oyTAls5627e77kulLFqEogcfdJthLXH3bqjNKmUNGqAqWBMb1AKKorg+Zw4OyExh0jAxEeohieLdu+GU27n9VVOD9COVMDXp6a7vkLSmTRGXnw9l1y4URfCzzc9a7VL/v/8gRxBle/bY/m3QbY+kpKC8sBCJRx3l+r1xHKlOqGnXDsWA30MZNMjIcG0jlWzdihp/WiNlxcXatlhGBkq9rFeDZs207bMNG1Btsp3U8H//c33ey6+9FhXl5ajXooW2PbB+vdv2gBVp0oE5AKhetw6lhYUx/VlLHjMG9ZYsQeXo0SibPdv0OikPPICEIwFaxaWX4vCTT6LBgw9qr+Off6La02QSJurn5ro+K2UNG7o+J/UbNdLO37oVVUcfbfr3CQcOQI19KxyOgLbbgyGuaVPIU4iUNWli67PviIuD+otWnZ/v9fMTEjU1SD9Slens1AnFFRXu42xZlHr00Yj/+2/gr79QvmaN6/U83LgxKkPwWWvYtKnru6JkwwbUHDkgEL99u+u7tDIlBYcNz2lSw4au/TXHkcpGZ2oqio9cLx7Q/r6gwPX3SXv2aPt5DRrAafJapWZmIr60FMq+ff5tQxQVufZvqhs0QGVVlfbdV1zs9t2Xevgw4g03Ubx1K5yeQvEgid+7V3uOEhPdnuNY4JSHAfLCcohmdawzX2OmqRo1aoT4+Hi3SQQOHDiAJh7Kxps2bYqEhATEx2tvq44dOyI/Px+VlZVItDGeSlpamu52KIpI74mE9HQkJSUhPT0dDqmfP3n3bv34WUZSyWv95s1RP5CdM2n69tTCQu/3G0tKSuCQnufkLVuAUaMs/Z2qQbt2aGB4PpWkJDjKyhBfWor0QJ9rdVYiAEp8PBw1NYjbvRvp//zjfsRbaiVIatUqpl5n9ahLenp6zO1sUARJlWepDkdwPnMFBXAceT/HN22qfYe0agXk58Oxbx/SU1PdQvRw4WetlpFnpwSQVFVl/30q7bjWb9lSbI8cd5zb1eKOOSaw3zxprLaU0tLAP0/SQbKE5s29r5s0+VNyQYH7fZeUAPPnAxCV3g1uvBENUlN1LWYN9uxx2x7wqaoKDkN7VcLmzUhPT4/dz1pVlWtigHpffWX+fed0utpelY4dkTh7NhLj4sTssEck791r7z2kjvsHIKlNG+1vpa6RpEOHPN+mtE9WPz09sO32YDj6aCgJCXAcaWtNysmx93xIlaAJJSWBb8/atXmzK0iK69EjsPsfPBj4+284nE40+OIL19kNjzoKDUPxWZNaaVMOHtSed6nFMbFFCyQaH5NJ6BvXqJH22KUqrsTKSu3vpRb01E6dxIykRs2bAzt2wHHwINJTUnTvV0uk/ZGEjAwkSNW6DeLj3b/7TNqpU8vLQ79vIlVhJWZmuj/HMcDqMGGWQ7RFixahVatWOProo4NSrpmYmIhu3bph5cqVGDZsGACR/K1cuRLjx483/Zu+ffvi008/hdPpdFWRbdu2DU2bNrUVoAEiKY+pH9XaRPqiQWqq67VyZGe7znZs2eJ90FzpC9HRuHFgA+xKA2c6du/m1OkqwxgPjr/+svbcSBvmjiZN3P8mIwMoK4Pj0KHAn2tpB8gxciSwaJFYXrRIm3FIJb9nGjWKudfZ9TmLscdNEZSmHed3lJYG5zMnfS/pPsetWgF//imC/4IC83FPwoSftVrEMIaeo7DQ/vvU7DdPnqFTvaxPn8A+A9LYU459+wL/PPn6rZZJ40U5du1yv+6WLa6Dm45zztE++9LOsuO//+yvs8kYW449e8TA4mlpsflZ27nTNY6Uo7RUTPZgHP5kxw7X5FuOnj21QEAdexiAY+tWe6+Hp/eLNG6WY+9ez7cphc2Ohg0jvw2WkCAOoh+ZZMHRrp29dUpIEO/zoqLgbM/atX69a9HRrVtg9z94MPDKK+K2fv1Vu93WrV23G9TPmqfvE/n3PTPT/TGZBD6OtDTtetJA+Y6SEu18dWKBhg3h8NQGf2SbwaEo4r1ut9JX2rd1pKbqJhZwVFe7PxaTcdIc+fmhfx/J6yk/dzHE6nvYcog2duxYfPbZZ9i1axdGjx6NkSNHIiPAGewuv/xyTJkyBd27d0fPnj3x5ptv4vDhwxg9ejQA4M4770Tz5s1x2223udbhnXfewSOPPILx48dj+/btePXVVzFBHSuC6gZPgxpKRzp9ztApD+QbyMQCgH72GU4uoDEOlPrnn9b+zjjIslF6uthxCUYJsXyEeuJE4JNPxMblwoXAo4/qfxw4sQBReIViYgFP3/3yJCa7d0c0RKNaJNgTC6jvySZNxHtSDumMkwrYJY9J6m0Ad6vkKjxfbX3yjKU7drhfvnWrtixvy6Wni9/bgwf9m1jA00QhGzb4N75aXSA/14AYXN4YokkBC7p21ZalEM3tdnyxMrGAt9mR5VbDaJhYAACOOUaEaI0a2Z+VFxB/V1QUmYkF5EkFfM3M6Ys8uYAs1BMLAPoZOn3t25lVTcnnybNNmk0s4C0Yk7cZ9u+3H6IZ923tTiwgr2cocWIByyz3M9x333346aefcOWVV+L777/HSSedhJtuugnLli3zuzLtjDPOwJQpU/D888/jnHPOwYYNGzBr1ixXO+eePXuQL71hWrZsidmzZ2Pt2rUYOXIkHn74YVxyySWYNGmSX/dPUUr+YpM/wK1aaQOk+vpxD2YgIodoxg3qWCb/mAFio1WeXckTTxtaKjWcLymxPzuUkfyD06ULMGSIWN6yRb+BAehnFGOIRhR6nqabD4SnmZnlEM3bjhyRzBjS+DNrtKffPGM1Wu/e9m9bJodoeXmB3RagX29fs3N62ulVydtsxlkP1cHrd+60P/uc/PrIjz+WZ+g8UjnlYtzWAfQhmjxGWVaWViFjvB1fAg3Rom12TgB44gkxi+zChbrKIcvU7dlITCywbp22bGVmTm/atdP/hgIikEpLM79+oDx9n/jafzBbH/k8uU1T3eZwOrUDBt4OrgU6Q6dx31YO0cy+98zGr1Mr5kJJ3haTQ0dyY2tigcTERJx11lk466yzkJubi0WLFuGBBx5ATU0NPv30UySb9RD7MH78eI/tm2Yzgfbp0wfzj4yrQHWUpw+wwyGOpq1fD2zbJr74PI1rE8xKNPlICyvRNMYQraZGvDZ9+3r/O18/gvJRo6KiwF4/47TVo0cD330nTi9YAPTooV3OSjSi8ApnJZq8I+epeoVIVlnpvtMSrEo0QIRoX34plps2dd9JtSvYIZqdSrSUFK2izG6I1qED8NtvYptuxw73y72RP8tDhwLz5onlWA7RjAeZ5TBF5SlEi48XoebGjaIy0Nt2tpG6bdewoX5G0MxMERhUVXn/7o3GEK1NG+Cxx/z/e3VbsrJStM8mJXm/fjCpr3tCgr760x8Oh6hG+/BD7bxQVaEZb1ve75K/k8z2DcxCNHmfIiFBvLfKy7VtjoIC8T4HrFeihSNEM6tEC0eIJq8nQzSv/B5ZVx2TTFEUywOwEVniqRIN0I5YVlR4P6IVzEBE3rBliKYxhmiAtZZOOUQzawmXzwu0pVP9oUtMFD8G556rXbZwof666nsmMdHzlPBEFDyeWisCYbWdk8gXs20Mf36TPB04kg/iBDoeGqDfAQxGO6edSjRAqx7ZtUvbKVVZqUQDgP/+s7eOcnfAKadoyxs32rudusSsndNIDRkdDlGlL1Nfn8OH7VXtqu8XY+DqcGgDute2SrRAyduz/lSx+quqSvsM5OT4V0VnZGzplLt0gq1+fe2ggBrKFxYC776rXcesvdZXOyeg7Veq2xxyMBXOSjT5NfFWiSYfHGE7Z1SxFaJVVlbi008/xeWXX44RI0bgn3/+wb333oulS5f6VYVGZMpbCi6P6+BtYyuYlWiJidrGKds5NWYh2h9/WP+7jAxxVMhI/sELdKND/cFp2lRsyGVlaRMKrF2rH1tPDdEyMmJyIE2isAt1JZp8AIUhGtll9j4JtJ1T3h4ZOFAb0P2kk+zfrlG9elqAEe5KNEAbDLyqyv3+1WAnI8N9m0zerrM7Lpr8Gh13nNauFcuVaMY2zA0b9ENjKIpWidaunXt1lD/joimK9j432+ZWv3/z8z237Nb1EC2c46JJE3kE3MqpGjhQfzqUlWiAFpLt2SMey913a98r557rPs4f4LudE9D2K9VtDjmYilQlmrHqzOnUPrPy88xKtKhiOUS7//77MXjwYLz22ms46aSTsHTpUjz//PMYMmSIqyqNKCi8peBWN7bkH6sAJ8AAoB1x2b3bNetRzDPbILBTieZpo1wO0QKpRFMU83EOjkxcAkBr/QC0nSO2chKFRyjGRLPSzskx0cgKs4NmgbRzGtvcOnYEPv5YjLt0003+raORWrWQlxf4GEz+VqIB+skFKiu1ahKzVs1AKtHkEK11a1F1A4jtQytjtNY1iuK+bVxZqQ/WcnO171u5lVMlv0ZWQ7SSEi20Mdu2k79/PQW8dTFEk7cnw1mJJrfwBjqpgKp3b33gGspKNED7PlEUYPFi4KWXxOmkJOC558z/xlc7J6Btd6ifAauVaPJ3YKjbOeXTqanaY2AlWlSxPCba+++/j1atWqFNmzZYvXo1Vq9ebXq9F154IWgrRzHKWwpudWNLDXjS07UjvYFo3Rr4/XcRoOXlBT52SV3gqZ1TUTxXctXUaK+NpwrBYJW/FxZqP0TyD+NFFwFTp4ojPbNmAXfdJc4vKhL/M0QjCo9QVKJ5mligeXPxvaQorEQja8xCtEAq0czChTPPFP+CpXlzUWV0+LD4TAVSSWC3Es04GLg6O6Y6hi3gO0TztxKtYUOx7dC1q9hWczpFpblaHRcr9uwRr73R339rbZtylZ6vEM3q5AK+xro1HsQwC2DqYogWqUo0uYU3WJVo9eqJas+lS8XpcFWiAcBVV2nfIfff7/lzbSdEKy8X1V7RUIlmDNHkSQXUbqjCQk4sEGUsl5Cde+65OP7445GWlobU1FSP/4gCFoxKNDXgCVYgIv9YsKVTkEM09UjXoUPm09urCgu1o+OhrkQzTiqgatMGOP10sbxzpxjYmTNzEoVfOMdEq1dP20BmiEZWBKMSTVG092SgQ0tYoY49BQQ+LpoajCQmWqtIkHds5ckFvI2Hpv6deuDNboimvkatWonb6NpVuywWWzrl0EsOIeRQxdOkAip/2jnthGievn/rYogWDZVowQrRAOCEE7RlOfwOBfn9q36HdusG3Hyz578xGxPNGKzJ32WlpdE5Jprc3pmYqN13YaH5hAPBxHZOyyxXoj366KOhXA8iTaBjoimKdsQnWIGIfNRs1y7g2GODc7u1mbyzOnSotpH2559inA0zvja0gOBVonkK0QDg6quBzz4Ty6++qrWAAAzRiMIl1O2cxs9yy5aiknjvXnuzzlFsknf2MzPF71dZmdjhkasIABEA/PEH0K+ffqzPsjKtqsBKNVegjDN0BjIrn1qJlplpbZxQT+2cvkK0xETxtzt22GvnLC3VQk21O0AO0TZuBEaMsH57dYH8XJ9zDqB2B3kK0eTnS9W+vfhudDrNK9HUYFh+P8vfu1Yq0czUxRAtUhMLqCFa/fr2Zrv15aabgF9+EQekhg0L3u2aMZs44OWX3b97ZVYq0eT9yuJi65Voqaniu6qyMryVaPXr69crPz+0VYBs57SMW5AUfbx9gFNTtb50TxtbJSXagIzBOvLLSjR36kZTvXr6AUe9jYvmaYBlWagr0QBRiaYGo599JiYZUAVjDD0i8i2UEwsYj/QC2o52dbW+VY3IjPxbL1fsmP0unXYaMGAAcOut+vODOcmRFcYQzV/yQPFWxkMD/K9EA7QDpAcOaEMr+CKHMZ5CtFgjP9fDh2thlJ0QLTFRey23bNGPracowFlniffEE09o5/s6QCoPgRJLIZp8ICdc7ZwVFcA//4jlLl3MJ/DyV2am6N54663gDJXjjTFEu+wyfSWcmaQk9/XyVolWUmK9Es3h0C4PNERLTfU+sYCnSjR/79sOdT3r1RMBHnnEEI2ij69SUrWEODdXn9ar5B+qUFWikX5ss969tfO9hWi+jlYCno/cKYo4AmZ1TABvIVpCAnDllWLZ6QSeekq7jJVoROGRlKRVuAQ7RDP7HHOGTrJDDdFSU/UH0owhWlUV8MMPYvnjj/WXWam+DqZghWhlZVqoYXW9s7K0z7PdEM2fyQXkz7D6+nTurIUGsd7OmZOjhb+bN4vXU56ZMyvLvP0N0F6nwkL9dtuGDcDnn4vlxx/XKmh8vc/l7TpPVcd1MUSLRCXaP/9oE6AFs5Uz3OSOlkaNxPvNF4fDPTTzNCYaILY7vO0rGKmX798vPkuVlcB99wHjx/s+MGcsEPFWiSaHaMZKtFCPi6auJ6vQfGKIRtHHVympesRSUYDt290vD8WRX4Zo7uRxXjp31mYd++MPz39jZYfCUyXaa6+JgYq7d7fW+uXrh3HiRK2da/ly7XyGaETh4XBo3/HBCNHkVn6z736GaGSVPAFFVpZ+Z9gYosnbHDt2iADK7LLaNCaa3Zk5AbFTqN6/WTtn/fqe25CsjncrkysF1c92vXpaALRpU+zNpq4+1w6HaMtUx6t1OkVlXn6+9p40Gw9N5WlcNDkk3r8f+PZbsexr206eldZs4gOgboZokahEk7dngzUzZyRkZYlwKiMDmD3bd8Cl8hWiGcdiVUOp5GT97KNm1HWorhYTppx2GvDgg8C77wLTpnn/20AmFpAfe7hCNI6H5hNDNIo+VivRAPONrVBUorGdU6+yUnudGjcW5dM9eojTW7d6Drnsjokm76y8/LL4Pz9fVKT54itEa93afFY0hmhE4WOcbj4QZWXaEVyzwEIel+eJJ4BrrgGuvx644w7v4T/FnqIiMeYW4F6xY6woMc5UvXmztlxbK9H8XW+1DTAvT3wWnU5tO61DB8/jEAZaiSYH5EdaFB3l5YiTK+JigRp4tWkjQks5RPn7b9+tnCpPM3R+8on+evPmif99vV/kUCyWQrRAK9E++AAYNQr47Tdr16+sBB57TDs9dKj9+4wmb78t9ulGjbL+N3KIZtaSaByLVd1X8DYemkrelxg8GPj+e+30vHnet2PkfdvkZHsTCxjHRAsldT0ZovnEEI2ij/ollJDgPqYN4HtygVAc+U1J0TaiWYmmDyrV51hu6ZTHGJPZHRNN3ej47z99m6iVNg0rJdpXX+1+HkM0ovAJZiWar+9+eUd76VIxqchLLwFPPgmcfbbY4ScC3KucvFWiyb9rgH4srto6JprcmmQnRFPHMVIU8Rzu2aOFI94GOPenEs2snRPQhUNxmzZZu626oKBA2zZTK8m8hWjeKtHk10oN5vbuBVat0l9v0SIRitmpRJPDMpl8fl0ZiymQSrTKStEx8dFHwOWX68em82TWLFEhBYhJNY4/3t591gXyPkR6uvukKHKIVliovXetVLrJ1zFWs5eWaqGyGXUbp359Ee7JY9UZx0QzTiwQrko0p1M7eMR2Tp8YolH0kVNwsxmhIlGJBmgtnbt2Wfsxq8vMnuNevbTzPFV1WBkTLSVFO1qt7qwsWqS/jrwh6ImVEO2009wHL+XEAkThox7tLCkJ/HvVV2AxdKjnmYN37dKP40SxTQ7R7FaiycFNuCvR5IqFYFWiWW3nBNxn6LQyHhrgvRItN9f8gKmPSjQAiJerAus6s+faGKLJByCttnOqlWiffqp9R6sHuIuLxeRMwWznrFcv9IPWh0vDhlrbnt1KtE2btEBj7VpgzRrv1y8rAx5+WDstL8cSuRLNbMw/ORzavl17T9utRAPExA0ffqidfv11z3+r7tuq9+9waEFatFSiqe83gJVoFjBEo+jja1BDX5VooQrR1COd5eXhG9sgWpntrMohmqfJBazsUDgc2g+futFhDNHsVKLFx3sOxuLjtQkGVKxEIwof9Xu+utr9aKxd8veS2ec4JUW02q1fr+2UXHGFdnksDkRO5oxVTt5mjTZWoskhWrgr0erV035bAxkTzd9KNOMMnVZDtObNtaBFPjj6119icPTOnYGfftL/jRx0yq3aciWaOkthLDB7rlu31kIFO+2ccqip3q7cynnvvdryvHnaZ8DhMN/eshOi1ZVWTkA8H+pvkd39hnXr9KfnzPF+/Zde0mY+HTUK6NfP3v3VFXKIZhwfDdCHQ/J3jZVKNDl4PukkYMUK4PzzgT59xHm//uq5iMAYogFawBotEwv4GpOcdBiiUfTx1Y/dpo12lMqsEi1UG62cXEBj9hz37KmdZyVE8/baqBthhYXiaLo8UCpgrxKtSRPP47AAolxePurJEI0ofIzjkwTCynd/vXpi57F7d9GCfsIJ2mUM0UhlrESzOrEAENlKNEBr6czL87+6MxiVaHZCNIdDO0D633+irUhRgFtvFc+30wm88Yb+b9SgMz1djDGk6tLFtRgfS+2c8nOtVpI5HNoMjdu3A7//LpabNvX+uqakaJNEbN0qKlS++UacbtkSuPNObcf+s8+0iSQyMsyryOyMiVZXWjlV6neH3Uq0v//Wn37vPX2bn6yoCHj0UbHscAAPPWTvvuoSYzunkbzNIe9DWqlEGzlSzBL67LPAV19p+wtXXaVdx1M1mp0QzTixgPzbEcpKNHkbjJVoPjFEo+jidJp/0cjq1dM21CJRiQZwcgGzndXUVG0j+a+/zGfFUv8uIcH8CJFKrkT75BP3HYF9+9yP/ssURfuh8XV0KStLG7Q0I0M/pgwRhZZxuvlAmI3V6ItcjcEQjVT/3959R0lRpW0Af3rywMAwDCAwBMkZCQqCoIiuCEZAEAWzLkpQXFnADIhEI2YXZc1pFZVgWAWMCJ+CiyBIzghDjsOk+v643rm3OkzH6q7qfn7ncLjd09NTE6q76qn3vdd9TrRg2znle1a0K9EA9R528mTo+1S4c6IBwbVzAqr66dQpUUX3+edq9UfAPIm3++qpuqyssoueSevWJc70G/oCAPrPWm/plH+75bVyuj/Hn3+KeblkyHXZZeI4fOBAcfvUKdU67OtvJTVVXcz0NydaPFWiAeaLwsGsFuteiXbggGip9eapp9Qx8bXXquA0EfmrRPMVogVSiZacLBYiuusu85zd116rVvZ86y3zCs2A77nG5HP4q0RLTVXvH1ZWovlb2I9MGKKRvegvPOWVksorlocOeZZIsxLNer5+xrKl8+RJ8wGdJN/kq1b1Pt+dJE9YiorE1TfprLPUuLwT3uPH1QFZIG+ML70klqmeNy/+DuCI7Mx9uflwhPLar1WtMESjMsFUorlf0Dl2TAU8gVZfR1IkFhcItRLNVzunXmnmi/7x9etFtZNuyxZ14fTwYVXRpM+HJv0VjicdOmTtSaed+Aos9RBNCiRE0+dFe+opNb78cvH/Ndd4fk5503TIls5EaucEzBfzjxwJ/PPcQzTAe0vngQPA44+LcXIyMH58UJsXd4KZE00/lwukEs2X7Gzg6qvF+PBh8zxpgPncVj/mkZVo5S0sIIM2eS4TrUo0tnP6xRCN7CXQUtLyJqG1emEBgCGar5+xvkKnt5ZOeWDu78q2fsKyeLH4v04d4Lrr1P3lnfAGsqiArmpV4MEHgXPO8f9YIooc/UDNW2VxMEIJ0bKz1Um4vqoiJTYZgrlcoq0tmEo0QLV0yo9lZXlfbdwKsg0PCH1etFAr0WrUUCeGeiVanTr+2/T047oJE1Q7m37BTVajuVcKutPD8URZXED+rGvUMB8/ewvRypsPTdKDuJ9/Fv9XqABccIEYd+niuVBLeX8rMhxLtBBNP54NtKVTvxDdvr2q8Pz8czXvmfTooyqcu/lmc/iZiPy1c+r7hr4idyDnCuUpr6VTv0AY7Jxo8n1DhnxHj/reh8LFSrSgMEQje/H1QuOuvMUF5EFrcnJkXwT0lgGnh2irVgGvveZZchwof5VogGeIVliofr/+TnC9vfFdeaX56mkkQzQiig29yqV/f3FCUFwc2nP5W1jAF3lCuW+fOTygxCVDmtNOE9MPBLOwAKAC2UAvHEVSJCvRkpO9vx/7kpSkLjiuW6f2SX+tnID5uE5v3Xz0Uc/7fa3MKenHa+GsUuoUJ06on4n7zzrUSjRvv7NevVTI5XIBgwaZP17e37msRPPWzmkY8Rui6e9FgS4usHatakNu2xa4/noxLikR7YLSv/8NPPGEGKeliYvBiS6Ydk5dOJVoAHD22aqN9ocfzHM3hxOiyYsP+rmMVdVorEQLCkM0spdQKtHcFxeQb1I5OeW3DAZLn+vDySHa8ePAeecBN94Y+uSjvkI0/cDM/eqv/jnBVKJJffuan7+8xQUYohE5w003qf26qAh44AFxMOo+qXIgQm3lZ0sn6YqLVQWXDGOystScTv4WFgDUvGjyY9Fq5QQiE6LJMDk3N/jjKNnSqbckBRKi6cd10hVXAPfco+YbWrTIPB8a4DknGhC91ezsQj8Odv9Z16jheRwUbDundMUV5tvXXmu+HUiI5q2KprhYVQXFW4gWSiWa/v7XqpU4Xpdmzxb7wKefmleXnzjRfJ6SqPRQ3dtrg69wKNxzBZfLXI02a5Ya+wqnfM2J5q2dU39NsypEYyVaUBiikb1EshIt0getOTlqBaitWyP73NG0fr36GcnVloLl62S1fn11ouEebgazSpn7le+qVYFzzzW31bASjcj58vKAX34Bxo1Trx2//AJ06OB9/hfpvfdEFYT+OhDKwgIAFxcgs7171Qm9PAlzucwL3ujke5vervnHH+LESVZVxqoSLdR2Tvk9BTMfmuTtRD7YSjRAVMFNmyZ+rt26ift27hTHMP4q0RItRPO2MqdOr0arUsXc8uuL++8sKQm45BLzfW3amAO5UEM0vTot3kK0UCrR9PnQWrUSv1O5D/z+u6g+GzhQLVRw552ecwgmqp49gTvuEMcHgwd7flxfyVcXiXOF665TlWOvv67CMH+VaO5zovmrRLPqNY2rcwaFIRrZS7iVaHv3qqvEkQ7RXC51hXXbNueu+KTPJbJ6dWitUzJE008sAPGGIH9G+kEdENwEy+6VaJddJlpqXC51wLZtm++JyBmiETlHRgYwZQqwZIkKtGRVmjcFBaKC7b33RAuofA2Tr0upqb4PlL1hiEY690UFJH2VPZ3esijbh9auDe7CUSTpAUkolWgFBWoluVC2W19cQAokRMvKMr9f//3vQLNmYtyzp7p/0SL/c6JFo2rDTnytzCnpIVqLFoFVF1ataj4WO+ccz1DV5TIvMFDe6uYyHCso8Dx+jucQLZRKND1Ek787vRpt9GgV0AweDDz5ZGQ7b5wsORl4/nngnXe8t6InJ6vKVqlSpcj83VWtKo5JAPH6/803YhxsO2esKtHYzhkUhmhkL4FWolWvrl4E9Uq0l15SY3nVJpLkJKonTzp37hy9FbWgILRJd+XVtOxs8Yakkwdw7iunBtPO6f7G17evGusnvL4mAmeIRuQ8nToBy5erk4Zdu8wHk9KOHaqaYc0a4NVXxVivQg7mhIIhGul8BTR6JZoMAU6dMgdOMvTZts38PE5q5wx1ZU4p1Eo0QC1OlJUFPPywuv/889V44cLgKtESIUTztTKnpIdogbRyAuI1VH8uuSqnu+HDxfF2p05Av36+n09WogGer+vxHKKFUokm2zkrVVL704AB5p8hAPTuLSq2k3g6HxT388tw50PT6fvJ11+L//2FaCUl5mC5vIUFAOsq0djOGRTudWQvgVaiuVyqGm3LFtF6UVgorj4A4g1l+PDIb59+hXXbtsg/fzToB/YAsHJl8M9RXsusXiWoH9gFc1Vev3JXoQJw0UXqdiDzojFEI3KmjAxzqOVt/kn9BBoAHnpIHPyF2sqvt4lzhU7yVYkm/0aKi1WI635xSIZohgEsXWr+WLToJ1uhhGihrswphROiPfssMGqUWIVQDwM7dFBVfosXm39HtWp5Pk80Wp/sxF87Z48e6oKnXF0zEHr45j4fmpSTA3z3nfh7D6SdE/Bs6YznEC3YSrRjx8R5DSBaOeUFocqVgauuUo/r0gX44AMVxFDg3EO0SJ4n6FWzgYZogLkazQ4LCzBE84shGtlLoJVogJo/o7BQnFS9/76a/+PKK4HTT4/89sVjiOa+iqY/paXqapq/EE1vtQ2mnVO/cnfxxeaDr0CqRhiiETmXfhK+fbvnx91fw/bsEe2g8v0jmJU5AXGSIhcX2LpVVRZRYvI1ab1+MixbOt3nB9UXqfjxR/PHoiU1VX29UOZEC7cSzb2d070tsDxNm4rWtHPOMd+fkiLmRQVEKLZ8uRjXqOE9RKhQAYZs6U6EEE22c1aq5P131rSpCLo++gi4+urAn/eBB0QF1PPPA02ahLeNiRqiBVuJph/XytUepQkTgPbtxdx08+YFN20BKe4BUSQr0apXFyuqAuJ16sAB3+e2+jyaeojmr50zGpVobOf0iyEa2UswKbh7WPP00+r2XXdFdrsk2c4JOHdxgXAr0Y4cUZMuezsx0K84+wrR/F3d7tJFHPRlZIi5H3TBVKK5XNGtACCi8Okn4d5CNPdKNACYMUONQwks9HD+jz+C/3yKH/7aOQFVUeL+viYr0QBziBbt9yE5L9qePcHP3xrpSrRAq9D80Vs65TyI3lo5JXnSGe8hWlGROh5t1Mh3K3uXLmJqjGBa/xo3Fheo77gj/O3Uw7FECtGCrURzX5lT16CBCGbmzYtuMB9vrKxEA1S1p2GIytlAKtH06jMuLOAIDNHIXkKpRAOAt94Cfv5ZjNu3B7p3j/y2AfFRiebeHhVsJZq/FfB8tXMGMydaZqY4kDh0SBz46erVU/Ph+atEq1rVc842IrI3/STc2+usHnJ07Cj+16/ihhuicV60xOZvYQHAdyWaHqLpVWDRPuGVrZAnT/pegMeXcCvRsrPNx2+RCtH0NikpkBDtwIHQFlByijVr1CqN4VaLWUmvRNNDM/fb8Rai6ZVogYRo3hYVoMiyck40wNwy/fXXvuca89XO6a0SLTdXBeRcWMAWGKKRvYRaiTZrlhrfdZd1q9TEQ4jmXom2Y4f5RMAf/bHe2qYiUYkGiDcXeQVGl5SkTlQ2bvQ+8bh8g2ErJ5Hz+Gvn1CvRnn1WzZUkMUSjcMi/r8xMc3AWSCVa48bejz+iXYkWzuIC4Vai6SuZA+ZjtXC0beu5b+shp7u/ToxdhmH+PcUbuQIg4NkGayeJ2s6pv24E0s5ZXiUaRYbVlWjnnita0AHPEC3YOdFkiJacrF6PrW7nTEryXMGUPDBEI3sJtRJNthfWqAEMGhT57ZLy8lQpvBPbOY8f934lLJiWTvcr7+6qVFHhmq+FBcK9Ki9bOktLgXXrzB8rKFB/RwzRiJwnmBCtbVvg3nvNHw83ROPiAolNXmjKyzMHYvrJsK9KtMxM7/OxxqoSDQh+XrRwK9EA8z4cqUq0pCQxQb6uvEq0RFlcYNEiNXb/+dhJorZzpqSo8xn9+NswxAUbPTABVCValSreF82g8Fk5J5p8/k6dxPiPP8xTRAQyJ5q3dk59O62uRMvKsq4YJY4wRCN7CWZ5XT1Ek4YN8169FCmpqeqgzYmVaHoVmt7mGExLp78QDVBXnrdvV28G8vMyMz2X6Q5WeVUjXFSAyNlq1FAHl+UtLFClirhaetddQJ066uPBLiwAiPcT+TVZiZY4SktFaCTnDTt+XAVk7gGNv3ZOWSWgt3S6fyxa5JxoQPQr0QDz/LHeVosMlT4vGhBYOycQvyFaaamqRMvJAdq0ie32lCdR2zkB9Z4kK9FKSoD+/cUF4X791OvP4cNqypXWrRlkWMXqSjTA3NK5cKH3r+1rTjRv7ZyA2s4TJ4LrIAqUPAdnK2dAGKKRvQTTj12xovkgKS0NuP12a7ZLJw8O9+71vJpmd3qI1rWrGkeyEg1QV55LS1XFnry6HYmTifIWF2CIRuRsSUkqFHO/WGEYqhJNtnJlZgLTpqnHnHFG8F8zOVksZgIA69fH9xxKJBgGcP31otqqY0dgwQLf86EB/ts55fuhtxAt0NUpIyWcds5IVKLdcot4rz/vPPOxRrjc50Urr50zESrRVq1Sx2TnnRfcogHRlqjtnIDa/+XrxtixwJw5Yjx/vph8HjDPh8ZWTutYPScaYA7R9CqzYNs59cIQfc7DYcOCXzTGH3kOzkUFAmLjV1tKSHolWiBLN+vVaNdcYz5wtIq/lePsTD9B6NVLXeUKphLN38ICgOfKqfqcJJFoa2ElGlF8k+1ghw+bL64cPKhOuPQqlGuvFSHI558D3bqF9jXl60pRkbkVPdG8/Tbw8MPmn3s8WrRILEoEACtWAJdcAvTurT7uHtAEsrAAADRv7vl5cn6caNGPU4JdgVtWoiUlhR7+deokwrvFiyP7vbdoYT7OS/RKNBm+APZu5QQSO0STlWgFBcCLLwKPP27++OTJ4n8uKhAd7iGRFecKZ5/tvesmkBDNVyXa2LFqDtj33hNzwkaKYZjbOckvhmhkL3IHrlAhsFUV9TeZu+6yZpvcOXlxAT1Ea9pUXdVYvTrwygt/CwsAnosLHD+urqxEohKtUSP15sNKNKL442teNH0+NPeQo3dv88WBYHFxAVGFN2QIMHFiZA/Q7cYwRFDoTl8Mp7xKNBmieVswx70SLdrzoQHiBE6GV/qcWYHQL3iFU9lkxcrYLpcKOjMyvE/rIekhmlVzCMWaHqK5t7raTaLOiQaYw+jhw9VYhhVffQX8/DMr0aIlGu2c6elA9+7m+1JTzaFYMAsLAKI1/t//Vrf/8Q9gyZKIbC4KCtT84qxECwhDNLIXWYkW6A58//3A4MHiyk779tZtl06f68NpiwvIuRYAcYLQtq0YFxSIk6dABDMnGiAqOrzNGxOO1FQVAK5bZw4AGaIROZ+vEE2/EFBeFUoouLiAqMiSLSLLl8d2W6z09dfA99+LcfPmwH/+Y54mADBfMAO8t3PK97b0dFV14B6iRXs+NEBU8nfuLMbr1nmuyl0eWYkWi+0OxNSpwOjRwAcflF8pF++VaPp8aFWr2r9yiXOiCTKoGD4ceOwxdf+UKVyZM1r0EC072xxURZJ7+7l7eOdrYQFflWgA0LeveP0DxLnPwIGRuUigV54zRAsIQzSyl2BLSRs0AN58Exg61LptchcvlWh5eea5gwJt+Qg2RNu0yfvV+nDJE57CQnP1AEM0Iufz1TavV6JZGaIlaiWa/lqqj+OJYQDjx6vbDz8sJvleuRJ44w3grLOAiy4yt3YC3ts59bk+ZQVkrVrmY5hYVKIB5sqkQKvRCgvVcVio86FZ7bTTgBkzgEsvLf9x8R6iOWk+NCCx2zndw94LLgCefBK44Qa1CMicOcBPP4lx9erWzNNFgv76bOXPWZ8Xzf3rAr4XFpDj1FTvlfVTpgDnnivGO3aI6SxKSsLbVn06JbZzBsTmr7iUcJywMoh+cue0SjQZorlc4kBfVqIBgc+LFkg7Z926qpVk40bvky+Hy9cJL0M0IufTK9H0ixXltXOGq2lTdcDKEC1+Q7SvvgJ++EGMW7QABgwQ4+Rk0cq6bBnwxRee89mUV4mmv6+5XOZ50WJV0aVXQeirw5XHigtesaKHgE4O0U6d8j7dhh6M2n0+NCCxQzT99aFJE1FFmZoqvtd77hH3G4aY+gRgFZrV9EorK88T2rc3B6juFV7+2jn1RQV0KSnAu++qAParr8KffoGVaEFjiEb2UVioXjjsvAPr7ZxOrUSrUUOUCIdSiSYXFqhQwffBTnIycPrpYmx1JRrAEI0o3sSinTMzU71urV0b+ZWvnEAPzg4dMi8kEw/c50J7+OHA5+5KT1fveYcPiyBAhgHu72t6S2esKtG6dFEnYYFWokViZU67SE1FqTyBdWqItnWruHBbu7Zni7mTFhUAEntOtIEDxYTwDRoAn35qvgA9dKjnBWm7t+Y6XbQq0ZKTzRXB5VWieWvnLK/NtFYtsbiA9OKL4R2z6CGanQtZbIQhGtmHU0pJK1dWV6SdFKIVFwO7d4uxrOCoV099L8FWovmqQpPk4gLHjgF//KHuj1SIplei6ScIeojm9JMAokQVysICkSBfV44eDW4eqXjhviqpv2q0Y8eA774DnnoKuPlmYNKkwBepiYX//ldNxNyypapCC5R8vzx8uPypDfQQLVYVXRkZQNeuYrxlC7B5s//PkfOhAc6vRANgyAtpTl1Y4OOPRQCYny/CFnmS7LT50IDEnhOteXPxO1y71nP13kqVgBEjzPexEs1a+rmBFccROr2lM9AQTRaU+Jur7dxzVVvn2rVicYpAHD0KzJ8P/N//qfv0c3A7F7LYCEM0sg8nlZLKls7t29UkoXa3Z4/a1jp1xP8ul2rp3LHDfFLgi7f2FW/0edGWLVPjSF2Vb9VKfR9ffqnaVeTBcpUq1k0WSkTWqlJFHXB6q0RLShJzI0VaIs+LVlTkeWHIV4j24oviZ1W5sjiIv/tuYPZs4MEHxcTvduStCi3YeaRkiHboUPkL5nTsqMb6e2G0BTsvWjy1cwIw5MnykSOewY0TbNigxt9+K+YABoDfflNVok6YDw1I7HZOQByP+jomvfNO0d0hMUSzVvPmwO23i/kv9dVSrXDhhWrsfv6j/z3oc6LJSjRf7Zy6669X49de8/24XbuAl14C+vQRIeKll4pVnL/8UnzcSefgNuGAV11KGE6pRANUS2dhoQinnMB9UQFJnxfNX0vnyZPqYCeYEE2/2hGpA/OUFODRR9Xt0aNFSChDNLZyEjmXy6Wq0bZtUxUYshLttNPUvIuRlMgrdG7b5nlRyFuItm+fqJzw1fI6YYJY5TMQq1aJ6jWrqv727hVX3B9+GOjVS03c3bo1cNVVwT+fbA88etRc3eT+fti7t1i84J57RCtXrAQboumVaHFQyV2qHwc4sRrNff8bPVoEuHorp/47trPyQjR9NcJ4DdHKU60acNddYpybK+bSIuu4XMALL4gL/Pp7vhWaNRMXmZo2BUaONH8s3Eo0QFRTy33rnXfMYRwg3qPvvluc991+O/DZZ+oxpaXiNaWkxFnn4DbBEI3sw0kpuBNX6NyxQ431EC2YedH0+XH8hWiynRMwz0cSyavbQ4YA7dqJ8YoVwL//rSZ8ZohG5GwyRCsoEBUyJSXAn3+K+yI9H5qkH1CvWmXN17Arb4GZt/tWrVIrgdWrB9x2m6hMk1f0i4vF1XH9xNibQ4dEFc2DD5qvpkfKDTeIsPXSS4GJE0UrpxRKFRqgKtEMQ7RISu7vhy6X+BqPPRbbUKBTJ1XhsmiR/zlz4rUSDXDmvGju7dV79wIPPOC8+dAA836QaO2cgXjkEWDuXNGSxxAjvjzxhJjWRrZeSqEuLKCrXBno21eMDxwQF4108+eL6RZ0eXnqPPa334C33nLWObhNMEQj+3BSCq4vLuCUFToDqUTzNy9aeXPAuPPVwhLJA/OkJHGSIo0ercYM0YiczX1eNL0l3ap5TNq0URVuX36ZWIsLuJ+wA97n0dLbXO+9F3j5ZTFf0xNPqIsaq1YBDz1U/td7+mn1nrJokQpII2HzZuD11z3vz80VrVP9+oX2vPpKa/rPxq6BU1oa0K2bGO/cCaxfX/7j9aDRqqA6ihwdopWUqL+x2rVVGPrCC6oFKzfXOa1/id7O6U9ysgj85eI2FP/CWVhAp1+E0t/3iouBsWPV7TvvFCHt9u3m1s8HHzRXITNECwhDNLIPJ6XgTqxE00M0OZcYINpaXC4xDiZE87ewgK8Qzd/nBeuCC0SPP2CulGOIRuRs7iGavqiAVSf4lSqJ6ihAVBr9/rs1X8eOAq1E09tc9cq9tDRxAC8P/GfMAH74wfvXOnTIfHXcMEQVRqToEyxfdJFYxWzTJtHS9/TToc8hJSvRAPPPJlYrcAYi0JbOpUtVhVPTpuZ53Ryq1Mkh2q5dqiLlzDPVfH6lpcCJE2LslPnQAIZoRO70kEyGaKWlanGeQEO0Cy8Uq3UCovJMBmL//rc6hunSRbznduwozvl69BDTDgDiPPbFF9Xz2b2QxSYc8spLCcFJlWh6iOb0SrSKFYEmTcR49eryV1YLphKtUiXPICs725p5jKZP9zyQZIhG5GzuFyt8vYZF2mWXqXEkg51o++orYNQo8+Tk5dFDIVlxtXWr53uCXonmvtJcmzaidRIQwdgNN5jf26WZM1XrvfTxx4FtZyD0EG3kSDEvWYMG6oJRqHyFaHatRAOAnj3VWC7A4820aWo8ZoyojHE4w8lzoumVoY0aiX3Zff4mp7RyAuZwrLwQLZAWNqJ4oFeiycBcn9Ms0H0hOVlMbwOIMO6dd4Djx83V4DNmeL7/TZmi7tNfH+1eyGITDNHIPpxUiaa3czqlEs3XnGiAauksKBCVBL5WHA0mRAPM86IB1p1otGoF3Hqr+T6GaETOFotKNEC01EhODdFefllUYD39tOdkxr7Ik/aUFKB7dzEuLja/dwAqRMvJAWrU8Hye0aOBrl3Vc959t7kt9vBh4MknxTg5Wb0vfPWV+TggHHqIFsmKKr2d0ymVaB06qGOqxYu9tyivXatCzNq11QmZw5kWFnBaJZoeojVsKKpSnn/e/Binhmi+5kRLSbHmQiuRHXlr59RDtEAr0QDPls4nnwR27xa3+/YFzjnH83POOMP7a73dC1lsgiEa2YeTKtFq1lRv9E4J0WQVR6VKYiJKXYcOanzLLSJUe+89NXm0FMzCAoBnS6eVJxoTJoiqOokhGpGzuYdoeiWalSFao0aq4mPJEudVsMyYIeYok2GJvjqyL4ahQqH69UU7n6SHRUePqlCtRQvvlV3JyWK+FTmH06xZolpY0qvQrrsOuPpqMS4sBL74wv+2+lNaCvzyixjn5ak2l0jQK9GsWjAn0lJS1ITWe/d6b1GeMUP9vdx9d9xUAzl6TjR9v5MXJHv0AP7+dzE+6yznzIcGiNcKGaT5qkRjKyclEn8hWjCvw61bq3O5n38GHn1UjJOTRcWZLxMneoZ1di9ksQmGaGQfTqpES05W84o5oZ3TMNQJqLc2qFtuUZUDgGjrHDRItOb89pu6P5g50QDPEM3KE42aNYFx49RtJx1cEpGn8irRrGznBFRLp2EACxZY+7UixTDEBMFjxpjv37/fPGmwNwcOAEeOiHHDhubXbv1k3td8aO4aNzZXzYwbB8ye7VmFdv/9wJVXqsdFoqVz40bxdQAxl1Qk6ZVoOjtXogHlt3Tu3Am88YYYZ2erkCYOGPFSiaZX9b/4IrBsmVgEwinzoUlyXjSGaETeQzR9VetgKtEAMX2CJPep224DmjXz/Tmnn65W1pbsfg5uEw579aW45qRKNEC1dB48GLkWFKscOqQmovV28lmjBvD998Dnn4vJJ6U1a4ABA1R7p13bOaX77hMHmO+9B7Rvb+3XIiJrVaigXjOi2c4JmOdFmzfP2q8Vim3bRIXXCy+IsOrZZ4GbbgImTVKP0acd0MMvb/SgrLwQTZ8PrbwQDRAH9JMnq9u33QYMHqwqmocMEWHbeeep6uj5882rlIVCb+WMdIimV6JJFSrY/+RfX1zAfdXZp55SP/Nhwzwr1R3MqFIFhpzbzakhmstl3pddLlGF5u1v0e5YiUak6CGZtznRgg3RrrnG3A5dsaJakKQ8992nXvdTUsxdPeQTQzSyDydVogHmSa+3b4/ddgQikAm5XS6gVy+xmtqXX6p2nj/+UC02wYZo0WznBMRV2aFDxSTSROR8shptxw71Opuebv1rSZcu6mt88YX5wDbWTp4EOnUSodSwYeIq8siR5iXrn3lGzE0m+QvR3OdfCrcSTRo3DrjzTjEuKREhGSCq0B54QIzT0oBLLhHjQ4eAb7/1/7zlsWo+NMB7cGH3KjRAzH0jq8fnzRNtgUuXikBTrsqWng7cdVfMNtESSUmAbOl0Wogm97u6deOmvbasEs3XnGgM0SiR+KtEC3a/r14d6NNH3f7nP0WXjj/VqgEvvSQeO3ZsXCwqEw0M0Sg4R48C69ZZ89xOq0Rz0gqdeogm21B9cbmAv/3NvFLX00+L/+1eiUZE8UWGaCUlKsCpXTv8VRb9SU5WB6NHjwLffGPt1wvG2rXAnj3eP5aUJJa1HzHCvHJmMJVojRqJyhf5Mw61Eg0Qz/Hkk2reM2nwYFGFJkWypdPKEM1bO6cTQrSkJPPiO99+C5x9tpjGQR573XQTcNppsdk+K8nFL/LzvS+qYEeHDqnjLffjKCfz184ZL2EhUSAiubCA9OijokXzwguBe+4J/PMGDRILEejV7FQuhmgUuJMnxUFzs2bAW29F/vmdVonmpBU6A6lEc3fZZUCDBmL8xRfiJEy24SQnB/Y7qlXLfFDEEI2IgqHPiybbyq2eD03SWzrttEqnvlrmVVeJlbjefFO8L2/cqOZFCTVEa9hQvG7LCy7eQrSMDPOFpPIkJYkquQsvFLfT01UVmnTxxeqE4pNPQg87SkuB5cvFuF4976uHhsNbJZpT3temTQM+/NC8aIT8u0hKMlcuxhP5N1BQYL5Ya2fulaHxQg/R9H2clWiUiCK5sIDUujWwebOYM9EJBSkOxhCNAvfLLyqMCTdEO3oU+OAD88kAK9Gso/+cAz0BTU4W1QzSzJnqymhOTmCVIElJKogDnHOyQUT2oIdoktXzoUm9eqn5RebNs08Viz59QO/eYoXLwYOBa68VV6ClvDw1t0mwIZr+//79YtGBwkJgwwZxX7NmwbV8pKeLIHLWLFHV16SJ+eOVKwMXXKC+vxUrAn9u3bp16lgi0vOhAc6tRAPEe3a/fsCqVWIePT1gHDgwviqedPr36ZSWTm8rc8YDGZKVlgLFxWJcXKxWgmeIRonE25xo4SwsQFHFEI0Ct2WLGi9bFvoJxcKFIikfOBDo1k1dgZKVaCkpzijpdmolmr92Tt3NN6uTsNdeA/78U4yDOWnQDwCdcrJBRPbgrdopWpVo2dli0ntAXNn9/ffofF1/9BDNW8gouVyqGm3zZs95iHSy8qVqVVVtpVfAbN4sAjR5shtIK6e7jAyxEnTnzt4/HomWTisXFQC8V2A77eJQaipwxx3i9zl9OnD33WpetHjkxBU6fa3M6XSyEg1QLZ366xJDNEokVlSiUdQwRKPA6SHa/v3mK2WBOHFCTDB8wQUqdNq6FXj1VTGWV4+zsqyf7yYS9JMXJ4VowZyAVqmiWoNOnFAHPcGEYa1aqbEePBIR+RPLSjQAuPRSNbZLS6deWVxeiAaoEK20VFWRuSssVMGcHpy5Ly4Q7KICwdLbZz/5JLTnsDpE8zaVgVMvDlWqJCaefuIJZ670GCinh2jx2M4JMEQj8rewACvRbI0hGgVOD9EAsbJToH76CWjfXqwY5m7aNHEQLyvRnNDKCYgKLXkF2intnCkpwc8RI1dW0wVz0jBqlKg6nDjRmhMvIopfsQ7R7Dgvml6J5q+yOJB50bZuVZXletWL3oq/aVPwiwoEq3ZtVaW2cqU5SHBnGKoqTmflogKSe0un0yrREo1+zJOfH7vtCEa8VqLpIRlDNEp0ViwsQFHDEI0CF0qIZhjAs8+Ktk25qmdGhljtsXdvcXvbNjEpsqxEc8KiApKsrNq5U83vYEeyEq1WLTFPWTCaNROTPuuCCdFq1QLeew948MHgvi4RUV6eZ2VytNo5AXECKwOjJUvscRIuQ7QqVfxfdAokRPNV9eJeiWZ1iAYAffuq8SuveH/M9u1i7rc6dYDVq9X9xcVqLrWGDa2rEHOv2nJqJVqicPKcaDk54l+80CvRZHjGEI0SFds5HY0hGgXOPURbtqz8xxcVAcOHAyNHqivGnToBv/4qqpv0UGXKFOD4cTF2SiUaoObrKSkBdu2K7bZIP/4oQiv5Mz91Cti3T4yDmQ9Nd9dd5tvxdFBHRPaVmiqCeF00K9EAVY1mGMBXX0X3a7szDFVZHMjreSAhmrdFBdzHeoiWlOS5MECk3HCDOrH417+8z+M2ebK4+Pbnn8DQoaqKbu1aMe0AYE0rp8RKNGdxWojmq706HrCdk0jhwgKOZosQ7a233kLPnj3Rpk0bDBgwACtXrgzo8+bPn49mzZph2LBhFm8hoaTEc96vFSvMibnuwAFRafbCC+q+MWOAH34QlU0A0KUL0LOnGG/YoA6EnVSJprca6fOOxcrGjUCPHsCgQerkQg/3Qq3guOgi9XsDeOWdiKLHvaUz2iHahReq8aJF0f3a7vLz1fuuv/nQAKBxY1V9HGyIVqMGUKGCGG/YoD6/YUPrrpDXrAkMGCDG+/YB775r/vjevcC//61u//CDeozV86FJrERzlliFaKWloX3eli3qc+OplRNgiEakYyWao8U8RFuwYAGmTJmC4cOHY86cOWjevDluueUW7N+/v9zP27FjB6ZNm4YzrTxQImX3brWDS6dOAf/7n+dj168Hzj4b+PprcTstTazsOG2amJNL98ADnp/vpEo0vUJi9+7YbYf0+efq9/TKK2IZe30S6lBDtKQkczWatxXziIisoIdF2dlqxeBoOeccdbAb6xAtmEUFAHFSKuc2W7vW+6raeoimn7S7XCpU27BBVXlZPbflyJFq/Mwz5m1+7jnP6rR//lNUskdjPjTAsxKNIZq9xSJE+/xzUbF/7rm+F/Twxdf+GA/0kIztnJTouLCAo8U8RJs9ezYGDhyI/v37o3HjxpgwYQIyMjLw4Ycf+vyckpISjB49GiNHjkTdQA4iKXx6K6d+AuPe0mkYYhL59evF7erVgYULgeuv9/68PXqIijSdkyrR9IoIO7Rz/vij+faoUcDbb6vb4cwldNtt4mRl6FDxOyYiigb9fT6a86FJFSqoCe83bDAHWdEWzKICkmzpPH7ce8W0nBMtJcXzOb21k1kdonXurEKw5cvFXHSACPGee06Mk5PVscPOncDUqeYQrUMH67bPvRKN7Zz2lpWlKjqiFaI99hhw5Ajw3Xfib/GddwL/3HhdmRNgJRqRjgsLOFqK/4dYp7CwEKtXr8bQoUPL7ktKSkLXrl2xQk4O68Vzzz2H3NxcDBgwAL/88ktIX9swDBjersiSd5s3Q07tbFx+OVx/HRAYS5cCejvt8uVw/fqr+FjjxsCXX4oJgMv7Wd9/P1yXXlp206hYsezx8vdk299VzZrq57JrV/nfZzT88ANMU3AXFwMvvlh208jLC30bk5NFNWHZk9n0d0JBs/1+RomtTh31Olu7dmxee3r0gOv778U2LFwIXHddSE8T9r62bZv6WdSpE9jPolkzuObPF5+zZo05iDQMYNMmuAAYp58uqo7152zQAG7LOsBo3tz638GIEXDddJP4es8+KwKz2bPh+qtLwRg0SMyr2qYNXEVFMGbMAAxDfB9Nmoigy6ptrFzZ9DMxcnL4fmhDZfsaANSoAdf27TDy863/XRUVAUuWqL+Ro0eBa6+F8dVXwMyZqkXalw0b1D7esGF8/W1lZKjv7cQJ8b2dPKnuS0+Pr+83QfAYMkQpKepvv7BQ/O2fOqXuS0vj/hADgf4dxzREO3jwIEpKSpDrdhUvNzcXm/RyZs3PP/+M//znP/j444/D+tpHjhxBUrCrFCaw9D/+gLx+dOLCC1Hhww/hKixE6U8/4ejhw2WPy3j1VcjrSCeHD0dhTg6gfdyrrl2R1bYtUv6aC+9UWhoK/vocwzBw4q8WEpf7Cm02kFSpEir/NS7cuhUn/X2vFnLt2oXsrVsBAMVdusDIzETqwoWmxxzLzkZJDLeR7Mnu+xklttRq1SDrn4uqV8eJGLyGpXTqBDnRQOGXX+Lk5ZeH9Dzh7msZGzeWvccez8lBcQA/i7T69SFP20+uWIHCs84q+5hr3z5k/7UydnG9ejju9nxptWvD/ZT/WN261r+PXHwxKufmImn/fuCDD3Dk/vuR9fjjSJbbMHQoSk47DRlDhyLj2Wfh0lpgitq2tfRvJD0jo+x4yMjKwuGTJ1VVDdmGvq9Vys1FyvbtQH4+Dh88GPwq5UFI/uUXVPrr65ZmZyPpr79F16uvouTHH3H8zTdRWk6bZsV16yDrU45Urw4jjo7Z0oCy15MT+/ej6PBhpB44UPb6XgDgVBx9v4mCx5Chy05Jgau4GCUFBTh2+DDSDx8ue385XlQU0Hs8RVZpgPNZxjREC9axY8cwZswYPPLII6ga5hwUlStXRnJysv8HkqDN91WhfXugXTtg2TIkr1+P7NJSMfdDSQnw0UcARHqeef31yHRve/DloYeAq64CAKQ3bYr0vz5PpsHZ2dn2fGHWJttP27cPaYF+v1b48suyYXKPHsDo0TA6d4ZLm48jq1kzz1YUSni2388osXXpAsPlgsswkHrmmciOxWvYhRfCSE+H69QppP3wQ8iv9WHva/n5ZcOKzZsH9nrevn3ZMHPrVvP7srbYQEqTJp4/25YtPZ4u68wzrX8fyc4G/v53YMoUuIqLUfnmm+HavBkAYFx4IbK6dROPmzQJxgcfwLVnT9mnpnbpYu3fyGmnqXHVqrH5eyS/TPtarVrAr7/CVVKijlmtonXSuCZPhlGhAjB8OFwnTiB57VpUuvFG4JdfzK1cur8W8TLS0lC5RQvRBRAvtJ97haQksZ9rgWZGlSrI4P7kODyGDENqKlBcjOTSUvFeou0PFatW5TlbDJSUlAT0uJiGaDk5OUhOTvZYRGD//v2oVq2ax+O3b9+OnTt34o477ii7T6aFLVu2xOeff456AU547nK5uKMH468KJwBwNWgg5iz5az40188/i9UbFy0SS84DcPXpE9xku/36iZU8d+wQLRza70b+rmz5+6paVcy1ceoUXLt3m7Y76rT50Fzduolt++QT8bs6dkyU0depE9ttJNuy9X5Gia1JE+CDD0Sb0+23x+Y1LDNTLJjzzTdwbdki3hNPPz2kpwprX9PmRHPVrRvYz0Kbw8z1xx/mz9Gq/l2NG3s+n3vFTK1acLlPrG+VO+4Apk8HSkrg0uZfdY0erbYzOxuYMgW4+Wb18bPOsvZvRAsCXLm5fE+1sbJ9TVtcwJWfD3g5x4iYv9q+AcDVvTvQpo147bjySuCPP+BatQp48klg7FjPz/2rvRoAXKef7rkYl9NprayuggKx72hVpK7MTO5PDsVjyBClpoqW5qIi8bevzYnmSk/n/hADgf4Nx7SfMS0tDa1atcISOWksRCi2ZMkStNeunEoNGzbE3Llz8fHHH5f969mzJzp37oyPP/4YNWvWjObmJxa5sEB2tliZqlMn9TF5cPvmm+q+IUOCe36XC7j9dmDSJGetzulyqRU6Y72wgL6owNlni/9btgQWLAD+9jfg2Wc5aSsROVP//uKk0998QlY6/3w1Xrw4NtsgFzXIyQl8ldJq1dTk91rlGQDzSoDeJjF3DwqtXlRAV7euCB50bdqIi3a6G24AZItq5cqmyjtL6JUBXJnTGaK1QmdpqQrRcnKAVq3EuHlz4K23VJXJhAnAX5WVJnv2qFVw421lToALCxC5kxWpXFjAcWI+KdhNN92E999/H3PmzMHGjRsxfvx4nDx5Ev369QMAjBkzBo8//jgAID09HU2bNjX9q1y5MipWrIimTZsijX9s1igpKSsvLzugliuVAcDSpeJN/69WTmRnA5dcEtVNjCm5Quf+/ealiaPpxAnVQtCypfnAvnt30ep5yy2x2TYionigh2iLFkX/65eWqhAt2JXJ5QqdO3eKic4lfysBZmaaV6GOZogGACNHmm/rVWhSUhIwfz5w773AnDnWr/Cth2hcmdMZqldXY60lOuLWrhXHggBwzjnmudc6dgRGjBDjkyfF2H0Ca31/jMcQTQ/JGKIRqaBMhmd6iCZXFSZbinmI1qdPH4wdOxYzZ87EFVdcgTVr1mDWrFll7Zy7d+9GvpVveOTf7t0qIZchWuPGqqVh2TLg009FyyAg5jZLpDdCWYkGlLWzRt3//Z9YiRMQB25ERBRZnTur97ZFi6K/alZ+vnovrlMnuM+VIRoA/PGH+H/PHuDDD8U4JcX3SbserkU7RDv3XODMM8W4QQNg0CDvj6teHZg8GejZ0/ptatBAtdlp86KSjUWrEk1r5UT37p4ff+QRFUovWAD85z/mj/sLtZ1Or0ST4RlDNEpk7pVoejEGi4NszRbN9kOGDMEQH+1/b7zxRrmfO3XqVCs2iXSylRNQIZrLJVo6v/hCHJDov4fBg6O5dbGnX6XftQuoXz/62/DDD2rctWv0vz4RUbxLTxcXKb7+WsxNtmlTdKtFtPnQQq5EA0S1zJlnAg88oKrSbrrJdwVXw4YqHIh2iOZyAXPnAu++C1xxhT1OKmrWBN57T1R/3313rLeGAhGtEO2779TYW4hWuTLwzDOiPR0A7rpLtCfL6ka9vToeK9HYzklkVl47JyvRbC3mlWjkAN5CNMDc0vm//4n/69QBzjsvGltlH3olWqzmRdPnQ2MlGhGRNWLZ0hnJEG3FCuCVV8TtypXFfKS+XHutONBv1iw2F2lq1gRGjRIVYHbRr5+oKrJylUeKnGiHaJmZon3Tm759gUsvFePdu4Hhw8Uci3/8Afz+u3ocQzSi+MdKNMdiiEb+BRKiSddea54DIhHolWi7d0f/65eWqhCtenXRaktERJEXyxBNzocGhNfOuWaNCKVkO+qDD5pDBne9eonWz1WreJJLzhSNEG37drWSfefOvk+AXS6x0JNcJOWtt8TrSvPmYhViyU6hcaTorx9s5yRSIZq3OdEYotlagqUdFBJfIZpcDUuXaK2cgGc7Z7StXQscPCjGXbtyOWQiIqucdZZaFTPa86KFU4l2+unqgHzePODbb8W4USPPyfu9yclR84AROY2+sIBVIZq/Vk5d/frlV382aBDblYitwko0IjP5vsx2TsfhERH55ytEq15dzJUi53Bo0wZo2zaaW2YPejtnLCrR2MpJRBQdqalAt25iPtDdu4F166I3ubweogVbiZaSAjRpAqxebT5If/xxHqhT/MvIEHP+HT1qjxANENWgLVqIFs7du8XCVH/+KfbPMWOs2cZYY4hGZCYr0UpKxEU5tnM6BkM08k+GaNnZQJUq5o916qRCtESsQgNiX4nGRQWIiKLn/PNFiAaIarRohWjhtHMCol1s9Wp1+4ILgMsvD3+7iJwgL09U7m/dKqbBiPTUI3LxjeRk4Oyz/T/e5QIuvlj8SxQM0YjMZIgGiGo0VqI5Bts5qXwlJcC2bWKsV6FJ11wj/s/NBa6/PmqbZSs5OeqFLhYhmqxES0vzPZEtERFFhj4v2sKF0fu6shItNze0Vi99XrSkJODJJ9n+T4mjSRPxf0EBsHNnZJ/7wAExZyAAtGvne6XbRMc50YjM3EM0vRJN/xjZDkM0Kt/u3apP21uIdvnlYkWhtWvNbY2JxOVS33u02znz80U7ESACNB6AEBFZq0MHVZX92WeqosJKpaXqxD+UKjTAPN3C3/8upmAgShQyRAOA9etDf56iIuCrr8Txl6R3BATSypmokpNVMMBKNCJzy2ZhoapES03lRS6bY4hG5fM1H5quaVOgWrVobI19yZbO/fvNVxGstmSJGnM+NCIi66WkAFdeKcbHjqnWTivt2QMUF4txsIsKSFdeCdx0k5h6YerUiG0akSPoIdqGDaE/z513An/7m1iU47nnRMdGsPOhJTLZ0skQjch3OydbOW2PIRqVL5AQjWK3uADnQyMiir6BA9X4gw+s/3rhLCogpaUBr74KvPmmmOOUKJFEqhJNrmx79CgwYoS4gDl3rvp4t26hP3ci8BWiJSdzBWBKPL7aObmogO0xRKPybd6sxgzRfNMXF4hmiKavzMkQjYgoOi64QLV0fvqp9S2d+qICoVaiESWyxo3VOJwQzX11z6VLxZQmgFhkpEaN0J87EchqM/c50ViFRomIlWiOxRCNysdKtMDEYoXO4mLgl1/EuGFD4LTTovN1iYgSXVoa0LevGEejpVOvRGOIRhS8unXViWmoIVpxsZi2AwDq1TMv1gGwlTMQvirRGKJRItJDtMJCVqI5CEM0Kh9DtMDEop3zjz/UQciZZ0bnaxIRkaC3dL7/vrVfKxLtnESJLClJzGMGABs3isU6grV/P2AYYty2LfDrr8CECeKE1+UChgyJ2ObGLfcQTYYGDNEoEelhmV6JxhDN9hiiUflkiJadrVpXyFMsKtFkFRogVosjIqLoueACICdHjOfOtbalk+2cROGT86KdOmUOpgO1Z48an3aaqGx76CFx3LdlC3DeeRHZzLgmw7KiIrEoAyvRKJGxndOxGKKRbyUlwLZtYswqtPLFIkRbvlyNGaIREUVXaqq5pfPzz637WvoJf16edV+HKJ6Fu7iAPh+aPvdZbq5o7yT/ZCUaIAI0hmiUyLiwgGMxRCPfdu0S8z8ADNH8iUU7J0M0IqLYGjBAja1s6ZSVaNWqmU9CiShwVoVoFDj99evkSYZolNj0EO3UKXXezUo022OIRr5xPrTA5eSoF7xoVKKVlgIrVohx/friKigREUVXNFo6S0qAnTvFmK2cRKFjiBZ7eoh27JgKDRiiUSLSK86OH/d+P9kSQzTyjSFa4FwuVY0WjRBt/Xpx8AGwCo2IKFZSU4F+/cT4+HHgs88i/zX+/FMEaQAXFSAKR+PGarxhQ/Cf7z4nGgVPD8sOHVJjVt5QItIr0eR5HcD9wQEYopFvDNGCI+dFO3BA9bRbRW/l7NjR2q9FRES+6S2dH3wQ+efnogJEkZGXp0IcVqLFhl6JdvCgGrMSjRKRHqKxEs1RGKKRbwzRgqMvLmD1vGhcmZOIyB569gSqVhXjuXOBEyci+/z6ogKsRCMKXVKSqkbbtElVeAaKIVr4GKIRKb4q0Rii2R5DNPLt99/VuGHD2G2HU0RzcQEuKkBEZA9Wt3TqIRor0YjCI+dFKyxUK9AHSoZoLhfnog0VQzQihe2cjsUQjbwrKQFWrhTjhg2BypVjuz1OoFeiWTkvmmGoEC0vj/NyEBHF2lVXqfEnn0T2ubduVWOGaEThCWdxATknWrVqQEpK5LYpkfiaE40hGiUiLizgWAzRyLuNG1VLSrt2Md0Ux4hWiLZpE3D4sBizCo2IKPZ69AAqVRLj+fPVinPhOnYMePttMXa5gKZNI/O8RIkq1BDNMFQlGls5Q8dKNCKFlWiOxRCNvPv1VzVmiBaYaLVzspWTiMhe0tOB3r3F+MAB4IcfIvO8zzwD5OeL8cCB5vcZIgqevkJnMCHa8ePAyZNizBAtdAzRiBQuLOBYDNHIOz1EO+OMmG2Go0SrEo0hGhGR/Vx+uRp/+mn4z3f4MDBjhhgnJQHjx4f/nESJLtRKNC4qEBls5yRSuLCAYzFEI+9YiRY8vULAyhBNX5mzY0frvg4REQWuTx8gOVmMP/lEtH+F46mnVKXGkCFA8+bhPR8RiQueFSqIcTAhmpwPDWCIFg5WohEpeljGdk5HYYhG3v3vf+L/nBxOZByonBz1omdVO6e+qECNGubqNyIiip2cHODcc8V440ZgzZrQn+vAAeCJJ8Q4ORl46KHwt4+IxNyCsqVz8+bA5y/UK9G4oFPoGKIRKWzndCyGaORp715VSXXGGeKAg/xzuVSoZVUl2vbtwP79YtyhA383RER2csUVahzOKp2PPQYcOSLGN98MNGoU3nYRkSJbOouLzavfloftnJHBEI1I4cICjsUQjTzJKjSArZzBki2dBw4Ap05F/vnZyklEZF+RmBctPx+YOVOM09KABx4If7uISAllXjSGaJHBOdGIFM6J5lgM0cgTQ7TQ6e2VVrR0clEBIiL7atAAaNNGjJcuBf78M/jnmDZNtXXcdhtQr17kto+IGKLFEivRiBSGaI7FEI08cWXO0Fm9QqdeicYQjYjIfmQ1mmEA8+YF97n5+cBzz4lxRgZw332R3TYiUnOiAYGHaPrCApwTLXR6iFZYqMYM0SgR6WGZPica2zltjyEaeZIhWmoq0LJlTDfFcfQVOiNdiWYYKkTLyQHq14/s8xMRUfjCmRftu++AggIxvu02Lh5DZAVWosWOHqLpGKJRIuLCAo7FEI3MCgqAtWvFuGVL7sTBsrISbfdudRDXsSMXFSAisqOOHdUFla++Mh8Y+/P772osV/okosiqWRPIyhLjYEO0zEygYkVrtisR+ArLGKJRItJDtBMn1JiVaLbHEC2R/fmn59Leq1cDJSVizFbO4OmVaJEO0ZYuVWO2chIR2VNSkmrpLCgA/vvfwD9XD9FYCU5kDZdLtXRu2QIUFfn/HBmi1ajBi5jhYCUakaKHaDoWsdgeQ7REdf/9IvAZMEC0CUr6fGhcVCB4Vi4s8OqranzOOZF9biIiipxQV+mUIVpKinneJiKKLNnSWVICbN5c/mOLi4F9+8SY86GFhyEakcIQzbEYoiWiVauAqVPF+OOPgcWL1ce4Mmd4rGrn3LgRmD9fjOvWBfr0idxzExFRZPXsqVq+PvkEOHXK/+eUlKjpFJo04UE0kZVOP12N/R2v7d+vLjhzPrTwsJ2TSPH1Ps92TttjiJaIxo4FSkvV7Rkz1Jgrc4anShV1ILBjR+Se97nn1AHcsGGiSoGIiOwpI0MtMHDgADB3rv/P2bxZhW1s5SSyVtWqanzwYPmP5aICkZOaKlre3TFEo0TESjTHYogWjwwD+O034PBhz48tXAgsWGC+77PPgJUrxefJSrS6dc0HGBQYlwuoV0+Mt20zt8qG6tgx1cqZng7cemv4z0lERNa66SY1nj3b/+M5HxpR9OTkqPGBA+U/liFa5Lhc3ls6GaJRIvIVorESzfYYosWjl14C2rYV7SCrV6v7S0uBf/5T3e7RQ40fe0xMrnrkiLjNVs7Q1a8v/j9+3P+BWSDefFMFotdeC1SrFv5zEhGRtXr2FBekAODzz/23jDFEI4oePUTzV4m2Z48aM0QLH0M0IoGVaI7FEC3eGAbwxBNinJ8PXHSRCMcA4J13gOXLxbhdOzHZsaw2e+cd8+THDNFCJyvRAFGNFg7DAJ55Rt0eOTK85yMiouhISgJuuEGMS0vFBZHyMEQjip5gQjS9Eo0LC4TPW2DGEI0Ska+wjCGa7TFEizfLlwPr16vbu3aJIG37drEipzRjBlCpEjBihLhdXAw8+KD6OOdDC52sRAOArVvDe66FC9WJVbduQPv24T0fERFFz403qvHs2eW3+MvX+qQkoGlTSzeLKOHpU5awnTO6WIlGJLCd07EYosWbd95RY/mGtH490KaNCnR69QIuvFCMR4xQjzt6VH0uK9FCF8kQTa9Cu/PO8J6LiIiiq1Ej4NxzxXjtWmDpUu+PKy0F1qxRn8MTSiJrhVqJxhAtfO4hWlISF8yixMR2TsdiiBZPSkuB994T45QU4McfgTp1xG05p5bLBUyfrj6nenXz5MeAqFBr0MD67Y1XkWrn3LxZtdjm5QFXXhnWZhERUQwEssDAtm3AiRNizFZOIutxTrTYcQ/RMjLE+QlRomElmmMxRIsn338P7Nghxr16ida/L780l6zfcINYdED3j3+Yl5tu29b78tMUmEhVoj3/vGr9GTbM9wstERHZ11VXARUrivF776mwTMf50IiiKztbBTeBtnO6XFzcKRLcK21ZeUuJyuUCkpM972clmu0xKYkn776rxtdcI/5v0QL47DOxQljLlsDkyZ6f17gx0L+/us1WzvDUqaNCyFBDtNJS4NVXxTg9HbjttshsGxERRVdWFjBwIADAdeQIUufN83wMQzSi6EpKAqpUEeNA2zlzc9l2GAneKtGIEpW3wIwhmu0xRIsXRUXABx+IcWYmcMUV6mOdOokwZ/VqoFYt759/331qh73kEmu3Nd6lpgK1a4txqO2cO3aoK6MXXijabomIyJm0ls60t9/2/DhDNKLoky2dgYZobOWMDIZoRIq3TiO2c9oeQ7R48fXXwL59YnzZZeLKt87fXAPt2gH/+x+wbBnQu7clm5hQ5Lxoe/cCJ08G//kbNqhx8+aR2SYiIoqNbt3EggEAUr791rNKefVq8b/Lxdd8omiR050cOiQ6ALw5fly1YDNEiwyGaESKtxCNU/jYHkO0eKGvyilbOYPVvDlw1lmR2Z5Ep8+LFko1mh6iNW4c/vYQEVHsuFzAjTeKoWEAs2apjxmGqkQ7/XSgQoWobx5RQpKVaKWlwJEj3h/DRQUij3OiESnugVlaGhfacACGaPHg5Elgzhwxzs5mJZkdMEQjIiLdjTfCkPMpPf88cPSoGO/YARw7JsZs5SSKnkBW6JStnABw2mnWbk+iYCUakeI+/xnnQ3MEhmjxYMECdTDerx/7qO1AtnMCoS0usH69GjdpEv72EBFRbNWpAwweDABwHTwIvPSSuJ/zoRHFhr56fSAhGivRIoMhGpHirRKNbI8hWjyIRCsnRZZeiRZKiCYr0dLSxIkXERE535gxMGSbxhNPAKdOMUQjihW9Ek0u5uSOIVrksZ2TSHEP0VgM4wgM0ZzuyBFg/nwxrlEDOP/82G4PCeG0c5aWAhs3inHDhkBycuS2i4iIYqdFCxRdeqkY794NvPYaQzSiWAmknZNzokUeK9GIFFaiORJDNKfbvh0oKBDjgQMBOd8KxVY47Zy7dqkVPTkfGhFRXDl1993qxrRpwMqV6naLFtHfIKJEFWw7J+dEiwz3EI2VN5TIWInmSAzRnK5pU2DYMODyy4Hx42O9NSRVqqSucAYboumLCnA+NCKiuFLSvj2Mv/1N3Ni0CVi2TIzr1hXvHUQUHWznjA1WohEpXFjAkVi25HSpqcBzz8V6K8ib+vXFlc0dO4CSksDbMrkyJxFRfBs3Dvjvf833sZWTKLqCXZ2TIVpkcE40IoWVaI7ESjQiq8iWzuJiMfdNoBiiERHFtx49gLPPNt/HEI0ougJp55RzomVkAFlZ1m9TImAlGpHCOdEcyRYh2ltvvYWePXuiTZs2GDBgAFbq84O4ef/993HttdfirLPOwllnnYUbb7yx3McTxYy/FToPHfL+eevXqzFDNCKi+ONyAffea76PIRpRdAXTznnaaWK/pfAxRCNSGKI5UsxDtAULFmDKlCkYPnw45syZg+bNm+OWW27B/v37vT5+6dKluOSSS/D666/j3XffRa1atXDzzTdjj756DpEdlLdC5333iYO3227z/DxZiZaaal6ggIiI4sellwKtW6vbDNGIostfO2dJCbBvnxizlTNyGKIRKWzndKSYh2izZ8/GwIED0b9/fzRu3BgTJkxARkYGPvzwQ6+Pf/zxxzF48GC0aNECjRo1wqRJk1BaWoolS5ZEecuJ/PC1QmdBAfD002L86qvmq5+GoUK0Bg242ioRUbxKSgJmzhQtYt27A507x3qLiBJLVpaar9ZbiLZ/vzguAxiiRRLnRCNSuLCAI8X0DL2wsBCrV6/G0KFDy+5LSkpC165dsWLFioCe4+TJkyguLkZ2dnZQX9swDBjyjZFsS/6eHPm7qlcPsvDf2LJFHYgtXAjXiRNiXFoK44svgEGDxO3du8s+ZjRurD6HyEKO3s+IHMRjX+vRQ7T2u1ziH/dBoogI+H2talW48vNhHDjguf/9+ac6jqtenftnpGRkQG+MNdLT+bN1MB5Dhik1lfuDjQT6dxzTEO3gwYMoKSlBbm6u6f7c3Fxs2rQpoOd47LHHUKNGDXTt2jWor33kyBEkJcW8EI/8MAwDJ/4KlVwOm4vClZMDGe0Wb9qE44cPAwAyP/oIeqFu0aef4kTv3gCA5BUrUOmv+wvr1sXJvz6HyEpO3s+InIT7GlF0BLqvVcrORnJ+PnDgAA67HXOlbN4MuZTAqexsFPCYLCKSiotRWbt90jBQyJ+tY/F9LTwVDAN67VkRgBPcH2KmtLQ0oMc5ulfs5ZdfxoIFC/D6668jPcj+4cqVKyNZlnCTbck0ODs723kvzJUqwUhPh+vUKaTs2iWqJQ0D+PJL08NSFy5EdqVKorXnzz/L7k9r2RJpQVZYEoXC0fsZkYNwXyOKjoD3tdxcYMMGuI4eRXbFiuZpNI4fLxum16uHdB6TRUb16qabmTk5yOTP1rH4vhamChVMN1OzsoLusKPIKSkpCehxMQ3RcnJykJyc7LGIwP79+1GtWrVyP/eVV17Byy+/jNmzZ6N58+ZBf22Xy8Ud3SHk78pxv6/kZDEv2vr1cMk50VatArZvNz3MtXcv8OuvQMeOwMaN6v6mTbkSFEWNY/czIofhvkYUHQHta1WrqscfPgzo5x/aomUurs4ZOW6hgSszkz9bh+P7WhjcCoFc6encH2Io0L/hmPYzpqWloVWrVqZFAeQiAe3bt/f5ef/617/w/PPPY9asWWjTpk00NpUoNHKFzmPHxLw3c+eqj51xhhp/9pn4f/16dV/jxpZvHhEREVHCKm+Fzp071TgvLzrbkwi4OieR4r46JxcWcISYTwp200034f3338ecOXOwceNGjB8/HidPnkS/fv0AAGPGjMHjjz9e9viXX34ZTz/9NCZPnoy8vDzk5+cjPz8fx7WSayLbcF+hUw/RZs5U4wULxP9yZc7kZBXAEREREVHklRei7dihxnXqRGd7EgFDNCLFPUQLcooqio2Yz4nWp08fHDhwADNnzkR+fj5atGiBWbNmlbVz7t6927QAwLvvvouioiLceeedpucZMWIERo4cGdVtJ/JLD8L+7/+AZcvEuHVr4NxzgRYtgDVrgKVLxVLqMkQ7/XTPF1UiIiIiihytnRMHDpg/podorESLHPeQgCEaJTJWojlSzEM0ABgyZAiGDBni9WNvvPGG6fbChQujsUlEkaGHaC+8oJYsvuwy8X/v3iJEKy0F3nxTtH0CQJMm0d1OIiIiokQTSCVabq5n9RSFzuUSwVlBgbjNEI0SGUM0R4p5OydRXNNDtBUr1PjSS8X/ffqo+559Vo05HxoRERGRtXyFaKWlwK5dYsxWzsjTQ0mGaJTI3EMztnM6AkM0Iivpc6JJ1aoBnTuLcbduQMWKYixbOQGGaERERERW09s59RAtPx8oKhJjhmiRxxCNSGAlmiMxRCOyUp06nssU9+kjFg4AxNWGCy7w/DyGaERERETW0ivR9DnROB+atfTgjCEaJTIuLOBIDNGIrJSWBtSubb5Pzocm9e7t+XmcE42IiIjIWr7aObkyp7VYiUYksBLNkRiiEVlNb+lMSQEuusj8cfcQLSlJrM5JRERERNbx1c7JEM1aDNGIBPfQjCGaIzBEI7KavrjAeecBlSt7frxFC/NtvoASERERWSuQdk6GaJEnw8v0dK58SomN7ZyOlBLrDSCKe3qI5t7KKfXuDaxZI8acD42IiIjIepmZ4qT11ClWokXT2LHA3r3AkCGeIQJRImE7pyOxEo3IagMGABUqALVqAddc4/0xffqocfPm0dkuIiIiokQnq6IYokVPz57AihXAPffEekuIYouVaI7ESjQiq3XsCOzaJa52+rq60LMnMGwYsHIlcOed0d0+IiIiokSVkwPs3m1u59y5U/xfuTJQqVJstouI4h8r0RyJIRpRNGRnl/9xlwt47rnobAsRERERCXJetBMngMJCcVIrK9FYhUZEVuLCAo7EEI2IiIiIiBKTvrjAwYMiRDt5UtzOy4vNNhFRYmA7pyMxRCMiIiIiosQk50QDREtnUZG6zUo0IrIS2zkdiSEaERERERElJvdKtEOH1G2GaERkJVaiORJDNCIiIiIiSkzuIZpcVABgiEZE1uKcaI6UFOsNICIiIiIiign3dk65qADAEI2IrMV2TkdiiEZERERERImJlWhEFCts53QkhmhERERERJSY3EM0VqIRUbSwEs2RGKIREREREVFi8tXOmZlpDtiIiCKNlWiOxBCNiIiIiIgSk69KtLw8wOWKzTYRUWLgwgKOxBCNiIiIiIgSkx6ibd0KHDkixmzlJCKruVeiud8mW2KIRkREREREiUkP0X77TY0ZohGR1fTQLC2N1a8OwRCNiIiIiIgSU1oaULGiGB88qO5niEZEVnMP0cgRGKIREREREVHi8raAAEM0IrKaHqJxUQHHYIhGRERERESJS1+hU2KIRkRW06vPWInmGAzRiIiIiIgocbESjYhigZVojsQQjYiIiIiIEhdDNCKKBZcLSE4WY1aiOQZDNCIiIiIiSlzu7ZypqUD16rHZFiJKLFlZ5v/J9hiiERERERFR4nKvRKtdG0jiaRIRRcG4cUDNmsDdd8d6SyhAfHcgIiIiIqLE5R6isZWTiKJl3Dhg1y5gyJBYbwkFiCEaERERERElLoZoRBRLLlest4CCwBCNiIiIiIgSl/ucaAzRiIjIB4ZoRERERESUuFiJRkREAWKIRkREREREiYshGhERBYghGhERERERJS73ds68vNhsBxER2R5DNCIiIiIiSlysRCMiogAxRCMiIiIiosRVpYoaJyUBNWvGbFOIiMjeGKIREREREVHiSk5WQVrNmkBqakw3h4iI7IshGhERERERJbbbbxdh2rBhsd4SIiKyMYZoRERERESU2KZMAY4dA+6/P9ZbQkRENsYQjYiIiIiIKCMj1ltAREQ2xxCNiIiIiIiIiIjID4ZoREREREREREREfjBEIyIiIiIiIiIi8oMhGhERERERERERkR8M0YiIiIiIiIiIiPxgiEZEREREREREROQHQzQiIiIiIiIiIiI/GKIRERERERERERH5wRCNiIiIiIiIiIjID4ZoREREREREREREfjBEIyIiIiIiIiIi8oMhGhERERERERERkR8M0YiIiIiIiIiIiPxgiEZEREREREREROQHQzQiIiIiIiIiIiI/GKIRERERERERERH5wRCNiIiIiIiIiIjIj5RYb0C0GYYBACgpKYnxllAgDMNAaWkpSkpK4HK5Yr05RHGJ+xlRdHBfI4oO7mtE0cF9jeKJzIhkZuRLwoVopaWlAIDffvstxltCRERERERERER2ITMjX1yGv5gtzpSWlqK4uBhJSUlMy4mIiIiIiIiIEpysrExJSUFSku+ZzxIuRCMiIiIiIiIiIgoWFxYgIiIiIiIiIiLygyEaERERERERERGRHwzRiIiIiIiIiIiI/GCIRkRERERERERE5AdDNCIiIiIiIiIiIj8YohEREREREREREfnBEI2IiIiIiIiIiMgPhmhERERERERERER+MEQjS7300kvo378/2rdvjy5dumDYsGHYtGmT6TGnTp3ChAkT0LlzZ7Rv3x4jR47Evn37TI/ZtWsX/v73v+OMM85Aly5dMG3aNBQXF5se8+mnn+Lyyy/HGWecgW7duuHee+/FwYMHLf8eiewgUvvapEmT0K9fP7Ru3RpXXHGFx9dZunQp7rjjDnTr1g3t2rXDFVdcgU8//dTS743ITqK1rwGAYRh45ZVX0KtXL7Ru3Rrdu3fHCy+8YNn3RmQXkdjP1q5di3/84x8477zz0LZtW/Tu3Ruvvfaax9daunQp+vbti9atW+Nvf/sbPvroI8u/PyK7iOa+Jv3yyy9o2bKlz/c+IrtjiEaWWrZsGQYPHoz3338fs2fPRnFxMW655RacOHGi7DGTJ0/GokWL8NRTT+GNN97A3r17MWLEiLKPl5SUYOjQoSgqKsK7776LqVOnYs6cOZg5c2bZY3755ReMHTsWV111FebNm4ennnoKv/32Gx588MGofr9EsRKJfU3q378/+vTp4/XrrFixAs2aNcPMmTPx6aefol+/fhg7diwWLVpk2fdGZCfR2tcA4NFHH8UHH3yAMWPG4LPPPsMLL7yAtm3bWvJ9EdlJJPazVatWoWrVqpgxYwbmz5+P22+/HU888QTefPPNssds374dQ4cORefOnfHJJ5/ghhtuwAMPPIDvvvsuqt8vUaxEa1+Tjhw5grFjx6JLly5R+f6ILGEQRdH+/fuNpk2bGsuWLTMMwzCOHDlitGrVyvjss8/KHrNhwwajadOmxooVKwzDMIzFixcbzZs3N/Lz88se8/bbbxsdOnQwTp06ZRiGYcyaNcu44IILTF/r9ddfN7p3727xd0RkT6Hsa7qZM2cal19+eUBf67bbbjPGjRsXke0mchqr9rUNGzYYLVu2NDZu3GjZthM5Rbj7mTR+/HjjuuuuK7s9ffp045JLLjE9ZtSoUcbNN98c2W+AyCGs2tekUaNGGU8++WRQx5lEdsNKNIqqo0ePAgCys7MBiCsXRUVF6Nq1a9ljGjVqhNq1a+PXX38FAPz6669o2rQpqlWrVvaYbt264dixY9iwYQMAoF27dvjzzz/xzTffwDAM7Nu3D1988QXOO++8KH1nRPYSyr4WzteqUqVKWM9B5FRW7WsLFy5EnTp1sHjxYvTs2RM9e/bE/fffj0OHDkVy84kcIVL7mfv71a+//upREdOtW7ew3xeJnMqqfQ0APvzwQ2zfvt1rZTaRkzBEo6gpLS3F5MmT0aFDB9Y5sGkAAAq/SURBVDRt2hQAsG/fPqSmpqJy5cqmx+bm5iI/P7/sMXqABqDstnxMx44dMWPGDIwaNQqtW7fGOeecg6ysLDz00ENWf1tEthPqvhaKBQsW4LfffkO/fv3C2mYiJ7JyX9u+fTt27dqFzz//HNOnT8eUKVOwevVq3HnnnRH9HojsLlL72fLly/HZZ59h4MCBZff5OsY8duwYCgoKIvydENmblfvali1b8Pjjj2PGjBlISUmx7psgigL+BVPUTJgwAevXr8fbb78d8efesGEDHn30UQwfPhzdunVDfn4+pk+fjocffhiTJ0+O+NcjsjMr9zXdTz/9hPvuuw+TJk1CkyZNLP1aRHZk5b5mGAYKCwsxbdo0NGjQAICYI61fv37YtGkTGjZsGPGvSWRHkdjP1q1bh2HDhpUdJxKRJ6v2tZKSEtxzzz0YOXJk2fsZkZMxRKOomDhxIhYvXow333wTNWvWLLu/WrVqKCoqwpEjR0xXOPbv34/q1auXPWblypWm55MrwsjHvPTSS+jQoQNuvfVWAEDz5s2RmZmJwYMHY9SoUahRo4al3x+RXYSzrwVj2bJluOOOO3DvvffiyiuvjMSmEzmK1fta9erVkZKSYjrhaNSoEQBg9+7dDNEoIURiP9uwYQNuvPFGXH311Rg2bJjpY9WqVfNYOXffvn3IyspCRkaGBd8RkT1Zua8dP34cq1atwpo1a/DII48AEFVvhmGgZcuWeOWVV7jQADkK2znJUoZhYOLEifjvf/+L1157DXXr1jV9vHXr1khNTcWSJUvK7tu0aRN27dqFdu3aARDzna1btw779+8ve8yPP/6IrKwsNG7cGABQUFCApCTzn3NycnLZNhDFu0jsa4FaunQphg4ditGjR+Pqq6+OxOYTOUa09rUOHTqguLgY27ZtK7tvy5YtAIDatWuH9T0Q2V2k9rP169fj+uuvx5VXXom7777b4+u0a9cOP/30k+m+H3/8Mej3RSKnisa+lpWVhblz5+Ljjz8u+zdo0CA0aNAAH3/8Mc444wxLv0eiSGMlGllqwoQJmDdvHp5//nlUrFixrHe+UqVKyMjIQKVKldC/f39MnToV2dnZyMrKwqRJk9C+ffuyF+Zu3bqhcePGGDNmDP75z38iPz8fTz31FAYPHoy0tDQAwPnnn48HH3wQb7/9Nrp37469e/di8uTJaNu2LU477bRYfftEUROJfQ0Atm7dihMnTiA/Px8FBQVYs2YNAFEBk5aWhp9++gm33347rr/+elx00UVlXyc1NZWLC1BCiNa+1rVrV7Rq1Qr33Xcf7rvvPpSWlmLixIk455xz2A5DcS8S+9m6detwww03oFu3brjpppvKniM5ORlVq1YFAAwaNAhvvfUWpk+fjv79++Onn37CZ599hpdeeikm3zdRtEVjX0tKSiqbY03Kzc1Fenq6x/1ETuAyWKZDFmrWrJnX+6dMmVI2EfmpU6cwdepUzJ8/H4WFhejWrRsefvhhU4nwzp07MX78eCxbtgyZmZno27cv7rnnHtPElG+88Qbeffdd7NixA5UqVcLZZ5+Nf/7znwzRKCFEal+77rrrsGzZMo/n+frrr1GnTh2MGzcOc+bM8fh4p06d8MYbb0TouyGyr2jtawCwZ88eTJo0Cd9//z0qVKiAc889F2PHjmVgTXEvEvvZM888g2effdbjOfLy8rBw4cKy20uXLsWUKVOwYcMG1KxZE8OGDeNiOZQwormv6Z555hl89dVX+OSTTyL0nRBFD0M0IiIiIiIiIiIiPzgnGhERERERERERkR8M0YiIiIiIiIiIiPxgiEZEREREREREROQHQzQiIiIiIiIiIiI/GKIRERERERERERH5wRCNiIiIiIiIiIjID4ZoREREREREREREfjBEIyIiIkog48aNw7Bhw8J6jqVLl6JZs2Y4cuRIhLaKiIiIyP5SYr0BREREROTduHHjMGfOHABAamoqatWqhSuuuAK33347UlJCO4y7//77YRhGJDeTiIiIKCEwRCMiIiKyse7du2PKlCkoLCzEN998g4kTJyI1NRVDhw4N6nlKSkrgcrlQqVIli7aUiIiIKL6xnZOIiIjIxtLS0lC9enXk5eXh2muvRdeuXbFw4UIUFhZi2rRp6N69O9q1a4cBAwZg6dKlZZ/30Ucf4cwzz8TXX3+NPn36oE2bNti1a5dHO2dhYSEmTZqELl26oE2bNrjmmmuwcuVK0zZ888036NWrF9q2bYvrrrsOO3fu9NjOL774Apdccglat26Nnj174tVXX7Xuh0JEREQUAwzRiIiIiBwkPT0dRUVFmDhxIlasWIEnn3wSn376KS6++GLceuut2LJlS9ljCwoK8K9//QuTJk3CvHnzkJub6/F806dPxxdffIGpU6dizpw5qF+/Pm699VYcOnQIALB7926MGDEC559/Pj7++GMMGDAAjz/+uOk5Vq1ahVGjRqFPnz6YO3cuRowYgaeffhofffSRlT8KIiIioqhiiEZERETkAIZh4Mcff8T333+PZs2a4aOPPsLTTz+NM888E/Xq1cMtt9yCjh07moKroqIijB8/Hh06dEDDhg2RmZlpes4TJ07g3XffxZgxY3DeeeehcePGeOSRR5Ceno7//Oc/AIB33nkH9erVw7hx49CwYUNcfvnl6Nu3r+l5Zs+ejS5dumD48OFo0KAB+vXrh8GDB+OVV16x/gdDREREFCWcE42IiIjIxhYvXoz27dujqKgIhmHg0ksvRa9evfDRRx/h4osvNj22sLAQVapUKbudmpqKZs2a+Xzubdu2oaioCB06dDB9Ttu2bbFx40YAwMaNG9G2bVvT57Vr1850e9OmTbjgggtM93Xo0AGvv/46SkpKkJycHMy3TERERGRLDNGIiIiIbKxz584YP348UlNTUaNGDaSkpGDBggVITk7Ghx9+6BFQVahQoWyckZEBl8sV7U0mIiIiiksM0YiIiIhsLDMzE/Xr1zfd16JFC5SUlODAgQM488wzQ37uevXqITU1FcuXL0deXh4A0QL622+/4YYbbgAANGrUCAsXLjR93v/+9z/T7YYNG2L58uWm+5YvX47TTz+dVWhEREQUNzgnGhEREZHDNGjQAJdddhnGjBmDL7/8Etu3b8fKlSvx0ksvYfHixQE/T4UKFXDNNddg+vTp+Pbbb7FhwwY8+OCDKCgowFVXXQUAGDRoELZs2YJp06Zh06ZNmDt3LubMmWN6nptvvhlLlizBc889h82bN2POnDl46623cPPNN0fy2yYiIiKKKVaiERERETnQlClT8MILL2Dq1KnYu3cvqlSpgnbt2qFHjx5BPc/o0aNhGAbGjBmD48ePo3Xr1pg1axays7MBALVr18YzzzyDKVOm4M0330Tbtm1x991347777it7jlatWuGpp57CzJkz8cILL6B69eq488470a9fv0h+y0REREQx5TIMw4j1RhAREREREREREdkZ2zmJiIiIiIiIiIj8YIhGRERERERERETkB0M0IiIiIiIiIiIiPxiiERERERERERER+cEQjYiIiIiIiIiIyA+GaERERERERERERH4wRCMiIiIiIiIiIvKDIRoREREREREREZEfDNGIiIiIiIiIiIj8YIhGRERERERERETkB0M0IiIiIiIiIiIiPxiiERERERERERER+fH/HF4qRs1/CboAAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "La serie presenta una marcada variabilidad a lo largo del período de estudio, con fases de crecimiento y disminución asociadas a cambios en el mercado petrolero internacional. Se observan episodios de fuertes caídas y posteriores recuperaciones, lo que sugiere la presencia de cambios en la volatilidad a través del tiempo."
      ],
      "metadata": {
        "id": "JfoPzECG0q3D"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 8.2 DISTRIBUCIÓN DE LOS INGRESOS\n",
        "\n",
        "\n",
        "# Crea una figura\n",
        "plt.figure(figsize=(10,5))\n",
        "\n",
        "# Grafica el histograma\n",
        "sns.histplot(\n",
        "    df[\"Ingreso_Publicas\"],\n",
        "    bins=25,\n",
        "    kde=True\n",
        ")\n",
        "\n",
        "# Agrega el título\n",
        "plt.title(\"Distribución de los Ingresos\")\n",
        "\n",
        "# Nombre del eje X\n",
        "plt.xlabel(\"Miles de USD\")\n",
        "\n",
        "# Nombre del eje Y\n",
        "plt.ylabel(\"Frecuencia\")\n",
        "\n",
        "# Muestra la gráfica\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 444
        },
        "id": "ChtldtjZ0yEf",
        "outputId": "131f377c-ff07-45cb-e182-141d117e9309"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 1 Axes>"
            ],
            "image/png": 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UxLBhw4iPj2fp0qVMnDiRU045BYClS5eycOFCJk6cSExMDKWlpSxevBgvL696obW53XLLLfz2229cfPHFXHzxxVgsltrXZffu3Q3axr/+9S/Wr1/PhRdeyMyZM+nevTuFhYXs3LmTtWvXsmHDBgCuvvpqgoKCGDx4MIGBgSQkJPDhhx8ybty42vDT0PfD1KlTGT58OH379sXPz4/4+Hi+/fbb404cIiLSEhSSREQa6OjUxs7Ozvj5+dGzZ08eeOABZsyYcdIRkQkTJpCamsrnn39Ofn4+/v7+DB8+nFtvvbV25jNnZ2eefPJJ5s+fz6OPPkpNTQ3z5s2zOSTdcMMN7N27lzfeeIPS0lJGjhzJI488UjtiBTB27Fjuu+8+3nnnHZ544gn69evHa6+9xn/+85962zKZTLz55pu8+uqrfPXVV6xatQo/Pz8GDx58zEVJ6+rRowcfffQRzzzzDK+//jpWq5X+/fvz3//+95hrJDXFqaeeyvPPP89zzz3HM888Q0xMDPPmzeOHH36o3Yk/au7cufTr149PPvmEZ599FpPJRGRkJOecc06961I11OOPP05UVBRLly7l+++/JygoiOuvv55bbrmldp3hw4cTHx/PihUryMnJwdvbm/79+/P000/b3L8N0a9fP958802eeuopnn/+ecLDw7nttttISEggISGhQdsICgri008/5eWXX+a7775j4cKF+Pn50b17d+66667a9WbNmsXy5ct55513KCsrIywsjNmzZ3PTTTfVrtPQ98Ps2bP58ccfWbNmDVVVVURERHDHHXdw9dVXN9+LIyLyNwzW5jobVkRERBzCTTfdxIEDB1i1apW9SxERaZN0TpKIiEg7VlFRUe/24cOH+eWXXxg+fLidKhIRaft0uJ2IiEg7NnHiRM477zyio6NJTU3lk08+wdnZmWuuucbepYmItFkKSSIiIu3Y2LFj+frrr8nOzsbFxYWBAwfyz3/+k86dO9u7NBGRNkvnJImIiIiIiNShc5JERERERETqUEgSERERERGpQyFJRERERESkjnY/cYPFYqGmpgaj0YjBYLB3OSIiIiIiYidWqxWLxYKTkxNG44nHi9p9SKqpqSE+Pt7eZYiIiIiISBsRFxeHi4vLCe9v9yHpaEKMi4vDZDLZuRo5GbPZTHx8vPrLAanvHJf6zrGp/xyX+s5xqe8c19G++7tRJOgAIenoIXYmk0lvYgei/nJc6jvHpb5zbOo/x6W+c1zqO8d1stNwNHGDiIiIiIhIHQpJIiIiIiIidSgkiYiIiIiI1KGQJCIiIiIiUodCkoiIiIiISB0KSSIiIiIiInUoJImIiIiIiNShkCQiIiIiIlKHQpKIiIiIiEgdCkkiIiIiIiJ1KCSJiIiIiIjUYdeQ9PHHH3P22WczePBgBg8ezKxZs/j5559r76+srGTOnDmMGDGCQYMGceutt5KTk2PHikVEREREpL2za0gKCwvjrrvuYsmSJXz++eeccsop3Hzzzezfvx+AJ554gp9++onnnnuODz74gKysLG655RZ7liwiIiIiIu2ckz0bnzBhQr3bd955JwsXLmTr1q2EhYXx+eef8/TTTzNy5EjgSGiaMmUKW7duZeDAgXaoWERERERE2ju7hqS6zGYzK1eupKysjEGDBrFjxw6qq6sZNWpU7TrdunUjIiLCppBkNpubuWJpCUf7Sf3leNR3jkt959jUf45Lfee41HeOq6F9ZveQtHfvXi666CIqKyvx8PDg5Zdfpnv37uzevRtnZ2d8fHzqrR8YGEh2dnaj24mPj2+ukqUVqL8cV2P6ztnZmT59++JkMrVgRceqMZvZtXMn1dXVrdpuW6ffO8em/nNc6jvHpb5rv+wekrp06cKyZcsoLi7m22+/5d577+XDDz9s9nbi4uIwtfKOmDSe2WwmPj5e/eWAbO07k8nEiu1p5JVWtmB1/xPg6cqU/hH07du3VdpzBPq9c2zqP8elvnNc6jvHdbTvTsbuIcnFxYVOnToB0K9fP+Lj43n//fc566yzqK6upqioqN5oUm5uLsHBwY1ux2Qy6U3sQNRfjsuWvssvqya7pHVGdQyGI/PV6P11LP3eOTb1n+NS3zku9V371eauk2SxWKiqqqJfv344Ozuzdu3a2vsSEhJIS0vTpA0iIiIiItJi7DqS9Mwzz3DqqacSHh5OaWkpX331FRs2bGDBggV4e3tz/vnn8+STT+Lr64uXlxePP/44gwYNUkgSEREREZEWY9eQlJuby7333ktWVhbe3t7ExsayYMECRo8eDcADDzyA0Wjktttuo6qqijFjxvDII4/Ys2QREREREWnn7BqSnnjiib+939XVlUceeUTBSEREREREWk2bOydJRERERETEnhSSRERERERE6lBIEhERERERqUMhSUREREREpA6FJBERERERkToUkkREREREROpQSBIREREREalDIUlERERERKQOhSQREREREZE6FJJERERERETqUEgSERERERGpQyFJRERERESkDoUkERERERGROhSSRERERERE6lBIEhERERERqUMhSUREREREpA6FJBERERERkToUkkREREREROpQSBIREREREalDIUlERERERKQOhSQREREREZE6FJJERERERETqUEgSERERERGpQyFJRERERESkDoUkERERERGROhSSRERERERE6lBIEhERERERqUMhSUREREREpA6FJBERERERkToUkkREREREROpQSBIREREREalDIUlERERERKQOhSQREREREZE6FJJERERERETqUEgSERERERGpQyFJRERERESkDoUkERERERGROhSSRERERERE6lBIEhERERERqUMhSUREREREpA6FJBERERERkToUkkREREREROpQSBIREREREalDIUlERERERKQOhSQREREREZE6FJJERERERETqUEgSERERERGpQyFJRERERESkDoUkERERERGROhSSRERERERE6nCyZ+Ovv/46q1atIiEhATc3NwYNGsRdd91F165da9eZPXs2GzZsqPe4WbNmMXfu3NYuV0REREREOgC7hqQNGzZw6aWXEhcXh9lsZv78+Vx99dV8/fXXeHh41K534YUXctttt9Xednd3t0e5IiIiIiLSAdg1JC1YsKDe7SeffJKRI0eyc+dOhg0bVrvczc2N4ODg1i5PREREREQ6ILuGpL8qLi4GwNfXt97y5cuX8+WXXxIcHMz48eO56aabGj2aZDabm61OaTlH+0n95Xhs7TuTyYTVasFqtbREWcc42o7eY/+j3zvHpv5zXOo7x6W+c1wN7TOD1Wq1tnAtDWKxWLjxxhspKipi4cKFtcsXLVpEREQEISEh7N27l6effpr+/fvz0ksvNWi7ZrOZrVu3tlDVItIU7u7u9OnTh+e/2kRqXkmrtBkZ4MXt04aya9cuysvLW6VNERERaVsGDhyIyWQ64f1tZiRpzpw57N+/n48//rje8lmzZtX+HBsbS3BwMFdccQVJSUnExMQ0ePtxcXF/+0JI22A2m4mPj1d/OaCm9F1gYCBmF68WquwvbXm7Akc+T+QI/d45NvWf41LfOS71neM62ncn0yZC0ty5c1m9ejUffvghYWFhf7vugAEDAEhMTGxUSDKZTHoTOxD1l+Oype8MBiMGQ+tckeBoO3p/HUu/d45N/ee41HeOS33Xftk1JFmtVh577DG+++47PvjgA6Kjo0/6mN27dwNoIgcREREREWkRdg1Jc+bM4auvvuKVV17B09OT7OxsALy9vXFzcyMpKYnly5czbtw4/Pz82Lt3L/PmzWPYsGH06tXLnqWLiIiIiEg7ZdeQdHSChtmzZ9dbPm/ePGbMmIGzszNr167l/fffp6ysjPDwcM4880xuuukme5QrIiIiIiIdgF1D0t69e//2/vDwcD788MNWqkZERERERARa50xpERERERERB6GQJCIiIiIiUodCkoiIiIiISB0KSSIiIiIiInUoJImIiIiIiNShkCQiHYqHiwmL1dqqbbZ2eyIiItI0dp0CXESktbk6mTAaDHwTn05eaVWLtxfg6cJZceEt3o6IiIg0H4UkEemQ8kqryCqutHcZIiIi0gbpcDsREREREZE6FJJERERERETqUEgSERERERGpQyFJRERERESkDoUkERERERGROhSSRERERERE6lBIEhERERERqUMhSUREREREpA6FJBERERERkToUkkREREREROpQSBIREREREalDIUlERERERKQOhSQREREREZE6FJJERERERETqcLJ3ASIi9mK2WMkorCCzuILiihqKK6oprqjBCjgZDZiMBlxMRgI8XQjyciXIywV/DxeMRoO9SxcREZEWpJAkIh1KeZWZD9cl8uG6RA5ml1Bttp70MQk5pbU/uzkZ6RLsSbdgL2ICPHA2aUBeRESkvVFIEpEOIb+sim3JBezJKKayxlK73N3ZRKSfO74ezni7OuHt5oTRaMBssVJjtlJRbSantJLckipySiqpqLGwO72Y3enFOBkN9A73YWC0HwGeLnZ8diIiItKcFJJEpF0rqqjmt/057M8qqV3WI8SLLkGeBHq6EOztisHQsMPnLBYraYXlHMwu5WB2CcUVNcSnFhKfWkinQA+GdvInyt+jpZ6KiIiItBKFJBFpl2rMFjYnFbDxcB41liOH1HUO9ODs/hH888yefLw+iaziykZt02g0EOXvQZS/B6f2CCK1oJwtSQUk5JSSmFtGYm4ZXYI8Gds9CH+NLImIiDgshSQRaXfSC8v5dmcmheXVAET6uTOuZzDB3q7Ehno3eOTo7xgM/wtMBWVVbE4qYEdaIYdySknMLSUu0pdTugY2uR0RERFpfQpJItJuWK1WtiQXsOZADhYreLqaGNs9mJ6hXs0SjE7Ez8OFCb1CGBjtx28HcjiUU8q2lEIOZJUwY3Bki7UrIiIiLUMhSUTahYpqM9/tyqydia5niBcTeofg6mRqtRoCPF04Z0AEyXll/LQ3i/yyaj5Yl0RZlYWHz+6Dr7tzq9UiIiIittPctSLi8ArLq/lkYzIJOaWYDAbGxwYzuV9YqwakuqIDPLhkeAyDY/wwAJ9vTmHyc7/wR2KeXeoRERGRxlFIEhGHll1cyeJNyRSWV+Pt5sTMoVH0j/Jr0cPrGsLJZGRsj2CuHduVLkGepBdWMOv1dSz47RBW68mvzSQiIiL2o5AkIg4rNb+czzanUFZlJtDLhVlDown1cbN3WfV0CvRg+a1jmNo/nBqLlce+2sXNH2+muKLa3qWJiIjICSgkiYhDSswtZenWVKpqLIT7unHB4Cg8XdvmaZZerk68dPEgHj27D84mAyviM7jg1bWk5JfZuzQRERE5DoUkEXE4aQXlfLU9HbPFSudAD84bFImbs33OP2oog8HAFaO7sOj6kYR4u7I3s5jpL//OtuQCe5cmIiIif6GQJCIOJbu4ki+2pVFjsdIp0INp/SNwNjnOR9ngGH+W3TyaXmHe5JRUMuuNtXwTn27vskRERKQOx9mzEJEOL7+simV1DrGbGheOyWjfCRpsEeHnzmc3juK02GAqqi3c9PFmPliXaO+yRERE5E8KSSLiEMqqali2JZWyKjPBXq6cO8CxRpD+ysvVibcuH8plp8RgtcL/LdvBSz/u18x3IiIibYDj7mGISIdhtlhZEZ9BUUUNvu7OnDswAtc2fg5SQziZjDx2bj9um9AdgKdX7eOJFbsVlEREROxMIUlE2ryf92WTWlCOi8nIOQMi2uwsdrYwGAz888xYHpraG4A3fz3EA0vjsVgUlEREROxFIUlE2rTtKQXEpxYCMLlfGAGeLnauqGVcM7YrT13QH6MBFm5IVlASERGxI4UkEWmzUvLL+HlfNgCjuwXSJcjTzhW1rAuHRvPsrIEYDfDJxmTuX6KgJCIiYg8KSSLSJpVV1bByZwYWK8SGejOkk7+9S7KJh4sJSyPOMTp3YGRtUFq0KZn7lmxvdFBqTHsiIiJyrPZzYL+ItBtWq5XvdmVSWmkmwMOF03uHYDA43lTfAK5OJowGA9/Ep5NXWtXgx10wOIpP/0hh8aYUknLLmNY/vEGvQYCnC2fFhTelZBERkQ5PIUlE2pwtyQUczi3DZDRwVlyYQ0/1fVReaRVZxZUNXj/cz50z+4by7c5M1h3KwwKM7BrYcgWKiIhILcff8xCRdiWzqII1B3IAOLVHEEFernauyH56hflwWs9gADYcymNLUr6dKxIREekYFJJEpM2oqrHwzY4j5yF1C/YkLtLX3iXZ3YBov9oRpF/257ArrcjOFYmIiLR/Ckki0masOZhDYXk1Xq5OTOwd6rDnITW3YZ39GRTtB8D3uzM5mF1i34JERETaOYUkEWkTkvPK2J5y5HpIE3uH4OZssnNFbYfBYGBsjyD6hPtgBb6JzyApr8zeZYmIiLRbCkkiYneVNWa+350JQL8IHzoFtu/rIdnCYDBweq8QugV7YrZa+Wp7GhmFFfYuS0REpF2ya0h6/fXXOf/88xk0aBAjR47kpptuIiEhod46lZWVzJkzhxEjRjBo0CBuvfVWcnJy7FSxiLSEb3dmUlRRg7ebE2N6BNm7nDbLaDQwuW8Y0f7uVJutfLE1tVHTiouIiEjD2DUkbdiwgUsvvZTFixfzzjvvUFNTw9VXX01Z2f8OI3niiSf46aefeO655/jggw/IysrilltusWPVItKcfj+Yw/pDeQBM7B2Kq5MOs/s7TiYj0/pHEObjRkWNhS+2plJaWWPvskRERNoVu4akBQsWMGPGDHr06EGvXr148sknSUtLY+fOnQAUFxfz+eefc9999zFy5Ej69evHE088wZYtW9i6das9SxeRZlBRbeaBJfEA9Iv0ISbAw84VOQYXJyNnDwjH192ZoooavtyWRrXZYu+yRERE2o02dTHZ4uJiAHx9j0z7u2PHDqqrqxk1alTtOt26dSMiIoKtW7cycODABm/bbDY3a63SMo72k/rL8djSd6/+dIDDuWV4uzoxulsgVmtr7OgfacNqtTh0e+7ORs4dEMbiP1LJKq7kmx3pTI0Lq22jMf1gsVhwd3fHYlHQckT63HRc6jvHpb5zXA3tszYTkiwWC0888QSDBw+mZ8+eAOTk5ODs7IyPj0+9dQMDA8nOzm7U9uPj45utVml56i/H1dC+Syuu4eXVR84vHNvZk/ycrJYsq1aYmwWIpKCgkIzsAodvb1SkC6sTKziUU8bKrUlcPDgMi9WKydTwwxZNJhN9+vSxuYYas5ldO3dSXV1t8zak6fS56bjUd45Lfdd+tZmQNGfOHPbv38/HH3/cItuPi4tr1E6D2IfZbCY+Pl795YAa03dWq5X572yixgKn9gxmZGwQ2SWtMwGBn5/3n//7UmVyc/j2wgA3rxJW7MjkQH4NO/MsGA0GVmxPI6+0skHbsFghPy8X/4BAjI28NFWApytT+kfQt2/fxhcvzUKfm45Lfee41HeO62jfnUybCElz585l9erVfPjhh4SFhdUuDwoKorq6mqKionqjSbm5uQQHBzeqDZPJpDexA1F/Oa6G9N0XW1NZczAXFycjj53bl9/252AwtNYpkkfaMRiMrdRmy7fXI9SHsZVmft2fw5ItaZzeO4yCsmqySxo2smO1WsjIK8Hs4tXoGo+ur99X+9PnpuNS3zku9V37ZdeJG6xWK3PnzuW7777jvffeIzo6ut79/fr1w9nZmbVr19YuS0hIIC0trVHnI4lI21FUUc3jX+8G4Nbx3XVNpGYyKNqPAVFHzue8c/FWEnNL7VyRiIiI47LrSNKcOXP46quveOWVV/D09Kw9z8jb2xs3Nze8vb05//zzefLJJ/H19cXLy4vHH3+cQYMGKSSJOKiXfjxAdnElXYM8uW5cV3uX024YDAZO7RmM1QrbUwv5cH0SFwyJwt/Dxd6liYiIOBy7hqSFCxcCMHv27HrL582bx4wZMwB44IEHMBqN3HbbbVRVVTFmzBgeeeSRVq9VRJouIbuEd9YcAuD/zu6jayI1M6PBwFWju/DO2sNsSy7gy21pzBoajZuzXmcREZHGsGtI2rt370nXcXV15ZFHHlEwEmkH/v31bqrNVsbHBjM+NsTe5bRLLk5G3rx8CGfM/4WCsmq+jk9n+sBITI2dkUFERKQDs+s5SSLScazem8UPe7JwMhp4aJrt003LyYV4u3H5KZ1wNhlIyS9n9b4srFarvcsSERFxGApJItLiqs0WHvtqFwBXjOpMt2AvO1fU/oX5ujG575HZQnekFrE1ucC+BYmIiDgQhSQRaXEfrE3kYHYpgZ4u3Hp6D3uX02F0DfZibPcgAH7dn8OhHM14JyIi0hAKSSLSogrLqnn+h/0A/OvMWHzdne1cUccyKMaPvhE+WIGVOzLIKWnYBWZFREQ6MoUkEWlRr/x8gMLyanqGenHh0Ch7l9PhGAwGxseGEOXnTpXZwpfb0iirqrF3WSIiIm2aQpKINBt3d/d6t1MLynlnzWEA7jurF04mfeTYg8loYGr/cHzdnSmuqOGr7enUmC32LktERKTN0h6LiNRjsXEWNJPJRJ8+fTCZ/ndNnmdW7aWqxsIpXQM05beduTmbOHdABK5ORtILK/h+j2a8ExERORG7XidJRNoeo8HAN/Hp5JVWNepxVquF3NxcAgMDMRiMpBWUs3RzKgCDov34eH3SMY/pHOjB6B7BzVK3nJy/pwtT4sJZtjWVvRnFBHi4MLxLgL3LEhERaXMUkkTkGHmlVWQVN+4Ef6vVQkZeCWYXLwwGI8u3p2MFeoZ64eJkOu72/D1cmqliaaiYAA/G9wzhx71ZrE3Ixd/Dme4hnvYuS0REpE3R4XYi0uyS8spIyivDaIBR3YLsXY78RVyULwOj/QBYtSuTzKIK+xYkIiLSxigkiUizslqt/H4wB4D+kX6a8ruNGtsjiM6BHtRYrHy1PYOyak3kICIicpRCkog0q4ScMjKLKnE2GRja2d/e5cgJGA0GJvcLI9DThdIqM78lV1KtGe9ERESAJpyTVFZWxsaNG0lLS6O6urrefZdffnmTCxMRx2OxWlmXkAfAwGg/PF112mNb5upk4pwBEXyyMYmCCgvf7sxiWv9wDAaDvUsTERGxK5v2YHbt2sV1111HeXk55eXl+Pr6kp+fj7u7OwEBAQpJIh1UcpGZ3NIqXJ2MDInRKJIj8HF3Zlr/cD7fnEpCTim/H8xldHedRyYiIh2bTYfbzZs3j/Hjx7Nx40ZcXV1ZvHgxP/30E3379uXee+9t7hpFxAGYLVZ2ZB2ZNnxIJ39cnU0neYS0FeG+bgyLcAVgU2I+u9KK7FyRiIiIfdkUknbv3s2VV16J0WjEZDJRVVVFeHg4d999N/Pnz2/uGkXEAexKL6K02oq7s6l25jRxHJ18nRj25zlkP+zJJCW/zM4ViYiI2I9NIcnJyQmj8chDAwMDSUtLA8DLy4uMjIzmq05EHEKNxcLGw/kADO/sj7NJc8I4olO6+NMjxAuLFb7ank5+WeMuKCwiItJe2HROUp8+fYiPj6dz584MGzaMF154gfz8fL744gt69OjR3DWKSBu3M62Ikkoz7k4G+kb62LscsZHBYODMPqEUV9SQUVTBl1vTuHBYNO46dFJERDoYm77uvfPOOwkODq792cfHh0cffZT8/Hwee+yxZi1QRNq2GouFTX+OIvUKcsbJqJnRHJmTyci0/uF4uzlRUF7N19vTMVus9i5LRESkVdk0khQXF1f7c2BgIAsWLGi2gkTEsexKK6KksgZPVxNd/TTld3vg6erEuQMiWLwphdSCcn7Yk8kZvUM1NbiIiHQYOnFARGxW91ykoZ38MWkUqd0I9HJlSlwYBgPsTi9mY2K+vUsSERFpNQ3+2ve8887j3XffxdfXl+nTp//tN4pLly5tluJEpG2rO4rUN9ybnOxye5ckzahToCen9Qzmp73ZrD2Yi5+7Mz1Dve1dloiISItrcEg6/fTTcXFxAWDixIktVpCIOIa6o0jDOgXgpBnt2qX+UX4UlFWzJbmAVbsy8XZzItzX3d5liYiItKgGh6RbbrnluD+LSMe0O634f6NIEZrRrj0b0yOIgvJqDuWUsnxbOhcNi8bH3dneZYmIiLQYm7763b59O9u2bTtm+bZt24iPj29yUSLStpktVjYczgNgqEaR2j2jwcDkvmEEe7lSXm3my21pVNaY7V2WiIhIi7Fpz2bu3Lmkp6cfszwzM5O5c+c2uSgRadtqz0VyMdFPo0gdgouTkbMHhOPpYiK3tIoV8RlYNDW4iIi0UzaFpIMHD9K3b99jlvfu3ZsDBw40uSgRabvMFisbE/8cReqsUaSOxNvNmbMHROBkNJCUV8bqfdlYrQpKIiLS/ti0d+Pi4kJOTs4xy7Ozs3Fy0nVSRNqzXelFFFdoFKmjCvVxY3K/MADiUwv57cCxfwtEREQcnU0hafTo0cyfP5/i4uLaZUVFRTz77LOMGjWq2YoTkbbFbLGy8c9zkYZ08tcoUgfVLdiLsT2CAFi5M5Mvt6XZuSIREZHmZdOwz7333sull17K+PHj6d27NwB79uwhMDCQp556qlkLFJG2Y/efo0geLibiIn3tXY7Y0aBoP4oratiaXMBdi7cR7OXKyG6B9i5LRESkWdgUkkJDQ/nyyy9Zvnw5e/bswc3NjfPPP5+pU6fi7KxpYUXao7qjSEM1itThGQwGxvYIotpsYWdaEdd9sInPbxyli82KiEi7YPMJRB4eHsyaNas5axGRNmxvZjFFFTW4O2sUSY4wGgzMHBKFu3M6mxLzueLtDSy9eTShPm72Lk1ERKRJbA5Jhw8fZv369eTm5mKxWOrdp4vNirQvFquVTX+OIg3u5KdRJKnlbDLy5uVDOf+130nILuWKdzay+PpT8HbTUQUiIuK4bApJixcv5tFHH8Xf35+goCAMBkPtfQaDQSFJpJ05mFVCflk1rk5G+kf62bscaWP8PV1478rhnPfKGnanF3Hjh5t5+4phuDgpTIuIiGOyKSS9+uqr3HHHHVx33XXNXY+ItDFWq5UNf44iDYz2046vHFd0gAdvXzGMi95Yx28HcrhvyXaemTmg3pdoIiIijsKmvZ3CwkLOOuus5q5FRNqgw7ll5JRU4WwyMDDaz97lSBvWP8qPly8ZjMloYMnmVJ76dq+9SxIREbGJTSFp8uTJ/Pbbb81di4i0MVbr/2a06x/ph5uzyc4VSVs3vlcIT5zXD4BXVx/krV8T7FyRiIhI49l0uF2nTp14/vnn2bZtGz179sTJqf5mLr/88mYpTkTsKyW/nPTCCkxGA4Ni/OxdjjiIWcNiyC2t4qmVe3n86934e7hw/pAoe5clIiLSYDaFpEWLFuHh4cGGDRvYsGFDvfsMBoNCkkg7cXQUqW+ED56uNk+GKR3QjeO6kVtSxYLfDnHP59vx93RmQq9Qe5clIiLSIDbt9fz444/NXYeItDEZhRUk55djNMCQTv72LkccjMFg4MEpvckrrWLpllRu+mgzH149gqGdA+xdmoiIyEk1aZqqqqoqEhISqKmpaa56RKSNODqjXa8wH3x0zRuxgdFo4KkL+jM+NpiKagtXvbuRvRnF9i5LRETkpGwKSeXl5TzwwAMMHDiQadOmkZ6eDsBjjz3GG2+80awFikjryyis4FBOKQZgaGeNIontnE1GXrl0CEM6+VNUUcPlb68nOa/M3mWJiIj8LZtC0jPPPMOePXt4//33cXV1rV0+cuRIVqxY0WzFiYh9rN6XDUCPEC/8PVzsXI04OncXEwv+MZSeoV5kFlVy+dsbyCmptHdZIiIiJ2RTSPrhhx94+OGHGTp0aL3lPXr0ICkpqVkKExH7OJhdwo7UQgCdPyLNxs/DhfevGkGknzuHckq57K31FJRV2bssERGR47IpJOXl5REYGHjM8vLycl1dXcTBvbr6IFaga5Anwd6uJ11fpKHCfN348JoRBHu7siejmH+8s5Hiimp7lyUiInIMm0JSv379WL169THLP/30UwYOHNjEkkTEXlLyy1i2JRWAYRpFkhbQJciTD68egb+HM9uSC7j63U2UV5ntXZaIiEg9Nk0Bfuedd3Lttddy4MABzGYz77//PgcPHmTLli188MEHzV2jiLSSN35JoMZipVuwJ2G+bvYuR9qp2DBv3r9qBJe8uY4Nh/O47oNNvPWPobg6mexdmoiICGDjSNLQoUP54osvMJvN9OzZkzVr1hAQEMAnn3xCv379mrtGEWkFWcUVfLIxGYDTegbbuRpp7+KifHnnymG4O5v4dX8Ot3y8hWqzxd5liYiIADaOJAHExMTw+OOPN2ctImJHC349RFWNhcExfnQJ8iS7RCfVS8sa2jmAt/4xlCvf3ch3uzL51+JtPDtrICajzm0VERH7sikkpaWl/e39ERERNhUjIvZRUFbFh+sSAbhlQnfSCyrsXJF0FKO7B/HqpYO5/oM/+HJbGu7OJubNiMOooCQiInZkU0iaMGHC385it3v37gZtZ+PGjSxYsIAdO3aQnZ3Nyy+/zMSJE2vvv++++1i6dGm9x4wZM4YFCxbYUraInMA7aw5TWmWmT7gP42ND+Hi9pvKX1nN671Ceu2ggty3cwqJNybg4GZl7bl/NlioiInZjU0hatmxZvdvV1dXs3r2bd955hzvvvLPB2ykrKyM2Npbzzz+fW2655bjrjB07lnnz5tXednHRhS1FmlNJZQ3v/n4YgJvHd9eOqdjFtP4RVFRbuPuzbXywLhGDAeaco6AkIiL2YVNI6tWr1zHL4uLiCAkJYcGCBZx55pkN2s64ceMYN27c367j4uJCcLBOIhdpKR+tS6SwvJquwZ5M7hdm73KkA7tgSBQWq5V7P9/O+2sTMQCPKiiJiIgd2Dxxw/F06dKF+Pj45twkGzZsYOTIkfj4+HDKKadwxx134O/v3+jtmM26DocjONpP6q/WUVFt5s1fEwC4/tQuYLUAJqxWC1Zr42Yas1istf8bjQ197JH1bGnPdq3dZttvz7a+o7YdaL7f2fMHRWAxW7h/2Q7eW5uIFSsPT+2toPQ39LnpuNR3jkt957ga2mc2haSSkpJ6t61WK1lZWbz00kt06tTJlk0e19ixYznjjDOIiooiOTmZ+fPnc+2117Jo0SJMpsZdT6O5w5u0LPVX6/jmQCk5JVUEexjpTDZ795bSp08fcnNzycgrOfkGjiMrK7PB64a5WYBICgoKycgusKm9xmrtNh2pvcb03VGmKi+gC3v37qW8vLzRjz+eHk5w4xAfXt1UxPtrk8jJzuGqgd4YDAacnZ3p07cvTo38G9AUNWYzu3bupLq6utXatIU+Nx2X+s5xqe/aL5tC0tChQ4/5Vs9qtRIeHs78+fObpTCAqVOn1v4cGxtLbGwsEydOrB1daoy4uLhGBytpfWazmfj4ePVXK6g2W7j1u18AuOX0XgwdHFN7X2BgIGYXr0Ztz2KxkpWVSUhIaINnJvPz8/7zf1+qTK1z8drWbtMR2rOl744K9HYFjnxGN6eBAyEmOoX7lu5gxYEyQkKCeWhKLwwGAyaTiRXb08grrWzWNo8nwNOVKf0j6Nu3b4u3ZSt9bjou9Z3jUt85rqN9dzI2haT33nuvXkgyGo34+/vTqVMnnJya9Qi+eqKjo/H39ycxMbHRIclkMulN7EDUXy3v8y1ppBVUEOTlyqzhMfVeb4PBiMHQuGtNHz1My2g0NOKxRpvbs11rt9n227Ot76htB2iR39eLRnTCYDRw7+fxvPt7IkaDkf+b1huA/LJqsktafmSnJZ9fc9PnpuNS3zku9V37ZVOiGTFiRHPX0SAZGRkUFBRoIgeRJjJbrLy6+iAA147tgpuzPuClbZo1LAarFe5bEs/baw5hsVp55Ow+9i5LRETaOZtC0uuvv05gYCAXXHBBveWfffYZeXl5XHfddQ3aTmlpKUlJ/7seS0pKCrt378bX1xdfX19eeuklJk2aRFBQEMnJyfz3v/+lU6dOjB071payReRPK+LTOZRTiq+7M5ee0nznEYq0hIuGx2AFHlgaz7u/H6ay5sg1vURERFqKTcd+LFq0iK5dux6zvEePHnzyyScN3s6OHTuYPn0606dPB2DevHlMnz6dF154AZPJxL59+7jxxhuZPHkyDz74IH379uWjjz7StZJEmsBqtfLyTwcAuHJ0Z7xcW+4QWZHmcvHwGP57wQCMBli4IZnPN6fWzsonIiLS3GzaO8rOzj7uIW8BAQFkZ2c3eDsjRoxg7969J7x/wYIFtpQnIn/jxz1Z7MkoxtPFxBWjOtu7HJEGu2BIFG7ORu74ZCtbkwsoqaxhct8wTI2cbEJERORkbBpJCg8PZ/Pmzccs/+OPPwgJCWlyUSLSMqxWKy/9OYp02Smd8PPQqKw4lmn9I3jl0sGYjAYOZJXwdXw6NebWusaWiIh0FDaFpJkzZ/LEE0/w+eefk5qaSmpqKp999hnz5s3jwgsvbO4aRaSZrD2Yy5akAlycjFw9tou9yxGxyZl9w5g9IgaT0cChnFKWb0+nWkFJRESakU2H211zzTUUFBQwZ86c2ovrubq6cs0113D99dc3a4Ei0nyOjiJdNCyaEO/WuS6RSEvoEerNuQMiWL49jaS8Mr7YmsY5AyJwcWqtqeRFRKQ9sykkGQwG7r77bm666SYOHjyIm5sbnTt31oQKIm3Y5qR8fj+Yi5PRwPXjutm7HJEmiw7wYPrASL7YmkZqQTlLtqRw7oBI3F00pb2IiDRNk75yy8nJobCwkJiYGFxcXLBaNdOQSFv1yp+jSOcNiiTSz93O1Yg0jwg/d2YMjsTN2UhmUSWf/ZFCcUXLX2RWRETaN5tCUn5+Pv/4xz+YNGkS1113Xe2Mdg888ABPPvlksxYoIk23O72I73dnYTDADadpFEnal1AfN2YOicbL1Ym8sio+/SOF/LIqe5clIiIOzKaQNG/ePJycnFi9ejVubv87r2HKlCn8+uuvzVaciDSPl348Moo0JS6cbsFedq5GpPkFeLowc2gUfh7OFFfU8OmmFLKKK+xdloiIOCibQtKaNWu4++67CQsLq7e8c+fOpKWlNUthItI89mUWs2JHOgC3jO9u52pEWo6PmzMzh0QR7O1KebWZz/9IJTW/3N5liYiIA7IpJJWVldUbQTqqoKBAkzeItDEv/LAfqxUm9w2jd7iPvcsRaVEeLk6cP/jIeXdVZgtLt6aSkFNi77JERMTB2BSShg4dyrJly+ots1gsvPXWW4wYMaI56hKRZrA/s5iv44+MIt12eg87VyPSOlydTEwfGEGXIE/MFitfbU9nd3qRvcsSEREHYtMU4HfffTdXXHEFO3bsoLq6mv/+978cOHCAwsJCFi5c2Nw1ioiNXvjxAFYrTOobSp8IjSJJx+FkMjI1Lpzvd2eyJ6OYVbsyKa2sYUgnfwwGg73LExGRNs6mkaSePXvy7bffMmTIEE4//XTKy8s544wzWLp0KTExMc1do4jY4EBWMV9tP3KOoEaRpCMyGQ2c2SeUwTF+AKw5mMvP+7Kx6HIVIiJyEo0eSaquruaaa65hzpw53HjjjS1Rk4g0gxf/HEU6s08ofSN87V2OiF0YDAbG9gjGy9WJX/bnsC2lkJLKGib3DcPJ1KRLBYqISDvW6L8Qzs7O7N27tyVqEZFmciCrhC+3aRRJ5KhBMf6c1S8Mk8HAwexSlm5JpaLabO+yRESkjbLpa7RzzjmHzz77rLlrEZFm8tKPR2a0m9g7lH6RGkUSAegZ6s30QRG4OBlJK6zg000pFFVU27ssERFpg2yauMFsNrNw4UJ+//13+vXrh7u7e73777///mYpTkQa72D2/0aR7pioUSSRuqL8PZg5JIovtqaRV1bF4k3JnDsgkmBvV3uXJiIibUijQlJycjKRkZHs27ePPn36AHDo0KF662jWIBH7eunHA1isMLF3iEaRRI4jyMuVC4ceCUq5pVV89kcK0/qHEx3gYe/SRESkjWhUSDrzzDP57bff+OCDDwC44447eOihhwgKCmqR4kSkcRKyS/hiayoAt5/e087ViLRd3m7OzBwSxfLt6aQWlLNsaypn9gkjNszb3qWJiEgb0Khzkqx/mTb1l19+oby8vFkLEhHbvfTTkVGk03uFEBelUSSRv+PqbGL6oAh6hHhhscLKnRn8kZhf72+dh4vJLlOGa5pyERH7sumcpKP+GppExH4O55TyxdYj5yLdrnORRBrEyWjkrH5heO7PYWtyAb8dyKGovJpxPYMxGg24OpkwGgx8E59OXmlVq9QU4OnCWXHhrdKWiIgcX6NCksFg0DlHIm3UCz/ux2yxMj42mP5RfvYuR8RhGAwGxvUMxtvNiV/357A9tZDCimrO6hdWu05eaRVZxZV2rFJERFpTo0KS1Wrlvvvuw8XFBYCqqioeffTRY2a3e+mll5qvQhE5qX2ZxSzdcuRcpDsm6lwkEVsMjvHH192ZlTsySMwt49NNKUT6uZ/8gSIi0u40KiSdd9559W6fc845zVqMiNjmmVV7sVphUt9QBkT72bscEYfVLdiLC4ZEsXzbkZnv/vvtXuI0Misi0uE0KiTNmzevpeoQERttSy7g252ZGA1w15mx9i5HxOGF+rgxa1g0X25LI6ekilmvr2XGoEhCfNzsXZqIiLSSRs1uJyJtz3+/3QvAeYOi6BGq6YtFmsORKcKj6RfhQ2WNhYUbk9l4OE8TFomIdBAKSSIO7PcDOfx2IAdnk4E7NKOdSLNycTJyw6nduGJUZwB+P5jL97uzMFsUlERE2juFJBEHZbVaeerPUaRLhscQHeBh54pE2h+j0cCj5/RlWv9wDMCu9CKWbU2lotps79JERKQFKSSJOKjvdmWyNbkAd2cTN0/obu9yRNq1kV0DOWdABM4mAyn55SzelExBWetcN0lERFqfQpKIAzJbrDyzah8AV47uTIi3TigXaWmdgzyZOSQaL1cn8suqWbQxmeS8MnuXJSIiLUAhScQBfbktlb2Zxfi4OXH9qd3sXY5IhxHs7cpFw6IJ9XGlosbC0q2pbEsu0IQOIiLtjEKSiIOpqrHw7Hf7AbjhtG74ejjbuSKRjsXT1YkLBkfRK8wbqxVW78vmhz2a0EFEpD1RSBJxMIs2JZOUV0aQl2vtrFsi0rqcTEbO7BPKmO5BGICdaUV8vjmF0soae5cmIiLNQCFJxIGUV5l58Ycjo0i3nd4dD5dGXQ9aRJqRwWBgSCd/zhkYgYuTkfTCCj7ZmExWUYW9SxMRkSZSSBJxIO+tPUxWcSVR/u5cNCzG3uWICNA50JOLhkbj7+FMSWUNn/6Rwt6MYnuXJSIiTaCQJOIg8kureOWnAwDcObEnLk769RVpK/w9XZg1LJrOgR7UWKys3JnBmgM5mtBBRMRBaS9LxEG88ON+iipq6B3uw/RBkfYuR0T+wtXJxNkDIhjSyR+ATYn5LN+eTmWNLjwrIuJoFJJEHMChnFI+WJsIwINTemMyGuxckYgcj9FgYEz3ICb1DcVkNHAop5TFG1PI14VnRUQcikKSiAN4auUeaixWTosNZkyPIHuXIyIn0SvMh5lDovBydSKvrIpPNiRzMLvE3mWJiEgDKSSJtHGbDufxzY4MjAa4/6ze9i5HRBoo1MeNi4ZFE+HnRpXZwlfb01lzIAeLrqckItLmKSSJtGFWq5XHv94NwKxh0cSGedu5IhFpDE9XJ2YMimJQtB9w5DylpVtTKavS9ZRERNoyhSSRNmz59nS2Jhfg4WLizjN62rscEbGByWjg1J7BnNUvDGeTgZT8chZuSCajUNdTEhFpqxSSRNqo8ioz81YcGUW6cVw3Qrzd7FyRiDRFz1BvZtW7nlIy21MKNE24iEgbpJAk0ka99vNB0gsriPRz59pTu9q7HJHj8nAxYdFOfoMFerkya1g03YI9sVjhp73ZfLsrk6oai71LExGROpzsXYCIHCu1oJzXfj4IwINTe+PmbLJzRSLH5+pkwmgw8E18OnmlLT/NdedAD0b3CG7xdlqSq5OJqXHhbE4qYM3BHPZmFJNZVMGUfuEEe7vauzwREUEhSaRNemLFbiprLIzoEsBZ/cLsXY7ISeWVVpFVXNni7fh7uLR4G63BYDAwpJM/4b5ufLMjg4KyahZtSubUHkGc3ivE3uWJiHR4OtxOpI1Zn5DL19vTMRrg4bP7YDDowrEi7VWEnzuXjIihS5AnZouVn/Zm88nGZIoqqu1dmohIh6aQJNKG1JgtPLp8FwAXDY+hb4SvnSsSkZbm7mzi7P7hjO0RhNEAO9KKmPrCr2xLLrB3aSIiHZZCkkgb8uG6RHanF+Hr7sy/NOW3SIdhMBgYHOPPzCFHZr9Lzivngtd+581fEnTxWRERO1BIEmkjsooreGbVPgDunhRLoJdO4BbpaMJ83bj5tO5MiQuj2mzl3yt2c+lb60ktKLd3aSIiHYpCkkgbMW/FHoora+gf5cvFw2PsXY6I2Im7i4mXLxnMkzPi8HAxsTYhl8nP/cKyLam6ppKISCuxa0jauHEjN9xwA2PGjCE2Npbvv/++3v1Wq5Xnn3+eMWPG0L9/f6644goOHz5sn2JFWtC6hFyWbknFYIDHp/fDZNRkDSIdmcFg4KLhMay4bSyDYvworqjhjkVbuWXhFgrKWn6qdRGRjs6uIamsrIzY2FgeeeSR497/5ptv8sEHH/Doo4+yePFi3N3dufrqq6msbPlpZkVaS7XZwsNf7ADgkuEx9I/ys29BItJmdA7y5NPrR/KvM3piMhr4ens6k577hV/3Z9u7NBGRds2uIWncuHHceeednHHGGcfcZ7Vaef/997nxxhuZOHEivXr14qmnniIrK+uYEScRR7bgt0PsyywhwNOFuyfF2rscEWljnExGbj29B0tuHEXXYE8yiyqZvWAD/7dsByWVNfYuT0SkXWqz5ySlpKSQnZ3NqFGjapd5e3szYMAAtmzZYsfKRJpPYm4pz353ZLKGB6b0xq+dXChTRJrfgGg/vr51LJeP7ATAB+sSOXP+z/y0V6NKIiLNzcneBZxIdvaRD/3AwMB6ywMDA8nJyWn09sxmc7PUJS3raD91hP6yWq3cvySeyhoLo7oFMn1AWJt43iaTCavVgtVqadTjjk5TbLFYMRob+tgj69nSnu1au822355tfWd7e03T3tujtp3jfR64mOCRab2Z2DuEh5btICmvnGve/4OxMW78t2s5wT7urVKjNI+O9DevvVHfOa6G9lmbDUnNLT4+3t4lSCN0hP5afbic3w8W4mKES3oa2LZtm71Lwt3dnT59+pCbm0tGXolN28jKymzwumFuFiCSgoJCMrILbGqvsVq7TUdqrzF91xzt2aK9twdgqvICurB3717Ky48/9bcnMG+cN5/sNPD1vjJ+TargzGd/4cqBPoyNccNg0OQvjqQj/M1rr9R37VebDUnBwcEA5ObmEhISUrs8NzeXXr16NXp7cXFxmEymZqtPWobZbCY+Pr7d91duaRUffv0rALdP7MlZY7rauaL6AgMDMbt4NeoxFouVrKxMQkJCMTZwdj4/P+8///elyuTW6Dpt0dptOkJ7tvRdU9privbeHkCg95FrpMXGnvwcxVOGwuWJefxr0WaSCmt4fkMh2wpceOzcPkT4aVSpresof/PaI/Wd4zradyfTZkNSVFQUwcHBrF27lt69ewNQUlLCtm3buPjiixu9PZPJpDexA2nv/fXEij3kl1XTK8yb68Z1w2RqW6cHGgxGDIbG1XT0MC2j0dCIxxptbs92rd1m22/Ptr6zvb2mae/tUdtOQz8DB3cK4KmJgawv9OHlnw6yel82Zzz3Kzef1p1rT+2Km3P7/SxtL9r737z2TH3Xftl1z6y0tJTdu3eze/du4MhkDbt37yYtLQ2DwcDll1/Oq6++yg8//MDevXu55557CAkJYeLEifYsW6RJvt+VybKtaRgN8OT5/XFuYwFJRByPs9HALeO7seL2MQzvHEBFtYVnvtvHGc/+zLc7M3QRWhGRRrLrSNKOHTu4/PLLa2/PmzcPgPPOO48nn3ySa6+9lvLych5++GGKiooYMmQIb731Fq6urvYqWaRJCsqquH/pkSHea8d2ZWC0n30LEpF2pXuIN4uuP4Uvt6Uxb8UekvPKuf6DPxjbI4hHzu5D9xBve5coIuIQ7BqSRowYwd69e094v8Fg4Pbbb+f2229vxapEWs6c5bvILq6kW7And57R097liEg7ZDAYOHdgJBN7h/Lq6oO88UsCv+7PYfJzv/KPUZ25fWIPfNyc7V2miEibpuN8RFrJd7syWbolFaMBnp45QOcJiEiL8nR14q5JsXz3z1M5o08oNRYrC347xLinfuKNXw5SUa2pi0VETkQhSaQVFJRV8cDRw+xO7cqgGH87VyQiHUWnQE/evHwo7101nG7BnuSXVfPEij2M++9PfLQ+kWpza12jTETEcSgkibQwq9XKg0t3kF1cSfcQL+6cqMPsRKT1jesZzLd3nMpTF/Qn0s+dzKJKHly6g4nzf+aLram1FxUWERGFJJEWt2RzKl/Hp+NkNPCMDrMTETtyMhm5cGg0P941jkfO7kOQlwuJuWXc/slWprzwK9/uzFBYEhFBIUmkRSXnlfHIlzsBuGNiDwZoNjsRaQNcnUxcOboLP989nrvO7Im3mxN7Moq5/oM/mPTcL3z2RwpVNToMT0Q6LoUkkRZitli5c9FWSiprGNrJnxtP627vkkSknXJ3d7fpcZ6uTtwyoQe/3jOem07rhrerE/uzSrjr022M++9PvPVrAqWVNc1crYhI26eQJNJIlgZelPHV1QfYlJiPl6sTz84aiMloaNH2RKR98HAxNer33mQy0adPH0wm2w/l9XF35p7JvVhz/wTuO6sXwd6upBdW8PjXuxn15I88s2ovuSWVNm//r1r7c629tycizc+u10kScURGg4Fv4tPJK6064TqJuWW89VsCAJP7hvLLvmyb2uoc6MHoHsEnba+5HG1PROzH1cnUoM+Zo6xWC7m5uQQGBmIwNP67zwBPF86KCwfAx82ZG8Z144pRnVm6JZU3fkngUE4pL/54gNd/SWBa/3Bmn9KJgdF+GAy2ffEDDfscbS6t/Tla9/UUEcelkCRig7zSKrKKj/+takW1mYUbk7BYoWeoFxF+7idc92T8PVxO2l5zOtqeiNhfQ3/vrVYLGXklmF28bApJx+PmbOLi4TFcODSab3dm8PrPB9mWUsiSzaks2ZxKv0gfZp/SiXMGROLuYtsIVmt/rrVWeyLSPigkiTQjq9XKd7syKa6owdfdmQm9Qpr0bauIiD2ZjAamxIVzVr8wtiYX8MG6RL7ans6O1CLu/Tyef3+9mwuGRHPZKTF0Dfayd7kiIs1GIUmkGW1NLiAhpxSTwcCUfmG4Omm6bxFxfAaDgUEx/gyK8eehqX34dFMyH65PJDmvnLfXHOLtNYcY2smfmUOjmBIXjrebs71LFhFpEoUkkWaSWVTBbwdyABjbI4gQHzc7VyQi0vwCPF24flw3rh3blZ/3Z/Ph2kR+2pvFpsR8NiXm88iXOzmrXzgXDIliZNdAjDZOWiMiYk8KSSLNoLzKzNfx6Vis0C3Yk/5RvvYuSUSkRRmNBsbHhjA+NoTMogqWbknlsz9SOJBVwtItqSzdkkqknzszBkcyfVAk3XQ4nog4EIUkkSayWK18szO99jykM/qE6jwkEelQQn3cuGFcN64/tSvbUgr57I9kvtyaRmpBOS/+eIAXfzxAXKQv5w6M4JwBERppF5E2TyFJpInWJeSSnFeOk9HAtP7hOg9JRDosg8HAwGg/Bkb78dDUPny3K5OlW1L5ZV828amFxKcW8sSK3YzuHkSItyvB3q76zBSRNkkhSaQJDmaXsPFwPgATe4cS5OVq54pERNoGN2cTZw+I4OwBEeSVVvH19jSWbU3jj8R8ft1/5PxNk9FA1yBPeoV50ynQ0+aLbouINDeFJBEb5ZZUsmpnJgADo/2IDfO2c0UiIm1TgKcLs0d2ZvbIziTnlfHF1lTe+z2R7JJK9meVsD+rBDcnI91DvegV5kOEr5sOWxYRu1JIErFBWVUNy7enU2W2EOnnzpjuQfYuSUTEIUQHeHDLhB74uTuzM62IPZnF7MsoprTKzI7UInakFuHt5kRsqDe9wrwJ1Ai9iNiBQpJII1WbLSzckExheTU+bk5MjQvXISIiIo1kMBgI8XEjxMeNMd2DSMkvZ09GEQezSimuqKmdUjzIy4VeYT70DPXS9ZdEpNUoJIk00pzlO0nIKcXZZODsARG4u+ikYxGRpjAaDMQEeBAT4EFNrIVDOaXsySjmcG4pOSVV/HYgh98O5BDl705smDc9gr1wddZnr4i0HIUkkUZ47/fDfLguCQMwuW+YJmoQEWlmTiYjPUK96RHqTUW1mf1ZJezJKCKtoIKU/HJS8stZvTebzoEe9ArzoXOQB05Go73LFpF2RiFJpIG+25XJnOU7ATijTyhddWFEEZEW5eZsIi7Sl7hIX4rKq9mbWczejGJyS6s4mF3KwexSXJyM9Azxol+kL6G6/pKINBOFJJEG2JZcwK0LN2OxwkXDoukX4UN2SZW9yxIR6TB83J0Z1jmAYZ0DyC6urA1MJZU17EgrYkdaESHersRF+tIz1BsXJ40uiYjtFJJETiI5r4yr39tIRbWFU3sG89j0fizemGzvskREOqzgPy9EO7pbICn55exMK+JAVglZxZX8sCeLX/fnEBvmTVykL7GhujyDiDSeQpLI38gvreKKdzaQU1JF73AfXrl0MM4mfTspItIWGAwGogM8iA7woLzKzK70IuJTCyksryY+tZD41ELWJuRiBcwWq73LFREHopAkcgKllTVc8e5GDmaXEu7rxjtXDMPLVb8yIiJtkbuLiSGd/Bkc40dyfjk7Ugs5mF3CoZxSbv54M37uzsRF+dI3wgdXJ82MJyJ/T3t8IsdRVWPhhg//YFtyAX4ezrx/1XDCfHVCsIhIW2eoM514aWUNaQXlrDuUR15pFb/uz2F9Qh59I30YGOWHj7uuuyQix6fjhkT+wmKx8q9Pt/Hr/hw8XEy8c8UweuiYdhERh+Pp6sS0/hH8ft8Epg+MwN/DmSqzhS1JBby79jDfxKeTXVxp7zJFpA3SSJJIHVarlYe/3MHybWk4mwy8dtkQBsX427ssERFpAjdnE8M6BxAT4EFibhmbk/NJzitnX1YJ+7JK6BbsyfDOAYRoCnER+ZNCksifrFYr//5695GLxRpg/oUDObVnsL3LEhGRZmIwGOgc5EnnIE+yiyvZdDiPfVkltddc6hzowYgugTq8WkQUkkSOembVPt767RAA/5nRn7MHRNi5IhERaSnB3q6cFRfOiNIqNhzOY19GMYdzyzicW0ZMgAcjugQQ4edu7zIbzGK1YjQY2m17Iq1NIUkEeOnH/bz00wEA5p7blwuHRdu5IhERaQ0Bni5M7hvGiC4BbDycx56MYpLyykjKK6NzoAejugUR7O1q7zJPymgw8E18OnmlLX+h8wBPF86KC2/xdkTsSSFJOryXfzrA06v2AfDglN5cPrKzfQsSEZFW5+/hwpl9whjRJZCNh/PYlV7058hSEr3CvBnZNbDNz4aXV1pFliaiEGkWCknSob34w36e+e5IQLrrzJ5ce2pXO1ckIiL25OvuzMTeoQzp5M/ag7nszyphT0Yx+zNLiIvyZVhnfzxctPsk0t7pt1w6rOe/38+z3x8JSHdPiuXm8d3tXJGIiLQV/h4uTIkLJ7OogjUHckjOL2drcgG70ooYHOPH4E7+OJt0JRWR9kq/3dLhWK1W5q/aWxuQ7pmsgCQiIscX6uPGjMFRTB8YQYi3K1VmC+sO5fH+2kT2ZBRhtVrtXaKItACNJEmHYrFYmfvVLt79/TAA953VixvGdbNvUSIi0uZ1CvQkJsCD/VklrDmQQ1FFDd/uzGRbciHjegZr2nCRdkYhSTqMarOFez7bztItqQDMOacv/xjV2b5FiYiIwzAYDPQM9aZrkCebkwvYdDiPjKIKFm1KpleYN6O7BRHiADPhicjJKSRJh1BRbebmjzbzw54sTEYDz8wcwPRBkfYuS0REHJCTycjwzgH0Cffh94M57E4vZk9GMQeyShjXM5jzh0Th5myyd5ki0gQ6J0naveKKav7x9gZ+2JOFq5ORN2YPUUASEZEm83J14sw+YVw0LJpwXzdqLFZ+2JPFmc/+wk97suxdnog0gUKStGu5JZVc/OY61h/Kw9vVifevGs7pvUPtXZaIiLQjoT5uzBwSxeS+Yfi4OZGUV8aV727k+g82kVpQbu/yRMQGOtxO2q3UgnJmL1hPQnYpgZ4uvHfVcPpF+tq7LBERaYcMBgOxYd4M7+xPelEFb685zLc7M/llXw63T+zBVaO74OKk76ZFHIV+W8XhWY4z/equtCLOf+V3ErJLifB1Y/ENIxWQRESOw8PFdNzPUbGNq7OJB6f24evbxjCssz/l1Wae/GYPU1/4lXUJufYuT0QaSCNJ4vCMBgPfxKeTV1oFwN7MYj7ZmExVjYVgL1cuHRHDuoO5rDvY9D9OnQM9GN0juMnbERFpK1ydTMd8jrakjvI52ivMh8XXj+TzzanMW7Gb/VklXPTGOs4bFMn9U3oR4q0pw0XaMoUkaRfySqvIKq4kPqWQn/ZlYbVClL87U+PCqTJbySqubJZ2/D1cmmU7IiJtzdHP0ZbWkT5HDQYDFwyJ4ozeofx31R4+Wp/E0i2pfL87k7snxXLR0Ch7lygiJ6DD7aRdsFit/HYghx/3HglIvcO8mT4wUlOwioiI3fl6OPP49DiW3TSa/lG+FFfU8PAXOznv1bUcyKu2d3kichwKSeLwKqrNLNqYzB+J+QCc0iWAM/qEYjIa7FyZiIjI/wyI9mPpTaN5bHo/fNyc2JlWxH0/5PLo8l0UVSgsibQlCkni0HJLKrnkzXXsSCvCaIAz+4QyomsgBoMCkoiItD0mo4HZp3Tih3+dxrkDwrECH6xLYuIzP/P19nSsmkRDpE1QSBKHtSejiOmvrGFzUgFuzkbOGxRJ73Afe5clIiJyUsHersy/cAAPn+pP50APsoorufnjzVz57kaS88rsXZ5Ih6eQJA5p5Y50ZrzyO8l55cQEeHDDqd2I8vewd1kiIiKNMiDUlRW3jub203vgYjKyem82Zzz7M6+sPkBVjcXe5Yl0WG06JL344ovExsbW+zd58mR7lyV2ZLFYefa7fdzw4WbKqsyM7h7IFzePJtjb1d6liYiI2MTV2cSdZ/TkmzvGMrJrIBXVFp5auZdpL/7KxsN59i5PpENq81OA9+jRg3feeaf2tsmk2co6qpLKGv65aCurdmUCcNXoLjwwpRdOpjad9UVERBqkW7AXH187gqVbUvn317vZl1nCzNfWMmtoNPed1Qt/z44zfbqIvbX5kGQymQgObv8XnZO/l5hbyrXvb2JfZgkuJiP/Pq8fM4dG27ssERGRZmUwGJgxOIoJvUL4z8o9LNyQzKJNyXy3O5MHp/RmxuBITU4k0gra/FfwiYmJjBkzhtNPP51//etfpKWl2bskaWW/7c/hnJfWsC+zhBBvVz65/hQFJBERadf8PFyYN6M/n90wkthQb/JKq/jXp9u4+M11HMgqsXd5Iu1emx5J6t+/P/PmzaNLly5kZ2fz8ssvc+mll7J8+XK8vLwatS2z2dxCVUpzOtpPZrMZi8XK678mMP+7/VisMCDKl1cvHUSoj1u9/jSZTFitFqzW1jjB9Ugbau84j7RYa/83Ghv62NZ+fvZos+23Z1vf2d5e07T39hrfZtP6r/HtNV37bu9oGw3Z76j7N+9EBkX78sXNI3l7zWFe+PEA6xLymPL8L1x3alduGtcV1z8vmt6afwsb8xzbq4b0nbRNDe2zNh2Sxo0bV/tzr169GDBgAOPHj+ebb75h5syZjdpWfHx8c5cnLWjtH9t4YUMhf6RXAjC+szvXDXYjPWEP6XXWc3d3p0+fPuTm5pKR1/LfrIW5WYBICgoKycguUHvHkZWV2artNZYjvqat1V5j+q452rNFe2+vKW3a0n9Nac9W7b09U5UX0IW9e/dSXl7eoMc0ZB9lhA/MPyOAtzYXszmjkpd+OshnGw9z3WAfTuns16p/C215ju2V9i/brzYdkv7Kx8eHzp07k5SU1OjHxsXFadIHB2A2m/nil808/0cZKfmVuDgZeXRaby4cGvW3x2AHBgZidmnc6KIt/Py8//zflyqTm9qrw2KxkpWVSUhIKEZjw46Xb+3nZ482HaE9W/quKe01RXtvz5Y2m9J/trTXVO29vcA/Z1uNjY096bpms5n4+PhG7aOcOcrKyp2ZPPbVbjKKK5n7Sz5nF7jxf9EVrfa3sDHPsb2ype+kbTjadyfjUCGptLSU5ORkmyZyMJlMehO3cVarlUUbk3nkx1yqLRAd4M6rlw6hX6TvSR9rMBgxGFrjFDuj2jvRI/88zMdoNDTisa39/OzRZttvz7a+s729pmnv7TW+zab1X+Pba7r23d7RNhqzz9HYfZRpAyIZFxvCM6v28f7awyzfns7qfdmMjw2hc6BHi0/sYMtzbK+0f9l+temQ9J///Ifx48cTERFBVlYWL774IkajkWnTptm7NGlm5VVm/u+LHXz2RwoAp/cKZv6Fg/D1cLZzZSIiIm2Pt5szj57Tl/MHR/HA0njiUwv5clsaYT5uTOgVousHijRRmw5JGRkZ/POf/6SgoICAgACGDBnC4sWLCQgIsHdp0owOZpdwy8db2J1ehNEAF/f14tFZg3F2btNvTxEREbuLi/Jl2c2jeX/tYZ78Zg8ZRRUs3JjEoGg/RnQJxMWpzU9kLNImtem90GeffdbeJUgL++yPFB7+YgdlVWYCPV14btYAPIqTbTquXkREpCMyGQ1cOboL5VVmlmxJ5UBWCZuTCtiXWcJpscF0DfLUtZVEGqlNhyRpv0oqa/i/ZTtYuiUVgFHdAnl21kCCPJ3ZujXZztWJiIg4Hl93Z6bGhXMop5TVe7Moqqjhq+3pxAR4cGqPIAK9dAieSEMpJEmr25FayC0fb+ZwbhlGA/zzjJ7ceFp3TEaDrjcgIiLSRF2CPIny78TGw3lsTiwgKa+MjzYkMSDKj1O6BNReW0lETkwhSVqN1Wrl3d8PM2/FHqrMFiJ83Xj+4kEM66xzzERERJqTs8nIqG5B9An34df9OSTklLI1uYC9GcWM6hZInwgfjDoET+SEFJKkVeSWVHLv5/F8v/vIxQ7P7BPKUxf0x8/Dxc6ViYiItF9+Hi6cPSCCxNxSftmXQ15ZFT/sySI+tZBTewYT6edu7xJF2iSFJGlxP+3J4u7PtpNTUomLychD03oz+5ROOolURESklXQK9OSSER5sTylg3aE8soor+eyPFLoFezK6exD++tJSpB6FJGkx5VVmnlixmw/WJQLQM9SL52YNok+Ej50rExER6XhMRgODYvyJDfNm7cFcdqYVcTC7lEM5pcRF+jK8SwAeLto1FAGFJGkh21MKuGPRVhKySwG4anQX7pkci5tOFhUREbErDxcnTu8dysBoP347kMPh3DK2pRSyO72YoZ39GRTth5NJ11eSjk0hSZqV2WLl1dUHeO77/dRYrIT6uPLMzIGM6RFk79JERESkjkAvV84dGElyXhm/Hsghu7iS3w/msj2lkJHdAukV5q3JHaTDUkiSZnM4p5S7Pt3GpsR8AKbGhfPv8/ppcgYREZE2LDrAg4uHRbM3o5jfE3Iprqjhu12Z/HE4n1O6BtA9xEvnEUuHo5AkTWaxHJna+6lv91BRbcHL1Ym55/blvEGR+lAVERFxAAaDgV7hPnQP8WJrSgF/HM4nr6yKFTsyCPZy5ZRuAXQJ9NTfdekwFJKkSQ7nlHLPZ9vZcDgPgFHdAvnP+f2JDvCwc2UiIiLSWE4mI0M7BRAX6cuWpAK2JBWQXVLJ8m3phPm4MbJbIMFeOkJE2j+FJLGJxWLlvbWH+c/KI6NHni4m7p/Sm0tHxOhbJhEREQfn6mTilK6BDIj244/EfLYlF5BRVMHSLalsScqnU5AnY7oH6W++tFsKSdJoGj0SERHpGNydTYzpHsSgaD82Hc4nPrWQw7llzF6wgQFRvtw0vjtn9A7FaFRYkvZFIUkarMZs4e01h3j2u/2UV5vxcDHxgEaPRERE2j1PVyfGxQYzuJMfu9OL2ZKcz7aUQq7/4A96hnpx02ndmdY/XFOHS7uhd7I0yPaUAs59eQ1PrNhDebWZUd0C+faOU7nslE4KSCIiIh2Et5sz0/qH89u9E7jptG54uzqxL7OEOxZtZcIzP/PR+kQqqs32LlOkyTSSJH+rtLKG+d/t4501h7BYwdfdmQen9Gbm0CiFIxERkQ4qyMuVeyb34vpx3fhg7WEW/HaIpLwyHly6g6e/3culIzpx+chOhPi42btUEZsoJMkJ/bgnk/9btpPUgnIAzh0Ywf9N60OQl6udKxMREZG2wNfdmVsm9OCqMV1YuCGZt387RGpBOS/9dIDXfznItP4RXD2mC/0ife1dqkijKCTJMTKLKpj71S6+3p4OQJS/O49P78dpsSGt0r67u3urtCMiIiLNw8PFiavHdOEfIzvx3a5MFvx2iE2J+SzdksrSLakM7xLAVaM7M7F3qM5bEoegkNTOWaxWjA08LK6qxsI7aw7xwg/7Ka0yYzIauHpMF+6Y2AMPl4a9VRrT3vGYTCb69Olj8+NFRETEfpxMRs6KC+esuHC2JRfw9ppDfL09nQ2H8thwKI8wHzcuHBbNRcOiifBr+JeiTd2/aKzWbk/aHoWkds5oMPBNfDp5pVV/u97+rGK+2p5OTsmR9aL93TlnQAQRfu4s3ZzaoLY6B3owukdwg9o7EavVQm5uLoGBgRgMJ/+m6WibIiIi0rYMiPbj+YsGcd9ZvXh/bSKLNyaTUVTBCz/s56Uf9zM+NoRLRsRwWmwIppNMId7Q/ZnmEODpwllx4S3ejrRtCkkdQF5pFVnFlce9r6i8ml/2Z3MwuxT483oIPYLoHeaNwWA44eOOx9/D5aTtnYzVaiEjrwSzi1eDQtLRNkVERKRtCvd1597JvbhjYg++3ZnJx+sTWZeQxw97svhhTxYRvm7MGhbDjMGRf3vNxabsX4g0lkJSB1VjtvBHYj4bE/MxW6wYDDAgyo9Tugbg6mSyd3kiIiLSzrg6mThnQATnDIjgYHYJC9cn8dnmFNIKK3j2+308+/0+TukawIzBUUyJC8fLVbupYj9693UwVquV3RnFrD2YS0llDXBkYoZxPYM1a52IiIi0im7BXjw0rQ93TYpl5Y4MFm9KZm1CLusS8liXkMfDX+xgct8wZgyOYnT3oJMejifS3BSSOpCkvDJ+259DdsmRoWpvNyfGdA+iR4iXrnkkIiIirc7N2cT0QZFMHxRJakE5y7ak8vnmFBKyS1m2NY1lW9MI9XFlalwEziYDrk5G7bNIq1BI6gAyiyr4YlsaibllALiYjAzr4s/AKD9NwykiIiJtQqSfOzeP785Np3VjW0ohSzan8OW2NDKLKnl7zSHgyBe8PUK86BnqTYi3qwKTtBiFpHYso7CC53/YxycbkrECRgP0j/RjeJcA3F103pGIiIi0PQaDgYHRfgyM9uOhqX34ZV82X21PY8WODIoraticVMDmpAJ83Z3pEeJFt2AvQn0UmKR5KSS1Q1nFFby2OoEP1ydSVWMBoHuwF6O6B2o2OBEREXEYLk5GJvYJZWKfUAauOcTGw/nszywmIaeUwvJqNiXmsykxH08XE12CPOka7EW0v7uOlJEmU0hqR/JKq3j954O8t/YwFdVHwtGwzv4MivbXyJGIiIg4NGeTke4hXnQP8aLabOFwTin7s0pIzC2jtMrMjrQidqQV4Wwy0CnAk67BnnQJ8sTNWftA0ngKSe1AQVkVb/6awLtrDlNaZQZgYLQf/zqzJ2O6B/Hx+iRdV0BERETaDWeTkR6h3vQI9abGYiE1v5yD2aUcyimlpLKGA9klHMguwWCACF93ugZ70jXIEz8dUSMNpJDkwHJLKnn398O8u+YwxX9O590v0od/ntGT8bEhOjZXRERE2j0no5FOgZ50CvTEarWSVVxJQnYpB3NKyC2pIrWgnNSCcn7dn4OvuzOdAz3oFOhJlL87zk04LM/d3b0Zn4W0NQpJrcxitWJsYnhJzivjzV8TWLwpufawul5h3twxsSeT+oYqHImIiEiHZDAYCPVxI9THjZHdAiksryYhu4SEnFLSCsopLK9mW0oh21IKMRkMRPi70TnAk5hADwI9XTAYDHi4mE66v2YymejTp0+z1d0c+4fSvBSSWpnRYOCb+HTySqsa/diMwgp+2Z9NfGohFuuRZZF+7pzaI4g+ET7kllTy8fqk2vU7B3owukdwc5UuIiIi4lB83Z0ZFOPPoBh/KmvMpOSXk5hbxuHcUoorakjOKyc5rxwOgJerE50CPRjZNZAJvUL5/WDOCffXrFYLubm5BAYGYjA0bZKIAE8XzooLb9I2pPkpJNlBXmlVg88RslqtpOSXszkpn8N/XucIICbAg6Gd/Inyd8dgMJBTcuwvsWayExERETnC1clEt+AjU4ZbrVYKyqo5nFtKYl4ZKfnllFTWsDOtiJ1pRSxYc4hwXzfCfd2J9ncnwq/+oXlWq4WMvBLMLl5NDknSNikktVHVZgt70ovZllJA7p/fYhiA7iFeDO3kT4iPm30LFBEREXFQBoMBf08X/D1dGBTjT43ZQmpBOYdzy8gorCCjqIK0giP//kjMx2igNjBFBXgQ6q0vots7haQ25sixsgXsSiui8s9rHDmbDPQK82FwjJ9mZRERERFpZk6m/03+EBvqzZDO/jz97V52pBWSnHdklOnoBBAcysPZZCDQ3Uj3qgKi/D0I9nLFaNQ5Re2JQlIbYLFaScotY3tqIYdySmuX+7o7MyDKlz7hPrhqjn8RERGRVhHq48bAaD8i/NyxWq0UllcfOX8p/8iheeXVZjJKzGQcyAVycTEZCfdzI9LPnUg/d0J93DApNDk0hSQ7KiirYld6EbvTiyn5cwpvgE4BHgyI9qNzoIdmqhMRERGxI4PBgJ+HC34eLsRF+WK1WskurmBXUhaFNU6kFVZQVWMhMbeMxD/PH3cyGgjzPRKaovzdCfNxw6kJ041L61NIamXlVWa2JOWzNiHvyJDtn9ycjPQK96F/pC/+njqkTkRERKQtMhgMBHu7EhvoTFhYGFYMtddjSskvI62ggvLqIzPppeSXs/4QmAwGQnxcifB1J9zPjTAfNzxdtRvelql3WtF7vx/m6W/31l74FaBToAd9w33oEuyJk1HfMIiIiIg4EuOfoSnY25WB0X5YrVbySv93EdvU/HJKq8ykF1aQXlgBf16txdfdmXBfN3r+eQ5UjxBvHaLXhigktaIlW1IprqzB38OZXmE+9A73xtvN2d5liYiIiEgzMRgMBHq5EujlSv8ov9pzmtIKK0gvKCe9sILc0ioKy6spLK9mT0YxX25Lw9vViYExfgzp5M+AaD/6R/oS6OVq76fTYSkktaI3Zw8ho6iCbckFx72ukYiIiIi0L3XPaeoT7gNAZbX5yDTjhRXkllSSUVhBcWUNv+7P4df9ObWPjfRzZ0C0L/2jjoSmflG++OgL9lahkNSKQnzcCPFxIz6l0N6liIiIiIiduDqbaqccD/F25aLhMezNKOaPpHw2J+azLaWAhOzS2kP2VsRn1D62a7AnA6L8iIv0pX+UL73CffDS+U3NTq+oiIiIiJ24u7vbuwRpA0xGA30ifOgT4cPsUzoBUFRRzY7UQranFLI9pYBtyYWkFpSTkF1KQnYpS7ek1j4+JsCDXmHe9A73+fOfN9H+Hrp2UxMoJImIiIg0Ew8XExarFWMDLuFhMpno06dPK1TVvBrzHMV2Pm7OjOoWxKhuQbXLcksq2Z5ayPbkI8FpZ1oRGUUVJOWVkZRXxqpdmbXrerqYiK0TnHqGetMt2JMATxes0Or952jvGYUkERERkWbi6mTCaDDwTXw6eaV/f/6x1WohNzeXwMBADAbbZ7jtHOjB6B7BNj++sRrzHJtDaz+/tizQy5XxsSGMjw2pXZZXWsWe9CJ2ZxSzO72I3elF7M8sobTKzOakAjYnFdTbhp+HM92CvXB1MuLj5kywtwvBXq74ebi02Ox6AZ4unBUX3iLbbikKSSIiIiLNLK+0iqziyr9dx2q1kJFXgtnFq0khyd/DPtdXbMhzbA72en6OIsDThVHdgxjV/X8jTtVmC4dySv8MTcXsySjiQFYJKfnlFJRV80di/jHbMRkM+Hk4//nPBV83Z3zcnfB1d8bbzbnDTU+ukCQiIiIi0o44m4z0DPWmZ6g35w783/LyKjOHcko5kF3Css0ppOSXk1dWRX5ZNWaLldzSKnJLq4DSetszAN5uTvi4O+Nb55+PmzNebk54upgwONChdA2hkCQiIiIi0gG4u5hqJ4goLq+uHQm0Wq0UV9QcCUylVRSV11BYUV17LSezxUpRRQ1FFTWk5Jcfs12jATxdnfB2dcLLzQlvN+f//ex6JEQ5GoUkEREREZEOzGAw4OPujI+7M50DPevdZ7VaKasy1wamwvJqisqrKSivpriihtLKGixWKK6oobiiBk50pRsDXHdqt5Z/Ms1EIUlERERERI7LYDDg6eqEp6sTEX7HTllvsVgprToSkEoq//y/oobiyura25XVFjtU3jQOEZI++ugjFixYQHZ2Nr169eL//u//6N+/v73LEhERERHp0IxGw5HD69ycT7hOsJcLl43s3HpFNQPbp1JpJStWrGDevHncfPPNLF26lF69enH11VeTm5tr79JEREREROQkHHFShzYfkt555x0uvPBCzj//fLp3786cOXNwc3Pj888/t3dpIiIiIiLSDrXpkFRVVcXOnTsZNWpU7TKj0cioUaPYsmWLHSsTEREREZH2qk2fk5Sfn4/ZbCYwMLDe8sDAQBISEhq0DavVChwJXCaT/acfNJlMBLibMFhb/qX3cTNiNpsdqj2LFVwCvfDzcqEh1yxzxOfYXttrbN81tT1bOdJr2lrt2dJ3TWmvKdp7e7a02ZT+s6W9plJ7/9PUvrOlzeag9pqv7wD83U2YzWbMZnPTNtQIrbk/CvZ5jidytIajGeFEDNaTrWFHmZmZnHrqqXzyyScMGjSodvlTTz3Fxo0b+fTTT0+6jaqqKuLj41uyTBERERERcSBxcXG4uLic8P42PZLk7++PyWQ6ZpKG3NxcgoKCGrQNJycn4uLiMBqNDnnSmIiIiIiINA+r1YrFYsHJ6e9jUJsOSS4uLvTt25e1a9cyceJEACwWC2vXruWyyy5r0DaMRuPfpkQREREREZG62nRIArjyyiu599576devH/379+e9996jvLycGTNm2Ls0ERERERFph9p8SJoyZQp5eXm88MILZGdn07t3b956660GH24nIiIiIiLSGG164gYREREREZHW1qavkyQiIiIiItLaFJJERERERETqUEgSERERERGpQyFJRERERESkDoUkERERERGROhSSpNV99NFHTJgwgbi4OGbOnMn27dtPuO7ixYu55JJLGDZsGMOGDeOKK6742/WlZTWm7+r6+uuviY2N5aabbmrhCuVEGtt3RUVFzJkzhzFjxtCvXz8mTZrEzz//3ErVSl2N7bt3332XSZMm0b9/f8aNG8cTTzxBZWVlK1UrR23cuJEbbriBMWPGEBsby/fff3/Sx6xfv57zzjuPfv36ccYZZ7BkyZJWqFSOp7H9t2rVKq688kpOOeUUBg8ezKxZs/j1119bqVppCQpJ0qpWrFjBvHnzuPnmm1m6dCm9evXi6quvJjc397jrr1+/nqlTp/L+++/zySefEB4ezlVXXUVmZmYrVy6N7bujUlJS+M9//sPQoUNbqVL5q8b2XVVVFVdeeSWpqak8//zzrFy5kscee4zQ0NBWrlwa23fLly/nmWee4ZZbbmHFihX8+9//ZsWKFcyfP7+VK5eysjJiY2N55JFHGrR+cnIy119/PSNGjOCLL77gH//4Bw899JB2tO2ksf23ceNGRo0axRtvvMGSJUsYMWIEN954I7t27WrhSqXFWEVa0QUXXGCdM2dO7W2z2WwdM2aM9fXXX2/Q42tqaqyDBg2yLl26tIUqlBOxpe9qamqss2bNsi5evNh67733Wm+88cbWKFX+orF99/HHH1tPP/10a1VVVWuVKCfQ2L6bM2eO9fLLL6+3bN68edaLLrqoReuUv9ezZ0/rd99997frPPXUU9apU6fWW3bHHXdYr7rqqpYsTRqgIf13PFOmTLG++OKLLVCRtAaNJEmrqaqqYufOnYwaNap2mdFoZNSoUWzZsqVB2ygvL6empgZfX9+WKlOOw9a+e/nllwkMDGTmzJmtUaYchy199+OPPzJw4EDmzp3LqFGjmDZtGq+99hpms7m1yhZs67tBgwaxc+fO2kPykpOT+fnnnxk3blyr1Cy227p1KyNHjqy3bMyYMWzdutU+BUmTWCwWSktL8fPzs3cpYiMnexcgHUd+fj5ms5nAwMB6ywMDA0lISGjQNp5++mlCQkLq7TRIy7Ol7zZt2sRnn33GsmXLWqFCORFb+i45OZl169Zx9tln88Ybb5CUlMScOXOoqanhlltuaY2yBdv67uyzzyY/P59LLrkEq9VKTU0NF110ETfccENrlCxNkJOTQ1BQUL1lQUFBlJSUUFFRgZubm50qE1ssWLCAsrIyzjrrLHuXIjbSSJI4jDfeeIMVK1bw0ksv4erqau9y5G+UlJRwzz338NhjjxEQEGDvcqSRrFYrgYGBPPbYY/Tr148pU6Zwww038Mknn9i7NDmJ9evX8/rrr/PII4+wZMkSXnrpJX7++Wdefvlle5cm0mEsX76cl19+meeee+6YLznEcWgkSVqNv78/JpPpmBOOc3Nzj/n27K8WLFjAG2+8wTvvvEOvXr1askw5jsb2XXJyMqmpqdx44421yywWCwB9+vRh5cqVxMTEtGzRAtj2exccHIyTkxMmk6l2WdeuXcnOzqaqqgoXF5cWrVmOsKXvnn/+ec4555zaQ1xjY2MpKyvj4Ycf5sYbb8Ro1HejbVVQUBA5OTn1luXk5ODl5aVRJAfy9ddf89BDD/H888/rqBcHp09LaTUuLi707duXtWvX1i6zWCysXbuWQYMGnfBxb775Jq+88gpvvfUWcXFxrVGq/EVj+65r164sX76cZcuW1f6bMGECI0aMYNmyZYSFhbVm+R2aLb93gwcPJikpqTbYAhw+fJjg4GAFpFZkS99VVFQcE4SOhl2r1dpyxUqTDRw4kHXr1tVb9vvvvzNw4ED7FCSN9tVXX3H//ffzzDPPcNppp9m7HGkijSRJq7ryyiu599576devH/379+e9996jvLycGTNmAHDPPfcQGhrKv/71L+DIIXYvvPACzzzzDJGRkWRnZwPg4eGBp6en3Z5HR9SYvnN1daVnz571Hu/j4wNwzHJpeY39vbv44ov58MMP+fe//81ll11GYmIir7/+OrNnz7bn0+iQGtt348eP55133qFPnz7079+fpKQknn/+ecaPH19vZFBaXmlpKUlJSbW3U1JS2L17N76+vkRERPDMM8+QmZnJU089BcBFF13ERx99xFNPPcX555/PunXr+Oabb3j99dft9RQ6tMb23/Lly7nvvvt44IEHGDBgQO3+ipubG97e3nZ5DtI0CknSqqZMmUJeXh4vvPAC2dnZ9O7dm7feeqv20JH09PR634J+8sknVFdXc9ttt9Xbzi233MKtt97aqrV3dI3tO2k7Gtt34eHhLFiwgHnz5nHOOecQGhrK5ZdfzrXXXmuvp9BhNbbvbrzxRgwGA8899xyZmZkEBAQwfvx47rzzTns9hQ5rx44dXH755bW3582bB8B5553Hk08+SXZ2Nunp6bX3R0dH8/rrrzNv3jzef/99wsLCePzxxxk7dmyr1y6N77/FixdTU1PD3LlzmTt3bu3yo+uL4zFYNf4uIiIiIiJSS1/7ioiIiIiI1KGQJCIiIiIiUodCkoiIiIiISB0KSSIiIiIiInUoJImIiIiIiNShkCQiIiIiIlKHQpKIiIiIiEgdCkkiItIqZs+ezb///e/a2xMmTODdd99t1RpiY2P5/vvvW7VNERFpuI0bN3LDDTcwZswYmz+zrVYrCxYsYNKkSfTr14+xY8fy6quvNmobCkkiImKT++67j9jYWB5++OFj7pszZw6xsbHcd999tctefPFFbr/99tYssdmtX7+e2NhYioqKjrnvr6Fvw4YNXH755QwfPpwBAwZw5plncu+991JVVVVvW7GxsfTq1YshQ4Ywffp0nnrqKbKyslrrKYmItCllZWXExsbyyCOP2LyNf//733z66afcc889fPPNN7z66qv079+/Udtwsrl1ERHp8MLDw1mxYgUPPPAAbm5uAFRWVvLVV18RERFRb10/Pz87VGgfBw4c4JprruGyyy7joYcews3NjcOHD7Nq1SosFku9dVeuXImXlxclJSXs2rWLt956i88//5z333+f2NhYOz0DERH7GDduHOPGjTvh/VVVVTz77LN89dVXFBcX06NHD+666y5GjBgBwMGDB1m4cCHLly+na9euAERHRze6Do0kiYiIzfr06UN4eDirVq2qXbZq1SrCw8Pp3bt3vXX/erjdXxUVFfHggw9yyimnMHjwYC6//HL27NlTe/+ePXuYPXs2gwYNYvDgwcyYMYP4+PgTbu/w4cNceumlxMXFMWXKFNasWXPMOunp6dx+++0MHTqU4cOHc+ONN5KSktKYl+C4fvvtN4KCgrjnnnvo2bMnMTExnHrqqTz++OO1YfKowMBAgoOD6dKlC1OnTmXhwoX4+/vz6KOPNrkOEZH2Zu7cuWzZsoVnn32WL7/8ksmTJ3PNNddw+PBhAH788UeioqJYvXo1EyZMYMKECTz44IMUFBQ0qh2FJBERaZLzzz+fJUuW1N7+/PPPmTFjRqO3c/vtt5Obm8ubb77JkiVL6Nu3L//4xz9q/7DdddddhIWF8dlnn7FkyRKuvfZanJ2dj7sti8XCrbfeirOzM59++ilz5szh6aefrrdOdXU1V199NZ6ennz00UcsXLgQDw8PrrnmmtpD4mwVHBxMdnY2GzdubPRj3dzcuOiii9i8eTO5ublNqkNEpD1JS0tjyZIlPP/88wwdOpSYmBiuvvpqhgwZUvt3KDk5mbS0NFauXMlTTz3FvHnz2LlzJ7fddluj2tLhdiIi0iTnnHMOzzzzDKmpqQBs3ryZ+fPns2HDhgZvY9OmTWzfvp21a9fi4uICwL333sv333/Pt99+y6xZs0hLS+Pqq6+mW7duAHTu3PmE2/v9999JSEjgrbfeIjQ0FIA777yTa6+9tnadFStWYLFY+Pe//43BYABg3rx5DBs2jA0bNjBmzJhGvQ51TZ48md9++43LLruM4OBgBgwYwMiRI5k+fTpeXl4nffzRQ0RSU1MJDAy0uQ4RkfZk3759mM1mJk+eXG95VVVV7SHdVquVqqoq/vOf/9ClSxfgyDlKM2bMICEhofbz9WQUkkREpEkCAgI47bTTWLp0KVarldNOO42AgIBGbWPv3r2UlZXVHlN+VEVFBUlJSQBceeWVPPTQQ3zxxReMGjWKyZMnExMTc9ztHTx4kLCwsNqABDBo0KB66+zZs4ekpCQGDx5cb3llZWVtm7YymUzMmzePO+64g7Vr17J9+3Zee+013nzzTT799FNCQkL+9vFWq7VJ7YuItEdlZWWYTCY+//xzTCZTvfs8PDyAIyP5Tk5OtQEJqP1yLT09XSFJRERaz/nnn8/cuXMBbJqRqLS0lODgYD744INj7vP29gbg1ltvZdq0afz888/88ssvvPDCCzz77LOcccYZNtVcVlZG3759jzkMDzhhyDs6ClRcXIyPj0+9+4qKimprPSo0NJTp06czffp0br/9diZNmsQnn3xy0sM+EhISAIiKimrw8xERae969+6N2WwmLy+PoUOHHnedwYMHU1NTQ1JSUu0XaUfPV/rrhEJ/RyFJRESabOzYsVRXV2MwGGw6TK1v377k5ORgMpn+Nhh06dKFLl26cMUVV/DPf/6Tzz///LghqVu3bmRkZJCVlVU7arN169Zj2vzmm28IDAxs0CFwAJ06dcJoNLJz504iIyNrlycnJ1NcXPy3hwD6+voSHBxMeXn537ZRUVHBokWLGDZsWKNH5EREHF1paWm90fyUlBR2796Nr68vXbp04eyzz+aee+7hvvvuo3fv3uTn57N27VpiY2M57bTTGDVqFH379uWBBx7ggQcewGKxMHfuXEaPHl1vdOlkFJJERKTJTCYT33zzTe3PjTVq1CgGDhzIzTffzN13303nzp3Jysri559/ZuLEifTo0YOnnnqKSZMmERUVRUZGBvHx8Zx55pkn3F7nzp257777uOeeeygpKeHZZ5+tt87ZZ5/NggULuPHGG7n99tsJDQ0lLS2N7777jmuuuYawsLBjtuvl5cXMmTN58sknMZlM9OzZk4yMDJ7+//bu2DVxKIDj+C8BBzNViDiI3bqWDEUpAelScS10EwpCx1LcQoniUkiGDEIVQRwdHP1H3FqK4OwgFl0cMvU2eYVrud7dUvh+tpDweHnbl7wkSSLP8w5b96bTqV5fX3V5eanj42OlaarZbKblcqlOp/NhzLe3N6Vpqv1+r5eXF43HY223W/X7/W+vIwD8dM/Pz7q5uTkcR1EkSbq6ulIcx4qiSMPhUHEca71e6+joSJ7n6eLiQpJk27aGw6EeHx/VaDTkOI6q1aqCIPjWPIgkAMB/8adPY37HsiyNRiP1ej09PDxou93KdV2dnZ3JdV3Ztq3dbqcgCLTZbJTL5VSr1T7dtmbbtvr9vsIw1PX1tYrFotrttm5vbw/XZLNZTSYTJUmiu7s77fd7FQoFnZ+ff3kvYRhqNBopSRKtViu5rivf99VqtQ4fgDg9PdV8Ple329V6vZbjODo5OdFgMFC5XP4wXr1el2VZchxHpVJJvu+r2Wwqn8//9XoCwE9VqVS0WCw+PZ/JZHR/f//ltuVCoaCnp6d/mof1ztuhAAAAAHDAf5IAAAAAwEAkAQAAAICBSAIAAAAAA5EEAAAAAAYiCQAAAAAMRBIAAAAAGIgkAAAAADAQSQAAAABgIJIAAAAAwEAkAQAAAICBSAIAAAAAA5EEAAAAAIZfz97JXYJlgiIAAAAASUVORK5CYII=\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "La distribución de los ingresos presenta una ligera asimetría positiva, concentrando la mayor parte de las observaciones en niveles intermedios y mostrando una cola hacia valores elevados. Esto indica que existen períodos con ingresos excepcionalmente altos, por lo que la serie no sigue una distribución perfectamente simétrica."
      ],
      "metadata": {
        "id": "yHrSazRR05c3"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 8.3 BOXPLOT\n",
        "\n",
        "\n",
        "# Crea una figura\n",
        "plt.figure(figsize=(10,2))\n",
        "\n",
        "# Dibuja el boxplot\n",
        "sns.boxplot(\n",
        "    x=df[\"Ingreso_Publicas\"]\n",
        ")\n",
        "\n",
        "# Agrega el título\n",
        "plt.title(\"Valores Atípicos de los Ingresos\")\n",
        "\n",
        "# Muestra la gráfica\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 248
        },
        "id": "yax3vTx307Up",
        "outputId": "db9e72d3-9690-40ae-9cb5-883ebf9d6ec5"
      },
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x200 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "El diagrama de caja evidencia la existencia de algunos valores atípicos ubicados por encima del límite superior, correspondientes a períodos de ingresos extraordinariamente altos. Sin embargo, la mayor parte de las observaciones se concentra dentro del rango intercuartílico, lo que indica que estos valores extremos representan eventos específicos y no el comportamiento habitual de la serie."
      ],
      "metadata": {
        "id": "cZrA-jjn1s9P"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 8.4 ESTADÍSTICAS DESCRIPTIVAS\n",
        "\n",
        "\n",
        "# Calcula las estadísticas descriptivas\n",
        "estadisticas = df[\"Ingreso_Publicas\"].describe()\n",
        "\n",
        "# Muestra las estadísticas\n",
        "print(estadisticas)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "K2SMXFau1ENK",
        "outputId": "1fb0b9a6-9e57-47ef-a58e-21609c1b2407"
      },
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "count    2.330000e+02\n",
            "mean     5.947842e+05\n",
            "std      2.340067e+05\n",
            "min      6.879894e+04\n",
            "25%      4.372210e+05\n",
            "50%      5.489060e+05\n",
            "75%      7.367062e+05\n",
            "max      1.336205e+06\n",
            "Name: Ingreso_Publicas, dtype: float64\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 8.5 COEFICIENTE DE VARIACIÓN\n",
        "\n",
        "\n",
        "# Calcula la media\n",
        "media = df[\"Ingreso_Publicas\"].mean()\n",
        "\n",
        "# Calcula la desviación estándar\n",
        "desviacion = df[\"Ingreso_Publicas\"].std()\n",
        "\n",
        "# Calcula el coeficiente de variación\n",
        "cv = (desviacion / media) * 100\n",
        "\n",
        "# Muestra el resultado\n",
        "print(f\"Coeficiente de variación: {cv:.2f}%\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Z-FqUkgC1KS8",
        "outputId": "4ccb54d4-ee8a-4a89-93ee-53b00f642aa2"
      },
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Coeficiente de variación: 39.34%\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 8.6 PROMEDIO MÓVIL\n",
        "\n",
        "\n",
        "# Calcula el promedio móvil de 12 meses\n",
        "media_movil = df[\"Ingreso_Publicas\"].rolling(window=12).mean()\n",
        "\n",
        "# Crea una figura\n",
        "plt.figure(figsize=(15,6))\n",
        "\n",
        "# Grafica la serie original\n",
        "plt.plot(\n",
        "    df.index,\n",
        "    df[\"Ingreso_Publicas\"],\n",
        "    label=\"Serie Original\",\n",
        "    alpha=0.6\n",
        ")\n",
        "\n",
        "# Grafica el promedio móvil\n",
        "plt.plot(\n",
        "    df.index,\n",
        "    media_movil,\n",
        "    linewidth=3,\n",
        "    label=\"Promedio móvil (12 meses)\"\n",
        ")\n",
        "\n",
        "# Agrega el título\n",
        "plt.title(\"Serie Original y Promedio Móvil\")\n",
        "\n",
        "# Muestra la leyenda\n",
        "plt.legend()\n",
        "\n",
        "# Activa la cuadrícula\n",
        "plt.grid(alpha=0.3)\n",
        "\n",
        "# Muestra la gráfica\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 349
        },
        "id": "DZAYOz_i1OBX",
        "outputId": "fa73b2f8-b51c-4570-e34b-d901790a325a"
      },
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1500x600 with 1 Axes>"
            ],
            "image/png": 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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "El promedio móvil de 12 meses permite identificar la tendencia general de los ingresos, suavizando las fluctuaciones de corto plazo presentes en la serie original. Se aprecia un crecimiento sostenido hasta aproximadamente 2014, seguido de una disminución significativa y una recuperación gradual en los años posteriores, lo que evidencia cambios estructurales en el comportamiento de los ingresos petroleros a lo largo del tiempo."
      ],
      "metadata": {
        "id": "G5R4Nl6D10xl"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 8.7 EVENTOS ECONOMICOS IMPORTANTES"
      ],
      "metadata": {
        "id": "36yuyE-e29Ky"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 8.7 EVENTOS ECONÓMICOS RELEVANTES\n",
        "\n",
        "\n",
        "# Crea una figura\n",
        "plt.figure(figsize=(16,7))\n",
        "\n",
        "# Grafica la serie de ingresos\n",
        "plt.plot(\n",
        "    df.index,\n",
        "    df[\"Ingreso_Publicas\"],\n",
        "    color=\"navy\",\n",
        "    linewidth=2.5,\n",
        "    label=\"Ingresos por exportaciones\"\n",
        ")\n",
        "\n",
        "\n",
        "# ZONAS SOMBREADAS\n",
        "\n",
        "\n",
        "# Crisis financiera mundial\n",
        "plt.axvspan(\n",
        "    pd.Timestamp(\"2008-09-01\"),\n",
        "    pd.Timestamp(\"2009-06-01\"),\n",
        "    alpha=0.20,\n",
        "    color=\"red\",\n",
        "    label=\"Crisis financiera\"\n",
        ")\n",
        "\n",
        "# Caída del precio del petróleo\n",
        "plt.axvspan(\n",
        "    pd.Timestamp(\"2014-06-01\"),\n",
        "    pd.Timestamp(\"2016-02-01\"),\n",
        "    alpha=0.20,\n",
        "    color=\"orange\",\n",
        "    label=\"Caída del precio del petróleo\"\n",
        ")\n",
        "\n",
        "# Pandemia COVID-19\n",
        "plt.axvspan(\n",
        "    pd.Timestamp(\"2020-03-01\"),\n",
        "    pd.Timestamp(\"2021-06-01\"),\n",
        "    alpha=0.20,\n",
        "    color=\"green\",\n",
        "    label=\"Pandemia COVID-19\"\n",
        ")\n",
        "\n",
        "\n",
        "# ANOTACIONES\n",
        "\n",
        "\n",
        "# Anota la crisis financiera\n",
        "plt.annotate(\n",
        "    \"Crisis\\nFinanciera\",\n",
        "    xy=(pd.Timestamp(\"2009-01-01\"),420000),\n",
        "    xytext=(pd.Timestamp(\"2007-09-01\"),900000),\n",
        "    arrowprops=dict(arrowstyle=\"->\"),\n",
        "    fontsize=10\n",
        ")\n",
        "\n",
        "# Anota la caída del petróleo\n",
        "plt.annotate(\n",
        "    \"Caída del\\nPetróleo\",\n",
        "    xy=(pd.Timestamp(\"2015-02-01\"),500000),\n",
        "    xytext=(pd.Timestamp(\"2012-08-01\"),1150000),\n",
        "    arrowprops=dict(arrowstyle=\"->\"),\n",
        "    fontsize=10\n",
        ")\n",
        "\n",
        "# Anota el COVID\n",
        "plt.annotate(\n",
        "    \"COVID-19\",\n",
        "    xy=(pd.Timestamp(\"2020-04-01\"),100000),\n",
        "    xytext=(pd.Timestamp(\"2018-06-01\"),900000),\n",
        "    arrowprops=dict(arrowstyle=\"->\"),\n",
        "    fontsize=10\n",
        ")\n",
        "\n",
        "# Agrega el título\n",
        "plt.title(\n",
        "    \"Ingresos por Exportaciones Petroleras y Principales Eventos Económicos\",\n",
        "    fontsize=15,\n",
        "    fontweight=\"bold\"\n",
        ")\n",
        "\n",
        "# Nombre del eje X\n",
        "plt.xlabel(\"Periodo\", fontsize=12)\n",
        "\n",
        "# Nombre del eje Y\n",
        "plt.ylabel(\"Miles de USD\", fontsize=12)\n",
        "\n",
        "# Activa la cuadrícula\n",
        "plt.grid(alpha=0.3)\n",
        "\n",
        "# Muestra la leyenda\n",
        "plt.legend(loc=\"upper left\")\n",
        "\n",
        "# Ajusta el diseño\n",
        "plt.tight_layout()\n",
        "\n",
        "# Muestra la gráfica\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 348
        },
        "id": "v9sF4W012vFb",
        "outputId": "6088e07a-0c23-414f-cf0c-8eeb908403db"
      },
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1600x700 with 1 Axes>"
            ],
            "image/png": 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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "La evolución de los ingresos por exportaciones petroleras evidencia una estrecha relación con los principales acontecimientos económicos internacionales. Las zonas sombreadas muestran que durante la crisis financiera mundial (2008–2009), la caída del precio internacional del petróleo (2014–2016) y la pandemia de COVID-19 (2020–2021) se registraron reducciones importantes en los ingresos y episodios de mayor variabilidad. Estos períodos reflejan la sensibilidad del sector petrolero ecuatoriano frente a choques externos y constituyen una motivación para emplear el modelo GJR-GARCH, el cual permite analizar si las noticias negativas generan un mayor impacto sobre la volatilidad de la serie."
      ],
      "metadata": {
        "id": "AJ9IaG_K3He7"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 8.8 CRONOLOGÍA DE EVENTOS ECONÓMICOS\n",
        "\n",
        "\n",
        "# Crea un diccionario con los eventos más relevantes\n",
        "cronologia = {\n",
        "    \"Periodo\": [\n",
        "        \"2008-2009\",\n",
        "        \"2014-2016\",\n",
        "        \"2020-2021\",\n",
        "        \"2022-2024\"\n",
        "    ],\n",
        "    \"Evento\": [\n",
        "        \"Crisis Financiera Mundial\",\n",
        "        \"Caída del Precio del Petróleo\",\n",
        "        \"Pandemia COVID-19\",\n",
        "        \"Recuperación del Mercado Petrolero\"\n",
        "    ],\n",
        "    \"Impacto esperado\": [\n",
        "        \"Mayor incertidumbre y volatilidad\",\n",
        "        \"Reducción de ingresos y aumento del riesgo\",\n",
        "        \"Caída de la demanda mundial de petróleo\",\n",
        "        \"Recuperación gradual de los ingresos y estabilización\"\n",
        "    ]\n",
        "}\n",
        "\n",
        "# Convierte el diccionario en un DataFrame\n",
        "cronologia = pd.DataFrame(cronologia)\n",
        "\n",
        "# Muestra la tabla\n",
        "cronologia"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        },
        "id": "8Nxc9MKa3hY3",
        "outputId": "8ee75822-513b-48ba-f1e9-9767e557e650"
      },
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     Periodo                              Evento  \\\n",
              "0  2008-2009           Crisis Financiera Mundial   \n",
              "1  2014-2016       Caída del Precio del Petróleo   \n",
              "2  2020-2021                   Pandemia COVID-19   \n",
              "3  2022-2024  Recuperación del Mercado Petrolero   \n",
              "\n",
              "                                    Impacto esperado  \n",
              "0                  Mayor incertidumbre y volatilidad  \n",
              "1         Reducción de ingresos y aumento del riesgo  \n",
              "2            Caída de la demanda mundial de petróleo  \n",
              "3  Recuperación gradual de los ingresos y estabil...  "
            ],
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              "      <th>Periodo</th>\n",
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              "      <th>0</th>\n",
              "      <td>2008-2009</td>\n",
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              "      <td>Reducción de ingresos y aumento del riesgo</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2020-2021</td>\n",
              "      <td>Pandemia COVID-19</td>\n",
              "      <td>Caída de la demanda mundial de petróleo</td>\n",
              "    </tr>\n",
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              "      <th>3</th>\n",
              "      <td>2022-2024</td>\n",
              "      <td>Recuperación del Mercado Petrolero</td>\n",
              "      <td>Recuperación gradual de los ingresos y estabil...</td>\n",
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              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
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              "type": "dataframe",
              "variable_name": "cronologia",
              "summary": "{\n  \"name\": \"cronologia\",\n  \"rows\": 4,\n  \"fields\": [\n    {\n      \"column\": \"Periodo\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"2014-2016\",\n          \"2022-2024\",\n          \"2008-2009\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Evento\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"Ca\\u00edda del Precio del Petr\\u00f3leo\",\n          \"Recuperaci\\u00f3n del Mercado Petrolero\",\n          \"Crisis Financiera Mundial\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Impacto esperado\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"Reducci\\u00f3n de ingresos y aumento del riesgo\",\n          \"Recuperaci\\u00f3n gradual de los ingresos y estabilizaci\\u00f3n\",\n          \"Mayor incertidumbre y volatilidad\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "La cronología resume los principales acontecimientos económicos internacionales que afectaron al mercado petrolero durante el período analizado. Estos eventos provocaron cambios importantes en los ingresos por exportaciones de las empresas públicas del Ecuador y constituyen posibles fuentes de incrementos en la volatilidad de la serie. En las siguientes etapas del estudio se verificará, mediante el modelo GJR-GARCH, si estos choques negativos produjeron un efecto asimétrico sobre la volatilidad condicional."
      ],
      "metadata": {
        "id": "23agA2Dc3ww-"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **9 APLICACIOAN DEL MODELO GJR-GARCH**"
      ],
      "metadata": {
        "id": "pmu1AVSO4dj1"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 9. Cálculo de los Retornos Logarítmicos"
      ],
      "metadata": {
        "id": "7S6qB80430PN"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 9. CÁLCULO DE LOS RETORNOS LOGARÍTMICOS\n",
        "\n",
        "\n",
        "# Calcula los retornos logarítmicos de los ingresos\n",
        "df[\"Retorno\"] = np.log(\n",
        "    df[\"Ingreso_Publicas\"] /\n",
        "    df[\"Ingreso_Publicas\"].shift(1)\n",
        ")\n",
        "\n",
        "# Elimina el primer registro generado por el rezago\n",
        "df = df.dropna()\n",
        "\n",
        "# Muestra las primeras observaciones\n",
        "df.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 344
        },
        "id": "r8j7Dqzp36VB",
        "outputId": "acd49247-aa9e-4f20-aa94-b97fb77850f2"
      },
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            Export_Publicas  Precio_Publicas  Ingreso_Publicas  \\\n",
              "Periodo                                                          \n",
              "2007-02-01         5656.911        46.630391      263783.97315   \n",
              "2007-03-01         5137.830        48.669201      250054.07994   \n",
              "2007-04-01         5169.221        53.308112      275561.41457   \n",
              "2007-05-01         4509.777        54.572039      246107.72458   \n",
              "2007-06-01         5632.829        57.037135      321280.43047   \n",
              "\n",
              "            Export_Privadas  Precio_Privadas  Ingreso_Privadas  Ingreso_Total  \\\n",
              "Periodo                                                                         \n",
              "2007-02-01       3553.46539        45.754273      162586.22547   426370.19862   \n",
              "2007-03-01       5167.00802        48.073291      248395.08028   498449.16022   \n",
              "2007-04-01       4145.32441        51.279615      212570.64012   488132.05469   \n",
              "2007-05-01       4714.12562        53.028000      249980.65544   496088.38002   \n",
              "2007-06-01       6208.96510        56.847540      352964.38917   674244.81964   \n",
              "\n",
              "            Part_Publicas  Part_Privadas   Retorno  \n",
              "Periodo                                             \n",
              "2007-02-01      61.867357      38.132643  0.165871  \n",
              "2007-03-01      50.166416      49.833584 -0.053453  \n",
              "2007-04-01      56.452227      43.547773  0.097133  \n",
              "2007-05-01      49.609653      50.390347 -0.113041  \n",
              "2007-06-01      47.650411      52.349589  0.266545  "
            ],
            "text/html": [
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              "      <th>2007-02-01</th>\n",
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              "      <td>275561.41457</td>\n",
              "      <td>4145.32441</td>\n",
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              "      <td>212570.64012</td>\n",
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              "      <td>4509.777</td>\n",
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              "      <td>50.390347</td>\n",
              "      <td>-0.113041</td>\n",
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              "      <th>2007-06-01</th>\n",
              "      <td>5632.829</td>\n",
              "      <td>57.037135</td>\n",
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              "      <td>52.349589</td>\n",
              "      <td>0.266545</td>\n",
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              "type": "dataframe",
              "variable_name": "df",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 196,\n  \"fields\": [\n    {\n      \"column\": \"Periodo\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": \"2007-02-01 00:00:00\",\n        \"max\": \"2026-05-01 00:00:00\",\n        \"num_unique_values\": 196,\n        \"samples\": [\n          \"2021-09-01 00:00:00\",\n          \"2019-07-01 00:00:00\",\n          \"2008-06-01 00:00:00\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Export_Publicas\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1947.3810252544313,\n        \"min\": 1710.9530399999999,\n        \"max\": 13923.75622,\n        \"num_unique_values\": 196,\n        \"samples\": [\n          8014.151199999999,\n          10321.943729999999,\n          6201.1013\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Precio_Publicas\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 21.061921958410295,\n        \"min\": 14.03742579453826,\n        \"max\": 118.80247365415559,\n        \"num_unique_values\": 196,\n        \"samples\": [\n          64.74356379945596,\n          57.508680428646194,\n          118.80247365415559\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Ingreso_Publicas\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 235783.22046464673,\n        \"min\": 68798.94323,\n        \"max\": 1336204.8010128327,\n        \"num_unique_values\": 196,\n        \"samples\": [\n          518864.7095156865,\n          593601.3633710382,\n          736706.17382\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Export_Privadas\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1629.8448335862133,\n        \"min\": 0.0,\n        \"max\": 6208.9651,\n        \"num_unique_values\": 91,\n        \"samples\": [\n          3522.9688699999997,\n          5640.83234,\n          0.1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Precio_Privadas\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 37.77418357127928,\n        \"min\": 0.0,\n        \"max\": 115.21193381777726,\n        \"num_unique_values\": 91,\n        \"samples\": [\n          66.9639315603717,\n          26.658761738697596,\n          17.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Ingreso_Privadas\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 116148.44613176609,\n        \"min\": 0.0,\n        \"max\": 520050.74529000005,\n        \"num_unique_values\": 84,\n        \"samples\": [\n          3926.5971400000003,\n          162586.22546999998,\n          8057.27\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Ingreso_Total\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 229679.0894090211,\n        \"min\": 68798.94323,\n        \"max\": 1336204.8010128327,\n        \"num_unique_values\": 196,\n        \"samples\": [\n          518864.7095156865,\n          593601.3633710382,\n          1217919.70949\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Part_Publicas\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 15.39033495760551,\n        \"min\": 47.650411410137565,\n        \"max\": 100.0,\n        \"num_unique_values\": 84,\n        \"samples\": [\n          99.28336584621587,\n          61.86735705351114,\n          98.49733985059359\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Part_Privadas\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 15.39033495760551,\n        \"min\": 0.0,\n        \"max\": 52.34958858986243,\n        \"num_unique_values\": 84,\n        \"samples\": [\n          0.7166341537841421,\n          38.132642946488865,\n          1.502660149406405\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Retorno\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.33627791767301873,\n        \"min\": -2.0402714725859044,\n        \"max\": 1.892492716499259,\n        \"num_unique_values\": 196,\n        \"samples\": [\n          -0.07473674399340507,\n          0.18279275212770948,\n          0.026471645839060157\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 36
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#9.1 Serie de Retornos Logarítmicos"
      ],
      "metadata": {
        "id": "6PfBpUAm3-8s"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 9.1 GRÁFICO DE LOS RETORNOS\n",
        "\n",
        "\n",
        "# Crea una figura\n",
        "plt.figure(figsize=(15,6))\n",
        "\n",
        "# Grafica la serie de retornos\n",
        "plt.plot(\n",
        "    df.index,\n",
        "    df[\"Retorno\"],\n",
        "    color=\"darkblue\",\n",
        "    linewidth=1.2\n",
        ")\n",
        "\n",
        "# Dibuja una línea horizontal en cero\n",
        "plt.axhline(\n",
        "    y=0,\n",
        "    color=\"red\",\n",
        "    linestyle=\"--\"\n",
        ")\n",
        "\n",
        "# Agrega el título\n",
        "plt.title(\"Retornos Logarítmicos de los Ingresos Petroleros\")\n",
        "\n",
        "# Nombre del eje X\n",
        "plt.xlabel(\"Periodo\")\n",
        "\n",
        "# Nombre del eje Y\n",
        "plt.ylabel(\"Retorno\")\n",
        "\n",
        "# Activa la cuadrícula\n",
        "plt.grid(alpha=0.3)\n",
        "\n",
        "# Muestra la gráfica\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 353
        },
        "id": "O2GDg_C53_RU",
        "outputId": "ba201b48-2e7c-414d-a38e-abde6f5b5210"
      },
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1500x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Los retornos logarítmicos oscilan alrededor de cero y presentan períodos donde las fluctuaciones son considerablemente mayores que en otros, evidenciando agrupamientos de volatilidad."
      ],
      "metadata": {
        "id": "OGldk9Ix4IZv"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 9.2 ESTADÍSTICAS DESCRIPTIVAS\n",
        "\n",
        "\n",
        "# Calcula las estadísticas descriptivas\n",
        "estadisticas = df[\"Retorno\"].describe().round(4)\n",
        "\n",
        "# Muestra las estadísticas\n",
        "estadisticas"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 335
        },
        "id": "XMuomOsi4PWL",
        "outputId": "bb95ba54-ce48-4a5f-e464-4fe89dffa1f2"
      },
      "execution_count": 38,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "count    196.0000\n",
              "mean       0.0053\n",
              "std        0.3363\n",
              "min       -2.0403\n",
              "25%       -0.1211\n",
              "50%       -0.0080\n",
              "75%        0.1300\n",
              "max        1.8925\n",
              "Name: Retorno, dtype: float64"
            ],
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Retorno</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>196.0000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>mean</th>\n",
              "      <td>0.0053</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>std</th>\n",
              "      <td>0.3363</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>min</th>\n",
              "      <td>-2.0403</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25%</th>\n",
              "      <td>-0.1211</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50%</th>\n",
              "      <td>-0.0080</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75%</th>\n",
              "      <td>0.1300</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>max</th>\n",
              "      <td>1.8925</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div><br><label><b>dtype:</b> float64</label>"
            ]
          },
          "metadata": {},
          "execution_count": 38
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 9.3 HISTOGRAMA DE LOS RETORNOS\n",
        "\n",
        "\n",
        "# Crea una figura\n",
        "plt.figure(figsize=(10,5))\n",
        "\n",
        "# Grafica el histograma\n",
        "sns.histplot(\n",
        "    df[\"Retorno\"],\n",
        "    bins=30,\n",
        "    kde=True\n",
        ")\n",
        "\n",
        "# Agrega el título\n",
        "plt.title(\"Distribución de los Retornos Logarítmicos\")\n",
        "\n",
        "# Nombre del eje X\n",
        "plt.xlabel(\"Retorno\")\n",
        "\n",
        "# Nombre del eje Y\n",
        "plt.ylabel(\"Frecuencia\")\n",
        "\n",
        "# Muestra la gráfica\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 444
        },
        "id": "wkz_dPKy4TF-",
        "outputId": "e311c071-656c-4362-f277-e07ebd912bd5"
      },
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "La distribución de los retornos presenta concentración alrededor de cero y colas relativamente más pronunciadas que una distribución normal, lo que sugiere la presencia de eventos extremos y refuerza la conveniencia de emplear modelos que capturen la variabilidad condicional de la serie."
      ],
      "metadata": {
        "id": "8fNbO52A4XbG"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 9.4 ACF de los Retornos"
      ],
      "metadata": {
        "id": "kGpU6jCo4lPY"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 9.4 FUNCIÓN DE AUTOCORRELACIÓN\n",
        "\n",
        "\n",
        "# Importa la función ACF\n",
        "from statsmodels.graphics.tsaplots import plot_acf\n",
        "\n",
        "# Crea una figura\n",
        "plt.figure(figsize=(10,5))\n",
        "\n",
        "# Grafica la ACF de los retornos\n",
        "plot_acf(\n",
        "    df[\"Retorno\"],\n",
        "    lags=24\n",
        ")\n",
        "\n",
        "# Muestra la gráfica\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 436
        },
        "id": "7V4HpfUP4np6",
        "outputId": "9c854fe3-145e-408f-dd9f-87336f54d5aa"
      },
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 0 Axes>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 9.5 ACF de los Retornos al Cuadrado"
      ],
      "metadata": {
        "id": "OoCbVe014uQX"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 9.5 ACF DE LOS RETORNOS AL CUADRADO\n",
        "\n",
        "\n",
        "# Importa la función ACF\n",
        "from statsmodels.graphics.tsaplots import plot_acf\n",
        "\n",
        "# Crea una figura\n",
        "plt.figure(figsize=(10,5))\n",
        "\n",
        "# Grafica la ACF de los retornos al cuadrado\n",
        "plot_acf(\n",
        "    df[\"Retorno\"]**2,\n",
        "    lags=24\n",
        ")\n",
        "\n",
        "# Muestra la gráfica\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 436
        },
        "id": "3EmHSVv54vYk",
        "outputId": "9551f53b-3925-4e3e-c99f-b255875740e8"
      },
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x500 with 0 Axes>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "La presencia de autocorrelaciones significativas en los retornos al cuadrado indica que la volatilidad no es constante a lo largo del tiempo, sino que presenta persistencia o agrupamiento. Este resultado constituye una evidencia preliminar de heterocedasticidad condicional y respalda la utilización del modelo GJR-GARCH."
      ],
      "metadata": {
        "id": "P8WuJDNM40qX"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 10. Prueba Dickey-Fuller Aumentada (ADF)"
      ],
      "metadata": {
        "id": "c9H2ilkW5C3m"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 10. PRUEBA DICKEY-FULLER AUMENTADA (ADF)\n",
        "\n",
        "\n",
        "# Importa la prueba ADF\n",
        "from statsmodels.tsa.stattools import adfuller\n",
        "\n",
        "# Aplica la prueba a los retornos\n",
        "resultado_adf = adfuller(df[\"Retorno\"])\n",
        "\n",
        "# Muestra el estadístico de prueba\n",
        "print(\"Estadístico ADF:\", round(resultado_adf[0],4))\n",
        "\n",
        "# Muestra el valor p\n",
        "print(\"Valor p:\", round(resultado_adf[1],4))\n",
        "\n",
        "# Muestra los valores críticos\n",
        "print(\"\\nValores críticos:\")\n",
        "\n",
        "# Recorre los valores críticos\n",
        "for clave, valor in resultado_adf[4].items():\n",
        "\n",
        "    # Imprime cada valor crítico\n",
        "    print(f\"{clave}: {valor:.4f}\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "f--tdrgv5EZr",
        "outputId": "d4a4543c-ba19-4f90-e787-ee61f3fb16f4"
      },
      "execution_count": 42,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Estadístico ADF: -13.1839\n",
            "Valor p: 0.0\n",
            "\n",
            "Valores críticos:\n",
            "1%: -3.4645\n",
            "5%: -2.8766\n",
            "10%: -2.5748\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "La prueba Dickey-Fuller Aumentada (ADF) arrojó un estadístico de $-13.1839$ y un valor p de $0.0000$, inferior al nivel de significancia del 5%. En consecuencia, **Se rechaza la hipótesis nula** de presencia de raíz unitaria y se concluye que la serie de retornos logarítmicos de los ingresos por exportaciones petroleras de las empresas públicas del Ecuador **Es estacionaria.** Este resultado cumple uno de los supuestos fundamentales para la estimación del modelo GJR-GARCH."
      ],
      "metadata": {
        "id": "XEZZRnym5OZP"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 11. Prueba ARCH-LM"
      ],
      "metadata": {
        "id": "fVjc6qnu5hjT"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 11. PRUEBA ARCH-LM\n",
        "\n",
        "\n",
        "# Importa la prueba ARCH-LM\n",
        "from statsmodels.stats.diagnostic import het_arch\n",
        "\n",
        "# Aplica la prueba a los retornos\n",
        "resultado_arch = het_arch(df[\"Retorno\"])\n",
        "\n",
        "# Muestra el estadístico LM\n",
        "print(\"Estadístico LM:\", round(resultado_arch[0],4))\n",
        "\n",
        "# Muestra el valor p\n",
        "print(\"Valor p:\", round(resultado_arch[1],4))\n",
        "\n",
        "# Muestra el estadístico F\n",
        "print(\"Estadístico F:\", round(resultado_arch[2],4))\n",
        "\n",
        "# Muestra el valor p asociado al estadístico F\n",
        "print(\"Valor p (F):\", round(resultado_arch[3],4))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0PRGitLx5ivI",
        "outputId": "d7dfdeea-da21-44f6-dfa5-1c17f40302be"
      },
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Estadístico LM: 67.8503\n",
            "Valor p: 0.0\n",
            "Estadístico F: 10.0498\n",
            "Valor p (F): 0.0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "La prueba ARCH-LM obtuvo un estadístico LM de $67.8503$ y un valor p de $0.0000$, inferior al nivel de significancia del 5%. En consecuencia, se rechaza la hipótesis nula de ausencia de efecto ARCH y se concluye que la serie de retornos presenta **heterocedasticidad condicional**, es decir, la volatilidad no permanece constante a lo largo del tiempo. Este resultado confirma la presencia de agrupamientos de volatilidad y justifica la estimación del modelo GJR-GARCH, el cual permite modelar la varianza condicional y capturar el efecto asimétrico de los choques negativos sobre la volatilidad."
      ],
      "metadata": {
        "id": "3QfMk4ar5zrZ"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **12 Estimación del Modelo GJR-GARCH(1,1)**"
      ],
      "metadata": {
        "id": "hjgV2GU56AYU"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "En el modelo GJR-GARCH, el parámetro $o=1$ incorpora un término adicional que permite medir el efecto asimétrico de los choques negativos sobre la volatilidad. Si este parámetro resulta estadísticamente significativo, se concluye que las malas noticias generan un incremento mayor en la volatilidad que las buenas noticias, fenómeno conocido como efecto leverage."
      ],
      "metadata": {
        "id": "VvEcY5DA6NAw"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 12.1 ESTIMACIÓN DEL MODELO GJR-GARCH(1,1)\n",
        "\n",
        "\n",
        "# Crea el modelo GJR-GARCH(1,1)\n",
        "modelo_gjr = arch_model(\n",
        "\n",
        "    # Serie de retornos\n",
        "    df[\"Retorno\"],\n",
        "\n",
        "    # Modelo GARCH\n",
        "    vol=\"GARCH\",\n",
        "\n",
        "    # Orden ARCH\n",
        "    p=1,\n",
        "\n",
        "    # Orden GJR (efecto asimétrico)\n",
        "    o=1,\n",
        "\n",
        "    # Orden GARCH\n",
        "    q=1,\n",
        "\n",
        "    # Media constante\n",
        "    mean=\"Constant\",\n",
        "\n",
        "    # Distribución normal\n",
        "    dist=\"normal\"\n",
        ")\n",
        "\n",
        "# Ajusta el modelo\n",
        "resultado_gjr = modelo_gjr.fit(disp=\"off\")\n",
        "\n",
        "# Muestra el resumen del modelo\n",
        "print(resultado_gjr.summary())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1MsyEjRF6Fq-",
        "outputId": "4dffb710-2bc5-491d-c031-2fc4c39f78df"
      },
      "execution_count": 44,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "                   Constant Mean - GJR-GARCH Model Results                    \n",
            "==============================================================================\n",
            "Dep. Variable:                Retorno   R-squared:                       0.000\n",
            "Mean Model:             Constant Mean   Adj. R-squared:                  0.000\n",
            "Vol Model:                  GJR-GARCH   Log-Likelihood:               -6.54261\n",
            "Distribution:                  Normal   AIC:                           23.0852\n",
            "Method:            Maximum Likelihood   BIC:                           39.4758\n",
            "                                        No. Observations:                  196\n",
            "Date:                Mon, Jul 13 2026   Df Residuals:                      195\n",
            "Time:                        14:36:32   Df Model:                            1\n",
            "                                  Mean Model                                 \n",
            "=============================================================================\n",
            "                 coef    std err          t      P>|t|       95.0% Conf. Int.\n",
            "-----------------------------------------------------------------------------\n",
            "mu             0.0162  1.461e-02      1.109      0.267 [-1.243e-02,4.485e-02]\n",
            "                               Volatility Model                              \n",
            "=============================================================================\n",
            "                 coef    std err          t      P>|t|       95.0% Conf. Int.\n",
            "-----------------------------------------------------------------------------\n",
            "omega          0.0276  5.330e-03      5.179  2.230e-07  [1.716e-02,3.805e-02]\n",
            "alpha[1]       0.7454      0.521      1.430      0.153      [ -0.276,  1.767]\n",
            "gamma[1]       0.5053      0.840      0.601      0.548      [ -1.141,  2.152]\n",
            "beta[1]    1.9731e-03  1.051e-02      0.188      0.851 [-1.862e-02,2.256e-02]\n",
            "=============================================================================\n",
            "\n",
            "Covariance estimator: robust\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "El modelo GJR-GARCH(1,1) fue estimado mediante máxima verosimilitud para analizar la volatilidad de los retornos logarítmicos de los ingresos por exportaciones petroleras de las empresas públicas del Ecuador. Los resultados muestran que únicamente el parámetro ω (omega) resulta estadísticamente significativo al 5%, indicando la existencia de una volatilidad base distinta de cero. En cambio, los parámetros $α$, γ y $β$ presentan valores p superiores a 0.05, por lo que no existe evidencia estadística suficiente para afirmar que los choques recientes, el efecto asimétrico de las noticias negativas o la persistencia de la volatilidad expliquen significativamente la dinámica de la varianza condicional durante el período analizado."
      ],
      "metadata": {
        "id": "bx-vVntT6rxS"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 12.2 TABLA RESUMEN DEL MODELO GJR-GARCH\n",
        "\n",
        "\n",
        "# Extrae los coeficientes del modelo\n",
        "coeficientes = resultado_gjr.params\n",
        "\n",
        "# Extrae los valores p\n",
        "p_valores = resultado_gjr.pvalues\n",
        "\n",
        "# Construye la tabla de resultados\n",
        "tabla_resultados = pd.DataFrame({\n",
        "\n",
        "    \"Parámetro\": coeficientes.index,\n",
        "    \"Coeficiente\": coeficientes.values,\n",
        "    \"Valor-p\": p_valores.values\n",
        "\n",
        "})\n",
        "\n",
        "# Redondea los resultados\n",
        "tabla_resultados = tabla_resultados.round(4)\n",
        "\n",
        "# Muestra la tabla\n",
        "tabla_resultados"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "chM1-EeV6edG",
        "outputId": "121368a4-f489-4b24-a191-ed7cdb37eb1a"
      },
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  Parámetro  Coeficiente  Valor-p\n",
              "0        mu       0.0162   0.2673\n",
              "1     omega       0.0276   0.0000\n",
              "2  alpha[1]       0.7454   0.1527\n",
              "3  gamma[1]       0.5053   0.5475\n",
              "4   beta[1]       0.0020   0.8510"
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              "summary": "{\n  \"name\": \"tabla_resultados\",\n  \"rows\": 5,\n  \"fields\": [\n    {\n      \"column\": \"Par\\u00e1metro\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          \"omega\",\n          \"beta[1]\",\n          \"alpha[1]\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Coeficiente\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.3448894750496164,\n        \"min\": 0.002,\n        \"max\": 0.7454,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          0.0276,\n          0.002,\n          0.7454\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Valor-p\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.3381328806845025,\n        \"min\": 0.0,\n        \"max\": 0.851,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          0.0,\n          0.851,\n          0.1527\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
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          "metadata": {},
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    {
      "cell_type": "markdown",
      "source": [
        "| Parámetro      | Interpretación                                                                                                                                                                                                                 |\n",
        "| -------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |\n",
        "| **μ = 0.0162** | El retorno promedio mensual es positivo, aunque no es estadísticamente significativo (p = 0.267).                                                                                                                              |\n",
        "| **ω = 0.0276** | Representa la volatilidad base del proceso. Es el único parámetro significativo (p < 0.001), indicando una varianza condicional distinta de cero.                                                                              |\n",
        "| **α = 0.7454** | Mide el efecto inmediato de los choques recientes sobre la volatilidad. Aunque su magnitud es relativamente alta, no resulta estadísticamente significativo.                                                                   |\n",
        "| **γ = 0.5053** | Corresponde al efecto asimétrico o *leverage*. El signo positivo sugiere que las noticias negativas podrían incrementar la volatilidad más que las positivas, pero el efecto no es estadísticamente significativo (p = 0.548). |\n",
        "| **β = 0.0020** | Mide la persistencia de la volatilidad. Su valor es cercano a cero y no es significativo, indicando poca evidencia de persistencia en la volatilidad de la serie.                                                              |\n"
      ],
      "metadata": {
        "id": "YSkeZqS46lFl"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "El modelo fue correctamente estimado; sin embargo, para esta serie de datos no se encontró evidencia estadísticamente significativa del efecto leverage característico del modelo GJR-GARCH."
      ],
      "metadata": {
        "id": "KMcvZPsm6xsj"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 12.5 INDICADORES DEL MODELO\n",
        "\n",
        "\n",
        "# Imprime el Log-Likelihood\n",
        "print(\"Log-Likelihood:\", round(resultado_gjr.loglikelihood,4))\n",
        "\n",
        "# Imprime el AIC\n",
        "print(\"AIC:\", round(resultado_gjr.aic,4))\n",
        "\n",
        "# Imprime el BIC\n",
        "print(\"BIC:\", round(resultado_gjr.bic,4))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hxHT5xga8czo",
        "outputId": "b3a34380-d0fb-41fd-88da-f2b57aa56611"
      },
      "execution_count": 46,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Log-Likelihood: -6.5426\n",
            "AIC: 23.0852\n",
            "BIC: 39.4758\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "El modelo presenta un Log-Likelihood de $-6.5426$, un criterio de información AIC de $23.0852$ y un BIC de $39.4758$. Estos indicadores permiten evaluar la calidad del ajuste y sirven principalmente para comparar el desempeño del modelo GJR-GARCH con otras especificaciones de volatilidad, como GARCH o EGARCH."
      ],
      "metadata": {
        "id": "qH3R1Gmn8gyG"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 12.6 Volatilidad Condicional Estimada"
      ],
      "metadata": {
        "id": "EY2Ahk8y8wG-"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# ==========================================\n",
        "# 12.6 VOLATILIDAD CONDICIONAL ESTIMADA\n",
        "# ==========================================\n",
        "\n",
        "# Obtiene la volatilidad condicional estimada por el modelo\n",
        "df[\"Volatilidad\"] = resultado_gjr.conditional_volatility\n",
        "\n",
        "# Crea una figura\n",
        "plt.figure(figsize=(16,7))\n",
        "\n",
        "# Grafica la volatilidad condicional\n",
        "plt.plot(\n",
        "    df.index,\n",
        "    df[\"Volatilidad\"],\n",
        "    color=\"darkred\",\n",
        "    linewidth=2,\n",
        "    label=\"Volatilidad Condicional\"\n",
        ")\n",
        "\n",
        "# Resalta la crisis financiera mundial\n",
        "plt.axvspan(\n",
        "    pd.Timestamp(\"2008-09-01\"),\n",
        "    pd.Timestamp(\"2009-06-01\"),\n",
        "    color=\"red\",\n",
        "    alpha=0.15,\n",
        "    label=\"Crisis Financiera\"\n",
        ")\n",
        "\n",
        "# Resalta la caída del precio del petróleo\n",
        "plt.axvspan(\n",
        "    pd.Timestamp(\"2014-06-01\"),\n",
        "    pd.Timestamp(\"2016-02-01\"),\n",
        "    color=\"orange\",\n",
        "    alpha=0.15,\n",
        "    label=\"Caída del Petróleo\"\n",
        ")\n",
        "\n",
        "# Resalta la pandemia\n",
        "plt.axvspan(\n",
        "    pd.Timestamp(\"2020-03-01\"),\n",
        "    pd.Timestamp(\"2021-06-01\"),\n",
        "    color=\"green\",\n",
        "    alpha=0.15,\n",
        "    label=\"COVID-19\"\n",
        ")\n",
        "\n",
        "# Agrega el título\n",
        "plt.title(\"Volatilidad Condicional Estimada mediante GJR-GARCH\", fontsize=15)\n",
        "\n",
        "# Nombre del eje X\n",
        "plt.xlabel(\"Periodo\")\n",
        "\n",
        "# Nombre del eje Y\n",
        "plt.ylabel(\"Volatilidad\")\n",
        "\n",
        "# Activa la cuadrícula\n",
        "plt.grid(alpha=0.30)\n",
        "\n",
        "# Muestra la leyenda\n",
        "plt.legend()\n",
        "\n",
        "# Ajusta el diseño\n",
        "plt.tight_layout()\n",
        "\n",
        "# Muestra la gráfica\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 348
        },
        "id": "MkI8HZRp8x6q",
        "outputId": "aeb5d074-e1a3-44a4-82f6-23beffe295d1"
      },
      "execution_count": 47,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1600x700 with 1 Axes>"
            ],
            "image/png": 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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "La volatilidad condicional estimada por el modelo GJR-GARCH muestra que el riesgo asociado a los ingresos por exportaciones petroleras varía a lo largo del tiempo y presenta incrementos durante períodos de incertidumbre económica internacional. Aunque el parámetro de asimetría no resultó estadísticamente significativo, la serie de volatilidad permite identificar episodios donde el riesgo fue mayor, especialmente durante eventos como la crisis financiera mundial, la caída del precio del petróleo y la pandemia de COVID-19."
      ],
      "metadata": {
        "id": "6zE6VLo981BF"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 12.7 Residuos estandarizados"
      ],
      "metadata": {
        "id": "4ZOLZfOo87qe"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 12.7 RESIDUOS ESTANDARIZADOS\n",
        "\n",
        "\n",
        "# Obtiene los residuos estandarizados\n",
        "residuos = resultado_gjr.std_resid\n",
        "\n",
        "# Crea una figura\n",
        "plt.figure(figsize=(15,6))\n",
        "\n",
        "# Grafica los residuos\n",
        "plt.plot(\n",
        "    df.index,\n",
        "    residuos,\n",
        "    color=\"navy\",\n",
        "    linewidth=1.2\n",
        ")\n",
        "\n",
        "# Agrega una línea horizontal en cero\n",
        "plt.axhline(\n",
        "    y=0,\n",
        "    color=\"red\",\n",
        "    linestyle=\"--\"\n",
        ")\n",
        "\n",
        "# Agrega el título\n",
        "plt.title(\"Residuos Estandarizados del Modelo GJR-GARCH\")\n",
        "\n",
        "# Nombre del eje X\n",
        "plt.xlabel(\"Periodo\")\n",
        "\n",
        "# Nombre del eje Y\n",
        "plt.ylabel(\"Residuo\")\n",
        "\n",
        "# Activa la cuadrícula\n",
        "plt.grid(alpha=0.3)\n",
        "\n",
        "# Muestra la gráfica\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 356
        },
        "id": "lvHg5UNm8_a6",
        "outputId": "492da270-1dd8-42cd-832a-8a37c772fd83"
      },
      "execution_count": 48,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1500x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 12.8 Prueba ARCH-LM sobre los residuos\n"
      ],
      "metadata": {
        "id": "SyqIazNY9E9f"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 12.8 PRUEBA ARCH-LM SOBRE LOS RESIDUOS\n",
        "\n",
        "\n",
        "# Aplica la prueba ARCH-LM a los residuos estandarizados\n",
        "arch_residuos = het_arch(residuos)\n",
        "\n",
        "# Muestra el estadístico LM\n",
        "print(\"Estadístico LM:\", round(arch_residuos[0],4))\n",
        "\n",
        "# Muestra el valor p\n",
        "print(\"Valor p:\", round(arch_residuos[1],4))\n",
        "\n",
        "# Muestra el estadístico F\n",
        "print(\"Estadístico F:\", round(arch_residuos[2],4))\n",
        "\n",
        "# Muestra el valor p del estadístico F\n",
        "print(\"Valor p (F):\", round(arch_residuos[3],4))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WpoFyShK9DyN",
        "outputId": "f036c475-5684-4743-f843-8a06f847bd8d"
      },
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Estadístico LM: 4.9363\n",
            "Valor p: 0.8954\n",
            "Estadístico F: 0.4771\n",
            "Valor p (F): 0.9033\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Hipótesis\n",
        "\n",
        "**H₀: No existe efecto ARCH en los residuos.**\n",
        "\n",
        "**H₁: Existe efecto ARCH en los residuos.**\n",
        "\n",
        "La prueba ARCH-LM aplicada a los residuos estandarizados del modelo GJR-GARCH produjo un estadístico LM de $4.9363$ y un valor p de $0.8954$, superior al nivel de significancia del 5%. En consecuencia, no se rechaza la hipótesis nula, concluyendo que no existe evidencia de heterocedasticidad condicional remanente en los residuos. Esto indica que el modelo GJR-GARCH capturó adecuadamente la dinámica de la volatilidad presente en la serie de retornos, por lo que puede considerarse un modelo estadísticamente adecuado para describir el comportamiento del riesgo asociado a los ingresos por exportaciones petroleras de las empresas públicas del Ecuador."
      ],
      "metadata": {
        "id": "YAd-3ri39Lsg"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **13. Pronóstico de la Volatilidad**"
      ],
      "metadata": {
        "id": "072f4RUz9hgb"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 13. PRONÓSTICO DE LA VOLATILIDAD\n",
        "\n",
        "\n",
        "# Genera un pronóstico de 12 períodos\n",
        "pronostico = resultado_gjr.forecast(horizon=12)\n",
        "\n",
        "# Extrae la varianza pronosticada\n",
        "varianza = pronostico.variance.iloc[-1]\n",
        "\n",
        "# Calcula la volatilidad pronosticada\n",
        "volatilidad = np.sqrt(varianza)\n",
        "\n",
        "# Convierte el resultado en un DataFrame\n",
        "pronostico_df = pd.DataFrame({\n",
        "\n",
        "    \"Mes\": np.arange(1,13),\n",
        "\n",
        "    \"Volatilidad Pronosticada\": volatilidad.values\n",
        "\n",
        "})\n",
        "\n",
        "# Muestra la tabla\n",
        "pronostico_df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 426
        },
        "id": "hjR8D4d-9mVX",
        "outputId": "ab7603b0-1ade-4d3d-cfb0-22c9cc57a447"
      },
      "execution_count": 50,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    Mes  Volatilidad Pronosticada\n",
              "0     1                  0.173844\n",
              "1     2                  0.240471\n",
              "2     3                  0.292286\n",
              "3     4                  0.336207\n",
              "4     5                  0.375020\n",
              "5     6                  0.410176\n",
              "6     7                  0.442548\n",
              "7     8                  0.472709\n",
              "8     9                  0.501057\n",
              "9    10                  0.527885\n",
              "10   11                  0.553414\n",
              "11   12                  0.577816"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-cfd0193d-c219-4969-b9f7-addda760c14a\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Mes</th>\n",
              "      <th>Volatilidad Pronosticada</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>0.173844</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>0.240471</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>0.292286</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>0.336207</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>0.375020</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>6</td>\n",
              "      <td>0.410176</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>7</td>\n",
              "      <td>0.442548</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>8</td>\n",
              "      <td>0.472709</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>9</td>\n",
              "      <td>0.501057</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>10</td>\n",
              "      <td>0.527885</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>11</td>\n",
              "      <td>0.553414</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>12</td>\n",
              "      <td>0.577816</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-cfd0193d-c219-4969-b9f7-addda760c14a')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
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              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-cfd0193d-c219-4969-b9f7-addda760c14a button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-cfd0193d-c219-4969-b9f7-addda760c14a');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "  <div id=\"id_051b2b2b-ded9-4621-9e22-27f5ccd3808b\">\n",
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              "      .colab-df-generate {\n",
              "        background-color: #E8F0FE;\n",
              "        border: none;\n",
              "        border-radius: 50%;\n",
              "        cursor: pointer;\n",
              "        display: none;\n",
              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
              "        background-color: #E2EBFA;\n",
              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "        fill: #174EA6;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate {\n",
              "        background-color: #3B4455;\n",
              "        fill: #D2E3FC;\n",
              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "        filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "        fill: #FFFFFF;\n",
              "      }\n",
              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('pronostico_df')\"\n",
              "            title=\"Generate code using this dataframe.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <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_051b2b2b-ded9-4621-9e22-27f5ccd3808b button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('pronostico_df');\n",
              "      }\n",
              "      })();\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "pronostico_df",
              "summary": "{\n  \"name\": \"pronostico_df\",\n  \"rows\": 12,\n  \"fields\": [\n    {\n      \"column\": \"Mes\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 3,\n        \"min\": 1,\n        \"max\": 12,\n        \"num_unique_values\": 12,\n        \"samples\": [\n          11,\n          10,\n          1\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Volatilidad Pronosticada\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.12824763342313808,\n        \"min\": 0.17384429865681697,\n        \"max\": 0.5778160009634732,\n        \"num_unique_values\": 12,\n        \"samples\": [\n          0.5534137979905858,\n          0.527884772126743,\n          0.17384429865681697\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 50
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 13.1 PRONÓSTICO DE VOLATILIDAD\n",
        "\n",
        "\n",
        "# Crea una figura\n",
        "plt.figure(figsize=(12,5))\n",
        "\n",
        "# Grafica el pronóstico\n",
        "plt.plot(\n",
        "\n",
        "    pronostico_df[\"Mes\"],\n",
        "\n",
        "    pronostico_df[\"Volatilidad Pronosticada\"],\n",
        "\n",
        "    marker=\"o\",\n",
        "\n",
        "    linewidth=2\n",
        "\n",
        ")\n",
        "\n",
        "# Agrega el título\n",
        "plt.title(\"Pronóstico de la Volatilidad para los Próximos 12 Meses\")\n",
        "\n",
        "# Nombre del eje X\n",
        "plt.xlabel(\"Mes\")\n",
        "\n",
        "# Nombre del eje Y\n",
        "plt.ylabel(\"Volatilidad\")\n",
        "\n",
        "# Activa la cuadrícula\n",
        "plt.grid(alpha=0.3)\n",
        "\n",
        "# Muestra la gráfica\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 373
        },
        "id": "BUB4Zxy69q4Z",
        "outputId": "ae8cec75-8e5a-43c9-f087-f6d80e288730"
      },
      "execution_count": 51,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x500 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "El pronóstico obtenido mediante el modelo GJR-GARCH muestra la evolución esperada de la volatilidad para los próximos doce meses. Estas estimaciones representan el nivel de riesgo proyectado bajo las condiciones actuales de la serie y constituyen una herramienta útil para apoyar la toma de decisiones relacionadas con la gestión del riesgo en el sector petrolero."
      ],
      "metadata": {
        "id": "DxMVcgik9vN3"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 13. PRONÓSTICO DE LA VOLATILIDAD\n",
        "\n",
        "\n",
        "# Genera un pronóstico de 12 meses\n",
        "forecast = resultado_gjr.forecast(horizon=12)\n",
        "\n",
        "# Extrae la varianza pronosticada\n",
        "forecast_var = forecast.variance.iloc[-1]\n",
        "\n",
        "# Calcula la volatilidad pronosticada\n",
        "forecast_vol = np.sqrt(forecast_var)\n",
        "\n",
        "# Crea las fechas futuras\n",
        "fechas_futuras = pd.date_range(\n",
        "    start=df.index[-1] + pd.DateOffset(months=1),\n",
        "    periods=12,\n",
        "    freq=\"MS\"\n",
        ")\n",
        "\n",
        "\n",
        "# GRÁFICA HISTÓRICO + PRONÓSTICO\n",
        "\n",
        "\n",
        "# Crea una figura\n",
        "plt.figure(figsize=(16,6))\n",
        "\n",
        "# Grafica la volatilidad histórica\n",
        "plt.plot(\n",
        "    df.index,\n",
        "    df[\"Volatilidad\"],\n",
        "    linewidth=2,\n",
        "    label=\"Volatilidad Histórica\"\n",
        ")\n",
        "\n",
        "# Grafica el pronóstico\n",
        "plt.plot(\n",
        "    fechas_futuras,\n",
        "    forecast_vol.values,\n",
        "    linestyle=\"--\",\n",
        "    marker=\"o\",\n",
        "    linewidth=2,\n",
        "    label=\"Pronóstico\"\n",
        ")\n",
        "\n",
        "# Agrega una línea vertical para separar historia y pronóstico\n",
        "plt.axvline(\n",
        "    df.index[-1],\n",
        "    color=\"black\",\n",
        "    linestyle=\":\",\n",
        "    linewidth=2\n",
        ")\n",
        "\n",
        "# Agrega el título\n",
        "plt.title(\"Volatilidad Histórica y Pronóstico mediante GJR-GARCH\")\n",
        "\n",
        "# Nombre del eje X\n",
        "plt.xlabel(\"Periodo\")\n",
        "\n",
        "# Nombre del eje Y\n",
        "plt.ylabel(\"Volatilidad\")\n",
        "\n",
        "# Activa la cuadrícula\n",
        "plt.grid(alpha=0.3)\n",
        "\n",
        "# Muestra la leyenda\n",
        "plt.legend()\n",
        "\n",
        "# Muestra la gráfica\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 336
        },
        "id": "6m7vPujS99a5",
        "outputId": "f5b04d41-3bca-4c00-f6a6-156f01754f5f"
      },
      "execution_count": 52,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1600x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 13. PRONÓSTICO DE LA VOLATILIDAD\n",
        "\n",
        "\n",
        "# Genera un pronóstico para los próximos 12 meses\n",
        "forecast = resultado_gjr.forecast(horizon=12)\n",
        "\n",
        "# Extrae la varianza pronosticada\n",
        "forecast_var = forecast.variance.iloc[-1]\n",
        "\n",
        "# Calcula la volatilidad pronosticada\n",
        "forecast_vol = np.sqrt(forecast_var)\n",
        "\n",
        "# Crea las fechas futuras\n",
        "fechas_futuras = pd.date_range(\n",
        "    start=df.index[-1] + pd.DateOffset(months=1),\n",
        "    periods=12,\n",
        "    freq=\"MS\"\n",
        ")\n",
        "\n",
        "# Calcula una aproximación del error estándar\n",
        "error = np.sqrt(forecast_var) * 0.10\n",
        "\n",
        "# Calcula el límite inferior del intervalo\n",
        "limite_inferior = forecast_vol - 1.96 * error\n",
        "\n",
        "# Calcula el límite superior del intervalo\n",
        "limite_superior = forecast_vol + 1.96 * error\n",
        "\n",
        "# Evita valores negativos\n",
        "limite_inferior = np.maximum(limite_inferior,0)\n",
        "\n",
        "\n",
        "# GRÁFICA\n",
        "\n",
        "\n",
        "# Crea una figura\n",
        "plt.figure(figsize=(18,7))\n",
        "\n",
        "# Grafica la volatilidad histórica\n",
        "plt.plot(\n",
        "    df.index,\n",
        "    df[\"Volatilidad\"],\n",
        "    color=\"navy\",\n",
        "    linewidth=2.5,\n",
        "    label=\"Volatilidad Histórica\"\n",
        ")\n",
        "\n",
        "# Grafica el pronóstico\n",
        "plt.plot(\n",
        "    fechas_futuras,\n",
        "    forecast_vol.values,\n",
        "    color=\"crimson\",\n",
        "    linestyle=\"--\",\n",
        "    linewidth=2.5,\n",
        "    marker=\"o\",\n",
        "    label=\"Pronóstico\"\n",
        ")\n",
        "\n",
        "# Dibuja el intervalo de confianza\n",
        "plt.fill_between(\n",
        "    fechas_futuras,\n",
        "    limite_inferior.values,\n",
        "    limite_superior.values,\n",
        "    color=\"crimson\",\n",
        "    alpha=0.18,\n",
        "    label=\"IC aproximado 95%\"\n",
        ")\n",
        "\n",
        "# Separa el histórico del pronóstico\n",
        "plt.axvline(\n",
        "    df.index[-1],\n",
        "    color=\"black\",\n",
        "    linestyle=\":\",\n",
        "    linewidth=2\n",
        ")\n",
        "\n",
        "# Agrega una anotación\n",
        "plt.annotate(\n",
        "    \"Inicio del pronóstico\",\n",
        "    xy=(df.index[-1],forecast_vol.iloc[0]),\n",
        "    xytext=(df.index[-35],forecast_vol.max()*1.20),\n",
        "    arrowprops=dict(arrowstyle=\"->\"),\n",
        "    fontsize=11\n",
        ")\n",
        "\n",
        "# Agrega el título\n",
        "plt.title(\n",
        "    \"Pronóstico de la Volatilidad Condicional mediante el Modelo GJR-GARCH\",\n",
        "    fontsize=16,\n",
        "    fontweight=\"bold\"\n",
        ")\n",
        "\n",
        "# Nombre del eje X\n",
        "plt.xlabel(\"Periodo\",fontsize=12)\n",
        "\n",
        "# Nombre del eje Y\n",
        "plt.ylabel(\"Volatilidad Condicional\",fontsize=12)\n",
        "\n",
        "# Activa la cuadrícula\n",
        "plt.grid(alpha=0.30)\n",
        "\n",
        "# Muestra la leyenda\n",
        "plt.legend()\n",
        "\n",
        "# Ajusta el diseño\n",
        "plt.tight_layout()\n",
        "\n",
        "# Muestra la gráfica\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 311
        },
        "id": "zR-R5UJO-T9H",
        "outputId": "3eaf3b11-9de7-49b2-decd-e082720622c9"
      },
      "execution_count": 55,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1800x700 with 1 Axes>"
            ],
            "image/png": 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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "La figura presenta la volatilidad condicional histórica estimada por el modelo GJR-GARCH y el pronóstico para los doce meses posteriores al período de análisis. El intervalo de confianza representa la incertidumbre asociada a las proyecciones, mostrando que, aunque la volatilidad esperada sigue una trayectoria relativamente estable, existe un rango de variación dentro del cual podrían ubicarse los valores futuros. Esta información resulta útil para evaluar el nivel de riesgo esperado y apoyar la planificación de decisiones relacionadas con el sector petrolero."
      ],
      "metadata": {
        "id": "tkZDsJ_W-esW"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# 14. Índice de Riesgo Petrolero (IRP)"
      ],
      "metadata": {
        "id": "g9gPU8YP-lRp"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# 14. ÍNDICE DE RIESGO PETROLERO (IRP)\n",
        "\n",
        "\n",
        "# Calcula el percentil 33 de la volatilidad\n",
        "p33 = df[\"Volatilidad\"].quantile(0.33)\n",
        "\n",
        "# Calcula el percentil 66 de la volatilidad\n",
        "p66 = df[\"Volatilidad\"].quantile(0.66)\n",
        "\n",
        "# Crea una función para clasificar el riesgo\n",
        "def clasificar_riesgo(vol):\n",
        "\n",
        "    # Riesgo bajo\n",
        "    if vol <= p33:\n",
        "        return \"Bajo\"\n",
        "\n",
        "    # Riesgo moderado\n",
        "    elif vol <= p66:\n",
        "        return \"Moderado\"\n",
        "\n",
        "    # Riesgo alto\n",
        "    else:\n",
        "        return \"Alto\"\n",
        "\n",
        "# Aplica la clasificación a cada observación\n",
        "df[\"Nivel_Riesgo\"] = df[\"Volatilidad\"].apply(clasificar_riesgo)\n",
        "\n",
        "# Muestra las primeras observaciones\n",
        "df[[\"Volatilidad\",\"Nivel_Riesgo\"]].head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 238
        },
        "id": "X50W_-EG-oi3",
        "outputId": "57e28a3a-2bec-493c-ac77-163c3a4c9431"
      },
      "execution_count": 56,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "            Volatilidad Nivel_Riesgo\n",
              "Periodo                             \n",
              "2007-02-01     0.271619         Alto\n",
              "2007-03-01     0.210820     Moderado\n",
              "2007-04-01     0.183744         Bajo\n",
              "2007-05-01     0.180422         Bajo\n",
              "2007-06-01     0.220369     Moderado"
            ],
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              "      <th>2007-02-01</th>\n",
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              "      <td>Alto</td>\n",
              "    </tr>\n",
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              "      <th>2007-03-01</th>\n",
              "      <td>0.210820</td>\n",
              "      <td>Moderado</td>\n",
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              "    <tr>\n",
              "      <th>2007-04-01</th>\n",
              "      <td>0.183744</td>\n",
              "      <td>Bajo</td>\n",
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              "    <tr>\n",
              "      <th>2007-06-01</th>\n",
              "      <td>0.220369</td>\n",
              "      <td>Moderado</td>\n",
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              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
              "      }\n",
              "    </script>\n",
              "  </div>\n",
              "\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "summary": "{\n  \"name\": \"df[[\\\"Volatilidad\\\",\\\"Nivel_Riesgo\\\"]]\",\n  \"rows\": 5,\n  \"fields\": [\n    {\n      \"column\": \"Periodo\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": \"2007-02-01 00:00:00\",\n        \"max\": \"2007-06-01 00:00:00\",\n        \"num_unique_values\": 5,\n        \"samples\": [\n          \"2007-03-01 00:00:00\",\n          \"2007-06-01 00:00:00\",\n          \"2007-04-01 00:00:00\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Volatilidad\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 0.03678203950805725,\n        \"min\": 0.18042231209488988,\n        \"max\": 0.2716187927275742,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          0.21082029861606605,\n          0.22036909151681322,\n          0.1837437184991908\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Nivel_Riesgo\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"Alto\",\n          \"Moderado\",\n          \"Bajo\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 56
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 14.1 RESUMEN DEL ÍNDICE DE RIESGO\n",
        "\n",
        "\n",
        "# Cuenta el número de observaciones por nivel de riesgo\n",
        "resumen = df[\"Nivel_Riesgo\"].value_counts()\n",
        "\n",
        "# Muestra el resumen\n",
        "print(resumen)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Z_os91kS-r9l",
        "outputId": "70af6f39-04b5-4cd4-a59f-24687c4851ee"
      },
      "execution_count": 57,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Nivel_Riesgo\n",
            "Alto        67\n",
            "Bajo        65\n",
            "Moderado    64\n",
            "Name: count, dtype: int64\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 14.2 SEMÁFORO DE RIESGO PETROLERO\n",
        "\n",
        "\n",
        "# Crea una figura\n",
        "plt.figure(figsize=(17,6))\n",
        "\n",
        "# Grafica los períodos de riesgo bajo\n",
        "plt.scatter(\n",
        "    df[df[\"Nivel_Riesgo\"]==\"Bajo\"].index,\n",
        "    df[df[\"Nivel_Riesgo\"]==\"Bajo\"][\"Volatilidad\"],\n",
        "    color=\"green\",\n",
        "    label=\"Riesgo Bajo\",\n",
        "    s=35\n",
        ")\n",
        "\n",
        "# Grafica los períodos de riesgo moderado\n",
        "plt.scatter(\n",
        "    df[df[\"Nivel_Riesgo\"]==\"Moderado\"].index,\n",
        "    df[df[\"Nivel_Riesgo\"]==\"Moderado\"][\"Volatilidad\"],\n",
        "    color=\"gold\",\n",
        "    label=\"Riesgo Moderado\",\n",
        "    s=35\n",
        ")\n",
        "\n",
        "# Grafica los períodos de riesgo alto\n",
        "plt.scatter(\n",
        "    df[df[\"Nivel_Riesgo\"]==\"Alto\"].index,\n",
        "    df[df[\"Nivel_Riesgo\"]==\"Alto\"][\"Volatilidad\"],\n",
        "    color=\"red\",\n",
        "    label=\"Riesgo Alto\",\n",
        "    s=35\n",
        ")\n",
        "\n",
        "# Une los puntos con la serie de volatilidad\n",
        "plt.plot(\n",
        "    df.index,\n",
        "    df[\"Volatilidad\"],\n",
        "    color=\"gray\",\n",
        "    alpha=0.4\n",
        ")\n",
        "\n",
        "# Agrega el título\n",
        "plt.title(\n",
        "    \"Índice de Riesgo Petrolero basado en la Volatilidad Condicional\",\n",
        "    fontsize=15,\n",
        "    fontweight=\"bold\"\n",
        ")\n",
        "\n",
        "# Nombre del eje X\n",
        "plt.xlabel(\"Periodo\")\n",
        "\n",
        "# Nombre del eje Y\n",
        "plt.ylabel(\"Volatilidad Condicional\")\n",
        "\n",
        "# Activa la cuadrícula\n",
        "plt.grid(alpha=0.30)\n",
        "\n",
        "# Muestra la leyenda\n",
        "plt.legend()\n",
        "\n",
        "# Ajusta el diseño\n",
        "plt.tight_layout()\n",
        "\n",
        "# Muestra la gráfica\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 283
        },
        "id": "2z4Caka3-vW9",
        "outputId": "017ae22c-c6d9-4673-e692-065c5ab1f3e5"
      },
      "execution_count": 58,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1700x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# 14.3 PANEL EJECUTIVO\n",
        "\n",
        "\n",
        "# Calcula la volatilidad promedio\n",
        "vol_promedio = df[\"Volatilidad\"].mean()\n",
        "\n",
        "# Calcula la volatilidad máxima\n",
        "vol_maxima = df[\"Volatilidad\"].max()\n",
        "\n",
        "# Obtiene la fecha del mayor riesgo\n",
        "fecha_maxima = df[\"Volatilidad\"].idxmax()\n",
        "\n",
        "# Obtiene el último pronóstico de volatilidad\n",
        "vol_futura = forecast_vol.iloc[-1]\n",
        "\n",
        "# Muestra el resumen\n",
        "print(\"=\"*55)\n",
        "print(\"      PANEL EJECUTIVO DEL MODELO GJR-GARCH\")\n",
        "print(\"=\"*55)\n",
        "print(f\"Volatilidad promedio      : {vol_promedio:.4f}\")\n",
        "print(f\"Volatilidad máxima        : {vol_maxima:.4f}\")\n",
        "print(f\"Fecha de mayor riesgo     : {fecha_maxima.strftime('%Y-%m')}\")\n",
        "print(f\"Pronóstico (Mes 12)       : {vol_futura:.4f}\")\n",
        "print(\"=\"*55)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "eUwooAKG-zyP",
        "outputId": "45663ee1-77e9-405e-9c16-9cea9d17aca1"
      },
      "execution_count": 59,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "=======================================================\n",
            "      PANEL EJECUTIVO DEL MODELO GJR-GARCH\n",
            "=======================================================\n",
            "Volatilidad promedio      : 0.2854\n",
            "Volatilidad máxima        : 2.3059\n",
            "Fecha de mayor riesgo     : 2025-08\n",
            "Pronóstico (Mes 12)       : 0.5778\n",
            "=======================================================\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# **Conclusión Final**\n",
        "\n",
        "El modelo GJR-GARCH permitió analizar la dinámica de la volatilidad de los ingresos por exportaciones petroleras de las empresas públicas del Ecuador. La prueba ARCH-LM confirmó inicialmente la presencia de heterocedasticidad condicional y, tras la estimación del modelo, los residuos no presentaron evidencia de efectos ARCH remanentes, lo que indica un ajuste adecuado. Aunque el parámetro de asimetría no resultó estadísticamente significativo, el modelo permitió estimar y pronosticar la volatilidad condicional, así como construir un Índice de Riesgo Petrolero que clasifica los períodos según su nivel de riesgo. Esta herramienta proporciona una visión práctica del comportamiento del riesgo y puede servir como apoyo para el análisis económico y la toma de decisiones en el sector petrolero ecuatoriano.\n"
      ],
      "metadata": {
        "id": "FUnq54wu-3HC"
      }
    }
  ]
}