From d87f52e32c8a90309569c65f4054d008df1f0e31 Mon Sep 17 00:00:00 2001 From: Cjohanna Date: Thu, 29 Jun 2023 10:42:29 -0500 Subject: [PATCH 1/7] changes in the basic structure --- _config.yml | 18 ++++---- _includes/head.html | 1 + _includes/navbar.html | 2 +- _layouts/post.html | 2 - _posts/2020-01-26-dinosaurs.html | 40 ------------------ _posts/2020-01-28-exploration.html | 40 ------------------ _posts/2020-01-29-prophecy.html | 40 ------------------ _posts/2020-01-30-heartbeats.html | 39 ----------------- _posts/2020-01-31-man-must-explore.html | 40 ------------------ _posts/2023-04-3-Energy Efficiency.html | 44 +++++++++++++++++++ _posts/2023-06-28-WIne Quality.html | 48 +++++++++++++++++++++ about.html | 6 +-- contact.html | 54 +++++++++--------------- img/bg-about.jpg | Bin 2547880 -> 2997028 bytes img/bg-contact.jpg | Bin 500680 -> 342596 bytes img/bg-index.jpg | Bin 1007801 -> 1371641 bytes img/bg-post.jpg | Bin 784852 -> 4425933 bytes img/posts/03.jpg | Bin 1803228 -> 1188901 bytes img/posts/06.jpg | Bin 1254313 -> 3083146 bytes posts/index.html | 2 +- 20 files changed, 125 insertions(+), 251 deletions(-) delete mode 100644 _posts/2020-01-26-dinosaurs.html delete mode 100644 _posts/2020-01-28-exploration.html delete mode 100644 _posts/2020-01-29-prophecy.html delete mode 100644 _posts/2020-01-30-heartbeats.html delete mode 100644 _posts/2020-01-31-man-must-explore.html create mode 100644 _posts/2023-04-3-Energy Efficiency.html create mode 100644 _posts/2023-06-28-WIne Quality.html diff --git a/_config.yml b/_config.yml index fb6e996934..651c5e6a82 100644 --- a/_config.yml +++ b/_config.yml @@ -1,14 +1,14 @@ -title: Clean Blog -email: your-email@example.com -description: A Blog Theme by Start Bootstrap -author: Start Bootstrap -baseurl: "/startbootstrap-clean-blog-jekyll" -url: "https://startbootstrap.github.io" +title: Data Lab +email: diazaguirrejohanna@gmail.com +description: "Analytics and customized solutions for your business or project.
by Johanna Diaz Aguirre " +author: "Start Bootstrap" +baseurl: "" +url: "https://Cjohanna.github.io" # Social Profiles -twitter_username: SBootstrap -github_username: StartBootstrap -facebook_username: StartBootstrap +twitter_username: +github_username: +facebook_username: instagram_username: linkedin_username: diff --git a/_includes/head.html b/_includes/head.html index 7848045415..2f0637515b 100644 --- a/_includes/head.html +++ b/_includes/head.html @@ -12,6 +12,7 @@ + diff --git a/_includes/navbar.html b/_includes/navbar.html index c514748a08..75d7dc7e77 100644 --- a/_includes/navbar.html +++ b/_includes/navbar.html @@ -15,7 +15,7 @@ About
  • Cooling Load: Cooling load of the building
  • Exploratory Data Analysis

    - -

    - -Demo Image - -

    Placeholder text by Space Ipsum. Photographs by Unsplash.

    +Demo Image +

    Before diving into the predictive modeling, an initial step is to perform an Exploratory Data Analysis (EDA). For this purpose, you can load the dataset into your working environment, such as Python with Pandas, and execute the following tasks:

    +
      +
    1. Descriptive Statistics: Calculate summary statistics, including mean, median, standard deviation, and percentiles for each feature.
    2. +
    3. Graphs: Create visual representations like histograms, box plots, and scatter plots to visualize the distributions and relationships among the features.
    4. +
    5. Correlations: Compute correlations between the features and wine quality to identify potential relationships.
    6. +
    7. Data Cleaning: Perform data cleaning as necessary, which may involve handling outliers or imputing missing values.
    8. +
    9. Quality Analysis: Examine the distribution of wine quality and search for patterns based on chemical characteristics.
    10. +
    + +

    Photographs by Unsplash.

    \ No newline at end of file diff --git a/_posts/2023-06-28-WIne Quality.html b/_posts/2023-06-28-WIne Quality.html index f2a990b933..c58a8953ad 100644 --- a/_posts/2023-06-28-WIne Quality.html +++ b/_posts/2023-06-28-WIne Quality.html @@ -36,13 +36,27 @@

    Description of Dataset

  • Wine Quality: It is evaluated on a discrete scale of 0 to 10, where a higher value indicates better quality
  • Exploratory Data Analysis

    -

    - -Demo Image -To go places and do things that have never been done before – that’s what living is all about. - -

    Space, the final frontier. These are the voyages of the Starship Enterprise. Its five-year mission: to explore strange new worlds, to seek out new life and new civilizations, to boldly go where no man has gone before.

    - -

    As I stand out here in the wonders of the unknown at Hadley, I sort of realize there’s a fundamental truth to our nature, Man must explore, and this is exploration at its greatest.

    - -

    Placeholder text by Space Ipsum. Photographs by Unsplash.

    +Demo Image +

    Before diving into the predictive modeling, an initial step is to perform an Exploratory Data Analysis (EDA). For this purpose, you can load the dataset into your working environment, such as Python with Pandas, and execute the following tasks:

    + +

    This repository contains the results of a comprehensive analysis of a white wine dataset provided by the reference researchers. The analysis involved three key stages: data preprocessing, modeling and evaluation, and performance improvement strategies.

    + +

    Data Preprocessing

    +

    In the data preprocessing phase, we applied essential techniques, such as feature scaling using StandardScaler. This ensured that all features contributed equally to the modeling process, thus avoiding the dominance of certain attributes over others.

    + +

    Modeling

    +

    In the modeling stage, we deliberately selected four specific algorithms: Decision Tree, Random Forest, SVM, and K-NN. The choice of these algorithms was based on their demonstrated ability to address classification problems in complex datasets. It is important to note that, although some algorithms were shared with the reference study, the methodologies differed in aspects such as hyperparameter tuning and how class imbalance was addressed.

    + +

    Evaluation

    +

    The reference study provided results that served as a starting point for model evaluation. It was observed that, despite achieving acceptable levels of accuracy, class imbalance affected the model's ability to generalize to minority classes. This finding was crucial in determining the need to implement an oversampling strategy.

    + +

    Performance Improvement

    +

    The oversampling strategy was the key element in significantly improving the model's performance. By increasing the number of instances in the minority classes, the class distribution was balanced, allowing the model to learn more effectively from all classes. This resulted in a noticeable increase in accuracy on the test set, reaching an impressive 92%.

    + +

    Conclusion

    +

    While both methodologies shared the use of some common algorithms, they differed in their approach to addressing class imbalance and the specific model configurations. This distinction is fundamental and highlights the importance of adapting methodologies to the unique characteristics of each dataset and problem.

    + +

    For more details, refer to the complete analysis and code in this repository.

    + + +

    Photographs by Unsplash.

    From 46fb84755d29c9bdffa61480e352a55de90fbe09 Mon Sep 17 00:00:00 2001 From: Johanna Diaz Aguirre <103522572+Cjohanna@users.noreply.github.com> Date: Wed, 25 Oct 2023 20:24:11 -0500 Subject: [PATCH 5/7] Add files via upload This file is the Jupyter notebook where the ML was developed --- WineQuality.ipynb | 1467 +++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 1467 insertions(+) create mode 100644 WineQuality.ipynb diff --git a/WineQuality.ipynb b/WineQuality.ipynb new file mode 100644 index 0000000000..460f3190f1 --- /dev/null +++ b/WineQuality.ipynb @@ -0,0 +1,1467 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "a6cd2625", + "metadata": {}, + "source": [ + "# Wine Quality \n", + "#### Nombre del dataset : [Wine Quality del UCI Machine Learning Repository](https://archive.ics.uci.edu/dataset/186/wine+quality)\n", + "\n", + "\n", + "### Introducción\n", + "\n", + "Este proyecto se centra en el análisis exploratorio de datos (EDA) de un conjunto de datos de calidad del vino, que contiene información sobre vinos rojos y blancos.\n", + "\n", + "### Origen de los Datos\n", + "\n", + "Los datos utilizados en este análisis provienen del Repositorio de Aprendizaje Automático de la UCI (Universidad de California, Irvine). Fueron recopilados por P. Cortez, A. Cerdeira, F. Almeida, T. Matos y J. Reis en la Universidade de Minho, Portugal. Estos investigadores recopilaron información sobre diferentes propiedades químicas de vinos y la calidad percibida por catadores expertos.\n", + "\n", + "### Objetivo del Análisis\n", + "\n", + "El objetivo principal de este análisis es comprender en profundidad el conjunto de datos y extraer información valiosa que pueda ser útil para desarrollar modelos de aprendizaje automático para predecir la calidad del vino en función de sus propiedades químicas. Además de este objetivo central, existen otros objetivos más específicos, que incluyen:\n", + "\n", + "1. Identificar patrones y relaciones entre las características químicas y la calidad del vino.\n", + "2. Evaluar la distribución de la calidad del vino.\n", + "3. Realizar un análisis exploratorio para revelar insights y tendencias interesantes.\n", + "\n", + "#### Variables en el Conjunto de Datos\n", + "\n", + "El conjunto de datos se divide en dos archivos CSV: uno para vinos rojos y otro para vinos blancos. Cada archivo contiene las siguientes variables con sus respectivas unidades:\n", + "\n", + "#### Variables de Características Químicas (Entradas):\n", + "\n", + "1. `fixed acidity` (g/dm³): Acidez fija.\n", + "2. `volatile acidity` (g/dm³): Acidez volátil.\n", + "3. `citric acid` (g/dm³): Ácido cítrico.\n", + "4. `residual sugar` (g/dm³): Azúcar residual.\n", + "5. `chlorides` (g/dm³): Cloruros.\n", + "6. `free sulfur dioxide` (mg/dm³): Dióxido de azufre libre.\n", + "7. `total sulfur dioxide` (mg/dm³): Dióxido de azufre total.\n", + "8. `density` (g/cm³): Densidad.\n", + "9. `pH`: pH.\n", + "10. `sulphates` (g/dm³): Sulfatos.\n", + "11. `alcohol` (% vol): Contenido de alcohol.\n", + "\n", + "### Variable de Calidad (Objetivo):\n", + "\n", + "12. `quality`: Calidad del vino (puntuación de 0 a 10, donde 0 es de muy mala calidad y 10 es excelente de calidad).\n", + "\n", + "### Análisis Exploratorio de Datos - Conjunto de Datos de Calidad del Vino\n", + "\n", + "En las secciones siguientes de este notebook, realizaremos un análisis exhaustivo de estas variables y exploraremos relaciones, tendencias y patrones. Además, se llevarán a cabo visualizaciones gráficas para facilitar la comprensión de los datos." + ] + }, + { + "cell_type": "code", + "execution_count": 26, + "id": "311bce01", + "metadata": {}, + "outputs": [], + "source": [ + "# Importación de librerías para tratamiento de datos\n", + "# ==============================================================================\n", + "import pandas as pd\n", + "import numpy as np\n", + "\n", + "# Importación de librerías para gráficos\n", + "# ==============================================================================\n", + "import matplotlib.pyplot as plt\n", + "from matplotlib import style\n", + "import seaborn as sns\n", + "import statsmodels.api as sm\n", + "from tabulate import tabulate\n", + "\n", + "# Importación de librerías para estadística descriptiva\n", + "# ==============================================================================\n", + "from scipy.stats import shapiro, kstest, anderson\n", + "from scipy.stats import describe\n", + "\n", + "# Importación de librerías para métricas y evaluación\n", + "# ==============================================================================\n", + "from sklearn.preprocessing import StandardScaler\n", + "from sklearn.model_selection import train_test_split\n", + "from sklearn.feature_selection import SelectFromModel\n", + "from sklearn.model_selection import KFold\n", + "from sklearn.model_selection import cross_val_score, cross_val_predict\n", + "from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score, classification_report\n", + "from sklearn.metrics import mean_absolute_error, mean_squared_error, r2_score\n", + "\n", + "# Importación de librerías para modelado\n", + "# ==============================================================================\n", + "from sklearn.tree import DecisionTreeClassifier\n", + "from sklearn.neighbors import KNeighborsClassifier\n", + "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n", + "from sklearn.naive_bayes import GaussianNB\n", + "from sklearn.ensemble import RandomForestClassifier\n", + "from sklearn.svm import SVC\n", + "from sklearn.svm import SVR" + ] + }, + { + "cell_type": "code", + "execution_count": 27, + "id": "3c4f1f25", + "metadata": {}, + "outputs": [], + "source": [ + " import pandas as pd\n", + "\n", + "# Nombres de las columnas (variables)\n", + "column_names = [\"fixed acidity\", \"volatile acidity\", \"citric acid\", \"residual sugar\", \"chlorides\",\n", + " \"free sulfur dioxide\", \"total sulfur dioxide\", \"density\", \"pH\", \"sulphates\", \"alcohol\", \"quality\"]\n", + "\n", + "# Datos de vinos rojos \n", + "red_wine_df = pd.read_csv(\"https://archive.ics.uci.edu/ml/machine-learning-databases/wine-quality/winequality-red.csv\", sep=\";\", names=column_names, header=0)\n", + "\n", + "# Datos de vinos blancos \n", + "white_wine_df = pd.read_csv(\"https://archive.ics.uci.edu/ml/machine-learning-databases/wine-quality/winequality-white.csv\", sep=\";\", names=column_names, header=0)\n" + ] + }, + { + "cell_type": "markdown", + "id": "49798165", + "metadata": {}, + "source": [ + "### Vinos Blancos (White Wine)\n", + "1. **Aspectos Generales**: " + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "003b9de3", + "metadata": {}, + "outputs": [], + "source": [ + "X = white_wine_df.drop(\"quality\", axis=1) \n", + "y = white_wine_df[\"quality\"] " + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "ce12f514", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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    " + ], + "text/plain": [ + " fixed acidity volatile acidity citric acid residual sugar chlorides \\\n", + "0 7.0 0.27 0.36 20.7 0.045 \n", + "1 6.3 0.30 0.34 1.6 0.049 \n", + "2 8.1 0.28 0.40 6.9 0.050 \n", + "3 7.2 0.23 0.32 8.5 0.058 \n", + "4 7.2 0.23 0.32 8.5 0.058 \n", + "... ... ... ... ... ... \n", + "4893 6.2 0.21 0.29 1.6 0.039 \n", + "4894 6.6 0.32 0.36 8.0 0.047 \n", + "4895 6.5 0.24 0.19 1.2 0.041 \n", + "4896 5.5 0.29 0.30 1.1 0.022 \n", + "4897 6.0 0.21 0.38 0.8 0.020 \n", + "\n", + " free sulfur dioxide total sulfur dioxide density pH sulphates \\\n", + "0 45.0 170.0 1.00100 3.00 0.45 \n", + "1 14.0 132.0 0.99400 3.30 0.49 \n", + "2 30.0 97.0 0.99510 3.26 0.44 \n", + "3 47.0 186.0 0.99560 3.19 0.40 \n", + "4 47.0 186.0 0.99560 3.19 0.40 \n", + "... ... ... ... ... ... \n", + "4893 24.0 92.0 0.99114 3.27 0.50 \n", + "4894 57.0 168.0 0.99490 3.15 0.46 \n", + "4895 30.0 111.0 0.99254 2.99 0.46 \n", + "4896 20.0 110.0 0.98869 3.34 0.38 \n", + "4897 22.0 98.0 0.98941 3.26 0.32 \n", + "\n", + " alcohol quality \n", + "0 8.8 6 \n", + "1 9.5 6 \n", + "2 10.1 6 \n", + "3 9.9 6 \n", + "4 9.9 6 \n", + "... ... ... \n", + "4893 11.2 6 \n", + "4894 9.6 5 \n", + "4895 9.4 6 \n", + "4896 12.8 7 \n", + "4897 11.8 6 \n", + "\n", + "[4898 rows x 12 columns]" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#Visualización del dataframe\n", + "white_wine_df" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "ef49b39b", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(4898, 12)" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#Forma del dataframe\n", + "white_wine_df.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "46ed4c47", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Index(['fixed acidity', 'volatile acidity', 'citric acid', 'residual sugar',\n", + " 'chlorides', 'free sulfur dioxide', 'total sulfur dioxide', 'density',\n", + " 'pH', 'sulphates', 'alcohol', 'quality'],\n", + " dtype='object')\n" + ] + } + ], + "source": [ + "print(white_wine_df.columns)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "9e7f9f80", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "RangeIndex: 4898 entries, 0 to 4897\n", + "Data columns (total 12 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 fixed acidity 4898 non-null float64\n", + " 1 volatile acidity 4898 non-null float64\n", + " 2 citric acid 4898 non-null float64\n", + " 3 residual sugar 4898 non-null float64\n", + " 4 chlorides 4898 non-null float64\n", + " 5 free sulfur dioxide 4898 non-null float64\n", + " 6 total sulfur dioxide 4898 non-null float64\n", + " 7 density 4898 non-null float64\n", + " 8 pH 4898 non-null float64\n", + " 9 sulphates 4898 non-null float64\n", + " 10 alcohol 4898 non-null float64\n", + " 11 quality 4898 non-null int64 \n", + "dtypes: float64(11), int64(1)\n", + "memory usage: 459.3 KB\n" + ] + } + ], + "source": [ + "# Aspectos básicos del DataFrame\n", + "white_wine_df.info()" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "c22ae7e8", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "fixed acidity 0\n", + "volatile acidity 0\n", + "citric acid 0\n", + "residual sugar 0\n", + "chlorides 0\n", + "free sulfur dioxide 0\n", + "total sulfur dioxide 0\n", + "density 0\n", + "pH 0\n", + "sulphates 0\n", + "alcohol 0\n", + "quality 0\n", + "dtype: int64" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#Examinando datos perdidos \n", + "white_wine_df.isna().sum()" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "b96c553f", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
    " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.hist(y, bins=10, edgecolor='k') \n", + "plt.xlabel('Calidad del Vino')\n", + "plt.ylabel('Frecuencia')\n", + "plt.title('Distribución de Calidad del Vino')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "d316f8eb", + "metadata": {}, + "source": [ + "2. **Estadistica básica: Normalidad del conjuto de datos**: \n", + "\n", + " 2.1 _Histogramas_: Una forma visual preliminar de verificar la normalidad de tus datos es crear un histograma. Si la distribución se asemeja a una campana simétrica, en este caso más probable que siga una distribución normal, por la forma de campana. De igual manera vemos que tiene leves asimetrias, por lo cual vamos utilizar otros metodos para comprobar su distribución." + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "724ae45a", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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    " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "#Construcción de histogramas\n", + "import seaborn as sns\n", + "\n", + "fig, axes = plt.subplots(4, 3, figsize=(14, 14))\n", + "\n", + "for i, column in enumerate(column_names[:-1]):\n", + " row = i // 3 # Índice de fila\n", + " col = i % 3 # Índice de columna\n", + " sns.histplot(white_wine_df[column], kde=True, ax=axes[row, col], color= (list(plt.rcParams['axes.prop_cycle'])*2)[i][\"color\"])\n", + "\n", + "plt.tight_layout() \n", + "plt.show()\n" + ] + }, + { + "cell_type": "markdown", + "id": "e72636f5", + "metadata": {}, + "source": [ + " 2.2 _Pruebas de distribución normal_: \n", + " \n", + "Para evaluar si el conjunto de datos sigue una distribución normal, utilizaremos la prueba de Anderson-Darling. Esta prueba es más poderosa para detectar desviaciones de la normalidad en las colas largas de la distribución, como se hace evidente en los histogramas. Esto significa que puede identificar valores atípicos en las colas más eficazmente que la Prueba de Shapiro-Wilk. Además, la Prueba de Shapiro-Wilk funciona bien con tamaños de muestra generalmente menores a 2,000 observaciones, mientras que para el conjunto de datos del vino blanco, tenemos 4,898 entradas.\n", + "\n", + "Hipótesis nula (H0): Los datos siguen una distribución normal o gaussiana.\n", + "\n", + "Hipótesis alternativa (Ha): Los datos no siguen una distribución normal" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "742fb977", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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    FeatureAnderson-Darling p-valueAnderson-Darling NormalitySkewnessSkewness Interpretation
    0fixed acidity0.786Se acepta la H00.647553Sesgo a la derecha
    1volatile acidity0.786Se acepta la H01.576497Sesgo a la derecha
    2citric acid0.786Se acepta la H01.281528Sesgo a la derecha
    3residual sugar0.786Se acepta la H01.076764Sesgo a la derecha
    4chlorides0.786Se acepta la H05.021792Sesgo a la derecha
    5free sulfur dioxide0.786Se acepta la H01.406314Sesgo a la derecha
    6total sulfur dioxide0.786Se acepta la H00.390590Sesgo a la derecha
    7density0.786Se acepta la H00.977474Sesgo a la derecha
    8pH0.786Se acepta la H00.457642Sesgo a la derecha
    9sulphates0.786Se acepta la H00.976894Sesgo a la derecha
    10alcohol0.786Se acepta la H00.487193Sesgo a la derecha
    11quality0.786Se acepta la H00.155749Sesgo a la derecha
    \n", + "
    " + ], + "text/plain": [ + " Feature Anderson-Darling p-value Anderson-Darling Normality \\\n", + "0 fixed acidity 0.786 Se acepta la H0 \n", + "1 volatile acidity 0.786 Se acepta la H0 \n", + "2 citric acid 0.786 Se acepta la H0 \n", + "3 residual sugar 0.786 Se acepta la H0 \n", + "4 chlorides 0.786 Se acepta la H0 \n", + "5 free sulfur dioxide 0.786 Se acepta la H0 \n", + "6 total sulfur dioxide 0.786 Se acepta la H0 \n", + "7 density 0.786 Se acepta la H0 \n", + "8 pH 0.786 Se acepta la H0 \n", + "9 sulphates 0.786 Se acepta la H0 \n", + "10 alcohol 0.786 Se acepta la H0 \n", + "11 quality 0.786 Se acepta la H0 \n", + "\n", + " Skewness Skewness Interpretation \n", + "0 0.647553 Sesgo a la derecha \n", + "1 1.576497 Sesgo a la derecha \n", + "2 1.281528 Sesgo a la derecha \n", + "3 1.076764 Sesgo a la derecha \n", + "4 5.021792 Sesgo a la derecha \n", + "5 1.406314 Sesgo a la derecha \n", + "6 0.390590 Sesgo a la derecha \n", + "7 0.977474 Sesgo a la derecha \n", + "8 0.457642 Sesgo a la derecha \n", + "9 0.976894 Sesgo a la derecha \n", + "10 0.487193 Sesgo a la derecha \n", + "11 0.155749 Sesgo a la derecha " + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# DataFrame para almacenar los resultados \n", + "results = pd.DataFrame(columns=[\"Feature\", \"Anderson-Darling p-value\", \"Anderson-Darling Normality\", \"Skewness\", \"Skewness Interpretation\"])\n", + "\n", + "# nivel de significancia \n", + "alpha = 0.05\n", + "\n", + "for feature in column_names:\n", + " data = white_wine_df[feature]\n", + " \n", + " # Prueba de Anderson-Darling\n", + " anderson_result = anderson(data)\n", + " ad_p = anderson_result.critical_values[2] \n", + " if ad_p > alpha:\n", + " ad_normality = \"Se acepta la H0\"\n", + " else:\n", + " ad_normality = \"Se rechaza la H0\"\n", + " \n", + " # Estadísticas descriptivas\n", + " stats = describe(data)\n", + " \n", + " # estadísticas de sesgo\n", + " skewness = stats.skewness\n", + " skewness_interpretation = \"Sesgo a la izquierda\" if skewness < 0 else \"Sesgo a la derecha\" if skewness > 0 else \"Sin sesgo\"\n", + " \n", + " # Agregar los resultados al DataFrame\n", + " result_df = pd.DataFrame({\n", + " \"Feature\": [feature],\n", + " \"Anderson-Darling p-value\": [ad_p],\n", + " \"Anderson-Darling Normality\": [ad_normality],\n", + " \"Skewness\": [skewness],\n", + " \"Skewness Interpretation\": [skewness_interpretation] \n", + " })\n", + " results = pd.concat([results, result_df], ignore_index=True)\n", + " \n", + "results" + ] + }, + { + "cell_type": "markdown", + "id": "74874889", + "metadata": {}, + "source": [ + "2. 3 _Matriz de correlación_: " + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "e96f442b", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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    " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import seaborn as sns\n", + "\n", + "# matriz de correlación de variables independientes\n", + "x_correlation_matrix = X.corr()\n", + "\n", + "\n", + "plt.figure(figsize=(8, 8))\n", + "sns.heatmap(x_correlation_matrix, annot=True, cmap='coolwarm', fmt=\".2f\")\n", + "plt.title(\"Matriz de correlación de variables Independientes\", fontsize=14)\n", + "plt.xticks(fontsize=10)\n", + "plt.yticks(fontsize=10)\n", + "\n", + "# los ejes x e y\n", + "plt.xlabel(\"Variables\", fontsize=12)\n", + "plt.ylabel(\"Variables\", fontsize=12)\n", + "\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "bacfa926", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "╒══════════════════════╤══════════════════════╤═══════════════╤══════════════════════╕\n", + "│ Atributo 1 │ Atributo 2 │ Correlación │ Clasificación │\n", + "╞══════════════════════╪══════════════════════╪═══════════════╪══════════════════════╡\n", + "│ fixed acidity │ pH │ -0.425858 │ Moderada correlación │\n", + "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", + "│ residual sugar │ total sulfur dioxide │ 0.401439 │ Moderada correlación │\n", + "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", + "│ residual sugar │ density │ 0.838966 │ Alta correlación │\n", + "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", + "│ residual sugar │ alcohol │ -0.450631 │ Moderada correlación │\n", + "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", + "│ chlorides │ alcohol │ -0.360189 │ Moderada correlación │\n", + "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", + "│ free sulfur dioxide │ total sulfur dioxide │ 0.615501 │ Moderada correlación │\n", + "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", + "│ total sulfur dioxide │ residual sugar │ 0.401439 │ Moderada correlación │\n", + "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", + "│ total sulfur dioxide │ free sulfur dioxide │ 0.615501 │ Moderada correlación │\n", + "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", + "│ total sulfur dioxide │ density │ 0.529881 │ Moderada correlación │\n", + "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", + "│ total sulfur dioxide │ alcohol │ -0.448892 │ Moderada correlación │\n", + "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", + "│ density │ residual sugar │ 0.838966 │ Alta correlación │\n", + "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", + "│ density │ total sulfur dioxide │ 0.529881 │ Moderada correlación │\n", + "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", + "│ density │ alcohol │ -0.780138 │ Alta correlación │\n", + "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", + "│ pH │ fixed acidity │ -0.425858 │ Moderada correlación │\n", + "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", + "│ alcohol │ residual sugar │ -0.450631 │ Moderada correlación │\n", + "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", + "│ alcohol │ chlorides │ -0.360189 │ Moderada correlación │\n", + "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", + "│ alcohol │ total sulfur dioxide │ -0.448892 │ Moderada correlación │\n", + "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", + "│ alcohol │ density │ -0.780138 │ Alta correlación │\n", + "╘══════════════════════╧══════════════════════╧═══════════════╧══════════════════════╛\n" + ] + } + ], + "source": [ + "classification = []\n", + "\n", + "for attribute in x_correlation_matrix.columns:\n", + " for other_attribute, correlation in x_correlation_matrix[attribute].items():\n", + " if attribute != other_attribute:\n", + " if abs(correlation)> 0.75:\n", + " classification.append((attribute, other_attribute, correlation, \"Alta correlación\"))\n", + " elif abs(correlation) >0.3:\n", + " classification.append((attribute, other_attribute, correlation, \"Moderada correlación\"))\n", + "\n", + "headers = [\"Atributo 1\", \"Atributo 2\", \"Correlación\", \"Clasificación\"]\n", + "table = tabulate(classification, headers=headers, tablefmt=\"fancy_grid\")\n", + "print(table)" + ] + }, + { + "cell_type": "markdown", + "id": "e23f6d25", + "metadata": {}, + "source": [ + "**Conclusión** : Se han identificado pares de variables con correlaciones altas. Una forma de abordar la multicolinealidad es eliminar una de las variables de cada par. Por ejemplo, \"residual sugar\" y \"density\" con una alta correlación. Sin embargo, antes de eliminar una variable, es importante entender la relevancia de cada variable en el contexto del problema. A veces, las variables correlacionadas pueden aportar información única y ser importantes para el modelo, para lo cual realizaremos un análisis de importancia de características o considera el conocimiento del dominio." + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "7553e929", + "metadata": {}, + "outputs": [], + "source": [ + "# Datos en conjuntos de entrenamiento y prueba (80% entrenamiento, 20% prueba)\n", + "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)" + ] + }, + { + "cell_type": "markdown", + "id": "64a07679", + "metadata": {}, + "source": [ + "2. 5 _Análisis de importancia de características_: " + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "fa07be18", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Feature: alcohol, Importance: 0.1132\n", + "Feature: density, Importance: 0.1064\n", + "Feature: volatile acidity, Importance: 0.1020\n", + "Feature: free sulfur dioxide, Importance: 0.0946\n", + "Feature: total sulfur dioxide, Importance: 0.0914\n", + "Feature: residual sugar, Importance: 0.0890\n", + "Feature: pH, Importance: 0.0846\n", + "Feature: chlorides, Importance: 0.0827\n", + "Feature: citric acid, Importance: 0.0808\n", + "Feature: sulphates, Importance: 0.0787\n", + "Feature: fixed acidity, Importance: 0.0766\n" + ] + } + ], + "source": [ + "# Crea un modelo Random Forest Classifier\n", + "clf = RandomForestClassifier(random_state=42)\n", + "\n", + "# Ajusta el modelo \n", + "clf.fit(X_train, y_train)\n", + "\n", + "# puntuaciones de importancia\n", + "importances = clf.feature_importances_\n", + "\n", + "# importancias con los nombres de las características\n", + "feature_importance = list(zip(X.columns, importances))\n", + "\n", + "# Ordena por su importancia\n", + "feature_importance = sorted(feature_importance, key=lambda x: x[1], reverse=True)\n", + "\n", + "#características y sus puntuaciones de importancia\n", + "for feature, importance in feature_importance:\n", + " print(f\"Feature: {feature}, Importance: {importance:.4f}\")" + ] + }, + { + "cell_type": "markdown", + "id": "4e868884", + "metadata": {}, + "source": [ + "**Conclusión**: \n", + "La importancia de las características te indica qué tan influyentes son las características en el proceso de clasificación. Cuanto mayor sea la importancia, más influencia tiene la característica en el modelo de clasificación : \n", + "\n", + "- **Alcohol** es la característica más importante, con una importancia de aproximadamente 0.1132. Se concluye que alcohol es la característica más influyente en la clasificación.\n", + "- **Density** es la segunda característica más importante, con una importancia de aproximadamente 0.1064.\n", + "- **Volatile acidity** es la tercera característica más importante, con una importancia de aproximadamente 0.1020." + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "f212ceec", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Árbol de Decisión: Accuracy = 0.61\n", + "Random Forest: Accuracy = 0.69\n", + "SVM: Accuracy = 0.56\n", + "K-NN: Accuracy = 0.54\n", + "El mejor modelo es: Random Forest\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/home/johannadiazaguirre/anaconda3/lib/python3.9/site-packages/sklearn/neighbors/_classification.py:211: FutureWarning: Unlike other reduction functions (e.g. `skew`, `kurtosis`), the default behavior of `mode` typically preserves the axis it acts along. In SciPy 1.11.0, this behavior will change: the default value of `keepdims` will become False, the `axis` over which the statistic is taken will be eliminated, and the value None will no longer be accepted. Set `keepdims` to True or False to avoid this warning.\n", + " mode, _ = stats.mode(_y[neigh_ind, k], axis=1)\n" + ] + } + ], + "source": [ + "# Escalar características \n", + "scaler = StandardScaler()\n", + "X_train = scaler.fit_transform(X_train)\n", + "X_test = scaler.transform(X_test)\n", + "\n", + "# Modelos (excluyendo MultinomialNB)\n", + "models = [\n", + " (\"Árbol de Decisión\", DecisionTreeClassifier()),\n", + " (\"Random Forest\", RandomForestClassifier()),\n", + " (\"SVM\", SVC()),\n", + " (\"K-NN\", KNeighborsClassifier())\n", + "]\n", + "\n", + "# Entrenar y evaluar modelos\n", + "results = {}\n", + "\n", + "for model_name, model in models:\n", + " model.fit(X_train, y_train)\n", + " y_pred = model.predict(X_test)\n", + " accuracy = accuracy_score(y_test, y_pred)\n", + " results[model_name] = accuracy\n", + "\n", + "# Imprimir resultados\n", + "for model_name, accuracy in results.items():\n", + " print(f\"{model_name}: Accuracy = {accuracy:.2f}\")\n", + " \n", + "best_model_name = max(results, key=results.get)\n", + "print(f\"El mejor modelo es: {best_model_name}\")\n" + ] + }, + { + "cell_type": "markdown", + "id": "f7072776", + "metadata": {}, + "source": [ + "_Conclusión_ : \n", + "\n", + "- **Modelo: Regresión Logística**\n", + "\n", + "Precisión: 54.34% con una desviación estándar de 1.38%\n", + "La Regresión Logística ha obtenido una precisión del 54.34% en la clasificación de la calidad del vino. Esto significa que el modelo acertó en su predicción de la calidad del vino en aproximadamente el 54.34% de los casos. Sin embargo, la desviación estándar del 1.38% indica que el rendimiento del modelo puede variar en alrededor de 1.38%. En otras palabras, el modelo no es muy consistente en sus predicciones y podría no ser el más adecuado para este problema.\n", + "\n", + "- **Modelo: Árbol de Decisión**\n", + "\n", + "Precisión: 57.96% con una desviación estándar de 1.80%\n", + "El modelo de Árbol de Decisión ha logrado una precisión del 57.96% en la clasificación de la calidad del vino. Esto representa un rendimiento ligeramente mejor que el de la Regresión Logística. La desviación estándar de 1.80% muestra que el modelo puede tener una variabilidad de aproximadamente 1.80% en su rendimiento, lo que es un poco más consistente en comparación con la Regresión Logística.\n", + "\n", + "- **Modelo: Random Forest**\n", + "\n", + "Precisión: 66.03% con una desviación estándar de 2.44%\n", + "El modelo Random Forest ha obtenido la mayor precisión, con un 66.03%, lo que significa que es capaz de predecir con mayor precisión la calidad del vino en comparación con los otros modelos. La desviación estándar de 2.44% indica que el modelo puede variar en aproximadamente un 2.44% en su rendimiento, lo que sugiere una mayor consistencia que los otros modelos.\n", + "\n", + "En resumen, el modelo Random Forest ha demostrado ser el más eficaz en la clasificación de la calidad del vino, con una precisión más alta en comparación con la Regresión Logística y el Árbol de Decisión. Sin embargo, es importante recordar que la elección del modelo no se basa únicamente en la precisión; otros factores como la interpretabilidad del modelo, el tiempo de entrenamiento y la complejidad también deben ser considerados en la toma de decisiones." + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "ef23761d", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Precisión en el conjunto de prueba: 0.69\n", + "Informe de Clasificación:\n", + " precision recall f1-score support\n", + "\n", + " 3 1.00 0.00 0.00 5\n", + " 4 0.56 0.20 0.29 25\n", + " 5 0.70 0.70 0.70 291\n", + " 6 0.66 0.79 0.72 432\n", + " 7 0.76 0.58 0.66 192\n", + " 8 0.80 0.46 0.58 35\n", + "\n", + " accuracy 0.69 980\n", + " macro avg 0.75 0.45 0.49 980\n", + "weighted avg 0.70 0.69 0.68 980\n", + "\n" + ] + } + ], + "source": [ + "from sklearn.metrics import accuracy_score, classification_report, confusion_matrix\n", + "from sklearn.preprocessing import StandardScaler\n", + "from sklearn.ensemble import RandomForestClassifier\n", + "\n", + "# Crear una instancia de StandardScaler\n", + "scaler = StandardScaler()\n", + "\n", + "# Ajustar y transformar los datos de entrenamiento\n", + "X_train_scaled = scaler.fit_transform(X_train)\n", + "\n", + "# Transformar los datos de prueba utilizando el mismo escalador\n", + "X_test_scaled = scaler.transform(X_test)\n", + "\n", + "# Random Forest\n", + "best_model = RandomForestClassifier(random_state=42)\n", + "\n", + "best_model.fit(X_train_scaled, y_train)\n", + "\n", + "# predicciones\n", + "y_pred = best_model.predict(X_test_scaled)\n", + "\n", + "# Calcular la precisión\n", + "accuracy = accuracy_score(y_test, y_pred)\n", + "print(f\"Precisión en el conjunto de prueba: {accuracy:.2f}\")\n", + "\n", + "report = classification_report(y_test, y_pred, zero_division=1)\n", + "\n", + "print(\"Informe de Clasificación:\")\n", + "print(report)\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "id": "5a5ee4da", + "metadata": {}, + "source": [ + "_**Conclusión**_: \n", + "\n", + "- **Precisión en el conjunto de prueba: 0.69**\n", + " - Esto indica que el modelo ha obtenido una precisión general del 69% en el conjunto de prueba. En otras palabras, el 69% de las predicciones del modelo coincidieron con las etiquetas reales.\n", + "\n", + "- **Informe de Clasificación:**\n", + " - El informe de clasificación se divide en varias métricas de rendimiento para cada clase de calidad del vino (3, 4, 5, 6, 7, 8).\n", + " - **Precision (Precisión):** Representa la proporción de verdaderos positivos (muestras correctamente clasificadas) respecto al total de predicciones positivas. Por ejemplo, para la calidad del vino \"3\", la precisión es 1.00, lo que significa que todas las predicciones positivas para esta clase fueron correctas.\n", + " - **Recall (Recuperación o Sensibilidad):** Representa la proporción de verdaderos positivos respecto al total de muestras reales de la clase. Para la calidad del vino \"3\", el recall es 0.00, lo que indica que muy pocas muestras reales de esta clase se identificaron correctamente.\n", + " - **F1-Score:** Es una medida que combina precision y recall. Un puntaje más alto indica un mejor equilibrio entre precision y recall. Para la calidad del vino \"5\", el F1-score es 0.70, lo que sugiere un buen equilibrio entre precisión y recall.\n", + " - **Support:** Indica el número de muestras en cada clase.\n", + "\n", + "- **Accuracy (Exactitud):** Representa la proporción de predicciones correctas en el conjunto de prueba. En este caso, la exactitud general es del 69%, lo que significa que el 69% de las predicciones del modelo son correctas.\n", + "\n", + "- **Macro Avg (Promedio Macro):** Es el promedio de las métricas de precisión, recall y F1-score para todas las clases. En este caso, el promedio macro indica que, en promedio, las métricas son moderadas en su conjunto.\n", + "\n", + "- **Weighted Avg (Promedio Ponderado):** Es similar al promedio macro, pero tiene en cuenta el desequilibrio en el número de muestras en cada clase. En este caso, el promedio ponderado muestra una precisión global del 69%, ponderada por el número de muestras en cada clase." + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "f2c263a1", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
    " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "\n", + "plt.figure(figsize=(8, 6))\n", + "\n", + "plt.scatter(y_test, y_test, alpha=0.5, color='blue', label='Valores Reales (y_test)', marker='o', s=50)\n", + "plt.scatter(y_test, y_pred, alpha=0.5, color='green', label='Predicciones (y_pred)', marker='^', s=50)\n", + "\n", + "plt.xlabel('Calidad del Vino')\n", + "plt.ylabel('Calidad del Vino')\n", + "plt.title('Comparación entre Valores Reales y Predicciones')\n", + "plt.grid(True)\n", + "plt.legend()\n", + "\n", + "plt.plot([2, 9], [2, 9], color='gray', linestyle='--', label='Igualdad Perfecta')\n", + "plt.legend()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "0b17b83e", + "metadata": {}, + "source": [ + "_Conclusión_:\n", + "El gráfico que representa los valores reales (y_test) en azul (círculos) y las predicciones (y_pred) en verde (triángulos) proporciona una forma visual de comparar cómo se relacionan las predicciones del modelo con los valores reales.\n", + "\n", + "- **Igualdad perfecta**: Los valores reales que caen exactamente en la línea diagonal (donde x=y) representan predicciones perfectas, lo que significa que el modelo predijo la calidad del vino de manera precisa.\n", + "\n", + "- **Desviación positiva**: Los puntos verdes que están por encima de la línea diagonal indican que el modelo sobreestimó la calidad del vino en esas muestras.\n", + "\n", + "- **Desviación negativa**: Los puntos verdes que están por debajo de la línea diagonal indican que el modelo subestimó la calidad del vino en esas muestras.\n", + "\n", + "- **Distribución de errores**: La dispersión de puntos alrededor de la línea diagonal muestra cómo se distribuyen los errores del modelo. Una distribución estrecha y centrada en la línea diagonal indica predicciones precisas, mientras que una dispersión más amplia indica un mayor margen de error.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "fd13b57b", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
    " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "\n", + "y_classes, class_counts = np.unique(y, return_counts=True)\n", + "\n", + "plt.bar(y_classes, class_counts)\n", + "plt.xlabel('Clases de Calidad del Vino')\n", + "plt.ylabel('Número de Muestras')\n", + "plt.title('Distribución de Clases en Wine Quality Dataset')\n", + "plt.xticks(y_classes)\n", + "plt.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "1577a5c4", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Clase 3: 20 instancias\n", + "Clase 4: 163 instancias\n", + "Clase 5: 1457 instancias\n", + "Clase 6: 2198 instancias\n", + "Clase 7: 880 instancias\n", + "Clase 8: 175 instancias\n", + "Clase 9: 5 instancias\n" + ] + } + ], + "source": [ + "y_classes, class_counts = np.unique(y, return_counts=True)\n", + "\n", + "for y_class, count in zip(y_classes, class_counts):\n", + " print(f'Clase {y_class}: {count} instancias')" + ] + }, + { + "cell_type": "markdown", + "id": "1daefcf9", + "metadata": {}, + "source": [ + "### **Resultados Preliminares del Modelo:**\n", + "- El modelo ha obtenido una precisión global del 69% en el conjunto de prueba, lo que significa que el 69% de las predicciones coincidieron con las etiquetas reales.\n", + "- El informe de clasificación proporciona métricas detalladas para cada clase de calidad del vino. Aquí se observan algunas tendencias notables:\n", + " - El modelo tiene un alto recall (sensibilidad) para las clases de calidad \"5\" y \"6\", lo que indica que es bueno para identificar esas clases.\n", + " - Sin embargo, el modelo tiene un bajo recall para las clases de calidad \"3\", \"4\", \"7\", \"8\" y \"9\", lo que sugiere que tiene dificultades para identificar estas clases.\n", + " - El modelo tiene una alta precisión en las clases \"3\", \"5\", \"7\" y \"8\", lo que indica que las predicciones positivas para estas clases son en su mayoría correctas.\n", + " - El modelo tiene una baja precisión en las clases \"4\" y \"9\", lo que sugiere que muchas de las predicciones positivas para estas clases son incorrectas.\n", + "- Las métricas F1-score y el promedio ponderado muestran el equilibrio entre precisión y recall en general, y el promedio ponderado tiene un valor del 68%, lo que refleja la eficacia general del modelo en el conjunto de datos desequilibrado.\n" + ] + }, + { + "cell_type": "markdown", + "id": "3cf23a60", + "metadata": {}, + "source": [ + "### **_Conclusiones preliminares_** : \n", + "\n", + "1. **Clases Mayoritarias:** Debido al desequilibrio de clases, el modelo tiene una cantidad mucho mayor de ejemplos de las clases \"5\" y \"6\" en comparación con otras clases. Esto hace que el modelo tenga más información sobre estas clases, por lo que puede ser más preciso al predecirlas. Esto se refleja en los altos valores de precisión y recall para las clases \"5\" y \"6\".\n", + "\n", + "2. **Clases Minoritarias:** Por otro lado, las clases minoritarias, como \"3\", \"4\", \"7\", \"8\" y \"9\", tienen menos ejemplos en el conjunto de datos. Esto hace que el modelo tenga menos información para aprender y predecir estas clases, lo que se traduce en valores más bajos de precisión y recall para estas clases.\n", + "\n", + "3. **Impacto en el Promedio Ponderado:** El promedio ponderado de todas las métricas se ve influenciado por el desequilibrio de clases. Dado que las clases \"5\" y \"6\" tienen muchas más muestras que las clases minoritarias, su impacto es mayor en el promedio ponderado. Esto significa que el rendimiento del modelo en las clases minoritarias puede no reflejarse tan claramente en el promedio ponderado.\n", + "\n", + "4. **Contexto del Problema:** En algunos casos, el desequilibrio de clases puede ser natural en un problema de clasificación. Por ejemplo, en el caso del vino, es más común encontrar vinos de calidad \"5\" y \"6\" que de calidad \"3\" o \"9\".\n" + ] + }, + { + "cell_type": "markdown", + "id": "c6ae325b", + "metadata": {}, + "source": [ + "### Estrategias para mejora el modelo:\n", + "\n", + "- Dado el desequilibrio de clases, podrías considerar estrategias de manejo de desequilibrio, como oversampling o undersampling de clases minoritarias, para mejorar el rendimiento del modelo en las clases desequilibradas.\n", + "- La ingeniería de características y la búsqueda de hiperparámetros podrían ayudar a mejorar aún más el rendimiento del modelo.\n", + "- Podrías evaluar otros modelos de clasificación y ajustar sus hiperparámetros para determinar si hay un modelo más adecuado para este conjunto de datos específico.\n", + "- Un análisis de residuos podría ayudarte a entender mejor las predicciones erróneas del modelo y cómo se pueden abordar.\n", + "\n", + "La estrategia más útil sería el oversampling de las clases minoritarias. Dado que las clases \"3\", \"4\", \"7\", \"8\" y \"9\" tienen menos instancias que las clases mayoritarias, aumentar el número de muestras en estas clases puede ayudar al modelo a aprender de manera más equitativa y mejorar su rendimiento en las clases desequilibradas." + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "id": "4b8a0466", + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "from imblearn.over_sampling import RandomOverSampler\n", + "\n", + "# instancia del resampler\n", + "oversampler = RandomOverSampler(random_state=42)\n", + "\n", + "# Aplica el resampling \n", + "X_train_resampled, y_train_resampled = oversampler.fit_resample(X_train, y_train)\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "id": "8dbd38e7", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Precisión en el conjunto de prueba: 0.92\n", + "Informe de Clasificación:\n", + " precision recall f1-score support\n", + "\n", + " 3 1.00 1.00 1.00 363\n", + " 4 0.99 1.00 1.00 338\n", + " 5 0.78 0.88 0.83 346\n", + " 6 0.81 0.66 0.73 375\n", + " 7 0.89 0.94 0.91 383\n", + " 8 0.99 1.00 1.00 332\n", + " 9 0.99 1.00 1.00 336\n", + "\n", + " accuracy 0.92 2473\n", + " macro avg 0.92 0.93 0.92 2473\n", + "weighted avg 0.92 0.92 0.92 2473\n", + "\n" + ] + } + ], + "source": [ + "X_train_balanced, X_test, y_train_balanced, y_test = train_test_split(X_train_resampled, y_train_resampled, test_size=0.2, random_state=42)\n", + "\n", + "model = RandomForestClassifier(random_state=42)\n", + "model.fit(X_train_balanced, y_train_balanced)\n", + "\n", + "y_pred_balanced = model.predict(X_test)\n", + "\n", + "accuracy = accuracy_score(y_test, y_pred_balanced)\n", + "print(f'Precisión en el conjunto de prueba: {accuracy:.2f}')\n", + "\n", + "report = classification_report(y_test, y_pred_balanced)\n", + "print('Informe de Clasificación:')\n", + "print(report)\n" + ] + }, + { + "cell_type": "code", + "execution_count": 25, + "id": "f72c45f7", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
    " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(8, 6))\n", + "\n", + "plt.scatter(y_test, y_test, alpha=0.5, color='blue', label='Valores Reales (y_test)', marker='o', s=50)\n", + "plt.scatter(y_test, y_pred_balanced, alpha=0.5, color='green', label='Predicciones (y_pred)', marker='^', s=50)\n", + "\n", + "plt.xlabel('Calidad del Vino')\n", + "plt.ylabel('Calidad del Vino')\n", + "plt.title('Comparación entre Valores Reales y Predicciones')\n", + "plt.grid(True)\n", + "plt.legend()\n", + "\n", + "plt.plot([2, 9], [2, 9], color='gray', linestyle='--', label='Igualdad Perfecta')\n", + "plt.legend()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "cfc1528e", + "metadata": {}, + "source": [ + "## **Discución**\n", + "\n", + "En este estudio, se exploraron modelos de clasificación, incluyendo Árboles de Decisión, Random Forest, SVM y K-NN, aplicados al conjunto de datos de calidad de vino blanco de Wine Quality UCI. Los resultados revelaron que el desbalance de clases en el conjunto de datos impactó significativamente en la precisión de los modelos, con las clases mayoritarias teniendo un mejor rendimiento. La estrategia de oversampling se utilizó para abordar este desbalance, resultando en una mejora sustancial de la precisión del modelo Random Forest de 0.69 a 0.92 en el conjunto de prueba. Se seleccionaron estos modelos específicos debido a su capacidad para manejar datos multidimensionales y su disponibilidad en bibliotecas de aprendizaje automático comunes. Las diferencias metodológicas entre el enfoque propuesto y el estudio de referencia radican en las estrategias de preprocesamiento y la evaluación de modelos. Si bien ambos utilizan algoritmos similares, los enfoques metodológicos y los resultados varían debido a las estrategias adaptadas a las necesidades de cada estudio. Esta investigación destaca la importancia de abordar el desbalance de clases en conjuntos de datos y adaptar la metodología a las características específicas del problema de clasificación.\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.16" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From 52378a05b52b0e7813f0430bfa1287d8f8af0113 Mon Sep 17 00:00:00 2001 From: Cjohanna Date: Sat, 28 Oct 2023 14:45:02 -0500 Subject: [PATCH 6/7] add new page article and date Colab --- .../WineQuality.ipynb | 0 _posts/.html | 62 ++++++++++++++++ _posts/2023-04-3-Bioinformatics.html | 70 ++++++++++++++++++ _posts/2023-04-3-Energy Efficiency.html | 34 +++++++-- _posts/2023-06-28-WIne Quality.html | 6 +- about.html | 2 + img/posts/07.avif | Bin 0 -> 63261 bytes 7 files changed, 163 insertions(+), 11 deletions(-) rename WineQuality.ipynb => DataSet/WineQuality.ipynb (100%) create mode 100644 _posts/.html create mode 100644 _posts/2023-04-3-Bioinformatics.html create mode 100644 img/posts/07.avif diff --git a/WineQuality.ipynb b/DataSet/WineQuality.ipynb similarity index 100% rename from WineQuality.ipynb rename to DataSet/WineQuality.ipynb diff --git a/_posts/.html b/_posts/.html new file mode 100644 index 0000000000..258dc4a308 --- /dev/null +++ b/_posts/.html @@ -0,0 +1,62 @@ +--- +layout: post +title: "Wine Quality Predictor" +subtitle: "Exploring wine quality through analysis and prediction" +date: 2023-06-28 23:45:13 -0400 +background: '/img/posts/03.jpg' +--- + +

    This project aims to apply Machine Learning techniques to develop predictive models that can predict the quality of wine based on its physicochemical attributes. To achieve this, visualization and exploratory analysis techniques will be explored to understand the distribution of the attributes and their impact on prediction. Additionally, the crucial role of data preprocessing and transformation in the modeling phase will be highlighted.

    + +

    Description of Dataset

    + +

    Source: This dataset was created by P. Cortez, A. Cerdeira, F. Almeida, T. Matos, and J. Reis. The "Wine Quality" dataset is available in the UCI Machine Learning Repository.

    + +

    The "Wine Quality" dataset is commonly used in classification and regression problems to predict wine quality. It was collected to evaluate the quality of white and red wines based on physicochemical attributes. The inputs were gathered through physicochemical tests, and the output is based on sensory data obtained from evaluations conducted by wine experts. Each expert rated the wine quality on a scale from 0 (very poor) to 10 (excellent).

    + +

    Attribute Description:The "Wine Quality" dataset consists of instances of white and red wines, with a total of 11 numerical attributes. These attributes include characteristics such as acidity, sugar levels, sulfates, and alcohol content. The wine quality is represented by a categorical target variable.

    + +
    Input Attributes (x):
    +
      +
    • Fixed acidity (Acidez fija): g/dm³ (float)
    • +
    • Volatile acidity (Acidez volátil): g/dm³ (float)
    • +
    • Citric acid (Ácido cítrico): g/dm³ (float)
    • +
    • Residual sugar (Azúcar residual): g/dm³ (float)
    • +
    • Chlorides (Cloruros): g/dm³ (float)
    • +
    • Free sulfur dioxide (Dióxido de azufre libre): mg/dm³ (float)
    • +
    • Total sulfur dioxide (Dióxido de azufre total): mg/dm³ (float)
    • +
    • Density (Densidad): g/cm³ (float)
    • +
    • pH: (float)
    • +
    • Sulphates (Sulfatos): g/dm³ (float)
    • +
    • Alcohol (Alcohol): % vol (float)
    • +
    + +
    Output Attributes(y):
    +
      +
    • Wine Quality: It is evaluated on a discrete scale of 0 to 10, where a higher value indicates better quality
    • +
    +

    Exploratory Data Analysis

    +Demo Image +

    Before diving into the predictive modeling, an initial step is to perform an Exploratory Data Analysis (EDA). For this purpose, you can load the dataset into your working environment, such as Python with Pandas, and execute the following tasks:

    + +

    This repository contains the results of a comprehensive analysis of a white wine dataset provided by the reference researchers. The analysis involved three key stages: data preprocessing, modeling and evaluation, and performance improvement strategies.

    + +

    Data Preprocessing

    +

    In the data preprocessing phase, we applied essential techniques, such as feature scaling using StandardScaler. This ensured that all features contributed equally to the modeling process, thus avoiding the dominance of certain attributes over others.

    + +

    Modeling

    +

    In the modeling stage, we deliberately selected four specific algorithms: Decision Tree, Random Forest, SVM, and K-NN. The choice of these algorithms was based on their demonstrated ability to address classification problems in complex datasets. It is important to note that, although some algorithms were shared with the reference study, the methodologies differed in aspects such as hyperparameter tuning and how class imbalance was addressed.

    + +

    Evaluation

    +

    The reference study provided results that served as a starting point for model evaluation. It was observed that, despite achieving acceptable levels of accuracy, class imbalance affected the model's ability to generalize to minority classes. This finding was crucial in determining the need to implement an oversampling strategy.

    + +

    Performance Improvement

    +

    The oversampling strategy was the key element in significantly improving the model's performance. By increasing the number of instances in the minority classes, the class distribution was balanced, allowing the model to learn more effectively from all classes. This resulted in a noticeable increase in accuracy on the test set, reaching an impressive 92%.

    + +

    Conclusion

    +

    While both methodologies shared the use of some common algorithms, they differed in their approach to addressing class imbalance and the specific model configurations. This distinction is fundamental and highlights the importance of adapting methodologies to the unique characteristics of each dataset and problem.

    + +

    For more details, refer to the complete analysis and code in this repository.

    + Open in Google Colab + +

    Photographs by Unsplash.

    diff --git a/_posts/2023-04-3-Bioinformatics.html b/_posts/2023-04-3-Bioinformatics.html new file mode 100644 index 0000000000..1a5ec49aad --- /dev/null +++ b/_posts/2023-04-3-Bioinformatics.html @@ -0,0 +1,70 @@ +--- +layout: post +title: "Bioinformatics: high-throughput methods" +subtitle: "High-throughput pharmacological screening consists of testing large collections of chemical compounds or natural products to identify biologically active molecules." +date: 2023-04-3 10:45:13 -0400 +background: '/img/posts/07.avif' +--- + +

    Executive Summary

    +

    Abstract

    +

    Dengue is an acute febrile illness caused by the Dengue virus (DENV), with a high number of cases worldwide. There is no available treatment that directly affects the virus or the viral cycle. The objective of this study was to identify a compound derived from natural products that interacts with the NS5 protein of the dengue virus through virtual screening and evaluate its in vitro antiviral effect on DENV-2.

    + +

    Methods

    +

    + Molecular Docking: Molecular docking was performed on NS5 using AutoDock Vina software to identify potential compounds that could interact with the NS5 protein. +

    +

    + Selection of Compounds: Compounds with physicochemical and pharmacological properties of interest were selected based on the results of molecular docking. +

    +

    + Antiviral Effect Evaluation: The preliminary antiviral effect was evaluated through several methods: +

    +
      +
    • + NS1 Protein Expression: The effect on viral replication was assessed by measuring the expression of the NS1 protein. +
    • +
    • + NS5 Production: The effect on viral genome replication and/or translation was determined by measuring NS5 production using DENV-2 Huh-7 replicon through ELISA. +
    • +
    • + Viral RNA Quantification: Viral RNA quantification was performed using RT-qPCR to assess the impact on viral genome replication. +
    • +
    + +

    Results

    +

    The in silico strategy proved effective in finding a compound (M78) with an indole-like structure.

    +

    + Antiviral Effect: Treatment with M78 at 50 µM reduced the expression of the NS5 protein by 70% and decreased viral RNA by 1.7 times, suggesting that M78 is involved in the replication and/or translation of the viral genome. +

    + +

    Bioinformatics: In Silico Assays

    +Demo Image +

    Virtual Screening of Natural Compound Derivatives on DENV NS5 Protein

    +

    As part of my data science experience, I conducted virtual screening of natural compound derivatives on the DENV NS5 protein. The objective of this study was to identify compounds that could interact with the NS5 protein, a key component of the Dengue virus. This research utilized cutting-edge in silico techniques to identify potential antiviral compounds.

    + +

    The virtual screening involved:

    +
      +
    • Obtaining the structures of NS5 proteins from the four DENV serotypes.
    • +
    • Selecting cavities for interaction, such as the substrate binding site and RNA tunnel.
    • +
    • Re-docking ligands SAH and 68E to obtain binding energy values.
    • +
    • Performing eight virtual screenings, two for each serotype.
    • +
    • Utilizing a library of 190,090 natural compound derivatives available on the DrugDiscovery@TACC web portal.
    • +
    • Employing AutoDock Vina 1.1 software for virtual screening calculations.
    • +
    + +

    Selection of Compounds by Interaction on NS5 of DENV

    +

    After the virtual screening, the selection of compounds was a crucial step. Compounds were chosen based on their ability to bind to NS5 in all four serotypes of the Dengue virus. The selection process involved the following criteria:

    + +
      +
    • Assessing aqueous solubility using the SwissADME web server.
    • +
    • Checking compliance with Lipinski's rules to evaluate drug-likeness.
    • +
    • Predicting possible toxicological risks using the ProTox-II web server.
    • +
    • 3D visualization of protein-ligand complexes using the Chimera v1.13.1 program.
    • +
    +

    This experience showcases the use of advanced in silico tools and computational methods to identify potential antiviral compounds, emphasizing the importance of data science in drug discovery and research.

    + +

    For more details, refer to the complete analysis and code in this repository.

    +Open in MPDI + +

    Photographs by Unsplash.

    \ No newline at end of file diff --git a/_posts/2023-04-3-Energy Efficiency.html b/_posts/2023-04-3-Energy Efficiency.html index 089630ecd4..1aeffc2d5d 100644 --- a/_posts/2023-04-3-Energy Efficiency.html +++ b/_posts/2023-04-3-Energy Efficiency.html @@ -37,13 +37,31 @@

    Description of Dataset

    Exploratory Data Analysis

    Demo Image -

    Before diving into the predictive modeling, an initial step is to perform an Exploratory Data Analysis (EDA). For this purpose, you can load the dataset into your working environment, such as Python with Pandas, and execute the following tasks:

    -
      -
    1. Descriptive Statistics: Calculate summary statistics, including mean, median, standard deviation, and percentiles for each feature.
    2. -
    3. Graphs: Create visual representations like histograms, box plots, and scatter plots to visualize the distributions and relationships among the features.
    4. -
    5. Correlations: Compute correlations between the features and wine quality to identify potential relationships.
    6. -
    7. Data Cleaning: Perform data cleaning as necessary, which may involve handling outliers or imputing missing values.
    8. -
    9. Quality Analysis: Examine the distribution of wine quality and search for patterns based on chemical characteristics.
    10. -
    + +

    Methodology and Modeling

    +

    A methodology consisting of two phases was implemented: modeling and evaluation. During the modeling phase, several regression models were trained, including Linear Regression, Theil-Sen Regressor, Random Forest Regressor, Support Vector Regressor (SVR), and Decision Tree Regressor. These models were trained independently to predict both heating load and cooling load.

    + +

    Modeling Results

    +

    In the modeling phase, notable trends in model performance for both variables were observed:

    + +
      +
    • For heating load prediction, the Random Forest Regressor model exhibited outstanding performance, with a Mean Squared Error (MSE) close to zero and an R-squared (R2) almost equal to 1. This indicates a nearly perfect fit to the training data, although overfitting is a possibility. The Linear Regression, Theil-Sen Regressor, and SVR models also showed good performance, though slightly behind the Random Forest model.
    • +
    • Regarding cooling load prediction, similar patterns were observed. The Random Forest Regressor model excelled with very low MSE and an R2 close to 1. The other models also demonstrated good performance, but not as remarkable as the Random Forest model.
    • +
    + +

    Evaluation Results

    +

    In the evaluation phase, the trends observed in the modeling phase were confirmed:

    + +
      +
    • For heating load prediction, the Random Forest Regressor model continued to exhibit exceptional performance, with low MSE and high R2. The Decision Tree Regressor model also showed good performance in the evaluation phase.
    • +
    • For cooling load prediction, a similar pattern was observed, with the Random Forest Regressor model remaining the leader, followed by the Decision Tree Regressor model.
    • +
    + +

    Conclusions and Recommendations

    +

    Based on the results obtained, it can be concluded that the Random Forest Regressor model is the most promising for this specific dataset. However, it is important to remember that results may vary in different datasets, so cross-validation is recommended, and model hyperparameters should be adjusted for more robust results.

    + +

    Furthermore, it is suggested to explore other feature engineering techniques and consider the inclusion of more predictor variables to further enhance model performance. This project provides a solid foundation for energy load prediction in heating and cooling systems and can be scaled and adapted for future applications in energy efficiency in buildings.

    +

    For more details, refer to the complete analysis and code in this repository.

    +Open in Google Colab

    Photographs by Unsplash.

    \ No newline at end of file diff --git a/_posts/2023-06-28-WIne Quality.html b/_posts/2023-06-28-WIne Quality.html index c58a8953ad..258dc4a308 100644 --- a/_posts/2023-06-28-WIne Quality.html +++ b/_posts/2023-06-28-WIne Quality.html @@ -56,7 +56,7 @@

    Exploratory Data Analysis

    Conclusion

    While both methodologies shared the use of some common algorithms, they differed in their approach to addressing class imbalance and the specific model configurations. This distinction is fundamental and highlights the importance of adapting methodologies to the unique characteristics of each dataset and problem.

    -

    For more details, refer to the complete analysis and code in this repository.

    - - +

    For more details, refer to the complete analysis and code in this repository.

    + Open in Google Colab +

    Photographs by Unsplash.

    diff --git a/about.html b/about.html index a8db4d39d4..bf4a62184f 100644 --- a/about.html +++ b/about.html @@ -12,4 +12,6 @@ data analysis, machine learning, data mining, and optimization to tackle complex problems. Each project highlights my technical skills and my ability to solve real-world practical problems

    +

    For more details, refer to my CV in Canvas

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zdP}o7Ha*ZL$Pj(2m=M Date: Tue, 23 Jan 2024 15:20:32 -0500 Subject: [PATCH 7/7] Mensaje descriptivo del commit --- DataSet/WineQuality.ipynb | 3634 ++++++++++++++--------- _posts/2023-04-3-Energy Efficiency.html | 2 +- _posts/2023-06-28-WIne Quality.html | 2 +- about.html | 8 +- 4 files changed, 2206 insertions(+), 1440 deletions(-) diff --git a/DataSet/WineQuality.ipynb b/DataSet/WineQuality.ipynb index 460f3190f1..6fcd93948a 100644 --- a/DataSet/WineQuality.ipynb +++ b/DataSet/WineQuality.ipynb @@ -1,1467 +1,2237 @@ { - "cells": [ - { - "cell_type": "markdown", - "id": "a6cd2625", - "metadata": {}, - "source": [ - "# Wine Quality \n", - "#### Nombre del dataset : [Wine Quality del UCI Machine Learning Repository](https://archive.ics.uci.edu/dataset/186/wine+quality)\n", - "\n", - "\n", - "### Introducción\n", - "\n", - "Este proyecto se centra en el análisis exploratorio de datos (EDA) de un conjunto de datos de calidad del vino, que contiene información sobre vinos rojos y blancos.\n", - "\n", - "### Origen de los Datos\n", - "\n", - "Los datos utilizados en este análisis provienen del Repositorio de Aprendizaje Automático de la UCI (Universidad de California, Irvine). Fueron recopilados por P. Cortez, A. Cerdeira, F. Almeida, T. Matos y J. Reis en la Universidade de Minho, Portugal. Estos investigadores recopilaron información sobre diferentes propiedades químicas de vinos y la calidad percibida por catadores expertos.\n", - "\n", - "### Objetivo del Análisis\n", - "\n", - "El objetivo principal de este análisis es comprender en profundidad el conjunto de datos y extraer información valiosa que pueda ser útil para desarrollar modelos de aprendizaje automático para predecir la calidad del vino en función de sus propiedades químicas. Además de este objetivo central, existen otros objetivos más específicos, que incluyen:\n", - "\n", - "1. Identificar patrones y relaciones entre las características químicas y la calidad del vino.\n", - "2. Evaluar la distribución de la calidad del vino.\n", - "3. Realizar un análisis exploratorio para revelar insights y tendencias interesantes.\n", - "\n", - "#### Variables en el Conjunto de Datos\n", - "\n", - "El conjunto de datos se divide en dos archivos CSV: uno para vinos rojos y otro para vinos blancos. Cada archivo contiene las siguientes variables con sus respectivas unidades:\n", - "\n", - "#### Variables de Características Químicas (Entradas):\n", - "\n", - "1. `fixed acidity` (g/dm³): Acidez fija.\n", - "2. `volatile acidity` (g/dm³): Acidez volátil.\n", - "3. `citric acid` (g/dm³): Ácido cítrico.\n", - "4. `residual sugar` (g/dm³): Azúcar residual.\n", - "5. `chlorides` (g/dm³): Cloruros.\n", - "6. `free sulfur dioxide` (mg/dm³): Dióxido de azufre libre.\n", - "7. `total sulfur dioxide` (mg/dm³): Dióxido de azufre total.\n", - "8. `density` (g/cm³): Densidad.\n", - "9. `pH`: pH.\n", - "10. `sulphates` (g/dm³): Sulfatos.\n", - "11. `alcohol` (% vol): Contenido de alcohol.\n", - "\n", - "### Variable de Calidad (Objetivo):\n", - "\n", - "12. `quality`: Calidad del vino (puntuación de 0 a 10, donde 0 es de muy mala calidad y 10 es excelente de calidad).\n", - "\n", - "### Análisis Exploratorio de Datos - Conjunto de Datos de Calidad del Vino\n", - "\n", - "En las secciones siguientes de este notebook, realizaremos un análisis exhaustivo de estas variables y exploraremos relaciones, tendencias y patrones. Además, se llevarán a cabo visualizaciones gráficas para facilitar la comprensión de los datos." - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "id": "311bce01", - "metadata": {}, - "outputs": [], - "source": [ - "# Importación de librerías para tratamiento de datos\n", - "# ==============================================================================\n", - "import pandas as pd\n", - "import numpy as np\n", - "\n", - "# Importación de librerías para gráficos\n", - "# ==============================================================================\n", - "import matplotlib.pyplot as plt\n", - "from matplotlib import style\n", - "import seaborn as sns\n", - "import statsmodels.api as sm\n", - "from tabulate import tabulate\n", - "\n", - "# Importación de librerías para estadística descriptiva\n", - "# ==============================================================================\n", - "from scipy.stats import shapiro, kstest, anderson\n", - "from scipy.stats import describe\n", - "\n", - "# Importación de librerías para métricas y evaluación\n", - "# ==============================================================================\n", - "from sklearn.preprocessing import StandardScaler\n", - "from sklearn.model_selection import train_test_split\n", - "from sklearn.feature_selection import SelectFromModel\n", - "from sklearn.model_selection import KFold\n", - "from sklearn.model_selection import cross_val_score, cross_val_predict\n", - "from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score, classification_report\n", - "from sklearn.metrics import mean_absolute_error, mean_squared_error, r2_score\n", - "\n", - "# Importación de librerías para modelado\n", - "# ==============================================================================\n", - "from sklearn.tree import DecisionTreeClassifier\n", - "from sklearn.neighbors import KNeighborsClassifier\n", - "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n", - "from sklearn.naive_bayes import GaussianNB\n", - "from sklearn.ensemble import RandomForestClassifier\n", - "from sklearn.svm import SVC\n", - "from sklearn.svm import SVR" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "id": "3c4f1f25", - "metadata": {}, - "outputs": [], - "source": [ - " import pandas as pd\n", - "\n", - "# Nombres de las columnas (variables)\n", - "column_names = [\"fixed acidity\", \"volatile acidity\", \"citric acid\", \"residual sugar\", \"chlorides\",\n", - " \"free sulfur dioxide\", \"total sulfur dioxide\", \"density\", \"pH\", \"sulphates\", \"alcohol\", \"quality\"]\n", - "\n", - "# Datos de vinos rojos \n", - "red_wine_df = pd.read_csv(\"https://archive.ics.uci.edu/ml/machine-learning-databases/wine-quality/winequality-red.csv\", sep=\";\", names=column_names, header=0)\n", - "\n", - "# Datos de vinos blancos \n", - "white_wine_df = pd.read_csv(\"https://archive.ics.uci.edu/ml/machine-learning-databases/wine-quality/winequality-white.csv\", sep=\";\", names=column_names, header=0)\n" - ] - }, - { - "cell_type": "markdown", - "id": "49798165", - "metadata": {}, - "source": [ - "### Vinos Blancos (White Wine)\n", - "1. **Aspectos Generales**: " - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "003b9de3", - "metadata": {}, - "outputs": [], - "source": [ - "X = white_wine_df.drop(\"quality\", axis=1) \n", - "y = white_wine_df[\"quality\"] " - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "ce12f514", - "metadata": {}, - "outputs": [ + "cells": [ + { + "cell_type": "markdown", + "id": "a6cd2625", + "metadata": { + "id": "a6cd2625" + }, + "source": [ + "# Wine Quality\n", + "#### Nombre del dataset : [Wine Quality del UCI Machine Learning Repository](https://archive.ics.uci.edu/dataset/186/wine+quality)\n", + "\n", + "\n", + "### Introducción\n", + "\n", + "Este proyecto se centra en el análisis exploratorio de datos (EDA) de un conjunto de datos de calidad del vino, que contiene información sobre vinos rojos y blancos.\n", + "\n", + "### Origen de los Datos\n", + "\n", + "Los datos utilizados en este análisis provienen del Repositorio de Aprendizaje Automático de la UCI (Universidad de California, Irvine). Fueron recopilados por P. Cortez, A. Cerdeira, F. Almeida, T. Matos y J. Reis en la Universidade de Minho, Portugal. Estos investigadores recopilaron información sobre diferentes propiedades químicas de vinos y la calidad percibida por catadores expertos.\n", + "\n", + "### Objetivo del Análisis\n", + "\n", + "El objetivo principal de este análisis es comprender en profundidad el conjunto de datos y extraer información valiosa que pueda ser útil para desarrollar modelos de aprendizaje automático para predecir la calidad del vino en función de sus propiedades químicas. Además de este objetivo central, existen otros objetivos más específicos, que incluyen:\n", + "\n", + "1. Identificar patrones y relaciones entre las características químicas y la calidad del vino.\n", + "2. Evaluar la distribución de la calidad del vino.\n", + "3. Realizar un análisis exploratorio para revelar insights y tendencias interesantes.\n", + "\n", + "#### Variables en el Conjunto de Datos\n", + "\n", + "El conjunto de datos se divide en dos archivos CSV: uno para vinos rojos y otro para vinos blancos. Cada archivo contiene las siguientes variables con sus respectivas unidades:\n", + "\n", + "#### Variables de Características Químicas (Entradas):\n", + "\n", + "1. `fixed acidity` (g/dm³): Acidez fija.\n", + "2. `volatile acidity` (g/dm³): Acidez volátil.\n", + "3. `citric acid` (g/dm³): Ácido cítrico.\n", + "4. `residual sugar` (g/dm³): Azúcar residual.\n", + "5. `chlorides` (g/dm³): Cloruros.\n", + "6. `free sulfur dioxide` (mg/dm³): Dióxido de azufre libre.\n", + "7. `total sulfur dioxide` (mg/dm³): Dióxido de azufre total.\n", + "8. `density` (g/cm³): Densidad.\n", + "9. `pH`: pH.\n", + "10. `sulphates` (g/dm³): Sulfatos.\n", + "11. `alcohol` (% vol): Contenido de alcohol.\n", + "\n", + "### Variable de Calidad (Objetivo):\n", + "\n", + "12. `quality`: Calidad del vino (puntuación de 0 a 10, donde 0 es de muy mala calidad y 10 es excelente de calidad).\n", + "\n", + "### Análisis Exploratorio de Datos - Conjunto de Datos de Calidad del Vino\n", + "\n", + "En las secciones siguientes de este notebook, realizaremos un análisis exhaustivo de estas variables y exploraremos relaciones, tendencias y patrones. Además, se llevarán a cabo visualizaciones gráficas para facilitar la comprensión de los datos." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "311bce01", + "metadata": { + "id": "311bce01" + }, + "outputs": [], + "source": [ + "# Importación de librerías para tratamiento de datos\n", + "# ==============================================================================\n", + "import pandas as pd\n", + "import numpy as np\n", + "\n", + "# Importación de librerías para gráficos\n", + "# ==============================================================================\n", + "import matplotlib.pyplot as plt\n", + "from matplotlib import style\n", + "import seaborn as sns\n", + "import statsmodels.api as sm\n", + "from tabulate import tabulate\n", + "\n", + "# Importación de librerías para estadística descriptiva\n", + "# ==============================================================================\n", + "from scipy.stats import shapiro, kstest, anderson\n", + "from scipy.stats import describe\n", + "\n", + "# Importación de librerías para métricas y evaluación\n", + "# ==============================================================================\n", + "from sklearn.preprocessing import StandardScaler\n", + "from sklearn.model_selection import train_test_split\n", + "from sklearn.feature_selection import SelectFromModel\n", + "from sklearn.model_selection import KFold\n", + "from sklearn.model_selection import cross_val_score, cross_val_predict\n", + "from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score, classification_report\n", + "from sklearn.metrics import mean_absolute_error, mean_squared_error, r2_score\n", + "\n", + "# Importación de librerías para modelado\n", + "# ==============================================================================\n", + "from sklearn.tree import DecisionTreeClassifier\n", + "from sklearn.neighbors import KNeighborsClassifier\n", + "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n", + "from sklearn.naive_bayes import GaussianNB\n", + "from sklearn.ensemble import RandomForestClassifier\n", + "from sklearn.svm import SVC\n", + "from sklearn.svm import SVR" + ] + }, { - "data": { - "text/html": [ - "
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    " + "cell_type": "code", + "execution_count": 2, + "id": "3c4f1f25", + "metadata": { + "id": "3c4f1f25" + }, + "outputs": [], + "source": [ + "# Nombres de las columnas (variables)\n", + "column_names = [\"fixed acidity\", \"volatile acidity\", \"citric acid\", \"residual sugar\", \"chlorides\",\n", + " \"free sulfur dioxide\", \"total sulfur dioxide\", \"density\", \"pH\", \"sulphates\", \"alcohol\", \"quality\"]\n", + "\n", + "# Datos de vinos rojos\n", + "red_wine_df = pd.read_csv(\"https://archive.ics.uci.edu/ml/machine-learning-databases/wine-quality/winequality-red.csv\", sep=\";\", names=column_names, header=0)\n", + "\n", + "# Datos de vinos blancos\n", + "white_wine_df = pd.read_csv(\"https://archive.ics.uci.edu/ml/machine-learning-databases/wine-quality/winequality-white.csv\", sep=\";\", names=column_names, header=0)\n" + ] + }, + { + "cell_type": "markdown", + "id": "49798165", + "metadata": { + "id": "49798165" + }, + "source": [ + "### Vinos Blancos (White Wine)\n", + "1. **Aspectos Generales**:" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "003b9de3", + "metadata": { + "id": "003b9de3" + }, + "outputs": [], + "source": [ + "X = white_wine_df.drop(\"quality\", axis=1)\n", + "y = white_wine_df[\"quality\"]" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "ce12f514", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 458 + }, + "id": "ce12f514", + "outputId": "3e3134aa-db16-4c32-84e9-e156c0967833" + }, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + " fixed acidity volatile acidity citric acid residual sugar chlorides \\\n", + "0 7.0 0.27 0.36 20.7 0.045 \n", + "1 6.3 0.30 0.34 1.6 0.049 \n", + "2 8.1 0.28 0.40 6.9 0.050 \n", + "3 7.2 0.23 0.32 8.5 0.058 \n", + "4 7.2 0.23 0.32 8.5 0.058 \n", + "... ... ... ... ... ... \n", + "4893 6.2 0.21 0.29 1.6 0.039 \n", + "4894 6.6 0.32 0.36 8.0 0.047 \n", + "4895 6.5 0.24 0.19 1.2 0.041 \n", + "4896 5.5 0.29 0.30 1.1 0.022 \n", + "4897 6.0 0.21 0.38 0.8 0.020 \n", + "\n", + " free sulfur dioxide total sulfur dioxide density pH sulphates \\\n", + "0 45.0 170.0 1.00100 3.00 0.45 \n", + "1 14.0 132.0 0.99400 3.30 0.49 \n", + "2 30.0 97.0 0.99510 3.26 0.44 \n", + "3 47.0 186.0 0.99560 3.19 0.40 \n", + "4 47.0 186.0 0.99560 3.19 0.40 \n", + "... ... ... ... ... ... \n", + "4893 24.0 92.0 0.99114 3.27 0.50 \n", + "4894 57.0 168.0 0.99490 3.15 0.46 \n", + "4895 30.0 111.0 0.99254 2.99 0.46 \n", + "4896 20.0 110.0 0.98869 3.34 0.38 \n", + "4897 22.0 98.0 0.98941 3.26 0.32 \n", + "\n", + " alcohol quality \n", + "0 8.8 6 \n", + "1 9.5 6 \n", + "2 10.1 6 \n", + "3 9.9 6 \n", + "4 9.9 6 \n", + "... ... ... \n", + "4893 11.2 6 \n", + "4894 9.6 5 \n", + "4895 9.4 6 \n", + "4896 12.8 7 \n", + "4897 11.8 6 \n", + "\n", + "[4898 rows x 12 columns]" + ], + "text/html": [ + "\n", + "
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0.98869 3.34 0.38 \n", - "4897 22.0 98.0 0.98941 3.26 0.32 \n", - "\n", - " alcohol quality \n", - "0 8.8 6 \n", - "1 9.5 6 \n", - "2 10.1 6 \n", - "3 9.9 6 \n", - "4 9.9 6 \n", - "... ... ... \n", - "4893 11.2 6 \n", - "4894 9.6 5 \n", - "4895 9.4 6 \n", - "4896 12.8 7 \n", - "4897 11.8 6 \n", - "\n", - "[4898 rows x 12 columns]" + "source": [ + "#Visualización del dataframe\n", + "white_wine_df" ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#Visualización del dataframe\n", - "white_wine_df" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "ef49b39b", - "metadata": {}, - "outputs": [ + }, { - "data": { - "text/plain": [ - "(4898, 12)" + "cell_type": "code", + "execution_count": 5, + "id": "ef49b39b", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "ef49b39b", + "outputId": "f6557d20-a320-44c0-8656-982f43a1f10e" + }, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "(4898, 12)" + ] + }, + "metadata": {}, + "execution_count": 5 + } + ], + "source": [ + "#Forma del dataframe\n", + "white_wine_df.shape" ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#Forma del dataframe\n", - "white_wine_df.shape" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "46ed4c47", - "metadata": {}, - "outputs": [ + }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "Index(['fixed acidity', 'volatile acidity', 'citric acid', 'residual sugar',\n", - " 'chlorides', 'free sulfur dioxide', 'total sulfur dioxide', 'density',\n", - " 'pH', 'sulphates', 'alcohol', 'quality'],\n", - " dtype='object')\n" - ] - } - ], - "source": [ - "print(white_wine_df.columns)" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "9e7f9f80", - "metadata": {}, - "outputs": [ + "cell_type": "code", + "execution_count": 6, + "id": "46ed4c47", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "46ed4c47", + "outputId": "bd2f6961-6741-4758-a20a-fa6015408825" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Index(['fixed acidity', 'volatile acidity', 'citric acid', 'residual sugar',\n", + " 'chlorides', 'free sulfur dioxide', 'total sulfur dioxide', 'density',\n", + " 'pH', 'sulphates', 'alcohol', 'quality'],\n", + " dtype='object')\n" + ] + } + ], + "source": [ + "print(white_wine_df.columns)" + ] + }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "\n", - "RangeIndex: 4898 entries, 0 to 4897\n", - "Data columns (total 12 columns):\n", - " # Column Non-Null Count Dtype \n", - "--- ------ -------------- ----- \n", - " 0 fixed acidity 4898 non-null float64\n", - " 1 volatile acidity 4898 non-null float64\n", - " 2 citric acid 4898 non-null float64\n", - " 3 residual sugar 4898 non-null float64\n", - " 4 chlorides 4898 non-null float64\n", - " 5 free sulfur dioxide 4898 non-null float64\n", - " 6 total sulfur dioxide 4898 non-null float64\n", - " 7 density 4898 non-null float64\n", - " 8 pH 4898 non-null float64\n", - " 9 sulphates 4898 non-null float64\n", - " 10 alcohol 4898 non-null float64\n", - " 11 quality 4898 non-null int64 \n", - "dtypes: float64(11), int64(1)\n", - "memory usage: 459.3 KB\n" - ] - } - ], - "source": [ - "# Aspectos básicos del DataFrame\n", - "white_wine_df.info()" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "c22ae7e8", - "metadata": {}, - "outputs": [ + "cell_type": "code", + "execution_count": 7, + "id": "9e7f9f80", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "9e7f9f80", + "outputId": "96b8e1f7-eeb1-45c5-a79e-547a6d2ed709" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "\n", + "RangeIndex: 4898 entries, 0 to 4897\n", + "Data columns (total 12 columns):\n", + " # Column Non-Null Count Dtype \n", + "--- ------ -------------- ----- \n", + " 0 fixed acidity 4898 non-null float64\n", + " 1 volatile acidity 4898 non-null float64\n", + " 2 citric acid 4898 non-null float64\n", + " 3 residual sugar 4898 non-null float64\n", + " 4 chlorides 4898 non-null float64\n", + " 5 free sulfur dioxide 4898 non-null float64\n", + " 6 total sulfur dioxide 4898 non-null float64\n", + " 7 density 4898 non-null float64\n", + " 8 pH 4898 non-null float64\n", + " 9 sulphates 4898 non-null float64\n", + " 10 alcohol 4898 non-null float64\n", + " 11 quality 4898 non-null int64 \n", + "dtypes: float64(11), int64(1)\n", + "memory usage: 459.3 KB\n" + ] + } + ], + "source": [ + "# Aspectos básicos del DataFrame\n", + "white_wine_df.info()" + ] + }, { - "data": { - "text/plain": [ - "fixed acidity 0\n", - "volatile acidity 0\n", - "citric acid 0\n", - "residual sugar 0\n", - "chlorides 0\n", - "free sulfur dioxide 0\n", - "total sulfur dioxide 0\n", - "density 0\n", - "pH 0\n", - "sulphates 0\n", - "alcohol 0\n", - "quality 0\n", - "dtype: int64" + "cell_type": "code", + "execution_count": 8, + "id": "c22ae7e8", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "c22ae7e8", + "outputId": "b12f4c57-48df-42ab-bfd1-7305bb0bf4d4" + }, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "fixed acidity 0\n", + "volatile acidity 0\n", + "citric acid 0\n", + "residual sugar 0\n", + "chlorides 0\n", + "free sulfur dioxide 0\n", + "total sulfur dioxide 0\n", + "density 0\n", + "pH 0\n", + "sulphates 0\n", + "alcohol 0\n", + "quality 0\n", + "dtype: int64" + ] + }, + "metadata": {}, + "execution_count": 8 + } + ], + "source": [ + "#Examinando datos perdidos\n", + "white_wine_df.isna().sum()" ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#Examinando datos perdidos \n", - "white_wine_df.isna().sum()" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "b96c553f", - "metadata": {}, - "outputs": [ + }, { - "data": { - "image/png": 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\n", - "text/plain": [ - "
    " + "cell_type": "code", + "execution_count": 9, + "id": "b96c553f", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 472 + }, + "id": "b96c553f", + "outputId": "4b9ffa8f-a325-40f7-f0ae-6dca228f4b0d" + }, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
    " + ], + "image/png": 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\n" + }, + "metadata": {} + } + ], + "source": [ + "plt.hist(y, bins=10, edgecolor='k')\n", + "plt.xlabel('Calidad del Vino')\n", + "plt.ylabel('Frecuencia')\n", + "plt.title('Distribución de Calidad del Vino')\n", + "plt.show()" ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.hist(y, bins=10, edgecolor='k') \n", - "plt.xlabel('Calidad del Vino')\n", - "plt.ylabel('Frecuencia')\n", - "plt.title('Distribución de Calidad del Vino')\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "d316f8eb", - "metadata": {}, - "source": [ - "2. **Estadistica básica: Normalidad del conjuto de datos**: \n", - "\n", - " 2.1 _Histogramas_: Una forma visual preliminar de verificar la normalidad de tus datos es crear un histograma. Si la distribución se asemeja a una campana simétrica, en este caso más probable que siga una distribución normal, por la forma de campana. De igual manera vemos que tiene leves asimetrias, por lo cual vamos utilizar otros metodos para comprobar su distribución." - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "724ae45a", - "metadata": {}, - "outputs": [ + }, { - "data": { - "image/png": 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    " + "cell_type": "markdown", + "id": "d316f8eb", + "metadata": { + "id": "d316f8eb" + }, + "source": [ + "2. **Estadistica básica: Normalidad del conjuto de datos**:\n", + "\n", + " 2.1 Una forma visual preliminar de verificar la normalidad de tus datos es crear un **histograma**. Si la distribución se asemeja a una campana es simétrica, en este caso lo más probable es que siga una distribución normal, por la forma de campana. De igual manera vemos que tiene leves asimetrias, por lo cual vamos utilizar otros metodos para comprobar su distribución." ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "#Construcción de histogramas\n", - "import seaborn as sns\n", - "\n", - "fig, axes = plt.subplots(4, 3, figsize=(14, 14))\n", - "\n", - "for i, column in enumerate(column_names[:-1]):\n", - " row = i // 3 # Índice de fila\n", - " col = i % 3 # Índice de columna\n", - " sns.histplot(white_wine_df[column], kde=True, ax=axes[row, col], color= (list(plt.rcParams['axes.prop_cycle'])*2)[i][\"color\"])\n", - "\n", - "plt.tight_layout() \n", - "plt.show()\n" - ] - }, - { - "cell_type": "markdown", - "id": "e72636f5", - "metadata": {}, - "source": [ - " 2.2 _Pruebas de distribución normal_: \n", - " \n", - "Para evaluar si el conjunto de datos sigue una distribución normal, utilizaremos la prueba de Anderson-Darling. Esta prueba es más poderosa para detectar desviaciones de la normalidad en las colas largas de la distribución, como se hace evidente en los histogramas. Esto significa que puede identificar valores atípicos en las colas más eficazmente que la Prueba de Shapiro-Wilk. Además, la Prueba de Shapiro-Wilk funciona bien con tamaños de muestra generalmente menores a 2,000 observaciones, mientras que para el conjunto de datos del vino blanco, tenemos 4,898 entradas.\n", - "\n", - "Hipótesis nula (H0): Los datos siguen una distribución normal o gaussiana.\n", - "\n", - "Hipótesis alternativa (Ha): Los datos no siguen una distribución normal" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "742fb977", - "metadata": { - "scrolled": true - }, - "outputs": [ + }, { - "data": { - "text/html": [ - "
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OUlISCxcupLGxcdDrqqurWbBgAQkJCWRlZfHQQw/h8XiGOL2IiIiIiIicSkVbERGRYW7btm386le/YsaMGYOWP/jgg/z5z3/mxRdfZNOmTdTV1XHbbbcF13u9XhYsWEB/fz9btmzhueeeY/Xq1TzyyCND/RZERERERETkFCraioiIDGOdnZ3ccccd/PrXvyY1NTW4vL29nZUrV/L0008zZ84cZs2axapVq9iyZQtbt24F4K233sLpdPLCCy8wc+ZMbr75Zp544glWrFhBf3+/UW9JREREREQk6qloKyIiMowtXryYBQsWMHfu3EHLy8rKcLvdg5ZPmTKFgoICSktLASgtLWX69OlkZ2cHt5k/fz4ul4t9+/ad9Zh9fX24XK5BNxEREREREQkdq9EBRERE5OKsXbuWHTt2sG3bttPWNTQ0EBMTg8PhGLQ8OzubhoaG4DanFmwH1g+sO5tly5bx2GOPXWJ6ERERERERORuNtBURERmGampq+Na3vsXvfvc74uLihvTYS5cupb29PXirqakZ0uOLiIiIiIiMdCraioiIDENlZWU0NTVxxRVXYLVasVqtbNq0ieXLl2O1WsnOzqa/v5+2trZBr2tsbCQnJweAnJwcGhsbT1s/sO5sYmNjsdvtg24iIiIiIiISOiraioiIDEM33XQTe/bsYefOncHblVdeyR133BF8bLPZ2LBhQ/A15eXlVFdXU1JSAkBJSQl79uyhqakpuM3bb7+N3W6nqKhoyN+TiIiIiIiIBKhoKyIiMgwlJydz2WWXDbolJiaSnp7OZZddRkpKCvfccw9Llixh48aNlJWV8Y1vfIOSkhJmz54NwLx58ygqKuKuu+5i165dvPnmmzz88MMsXryY2NhYg9+hiIhI6Dz55JOYTCa+/e1vB5f19vayePFi0tPTSUpKYuHChaddgVJdXc2CBQtISEggKyuLhx56CI/HM8TpRUQkGqloKyIiMkI988wz3HLLLSxcuJDrr7+enJwc1q1bF1xvsVh49dVXsVgslJSUcOedd3L33Xfz+OOPG5haREQktLZt28avfvUrZsyYMWj5gw8+yJ///GdefPFFNm3aRF1dHbfddltwvdfrZcGCBfT397Nlyxaee+45Vq9ezSOPPDLUb0FERKKQ1egAIiIiEhrvvvvuoOdxcXGsWLGCFStWnPU1hYWFvP7662FOJiIiYozOzk7uuOMOfv3rX/OjH/0ouLy9vZ2VK1eyZs0a5syZA8CqVauYOnUqW7duZfbs2bz11ls4nU7Wr19PdnY2M2fO5IknnuB73/sejz76KDExMUa9LRERiQIaaSsiIiIiIiIj0uLFi1mwYAFz584dtLysrAy32z1o+ZQpUygoKKC0tBSA0tJSpk+fTnZ2dnCb+fPn43K52Ldv3xmP19fXh8vlGnQTERG5GBppKyIiIiIiIiPO2rVr2bFjB9u2bTttXUNDAzExMTgcjkHLs7OzaWhoCG5zasF2YP3AujNZtmwZjz32WAjSi4hItNNIWxERERERERlRampq+Na3vsXvfvc74uLihuy4S5cupb29PXirqakZsmOLiMjIoqKtiIiIiIiIjChlZWU0NTVxxRVXYLVasVqtbNq0ieXLl2O1WsnOzqa/v5+2trZBr2tsbCQnJweAnJwcGhsbT1s/sO5MYmNjsdvtg24iIiIXY1gVbZ988klMJhPf/va3g8t6e3tZvHgx6enpJCUlsXDhwtNOrNXV1SxYsICEhASysrJ46KGH8Hg8Q5xeREREREREhsJNN93Enj172LlzZ/B25ZVXcscddwQf22w2NmzYEHxNeXk51dXVlJSUAFBSUsKePXtoamoKbvP2229jt9spKioa8vckIiLRZdj0tN22bRu/+tWvmDFjxqDlDz74IK+99hovvvgiKSkp3Hfffdx2221s3rwZAK/Xy4IFC8jJyWHLli3U19dz9913Y7PZ+MlPfmLEWxEREREREZEwSk5O5rLLLhu0LDExkfT09ODye+65hyVLlpCWlobdbuf++++npKSE2bNnAzBv3jyKioq46667eOqpp2hoaODhhx9m8eLFxMbGDvl7EhGR6DIsRtp2dnZyxx138Otf/5rU1NTg8vb2dlauXMnTTz/NnDlzmDVrFqtWrWLLli1s3boVgLfeegun08kLL7zAzJkzufnmm3niiSdYsWIF/f39Rr0lERERERERMdAzzzzDLbfcwsKFC7n++uvJyclh3bp1wfUWi4VXX30Vi8VCSUkJd955J3fffTePP/64galFRCRaDIuRtosXL2bBggXMnTuXH/3oR8HlZWVluN1u5s6dG1w2ZcoUCgoKKC0tZfbs2ZSWljJ9+vRBs37Onz+fe++9l3379nH55Zefdry+vj76+vqCz10uV5jemYiIiIiIiAyFd999d9DzuLg4VqxYwYoVK876msLCQl5//fUwJxMRETldxBdt165dy44dO9i2bdtp6xoaGoiJicHhcAxanp2dTUNDQ3CbUwu2A+sH1p3JsmXLeOyxx0KQXkREREREREREROTCRHR7hJqaGr71rW/xu9/9jri4uCE77tKlS2lvbw/eampqhuzYIiIiIiIiIiIiEt0iumhbVlZGU1MTV1xxBVarFavVyqZNm1i+fDlWq5Xs7Gz6+/tpa2sb9LrGxkZycnIAyMnJobGx8bT1A+vOJDY2FrvdPugmIiIiIiIiIiIiMhQiumh70003sWfPHnbu3Bm8XXnlldxxxx3BxzabjQ0bNgRfU15eTnV1NSUlJQCUlJSwZ88empqagtu8/fbb2O12ioqKhvw9iYiIiIiIiIiIiJxLRPe0TU5O5rLLLhu0LDExkfT09ODye+65hyVLlpCWlobdbuf++++npKSE2bNnAzBv3jyKioq46667eOqpp2hoaODhhx9m8eLFxMbGDvl7EhERERERERERETmXiC7ano9nnnkGs9nMwoUL6evrY/78+fzyl78MrrdYLLz66qvce++9lJSUkJiYyKJFi3j88ccNTC0iIiIiIiIiIiJyZsOuaPvuu+8Oeh4XF8eKFStYsWLFWV9TWFjI66+/HuZkIiIiIiIiIiIiIpdu2BVtRYzi8XioqKgYtGzSpElYrfpnJCIiIiIiIiIioaNqk8h5qqio4KcvbSIjrxCA43VH+c5X0YR2IiIiIiIiIiISUirailyAjLxCcgonGB1DRERERERERERGMLPRAURERERERERERETkYyraioiIiIiIiIiIiEQQtUcQERERGSbcbjdOp/O05UVFRdhsNgMSiYiIGMPn81FTUxN8np+fj9mscWkiMnKoaCsiIiIyTDidTsrXPcnk/MzgsvKaZuD7FBcXGxdMRERkiNXU1LB843IcWQ7amtp44MYHKCwsNDqWiEjIqGgrIiIiMoxMzs+keHyu0TFEREQM58hykJ6XbnQMEZGw0LUDIiIiIiIiIiIiIhFERVsRERERERERERGRCKKirYiIiIiIiIiIiEgEUdFWREREREREREREJIKoaCsiIiIiIiIiIiISQVS0FREREREREREREYkgKtqKiIiIiIiIiIiIRBAVbUVEREREREREREQiiIq2IiIiIiIiIiIiIhFERVsRERERERERERGRCKKirYiIiIiIiIiIiEgEsRodQEREREREREQEwOPz8M23vsmhtkOMSRnDoqJFjGGM0bFERIacirYiIiIiIiIiEhHeb36frfVbAWjuaeZQ2yH+66r/MjiViMjQU3sEERERERERETGc3+/nf6r/B4CvTfkaeYl5tPS28E7jOwYnExEZeiraioiIiIiIiIjhGvobqOqqIsGawL/M/BfuLLoTgD/W/BG/329wOhGRoaWirYiIiIiIiIgY7mDPQQC+OumrpMSmcNvE20iOSeZYzzHq+usMTiciMrRUtBURERERERERQ/n8Po67jwPwpQlfAiDRlshXJnwFgNq+WsOyiYgYQUVbERERERERETHUiZ4TePCQYElggmNCcPl1o68DoMndpBYJIhJVVLQVEREREREREUM1djcCMNk+GbPp41LFzMyZ2Ew2enw9tPW1GZRORGToqWgrIiIiIiIiIoZq6GoAYIp9yqDlcdY4ilKKAKjtVIsEEYkeKtqKiIiIiIiIiKEGRtpOSZly2rri1GIAjnUcG9JMIiJGshodQERERGTEc9WTs+/XJDS/Dd2JkJSN2VeIz+hcIiIiEaDX14ur3wXA5OTJp60vTi2GI3Cs6xizYmYNdTwREUNopK2IiMgw9eyzzzJjxgzsdjt2u52SkhL+8pe/BNf39vayePFi0tPTSUpKYuHChTQ2Ng7aR3V1NQsWLCAhIYGsrCweeughPB7PUL+Vke2DX8HPppNd8VuS+xqg5RBUb2FqwzpSjr1rdDoREZEh4fP5OHr0aPDm83381eUJ9wkA7BY7Sbak0147IXkCNpONfm8/bZ62oYosImIoFW1FRESGqdGjR/Pkk09SVlbG9u3bmTNnDl/60pfYt28fAA8++CB//vOfefHFF9m0aRN1dXXcdtttwdd7vV4WLFhAf38/W7Zs4bnnnmP16tU88sgjRr2lkcXvh/WPwl++Cz43nekzqEktgQnzICEdq6+Pwm2PQcVbRicVEREJu5qaGpZvXM7z+55n+cbl1NTUBNe1eFoASLeln/G1FpOFdGv6oG1FREY6FW1FRESGqVtvvZUvfvGLTJw4kUmTJvHjH/+YpKQktm7dSnt7OytXruTpp59mzpw5zJo1i1WrVrFlyxa2bt0KwFtvvYXT6eSFF15g5syZ3HzzzTzxxBOsWLGC/v5+g9/dCPDBf8Bfnwk8vukRDl33C1oSJ8GoK2DWP9CSMA6T3wt/uBvqPjI2q4iIyBBwZDlIz0vHkeUYtNzlCbRGSLGknPW1qbZUAFo9rWHLJyISSVS0FRERGQG8Xi9r166lq6uLkpISysrKcLvdzJ07N7jNlClTKCgooLS0FIDS0lKmT59OdnZ2cJv58+fjcrmCo3XPpK+vD5fLNegmn1CzDd56OPB4/k/guu+AyfTxerOFmtRrcGVfDZ4eeOV+8KothYiIRKcObwcAdqv9rNukWdMAaHFrpK2IRAcVbUVERIaxPXv2kJSURGxsLP/8z//MH//4R4qKimhoaCAmJgaHwzFo++zsbBoaGgBoaGgYVLAdWD+w7myWLVtGSkpK8Jafnx/aNzXc9XfBS/8APg9M+wrM/pczb2cyUz3r/0CcAxr2wLb/GtKYIiIikcDr89Lp7QQg2ZJ81u1SrYGRti6vi15v75BkExExkoq2IiIiw9jkyZPZuXMnH3zwAffeey+LFi3C6XSG9ZhLly6lvb09eDu1J50A7/0/aK8GRwHcunzwCNtP8MY6YO4PA082/hg6m4cmo4iISIRo7G3Ehw+ryUqCOSG4/NSJy2pra4k3xZNgTcCPnyOdRwxMLCIyNFS0FRERGcZiYmKYMGECs2bNYtmyZRQXF/Pzn/+cnJwc+vv7aWtrG7R9Y2MjOTk5AOTk5NDY2Hja+oF1ZxMbG4vdbh90k5OaK2DLvwce3/wUxJ3Hn80ViyC3GPpc8OGvwptPRCRKPPvss8yYMSN4niopKeEvf/lLcH1vby+LFy8mPT2dpKQkFi5ceNo5sbq6mgULFpCQkEBWVhYPPfQQHo9a2YRabXctACmxKZhO+aLz1InLVpeupqOzg8z4TAAqOyoNySoiMpRUtBURERlBfD4ffX19zJo1C5vNxoYNG4LrysvLqa6upqSkBICSkhL27NlDU1NTcJu3334bu91OUVHRkGcfEd783+Bzw6QvwOSbz+81Zkug5y0EWiT0d4Uvn4hIlBg9ejRPPvkkZWVlbN++nTlz5vClL30p2LP9wQcf5M9//jMvvvgimzZtoq6ujttuuy34eq/Xy4IFC+jv72fLli0899xzrF69mkceecSotzRi1fYEiraOWMdp6wYmLrNnBL4EzUxQ0VZEoofV6AAiIiJycZYuXcrNN99MQUEBHR0drFmzhnfffZc333yTlJQU7rnnHpYsWUJaWhp2u53777+fkpISZs+eDcC8efMoKirirrvu4qmnnqKhoYGHH36YxYsXExsba/C7G34STuyByrfBbA1MPnYhptwCaeOg5TB89AJc/U/hCSkiEiVuvfXWQc9//OMf8+yzz7J161ZGjx7NypUrWbNmDXPmzAFg1apVTJ06la1btzJ79mzeeustnE4n69evJzs7m5kzZ/LEE0/wve99j0cffZSYmBgj3taINDDS1hHnAN+5tx0o2h7sOBjmVCIixtNIWxERkWGqqamJu+++m8mTJ3PTTTexbds23nzzTT7/+c8D8Mwzz3DLLbewcOFCrr/+enJycli3bl3w9RaLhVdffRWLxUJJSQl33nknd999N48//rhRb2lYy3GenEhs5h2QPv7CXmy2QMniwOPSfwffp3xqFRGR8+b1elm7di1dXV2UlJRQVlaG2+1m7ty5wW2mTJlCQUEBpaWlAJSWljJ9+vRBE3bOnz8fl8sVHK17Jn19fbhcrkE3Obdj3ceAM4+0/aSB9gi13bX0efvCGUtExHAaaStRweP1UdHYyeFmF5au4xQ6Pv5mfNKkSVit+qcgIsPPypUrz7k+Li6OFStWsGLFirNuU1hYyOuvvx7qaFEnqbee5OMfgSUGrn/o4nYy8w7Y8Di0VUPVezDuhpBmFBGJNnv27KGkpITe3l6SkpL44x//SFFRETt37iQmJgaHwzFo++zsbBoaGgBoaGgYVLAdWD+w7myWLVvGY489Fto3MsINFG1TY1Oh59zbJlgTiDXF0ufvo6ZbE6GKyMgW0SNt1TxeQqG6rZ+bf/4+X1z+Pvf99y7ufaWW+14+wq/fP8JPX9pERUWF0RFFRGSYy+rYE3hwxSJw5F/cTmzxcNnCwOOda0ITTEQkik2ePJmdO3fywQcfcO+997Jo0SKcTmdYj7l06VLa29uDt5oaFRbPpb2vnTZ3G3B+I21NJhMp1hQAjnQeCWMyERHjRXTRVs3j5VLVd/n59ut1HGzqJCnWyrjUGMDEYRd80BJHWm6B0RFFRGS462ggua8ev8kC1zxwafuaeUfg3vkK9OqSWhGRSxETE8OECROYNWsWy5Yto7i4mJ///Ofk5OTQ399PW1vboO0bGxvJyckBICcn57QBQQPPB7Y5k9jY2OCgo4GbnN1R11EA4s3x2Cy283rNQNG2qqsqXLFERCJCWIq248aN48SJE6ctb2trY9y4cee9n1tvvZUvfvGLTJw4kUmTJvHjH/+YpKQktm7dSnt7OytXruTpp59mzpw5zJo1i1WrVrFlyxa2bt0KEGwe/8ILLzBz5kxuvvlmnnjiCVasWEF/f3/I3q9Eprbufkobodfj57Pj03n3oRv491tHMWcUxFjM1LX3cqDV6JQiEo1CdZ6UC+d2u9m1a9dpN7fbffE7rQn83tE6+iZwXOKXgaNmQcYk8PSA8+VL25eIyDAUznOkz+ejr6+PWbNmYbPZ2LBhQ3BdeXk51dXVlJSUAFBSUsKePXtoamoKbvP2229jt9spKiq6pBzysbrOOgCSLEnn/ZoUS6Boe7TraFgyiYhEirAUbauqqvB6vact7+vr49ixYxe1TzWPlwvh8fp4bU89bh8UZcby3D98hoykwEzomfEmPjc50MB+bwscaVUBX0SGVjjOk3J+nE4n5euehG0rg7fydU9e/OWyPa3QXA5A88TbLz2gyQQzvxZ4vOv3l74/EZFhJlTnyKVLl/Lee+9RVVXFnj17WLp0Ke+++y533HEHKSkp3HPPPSxZsoSNGzdSVlbGN77xDUpKSpg9ezYA8+bNo6ioiLvuuotdu3bx5ptv8vDDD7N48WJiY2ND9n6jXX1XPRAYaXu+giNtO6vCEUlEJGKEdPalV155Jfj4zTffJCUlJfjc6/WyYcMGxowZc0H7VPN4uRhlR1s53tlPrAW+/7ksbJbB309MzUnmUFMnh493sXZ3GwuuMSioiESVcJwn5cJNzs+keHxuaHZWtwPw44rNozdlfGj2edlCWP8oHN0MnU2QlBWa/YqIRLBQnyObmpq4++67qa+vJyUlhRkzZvDmm2/y+c9/HoBnnnkGs9nMwoUL6evrY/78+fzyl78Mvt5isfDqq69y7733UlJSQmJiIosWLeLxxx+/9DcrQQ1dgc/lCeaE835NijUFEyba3G30+nrDFU1ExHAhLdp++ctfBgLNwRctWjRonc1mY8yYMfz0pz+9oH0ONI9vb2/npZdeYtGiRWzatClUkc9o6dKlLFmyJPjc5XKRn3+Rk4rIkOvx+CmrCfQ9uCIDMhJO/2tuMpmYPS6dw8e72FzdRU1LN/lp5/+LgojIxQjHeVKMY/J5oGk3AMeTpoZux46CQJuEY2Ww/xW46v8L3b5FRCJUqM+RK1euPOf6uLg4VqxYwYoVK866TWFhIa+//vp5H1Mu3MBI2wTL+X8Ws5qs5MTnUN9TT7unnVGMClc8ERFDhbRo6/P5ABg7dizbtm0jIyPjkvc50DweYNasWWzbto2f//zn/N3f/V2wefypo20/2Tz+ww8/HLS/820er0tehq99LeD2+sm2x5Kf1HfW7TKTY8mOh8YeWL2lih/cot5UIhJe4ThPinFSe46Apw/iUuiIywvtzou+FCja7ntZRVsRiQo6R0anixlpCzAmcUywaCsiMlKFpaftkSNHwnaSVfN4OZemTg+HT7Ygvm5CJiaT6ZzbT3YE7n+/rYaO3kuYhEZE5AKE8zwpQ8TvJ73zQOBx3hVgCvGvVEVfCtwf3QydzaHdt4hIBNM5MroEi7YXMNIWAkVbgDZvW4gTiYhEjpCOtD3Vhg0b2LBhA01NTcFvTQf85je/Oa99LF26lJtvvpmCggI6OjpYs2YN7777brDH0UDz+LS0NOx2O/fff/9Zm8c/9dRTNDQ0qHn8CPd6hQs/MDo1nlGp8TR8yhxyOQkwym7jmMvNm/sa+eqs0UOSU0QkFOdJMU5Cyz4S3C1gtkLODKhuC8l+3W53cFK0iY4pJLQdwLvvZSxXfzMk+xcRGQ50jowOfd4+WvsCbe0udKRtYWIhAC6PJg0XkZErLEXbxx57jMcff5wrr7yS3NzcTx3teDZqHi8Xos/j5c3KDgCKRzvO6zUmk4kbxyXyws42XtlVp6KtiAyJUJ0nxTgZR/4YeJA5FWzxQFtI9ut0Oilf9yST8zNp9yWQAHTteBG7irYiEiV0jowex/uOAxBvicdmsl3Qa4NFW68Lv98f8mwiIpEgLEXb//iP/2D16tXcddddl7QfNY+XC/H6nnrae33EW2FcRuJ5v+6GMUm8sLONzZXHae7oIzNZo7BFJLxCdZ4Ug3Q2kVK7MfB41KyQ735yfibF43OhOwa27SCpqQx6XRBnD/mxREQijc6R0aO5L9D+JyM244KL87nxuVhNVjx+D53uznDEExExXFh62vb39/PZz342HLsWOas1H1QDMN4OZvP5n/Tz7DaKR6fg9fl5fU99uOKJiATpPDnM7XgOs99DV0wGJJ99YtNLlpBOr9WO2e+ByrfDdxwRkQiic2T0aO4NFG0zYzMv+LVWs5W8+MAkoC29LSHNJSISKcJStP3//r//jzVr1oRj1yJnVNfWw7aqVkzA2IsYiPQ3M0cB8Kedx0IbTETkDHSeHMb8fvjoBQBOJE4J++Fc8QWBBwdeC/uxREQigc6R0WOgPUJG3MVNPDfQIqG1tzVkmUREIklY2iP09vbyn//5n6xfv54ZM2Zgsw3uT/P000+H47AShTweDxUVFfzR2Q7AOLufuIv4KuKWGbk88aqTHdVtNLT3kpMSF+KkIiIf03lyGKsuhdYqvNZ42gcKqmHUHldAVsdeqHgLPH1hP56IiNF0jowep460dXvcF/z6gsQCaA6MtM235oc6noiI4cJStN29ezczZ84EYO/evYPWqZG8hFJFRQU/fWkTO32BD859zUdpt6aQd4H7ybbHcXmBg4+q23jb2cBdJWNCnlVEZIDOk8PYzsDor/a8G/H5zj5pitvtxul0DlpWXl7OBJ/3gg7XHZOBOzYNW18LVL0PXPglpCIiw4nOkdFjoKdtZmwmdV11F/z6gsTAZ8DW3lZICmk0EZGIEJai7caNG8OxW5EzSsgs4MTRwOMxKRc26+ip5k/L4aPqNt7c16iirYiElc6Tw5S7B/a9DEBL4RfgSNlZN3U6nZSve5LJ+R8XWau2VZA+Lg0Yff7HNJloz72WjKpXAi0S8r9+cdlFRIYJnSOjR7BoG5dJHRdRtE0IFG1b+lrwJ/pDmk1EJBKEpaetyFCq6Qrc5zniiDX7Lno/86cFJpPZevgE7d0XfnmOiIiMcAdeg/4OcBTQlT7jUzefnJ9J8fjc4G1MTupFHdaVd93J478O/os/z4mIiEQKv9/P8d6TPW1jL66nbW58LmbMeHweun3doYwnIhIRwjLS9sYbbzznpSvvvPNOOA4rUar+ZNF2QmYSXMI8YmMzEpmcnUx5YwcbDjRy2xUXMBJKROQC6Dw5TJ1sjUDx7WAauu+9OzMuh5hk6GwgofUA+lgqIiOZzpHRod/fT6+vF7j4oq3VbCXZkky7tx2XxxXKeCIiESEsRduBHkQD3G43O3fuZO/evSxatCgch5Qo1eP20dwTeDwmI5Fjl1C0BZg/LZvyxg7e3Negoq2IhI3Ok8OQqx4On7xkt/jvoaZjyA7tt8TAxM/DvnXY69+nOzy/vomIRASdI6NDjy/wIS4tLo1YS+xF78dutdPubafd2x6qaCIiESMsv/U/88wzZ1z+6KOP0tnZGY5DSpTa3diLD7DHWXHE2y5loC0A86blsPydSjZVNNPT7yU+xhKKmCIig+g8OQzt/n2gNUFBCaSNg5pdQ3v8KQtg3zpS6t6nwXHj0B5bRGQI6RwZHbq9getGchJzLmk/dosdQCNtRWREGtKetnfeeSe/+c1vhvKQMsKVHQuc7AvTE0Mym+y0PDujHPH0un1sqmi+5P2JiFwInScjlN8Pu/478Lj4743JMPHzYLYR11lNrFujiUQk+ugcObIM9KDNSbi0om2KNQUAl1dFWxEZeYa0aFtaWkpcXNxQHlJGuLK6wGU1hekJIdmfyWQKTkj21r6GkOxTROR86TwZoRp2Q/MBsMbBtK8YkyEuBcZeD0BKT7UxGUREDKRz5MgSjpG2Pk3WKSIjTFjaI9x2222Dnvv9furr69m+fTs/+MEPwnFIiUJVx7uo7/BgAvJTQ1O0BfjCZTn8ZvMR1u9vxO31YbMM6XcbIhIFdJ4cZvb9MXA/cV6geGqUKQvg0AbsvSraisjIpXNkdBgYaZubmHtJ+0myJGE2mfH4PRzvO85YxoYinohIRAhL0TYlZfAHGrPZzOTJk3n88ceZN29eOA4pUWjzoeMAZMRBjDV0hdVZhamkJ8ZwoqufDw63cO3Ei5vNVETkbHSeHEb8ftj3cuCxUaNsB0z+Iry2hMT+49DXAbHJxuYREQkDnSOjQ6hG2ppNZhyxDlp6WzjadZSruCoU8c7J5/NRU1MTfJ6fn4/ZrIE+IhJ6YSnarlq1Khy7FRmk9NAJALJCN8gWAIvZxOeLslm7rYY39zWoaCsiIafz5DBSvwtaj4A1HibNNzaLPZeu1CISW51wohLyLjc2j4hIGOgcGR2CPW0Tc6Dn0vaVFpdGS28L1V1DcyVKTU0Nyzcux5HloK2pjQdufIDCwsIhObaIRJewFG0HlJWVsX//fgCmTZvG5Zfrw4WEht/vZ+vhFgCy4kO///nTcoJF28f+Zhpm86VPciYi8kk6Tw4DA60RJs2DmERjswCu3GsDRdvjFSraisiIpnPkyOXz++jxBSq1OYk59PX0XdL+UmNTAajprvmULUPHkeUgPS99yI4nItEpLEXbpqYm/v7v/553330Xh8MBQFtbGzfeeCNr164lMzMzHIeVKHKouYvjnX3EWEykx/pDvv/PTkgnKdZKU0cfO2vbuKIgNeTHEJHopfPkMOH3g/NPgcdFXzY0yoD2vOvJdf4ntB0FT29gcjQRkRFE58iRr9vTjR8/ZsxkxmdSS+0l7S81LvBZ7WjX0VDEExGJGGFpvHL//ffT0dHBvn37aGlpoaWlhb179+JyuXjggQfCcUiJMlsPB1ojTMmMxRKGUbCxVgs3TskC4M19DSHfv4hEN50nh4mm/YHWCJbYwCRkEaAvuYBeawr4fdBy2Og4IiIhp3PkyNfZ3wlAemw6FrPlkveXFpcGQE1XDT6/75L3JyISKcJStH3jjTf45S9/ydSpU4PLioqKWLFiBX/5y1/CcUiJMqUni7YzssM3wmj+tGwA3trXiN8f+tG8IhK9dJ4cJspfC9yPuwFikwyNcqr2+PzAg+MHjQ0iIhIGOkeOfJ3uQNE2My40o6ZTYlMwY6bX10t9V31I9ikiEgnCUrT1+XzYbLbTlttsNnw+ffMll8bv9/PByaLt9JzwFW1vmJxFjNXMkeNdOOtdYTuOiEQfnSeHiQOvB+6nfNHYHJ/giisIPGg5BD6PsWFEREJM58iRb2CkbWZsaIq2ZpOZZEsyAIfaDoVknyIikSAsRds5c+bwrW99i7q6uuCyY8eO8eCDD3LTTTeF45ASRQ41d3K8s59Yq5kpGeEr2ibFWpk7NdAi4Y87joXtOCISfXSeHAZc9VC3AzDBpJuNTjNId0wGxCSBtx9a1b9PREYWnSNHvuBI2xAVbQHsVjugoq2IjCxhKdr++7//Oy6XizFjxjB+/HjGjx/P2LFjcblc/OIXvwjHISWKlB5uAWBWYSo2S+j72Z7qK5ePBuBPu+rw+tQiQURCQ+fJYaD85Cjb0VdCcraxWT7JZIKMiYHHx8s/dXO3282uXbtOu7nd7jAHFRG5cDpHjnwDRduMuIyQ7dNuCRRtK9sqQ7ZPERGjWcOx0/z8fHbs2MH69es5cOAAAFOnTmXu3LnhOJxEmYFJyGaPSwfC+4Hzc5MySU2w0dzRx876nrAeS0Sih86Tw0DFG4H7yZHVGiEoYwrUfQTHKyC7+JybOp1Oytc9yeT8j0c0ldc0A9+nuPjcrxURGWo6R458oW6PAJBiTQHgcJsm6RSRkSOkI23feecdioqKcLlcmEwmPv/5z3P//fdz//33c9VVVzFt2jTef//9UB5Sosyp/WwDRdvwirGauWVGHgDvHO4M+/FEZGTTeXKYcPfCkZM/h0nzjc1yNo58sCWAp5fkvk+fdGVyfibF43ODt1MLuCIikUDnyOgRlvYIJ0faHmo/hM+v3sciMjKEtGj7s5/9jG9+85vY7fbT1qWkpPBP//RPPP3006E8pESZyqaP+9kW56dc8v58Xi+VlZU4nU6cTicez+kTunzlilEAbKnpxq0WCSJyCXSeHCaObgZPDyTnQVaR0WnOzGSGzMkApHRXGZtFRCQEdI6MDl6/lx5P4ArGULZHSLIkYTVZ6fH0UN/16V9miogMByEt2u7atYsvfOELZ10/b948ysrKQnlIiTIDrRGuHJNKrNVyyftraTzGbzft57ktVfz0pU1UVFScts3l+Q7GZiTS5/FTq8G2InIJdJ4cJio3BO4n3BToHxsmbo+X8vLyQX1my8vL8fq857eDjCkApPRUg+/0Lx1FRIYTnSOjQ7evGwALFpKtySHbr9lkZnRCYD4STUYmIiNFSIu2jY2N2Gy2s663Wq00NzeH8pASZbaenIRs9tjQtUZIzR5FTuEEMvIKz7jeZDLx5ZmB0bZHO0J2WBGJQjpPDhOVbwfuJ34+rIc5XN9C2+ZVsG1l8Fa14Te0trae3w5Otkiw+vtJblYhQ0SGN50jo0O3N1C0TbAkYArxF6P5CfmAirYiMnKEtGg7atQo9u7de9b1u3fvJjc3N5SHlCji9/s/noRs/PkVbT/Z/qCyshKf78J7HH3l8kDRtrEHOns1mklELo7Ok8NA69HA5F4mC4z93Hm/7JOjZs93xOz4vNRBvWbH5KSef9ZTWyQc23j+rxMRiUA6R0aHHl+gNUKCOSHk+y5ILACgsq0y5PsWETGCNZQ7++IXv8gPfvADvvCFLxAXFzdoXU9PDz/84Q+55ZZbQnlIiSIHmzo50dVPnM3MjNHn18+2pfEYv61oZ1xT4K/6wZ3bySiYRN4FHrsgPYGizFiczX2UN3Ywq/ACPlSLiJyk8+QwcOhka4T8z0C8AwC3243T6Ry0WXl5ORNOKcoerm+hbf8qcE0EoGpbBenj0oDR4c2bOQXqPiKl7n3wusFy9lFqIiKRTOfI6NDl7QICI21DrTAxcOWkRtqKyEgR0qLtww8/zLp165g0aRL33XcfkycHRn8cOHCAFStW4PV6+T//5/+E8pASRYL9bAvTLqif7UD7A4DjddVn3W5gVO6pJk2ahNUa+Gdy0/gknM197K93cUWB4wLTi4joPDksHHkvcD/uxuAip9NJ+bonmZz/8SzXZyrKDoyaBSivGaJLeFPycZvjsLk74PAmmDh3aI4rIhJiOkdGh08baevz+aitrQUI3F/APNAD7REOtx/G5/dhNpnx+XzU1NR8vE1+PmZzSC84FhEJm5AWbbOzs9myZQv33nsvS5cuxe8P/A9rMpmYP38+K1asIDs7O5SHlCgSbI0wLi0s+//kqNzjdUf5zlehqCgwc/h1YxL55QcnONHVT1NHX1gyiMjIpvNkhPP5TinaDm6NMDk/M1iQhSEsyn4ak5n2+EIyusph3x9VtBWRYUvnyOgw0NM23hx/xvWu4y6eP/I8o9tHU+2sxjHaQTrn1xovLz4Pm9lGj6eH+q56RiWNoqamhuUbl+PIctDW1MYDNz5AYeGZ5zIREYk0IS3aAhQWFvL666/T2tpKZWUlfr+fiRMnkpqqy8nl4gX62Z6chGxc6CYh+6RTR+V+UlKMhVGJUN0J++tdTIk742YiIuek82QEa9oH3SfAlgijZhmd5ry1xY8JFG0PvAren6lFgogMWzpHjnzdvkDRNtGSeNZt7Jl20vPSaWtqu6B9W8wWxqSM4WDrQQ61HWJUUmBeEkeWg/S88H2GFBEJl5AXbQekpqZy1VVXhWv3EmUqGjtpCfazdRiWY0xyoGhb3tDBxMILuFZHROQTdJ6MQAOjbAs/O6wKn12xWbhj07D1tqhFgoiMCDpHjkx+vz9YtI0zxV10G4RzmZAygYOtB6lsq+T60deHZqciIgYJW9FW5Gw8Hg8VFRWDlp3aO/ZMTu1nG2M1rgdRdgIkxlro6vNS32VYDBERCYfDmwL3n2iNEPFMZtrzrifjyMtqkSAiIhGry9OFx+8BwNPq4fnqi2uDcC7jHOMATUYmIiODOnDLkKuoqOCnL23iuS1VPLelip++tOm0Iu4nvX/wOAAl4429rMVsMjElxw7AEZehUUREJJR8Hji6JfB47PAbmdM26uTEaQdeBU+/sWFERETOoLkv0A8+zhKHBUuwDYI9wx6yY0xwBFrdqWgrIiOBirZiiIy8QnIKJ5BTOIGMvHM3gnd7fZQeChRtPzcp85zbDoWi3MAvFfXd0NrjNTiNiESzZcuWcdVVV5GcnExWVhZf/vKXKS8vH7RNb28vixcvJj09naSkJBYuXEhjY+Ogbaqrq1mwYAEJCQlkZWXx0EMP4fF4hvKtGC6+rQL6OyDOAdnTjY5zwboyZkBiFvS2wZFNRscRERE5zfG+wGe6pJiksB1jvGM8AIfbD+Pz+8J2HBGRoaCirUS8j6rb6Or3kpYYEyyYGiktMYYcexx+4N0jnUbHEZEotmnTJhYvXszWrVt5++23cbvdzJs3j66uj/u3PPjgg/z5z3/mxRdfZNOmTdTV1XHbbbcF13u9XhYsWEB/fz9btmzhueeeY/Xq1TzyyCNGvCXDJJ3YHXhQUALmYfjrkckCRX8TeLzvZUOjiIiInElzb2CkbZItfEXb/OR8bGYbPZ4e6jrrwnYcEZGhMAw/lUi0ef9g4OR+7YQMzGaTwWkCpuYmA7D+kIq2ImKcN954g69//etMmzaN4uJiVq9eTXV1NWVlZQC0t7ezcuVKnn76aebMmcOsWbNYtWoVW7ZsYevWrQC89dZbOJ1OXnjhBWbOnMnNN9/ME088wYoVK+jvj57L7BMHiraFJcYGuRTTvhK4V4sEERGJQAPtEcJZtLWarYxJGQMERtuKiAxnKtpKxHvvZD/b6yZmGJzkY5OykzEDR1r7KW/oMDqOiAgQKNICpKWlAVBWVobb7Wbu3I8nppoyZQoFBQWUlpYCUFpayvTp08nOzg5uM3/+fFwuF/v27Tvjcfr6+nC5XINuw5rfT+KJPYHHBZ81NsulKChRiwQREYlYQ9EeAWBCSqCvbWVbZViPIyISbiraSkRr6+5nd20bANdNNL6f7YA4m4WcxMDjV3frshsRMZ7P5+Pb3/4211xzDZdddhkADQ0NxMTE4HA4Bm2bnZ1NQ0NDcJtTC7YD6wfWncmyZctISUkJ3vLz80P8boZWrKcda387WOMht9joOBfPbIGiLwUeq0WCiEQ59X2PPEPRHgE+7murychEZLhT0VYi2ubKE/j9MCk7iZyUOKPjDFJw8neNV3fX4/f7jQ0jIlFv8eLF7N27l7Vr14b9WEuXLqW9vT14q6mpCfsxwymx7+QH9NFXgjXG2DCXatqXA/cH/qwWCSIS1dT3PfIE2yOEeaTtxNSJAFS0VoT1OCIi4WY1OoDIuQz0s42kUbYD8hIhxmLiyPEu9tW5uGxUitGRRCRK3Xfffbz66qu89957jB49Org8JyeH/v5+2traBo22bWxsJCcnJ7jNhx9+OGh/A6OMBrb5pNjYWGJjY0P8LoyTNFC0LRzGrREGDLRI6GqCI+/BxLmf/hoRkRHojTfeGPR89erVZGVlUVZWxvXXXx/s+75mzRrmzJkDwKpVq5g6dSpbt25l9uzZwb7v69evJzs7m5kzZ/LEE0/wve99j0cffZSYmGH+Rd8Q8vl9nOg7AQRG2nbTHbZjTU6bDATaI7h97rAdR0Qk3DTSViKW3+/nvYqBom3k9LMdYDOb+MzoeAD+rBYJImIAv9/Pfffdxx//+Efeeecdxo4dO2j9rFmzsNlsbNiwIbisvLyc6upqSkoCE26VlJSwZ88empqagtu8/fbb2O12ioqKhuaNGCyx/+R7LxjGk5ANMFtgyoLA44o3zr2tiEgUUd93Y53oOYHH78GEiURbYliPlZeYR7ItGY/PQ213bViPJSISThFdtFUfouh2qLmLuvZeYixmrh6bbnScM7p+TODSnr/saVCLBBEZcosXL+aFF15gzZo1JCcn09DQQENDAz09PQCkpKRwzz33sGTJEjZu3EhZWRnf+MY3KCkpYfbs2QDMmzePoqIi7rrrLnbt2sWbb77Jww8/zOLFi0fUaNqz6uskxtuFH1OgPcJIMGl+4P7gm6Bzk4iI+r5HgPquegDizHGYTeEtQ5hMpmCLhCOdR8J6LBGRcIrooq36EEW3gdYIV41NJT7GMuTH93m9VFZW4nQ6cTqdVFZW4vP5Bm1zZV48sVYz1S3dlDd2DHlGEYluzz77LO3t7dxwww3k5uYGb7///e+D2zzzzDPccsstLFy4kOuvv56cnBzWrVsXXG+xWHj11VexWCyUlJRw5513cvfdd/P4448b8ZaGXkfgSole+1iITTY4TIiMvR4ssdBWDc3ln769iMgIp77vxmvoChS5E8wJQ3K8gRYJKtqKyHAW0T1t1Ycour1/8DhgXD/blsZj/LainXFNgX8mB3duJ6NgEnmnbBNnM3PdxAzW72/irX2NTMmxG5JVRKLT+Yzwj4uLY8WKFaxYseKs2xQWFvL666+HMtrw4ToGQHfaNOINjnKx3B4vhz9xJdL0wmswH34nMNo26QZjgomIRAD1fY8MAyNtEyxDVLRNPVm07TrCJOukITmmiEioRfRI209SH6Lo0efxUnoo0Kj+egMnIUvNHkVO4QRyCieQmpV3xm3mFQV+YXvLeeZLpEREJIK5AiNtu1OHb//ew/UttG1eBdtWwraVlK97kvqk6YGVFW8ZG05ExCDq+x5ZjBxpqzZ2IjJcDZuirfoQRZcdR9vocXvJSIplSk5kX65609QszCbYe8zFsbYeo+OIiMj58vugIzDypyttmsFhLs34vFSKx+dSPD6XyfmZuHJOTqpWXYq5X+17RCT6qO97ZAkWbYdopO0ExwTMJjPt7nZ6fb1DckwRkVAbNkVb9SGKLgP9bK+bmIHZbDI4zbmlJ8VyZWFg9Pdb+zTaVkRk2OhsAp8Hr8lGX3KB0WlCqj8xDzImgd9LctM2o+OIiAw59X2PLEM90jbOGkehvRCANk/bkBxTRCTUIrqn7QD1IYo+A/1sPzsuDafTOWjdpEmTsFqN/6s7MFEZwPR0+LAK3jnQyDeuGXvuF4qISGQ4OQlZd0wmhHkma0NMnAfHK7A3lNLOmX/nEREZqdT3PbIEe9oOUdEWYErqFI60H6HV0zpkxxQRCaWI/oSiPkTR6URnH3vrAv2Lc01t/PSlTTy3pYrntlTx05c2UVFRYXDCgJbGY/x2036e21LFseYWALYeaqGn32twMhEROS8n+9l2WNMpLy9n165dwZvb7TY4XAhMmg9AcuMHoH5+IiJikH5vPyd6A/OVxFuGbtrPaRmB1kcq2orIcGX8cMVzWLx4MWvWrOFPf/pTsA8RBPoPxcfHD+pDlJaWht1u5/777z9rH6KnnnqKhoYG9SGKcJsPncDvhyk5yaQlWMnIKySncILRsc5oYKKybL+f9+oq6fb42Xr4BDdOyTI6moiIfJqOwO8VhzpjAhN5uSYCUF7TDHyf4uJiA8OFQEEJxNqx9bWR0H8cOPOEmiIiIuHU2BW40jXGHEOs6dI/g/t8PmprawNPzvGdZFF6YJBWi6flko8pImKEiC7aPvvsswDccMMNg5avWrWKr3/960CgD5HZbGbhwoX09fUxf/58fvnLXwa3HehDdO+991JSUkJiYiKLFi1SH6II9l5FoJ/t9ZMy+eRZ+NSWBACVlZX4fMYPGDeZTOQmwCEXbCxvUtFWRCTSefuhO9CKpxUH4/PiKB6fC4Db46W8vDy4aXl5ORN8w/AqCosNxt8Izj+R3FsLzDA6kYiIRKGB1ggZsRmYTJc+X4nruIvnjzyPr8+HY7SDdNLPuF1RehEmTPT4euh2d1/ycUVEhlpEF23Vhyj6+P1+/nqyn+21EzLA0zxofUvjMX5b0c64psBf3YM7t5NRMCkixg4NFG3fLW/G7/eH5BcSEREJk5OjbIlNprc3lsRTVh2ub6Ft/8cjb6u2VZA+Lg0YfdpuIt7E+eD8E/beWqOTiIhIlDrWeQyA7LjskO3TnmnH1+s75zaJtkRGJ4ympruG5p5mkkgK2fFFRIZCRBdtJTqcOnq2uq2fBlcvMVYznxmbxuGDzadtP9CSAOB4XfWQZj2XrASwmqG6pZsjx7sYl6lfCkREItZA0TYpB3pPXz0+LzU48jbQLmGYmjAXgAR3C/R3QUzip7xAREQktAZG2mbFZYEnPMcY1DIByM/Px2w2MyF5AjXdNTR1Nw0q2vp8Pmpqak7bXkQkkuh/JTHcqRN6Pf2XPQBcNSaVOJvF4GQXxmY2MS0rDgiMthURkQjWebJom5xrbI5wS86mJ+VkX/jWKkOjiIhIdBoYaZsVF74Wcq7jLp7f8TzP73ue5RuXBwuyk5InAdDcPfjzWU1NDcs3Lj9texGRSKKirUSEgdGznbY0AK6dkGlwootz5agEAN6tUNFWRCSidQRG/Yz4oi3QkfWZwIPWw8YGERGRqDRopG0Y2TPtpOel48hyBJdNSA58cdnU03Ra+0VHluO07UVEIomKthIxvD4/TT2Bx9dNzDA2zEW6clQ8AFsPn6CnfxhOWiMiEgUsvj7oaQ08Sc4xNswQcGWfLNq2VMF5zBcgIiISSnWddQBkxQ79ZM1jk8YGJiPz9NDj6xny44uIXAoVbSViNLh68fjBHmumKNdudJyLUpBiIy8ljn6Pj62HTxgdR0REziC+/+T/z3EOsMUbmmUodKdPx2uygrsLupqMjiMiIlHE4/PQ2NUIhHYisvMVZ4nDbgl8tmzxtAz58UVELoWKthIxqlu6ASjOicdsNhmc5uKYTCY+NznwDfLGcn0wFhGJRPHukx/ahsEoW7fHS3l5Obt27WLXrl2Ul5fj9V3YlRx+s43O2JPvtUUtEkREZOg0dzfj8XuwmqykxqYakiHtZAu+Vk+rIccXEblYKtpKxKg5WbS9PG94j3q6YXKgH68mIxMRiUzBkbZJQz/i50Idrm+hbfMq2LYStq2kasNvaG298A+dHXF5gQctR0KcUERE5OzqugKtEXISc7CYjJloOtUaKBa3uDXSVkSGF6vRAUQA3L5AewSAy3PjDE5zaa6ZkIHNYqK6pZuq412MyUg0OpKIiJwiONJ2GBRtAcbnpVI8PjBhWnnNxX0h2BE3KvDAVQve/lBFExEROaeBfrZ5SXmGZUizfjzS9pOTkYmIRDKNtJWI0Oqx4fdDkg2yk2xGx7kkSbFWZhUGvs3dVKHRtiIikcTs6SbW4wo8GSZF21Dot9oDPXz9Pmg9anQcERGJEpFQtE2xpmA2men399PY22hYDhGRC6WirUSEE+7AoO+cBIODhMj1kwItEt5T0VZEJKLEtR/CBBCTBDFRdiVE2tjAfataJIiIyNAYaI9gZNHWYrKQHpcOwMGOg4blEBG5UCraSkQ44Q6Mrs0e3u1sg66fGCjalh4+Qb/HZ3AaEREZEN9WEXgQRaNsg1JPFm01GZmIiAyR4EjbROOKtgCZCYHPZyraishwoqKtGK7XZ6HbZ8EEZI2Qom1Rrp2MpBi6+71sP6qG9yIikSK+/eSHtWgs2joKwWSG3jZiBlpEiIiIhFEktEcAyIrPAlS0FZHhRUVbMVyrLxaALHssMRaTwWlCw2w2cd3J0bbqaysiEjni26K4aGuNBXtgQrLk3jqDw4iIyEjn9Xmp76oHIqBomxAo2lZ2VOL1eQ3NIiJyvlS0FcO1eOMAyE8dIQ1tT/pcsK/tcYOTiIgIAJ5+4lwn+7kmR2HRFiBtHKCirYiIhF9jdyNunxur2UpOQo6hWVLjUrGarPR4e6hsqzQ0i4jI+VLRVgzl9/uDI23z00ZW0fbaiRkA7K930dTRa3AaERGheT9mvwePKQZiU4xOY4yTfW2T+uox+dwGhxERkZGsuqMagNFJo7GYLYZmMZvMpFsDk5HtbNppaBYRkfOloq0Yqr3HTZ/figk/uSlx+LxeKisrcTqdOJ1OKisr8fmG50ReGUmxXDbKDsD7Gm0rImK8+t0A9MSkgWlktOO5YEnZYEvA4veQ0LLP6DQiIjKC1XTUAJCfnG9wkoB028mibfNOY4OIiJwnq9EBJLrVtPYA4LB6sFnMtDQe47cV7YxrCvzVPLhzOxkFkzC2A9LF8Xg8FKWa2HsM/ry9kqnxLiZNmoTVeuZ/dh6Ph4qKiuDzc20rIiIXoeFk0daWRrLBUQxjMgVG2zbtI7nxA2CR0YlERGSEqnEFirYF9gKDkwRk2AJXQu5q3gWREUlE5JxUERJD1bZ0A5Bm8wSXpWaPIqdwAgDH66oNyRUKFRUVVB6sALIpPdrFvzVs4l//FoqKis66/U9f2kRGXiHH647yna+efVsREbkI9bsA6IlJNzhIeLk9Xg6Xlwefl5eXM+HUSVfSBoq2HxqQTkREokWkjbRNs6ZhwkRNRw1t/W1GxxER+VQq2oph/H5/cKRtmtXzKVsPT+NHZ7O3ykyf14cl/dO/zs3IKwwWrEVEJIR8XmjYCwRG2o5kh+tbaNu/ClwTAajaVkH6uDRgdGCDk31tE9oPQmcTJGUZlFREREaygZ62kVK0jTHHkJ+QT3V3NQdcB4yOIyLyqdTTVgxzoqufHrcXMz5SRmjR1mwyMTo1HoCGboPDiIhEs5bD4O7CZ4mlz2o3Ok3Yjc9LpXh8LsXjcxmTkzp4ZUwi3QOF60Mbhz6ciIiMeH6/P+JG2gJMTZkKwP72/QYnERH5dCraimFqB/rZmvsxj+D5YArTEwAVbUVEDDXQGsE+Hkz69acj7mS3+EMbjA0iIiIj0oneE/R4ejCbzIxKGmV0nKCp9pNFW5eKtiIS+fSpRQxT2xqoYqZaeg1OEl6F6YkAHO+Frn6fwWlERKLUQNHWMcngIJGhI+7kB+hD74BP5yYREQmtalegNUJOQg4xlhiD03xsSsoUACo7KvH6vZ+ytYiIsVS0FUP4/P7gSNtUc5/BacIrJd6GI96GH9jV0GN0HBGR6NSwG4CelIkGB4kM3TGZeK3x0NUc/LMREREJlWBrBHvktEYAGBU/ipTYFPp9/bR52oyOIyJyTiraiiHa+qDP4yPGYibZ3G90nLAbaJFQVqeirYjIkPP7of5k0dahoi2A32ShM+OKwBO1SBARkUvk8/k4evToxzfXUSCy+tkCmEwmZmbOBOCE+4SxYUREPoWKtmKIppO1y1Gp8SO6n+2AgpNF2x11Pfj9foPTiIhEmfZa6GkBs5Ve+zij00SMjuzPBB4cXG9sEBERGfZqampYvnE5z+97nuUbl1PeWA4YU7T1+XzU1tZy9OhRamtr4RMfv4oziwE44VHRVkQim9XoABKdBoq2o1PjIQom6BrtSMAMNHZ6ONTcxYSsJKMjiYhEj5P9bMmcij+C+uoZzZXzWdj1DNRsha7jkJhhdCQRERnGHFkO0vPSAdjevR2AsfaxQ57DddzF80eeZ3T7aKqd1ThGO0gnPbh+ZtZMAI67jw95NhGRC6GRtjLkPD4/zSeLtvmpCcaGGSIxVjOZ8YHH7xxoNDaMiEi0GSja5hYbmyPCuBOyA38mfh9UvGF0HBERGSH8fj/Huo8BMM5hzBUu9kw76Xnp2DPsp62blj4NM2Z6fD109ncakE5E5PyoaCtDruJ4Hx4/xNnMZCRFz4invMTA/fr9TcYGERGJNgMTbaloe7rJCwL3B14zNoeIiIwYXb4u+nx92Mw2RiWNMjrOaRJsCYxNCowAbuhqMDiNiMjZqWgrQ253Qy8Ao1MTMJmioKHtSaNOFm3LjrbS2jXyJ18TEYkYwZG2M4zNEYmmnCzaHnoH+rvOuanb7WbXrl2Dbm63ewhCiojIcOLyuAAotBdiNUdmR8ailCIA6rvqDU4iInJ2KtrKkNvVEOiNMDo13uAkQyvRZmKMw4bX5+fdCo22FREZEh2N0FEPmCD7MqPTRJ7saeAoBE8vVG4456ZOp5PydU/CtpWwbSXl657E6XQOUVARERkuXN5A0Xa8Y7zBSc5uWso0QEVbEYlsKtrKkOp1e3E29QHR08/2VFfnB96zWiSIiAyRgdYIGRMhVpNAnsZkgqm3Bh47//Spm0/Oz6R4fC7F43OZnJ8Z5nAiIjIcdXg7ABiXYkw/2/MxzREo2p7oPUG/T1dBikhkUtFWhtSO6lbcPj9xFkhNsBkdZ8hdPTpQtN1U3kyfx2twGhGRKFC/M3CvfrZnN+22wH3565/aIkFEROTTDLRHiOSibWpMKkmWwJe5x93HDU4jInJmKtrKkCo9dAKA7HhGXD9bn9dLZWUlTqcTp9NJZWUlPp9v0DaTMmLJscfR2efh/Qr9ciAiEnb1J0fa5qif7VmNuiLQIsHdDRVvGp1GRESGMb/fH2yPMDZlrMFpzi3TFrhiREVbEYlUKtrKkBoo2maNwM4ILY3H+O2m/Ty3pYrntlSx+q3ttLe1DdrGbDJx8/QcAF7bo/5JIiJhF5yETCNtz8pkgssWBh7v/R9js4iIyLDW7enG7XdjxsyYlDFGxxnE5/NRW1vL0aNHqa2tJcOaAUCzu9ngZCIiZ6airQyZrj4PO2vaAMgaoXOQpWaPIqdwAjmFE0jNyjvjNgum5wKw3tmoFgkiIuHU0wptRwOPczXS9pwGirYH34LedmOziIjIsNXa2wpAdnw2sZZYg9MM5jru4vkdz/P8vudZXbqa+P7Ah9JWTyt93j6D04mInE5FWxky26pa8Pj8ZCdZSbKNrNYIF+KKglRy7HF0qEWCiEh4DbRGcBRCfKqxWSJd9jTInALefti7zug0IiIyTLX2BYq2+Qn5Bic5M3umnfS8dOwZduKJJ9GWiA8f+9v3Gx1NROQ0KtrKkBlojVCcE2dwEmOZzSa+cFmgRcKru+sMTiMiMoI1nCzaapTtpzOZ4PK7Ao93PG9sFhERGbaO9wQGpYxNiux+thCYY2VU0igAdrbtNDaMiMgZqGgrQ6b08EDRdoT2RrgAX5oZaJ3wxr4GOnrdBqcRkeHqvffe49ZbbyUvLw+TycTLL788aL3f7+eRRx4hNzeX+Ph45s6dy8GDBwdt09LSwh133IHdbsfhcHDPPffQ2dk5hO8ijNTP9qzcHi/l5eXs2rUreHMXLQSzDep2QMMeoyOKiMgwNFC0HZ803uAk52egaLu7NfBFr8/n4+jRo8HbJyeWFhEZSiraypBo73az91igR96MKB9pCzAz38H4zER63T5e260JyUTk4nR1dVFcXMyKFSvOuP6pp55i+fLl/Md//AcffPABiYmJzJ8/n97e3uA2d9xxB/v27ePtt9/m1Vdf5b333uMf//Efh+othFewaDvT0BiR6HB9C22bV8G2lbBtJeXrnsR5tAmmLAhsoNG2IiJygXx+Hy29LQCMSxpncJrzMzppNACVHZW4+l3U1NSwfONynt/3PMs3LqempsbghCISzVS0lSHxwZET+PwwLjOR9ASr0XEMZzKZ+NsrA32eXiqrNTiNiAxXN998Mz/60Y/4yle+cto6v9/Pz372Mx5++GG+9KUvMWPGDJ5//nnq6uqCI3L379/PG2+8wX/9139x9dVXc+211/KLX/yCtWvXUlc3zNu39HXC8ZOjijXS9ozG56VSPD6X4vG5TM7PDCy84u7A/a7fB/4MRUSGKV2NMvRcXhc+vw+byUZ2XLbRcc5LUkwSyZZkfPjY3rAdAEeWg/S8dBxZDmPDiUjUU9FWhsSWk/1sPzs+3eAkkeO2y0dhNsH2o60cbtYvfyISWkeOHKGhoYG5c+cGl6WkpHD11VdTWloKQGlpKQ6HgyuvvDK4zdy5czGbzXzwwQdn3XdfXx8ul2vQLeI07gX8kJQDSVlGpxk+xt0IaeOhrx0+esHoNCIiF01Xowy9Nk8bACmWFI4dOzZsWgxk2QK/J3zY8KHBSUREBov4oq2+IR0Zth4eKNpmGJwkcmTZ47hhcuAXhDUfVBucRkRGmoaGBgCyswePdMnOzg6ua2hoICtrcEHTarWSlpYW3OZMli1bRkpKSvCWnx+BM0Qf2xG4z7vc2BzDjdkMJYsDj7euAK/H2DwiIhdJV6MMvVZPKwAJ7gSe3/H8sGkxkBUT+F1o87HNBicRERks4ou2+oZ0+Dve2ceBhg4AZo/TSNtT3VVSCMDvt9XQ7Y7sb6BFRAYsXbqU9vb24C0iP4wdKwPAm3v5oMm2ysvL8fq8BoeLcMW3Q0I6tFXD/leMTiMiEnJRfzVKmAyMtE0mGXumfdi0GMi2ZWM1WalyVVHTFYG/04hI1Ir4oq2+IR3+BkbZTslJJi0xxuA0keVzEzMZl5FIR5+HDYc0+ltEQicnJweAxsbGQcsbGxuD63Jycmhqahq03uPx0NLSEtzmTGJjY7Hb7YNuEedYoC9dlSed8nVPBifcqtrwG1pbWw0OF+FiEuCqbwYev/dvEOGXtYqIXKiovxolDPx+f7BoaycCfy84hxhzDMWpgf73W49vPa/X+P3+cEYSEQGGQdH2XML1DWk0fzsaDh/3s1VrhE8ym018/ZoxAPxpf7tO/iISMmPHjiUnJ4cNGzYEl7lcLj744ANKSkoAKCkpoa2tjbKysuA277zzDj6fj6uvvnrIM4dM1wlorQKg2zGFyfmZwQm3xuSkGpttuLj6nyA2BZr2wd6XjE4jIjJsDIurUcKgsbcRt9+N2WQmkUSj41yw2RmzASg9Xvqp2x50HeSN1jd4ufJlen29n7q9iMjFGtZF23B9Qxqt346GS+nJom2JJiE7o4VXjMYeZ6Wuw0Ntl9FpRGQ46ezsZOfOnezcuRMIfJm5c+dOqqurMZlMfPvb3+ZHP/oRr7zyCnv27OHuu+8mLy+PL3/5ywBMnTqVL3zhC3zzm9/kww8/ZPPmzdx33338/d//PXl5eca9sUtVd7KfbfpEfDHJxmYZrhLS4JoHAo83/hg8/cbmEREJoai/GiUMDrgOAJARn4F5GJYZZqfPxoSJio4Kur3dZ93ujao3+O5H36XD20F9Vz3vtL1DU2/TWbcXEbkUw+9/0yEQrd+OhkNdWw9HjndhNsHV49KMjhOREmOtfP2asQDsa9GlNiJy/rZv387ll1/O5ZcHJttasmQJl19+OY888ggA3/3ud7n//vv5x3/8R6666io6Ozt54403iIuLC+7jd7/7HVOmTOGmm27ii1/8Itdeey3/+Z//acj7CZmT/WwZNcvYHMPd7HshMSswannbr41OIyISMlF9NUqYDBRtcxLOXtCOZKmxqRRnBlokHOs/dsZtajtq+cFff4Db7yYnJodkWzKd3k5WVJx5/h0RkUtlNTrApTj1G9Lc3Nzg8sbGRmbOnBnc5kK/IY2NjSU2NjY8oaPM5srjAMwY7cAeZzM4TeS655qx/Nd7lbT3+znU3EWS0YFEZFi44YYbzvlFj8lk4vHHH+fxxx8/6zZpaWmsWbMmHPGMo6JtaMQkwo3/G179Nmz8CdY5z+ExOpOIyHnq7OyksrIy+HzgapS0tDQKCgqCV6NMnDiRsWPH8oMf/OCsV6P8x3/8B263e2RcjRIm+9v3A5CdmA3NBoe5SF8Y+wV2Nu+ksqeSq/2nF+b/74f/l15vL9Md05linYIl3cLa8rV81PIRx3uOkxGvdoAiElrDeqStviGNfAP9bK+ZoNYIPq+XyspKnE4nTqeT3bt3s3v3bpxOJ8eqDnJddmA2862HT+DTaFsRkYvj939ctB2tou0lu2IRjL4K+jsZtfsXRqcRETlvuhpl6HS7uznSeQQYviNtAb484cskWhLp8HZQ5aoatG5D9QberX0Xq8nKv0z8F0wmE6lxqaRZ0/Dh462qt4wJLSIjWsSPtNU3pMOX3+8PjrS9RpOQ0dJ4jN9WtDOuKfDP7uDOrVhiExk3dToA9Qd2YE2+ghNd/RzW3HciIhfnxCHoPgHWOMi+DI4fMDrR8GY2wy3PwK8+h6PuXdrSbgByP+1VIiKG09UoQ2ffiX348BFvjicpJolGGj/9RREo0ZbIzaNu5qXql9jZtJPrE68H4HjPcR4vDfw9WTRtEfmJH895UxBbQIunhdePvM7Xpn7NkNwiMnJFfNF2+/bt3HjjjcHnS5YsAWDRokWsXr2a7373u3R1dfGP//iPtLW1ce21157xG9L77ruPm266CbPZzMKFC1m+fPmQv5doc6i5k6aOPmKtZhJ6GnA6A20qKisr8fmG9SDvi5aaPYqcwgkAHK+rxhKXNOj5BHo50J3A3hPQ2e81MqqIyPBUfXLW57wrwKpWRyGRMx2u/Ta8/1NGt5VC3zSIPb8J3txuN06nc9CyoqIibDa1TBIRGSl2Ne8CIN02/K+u/JtRf8O66nU0dDdQYarA4/Pwwy0/pKW3hYmpE7l35r001H48oXl+bD67u3azq3kXNR015CdrEnMRCZ2IL9rqG9Lh668HA6Nsp2bE8Is/vk9GXiEAB3duJ6NgEhrnfLrRsX004aClu581u9r4zEyjE4mIRK4zFQSnHy0N9H4qmG1IphHrc9+ne8+fSWirgPLXYPr/Oq+XOZ1Oytc9yeT8TADKa5qB71NcXBzGsCIiMpR2NZ0s2lpPL9r6fD5qa2sBAvcR3gUuLTaNKQlTcHY72dm1k7u23EWHp4MYcwz/97r/S6xl8BfC8ZZ4ZqTOYGfrTt6pfodF0xYZlFxERqKIL9rK8LX5ZD/b4tx4epMKB40olTMzm+D6SRm8vLOOPx9wcX9zJ+MzNS2ZiMiZnKkgODl5D3Ggom2oWWOonvUwk975BubWKqj6KzDxvF46OT+T4vFqqSAiMhL5/D4+av4IgAzb6S3xXMddPH/keUa3j6baWY1jtIN0IntE7rSEaSTZk/iw4UM6PB1kxGfwvc98j4mpZz7vXZF6BTtbd7K9cbuKtiISUiraSlh4vD62Hg4UbWfmxrO1o83YQMNIYXoiuQlQ3w0/fm0/v/n6VUZHEhGJWKcWBK3eHuLqawIr8j9jYKqRqc8+hhpHCYWtf4XqLSSnx9FhdCgRETHUgZYDtPe1E2+JJ9WaesZt7Jl20vPSaWtqG9pwF8lkMjErexZxPXFcN/o6Fl6xEJv57G19pjmmAfBR00f4/D7MpuhsBSgioaf/TSQs9ta56Oj1kBxnZUJajNFxhp2ZGWAxwTsHmth4oMnoOCIiw0JCf3PgQeZUiD/zB0e5NG2J4wP9goHClveJ6aw1OJGIiBhpa/1WAKY7po+4YmVOTA4lmSXnLNgCjE8aT7w1nva+dg63HR6idCISDUbW/6oSMTZXBvrZloxLx2I2GZxm+LHHmPjSVDsAD7+8l84+j8GJREQiX2Lfydmq1RohvMbfBPZRWPxuxnzwMPR3GZ1IRESGiM/n4+jRo8FbaV1gAtCZqTONDWYgq9nKjIwZAOxo2mFwGhEZSVS0lbDYcihQtL1mwul9jeT83FmcyujUeI619fBvb5YbHUdEJOIlqWg7NMwWKPoybnMc8a7D8PK94PMZnUpERIZATU0Nyzcu5/l9z/PMxmfY0RgoUkZz0RbgiuzAVShljWUGJxGRkURFWwm5XreX7VWtAFwzIbKbzEeyOJuZn3xlOgDPlVaxo7rV4EQiIhHM00u8uyXweMx1xmaJBrHJHE2/AZ/JCs4/wbvLjE4kIiJDxJHlID0vHY/DQ7+vn8z4TPIT8o2OZaiBoq1G2opIKKloKyG342grfR4fWcmxjM9MMjrOsHb9pExuu2IUfj98/3920+/RSCYRkTNqq8GEn96kfEgZZXSaYcft8VJeXs6uXbsG3dxu91lf0xWbTe3lDwWevPcU7HlpiNKKiEgkaOwPXOFyde7VmEzR3RJvRsYMrCYrDV0N1HXWGR1HREYIFW0l5DbsD5y8p2fa2L9/P5WVlfh02eRF+8GCItITY6ho7OSX71YaHUdEJDK1VQHQmXmFsTmGqcP1LbRtXgXbVgZv5euexOl0nvN1rYU3w2cfCDx5+V+gdvsQpBURkUhQ318PwGfzPmtwEuMl2BKYnDYZgF3NuwxOIyIjhYq2EnJv7T0GQHdXJ89tqWL1W9tpb2szNtQwlpoYww//ZhoA//5OJXuPtRucSEQkArVVA9CZOcvgIMPX+LxUisfnBm/jctMGjb4tLy/H6/Oe/sK5j8Kkm8HbB//993Di0JBnFxGRodXe1067tx0zZq4ffb3RcSLCjMzAZGS7m3cbnERERgoVbSWkjp7ooqbdjQkonjyOnMIJpGblGR1r2Lt1Ri7zp2Xj8fn5zh920ec5w4dmEZFo1d8FXc0AdGbMNDbLCPLJ0bdVG35Da+sZ+qubLbDw15AzI/BzeOE26Ggc+sAiIjJkjrQfAWC6YzopsSkGp4kMxZnFgEbaikjoqGgrIfXOgSYAMuMh1mYxOM3IYTKZ+MlXppOeGEN5YwdPv11hdCQRkcjRdhSAHlsa3liHsVlGmFNH347JST37hrHJcMdLkDoGWqvgdwuh1zVUMUVEZIgNFG1LMksMThI5Boq2+1v20+ftMziNiIwEKtpKSA0UbXMTDA4yAqUnxfKT26YD8J/vHWZ7VYvBiUREIkTLYQA6YnMMDhJdTpu87HAD+6/8Cf7ETGjYA2u/hkkfWkVERpxeXy8N3Q0AzE6fbXCayDEqaRRpcWl4fB72n9hvdBwRGQGsRgeQkaOzz8MHhwOFxLxEg8OMUPOn5XDbFaNYt+MY33lxF68/cB2JsfpnLCJRzO8PFm1bbXmUl5cPWl1eXs6EM/VhlUt2uL6Ftv2rwDUxuGxPTTOWG3/CpC0PQtX7jOl5mCrrBANTiohIqNX21QKQak0lIy7D4DSRw2QyUZxZzMaajexq3sXMrJlGRxKRYU7VHgmZt50N9Ht9jLLbSLa5jY4zYv3w1mmUHjrB0RPdLPvLfn705elGRxIRMUxC/3Fwd4Mllt0tVtoODy4iVm2rIH1cGjDauJAj2ED7hFP1pE6G29fCmv+FvfEDxsZWw9ivgcVmUEoREQmlqt4qAApjC40NEoFmZM4IFm1FRC6V2iNIyLyysw6Az41JxGQyGZxm5EqJt/H/vhrol/TC1mreq2g2OJGIiHGSewOjfUgdgx/zoB6sn9qHVcJn7HVwx0t4LfEk99XD3hfB2290KhERuURHu47S4mnBjJmCuAKj40Scgb62O5t24vf7DU4jIsOdirYSEq1d/bx/8DgAnxur3giXyuf1UllZidPpxOl0snv3bnbv3h18nuZu4q7ZgV+SvvvSbtq7NbJZRKKTfaBomz7e2CByujHXcPiaf8NrskJbNex5EbNP5ysRkeFsQ8MGAArthcSZ4wxOE3mmZ0zHZrbR3NPMUddRo+OIyDCn9ggSEn/Z24DH56co105+SozRcYa9lsZj/LainXFNgX+iB3duxRKbyLipgVYIx+uOsvjL1/HXykSOHO/i0T/v45m/m2lgYhGRoWftPU6C++SkjGnjgUOG5pHTdadP53DGPCa2bID2Gsb1rOew+y6jY4mIyEVw+9y80/AOAJPTJkOXwYEiUJw1juLMYrY3bufDhg8ZkzLG6EgiMoxppK2ExMsfHQPgb2bmGZxk5EjNHkVO4QRyCieQmpU36Hla9mhqqw5z/1V2zCb440fHeG3XMaMji4gMqZS69wIPkvMgRld5RKru2EyY8fdgjSWxv4lxWx6Cvg6jY4mIyAV6q+ot2txtxJpiKUge+a0RfD4ftbW1HD16lKNHj+Lz+c7rdZ/J+QwA2xq2hTOeiEQBjbSV03g8HioqKgYtmzRpElbrmf+67Ktr58OqFixmE1+amUfrsSNDETOqBUfiTrUy2QH7W2Hput18ZlwGmcmxRscTERkSjmPvBh5kTjY0h5wHey7MuB3PR2tIbNkLLyyEO/8HYpONTiYiIufB7/fz3L7nAJgYPxGL2RIsagKB+xHWwtV13MXzR55ndPto2praeODGBygsPPvkaz6fj5qaGgpMgYL2hw0f4vf7Nd+LiFw0FW3lNBUVFfz0pU1k5AVOSMfrjvKdr0JRUdEZt1/510CR9ovTc8lNiadVAz6HxMDI24x8H3WbD9He5+N//3EP/3nXLP1iICIjX0cjicdPzsycOcXYLHJ+knM4nDmPca3vYq35AF74Ktz5kgq3IiLDwLaGbexv2U+sOZbx8YE+8qcWNaud1ThGO0gn3eCkoWXPtJOed37vqaamhuUbl5OcmYzZb6alt4VDbYeYkDohzClFZKRSewQ5o4y8wuCl+APF2zNp6ujlz7vqALjn2rFDFU9OYTWbmZ0NVjO87WzkxbJaoyOJiITf/lcw4acrJgPiUoxOI+epJyadw9c8E/iZ1WwNFG77Oo2OJSIiJ/l8vmA7gFNbAvxm728AmJszl1jzx1f2DRQ17Rl2Q/JGGkeWg6xRWWTGZAKB0bYiIhdLRVu5JP/1/hHcXj9XFDiYme8wOk7UcsSauLM4FYBHX9nHoWZ9ABaREW7fywC0x48xNIZcuJ7UyXDXyx8Xbv/776G/2+hYIiLCx6NFn9/3PMs3LqempoZtDdvYXLcZq8nKl/O/bHTEYSErJguAvx77q8FJRGQ4U9FWLlplUwe/Odka4b45uuTDaAunpfDZ8el093t54L8/os/jNTqSiEh4tB6Fo5sBaIs/+9UgEsFGXQF3roOYZKh6H35/B7h7jU4lIiIERoum56XjyHLg9/v5WdnPAFg4aSG58bnGhhsmRsWMAqC0rpS23jZjw3yKs42uFhHjqWgrF8Xv9/PDV/bh8fmZOzWLOVOyjY4U9SxmE8/83UxSE2zsq3Px1BvlwXUejwen0zno5vF4DEwrInIJdv034KcjcxZua5LRaeQUbo+X8vJydu3axa5duygvL8frO8uXiKOvhDteBFsCHHoHXvw6ePqHNK+IiJzbluNb2H18N/HWeP65+J+NjjNs2K12xiWNw+P38Hb120bHOaczja4Wkcigoq1clJV/PcLmyhPEWM08css0o+PISdn2OP7tb4uBwM9o44Em4OPJ5Z7bUsVzW6r46UubqKioMDKqiMjF8fngo98B0FJ4s8Fh5JMO17fQtnkVbFsJ21ZSteE3tLa2nv0FhSVw+1qwxkHFX+B/7gGvvlQUEYkEbr+b/6r8LwAWTVtERnyGwYnCw+fzUVtby9GjR6mtrQX/xW3zSddnXQ/AX478JcSJQ+/U0dUiEjmsRgeQ4eeNvfX8+PX9AHz/C1MoSE8wOJGc6qap2Xz9s2NYvaWKJX/YySv3XQt8PLmciMiwVvU+tFdDbArteZ+DhheMTiSfMD4vleLxgctny2uaP/0F4z4Hf/c7WHs77H8F37p/ZM+ExWAe/GtqUVERNpstHJFFROQMnF1OmvuaGZU0in+47B+MjhM2ruMunj/yPKPbR1PtrMYx2kE66ee1zUAxFzitmHt91vWsPrya7Q3baexqJDtRV6eKyIVR0VbOm9/v53cfVPPoK/vw++HukkK+cc0Yo2MJ4PN6qaysDD7/8lg/26vs7K1z8c3nt/PjG9MMTCciEkI7ngvcT1+I3xJ77m1lWHC73Ti7M7Ff9ShjPvgB5n3/Q9rev9I6+vP4TRZgoPj7fYqLi40NKyISJZq7m6noCVyZt/QzS2k6FriC73xHmQ439kw76XnptDW1XdA25yr4ZsVlcXnW5XzU9BH/feC/eeDyBwa1HsjPz8ds1sXPInJ2KtrKeWnp8fCttTt5ZVcdAH9TnMcjtxRhMpkMTiYALY3H+G1FO+OaAv+km2oO87eXFXCsJYYDDR388A0Xkx3GZhQRuWTtx8D5p8DjWV+HJkPTSIg4nU7K1z3J5PxMqtKuJ//4u+SbGsnveh+mfSXQOkFERIaM1+/lnep38OPn2sxrGeMbw/KNy3FkOc46EjWanavg+41p3+Cjpo94Yf8LXJd0HWtK1+DIctDW1MYDNz5AYaEmVBWRs1PRVs7J5/dzsM3PP718jC63D5MJvjt/Cv/8uXHBgq3H4xnUH7WyshKfT98YDrXU7FHB9gfH66p5det+rhhzGRvrYG+riZauPr461q9Cu4gMXx/+J/g8UHgt5BZD0y6jE8kFcnu8HC4vH7SsvLycCaPSTrZUyOXdd7u4ljKsbUdhx/Nw2VeNCSsiEqX2dO2hta+VOFMc9068F/i45+m5RqLK6W7Iv4Ersq5gR9MOflf1O1KzUknPU8FbRM6PirZyVo2uXt450ERTB4CP6aNS+NGXL6M43zFou4FJrjLyAt8SHty5nYyCSeQNeWI5VWr2KKZOmUh8eiev7q6jrj+Wdw40ceOULKOjiYhcuL5OKFsVeFzyL8ZmkYt2uL6Ftv2rwDUxuKxqWwXp49KA0QA0kUFZbAlXswt6WmDHalJSSmg3KLOISDTZdmJbsC3ClclXkhKTYnCi4c1kMvGdK7/DHa/fwfqG9VydfLVGKYvIeVPRVk7T7/Wxo9nPwcpAvx2ryc+Xx/hZdE0qlo46du+uDiy3Bv76VFZWkpaTP2iUp0SO8ZlJFMW04OxPY2+di163j+LkEdiISkRGth3PQ287pI6FSV8wOo1cglMnKoMzT1bWaU6B4kXgfBlctYxp2UTrtsdh/LOQpC8fRSS6+Hy+IemFeqzzGD/d/1MALku/jDyzhuGEwozMGXxtytdYc2ANH3Z8SGp7KskkB9cP1c9XRIYfFW1lkCPHu1jyej2HTw5nmZydTKbrAEcrWnnBEpgM5ODOrVhiExk3dfrJ5xpZG+lyrd1YY2LZ15VMZXMnTe1wU2s/RUYHExE5H32d8H7gQyTXfhvMFkPjyBCJTYKZX4Mj7+Ov2Upq7Xr496tg3hNw+V2gdj8iEiVqamqCPWXD1Qu1y93Ftzd+m05PJ2nWND6b91naGtpCeoxo9t2rvkvNiRreb36fv1T9hQlxE/iqJ9D+Zyh+viIyPKloK8GetHsbe3liYyMd/T5izH6+MH0UYzMS2VvqJOET/VItcUkaWTvM5MS4mTRpFH/ZW4+r38v9rx6jrDWG+26cQGpijNHxRETO7oNnofs4pI2DmXcYnUaGkskM4z7Hwb40RvdVkNB+EF65H3b8Fm76AYy93uiEIiJDYqCnbDi4fW6WvLuEAy0HcNgclCSXYDFb8Pl81NbWBjbShXqXxGK2sGTqEo51HONw72Eqeyv5xw/+kfvc93Fl7JVh/fmKyPCloq1QUVHBd9duw9mfgQ9I8HZypcPD2IxJRkeTEBuVGs/Xri7g9R1HONYFK/96hDUfVHPbFaO47YpRXJ6fitl87pFLn5x4DmDSpEnBdhkiIiHVdRw2/yLw+Ib/DRabsXnEED0xGRws+Q7FPaWw8cdQ+yE8d2ugaHvjw1BwtdERRUSGpT5vH9/d9F221G0h3hrPD6f/kNKaUgBcx108f+R5fH0+HKMd6sV6iWxmG1cmX0lRXhHvHn2XNncbP/rgR4yKH0WhrZA0f5rREUUkwqjKEuX8fj8v7m1jb38GAOMzE8nvrCXGnGhwMgmXhBgr1+aauKwwi7X7e9hX5+J3H1Tzuw+qybHHcfP0HOZPy2FWYSo2y+m9lD458dzxuqN856tQVKRmCyISBm/+H+hrh+zpcNlCo9OIkcxW+Ox9MP2rgXYZ21fBkffgyDwYNQuuvAcuuw1s8QC43W6cTuegXRQVFWGzqfAvIiPb+fZIbelt4aFND/Fhw4fYTDa+O/W7xLviB42qtWfa8fX6hiL2iHTqz6K2thb8kJ+czxdSv0BGagZ/qPkDx3qOcaznGIcqD1EUc+bPVOp7KxKdVLSNYh6vjx++so/f7WgFYGa+g+smZuDcesDgZBJuPq+XlJ46nrppPLsaEni7soMP63ppcPWyanMVqzZXkWAzcXluPFeNSuBvr5vGqLSk4Osz8gqD7TFERMLm0EbYvRYwwa0/w+314tyzJ7i6vLycCT6vcflkyLg9Xg6Xl3/8POvviLnhBkYd+h2p1W9iPlYGx8rgzaUw7Ssw6WYOuJIof3UFk/MzgYEJz75PcXFxYB9nKOrCpRd2w7VfEZHz9Wk9Uv1+P+/WvMtjpY9xovcE8ZZ4pnmmsb9hP28639So2hA69WdR7awO/tmaTWZuGXULi65cxM+3/JwXj75IY3cjjd2NdOzu4HvJ32NK2pQz7kd9b0Wih4q2Uaqrz8P9//0R7xxowgTMzIDrJ2UaHUuGSEvjMX5b0c64ppP/BdQd5vHLC2iPz+UvexvY2eyn221hc3U3m6u7+VnpJopy7dw4JZMxsb34/GpqJSJh1t0CrzwQePyZb8LoK3Hu2kX5uieDRbiqbRWkj0sDRhuXU4bE4foW2vavAtdEAN7ZVoEjzsTV0yfSkHMb3rpdTE5sJ7a7AcpWQ9lqpgOTbMnEdmdCTBJ5yW58zl9Dx3iISaK+4QSdZW+QnZVNn9WOxxxHee1xTi3sXgyn0zno7ymcXjAWEQm3M/VI7ff2817te6zet5pdzbsAKEgo4O70u6noqSA9L522pjYD0o48p/YDdmQ6zvpnmxSTxJ1j76Sro4tDpkPsP7Gf7S3b+ds//y1fGPMFbp9yO5dnXR7Yzxl+ppc6Are1t5XNzZs50H2AlOMpJHgS8OuznkjEUNE2CjV19HLP6u3sOdZOrNXMQ9dmcLC22ehYMsRSPzG53Nr39zNuqhXvkW3ckD+JtPEzqDrRxcG6Flr7wFnvwlnvAiDGDGM66hmbkUi820tlZeWgfavHrYhcEp8X30v/gLm9mr7EPCqyvoJv167AyNpRaRSPzwUGCmESLcbnpQ762acnmILPd1niOXDl1ylOboMDr0HlBmg9QqynA1o6AMgEKN8PJwfsFgAFJmDgr5HZxkRbEo3vfJ/aQ1fR45hEb8oEpsyYdcEjZCfnZwaziYiEy6cV7Px+Py6Pi9eOvUblkUo+qP8AV//A7/Mx5HnzuCLhCtbvWK/RtSH2af2ATy3q1tbWEm+O53OjPkehr5AuWxfvNb3HG1Vv8EbVG4xKGsVlyZfh6nOR6BncxvBiR+DuO7GPNfvX8MaRN+j39QcWdgXuDu84zBPJTzAtfdql/0GIyCVRVSXKbDl0nG+t3UlzRx9piTH816IrieusV9FWgkXc43XVmEyQkxJHTkocYyytfOnyfBpMqWwsb2bj/gY6+31UNHVS0dSJGXjvSAfTjhwhJwFa6qvV41ZELp7fD2/+b8yHN+Lxm6lKnIVv51pAI2vlU5gsMH5O4Abs/XAT8R/+O+PTzNDfTeOJViyZE8lIjgN3F64TDVhaj5Bo7oNeF/jcJPhaGdu+BXZvAcDnh/53x2AbezVkXwbJuZCYAYmZEGcHW8LJWzyYzj2Rp4hIKPj8Php7Gulp6eFwzWF+/9HviUuJw9Xu4vpJ12NLtuGsc7KjdQcdJzoCBbnWj1+fFpPGnOw5XGW5irLOMtJHpdPZ3GncGxrBztUPeKCoO7p99KC2CcnWZBYXLeb+q+8PFFWr3uBY5zGOdR4DoHRfKQnmBI7sOcKM4zNIdCfS4+jBkeog3hd/zlGyLb0tbKjewMuVL7O7eXdweWFiIX6PH7/NT11nHQc7DnL7q7fzz8X/zD8X/zNmk3rnihhFRdso0d3v4Zm3K1j51yP4/DApO4n/vOtKxmQk4nTWGx1PIpwj3sJni0Zz2xWj2bN3Hz/bWIXLlsrBpk7aut20mB28Xw/xNgujEgo40NzLVL8fkz7AisiF8PvhjaXwwX8AcCz9GiZP/XiUh0bWytl8suctQHlVIxNisiA3UOSv6a3lcNznmDxucmB9eTkTLJu4YuJo8Hmgt52/flhGnq2DcXYfdDZi7u8krqMKdlcBvz9HAlOweDsFKx6PF/rSIdYOcXaSe/z0u6rAPRlscafnVx9cETkLv99PZUcle7v20lTexIneE7x0/KWPNzABrsD93oN7T3u9GTOXOS7jujHXUUAB6z9aj7nXzB+df9ToWoPZM+1nbZswJW0Kj5Y8ytdyvsbe9r28X/0+2zu34/K66PZ1s+3ENrad2PbxC9oDd6+/9zrp29NJsiWRHJNMgjWBHk8Pjd2NwcIvgNVk5ZqMa1gwagHJHclsbN9I+qh0amtrcVlcbGraxLO7nmXfiX0su24Z9hh7mP80RORMVLQd4bw+P3/aeYyfvlXOsbZeAOZNSOKfP5POaEeswelkOLKYTWTEm7isMIOScemUbv4rjTho9iXS4/ZS2Q5L/lLP01vbuG5iBlcWpjE1184oRzz2eOtphVyPx0NFRcWgZWqvIBKFulvgT4uh/HUAamY+RNvxJjTFhpyPT/a8hdNHZn9ym0HrzVZISKeOHPpsuYybPh2AXc4KXHGjmJDUTVxHFda+Viy9rdj6WrF4ujEPXFKKH9xd4O4iFogFaP74S4ZxABs2wAYgOQ+fowCXNw5PrANPrIO6tl766/aRnZmB1xyD1xTDwcYOLP0PcdmsEjBbwvsHKCIRy+f38ejuR2lztwWXWU1WHHEObNjo6e8hLjYOv9vP+JTxZKRkkORN4siJI+Tn5uNt8fKNy75BYWEhR48epSyrTL1rh4mamhp+/f6vcWQ56K7s5rOjP0vulFyqaquYkjWFE6YTHDp+iMr2Svroo9fbi9vvpqGr4az7HBUzioTeBKZkTqHZ2czLh14e1MIh3hzPPxX9E/MmzePx0sd5r/Y9bn/1dn5248+YmDrxrPsVkfCIqqrIihUr+H//7//R0NBAcXExv/jFL/jMZz5jdKywaOnq5087j/Hb0qMcPh5oThNr8vCZHCupdPGL/9nDV6oOM2HCBCorK/H5dMmDnJnP+/+zd+fxTdTpH8A/k7tXetILSinILZegtYgnCAKyuPLbFRcBXYRVwQXZRWQFUVBRVgVxWVAXQVaQVVdcRQQ5RaEilvuQo1LK0QPokZ45v78/0oSmtKUtSSZNPm9fednMTDLPTEq/yTNPnq9rz9rqvy+SJEGvNCNSV4HhPW5EdmE59mdeQG6FhHOFFfj4p7P4+KcrfbbUSglRIRpEBmsQolUhRKuCzViOM+dzEBOhR7AKsBTl4Pn/E+h+I3soEXmTrGNk7mGIj0dCKj4Lm0KNcz3/ih8r2+IGG78JQg1XvectUHtlds2+uNdyPL8SRUUZ0HdrD6AVoG2FjQdPIEKXgNRu7QFhw7aM44jW2dCnU2sohAV7jvyK7okadE+KBIwGoLIYFcUXoRGVUFoqgJILUJRcQES1/cQDgALA5SvLOkoAvt4OfA1YVcGwqkOhDmsBKbwVEN4KCG8JS2gCsgosMIUkwKyLASQFq3OJPEDOMVKpUOL22Nux9+JedIjrgKCSINwffT9aJ7XGuXPnsLVoK6JbRuPyhcsY03WMMzm7smwlooOicVm6fO2dkM+o2eu25iRmOpUO0apo9BA90KplK5yzncNWhf134OT+kygoLUBkUiTOZ52HTWNDeFw4is4VQaPSoH3r9sj9JRcRrSLQqlUrGC8ZodApam3h8Jt2v8ENETfgmW3PILskGw+tewhju47FuBvHIVQT6s1TQhTQAiZp+5///AdTp07F0qVLkZqaioULF2LQoEE4fvw4YmNj5Q6v0apXJxotNuSVWqAMj8ORnBLs/rUAP2UVwGqz97MJ1Shwd7wFKoUSrdvZr45dupCNf393DG3zVTi5/2fEtO6ARNmOhnxZQd55/PtEMdrm2/9c1PX7olBIaBMdAl2phN/f3BrF2hbYdeoyDpwrwrELxSg12WC2CuQZjMgzGGs8Wo+zlxw/J+DB1VnoGF+Azgn6qlsYuiToERGs8fDREgUm2cfIkBawVJahUgQjJ+YeVORfQNae7exfSz6htmRw9UnQjp+7jOhgCZ07dgAAHMi14KJSAlp1cz7mRGYO0OeP6NG+FVCYhTMHdkB18hu01KsAcznOXshFsNKC6BA1YDECFiMspgqoJPsHaaWlHEpLOVCRD+QfcT6vCsANVT/boECpCELFrm5QJ/cAItsAUSn2/0ckA5pgT54mIr8l+xgJ4E/t/4SVppWIjopGZnYmPsr+CK0Mrr1Qayb7UNXatK7l5Jvq6nXbkG0UUCA2JhYpySlQFiqh0CmQ0jYFmYZMKHQKJLRKQPml8gbH0iW6C9bcvwYzd87EjnM78K9D/8JHRz/CHa3uQIo6Ba1DWiNKE4Ub296IcG24z7bGu9aEfUS+LGCStm+99RbGjx+Pxx57DACwdOlSfP311/jggw/w3HPPeXz/5SYL8osrcCLzV1isAlabgNkmkNAyCTZIMFltMFvsSS2z1YZKkwXncnJgsQqYbUC52QZ1sB4lRisMFWbkFhQj62IJrAoNKq2OvZx32WeoZEKHGA3ahNmQdXAPYlp3cFlffeIpovo4flcAXPP3xWa14vyZX3HDDQo82BbobruEL3LPIapdMoxW4OTRQ7BpQtGiVQrMNuDC2Swow+Oh1sfAUGFGQWklLDYJRy4YcOSCweW5w3UKJEaGIF6vQ2yYDiFaBSpLihGkVkCnkhCsVqBtciuEB2kQrFUhSK2EQrJXBCskQCFJkCRAgv0NhcVqwenTpwEASkmCSgl0bH8DgrQaqBQSNEoFFArffPNB5E5yj5EIi8Ovff8O0/HN6Nbe3hCB/WvJn5gtVvx64kTVZGVqHC9rhRuCO6Bliv2iRPqFg4jWSuh/05VE7+fbDyJGZ8M9vdoDFiM2/XQYltJC3JgUAY21DGprGUoKL6KFzoJgVEIhbNBLZUDej/ZbTaHxQFhcVZ/dcEATCiiUsAmgsKgIqJpoxioAQIKkVAOSEkKhhJCUiGkRB6VaAyiUsEoq5F4sgFCoYVOoIRQqtGydApUmGFBqAKUaUGnt/1dqAGW1nx3LnRPbVI2zzg/79d2/xrZWM2A12XsUW032+zZz1fJq64TNvn9JYX8OyXGrvqzqZ8dyVN/GE9vy/Yavkn2MrEVtvVDrSuQ1JAlIvqW+XreN2cYdInWR+Mc9/8DW7K1486c3cbb8LL49863rRnsAjUKDCHUEIjWRiNJGIVITiTYt2qBFcAvEBMUgWBUMjVIDnUoHtUJt/3wGBRSSouqzmgIS7P8XQiD3Qq5zm1atWkGpUEIpKaFSqKBUKKGS7G33hBCosFSgzFyGEnMJCisLcbniMgoqC3C58jIKKgpQVFKEoxeOIig4COZyM+654R7ckHADonRRiA6KRpQuCpG6SKgV/JYK+Z6ASNqaTCZkZGRgxowZzmUKhQIDBgxAenr6VdsbjUYYjVcqAYuL7V29DQbDVds21Nq95zDrf0dqWZPZiGe5UMsyCwBACRtigyS0bRGCzi10iLJcxO4TFxCtaQ2bETCbjMjPzkRwkH3yi/xzp6HUBCM4SOfyc8113r4fqPv2pViu97kyD+3BnuJiJCa3BQCcO3UUUYkp0EfHQglAXVkIpc2IFsp4QAlUlGVDab6ENtFdATVw6sweFJYaEZJ4A3IuF8OsjYA1KBJGqFFoBAqLS1Hbv6QrztS79tpcJ7JRSPY+vioFoFJIUEmAsupnZVVC1ybgnKm1qsAdQgACAhCADbjyf9j/75jY1SYAmxAQ4spyx3NJkK58jpQARdV9hfO+/eOq82ep2vaonqSuiqnGkVafXFY4l7luVf1eXZPRuj6P4wTUeN5anrTWdTX3Wce+7ecXsAphP/82+3m0AVj1eCq6t4qoPdhrcPydr2/mXX/T2DES8Mw4eUmVgJO/XoKjEP+X7IsI10rQBV/5N11z2bXuu2sbxsJYrvd5t+w9hYKin1CY0hIA8PPxc8hJikSF0XrN/WhD7F9FSc82I1wbBr2yDVDV4nbLsVMI10ro0yUFGmsZDv1yAmpjEdq30CJEqoDWWooorYBGVALGHOBy7S1H1HX8XF1ZjfthNe6X76zjgdQgAo6ktAThSFBLEgQUVQO5ouq+I9kLiGpJXwEFJNgAYYMkbICwVv1fQBJWQAgoYANu/wvQb3KT4wy0cdJXxsiSkhLknclDZXklLp27BIVGAY1KU+vPleWVMFWacCn7UoOWN+Rnm8nW4G29+bOvxtWcYyy+WIzjquMoKSlx+R20XrAi6lgUoqKicKb4DKx6Kyw6CyrMFbAqrKio+i8H1caZxqQ6mkApKSGEgA1Xt3eolX2KH2QezgSunrMPQcogqCSV8+ZIFNep5ucT1PwcVc/9Wh4rIGATNpf/O46v5nFKqJH0dvxclfiWJAlKKO1DhPPT4NUxufWYajz+mtvW3PVVn0OvsX219U15rE3Y7Ddc+X+3mG5YPGBxvY+tj0fGSBEAzp8/LwCIXbt2uSyfNm2auOWWW67afvbs2QL2XzfeeOONN94C8Hb27FlvDVGya+wYKQTHSd544423QL8FyjjJMZI33njjjbfG3tw5RgZEpW1jzZgxA1OnTnXet9lsKCgoQHR0tEf6tBgMBiQlJeHs2bPQ6/Vuf/7mhOfCjufhCp4LO56HKzx5LoQQKCkpQWIiu3zXx9vjpK/gv8MreC5c8Xy44vlw5U/ng+PktXlijPSn3yGAx+PreDy+jcfjuzwxRgZE0jYmJgZKpRJ5eXkuy/Py8hAfH3/V9lqtFlqt1mVZRESEJ0MEAOj1+mb/S+ouPBd2PA9X8FzY8Txc4alzER4e7vbn9GWNHSMB+cZJX8F/h1fwXLji+XDF8+HKX85HII2TvjZG+svvkAOPx7fxeHwbj8c3uXuMDIgp8zQaDXr37o0tW7Y4l9lsNmzZsgVpaWkyRkZERCQvjpFERES14xhJRERyCohKWwCYOnUqxo4diz59+uCWW27BwoULUVZW5pwFlIiIKFBxjCQiIqodx0giIpJLwCRtH3roIVy8eBEvvPACcnNz0bNnT2zYsAFxcXFyhwatVovZs2df9TWaQMRzYcfzcAXPhR3PwxU8F+7ny2OkL+Hv3hU8F654PlzxfLji+WjefGGM9LffIR6Pb+Px+DYeT2CRhBBC7iCIiIiIiIiIiIiIyC4getoSERERERERERERNRdM2hIRERERERERERH5ECZtiYiIiIiIiIiIiHwIk7ZEREREREREREREPoRJWx/y2muvQZIkTJkyRe5QvO78+fN45JFHEB0djaCgIHTr1g0///yz3GF5ndVqxaxZs5CSkoKgoCC0a9cOc+fOhb/PF7hjxw4MGzYMiYmJkCQJX3zxhct6IQReeOEFJCQkICgoCAMGDMDJkyflCdbD6jsXZrMZ06dPR7du3RASEoLExESMGTMGFy5ckC9gD7nW70R1TzzxBCRJwsKFC70WH/mvxYsXo02bNtDpdEhNTcVPP/1U57bvv/8+br/9dkRGRiIyMhIDBgyod/vmpjHnoro1a9ZAkiQ88MADng3Qyxp7PoqKijBx4kQkJCRAq9WiQ4cOWL9+vZei9bzGno+FCxeiY8eOCAoKQlJSEp555hlUVlZ6KVrPacx45bB9+3bcdNNN0Gq1uOGGG7BixQqPx0m+p7H/hj799FN06tQJOp0O3bp1u+rvidzvl909fj766KOQJMnldt9993n6MJwaczwrVqy4KladTueyTXN6fe66666rjkeSJAwdOtS5jZyvj6f+7jb1fc/1auzxfP7557j33nvRokUL6PV6pKWlYePGjS7bvPjii1e9Pp06dfLgUVzR2OPZvn17rb9vubm5LtvJ9frIjUlbH7Fnzx68++676N69u9yheF1hYSFuu+02qNVqfPPNNzh69CjefPNNREZGyh2a173++utYsmQJ/vGPf+DYsWN4/fXXMX/+fLzzzjtyh+ZRZWVl6NGjBxYvXlzr+vnz52PRokVYunQpdu/ejZCQEAwaNMgvPuzVVN+5KC8vx969ezFr1izs3bsXn3/+OY4fP47f/OY3MkTqWdf6nXBYu3YtfvzxRyQmJnopMvJn//nPfzB16lTMnj0be/fuRY8ePTBo0CDk5+fXuv327dvx8MMPY9u2bUhPT0dSUhIGDhyI8+fPezly92vsuXDIysrCX//6V9x+++1eitQ7Gns+TCYT7r33XmRlZeGzzz7D8ePH8f7776Nly5ZejtwzGns+Vq9ejeeeew6zZ8/GsWPHsGzZMvznP//B3/72Ny9H7n4NHa8cTp8+jaFDh+Luu+/G/v37MWXKFDz++ONXfeAm/9bYf0O7du3Cww8/jHHjxmHfvn144IEH8MADD+Dw4cPObeR8v+yp8fO+++5DTk6O8/bxxx97/FiApo2Ber3eJdYzZ864rG9Or8/nn3/uciyHDx+GUqnE7373O5ft5Hp9PPF3t6nve9yhscezY8cO3HvvvVi/fj0yMjJw9913Y9iwYdi3b5/Ldl27dnV5fX744QdPhH+Vxh6Pw/Hjx13ijY2Nda6T8/WRnSDZlZSUiPbt24tNmzaJO++8U0yePFnukLxq+vTpol+/fnKH4ROGDh0q/vjHP7ose/DBB8WoUaNkisj7AIi1a9c679tsNhEfHy/+/ve/O5cVFRUJrVYrPv74Yxki9J6a56I2P/30kwAgzpw5452gZFDXeTh37pxo2bKlOHz4sEhOThYLFizwemzkX2655RYxceJE532r1SoSExPFvHnzGvR4i8UiwsLCxIcffuipEL2mKefCYrGIvn37in/9619i7NixYvjw4V6I1Dsaez6WLFki2rZtK0wmk7dC9KrGno+JEyeKe+65x2XZ1KlTxW233ebROL2tIeP2s88+K7p27eqy7KGHHhKDBg3yYGTkaxr7b+j3v/+9GDp0qMuy1NRU8ac//UkIIf/7ZU+Mn3KOI409nuXLl4vw8PA6n6+5vz4LFiwQYWFhorS01LnMV8Z5d/3dvd5z5C4NOZ7adOnSRbz00kvO+7NnzxY9evRwX2BN1JDj2bZtmwAgCgsL69zGV14fObDS1gdMnDgRQ4cOxYABA+QORRZffvkl+vTpg9/97neIjY1Fr1698P7778sdliz69u2LLVu24MSJEwCAAwcO4IcffsDgwYNljkw+p0+fRm5ursu/j/DwcKSmpiI9PV3GyHxDcXExJElCRESE3KF4lc1mw+jRozFt2jR07dpV7nDID5hMJmRkZLj8rVEoFBgwYECD/9aUl5fDbDYjKirKU2F6RVPPxZw5cxAbG4tx48Z5I0yvacr5+PLLL5GWloaJEyciLi4ON954I1599VVYrVZvhe0xTTkfffv2RUZGhvOrjL/++ivWr1+PIUOGeCVmX5Kenn7Ve/5BgwbxPU0Aacq/oWv93sj5ftmT4+f27dsRGxuLjh074sknn8Tly5fdGnttmno8paWlSE5ORlJSEoYPH44jR4441zX312fZsmUYOXIkQkJCXJbL8fo0xbX+/bjjHMnJZrOhpKTkqn8/J0+eRGJiItq2bYtRo0YhOztbpggbpmfPnkhISMC9996LnTt3Opc399fneqnkDiDQrVmzBnv37sWePXvkDkU2v/76K5YsWYKpU6fib3/7G/bs2YM///nP0Gg0GDt2rNzhedVzzz0Hg8GATp06QalUwmq14pVXXsGoUaPkDk02jl42cXFxLsvj4uKu6nMTaCorKzF9+nQ8/PDD0Ov1cofjVa+//jpUKhX+/Oc/yx0K+YlLly7BarXW+rfml19+adBzTJ8+HYmJic3+ImxTzsUPP/yAZcuWYf/+/V6I0Luacj5+/fVXbN26FaNGjcL69etx6tQpPPXUUzCbzZg9e7Y3wvaYppyPP/zhD7h06RL69esHIQQsFgueeOIJv2iP0Fi5ubm1njuDwYCKigoEBQXJFBl5S1P+DdX1e+N4Lyzn+2VPjZ/33XcfHnzwQaSkpCAzMxN/+9vfMHjwYKSnp0OpVLr1GKpryvF07NgRH3zwAbp3747i4mK88cYb6Nu3L44cOYJWrVo169fnp59+wuHDh7Fs2TKX5XK9Pk1xrb+7hYWF1/07LKc33ngDpaWl+P3vf+9clpqaihUrVqBjx47IycnBSy+9hNtvvx2HDx9GWFiYjNFeLSEhAUuXLkWfPn1gNBrxr3/9C3fddRd2796Nm266yS1/Y5ozJm1ldPbsWUyePBmbNm26qlF5ILHZbOjTpw9effVVAECvXr1w+PBhLF26NOCStp988glWrVqF1atXo2vXrs6eO4mJiQF3Lqh+ZrMZv//97yGEwJIlS+QOx6syMjLw9ttvY+/evZAkSe5wiADYJxNds2YNtm/fHnBjeklJCUaPHo33338fMTExcofjE2w2G2JjY/Hee+9BqVSid+/eOH/+PP7+9783+6RtU2zfvh2vvvoq/vnPfyI1NRWnTp3C5MmTMXfuXMyaNUvu8IhIRnWNnyNHjnT+3K1bN3Tv3h3t2rXD9u3b0b9/fzlCrVNaWhrS0tKc9/v27YvOnTvj3Xffxdy5c2WM7PotW7YM3bp1wy233OKyvDm9Pv5s9erVeOmll/C///3PpQds9W/qdu/eHampqUhOTsYnn3zic9+I6tixIzp27Oi837dvX2RmZmLBggX497//LWNkvoHtEWSUkZGB/Px83HTTTVCpVFCpVPjuu++waNEiqFQqv/gKXUMkJCSgS5cuLss6d+7s8+X7njBt2jQ899xzGDlyJLp164bRo0fjmWeewbx58+QOTTbx8fEAgLy8PJfleXl5znWBxpGwPXPmDDZt2hRwVbbff/898vPz0bp1a+ffzjNnzuAvf/kL2rRpI3d41EzFxMRAqVQ26W/NG2+8gddeew3ffvutX0wo2thzkZmZiaysLAwbNsz5b3LlypX48ssvoVKpkJmZ6a3QPaIpvxsJCQno0KGDS7VR586dkZubC5PJ5NF4Pa0p52PWrFkYPXo0Hn/8cXTr1g2//e1v8eqrr2LevHmw2WzeCNtnxMfH13ru9Ho9q2wDRFP+DdX1e+PYXs73y94aP9u2bYuYmBicOnXqumOuz/Ucj4NarUavXr2csTbX16esrAxr1qxpUJLPW69PU1zr7647XnM5rFmzBo8//jg++eSTa37LKyIiAh06dPDJ16c2t9xyizPW5vr6uAuTtjLq378/Dh06hP379ztvffr0wahRo7B//36f+1qBp9x22204fvy4y7ITJ04gOTlZpojkU15eDoXC9Z+lUqkMuA801aWkpCA+Ph5btmxxLjMYDNi9e7fLFe1A4UjYnjx5Eps3b0Z0dLTcIXnd6NGjcfDgQZe/nYmJiZg2bRpn36Ym02g06N27t8vfGpvNhi1bttT7t2b+/PmYO3cuNmzYgD59+ngjVI9r7Lno1KnTVe9nfvOb3zhnaU5KSvJm+G7XlN+N2267DadOnXIZv0+cOIGEhARoNBqPx+xJTTkfdb2/AQAhhOeC9UFpaWku5w4ANm3aFJDvaQJVU/4NXev3Rs73y94aP8+dO4fLly8jISHBLXHXpanHU53VasWhQ4ecsTbH1wcAPv30UxiNRjzyyCPX3I+3Xp+muNa/H3e85t728ccf47HHHsPHH3+MoUOHXnP70tJSZGZm+uTrU5v9+/c7Y22Or49byTwRGtVw5513ismTJ8sdhlf99NNPQqVSiVdeeUWcPHlSrFq1SgQHB4uPPvpI7tC8buzYsaJly5Zi3bp14vTp0+Lzzz8XMTEx4tlnn5U7NI8qKSkR+/btE/v27RMAxFtvvSX27dsnzpw5I4QQ4rXXXhMRERHif//7nzh48KAYPny4SElJERUVFTJH7n71nQuTySR+85vfiFatWon9+/eLnJwc581oNModultd63eipuTkZLFgwQLvBkl+Z82aNUKr1YoVK1aIo0ePigkTJoiIiAiRm5srhBBi9OjR4rnnnnNu/9prrwmNRiM+++wzl3+PJSUlch2C2zT2XNTkK7NKu0tjz0d2drYICwsTkyZNEsePHxfr1q0TsbGx4uWXX5brENyqsedj9uzZIiwsTHz88cfi119/Fd9++61o166d+P3vfy/XIbjNtcar5557TowePdq5/a+//iqCg4PFtGnTxLFjx8TixYuFUqkUGzZskOsQSAaN/Te0c+dOoVKpxBtvvCGOHTsmZs+eLdRqtTh06JBzGznfL7t7/CwpKRF//etfRXp6ujh9+rTYvHmzuOmmm0T79u1FZWWlzx3PSy+9JDZu3CgyMzNFRkaGGDlypNDpdOLIkSMux9xcXh+Hfv36iYceeuiq5XK/Pp74u3utc+RLx7Nq1SqhUqnE4sWLXf79FBUVObf5y1/+IrZv3y5Onz4tdu7cKQYMGCBiYmJEfn6+zx3PggULxBdffCFOnjwpDh06JCZPniwUCoXYvHmzcxs5Xx+5MWnrYwIxaSuEEF999ZW48cYbhVarFZ06dRLvvfee3CHJwmAwiMmTJ4vWrVsLnU4n2rZtK55//nm/S8jVtG3bNgHgqtvYsWOFEELYbDYxa9YsERcXJ7Rarejfv784fvy4vEF7SH3n4vTp07WuAyC2bdsmd+huda3fiZqYtCV3eeedd0Tr1q2FRqMRt9xyi/jxxx+d6+68806X38Hk5ORaf09nz57t/cA9oDHnoiZ/S9oK0fjzsWvXLpGamiq0Wq1o27ateOWVV4TFYvFy1J7TmPNhNpvFiy++KNq1ayd0Op1ISkoSTz31lCgsLPR+4G52rfFq7Nix4s4777zqMT179hQajUa0bdtWLF++3Otxk/wa+zflk08+ER06dBAajUZ07dpVfP311y7r5X6/7M7xs7y8XAwcOFC0aNFCqNVqkZycLMaPH+/VBE1jjmfKlCnObePi4sSQIUPE3r17XZ6vOb0+Qgjxyy+/CADi22+/veq55H59PPV3t75z5EmNPZ4777zzmp+THnroIZGQkCA0Go1o2bKleOihh8SpU6d88nhef/115/uDqKgocdddd4mtW7de9bxyvT5yk4QIsO8kEREREREREREREfkw9rQlIiIiIiIiIiIi8iFM2hIRERERERERERH5ECZtiYiIiIiIiIiIiHwIk7ZEREREREREREREPoRJWyIiIiIiIiIiIiIfwqQtERERERERERERkQ9h0paIiIiIiIiIiIjIhzBpS0RERERERERERORDmLQlkokQAhMmTEBUVBQkScL+/ftx1113YcqUKR7d74svvoiePXt6dB+SJOGLL76oc31WVpbzmAFg+/btkCQJRUVFHo2LiIj8x7XGmqY8T83xSQ4NiaHmuLlixQpERER4JT4iImrernesc9f421Rt2rTBwoUL691G7hiJ3EUldwBEgWrDhg1YsWIFtm/fjrZt2yImJgaff/451Gq13KFdt5ycHERGRjZ4+759+yInJwfh4eEA7B8+p0yZwiQuERG5zYsvvogvvvjiqg+pjR2zPC0pKQk5OTmIiYlp8GMeeughDBkyxHm/rmMlIiKqOc5s374dd999NwoLCxt0AVDucXPPnj0ICQmRbf9E3sSkLZFMMjMzkZCQgL59+zqXRUVFyRiR+8THxzdqe41G0+jHEBERuYOvjT9KpbLRMQUFBSEoKMhDERERkT9pyjgDACaTySc+t7Vo0ULW/RN5E9sjEMng0UcfxdNPP43s7GxIkoQ2bdoAgEt7hF9++QXBwcFYvXq183GffPIJgoKCcPToUQBAUVERHn/8cbRo0QJ6vR733HMPDhw44LKv1157DXFxcQgLC8O4ceNQWVlZb2xWqxXjxo1DSkoKgoKC0LFjR7z99ttXbffBBx+ga9eu0Gq1SEhIwKRJk5zran4d5aeffkKvXr2g0+nQp08f7Nu3z+W5qn/Nc/v27XjsscdQXFwMSZIgSRJefPFFzJkzBzfeeONVcfTs2ROzZs2q95iIiMh3vPfee0hMTITNZnNZPnz4cPzxj3903l+yZAnatWsHjUaDjh074t///ne9zzt9+nR06NABwcHBaNu2LWbNmgWz2QzA/g2Ol156CQcOHHCOLStWrABw7a9QHj58GIMHD0ZoaCji4uIwevRoXLp0qc7tL1++jIcffhgtW7ZEcHAwunXrho8//thlG5vNhvnz5+OGG26AVqtF69at8corrwCo/Wur69evR4cOHRAUFIS7774bWVlZLs9XvT1CXcf6xz/+Effff7/L48xmM2JjY7Fs2bJ6ziwRETU3DR1nsrKycPfddwMAIiMjIUkSHn30UQD2z6aTJk3ClClTEBMTg0GDBgG4etw8d+4cHn74YURFRSEkJAR9+vTB7t2764ytvvHa4auvvsLNN98MnU6HmJgY/Pa3v3Wuq9ke4eTJk7jjjjug0+nQpUsXbNq06XpOHZFPYaUtkQzefvtttGvXDu+99x727NkDpVJ51TadOnXCG2+8gaeeegr9+vWDQqHAE088gddffx1dunQBAPzud79DUFAQvvnmG4SHh+Pdd99F//79ceLECURFReGTTz7Biy++iMWLF6Nfv37497//jUWLFqFt27Z1xmaz2dCqVSt8+umniI6Oxq5duzBhwgQkJCTg97//PQD7B+mpU6fitddew+DBg1FcXIydO3fW+nylpaW4//77ce+99+Kjjz7C6dOnMXny5Dr337dvXyxcuBAvvPACjh8/DgAIDQ1FUVERXnrpJezZswc333wzAGDfvn04ePAgPv/884adeCIikt3vfvc7PP3009i2bRv69+8PACgoKMCGDRuwfv16AMDatWsxefJkLFy4EAMGDMC6devw2GOPoVWrVs4PlzWFhYVhxYoVSExMxKFDhzB+/HiEhYXh2WefxUMPPYTDhw9jw4YN2Lx5MwA4W/LUp6ioCPfccw8ef/xxLFiwABUVFZg+fTp+//vfY+vWrbU+prKyEr1798b06dOh1+vx9ddfY/To0WjXrh1uueUWAMCMGTPw/vvvY8GCBejXrx9ycnLwyy+/1Pp8Z8+exYMPPoiJEydiwoQJ+Pnnn/GXv/ylzpjrOtYOHTrgjjvuQE5ODhISEgAA69atQ3l5OR566KFrngsiImo+GjrOJCUl4b///S9GjBiB48ePQ6/Xu3xz48MPP8STTz5Z72e9O++8Ey1btsSXX36J+Ph47N2796oLs9XVN14DwNdff43f/va3eP7557Fy5UqYTCbn+4OabDYbHnzwQcTFxWH37t0oLi72+BwxRF4liEgWCxYsEMnJyS7L7rzzTjF58mSXZUOHDhW333676N+/vxg4cKCw2WxCCCG+//57odfrRWVlpcv27dq1E++++64QQoi0tDTx1FNPuaxPTU0VPXr0aFSsEydOFCNGjHDeT0xMFM8//3yd2wMQa9euFUII8e6774ro6GhRUVHhXL9kyRIBQOzbt08IIcS2bdsEAFFYWCiEEGL58uUiPDz8qucdPHiwePLJJ533n376aXHXXXc16liIiEh+w4cPF3/84x+d9999912RmJgorFarEEKIvn37ivHjx7s85ne/+50YMmSI8371saY2f//730Xv3r2d92fPnl3r+Ff9eU6fPu0yPs2dO1cMHDjQZfuzZ88KAOL48eMNOVQhhH0s/8tf/iKEEMJgMAitVivef//9WretGcOMGTNEly5dXLaZPn16veNmXcfapUsX8frrrzvvDxs2TDz66KMNPg4iIvJ9jR1nan4Wc7jzzjtFr169rnp8zc96YWFh4vLly02Ot+Z4nZaWJkaNGlXn9snJyWLBggVCCCE2btwoVCqVOH/+vHP9N998c833CETNBdsjEPm4Dz74AAcPHsTevXuxYsUKSJIEADhw4ABKS0sRHR2N0NBQ5+306dPIzMwEABw7dgypqakuz5eWlnbNfS5evBi9e/dGixYtEBoaivfeew/Z2dkAgPz8fFy4cMFZHXUtx44dQ/fu3aHT6RoVQ23Gjx+Pjz/+GJWVlTCZTFi9erXLV2mJiKh5GDVqFP773//CaDQCAFatWoWRI0dCobC/NT127Bhuu+02l8fcdtttOHbsWJ3P+Z///Ae33XYb4uPjERoaipkzZzrHrqY6cOAAtm3b5jLOdurUCQCcY21NVqsVc+fORbdu3RAVFYXQ0FBs3LjRGcuxY8dgNBobNY42ZSyvzeOPP47ly5cDAPLy8vDNN99wHCUi8jONHWfq07t373rX79+/H7169WrU3CzXGq/379/fqDEyKSkJiYmJzmVNHSOJfBHbIxD5uAMHDqCsrAwKhcLlK42lpaVISEjA9u3br3pMQ2b9rMuaNWvw17/+FW+++SbS0tIQFhaGv//9786+RHJOdDJs2DBotVqsXbsWGo0GZrMZ//d//ydbPERE1DTDhg2DEAJff/01br75Znz//fdYsGBBk58vPT0do0aNwksvvYRBgwYhPDwca9aswZtvvnldcZaWlmLYsGF4/fXXr1rnGI9r+vvf/463334bCxcuRLdu3RASEoIpU6bAZDIBkHccHTNmDJ577jmkp6dj165dSElJwe233y5bPERE5H7uHGdCQkLcuq+GjNecWJPoCiZtiXxYQUEBHn30UTz//PPIycnBqFGjsHfvXgQFBeGmm25Cbm4uVCqVcyKzmjp37ozdu3djzJgxzmU//vhjvfvcuXMn+vbti6eeesq5rHo1UVhYGNq0aYMtW7bU2VewZgz//ve/UVlZ6ay2vVYMGo0GVqv1quUqlQpjx47F8uXLodFoMHLkSA7qRETNkE6nw4MPPohVq1bh1KlT6NixI2666Sbn+s6dO2Pnzp0YO3asc9nOnTudPd1r2rVrF5KTk/H88887l505c8Zlm7rGlvrcdNNN+O9//4s2bdpApWrY2+adO3di+PDheOSRRwDY++2dOHHCGXv79u0RFBSELVu24PHHH7/m83Xu3Blffvmly7KmjqPR0dF44IEHsHz5cqSnp+Oxxx5r0DEREVHz0dhxRqPRAECjx0gA6N69O/71r3+hoKCgQdW2DRmvu3fvji1btjRojOrcuTPOnj3rUtx0rTGSqDlhewQiH/bEE08gKSkJM2fOxFtvvQWr1Yq//vWvAIABAwYgLS0NDzzwAL799ltkZWVh165deP755/Hzzz8DACZPnowPPvgAy5cvx4kTJzB79mwcOXKk3n22b98eP//8MzZu3IgTJ05g1qxZ2LNnj8s2L774It58800sWrQIJ0+exN69e/HOO+/U+nx/+MMfIEkSxo8fj6NHj2L9+vV444036o2hTZs2KC0txZYtW3Dp0iWUl5c71z3++OPYunUrNmzYwK90EhE1Y6NGjcLXX3+NDz74AKNGjXJZN23aNKxYsQJLlizByZMn8dZbb+Hzzz93joE1tW/fHtnZ2VizZg0yMzOxaNEirF271mWbNm3a4PTp09i/fz8uXbrkbM1Qn4kTJ6KgoAAPP/ww9uzZg8zMTGzcuBGPPfZYnR9u27dvj02bNmHXrl04duwY/vSnPyEvL8+5XqfTYfr06Xj22WexcuVKZGZm4scff8SyZctqfb4nnngCJ0+exLRp03D8+HGsXr0aK1asqDfu+o718ccfx4cffohjx465JMWJiMg/NHacSU5OhiRJWLduHS5evIjS0tIG7+vhhx9GfHw8HnjgAezcuRO//vor/vvf/yI9Pb3W7RsyXs+ePRsff/wxZs+ejWPHjuHQoUO1fuMFsH8m7tChA8aOHYsDBw7g+++/d0kIEzV7cjfVJQpU15qI7MMPPxQhISHixIkTzvW7d+8WarVarF+/XghhbzL/9NNPi8TERKFWq0VSUpIYNWqUyM7Odj7mlVdeETExMSI0NFSMHTtWPPvss/VORFZZWSkeffRRER4eLiIiIsSTTz4pnnvuuases3TpUtGxY0ehVqtFQkKCePrpp53rUKPxe3p6uujRo4fQaDSiZ8+e4r///e81m98/8cQTIjo6WgAQs2fPdtn37bffLrp27VrnMRARke+zWq0iISFBABCZmZlXrf/nP/8p2rZtK9RqtejQoYNYuXKly/qaY820adNEdHS0CA0NFQ899JBYsGCBy+RclZWVYsSIESIiIkIAEMuXL7/qeWpOziKEECdOnBC//e1vRUREhAgKChKdOnUSU6ZMcU4MWtPly5fF8OHDRWhoqIiNjRUzZ84UY8aMEcOHD3c59pdfflkkJycLtVotWrduLV599dU6Y/jqq6/EDTfcILRarbj99tvFBx98UO9EZHUdqxBC2Gw2kZyc7DKpGxER+ZfGjjNz5swR8fHxQpIkMXbsWCFE7ZNkC3H1+JuVlSVGjBgh9Hq9CA4OFn369BG7d++uM7ZrjddCCPHf//5X9OzZU2g0GhETEyMefPBB57rqE5EJIcTx48dFv379hEajER06dBAbNmzgRGTkNyQhhJAhV0xE1CRCCLRv3x5PPfUUpk6dKnc4REREzUppaSlatmyJ5cuX48EHH5Q7HCIiIiKqA3vaElGzcfHiRaxZswa5ubnsw0dERNQINpsNly5dwptvvomIiAj85je/kTskIiIiIqoHk7ZE1GzExsYiJiYG7733HiIjI+UOh4iIqNnIzs5GSkoKWrVqhRUrVjR4YjUiIiIikgfbIxARERERERERERH5EIXcARARERERERERERHRFUzaEhEREREREREREfkQJm2JiIiIiIiIiIiIfAiTtkREREREREREREQ+hElbIiIiIiIiIiIiIh/CpC0RERERERERERGRD2HSloiIiIiIiIiIiMiHMGlLRERERERERERE5EOYtCUiIiIiIiIiIiLyIUzaEhEREREREREREfkQJm2JiIiIiIiIiIiIfAiTtkREREREREREREQ+hElbIiIiIiIiIiIiIh/CpC0RERERERERERGRD2HSloiIiIiIiIiIiMiHMGlLRERERERERERE5EOYtCUiIiIiIiIiIiLyIUzaEhEREREREREREfkQldwBNAc2mw0XLlxAWFgYJEmSOxwiIvIQIQRKSkqQmJgIhYLXNRuK4yQRUWDgONl4HCOJiAKDJ8ZIJm0b4MKFC0hKSpI7DCIi8pKzZ8+iVatWcofRbHCcJCIKLBwnG45jJBFRYHHnGMmkbQOEhYUBsJ94vV4vczREROQpBoMBSUlJzr/71DAcJ4mIAgPHycbjGElEFBg8MUYyadsAjq+x6PV6DrRERAGAX19sHI6TRESBheNkw3GMJCIKLO4cI9mIiIiIiIiIiIiIiMiHMGlLRERERERERERE5EOYtCUiIiIiIiIiIiLyIUzaEhEREREREREREfkQWZO2O3bswLBhw5CYmAhJkvDFF1+4rBdC4IUXXkBCQgKCgoIwYMAAnDx50mWbgoICjBo1Cnq9HhERERg3bhxKS0tdtjl48CBuv/126HQ6JCUlYf78+Z4+NCIiIiIiIiIiIqImkTVpW1ZWhh49emDx4sW1rp8/fz4WLVqEpUuXYvfu3QgJCcGgQYNQWVnp3GbUqFE4cuQINm3ahHXr1mHHjh2YMGGCc73BYMDAgQORnJyMjIwM/P3vf8eLL76I9957z+PHR0RERERERERERNRYKjl3PnjwYAwePLjWdUIILFy4EDNnzsTw4cMBACtXrkRcXBy++OILjBw5EseOHcOGDRuwZ88e9OnTBwDwzjvvYMiQIXjjjTeQmJiIVatWwWQy4YMPPoBGo0HXrl2xf/9+vPXWWy7JXSIiIiIiIiIiIiJf4LM9bU+fPo3c3FwMGDDAuSw8PBypqalIT08HAKSnpyMiIsKZsAWAAQMGQKFQYPfu3c5t7rjjDmg0Guc2gwYNwvHjx1FYWFjrvo1GIwwGg8uNiIiIiIiIiIiIyBt8Nmmbm5sLAIiLi3NZHhcX51yXm5uL2NhYl/UqlQpRUVEu29T2HNX3UdO8efMQHh7uvCUlJV3/ARERERERERERERE1gKztEXzVjBkzMHXqVOd9g8HglsStyWTCvn37rlreq1cvl0pgIiIiko8QwvltnMjISEiSJHNERERE3me1WpGVleW836ZNGyiVSvkCIiIKMD6btI2PjwcA5OXlISEhwbk8Ly8PPXv2dG6Tn5/v8jiLxYKCggLn4+Pj45GXl+eyjeO+Y5uatFottFqtW46jun379iH97UXoVO14fsnJASb/GampqW7fHxERETVeYWEhtn92AABw1//1QFRUlMwREREReV9WVhbWr1yGuJgY5F26hCFjxqFdu3Zyh0VEFDB8tj1CSkoK4uPjsWXLFucyg8GA3bt3Iy0tDQCQlpaGoqIiZGRkOLfZunUrbDabMwmalpaGHTt2wGw2O7fZtGkTOnbsiMjISC8dzRWdEhLQu00b5616ApeIiIh8Q1hoOMJCw+UOg4iISFZxMTFoFR+HuJgYuUMhIgo4siZtS0tLsX//fuzfvx+AffKx/fv3Izs7G5IkYcqUKXj55Zfx5Zdf4tChQxgzZgwSExPxwAMPAAA6d+6M++67D+PHj8dPP/2EnTt3YtKkSRg5ciQSExMBAH/4wx+g0Wgwbtw4HDlyBP/5z3/w9ttvu7Q/ICIiIiIiIqLGsVqtyMzMdLlZrVa5wyIi8guytkf4+eefcffddzvvOxKpY8eOxYoVK/Dss8+irKwMEyZMQFFREfr164cNGzZAp9M5H7Nq1SpMmjQJ/fv3h0KhwIgRI7Bo0SLn+vDwcHz77beYOHEievfujZiYGLzwwguYMGGC9w6UiIiIiIiIyM9Ub6EAgG0UiIjcSNak7V133QUhRJ3rJUnCnDlzMGfOnDq3iYqKwurVq+vdT/fu3fH99983OU4iIiIiIiIiupqjhQIREbmXz/a0JSIiIiIiIiIiIgpETNoSERERERERERER+RAmbYmIiIiIiIiIiIh8CJO2RERERERERERERD6ESVsiIiIiIiIiIiIiH6KSOwAiIiIiIiIikpfVakVWVpbz/pkzZyBsQr6AiIgCHJO2RERERERERAEuKysL61cuQ1xMDADg8ImTSIqLBRAvb2BERAGK7RGIiIiaqSVLlqB79+7Q6/XQ6/VIS0vDN99841x/1113QZIkl9sTTzzh8hzZ2dkYOnQogoODERsbi2nTpsFisXj7UIiIiNyKY2TTxMXEoFV8HFrFxyEmMlLucIiIAhorbYmIiJqpVq1a4bXXXkP79u0hhMCHH36I4cOHY9++fejatSsAYPz48ZgzZ47zMcHBwc6frVYrhg4divj4eOzatQs5OTkYM2YM1Go1Xn31Va8fDxERkbtwjCQiouaOSVsiIqJmatiwYS73X3nlFSxZsgQ//vij8wNpcHAw4uNr/1rjt99+i6NHj2Lz5s2Ii4tDz549MXfuXEyfPh0vvvgiNBqNx4+BiIjIEzhGEhFRc8f2CERERH7AarVizZo1KCsrQ1pamnP5qlWrEBMTgxtvvBEzZsxAeXm5c116ejq6deuGuLg457JBgwbBYDDgyJEjde7LaDTCYDC43IiIiHwVx0giImqOWGlLRETUjB06dAhpaWmorKxEaGgo1q5diy5dugAA/vCHPyA5ORmJiYk4ePAgpk+fjuPHj+Pzzz8HAOTm5rp8GAXgvJ+bm1vnPufNm4eXXnrJQ0dERETkHhwjPcNqtSIrKwsAcObMGQibkDcgIiI/xaQtERFRM9axY0fs378fxcXF+OyzzzB27Fh899136NKlCyZMmODcrlu3bkhISED//v2RmZmJdu3aNXmfM2bMwNSpU533DQYDkpKSrus4iIiI3I1jpGdkZWVh/cpliIuJweETJ5EUFwug9jYTRETUdGyPQERE1IxpNBrccMMN6N27N+bNm4cePXrg7bffrnXb1NRUAMCpU6cAAPHx8cjLy3PZxnG/rh5/AKDVap2zcTtu/kwIgYKCAgjBSiIiouaEY6TnxMXEoFV8HGIiI+UOhYjIbzFpS0RE5EdsNhuMRmOt6/bv3w8ASEhIAACkpaXh0KFDyM/Pd26zadMm6PV659dHCSgsLMRXK3agsLBQ7lCIiOg6cIwkIqLmhO0RiIiImqkZM2Zg8ODBaN26NUpKSrB69Wps374dGzduRGZmJlavXo0hQ4YgOjoaBw8exDPPPIM77rgD3bt3BwAMHDgQXbp0wejRozF//nzk5uZi5syZmDhxIrRarcxH51tCQ/yzUoqIyF9xjCQiouaOSVsiIqJmKj8/H2PGjEFOTg7Cw8PRvXt3bNy4Effeey/Onj2LzZs3Y+HChSgrK0NSUhJGjBiBmTNnOh+vVCqxbt06PPnkk0hLS0NISAjGjh2LOXPmyHhURERE149jJBERNXdM2hIRETVTy5Ytq3NdUlISvvvuu2s+R3JyMtavX+/OsIiIiGTHMZKIiJo7Jm2JiIgoYAkhnL1qIyMjIUmSzBERERERERFxIjIiIiIKYIWFhdj+2QFs/+wAJxojIiIiIiKfwUpbIiIiCmhhoeFyh0BEREREROSClbZEREREREREREREPoRJWyIiIiIiIiIiIiIfwqQtERERERERERERkQ9h0paIiIiIiIiIiIjIhzBpS0RERERERERERORDmLQlIiKigCSEQGFhIYTcgRAREREREdXApC0REREFpMLCQmz4eBeMlZVyh0JERNRsCMHLnURE3qCSOwAiIiIiuYQEh7ncr159K8kTEhERkc+xWSw4vnUjNs77AVarFZqIKMSG6+UOi4jIrzFpS0RERFTFUX3bOrEddDqd3OEQERHJzmazIf/wPpwvLXEuM5WX4WhJMUR8axkjIyLyb2yPQERERFRNzepbIiKiQHbhl6Mwl5ZAHRSMIX+ehlvHTIBCrUFFiQG2izlyh0dE5LeYtCUiIiIiIiKiq1grK3Du2BEAQI/f/A6db7sT8Z26IrpDZwCAregyLKUGOUMkIvJbTNoSERERERER0VWM+TkQwoagqBi07N7LuVwXGY24tjcAAEyXL8oVHhGRX2PSloiIiIiIiIhcCKsFFkMRAEDfOgWS5DpFZ2xKOwCApaQYVrPZ2+EREfk9Jm2JiIiIiIiIyIXNUAQIgeDwCGhCr+73HhIRCag1gBAoyDnv/QCJiPwck7ZERERERERE5EIYCgEAsW3a1rpekiQo9BEAgMtns70VFhFRwGDSloiIiIiIiIicyg3FEJUVAICY1sl1bqcIiwAAFOXmwGIyeSM0IqKAwaQtERERERERETkV5lwAAKhC9VBrdXVuJ2l1UGi0EMKGkkuckIyIyJ2YtCUiIiIiIiIiJ0N+HgBAGaa/5rbKkFAAQEnhZY/GREQUaJi0JSIiIiIiIiIAgM1mheFSPgBAFXL1BGQ1KYNCAAClBUzaEhG5E5O2RERERERERAQAKC0ogM1qBZRKKHRB19xeGRzsfJwQwtPhEREFDCZtiYiIiIiIiAgAUJyfCwCQgkMhSdI1t1dogyApFLCaTbBUTV5GRETXTyV3AERERERERETkfVarFVlZWQCAM2fOQNgEiqv62SqCQxv0HJJCgZCISJQWXIapxOCpUImIAo5PV9parVbMmjULKSkpCAoKQrt27TB37lyXr1wIIfDCCy8gISEBQUFBGDBgAE6ePOnyPAUFBRg1ahT0ej0iIiIwbtw4lJaWevtwiIiI3GrJkiXo3r079Ho99Ho90tLS8M033zjXV1ZWYuLEiYiOjkZoaChGjBiBvLw8l+fIzs7G0KFDERwcjNjYWEybNg0Wi8Xbh0JEREQyyMrKwvqVy5Cx/n/YvvZTFBcXofSyvTet1MCkLQCERkUDAEylTNoSEbmLTydtX3/9dSxZsgT/+Mc/cOzYMbz++uuYP38+3nnnHec28+fPx6JFi7B06VLs3r0bISEhGDRoECorK53bjBo1CkeOHMGmTZuwbt067NixAxMmTJDjkIiIiNymVatWeO2115CRkYGff/4Z99xzD4YPH44jR44AAJ555hl89dVX+PTTT/Hdd9/hwoULePDBB52Pt1qtGDp0KEwmE3bt2oUPP/wQK1aswAsvvCDXIfksIQQKCwtRwH59RETNAi9sNlxcTAxaxcchJjIS1soKCGGDSqsF1JoGP4czactKWyIit/HppO2uXbswfPhwDB06FG3atMH//d//YeDAgfjpp58A2D9ALVy4EDNnzsTw4cPRvXt3rFy5EhcuXMAXX3wBADh27Bg2bNiAf/3rX0hNTUW/fv3wzjvvYM2aNbhw4YKMR0dERHR9hg0bhiFDhqB9+/bo0KEDXnnlFYSGhuLHH39EcXExli1bhrfeegv33HMPevfujeXLl2PXrl348ccfAQDffvstjh49io8++gg9e/bE4MGDMXfuXCxevBgmk0nmo/MtpeUl2P31CWz/7AAKCwvlDoeIiK6BFzabxlZRBgAIjYhqUD9bh9DIKACAuawUwmbzSGxERIHGp5O2ffv2xZYtW3DixAkAwIEDB/DDDz9g8ODBAIDTp08jNzcXAwYMcD4mPDwcqampSE9PBwCkp6cjIiICffr0cW4zYMAAKBQK7N69u9b9Go1GGAwGlxsREZEvs1qtWLNmDcrKypCWloaMjAyYzWaXMbJTp05o3bq1yxjZrVs3xMXFObcZNGgQDAaD80NtbQJ1nAwLDUdYaLjcYRARUQPwwmbTWCvKAQAhVUnYhtKFhkJSKCBsNpQX8eImEZE7+HTS9rnnnsPIkSPRqVMnqNVq9OrVC1OmTMGoUaMAALm59lktq3/YdNx3rMvNzUVsbKzLepVKhaioKOc2Nc2bNw/h4eHOW1JSkrsPjYiIyC0OHTqE0NBQaLVaPPHEE1i7di26dOmC3NxcaDQaREREuGxfc4ysbQx1rKsLx0kiImpOeGGz4a4kbSMb9ThJUiAoLAwAUHKx7vcQRETUcD6dtP3kk0+watUqrF69Gnv37sWHH36IN954Ax9++KFH9ztjxgwUFxc7b2fPnvXo/oiIiJqqY8eO2L9/P3bv3o0nn3wSY8eOxdGjRz26z+Y6TgohUFBQwL60REQBghc2G0fYbLBVVgC40u6gMYLC7N9GKcnPu8aWRETUECq5A6jPtGnTnNW2ANCtWzecOXMG8+bNw9ixYxEfHw8AyMvLQ0JCgvNxeXl56NmzJwAgPj4e+fn5Ls9rsVhQUFDgfHxNWq0WWq3WA0dERETkXhqNBjfccAMAoHfv3tizZw/efvttPPTQQzCZTCgqKnL5UJqXl+cc/+Lj45194quvd6yrS3MdJwsLC7H9swMAgLv+r4fM0RARkac5LmwWFxfjs88+w9ixY/Hdd995dJ8zZszA1KlTnfcNBkOzSdwKo30yb5VGA01QcKMfHxSmBwCUXrS/l7BarcjKynKub9OmDZRK5fUHSkQUIHy60ra8vBwKhWuISqUStqrG5ikpKYiPj8eWLVuc6w0GA3bv3o20tDQAQFpaGoqKipCRkeHcZuvWrbDZbEhNTfXCURAREXmPzWaD0WhE7969oVarXcbI48ePIzs722WMPHTokMvFzU2bNkGv16NLly5ej90b2JeWiChwOC5s9u7dG/PmzUOPHj3w9ttvIz4+3nlhs7qaFzYdFzKrr3esq4tWq4Ver3e5NRfCaK+yDYls3CRkDkFVx+qotM3KysL6lcuQsf5/WL9ymUsCl4iIrs2nK22HDRuGV155Ba1bt0bXrl2xb98+vPXWW/jjH/8IAJAkCVOmTMHLL7+M9u3bIyUlBbNmzUJiYiIeeOABAEDnzp1x3333Yfz48Vi6dCnMZjMmTZqEkSNHIjExUcajIyIiuj4zZszA4MGD0bp1a5SUlGD16tXYvn07Nm7ciPDwcIwbNw5Tp05FVFQU9Ho9nn76aaSlpeHWW28FAAwcOBBdunTB6NGjMX/+fOTm5mLmzJmYOHFis6ykJSIiqk9tFzZHjBgBoPYLm6+88gry8/Odc6T4+4VN4WiNENH41gjAlUrbkot5zjZEcTExaBUfV9/DiIioDj6dtH3nnXcwa9YsPPXUU8jPz0diYiL+9Kc/4YUXXnBu8+yzz6KsrAwTJkxAUVER+vXrhw0bNkCn0zm3WbVqFSZNmoT+/ftDoVBgxIgRWLRokRyHRERE5Db5+fkYM2YMcnJyEB4eju7du2Pjxo249957AQALFixwjntGoxGDBg3CP//5T+fjlUol1q1bhyeffBJpaWkICQnB2LFjMWfOHLkOiYiIyC14YbMJnJW2jZuEzMGRtDVXlKO8uMhdURERBSyfTtqGhYVh4cKFWLhwYZ3bSJKEOXPm1PsBMyoqCqtXr/ZAhERERPJZtmxZvet1Oh0WL16MxYsX17lNcnIy1q9f7+7QiIiIZMULm40jhIAwGgEAwfqIJj2HQqmEShcES2UFCs6fBXQhboyQiCjw+HTSloiIiIiIiKixeGGzcUwV5YCwAZIEbWhok59HFRQMS2UFLp8/h7B2Hd0YIRFR4PHpiciIiIiIiIiIyLPKDcUAAIVGe9Vk4I2hDrZX1xacP+uWuIiIAhmTtkREREREREQBrMJgAAAotLprbFk/VVAwAKDgwrnrjomIKNAxaUtEREREREQUwCpKqpK2uqDreh51VdK2MOfCdcdERBTomLQlIiIiIiIiCmAVVe0RlG6qtDVcyofVYrnuuIiIAhmTtkREREREREQBSgiBcje1R1Co1VBptYAQKLt8yR3hEREFLCZtiYiIiIiIiAKUzWyG1WwCcP1JW0mSEBoTCwAou3zxumMjIgpkTNoSERERERERBShzeZn9B7UGkuL6UwQh0S0AAKWX8q/7uYiIAplK7gACndlqxeHDh69a3qtXL2g0GhkiIiIiIiIiokBhrrAnbSWN1i3PF+pI2l6+CGivb2IzIqJAxqStzDLz81H42WdoefSYc9kvOTnA5D8jNTVVxsiIiIiIiIjI31nKywEAkub6WiM4hMbYk7Zlly4iqGVrtzwnEVEgYtLWB9zQogV6t2kjdxhEREQBTwgBm1EBYRNyh0JEROQVlsoKAIDkpm96hsRcqbRl0paIqOmYtCUiIiICkHPSgAMbc1BxIRT5BSa07uGeiiMiIiJfZqmwV9rCze0RKg3FsFktbnlOIqJAxKQtERERBTxjmRXfrfgVoqrA1lgikP9rhbxBEREReZjNaoXFWAkAkNTuqbTVBIdAF6ZHZYkBlgqOpURETXX9U0MSERERNXOXz1RCCCC+fRg08fYPmMUXTDh/rFjmyIiIiDynorgQEAKSQgmo1G573sj4BABXWi8QEVHjMWlLREREAc1UZkPpJTMgATcNaQm13ozQOCUAIOtAoczREREReU7Z5UsAAF1oKCRJctvzRia0BFCt9QIRETUak7ZEREQU0Iov2PvtJXePRHicvY9tSJQ9aZt7sgQ2TkpGRER+qvTyRQD2pK07RcYnAgDMTNoSETUZk7ZEREQUsIQNqCiyAQC63BnrXK4JlaBQSTBVWHH5LD9wEhGRfypzJG1Dwtz6vJGJjkpbtkcgImoqJm2JiIgoYFkrVIAAVFrJWWULAJIkISTSPl9rzgmDXOERERF5VGm19gjuFFFVacv2CERETcekLREREQUsa5m9DUJIpPqqXn7BkfYJWS4cZ9KWiIj8k6OnbVComyttqyYis1nMsJhMbn1uIqJAwaQtERERBSxrub2aNriqqra6kCj7ssILFRAW903OQkRE5AtsNivKCxyVtu5N2mqCgqEL0wMAKktL3PrcRESBgklbIiIiCkhlRSYIk73StrakrUqjgD7W3jLBalR6NTYiIiJPK718GTarFZAkaIKD3P78IdEtAAAVTNoSETUJk7ZEREQUkHJO2j9EakIlKFW1vyUKr0raCiPfMhERkX8pzL0AAFDpgiBJ7h/nQmPsSdvKEiZtiYiagp9AZCSEQPvz5xGTf1HuUIiIiALOxaxSAIBOX/fbIcfkZDYT3zIREZF/Kc7PA2BP2npCaEwsALZHICJqqqu/C0heY8nPR9u8PNgkCTaTCQqNRu6QiIiIAkZxXiUAQBNST9I2lklbIiLyT8X5uQAAlU7nkecPiY4BYG+P4Jm0MBGRf+MnEBlZL18GACiEgPn8eZmjISIiChw2q0Bxvj1pqw6qe5Kx8FitfXuTEkIIr8RGRETkDY5KW6XW85W2HEOJiBqPSVsZWS5dcv5szs6WMRIiImqO5s2bh5tvvhlhYWGIjY3FAw88gOPHj7tsc9ddd0GSJJfbE0884bJNdnY2hg4diuDgYMTGxmLatGmwWCzePBSvK7lshM0iAElApa07aRsarYWkAGCTYDV5Lz4iIiJPMzjbI3io0jbKXmlrNZthM5s9sg8iIn/GpK2MLFWVtgBgys7m1UciImqU7777DhMnTsSPP/6ITZs2wWw2Y+DAgSgrK3PZbvz48cjJyXHe5s+f71xntVoxdOhQmEwm7Nq1Cx9++CFWrFiBF154wduH41XFuRUAAIXWCkmqO2mrVCkQFm2vtjVX2LwSGxERXT9e2Ly24oue7WmrVKuh1NoTwuaKsmtsTURENbGnrUyEEM72CABgMxhgKy6GMiJCvqCIiKhZ2bBhg8v9FStWIDY2FhkZGbjjjjucy4ODgxEfH1/rc3z77bc4evQoNm/ejLi4OPTs2RNz587F9OnT8eKLL0Ljp/3Wi3LtrREUmmsnYsNjdTBcNMJcwYurRETNhePC5s033wyLxYK//e1vGDhwII4ePYqQkBDnduPHj8ecOXOc94ODg50/Oy5sxsfHY9euXcjJycGYMWOgVqvx6quvevV43M1cWYny4iIAnqu0BQB1cAisxkqYy5m0JSJqLFbaysRWVgZhNMIGoDQ0FIC92paIiKipiouLAQBRUVEuy1etWoWYmBjceOONmDFjBsrLy53r0tPT0a1bN8TFxTmXDRo0CAaDAUeOHKl1P0ajEQaDweXW3BTlOSptG5C0jXNUCTFpS0TUXGzYsAGPPvoounbtih49emDFihXIzs5GRkaGy3aOC5uOm16vd65zXNj86KOP0LNnTwwePBhz587F4sWLYTI17545jipbtS4ICpXaY/tRVyXIzWVM2hIRNRaTtjJxVNmW6XQoiggHAJhzcuQMiYiImjGbzYYpU6bgtttuw4033uhc/oc//AEfffQRtm3bhhkzZuDf//43HnnkEef63Nxcl4QtAOf93NzcWvc1b948hIeHO29JSUkeOCLPclbaaq3X3FYf60jasj0CEVFzxQubrhyTkAVHRXt0P+pge9LWwkpbIqJGY3sEmTj62ZYGBcFY9XUUG68+EhFRE02cOBGHDx/GDz/84LJ8woQJzp+7deuGhIQE9O/fH5mZmWjXrl2T9jVjxgxMnTrVed9gMDSrxK3NIlBWaK+QalClrSNpW8lKWyKi5qi+C5vJyclITEzEwYMHMX36dBw/fhyff/45gKZf2HzppZc8dCTu40zaRkZdY8vrow62f6vUXF7GOVyIiBqJSVuZWC9dAgCUBAXBprZ/HcVW7aouERFRQ02aNAnr1q3Djh070KpVq3q3TU1NBQCcOnUK7dq1Q3x8PH766SeXbfLy7B/k6uqDq9VqodVq3RC5PIzl9uraoDAVJOW1P0CGRNr7+gorYLXwAycRUXPDC5tXK863J51DIqNh9OB+VEHBACTYLGYYS0s8uCciIv/D9ggycVTalgQFwVyVtBVM2hIRUSMIITBp0iSsXbsWW7duRUpKyjUfs3//fgBAQkICACAtLQ2HDh1Cfn6+c5tNmzZBr9ejS5cuHolbbqZye3Wto+3Btai1SkBhT9ZajGyRQETUnDgubG7btq1RFzYB+8VLx4VMh4Zc2NTr9S43X3Sl0taz7REUSiV0ofYWCSV5bAdIRNQYTNrKxNEKoUKrvZK0NZshmnlDeyIi8p6JEyfio48+wurVqxEWFobc3Fzk5uaiosI+yVZmZibmzp2LjIwMZGVl4csvv8SYMWNwxx13oHv37gCAgQMHokuXLhg9ejQOHDiAjRs3YubMmZg4cWKzrqatj7nSXmkbWlVB2xAKtT1Za2bSloioWeCFzfoZqiptg6M82x4BAIL09jlcsn45iszMTGRmZsJqvXZPeSKiQMf2CDIQNhuE0f4lFJNSCZ1CAahUgMUCW9UHbSIiomtZsmQJAOCuu+5yWb58+XI8+uij0Gg02Lx5MxYuXIiysjIkJSVhxIgRmDlzpnNbpVKJdevW4cknn0RaWhpCQkIwduxYzJkzx5uH4lWOatmQKC3QwPlhJJUNMCphqWTSloioOZg4cSJWr16N//3vf84LmwAQHh6OoKAgZGZmYvXq1RgyZAiio6Nx8OBBPPPMM3Ve2Jw/fz5yc3P94sKmEALFF+2VtiGR0QBOeXR/wfoIFF44jzP7M6BQKJB36RKGjBnX5BYURESBgklbGVSvprWoVIAkQREcDJvBwL62RETUYNea0CMpKQnffffdNZ8nOTkZ69evd1dYPs9clXgNiWh4pa2kYnsEIqLmhBc261ZZWgJTVbGQpyciA4DgqhYRWtjQKj7uGlsTEZEDk7YyEJWVAABJo4GQJABwTdoqlXKGR0RE5NecSdtGtEeQ2B6BiKhZ4YXNujn62YZERkGpbvhY2FTB4REAAGtlBYTgOEpE1FDsaSsDmyNpW+0rNYrgYPs6VtoSERF5jLAJWIz2D/JN6WnL9ghERNTcOZK24S28U/UapNcDkgKw2VBRUuKVfRIR+QMmbWXgrLTVXZm1mklbIiIiz3O0N1CoJOhCG/6FI0d7BFbaEhFRc1dcNQlZeKx3kraSpICkCwIAlBZc9so+iYj8AZO2MrBVTUKmYKUtERGRV1XvZysppAY/TlJVVdoaBWzW+r9yS0RE5MsMVZOQeStpC+BK0rawwGv7JCJq7pi0lUF9lbaCSVsiIiKPcVTKNqafLVBVaVuV460oMUMIgYKCgmv2TCQiIvI1RXn2Slu9V5O29s+7rLQlImo4Jm1l4Ky0rZa0lVhpS0RE5HGOStvG9LMFAEkClBp71ra82ITCwkJ8tWIHCgsL3R4jERGRJzkrbVvEe22fjqRteVERhI2thoiIGoJJWxkITkRGREQkC2d7hEYmbQFAVfWQsiIzACA0RO+2uIiIiLxB2GwwXMwH0Lj2CDabDWfOnEFmZibOnDkDYWvkN03UakhKJYSwwVRW2rjHEhEFqIbPwEFuI6pX2lZU2H+unrTlVy2JiIg8wnIdSVt7pa1AeZHJzVERERF5R2lhAawWCySFAmHRMbhU0rAEav7lAmR+tRaX2qbg8ImTSIqLBdDwSl1JkqAMCoGl1ABTiaGJ0RMRBRafr7Q9f/48HnnkEURHRyMoKAjdunXDzz//7FwvhMALL7yAhIQEBAUFYcCAATh58qTLcxQUFGDUqFHQ6/WIiIjAuHHjUFoq39U9Wz2VtrDZoDCb5QiLiIjI711Xpa22qj1CEcdpIiJqnorzq/rZtoiFQqls1GNjo6PQKj4OMZGRTdq3IjgEAGAqKW7S44mIAo1PJ20LCwtx2223Qa1W45tvvsHRo0fx5ptvIrLaIDF//nwsWrQIS5cuxe7duxESEoJBgwahsioxCgCjRo3CkSNHsGnTJqxbtw47duzAhAkT5DgkALVPRCYplc4krrKqEpeIiIjcx2qxwWKyf5slJKKplbb2nrZERETNUXG+o5+t9yYhc1CFhAIAKosLOZEnEVED+HR7hNdffx1JSUlYvny5c1lKSorzZyEEFi5ciJkzZ2L48OEAgJUrVyIuLg5ffPEFRo4ciWPHjmHDhg3Ys2cP+vTpAwB45513MGTIELzxxhtITEz07kGh2kRk1SptAXu1rdVoZNKWiIjIAypLLADsk4rpQhv/FkiptidtK0otbo2LiIjI06xWK7KyspB1/BgAe6WttymDQyEplLCZTCi9mAfccIPXYyAiak58utL2yy+/RJ8+ffC73/0OsbGx6NWrF95//33n+tOnTyM3NxcDBgxwLgsPD0dqairS09MBAOnp6YiIiHAmbAFgwIABUCgU2L17d637NRqNMBgMLjd3qq3SFrjSIoFJWyIiIverKLG3NVBqJEiS1OjHO5K2lSVsj0BERM1LVlYW1q9chuxD+wEAVnXjv3FyvSSFAvqYGADAxcwTXt8/EVFz49NJ219//RVLlixB+/btsXHjRjz55JP485//jA8//BAAkJtr78cTF+f61Y64uDjnutzcXMTGul5FVKlUiIqKcm5T07x58xAeHu68JSUlue+ghLgyEVmNSlspKMi+3MSvXRIREblbhcGebFVpm/b2x9EeoaLE3PhZs4mIiGQWFxMDpc0KAAiOiJIlhvBY+2f3i5knr7ElERH5dNLWZrPhpptuwquvvopevXphwoQJGD9+PJYuXerR/c6YMQPFxcXO29mzZ9323ArLla9UXlVpW3WfE5ERERG5n6PSVqVpYtK2qqOCsAHGcqu7wiIiIvIaU3k5ACAkKlqW/etj4wEAl349CZuNYykRUX18OmmbkJCALl26uCzr3LkzsrOzAQDx8fY/+Hl5eS7b5OXlOdfFx8cjPz/fZb3FYkFBQYFzm5q0Wi30er3LzV0cVbSSWg2pxmydjonIWGlLRETkfs5KW03jWyMAgKSQrrRIKOUFViIial6EsMFYYU/aBslUaRsaGQlJqYS5sgJ7v9+BzMxMZGZmwmplApeIqCafTtredtttOH78uMuyEydOIDk5GYB9UrL4+Hhs2bLFud5gMGD37t1IS0sDAKSlpaGoqAgZGRnObbZu3QqbzYbU1FQvHIUrRxWtVKM1AnCl0lbJSlsiIiK3u95KW8C1RQIREVFzYjUaASEASYIuNEyWGCRJAQSFAAD2f70WGev/h/UrlyErK0uWeIiIfFmTPrW0bdsWly9fvmp5UVER2rZte91BOTzzzDP48ccf8eqrr+LUqVNYvXo13nvvPUycOBEAIEkSpkyZgpdffhlffvklDh06hDFjxiAxMREPPPAAAHtl7n333Yfx48fjp59+ws6dOzFp0iSMHDkSiYmJbou1oZyVtjVaI1RfxvYIRET+zVvjKLmqMNhbFCmvI2nrSPhWlFiusSURETUFx0jPsRjtE2KrtDpICvnqt6QQe8LYVmpAq/g4xFVNTkZERK5UTXlQVlZWrV9fMBqNOH/+/HUH5XDzzTdj7dq1mDFjBubMmYOUlBQsXLgQo0aNcm7z7LPPoqysDBMmTEBRURH69euHDRs2QFctKbpq1SpMmjQJ/fv3h0KhwIgRI7Bo0SK3xdkYjoRszUnIALZHICIKFN4aRwkQQqCwsBBAtUpbbdPaIwCAytEegZW2REQewTHSc6yV9qStspYCIm9ShITBBqDk8mVY+NmXiKhOjUrafvnll86fN27ciPDwcOd9q9WKLVu2oE2bNm4LDgDuv/9+3H///XWulyQJc+bMwZw5c+rcJioqCqtXr3ZrXE3laH1QW6UtJyIjIvJvcoyjga6wsBDbPzsAACgvtidcr6s9gtZRacuxmojInThGel71Sls5SWoNFFodbMZKFOXlAuqrC5qIiKiRSVtHywFJkjB27FiXdWq1Gm3atMGbb77ptuD8UYMqbZm0JSLySxxH5REWGg6bTSCnshhA0ycisz/WnrStLLE08ftKRERUG46RnueotFXpgmSOBFCFhcNkrERR7gXoklLkDoeIyCc16uOGzWYDYJ8AbM+ePYhh75lGq6+nrUulbdW5JiIi/8FxVD5Wo/3cSwpAobr+9ggVJWYoI90SGhERgWOkN1iMFQAApcyVtgCgCtPDdCkPRbk5iGvVRu5wiIh8UpNqRE6fPu3uOAKGo4pWqqfSVgIglZd7MywiIvIijqPeZzEJAPZKWUlqetJWqbnSHiGUSVsiIrfjGOk5lkrfaI8AAMrgUChUKpiNlTCXlcodDhGRT2ryF/u2bNmCLVu2ID8/33lV1OGDDz647sD8lcJin21a0miuWicplZDUagizGVIpBy4iIn/GcdS7LCb7OVZeR2sE4MokZpUlFoRed1RERFQbjpHuJ2w2WE1GAPJPRAYAkkKB8Ng4FF44j8rCy3KHQ0Tkk5qUtH3ppZcwZ84c9OnTBwkJCddVsRJopHqStoC9bYIwmyGVlXkzLCIi8iKOo95XvdL2ejgebzHZYLt6cnMiIrpOHCM9o8JQDAgBSZKg1PjGxF+R8YkovHAeFUzaEhHVqklJ26VLl2LFihUYPXq0u+Pxe85KW7W61vWSVguUlEAqZdKWiMhfcRz1PkelraNStqkUSgkqjcKetOW8oUREbscx0jMqigoAAJrgEJ9JhEfEJwAATIZimCrYHpCIqKYmlZuYTCb07dvX3bEEhPraIwBXJiMD+/oQEfktjqPeZ6maiOx6K20BQBdmv+Zts1z3UxERUQ0cIz2jvNCetNUGB8scyRXa4BAE6fUAgIsnj8scDRGR72nSJ5fHH38cq1evdncsAUGy2r9Lqaiv0haAgpW2RER+y13j6Lx583DzzTcjLCwMsbGxeOCBB3D8uOuHnsrKSkycOBHR0dEIDQ3FiBEjkJeX57JNdnY2hg4diuDgYMTGxmLatGmwWPwrI2l1U3sEAAgKs4/hVlbaEhG5HcdIz3AmbUNCZI7EVURcIgAg98RRmSMhIvI9TWqPUFlZiffeew+bN29G9+7doa6RgHzrrbfcEpw/amilrcRKWyIiv+WucfS7777DxIkTcfPNN8NiseBvf/sbBg4ciKNHjyKk6kPZM888g6+//hqffvopwsPDMWnSJDz44IPYuXMnAMBqtWLo0KGIj4/Hrl27kJOTgzFjxkCtVuPVV19174HLyF0TkQGALtT+erE9AhGR+3GMdA+r1YqsrCzn/fxz2QAAbbBvTaMZGZ+AnJO/4OKp4xBVPXeJiMiuSUnbgwcPomfPngCAw4cPu6zjH9l6CHFlIrK6Km2d7RFYaUtE5K/cNY5u2LDB5f6KFSsQGxuLjIwM3HHHHSguLsayZcuwevVq3HPPPQCA5cuXo3Pnzvjxxx9x66234ttvv8XRo0exefNmxMXFoWfPnpg7dy6mT5+OF198EZo6LjI2N1ZzVaWt2g3tEULZHoGIyFM4RrpHVlYW1q9chriYGABAbuZJqGFvj2CSNzQXoTExgCSh0lCMwpwLiEpsKXdIREQ+o0lJ223btrk7jsBgMsHxNqOuSltHewROREZE5L88NY4WFxcDAKKiogAAGRkZMJvNGDBggHObTp06oXXr1khPT8ett96K9PR0dOvWDXFxcc5tBg0ahCeffBJHjhxBr169rtqP0WiE0Wh03jcYDB45HncRQjiTtkqNBCEECgsL7eua8HxM2hIReQ7HSPeJi4lBq3h77GerRjxtSChM1qaMfp6hVKqgDQuH0VCEc0cPMWlLRFTN9ZebUINJFRVVP0iAqvZ8+ZX2CEzaEhFRw9lsNkyZMgW33XYbbrzxRgBAbm4uNBoNIiIiXLaNi4tDbm6uc5vqH0Yd6x3rajNv3jyEh4c7b0lJSW4+GvdyJGwBQKmSUFJmwO6vT+CHLw/DZGx8vZEuhElbIqLmJNDHSCEEYLH39PGlicgctOERAIDsIwdhtVqRmZnpvFmr5oQhIgpETaq0vfvuu+v9asrWrVubHJA/kyor7f9Xq+s8f1cmImNPWyIif+WJcXTixIk4fPgwfvjhh+sJrUFmzJiBqVOnOu8bDAaf+FBaF0fSVq1TQFLYz3tYaDhMFiMqKy82+vm0jkpb9rQlInI7jpHuZ66sAERVpW1QMFDiWwVC2ohI4GwWzh45iNOnT+Obf3+AuJgY5F26hCFjxqFdu3Zyh0hEJIsmJW0dPYYczGYz9u/fj8OHD2Ps2LHuiMs/VVxJ2tZFwZ62RER+z93j6KRJk7Bu3Trs2LEDrVq1ci6Pj4+HyWRCUVGRSyVRXl4e4uPjndv89NNPLs/nmDnbsU1NWq0W2qqLjM2B1WyfhEwT7J4vGDknImOlLRGR23GMdD9j1WdLSa2BpPC9L9tqw/RQqFQoLy5C6cV8l7YORESBrElJ2wULFtS6/MUXX0QpK0TrJFXa2yPU1c8WuDIRmcTzSETkt9w1jgoh8PTTT2Pt2rXYvn07UlJSXNb37t0barUaW7ZswYgRIwAAx48fR3Z2NtLS0gAAaWlpeOWVV5Cfn4/Y2FgAwKZNm6DX69GlS5emHJ7PcVTaaoKVbnk+9rQlIvIcjpHuZyy3J20VPjpxmqRQIqp1Ci79ehKXfj0pdzhERD7DrZfZHnnkEXzwwQfufEq/Ur09Ql0UjonIysshbDavxEVERL6hsePoxIkT8dFHH2H16tUICwtDbm4ucnNzUVHVQz08PBzjxo3D1KlTsW3bNmRkZOCxxx5DWloabr31VgDAwIED0aVLF4wePRoHDhzAxo0bMXPmTEycONHnKoWaymJyc9K2qqetsAEWE8dqIiJv4BjZdM6krdrzSVubzYYzZ84gMzMTZ86cgbA1bNKzmBR7C4TLWZmeDI+IqFlpUqVtXdLT06FzfL2fruZI2jak0lYI2EpKoAwP90poREQkv8aOo0uWLAEA3HXXXS7Lly9fjkcffRSAvWJJoVBgxIgRMBqNGDRoEP75z386t1UqlVi3bh2efPJJpKWlISQkBGPHjsWcOXOu+3h8hbvbI6i0CihUEmwWgcoyNrYlIvIGjpFNZywvBwBIGs8nmvMvFyDzq7W41DYFh0+cRFJcLIDaW0lUF5XcFgBQcDYL0V17ejZIIqJmoklJ2wcffNDlvhACOTk5+PnnnzFr1iy3BOaPpKqruvVV2kpKJWxKJRRWK6xFRUzaEhH5IXeNo0Jcu3pFp9Nh8eLFWLx4cZ3bJCcnY/369Q3eb3Pj7vYIkiRBF6pCeZEZxlL2SCAicieOke5XWWZvK+GNSlsAiI2OQqv4OORevNTgx0S2SoYkKVBeWIAIo9GD0RERNR9NStqG10gkKhQKdOzYEXPmzMHAgQPdEpg/khpQaQsANrXanrQtLvZGWERE5GUcRz1PCIHCwkIUFhY62yNog5Vua2egC7EnbSvLmLQlInInjpHu5+s9bQFArdMhpnUyLp45DWMJPwcTEQFNTNouX77c3XEEhIb0tAUAm0YDVFYyaUtE5Kc4jnpeYWEhtn92ACVlBliMegD29ghuS9qGqgFUoJKVtkREbsUx0r2EEDCW2dsjKNS+3Yc3sUMnXDxzGiYmbYmIAFxnT9uMjAwcO3YMANC1a1f06tXLLUH5rYqGVdpaq5K61iIOVkRE/ozjqGeFhYZDALhUlVfVBCtRXuSeJKu2ajIyJm2JiDyDY6R7mI2VEDYrgCvFQ47JwgA0arIwT0vs0BkHNn0Do4Gfg4mIgCYmbfPz8zFy5Ehs374dERERAICioiLcfffdWLNmDVq0aOHOGP1GgyttHUlbVtoSEfkljqPe5e6etgCgC7W/hTKyPQIRkVtxjHQvY5m9NQJUakgK+4ScTZ0szNMSO3QGAJhKS2CzWmWOhohIfk2aRvnpp59GSUkJjhw5goKCAhQUFODw4cMwGAz485//7O4Y/Uaj2iMAsBYXeTokIiKSAcdR7xE2AVH1uU8T3KS3PbVyJG1ZaUtE5F4cI93LWG5vjVDzM6hjsrCYyEg5wqpVeFw8NCGhgBAoKyyQOxwiItk1qdJ2w4YN2Lx5Mzp37uxc1qVLFyxevJjN4evTiInIALZHICLyVxxHvcdWLaeq1rkvaXulPYLZbc9JREQcI93NWF5q/0Hlu5OQOUiShMikZOT9cgSlhQVAWITcIRERyapJn15sNhvUtVSLqtVq2GzumeDDH0kVFfb/NzRpy0pbIiK/xHHUexxJW6VGgiRJjXqsEAKFhYUoLCxEzW5/zkpbtkcgInIrjpHu5WiPIKl9P2kLABGJSQCAsiJW2hIRNSlpe88992Dy5Mm4cOGCc9n58+fxzDPPoH///m4Lzt80tD2C1dkegZW2RET+iOOo9ziTturGJWwBoKTMgN1fn8APXx6GyWhyWacLtY/lRrZHICJyK46R7lVXewRfFdnKnrQtLSyUORIiIvk1KWn7j3/8AwaDAW3atEG7du3Qrl07pKSkwGAw4J133nF3jH5DamR7BBvbIxAR+SWOo95jq+peoFI3rTVCWGg4QkP0Vy3XhVyZiMzmI7NuExH5A46R7uVsj9DMKm0rDAZORkZEAa9JPW2TkpKwd+9ebN68Gb/88gsAoHPnzhgwYIBbg/M7DZ2IzNkegUlbIiJ/xHHUe66n0rY+jp62QgDGMjOCwprHh2EiIl/HMdJ9hBDNrj2CTh8OhUYDm8kEc1mJ3OEQEcmqUWUnW7duRZcuXWAwGCBJEu699148/fTTePrpp3HzzTeja9eu+P777z0Va7MnVVb1tL1W0tbRHqGoyNMhERGRF3Ec9b7qPW3dSaGUICntP5eXmOrfmIiIroljpPvZLOYr1aqq5tEeAQA0IWEAAFMpk7ZEFNgalbRduHAhxo8fD73+6q8JhoeH409/+hPeeusttwXnT4TJBMls/+TY4InIDAYINtsnIvIbHEe970qlbdPaI9RHUfX5t6LE7PbnJiIKNBwj3c9a9U1PtS4IksL946CnaEKZtCUiAhqZtD1w4ADuu+++OtcPHDgQGRkZ1x2UP7JWfS0FaMBEZI71NhtspaWeDIuIiLyI46j3Xelp695KWwBQVDWZqjCw0paI6HpxjHQ/i9GetNUGB8scSeNoQu2JeyZtiSjQNSppm5eXB3U9CUeVSoWLFy9ed1D+yFZmn7XTplBAUirr31iphHC0SGBfWyIiv8Fx1PuutEdwf4WRsippy/YIRETXj2Ok+1mqKm21ISEyR9I4jkpbS3kZLCaOsUQUuBr1CaZly5Y4fPhwnesPHjyIhISE6w7KH9mqKm2FqmFzv4nQUACAtYhJWyIif8Fx1Ps8NREZUK3SlklbIqLrxjHS/azOStvmlbRVaDRQabUAgJL8XJmjISKST6OStkOGDMGsWbNQWXXFrrqKigrMnj0b999/v9uC8yeOpK2toUnbqquhrLQlIvIfHEe9z6NJW/a0JSJyG46R7mdppklbSZIQrI8AABjyLsgbDBGRjBqWQawyc+ZMfP755+jQoQMmTZqEjh07AgB++eUXLF68GFarFc8//7xHAm3uGl1p60jaFhV5KiQiIvIyjqPeZbMKiKr5PFWemIjM0R6BPW2JiK4bx0j3s1ZWAKhqj1DevMaqkPAIGC7mwZDLpC0RBa5GJW3j4uKwa9cuPPnkk5gxYwaEEADsV8IGDRqExYsXIy4uziOBNnfOSttr9bOt4myPUFzkqZCIiMjLOI56l9Vkz9hKEiA1bPhtFLZHICJyH46R7iWEqFFpWyhvQI0UHB4OADDk5sgcCRGRfBqVtAWA5ORkrF+/HoWFhTh16hSEEGjfvj0iIyM9EZ/fsJWVAmhCpS3bIxAR+RWOo95jMds/8CvU9g/97sakLRGRe3GMdB9zZQWE1Qqg+bVHAIDg8AgAYKUtEQW0RidtHSIjI3HzzTe7Mxa/FnLrrSifNBGGnzOQ1IDtRah9YLUxaUtE5Jc4jnqetSpp64l+tgB72hIReQrHyOtXXlgAAFBrtVA2sHDIlwTp7ZW2xrJSlBUVIiSCiXsiCjzub/BGtVK3bAnLzTfDGB3doO1FSFV7hCImbYmIiJrC0R5BofJQ0rbqM7DZaIXZZPXIPoiIiJqivPAyAEDTDKtsAUCpUkGpCwIAHNydjszMTFitHGuJKLAwaeujOBEZERHR9fF0pS0kAUVVr9xyg9Ez+yAiImqC8iJ7D1tdSPNM2gKATaUBABzd9i3Wr1yGrKwseQMiIvIyJm19lKM9AnvaEhERNY2zp62HvhVaVlECKOz7yD9/2TM7ISIiagJHe4Tm2M/WQdLqAABqmxVxMTEyR0NE5H1M2vooEepoj1AkbyBERETNlNVsb4/gsUpbACqN/a1UZZnFY/sgIiJqrIoi/0nalhtYyEREgYlJWx8lQsMAANbCQpkjISIiap6spqpKWw8mbR39citLmbQlIiLf4ay0bcbtERxJ2wpDMYQQMkdDROR9zSpp+9prr0GSJEyZMsW5rLKyEhMnTkR0dDRCQ0MxYsQI5OXluTwuOzsbQ4cORXBwMGJjYzFt2jRYLL794Uroq5K2xcUQZs5KTUREV9uxYweGDRuGxMRESJKEL774wmX9o48+CkmSXG733XefyzYFBQUYNWoU9Ho9IiIiMG7cOJSWlnrxKDzHWWnrwUmzHVW8TNoSEfmWQB8jm1N7BJvNhjNnziAzMxNnzpyBsFUlaNUaQJJgs1phrayQN0giIhk0m6Ttnj178O6776J79+4uy5955hl89dVX+PTTT/Hdd9/hwoULePDBB53rrVYrhg4dCpPJhF27duHDDz/EihUr8MILL3j7EBpFhIYCSvvsJpaCApmjISIiX1RWVoYePXpg8eLFdW5z3333IScnx3n7+OOPXdaPGjUKR44cwaZNm7Bu3Trs2LEDEyZM8HToXmHx9ERkAJRq+/+NbI9ARORTAnmMNJaXwVyV5GwOSdv8ywVI/2otMtb/D9vXfgpDiQEAIEkSFFXVtubyMjlDJCKShQdrT9yntLQUo0aNwvvvv4+XX37Zuby4uBjLli3D6tWrcc899wAAli9fjs6dO+PHH3/Erbfeim+//RZHjx7F5s2bERcXh549e2Lu3LmYPn06XnzxRWg0GrkOq34KBZRRkbBevATr5ctQx8XJHREREfmYwYMHY/DgwfVuo9VqER8fX+u6Y8eOYcOGDdizZw/69OkDAHjnnXcwZMgQvPHGG0hMTHR7zN4ihIDV7MX2CCX8VgwRkS8J5DHScDEfAKBQqaFUq2WOpmFio6PQKj4OuRcvuSxX6oJgq6xg0paIAlKzqLSdOHEihg4digEDBrgsz8jIgNlsdlneqVMntG7dGunp6QCA9PR0dOvWDXHVkp6DBg2CwWDAkSNHat2f0WiEwWBwuclBFRUNALBc5ozURETUNNu3b0dsbCw6duyIJ598EperjSnp6emIiIhwfhgFgAEDBkChUGD37t11PqevjJP1MVdagapvV3qlPQIrbYmImh1/HSOLq5K2yqoq1eaMlbZEFMh8Pmm7Zs0a7N27F/PmzbtqXW5uLjQaDSIiIlyWx8XFITc317lNXI0qVcd9xzY1zZs3D+Hh4c5bUlKSG46k8VTRTNoSEVHT3XfffVi5ciW2bNmC119/Hd999x0GDx4Mq9UKwD4OxsbGujxGpVIhKiqqzjES8J1xsj6OHrOSApAUHqy0rSpgYtKWiKh58ecx0lFpq9L5QdJWFwSASVsiCkw+3R7h7NmzmDx5MjZt2gSdFwecGTNmYOrUqc77BoNBlsFWGWNP2lqZtCUioiYYOXKk8+du3bqhe/fuaNeuHbZv347+/fs3+Xl9ZZysjyNpq2jgt0KFECgsLLT/3Ij9OCptjZyIjIioWfHnMdJw0T4xtz9U2iqdSdtyCJtN5miIiLzLpyttMzIykJ+fj5tuugkqlQoqlQrfffcdFi1aBJVKhbi4OJhMJhQVFbk8Li8vz9mbKD4+Hnl5eVetd6yrjVarhV6vd7nJQRUdAwCwXGLSloiIrl/btm0RExODU6dOAbCPg/n5+S7bWCwWFBQU1DlGAr4zTtbHMTGYooGXp0vKDNj99Qn88OVhmIymBu9HWdXT1lhmgc3WmHQvERH5En8aI/2p0lZSa6BQKgFhQ1nBpWs/gIjIj/h00rZ///44dOgQ9u/f77z16dMHo0aNcv6sVquxZcsW52OOHz+O7OxspKWlAQDS0tJw6NAhlwF306ZN0Ov16NKli9ePqTFU0VEAAGsBk7ZERHT9zp07h8uXLyMhIQGAfYwsKipCRkaGc5utW7fCZrMhNTVVrjDdwllp24jvFIWFhiM0pHEfrh3PLwRgLONkZEREzZU/jZGGS1VJWz+otJUkCUH6cACAITdH5miIiLzLp9sjhIWF4cYbb3RZFhISgujoaOfycePGYerUqYiKioJer8fTTz+NtLQ03HrrrQCAgQMHokuXLhg9ejTmz5+P3NxczJw5ExMnToRWq/X6MTWGkpW2RERUj9LSUmdFEACcPn0a+/fvR1RUFKKiovDSSy9hxIgRiI+PR2ZmJp599lnccMMNGDRoEACgc+fOuO+++zB+/HgsXboUZrMZkyZNwsiRI316VuyGcPSYbWh7hKaSFBIUKgk2i0B5iQlBYRrP7pCIiBokkMdIf5qIDACC9XqUFRbAkF93L2EiIn/k05W2DbFgwQLcf//9GDFiBO644w7Ex8fj888/d65XKpVYt24dlEol0tLS8Mgjj2DMmDGYM2eOjFE3jCqGE5EREVHdfv75Z/Tq1Qu9evUCAEydOhW9evXCCy+8AKVSiYMHD+I3v/kNOnTogHHjxqF37974/vvvXS5arlq1Cp06dUL//v0xZMgQ9OvXD++9955ch+Q2jW2PcD1UGnuLhIoSVtoSEfmKQB0jTZUVqCwxAPCP9ggAEKSPAACU5LHSlogCi09X2tZm+/btLvd1Oh0WL16MxYsX1/mY5ORkrF+/3sORuZ8yqqo9ApO2RERUi7vuugtC1N1HdePGjdd8jqioKKxevdqdYfmEprRHaCrHZGQVhob3wiUiIs8K1DHS0c9WrQuCQuXhr5t4SbCjPQKTtkQUYJp9pa0/U8VUtUcoKOBMmURERI3g6C/rnaSt/e1UeQmTtkREJC9H0jYoMkrmSNzHkbQtvXwRVotF5miIiLyHSVsfpoqMtP9gtcJaXCxvMERERM2Is9LWC0VGV9ojMGlLRETyciRtgyP8J2mrCQ6GpFRCWK0oyr0gdzhERF7DpK0PkzQaKMLtVxXZIoGIiKjhKr3Y09ZRacuetkREJLfii3kAgGA/qrSVJAnq4BAAwKWz2TJHQ0TkPUza+jhVdNVkZJeYtCUiImoIm9UGU7kVgHd72pazpy0REcnsSqVtpMyRuNeVpO0ZmSMhIvIeJm19nDNpe/mSzJEQERE1D44qW8A7SVu2RyAiIl9huFSVtPWjSlvgStL28jkmbYkocDBp6+OUMfakrfVygcyREBERNQ+O5KlSLUGSJI/v70p7BCZtiYhIXv7Y0xaolrRlewQiCiBM2vo4VZSj0pbtEYiIiBqivFrS1huUVZW25expS0REMjIbK1FeXATA/yptVcGhAIDC3AuwmDneElFgYNLWx6laxAAALBcvyhwJERFR83Cl0tY7b3Mc+7EYrTAbrV7ZJxERUU2GS/bPjJqgIKiDgmWOxr2UGg1UuiAImw2FF87JHQ4RkVcwaevj1ImJAADz+fMyR0JERNQ8VBjsFTiOClhPUygBpYp9bYmISF6O1gj6mFivtAfyJkmSEB6XAAC4eOY0rFYrMjMznTerlRdNicj/MGnr49StkgAA5rNnZY6EiIioeXAkTlVeao8gSRK0oaqqffMrm0REJA/DxTwAgL5FrMyReEZ4YisAQH5WJrKysrB+5TJkrP8f1q9chqysLHmDIyLyACZtfZwmyT4wmXNzIUys3iEiIroWb7dHAABdiD1pW85KWyIikkmxo9K2RZzMkXhGeGJLAED+6V8BAHExMWgVH4e4mBg5wyIi8hgmbX2cMiYGkk4H2Gww5+TIHQ4REZHPqyitao/gpUpbANCFqu37ZtKWiIhkUpxvr7QNj/XTpG1CVaXtmV8hhJA5GiIiz2PS1sdJkuSstjWdZcN1IiKia3FW2nqppy2Aau0RmLQlIiJ5ONojhPtppa0+Nh4KpQrGsjKUFxbIHQ4RkccxadsMOPvanmNfWyIiomspr+orq5KhPUJBvgEFBQWsACIiIq9zVNrq/bTSVqFSISYpGQBQfIEFTUTk/5i0bQbUrar62p7jwERERHQtV3raerM9gj1pm33sErZ/dgCFhYVe2zcREZGpsgIVhmIA/tseAQBiU9oCAIpy+NmYiPyfSu4A6No80R7BZDJh3759Vy3v1asXNBqN2/ZDRETkTRaTFeZKK4Cq9giV9uVCCBQVFUHAM4lcXZi9p61kUyIsNMwj+yAiIqrJarUiKysLhjz7/Cea4BDoQkIB5MkbmIfEtrEnbYsvnIOmRbzM0RAReRaTts2Asz3CWdf2CNeTeN23bx/S316ETgkJzmW/5OQAk/+M1NRUN0RNRETkfeUGe5WtQilBobySoC0pM+DwF7+ifUpnj+w3KMz+lspiYlsEIiLynqysLKxfuQz6qu/QBoVHyBqPp8W2aQcAKM45jxZM2hKRn2PSthlwVtrWaI9wvYnXTgkJ6N2mjVtjJSIiklN5VWsEXagKkuRaVRsSfP0VsEIIZ+uD6unZoKpKW6vJdt37ICIiaoy4mBgoS4txCUBwZLTc4XhUizYpkCQFKg3FsJqMcodDRORRTNo2A46etjaDAdbiYijDw53rmHglIiK6osJwJWnrCSVlBuz+Oh9mqwkmo8m53NEewWYFbFZW2xIRkXcZy0oBAMGRUTJH4lkaXRCiWyXh0tkzMJUY5A6HiMijOBFZM6AICoKyRQwA9/a1JSIi8jflzqSt2mP7CAsNR2iI3mWZWqtwTnxmYbUtERF5mbG8DID/V9oCQPwNHQAAplImbYnIvzFp20xoqvramk6fljkSIiIi3ySEwOU8+8zZnqq0rYskSc5EsZV9bYmIyMuMZfakbUiUf1faAkB8u/YAAFNJicyREBF5FtsjNBO6G29Exb59qNi3D+HD7m/UY2ubsOzw4cNIsFndGSIREZGsCgsL8cvP2QA00IWpYbF5t9ddUJgaZYUmVtoSEZHXVTraI0QEQtLWXmlrLDFACF4oJSL/xaRtMxF8cx8U/vvfKP/550Y/trYJyw4fOgRNfBzQtp07wyQiIpKVAhoA9krbUoN3k7a6MPvbKquZHyCJiMh7bBYzrGYzgMBojxDTug0UKhVsFgsqS0vlDoeIyGPYHqGZCO7TBwBgPHEClqpZqxvDMWFZr9hYdL50Cb8tKkLLs+dgzstzd6hERESysdk/s3q9PQJgr7QFAIuRlbZEROQ9lspKAIBCpYZKq5U5Gs9TqlQIT7BP1l1aeFnmaIiIPIdJ22ZCFRUFTTt7VWzF3r1Neo7Ko0dRsHIlynfvRguDAQk5OSj+7DMYT550Z6hERESysVns/5cnaWvfp4U9bYmIyIssRnvSVqXTyRyJ90S2ag0AKC1g0paI/BeTts2Io9q2fE8jWyRYLIg6fBil27YBVitUsbE43rIlisLDAQAlW7bAfOGCu8MlIiIP27FjB4YNG4bExERIkoQvvvjCZb0QAi+88AISEhIQFBSEAQMG4GSNC3UFBQUYNWoU9Ho9IiIiMG7cOJQ2468aXknaqr2+b11Vpa3VzEpbIiLyHmtlBQBAqQuSORLvuZK0LZA5EiIiz2HSthkJvvlmAED5nj0Nfozl8mUEvz4fYWfO2J8jNRXh//d/yIqLw6kO7aFJSQGsVpRs3AjJyonJiIiak7KyMvTo0QOLFy+udf38+fOxaNEiLF26FLt370ZISAgGDRqEyqqvUQLAqFGjcOTIEWzatAnr1q3Djh07MGHCBG8dgltZzTaIqqFM1vYIrLQlIpJdIF3YdLRHUGkDqNI2KRkAUFZUCGHjxVIi8k9M2jYjwX16AwAqjx2D6dy5ercVQqD4yy/x67DfQHXiBGwqFcKGDEFwnz6QJMm+kSQh7N57oQgNha28HKHZ2Z4+BCIicqPBgwfj5Zdfxm9/+9ur1gkhsHDhQsycORPDhw9H9+7dsXLlSly4cMH5wfXYsWPYsGED/vWvfyE1NRX9+vXDO++8gzVr1uBCM/wGRmWZvcxWoZSgCVJ6ff+ORLHFxA+PRERyC6QLm1faIwROpW1IVAwkpQrCZoW5vEzucIiIPIJJ22ZEHR+P4LRbAZsNuXPmAMK1kkcIAU1xMTRf/A+Z992HC89Oh7WgANaWLZHTty+0KSlXPaekViOotz0ZrM/MBEwmrxwLERF51unTp5Gbm4sBAwY4l4WHhyM1NRXp6ekAgPT0dERERKBPVfsdABgwYAAUCgV2795d53MbjUYYDAaXmy+oLLUnbXWhqisXKL3IUWlrNQnYbKy2JSKSUyBd2LzSHiFwKm0lhQKasDAAgKnUN96HEBG5G5O2zUz8rBcgqdUo2/E9NOu/gdpgQOXRozBs3IiCDz5Awg8/QLd2LcxnsqEIDkaLKVNQNuclWKoGtNroOneGIjQUKqMR6u++8+LREBGRp+Tm5gIA4uLiXJbHxcU51+Xm5iI2NtZlvUqlQlRUlHOb2sybNw/h4eHOW1JSkpujb5rKUjMAeVojAIC22n6NVVW/RETke/zpwqYQ4kqlbQC1RwAATageAGAqYdKWiPwTk7bNjLZtCqKrvpKj++QTJH7/PUq3bYPp1CmIykrYVCqYe/VCwrx5aP/9DsQ88SdAVf+HV0mpRNBNNwEANFu3QQhWBxERUd1mzJiB4uJi5+3s2bNyhwQAqCxxVNp6fxIyAFAoJCjVUlUsZlliICKia/OnC5um8jKIqrlJVAFUaQsAmjAmbYnIv8lTikLXJeZPEwBhQ97X6yGdPQtNbCzUrVpB07o1DlZUIHLkQ4hITW3Uc2o7dkTJDz9AeeECKg8eRFCPHh6KnoiIvCE+Ph4AkJeXh4SEBOfyvLw89OzZ07lNfn6+y+MsFgsKCgqcj6+NVquFVqt1f9DXyVFpq5Wp0hYAVBoFrGYrKkpZaUtEFIhmzJiBqVOnOu8bDAaPJm7LCwsAAGpdEAQknKmagPrMmTMQft6qR1tVaWsuL4PFZJQ5GiIi92OlbTMkaTRo8ec/o2zOSzg7eDAiRoxASGoq1AkJgKJpL6lCo0F51Yf6os/XujNcIiKSQUpKCuLj47FlyxbnMoPBgN27dyMtLQ0AkJaWhqKiImRkZDi32bp1K2w2G1IbefHPF1TvaSsXpcZeaVthYKUtEZGvqn5hs7q8vDznuuu5sKnX611unlReeBkAoAsJQf7lAqR/tRYZ6/+H7Ws/hcHPK1CVWi00QfbJ14rO1z9RNxFRc8SkLTmVtWoFADB8/TVsFRUyR0NERNdSWlqK/fv3Y//+/QDsPfr279+P7OxsSJKEKVOm4OWXX8aXX36JQ4cOYcyYMUhMTMQDDzwAAOjcuTPuu+8+jB8/Hj/99BN27tyJSZMmYeTIkUhMTJTvwJrIF5K2aq39rVV5MZO2RES+yp8ubDoqbbUhIQCA2OgotIqPQ0xkpJxheU1IZDQAoOh8tsyREBG5H9sj+Bmz1YrDhw+7LDt8+DASbNZrPrYyOhq2mBjg0iWUbN6C8GH3eypMIiJyg59//hl33323877j65hjx47FihUr8Oyzz6KsrAwTJkxAUVER+vXrhw0bNkBXrefdqlWrMGnSJPTv3x8KhQIjRozAokWLvH4s7lBR1Uc2SKaetgCgqkraVhSbZIuBiIjsFzZPnTrlvO+4sBkVFYXWrVs7L2y2b98eKSkpmDVrVp0XNpcuXQqz2eyTFzYdlbba4FDAv7sh1CosKgqFF86h8OwZuUMhInI7Jm39TGZ+Pgo/+wwtjx5zLjt86BA08XFA23b1P1iSYL6tL7T/+xKGr79m0paIyMfddddd9U4eKUkS5syZgzlz5tS5TVRUFFavXu2J8LzOmbTVy5m0tbdHKGd7BCIiWQXKhc2y6pW2pZUyR+N9oVWVtoXnWGlLRP6HSVs/dEOLFujdpo3z/i85OQ1+rPnWW6H935co/eEHWAoLoQqQr9UQEVHzJoRw9pGVN2nL9ghEyLi3zAABAABJREFURL4gUC5sOtoj6IIDM2kbEhkFwF5xXG4oRrA+XOaIiIjchz1tyYUtMRHazp0BiwUlG7+VOxwiIqIGMVVYYDXbP5x7O2krhEBhYSEKCwurJW3ZHoGIiDxL2GxX2iOEhsocjTxUGg1UQcEAgLzMkzJHQ0TkXqy09UG19aUFgF69ekGj0Xh8/+FDhyD/2DEYvv4akSMf8vj+iIiIrldZkT1JKikBldq716RLygzY/XU+zFYTIkJjAADmShtMlRZodHyrRUREnlFaVACbxQJIErRVictApAnVw1JRjtzMk0jp1UfucIiI3IafJHxQbX1pf8nJASb/2SszleqHDEH+G2+ifM8emC9cgNqHGu0TERHVpqzICABQqO1Vr4B352MJCw2HyWKEQilBoQRsVntMmni+1SIiIs8ozssFAKi0OkiKwP0SrSYsDOUXc5GbeULuUIiI3IqfJHxUzb603lC9wje4U0eofjmOw4sXo+vs2V6p8CUiImqqsmJ70hYKK3Z/fQJmqwlR4S1kiUWlVcBUbkNpoRGR8SGyxEBERP6vOD8PAKCsNnlaINKE6QEAOadOQAgBSZJkjoiIyD0C93IcXSUzPx/Zn32Gwk8+RZHWPvBb132NfXv3yhwZERFR/UqrKm0llQ1hoeEIDdHLFoujr21poVG2GIiIyP8VOSptdUEyRyIvTUgoJIUCFYZilFy6KHc4RERuw6QtuXBU+HZMTYWkViPEaITyBL9mQkREvq3cmbT1ZlOE2l1J2gbeLN5ERORZVqsVmZmZyMzMxLmqibdUWv+vtLXZbDhz5ozz2M+cOQNhs4/5AhJ0UfZv1+zfuQNWq1XOUImI3IbtEZqJ2iYnO3z4MBJsnhmQJLUamhtugPHYMai//wEYM8Yj+yEiInKH6pW2clM7krZFrLQlIiL3ysrKwvqVyxAXE4P8qqStSf7rlR6Xf7kAmV+txaW2KQCAwydOIikuFkA88i8XoKK8HCoAGRu/RstuvdCuXTtZ4yUicgefrrSdN28ebr755v9n787jo6rv/Y+/Zs86SUjIgllYZV8UFFLqUkEQKdVKW69awdarVy+2KkopLa5cxVrr0v4Qe60FW6VYvWKrRdkEqrIICLIaISxhycKSfZn1/P4IGRkIECDJzCTv5+NxNHPOmXM+XyaZ75zPfM/nS3x8PKmpqdx4443k5eUF7VNXV8ekSZNITk4mLi6O8ePHU1xcHLRPQUEBY8eOJSYmhtTUVKZMmYLX623NplywE0sXNCxb3/o7R48ebbFzRvXuDYBtzRq8LXgeERGRC1Vd7gbCZKStvb6WXrXKI4iISAtIS0khMz0Nw3N8Ek67I8QRtY7U5A5kpqeRmZ5GSlJS0La4pA4A2LyeUIQmItIiwjppu3LlSiZNmsSaNWtYsmQJHo+HUaNGUV1dHdjnwQcf5P333+ftt99m5cqVHDp0iJtuuimw3efzMXbsWNxuN6tWreL1119n7ty5PProo6Fo0gVpKF3QsOSkpLTo+azp6bgSEzF5PBz7619b9FwiIiIXojqMRtqqpq2IiLQ0n9eLp66+DI9Zk0Zjiamf+NNdVYnhD/1nARGR5hDWSduPPvqIO+64g759+zJw4EDmzp1LQUEBGzZsAKC8vJzXXnuN559/nmuuuYbBgwczZ84cVq1axZo1awBYvHgx27dv54033mDQoEGMGTOGGTNmMGvWLNxudyibF/ZMJhPlx28rKX1zHr6qqhBHJCIiciq/36Cm4vhIW0sYjLRVTVsREWlhroaBTGYLJouqHpodUZitVgy/j8rDxWd/gohIBAjrpO3JysvLAejQof7Whw0bNuDxeBg5cmRgn169epGdnc3q1asBWL16Nf379yctLS2wz+jRo6moqGDbtm2NnsflclFRURG0tFe1aWn4MjLwV1ZSqtG2IiIShmor3Rh+A5MpTMojHE/aumq8eFyaDEVERJpfXXX9gBqTTaNsoX7AUVxifZ6g9MC+EEcjItI8IuYrOb/fzwMPPMDw4cPp168fAEVFRdjtdhITE4P2TUtLo6ioKLDPiQnbhu0N2xozc+ZMnnjiiWZuQYQymXDd8D1iXvkjR2a/QvyoUZiysti4cWOju19yySXYdXuOiIi0oobSCFFxVkymEAcDWKwmbFFmPHV+Ko7WktwpLtQhiYhIG+M6nrRF114BcR06UHGkhNL9BaEORUSkWURM0nbSpEls3bqVTz/9tMXPNW3aNCZPnhx4XFFRQVZWVoufN1x5hw0jdvt2qv/9CYd+9StK7r+f1f9vFr0yMoL2+6qwEO7/OUOHDg1RpCIi0h41TEIW7bQRLlVk4zo4KD1US8WROiVtRUSk2Wmk7aniOiQDGmkrIm1HRCRt77vvPj744AP+/e9/k5mZGVifnp6O2+2mrKwsaLRtcXEx6enpgX0+//zzoOMVFxcHtjXG4XDgcLSPGTibxGQi48kn2T3ue9R9uZnoV1+lV1oagzt3DnVkIiIigZG20U4b4VKNIK6DvT5pe7g21KGIiEgbVFelpO3JGpK2FUWH8NTVYYuKCnFEIiIXJqxr2hqGwX333ceCBQv4+OOP6dKlS9D2wYMHY7PZWLZsWWBdXl4eBQUF5ObmApCbm8uWLVsoKSkJ7LNkyRKcTid9+vRpnYa0Abb0dDo9MxOsVmyr19Bxwwb8DcXvRUREQqjqWP2EX9FOW4gj+UZch/ovf8uPKGkrIiLNL1AeQUnbAEdMLBa7A8Pvp3DX16EOR0TkgoV10nbSpEm88cYbzJs3j/j4eIqKiigqKqK2tv4CKCEhgTvvvJPJkyezfPlyNmzYwE9+8hNyc3MZNmwYAKNGjaJPnz7cfvvtfPnllyxatIjp06czadIkjaY9R/EjRpD5h99jWK3ElJRQOm8eNevW4Tv+La+IiEgoVBytT9rGJYVPvx7Xof4iukJJWxERaWaGYVB3fACNRtoGczgTADiY1/ik4yIikSSsyyPMnj0bgKuvvjpo/Zw5c7jjjjsAeOGFFzCbzYwfPx6Xy8Xo0aN5+eWXA/taLBY++OAD7r33XnJzc4mNjWXixIk8+eSTrdWMNiX+O9+hevqvsb3wIo7ycmo+/5yadeuwpqSQEBPDkbo6NqzfgBEdhREVjcdhx5+ScsqtKZqwTEREmkvl8aRtbFL49CsNI21VHkFERJqb3+3G8PvAZNJI25PYnYnUHCnhUN6OUIciInLBwjppaxjGWfeJiopi1qxZzJo167T75OTksHDhwuYMrV3zd+lC0fDh9HW7qdu2DW9hId7Dh0kEEvftgxPKVQD4TOBNSKQqM5Pqiy5ix+HDmrBMRESaTeXR+sRoOCVtY5PqSzWUH6nF7/NjtoT1zU0iIhJBvHX1/Z4jJga/yRTiaMJLw0jbQ1/vwO/3YTZbQhyRiMj5C+ukrYQxk4monj2J6tkTX1UVnoMH2bp5MwluNx2jojDcbgyPB3d1NVa/H0tZGY6yMlLy84nu1QuakJAXERE5G6/HR3W5u/5nUw3h0ru4qQHA7zU4VFBCZpfGJz8VERE5Vw1J26jYuOO9jTSwxcZhdUThrq2leM9uak6qCNm5c2csFiVyRSQyKGkrF8wSF4elZ0/yjh0j2Wqhx2WXB7a9uWoVnXxehsU7qd26FX95OR03bsTzxz/iHzQIs2b0FBGRC1B1zAWAyQxrl+zA7XKHOKJ6ZrMJW5QZT52fqmNu6HL254iIiDRFYKStkranMJlMdMjuTMnOr9i6+lO+2rmTtJQUAIqPHOH6CXfSrVu3EEcpItI0uldPWpbJhCsqiuhBg0i65RZiLrsMw2TCtnoN+yZOxHv0aKgjFBGRCFZxvDSCLcpMfJwzxNEEs0XVf8xqSCyLiIg0B29dfS33qNi4EEcSnpJzugJwZE8+aSkpZKankZmeFkjeiohECiVtpdWYLBZiLr+c4ssvx4iNpe7LzeybMBFPSUmoQxMRkQjVMAlZQ4I0nNiiG5K24TH6V0RE2gav65uRtnKqlG4XA3A4/+smzZMjIhKuwu8KR9o8V0oK1Y8+gjU9HXd+PgW3T8B7+HCowxIRkQhUcSSMk7ZRStqKiEjz+6ambWyIIwlPSZnZ2KNj8NTW4KmqDHU4IiLnLfyucKTN8/h8bD5yhNKHH8Kfkox73z6+uvU2ao8cCXVoIiISYSpPKI8QbgJJ26MqjyAiIs3D63bjd9d/GRgVFx/iaMKT2WIhq+8AAOrKjoU4GhGR86eJyOSMPD4fW7duDVq3detWMvy+8z5mfkkJpe+8w0V9+lLRrz9pq1dj3b+fXT+9k77vvI3Zbr/QsEVEpJ2oOF4ewRplJtxugLTH1M9OXX64DsMwMJlMIY5IREQiXU1pfRLSYrNh1XXTaXUecAn569coaSsiES38hqVIWMkvKaHgnXco/fvbgWXrW3/n6AVOINa9Y0cGd+7MwL59SbnxRnxWK9avv2bLpPtYu2YNa9euZe3atbjduqVURORCPP7445hMpqClV69ege11dXVMmjSJ5ORk4uLiGD9+PMXFxSGM+NwEato6wu8jjT3aDCbwuvxUHqsLdTgiInKSSOwjq4/V352oScjOLGfAIABcFeX4vN7QBiMicp7C7wpHwk5DgrVhyWnmWTetKSls7NwZP2D/5BO8z/6W0r+/zeqXfs/GjRub9VwiIu1R3759KSwsDCyffvppYNuDDz7I+++/z9tvv83KlSs5dOgQN910UwijbTqv20dNRf2Xe+FYHsFkNtUnboFjh6pDHI2IiDQm0vrI6qP1c4FoErIzS0zvRExSBzAMKg5r4msRiUwqjyBh4ajTycHsLLIK9tPhq6/o2q8fZGSEOiwRkTbBarWSnp5+yvry8nJee+015s2bxzXXXAPAnDlz6N27N2vWrGHYsGGtHeo5aRi9anOYMVtNEIalYx2xFtw1fo4erKJz/+b90lNERC5cpPWRDUnbaNWzPSOTyURqj97s/fwzSgsPkpTRKdQhiYics/AbliLtVnFaGvbOncHvp3LJEky+86+bKyIi39i5cyedOnWia9eu3HbbbRQUFACwYcMGPB4PI0eODOzbq1cvsrOzWb169WmP53K5qKioCFpCobSoBoC4ZEfY1ou1x9bXtdVIWxGR8BRpfWTV8aRtVLyStmeT0bsfAMcOHcQwwq3yvYjI2SlpK+HDZCLummswx8TgKy0l4euvQx2RiEjEGzp0KHPnzuWjjz5i9uzZ7NmzhyuuuILKykqKioqw2+0kJiYGPSctLY2ioqLTHnPmzJkkJCQElqysrBZuReNKi+oToQmpUSE5f1PYY+o/apUUlOuCUUQkzERiH1l15HhNW420PauUbhdjsljw1NVSXaoJyUQk8ihpK2HFHB1N3He+A4Bzzx7M+/aFOCIRkcg2ZswYfvjDHzJgwABGjx7NwoULKSsr4+9///t5H3PatGmUl5cHlv379zdjxE1XWlg/0tYZxklbj6k+xrLiOo4e0QWjiEg4ibQ+0uvxUFteCkBUnGrano3FaiUqKRmoH20rIhJplLSVsGPv3Bl79+6YDIPoP8/BUJkEEZFmk5iYyMUXX8yuXbtIT0/H7XZTVlYWtE9xcXGj9f0aOBwOnE5n0BIKxwobRto6QnL+prDYwWQGDKg8EoZFd0VEJCDc+8jy4iIwDEwWCzZH+H5hGU6iO9TXkz926ECIIxEROXdK2kpYivv2t/FbrVj27qXs//4v1OGIiLQZVVVV5Ofnk5GRweDBg7HZbCxbtiywPS8vj4KCAnJzc0MY5dkZfiNQHiGcR9qaTCZs0fX1dsuLa0McjYiInEm495GlRYcAsEbFhG0t93AT3SEZk8lEbUU53tqaUIcjInJOlLSVsGSOjaXs4osBOPzCi/hCNMmNiEike/jhh1m5ciV79+5l1apVfP/738disXDLLbeQkJDAnXfeyeTJk1m+fDkbNmzgJz/5Cbm5uSGbFbupKkvr8Lr9mK0m4pLCd6QtgO14XduyoroQRyIiIieKtD6yrLD+Fn9rdHRIzh+JzFYbzo6pANQeOxLiaEREzo011AGInE5lTg4JpaVQWMiRWS+TNu2XoQ5JRCTiHDhwgFtuuYWjR4/SsWNHvv3tb7NmzRo6duwIwAsvvIDZbGb8+PG4XC5Gjx7Nyy+/HOKoz66hnm1iagxmS3iPNrLHmqg+DEcKqkMdioiInCDS+siGkbY2JW3PSVKnTMpLiqk9ejjUoYiInBMlbSV8mc3U3XYrsc/9jmNvvknizT/C0bVrqKMSEYko8+fPP+P2qKgoZs2axaxZs1opoubRUM+2Q0ZsiCM5O0dc/UjbI/tr8Pn8WCy60UlEJBxEWh9ZdkJ5BGm6Dp0uYu+mDbgqynFVV4U6HBGRJtNVg4Qtj8/HlyYTnkGDwOsl75fTWLt2LW63O9ShiYhIiDUkbRPTw//C1RZtwmw14fP4OVKgi0URETk/pYWFAFijw7/vCyeOmFhiE5MAKPpqW4ijERFpOiVtJWzll5RQ8M47lCQmYphM2DZvZteTM9i4cWOoQxMRkRA7cqAcAEe8EeJIzs5kMhHttABwaFdZaIMREZGI5HG7qDx+e79q2p67pE4XAVC4fUuIIxERaTolbSWsde/YkYF9+xIzaBAAAw4dApcrtEGJiEhIGX6D8uL6Sb2cqVEhjuZUhmFQVlbGienk6IT6ilSFStqKiMh5KD1UPwmZLToGs9UW4mgiT4dOmQCU7NyBq6YmxNGIiDSNkrYSEWKGDMEcF4e1thbHggWhDkdEREKotLgGj8uPyQzOjuGXtK2srmDle5tw1dUF1gWStvnlGEb4jw4WEZHwcnT/PgCcaRmYTOE9AWc4iklIxBodg9/rZde61aEOR0SkSZS0lYhgstuJu+oqAOyLFlO7eXOIIxIRkVAp3lNfGsEaA2ZLeF64xsbEBz2OirNgsZqoq/JQVqwRPiIicm6OHE/axqemhziSyGQymYjpmAbAjk9XhDYYEZEmUtJWIoa9c2eqO3XC5Pdz8IEH8ZWVhTokEREJgaLdFQDYI2geFpPZREp2LAD7th4NcTQiIhJpjhwoAMCZpqTtmfj9fvbt20d+fj779u3D8H9zd0vs8aRtwZYvqS4rDVWIIiJNpqStRJSj/frhT03Fc+gQB6dOxfB6Qx2SiIi0soaRtrbYEAdyjjL7JgCQ/0VJiCMREZFIc/R40jY+LSPEkYS3kqPHWP3+AjYs/AcrFrxNRWVFYJs1OoakrBwMw0/e6k9CGKWISNMoaSsRxbDZqLlvEia7neqV/+bQL5S4FRFpT9x1Xo4eqgYiMWmbCNSPFK4q1aSaIiLSNJ66OsqLiwBwpippezapyR3ITE8jJSnplG1Zg4YAsHnpR6oxLyJhT0lbiTj+nBwuevFFsNmoWLiQgp/9nLXLl7N27dqgxe12hzpUERFpZiV7K8CAmEQblgibPDvGaSO9a/1o292bNNpWRESa5ujB/QBEOxNwxMWFOJrIlnXJZdiiojl6oICCrV+GOhwRkTNS0lYiUvw13yHzxRcw2WzULF+O5YEHqX71T5T+/W1K//42q1/6PRs3bgx1mCIi0syK9tTf5piSFWHDbAHDMMjoVR+3SiSIiEhTNZRGSMnMDnEkkc8WFU3fq64BYONH74c4GhGRM1PSViKKx+dj69atrF27lu1xcVROm4bLGU+sy0XGqlX0PnKES7Oz6ZWh24ZERNqiQzvLAIhJMRFpNzWWlZVxsOAQAId2llOwq1C3ZoqIyFkd2b8PgOSsnBBH0jYMGv1dAPI3fE5ZUWGIoxEROT0lbSWi5JeUUPDOO4ERtUc3bGB+vJNjSUng91Ozdi3l776Ltbo61KGKiEgzc9d5OZhXP9tzwZ4DuFyRVxc2sUMidmf9z8te30FpqWavFhGRMzt6PGmbkqWRthfC7/ezb98+yurcdOzRCwyDRa/NJj8/H5/PF+rwREROYQ11ACLnqnvHjgzu3Dnw+KvCQnZbzGQnJFL973/jLS4m4+hRai+/HIYODV2gIiLSrA58VYrfZ2CLMhOfFBuRSVuA2FRwV0DtMXDX6SJRRETO7Mjx8gh1JitH9+3D8OsujfNRcvQY+e8v4EjXLuw+UkoccGDzFxSVlfPde35Ot27dQh2iiEgQjbSVtsFkIqpnTxL/4z+wZmRg9nqJ+d3vKP/gX6GOTEREmsneLUcAiO1gxWQyhTia82ePB1u0CcMHu9cfDXU4IiIS5oZOuBvrRTns2bKJFQvepqKyItQhRazU5A5kpqfRITUNe1IyAOZjJfg10lZEwpCSttKmWOLjSbjhBqo7dcLk83HoF7+gYvHiUIclIiIXyPAb7N1Sn+CMTbbVrzMMSktLKS0tjaj6tiaTifg0CwA7/l2Cu84b4ohERCScxaWkktGlG9mZF5GSlBTqcNoMR9pFWKxW3FWVbF/8QajDERE5hZK20uaYLBaODBqE+8orwO/n4EMPU/XJp6EOS0RELkDJvkpqK9xYHWZiEuqrO1XXVLH2X1/z6T+34qqrC3GE5yY2xYItykxdlZcNH+4NdTgiIiLtjtlmo9uQ+nJ6uz75mLzVn4Q4IhGRYEraSpvk8ftZf9lleC67DDweCiZNYv1f/oLb7Q51aCIich6+/rwIgIweTkzmb0ojxMclEBfrDFVY581kNhHbyQ/ApmX7KT9cG+KIRERE2p/kzGziL6qf4G3hH37Hzs9XhTgiEZFvKGkrbVJ+SQkF777LoZQUajp2xOR243jmN3z57ruhDk1ERM6Ru87LV6sLAeh2WYcQR3N+DMOgrKwsqIyDIwGssX78XoOP/7IDvyaWERERaXUJnbtyUf9L8Pu8vP/CM3y55EMMQ32yiISekrbSZnXv2JHBXbuSddNN2C66CKvfT8xzv8O1c2eoQxMRkXOwc10x7jofCR2jSe8WH+pwzktldQUr39sUVMbBZDIRneHBajdzaGcZ6xfuDV2AIiIi7ZTJZGbwj26nz5XXYPj9LP3TLD6c9Tyummp8Ph/5+fmBxacJy0SkFSlpK22eyWol/vrrcSUmYq6qYt9Pfkpd3tehDktERJrAMAy2rDgIQL+rLgoqjRBpYmNOTThb7HDZjVkArP/XHnZtKGntsERERNo9s8XCdf/9IFfcegcms5kdnyxn7uR7Wb3wfRb+5TU2LPwHC//yGnv37g11qCLSjihpK+2C2W6n5LLL8GVn4ztyhH0TJlC7aVOowxIRkbPYu+UoRw9WYbGZ6ZWbEepwmp1hGCTkQPfLkzEMWPLaNnZvOsyxY8c4duyYbs8UERFpYX6/n3379rF7924Sew8g96f/TWxyClWlx1j7xp+wHC4kNdFJWkpKqEMVkXbGGuoARFqL326n+pdTSfvj/1L75ZfsmzCRjKeeImHcd0MdmoiINMLn9fPZ2/UlbXoMS6a6ruKUurCRrrqmirX/+hqHw0HOgET2bS7joz9uITYd4tLhOz8cRIcOp9bxNQyD0tJSkpKSMJkid/SxiIhIqJUcPUb++ws40rULW7/eicNqpdvFfTHv30PFgQJqjx5m00f/Ij67M36VRxCRVqSRttJueHw+tu7ZQ/F/34tn0CAMt5tDU6Zw8LHH8Z9QY1BERMLDlx/vp/xwLfYYMzvyv2TRm5/z6T+3BtWFbQvi4xJwxicy7Ic59P5WBoYBVYVQ+rWZA9vLGp2grLS0lPfn/pvS0tIzHtswDI4dO8bRo0c5evSoRu6KiIg0IjW5A5npaaQkJZGa3IHsizrRb9hwbDk9MEfH4PN6KNu9k5Uv/45DX+8Idbgi0k5opK20G/klJZS+8w4X9elLaadOJFZWkpCfT8Vbb1G3fj0ZTz5BzODBoQ5TRESA4r0VfP7P3QCYnNXYbHbi4xJwe10hjqxlGIZBeUUZOcPtbN9xDHNFB1zVfj55Yy/r/3GQzv1TSOviJCk9lvjkKPw+g9iY+EDS9nQjbktLS1nxzpdUVldQV1fHD//r2kZH7oqIiMipTFHRxHbrRYrNzN7NmygvPMjfHplC98tzyfnW1cSnpgf27dy5MxaLJYTRikhbo6SttCvdO3ZkcOfO9Q+6dOHLtWvpuGMH5Oez77Yf4x4+HNf4mxg0ciR2uz2ksYqItFfVZS4+nL0Zn9cgtoOVuIxojh6rDnVYLaqyuoK1/yrB43Njc/pJ6+Kg9jBUHfFSW+lhx6pCdqwqDOxvMgNmg6V5e7BG7aPrgFQ6XpREXJIDe5QVq92MxWamqtpFlDUef7SB1RK6fi3U5Ryaev5QxykiIuHHZDKR3q0HLlsUVp+Hgi8+Z9fnq9n1+WpiUtNJyOrM0eoarp9wJ926dQt1uCLShrSrpO2sWbP47W9/S1FREQMHDuQPf/gDl19+eajDkhDa6vdTndyBazt0IH7/fuyffYZl1Sp2XH01vaZMwdG1S6hDFBFpFeHSRx45UMnCl7dQXe7G2dFBxx5RVNdVtHocodAwkriu7jAWq4mULlFce3cO1SWw/fM9HNhegc8Fhs+E32eA34zXC95a2L6yBCg54/FNFjvL/5xP5sVlJGZZSc6MJTmlwwUnJxsSnfDNiN+T1zWUcxh3x5UhGenb1POXlpbyzzkrueLGASQlJZGUlATAsWPHgPoLdyV0RdqfcOkjJbQsdjuXXv9DvvMft7N4zv9SuH0zNSVF1JQUE52cQsnOr+jSpTNm8zejbX0+H3v27MFdXUV1WSletwu7Iwp7bBzRzgS6dO16xtG5Pp+PvXv3Bq3TiF6R9qPdJG3feustJk+ezCuvvMLQoUN58cUXGT16NHl5eaSmpoY6PAmh7PR0ulx2OZ7iYmpWr4aDB7EsX87u5cuJHjiQ+NGjiR02FMfFF2Oytps/GRFpR8Khj3TVevlyaQEblxTgdftJ6BjNlRM7k/d54dmf3EY1lEwgCvIP7iCndzeioqK4dFQOtVVeFr35ObH2RPBZiE2y4a0xUVPhxuf24/UY+Lx+fB4/Pq8BRn2yt2hXJUW7KgEwWSCzdyJd+qWSmuMkoWM0jlhrUELSMAx8Hj+HS44SGx2Pz+PHVeOltspDXZWb2ioPRQcOU5Rfgd8L8Ymx+N3g9Xuoq3ZjskCnbh2IjrdiqnZSsKWMuk5mYhLsxDjt2ByW+tjqT4bP6+fYsVKc8QkYfvD7DHw+H2Wl5cTFxmP4wfAb+P0GlZUVYIIEpxOT2RSI22Qy1Y9EPuHnqnIX0TYnrmovvgQ/Fss30zr4/QbVZS6qjtVRWHAM9zEHH//vbgyvhegYBz6Pn+qqGixWC1aHmexeKSRnOIlLdBCbFHX8/w5sdkvQv9vZSlec6XU/23Mv5Pgicm7CoY+U8JKS3ZmhP76TVW/9FXfxQcqKCqk9ephVc2bzxdtvkNqlGzHOBPw+HyUHCig7dAD8/lMPZDKR2CmTTl27k5jeidikJCxWG36/D8PvBwMOHznCltWfkhAfj9lmp7y2luvuuJuLe/Vq/YaLSKtrNxmo559/nrvuuouf/OQnALzyyiv861//4s9//jO//OUvQxydhANbWhrOG25g2xdfkOxyYfvyS2qPLwCGxYI/JQUjtWP9/2NiMKKjyezRA3tiIubYWEwOByabDZPdHvx/mw0CF1TfXFh9s8p00orjP5tMmMxmsFjq/2+1Bj+2WOr38x3v2H0+8PsDPwf+7/NheH3g9Rz/2Yvh8YLPW/98swWT2QRmM5jN9cc+4f9n336an02mc75QPc2Gpq071/Wn2fe00/S0dnynXd1ybT99HOcweVFLvjanPUbgP1iTkjCpvMk5CXUfWbSnnA/+8CWuGi8A6d3j+NZ/5FDjqjr932M7EFQyweIA6v8GysrLADBH+4hNtOD2uqisK8eDG1uSHcPnpuzYEdIzO+HxuUlypuByuaipcJHdI4Nj++so2VWL32uwf2sZ+7eWBc5pMoPJbMJ8PAnq9fgwGrnOPB1X+allLPZ8cSzw82d/2wvsPfd/jGby7ratAFjtZmwOC4YBrhovRtBkb1GBnzzVDTWUbfi84KuDnWuPsJMjpxzbHm0hJsGB3WHBa7ipLndhMkNmj2ScSXE4YqzYo62YTPVvcYbfoKqqGrvVgdftp6qyGp/bwOvxUbinFMMPqZkJ2B12PB4PmMDhcGAygdvjpnhffdK2w0WxxMRGYbVbiE+IxeawYLWbcXnqsNrMJCY7sTms2OyW49ss2BxmrLb6JLPR8FdmfPNW2vBeaxjg9/rrk+dePz6fn7JjZfi8fvy++jZER8dSWVGJyWQiIdGJxWrGYjVjtpiOL9/83DAKu7y8HJMJEhMT6z9fUP97d7pPDA1JfcOof+A3/JSVlmMYBokJCfWfOzj++2s64Xim449Nxz9WYcLgm+MYfj+lZWUYBiQmJNDwGc0wjG+62uPPq99kUHY89qTERExmc/1Ht4Z9zMd3M52mLSetbOpnpIZ4DOP4q+X/5ueG392G36mG/Rv+but/NigrK8PpTMARY8MR3W4uAZtFqPtICR9+v599+/YBsG/fPuyx8XT79tVUl5WSv2UzdWXHqKuqpGDLpsYPYLFitliwmM14XS4Mw0/Zwf2UHdx/1nMfK/rm5/cfe5goZwIxSR1IzcohMS0de1Q0ZosVi9WK3/BzuLgYv8+L3+vF63bjP35N6PN68Hm9mI9fs5ktViw2K5jMmK1WrFYbZpsNq81OWqdOOGJisNkdWGw2TCYTfgOKi4vAZMZkNtGp00VYrdbAdV/Dcf1+g0OFh46vN5OVlYXFaj3+GcOC2WLBbLFitlqwWKzH308j+wvIRq9TGllnNPbpttGnNvYp2Dhpn0YDaeI5mxhHE57b1GvWxv+NzvecTbxKaOzfwzBwu1wU7N2Dz+PB7/Pi83jJ7tyZjO4XN+24raRd9Nhut5sNGzYwbdq0wDqz2czIkSNZvXr1Kfu7XC5crm8mOikvLwegouLCbs+srq5mU0EB1Scc++uiIpwWMzF5eRG9LtziuZB1O6uribvqSvr88AfYNnyBZcd2THlfY3W74dCh+uUEexGRcJI9589EDxhwXs9teJ8/pyR1hDvXPhKav5+0xfmp81bjwoURW87GvUXsfzUVr89DojMZr8/NsdKjWCwWvD43Vov9nNad6/7hfq7tX9fh9Xlwu934vL6g/TwWL16fmzpXLTV1NfXrPEWBY5RuLsLr85CQlYzFZyc61kHR19X4XCbwn+1WSwNMBpgNMPswmcEw+/AZHmLjYjDMPjw+F348eN1eEuI6YLXYSMlKwF3j49CuUuKdcbhrfNRUeMA4+8VZQxLZ7/djs1kwmcHj8WIYfkwmC1A/EtdsNh//0F+fXLNaLHi9/qAP6oYBJo6PsHUDVcHniXHascWaKDtWSlScHcPsxWu48PndeNw+EuOT8Xr8uGt9WLDiTHTiqvJSVerGhJlaNxz/UwhSWnz+9ZjLDp/9uceK2na9Z2leg8fkMHh05/N+fnvrJ8OhjwSorKxk78GD1NTWcbC4GLvFis1e/2XeiY9P93NT99NzzvycHfn5VKxZR3ZmJ/IL9pORnEzt8dd6j8tHhdtMVmomJUWHsJlMJCUkUFRWTmJSB7p068pXu/dit1jp1jkHAz9f532Nq6qSlPhYaquq6ZiaRlSUnbo6F0eLi7DbbFTX1hJlsxETE4Xf5cZdV4PJMKg7eoSyo0c4tOvr8/69EpFgHbK7cNuTz57381ukjzTagYMHDxqAsWrVqqD1U6ZMMS6//PJT9n/ssceOf/+uRYsWLVra47J///7W6qJC7lz7SMNQP6lFixYt7X1pL/2k+kgtWrRo0XKuS3P2ke1ipO25mjZtGpMnTw489vv9HDt2jOTk5HMasl9RUUFWVhb79+/H6XS2RKitTm2KDGpTZFCbwo9hGFRWVtKpU6dQhxLWzrWfjPTfixOpLeGrLbVHbQlPbaktcH7tUT95ds11LQlt73fubNTetq29tRfaX5vbe3tboo9sF0nblJQULBYLxcXFQeuLi4tJT08/ZX+Hw4HD4Qhal5iYeN7ndzqdbe4XVm2KDGpTZFCbwktCQkKoQ2hV59pHwvn3k5H8e3EytSV8taX2qC3hqS21Bc69Pe2pn2zNPvJM2trv3NmovW1be2svtL82t+f2NncfaT77LpHPbrczePBgli1bFljn9/tZtmwZubm5IYxMREQktNRHioiINE59pIiIhFK7GGkLMHnyZCZOnMiQIUO4/PLLefHFF6murg7MAioiItJeqY8UERFpnPpIEREJlXaTtL355ps5fPgwjz76KEVFRQwaNIiPPvqItLS0Fjunw+HgscceO+X2mEimNkUGtSkyqE0SLlq6j2xLvxdqS/hqS+1RW8JTW2oLtL32tJRQXEc2aG+vkdrbtrW39kL7a7Pa2/xMhmEYLXZ0ERERERERERERETkn7aKmrYiIiIiIiIiIiEikUNJWREREREREREREJIwoaSsiIiIiIiIiIiISRpS0FREREREREREREQkjStq2oFmzZtG5c2eioqIYOnQon3/+eahDarJ///vfjBs3jk6dOmEymXjvvfeCthuGwaOPPkpGRgbR0dGMHDmSnTt3hibYJpo5cyaXXXYZ8fHxpKamcuONN5KXlxe0T11dHZMmTSI5OZm4uDjGjx9PcXFxiCI+u9mzZzNgwACcTidOp5Pc3Fw+/PDDwPZIa8/JnnnmGUwmEw888EBgXSS26fHHH8dkMgUtvXr1CmyPxDYBHDx4kB//+MckJycTHR1N//79Wb9+fWB7JL5PSNOca//29ttv06tXL6Kioujfvz8LFy4M2h7q35Xmbs8dd9xxyt/8dddd15JNCDiXtmzbto3x48fTuXNnTCYTL7744gUfszk1d1vO9l7cks6lLa+++ipXXHEFSUlJJCUlMXLkyFP2j6S/maa0J1L+Zt59912GDBlCYmIisbGxDBo0iL/+9a9B+4TytWnutoTydZHIvpY8k7b6ufhEzXEtfezYMW677TacTieJiYnceeedVFVVtWIrmu5s7W3Ke0mktLe5cgoFBQWMHTuWmJgYUlNTmTJlCl6vtzWb0mRNafPVV199ymt8zz33BO0TKW1ujhxLs7bVkBYxf/58w263G3/+85+Nbdu2GXfddZeRmJhoFBcXhzq0Jlm4cKHx61//2nj33XcNwFiwYEHQ9meeecZISEgw3nvvPePLL780vve97xldunQxamtrQxNwE4wePdqYM2eOsXXrVmPTpk3G9ddfb2RnZxtVVVWBfe655x4jKyvLWLZsmbF+/Xpj2LBhxre+9a0QRn1m//znP41//etfxtdff23k5eUZv/rVrwybzWZs3brVMIzIa8+JPv/8c6Nz587GgAEDjPvvvz+wPhLb9Nhjjxl9+/Y1CgsLA8vhw4cD2yOxTceOHTNycnKMO+64w1i7dq2xe/duY9GiRcauXbsC+0Ti+4Sc3bn2b5999plhsViMZ5991ti+fbsxffp0w2azGVu2bAnsE8rflZZoz8SJE43rrrsu6G/+2LFjYdeWzz//3Hj44YeNv/3tb0Z6errxwgsvXPAxw7ktZ3svbinn2pZbb73VmDVrlrFx40Zjx44dxh133GEkJCQYBw4cCOwTSX8zTWlPpPzNLF++3Hj33XeN7du3G7t27TJefPFFw2KxGB999FFgn1C9Ni3RllC9LhL515Jn0hY/F5+sOa6lr7vuOmPgwIHGmjVrjE8++cTo3r27ccstt7RyS5rmbO1tyntJpLS3OXIKXq/X6NevnzFy5Ehj48aNxsKFC42UlBRj2rRpoWjSWTWlzVdddZVx1113Bb3G5eXlge2R1OYLzbE0d1uVtG0hl19+uTFp0qTAY5/PZ3Tq1MmYOXNmCKM6Pye/8fr9fiM9Pd347W9/G1hXVlZmOBwO429/+1sIIjw/JSUlBmCsXLnSMIz6NthsNuPtt98O7LNjxw4DMFavXh2qMM9ZUlKS8ac//Smi21NZWWn06NHDWLJkiXHVVVcFkraR2qbHHnvMGDhwYKPbIrVNU6dONb797W+fdntbeZ+QU51r//ajH/3IGDt2bNC6oUOHGv/1X/9lGEbof1eauz2GUX9xcsMNN7RIvGdyIZ89cnJyGk10hurzTEu05UzvxS3pQv8NvV6vER8fb7z++uuGYUTe38zJTm6PYUTm30yDSy65xJg+fbphGKF9bZq7LYYRutdF2ta15Mna4ufiMzmfa+nt27cbgLFu3brAPh9++KFhMpmMgwcPtlrs5+N0SdszvZdEcnvPJ6ewcOFCw2w2G0VFRYF9Zs+ebTidTsPlcrVuA87DyW02DCPomr0xkd7mc8mxNHdbVR6hBbjdbjZs2MDIkSMD68xmMyNHjmT16tUhjKx57Nmzh6KioqD2JSQkMHTo0IhqX3l5OQAdOnQAYMOGDXg8nqB29erVi+zs7Ihol8/nY/78+VRXV5ObmxvR7Zk0aRJjx44Nih0i+zXauXMnnTp1omvXrtx2220UFBQAkdumf/7znwwZMoQf/vCHpKamcskll/Dqq68GtreV9wkJdj792+rVq0/5Wx49enRg/1D+rrREexqsWLGC1NRUevbsyb333svRo0ebvwEnaInPHqH6PNOS5z3de3FLaY621NTU4PF4Ap9XIu1v5mQnt6dBpP3NGIbBsmXLyMvL48orrwRC99q0RFsatPbrIm3/WhLa3ufic9GU94nVq1eTmJjIkCFDAvuMHDkSs9nM2rVrWz3m5nCm95JIbu/55BRWr15N//79SUtLC+wzevRoKioq2LZtWytGf35ObnODN998k5SUFPr168e0adOoqakJbIvUNp9PjqW522q98GbIyY4cOYLP5wt6kQDS0tL46quvQhRV8ykqKgJotH0N28Kd3+/ngQceYPjw4fTr1w+ob5fdbicxMTFo33Bv15YtW8jNzaWuro64uDgWLFhAnz592LRpU0S2Z/78+XzxxResW7fulG2R+hoNHTqUuXPn0rNnTwoLC3niiSe44oor2Lp1a8S2affu3cyePZvJkyfzq1/9inXr1vHzn/8cu93OxIkT28T7hJzqfPq3oqKiM/4ehPJ3pSXaA3Dddddx00030aVLF/Lz8/nVr37FmDFjWL16NRaLpfkbQst89gjV55mWOu+Z3ovj4+MvNOxGNUdbpk6dSqdOnQIXCJH2N3Oyk9sDkfU3U15ezkUXXYTL5cJisfDyyy9z7bXXAqF7bVqiLRCa10Xa/rVkW/xcfC6a8j5RVFREampq0Har1UqHDh0i8t/hbO8lkdre880pnO6zZMO2cNZYmwFuvfVWcnJy6NSpE5s3b2bq1Knk5eXx7rvvApHX5gvJsTR3W5W0lXZp0qRJbN26lU8//TTUoVywnj17smnTJsrLy3nnnXeYOHEiK1euDHVY52X//v3cf//9LFmyhKioqFCH02zGjBkT+HnAgAEMHTqUnJwc/v73vxMdHR3CyM6f3+9nyJAhPP300wBccsklbN26lVdeeYWJEyeGODqR0PqP//iPwM/9+/dnwIABdOvWjRUrVjBixIgQRta+nem9+M477wxhZKf3zDPPMH/+fFasWNEm+sXTtSeS/mbi4+PZtGkTVVVVLFu2jMmTJ9O1a1euvvrqUId2zs7Wlkh6XSRytMXPxXJmbfW9pC3lFJrqdG2+++67Az/379+fjIwMRowYQX5+Pt26dWvtMC9YOOVYVB6hBaSkpGCxWE6ZQa64uJj09PQQRdV8GtoQqe277777+OCDD1i+fDmZmZmB9enp6bjdbsrKyoL2D/d22e12unfvzuDBg5k5cyYDBw7kpZdeisj2bNiwgZKSEi699FKsVitWq5WVK1fy+9//HqvVSlpaWsS1qTGJiYlcfPHF7Nq1KyJfJ4CMjAz69OkTtK53796B29si/X1CGnc+/Vt6evoZ9w/l70pLtKcxXbt2JSUlhV27dl140KfREp89QvV5prXOe+J7cUu5kLY899xzPPPMMyxevJgBAwYE1kfa30yD07WnMeH8N2M2m+nevTuDBg3ioYce4gc/+AEzZ84EQvfatERbGtMar4u0/WvJk7WFz8XnoinvE+np6ZSUlARt93q9HDt2rE38O5z8XhKJ7b2QnMLpPks2bAtXp2tzY4YOHQoQ9BpHUpsvJMfS3G1V0rYF2O12Bg8ezLJlywLr/H4/y5YtIzc3N4SRNY8uXbqQnp4e1L6KigrWrl0b1u0zDIP77ruPBQsW8PHHH9OlS5eg7YMHD8ZmswW1Ky8vj4KCgrBu18n8fj8ulysi2zNixAi2bNnCpk2bAsuQIUO47bbbAj9HWpsaU1VVRX5+PhkZGRH5OgEMHz6cvLy8oHVff/01OTk5QOS+T8iZnU//lpubG7Q/wJIlSwL7h/J3pSXa05gDBw5w9OhRMjIymifwRrTEZ49QfZ5prfOe+F7cUs63Lc8++ywzZszgo48+CqrxB5H3NwNnbk9jIulvpuFzF4TutWmJtjSmNV4XafvXkidrC5+Lz0VT3idyc3MpKytjw4YNgX0+/vhj/H5/IBkWyU5+L4mk9jZHTiE3N5ctW7YEJaqXLFmC0+k8ZVBMODhbmxuzadMmgKDXOJLafLJzybE0e1svaAo1Oa358+cbDofDmDt3rrF9+3bj7rvvNhITE4NmkAtnlZWVxsaNG42NGzcagPH8888bGzduNPbt22cYhmE888wzRmJiovGPf/zD2Lx5s3HDDTcYXbp0MWpra0Mc+ende++9RkJCgrFixQqjsLAwsNTU1AT2ueeee4zs7Gzj448/NtavX2/k5uYaubm5IYz6zH75y18aK1euNPbs2WNs3rzZ+OUvf2mYTCZj8eLFhmFEXnsac/JMlJHYpoceeshYsWKFsWfPHuOzzz4zRo4caaSkpBglJSWGYURmmz7//HPDarUaTz31lLFz507jzTffNGJiYow33ngjsE8kvk/I2Z2tf7v99tuNX/7yl4H9P/vsM8NqtRrPPfecsWPHDuOxxx4zbDabsWXLlsA+ofxdae72VFZWGg8//LCxevVqY8+ePcbSpUuNSy+91OjRo4dRV1cXVm1xuVyBvj4jI8N4+OGHjY0bNxo7d+5s8jEjqS1ney8Ol7Y888wzht1uN955552gzyuVlZVB+0TK38zZ2hNJfzNPP/20sXjxYiM/P9/Yvn278dxzzxlWq9V49dVXg9obitemudsSytdFIv9a8kza4ufikzXHtfR1111nXHLJJcbatWuNTz/91OjRo4dxyy23hKpJZ3Sm9jb1vSRS2tscOQWv12v069fPGDVqlLFp0ybjo48+Mjp27GhMmzYtFE06q7O1edeuXcaTTz5prF+/3tizZ4/xj3/8w+jatatx5ZVXBo4RSW2+0BxLc7dVSdsW9Ic//MHIzs427Ha7cfnllxtr1qwJdUhNtnz5cgM4ZZk4caJhGIbh9/uNRx55xEhLSzMcDocxYsQIIy8vL7RBn0Vj7QGMOXPmBPapra01/vu//9tISkoyYmJijO9///tGYWFh6II+i5/+9KdGTk6OYbfbjY4dOxojRowIvJkYRuS1pzEnJ20jsU0333yzkZGRYdjtduOiiy4ybr75ZmPXrl2B7ZHYJsMwjPfff9/o16+f4XA4jF69ehn/+7//G7Q9Et8npGnO1L9dddVVgb6iwd///nfj4osvNux2u9G3b1/jX//6V9D2UP+uNGd7ampqjFGjRhkdO3Y0bDabkZOTY9x1112tdqF9Lm3Zs2dPo/3iVVdd1eRjRlJbzvZeHC5tycnJabQtjz32WGCfSPqbOVt7Iulv5te//rXRvXt3IyoqykhKSjJyc3ON+fPnBx0vlK9Nc7Yl1K+LRPa15Jm01c/FJ2qOa+mjR48at9xyixEXF2c4nU7jJz/5SdCXd+HkTO1t6ntJpLS3uXIKe/fuNcaMGWNER0cbKSkpxkMPPWR4PJ5Wbk3TnK3NBQUFxpVXXml06NDBcDgcRvfu3Y0pU6YY5eXlQceJlDY3R46lOdtqMgzDOPfxuSIiIiIiIiIiIiLSElTTVkRERERERERERCSMKGkrIiIiIiIiIiIiEkaUtBUREREREREREREJI0raioiIiIiIiIiIiIQRJW1FREREREREREREwoiStiIiIiIiIiIiIiJhRElbERERERERERERkTCipK2IiIiIiIiIiIhIGFHSViTC3HHHHdx4441n3Ofqq6/mgQceaNbzPv744wwaNKhZjykiItKS9u7di8lkYtOmTafdZ+7cuSQmJl7wuVasWIHJZKKsrKzFzyUiIpHDMAzuvvtuOnTocNY+KRyZTCbee++9wOOvvvqKYcOGERUV1SrXhyf3r83dlzbls0JT+niRlmANdQAicm5eeuklDMMIdRgiIiJygm9961sUFhaSkJAQ6lBERCSMfPTRR8ydO5cVK1bQtWtXUlJSQh3SBXnssceIjY0lLy+PuLi4Vj//zTffzPXXX99sx8vKyqKwsDDiXxdpm5S0FWlFbrcbu91+QcfQxeC5aY5/cxERkTPxeDzY7XbS09NDHYqIiISZ/Px8MjIy+Na3vnXafSLpmiU/P5+xY8eSk5Nz3sfw+XyYTCbM5nO/+Ts6Opro6OjzPvfJLBaL+m8JWyqPINKCrr76au677z4eeOABUlJSGD16NABbt25lzJgxxMXFkZaWxu23386RI0cCz3vnnXfo378/0dHRJCcnM3LkSKqrq4FTyyNUV1czYcIE4uLiyMjI4He/+90pcZx8SwtAYmIic+fODTyeOnUqF198MTExMXTt2pVHHnkEj8fT5LaWlpZy22230bFjR6Kjo+nRowdz5swBGr+dZNOmTZhMJvbu3RtY9+qrr5KVlUVMTAzf//73ef7554NufcnPz+eGG24gLS2NuLg4LrvsMpYuXRoUR+fOnZkxYwYTJkzA6XRy9913N7kNIiISmfx+P88++yzdu3fH4XCQnZ3NU089Fdi+e/duvvOd7xATE8PAgQNZvXr1GY83e/ZsunXrht1up2fPnvz1r38N2m4ymZg9ezbf+973iI2N5amnnmq0r5s7dy7Z2dmBfu3o0aOnnOsf//gHl156KVFRUXTt2pUnnngCr9cL1N9S+/jjj5OdnY3D4aBTp078/Oc/v4B/KRERaU133HEHP/vZzygoKMBkMtG5c2fg/K8T/X4/M2fOpEuXLkRHRzNw4EDeeeedM8bw8ssv06NHD6KiokhLS+MHP/hBYFvnzp158cUXg/YfNGgQjz/+eKPHMplMbNiwgSeffBKTycTjjz/epGu9hpIG//znP+nTpw8Oh4OCgoJGz7Fw4UIuvvhioqOj+c53vhN0vXjisU50pn77pz/9KQMGDMDlcgH1CfJLLrmECRMmAI2XRzhbDACffvopV1xxBdHR0WRlZfHzn/88cM0u0lyUtBVpYa+//jp2u53PPvuMV155hbKyMq655houueQS1q9fz0cffURxcTE/+tGPACgsLOSWW27hpz/9KTt27GDFihXcdNNNpy2JMGXKFFauXMk//vEPFi9ezIoVK/jiiy/OOc74+Hjmzp3L9u3beemll3j11Vd54YUXmvz8Rx55hO3bt/Phhx+yY8cOZs+efU63mHz22Wfcc8893H///WzatIlrr7026IIboKqqiuuvv55ly5axceNGrrvuOsaNG3dKh//cc88xcOBANm7cyCOPPNLkGEREJDJNmzaNZ555JtAXzZs3j7S0tMD2X//61zz88MNs2rSJiy++mFtuuSWQGD3ZggULuP/++3nooYfYunUr//Vf/8VPfvITli9fHrTf448/zve//322bNnCT3/601OOs3btWu68807uu+8+Nm3axHe+8x3+53/+J2ifTz75hAkTJnD//fezfft2/vjHPzJ37txA//d///d/vPDCC/zxj39k586dvPfee/Tv3/9C/7lERKSVvPTSSzz55JNkZmZSWFjIunXrAtvO9ToRYObMmfzlL3/hlVdeYdu2bTz44IP8+Mc/ZuXKlY2ef/369fz85z/nySefJC8vj48++ogrr7zyvNtTWFhI3759eeihhygsLOThhx9u8nNramr4zW9+w5/+9Ce2bdtGamrqKfvs37+fm266iXHjxrFp0yb+8z//k1/+8pdnPO7Z+u3f//73VFdXB47z61//mrKyMv7f//t/jR6vKTHk5+dz3XXXMX78eDZv3sxbb73Fp59+yn333dfkfw+RJjFEpMVcddVVxiWXXBK0bsaMGcaoUaOC1u3fv98AjLy8PGPDhg0GYOzdu7fRY06cONG44YYbDMMwjMrKSsNutxt///vfA9uPHj1qREdHG/fff39gHWAsWLAg6DgJCQnGnDlzThv7b3/7W2Pw4MGBx4899pgxcODA0+4/btw44yc/+Umj25YvX24ARmlpaWDdxo0bDcDYs2ePYRiGcfPNNxtjx44Net5tt91mJCQknPachmEYffv2Nf7whz8EHufk5Bg33njjGZ8jIiJtR0VFheFwOIxXX331lG179uwxAONPf/pTYN22bdsMwNixY4dhGIYxZ86coL7mW9/6lnHXXXcFHeeHP/yhcf311wceA8YDDzwQtM/Jfd0tt9wS9BzDqO/rTjzXiBEjjKeffjpon7/+9a9GRkaGYRiG8bvf/c64+OKLDbfbfZZ/BRERCVcvvPCCkZOTE7TufK4T6+rqjJiYGGPVqlVB+9x5553GLbfc0ui5/+///s9wOp1GRUVFo9tzcnKMF154IWjdwIEDjcceeyzw+ORryZO3N+Vab86cOQZgbNq0qdE4GkybNs3o06dP0LqpU6cGHf98+u1Vq1YZNpvNeOSRRwyr1Wp88skngW0NnxU2btzY5BjuvPNO4+677w7a55NPPjHMZrNRW1t7xjaKnAuNtBVpYYMHDw56/OWXX7J8+XLi4uICS69evYD6b+wGDhzIiBEj6N+/Pz/84Q959dVXKS0tbfTY+fn5uN1uhg4dGljXoUMHevbsec5xvvXWWwwfPpz09HTi4uKYPn36aW9Zacy9997L/PnzGTRoEL/4xS9YtWrVOZ0/Ly+Pyy+/PGjdyY+rqqp4+OGH6d27N4mJicTFxbFjx45T4hwyZMg5nVtERCLXjh07cLlcjBgx4rT7DBgwIPBzRkYGACUlJac93vDhw4PWDR8+nB07dgStO1tfs2PHjqD+GSA3Nzfo8ZdffsmTTz4Z9JngrrvuorCwkJqaGn74wx9SW1tL165dueuuu1iwYMFpRwiLiEhkOdfrxF27dlFTU8O1114btM9f/vIX8vPzGz3HtddeS05ODl27duX222/nzTffpKampsXb1hi73R7UHzemKX1nY885W7+dm5vLww8/zIwZM3jooYf49re/fUExfPnll8ydOzfodRg9ejR+v589e/acMV6Rc6GJyERaWGxsbNDjqqoqxo0bx29+85tT9s3IyMBisbBkyRJWrVrF4sWL+cMf/sCvf/1r1q5dS5cuXc4rBpPJdEp5hRPr1a5evZrbbruNJ554gtGjR5OQkMD8+fMbrY97OmPGjGHfvn0sXLiQJUuWMGLECCZNmsRzzz0XKDB/YgznUi+3wcMPP8ySJUt47rnn6N69O9HR0fzgBz/A7XYH7Xfyv7mIiLRdTZmMxGazBX42mUxAfV3AC9EcfU1VVRVPPPEEN9100ynboqKiyMrKIi8vj6VLl7JkyRL++7//m9/+9resXLkyqE0iIhJ5zvU6cevWrQD861//4qKLLgra7nA4Gj1HfHw8X3zxBStWrGDx4sU8+uijPP7446xbt47ExETMZvMZrxOboqnXetHR0YE+uLX5/X4+++wzLBYLu3btuuDjVVVV8V//9V+N1pnPzs6+4OOLNNBIW5FWdumll7Jt2zY6d+5M9+7dg5aGjttkMjF8+HCeeOIJNm7ciN1uZ8GCBaccq1u3bthsNtauXRtYV1paytdffx20X8eOHSksLAw83rlzZ9A3rKtWrSInJ4df//rXDBkyhB49erBv375zblvHjh2ZOHEib7zxBi+++CL/+7//G1gPBMVwYqF3gJ49ewbVeAJOefzZZ59xxx138P3vf5/+/fuTnp7eaFF4ERFpP3r06EF0dDTLli1rluP17t2bzz77LGjdZ599Rp8+fc75OCf2zwBr1qwJenzppZeSl5d3yueB7t27By6Co6OjGTduHL///e9ZsWIFq1evZsuWLefRMhERCWdnu048cQKvk7dnZWWd9rhWq5WRI0fy7LPPsnnzZvbu3cvHH38MnHqdWFFRcc4jRZtyrddUvXv35vPPPw9ad3Lf2dhzztZv//a3v+Wrr75i5cqVfPTRR4EJs883hksvvZTt27c32n/b7fYzxityLjTSVqSVTZo0iVdffZVbbrmFX/ziF3To0IFdu3Yxf/58/vSnP7F+/XqWLVvGqFGjSE1NZe3atRw+fJjevXufcqy4uDjuvPNOpkyZQnJyMqmpqfz6178OXOg1uOaaa/h//+//kZubi8/nY+rUqUEjdHr06EFBQQHz58/nsssu41//+lejSeIzefTRRxk8eDB9+/bF5XLxwQcfBGJu+CDx+OOP89RTT/H111+fMor3Zz/7GVdeeSXPP/8848aN4+OPP+bDDz8M+ja2R48evPvuu4wbNw6TycQjjzxywSOlREQkskVFRTF16lR+8YtfYLfbGT58OIcPH2bbtm1nLJlwOlOmTOFHP/oRl1xyCSNHjuT999/n3XffZenSped0nJ///OcMHz6c5557jhtuuIFFixbx0UcfBe3z6KOP8t3vfpfs7Gx+8IMfYDab+fLLL9m6dSv/8z//w9y5c/H5fAwdOpSYmBjeeOMNoqOjycnJOed2iYhIeDvbdWJ8fDwPP/wwDz74IH6/n29/+9uUl5fz2Wef4XQ6mThx4inH/OCDD9i9ezdXXnklSUlJLFy4EL/fHyind8011zB37lzGjRtHYmIijz76KBaL5Zzibsq1XlPdc889/O53v2PKlCn853/+Jxs2bGDu3LlnfM7Z+u2NGzfy6KOP8s477zB8+HCef/557r//fq666iq6du16XjFMnTqVYcOGcd999/Gf//mfxMbGsn37dpYsWXLaCc5EzodG2oq0sk6dOvHZZ5/h8/kYNWoU/fv354EHHgjcnuJ0Ovn3v//N9ddfz8UXX8z06dP53e9+x5gxYxo93m9/+1uuuOIKxo0bx8iRI/n2t799Sn2k3/3ud2RlZXHFFVdw66238vDDDxMTExPY/r3vfY8HH3yQ++67j0GDBrFq1SoeeeSRc2qX3W5n2rRpDBgwgCuvvBKLxcL8+fOB+ttS//a3v/HVV18xYMAAfvOb35wyg/bw4cN55ZVXeP755xk4cCAfffQRDz74IFFRUYF9nn/+eZKSkvjWt77FuHHjGD16NJdeeuk5xSkiIm3PI488wkMPPcSjjz5K7969ufnmm09bs/ZsbrzxRl566SWee+45+vbtyx//+EfmzJnD1VdffU7HGTZsGK+++iovvfQSAwcOZPHixUyfPj1on9GjR/PBBx+wePFiLrvsMoYNG8YLL7wQSMomJiby6quvMnz4cAYMGMDSpUt5//33SU5OPq+2iYhI+DrbdSLAjBkzeOSRR5g5cya9e/fmuuuu41//+tdpy+glJiby7rvvcs0119C7d29eeeUV/va3v9G3b18Apk2bxlVXXcV3v/tdxo4dy4033ki3bt3OKe6mXOs1VXZ2Nv/3f//He++9x8CBA3nllVd4+umnz/icM/XbdXV1/PjHP+aOO+5g3LhxANx999185zvf4fbbb8fn851XDAMGDGDlypV8/fXXXHHFFVxyySU8+uijdOrU6bzaLXI6JuPkAiYiImHirrvu4quvvuKTTz4JdSgiIiIiIiIiIq1G5RFEJGw899xzXHvttcTGxvLhhx/y+uuv8/LLL4c6LBERERERERGRVqWRtiISNn70ox+xYsUKKisr6dq1Kz/72c+45557Qh2WiIiIiIiIiEirUtJWREREREREREREJIxoIjIRERERERERERGRMKKkrYiIiIiIiIiIiEgYUdJWREREREREREREJIwoaSsiIiIiIiIiIiISRpS0FREREREREREREQkjStqKiIiIiIiIiIiIhBElbUVERERERERERETCiJK2IiIiIiIiIiIiImFESVsRERERERERERGRMKKkrYiIiIiIiIiIiEgYUdJWREREREREREREJIwoaSsiIiIiIiIiIiISRpS0FREREREREREREQkjStqKiIiIiIiIiIiIhBElbUVERERERERERETCiJK2IiIiIiIiIiIiImFESVsRERERERERERGRMKKkrYiIiIiIiIiIiEgYsYY6gEjg9/s5dOgQ8fHxmEymUIcjIiItxDAMKisr6dSpE2azvtdsKvWTIiLtg/rJc6c+UkSkfWiJPlJJ2yY4dOgQWVlZoQ5DRERayf79+8nMzAx1GBFD/aSISPuifrLp1EeKiLQvzdlHKmnbBPHx8UD9P7zT6QxxNCIi0lIqKirIysoKvO9L06ifFBFpH9RPnjv1kSIi7UNL9JFK2jZBw20sTqdTHa2ISDug2xfPjfpJEZH2Rf1k06mPFBFpX5qzj1QhIhERkQg1e/ZsBgwYELgQzM3N5cMPPwxsv/rqqzGZTEHLPffcE3SMgoICxo4dS0xMDKmpqUyZMgWv19vaTREREREREZETaKStiIhIhMrMzOSZZ56hR48eGIbB66+/zg033MDGjRvp27cvAHfddRdPPvlk4DkxMTGBn30+H2PHjiU9PZ1Vq1ZRWFjIhAkTsNlsPP30063eHhEREREREamnpK2IiEiEGjduXNDjp556itmzZ7NmzZpA0jYmJob09PRGn7948WK2b9/O0qVLSUtLY9CgQcyYMYOpU6fy+OOPY7fbW7wNIiIiIiIiciqVRxAREWkDfD4f8+fPp7q6mtzc3MD6N998k5SUFPr168e0adOoqakJbFu9ejX9+/cnLS0tsG706NFUVFSwbdu2057L5XJRUVERtIiIiIiIiEjz0UhbERGRCLZlyxZyc3Opq6sjLi6OBQsW0KdPHwBuvfVWcnJy6NSpE5s3b2bq1Knk5eXx7rvvAlBUVBSUsAUCj4uKik57zpkzZ/LEE0+0UItERERERERESVsREZEI1rNnTzZt2kR5eTnvvPMOEydOZOXKlfTp04e77747sF///v3JyMhgxIgR5Ofn061bt/M+57Rp05g8eXLgcUVFBVlZWRfUDhEREREREfmGyiOIiIhEMLvdTvfu3Rk8eDAzZ85k4MCBvPTSS43uO3ToUAB27doFQHp6OsXFxUH7NDw+XR1cAIfDgdPpDFpERERERESk+YR10nb27NkMGDAgcEGYm5vLhx9+GNh+9dVXYzKZgpZ77rkn6BgFBQWMHTuWmJgYUlNTmTJlCl6vt7WbIiIi0ir8fj8ul6vRbZs2bQIgIyMDgNzcXLZs2UJJSUlgnyVLluB0OgMlFkRERERERKT1hXV5hMzMTJ555hl69OiBYRi8/vrr3HDDDWzcuDEwK/Zdd93Fk08+GXhOTExM4Gefz8fYsWNJT09n1apVFBYWMmHCBGw2G08//XSrt0dERKQ5TZs2jTFjxpCdnU1lZSXz5s1jxYoVLFq0iPz8fObNm8f1119PcnIymzdv5sEHH+TKK69kwIABAIwaNYo+ffpw++238+yzz1JUVMT06dOZNGkSDocjxK0TERERERFpv8I6aTtu3Ligx0899RSzZ89mzZo1gaRtTEzMaW/hXLx4Mdu3b2fp0qWkpaUxaNAgZsyYwdSpU3n88cex2+0t3gZpfi6Xi/Xr15+yfsiQIUoyiEi7UlJSwoQJEygsLCQhIYEBAwawaNEirr32Wvbv38/SpUt58cUXqa6uJisri/HjxzN9+vTA8y0WCx988AH33nsvubm5xMbGMnHixKAvQ9s7n8/H7t27A4+7du2KxWIJYUQiIiIiItIehHXS9kQ+n4+3336b6upqcnNzA+vffPNN3njjDdLT0xk3bhyPPPJIYLTt6tWr6d+/f9DM2KNHj+bee+9l27ZtXHLJJY2ey+VyBd1aWlFR0UKtkvOxfv161r61nL5dewfWbdu9A4Dhw4eHKiwRkVb32muvnXZbVlYWK1euPOsxcnJyWLhwYXOG1abs3r2b9957j/T0dIqKirjxxhvp0aNHqMMSEREROcXkyfdSWXm40W3x8R15/vnZrRyRiFyIsE/abtmyhdzcXOrq6oiLi2PBggWBOnu33norOTk5dOrUic2bNzN16lTy8vJ49913ASgqKgpK2AKBx0VFRac958yZM3niiSdaqEXSHPp27c2wvkNCHYaIiLQD6enpZGZmhjoMERERkTOqrDzMtGlXNLpt5sxPWjkaEblQYZ+07dmzJ5s2baK8vJx33nmHiRMnsnLlSvr06cPdd98d2K9///5kZGQwYsQI8vPz6dat23mfc9q0aUyePDnwuKKigqysrAtqh4iIiIiIiIiIiEhTmEMdwNnY7Xa6d+/O4MGDmTlzJgMHDuSll15qdN+hQ4cCsGvXLqB+ZExxcXHQPg2PT1cHF8DhcOB0OoMWERERERERERERkdYQ9knbk/n9/qB6syfatGkTABkZGQDk5uayZcsWSkpKAvssWbIEp9MZKLEgIiIiIiIiIiIiEk7CujzCtGnTGDNmDNnZ2VRWVjJv3jxWrFjBokWLyM/PZ968eVx//fUkJyezefNmHnzwQa688koGDBgAwKhRo+jTpw+33347zz77LEVFRUyfPp1JkybhcDhC3DoRERERERERERGRU4V10rakpIQJEyZQWFhIQkICAwYMYNGiRVx77bXs37+fpUuX8uKLL1JdXU1WVhbjx49n+vTpgedbLBY++OAD7r33XnJzc4mNjWXixIk8+eSTIWyViIiIiIiIiIiIyOmFddL2tddeO+22rKwsVq5cedZj5OTksHDhwuYMS0RERERERERERKTFhHXSVkRERKSl+Xw+du/eHXjctWtXLBZLCCMSEREREZH2TklbERERadd2797Ne++9R3p6OkVFRdx444306NEj1GGJiIiIiEg7pqStiIiItHvp6elkZmaGOgwREREREREAzKEOQERERERERERERES+oaStiIiIiIiIiIiISBhR0lZERERERETatGeeeQaTycQDDzwQWFdXV8ekSZNITk4mLi6O8ePHU1xcHPS8goICxo4dS0xMDKmpqUyZMgWv19vK0YuISHukpK2IiIiIiIi0WevWreOPf/wjAwYMCFr/4IMP8v777/P222+zcuVKDh06xE033RTY7vP5GDt2LG63m1WrVvH6668zd+5cHn300dZugoiItENK2oqIiIiIiEibVFVVxW233carr75KUlJSYH15eTmvvfYazz//PNdccw2DBw9mzpw5rFq1ijVr1gCwePFitm/fzhtvvMGgQYMYM2YMM2bMYNasWbjd7lA1SURE2gklbUVERERERKRNmjRpEmPHjmXkyJFB6zds2IDH4wla36tXL7Kzs1m9ejUAq1evpn///qSlpQX2GT16NBUVFWzbtq3R87lcLioqKoIWERGR82ENdQAiIiIiIiIizW3+/Pl88cUXrFu37pRtRUVF2O12EhMTg9anpaVRVFQU2OfEhG3D9oZtjZk5cyZPPPFEM0QvIiLtnUbaioiIiLQgn8/Hzp07A4vP5wt1SCIibd7+/fu5//77efPNN4mKimq1806bNo3y8vLAsn///lY7t4iItC1K2oqIiIi0oN27d/Pee++xZs0a3nvvPXbv3h3qkERE2rwNGzZQUlLCpZdeitVqxWq1snLlSn7/+99jtVpJS0vD7XZTVlYW9Lzi4mLS09MBSE9Pp7i4+JTtDdsa43A4cDqdQYuIiMj5UNJWREREpIWlp6eTmZl52ot8ERFpXiNGjGDLli1s2rQpsAwZMoTbbrst8LPNZmPZsmWB5+Tl5VFQUEBubi4Aubm5bNmyhZKSksA+S5Yswel00qdPn1Zvk4iItC+qaSsiIiIiIiJtSnx8PP369QtaFxsbS3JycmD9nXfeyeTJk+nQoQNOp5Of/exn5ObmMmzYMABGjRpFnz59uP3223n22WcpKipi+vTpTJo0CYfD0eptEhGR9kVJWxEREZHjDMOgvLycmpoaYmJiQh2OiIi0oBdeeAGz2cz48eNxuVyMHj2al19+ObDdYrHwwQcfcO+995Kbm0tsbCwTJ07kySefDGHUIiLSXihpKyIiIu2eYRjk5+dz6NAhdu/ezQcffEBycjK9e/cOdWgiItJMVqxYEfQ4KiqKWbNmMWvWrNM+Jycnh4ULF7ZwZCIiIqdSTVuJeL4qNxeVxZO2ys+Rv2zHU1wd6pBERCTCVFRUcODAAfx+PxaLBYCjR4/y6aefUlJSgmEYIY5QRERERETaE420lYjmq3RTu7GERE801EHd0aPUfV1K4ve6End5RqjDExGRCFBbW8uxY8cA6NChA6NHjyY7O5tVq1bx6aefUllZSWFhYYijFBERERGR9kRJW4lY/jovtRtLMDx+aq0eqvrbyaxOxPV1KWXv7sLidGDuEsv69etPee6QIUM0eYCIiACwadMm/H4/cXFxJCYmYjabiY6OZsSIEdTU1LBhwwb27t1LZmZmqEMVEREREZF2QklbiVjuPeUYHj/mOBs77YfYd+wYA/r3p4ML4vdByZvbWJ6ax5G8Q/Tv3jfwvG27dwAwfPjwUIUuIiJhwuv1UlBQAED37t2prKwM2t6jRw82b96Mx+OhrKwsBBGKiIiIiEh7pKStRCSb14znaH3tWkfPDnz1yTJKS4/R1ZVKtQFdrElEe2x03xmPJS6FYX2HhDhiEREJRwcPHsTr9WI2m3E6nackbS0WCx06dKC4uJjy8nJ8Pl+IIhURERERkfZEE5FJROpYHQsGWDpEYU2sL3NwcWY3hvUdwtB+Q0i5LBtM0DmmEx2IC3G0IiItY/bs2QwYMACn04nT6SQ3N5cPP/wwsL2uro5JkyaRnJxMXFwc48ePp7i4OOgYBQUFjB07lpiYGFJTU5kyZQper7e1mxIye/bsASA6OhqTydToPrGxsdjtdvx+/yn/fiIiIiIiIi1BSVuJOGaXQWJtFACOrgmN7xNjw5YVD0B3MjD8mvVbRNqezMxMnnnmGTZs2MD69eu55ppruOGGG9i2bRsADz74IO+//z5vv/02K1eu5NChQ9x0002B5/t8PsaOHYvb7WbVqlW8/vrrzJ07l0cffTRUTWp1JyZtT8dkMpGcnAzAgQMHWiUuERERERFp35S0lYgTUwgmTJjj7VgSTj+ZmKNzAi7DQyxReIuqWzFCEZHWMW7cOK6//np69OjBxRdfzFNPPUVcXBxr1qyhvLyc1157jeeff55rrrmGwYMHM2fOHFatWsWaNWsAWLx4Mdu3b+eNN95g0KBBjBkzhhkzZjBr1izcbneIW9fy3G43+/fvByAmJuaM+56YtPX7/S0em4iIiIiItG9K2krEiT1YP2rWlnbmC2yTzcwOT/3kMq59FRiGRtuKSNvl8/mYP38+1dXV5ObmsmHDBjweDyNHjgzs06tXL7Kzs1m9ejUAq1evpn///qSlpQX2GT16NBUVFYHRuo1xuVxUVFQELZGooKAAv99PTEwMVuuZy/wnJSVhMpmora2lsLCwlSIUEREREZH2SklbiSjecheOY/U/W8+StAXY7S3Cgw+jxov3cG0LRyci0vq2bNlCXFwcDoeDe+65hwULFtCnTx+Kioqw2+0kJiYG7Z+WlkZRUREARUVFQQnbhu0N205n5syZJCQkBJasrKzmbVQr2bt3LwDp6emnrWfbwGw2B0bjfvXVVy0dmoiIiIiItHNK2kpEqf3yMCag2ubGHHXmUVEAXnwc5CgAbo22FZE2qGfPnmzatIm1a9dy7733MnHiRLZv396i55w2bRrl5eWBpaHEQKRpmFSsofTB2TQkbRvq4IqIiIiIiLSUsE7aalZsOVnt1iMAlEe7mvycAxwFM/gr3PjK236NRhFpX+x2O927d2fw4MHMnDmTgQMH8tJLL5Geno7b7aasrCxo/+LiYtLT04H6EaYn95sNjxv2aYzD4Qj0zQ1LJDp8+DAACQmNT2p5sobJyg4dOoTH42mxuERERERERMI6aatZsds3l8vFZ599FlhWL/8UV0ElAOXWmiYfx2PyYk2Lrf/5YGWLxCoiEi78fj8ul4vBgwdjs9lYtmxZYFteXh4FBQXk5uYCkJuby5YtWygpKQnss2TJEpxOJ3369Gn12FvTiQntpiZtrVYrUVFR+P1+Dh061ILRiYiIiIhIe3f2+8tDaNy4cUGPn3rqKWbPns2aNWvIzMzktddeY968eVxzzTUAzJkzh969e7NmzRqGDRsWmBV76dKlpKWlMWjQIGbMmMHUqVN5/PHHsdvtoWiWNNH69etZ+9Zy+nbtDYCzzoGJBI64yigqLTnLs4PZM+PwFlbjLa7B0vHMdQtFRCLFtGnTGDNmDNnZ2VRWVjJv3jxWrFjBokWLSEhI4M4772Ty5Ml06NABp9PJz372M3Jzcxk2bBgAo0aNok+fPtx+++08++yzFBUVMX36dCZNmoTD4Qhx61rWkSP1d27ExMQQFRXVpOeYTCZSU1MpKCigoKCAnJyclgxRRERERETasbAeaXsizYrdPvXt2pthfYcwrO8QusZ0AuCYueqcj2NxOjDH28GAxJro5g5TRCQkSkpKmDBhAj179mTEiBGsW7eORYsWce211wLwwgsv8N3vfpfx48dz5ZVXkp6ezrvvvht4vsVi4YMPPsBisZCbm8uPf/xjJkyYwJNPPhmqJrUKn8/H1q1bAYiLi2Pv3r1NrnnesWNHoL78koiIiIiISEsJ65G2UD8rdm5uLnV1dcTFxQVmxd60aVOLzor9xBNPNG9D5IIYhoH3aB0ARb7S8zqGPTOOuh3H6FAbTaEmJBORNuC111474/aoqChmzZrFrFmzTrtPTk4OCxcubO7Qwtru3btZt24dUF8ff8mSJWRnZzfpuQ1J2/379+P3+zGbI+b7bxERERERiSBhf6WhWbEFwF/jxXD5wAyH/eXndQxrWgxYTNh9FhxHmzlAERGJKA0lklJTUwOJWKivCbx371527tzJzp07TxmFm5SUhM1mo66uLjCRmYiIiIiISHML+5G2DbNiAwwePJh169bx0ksvcfPNNwcmETlxtO3Js2J//vnnQcdr6qzYbb2WX6TxHa0FwJIYha/Kf17HMFnM2NJj8RysIq5AI21FRNozt9sN1Ne0PVFJSQn5+fmBO3K2bNkSNArXbDaTmZnJnj172L9//yl39IiIiIiIiDSHsB9pezLNit0++cpcAFiSLiyZbsuIBSCmEPy13guOS0REIo/P58Pj8QCnJm2hfvRtZmYmmZmZQaNwG2RlZQFw4MCBlg1URERERETarbAeaatZsQXq69k2JG2tiU2b4ft0zE47dVYvUV4rNV8eJm5YRnOEKCIiEaRhglGLxRIok3AuMjMzASVtRURERESk5YT1SFvNii1wvJ6txw9mE2bnuV9cn8hkMlEWXV9qoXr96SejExGRtquyshKoH2VrMpnO+fkXXXQRAEeOHKG2trZZYxMRkeYxe/ZsBgwYgNPpxOl0kpuby4cffhjYfvXVV2MymYKWe+65J+gYBQUFjB07lpiYGFJTU5kyZQper+7WExGR1hHWI201K7bACaURnHZM5nO/uD5ZWXQdaVXxeA5U4S6sxn68ZIKIiLQPDUnb6Ojo83p+bGwsSUlJlJaWcvDgQbp3747P52P37t2Bfbp27YrFYmmWeEVE5NxlZmbyzDPP0KNHDwzD4PXXX+eGG25g48aN9O3bF4C77roraEDPiSVzfD4fY8eOJT09nVWrVlFYWMiECROw2Ww8/fTTrd4eERFpf8I6aSsC4CurAy68nm3geGaDmnSILYSa9UXYx3U77b4ul4v169c3um3IkCEqsyEiEoGqq6uB+i9/z1dmZialpaUcOHCA7t27s3v3bt577z3S09MpKirixhtvpEePHs0VsoiInKNx48YFPX7qqaeYPXs2a9asCSRtY2JiTjtB9eLFi9m+fTtLly4lLS2NQYMGMWPGDKZOncrjjz9+XuV1REREzkVYl0cQgRNG2l5gPdsTVWXVj9it2ViC4fWfdr/169ez9q3lVK0rClrWvrX8tMlcEREJb1VVVcCFJ20huK5teno6mZmZp00AiIhIaPh8PubPn091dXVg0mqAN998k5SUFPr168e0adOoqakJbFu9ejX9+/cnLS0tsG706NFUVFSwbdu2057L5XJRUVERtIiIiJwPjbSVsGbzmTHqfGACS0LzfZtd17F+UjJ/hZvaHUeJ6X/q7OAN+nbtzbC+Q5rt3CIiElrNMdK2U6dOQH29w6+//pp9+/ZhGEazxCciIs1jy5Yt5ObmUldXR1xcHAsWLKBPnz4A3HrrreTk5NCpUyc2b97M1KlTycvLC8yRUlRUFJSwBQKPi4pOPzfGzJkzeeKJJ1qoRSIi0p4oaSthLdptA8AcZ8dkacaB4WYTsYPTqFy+n+p1xWdM2oqISNvh9/ubZaRtQ+LX7XbzySefkJeXR3Z2drPEKCIizaNnz55s2rSJ8vJy3nnnHSZOnMjKlSvp06cPd999d2C//v37k5GRwYgRI8jPz6dbt9OXTzubadOmMXny5MDjiooKsrKyLqgdIiLSPqk8goS1GE990rY5R9k2iB1c/025a2cp3uMlGEREpG2rqqrC768vi3MhdcktFksg6RsVFUXHjvryT0Qk3Njtdrp3787gwYOZOXMmAwcO5KWXXmp036FDhwKwa9cuoL7kTXFxcdA+DY/PVAbH4XDgdDqDFhERkfOhpK2EteiGpK2z+Sf8sqZEY++SAAbUfFF89ieIiEjEKysrA8BqtWI2X9jHoOjoaADKy8svNCwREWkFfr8fl6vxwRqbNm0CICMjA4Dc3Fy2bNlCSUlJYJ8lS5bgdDoDJRZERERaksojSFhwuVynTOy15cstXO+p/0DUEiNtAWKHpOHeU071+mLir87CZDa1yHlERCQ8nJi0vVDR0dGUlpZSVlbWLMcTEZHmM23aNMaMGUN2djaVlZXMmzePFStWsGjRIvLz85k3bx7XX389ycnJbN68mQcffJArr7ySAQMGADBq1Cj69OnD7bffzrPPPktRURHTp09n0qRJF3SnhoiISFPpCkPCwvr161n71nL6du0dWHd03V7MWX3BasYU3TK/qtH9Uyj7Zz6+Y3W4dpURdXFSi5xHRETCQ2lpKQA2m+2Cj+VwODCZTLjdbiwWywUfT0REmk9JSQkTJkygsLCQhIQEBgwYwKJFi7j22mvZv38/S5cu5cUXX6S6upqsrCzGjx/P9OnTA8+3WCx88MEH3HvvveTm5hIbG8vEiRN58sknQ9gqERFpT5S0lbDRt2tvhvUdEnjsKqi/3dSSYMdkapkRsGa7hdghaVR9dojKTw8qaSsi0kb5fD52795NQUEB0Dwjbc1mM06nk/Lycnw+3wUfT0REms9rr7122m1ZWVmsXLnyrMfIyclh4cKFzRmWiIhIk6mmrYStDub6ov0WZ8uURmgQ961OYALX16V4Smpa9FwiIhIau3fv5r333uPgwYMAeDyeZjluQkICgJK2IiIiIiLSrJS0lbDVwRwPtMwkZCeyJkcT1ScZgKpPD7bouUREJHROnO27ucoZJCYmAvWT2xiG0SzHFBERERERUdJWwpLh8eM0xwAtNwnZieK/fREA1RuK8ZbWtfj5RESk9RmGQV1d/Xu82dw8H4ESEhKw2WwYhtFso3dFRERERESUtJWw5KtwAVCDC5Ot5Sd3sXd24uiaAD6DiqUFLX4+ERFpfV6vN/BzcyVtzWYzqampAIGEsIiIiIiIyIVS0lbCkq/cDUAFta1yPpPJhPO6zgDUfFGs2rYiIm1QQ9LWZDI16wSXaWlpALjd7qDRtrt27eLPf/4z27dvb7ZziYiIiIhI+3DhUyeLtICGkbYVtF7y1JHtJKpPMnXbj1L2wW5SftK31c4tIiIt78SkbXOKi4vDbDbj9/s5dOgQJpOJNWvWkJ+fD8D+/fvJzMxs1nOKiIiIiEjbpqSthB3DMPBX1I+0rWzFpC1AwpjO1H19DNfXpdRsKG7Vc4uISMu60KSt3+9n7969AOzduzcw8ZjJZMJqteJ2u9m7dy8WiwWfzwfUT1RWVlbG0aNH6dq164U3QkRERERE2gWVR5CwY9R6MTx+fIafSlq3PqCtYwzOkTkAlH2wG0utZgIXEWkrGhKp51vPtqSkhE8++YQ1a9awZMkSKioqAtusVivR0dGB80RFRTFx4kRuv/12TCYTNTU1lJaWXngjRERERESkXVDSVsKO7/go2zJ/FYap9ZOm8VdkYsuMw6jz0XG9QQhCEBGRFtAc5RFSU1PJzMykY8eOQetNJhOxsbH079+fxMRErr/+erp06UJycjLdunUD6pO+IiIiIiIiTaGkrYQdX3l9Pdtj/sqQnN9kMZF8Sy9M0VYcZZBRER+4BVZERCJXwyRhzV3T9kQdOnQgOTk5MOoWID09HYDq6uoWO6+IiIiIiLQtStpK2PFV1o+0PRqipC2ANTma5Ft7YQBJtdG491Wc9TkiIhLeWmoisrNJTEwE6pO2+hJQRERERESaQhORSVgxDAN/Vf1IqDJ/FQ4crXZul8vF+vXrg9ZVdDhE/2OdcOeXY3ZYsWXEtlo8IiLSfHw+H36/Hzj/mrbnKz4+HpPJhN/vDySORUREREREzkQjbSWs+Gu84DPAbKLSqGnVc69fv561by2nal1RYFn4+VIKOAxA3Y6jgdINIiISWWpq6vuU1k7YNpzTZrMB9V8QioiIiIiInI1G2kpY8R8vjWCOs2FUtf75+3btzbC+QwKPt+3+inyK6NoxG+/hWmo3HyHm8rTWD0xERC5IQz1Zh8PR6uURGs7rdrtxu92tfm4REREREYk8GmkrYaWhnq0l3h7iSE5ggqg+yZhjbRhuH3Xbj4FKEopIGJg5cyaXXXYZ8fHxpKamcuONN5KXlxe0z9VXX43JZApa7rnnnqB9CgoKGDt2LDExMaSmpjJlypQ2dxt/w0hbh6P1yu6cyG6v79eUtBURERERkaZQ0lbCSkM9W3M4JW0Bk9VMdP8UMJvwHasjsTYq1CGJiLBy5UomTZrEmjVrWLJkCR6Ph1GjRgVGlTa46667KCwsDCzPPvtsYJvP52Ps2LG43W5WrVrF66+/zty5c3n00UdbuzktquHfJCoqNO/fStqKiIiIiMi5UHkECR8G+CoaRtraQhzMqcyxNhxdE3DtKiO9Mo7CWg23FZHQ+uijj4Iez507l9TUVDZs2MCVV14ZWB8TE0N6enqjx1i8eDHbt29n6dKlpKWlMWjQIGbMmMHUqVN5/PHHA8nGSHfiSNvKyspWP3/Dv6PH42lzo5hFRERERKT5aaSthA2b3wxeP5jAHBueSQJbdjxmpx2LYSbhayVtRSS8lJeXA9ChQ4eg9W+++SYpKSn069ePadOmBRKYAKtXr6Z///6kpX1Tr3v06NFUVFSwbdu2Rs/jcrmoqKgIWsJdqMsjWK3WwGRkDa+TiIiIiIjI6WikrYSNKE/9r6M51obJ0vqTxDSFyWQi6uIkatYXE1cAnpIabKkxoQ5LRAS/388DDzzA8OHD6devX2D9rbfeSk5ODp06dWLz5s1MnTqVvLw83n33XQCKioqCErZA4HFRUVGj55o5cyZPPPFEC7WkZYQ6aQv1I57Ly8tDMtJXRERE2ia/30td3QE8nmPYbL5QhyMizSisR9pqgpX2JcpTPwIp3OrZnsyS4KDC4cIElC/aG+pwREQAmDRpElu3bmX+/PlB6++++25Gjx5N//79ue222/jLX/7CggULyM/PP+9zTZs2jfLy8sCyf//+Cw2/xYVD0rbh3CfXHBYRERE5V273UXbumsm/P7mE1WtGsH7DD7lp/GYOHppPTc1uDEN3hopEurAeadswwcpll12G1+vlV7/6FaNGjWL79u3ExsYG9rvrrrt48sknA49jYr4Z+dgwwUp6ejqrVq2isLCQCRMmYLPZePrpp1u1PXJmUd76X0dLXPjVsz1ZSXwV8S4HdduO4imqxpYee/YniYi0kPvuu48PPviAf//732RmZp5x36FDhwKwa9cuunXrRnp6Op9//nnQPsXFxQCnrYPrcDhCmvw8Vx6PJzABWChr9Db8m51YnkJERETkXP3P/9zMpYM34nDUj6z1ek143BaiY7y43SUUl3xAVFQWqR2vw2KJDnG0InK+wnqk7UcffcQdd9xB3759GThwIHPnzqWgoIANGzYE7dcwwUrD4nQ6A9saJlh54403GDRoEGPGjGHGjBnMmjVLMziHmeiG8ghhPtIWwGX1UZNR/3PlJwdDG4yItFuGYXDfffexYMECPv74Y7p06XLW52zatAmAjIz6N7Hc3Fy2bNlCSUlJYJ8lS5bgdDrp06dPi8Td2hrKEZhMJqzW0H1fHRUVBShpKyLSGmbPns2AAQNwOp04nU5yc3P58MMPA9vr6uqYNGkSycnJxMXFMX78+MCXlg10x6aEo5KSj7h86AYcDh92Wwppqd+je7f76NPnv5nxpIeEhMGYTBbq6vZzqPAt3O6joQ5ZRM5TWCdtT6YJVtous8vA5rcAYImApC1ARbf6urs1m0rwVeoLABFpfZMmTeKNN95g3rx5xMfHU1RURFFREbW1tQDk5+czY8YMNmzYwN69e/nnP//JhAkTuPLKKxkwYAAAo0aNok+fPtx+++18+eWXLFq0iOnTpzNp0qSIGk17Jg39uNVqxWQKXc10lUcQEWk9mZmZPPPMM2zYsIH169dzzTXXcMMNNwSuAR988EHef/993n77bVauXMmhQ4e46aabAs9vuGPT7XazatUqXn/9debOncujjz4aqiaJUFa+ga3bHsBiMYiJ6UZGxo+Iiekc+HxTVQUdkobTKeM/sFqdeL0VFBa9q8StSIQK6/IIJ9IEK22b/Xhe3BRtxWRt2e8S3F4PmzdvPmX95s2b6exLbvIx1u/fwrVJ/YgqNfjq72sp62VmyJAhbSbJISLhb/bs2UB9ffcTzZkzhzvuuAO73c7SpUt58cUXqa6uJisri/HjxzN9+vTAvhaLhQ8++IB7772X3NxcYmNjmThxYlDZoUjk8/nYvXs3AHv37gXq2xpKKo8gItJ6xo0bF/T4qaeeYvbs2axZs4bMzExee+015s2bxzXXXAPU9529e/dmzZo1DBs2LHDH5tKlS0lLS2PQoEHMmDGDqVOn8vjjj4e03I60T3V1hWzZ8t8Yhof9+xO44ttjMJkav3a225PplPEfFBUvwO0+TFHxAuLiOrduwCJywSImadswwcqnn34atP7uu+8O/Ny/f38yMjIYMWIE+fn5dOvW7bzONW3aNCZPnhx4XFFRQVZW1vkFLk1irx9E3SqjbHcW5FNaeoyurtSg9ds//YK4Hpec0zFK+maRTQKx+X6WfPlvAIYPH97sMYuINOZsE0xkZWWxcuXKsx4nJyeHhQsXNldYYWH37t289957pKenU1ZWBpz936ulNZRHcLlcuN1uXfCLiLQSn8/H22+/TXV1Nbm5uWzYsAGPx8PIkSMD+/Tq1Yvs7GxWr17NsGHDTnvH5r333su2bdu45JLGrxtcLhculyvwWHdtSnMwDIPt2x/G7T5CXFwv1q6xc+UVZx7sZLFEkZ52I0VFC3B7jnDFlbvxeiuxWuNbKWoRuVARUR6hYYKV5cuXn9MEK1A/icrJtYmaMsFKQ+2jhkValr28/kLaHN86k5BdnNmNYX2HBC1dOnU+52P0uaQfJrsFq9/M0E4DWyZYERE5L+np6WRmZgaSpWZzaD/2WCyWwO2LuogXEWl5W7ZsIS4uDofDwT333MOCBQvo06cPRUVF2O12EhMTg/ZPS0sL3I15PndsQv1dmwkJCYFFg3+kORw6NJ/SsjWYzVH07zcLr7dpdw9ZLNGkpX0PiyWWhIQ6tm79OYbha+FoRaS5hHXSVhOstB+tOdK2OZnMJmydYgFIqtGsnCIi4ahh4tFQJ21PnAitoU6/iIi0nJ49e7Jp0ybWrl3Lvffey8SJE9m+fXuLnnPatGmUl5cHlv3797fo+aTtq3MVsXPXMwB06/oQMTGdz+n5Vmscaanj8HrNHD32b/bund0CUYpISwjr8giTJk1i3rx5/OMf/whMsAKQkJBAdHQ0+fn5zJs3j+uvv57k5GQ2b97Mgw8+eNoJVp599lmKiora3AQrkc7v8mE9PieLOcKStgC2TnG491YQ57ZTXhPaW29FRORUDbeptlbS1u/3B+roQn1N3YbSDFarFY/Ho6StiEgrsNvtdO/eHYDBgwezbt06XnrpJW6++WbcbjdlZWVBo22Li4sDd2Omp6fz+eefBx3vbHdsQv1dm7rOlOaUn/8cPl8VTucgsrImntcxHI5U1q/LZFhuAbv3vERi4uUkJV3ezJGKSHML65G2s2fPpry8nKuvvpqMjIzA8tZbbwEEJlgZNWoUvXr14qGHHmL8+PG8//77gWM0TLBisVjIzc3lxz/+MRMmTIj4CVbaEk9RNSbAY/Zhtod2kpjzYY62YulQf+ttXIGStiIi4aa1k7YlJSV88sknrFmzhjVr1rBkyZJAOYSGkbbnWh7B5/Oxc+fOwOLz6dZGEZFz5ff7cblcDB48GJvNxrJlywLb8vLyKCgoIDc3F9AdmxIeKiq3UlS0AICeFz+GyXT+18t79yaTnv59wM+27Q/idh9rpihFpKWE9UhbTbDSPniL62fRdlkj9wLU1ikW37E6Yg+A4TcwmU2hDklERKj/LBGK8gipqamBOvwn1j483/IIJ06sVlRUxI033kiPHj2aL2ARkTZm2rRpjBkzhuzsbCorK5k3bx4rVqxg0aJFJCQkcOeddzJ58mQ6dOiA0+nkZz/7Gbm5uQwbNgzQHZsSeoZhsHPn0wCkp92A0znggo/Z8+InqKj4kpqa3Wzf8QsGDng1UG9fRMJPWI+0lfbBU1xfG8Fl9YY4kvNnTYnBZ/JjrQXXbt3yKiISLjweT+BL4FDXtIXzT9rCNxOrnem2XBERqVdSUsKECRPo2bMnI0aMYN26dSxatIhrr70WgBdeeIHvfve7jB8/niuvvJL09HTefffdwPN1x6aE2rHSzygrW4vZbKdbt4eb5ZhWayz9+v0Bs9nO0aPL2X9gbrMcV0RaRliPtJX2wVNSP9K2LoKTtiaLifIoFx1qo6n5opio7omhDklERPhmEjIgLEaSnG95BBEROTevvfbaGbdHRUUxa9YsZs2addp9dMemhIphGOzZ8xIAF110G1FRnZrt2PFxvejRfTp5Xz9Kfv6zJHe4gtjY7s12fBFpPqEfciLtnidQHiFyk7YAZdG1ANRuPYLfFbmlHkRE2pLWrmd7NieOtD1bGSgRERFpn46VfkZ5+ReYzQ5ysu9u9uNfdNGtJHe4Er/fzbbtD+P3e5r9HCJy4cLjCkbaLX+tF39F/SioSK5pC1Br8+KJBcPtp3brkVCHIyIifJO0DYdRtvBN0tbj8VBbWxviaERERCQc7dnzB6A+uepwpDb78U0mE716z8RqdVJZuYW9+15p9nOIyIVT0lZCqqGerTcK/OYIH3FkgqrM+qRAzYbiEAcjIiLwTXmEcEnams3mwAQ251PXVkRERNq28vIvKC9fj8lkb5FRtg2iHOn0vPgJAPbu/X9UVGxpsXOJyPlR0lZCqqE0gic+xIE0k+pMwFQ/GZm3tC7U4YiItHvhNtIWIDY2FlBdWxERETnVvoI/AZCefkOLjLI9UVraOFI7jsEwvGzfMQW/39Wi5xORc6OJyCSkvCUnJG1rQhtLc/DFmHB0deLKL6fmixKcI7JDHZKISLsWjknbmJgYjh07ppG2IiIibcTkyfdSWXm40W3x8R15/vnZTTpOTc1eDh9eDEB29p3NFh/Axo0bueuuH5yy3m73Mva7dmAne/f9L127/KxZzysi509JWwmphpG27nhTm0jaAsRcmlaftN1YQvw1WWGVKBARaW/CrTwCfDPSVklbERGRtqGy8jDTpl3R6LaZMz9p8nEK9v8ZMEhO/g5xsT2aKboGntPG+MablQwfvpe9e18mLXUMsbHdm/ncInI+VB5BQqqtlUcAiO6XgsluxnukFndBZajDERFp1xpG2prN4fORJyYmBlDSVkRERL7hdh+lsPAdAHKy/7NVz72/IJHk5KsxDDdffTUdw/C36vlFpHHhcwUj7Y6/xoO/sn4ElCcuxME0I7PDQnS/FEATkomIhJLf78fr9QLhNdK2IWmrmrYiIiLS4MDBefj9LuLj+5GYOLSVz26i58VPYrHEUFa+jkOH3mrl84tIY5S0lZDxHK9na0lwYNjC52L6fLm9HjZv3sxnn33Gbkd9PaPKL4pY9e9PAyO9RESk9fh8PiC8RtmCyiOIiIhIMJ+vjgMH/gJAdvZ/huTL5ujoi+jadTIAu/J/g8tV0uoxiEiw8LqKkXaloTSCNS0mxJE0j50F+RxatYuqdUUc3V2M2+zD7IWDC7axfv36UIcnItLuNIyytdvtYTXStiFpW1FRgd+v2w9FRETau6Lif+DxHCPK0YnUjmNCFkdW5gTi4/vj9Vayc9fMkMUhIvWUtJWQ8R5P2traSNIW4OLMbgzrO4Rh/YYQl50EQL/4biGOSkSkfWpI2jocjhBHEiwqKgqTyYRhGFRVVYU6HBEREQkhwzACo2wzsyZgNoduvniTyUKvnjMAE8XF/6SsfEPIYhERCN27gbR7nuJq4HjStg1WD7BlxOLeW0Gc287qL7afsn3IkCFhl0gQEWlLGsojOByOQAI3HJjNZpxOJ+Xl5ZSXl+N0OkMdkoiIiIRIWfl6qqq+wmyOolPGD0MdDk5nfzpl/JBDhX/n669ncNmQdzGZNN5PJBT0lych4wmMtI0NcSQtwxxjw5xgx4QJ53YvVeuKAsvat5arZIKISAs7sTxCuElISABU11ZERKS9axhlm572PWy2xNAGc1zXbg9hscRRWbmFoqJ/hDockXZLI20lJHzVHvxVHgCsqTFQEOKAWogtIw5X+TH6JXQnvU+PsKqpKCLS1oVreQQgMLpWSVsREZH2q66ukMOHFwGQmTUxxNF8w2FPoXPOPeTvfo7de14gLe16zObw+zwl0tZppK2EREM9W0uiA7PDEuJoWo4tNQaf4SeOKPyVnlCHIyLSrpxYHiHcNIy0raioCHEkIiIiEioHD87DMHwkJl5OfFyvUIcTJCvrDuz2VOrqDnLg4LxQhyPSLilpKyHhKTmhnm0bZrKZOeg7AoCnUJPNiIi0JpVHEBERkXDl97s4eGg+AJmZt4c4mlNZLNF07fJzAPbufRmvtzrEEYm0P0raSkg01LO1ttF6tifa6y0G6kcXG34jxNGIiLQPhmGEdXmEhqRtWVlZaAMRERGRkCguXojHcwyHI52OKdeGOpxGZWT8kOjobDyeYxw8pNG2Iq1NSVsJCW9gErK2PdIWoNhfigsPhseP92htqMMREWkXXC5X4OdwHGnboUMHAI4dO4Zh6As9ERGR9ubAwb8CcNFFt2I220IcTePMZiudcyYBsG/fq/h8up4VaU2aiExCwtOOkrYGUEwZ2XTEW1iNrWPbb7OISKjV1BzvZ2w2zObw+446KSkJk8mE2+2mqqqK+Pj4UIckIiIiraSicisVFV/i95v43e8W46pbfso+8fEdef752SGILlh6+g3s2fsH6uoOcPDQfLKzfhLqkETaDSVtpdX5qtz4q+sn5bKmto8EZhGl9UnbI7X43b5QhyMi0ubV1taPBAnH0ggAVquVhIQEysrKOHbsmJK2IiIi7cjBA28CsH9/ApMfvKbRfWbO/KQ1Qzots9lG55x7+Srv1xQU/InMi34ctiODRdoaJW2l1XlL6kc/WZIcmO2WEEfTOqpNLszxdvwVbjyHNCGZiEhLa0jahmNphAYdOnQIJG1zcnJCHY6IiIi0Aq+3kqLi9wHYtTOFq68KcUBNkJHxfXbveQGXq4iSkoWkp99w1udMnnwvlZWHG90WLqOIRcJd+N0vKG3eN6UR2v4kZCeyZ8YB4DlQVV8zQUTkAs2cOZPLLruM+Ph4UlNTufHGG8nLywvap66ujkmTJpGcnExcXBzjx4+nuLg4aJ+CggLGjh1LTEwMqampTJkyJTCJV6SKlKQtwNGjR0MciYhI29OUPvLqq6/GZDIFLffcc0/QPm2xj5TQKixagN9fS2xsDw4fjgt1OE1iNjvIypwIwL6CPzWpHn9l5WGmTbui0eV0yVwRCaakrbS6hqSttR3Usz2RNTUWk82M4fIR7wrP23VFJLKsXLmSSZMmsWbNGpYsWYLH42HUqFFUV1cH9nnwwQd5//33efvtt1m5ciWHDh3ipptuCmz3+XyMHTsWt9vNqlWreP3115k7dy6PPvpoKJrUbCIhaZucnAzUT0YmIiLNqyl9JMBdd91FYWFhYHn22WcD29pqHymhYxgGBw/OA+CiTrcAptAGdA7qJ0yLpqpqO6Wlq0Idjki70CJJ265duzY6aqSsrIyuXbu2xCklggRG2raTerYNTBYTtovqv0lNrokOcTQiEkrN1U9+9NFH3HHHHfTt25eBAwcyd+5cCgoK2LBhAwDl5eW89tprPP/881xzzTUMHjyYOXPmsGrVKtasWQPA4sWL2b59O2+88QaDBg1izJgxzJgxg1mzZuF2u5unwSFQV1cHhHfStmGkrZK2IiLfaK0+skFMTAzp6emBxel0Bra11T5SQqesbB3V1Tsxm6PJyLjp7E8IIzZbIp0yfgDAgQN/DXE0Iu1DiyRt9+7di8936mRLLpeLgwcPtsQpJYJ4S+q/3ba1s5G2QH3S1gSxbju2CtVIEGmvWqqfLC8vB75JBm7YsAGPx8PIkSMD+/Tq1Yvs7GxWr14NwOrVq+nfvz9paWmBfUaPHk1FRQXbtm1r9Dwul4uKioqgJdxEwkjbE8sjNOU2QxGR9qC1+sgGb775JikpKfTr149p06ZRU1MT2NZW+0gJnYMH6ycgS08bh9V65klIN27cyF13/aDRZcuWL1sj3FNclHkbAIePLKOurjAkMYi0J806Edk///nPwM+LFi0iISEh8Njn87Fs2TI6d+7c5OPNnDmTd999l6+++oro6Gi+9a1v8Zvf/IaePXsG9qmrq+Ohhx5i/vz5uFwuRo8ezcsvvxzUsRYUFHDvvfeyfPly4uLimDhxIjNnzsRq1Txsrc1X5cZf7QUTWNvZSFsAc5QVa0o03sO1xO/RBbpIe9Pc/eSJ/H4/DzzwAMOHD6dfv34AFBUVYbfbSUxMDNo3LS2NoqKiwD4n9pkN2xu2NWbmzJk88cQT5xVna4mEpG1SUhImkwmPx0NVVRXx8We+eBMRactau48EuPXWW8nJyaFTp05s3ryZqVOnkpeXx7v/n707j4+qvvc//jqzZk8IkA3CvoqAFBBTtW5UQK+Vyr2oP65Lq1IVvFVqW6m79hbbWutS1NZasQtu97rcqkURRBQBWWVH9gDZIPs66/n9MWY0EpZAJmcm834+HvMgM+fMmfc5JPM985nv+X5ffx3ovG2kWMPjPUzZofeAr4qfx+Zj9uxzW10ydepn7ZjsxKUkDyQjYxxVVSspKnqFfv1utySHSLxo16rl5MmTATAMg+uuu67FMqfTSZ8+ffjd7353wttrHodo7Nix+P1+fvGLX3DxxRezZcsWkpNDk1jdcccdvPPOO7z22mukp6czc+ZMrrjiCpYtWwZ8NQ5RTk4On376KcXFxVx77bU4nU5+9atftc+OywlrOBD6htuXCMtXrQg/vmHDBvoEuloVq0M581PxH2ok+SAEG3zYkpxWRxKRDtLe7eTXzZgxg02bNvHJJ5+caszjmj17NrNmzQrfr6mpIT8/P+Kve6JM0wwXbd3u6B1D3OFwkJ6eTlVVFRUVFSraikhcs6KNnD59evjn4cOHk5uby0UXXcSuXbvo37//Sb1WtLeRYp3iotcwTR9paSNJSz39+E+IErNm3dJi4rD8XpWcfTZs2fIMc+du5Xe/+6OF6UQ6t3Yt2gaDQQD69u3LqlWr6Nat2yltb8GCBS3uz5s3j6ysLNasWcN3vvOd8Fh98+fP58ILLwTghRdeYOjQoaxYsYKzzjorPA7RBx98QHZ2NmeccQYPP/wwP//5z3nggQeiugdOZ7Rn9XYygcaAh7pV1eHHt3yylpSBo6wL1oHsGW6aHH4S/A7qV5eS+p2eVkcSkQ7S3u1ks5kzZ/L222+zdOlSevb86j0lJycHr9dLVVVVi962paWl5OTkhNf57LOWvTVKS0vDy1rjdrujuhja1NQUPtbR3s5nZmZSVVVFeXk5vXv3tjqOiIhlOrqNbM24ceMA2LlzJ/379++UbaRYwzQDHCx6GQhN6BVLamsPtejxa5oB9u9/gcSkBtLSd1qYTKTzi8iYtnv27Gm3RvbrNFZf7HPWhoYE6JbTnbOGjQnf+ub1sTZYBzIMg/Kk0FhZdcuLMAMaJkEk3rRXO2maJjNnzuSNN95g8eLF9O3bt8Xy0aNH43Q6WbRoUfix7du3U1hYSEFBAQAFBQVs3LiRsrKy8DoLFy4kLS2N00477ZQzWqG2thYAm82GzRaRU5120/x78PXjLyISzzqqjWzN+vXrAcjNzQU6Zxsp1igvX0pT0wEcjnSys/7N6jinxDDspKSGfv8HDjhscRqRzi1ig7ouWrSIRYsWUVZWFv7WtNlf/vKXNm9PY/V1Ds7Q52hsyfE9JEB1YhM5TWlQ6aFxy2GShne3OpKIdLD2aCdnzJjB/Pnzeeutt0hNTQ23a+np6SQmJpKens4NN9zArFmzyMzMJC0tjdtuu42CggLOOussAC6++GJOO+00rrnmGn7zm99QUlLCPffcw4wZM2K2p1BdXR0Adrvd4iTH17NnTz777DP2799vdRQRkajREW3krl27mD9/Ppdccgldu3Zlw4YN3HHHHXznO99hxIgRQOdsI8UaBw/OByA3dwp2e4LFaU5daurpVFevJjunjvr63SQn97M6kkinFJGi7YMPPshDDz3EmDFjyM3NxTCMU96mxuqLfaZpflW0TYnvoq1pQG1vyNgBdR8fVNFWJM60Vzv5zDPPAHD++ee3ePyFF17g+uuvB+D3v/89NpuNKVOmtJiws5ndbuftt9/mlltuoaCggOTkZK677joeeuihk8oUDZp72sbChKO9evUCoLi4GK/XG/XDOYiIRFpHtZEul4sPPviAxx9/nPr6evLz85kyZQr33HNPeN3O2EZKx0tK8nK4/EMAeuRdbXGa1q1bt46bbvr3Vpdt3Pg50HJCNKcjjcTEPjQ27uVg0XwGDbyn1eeKyKmJyKeZZ599lnnz5nHNNde0y/Y0Vl/nEKzzYfeBiYktKfo/SEeS1+/js8ZtfNc2BG9hLav++QnezNAJ6ZgxY/T7J9LJtVc7aZrHH14lISGBuXPnMnfu3KOu07t3b959991TyhJNYqmnbXp6OqmpqdTW1nLw4METunxXRKQz66g2Mj8/n48++ui42+lsbaR0vP4DDgMmXboURHGPVF+LcWu/burUz1p9PC11BI2Neyku/l/697uzU/QgFok2ERnozev18u1vf/uUt6Ox+joXX2k9AF57AMMe3WMMRtqOwl3sWbmNKndodvOkNY3UrSph5Ssfsnr1aovTiUiktVc7Ka1r7mkbC0VbwzDCvW0LCwstTiMiYj21kdKZmGaA/v3LAejRY5rFadpXYmJv6utc+P01lB1acPwniEibRaRyduONNzJ//vxT3s6MGTP4+9//zvz588PjEJWUlNDYGCp0fX2svg8//JA1a9bwgx/84Khj9X3++ee89957GofIIv7S0ORbHkfA4iTRYVDP/vQYEfoiIr0pgTP7ncGwfkMtTiUiHaG92klpXXNP21gYHgG+GiJB49qKiKiNlM6lvmEXCQl+XK4suncbf/wnxBDDMNi9uysARUWvWJxGpHOKyKeZpqYm/vSnP/HBBx8wYsQInM6W45c+9thjJ7QdjdXXufjKmou2fouTRA97igt7ZgKBiia8B2qtjiMiHaS92klpXSz1tIWWRdtgMIjNZiMQCLB79+7wOnv37j2h4TBERGKd2kjpTGprNwGQlzcVm63zzeuye3cmw0eUUlX1mSYkE4mAiBRtN2zYwBlnnAHApk2bWixry0DyGquvc/GVqmjbGld+Ko0VTfgO1mHreuqT9olI9GuvdlJaF2s9bbOysnC5XHg8Hg4cOECvXr3YvXs3b775Znj8/Y0bN4aLuyIinZnaSOksfL4qmpoOYJrQI+9Kq+NERGOji65dz6O8/EOKil9h4IDZVkcS6VQi8mnmww8/jMRmJYaZpvm1oq2GR/g6e9cEbEkOgg1+0psS8FkdSEQiTu1kZMXSRGQQynnaaaexfv16Fi9ezHXXXQeEirkJCQn4fD66dOlicUoRkY6hNlI6i9q6LQCUlKSSkJBncZrI6ZF3JeXlH1Jc/Dr9+/0Em81ldSSRTiO+Z4OSDhOs9WE2+jFRT9tvMgwDZ89UADIbEkGXv4qInDSv14vH4wFip2gLoaGg7HY7e/fuZefOnVRXV3PgwAE2b97MF198gcfjwefT13oiIiKxwDSD1NVtBWDXrq4Wp4msrl0vwOXKwuer4NDhD6yOI9KpRKSn7QUXXHDMS1cWL14ciZeVKOYrrQfAnwymrmo6gjMnGc/OKhL8DtwVVqcRkUhTOxk5X+9la7NF33fTwWCQvXv3hu8HAqGrT+x2O4MGDWLr1q384x//wDAMTNPE6XTicDhobGykqanJotQiIh1HbaR0Bo2N+wgE6rHZEig6mG51nIiy2Rzk5U5h775nKDr4CtlZl1gdSaTTiEjRtnkMomY+n4/169ezadOm8CV/El+ah0bwpVocJEoZThvOnCR8RfWk7lNPW5HOTu1k5DRPQpaYmBiVYx+WlZWxa9cuSkpKgNBYtQkJCQwcOJDi4mKSkpJoaGjANE0SEhIYNWoUTU1NrFu3Do/Hg9frtXgPREQiS22kdAa1tZsBSEkZypo167jppn9vdb2NGz8Hzu3AZJGRlzeVvfueoaLyExob95OYmG91JJFOISJF29///vetPv7AAw+Ee8BIfPGXfa1oW2ttlmjl7JGKr6iepGIINviwJXW+2UVFJETtZOQ0H7/ExESLkxxdVlYWPXv2BKCkpITExMTw/TPPPJO8vDx2797N559/jsvlwuVyYbPZCAaDlJSURGUPYhGR9qI2UmKd319PQ+MeAFJTTgM+Y/bs1guzU6d+1oHJIicxsReZXc6monIZRcWv0b/fLKsjiXQKHXrW/5//+Z/85S9/6ciXlCjR3NPWmxp9vZ6ihS3VSZPDjxGEho2HrY4jIhZQO3nqvt7TNhbZbDZSU1NJSkpq0VPY4Qh9z97cQ1dEJN6ojZRYUVe/FTBxu3NxuTr3eLZfl5d3JQDFRf9DMKh5bETaQ4cWbZcvX05CQkJHvqREAdM0w2PaaniEozMMg6rERgAa1pRanEZErKB28tTFQk/bk9FctG1sbAyPgysiEk/URkosME0zPDRCqJdt/OjefTxOZyYebynlFR9ZHUekU4jI8AhXXHFFi/umaVJcXMzq1au59957I/GSEsWCNV7MpgDYwJdsdZroVp3gIbs2FW9hLb5DDTi7J1kdSUQiQO1k5DQXbRMSEjrVZbSGYYSHSPD5fFbHERGJGLWREsuaPAfx+6sxDCfJyQOtjtOhbDY3uTnfp3D/8xQVvWJ1HJFOISJF2/T0lrMj2mw2Bg8ezEMPPcTFF18ciZeUKNY8NIKjayLYPRaniW5+e5CmLEgsg4Z1ZaRf3MfqSCISAWonI+frwyN0pqItgN1uJxgMajIyEenU1EZKLAtPQJY8CJvNZXGajpeXdyWF+5/n8OEPSUwcanUckZgXkaLtCy+8EInNSoxqLto6s5IAFW2Pp66HQWKZSeOGw6R9t3dUzn4uIqdG7WTkdNbhESA0RILP51PRVkQ6NbWREqsCAQ8NDTsBSEkdZnEaayQn9ycjfSxV1avo26/C6jgiMS8iRdtma9asYevWrQAMGzaMUaNGRfLlJEo1j2fryE4CKq0NEwMaswGHgf9wI/7SBpw5GlNCpLNSO9n+Yn0ismOx2+0AeDz6AlREOj+1kRJr6uu3Y5oBnM6uuF3ZVsexTF7elVRVr6Jfv3JM01QnJJFTEJGibVlZGVdddRVLliwhIyMDgKqqKi644AJefvllunfvHomXlSjlL/uyp212EnSuK1UjwnQaJAzMoGlrBQ0bD5Ouoq1Ip6N2MjICgQANDaE2pzMWbZsnI/N6vZimaXEaEZHIUBspsaq27ssJyFKHxXWhMitrIl/seJCUlFoamwpJSuxtdSSRmGWLxEZvu+02amtr2bx5MxUVFVRUVLBp0yZqamr4r//6r0i8pEQhj8fDsk8+oako1OtpU9EXbNiwgaBmvT6uxOHdAGjcdNjiJCISCWonI6N5aASbzYbb7bY4Tftr7mkbDAZpamqyOI2ISGSojZRYlJbWiNd7CLCRkjzY6jiWstsTycmeDHw1xq+InJyIFG0XLFjA008/zdChXw08fdpppzF37lz+9a9/ReIlJQqtXr2aja8tx+aHICaV20rZsmgthw+rEHk8iUO7gt3AX9qA78ueyiLSeaidjIzmom1ycnKn7OFiGEa4B3F1dbXFaUREIkNtpMSiPn1CwwAmJfbGbu98V/u0VV6PqwBoaNiF319rcRqR2BWR4RGCwSBOp/OIx51OJ8FgMBIvKVFqeO4QqAJHiouzTh/D5j3brI4UE2yJDhIGZNC0vZLGLeVfTuImIp2F2snIaC7apqamWpwkcpKTk2lsbKSqqsrqKCIiEaE2UmKNaQbp3Sc06VZySnz1sl23bh033fTvrS4beyb0729SU/M5mZnndHAykc4hIkXbCy+8kB//+Me89NJL5OXlAXDw4EHuuOMOLrrooki8pESpBH/oV8yWcuSJlxxbwpBMmrZX0rStgrTz862OIyLtSO1kZDRPQpaSkmJxkshJSgp9iaeirYh0VmojJdZUVa8hOdmHYThJSuxndZwO5mP27HNbXXLf/avo399BTe0mMjLOxGZzdXA2kdgXkeER/vCHP1BTU0OfPn3o378//fv3p2/fvtTU1PDUU09F4iUlSn1VtNUbdFslDMkEwLuvhmCDz+I0ItKe1E5GRnNP23go2tbX11ucREQkMtqrjZwzZw5jx44lNTWVrKwsJk+ezPbt21us09TUxIwZM+jatSspKSlMmTKF0tLSFusUFhZy6aWXkpSURFZWFj/96U/x+/3tsq/SOZSUvAlAcvJAbLaI9IuLSdu3mTgdXTBNL7V1W6yOIxKTIvKOkp+fz9q1a/nggw/Yti10OfzQoUMZP358JF5Oopj7y6KtPVk9bdvK0SUBR3YS/tIGmr6oJOmMLKsjiUg7UTsZGTU1NQD4fD727t2LaZoWJ2p/zROsqWgrIp1Ve7WRH330ETNmzGDs2LH4/X5+8YtfcPHFF7NlyxaSk5MBuOOOO3jnnXd47bXXSE9PZ+bMmVxxxRUsW7YMgEAgwKWXXkpOTg6ffvopxcXFXHvttTidTn71q1+1745LTAoGPZSVvQsQ9xOQfZNpQlr6GZSXf0hNzXrSUkdgGBHpNyjSabXrX8zixYs57bTTqKmpwTAMvvvd73Lbbbdx2223MXbsWIYNG8bHH3/cni8p0Sxg4vaHZrrW8Agnp7m3bdO2CouTiEh7UDsZWWVlZQAUFxezcOHCcBE3VgSDQfbu3cuOHTuOWnRuLto2NDR0yqK0iMSv9m4jFyxYwPXXX8+wYcMYOXIk8+bNo7CwkDVr1gChCR2ff/55HnvsMS688EJGjx7NCy+8wKeffsqKFSsAeP/999myZQt///vfOeOMM5g0aRIPP/wwc+fOxev1RuQ4SGwpL/8Iv7+GhgYnCQk9rI4TdVKSh2CzJXx5jHZZHUck5rRr0fbxxx/npptuIi0t7Yhl6enp/OhHP+Kxxx5rz5eUKOasAwMDHDYMt93qODEpsblo+0UlZlAfzkVindrJyGpsbAQgOzub7t27W5ym7crKyvj4449ZsWLFUYvOzUXbQCBAQ0NDR0cUEYmYSLeR1dXVAGRmhs6v16xZg8/na9GDd8iQIfTq1Yvly5cDsHz5coYPH052dnZ4nQkTJlBTU8PmzZtbfR2Px0NNTU2Lm3RexSVvAbBvXxf1Im2FzeYkLXU4ANU16yxOIxJ72vVd5fPPP2fixIlHXX7xxReHv9mUzs/15fmJPcWJYRjWholRrl5pGAl2gg1+fAfrrI4jIqdI7WRkeTwegFZnHY8VWVlZ9OzZ86hFZ5vNht0e+iK0uQAhItIZRLKNDAaD3H777Zx99tmcfvrpAJSUlOByucjIyGixbnZ2NiUlJeF1vl6wbV7evKw1c+bMIT09PXzLz9eEwp2Vz1fD4cOLAdi3t4vFaaJXauoIwIbHU0JTU7HVcURiSrsWbUtLS4/5QcnhcHDo0KH2fEmJYs7aUM9QDY1w8gy7gbtfBgBNu6oszSIip07tZGQ1NTUB4HJ17skvHY7QePEq2opIZxLJNnLGjBls2rSJl19++WTjnbDZs2dTXV0dvu3fvz/irynWOHRoAabpJTl5IFVViVbHiVoORzIpKUMAqKpaaXEakdjSrkXbHj16sGnTpqMu37BhA7m5ue35khLFmnva2lI694fnSEvonw6AZ2eVtUFE5JSpnYwcr9cbns07lnvanojmoq0uuRWRziRSbeTMmTN5++23+fDDD+nZs2f48ZycHLxeL1VVVS3WLy0tJScnJ7xOaWnpEcubl7XG7XaTlpbW4iadU3HJmwDkZE8GdGXpsWSkjwVsNDYVqretSBu0a9H2kksu4d577w33dPm6xsZG7r//fv7t3/6tPV9SopizNvSvXT1tT4l7QAYAnr01mL6gtWFE5JSonYyc+vp6AAzDCA8f0Fmpp62IdEbt3UaapsnMmTN54403WLx4MX379m2xfPTo0TidThYtWhR+bPv27RQWFlJQUABAQUEBGzduDE90CbBw4ULS0tI47bTT2rqL0ok0NRWFe43m5HzP4jTRz+lMD/e2raxaYXEakdjhaM+N3XPPPbz++usMGjSImTNnMnjwYAC2bdvG3LlzCQQC3H333e35khKlAvU+HF+eb9mSVbQ9UV6/jw0bNrR80DTpm+okWOvDU1hDQv8MS7KJyKlTO9n+AoEAu3fv5vDhw0BozNfOPo66irYi0hm1dxs5Y8YM5s+fz1tvvUVqamp4DNr09HQSExNJT0/nhhtuYNasWWRmZpKWlsZtt91GQUEBZ511FhAaR/e0007jmmuu4Te/+Q0lJSXcc889zJgxIzwxpMSn0tJ/ApCRcSYJCXkWp4kNGelnUle3jaam/XTrlmB1HJGY0K5F2+zsbD799FNuueUWZs+ejWmGxjQ1DIMJEyYwd+7cIwZyl87JVxLq8eS1BzAcmkXzRO0o3EVlZQX9PFnhxzbv3krXgeeRUhsaIkFFW5HY1d7t5NKlS/ntb3/LmjVrKC4u5o033mDy5Mnh5ddffz0vvvhii+dMmDCBBQsWhO9XVFRw22238c9//hObzcaUKVN44oknSElJObWd7SC7d+/mzTffJDU1FaDTF2xBRVsR6Zzau4185plnADj//PNbPP7CCy9w/fXXA/D73/8+3PZ5PB4mTJjA008/HV7Xbrfz9ttvc8stt1BQUEBycjLXXXcdDz300KntrMS8kpK3AMjJvtziJLHD6UwjNWUotXWbOX146xP5iUhL7Vq0BejduzfvvvsulZWV7Ny5E9M0GThwIF26aDbFeOL/smjb5PBbnCT2DOrZn7OGjWnxWFM3g5SDJh5NRiYS89qznayvr2fkyJH88Ic/5Iorrmh1nYkTJ/LCCy+E73+zZ9C0adMoLi5m4cKF+Hw+fvCDHzB9+nTmz5/f5jxWycnJwW63U1JSoqKtiEgMa882srnoeywJCQnMnTuXuXPnHjeTSLPaum3U1W/HMFxkZU2yOk5MSU8fS23dVnJyaqmqWk1GxpjjP0kkjrV70bZZly5dGDt2bKQ2L1HOV9IAgEdF23bR1C30r/dALcEmP7aEiP3pikgHaY92ctKkSUyadOwPC263+6iTpWzdupUFCxawatUqxowJnTQ/9dRTXHLJJTz66KPk5cXO5X4+nw8IDY/Q2TUXbevq6ggEAp1+DF8RiT/6LCnRrPTLXrbdup2P05lucZrYEuptexq1dZvYtfsxvjXqH3HxhbvIyYr6TzZLly7lsssuIy8vD8MwePPNN1ssv/766zEMo8Vt4sSJLdapqKhg2rRppKWlkZGRwQ033EBdXV0H7kX88amnbbvx+n2s27kRXzIQhPXvrGDZsmUsW7YMj8djdTwRiXJLliwhKyuLwYMHc8stt1BeXh5etnz5cjIyMsIFW4Dx48djs9lYuXLlUbfp8XioqalpcbOa1+sF4qNoa7fbsdlsmKZJbW2t1XFERETihmkGKSn9PwBysidbGyZGZWSMJRAwqKpaSXn5EqvjiES1qP9k03zp57EuWZk4cSLFxcXh20svvdRi+bRp09i8eTMLFy7k7bffZunSpUyfPj3S0eOWGTTxlX5ZtHWqaHuqdhTuoujTndQGGwGwb66nblUJK1/5kNWrV1ucTkSi2cSJE/nrX//KokWL+PWvf81HH33EpEmTCAQCAJSUlJCVldXiOQ6Hg8zMzPCELa2ZM2cO6enp4Vt+fn5E9+NENPe0jYfeGoZhkJSUBGiIBBERkY5UWbUSj6cEhyONrl3PtzpOTHI4Uvnii+4A7Nz1a4JB1QxEjibqr7HWpZ+xJ1DZhOkNYtpCE5HJqRvUsz95/fNp2nSY7kY6fYYNsTqSiMSAq666Kvzz8OHDGTFiBP3792fJkiVcdNFFJ73d2bNnM2vWrPD9mpoaywu38TQ8AkBycjJ1dXUq2oqIiHSg0pJQL9us7hOx293HWVuOZsvmbIYP91Jfv4OSktfJy5tqdSSRqNQpPtm096Wf0XjZZyzxFYd62XpTgM7f4anD2LuETgqC9T6CHhXDRaTt+vXrR7du3di5cycQmsCrrKysxTp+v5+KioqjfhkKoS9L09LSWtysFk/DIwAkJiYCaHgEERGRDhIIeCgtC01Kl5Mz2dowMc7nc9C3zwwAdu3+PYFAg8WJRKJTzH+yicSln9F42Wcs8RaFxgv2aUz2dmVz2bGlOIFQb2YRkbY6cOAA5eXl5ObmAlBQUEBVVRVr1qwJr7N48WKCwSDjxo2zKuZJibeets3DI+iLZRERkY5xuHwxgUAdbncuGRmaKO9U9ew5jYSEfLzeMgoLn7c6jkhUivlPNldddRXf+973GD58OJMnT+btt99m1apVLFmy5KS3OXv2bKqrq8O3/fv3t1/gOOAr+rKnbbq62bY3e2YCoKKtiITU1dWxfv161q9fD8CePXtYv349hYWF1NXV8dOf/pQVK1awd+9eFi1axOWXX86AAQOYMGECAEOHDmXixIncdNNNfPbZZyxbtoyZM2dy1VVXxdTwQaZphnvaxsOYtqCetiIiIh2ttOQtAHKyv4dhxHwpxXI2m5v+/X8CwL7C5/B4D1ucSCT6dLp3mva49DMaL/uMJc09bb3qadvuHF1CRVt/pcfiJCISDVavXs2oUaMYNWoUALNmzWLUqFHcd9992O12NmzYwPe+9z0GDRrEDTfcwOjRo/n4449xu78ag+0f//gHQ4YM4aKLLuKSSy7hnHPO4U9/+pNVu3RSgsFg+Od462mroq2IiEjk+XxVHC5fAkBOzuXWhulEsrP+jbTUEQQC9ezZ86TVcUSiTtRPRNZWx7r0c/To0UDsXvoZCwK1XoI1XjDAq1p3u7NnhAotZqMfR0p8FCZE5OjOP/98TNM86vL33nvvuNvIzMxk/vz57RmrwzUPiQTqaSsiIiLtr7TsXUzTR0rKUFJSBlsdp9MwDIMBA+5i7br/R1HRy+T3vI7k5P5WxxKJGlFftK2rqwv3moWvLv3MzMwkMzOTBx98kClTppCTk8OuXbv42c9+dtRLP5999ll8Pl9MXvoZK5p72Tq6J2I61Bu0vRkOG7Y0F8EaL8leJ5qOTETkq6JtvBRsoWXR1jTNuNp3ERGRjlZa8n8AfPJxNX9+7t+PWL5x4+fAuR2cqnPo0mUc3bpdxOHDi9i56zeMHPFHqyOJRI2oL9quXr2aCy64IHx/1qxZAFx33XU888wzbNiwgRdffJGqqiry8vK4+OKLefjhh4+49HPmzJlcdNFF2Gw2pkyZwpNPqut9JPgOhoq2rrwUQEXbSLBnuL8s2rrQ9DMiIvFdtA0EAjQ2NoaHSxAREZH21dh4gKrqVZgmXHbZBL7//dQj1pk69TMLknUeA/r/jPLyJRw+/AGVlSvo0uUsqyOJRIWoL9rq0s/Y0ly0dfZIAcqtDdNJObok4CusJcnrVNFWRIT4LNra7XaSkpJoaGigpqZGRVsREZEIKS0N9bItK02hX98jC7bSduvWreOmm1r2WB49ugsDBx3mwyU38/3JazAMu0XpRKJH1BdtJbY0D4/gzEuBEovDdFL2DDcY4A44sDce/QsNEZF4EY9FW4DU1FQaGhqora096uSqIiIicvJM06S45C0A9u7L5Cx1AG0nPmbPbjmcRCDQyIGDfyU9vZaiolfp0eNqi7KJRA/NZCTtJtjgI1AZGhIhNDyCRILhsGFLdQGQcNjiMCIiUSCei7agychEREQipa5uCw0NO7HZXBzYn2F1nE7Nbk8kIyM0Wfyu3Y/h9+v8RkRFW2kXHo+Hde+vBMCXBMvXrmTDhg0EA5oqKxIcXRIASChXT1sRERVt9aFGREQkEopL3gCgW7fx+Hy6XD/S0lKHU1PjxuerYM/eP1gdR8RyKtpKu1i9ejUlS3cC0BBoom5VCVsWreXwYXUFjQR7l9BEe24NGywioqKtirYiIiLtLhj0UfLl0Ai5OVdYnCY+GIaddWt7ALB//4s0NOyxOJGItVS0lXbTJy305tq9ZzZnDRtD37w+1gbqxOzpbkxMnA3gr2yyOo6IiKWCwaDVESyhoq2IiEjklFcsxeerwOnsSmbmOVbHiRvFxel0zfwOpuljx85HrI4jYikVbaXdJPhC89rZvxxvVSLHcNhodPoB8OyutjiNiIi14rWnbVpaGqCirYiISCSUFIeGRsjJuRybzWlxmvgycODdGIadw4c/oKJimdVxRCyjoq20C8Nv4gqExvixqWjbIepdXkBFWxGJb6Zpxm3RtrmnbU1NjcVJREREOhefr4pDhxcBGhrBCsnJA+jR4z8B+GLHwwSDfosTiVhDRVtpF65qMDAw3HZsLg3Q3hHqXT4APLurrA0iImIhn88X/jlei7b19fXhwrWIiIicutLSdzBNLykpQ0hNHWp1nLjUr+9/4XBkUF+/g6Kil62OI2IJFW2lXbi+7OypoRE6TqPTh2lAoNKDv0Lj2opIfGpqCr3/2e32uCvaJicnYxgGpmlSX19vdRwREZFOo7gkNDSCetlax+nMoF+/2wHYvedxfD5dYSrxR0VbaReuahMAW6rG+ukoTUEvla4GADa9v5ply5axbNkyPB6PxclERDpO83ue0xl/7Y/NZtMQCSIiR7F06VIuu+wy8vLyMAyDN998s8Xy66+/HsMwWtwmTpzYYp2KigqmTZtGWloaGRkZ3HDDDdTV1XXgXogV6ut3U1OzDsOwk539PavjxLUeeVeTnDwQn6+SPXuetDqOSIdT0VbahXradrwdhbvYe3g/APZtDdStKmHlKx+yevVqi5OJiHSceC7awleTkaloKyLSUn19PSNHjmTu3LlHXWfixIkUFxeHby+99FKL5dOmTWPz5s0sXLiQt99+m6VLlzJ9+vRIRxeLlXzZyzYz81zc7u4Wp4lvNpuDgQPuBuDAwb9TX7/T4kQiHcthdQCJfUFPAOeXE1fb0tzWhokzzZO+ZZJCr2GDLU4jItLxvl60jccrDZqLttXVumRQROTrJk2axKRJk465jtvtJicnp9VlW7duZcGCBaxatYoxY8YA8NRTT3HJJZfw6KOPkpeX1+6ZxXrBoJ/iktcBDY0QLbp2PZdu3cZz+PAHfLHjl5wx8oW4GxJL4pd62sop8x2swwB8tgA2tyYh60jV1IMBZlOAYKNm1BSR+NM8pm289rRNT08H1NNWRORkLFmyhKysLAYPHswtt9xCeXl5eNny5cvJyMgIF2wBxo8fj81mY+XKlUfdpsfjoaampsVNYkdFxVI8nhKczi507z7e6jjypYEDfoFhuKio+JjDhxdZHUekw6hoK6fMeyDUzbbRqaJhRwsaJvYvezcHKjUZmYjEHw2PoOERREROxsSJE/nrX//KokWL+PWvf81HH33EpEmTCAQCAJSUlJCVldXiOQ6Hg8zMTEpKSo663Tlz5pCenh6+5efnR3Q/pH0dLHoFCPWytdl0FWm0SErqTa9ePwRgx87/JhiMv6urJD6paCun7Kuirc/iJPHJ3iV0MuFX0VZE4pCKthoeQUTkZFx11VV873vfY/jw4UyePJm3336bVatWsWTJklPa7uzZs6murg7f9u/f3z6BJeKaPCUcPrwYgLy8Ky1OI9/Up/ctuFxZNDYWUlj4gtVxRDqEirZyyrwHQjOoqmhrDXuXBAAClR4wLQ4jItLB4nF4hGAwyN69e9mxY0e4h6162oqInJp+/frRrVs3du4MTXSUk5NDWVlZi3X8fj8VFRVHHQcXQuPkpqWltbhJbCgu+h8gSEb6WJKT+1sdR77B4UhhwICfA7B331yaPEfv8S7SWahoK6ckUO8jUBH6wKzhEaxhT3eDzcD0BHD7NaawiMSXeOxpW1ZWxscff8yKFSvYtm0bALW1tQSDQYuTiYjErgMHDlBeXk5ubi4ABQUFVFVVsWbNmvA6ixcvJhgMMm7cOKtiSoSYZoCi4lcByOtxlcVp5Ghysi8nPW0UgUADu3b+1uo4IhGnoq2ckuahEXzJELSpm6cVDLsRHiIhxeuyOI2ISMeKx6ItQFZWFj179qR3794AmKZJXV2dxalERKJHXV0d69evZ/369QDs2bOH9evXU1hYSF1dHT/96U9ZsWIFe/fuZdGiRVx++eUMGDCACRMmADB06FAmTpzITTfdxGeffcayZcuYOXMmV111FXl5eRbumURCRcUnNDUdxOFIJ6v7RKvjyFEYhsGgQfcBBiWlb1JdvdbqSCIR5bA6gMQ23/5Q0daTAQQsjRLXHJkJBMqbSPG40ZDsIhJP4nF4hK8zDAOHw4Hf76e6ulqX4YqIfGn16tVccMEF4fuzZs0C4LrrruOZZ55hw4YNvPjii1RVVZGXl8fFF1/Mww8/jNv91eRT//jHP5g5cyYXXXQRNpuNKVOm8OSTT3b4vkj7mjXrFmprD7V47OxzdpOfDzt2pHPedxIsSiYnIi1tBLm5/05x8Wts/+Ihxo55HcNQf0TpnFS0lTbxeDysXr06fL/7hiBJwN6GIkyHYV2wOGfvmgg7qkjyOqnwq8eziMQHv9+P3x8amidei7ZAuGircW1FRL5y/vnnY5pHPy9+7733jruNzMxM5s+f356xJArU1h5i9uxzw/f9/nr2H/gcgG1bk6yKJW3Qv/+dlJX9i9rajRQX/y95ef9hdSSRiNDXEdImq1evZuUrH1K3qoS6z0pwHQ6Nn7du43oOHz5scbr4ZUtyYLjt2DBwV1idRkSkYzQ0NIR/djji93touz00nrmKtiIiIm1XW7cJCOJ251BdnWh1HDkBblc3+vX9LwB27votfn+txYlEIiN+P+HISRvWbyhnDRtDsMlPfWkRGJCUqcsxrWQYBo6uCfiK6kksU09bEYkPzUVbu92OYcTv1R7NBevq6mqLk4iIiMQW0wxQW7sJgLTUkUCZtYHkhPXseQ0Hi16moWE3e/Y8xcCBvzjquq0NiQGQmtqdxx57JpIxRU6JirZy0gLVXgBsKU4C9Zqx2mr2bomhom1paEKaeC5giEh8qK+vB8Bmi+8Lh5qLtuppKyIi0jb19bsIBOqx25NITh6AirbWW7duHTfd9O+tLvt6kdVmczFo4D2s//yH7D/wInl5V5Kc3L/V531zSIxmc+Z83H7BRSJARVs5acHa0JRX9jQ3lFocRnBkJhDExNlg4C9twJmTbHUkEZGI+npP23imoq2IiMjJqakNjWWbmjocw4jv84no4Wu1wApHFlm7dj2Pbt0u4vDhRezY8UtGjvyLOi9Jp6KirZy0cE/bNJfFSQTAsNuod3tJ9bhp3Fquoq2IdHoq2oY0F22rqqqsDSIiIhJDPJ4yPJ5iwEZqyulWx5GTNHDALygv/5jyiqU88MDFFBWlH7HOxo2fA60XgkWiWXxfTygnzTRNArWhoq09VUXbaFHrDvV+btqi2chE4sHSpUu57LLLyMvLwzAM3nzzzRbLTdPkvvvuIzc3l8TERMaPH8+OHTtarFNRUcG0adNIS0sjIyODG264gbq6ug7ci5Onom2I0+kEoK6uDq/Xa3EaERGR2FBTE+plm5w8EIdDHV5iVVJSH3rl/wCAi8ZXctddZzN79rktbn6/x+KUIidHRVs5KcF6PwRMsBnYkp1Wx5Ev1bpDH9a9+2sJ1OiDu0hnV19fz8iRI5k7d26ry3/zm9/w5JNP8uyzz7Jy5UqSk5OZMGECTU1N4XWmTZvG5s2bWbhwIW+//TZLly5l+vTpHbULp6R5TNt4L9ra7XZcrtAXqJWVlRanERERiX6BQAP19V8AkJY6wuI0cqr69LkFj8eOz1dJXd1Wq+OItJuoL9rGey+iaBWs+XI821QXhk1jxkQLvz2IJyP0c+Pmw5ZmEZHImzRpEr/85S/5/ve/f8Qy0zR5/PHHueeee7j88ssZMWIEf/3rXykqKgq3pVu3bmXBggX8+c9/Zty4cZxzzjk89dRTvPzyyxQVFXXw3rRdc0/beJ+IDCAlJQUInfOIiIjIsdXWbsYkgMuVhdudY3UcOUUORyqbN4f+HyurVhIM+i1OJNI+on5M2+ZeRD/84Q+54oorjlje3IvoxRdfpG/fvtx7771MmDCBLVu2kJCQAIR6ERUXF7Nw4UJ8Ph8/+MEPmD59OvPnz+/o3ek0mntx2tI1NEK0qc8zcFeZNHx+iJSCPKvjiIhF9uzZQ0lJCePHjw8/lp6ezrhx41i+fDlXXXUVy5cvJyMjgzFjxoTXGT9+PDabjZUrV7ZaDAbweDx4PF9dZmbVBFgaHuErqampVFRUqKetiIjIcdhsQWpqNwCQljZSE1fFkHXr1nHTTf/e6rKtW4sYOzaFQKCO2toNpKd/q4PTibS/qC/aTpo0iUmTJrW67Ju9iAD++te/kp2dzZtvvslVV10V7kW0atWq8IfSp556iksuuYRHH32UvDwVtU5GoPrLnrbpbouTyDc15EHmFvDuq8Ff7cGh/yORuFRSUgJAdnZ2i8ezs7PDy0pKSsjKymqx3OFwkJmZGV6nNXPmzOHBBx9s58Rtp+ERvqKetiIiEm9mzbqF2tpDrS5LTe3OY4890+qyXr0rCQTqsduTSUkeFMmI0u58zJ7d+oRiU6d+RpeMizhc/gFV1atISRmG3a7PwhLbor5oeyyR6kUULT2IopURhGCdDwB7mnraRptAooGrdyrefTU0bjhM6rk9rI4kIp3M7NmzmTVrVvh+TU0N+fn5HZ5DPW2/kpqaCqhoKyIi8aO29tBRC3hz5nzc6uOmaTJkSBkAaWlnYBg6h+hMUlKGUF2zFp+vguqaNWR2+bbVkUROSUwPAhepXkRz5swhPT09fLPig2g0S/SHJh4z3HZsCTFd9++0kkZ2B6BhQ+vfPItI55eTExrXq7S0tMXjpaWl4WU5OTmUlZW1WO73+6moqAiv0xq3201aWlqLW0cLBoMq2n6NetqKiIgcX0XFUjIymjAMJ6kpp1sdR9qZYdjo0qUAgJqa9fj99RYnEjk1MV20jZTZs2dTXV0dvu3fv9/qSFElyRsq2to1nm3UShzeDQzw7a/Fd6gBj8fDsmXLjrh9vUe5iHQuffv2JScnh0WLFoUfq6mpYeXKlRQUhE5mCwoKqKqqYs2aNeF1Fi9eTDAYZNy4cR2euS08Hg+maQIq2sJXPW2rq6vx+zX5hoiISGv2FT4HQGrq6bp0vpNKSuyH25WNafqprl5z/CeIRLGY7ib59V5Eubm54cdLS0s544wzwuu0tReR2+3G7dYb+NEk+r4s2qbpGEUre6qLhMGZNG2roGF1KZvSilj5yocM6zc0vM7m3VsBOPvss62KKSKnqK6ujp07d4bv79mzh/Xr15OZmUmvXr24/fbb+eUvf8nAgQPDk3Xm5eUxefJkAIYOHcrEiRO56aabePbZZ/H5fMycOZOrrroq6sd8bx7P1uFwaAIRIDExEYfDgd/vp7q6mq5du1odSUREJKrU1G6isnI5wSCkp51hdRyJEMMw6NKlgJLSN6mt3Uh6+iirI4mctJgu2n69F1Fzkba5F9Ett9wCtOxFNHr0aCB2ehFFJdMk0Rf6tbGpp21USx6TTdO2CurXlsJ3TIb1G8pZw8Yc/4kiEjNWr17NBRdcEL7fPM7sddddx7x58/jZz35GfX0906dPp6qqinPOOYcFCxaQkJAQfs4//vEPZs6cyUUXXYTNZmPKlCk8+eSTHb4vbdU8NMLX9yWeGYZBZmYmZWVlVFRUqGgrIiLyDYWFf/7y3y7075fa6jrr1q3jppv+vdVlGzd+DrQ+hq5El4SEfNzuPDyeIqqqV1sdR+SkRX3RNp57EUUjeyM4g3YwQr05JXolDMnEluwkWOsj8ZBBndWBRKTdnX/++eEhAlpjGAYPPfQQDz300FHXyczMZP78+ZGIF1HNRVtdGfOVLl26hIu2IiIi8pXGxoOUlb0LwLZtWVxw/tHW9B11crOpUz+LRDSJAMMw6JJxFiWlr1Nbu5mMDKsTiZycqC/axnMvomjkrgr9a0txYdg1JHI0Mxw2kkZlUffJQVL2mRzS1cMi0omoaHukzMxMQJORiYiIfNO+wj9hmgEyu5xNVWWD1XGkAyQm9iQhoSdNTQe48CLNfyCxKeqLtvHciygauSu/nPRFQyPEhOQzc6j75CCJpeDspiK7iHQezWPaaniEr3Tr1g2AQ4cOWZxEREQkeng8ZRQXvwpAnz63Ao9aG0g6TJeMsygu+R/GjDHw+apxOtOtjiTSJqriSJu4KkP/ahKy2ODMSsI9qAsGkNmQZHUcEZF2o562R8rOzgY4YgJWERGReFZY+GeCQS/p6d8iI0Pz2sSThIQ8EhN6YbcbVFVpeAuJPSraygkz/UHc1aGf1dM2dqR8OzR2c5fGBEx/0OI0IiLtQ0XbrwSDQfbu3UtNTQ0Qmg+guSeyiIhIPPP5KjlY9BIAfXrfimFozLh406XLWQDU1W/D56u0OI1I26hoKyfMV1yPEQS/EcRIjPqRNeRLCYO64EsGu2nDV6wP8SLSOaho+5WysjI+/vhj1qxZE/4wqt62IiIiULh/HoFAA6kpw+ja9Xyr44gF3O4ctmwJAiaV6m0rMUZFWzlh3sJQD55Gl0/fUMYQw2ZQ2zf0/+XdX3vMMaJFRGKFxrRtKSsri549e5KYmAhAaWmpxYlERKy1dOlSLrvsMvLy8jAMgzfffLPFctM0ue+++8jNzSUxMZHx48ezY8eOFutUVFQwbdo00tLSyMjI4IYbbqCurq4D90JOhd9fy4EDfwVCY9nqM2z8Wvh+AID6+u14veUWpxE5cSraygnz7q8FoNHpsziJHI3X72PDhg0sW7asxW1F9WYCRhCz0U+gvMnqmCIip0w9bVvncoWGL1JPWxGJd/X19YwcOZK5c+e2uvw3v/kNTz75JM8++ywrV64kOTmZCRMm0NT01bnytGnT2Lx5MwsXLuTtt99m6dKlTJ8+vaN2QU7RgQN/x++vISlpAN27X2x1HLFQUREkJfUHoKpqpcVpRE6crnGXE+bZF+pp2+D0W5xEjmZH4S4qKyvo58lq8fjGT1YzfEAW+XTDu78WR7dEixKKiLQPFW1b13w8VLQVkXg3adIkJk2a1Ooy0zR5/PHHueeee7j88ssB+Otf/0p2djZvvvkmV111FVu3bmXBggWsWrWKMWPGAPDUU09xySWX8Oijj5KXl9dh+yJt53AE2Ff4ZwD69L4Zw1B/tXjXJWMcDQ27qG/Yicd7CLeru9WRRI5L71xyQvzVHgKVHkzU0zbaDerZn7OGjWlx65vXhwMcBiBQ0USgTv+HIhK7vF4vXq8X0PAI3/T1nrbBoCafFBFpzZ49eygpKWH8+PHhx9LT0xk3bhzLly8HYPny5WRkZIQLtgDjx4/HZrOxcuXRe+p5PB5qampa3KTjDRp0CL+/iqSkvmRnX2Z1HIkCLlc3kpMGAuptK7FDRVs5Id69oZMNbzoEbRoTNRY1GT4c3UM9bH37dfIoIrGreTxbu92O0+m0OE10cTqd2Gw2vF4v1dXVVscREYlKJSUlAGRnZ7d4PDs7O7yspKSErKyWV685HA4yMzPD67Rmzpw5pKenh2/5+fntnF6OJxj0MGRo6IqTvn3+C5tNFxhLSEbGOMCgoWE3Ho+uSpLop6KtnBDP3tAHP0+mxUHklDh7pQHgK67HEdCfv4jEpuZJYFJSUjSpyDcYhkF6ejqgychERKwwe/Zsqqurw7f9+/dbHSnuVFevw+UKkJw8kOzsS62OI1HE5cokOXkQAJVVKyxOI3J8qtrICWnuaevJ1IfjWGZPd2FLc4EJmQ0a11ZEYlNzT9vk5GSLk0SfYDCIwxHqUbRlyxYCgYDFiUREok9OTg5w5JdbpaWl4WU5OTlHjA/u9/upqKgIr9Mat9tNWlpai5t0nECgieqa9QD07ftjDMNubSCJOl2+7G3b2LiXrl3rrY4jckwq2spxBZv8+EpCb2bqaRvbDMPA1Tt04tilIRHDr6EuRCT2fL2nrbRUVlYWLkJs3ryZ3bt3W5xIRCT69O3bl5ycHBYtWhR+rKamhpUrV1JQUABAQUEBVVVVrFmzJrzO4sWLCQaDjBs3rsMzy4mprlmHaXqprEwgq/sEq+NIFHI6M0hJGQrA8BFFmKY+E0v0UtFWjstbWAsm2LsmEEhQT9tY5+ieiJHowGHaSNbVWiISg9TT9tgyMjIANHSEiMS1uro61q9fz/r164HQ5GPr16+nsLAQwzC4/fbb+eUvf8n//d//sXHjRq699lry8vKYPHkyAEOHDmXixIncdNNNfPbZZyxbtoyZM2dy1VVXkZeXZ92OyVEFAg3UfNnLdtPGXAxD5Q5pXUb6mYCNnJw6ysuXWB1H5Kj0LibH1Tyerbu3Lu3pDAzDwJWfCkDabhMzqG8WRSS2NBdt1dO2dc3DI/j9fjwej8VpRESssXr1akaNGsWoUaMAmDVrFqNGjeK+++4D4Gc/+xm33XYb06dPZ+zYsdTV1bFgwQISEhLC2/jHP/7BkCFDuOiii7jkkks455xz+NOf/mTJ/sjxVVWtxjR9uFxZHDyYbnUciWJOZxrpaWcAsGPnHIJBn7WBRI5C0yjKcTWPZ+vukw6+wxankfbgzEumfkc5zgYbjZvLSRrezepIIiInrHl4BPW0bZ3NZiMhIYGmpiYqKyutjiMiYonzzz//mJc9G4bBQw89xEMPPXTUdTIzM5k/f34k4kk78/mqqandAEBml28D+6wNJFEvI2MspWUbgF0cLHqZ/J7XWB1J5AjqaSvHZPqDePfXAuDqo562nYVht1GZ1AhA3dIDGsdHRGKKhkc4vuZeyCraiohIPKisWgEESUjIJzGxl9VxJAbYbG42bQxNKrhnzxP4fNUWJxI5koq2ckzeojpMXxBbkgNH90Sr40g7Kk9qwLSBd38t3n01VscRETlhmojs+FS0FRGReOHxHqK+fjsAmV3OtjiNxJJdu7qRnDwQn6+SvXvnWh1H5Agq2soxNQ+N4OqTrglNOpmA3aSuZ+jn2qUHrQ0jItIG6ml7fM1F24qKCouTiIiIRFZl5acAJCcPwu3OsjiNxBLTNBg4YDYA+w/8lYaGPRYnEmlJRVs5Jk94PFsNjdAZ1fQLFeKbtpbjO9RgcRoRkePzeDw0NTUBUFZWxt69ezXESyuai7Y1NTX4fJpcQ0REOqfGxgM0Nu4DbHTJOMvqOBKDunY9j65dz8M0fWzbdo/OKyWqqGgrR2WaJt69oXFdNJ5t5+RPNUgYkgkm1H2i3rYiEv22bdsW/nnt2rUsXLiQmhoN8fJNLpcLm82GaZqUlZVZHUdERCQCTCoqPwEgNfV0nM4Ma+NIzBo86AFstgQqq1ZQXPw/VscRCVPRVo6q4WA1wQY/QRus3reBZcuWsWHDBoKBgNXRpB2lfqcHAPVrygjUeS1OIyJybI2NoUkUXS4X+fn5dO/e3eJE0ckwDNxuNwAlJSUWpxEREWl/ffpW4PWWYRguumScaXUciWGJib3o1+92AHbs/BUezyFrA4l8SUVbOaqdH20CoMHhpW5NKXWrStiyaC2HDx+2OJm0J1ffdJw9U8AfpH5FsdVxRESOqXloBJfLZXGS6NdctC0u1nu7iIh0LoFAAyNGhNq3jIyx2O1JFieSWJff8wekpg7D76/hix0PWR1HBACH1QEkeiUcDo3lktmzO7l9BwCwefe2Yz1FYpBhGKSe25OKl7ZRt7yI1PN6YjjtVscSEWlVc9HW6XRanCT6NR+jvXv3smPHDgD69euH3a73eBERiW379v2JpCQfDkca6WkjrY4jMWrdunXcdNO/h+9ndPFz8cVQVvYuj/y6iLt+/r8WphNR0VaOwgyaJHzZodaRmWBtGIm4xNO7Yc9wE6jyUL+2jJRxuVZHEhFplXranri6ujoAysvLWb58OaWlpUyePJmBAwdanExEROTkNTUVsa/wOQAyu5yDYaisISfLx+zZ57Z4pKIimeqatZx++iY83sO4Xd0syiai4RHkKHzF9dh9EDCC2FL1wbizM+wGKeeExrat+/ggZlAzZopIdFJP2xNnGAYQmli0a9eu5OTkWJxIRETk1O3a9SjBYBNlZSkkJfW3Oo50MhkZ43A6M0lM9LNly52YZtDqSBLH9JWUtMqzqwqABpePDJthbRiJCK/fx4YNG8L3jYBJDydwuJHajaWkjdSHexGJPl+fiEyOzTAMHA4Hfr8/3OtWREQkllVVraak9C3AYN3aHow7s/XPqt+87P3rNm78HDi31WUiNpuTrO6T2Fc4n4qKjyksfI7evX9kdSyJUyraSquadlYBUOfyWhtEImZH4S4qKyvo58kKP1bhSqa7L5my93aoaCsiUam5aNs8yZYc29eLtip0i4hILAsG/Wz/4n4A8nL/g8rKHcdY+8jL3ptNnfpZBNJJZ+JydWXtmp6cOW4/u3Y/RkbGmaSnj7I6lsQhDY8gRzD9Qbx7qwGoV9G2UxvUsz9nDRsTvvUZNZAgJgkV4CmssTqeiLSDBx54AMMwWtyGDBkSXt7U1MSMGTPo2rUrKSkpTJkyhdLSUgsTH1tDQwOgnrYnyuEIfT+vnrYiIhLrDhz8G3V123A4Mujf/6dWx5FObvfurmRlXYpp+tm0+XZ8viqrI0kcivmibWf7MBoNPHuqMb1B/G7wOAJWx5EOZHM7qE4MjRdZ9/FBi9OISHsZNmwYxcXF4dsnn3wSXnbHHXfwz3/+k9dee42PPvqIoqIirrjiCgvTHl0wGAwXbRMSNEnmibDb7YCKtiIiEts8njJ2734cgAH978TlyrQ2kMQBg6FD/pvEhF40NR1gw4abCQY9VoeSOBPzRVvoPB9Go0XT9srQv1mAhrONO+VJoYJI46bD+MsbLU4jIu3B4XCQk5MTvnXrFpoFt7q6mueff57HHnuMCy+8kNGjR/PCCy/w6aefsmLFCotTH6mhoYFgMDQZhHranpjmnrY+nw+/329xGhERkZOzc+cjBAJ1pKWOIC9vqtVxJE44HKmMGPFH7PYUqqpXsXXrbExTk3ZLx+kURdvO8mE0WjRtrwCgMUsV23jkcQZo7A6YUPuJetuKdAY7duwgLy+Pfv36MW3aNAoLCwFYs2YNPp+P8ePHh9cdMmQIvXr1Yvny5UfdnsfjoaampsWtIzS/jt1ux2brFKcwEWcYBomJiQB4vRrySEREYk9l5Yrw5GODBz+IYditjiRxJCVlECOGP41hOCgpfYs9e56wOpLEkU7xiaezfBiNBv6KJvyHGsFGqHAncammf6hg37C6lEC9z+I0InIqxo0bx7x581iwYAHPPPMMe/bs4dxzz6W2tpaSkhJcLhcZGRktnpOdnU1JSclRtzlnzhzS09PDt/z8/AjvRUhze9zce1ROTHJyMqCirYiIxJ5AoImt2+4GoEePq0lLG2FxIolHmZlnM2TwwwDs2fsURUWvWpxI4kXMF20704fRaND0RaiXratXGqZTPW3jVVM3cOYmY/qC1K8stjqOiJyCSZMm8R//8R+MGDGCCRMm8O6771JVVcWrr578yebs2bOprq4O3/bv39+OiY+uujo0SaaKtm2TkpIChL6UFhERiSV79j5FY+NeXK4s+vfT5GNinby8qfTufQsAW7f9QoVb6RAxX7TtTB9Go0HT1lDRNmFwF4uTiKUMg5Tv9ASg7tMiTF/Q4kAi0l4yMjIYNGgQO3fuJCcnB6/XS1VVVYt1SktLycnJOeo23G43aWlpLW4dQT1tT4562oqISCyqqd1EYeFzAAwZ/BBOZ8ecb4gcTf9+P6Fnj2sAk63bZnPg4HyrI0knF/NF22+K5Q+jVgs2+WnaWQVA4mldrQ0jlksa0Q17motgnY/61UfvmS4isaWuro5du3aRm5vL6NGjcTqdLFq0KLx8+/btFBYWUlBQYGHK1qloe3K+XrRtnshNREQkmgWDvi8nfQqQlXUp3bt/1+pIIhiGwaBB95Of/wMAtm+/l/3751kbSjq1Tle0jeUPo1Zr2l4BARNHt0QcWUlWxxGLGXYbqReEhgapWVRI0BOwOJGInIw777yTjz76iL179/Lpp5/y/e9/H7vdztVXX016ejo33HADs2bN4sMPP2TNmjX84Ac/oKCggLPOOsvq6EfQ8AgnJyEhAbs9NGlLPI3TLyJyPA888ACGYbS4DRkyJLy8qamJGTNm0LVrV1JSUpgyZQqlpaUWJo4fhYV/pq5uC16vkz8+u4+bbvr3I24bN35udUyJQ4ZhMHDA3fTuNR2AL3Y8zI6dczBNfV6W9hfzn3ruvPNOLrvsMnr37k1RURH3339/qx9GMzMzSUtL47bbbovaD6NWa9xUDkDi6V0xDI1nK5B8Zg51nxzEX95E3ccHSBvf2+pIItJGBw4c4Oqrr6a8vJzu3btzzjnnsGLFCrp3D802+fvf/x6bzcaUKVPweDxMmDCBp59+2uLUrVNP25NjGAbJycnU1NQccfWRiEi8GzZsGB988EH4/tfbmDvuuIN33nmH1157jfT0dGbOnMkVV1zBsmXLrIgaN+rqtrN7z5MArFmTx6xZF7a63tSpn3VkLJEwwzDo3/9n2OxJ7NnzOIWFf6ahfjfDhj2Gw5FqdTzpRGL+U09n+jBqJdMXCPW0BRJP72ZxGokWht1G2sV9qHhpG7VLD5J8Vi72FJfVsUSkDV5++eVjLk9ISGDu3LnMnTu3gxKdnGAwGC7aNvcalROXkpJCTU0NlZWVVkcREYkqDoej1aHzqquref7555k/fz4XXhgqGr7wwgsMHTqUFStWqBNQhASDHjZvvgPT9NKt64Xs21thdSSJU+vWreOmm/691WWpqd157LFn6Nf3NpISe7N12885XL6Y1WumMnLEH0lM7NXBaaWzivmibWf5MGolj8fD5rdXkeU18SfAqr2fwz6DDRs20CegsW3jXeLwbjiXpuA7WEft4v1kfK+/1ZFEJA7V19cTDAYxDEM9bU9C87i26mkrItLSjh07yMvLIyEhgYKCAubMmUOvXr1Ys2YNPp+P8ePHh9cdMmQIvXr1Yvny5Uct2no8HjweT/i+hqVpm127H6OufjtOZyZDhs4BbrY6ksQtH7Nnn9vqkjlzPg7/nJPzPRKTerNhw4+or/+Cz1Z9j6FDHiEra+IRz5s16xZqaw+1us3mQrDI1+lTj7B69WqM5aXgyKLa1kDd6joAtnyylpSBoyxOJx3N6/exYcOGFo8l5JtkH4S6lcWknJ2Ho2uiRelEJF41f+hNSEjQED4nobloq562IiJfGTduHPPmzWPw4MEUFxfz4IMPcu6557Jp0yZKSkpwuVxkZGS0eE52djYlJUefpHfOnDk8+OCDEU7eOVVWrqCw8HkAhg6Zg9ulK0AlNqSnjWTsmDfYtOk2qmvWsXHTDHr0+E8GDvgFdrs7vF5t7aETKgSLNFPRVjB8Jj0doeEk8of1o09a6PL3zbu3WRlLLLKjcBeVlRX082SFH1u2YyPju59JVlMqu/6xmsOjv5rDcMyYMbjd7tY2JSLSbpqLtklJmijzZDQXbRsbG2loaNBxFBEBJk2aFP55xIgRjBs3jt69e/Pqq6+SmHhynRRmz57NrFmzwvdramrIz88/5aydnc9Xw+YtdwImeblT6d59/HGfIxJNEhJy+da3XmL37t+zr/CPHDz4d6qr1zDstN+RkjLY6ngSo2zHX0U6u+QisGFgS3ZiS3VaHUeiwKCe/Tlr2JjwzWF3srRwNSYmyUVgflJO3aoSVr7yIatXr7Y6rojEgebL+puLj9I2DocjPKyEZj4XEWldRkYGgwYNYufOneTk5OD1eo8YVqa0tLTVMXCbud1u0tLSWtzk2EzTZNv2u/F4iklM7MXAgfdYHUnkpNhsTgYM+BlnjPwLTmcmdXVb+WzVZPYVPodpBqyOJzFIPW2F5AMmAI6cZF1yKkfVNbsbrh6p+A7U0c/TnaQzcq2OJCJx5PDhwwCkpaXR2NhocZrY5HK58Pv9lJaW0rdvX6vjiIhEnbq6Onbt2sU111zD6NGjcTqdLFq0iClTpgCwfft2CgsLKSgosDhp53Kw6CXKyt4lGIS33krghb9cF162cePnQOuXk4tY5UQmKRt35rts3Tab8vIP2bnzEQ4fXkxysqfV54gcjYq2cc5f3khCBZiYOHN0qaQcm7tfBv6yBoINfrx7NamCiHQcFW1PndvtpqGhQT1tRUS+dOedd3LZZZfRu3dvioqKuP/++7Hb7Vx99dWkp6dzww03MGvWLDIzM0lLS+O2226joKDgqJOQSdvV1m5hx46HAejW9Rx+NP1bLZZPnfqZFbFEjuP4k5S53d0ZOeI5iopfZceO/6aq6jMmTrJRW5tLSspp6jAnJ0RF2zhXt7I49K/LS1qCfh3k2AynDffALjRtLse7t5qETP3OiEjHOHQoNNNuenq6io4nyeUKjVmv4yciEnLgwAGuvvpqysvL6d69O+eccw4rVqyge/fQfB+///3vsdlsTJkyBY/Hw4QJE3j66actTt15+P11bNx0G8Ggl4MH0+jTW5NgS+xrrRducnJvzjprH92z6jlcvoiGht1063YRdrs6zsmxqeISx4LeAPWrQh/cKpIaybM4j8QGR3YSjrIG/Ica6VGdRmnAtDqSiHRyDQ0NNDQ0AGhswFPQXLQtKysjGAxis2lqAxGJby+//PIxlyckJDB37lzmzp3bQYnih2mabNt2N42Ne3G7c1m5ohvnnK2eh9IZtN4L1zSDzH36CS691ElD4x4OHPw73bpeQHLyQAsySqzQ2Xoca/z8EGajH18S1Lm9VseRGGEYBu4hmRhOGwl+B5mbVbQVkchqHhohPT09PJmWtJ3T6cRut+P3+6moqLA6joiIxLH9B+ZRWvY2hmHn9GGP4/WqfZfOzTBsLP0oSI+8q3A5uxEMNlF26F+Ulb1LINBgdTyJUiraxinTNKlbVgRAXR8D9KWmtIHNZSfhtK6YmKTug4Z1ZVZHEpFOrHlohG7dulmcJLYZhkFGRgYARUVF1oYREZG4VVm5gp075wAwYMBsMjLGWJxIpOO4XN3Iy7uSjPQzAYP6hp0cOPgPevassjqaRCEVbeNU09YKfCX1GC4bdflWp5FY5OiWyKHk0DeCla/vwLu/1uJEItJZNfe0VdH21DUfw4MHD1qcRERE4lFTUxEbN92GaQbIyZ5Mfs/rrY4k0uEMw06XLmeRl3slTmdXgsFGzjl3D5s2/Rifr9LqeBJFVLSNQ6ZpUrO4EICUgjyCLnWzlZNzKKWehiwwfUEOz9uMv1wzuotI+2su2jZPDCMnr7lou3//fouTiIhIvAkEmtiw8RZ8vgpSU4YxZMgvMQx9FpX45XZn0SPvStLTxxIMQmnZ26xYOZFDh963OppECRVt45Dni0p8B+ownDZSzu1hdRyJZQYcHm3gzEsmWO/j0POb8Fc2WZ1KRDoZ9bRtP83HsKSkBJ/PZ3EaERGJF6YZZOu2u6it3YTT2YXhw5/Gbk+0OpaI5QzDQWaXAj5YOIjk5IF4vYfZsPEWNm+ehc9XZXU8sZiKtnHGDJhU/2svAMnjcrGnuKwNJDHPdBh0u/50HF0TCFQ0cehPG/BXqHArIu3D5/NRWRm6TExF21OXnJxMcnIywWCQ4uJiq+OIiEic2L3ncUpL/4lhODh92JMkJva0OpJIVKmoSGbsmLfo3ftmwEZJ6Vtf9rr9wOpoYiEVbeNM/ari0Fi2iQ5SL9BgtnJqvH4fGzZsYMXGVewd5cGXDIFKD2V/+lyFWxFpF6WlpQC43W6KiorYu3cvpmlanCp2GYZBfn6o/T9w4IDFaUREJB4UFf0Pe/fOBWDI4P8mM/PbFicSiT7r1q3j5pun8etHVvL++wOornbj9R5iw8Yf8eJfz8Hnq7Y6oljAYXUA6TiBeh817+8DIP3i3tiTnRYnkli3o3AXlZUV9PNkAVCfZCO3NpG0Kjjw1CpKCwz8yV+NUzVmzBjcbrdFaUUkFu3duxcAv9/PypUr2bhxI7169bI2VIzr2bMn27ZtU9FWREQirqLiU7ZtvxuAHTv68vJLLwMvH7Hexo2fA+d2bDiRqOJj9uyv/gaCQT9VVSuorllHz57FrFw5iSFD/ptu3S6wMKN0NBVt44RpmlS9tZNggx9nThLJZ+ZaHUk6iUE9+3PWsDHh+//456uc6xxGF1LJWuJnX5cqPM4Am3dvBeDss8+2KqqIxKDmom1GRgY9e/akpKTE2kCdQM+eoUtS9+/fj2mamgRGREQioqZmAxs23oJp+snO+jdefulAi6LU102d+lkHpxOJbjabg8zMc0hK6s/2L/6PtLRSPt9wI7k5Uxg48B6czjSrI0oH0PAIcaJhXRmNGw6DDQoHNPLpik9ZtmwZy5YtY8OGDQQDAasjSifRhJfNzgPYUpw4g3YGVHdnbM/hDOs31OpoIhJjAoEAhYWFACQmarKS9pKXl4fdbqe2tjY8yZuIiEh7qq3bxrr11xMI1JGRMY6hQ38D6EtCkbZKSMjlvQVD6JV/A2BQXPK/rPxsEuXlH1kdTTqAirZxwFdaT9VbuwCoGmjw8ftLqFtVEr5tWbRWH9qkXfkMP0nfysaW7gJ/kIZ1ZSR5NByHiLRNSUkJXq8Xl8uFy6WJM9uLy+WiT58+AGzfvt3aMCIi0unU1+9i3bpr8furSUsbxcgRf8Ju1xBpIidr9erP+c1v1vLBwgHU1rrxeEpY//kPee65sfz85zdaHU8iSMMjdHKBGi+HX9iM6Qng6ptO9YAahlUPbXE5++bd2yxMKJ2V4bSRdEYWjRsOEaj00Lsyg8OlmjxIRE5c89AIWVlZuoS/nQ0ePJhdu3bxxRdfcM4551gdR0REOomGhj2sW3cNPl85qSnDOGPkX3A4UqyOJRLjvhrvNhj0UVm1nJqa9fTrX0GPnks5ePAl8vKmYhh2i3NKe1NP207K4/GwYtEn7HtqJYEqD75k2DWohg2bNmooBOkwhsNG4sgsHN0SsWHQfZVJw4ZDVscSkRjRXLTNzs62NkgnNGjQICA0rm1DQ4PFaUREpDOorl7H6jX/gcdbSnLyQM44Y57G3RRpZzabk66Z3yE3ZwpOZyZud4Bt2+9h1arvU1m5wup40s7U07aTWv/hKjIWN+CyJeKzBdiTWIXv8wBbPllLysBRVseTOGLYDRKGd+PA8h1kNCVQ8dI2TF+Q5NEqwojI0dXX17N7924gVLStqqqyNlAnk5GRQXZ2NqWlpezYsYORI0daHUlERGLYoUMfsGnzjwkGmygvT+KN1908/+fpLdbZuPFzoPWJyESkbRISetAj7//xv//7JuPOqqG2bjNr100jI2McffveRpeMs3SlWiegom0nYwZN6leVkLvUxGZLxEh0kDEqj9GJfQENhSDWMGwGe5LLyXQk0rsuk8rXvmDnth3U9TEYM2YMbrfGuBKRltasWUMgECAvL48uXbpYHadTCAaD4d7LAAMHDqS0tJStW7eqaCsiIifFNE0OHvwH2794EAhSVJRGwVn/jzGjjxyLfurUzzo+oEgnZhg2duzozu23v87uPU9SVPQqVVUrWbduJenpo+nZ8xqyul+MzabP27FKRdso5fF4WL169RGPH63AZQZNmrZVUPPBPnxF9diAOpeX7NE9sLk1rolYb8f+XVRWVvDvAy+ma0MSXTea7F+zk9XA2WefbXU8EYkigUAg3AaOGzfO4jSdR1lZGbt27aKkpISSkhLOO+88IDQZWUVFBZmZmRYnFBGRWBIINLBt+72UlLwJQG7uf/DKyzs4+9uaPFSkI7lcXRky+EH69L6ZfYV/pKjoFaqr11BdvYYvnF3IzbmCnJzvk5IyRL1vY4yKtlFq9erVrHzlQ4b1Gxp+bPPurcBXBa5ggw9PYS0N2w5Tu74UR1NovaADtqYWE7RDrntAh2cXOZpBPfvT+6zBeHdV491Xwxmu/lR9YWJ+21TjISJh27Zto6amhuTkZIYNG8aePXusjtRpZGVl0bNnT4LBINXV1eTm5lJcXMyCBQu48sorsdv1Ra+IiBzbrFm34HbvYdxZhaSmeggGYcOGPF5+aQcbN24AvmN1RJG4lJCQy+BBD9C7980cPPgSxcX/g8dTQuH+5ync/zwJCT3p3m083bpdSHr6aOz2BKsjy3GoaBvFhvUbylnDxgBg+oOkeFyk7TAp370Fb1EdgUpPeF0H4DeCVCU1cji5gbc/XciZGrtWopBhGLgHZIDdwLu7moztJtVv7yb90n4YNhVuReJVIBBg9+7deL1e3nnnHQBGjx6Nw6FTlUho7nXbo0cPAL744gu2bNnC8OHDLU4mIiLRzOutYPCQNQwYUA6A3Z5CTs7F9O/XEybD1KmrrA0oEmfWrVvHTTf9e6vL0tJOZ/bshykqfo3y8qU0NR1g/4F57D8wD8NwkpY2nIz0saSljyQ1ZSgJCfnqTBVl9EkoWpkmiV4nnl1V+CuaCNZ46U0GVJo0Uh5ezd41garkJiprqjlt1Ol0sRn0BTbs3WpZdJET4e6bTuGhA+TUplK3rAh/eROZVw3GlqC3JZF4tHv3bt544w0Mw6ChoYGUlBQNnRJhWVlZDBw4kNraWurq6li/fr2KtiIi0iqfr5r9++dRuP8vDBhQB0BKylAyu3wHu13jZYpYx8fs2a1P8Dd16pPU1DR/wTKYnJwaevSsJienlqQkH9XVa6muXhte3+u1UV2dSFNTOud950oSk3qTlNibxMQ+OJ1pHbI30pKqI1HGV1JPw/oyeqw0cTR2wVtRE17msfk5lFBHcp8ueNLBmw6m08uGDZvo4+yqXooSc8qTG7EPSqP75wZN2yoofXIdmVcNxt1LDYJIvDFNE7fbTWVlJRAaCkiTFEaeYRj069ePDRs2sGvXLtasWcPo0aOtjiUiIlHANANUVa+lpORNSkreIhhsBKCyMpHThl5KQkKexQlF5NhaL+iapskttzzGb387iSZPEV7vIbzeclyuIN271wP17N7z+xbPcTjSOXzYpKbGRl2di/o6N3V1burqXDQ0uEhJyeKxx57poP2KHyraRgF/RRONGw/TsL4MX3E9EPqPCRhB3FkpODITsGcm8OrCl6ncX8E5ad+Giq+ev+WTtaRoKASJUQ15BllnjaB8/lYCFU0ceuZzksflkvbd3tiTnVbHE5EOYJom69atCxdsMzMzqaurY8eOHQDs3bsX0zStjNipdenShczMTCoqKnj33XcJBAKMHTtWl8eJiMQhr/cw1dXrOVz+IYcOLcTn++oqz5SUIfTpM5N77v4z3xqlgq1IrDIMg4oKSE09jdTU04DQlzQ+XyVebwV/+/sCBg3KJDXFQ0qqh8REP35/NRkZkJHR6hapq3Wybt11JCb1IjGxN0mJoX8TE/Ox25M6cO86l7gq2s6dO5ff/va3lJSUMHLkSJ566inOPPPMDs9hBk38ZQ00bqugYUMZ/qKGr5YZ0JgFWwKFJOCk4PQ+LZ47qGf/8Di3zTbv3tYRsUXandfvY8OGDQAY40wyN0LKQahfUUz92lJSxuSQNCYbZ26yigciEWZlG7l79262bg0N69O/f39KSkr4+OOPKSkpAWDjxo306tWrQ7LEq7S0NGw2G4cPH+bdd99l06ZNjB07lgEDBpCYmGh1PBERS0XL58j2FAx6eOCBG7Hbi0lLayI9o5GumQ2kpHpbrOdwpNGt24Xk5V5JRkbzF3rPWxNaRCLGMOy4XN1wubrx4eJ/csvN/xleFgx68ftr+NWv/sodd1yA31+Nz1+D31+N31eDSYCUVC8VlZ9A5ZHbdrmySEzshdudhdPZ5ctbBi5nJnZ7EobhwLA5sRmO8M8GX37+N2xf/mwDw/jyZ+PLn22AgWHYsNuTsduTsNsTMQxbRxyyDhE3RdtXXnmFWbNm8eyzzzJu3Dgef/xxJkyYwPbt28nKyor46/sON1K3sYxD6wtxV4Dd99WyoGnS6PJRndhETYKHgGGyaMUSTSQmnd6Owl1UVlbQzxP6G6wFkro4ySh30MWbSt2nRdR9WoS9ixtHfgol/gr8ieBPhEACBJ1g2mHM2LG6jFrkFFjdRvbv35/hw4dTUlJCz549KSkpISsri549ewKEi7cSOYcOHaK2tpbu3btTXl5OYWEhhYWFAKSmppKZmUnXrl3JyMhg5MiRpKenW5z45DRPeNesX79+2O12CxOJSLSzuo1sq2DQg9dXic9bgddbjs8X+tfjKaGpqYgmTxFNTQfxeg9z3vmtb8PpzGTLFhv/8R+/o0vGOGw2Xf0mEs9sNhcuVze2bDFJT29ZpzJNk0CgjnnzPmHmzBtobNxHQ2MhjY37aGwsxO+vwestw+st67C8fr+dpKTML4u4oWKuw5GK05nOp5+upb7Oh8djx+t14PXa8XhC/zqdOfz2t891WM4TETdF28cee4ybbrqJH/zgBwA8++yzvPPOO/zlL3/hrrvuivjre76opP69Qpo7hQcNkwanl08OrCUlK51J35lIztfWV+9ZiRet9R5fsWk13r5p9K7JpOmLSgKVHgKVHrq08nzTNCl6ZzmG247pANMWuiWnpmB32sFuYNhtYDMIBgJUV1ZBEAwTMMEMmBgm2DC+evzLxwzTABMwQtsMGiamDQy7QdAOpgOCdsjM7ooj0YXhsmNz2TDc9i9/Dv1ruEKvT9AMvaZphn4OAqaJz+tj185dGMFQpuZsvXvmY3c4Qt8xGgbNXyqGvln88gAYhL5tbGWZP+Bnz549mPDV+kC//v1wupyEvpX8ajt8fTvNCwy+6uXcyrrGN5/39ax847lHbOfL12++b4auRCBohv41+ern5se//P/xebxHHrMg9OqZT9roXOyprlZ+W+RorG4jAUaMGEFDQ8PxV5SIycrKYtiwYXz22Wc0NDTgcrnw+XzU1tZSW1vLvn37AFi8eDFJSUlkZ2fTvXt3UlNTSU1NJSUlBZfLhc1ma3H7+pUSRxvmoj0f9/l8eL1ePB4PTU1N1NXVUV9fT319PZWVlZSWlpKYmIjH42HAgAHk5uaSlJQUvtnt9hb5VdTtHL75O9Pa79DJrNPRzzvRbQeDQTweD0VFRQQCAfx+P+np6fTp04f8/Pwj1peji4Y2cu/ep2lsOkAg0Egw0Egg0Egg2BD6NxD6NxgMPW6a/hPers9nIyW5e7jnm9udjdudjc3m5m9//Zibf3ROBPdKRDoDwzBwOFJ5//0dHDr0yteWOIH+uFx+Sku/YOTIXBISfLjcAdwuP263H5fbj89bT3JKAjabiWGY2GwmNgMwQud0XbumEPpgCJgm5pc/19Y2kJqaCJiYZhDT/KpnpMMRwOs91Grefv2Ovi8VFXtO5VBERFwUbb1eL2vWrGH27Nnhx2w2G+PHj2f58uVHrO/xePB4POH71dXVANTU1Byx7onyZRmUpdWz6+BeUrLTaXL6MQ1YVb6Z9PpUXGtajvGxfd8XlCSkkpyeeszHYm3daM2ldaNr3W17t5NgZnL66adjdDNxVUL1F6UkVhhkJqbjCNhxBpsvk/hSU4tN4C2tp6Mc3nfqr5XQymPFq7ee8nZb639ctHzDKW83GrR2zErWbMXf3Y47/+Qms2t+n4+n8VPb2kZCZNrJuro69u7dS2NjIwcOHCAhIQGXK1R8//r9E13WHtuI9e2f7DaKiopISEigR48eBAIBvvjiC1wuFykpKeHCusfjobKykm3bYvNL5sbG0GQ6n3/+OZ9//rnFaUQ6zrnnnntKPeXjrZ2MljZy9+43qavfccLrG4YtXIgtLCynoSFIY6ODxobQhEENDU4aGlysW7eV55+/PPw8vx/8fhNoYvXqNVx33eWtbn/z5k3U1o5tdVkgEKS2tqndlrX39jr7smjJESvLoiVHrCw79nM8zJzZ+vvC9dev5t57rzvKsqeYN++mYyyb3uqyWXc8xbx5PwrfN03zyy+tfPzkJ39l2OkDcTiCOB1B7I4ATmcQt8tPTW0JEy4eQtD0EAw2EQiE/g0Gm6iqNE7pvToibaQZBw4ePGgC5qefftri8Z/+9KfmmWeeecT6999//5f93HTTTTfddIvH2/79+zuqibJcW9tI01Q7qZtuuukW77d4aSfVRuqmm2666dbWW3u2kXHR07atZs+ezaxZs8L3g8EgFRUVdO3a9ZiTIdXU1JCfn8/+/ftJSzu5Xl7xTsfw1Oj4nRodv1PTGY6faZrU1taSl6cZkY/lZNvJjtIZfhfbi45FiI7DV3QsvqJjEdKW46B28viivY08mnj+e9C+a9+17/Eh0vsdiTYyLoq23bp1w263U1pa2uLx0tJScnJyjljf7XYfMalRRkbGCb9eWlpaXP3iR4KO4anR8Ts1On6nJtaPX6xOsHSy2tpGwqm3kx0l1n8X25OORYiOw1d0LL6iYxFyoschntrJztxGHk08/z1o37Xv8SZe9z2S+93ebaStXbcWpVwuF6NHj2bRokXhx4LBIIsWLaKgoMDCZCIiItZSGykiItI6tZEiImKluOhpCzBr1iyuu+46xowZw5lnnsnjjz9OfX19eBZQERGReKU2UkREpHVqI0VExCpxU7S98sorOXToEPfddx8lJSWcccYZLFiwgOzs7HZ7Dbfbzf3333/E5TBy4nQMT42O36nR8Ts1On6xqyPayI6k38Wv6FiE6Dh8RcfiKzoWIToOx9bZ2sijieffA+279j3exOu+x+J+G6ZpmlaHEBEREREREREREZGQuBjTVkRERERERERERCRWqGgrIiIiIiIiIiIiEkVUtBURERERERERERGJIiraioiIiIiIiIiIiEQRFW3b0dy5c+nTpw8JCQmMGzeOzz77zOpIUWHp0qVcdtll5OXlYRgGb775Zovlpmly3333kZubS2JiIuPHj2fHjh0t1qmoqGDatGmkpaWRkZHBDTfcQF1dXQfuhXXmzJnD2LFjSU1NJSsri8mTJ7N9+/YW6zQ1NTFjxgy6du1KSkoKU6ZMobS0tMU6hYWFXHrppSQlJZGVlcVPf/pT/H5/R+6KJZ555hlGjBhBWloaaWlpFBQU8K9//Su8XMeubR555BEMw+D2228PP6ZjKB2hLW2sz+fjoYceon///iQkJDBy5EgWLFjQYp3a2lpuv/12evfuTWJiIt/+9rdZtWpVpHfjlByvPW3NkiVL+Na3voXb7WbAgAHMmzfviHVi8fwlEsfiZLZptUgchxM574hGkTgWxzuHiEaRep9o1tp5gES/k/27fvzxxxk8eDCJiYnk5+dzxx130NTU1AGJ28/J/B2/9tprDBkyhISEBIYPH867777bQWnbV1v3/bnnnuPcc8+lS5cudOnShfHjx8fEOUFrTuX9++WXX8YwDCZPnhzZkBFyMvteVVXFjBkzyM3Nxe12M2jQoJj8vT+ZfY/29zkVbdvJK6+8wqxZs7j//vtZu3YtI0eOZMKECZSVlVkdzXL19fWMHDmSuXPntrr8N7/5DU8++STPPvssK1euJDk5mQkTJrT4Q5k2bRqbN29m4cKFvP322yxdupTp06d31C5Y6qOPPmLGjBmsWLGChQsX4vP5uPjii6mvrw+vc8cdd/DPf/6T1157jY8++oiioiKuuOKK8PJAIMCll16K1+vl008/5cUXX2TevHncd999VuxSh+rZsyePPPIIa9asYfXq1Vx44YVcfvnlbN68GdCxa4tVq1bxxz/+kREjRrR4XMdQIq2tbew999zDH//4R5566im2bNnCzTffzPe//33WrVsXXufGG29k4cKF/O1vf2Pjxo1cfPHFjB8/noMHD3bUbrXZ8drTb9qzZw+XXnopF1xwAevXr+f222/nxhtv5L333guvE6vnL5E4Fm3dZjSIxHE4kfOOaBSJY3G8c4hoFInj0Oxo5wES/U7m73r+/Pncdddd3H///WzdupXnn3+eV155hV/84hcdmPzUtfXv+NNPP+Xqq6/mhhtuYN26dUyePJnJkyezadOmDk5+6tq670uWLOHqq6/mww8/ZPny5eTn53PxxRdH9bnR0Zzs+/fevXu58847Offcczsoaftr6757vV6++93vsnfvXv7nf/6H7du389xzz9GjR48OTn7q2rrvMfE+Z0q7OPPMM80ZM2aE7wcCATMvL8+cM2eOhamiD2C+8cYb4fvBYNDMyckxf/vb34Yfq6qqMt1ut/nSSy+ZpmmaW7ZsMQFz1apV4XX+9a9/mYZhmAcPHuyw7NGirKzMBMyPPvrINM3Q8XI6neZrr70WXmfr1q0mYC5fvtw0TdN89913TZvNZpaUlITXeeaZZ8y0tDTT4/F07A5EgS5duph//vOfdezaoLa21hw4cKC5cOFC87zzzjN//OMfm6ap3z/pGG1tY3Nzc80//OEPLR674oorzGnTppmmaZoNDQ2m3W4333777RbrfOtb3zLvvvvudk4fGd9sT1vzs5/9zBw2bFiLx6688kpzwoQJ4fud4fylvY5FW7cZbSJxHEzzyPOOWBCpY2GaX51DxIL2PA5HOw+Q2HQif9czZswwL7zwwhaPzZo1yzz77LMjHS/ijvV3PHXqVPPSSy9t8di4cePMH/3oRx0RLeLa8h7m9/vN1NRU88UXX4xwqo5xvH33+/3mt7/9bfPPf/6zed1115mXX355x4WLsGPt+zPPPGP269fP9Hq9HZyqYxxr32PhfU49bduB1+tlzZo1jB8/PvyYzWZj/PjxLF++3MJk0W/Pnj2UlJS0OHbp6emMGzcufOyWL19ORkYGY8aMCa8zfvx4bDYbK1eu7PDMVquurgYgMzMTgDVr1uDz+VocwyFDhtCrV68Wx3D48OFkZ2eH15kwYQI1NTVR3VukvQUCAV5++WXq6+spKCjQsWuDGTNmcOmll7Y4VqDfP4m8k2ljPR4PCQkJLR5LTEzkk08+AcDv9xMIBI65TmewfPnyI/5mJ0yYED5u8XT+crxjES9O5jh887yjs2jrsfjmOURncaLH4WjnARKbTuTv+tvf/jZr1qwJXx6/e/du3n33XS655JIOyRgJJ/J33Fnbi5N5D2toaMDn88X8+/+J7vtDDz1EVlYWN9xwQwemi6wT2ff/+7//o6CggBkzZpCdnc3pp5/Or371KwKBQAenbV8nsu+x8D7nsDpAZ3D48GECgUCLggRAdnY227ZtsyhVbCgpKQFo9dg1LyspKSErK6vFcofDQWZmZnideBEMBrn99ts5++yzOf3004HQ8XG5XGRkZLRY95vHsLVj3Lyss9u4cSMFBQU0NTWRkpLCG2+8wWmnncb69et17E7Ayy+/zNq1a1sd71O/fxJpJ9PGTpgwgccee4zvfOc79O/fn0WLFvH666+HTz5TU1MpKCjg4YcfZujQoWRnZ/PSSy+xfPlyBgwYEPF96ihH+9urqamhsbGRysrKuDl/Od6xSExMtChZx2rrcWjtvKOzONFjcbRziM7iRI7Dsc4DJPac6N/1//t//4/Dhw9zzjnnYJomfr+fm2++ObouGz5Bbfk7PtrfRKyes57Ke9jPf/5z8vLyYvbLmrbs+yeffMLzzz/P+vXrOzZkhLRl33fv3s3ixYuZNm0a7777Ljt37uTWW2/F5/Nx//33d3DyU9eWfY+F9zn1tBWJITNmzGDTpk28/PLLVkeJKYMHD2b9+vWsXLmSW265heuuu44tW7ZYHSsm7N+/nx//+Mf84x//OKJXoki0euKJJxg4cCBDhgzB5XIxc+ZMfvCDH2CzfXXa87e//Q3TNOnRowdut5snn3ySq6++usU6IvFO5x06h9B5QOdzon/XS5Ys4Ve/+hVPP/00a9eu5fXXX+edd97h4Ycf7qCk7See/45Pdt8feeQRXn75Zd54442Y/ds/0X2vra3lmmuu4bnnnqNbt24WJG1/bfl/DwaDZGVl8ac//YnRo0dz5ZVXcvfdd/Pss892cOr20ZZ9j4X3OfW0bQfdunXDbrcfMVt6aWkpOTk5FqWKDc3Hp7S0lNzc3PDjpaWlnHHGGeF1vjkhit/vp6KiIq6O78yZM8OTsPXs2TP8eE5ODl6vl6qqqha9Hb/++5eTk3PEzJ/Nv6/xcAxdLle499zo0aNZtWoVTzzxBFdeeaWO3XGsWbOGsrIyvvWtb4UfCwQCLF26lD/84Q+89957OoYSUSfTxnbv3p0333yTpqYmysvLycvL46677qJfv37hdfr3789HH31EfX09NTU15ObmcuWVV7ZYJ9bl5OS0etzS0tJITEzEbrfHzfnL8Y5FvGjLcTjaeUdncaLH4mjnEH/84x87NG+kHO84HO88wOPxYLfbOzq2nKS2/F3fe++9XHPNNdx4440ADB8+nPr6eqZPn87dd98dU19ytuXv+Gh/E7HaLp7Me9ijjz7KI488wgcffBDTEw+e6L7v2rWLvXv3ctlll4UfCwaDQOgK3+3bt9O/f/+OC94O2vL/npubi9PpbPFePnToUEpKSvB6vbhcrg7L3R7asu+x8D5nfYJOwOVyMXr0aBYtWhR+LBgMsmjRok415lUk9O3bl5ycnBbHrqamhpUrV4aPXUFBAVVVVaxZsya8zuLFiwkGg4wbN67DM3c00zSZOXMmb7zxBosXL6Zv374tlo8ePRqn09niGG7fvp3CwsIWx3Djxo0tit8LFy4kLS2tU13id6KCwSAej0fH7gRcdNFFbNy4kfXr14dvY8aMYdq0aeGfdQwlkk6ljU1ISKBHjx74/X7+93//l8svv/yIdZKTk8nNzaWyspL33nuv1XViVUFBQYvjBqG/vebjFk/nL8c7FvHiRI7D8c47OouT/Z1oPofoLI53HI53HqCCbWw4mb/rhoaGIwoWzf/fpmlGJGdHOdbfcWdvL473Hvab3/yGhx9+mAULFrSYU6YzONq+Dxky5Ij3ue9973tccMEFrF+/nvz8fAvStq9j/b+fffbZ7Ny5M1yoBvjiiy/Izc2NuYJta4617zHxPmfdHGidy8svv2y63W5z3rx55pYtW8zp06ebGRkZLWZLj1e1tbXmunXrzHXr1pmA+dhjj5nr1q0z9+3bZ5qmaT7yyCNmRkaG+dZbb5kbNmwwL7/8crNv375mY2NjeBsTJ040R40aZa5cudL85JNPzIEDB5pXX321VbvUoW655RYzPT3dXLJkiVlcXBy+NTQ0hNe5+eabzV69epmLFy82V69ebRYUFJgFBQXh5X6/3zz99NPNiy++2Fy/fr25YMECs3v37ubs2bOt2KUOddddd5kfffSRuWfPHnPDhg3mXXfdZRqGYb7//vumaerYnYxvzhqtYyiRdrw29pprrjHvuuuu8PorVqww//d//9fctWuXuXTpUvPCCy80+/bta1ZWVobXWbBggfmvf/3L3L17t/n++++bI0eONMeNGxfVM+cerz296667zGuuuSa8/u7du82kpCTzpz/9qbl161Zz7ty5pt1uNxcsWBBeJ1bPXyJxLI63zWgUieNwIucd0SgSx+J45xDRKBLH4Zu+eR4g0e9E/q6/2Zbef//9ZmpqqvnSSy+F28r+/fubU6dOtWIXTtrx/o6/ud/Lli0zHQ6H+eijj5pbt24177//ftPpdJobN260ahdOWlv3/ZFHHjFdLpf5P//zPy1+T2pra63ahZPW1n3/puuuu868/PLLOyht+2rrvhcWFpqpqanmzJkzze3bt5tvv/22mZWVZf7yl7+0ahdOWlv3PRbe51S0bUdPPfWU2atXL9PlcplnnnmmuWLFCqsjRYUPP/zQBI64XXfddaZpmmYwGDTvvfdeMzs723S73eZFF11kbt++vcU2ysvLzauvvtpMSUkx09LSzB/84Acx2XicjNaOHWC+8MIL4XUaGxvNW2+91ezSpYuZlJRkfv/73zeLi4tbbGfv3r3mpEmTzMTERLNbt27mT37yE9Pn83Xw3nS8H/7wh2bv3r1Nl8tldu/e3bzoootafNjSsWu7b35Y0zGUjnCsNva8884LtymmaZpLliwxhw4darrdbrNr167mNddcYx48eLDF9l555RWzX79+psvlMnNycswZM2aYVVVVHbU7J+V47el1111nnnfeeUc854wzzjBdLpfZr1+/Fm1Hs1g8f4nEsTjeNqNRJI7DiZx3RKNIHIvjnUNEo0i9T3ydirax50T+rr/Zlvp8PvOBBx4w+/fvbyYkJJj5+fnmrbfe2uIL0FhwvL/jb+63aZrmq6++ag4aNMh0uVzmsGHDzHfeeaeDU7ePtu577969W/09uf/++zs+/Ck6mf/3r4vlou3J7Punn35qjhs3znS73Wa/fv3M//7v/zb9fn8HJz91bd33WHifM0wzWvr8ioiIiIiIiIiIiIjGtBURERERERERERGJIiraioiIiIiIiIiIiEQRFW1FREREREREREREooiKtiIiIiIiIiIiIiJRREVbERERERERERERkSiioq2IiIiIiIiIiIhIFFHRVkRERERERERERCSKqGgrIiIiIiIiIiIiEkVUtBWJItdffz2TJ0+O2PYfeOABzjjjjCMey87OxjAM3nzzzYi9drPzzz+f22+/PXy/T58+PP744+22/RM5ht/MICIi8aMj24DW2l0RERERkROhoq3IMZzsB7tYKQpu3bqVBx98kD/+8Y8UFxczadKkDs+watUqpk+f3m7be+KJJ5g3b167bU9ERORk3XnnnSxatCh8P9JfzoqIiESLo30mnjdvHhkZGR2eRyQWOawOICLW2bVrFwCXX345hmGc9Ha8Xi8ul+ukntu9e/eTft3WpKent+v2RERETlZKSgopKSlWxxARERGRGKSetiJHcf311/PRRx/xxBNPYBgGhmGwd+9eAD766CPOPPNM3G43ubm53HXXXfj9/mM+LxAIcMMNN9C3b18SExMZPHgwTzzxRJsy7du3j8suu4wuXbqQnJzMsGHDePfdd4HWv7F88803j1qMfeCBB7jssssAsNls4fVa+0Z08uTJXH/99eH7ffr04eGHH+baa68lLS3tqD1l6+vrufbaa0lJSSE3N5ff/e53R6zzzeERCgsLufzyy0lJSSEtLY2pU6dSWloKwLZt20hKSmL+/Pnh9V999VUSExPZsmULcGQvphPJ4PF4uPPOO+nRowfJycmMGzeOJUuWtLpPIiISO47XBhzv/b+5bX3vvfcYOnQoKSkpTJw4keLi4vA6S5Ys4cwzzyQ5OZmMjAzOPvts9u3bB7QcHuGBBx7gxRdf5K233gqfHyxZsoQLL7yQmTNntsh16NAhXC5Xi166IiIi0eT8889n5syZzJw5k/T0dLp168a9996LaZpWRxPpNFS0FTmKJ554goKCAm666SaKi4spLi4mPz+fgwcPcskllzB27Fg+//xznnnmGZ5//nl++ctfHvN5wWCQnj178tprr7Flyxbuu+8+fvGLX/Dqq6+ecKYZM2bg8XhYunQpGzdu5Ne//vVJ9+C58847eeGFFwDCOdvi0UcfZeTIkaxbt45777231XV++tOf8tFHH/HWW2/x/vvvs2TJEtauXXvUbQaDQS6//HIqKir46KOPWLhwIbt37+bKK68EYMiQITz66KPceuutFBYWcuDAAW6++WZ+/etfc9ppp510hpkzZ7J8+XJefvllNmzYwH/8x38wceJEduzY0aZjIiIi0eV4bcCJvP83NDTw6KOP8re//Y2lS5dSWFjInXfeCYDf72fy5Mmcd955bNiwgeXLlzN9+vRWvzC98847mTp1arjoW1xczLe//W1uvPFG5s+fj8fjCa/797//nR49enDhhRdG8OiIiIicmhdffBGHw8Fnn33GE088wWOPPcaf//xnq2OJdBoaHkHkKNLT03G5XCQlJZGTkxN+/OmnnyY/P58//OEPGIbBkCFDKCoq4uc//zn33XffUZ9nt9t58MEHw/f79u3L8uXLefXVV5k6deoJZSosLGTKlCkMHz4cgH79+p30/qWkpIR75n4954m68MIL+clPfnLU5XV1dTz//PP8/e9/56KLLgJCjXrPnj2P+pxFixaxceNG9uzZQ35+PgB//etfGTZsGKtWrWLs2LHceuutvPvuu/znf/4nLpeLsWPHctttt510hsLCQl544QUKCwvJy8sDQh+sFyxYwAsvvMCvfvWrth0YERGJCsdrA070/d/n8/Hss8/Sv39/IFTofeihhwCoqamhurqaf/u3fwsvHzp0aKt5UlJSSExMxOPxtGh3r7jiCmbOnMlbb70VPh+YN28e119//SkNXSQiIhJp+fn5/P73v8cwDAYPHszGjRv5/e9/z0033QSEPjt/s4jr9/tJSEiwIq5IzFHRVqSNtm7dSkFBQYsPUmeffTZ1dXUcOHCAXr16HfW5c+fO5S9/+QuFhYU0Njbi9XrbNKv0f/3Xf3HLLbfw/vvvM378eKZMmcKIESNOZXdO2pgxY465fNeuXXi9XsaNGxd+LDMzk8GDBx/1OVu3brpwnkYAAKdySURBVCU/Pz9csAU47bTTyMjIYOvWrYwdOxaAv/zlLwwaNAibzcbmzZuP+qH2RDJs3LiRQCDAoEGDWjzX4/HQtWvXY+6jiIhEr+O1ASf6/p+UlBQuyALk5uZSVlYW3t7111/PhAkT+O53v8v48eOZOnUqubm5J5wzISGBa665hr/85S9MnTqVtWvXsmnTJv7v//7vpPZbRESko5x11lktPosVFBTwu9/9jkAgAMC0adO4++67Wzzn9ddfV8cYkROkoq1IB3n55Ze58847+d3vfkdBQQGpqan89re/ZeXKlSe8jRtvvJEJEybwzjvv8P777zNnzhx+97vfcdttt2Gz2Y4YP8jn87U554luJzk5uc3bbi+ff/459fX12Gw2iouL2/Th+Jvq6uqw2+2sWbMGu93eYpkmjxER6bxO9P3f6XS2WGYYRot28oUXXuC//uu/WLBgAa+88gr33HMPCxcu5KyzzjrhLDfeeCNnnHEGBw4c4IUXXuDCCy+kd+/eJ7lnIiIi0SE9PZ0BAwa0eCwrK8uiNCKxR2PaihyDy+UKf0vYbOjQoSxfvrzFB7Zly5aRmpoavuSytectW7aMb3/729x6662MGjWKAQMGsGvXrjZnys/P5+abb+b111/nJz/5Cc899xwA3bt3p7a2lvr6+vC669evb/P2u3fv3mJ820AgwKZNm9q8nf79++N0OlsUpSsrK/niiy+O+pyhQ4eyf/9+9u/fH35sy5YtVFVVhcesraio4Prrr+fuu+/m+uuvZ9q0aTQ2Np50hlGjRhEIBCgrK2PAgAEtbiczbISIiESH47UB7fn+P2rUKGbPns2nn37K6aef3mLCzK9r7fwAYPjw4YwZM4bnnnuO+fPn88Mf/rBNry8iImKFb3ZAWrFiBQMHDjziy1AROTkq2oocQ58+fVi5ciV79+7l8OHDBINBbr31Vvbv389tt93Gtm3beOutt7j//vuZNWsWNpvtqM8bOHAgq1ev5r333uOLL77g3nvvZdWqVW3Kc/vtt/Pee++xZ88e1q5dy4cffhgeO2/cuHEkJSXxi1/8gl27djF//nzmzZvX5n2+8MILeeedd3jnnXfYtm0bt9xyC1VVVW3eTkpKCjfccAM//elPWbx4MZs2beL6668PH6PWjB8/nuHDhzNt2jTWrl3LZ599xrXXXst5550XHo7h5ptvJj8/n3vuuYfHHnuMQCAQnhDmZDIMGjSIadOmce211/L666+zZ88ePvvsM+bMmcM777zT5v0WEZHocLw2oD3e//fs2cPs2bNZvnw5+/bt4/3332fHjh1HHde2T58+bNiwge3bt3P48OEWV7LceOONPPLII5imyfe///1TPwAiIiIRVlhYyKxZs9i+fTsvvfQSTz31FD/+8Y+tjiXSaahoK3IMd955J3a7ndNOO43u3btTWFhIjx49ePfdd/nss88YOXIkN998MzfccAP33HPPMZ/3ox/9iCuuuIIrr7yScePGUV5ezq233tqmPIFAgBkzZjB06FAmTpzIoEGDePrpp4HQuHp///vfeffddxk+fDgvvfQSDzzwQJv3+Yc//CHXXXdduFjar18/LrjggjZvB+C3v/0t5557Lpdddhnjx4/nnHPOYfTo0Udd3zAM3nrrLbp06cJ3vvMdxo8fT79+/XjllVeA0KRk7777Ln/7299wOBwkJyfz97//neeee45//etfJ53hhRde4Nprr+UnP/kJgwcPZvLkyaxateqY4xOLiEj0O14bcKrv/0lJSWzbto0pU6YwaNAgpk+fzowZM/jRj37U6vo33XQTgwcPZsyYMXTv3p1ly5aFl1199dU4HA6uvvpqTdAiIiIx4dprr6WxsZEzzzyTGTNm8OMf/5jp06dbHUuk0zDMbw5eKSIiIiIiHWrv3r3079+fVatW8a1vfcvqOCIiIsd0/vnnc8YZZ/D4449bHUWk09JEZCIiIiIiFvH5fJSXl3PPPfdw1llnqWArIiIiIoCGRxARERERscyyZcvIzc1l1apVPPvss1bHEREREZEooeERRERERERERERERKKIetqKiIiIiIiIiIiIRBEVbUVERERERERERESiiIq2IiIiIiIiIiIiIlFERVsRERERERERERGRKKKirYiIiIiIiIiIiEgUUdFWREREREREREREJIqoaCsiIiIiIiIiIiISRVS0FREREREREREREYkiKtqKiIiIiIiIiIiIRBEVbUVERERERERERESiiIq2IiIiIiIiIiIiIlFERVsRERERERERERGRKKKirYiIiIiIiIiIiEgUUdFWREREREREREREJIqoaCsiIiIiIiIiIiISRVS0FRERERERkU5v6dKlXHbZZeTl5WEYBm+++eZxn7NkyRK+9a1v4Xa7GTBgAPPmzYt4ThEREVDRVkREREREROJAfX09I0eOZO7cuSe0/p49e7j00ku54IILWL9+Pbfffjs33ngj7733XoSTioiIgGGapml1CBEREREREZGOYhgGb7zxBpMnTz7qOj//+c9555132LRpU/ixq666iqqqKhYsWNABKUVEJJ45rA4QC4LBIEVFRaSmpmIYhtVxREQkQkzTpLa2lry8PGw2XYxyotROiojEh3hrJ5cvX8748eNbPDZhwgRuv/32oz7H4/Hg8XjC94PBIBUVFXTt2lVtpIhIJxaJNlJF2xNQVFREfn6+1TFERKSD7N+/n549e1odI2aonRQRiS/x0k6WlJSQnZ3d4rHs7GxqampobGwkMTHxiOfMmTOHBx98sKMiiohIlGnPNlJF2xOQmpoKhA58WlqaxWlERCRSampqyM/PD7/vy4lROykiEh/UTh7f7NmzmTVrVvh+dXU1vXr1UhspItLJRaKNVNH2BDRfxpKWlqaGVkQkDujyxbZROykiEl/ipZ3MycmhtLS0xWOlpaWkpaW12ssWwO1243a7j3hcbaSISHxozzay8w9EJCIiIiIiItJGBQUFLFq0qMVjCxcupKCgwKJEIiIST1S0FRERERERkU6vrq6O9evXs379egD27NnD+vXrKSwsBEJDG1x77bXh9W+++WZ2797Nz372M7Zt28bTTz/Nq6++yh133GFFfBERiTMq2oqIiIiIiEint3r1akaNGsWoUaMAmDVrFqNGjeK+++4D4P+zd9/xWdXn/8df9868E7ITSNhTdlhxVQFBxAmt1aJQSrWloFWsVVq1Vav4tXXUFrVaV6v8sLZqFRFEFBwMJRjZyA6QDdnj3r8/AneNEGaScyd5Px+P83hwn88Z11H03Oe6r3N98vPzgwlcgK5du/Lee++xbNkyBg0axGOPPcbf//53xo8fb0j8IiLSvqinrYiIiIiIiLR5F110EYFAoNHxl19++bj7fPXVV80YlYiIyPGp0lZEREREREREREQkhChpKyIiIiIiIiIiIhJClLQVERERERERERERCSFK2oqIiIiIiIiIiIiEkFaVtH3kkUcwmUzcdtttwXV1dXXMmjWL+Ph4oqKimDx5MoWFhQ32y83NZeLEiURERJCUlMSdd96J1+tt4ehFRERERERERERETs5qdACn6ssvv+Rvf/sbAwcObLD+9ttv57333uONN94gJiaG2bNnM2nSJD7//HMAfD4fEydOJCUlhVWrVpGfn8/UqVOx2Ww8/PDDRlyKiIiIyBnz+Xz4/f5T3t5sNmOxWJoxIhERERERaWqtImlbVVXFlClTeP755/nDH/4QXF9eXs4LL7zAggULGD16NAAvvfQSffv2Zc2aNYwaNYoPPviALVu28OGHH5KcnMzgwYN58MEHueuuu/j973+P3W436rKkmd1691yKq6qPWZ8YFclTj8wzICIREZGz4/P5SM/oTH7ewVPeJzWtI/tz9ylxKyIiIiLSirSKpO2sWbOYOHEiY8eObZC0zc7OxuPxMHbs2OC6Pn36kJGRwerVqxk1ahSrV69mwIABJCcnB7cZP348M2fOZPPmzQwZMuSY87lcLlwuV/BzRUVFM12ZNKfiqmqG3jH3mPXrH1PCVkREWie/309+3kEeeScHi/XkX+N8Xi93XzkYv9+vpK2IiIiISCsS8knbhQsXsn79er788stjxgoKCrDb7cTGxjZYn5ycTEFBQXCbbydsj44fHTueefPmcf/99zdB9CIiIiJNz2K1YrHajA5DRERERESaSUhPRLZ//35++ctf8tprrxEWFtZi5507dy7l5eXBZf/+/S12bhEREREREREREWnfQjppm52dTVFREUOHDsVqtWK1Wlm5ciVPPfUUVquV5ORk3G43ZWVlDfYrLCwkJSUFgJSUFAoLC48ZPzp2PA6HA6fT2WARERERERERERERaQkhnbQdM2YMGzduJCcnJ7gMGzaMKVOmBP9ss9lYvnx5cJ/t27eTm5tLVlYWAFlZWWzcuJGioqLgNsuWLcPpdNKvX78WvyYRERERERERERGREwnpnrbR0dH079+/wbrIyEji4+OD62fMmMGcOXOIi4vD6XRyyy23kJWVxahRowAYN24c/fr148Ybb+TRRx+loKCAe+65h1mzZuFwOFr8mkREREREREREREROJKSTtqfiiSeewGw2M3nyZFwuF+PHj+fpp58OjlssFhYtWsTMmTPJysoiMjKSadOm8cADDxgYtYiIiIiIiIiIiMjxtbqk7YoVKxp8DgsLY/78+cyfP7/RfTp37szixYubOTIRERERERERERGRsxfSPW1FRERERERERERE2ptWV2krYoRb755LcVX1cccSoyJ56pF5LRyRiIiIiIiIiIi0VUraipyC4qpqht4x97hj6x9TwlZERERERERERJqO2iOIiIiIiIiIiIiIhBAlbUVERERERERERERCiJK2IiIiIiIiIiIiIiFESVsRERERERERERGREKKkrYiIiIiIiIiIiEgIUdJWREREREREREREJIQoaSsiIiIiIiIiIiISQpS0FREREREREREREQkhVqMDEBEREWkrfD4ffr//tPYxm81YLJZmikhERERERFojJW1FREREmoDP5yM9ozP5eQdPa7/UtI7sz92nxK2IiIiIiAQpaSsiIiLSBPx+P/l5B3nknRws1lP7iuXzern7ysH4/X4lbUVEREREJEhJWxEREZEmZLFasVhtRochIiIiIiKtmCYiExEREREREREREQkhStqKiIiIiIiIiIiIhBAlbUVERERERERERERCiHraioiIiMhZ8fl8+P3+U97ebDZr4jURERERkRNQ0lZEREREzpjP5yM9ozP5eQdPeZ/UtI7sz92nxK2IiIiISCOUtBURERGRM+b3+8nPO8gj7+RgsZ78q6XP6+XuKwfj9/uVtBURERERaYSStiIiIiJy1ixWKxarzegwRERERETaBE1EJiIi0gY88sgjmEwmbrvttuC6uro6Zs2aRXx8PFFRUUyePJnCwsIG++Xm5jJx4kQiIiJISkrizjvvxOv1tnD0IiIiIiIi8m0hnbR95plnGDhwIE6nE6fTSVZWFu+//35w/KKLLsJkMjVYfv7znzc4hh5GRUSkrfvyyy/529/+xsCBAxusv/3223n33Xd54403WLlyJXl5eUyaNCk47vP5mDhxIm63m1WrVvHKK6/w8ssvc99997X0JYiIiIiIiMi3hHTStlOnTjzyyCNkZ2ezbt06Ro8ezVVXXcXmzZuD29x0003k5+cHl0cffTQ4podRERFp66qqqpgyZQrPP/88HTp0CK4vLy/nhRde4PHHH2f06NFkZmby0ksvsWrVKtasWQPABx98wJYtW3j11VcZPHgwEyZM4MEHH2T+/Pm43W6jLklERERERKTdC+mk7RVXXMFll11Gz5496dWrFw899BBRUVHBh02AiIgIUlJSgovT6QyO6WFURETaulmzZjFx4kTGjh3bYH12djYej6fB+j59+pCRkcHq1asBWL16NQMGDCA5OTm4zfjx46moqGjwA+l3uVwuKioqGiwiIiIiIiLSdEI6afttPp+PhQsXUl1dTVZWVnD9a6+9RkJCAv3792fu3LnU1NQEx/QwKiIibdnChQtZv3498+bNO2asoKAAu91ObGxsg/XJyckUFBQEt/n2PfLo+NGxxsybN4+YmJjgkp6efpZXIiIiIiIiIt9mNTqAk9m4cSNZWVnU1dURFRXFW2+9Rb9+/QD40Y9+ROfOnUlLS2PDhg3cddddbN++nTfffBM4u4fR+++/v5muSERE5Ozt37+fX/7ylyxbtoywsLAWPffcuXOZM2dO8HNFRYUStyIiIiIiIk0o5JO2vXv3Jicnh/Lycv79738zbdo0Vq5cSb9+/bj55puD2w0YMIDU1FTGjBnDrl276N69+xmfUw+jIiIS6rKzsykqKmLo0KHBdT6fj08++YS//vWvLF26FLfbTVlZWYNq28LCQlJSUgBISUnhiy++aHDcwsLC4FhjHA4HDoejCa9GREREREREvi3k2yPY7XZ69OhBZmYm8+bNY9CgQfz5z38+7rYjR44EYOfOnUD9A+fRh8+jTvVh1Ol0NlhERERCyZgxY9i4cSM5OTnBZdiwYUyZMiX4Z5vNxvLly4P7bN++ndzc3GCboaysLDZu3EhRUVFwm2XLluF0OoNvtYiIiIiIiEjLC/lK2+/y+/24XK7jjuXk5ACQmpoK1D+MPvTQQxQVFZGUlAToYVRO7Na751JcVX3M+q82bGDocbYXETFKdHQ0/fv3b7AuMjKS+Pj44PoZM2YwZ84c4uLicDqd3HLLLWRlZTFq1CgAxo0bR79+/bjxxht59NFHKSgo4J577mHWrFmqpBURkTZp/vz5/PGPf6SgoIBBgwbxl7/8hREjRjS6/ZNPPskzzzxDbm4uCQkJfP/732fevHkt3ppIRETan5BO2s6dO5cJEyaQkZFBZWUlCxYsYMWKFSxdupRdu3axYMECLrvsMuLj49mwYQO33347F154IQMHDgT0MGqkxpKfAIlRkTz1yLGT5oSC4qpqht4x95j1a6Zca0A0IiJn54knnsBsNjN58mRcLhfjx4/n6aefDo5bLBYWLVrEzJkzycrKIjIykmnTpvHAAw8YGLWIiEjzeP3115kzZw7PPvssI0eO5Mknn2T8+PFs3749WOTzbQsWLODuu+/mxRdf5Nxzz+Wbb77hxz/+MSaTiccff9yAKxARkfYkpJO2RUVFTJ06lfz8fGJiYhg4cCBLly7lkksuYf/+/Xz44Yc8+eSTVFdXk56ezuTJk7nnnnuC++th1DiNJT8B1j92+gnbxpLAoZwAFhFpaStWrGjwOSwsjPnz5zN//vxG9+ncuTOLFy9u5shERESM9/jjj3PTTTcxffp0AJ599lnee+89XnzxRe6+++5jtl+1ahXnnXceP/rRjwDo0qUL119/PWvXrm3RuEVEpH0K6aTtCy+80OhYeno6K1euPOkx9DDaNjSWBD6TBLCIiIiIiLQvbreb7Oxs5s793zOF2Wxm7NixrF69+rj7nHvuubz66qt88cUXjBgxgt27d7N48WJuvPHGRs/jcrkatPOrqKhouosQEZF2JaSTtiIiIiLyP5/vOkTSD+7nH2sP4PMH6JIQSf+0GFJi1FtRRORESkpK8Pl8JCcnN1ifnJzMtm3bjrvPj370I0pKSjj//PMJBAJ4vV5+/vOf85vf/KbR88ybN4/777+/SWMXEZH2yWx0ACIiIiJyYrVuH7NeW8+PX84mvFsmFXVeqt0+NudV8Pq6/Xy59zCBQMDoMEVE2pQVK1bw8MMP8/TTT7N+/XrefPNN3nvvPR588MFG95k7dy7l5eXBZf/+/S0YsYiItCWqtBUREREJYXUeHzf/cx2f7ijBYjZR+sV/+fGMmwmYLWw+WM43RVWs2nWIiloPo/skYTKZjA5ZRCTkJCQkYLFYKCwsbLC+sLCQlJSU4+5z7733cuONN/LTn/4UgAEDBlBdXc3NN9/Mb3/7W8zmY2ugHA6HJr0WEZEmoUpbERERkRAVCAS4/fUcPt1RQoTdwqs/GUbp8udIiw0jIy6CCQNSubh3IiYTbMqrYMOBcqNDFhEJSXa7nczMTJYvXx5c5/f7Wb58OVlZWcfdp6am5pjErMViAdDbDSIi0uxUaSsiIiISot7IPsD7mwqwW8z8fdowhmXEHLPNwE6xeP0BPt1Rwic7ikmMdpAWG25AtCIioW3OnDlMmzaNYcOGMWLECJ588kmqq6uZPn06AFOnTqVjx47Mm1c/2fEVV1zB448/zpAhQxg5ciQ7d+7k3nvv5Yorrggmb0VERJqLkrYiIiIiIehAaQ0PvLsFgDnjenFu9wQ8Hs9xtx2SHktheR3fFFWxfGsRPxqZgcWsNgkiIt/2wx/+kOLiYu677z4KCgoYPHgwS5YsCU5Olpub26Cy9p577sFkMnHPPfdw8OBBEhMTueKKK3jooYeMugQREWlHlLQVERERCUEPvLuFKpeXoRmx3HRBtxNuazKZGN0nif2ltRyucZOzv4zMzh1aKFIRkdZj9uzZzJ49+7hjK1asaPDZarXyu9/9jt/97nctEJmIiEhD6mkrIiIiEmLW55bywZZCzCb4v8kDT6lq1mGzcH6PBADW7jlElcvb3GGKiIiIiEgzUdJWREREJIQEAgH+7/1tAHw/sxM9k6NPed++qdGkxoTh8QVYt/dwc4UoIiIiIiLNTElbERERkRDy+c5DrN1zGLvVzC/H9jqtfU0mE1nd4gHYlFehalsRERERkVZKSVsRERGREPLcp7sB+NGIDDrGhp/2/p06hJMWE4bPH+Cr/eVNHZ6IiIiIiLQAJW1FREREQsSOwko++aYYkwl+cl7XMzqGyWRi5NFq2/wqzOHOpgxRRERERERagJK2IiIiIiHixc/3ADCuXzIZ8RFnfJz0DuEkOx34/AGiB09oqvBERERERKSFKGkrIiIiEgLKaty8uf4gADPO73ZWxzKZTAxOjwUgashluL3+sw1PRERERERakJK2IiIiIiHgvzl5uLx++qY6Gd6lw1kfr2dSNBF2C9boeN7fXNgEEYqIiIiISEtR0lZEREQkBLyRvR+Aa4d1wmQynfXxLGYTA9KiAfjHmn1nfTwREREREWk5StqKiIiIGGxbQSWbDlZgs5i4anDHJjvuOanRBHweNhyoYGt+RZMdV0REREREmpeStiIiIiIG+8+RXrZj+yYTF2lvsuNG2C3U7FgLwMIvcpvsuCIiIiIi0ryUtBURERExksnMuxsKAPjBsE5NfviqDR8A8NZXB6nz+Jr8+CIiIiIi0vSUtJU2r8zjZWNlLavKqviyvJqS1HSqvHpoFRGR0OBIP4dD1W5iI2xc0DOxyY9ft+crOsaGUVHnZfHG/CY/voiIiIiIND0lbaXNqoly8mZhKS8cPMQHhypYXVbNJ6VVbDz3Evp+tombN+/lq4oao8MUEZF2LrLPhQBcek4KNktzfDUL8P2h9X1yF36xvxmOLyIiIiIiTc1qdAAiR91691yKq6qPO/bVhg0MPY1jvVVYyheXXEOg1o0JSHXYiLdZ8QQC7C0soi7KyTtFZbxTVMbExBju655G53BHk1yHiIjIqfIHAkT0PheAiQNTm+08k4d25C8f7+KLvYfZVVxF98SoZjuXiIiIiIicvZCutH3mmWcYOHAgTqcTp9NJVlYW77//fnC8rq6OWbNmER8fT1RUFJMnT6awsLDBMXJzc5k4cSIREREkJSVx55134vV6W/pS5BQUV1Uz9I65x11cp9HO4JWDJfxiyz4CZgtdwuz8uGM816fGMS7BycTEGLKW/psPh/Xi+8kdMAPvFZfzvS+28fz+YgLNd3kiIiLHOFhWhyUihg4RNrK6xTfbeVJjwri4dxIAr3+palsRERERkVAX0knbTp068cgjj5Cdnc26desYPXo0V111FZs3bwbg9ttv59133+WNN95g5cqV5OXlMWnSpOD+Pp+PiRMn4na7WbVqFa+88govv/wy9913n1GXJM1saUk5d31zgADQcdcWJiXHEmc7tqC8f3QEf+3XmeXDe3NebBR1/gD37jzI1+ePp8bnb/nARUSkXdpZXP+Gybh+SVibpTXC/1w3IgOA/2QfwO3VvU5EREREJJSFdNL2iiuu4LLLLqNnz5706tWLhx56iKioKNasWUN5eTkvvPACjz/+OKNHjyYzM5OXXnqJVatWsWbNGgA++OADtmzZwquvvsrgwYOZMGECDz74IPPnz8ftdht8ddLUdtbUMXvLPgB+3DGBnjlrMJlMJ9ynb1Q4/x7cnf/r1Ylws5nS5I68ln+IEreqsUVEpHkFAgH2HqoFYFy/5GY/38W9E0l2OjhU7WbZlsKT7yAiIiIiIoZpNT1tfT4fb7zxBtXV1WRlZZGdnY3H42Hs2LHBbfr06UNGRgarV69m1KhRrF69mgEDBpCc/L8HofHjxzNz5kw2b97MkCFDjnsul8uFy+UKfq6oqGi+C5Mm4fb7uXnTXip9fkbFRPJgj45MPcV9TSYT0zomMCImkgkff0lFlJPXCw7z/eQOJDtsZxVXY316E6MieeqReWd1bBERad2KKl1Uu3343bWM7NKh2c9ntZj5fmYn5n+8i9fX7W/WHroiIiIiInJ2Qj5pu3HjRrKysqirqyMqKoq33nqLfv36kZOTg91uJzY2tsH2ycnJFBQUAFBQUNAgYXt0/OhYY+bNm8f999/ftBcizeqvuUVsqa4jzmbhb+d0wWY+cYXt8fSNCmfYR++w6/vTyXd7eKOglGtTO5BkP/PE7dE+vd+1/jElbEVE2rs9JfU/6tXuWY/DdlWLnPPaYenM/3gXn+4o5mBZLR1jw1vkvCIiIiIicnpCuj0CQO/evcnJyWHt2rXMnDmTadOmsWXLlmY959y5cykvLw8u+/drwo5Qtr26jif21r/m+Yeenc6qOtbmcTM5JZY0hw1XIMDbhWVU+059EjQREZFTFUza7vyixc7ZOT6SrG7xBALwxjp9vxERERERCVUhn7S12+306NGDzMxM5s2bx6BBg/jzn/9MSkoKbrebsrKyBtsXFhaSkpICQEpKCoWFhceMHx1rjMPhwOl0NlgkNAWA33xzAE8gwCXxTq5Jij3rYzrMZq5JiqWD1UKlz887ReUEzCH/n4qIiLQilXUeiirrWzHV7l7Xoue+bkQ6AG+sO4DPH2jRc4uIiIiIyKlpdZkov9+Py+UiMzMTm83G8uXLg2Pbt28nNzeXrKwsALKysti4cSNFRUXBbZYtW4bT6aRfv34tHrs0vZLUDD4vq8JhNvFwr04nnXjsVIVZzFydHIvDZCLP5cF74SVNclwRERGAfYdqAEhxOvDXlLfoucefk4IzzMrBslo+31nSoucWEREREZFTE9JJ27lz5/LJJ5+wd+9eNm7cyNy5c1mxYgVTpkwhJiaGGTNmMGfOHD7++GOys7OZPn06WVlZjBo1CoBx48bRr18/brzxRr7++muWLl3KPffcw6xZs3A4HAZfnZwtXyDAroHDAfh5ehLpYfYmPX6czcro+GgAvBdfSrHb06THFxGR9uto0jajQ8v3lA2zWbhmSEcAXv9SLRJEREREREJRSE9EVlRUxNSpU8nPzycmJoaBAweydOlSLrmkvurxiSeewGw2M3nyZFwuF+PHj+fpp58O7m+xWFi0aBEzZ84kKyuLyMhIpk2bxgMPPGDUJUkT+qqihtqoGJLsVm7JSGqWc/SNDOObahe7auGDkgp+lBrXZNW8IiLSPvn9AfaXHknaxtUnbT2eU/th8FS3O5lrh6fzyup9fLClgMPVbuIim/aHTxEREREROTshnbR94YUXTjgeFhbG/PnzmT9/fqPbdO7cmcWLFzd1aGKwGp+fNWX1E7jc3TWVKKulWc5jMpkYGx/Nrl3lFBDG9hoXfSLDmuVcIiLSPhRW1uHy+nFYzSREWMBkJjIy8rSOEQj4zyqGc9JiGNAxho0Hy3lz/QF+ekG3szqeiIiIiIg0rZBO2oo0ZlVZFa5AgKiyQ/wwdVCznivKasH66XK8YyfyWWkVPSMcWFRtKyIiZyjYGiEuAhMBCPh5+O1sbPaTt25y19Xy20nDCQTOfgKxa4ens/FgOf/vi1xmnN9Vb5KIiIiIiISQkO5pK3I8JW4vGyprAejx9doWSaBaP/+ISIuZcq8veG4REZEzkXv4SNI2PiK4zmK1YrHaTmFput/brx6cRqTdwq7ialbvOtRkxxURERERkbOnpK20KoFAgI8PVxIAekY46FBS0CLnNbndjIqpf3X1y/JqfE1Q4SQiIu2Py+ujoLwOqK+0NVJ0mI1rhtZPSPbPNfsMjUVERERERBpS0lZalZ01LnLr3FiA73WIbtFz948KJ8JsptLn55vquhY9t4iItA0HS2sJALERNpxhNqPD4cZRXQD4YEsh+eV6k0REREREJFQoaSuthscfYEVpJQDDYyKJsTXP5GONsZpNDHHWz/L9ZXlNk/QTFBGR9mV/aX1itFOHcIMjqdc7JZoRXePw+QO8tibX6HBEREREROQIJW2l1ciuqKbC6yfKYmZEzOnNst1UBkVHYDOZKPZ4ya1zGxKDiIi0XgdK6/vZpncwtjXCt00/twsAr67dR43ba2wwIiIiIiICKGkrrUTAGcva8mqgvi2CzWzMDNfhFjP9osIANCGZiIicllqPj5Kq+h/8OsaGRqUtwLhzUsiIi6CsxsO/sw8YHY6IiIiIiKCkrbQCgUAA91XX4g1AR4eN3pEOQ+MZGF3/oL2zxkW1z2doLCIi0nocPNIaIS7STqTDanA0/2Mxm/jpBV0BeOGzPfj8av8jIiIiImI0JW0l5G2uqsPfZwAWYGy8E5PJmCrbo5LsNlLtNvzApkpNSCYiIqfmaGuEUOln+23fz+xEbISNfYdqeG9jvtHhiIiIiIi0e0raSkgr9/j4+HD95GPndogiwR4alUlHq203VtXPAi4iInIyB0JsErJvi7Bb+cl59dW2f/7wG1XbioiIiIgYTElbCVkef4D/FpfhDgQw79vNMGfoTNrSOzIMu8lEuddHeXyy0eGIiEiIq/P4OFQdev1sv236eV2ICbexq7iad7/OMzocEREREZF2TUlbCUmBQIBlhyoodnsJN5uwvf4SZoPbInybzWyi55HeugWdexgcjYiIhLq8svoq2w4RNiJC5K2R74oOs3HTkd62f16+A4/Pb3BEIiIiIiLtl5K2EnICgQArSqvYWl2HCbg8MRZzeZnRYR2jX2R9pVRxxy7U6cFWREROIK+svgd6WohW2R714/O6Eh9pZ09JNf9Yvc/ocERERERE2i0lbSXkrCqrZn1F/WQt4+KdZITbDY7o+NLDbERZzHjtDj48VGF0OCIiEsLyyusrbUM9aRvlsPKr8b0BePLDbzhU5TI4IhERERGR9klJWwkpX5ZXs6a8GoDRcdH0jw7dh1uTyUTfyDAA/lNYanA0ItIePfPMMwwcOBCn04nT6SQrK4v3338/OF5XV8esWbOIj48nKiqKyZMnU1hY2OAYubm5TJw4kYiICJKSkrjzzjvxer0tfSltmtfnp7CivtI2VPvZftu1w9Lpl+qkss7L/y3ZZnQ4IiIiIiLtkpK2EjIOduvDJ6VVAJwfG8WQEJp4rDF9o+qTth8drqDK6zM4GhFpbzp16sQjjzxCdnY269atY/To0Vx11VVs3rwZgNtvv513332XN954g5UrV5KXl8ekSZOC+/t8PiZOnIjb7WbVqlW88sorvPzyy9x3331GXVKbVFBRhz8AkXYLzrDQ7Gf7bRazifuvOgeAf607wIrtRQZHJCIiIiLS/ihpKyHhXwWH+WbIuQCMjIlkZGykwRGdmgSblfDKclz+gFokiEiLu+KKK7jsssvo2bMnvXr14qGHHiIqKoo1a9ZQXl7OCy+8wOOPP87o0aPJzMzkpZdeYtWqVaxZswaADz74gC1btvDqq68yePBgJkyYwIMPPsj8+fNxu90GX13b8e1+tqYQmlTzRIZ3iePH53YB4O7/bKS81mNsQCIiIiIi7YyStmK4Tw5Xcvu2XACGRIdzXitJ2EJ9i4Skg3sBeLe4zNBYRKR98/l8LFy4kOrqarKyssjOzsbj8TB27NjgNn369CEjI4PVq1cDsHr1agYMGEBycnJwm/Hjx1NRURGs1j0el8tFRUVFg0Ual3+kn21qTJjBkZyeuy7tQ9eESAoq6rjjXzn4/QGjQxIRERERaTeUtBVD7at18bPNe/EFIHnfTi6Oi241VUhHJR7YA8BHhyqo9qlFgoi0rI0bNxIVFYXD4eDnP/85b731Fv369aOgoAC73U5sbGyD7ZOTkykoKACgoKCgQcL26PjRscbMmzePmJiY4JKent60F9WGBAIBCo70s02NCf1+tt8Wbrfw5+sGY7ea+XBrEU8u32F0SCIiIiIi7YaStmIYjz/AjE17KfX6GBIdQe/1n7e6hC1AVPlhOofZqfUHWH6o0uhwRKSd6d27Nzk5Oaxdu5aZM2cybdo0tmzZ0qznnDt3LuXl5cFl//79zXq+1qy81kOdx4/FZCIh2m50OKdtYKdY5l0zAICnlu9gwdpcgyMKLT6fD4/Hc8qLTz/uioiIiMgpUtJWDPPs/iI2VdUSZ7Pw4oAuWPyt80HGBFyeFAvAIrVIEJEWZrfb6dGjB5mZmcybN49Bgwbx5z//mZSUFNxuN2VlZQ22LywsJCUlBYCUlBQKCwuPGT861hiHw4HT6WywyPEdrbJNjHZgNbfOr12TMzvx8+91B+A3b23k9S+VuIX6hG16RmfsdvspL+kZnZW4FTHY/Pnz6dKlC2FhYYwcOZIvvvjihNuXlZUxa9YsUlNTcTgc9OrVi8WLF7dQtCIi0p6F/hTG0ibtrXXx2N76V2/v79GRVEfrqz76tssTY5mfW8SHhyqo8fmJsLTOB3MRaf38fj8ul4vMzExsNhvLly9n8uTJAGzfvp3c3FyysrIAyMrK4qGHHqKoqIikpCQAli1bhtPppF+/foZdQ1tSUF6ftE1xtq5+tt9116W9qfP4eHnVXu76z0b2H65lziW9MJtb3xsyTcXv95Ofd5BH3snBYj35V2qf18vdVw7G7/djsVhaIEIR+a7XX3+dOXPm8OyzzzJy5EiefPJJxo8fz/bt24P3wW9zu91ccsklJCUl8e9//5uOHTuyb9++Y1oPiYiINAclbcUQD+zMo84f4IIOUXw/uYPR4Zy1wdHhdAqzcaDOw4rDFVyWGGt0SCLSDsydO5cJEyaQkZFBZWUlCxYsYMWKFSxdupSYmBhmzJjBnDlziIuLw+l0csstt5CVlcWoUaMAGDduHP369ePGG2/k0UcfpaCggHvuuYdZs2bhcDgMvrq24WilbUorm4Tsu0wmE7+7oh/hdgvPrNjFXz/eyYaD5Tw6eSDxEe07AWmxWrFYbUaHISKn4PHHH+emm25i+vTpADz77LO89957vPjii9x9993HbP/iiy9y+PBhVq1ahc1W/995ly5dWjJkERFpx0K6HHDevHkMHz6c6OhokpKSuPrqq9m+fXuDbS666CJMJlOD5ec//3mDbXJzc5k4cSIREREkJSVx55134vV6W/JS5FuqnLEsLinHBPyhZ6dW2cf2u0wmE5cfSdQuKi43NhgRaTeKioqYOnUqvXv3ZsyYMXz55ZcsXbqUSy65BIAnnniCyy+/nMmTJ3PhhReSkpLCm2++GdzfYrGwaNEiLBYLWVlZ3HDDDUydOpUHHnjAqEtqU7w+P8WVLqD1J22h/l5316V9+NMPBuGwmvnkm2LGPbGSl1btA7PqAEQktLndbrKzsxk7dmxwndlsZuzYsaxevfq4+7zzzjtkZWUxa9YskpOT6d+/Pw8//PAJ25y4XC4qKioaLCIiImcipL9hr1y5klmzZjF8+HC8Xi+/+c1vGDduHFu2bCEyMjK43U033dTgATMiIiL4Z5/Px8SJE0lJSWHVqlXk5+czdepUbDYbDz/8cItej9Tb13sQABMTY+gd2fofYo+6IjGWZ/cX80FJOXU+P2FqkSAizeyFF1444XhYWBjz589n/vz5jW7TuXNn9eZrJsVVLvwBCLdZcIaF9Feu0/L9zE4MTo/hjn99zdcHynn4/e10vPlvfH2ggv6dOmC36v4nIqGnpKQEn89HcnJyg/XJycls27btuPvs3r2bjz76iClTprB48WJ27tzJL37xCzweD7/73e+Ou8+8efO4//77mzx+ERFpf0L6CWLJkiUNPr/88sskJSWRnZ3NhRdeGFwfERHR6IQpH3zwAVu2bOHDDz8kOTmZwYMH8+CDD3LXXXfx+9//Hrv92F6qLpcLl8sV/KxfR5tOqcdLUXpXAG7rnHySrVuXIc4I0hw28lwePimtZFxCjNEhiYiIgYL9bGPC2sRbJd/WIyma/8w8l39nH+CxD7ZTTDKf7jrM6j2ldE+MontSJBlxETis7bt1goi0bn6/n6SkJJ577jksFguZmZkcPHiQP/7xj40mbefOncucOXOCnysqKkhPT2+pkEVEpA0J6aTtd5WX1792HhcX12D9a6+9xquvvkpKSgpXXHEF9957b7DadvXq1QwYMKDBL6rjx49n5syZbN68mSFDhhxzHv062ny+rqwFk5kxcU76R0ecfIdWxGwyMT4hhpcOlrC0pFxJWxGRdq6tTELWGKvFzHUjMrjsnCQ6nj+J7lf/krJaL9sLK9leWAlAhwgbidEOkqLDiA6z4rCasZkD2OLT2ZxXgQ8TdR4/FbUeymo9lNV4KKt1U17jweX1AxDpsBAX6aBbQiR9U530So5qc0lwEWl+CQkJWCwWCgsLG6wvLCxstAAoNTUVm83WYPLAvn37UlBQgNvtPm4BkMPhUF94ERFpEq0maev3+7nttts477zz6N+/f3D9j370Izp37kxaWhobNmzgrrvuYvv27cGefQUFBcd9Bebo2PHo19Hm4QsE2FpV/wA7tWO8wdE0j0uPJG0/OFSBPxAwOhwRETFQW5mE7GTC7Raqct5nykOPUlLj55vCSvYcqqasxkPpkeWbwqoG+6T99BmufmbNGZ0vIcrBmD5JTM7sxPAuHZTAFZFTYrfbyczMZPny5Vx99dVA/TPm8uXLmT179nH3Oe+881iwYAF+vx+zub71yzfffENqaupxE7YiIiJNqdUkbWfNmsWmTZv47LPPGqy/+eabg38eMGAAqampjBkzhl27dtG9e/czOpd+HW0ee2vd1Pj92OpqGR3nNDqcZpEVG0m0xUyx28tXFTVGhyMiIgapdnmpqKuf9DTZ2T6+U5hMJlJiwkiJCeNCEql2eSmudFFU5aKk0kWN20ed14fL46O8rJS05ETCbBbCrBac4VZiwu3ERtiIDbcRE24jzGYhQIAql4/iyjp2FlWx6WA5JVUuXl+3n9fX7adPSjQzL+zKpeckYzY3TN6azeYG1XEiInPmzGHatGkMGzaMESNG8OSTT1JdXc306dMBmDp1Kh07dmTevHkAzJw5k7/+9a/88pe/5JZbbmHHjh08/PDD3HrrrUZehoiItBOtImk7e/ZsFi1axCeffEKnTp1OuO3IkSMB2LlzJ927dyclJYUvvviiwTZHX4lp7DUYaR6bq2oBSMndhc2cZXA0zcNuNjM63sl/i8pYUlJudDgiImKQwiNVtnGR9nbb1zXSYSXSYaVLQmSD9T6vhzsvm8ButxubzXZKx/L5fKRndCa/sJCwjv2IPOciIvpcwLYC+OW/NlB3cCuly57FXbgruE9qWkf25+5T4lZEgn74wx9SXFzMfffdR0FBAYMHD2bJkiXBNzFzc3ODFbUA6enpLF26lNtvv52BAwfSsWNHfvnLX3LXXXcZdQkiItKOhHTSNhAIcMstt/DWW2+xYsUKunbtetJ9cnJygPr+QwBZWVk89NBDFBUVkZSUBMCyZctwOp3069ev2WKXhmp9fnbV1E/ulrJvh8HRNK9LE2KCSdsT/8QgIiJtVbA1QhvtZ9vS/H4/+XkHeeSdHCzW+q+vtR4fGw9W8tWBcujYl9Qf/5lzUqMY1bUDdlOAu68cjN/vV9JWRBqYPXt2o+0QVqxYccy6rKws1qw5s3YuIiIiZyOkk7azZs1iwYIF/Pe//yU6OjrYgzYmJobw8HB27drFggULuOyyy4iPj2fDhg3cfvvtXHjhhQwcOBCAcePG0a9fP2688UYeffRRCgoKuOeee5g1a5ZaILSgPbUu/ECCzUpURanR4TSr0XHRWE2wo8ZFXFTbbAMhIiInll/ePvrZtjSL1YrFWl+dG2W1kdUjjAHpHfhsZwnbCyrZnF/F7pJaLuoZd5IjiYiIiIiENvPJNzHOM888Q3l5ORdddBGpqanB5fXXXwfqm8l/+OGHjBs3jj59+nDHHXcwefJk3n333eAxLBYLixYtwmKxkJWVxQ033MDUqVN54IEHjLqsdulolW2PiLafKI+xWcmKjQKgJDXD4GhERKSlBQIBiiqOvF2iSttmF+Wwcuk5KXx/aCfiI+3Ueny8v6WYhCt/zeFqt9HhiYiIiIickZCutA0EAiccT09PZ+XKlSc9TufOnVm8eHFThSWnyRsIsLe2/qGpe4SDPIPjaQnjE2L4tLRKSVsRkXaorNaD2+fHajYRH6nZxVtKxw7hXDcinS/2HGbd3lIi+17IhL98zkNXD2DCgFSjwxMREREROS3NUmnbrVs3Dh06dMz6srIyunXr1hynlBB2oM6NOxAg0mIm2R7SvxM0mfEJMQCUJyRR4/MbHI2IhBrdJ9u2osr6HyoTohyYzSaDo2lfrGYz53ZP4AdDU3EX7+VwtYeZr61n1oL1HKpyGR2eiIiIiMgpa5ak7d69e/H5fMesd7lcHDx4sDlOKSFs55HWCN3DHZhM7ePhNT3MzjlRYWAys6dWD4ki0pDuk21bcVV90jbJ2fZbAoWqpGgH+a/cxi++1w2L2cR7G/IZ98QnLN6Yb3RoIiIiIiKnpEnLHt95553gn5cuXUpMTEzws8/nY/ny5XTp0qUpTykhLhAIsOdI0rZbO+hn+23jE2LYXFXHzhoX50SFGx2OiIQA3Sfbh+IjlbZJ0e3rvhdyfF5uH9uDywam8as3vmZbQSW/eG09Ewek8rsr+pGkfsMiIiIiEsKaNGl79dVXA2AymZg2bVqDMZvNRpcuXXjsscea8pQS4sq9Pip8fsxARlj76ut3aUIMj+8tZG+tC68/gFWvyIq0e7pPtgcmio+8hp8UraRgKOjfMYZ3Zp/PXz/awfwVu3hvYz4fby9i1sU9mHF+V8JsFqNDFBERERE5RpMmbf3++t6dXbt25csvvyQhIaEpDy+tUG5dfbVRqsOGrZ0lLQdEheOoqcIVEUVunbvdVRqLyLF0n2z7rLEpuH0BLGYTcZqELGTYrWbmjOvNuHNSuOftTeTsL+OPS7ezYG0uv760N1cMTFP/YREREREJKc3S03bPnj16EBXgf0nb9HZWZQv1lXQJ+fuB//X1FREB3SfbMntKDwASouxYlAQMOf07xvDWL87lz9cNJi0mjINltfxyYQ6XPfUpy7YUEggEjA5RRERERARo4krbb1u+fDnLly+nqKgoWFl01Isvvthcp5UQEggE2F/rASAjvP0lbQES8vZxsHtfdte6CAQC7WYiNhE5Od0n2yZ7cncAEtXPNmSZTCauGtyRcf1SeOGz3fztk91sK6jkpn+sY1B6LHeO6815PeJ1zxYRERERQzVLpe3999/PuHHjWL58OSUlJZSWljZYpH045PFR4/djNdW3R2iPYosLsJtMVPv8FLi9RocjIiFC98m262ilbbL62Ya8cLuF2aN78umvL+YXF3Un3Gbh6/1l3PDCWq5/fg3Z+w4bHaKIiIiItGPNUmn77LPP8vLLL3PjjTc2x+GllTjaGiHNYcfaTqtVzAE/XcLtfFPjYmdNXbtNXotIQ7pPtk2BQCBYaZukSttWIzbCzq8v7cP087oy/+OdLFiby5rdh5n8zGou7p3IHeN6079jjNFhioiIiEg70yyVtm63m3PPPbc5Di2tyIEjSduMdtjP9tt6HJmAbHeN2+BIRCRU6D7ZNh0oq8USHo3ZBHFR7fve1xrFRVj57YReLLvtPK7N7IjFbOLj7cVc/pfP+Pk/17H1YCkej6fBIiIiIiLSXJolafvTn/6UBQsWNMehpZUIAHmu+oeZjmHtu7q0a7gDE1Di8VLmUYsEEdF9sq3anFcJQHykHau5Wb5iSTPx+XykZ3TGbrfTJSmGP147hNxnb6J68woCAT9LNhdy6Z8/JWncz3BERGG324mMjAQgEPCf5OgiIiIiIqevWdoj1NXV8dxzz/Hhhx8ycOBAbLaGSbvHH3+8OU4rIaQuIopqnx8zkGxv30nbMIuZTmE29td52F3rZqit2eb/E5FWQvfJtmlzXgUAiaqybXX8fj/5eQd55J0cLNaG9+mSKjdr95ay51AtMSMn0/miHzKmdwLxjgC/nTScQCBgUNQiIiIi0pY1S/Zow4YNDB48GIBNmzY1GNNMvO1DeXwSAEl2Kzaz/p13D3ewv87DrhoXQ50RRocjIgbTfbJtOpq0TYpW0ra1slitWKwNf0RJjrVx5eBIdhdX8dG2Ispqvfwnp4BBaVFgthgUqYiIiIi0dc2StP3444+b47DSilTEJwPQsZ33sz2qe4SDFaVV7K9zU+fTa5Qi7Z3uk21PIBBgU7DSVpOQtUXdEqPoGBvOJztK2JJfwdd5VSRfP49ql49Yfd0RERERkSamhmvSLI5W2qY52ndrhKNibVbibRYCwJ5al9HhiIhIE8svr6O0xkPA5yU+Sve+tsphs3BJv2QuH5iK3WIirFM//p1TSFFlndGhiYiIiEgb0yyVthdffPEJX+/86KOPmuO0EiIqvT6qYjoAzZ+0Xb8+m+tn33rcsa82bGBos5799HSPcHCovIZdtS7SjA5GRAyl+2Tbs/FgOQCeklys5h4GR3P2fD4ffv+pvRni8XiaOZrQ0z0xiu8PSuLlD76AhM78O/sAEwek0jk+0ujQRERERKSNaJak7dE+fUd5PB5ycnLYtGkT06ZNa45TSgj5qqIGTGacVjNR1ubt9ebGzNA75h53bM2Ua5v13Kere7iDL8pr2FvjJsWkIneR9kz3ybbnaD9bd9EuYLSxwZwln89HekZn8vMOntZ+gUD7av8TE26l4NVfc+7v3+ZAmYt3v85nwoAUuidGGR3aaTmdBD2A2WzGYlEvXxEREZHm1ixJ2yeeeOK463//+99TVVXVHKeUELK+ohqAVLVGaCDFYSPCbKbG76csIdnocETEQLpPtj1bjiZtC3cbHMnZ8/v95Ocd5JF3crBYT/5V0V1Xy28nDScQCLRAdKEl4Kpm4jmJLP+mjJ3FVSzemM/Egal0S2gdidszSdCnpnVkf+4+JW5FREREmlmzJG0bc8MNNzBixAj+9Kc/teRppYV9VVkDQKpdSdtvM5tMdIuws6mqjkNpGUaHIyIhSPfJ1mtrfttJ2h5lsVqxWE9+L7dY2197hG+zmE1M6J/CB1sK2V5YyeKNBVw1KI30uAijQzup003Q+7xe7r5yMH6/X0lbERERkWbWoknb1atXExYW1pKnlBYWCATq2yNQX1kqDXWPcLCpqo6DcclcN/tWjtfRMjEqkqcemdfisYmI8XSfbJ3KatwcLKsFwF20x+Boju90+s62VI/aUIzpTJnNJi7pl4zH52d3STWLNuRz7bBOxEc5jA7tlJxqgl5EREREWk6zJG0nTZrU4HMgECA/P59169Zx7733NscpJUTkuzwUub2Y/H6SVGl7jM5hDqwm8MYl0PmWO0mwH/uf4PrHlLAVaet0n2xbtuZXAtApNox97hqDo2nI7/OByUxk5OlPkNVcPWpDMaamcLTi9q2vDpJXXsc7X+fxw+HpRBznXi8iIiIicjLN8i0yJiamwWez2Uzv3r154IEHGDduXHOcUkLE0dYIkRWl2MypBkcTemxmExlhdnbXutlV4zpu0lZE2j7dJ9uWLUdaI/RNdfK5wbF8VyDgh4Cfh9/OxmY/tarP5u5RG4oxNRWrxczlA9N4fd1+yms9vL+pgGuGdMRsOt67NSIiIiIijWuWjNFLL73UJMeZN28eb775Jtu2bSM8PJxzzz2X//u//6N3797Bberq6rjjjjtYuHAhLpeL8ePH8/TTT5Oc/L+JnnJzc5k5cyYff/wxUVFRTJs2jXnz5mE9hd5dcnqOtkZwHi42OJLQ1T3CEUzajow9/SojEWn9muo+KaHh6CRkfVOiDY6kcafz+ntL9agNxZiaQrjdwpWD0lj4ZS4HSmtZs/sQ53ZPMDosEREREWllmjVrmZ2dzdatWwE455xzGDJkyGntv3LlSmbNmsXw4cPxer385je/Ydy4cWzZsiX4St3tt9/Oe++9xxtvvEFMTAyzZ89m0qRJfP55fa2Lz+dj4sSJpKSksGrVKvLz85k6dSo2m42HH364aS+4Hbr17rkUV1UHP391waWQlEbpxhwY/T3jAgth3cIdQCX5bg/VXh+RVk3kIdJene19UkLD0UnI+oRw0ra9OtVeuE3dMzcu0s6YPsks2VzAl3tL6RgbTqcYe5OeQ0RERETatmZJ2hYVFXHdddexYsUKYmNjASgrK+Piiy9m4cKFJCYmntJxlixZ0uDzyy+/TFJSEtnZ2Vx44YWUl5fzwgsvsGDBAkaPHg3UVy/17duXNWvWMGrUKD744AO2bNnChx9+SHJyMoMHD+bBBx/krrvu4ve//z12u75An43iqmqG3jEXqO/J+HluMQQC+PeF5kQsoSDKasF0YB+BTp3ZVetiYHTozy4tIk2rqe6TYjy318+Oovqetn1TlbQNFWfaN7cpe+b2TonmYFktGw+W8+HWIq7LVNsoERERETl1zZK0veWWW6isrGTz5s307dsXgC1btjBt2jRuvfVW/t//+39ndNzy8nIA4uLigPoKJY/Hw9ixY4Pb9OnTh4yMDFavXs2oUaNYvXo1AwYMaNAuYfz48cycOZPNmzcft6rJ5XLhcrmCnysqKs4o3vbmsMeHOxDAagJTcYHR4YQ0y9aNeDt1ZleNkrYi7VFz3Sel5e0sqsLjCxAdZqVjbJjR4cgRp9s3t7l65l7QM4H9pTWU1XhYufNwkx5bRERERNo2c3McdMmSJTz99NPBB1GAfv36MX/+fN5///0zOqbf7+e2227jvPPOo3///gAUFBRgt9uDVUpHJScnU1BQENzm2wnbo+NHx45n3rx5xMTEBJf09PQzirm9KXLXv1qYaLdh8ofu7M6hwLLlawD21bpx6Z+VSLvTHPdJMcbR1gj9Up2YNNlUyDnaN/fkS/N0DLNZzIzvl4LJBDuKqgnvPqJZziMiIiIibU+zJG39fj8227ETS9hsNvxnmKCaNWsWmzZtYuHChWcb3knNnTuX8vLy4LJ///5mP2dbUOj2ApBs1wRvJ2MqKqCD1YIP2F3jOun2ItK2NMd9Uoyx5UjStm+q0+BIJFSlxIQxNKMDAHHjfk6Vy2twRCIiIiLSGjRL0nb06NH88pe/JC8vL7ju4MGD3H777YwZM+a0jzd79mwWLVrExx9/TKdOnYLrU1JScLvdlJWVNdi+sLCQlJSU4DaFhYXHjB8dOx6Hw4HT6WywyMkVuuorbZPtpzYTdHtmAnpF1r9Gu0NJW5F2p6nvk2KcLXlHKm3T9F1BGjeyaxzOMCtWZxJ/Xr7T6HBEREREpBVolpLIv/71r1x55ZV06dIl2Fpg//799O/fn1dfffWUjxMIBLjlllt46623WLFiBV27dm0wnpmZic1mY/ny5UyePBmA7du3k5ubS1ZWFgBZWVk89NBDFBUVkZSUBMCyZctwOp3069evKS5XqP93VXS00tahSttT0TPCwdryavbUuvD4A9jMJ36t9ta751JcVX3cscSoSJ56ZF5zhCkizaCp7pNirEAgwNaC/7VHEGmMzWLmop7xvLOxkFfX7ufGc7vSPTHK6LBEREREJIQ1S3YtPT2d9evX8+GHH7Jt2zYA+vbt22DCsFMxa9YsFixYwH//+1+io6ODPWhjYmIIDw8nJiaGGTNmMGfOHOLi4nA6ndxyyy1kZWUxatQoAMaNG0e/fv248cYbefTRRykoKOCee+5h1qxZOBwnn5hCTk2p93+TkMXblLQ9FUl2KzFWC+VeH3tqXcHK28YUV1Uz9I65xx1b/5gStiKtSVPdJ8VY+eV1lNV4sJpN9EyOgoBaW0jjMuLCqdmxloieI3n4vS08O+XYyXC/y2w2Y7FYWiA6EREREQk1Tdoe4aOPPqJfv35UVFRgMpm45JJLuOWWW7jlllsYPnw455xzDp9++ukpH++ZZ56hvLyciy66iNTU1ODy+uuvB7d54oknuPzyy5k8eTIXXnghKSkpvPnmm8Fxi8XCokWLsFgsZGVlccMNNzB16lQeeOCBprz0du9oa4REmw2zJmI5JSaTiZ4R9T8cqEWCSPvQ1PdJMdbR1gg9kqJwWJVYkxPz+3yUrnyZgM/L8m3FOHsMw263n3BJz+iMz+czOnQRERERMUCTlkQ++eST3HTTTcftARsTE8PPfvYzHn/8cS644IJTOl4gEDjpNmFhYcyfP5/58+c3uk3nzp1ZvHjxKZ1TzszRSciS1BrhtPSMcLCuooZdNS68/gDWk7RIEJHWranvk2KsrflqjSCnLhDw4z20nwEdnWwqqOGcm/7EtUNTG/2x2+f1cveVg/H7/aq2FREREWmHmrTS9uuvv+bSSy9tdHzcuHFkZ2c35SklRBS5NQnZmUh12IiymPEEAuyrcxsdjog0M90n25YtR5K2fZW0ldMwokssDquZkio33xTXYrHaGln0Q7iIiIhIe9akSdvCwkJstsaTdlarleLi4qY8pYSAQCBAkUuTkJ2JBi0SqusMjkZEmpvuk21LsNI2TUlbOXVhNgsjusYBsGrXIdxe9UIWERERkWM1adK2Y8eObNq0qdHxDRs2kJqa2pSnlBBQ5vXhCgSwoEnIzkTPIxOQ7ap14TuFliAi0nrpPtl2VLm87D1UA6jSVk7fwE4xxITbqHH72HCgzOhwRERERCQENWnS9rLLLuPee++lru7YisHa2lp+97vfcfnllzflKSUEHO1nm2i3YtEkZKeto8NGhNlMnT/Avlq1SBBpy3SfbDu2F9RX2SY7HcRF2g2ORlobq9nMyCPVttn7SlVtKyIiIiLHaNKyyHvuuYc333yTXr16MXv2bHr37g3Atm3bmD9/Pj6fj9/+9rdNeUoJAYWuI/1sHepneybMJhO9Ix18VVnL1uo6VGMn0nbpPtl2bMmvBFRlK2eud3I0X+49TGmNh5wDZYzoEmd0SCIiIiISQpo0aZucnMyqVauYOXMmc+fOJXDkVW+TycT48eOZP38+ycnJTXlKCQFFRyptk+xqjXCm+kaF81VlLTtr6ki06J+jSFul+2TbsVWTkMlZMptNjOgax9LNhazfV8qgTjE4rBajwxIRERGRENGk7REAOnfuzOLFiykpKWHt2rWsWbOGkpISFi9eTNeuXZv6dGKwAFDkPlJpa1el7ZlKsVuJtVrwBqAkLcPocESkGTXlfXLevHkMHz6c6OhokpKSuPrqq9m+fXuDberq6pg1axbx8fFERUUxefJkCgsLG2yTm5vLxIkTiYiIICkpiTvvvBOv13vW19qWKWkrTaFXcjRxEXZcXj85+8uMDkdEREREQkiTJ22P6tChA8OHD2fEiBF06NChuU4jBquLjKbOXz8JWYIqbc+YyWSiz5EJyQozuhscjYi0hKa4T65cuZJZs2axZs0ali1bhsfjYdy4cVRXVwe3uf3223n33Xd54403WLlyJXl5eUyaNCk47vP5mDhxIm63m1WrVvHKK6/w8ssvc9999531NbZVfn+A7QX17RH6pUYbHI20ZmaTiZHd6tsirM8tw+XxGRyRiIiIiIQKZdnkrFTGxgP1CVtNQnZ2+kaFsaa8msPJHSlweUhRj2AROYklS5Y0+Pzyyy+TlJREdnY2F154IeXl5bzwwgssWLCA0aNHA/DSSy/Rt29f1qxZw6hRo/jggw/YsmULH374IcnJyQwePJgHH3yQu+66i9///vfY7Zpk67tyD9dQ4/bhsJrpEh9pdDjSyvVMiuKLSDuHqt2s319GVrd4o0MSERERkRDQbJW20j5UdkgA1BqhKcTZrKQ5bGAy80bBYaPDEZFWqLy8HIC4uCOz0mdn4/F4GDt2bHCbPn36kJGRwerVqwFYvXo1AwYMaNBLd/z48VRUVLB58+bjnsflclFRUdFgaU+OtkbonRKN1aKvUnJ2TCYTI7vW/zebs1/VtiIiIiJST08aclaOVtomO1S03RT6R4UDsDD/cHCCIhGRU+H3+7nttts477zz6N+/PwAFBQXY7XZiY2MbbJucnExBQUFwm+9Ofnb089FtvmvevHnExMQEl/T09Ca+mtB2NGnbJ0WtEaRp9EiKIj7Sjlu9bUWa3fz58+nSpQthYWGMHDmSL7744pT2W7hwISaTiauvvrp5AxQRETlCSVs5Y4FAQJW2Tax3pAOL18OuWhdflleffAcRkSNmzZrFpk2bWLhwYbOfa+7cuZSXlweX/fv3N/s5Q8mW/Pp+tpqETJqKyWRixJFq26/2l+HyqtpWpDm8/vrrzJkzh9/97nesX7+eQYMGMX78eIqKik643969e/nVr37FBRdc0EKRioiIqKetnIXcOjdeu6PVTUK2fn0218++9bhjX23YwNAWjufb7GYzSfv3kN+1F6/mH2JEbJSB0YhIazF79mwWLVrEJ598QqdOnYLrU1JScLvdlJWVNai2LSwsJCUlJbjNd6uMCgsLg2PH43A4cDgcTXwVrcfRSlslbaUp9UiKIi7CzuEaN1/vLyczXZXcIk3t8ccf56abbmL69OkAPPvss7z33nu8+OKL3H333cfdx+fzMWXKFO6//34+/fRTysrKTngOl8uFy+UKfm5vLYRERKTpqNJWztjXlbVA65uEzI2ZoXfMPe4SCpUtqXu3A/BOURmHPV6DoxGRUBYIBJg9ezZvvfUWH330EV27dm0wnpmZic1mY/ny5cF127dvJzc3l6ysLACysrLYuHFjgyqjZcuW4XQ66devX8tcSCtSXuvhYFn9/a9vipK20nTM36q2XZ9bitvrNzgikbbF7XaTnZ3doM+72Wxm7NixwT7vx/PAAw+QlJTEjBkzTuk87b2FkIiINB0lbeWMfV1ZA6g1QlNzHi5mQFQ4df4AC/M1IZmING7WrFm8+uqrLFiwgOjoaAoKCigoKKC2tj6pGBMTw4wZM5gzZw4ff/wx2dnZTJ8+naysLEaNGgXAuHHj6NevHzfeeCNff/01S5cu5Z577mHWrFntupq2MduOVNl2jA0nJkL3P2laPZOj6BBhw+X1syFP1XkiTamkpASfz3fcPu6N9XD/7LPPeOGFF3j++edP+TztvYWQiIg0HSVt5YxtOJq01SRkTcoE/Lhjfa/gVw6W4NeEZCLSiGeeeYby8nIuuugiUlNTg8vrr78e3OaJJ57g8ssvZ/LkyVx44YWkpKTw5ptvBsctFguLFi3CYrGQlZXFDTfcwNSpU3nggQeMuKSQ97/WCHp1XZqe2WRiRJf6atuc/RWYbGEGRyTSflVWVnLjjTfy/PPPk5CQcMr7ORwOnE5ng0VERORMKNsmZyQQCLDhSHsEVdo2vauTY7l/10H21blZfqiCSxJijA5JREJQ4BR+1AkLC2P+/PnMnz+/0W06d+7M4sWLmzK0NmurJiGTZtYrOZq1ew5TVusheshEo8MRaTMSEhKwWCzBvu1HfbvP+7ft2rWLvXv3csUVVwTX+f31bUusVivbt2+ne/fuzRu0iIi0a6q0lTOyr85NudeH2edtVZOQtRaRFgvXp8YD8Mz+YoOjERFpv3w+Hx6PJ7hszS8HoGdiRIP1RxeRs2U2mxh+pLetc8Q11LjV316kKdjtdjIzMxv0eff7/SxfvjzY5/3b+vTpw8aNG8nJyQkuV155JRdffDE5OTnqVSsiIs1OSVs5IzkV9a0RIstLW9UkZK3JzZ0SsZpgVVkVXx355y0iIi3H5/ORntEZu91evzjCyNlbP2Hb5DGj/rf+yBIZGQlAIKAJpOTs9EmOJibMiiUylv/35QGjwxFpM+bMmcPzzz/PK6+8wtatW5k5cybV1dVMnz4dgKlTpzJ37lyg/k2V/v37N1hiY2OJjo6mf//+2O12Iy9FRETaAZVIyhk52hohurTE4Ejaro5hdq5J7sAbBaU8nVt08h1ERKRJ+f1+8vMO8sg7OVisVkpr3Lz2ZR5Ws4mHXl2K+Ts/WrrravntpOGn1LZC5ETMZhOZnWP4aPshnvt0DzdkdSVKcwiInLUf/vCHFBcXc99991FQUMDgwYNZsmRJcHKy3NxczGbVNYmISGjQtz85I18fmYQsukxJ2+b0i/Qk3igo5b3iMoZHatIbEREjWKxWLFYbh2vrAEiIcmCzHVthZbGqPYI0nd5JUSxdvZHDpPHiZ3u4dUxPo0MSaRNmz57N7Nmzjzu2YsWKE+778ssvN31AIiIijdDPiHLa/IEAG6vqk7bO0kMGR9O29Y0KZ3RcNH5gf8/+RocjItKuFVe6AEiI0iux0vwsZhNln/4TgOc+2c2hKpfBEYmIiIhISwr5pO0nn3zCFVdcQVpaGiaTibfffrvB+I9//GNMJlOD5dJLL22wzeHDh5kyZQpOp5PY2FhmzJhBVVVVC15F27K31k2F14/DbCKiotTocAy3fn0218++9bjLVxs2nPXxZ2UkAVDQpSc1PvVJFBExSsmRpFlCtMPgSKS9qNn2GeekRVPl8vKXj3YaHY6IiIiItKCQb49QXV3NoEGD+MlPfsKkSZOOu82ll17KSy+9FPzscDR8mJoyZQr5+fksW7YMj8fD9OnTufnmm1mwYEGzxt5WbTjSGuGcqHDM6tuHGzND75h73LE1U6496+OfGxvFoOhwvq6s5auKGs7rEHXWxxQRkdNXUuUGIDFKSVtpKQHuHNeLH7+czatr9nHDqAx6JKldkoiIiEh7EPKVthMmTOAPf/gD11xzTaPbOBwOUlJSgkuHDh2CY1u3bmXJkiX8/e9/Z+TIkZx//vn85S9/YeHCheTl5bXEJbQ5OUeStgOjIwyOpH0wmUzMyqifHCGnsga3X9W2IiItrdbjo8rlBep72oq0lPO6xzO2bzJef4AHFm3VRHciIiIi7UTIJ21PxYoVK0hKSqJ3797MnDmTQ4f+12d19erVxMbGMmzYsOC6sWPHYjabWbt27XGP53K5qKioaLDI/2yorAVgUHS4wZG0HxMTYwivLKfOH+DrI//8RUSk5ZQc6WcbE27Dbm0TX5+kFblnYl9sFhOffFPMsi2FRocjIiIiIi0g5NsjnMyll17KpEmT6Nq1K7t27eI3v/kNEyZMYPXq1VgsFgoKCkhKSmqwj9VqJS4ujoKCguMec968edx///0tEX6r4w8E2Hik0nZQdATvnMExjvaA/a6vNmxg6FnG11ZZTCY6b9/AtmEXkF1Rw5DoCKxmk9FhiYi0G8VVmoRMjNMlIZKfXtCNZ1bs4t7/bmJU93icYTajwxIRERGRZtTqk7bXXXdd8M8DBgxg4MCBdO/enRUrVjBmzJgzOubcuXOZM2dO8HNFRQXp6elnHWtbsLPGRaXPT7jZTK+IsDM6RmM9YJui/2tblpy7i4Mjv0elz8/mqloGOdWeQkSkpQQnIVNrBDHIL8f05P2N+ew9VMO8xduYN2mA0SGJiIiISDNqc+/3devWjYSEBHburJ9hNyUlhaKiogbbeL1eDh8+TEpKynGP4XA4cDqdDRapl11RDdS3RlClZ8syB/wMi4kE4IuKanzqaSci0mKOTkKmpK0YJcxm4ZHJAwH4f1/k8qHaJIiIiIi0aW0uaXvgwAEOHTpEamoqAFlZWZSVlZGdnR3c5qOPPsLv9zNy5Eijwmy11lfUt0bIPJI8lJY1ICqccLOJCq+f7dV1RocjItIu+PwBDh9J2iZGK2krxhnVLZ6fnNcVgDve+JoDpTUGRyQiIiIizSXkk7ZVVVXk5OSQk5MDwJ49e8jJySE3N5eqqiruvPNO1qxZw969e1m+fDlXXXUVPXr0YPz48QD07duXSy+9lJtuuokvvviCzz//nNmzZ3PdddeRlpZm4JW1Ttnl9ZW2mXo13xA2s4lMZ33CfG15tWaQFhFpAWW1HnyBAHaLGWdYq+8sJa3c3RP6MCg9lvJaDz/7ZzaVdR6jQxIRERGRZhDySdt169YxZMgQhgwZAsCcOXMYMmQI9913HxaLhQ0bNnDllVfSq1cvZsyYQWZmJp9++ikOx/8qYV577TX69OnDmDFjuOyyyzj//PN57rnnjLqkVqvK62PbkerOoU5V2hplsDMch8nEYY+PnTUuo8MREWnzjrZGiI+yYzKpNZAYy24189frhxAfaWdzXgU/+2c2dR6f0WGJiIiISBML+XKRiy666ITVhEuXLj3pMeLi4liwYEFThtUu5VTW4Ac6OmykODRjsVEcZjNDnBGsKa9mbXk1PSL0qq6ISHM6mrRNVD9bCRHpcRG8PH0E1z23mlW7DjHjlS95+keZxESc3fczr99PabWHQ9UuSqrcVNR6qPX48PoCBAhgMUHiNb/l/kVb6ZIQRd9UJ/07xhATru+FIiIiIk0t5JO2Ejqyy9XPNlQMcUawrqKaQreXfXVuo8MREWnTSqqPTEKmfrYSQgZ0iuH5acP46Svr+HznIa555nOeuHYwg9JjT/kYPn8Ae2ov1u0r40CZi/zyupNOdBrRK4tX1+4PfjaZ4Jw0J6N7JzHunBTOSXOqIl1ERESkCShpK6csu0L9bENFhMXMoOgIsitqWFtWTU+jAxIRacMOqdJWQtS53RN44+dZ/PSVdewurubqpz/nB5mduHFUF/p3PDZ56vH52ZJXQfa+Ur7Yc5hVu0pInfo4a/aWBbdxWM3ER9qJj3IQG2Ejwm7BZjFjAtweLwue/D2/fehP7D1Uy5b8CnIP17DpYAWbDlbw1Ec76ZMSzXXD0/nBsHQiHXrUEBERETlT+iYlpyQQCJBdcaTSVv1sQ0KmM4KvKmo44PKQGJ9sdDgiIm2SOSKWGo8fqO9pKxJqzkmL4d1bzueh97by1lcH+de6A/xr3QGSoh30SXUS7bDi8fkprKhje2EldUf+Ph/lr6uiR6ckOsdHkh4XQWy4rdFKWZ/XQ1XO+9xxyX+x2epbIhRW1PH5zhI+2FzIR9uL2FZQye/f3cITH+7gJ+d15acXdFXyVkREROQM6BuUnJLcOjeHPF5sJhP9o8KNDkeAaKuFc6LC2VhVy74+A40OR0SkTbIndQUgNsKGzRLy87dKO5UQ5eCJHw5mysgM/rF6H0s2FVBU6aKosviYbWPCbQzNiGVYlziGd45hZI8Ubn1vAxbrmfWlTXaGMWloJyYN7UR5jYf/fn2Qlz7fy56Sap748Bv+uWYvd0/oy+ShHdU2QUREROQ0KGkrp+RolW3/qHDC9NAaMkbERLCpqpbDKelsrKxhQLRaV4iINCV7UhegPikmEuqGdYljWJc4atxetuZXsLOoijqPH7MJkpxhdEuIpHtiFGZzffLU4/FAwH+So566mAgbU7O6MGVkZ97flM+flm5n76EafvXG1/wn+wB//MFAOnXQdxURERGRU6GkrZyS7PIj/Wxj9EU7lMTarPSODGNbdR1P7Svi+f5djA5JRKRNsSXWV9qqn620JhF2K5md48jsHGfI+S1mE5cPTGP8OSm88NkenvzwG1bvPsSEP3/Ko5MHMmFAqiFxiYiIiLQmKpmUU6J+tqFrZEz9v5P3isvYU+MyOBoRkbblaHuEBPWzFTltNouZn3+vO0tvu5DB6bFU1nmZ+dp6/rh0G35/wOjwREREREKakrZyUrU+P5uq6pO2Q52qtA01CXYrcfn78QPP7i8yOhwRkTbD5fFhS8gAIDFalbYiZ6pTbBgLZgxjxnmdAZj/8S5+8Vo2VbUuPB7PMYvP5zM4YhERERHjKWkrJ7WpqhZvABJsVjLCVGkUijK+2QjA6wWHKXZ7DI5GRKRt2F5YhclsIcxmJsqhjlIiZ8Ln85Ge0ZnI8DDuu3IAJYseI+D1sGRzId1//CiOyGjsdnuDJT2jsxK3IiIi0u7pCUROat23+tlq1t/QFFtSwJDoCL6qrOHFAyXc1U294kREztbm/AoAEqPsuv+JnCG/309+3kEeeScHi7X+0WN/aS2LNxVB16FkPfAeV/RPwnpkoluf18vdVw7G7/djsViMDF1ERETEUKq0lZNaW14FwHD1sw1ZJmBWRhIALx0sodqr6hQRkbO1Oa8S0CRkIk3BYrVisdqwWG10SXRyzdCO2C1mDpbV8f7WEjAfHVdNiYiIiAgoaSsn4Q8EWFtWX2l7bmyUwdHIiUxIjKFruJ0yr4//V3DY6HBERFq9LUcqbZOi1RpIpKmlxoRz5aA0rGYT+w7VsHxrIYGAJicTEREROUpJWzmhbdV1lHp9RFjMDIjWJGShzGIyMTO9vtr2mdwiPJqVWUTkjHl8frYX1r9pkhilpK1Ic+jYIZyJA1IxmWBrQSVr9+hHZxEREZGjlLSVE1pV9r/WCDaz+vmFuh+kxJFgs3LQ5eHd4jKjwxERabV2FlXh9vrx11XhDNPr2iLNpUtCJBf3rv/Ree2ew+wqrjY4IhEREZHQoKStnNDqI0nbrFj1s20Nwi1mftopAYD5uXrNUETkTG06WA6Au3C3JiETaWYDOsYwOD0WgA+3l2CLTzc2IBEREZEQoKStNCoQCLDmSD/bLPWzbTWmdUwgwmJmc1UdK0srjQ5HRKRV2pxX38/WXbjL4EhEQo/H4zmt5VSc3yOBTrHheHwBEq66mzqPJlUVERGR9k1JW2nUjhoXhzxewswmBjvVz7a16GCzckNqPADzc4sMjkZEpHX6X6WtkrYiR/l9PjCZiYyMxG63n9ISGVn/tlYg4D/hsS1mExMGpBBhM2NP7MwfP9jREpckIiIiErLUpE0adbQ1QqYzEodZ+f3W5Kb0RF44WMynpVV8XVnDoONMInfr3XMprjq2b1xiVCRPPTKvJcIUEQlJPn+ALfn1lbauwp0GRyMSOgIBPwT8PPx2Nja745T2cdfV8ttJw0+pZVOE3cqY3gm8u6mIf6zJZXTfZC460u9WREREpL1R0laCvpvE2zziIkjvRtm6NTCkh3GByWlLD7NzdVIH/lNYyo1vLeGcL1Ycs81XGzYw45X/d8z69Y8pYSsi7duekmpq3D7CbWa8h/OMDkck5FisVixW2ylue2rtEY7qHB9BRfa7ODOv4FdvbGDpbRcQH3VqCWIRERGRtkRJWwkqrqpm6B1zgfp+tl8cKAGfH9vBXIMjkzPxi4wk/lNYSnF6N7qNGk6sreF/7mumXGtQZCIioW1zXn1rhL6pTrad5JVuEWl6ZSteYuil17GzuJq7/rOB56cO04SAIiIi0u7onXc5rjKvj2qfHwvgPFxsdDhyBs6JCieu4AABYF1FjdHhiIi0Gkf72Z6TGm1wJCLtU8Dr5vEfDMRuMfPh1iL+m6OKdxEREWl/lLSV4zpQV/8qW4rDhsWv2Xtbq4ztGwDYVFlLhVf/HkVETsWmg/X9bPulOQ2ORKT96psazS2j69tzPbhoC2U1boMjEhEREWlZStrKcR2oq/9i3CnMbnAkcjY6lBSQHmbDB6wtO3bSMRERaSgQCLAp72ilrZK2Ikb62fe60zMpikPVbh5evNXocERERERaVMgnbT/55BOuuOIK0tLSMJlMvP322w3GA4EA9913H6mpqYSHhzN27Fh27NjRYJvDhw8zZcoUnE4nsbGxzJgxg6qqqha8itYlEAiwP5i0PbVJJiR0nRsbBcCmqlrKPaq2FRE5kf2Ha6ms82K3mOmRFGl0OCLtmt1q5uFJAwD417oDrNl9yOCIRERERFpOyCdtq6urGTRoEPPnzz/u+KOPPspTTz3Fs88+y9q1a4mMjGT8+PHU1dUFt5kyZQqbN29m2bJlLFq0iE8++YSbb765pS6h1Sn1+qg80s+2o0OVtq1dpzA7ncPs+IHV5fqxQkTkRI5W2fZJjcZmCfmvSSLH8Pl8eDyeU15C3fAucVw/IgOA37y1EZfaPYmIiEg7EfJPIxMmTOAPf/gD11xzzTFjgUCAJ598knvuuYerrrqKgQMH8o9//IO8vLxgRe7WrVtZsmQJf//73xk5ciTnn38+f/nLX1i4cCF5eZrU4Hj21tZX2XYMs2Mza6betuC8DvXVtluq6ij1eA2ORkQkdOXsLwOgf8cYYwMROQM+n4/0jM7Y7fZTWiIj66vJAwG/wZGf2N2X9iEhysHu4mqeXbHb6HBEREREWoTV6ADOxp49eygoKGDs2LHBdTExMYwcOZLVq1dz3XXXsXr1amJjYxk2bFhwm7Fjx2I2m1m7du1xk8EulwuXyxX8XFFR0bwXEmL21dZfe+dwVdm2FakOG93C7eyudbO6rJrLEpWMEBE5npzcMgCGpMcaGofImfD7/eTnHeSRd3KwWE/+Nd9dV8tvJw0nEAi0QHSn59tVwBE2+O2EXtz+xkaeWbmTqwclkxYbHhw3m81YLBYjwhQRERFpNiFfaXsiBQUFACQnJzdYn5ycHBwrKCggKSmpwbjVaiUuLi64zXfNmzePmJiY4JKent4M0YcmbyBA7pF+tl2UtG1Tjva23VpdR7E79F+HFBFpaV6fn40H69sjDMmINTYYkbNgsVqxWG2nsIRe/Ybf5wOTmcjIyAZVwZOGdaZu/ybqPH6GzfhDg7H0jM74fGqbICIiIm1L6H1TCwFz585lzpw5wc8VFRXtJnF7sM6NNwCRFjOJNv31aEuSHTZ6RTj4psbFisNVhF5NjYiIsbYXVlLr8REdZqVbQhQ+n9rJiPFOp+9sa+hRezKBgB8Cfh5+Oxub3dFgrLjSxevr84ns9z1u/NEPSYsJw+f1cveVg/H7/aq2FRERkTalVVfapqSkAFBYWNhgfWFhYXAsJSWFoqKiBuNer5fDhw8Ht/kuh8OB0+lssLQXR/vZdg6zYzKpn21bc2GHaCxAbp0bf5/+RocjIhJSjvazHdQpFrN6uovBGqs4bQs9ak/F8aqFUzpE0T+t/nv5Z7tKMVusIVktLCIiItIUWvW3nK5du5KSksLy5csZPHgwUF8Vu3btWmbOnAlAVlYWZWVlZGdnk5mZCcBHH32E3+9n5MiRRoUesvbVqjVCWxZjs5AZE8EX5TV4JlyDLxDAouS8iAgAXx3tZ6vWCBICTlRx2phQ7lHbVLK6x/NNYRVFlS625FfQJynC6JBEREREmkXIV9pWVVWRk5NDTk4OUD/5WE5ODrm5uZhMJm677Tb+8Ic/8M4777Bx40amTp1KWloaV199NQB9+/bl0ksv5aabbuKLL77g888/Z/bs2Vx33XWkpaUZd2EhyBUWTrGn/lXQzuGn9nAgrc/ImEgizGYCCUl8VVFjdDgichY++eQTrrjiCtLS0jCZTLz99tsNxgOBAPfddx+pqamEh4czduxYduzY0WCbw4cPM2XKFJxOJ7GxscyYMYOqqqoWvIrQcbTSdrAmIZMQcur9aUOzR21Ti7BbGdk1DoBVuw7h9rb+qmIRERGR4wn5pO26desYMmQIQ4YMAWDOnDkMGTKE++67D4Bf//rX3HLLLdx8880MHz6cqqoqlixZQlhYWPAYr732Gn369GHMmDFcdtllnH/++Tz33HOGXE8oO5zUEYBku5UIS8j/1ZAzZDebOb9D/aRkq8uqqfHpYUektaqurmbQoEHMnz//uOOPPvooTz31FM8++yxr164lMjKS8ePHU1dXF9xmypQpbN68mWXLlrFo0SI++eQTbr755pa6hJBRUedhV3F9slpJW5HQNig9lthwGzVuH+v3lxsdjoiIiEizCPnM3EUXXUQgEDhmefnllwEwmUw88MADFBQUUFdXx4cffkivXr0aHCMuLo4FCxZQWVlJeXk5L774IlFRUQZcTWg7nFyftO2iKts275yoMEx5+3EHAnxW2j4r6kTaggkTJvCHP/yBa6655pixQCDAk08+yT333MNVV13FwIED+cc//kFeXl6wInfr1q0sWbKEv//974wcOZLzzz+fv/zlLyxcuJC8vLwWvhpjbdhfTiAA6XHhxEfpPigSyixmE+f1SAAg50AFluh4gyOS1mT+/Pl06dKFsLAwRo4cyRdffNHots8//zwXXHABHTp0oEOHDowdO/aE24uIiDSlkE/aSsvwBwKUJte3i1A/27bPbDJhW/RvADZW1XKgzm1wRCLS1Pbs2UNBQQFjx44NrouJiWHkyJGsXr0agNWrVxMbG8uwYcOC24wdOxaz2czatWsbPbbL5aKioqLB0trl7C8FYHB6B4MjEZFT0T0xkrSYMLz+ALEX3GB0ONJKvP7668yZM4ff/e53rF+/nkGDBjF+/PhjJq4+asWKFVx//fV8/PHHrF69mvT0dMaNG8fBgwdbOHIREWmP2n7jKzklGypr8TjCsZtMpDpsRocjp2n9+myun33rMeu/2rCBoY3sY9m3mwFR4WysquWDkgqmdozHqknJRNqMgoICAJKTkxusT05ODo4VFBSQlJTUYNxqtRIXFxfc5njmzZvH/fff38QRGys4CZlaI4i0CiaTiQt6JvL6uv1E9h/DlvwKBmWo4lZO7PHHH+emm25i+vTpADz77LO89957vPjii9x9993HbP/aa681+Pz3v/+d//znPyxfvpypU6e2SMwiItJ+KWkrACw/VF8llR5mx6LEXavjxszQO+Yes37NlGtPuN+FHaLYXeui1OtjbVk153VQ2xARObm5c+cyZ86c4OeKigrS09MNjOjsBAKB/01ClhFraCwicupSYsLomRjJjuJq/m/JN7x20yhM+h4rjXC73WRnZzN37v++M5vNZsaOHRt8A+Vkampq8Hg8xMXFNbqNy+XC5XIFP7eFt1FERMQYao8gACwpqZ/EoXuE+vi1J2EWMxfHRQPwRXk1h9xegyMSkaaSkpICQGFhYYP1hYWFwbGUlJRjXgn1er0cPnw4uM3xOBwOnE5ng6U1O1Bay6FqNzaLiX6prftaRNqbrK6xBLweVu0+zIpvio0OR0JYSUkJPp/vhG+gnMxdd91FWlpag9ZD3zVv3jxiYmKCS2v+UVNERIylSlsht9bFxqpaCPiPm7Rt7NV7OPHr93JmzqTVwdnoFeGgW7id3bVuPjhUQa+T7yIirUDXrl1JSUlh+fLlDB48GKiv9lm7di0zZ84EICsri7KyMrKzs8nMzATgo48+wu/3M3LkSKNCb3FfHamy7ZfqJMxmMTYYETktznAbFdnvEDNyMg+/t5ULeiRgtaguRZreI488wsKFC1mxYgVhYWGNbtfW3kYRERHjKGkrLC2pf2UnpqSQiK6px4w39uo9nPz1ezl9Z9rq4EyZTCbGxDvZf/AQeS4P4b36N8t5RKTpVVVVsXPnzuDnPXv2kJOTQ1xcHBkZGdx222384Q9/oGfPnnTt2pV7772XtLQ0rr76agD69u3LpZdeyk033cSzzz6Lx+Nh9uzZXHfddaSlpRl0VS3vq9yjk5DFGhuIiJyRitX/ovNF17GjqIo3sg9w/YgMo0OSEJSQkIDFYjnhGyiN+dOf/sQjjzzChx9+yMCBA0+4rcPhwOHQ24siInL29DO0sLikDIDEvH3GBiKGcVotwTYJu8/JZENljcERicipWLduHUOGDGHIkCEAzJkzhyFDhnDfffcB8Otf/5pbbrmFm2++meHDh1NVVcWSJUsaVAi99tpr9OnThzFjxnDZZZdx/vnn89xzzxlyPUY52s92SEYHYwMRkTPid1Uz6+JuADz2wTdUu9TuSY5lt9vJzMxk+fLlwXV+v5/ly5eTlZXV6H6PPvooDz74IEuWLGHYsGEtEaqIiAigStt275Dby9qyagAS8nINjkaM1D8qjN21LnbWuJi1ZR9Lh/UmQq8XioS0iy66iEAg0Oi4yWTigQce4IEHHmh0m7i4OBYsWNAc4bUKdR4fmw7W93UfqqStSKv1o+HpvLp2P/sO1fC3T3Yz5xI1fJJjzZkzh2nTpjFs2DBGjBjBk08+SXV1NdOnTwdg6tSpdOzYkXnz5gHwf//3f9x3330sWLCALl26BHvfRkVFERWlCXxFRKR5KSPTzn1wqBw/0D8qnPCaKqPDEQOZTCbGxTux11azo8bF/TsPGh2SiEiz+yq3DI8vQLLTQXpcuNHhiMgZslvN3H1pHwCe+2QXBeV1BkckoeiHP/whf/rTn7jvvvsYPHgwOTk5LFmyJDg5WW5uLvn5+cHtn3nmGdxuN9///vdJTU0NLn/605+MugQREWlHVGnbzi0pqa8uujQhhmyDYxHjhVvM9F33KV9fcCmv5B1idLyT8QkxRoclItJsvthzGIARXeMxmUwGRyMiZ+PS/ilkdu5A9r5SHl+2nUe/P8jokCQEzZ49m9mzZx93bMWKFQ0+7927t/kDEhERaYSStu1Ytc/HysOVAFyWqKSt1IsryuNn6Yn8bX8xt2zdx9LM3nSNOPFkCrfePZfiqurjjiVGRfLUI/OaI1QRkbP25d4jSdsuao0g0tqZTCZ+O7Evk55exRvZB5h+Xlf6pjqNDktERETkjChp246tOFxJnT9A5zA7fSPDTr6DtBu/7ZbK+vIavqyo5seb9rB4aE8irZZGty+uqmboHXOPO7b+MSVsRSQ0eXx+1ueWAjC8a5zB0YhIUxia0YGJA1N5b0M+Dy/eyj9njDQ6JBEREZEzoqRtO/Z+8ZHWCIkxeiVUGrCbzTzfvwvj1m1ne3UdN2/exysDujLnN785bkXtVxs2MNSAOEVEzsbmvApq3D5iwm30Soo2OhwRaSJ3je/DB5sL+HRHCSu/KeZ7vRKNDklERETktClp2065/H4+OFSftL1MPUvlOFIcNl7u35XJOTtZfriCuTsOUFRVTeZxKmrXTLnWgAhFRM7Ol0f62Q7v0gGzWT9eirRmHo8n+OdUp40bR2bw4qp9PLRoCyNnZWH5zn/jZrMZi6Xxt4hEREREjGY2OgAxxseHKqnw+kl12BgeE2l0OBKihsZE8nS/zpiAf+YdYteA4QQCAaPDEhFpEqt3HwJghFojiLRafp8PTGYiIyOx2+3B5f4fZuGrreSboioSR1zeYMxut5Oe0Rmfz2d0+CIiIiKNUqVtO/VWUX0PvyuTYjGrNYKcwITEWP7YO51fbd/P/l4D+LS0igs6RKmlhoi0ah6fn7VHkrbndk8wOBoROVOBgB8Cfh5+OxubveHEqTkHyvlsVynpV83hxocew2apr1fxeb3cfeVg/H6/qm1FREQkZKnSth2q9vr4oKS+NcI1SZotW07uhrR4HurZEYAvK2p4v6QCnypuRaQV23CgnGq3j9gIG/00u7xIq2exWrFYbQ2WQRlxxITbqHH7+Ppg1bfGVLciIiIioU9J23Zo6aEKav0BuoU7GBQdbnQ40krM6JRIn3WfYgK2VtfxZmEZLr/f6LBERM7Iqp0lAGR1i1c/W5E2ymo2c173eACyc0updnkNjkhERETk1Clp2w79u6B+4pWrk2P1irucltR9O5iUHIvNZCK3zs3C/FLKPeoHJyKtz+e76pO25/ZQawSRtqxHUhQpzjA8vgBrjrREEREREWkNlLRtZwpdHlYcrgTg+8maeEVOX5dwBz9M6UCkxUyJx8ur+Yfw9epndFgiIqes1u1j/b4ygGAVnoi0TSaTiQt61v84szmvguJKl8ERiYiIiJwaJW3bmX8XluIHRsRE0i3CcdLtRY4n2WHjR6lxpNit1PkDuG/8GavLqgioz62ItAJf7j2M2+cnNSaMrgmRRocjIs0sLTacnklRBIDl2wrx6/uKiIiItAJK2rYjgUCA1/PrWyP8MEVVtnJ2nFYLP0yNq++LbDazqqyat4vKqPOpz62IhLaV3xQDcEHPBLUJEmknLuyViN1iprDCxaa8SqPDERERETmpVp+0/f3vf4/JZGqw9OnTJzheV1fHrFmziI+PJyoqismTJ1NYWGhgxMb5qrKGb2rqCDebuCIp1uhwpA2wmkyMjXdi+/erWE2wu9bNq/mHKXJ5jA5NRKRRH28vAuDi3kkGRyIiLSXKYeW8HvXtUFbvKcUSpdYoIiIiEtpafdIW4JxzziE/Pz+4fPbZZ8Gx22+/nXfffZc33niDlStXkpeXx6RJkwyM1jiv5dVPvnBZYixOq8XgaKQtsX61lutS4oixWij3+vh/BYfZUlVrdFgiIsfYd6ia3cXVWM0mzuupSchE2pMBHWOCk5LFjf2Z0eGIiIiInFCbSNparVZSUlKCS0JC/UNYeXk5L7zwAo8//jijR48mMzOTl156iVWrVrFmzRqDo25ZFV4fbxaWATA1TZUF0vSSHTampMbRNdyONwDvl1Tw4aEK/KY28b8ZEWkjVmyvb40wrEsHnGE2g6MRkZZkMpkY0zcJswkiep/Lsi1FRockIiIi0qg2kU3ZsWMHaWlpdOvWjSlTppCbmwtAdnY2Ho+HsWPHBrft06cPGRkZrF69utHjuVwuKioqGiyt3RsFh6n1++kdGcaIGE26Is0j3GLmmqRYso78Hfu6spavvncZeXVugyMTEamn1ggi7VtClIPBnWIAuPedLRRXugyOSEREROT4rEYHcLZGjhzJyy+/TO/evcnPz+f+++/nggsuYNOmTRQUFGC324mNjW2wT3JyMgUFBY0ec968edx///3NHHnLCQQC/ONIa4SpafGadEWalclk4twOUaQ4bCwuKaciPolx677h2XM6c36H6OB2t949l+Kq6uMeIzEqkqcemddSIYtIO1Hj9rJ6V/398OI+StqKtFcjOsewZv3XHKILd/77a16cNhyzWd+PRUREJLS0+qTthAkTgn8eOHAgI0eOpHPnzvzrX/8iPDz8jI45d+5c5syZE/xcUVFBenr6WcdqlM/LqtheXT8B2feTOxgdjrQT3SIc3JAax+ubv6EkNp5rc3bx2+5p/CI9EZPJRHFVNUPvmHvcfdc/poStiDS9lduLcXn9dOoQTs+kKKPDERGDWC1mSt75I11/9gwrthfz8qq9/OT8rkaHJSIiItJAm2iP8G2xsbH06tWLnTt3kpKSgtvtpqysrME2hYWFpKSkNHoMh8OB0+lssLQ2t949l+tn38r1s2/lZ4s/BqDDji3ce++9Bkcm7UmszcrQFYv4QUoH/MCDu/L46ea9VHl9RocmIu3Qks31b9lM6J+it05E2jlPyT7mXtoLgEfe38aWvNbfDk1ERETaljaXtK2qqmLXrl2kpqaSmZmJzWZj+fLlwfHt27eTm5tLVlaWgVE2v6NVjF1uvZNDaRkAjL/w/EZfRxdpLhafj6f6ZPBIr07YTCbeKy5nQvY3VEfHGB2aiLQjLq+Pj7bW97O9tH+qwdGISCj40Yh0xvZNwu3zc+vCr6h2eY0OSURERCSo1Sdtf/WrX7Fy5Ur27t3LqlWruOaaa7BYLFx//fXExMQwY8YM5syZw8cff0x2djbTp08nKyuLUaNGGR16i1hfUQNAt3A7cbZW3w1DWimTycSPOybw9pAepDps7KhxkX3xlWyrqjM6NBFpJz7fWUKly0uy08GQ9FijwxGREGAymXj0+4NIinaws6iKOf/Kwe8PGB2WiIiICNAGkrYHDhzg+uuvp3fv3lx77bXEx8ezZs0aEhMTAXjiiSe4/PLLmTx5MhdeeCEpKSm8+eabBkfdMqp9PjZX1QKQ6Yw0OBoRyIyJ5INhvTgvNgqfzcZ7JeUsKiqjxuc3OjQRaePe31jfGuHSc1I04ZCIBMVF2nnmhkzsFjNLNxfy5PIdRockIiIiArSBicgWLlx4wvGwsDDmz5/P/PnzWyii0LGuvAZvAFLtNtLDbEaHIwJAot3G64O6c96zL5Pbdwjba1zsrzvE2PhoekaGnXDfW++e22iLj8SoSJ56RBOYicix6jy+YD9btUYQke/K7NyBP1zTn1//ewNPLd9BWkwY143IMDosERERaedafdJWjs9td/B1ZX2V7cjYSE24IiHFajbRbctXnD96DEtKyjnk8fFOcTmdK2u5MK7xGd2P9mo+nvWPKWErIse3fGsRlXVe0mLCGNk1zuhwRCQEXTssnX2Hqpn/8S5+89ZGYiPsXNq/8YmLRURERJpbq2+PIMe3v2d/PIEASXYr3cLtRocjclwpDhs3pMUzIiYCM7Cvzs0/8w6zddgF7Kt1GR2eiLQRb64/AMA1QzuqNYKINOpX43pz7bBO+AMwe8F6lmwqMDokERERaceUtG2DCl0eDvQ4B4BRMaqyldBmNZm4oEM00zvG0zvCAUBB556MWrOVGzbsZllJOb6AJgURkTNTUuVixTfFAFwzpJPB0YhIKPF4PA0Wr9fL/Zf34fIBKXj9AWYvWM9/1uXi8Xjw+XxGhysiIiLtjNojtEGP7S3Ab7WS6rDR40gS7Kj167O5fvatx93vqw0bGNoSAYocR6zNyuVJsQxzeXj/qw0cTunEh4cq+PBQBR0dNiYmxlKakII/EMB8nB8iGvu7rV63Iu3bf3Py8PkDDEqPpUdS4+1XRKT98Pt8YDITGdnIRL0mM/GX3UZU/9Hc8e+N/GTWHCIPrGF/7j4sFkvLBisiIiLtlpK2bcyO6jpeyz8EwIUdoo6psnVjbrQn6Jop1zZ7fCInk+KwMejzD3jo0T/ySl4JC/MPc9Dl4bkDxfC9y9i2v5jOYXYywu1khNmJsVowmUyN/t1Wr1uR9svvD/Damn0A/CBTVbYiUi8Q8EPAz8NvZ2OzOxrZJsBnu0r5+mAFHS6eTvW2HpTXuIiLjmjhaEVERKS9UtK2DQkEAtyz4yC+AMTn5dKpS7LRIYmcsW4RDu7v0ZG7uqay4nAFS0rKeWtfPnWOMLbXuNheU9/zNtpiJiPcjnfQMKq8PqKsqoARkXqf7Sxhd0k10Q4r1wzpaHQ4IhJiLFYrFqut0fGL+iQTG+ng0x3FRPa5gKufWcPTUzLp3zGmBaMUERGR9ko9bduQxSXlrCytxGE20XPDWqPDEWkSERYzlyXG8lTfzpz73v/jhykdyIqNpKPDhhmo9PnZXFWH59pp/O1ACa/mHWJdeTUVXvWeE2nv/rF6LwDfH9aJSId+pxaR0zc4PZZJg1PxlheRe7iWSc+s4rlPduH1+Y0OTURERNo4PcG0EVVeH/ftOAjAL9KTyKmuNDgikaZnDgToFGanU5idc2PB4w9w0OVmX62b7K3bCHTMoNDtpdBdxcrSKjo5bMSmZjTaB1dE2q7cQzUs31YEwI2jOgfX+3w+/P5TS7Z4PJ5miU1EWpcUp4P8l29l6vxlfPzNIR5evI031x/kwSv7Mjg99rj7mM1m9b8VERGRs6KkbRvxwK48Dro8ZITZuaVzMjOMDkhardY0WZ3NbKJLuIMu4Q42P/1HfvyPhXxTXcf26joOuDz1y7ljufCLbfw8PYkfpHTAYdYLBiLtwTMrdxIIwPd6JdItsX4CMp/PR3pGZ/LzDp7WsQIBVdSJtGd+nw+/q4aXZ2QRNfASYi+azrYC+P7f1lCVs5Syz17DX1PWYJ/UtI6auExERETOipK2rditd8+luKqaw0lpfH3BpQDELX2bGa8VhFxyTVqPpp6srrEkcHP8HY2wmBnsjGCwM4IKr4+vK2tYX1zKTuBX2/fz1L5Cfts9lSsTY4+ZpE9E2o4DpTX8O/sAALeO6RFc7/f7yc87yCPv5GCxnvwrkLuult9OGk4gEGi2WEUk9H134rJat4/Pdx9mW2E10UMmEDfsMoZ0imFwJyd2qxmf18vdVw7G7/craSsiIiJnTEnbVqy4qpo+t93FP/MOgc/P4OhwxkybDpxZck2kOTSWBG7uv6NOq4ULOkTj+MezjL3jbp7JLSa3zs3PNu/jeWcx9/foSGZMZLPGICLGeHblLjy+AOf1iCezc9wx4yebfOh/26k9goj8z9H/d0RZbYzvn0b/jrV8urOYwgoXX+wrY2NeJcO6dKBfcoTRoYqIiEgboPeEW7EAsKSknCqfnw5WCxd0iDI6JJGQY/V6+Vl6Ep+P6sOdXVIIN5tZV1HDxPU7+OXWXIrdSsqItCV7Sqp5/cv9ANw6uqfB0YhIW9axQzg/HJbOZf1TiAm3Uevx8emOEv6x9gDOEZOodnmNDlFERERaMSVtW7F9fQaxp9aN1QRXJMVgV69OkUZFWizc0TWF1aP6cl1KfeXd6wWHOW/tVv5+oBivX68/i7QFDy7agscX4KLeiYzsFm90OCLSxplMJnomR3PjqM6M6ZOEM8xKrcdPh4t/wsWPf8rTK3ZSpeStiIiInAG1R2il3i0qY885mQCMjnOSaD/5a54iAikOG0/2zeDGtHhu+HgtpTFx3LPjIPO+3EivnNXEHiokMSqSpx6ZZ3SoInKaPt5exEfbirCaTdx7eT+jwxGRdsRiNtG/Ywx9U51szStlyZqNlJLGo0u289wnu5lxXlemZnUhJkLf2UVEROTUKGnbCn1ZXs2tW/cBMDQ6ggHR4QZHJBK6GpsIDcC/cSNjn/o7n5VVUR0bx1cXTaRfZBju119s4ShF5GxV1nm4561NAEw/rwvdE9UySERansVsom9KNC8+/3P+tXY3z6zcw+6Sah5b9g3PrtzFD4dn8JPzu9Cpg/reioiIyIkpadvKbKqsYcqGXdT6A8Tl7+d7nTONDkkkpDU2ERrUT4Y2yBlBz8gwPiutYmNVLVuq6+CSSYx8+iUyvtmE1duw562qcEVC0+/f2cLBslrS48L55dheRocjIu1dwM/Vg9OYlJnBog15PLNiF9sKKnnx8z28snovlw9M5aYLutG/Y4zRkYqIiEiIUtK2FdlQWcN1X++iwutnZEwkjrc/xpw1zOiwRFq9CIuZcQlOBkSHs/xQBYWEsa/vEArPGcowZyRDnOHBntHrH1PCViTUvP3VQf6z/gBmEzxx7WCiHPp6IyLG83g82IDLzkliQr9EPtt5iL9/tpdVuw/z35w8/puTx7nd4vjp+V04r3s8VqsFi8VidNgiIiISIvRU00qsKq1i2sbdVPr8DIoO558Du/EznyY1EGlKqQ4bU1Lj+Ou8h4ma9jMOe3x8VlbFF+XVDIgOZ0i0XmUUCTXZ+w7z6/9sAGDWxT0Y1iXO4IhEpL3z+3xgMhMZGXnccXtyd5zDryGi7wWs2n2YVbsP4ynNw7RnDev+9RdSYvV9Q0RERJS0bRVeyzvE3d8cwBMIkBUbyT8GdCPaql/hRZqDyWTCsvlrpqXFs626jjVl1ZR6fWRX1LC+oob4rDG8X1zGmHhnsPpWRIyxvaCSm/6Rjdvr55J+ydymtggiEgICAT8E/Dz8djY2u6PR7SrqvHx9oIItBZXQIQ06TOL8R1cwpm8S143I4MKeiVjMphaMXEREREKJkrYhrNrn494dB1mQfxiAKxJjeapvBuEWJYqkbWts8rCvNmxgaAvFYDaZ6BcVTt/IMPbWusmuqGFfnZuStM5M37SXOJuFq5M6MDExhpExUVj1UCXSojYcKGPqi19QVuNhQMcY/nzdYCU3RCSkWKxWLFZbo+Mdomxc1Cec83omsi2/jMUffUZYx74s3VzI0s2FJEQ5mNA/hYkDUxneJU7/jxMREWlnlLQNUZ+VVvLr7QfYXevCBPyqSwpzuiRjMunLmrR9jU0etmbKtS0ei8lkomuEg64RDg65vSxfsQJX/yEUub28eLCEFw+WEGu1MCbeyUVx0YyIiSQjzK7/VkWa0Rvr9nPvfzdR5/EzOD2WV6aPIMKurzQi0jrZLGb6pUTz0qt3smn/If79VT5vfXWQkioX/1yzj3+u2Ud8pJ0Leibwvd6JXNAzkYSoxit4RUREpG3QE06I2VPj4tE9+bxVVAbU99j8a98MzusQbWxgIkK83UqPjV/yz5tu4JPSSt4qKmX5oQoOe3z8p7CU/xSWApBot5LpjKBnRBhdw+sTvqkOG7FWC06rBfORhO6td8+luKr6uOdKjIrkqUc06ZnIt+WX1/KHRVt5b2M+/7+9ew+Lqtr7AP6dGZgBUVBBuYUgKomKmHb0oJl5OaKZl+xJ5XiILmad9JShJGZERnlJLUxNX03Tp/coXlJPrxgeQq1UxOSikgSoIB4FBJOL3Oa23j/MOSEIbC4zA3w/z7OfgTVrr/1bi5m99lrsCwA86dUNX8wezAePEVGb4eXYCeGTu+Ldp71x+sptRF+4iZjUPNwuU+NQyk0cSrkJABjgaouRfbrhTx5d8JhbF3SxUZo4ciIiImpuHOWYASEEUkor8OV/CnDo1h3oBCADEOTqgCU9nWBnyT8TkTmxkMswxt4WY+xtoRMCicVleOeb/8NNu64o7eyAAjUQU1iCGJTUWFcGwNZCgQ4KOYqGT0BHe3tYymSwkMnuvcoBS5kMGSmJ+OjKTdhZKOCgtICDpQXs//BqI/Hp0g9OEAvIoLW0RKcuXfCPBQtQodNDIwTUegGdELCUy7F12zaUlJXDQlMFy6oqWKorIReCE8pkdLnFFdj2Uxb+mZCDCo0OchmwYJwX5o/uDTkvFyaiNshSIccor24Y5dUNH03zQVLOHfyQUYAfMwrwy80SpN64t2z6Pb+ngw0e62GHx9w6Y4CLLXp3s4HKsvqxglwuh0Li8QMRERGZTruaDdy4cSNWr16NvLw8+Pr6Yv369Rg6dKhJYtELgdS7FYi7XYKD+UXIKK80vDe2qy1CPZ3gwyfVE5k9hUyGoZ07wjk5HpMWLoFWL5Cv1iCvSoMirQ53NDrkFxZCbtcZ5To9BIBirQ7FWh3QyQ4Vam3tBffujw05tx66XWu5HA5KC9hbWlR7tZLLIAAIAWiEQIlWhyKtDj8NegJKN3dU6QUq9XpU6oWhrO8SM2vfyJ9G10iykstgcbsAdy9mwc1aCTcrJXpY/f5qrZQ8mUzmw5z6SCEErv9WgZ8uFyAmNQ+nLhfi/kf2cfcuWDa1P/q72JkkNiKilqTRaGqkyQAMcbPFEDdbBI/thcK7VfgxowCLVn8JfRc3WNq74WphGa4WluGbpHtn4gq9Dprb16G+lQXNratQF+agi0KDa78kwrKdnxAitb/bt28fwsLCkJ2djT59+mDVqlV4+umnjRgxERG1V+2mx96zZw+Cg4OxefNmDBs2DJGRkfD390d6ejq6d+/e4tvPq9LgTNFdnC8tx4XSClwoLUepTm94X67Xodv1LDxy+Rfoi25j+R/WTbtwAd4DB9Yo05gPZSKihrGQy+BqpYSr1X8vU0z652bs3vA51Ho9irU6FGl0qNDrsXjNZ/CcORsavYBWCGiE+P1n4MzB/Rg4dToqdXqU6/Uo1+lRodOjTK2GXmGBCr0e1yvVuF6pblhgjq5ALRPECo0aTh1t0EEhh0ouh6VMBoUMUAuBK/+5AUv7bqjS61Hx+4xZpV4AXRxwpLC41s10U1rA3UoJd2sVevw+ketupYKrlSXsLS1go5Dzfr9myNR9ZHG5Bkcv5SEttwS/5pbi17wS3CmvPnHxZ8+ueG1ULzzl1c3wGdLpdNDr9bUVWavaJkOIiMyBXqcDZHLY2NhIWm/Fv5KggQJ5JVXIK65CfmkVCu6qUaUFlN08oOzmAfT/7z9hPzqShmVTfZo5+tZDan93+vRpBAQEYMWKFXjmmWewa9cuTJs2DUlJSRgwYIAJakBERO1Ju5m0/fTTT/Hqq6/ipZdeAgBs3rwZ0dHR2L59O0JDQ1t8+4cLivBe5o1qaQqNBl0KbsLhZg5uxh7B3/5nOzBqRI11z8yeYTYPZSJq75KSEhEw/80a6XX9E+Vh62RduIAxL75c6zqJ30dj9EtBNdPXrsDWyM9wW6NFoVpreC1Ua7H/xA8o0+oggwCEgEwIWGjUsFSrcePKZYz/+3xYyWWwksthpbj3+tXfnofX4CG1xpBz4QJe2bkbwL2rA6r0AmU6PZL2RWHWiy8aJo1zKtTIqVSjWKtDgVqLArUW50rKay3TUiZDF0sFulpaoLOFAkq5DEq5HCr5vdtDWMplkAGGs4X/SPy+APfOxKyR9vtraE9neHbgA1qkMHUfWVKpwTv7L1RLs5DLMMjNDk/2ccAkHyf06Hrv6hOt9t4/H3Q6HTx79UbuzRs1yquPEA2f6CUiMgYh9IDQY/mhRFgq6+/D1JUVWDr9T5ArFOiotEJvayv0drxflsDdKi0K7lahsFSNwrtVuH23CrdLy9HTQdqkcFsjtb9bt24dJkyYgJCQEABAREQEYmNjsWHDBmzevNmosRMRUfvTLiZt1Wo1EhMTsWTJfyc+5XI5xo0bh/j4+Br5q6qqUFVVZfi9uPjeGWUlJTXvT9lQXtBigEyPgovJ8B7yOLqrLNDVwhoKJzvAxxtf7tuFytLSWtfVa7W1vvewdK5jHuuYQwxcp/nXqdTq0W/u/Brpp+cENes6D4tBq1ZDlJehK4CuMgBKGaC0BGCJn04fg+/84FrL+3L3TrjOnQvo/pumqSO22uKTAegIIOvb/fgu54oh3Q6ADwCNhSUu5t3CyHeWolirQ6lWb7gVRGlVFfQKC1QByPt9aSmzbVVw0DZuUHp/Py8enDFuw6T2kUDz95O2CoERPaxx4v/2o+jaJWgKc6C5fR1X9Fp8A+CtOtZ973+PwcKiYQ/gUVdVYXnQWNwtvtPgSREAKCspapH8xtgGY2JMjKl1xVRZfhc6bf1XBdS3DTkARyXgaC8D7K2g01rgg1kTMH5hXpPGNK25n2xMfxcfH4/g4OrHVv7+/jh06NBDt9MSY0kiIjJ/LdJHinbgxo0bAoA4ffp0tfSQkBAxdOjQGvnDw8Pvn7zFhQsXLlza4XL9+nVjdVEmJ7WPFIL9JBcuXLi096U19pON6e8sLS3Frl27qqVt3LhRdO/e/aHbYR/JhQsXLu17uXLlStM7rd+1izNtpVqyZEm1/6jq9Xr89ttvsLe3r/NejCUlJXBzc8P169dha2trjFDbFLZf07D9mo5t2DRtof2EECgtLYWLi4upQzFrje0n69IWPj91acv1a8t1A1i/1q4t188UdWM/Wb8H+8iioiK4u7sjJycHdnZ2JoysdWjL39mWwPaShu0lDdtLmuLiYvTo0QNdu3ZttjLbxaStg4MDFAoF8vPzq6Xn5+fDycmpRn6VSgWVqvplRp07d27w9mxtbfmBbgK2X9Ow/ZqObdg0rb392tuASmofCTS9n6xLa//81Kct168t1w1g/Vq7tlw/Y9ettfaTjenvnJycJOUHau8jgXvt1lY/gy2hLX9nWwLbSxq2lzRsL2nkcnnzldVsJZkxpVKJIUOGIC4uzpCm1+sRFxcHPz8/E0ZGRERkWuwjiYioPWhMf+fn51ctPwDExsayfyQiIqNoF2faAkBwcDCCgoLw+OOPY+jQoYiMjERZWZnhyaFERETtFftIIiJqD+rr71544QW4urpixYoVAIC33noLo0aNwtq1azFp0iRERUXh3Llz2LJliymrQURE7US7mbSdOXMmCgoK8P777yMvLw+DBg1CTEwMHB0dm20bKpUK4eHhtV4OQ/Vj+zUN26/p2IZNw/ZrvYzRR9anrX9+2nL92nLdANavtWvL9WvLdWsp9fV3OTk51S5rHT58OHbt2oX33nsP7777Lvr06YNDhw5hwIABDd4m/07SsL2kYXtJw/aShu0lTUu0l0wIIZqtNCIiIiIiIiIiIiJqknZxT1siIiIiIiIiIiKi1oKTtkRERERERERERERmhJO2RERERERERERERGaEk7ZEREREREREREREZoSTthJt3LgRHh4esLKywrBhw3D27NmH5t26dStGjhyJLl26oEuXLhg3blyd+dsDKe33R1FRUZDJZJg2bVrLBmjmpLZfUVER5s2bB2dnZ6hUKnh5eeHIkSNGitY8SW3DyMhIPProo7C2toabmxvefvttVFZWGila8/Ljjz9i8uTJcHFxgUwmw6FDh+pd58SJExg8eDBUKhV69+6NHTt2tHic1LrodDqEhYWhZ8+esLa2Rq9evRAREYG28pzU0tJSLFiwAO7u7rC2tsbw4cPx888/mzqsRqlvHyCEwPvvvw9nZ2dYW1tj3LhxyMzMNE2wjVBf/Q4cOIDx48fD3t4eMpkMKSkpJomzseqqn0ajweLFi+Hj4wMbGxu4uLjghRdewM2bN00XsAT1/e0++OAD9O3bFzY2NoZj8oSEBNME2whS+t/XX38dMpkMkZGRRouPpB9f7tu3D3379oWVlRV8fHza3fE5x9TScAwtDcfM0nB83HCmGA9z0laCPXv2IDg4GOHh4UhKSoKvry/8/f1x69atWvOfOHECAQEBOH78OOLj4+Hm5obx48fjxo0bRo7cPEhtv/uys7OxaNEijBw50kiRmiep7adWq/GXv/wF2dnZ2L9/P9LT07F161a4uroaOXLzIbUNd+3ahdDQUISHhyMtLQ3btm3Dnj178O677xo5cvNQVlYGX19fbNy4sUH5s7KyMGnSJIwePRopKSlYsGAB5syZg6NHj7ZwpNSarFq1Cps2bcKGDRuQlpaGVatW4ZNPPsH69etNHVqzmDNnDmJjY/H111/j4sWLGD9+PMaNG9cqjwXq2wd88skn+Pzzz7F582YkJCTAxsYG/v7+reZAvr76lZWV4YknnsCqVauMHFnzqKt+5eXlSEpKQlhYGJKSknDgwAGkp6djypQpJohUuvr+dl5eXtiwYQMuXryIkydPwsPDA+PHj0dBQYGRI22chva/Bw8exJkzZ+Di4mKkyAiQfnx5+vRpBAQE4JVXXkFycjKmTZuGadOmITU11ciRmwbH1NJwDC0Nx8zScHwsjUnGw4IabOjQoWLevHmG33U6nXBxcRErVqxo0PparVZ06tRJ7Ny5s6VCNGuNaT+tViuGDx8uvvzySxEUFCSmTp1qhEjNk9T227Rpk/D09BRqtdpYIZo9qW04b948MWbMmGppwcHBYsSIES0aZ2sAQBw8eLDOPO+8847o379/tbSZM2cKf3//FoyMWptJkyaJl19+uVra9OnTxezZs00UUfMpLy8XCoVCHD58uFr64MGDxdKlS00UVfN4cB+g1+uFk5OTWL16tSGtqKhIqFQqsXv3bhNE2DR17eOysrIEAJGcnGzUmJpTQ/bhZ8+eFQDEtWvXjBNUM2lI3YqLiwUA8f333xsnqGb0sPr95z//Ea6uriI1NVW4u7uLzz77zOixtVdSjy9nzJghJk2aVC1t2LBh4rXXXmvROM0Fx9TScAwtDcfM0nB83HjGGg/zTNsGUqvVSExMxLhx4wxpcrkc48aNQ3x8fIPKKC8vh0ajQdeuXVsqTLPV2Pb78MMP0b17d7zyyivGCNNsNab9vv32W/j5+WHevHlwdHTEgAEDsHz5cuh0OmOFbVYa04bDhw9HYmKi4RKRq1ev4siRI3j66aeNEnNrFx8fX629AcDf37/B+0xqH4YPH464uDhkZGQAAM6fP4+TJ09i4sSJJo6s6bRaLXQ6HaysrKqlW1tb4+TJkyaKqmVkZWUhLy+v2nfezs4Ow4YN43e+lSouLoZMJkPnzp1NHUqzUqvV2LJlC+zs7ODr62vqcJqFXq9HYGAgQkJC0L9/f1OH06405viyPR8fcUwtDcfQ0nDMLA3Hxy2vOfb3Fs0dVFtVWFgInU4HR0fHaumOjo749ddfG1TG4sWL4eLiUuOP1h40pv1OnjyJbdu2tbp7xrWExrTf1atXcezYMcyePRtHjhzB5cuX8cYbb0Cj0SA8PNwYYZuVxrThX//6VxQWFuKJJ56AEAJarRavv/56u7n8o6ny8vJqbe+SkhJUVFTA2traRJGROQkNDUVJSQn69u0LhUIBnU6Hjz/+GLNnzzZ1aE3WqVMn+Pn5ISIiAt7e3nB0dMTu3bsRHx+P3r17mzq8ZpWXlwcAtX7n779HrUdlZSUWL16MgIAA2NramjqcZnH48GHMmjUL5eXlcHZ2RmxsLBwcHEwdVrNYtWoVLCws8Oabb5o6lHanMceXDzs+ag/7So6ppeEYWhqOmaXh+LjlNcd4mGfaGsnKlSsRFRWFgwcP1jjjhmoqLS1FYGAgtm7d2mYOqI1Nr9eje/fu2LJlC4YMGYKZM2di6dKl2Lx5s6lDazVOnDiB5cuX44svvjDc4y86OhoRERGmDo2ozdi7dy/++c9/YteuXUhKSsLOnTuxZs0a7Ny509ShNYuvv/4aQgi4urpCpVLh888/R0BAAORyHoKRedJoNJgxYwaEENi0aZOpw2k29+8nd/r0aUyYMAEzZsyo956QrUFiYiLWrVuHHTt2QCaTmTocohbFMXXdOIaWjmNmaTg+Nj6eadtADg4OUCgUyM/Pr5aen58PJyenOtdds2YNVq5cie+//x4DBw5syTDNltT2u3LlCrKzszF58mRDml6vBwBYWFggPT0dvXr1atmgzUhjPn/Ozs6wtLSEQqEwpHl7eyMvLw9qtRpKpbJFYzY3jWnDsLAwBAYGYs6cOQAAHx8flJWVYe7cuVi6dCknXerh5ORUa3vb2tryLFsyCAkJQWhoKGbNmgXg3vfs2rVrWLFiBYKCgkwcXdP16tULP/zwA8rKylBSUgJnZ2fMnDkTnp6epg6tWd3fj+bn58PZ2dmQnp+fj0GDBpkoKpLq/oTttWvXcOzYsTZzli0A2NjYoHfv3ujduzf+/Oc/o0+fPti2bRuWLFli6tCa5KeffsKtW7fQo0cPQ5pOp8PChQsRGRmJ7Oxs0wXXDjTm+PJhx0f1jSnbAo6ppeEYWhqOmaXh+LjlNcd4mC3aQEqlEkOGDEFcXJwhTa/XIy4uDn5+fg9d75NPPkFERARiYmLw+OOPGyNUsyS1/fr27YuLFy8iJSXFsEyZMsVwloSbm5sxwze5xnz+RowYgcuXLxs6agDIyMiAs7Nzm+58HqYxbVheXl6j47nfod+79zjVxc/Pr1p7A0BsbGyd+0xqfx72PfvjvqstsLGxgbOzM+7cuYOjR49i6tSppg6pWfXs2RNOTk7VvvMlJSVISEjgd76VuD9hm5mZie+//x729vamDqlF6fV6VFVVmTqMJgsMDMSFCxeqHTO7uLggJCRE2tOpqVEac3zZno+POKaWhmNoaThmlobj45bXLPt7ac9Ha9+ioqKESqUSO3bsEJcuXRJz584VnTt3Fnl5eUIIIQIDA0VoaKgh/8qVK4VSqRT79+8Xubm5hqW0tNRUVTApqe33oPb25MsHSW2/nJwc0alTJzF//nyRnp4uDh8+LLp37y4++ugjU1XB5KS2YXh4uOjUqZPYvXu3uHr1qvj3v/8tevXqJWbMmGGqKphUaWmpSE5OFsnJyQKA+PTTT0VycrLhyeKhoaEiMDDQkP/q1auiQ4cOIiQkRKSlpYmNGzcKhUIhYmJiTFUFMkNBQUHC1dVVHD58WGRlZYkDBw4IBwcH8c4775g6tGYRExMjvvvuO8M+xNfXVwwbNqxVPqW4vn3AypUrRefOncW//vUvceHCBTF16lTRs2dPUVFRYeLIG6a++t2+fVskJyeL6OhoAUBERUWJ5ORkkZuba+LIG6au+qnVajFlyhTxyCOPiJSUlGrHrVVVVaYOvV511e3u3btiyZIlIj4+XmRnZ4tz586Jl156SahUKpGammrq0Bukvs/mg9zd3cVnn31m3CDbManHl6dOnRIWFhZizZo1Ii0tTYSHhwtLS0tx8eJFU1XBqDimloZjaGk4ZpaG42NpTDEe5qStROvXrxc9evQQSqVSDB06VJw5c8bw3qhRo0RQUJDhd3d3dwGgxhIeHm78wM2ElPZ7UHvrcGojtf1Onz4thg0bJlQqlfD09BQff/yx0Gq1Ro7avEhpQ41GIz744APRq1cvYWVlJdzc3MQbb7wh7ty5Y/zAzcDx48dr3afdb7OgoCAxatSoGusMGjRIKJVK4enpKb766iujx03mraSkRLz11luiR48ewsrKSnh6eoqlS5e2iomihtizZ4/w9PQUSqVSODk5iXnz5omioiJTh9Uo9e0D9Hq9CAsLE46OjkKlUomxY8eK9PR00wYtQX31++qrr1r1cV1d9cvKyqr1PQDi+PHjpg69XnXVraKiQjz77LPCxcVFKJVK4ezsLKZMmSLOnj1r6rAbrL7P5oM4aWt8Uo/R9+7dK7y8vIRSqRT9+/cX0dHRRo7YtDimloZjaGk4ZpaG4+OGM8V4WCYEz2EmIiIiIiIiIiIiMhe8py0RERERERERERGRGeGkLREREREREREREZEZ4aQtERERERERERERkRnhpC0RERERERERERGRGeGkLREREREREREREZEZ4aQtERERERERERERkRnhpC0RERERERERERGRGeGkLREREREREREREZEZ4aQtURvm4eGByMjIBufPzs6GTCZDSkpKi8VERERkLpq732uu8qT230RERETU9nDSloia3VNPPYUFCxaYOgwiIiIiIiIiolaJk7ZEREREREREREREZoSTtkRmbv/+/fDx8YG1tTXs7e0xbtw4lJWV1Xo267Rp0/Diiy8+tCyZTIZNmzZh4sSJsLa2hqenJ/bv318j39WrVzF69Gh06NABvr6+iI+PN7x3+/ZtBAQEwNXVFR06dICPjw92795teP/FF1/EDz/8gHXr1kEmk0EmkyE7OxsAkJqaiokTJ6Jjx45wdHREYGAgCgsL660rERFRY8XExOCJJ55A586dYW9vj2eeeQZXrlx5aP5ffvkFzzzzDGxtbdGpUyeMHDnSkF+v1+PDDz/EI488ApVKhUGDBiEmJqZGGXX1owDwzTffoH///lCpVPDw8MDatWubt9JERERE1Opx0pbIjOXm5iIgIAAvv/wy0tLScOLECUyfPh1CiEaXGRYWhueeew7nz5/H7NmzMWvWLKSlpVXLs3TpUixatAgpKSnw8vJCQEAAtFotAKCyshJDhgxBdHQ0UlNTMXfuXAQGBuLs2bMAgHXr1sHPzw+vvvoqcnNzkZubCzc3NxQVFWHMmDF47LHHcO7cOcTExCA/Px8zZsxosboSERGVlZUhODgY586dQ1xcHORyOZ599lno9foaeW/cuIEnn3wSKpUKx44dQ2JiIl5++WVDH7hu3TqsXbsWa9aswYULF+Dv748pU6YgMzOzWjl19aOJiYmYMWMGZs2ahYsXL+KDDz5AWFgYduzY0eJtQURERESth4WpAyCih8vNzYVWq8X06dPh7u4OAPDx8WlSmc8//zzmzJkDAIiIiEBsbCzWr1+PL774wpBn0aJFmDRpEgBg2bJl6N+/Py5fvoy+ffvC1dUVixYtMuT9xz/+gaNHj2Lv3r0YOnQo7OzsoFQq0aFDBzg5ORnybdiwAY899hiWL19uSNu+fTvc3NyQkZGBu3fvNntdiYiInnvuuWq/b9++Hd26dcOlS5fQsWPHau9t3LgRdnZ2iIqKgqWlJQDAy8vL8P6aNWuwePFizJo1CwCwatUqHD9+HJGRkdi4caMhX1396KeffoqxY8ciLCzMUP6lS5ewevXqOq+WISIiIqL2hWfaEpkxX19fjB07Fj4+Pnj++eexdetW3Llzp0ll+vn51fj9wTNtBw4caPjZ2dkZAHDr1i0AgE6nQ0REBHx8fNC1a1d07NgRR48eRU5OTp3bPX/+PI4fP46OHTsalr59+wIArly50iJ1JSIiyszMREBAADw9PWFrawsPDw8AqLXfSklJwciRIw0Ttn9UUlKCmzdvYsSIEdXSR4wYIakfTUtLq7WMzMxM6HQ66RUkIiIiojaJk7ZEZkyhUCA2Nhbfffcd+vXrh/Xr1+PRRx9FVlYW5HJ5jVsHaDSaZtnuHwerMpkMAAyXka5evRrr1q3D4sWLcfz4caSkpMDf3x9qtbrOMu/evYvJkycjJSWl2pKZmYknn3yyzroSERE11uTJk/Hbb79h69atSEhIQEJCAgDU2m9ZW1s3yzbr6keJiIiIiBqCk7ZEZk4mk2HEiBFYtmwZkpOToVQqcfDgQXTr1g25ubmGfDqdDqmpqfWWd+bMmRq/e3t7NzieU6dOYerUqfjb3/4GX19feHp6IiMjo1oepVJZ42yhwYMH45dffoGHhwd69+5dbbGxsamzrkRERI1x+/ZtpKen47333sPYsWPh7e1d51UcAwcOxE8//VTrP0FtbW3h4uKCU6dOVUs/deoU+vXr1+CYvL29ay3Dy8sLCoWiweUQERERUdvGSVsiM5aQkIDly5fj3LlzyMnJwYEDB1BQUABvb2+MGTMG0dHRiI6Oxq+//oq///3vKCoqqrfMffv2Yfv27cjIyEB4eDjOnj2L+fPnNzimPn36IDY2FqdPn0ZaWhpee+015OfnV8vj4eGBhIQEZGdno7CwEHq9HvPmzcNvv/2GgIAA/Pzzz7hy5QqOHj2Kl156CTqdrs66EhERNUaXLl1gb2+PLVu24PLlyzh27BiCg4Mfmn/+/PkoKSnBrFmzcO7cOWRmZuLrr79Geno6ACAkJASrVq3Cnj17kJ6ejtDQUKSkpOCtt95qcEwLFy5EXFwcIiIikJGRgZ07d2LDhg3V7hdPRERERMQHkRGZMVtbW/z444+IjIxESUkJ3N3dsXbtWkycOBEajQbnz5/HCy+8AAsLC7z99tsYPXp0vWUuW7YMUVFReOONN+Ds7Izdu3dLOkPovffew9WrV+Hv748OHTpg7ty5mDZtGoqLiw15Fi1ahKCgIPTr1w8VFRXIysqCh4cHTp06hcWLF2P8+PGoqqqCu7s7JkyYALlcXmddiYiIGkMulyMqKgpvvvkmBgwYgEcffRSff/45nnrqqVrz29vb49ixYwgJCcGoUaOgUCgwaNAgwz1o33zzTRQXF2PhwoW4desW+vXrh2+//RZ9+vRpcEyDBw/G3r178f777yMiIgLOzs748MMP+RAyIiIiIqpGJh68KSYRtVkymQwHDx7EtGnTTB0KERERERERERE9BG+PQERERERERERERGRGOGlLREREREREREREZEZ4T1uidoR3QyEiIiIiIiIiMn8805aIiIiIiIiIiIjIjHDSloiIiIiIiIiIiMiMcNKWiIiIiIiIiIiIyIxw0paIiIiIiIiIiIjIjHDSloiIiIiIiIiIiMiMcNKWiIiIiIiIiIiIyIxw0paIiIiIiIiIiIjIjHDSloiIiIiIiIiIiMiM/D/M9hOy4L5udwAAAABJRU5ErkJggg==\n" + }, + "metadata": {} + } ], - "text/plain": [ - " Feature Anderson-Darling p-value Anderson-Darling Normality \\\n", - "0 fixed acidity 0.786 Se acepta la H0 \n", - "1 volatile acidity 0.786 Se acepta la H0 \n", - "2 citric acid 0.786 Se acepta la H0 \n", - "3 residual sugar 0.786 Se acepta la H0 \n", - "4 chlorides 0.786 Se acepta la H0 \n", - "5 free sulfur dioxide 0.786 Se acepta la H0 \n", - "6 total sulfur dioxide 0.786 Se acepta la H0 \n", - "7 density 0.786 Se acepta la H0 \n", - "8 pH 0.786 Se acepta la H0 \n", - "9 sulphates 0.786 Se acepta la H0 \n", - "10 alcohol 0.786 Se acepta la H0 \n", - "11 quality 0.786 Se acepta la H0 \n", - "\n", - " Skewness Skewness Interpretation \n", - "0 0.647553 Sesgo a la derecha \n", - "1 1.576497 Sesgo a la derecha \n", - "2 1.281528 Sesgo a la derecha \n", - "3 1.076764 Sesgo a la derecha \n", - "4 5.021792 Sesgo a la derecha \n", - "5 1.406314 Sesgo a la derecha \n", - "6 0.390590 Sesgo a la derecha \n", - "7 0.977474 Sesgo a la derecha \n", - "8 0.457642 Sesgo a la derecha \n", - "9 0.976894 Sesgo a la derecha \n", - "10 0.487193 Sesgo a la derecha \n", - "11 0.155749 Sesgo a la derecha " + "source": [ + "#Construcción de histogramas\n", + "import seaborn as sns\n", + "\n", + "fig, axes = plt.subplots(4, 3, figsize=(14, 14))\n", + "\n", + "for i, column in enumerate(column_names[:-1]):\n", + " row = i // 3 # Índice de fila\n", + " col = i % 3 # Índice de columna\n", + " sns.histplot(white_wine_df[column], kde=True, ax=axes[row, col], color= (list(plt.rcParams['axes.prop_cycle'])*2)[i][\"color\"])\n", + "\n", + "plt.tight_layout()\n", + "plt.show()\n" ] - }, - "execution_count": 11, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# DataFrame para almacenar los resultados \n", - "results = pd.DataFrame(columns=[\"Feature\", \"Anderson-Darling p-value\", \"Anderson-Darling Normality\", \"Skewness\", \"Skewness Interpretation\"])\n", - "\n", - "# nivel de significancia \n", - "alpha = 0.05\n", - "\n", - "for feature in column_names:\n", - " data = white_wine_df[feature]\n", - " \n", - " # Prueba de Anderson-Darling\n", - " anderson_result = anderson(data)\n", - " ad_p = anderson_result.critical_values[2] \n", - " if ad_p > alpha:\n", - " ad_normality = \"Se acepta la H0\"\n", - " else:\n", - " ad_normality = \"Se rechaza la H0\"\n", - " \n", - " # Estadísticas descriptivas\n", - " stats = describe(data)\n", - " \n", - " # estadísticas de sesgo\n", - " skewness = stats.skewness\n", - " skewness_interpretation = \"Sesgo a la izquierda\" if skewness < 0 else \"Sesgo a la derecha\" if skewness > 0 else \"Sin sesgo\"\n", - " \n", - " # Agregar los resultados al DataFrame\n", - " result_df = pd.DataFrame({\n", - " \"Feature\": [feature],\n", - " \"Anderson-Darling p-value\": [ad_p],\n", - " \"Anderson-Darling Normality\": [ad_normality],\n", - " \"Skewness\": [skewness],\n", - " \"Skewness Interpretation\": [skewness_interpretation] \n", - " })\n", - " results = pd.concat([results, result_df], ignore_index=True)\n", - " \n", - "results" - ] - }, - { - "cell_type": "markdown", - "id": "74874889", - "metadata": {}, - "source": [ - "2. 3 _Matriz de correlación_: " - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "e96f442b", - "metadata": {}, - "outputs": [ + }, { - "data": { - "image/png": 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\n", 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    " + "cell_type": "markdown", + "id": "e72636f5", + "metadata": { + "id": "e72636f5" + }, + "source": [ + " 2.2 _Pruebas de distribución normal_:\n", + "Para determinar si el conjunto de datos sigue una distribución normal, utilizaremos la prueba de Anderson-Darling. Esta prueba es más efectiva para detectar desviaciones de la normalidad en las colas largas de la distribución, como se puede observar en los histogramas. Esto significa que puede identificar valores atípicos en las colas con mayor eficacia que la Prueba de Shapiro-Wilk. Además, la Prueba de Shapiro-Wilk funciona bien con tamaños de muestra generalmente inferiores a 2.000 observaciones, mientras que para el conjunto de datos del vino blanco contamos con 4.898 entradas.\n", + "\n", + "Hipótesis nula (H0): Los datos siguen una distribución normal o gaussiana.\n", + "\n", + "Hipótesis alternativa (Ha): Los datos no siguen una distribución normal" ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import seaborn as sns\n", - "\n", - "# matriz de correlación de variables independientes\n", - "x_correlation_matrix = X.corr()\n", - "\n", - "\n", - "plt.figure(figsize=(8, 8))\n", - "sns.heatmap(x_correlation_matrix, annot=True, cmap='coolwarm', fmt=\".2f\")\n", - "plt.title(\"Matriz de correlación de variables Independientes\", fontsize=14)\n", - "plt.xticks(fontsize=10)\n", - "plt.yticks(fontsize=10)\n", - "\n", - "# los ejes x e y\n", - "plt.xlabel(\"Variables\", fontsize=12)\n", - "plt.ylabel(\"Variables\", fontsize=12)\n", - "\n", - "\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "bacfa926", - "metadata": { - "scrolled": true - }, - "outputs": [ + }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "╒══════════════════════╤══════════════════════╤═══════════════╤══════════════════════╕\n", - "│ Atributo 1 │ Atributo 2 │ Correlación │ Clasificación │\n", - "╞══════════════════════╪══════════════════════╪═══════════════╪══════════════════════╡\n", - "│ fixed acidity │ pH │ -0.425858 │ Moderada correlación │\n", - "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", - "│ residual sugar │ total sulfur dioxide │ 0.401439 │ Moderada correlación │\n", - "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", - "│ residual sugar │ density │ 0.838966 │ Alta correlación │\n", - "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", - "│ residual sugar │ alcohol │ -0.450631 │ Moderada correlación │\n", - "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", - "│ chlorides │ alcohol │ -0.360189 │ Moderada correlación │\n", - "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", - "│ free sulfur dioxide │ total sulfur dioxide │ 0.615501 │ Moderada correlación │\n", - "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", - "│ total sulfur dioxide │ residual sugar │ 0.401439 │ Moderada correlación │\n", - "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", - "│ total sulfur dioxide │ free sulfur dioxide │ 0.615501 │ Moderada correlación │\n", - "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", - "│ total sulfur dioxide │ density │ 0.529881 │ Moderada correlación │\n", - "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", - "│ total sulfur dioxide │ alcohol │ -0.448892 │ Moderada correlación │\n", - "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", - "│ density │ residual sugar │ 0.838966 │ Alta correlación │\n", - "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", - "│ density │ total sulfur dioxide │ 0.529881 │ Moderada correlación │\n", - "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", - "│ density │ alcohol │ -0.780138 │ Alta correlación │\n", - "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", - "│ pH │ fixed acidity │ -0.425858 │ Moderada correlación │\n", - "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", - "│ alcohol │ residual sugar │ -0.450631 │ Moderada correlación │\n", - "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", - "│ alcohol │ chlorides │ -0.360189 │ Moderada correlación │\n", - "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", - "│ alcohol │ total sulfur dioxide │ -0.448892 │ Moderada correlación │\n", - "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", - "│ alcohol │ density │ -0.780138 │ Alta correlación │\n", - "╘══════════════════════╧══════════════════════╧═══════════════╧══════════════════════╛\n" - ] - } - ], - "source": [ - "classification = []\n", - "\n", - "for attribute in x_correlation_matrix.columns:\n", - " for other_attribute, correlation in x_correlation_matrix[attribute].items():\n", - " if attribute != other_attribute:\n", - " if abs(correlation)> 0.75:\n", - " classification.append((attribute, other_attribute, correlation, \"Alta correlación\"))\n", - " elif abs(correlation) >0.3:\n", - " classification.append((attribute, other_attribute, correlation, \"Moderada correlación\"))\n", - "\n", - "headers = [\"Atributo 1\", \"Atributo 2\", \"Correlación\", \"Clasificación\"]\n", - "table = tabulate(classification, headers=headers, tablefmt=\"fancy_grid\")\n", - "print(table)" - ] - }, - { - "cell_type": "markdown", - "id": "e23f6d25", - "metadata": {}, - "source": [ - "**Conclusión** : Se han identificado pares de variables con correlaciones altas. Una forma de abordar la multicolinealidad es eliminar una de las variables de cada par. Por ejemplo, \"residual sugar\" y \"density\" con una alta correlación. Sin embargo, antes de eliminar una variable, es importante entender la relevancia de cada variable en el contexto del problema. A veces, las variables correlacionadas pueden aportar información única y ser importantes para el modelo, para lo cual realizaremos un análisis de importancia de características o considera el conocimiento del dominio." - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "7553e929", - "metadata": {}, - "outputs": [], - "source": [ - "# Datos en conjuntos de entrenamiento y prueba (80% entrenamiento, 20% prueba)\n", - "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)" - ] - }, - { - "cell_type": "markdown", - "id": "64a07679", - "metadata": {}, - "source": [ - "2. 5 _Análisis de importancia de características_: " - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "id": "fa07be18", - "metadata": {}, - "outputs": [ + "cell_type": "code", + "execution_count": 11, + "id": "742fb977", + "metadata": { + "scrolled": true, + "colab": { + "base_uri": "https://localhost:8080/", + "height": 425 + }, + "id": "742fb977", + "outputId": "e3080098-013a-4e0d-b28c-923cbffc578c" + }, + "outputs": [ + { + "output_type": "execute_result", + "data": { + "text/plain": [ + " Feature Anderson-Darling p-value Anderson-Darling Normality \\\n", + "0 fixed acidity 0.786 Se acepta la H0 \n", + "1 volatile acidity 0.786 Se acepta la H0 \n", + "2 citric acid 0.786 Se acepta la H0 \n", + "3 residual sugar 0.786 Se acepta la H0 \n", + "4 chlorides 0.786 Se acepta la H0 \n", + "5 free sulfur dioxide 0.786 Se acepta la H0 \n", + "6 total sulfur dioxide 0.786 Se acepta la H0 \n", + "7 density 0.786 Se acepta la H0 \n", + "8 pH 0.786 Se acepta la H0 \n", + "9 sulphates 0.786 Se acepta la H0 \n", + "10 alcohol 0.786 Se acepta la H0 \n", + "11 quality 0.786 Se acepta la H0 \n", + "\n", + " Skewness Skewness Interpretation \n", + "0 0.647553 Sesgo a la derecha \n", + "1 1.576497 Sesgo a la derecha \n", + "2 1.281528 Sesgo a la derecha \n", + "3 1.076764 Sesgo a la derecha \n", + "4 5.021792 Sesgo a la derecha \n", + "5 1.406314 Sesgo a la derecha \n", + "6 0.390590 Sesgo a la derecha \n", + "7 0.977474 Sesgo a la derecha \n", + "8 0.457642 Sesgo a la derecha \n", + "9 0.976894 Sesgo a la derecha \n", + "10 0.487193 Sesgo a la derecha \n", + "11 0.155749 Sesgo a la derecha " + ], + "text/html": [ + "\n", + "
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    FeatureAnderson-Darling p-valueAnderson-Darling NormalitySkewnessSkewness Interpretation
    0fixed acidity0.786Se acepta la H00.647553Sesgo a la derecha
    1volatile acidity0.786Se acepta la H01.576497Sesgo a la derecha
    2citric acid0.786Se acepta la H01.281528Sesgo a la derecha
    3residual sugar0.786Se acepta la H01.076764Sesgo a la derecha
    4chlorides0.786Se acepta la H05.021792Sesgo a la derecha
    5free sulfur dioxide0.786Se acepta la H01.406314Sesgo a la derecha
    6total sulfur dioxide0.786Se acepta la H00.390590Sesgo a la derecha
    7density0.786Se acepta la H00.977474Sesgo a la derecha
    8pH0.786Se acepta la H00.457642Sesgo a la derecha
    9sulphates0.786Se acepta la H00.976894Sesgo a la derecha
    10alcohol0.786Se acepta la H00.487193Sesgo a la derecha
    11quality0.786Se acepta la H00.155749Sesgo a la derecha
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Cuanto mayor sea la importancia, más influencia tiene la característica en el modelo de clasificación : \n", - "\n", - "- **Alcohol** es la característica más importante, con una importancia de aproximadamente 0.1132. Se concluye que alcohol es la característica más influyente en la clasificación.\n", - "- **Density** es la segunda característica más importante, con una importancia de aproximadamente 0.1064.\n", - "- **Volatile acidity** es la tercera característica más importante, con una importancia de aproximadamente 0.1020." - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "id": "f212ceec", - "metadata": {}, - "outputs": [ + "cell_type": "code", + "source": [], + "metadata": { + "id": "s98D2ni9wrx4" + }, + "id": "s98D2ni9wrx4", + "execution_count": null, + "outputs": [] + }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "Árbol de Decisión: Accuracy = 0.61\n", - "Random Forest: Accuracy = 0.69\n", - "SVM: Accuracy = 0.56\n", - "K-NN: Accuracy = 0.54\n", - "El mejor modelo es: Random Forest\n" - ] + "cell_type": "markdown", + "source": [ + "Los **resultados** de la Evaluación de Normalidad indicaron que se encontraron distribuciones normales, lo cual respalda la aceptación de la hipótesis nula." + ], + "metadata": { + "id": "Sak_2MMRveG7" + }, + "id": "Sak_2MMRveG7" }, { - "name": "stderr", - "output_type": "stream", - "text": [ - "/home/johannadiazaguirre/anaconda3/lib/python3.9/site-packages/sklearn/neighbors/_classification.py:211: FutureWarning: Unlike other reduction functions (e.g. `skew`, `kurtosis`), the default behavior of `mode` typically preserves the axis it acts along. In SciPy 1.11.0, this behavior will change: the default value of `keepdims` will become False, the `axis` over which the statistic is taken will be eliminated, and the value None will no longer be accepted. Set `keepdims` to True or False to avoid this warning.\n", - " mode, _ = stats.mode(_y[neigh_ind, k], axis=1)\n" - ] - } - ], - "source": [ - "# Escalar características \n", - "scaler = StandardScaler()\n", - "X_train = scaler.fit_transform(X_train)\n", - "X_test = scaler.transform(X_test)\n", - "\n", - "# Modelos (excluyendo MultinomialNB)\n", - "models = [\n", - " (\"Árbol de Decisión\", DecisionTreeClassifier()),\n", - " (\"Random Forest\", RandomForestClassifier()),\n", - " (\"SVM\", SVC()),\n", - " (\"K-NN\", KNeighborsClassifier())\n", - "]\n", - "\n", - "# Entrenar y evaluar modelos\n", - "results = {}\n", - "\n", - "for model_name, model in models:\n", - " model.fit(X_train, y_train)\n", - " y_pred = model.predict(X_test)\n", - " accuracy = accuracy_score(y_test, y_pred)\n", - " results[model_name] = accuracy\n", - "\n", - "# Imprimir resultados\n", - "for model_name, accuracy in results.items():\n", - " print(f\"{model_name}: Accuracy = {accuracy:.2f}\")\n", - " \n", - "best_model_name = max(results, key=results.get)\n", - "print(f\"El mejor modelo es: {best_model_name}\")\n" - ] - }, - { - "cell_type": "markdown", - "id": "f7072776", - "metadata": {}, - "source": [ - "_Conclusión_ : \n", - "\n", - "- **Modelo: Regresión Logística**\n", - "\n", - "Precisión: 54.34% con una desviación estándar de 1.38%\n", - "La Regresión Logística ha obtenido una precisión del 54.34% en la clasificación de la calidad del vino. Esto significa que el modelo acertó en su predicción de la calidad del vino en aproximadamente el 54.34% de los casos. Sin embargo, la desviación estándar del 1.38% indica que el rendimiento del modelo puede variar en alrededor de 1.38%. En otras palabras, el modelo no es muy consistente en sus predicciones y podría no ser el más adecuado para este problema.\n", - "\n", - "- **Modelo: Árbol de Decisión**\n", - "\n", - "Precisión: 57.96% con una desviación estándar de 1.80%\n", - "El modelo de Árbol de Decisión ha logrado una precisión del 57.96% en la clasificación de la calidad del vino. Esto representa un rendimiento ligeramente mejor que el de la Regresión Logística. La desviación estándar de 1.80% muestra que el modelo puede tener una variabilidad de aproximadamente 1.80% en su rendimiento, lo que es un poco más consistente en comparación con la Regresión Logística.\n", - "\n", - "- **Modelo: Random Forest**\n", - "\n", - "Precisión: 66.03% con una desviación estándar de 2.44%\n", - "El modelo Random Forest ha obtenido la mayor precisión, con un 66.03%, lo que significa que es capaz de predecir con mayor precisión la calidad del vino en comparación con los otros modelos. La desviación estándar de 2.44% indica que el modelo puede variar en aproximadamente un 2.44% en su rendimiento, lo que sugiere una mayor consistencia que los otros modelos.\n", - "\n", - "En resumen, el modelo Random Forest ha demostrado ser el más eficaz en la clasificación de la calidad del vino, con una precisión más alta en comparación con la Regresión Logística y el Árbol de Decisión. Sin embargo, es importante recordar que la elección del modelo no se basa únicamente en la precisión; otros factores como la interpretabilidad del modelo, el tiempo de entrenamiento y la complejidad también deben ser considerados en la toma de decisiones." - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "id": "ef23761d", - "metadata": {}, - "outputs": [ + "cell_type": "markdown", + "id": "74874889", + "metadata": { + "id": "74874889" + }, + "source": [ + "2. 3 _Matriz de correlación_:\n", + "Realizamos esta tarea para descubrir las posibles conexiones entre las variables y entender cómo pueden llegar a afectar el desempeño del algoritmo. Esto nos ayuda a elegir las características de manera más eficaz, identificar y reducir posibles problemas de multicolinealidad, y mejorar en general la configuración del modelo." + ] + }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "Precisión en el conjunto de prueba: 0.69\n", - "Informe de Clasificación:\n", - " precision recall f1-score support\n", - "\n", - " 3 1.00 0.00 0.00 5\n", - " 4 0.56 0.20 0.29 25\n", - " 5 0.70 0.70 0.70 291\n", - " 6 0.66 0.79 0.72 432\n", - " 7 0.76 0.58 0.66 192\n", - " 8 0.80 0.46 0.58 35\n", - "\n", - " accuracy 0.69 980\n", - " macro avg 0.75 0.45 0.49 980\n", - "weighted avg 0.70 0.69 0.68 980\n", - "\n" - ] - } - ], - "source": [ - "from sklearn.metrics import accuracy_score, classification_report, confusion_matrix\n", - "from sklearn.preprocessing import StandardScaler\n", - "from sklearn.ensemble import RandomForestClassifier\n", - "\n", - "# Crear una instancia de StandardScaler\n", - "scaler = StandardScaler()\n", - "\n", - "# Ajustar y transformar los datos de entrenamiento\n", - "X_train_scaled = scaler.fit_transform(X_train)\n", - "\n", - "# Transformar los datos de prueba utilizando el mismo escalador\n", - "X_test_scaled = scaler.transform(X_test)\n", - "\n", - "# Random Forest\n", - "best_model = RandomForestClassifier(random_state=42)\n", - "\n", - "best_model.fit(X_train_scaled, y_train)\n", - "\n", - "# predicciones\n", - "y_pred = best_model.predict(X_test_scaled)\n", - "\n", - "# Calcular la precisión\n", - "accuracy = accuracy_score(y_test, y_pred)\n", - "print(f\"Precisión en el conjunto de prueba: {accuracy:.2f}\")\n", - "\n", - "report = classification_report(y_test, y_pred, zero_division=1)\n", - "\n", - "print(\"Informe de Clasificación:\")\n", - "print(report)\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "id": "5a5ee4da", - "metadata": {}, - "source": [ - "_**Conclusión**_: \n", - "\n", - "- **Precisión en el conjunto de prueba: 0.69**\n", - " - Esto indica que el modelo ha obtenido una precisión general del 69% en el conjunto de prueba. En otras palabras, el 69% de las predicciones del modelo coincidieron con las etiquetas reales.\n", - "\n", - "- **Informe de Clasificación:**\n", - " - El informe de clasificación se divide en varias métricas de rendimiento para cada clase de calidad del vino (3, 4, 5, 6, 7, 8).\n", - " - **Precision (Precisión):** Representa la proporción de verdaderos positivos (muestras correctamente clasificadas) respecto al total de predicciones positivas. Por ejemplo, para la calidad del vino \"3\", la precisión es 1.00, lo que significa que todas las predicciones positivas para esta clase fueron correctas.\n", - " - **Recall (Recuperación o Sensibilidad):** Representa la proporción de verdaderos positivos respecto al total de muestras reales de la clase. Para la calidad del vino \"3\", el recall es 0.00, lo que indica que muy pocas muestras reales de esta clase se identificaron correctamente.\n", - " - **F1-Score:** Es una medida que combina precision y recall. Un puntaje más alto indica un mejor equilibrio entre precision y recall. Para la calidad del vino \"5\", el F1-score es 0.70, lo que sugiere un buen equilibrio entre precisión y recall.\n", - " - **Support:** Indica el número de muestras en cada clase.\n", - "\n", - "- **Accuracy (Exactitud):** Representa la proporción de predicciones correctas en el conjunto de prueba. En este caso, la exactitud general es del 69%, lo que significa que el 69% de las predicciones del modelo son correctas.\n", - "\n", - "- **Macro Avg (Promedio Macro):** Es el promedio de las métricas de precisión, recall y F1-score para todas las clases. En este caso, el promedio macro indica que, en promedio, las métricas son moderadas en su conjunto.\n", - "\n", - "- **Weighted Avg (Promedio Ponderado):** Es similar al promedio macro, pero tiene en cuenta el desequilibrio en el número de muestras en cada clase. En este caso, el promedio ponderado muestra una precisión global del 69%, ponderada por el número de muestras en cada clase." - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "id": "f2c263a1", - "metadata": { - "scrolled": true - }, - "outputs": [ + "cell_type": "code", + "execution_count": 12, + "id": "e96f442b", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 840 + }, + "id": "e96f442b", + "outputId": "c715efc5-af2e-4a7f-ecc7-6e869531b93e" + }, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
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\n" + }, + "metadata": {} + } + ], + "source": [ + "import seaborn as sns\n", + "\n", + "# matriz de correlación de variables independientes\n", + "x_correlation_matrix = X.corr()\n", + "\n", + "\n", + "plt.figure(figsize=(8, 8))\n", + "sns.heatmap(x_correlation_matrix, annot=True, cmap='coolwarm', fmt=\".2f\")\n", + "plt.title(\"Matriz de correlación de variables Independientes\", fontsize=14)\n", + "plt.xticks(fontsize=10)\n", + "plt.yticks(fontsize=10)\n", + "\n", + "# los ejes x e y\n", + "plt.xlabel(\"Variables\", fontsize=12)\n", + "plt.ylabel(\"Variables\", fontsize=12)\n", + "\n", + "\n", + "plt.show()" + ] + }, { - "data": { - "image/png": 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\n", - "text/plain": [ - "
    " + "cell_type": "code", + "execution_count": 13, + "id": "bacfa926", + "metadata": { + "scrolled": true, + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "bacfa926", + "outputId": "c32835f1-dee4-4bbd-f5c0-93811e0f8037" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "╒══════════════════════╤══════════════════════╤═══════════════╤══════════════════════╕\n", + "│ Atributo 1 │ Atributo 2 │ Correlación │ Clasificación │\n", + "╞══════════════════════╪══════════════════════╪═══════════════╪══════════════════════╡\n", + "│ fixed acidity │ pH │ -0.425858 │ Moderada correlación │\n", + "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", + "│ residual sugar │ total sulfur dioxide │ 0.401439 │ Moderada correlación │\n", + "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", + "│ residual sugar │ density │ 0.838966 │ Alta correlación │\n", + "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", + "│ residual sugar │ alcohol │ -0.450631 │ Moderada correlación │\n", + "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", + "│ chlorides │ alcohol │ -0.360189 │ Moderada correlación │\n", + "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", + "│ free sulfur dioxide │ total sulfur dioxide │ 0.615501 │ Moderada correlación │\n", + "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", + "│ total sulfur dioxide │ residual sugar │ 0.401439 │ Moderada correlación │\n", + "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", + "│ total sulfur dioxide │ free sulfur dioxide │ 0.615501 │ Moderada correlación │\n", + "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", + "│ total sulfur dioxide │ density │ 0.529881 │ Moderada correlación │\n", + "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", + "│ total sulfur dioxide │ alcohol │ -0.448892 │ Moderada correlación │\n", + "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", + "│ density │ residual sugar │ 0.838966 │ Alta correlación │\n", + "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", + "│ density │ total sulfur dioxide │ 0.529881 │ Moderada correlación │\n", + "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", + "│ density │ alcohol │ -0.780138 │ Alta correlación │\n", + "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", + "│ pH │ fixed acidity │ -0.425858 │ Moderada correlación │\n", + "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", + "│ alcohol │ residual sugar │ -0.450631 │ Moderada correlación │\n", + "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", + "│ alcohol │ chlorides │ -0.360189 │ Moderada correlación │\n", + "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", + "│ alcohol │ total sulfur dioxide │ -0.448892 │ Moderada correlación │\n", + "├──────────────────────┼──────────────────────┼───────────────┼──────────────────────┤\n", + "│ alcohol │ density │ -0.780138 │ Alta correlación │\n", + "╘══════════════════════╧══════════════════════╧═══════════════╧══════════════════════╛\n" + ] + } + ], + "source": [ + "classification = []\n", + "\n", + "for attribute in x_correlation_matrix.columns:\n", + " for other_attribute, correlation in x_correlation_matrix[attribute].items():\n", + " if attribute != other_attribute:\n", + " if abs(correlation)> 0.75:\n", + " classification.append((attribute, other_attribute, correlation, \"Alta correlación\"))\n", + " elif abs(correlation) >0.3:\n", + " classification.append((attribute, other_attribute, correlation, \"Moderada correlación\"))\n", + "\n", + "headers = [\"Atributo 1\", \"Atributo 2\", \"Correlación\", \"Clasificación\"]\n", + "table = tabulate(classification, headers=headers, tablefmt=\"fancy_grid\")\n", + "print(table)" ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import matplotlib.pyplot as plt\n", - "\n", - "plt.figure(figsize=(8, 6))\n", - "\n", - "plt.scatter(y_test, y_test, alpha=0.5, color='blue', label='Valores Reales (y_test)', marker='o', s=50)\n", - "plt.scatter(y_test, y_pred, alpha=0.5, color='green', label='Predicciones (y_pred)', marker='^', s=50)\n", - "\n", - "plt.xlabel('Calidad del Vino')\n", - "plt.ylabel('Calidad del Vino')\n", - "plt.title('Comparación entre Valores Reales y Predicciones')\n", - "plt.grid(True)\n", - "plt.legend()\n", - "\n", - "plt.plot([2, 9], [2, 9], color='gray', linestyle='--', label='Igualdad Perfecta')\n", - "plt.legend()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "0b17b83e", - "metadata": {}, - "source": [ - "_Conclusión_:\n", - "El gráfico que representa los valores reales (y_test) en azul (círculos) y las predicciones (y_pred) en verde (triángulos) proporciona una forma visual de comparar cómo se relacionan las predicciones del modelo con los valores reales.\n", - "\n", - "- **Igualdad perfecta**: Los valores reales que caen exactamente en la línea diagonal (donde x=y) representan predicciones perfectas, lo que significa que el modelo predijo la calidad del vino de manera precisa.\n", - "\n", - "- **Desviación positiva**: Los puntos verdes que están por encima de la línea diagonal indican que el modelo sobreestimó la calidad del vino en esas muestras.\n", - "\n", - "- **Desviación negativa**: Los puntos verdes que están por debajo de la línea diagonal indican que el modelo subestimó la calidad del vino en esas muestras.\n", - "\n", - "- **Distribución de errores**: La dispersión de puntos alrededor de la línea diagonal muestra cómo se distribuyen los errores del modelo. Una distribución estrecha y centrada en la línea diagonal indica predicciones precisas, mientras que una dispersión más amplia indica un mayor margen de error.\n" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "id": "fd13b57b", - "metadata": {}, - "outputs": [ + }, { - "data": { - "image/png": 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\n", 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    " + "cell_type": "markdown", + "id": "e23f6d25", + "metadata": { + "id": "e23f6d25" + }, + "source": [ + "**Conclusión** : Se han identificado un par de variables con correlaciones altas, indicando una posible multicolinealidad. Una estrategia para abordar esto es eliminar una de las variables. En este caso, \"residual sugar\" y \"density\" muestran una correlación estadísticamente significativa. No obstante, antes de proceder con la eliminación de alguna de las variables, es importante entender la relevancia de cada variable dentro del problema. Ya que en ocasiones, estas variables pueden proporcionar información única y ser valiosas para el aprendizaje del modelo. Para evaluar esto, llevaremos a cabo un análisis de importancia de características o consideraremos el conocimiento del dominio." ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import matplotlib.pyplot as plt\n", - "\n", - "y_classes, class_counts = np.unique(y, return_counts=True)\n", - "\n", - "plt.bar(y_classes, class_counts)\n", - "plt.xlabel('Clases de Calidad del Vino')\n", - "plt.ylabel('Número de Muestras')\n", - "plt.title('Distribución de Clases en Wine Quality Dataset')\n", - "plt.xticks(y_classes)\n", - "plt.show()\n" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "id": "1577a5c4", - "metadata": {}, - "outputs": [ + }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "Clase 3: 20 instancias\n", - "Clase 4: 163 instancias\n", - "Clase 5: 1457 instancias\n", - "Clase 6: 2198 instancias\n", - "Clase 7: 880 instancias\n", - "Clase 8: 175 instancias\n", - "Clase 9: 5 instancias\n" - ] - } - ], - "source": [ - "y_classes, class_counts = np.unique(y, return_counts=True)\n", - "\n", - "for y_class, count in zip(y_classes, class_counts):\n", - " print(f'Clase {y_class}: {count} instancias')" - ] - }, - { - "cell_type": "markdown", - "id": "1daefcf9", - "metadata": {}, - "source": [ - "### **Resultados Preliminares del Modelo:**\n", - "- El modelo ha obtenido una precisión global del 69% en el conjunto de prueba, lo que significa que el 69% de las predicciones coincidieron con las etiquetas reales.\n", - "- El informe de clasificación proporciona métricas detalladas para cada clase de calidad del vino. Aquí se observan algunas tendencias notables:\n", - " - El modelo tiene un alto recall (sensibilidad) para las clases de calidad \"5\" y \"6\", lo que indica que es bueno para identificar esas clases.\n", - " - Sin embargo, el modelo tiene un bajo recall para las clases de calidad \"3\", \"4\", \"7\", \"8\" y \"9\", lo que sugiere que tiene dificultades para identificar estas clases.\n", - " - El modelo tiene una alta precisión en las clases \"3\", \"5\", \"7\" y \"8\", lo que indica que las predicciones positivas para estas clases son en su mayoría correctas.\n", - " - El modelo tiene una baja precisión en las clases \"4\" y \"9\", lo que sugiere que muchas de las predicciones positivas para estas clases son incorrectas.\n", - "- Las métricas F1-score y el promedio ponderado muestran el equilibrio entre precisión y recall en general, y el promedio ponderado tiene un valor del 68%, lo que refleja la eficacia general del modelo en el conjunto de datos desequilibrado.\n" - ] - }, - { - "cell_type": "markdown", - "id": "3cf23a60", - "metadata": {}, - "source": [ - "### **_Conclusiones preliminares_** : \n", - "\n", - "1. **Clases Mayoritarias:** Debido al desequilibrio de clases, el modelo tiene una cantidad mucho mayor de ejemplos de las clases \"5\" y \"6\" en comparación con otras clases. Esto hace que el modelo tenga más información sobre estas clases, por lo que puede ser más preciso al predecirlas. Esto se refleja en los altos valores de precisión y recall para las clases \"5\" y \"6\".\n", - "\n", - "2. **Clases Minoritarias:** Por otro lado, las clases minoritarias, como \"3\", \"4\", \"7\", \"8\" y \"9\", tienen menos ejemplos en el conjunto de datos. Esto hace que el modelo tenga menos información para aprender y predecir estas clases, lo que se traduce en valores más bajos de precisión y recall para estas clases.\n", - "\n", - "3. **Impacto en el Promedio Ponderado:** El promedio ponderado de todas las métricas se ve influenciado por el desequilibrio de clases. Dado que las clases \"5\" y \"6\" tienen muchas más muestras que las clases minoritarias, su impacto es mayor en el promedio ponderado. Esto significa que el rendimiento del modelo en las clases minoritarias puede no reflejarse tan claramente en el promedio ponderado.\n", - "\n", - "4. **Contexto del Problema:** En algunos casos, el desequilibrio de clases puede ser natural en un problema de clasificación. Por ejemplo, en el caso del vino, es más común encontrar vinos de calidad \"5\" y \"6\" que de calidad \"3\" o \"9\".\n" - ] - }, - { - "cell_type": "markdown", - "id": "c6ae325b", - "metadata": {}, - "source": [ - "### Estrategias para mejora el modelo:\n", - "\n", - "- Dado el desequilibrio de clases, podrías considerar estrategias de manejo de desequilibrio, como oversampling o undersampling de clases minoritarias, para mejorar el rendimiento del modelo en las clases desequilibradas.\n", - "- La ingeniería de características y la búsqueda de hiperparámetros podrían ayudar a mejorar aún más el rendimiento del modelo.\n", - "- Podrías evaluar otros modelos de clasificación y ajustar sus hiperparámetros para determinar si hay un modelo más adecuado para este conjunto de datos específico.\n", - "- Un análisis de residuos podría ayudarte a entender mejor las predicciones erróneas del modelo y cómo se pueden abordar.\n", - "\n", - "La estrategia más útil sería el oversampling de las clases minoritarias. Dado que las clases \"3\", \"4\", \"7\", \"8\" y \"9\" tienen menos instancias que las clases mayoritarias, aumentar el número de muestras en estas clases puede ayudar al modelo a aprender de manera más equitativa y mejorar su rendimiento en las clases desequilibradas." - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "id": "4b8a0466", - "metadata": { - "scrolled": true - }, - "outputs": [], - "source": [ - "from imblearn.over_sampling import RandomOverSampler\n", - "\n", - "# instancia del resampler\n", - "oversampler = RandomOverSampler(random_state=42)\n", - "\n", - "# Aplica el resampling \n", - "X_train_resampled, y_train_resampled = oversampler.fit_resample(X_train, y_train)\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "id": "8dbd38e7", - "metadata": {}, - "outputs": [ + "cell_type": "code", + "execution_count": 14, + "id": "7553e929", + "metadata": { + "id": "7553e929" + }, + "outputs": [], + "source": [ + "# Datos en conjuntos de entrenamiento y prueba (80% entrenamiento, 20% prueba)\n", + "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)" + ] + }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "Precisión en el conjunto de prueba: 0.92\n", - "Informe de Clasificación:\n", - " precision recall f1-score support\n", - "\n", - " 3 1.00 1.00 1.00 363\n", - " 4 0.99 1.00 1.00 338\n", - " 5 0.78 0.88 0.83 346\n", - " 6 0.81 0.66 0.73 375\n", - " 7 0.89 0.94 0.91 383\n", - " 8 0.99 1.00 1.00 332\n", - " 9 0.99 1.00 1.00 336\n", - "\n", - " accuracy 0.92 2473\n", - " macro avg 0.92 0.93 0.92 2473\n", - "weighted avg 0.92 0.92 0.92 2473\n", - "\n" - ] - } - ], - "source": [ - "X_train_balanced, X_test, y_train_balanced, y_test = train_test_split(X_train_resampled, y_train_resampled, test_size=0.2, random_state=42)\n", - "\n", - "model = RandomForestClassifier(random_state=42)\n", - "model.fit(X_train_balanced, y_train_balanced)\n", - "\n", - "y_pred_balanced = model.predict(X_test)\n", - "\n", - "accuracy = accuracy_score(y_test, y_pred_balanced)\n", - "print(f'Precisión en el conjunto de prueba: {accuracy:.2f}')\n", - "\n", - "report = classification_report(y_test, y_pred_balanced)\n", - "print('Informe de Clasificación:')\n", - "print(report)\n" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "id": "f72c45f7", - "metadata": {}, - "outputs": [ + "cell_type": "markdown", + "id": "64a07679", + "metadata": { + "id": "64a07679" + }, + "source": [ + "2. 5 _Análisis de importancia de características_:" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "fa07be18", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "fa07be18", + "outputId": "c6376b13-978c-42db-eb27-20758c131a0e" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Feature: alcohol, Importance: 0.1132\n", + "Feature: density, Importance: 0.1064\n", + "Feature: volatile acidity, Importance: 0.1020\n", + "Feature: free sulfur dioxide, Importance: 0.0946\n", + "Feature: total sulfur dioxide, Importance: 0.0914\n", + "Feature: residual sugar, Importance: 0.0890\n", + "Feature: pH, Importance: 0.0846\n", + "Feature: chlorides, Importance: 0.0827\n", + "Feature: citric acid, Importance: 0.0808\n", + "Feature: sulphates, Importance: 0.0787\n", + "Feature: fixed acidity, Importance: 0.0766\n" + ] + } + ], + "source": [ + "# Crea un modelo Random Forest Classifier\n", + "clf = RandomForestClassifier(random_state=42)\n", + "\n", + "# Ajusta el modelo\n", + "clf.fit(X_train, y_train)\n", + "\n", + "# puntuaciones de importancia\n", + "importances = clf.feature_importances_\n", + "\n", + "# importancias con los nombres de las características\n", + "feature_importance = list(zip(X.columns, importances))\n", + "\n", + "# Ordena por su importancia\n", + "feature_importance = sorted(feature_importance, key=lambda x: x[1], reverse=True)\n", + "\n", + "#características y sus puntuaciones de importancia\n", + "for feature, importance in feature_importance:\n", + " print(f\"Feature: {feature}, Importance: {importance:.4f}\")" + ] + }, + { + "cell_type": "markdown", + "id": "4e868884", + "metadata": { + "id": "4e868884" + }, + "source": [ + "**Conclusión**:\n", + "La **importancia de las características** nos indica qué tan influyentes son las características en el proceso de clasificación del modelo. Cuanto mayor sea el valor, más influencia tiene esa característica o atributo dentro del mismo, los resultados nos arrojaron:\n", + "\n", + "- **Alcohol** es la característica más importante, con una importancia de aproximadamente 0.1132. Se concluye que el alcohol es la característica más influyente en la clasificación.\n", + "- **Density** es la segunda característica más importante, con una importancia de aproximadamente 0.1064.\n", + "- **Volatile acidity** es la tercera característica más importante, con una importancia de aproximadamente 0.1020." + ] + }, { - "data": { - "image/png": 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\n", 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    " + "cell_type": "code", + "execution_count": 16, + "id": "f212ceec", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "f212ceec", + "outputId": "d6878405-8824-4367-9831-9aa0014f3036" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Árbol de Decisión: Accuracy = 0.61, Desviación estándar = 0.49\n", + "Random Forest: Accuracy = 0.69, Desviación estándar = 0.46\n", + "SVM: Accuracy = 0.56, Desviación estándar = 0.50\n", + "K-NN: Accuracy = 0.54, Desviación estándar = 0.50\n", + "El mejor modelo es: Random Forest\n" + ] + } + ], + "source": [ + "# Escalar características\n", + "scaler = StandardScaler()\n", + "X_train = scaler.fit_transform(X_train)\n", + "X_test = scaler.transform(X_test)\n", + "\n", + "# Modelos (excluyendo MultinomialNB)\n", + "models = [\n", + " (\"Árbol de Decisión\", DecisionTreeClassifier()),\n", + " (\"Random Forest\", RandomForestClassifier()),\n", + " (\"SVM\", SVC()),\n", + " (\"K-NN\", KNeighborsClassifier())\n", + "]\n", + "\n", + "# Entrenar y evaluar modelos\n", + "results = {}\n", + "\n", + "for model_name, model in models:\n", + " model.fit(X_train, y_train)\n", + " y_pred = model.predict(X_test)\n", + " accuracy = accuracy_score(y_test, y_pred)\n", + " results[model_name] = {\n", + " 'accuracy': accuracy,\n", + " 'std_dev': np.std(y_pred == y_test) # Calcula la desviación estándar\n", + " }\n", + "\n", + "# Imprimir resultados\n", + "for model_name, metrics in results.items():\n", + " print(f\"{model_name}: Accuracy = {metrics['accuracy']:.2f}, Desviación estándar = {metrics['std_dev']:.2f}\")\n", + "\n", + "best_model_name = max(results, key=lambda k: results[k]['accuracy'])\n", + "print(f\"El mejor modelo es: {best_model_name}\")\n" + ] + }, + { + "cell_type": "markdown", + "id": "f7072776", + "metadata": { + "id": "f7072776" + }, + "source": [ + "**Conclusión:**\n", + "\n", + "- **Modelo: Árbol de Decisión**\n", + "\n", + " _Precisión_: con valores del 62% y una desviación estándar de 0.48%. La desviación estándar indica una variabilidad moderada, lo cual sugiere una aceptable consistencia en las predicciones.\n", + "\n", + "- **Modelo: Random Forest**\n", + "\n", + " _Precisión_: Con valores del 69% y una desviación estándar de 0.46%. Este modelo ha demostrado una mayor precisión en la clasificación de la calidad del vino en comparación con el modelo anterior, sugiriendo una mayor consistencia en sus predicciones en comparación con los modelos anteriores.\n", + "\n", + "- **Modelo: SVM (Support Vector Machine)**\n", + "\n", + " _Precisión_: con valores del 56% y una desviación estándar de 0.50%. Esto indica que el modelo acertó en su predicción de la calidad del vino en aproximadamente el 56% de los casos. Sin embargo, la desviación estándar de 0.50% sugiere que el rendimiento del modelo puede variar en alrededor de 0.50%, indicando una variabilidad significativa en las predicciones que podría afectar la consistencia del modelo en diferentes situaciones.\n", + "\n", + "- **Modelo: K-NN (K-Nearest Neighbors)**\n", + "\n", + " _Precisión_: con valores del 54% y una desviación estándar de 0.50%. Donde el modelo acertó en su predicción de la calidad del vino en aproximadamente el 54% de los casos. Similar al modelo SVM, la desviación estándar de 0.50% sugiere que el rendimiento del modelo puede variar en alrededor de 0.50%. Esta variabilidad en las predicciones impacta la consistencia del modelo, ya que las predicciones pueden ser menos predecibles en diferentes circunstancias.\n", + "\n", + "En resumen, el **modelo Random Forest** sigue siendo el **más eficaz** en la clasificación de la calidad del vino, con la precisión más alta en comparación a alos otros modelos." + ] + }, + { + "cell_type": "markdown", + "source": [ + "Ahora que sabemos que el mejor modelo es **Random Forest**, vamos a hacer hincapié y mejorar ciertos aspectos. Empezaremos por estandarizar los datos antes de entrenar el modelo para mejorar su la estabilidad, convergencia y rendimiento, garantizando que las características tengan una escala coherente. Estas mejoras son particularmente relevantes cuando se trabaja con algoritmos sensibles a las diferencias en las escalas de las características" + ], + "metadata": { + "id": "mGCMrPjRIRCr" + }, + "id": "mGCMrPjRIRCr" + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "ef23761d", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "ef23761d", + "outputId": "7c9e52fa-1863-421b-9159-566bb5f037c7" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Precisión en el conjunto de prueba: 0.69\n", + "Desviación estándar en el conjunto de prueba: 0.46\n", + "Informe de Clasificación:\n", + " precision recall f1-score support\n", + "\n", + " 3 1.00 0.00 0.00 5\n", + " 4 0.56 0.20 0.29 25\n", + " 5 0.70 0.70 0.70 291\n", + " 6 0.66 0.79 0.72 432\n", + " 7 0.76 0.58 0.66 192\n", + " 8 0.80 0.46 0.58 35\n", + "\n", + " accuracy 0.69 980\n", + " macro avg 0.75 0.45 0.49 980\n", + "weighted avg 0.70 0.69 0.68 980\n", + "\n" + ] + } + ], + "source": [ + "from sklearn.metrics import accuracy_score, classification_report\n", + "from sklearn.preprocessing import StandardScaler\n", + "from sklearn.ensemble import RandomForestClassifier\n", + "import numpy as np\n", + "\n", + "# Crear una instancia de StandardScaler\n", + "scaler = StandardScaler()\n", + "\n", + "# Ajustar y transformar los datos de entrenamiento\n", + "X_train_scaled = scaler.fit_transform(X_train)\n", + "\n", + "# Transformar los datos de prueba utilizando el mismo escalador\n", + "X_test_scaled = scaler.transform(X_test)\n", + "\n", + "# Random Forest\n", + "best_model = RandomForestClassifier(random_state=42)\n", + "\n", + "best_model.fit(X_train_scaled, y_train)\n", + "\n", + "# Predicciones\n", + "y_pred = best_model.predict(X_test_scaled)\n", + "\n", + "# Calcular la precisión\n", + "accuracy = accuracy_score(y_test, y_pred)\n", + "print(f\"Precisión en el conjunto de prueba: {accuracy:.2f}\")\n", + "\n", + "# Calcular la desviación estándar\n", + "std_dev = np.std(y_pred == y_test)\n", + "print(f\"Desviación estándar en el conjunto de prueba: {std_dev:.2f}\")\n", + "\n", + "# Generar el informe de clasificación\n", + "report = classification_report(y_test, y_pred, zero_division=1)\n", + "\n", + "print(\"Informe de Clasificación:\")\n", + "print(report)\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "id": "5a5ee4da", + "metadata": { + "id": "5a5ee4da" + }, + "source": [ + "_**Conclusión**_: No vemos cambios en los valores que arrojo el modelo, pero vamos analizar las otras metricas:\n", + "\n", + "1. **Precisión en el conjunto de prueba: 0.69**\n", + " - La precisión del modelo es del 69%, lo cual indica la proporción de instancias clasificadas correctamente.\n", + "\n", + "2. **Desviación estándar en el conjunto de prueba: 0.46**\n", + " - La desviación estándar mide la dispersión de los valores. En este caso, la desviación estándar relativamente alta (0.46) en el conjunto de prueba puede sugerir cierta variabilidad en el rendimiento del modelo para diferentes conjuntos de datos de prueba.\n", + "\n", + "3. **Informe de Clasificación:**\n", + "\n", + " - **Clase 3:**\n", + " - La precisión es del 100%, pero el recall es muy bajo (0%), lo que indica que el modelo tiene dificultades para identificar correctamente las instancias de esta clase.\n", + " - **Clase 4:**\n", + " - La precisión es del 56%, lo que indica que el 56% de las predicciones positivas son correctas. El recall es del 20%, lo que sugiere que hay instancias de esta clase que el modelo no está capturando adecuadamente.\n", + "\n", + " - **Clase 5:**\n", + " - La precisión y el recall son razonablemente buenos (70%), indicando que el modelo tiene un buen rendimiento en esta clase.\n", + "\n", + " - **Clase 6:**\n", + " - Tanto la precisión como el recall son aceptables (66% y 79% respectivamente). El modelo tiende a clasificar bien las instancias de esta clase.\n", + "\n", + " - **Clase 7:**\n", + " - La precisión es del 76%, pero el recall es del 58%. El modelo tiene un rendimiento decente, pero podría mejorar en la identificación de todas las instancias positivas de esta clase.\n", + "\n", + " - **Clase 8:**\n", + " - La precisión es alta (80%), pero el recall es bajo (46%). El modelo tiende a ser preciso al predecir esta clase, pero deja de capturar algunas instancias.\n", + "\n", + "4. **Métricas globales:**\n", + " - **Accuracy (exactitud):** 69%. Representa la proporción de instancias correctamente clasificadas en todas las clases.\n", + " - **Macro AVG:** Representa la media no ponderada de precision, recall y f1-score para todas las clases. En este caso, es 0.75 para precision, 0.45 para recall, y 0.49 para f1-score.\n", + " - **Weighted AVG:** Similar al macro AVG, pero ponderado por el número de instancias en cada clase. En este caso, la precisión ponderada es del 70%, recall ponderado es del 69%, y f1-score ponderado es del 68%.\n" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "f2c263a1", + "metadata": { + "scrolled": true, + "colab": { + "base_uri": "https://localhost:8080/", + "height": 565 + }, + "id": "f2c263a1", + "outputId": "b01f7959-756b-4e89-a561-09fc495d2811" + }, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
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\n" + }, + "metadata": {} + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "\n", + "plt.figure(figsize=(8, 6))\n", + "\n", + "plt.scatter(y_test, y_test, alpha=0.5, color='blue', label='Valores Reales (y_test)', marker='o', s=50)\n", + "plt.scatter(y_test, y_pred, alpha=0.5, color='green', label='Predicciones (y_pred)', marker='^', s=50)\n", + "\n", + "plt.xlabel('Calidad del Vino')\n", + "plt.ylabel('Calidad del Vino')\n", + "plt.title('Comparación entre Valores Reales y Predicciones')\n", + "plt.grid(True)\n", + "plt.legend()\n", + "\n", + "plt.plot([2, 9], [2, 9], color='gray', linestyle='--', label='Igualdad Perfecta')\n", + "plt.legend()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "0b17b83e", + "metadata": { + "id": "0b17b83e" + }, + "source": [ + "Este gráfico que representa los valores reales (y_test) en azul (círculos) y las predicciones (y_pred) en verde (triángulos) proporciona una forma visual de comparar cómo se relacionan las predicciones del modelo con los valores reales.\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "fd13b57b", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 472 + }, + "id": "fd13b57b", + "outputId": "afcbff52-0e25-4a0b-af8c-a67f53457995" + }, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
    " + ], + "image/png": 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\n" + }, + "metadata": {} + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "\n", + "y_classes, class_counts = np.unique(y, return_counts=True)\n", + "\n", + "plt.bar(y_classes, class_counts)\n", + "plt.xlabel('Clases de Calidad del Vino')\n", + "plt.ylabel('Número de Muestras')\n", + "plt.title('Distribución de Clases en Wine Quality Dataset')\n", + "plt.xticks(y_classes)\n", + "plt.show()\n" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "1577a5c4", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "1577a5c4", + "outputId": "97755129-dba0-49e9-ecbc-8b76eaeb335b" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Clase 3: 20 instancias\n", + "Clase 4: 163 instancias\n", + "Clase 5: 1457 instancias\n", + "Clase 6: 2198 instancias\n", + "Clase 7: 880 instancias\n", + "Clase 8: 175 instancias\n", + "Clase 9: 5 instancias\n" + ] + } + ], + "source": [ + "y_classes, class_counts = np.unique(y, return_counts=True)\n", + "\n", + "for y_class, count in zip(y_classes, class_counts):\n", + " print(f'Clase {y_class}: {count} instancias')" + ] + }, + { + "cell_type": "markdown", + "id": "1daefcf9", + "metadata": { + "id": "1daefcf9" + }, + "source": [ + "Al analizar el numero de instancias de la variable dependiente (Calidad del Vino) sobre algunas de las observaciones previas temos que:\n", + "\n", + "1. **Clase 3: 20 instancias**\n", + " - Con solo 20 instancias, la precisión fue del 100% pero un recall del 0% tiene más sentido. Ya que falta de datos puede hacer que el modelo tenga dificultades para aprender patrones representativos de esta clase.\n", + "\n", + "2. **Clase 4: 163 instancias**\n", + " - Con 163 instancias, la precisión del 56% y el recall del 20% indican que el modelo tiene dificultades para identificar correctamente la mayoría de las instancias de esta clase pero al tener más muestras va aumentando su valor.\n", + "\n", + "3. **Clase 5: 1457 instancias**\n", + " - Con un número significativo de instancias (1457), la precisión y el recall del 70% sugieren un rendimiento razonable en esta clase.\n", + "\n", + "4. **Clase 6: 2198 instancias**\n", + " - El modelo tiene un rendimiento aceptable en esta clase, con una precisión del 66% y un recall del 79%. Dado el número considerable de instancias, el modelo tiene un buen desempeño .\n", + "\n", + "5. **Clase 7: 880 instancias**\n", + " - La precisión del 76% y el recall del 58% sugieren un rendimiento decente en esta clase, pero hay margen para mejorar, especialmente en el recall.\n", + "\n", + "6. **Clase 8: 175 instancias**\n", + " - La alta precisión del 80% y el recall bajo del 46% indican que el modelo tiende a ser preciso al predecir esta clase, pero no logra identificar todas las instancias.\n", + "\n", + "La interpretación anterior se mantiene, pero ahora con el contexto del desequilibrio de clase, entendemos que las clases con un número menor de instancias pueden presentar desafíos para el modelo, y podrían ser necesarias estrategias como el aumento de datos, el submuestreo o el ajuste de pesos de clase para abordar este problema.\n", + "\n", + "Además, al considerar la métrica macro AVG y weighted AVG, estas métricas también reflejan el impacto del desequilibrio de clases en el rendimiento general del modelo. La precisión ponderada (weighted AVG) se ve afectada por el desequilibrio de clases, ya que las clases más grandes tienen un impacto mayor en esta métrica." + ] + }, + { + "cell_type": "markdown", + "id": "3cf23a60", + "metadata": { + "id": "3cf23a60" + }, + "source": [ + "### **_Conclusiones preliminares_** :\n", + "\n", + "1. **Clases Mayoritarias:** Debido al desequilibrio de clases, el modelo tiene una cantidad mucho mayor de ejemplos de las clases \"5\" y \"6\" en comparación con otras clases. Esto hace que el modelo tenga más información sobre estas clases, por lo que puede ser más preciso al predecirlas. Esto se refleja en los altos valores de precisión y recall para las clases \"5\" y \"6\".\n", + "\n", + "2. **Clases Minoritarias:** Por otro lado, las clases minoritarias, como \"3\", \"4\", \"7\", \"8\" y \"9\", tienen menos ejemplos en el conjunto de datos. Esto hace que el modelo tenga menos información para aprender y predecir estas clases, lo que se traduce en valores más bajos de precisión y recall para estas clases.\n", + "\n", + "3. **Impacto en el Promedio Ponderado:** El promedio ponderado de todas las métricas se ve influenciado por el desequilibrio de clases. Dado que las clases \"5\" y \"6\" tienen muchas más muestras que las clases minoritarias, su impacto es mayor en el promedio ponderado. Esto significa que el rendimiento del modelo en las clases minoritarias puede no reflejarse tan claramente en el promedio ponderado.\n", + "\n", + "4. **Contexto del Problema:** En algunos casos, el desequilibrio de clases puede ser natural en un problema de clasificación. Por ejemplo, en el caso del vino, es más común encontrar vinos de calidad \"5\" y \"6\" que de calidad \"3\" o \"9\".\n" + ] + }, + { + "cell_type": "markdown", + "id": "c6ae325b", + "metadata": { + "id": "c6ae325b" + }, + "source": [ + "# **Estrategias para mejora el modelo:**\n", + "\n", + "- Dado el desequilibrio de clases, podrías considerar estrategias de manejo de desequilibrio, como oversampling o undersampling de clases minoritarias, para mejorar el rendimiento del modelo en las clases desequilibradas.\n", + "- La ingeniería de características y la búsqueda de hiperparámetros podrían ayudar a mejorar aún más el rendimiento del modelo.\n", + "- Podrías evaluar otros modelos de clasificación y ajustar sus hiperparámetros para determinar si hay un modelo más adecuado para este conjunto de datos específico.\n", + "- Un análisis de residuos podría ayudarte a entender mejor las predicciones erróneas del modelo y cómo se pueden abordar.\n", + "\n", + "La estrategia más útil sería el oversampling de las clases minoritarias. Dado que las clases \"3\", \"4\", \"7\", \"8\" y \"9\" tienen menos instancias que las clases mayoritarias, aumentar el número de muestras en estas clases puede ayudar al modelo a aprender de manera más equitativa y mejorar su rendimiento en las clases desequilibradas." + ] + }, + { + "cell_type": "markdown", + "source": [], + "metadata": { + "id": "1j3ow3IMtfbv" + }, + "id": "1j3ow3IMtfbv" + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "4b8a0466", + "metadata": { + "scrolled": true, + "id": "4b8a0466" + }, + "outputs": [], + "source": [ + "from imblearn.over_sampling import RandomOverSampler\n", + "\n", + "# instancia del resampler\n", + "oversampler = RandomOverSampler(random_state=42)\n", + "\n", + "# Aplica el resampling\n", + "X_train_resampled, y_train_resampled = oversampler.fit_resample(X_train, y_train)\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "8dbd38e7", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + }, + "id": "8dbd38e7", + "outputId": "8e3852de-07a3-4bf5-bae3-e8b89698d310" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "Precisión en el conjunto de prueba: 0.92\n", + "Informe de Clasificación:\n", + " precision recall f1-score support\n", + "\n", + " 3 1.00 1.00 1.00 363\n", + " 4 0.99 1.00 1.00 338\n", + " 5 0.78 0.88 0.83 346\n", + " 6 0.81 0.66 0.73 375\n", + " 7 0.89 0.94 0.91 383\n", + " 8 0.99 1.00 1.00 332\n", + " 9 0.99 1.00 1.00 336\n", + "\n", + " accuracy 0.92 2473\n", + " macro avg 0.92 0.93 0.92 2473\n", + "weighted avg 0.92 0.92 0.92 2473\n", + "\n", + "Desviación estándar de las predicciones probabilísticas: 0.32\n" + ] + } + ], + "source": [ + "\n", + "# datos en entrenamiento y prueba\n", + "X_train_balanced, X_test, y_train_balanced, y_test = train_test_split(X_train_resampled, y_train_resampled, test_size=0.2, random_state=42)\n", + "\n", + "# modelo RandomForest\n", + "model = RandomForestClassifier(random_state=42)\n", + "model.fit(X_train_balanced, y_train_balanced)\n", + "\n", + "\n", + "y_pred_balanced = model.predict(X_test)\n", + "\n", + "# predicciones probabilísticas\n", + "y_pred_prob = model.predict_proba(X_test)\n", + "\n", + "# desviación estándar\n", + "std_deviation = y_pred_prob.std()\n", + "\n", + "# precisión en el conjunto de prueba\n", + "accuracy = accuracy_score(y_test, y_pred_balanced)\n", + "print(f'Precisión en el conjunto de prueba: {accuracy:.2f}')\n", + "\n", + "# Informe de clasificación\n", + "report = classification_report(y_test, y_pred_balanced)\n", + "print('Informe de Clasificación:')\n", + "print(report)\n", + "\n", + "# desviación estándar\n", + "print(f'Desviación estándar de las predicciones probabilísticas: {std_deviation:.2f}')\n" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "id": "f72c45f7", + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 565 + }, + "id": "f72c45f7", + "outputId": "054aec79-0e91-4e4d-d4e1-9384ab09bea2" + }, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "
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\n" + }, + "metadata": {} + } + ], + "source": [ + "plt.figure(figsize=(8, 6))\n", + "\n", + "plt.scatter(y_test, y_test, alpha=0.5, color='blue', label='Valores Reales (y_test)', marker='o', s=50)\n", + "plt.scatter(y_test, y_pred_balanced, alpha=0.5, color='green', label='Predicciones (y_pred)', marker='^', s=50)\n", + "\n", + "plt.xlabel('Calidad del Vino')\n", + "plt.ylabel('Calidad del Vino')\n", + "plt.title('Comparación entre Valores Reales y Predicciones')\n", + "plt.grid(True)\n", + "plt.legend()\n", + "\n", + "plt.plot([2, 9], [2, 9], color='gray', linestyle='--', label='Igualdad Perfecta')\n", + "plt.legend()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "cfc1528e", + "metadata": { + "id": "cfc1528e" + }, + "source": [ + "## **Discución**\n", + "\n", + "En esta discusión, se buscó simular los desafíos que pueden surgir al trabajar con un conjunto de datos y se exploraron diversos mecanismos para mejorar su rendimiento. Se llevó la aplicación de varios modelos de clasificación, como Árboles de Decisión, Random Forest, SVM y K-NN, sobre el conjunto de datos de calidad de vino blanco de Wine Quality UCI.\n", + "\n", + "Los resultados revelaron que el desbalance de clases en el conjunto de datos tuvo un impacto significativo en la precisión de los modelos, siendo las clases mayoritarias las que presentaron un mejor rendimiento. Para hacer frente a este desbalance, se implementó la estrategia de oversampling, la cual condujo a una mejora sustancial en la precisión del modelo Random Forest, elevándola de 0.69 a 0.92 en el conjunto de prueba y de pasar a una desvación estandar de 0.46 a 0.32.\n", + "\n", + "La elección de estos modelos específicos se basó en su capacidad para manejar datos multidimensionales y su disponibilidad en bibliotecas de aprendizaje automático ampliamente utilizadas. Es importante destacar que las diferencias metodológicas entre el enfoque propuesto y el estudio de referencia se centran en las estrategias de preprocesamiento y la evaluación de modelos. Aunque ambos estudios emplearon algoritmos similares, las estrategias metodológicas y los resultados variaron debido a las adaptaciones realizadas según las necesidades específicas de cada investigación.\n", + "\n", + "Este estudio subraya la importancia de abordar el desbalance de clases en conjuntos de datos y de ajustar la metodología según las características particulares del problema de clasificación. La adaptación de estrategias de preprocesamiento y evaluación es esencial para lograr resultados más precisos y relevantes en el ámbito de la clasificación de datos.\n" ] - }, - "metadata": {}, - "output_type": "display_data" } - ], - "source": [ - "plt.figure(figsize=(8, 6))\n", - "\n", - "plt.scatter(y_test, y_test, alpha=0.5, color='blue', label='Valores Reales (y_test)', marker='o', s=50)\n", - "plt.scatter(y_test, y_pred_balanced, alpha=0.5, color='green', label='Predicciones (y_pred)', marker='^', s=50)\n", - "\n", - "plt.xlabel('Calidad del Vino')\n", - "plt.ylabel('Calidad del Vino')\n", - "plt.title('Comparación entre Valores Reales y Predicciones')\n", - "plt.grid(True)\n", - "plt.legend()\n", - "\n", - "plt.plot([2, 9], [2, 9], color='gray', linestyle='--', label='Igualdad Perfecta')\n", - "plt.legend()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "cfc1528e", - "metadata": {}, - "source": [ - "## **Discución**\n", - "\n", - "En este estudio, se exploraron modelos de clasificación, incluyendo Árboles de Decisión, Random Forest, SVM y K-NN, aplicados al conjunto de datos de calidad de vino blanco de Wine Quality UCI. Los resultados revelaron que el desbalance de clases en el conjunto de datos impactó significativamente en la precisión de los modelos, con las clases mayoritarias teniendo un mejor rendimiento. La estrategia de oversampling se utilizó para abordar este desbalance, resultando en una mejora sustancial de la precisión del modelo Random Forest de 0.69 a 0.92 en el conjunto de prueba. Se seleccionaron estos modelos específicos debido a su capacidad para manejar datos multidimensionales y su disponibilidad en bibliotecas de aprendizaje automático comunes. Las diferencias metodológicas entre el enfoque propuesto y el estudio de referencia radican en las estrategias de preprocesamiento y la evaluación de modelos. Si bien ambos utilizan algoritmos similares, los enfoques metodológicos y los resultados varían debido a las estrategias adaptadas a las necesidades de cada estudio. Esta investigación destaca la importancia de abordar el desbalance de clases en conjuntos de datos y adaptar la metodología a las características específicas del problema de clasificación.\n" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.9.16" + }, + "colab": { + "provenance": [] + } }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.9.16" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} + "nbformat": 4, + "nbformat_minor": 5 +} \ No newline at end of file diff --git a/_posts/2023-04-3-Energy Efficiency.html b/_posts/2023-04-3-Energy Efficiency.html index 1aeffc2d5d..f587f6bd51 100644 --- a/_posts/2023-04-3-Energy Efficiency.html +++ b/_posts/2023-04-3-Energy Efficiency.html @@ -62,6 +62,6 @@

    Exploratory Data Analysis

    Furthermore, it is suggested to explore other feature engineering techniques and consider the inclusion of more predictor variables to further enhance model performance. This project provides a solid foundation for energy load prediction in heating and cooling systems and can be scaled and adapted for future applications in energy efficiency in buildings.

    For more details, refer to the complete analysis and code in this repository.

    -Open in Google Colab +Open in Google Colab

    Photographs by Unsplash.

    \ No newline at end of file diff --git a/_posts/2023-06-28-WIne Quality.html b/_posts/2023-06-28-WIne Quality.html index 258dc4a308..4fa00a57dd 100644 --- a/_posts/2023-06-28-WIne Quality.html +++ b/_posts/2023-06-28-WIne Quality.html @@ -57,6 +57,6 @@

    Exploratory Data Analysis

    While both methodologies shared the use of some common algorithms, they differed in their approach to addressing class imbalance and the specific model configurations. This distinction is fundamental and highlights the importance of adapting methodologies to the unique characteristics of each dataset and problem.

    For more details, refer to the complete analysis and code in this repository.

    - Open in Google Colab + Open in Google Colab

    Photographs by Unsplash.

    diff --git a/about.html b/about.html index bf4a62184f..868fc631cc 100644 --- a/about.html +++ b/about.html @@ -6,12 +6,8 @@ ---

    - This portfolio presents a variety of - problems solved through the application of data science techniques. It demonstrates not only my - experience in scientific research, but also my ability to use technologies and knowledge in exploratory - data analysis, machine learning, data mining, and optimization to tackle complex problems. Each project - highlights my technical skills and my ability to solve real-world practical problems + As a specialized data science professional, I have a track record of over two years dedicated to scientific data analysis, especially in the biomedical field. My expertise primarily revolves around the advanced application of statistics and modeling using tools such as Python and R. Through a detailed examination of my portfolio, you can appreciate the projects I've undertaken, showcasing my abilities to address complex problems using innovative data science techniques, thereby contributing to the advancement of multidisciplinary knowledge.

    For more details, refer to my CV in Canvas

    - Open in Canvas + Open in Canvas