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} } } } }, "cells": [ { "cell_type": "markdown", "source": [ "#Hugging Face Setup" ], "metadata": { "id": "mXJTivFAPG2G" } }, { "cell_type": "code", "source": [ "from huggingface_hub import login\n", "\n", "login()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 270 }, "id": "Z0MDYeNePFuO", "outputId": "111d2c76-f05b-4dc8-edbc-0805cb9efc41" }, "execution_count": 1, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "" ], "text/html": [ "
\"Hugging

To log in, open this URL and enter the code:

https://hf.co/oauth/device

LYHL-FUXM

" ] }, "metadata": {} }, { "output_type": "display_data", "data": { "text/plain": [ "" ], "text/html": [ "
Waiting for authorization...
" ] }, "metadata": {} }, { "output_type": "display_data", "data": { "text/plain": [ "" ], "text/html": [ "
Login successful. Logged in as Swetha1929 (token: oauth-Swetha1929).
This token will be refreshed automatically when it expires.
" ] }, "metadata": {} } ] }, { "cell_type": "code", "source": [ "from huggingface_hub import login\n", "\n", "login(\"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\")" ], "metadata": { "id": "Mn-6_OGfPOdg" }, "execution_count": 2, "outputs": [] }, { "cell_type": "code", "source": [ "!pip install huggingface_hub datasets pandas" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "yhzToHyJPT8Q", "outputId": "482d220b-dbd9-4d00-d6b6-c096939b56da" }, "execution_count": 3, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Requirement already satisfied: huggingface_hub in /usr/local/lib/python3.12/dist-packages (1.23.0)\n", "Requirement already satisfied: datasets in /usr/local/lib/python3.12/dist-packages (4.0.0)\n", "Requirement already satisfied: pandas in /usr/local/lib/python3.12/dist-packages (2.2.2)\n", "Requirement already satisfied: click<9.0.0,>=8.4.2 in /usr/local/lib/python3.12/dist-packages (from huggingface_hub) (8.4.2)\n", "Requirement 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six>=1.5 in /usr/local/lib/python3.12/dist-packages (from python-dateutil>=2.8.2->pandas) (1.17.0)\n", "Requirement already satisfied: charset_normalizer<4,>=2 in /usr/local/lib/python3.12/dist-packages (from requests>=2.32.2->datasets) (3.4.9)\n", "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.12/dist-packages (from requests>=2.32.2->datasets) (2.5.0)\n", "Requirement already satisfied: aiohappyeyeballs>=2.5.0 in /usr/local/lib/python3.12/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]<=2025.3.0,>=2023.1.0->datasets) (2.7.1)\n", "Requirement already satisfied: aiosignal>=1.4.0 in /usr/local/lib/python3.12/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]<=2025.3.0,>=2023.1.0->datasets) (1.4.0)\n", "Requirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.12/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]<=2025.3.0,>=2023.1.0->datasets) (26.1.0)\n", "Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.12/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]<=2025.3.0,>=2023.1.0->datasets) (1.8.0)\n", "Requirement already satisfied: multidict<7.0,>=4.5 in /usr/local/lib/python3.12/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]<=2025.3.0,>=2023.1.0->datasets) (6.7.1)\n", "Requirement already satisfied: propcache>=0.2.0 in /usr/local/lib/python3.12/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]<=2025.3.0,>=2023.1.0->datasets) (0.5.2)\n", "Requirement already satisfied: yarl<2.0,>=1.17.0 in /usr/local/lib/python3.12/dist-packages (from aiohttp!=4.0.0a0,!=4.0.0a1->fsspec[http]<=2025.3.0,>=2023.1.0->datasets) (1.24.2)\n" ] } ] }, { "cell_type": "markdown", "source": [ "# Capstone Project - Predictive Maintenance\n", "\n", "## Project 3 - Predictive Maintenance\n", "\n", "### Objective\n", "\n", "The objective of this project is to develop a machine learning model that predicts the operational condition of an engine using sensor data. The project follows the complete machine learning lifecycle, including data registration, exploratory data analysis, data preparation, model building, and experimentation tracking." ], "metadata": { "id": "8utU_4F7PtyP" } }, { "cell_type": "code", "source": [ "import pandas as pd\n", "import numpy as np\n", "\n", "import matplotlib.pyplot as plt\n", "import seaborn as sns\n", "\n", "from datasets import load_dataset\n", "\n", "import warnings\n", "warnings.filterwarnings(\"ignore\")\n", "\n", "plt.style.use(\"ggplot\")" ], "metadata": { "id": "DWxNDstFP0nf" }, "execution_count": 4, "outputs": [] }, { "cell_type": "code", "source": [ "from datasets import load_dataset\n", "\n", "dataset = load_dataset(\n", " \"Swetha1929/predictive-maintenance-engine-data\",\n", " data_files=\"engine_data.csv\"\n", ")\n", "\n", "df = dataset[\"train\"].to_pandas()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 113, "referenced_widgets": [ "7e10ebd916da4987b3fa9a8498fedf58", "165fbaa695e54ecf96691d913bbad196", "4f1c7d8aec4b4eb58029675aa2ab70fe", "1c605c14d5d44c1995a6e3a0b3d60fc6", "e589e41c5ae1440abbbe4d5dc3268590", "6d7961da73f24fe7bacfdf6c18735c00", "c80137b5d4b14a82968ea628acba903d", "d8c975bad6e0492f8e4f428ff432d9e2", "cc1e4f93face434fadb7d628de05dce3", "b656250a75c64337bb0bd74a0946e8b3", "cb4243f05820402982c2a52055ef5e22", "f67bc05753034911a9834813eb788c6a", "a7bf4e17b3a64abaad0b7840412f5904", "d3d573c036dc4d8c9fd89df0747ccc36", "afa20d3281fe454789291dc1061c08f7", "5ee57c9ca7cc4f348c922b76726dce43", "e5d4554f83444013a6a0c00adefe5342", "3cb7088affa74f039af59ac546f91707", "6e85eb2eb42a42c7874d555d778c09d4", "6de3bc4b308446ffb3fec3f285a7cd78", "a8eb485cedc04325ad7842118768882a", "356d5245d3c442eab17c2f78c8abd9c6", "5ba1efbf8f374e849b8168862766a8f3", "adbdd3769ea849f0832c4476bf31d85b", "4b7cfac14555494d81a9be0ad1e57c42", "726d42b4d6384eb1baf519088f5ae774", "132a8601e0284ce0a5610e82b643015a", "bf103a63e11a4a06ae614b8be0c9887c", "6bf1bedd65ff4838924aa4cd9c41801a", "33aa1b2fa3374ef487e6af1fdf3539b1", "6818fd9d39154d34aa241a00274cbe09", "063b0f4c2ee74278a22620d7061acd7f", "d3ef1cc9e9f74dc3826e391107ba9daf" ] }, "id": "zFj1143IP46l", "outputId": "549061fb-4098-44f9-b23c-400060f25c21" }, "execution_count": 5, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "README.md: 0%| | 0.00/1.55k [00:00\n", "
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" ] }, "metadata": {}, "execution_count": 8 } ] }, { "cell_type": "code", "source": [ "df.duplicated().sum()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "xFGf9qgiQQJ5", "outputId": "336a9b47-9b5d-4bdd-c4bc-2c74fcb90749" }, "execution_count": 9, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "np.int64(0)" ] }, "metadata": {}, "execution_count": 9 } ] }, { "cell_type": "markdown", "source": [ "The dataset contains 19,535 records and 7 columns, consisting of 6 predictor variables related to engine operating conditions and 1 target variable (Engine Condition). The features include engine RPM, lubrication oil pressure, fuel pressure, coolant pressure, lubrication oil temperature, and coolant temperature. The dataset contains 5 numerical float variables and 2 integer variables. A missing value check confirmed that all columns have complete data with no null values, indicating that the dataset is clean and ready for preprocessing and model building without requiring any missing value treatment." ], "metadata": { "id": "V_NDM3UxQeyt" } }, { "cell_type": "markdown", "source": [ "## Descriptive Statistics\n", "\n", "### Methodology\n", "\n", "Descriptive statistics provide a summary of the central tendency, spread, and distribution of the numerical variables. This analysis helps understand the operating ranges of engine parameters and identify potential variability in the dataset." ], "metadata": { "id": "B1-2Br14QkUb" } }, { "cell_type": "code", "source": [ "summary = df.describe().T\n", "\n", "summary = summary[[\n", " \"count\",\n", " \"mean\",\n", " \"std\",\n", " \"min\",\n", " \"25%\",\n", " \"50%\",\n", " \"75%\",\n", " \"max\"\n", "]]\n", "\n", "summary = summary.round(2)\n", "\n", "summary" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 269 }, "id": "J5AZ1hgBQfsr", "outputId": "e222b635-c54a-4d76-98aa-465df09967a7" }, "execution_count": 10, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ " count mean std min 25% 50% 75% \\\n", "Engine rpm 19535.0 791.24 267.61 61.00 593.00 746.00 934.00 \n", "Lub oil pressure 19535.0 3.30 1.02 0.00 2.52 3.16 4.06 \n", "Fuel pressure 19535.0 6.66 2.76 0.00 4.92 6.20 7.74 \n", "Coolant pressure 19535.0 2.34 1.04 0.00 1.60 2.17 2.85 \n", "lub oil temp 19535.0 77.64 3.11 71.32 75.73 76.82 78.07 \n", "Coolant temp 19535.0 78.43 6.21 61.67 73.90 78.35 82.92 \n", "Engine Condition 19535.0 0.63 0.48 0.00 0.00 1.00 1.00 \n", "\n", " max \n", "Engine rpm 2239.00 \n", "Lub oil pressure 7.27 \n", "Fuel pressure 21.14 \n", "Coolant pressure 7.48 \n", "lub oil temp 89.58 \n", "Coolant temp 195.53 \n", "Engine Condition 1.00 " ], "text/html": [ "\n", "
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countmeanstdmin25%50%75%max
Engine rpm19535.0791.24267.6161.00593.00746.00934.002239.00
Lub oil pressure19535.03.301.020.002.523.164.067.27
Fuel pressure19535.06.662.760.004.926.207.7421.14
Coolant pressure19535.02.341.040.001.602.172.857.48
lub oil temp19535.077.643.1171.3275.7376.8278.0789.58
Coolant temp19535.078.436.2161.6773.9078.3582.92195.53
Engine Condition19535.00.630.480.000.001.001.001.00
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\n" ], "application/vnd.google.colaboratory.intrinsic+json": { "type": "dataframe", "variable_name": "summary", "summary": "{\n \"name\": \"summary\",\n \"rows\": 7,\n \"fields\": [\n {\n \"column\": \"count\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.0,\n \"min\": 19535.0,\n \"max\": 19535.0,\n \"num_unique_values\": 1,\n \"samples\": [\n 19535.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"mean\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 290.56786658279367,\n \"min\": 0.63,\n \"max\": 791.24,\n \"num_unique_values\": 7,\n \"samples\": [\n 791.24\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"std\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 100.24487342312848,\n \"min\": 0.48,\n \"max\": 267.61,\n \"num_unique_values\": 7,\n \"samples\": [\n 267.61\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"min\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 34.72442498409715,\n \"min\": 0.0,\n \"max\": 71.32,\n \"num_unique_values\": 4,\n \"samples\": [\n 0.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"25%\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 216.85746520303542,\n \"min\": 0.0,\n \"max\": 593.0,\n \"num_unique_values\": 7,\n \"samples\": [\n 593.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"50%\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 273.6622656017554,\n \"min\": 1.0,\n \"max\": 746.0,\n \"num_unique_values\": 7,\n \"samples\": [\n 746.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"75%\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 343.8010202968323,\n \"min\": 1.0,\n \"max\": 934.0,\n \"num_unique_values\": 7,\n \"samples\": [\n 934.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"max\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 828.9525637154856,\n \"min\": 1.0,\n \"max\": 2239.0,\n \"num_unique_values\": 7,\n \"samples\": [\n 2239.0\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}" } }, "metadata": {}, "execution_count": 10 } ] }, { "cell_type": "markdown", "source": [ "### **Observations**\n", "\n", "- The dataset contains **19,535 observations** with **six numerical predictor variables** and **one binary target variable (Engine Condition)**.\n", "- All variables have **19,535 valid records**, confirming that the dataset is complete with **no missing values**.\n", "- **Engine RPM** has the highest variability (Mean: **791.24 RPM**, Standard Deviation: **267.61 RPM**), with values ranging from **61 RPM** to **2239 RPM**, indicating diverse engine operating conditions.\n", "- **Lubricating Oil Pressure** has an average value of **3.30** with a moderate spread (Standard Deviation: **1.02**), while **Fuel Pressure** has a mean of **6.66** and shows relatively higher variability (Standard Deviation: **2.76**).\n", "- **Coolant Pressure** has a mean of **2.34**, with most observations concentrated within a narrow operating range.\n", "- **Lubricating Oil Temperature** is relatively stable (Mean: **77.64°C**, Standard Deviation: **3.11°C**), suggesting consistent lubrication system performance under normal operating conditions.\n", "- **Coolant Temperature** has a mean of **78.43°C** but exhibits a wider range (Maximum: **195.53°C**), indicating the presence of extreme operating conditions or potential engine overheating events.\n", "- The average value of the target variable (**Engine Condition = 0.63**) aligns with the class distribution observed earlier, where approximately **63.05%** of the observations belong to class **1** and **36.95%** belong to class **0**." ], "metadata": { "id": "xu1_RxVQQshE" } }, { "cell_type": "markdown", "source": [ "# 3. Exploratory Data Analysis\n", "\n", "## 3.1 Univariate Analysis\n", "\n", "### Methodology\n", "\n", "Univariate analysis is performed to understand the distribution of each individual feature in the dataset. Histograms and boxplots are used to identify the spread of data, skewness, and potential outliers." ], "metadata": { "id": "HAW57XR8QyCX" } }, { "cell_type": "code", "source": [ "df.hist(figsize=(15,10), bins=30)\n", "\n", "plt.suptitle(\"Distribution of Numerical Features\", fontsize=16)\n", "\n", "plt.tight_layout()\n", "\n", "plt.show()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 874 }, "id": "7n4Ger5sQxYj", "outputId": "366343fa-9f8d-4c7c-d775-a3aeab6ec11a" }, "execution_count": 11, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "
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}, "metadata": {} } ] }, { "cell_type": "code", "source": [ "plt.figure(figsize=(15,8))\n", "\n", "for i, column in enumerate(df.columns[:-1], 1):\n", " plt.subplot(2,3,i)\n", " sns.boxplot(y=df[column])\n", " plt.title(column)\n", "\n", "plt.tight_layout()\n", "\n", "plt.show()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 703 }, "id": "KSleeUqnQmxj", "outputId": "81cb9011-1291-4089-830d-a9bc4e839019" }, "execution_count": 12, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "
" ], "image/png": 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}, "metadata": {} } ] }, { "cell_type": "code", "source": [ "plt.figure(figsize=(7,5))\n", "\n", "ax = sns.countplot(x=\"Engine Condition\", data=df, palette=\"viridis\")\n", "\n", "plt.title(\"Distribution of Engine Condition\", fontsize=14)\n", "plt.xlabel(\"Engine Condition\")\n", "plt.ylabel(\"Count\")\n", "\n", "for p in ax.patches:\n", " ax.annotate(f'{p.get_height()}',\n", " (p.get_x()+p.get_width()/2, p.get_height()),\n", " ha='center',\n", " va='bottom')\n", "\n", "plt.show()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 492 }, "id": "VBXHvvK9QmuW", "outputId": "d02c3014-6783-4cdd-ea53-31912db755e9" }, "execution_count": 13, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "
" ], "image/png": 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\n" }, "metadata": {} } ] }, { "cell_type": "code", "source": [ "(df[\"Engine Condition\"].value_counts(normalize=True)*100).round(2)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 178 }, "id": "P1Q5F6sjQmrp", "outputId": "a75b1456-ab42-4295-8656-fc6a94426c8b" }, "execution_count": 14, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "Engine Condition\n", "1 63.05\n", "0 36.95\n", "Name: proportion, dtype: float64" ], "text/html": [ "
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" ] }, "metadata": {}, "execution_count": 14 } ] }, { "cell_type": "markdown", "source": [ "### **Observations**\n", "\n", "- The dataset contains **six numerical predictor variables** and **one binary target variable (Engine Condition)**.\n", "- Most numerical features exhibit a **right-skewed distribution**, with the majority of observations concentrated within normal operating ranges.\n", "- **Engine RPM** is primarily distributed between **500 and 1000 RPM**, with a small number of high-value observations.\n", "- **Lubricating oil pressure, fuel pressure, and coolant pressure** are concentrated within specific operating ranges but contain a few extreme values.\n", "- **Lubricating oil temperature** shows two distinct concentration regions, indicating possible variation in engine operating conditions.\n", "- **Coolant temperature** is mainly distributed between **70°C and 85°C**, with very few unusually high readings.\n", "- Boxplots indicate the presence of **outliers across all numerical features**, which may represent abnormal engine operating conditions rather than data quality issues.\n", "- The target variable is **moderately imbalanced**, with **63.05%** of observations belonging to **Engine Condition = 1** and **36.95%** belonging to **Engine Condition = 0**.\n", "- The class distribution is sufficient for building a classification model. However, evaluation metrics beyond accuracy, such as **Precision, Recall, F1-score, and ROC-AUC**, should be considered during model evaluation." ], "metadata": { "id": "aHjC2YbJQ82Z" } }, { "cell_type": "markdown", "source": [ "## 3.5 Bivariate Analysis\n", "\n", "### Methodology\n", "\n", "Bivariate analysis examines the relationship between two variables. In this project, the analysis focuses on understanding how each engine sensor parameter varies with the target variable (**Engine Condition**). This helps identify the features that have the greatest influence on engine health and supports feature selection for predictive modeling." ], "metadata": { "id": "fHJzaS0ERA84" } }, { "cell_type": "code", "source": [ "plt.figure(figsize=(10,8))\n", "\n", "corr = df.corr(numeric_only=True)\n", "\n", "sns.heatmap(\n", " corr,\n", " annot=True,\n", " cmap=\"RdBu_r\",\n", " fmt=\".2f\",\n", " linewidths=0.5\n", ")\n", "\n", "plt.title(\"Correlation Matrix of Engine Parameters\", fontsize=14)\n", "plt.show()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 804 }, "id": "ZTthgn8aQmpI", "outputId": "1af8b153-2e7f-4da6-e5f6-d1d1d793896a" }, "execution_count": 15, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "
" ], "image/png": 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}, "metadata": {} } ] }, { "cell_type": "code", "source": [ "target_corr = (\n", " df.corr(numeric_only=True)[\"Engine Condition\"]\n", " .drop(\"Engine Condition\")\n", " .sort_values(ascending=False)\n", " .round(3)\n", ")\n", "\n", "target_corr.to_frame(name=\"Correlation with Engine Condition\")" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 237 }, "id": "lQxgVFXJQmmz", "outputId": "d1d434c7-0d71-44db-ec73-2ff63a3d6e74" }, "execution_count": 16, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ " Correlation with Engine Condition\n", "Fuel pressure 0.116\n", "Lub oil pressure 0.061\n", "Coolant pressure -0.024\n", "Coolant temp -0.046\n", "lub oil temp -0.094\n", "Engine rpm -0.268" ], "text/html": [ "\n", "
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Correlation with Engine Condition
Fuel pressure0.116
Lub oil pressure0.061
Coolant pressure-0.024
Coolant temp-0.046
lub oil temp-0.094
Engine rpm-0.268
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\n" ], "application/vnd.google.colaboratory.intrinsic+json": { "type": "dataframe", "summary": "{\n \"name\": \"target_corr\",\n \"rows\": 6,\n \"fields\": [\n {\n \"column\": \"Correlation with Engine Condition\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.13393393894006106,\n \"min\": -0.268,\n \"max\": 0.116,\n \"num_unique_values\": 6,\n \"samples\": [\n 0.116,\n 0.061,\n -0.268\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}" } }, "metadata": {}, "execution_count": 16 } ] }, { "cell_type": "code", "source": [ "features = df.columns[:-1]\n", "\n", "plt.figure(figsize=(18,10))\n", "\n", "for i, feature in enumerate(features, 1):\n", "\n", " plt.subplot(2,3,i)\n", "\n", " sns.boxplot(\n", " x=\"Engine Condition\",\n", " y=feature,\n", " data=df,\n", " palette=\"Set2\"\n", " )\n", "\n", " plt.title(feature)\n", "\n", "plt.tight_layout()\n", "\n", "plt.show()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 733 }, "id": "r4NovcLJQmkO", "outputId": "65d34591-fdb0-4bbc-d6a4-0ff5b9f2ce29" }, "execution_count": 17, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "
" ], "image/png": 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}, "metadata": {} } ] }, { "cell_type": "code", "source": [ "mean_values = (\n", " df.groupby(\"Engine Condition\")\n", " .mean(numeric_only=True)\n", " .T\n", " .round(2)\n", ")\n", "\n", "mean_values" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 237 }, "id": "loqEd8uVQmhs", "outputId": "b99531d2-a869-4029-f86b-2916595bd946" }, "execution_count": 18, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "Engine Condition 0 1\n", "Engine rpm 885.00 736.30\n", "Lub oil pressure 3.22 3.35\n", "Fuel pressure 6.24 6.90\n", "Coolant pressure 2.37 2.32\n", "lub oil temp 78.02 77.42\n", "Coolant temp 78.80 78.21" ], "text/html": [ "\n", "
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Engine Condition01
Engine rpm885.00736.30
Lub oil pressure3.223.35
Fuel pressure6.246.90
Coolant pressure2.372.32
lub oil temp78.0277.42
Coolant temp78.8078.21
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\n" ], "application/vnd.google.colaboratory.intrinsic+json": { "type": "dataframe", "variable_name": "mean_values", "summary": "{\n \"name\": \"mean_values\",\n \"rows\": 6,\n \"fields\": [\n {\n \"column\": 0,\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 349.4414866278282,\n \"min\": 2.37,\n \"max\": 885.0,\n \"num_unique_values\": 6,\n \"samples\": [\n 885.0,\n 3.22,\n 78.8\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": 1,\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 289.1225312562132,\n \"min\": 2.32,\n \"max\": 736.3,\n \"num_unique_values\": 6,\n \"samples\": [\n 736.3,\n 3.35,\n 78.21\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}" } }, "metadata": {}, "execution_count": 18 } ] }, { "cell_type": "code", "source": [ "mean_values.plot(\n", " kind=\"bar\",\n", " figsize=(12,6)\n", ")\n", "\n", "plt.title(\"Average Sensor Values by Engine Condition\")\n", "plt.ylabel(\"Average Value\")\n", "plt.xticks(rotation=45)\n", "plt.show()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 625 }, "id": "cycjkTG-RIhw", "outputId": "9990b8d8-3f7a-4d29-dc4f-2f02b0972506" }, "execution_count": 22, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "
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\n" }, "metadata": {} } ] }, { "cell_type": "code", "source": [ "plt.figure(figsize=(8,6))\n", "\n", "sns.heatmap(\n", " mean_values,\n", " annot=True,\n", " fmt=\".2f\",\n", " cmap=\"YlGnBu\"\n", ")\n", "\n", "plt.title(\"Average Sensor Values by Engine Condition\")\n", "plt.xlabel(\"Engine Condition\")\n", "plt.ylabel(\"Features\")\n", "\n", "plt.show()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 569 }, "id": "w69yDtvVRIew", "outputId": "6ab7c97c-6fd0-40a9-b957-e03cb644d560" }, "execution_count": 23, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "
" ], "image/png": 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\n" }, "metadata": {} } ] }, { "cell_type": "markdown", "source": [ "### **Observations**\n", "\n", "- The correlation matrix indicates **weak linear relationships** among most predictor variables, suggesting that multicollinearity is not a significant concern in the dataset.\n", "- **Engine RPM** has the strongest relationship with the target variable, showing a **moderate negative correlation (-0.27)**. This indicates that Engine RPM may be an important predictor of engine condition.\n", "- **Fuel Pressure** exhibits a weak positive correlation (**0.12**) with the target variable, while **Lubricating Oil Temperature (-0.09)**, **Coolant Temperature (-0.05)**, **Lubricating Oil Pressure (0.06)**, and **Coolant Pressure (-0.02)** have only weak correlations with engine condition.\n", "- The boxplots reveal noticeable differences in **Engine RPM** between the two engine conditions, with **Engine Condition = 0** showing higher RPM values than **Engine Condition = 1**.\n", "- **Fuel Pressure** and **Lubricating Oil Pressure** show slightly higher median values for **Engine Condition = 1**, whereas **Engine RPM** displays the largest separation between the two classes.\n", "- **Lubricating Oil Temperature**, **Coolant Pressure**, and **Coolant Temperature** exhibit overlapping distributions across both engine conditions, indicating that these variables individually have limited discriminatory power.\n", "- The average sensor value comparison confirms that **Engine RPM** differs the most between the two classes (885.00 RPM for Engine Condition = 0 and 736.30 RPM for Engine Condition = 1), whereas the remaining variables show relatively small differences in their average values." ], "metadata": { "id": "MC5k3v3ARNtD" } }, { "cell_type": "markdown", "source": [ "### **Business Insight**\n", "\n", "The bivariate analysis suggests that **Engine RPM** is the most influential sensor parameter for distinguishing engine conditions, making it a valuable feature for predictive maintenance models. Although the remaining sensor variables exhibit weaker individual relationships with the target variable, they may collectively improve predictive performance when used in combination within machine learning algorithms such as Random Forest, Gradient Boosting, or XGBoost." ], "metadata": { "id": "Y_qaTMqzRRsH" } }, { "cell_type": "markdown", "source": [ "## 3.6 Multivariate Analysis\n", "\n", "### Methodology\n", "\n", "Multivariate analysis examines the relationships among multiple variables simultaneously. It helps identify patterns, interactions, and clusters within the data that may not be visible through univariate or bivariate analysis. Since the dataset contains over 19,000 observations, a random sample is used for visualization to improve readability and reduce computation time." ], "metadata": { "id": "0sYOnYRvRVe2" } }, { "cell_type": "code", "source": [ "sample_df = df.sample(1000, random_state=42)\n", "\n", "sns.pairplot(\n", " sample_df,\n", " hue=\"Engine Condition\",\n", " corner=True,\n", " diag_kind=\"hist\",\n", " plot_kws={\"alpha\":0.6}\n", ")\n", "\n", "plt.show()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 1000 }, "id": "2Fak4wLYRIb7", "outputId": "b17e79cc-2030-45cb-a092-72881de18cf8" }, "execution_count": 24, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "
" ], "image/png": 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S9M5gACO9Ri9MVS+4/ZaLXMfrFrdofPurFxgIKHzm9yCILnpJkiRJkiRJknSlCy91AZIkSZIkSZIkSVcaZ8BIl1gYhuSb9XXHs1yBlWD9r2pnFhPEzXXHgyx7U/VJkiRJkiRJkl4/AxjpUotjGt/923WHCx/7Le57YXbd8S9e1bXOEmNrSh/53JsoTpIkSZIkSZL0RrgEmSRJkiRJkiRJUps5A0a6zIVhyCc2l9Yfd4kxSZIkSZIkSbrsGMBIl7s45vi9X153eOiLX7iIxUiSJEmSJEmSXgsDGOmSC4iz4FXHJUmSJEmSJElvLwYw0mXghanqumO3XMQ6JEmSJEmSJEntEV7qAiRJkiRJkiRJkq40zoCRrnjrLXEW0IoTyEcXvSJJkiRJkiRJutIZwEhXvGzdJc5uzrKLXIskSZIkSZIkvTO4BJkkSZIkSZIkSVKbGcBIkiRJkiRJkiS1mQGMJEmSJEmSJElSm9kDRnoHC4KAqFEH1ukFkysQh+a0kiRJkiRJkvR6GcBI72RxzOP/5f9ad/imP/x9KJQuYkGSJEmSJEmSdGXwT9slSZIkSZIkSZLazBkw7yCdWYtPbF5/NkNEehGr0dtDQD1bP6fNhwFRlqw/niYQt9Y/fC5PK4zeTIGSJEmSJEmSdFkygHkHCeIWx+/98rrjQ1/8hxexGr0dZBnc9/TkuuP37B8hCl7lAHGLxre/uu5w8WO/BQUDGEmSJEmSJElXHgOYy0wSRLTSdRqi85tnHOidKCDOXi0FebWxVxdF4avOmupOm6RJvP6Zs/U/y5IkSZIkSZJ0JTOAucy00uzNzTjQO9ILU9V1x255MweO4984a+rx//J/rX/uL37hzZxdkiRJkiRJkt621m/uIEmSJEmSJEmSpDfEGTBtdqmXEKtk8bpLRkWkb9l5JUmSJEmSJEnSKwxgXqN8Pn/O61zuwreu0cr42rPT6x7nc9cOU/q1Y/36+8Nw/abkQRCSz68/nlVXOPGVv77g2NDvf4EgePX1y9Ybf3n7G31/O8Yv1rl/0z24lLW9FeNv7bmD3/B5Ds77bkmSJEmSJEnSlSDIMrtkS5IkSZIkSZIktZM9YF6n1dVV/tW/+lesrq5e6lIuinfS9b6TrhXeedcrSZIkSZIkSReTAczrlGUZR48e5Z0yceiddL3vpGuFd971SpIkSZIkSdLFZAAjSZIkSZIkSZLUZgYwkiRJkiRJkiRJbWYA8zrl83k+//nPk8/nL3UpF8U76XrfSdcK77zrlSRJkiRJkqSLKchsACFJkiRJkiRJktRWzoCRJEmSJEmSJElqMwMYSZIkSZIkSZKkNjOAkSRJkiRJkiRJajMDGEmSJEmSJEmSpDYzgJEkSZIkSZIkSWozAxhJkiRJkiRJkqQ2M4CRJEmSJEmSJElqs9ylLuDtZHp6mjiOGRsbY2JigizLLnVJb7kgCN4x1/tOulZ4e13vhg0bXtf+4+Pj5217O11vu3ntXvvFvPbX+32VJEmSJEm6UjkDRpIkSZIkSZIkqc0MYCRJkiRJkiRJktrMAEaSJEmSJEmSJKnNDGAkSZIkSZIkSZLaLHepC5B0cURRRJhlpEFAkiSXuhxJkiRJkiRJuqIZwEhXuCAIKC/NEx98lnhygrCzi/JV1xEPjV3q0iRJkiRJkiTpimUAI13BgiCgNHma6ve/QRa31jbOTNI8dojKLXeSDQ1d2gIlSZIkSZIk6QplDxjpClaIW9Qf/OEr4cuvqD32C+LJ8UtQlSRJkiRJkiRd+QxgpCtYtLxAsrRw4cEsJZ44RRAEF7UmSZIkSZIkSXonMICRrmBZmr76+AVmxkiSJEmSJEmS3jx7wEhXsKyzm7BcIV2tXXA8N7qRLMsuclV6u0mCiFb66p+TfBgQZclFqkiSJEmSJEm6/BnASFewZqlC6aZ3UfvZD4Bzf0AvbN9DbnQTLCxcktr09tFKM+57evJV97ln/wiRq9lJkiRJkiRJZxnASFewNE2Jd15FR7lC48mHSZbmCYtlCldfR7BrH2G5bAAjSZIkSZIkSW8BAxjpChdnkGzYSn50E4VmgyzK0SoUXXpMkiRJkiRJkt5CBjDSO0CWZTSDEIrltQ1pShC4XpQkSZIkSZIkvVXCS12AJEmSJEmSJEnSlcYARpIkSZIkSZIkqc0MYCRJkiRJkiRJktrMAEaSJEmSJEmSJKnNDGAkSZIkSZIkSZLazABGkiRJkiRJkiSpzQxgJEmSJEmSJEmS2swARpIkSZIkSZIkqc1yl7qAi2Fubo6//Mu/5Mknn6TRaDA6Osof//Efs3Pnzktdml6DMMqRAhEZSZJc6nIkSZIkSZIkSfqNrvgAZmVlhS996Utcc801/I//4/9Id3c3ExMTdHR0XOrS9BtkYY6JasovxxdYrrcY7iqyf6ybwWJKlqaXury3XBLmmG9kzFZbFPMhw5UcHWFClmWXujRJkiRJkiRJ0m9wxQcwX/va1xgYGOCP//iPz24bHh6+hBW9PYVhyGoaUmtlRCF05zOyt3I2Shjx5OQqDx6ZPbtpZqXBgcllPr5vlG1dIekVHMI0gjzff3GOY7PVs9uKuZAPXTXC9iv82iVJkiRJkiTpSnDFBzCPPvoo119/Pf/b//a/8dxzz9Hf389HPvIRPvShD637nlarRavVOvs6CALK5fLZf//qf690QRBQbyU8Pxfz0LE5lustwgC2DXTy7h19dIXxW3LehVbIQ0dnz9uepBk/PjTD2A2jFIL2zgS5XJ5tGEU8cnz5nPAFoBGnfOe5M/yDmzfRE735a79crleSJEmSJEmSrkRXfAAzNTXF/fffzyc/+UnuueceDh8+zF/8xV+Qy+W4++67L/ie++67j3vvvffs6+3bt/Nv/+2/ZWho6Oy20dHRt7r0y8ZDx2b5+YllCPNUKnkAztRSvntokX9wy2YGO4ptP+fxo7OUypULjiVAIyqxdbir7eeFS/9sJ5fqHF+cp1K58PWfWc24avdY2853qa9XkiRJkiRJkq5EV3wAk6YpO3fu5Atf+AKwFqacOHGC+++/f90A5p577uFTn/rU2dcvzxCYnp4mSRJGR0c5c+bMO6IXRzPI89CxBWqrNfi1y63V4PlTs+zuCdtyL4IgoNhYJZifZWS5xvuKBY5kHby40Pr1U1OtVpmYWHnT5/z1818Oz3YhzrG4XF13fHw2x1QPJG9yCbjL5Xpfi7Gx9gVOkiRJkiRJknQxXPEBTF9fH5s2bTpn26ZNm3jooYfWfU8+nyefz19w7OUfqrMsu+x/tG6HWpyx0ojPC19edmq+xp7erjfdkyQMQ0rTE9R+9C3SWpUkDanOrLBjy3aGbrqbn83EZ0soFyK6ixFZ1nrVY75Rl/rZFiMo5yNWWxcOWIa7iiRJ0rYaL/X1SpIkSZIkSdKVKLzUBbzV9u7dy/j4+DnbxsfHz1lOTOuLQghfpUVIpZBry4/3xdoy1e9/g7S2NvOjGEFfpcDKiaP0PvcLNnQXAAiAO7YN0BG+udkfl7OOKOW6jb0XHCvlI7b2lgxMJEmSJEmSJOkyd8UHMJ/85Cc5ePAgX/3qVzlz5gw//elP+f73v89HP/rRS13a20J3DrYNdFxwLAB2Dlbe9OyXIAjIJsfJGvVXtmUpI10FNvaUaRw/zL5ii7GeMp/aP8ZV/fk3fc7LWZIkXD9a4fpNveR+Jf3qLRf41LWjdIbxJaxOkiRJkiRJkvRaXPFLkO3atYt/8S/+BX/1V3/FV77yFYaHh/nDP/xD3vOe91zq0t4WsjTmvTsHOTWzyEKteXZ7ALx71yD9hQzeZBYSBAHp0sJ528MspbcY0FMsUO7LsWtggDBLyLIrd/bLy3JZi/ds6eC6sS6WGgn5KKCvGFIgdvaLJEmSJEmSJL0NXPEBDMDNN9/MzTfffKnLeNva0Fvm89eNcmqpycmFGpVCjp0DlZfCl98choRhSBAE6zaNz7KMsLd/3fcHuZCoWCBI4/Va0VxxwjAkF7cYyBJ6O4okaQJZ8o65fkmSJEmSJEl6u3tHBDB684q02NkdsLu3iyzLSNP4N858yaICU7WEI7NVMmB7f4XhSkSUts7dL8sIRjYQliukq7Xzz71jL83OHriClx37VaW4CUcP0jzwNFkckxvbSHHfDdR7Bq7opdckSZIkSZIk6UpiAKPXLMuydWexvCwIAupZjrkmPHxinjSDnnKegIynJ1bIh/DubT3ks3NDmHqxQuVDn2H1x98meXk5siCksG0n0U130nqHBA/FpEXrx9+mNX7y7LZkeZHmsUN0fPQear2Dl7A6SZIkSZIkSdJrZQCjtqpR5NFTC3SUC6TATw7PMrlcp6OQY0N3kffsHODUcosdXcE5vUyyLGO1b5DCp36XaGGOrNkk6Oik1dNHPXtlGbO12TdXbhgTTo6fE768LGs2aTz2c/If/AytC7xPkiRJkiRJknR5CS91AbpChBETjRx/9cQ4j55cYrmR8vDxBZYbMVkG1WbM5EqTrz09wXQtIQmi8w6RZRmNKE9tYITVsc3UuvuICVhKcjwx2eT+I8v8crrJcponDK+8j24ul6N15MV1x1sTp8mtVi9iRZIkSZIkSZKkN8oZMHpTgiAgyuV5aqrOd1+Y5uBMlatHu/n50TkOTq2wpb9MnKQ04pQ4zQiBJ04tcvPYGBC/6rHDMOT4Ssa3nztNK1mbLfMC8FAu5JPXjLGhfO4smneE4FIXIEmSJEmSJEl6La68aQS6KIIgYJU8z88nPDrZ4Cu/PEM9BYKAzmKO6eU6GRnjC3X6OwoApC+FJYurTdLXkJtU04jvvTB1Nnx5WTNO+d6BKRrZ+vlhGIaUV1coT41TmZ2kFDcJgnPTi0KhQLFUolAovL6Lfx2CIKCQJVQWZynPTFCuLROFF05R4jgmv3PPusfKj20iLnW8VaVKkiRJkiRJktrIGTB6TVpBjlaaUYgCclnMUpLjvqcmWGnE7B7t5cxyne5KkVorZabapKech/mAVpqeDT5yQUAYwMaeEoUwIyA8288lDENqaUSSBeSigHKQMLucsNpKLljPcr3FXD1htHT+WD5NCJ97gtpTj5K1mmvH7+yifOcHaIxtISPk9GrAIwfnObPUYHN/iZs29rKh0t7ZNEEQUF6cpf7T71GfnV7blstTvHo/uetuoRHmz3tPOryB/MYttE6fOPdYhQLFW+6k1tYKJUmSJEmSJElvFQMYvapWkONnh2d48OAk1WZMdynPrdv6mKnWWGmsLSGWZlCLU5orDSr5iMOzVd69Y5DDM1UacUqWQRQGdBYjtnbluWMwR/7RByDKkduynVrvCCcW6jA5TnL8EEHconvHLlqjO9YvLIAkTakszZHV6wTlCq3uXmICohOHqT3283N2T1eWqf7gm3R87vf5ea3M//cXx4jXsh+eGofvH5jmv7tzGwMDadvuXaleo3b/35HWXunbksUt6k8/TjmXJ7zutrMB1MsaUZ7Sez9K/tghmgeeJotjcmObyF99PfWefkjbV5/UTmEYrs2CexX5MCDKLhyqSpIkSZIkSVcaAxitL8zx8+PLHFloUltdm0kyW23w9Wen2NRXYaizyHytSS4KSdOMaitmsL9CIR+RpBm3bu3jl6cWGeoqsrGnSCVtsZNlhl48yOKx5yiGGeHRg5y65WNkzz3Bwi8fO3vqxWefoveTnydKCyRhdHZ7lCZQr5HLUrpPLlH/2d+T5PNkQUhhy3Y6b38vK089euHriWNmFmt85dm5s+HLy+qthHsfP8XOoS6Kr+HWBFGOOAvIBRlZcn4vmyAIyM6cOid8Oed8z/2S8u5rqBfL54/lCgS7ryG/62pIU5JcnlqaGr7oshYnGV97ZvJV97ln/wiRfYwkSZIkSZL0DmEAo3XNN+HZ8QXKlco520e7SlTyObq7SpTLTQY7Cvw/bhtkfmGFmTjkx1MxPzo4zVUjXfzRndtppQlBBhtXp0ifeoHjh18kAPorBbqvvYrg1FEWH38Youic88TPP8n2rTdxKI4gg1zcJD51nLBYYndvRMdPf0zr+CFyoxtJu3poHj9MlLQIu7pJFufPv6BcjlPzqzTPz0sAOLPc4PRinZ2VgCxbZzmyMGJyFR4/tcB8rUlnMeLGTb1s6owI0lcOHIYh6czUuvc2a9QJGqtwgQAGIMsymgQQRgYvkiRJkiRJkvQ2ZACjdU1Xm/x6DLFpoIuZWsw3HjvJtoEOPjCaJ/rFz+k6c5juVotcPeMfX3sDh3ddRaNQ5sGj01QKeT62o5uVr9xL0mgAkAGztSaFrn7iBx8gazYIyh1kv3LGlSOHuXXzFno2XsNzU8vUxycohnDTnjGuOfQzsmMHAYjPnCZfKhPnCzRPHqe8/yZap46fdz1BGNEIcyRZi+ClGn5d69enxvyKMAw5sBDz/RcmSV9680INTs2vcsf2AW4eLZGla8srpWlKrqtr/Zsb5SB3fg8YSZIkSZIkSdKVwQBG68qF4TmvszCiHmd876UAYndPjs7Hf8TSiaMsAyNdRUpJTOG5x7gxa/HVjquZrMaEQZPD3REbi8WzAczZYyYpWb0GWUbK2tpEpVxISsBSvcXiY79g5NM76dzSx/CWa+lbnad3cZLqgSehp49ktUrWbJJVl6F3gDQMCTs6L3xBrSabxwaJn36RrBUTRBFBoUgarX0NyvmIke4iWXbhVve1LMcDh6eppyFhALkgJc1C6knG9w7OMtqzmcFSSJGYLMuINm6F6EF4aYmyoFCguHErUT5PWCxBq0khS2kG4QXPJ0mSJEmSJEl6+zKA0bqGOnLkwpcaNgQhpXzEk6cWABjsLPDB/pTWwgRZd5EgCKg1YqIwZGJxlfDRx7jlE7t5iCITS3UmqjF7R8doLC2dc4705BEqO3axMDlNLksZzsXkq8vErZjBjk66xrbys2rGU0eniOImv72ri0ozJj5zGtKU3MgG0jAii+O1vitZRjA0SnHX1TQOvUAQQNhqEhDQcetd5BbHuWt7Pz9+foIsSciaTYJKB1m+wEeuHmFbXwcLc+cHMHGY59Bsk6fGl4nTlCgM6KsUgZSZlToAvzy9xPzKKh/fN0x/PqHe2UvH+z5K7Sf3QxBQ2bmH1Z9+n2y1Sji2meTpx8mPbaT8no+yus5SZJIkSZIkSZKkt6fL7k/vZ2Zm+I//8T/y3//3/z3/+B//Y5577jkAlpaW+PM//3OOHj16iSt85+iOUt6zawiARpoRBgHL9Zj37R7kc9dtoLiywPjSKifmV5labpBk0FvOEwUBYZYyQp1yDkr5kGIxT2731eccPwA4fpC+nbvpH+pntLVIfOIItelp6vNz5OcmyY+M0Zs2ODK1zPOHx/nhkXmeTjpo7L0Rooh44iRhqbS2fFmWkRsYptE7AHe8n55P/y4dV++ntPtqSlfvZ/lH3yL79r38zpY8v3vbdoZ6KkRhwGg54B/dtpn37+ilXDw/kwyiHA+dXGZyuU78Uj+WJM04Oldjttak46X3ZGQs11t889lJGlmONMuob9pO5bP/Dd3v/zjNZ54g7Ogk3LiV5KVZN62J07Qe/CF5G5NLkiRJkiRJ0hXlsgpgTp06xb/8l/+SBx98kOHhYWq1GulLP3h3d3dz4MABvv3tb1/iKi+OIAgIw4v/eJIwz1Qz4uBixskq7Bgo8bs3beSqkW7K+YiPXztKo5UyudLgdDUhyyAMAppJSjNJmVpusLm/QlchIsrnydKU4c4CI51FHkr66Hv/xyh29wBQKhbIBkY4E5bZ+enP0tnfR7mQp5SP6N+ymfKHP8MLzx4m/8zDbOkMCaKIIzNVji00mLn+vaQ79kEG6eICQaVC1N1H6X0fpRlEpFFI48gBVg48R/X4EVZ/+QjJ5AStE0cI/q//Jx9rHuZfXlPkX79/M/9ib567S0sU0sYF78liC54ZXyQMoKMQrd2nDOIkZa7apJiLiMKAzmKOJMtYqreYXl3rBZNlGavlTuIkoRXliEsVkl9bcqx56jj5pYW37qFKkiRJkiRJki66y2oJsr/8y7+ko6ODf/Nv/g0Af/RHf3TO+I033siDDz54KUq7aIIwZLEVcnKxwUqjxXBXiQ2deUrBWl+RN3XsKMdiE+pxRjkf0JOH9KX+JACrFPjO89OML6ye3dZRyHHPzdv40J5Bnp1YhDDPkekqBydXGOztISJHq1EnCKDRSugq5QkJqPT2cibXSUcBPnT1CFmWcmgq4/vBGHvv/i0GaLBxsJufzaUsLKcEZ54lHNjMyLU3UWsmTC8sM//0iywvVQknZ7jxQ9dwdDIiX8jTbK7y3acn+Z0P3MPoVfvWwqp9N9AaGGY1X4Qso1Bdpnbg2bP9V/iVe5fMTpMtLlA5dICe3j4IArLeW9a9b4v1hCTNOD23wvt2DvLtp08RE0GWQhASpxnv2t7P1NIrS5dVmzGU14KWIAhIl5fWOzxkKVljFbp6X+cTlSRJkiRJkiRdri6rAOb555/nt3/7t+nu7mZ5efm88cHBQebm5i5BZRdHEIYcWkz5/gsTxOkrgUFPOc9nrh2lK2y94WOvkueBg/McnVkhzSAXBuwZ6eLOrT0UshZBlOOBg3PnhC8AC82UP/v5Ue7a3sfJuVUI61yzoZu/e3qC+07E/NHdH2bu+98iSxLSDFZbCWk+z65Pf4bO3hFuLIRUwgQI+L0bNzD/UpjRV4oo5HN0NlbIcjGTwzvo6R7g9LEXqI+f4sxSnVI+R8ZaSFQIAQL2behl+sVpmvkSz06v0re8RNDbRzC6mTjLXglaVmtk8Sv3KygUIQwgzSCKyHX3UKwu0/jlo5ClRKUK5WIJGDvv3uWjkDBLWV2pUZqf4p69Azwx0+LobJWeSoFP7x9lemmVk3PVs+/pLuWAtdlbWZYRdnWv/3CCEEr2gJEkSZIkSZKkK8llFcCkaUqxWFx3fGlpiVzusiq5rRbj6LzwBWBxtcUPD83wmasHXpnR8TokYZ7vPD9zTrgSpxnPTSwRpxkf3tnDYhOOzqyc874mIUdnaxCEXD3Syea+Ms9NVRnqCpirNlluxPxF2MXvfPL36Jw6Dkvz5AdHCPbsJb9plJFmE0h4aRU5yqSUS2v/TsOMJyaWuf/ANNMrDTZlVVpnJrh5515u6upm7olfErC2zFfH4BBH4gLbhrroSBucbMUQ5RjoLJKM16hcdTervz47qFCAIDgbyCT5AlHfIMnsNJWb30X90Z/TOHYI0pTc0AirB5+FE0fo+PwfQJgH1maulFeWGJpboGNmguXpWWa6ulmoNtnZ38nIll7q9Sat2RlOL6bw0pJxA51FBkovzZB5STY4QtjZRbpyfrBY2LyNuLtvLRySJEmSJEmSJF0RLqseMDt27ODxxx+/4FiSJPz85z9nz549F7mqiyMIAk4vNs4LX152en6VxQu3KPmNZuvpeTNbXnZoapn5l5YlO+fUAcxVm8TJWojQaCVMrTToKuZYrrfYOdRJlsHppQb/54EGfx5v5d6BW/mrZBMThZ51r+Nlp1ZSHjo6S08pRz4KaRQ7CHJ5Hjk0wZHuTWwa6mZjb4mhrhKD77qLjsEBrt/Uy4EDx4G1/jEbc01K199Ga3jDecePO3vJb9h09nUG0D9EfsdugiAkmZ8lLBTJbdhM1jtAlkFWX6Xx5MNELwUp5ZUFat+6l+gX9/PBLV1EzTrxmXGak+OcmVlkcWaGfaOdHH3xCGGzDsBId4lP7Bsmn507W6lRKFH54KeJevrOucn5DVvI33E3LcMXSZIkSZIkSbqiXFbTST73uc/xv/6v/yt/9md/xl133QXAwsICTz31FPfddx+nT5/mv/1v/9tLXOVbIwiCtb4h68jgDf9Iv7i6/nHTDFYaCT2liFwYnA1Okixgqf7K+8Z6ytz3y9PsGOyko5Tjxk29nJyvMVNtEqcZURSyc7CDPcOd9HcUCMlI1zlnEOV44uQsADlStvWVWWmm5Ldsh9lJDs7W2D62hdrUGfZ88H08WdrAz56bJgS2bd1Jby7jY3sHGcvHpJVOouV58ivLBMUiSe8AzVyBVpZRedcHSL//DZL5tXOFw6OUt+4kWK0SDo3QnJ+jOT0JZIRZRpAmNI+8SOHam8mKZVpPP066utbXZdNTP+T3rr6Go3GByWqLka39bC+06Jl9lr27BmiOjpDv6aa/GBCm5y8Vl2UZqz39FD75O0QLc2SNOkFHJ62eflYJfuMzDIKAJjkWGylpltFdjKiECWm63l2+sCzMsdCE+dWYQhQQLdcJguBN9xeSJEmSJEmSJJ3rsgpgbrzxRv7ZP/tn/MVf/AXf+973APjTP/1TAMrlMv/sn/0z9u3b97qP+9d//dfce++952zbsGED//v//r+/6ZrbJU1TRrrWX36tmAup5EMged3HLuejVx0v5EJ68rB7pIvnJ85vFt9bztNZyrHUSPjJ4Rk+tHeE7lKO9+0aopWkjPWUmKs1OTJT5ZnTi+zb0EV+7zBbKxFk59cbZwHV5ivbI1J6ChCWKyzkt7AQxDT27GN8sc6PllI251L+4Lat1JoJw10FNlKl/OD9tHp6iA88S7IwR9bZTRoERN29lO/+GKu9g9TKnRQ/9tuEc5NErZjWC0+x+tiDJCePkDabFHfvo7J3H40nHyGdPkPSrBP09FM+dYzK6EaWTx59pej6Kl33f5kbunsIO7qIlvvJhsdoTZyiD+j8zO9Ry3ewburEWgjTiPIwMPIbn9mvCsOQk1X48cFJFlabAFQKEXdsH+Cq/jykr+0z0QrzPHB0kRfPLPFy3NJ3fIk7t3SxrSske51hjiRJkiRJkiRpfZdVAAPw3ve+l9tuu42nnnqKM2fOkKYpo6OjXH/99ZTLb7xR+ebNm/nSl7509nUYXlarrwEw0pGjv6PAXLV53tgNm3rpjF7pp/J6DFYiOgq5C86w6e8sUcznOFNrcdvWfpI049DUMpDR/dLyYB++eoTFaoMsW1um7LsvTPKZ/WN0FCNaccAjJ+Y4MbdKnGRs6Cny/PgScysNfu+GDezoOn92RT7IGOgssFA79zrjFBIC+nq6oVBiNWsy0l1ksZHxrV8cIyRjByt0N1f41PXXM/jQd2g8/xQAUf8gweAIydICte99ndKnf496oUwjl6cwsonkge/QmDhFlmXkN24lyOUJgoDk+GGijg7ik2tLtBU2b2P1hV9SXFogzF6ZxZMWioSVDtKlRdKlRYIoRzA8tnY9Y5uIu/tf/4N5jWabId985vQ5y7rVmgk/PDBFx/4xtnT85hksYRjy5ESVA2fODdgaccp3njvD7960kf782n5ZlpEkrz/okyRJkiRJkiS94rIJYBqNBv/0n/5TPve5z/GZz3yG2267ra3HD8OQ3t7eth6z3QpZi09fM8KPj8xxYrZKmkEpH3HDpl6uHymTpusvJfZqykHMR64Z5b5fnmF+tUkUrs2mqRRz7B7u5q8fO0krSSnlI967a5ibN/dRbbQIcjkOTi5zeKZKVw52DHbw5KlFyvmIg9NVFlebfHr/Bn5xfJ4NPWXqrYSVeos4zag2Ex48Osum60bIc+6SXGkSc+PGHo5Or1DKR1SKeaZrMUemV2iu1rl1IOKHP3uC9+4ZpVbu5T8/PUO9lbK9MySdmKZVKlCrNanNz68FaWlKMj9LvqePOF8grVUJps4QbN5BMyyytLTMSmWM0vZORioR0cQJ6k89Cq0m+U1bqdxxN81jhwlyOfJ7rqHxxMO0GnWKA0Nkp4+TBOHa7JqxTXDmNGlthfyuvdTnZils3k7+Xe9nNTg/0AvDkCAISNP0DS/xFYYhz02uXLCnTgY8cnyeTdcOEiSv/tmopRFPn1684FghFxLOz1CYOU48fpKwq5virqto9A2/gflWkiRJkiRJkiS4jAKYYrFIFEUUi+svw/VmnDlzhn/yT/4J+XyePXv28IUvfIHBwcG35FxvRkfQ4pN7+lhs9tFKMyr5kI4wecPhC8BqluPp0/PsG+2iFqcsrbbo6yyysafEcyfnaCVr8zzqrYSfHZnm7t3D7OyJSJKY3k1dDCwmPHdqhrt3DxGFASuNmDhJyTJ47MQ8YQCn5msUciERKUGaUggylmoNqgl0RHkCMgpBerZnyVgl5FPXbeaxUwucXqhTzEV8cNcAHWmTU4eOcnJ8lq8lOW6/qsRtQ3ma5S56syZbu4bpnDnF0Oxx4jPjFLq6yZKEZGWZrFGHfAGAdHmR+bTIV5+YYH5qmtrxCTZs2cDtUcauyWkK1WWCRoP6Yw+SrqzQ/enfJW2uvY5PHCFOEkq//UV47klypTJxqUIS5Qg3bqXU3UP+tveylO/iZJKn1UwZiHL0FNb6yIRBQGl5geT0MdLFBfKDwwQbtlIvd7zuICYLQiYW6+uOz9eaNOKA0m9oI9NK157vr8tHAe8urrL8t/fSVYIsW3s+jReeoXLHe2H3tYYwkiRJkiRJkvQGXDYBDMDtt9/OL37xCz7ykY8QBL+5MflrtXv3bv74j/+YDRs2MD8/z7333sv/9D/9T/y7f/fvLrisWavVotV6ZdZGEARn93u5rnbWd540oefsk1kLOt7o+cIw4hdHFzk0tQJALgwo5COePFHlW0t1fuu6jcxUG3QUc7yrK6Y0cZDw+z+DbRsob99F1DvAR/eNcvVQkclqwj37N7DcTJhcbpCPApbqMQemlonCgFzcXGtan6V0lRJiCtSWVzk5v8h4UmCoq8S+4Q4qYczp6trSV7UYZmot4iTl5Jk6H9jeR9Js0l3KsXXLKMtRiUNziyxlMdf2F9kWBDRPHKWxdROt6gr5xRnCrh7Czi74lWXlGht28OcPHefwdJUtBQhzOaqLy3z3hVPE19/C/rkJgvkZSEqQxjSOHiRr1ElOHj3bU6U5foLyez9K69hBwrhFUihR3LMPdl3D4ysRP35m+mx4FQZw7cZe3rW5m8qpF1n50XcIXwozmi8+C8USHR/5LPW+odcVwkQBdJVyTC1feLycz5GLIMhe/fNRiNb6xtR+pfcOAeyoBMQ//iHlLAZ+tVdQRu3hn9C5YTOrnb2vuV5JkiRJkiRJ0prLKoC58847+U//6T/xJ3/yJ3zwgx9kaGiIQqFw3n47dux4Xce98cYbz/5769atZwOZBx98kA984APn7X/fffdx7733nn29fft2/u2//bcMDQ2d3TY6Ovq6arhUzizWObU8T6VSOWd7NW6RBRHzjYQNAz3clk2z8t1vUG02CIBGdZrm809Tec+HGC908pWnZzg2u8LW/g6++8IknYUcn75ujFI+otpM6SmEZKtVwiBg82APpRx0x1WS73+N4pkJrtl1FVx3G8/O5Ll2Qzc/PX6GKF8kHyQs1esk9VXS2grfrNb45O4tLM4uMBcH/P0vx+kNY4JiwMkjxzkyO8VHrruTzvFnGdx7DeGzj5EtzpHv6SXX0UlQrhB0dHEw18Px+QVyuRz1XI6unm6y+RkIAh4+MsOuq26h65HvExSKkCSkB5+nsHdttkcuWvtaFMc20Tr0HLnuXorX3Ehp3/WElQ4OTa3w4POnyBdL5H/lnh6aazLWUeeaJx+muLpCujBPlsZEnT2EAfDITxj6rS8SdXa9rmd4R1piojp+wbHbdg6yZfS1zeR61+6MB4/OnbNtLFmmsTjPwGAH5eL5/zsoLs7Ru/vq11WvJEmSJEmSJOkyC2D+5E/+5Oy/n3/++XX3+/KXv/ymztPR0cGGDRs4c+bMBcfvuecePvWpT519/fLsk+npaZIkYXR0lDNnzrzhvh4X03wrYmmles62IAgISYnjmNmVOjf3BlS/9x0atbUApa+jyOmVFunW3cSTNVr5GbpLEXfvGeL/9ZPDNOOMeivhLx85wX/3rm383k0b+enBSXqK3XRHGcUgIaiv8p7t3az87XOkBCSd3Rw5fIrn6GFhtckTJ+cY6iiQD4E0IQOyNKO62qIZ5ukdGeS7T45T6e4maTToDTNaS0t093RzeLHJ5k07KDX7yaqLNA+/QNqo0whCgihH5d0f5tB8gzheW7ZtJg3o6huChRnIMlaWq1R3jlAJAvLbdtOaGicsFElaTQDiJKZ8y13Upqdo1WpQq9EMQqpbd5OtVHn4yBLVau2C9/vRF+bZGhUJjh0+u621tEQwM0mu2YTjR1jtH17rXQNnl2R7NT1hxPWjZR46OsuvtoLZO9LFts6MiYmJ1/RZ2NmdY6a/wDPjiyRpBgEUOjIGuguEaYtarXnee7LFRRYvg8/62NjYJT2/JEmSJEmSJL1el1UA80//6T+9KOep1+ucOXOG97znPRccz+fz5PP5C469/EN0lmWX/Efp16IYBZTy0Tn9P7Iso7uU58xyg55Snkptltr8ImEAPeUCs3FI8Y73cf/heaqnT9I4lfBio8CH9o5wx7ZBHjo+RzNOaMUpX396gvdu6+G39vSxuFSlNnGazcWUzYVlOn70PYZuvZmZUh/fHG8xPnuCwvAIS8N9ZElCa36OQrNKX76LqWaDoFgkazVJMlhoJGRpylg5Yj4J6S4XuOqWfZypJZxajXmqr4dCocZoVxfdt70HCkXYupO4p596sUznaoMoDEjSjDTNOFUP2DayiTA9SZillDo6ibbuJM7liTZto7RpG3GtSuGqaylt3UVzZZnWxKmz9yzs7l0LS4KAuVrrQrcagNryCo0gT+nXtmfNJunMFCQxM82I4/M14gQ295UYKofkslfp8ZPE3DhSYnvfJsaXGyRJxlhPkYFiQJC2eK2fwlzW4t1bOtk/2sliIyEfhewupyw/Xl5bOu4CouExGq8hJJIkSZIkSZIkneuyCmDuvvvut+S4//k//2duueUWBgcHmZ+f56//+q8Jw5B3v/vdb8n5LicdUcL1G3t46NgrS08lhMzXmmzqqUAAy9VVqvUWXaU8KdBx423c99wk1dUm+VxIEicQBPzs6CzXjnXTU8qxWIdGK2E1Tjkxv8p1hRluOfwohaRJfPwIc+MTrGYZ0anjdP3hP+fU0y+SAfHiIsOViN7qLPWZacJ8SN9gjmoUslJdJSyV6CwEzMUBgz1lKsvTDA6NsH3LCF9/+EUaCdBsQG2FQxNHef8d13BjeQU6u2gMjq2FYknCrv4yQ50Fziw1AGjEKQulTvLFDrYPVOhcmiSJciRZQNLRS3r7h2imGf2HnmT5wHMEuRCCELK10CW/ex+1JCGKorXjLq6ed6+DMKCro0RhfOaCzyJt1KlR4K8fP3U2NHn0BGzpr/CRPQMUsvWDHdKE3hz09a99ZbMsgTeQi2RJTHcE3RUIgpSu0TFa199K7Rc/Pm/f/KatxH2vbXkzvX0lQUQrffUYL+Mt7HklSZIkSZIkXaEuqwDmrTI3N8f/8X/8HywvL9Pd3c1VV13Fv/k3/4bu7u5LXdpbLk1Trh/toJFkPHN6gTjLmK62KEYhH947RJKmDHcM0xjopiuXUQ9yTAdlavU5kiwjlwHFEvXFhL5KgUdPzvPenYP86OAMKVDMhZRzIemhZ2kcO0yUtchmp8hHIc04gTBi+YVnGO4f4MzsMhkBG+JFruqKODSbEtZqBCeW2DwwwupAH5tG+hjpLrNrMGJ8ap6wPMjGsQF+cniaVpiHpTnyuZBCvUnabPKjnz3Fxls3s3HLIPVfmZHUm0v53HVjfPeZCZLVGrRakOYZ3LOHT+6skHvoCKsdfcz3b2Bp81X89GANMrhp+HpuGdpI7uDThP2DNAbGqHUPUB0YIMwSkiThmtEunptYWlvG69fctKmH0tEq5y/mBblrbuRoIzxvxsqJuRrPTJa5ZbT4G5ckeytmXSW799FRLFF/8mGSxQWCUoni7n2E19xIPYzafj5dXlppxn1PT77qPp+99u3R80qSJEmSJEm6nFxWAcx/+A//4TfuEwTB616q7J//83/+Biu6MuSyFu/eVGH/aAcLDTg2V6PaaPHUyVlaScp0V4nbrrmOhSceoWOgm5na2nJYWQZhZxdxoUxGjTCANIVCFNKIE8r5iL5ynl6alGtLJHHMamOVcmcXpeVl4jQiDaA1foqhLRsYn11mcNMYyZGDvCddYnBrH08dmyJuJBSXZrl5MM8tzRkGu6+n2tnNrTfu4aGjs5QKOaYXqmSrNYIwZKynTG78EFkYkOXzTIQdDJ08TnLNrTTilEIIhSDhlkqLTRtinp9usriasKErYENhllzUQf2j/w2PHZ3mZB1mZ2OqrZSwXuO7zz1HetUI+2bmmXn+MM1ShfD9n+axMxk3belnW3eeoVzKx/aN8sMXp6k11+5VPgq4aUs/e5glt3sf0cgGlustiGOKUycobNzK8uAmDq5cOEB5dmKJa0dGKLyRaS1vUhxExFt3U9i0lbDZJAsjmqXKa+pPI0mSJEmSJEm6sMsqgHn22WfP25amKQsLC6RpSnd3N8Vi8RJU9vaXpgldIVDM8/SpuXPGTi/XeWFkH7vvKNNx+jC9pRxhlKPU38d0sZt6I6W/o8DMSoPt/R30VwpU8hF7hjuJWzE7h7tJg5DFSh89nT2EuZR8s0lnMaDaatLb3UGcwkB/D7muHgrVCRo//Ba7Oju5+vrbCPrGCMnIDj3Jwsw0xV1XkXbnuHFjiZGuEhNLdQohlIoR/V1lyrMTEOYIcgEUy9TTgJlDh3m8sI3nZ2p0lfJ8dEcPQz/5Bh0zU2xKCowEEY3lJc40GvRs2cqLN3+CZ2YTCmHK/GpKq9GkZ+oEueYqTx+ZYGfvEOWpSZq1Gq2ffpfSLZ/iT398hM9ct4HBSsRVQ2X+wY1jzNcTkjSjpxTRncvIN/uZXNrME9koJ2kSBgG7dt7JtaUGtajE0bkLLzPWaCUkl7ClUJZlNMI8lF7qfWT4IkmSJEmSJElvymUVwPz7f//vL7g9jmO+973v8c1vfpMvfelLF7mqK0sxgq5Sfm12xq94fqHFyeI2PveR69gb5PhRo4sX51ssL8dkxIx0ltg32s2+sW5u29bHjZt7ODOzyMKZSQ4/f5je0S0sHjrEQr7Anq3DlHdWyKpVuhsNijfcSHdjiIPTTR46PMvv3ryR5VqNqL5K5Zc/Z6nYzezSWhP4Un8/h04uU1uZ54ZggdziAqNbdrFtoIPW6VnCqQXSpLXWBwYIcwW6cwEzSzVqzYQ0g8XVFsunx0lOjFPMhyzOnxs4pa2Y+cUVpqoxo10lplaW2V1sES/MrgV+tRVW+7pJjx5icONGjk4nbGwt0Ewifnxwmju39XHgzBKf3jfMWOnloCImS+FM0MHfzZeoTi2QLC9ClvHYwjJHt27m9qu30Joev+Bz6e8sUAp5Q31dJEmSJEmSJEmXn/BSF/Ba5HI5Pvaxj3H99dfzn/7Tf7rU5bytlYKEm7f0XnCslaSElQ5G+yv89q072Dvaxd7hLvZv6GFrf4Xucp5GK+Fffe0Z/stDJ2ilAUmzycFTMxyvDNO9cw+jlRzl1RXi6UmWTpwgHNnA/NwCHx7MuGFzH1v7KswXuhnYv5/ucp5aqZvx+epaX5QwpOOO97GQRUwcPcHxrMI3jy7zt9/8OZvKAUkQsprAKjkorM2E2jLWT3DyMNHua5h4aek0gEJcp5lmJFlAX6VIZzFPSEBGwGq1Sk8uYHa5znIjJgwCwtUqWZIQAKVykai2DGSsTowzlk/IxU1yYcjMSoNiPmJqucGJxSZB8Epz8jCKePL0IstpSDaygdy23eS27yHYtI3ZJMdMrUVfR+G8+x4At2/tJyIlH4bkw4AwfFt8NSVJkiRJkiRJ67isZsD8Jlu3buWBBx641GW8raVpyt6BIvXtAzx+cp5mvDblor+jwAf3DNFTyDi+2OJ7L0yye7CDIAzpLuUo5yMePTHPV548TW8lz1DU4ujR09y0dwvHTs/w4tQK1998C4Otq8iefoRcRyfl6+9kanae7PGHWX7scXa+6yMc7uzjqXqBD91wJ8WtO5l78ShRGSpjo4zccScrK1WuPvAzYgKinv3cee02Hnr6KO8azrNv435+8dAzzM8uUK50ct1wiT2FBrMnl5kd2MJoVqCjmKeYi6iUe1ksdbBYXaHeWlsmbKCjyNz8ErXjR9n18QL5RpV8VqY7SEiSV6aeXLd1iOCRr/PyimCF1WW6KiU2tObJdXQyVAoJgOcnl7l6oJ84Xgt+6knAsdm1mTxZBkl07tfr6PQyn9g3xv0vTDK1XAegu5TnXTsG2JlvwOGjtA48Q5Yl5LfvIdy2i3q5kyy7hGuTSZIkSZIkSZLekLdVAPPUU0/ZA6YNojTmltEiVw1tZKmRkAsD+koBuSxhuh7x989MMLXc5PkzS+SjkA/sHeE//OQIOwY6+OjWDm6snyZ54klWFpdpHhrh9+96FwuNmOlvfoXBG/fRPPQ84cAwZ8ZnWZqZJV8qU+jtI/zlg2y/5VP86NAM23eM0DO/wokbP0RjdZWesV5O/uCbrM7OUg3ylAo5CuPjbN29nT94/4f5ys9f4NT0Ih9/1z46wjFysxOMrc6RDW/nyIZ9VAud/PLILOOLdTb0lHkqn3LHLR+k+/mHWTp8jP6OAou1Bl2lPFHnCOPj03z+xs388sgkLSJW6w1KXd3s7C+zvzFBbW6GQhgSpAml0TEeX2jQnJ5iWzGl79kHuWPTPk4mv3ZjA3h5QkwQBgQEpFnKy0lOAPTmU37r2kEWm5BmGd2FkO5WjeYPv0nrzOmzh0qWl2jGAfNbr2ExDegt5Rkoh+TSC/eQkd4OwjCk/hqW2cuHAVH2618wSZIkSZIk6e3lsgpg7r333gtur1arPP/88xw9epTPfvazF7mqK1OaplSClErp5Q1rS2g9M7FMK0npLeeZrzXpqxQ5vVgny2BLR8DN408y++zT5LIUsoyFkydp/niRrfuuJtk+SnLgGdLpSbKlRYZ37WclCGnV63SGGSePn2Tw5jorqy3+7lTA7+y9joXpKqfOLLO7eZDV+XmaYZ5SLsdQV4mVJGQxKrO8ErPzphvYMD/Hd3/xLEmaMTbYzeDANu7afR3V8WX+7qkJGnHCjq4c8eRJjs/OsTQ0wGd2X8+uqRMcWqrTUcxR2riJ1d038diBM/zW/oB9uyrMd4+wdDRhy+h2+l58jPoPv08+CiEM6Ny1j+DdH+GJB0/T21nitqEcsz95hIEUhu64myR55UfiUpCyc7ibnx+dY361SZxmdBdzdJdy5EjZN9YFaUyYZfS99M0LSMlOHT0nfMkVCkxefSd///wk9aNPko1sJM1guKvEx68epiNoAhBGOZIMckF2Th3S5SpOMr72zORv3O+e/SNEwW/cTZIkSZIkSbqsXVYBzN/8zd9ccHtHRwcjIyP80R/9ER/84AcvclXvHAkBk8trze1LUcbmvgr1OKUQrfUjuas3pZQM0vmRz1AIYCRsUjn8FN0zp0gff5Di/ptpzU4RFEuk9RrlmVPsGB5gejUhaTQZG+hivphnrDNmenaBrxzOc/PmHrYXCyw88AiLjZRSHnrLZU6vQv/dH+S7xxaYuP9Jpno30t9Z5K5bb+DMoaOMzy4wt7jCvv27STKotxJGSgHB+HEW5lfIgIWpGR4o5vi9D3yC24OUpVyFcl8vYa3J53MppfEjFE8eJN9qsudd72XmW9/ldM8Q/R/8LCVS0iBkYrFKVB7gIzcV6F44Q+3BH5GlKRx9gW3vuZM4e+UrFBMw2FlkqR6zuLo2U6XaiJmuhtyxrY+d/SWy7NwZLFEQ0DrwzNnXuWaD6oadfP2RQ9RqdYLCIvl8gaCnn6nlOj84NMOnrh7izErMk6cXWKq3GOgocP2GboZLkKUGMZIkSZIkSZJ0ObisApgvf/nLl7qEd7QogK5Sjum1/vN05qGcy7FtoMI1o50EpRJfOVKlkC6ye2M/tU0b6Lj1U2xpzdP/g78h6uom3H8TjWefgDQlaTaJikV6wpQkV2TD7l30bxmld/wIA6O97Bgq05PWGe7JsZIkZFlGX2eZM8t1hj/wUf7uuUlWa3XI5YkCODS5TBIn3LVlI61qlVYcs9pMWKg12DnYSbA4S9JoEgRry30FScLpk+Os9vWRPv4Tpga30Dk7wWg5oLVhO/n+Aca/9Usgo+ua6wlvuIPqz37C/AvPU+zspGN0hOTa2/nOo4f41O5eVh77OYUgoK+nQndHjnzSJM698hWaXoUHXjzDh/YOMbXS5OD0CmEQcPVIJ1v7K5TClF9fVSkA0pdCkyhJiMdPcuaqd1OrHV/bIc1IGw2YmiAY28Sp+VUOLbS4/9nxs8eYXWlwaGqZD189wu6eiDR9DWs8SZIkSZIkSZLeUpdVAKP2C4KAJIioJwFRkFGJ1l+uKoljrt/QzZHpFcqFiL2dAQM06QxXGL15E1//yTPkQ7jnA7fw+Ml5fvbkYbIootLfz9X7Ps4HejvpCiNKN99J49gh5oa3Mb7UgDBHEBYINl7HifElfveOPeTrK2SnjvKfHzzBppE+Prp7Oz1pnXKpwGq+zMlmjkZtlZAAurpYrrcgTYlTePL0IjcMdnHk+CSVYp6uQkIplxHUl6mHkAuDl64xY7CrQjB5mpWDB+jZcQ25udO0Tp6kNXmG8s13EHV2EjYbLHYM8F9fXOa6Wz9Mb5QSlMscSIscef4oaZoxUe3i5h0bKAwMEQWQxTHR4jzF/hzNfJEwDDkwtUIryXj29DxdpTzXjXaSATMrq0zMr7C7fzMdwbn3PgHyO/YSz0xBvQZRxHLzlX3Cri7SuElWr5NrNVmNSpycXz3v2aUZPHBoho03baDEWxTAhDlqSUBARkcuI3XZM0mSJEmSJEla12UVwMzMzDAzM8NVV111dtuxY8f4xje+QavV4q677uK22267hBW+vWRhxInllIePzzBbbVDMRewb6+L60U6KnN/MPQgCNnRGfHzvAKUTB+HhR0iWFikODLKw+04Gejv52P4hfvDYAU6cPHP2ffHMNAc3bSAtwyc6yzTf9WGa7/0MEz97kKzcIty6i2zrbr4/lfHi1CyrYYGbujPyLz7Fe665jh89c5y5G7bSqD5JAIQdA5xZbpDGLXKlEnFXH/Xp6ksXlTK1sExxVw+VEYhqy/R3dpFOrRBFEVGw1sA7TSAIQ67b0A0//S5hoUg+H1FprBCtrhB191B/9GcM7b+O1tQZxpOAheUaP3lxlTTLKBaL9O3cQUoAZDSSjMrW7dR+8Pcks9PkNm6hduwQUXcf5Q9+kmbvAK3kleBjud5aC41+RZqxNuXlV7elKeG23eReeJpsboasUaevGK09j1yOsKefeGHupRsd0yQ9vzdGENBMYWEl5shCzHAlYqAYEKTxG/jUnC8IAqaaOX52bJ7xhRqFKGDHQAe3bumhO4zJsqwt55EkSZIkSZKkK8llFcD8+Z//OY1Ggy996UsALCws8Cd/8ifEcUy5XOYXv/gF/8P/8D9w++23X+JKL39hGPLiQsz9z0/y8s/jtWbMo8fnObPU4BN7B8i91I8kCAKWk4jTS01qrRY3rp5m7pEfM7FUY7WVMtgXMDE1z2g+pFUPOHHqzDnnStOUeH6Wo8Uix6+5nmNzNQrFAgMfG6OzudaP5bHliFwh4717R6i3Up5bjnjf2AaiiecZveM6jizFXPPZ36Hr5AGYX6KrGJHv6SPrHWCmkdHbVWZPT4EdPXlOlzOKff18sK9M88EfUr35I7xv9zALwxXqS0uEWcbpkxNEacz+eJr67CTd+28kmJ+iHKQk5QphLkecpkRjm3ni6BSV+XnKlRK11bUeOGGlQlIokd+0jXhynGs3dFP7u6+SLs6TG91IWukCIFmaZ/WH36Lwyc+zbaDCgcnlCz6Pgc4ilRxcaHJKvVSh/NHPkT76M9Kf/5Dh6jQDW7ewFBRIlpfWdgqAXI69w13MVeuvvDkImK8nTCzVyTIYX1zlRy8ssGu4k/fv6COfnR+0vR5BEHCqnuP//bMjLNRaEAR0l/KsNDNOzdf4/PVjVII3dw5d/jqzFp/YXPqN+0iSJEmSJEl6xWUVwBw+fJiPf/zjZ18/8MADNJtN/t2/+3cMDw/zv/wv/wtf//rXDWBeg3oW8eDRaS40N+HUfI2p1V42lNZ+YD9RhW8/N04rTbl1uMTEgz/l8JlFuoo5OrsqdPb3MdTfRW9SZ25+iSBfIEsSyDIIQsJcRAYsV+s8N13j4SPTRAvTdCUNPrSzl5Pf+RY9vb3ccPsH+P+9mNFTKvD5GzdyKLua4nPPM/PMl9m1ewe90yFdfX2EN32cPXGBBxaO0pivctemDvZHVaIjzxM0Vnnvts0Md1zLiz96gDiXo6tc5OdHZlhtJiwvrZI1m+zfMMZ7O6oU//7bdN92Bx37b6T2d1+mtTRPfudVNDq6aVZ6WKmn1Fop6QvPctstd3P/Uycp5CJKg0OkaUpaLDNw1VWMdmfEu6+G6Fqa83NkjVdCkGRhlmhhlm1DW9i/qY+FWpPJpVWa8VraEgZw5/Z+cllMEIbUs4jlZkoUBnTnIcoSaqUOKne8n1K+QDFL+eTOEb7zwjRTydosllxXDzs2DHDrtn7+70eOnz33agLji2u1lPMRuWBtesyhqRWGOorcPFp8Uz1hlrIC9/3yFHPVl35czzIWak1W6jHBYIWDs6vcOFyw78wVLohbHL/31Xt09f/BFy9SNZIkSZIkSdLbw2UVwKysrNDT03P29WOPPca+ffsYHR0F4LbbbuO//tf/eqnKe1tZbqbnLYH1q07Or7J5U4VaI+UHjx8lazbJrdbYOjzMkUPHCaIco/uvpbtZJXnhSa65a4S5fIlc/FLfjzAkCALIMsr5iDRd6wmSi0KKC9M0ZqdZCiN+Ml7kA7/1u9TOTBCcOcTvbN/P9ycT+lorJHGTTZ+6h665ebIjB6iM9pOVK/Q3l2lkBT581TDT80vcMPUM9QPPkjYbdOQyykunWHjsx2y884Msbr+Wv35hmtMLNXYNdjDYUyZazTjzwgEe37WFT3/6d4h/8h3q3/wb8tt3EVQ6qE5Ocni6ys7bb6U1soOuE+MsT0zQfexZPnH7zTy1kqNZLBMFGXtGOvnwYADPPkrryIsEuRyl3ftIC0XqRw4CGUEQUF9t8uMj85xabFBrpWwf6CbIUlbqTW7f1s/GjoAMOLgQ8+DR6bPPZrirxPt2DTBSyljNFyjvvYbaD79F55GD3LNlJwtbNtIsd9K9eTNd5RxZFnPDpj4ePzlPEATM1155xu/ZOcj4/MrZ10+NL7JveIziG+wJE0Q5jkzVODZXO28sTlMWVlscnqly42gZDGAkSZIkSZIk6RyXVQDT3d3N9PQ0ANVqlYMHD/KFL3zh7Hiapv6l/Wv08kyI9RSikNLiHC+emKW+sEh8+gRZq0myb5iEgB03XEPwxM9YnJ5c64my/NeMff4fs3Rmlp6eThbmFsnSlFIhR75VJ8kCtmzbyFBnkX2b+5kKW4xs2cCx5ZS/PrbK8rF5Rvq6+PBAF3/MKRa/9nV6siYHVmP2vu/ddGwcoXboOVonj9G39yq2XXsjfRMvkNt7PZNPHCDJxZRLOfLL80StAtW5BXjyYcIb3suJp8fpKOaJgow0CwiAoLefwweOML6zg75Tx2mOn4KTxwiGRine/QmSE9M80b+XnsFRmh/+PD21RfJRxODoKNvKRTqjjICM4fo81b//G9L5WeKJUwC0Th4jv20Xpb3XUj96kGoMM9WMF+ZfXi4s4MDkElePdvGZ/SPkkyZkGSeqnLMkHMDUcp2/e3qC37lhA91RzGrfMKVP/wOC+RloNuju6CLu6acZQPbSbJjbNnYw2FnkydMLTNUStvZXuHlzL0u1BgurrwQy9WZCkmXn9Z15repJwEItJhcFXKBlEEv1mFwUEvxKD5gwDAnD0O+qJEmSJEmSpHe8yyqA2b9/P9/61reoVCo8++yzZFnGbbfddnb81KlTDAwMXMIK3z66CjDaXeLMUv28sQDY0Vtg9Xv3UdtyG8nsFPkgY2znFqqVXrZ87JN0HH+GpfHT5PNrH5F4dprc1/+K7R/6OJ/v7ecbzySsVmtEcZNWoUyxp5vrN3Tz9cePcnJyjk/efBVnFms8dOQ0G/o6gIDppVW+9+iL3DFapl5rsKW/SHHnXqr3f53VxTl6tm4jmZ+h9vDPyE4eoeejn6P+4P30nX6RqFIhqa6QdvcRlDvoHS2Sxg2y5TlG8xnlruLakmisNa9PV2vEi4ssxp1ELShu20PWWIUkIQxDZt71af7u0AIfyK3QaLbYPjTGYjPhkWNLDBRh/2gXg51FVh/5OSwuEuQLhJUO0loVgNaxQxR274N8kcVyN0eyTqC5doOzjBwZB88scv1oJ8PFjDTM8dDxmQsuCdeIU16cqXHbWIk0TannCjC0Yd1nG2Yxu3sCdvYNs39jk4OTyxyZWqSVnHv07nKeQsQF+86se+wwpLBaJVicIyh2Ul2JuXqkm4ePz52/bxCwf0M3aZoQBgGlpXniowdJ56bJ9Q+R276bencfaXahq5YkSZIkSZKkK9tlFcB84QtfYGJigv/yX/4LuVyOL37xiwwPDwPQarV48MEHueuuuy5xlW8PUZbw3l0D/N3TZ6i3knPGbtvWz9DqHPW5GYb3V9gw0E1p7GqeOLXAEw8f5+5dY+yvPUxpeISgukyxu4c0jAiKZdKTR9nRUeEPtvUy0exjPt9BubeXQmcH9/3gUbK+YVICfnh4lhs29dFVzlPKBcRkdPV20Zqb4SfVMp++9lpWp07QsbpAc26ScgilVo1gYBByORrNhML0GXJbdpAbP0FYKBINj5Hli9ROHKXZaEGWUWzU6Jo8Trmyk3qxA4BcvkhWXSYloxCkLC+vsLy8QpjLkSsWmTt4jPHyNZTyOY7NVbljaz/ffX6SVr1Bd3OZidkZXsxSrt23nfe1EupHD1PJh5RGxkiA5OUQ5vAL5K67naW+Xbw407zgczg2V2N0Y5laEjC30lj3eZ2cX+X2jZXXvJRXlmUESZPRjjwPLK6eF74A3Lq1j3yWXDD0uZAwCCiePELt5z8gq68SdfcyOHoj3f2jHOssMLVy7jXevq2PzV05AhKKp4+x8sNvwUuzdDh5FJ55nI73f5zGxm3OhlHbJUFEK331T3c+DMi9wSX4JEmSJEmSpDfrsgpgent7+Z//5/+ZWq1GoVAgl3ulvCzL+NKXvsTg4OAlrPDtI8syhgopv3PDBg7O1Dg+V6OzlGP/aDfD5YDwxEnIMkbzMcHYZv7ul2uN3cvFApXOLZza/z6ae++ktxAQTp1m8ZePky4n7Dl6hM5cQP9td9ET1DkzspnvvTjN4fGDNFfrFCp1Oju7qTVTHj4xz/5tQ0ydXlvGLIoi4iRlcWGFwp4NpLVFysefJdeoEoUhca3GSu8YU8urpHFC5fFn2X3Pb5MdPUg8eZogTUnnT1JIY/Jpi2hgmLC6SF8pZOb4MZZHtzPdSNnQVaS31MFwbyfdS1M0hoZpzs8ThAHZ4Bhn6ikbejvoGigy1l1iarnO6mqDrrlxlldWKEYBweoKB4+cZttIDzv6+1menCI4fZLC2EbC4TGyOCYa3UDj1vfx41+cYL3fgV/+6TcKoJiPiBvxBffrKERrS6cFAUkQUU8CwgAqUUqaJOe/Icqx1IQ0y/jcDZv42aFpxhdXASjmQm7Z2s+O3hxZeoH3rqO0OMfKj78NL50vWVrg2m0N/v7QYd63axfLYR+Hp6tEUcBNm/q4eWMHubRBoVln9affeyV8eVkSs/rT71H67BeoF0qvuQ7ptWilGfc9Pfmq+9yzf4RceJEKkiRJkiRJkn7NZRXAvKxSqZy3rVAosG3btotfzNtYlmV0hS1uGS1y24YyAHEcQwZhZxcAK62U01PzdHeUabVi3nvDDr76/DTdy8vUZ6Yp5SPKpSKfuPvjVL/3depJQGF4mPSpJwiyhB8udHFyaonOcoF6pQKdXaSNjFw+Ym6lwfa9g0w98yxRFBF199Ko1ugvZbRaCYOlHFGrTlIs0SCkEeQ5MLVMK0npKBfJFUocoJPhzXvpWpwnaNbJ4ubaMmBBSPn6W6h+46/46Pt/h28eXYGsyUJUoJ4G5PoHubWnwZEf/ZQw6mR4xxCtOOVkUqDvI5/mgbkWh2cX+NCeYR4/tUBnMUepmKdQHiAfN8kqJYJSmeeaITs6Osl3VonrVYLJcXLbdpEUihT3XkdGRm+lyFz1wrNbtvdXSNOEShRwzVg3Dx87fykvgGs3dBMnGSer8NCxGWZW6uSjkN3DXdy6uZvyS01YgiBgPs7xwIsznJ5fJQM6izlu3T7I+3YP0WjFdBcjOqOE9HWEL1EUER96/mz48rLSMw/xqatu4kRjjqPlIW7f0sOOwQ76i5BP1645WJglra9e8LhpfZVgYRaGN77mWiRJkiRJkiTpSnBZBTBPP/00R48e5TOf+czZbT/4wQ/4m7/5G+I45q677uIP/uAPCEP/pPn1uFBD9LhngNzwGLPLdaJWg03ZKtuu28NDp6ucXKizq6uHJJgjy2BmfpnvHIFPXncjyy88Se/e61m8/+v0RCkD2yNODI0yVY9ZiSFMC3R3hhQLBcq5gLTVomPzFtLOHubjgHrvKLv6SxT7M6KZI+R2XsXcqdMUijlq+Qr15QYQsFJr0HPDTh5ZyNi86Sbu3rwZHv4x6eIChU3byO/eR/XRn1OfPEPv3/5/+Afv+yTz+4cZz3UxXW2xo9hD/Rv/N/UUAvI8O1Nna1+F7jvv5qsnWjy3uMq2vgrlXECjlUBrlUqWkhw/Dmm8NpsjikhuvJFwdDP5+VmSVdYCilaLaHAENm0jymLes3OAbzwzQfJr02B2D3cyVAoggyRJ2D/awcRSnZNztbP7BMCt2/oZ64g4vhTz989MnF0yrBGnPDO+yJmlOp+7dphC1qKa5vjaUxNUm6/MNllpxPzwhTN8dN8Iu7pDwiAhiltkYUQcBGSvoQdLGIYks1MX+PAkFJ57hN3lCjfe8/s0imWSJDn3mPGFZ/W85nFJkiRJkiRJugJdVgHM3/zN35yzxNiJEyf4sz/7M7Zs2cLo6Cjf+ta36O3t5XOf+9ylK/JtKAgCsjAiA6JsLYxphhHl932U8PQ8rWKFRlSmGAWcnl+h2Uw4kcsxunEb+cYiwcws00t14puuJ9myl0diuOamdxE8/mN27t3BV7/3Aq0sJChXSGfnqCYthgd7uXvPGLMrdaqVPg5OrtBKUkY78uzoL/O3jz7DB3fu4WoWiIZGyZXLnKolL9ULpc4OZjftZXIlZq6asfP6a7iqv5esXqU1M031O18jn8tRLBUgbpL73lfYc9PN/ODwMr84Okeus5N7bvsIAyeeIz5+mN5KSscNN/Js/xam5he5ZrSbSi6jWm+yvb+DxZMzVGdmKORCXppsAknChtoU3Vfvo5o0ab7wDGEhR/nG28n238JqoQRZxqaOgN+6YSNPnFpgcqlBMRdy3cYedvYXCdMWuSAgX1uhnCbcs6uL080+js+tks8FbO0r05fPSDN46PA0YbMOQJYvkAZrQePMSoPx5RbbuwKOzzfOCV9+1Qtnlrk2adF65nFas1OEpRKla24k2biVZhC96mckTVOigSFaZ05f+DMU5Yizl2ZQ/fpYdy+E4YX714QhQVfvq55bkiRJkiRJkq5El1UAc/r0aW6//fazrx944AHK5TL/+l//a4rFIv/xP/5HHnjgAQOY16EZ5Dm93OLY3DK1RsxAZ4FrRjrpjmJWSx0M7uyleeY4x2eq7Cl1Ug8WIB/RyuDAUsquoVGSYi9pmnEg7OX58XGu2z7E6dFhtu+7nhMrKR+8cRffe/Y0rZeWBssIGSrluHUgRzLQRXwmpaMQsrGvQn85z/GpBYobt/CTqQWGrt9D6fc2Es9Mkj30KB0dGaXtu1jetJu/PZmwsScmmJ+E0y2yjpRktUb91HHyYUhWWyGLYwKgsPcaqmGB49NzxNUVsizly0c62DSwn2vu2s9ApcCLHd2cnK+xvb9EkKaQweTSKu/ZMci3nl+iEacUo/zZGRuVSomrohrVB5+mcd276BgaJeroIL35Luq/MtslS1OG8ikf3dVLMw2IgowoSyCLKVeXaD76M6qnjkGaEvUOsO2WO9m0cRtZGJKrLhPWGsymEbPPP0/aWmt0HxSKRMNjJOUOAI7O1tg70Mfx+dkLPudyPuK6xhkWvvEj8tlagpQsQWvqW5Suvo78Le+mRbDu5yRJEoo7r4bnn4YLLF1WuuZGmoXiBUOWZlcvxd37aBx45ryx4p5raHb3wG+ehCNJkiRJkiRJV5TLKoCp1+uUy+Wzr5988kluuOEGisUiALt27eInP/nJmzrH3/7t3/JXf/VXfOITn+Af/aN/9KaOdbnLckVOLcbMrqaEUY7OSo4UuP/ANB/YM0Rv1KIzH3DdlgGOzteJopAsywiylCyBHYMVzizVqTYT0jQjH4Vs3zzEgellqtWIpc4cP3n+FAOtFT63bxtLMTTjlMGOHMsTZ3jsoV/yyZu3U4i62NJdoDY3z6H5OQhCws4uoqFRDmcdPPL4IW64dicnbhwiyxKOzNaZOrxKUMxgqUaxUaV7rkncKpPfu5+OUoXVx35BkCYQRRSvupZox9XUZqbZ3NfFyckF0nqdXKHImdkVJs402NJX4c5tAZ1hQPVXQoQ0g6C6xGeuHeXh4wWWpmdJczm2bx7k9t6A8v1fJth3PYXZCVpzk+Q/8jlW1wkTsiQmD5Ct5Q3lRo3at7+61rPmJcnCLNXvf4OuD32KeGmJ1aceobJlB63VBBaXCUrltdlKzQbx6ePkt+wgLpQo5kLSNKWreOGv7N6ugOZPHiDIJfx6zlJ//mk6d++j1TPwqp+Xem8/He/7CLWf/5CssTYThzCkdNV+sl1Xn7eM3cviLKN4812Uu7ppPPdL0lqVsNJBcd/1sGc/DcMXSZIkSZIkSe9Al1UAMzg4yOHDh/nABz7AmTNnOHnyJJ/61KfOjq+srJDP59/w8Q8dOsT999/P1q1b21HuZS2MIp6fj/mLXxznxPxaz5HNfWXu3DHAQHeZp8aXeN+2TtIsJUxT/sHNm8mnCdePdXJ8pkpvOUclgsUoJMnD3qFOtg128sSpFoutgNPH5vjwdVuIuwcYP7HA1MPPEGYpIRmHs4ByLuDqrUOkXb0cOzBPNnGCeGWFfBRSKeZIs4CVQic7wjyLXYM8N1llbKCbnz5/kl1bRtnV3UmzViOdmeT9e0coH/gZyY49hL0DxC88Q8eHP0WQZYRZRuPIAZKFeaaefoqbrn8fjxZyJIQESbwWfoQhrWaODa0lBtOU2WaOuLAW6hHAqTpsfPIhPjLUT+H6EcLaCl0nDhAcGyfcvIXC6AbCvfvIBu5mtdL5mnuqpCeOktaqBMHLPYuytYALaD7wXcL+QQpRROupR+gOc2wevoHj47MEnd1kYQhZRrowSzCykV1DHbRaLfYMd/DUqYXzJpQMpzVKjSr5Qp7zy8tIxk8S9A6+au1pBvXNO6l8dhTm5yCNCbr7aHb1Ev+Ga25EOcJrbqa0ax9B3CLL5WkWy+uGNtKrCcOQ+m/46GSvMqNLkiRJkiRJuhxcVgHMu9/9bu69917m5uY4deoUHR0d3HrrrWfHjxw5wtjY2Bs6dr1e50//9E/5J//kn/DVr361XSUDaz1WVtIc07UWrTijv5Knrwhheumaj082Iv7PHx9gvtY6u+3k/Cpfe2qC37tpE8MdRWpJSCWI2dBTpD4zQ+8zP+cP3/dx/uapFsdmqtTjjI5ijus39XLXjgGemljiewemiVartGo1njkxTT0rEA5vIjt9lGKWEgL5pEFSq7NrZBcLExP0L8z9/9n7zyjLzvu+9/w+O52cT+Vc1Tkn5AyCRCQBUlAgadnX8Y6s6zWzZuQoyb5OY0vWi1le1nitsX2VLFoUwQiSiCRy7pxTVVd15XRy2PmZF9VooIEGCVIi0CCfz1pYjXP2OXs/dfY+9WL/6v//04xGqDcauEGIyHYyW/dw3VWMjV1sW9fHs8dn6BuI89BtO3nh/Aonp6uMZS0+vXOMwZnDBO02pQuT5PfdiD62CW/8FMHiHFo8iblpO140weKBE3T3DHLrphFevlAibLfWZpMAewfzDFROEVpRzss0M1iECOxA8Oxkg9/YsRf7jR+wcOYscUPgxQzihV6afkhix6208l3kTNDkhzunmqbhT1+gFQhKLRcvCElaBpmYQVz6uMcPEr/7QYhEsC9eIGxUue2R3ayUI7R8HywLgLDd4rr+LMWIAAkdEbh5rMir4ytXhDAxU6cjaSHlB921lmuzgH5MkCKlpB2JQ3f83U9+qJ85DENsMwJm5O0nPtT7FOW9/EDy7eOLP/I1D2/r/ohWoyiKoiiKoiiKoiiKoig/nWsqgPnCF76A7/scOnSIYrHIP/yH/5BEYm0GRqPR4MSJEzzwwAM/1b7/+3//7+zevZsdO3b82ADG8zw8753gQghxuTWaEOLKfzWN8WrAD87M4vprN5wFsK4zxZ2jOSw8PmpCN3hjvELDeWeWhxBgGTpeIDk6V+WmkQIzdZ+RjMFIzqQ6X+XsidPEFpb57L2fpbyxl7OLdXTLYr6yFpw8c3qJcssjH40iWi3OL9a5Y9cYPzi9yOjQKNbSNFq9Qgj0bdlEDo/okf1sz2/ijYsl4ukUYShZtiWuG9CXT1BZWGZBT/DlWzcwsdzihQuL9GUj3DicR7MbTJVaGAO76bR9Sk0Xw4wjFuYx0zn0Yg9Ou039wiR1L8TUdFaXVsht3sCv7OpjoVQDzWComGSXt4g+fgIdwWc27GBxw3qOlV3may6butMsmgX6dlxP7uibREKfsu0z55vkbvsUTy9Iqhdm2N6f5aaBFMaPCGGEEJi+h952WQ5NJlcal+biSFquz2pLsDFtYmYLaKaJDEISd92PffhNUt/7Ux799C8zGe/iQlsjZgq29efoG0gRhv7aSZQhu7oiDGb7mSy1afsBA9kYw5aPfzRJUK9ddV16zwCulJev27fX+u5/TSkxaiVkvYYwTWSuiBOJfaiKH0VRFEVRFEVRFEVRFEVRFOVK11QAo+s6X/ziF/niF7/4vm3JZJL/9t/+20+131deeYULFy7wH/7Df/hQr//mN7/JY489dvnxyMgIv/d7v0dHR8fl57q71/76erLU5KXJaQwrimG9s4/ZRsCpis+9m7qvuOn9Uai2PRaby0RNHf/SvfOIrlF3fcJQMllqc8Ow5NWpKouFBA9s7SZqSRrZOJV6lfDsSQ5r3ay6EEbjlBo20/kUuhBIwA4F0VgMF8FbF0vcvbmLuuPjxSz0epktPRk2UGPu6e+TSGnscI8TGd7GYTfGQjuk3fTZOZRnXdrgxNkZJlO9ZOMRnjy9yJauFEP5BN85NgfN+tpcFV3nc9dfT1Be4ZlXJ/hM3yYSF07SLJWRYUBttUHguhQ6CrB1B1+/UKHLrxFrVOgf7men3yJ96k2IX6rqmDlH33XXs354kK8fmeXkQp1PJds49Qb5TVtJ6xCPpWh0DfNSO47rhsTiFudLLmNdBnsHO676uUspcc+fpv3acywObqOS7oJmHS0aQ0RiIKDLkrQmx8mPjdF6+QeEywto2Tzm8DqEYZB44ivs3rabG0Y3In2faLaTaNf7j9cDbB288jn7jntpPf/E+ypPrPVbiI+uJxuNcTXd3d0ElRKtF5/Gmxpf+1kAEYuTu/1eIhu2fNhLT1EURVEURVEURVEURVEURbnkmgpg3q1cLlOtVunu7iYajf7U+1lZWeGP//iP+Z3f+R0sy/rxbwA+//nPXzF75u0AZXl5mSAI6O7uZmFhASEER2bbNJqtq+5n/7jDxoxBVHy0VTCBZhDVBaYGhoB01CBqGuQTJkEoSUUN0hGDZrPF0WaLkZxFdyKNpcFwPo4sZKieWsT3fHQrQrFngBBBJmaw2tJwg5BoLIEuYKrcZnJlmn95/xYSzZDqwZM0n3uBWa9NOqJRCwSp5Vn6x88y9ujfZjmW49Ryi/nZJfafq6IVitQdH9cPabk+G7tSPHZoFkMXpAyD0PNoWxYvTpS4eyjLYLFGY2QLut3m5P4jdCQsejsLxIQkcdPtnI2kuX1MsLXQh7U4SWZlErl/irZpEekdQDMMhK5j2w71eoMLS3XuSjRpP/EN6o6DnYhw1vGp2z7pfIbND/4KL1beqSR67fwCvVEfgvdXwcTqZVrf/RrCMLiQdZmrB2zdtY/KgTfQACsaxagsIxMpGNuCf/B1YK1iyRk/Q+zWe/DmZwjDkPrFC0Q376CZ66A8P/+hzrtW6CZyx/24xw7gl5aJDK8n2j9IGIbUzp4izOZxrejlihYhBN3d3SwvLSFefx771LErd9hq0fre10joX6QdT/10F+Nfk5+29aCiKIqiKIqiKIqiKIqiKMrH5ZoLYN566y3+/M//nPlLN51/93d/l23btlGr1fh3/+7f8eijj3L99dd/6P1NTExQrVb5p//0n15+LgxDTp06xZNPPslXvvIVNE274j2maWKa5lX39/bNayklmqax2nI/8Ni2F+CGkoj20bZw0kOfvX0pzi83yCcF5abHfM0mkBJL1/j8zj4Ea1USUghem6owEo3RmSuyLHW0dBebdw8QhCG+brL/YgWhwULNYTAXo9r2EEDLDzF0jeFiktlqi8ziIrX9b2BoGhFLoztl4ZWXkMkkCUsnmL9Ie/UU7ewIgecRCA09lcNqhiQiBhs6U8zV2gB4gURGo+hCozsiyLdWmTp6kV8d0NFac+j79tB3/XWYvkvr4gVqTYfzR05iJabo3HUrxXwHxqGz+EsLiHiSeP8g7VefIyitYPT0Iy+cI7XjOj4zshH7+VdpOg6wNkvF9gJilo5ot0jMnCOV3UjdXgvR2q6PF0iM97TlMgyD9plTrDYcgohO05Wcm6sge/rZ/NAQ2twkhZiBpW+k6YbUzpwgmkpjZztZdUFYMTodn/BX/29YhkaybwAvk8MV2oeewRJISSvfiXn3g2TqFZzXnqPy1DdBSvRsHr3YReK2T+P0DuKG7+zTaNRonT951X1K1yWcvQjrt6pWZIqiKIqiKIqiKIqiKIqiKD+BayqA2b9/P3/wB3/Ahg0buPXWW/na1752eVs6nSafz/P888//RAHM9u3b+YM/+IMrnvuv//W/0tvby8MPP/y+8OUnEYYh3akIE8uNq25PRAwiP/3uf2pSSsZyFtcN5fneyUWW6mtD4AG2D6U5uVBjtBCnOx3lfMlmqe6QjiTo+swvcfrkFAdfPI3f0cOio2FaBndv7mFqtcXewSxvTJbY0JFE1wRuIPEcm1uHs7x4dolNqTjriwWsegladZxIBL+0SnNlhc6+bsTm7QTTq8QiBUQ0y85deexQcPHcEk3HJxM1WKo7+KEkYeng+xSMEGtxltBt0jZ1tN1b0S6eZ3y1yYk6NG2XLRtGSMcahDJKO54i6TQQmiD6qc/iH30LXUDze48hEBh9g4SJFNJxaL31MttujrC/uoIuBH3ZGGEo0QQ4XgASvMnzdN6wibq99tl2pCKYGsh3imIQQrDSDqmcGccJdKzhzWQGB6iUNE56gsmpEqkwzS3bNtD6i/+BHnisz0XwhjYytdLA91wQgqDc4szoMA007s10kND8Dx2+vFukUcd+6RlaL/8ABGhBgLeyQDA/g78wR/zu+zF6+rGLl6pKXAfpfXCVVlApoWkaQRB84GsURVEURVEURVEURVEURVGUK11TAczXv/51tmzZwr/6V/+Ker1+RQADsGHDBp555pmfaJ+xWIzBwSuHZUQiEVKp1Pue/0mFYchoIcb+qbW2XO+1pz9HVAveO5LjI2ERsLM3jRvCVGmtRVpPOsr4SoNnTi/SkYzwD28d5fWLU+zozZCPWzw9U+eNFY1C9yCpWAQ7KpgqtfnGkTk+t72Xi6UWv3HrKK9eWKXSctnUlaYrkuDC2fPoeoapJtx8z320vvUVvDBAC3xEGKDH0/C5v8Gzk3WONaP4fg3XjHL6fInuTIxPbeyiZnvcvq7Iy+Or+GFIGAp03yZuuFihy4YNw8QHh3ihUmfVXE8xpiFrC8xOzzM/u0R+xy7GRndw8PwCu+NRYucu0JNPkNx9I/LYAfT+YaSmE7xnHo9/bD+bNo9Sl20mlms4XsBAIUW95eB7Ie0QWnItRdME7O7LIN/TfqwZGrw8ucqejm5qG/fy3ZMLDPozWIbB6cUqxUSCLsPg/FKTvlSGYthCq6+yEBh4ztsVVCHawAiLjqQrYzFR9dFlQNzS6EyYxIX/vgoUIQSapiGlJLx0kRlCEE6exT70xtqag5CwUSeyZSfWxm00OwaoZQtY9SbRWBXohkgEYVlI9+rVXHqugP9xXMSKoiiKoiiKoiiKoiiKoiifYNdUAHPx4kX+1t/6Wx+4PZPJUKvVPsIV/XhZI+TBbT08e2bpcpsqQxNs78uypSNCGL5/VshHQQjB2eUm3zoySzZmYuoaL59f5u3b6MsNB00T3Lu1m2zUpJCIMHViga19WQZycXRN4PmS7lSDuZpNJmayqz/D6YUahiboy8TY05vimWMzBE0HEXOYXy7ztJ/kxjseYli3yS1NIHbuwUlkOdfSeOvIWbT+YVZdiKZiWIbGbKXNlu4UI/k4U6sNPr+zj9GOBFooEb5D6fRpRreO8daqj39mAcNzmVyugtDYO9LBxk0W56YWmJ2aIZnP8GDRo/zcE0y1mqzGo2zbs5VIbZVQN7haLUnQbJDb2UvpzdfRXZs4UC+VGcokWaw76GObObbYYqwQ5dbRAh0RyXt3tNzymSm32LnrJr7/3dfw/IAz56fZtX093akOTs6WqafzLLdtbr/7blpf/xOcZJx600ZLJEHT6diyidToMHdGYjwxXuGF86v0pi2Qkrilc/+WbrqjIVJKhBBE7RZydopgcRaRSGIMrcfJFjDbDcJGnbDZAAHStYnfeg/Njn7eaJkce20CN5wgU8hxyw0ZdvQ5ePEUkfVbsE8cfv91ZEUQvYOq/ZiiKIqiKIqiKIqiKIqiKMpP6JoKYCKRCLZtf+D2xcVFksnkX/k4/+f/+X/+lffxtjAM6Y0Jfm1XNyU7xA8lqYhG1pAfW/gCa23IoqaO64cs1R00IUhGTWwvuLRGAyklb0yWmCu3eHhHH9v7skyVWvyvA9OAIBczuW4oRzxicGS2Srnl4AVr+w38kLQJoz1ZFnQJ5TIymyRo1JmoNRjK+KwcPEDQbJLbtZsTxTQSgW6aaGaUM0t1ElGLlhvw+LE5bhstsLE7w2OHZ2jYPtWmTd4MuWvTOhzXoxVU6AjrTLUFSIkQcODCEo9cN4o3vYLbbLElrBC+9DStUgVhWlTbHiuLq/TqLlqrSRBPvO9zEtEoZqGIl0ijl+pIIAigVa0ysmkz7ZER7hRJ9vZnSAoXKd9fCdL2AuKWwdGqRMsXEcuLSAn7j5ylkIxw9+YxYuk0WzI69cnTZG6/B//sCWjXEJEo6++4FX/iLEuHDvK87GRxqUoul0NP9hEIjZYb8MTJBX51dy8xPGL1Mq2nvkXYar6ziKMHid90B6J3CBkGaLEYtJpo3X24hR6eXgyYmF4ATUdLJFhZXOHb330RJ5ZiY08Sbcd1ROw2zsQ5uPQzaskU8dvvxU6k+FjKuBRFURRFURRFURRFURRFUT7BrqkAZuvWrbzwwgs8+OCD79tWqVT4wQ9+wN69ez+Glf1oUkpMPLoibz8Tfuz3q6WUDOfjWIbA9SWhlDhegKlrxC3Buo4kbS+kI26ytbubzT1pHj8+z0LdYbSQpOn6rDRdnju7zK1jRXb0pfjh6TZ228Vuhvwft42QbFeZaLTYsqkLf8FHT2fJ+G2s57+F/cqbICUxywDHIXRdIrEoxJMsLrVIRC0MXRCGAa6nMVJM8cdvTDKU0Mm1qnRELHxN53DJY29fmt7WOcJQInkngBO6wYmlFoV8msFEnB57FXPrFlhYYWl2Ac/1aK6uou3bhXf+NCKeRBNcUc0R2bQDt1oluPV+cnNTyMlzSCHQ1m1mwshw8MWjJMbWc31/6gOrQPJxk5hlcLHisGJlyQ2m0OwmfhDSiEY5URdMnJnk4S0dnL3gctO6MbbdOUyXFkFLplj9wXdZWVolcvtnmD48jwREo4pc1hFdvUgJLTdgqemzLiFxXnv+yvAFQIa03nqZ/OcGaJVXsYbXYb/5EtHdN3DRTDExPXHpM9NA1wk8j1DCc4cmaGkbKcSiDN52L8nte5GNGhgWMlegbUaQP8nFrBtUHXBDSdzUSBkhoZodoyiKoiiKoiiKoiiKoijKL6BrKoD5tV/7NX7nd36Hf/7P/zk33ngjAIcPH+b48eOXZ788+uijH+cSP1G644K/f/Mo3zsxj+NLNCGwPZ9MzGTvQJZa22GoEMcJ4OhclRfHV/GCkCCUJCMGPekoU6Umr06s8qmNm6hXm1hakltSDpE3vg+nD7MrlUUb3UhqyzaaF0+RtavYpUUMy8CIWISpHKEVobeQYkakWHRC2l6AoQk0TccyDHYPZDm/0sBr23gypDU7Q1TXyAiXoNDNId9jJGkx70BG6DRbGiBBN3C8gPs3dDHSXMA4dRBZKTGazjJ2980sTc+yNHmRs2cn6d17K+WJCdA08lEDQYg1sh6xaTvBxBmkb/JsxaBr9Ea8IGB5sYbrLoEQrOvKENdDwg/IEQpRjVzMAE3n+HxI0xfoehpbhqQ1A2+pjKGB3bYpVRt870CD1Q293LpnmMrMHCtLKwC4UiBZa2Fn6YKgVsHIFwkMC4CG42PQpLkwd9V1xIbHaDz+VcyR9YSeR2TTDrREkrmaA0KApqElUniOgx9ItFiESrVB3Q54+ewid27oZGuhQJjKvbPTn6D1WD00ef7cKjOlFhKwDI3tvRn29iYxpPeh96MoiqIoiqIoiqIoiqIoivLz4JoKYPr6+vi3//bf8kd/9Ed89atfBeDxxx8HYMuWLfzdv/t36ezs/DiX+Ini+CEt1+P6oTyrTZemGzCcj7O5O8X5pToRy+D8cp2psk1fNkZEXxvo7geSprPWPq0rFSUdNbiw2iSXSdDfXmbxW98gEbp0ZXMsrVYpHThC9OQZorfdw2K8wLYvbSM2O011ZprVuUVi6U42rh9m//kmft0jCEI8X+J6AcVUlOuG8zx1fB6/2SCwYhBKTAvCUEO3W6zWW2wfHUUePUUml6VkSwqpKJZl8PDOfroOPMvEseNgt4gZGkVZJfL0Ywzc90uslqpU5xcJownMe38NZ3mRRMKgo68LN53HFoJ4zwD9x4/Sm08ytVTG999pHZfr7GD3SJEwuPqAegA99Lh1NMf5sscbk6u0vRCJpCMVxfZ8bAxuH05zcWoSASDgXCPg1mSKfproqSg128cUIamogSFYe52U4PtwKYDJxUxwXN43hAYQkSi0Wvjz0wSRKNG+QYhGMQbHiKz66OkWGAZBu43vBwjDxDdMZCRKKEMk8OrECkPZPuLiJy/fcoXJ4ycWqbTe+ZxcP+TAxTJCwI19cVUJoyiKoiiKoiiKoiiKoijKL5RrJoDxfZ/Z2VmSySS/+7u/S6PRYGFhASklXV1dpNPpj3uJnyy6wQ/PrjK52sSVGl6wdtP+8HSFpbrD1u4kR2erdKZjPHd+lXXFBEEYIkNJKmqAlGhAZ9Jiruaw2nDJRnTkyUOUSxX0VIypmofdchGmwPYtNkQC6qsrzJ2cJKJrmP2D9N95P682IsyteuwbLZJfabHcsKm1PfpzMe7e0MVcpU02orFo6MRFiLR0HNvFtHRYWaS/qwckaLEEY0nBZweyOOdPoVfbbJyvUI5ECEJJemCQjoE+RK1MxBpBr5XYefftPPcnX0Hr6ONPz9i4QYoeJ8ZvbOknTRsAO5Uh3dvL3XNzLO7o5/B8HT+UbOzJsmHTMKbwfmwhSFR67Cwa/KM71vHW5CobTYe4XaVqh5gbu0lFDAKrgOYmSHR0UM10MlXz2RxPUoibFOMGojrFtqFhzlxcvrxfoesA5BMWHXEdqSfRojFCu33l6c7k8CfPIWIJgnqV5pkTmF09iHaTwb5+ODqJ1DUwDDQriq/pOGh0dhZp2GvVKY4fUrZ94rGf/HJbaPhXhC/vdnS2yrauBHHxk+9XURRFURRFURRFURRFURTlk+qaCWA0TeOf/bN/xq//+q/zwAMPkEwmWbdu3ce9rE+ssgNTK2tzQixCLEMQSIjHddquRypqUm27ZBMRwiAg8H1SEYNS4OJ6Pp4fYApoOya5uMlspUWuI463MIcGxKMW06t10pEomgzp370df/8rLKy2KLc9LNNATC6SOnaKoQce5XtzLgGCsUKcdbeOMbnSYLrc4gdnFjE1uHssx+pqFLeygpXKkIkY6EgEHVyXkfSlJVrcZ135POXvvUiip4diJk756SP41SrbfunLtE8do/Hdr0EY0jZ0EsIn9fCXWH/vvbzg54gSUBQucn6Z2rhPZ1IgOzpxNBNnaIxcRxdd9Sob4hItlyNIZbA18YGzX94r8H3WxwXrxEXKb7yBa7skdJOOTRuxjx9muu6RjFrMNV3o7CG8+dMcJUGiGdIbE1jz09y6tQcx1MFCpQWRGF4sxo7eHOs7k7hhiJdIEd15Ha03XnzP0SUilkATbbDba3NeFmbxFmbJ7tC49aadvHRsksBYa2Wm6xbJ/iG2D3dxfHr5XXv50TRNw/QdhO8TWFE8BJqmsdywP/A9rh/S9CRx60N9jIqiKIqiKIqiKIqiKIqiKD8XrqkAplgsXtH+SfnptbzwfTfTnQBWmjaOH7Kx5rBvuEgQhsR1qKxWeGR9jm8dmsYJJUQi2IEkF9HZ1p/nKwemuHkwA1JimgZ+GEIYEqKTyOVI65LzcyuUAgPTMAgllFsOK02XdUcP0Ne1l784OMN9mzvZ059D12BipYlu6BRiEUbzCcy+BKdlm3BpnlariWGajA52szHmUUiZDHQblJ8/QudwF4FuUGraJKUkbNXhxH5ks42UEqFp+KFERizsYwfgtkcYn/VJVJdwWi00TeAuG5RefoPU0CDmHQ+w4JnMtWLEkjkKBciaIeKDhr58ACEE+uwFmm+9SBywLA2nb4jaU98haNQZHB7jfMulZruI6Yv0H3+V8e13svG2e5l98UkGExpGo8LW/s2Ynb1Es1ky8QiHp0scvLiKrglGigluWbebgmVhH3qDsFEHw8DM5rGGRqn8xf+AIAQh0BJJ9K5e3KP72XPbZ+j9/F0cnimzUHfJZ5JkklGmyy1cf63lWMTQyEd14OrfwajvIsdP4546SujYGLkCsZ3X43X3k4h88K8STYClq/IXRVEURVEURVEURVEURVF+sVwzAQzA/fffz5NPPsndd99NMpn8uJfziRYzNQSXKhoEVJyQ2co7batCKXlpfJV7N3Vye5fFxIkznF2O88imUVYdSd0JGOrN0xfX+dqJRTZ0ZbhQbnPD5u0Yb76AEYYgNDBMjI4u2jPTNAOBE0JMF1TbHpcmmTB76gy3bL+JZ87CD88s05GMMJyxuGs4zd6xLqaWqxycLvFw1mebLxmP5ZFWD11xA33yLGe/8SwDn76Xjqgg6rbQAhffjCBdHRlNEEmlsY8dJHbbp2mcOHo5hCGWoCVMVo4cZsv6mzgxXUUYJmM9ecT0OKGUOGacN84scbQqkUA8HqfdarFzIMcN/Qn08MMHgoYMcY7uv/zYNHRieshiowaAqJUIjQIAcVOneeE8A1uv54dOht33/DLkLV6aaXJ+sokZCRiOJvifb10kGTXpTUUgDDm/1GCx5vDoru1k+0bQXBvNMPDPn8JZWcYcHMO7cA6kXAtngmnMDVswO7ooJDTu3dbD6ZLLGxdWuVBqEo/HuXSJcPNokaQeEl5lBIwlA/xXn8OdOn/5OW9xDu+Zb5O4414G+jdj6uJyq7t368vFyZjATz5aRlEURVEURVEURVEURVEU5RPrmgpgwjDENE3+0T/6R9xwww10dnZiWe/vW/TQQw99DKv7ZMlZ0JONMVdp40uNhVrznW2JCKWmy1yljVxd5tPpNt/OxJhfqVB74yipVILOfIoNpQrNVpJNfZ34IcwulVmJ5+nIF7C89tqN/yDE8UN8XcfTTXw/IJRX3muXQiBZq4QIAUMTRCyTtBGS9ttsyEXJ+y3SgY333LfYVujkYrlFvVFHM0xsdCb2HyKybQORWIrg1CHCQhfpQi/LdYf+fJ5wqnRF/yzTMrGKHSwHOmG7RdRtgdDo7Mxz20gOd/8JrGiUiUQvR46dRxscRV4KjBCCw9NlejMRRpIfvgWZ5rl49drlx8Iw0JtV0lETxw+QrkM8qoEw0QXIMMTwbZqu4GBdx8wmOD1xjrBRp3e4h9dOTBE0HOpBglrEIGutra9ue0yWbLbkI0jTItas0j78FoQh0Y3bsEbW4547ifR9zMFRojffRT25Vr3key6jGYPIuiIHZ6r4GBSiCfYOZOiNC8IPqPoxSis03hW+vHNyJe39r1DoHeLTm7t45tTiFSFMLmFx17oChN6H+gwVRVEURVEURVEURVEURVF+XlxTAcyf/dmfXf7/55577gNfpwKYH0+EPp/eUOSJU8tMVmyCcO2meCFhcc+mTp44schNowVG9BLhKy/wq2MbaG5eTzuQxHyHzPIk7ssnGP7Cl1g04jx1aoGYbvCGk+Seuz5Hh19n9+IMCwsrxLbuxBI+7XOPo2trIYGuCfxAApLE6DoWZWRtmwRT17gwX0HXDAzpU/7uN+nUApqdecpWCrvuYPshMprEC0Jcx8VbWkZ03E7N9klrGrrvEgtdROBT1lJ0jmyAMMBKJtHiCRKFAsI0IIwyODpA2FngkbEhPMflh+dm6BrcTWFdF0dOLa5VyyBwpSCoVKHVRCfg2Lhgw65u3Et5ghBr806klIRXKRORhokWTxLaa5VGoeeipfrQkcRNDaIRDEOgX3qv0HU8IwrArp4ER46eJbxULZNIp5ibWgQJYatBOWKQicQQl8Kg8ZUG2zvyay37mk24FJzYE2cRVgRjdCOaJvBqVbRKCQrdl9ephT4DcRjcXCCRydKslZG+/4EVKpqm4c/PfOC1FjbqiHqF0XwnX9zbz2zVoeH4dCQjdCcNLKnCF0VRFEVRFEVRFEVRFEVRfvFcUwHMf/kv/+XjXsLPlYTw+Py2ItNNOLlQJ2pohEHIxEqDG0byfPvYHFu62uiVFh0nj9NyDiFkSBi6ENWJmAatUKMjEeGXd/UyVWoxko8xvVzhvEhQXD/C4I1JxktNNsYDtmwdozIzR8P20AFDF1ipNP7GnZxcqKMLQSZmMJCJ8MbMIvW2w+LZEjfnisyePU3X6Ai6BsuVFqFuYvshliHQLAtN1yjHC2iFbgy3iucHGJqg3wqo+x76PQ8w99abmH0jpEwNzW2xPDtHoneA7O7r6dCSPP/mSS7OLhExdGqGjpbJsxLLobU83NIqJpLW4gK2FyCAWKuOLWZJbtqK9D3CmUnC5UW0TBZ9aAw7lVubtaJphGGIJwXR7XvwX3hq7QQEAdI00dJZwloFI1/E8HQ6IpKI9Ilt2MSZWBJTb9Oj+Rx7V/VMGARYho7tBRAEBH6AlG83dVtrYfY2YUWuOO/SdfDeFZiIaPzqVTyhTzpq0qqszYz5UZU+Qtc/cBuAEGufQVKEbMrpCGGshVQqfFEURVEURVEURVEURVEU5RfUNRXAdHR0fNxL+Lmjhz5dMZPnKg3a7lqVxPqeHI8fX6Bm+9iJLP2pGKcXKgggamhkrAjLLUlvR5pisZNy06UvZdAzkufpA+PYc7NovYN4QucrB04TjxjYjssvb76T0f4ZsudPsNpyCAY3UO1fTzmeZ2JygY6kxcPbe2m5Pk00mgsL1Nst5O5+nANv0dJMItEYMmwjRIipa5eqaCC3dRtv1gV3PfAo1UOvsnzoIGHVpXfdRvq278BbWWZoy0aaLz1L4DhUpcDq6cO68wGeqEbYP71CVzzLrTd2M3X0BGYuS4dsI+MRJtsJZKOJc3ECMxJBGhGcEFJxE+fiFPHyEq5j4y/MXv5cxcRZmrd/jjOOxXLDoTMZYawQo2NwlOiOfdjHD0EYYE9NkPjUg7injuKHIYNejdriAvrgKI4ZIfnct3jo5rvoj5j0ZOPU6i0AVhdX2Nxb4NDUKgBxU0O7PNQHNnWn1qpfAD+TxSh04q8uve/8a9EYFDqvem0EwuDsUp1ziw6GEPRno+Qsebma5m1hGKL3DgDvWsC7GLkifipz+bGU8kO3bVMURVEURVEURVEURVEURfl5dU0FMG9rNBocPXqU5eVlYC2Y2b59O6lU6mNe2SdTQgu4aaTAc2eWEAKCUFK1PZIRAy9bpDGylWDuFYQAJ5B4QqMV+Hjrd2Dk83xhXZbT82X+22tTWI0mSI0N+RRfPz5Hw/YxWhrD+ThfPTxPX3cHD3/610gZUA40nIbDdKXF+o4km7pSnF2uM7FQ4d4tPZyZm8KKJkkmIhT2bGPmzHm2fvpeKk8/w/xyFU0I0CA3Mkp183Xkkkn+6OAkXdUIG268j6iusV8auM0YdxVNzEYZ88FfIVKrELcinLOK/PDEPKvdORbKDZZlyORyg//Xrdtxjh/E/uGz9HV3Mda3nkp/gRenBaHjYOkGgWayoyPG0mtTxLwK0ZvuvBzAiESSiyP7ePLJ/dA/SmCYTCw3OHBR8MDWHob33ERybBOysgpCQ+Y7MHffSGxmCm9qnNh1EZqVKrXJcToERN56hthnHmRXR5TxOQ0/CFlaqbCzv4eZcpSVuk0xYcGlUGPXQJaumAZyrWeYK3Tit32a1rOPX25hBiAiUeJ33ocdS8B7WqZ5msVz42XmGgGt1lroI4Drh/Ps7o6jSf+K17vpPNGd+7CPvHXF88I0id54O23duLw+5doQCB3vUutBpGBmuYwbarw3RLs8+0hRFEVRFEVRFEVRFEVRlL9W11wA85d/+Zd8+9vfvvzX/W8zDIPPfe5z/Oqv/urHtLJPrjAM2ZQ3Se/s5dhcDTcIKcQtoqZOKxC8kFzPbfdmcY7tx603iHfk6Ni5j7Pxboymz6JbZarUZqnu0GWaJDIZVho2jrfWE8sPQzQhcA2Lkwt1NNNgR2eC107P8fAN60g3PVYbLl/ZPw1SkjAFz59d5P950zrKr79M+rXDaKuLbLntbrx0kZG/8XcwL8zQajQIUjkuiDRLbYlw2uhhwGqtzWsrFRCgJ9JIXWfdxiKFE0dxpyexK1W8L/wdvv3KYXTTQO8cRnMdpK7z8Pok849/naxTI+I6GCvzZBtVND3GzVt28fLxSTJRg89dtwGjWcO+7m5WpE1XRxZx4SzS82gNb+XZUwv4no/htMEwAfACybOnl/jV3T1EkxlIvlMVYskQ5/gB/JW1KpVWIFhpOLQ9H2gQnBsnH7p8dmc/L0+WWS7VOXHsDPfv3kw8lWTRkVimwYbOBJ0xgRZe+f1op3NEH/oVxPICQXkFLZlBdPVgx1NXzKsRQuAKizdnG7w8WSZmWcR0DUsLkRLemCzRm4nSE73yGvKFwNy+j0RXL97JI4R2C6OrF2P9VtrpHFJKNE2jHeqU7IBQQjaqk9QD5FXm5Sg/e14o+eaxxUuPBKlUknq9wXsDmIe3db/vvYqiKIqiKIqiKIqiKIqi/NVdUwHMY489xte//nV2797NfffdR29vLwBzc3M8+eSTfOMb30DXdR599NGPeaWfQGFAbxT61me52JRcWGkiNIGlC/YvtDlmptm36wEKekA5HmfZCWlVAjo7Q54/NsO6YhJd17CNOF0xyUrTRQYepm4SIgmBpuNjmTqOD5lEhO2DeZ4+s0zJ9qm0fWx/7Ua8pWs81KNT+t438FcWMTqypLbvQp47if36i+hDG+jdfSMnipv45ukyluHy6/sGeP7gOXp682jFBJXpGcoLi0hNw+js5kTd57MRnbZdJ93bxQEHDA2MdAbZrCFMk558ivj4YYJGnY5YSHthHn/OJp1Jki52MVzcw+B1Q6SiJocqbV49tQSBT1L6dK5PceeOOygcf5mSlcZ2qmufa3Blu66m61Oy1z7rd9McG79SAsAONaZKTcJ3VYysXJgketcDdBx4li+kM9QH1m6KZ5qTJAe24WXzhGFIEARwlTxDSoltRqB3CK1/5J02YO8JP8q+zuG5Kj88t8Jq08UwQsLApz8XJ2UCEo7M1ehfn1k71rt4QsPr6sfoHUSXEh+BG4ZrlS9CY6IW8sK5JZruWjhkGRrXDeXZ3hlBe09bM0VRFEVRFEVRFEVRFEVRlJ9311QA88wzz7B3717+yT/5J1c839nZya5du/iP//E/8swzz6gA5q9ABj49ySg7B7IcnqmiaYJiIoKmw8uzTTJRk5jZpC8TZbHmsNRwOLfcpCsVZbbaRhMaxaEchbQGsowIPEzDQAhBRyaOaZpUbY/Zqk06kyasV6i1PQqJCA1nLYTp7UhgnTlAudpg23A/2a4ijae/gyN0EBpeKBmfmKH7uhv4u/tuY6bcxG+3icajvHmxhIhE2bxhKzv27eHUxBxu28ZKx5HNBmGjhrAspOsgNB0tlSHUdaLxGOsSkuD4FCPREG9xjsBuE7FMRLMG7Sbiue/Se/OnebNp8sKZKXRNI2royESaxYUVvrMMv7JxL/67Mg0ReVfSItYqTIKrBSS6gWZFkEFAqeVeEb4AyFiCV8uwbe+97DAaJOs1RCJJmNtI27SQ3ocfZh9+QMVJqBn84NQK2USE5qV5QJqAdfkYY7GAXDLKlC1o2P6PbEvlX/4B3/kZVl2Np07OE7zr53L9kFfGV0hHuxlNCTUXRlEURVEURVEURVEURVGUXyjXVADTarXYtWvXB27fs2cPJ0+e/OgW9PNI0zi91OSV8VWmyi1Wmw692Sj7L5ZZ35EkDCXVtkvDDdnYlWKh2sILJEdnK9w4XOCl8RVOLTX47LYejGiEIJRkExECCXYIy9U2d27o5NDUKv0dGRZrDvlEhMW6TU96Lay4qaATHpsiFTHRe/tpHXgJTdeR6DiBJNqo0TPYi+Xb5KZP0BWGLNdjZPUEq6FJeaXF2aUmxVSET23s4sSFeTYMdhAT1yGlJGy3GFs/xNF2hJYeYbrcYtNwhjt7DFKmjb64hJGMk8xmkOUVgoaPI310AUHvMG+9dI6WGxKxNOJdXXhCw12cA1NjOojSG2dtPk08SXgpgPGkRs32absBVTfE0nU6YyAuVX740RiRDdtoHXmLlvv+ahCxYSsLtTZ1x2RwZz9W4V0txv6agouKC4s1m6hp0JWMUHc8frkzQB57mebcDMl4lJs3bCSxax+CD39MXdc5MV2/Inx5t7emygxt73jfXBlFURRFURRFURRFURRFUZSfZ9rHvYB327RpE+fOnfvA7efOnWPjxo0f4Yp+/lR8jcPTZUwdsjGDUEJPOsJnt/cQhBJfhvTnYuwdzNKVNCk1XbwgZGK1RRhKPrOpizCEgzNlvrRvkI1dKVJRA13TsD3Jnv4MXVHBSsvj9FKDPYM5Zqs2cctgvtZGExDKgLYTkLQ0HM3CbbUhngChEUpwDIvM2BjBi08hnv0mM8/9gMXvfoPRN7/L3xyNYAgAyWqtzXzdpZiKkzI16uPjWCPriazbTMfkMdZ1JFj1BKPdOe6Nlmk//S3iyQRyZRFn5iLOzBQiW0DGU4RBiDYwRiMUVDqGsIZGcXpHmLeytFN55OA6gnwn8+2AXHOFLdvWoXX3ESJwQsHEapOFms2GziRnFyp8/fAshxZspNABCIIAsWkHVt/AWnjzNiHI7ruJ42QJ5VrbLuOv6VupaxoR3yWCJO60ya9Mc3+qRa9mc+u6Ar9cdGk+8Q2qE+fxbRun3qB+9CDpV7+P2W5+6ONIBEt15wO3120PJ1CD3hVFURRFURRFURRFURRF+cVyTVXA/P2///f59//+3/PHf/zH3HfffXR2dgKwtLTEk08+yblz5/gX/+JffMyr/GTSNI1GoHN2xUYzTLb2JGg4AW9OrvLK+ArZmMmGrhTXDeYpJkwOTa8yvtzA1DQ6khHOLbscmq3wqcEU/49dGXrzSRw0NhT78SSsNj1KtRazqw2ePzHNcGeByYpDte2xuTtFNmZSTFjomiCbjrDpy1/GdxzywsZ7RYAfEuvtIxjagrd1HwsLc8T33kpYmsMp2ZiawF1ZJnfgB9y//V6eHq+gIak6Pp9bX+Tc7BI3bdlJcPxNfAS6ENx241aMriwF4RB8/+ukLB2xeQ/h0f2EtSoEIfbcDKK7j0h3H41MJ6tNl/NVn7oTEo3oyJZN3rdYbfoUYkl2DfVg9lrcasZIzjU4Ol9jaqFOQpPsHc6TieqcXVkLL964sMq64iAdQRvNc5GmgXn3gwxvnGfuzHmkYRJ0D3BKJrADjUJCY0dvBl0GP0H9yfsJIYhVVvFOHiLwPIwwxD57HDeSoLXaJp5IsPH+z+JMH+OcDHi7uVkiojOQjaJXV2FmEjG2+UO1DRNIsnGTpbp91e1xy8DS5HtnvyuKoiiKoiiKoiiKoiiKovxcu6YCmN/6rd9CSskTTzzBE088gaatlQK8PdPCNE3+8T/+x+9735/8yZ98pOu8VgkhCISOEwp0ATEtxAk1XCkotUKePb3AVMW5fKM8FbP41KYunjm1QMPxOb1Y5/axIl2xkIFsjPGlBgCWLnhgfY4bgyW0w89j1suYkRBjYB1GsRdGNjDjJnnp/BLNldW1Cg/PIx8zma+1eWR7L1OVNm9dLBExDPaHIecKMXpbDSadKsPZPnKax+yWW3lptk3j2CKNySni8Qi37bkL48wR/IsXoN3EmbnIvutsjiUtohETUxOcL9lYegw330fulk8hq2W8mUncY2/SNbyPXcmAWmuZVT/FxCuvMvbpz+FNnsebPA+mSeyG26mLCGcOHMbq3cLGrgjHFxrUbY+4ZbA2y17iS0BoXHAMejWHG/uibEhpHDRcPNtm4fwpFpo2RrGTMJNnU9bCPLEf9/xhZCyJny0S7+klPjDKDAUurrboicWptzxm6226UxFyiQihCBHypx9aHyst0XzqmwDEB0ZoPPOdtfOYyVNIdrDcaOCdP4U5O0FfNoYMQwxNo5Aw0C8d15s4g75hG77/49uGBUHA9t405xbrV81YdvdnMfirhUqKoiiKoiiKoiiKoiiKoiifNNdUAHPDDTcghGpV9NOQms7FesibF1coNx36cwk6MnFOL9ToTEV5/twKpqGhCY2mJ7F0Qa3tsX+qzN0bujgwUwEpWarb1NswUkiQjVmstH26khFuqJ/Fee05RLtJdz5GZeIiYn6B4q13sdAcYKhY5FObezg/KZkvNfFDSbXlsqUnww/PLVNpuTh+SLVtU2l7VFZK7OlO0hca9Gy9joVklicOXcB1XKxIEpA4vuT7h6d4aM9u9IUZZMNHaIKIb1M0DVbcgK6cwYDh0nHseRYXZ1iyLHqjYBkGhdvuoWZkoTpLkM6x2gTPD0ifOIHp2Vjrt0IoaZtRjr30JkO33c6fznoM9aRpeJITCzVycZOG4xO3dD67rYfZUp1So80jWwqYi7N48yscP7yAkBIuXbv+0gK9+TTr5s7RWLpIY8eNHF5qs7TUJlGrsTtY5OZ1gwwVkvz5/mkark86YrBUt/nGoWluHi2ysytyeX7MT8IEnAOvIj0Pq28I+9iBy9uCaomubAGSUUQYQr2GF8ujIckn9cvhC4AwfrJfDV1RuGN9By+Pr+CHa1GLJmBbb4b1eQup5r9cs5LS44GB6I98jU74Ea1GURRFURRFURRFURRFUX5+XFMBzG/+5m9+3Ev4RNI0jTMVn2dPLSKBuKWDpvOnb0yRT0YppmI0vZDZ5QY96RiaJqjaPpYhkDWbHcBSrc19W7o5u1ClbnucXqzzue09HL+4SrJVxnj5VVJRnUwqjT0zRaxYpCKiHH75DeLZYb5/vkk9kuEzG/oJKyVqRpylUo0to3m+emCGqu2TjhqkDB1dhoQ1lxMLVW68bRPLns9MW9IYimFUlhGWhZlI0JYGLSfgyFyV20fHqDXrSMdGNwxuT7SJxyy2rIvivfYDWqfeWhscH4tDcT1hs0rj6W/R9ejfZTHoouIKGraL6wec8kPGsgnk/DzSbpK47nayD3+RIzJBe8nm1FKDkUKSW0YLRE0d2w0wdcF8uU617WF7IW4oME4cImUmSJuCWqkKQiBMC0yLTXoTe/w07g138cyhGaJRCyFgbqnM7FKZe9IFTq7aJE1ImeZaqy+5dpP7tYkVhnL95H6Kb6dhN2kuzK1dF5EIbmn1yheUFunuG0J6dYyREZKOgwwDpLzyBru5YRvtD1H9clkYsLVoMpjrZ6nhEYSSjqRJxpSI8P370TUN3XNB1/GE9qFanSk/G8L3mHrsqz/yNR2//uWPaDWKoiiKoiiKoiiKoiiK8vPjmgpgflaefvppnn76aZaXlwHo7+/n0UcfZffu3R/zyv56tEON1yaWLrd46ssleGlilYRlMFdpY+kaM5UWAPM1m7FigqihUbN9mm6AqQk+u72Htu1St9cmgsQJ0A6/yk1z48iBdbS8MkZ1BU03SHYWWZIWpUoTGUrMWgmtHiORzvPkuRI3DOU4NlPh+pFuplZbLNfaeKHED0Iars9YIY7vmcQTCSYqNlMLZRZcjZVWSMLIMpxJYlcbtGsNTF2jUqlTGC1inZbk73+E5vRZus+cIB3YaG9GiPWP4O+9ibqwqHeP8upqC5k1GMuY9IcGb5Rsdq3fTPrUKVaaLr5mcKYWkI9n6dyyjwPxURzdJBvV6WpDqe1jaIKlWpvDF0v05xPsGchSba99NlFTJ0KIWF3CvHCWG294hKdXVpESpO8jPJeY3cAa28CxRsjmXVuYr7uEErakLRorqyzVbCZLbSIayPc055LAZLlNoStyuf3ehyYBsfav9D20ZIqgvTaTBiEQ+lpLNbmyROyG2wjOn6K5unzFLqyhMcLu3p/suIAMQ5IiJJni0iJ83ls4IYQgVi3hnTyMtzCLME0im3bA0Bi2Yf3Ex1QURVEURVEURVEURVEURblW/UIEMPl8ni996Uv09PQgpeSFF17g93//9/n93/99BgYGPu7l/ZXVXUnDeafKwDR0VpsuuUSEZOTKUyyRzFTaJCydvkwUXRNs7Ezywpl5bG+tBZUmYLtWZ+aFFxgrxkh09xHIAC2eQPo+dPagRXN09fm0V1YwTJPBTesJrQh+KMknIty2voO/ODjDDcMFdMPAtW2QGjIMmavabMrnOLtQYd9gjsAPSEctlhsO1Xqdi6ZJV+8gcXmRsFEjEzWxFqYY2bcbf/os2tmTRNo2GuDoBarPPkHm05/lWHqEl16bwDQ00lGDs7MGWTvBWDHJ7MhuxvJ5yq/up9lqo1sGYsN2zm26jpmGyy9tL1CuNbmAR0cCFsoVTk2vggw536iTj1sUEharTZcdfRksXRCGIUG5xOjJF3lgz+28MVlmtVQlYmgUsim85AAL0zZvHpy54hxs68/Sn4zTmG4QiWpXPaeu/047ME3TEELQCDSkhJgOIvSu+j4/nsTsHVybgbO0QGzbbpovPIWeTCEAoQlkrQyxBLLYRWrLDuTxw3iT58AwsDbtIOwewNHMn+JK/PHenk8jvXfW77/6Q8yLE0Tu+MzP7LiKoiiKoiiKoiiKoiiKoigftV+IAGbfvn1XPP7iF7/I008/zblz534uAhhdu3JujmAtRJESIobGatNlQ2eSs0uNte1C0HIDAumwtTtNw3Evhy+6EGzrzZA7cwQ7YeHH0lipDG2nhb+8SPymu5CxBPHTR5FhSH5olPiW9Tw5J3j+1By2F9KfjfGFXb2Y+lq4EDE0XNNCaIKoaRD6Hr6eZLSnwLIdcNEW3DNWYLLURrdM6p4kg060q4dUR5G964tkllyElLS/9xgimUZ3bILuIdreWolF9fw5sntGQIAfhDTdkFhMUHIl3fEMLS/GIT/JXV/eQbPeYL4tecaOkKpLbhjOUTj7Fsf9PPWLs/jtFiRSFFMpVmot8HyOz5Z5aEcv3ekoGwoRaDcxRtZB28Eu9tJbnuFXs5JmVwbNbdOdMnlTi/PmxJXhC8Dx2QrXbR0hGzNBXn3OS382juXaiJUF3NUSJSLMR/McqOvEoyY3jeTpiUnkeypkPCmJ770Jf2ke0jkaYzsQRozGwdeJtOsYzTKhqJK45VMIAXpHN97WPWhbdiOFwA7Dn1k7MBOJ89bLV4Qvl9c9M4m1tADdn/zvo6IoiqIoiqIoiqIoiqIoCvyCBDDvFoYhr732Go7jsGHDhqu+xvM8vHfdJBZCEIvFLv//u/+9FmQsQUcqwnLdAaDcdFjfkWSh4VJ3fNq+z9buNHHT4Ph8FVMXSAk3DOdZX0wSBBJDE3Rn4hRSUSxNUFou0W56FLb2M//NvyB3/e1EamW8cydxV5bxQo1QaOjRKKe+8XW23fgAT/khEgiRzFZsWm7A4Zkyn9ncxcvjK6w2XZIGeLpFKmLSn43y3YNTeEHIqbkqN40WeWvGpO0GRE0Dc7VEV9qkWJ2ndXESMbSelZ4NtD2fZNZEjyVoVWtki53M1NskAhckCA38MGTL9vVUY3leuVCiIxkhauq8UjEYXxZ0JSNs6kowPr3M//XDOfrvGKK8/yRaLAHtFqJZpyMWkilkiURMbuyKsi9cwPJs9FIBsnnGC2O8NZBj8dwElmmytS/PtqBMOmjjeB5n2h6maeB575qBIkDEErw6scLdm7p48fT8+85nTybGgOHhfP8xnGqVC6stvECiRSzuuOt+fmhn+fbROR7Z2Ut35P3XoZ0tYnzhb/HSmUVOHF+m18yy6aaHiLtNenJxkl4be+Yi9jPfId7RhZQCX8q1xI6f3bVttho0Ft//877NnzyP0T9CEFw9lFKUn5SmabRDycxyGTfUgPeHi6Ym0D8gCFUURVEURVEURVEURVGUv4pfmADm4sWL/PZv/zae5xGNRvmt3/ot+vv7r/rab37zmzz22GOXH4+MjPB7v/d7dHR0XH6uu7v7Z77mn8T9Isp3js3jBiE1D24Y7eCZ04tEDIOEZfLc2WU6khZf3DeIH0gEsFizcfyQs3Wbz2wboFJvEbYaZIM2XcMDtCuLhKuLhJUSpdOn6brpZtxjBzCiUeLxNO1oikYix/xylcTpA2wqXseZlRbWpcqXUsslZsZ4/UKJezd1UW17+K5LNhVjrDPJ7z91Gj1iEdUEZ5YbtELJPZu6cH1JVzpCZmsPBT0kKRwmOwfQz5+gXG0ikVTbLr6j052IQzSNXG0gdQNNA4TG7n3bOdQwOXFhkbYX0HIDxlea9Gai3DZa4HuHpuja1cfByWWkhJVApyumc2GhjJlIIh0bPIeusM4tVoD9wzcRnQmEriEjUc5vv5snx+v45RpazwBO4HOwBUtdG/lspoWVLUIYo6+vk+mlKtL3QNcRVgRhmHhSsKM3QyER5c2pEuWWR8TQ2NiZ4vqBFNGnH8N3bUq2T9BuI8IAfJfm809yw0Nf5rVahKOLbbbsGSBi6u+7Hp49Oc9pJ4KWKzI9Nc5MSaDrGuZKm1/ZnCfnngFdx5ufoXvndR/JNeotSsJ47AO3W9Eoyc7Oj2Qtyi8GP5B8+/giqVSSer3B1QKYz2/vQr928nRFURRFURRFURRFURTl58gvTADT29vLf/pP/4lWq8Xrr7/OH/7hH/Kv//W/vmoI8/nPf56HHnro8uO3KwKWl5cJgoDu7m4WFhZ+Zq2afhoZTeOhTTnOLDWZrrRptlr8g5sGKTVdLpTa/O0bBjk8W+HFc8vomqCYMNk7kKUjpqFpFt8+MEl9chyn0URKuPP6TewbraHNjhMGAYZhUHvtRXBdSOfwoinKniBwAkIJrakL7Bu7DjuMs1B3ODZX5cbhArOVNlFT4+RijaW6TUoEjGpQW/H539dZhK0GnmHxRiPK0ZUWU2Wbu9YXeO18jeNLDbZkTe4aSnNwpsJdiRy6ZRLYNppp4AMLrQA0jezQEMcSHUQGIsSiFs1EjhOT80gp6UhEcYO1Vl2zVZtSy+Vv3jzCc4cvIOVaGKUjGaDJW0GAj1ibdQPs7oxSeuIx+ns6CFyHlpQEfWM8f+QCvrAIAb+8CoDQDSbnAqZ7R1iXzZKtuyQsjaGeHCsNl7YXYGiCQsJkUzGOdBr0WSEPrU9jhwJdSBJaiLU4RX1yHKNZp7zcwG80L1X2CMJmg+zKNG7YzYWFNjPLCeLinQobQ4bYtSZvvnIGu97ASGcJHRsME98Hx4FzDckOCdJuE202WFxcJHxPK7OfBRMI0lm8hbmrbtd6Bpifv3qFTE9Pz89wZYqiKIqiKIqiKIqiKIqiKH/9PtYAZmVl5ad6X7FY/InfYxjG5aqV0dFRxsfH+f73v88/+Af/4H2vNU0T07z6MPC3Qxcp5TUVwARBQFoLuLEvxo39cQTg+y5dWcG2QopQaGzs6GVioAVhSKdfJzj8Au7Qep670IbAJ2y3WIuaJC8fHqdwyy6ui5u0U3kY2wTH34LSMo16g8ZKlUwuR5DPU7YDDMskjJvMXagTSsmZpQY3Due5fijHi+PLXFhts64jwfWDGbq9Os2XniCxMstizcb2Qm7vG+CG6+/ijWaErd1pLlyYZ6flknNbrHopzi41SHVF+NR9n6fy9HfAD7AMnZrjoyfTRG/5FK+ecVmse2zOZTm52MALJRJBPm5iGQaWriGRrDZcumMaC5UWAOt7spjlFazxkzxy/d08vypYbtZJJ2PEVmbJd+ZJRXWkXAspGok8ldoiaG2swVGCahlXt2hrFul0nPMiC67Flt4YZxZrxDTJQMYikGuzeXQk+wbSSN9HAjohibWPnSAA6boYTgt/egItUrz8R/sylEjXIVxdxir2ECIQvHNN6kKgnTpMwzNolitr7wl8ZLuFsCIQiQKw3HTRojH8dgs9XyT8Gc59eTcXiO+7Bf+pb71vDozZP0zQ0XVNfacURVEURVEURVEURVEURVH+Kj7WAOY3f/M3f6r3ffWrX/0rHzsMwyvmvFyrNE2jLXUqdoAEshGduBZ8YMXCe+dnSCnxL1Vz1G2Niwur7Fw8wfLBN4kXOzhpdBHaPkG1jAhDJIJcJkk2FaPmSo6M3MyB+f20T1Z4YHAb2sIKaeki5+fQTAs7vBREdfdzqmXQl41RarrcNpBltmpzdrnBYD7OQC4OEhbLTXbM72f/yROUw5BcOk4xFSdorZI+/RLxGx5g/NR5gtkpLEtguzbtXIZACJYbLk9NLnLLPY8QW50DxybV0Yu5YSPfng/59NYiRyc0cukYy6sOUdOgmDCZXa6CEOSzKWYqNu14wGh67dLvTMf4/PYeSt//S9ptn3VJi8+O9AEjxC0d880f4iUMAvnO5y0u/SfDkFAI3GIv2bhFt2lwaqFOe6bKctNlfWeCz+7s54WzS5SaDjqQjVrcMlagOwbyA4pORCKJbDUJGzVymS5qjXefUJCxOH67zYbBTuJ6SHjplFvNOs3Db2Ju3EvEMnFcj8C20XMF/NVlNNNCahr5mEG4YqNnCxg9/dCyf+Lr8qfVzneReOCX8U4exl+YRZgm1qYdMDSGrV099FQURVEURVEURVEURVEURfkk+lgDmN/4jd/4SI7zla98hV27dlEsFrFtm5dffpmTJ0/y27/92x/J8X9aQtMYr4W8eH6JprMWosQtnZtHi2zIGVy+8/6j9iEEodCxA4haGrujDqVDb2Gl0uTHxqj7UULRQpeSVNRk887NXKx7rNgBoWthN33i/YOsjk8xraUopvI45RU6BodYFjFs22ekJ8/qnht560QVy9BJWDoDuTivX1jFDyUXVpoEUhKGkv/7pggLx46TS0Qpt11KLY/ADgmCkHTbY2x3ie+fmVpbvAxp2zaFqEbYbCCzRcrlOt99s0E6lSAztBGn0uChVp1HBrL47Qo744uYiYCu/ABfO3CRmeUaoZQIISjV2wxkY1w/nKcQ1fjf7trKjoxGYeIIxp5NeMkszwVFBtqSocYc4uI5ROAQTl/AKHQSxBJIIFWapbujwEK5idANOlNRpsptjswuATBaTDC+XOetiwa/cesov7Kjk4orQULKElj4yB9x7sJkBmt0I965UyRaFXKpFOV6G4BYVxdzrkYqrbO3P00YvCtErJbA90nMnWfr4HYOnl9Ym2WTSmMUOwgdB0PXGEkI9GyeyM13o2dyBPYyNVeiAUkTdBn8zCpRpJS00jn0mz+F6bmg6zhCU5UvysdG0zTsD9GBz9A0/B/Tqs/UBLr88b+XFUVRFEVRFEVRFEVRlF8MH2sAc+edd34kx6lWq/zhH/4h5XKZeDzO0NAQv/3bv82OHTs+kuP/tJZswVMnFwjfdW+65Qb84PQiyZ299EZ/zA40jZkmvDG1QssJWN+VYSAaZeMXHsWcn8JdWaInX2BR10isW89oR4pvHpii5QV0FHMcPbdEVPp8ZlsfHdu389rCKjff/BAd5RlkaZpk28Hs7Kc8vIUZM8cX90LD9RkpJDiz2CAZNZittFlqOER0gYEk5oVU6i2GCwmklNRsDw1JKm4xVIjRmp3F1ARJS2AIgdA1mkvLrO9KoxHiGyZh4FOpt/CaLju6smRffxLZN0oLndaT30De8SDZjTkKMZ3ypeoRKSWOHxLR4fa+OKlWGctzaR44QnnmAqVam8KGddy8t4dnxud5cXGVkWwvdw8nEW++jD89idE3iJ9IIeYmuX3nCN81k9i6ScQ0ODJbBaAzFcHx1m7A1m2fZ84s8Q+u6yZvXApK5NXGgF/Jl5L41t0Eq0s4Rw/QnZRkOvK4XUO4O28ibNncsKsXTby3gmutgVxQXmVPd4N6f4HzM6sE9RoiEiW1bpi7N3fTG/Hwtm7B1nVOLtR45vgSy3UHgK50lFtHC3RHf7ZtyYIwJNAv/fpR4YvyMfIDybePL/7Y1z28rfvHvu7z27vQxV/XyhRFURRFURRFURRFUZRPuo81gPmofFSVNn+dNF3n8Gz1ivDlbRLYf7HM5zYVIPTf/wLW/qr7fDXkqZMLZBMWXdkET51e4gsdHt7cBH4kQSzVwVgCXj46w3A+zkszTQLDwjA1hBXBioAhdZ6frPLpDUVOL9U5W3EpFAf5zU/fRK1p88PpFvMXHbb0uPSno3SnEhydrTJRanFqoU4+YTGcjzO/UsWMWAS6ScwySFo6Q8UkvhTomsAyBDgOfjxGMqyCH4AM0QXMTE3zwAN3U260Oe4M06pUiRsaN27spm/yCLXTp+jYfRNGKImPjlJPJnjjxTd55LbrmOjLrX2OwE1DOXZbTap//v8jMzZE6/XnCXSDWjyHpmtMnzhDcOIs62//DCeWVllekMyupvmbj/4dxLf+lHBhFn10A6EQ9Is2X7h9L1MNj1cmymTjJrmYhR8ENJx3zsm5pQZ1T5DSdSqeoOGEWLogFxUYlypNDMMAKZGstZDzgwCZyiCjceKfehCAlG4Qeg7+W98jum0vXjzy/hZ62RzCNJGeh3lqP5/qH2Xv7hEqvsAydbrXD2JZGi0ZAWDFFjxxZp5607m8i8WazXeOzfHorj5yxtWvLUVRFEVRFEVRFEVRFEVRFOXH+1gDmMceewyAL3zhC2iadvnxj/Poo4/+LJd1TfBDwUrD/cDt5ZaHE0LkA7bbUufViWWEgN5ckscOzbB3IEdgajy+alBuNUl1dbCnu4O/98Uxzi1UWTiyRBCJ0W7Z9Bgavh9gS4iKgHjEYt+mfsZnVtnbm+IvT6zw5lQZU9fw/IDpUoOHd/ZjGjrJqMG+oRwrDZfFhkPC0tnQkSRp1xifbbK7mENMnSBlWXiZAhMrTSSSLWP9pIoZRgoNpqZmCUOI9PSxdaSbkQNPsrU0x+bCIHJDH6nhEZZefYm4XSW2cw/euZNU979G4fZ7EO0K2zdvpLxcoigkd/em6OsuYB54iYn9+xnrLyJWF2mtLBNIiHdKRGcPk0s1ksIncuowY70bmZ2aYXl6jsf1kIf33ITh2Fhbd1HrGOD5qsaJI3OMdKRJRgx60lEqLRdNCCKGhuOvtSpKRHRCBC9dbHJirop/KVErJCI8uKWDzuo83pnjhJUSerGTyPqt2NkCTq5IdN/N2K89j3P+FPg+WiJF7Prb0HbfcNX5RU48RWzvLbRefwGQiJkJcjMT5IRO/MbbcC2N8FK1idANDl6oElyl+sQLJEfna9w1nCIMVDsl5aOXlB4PDPzoEr+kvPZneCmKoiiKoiiKoiiKoii/2D7WAOZrX/saAI888giapl1+/OP8IgQwugbJqEG5dfUQJm4ZWDrwAffH625IzfbozcY4Mlsln4jQnTR5/MVDiHSGesZictnm2PIFtg3keXjvCOvn25RDnSAZwQ1DhK5z02COQjLKVMWm6kpu2zZIMhbh5FITPwgJJQgpeXB7H0dmKzx/zqPtBdw6ViSUkv5sjJbtkm+XcZYWOK0JPnP3p9H+11nsqQnMrjZ9xT7mHdBuvRfjwkk+PXWQ+qa9+NEE6a5OIo//GaK8BAMjxMePYR9/E1JJBm6/j2DmArG+AVrTkzhSY8EVTPdt5XjT4ux8hZ7OHDf0FxlsL1E/8Trbsxapng7axw8TIpBIwkYVJ10kUSiQTkSQ9So9/TDvOQgJk5NzlLYXSLzwLZyt1/FHR1Zo6RYAF5ZqjHRnObNQoxjTCdvttWoeS2fV19jSlWauanNkpvKucyvoTeiYk2exp84QLM0gXRdveQHOniBxx304A6MwvIFIsYvo4hwy8NEKHQTFbhpCv+o5D6XEX7+VRDaHd+IwQa2Cns5ibt2F19F7OXwBcEJYqLbh0s/xXnMVG0+mufqRFOVnS/geU4999Ue+Jv83f/0jWo2iKIqiKIqiKIqiKIqi/HQ+1gDmq1/96o98/ItMBj67+jJMl1pX3b67P4MWBh84T0QTa4MIYpbJYq3Gtt4sr15YJZZKsxiYVBttYG04/cnpErdt6MH3fOxAMlNziBoaD27p5tRSg2fPrjBWiDNXbjFXcygkItwwXOD0fA00wWA2wULN4fBMlXTMJGnpvHh+hc9s6uRiuY2R0AlXqvRt28LOvgxTtRVGP/sl0rMXCKplUtv3sRDpouQ2yYeCSDpF8P3/SXzHPuRz48hWC5Er0JydRg5vJB2PEdYqaOVl2oZF88//G5FYjNyv/D2+c77K+AsH0BMp8p0DtG2XV984Ru+OHtbv3I7uOohkkmhXJ2GjTqNSRS92IW/5DDNLbeZjMfZ0RulPWHTGdI7P1bg4s0g7FMTXb+doVdJaXUXr7mVzxmCD6eDGQl4LPS6uOISOg/Q9unIJRjMxbhnN89SJucvnpSdpsk+UyR99Hvv4IbRsmtT23fhBgDszBUFA+7XniHZ0Y1tR3HQePdeBEIIgWGtZpus6QgjCMCR8z1BwH/A7ejHu7scMPELdpH2VweGGgIih0/6AC8gy9B85y0Jcur5+lnNiFEVRFEVRFEVRFEVRFEVRPsl+IWbAfFL1JTVuGM7z1lTp8iwYAezozzKStZDhB7fgyVjQmY7iBwFxy8DUNeYbPqOZPJWZFd7emyYECJhYrLBrpMgLFxukoyExQ6DrgvGVJn2ZKKau0ZOLk4kanFqsUUhY7B0uMLFcZ1tvhhfOr1y+KQ/gByF/8dYUY51p/vcbB1lZ0Bk/O8Xjh48SNXSi0uP+bf0UjhwiPriew3qBT+c0WqeOEiEg+enPERsapbU0T+j7ePOzaIUOTKdJ68I4fquBb8WIbNhC9J6HcF56hgUH5poBUoJsNUm2K+jCxzTA8wO0bBHmLxJOnUdPpkjYdSIbNjC+9U6ePTbPxr4c61fPsfr6KaZaDgOFJLuzRbbevIfI+GHkdXfw3PGLBFaMW/IGhYM/pDG6hceeOczeXZvoj0U5XxHYrkFH3OJTGzvpp0nLXStTSkdNbnBmaLz8Q6Sw8Sol7EYVbXGG6O6bMDq78ZcWCNstRLUMHT3AWsgRhiF6GGKVlvDOnUS2GsS6+9CKXfiOg0hn8TI5PNbOgR+GIHS4SvgCoMuA7X0Z3pxpEAoNpEQX7wQqO/vSiKsEfELTqfqC+ZqLF4R0pSLkowL9A2YRKb84dF1TbcMURVEURVEURVEURVEU5V2uyQDGtm1OnjzJyspaUFAsFtmyZQvR6I++uffzRgsD9vbEGCv2s1h3CSV0pyyylkT8iPAF1m6w3zFW4KlTS+zsy+AGkpYX0NZi6LpOEAQg1yplAilBCEpNj89u7ebpk/MUklFOLzbIxExyUZNy26Xacik3IG4aHJguc/1gnnTMwtCg5QYYmiATNXA9H8KAiKlTarnsnyrROHOO+fllYhETzXdpuS7fOzbHL++6hbhpESwvMBea7Ni6E+/8SYKleZwwpF1aQTYbmPE4ejqLMzVB0GoAIOIJ2qePI5p1Uvc+wsVSEyOdRrcdAk3DzHdRdCvclHRofeOPaUQDzNUF9EIniTvvxVqYobV+J69MrNDbkWdD+QLlQ/shkSLQdGYrbXrdOfqjGrEtW5maWSYITOK5LNmJY4TNJmdKDr7r8dabx+ksprmtrwMjX6C6sMj+/ccZvWkdEUPD1HU+NxyHN+awU2lqjZBYdz9Gowy+g334DZIP/jL+0sLaCQwDPGGy0PSZr7bpiuuMzByncehVhJRo9Sq1F55CiyWIf+pBGi89S2RkjMj1t+Po5o+9tqSUDOXjHFtscXSmhQQyUZNc3GRbd5LhjIV8781yTefkqseL55cJwneimdGOJHeP5bDUzfVfbL6v2oYpiqIoiqIoiqIoiqIoyrtccwHME088wV/8xV9g2/YVz0ejUb74xS9y3333fUwr+5iEAVkdcrm1aRxS+nD1ooYrSCnpiko+u72bxYbHXM1jKB/HQ6AlUmiuDf7aDXPTipLNZTh4sUx3pMwmWWX7YIEfTDc5t9wkqguWGw6mJvBDSWfcYqXlYAhYLDdIjxVJRTTSMZNM1GSuZeN5ARHLpCMZIRoxKPshmZiJ5jkEfkAoodV2WYr3Ey10sVq1aRTz7NcHObtkYIQhe7uKrLsnSvu5J9CLHXi1KoQhQoAmNOJbdtCI5zAiFmEyRdSOEV6sUJcldMMiYehcZ3m0X/khPZbEbNWhUSOwW7SefZzU5/8GF2UaWbrI5nyU9otn0JNpbD/E1ARC00hlUjhH3oJ0lva582zadifRYpLGC8dJFQss1+21KhMhaDZanDt2Gi2bR5oWRujjS8F9QwnSi1Pw/Tdxpy9QGBqDoR1MvvIqA5kOrMYKODZho4YwTEBQy/fxzeNLrDQchBDcl3U59tSz9KSjFDQff2EWpCRs1nEOvYG1biPO+dPEMnm0bXvf15rsvVqYfOvoLN25NA9t62G63AIE6zoS7O5NYUj7fe9ZceD5s0vvq4qZWG5QTFjc1BfDqFWhWlrbkM3jxFMIITDtJgBeNEHwY9am/Pz6MFUyAPqH+SWnKIqiKIqiKIqiKIqiKNe4ayqAeeGFF/jjP/5jNmzYwP33309fXx8As7OzPPHEE/zRH/0R8Xic22+//WNe6Ufvw87a0DSNdqjhSYEpIWcE5HM6GwsRxooxHjs8x2rDQLNSyCBACME9GzuYmbhIstGkZ3CIgwur+J7H4PAo+8MQoWlYusBxAySSxVqLuzZ2kdDXbqjOVFrcsb6LmXKLWtulkIph6RoakmLKIh/RWMwXobyK5wWEUmLqGiECt3OAt1abXD9U4OBsFa1aQuT7CWsVnlkM0TbuYXhvBRZmEKVVhK6jaRqZX/nfqHePMPP971KfuYhuRcg98kWwAwqDA7Rdj+F8DO+Vg/RGwZ+fIdAkmqYh2228C+fwzp0gteMORCZPXNg02m2kGUUCgQQtCC997pKwXkVYMbZvGWWq1MJtNvHiUXJ5ixlNQ9c1NN/DC0JMz0dEoiTjMTLJKPHnnmDx/DiGkDhLC9jzs1iZLOvvuJeJF14glsthOfMIIZBSEr/lLr4312al4WB4DjGnQaw2jxXatJshTjKC/q7rwZuZJLHrelymcU4dIbJ+C44Z+eBrxLA4OtNivu5RduoY0icdMQDJ0YurGITc3B9fq5K6RNd1Tk43PnDmULXWgvJpWodeR14K9oRpktx1PYHv0z55BABrYJjI9n20U1k1P+YX0YeokgHo+PUvfwSLURRFURRFURRFURRFUZSfrWsqgPnud7/L5s2b+Zf/8l+iadrl54eGhrjxxhv5N//m3/D444//QgYwH4YvTE4stTk8XaHp+sQtgx39WdZ1JFmu2ERNnb99/SDHFuu8NVVGCI2tXQmmjp+itFLmM9v70UuL3LJnA8su7BjIcWq5xWrbp+mGIEMIJZ7nk4voNB2HL18/xM6+HKVGm+X5BeamVhGmiWboDOQT/NLGbl548QC+D5HNO/AqJWSzgRaNYRWKpNMJetrLvDHTpnluikizilbowCh04C/N8/hLC/zqXffQ76xgHD+AnskikxmWu9cz/b/+BK9eAyAUguDcSUZ7tjDeChCFLlJGSCJwcVeWsTSNaruNrhnEExZau4l77jRd+26HZg1yCTwjQqvtggApNEKg5XhY/eso7tiDG2Z4eqrB7u4kfSN9lOcX2NYZ58JcFC30CUKNMGKsVcDEkty4uRMOv07zlR8Q2h5GIk6xq0i9VEVrNzBmxsmOjtEsLRCJRNEKncRHN1Ie2Mz4gVkMu4W+PMftm7ooTKzSWJoGIZAdHWgDY7itJma9hHTdS7NeBFoyg9VuojXrEI3hxlNXVJy0sTg51+KZM0ss1GwMwyVmQG86inGp6uD8coO9vYkrfjkIIai0r95izNAEG50lGgdfwRTvHEtvN6n/5R+R+MzDSG9tjc7503gzU8QfeJRWIv3X/RVQFEVRFEVRFEVRFEVRFEW5ZlxTAczc3By//uu/fkX48jZN07jxxhv5sz/7s49hZdc+oem8frHG0dnq5efqXshfHl5gIBdDAEt1m65UhM/v6GZXb4aXJ1axW2225CPkCgVCTfCdYys47hyBlEyeOMsvf+4uXpooMVNpkYtZXDeUZ99gHmRIzMwwsVzjpfElDM/l+t4km/IRnEAQMQR5PSBZXmTvYIHnpuus1lssuRZWopOoadBXXsE4fJ42gnMXPZASoWloukawOIfvrlWU/PBinUfWdxGkumicPkHk9nupzUzj1WpIJMWNGymOjhK0mvSkXLaPDnGwYZBJCLKpGHLWx7VtZCjxw4BaEJJOpPASSaylOXYMFJkIoFgowuw8UkqEkHRl4tRaDiVpUot08ucna+wZ6aTk+oxt3s5wfZmVY6/xqZ238PSxaZqNFkLTcYw41/fnGahcxDlxGKQEKbGbLVJ2k0KhA3t2Gk4eov+O+7CdCql7vkSwZTeObuD4EIYBcmmeu0dz2E9+nWDrZjzbRkqJPj+H2awiCt0EmQLRZBKiMeKbtuJfOEfjO39BICXCtIhs2Iqx4zocwyTUDJ49s4L+nu9X3faZkTZD2QhCSgTifddXGIb0ZaPMlFvv2zaYNuHoIfR3vU0IQVgpIT0P9/QxzN5BvMW5tX3Zbfwzx9D23fZjW6UpiqIoiqIoiqIoiqIoiqJ8Ul1TAUw8Hmd5efkDty8vLxOPxz/CFX1yVDzB8bl3whehaSzUPC6WW8xW2nxhVy8n5qustlzsgwF/74YBsnGTTtMheegt5jL9vNqMUm3ZeEGIAOJxeP7kDMl0kv/3Q1uptD1+eHaJ/+8L59A0jart8Uu7+plcrnNuapG+hM5tgynKM7Ns7bCQp49QrpXZ3NdB7+Z9vFC1eHKygeO02DxS5E7LovXMG8Suu5UgdIgYa8GAsKIY7Sbrh7sYKCSJpNOcq/lEhncQnJ8gqsdwF8chYtG/ezfx0gKV734NN5AIIJ1N8/m/9RvMdW9GX7+V8tGDWIYFrIU8AK0Akhu2U7M9tsccjsV6MW6+h+gz30a2mnSkogSOQ0uPkbjjPk56MRZbZd66WOZXtnUQi2TQ9t2C99JLxA69yINj2/ByI4T5LjwrSuHk68wszzLqeQjXRvghhq6vBSuOjZEvEthtNNMkvXkbZu8ArrbWgiymQ1KDWNLCOHeUdq1GrWVj9Q8RzF0kpkmCpQWEZlCrVIk/8Ai6rmMfO05YqxBmcmufo+vgH3oNq1UnftNdLIQW06UW6ajJhs4UC7V35rw0HR8niBDVYKwzQUSTBAEYQmA2qtBucn0kRq0Q5WzJIXhX+7CUCMmEDtq75naIMCBs1AEIKmXM4XVXXK/e9CTmrhtwtWvqV5CiKIqiKIqiKIqiKIqiKMpfm2vq7ueePXt48sknGR0d5ZZbbrli26uvvsqTTz7Jbbfd9jGt7tpWsX3Cd43UyCQiRCyLsWKCpbpNcGljGEpmKjbHFhrs7MtwcMpjd08f0XQvKwen8S+FLwCaEKCZBL5kteXx/3nuHAD92RgXVpsgJd8+MsMv7R5gYmaV2dU6leFO7uyLMvP9x8HzEGFA26+RmJ3kvl03sf1TN3N+scrGONS/9j1C00IuTDPSu4Gl+UWk55KKWdzW24136DWqB5uYyRiBZuLtupHa7Y/Q15HFWFrA6ugmEXpUjh8hEJeqOgRork35e99APvg3mB/cRsfWnVSPH0HXLQwhQdeJ3XoPy6UqpeIGkpZOl11h0pFs+vyvEisvUJ+dRcsUkMVBHp/1uaEDdvSm0XSNiekldskpFguD6A9/mepCiUBonKlKjs0ucX1XFHn8CDHpw/pRmDhLNGZhhgFho4FbLhEWuzFHN1HxBbFjrxKcP0nkrvsJhzcSEyHXDeWpeSu0j4wjgZnDRxm+6UYK/f34h14nFGDEE+TvepD5C5MMaCBLy5AvAmA4NsHiLJ5t481MkYwnSMZzDKe6mKx7bC0kKSYjVOx35rx4oaQjbrKtK0kQeER9l+DAqzTHT0MQIITGrcVexrbczJOLIX4oiRgag905MvkM/kL9XVekALF2JenZHKHrXnnBahqI91e6KYqiKIqiKIqiKIqiKIqi/Ly4pgKYL3/5y5w9e5b//J//M3/6p39KT08PAPPz81QqFfr6+vjSl770Ma/y2mTqazezLUNjU0+WM8trraLils5wMcmGzjQCeHViBdsLWGy4ZPSAYjKCvvdmIvMreEG4Frqwdu+8nchyx3CBxbrDd47N0fYC0lGDUsslkBJNCNxAcmqxzq2bulkXRFmnrWC9/jQDSYOKjBJIICpxfR//B48zkCsw04hw3rYY6OmjvLRCsrLC3buv59vlMq6W4ab+JI1vfQXf8zCyBXzfp1KuIJ56nOxDj/LkTITbRreQ9R2abzy7Fjxdut9vaoJYNoutazBxmqcyO3n4ts+SHt1EuLoEhomXyHJqapqNG0d4riToSJrs6c0xPjXOqRPjmIUOyO9mouaxuFCnJxtnIKYx7TXw9CQVaeD1jZGsrHLQi/GXZ5ogQ0Qsjgx8WhkN04oQlmu0oyn8fBfu0gJa6OGHEkvXEYaONjhG5MgbaKUl3PIy5tbdRIpdtBIZtnTGWG4VWNE1PAkyDKgdP0IuEyGy9ya0VBpHGMwvlbErdWRPkaBRQ+SK6L6LNzMJwaVwxfeRtk3r6Avs2HU7C2YXZ+YrfGp9kaVWwMm5MgA3jxTY2xMnofnoCIIDr+KcPXH5GpMyRF+eYeDID/g7n3mUVSzSlk5CD4hs342/MPPOazUNPZPDX17E2rSd5viZK65Xa/0WPN24NLtGURRFURRFURRFURRFURTl5881FcCk02l+7/d+j2effZZDhw6xsrICwODgIA8//DD33HMPlmV9zKu8NuWjOnFLZ7QjzbNnl9nZl+PJU4ss1h00AemowaauFHds6OT5s0t0JqP4IWwuRphrGsQHUySGbLxmA3QdL5KgaUU4uVCjLxtjsWYj5Fp1jB/KteoHXeD6PtL3uSEscf473yS8cRf2xUnatkcqkybaP7Q2f0RKXCOGpZmsWzdA1fbpK95F/rnvk1ieRn77f/C52z/HeS9KZPocnmWSyyQIIxbnF8oITQcgsniRTduHWTItgu03k02miRx7He/8aTQBqWwaL9+FjiTWqtCKevyvlQi3Z0cwSjbtuXkMvc7QTTex0jfCoWfP8uj2bvYfm+C67WM8r0eZbAasLDRx3LUAY2NXmtcmlhnr7+T0SgvdMtEH+ygWsww5EeLnSrTdAClDhG5wquRwy7ZdNF56hsUTJ8jvuolEeRntzBFEu0XsuluR/SPIgy9hLM+C5PKcGFlehUSGUMBALkZh20YaZ0/h+yGmdHHGL2C7Ll4kjnX7vVQX5kkYGiIaJfQ8DBki69V3wpdLhG4Q1QXhsf2su+GzHC8HHJ8t05VLs28gQ8IyuGUggRa4SAlms/a+0ORtsrJKqrKA0dUPhIQheN0DxK67FfvQG0jfW5ujk+8guet6nErpiqDFKHahjW5U818URVEURVEURVEURVEURfm5dk0FMACWZfHAAw/wwAMPfNxL+USJawH3benmpQsVhnIJXhpfodL2MHVBMmJgewETqy2ajs/OgTyFpMVXDi8wXIizsyeNZprkujvZf9EgDCVeW3JLd4JXJlb5pZ199GVjlBo2jhdSSEWotD2CUKJpOqNJgXviILoAXRM4YYiua1huG1kpMW1kKCQtLlRc0qst/q+TF3hgaw+TVY/PfuZB2t/+n/iz02TffJpbf/3/oP3KeTK5BBFDY6ruIIUGUpIdHWU6O8QPjs1yseKwfSBHetFn65a72Dc8BhdOM+/qTM41KcZNtu7pp8eweO7cCoupGIODN9A9FiJ1g4V4DG/FYzgXw6lVSZqwO9KkPdbFqxPLGIGBZWjs7M1wYX6VC6U2A/2dmLpgQ2eKmB7ixZOMTR/nwS29PD9ZRUrQkCREwGq6k/zoOvS5C0y+/CrxYoGRPTdjJdNU0Fl46VXWpSP8/9n70yA9rvvO8/2ezHz2pfYd+0psJMCdIkVRpKiVtkxZttRj2b7dV+6wpejo20t0R7eiZ+ye7p5RTLdfzI1+c+PKt6U7M76SZdMty9RKbZQocRG4YCEBEDtQ+171rJl5zn1RQAFFVGEtVBWA3ycCJJ48+WSeU5X5ICJ/zzn/RHsXYa2O39KK9Qz+uQXgnHNUGlsoPPg+OHqQyugwUSJNstBAdbqEa++mkswSVyo0t+SwQQK/0IDn+dipSUxUxxgP5/v4nT1E1QoeljZXpZa07D933UzVIso25JEdjfg2ZHYVu2oF4mjB682Oj2A6V+PO1YKJMLjtu8mu2QATY4CBxiZIpkiePIoxMwFaYvM2WL2eSiJ1c24EERERERERERERkRVixQUwcn2stXTlktTjmI6GNC8cGSbwPQIzU2A98D3C2DJVj7l3dSMHTo8wXq7zRrnOyHSN1S0FHlzbRBjHvHZilFoYk/A9CkmfN04O86FNrUxOl2jKZ8mmAkamqlRjR0Mmwe68ZeDUGXzPkE4lMA0NmMkJyvUIMzxMsiOHZ1IkPEO9sZ2H/ZhEZYpNq5uIoklKQY7sA48zeNeD/Pr1U+wYmWTi2Fk6ujtIpNIkkzFxGME9D/PKqQrJXJYOP0mIh1co8vKxIdLbN5F85yhhpUo+MbMc25mG1WxLJOjY3c2BkSrToWUqlcE5x4FT4zy2KseDXRmOHDrOszvamRoZ49BEgS3FgO0Jn+E4yc/2nSDyE5DOcmy4zNa2Ag+sbsDGdZK1CuHh/ex633r6Szl+ebiPMIzI+HCkpYcPPv5h3MkjFM+cBOcI77qH2vgYI6++Qn10mHqqiZGqZcLLUdz9JCfDBDvb1pE1Bucc1jmmWrvJ/aP/B6m332Ts2DGiMMTP5YnzjfTvO8Cqpiwp31A6c4amZ/8HSs//DTas40olHOA1t5J94DGmjx0GIJNJsq27kXR7kolqRGdTkaJXJ0U0G6YAmEQSMIC79GIDTLYwZ3+A2Doq2QJkC3P33bgNf/MOAGrWXvI+ERERERERERERkduRApjbiHH23LJgFoPDOajGDowhjB3ZpKG7mGayXGdgqkZHMUNbMYPFcGKsyl0deT60uZUNDSmq9ZCWbIKwnoY4otmPeXhjB3vPTGCJ+ez9azg6XOKu9hzewZ+S8Q3FXJrj77zL5gcfw3vh78kkPeyu+wi3P8QIAZu62jD9p+HXP2NqZJRgfRduTQ8tDz/CgMny9qSjWo/wtuzCe/cIpckpaEywqpgiePij/H0pxclanbFyiVwyIJ2Iqfsp0i0tvH5yhCe7upl65wANjY2kH3qcH58YZ9fGDEdffYOezg5cWwf9lYjxSshv3tPD2eFxXOz49Pu20mWnmejciHdokrPlMqZax7mQdWs6mag7YmtZ1ZjhgxubMVH13A/cMLL1Af72lSMUy+M8u2E1oecTGEjYKU5X0+x95SirNqxlz6oiQ0fepXGsl1UteZL3fIz+46cojY+TvPsBfj6dYqgccvDgMM/e3U3RD4GZmTDT2QLeA4/TeO/7CJ2HPXWM6OcvsKEly0QlZGA6JL9qOwerebb+xh/QPHqG+v7X8ZuacRimf/p9vI4uYuOR3LKDKJ1itbWszSfo7Gygr6/vklAkLDaS6OwhvKiuy+x1lkpj2juv+rp0zhG9Z0k0ERERERERERERkdudApjbiLMxWzqKnBitkjTgmRg8sHhUrSGXDKiEMbG1rG/LU4kN339nkEI6ycBUlW/v7+MDm1rZ0ZYlIEVlYoL3dWfpK1v+Xz88SKahQL6hQDV2/PrUGB/f0cnqpjRNQw20Nac5NjTF6to4kweHaXzio5Sau3hhIOLs4VFa1q0jdWAffS+9xKrGNDYVkK6VKafyvG3a2V9J8NaxfrobG9m0qoOOD36Y0Vd/SWMyQdzcxslEE2eHqtggQQaLi2NGRyeIE4aWhkZq6RzJDRto3LKTvpEpDr7dT5zM0La1jYe3dPHL46PYmiXb2c1j6zvAxfQ0F9i9o5OkC6laS8r3WdWU5Z1SGYKZWkNJoC1rMPjs6c5fCF+AKFfkrdIAxJZKqcLRtw5QqdSAmZorT3zigzTs2MW9xZDJ7z6Hq4eMTU+SyabpHBujYdf9HKulefOtE7hiGX/rDkr1mF+fmeCp9QWsvRBaWGupGQ8MeOs30tbZRd+pXmqVOuQa+fU0nN57kBeBZx/ZysYtVUov/D2uUgHAa2wisWkb3vbds7VXLjcTJcSQffRJ7I/+nnhsZHa7SaXJffBjVDP5OXVdRJaa73t8fHX6svvkXXjF4+RdeMXjXO2xRERERERERERELqYA5jbinKM9l2BsdILNeTjSNwWA8QwtxQLFlE9XMU3KNyRyGZ771Umsg8FSnWwiIJXw+c7BAdJ3d/Pq4dN8dFML0dg4xysJkoUcU5U6k9MDdHa1Y3yfv3mzl0/v6cFu2kPjUD+ba+8yfvgoOEeUyfOSt5reRJ5avcyOAoy8uJfYOQamamxvTOJ1r+HvT5XpG/glia07aGvMc2K6zv/ntbN87pHHaF+7meTEEInVG/jVmRrNTUWOnhghFXh4UR0vCpmKPbJFnyAO+dXZKfpP9BGPj5L0DUkMjaO9mDd/xUfaV5PIxjSvWcPYu3vJEeMVGiCzBtNYIFUt402M8UhzO2fOWkrOu7D4loMNbTm6Cz4+BntuGa1aZOlsyrG5PkxUnsQ056k1ruO1EyOM12KOvLGf37p3I0Pf/mucAxfWMcbQXMzRPzpJ9fm/p+ljnybCYMrT+FEEQZITIyUqa4ssVCXFOscpk+dvxjJ4NQ83PIVxFuMsznh8740TfG5bO8WnP4kdH8HV66R23ktt9Qaqnn/V11M5WyD10d/GGx3Ejo/i5fLQ2kE1k58NcUSWTRRx8ptfv+wuzX/w+1c8jInCKx7nao8lIiIiIiIiIiJyMQUwt5m2yX6qpw6yeufdfDeT5MjAJMWUT5Yq6xuK3L+1nYHJCt/e3890LSIZ+JSqEaMupKOYopAK2Nc3yarOVn41VOfjO7qJjo6wtr2RSq2On0hythRxaqxEbB37eyf4+pEzfHzbozza0ETxzHEq1Trx3Q/RN5bExRHWOTLTo4xVa2RTCfywRj02TDT3MHDqFM5ZXKVCfbiXtp51nBmv8Py+M3z03g38YDjH47bAsRPHuP/ujeyP64TVCOMZnAdeMkXsHA/2FDl0vBc/mYBcntha7lrXSX7fL6lXphk+8jatKUumpYg3fIr64f1Qr2O2biN338NM7v0V8cQYzU3NfHLDbg57jZyIUwSBzwOrGtjopmD/K9jpKRLtXZiuVRhryf30W0wMDeMmx3FhiEkEPP7UJ/j5hEcY1mkbPknaTlNtymCzhkTJkpwcYJQ8LorIliYIAh/rB2Bmatc4Fqq8MsMYw8B4CXf2JGG5DEDQ0ISbmsTk8pQrMBoZ/Hf24aXSeDYmFQQEk2PQ0EToBVddh6UWJKC9B9Ox6sJ7FL7ILeL8LBnft8SNaea7s3x0PYuIiIiIiIiIyM2xYgMY5xyTk5MAFItFjDHL3KOVz/c8zLv7Kb/+Gubgm3zq7j3Ud3YzXamRiKGhcowa3RweKjFVDUn4Hg6HZwyeB4NTNdY1Z5mshqxqTHNksE4xmyYyHsPlkEwyBdZwdLiEMRB4Hs6BcTF/e2CAxgd289AfNGFLJfq6N1M//BqUS6RTGQJ/FYWEIbIWv14l2dTBifE6GINJpDCewXcWrzJNIp1lIPTJpJO8cWacbR0FJortHO0d4zfv7uHHhwcYr8X4uSytCcdv7l5N1nOEyTQDJ88wNl1m1/pOtntTRJMTJGs1WlM58pu2EO39JdNv7Z39mTljGXv5J+Sf/RzTUxO4WpXCr3/EAw1NPPrY09iODhLvHqT08x9eCB7e2Udq/SZMaZp8VGbCGLx8EVeaxjnL+E+/z56P/Q6eH+CnapihXjKeR6JQpH7qCC6RoGlVE+VqHRdHeJ4Hza3E/sztuK4lR9Z32AXKpgTGEIwNYc+FLwA2CjHZPK40jckX8c/9PN3Zk7hkiuqxw9ROvEvQ1Erm/R+i0th6TdfW1QY2IitKFHHym/8/kskk9Xp93l3afv/3lrhTIiIiIiIiIiJyp1hxAcyZM2f4+te/zptvvkmtNlNPI5VKcc899/A7v/M7rFmz5pqP+dxzz/HKK69w9uxZkskkW7Zs4XOf+xzd3d2L3f1l5dkYNzLAqsYMp8crDL3yy9k243kUu5sZ2/MovoFVTVnGeieJrSPwPRozAbubArY2BPjJBOl8jicbI5oCx1ipTv9Ujdg5sgmfdS05To+VqUWWhkyCcujAWH5yeJDNazM0DB7BmyjhTU1gkilsZZqBsWmaAkMYxbjAw4/qeAYiB14QEBufXDaNMzEtLU3EzhFax6rGLJ4xTFnDy5MeA1R5cNtqkskka5szjI6XeP3QKQ4PlynkszyxbQMb16SYfOE7nJyYor2Yoc1V8BOGdFsHZ1/4zuzPJEhnMNMTuOkpam++SmLdRuz4GHXnMT0wgv/jH9L29CeY+sVP8N4z68NPpqn8/Ic09axnKp1gsgomX4Q4gjiiw6vTevcO3OkjkEjiKmWc8Qh61hD1naEQV8mkU8QNzcTDE/idPURAJunz4Koi6dEBXK0GuRxhoZHIXghAgskxuuw0njHYc8GILU8TtLYTD0NLMUPT5CCMjWDSGdIPvp/SoQMARGPDlH/wLTK/8Rmq6dxNvBpFRERERERERERE7mwrKoB5++23+U//6T/hnOP++++fDUh6e3t57bXXeOONN/i3//bfsm3btms67sGDB/nIRz7Cxo0bieOYv/zLv+Q//If/wJ//+Z+TTl+5+PKtwnk+Xr5IfnSYja05pmsR9ciRTnjkkz7pfJaJwHBmvMxdnQ28eXYc62Bnc5KPpcaI33wVrzTJ1u4mMk1NjG57mO/9+DX2rF5L/0QZz/MZKddxDlY3ZWnKJDg8OI1LpjHVElOxIZ3NUn75Z2RbOti08QmOHDqBtZb9x/v50H2PEr/8MzwcwcQwmzYY9htDsrObaml6ZlZONmC0ErK+JUfCMzRnfF45McpTWzv4u319HBmvcXJqhA9taefrr50iHxiCesjQ6CRDo5Oc7hvmDx9ez9o16xh6Yx9DU1U6N62l+L4nmHzxh3OWz0qlElCqYJJJomOHyG3ZweTwMOORx0jdETBJ6ti79I1Ms7oxTXDxUkU2xpZKJOpVehoytOSSTFYjAIrpgKakI04G1NdvpfCbn6X0w29hrcXvWUOqrZN4bIStD9/PmfWbac1H1I3HupYc97Ymyf/kb5juPT1zHs8ntXEr6fsfpRokZ7bVqhRPHuB9d+3kF2+fnVlUyUE0MUq6tZWnH9lKQ32UOOkTlaZnwpc4utD1ShnXewaz8a6bfEWKiIiIiIiIiIiI3LlWVADz1a9+lYaGBv70T/+U1ta5SyQNDw/zP/1P/xNf+9rX+F/+l//lmo77pS99ac7rL37xi3z+85/n2LFjbN++/Yb7vVJE1pLZdg/1U8dIGktz2sMYc275KEty+z2kkykmKhFv903wmzu72d83wSfcKQZ+8CMygc+uzhzx4f2Um1vZX9zKaS+P1zfGU5uaeWugTOwsycDnkfXNRJHl+f29JHyfTDpDV0OWvKsxPjqEby3v3zpOrbuVU/2jTJVr/PDYKB/5xG+zevQk/tljrKLM7kfv5813TjI5PoXFYLIFqvWQVcUUb/eNUwtjRkohB/sn+Qf3rWKyGjFVDelpzHC4F/oHRyk2NuDli2BjgmSCH/fW+N33f4KG7Q9DtUy4cTUm6RE4N7NMG5AOPFK+wcvniXrHcGFEVJ5m4thRUokEPV1rmGpspF6pUq5HDE3X6S4kZpficoDJ5HDO4jlL1odcfuZ2cs4RtLYRWksdsDvuJdPYQv3NV4gmJ/CaM6Sf/ATelp2s9gM+tcrDOUchrlH91v9FODVx4ZdqY2pHDpLyPPyHP0hsLaQzMDbMTv8dOvdsY/9IjclaTE8xydacoSueIM4XKb39Fl4uT23LbiZTRQAaK6OkTh0mHhnA23z7XPsiIiIiIiIiIiIiK82KCmBOnz7NZz7zmUvCF4DW1lY+/OEP81d/9Vc3fJ7yudoZ+Xz+ho+10oTt3WTufx+VvS+DjWcCA2NI37ULt24L1lo+eXc3X//1KUr1iN/fkif13X3kW/M0pAMKpWGqtQqJjXdx+OQAcaGdo+NVjvSOsWNdG7u3d9I/UeXtvkl8HL43s6xYIp3iiR2riCtnSO3Yg28jSj98jqd33Mv4nl2UnE/Oc7SVhmDgNMnu1ZgzR3kskaBlUwd7MwlsUxt+YzObEwE/PtjLB9YW+KebAwaGp5nyDMdHfI5O1HlkfQsTlTqnzw5ijCFjLVM1S09LgWrsODAwxb7BImNlj/vWruOFvir1sM5v3vsY2aF+EhPDuCjC+D4m8AFDYv1Gyr1nAYjrNfz+0zQ98TEm/AwehjiOcbGP5xksUBvoI3Pfw9T7zsz+7M+HM35jM66ta3Z7ZDzi1RtI9KwhUa/hggS1RAprLcQxPueKvQycIT4XvphUmrhrLWEqS6oyRf3EUbI776WSLRAWGkmt20zt6Dt0xSHre9ZinMW5KuH4FHbLBkwcQXsPR7q284t3hyiVewEo5DM8ftdjbC1AaFV8/HaWdREfX31+hp9ZsBC9itCLiIiIiIiIiIjcHCsqgGlrayOKogXboyiipaXlhs5hreW//bf/xtatWxesJxOGIWEYzr42xpDJZGb/fvH/V5oYYPu95NdswA0NzMzQaOtkPN/GsfEae3uHKNdjfu/BdYyVQsxkL6XpEk3ZBNV6SDgxge8ZbJAkdg5Tr2CMRy2M2Ht0gPRInWwmSXM2RdI4nIOtnQ08s7OT3qkKpys5tjatonWiHxsksO+8ReOht+iIqlCvk/uNz1Davxf3vg+Sef/TeKUSjVMV3r+1i8M2ywtHBhisG/5gQ4r0K9/hzOQoXU1ZvErIB1av4an3f5hCRzM/ODSEl0gQ1er4ztHZnGO4HDJdC0n4Hrl0gtFqzP/2o3fZ0p4n6cHrnW10ta6jzQ/IxFXqOx8mNB6ZXQ+RKeQZ/85/B8D4Aem776PW2ErJpdjY3Uz1nf3YEYtJJgiaW7FAYveHMWs2UNm3F1ergueRXLWO5IOPU0mkeO8VEnoBpM/dcs7NuYaMMdjx0Znf4fqtHC+sZu+ZccqVOsV8Cw9s38AmO7Nf7BzpBx4j0dJKuH8v03/7f+HCOiaTJfPAY/jOUss3MLT9ffzgZ/tngyGAqekK3913lsZPPk7zReeW248X1Tn5za/Pvl6oEL2K0IuIiIiIiIiIiNwcKyqA+fSnP81Xv/pV7r33XtatWzen7fjx43z3u9/lD//wD2/oHF/5ylc4ffo0//7f//sF93nuuef45je/Oft6/fr1fPnLX6atrW12W2dn5w314+brgs0ztXJ6Jyp8+42zM8t31WLeHZrmxFiVza15dhXTnKiG9E1WWNuUwUsElEqW5NmT3LX2YX496WFtjGHmQf10LWSiEvJbu7rw44jHNzazsS3P//78G4y7BOlshva7HqL+8+fpzGSoT5fxPYeJY9IPf4B4ehq/tYPklh2k1m2EhnZeePEogyd6seE046WID21sobjvZ3gdHaTWrqE0Osj48FkK/WdJvvIjOn/3c6xvyZMsFAjMFOXpEk1tLZydqBL4HnevaiKbCvjJoQFyCcPY+BR3dRR4p5Ig+/hvUTRlDo+W2He8n0o9orlnE/evbWLtP2in3t9LnEwzfLaP7HSJ4lQv8aoNZOpV/NNH8Oo1mJqk8MBjZHftwcsVKO5+EFeahmSSoKUNk0jSeB2/sepAO27NRn6WXMWbb/fPbh8ZL/Hd8RJPdq3j8c2dM8vKRRHT+39NVJom1bN6ZjZPOouZHMP98sc0PPM7fKeeJcgXcJXyhZN4HkFnDwcmHZ/a0AHcCteyiIiIiIiIiIiIyK1nWQOYv/iLv7hkW0NDA//6X/9rtm7dOvtguK+vj8OHD7NmzRqOHDnCY489dl3n+8pXvsLevXv5sz/7s8vOpHn22Wd55plnZl+fnyEwNDREHMd0dnbS398/Z2bBSuX5Pj85Nkn/6CQAvvFoyQb0T9X5Vn8vux5dhc0XiIZHGZyu05ZrxI1NYCfG2GCmOdGyhncnh8FZ/HSW0ML6liwJLD947Qg7NnQwcOI007UQF/iUKzW+MRjwqSc+Sc/A22T3v0YqlyO7dRuVs2cZ+fmPKdxzP6Nj03gv/pjCzt1s72zkjTMZOvLQlnQ8srqBQ+VdHOibIB16dLRtZ9vmXXgHXyHqPY0ZPE1PQycf3NrJDw46PB/yKZ9H1xRJJAK2tec5OThBIXC4WpVaFFFNRpipCU5mevjlVIJ6PUeqpYdw4Cz9x0/y7eMneWz7app6B5kYHASg/ZEE737/ZwxFEZs2ryOzbTs4h7Mxpd7TxP19VHKlmR90Ij2zstPwyHX/rtKFJgbbN/D63jPY91xbXi7Pz0+O0dOcJedFZKYnmH77LTAeJM8tMxWGM3/KJ7AnTtA75WE7e/BqVVytBr6PSWeoBQlODU3QP5Shp6P1lriWu7q6rryTiIiIiIiIiIiIyAqyrAHM9773vQXbDh06xKFDh+ZsO3XqFKdOneIf/sN/eE3ncc7xF3/xF7zyyiv86Z/+Ke3t7ZfdP5FIkEgkFjzW+f+v9IfWANMRHB2avrDBWfKpgMpoBc8YfnC6xLNPfATzvf9OWK1xuu6zobUVwipp37CrLU17oYe3h8u4VIa1DSniOKY6OkrL2Bm2N67iZwdO0dXczemKw05NMDrl+H8Pe+xcu4M//oOHSZ89xvivfgpA9+/934lqNUa++038TJZEvcqjj3yQd9c289LxET64tYMXjvRx4p1e0gmPMtA3NsXZQoZP7nmUxv0vEpemaW2w7GjPs755Pevro8SH98NgL14uRy21mchrgIkRgkwOP5XAJJPUS5M0phN8550hNrbmCJIpjPFmK2K8drSfz+y6h/DFH+O1dVHFw4tjOgtpkuNDlMcHZnY0HnUL0cgY/V4DzWmfrBfP1HS5AbVsnrGWVTivF+J4drtJZ/A7eqiElrFqTDbjcOXpOfu8lxsfoZjuplSLsKkspLIXNUIuFeCbmf7eKteyiIiIiIiIiIiIyK1kWQOYr3/961feaRF85Stf4ec//zn/6l/9KzKZDOPj4wBks1mSyeSS9GG5OGeI7NyH62FsSXiGbNIntI6fxU1s/dCnyJ19l/rAWeL199GyeTNhqokDr58mKBZZ297A2ZESe48M88T6JgYOHuHxrZ0kp0aJ4phCZZx1hRaGSFKpx/ieYXRsmn7aadu6h7F0K2ercPzwCbpzCTY//DT2p99m6LvfoisOefqxT7K+Jctk3XI8dDTnkhjAOkcuERBFEW8O1Vjd3olJZ/DiOhuaksQnThL88DlqlTJHB6YAR4Jf8fBvfoq9TVmmvCQmm+fU5DQJl6RloorveyQ8g8Xgd62GgTPYUolqLaSayrFlxxbsI09hRofJtmYJjMO5mbDCGo/B6ZDRUp3ieIVv9/aSTQY8tbWNtXnvhkIYay0um8VfuwlqFYgiSKZwqTSR8QDwzpVrMcnUZY/lZTPsyhfpm6jM275nVQPuMgGOiIiIiIiIiIiIiNyYFVUD5mb5/ve/D8Cf/umfztn+hS98gSeeeGLpO7SEMr6jo5imd/zCg3jfgO8ZorqjuyHDKydG+FE1or2wiaYN2/js/as5WKpRq1v23LedkUpEuRbyvtY8q3KrSE4Ok60lKZ54mcF7P0TQ3IKNYlL9J1mdyRJnUhgbk6pM0lBv4/l3HO++3Ys3OoCtVjkF7Mtl+K0P/Tb+t/9PKm/9mrUPvp9s92r++q1+6ukcyeZWwoF+wlptptOex8nBMeIHtxI1zJSPb4hK1N94EVuZwpRLtBWzjE2VsfWQyZ/9kGc/8Tn+n2+XsdNVvHIF6/s4a8klA0ILvgexH+B1ryVRr+HimPSGjfjbt8wUum9uJE4EuHCmcLkxhrFKxEiphp9MMpVpgDKU6xHfOdDP797bQ6N/Y7Ng2rIJSCSI/UtvzWwyoDntA5ao2ETQ2kE0PHDJfiaVhuYO1mcS7OppYP/ZidlZPp6Be9c005P3wS1fAOP7Pp43E1jFCoJERERERERERETkNnRHBDDf+MY3lrsLy8bYiIfXNfPf3+olPjcTJuV7pHzD2uYMxbRPJZwJDQanaqxrzjA4VefFd4doTHngHK0NBXwX0t3VzKacxeSb8Truw91zD52ZAuvqfRx5620AXKWMd67o+/3behiZrvLuUEiQCIiq1dl+lUoVXh0t8P61G8CH4WPHeXkiw+BklaPDJVImQ1fXWry+k8S1Gj6OXCZFct1m6sxMA/Enx4inxvF9D396gs6CodiaZ3SyQr1cZrNf5sE1DRw4O07ZQXM+xd09jewbmKZ3ssL6pjTGOSwGm0zTmE3S2dlGaXwYgFq2QOa+91H+1U8BRxwkqRay5HOW5KbtvFhJACEAkXW8O1zmwa70Dc2CKQaWRza08It3h7l43pJn4PHNrWS8GGuhbjyy73+ayg//jnhq4sLvO5ki+8RHqWVz+DbisTUFdnQW6J2o4nmGrmKKpoQDG8G52kZLyTOG9OQo0bvvEA8P4De1kNq8nVpjK7GWQRMREREREREREZHbyIoKYD7zmc9c1X5LtXTZ7aIr4/jk3d386sQo/RMVkj58ZFsHjZmAN8+Ms6OzQN06skmPT+1ezbfeOkNj0sC5B+LlMKZcrvLCOwO07ekmEwBBElIzs0Ke7klRLHdy4PQo1VqdYj7DfWtb2GkmeP5UDT/Vjpe6dMmsY2dHeHTLPZROHWF0qkafX+Wu9hxHT/UTB0nOOI9Nm7aRqkwSeB4bW1Nkp0eoNM/U8HHng45MFjwPMzVOrjRJwfPAeEwNDpEbG+NjG9fj2QKVSpVjg2M8sr6FH7w9QGgheS6DSPgeH9zcRjGToDQ+s806R7RlB7mGJszIAHZslPbjxzANzUwV8qzyYbR8YTxDUzW8nuwNBTDOxuxqS9GW6+HN3gkmKyGt+RR3dxVoS4O1F2aLVAqNpD7xO5ihfuKxYbx8EdPeTS1XmO2DsRHNAbS0ztQ0ci6CG5ukc908zyN19gTTP/4OxBEAYf9ZOLSf3GMforZuC1YhjIiIiIiIiIiIiNwmVlQA89u//duY93wr31rL0NAQr776Kt3d3dx7773L1Ltbl7OWzhR8clsrldhhMOQTMBlCc9pnpFynJZtkVWOawek6np1/SahKGDNWjclkLjq2c+RSAQ8P7+OeDRuIEg0kK5Okjv0Skytgc9tJ+oYo30hQbCCavDBbw2FItLTR/85B/M7VjI3V6cwnWNuQ4uTwNHiGicDSWZ0g5TnuXd1CdPwwflvXzLJV+SImmcICQUc3Uf9ZsBZnLcYzuKYWRsaqDOx7Gy+Vwe/oJpoMaS/6/M6eHuqxo1St0dWQZmtbjubEpclE5CDR2Ext70tEgwMMTNaZ7J/AHTpGz/qN+Ls+wOujM7NgWvPJGwpfzjM2pisNPZsbiZ3BNxYbx7j3HNo5RzWRgu61eKvW45zDOQfz9MGtgGAjWS1TeelHs+HLLGsp/+onZDu6qaRzy9M5ERERERERERERkUW2ogKY3/3d312wbWxsjC996Ut0dXUtYY9uL8aGZM/lW3EEOQN3NfmY5uy5h/f1K85AmK+1lm8gvWU79uWfkzq3hwUwHtvuW8eJYxN4qST+uk1w6hhEEZ5nWNPTSnpigPTWneyPc0DIu/1j3NeeYkt7gbf7p/ATPvet6WabX6Kw7xd4O/fMLlVVy+bJ7HmQ8ssvYgsNJFJp7OQ4LqyT2f0glfWbMWO9BM2tuCDJ+cf+g5NVPOB37unA2BjnHHEc4dylS3J5noc9coBwaADjGdLJgInazJGmjx9l1brNHAg6iK1jU1sOa6NLjnG9bBxhuLoJK4sR/NxsZmIMWy7N2+bqdRgbhi4FMCIiIiIiIiIiInJ7WFEBzOU0NTXx9NNP89d//dc89thjy92d28bsrIlzWrNJPAN2nqQlFXg0pT3eGwnEgNlyN/m2TsLDB7GTEwTdq/DXbaan0EDrYJXh6Ro2myO9YTN2fASvXuORzZ3kkm2crTdwbHCmPkzsJzl88iSpuM7O9ma6W3M8NHKQ+okjOGPwV2+gdi5ssNYSbdlFLpun9sarxFMT+K0dpLbfAxu3kfJTrO1u4ejQ9Jz+JnzDoxtasGH9ijNDEvUa9SMHZ39WzdmAepxkvFzHAfE7+1j30Fo2dRZpTthLZqnIRa4QTrlo8cIrERERERERERERkeV2ywQwAKlUisHBweXuxm2tIWG5d00zr50cndvgeTy0oZVCwlyyghRABERN7fjv68LzPMI4pmYtSVvnN3a081b/NIf6p4gSOXp6WnlgdZHOlCMyHtnBGpwLYCwQtHdRPX2CU6f6ua8lQf3kUcCQfeAxasWm95zXEK/eSKJnLcl6HRcE1BIprLX4LuLJjY2sa87yVu8k9SimuyHD7p4izYn46pblcnZOMOA5S3chSUs2ST22pHIBazc24hl3oSaNzK/QCEEA8wUtxsNrbF7yLomIiIiIiIiIiIjcLLdMAHPq1Cm+853v0N3dvdxdub3ZmPu6s7Tmkrx+ZpypWkwm6bG1rZne8SqnR0vs6WmkKztTMP694jieqc9ykQwh7+vJsqcrh3WQ8R0ujqlbgJi7WjMMThU4NDAFQBQkSazdyMNdWVaXT+Lv2E2wYQu1hmbmq07jnKNufEidK05zURCScBF3NflsaW4ldpA0DmsjrrYkSpxME3T2UD9+5KITWlIepDxIr1tH7BviWOHLldRzRdI7dlN987VL2lJbtlMvNM3zLpGVwfc9Pr46fdl9si7CGm+JeiQiIiIiIiIiIivdigpgvvjFL2LMpXU4SqUS5XKZVCrFP/7H/3gZenZn8W3ExqJh/c523h0POT5WY9/pEaJz65KdGC7x1F0d3NXkX3XtkTiOSZ77u3tPipJwIU9uaOCeniJ9kzUCz6OrmKQp4TBeG7Fz1OP5oper45zDuIiA+ZdWu5zIObK77iM8fQIXhXPaTDpDsHnbDfXtThI7h7/rAbL5IrW3fk1cmsLL5kht3w2btlNb7g6KXE4UcfKbX7/sLi1/+Dls8vIhjYiIiIiIiIiI3DlWVACzffv2eQOYfD5PR0cHjz76KPl8fhl6dudxzjFZt/zo7X5Smcxs+ALggF8cHWb1vd1krqpE/JUZG9GagLbWxLnzRzgL0QqYWFJpbCX30Wep7X2JsL8XjCHZs5bkvY9QyRW56uk0Qt14eJt2kFyzCS+qY4MEYTJ91UGeiIiIiIiIiIiIyK1iRQUwX/ziFy/bXq1WGR0dpblZtSKWwnA5JF4gXKiEMePVmMwif9n7quqyLDHnHOWmNhJPfZJctQxAmM1Rtk7hy3Ww1lILEhAkzm9Y3g6JiIiIiIiIiIiI3AS31GL1zz//PH/yJ3+y3N24YyhbmCsEKukslXR2zowgEREREREREREREZH3uqUCGFlabbkE3qUrwgGQTvg0pv2l7ZCIiIiIiIiIiIiIyC1iRS1BJitLQ8Jx/9pm9g9W52w3wPs2tJDzYq0eJSIyy1B1l/9eQ+B5RFfxwZnwDL6LF6tjIiIiIiIiIiKyDBTAyMJszH1dOVa3NfCLw/2UahFN2QT3rm6kO2uwVg8HRUTOcw6e2zdw2X0+ubOT/77/8vsAPLurA3+BGYgiIiIiIiIiInJrUAAjl+W5iD2r2uhMRtRjSHoOF0egmS83xPd9nHNYTSESERERERERERERuS0tewBz7Nixq953dHT0JvZELiuOSDjH7bAiju/7YAwGiKJoSc+dikK8oT6iMycwiQTB2o2Eja2ERuWYRERERERERERERG4nyx7A/Jt/82+WuwtyhzDGMBb5vNNXom+iSmM2wc7OAm1pYAmWU8vUq9R+/PdEg/0XNu7bS3rnHhL3PEzoKYQRERERERERERERuV0sewDzJ3/yJ8vdBblBxg8oRQYHZH2HsTc2q8T4AZXY4OHI+I44XiAc8XwmQ8NQOcRaaMslaEy6ecMUYwxnyobnD5wljB0AfRMV3umb5AOb29jRmgR385YD8zyP+O0354Yv51T3v06uZy1he89NO7+IiIiIiIiIiIiILK1lD2CeeOKJ5e6CXCdjDKOhzy+PjnFqpIRz0NmQ4ZH1zXRlHO4a65sYz2Ow6vHKqTEGJqsEnmFbZ4FdnXnShHP2dV7AmwNVXj4xQmxnAhXPwO5VTTzYk8Nzc0OgGgE/Ptw/G77MHgf4+dFhVjeuoujfvAAmWatQPXJwwfbwnX0E3WuXfEk0EREREREREREREbk5tOaRXLfJOOBv9/VxYriEdTNhRt9EhW+91ctg7dovrf6K4bk3z3JypEQ1jJmuRbx6coy/OzhIzSTm7Ntbsrx0bHg2fAGwDvaeHuP4ZIQxZs7+4zXLZHVuiHNeZB39U/Vr7u81sTE2XPgcrlIG5xZsFxEREREREREREZFbiwIYuS6e53FoqESlfulyX5F1vHpqDONf/QQr5wW8dHyUyF4aQgxN1Tg7WZ8NVfxEktfPThJj4D1BC8De0+NYz5+zLZ7nuBcLrb0ktFlMcSpDoqVtwfZg1TqsAhgRERERERERERGR24YCGLku1nicGCkv2N4/UaVyDXXty7Ghf6KyYPuRoRK+71MjweHRkP39UxwdqXB2KqRm5wYn5VrEe3OhhpRHKpj/cjdARz6Fu4kBSGQ8kvc8BObSPphUGm/DFuw1LtkmIiIiIiIiIiIiIivXsteAWQoHDx7kW9/6FsePH2dsbIx/+S//JQ8++OByd+uW5hlI+AvPGEn4Hr5hZl2yq2AAzxjiBUKQwDOEJuDv3+nHOmhIJzk9VmG8XGeyErK+JUvam3lvQzZBygcuCmHyvuX+tc384ujwJcfe0lmkKXX1fb0ezjnqHT3knvw41ddeIp4YBWNIdPaQevD9VLIFLUEmIiIiIiIiIiIichu5IwKYWq3GunXrePLJJ/nP//k/L3d3bgsujtnV3cDZ8flnrWzrLJD2HPFVzoLJBZa1LVmODZfmbb+ro8CJ0Qr9E1UMsGNVMwf7J7AOrHMMTNVY25jCOMf9a5ognlvM3lrLrvYU+WQnr54aZbISkkkG7OopsqMti2fDeZczW0wxUO1ZR7KzB69cAmOIckXKoPBFRERERERERERE5DZzRwQwe/bsYc+ePcvdjduKc441xQSb2/McGZye09ZeSLGzI0ccz1/0ft7jxTGPrGuib7J6SV2ZLR0FugsJvntoYmZfoG9smk/s7OInR4aYqkaUahF+kOP96xpZlTMwz2peno3Z1GBYt6udmjUEniNtLNZefT9vlHOOmhdAvmHJzikiIiIiIiIiIiIiS++OCGCuVRiGhOGFh/LGGDKZzOzfL/7/7e5y400Q8dTGJrZ3FnlncJo4tmxuy7OqmCRJyMzCYlevKWH53d3dvDNU4vhwmWTCY1dXkTXFBElj8S7qw0ipTi2yPL21DXOursp9q4o0B9FMLZXL/H4CYs6Xg3Hu0jHqdysiIiIiIiIiIiIiN0oBzDyee+45vvnNb86+Xr9+PV/+8pdpa2ub3dbZ2bkcXVs2lxvvKuCBjYt0HmBzTxthZDEeBN6FovX31hP0lS5MbbHA6YmZoGxtc5ZNHU0kgkuL3F9zH/S7FREREREREREREZEbpABmHs8++yzPPPPM7OvzMwSGhoaI45jOzk76+/txd0DdDmPMTR2vMeaqj9vkBbSl4eRoec72dMJnT2cLw0MDN9wX/W5Xpq6uruXugsgV+b7Hx1enL7tP3i3dkociIiIiIiIiIrK8FMDMI5FIkEgk5m07/6DaObfiH1ovpsUeb9Jagolh4qFBTCKBae+ilm/AXuYcASFPb2nh+Fiefb2TRNaytjnLjs4CDX60aP3T71ZErksUcfKbX7/sLs1/8PtL1BkREREREREREVluCmBkyaWjOtEvXmD61LELG32f7EMfINy0jfgyWUDShdzV5HNXSyuxgwCLtSE3kh94nkcQ1jHejS9fJiIiIiIiIiIiIiICd0gAU61W6e/vn309ODjIiRMnyOfztLa2LmPP7jy+72PfepP6xeELQBxT/uWPybe0UW68/O/EOQdxhMdMHZjrZYwhMz1BdGgf4ekT4HmUd91LunstleTllxESEREREREREREREbmcOyKAOXr0KH/2Z382+/prX/saAB/4wAf44he/uFzduiMlqmWqh/fP3+gc4btv4z/0BHEc3/S+ZKbGKX/nr7HVyuy26q9fon7wTdJP/ybVhEIYEREREREREREREbk+d0QAs2PHDr7xjW8sdzcEMFGIrVQWbHeT4xhjbno/fM8j3PfrOeHLedHIEMnTxzEbt6s2iqxIsfEJ7eWvzRw3/z4SERERERERERGRhd0RAYwszHg+k5FhsmYJPENT2iPF4hW0fy+bTOMXG4gnx+dt9zu6Ce2NLCx2dRLVMpXTxxdsD4+8jb9pB5ECGFmBQut4bt/AZff53NbiEvVGRERERERERERE5qMA5g5mTcCve8u8cWaMMJ4JGgrpBE9uaWNVlpsSwtSDBKl7HqD84g8uaTPJJP66zdSWIIC5MgNLMBNHRERERERERERERG5P3nJ3QJaH53kcGq3x6snR2fAFYKoa8vyBPsajm5PNOeeI124i88BjmGRqdrvf0EzuQ79JtdB4U877XmE6S3L1+gXbE5u3Ea+IIEhE7kSe51F1l/8TG3+5uykiIiIiIiIiIpehGTB3qJrz+PWp8XnbwthxZLjEg13pG54F43kzGZ+9KMwIjYe3fQ/ZdZuhNIXxfeJiAxU/iVui0CO2ltTd9xGePYmtlOe0Ba3tsHq96r+IyLKJYsd/33/5Zeae3dWBr4l6IiIiIiIiIiIrlgKYO1TdGqaq4YLt/ZNVvJ4scRxf1/FTcYg3MkDcdwaTTOH3rKNWbCQ+VxjcWkslnYV09sKbljjwqOQbyX7s00SH9hOePobxfdK77sV0r6WSSF35ACIiIiIiIiIiIiIiC1AAc4cKjCObDCjVo3nbm7LJ654BkqlXqf3keaKBvgsbf/1LMve9D7PtHiJWxle2nXOUcwW8+x8lsftBjPHI9vQw0de35GGQyLXIuoiPr05fdh8fLaG3Evm+d8XfHUDeLRyQi4iIiIiIiIjIrUEBzB0q41l29jTw8vGRS9o8A3e154njCHONheh93yfe9+u54QuAc1Re+wX5zm6ipvYb6fqis9ZS9/xrHqvIcvGiOie/+fXL7tP2+7+3RL2RaxJFV/zdATT/we8vQWdERERERERERORm8pa7A7I8rLXc3ZFla2dxznyUhO/x1F0dtKaubwZIolKi9u7bC7aHR97G91U4WkRERERERERERERub5oBcwdLuJAn1xfZ01NkpBSSCAxt2QR5P8bZ66v9YuIYV68v2O5KU1ecaeJ5HlXngYO077DXWYdGRERERERERERERGS5KIC5wxkb0RxAc8P5UCTE3UDpCJtK4zc2E49furQZgN+9htDOfwJjDFM24M3TUxwdmsY5WNeSZU9PAw1BdN01aURERERERERERERElpqWIJNFVfcD0nsenLfNS2fw1mzELhDATNuA597q580z40zXIkr1iAN9k/z1W71MxMoKRUREREREREREROTWoQBGFpVzjrBnPdn3P42Xy5/bakh0dJP98G9RzebnfZ/neRwaKjNVDS9pq9Rj3jg7iafaMSIiIiIiIiIiIiJyi9C0All0kTHYDXeR7lmLKU+D7xPlGyhjYIFlxGI83h2aXvcvmUcAAQAASURBVPCYJ0ZKVNcUSF60zXgeU5HHSCXG4WjOBDQE7rrr14iIiIiIiIiIiIiILBYFMHJTWGupJlLQkLqq/Y0xGGMWbPeMwXCh3Rmf/UN1fnl8mDCeCXV8z3D/mib2dGXxbHRjAxARERERERERERERuQFagkxWBM/FbOssLNi+uT1PylyY2dJXcbz47tBs+AIQW8fLJ0Y5ORldNswREREREREREREREbnZNANGVgRrLZub07xdSDE0VZvT1pBJsKszj7Uz9WE8P+CNs2PMv5gZ7D09zrodrRi3+LNgzs/UsdYu+rFFRM7zfY+Pr05fdp+si7BG36MQEREREREREVmpFMDIipEi5De2t3NsrMrBvikcsKU9z5bWDBnC2f0iB5OVcMHjTFcj6haubvGzq+MZQ2p6AjdwFlsu47e2Y1s7qQWJRTyLiMg5UcTJb379sru0/OHnsMnLhzQiIiIiIiIiIrJ8FMDIipImZEdzwPbWVgA8Z2dnvpwXGGjKJhkt1ec9RjGTIOUD8bzN18wzhtTpo5Re/AFEF2bVBM2tZJ96hnI6tzgnEhEREREREREREZHbhtYukRXHOQdxBHE071JfNo7Y3dPAQlVe7lvdiLGLlL4A6alxSj/7/pzwBSAaHab+yosEqjcjVyk2PlXnXfZPbPzl7qaIiIiIiIiIiIgsAs2AkVtSRwaeuquDnx8dphrOhC1J3+PB9c2sLvg4uzj1X4wxxL0nIZ4/0KmfPk5ueoIoV1yU88ntLbSO5/YNXHafZ3d14CvTExERERERERERueXdMQHMd7/7Xf7u7/6O8fFx1q5dyz/6R/+ITZs2LXe35HrZmLuafFbv6WakOhO2NKUD8n68aOELzAQwrlS6TD8sRAvXoxERERERERERERGRO9MdsQTZSy+9xNe+9jU+/elP8+Uvf5m1a9fyH//jf2RiYmK5uyY3wFpLxoSsyjhWZRw5E+LmWbLsRjjn8Fo7Fmw3qTQunV3Uc4qIiIiIiIiIiIjIre+OCGC+/e1v89RTT/HBD36QVatW8Ud/9Eckk0l+/OMfL3fXZIVzzkFHN15+/iXG0jt2U8/klrhXIiIiIiIiIiIiIrLS3fYBTBRFHDt2jF27ds1u8zyPXbt2cfjw4WXsmdwqaqkM2Q9/kkRnDzBTnMMkU2R2P4Tbthu7yLNuRESujqHqvAX/VKzH0JhmeoqIiIiIiIiILJfbvgbM5OQk1loaGxvnbG9sbKS3t3fe94RhSBheqOthjCGTycz+/eL/3+7upPFebqyVfAOJD/8WqalxXBhBNkc9m8day636k7mTfrcityPn4Ll9A5fZw/CZ+1bjL1mPRERERERERETkYrd9AHM9nnvuOb75zW/Ovl6/fj1f/vKXaWtrm93W2dm5HF1bNnfSeC871q7upevIErmTfrfvFRuf0LrL7pPwDL6LL7+PjSEKL7sPgBckr6l/IiIiIiIiIiIicuu67QOYYrGI53mMj4/P2T4+Pn7JrJjznn32WZ555pnZ1+dnCAwNDRHHMZ2dnfT398/UB7nNGWPumPHeSWOFW2u8XV1dN+W4oXVXmEEAz+7qwL/SJKEopPbdv7ni+ZIf/dQ19E5ERERERERERERuZbd9ABMEARs2bGD//v08+OCDAFhr2b9/Px/96EfnfU8ikSCRSMzbdv5BtXNuxT+0Xkx30njvpLHCnTdeERERERERERERkaVw2wcwAM888wz/9b/+VzZs2MCmTZt4/vnnqdVqPPHEE8vdNRFZRlkX8fHV6cvuU7R1bBxddh9zlQGW53lXPF/ORZSu8NGcu2UrD8li8v0rXU+GZL1C7F3+ernaJfQIEoSeKsqIiIiIiIiIiFytOyKAed/73sfk5CTf+MY3GB8fZ926dfzbf/tvF1yCTETuDF5U5+Q3v37Zfdp+//fY+//9Py+7z/2//z9c3Qmj6Irna/6D3+e5QyOX3edzW4tXdz65vV3F9dT6f/sDSKaucJyrW0Iv9dFPQVIBjIiIiIiIiIjI1bojAhiAj370owsuOXa1giCY9+93gjtpvHfSWOH2HO9CSwjC3PG6em22xtPlXHkfg3dVMwPMlY9luPKxzNX06dJ9FnrP4vwMFm+fm3G+y+27XH1aqmNd6R43Ye2qrl9jzGXvLRERERERERERmcs4FX8QERERERERERERERFZVN5yd+BWU6lU+Nf/+l9TqVSWuytL4k4a7500VtB47yQau8YuIiIiIiIiIiJLTwHMNXLOcfz4ce6UiUN30njvpLGCxnsn0dg1dhERERERERERWXoKYERERERERERERERERBaZAhgREREREREREREREZFFpgDmGiUSCT796U+TSCSWuytL4k4a7500VtB47yQau8YuIiIiIiIiIiJLzzgtDi8iIiIiIiIiIiIiIrKoNANGRERERERERERERERkkSmAERERERERERERERERWWQKYERERERERERERERERBaZAhgREREREREREREREZFFpgBGRERERERERERERERkkSmAERERERERERERERERWWTBcnfgVjI0NEQURXR1ddHX14dzbrm7dNMZY+6Y8d5JY4Vba7zd3d3X/J6hoSHCMJx9fSuNd7Fp7Br7Uo79Wu/X3t7eebff6r+7W73/oDGsFDdrDNfzb6uIiIiIiIhcG82AERERERERERERERERWWQKYERERERERERERERERBaZAhgREREREREREREREZFFpgBGRERERERERERERERkkQXL3QGRaxEEAcYY4jjGWrvc3RGRFcr3fTzP0+eEiIiIiIiIiIgsGwUwckuwns9gxbH/xATlesy65iwbWzLkvQjn3HJ3T0RWCs9nqApvD0wzVg5Z1ZRmT7JMwvOI43i5eyciIiIiIiIiIncQBTCy4jkv4LXeMq+dHJ3ddmaszN7TPr91dzeNfriMvRORFcPz2T9c58UjQ5yPZc+Olzk0XOepTQ10powCWxERERERERERWTKqASMr3kjNzQlfzivXY148NgKeckQRgYnQ8It3h3lvxFKPLT8+PERk/GXpl4iIiIiIiIiI3JkUwMiK5nke7w6XF2w/M1pmKjJL2CMRWYmMMfRO1okXmOEyWqozXtPsFxERERERERERWToKYGRFM8YQxgsX0XZAbPVQVUS47GcFQKTPChERERERERERWUIKYGRFi+OYNU2ZBdsbM0lyCc2AEbnTOefoLKQWbE8nfIopLUEmIiIiIiIiIiJLRwGMrHhd+QTt8zxYNcAjG5pJEi19p0RkxWlNG9a35OZte3BdMzkvXuIeiYiIiIiIiIjInUwBjKx4SRfyzPYO7lnVSDrh4xloL6T5xM4u1hc93AI1H0TkzuK5iKc2N/PAumayyQDPQHMuyYfv6mBHaxprL79EmYiIiIiIiIiIyGIKlrsDIlcjTZ33r85yX0+B2EHGd/guxumBqohcJOlCHu7OcHdHlsgZ0j6s7myir68PRbUiIiIiIiIiIrKUFMDILcNaSxo7s/aYRQ9TRWRecRyTAlIGjFONKBERERERERERWR5agkxERERERERERERERGSR3fIzYJ577jleeeUVzp49SzKZZMuWLXzuc5+ju7t7dp96vc7XvvY1XnrpJcIw5J577uHzn/88jY2Ny9dxERERkXl43qXfj1ENIxEREREREZFbzy0fwBw8eJCPfOQjbNy4kTiO+cu//Ev+w3/4D/z5n/856XQagK9+9avs3buXf/7P/znZbJavfOUr/Jf/8l/4n//n/3mZey8iIiJyged5vN5fZrRUn93WnEuypzOrEEZERERERETkFnPLL0H2pS99iSeeeILVq1ezbt06vvjFLzI8PMyxY8cAKJfL/OhHP+IP//AP2blzJxs2bOALX/gChw4d4vDhw8vcexEREZG5Rkt1+qdqs38uDmNERERERERE5NZxy8+Aea9yuQxAPp8H4NixY8RxzK5du2b36enpobW1lcOHD7Nly5ZLjhGGIWEYzr42xpDJZGb/fvH/b3d30njvpLHC7TPeq7lfL/77rT7e66Gxa+wiIiIiIiIiIrL0bqsAxlrLf/tv/42tW7eyZs0aAMbHxwmCgFwuN2ffhoYGxsfH5z3Oc889xze/+c3Z1+vXr+fLX/4ybW1ts9s6OzsXfwArQGQtYeRIBh6+d+Gh3e063vncSWOFW3+8V3O/XuxWH++NuJ3G7pyjGlp8D5KBf8X9b6exX6s7eewiIiIiIiIiIsvptgpgvvKVr3D69Gn+/b//9zd0nGeffZZnnnlm9vX5bw8PDQ0RxzGdnZ309/fjnLuh86wkzvj0lR1vnB1nshLRnEtyT0+RzqxHZ3vbbTfe+Rhjbsvf7UJupfF2dXUt2Ha5+zWKojnbb5XxLrbbaezGGCYinwMD05wcLZPwPe7uLrKuMUnCRfPuf7uM/Vot19gvd7+KiIiIiIiIiNxJbpsA5itf+Qp79+7lz/7sz2hpaZnd3tjYSBRFlEqlObNgJiYmaGxsnPdYiUSCRCIxb9v5h1jOudvmYZ7xfPYP1Xjx3SHOj2ikVOPo0BRP3dVJZ/vtNd4ruZPGCrf+eK/mfn3vtlt5vDfidhj7aOjz3Fu9VMN4dlv/RIX1rTme3txEYC8NYeD2GPv1upPHLiIiIiIiIiKynLzl7sCNcs7xla98hVdeeYX/8X/8H2lvb5/TvmHDBnzfZ9++fbPbent7GR4enrf+y51oMvJ46dgw7308Zx28+O4QQ1O1ZemXiMjFjB/w0omxOeHLeceHS/RNX7pdRERERERERERkudzyM2C+8pWv8POf/5x/9a/+FZlMZrauSzabJZlMks1mefLJJ/na175GPp8nm83yF3/xF2zZskUBzDkj5ZDIzv/t6GoYMzRdo2mJ+yQi8l7TkeH0aGnB9kOD06zf1DBn6TkREREREREREZHlcssHMN///vcB+NM//dM527/whS/wxBNPAPCHf/iHGGP4L//lvxBFEffccw+f//znl7inK9cC2cuF9kvmxoiILI/LraQVX+nDTEREREREREREZAnd8gHMN77xjSvuk0wm+fznP6/QZQEt2QDPzB/EJAOP1lwSVyrPbjtf5Fw1BURuTyv1Hs8Fju7GDGfHK/O2b2nPE8dahkxERERERERERFaGW74GjNy4hoTj3jXN87Y9uK6F9kIaAOcFjEYBB0Yi3h6LGY8C8Pyl7KqI3ETWCxgOffaPhLwzFjMZr7B7PI54ZH0zCd9c0tTZkKankFhxoZGIiIiIiIiIiNy5bvkZMLIIbMx93Vlackn2nh6nVAtpyCS5b3Uja4o+njFEJuAXJyc50DsxuyCZZ+CBdc3s6czgWX3rXORWVjcJfnJ0jHcHp2e3+Z7h0Y2t7GxNwgq5xztSlk/d08Ovz4zTN14l4Xts6yqwvS1L0oXL3T0REREREREREZFZCmAEAN9GbCoaNuxqpR5D0jN4Lpp96PruWJ39vRNz3mMdvHx8lI5CN6syy9FrEVkMnudxcKA8J3yBmZoqLx4Zoj3fQ3tymTr3Hs45WhIRH9nUSC0Gz4MkFmsVvsitx/MunYh8fglAEREREREREbn1KYCRWc45TByRArDgmHkQVKpHvHFmfMH3vXF2nDVbm7FxtEQ9FZHFVHU+b52dmLfNAQf6p+jeUCSKVs497uKIJIAFu9ydEbkOnufxen+Z0VJ9zvZ1zVmFMCIiIiIiIiK3CQUwsiBjDNYL6JuoMFaNifHwzblk5iKlakzsQI+LRG5NkYVKuPASY+PlmzO7xPg+E6EhjB2ZwCPvx1irOEXuHKOlOv1TtTnbmrOJZeqNiIiIiIiIiCw2BTAyL8/zGKgafnp0iGIuS6kec3qsQkcxTUOSOSFMeyGFb5y+hS5yi0p5joZMktFSbd727ob0ohe3L5PgZ0fGODE8jXWQCjzuXtXInq4sgV05M21ERERERERERESu16WLj4sAY5HPt/b1MThZZWCqxp5VjUSx5cxYmemLvgzve4a7exrwPY8gWDjP84MEVZOk7BI4P9DyKiKLxPd9qiQouQSxub57KyDmgbVN87YlfI+72nPE8dwZMt65ez6RSBAE13be0AT8/YFBjg3NhC8Atcjy6olR9vaW8Hz/mscgIiIiIiIiIiKy0mgGjFzC930O909Ti2bmtMTWMTJV4eM7OvnZ0WGGpmvkmtIUUwHv29TO0HSNF49Ok0v57Ows0JE1eHbmYa0XJBiq+/zi0CgHeidwODa15nn/+ia6sw6n5YZErlvFJNh7aop3+iepR5bmXIqH1jWxtuBj3MJLir2Xc471DQGPb2rjlZOjVM8tR9aYSfLEllYag5jZCTCez0jNMFKJGS5VOD1eIZPw2NGRY3UxSdJdebmywbJlaHr+2TZvnZlgR3uenHdp/40XULEGA2Q8LVe2EAXcIiIiIiIiIiIrgwIYuZQxnB6rztk0MF0nUY15dEMrycBne2eeQtLjuwf65hQQPjIwxQNrm3mgJ8doDY6P1Pm/Xj3FcCmkMZugmAr4xbERzoxX+OyebnoyZtGXNhK5E4QmwfMHhxiYvHCvjpRqfOdAPx/a1sHWRv+aAgrPRtzdlmBDSzeTtRjfGBpTHkmiC/eo57NvqMZwKeLV0+OcHC0DkAw8jo+UWdOQ5ON3tZFi4RDGGLNg+AJQjy2lMCaXmvue4brPa6fHOTtewTOGze15dncXyJmbU5/mVhR7AcMVR99klWTg0VNM0xorpBIRERERERERWS4KYORSzpFLXVgCqBLGnByrUq5HvHV2gqZsgvZcwE8Hppks1y95+6snR+luyvGDQ4MEvk/f5MzD1qGpGpPVkJ5ihtPjFV46McZv72jGxKr3IHKt+kvRnPDlPAf86vgoa3d3krzGykzWWrJYsufDDxdfXO6JkZrh9VPj5HLp2fAFoB5Z+idrJIzjyGiVu1sTlw1/ssmFlxgzzCx7xkV9H677/M2bvYQXhQlvnhnn5EiZZ+/uIHOZwOdOUTcJXjg8yvGR0uw2z8BTNdhc8EGfsyIiIiIiIiIiS041YOQScRyzq6sIzHzzvH9yJnw5b1d3I7XI8fKxEWrxPEvdGMOvT0/QmElyYqQ8p6kWWmqxxVo4NVahEmmpHJFr5Xkep8crC7ZPVUNK4eLOfPA8j2MjZVqLad7um5z3nHULB3oniS7zT4tzju5CkoQ//73f2ZChMXnhtfF9Xjk1Nid8OW+8Uuf4WPWOX3LL933e6i/NCV8ArINfHB1hsKJZhiIiIiIiIiIiy0EBjMyrM2d4YG0zkTNMVi98u3xTW472XIJqGGOByVo885X1i0TOMF6pE9uZmTTvfTQ6WQlJJTw8Y7jDn5uKXLeUv/DHtwH8Rb65jDGU6xEGQ32eMMQB3rlz2is87y8Elqfv6iDw5vaxkE7w5JYWjL0Q+JZjw9nLhE2HBqbx/IVn1NwJyrHhQO+lodh5B/unCAJNeBURERERERERWWp6IiPz8mzM/d0ZVjXneenEOJV6nZ6GDNV6xDt942zsKNKSSxLGFoOPu2ihonRguHd1E31TVXZkknQVM4xX6rx8YpRaZDFm5gHx9q4iOW9mNoyIXD1rLeuas7xyYpT5so7upgzFJHBpHfsbOueqpgyvnRxjfUuOkYtqP3UWU+zsbiIVGIrpgKnI0JgI5gQpF3PWsr7o8dn7ejg9XmOqFtKRT9NVSJAxEReXhTKY2WBnPr6nFDd2hkq48BJjE9Xojp8lJCIiIiIiIiKyHBTAyIKMjWlOeSR9j3Icc6hvbPab7WfHSjy6sZW9p8YuFOhmphj3nrUt/OTwEG8PTBIEPrXI4nuGj+3o5Pn9/TRmknQWkzy6tgFrFy7GLSILa046Hlrfwq+Oj8zZnk36PL6xFeLFrYvinKOnkORX1rG5Nc/B/knK9Zi1zVm6GrL84NAAgYENLTn2nRphe1eRx9Y24Lv5++GspehZdrYEGHO+Zkw4J3wByPqWjW25BWd47OwqYuNFTJpuQSnP0ZhNMVqa//N0VUOa+A7/GYmIiIiIiIiILActQSaXlfUsd3UVmKqGc5YVqtRj6rWQz963ivZCGt8YMkmf92/uYH/vBLGzJH2PMLKkA59swuedgWk+fW8Pv727mz96aDU5FL6IXC/jYvZ0pvn07h62dxVZ05zl/Zta+Z3d3TQHN6fgepqQT+7qJIojfmtXN9s7C+zoauAXx4ZpSAWsb8mRNBYHHOib5O3hKp53+X9mnHPnwpf52TjmvlUNFNKJS9rWtuRYXQzmhMB3ooCYB9c1zduW9D22tOUu+zMWEREREREREZGbQzNg5LKstdy3uoWpUpnXT41Ri2Ye4nUU0zy2oYmWpGXtzlaq8Uz9h7GqpVSpkQDWt2SZqEZMVCNwjpRveGB1I92piDhW+CJyo4yNaU9B1/oCxhistVh76SySxZQ3IR9cV2QygvtXF/jx0TG2d+QJjAM39yH/m2fH2draSYIbe/hf8CJ+++5OjoxUeHdomsAz7OwusqaYJLHADJs7iXOO9cWAJza38fLJUSr1mdkuLfkUH9/VRSNlNAFGRERERERERGTpKYCRK8qnAh7oTHNXaw/T9ZiE79GQBM9GWAseluy58gLl8MKT3wBLS8ajJZPGGIezjnq9ThysrG+rG2OIjU8lNgxMVjF+gIv0UFduHUu9vJSzEQVvJnQtV+oEWOYrRlOux4TWkbjB8iPOObImZE97kj0drRgzMzPGXSZ88TyPivWJLIxM1/B9nyi6OTODVgJjI3a2JtjQ3M1kbWbZx6aUYVVHgb6+6eXunoiIiIiIiIjIHUkBjFwVay1ZE5NNAVgW+kJ7IfmeS8rN7O8cGCCX9IGV8xDUGI8zZfjliWGGJqvkczk6ch6PrG2k6Ed3/NJGIpdjnKW9kKR/sjJvezGTIOWbBT8vrtXMMlpXPlhkAt4erPH6mUGmaxEtDXk2Nae4uyN7W8+YsdaSxpJOzbw27gaTLxERERERERERuSGqASOLqiVj6Cim521b05ylKbnEHbqC3gr83b5eBierOCB2jncHp3jurT5KVvmkyOXEccyOzgKBN/+D/gfWNBG4pQ1cje/z6tkSLx4dYro2c+5KaHn5+AgvnpjAebqvRURERERERERkaSiAkUXl24iP3tVGT2OG849kDbCuNcdTm1sxduXMfnFewK9OjGHnmeQyXYs4Nlq5YgFxkTtdc9LysR2d5FMXgo1k4PHoxlbWNfhLPotsMvTYd3Z83rZD/ZOM15e0OyIiIiIiIiIicgfTV4Fl0eVMyG9ua2G8DuXQkk14NKWAeGU9+azEhqGp6oLt7w6X2d2RPrfskYjMx1nL2rzHZ3d3MVazWOdoSPnk/Rhrl77y+0Q1IpovVWVmRcTRSkhTQUtziYiIiIiIiIjIzacARm4KYyOaAmgKACzc4HPY8zNRFjMM8QwEvke0wEPidEKzX0SuhrWWJJaO1OwWliu3XGg5tPMSvse54lTXxRiDMQbnnGpEiYiIiIiIiIjIZekJs6xokUlwtuLxizNlXu2rMhIGOM9flGNnfcvm9vyFDZ6hGsXEeGAMOzuLRNHKWTJNZKXxPI/IJKi6BM4PMGb5Z5Y0Zfw5y6FdLBV4tGau7/PDeB6TccBbwyE/P1Pm3UlLlcSKGLOIiIiIiIiIiKxMmgEjK1bNJPjeoRHOjJVnt71yYpT71jZzf3cGb56ZK8YYrOcTW0h6DhsvPPXGxjH39RTpnajSOxUyNFGjGteJo4jHN7XRnEtiqOlb7iLziLwE7wxVeevsMJUwojGb5IE1TaxtSBDGDt8Dz8ZLfv+kiXhqazvPH+gjjC+c2/cMH9zaTs6LudYuGc/j6KTlh2/3zVnerJBO8Ju7OmjwFNSKiIiIiIiIiMilFMDIiuT7Pm/1luaELzCzcNBrJ0dZ1dRDazog6YE595A3NAneHa2xr3eUMLb0NGS4u6dIS2Lhh8BZE/KR7V386uQYySGPTCrBuqY05Vqdv37jLJ+6u5OcCZdgxCK3DusF/Oz4BO/0T85uG5iq8jdv9XPf2mZGp8rUIst9a5pY3ZDGuJiUZy8biC4W5xyrsvC7967i6HCJgak6q1qLrM630JSIcdexNtpk5PPCO32X1JaZqob86PAIv7W9BWMVwoiIiIiIiIiIyFwKYGRFKsceB/smL9nujKEUOr53aJjOXIJqGHPv6kZ6ikl+eHiE48Ol2X0nKiFHhqb5rbu7aEvO/+DX8332HhvlzMg0HbkkyVSKw31jnH/Oeni4zH0dqUWtPbMYfN8nUZ7GVMsQJAjzDUSaqSNLZKzGnPAFoBobjo+W6Z+q8ZFt7Rjg12em+Jt9A7TnZoLN3T1FmhJ2Ue6nBBCUJiCKcJkc9XR29rjOORq8kPs70/g9Odra2ujr68PZa79HjDH0TtbmzKa5WP9EhfH6+XpXIiIiIiIiIiIiF+iRkaxIMVAL3xOaGBirxvRNVPGMoTnl0TdR4e8nKty9poWp6qXfQA9jy8+PjS74DfVK7HFqtEQ9sgxOVcnGHhc/o313qMS9nRlg5QQwSRth3n6dyr69uFoVPI/kqnVkH3w/5Uz+ygcQuQHGGPomq+/dSP9UDWsdU7WItnyGb+3v5ex4BQDnspSqdd4dmuZT93TTFFz//WSMITM1Tu3ln1DqOwvO4WVzpO95gHjjNkJzobSZtfaGl0AzxlCuLzy7xTHzOaN/TUVERERERERE5L28K+8isvTSnqMln5qzLXQeA1M1AHoaM7OBizGGH74zSEdDdt5j9U9UmI7mL5RtjMO7TBFtzxhWUoltz/Mw7+yj8tpLM+ELgLXUTx2j8sO/Ix3Vl7eDckcI/Ln/dITOUKrN3I+ZhM9YNZwNXwDGKyHGM9QiyyunxjHe9acV6WqZ8vf/lrD3DOeLudhyifIvf4J//DCet7j/rFlraS+kF2xPBh65pL+o5xQRERERERERkduDAhhZkXwX8+DapjnhRy2yWOvIJn16GtJMVi/UZomsoxrZaw5L0saypaOwYPvOrgLO3vy6FVcrWSlR3b933rZ4fBQz1LfEPZI7jXOOzkISb4GbbVtnkXcGphZ8/+nRMuXrvKWMMbjeU9jS9Lzt1TdfIVGvztt2I9qzHm3vCYTPu7unkcINzOgREREREREREZHblwIYuS7mMrNGFoNzjtV5w4e3d1JMJ2bOCaxtyvIbO7s4NjgxZ99iOsAAmaTP2pY861sLtBdSGKCzIUM+mH8ZImstd3fmacwkL2nracywril1w0sYLSZTKV2Y+TKPeHBg0WcAyC3KCwhNgPEXf22sxoTl4fWts68TxpFLBSR9j3tXN1B9z5JdjZnEhfor5tyf6+B5HnH/mQXb7fQUXq0yZ9tifFYlXMQntrezsT2Pf+546YTPw+tbuLcri41XTkgrIiIiIiIiIiIrx5KvWh+GIcePH2diYoKtW7dSLBaXugtynYwxVFzAYCliuhbRkEnQnvVJuPDKb74e1rK5wWP17k6mQ4fFZ++pUQ71jV1SELsh5bG5vUA1srzRO0EtsqxuynL3mhbuasvMW//lvKwJefbuDo6NVjkxEREmHTs6i6xtSJK8WWO7XkECjJldeum9TC63ogIjWXrOCzgzHbP39AiT1YiGTMC9q5tojhYxJLCWezpSdBR6eKt3gqlqxNauRtKBx5G+cTa25WdnweRTAdnA43wdpXUtOXI+XM/EMuccJneZOkd+AH6AMYYaAYOlmIlqyLCdIG8CUia67vsja0I+urGRibWNhLEjm/DIeTH2Mp8tIiIiIiIiIiJyZ1vSAOb555/nr/7qryiXywD8u3/379i5cyeTk5P8s3/2z/i93/s9nnzyyaXsklwlYwwDVcPzB/ooXfTt9qZskmd2dFDwbk5QYa0liaU5AM+zrGnOcHTo0uWNPnxXJwf7J9jXO8loOcQ6x4nRMrUwZkvLwvUbzssQcndbkg9u62F0ZIQ4jnArLXwBonwDie7VhGdPXdro+/hdqxTA3MGM5/PmYJVfHB2e3TZVDTkzVqHqfLYUPNwizdYwNqYrDas2N2Ax+AaGqjMheyLw2dpRYKoaUkwFeOfCl0zS54HVDdj4+kILay3B2k3w1q/nDSFT6zcR5oqM1gzfPtDP1LllCrPZEoENeWZnJ03B9YcwzkYUPc7NHY2xWnlMREREREREREQuY8nWKvrxj3/MV7/6VXbv3s2f/MmfzGkrFovs2LGDl156aam6I9eoYgOePzAwJ3wBGCvX+cHhIewNFNW+WtZa7mpO8Fv39LC+NUdTNsna5izP3t1NIjCcHJqiKWXY0JxhU0uWVcUknov5+bFR3FX0z1pL4HvnwpeVGWKEQOrhJ/ALjXMbfJ/cYx+imm9Yjm7JCjEZGV45MXJpg4GXT4wybRf/Po3jGBdHRFFEUxDx5PoCD/Vk+ccPr+LZXZ10FpI0ZZPcu6aJT9/TTWNwYwFQrbGF7EMfADP3n6+guZVgz8NUrOE7bw/Ohi/nTVZDvnNwgPrST/wUEREREREREZE71JI9ifr2t7/N/fffzz/9p/+UqalLZzBs2LCB73znO0vVHbkMYwx1EzBWtcTWwWSVoUp8SfhyXv9ElbGaoyWxBJ079637ni1N1B0kDHg4Xjg+c01FeExVI6ZrMQnf0JBJ0D9ZZToyFFZwaRTf80hWpiGKcMkU9VQGu8DX6yu5IqlPfBoz0Es81I/J5fC711ItNGBXZm4kS2SsEl+yPF+Mx3Td0jcwxYHWLD3FBB0ZD9/dnKWzbBwTAIGL2NHss62lFecgMBZrw4VWz7tqsQOzZScN3atxIwMQW2hoIio2UgmSjFQs4+X6vO8dK9cZrcZ0pG6sD+9lPJ/JyDBVswS+oSnlkWTlBrkiIiIiIiIiIrI0liyA6e/v52Mf+9iC7fl8nunp6aXqjszD8zyc59NXdvzo0MDsQ8yWhklWNaaxxuAt8ECxGjlYigDmHBtHBIAD8H0MUHMeJ0bKRBcFFyOlOl3F9EzdlBUqU68SvfEy5WOHcGGIl82R3nUfdtN26p5/yf7OOaqJFKxaj7dmI865mQe9etYr7xHhcXKsQjWMCYKA8UrIq8eH2N5V5P3rGvDtzV1mzzmHcREGFi0c9IFE30mmX30JOzEKxiPoXk3q/kcxxRTV+DLrghlDJQbPD657GbT3ik3Ar3vLvHnmQm2qxmySp7a20ZV2CwapIiIiIiIiIiJy+1uyOQHZbJbJyckF28+cOUNjY+NSdUfeo2YSvDUc8kpvhf/9Z8c5PFwhxAMDldBSC2PGqzHMk2N4BnLJ5ZteEscxm9oL9E1W54Qv56UTPvN2fAVI2Zj6T79L7dB+XDjzMNyWS5Rf/hnm7TfwvMv/XK21+pa9zGrK+CT8c9e6geFSnWo4s+RXOvBInms72DdJ7/StVzzeGENy4CylH/498fjITPhoY8IzJyh/7znS5WnyyUu/V2CdoxwbTk3U6J+s8+3DY/RWPZgn4LwWnudxcKjGaydH58w8Gi/X+fa+PiaiGzu+iIiIiIiIiIjc2pbsqfmePXt44YUXKJVKl7SdPn2aF154gfvuu2+puiMXqZHg2weH+PWpMU6OVpiohAxN1zg2XKZuZy6RKIoJPI/YXXrJbGjL05S8+vMZY4i9BMN1n7MVj4k4wPg3NhmrmA5Y3ZC5ZHsq8HhwbRPHRqavGGYsB390iLD/7Lxt1f2vkyprVphcvWJgeWh9CwCxM0xUZkI9A7x/Uyu9Yxeup329kwTBrVUPJbCW2hsvYxIJok27GNrzFL33PMXU7seh0IA9+S4tGY+epos+C4xhcKrG8ZES7fkUw9NVTgyX+O9v9nJguI65gc+FivXYe3ps3rZaZDk+VlmRnzsiIiIiIiIiIrI0luzp22c/+1m+9KUv8S/+xb+YDVp+8pOf8KMf/YiXX36ZpqYmPv3pTy9Vd+QcYwwnxmoMTFZpL6QZmKrNtkXWMlyq05BLc3x4isc2NNM/VWNovIRjZubLhrY8H1jfhIuvbikjYwyjoc8PDg0yPD1zLs/ApvYCj69vJOmub0mkMIrY1pFnXWuW/b2TVCPL6sYMd3XkOTY4web2wnUd92YyxhAPDyzY7uo1KE1BOruEvZJbmbOWXW0pmrPdvHZ6gpFySGM2yT3dDVQiGCtfuL9qkb3lVq0LalXC0jTDux7n+++OMn50Jrz0fY8da7fwqHUksXx4Sys/eneUUyMl6s4wNF1la0eB3T0NHDw7Csys2PfLYyOsa+ohZ65vmbC6NQvWxgLon6zidaS1DJmIiIiIiIiIyB1qyQKY5uZm/tf/9X/lL//yL3nppZcAePHFF0mn0zz66KP83u/9HsVi8ZqPe/DgQb71rW9x/PhxxsbG+Jf/8l/y4IMPzrb/1//6X/npT3865z333HMPX/rSl25sQLcJ4/sc7B8HoBbFNGbmFnKZqobUIou1jncHJvgH962mVG+iFlqySY/GJFcdvgBUXcC3D/QzVb3wHuvg8MAUgefx5Po8No6veRy5wNA7XiKyjl1deXzPMF0Jeev0zMPWVY0LF7VfTiaVvnx7sISFdeS2YGzMqgys3tFKZzHFwESVw/3jpNJzZ4htaM3hVuA9cTnOM5S23se3DgxQrdVnt8ex5a1jA2R2b+Z9nkeGOp/Y2sRYrYnhqmWoFDE8Mc2BM6NzQqd6bBmtROSuM+MMvJlZdrVo/p9jcya5Ij93RERERERERERkaSxJABOGIW+++SZtbW388R//MX/8x3/M5OQk1lqKxeINLdFSq9VYt24dTz75JP/5P//neffZvXs3X/jCF2Zf32rL7txchvMlRCYqITtXFfBPGuJzFbMv/u+2ziIZ6qQCe+7KsbhrzEr6S+Gc8OVihwcmuW9VgcJ1XA4Zz/LQuhZeODTAqZG5y9y1F1J05AK4ztk1N4tzDtPeBX4A8xQED1raiIqNS98xuS24sMa6pgxvnBrFvmeqSy4ZsKklg7Ur6564kjCT42ymlWqtf972AxOWHTVHxgBxRFMAU57h8OA05XJ53vfcSAmlnBezrauBN+ZZhsw3ho1tWay99WrtiIiIiIiIiIjI4liSxemDIODP//zPOXTo0Oy2YrFIY2PjDa+Pv2fPHj772c/OmfUy3/kbGxtn/+Tz+Rs65+3ExRF3dV74eZwdnebjOzpJBTO/l0I6QTLw2NiWZ093/oa+ze15HqOl+oLtkXVUwus7vrWWLc0BH9neSWN2piBNwvfY2d3AJ7Z3XPfSZjdbLV8k9+iT8J77wM9kyb7vSUwc46uGhFynzrTjN+/upqM4M9NqJhTI81v3dJL3bs1gYMjPzTtzzG9qoRIkqcZzP0Oa0wGBZ+Y9VuAZmjP+dffFWsv9PXnWt+bmbE/4Hk9v66ApWPzZLwkgFdZJ4jBm/nGJiIiIiIiIiMjKsCRTQYwxdHV1MTU1tRSnu8TBgwf5/Oc/Ty6XY+fOnXz2s5+lUFi4JkgYhoThhQf2xhgymczs3y/+/+1gQ1Oat3JJRkt1xsp1rHV8clcX9djRUUyzuaNIJq5gbATzjdsLqMQzhb6zvl0wpHHOUcwkF+yHZyCd8DHm+r6Sbpxlc4PH2ns6qMUzx8sHDhuHzPTuCu9fht+tA+rrt5JvbiU+eRQ7NUGytQMvm6X0q59iy9MEHT1kd95LtakVdyNf13+P2+Vavpr79eK/3+rjvTaOVVnDp3a2Y9I5KqUSOd/hzs3KuNV+Fs45ivkM/qr1UCnhSpPg+XiFIjaVwfc9Ur6HMRZrAqp2Zomwxza18PybJd5b9ObBdS0UEw5nr//nkCLiI1uaGVvTxGCpTtr3aM8nKAR2Zom3RfoZ+ziSA2epvfVrwolRvEyO9K57iVetJ/TmD5HuzGteRERERERERGTlWLK1uJ599lm++tWv8sgjj9Dd3b1Up2X37t089NBDtLe309/fz1/+5V/yn/7Tf+I//sf/uODsm+eee45vfvObs6/Xr1/Pl7/8Zdra2ma3dXZ23vS+L6XfKxR46+wEhwamsA4y6SSPrm5iTdP54giXzhqyznF6rMzeU2O8O1wi8Ayb2go8sLaJzuL8tU28fJVXzkzPWzNhXUuWDZ3NJIPr/0b6YliW321nJ2zdQTw9Sen7f0f41glmo6r+09jhPpo/8izJDVtuwqlv7Wv5au7Xi93q470hDZkr77PCRekKb/aXifJ5aOuY07ajq8iajmYOD07z8olRRqbrpAKPrR0FPvvgBl45Oc5UNSSfTnD/mka2tudJJxbnn8FVi3KU+TnnqO79FZWXfkSCmVkwVKZxr/yMdGmSlvc/jUksHG7f0de8iIiIiIiIiMgyWrIA5vDhwxQKBf7Fv/gXbN++nba2NpLJuQ+MjDH8w3/4Dxf1vI8++ujs39esWcPatWv5J//kn3DgwAF27do173ueffZZnnnmmTn9AhgaGiKOYzo7O+nv71/U2Qgrwd1NHnc1NmAdpH2HrU7Q3z95yXiN5zFcM7zeV2Jf7wStuRRrmzKcHJ7k5XenOdw3wrM7O8iYS5c4MsbwwQ0NfPdgP+X6hQIyXQ0ZHurOMjI0uGTjvZjnecTGo6mpmamxEeL4GovbLJL0meOUjhycty38+Y/wMwUWazE1Y8wtcy13dXUt2Ha5+zWKojnbb5XxLralGLvxfIZrcHBgmtFSnY5imq1tOZoT8XWf0xiD83ycA5+Z2XWBMTy+rsgPDw1SDS/cp+tactzTnuTVY4N890DfhckuBkr1mBOD8PHtbdjYkvKBuMLYcOWGx70U0tUy5Rd/iKtVL2krv/YrolXrqRSaLmlbrmv+cveriIiIiIiIiMidZMkCmO9973uzf9+/f/+C+y12APNeHR0dFAoF+vv7FwxgEokEiURi3rbzD7Gcc7fdQ9w4jvGJ8bm0Jvz58RrP49BYxAuHBjk2VqNUizjCNK+dMvzGzi6ikWnGSnVOjte4q8m/5GfknKMrbfjsnm6GyhHlekxTJkFL2uC7+g0VxL5eZZfg0GCZI4PTZDJTrGuYKVCeWbSo4+oEQUB47NCC7WH/GZLlaeqZ3IL7XI9b/Vq+mvv1vdtu5fHeiJs19pnPhZAX3hnAnjv8mbEyb54e4+M7OlmTN9dcP6pGgqOjVQ70jWKtY2Nrjrs6chS8iLV5Zj9DalFMczZBc8oQO8tLx4bnrjR2UX8GpkJ6MhZ3q5W/mRyfN3wBwFns8CAu37jg2+/ka365eJ6HMYYwDPE8D+fcDdVQExEREREREZFb05IFMF//+teX6lSXNTIywvT0NE1Nl35bWK5sOvb56ZF+6hbK9QtPMcPY8cLhIZ7c3Mrh/gkOD02zo7V5zgyE84wxWAvZhEdj2p+pwfDexGeJlFyCv93Xz0RlJmzJWp/TQ+Mc6EvyyZ0dSx7CmAWWxZtpNFxSxEJkBZiKfX5yuB/rwBrD+Ykp1hh+dHiIz+7uIsnVP3yumQTPvz1E38SF0GGkVONA/ySfuruLgheSNSFrcwAeEIOFiSiYvZfnc3KszOpc9tZ7EH6lGi6q8bKieJ7H6/1lRksh2WyNcrlCcy7Bns5b8NoTERERERERkRuyZAHMzVKtVunv7599PTg4yIkTJ8jn8+Tzef7qr/6Khx56iMbGRgYGBvg//o//g87OTu65555l7PWta6wan5ulYjAY3EWBwEQlnK2rk/DnDxIiL8EbfSXePDNOLbJ4Bta35nn/+iayZmnCDmMMeD7OeBw8W5r3ge1oqc7h4Qr3dqTwoxB/egKsxeUK1JPpm/IQLYoiMhu3Ujt2eN72RPcaomyBZZkmJHIZw6WQ0FpKEfRNVmZrPKUCj65imrGapSN1dccyxnByvDYnfDmvVIvYe2aCD64vYOdZJtAzcLmYMnG5gPMyEjiC6QmILXG2QJjJQ1yfd1bJ+SXwFnPGiWtoxMtksZXypY2ej9fSvmjnksUxWqrTP1WnQIKpqRozV2X2Sm8TERERERERkdvMLR/AHD16lD/7sz+bff21r30NgA984AP80R/9EadOneKnP/0ppVKJ5uZm7r77bj7zmc8suGSRzC80AUOVmJPjNbqa8hTSAZF1HB0uzdkvPrf+0PaOwiWzXzzf57Uz0+w9NTa7zTo4OjTNVDXkkzvaSCzC2kDGmAUffsYm4MRkyJtnx2jNZ3j19DgGQ9p3lzy1fWdgigdydaKffofq0EzI5+UKpO97hGjtZm7GnB3b3kVyzQbqp47NHVMyReq+RygrfJEVKIwd1dhwcqw0Jx+sRZaTY2WmI646gPF8nwN94wu2Hxsu8dCaIul52opJ6GhI0z9PeAOwviWLtVd/5xpjyEyMUPvVTxntG2CkVCNMZijc/wjRph20FFMkbHi+44yFht6JGtY6uhrSNKccnr3xelL1VJbMQ49T+un3wc0NfzO7H6RWaNDkuBXOMzPXk3dRCGg0c0lERERERETktrdkAcxnPvOZq9rvWpcq27FjB9/4xjcWbP/Sl750TceTSw1OVfm7g8P0TVSoWcO7wyWSvsfT2zupRZYz4zOFrJO+R9I3bGrP0533eW+hhanIY9/ZiQXOUWOwbOnJXF8fPc+jFPv0T4dM10Oas0nasj5Jd2F2i/UCfn5ykgO9kwBkkwkmKiGj5Tprm7Lk3pPJ+WGdyhtvYoYuzLCypSnKP/sBuaeSxD3rFr2uQs1LkHr0Q2TXHqf+9lu4KCTRs4Zg606qhSbQ8jWyArXmk4yU5q/hlPA9SvUIr5jAXmGpQWMMZRcwFTpGqpZMwiPte3gXLV82c4r5H1ybOOLxjS18a18/1XBu8HHfmiZaUnANK6GRLk9T/t7fMl2qcnK0jHUOKnWmX/guTXj8onk971/XgMHyel+FV0+OztbAAbirs8jj6xoI3I3N7rPWUl+zifwnCtQPvEE8OoyXz5PcvoeocxWxwpcVrzGT4PW+EiOl+uy2dc1ZhTAiIiIiIiIit7klC2B++7d/+5IHDdZahoaGePXVV+nu7ubee+9dqu7IVfI8n58fG6FvYiZkSfnQlE0yVq7zvQN9PLt7FS++O8RkNeL9G1vY0palLWMI5vmW+XQ9JoznPv30DLQX0yR8n3I9xmS9aw41PM/jbNnwnYO9cx66NmWTPLOzg8K5pc1Gqm42fAEYL9XY2Jpn5OQofZNVNrRctDyMgY05CE6c4dLvrztqb7xMoms1oecTG5+aNSSNIyBesP9XuzRRLUhg1m8lWL8VY2MiP6Bu7YoPX4znMRn5DJVCYutozSVoTDrMIswAkJWtkPTY0p7nlZNjl7Q9samVSi0iMmkCz85dvs8LGKvDUKlOwvdIJgJePzVIQzpB/+TMLJZM0mdNY4bgXHKypjlL1ne897I6f3+1pxyf3t3F4aEyp0YrZFM+D23spNFUMdcw+8XzPOzpY8S1Gv2TtZnw5SLV118meLSToXKe2MHLJ0YvOcY7/ZN0FVNsbw4WvO9936ccGxyGjOdwC/Qxdo5yUzvB4x8lEUXYwKdilbzcSkbLIf1TtdnXzVnNxBURERERERG53S1ZAPO7v/u7C7aNjY3xpS99ia6urqXqjlylqdjw7uD0hQ3O0VlIkgo8Rkp1Bqeq7OzMsa2zyF0taYhqC37DPOl7c+ozdDVmacimONg/yWS1gvF9WnINtCRj3DWEDaXYvyR8ARgr13nh8DCf3NaCj+XUWGVO+2i5zt2rmzk0MMVENSS86GvkDZkEd3kTxFPzz9iJxkfxY8vRaY/XTg0xWQ3JJQP2rGpkc3MS/6LZPz6Qmp7ADvbiogi/vYuwoZnQLFyPwjlHCGC8FR+8AOD57B+u84ujfUTnHgp7BnZ0N/C+1YU5Pw+5/fjOsrU9Ty4V8PrpcSarIe35NM/s6ma4VOVXJ8c5NVZhW0eOTc1p0oREXoKXTk5yoHcCB9Sdx+mxMh/Y3EZ3MU1nIUX/VI1KPaZvqsbqYpJ04HH/6kZsfGFGScI5EpOjxEMDGOPhtXfQVGjkwa40D/VkMUB7e5G+vtI1rdLleR5x72lCC5Xw0uu3MjpCsx8xXI44NTZPbZZz3jgzwZbmdvz3LFpojGHaJnjj1CRHBqewDnoaMzywppGWxMJBbmQteB4ofBERERERERERWfFWRA2YpqYmnn76af76r/+axx57bLm7IxcJY2YfqJ/nOUtLxqMxnaUlm+DJDQ34NsRGtQWOMqMxBZ0NGfomKrQX0kQY/vqNszPHNIZswuPsyBQf39HJmtyFOi4JLImJMezoCCaRgJY2atnC7DfSB0rhJeHLeX3jFcbq0Jq8tERCPhVQrE3xhT3NHBys0F+JyaYC7mpt4p7uIsVf7mOhEfmtnbw+GvOz48Oz2+pRnR8dHmS4p4HH1uYhjglwBIf2Mf3aL+YEKcn1m0k9/EFqwe3xDeiBCvzsyNCcn7F1sO/sBK255GVnAMitKWEgMTGKq5Qx6SybCg0cHaz//9n7zyDLrvu++/2uHU+OndP05BwxAAaBAAMIAiRFEhAp8pHvc6XHsly3SlY9cpXtF6pSya6Sy1bZ5bKfunZd26VrW8+1FSiRYgQJIhJEGKTJOfV0jifHHda6L86gZ3qmBxgEDgLX581M733OPuucPnt31frt//rz6Q1d2KZBPu7yo5MzTBSbDGWiLFRCFioNjscdvrazj4tLTY5PXw04a15AK5A8eWqOb+4b5MENXUxV2pyaraCUYlNfmjsHE2SsYHmpM1cGGOdOospFqFXAcZCLs1iZHHLTDnxpvOclnpRSGInETfebrounBLYQ1Ns3DxhbfogvwbxuGA1l8XfHZig3r4ZJFxZqTBQaPL5ngJylQ0tN0zRN0zRN0zRN07SPu49EAAPgui7z8/Mf9jC060QsiNkmN9zfrcBEMpRyMELvhuV5ViPCgM9uzPP943P0pGP8zXL4AkOZKI6hCCU8f26R39jTh4OPG/iErz5P7cJZlrs/2Daxez4DQ2tRMkQoe0VlzXXDpB1IpCUZyUZ5dayzvStmcW84R+2nz1Os19nS18uDmzaS6N6Mkc/Tlm3sjVtonzux6ntp7ryHgxOVVfcdny6zoy9JxgJnaY7aq7+4YXTepXNE8z0Y2/etXJLpY8g0TY7OVG5aXXCzCgDt4yvqNfFffIba1GU6aYigu3+Ih3c+wHcuV4g4JksNj4lik0zMIemay83jC3WP43MNposNDOgsCyaM5T4mCjg5WycXEchQcu9oFiEEdw2nSImrfWaEEDgLMzReegbv4tnlsYlojPinH8EsLODne9/zewzDEHf9FuzTJ4na1g1VMIlN23i5ZfFQ0map5rJQba16nGzcIWLBtWsZGobBhYXWivDlLV4oeW28xCMbM6h36JmjaZqmaZqmaZqmaZqmfbTdfA2k22h8fJwnnniCgYGBD3sov7IM00QZFoa5MpOLGZI9w5lVnxNzTIbT7ruqbMhYIb+xp4+YY5KN2fSnI6zvipN0WM4oKi2fUltiGAacOYp34QzXBhhGq0nze/8TcexVWn/3Pxl44ykezQckHPOG1zMNQdzufM27IoItfSkEcJfboPTsT/DrdQSCjFfFOXMI85nvYU6PI4TAy/cS3XeA6xt+2/1DlFM9tIPVq26kgoW6j2VZ+KePsXo0BO3Tx7C9t68a+jhQCMqNmzcZb3gBntSNpj8pbBTeC0/hTY7xVhoihCCYnaL38LP81p4e7lnXzVy1zbquOP1JG0OtDBlPzVWJGyFq+jLB2HnCy+fJ1wv0RDrnarnl4dom5abPxYUqk4Ua1nXnkYui9crzK8IXANVsUH/qh4j5aSzj/f2J87I9xPffQ186gnHNdSDWP0B5wx5SUZuMDTv6kljGjd9xAdw5koXrgxTD4Oy1SzteZ7LYoBnoc0bTNE3TNE3TNE3TNO3j7rZVwPze7/3eqkvB1Ot1Go0GruvyD//hP7xdw9GuMAyDRc/g+ESVmUqLmGOyezDNUMLEkAFSSvaP5KnWGhyaLOIFnYnUnmSEz27qIm5cXQ7oViiliIiAqAm9cetKNqFuyCiUUjjtJq3Tx1ZsN8OQcHIM1W7jXzyHcCMwcYHg5Fke+PzX+EnRWtEaYVNvkrQDKgRDBjwwmmZzdxzz5z+mJSAaselKuERNtRwktY++htU3hI+A7XeQGF7XeU3fw+wfRnZ1I70bw55rWaYApZDV1atkAFSriQgD+JgvQyZQ9CRd5m9SAZCM2LimumlvIO3jxS4XqE1PAKCEoBHAUr2NH0gilXFG7lhgY98wb0SMTvCwyvXB8No40kPWOyGECkNUYY6IWSafH6Q74dL0rgacuwYzJMxwRTskq1ameeLwqmNUvkc4M4mxfR+rx6S3JgDUlt30DK4hMX6ZYrlGK9fHfLwLN5HkoZyLqXzyrsEXt/fx/PnF5aqWuGNxz7o8g3Fxw3dfKDCvX5PsGoYhOg/SNE3TNE3TNE3TNE3TPtZuWwCzbdu2VQOYRCJBb28v9913H4m3WW9f++AJIZhswA+PTS33eVkCJgoN9g1nuXsohlCShGtx10CErT2DVL0Q2zTIOGCqmzeKfjtKKfqSLuLG3AXoVNakXRPRCpCN6xY/q1dR7U7ViCwXMQZGMCkynDApnX6DoY2fYrzsYRqCzb1J7l2TRl3TsNtSPmvjCj+s0pWPYQg6SyNdM5CwXMLyPbBdAiBIZTF25AHwrswA5yImMcei4d24RJBlCLpjFgqF2TuAvzC76udgpjJIx73lz+2jKgxDtvclOTVTIVzl+3Dnmmznu/IhjE374KlGA1AgBIVmyGzlavDWCkKYmEfE+1nfleD1euGG5xtKspYGIzGHo9duB6JBC1f4bOxOcHRiCdsU7BjIsLc/jpTXVVnJzhhuOk6vBaYFwftbxisEGskMxs4c3aZJM1D0ireuf50xKSkZjgt+Y3cv5bZCKkXKNYkZIVLeGAFJ2Tlnpoo3LO4IwPquBDFTscpTNU3TNE3TNE3TNE3TtI+R21oBo320+Fg8f25uOXy51qGJIpt64uSvFGdIKYmJkJgLIEGCMiyKPpRbAZZhkI+ZxI3wlnqaZF3F1v4UJ2dWVogI4MDafGfi0nYwkynCaqdRtxACWSktP9bs7sVv1gGwhaS7scCX1sSYE13EHZOUrVaEL2+RwsRMJAkLC6vfnR9PoK6rSrn+PUWNkAc3dvHkybkVoYMA7l/fRdKUhKHE3bAVcfoYKrhxHO7uO2kZJu+qhOgjqsuVPLK9j+fOLlC/Eko5lsGda3KsSVkoqXtZfFKISCc09KRgrnLjEnoqEuXp07N8bfcQp2YrNzSoj5uww20TnzjLfVvW8drFObwr35lUPMLnNmfoGkqyIe+SsE2SlkRdH74AgeNiDowgz5+6cZCGwB7dSP19hi/XklIipcSG1Yr2UEphE9DlLD+Dm10KlVKMpB1GcjHGCytDmFTE5o6hNC2pWGwp2oEk6Vrk3E4Vn6ZpmqZpmqZpmqZpmvbxcdsCmJsJgoAgCIhEIh/2UH7llD1FseGtuk8BE6UWXT3Oqvt9YfPCpTJnZq82X486Jg9t7mEkLt6xMsaQIfevSdObdDkyVabhhWRjDvtHMgwnDKQM8W0Xd+cdNF565sqzxPId78JxMHsHaZ0+hnBcVO8g0o2RdEz6TAlI1E3uHg+kJLptN974xVX3u9v3vmMwIqVkbdLg63sHOTFbZb7aJhOz2TWQoicC6sqt681Ultjnvkzr5WcJr4RHIhIluvdu/MHR91RB9FGkrnwefXv7KbQ7S0VlIiZJM0TqSeNPlCCTx8p3U5lZQF0XQ0QyGabtDI2KT9sPeHxXP4enq5xfbCBQrM1HubMnSvR7P0G1m+ypl9mwaQtlM4opINMqkS5fJhB9RN0r5/FNQgwvGsfedwBVrxIuzKKuhC3CcbBG1iFHN6KUWrXy8qPAUT4Pb8ozXk5yYqZCIGFjT5yN+SiNIOS7R+eptK4GT0PZKJ/f1E2U1a/Z2kebEJCL2Suu+amIRbmlr4+apmmapmmapmma9kl22wKYF198kXPnzvHbv/3by9u+/e1v853vfAeAffv28fu///s6iLmNrp88vZ6UctXJS8MwODRd4/TsyuqVphfyk5OzfHPvICnznSeVLOWzLWexKdeDr8A1QMiAt9bdkVIi124i2qjTOv4mKvAx01mwbWL3fY7mxBjBxl2MRbo5MlsjVDEGZgJ29kXJ2W+/PJrf1U/0zvtpvvkyhFeSGmHgbNtDe2T9rQUjSpK3JZ8ZTaBIIlCEYbii34NSilbvIM6XfwOzUkJJiUqk8GOJzmM/QaSUuEj6l1dVu3kFgPbx5QmT2IOPYP3kh1C6Wr3hptOYD3yR46XO9zpQgmIzIJSSjT0J4o7J2lyEtBUiszn82SlkqUCs9BKxa45vfvHXad/CuSGlhG17sD0PTh2GZhMhBEZXL86nv0AzmvjIV5c5ymdj2mBzLo9CgAypS/jhsbnlSrK3TBabPH+xwKMbM6hQT9p/3CRdi+zFYyRn5pa39Qz2Ue3fylR59f5ZmqZpmqZpmqZpmqZ9/N22AOaHP/who6Ojyz+fOXOGv/mbv2Hv3r0MDQ3xxBNP8J3vfIff/M3fvF1D+pWXcgySEZtq68blfQCGMtFVlxOrS5Pj06s3l/dDxaVCi729zi0tRaaUwiTAhFWbtHuGibn7LmIbtmBUSph0ejvUTx3D7xni2WaS8+enEJaFNdxDYarMmdkqX93VT49z80ncQAjU1j3Eh9eilhZASYx8N/G1G6guLr2ridt3ClKUUrRNG7Ld1z7plo+vaR81zUSa2K99k/T5MahXIRpnNpLlaFnihRLXNqn7kqdOzqx43sGL8IVtfey45zMEP/o2ylu5hJm7aRt+rptb1TZtzP33E9myE+pVhGUTpnM0LfuXWl0mhMCWIWa7hTJNPHf1a+WtUEoRXrNU2lxN3hC+vGVssUZpTYa0+Z5eSvuQtRYXqU5NLf+ciVjQ/yEOSNM0TdM0TdM0TdO0X7rbFsDMzs7y4IMPLv/8i1/8gkwmwz/9p/8U0zSRUnLw4EEdwNxGERFy3/o8T56c5fo2MJt7k+QiYtUeKX6oaPk3DxAW622E+ACbyyuFqFVoHXkNf3EOyzRx+ofxN2xj7MWLmF09OJkcvV1pkhEbBZyeb9A9Eu9U1NxEqBTNeAriKQzDoC5NZpZatFoGGdcgeov9bDTtV41SCiPiMJUZ4li9RFhXqPrVc23fmjxvjC3c8Dyp4OfnFxnaN0D6y79BcO4kwfQ4wongbNuFHFhDBYdSWyKVIu2aJMybn4dCCDxhUY7lMWJ54pbqVIf8EsMXE3CmL9M+dJBWaQnDcXE2bMXctpem8/6ue0IIyjcJxKHz+bUCqQOYX0GG6Hw/DMNYsV3/jdI0TdM0TdM0TdO0j7bbFsAEQYBtX21sfvToUfbs2YNpdmaShoaGePLJJ2/XcDQ6EzfrUiZf2TXA6+NFCnWPiG2yezDNxnwEU/rLPVeuZZuCiG3eNITpSrgf2N3nQgicmQlqT/2At5pBBGFIOH6J4uwS+/d9gYueyUA2yYsXFhkvNjAMwcauOFv6UvS+w1JkAMowOb7o8crYHIbt0mg0iDsWD2zsYl3SQN2sCYWmvQ9vLe/3se0DJEPuGorTlXA4NFGi4QWkow53jGSRQLGxepBQbwcUmyF2PIWx717MvfeghKCpYKwmef7cDPV2J8yJ2CZ3j+bY1uUg5HXXG8NkvCZ5ZWyehWob0xCs7Ypzz5osKTP4pXyuhmHgXD5H/bmf8lY6LZsNWsfewJqfxv3cr3Wq3d4jpRSZ6M3/LBsCopbBquWC2idaJmpzaKbOUv1qD6Bc3GFvX0yHMJqmaZqmaZqmaZr2EXbbApienh6OHTvG5z73OS5cuMDs7Czf+ta3lveXy2Xd/+XDIEMGIvCVLXlaEmxDYKkAJW9+F3bcCNk1mObVscIN+2zTYG0uckPjdSEEpml2ltt5F8tv2TKg/eZLCNvGTKUhDAlKRUARuhG6Ey6VIMK5hRqb+1K4jsnZuSqn52t898g0v7m3j6Rx8/cihGCiJnnuXOdu/diVudO6F/DkyTl+fe8AXe99PlXTbqAMi6W2YrrcCQ0G0y4ZWy33PvowvBWEK6UwDKPTf+kWJnVNGbApbbA+040nwTUEhgo4WXiHZfneCi+k7EQJSrHkW/z0xAzhNcFJyw95/twCSbefNQmxHKoIIZisK350fGa5ei+UivPzNeYqbb6+q4+ouPl5/17ZXovWGy+xWmlgMDeDuzQHPUPv6zV64zYJ16LWvrF6b113grSjUHoFw19JhYbPbLV93dbYqo/VNE3TNE3TNE3TNO2j4bYFMA899BD//b//dyYnJ1laWiKXy3HHHXcs7z9z5gzDw8O3azja9WRABECuuurYyodKye6+OPV2yKnZ8vIEaNy1+PyWHtJmuLwCkBCCurK4XGgzWa6RdC02dsXJu5Jb6dButpqU+9YyMZDkYqmNawq2rHXpkk3O1x1eef0Sl0SKQt1DAPvXZNk7nOX0XIUgDDizUOeu/ggCsLwWyjAIrKv9aaQweW18cdXXDpXi2HSVz61LInXPFu0D4AuLn1+qcGb2ag8lQ8Bdo3n29kXfdsm8X4ZA2MzUAyZLDVIxl3IroNRok49ZbOqKk3MkSkosITD9NsowCSx7RTijlMJQK68ffUkHwerXkphjkXFNrq3iMEyTo5crK8KXa70+UWR4WxdCdT6fUJi8fGnxhqUTAaotn7FSm2058wOvgjEadcLq6v2vAMLJcYy+kfdVkRAVAb+2o4+fnJqn2OhUOwhgTVecB9ZmUeEHHyxpmqZpmqZpmqZpmqZpvxy3LYB59NFHsW2bQ4cOsW7dOr761a/iOA4AtVqNUqnE5z//+ds1HO19spXPp0cT7BlMUm4FWKZBPmoSYeXSP8XA5HtHZ1Y0lT40XuSBjd1s73Le8a7/kp3gu1MhxfLVxsVnJw3237uPQxfOImJp6rXOsRXw2uUiX97Rx2iu0/9lrtImEm/iH3+T9vQEwjRxNm3DWL+VphPBk1C+yVJJAAu1NqFKI9ABjPb+GIbBmYX2ivAFOn09Xrm0RF9ygIHo7RuPJ2yePLvEfLXNup40/99XLtPyQ5IRi6FUhEPjRb60o5/N/hLesTdpz08jbAdn8w7Eus20LOemx844it3DGQ5PlFZsF8B96/NX+itd3S4xWKhdf2f/VaWGT1vCWzWSzVCwUG3d9PEXFmvs7M4RBB9woGUYcNNoCXBu/pncKqUUOTvk67t6KbQkrSAk6VpkHYF4m8pETdM0TdM0TdM0TdM07aPntgUw0KmCeeihh27Ynkgk+Nf/+l/fzqFoHwAlQ9ImpOPQufVdrpiWVIbFc2eWVoQv0Jm6fOH8AoOpITJv8w0Uhskr01XK4cqmw709OX5+bp7ATRKLx4i0fQKpUAosU3B+ocb+oRTjSzXucus0fvwjZPvqZG3z9Zewxi4QeejXCF2bmGPRvEk/m2TExhRKd1zQ3jdPGRydKt90/5GZCsObMoQfdGiwCiEE5wstxgsNNvSmeObs/HJPp2oroBwJ6YkaiIlLlN74GVZ4te9E8+DPsSfGcD/9KG1z9RNYyJADQwl6kxEOT5aotwNyCZc7hjL0R0FeF7waKJIRm8WbhDBxx8I2xHLRjCE6yx164epnZtT+5XSpDxIp7N5+/LnpVfYKrOG1eB9APw6lFDY+vS7gAgS67YumaZqmaZqmaZqmadrHkPHOD/nlUUpx/PhxDh06RLPZ/DCHor0HthBEUDi2jWXdOBFb8WGmtPrvVSoYL7WWG5GvpiENzs3XMLv6ENcc33Jsaq2AkjSxHYe+pEPKNUlFTOK2QcsLMQ2D4aRL6sybK8KXtwSLczA9gU3InuH0TceweyCFDG/vslDaJ1MgBU3/5t+leisg/OD7xq8qFCbHpjuVOLZprmjsDVCoe4ymHLw3XqTR9G54vj89jrEw87avYciADSnB49u7+M29/XxtWxdDCYFYJUmQYcCewdTK5wOGkggBe4bTWOrqZxc3JBt6Ejd97a19yQ+++gXwEbh3P4Bwb+xXFt1zJ14q94G/pqZpmqZpmqZpmqZpmvbxddsqYP7iL/6Cs2fP8sd//MdAJ3z5kz/5E44fPw5AV1cXf/RHf0RfX9/tGpL2HlkonMUZFqoeZ0s+YzVJLJdj+9oeBuImxpWJ0kCqt+0n0/RDhHBu2qdBKgikRNoO5sg6VLWCqlVoKYO+3hwXii1CFNmoTbUVLFex9CRdWl7AnVmBeXhq1WMDBBdOY6zfwoaMw8JgmmPXVCeYhuDA2jz9caHvPNc+EK6pyMYdZsurL53Vl3IxlLwtXzepwA86rxSu0khFKsWQ0aY+M00mHaWz7NZKwdh5zMFRwrfpj6SUoq0EF4stzszVMA3B9v4kIykHW61cTqsvJrhvfRevXlxAVquExUWElOzaPMw2x0MRXb6eSBly10iGmUqL4nXh0e6hDH1RA9Qv55NsZrqIffk3kGPnCSYvY8TjWJt3EOR7Cd4mUNY0TdM0TdM0TdM0TdN+9dy2AObgwYPs379/+edXXnmF48eP861vfYs1a9bwX//rf+Xb3/42v//7v3+7hqS9ByZgnj3GUjTHz8erzCyUaLY8uDzJ2PQg27aOct9wAkMFxG2DmGPReGsJMiEIlEABplAMZiJv26w6aiq6khHmKy1C04ZsHjPbRdFvs7UvQbEVgAILyZpslLovqbR9HtjYzVDSZo2o0+BtQiCjM1lqqoD7RhJs709RDQy8doueuE3KVu/Yo0bTbpWhQu4cyfLDYzM3fCctQ7C9L4mU771qwzAMWtLEU2AJiBnhTc8vRygGMlEqsz62KXAsAy+4+tiEayEAQymihsIMQ6RlL4elQogr/VBuzrIs2srkmbOLjC3Wl7dPFhsM52I8sim/IoQRMmR/t836FswsKsJcjl5HkZ45gn9ihvjnvkyrb2h5DDE8HtvRy0TZ49JSHccy2NKboCdqYLyPz/GdKKVoxpIYO+7A2HUnCmjehmXjNE3TNE3TNE3TNE3TtI+f2xbAFAqFFdUtBw8eZGhoiMceewyAz3/+8/zsZz+7XcPR3qNoo0pQq1E7dJSttTrbRzZQGunllYuL+IuznBxPsKk7Tq/bmQC+a02W584tEGAwV/WoND2kgnX5OBHHRlgKIUMMw0BKuWLC2FQh94zm+MGxaaQCy/cI52cI6jWWWgW+sXWUl8/NUXGTIKA/YfH39g+SdEwuLdVZFAbrekcwpi5hrVJXYG/YRuvK3ftChuQsyfbhfmZmZlBK91zQPlhKKYYTJp/d3MvLl5aWg8lM1OHBjV3kHcl7bR8SCotjC23enJin3g6I2CY7BtLs6Y/jqBsbt0sZsncwxYWFGnPlBnetyfGLC4sAWIbBgCMZny2wp78HZ/I0QbOOle+hnc5T9SRtP6SrfwNt3yBtqZXnrQC3sEBw9gTVmUV2JLJsHt3CwXqEUqszlolCg8uVFFtzNmF4NSiyC3PEnv0O600TEHDN8n+tV1/A+dI3aBtX+7tE8NmUMdiaz6CU6lTjfAA9WG7F9dcrTdM0TdM0TdM0TdM0TbvebQtgTNNcXpP/rd4vDzzwwPL+TCZDpVK5XcPR3gM3DPB/8RTlk8eYK7Q6d/FfvoybzfLgA1/iqVMz4LU5t1BnYE2cMAzZ0uUgzD7+9vA0pYaHYxk8sj7LPYk25RefpRk1UX1DTNgZ2naEtbkoSSNAKYVSisG4wZd29PPaxUVmT57DCAM2DnVxT7dN6tUfMNi/ltpIHtnVRzpicrHQ4kdHp5Cqs2hSZGQX8txFhqIGjrg6WWoPDCP7Bm+6/Jmm/VLIkK05k9FMP+V2iCEEadfAIUCushTYrRCGyetTdd4YLy5va/khr18uUGp6PLQ+g6lurOTK2SFf3dXPixcLJG2Dh7f2cny6QtqUuAvjZAayjNx9F42xoyigqkwmpguEdoTE+o283Ixw7tAUX9zex1CsE6AaAuwLp6m99AxSCebma/jtUxhvHOSBL3yNZ6081UDhY/CLS0XKzQSBlGzsitMdEQRT453BrbKsWVhawqiV4bo+K0qpX0q/F03TNE3TNE3TNE3TNE17v25bADM8PMwLL7zA/fffz6uvvkq1WmXfvn3L+xcWFkilUm9zBO39EEIQCpNmKBAC4qZCvcvm8sbcFK0LpwFWLKHkFYukLh6nO7eWkmHQDBUF30RKQcYVJB24a00G1zLpcSB/5lUu//AgXqCYVYrehIvVM0Bt32f468tFfm1HHz2uRCmFUJLBpM2aYZuSymCGAfG5i8hDM4RKYVWPkB07Reyrv8mMl+bZM3O8NY+tgOcqNvd/7nFqM2fpLk8jDBNny04YWUfLcj6YD1fT3gUpJS6SHvfKBhW+ba+kd1INBEcmS0AndOxKunQnowghaLR9Kp4ga9/4PKUUPU7I17blqQUCyzR4dFOOsLgE502iU2/SmvCIf+ExvGKBifOXcXM29r57mUgPcqLQqWZ58tQ839rbTwSJW69RP/g8QilEs0lYK6NCSQjUn/4Bmz/1FV4Pklwo+Qyko+QjFhPFOofGizyyrZ9Nv8J5qBACH4uyJ5EKUo4gary3Kpu3rve+FDS8ACGEDps1TdM0TdM0TdM0TdM+BLctgPn617/On/7pn/I7v/M7AGzZsoUdO3Ys73/zzTdZv3797RrOrxQhDKaa8Pp4AcswcCyTXNxiUz5G0gyWJ+ZM0yREYAoIr7uj3LIs/LPHEW4Eq1bDdW3a7StLG5kW9fEx1j18gJ8VLdYLg796Y4JAKnrTUTb3ppks1PGCkLWJGnOvvoJUnYlBBRiGoD4+RlfvGZz0Fp45u8jXd3ajDMH5Qpuz8yX2zR2nffhVuhMO0hZwzWSi8jyE12a81uL6IoJWEPLTJYNkaju/fveDRG0DLIF8l+GTpn1UlduSQKpOg/uBLKfma7x8eRYvkPSnI4zkk2Rz5k2fL2RA0gAUmIaJeeEorWqFpXV7aUhBxFAYO7dz3h7FDyVzfp5G4er50/AClpohg1GgMA9BgOm1UEuzJCJJyvUWAF65zIDpM2RI0mty9KZcpgs1AKSCn52aZeO6UTh8sDOuSBTZP4JvR3DqJcxGHZn4ZIb0hmEw2YDnz81RbHhApw/PvevybMiY72pZNWmYXK6EvDG+SKXl052psq07wtq09UvtjaNpmqZpmqZpmqZpmqbd6LYFMLt27eJP//RPOXr0KLFYjHvvvXd5X61WY+vWrdx55523azi/UqaacGiyjGPbHJosUWn55OIOVU9x11CSmOGz5BmcmKwyV2mTiFjsHkjRHzPgmqWLlO8T2g6269LnWIz7IYETpRUqVCukGhq4jk1fKsK52U4SMl9pcX6pwYE1OZaqTdTpVwAIpEJxpZn3Fd7ZE2z57BZeXWhTCw2OTJU5Pl3GsQxUJEbDCxgvBAyko2QjRic4EgKjd4BqLE+55iExMN5q3iKg6sN0qUEgJWtyCc7Pldg3kmVvX0xPRmqfCJbROYc29qZ5+uwC87X28r7pcosfnZghsaef/r6bHeEqpRS1ka389PAlJg5Po+i0Qtp5Zw9v1i3kwiyxdXmEa2Be0yTJDzv/V0Gn2kJWK6hmna6uDNVm51zNZFMYboQXz5YRCYVl5VnXk+L8XJmGF+JLxbSbYWDjVurK4kKkhyPTFZotj670IJ/69A4iZhwvCHFMQdyUnZ4vnwBLnsEPj00RXJMg19oBPzs1R2zXAAPRWzuOMEyOzLV4+eLS1WPXPX66UOLO0Rx39UdR8pPxmX1UGIZxw7Zr/65pmqZpmqZpmqZpmvar7bYFMABDQ0MMDQ3dsD2RSPDbv/3bt3MoHytCCIRhdgIL9e6WpFGGxdn5KuW25MWLM8vbK62AsaUGtjnC5q4of3tocnnyb74KFxdq3LMuz77eCABhGOKs3Yg/O4XK5Ei3WwzHEkyUWliGIjW6Frq6uN91ee7cPFt605yZLaOUwjYMCg2fpGMgm5073t8qYElHOmsj5eIRvMAn7ZjsGEriKcGJ6TIAXiCp5fsxbBvp+8xV2yTcGJZpUt91HwdrLuNH5hjqSnKh0KAnGSFlC9ohTBTrKAVJ10IqiR8qDl4qkHJtNmUMvSyP9rGXixjk4y6tUK0IX6BTXeZaBq+MFdgx3PWOx/IMh5/OK85OFREoLMOg1g7wWi2magHDPX1MNhWq2WQkE8VEIgSkozaGpTDy3YCAwAcFbnGOtble6maEyaai0jRRSpCLWPzi/AIR2+CrO/s5NlFAAbMt6Lvnc7x8YpYTJ86DDBGRKIm16/nxeIOFaglbhEQtk52DaXb3xbDVRzxINUxKvqDQCLAMQT5mkTBD1JXruGmaHJuorghf3qKAV8eLfG1bHm6haq8aCF4bK6y6783xIpu7Y6RuzAu098gwDA7NNijUvRXbR3MxHcJomqZpmqZpmqZpmgbc5gAG4OzZs5w4cYJyucwXvvAF+vv7abfbTE1NMTAwQCQSud1D+khrC5uLhTYnZ0sopdjcm2BDPkoU/5ae3wzBMk1eucmk3E9OzZHcM7Dq5N/BS0usyw/TT+fOeDG8DvP4YcJqCaJx/GZILOoSMQxid97HfzkxT70d8vDWHoQQOJaBF0hcE7xQEpoGVv8IzMxgXZkY7k9FKDY95iotEoNDvDHd5NhiicdUH4+PuLQX5wHwrCzpR77C/E++T+D7eKEi3LaXH0y0qaVSBEJiArmozWSxwXA2RssPl4Oeu0dzzJYay+/t9fEi6zI9mHzEJ2817R04BHx+aw9/e3R2xXYBDKaj2EKyVGtTaQW83dx7S9gcn2nw3OUKvd39hLNTtPwAXypmp+bZ1J+lrBzqlc6SYhUvJOGY9CYiHJ2uUmy0uW84Td/GbchyAcolCALc4hzN7CD5vXdzohHSFVSptxJIpWh4Icemq/SmI8yWW/QkXWY9OFFVGCPrQCoGcgnOlQOOTJWwTYP1+RhNP+TVsQINL+TBNYnbVtXhygCztIRqNRHRGEE6j2fcfHm3UFgcnKxxdLK0vDyiYxo8sLGbTVkLZEiIYPbKZ7qaQt2jFcKt/GUstsJVr+UAoVQUmgGp+C0cSLtlhbrHbHVl8JmLrdJ0SdM0TdM0TdM0TdO0X0m3LYAJgoB//+//Pa+99trytv3799Pf348Qgn/5L/8lX/rSl3j88cdv15A+8lrY/PDEPPPXTO7MV1scn3H46o5eYrcQwgghqPsh4U0m5ZqBotQKkcLAUCsra6SCmUqbrW+NJxIj+oWv4R97neblSxTKVRqZXoydd/LnY5KZSovBVAS/VGTDmix2d4LjMxVQipFMhC09cYhvR1w4QVRIQqloB5LZSgshBPauO5mpKf7+1iTrq5donztN4dIYQRBgOg7q3gdJP/6/o2bGSUQFY90bqHplwisToOfnK3xmUzdHpypcLNRJuDapiMXdo3lMJOXm1c+r2vJpS0FM36SsfcwppeiNwIauODOVNk0vxLUM0hEL11Cd3i5CYBqCm9V7GabJq2MV2lLQCiSzVoyBtRvxqlUM32daRNnSm6ffMCg0fZp+SM0L2dSTIhu1ODFTAqX4dqnJ59fcwe5UmubPvkdQLGANDqN2PsCpmkV5YoJI9wBT11y6LizW2Njdg20a9MRMjszWAZAIMASZRIRfjM1wV2+UvBVixywm6wHtQHJypszugSTpm2cgH5hYvULr2SdoFheXt1k9fcQeeIRG9MZUwzAMTi21OTxRWrHdCyXPnJkju2eQ3oiBE/rckRWcMx0uV/0brtUR28QWcNNf3jXeqejCELd4IE3TNE3TNE3TNE3TNO0DcdsCmL/8y7/kjTfe4Hd/93fZvn07f/AHf7C8z3EcDhw4wGuvvaYDmCsMw+D8YmtF+PKWYt3jxGyNA4Oxd+yBEDcl6eiNd+NKoOFJelImC9U2F5ca9KYiJK9rcH/t3dRKKRrROOaBz2Duvo+ps3OcrhmcnmxhGCH/YFOU1MXjNI6fQ2WibBkeZnDdTl6oOmzqipE1fayhXoa+8Q2aLz2Pt7TAucUm+XXriD/weYpWnMfqZQYq08hXnsJWsPnOvVw4dY5WqcTc80+RfvRxDsZGGd7bz8VzheXwBTp3eB+bKNCfjrJ9oI+BTIzxxRrTpQbV1sqwKu5a2Fcaj2vax53v+2zviXNqpoSImZ2l9a45j9d2J+iKOyzUV39+LTA4M1dlU18GgHYgWQod5sMYoVCYLcHE2QV+6+41fHF7H4HsXEPKjTZ/d3SOVMSmN+liI/nZ5RqpvfvZMLKO8PJ5Qt/n1VKUsYUCVm8/RipLT1uyUPPwQ4llCgYzUdZl0hjSvxISXJUxQ34rXaJ95A3alQpdXVm279rH6fQAZ8s+5VZA+pdc1eGGPs1nfowMPJo7DlCwk4QSMkZA7sRhnDvuwRMr64s8ZXJoYnHV40kFjXIF9/IYrZOH6W20Mcw423feycEwxXz9amXersE0tpDcJENfIRexcC2DdnDjMpWOaZCPWnCL1ZOapmmapmmapmmapmna+3fbApgXX3yRhx9+mIceeohqtXrD/sHBQV555ZXbNZyPvBCTU7OrLxsGcHa+xt7++Dv+AmUYsqk7TsI1qbU7YY1EUGkF5OMOCacTYLQDyXihwZpcjMQ1B+1PuTeOTUpKVpQn5ySVZicg+vqwQ/z571MqFJEKfEdSOnWS8Nw5vvXN/wcRV6FkpxIqzHRjP/IYbqNGrhJyNojwvfOLiKkTmK0m0aDJHesOsGX8EPUn/paRh77K+SPHkb6POnOUzzz6OJYMiDk33vaugJlyk/lKi629Sc7NlVeduNwzlMEV4S1Nan7YLKvzCwnDUPes0W6qKyq4YzjLG+PFFduTEZt7RjNY5s0XIAukwg8l9bbHmlyMy4UGfhASc0yW6h6O1ekzU2l6HBwv0fQka7tiXFrs9FgqN31afsi6fAxTKI5NVxjckENs24fVrLKlbjPhLBGaJijIRgxSboxQwc7+FDu7HALfQwFDmQhv1Wn0xG1GJo5z9KmngE4FR3NxgdYzP2HLHXdT6d5+5X3del+s98IsLSFRXNpwD8+enqHVLnXGYwi2r+nh020Prls+05dQ91YPO7ZkbJyDz9AoTaKUJCoE0UqdpZ98lwOf/SJPOV00vJBNvUk25yNIeWuhScIM+dSGbp45M7fi2iaA+9Z3Xek9814+AU3TNE3TNE3TNE3TNO29uG0BTKVSYWRk5Kb7DcOg3b6x2uNXlUIh3yYdCKW65SnHvBXwv90xzBMn56i0AgIFuZiDVCG7B1MYQixPeM7X2sSzEYRSbOlLkbsxfwHANWAkE+F0OyAZseheuEShXMIyDSxDkHAtHBNitkni3CFU38MUAotKK8Q2DXIRi0jaYabt8+03LjFktGk3GtgG+J7PKycnyO/bz7rZC4RHX6N3dAutqXF6RItEJMQLJBu6YhwaL65axDLaHac3Ap/Z1MvPzy/gh51PyxCwfSDN5q6Vk5pCCBwZEiwt4IQ+vuUg5Yc7U+lKH2N2Cv/sCZQf4K7bhBhaS9N9d32SLMCplVHFJTAMyOZpx5O6+OcTxpABdw7GGM3FODlXpeWFjObjjGZc4ubbV8pFzM45O1Goc+/aHEGomCo3ySVcyi2fvlSEh7f0cGKmzEK1zVA2RiZqU2x0mo9bpkG3JWFhFlp1QtVLpMunlUjRjCYZitr0LrWZKTUwfQ/VbmMagkQqyb3DCaxaGcNx8A2LrKPYO5zlzYkiOyIetZdfwzYNglASc0zeWkitdPh19nx1M/moCUoihCDApNDuLG0Yd0yyDqDef38YWa9TWLeXJ49MEl5zXZBScezSHPk1I+wcia24ZjiGIhmxb2jQLoD1qoqcuAjJTnWiUIrumEk6EsM79SpffOSbiFicXERg3mL40hmPZFPWIrNnkKPTFQp1j/58nE25LL0RbluvHE3TNE3TNE3TNE3TNK3jtgUw+Xyeqampm+4/c+YMfX19t2s4H3kWkvXdcZbqq4dSo/k4EUNxK/NpSobs7rbpuXOQYzM1zizUcUyDrX1JZkt1LEPw2O4B3hgvsVhvk4o67BtMsTkfwZCrN6lPWpK9gynaoaI3aiJfO49lGLiWQcQ2yEZNbCRCKBpTk9QKdQ6XFDOlBqWmRypi86Xt/UwUmzi2iSpXgE51jmUYKKU4MlNlw/qtGKcOM3TgPpqVGexMGkln7bC8AwfW5Xn54tKKsaUiNveNZlGBx5acydAdgyw2AgIpycds0rZCXDOpaSuJNTFG++hrVAIfD4G7fQ9q3Wbaxm07RVZwA5/wpadpXr6wvM2fncRMZ4k+/FWakVtbc8lRIRx5ldqJw3BlclhYNtE77yPYuOOXMXTtQ2TIkF4XBtYmEUJcqZryUertm4NEjJA7RrI8f26BE1NF7hhKce+6HO1A8fU9gyilODFRQGCwezDN3uEML5zvLK9lGIJB08OfuExTQMw22Jo2qL35Ku76jbBmAw0fPrOhm2qxxKGj56m3WmzoirPVmCb32inaxSUIQiK79xMMreXOoTgDmQixifNUWm3W5ePMVVtc28VGSMlaq4VBAEJQCkx+cnqBpVrnmmkIWNuV4DPrc+/7c7XSWc5MTa8IX651dKbKxuE8zjWxuEXIHcNZfnZ6bsVjY66FmJ0kG3NQ15SjCBSuoXD9Gv2iQcOJvLfCHhnS48AX1qcIMejt7mJ+bhb1cSj3+xjKxW5c4jMVsSi3Vv/bqWmapmmapmmapmnar5bbNrt8//3388Mf/pADBw7Q39+/Yt9TTz3Fyy+/zG/+5m/eruF85Ekp2doT5+RMhVp75URO1DbZM5BChrd+Z7SQIQMRWLM5S3fSZaHSJAhCelMxmr7PZKHKtr44iUiWu0fSxPE6FSLX9WOwhMD0PaSAOwaTNP2QdssjEbURrolzpZ+DIxShMlhqBCzVmpw6t8RrSwF7h7NsSEU4P1fh1fEi5abPQCpKWDUQQmCkUtDdg2q3KHt16vE0EQRCKZQCe/semleW4RIqZE9PhOHMIOcW6jR9yXAmynDaISoClAIlJXEhicehc+95sGJS0xAC4/Qx6q/9AgAnFiNsNGi8/BxuYRHrrgf5wKfRDItm2Kk6ilkSeV0fHyEExuzEivDlLWG5SHjyMMb+T71jhY4QAuPyBRrH3lyxXQU+jZefJ5HrguvORe2TIQxDhBDYSiKCAOncpJTtCiklW7pcvDDPm+NFLix0lolc351gJO0SMWFL1wC+FPzkxDSvXphn12CWi4t1EhaEszPIUBJLRLj7zm3M+QGvNXKsbyeZPl1iotyEpQXiXo27Ng+yoTWP/cbTNAtLlEyL9MNfoXnkVerP/YTo/vuwt+1lJKaIZiLUshEMIB2JU2kFtANJxDZIuhZx26ChFJ6w+cHxWSrX9HqSCi4s1LAMg8HudwhhTItGKDDo9M26vreWzOZZ9GZWfaoRjVFVBoEE55rLpVKKdVmbu0dzvDlRxA87162obdKfjWFOvE0gIt4+MLsVne+AxDTe/7G01QkhWDN1ktTs/IrtPYN9VPu3MlXWVb2apmmapmmapmma9qvutgUwjz/+OOfOneOP//iPGRwcBOB//I//Qa1Wo1AosHfvXr785S/fruF8LCSMgMd293N4qsLFhToKxWguzt6hFGkr4L20A/G9NsOZKKdmaxybLtDwQ3oSLneP5qg02mSj6kr4snJy3wSchRnax16nXS5iROOkduzj86PrKAZp4uIOGi8+g2sKTCQKg9maR6HhY27ZwsmqotoO+Pn5BfYNZ+lPR6m1fVzLJGJKjJ5uSKSYrnnUSx62MNk2OILq7idYmqFerRG/9zN4XSsDA6FCumzoHe5UhEgpr9zxf2ufh9us0Tjy6qr72mdPkNiykyD1/u+gh85k3bxncvBysbMUk2GwvjvO/qE0CSNY7u9iGgbe6WM3PY538Szuzv207befVLdlgHfs0E32KryTR1Dbdr/Xt6N9hLmhjxi/gHfyKNJrYXX34d15P0Y0QXiTk8OUAXf0umzuGqTmhTiOy/mFKj84Nk3TC8jEHO4ezTOYjbNQKzK+WOHxPYPMzRe5PCdJJmM89MAeXjg1RXt2io0b1/DE6QWmmorBXIJUcYmy7/Gzg6fxtw/R48FCNURKn+6zFxF3P0rX6VdoHX2N2NqNnSqvTBbDtlFeG0dAd8ykczUCbAuV6Zybc/VgRfhyrfPzVWarrdX/2AmD2Zbg4OUl5istLMNgU2+SvYNJYtc0q28Lg/61a5icL6HaratPj8Yw+4eIuQ62obh+XT9TBuzvj7K5O0axFWIKQS5qkilLqkdX73lmZbsIkqlV92kfPa2lRarXVfdmIhbobFvTNE3TNE3TNE3TNG5jAGNZFn/4h3/ICy+8wCuvvIKUkiAIWLNmDd/61rd44IEHEB/AXb+fJEopksLn02sS3DWUAhQRQ6HkewtfAAJh89LFRc4u1KheqayZqbT4u6PTPL57kDuHU0h541279qUz1F54irdmGGWtSvDsj4nsuoPs7gNYa9dhXTpJMNe5S7wdQqnh4WSyzI9sY3bs6jGPTJX4+p5BTk4VOLChl6VKg4YVYaxSpdXoTG6GAtbmE3z/whiPPfZ/MNbwWT/aiwpWn2S9/o71W1Ypozxv9X1KIUtFRLYHCZhKvq++MPOeyXcPTxFcWQrID0NOTFeYKDT59V19RIW//LoEN6+7UWGIuIVxGL5P2KjddL+slFD+rVdRaR8PjpSErzyHd/Hs8javVqW2MIt73+do9g4th33Xk1LimiZNy+KHJ2Y5M1fFMgXpiEVYa/Pj49N8alMv/ekoM+UmJyaX+Eq/yR2DBl3dGV6+OE57ZhbTMDBiCSYLU4holCAI8D0fW3SuIM+cnOHLw5sJJ2cBaM7PceTCAruGdjN66udQKUEkTjuaIHbgAeovPA1KXh23EMTu+hTtaAIBFBs3/x6HStHwQq6PNIQQTDfh+0enl0MpPww5MlliotjgsZ29uKpz3DAM2TCQ4fCadahWCxUGCNNCui4BBnuHM7hCstoqX0qGJAxIxKDz7iXtdI7Izn20jr2xckyWjXvgAVqGxXu+yGuapmmapmmapmmapmkfGbclgPE8j7/4i79g+/btPPDAAzzwwAO342U/McIwxKUTMKj32Rd+vhkyVWzQE7c669Q3faSCZMRivFBHrUnc8JygsEDztV8ACiGMzjiuDKR17BCJ9VtoJDJEPvMl3Mkx2udO0W4HpDbup9gzyvfPN1a+H6loBSFSQcSEz2zp5X+9MUXgRLEMC1f63L++m3qjxVi0hx/MwdHJGv9nbx99V5bbF0LcdBL53RCGcdN9waZdnLC7OXx8iSCUjOSibO9LkjaDd//ahsXBy8Xl8OValZbPxWKLnV02UkokYI9uwF+YXfVQdt8AQST2jhO00nYwEymCa+7Yv5aZ7ULYN/Yv0D7erOICtWvCl2UypPnqC9hf/AaeYa76XGXanF7yKbYCfn5hCdMQZKI27ZpPV9wmYijeGFvkG/uGKDUCCs2AmCvpqs7g55JcmigDEI+5zFQ7waYwLTwlCAwTWwUEEmrNJt7w1coyke+h0fJ4eWyJ4bVbEFfGJ6XEW7OJRDKDf+ooYbmAmc5hb91FO9+LvHIOpCI3/1NmCIjYBlyXK0vD5OVLiysqgoQQGIFPuewxVUyzMe8sh7s5R/L57f08e3aBptfZZhqCPYMZtuRd5E36Za0mQGDvvot43yD+ySPIVgOrZwBr83aaqdwHcm3TNE3TNE3TNE3TNE3TPny3JYBxHIennnqKoaGh2/Fy2k0YhsFUqTMZL5QiakAs0ZmAV0rRbHvUPIl73Zy8LC4RttvUfSg02yilyKbipHJpzMBDLs5DIkM9kmAis57JkQy5TJK/PblAZDYgHXNolpsrjmkZBpYh6E84RCzBZzd1Ufckwvcx/RZjl2eYnS8iojHquQTdCYfJUpPe/hiFZshC3cM2BT1xm5QlUbdYmWIYBrbXxgg8pO2gMjmMeALZaiL6hmlmuqBaIozEebqeYPxiidByAFiqtzk1W+WxXf1krXfXGaYZCmZKzZvuPztfY1dPHmSnysYY3Yhx8giyXl35QMvC2X0njVuYoPUNk8iu/QTP/ni1DwJ76663DaC0jx/DMAgmL910f1hcIlKvQDJ7wz4hBGM1xbPHJ8klXGjWCU2Tec8nFXMptqA/blP3JXO1gEPjS1RaAadcizv2P0JvWEOqEgBBKElYBtg2yjSp+IpcrhtRmMEPJcIQmCikAmWYBGs3kw9jiEiMk0mX3liarLBxlE8INHI9mJ96GFMppBA0pFwRQPYlbGKOScO7sRJuOBenLxWhsFBZsb0RCOYqV8NJU4aowjxBuUQqFmH2UshOz8Hr7scXBkpK1iUN+vYOsNTsBMiJiEXWFYjAu371sXfkCwO/bxhnaC2O1wIZEgrjAwuXNU3TNE3TNE3TNE3TtA/fbVuCbN26dUxMTHzgxz158iTf//73uXTpEsVikX/yT/4Jd9111/J+pRR//dd/zdNPP029XmfLli38g3/wD+j/FW0+7pgrJ9yvn+hbrWGzF0imyh7llodh2wxu30bEb+EtzJBIJbEtE98wOTFZZnGphK8ECgMjCBifK9A70Esu7lCod+6IT0UsTKH4wrY+MnZIQxqcnyvTXiwwf2mMUCriUYe7hnIMRiRZt4A7MsCia/Hjs0UuXzOR6piCz67Nst2sIgQEqSyeWD1UcGUA507jzc7gGRauAe7QMNEHH+X8XIXXp8rUJgNibhebN2xi7Nw86kr48paWH/Ly5SJf3JSF8NZDGCE6n61/k5XSbFNw7SffisaJPfIY/tHX8S5fQIUhdt8g7t67aWZ7bml5IqUUweAaovvvpXXkteXlxkQkSuzuB2nnem55/NoHTwiBFFan4klI5HtdRu/GI7+nZxl2hGDqAg+b88Ti3dS6Xd6criIV1FEkI0nirk1XMkqpFZBNRMnGJROFOk9O+uztTbFj23qOnrhA0w/ZkEtizrYJEQRSoTIZDELEwjzD+TRiZgwRi5P+9BcYj/Xy5NFpKs0ldqztw5prkY06fHl7L0njyjJgUnbqAFf57kdFwJe29/HEyTlq7avnZV8qwmc35HGtGyt+BJ1zMpAKQ0nkzAS9UYM9G/NYM5dJTM4iW0lczyMcWd+pTpOSiNE5nw9PlijWPWKuxd6hDGvTFsZ1VTCGYeC0m4hyEQCVyuBFYstLGbphgDh7nMaJQ8hGDTOexN25D7l2802rlDRN0zRN0zRN0zRN07SPj9sWwPzWb/0W/+pf/SuGh4f59Kc/jWl+MJNL7Xab0dFRPvvZz/Jv/+2/vWH/9773PZ544gl+7/d+j56eHv7qr/6Kf/kv/yX/7t/9OxzHWeWIn1xSSkayEV7ihl7RAIzkYmQjJgThimBmyU7SMG2EEbB27268XzxJrbAEQqAScVSpAHc3mfC7eOLEPJ5pkxhv8OCWfgI7wmKhwrqBHNmojVSKX9s5wNqMQ8KU+L5P3FBszEY5dnYO2zTIJCN8adil+crPaBQK9OTj5Nat5fS2L3CxLN9qwY0pQ4L5OX569iTp3f1k33waq7uX2P0P00ymUcKg7AtKrQDbMOipFllScQ4F3SxVW8SjDvvqJiKa5GBL0jWUJisg4lgcKwbMqQg9Qtww4Tu+VKce5Ii/i3numCnZ0J3g+HR51f07+lME1/R9UUrRiCUx7/0c0X33IKQkiMZoKN5VbwhfGBjb7yA2urHTV8MwUOks7Uhc32X/IfKFzYVim2PTRfxQMpSJsmsgSc5+f32GpJRYw6Nw9PVV91u5LsL4jQ3eXenjv/wKjR//FK/ZJNKT445Ill13PMj/71wdv1ln79Aga/IJLi81ODtf4/BkEYHgs5t7cC2Dii8ZXr+OPd29LFaazLQln9vax89OzeHaJrZlofLddHV18eCaFNXZLLVt97JgOvz01DyVUJDI52gaFmlhUGx4PHlmgce2d90QbFxPKUV/TPCbdwwxX/eptwPSEYt8RGDRCXAMo1Nd8laQErcUo11xzs/XEO0WPVGDu6wKxR9+D5Qim09Qe20KM9dN6nf+TyrJLIZhcLoY8vTpueVraK0d8NOTs+wZznLPUAwhryxPJgTO+HmaB3+ObNQ7Y4hEidx5P/7oJoQAdehlmqeOLr+PsFqm8dKzRKoVzL33rFgeTdM0TdM0TdM0TdM0Tfv4uW0BzH/6T/8JwzD4L//lv/Df/tt/I5fL3RCACCH4N//m37yr4+7du5e9e/euuk8pxY9//GMef/xx7rzzTgD+0T/6R/zu7/4ur732Gvfdd997ezMfYxlHcWBdnpcvLi1vS7gW63vTRGyT5y6UyMdt1mSjpK0QwzR5pRSy7q5PIS+cRJ46TFBYIppO41gmwvcIi4tMPvM03Qe+RNuO4oeSpVqbp09O88CmXqyhDBLFSMZlYzZCd2ka/7nDSCWJb9wOmRyfGoozftQh8AIeWZ+h/KNvI32ffDJCImhSz/Rw+NApnP5Bwmi8M3m5NE945c7yM5WA+1IZgoU5mk/9APvL3+TpWZ8T02Wkgowp6Y5ZHB73iZWr4HuUKnXGPZsDCVDRGD8cL+JLyEZttvWnGM3FKTbbuNcFLX3pKC0pqAUGrmWQcXjHahgZhtwxlGK80KDSWtkwfH13gqGkDerGRuKhlIROpPPDNXOx72aZIiklzWgCoolrNyLEe6uU0N6fQNj87FyBsaX68rZSw+PsfJWv7eqn63225fGzXbgbttI+f2rlDtMkctenaJorG7wbhgHHjtA4fBDldRqlVKt1kiEsPfcjvvSpX6OVzFFphfxfz51HCEEmanFgTZ6xQp2nzyxwYG2Ob785yWg+RiZqM5SJ0p90qLd8fu+B9SzV2zTbHkOZGKO5GM9cKPLjyyYCj4e25pgLyyQTMXKpCAs1j4plkHBMgopHsQ35t/lMTCFwS4sE507hFhcZ7erF2rCFViSHVAphGPjT41gnjhIuzmFl81hrN9FKZTmwJstMuUWz1GB3d4TiDzrhSyYRIdquglKES/O0X3kO95GvU/MlL5+f65TPXPkIbdNgTcLCqFXwwtjy9cJdmqP23E9XNO6SrSaNF54iHksgYnFqZ45f2SMQfYNUetfRxMQ1FH1em9D+1bpJQNM0TdM0TdM0TdM07ZPmtgUwiUSCZDLJwMDA7XpJ5ufnKZVK7Nq1a3lbLBZjw4YNnD179lcygBEyZE9vhIHUICdnq7QDyVA+wcFLBfqTDrZlMF5s8eZEiYe29DCSElSaPq84/XzlQIbG//h/k+jqwqxXCCstPGHiJNIslms405fIR9cyP18BFPXA5sdHfb60c4DtfSm2523UL56kfv4UkdENCN+n/rd/jgp9otv38ve3b2bMHEUcO4gZtchmIzitGs2lJYxoEuk3kEvzGENrwfcJyqXlxZaKzQDDdQkBWStTmZjk5EKUt3re96ej/OzYJJWmx4Z8F4OiQVdfD6neXt6cqjBdadH0QizLYqnW4tCEZCAdIRdzqDevdu/eOpBhqtzmbw5NEoYSAYzkY3xmQ54YNwYo10oYAb++q4+LxRZn52vYpmDnQIrBhI21Svhyw+9OCCKNKmp+BtVqYuS6kPke2sZtO421D8BMPVgRvrzFCyQvjxX5tc05eBcN3a9lGAbl0CbY/xCRrfuJnXiNcHEWq6ePxP77KLixG/olOY0azVNHcGRAxLEIWz7NZhtDCAYScTaMZPjORJuz83XiyidQBqW65DtHp/nmviGeOTvP+cU6G3oSeIFkoljHMQXr8lEeWJvCViHkoggRIwxDDDMg5Qi+vmeQC4sNDCEYzMQwhOD0bAUFpCI2pYaHbRpUfbUigDEMk6YUgCBmSpxLZ6i98DO48r782Sk4dZT4Zx7FG1qLOzNO9eVnaFauLF04fhGOv0n8gS+QGVnPN/b0MzXlkDx5EDPqkouaxLw6onK1Wi0Yv0j0zFGWfIf6uWmMRAozm2dNLs52bx7vjTfx61WCc31k77iDsH8Y7+ThFeHLVQrv2OtE99x1ZcyC9s67+UXZ5sLxRUIpMYRgHV08sGOI6DtcVzRN0zRN0zRN0zRN07SPrts2c/vP//k/v10vtaxUKgGQTqdXbE+n08v7VuP7Pr5/ddJLCEE0Gl3+/7X/fhwJJemLwOD6FC1l8uyFIoPZKG9OlCg2PLIxh33DGU7MVumO59jYk+CpE0UuuQZOuo9eWaO6tEQgDRxTIA0TISWqUcOOB5imQRAEyHYb4fsUGx6lZptCsUXs/CmcoTXIiYu0Tx1DuBH8RJr2xYuYr7/Cxi8+Tqs2Rz2o0Jit40mFZZrEwja5VIxCvU291sIMfGTTx7VNHBP6Ew7hVAOAQAmWpmZx4utpvtWU27QpNzwMIdi0tp/phQovnVrkgUiWZ88uMtKVIBW1afidxuACODVb5bHdA5y7EsAMpKOcW6xTbQVEjU6yo4DLSw1+Eii+tr0HA4kpQN6kIiZmBOzsstnd24WAK8uOBZ2mEm/DEAJ38iL1nz+53MsFwOrpI/bpL9KMxN799+AT8F2GWztfr/3/h/l+TdPk7HXN4K81VWxQD/MkVunF9E48YfPmVJXj02XagcSxDXasvY+77ktgWQqnpxdmZ294/8JrodotLEPQl4owHgQIYWGaBoaASq1Ffb5AUAtRoSQMJbZtk4kmeOHCEhu7k1xaqrO1L8FizaPS9Ki0Ak5Nl9nTG8cU14UQSpGN2vziwgL5RIS+pINtCM4v1lCqU1HyVhenUEqKjYB1KQdkSCkwefNymbFCHYFgUy7CjoZPwrRQ0rv6GmFA6+xJRK6PxeeewvI9TGFgoDqVY2FI48WniXX3oSIx9vY6eIeWaMsKstBkObkFTNclLC4RLM1DrA8VBISlAj2OZId/mcIbryw/tj0bUPvZFIm7HyDwrhnPdcJycTk8FkOjPFswOT0xj1KdvjSWobi8VOOnZ5b4yrY8pgzeVdXb8u/2I/Cd1zRN0zRN0zRN0zRN+1Wmb51fxXe/+13+5m/+ZvnntWvX8qd/+qd0d3cvb+vr6/swhvaBOz1TYaklef7cIoYBpmEwW/P54Yl5HtjQRRuHLb02RyaTFA2PfCxBfewyoVQIwDINhJLYgY+7dj1qySGec7CQEASUSlU25SJ40qBdLtIVi2GnMtR+/iRGKsuiFWex3ESViwx15QlffI7U9t1Ez53AjUdQUmL39mGXZtg1cgdPnJihjUnUVEghaPohtuWyKWUSmQghFqPhhYhUGtuMIKzOhKVh2wjTYPdoN69PVllYLGIATT/Ak5KZSouuhItrGYBF3Zd0JSP0JKNU2yGBVGzqTzF5dp58InrD5zhdCzhdDLiwWCdim+wZSrOhO0Hc+WBOMX9mkuqrPydq22BfUw5Qq2Aef4O+Rx9HWO/ttT7u3+VbOV+v9WG/38ikRyx28wqXRCJBf/rG79jb8YKQHxyf4cxiG9OJIERILZC8OlWnoUy+vmcQWP29+0KiEkmU55CtVbCHelhshizVPQa6crxeaOBIH9t2CJWPjUEYBMhWg/lAsXsoTbJmUWr4FBo+mXiEQAmwHJxYnP7Mje9lb6zFmUKbaisgUIJ0zAHRCXxiroVldiKYrb1J5hsegZ1DoXji5CRNX4Ll4kvJockS51uS39j3IOljLy4fv7lhJz9vxFl7/jLVmULnc7cMhrIxku7V8yTaqpNdux4VBjQ2bcN/8yUMw2Q5ATJNzFwXKgiwDINu2SSdjFNvttmZi1B55mdYrgt0QttU1CXmWshTh0ls2027uLDq78vI5on09uOnM4x3r+PIwUnkNdUytmNjR+KUPCiFDlI5lJs+qajFUCZKPu7e+pfjJr93TdM0TdM0TdM0TdM07ZfvtgYwvu/z9NNPc+jQIebn5wHo6elh7969fPazn72hJ8z7lclkACiXy2Sz2eXt5XKZ0dHRmz7vscce48tf/vLyz2/dPbywsEAYhvT19TE7O/uxb2JekRaT1ZCfnJjFCyVCgG2amIag5Qc8cWKGvUNporbBo1vyPHl2kd133w1jR1BhC9MwkKFC1CpkR7dwWCWYqTRpqc4Ebcy12bq2n9HWPDN+Gsds0RImcvoygVJU7DizhdryeKZa0BMxyY+ux8vkMIIAIlE8N069WCbDWe7bfxc/GG/SRpCNxYkbks9tzOOceJVGo1MBI50o1VQXlbmryzyFaYdUOkV/PslYYZ7BmIlQgrRj4DoWhiGYr7ZYm09Qb3XuXDeFRX/cZEc+gwgDFpohdtCmKYOrv3sBzVAwttRgTTbCTKFKIBXnppfYNZThvuEEhgrf1+9JCIFz9iSNanX1B5w5TrhtD81Y8l0f9+PyXe7v77/pvrc7XzsVRle3fxTe71DS5Mjlxqr7BrMxaNeYmSm9q2OWApMjY/OECIqtkIVKi1BKEILLizU2dcW4a233De9dGAaecpDZPloXz+Fke5maK9Jqtok4Nkajih1xqRUnyPUMMtXyEIBUCuV5JKMxXFPw+JYMXDiFdELs3n5O+lGaQRuvUWemWUIIgdusw/Q4wewkRjzJt9Zs4pVGhLGlCvetzVFr+UyXmxhKIkPJ5t4kW3tinJwq0hhOcmi6ykK5AYag2g5ZrLUJ2m0sL2RkqI8Hh9Yjzx7DyHfzUiPK0QvTrNnRRxAEWJZFreVxYS5gXVesExADolKhODMDQGzdFqzt+/DHL6J8DyMax0gk8Wcmid7zaZqXL+G2G9y76T6ePDJPpG5SbtTAMFECehIRDOnTaHgYgGO70DeEsB38WgVvZnJ5mbT4XVspKANj773MzTYI5NVrhBACuvuYrAXkVIs3xwucny0uF+UkXIsv7+inywnf8Xv8YX3n3+581TRN0zRN0zRN0zRN+1Vy2wKYpaUl/uRP/oTp6WkymczyHbljY2McPnyYn/zkJ/zRH/0R+Xz+A3vNnp4eMpkMx44dWw5cGo0G58+f5+GHH77p82zbxrZX7/r81iSWUuojP2n9djxh8/1js2zqz+JfmRRUClp+gGuZRB0LP5Qs1jy+c3iaL2zt4XM9Fub5JomHv0L1qR8QLM6DFRC78z6idz/C2RNFzHaLqGWhkERDyZ6uHNbcRbrWJOhJRWmiAAOVSLNQay2PR5idKVGBolWtI9dtpfTi84RhgGFaxEfXQs4klYzype1pAqkYjg2QuHCU8stPUYsIMo5AuBHSn30UaeZhbn75+FPFOl/ZO0xYqRCdu0zQaoJhYAyk6XehLgQNJRCiM8GZjzv0Jx26HEns3DHax97E3LSf8PJC5474ZBopDBSCmXILqRRR2yC8Zumio5MlNnfH6Xbe3/dECIGslm/+gDBE+d57/j5+3L/Lt3K+Xr/tw3y/AwmLoWyMyeLKEMY2De5dm0MF777nR7kVIBVUPcnsfAnltTv9RwyDthvl9GyV/kwc69r3bphcLEumK03WbzuAUypTmJqmrGwiMRs34hDds59+0yPwA+LtGvlUjMVK80oDesWO/iRboyHBMz+meP4C0KlgObBvL9ZdDxAzQ8JQEa0UaTz5d8jGNb1vjr7O/fd+lt3bdjBel+wbTPLg+hx+qLBNQane5uRUkZhj4WHy0qUixaZPqKDU9HEMiDk2Rujx6niRwfWbWb84Q21gIyfOLIIQtGJphGkuv6QvJQ1PknIAIRCZLBYKq1pGBj7RL3wNceQ12uOXkGGAkUgS37ydoFolvHiasFphtFjksTsewjEFTUPguCa5hEvcFqAUZhgg56bxpydov/4iQWERe3gt8T13UT97isiWHYRDa5FSciEzSizSwh1votothBtFJtPMhhYRBZeLTXYPpq9dEY1aO+CJk7N8Y3cfzi30joIP/zuvaZqmaZqmaZqmaZr2q+q2BTB/9md/xsLCAv/4H/9jDhw4sGLfyy+/zH/8j/+RP/uzP+Of/bN/9q6O22q1mJ2dXf55fn6esbExEokEXV1dfPGLX+Q73/kO/f399PT08Jd/+Zdks1nuvPPOD+R9fVzN1HzKTR8/lGRjDoVaCz9UhFLi+wGJiE0iYhOxTSrtgPlqm9i5g8TOHUHtuwNjzwFijoOSkvk1O/jOU4fYONTD3gPrWChWcUyB6bc59vpRNt63laH2EpboIjK8DjuVon3+FH1Rg0YkSqHeRkWixB2DiCEpTk4ysdRm7aNfx6kXcUIP0d2PyozywuELOJksgeNyXgh25NYy9JkcSdEkno5DrodmLMFGZbI4mObEdBmpoNby2eAvMd+sYKEIHRchYHJsii9sXc+PL1QwHItszMGJGziG4OHN3USPH6Rx6CAAmcIU3ckU83PTmF4b0dWHF0LTD0lHbAyuzEtfY6zQpHcggpSrNeO+NUopjHzvTfcLN4Jy392SVdqHx1YBj2zOc3YpzvHpCn4oGcxE2TuYImeHvJd5cts0AMH8YhHVal7dEUpUo44ReJyerbArZxCGnWqLRd/imfOzHJkqAfCbuz9Pau0CidISTjyOn+9lrjKPPPEGn9q2k5dPTdGTC0nn01QDSS4Z5Zu7+2j/4C+5MHYJ6LQysg2BdfEU6zatwc9txkbRfuVZRKWE2W6BlAg3Qui41F9+llR3P0OpLg62PMaXalxv+1CO45NF6l6AbRpMLNVJOCYDVohVLUKzQXc8T0pEaW/cQ6sV4PsBZr6bE0GU/Tv2UDtxZPl4rSAk7Vo46zdjOBHUMz+iPjUOSiIcl9gdB0jtPYDw28hKieDyRfxjryOX5hG2i5qbouuJ/5vEo18jnXUwnQBpRzrnKSBnp1BSIQ0TmevGTqRRrQbB2DnSX/0WzXiSAIEhBAt1n6WGhL4hFmseoZS02xKQRB1B1DZQq1w7yk2fQjOkL/Luvyuapmmapmmapmmapmna7XPbAphjx47xpS996YbwBeCee+7h0qVLPPHEE+/6uBcuXOBf/It/sfzzn//5nwPw4IMP8nu/93t89atfpd1u85//83+m0WiwZcsW/vAP//ADX+7s48QwDJbqneoTLwjpjVkI5TJ35c520xT0JFxiBMwWauwbyuA2a6iLZ5ittuHECbo2bqB18jCtsfOU0qMo02QqsPF/9gymY+MnsnixJKKrH5HOYT77U9RdnyKcmSC83MLu7iV443Vc22V4zTrKRoSegW7E9v0sXp7AbNWZeeUlesyA8tICZjqDuOdLhKU2rXIR+kdYMqMcDOCYneQbe7fSICRpC2whiRBy51Ca7QMZglBiAF2vP4WbyJKNO3h+Z2kqr9Vk9vxFHtuygbIZIx2PkHVgNBuhzytSPfr61c9t/DwP73mAH/g+5VIBO5NDGS5J1+IL23q5OH9jlUrwPoKXtyilEH2DGLH4ygqCKyLbduNF48vLG2kffY7y2dVls62rm1AJXCGRMnhP4QtAPmISswzajRuXNktGHVSlxIQS7OnKEYYhlu3w0oUib050msFHHYuLTYOThRimiJPyLdwF+Ey+G7O4xCDH+Ma+ncy3oem1yEVs1vTZtJ/+AZXLlxnNRhGGQCnIx21ipiI4cQh7dAN2vULj3CmCuemr31EBZjqL0d1HOHOZSDrL13b08uLFAhcKDcJQkYzY7BnJYwpBGFrsGkjzxmSZiGUwQp3W5Slsw8AANsYUxe/+L7offhiZSOH2DxIk0sxUfS6N7GZjKk3l0KuEnkdix25aG7cT5LoJX3uaYOoyyx98Ms1My2B2qkqj2aLPkKxbsxHjxCHafWvw8v3Yfgvn3BG8i+dI7L+X2lM/wFyznlAYGF4bv9Eg/plH8Lw2/oadhDLAmpukXa9it5sE8RQAUkp6kg6HJ4vcszbHT0/NU2xcXTIv4VrcuzbLhbnVq99agT7fNU3TNE3TNE3TNE3TPupuWwATjUZJp9M33Z/JZIhG3/1d/Nu3b+ev//qvb7pfCME3v/lNvvnNb77rY39SKaVIup0lm2YWy+zpS/CDE7MMpiMYwugsp2VIduUjXBibpnu4n4QNIvRpeAG0W1x4/RA9oyNkd+xFjIwiFi8hojHM7j4asRSz9YBGVYIVMF1u4d73a4i5S4TZHqzFaZyhNeQH19KcGKfpxJB3fo5feC4nj5zHVi5bt97DTrtB+2//GyrwwPfoMTxMy6JYbWBNTiAH1lIIFWvyGZ48M0et4fHooEPEgFdOTzG5UIZUhnx/L/uGMzQvjiODC3x67wM8c2KCMOxMYFaqDS6cOs83vnw/m0Z6mZhdJFQKGk2EVFerWsKA1NEX+MaGXcy5g1TTKSK5HAs1j1MzRZrejb1e1uRi76v65S2tSIzYw1+j9YunCBbnABC2jbtlF2zbjRACT1goBTHbQFxp6H1tDxTto0VKiUEnHJTvc3WoiBHyhQ0ZTl+eo9poL293bZOHt/Zw+dQ5tu7LLC9DVQkEr44tYQhBJu6yWGvjWgYbu5M8cXKWqG2SjdqEKspXHvoK8uVniL/2NA/0ZpClIuHWfZytxTDHLhBWSlRqBiKeIpeMEDUVKIVs1hGBj1mvEcxOsSJdUhCWilhuFNuNIs6fhDPHeDidoz66gyDXy2Jo8eKlJV6+VCDmmHxj7zDzdR/Tb9EenwHV6UUz2JNhXS6Cv+cu2tUqqS07uCstOD5dotTwOF70mc9uZc/XtmBYDj+ZrbIw5mOfPs+IzHFg76dJHvsFKpPnRO9OXj+3QFc2xMrmOXN5kvF1I3R/+f/Fa0fOUZ6eIZroYs/D/4CdSQnnjhF/5DHCShnqNWzXJXLHvUyl+nlzssTUbB3TdNg2vJ8tZp1YvQa5q9VsfXGbmGNxZqbEZzfmCZWg1PJJuRZb+1I8fWqalr96D6mEawH6/NY0TdM0TdM0TdM0Tfsou20BzKc//Wmee+45Pve5z+G67op9rVaLZ599ls9+9rO3azi/0pRSDKQcHMugUmsSNJp8cVsv55YatAPFup4k23viVEsVCEPqgSSaT+F29RCp1LEMQSbqMH3xMmNnL9G1vkC2ewczykIksoyV2gRhCEHAlp4MUdvgZzMhrUY30QpsHR5ko9XELS9xes/DqGSWb58tYYZN7EKFwPcpFKuMZ6M8+uAX4em/Q/o+UUPyufXdnC4lWKy26e2Lo6Ixzs9XaQWSrw+ahItz/Pc3p3AMhSGgWq5RnFug7W/ly115Jo+fwH3jeR6/4wDTbUGpFdCXcFgTE8RMxU9OznL84gxBpcxw2mXPpv10nXoFCYSGgfJ97FNvMGQYJB7+Gs2kwhI2h8dvnCQd7YrTGzU6vTg+gN9ZI5nBeeRxIpVSp09ILI4XT1GTJsenaowXW+yLtEjPXSRdmiOSShDbvAMv10twpTG99skkpWRDe57fuWuYE/N1luoeubhNzoGxMxdoNtts708uLz+GEvQkXRKuzZn5Gtv7UxybqbCxO4lrmbT8kJopODtf5W+8CA/s/QxbspJIYZ6wWqZdKzHUO4w/MsJ8qYhpCLqSJvGEvRz+meksuBHCahkjlkDWqyDEcthkCLCH1+Ife51msdDZuDiPe/EM5cBG3f8lFqqd/i0NL+R/vX6Z/23/GvZnBW82FhEC9qztpbc7w3NHLrBQEUQck/1TdZZwiEdcelNRlip17nEqNOqCJw9dwoxEMNNZQs/n3OwSs8UIv75lP3U3yVTNJDa0htemy6h2m91rN1KLOPz0yBTdiwWEE6UeCn5xYpyF/gyftlyE52E+/DXswMdu1Bgbn+e7r40tV9kBvFSpczGf4tc39WMYBg1pUmyFSBXy6I4Bjk4WOTVT7vSgitjkMy4DMZPuhMt44caqpsFslJwL6CIYTdM0TdM0TdM0TdO0j7TbFsCMjo5y6NAh/uAP/oAHH3yQvr4+AGZnZ3n++edJJBKMjIxw8ODBFc+7++67b9cQf6UkjIBHt/Xxs6OTFCp1ztVKPLi5j6onabZ95qdmyTSKbInYDA50cckXJHfuJz8/TSrqcH6hRig7vSfak+Pcd9/n+NGFCrNOAr9ZwhCwZSjH53cO8ecvXqIsBQlDsd61eO7kDK/FIzxy115OHrtMKQalmocTjTCQydBcWqTphyxWmkyM9LAmkcSOxSn7YJ5+hb3JBE4sjshu5F8dnsOXMJCOEJ0d4826Tb3tI20DxzQIpIJWi9mZeeobthE5c5pmoYB69qfsGspj2jZyuoF71wP81ZkCxWqL1sVzKN/jTDXD+cV5Htt9P9GDT+PZLqZpELEMbNtBJTsVBaNJk6/uGuSNiSILtTauZbJjIMXWrijmLTbJvlWeMPDSueWf29LkByfmqTR9Hk42qP3o+9TabWaEYG0+TuTCGaL770Vt3cvq99FrnxQqnmRk4hQTzRiNUoPinIeRinLPcIo1iRx9QYUmKeakzemFGrZpMZCxGMnFiTkm//dr41xcrPPItj4Wax7nF6okTOi1Qzb1Z2k1ihQPvYlXWCKWjBOdmaJr114SZ15H+B4slTFi65BCAAJn1358YSBnp4nccYDqz5+i6YX4VyrPnGSaeCqNf/kCmFf/FHlSsLhUInHidUY3PcB4qYkXSPxQ8deHxvlXWwyi/gRuLE5V5fnLn75GqCCQCkM0+dnJGXoGeshETCK2zW8kyjTHL/NSIw3NOl6jjr+4RLS3l4YyCaotLlsD2IkMY4tlTk8vUqm3MZKCDX6an56doT8RIUhmMabGEJYFiRRnJhbZvW89IwNZGqEEYaISWQ4uTK4IX94yXW5xPoygyvDChVla7c61wTYN7lyb5+/dNULbD4nZgqSlkGGLhzZ28dzFAmOLNaTqhFYj+TifWZ/DkB/stUX7+DFEp8rXMIwb9n0QlZeapmmapmmapmmapr1/ty2A+Q//4T8s//+73/3uDfsLhcKKx7zlr/7qr36p4/qkE6ZF2YemL4mYBmkHkAFKKYZi8M0Dazk5VWKhGTJb8RhfqvCIs0TjpecJ2w0KUkEuxfr7P8Xx1Cif+vpvcPnZZyg1CwjDIDmyBm/33fzk1Dw7uyJsyXQTjqQw2g38SpkXzi1QVYJPj2bYKEskGw1E0qVkxVgMTLpyKd4cK4Mbww8lzVSeaBjSLJeRwuD0UpNdn/4CseE1lI4fZchsY6S6MNIpXq5KYq5N3Da5u9shmGwwtmgShBLfEFx7e3hQLPCLZi8P3/8Zpn7+LO0gxKs3cAyIbNvFVNc6Zk8tYRUWUL4HQNioQ98Iz8002BfJ0JidQzkOtmWx9WuP4MUTEIYoGdIfgS9vztGWYBrgIJHvcYJUCIGlJEYYENpOJ0S6yePGyz6Fhs/WtIn/8vOE7c7yU1Ip5qttRjIuzTdeITE0SiOZfU/j0T4e2ok06VSCB+vTLK0bwY5GiZ45BK+cJBJxaGZzFKw4hR33c6xsMVcNuDjWIGYbfGnHALZhUPdCfnB8hvtGc9wxlKbbDBH1KhXD4XIlJNUIqBfriFKDrr4e+i5fInHPp2m8/Byq2elPJCJRonfci98/jAKMWJx2swn3fh715su40RjJbbuI9PYTXjiF9AMM00TSqdLyQokCGuOXWLv9AOdSEcYLDTIxm239aeZSUZJbthNNJHju8ASOZVL3AgzR6W8VWDanZqv81oE1xGtFFn/+DM6eu1mcXCSUUPWCTpgxN4edSiMaNVIW5JfGODB1gXsyXZTWDfLdWTBNg3IzwDYE3V29mNUSKgxQgIjGKOUH6ckll3vblKXJrJ1COEWU1zkXFdDCJMz38/JElYVqi6lyi+FMBEco/FDy0vkFUtv6WJ8SKKWQV9LSCB6PbsxQGsnQCCRR2yBjAzp80YBM1ObQTKfi7Vq5uMPevg9m+UtN0zRN0zRN0zRN096f2xbA/PEf//HteintCk/YvHSpzJm5KqHsLMk1nIvzmQ05YvidZa38kMPjBTb2pvibMzP8/TUGSz/6ETKUuI5F3LVp1pvUXnmBu7+Y4cfNHspbP0/35iaGYXDeiBIL2qxNCzBNjo8t0FTQarTYNdzDmYkKj23MkDz4JNWZKTAkqlbFjsWw/49/DLYLVFFBCKZNOTQQ+X4SPX24QjHQEyXWOE/tf/5/8FoenhJw4jCp7bvY+ehOzrVszi/WGKuFrFu/hQQFlkq1K70uVt4VvNBWTK3bQfQr/TjlRRIZF6eriyDTxYsnCxhhAGGAle4EFUYsTl3YzKoI0f33Y772C4yhNQRrt/B3zSSfDwxi4mpdiSkUhmHihQoME1uo5Z4bt8qRIcbkGN6JQwTtJma2i9iOfbS7+hCmiQKUlFiBj1MtceZEATW7xFC0i+b8XOeW6Cvq7YBAulhCEs5MIFK5dz0e7eMjVAo2bifZ1U1sagJOH6Z97hRGIk3oujT9kLHL45hzP2DfZx+nFVhU2w6lpk+56dOTdCk1fYYzUc4t1BhKWAwMJDlbTzA9XidpZdj7679D/vJpGq88T63RojU/j9mqE7nvM9j5XlRXD2E8hReNI4TANAyim7dT/19/hrAduh79KqLZpPzSs9TG80RDj+rlMdJdOcyevk4j+yvL5SmlEEDChgPr8kRti2fPLXBpwSFV8YhlJOu3bmT83EXaixVMU+D09FFzI8QkLNY94oZBaXgzEV8SCouq18IPFUIIGn7AQDbNA92S4Cd/w5wwKM2XQQisZJLf/fyvUc5FGU3bLNTayNDEHR6FSBSkRAkDI3b9JLcitByM4XWIdhMCn4YyqWFTl4KUF+JLRcsPuVxssi4Xw7wSFL82XmR0Zw/GdVVzKgxIW5C2AKRedkxbodDwma22V9kTu+1j0TRN0zRN0zRN0zTtRrctgNm2bdvteikNEKbJCxdKnJmrLm+TCi4v1XnCD/nq9m4iBixVfFKpGIFpM5qPEx8/TNsQmIaJVJ3n+KHEDyWV1w8itn+eY0s+E0Wf/319hE0XX6Nx4Swy8Olbv46H7v0CPz46SapeZEMsy84NDt2FCabiUUQ8hlkvE9oWXqtN8vJpWtEhtqwf4s1Lc2QjJi1lcK7cou35ZKI2f2+LzdKzvyAMFJFoBCVsyHWz2FZUnnmS8tD9VNsBl6uCJ+YW2bJukJmlCnajiilAKImbTBHLZLgz3iL76pOE+T5Ys55wqItGGGAJgSEERhgSLi2AbYNh4c1MQRhid/dgb9vM2B0PMWGlWSy0gRZzNZ+1SUCYFAKT07MNFmrtTvPyMGQwHWF91saUqzfKNgyD8EpIZCIxZQhvvkTj1NHlx4TVCk0nxlyY4EhF4gWSLd0x1jVmiZ05hDBGkI06quai6hWMeBJ5ZTmaKytBdfgBQggdwHzChUAj20M8Gqd2/E3I9xAohUDQCkIsQ9CuVuiqLeCIPMOZCDHbJBuz6Um6JF2TWssnl3Dpz8X4ztE5WkoQt2AwHcFxbGK5jeS+vJbRwhjBK0/iTV5AlQq43/z7VNNdABR9gzOzVWZnFskYATu/9P8k8cP/gTE7ReO5J1CmS2BHCLbspHnuPJFSkagbQeS6cAHbMIgMjXDMt7CEz0Aqwt8dmsBUkrRh4OZylAP4wYkZHtu5jvnaafxMnkkZZWsiQj7u8trlEm9UitgFOJBLs3FzjpdePYmkc2ELQticdak/9wrDEZtCK0C4LoYQDDshyZe+x7oDD5KsTxOs28KCZTE2V0WViwT1OqZl0DsoiYVRmtkeDMMg47cZTVlcWmwjo3HaSnBhoY5CEnctRjJRnpqtAOAFkmYgSVz5K1xt+bQlRD+cr46maZqmaZqmaZqmaZr2S3DbAhjt9ip5gnPz1VX3zVbaTNQUZ2fLnF9qYpsGmwdi9MQdgvOLKARSdao3lFK0AolrmQTVCrbfZlt/irvSEvf577NUKWNemeQvnz/PSNzh/jV3kF0qYT31t6TbZcrnz9C3ax/ia48zX66jWk0YO09y6hzbDmwgXvaYijss1FsseQpfQiLisDYXpXn5IouBQ7p/FNMUuI7NXEtRqLTxyxPcu1Px5qxPECqyyTR+vcqmDcNMHD2ODCTJVBJDBvQEVXqWChROn8QyTrN++hSxR76KH0sg2k129yf48dHjCNsB3yNYnEZZFjKUrI1I5M/+jpH127mYSi5/jpV2AOkIR+bb/O3RWZbqV+9C3jGQJpRQawfs748gw5UdWJrYnJ1vLgdkm3oS7EgKjHOnVjwuXL+dZ1ppLjz7BsbIeqRhMj+zwOvleR7btJFtgcHYNJSURTIex283EdE4ik4zb1uAUmD2DdL+iCxHYyOxy0VkcQnhuJDrohVN6HDoAySbdZTvoTCoeopCo0VbghAGubgD1SJuogffD3FMwZGJAgfWdvGdw1MoYEd/mqfPzNEIJb2pKOtzUeZqPn9+8DLpmEO/q+hR8Kk9D3OnKODYFpWnfkj8C49x1sjwxPEp7FqR7W6bHtmkfnaC5Be+gVWdR+S7icWSLIgILWmTGR2lOTVBa26BwErguA5DvVkKu+9masljMBvnzYvzyFqF4WwcY+oSXhjgDoxCIsWphoG5ZiPnlpoMpCNEbJPvHZ1mJBfDCgV2rcWzhy/wtUfv5fKObcwXKgjfIygXyYUNgsBjNpAkoy4RO2AwIjBmL1NvtbE37yQ5O8bc6RNs3rkdw+3hbNPHT2U4sGMU3y9TOXWS7E4Hb/wCrROHuXP7vUzMLOLZEayuvuXfyWguhmMaeOHV87AdSBJWJzCNOxaOUJ01yzRN0zRN0zRN0zRN07RPBB3AfELVPYnEAKGAayb1hKDQDDk2XWauVKPqKc4v1JmrtdnVn4JECj+cxjQElilQChzTwDTAt1zGG5J0xmCHN8/5YglDgGkKUBC3wD35JvePjrB4+hVaQUjCEnDX/Zzo2cKR50/i9w1Tqfhs6tnOg5mA4eJlLCfD6L0beOb8EhdLbWzTYGNPkkzUYvHUCcqlGpFslPn5MuuzEXKWQwkDP5DgeQxno8xVPV6f96k0Db68Jcbue7ZwebGGk0yyVlaJLk7QOHqSvmSEVMTCrZXwX3gSlcrhzUwwes9DDMUtZoII3vlTy59VamiEHTs30JhLIC2bu7tdfj4V4oWSXMxmtql4+tziivAF4Ph0mZ6Ey0K1yebuGPFrliprYvO943MUrlm3f7HW5nRQ59e23030yC86G02LqUT//5+9/4yRJE/zO8/v37SbaxFaZ0RqnZWVmaV1l2g1rWeGM9xZ7pLcWeJugQNBLHHgmwOJAw53WGABEkcueSSH3CF7pqdnqkV1dWmdJTOzUkZkRoaWHq6FuZu+F5GVVTVVxWmZLcY+bxJhFmHxT3dzD+D/8+d5mJ1b2V6O6yBiJkGjSqPV4d1ygnuyAWP9WS5vNnnw+J1UX3oGoYcoikxvQiMMA9Thcbxs4Zd1q32MKgmE6xCqGu6nzK4xPAfv9Iu0Fq7zwU0pNB3zroewR3YQRCHML4amE0oKa/Uutc72fRYiUes4VNoSB3sK+FaICEN6EyoZ0+DAQIqpQpzFUpuW55M1VbK6tD1QXpKZKVaJxzSCEIy4ScdTeHWjxPChHfS89RSEIc1ikZcbLkp1i3sTXdyXn6JWqQBQN2Ls3TOBvv8orbPvoMWStDZWcO99Aq1rweWzBLJKtTBK9tjt5AaGuSPVQgoDpue6TGUNYu0SnrddUSaKaxT6J1msdulNGtQ6DR7f3893z62SNrfbhpmKwlC+wKEd/fzwwjq7B3PkDZmVhsPwnnHGYg2qhsxWw8FIGKRUgd4o4bkOmiKQfQe7WmZfT5bW9Uscemgn9XyK3rjK7NkLvGm5TI738/il9wmuXSQMQzKX3uDre09yqRmy0CxzsK+fwXwCU5ZQFIHgw7djTZEQN/69bTSDgh/lL5FIJBKJRCKRSCQSiUQiv0WiAOa3kC1ULN9nvtolJCRtqKQNBYUAJxAUm13SRgEtF2dYUjBVhffX6uzuT5I9chtbMzN4QUjSUAnDkB07hnEHRpAnd6O1YkCIkYiz//67aV6/hluvkYkp9Mc1wof+DptvvcbmVgNJklDHhrk6eIh3pldwkAhbFjUtzfk2tOQYj4+ZhK5HZ2OduOtxbDBD2/FYq1lcXrMZy/bg+yF+KPD9gECS0PEZlWyCtIlU0Llow1YrpBBXqYXwVsnnVG+WwwcHmLh6mtbTf4mk64h8L0FMRQ58wuIGnfmrxB/7Cna7SXz5Ko/3mSxnhzkXdnDaFuMH9iBLgpdOn6e/L09yII8faIz1akgipDcV45XZLbrexytLhICYKnOt2OLUeIa2G2LoCn4IMUVwbcMiJgsm0joVJ9ievxFXOSgk8CC+az+hAN/zuFTqfOS6N0qNblSyzK7XOGEaPJJ0WCr0sGiH7PriV9EWZojZbTRDRd91ALHnIF1J/qXec0oYohZXcC6eIWg2kJIpYgeO4fYO491YtyRJBBfP4CzMfuxnQ8em/cqPSXzxd7GSmV/qOv+2cBMZwsExahsXbh5TZAlDkZE0jWUtx5Bu0vUCUqaOJsv8+MomW80uu3sTZE2NhKbQcQKODBZ4d7lG1w/pMRVuG05TSOg0LIem0+L8WoNH8z14pSLlQKXS6nJsIEPnlSdxQhmRyiB52zOnmuUK8uYyxtgO3IEJNlLj/HihhRtq7D76JSYnh7i42WZxyeLrOZfbBgyC5UX0QTAaTTB8gnie6xZcK1nYrRZ7xvpIGwptJ00mpt6cZVO1XPJxjT0HdvHq9U0qjTadALKeRU9Plma1jmNAprxCjwSK45NNmVjlNnzQvlDTGNEDjJWrJDQda+kKcWmA82sVAs9FSiQZVAOmX36VHX0ZJAnCbofUuZe5M53lRKYXa2yE765ZbHgBJyby/MHto7xwbYtm1+XAQIqELhMEAiEkmr5MUgkIf02q1SI/I0kiqSv0J3VMUyGOjql9ynvwR77vo1KGQr376a0rI5FIJBKJRCKRSCQSifxmiQKYXwAhBHaoULF9PD8kZSik1YDwr7WduhUcofLUlS0MVSFnqqzUOnQcn4olMZHb3nA9MZ5HSIJ3lhusN2wKSZ3H9/Vzeb3B3v3DnPjSE7TfO40sCcTRu3i/EbLiyHTXoCctk43rPFlKE0gGB0/tZK+zRfrCaez7nmD62jrmhUu4dhd8n8qxO3l9rkwga1idLkqzSZg2Wa93KLc1Th6Z5PSVFY7v6uet2QXa60Wsro2kauRMjbVCgXxPD6HfRlFlYqGHs7SM5wv0ex5h6Uc/5KFEgifu+RzTloQjyQznk2w0bd44s8Lf91rIvUPU2za1cgcMQUoVZBQdNQxBSMR27kXyfdSXv8uuQj+7x3cSHt7DyytVdhdiHNmTo54f4i/Pr1PyNnETGVKJGK7jUe54yB8ZfJ8wFGRJptZxsJtdBrMJ5msOz2/W8IKQkwNxplob5K68i9vpIA+OEd93EHnxGvV3T7Neq6GpDnK3TeKJb+B52xtzQlUJFI0wCJETKYJ2Cz8ICCUZ9er7TGk6O3v6kHsGMb7+ewTdDoEs4+qxm0PCZUlC9j0CScb7BVaaSJKEMn2O9luv3jzmNxu4ayuYJ+4h2HuEIAjQOm06Vy99+kV8H29xFunQib821Dzyswglier+O4mvV2ivr24f9D3Shox+5/089f4837x7L2vEcITCudUaXS9gNBdnYauF1pfAa7fJ+h0KRpZ61+XLhwZx/ID3lqs4XsBYNsYdB3YRtpuwtUY4YFAyC1wrrXKX4rK6UcZQZVKqhu/5SKFPEIZIvod27BRPrQa88/4yrh8QhFBSTP5seZEvHxoEyeZ6uc2oaSIXl+k5/QYra6Wb/78dEzvoOXwvT1Z1pgoJptcb3DGeYzBtoMoS9c72IPvhhILf7bC2UUYRApHUCOwu1aUVyuU6p90+Htt/mO4LP8TdXCO+9yA6HjFDQZvcg7h2gXB+GlJpnEwPpY0SrXQGPBchJAjBDFystkXbS2OoMi3Hx/MDYm4Vs1YjWyhwaGA3WSnknYvXaLU73LFjhJHhId5ernG12EKXQq6shaiy4MHdvUylZMLw1+d1oEgS0i/hveO3lZbJ0rtwAVY3UFUF1/XIsou2Ij7z+z6qd6if5sBeVuvdW7nsSCQSiUQikUgkEolEIr8EUQDzcxJCsNoRPDe9Tsve/sSqLAkODmU4MRxH+YwB7L+stcxVbdbrXRRJcM+OPM/MFCm3HRwvoGy5HBxIocgyf3F2BTcIadg+tY7LfLnN43v7CWSZl+KT9J3MM5SN8/x8jXooUZUV3KbLOyvrmLrCw7sKfO9MlUtFixMjOf67L/0er791CRyHVNzE6VgIScJWDZrdGroiIRAgy3hBiKRp2FqMc2tNbpvsodlxCF0PRUhomoYbwFazy9PLCn/wwBcx596lb+06zvQ5RCpL790PM1uxoLRJzGmiTr9HbeA4V0sNKk2bkUKCE7v6UTsu8xcuoUka8YQKsoJjd1m1Asb3HEFOZ7BeeAq7WScoFxGej3vuLbjvC9y/ex+lb/8bWhO7+SFFWnaAWeinU1xFiY1vtx2TFXRFQhJgagodN6TUagNwbCTD24sV3l6oMJGPcTCjoL/zIoulEjsnh3E9D2WoD9GuMPv6q1heQC6ZIpQdwmaN9nPfY89X/xdWlteRewfw5e0NX+JJhKoxmI9jVtcJ2a4iCddXMQ8dp40Aw9y+KYIASQiMagn/8ln84jpSPIl58Da8/uFfyH2ntxtY7735qec6Z9/EHN1BJ5ZAeC6h/dkbikGtsl0lEwUwvxCXOgrS8UcZC5rI9TKEASUM3liu41s2kqawWuzwp+9v0LR9JAFq6LO/LwF+jGwyhl3tUF9Z5kv7Rjm73uDCagNVFkihz+WWxcxKmf/rA7vR+46yYStsdXxkVcVvV4lpCgkpIHQcJAGh72MELn6lRDeWYrNTYv/eCWJxE2HEOFeyqW+0eGuhykhGJ0RCaTdpv/w0CccjkzCotbbvn9b8HOlsgXuPPcqVjQapmMabCxUm8nEkIdg/kKJiOQzSYbXsIQmBkCTUwMMLwV9ZIpfOcPXKHA8/cBuGblCdnaXY8lH7pug9sB+l0EPn3/1/ALYDz2EThseprTS3y9wEIEkEioLQDRpOwGbLxv5IRZyhyOyPxZnQQ/70R2/iuAFCwKbwWaxYnC91Ge/Pbg9qAlw/5Nkrm+RuGyYr/+pfBzKglzdxLp3FrVeRk2li+4/g9gwS1Wf8tzmVEs3VVTRNw3Ec3MG+/+b3fVTGUGDgVqwyEolEIpFIJBKJRCKRyC9bFMD8nOqezA8vruF+ZLCyH4ScW66S0GSO9Gq3bkNZkrm0XgPAC0KurNe4bzJPgKDWccmaKgcG0vy/npvGC0IEIAtBQIjvh7w8u8WhoRRn1xokNI2dMYPprkJMU0EKWalY+H5IOvSh0+GfHk5Q7nicrXZYDPu4vlFFdh127DtC55VnEQgURSIIA2xfoBo6otCHZSt0JUHbdtFkyEkhb55+j4d2TvDD86vEdANNj1G3oWY5kBumpt7GyK4d2EPDYHfpbm7S5zo4+SQVO2D6zTOkn9jFfNFidsEiHtf5ndunEP1jpHryrK1s4HcDhmIOKbeDrvrEjpxAUiSCVgNXNZDG9xA0q6jjUyi9vVh/8R/xKzWa93yR0rlVEBKhs4QxMAKtBlVZ4uBwgs1ml4F0DMsNWK5thy+yJDgxnuMvzqzgBwFbLYepdIeUJpEXFrWnvoNW6KP4ztv0ZBMMHtjH5fcuULRcAk1itGeAsFZiwi5R2LuXsituDo7wZQVjdII7RnV44xzIMmpPP/rRk3R7Bm9u5sJ2KBdbW8T6wZ8RFNcIHAchy8hXzmPc+zmCwud//vuuViH03A+/FhLbc4dCQteFWgViCUJNR4qZBB3rUy8j9/ThRuHLL4Tv++woxPnBxQaXMFC2BGG7g+s2ABgspCnagleul+i623NHFAGBtz0fqj9tsLNgYvYaXLt8ncMHTP70zAqqFCJ5LgiBJEkIAe8tV9g3FUetrrCy0OKu0QmSvoMSdKFlbd+Pmko+n0arbYCi0lYMcnv38+rsFlsbFqHU4eBAmsf39/PclU0ODCQZy8fxls8hzCRSaY7BeJJcPonlhQhZQi6tMCW1KZox/uu7KwRhyHKtyz2TBV6Y2WRHWsWrVEgNDSEEDGRNnHoZXQrwAVwHPZWmlSrwujJG36ExYoqElynw4sVZ+oOQ++55HOX900hmHDWbhl27GfeWuF6y8BCEQrDYlRgf24FXK+H5H68OcZCw0wVeP3sVgoAPulD1Dfbxg5kKtufT7MTJmsrN13cQwlzJ4vYB41caRkqShHr9Mq3XX7j5nuLXKjjLC5in7iPYdSCa2RSJRCKRSCQSiUQikUgk8jf4pQUw3/nOd36mn/v617/+C17JL48kSVzf6nwsfPmos8s1dhf60bl1m2gf3RBz/YCZjTqSAF2VcRyHkUyMhKFht7aHxhuqdHP9aUOl0nbZ25tkb3+Ks6t1dEWm0XFBgOsF7EwIpOIyV0o++wYl3Hfe4t6pKXSnj1g2R71cZcMsUJjcSWthHrE8x1DPGOvlBiKdYx2Dhu/fmDGjkcWl3XYol2uE/ixfPzzFctun5YXkC1kGEhp9dOCdF6kGXexLZ4lnM+iyQGm3UHpHWGz7aGGA5HVJCp9MzoQw4O2FEnsHd3B93/30JS7StzqN36ghjU0ijpxkE53c+bcI73iE66+fJmg0SSTSjB86iHf1El65hKrp2ELeDhWEIHRdhGMDIVImw0KpweP7+nhvscLFzTa6IhHXFR7b18dGvYsXhDgB+KFAqxWRVuawLp0FTafmCUTgYV25gFzaYmzv7RRnr9EOQhqxDPl0BmVxmi8/cYy3V5rMbm23HRtIxzgxlqUvBmrP7yPCAE+PYSE+Fr5IkkQs8Og+/328pbmbx8MgwNvawHr2SeL7DoEe/4Xce0q+B72nn/CDgMWIYRfXb5539Bj6gWN03nntEz8rNA1peCKqfvkFGkjIDGVibJSbOI06iiQBIMsS9+8b4MXVGojtiiNJSIhgO4gRwPmVOvsO9nJcbvLQLpXN4jX+bwcTPLnYZbEWEPouhiozkI4xc22ZjZ4xpppb9GcKDKkd0qZJamQQr1oBSSamKaScJooZQ+ofYjZM8MzlDdrItG5UjLy5WGGqJ8Fto1n60zFShkq7VsdRYpjD44h2A8XrYPg+bqiyUIFcGHB6rkQqJjOQMtBkmXOrFR7d109K8ml7Fcb7UyyXmoSVIrbrEYspqLkCqhnj4GCaa2tVFqtdFiQZZ2sTfUJDTuaZrTSZ3HkbO+avIOfyqP1DLP3gz9mRyjN27B5eXKgRmEmWtAwjtz9A8q2naRXLNx9/Ictk7n+EcqCwXKx97LmRZIWuu92ism7Z5OLb87Y+UOt6H858+hXRrRbW26997D1lW0jnvdcxh8fpxH4x7x2RSCQSiUQikUgkEolEIr+tfmkBzJ//+Z//TD/3mxbAbDbtzzzfdjycQKBLt2Y9IgzY2RNnq/nxNk9BCB3XZzSXIGQ7aEnoCqXmdrscI6GT0BUkETKQNjBUeTtw8QPiuoKuyvhBSFoVSKsLdCyLWDyGMAx6Dh0hDAJS19/n1OG9LDcdGoEg9rkpCnYde/o8jx6Y4JkNj6WuQHICBtMqiix4eCpPd2URoz+JrCg0213eee8S6VSCnKlTDXzevOryj0/1k06YaIk8+sYC7laRwNCh08ZKOfiNJqlcHidmULDWcTeb292B2nmCdh9PzrX4o8PHkQ4dZLXucGWzxZXT6xiqxKH+nZz0O6gjO6jPzyGMBHbPIEnPxhASrcV5YqHPdg+lGw9op40c327x1ex6FGIy3zrcx75il4rlIgDX81hodul6AR3XJxtTyZkqlUvvE/ohZiLJVsdFVyUSmo67tkzu5L2UBBBCxXLJGAZaIklCDrh/PMGJkRRhCDE5hMDD98HXjE/eB0JgdFoEi7PIioJ74QxCkkBR+ehWatCo48xdRew79rHN359aJoc2PI5ktWj98Dvg32hOpCiYd9yHlCts/74ggJ37MTptulcu3Pw+OZkidvfDdJMZ+FUFMLKC5YntVnJyQPArmN/0i6aLgEf29LHRSLOWFpTWS2gi4PhggsL6NRwmkAiRJYngxtN/4/bjaI/O3uUzWGdfx5B8GmGMsO3z9+57kBcywyzXLFRp+7sL/T2omQy1JZ87prKsnD2LJQmyD36B8nNP0VpaQjhdSqrM1G1HiN12kpcuriFQ8PyAlKHS9bbnZy2ULZ7Y10cupvIX51Z5REoSb7Xxq0V0u4UU+PhaDLl3EM+P0QhkDvSnGIgrLBZrSLiM9SeodTtkkgon/BW23l/i3p4pnl3t4AcB6lAf4doSKbrsT2f57uvTBLZHMDBCsOcIFqA5HWJjk1wm5MAXvol98Sz2tUsMZNIsNpuIc29wx8Nfo92xickSueE+6oU/RGm30Z0O8dClKWm80lK41/VQJAnnI8+Na9ukTY265SB9StAykNJ/9WFkvULofPrft+3KthJEAcwvhySR1BX6k/rNQylDod6NGr9FIpFIJBKJRCKRSCTym+aXFsB8+9vf/mVd+tdGEATkTY25zzhvqDLaLQpfPljPrh6TC2sNmt3tllABEk4AgRDEdJViw2a52gYEA+kYprK96ewDu/vSnF9r8L0L6wjgiwcHuLbVom37OH6AFrikElmSiQRHJvtZbte53PaRZEErt5OEmeaZs1cJJJmQBj2myqndpwgDhQeP9LBa72I5PmEY0vUCPM/n5FgOsTJHWgrodLqoiozXCllrtfFyKn3pLD++Xifec5z/fm+SxluvECganh8gawZBGBKGIdn9B3jp+hpeq4kkQCBwmw26S/P83qRJUoZ/e3qRasMCSQIBISFXVqqEvXHu3jWFMTRMvK8Pu1ZGmr+G2qiSOnocpVtlfKiH+ZUthABFU5HMOF4I/WmDjCZQApe0JvHGbBUAVRZM9qQ5vVABoOV4CFUjvBE6CCGQCOhaDkouT2C1CdvN7fkZzgdbtQLl0O1s+QpCQFwKEIHH31RQFWvVsZ7+LoHVRj1+582KFKHpiJj5sRAmtNo/9yftnXiK2MAg9f/z//j4Cc/DmbmEfPgk9G0HVrasIN92N/HdB6FZRygKfjpHR9UJfwUbzkKS2OgI3loss9noIksSO3sT3DaUwhTu33yBX1OhrDJdcXhnaY1W10WzOhwY7uewVEN55zlIZRgbHOI6EgOZGMvVDkgyoe+T1BXuk8u4Z94j1qjiaArZVIxl12X9+We554tf5z+hUHUELcdn34BOxQ54uyIx3pYY7+vlUlfjjfeX2bHnJL2HTyF5Lr6scF42mMiOsqd/Dael0C51gO1ZKaG83RYR4K/Or5LSJTLDvbi1Ela9jsX2e2qzbqG259j7pW9yPZ1ja36ZV89ubM+YIuRN4LaJHnoSeYKeQYo/fgY5X+LrB4+x4UrEsykGkwWG3Cq27zF522E2fZW3r67TcZqEQqDIEv1xyHQbtBubBI4NyQwCGMsn0KcmCRfeor6ygioElUs5WmMH+e6WStPx6E8Z3DWRo1Wp4oYqO4fyXJrfrgYLQlhZXuf42DjPT6+TSxiEwYevSkOVGcsYhOHPdv8JIfCFQt0J8UPQWjaSJOH/tKHi3xTKRt3Hfmm0TJbehQuwunHzWO9QP82BvazWP3uOViQSiUQikUgkEolEIpFfP9EMmJ9DEATs7DE5s1zFDz65G3VwKI0pB9zKD9PHhcdXD/Vzbq3Jpc02K7UO+wbSmJrM9y6s0Z8yuG9nL89Pb7JUtZjIx1ElGEwZdL2A719Yw3J8BlMGGUMlCKHYsulL6qQUjdCXyfX2kcvofP+Nc4RAKpvhmbkaI12FJ07u4r++vUDb8ekQkGjAN44P8vT0Fu8tVWnZHoWExu2jOWodl81aiaHXn+bxu7/EM5fXaTTbSL6HZsTp7clQ6Mny9DvX0BSJ39lboP13/zGtjXWMdoP0/HmMZp38bSdYTo1QvrK4vSkYBqComLpCzG4Tbqzj9t5BtbEdPG3brmjxZJmVeofWvad498w0889dQNNUdg7fxclMgPH9P8E8cjuPjed5We1nfqWEkslBzGQsb/LAZB45cAmBoaRKT1Jnq2nj+iGeH7CzJ8G1rRbZmEZVk1HNOL7VRg89EmaSaqlKuatQGBxGMmIE3nZAk+8rYNx1L6vzS7RWTiMl07R27CI1Mkxc9j+zYkURAufMaQKrDYqCnMygTe7Bb1QJWo3tqhP5xsteCJS+wZ+v+gWQwoDOwhzK8DhBtUToOghVQ8oWCGJx7ItnUPpH8D6YIxEEdMwkmMkPL/IrmiWxZgm+d34N/+YQdJ8Lq3VWah2+cqAPg9+sEEaSJFqBwumFJk9f3kSVBTlTIyVrnDl/lUpPkoeHdxB2WuwZ7sFPQV3SObdaZ6Hcxpfh4fEEhfn38Oul7fBOS2E0ygxne1hvufizl4nlb2O21sZUZHYW4vyHFy/x+X1TzBYbDB06wnCzRW+9TkIOCTyP67aCE09zebNFeLZIo95h52gfOweyPHlhjSAIycU1MjEVPwgZTBsMJDXay1cw7v4c0umX8EubtB0fVVUxDhyBeJLAc7m6uAlAytRIatutAme3mozlTPzJ/eSPlFh+9z2a608xeep2xtnEyfbwXr2Xmdk6VzWDMPQ4eWgHcytFlq0QX9VZrVjcfWAAaeb8xzJPc3IK+43nEYqKmcmzVLepd8tYV67xlce+yr9fhqWKRcfxuWsiRzemc8e+YVZKDTYqTWwvoNZtsjtV5bFjk6xbHt4Hr/u4zkO7CyQk72d6SUiSxGZX8PLsFsUblZCFTJ1DfTF251RE8FP8MUpnEYr68flOH5AVSGd/+gVGfmJOpURzdfXm1xlTIzn+k1XFSOJGyC99/BMgv/KqqkgkEolEIpFIJBKJRP4WuuUBTKVS4fLlyzQaDU6ePEk+nycIAizLwjTNT2wY/LrLqgGP7u3j+Zki9o1ZBgLY1ZfkSH8c37+1G7hhGBIXLidH0/iB4Ohwmutli2cubxACzW6LpK7y5cNDnF2p4wYh/SmDOyZ7+H8+O4PjBaiS4OhIhv/w1gKnJvLcvSPPSq1DudllIquTNnUul7vceXwv164usufoHpbbAVdLFpYPD+8fYr1ucX6lhu0HvHa9zPPvLyAZMZwgZL5ssVjp8JVD/cy3dfY++jvkrl/ij/cP08nuZLHWQROgTPbx7y9WmBgb4Mhojr+6tsXixUsYySSqGmN058M8OpWjWu7y7mtnQMhIsoQka6gC7pzsJTn7HkHXA1kmrckgBDYCLwBdkWi5PredPMqTF9bpXFtA0TRCQmZrNssix5f++P9BZ/YieVXi4fpFnC9+kU5+EEVXyWgghT5ap4NoNzCFxJf39nNmw2J6o8ncVouTY1ke2NXDu4sV3u5qfP7x38H0u7jFDZLJNAXZYH1+ka1Om/z4PlK9O9ANnf6syZXv/gXtVvvmcyvOvQP3fw716DHUzwgG1E6L9vI8ciaH0duP9c4rqFO7cJ75PnIqjUgk8SwLggD94DHkweGfP4BxHVyrTWDGkcw4IgxASHyw1Ru0mqi+B5L8c/2eX7RQUnhzoXwzfPmoatthqW6zOyP/3I/PrSKEYKMrmNlq8tSljQ9njHRcBtIxBkZ3sFQuUrvjbt6fXmL+0iY1PYXldzgynGU0G6PZsXl8XEN7fR7HahGoGmEyQ2dlkUFVI9k/QLnbZmchQTZpMpjSefPiAnbX4f2NNl84voMnX71Ic2ODjhsQAsenBtm9a4T/dL7I9YbDYD5FTNV4dqbIaDbGPzw1ylbLoT+hMBq26WnOYWtgx3oJFmdw2k3CwyeIxww8x0XRdRYWVkm/+SZufJiRQgo18BDVEl65gRASPckUllsgJoVUj97P4RN3YPmCyxWbTVwulGyaLYt46BDTFWY2GixVVvji4SGqG22Wmw69MRmVgC0pTooaMgGSEUM0agSba6hDo3Qcj1LLpuuF6IqMdOldJkfv5mqlQ8Vy6E8b7MxpGKHMF+45yNWlItPrdXRd5eCuEYQZZyiQyJkaihTSF5fRQ5fgUwL9n0Tdk/nehdWbf4sALMfnhZki+v5+diTFT3w/2/EUxtGTnzqzKXb4OE4i/SsLTv82+mmqYjIxlbPrbcrtDxvf5eIaR/vNKISJRCKRSCQSiUQikUjkFrtlAUwYhvzJn/wJTz/99M0NgNHRUfL5PN1ul3/0j/4R3/zmN/n85z9/q5b0CxEGARNJwe8dG6LU8XC8gJypktVB3OLw5aOWal0urlWZ7E1xYbV+s1uMLAnmyhZnVqqMZU1GUgbjGYOWvb2RqAgIXQdVhLRsn8sbTTRZom17pA2F5a0GL5Q7yJLE7ozMo/ce4z+/X2St7SFJEo4fUmo7TOXj/O6xYVw/5NlrJZLJBOuN7vYnyW+0vHr60gbfONhHd3UR5YUfEIbgyhq7H/48YnSSK+UyGw2buyYLvHG9hOrahK5Lp1qlicTm2gbtWh9fOjJMeGSKC4slFMsmETc4MZZj98o5wnoJvWeAhhnj0IFJFq9cpdV1wTAJZYlsLs2Fiotk2wjfx3dsyPXQTvez1bCJr7s4JY3e7DD3fv0EGVMlHoaAh+KDsngVd3Ya30zSRSYmrvDgrr0cOzZIN5A4PV9hoVhnd8FkT1IQrrXZfOGHKJ5DTJWQZYUddz1CdcdBnrlWYnzXDo5N9HDtv/yHj4UvsH2vlV95jvT4GFou/ekbqSEIWcXI99B66i9ACPTJ3SQe/R3sy+cIOhb6jp0oo5MoO/eh9g5CqfRz3WuBqiGn0gTt5o3n9+MhqpzJESjqr26+y2ewfMFmo/OZ52e32uzLZ29WJ/w6kyUJpdulvdGk7yNzOWRJoCkytY5D2kyy7+Bevrto4ctZSErEggBdEVxfr3BqsgdTMlnsdugvDOMLHce2WStbTAyNobsW7XaTwq5xkkrAzMIm0zMd/BACSWbnSA8vnJunuVHEMAwUUwI/wJZknl9sEvM66HoM3/NJZePErTod12ep1uHSQhGttM6+vjhHMhL1Hz9JcniYQUOwvF4k57o0QoHt+YQhlGsdCsM5bNuhny7drXU6toschggRoneauItzxCaTvHStyXwuxiszm/SnDO4ez3BmfhlNkRjJZ2lX64xn42xZDq/NV7h9PE/KdDg6nOHSlWl6FZNGvctYxkDVdZxL5wgdB6/TwXIEStclZph0vABpY43bj8p0iRNTBKoIUUKPkifzF3NtxjM5bjvcQzuQeKPYYaG2TtVy+MbRYS6tVMjHdR7e00NBDX/q4E+SJGaL1sfCl496e6HK6MEeZH6y+zkIAoI9h4inMzgX3sNvNpDiCfSDt+ENjX1qcBn55fpEVYyhwMCnf2/Fctn4xIw685e3uEgkEolEIpFIJBKJRCKf6pYFMN/73vd46qmn+PKXv8zBgwf55//8n988Z5omJ06c4K233vqNC2BgO1wyhcuoCdv1Lx78Cmd4S5JE1dr+RKznB8R1hVpnOwyKawobzS6KJFisWCiSYKrHJKEpZGMaXddHVWOo6vatcXQ4zQtXt9AVGS8IGIgrILYzlLWGTcWVaHshkiTRm9Spd13WG12ubjb53WNDeH6Iqat0XB/Hu/GgSDKSBO2ug+N6BAPjqP3D4DnomkH70jm8VB+FvMpQWiJlaFiOSxBI9A+P4tUq6K6LJAXUOg5hGHIvWxzId3CHE6jtBsb5d2h4go2mR2znED98Z45lR+au47fRnJlma7MEqSxDE6Oc3vIYcB08zyM2OkHdzLG2VUdIgvmmy96BXi6XuxSvNfnmoV4MXIQQOI0W07bJtd6TOAH0xGQ6lTKTazV2xuLoZpzJgsl8qUkF0IvXuXruAvnCIHEVFKuOIilw7QIDk7v5UrZDJmHhNErUNzY+7akl8Dyc1WWSPTncEBwfdJmbA+39mEls9166rz1/M/Cw567hV0oofUOoiSTakdsJsj3YmTwpVf257zc3hNjB47jrq/z1wRBCkojtPYRXWkcFwmQGR4/9WnwKW7AdUAT+p28kq8pvRjVezLbwzr9LfXaW1nqF/pEh/oeJw7wW5rlec2l0XQxFwvU8mrbP/FaTbqtNOmmSTxpIIiTWbfLulS6jMbhU8/jKztuwN34MToisqJiaApaDaVdRhwaZDFtMSyGbrkuoaKQzCRwhEzRr0DtAJZSxXB9dljg4MshL7y0xnpApaDKyplJrd+hLmcxV2ixVOkwZHiW/y9WFFvOKxBfveoD6K88x+rmHSZRrXNusY+oaigjJGAon+gzSBw+wHE9RCDYgodCUfJqWDUFIaIf0Gmnc+VnuGd/Nf3x7EcvxMboum90QVZEQksym5TGQTbG6USIdi6GaOnv6klTrGzx1eZ2jvQPoVpOK7RPaXfyihdBjqIMjtOt15GwMp2sjIXAlHc8JaLRdvEBGEYKEphCGAU3bx/YDZsodZso3qpXaHpUbFQpt20MSUG7bfP/COt86Mkjsp5xBJMsyS9XPDhSrlo0dCMyfYuSTi8AbHEcZGEVxHQJVoyuk35iqsEgkEolEIpFIJBKJRCKRX7VbFsA8//zz3Hffffz+7/8+zWbzE+fHxsY4d+7crVrOb7UwDEnHtjfWN+oWh4fSrNa2N+YUWaLj+DfOhzy+f4CtlsO7C1scHUrxwvQGlu9TanQYzRposoTtBZiaTBCC5UMmGafjeMTNGHN1G2SFlAzF1nYY0nV9/DBkrtxhd28CPwjJxnUMVaHZdSg2bQTbrXAKmTgb7Q4jmR78xWsExS2kmImIx1nWc4zmLfwwJJc0qbZtrnsJElmTTGhjel1kBbpeiFBVzEsv4cxcQoqnYGCIjpxA6elnxcgTLK6RzQ/xzKUNfufYIRqXr+EbcZJxnR2eTGvFJj42jtO12dwoETrO9jBuR0NOxjA1k1bHZqXhsDO9PWfjybcXuN6V2ahuV6pIAh7eN8hby6vU1Ti3H8qyJx+SPzZMrVwn/NFFUnGDlOQiBR5ePI1o1wm3NpHPvE4snUMcOIRkO0gIgs+Ych0LPeYaPu8sbs/UScdUbhvJMJyQcMOA5PA47eJHAhzPxSsVCbod5IERwuIm/tSBX2gI4vYPYd55P5133yB0tj91LekGiQNHsS6ewV1d2j4WTxA7cQ/OyOSv/BP0cSVkPB/nWrH1qef39SU/tfpFkiRavkTTCVBliYwGcvjZc3l+mQzPwX7u+3iVEoEvIAzpFIu4y09z6s6Hec9K0HI8evJxKpU6SuCT1QSDY3k0TUFTFeKGxroUUlpeYXhsipmNBWZiAxw7doLw/Nv0mxLB0iyEIYkHnuDyM89gdx0+f8f9fF/vZbEVkMxmCIFWLM18sYnr+ze7U5XbHo5m4Msh/QmDC8UO41md5UoT1/aIyeBUyogwxHYcHAc21QHGv/A1VgfG6GxUkeuXSEgBPaFFsLKF3zcIwJHuCu7ECKcXKowOxhiXPa6eOU+o6RweSOItXCHRv5ecIWMQoAUuhAGyZhBYLWyrjdBhUAuwTIPr5RbFeoei5WFoKhP9WaxgP0NDY+iNNVTXRtY0Gt/7rwSej9tokDBjtDo2ZkInuWcP79kKfhiQTcbImBpC2Gh/LcxzQ0HV+rA9lKZIfNB1zHJ8VhoOuzI/XdARhiGpmMJq7dPP66qM/FOELx+9rosAVf/gwE9/kUgkEolEIpFIJBKJRCKRv6VuWQBTLpfZtWvXZ57XdR3Lsm7Vcn6rhWHIYFLFUGW6ro9MyPHRLO8tVQlDMFQJRYR89cgQXhDyp2/N4zfr/O5de6iM5pjebPLefIknDo+AEAymDAxVxgsDmh2PiUKc2a0WDjKqolDrOAxnTLZaNroisV1QINhRMEkaCrOlFoYiU2k7ZEyVHT1JVmoWE7kEnY7N5arH6u4HuO22e0i9+wKtw3fzdEnmvdoG6ZjKvZNxvrNWB0AT4HVbNDSNsVweuV6EcpHF//RvyJ+8k/iO3biL1/FllbH7PscrFcFb718HVcMIVpjI5FkvN/nczjyGKpH0t4jHk7ynafiba/iJDI7TvdkmbW9PnM1rc7hju5FVibVKm/2FPK9d3GTLFRTrH96zQQjPXV7nD0+Ok2xu4b33BlKtQn9vH2ODo9SNACQNt9bGqlYJJYGayqCkewitNvrt9+AkM2iaRTaToFz7ZFAZUxXsTA8/vLB+M55p2x7rtQ737uzhYEHFiydRR3fgb20QdDsISUJKpZFHJiCdQ8rkf+EFWl4Iwc4DmMPjUK8CoKgazZef2a6K+OAxardov/RjEo9/FSvf9wtexU8n9D1OjWVZr3dp2R8PWvb0p+iLS59om+ZJCu+vW5xdqeHcaPXUmzR4cFeBvPrpIYwQgi4KZcun4/mkdIW8ISEFP3+LQrG5hlfZbiGnyAJVkvCCgIKpsvreaU4d+zwX6jLDKZ3BfpPhQoLZrTbPzWxiuz5K6NOX0Hhwdx+628OIKfijhw9RLtWo5W+jMLUHeW0Gb2wn+D7+wiwxu4nVtrHefJn7H/4a/37Lwg9SDGRMXr3s4/r+diu8G2tc2KwxkY+j4tP0BbIskISg3XWRZYnJgsm592sYmoIAJFlmScsiG4Lvn9lgT3YPJz43ycDKRfytDYw9h3CFzNXTb9Nqd+jfe5Ce3H5emd0gril8/XMP0NetUHr9RUQiTdUOkTSDpKIgey7DMYm3Om0IA4SqIghRmjViQcCx0XFWmw6bHZ+HdmYouE2C+SsUS5tkMgrNlWXSu3ehjk3SmpnGrtfpG4gThBphNou96xAn202ytQUGbZ9mpx91124K6RQZU6N2I3TxghD/RuIS1z4ZjGy2XdIxk6rlkDIUCjEJNfxvtw7zPI/9fUmm1xufGt3u608Rk/xft06AkUgkEolEIpFIJBKJRCK/1W5ZAJNKpSiXy595fm5ujkKhcKuW81svIQd8fn8/T1/ZZG6ryWDG5JvHhsnGNVR5exi6rsgUm1125w1m2w2+++ZV7t43zMnRESw3YCStM5xPMl+2OL9WR5YEvUkdScCu3gRdx2cgpaPKEqosiGkythegyYKpnjjltsPbixUe3NnLy7NbxHUF1w9o2h57+5LcPpjkx+9e47HJDGsrGyj7drP3i3+P81WfUqeJrshkYyqOF6ArEs2uS0xX8D0fRxHYVoeDA1nMd79HoGk0z75L19AxevuwbJvOGy8j9j6ArRjYjgd2G7lpobfrpHMWeqvGWjdk/wMPsZCJs3a9icj2ItSAwA/YNZhBczpYnQ5Ks0azWkOXe2koDZY3uviqThBsVxZpmkImpmAoMlLgo7z1PDVdkFCA+auEO3ahqyrlq9PYzeb2xr7v4ZRKaIUeYo9+kXBqL14YEhhxRk+dwnr+BbqujyJJBGFIEMLw7p2809UJ+fjmfQi8OV9mIjuEbKYQk3sQuoHiewgjhj65B7+4jrdwjVCEKNkcfu/wL/SeC4KAjm5Cr4kqS7gvPvWx8OXDxQY4F8+gPPAE3s84bPwXJSV7fP3wAHOVDte22uiqxMGBFINxGTn4+Ia3JElcLnZ5a6HysePFZpfvXVjnm0cGMf9a2yghBFu2xI+ubNDsfnhuKBPjc7sLxPjZQxhZlvFWFm5+rYqQ3qRBy/FYb3TJmwEP70gz5hosrJfZXC0ykJvi6csbaATEpBCn3WGza/G9rsfv3znF9UaD4maJ3qTOa2fn+HwhoPbCS3jtFqHjEIvpTPRnSOaytL2QhGjy9x4+StzUkSUJX1ER4uOD3mc36vyDR0Z4d6XOtaLFRD4BnkMqlWBPf5Jax0MyTIQIUBUZkS3Qtj1ExqTa7HC6ZNO3J4ddsgg8HeXiDBlDYb3tkZRCrPfe5O4vjtIqxAj1GIvrFWJrF1hZL5O//xi1rsdSxWI4G6MQl9icnuaeyV5evryKrISoVgM1dIjj8sTeHG9u2PzewV7mLs3w7fUyO4fynEylwW/gri3TUWViU3tJju7Ev3wR4Xvsve8+mjsO4S1dp/XWSwRdm9VWG4Sg09fPnj/8Qx7d189rs1tsNLr0xHRatke94/LYvn6WSh+GraqmEtdVZrYsgjDketnCsl0e3dNLUvpv3y89Btw5WeD0XImPvrRGciZHBhMEv4DQLxKJRCKRSCQSiUQikUgk8pO7ZQHMyZMnefbZZ7n//vsxzY8Pgn3//fd56aWX+PKXv3yrlvNbLwgC+g3B7x4ZoNTxCUIwDZ2XZ0ucW6kT3vjEdSam8sjBEe7dO8jsaolXL61iex4HRwuMZ0b4356f5shYgcsbDepdj4rlkjc1xnMxvnZ0iJSh0hvfDmUkQL/RSufOiTyvzJYotR38AL5xdJgzyzUatstg2uDBnT08+c48/XGVhByi7TnI85tdGpkEL8wukk4nyZkKuiLz9PQmT+wf4MWrWzTaXWLxBJbrM96b5t5kHW/+GpbrY2oq7a5Ld2UVz/eRA0ilk9hIN7rmhARBiJAEvudhjo7jvvEWmiLzhRGDmXY/1xyXxGQ/g6ZMUK9y5cJ1pMAnbDfw7C5DeoBVrWAvFzF6BlEUmZShknTbuGur6Pk8jdkS+0ILNTSA7bDLWV3C6BtEki+jD46g9/ZBEGAtLuB12oihCRxZBc8lCAKUvQfZZxhUz7xDp95A0XTSe/fi7DvOxYvVT33ObS+g2vUxYyHm7XfRaTVwCsOYAwM0nvkr5NIGoW5SvL5E6cIcmcPHWLvjQTKmiobzqdf8aQghaAcK6y2Hrm2T7d9NQYujXL/4iUoSv1pGdR2Qf/4ZND+PD+Y3HerRONxnbE9w8jz4lGoDK5A5s1z71OtYjs9y3WZPVv5Y+GCFCj+4tIblfLzmaLXW4aXrVb6wJ4fctRBhiKfp+D9FeUIYhghd/9jXaV2gKhqr9S51I0WtDe+vFrGvzzAxkOOFSyuk4zrVto3u2WjpDKHv0xESK1ULd3GRwo4J3pndZMfYAOmUTyeRJJVKYNdraLrOYkfC2loj1HS6pQrTSo2x3hS6pvDA3gFemwGr0ST0PASCIxM9lJodHt4/xO7BDovVFnE1zvEdKpfXmzw1s8WuZJZOcZ2ErmPH4owkVaqNLnEJ2pKghy6NlWWCMCSXjNMMBVLoEtx47JTiGtL1Cl4syUqhnz0DI2SsDlfNAebWaxwYSrFU7dCHS7FYZUgSfOPEDipOiLS2yPCOXvpMBen6NHPNLN35a/iOA0Kw2HC46/7jCLtMbPYKsmvjLM1RcWVWU0P4IST791Jfq8APv4dnWUhi+70QoL68TO3FZ7l26HPs6E2zayDLTLHJITPLRN5ks9am7Wzfb71pEx+JZ2eKLJa3WxuOZU3umMjx8vUyT+zOIQWfXQkjQp/DvRqj2WFWql2cIGRnf5Y4NnIUvkQikUgkEolEIpFIJBKJ3HK3LID55je/yaVLl/gn/+SfsGfPHgCefPJJvv3tb3P16lUmJib4yle+cquW87dCGIbouAybgk1b5nsX1nh3uUrHDXH8gP6UQcVy+JevtDg6nEJXNP7ooQM89/48U0NZXp2vst6wWb24zv27erFdn82mTW9S5+R4jmtbLSTgd48PM7PZZLXWQQIODaZJx1RW611UWbBc7dC2N0jGNLIxlVLT5mqxxZ7+JFNmnA1b8PpGmbbt8/lUjP/+rh2oVgu1XUHJ9zK37vLS1S1uG0oylO6lkFCxvZCkLhFuNgnSaWK1Km3Xxw9CJEmQjGm0FZ2yE6JP7CSsVQgdm6BR48hgEiWbB1Xi4IEpVgKVXG2dkdf+kt39/Xj3fp7vXtpia6uKqigETQtF07l7T5Zg+jzGjnHiMZ12pUh/dhC5VsIuFRFCIIUBg6ZMd3kJPWkiD40SArLVor26Qt83/pDmq8/hXDmHUDR6Dh5B23+M5vn3MBUJkc7QjSWoyHFekcZgV5qc5DOQTxDGdHQ/YHdvnJli+1PbDEk3gjUrXWDxnm+wslpk8OVnsIotkqkB4jGdzUaXgJCts++SHd3J00GKx3fn/sYWRzd/hyThsR20aVJI4PsIIVi24MeXV7G9AAkIV9YpxHSeOHw3sXOvQfhhuCDFYoSKymeMubnlgiD4REj013X9EMv57Mdoo9FlXz6J738Ytmy23E+ELwCyJBgVFsF7MwTz04RBgDoyhr73CJ1E+iea/REEAcrYFFw4c/OYICSuCPoSOuqd9/DkfJ20XUcKPJJDQ8xfq+CHgp6UiSRMRBgQN43ttbYdTu2dQE8m2XJCrpba7M2kSaRS1Ks14skMLdej3uoQE4JQkrEy/bwzV2S60uUPToxzem6Vo+MF0sYAUrhdDTdTbPHkdJWvGTEurlT41rFhNmtt5ls+a80OHTegnEgyNKIgOzYPHBxl5do8TRfu2TfEteUiuYSOmtiuZBM3wt7elIHwVSRJYGYzyEkX23KQfI/4zr2c1/r44VyTIAi4e6qH4Yk8odVia02h1LDY5bW5Q2kSj23RWVji6kqZzBe/SUqBkIBA15D7Bqh0A95YbvGWL3H3Q98ifu412pUapqHh1lsouw+wpcTJbZyndiN80cw4ickpPEUj2NqkeW2Gffc8wb++sMFKrcNEIY4s4O2FMkeH0uzO6axsNUgbaV6Zr9DsfBiWLFYtSm2bL+zvp2KHFP6mzDIIyMoBuR4VSZLo60uxvr7+6/JSi0QikUgkEolEIpFIJBL5W+WWBTCmafIv/sW/4Pvf/z5vvvkmmqZx+fJl+vv7+cY3vsGXvvQlNE27Vcv5W8UKFK6W2ry/WiMIBU3bZSxnMlduIwlBSlfY05/m7EqNZ2cr7BobYOdghtPLC3gBdIOAv3x/jZShsH8gxcX1BvNli919CTYbNtObLfIJjf/7o3t59XqJ95ZrDKQMvCAkoSukYyoL5TZBvUsmptGb1BnNxlg8P4+0Y5Dn5qo4ocTvHJ/gyvVVZi9M43g+PbkUDx2OcSod8H4jZGF1i5zRz3+5sMxyzcKMm9zZq3PbXV9j4vLLBDPTSEJsByGFfpSRHbRTPexKKsAgQeAzktK5z2jQeed13MXr4HtIroyyfz+pO+6jdOF9tv7iz7jjtjtoDk5Qt2zixigD/TmKr71MtbLJiOZx+47befHiMllNUG7WUTWNsdF+JiZHSQUNtDseQJ5+F6ndwLUswkQKY2SS+o+/h9tuIidSKBJ0LpyhMzuDduIeuuffJayWUH/n7/Kd6SrvLVW4f2cP8bjg8vwqktNlV1bjpN9irDDMS7Xtlm8fiGkyGV1GiJDrdY8fz5S4Py9hVSqEsQQrLQ+149OfMqhZNgBi+TqtwkHWWz6j8U/eO0IINNdBch1CWaYdS3GhaHFpvYHnh4zkYhweTKHKEk9fXrk5FyUA5GyB4toyLxsajw8ME64t3byutv8YXQS/NgnMT0CVBIokPrNtWjKmfiw4EUJQ73561cGpnEB7+Yc0RQdT3v4Z+8oF3PlZzMe/hpVI/0RrcjIF4kdO0H3/HZxQEAIqIQN9WRbyw7SXi6iVCom+AdaaDqokKNW7VFsd9g5mcX3BctWi0nY4NZ7j9IrFnXuz9BsSXlzmz89v8rWxfbTXXyFfSLBpeciqihAxtMFRrkpJxgsKw71pfN/nd28b5q/eX2WtYdPoeoRAQpO4b6rAcrnJZrnBd96e5/fGVJ5b9RjPxnliVw9WtULS9phIaKSXz7J3dAjRN4Tb6ZBUennf9smdepxev01i/hKS02F+o4btekiKQiHZz+6jA5x9f4a4prDSdDmz2WUwa2I5PmdW6uwbSPPV3QVUbQApmeLaWpW/qLoU4iMcvW0XevA6q3qWbs3B9nzMoUFW613GsgZ7CiYLNYt/vRhy257P8UifTLfTYU+hwEsVCTOUkLotAAYeeoz2jv0sWj4EIdpkl2zMY75us1DZnhlVabvcuyPH3p4EazULvZDgkf1J3p0rku426UoG7kdyu7bjs9V28ALzkzfBZwjDcDtYjEQikUgkEolEIpFIJBKJ/MrcsgAGQNM0vva1r/G1r33tVv7av9VkWabZFSQNlZShstFyiGsytY5LEICqCPIJnQtrdc4uVwlCWKm2kWWZuKEhKQ6KF6DoCn4YslCx2Kh3OTSUpt5x2Wh0CIKQ6WITXZYpxDXumyqQM1XunsyzWLaQBQRBiCpvzzLpi2vksSGjI5txNipL/M7xcc5cW8eev4apyriez1atyV+dnuabj9/BtdOXOHx4H98/t4LwXDRNJQhh2ZboWgrpE4+S3dokFIIwmWYrlkN/8EtMzza5Xq6hKxKaIjilyyw99V3klTnM0EUZGKb61uuEC9eIf/FbWK5CcP4M5VdewEilufvUMdDTnPurP8OyXfqSBtVynZwyze1TO5nxZfx4jP2HdnOx1KG4WOOdmbOkEgan7v4mgxszFKdniMV7KMzPbs+EqDfQAg/Xat6sukjc/SC21SSwuyzVury3WOH+3b3UK3X+7KUPW3i9IQmeODrO0JX3uHPv7by4PX8dScDdkwXiso8TKrw5t0kIiDAgCHwCBF4Q4AXgByGyEPhhiKKq7OhJUrR8NEUjowtMyScIAtQwQF6YxX7/HUIjTqdvlHaygGpkqLYdQuDSmsti2eLoWOFm+PKB0EwiZ/MsrleoHxwntbYEQmDsP4I/OPoTVXn8OkkqATv7klxZb3zinCwEO7Ixgo+0hwrDkEzsk2+xpiaT21qkXimj9MT5aAgVdDu4F88g3/nQ39iOTJZkqs0u64W9pE4UiC1fw3A6BKPjZKb2ILsmIWDqGlVPYnmpyJGpIdbr6wgEQpa4vlZBj8eQJMGOQpzL1+s8eWaBe3b18fzlWYIQnh3M8OCpe+kuXMEN26RiMWI9o3RvfxBdy+KvN/jx9CZn1xroiuC+nb00bY/X58okNJm9/Ql6dIkLV1bJNip0WxLq7n18czjgz9c7DE+fI15eY6nU5HKlSiGuI4l3OfzQvXy3pDJXtghSWWJCgs0Gnzt8N/K7L+EHAaEQ5O68j+9eb9Lpujx4YIp+2WPF9mgEEgMy7BpKkdA1Wo7L6fkqxwdG+asfvYFtb4djc8DMWowHHvoaFQymhkPkpMxm1+eRnhBp9gL5198ksDym9hxkUd3Bv1yEwNe5cm6du6Z6OBTX6Z2axMj3cCYxxrOvL2LZHhAy1pPC3zeEJuvoioTjBRwbyfD2YpXV5XUALsUNRlM6I/k4qW6NwMyxKLbf4wTblU2r9S4pQ4XwkxVVkUgkEolEIpFIJBKJRCKRX0+3NICJ/PLJsowjFBw/xAslLq42eXe5ju2HDKRN9g9mOD1fZqNhIwT0JnVWqh329SfxQ9AUCSFJrNbaJHWFlKGyUNkOUUZyJsWmjSwLJgtx3lmqIgtB2/Vpdj3OrdYYy5uUWg5r9S6P7e1jttgiYWiEIfQkNHZlNb7c45J+/0V6NQMpMcYf3LGDUFZR7DadIMB2Q5KGiuUFBH7IW+eu8XfvnOKpoovoWoBgoJDE0DUWi3VSPRne8hUeeuDLtKYv4ed6Ue98kP/tzQ2Wy00MVWIgmwA3ZOP0myRbNgO9A9RmZ0gGy6TywziWRfXyNO9kdrPzkSmM0KWjGCxlTBb+z//AcDqG5wWYmsxcqU2hO0df22LPY1+mOZbke1dK0KyhSQKSKVrtNt97f4WHjxzAmJmlkM3hXltlreWSzfejlFdvbrBLqoa/soiUzROYcUrdgD05nY7tsXp94WOtsYIg5LXLq/ze7bvoLS0wktuLrkgcHkrTZ0AQ+Fi+RK2zPdOliM5gvkC7VL55jbbjo8kSWu8A6yMH+Kvza8iyzHBSJaZK3D1ZYFdOQ7r4Lt2LZ6jsu4N3izbXp+t0vAZ7J4e4b9cEb8xXcPyAMISF8vbAcT4SqgRCIAp9yOkswUCamHk/ct8gTiKDJ8QteT38IgW+zx2jGWqWw3q9e/O4Igke3N1LVg3465lSf1wloSu07A+Dmbyp0b00TUxT8EPwhYTMh8+xu7KAbnfwVZ3PIskKV5crPHlxg3rXI+F36FOy5BID3BVLYy8skh7fx2DawFDzLG42sWwXt2tzfDTPXMWi3HJAlnH9kMf393NpuUJckyl7Eq9fLzPVn+Haeo3zG20WzTj/40NfxS7V8ZIx3rNVFKHyypVNlisWIVBIGlhOyAszmzy8p48vHeinXGtSq9Z5e3oGv2OhmiZqLEZY2mB4a5l/sOsYm395kZmaRRiEaDdC2sG4ytwLLzB66nHmllr4zSZOLEZicJinr9f5xu33MJiboTuxjx8VQ1ZqLVKGQj6XZVf1KlfUPA/t7mOu3ObcSp2kqfPlQ4MkFPgvr02j9Y+hd5qEnQ5oOkG+wHMbHjv7JL53aY3JrM4f9To0nn4aNxRsOh6NVhejXGJq3xbZo/eDEWMoE2e13uFfvVbi3zwyynrM4/nTs+wazqMrMrV2l8X1Kj+YKfHgviH29CWpWg7XyxYrpQYfvAp8PyAMfJ6f3uQL+8Z4+8IcIjVAveMhhMBQJXqTOkk1xP/5xzVFIpFIJBKJRCKRSCQSiURukVsWwPyrf/Wv/sbvEULwx3/8x7dgNb99hBC0Qp3zqy1eu77GoaEMry2Usd2AhCaz3ujiBiExVea+qQJ/eX6NwNvePI6p2/M8bD8goStYjsfVjQYP7R2g1vVYqloE4fbmf1wRjPUkSCoCy/FRZYmYKlMKwfVDuo5PveMiCXhrocwfnhjFVBU+t6uX3phgwK6g1is09x5nQU7zzpU6PoK63eHw1DAdM2R1eYOAEFWXUWQJu9FALy6jNhPsjocQ+Cj1Vdq9IwwkNdqL86yMjHKhZ5yNPpmm5TBQh9VSHUlRSOgqrtXh9/ZnyV9bwnMsVF0n3duDVa2SlnxKqHSuXqE2UeDPrQAzm6Xe8ZiwAu47ejv60mWGszFWatZ25ZCmEj9+B+uBzlbXpuoExGUN0aohZ3KIRBpnfZO3lqp89cu/i0ilqCwvI0sOrgiRcgWCZh01nUHN9xB02siTu9FSGYxakQlN4/3VLbBaSAI+2vVKkuBqpcsjcpvf2ZMnJCTwPT7Yw5ckgSwJ/CDkWsNn4vhddJ/9Aaos4foBsiRAkvAO38H3Z2s0bZ/xnE4Ybj9/L1xeJXdokNzFM1T3neK7F4vYjkvLCfCCgEtX5tgINE7tHuL0Qpmu52OoMl74yTeUEIEwYuiFHpze7G9c1ctfZ+DwxX09bFk+xZaDoUgMpnRSik/4KRUrhvD44oF+fjxdpNJ2cELBRrPLfklCUyTmSy0USWI0Z2JIP3m7qGbH57n3rtOUYsTbVeR2gwoBS0s+W6Us99iLxCtVDg8c5NKyjVA6YHu8eXWdPUM5/i/37+T8ag0nzKFpCmtVi6V6h31mgBca1Npd9hUM0qbK3p44KTlkrmZzpqmiWQHCrnNwtEC7Y2OoMiFgOz6bLYe+lMb7a3WG0zFev7rFsF8HQvQdO2mFCveOZ9CNFmHg07tyGSVooSY0HElBliTCMMTUFdbXGqT8DroqYxJi2R3qHY8VV2Pa6KdSkJi7vImIJ9mVUdDrJUrTFrHRGCdMh/841+Rq1SGhK8iS4N+/Mcf9UwWG+7OcmV1HVQzUuAmSjCHFWF5rMtGbJG0oTMVh9aUXSAiJjCFzpdoGSaInaeAtzZKc3M//cUmi4/rcuSPPw5kYp+syXT/k+L5x3l+pYHW7DGZMPndqD+dWamw2bYbTMTKmxvNXt1C8D5OUhC4jt2qkzSRlJ+DBnQXaqsrFlsb5UpcdOZM7dxRYanoIZHKGjCm8qMVYJBKJRCKRSCQSiUQikcivuVsWwFy6dOkTx4IgoFarEQQBqVQKXf/sT3xH/tsagcYPp4u8OluiJ6GxVLO4urk9k2CyEEeVBQldodR2KLcdpnoSvL9SJ22onBzL8ezMJqYq4/gBOVOj0XF48VqJf3j3BBN5k8WtJoOqz+RgPxlNZrlY4wtjMc5XXLrImJrE/TsLrNY6pAyFobTBQDrGk+fXcQOfcR2k9TluG82T35xjOTfBi/Mz2Nk+6qhoqsKPNivc1Z+kP1GlWG+DoiL8ACOmYAQeMRFgb26gShCEPkkBRqaHpt0hi4PkCmYXNinkUpRaNmEYElNkdveYPJ5o0bNxhWBrhcBqo8q9BN02qWwav1Ik0T9OU9EJgE67g6Po5BMG65bPhYGDfGnPFOWz76BLDXpGR+g7fpw/WQqoFktIgc982SKmyUzm+xH1LWqpPoLxNPVYjEtGjvNX1nkg1Utt+jKyrBAbGiCrKgQdC69WIXHqXoJGndaLT9H/6LdYTU3S7tjovo8UBIRIBIAiS0hA3Q6QcjohwceGvgMk5ZDxQpzrxRae4/K2b3Dy/kcxLp9ja2WNbDaNOHKCH3fjlJwOKUPFVCWUTgu/soXb7XBGdXks38fZLRvb2W7VpEkhuucQdGyaqyvUDI8vpmVOO0lUCVKGhtW1P3Fv7h9IkVS2q5l+GyiBy4ABg7Htaehh6BJ+xj54GIbkVJ+vH+yjbMNMqY0qSaSVg6w//zQh4AYBy1WLHXkTmQB1bBJPj32s8umjhBAsl5t0JQVDhITNGnLg0Q4l/CBkebOCu3+SjeeeZuirfZgjefpySa6u1UirIbsLcRZXiizUfS6st8jHNWTHps/UCP02MU0gmyoTaY27Ahf30ks47TZGPs9jjzzEi+sdzs4vsqELwlaTtK4x3J9npthEVVSypk4YwETe5Jwu45cslJEdrFTbnOpXOLl+lrkXnkMyTfbfcRypuEpB0ahnh5iuuDdetwmQJWRZJrC7KE4HLZbEIcSxHTZaNs1QB0kiKBVRVYEsQpKDw6xuzPJiy8GwQ8Yz/ZRbNmulLq6kcLXcYV9vgiCexgl8EnGdHf1pKh2PtYaNZXuYqsyhmIM80E+3MIgf0+hbWsaZv4ofhixXLYbWl5ClCRpdj9PzFXb2JDg5nuWpi5ucWSxBEBAKqG61ma50+eKhIeodl0xcw29vB9QiDAkBWZbIKBDUW/T3Z0kHNkPTb9JstBjr7efrp+5mhiz/+e0lqh2HMAjpTW5X9OxNywRB1JLsVpEk6WNfi9/ASr5IJBKJRCKRSCQSiUQit9YtC2D+5b/8l5963PM8nnvuOX74wx/yz/7ZP7tVy/mtEsoKMxsWp+e220wNZUyubbXxg+0wxfVDhjImtY5D3tTouD5fOTjI3RMF8gmVf3t6AS8ICYOAhKEB0HFDKlabuVKblC7xx4M2XUnj7UqTb09v0LY9snGDe/cMEEslsbwcK1WLxWqHw4Npjo5k+Kvzq1iOT1oDb3UBp9bgR9U2v/f43bz843dxbAc9DJEzgyhCpqtovLlQ5Uv7J7n26nuAi6TrHBvMIxuwi5BZVSaZMPE8H69Rx0gkEIbK8VTAYHOJ3hMTLNRdwrjCaD5BTzrGF+J16n/5X/BzOYbGJmmfeRNvfQVZN/AkGdE7gI5Heudu1IrFlAmYgplqi2qgUmw7ZA8NIQ49As0GQ+N5/n+vXaLc6tI3PkrHSCISSbzQZ7krmOwbwQ8VWs02btvFcT0cL8Ddewx1aRG3Y7Fc7xIzTJRqGW1qD+rIBPX//K8BSF07x85H9vPmqgbpDE5pC0mVCUNI6Qqtdoe8IbOVHiIWSKh8fAM2DDzuGs9SrbWpXJtjw3H4oSIzMXSQI/c/hqKpzGOydGWL4UyMmByitBu4a4s3x5GUmx2aqR6WrmwiQhkApdvBtW8ELEJieqXMMOvcPrKDOTHFVw/18dxMkY0b7bkUSbBvIMXtw0kC/9OH0f8m+0mrecIwRMFFIHNxuQKAXugn3duPVdwAwPEDun5IMhlH3X8U60b4IoSgi0LZ8ul6ASlDoRATdFwfIUBybRRCAiHhuj4gEEIQKxSQ7n4YNZGg3erw8O4R/AD8MOTF1TrlTsADu3q4vNEiKYe4Xpdc4OEpOrrd5r79YwxceZ3mmXfxgwDH9ckKh/Z//N959NEvMXZsjE0txWq9g2pbsHydkZ4RFtsBG40uNcvlvp0F/ujuXczMxlhqedw9nOCJvMvSnzyL7wUEzSZtX0JVNSr1FrpcwlRz2K5Hx3Yx8j1s+iqSEISeh+Y7iHadTCJDLmny7vQqZiLHQKEHLfTxrRajmouV7mHu6vJ2S7NEjk4AyAq6sl1hs1BpU4hr7OpL0HYCVupdXC/kvp097OxJMr1eg3w/L1xeZeXCFroqkUmmuf/+J2i9+TKq3EUSYHsBMU1BCEGj65DQVTaaXULfAyGBkPAR2G7Iy9e2+ObRIZKGStt2yUseNVXDMGP0JQ1Ct4Oc7yFYmmV87wCp/QeouSp1odAmxvm5Na5VPVRJQpVgsWLx/311jn/88E6GtCiAuRUkSeLshkWl/WHl0r7+JBCFMJFIJBKJRCKRSCQSiUQ+2698BoyiKDz22GOsrKzw7/7dv+Of/tN/+qte0m+cmg1Vy8G70afqg+2gkaxJ1/Xxwu1N0SCEnKmRialoMvQlVYQQnBrP8fZciXhMwjR1FioWThBw12SB6Y0Gd6dd1kpbPDlbRxEw2jtI2dEot7psNrv0xUxW6l02Gl0USbBUs5gpNjk2kuGVa1vkpZCg20VoGp4dsNT2CfUY2A5Os0U+71O0bNKJGFUvQUfSQAjCMGR8qIeRnhRn1CSDAyZHkv1cWCyR1GX29CapNjr0JWH3/LsYa/MkN9bYNTiCNfpNribjDBlgvfEStu3gbGwysOceEmuLhMVVuq0W6sg43a5Nc2CS+J4DeH/xAlI8BX0DDOpJMm7A/TsLvLdQoUfxOKpa1EuwuVUFYO3KDHc+cIr3liUsX9AKIR7qKJIgn4pzICNxdPFdjrht4tlj6P/T/8TKuXP4C9fxsibK3Y8wrWTJlBoII0M624siS4xeeoWv7LuPp69JmIGDcGxCIbC6XWK6ykTe5LyfJLXV4UivdrMVkSxJaK06ccfhm8My12OjLGw1SSQT7C7E6GusIHcteo7cwUJvnKYL3XYLv1REMhMIWYFwO4jTZAvh+zdDGeG5CCEIBYSqhowHvk/3zGnu/sO9SMLhd/YVqDngeAFxTSKthr+V4cvPwvY+rGh5u+xz8s7HyBfn8WavEPg++qGDxPbupWMmIQwRQrBpSzx9ef1jM2TG8iaHBrMo9gyBFiO8UUkBAl1TOHHHUV6vtJi9VEZtblDXk6R6LIbSBhdWquSTMQopwUha4+8cHeTdmRVM1ccKNEqNFl89PMw9SZvquZfpsdvI8QRSLoWQZdxSA+u575M4fC92uh9/vYRtO6iKjO47dJ2QQlxjd6/Om/NlxrMmdx+e4Ll3ZolLUHnrNL4fwI22eutXrjB16j6kZ3+EXa8xNN5PWc3hyYLCnffy4jpImgaWQHguWqfJ0T27SSswktExnBbh/DpeTz8nb99PtbaF1DuCMSLhVysEvkezGxJKMrEANFkwko3Tm9T4q/dXaXY9FFmibXtstW3qXZevHRvjT99bRGs6qARoskKj2eZHF2yeOHkP8gtPEQyOkdvU2JXQ2NmToNi0eX6myJHhNLcNpXlpep2aGyLCEFnAVtNmKBPjrdfeZbQ3y1dPTPLD86u0WhZLK5sIRWE8pZKLm2SHh/j2c+/QbnWY3DXO+c0lNiyfib4Ca60PK8wcP+CV2TJ/cLiA70aDYW6FSttho/nhczCeixH7Fa4nEolEIpFIJBKJRCKRyK+/X3kA84GxsTFeeeWVX/UyfiP5QYgQH7ZGWalZHBlK8/pcGU2RWShbJHSFIITVeoexXIy4ItDqFUptl725LFm9j9evb7HVtJnMx+lPx6h3HCqVBvlEwIKv4XsepqGhWXVypsHRyRxTU/28sVCl68O+gRQxVeHN+TIbjQ5JTaZP8+k02+gEhJKEF/o4XoAUMxDNBpKioKsSuFAwVRKySS6f4cR9pxhN63hByH+e3uLQZJqn3l6m2WiTzCQpWyFz8w2+dXSYI5U61ulrBKZJqKjY89fQNlc4Mnwcs1WhW61sBwfA6ntnOHjnfYS1Ms7SPGqhF/22u3m7k0YqWnzrj77Ka8stLm82yZsap3oTlNpdvnCwn8GgRea1V7ksjtx8rIWA1WvXeXjnBD84v4YfBniORlyFEb/OEdvFajZI6wr2D/4rgaEzeuo+aru+wHXfYGatTM0TPJrUaXgKZVtm3FSIbW1wsG8WdaiPN5wUrY6N12qxe+cYd+wfZWGzxnnbJd2ts6+nH00CzbHx33ud9vUZZLtDuDTP/hP3cNueg7Rf+T7O9WlsVUPp6Sdmxrlt+DAvzdeRfA+hafiVLYJuBxSFowcGSEtJdg/7nJnfuvG/DVFlCal/iFarxYGpHmLTJdKaT6JTx9LzSIFHTuHGO0vAb1N3pA/aD/2sczfimoxgO88KQjhd8okbOxg8MYVESH6qH0124UZlTTtQ+OHFNTruxx/ExbLFcC7BwMQom7U2XVkGz0MSgkNH9vD2WhNveQHV0OkqOpstl2dnttjXl0TVFIZTMTRVZmdlgc7qInsGh6iqeTaIoQQuu3Ub5cIFksKDeAy/UYbqJno2h9vbS7NcIa3JzJ15m8duv5dnzi/j+QHCtdHVGL0xmWODcewQXl0oI4mQl2e32NljskfIoOmEjg1C4FSrdKwOg1/9XVqSzkpygIV6gJRMMZjPcSjhcEUSkMkgS4IRPeRuVlBXaxT6+thsK5i7jyMpMnPXFti4fIWRyXFkOYWVLmBoGmAjgN6kzrVik68cGuTqVpOErmDbLkEQMJQ1EUJwdqXORC7Oattjx8AwrC6iCAGSQALOrLe44467ebKm4vgBg+kY37+4jgD6UjGq7e3N+ccODfP9c0t0HI+YorCjN4nfseg0GujDPYSex8mxDM/MuLSNFJos0Z+A+w4f5EevvU+70QbAME0qxRZuICi1uqQMjXb3w0BzqWrR8kUUAkQikUgkEolEIpFIJBKJ/Jr6tQlgzp8/H82A+RklNAlDFiR1habtsdVy+PKhJPMVi0vrDdKGShCGWI5Hf1KnTxecPn2eXWsXSTWK6LleErfdjT9RwNRVDgymePpykfOrdXZKbXQ1ScUJOLx/ByKe5Hq5QyEfJ5tO8R/fWmKr7ZCIaZxZqdFjqjy2t5fvn1/l6kaVR/f0Mb9kI3kBhqFy7+4ChzIyy6ZKd3yErmKw7snIUoDVaBL3OoxuNZDqVeYrCb5fhAPj/bwxXyF0Axr1Jo16EwmQ4gleOXOVqTt3YN73OPWr09QCg0JcZaV/F0tLG3x+MoWfT+JoIYYs0DyH4tkz1CUDkoOYEwd4pdNDIZukWO9SciWulVoEQcBCuc3p+RIjWZMrS2X+5yN55GaVPlMhfmNejipLLCxtMpbK8a0jg2y2HAbTBjvlDn0bDaprJZIbCzRnLiEQCAHO1hb+6A767/08r1+/TigrNI9OIcViBJJEdd8pmtk8vPEc2eZrfHn3Idp9vbhSEnVzmXC6yrwyiGbEOJgIMVdmkSpFpI4FQiB0Azpt8D1kVaX+H/53xMAI7Qe+wrqSpGV79DZDRnWfoyMZ3nlnhe7yPLA9j+LEZB+9rz1JN25y2/1fYklKUClWkBJJRDyJ3+2wsyfOQaWJrnjbrbj+2myE3yZq6KNWSngrCwAow+O4uQKukH+q62Q1wWg+zmK5ffNY2/G45kB/2iClAjeyHSEE6w3nE+HLB96+vsU3j49z9voG17vDdBbmGR7IYabTKPNXMYSHMjCM5NuMmQa26/POUpWdvQl66bLLazEY1PHtMqLuE4xO8e3NkMn+LOv1LVQ9gyYYc1JhAAEAAElEQVQUKG0g+R5etwutBrIZx8j2omgqhtWE917mW0dPsOIqONl+HurJUyxW8FyXv3x/DTSDraZNT0+ajXqdbu8I3tICiu+TS8VJCRflwtsUzc/xipxj1ZZYcxRKxQbM1rlnNM23DvYSzJYwcjmSV96BlS02Wjbx/afYOT7FVVulWe/QM9hHfX2dymaRe06N8heXiiipNNkEZEwd1/c5Mpxlo9HlmcsbNDouGVOjJ6GhqSozxRaaLHhvucpgymChATvHpzC6Dbrt7RCkrKfZGh9h+swGn9vTx5PnVwFBOqaQiSnU2x1Cx+H8UpmHdxa4ul4nrkC/1GZMz9O98zYubXVYuLTGnoEMf3BijKVSC4mAA/YGG8vrNLo+qrH9t9BzXVKmjtVy6DgeqbhB+yP3Qc7UttO8SCQSiUQikUgkEolEIpHIr6VbFsB85zvf+dTj7XabK1euMD8/z5e//OVbtZzfKqbk05dUeWh3Lz+4uI4XhPhhyBP7+knoCrNbLYIQ7p4sMJ5SOf3iG4gg4NDeKaqvL6N0V6ktfpuD3/oDrHQ//+/nZrhzssDnD/ZzNKySlD32Tg3z/ZkK16+t4ocho/1Z/uzdJWRNRVdl5DCAIKDY6HJmscyR4QyvX99CSDJNoVMw4zw8lSU8/RzqnMKDJx+jWG0SV1p4qQLPrXaYLzb54tEREnGb7voCB/pNzJ37sITC28VleuImQTpJs1ZHisXJpeOois/KRpk9xSX6TpzEyA9xthZyrSNz1nIZ6MQY1ZL0epu465v4gyPMbzVRRBM2iwRH7uDd5RrxlTJ/eHyY1NnnebjaxR/ewZsixmp9+1PmUzmTzXqHATNOobbKeH+GzWIFN/ARgc9GtcVbCxUOjWTZnQ+IvfQ9NlsWg7unqM9cQgIQIfg+Qb1Ku1Sh99o59u6aRIrF2ZIMRr7y36GHHk++Oc1jfkjjyhUIQ8JKm1w6jlWr47oeajzOwa/+D8SFh/bKj+goDqrdwV28jtB14g99ASfwUYfHcOevgpBYuv3z/OjdWVx3u3WaFE+Qq0l889ETjI8qFOMT4Af0iC752gJqXx8A2domX7trD9frPhcvzCB8l/0jecbcKur02e35JtkCXiL1q3sB/BLpgUfw1su0Zqc/PHj+XfTJPein7sOWfvK3UBG4PLgzx8uSoGY5qLJMx/FImyoPTeWRgw8rG4QQ1Dqf3brNDUJsx+XBPQXuHErgHR/FbFV5arWEFriQ66W6WSJwPQxVxsv3QTLHA6MJhsqLdF76ETWribo6h5Pvp33lKo998Vt8Z6XFwpkZ/teHd9FaXwPfR1dkTEMH19mutHEdgniKHsVHsesE777IkfEdGAd3sLy1SSLosE6aIABCuLjR5PM7+1irJZBHM6R37SXpd0mcfRnnzZcRQ0NMk2a16VIszpDoH2DF0ei6PlcqXe7vlYk5LpcbElVlguF9h+kfHeb7b1yhUS+y3PbRdI1c0uHv33cE/+oluPYO/8uJU1y2ZJaNkFYgMTlQYKtpc22zjh+EEAQ4jku14TEq2xxyG/jxHgJNRldkdhQSpAyFipUjKUvEdZm67XG57BCTBfWOg+2HqFJIf8ogLkMuprJl26xV29w1mqbstRBbW9x9ajevvHWB2WITr3eYlY0mC8tFUnGdz9+2gyffvM7E4RyWU8d3XeROmzAIWL82x+3Hj/PD6RI2EsFH5g5JAg4NptCl8GZwF4lEIpFIJBKJRCKRSCQS+fVyywKYP//zP//U4/F4nL6+Pv7+3//7PPTQQ7dqOb9VgiBgMqOiKRK/f3yEctuh2fU4u1pjpdphshDH9QMubzSYX7HRZA3cDoGQQcBg2iDR9dDmLtHJ9bPZ8hBIJFQZrVRm4eJ5Wg9+jbniAmEIQ+kYK1WLdtemN2HQ9QJEp01CSNiyxvRajQNHBjk1lmNjo0S53uKBgzvhte+S9tr09E+RXzxDdmGJUqONh+DvHDmO/uVHWOmEvFbvspI6TFqNs0vVcF2fYsulYTmYaozBySy+F5DyLGqLy9T0HtqLi6y/+irpPXsZeOzv8l4jpB1I/GChyT84ehfWqyVSikLJvdFCSpHJHDvBRdckEwuRNjd552yLB+0StQtXCc6d4c4DB9GHjvLymgWSYLNURTLjqPOXeXTnMZ5tKyxXWohQ4Pghu4by7MtrFNeKjHseUjpLODeDLG23ibs5S4UQmZCOkWIzNHj17CqhgEJ/L4QhDx7Zj7J8DmHEELKCLyksVdqMphNUKzW8UDAou5Rfe4mcZ4HdRQQeIgwJu13aL/wI86HPE5px7HNv0zr1KM+cX8L1tqsphCyDolApVXj2wjKPbM6SXZjBK20SP3oHztw07blrEPjoR5ZIPWZycGSSvdIgtXoTOi20cplQCISqYtx5Px1Zudk667eFEAKxNIf90fDlBvv6NObgKGJi13YF0E/IFAEnxrJc3Giz1bKZ7Euzr88kLrkfe/iCICBrap95HUUSxFRB4HkYcQ0dBT3VR7ZZQYhN/GYdnRBHFrS6LmJ9jUKhgO7aLD77Y+rLq2iayujkQZbXtpDqa6Sf+wHjhz/HmqrQLFdI3n4XrTdewnYCNENF9RwkM07ixF20GhXq6xsA9B45TN/UJO/+yb8j6HZRRcjY4Cj/cO9J/u2CTyGhk4wbDGoaLy212Kw5JETAyYOPcXzfUaz1NRZFmnpji8D3cbc2GR2coBVo+J7P81sho2S5PL+FHDPptkKeuVAiNHMoAtIxDVfIfL7fZ/W732bMFJS2KnTeeIWD+/Zx78m7aOhJ/nJ5k3c3OkzkTHb1xLm65kKzTttxsApxjM015FaTOx65FxuZN5dqPHW5dvMx94OQPzo5RjqmMJw1KLUdehMamZiGKoETgiwgEzeoWC6KqrAzFnCoL4fTbjFz+ToAoeszkBtksdSk1upyeWmLQxN9XG44HOrLw9VVEBJChHQtC6m8yV37xnl2roYktid8GYrEg7t72ZGLIYcev12vvF9fOVP92Nem9tNVwUUikUgkEolEIpFIJBL52+eWBTDf/va3b9Wv+ltJCjzG44LBuEHLT/Cd99cYzZq8s1il0nFxvAABaKHP7pExpM1lgnaTrhvQ6nq0ug7u4gLm7T7/6yO7mK+0WW9Y7J3YQ35ghLc2LPqG+ihVmqiqjB1AICuIcHszOASwbXRTpul6BEHIwaxCW1PZke/h7mxIV/bRhkaQuhblt9/EC6HH3J69ICdiXN5q8ufTVdZqHRIxnfpcFd0o8s3bx7l3Ms8bs0UsIai5UJADrJVFQs8jrghmyh0Ge/rZOH+B/uFX2bPvc8xutSm1bZ5v6Tx68lG0rQW8jU0yQzrqrgOcbytcuHiNZE+eeq1KVSQx+lPkDYVK16N+6QInh8a4bCYgCOjp74VqAOUtjNk/5Yu7DlHdt5/64BTFtktpZZXpBZWs5LFzYBDV6iLqDlLgI0s3NuokCS0ex+np492uwUy5tv3YhRAguF7p0HBD/smB/XDmHcIQJN/brkBQNeRUhm4gSEgBQX0DSutUrRaZngKi1UQy4wSdNjhdAj2G3DfImpbGuVH5IlQNETMJhYSQFdZqHeqFUTKrCyTu+RzWM0/iV8sgS4hYDN9q0zrzJsVYP69tCkpFHxpdRnI7uPvhOxlIqnQSacKfcS7KrzMlDHAuv/+Z553L51DGp3ARP9H1hCRxrebx3PTmza5Rm7U2F1ckPn+gn6EYHwtzBpMqcU2h7XifuNbO3iQpFUJ/O6zpxBKITotJxeKM7+EJQbW7vTJFEmi5HIW4RmdpnsbyMsGNBazVOnSUGL2pJKsrm4wd7XIhncAqFrE7Pr1PfBVv5iJBp42+YxL9wDHa6+vI+6f+/+z9Z4xl553neX6f4683ceOGNxkZkZHeZ9Jb0UiiSIkyJVVXT9VWTwONbuwOejGLebOoftcL9O420PNmdwbTOz3o6aopqVWlkkRZkqJn0iQzmd6E9+Z6f4999kVQKaVISVQVWZKo8wESyDjn5jnn5nlOXOD53ef/J/XAo6ipFOlElIXvP4PlC1zHIRIx6WyuIbee4U8f/RJuKs1m29vpZ+P4aKogKgKWSi2WJvv43JFRSs9fRHEdUpaOkAG65tOqd2hoFkvVDkf3TdHyNlF1nZ7RDD9+c57p/jSDuSRuuc2A4WO/9iMa5TopESURi+C2mqjbq3T+8v+L92f/N0rXbzA2tAsUhcODKZa2qrSDAKFpdAKBmc2j5PvICI/zVYezS2WihoahCpqOT8zS+PG1Te7dnSNuauRiBi3Hw/UD0pE4S+U2bruDsDvsyqfZG5SpzbxOIpPghcQe8DzQddRum4jXxdBUHM/nxnqVJ09Ncv7tS0z27GZo317K8/Pg2IhYnFVbobdb418/tJuW7eF4AZmIzmjapEf3f6MAMPT3J4RgbO0qyc3tW9sy7KGlfbjnPxQKhUKhUCgUCoVCodAfpo+1ccNf/dVfsbS09HGeIvRzpJTo0qPe6eI6DilLYzgToe34tByfruvTsl0qdsDJE/txVxdJWRqO51FrO+Tve5Cqp/DNd9d49vo2QijcaAlu2DqFRoeteofRvjRoKuM9cSKqoFFv0BdRyCUjWIaKgWTvSI69Aynm1srMr5eYMj2C2as4zSbtbD9b58/hI0CC36jjd9psZ0d4a6FEvWUjFAVfSgQS1w948fomp4YTpNUAQ1OpN7vEREA0kWDv5AjRwgquL2n4CqlEFHvmOgciHp872E/cUGnWWnzjwhpvZ6aZOfkEl/c9yNevVzl7cxUzGkFWSpi6SkIDsbHIiOmjC9DxUa6f55F+nT/ucznlbpDYd4j4p5/GOnoHpvQY9esM1deYPXeBlc0yUlGpSh394HHyioc+thtFKEjfR3lv5YsfjaPv3sv17Sa1rr8zGa4oBIAQ0HF91kQUNRJBCpCahqapWKbGaC7BrslREoaCur6I124CYLsevqYRtBsIJLLbwamWMI+cpCU1hGmhJJIQiyPf69ei5fJ09Ai1/C62Tj5GI92HjEQR8fdepxuIeIqtiRN864VzFBo2fiRG0D/CspHlb9cDtqzs37sp/e864fs7zeJ/CenYCP+De7R8kIav8sLNwvtadrh+wE9uFLB/IQ+PCI/PHeon/XMrYQSwuzfOvbvS6J6D4Xuo791P6bn0rFzj7r1DaGKnabxgp0VI30AvIzEVp9kkkBJFEVimTr3j0Oo6BIqCG0ga9QZmKoPM5qnM3GD2zJuUY1m6E/uRVozW899HKW+x5Gj8aN1hvqOw+pPnaHcdxizJREIhKl36YzpRt8N4bZWUqXJ9o0rb8Wn74KPg+gHdTpfXrq6y5SoMZGJ4nk+326XT6dLuOjTbNq7rMZiKUPUVyq5gsdSm5gQ8fHicSDzKO6s1GrbHdD5OZHAIgcTxfLaaLol0irgIUNsNrMCDwCMtbRqu5LW5Ik/sybBvKEs0ESOby3Dy8CRPT6VRGyXmVgtMZKPEDYWELjjSFyMfN9ACD821OZnwCVyXqVycXMxEDzx6VY+huE7c1LlrJEnzR9+hu7JMtW0jESjv3RPFc4h0GyQTUYRQ8P0ARQbENUmyUeQBs85IfxZhmAStBnJrlZxwOdqjc8dghLtH4hzLG/RoLshP5rP3u6pbKtJYW7v1x63VftuX9KEpYidEUhTltj+hUCgUCoVCoVAoFAqFPl4f6wqYb3/724yOjjI2NgZAo9Hgn//zf85f/MVfcPDgwY/z1H/QflqmZn67zn0TOaJGlWsbDbwgIBE1uX+ql8LqCvmRXfQHDeYLDXKHDnM9OswP3phFlT49msbF1Qrfu2LzZ3eMsmcgw+XtDt1WG7m+hNljktcDNqsdHB36/RZ5S0VEIzyyvwft5iXui8LAUBz3te+SOnUXribwAg+naxPVVdz3Ju6N0V2U9ARX1pbAjGBqOsFPAwtFodrqst1y+fMH9vLslTWCehWzWOdwWuG4Ucb0fNTdE9Rmb9JnmaidBon6FtXUKH9+5xherUYt6tCj+ShRle++eAkDn0xEQ9dVhB2geDZHs0nMVy8TGFGiIk4bQd/oED2bF4mszuBXN6jWKwjTIvbYF6C3n87rP8Fc/Ql//IU/Y6kj2Kq2ODKYIHrlDaJ7p+n6Ersnh1eroCUSBIkMDSdADwL0TBat7iKRCCuCpYqdFQBI5hseD9zzINvP/3CnDwySiK7SkirpE3dRXZhH/lzhoW69jpEfhM3VnT4dyTRycwPXduif3Euwcfm2MSJ6B9hWYjRrNsttiyvXSsR8m/vv+RJjbz+DLG6j9ebxR3fz5lodv9NB8z1QdaTcOXPb8bhZbHOy3/xEhjC+bqD29uE3PniSVc314esGfMj3Xmi5uP4Hv7bedal0A/rMn22TUpLTfb5yuI9yN8DxA+KGyoDowo3zODcuIT0PbWAYc/8RpBVFrZc5Iq8xdmI/l0ou1a7LeE8MJRHhJ0sFHopH8aXAUt4LaIRASont+MRMAyeSoNIWzCtJdu05QOvGFarz8xi9WQK/QVDaIvbIE+wWTYy9vaR7M8hLbaJxBbW4RtDtoMdTdOwmY6keEtVluuIIc4sb6AFELAupqDiBgqEIAj9gptDkoT15ZhbWcf0AzTRoBQJVCCKmxkBMpda2MYRkvd1lMB3h//PKAm4g8f0APJcfdepMar3sP3gYY32GsuMy0ZOku3ATRSjkWtvsGe1jtdmirBh4muDtlVl2jw+yt1/l1KBC57lvUVteoWf3BA8ffJj/tNik60qEqaJYgglh4zg1lEIH9fpl7k8leeiOhzi/XOLixZvIjkNysJ/P3znJ7rSF+/CjlM+8QnVpkelDd7M8pxJ4HooQqJ5LnxGQzEUZzSU52J9g/5hJ7fvfoC9h8EQ2Q3XiMDZRol6HXPMGitiPg6AZQMMTWKqGKYJP5LMX+uilIzrnN1qUWs6tbdmYwbH+aDiGQqFQKBQKhUKhUCgU+hj9o5UgC/3jyUU0LF2l3PW5cn2TXbk4Xz42uPPNeymJ+13enVvl+MkxKu+U6U/EiTz8GM+9fAVts4Dn+UQsjYwZI5LJ8+z1bf4v9+/m+ZslWtIjLgS1SpWv3bmHYicA6VMulqm2HO7YO0SusEB8/izy7Mv4UpB4/AsUX32R9PguyurOkItoCp7jIAMfJRonkDsrATRFwSTACSRGJIIvBB1fsl7t4HVt/mh/D1rRIV2tI1/+LvbaKjaQf+QJ7FwO4VRxhIK6ushQvcF4PI5sNZHzL9FptrH3HuHwWD8zS5sIzyWIxEHCrr4047KM0DQ0u82ufA9NK8mAAfbSPNrmHH6pCIBwHOp//f8j8eU/Rd9zADU/gHzzWXbduMLhp75K+zt/A5qG26hgHjjOwL/4v9K5fJ7GyhLClwxELdr5fjrXrtNjWPQODGKrJlnVJzCh0HSIaQpnxRAHPvdHiIUbRO0m2elJGokhNlot5PIK+QNHaV84C4AMAuqlMtmBYcyRcdT+EaIDI4j8AP3RNPlyQGm7DEiUaJyKMNmodLh3Ms9mx0XtH6K9usgPr6zxlXueJHf+JwRmlE6ql+25JijqzvKcX7BQanNyIMonsQu4HwREDxzDWZoH/xfKgKkaxsFjtH+DiUvH+9Wv9X5xaQzvrWrDvRXMmH4H98Uf4K6v/Ow6GzWcxRniT/wR5sHjdN5+lUxhgzsjKTabLttXGnh3P0ZbjbCgWeyfnqZ28zrtdpdMKknb8eg4HkNTu/mBF6Phtnjj2iqJw/cwODSMff0SCdnG6fqknvwaQX6YtZpDSnPprazRWp1FOl3E+CT0DyOaTTTVIKl4qHabiNhZzaYBQaeN4ntokRjCtJDdDr5jk5u5wBeO7eLMSo2ikaLe9tjTn+TE5ADlWpNUQuNQzuT4QJyf3NgmamjUbRcCnyAIcNG5sVbh8PFJlI1ZItLFbzbwXA9FgN9s8tBwH3+95OI0PDqoRHK9bN6c4cjhEZI/+kvE0hIx00JXJMNKh6+dmGCj6eL5AcVKA39pEaXbYXxgN2O7hmitrtAqFxily/A9B0hm09RrLc6cOcvzhSrJdIrDxz/FricyVDse1mGTxlYBsb2GiCdRC5tEgoB7d1ksXJ9hSlUZjqpENhYIVm+Smr16K2JVPv00fqvF8wXJ7HYD15ekIjqnxrJMpnUU+f4ydaHQLyq3XTYbv7iqL/pbuZZQKBQKhUKhUCgUCoX+UPxBBDDf+MY3+OY3v3nbtsHBQf7Df/gPv50L+phFFY8HpnJ869IWfrAzYXdzu4lQBJ+a6uVqJSAyMkZHtbB27SV5x90UCkWUrXWSnguKiioU2vUa0cCnmRrg8kadf3bXGC/c3OLo1AneXSzwzqs36c/EUA2TwVSM+8dyvPvudV68cpWRwREee/TLyO/9HwSriwS2TTc/jC40ImOjyMUZEoaBH03jS0ipAeP5FJuOAq0GRiJF3ZW47k4T7+F0hPnlLW68McsjR8bIL92gUyzs1FiSkubrLzL02FOIK+cQY3vwDAtt/iqV7QIilqB3ah/dH3+XRK3AE3c/QumuCa6QZtuBO/pHEa/+kNmL50glkgwlVVS/S++ufYj5q+gL1/DrNdA08D2EoiCDAOfGZfQDx1D7h2iceQE124vfamAevQPPjFIXBtTbpJ0Zoj09aIkky4kBrhSb5Btd9h07xBvz27jlJjmzSbe0RU8iQTSdJ+02ubRaYTOb49jxhxgdTOAFDsWCg9Hq4Gxukdi/j9hxjfaV80jbRgiBNjRG5NEncTpdhOciHAfTcvjM0VFemI2xWmnjIqjVHe7c1cNgyuLKShMUDS0/iGvbXOkaPDAwgqyUUDwHXdPwY1F8VeMXu32bmkCIT24Pim6ml9gjn8N+61W8yk4Ap2VymKfvpZvphd+g/0YuZuwM1w/Yp6uCpKnw64IsZWvttvBF6Dre2DTlRB9rWw2Sk8dJxdK0r11ipe7g4ZPM96KMjzL3+jo1R2Ps9CNkFYXG7A0iIiCTiJAYHmXt4L0klCQJGwy/l7cvzjE93MN9j30Gbe4KslKmvLSEu/c0zuYSleIm2tgI2c99hfZPvgeRGJ1YBhFJgedSXpjF2HeKRLPEnv4019YqaIpA8RxULKRp0pNNcGCkh6BpsKezQe7UIW60VdpdB7vZYl9QZjjRpj37Jvb6Cp2TD3Ot4DCQSJOKRFjasgmALUewuzfHatNhQjMQvofi7PS90sYm2SxUSC/O8fj9XyJTcqnbPnf3mYxm6kR++J9w6jUcx0fvH2Zm5ChnbpTYTOjcaEB/XOPxPTkKa4KugCnqlGzJ2l1fZGlhmc2FFQ5POCysFnnz8gKG7+DaNvVIjO+/donDh6eJC5/dcZNNfYBavg+rXWOkN8rpiTwDKZNePSCnWMjpPdjtCn65sDNSFJXIibtwuzZLmxWubf+sZFSt4/Lc9S38PXkO9GjhKoZQKBQKhUKhUCgUCoVCod9BfxABDMDIyAh/8Rd/cevnT3LtcyklkymNPzk5yveubrFW65KyNKZ641xYr7FYaqNLhdNmnCtDx/kKLqsb2/idNkEQEEgQTpdsNE6x0SST9mg7Hn/51gL/7Z1jnF9roFsRRjpNAs/Dth1WiluY9TgP9WkUIlOcub7Gm7Es941P4W1voB86zbkXX2f6n/9LssNDeN/9K7A7BLaN164z0triwcN7+Po7q0hVRUqQvoeBZHdaR29WUDpNQPLC5WUGpw6QaLfwl2ZxalWk3SUZNSmP7EYZ2YVmRbg5t4JpGuhBk/JmgZ6nvoK9OI9Z2ya6/wTFmTJeo8kbC23uHR7H2FynuLmJEe9jIJcgvms39XOv49eq4NqIeBLpe6DpCMNHdto4Vgw5MkXi83+CPTiBqBZYrDucWSyxvr6BQGF8rI+7R3WyToNyvc25S3NI3+fA8YMMJi2abRt7YxVVEyTtBl/dN4kaiRKPWjiaCVJSbrv0GJJd2SivlRJMjYyxfvkqsXye3oefQiUgmc1gKpL6D76F/9PJWCEwJ/fRc+pentybpWZnafmCuWKLjWqLhVL71rgJrAhqNsdW00FGY1ApEdlcYv/4HZy3rQ9MDg4PpvC9T+637wMp6fYNo3/2y5jNOgB+PElX1X7j5ucZE3bn48xuN9+37+hwhqQmf2VLD03TcOdu3PpZGAbVQ/fxw/kq5bk1pBAEG4KebIa9Rz7NO3ObpKMm/b0pVgsdHpnu5XuXNjjb28P+h75M9lGJwOV4ymS90uLcShPbtHnqQB9DkX7UlSjBi9+n/txVdE1Fn9pP4jNf5Obzz9JaWQbXpfLuOxx89GHMA8dwSkX08ha1QpF0T4bEyVNUK0WWrz/DU1/8UzarTZqNDkIRiG6HhKUzpUtShUUquw7j+AHRVg2j6hG1TI4k25jLCzhvvUSrXMPxfBjfT7Lq4jst0sPjJIbSNDsOQlFoBRnsqEDEUgzkGsjyBrEjJ2j2jbN95SrDn3+C713bYmarzlh/hv2JIt7f/SewOwgBZizB1tGHef78IsIwSPcMYmqwXevwvUtr/NPjhxgTbeYrLV5tW1z54UWSiShHx3aTn8zz/f/6Al3bRYtaaELQcjx8oXHp6hxf+ezdfO+5t+gZHmJqMM+pkVESW0usvXuOQqNC//69aKqC02oQufMBtKGxncdN0wnsLr7j0NEswHnfuHhrscxEZgDzE7gKLRQKhUKhUCgUCoVCoVDo993HHsBsb28zPz8PQLu9M9m7sbFBNPrBZS8mJiY+lutQFIV0Ov2xHPt3kQx8spZGf8Kk2XVp2R7fv7JBLmGRjeqMZVO4us7J0QzK8nn6FAtFEWgoOH6ADCRKt0XMiKOqPgIo19rMFlq8eH2Dqb4kWqYP027SWV3BdhyubEgOH87DC9/l0Uef4ifXtzh17F6icxepBipRQ2e20CQ+2kfiU08SzFzFM6NUjBQ1VyVlN/jaiWFeXqyyXu0wENM5PZphxPR59Y1LWLEYptul5aiUggyFUpvB4d2Y2TpxS8fo6aVTbdPKDOO9/CMsy2C12qXj+LBZJzG3Rn4gx8i+PVwKkqxtL9DZ2gAJG2Wd/XvvYfyBNCXDwsqlSLQ2UX46Tt8r34amE6ga/tAuOtMneakep3apSCIxypRrklUTfOOtt3FdD01RUQKP+ZUCG6UGX3vwIGrL3ynn5ftcOXeZw0f3MTYYo5ofJmso5J0qC9UmP3npMhIQhokyOsHbqsqDeweoNuskE1Gax+5HNFo0trexiwV64xa59FE6Z98gsCI/NxAk9sxVIpkelH1HSWkBMUPjxXKTatu57TkMECg9eXozBpYw8WMJtOFxjg9MsHy9zHaje9sYOzCQZCihQeB+7OP5t0lKiaOokMz8/MZbf9WR6PUq0nUgGsOJJfA/oJyYEng8NJEhGzW4vF6j7fgkLJ3jo2n2Zk1k8JsFWd3JI3z3ZplGs7NzSZpBqetz/soGy/0pFCk4M1vBmany9OFBlssN/ruH9vDOapVvXS2S1AVRPMZzCR6Ta3y5PMva5En++rvn8RHct3+Iw5/6HNmHPw2xJNdFitgbP6Zy8yZBIFE0FYTChedf5vS9J0gdPsHmhUtEhnYTPXSY2qs/wd9YZyCVQ3nuG/z39zzGG2XJarFBJB5lj+UxUl6k+P03CUyL2CNPsu1pjFInnY7TOXMeQ/EImg2EgKSl4a/N0RvbzXytTlAoUtZipCM6nXaXii+I54fQ+j+N7raImBqb2xXajk/6i0epppOMVkpcXqtSarn4KFQdianv9F+KHj7J22v1nXtnO0RVwXDKIKqa6K0anVabTb/DC7NFltUkSEnD9nh9rsDoQA9BNI5wq3R8ScSI4Dg+gaLi+QG1ro+WyTE/v8rGygbpxF3021BZWiZ/xynsN17CcW284jauGUPTVPTpgzQLBfzlecyBIVJ3mYwlJlhq3P68tRyPphtg6r/R8AmFQqFQKBQKhUKhUCgUCv0j+NgDmK9//et8/etfv23bf/yP//FXvv7jsLm5yb/4F/8CXdfZs2cP/+Sf/BNyudzHcq7fBYqiMFtsY6rQlzS5slHnnt05TE3F0BQODaZ4da7IgFugaXso189wZPIu3r25jqkqSCQykCQ0wX37h1mvNhlPmSAEg+kIC0sbHBvLUV9bwXE8NKEQ+B5toeO3O9ivP8+RR76CO9JHcd8JWsUiEyfvYi05xA8WiwwHMfJ3f4G/u7RBudFGKdokV1bI2xU+fe+d9GSGqKxvMHP+PGfqNrYTYMYTBLaNFYmhEhA4Nl0/Qlq6iEClubFJOTPEWs1jn6lyY6WD7cudMmVA03Zhs0hqZIQELicO7mJruI+V9W1MXWNRWtyYr+H5Vf75o3m2nCS5fUfwN1bxi9sIRQHDxEvnWPM0IoMTOKWAgqfw6oVl0qdGmCvUcG0HFAXPD9BVDSEE7Y7N1UKHfVPDqNYCnrvzTfZWo0Fw43X6qgV67QrtT/8xL11evrXYRHouQga0PZX//a1lHprsYb5QZTgTZe+Tf0RPu0LaaRDNpvFuXMa3Ih+4MsO+egFz9z5sTccg4OhwihdvFt73Oolg33geN5IHoOP7aAQ8daCX9YbLfKmNpgimemPkIwrqJzx8+VWEEEQaNezXn6e5tQFIhKZjTh9EO3IKW33/jLguXe4YjHCoL4YnQVfAEj7BhwhfPM8jsnsaZ3EWFIVtI0WjuQqAEgR0UzlWK20MVeHKaomn9ueZmVslapi8fnOT/+aucV6Z2aLQ6DKSjrJUbKJYKhvr2zzXqfJQvUSie4Y79x5mrtTirbkC7yzrfPHUOOc3HEa1dVo3r6EroBoGqqbi+z6BlHTOvwmtA2wJCz3TR0NN4kqTJhFSQKJRhv/0/+bJ8XE66T7EyGFWf/BdKqUyQtVQFAUxf53Z3ffQHhlkcPkK8Uye6vlXMSRYmoobBHSvXuSuJw6z3fKo16skBjP4UqKYFoeyUfIxg5m1MjPbbZZlBLupsGe4l0OuwcblGXb15nlk/wDXCi0aQkfND+BVCqjJJHbfMO0lF1NXEYkUCJWUBsHqAmq1yGr8AJVmg0A3cbsegZRoikogHRpdlyCVJahWdwIcAVIIPM9DCAWh69RqTWKmhto3xELTp2P1svf+h1Cun8UvbiKsKP7wbvRWHXtpDmdjlcSTX6XWqNE0E2y+8hKHH0+zqiRvC/gEoCnv788UCoVCoVAoFAqFQqFQKBT67ftYA5h/+S//5cd5+A9tamqKf/Wv/hWDg4NUKhW++c1v8m/+zb/h3//7f08kEnnf613XxXV/NrEshLj1OvFeI3LxAQ3Jf5eoqspiucZSqUUuZvC1E6P88NoWlbbDwYEk//NrC6xWOpzc5VOpNkm3GxzavEz+yFHeXa/R7jjkchlODKfoayySevN1TuyaoJwa5juVNlYiiXRsDCHpqCoBEqEq6EJi9fYyfOI4an2R9ktn6SgW8f2HebEV48zNZQ7nLK40JZdnS7y9XCWhCxTHpeR5yEwv9TcvoSZTTEQFW8U6tmaBlLSrNWJ9AyRVSaRawBfQ6Lrk071Ep6Zpbm2SvPM43XKTvvFxgo1VGoHGRsfH9iRCEUyeOEJKCQhe/TZ+sUG+f4DTB4/ywwsrlJaWQRGk0kn02YuYsRja9CFi0Rit731zJ5TSdNz8MOnjD/CdmkVDVRnOxUjELHTTYnarhhpP4LWagEAaFlpPDhSFJUfl/rjBP336Pl67tka50SHWm2ZILaKWFtFSaQpaHM+v3rqPQjdB0Sg2XartnVJLri9ZKLZYKIJA4Z7JSU72R/DPvn4rfBGGgTEwgmaayCBAqioqAUIIpJRM91iUhjNcL3Ru9bTRFMG9kzn6I4Ig8HeO8944N/HYlRBMppMA+L4P+PA78Bx8mOf15//+655dRVHoBAq+BFMBDf8DQy3L6dJ57jv4jdqtbdJz6V45j6WqqMfv/sC+HEEQYIngVjAo5Yf/fSL7h9AHR/BKBardndBGsFOur2tEUWWToNVCaBaBZOfe2zbHEjH6/Bbe7DX6pAcFjelcHokOqsJ6V2CffojRbokHtm9w2rNpDvXTM95P440f0zdwCFVXUAKfdG+WhhPQ8QIsS2U4aaK3KyiBhzUwzutNg7kXr/KlAyex177LVqVJRVOZzPfhXX2X2Kn7WDnzCp1KbSd48R0C26axOI+f3UtLz+H5PoFQUBWodT0sTaHl+ATSJfbSt/nKE3/C2SosGAaFepfjI2lyBjx3bYOuUDk0Oca7lza4a2qQP96XxqoV2SrZ5NUGo4MJhqMK8YxF/PNfJnj7ZbqX3kHZWMZUh/ByebRMD56hIzsO0nUQiSTxZJJ2aQthexhGmq7jkk7GiHkCISWJeJRuxMD3AxRFIZABIIhmUriqjpHrBcOgo+jETY2rxTpj/eP0XH4dJdePY0YpOIJMt4uI76yw8Stl6oNT0GrgBy7etfMMH3yUpfrPGqkPZaKkTQH++8fQ78vnVSgUCoVCoVAoFAqFQqHQJ9XHGsA8+OCDH+fhP7Rjx47d+vvY2NitQObMmTM8/PDD73v9t771Lb75zW/e+nnXrl38u3/37+jt7b21rb+//2O7Xtvz2W7Y2F5AwtTIJ8y/1wRads2m2JVMD6V4eb5Eqe2iqQqpqMlKZZtASopKlMTyEj3H7sR96cfkrp7nS4eOIwb7UTfPY2SmufjWBcrVBv7yBoNqhIO5EdYchbbTQldVwCcABvM9RJoVBk8cpfLj7xAbGqLYBaFqqJVN7j19H/rEBL1xi9cvN+jYXTzXpavoxDQNz+my3Q0Yt0xaK8uMP3Kaa5dvIhEEgOc4+IHFow8ewX/274ikUxgDI8TuOIlpGaBp6K1t7LdfpbtnClEpkrA7ZPP9zDkm+QP70K+fp4aCGo3jtZqUr10lcfMyjz38Wf5ruYon4b5jk/SsvUPrhbO0enoxBgbJ/nf/d/x6DcewONeJ8fqWy1atTa3j8sZSlT19CY5PpNATSTqdDkpcQdEN9EQcb2sdAh/FCPBenWWgJ8uffOoROl0fvVlGGTqBm0ngt9qgqGjazx5Lra8fzzDpei6apqGq6vvK9y3VXB7aO4g3Mo7dqCIiUbT+YTpvvkR3exMAJZXByvWRPHk3jqpzc7uJYRgcGzbpuD65uMlUb4zBdATt96w/0od5Xn/er3p2K22HcysVLq9X6XoB6YjG6bEe9g8kMDX1ttd2L59H+i58UDnFpVnSJ+9G6xv4+72pX8F/6qs4M9focaMEFQ1X03d6WgkN7C7SdYlaEdT3buPRwTiHty7RTrqIShEpABngVkpowyOgG2g9Odxokvr/9v+EbhvV0OkdncB/2yb92NNM9Y7SUi1a0a+y1eoS6dZJzF4mXd3EW1nD9h2sfYcIxqZYPDOL7bj8YKbCpx5/GmtriaCwhZNLkT9ynFqxRHFhZqfHvO+B2Am9PKFi+xKn00HN9OCsL2INjuNsn8PSFAIpkRKcUhHrtR/y5Kef4ofFFgNKk61z82wbOmpuiLpUqHQ8/odHpjHaNWKvPIN36R36I1FsX5KMxXjk4c/iJ7MEF+ZxVZ3Yp59GqBon8vv5ydmbSNfD0SzKgSQWT9MoFvhsf5xvv9vFVKA3aeHrKfTiOna9xtVmhccfPs2PZ6+gmDvPlKEpuKrBvXce5kfXtul4Cp1Gi8ODSfb2J4lZBvmYjRGLoSbi2F0PtdbEcVx8qYIMkM0WnpHEd1z6khG67RbZiEbB2xmLUUPlM4cHGcjGfuWY+Tg/r0KhUCgUCoVCoVAoFAqFQr/cx16C7HdRLBZjcHCQzc3ND9z/9NNP87nPfe7Wzz8NPwqFAr7v09/fz+bm5m/chPvDaAQ6L82VWCm3CCSYmsKR4TTHBmJo8jfrEbEna5KP6ghFYTAZoTdmMl9qsl7vENUEgW1zrm7wxPhult58m76T9xJVBJa0iUQ0gnye6uwN/HKBhBXDDqDy5ut85U/+Gc8UFPympLXlEzM1IhGLB8fiqNsVWmdfRZM+wrRQFRXXD1gqtzB+8jxH/2iYv5ptst0J2NOfQFmtYHsBlhKgRKI0/QA/lkDd2iBbWuaP7t7D2a0Om/Uuw+kIU3EozMwxawwQ3XOQwb4M/c89gzswRHxiN41nn6FccQh8n/TDTyBnrtCZv8nk+ATJ3jStZYU1R2WXKpjoibJeadEtl4leOsv06GF6B/s5tHGJ5t/9JSQzSNOgWzToPPsM8cc/T0FaxOeu81BpG5FIURsY4e+2BEt1l+Wmx9Secd4tlQkkRDM9dJfn0XwXRVU5lI9iP/OX2AISEpSxSWqvPEvQqKF0WmjJDL17ThIEKwSA1pPHNSN4jovv+2iKQPr+rV5KP5XUJZVKGWt4F+3zbxEfnaDxzDcIOi2EUJCqCoZJ9fUXcDSdt+O7eHmmAAKikSi6dFnaluBlMd3mB67a+KgJIXZWCQTBh3qOBgZ+eZDxq55Xz/Nu2/6rnl1faDw7W2Gu0Ly1rdGElUKN8p48B3P6rf8bRVHQVpfp/MK9+Jk2orBF1/t4/i+9kSm6NY9txabacgjqJfIDfWBZ4LlMJzXcdptsMsrdWQXtwg0i42OoBCiaDqhI28ZbW0EbHkeJGgQrC3TMOEFumA4KAVFUI4J5/hzb943ynbU6VG0ay8vEIyaPH7yL9Nkf4W2t04lFSWbzXL08iykCvFiMWqvN376zyNDePeQn7mS2UuSJeIvOm2cIJGhIpAzAsAikxJjcy6otONiToK0kGIhHkAP9GHMzBE4HRQg8KTFzvUTTSVZthbffvgwSIpaB4nrYrXkyY7t5d6XCqcEYI5dewn3he7jlMqgqkZ4etPwAztf/I8mv/Blbq0uUWy7NlS00AWN3Rzg42sO1xQ103SDpK3iZXh47vAurtIEeT9DxJbFkgqC4RaPdRioqrbZNdHuZP/nsndwotFhrBaQySUb6M3z78iYLxQZDCYODu/o43Gvxg7dnaesWep/JfmES7zQIAknXl0Q0Hdlq7YS2+T7aV2fxOm16hvL0DffhJi2GcRhORxhLm5hOg42N+geOk1835j8uv+p5DYVCoVAoFAqFQqFQKBT6Q/IHGcB0u102Nze57777PnC/ruvo+gd3NP7pJJaU8iOf0HKEznevbFJpObe22V7AW4tlpIQ7Bq0PPTmuKCqtrse51QaXN+tcXKsTNVSODKc5OpjklatrmLrOtWKHfeNHmQA2Ll9Eui4HH7yHzswlvEYDtjaYyvTiKAFSUTDiBtblV3j8nqeZK0ew4j5Jv0umU4F3X2X0wF7anRr09FBwBIV6Cw+FtuvjN2zM1RV6YiOcX+xyalcvVsSi27GRAvxmEzWdoW3GOXbXSZbf/CGR6iaP7B6n2jdM12tjJfp45ewsdVcSNxzub65hn30V9egp3GgEWnXSkSSy3eLya2+RHBxk6LNfJbdrjOqVS1yo+mRjGovlNiqSiVwMR3NR2yW+dCCPXlyl8c3/FRGN4isaTcdnu+4SS5pEFufpnDtHu9Kh5XgQBCi6zj997PP8hyWVl2cLfPX4MJk90xQ2tqDTRFcFihFh10API4sXCGoVUASt73+T6Ge+iDBNZF0SRGJ43Tbp2fPcdf89rNRtHKFRaOxMhaciOkeHUqxXfhYO/HRN1IH+xE4JqmSG9MOfxX7jRfziNgBSVdH6BlCiMXwpaZx/m/r+LADD6Rg9yRgr5Z1jljo+zSBCRNp8XBRFwWzVCVaXCMoF9HQGdXicTjz9936ePszz+ovbPmh70Q5uC19+3puLJXZlBrHYKc0WBAEiFr+1X4lEMfqHdsINIfBdG0zrY5n0VhSFK5sd3p3b4LGJJM/eLFJWNZr1OjHTYKCnnwNxj7ffPM9IT5ZsPaA/oaFsz9PT10utWCbotHdK6vkegeuQchrk/QpbsQyFcgslFqfdbiMdl1FFx6vXqDZVGr7JyPAoemWbF87e5PPHH6RXFWj7j1JbXMRRBqFUIjkyQa3bRY9YtFWLmxUbtRVwT38WkUjRJ1VK1SZC05CagZ7OUh2e5t50jr89t0AlUPk/n3wI+8JbjD3yFObKLPr6Ml4ygzh4EhmLcW6tDoqKgkTTNVpugK4ExFpVhjWTA7KK99qP8Rp1pADp+zjbmzvPbS6PXSqyUOrQ7dqoAhTDYOGllzm4fx/79+9iI5GgVa0xkNJZURR+0Epw6u4x/vrCBrslBM0GUUNFKBqPHhohcf0sN2ZXiPTmufvBx3imKrh+ZZOpXIw7xrP0x3SWig3Ov3keJZ0jbujc2KgyMjKN985L5AyIGxoinYVKGTWdxdYjCFUlcfQkak+KxMFD7O+1OJCP4Ps+Urp8mI+Ej+PzKhQKhUKhUCgUCoVCoVAo9Ov9QQQw//k//2dOnjxJLpejUqnwjW98A0VRuPfee3/bl3abzaZ3W/jy8y6uVdnfN0hM/OrZNkVRiNRKXC7anGsZfOvCGkM9SVQFOq7PueUKigx4eN8gL8wUUfyAN9caXG8mOHr3ZxnMxLCyBu0r56kWK8QHRrAUMBt13HiKWrtLs97izI0NrlZ9Hh9NoM3OsnnjCrguIxIivXk6sRTFtSqGptN1PQxFxVWg0eqSyRgkTY035wt89vAQP7y0iuo5kExh6RopU8OOJmgevodY0ORqNM31iktdaHQLKofvvINB0WG4soL21/8L3SBAdtoIx0YEAarfxYjF2LtrAGtoGGX1JvbWAilN4WhGo6loXNtuEjNUFkttxoIuRr2INnMRb2kOEYnRUUxc28VQdTpdh8z0MKUf/R1ashddFWiKggd4rkf9hR/y6D1f4EJDYNsuKpITR/bQXl3GysXYa7nkly+jvPEcAELT8TbX8Lc3MHvyeIUtpNwJYerpAYSiUAlUbNdnejCDBjyWjrBYbLFRcclGdI5EXeKtChFNMKTF8GUCNfBx1paQjo0+ugspAUXgd9oEa0uoIxM0yhVSwmVXb5z1usvzc6u3rRKpdft5fHcKTbofOL7+IYQQWIUNWs99F+n8LOQR594k+tCnsQfH/1FW3/yya9uo//Lgqe341G0fy9z5WUqJGBhGaDpKIomZztB982X8ahkAfXw3xvQhlFjyI39P3UDh3ctzNNZWubGsc//0LtTdY9itNvlsgripcfb1d+hNWPQlNMYyCqpv4198g09/6is8027TUlWCICAQCsmeLJ8ZtXB+8CwVO8CIRgmQRFVBNBNju2mjuj6qUCnUOtgxk0ODI8hkindJc8/BO9l88XnGB7Ls2b+PxbUCmvTI5ntQYnG63Q4LjsHRsSHWLMjd9SiDQZf82hLlRgdnYIxWpp/BsWH+8vWbrJVb6IkE7zZV3lb3cF9EMHnXfvoTFldqAX63i/mjrzN476Nc1HSihooTSEwFDLdDUNgkNzqCtr6IV9zCTCRxzNjOSrBonE07QLGy5NwAH4kIfKTn4isKTqvJ8tmzTK3cZOLInVx4+yJrnsvQPffznBxjbabMk4eHyGGz3E7Qo0smYwLr3Z+gezYRQ6O2sQlzs2wpY9TLZbbKNT5/bIRGy2Pu6k1wPXTDwF9bptlp8XZvkruO3Yt79Qw9zSL1aJrk3Q8S9A2z3fEo3fE4s6UOtKP0zDY5EYOBiNxpHhQKhUKhUCgUCoVCoVAoFPqd9gcRwJTLZf7H//F/pNFokEwm2bt3L//23/5bksnkb/vSblEUhe1m95fut72AjiuJGb/6OFa9QnlmllV9gDNLDaSEZsdmMGlR6Xp4fsD17SZ33TXOOysVHBcM2aZUbXBdV5hOCBrPfId4fz+sziOtKDXbhWiG5a0aY+NDtMb3crkesN1y+NuFgINDp5ge2Y/abVEdTNE7d4XiRhm/00aJJwg8D0UEaJqGnciyXe8wkU/wzuwmMxGVPz4yQLuyU4rsxP4xrm81uV5ssad3hGIAbywUSegmZmEFX8JbG+vcsyvD4OocQTaP2N7AGt+NtG10u4UiBM2Oyt7hfhrPfwvpB7hmhOiDj+OfeQWrd4CobuL4AS0gSGewkjFE4BM9chKtbwALBakbFDYLBCsbRFTo1OqIVB4BxE0Vx99Z2aObBvf0qoyO9fHiu/MsFRsMF+v8WabOcPEy/uvPoWjaTmmsnY7rqIk0QbOBMCyEpiMDn+rBu/nW1SLO0nVk/xB+AJfWahwfSbE7qTAUT7InaxKbu0j9uVeJ64K4odB5FyL7j2ANjdF45wyqoeOuLSEMCwwDiUACqt1FjWdxhAZC5dzK9m39ZgCubtSZ6rGYTqsf+TfmDdem88qPbwtfYKdxffvlZ4l8/p/QNSMf6Tl/E7r6q/ssqcrt+7uxJNEHP41YXaDxzH/lp0sRFMsCVaPx3HeJP/EV2snsR3qdbqtNY20VANtxmZlfRzTrjO4eox2PoHoOnzs8hFneRGs3iZpZGiuLSLtN9vv/O//0sS9RSg6w3fEQioLZk8GULRooqNLH73TxpEAKgabFEVqMTSwMXUFRBM2uSyui0d0u4rZa7E+1UTQNpVlluLFB30AfVd3ELxdxujblnhFKjsfBoQz/j+euETVVBjJ5nj66l+z8Rex6ne7yWVqKQdv2UYVEDXzqXZeWF/CNRQ912SEXt0lFNP7JVIJ4bxyDBkO55M5KGiDKzmoeLRbnwb39qFdexB/fQ8EOqDoSo3+U/olx+gMXpMQYHEbJD+CsrmKaJv575eRkIHGsBG7Xxe92caWgde0SJ+/ezUsbNsXNAo8nq0zMvYBlt6mur+MIgWda7N29mw0dlIE+cnaM46MZDvfF6O+UOFNwodNG6AZ02gSdFgBrhTrfc5L8ydN/TlApoVoxGokMJgFX58ssbFVQLBW/XqfVaLGGxaP7B5lMKb+1wDIUCoVCoVAoFAqFQqFQKPTh/EEEMP/6X//r3/Yl/FpSSmLGL78dgl8/QawoCt7Nq7S0BN1AodZ2kEDMMpCKgqUplGwPxw94d6XK/+nOCbqdLp1Gg9FdUXLLV7D/6zcpuTbGyDjqxDR2pUyqp5ebGxWSmTStWJbl7C5uzBWAnablG3Wbtb4EzWpAkFZ5dGgMsV5CEQIkCARSBmT3TPN6R+f11S3+9YOTJDRB1/WYe/llhlIR7h/NMOwluGmluFGoko1bfPviOtmIhhczSUeSBKuL4Ni8WisxOD1ONL5Kf7YHJRojaDUAyKeidMf3UnvhB7QaHQxDw0vGKBVbJHftoT1zneHh3Sy2wUeBRIrUpx6h/eKPaF16B3t9FTSdIBInefp+mjtLXXb6axgmdB0EAYlUgum9ewg2VlDfepZIspd4boxXtDgX1xsUBzL0l4sIzwXfR1gW0t1ZWWIeO42zNIfZk9+5uQMjvLbeodN1UGMppJQogILk4kqFPT1R8qbHPq9I88obZOPqTv8MAoQUOK8+j3bn/UjPw7rrQdR0Fr9Ww128ie/tlM2Svkdy/yHqRozLy9X3jR9VEZia4MJanalsDuH/Zj2Hfh21WsZvfHCvCml3EZUi9I98pOf8sKSUDCZNFAHBB+RO2ZhByhQQ3P5v/MFRuPg2Wt8g+B6YFlgRPKGA5+Fev4x610P4vv+RXKeqqqjVIrqm4r53X5XA58Dxg5xdqjA3N0Nffy95xWEq3sMjE4PUzryIdvJeDN9Bsyzst14g6/n0T+5DHL+H//knZxmdHGPf8CSxxgVajiAVixLRFFRDxzh2B98pB8jAJ5+KUmi5tFUTVdNIRk261Q1yyShxr4733N/wxKNf4kpuhKvdJl7vIL4Z56uTcVY3i6SiOoWGTbVdoet4/DejQ9TOniVq6tSrdZLNCql8D24kSalp86XDg3zvygarlQ5q0mS91uXl7Qh/cvAwV198hQfvfZirqQjza0Vo2vT2pLj3jn3s3rhKKztIZUKw/cZrJKemyfWkqTzzTaq+RzoZo3D9OhNT06zoOq21tfeeJxCqinXnA2yfPQu+h6YZdDpdOl2bjutz2C2ycukmPfEE/voSSAhkQNBpE1RKRHpHKcSyjHYaVN+Z4zvVOvsmBklMTCJ0HS3Xi/deiUAAIlG29RRnVupcvbSAECAiMU6d2MfMegmlvH1r2CmJJIFQeG2+xPDRfgzCACYUCoVCoVAoFAqFQqFQ6HfZH0QA8/tASslwykRTBN4HzACPZKOkDOBXzOOqgY+7uUq3d5JAD1A8l55EnGrXo9y0SUUNRjNRNFUw3hPl6kqBfs1laWGN0+MmUtOwDh1Hz+VwJ/bAnsOoS7Oo9SIRJUbkwDFmEsNc7dzeb8PzJWu1DsPpFOOqjV3cZOCRx2m/9DJ2u00yl8GYPsTN1ChXVmtM9cTZLNboaWzz2JCJmusSlw0MT7BQH+C1lTKVlkMQBPiBJBExWCi2GEtF6O/txd7axPYC6nqUbtdj+LEncN45g9esY0wdoHXzOvljcSrdDpapoacyFPU4K5eusvvoQTIjE4hGhWZHoA2N4R0/SWVrHmoV9EQKPWdjb2+B7+G9/CMGHv0CUlFRevJsthx29UQp2wH9+6ao//jbYNuoE1PMzazi+md56PQ92L1DvFiGux99ks7qPLJSBCFA07FO3YewouDY6Pl+RDxJIdXPyts7qxqUePJ9IcBMscXweAL76rtIefsgUDwXr7SN7Haxdk3S/N5/Bc9Deg7W4ZP4jTrd2esYE3sQB48y1DZpzZbeN376EhaakHRdHy8QfHBXlb8/6f3qsmbS/eDye/9Y0prkrokcr80Vb9tuqAoPTvaiS59ffDKFY2PXawSJ1Ace099eR/U9fH51ePphCSFIlFaZGspydWknBB0f6uXltTarm1WEEMSFz0zVZb6pcCApKK9uM3bPPejzl+m8/SpO10aYFt3rl/BrNe7Yfz8vbXTQxo5yeqAP3nkVZ3URonGih47gjU9iXqvT1EwIfEZ7LTYbXSb6Bzndp9B/rohZL+A5TbRMjmRE5+5ggwOjGmIqz7curPHKzTaiUeH+/WN85+I6nhSs1zo8X82w974n2RXzSMSzXGsJhBB4G7Og6cx0c3xqchBNU+lNRig0HFRVcNnZTWxoEfuNFzk2MMAD+3dDWyXdmyPiFfDtLjfTk7SGs/Qec+nrzVD8ztchCFBNE2VglPWax/o7F9n76cfZSKZw11YhnsDftZeyapHoNqiqCu1AkhocpCYsTg8qDCydpbq1iThyGMVzUW9cIwh8pATVtDDuf5zXrm/ilQoIX6LoBtcXN3nk0AGMkXECoSCDzVv3tBvL0BPVKWxuIwFF1YhGTGY265R9jV7duPVsqJkePAmNrkvdCch91A9pKBQKhUKhUCgUCoVCoVDoIxUGML9DkprPo/v6ePba1m0hTDpi8MDuHvB/zQS2ouKpJvb8DazJFLt7olTRmC13QECt41B3fDIRHQ146dIy907mODzaQ7G0Rpso8UN3s+6qXLlWwbZd9g6Mc3r/KbREhu/PlHnlcoVP7R8kGzMotxwQCgD1jkuQijCYjmJfuUgQz9G563GUwMPM9XOhLri6tI0qVO7qt9i8fIlHj46TWr6M0AXtjSJ2p8uNyB5qHZ+xbJRM1CAV0dEUga4ItmttAiNKenAcXfroQ8PU7/0cC67G5O49dM+eIYhnUe//NFI30KMRItk8FT1KrWITSMn8u5ewIhYTX/gS1+wEy62AE1WPo+++Q2Rrg3ZxG2tgCKVvEFmroAY+0VaVyvEHqVfqqCuLRDTYvWsC59KbJIWHzGWZaQV4cmcxS/nt13noqa+xoSZwG4ukvvbneGvLoOkIK4I9cw37wtsYB47Seu0F3PVlxJ/+90jTQk0k8Q3rfffW9QJE4BPUq++/8a6DsXsad/4G3uYa3voKIhJFTWewr7xL5N5HUR57Gjs/DLrOVEblxGiGV+eK+ChYmkYuZhDTdkqk5RMmhiKRH82ijVtEPAmKCsEHHVigJNMf7Ql/U9LncK9Jf2KISxt1Gl2PobTFdG+cjO4TfEAwKlUNYVrQ7XzgIUU0ilRUPlSn9A/B933MRIo7ZZtqb4qNQg09kWRtYR0tkWAwomJ0GyB0VE2j0bbJZlMolQKbb5whlcvi6tGd0lobmxiqSSwxQzIxxcWtFpk9U4yNbqGO7aHVaLHw9rtYa0UeO/EA3y9LNroeUUMjHdW5/9AY+802ZqEf229hjp+A/CDli+/QeOcthK6TeOAxMj2HiKuSTWFwbXaNLx8dZqbUxvd88kbA2FCORiTKgOpiNirUNzZQBUgh8GpVZjfWOHT6KPVCi7aIUOu6lA2d4w98ln1qE7m1TtRUkdEMdq3M8t99HX18kiv9ETaXVjl18iC95ZsYw+MgBG3FYLajkk+bzKxXuPr623Qf+zLbA0coLiwQ3+5wamOB2naJoVwGRzXJ3HkP+80swxGF+tUuK5U2yqXLuJk++j6zHzNw0U0T2w+Y2WrglQrvjQ8VIlEEcHNxk7sP7OGVm5soVoSg1USYFlbEZDqj31qVJpJplEQCRRGUWzaZeBK1UUHr7cc3o7fGgvIRhXqhUCgUCoVCoVAoFAqFQqGPTxjA/A6RQcBEUuGPTwyzWrNp2h75hMFAXMf4EE3RfSkJ9hyi+a2/YXxiL9rYIK9tdhGBj66qIBSSUYPPH+hjc7uCqatEE3HqpsIr19bR82PEvBTDKZNSCdJJhZrT4tmbRR58YASHKl4Az11Z44kjo1zYqHN9s4GqKpzqj/DERBzTruCPTeBcO8euz+7lqjrAG0sVbFROHxrn+HgvVmENYZWR/+U7bHVaSM8lkk4TveshilJnzLRRnTYpP0ZGuGgYCOnjBwEtF+q1Fqmowdp2lSuXF/nikSHcTgc/mqC7scb8ynmmHnwAp20jq3OIiWkmslG2Wg61VhfL3wmi/FaLe0bybG8UoFHFr1VRNY2gXKAtVRQrArqCKBaYKbaQ40c4MTKAtngN3YrQLWxg9OTwMr3kbEAIWu0Opq6xhzrH9C7euXN0enqJ7T9Kbe4m9tUruLaN9fBTuL4L1TJqLIE18y594yfZ9rX3rbIA2JWL4iFQs7lbk7tCCNxA0MQkNbaH7k++hz44jFKrEDQbeIFPt3+cpQtXaQ0d46WVLYYzUU6N5zg4kODSeg1VVbFU0EUAUqIKwfHhNPIjLj8G4CTSmFP7sG9cft8+Y2wCN5X5yM/5y2hCoNk7oYlrRfHfC0iE9OkzYWgytXMfpMT33V+an3iajrnvCO03XvzA/ca+o3Q+wj4dUkrE0CiRd7/J5/pGKI+NMavpDKciRFVJJGIh1TgJV2Op0mZTjRNL53BmrmNZBnajge0FEPgIVcFVNJzFOaY/cwdvzxUQpW2qN2/QKFdBCCK6Rq6+Sezic+x68k+5ahts1W1O5TT0m+9SmLlEz9Qetg4+xKWNBo3ZWYb6jzL15UNoL36H9vXLnPzCCRZKOlYki6iVCOpV/nRAEKsW0NfmUS5s4d/9GJmIyhMDCs97WTa3d0oYCrvL4ZEs97srVFO9vGZHKDS61Lou1bpBWWtwas8eGpks6o2LFP/2fwIZIBQF13EIzCj1VoeNrRJVV2PAgpjTIh54xCMZ9g+m2XIcnG6bcsPm4NH9jBbn2P7JdQKh0IlnyT3wMD+uRzHMLmcW2nxhYIz+UpFm16E2v8D2/AICmOyNowyPs+q033/fgG0HHsuaDJ0YZmMkQX15keFcijWivDZboNszhKooRJNxGqrCwYE0cq2NSEfRsj346s8+rndK4kFYgSz0QYSAbFS/rY9X0tKodT/63+uhUCgUCoVCoVAoFAqFfrUwgPkdI4OAhBKwP6sihLbTZPlDhC+wMznbyo+S3HuA5usvMHL8NH9y9BTT/WnW6l1SMYuBVITtaoOuorF7fBArGuH5+SKZbJ6Cq7BwdYN8wuR/OJam9O459O1VdF1D3NS5Z2SUs0tlqm2Pv3l7gb0DKb56bIhDSYF+7R3MH16jIVzSu6awexq8ulBlfmMeEU9h6garMw0KjS5fns5iljZpdZqomobam6cdSZEZ20W667I6f52uFFypbHPv5G7e2WyhCYEvFIT0MVSFhyd7WLhwEU36pN0GfqeFUdlGi8RIxkzWrl5j5PBJ3NlrFCoN8kadEddlPJ3G2HeUVlzj7sXLFFc98sfuQ1FVAsNC9brgeUQjBk7g4XQ9At1g90CWoNtBu7yCsXsaLduLMTy+s9LG6TKgKvT1RnADC7VRI7K9gOt6GHv2oydS1JttgslDGP2jVBaXWL46g+84ZKMxBgazqLUSd+43eWYzwJcS+d632wWSfNxkIK7j+y7m9CHsuRsIKWl6sFJpg6JgVKo4sRQrpTbDw7sxO3Xa0TRL5Q7SCIi6HQIZ42axw5mlOf70jjEe29fPa/MlFooN+hIWYxmT+yZ66DUDPjAF+gfypMQ8cTeRSJTutYs7fV8MA3NyP8rhU3RRPvqTfoBIvYxz4Syd9WWEEOhjuzEPHqcTS96asPS8DzdRGQQBcmIPxtYazsLMz+0RWAeP4/UPf+TX3zWjRB/7As7ZV+g9/xM6hz9FqlVEzfYSmBEqLmw2Oti+5JWqxrFdE7TnruC6ASlrp3dMgMDoG2AbnUBR8Oo1LMtgqLVJtLlNTzqBoirQ7eIVS9i6Du+eIT+8jzv1Ls7lBa6ev0p+qJ9XK4LzbzxPpKcHRUoK15e5Gonw2Ue+QuL8i8h6hccPniQtXCLrDZKlBZSFneC2dPMqbT1C8dy7GKJOZG2Vx/pG6R7ei4MgqQREGhu0b9j0fuYLXDtXxfcDVLtDK+hyvrjK/FqJpx89ibexiZHpwakU8daW2D91By9X21RrTaLJBD21TVrLS9iBJGJodKoldNNk74m7UPssTtVmURJJyslphrM5DEOHdA8lqbE3ZXCj0OLgQJL+5DG8rTnWNssYqoKqCLJRg2wyRnDiDrZevvm+e6bE4mTzPej4mKpHdiiBZfVSb3Q4W3WZKTRB01AiURTfYSQdodiyuX/vAJu1Nj9f/E5XBfdP5tA+oCReKASQMDUy85dIbGzd2pYf6qcxsI+1Wve3eGWhUCgUCoVCoVAoFAr94QkDmN9RUsrbvr36YWlRi/nJO5iY2IdcnkW7+g6jo4dYrkhmthuUm11UAhA7Db3jpkoiYmD7KqViEyHgj4YVKt/5BnatStn2SMWjtL/xX9jzxS/zyJ4hfni9gAwCVooNDsR8Gs/9kLzsYjktGgsz+I06pU//U5ZeuwK6ju50QNdwXR+/UuNH111O3PsU2ZP3I4vbGLEI+cEBNMNgemmbC35A13HpdLpY1iqP79nFoq2yUG7Tp3nsTWdZuXSFVqPFo0fG0W++jth/DL9WwdQ1BmMWM6UCjYkJEp8+SObC23izV4ikkySPnKA5foD57QZB3wTRwKE3rmIdPEb5xhXSkTidro3btlEUBSMaIbH3ANnmFo2//J/w4gm8eo3YkVNgd/EXZwjeK8MmTAurbxCZTGIeOoGlG7ReeZZ212a22KZHk6iFNTKf+hxVTcN3HMpth3REJxJ0Gdu+yWcPPchzN7a5sd3E0hTu2JXl3l0ZDLkzaWZn88QeeJz66y+zsl3ElxLNMDCHRtm8eo1Wx2ZNwJipUqh3CBQFFAUUlUAoVLounoSXZku0ug6jPXHumehBFTDVEyEh7FvNyD8OtqqjHLmDyJ6DCMcG3cCJxnE+wlUiv4q7ukjr+3+DdGxgJ2eyb1zGXV0k8pkv04nEfuNj2qqOfs+niB84ulP+TVFQB0dxUj18HN83l1LSjiXQHnyCWKvOsBol2o3T9iWBVNhutBFIEqaGI1Ru5qY4cOoeasUtNBUSCZ2ulaDsKTQqRZL7DrDZgWO7esm89gJOp4lot2g5PlLViA2PoImASLuMePvHNG5exJGCfafvY2PsEBdeu4IQ4JaLRIZHCUoFuq0Wb6y3+MLnvsp3yibDy6u4b/2YEc2lOjzBtp6jJVV6/+hf4SzPI9bXaG2ViMbjtC6eRbvwFpF7HmU5NcyVRhIRidO76XG0L8rL7y7QcH3SPXEAqs02i5tl+lstqrEsmUQaxXOYMDxu9CRZW98m9+gRam+/gC4EgSowVHC8AMVxsEbGuBlYTO45AC//AK1YphVNU2h2EN0Offv3okwdQ1UU1pw4N7woI/d/jv4rb+OsLCGDAPKDRB54gEa6j8guH7taI6hXQAiUdBYicU7uyqG+F5r4QUC3d5BX6jWyGYVINkvXlwRA4AcsV9oYquBLRwaRQYp316u0bZ+BlMXB/gRZ3f97fT6EPhxFeX8YLIT43Sv6pigkTI3+hHnb5qihYheLNNbWbm1LWxoM/GNfYCgUCoVCoVAoFAqFQqEwgPmESag+I/0ZfnjdITFwHAEkO5LRXBy11gHfQxEwnIkxkInx+nyRpu3RtH2EpnOw38C48galco183KTlKziBJKpq2K88y+Nf/HP60+O8PFfA6TrcmZaoioPudAk2VxECdEVy8foiUt8JBjpdh/bGGpppYlQKFDc1eh7Yh4zm6YnodM68SPX7Xyd1+m76ylXuOnAPL1xaxkewvllia7vEI3fu5/P37OLKpVlWZ2bpS5g8PDxE/NyzcPA4y0urTDz1NZTSFkYQcPyRfazoaX68VOXxR58iumcKLZvjtU6Ud35yBakqeCi4vuSO1ACZ3QfIP/QolTde2Vl9oqiIZBL97k+xuLROPDtMIhJBzeTwDRPZbqKPTeDMXUPEEkgE0u7iri0SuecRgoFROj/8Fl6ngx0oOH6AoypEfI/2iz+g/65HWLl4CYCm7RONqbRGpzkzt01vTGN8uhdfSgr1Nt+90OELh/qIChdfSpyxKezkANGVdZABLSvJki7oWHGEDy3bx8ll6dQcRCAxEkm29QRe4NO0fbbqXfxAMpmL8fpCmWK5zgODJprloCajeP5H3PzlFwRBQNeMgBn56YaP9Xw/pSoC+/w7t8KX266p1SSYv45y6NTOqrPfkCtU3EwepacfAPsf4T15UuJFExiKwuMHBvjB1S3qToDj7Zw7Hzf41J4cZ1YrRMcO07N/Ab1dRlYKqJqOFgQk0ikSx+/gSK3OmGIiVAUxPAGej+JJWkJDR9KYn0c9fBp7bh6l2QQp6b77BsWho0jDRPFc8Dxkp40ajeG3mhREhNnYIKWNIgduvErQ6VC4+yF+8NYNTMNmaihLsLSC0jPEQG8fyk2JN38dObIba3o/LzoZFmbLBKqGoim8c6NIs9XlicPjvHR5mYgKWioDAmYKbSaHh1m/epWdAmAG+Qtv8+j4FGvHdtOuNUg/8jmcN15A67aQnocZjaLe9RAL8yvEcruZe+4Z/HIBS1WoFJZIJ+PE7Br288+Qsyy0+TnGB4dwTjzASy2TieOPkjvSotpyqOsRBnsyJITP544M89JchO3GzrVFDY27dmUZiSvIn+t/VHcFK5UOAfDkkSFeni2yWd8JWiO6yunxHoZigB8wOp0lAFQkvu8RZi8fH0VR4Op5gkrp9u0juzDUf5xVeh+Wkc6QX7wEa5u3bc+wh5b2OxcXhUKhUCgUCoVCoVAo9AcpDGA+YWQQMJVW6Tk+zI1Ci0rLoT9pMZ2PoYoMTcdHVwQpS+VvLm5hewFCCMpth3zC4lhGUnt9EUNVkYqKUDwkEI1FEa6N8coz7Bvbx6EjB5DRONnCIpuei+v5WPl+Io0yuu/hdm3crU3UVBpdNyAI0C0Tv7iJ1pOjoxjoGytc/v7foakq2Z5B4hLk5gr99ut89ehptlyVwHPpj2poV8/QpsPugTx3s427NIu3JfH2H2N5dp7RyQk6rk969zRSUWmce5NBTeXzsRQxexedd1/nyokneOvCFQCEoqBFokjV4K35bXru2sdQLIvy0FNEhI8CtDtdlq7PEL3rQZ67ss7Tpz+FvzaH0T9I582XUUyL+ONfxJ69hlcuIiJRzH2HMfYeRnZaeOXCbfem6kG8J4+zvkJCYadQv5QIAWo2xzU3SrFZh+b7A4LrhTYn+82dkldSMtPVONN8b7VGS5KNqNx336eovvKTnUleVUc4dfADzCOPcH1+DS/ex3ZjZ4LX1FRiuuDPB1y8d1+h/NI6g8MZxNQk0UMnaf89VoL8rtPsLu768i/d7y7Ooh44TvAP+J773ye8+YcKgoChqMLXjg2y0vAYWq+TjugoSK6ulZGB5KUCPP3oF+HM93G3NlBKKwxO7cM4fIriG89hXbtMa99B+r7wVVrn3kYxLTRfojUaKDcvkLzjHlYXV8hoKk4QoCExhMCrlpFmBM/1iFggNA19YAjdjFDToqy0JaeTHuW5OQYe/BQ/uLzK7sEc+80u3Qsv0a1UMPv6EUeP03P8NJXNFUSgs5yd4NqFFXyhoQiVZG+e6laHrutzaaPJfVN9bF6+glurgJR4YpToxDjJRIx6owWACAL8l77HnrFxkvsP0Vm+SebUnaBoOJ4HqsZaqUl1a5vJOxwKW1tI1yaVzxLtdsnLDkLxIZchZtepZvNcv3gdY2WbkU99kZW6y6W2ZDSV4OhQAg2fIJD0moKnD+SoOzt9uRKGgiV8gp+GL0Kl6gnmKzaWadKbMLBdl9OjKUytZ6eti5REVYkig/dWxeyspfp4o9HQTwWVEkHh9lBDZnp+S1fzqznl21e6ALiDfb+lqwmFQqFQKBQKhUKhUCj0i8IA5hNIBgEZLeCe4ShCxAiCgCBwQIKpv/ciz2dff5LVuoOUHrqqEEiJrkAQSFIxAyeSoHffMSKxCP3tIu3nn0E1TdRMH8bcFV7YdJge7qG9sYUMJIqmkU/2kOu22Zez2NjUEEJAq0lqeAjf8xHpLOmJCdY2S6TefI1u10FVFNZth74Tvfiuh7O5hrv1XbKKAM/DURV8VaW+5wTFhqQfKDRsqqUy8bbL9J4JOu+8jlev0BoaQh+fInH4OM3L70K1iKpOEezez/m1+m3/R7LdQo+rWKkkN0odek7cj/PuWxSuX8KzbaK9eWKPfZ43Sz5bzSqt3YPE1uZQTYtuqYAfBHjbm1h3PICeSCB9H7e4hX/9EpE77rt1LkPdCTxsz6esR8n2D4Ln7vSd8Twyg/0oDz7BtflfXpv/xlaDI/1RVAKCIKAnZty2v9zxeCM2zPEnvoI+exnTLjK8a5r1eD8vrdRotqp4evrW6w8PpjjoblP7wd/iuTs9hryujX3jMt76KpHPfpGOEfmHDsXfLULslGP7ZRT1vVDsH++SPipBEBAVAXszKqsVlZmtKsF778NQFUYTOjYayuhuuvEekqrEWZqj9Dd/heN46JaFke3F6XYR2+vI7XX0dovhoUHiTz1N+eYsmY1ZYrEIWCZes4lT2GRYdzirqnQR+EGAGkvgdru4tk+QjlLrOAwEPql4jLKIkE5K9gVbVJ57GcROOTW7UmbtR98n272H9Jf+jOaFCyw1HBKmghqNIXr62O54ZBIRSo0O2/UO96Y81qrlW+//YF+M1ed+xOijj7P0+us0NjfpSIXe3j7i0wfQEylay/O0l+fxJDRsD6NvgLqaRI9GcTUTDBOBRAXGUwbB4gyy3QJFwekbJLP7IJW+fkpr6yRLG7xcifPEgQHGsxY5U9D0VAQQVUHxPdI//XSV/q17IYXKpaLN63NF7EBhttgkkDCdj3NoIMHV9cqt9/TYvr6wzFgoFAqFQqFQKBQKhUKh0O+5MID5BPPfKyUlFZ2OVFEERNWAwN/pHzCRMRlJm9Rtn3zcZKXaZr03zenJXaQnJznXNpjdrKIXW2Q0i9NP/TkZM8AqbnCuHOP6zAoikWT/3gPUr1wC12Gr7BHJWIzVVskND9GwLGS3TbCximqaRAYHOT6SobtSw62USaXiICWddpelpTWGp/aSX1llvdYlkD4yCBDROMl7HubFpW0eHmoSc+oMlBYY6BvGGB+l8cO/Q1NAswyIxumWCritJqnHv0BgmNivPgcHTtJ+5ReaY0uJmkwhDYOu7bIVRJkbPM6eycNEFMFyO+BGuQuig6ZrKMHOt9ADz0OJxgmadYSi4GyuEmz9bNWENjgKprUz2R8EKDJgIGWxXGrTcANsNcHo9GGs0UPkUjGiA73Yqo58r8+LAgjXgcAHVSPQ9Z1M4OcmY/vjGqmITq3j3tq21fL4UUvjzvFD7GrN40UzXFntUm/tHFd1bSxVsKs3QZ8F7ltnCLydMaIpCtp72YTfqCJXFhGT+z9RE8CeGSE2MU2rsP2B+43pA9gIfi8TmPdI3+f0SIr1aodG12VfRmeqtY731nmyhkTDJTG8m4XZJdRah/jAKKaqUfUVchOTbH73bymVa0wM5QhUjfpWAfuv/1fMux7GW1+AWJzM8BDNxXls12fAbzE1MsqS3doJGQKJ5nQxonGO7R/g4nYbNRnDSMQo2j6H+qLUf/QOP11kJNgJxWQQ0Jq7gXroJJdiI+jxDEZHEjg2wcYyvaZFZmAM6Xt47Q7Sf+8AimBweIBBv4nXaWBfu0DmyT8iWquSNQQZQ9B49VnMdAY124NfLiEARd8JmN1uQPrwCa67Fj19/bS3N8nqEjm3QNCsQQBCERj5Pso/+BvGHv4c9WIRtVrE0pJs1DoMJk1+OFtlqdRCCBjLRjk9miatvb9Py3YXXpstItkp1ZiOGJTbDje2m+ST1q1nOmKoDCYMpHQJhUKhUCgUCoVCoVAoFAr9/goDmE8yobDZFZxZKLLd6KKrCpO9cU6OJIniElF8Hp3uY3e+y6X1OmM9UTRTY+CzT/LM69fYKBSwdAWv2WTDtnmmafPUp+8mVyxwca2GFArXr80zcPpusqpK4/JFQFL1VXZ3KnzlkUd4+8oiNzsNXHxGe+Mc6hP4bz/L8D0Ps30hT6FQAiHIZLL45RLtiQlypwbRl1fYXNtC7+3DOHKKi+t1jvda5M89R9tuk7jzfgLbxr3wBpYuUOJJlJ48nrozpP1uB3t9GWXqAHa5iIitkt+zh+XFVWSnjdB0lHQGKRSQkE+YjGWiVLuS1za7tB2P0UyU6YE0c1uwa+8Esc23CQC3uI154Aids6+h5gfwxM+XrBLoU/vpWlHM8Sns+RsAxDXYlYtRbjmQyzOnZ4n3JkjENVzpoYuA3b0xLsy18LfX8VvNncMpCmo6y/SxaQxF8tP2LCYeTx7s59kbBbbe6xuhKoL9uRj7Slewr19CFYLPTB1ifWCYmYoNqQinJlMUXYFfr9HcWAcBpqoSN1Us9Wfhgzt/E3X6EJ73cbSR/+3wfR/zwDHU61fwa+Xb9ml9AzAy8YkInJKqx5eP9FNvdjDeepHOuTfo1QURp4WvKsgr5xl/6Elm2y3qGzuN4vv2TmMVVkgFHWKGh1LaJKiUsT2wetIES7OYff34CzMosSjx0/fSGtnPWyLFUCpBovcUy3Ubd3meXF+aOyb7UXqinFurcd02uHNsF9moSszrUu90UDX9vYBRRSgqWiKJ8AMob7Nv9zTdSpn52s9WgyiGiaEKdvWlyChxVNGm/8hhpoZ6yWsuxbOv027YUJtn6LRN38QoeA4tIHr3p5A3LhK5/3Hsi2+jlIrosSwb0iRzxwlu5qaYL3R5/MTdJF79PhSWkZ6LAqCAMrYbp7BNxO3gXDpL7/g+upEodjsgGzP59qUNUqZAvrfMZWa7yWq1w5ePDJJQfhagaJrG1aX6z+I9KcnHDXwpqXdcLq7WeGgqB7R5bG+emBL2egmFQqFQKBQKhUKhUCgU+n0XBjCfUEII1jrwnYtrt8rf+IHP5fUaa7UOnz88yKW1GpfXNxFCMJiOcGw4y1g2ymbdppHsJe6xs3rFMNDSWQIzwsvX1nlyeILuwk00RSBch9cXKwz07GPPo7uJqAIZi6EFFczv/G/cWatxdGwPSq6PWHOO4osLtBSTQqFMZ2ya7ubroCisNR1M1SO1vozrtxn6zBfpiWeoaxGqa+vcF9kgdvY5glKBQNPoLM4SPXE37uw1tPE9+JqG9wuzld7qEsbB46jRON7CdY4eHWJZ1xFmD8gAr1FHiSdQFYXjI2mubTZ4cbbMZnWnh8TN7SYpS+fpo0NMZy38nIJ/4xLYbaIHDyMiMbobqz9bmaKoRE/fi53pxZdgnb5/p/TY3E2k7+2sPjmwB/XOh3CicWTgI+V7vR18nyO9UW68s0Xjp+ELQBAQtVscEHWQ0VubpZQkFZenD+SoOmB7ATFdpY8OrTMXfvoitJsXGVU1JtIZRBBlLnOam2UYTxtEYhbSc0EGDCUtNPGz/iVC1/kk0nr7sD79NHJpDnfuOggFffoADI/T1Yxff4DfA1JKYopPf2uTxpXXQQ/wux2EY+NrOpppIc+9wr47H6Ym26jSJ3f4IO0Xf4BS2ECzogS1Oq4vUYXAdz0s6aPleuku3sSOxLmQP8Cb8y1IWdjLi1giYN/RAxybPEYfHUQ8TstQOTCY5Mp6nbXhA4zLJk4bkBLpeyi6gYhEkLZNJhnFapaJJWIM9yXx0hFGWyrrpQbCtAgMkwBBRBV8diyO21Gx12o899oFurbLWP8wd903iXfudZaqXdoxl9G4gu/7dHL99O3ZR31tlejhk0jHRnU8VmvwSh0q1Z2Q5C0y/Onnv4j9zF/jdjsosSTG1F583aT20rMAqJUCyYN3sJHqJyU1ZgpNEOJ9wV3H8bmy1eTuochtfYFq3dtXtKgEDCcN7JhBABwZTpHRExi8f/VMKBQKhUKhUCgUCoVCoVDo908YwHxCBYrKGwvFW+HLz4toKs/dLLFaatzaNl9oMl9ocmwkg0QgTQsxMIImA2g1Ka+t4TZKaCKHLy1ySYvNzTKqaSBrFTbaBtuWhaLrHEvGOJSQtG5eRdpd9OU5jP1HcOJJYsk4G6UOzsx1qntOkioVqC4uIBB47/2JPvIUq32TzNcc/EqDgWYTo14iKBdRIlHUvkE8CV61hN9qQSzxgZOVSjyBi4Jx8BjeK88ytHmTL588ysxGleVSk1JHkhoY4J79fbh+wDtLJQaTEaIa1DouvoS4qTFXbLFVbbJW0ckP3klMV9jbm2FqdJJYpYC/vYHQDZT8IHY8datRdlc30O58mNjBE9DtgGnhJdN0Awn++1eWZMorPD1qcjnbx+zWzr2Z7EtwMC6xXvs+xme/TCcSv/09Bh5Zjfee5ABXMTBGJ3AWfq7cmu/hlQoA7D12J8nBflarHXqnpwmWZkgaCpYqbytxpk8fpPMJWv3y87pmBDF9CHX6EFII7CD4RE12CyGINWs4l87uhExSIqIxlN5+/HaLQAi0aJzo6BiRkTFwuriVndUmXS/AMExUw0R2HXw/oFVvYAyOED15D8RTbB+8l7PzLbrCpru+gQQc0+SNlTq1IM0X9uURvocWeNw7lmQ6H2d+s856K+DYvhGY2EVtaxvpechmg0wqQZ/ioOoqom8APwgQuspjx8e5XuhwdaOO6wcMZ6IcG04RdGy+/eJFyvU2rr8TbixslPFllq996Y/ZEBEubLZYj2qMpS1yEQXFtOhEYjv3WbcQccFEVsNquJRaDklLYyRlwcYM6thulGwvwjCwL7yNs7GOQBIEEj0WQ+ya4luzHrt6I2w1bCK6iu0LTOX2MbRQbHF6MIbCzjUGQcBwOsJ6tXP7DZMSU4GemEmPIVED7/e4CF4oFAqFQqFQKBQKhUKhUOjnhQHMJ1TbE7dKU/2iTNziR9e3GEmZt8rm/NRcocmufBKEwJcgVQ0rHiemCZxAgWYd3RWcHknx/VINGUvi+BJ8B9W2SYyNM9ndxtleR9o75xexOFjR9yY/DRzhIHSdFzcddu+9n4MHTyIK60SiFv6effzEt3jn3QK6CFADn2CxynBmik8/OYF6/Rw/jQWcwjbmvkN03wsXfkq8VxJMnzpA2/NQxnaTQOLNXKPvR/+FHiPCnWNTaHecwO8bRlcCXlneWXWiKoKIIonGdYQQlLo+r80V+PLRIfxym426DcB8ucNXjg3Tk8kjsn0AHziJ70mJF0tCLLmz4YMSsfeuOShsEXv3de5KZTieHwLALFwkmK3sTOF22vALAcz7zhcERE/chVfYJGjWb9tn7TuMn8qQFR69/RaRB+/Df6FBa3vztrYnxsQ0ft/grzzP77sgCAh+/ct+L1mdFp1nv43qOrfGm2y1cLuLaCPjuI06frOOTGZopnrQFIHRqhOJx6n+5FnqioHZtQkCG0PdaQzkD0+w/dYbiGqRueFTNCp17Fbr1jnVXJ61jk+i0qFmZ241oFcDj34ThnenMTfrtM88y97HH6X0g2/jdrtoUsfs1CAQJP7on9GOZ+C9FSOmdDmWNzjYm8cHNFVltRnwzkaX3kOHGRMB8/OrtAvbPDKVY6Cxydb3/pZq12dsaj/28BR/u1Riui/JU+n0rWtVFAUXFVVKdicVdictpJRI6eDbDkoiRfOlH4OioCWSmKPjiHZn53fhI0/y/9owKbbbnIwa6KrC1fUamirYnY3eClsANFVB/FxLoSAImOqN8e5qFcd7/+g7PZ5Bk2H4EvqYKAoJU6M/Yd7alI3+8pWOirLz7AshcF0XRVFu9ZULhUKhUCgUCoVCoVAo9OGFAcwnlGAnTPA+YMLf9gNudcH+BTFToy8ZYbFi4/gBhqbQn4oSHZtAX1smr7pkFI/E9gwP3nMHz11ZpdlqoxgGg3smOTyex+xAUFxA3zWJV9hCGxpFygC1VkdqJqYAbWKazrrgbMnlkm7Rm9pH2/Y41TV44cYmbcdjIBUhY+mIZJblYpELmQFOJVKIZh0pJX6tgvmZp3HPvYm3tY4a+NBuITttInc+gGJaqIDwfboz15ArC8ggQLXbsHSDoLRO7PEvYmdy75sQlVLiS0GxaX9gZhJIuLLZ4KHx+Ec2KSWisZ1j1yro7/W/+LmiYB+6LFgnmiDy2S8jVxfxluYQpok2dQCvtw9XqMBOybOWGaX3ya8ir17EXbiJ0A306YP4fYM4Svir4feRoigEKwv4lRL6yDg/TQCEpiMUhaBcRM/2omZ6EHaXaL2CncrQjiTQp4/QmlujfOMaI+kegnqdIAiIHjpO1fHxbZ+evmGCeAqnvQqAqmvouT6KShTfC5CA/0FBpOcR9A4SueM+3PUVck88jb88j1/cRsn3ox04Rifbh/9z5bqEEAgh0KSPg87/cX6T2UKb+VILKcFSBZ87OMqx3Sm6P/gb6kKyVuuiKwJRfJn86Bwn7/g0b23W2bPVYMQUtKXG9a021zcbBFIy3hPj8ECCpLoT64rePpzZq0TveZj2mRfxalVQBIqqI3ZPszR8gMSyy5ePZZjIRri53eSylDiepOMHxNSfvecDAwkU6d8WqGQ0nycPDvDiTJFSayfMjRoqd4z3MJ5UkUE4wR36eBjpDPnFS7C2eWtbpj+PGDz9vtcqisL5zfZOzzIE0aiNJTyO9UdvK6kXCoVCoVAoFAqFQqFQ6NcLZ1k/oWKaZFcuxsx28337NEUhE9Hft/olGzOQispbiyWODqd4bb6E6wfMF1vkYgZD45M8NJXAX7hEcM/jpLdKfPnkOB0rQWBE2LIDLly4znpM4/PpXqL3DdN56zXQdZziNornIgKf/IG7uNBwGEsm8YRKpeOxUGgykomwVu3S9QICCevVDpFcjFi2h6Dd5MpqmcM9fRhz11FMC+PAUZyePvRPfY7Y1hr2uTegB9S+QezSNv73vkni/kfAcXA2VggME6n/XJ+Pbhfn/BuIBz/LWDbKlY3bV4wEgOcH5BMmCnAoo2MQsOWrrDccSi3nvQnufzgpJaJvEKHrSNd93369fxA3kf7Qx+qYEcTk/p0yW/BLy4lpuTzOnoMoew/Dr3hd6PeDqqp4S7MEmo5b2sY6cRf2pXeQ3TbS86BRQ1hRtKOn8BZu0t3ewNx7BPYcwNc0gnsfIzF5kO7WCj2HTyB1g8LGNqWbM4wO9qLfeR9GvA9ltIuQEkfR2HbBdQMSlk4qopGydCyniwwCPDNyK1QJJLSTWdRML76qIfccQSXA8X06vn+rBJ4QAqvdQG6s4JcKqINjvNDOcnapQjJi7ATLvqTtSy6s1rjHv4IjA8odD1UR6KqCrgramxvka+uYWj/vrlXJTaT5zpUNSk371v/XhdUqM9sNvnhkkKTi4iXSRPYfxS9skPjj/xZ/eRHpuWj5Abzd+7lWNdiT06i2OrxSrLN/MM1QOsJatYPnS1B3fh8MpSNMZi2kvP1ZDoKAfkvw5UO9VB3wA0nSVIgqPkEYvoQ+Zk65SGNt7dbPEV35pa8ttxw2GzYgSKAT4/2fS6FQKBQKhUKhUCgUCoV+vTCA+YSSvsedYxk2al2a9u2T6n0Jg3xMp2XfPqEykI7xzOUtRjMWoxmLLx0d5vJGnWrXYyhlcfdoimdefoNDIz1oNY/vnFvHMg18z8fzfTKTk4iBUTYdm9rRQ+gxDbFrP1uvvETb0bFiUfLHjpPpH2TxtXmwugQ9A2z//9n77yi5jvvA4/3WDZ27p3tyAjCDHAmAYKaYxUxKpCRbksOxZFvys63d82x512v7eO09a0n20TrsOup5bUn2rs9almQFKjEHkWIAQeScgcl5pvMN9f5oYDCN6RkM8oTf5xweom/d27eq+9ZtoH63fjVWQAON8RB5z8c9s66DBgbzHoMaQskmXCdDvjZFuH0FdkMzvgKzvxenoYXc0YN4roP2PPz9u7AbWgi3tFJ44yVIj+KdPIqZqkUlU/jKOJNySFPsOEk0l6E5XkVtPEh2whiooSBgGXxybRXmoe1kD+zCKxZpaGhm47obGaiqLls3ZTq+YTFchOGcS9AyqAmbZwZdzz1NnI/Eidz9MNlXf1QWhDHjSYJ3PEB2illLU14DWuPOIKAy0/3E7Ke1RgVLKbW8bA47mSJ636MUdr6LPzaM2dhC9N5HSP/kFZzO08Qe/zCZt14l1tBMNpGiNhnlu51V5JNxIgGTJbZLdfUS6jffRu3iZrxonEBvFjsW52BfGoWPaShMw6A2GuTRBpOh53/AUMdxkiGTSNtSjDWbScdSRAwPR8OpMZ/tHX1kCi41sSCbmhPUhwy076OUIjzYS+a574ynMExHatlxIo92IGcapCIB+sYKGMC6mM/o9qMoQ5FzPGzTIF10sQ1FNGChD++ldtNilIZDA7my4MtZ2aLHe6dHeazOp/Du66Q7TmI6RayaOuylq3EMoGkxfZFajhw8VTajZX/XMLcuTpJrriLneAQNzbqmOIsSAQK68oC11hoTl5rxCW0eMqlACCGEEEIIIYQQYn6SAMw8ljBdPrKxiWNDeQ71ZQjZBusbE7TETapDdXxvT3dZ6i1PQ3tNBNvw6RjKUhjM4biaZNjmWH+aJckgY9kC2472sGrjOmKhAL7nYZkQCQbxg2EGC5r+NOzPGAz0F9h2cIRVNRuoSy2j6MOpA6PcodL89IZ6dg55HAxa1MUCrG5I0F4T5uhAFig9BV/wNEPZIiEDBoeGaauNs8sLEF95D+v69qJOH8Po6iD+8FOMnDwKZ1KBGVUpLHwyP/o2dmsbhqlQlg2FHP7xAbRpYcTiEEvgmRYoCGiHJ9c2sLu/yM4TeRzPpy5m8/E1reR/9E0GT5wY/5yco4cwTx7n5o9/HN8PciEFZfPK4SHG8i62qUgXPIqez0Nr6mmNGONBGK01+ZY2Ih/4GXT3afzMGGZNPbqukVwgNONgj1i4XNclvGodxeOH8UwTY2iAQudpAu0rsLSHUdvA2Fuv4546DoDX14MRDuOdOoqx4WZCvsMH1tZzcqTI/t4xunWAmpY2WsIeZtdxvMMHaHPglzbfyWs1IV44MkjINlmcivDTiyzy3/83RgaHAEUXivrBUUa27sR6+MOkE7UUXM3W4/3j9R3MFDnSO8bDaxtZljCwnSK5V58dD74AOKYFSrM0bqIipSBptuiRKZRmvHi+xnU8aqNBRvJFTAW+1qSLLlUalFa01UTY3zk05ed2qmuQgb4OAscOAWdmvw304RTyhB75ENlQlIShaa2OcGowO36cr+FA9whNVWF+ekMDpnbxPG/SzJdrwbJKP+el88u9QgghhBBCCCGEEGI2kADMPKa1JqIcNtTabKyvBkoDtHg+LRGDj25u4cRQjuGcw7qYIj7aw7LcKVQ0zlhtA9/r8jkxlMOyLFzXRSuF2dhCofs0WmuMaBQzPQpKYTUvpivn05cuLdwdD9v86/bTFEbS5HIWzboAmVI6tB/v72TRygS39eznpid+jldPpukYzrL1WIYNTQkiXpG0BzkXUqkIxXwR5Wu2tFaxZ+deXNejZfNSUqeP4WczqGx6PPgCEGpoJvv8d0rt7e0idu/DuN0/wj1xGhQYsQRuNoMa7Cd85/04oSic+aye3NDEhlobT0PYhEjnMY4P9GCgCFoGtgFaKVIRG/3e69gPPUVRTZ3GxTBNjnSPsarYhzqyBz8zilHfTHHxSl491McT6xuJqXNBMK01uUgMtWwNSimKZx+NlwFVMUNebRPB1RsoHj1IYOlK7PpG/JFhzOo6rNYl5N57a3xfPzOGCobxc1nUmXR6QRxWJg3W1JTuGXYuS+HFZ8j1dtOf8+gezWPt2cf71t/ArXc9QL9vsrdzlMK+7WeCL1DwNNmig20qLAXWoV14m+/jGzs6WFQVLlus3tfw2uF+mjc1EhodwohEMGJx/PQYfrFAbU2Kj412MLZvN8pQsGwt3ctbeLmnSJcOcs+ypRSOHsIyFEPZczNctNb47asZzjusqI+zr6NyAEYp8IcHIVk+C0xrjTs2infkAMaGm/B9l/evqOG5g5qOodz4TJiGRIj3r6xFO3muxzyygO9h9nbiHNoLrkuwfQU0LyYfCF2H2oi5RFF62MEwyn/D1BVKrSmEEEIIIYQQQggJwCwIvu9PWjjX933ihs+GWptINkf22e+QHxkl3Z/B1xozGOLJOx/i/+TCpF0IWQYBQ+FF4liLluKjSTXUMRYMYsSryNlhBvpKAZYbWqoYzBQpOD7KtBlO56iprSJ4JgBTLLoMmRHiGmLKoSEe4ED3CGp4gN3HD/Hw2hW82Vtgf88YllskHLG5fWkr/SdP4bilQEtHXhMPRNCFPNq0MWIJ/EwaK5nCjEbHk3Vpp4DV0IwRiuABaNCeB4YJlo3VvBh/QlIhQynCykWjMZWJd+wgDVGLBtPBGxpAF/KYgQBWsBqvt4tgLgOR+JSffcFTJA/vZOCNV85t7OjA3LODO97/JB2jKVYnzUlPrJ9NkSbExSoaJoGb30fV4nYy3/w/uN2nMSJRnGMH8V9/gci9j5J5+8foXAazph6nrwersYW8Xx4IdF0XwzDwj+7H7enCw2AgXQTA9X06d26nqaaOF51mEspl5PBBFAofyDulUMRIzqE5EaJ46hjB9beRLnjkXJ/o2V8epXC0YjDvM1bwqRnsQ588hi7ksZeuhNse4PQPvwvDw/QPZNFKYR0/SU1LC3dteT8HC2BsuJmxw0dQ+TxLqiP0jBbIOi7RhiaGahfxYGsDi1IR1jTG6RnNTfq8lOexJGYS6j9NpUxgzonDmBu2YFgWMe3z5JoaBvOarOMTsgyqQwamf33Wxwh4Lv6bL5M/emB8W/H0ccxkNeGHPkg+FL0u9RJzQ8A0ODSQ5/iEWV0AbdURCcIIIYQQQgghhBBXiARgFjhL++Rfew5vdBjbUNTHg3SP5vELBfIv/4AH7v8I3+n0uXtFHR2DpQCKawfp82w+cPtqXjzYS+dQloLrYxkGN7RUsTgZIueUAiXKDqALOQo+BBWcjXVoILTpZvLKZE2thZdP8OrRgwylcwxv3c0tt2/myXWN9PUNks8X6B5Ik+kfBsDxIVP0OdKfxisUyBQtUnc+TE/fMAf7M7iZKItvf5rWsS4ix/ZQ3L8Le9U67CXLKB7aC5aJ2bYSe+lKMnt3El6yDCdaVfHzUaaJkR7B7TyF0hoF6EIOZ2wEq6EJdYF1WYKjAwy++dqk7V6xSPGtVwg+0YRhxPA8WYBbXDnK8xh781V0IokJuD2dGIU8fiZN9tVnCd14O4WDe1DROEZ6DN3QUjHgZ3kuxYN7gNJMFfe8QK57cA9tNyyiP+2hz/QGX5dSgJ2loRTIObMpU/SIBSwKHnSPFkjnXaoCBmOnTjH8yo9QJ48Cmkwojpl7kUBfBwUs2muinB7Jk3c8xk6dYtWKk2y45X08d6SfLQ9/iMCRPRRPHad1UYrw6nXkFq0kF06wKFoKrC6rDrE7FqT/vHVgIgGbG+MB/CN9kz9I06SwdAOnRnwO948RMA1W1ceojxjU2BrwwL9+fdfsOV0WfDnLGx7E2/Mexs13X4daiblkrODSPVbeJ6oj9hR7CyGEEEIIIYQQ4mJJAGaBs0eHSPd0l15oTXXYJGhFGcgUMByfWn+Ej2xeTc9QmuHcuae8N7YkSKgCH1hdw3CxmuGi5uRglr7RHAe6R1jXkiJgGhSBSCqFHbbQThIjnykFepobyNdUczoLmUKBjYUuEotDZO0kllLEvX6+9dp++ofTKCC5bBlKKVxPkym41NmaXD5P1aq19Aar2J316BwaZeDQacx4kv39PdQkEzx131NYu96gcGA3Kp7EXroSs6GZYjZLcd/OUmO8yitge55HZPFS8j/4RsUUYCoSwzCnTj+mlMLo6cTQmkpDtLmBflb6GXw/MsNvS4iZMYcH8UaHSy+icazaBnQugxEK4w8PYtXWYS56HLdYJPzgB8jaU6xl5Hul9H7KQClFPGQzlnfG54zlcgWWVAV5szPLXSvXUnjnx2UhyaqwTcH1CC9dSSEQRinQKNIOHB/MlWbbAU0BDR3HOZnRLEkkwXUoVNVi7tsB2QxetBa/4LCqJgGGgWUaJLv3Ez4aojO4iGcHFLXNN9K0ZBMuilM5Tf54ho/emBwPboZw+MC6eg7059jXPYavNUtro6xvjFOz9w0mz42B3Prb+f5wmL6RnvFte7tG2dCS5I4lVXi+R8AAvGuffMwyTZz9u6csLx49SGjDTdewRkKcc35aM2DSTFwhhBBCCCGEEGIhkADMAqeLRZiQgktpTcyCWDJUSscT9Nk2lh9P3WMqxebFSZZW2WjtorRDyoKIbfP6oTGCtkVDIsTAWI67V9Sx7fQwIzmXUzkfy0qRrKvnifVNqPo4/3d7B8PZIvXxIK35IU6//BIajaEU+ao4t996P9/bkcH3NS4G4Zp60t09bFnehHnqEPUPPEJP82p2dGY5NpBmeSzGxrvv4OjJbvKJKgZOHeOt7hyPtK+isOc9/LERvP5eHOfcALIZr8KPxKb+gMIR7OVrKO7fVbZZhSMEb7gJt7cLFi2b8nDLd0hGAgxkCpPKTMMgZoIjqcbEFaaLpetNKUVeG4wEqsjpKGbIp7p1BYnFy9B1jehonOyZqSmVFnF3AhEKdYs4eXIbnvYxDZNUNEQmX6Tg+Zgti3HtENGAyWjzMqpq95Pr78cyDAwFVSGbTCDCaOsqjg9kWdNURe9ogZ50kaFsEaWgLhrkziYb57XdFByP4WgtVTi4vsZwXdyxMRK1TXSmHbJdvQCEgwGqvSx+TycbUx5jNSs40J+l/0z7Q7bJo+saSdl+Wew0hMPm+gAb6uvQGmzl4/tFjGVrMY8cxBs5t06MUV3Le06UQW0zMaqkleKNE8OYlsXRnmFiIZsti5K0xgzUNZ4No53i1GWui9Iy4C2uPcMweK87y2Dm3PVZHQ2wuTEiQRghhBBCCCGEEAuOBGAWukgUTGvyE9zaxwBidbV8uK2V473D+FpTHbaosjX45fsn/Dw/W1fg9LY38R0HY8lyYstWYqgUu7pGyeYdUpEQm1uTjBRctneMMZwtYhmKhqoo2WAD+TPru9imYnhohMR7b/CRLbeze7DIWFWMRLyOWzctp1YXyNPGayOKN7d1knM1+UKRUydGSYZtnlzfyP49h7GaF3MskyO9dDHB5WvxtcYLhiaGmwhtuZ1CIAhTDAq5xSLG4nairW0UD+5BF/JYLYuxFrWRO36YUE39lB+t1hqjrpH6qI3na0ZyxfFz26bB4qYa7ESc67N6hJjPVDQOSpFz4fhgBk9rLMvCdX2Gi3m0FScarUL5HgHPxezrxDl8ADyX4NKV0NhKNhjhx8dHaWlYQdHYgVcorY00lHVoTAQBk+KydezpHOaXbmujdyyHf/8Hqe8+RsupQyityTQvJV/fzhtDmiMDQzy1qRnta1481E82bFMfD3Ln0loaTm1jYHQUgO6MS7w+QT5fJLp0Jc7oKBgmupgeb59pKgKtS0qpAE8d45GnVrJ5SSuDOYegaVITMYkoF9/3J61l4fs+xpnVXs6mRcuFIoQf/hD61BGcIwdAGRRuvpcjR/J4Ex/kV4r+rEfvWJ7twWEaohadwzk6h3O8b3ktG+sC6Gs0wOxrjb1kGU5vV8Vyq74JLySz68T1MZgpTkptBnI9CiGEEEIIIYRYeCQAs8AVY1WEVqwlv3/npDKruha/po6mqjBkh888Se5y/krVAd/Ff/MV9JH91GmDkZyL33uK0b3vseyOxzCbotiGSdHzONY3wpgDqxviBCyDxkSYt04M4dXFaF65jI4DR9AalILRnh70i9/jniefJrx6MUED3j7cS8bNYqVS7DzZjWWaeGcW/FZAtuDy1skRVtcnOXmyGyJhioZJ1YNP4gz24x3aB8UCVqqG4ObbKDYtnv6J3HgVxc7ToH2s9hUYhoGTHqOwbxcohTFNAAbATdYSWtJOy8lj1MYCOJ6PoRRBU5G46VbywfCUwR8hLpWTSGEvWcbR9/binTfDKra4jbfHLDYWFM3KwXvjRfInDo+XF08exaptgHufZHfnCEcDNvc8/CHUrrfJnDpJxFbQ0saqu++hO1LNRwMGYcOlOWTjUodqqyd8+81kHOgZdTjZl2Z5fZB72lJE8iMow+D+FTUc7M0yWnD40d5OljYmx89vGApDaYLZMdSadQROn2D0vIklddVxzMYW8nt3AGAWs6TicVJxRekG5VfKGjitXDCEWrEec9UNpc/QM8jr00ycIVj0Ff3pPAB5p9SXz3r72CDLqluIqmsUgPF9jLblGHvew89mygtNk+CmW8jJ5LpLopSqsAj9PFyU3jCIBy0a4+UpCKtCFoahzsyEU0QiFqHrU0MhhBBCCCGEEGLOkwDMAuf5Ptbm2wiZBoUDe9CuA8og0LKYwO33kjMvvBiv2d1B5sh+AALKpz5q4miDw729JI7uJN2wkcGsg4tB3tU4PvSMFVnRkAAUxwf6ODWU5f9732M0Vb3NyL5d+Pk8kZpa4jfdhteylIThEBroYe3Ol+ntG+To8lsJdw+RaGiGUJg+xyMQiYDncXKkwK1tTXC6l7pogMDpw3grVuHceCfhtZtRvocXDJM3zIoLj09UiMQI33gb2Tdfwek6XVYWWr2BYiI17fFFwyB0xwOYtbsw9u8mWMhhJVIEN92C07xE0rGIq8IBuOV+7FGP/KH9aM9DmSaJ9mWMrr+DA30OVUM5Wv0uchOCL2d5A73k9+ygKryMkZzDj4YsmtfcS9sNDhrFe45FNFpDg+0C3ngM8ezMkjxgKlibsrgxVUV+/172PPMCI7kcpmWzdsN6crVr+XZvHl/DiWANS5qayXZ1UhW2MfFJhS16jhyl+Wd+hZFt24i4e0mFLarbl5JYdwPFgT6MaBy0j04kr8jnprXGPbtmjKGoj4foGjm3OkzB88dnzbTXRBjJ5MfLip7PUM4leokP+RuGQdozGci5+BpSYZMqS6OnSWuWD8eIPPJhitvfxDl5DO152A1NBG+8nXxNw6VVZIFTSjGQcxkazJdtb3H8eReDCSRT1B/fBR3dZdub15RmnsXObLdti1hNDar55utRTSGEEEIIIYQQYk6TAIygYNmYN72PyJqNkMtCIIgbryKrLzzeZFkWznnro5SCGhoNZA/vZ2nbDRwb1nSNZvB8jXdmALMlGaIpUXry1vU1/+u9AR5cfTurN9+CWyyQtUI4sTjNSYvgcD/pH32LSNEhbAdwfY1bKOCdOkbjqvVkRgr4udyZNRE0Xq6KQFWK29oSBLp68Rta8H2ffCA0saIX/Gx838ddvo5oNE5hxzt4YyMY4QjBdZvx21Ywk6W385aNsf4mgivXo1wXPxiaUfBHiMsxaIZ4r/02Vq3aTMApQDjKjpxFR18BTSn46h7eP+XxhUP7aNuylB25Uqqu06NFSiFIDRSZydWrAHfrj8nu3omXKwUyPNdheO9uVjYOc2vbnfykK8d7Qx7Vtz1MU9dBanuPglMgXNfIik23cCraiH1/M23rVkPHcfSpIwz94//CiEQJv+9+jBVrr8pMMuW73NqW4js7c+NBl7OqwjbVEZuuofR5B13iyQyT/UMurx3upuCW2mEais2LUmxpimDqyncarTXZaBzrroeJZNOAxg1FyKJA6wqzOBa2SgvDn08pRcH1SRfLA1+uNz+D5cXBfsY6Osq2Oc0NFIcGxrcHAgGsGfV4IYQQQgghhBBCnE8CMAIAz9fkwjEIn1mQfqZjLVqPL/g9kaUgHrRIOw74mo7h3LmF7xWsbozzw73dPL6+iTVNcfZ2jVF0fV461EdnTYi48igW0jy4LoDta9wj+9HFAhbQaLm4tRF2HTewImGC3SdYFk/RY4YYy0JtOEDIL/JYs8XKmgjusveTn8FMnqm4SuG1tGE3LyZQLOBbNgXTuqgAiu/7FKwAWIHxz02IqylmG6QdzUtjCggRcYNks9nx8sXJMN7YSMVjtdaETB9LVb5Ok+EAiYAi4PtYI0PoXAYVCuNWVVM0zPH9AukRMvt3EzA0iXCAkVxpUe50wSHadZonbwVCNdTHbBI1EWpXtBAp3ozyPNxgmJzW1CmfUO9J8m++AJk0/lA/yrbAUBQP7CG8/qarNpOsJQJPbmjmJ8cG6R3LE7UN1jcn2NBUxf6uobJ9g5ZBdciEGYVly/Xl4cUDPWWBHs/XbD0xSCpsszJpTHu/cX0fV9Z7mZZhGLD3PfyhgfFtZqqGw03rOD54rl+sbYwz76a6CCGEEEIIIYQQ4rqRAIy4LL7W2G3LcPrKU5igferiQVS0jm2Z8nhOe02UmG0StExeP9LPhza1cKQvg20ZtEUMnBNH6c9laWtMUrPnBL5tQM+59F+m79KS6WZVSzXdRYXbcYJAPktrJIpXHefRDa2s6NiFOrYfr/YBCnVNlx3w0FpTRMHZGTQSQBGzXEh53LG0hh/t7Z4UT21NRaiP2lgtS3D7eyseH2tqJpKsgsHBsu2mUty1vIaqwiiFV35Evvvc0/NWbT2Rex4hG4mXNqTHwCsFJJripeDjaK40eyZbdIj39/JTN91CVHl4nof2ChRMG0x7vI/Zvkdhx1Y8gGgMIxZD+RqtFC5Q3L8T887343lTp+q6VNr3aY0oPrS+lqynMJSiJ+3ywz2dZZ+pAu5cVkvM9C96Io5pmuzsHJ00y+asbaeGWZqqx9TOpTZDnOEPDeBP+K1SSjGacsoWi2+rDhO+HpUTQgghhBBCCCHEvCQBGHFZSgtBr8DYs33SQtBBS7H03nt4ZyBMY8LBMhTrmhJEbYOD3cMsqgrgK0VDLMB/fv9KDnYM0nmiA6s2yQ0t7Sx1+jG2voVb34gxNoKpfaiqJtDQhNIuT66tZ3vWZudQD45lUh21uXVRkOZdz+P39wDgDQ2gliyXdF9iwfF9n6VVBk9saGLryWHG0lkSusD6lhQbWpOYfhFr+RqMA7vx87nygy2L4IYtrE1FCAdtTg9mWaQzVKkitakE4aim8NyzON3lqYvc/l7yL32f4KMfpmBYKPvczDMTn9aETTEWwPU0hqGoqU+Q8wrTzhkxnCJeevRcuzQwIbWWN9SPqX2ufPilRGuNoV1iZ07ZljD54MZm3js9wmjOIRmx2dSSpCkC/jTrtUzFRzGUnTq4ki44OF5p5qC4PEqp89KyyYc6U4rS53d+GjdZx0wIIYQQQgghhJieBGDEZSstBP0hiu+9SfHkMfA97PomgjfehtPQxGI3S9CIozX0jWY57ZwZpNSamrBNdQDifadYdOQtMkMjGG4R8+0jBNpXoNqXkz95lGjbcozhAZQdJPfSD9Bngj13PfVxNrQHcaJxgmMDGDu3od1zg5lGokqCL2Lh8n2Wh1zaAj3kQ3m8zCjhd1+DdyF814MU6ptLfXfbTyh2nABfYzc2EbzxDnKpOkztsj7qsubge+QP7UN5Lj7g1zcQqK7D6emC84IO7mA/oaEBqGnArarGStXiDvWXCrUmoDQBC1QgADX1F26CZWNEYngVUh0CmIkUPoqZ5028PMr3aA5By6oUrgZbge+5cInj0Aaa6miA3rF8xfJY0MY2ueT3FyVKKQZyLkOD5z7n+oQn6+TMUMBUHBrIl6Vrq44G2NwYkSCMEEIIIYQQQggxDQnAiMtWWgg6gXXXw0RzGdAaN3xmIWjXpb06wtYTgxVT7GxelCSeGybz/HcxhgcwT58ASmON+R3vEA6FMKJxXN8nWN/EyLf/X9nx+X07iVgWbi6HZ9nlaYGCIVRjqwRgxIJlGAbs3o7z3lvEIxGy2ez4TJHM898l8uTHyMaTWPc+RjRXWlDeDUfJakBrLKXw3n2DwoHdZXMFiscOwaF9hG64ifzxw5PO62fSUNOAY1qE73o/2We/XT7LxrKI3PUg+XDsgun8HNMiuH4T2R+/UKFUYa/eQPY6DABrz+VKxEU8z2NDU5yDPZXTkG1ZnMTSriyBfgUUXJ908VzAMOVJ4OBijBXcsnRtJbL2kBBCCCGEEEIIMR0JwIgrxtW64kLQtUGfB9c08sqhPvJnZr+YhmJTa5JV1UH8g/vQxQLKLF2OyrLwYlUUrCCF7m7iDz+F2d9F4ch+7CVL8dNj4PuoWBzf19jLVqM6TuKk02Qdje9rwok4yfsfphCJcdGLMggxTwTyGXJ7d1Qs08UCfscJ1Mr1Z/pu9EzBuX3s9AiZw/smHatMC+f0CUJbbi+lAzsviKIipfuA1ppcspbwkx9Dd53CG+jFrK7FaGolH61CT9E3DdNkzDUYzXtYpqKpbTWh4UHye3eA1hR9RVGZxG69i+FUM0ED9CWk/5ot6kPwwOoGXjvcP36PtAzFjYtTtCdttD9dkjYhhBBCCCGEEEIIMVtJAEZcddr3WZ5QNN/YzGDOw/M1ybBFleVjKB9voA8APxDEiCUYCyXoyrrULl1FLBwid+IERusivLG3cYNh1Jkgj39m0Dd7YA/WhpsZTraQHRiEQJCjoSQjmSh31poEJHePWKBUoYAuVE5tBeAP9GIYxtQL2OcyUKHMDwQxwmH8kSGUHUBPSA9mJlL4ydrx11prcqEIgbYVBJLVeD2d+B0nCTW2UIgn8c6b2uEpi62dWd47NYxzZoZCMhLgiQ130bhyA4NdPfTnXEbDKXbmLEbf7eSWtho2NoRQczRQoX2PVUmTls2le6SvNamwRcLyJfgihBBCCCGEEEIIMYdJAEZMYhoGVjGPVgZeIHhF3lNrTRiHlvDZLQ7aB20YGMkUAL5SOA2LOH26jyW33oq79TXSvd34i5aSzd5IpKuTUHUNXixellas6Cs6ekd53VzGsFuL7wAZDxjFMhT3LInhTzXALMR8ZgdQgQC6WKxYbCRTeNOkAFN25f7vK4XVtAgzVYNlWZiBEL7r4BeKhO68n5wdKJsVE3Id3DdeYOzEkQlvbhDecjtqzUbcMwnODMNgT3+Bt48Plp1vOFvkm7u6uXtlIz8aKK3/pLMaKK339MbRfmqiTSyaw9mQfN8nonwi420o3SOFEEIIIYQQQgghxNxlXO8KiNlDKUUkPYzxkxcpfOf/4Tzzr1g738Yd6L1q5/R9H7O1DWXZpUWS8x6JFavhyF6c/l7sunpGzDD9HV3o5Wtxuk5jOOWDyemCj7tkBYOZ4qQ1FPZ3j5F2p15kWRZgFvNZMRIjuGJt5ULLwly0dNoFtN1EEqu+qWKZH41jL1uD5bp4xw7B0ADhVWvxouUBUsMw0Ad3U5wYfAHQPrmtrxMY6Bnvhznf5N2TQxXPl4oE+fHRAbSi4noo204NgyHPFAghhBBCCCGEEEKI2UMCMGJceHSQzPe/QeHgHvzMGN7oMLltb5L+wTcJFadOY3S5crEkkXsfQQXD5IoeqfpacscOYSdT5KvqyLk+ucFB8rUtWIvbIZseP1aZJqFb72K7U/nRd8fzKZyf4wgI+B6RgR4CB3cROnmEcC4twRgx73i+j3HDzQSWLCvbroIhovc+Sj6enPb4ojIIve8BzPP2M4Ih4re8j5FXfkSutxtHKYqZNGM/fgH/nVexJ6T9s4t5Cvt3TX5zwyTUtgKj6zShw3sIdxwjnEufv5zMuIBl0jNamLKfjuVdXFmpXgghhBBCCCGEEELMIvK4sADAUorijq0V14vwhwbg5FHU8rVlT7ZfKVpr8s1LiDz1M9Se6CDoF3Fa2xnBYiR/biC3e9cuajatJdTciuO6KDuA0dTKST9O196eiu8dtAyCpgGcS0EWLuYpvvos+a5T49uUbRN53/vR9fVXvH1CXE95K0Dg7oeJOXlUVwfYAaiuJR+KoqeZ/XJWLpYk+MRPofq68Qf7UbE4dl0DmVefxc+MTdq/cHAvsVU34CRrADBcF7+QK99JGURXrSP/1qsURoZg8VK01vjBCA/ecA/PqQSZQvnaJ0XXoyERJJ2rHAxORmxsA7RkG1zwDGPysyUVA3eGQTxo0Rg/l2ovEjCvZtXmFcsofdbnf7ZKKYyLeJ6h0vc13cy8K3381TAb6ySEEEIIIYQQ4vqQAIwAwCrkyHWenLLcObwPc+V63Ku0lorWmqwdpLB4BadPdqJUGK9QKNunJhLAOXUUe/lqiq3t48fVapugZVBwJw9urGuqIm754+uIm4bC3f4mzoTgC4B2HDKvPkusZTEY9lVpoxDXi6MMAkuWMRCInAuizjCYqrUmbwWgaTFGSxtaa9RgL25f5aAngNd9GpWqRWuNFwxhJVK4g33j5XZjM8Vd7+J2d2DW1I2nFDOLOcyfPMeNdz3Fa+Xdn97RHA+ua+EHu05PSkGmgBsXJdGeLFi/0BmGwXvdWQYz5akq1zbGgfKoQCCZov74LujoHt+WYiUZS2ZDzkRrMszIu+8w1luepjTV2ECqYTWdo4Upjjyn0vdVHQ2wuTEyo4DF5R5/NczGOgkhhBBCCCGEuH4WTADmhz/8Id/97ncZHh5myZIl/OIv/iLLly+/3tWaRS4wGGuo88euror6EGQaGrDXbWRo29tA6bRV4QDJsIkRS6Drm8pm4sRNjyfWN/Hc/l5G8854dVc1JtjSGsPznPF9A9k02SMHK5/c83COH8ZYvg7vKgWahJjLzg0eXuBmMOGJeMcwCW26BffF741vs+NVZI4fBsPASCRxz/RnrTXVlk+gOIhlVOOeWdTJNhX3raynLQH3rKjjJ8cGxgOuQcvg9vYamiMKZGxTAIOZIt1j5YP/bdVhwhX2LQ72M9bRMf7aaW64yrWbX8Z6++g9Xv5AQ9A0oGH1jN+j0vcFk9OKmubk2UlKKYazFz5ea11aj6pC4LlSUORyZ7DMtE1CCCGEEEIIIea/BRGAeeONN/inf/onPvWpT7FixQq+973v8bnPfY6/+Iu/oKqq6npXb1ZwQlECi5dSOLS3YnlgxTry3jUY3fQ9llaZeHfdTX0sQHrvTkL4BE1FoKGR4B33kwuEyp7e932fxpDipzc1Mpj3cDxNImiSDGj0hOALAI6Dds/bNvH0o8OyFowQF+AnqjDjVXhjIxVKFWZj6/hAp9Yap3kJkTvuJ//em/i5LPgeyg5gNjThBYJl/dnEp0EV+MiNLXSPFghaBvVRm4Tlo12X9bU2balmBvOlIGl1yCJmevi+BE2FmK9M02R029ZLnm3jui7bujKTZkZVmpkiM1iEEEIIIYQQQlxJCyIA88wzz/DAAw9w3333AfCpT32Kbdu28dJLL/HUU09d38rNEp7vE9ywBef08dIA6QRmXSNea9tVWf+lEu17GJYifOudVG24AbIZlG3jxJNkURVTJ2mtCeDQOJ7K3624FoQOhjBCYfx8bnIhYNY3yQCLEBdQtAKEbrubzIvfh/Nmi4XWb6KYSJVtc5XCX7GO0KJ2VHoUW0Hh2EE8z6/Yn81kNdWmS021dea+46LPdEvf94kon8j4dAYH6bJCzH9jvb2XNdtmMONUmJUClWamyAwWIYQQQgghhBBXyrwPwLiuy9GjR8sCLYZhsGHDBg4enCIV1QKVi1UReewjuIf24Zw8gjJNAivXE9uwmd58ccZrRlwpnu+TC0UhFL1i7+mEowTXbya39Y1JZUYojL14KbrCWjJCiHO01hSalhB77CM4+3bg9vVghKME1m3Ca2rFrTCLzPd98oEQVIcoGgb2inV4+3dN2s+MJ9F1jePnEeKsSmmhzqeUojY6eR2vSGBy+ipxEQyDeNCiMT7+lMNFfaaGKn0353+HSikMdeF9ZWaqEEIIIYQQQoi5at4HYEZHR/F9n2QyWbY9mUzS2dlZ8RjHcXCcc2mqlFKEw+HxP0/8/3yTiyYwt9yBvfEmUAaOYWKmalDd3Rc+eA7wfR9W30DIcSjs2T6ejsyqriX8vvdj1TXMm7ZeyHy5lmfSXyf+ea6391JcjbZrIJeqw3zfgwRcD980yZ8JmFzoLL7W2DfeTlD7FA7vH59FY9U3Eb7r/WTt4BVbckq+9/nRdsMwYO97+EMD49vMRe2QHsWbsM1a1M7SgWFiHeX38RQryVhz/3O4XgLJFPXHd8GEz/ViPtNk2IY928q+PwAzVUMytbIshVgybPNeV4aBCSnA1jbGuSYL0QkhhBBCCCGEEFfYvA/AXIp///d/5+tf//r46/b2dv7kT/6Eurq68W2NjY3Xo2rXzXxrr25qwbvxVvzREbBtzNoGzGgMmH9tvZC53t6Z9NeJ5np7L8dsa7tuasHt70Gnx1CBIGZdI0Y4zNVYmWu2tf1ami9t18OD6P6ecxtSNfjDg/h954ICOlVDcaCfsY6OsmOd5oZrVc15qzhY/rlO+ZlWmC1TFbLwh4fKvz/AVwakzn8DGMyWpwtrqw4TnrzbZbtWs22mmgEESNpTIYQQQgghhJjn5n0AJpFIYBgGw8PDZduHh4cnzYo56+mnn+aJJ54Yf332H+N9fX14nkdjYyPd3d0LIj2OUmp+tzd6Zqh3dAw1lp7fbT3PXPpum5qapiybrr+6rlu2fa6090qb3W03zvXD4eHSf1fQ7G771XW92j5df71USikGci5Dg/nxbQ0Fj5jMiph1Ks2WaV6zkrGCR++E7w+gPuFd1xlalWbbtFVHrnidKp0HoDoaYHNjRIIwQgghhBBCCDGPzfsAjGVZLF26lN27d3PLLbcApacNd+/ezSOPPFLxGNu2se3JOeTh3JoEWusFNZi3kNq7kNoKc7+9M+mv52+by+29HNJ2aftcVnB90kVv/HW1N/fbNF9Vmi3j+OXfH0DKu/6Bh/Nn21RHKv+eXOnznBO5KucTQgghhBBCCDE7zPsADMATTzzBX//1X7N06VKWL1/O97//fQqFAvfee+/1rpoQQgghxMJUIV1ZImQxknenOWj64+uiNoZhlK2BlM/nqY3alFavOqfSuZQqBWEmBi1ro/aUKcTOdyVmz5x/HqVU2Vpn0+0LktZMCCGEEEIIIWaTBRGAueOOOxgdHeVrX/saw8PDtLW18bu/+7tTpiATQgghhBBXV6V0ZfUtjYw1raFjJD/NkVMf37JmJZn3xhjqPrvejKJ+1QqWDg0Tm7DfVOeKBy1SR3cR7+op2+9wcAPHB7Nlx7dVRxgruFc0hZlhGLzXnWWwLF2ZornaZW21hed50+4rac2EEEIIIYQQYnZZEAEYgEceeWTKlGNCCCGEEOLaOz9dWTJkwUUsI1Qp3VlxaIDe46fGt1U11lMcHCjbb7pz5fsn12msyZ2UQqw6YjOUc694CrPBTPG8cykikTCV/to+eV+QtGZCCCGEEEIIMXssmADMlWBZVsU/LwQLqb0Lqa0wf9s7Vbvma3tnQtq+MM32tk+1htNZlmWhlCJRX4/i3MyCSCqJWQxgGOe2GfEqIvWahvPWhwmlkliWQYOrL3rb5exrmiae512Vc12r403TvCaf1VmR+joa46GyWSTVkSB2fR3nzyuZ6bmCVVUYChrc8lkhMz1Xpf0AGmJBqsIeNdHARW+D0mybSv2zvSZKbSxYtq06ZmOaJqZpTrvv2fecD+s+CSGEEEIIIcR8oLT8C00IIYQQQgghhBBCCCGEEOKKuvBqoqJMLpfjt3/7t8nlcte7KtfEQmrvQmorSHsXEmm7tH0ukvpff9KG2WE+tEEIIYQQQgghFioJwFwkrTXHjh1bMKkdFlJ7F1JbQdq7kEjbpe1zkdT/+pM2zA7zoQ1CCCGEEEKIq+srX/kKyWTyelfjqmtra+Mv/uIvxl8rpfjWt7417TGf+MQneOqpp65qvaYjARghhBBCCCGEEEIIIYQQ4gr7xCc+gVJq0n+PPPLIFT3PRz/6UQ4ePHhF33Mqhw8f5pOf/CStra0Eg0Ha29v5+Mc/ztatW6/J+Sfq6uri0UcfBeD48eMopdi+fXvZPv/zf/5PvvKVr1zzup01u1fmFUIIIYQQQgghhBBCCCHmqEceeYQvf/nLZduCweAVPUc4HCYcDl/R96xk69atPPDAA6xfv54vfelLrF69mrGxMb797W/z2c9+lldeeeWq12GixsbGC+5TVVV1DWoyNZkBc5Fs2+YjH/kItm1f76pcEwupvQuprSDtXUik7dL2uUjqf/1JG2aH+dAGIYQQQgghFrJgMEhjY2PZf6lUarxcKcX//t//m6effppIJMKKFSv4zne+U/Ye3/nOd1ixYgWhUIj77ruPr371qyilGB4eBianIPvDP/xDNm3axD//8z/T1tZGVVUVH/vYxxgbGxvfx/d9vvCFL9De3k44HGbjxo18/etfn7IdWms+8YlPsGLFCl577TUef/xxli1bxqZNm/iDP/gDvv3tb4/vu2vXLu6//37C4TA1NTV8+tOfJp1Oj5efTQv2P/7H/6CpqYmamhp+/dd/Hcdxxvfp7e3lySefJBwO097ezv/9v/93Up0mpiBrb28HYPPmzSiluPfee8vOdVahUOA//sf/SH19PaFQiPe9732888474+Uvv/wySileeOEFbrrpJiKRCHfccQcHDhyY8rOZjgRgLpJt2/z0T//0gvlH8EJq70JqK0h7FxJpu7R9LpL6X3/ShtlhPrRBCCGEEEIIMb3/9t/+Gz/90z/Nzp07eeyxx/jZn/1ZBgcHATh27Bgf+chHeOqpp9ixYwe/8iu/wu/93u9d8D2PHDnCt771LZ555hmeeeYZXnnlFf74j/94vPwLX/gC//RP/8Tf/d3fsWfPHn7jN36Dn/u5n5tyFsv27dvZs2cPn/3sZzGMyWGFswGgTCbDww8/TCqV4p133uHf/u3feP755/nMZz5Ttv9LL73EkSNHeOmll/jqV7/KV77ylbJUYZ/4xCc4deoUL730El//+tf5m7/5G3p7e6ds79tvvw3A888/T1dXF9/85jcr7vef//N/5hvf+AZf/epX2bZtG8uXL+fhhx8e/7zP+r3f+z3+9E//lK1bt2JZFr/4i7845bmnIwEYIYQQQgghhBBCCCGEEOIqeOaZZ4jFYmX/ff7zny/b5xOf+AQf//jHWb58OZ///OdJp9PjAYUvfelLrFq1ii9+8YusWrWKj33sY3ziE5+44Hl93+crX/kK69ev56677uLnf/7neeGFF4DSLJDPf/7z/OM//iMPP/wwS5cu5ROf+AQ/93M/x5e+9KWK73fo0CEAVq9ePe15/+Vf/oV8Ps8//dM/sX79eu6//37+6q/+in/+53+mp6dnfL9UKsVf/dVfsXr1ap544gkef/zx8fodPHiQH/zgB/z93/89t912G1u2bOEf/uEfyOVyU563rq4OgJqaGhobG6murp60TyaT4W//9m/54he/yKOPPsratWv5+7//e8LhMP/wD/9Qtu/nPvc57rnnHtauXct/+S//hTfeeIN8Pj9t2yuRNWCEEEIIIYQQQgghhBBCiKvgvvvu42//9m/Ltp0fHLjhhhvG/xyNRkkkEuOzPQ4cOMDNN99ctv8tt9xywfO2tbURj8fHXzc1NY2/5+HDh8lmszz44INlxxSLRTZv3lzx/bTWFzwnwL59+9i4cSPRaHR825133onv+xw4cICGhgYA1q1bh2maZfXbtWvX+HtYlsWWLVvGy1evXl2WZu1SHDlyBMdxuPPOO8e32bbNLbfcwr59+8r2nfidNDU1AaW0aIsXL76oc0oARgghhBBCCCGEEEIIIYS4CqLRKMuXL592n/NTDiul8H3/ss473XueXY/le9/7Hi0tLWX7BYPBiu+3cuVKAPbv3z9lkOZK1W82mFg/pRTAJdVPUpAJIYQQQgghhBBCCCGEELPQqlWr2Lp1a9m2iYvGX4q1a9cSDAY5efIky5cvL/tv0aJFFY/ZtGkTa9eu5U//9E8rBiKGh4cBWLNmDTt27CCTyYyXvf766xiGwapVq2ZUv9WrV+O6Lu++++74tgMHDoyfo5JAIACA53lT7rNs2TICgQCvv/76+DbHcXjnnXdYu3btjOp2sSQAI4QQQgghhBBCCCGEEEJcBYVCge7u7rL/+vv7Z3z8r/zKr7B//35++7d/m4MHD/K1r31tfLH6szMzLlY8Hue3fuu3+I3f+A2++tWvcuTIEbZt28Zf/uVf8tWvfrXiMUopvvzlL3Pw4EHuuusuvv/973P06FF27tzJ5z73OT74wQ8C8LM/+7OEQiF+4Rd+gd27d/PSSy/xH/7Df+Dnf/7nx9OPXciqVat45JFH+JVf+RXeeust3n33XX75l3+ZcDg85TH19fWEw2F++MMf0tPTw8jIyKR9otEov/qrv8p/+k//iR/+8Ifs3buXT33qU2SzWX7pl35pRnW7WBKAEUIIIYQQQgghhBBCCCGugh/+8Ic0NTWV/fe+971vxse3t7fz9a9/nW9+85vccMMN/O3f/i2/93u/B0ydLmwm/vt//+/8/u//Pl/4whdYs2YNjzzyCN/73vdob2+f8phbbrmFrVu3snz5cj71qU+xZs0aPvCBD7Bnzx7+4i/+AoBIJMKPfvQjBgcHufnmm/nIRz7CAw88wF/91V9dVP2+/OUv09zczD333MOHPvQhPv3pT1NfXz/l/pZl8b/+1//iS1/6Es3NzeMBofP98R//MR/+8If5+Z//eW688UYOHz7Mj370I1Kp1EXVb6aUnunqOYK+vj5c16WpqYmurq4ZLzw0lymlFkx7F1JbYW61t7m5+aKP6evrw3Gc8ddzqb1XmrRd2n4t234l+ivM/e9urtcfpA2zxdVqw8X21c7OzmtSr9lK2ju/zfb2XspvqxBCCCHmt8997nP83d/9HadOnbreVREXYF3vCgghhBBCCCGEEEIIIYQQorK/+Zu/4eabb6ampobXX3+dL37xi3zmM5+53tUSMyABGCGEEEIIIYQQQgghhBBiljp06BB/9Ed/xODgIIsXL+azn/0sv/M7v3O9qyVmQAIwQgghhBBCCCGEEEIIIcQs9ed//uf8+Z//+fWuhrgExvWugBBCCCGEEEIIIYQQQgghxHyzIGbA/Pqv/zp9fX2Ttj/00EP88i//8nWo0fyllMI0TbTWeJ53vasjhLgKLMuSPi7EAqCUAsA0TVzXvc61EUIIIYQQQggh5p4FEYD5whe+gO/7469PnjzJH/3RH3H77bdfx1rNTqZhYBXzYChcO1T2uU1HKUVGW5wYLHBqeIxowGJVfZTaIODLIK0Q80FR2XSlHQ73jWAoxcr6GI0RA1OXBmYNw8ByHZTn4QWCuFpf5xoLcXUYhoFdLADgBIIz/q2cK5RSpH2L4/15Xuk8ha1dVtRGqQ1qtPymCyGEEEIIIYQQM7YgAjCJRKLs9be+9S0aGhpYu3btdarR7KOUIpwewdm7ncLp4yhlYC9dQXDVDTM6ftg1+dauLjKFc0/I7jw9zB3LatlYH5QgjBBzXEHZ/HB/Px3DufFt+7pHWV4f4/6lKWJOBn1kP8UDu9FOEauhmciGLeRTdfNucFosXEopwplR3P07KZw4glIKe8lyrNUbyEXi6HkQdFRKMeCYfHtXJ7miRyQSIZvN8t7JIe5dWc/aGluCMEIIIYQQQgghxAwtiADMRK7r8tprr/H444+Pp9Y4n+M4OI4z/lopRTgcHv/zxP/PF5H0CJnvfx0/f25w1duxFev4EdyP/Pz07TUsXjk4UBZ8AdDAG0f6WZxspdqe/Z/XfP1upzJf2juT/jrxz3O9vZficttuGAb7unNlwZezDvemWVkTYfn2FyieODq+vXjsEMWTx4g9/BS52sZLq/gVIN/77Gr7TPvrxNezqf7h7BjZH3wDP5sZ3+bt3oZx4jCRRz5ELhwb3z4b6z8TvmHx4qE+ckUPzlZdgdbw6qE+WqpaqTLnTlB1rn4PE82HNgghhBBCCCHEQrXgAjBvv/02mUyGe++9d8p9/v3f/52vf/3r46/b29v5kz/5E+rq6sa3NTZevwHFK037PpkdbxIyFEQi5YVOgeKh/TTefs+Ux58ayjFUGCBy/rFndOdg3eKmK1nlq2o+fbczMdfbO5P+OtFcb+/luNS2j+Ydju4/MWUf33uyn1WGVbFc7X6Xhqd/FiMUvqRzXynyvc8OF9tfYfbUX2tN9sVthNCTfys9F/v0MZJ3PzTpuNlS/5k6PpAh7Rpl/TkSPvfngaJi9dK585t+1lz7HiqZD20QQgghhBBCiIVmwQVgXnrpJTZt2kR1dfWU+zz99NM88cQT46/PPnHY19eH53k0NjbS3d09L1KNAASdAvlD+/Cz2UllSimMI/vJta+kOEVzRx2TTIVjzxoaDdDTo2d9GiKl1Lz7bqczl9rb1DT1YN90/XXiotFzqb1X2uW2vaAtRtMZssXJaYeUocjkhshpHyrdB04eQ58+SS6amFx2Dcj3fu3bfiX669my2fTdBVyH4oE9eFP83hX27SK/bB1FwwBmX/1naqRgkD3bRlUKvmRz2dK0VmBoNENPjzfrf9PPmqvfw0RXqw3T9VUhhBBCCCGEEFfGggrA9PX1sXPnTn7rt35r2v1s28a27YplZ//hq7Wes/+QP9907dBao5RCT7Nf1FLEghbp81KQndWaDON5cydf/Hz6bmdirrd3Jv31/G1zub2X41LbHjQ0TVVhjvSlK7wpLK6OYhwdoPJw7PT3j2tFvvfZ0faL7a9nt8+G+muAaVJAlX4rJ9d1ttR/pmIBg5Btkne88aALE6rfmAjOqd/0s+ba91DJfGiDEEIIIYQQQkznr//6r/niF79Id3c3Gzdu5C//8i+55ZZbrne1LotxvStwLb300ktUVVVx4403Xu+qzCpOMExgyfIpywMr1+Ey9aBTyPC4ta2mYlltLEhjbEHF+YSYd7TvsmVREsuYfB8IWgYb2urxR4YqHms3NeNG41e7ikJcdV4giN2+Yspye9kqXHPu/95FDY+blqQqlrUkw9SHzWtcIyGEEEIIIYQQ15qXSVM8doj8nu0Ujx3Cy1R4KPcK+9d//Vd+8zd/kz/4gz9g27ZtbNy4kYcffpje3t6rfu6racEEYHzf5+WXX+aee+7BNGXwYCLf97HWbcKITR4ktWrqsZetmvaJS9/3WVlt8dCaBpLhAAC2qVjTlOCJdfUEtDPlsUKIuaEu6PPBG5pprAqhAEPB4uoIH7yhiVQ0QKBtchBXBQIEb7oTRx7YFvOA53mYK9djxpOTysxkNcbS1XMmLdd0fN9nfV2I+1fVkwiVZisFTIMNLVU8vKoWS37ThRBCCCGEEGJec7o7GPv2v5B+5mtkX/we6We+xti3/wWnu+OqnvfP/uzP+NSnPsUnP/lJ1q5dy9/93d8RiUT4x3/8x6t63qtt7j+qOUO7du2iv7+f++6773pXZVbKReKEH/kw/tH9OMcOgWFgL1+D0b4Sq7oWurqmPV75HiuqDJZsbCDvgakgZvr4vgzUCDEfaN+nMaR4el0tGVeBhpilwXcpoAjecT+RxUtx9u3Ed4rYTYuwVq8nn6iGeTAoLQRALhQh/OjT+EcP4Bw5AEphL1uN0b6SXDB8vat3xRi+y9pqi2WpRqxwjHw2TdT08T35TRdCCCGEEEKI+czLpMm8+D38gb6y7f5AH5kXv0f8gz+DGY1d8fMWi0Xeffddfud3fmd8m2EYvP/97+cnP/nJFT/ftbRgAjAbN27ka1/72vWuxqyltSYXjmJsuBlr3Y1owDHMi8o1rrXGxsE+M69KxlyFmF+01ijPJaYABRMXfSmYNqptJVbbCkzfx7Nsip4nNwIx7+SCEYx1WzDXbAJKv5XzYebL+XzfJ6A0TckwXblhfE+msgkhhBBCCCHEfOf1dk0KvpzlD/Th9XZhTpOe+1L19/fjeR4NDQ1l2xsaGti/f/8VP9+1tGACMGJmfN+neHa9F99HTbPg8HxjGAbe8CChoT6UYeDGqnBMSxa8FWKGtNY4AMqAWbZIt1KKgOdgjo2gfY2OJygGQvNy4FxcXYZhEMyOQS6Lsm2IJ5GrSAghhBBCCCHEfOBnM5dVLiaTAIwQgIkmcHQ/o3veI3Mmymulagnffi/5uiYZpBViDtNaE+o5Te4nr+CNDAJgxOKEb7qT4uLleBJkFTMU8D3U7q1k92xHFwulFGSNLUTuuJ9cNCEBeyGEEEIIIYQQc5oRiV5W+aWqra3FNE16enrKtvf09NDY2HhVznmtGNe7AkJcb0opAt2nyLz6HDp3LorrDvWTee47hEaHrmPthBCXyzl1nPTz3x0PvgD46TEyr/yIYO/VXUBOzB+GYaD2bif33lul4AuA1jhdp8k9+x2Cxfz1raAQQgghhBBCCHGZzPomjJq6imVGTR1mfdNVOW8gEGDLli288MIL49t83+eFF17g9ttvvyrnvFYkACMWPFv7FN57G5j85LJ2iriH9mKa5rWvmBDishmGQXHfDnDdyYVaU9jxDva1r5aYgwK5NPm92yuWeWPDqJ7Oa1shIYQQQgghhBDiCjOjMaL3Pz4pCGPU1BG9/3HMaOyqnfs3f/M3+fu//3u++tWvsm/fPn71V3+VTCbDJz/5yat2zmtBUpCJBc8o5MuejD+f19OBoTWza0ULIcRMmL6H29s1Zbk3NIBVzEMgdA1rJeYilcuhC1PPcvH6ezAWL5OUlUIIIYQQQggh5jS7sYX4B38Gr7cLP5vBiEQx65uuavAF4KMf/Sh9fX381//6X+nu7mbTpk388Ic/pKGh4aqe92qTAIxY8LRpoYIhtONULFfROL5S17hWQogrQRvmtPlJVTCEtmQOjJgB2wbDgCkCLCoalzVghBBCCCGEEELMC2Y0htm+4pqf9zOf+Qyf+cxnrvl5ryZJQSYWPCcQJLh6w5Tl9qoNeJ7MfxFiLnJ9n+C6zVOWB9dsxJUAjJgBJ1ZFoHVJ5ULTwmxeJAEYIYQQQgghhBBClJEAjLimAtojMtRLuOMYkf5ugp6Dus6zS3zfR61YR2Dx0vICpQhvvhX3Ki0uJcT1Mhv74dVkty0jdMNNQHkbA0tXoZeulJRRYkZcrQnccg9mqqa8wLSI3v0g+VjVjN7HRhMZHSTccYxw72lCxTyGIX8dE0IIIYQQQggh5iNJQSaumUg+Q/7lH5Lv6x7fZlZVE77vEXKJ6uv65HDeChC8+2FihQz6yEGwbMymRRQTKSos3S3EnDV1P3yUXCI1L5/gN0IR9MZbiLWtwOs6BZ6H2dyKk6yhoMzrXT0xh2TDUUKPfAjV343X34sRjqIaWyjEqvBn0HdCbhH3zVdIHz8EZ/Y3QmHCdz9EvlFm0AghhBBCCCGEEPONBGAWIKUUhmGgtb5mT34H0BReew53wqAvgDcySO7FHxB4/CMUrMA1qctUioZJYOkq3GgS3/dlIEzMO7aerh9+f8b98HrcQy6XqwycqmpUsgalFIU5Um8x++StADQuxmhuQ2td+q2Ywe+FYRj4u96leOxg2XY/nyP74veJfOBj5KKJScfNxf4mhBBCCCGEEEKIEgnALCBKKTLa4tRQge7RDPGQzdLqMKmAj77KgzrWyCD57o6KZd7oEMZgP9Q3X9U6zJQEX8R8ZY0MTN8Ph/qhbup+qJQi7VucHCrQO5YhGQ7QVh0iaV/9e8iVMj5gLsRluthgSCCXJndwT8Uy7Tr4p49jrNk0/r5KKTK+xcnhAj2jGRJhm/bqMKk51N+EEEIIIYQQQoiFTgIwC8igY/LtXV1ki+eSar19HN6/uoHlVSboqzego/O56cuz6at2biFEyQX7YSYNdZXLlFL0FQy+s7uTvOONb3/ruOKhtQ20x5QENoSYhioW0cXClOX+0MD4WkxKKfqLJt/Z3UmueK6/vX1c8eCaBpYlDAnCCCGEEEIIIYQQc4Cs+rpA+IbFi4f6y4IvAL6GFw/0MuZd2XUQDMMoW9RbhSKcvwD2RCoav6LnF0JMpsIX6Iexqfuhg8VzB/rKgi8Arq95fn8vab9yPN8wDFlgXAhAB4KoYGjKcqO6dnz2i6ssXjjYXxZ8AfB8zQv7exlzZe0iIYQQQgghhBBiLpBRsQViuAg9o/mKZa6v6RwtlAVMLlVR2ZzIwJsdefYMuoz6NsowcKpS2M2tFY8xq6rxU7WXfW4hxPTcy+iHQwWfoWyxYlnR9enNOGXbtDIZdC3e6ynydlee7oKBp2TSpVi4iuEowdUbKpapQACjtQ2APDYn0j57ezMMFTXOeX9Vczyf7nTlviiEEEIIIYQQQojZRUbDFgjXmz5VSc7xgMt7onZM23x3Zw/DuXMDQ5ZRSpeyNGESet+D8NqzOF2nz5VX1xG69xFydmB8EWPLUJjFAtq0cAxT0hoJcYU4GGf64Y9wus6tBTPeD63AlIuJO970/bDg+ihV6q++snivO8vbxwc5e9TbwJKaKA+uqCagnene6rpRSmFrH+U6eHYQV+494gryfR+1bjPBXJbC4X1wZraLEY0Ruesh8rEqhhyD7+7upikVpS9dSldmKMWiVJjYhL+x5R0Ppexr9vtoo1FuEd8O4Ei3EEIIIYQQQgghZkwCMAtELGAQtAwKbuVATH08iL6cNWBMi5f3D5QFX6A0u+blg33Ub25BB8MEHniS4MggOpdBhcK4VTVkDRO0xlAQGuiluOtdCgN9GIEgwbUb0UuWUzDlUhXiSsgFwwQe+MCU/XAq8aCBZShcv/I+NREbrUvpknpyPm8dH5y0z4mBDLsTIW5qDJYGo8/MupsNQdaA72KcPEZx73b8fA4rVUPkhi0UahrxLny4EAAXvKYLpo11273E1m5Cp0fBstHJanKBEB4GLxzsZyzvsFip8d9sX2tOD+dYVhvFpvQ7XRcLjve3q8nWPvnd23Dffh0/m8FMVBHesAWnsRX3+ndbIYQQQgghhBBi1pMUZAtEzPTZvChVsayxKkR9+PJmv4wU4fRgtmxbKmxxf43m/V4H5s63iPR3obRPNllLrmkJ2VQ9RaN0XqUUwc6TpH/wDYonj+JnxnCH+sm+/gLeWy9jTzHQZBgGmBaGBGiEmLGiMir2w/NN7F9VlmZ9S7LifourI9SESgPPpmmys3N0ynPv7hwBzycy0ENg33aCh/cSSY9c5vy7y2NrH731dbKvPYs70IufGaN4+jjpH/w7gVNHZQ0bcUEmEEkPEzy0h8C+7USGeqf83XI1ZONJck2LydU1kbeDaK0ZKujxVKHdIxluXnLuN9v3dWkWmlK0pqLUhi4/ZegF26RA7dpK9qUf4PZ142fGcLpOk3n2O1iH9ki/EEIIIYQQQghxxbz66qs8+eSTNDc3o5TiW9/61vWu0hUjo9YLhO/7bGwIY5m1bDs5TLboYhmKFfVxbluSxNKXl0/e8TQTH4atCVu8z+tm+HvPM+w6BGIhglETs76R8D2PkTtvIeKA65B/+7XxlCzjlEHh6CESa27ASdWf26wUQ67Jno40nSN5IgGDjc1JmmMGhu9eVluEmE9M08TFoOh6KKVmNNvEMAyGHJN9XWlODeUI2wY3NFdxc2uCkGWw4/QwOcfDNg1WN8a5ZVEVhn/mHqIUmcLUT+ZvrFL4L32fdMexCSc0idxyF6xYd11mm9gjg6QP7JlcoH1y7/yYUFMreStw7Ssm5gRLa8z9O0hv+8n4b5gZT6BWbyIXS8y43xUnpPkbyBRpr4tx/8p6dneNUvQ0A1mHpqYEKxsTjDhQEzDQ5/9mXkHBsRHSO7cSCYXOK9Hk3v0JkdZ2cqHIVTu/EEIIIYQQQojrJ5136BrNkyl6RAMmTYkQsZB91c6XyWTYuHEjv/iLv8iHPvShq3ae60ECMAuIqV021QVYWdNE3tXYhiJu+/je5OCLYZjkfIVC4c9g4Chil6c42xIpMvTMs2ivNJwatg201rg9XZjvvYF5x/vxJgwcGelRvNHh8dc+BmNFn8FsHt/XNBw+hnlzKzFVWjuiO2/wnV2dOBPWtjkxkOXGRSlubY2gfEkaJBY2pRSjnsXe7jTHB7LEo2lWVAdoqwpgX2ANlp684tu7OihOSFl4cjDLDS1V3NWWYE19hIKrCZgQs3T5PURrFqVCdI/mJr1vKmzTdHofXucJyp7f9z2yb75CrLaebKruMls+NcMwyGsDX0PYBO25KKXwujuByvc5PzOGGhuBq1gvMbfZAz1ktr4OgLIDZNbeyoGcyeGjWULpfaxa3sLSVHDatY8M0yQatFjVWMVAOk9/usCxvjRLa2M8sraR08M5EkGL4UyWF/d1YRmKx9Y1sig6s+DOpfAH+yc/FHGGLhZgdAgkACOEEEIIIYQQ807HcI7v7+keX5sUSqmwH1vXSEsyfFXO+eijj/Loo49elfe+3hZEAGZwcJD/83/+D9u3b6dQKNDY2Miv/dqvsWzZsutdtWvO931C+ITOfPPnxymUUgy7JttOjHJiMEMyHGBdBgLKxFY+qZBJRLmTBnxipscNrUneOT5INGgR6DxI7kzwJWiZhG0DzuSuLxw7RHTTreRC0QknnlBHDDpGC4zmzw1WDWVd3tzdw0Or60gEFC8f7i0Lvpz13qkhVtRFqbl6AVkh5oQh1+RbOzupi4dprIriK4POUYfhnMvmxgjWFIPB2rR47Uh/WfDlrJ0dI6ysj1Ef8AhPcQ/xPI+V9TF2doxMWnNqZcQnsvcgquJ6Uxrn8D7M2xrxvCsfQM1js7s7zb6uMYqeT2MixM2LUzSENVwgm9PZdT2EOJ9pmjj7d42/Tq+/nW8eGiGdKaUSs7IO3a7JvmSEx9bUETyv350NlG47NcKxgRw9GYfaaIAbFlVzoGuYqmiIAz2jVEVKM7DqExEMpegZzfPK4X5+emMDNldn1ucFr3vpF0IIIYQQQggx76TzzqTgC0BfusD393Tz8S2tV3UmzHw07wMw6XSa3//932fdunX87u/+LolEgq6uLqLR6IUPXoBGPItv7uwkV/RoqgqjTIv//cYxCkWXtpoIEdvk7uW1rK2x8Z1zA0m+77O5MYKi9KS8To+igFjQpikRxGTCgKvrguPAhKwmfqwKM1mDNzxA1vXLgi8AurGVgeECbxwf4o72agbOuwmM7wecHMpS1xjCv4qpWa4VpRSGUZo9NB/aI64NZVi8fWyYZfUJ3jk5zNH+XkzLwnVd2muitKQiNE+RUWusyPg6FJUcHcjS2BKe9npMWR5PbmjilcP99I2V+mosaLG2NkzArdx3AfTYyFUJdgzninx/Xx9dI+dm5RwfyHBqKMsHNjSxrGkRpSjM5JkEZrwKL1Z1xet0NSil8A2TrKswDEXClgHyq00BOl1a88ioqWPbsD8efAHA88D36RrJc2K4wKqkWfYAw6hv8Y0dXWSLpSBK1DI4OZTjaH+GD29sxsNgR8coWcfDQGMZis2tSVbUJzjUO8pIQdMQNq/Ob0R1LZiVV2dSwRA6UXldOQHKtEi7CgVETA2SGlUIIYQQQggxR3SN5icFX87qSxfoGs2zQgIwF2XeB2C+/e1vU1NTw6/92q+Nb6uvr5/miIXLME22nxolV/SwDEUiEuSbOzoxLYu849MxUsD1PPZ0j/JLt7exIhUgzLlAiaVdbmkKsa4hRiSwlFz/MQIGcN7T7kY4gj5vDZiiaRG69S6yL3yf4bFsWVli3Ub2+zHA4dRghuLi6mnbUeHB/TmpoGxOjxQ5PZwhHDBZVhOlJqgnTzkQ4jwZT+FreOvkMMf6M2VlxwYyfHNHF79+ewuqQjBE66mScZV4vr5gkMT3fRqCig+vr2ekqPF8TSJgkPDzFOKJsnSDE5kNLThXIdB4fCBbFnw5y/M1bxwbpHltLaH1m8jvfq98B8MkdOtd5O1A6YOZzZRBRw5+cnyQE0M5co7HsroY9600qAnYWBVSTYrLpwGzoRmnr5tcbStHTo6UlatAAP9MEGNP1xira2rQbmkw3jAMdp8eGw++ABj4NEQtHA3hoM0zu7rIOy5nl7t3fc07J4cIL68lFgnRn/fZ3ZWhOhqgrTpEleldsZRkxWiCyI23w55t5QVKEb7lLorh6JQpyhYqwzDoKxq8eXiI04NZNJrW6ii3L0lRF/TlQQohhBBCCCHErJcpTj/ueKFyMdm8D8Bs3bqVjRs38md/9mfs3buX6upqHnroId7//vdPeYzjODgTZncopQiHw+N/nvj/+aTgG5wYLAU/mpIR3jtdGkgqOB7pgounNbVRm3Te5fUjg/TVhbm7LUlgQhBGa01EOYRaW9GREH4uO+k8ofU34oSjqPMGIopNi4k/8RGib22leOoUZjCEuXYjRyONHBlyzrw/RIMmiZA9aZbMWYtTYbT2L/o7utLfrWEYpSfSff+iB8TS2ubbO7sYzp5r47snhrhzeR0b6wNXZNBrvlzLM+mvE/8819s7U5FggGP9vRXLTg/nGMj71FWYIRELKKqjAQYzlQfs22oi+P7M+pepXarHH4rwKVo2oU23kHn12Un7qkAQs30FRX3hAM/FsCyLw93pqSa40DOaZ9Q3qNl8G9GGZop7tuPnspg19QTWbaJQXQ8XWSfzzID7pfT9S9WZU3x7VyfdaZf+M0+qdI7k2d+b4fG19WyoD5cFzK+XmfbXia9nc5/1fZ/girWoA7tAGWhd/hdRs6YeTxmgNb4GUOPtcTE51j/5NxKtSQRMjvZnMI0JbT/7Rw1vnRjirmW1dA7n2N9dmoHz1nHFY+uaWBwzrshAvw/4azYRb2nFfecNvPQYZrKawLrNFGsb0Ve4r14t1/I6GnJMvrWjoyz94smBDN0jOX5qUwtJ69LuB3OhLwghhBBCCCHmh2igciaEmZaLyeZ9AKa3t5fnnnuOxx9/nKeffpojR47w5S9/GcuyuPfeeyse8+///u98/etfH3/d3t7On/zJn1BXd24R5sbGxqtd9WtuNO8QiYzgGTbxSJiRwhiGaZLLOSjDwDQMTMPEsmAo7+IbNoOexebW2orvF336Z8j9+Hm8s4PAdoDguk2EbrwdMxqrXImGBqx4Mz3H+yhg0JX1cAqaSMRG+x6NIWgc6+He5hDPHSmgwhEwjPHD22uirGiuIRa89Ev7cr9b7fu4nacoHj6EPzqEWddIYMkyrIbmGR3vej6vbO+giE0kUj6lb1tnhpVN1SxtuHIp9Ob6tTyT/jrRXG/vTBRcj529RSyrvB+cfV0TC+Eqi6amyp/RA57N9/d0T5r00ZoKs6q5hsRlTDX1k1WEDEV+xzvoQilVk5GsJnLnAwSWriR5ye88Naurg0i48mLhSkE8FqO2qg6aW9Ebb8IvFjFCIZR5cfcR7RRxOk/hHD2An81gNS/GXrwUq6by56wdB7e3E7e3C3yNVd+E2dCEEQhe1HlzjscPtp6ioE2G84Wy730o69CTdgjZNg+tabzuA7gX219h9vdZ3dhI+MmPktu3k/amFIdOD4BpYtY2YFQlCRulv5xubqulsf7c72Wm6BKJjFJUk6+zZAAGx3JE/CI1IZOhTB4ctxSEsQOM5Hzaa2Mc6csQiZy7tn98YpSfv2UJDbGLu4am1dRE3bLV+IUCRjCEsubmXx2v9nXka83bu7owAyEiFVI8Hhgq8oENzRiX0Qdne18QQgghhBBCzH1NiRB1sWDFNGR1sSBNiVCFo8R05ua/oi+C7/ssW7aMn/mZnwFKgz0nT57kueeemzIA8/TTT/PEE0+Mvz47YNXX14fneTQ2NtLd3X3Nnmy+VgzDYHHc4p3BUTJhg6il6Pd8PF0KKlSFgmTyDq7vEwuESWey7O9waQkUKy+abYUI3PMY5ugw2nUgEiMdjTM6OgajY1PWI6IsevMeXSNpkmGb5ngY04Bs3xA3BouMfudFWpLVPNS2mW3pAgNWFNsy2dBSxZq6MGODfUz97lNTSl32d6uUInjycOkJ/wmfiQoEiT70QfI1DRd87zHfYt+pfrwp9tt5so+ol77sJ5yvRHuvlaampinLpuuvruuWbZ8r7b0SWhIBfM/DP9NW68waMOGAScjQ4Bbp6uqqeGyDZfDwihRvnxiiP10gYBqsb65ibUOEzFA/mYpHzZzRtopAfQsqM4YyLbxEFYOmjZ6iPpdDKcXK+jhbj/ZUnAGzuCaKyqfpyg6XF4yOoQyTnKdQCsLG9OmDTMA6sIPsWz9m/ES7t2PE4kQffppsNFG2v6191O53ye1459yMNmUQWrcRtel2ihMCyxeS8S1O9Y/QN1oou+ah9L0f6hnF8FyOd1mE1NWfBXMl+uvZsrnSZ1U8hX3j7dySh1NmJ3lMHMvCMkyyuSypSIDmCHR1daFMk5yrMA3F6roQL+4vT1tmuQ4jg90sXtnOwdN91Ls+AWwGfR/X19j4LEnFSRgePUOjZcdmgWM9QzhjV+bzOvsd9PQPnPkOLuXX9fq6VteRpywOdQ6SzVWePXiww+F0XQCbi18P5mq1Ybq+KoQQQgghhFiYYiGbx9Y18v093WVBmLpYkMfWNRK7Suu/pNNpDh8+PP762LFjbN++nerqahYvXnxVznmtzPsATCqVorW1tWxba2srb7311pTH2LaNbVe+mM7+w1drPesHhC6W53msa4xyuD9N10iWzYuSnBjuBiAatAiYimyhNFC4oTnBgc4hmqpC06bZKaBg4kK9lQI157FxeGx1LR0Zn3dODvPjY0MEcVmfsjEtjRGO4A/00jT8Ao83LUJvuQu/qpqg8vD94rTrV8yEr0wGC5qM4xG0DGqCClPPbMAklB0j++MXJrVTFwvkXnuewBM/RcGYvtu5vp4y+AKQO7NewJW6/ub6tTyT/nr+trnc3plqicCtbSn2do+RKXjYpkF1OEgqbFMXtagJTU6XdJb2PBqD8IHV1eR9ham4Yv0LSveaXDAMwfC5jVdxbYQl1RFWNSQ40H1usNrFwFCKja3VjDqahGWgz6yvpJSir2jyzslhukZymIZiVUOcG5piRKZI4xUYGSQ9MfhytlnpMQpvvYp1/xM4E647s/s0mffO+x3SPvnd7xGtaYAly2d8nSoFlqGmXD8naBnk3VIaSX1FvsFLd7H99ez22d5ntdYUDItEzOCpW5ay7fQoJwezRIMWa+qq2dAYJaxcegsm75wconskj2UoVjRWcXN7He8e78PXYKDxuk8TDBpsqrY54hRwTp8iZQeoSlajY3G0m2elCbGuYwSsODXRIDXxMAXXxzQUyjAB94p+ZnPhO7iQq90GZWgsc+rZLbZpYCiN9i+9DvPhexBCCCGEEELMfi3JMB/f0krXaJ5M0SMaMGlKhK5a8AVKy4jcd999469/8zd/E4Bf+IVf4Ctf+cpVO++1MO8DMKtWraKzs7NsW2dn57TpThayCA5PrW/gyECeoZzLQ6vr2d45iut6jGSL2KbinuV1DKfz+BqW10bwJywKf/Zp5ssdINDAO8f76UsXqY9amL09nO4c4puWyVMbb6N22wvguXD6GAHXwXj4KZzLGNSA0gygzuEcb3ZkONg1SvpMoKMuHuTh1fUkjBk8OT7Qi3YqP/3qjQxijgxBavprL2op4iGbsSnWuGlNhmUhX3FBhu/wgbV1WErTl3YIBgN4xQJVYYtH19QTwL3wULzvEgLQMFX3UqaFq8FWGn8GAdbrIRq0uLe9iqU1EXZ1jdKf8YgETZoTIZ7f14nr+dy0pJqNDSEM36O3YPKtnR043rlGbzs5xPGBDE9vaCCoy/umYRi4p45ScYoNUOw4STQ9gnNmFoytFMXd2yruC1DY8x7W4qV4hjmjvh41fZbVRTk9WiRTmBwsXlUfZySTI2Tq0sIe4qrxfZ8q0+eB9jj5tipSySSFsSFc16E7Z/LtnR24EzrTeycGqI6FeWxDC+8cH8B0iqxoS7FUjVF1YicPLU7xbH+AfL6I6uvGimVYsriRdcYImW07ufX9P8XbnRleOtKBd+Z9N7dW8fiaeloiWn4rLtPZ+5ulQHvTP4hh+B7rmxO8fLCvYvm65gQWvnRBIYQQQgghxJwQC9msuIoBl/Pde++98/aBs1kXgMlmszz77LPs2bOHkZERPv3pT7N8+XLS6TQvv/wyN91000XlwH788cf5/d//fb75zW9yxx13cPjwYV544QU+/elPX8VWzG1hHG6os9EqiDJM7l9VzzvHB/B8Tcgy6BrOMJgpcnNbNTVBSgN6ymDUM+gcLZJ3POrjQerDJpa++HQ3SilODhcYSBcwKA1q+Nk0AI7r8VbHGE80LUJ3HAfAz6YxHRfMS1sESilF2rfY25Xj9eOHyeSLrG6Ms7jWYn/XMH1jBb63p4eP3FCPPc1MGKUUujg5P+JE2rnw5xFUHre2VfP8/p5JZVVhm5ZEAH0Jn6tYeBKGw4c31DOQ8/EMG+PMehLBK/B0vG9YnB7zeO/0ANmiR20swKaWKupDGj0LB30t7bI0rqiO1vHjw/2M5B12nx4cL//J0QGqQo0sS9q8eWKgLPhy1mCmyInhAquSZtnnp5RC53NTn1z7MDFQ7bv42akTuTnZHENph6NZl1TUpjFqE1ZTf2e+53FTaxXHB/P0pwtlA/ybW5MUig43L0lhau86z39ZOHzfI6h8qsI2XcMe2rB449hA2Xdz1mA6h+t6fPSGetRAPwPPvMFYOkNo5UoWHfgJH1u6noFoE0VPUx0PkRrppnPPfohWkc0X2HZqaPy9EmGbouPyvT1dfGxzCzFj9vXFuUAbFh0Zn/dOD5LOu1RHS/e3xjDjM+UmHaM1y6tDHE5FOD2ULStrSUVYWRPC9+W3WwghhBBCCCEWmlkVgBkYGOAP//AP6e/vp6mpiY6ODvL50iLNsViM5557jr6+Pj75yU/O+D2XL1/Ob/3Wb/Ev//IvfOMb36C+vp5f+IVf4K677rpazZh1jDNrCVzMk7ClfUuDhmuaarD9IscG8xwfzNKQCHHfijrqQgrluyjD5MCQy0sHu8afwAVoToZ5eHUt4YsMFpimyYHecznxtWGiAsHx4EVH3wjZNU2EzwRgzOpafMti0orhMzTmW3xzRxcDOY/jw6U1FDpHcjRXhbijrZp9XcMMZYv053yapllnSmuNkaqdslxZNsTiF6yP7/usSNmwuoG3jg8ylncwlaKtNsqd7SlCU6RAEqIS23doCimamqrp6upCa+fyB+ENk62dWbaeOBfAGMoWOdKX5pF1jSyNG5PuN0qpUqDiOqbQUYbBu8eHODFYOfix9eQQDfFGOoenDqYc7E2ztqa6bL0Sz/MINC2isG9nxWOMaBwdjo6/9k0bs7oWb2Ro0r5ZTzFEmF2nMxwfKQV0Y0GLJzc0UW1NHYSJUOSjG+vZsjjFmyeGcD2f5XUxIkGbpojJoujUKefE5ZnJtZ31FN0j01xXfRmSkQBDfRlyPUNo3yfb1U+DHSHw6vdoRYNpYjUvxgtHaIwF8Fas4JudpYF+w1CkIgHqIjZon6KrOT6cZ0ONNW+fILpqDJPtPTl+cnRgfNNQtsix/jQPrG5gVXLqmWkB7fDoqmo60wn296TRwOr6GC1xG1senBBCCCGEEEKIBWlWBWD++Z//mVwuxxe/+EUSiQSf+tSnyspvvvlmtm2bOm3LVLZs2cKWLVuuVDXnjKKy6Uo7dIxkidoWi6tDpGxd9iT2TEWVy/oai431KbTWeJ43nm1nsKh48UDPpBRFncM53j4xyn3tsYtOTWQZ5/Koa8CqrsPPlGbBGIZRtmh1YN1mspc4wGSaJttPjJIuuLjnjad0juQZLXiEAya5osdYwaUpNP3C2G6yhsCidoqnjk0qC665gWIsMXUupwmU77I6ZdKWbCTraiyliFsaLU/PillgqKjYdnJw0nZfw2uHB2je2EjgTKIdpRQ5bdExWqRnrEA8aLEkGaLK9q/5TBmNYiBTOUUgQLrg4gGGUkw1V8Q0K98DdH0TZrIab3jy5xLafCvFQGj8vuX6PpG1myieOFK29o2LwenhHNFbb+TU6Ll6pgsuz+7r5cM31GFNMwsvqB3WpxQb6xvJuIqC49FclyQ7PFCWKlJcGUopRj2LUyN5hnMOddEgLYkAUWNyoExRCpJ4U9z/lVL8+Eg/hhdkw7IVjB46wFhXF403byF39AAxw8ewbQiVngIwAxahdTdg7M2xvC6KqRS20mh97nrqHytg1AVKv9dixkYdxdvHK9/ffnykn9bNzYSnSSRma5clUVi2MgmUArQya1UIIYQQQgghFq5ZFYDZuXMnjz/+OK2trYyNjU0qb2hoYGBgoMKR4nwZbfPd3T0MThhsfPuE4uG1zbTGg1h4+BfIZ34+rXXZU99QCoYcGchOGVM42DvKzYviRKZel3YS13VZ2xjnWP+5p9S9UASrqQWvt4f2xiqivUchEiV8y10UahouefZLzlMcOXMe05hcyf09Y6ytj3KqmCEWsLjQAgpFZRC68wGMXVspHNqLLhYxwhGC629Er1w/5eBbJb7vE8AncCazmpZMMmIWUErRNVaYss+P5R2GCx71wdLrYc/kO7u6y9Y0esNQPLi6gWVVxjUNwhhoqsIWfZN/XgCIBiwSlqKtJsKh3nTFfdY1xCfdBwHydpDIgx/E2fYGheNHwHMx41WENt+Ks2T5+BPzpmniaEWuroXYA4+Tff3F8XRkjh0mftcdvO0n8M4LtAxkCgzmNfWB6duotcYtFggCIUuRCNlkZAbEFaeU4lQWfrCnA8c7dw1HAiZPbmii1i4PekQtzZLqKEf7K19Xi6ujvHqgG09rWtbdQbUyGDt8gN6uHhp+9v+D0X0Cu7eDYtHBbmomeNOdDCVqiFqnKbga0JN+BqujAZn9cgn6ss6Uv9W5osdw3iM8zWzYsyrdJ4QQQgghhBBCLDyzKgBTLBZJJBJTludy0+TYF+OUafH64aGy4EtTVZiqaIh/39VFMmzTGLMvmM98RudSitH81IMMjqdLM0sucnmWlphNe210PAijAS+eJJFKcueqGsK5RnRVikLw8hak16jxmTwhUxEJmIxOGDTRAKq09kptxJxRFCRvBzFvvpvIus3guuhAkOJl1lOI2eRCY7pni7Vh8eL+gbLgC4Dna57f30Pdllbi13CNCs/z2NhcxZHedMX5LTcuSqK8ArcuSdE5nCdTLL+3tddGaY5ZMMXT7NlQBPN9DxG9cQw8Dz8UpmAH8X0fpRRjnsW+7jRH+rMYCtY1tbD66U8SG+oGrckGqnjxWJaxdOX3L7o+XCAAI66NjG/x7L7OsuALQLbo8dz+Pn7qhjqsCSnftOdye1uS7tEc2WL5b+6K+jghS+Gd6Vg/6XdpX/U+1t3xIMcGMjw3mCNW18QN68KsTAUxAgZZDRHDY01TFdsnrAFzlm0q2lIhfF+CABfrQve3i3iOQgghhBBCCCGEmF0BmNbWVvbt28eDDz5Ysfydd96hra3t2lZqDhpzVNnskZpYEF+ZfGN7BwD18SCZvDmjfOYX4vs+TYkQ+7tHK5ZHgxbBGQRfDMMoy59vaYf3L6/mZH2M3Z2jOJ5mWW2UlXURooZLLtp4tgKXVO+zwqZPW02EPV2joH0WJcMcdV1yZwbIVtTH8HyPx9Y2lBYun+H7ep5HLhiBM7MALree14IN2GND6LFRsAPoVA0FOyhPUC9gZ9e2mHh/0FrTlAiioGJ/iAYskkET8BkuMuW6F66v6RgtsCZlXrFrzFCKYHYMRs6kD6qqphgtD+o3hOHelfX8+Ej/+OC5qRSbFiVZlrTR2qXKdPnIpiYO9mU50p/BNhXrmxMsTgSwLpBKyPN9cqFz672c7fujXmmtqYlBnVcO9XGgKsQTa1oJaIds0WQsP3L+W55pG0QDJiAD6rNBb9Yh71R+eGEwU2Aor6kLlm9PWh4f2dTMgb4Mx/qzBCyDDU0JFlXZ+OkMj8czKNehGI6TScX5/23vZCjrYChYhsVAtsiegRBPrKkjhIPnedzUEiNdcMqCiuGAyYOr66myvEudHLqg1UVtDFU50BKyTapDpfubEEIIIYQQQggxE7MqAPPYY4/x13/91yxevJjbb78dKA3wd3d382//9m8cPHiQz372s9e5lrOf6+uy9BlNVRG+saNz/LXjaRQKX2teO9xP643T5zOfjtaaJckgkYA5/lSvAgKWgedrblqcImz4U8Yfgq6D0d+N19uFCkcwmxaRjyfxtcbWDssTBitTNfgalPbxfeeKDij5nsfmliqODmTIFT0iAYv2VJi8p4kHbe5aWk3K1gRwUUphmua5NXCus4D2sYYH0OkxCAbRqVoKgdAlDWaH3CLeW6+SPnZofJaPEY0Tuech8nXNMntnHtCOQ3hsGD08CIYBqRoKkTh+hevFMAyC6RF012n8zBhmTT26vmn8+koFYENLFTs7yoMFCrhzWQ1hw8P3S/ea6a7GXNFFqfJFwk3TRCl1Zt2EmV/LltZYB3eR3fYTtFMKkijbJrzlDvzq1LkdfY+1NRaLki0MZl08rakOW1TZGs7MFtBaE1UOWxqD3NgULg3GXsY6DoZh8u6JkUkzagC6R/IcHy6wKmlSEzJYXB2hezRfmu0ywdK6GKkAMu57GSyr9FeeK5EaKu9cIB2lN/natT2X+uFu6rXDnYsSEE/gmCaBruNkXnuB4ul+8q5HpKGB7lXvw/RL6w21xANEChn8bJr+IYOTNUHWNURwtCagHR5cluSmRUmGcy4B06AmYhI1vFlx31ZKzbkgfpWtuXFxNVtPlK8Do4Db22uImt5ceKZCCCGEEEIIIcQsMasCMHfffTf9/f3867/+K//v//0/AD7/+c+jtcYwDD7+8Y9zyy23XOdazn5hC2JBi3TBRQFZx8edEJCJBs49cZ53PIZyHuHwpZ8varh8YEMTLx7qJxKwiAZthnIOTVVhWpNh/CkWjQ7nsxRefAZ3oO/cRsMkcse9OO2r8SgNhHpnBsuu1hBOleXy4Y3N7OoaoyvjY2uTVfVx1jZGiVDEUAah9CjeicN4fT2YVUmC7avIV1VXHLy+FsKFHMXXfkS+q2N8mxGNE7nvUXLV9Rc14GUaBv7OdygcPVC23c+MkXn+GSIf+Bi5cOyK1V1ce7b2yL7+POl3fgJnUg4q2yZ80504y9cxMZxoGAbBU0fJvvos2j0XcDDjScIPPkk2mkD5LrcvTtCYCPHe6RFyRZfqWJAtrUmawowv+B4LKIKWQcGtPFpZHw+NDxJb2icw2Idz5AA6nyW4qB3Vsph8MDKj69nu7SDz1qtl27TjkH3zVaKNzZCoObfd94kpn9j4RBW3YmCjVDefyw23Zn3FsYHMlOV7usZYU1vPWN6jvS5BMBggaBoMZfJ0j+RY2RDnjiVV4MtC3pci6DsYvV24Rw6itSa8dCV+QzMF077k96yOTH2saShiwfLZSpF8hvzLPyTf131uv3gV8bseZPS15yGbZnEqTNdoHt2wiH2HThENJ6iqrSPU34mTObdw0c5tBdavTWEvasNRBsp3qbagOg6lC3nqhx6ulaKy6ct6DGaLxAIWjTH7TOBiDkQufI+bmiPURgO8d3qYTMElGbHZsihFS1SN39+EEEIIIYQQQoiZmFUBGIAPfehD3H333bz55pt0d3ejtaahoYFbb72VhoaG6129OSFs+Ny0JMXLB/tQqjxwYZvGmTQ2E1IKXeb5tNbU2B5PrGvg+/sH2HdyCNs06BxKs+OE4r5V9axMWmVrzVhK4b77RnnwBcD3yL7+ErGaBrKJFFfKdE/haq1JGA53L44STlQzMjJMQPl4noNSilBfJ5nnv4sunltTh93vEb3rQQpLVlzzIIylFM5br+BMCL5AKWCSfeEZwk9+jFxw5hE1OzNG9uDeimW6WEB3nkItXzvnnmIWJUopzBNHKOzaNh58gTPBiZ+8QixVS7bm3L01mB6dFHwB8MaGKbzxIvaDH8RBYfoOK6oMlqVqcXwIGqV1LibeUGKmz8bWJG8fL3+SHKAuFqT+zLpKFhpj11bSO94ZLy+eOIIRSxB5+Cmykfi0bbSVorh72xSlmsKud7He9xDONb6Ez9131LT3Wa0UBweLPLevq5T2SCkcH1Y3JviZm+tImB7ak+DLpQi6Du6Pn8U5dXx8W/HYQeymRYTueZi8HZz64GnUhAxaU2FOD01Osbe2KXFmRlXpta19Cq89hzsh+ALgp0fJPPOvBFasJX/kALbyWZwMkY0HiQ37OH6eUG6Y7ITgC5R+swpH9hMJhXDqmy+p/lfTmLZ5ZlcPQ9lzv5kh2+TRtY20RIw5EYQxfJdlCUX7ulocDQFFaYbc7K+6EEIIIYQQQohZxrjeFTirUCjw27/92zz77LPU1tbyxBNP8Mu//Mt86lOf4gMf+IAEXy6C7/usrglwz4o6QrZFNGBiGYpY0KKtOoI1YQQhaBmkQjNYpOUCDMNg2+kRuofShE1K59CldGgv7O9hsKjK9rezYxROHKn8ZtrHO3UUw7j8y9NVNt0Fkz2DLsczkMWe8n193ycRtrG0O55iLOAWyb32fHnwpbQz2TdeLK03cY3ZY8MUTx2rWObnstDXdXFvWCygneKUxd7QwBX5LsT1YfteKfhSkaa4bwemWfp+lVLono5JwZeznO5O7LFzace01ijPJaDdUvDlPL7vs7kxwm3tNYTs0n3GVIpldTEeX1ePfSalV2Cwj/yE4Mv48elRitt+gqXUpLKJlFvEH6u8dgqAPzaCMUWbrjSlFBltc3QM9gy69BZNAmYptdhU2mpivHqo99yaE1pjK82RnhFOD2XLAmdi5pRSqJNHyoIvZzldp9DHDl7yvc30HR5aVcvqxjiWUbo+g5bBjYtT3LYoUdYfrNEhnO7Oiu/j9XVT6hlnrnHtkyiOcdst62hfu4KaumrW37iexYsax49ZVRdBDfbiHNiFaV7+7/eVpE2L5w/0lwVfoDTb9od7u0n7s6u+09Fao/zS/e1sekIhhBBCCCGEEOJizZoZMMFgkN7eXtQFBtrEzBi+x4Zam2XVTRR8sMxWtp8cHF/fA0rDPbe11xC7AvnM057Bvq7RimW+hoN9GW5vCZ978tV1ocKA7fgxmfRlXwtZbH6wt4+e0fz4trBt8vDaBlpn+BSuOTKEN8XArnYc6O+FRTNPz6WUIuA5mCNDpQG6aJxiNIF3MV9AIc90X5g/OnJxefcDQZRtj6+bcT4zWY07B55YFpUZThEvkwZzisDjyBCmX0qzZRgGpmkSXbkW7XlgWRT7eyfMVNPTBusqMbXLTY1B1tQ1k3V9bFNRZYE+k07LNE3cowenPL548ijR7BjuNGnwtB3AiCXwxirfg4x4FY4VmLbfXAnKMDg25vP8/o6yNVwWVUe4e3k9JwezkxZur4mFMBXkpljQffvpEVZW12MiA8AXy9I+xf27piwvHtiNvWItRXVpQYGQdnj/0gS3LEpS8HzClkHcKs2enEjn80w111QFQ6XAuWmC56Kq69iXXMorB3s5NOri5POgYV1LitVrltLd0c1yK4+fzaAzac7/lVRKEXAKmKNDaN+HWJJCJHrNZp0MFaB7ZPKsIChd470Zh7ZoxWIhhBBCCCGEEGJemjUBGIBNmzaxY8cOHnzwwetdlXnB931C+IQMuK05TGO0gfdOD5MuuFSFbW5anKIlcmXymbs+U67zADCSczCMc4NAOhTGiETxs5XXRTDrmy5r0F+ZFi8fHCwLvkBpAOgHe7r52I0tRNWF319fYLFm7RRmHOwwDIPQQA+5157HGymlZFK2TXDtRsz1N1E0ygcBDdMk7Rq4viZoKcKqlD/fSCSxmxfhjY7gpycPOBvJ1EWlC3OicYLL15Lft2NSmQoEUC2LJf3YHObbAcxYFeQqz9YyUzX4ykChCQ72UnjnNQrbS7NRlB0guOFGzPbl+OkxCIZRscTF18H3CSuf8JllMybEgUv9p5CvfCCA510wcOL4mvD6G3G6TlcsD67fQuZSr2HTIu0qtIaoVQooTdUfhh2DZ/d2la25BXBqMMv200N8bEsLW0+OcGIwi6kUqxpjrG2M8/3dPVOePud4OBrmzryB2UP53pSzuQC066A8D6xL/3R9zyNmeMQMAA+vws+pCocp5QMtvy601qhoHCMWh87StTvQdgMvbj8FhsHSRcvpzUQYzRU5OFxkeWMdH1lTxH7nZQDMptby9ZuUIth1ktxPXh7/bVDBEOFNt+CuXI87KVxTmWEYGEqBUuOzQWeq4PrTpttL511UzJbfFCGEEEIIIYQQC8asCsB8+MMf5s///M/5y7/8Sx588EHq6+sJBAKT9ovFZEHwizUpn7lBaQbKFRoDCZoQC1qkC5UDFk1VobIncIvBMKEbbib75suT6xqNoZoXXdYAzXARTk6x6HXB9ekaK7KiyrjwOeIJlGVPOYhnXMSC98HMKJnnvlM22Kwdh/yOrYQDIYy1m8c/o4IK8PaJEQ50j1H0fKIBiweWJlnh9OPs24Hq6SSQSGKu2UDu2GH8fOmJYyMaR9c2Vjz/VDzf//+z959Blh33Yf/97T7h5jA572zOEYucCAIgSICASIgUReqvx4+t54Wq9MJ22S9ckiVbZVuWVZarJNuSpb9VLstWMCWamQRIEInIwCJsznknp5vDCd3Pizs7O7MzsxnA7G5/qlDYOefec/vce/rcmf51/37Y2+7GrVXwTh7j/EUh4wniD3+eWiL9sa8cMD4+vrSIbtuJXqCvISTOhm1UlCJWr1B54fuIcgkRiaLrNbTvoUtFIstWUj93GiEl6sRhYv2rqMVTN2QQNQxDIr3L4cThBfdb2RZUdPH0Xef5nX3E736I6gdvz/RXYTvEdt6Ls2INTM6vQ3MpQgjGfYs3jkwwMFVFA22pCA+sbKEnLhqrC2aRUnJqrDYv+HLekZECd/WmeWR5klpfCinAFQohAlpTLiPFhYNQTXGXiMTUnrgGoe1id/cR5qcW3O909hC40Y/9/hakm3F7+vHOnZq3T7d2YK/ZhDx7CuFGOJwPUGh0ey9jdU09UMSlxrIkB4cLPNjv4IQBwnWxV63HmxUgieYnKb304zmrS3W9RuWdn5OIJwn7Vl6yzwohiNbKqDMnCE4eRTgu0fWbCVNX/jtXwpFYUhAu0g+a4y5am4vZMAzDMAzDMAzDuH0sqQDMP//n/xyAc+fO8frrry/6uG9+85ufVJNuKVprhA5wAW5wSYGoCLlzWROvHB2bv8+xWNEcQ6kLQQylFOHq9cTCgNre99G1KiBwOruJ3PdZqpH4vNnCV6MeaBYZ/wGgUPMR2eicwSghBGG5RMSvEzgRAq3xEimim3dQ/ejdecdw+1fhZ5qvqD1CCNS504vO9K/v/5DoqvXUnAihdPjp4XHOTlZm9rdEQH/4JicP76YjYSHDAP/AR+i975N4/BnKxw5iJTPEPvN5qpHYVb93NcfFefAJklvvRJcKYLvophaqbnTeQLNxc9FaE/T0k9h5H9W3fz6Tak5EosTveZh6czsC0IPnGqmQpMTu6SccHcTu7EUoReFv/l/cVesIk2nq772O3Ps+8S88SyXVdEPaR1cvVqZpgYFyQfSOe6nZzqLXtC0ElldDS4tw0w7ifStgeoUZmWa8ZAYZufpC64XQ5nt7BuekDBsr1vnBniG+vL2bjovmBgghyFUXT8/mhxov1CgRNu7Bmpl71ObONIeGi/MGrQVw57IswtSfuCahUkTWb8E7fhjt1efsE46Ds2kHlU/g/uYD0fsfRb/xM/yBs5wPctvNbUQf+TzlVBPRX/gGdq1C8bSHXNHEqWJIyfMBgQhAl8rkphSDa1ezYcVaIhu2EsTi2EIQaN1I5Xd0/6KpPeu738Pp6ccTi9e8iVWKVJ7/zpyVld65U9iDZ3HvuI/6FaRqy7iwtiO1YErS5oRLW9yauwTOMAzDMAzDMAzDMG5xSyoA85WvfMXUgLlJKaVY1xKhFrTwwdmpmfoHLYkIj65tJb1AnRlfWFib7iC2ci2iUgbbJkhlqWiuK/gCEHMEthSLzkZvSbhzVuREAh9x6gjFk0eoFfLYre3Et+yk1tKB3rSDeDRObe/7qHIREYkSWbcJuekOald4vVqWhRobWnS/qpQRXh2cCBNVNSf4ArDJrpD74F0soCmWwJEWsqsPy6sTDp4h8/TX8BIpqta1p3bxAT/dDOlZQSWTJuaWEAiL2L2P4HX0ovM5kAKdaaYWjaOnB2/DiQtpsALbRnT3E1mzntIPvomIxdGROOH04K2qVam/9wbOY0/j34BLpOZGiT/xJfwP36Z+6hgEAXZTK5E77sXr7l/wmhZCEMtP4O15n/rIAMJ2cNduRK/eSK2r/8LjruEatiyLA0OlefVaAEKt2XUmx9PrmuYUWldK0ZGOsn+RWlhRxyJqL3y/aI0ontrUyatHxynUGgGyuGtx74oW+pISbkCayNtVLd1M4vPPUn//zekUdboR6N/5ANVMyyd2j6tGYjiPPk0yP4mulBHRGEGmmYq0QClqbhQZjdNWq7GvOEVpVsBIOy7CdmiJ2wzUBf1b7iV8/TlUrYLd3kV8650ELR2EY8OLvn5YzOF6dYjEFtxvSYm/+70F01r6p44ie5ZB57LLnqcOAx7ozyCAwyONoKIAurMxHlvbiqMXTwlnGLeKAIkXLnxvcS2BbZY0GoZhGIZhGMZtZUkFYL72ta992k245QjLJleHiq+IOJKmCIhFZsher/PFtte39VDwQmwhaIoIbELUIoGQMAwJ3Ri404NCN2gsLONoNnSl2TuQn7cvFXXoTDg0Qg7gqpDwzZfwTh8jHo+jKhW8Myfxzp0m8djT1LqWIdZtIbJ8DdL30LaNF41fVVFjpRR2OrvofuG6YNkIIRgtzZ2pnYzYWENHQWtCGvUuHKuRkUi5EYJCAUtI6tI2ARNjUUJKqvEUenYx++nrRSmFncrMebxMZ/AHzqClBVKi5dzggT94lkS5hB+/MSkhK9EE1gOfI3HHfRAqwmiMmmUvGlCMTY5Qfv67c9IDVne9iX32JJFHn8ZzIgRYTHmQGy5ghTZpW11RzSuF4MzUwoXEAUYKNaohRGdt01qzLBMh5lhUFwjcbO/NkrDUgjVCtFIsSwi+tr2TXF2htSYTsYjL8IbU6LqdKaWoZFtwHnuGRLWRljKIJ25IoP9q+Qj8TAtkWma2CWmT96HsKVxbsLotxYtH56fL00Jw14pWTh8+wrqeCO2TjdWm3qljeGdPkXrml9GpDIwtXE9IRuNo21m0bU61TPX0scXbfng/du9KgsvURQNwtc9nV6TZ2Zuh7IVEbEnWFQhlgi/G7cELNd/bP7rgvi9tar+eslOGYRiGYRiGYdyEllQAxrix6sLl1WOTnBgroXQjnU1XNsbja1tJio9nIEQpRVwo4ucz/ugbFlO5OlrzYFccXatyZDhPaLmElkV7Ksrn1rYSFcHM2Js1OUZtoYEnpai9+zru079EXdrUHRccd2bf1VBKYfevgt27FpzNHlm9AS+eRCtF5KK/zKUQM2mjAOYnkNFmhrxxXbTWWL3L4f23LqQwknImuGGl0ijHnTtgrRVohYPGKeTQXg1iCfxkhuAaB7ZDpRrpBy80bMHHOQLq77+5YG2mYGSI6PgwE62reOHQKBPlOvF4HK9WZXN3hrt7U9iXmYUvBETsxVM1uZbEEmLezS0hA57Z0snPDo8xWW6kI7OlYHNPlq0dccLwEgXhtcbFp30mtZkypZduIB/wY4nGD0skTu0JhzdO5TkyXCScvtZXtyd5ZmsPf/veaSamr6GoLblneTOyVqE4MYnd1zX3QGFA9a2XSe68n+Dwfgh9sGy0487Ms3c3bsN33EW/u4TW6IWig9O073M165N1GJCSkIoCKFPDyDAMwzAMwzAMw7htLakAzLe+9a0retxXv/rVj7klNz9h2bx6bJJjo6WZbRoYzFX58YFRnt3cfsumArGEwD11lOp7r/FQKsu2rtWUbUW8s5NsSxaUPzOuK6UkXKAw8nlhfhJZKkL6+mtd1NJNJB7+HJU3XpwTUHF6+7G23oU3PTDWlXJwLIE/nb6iVPcRnX2w+32itkXEEsweQbRSGVQ8dd3tM25vtWSGxCOfp/LaC2jPIywWiCxbjn/iCKK1E3VRMMTKtmBbFt4L36c0PABosCwiK9cR3fkANcdd+IVuALtapjy8eEq/yZrmB/uHKNcuzNYPlOajczlcW3J3V/SSK9h0GLK1O825qcqC+zd2pYmIcF6dKa01ba7iq1vbmappglCTjEgytp5TA8swpGXx1qnCvFopx0ZLtKRiPLSqFdtqFLN3pGA4X+HM8TO0NqfI5udf+3rwHHp9HrdvOZU3X4IwRCZTWO092Os3w6r1l7zmg2gcp71rOk3bfM6KNdQvEaAxjFvR/FRigrOjU9QDYVKJGYZhGIZhGIZxxZZUAObv//7vr+hxJgBzeVMenBgrLbhvvFRnvBrSFV1w900vMjpI6ec/acyer5RJjQyQApCS+FNfodLUPvcJcvGZ7kBjOvwNoDTUl60m3tqBHh9B1+tYLa0E2Vaqswojp2zFo+vaeeHgCGq6UPfZSDM9y/ppr4wj5vzBL4juvJ+6G7nqVTmGMZvSmlrPCuJf+hUYH0HVajhtHQSFPN7E2NwHC0li531Ufv5T/JHBC9vDkPrRA0TQ2Pc/tmgNpusnGkv6Fji8cF3O+g4Vb+HB4j0DeTZ1JIhdYuBMa01fymZDZ5qDw3MHyLszUTa1xxcNqGitsXVAm1nJYlxC3hccHl64XtDhwRybelt469jwTJBPCEE86vBYbxJrz0dzLn0JqJFz+MNDeLUaiSe/AuUiOgiwe5ahNmyf8x2zEB+I77gXf/S7F1bBnT9+KoPuW3HN9cUM42Y1P5WYIJVKUiyW+NKmNpNKzDAMwzAMwzCMK7KkAjDf/OY3521TSjE+Ps7zzz/PwYMH+a3f+q1PoWU3n7Kn5s3Oni1fC+iOWTftgIqUkmA6GZeNmpnZawuo7/tg4dRFSuHt/wj74S8QTD9eKYXdtxx2v7fg69gtbYTJ9A1rt9KaaiwJfUmEEAu+/1opVqctWnb2cny8Qr4W0JSOsOpLz2Id+gjv6H6UV8fOthDZcQ9eZ99V1aMxjMVoralGE9C7EsuyqCGIfe7LWPs/oH7sIMr3cFracbffjbLducGXWerHj5DYspMgkVlw//XyYwnc7mV4C6xek9E44yKCXiRAUvNDaoEidplvP0sHPLw8zYbOJEdHywRKs6o1QVfSumVXDxqfnIqv5gYohUAhEGhyVZ+IVHx9Zx/Hx8vkawGd6QirnAzuj/96zgpKAOnVoLUdv5gnzE1QyU00aopJgR4eINmzDDKtl21TrbWT5Beepf7hOwSjQ2BZuCvWkLzvM4yFmBpjhmEYhmEYhmEYhnENllQAZiFSStrb2/kH/+Af8J//83/mf/yP/8E/+Sf/5NNu1pIXtS+9aiPh3rzBl4p2ODxc4fBoEYA17Uk2tCdIiADLr1Ofmlj0ueHEGE7gg7wwbdHPthJZt5n64X1zHitsh+g9D1OV1scy8HSp919rRdZS3NUVRQiBUqpRI2DHvUQ2bEWGIWEkQk0uXqTcMK5VHYfDo1UODhdRSrOp9062btxJQvsEkRg1IXGP7lv8ACqEShk+pgBMoDXxnffhjw2j67U5++z2LjLZFEzML2QOjZosjiWBy6dTsnRAZwR6licBCMMQ9OWLkBvG5UQtiRSN0ih1JZgs+ZS8ACkEzQkXy7LIWv6c7wAnBNXVi3fqoppl0iKy+Q7KRw9c2BYG6OlLXJdLVxSAUVpTaW7HeewZYvUKCEkQS2C3d8DQ4in/DMO4clJKKuHCk2ZMWjPDMAzDMAzDuDUt+QDMbBs2bOCv//qvP+1m3BSaIoLOTJThfG3evkTEpj1u00g6cnOpaIfv7h0hV/Vmtr1zcpJDw0We3dKJbStkLI4qFxd8vown0bbN7OVBvpC4Ox8k0bMMeeIIVm4Su6MbZ/1WqpnmTzXAcfHKljAMCZ0IONMbTPDFuMHqOPzgwBijxQv3jtePj/OBa/GLW7tJ44PWyHjiEkcRCPfjzXFYzbSQeOqrBEcPEAycBsvB3bAF3buCXhHDllMLpkBb054ibSvUVZSzCE3tC+MGy7jQ1xzn8FiVk5MV1KxrNVfxKHshgYhgz1rJ5UmLyP2PEl+2Ev/gnsaKtJ5lRJetoPDKT2CR6/Rq+6IP+JF447lmdaVh3FB+qPnhgdEF931pU7tJa2YYhmEYhmEYt6CbKgBz/PhxxDXU4/i7v/s7vvWtb83Z1t3dzR/90R/doJYtPVIFfG5tGz/cP8JU5UKwIuHaPLWxg6gIbsjYvRACy2qspvm4BymllBwarswJvpyXr/rsHylxX28Cd9MOglefX/AY7qbtVBcYlPUsC9m3io4dd+OPjhJKi4pSJsBh3FaEEJyaqs8JvpxX8ULeP5fnsRUplAqhpQMZjaFq1XmPdTo6CTJNH2tbtdZUkhnkzgewd9yLFoI6jbR+Wan4wsZOXjg0Qj24MIDc2xTjvuUZVLg0gs+f5P3TWGJUwCOr2zg2cXZO8CUZsXlyYycHB3P0ZjrojNoEwYVVV3XLQSxfi71iLVYYElg2db+OcFyoVua9jJXOEja1fCKnZBiflgCJFy7++9qlVpZc6rmaG1MD0DAMwzAMwzCM29uSCsC8+uqrC24vl8scPHiQd999l0cfffSajt3X18fv/M7vzPwsL1d4/RaQkj5f2drBeCUkV/VJRmzaEzYxEVz3qg4hBGVtc3qyzsmJAjHXYmNHirYYyKuZWn4VAiRHRhde2QJwdLTMjq4E8b7lRDdtp7Z/NzNVuoUkuuUOgq6+RZ+vtUbYDr6QaDPr17gNScviwHBu0f0nJ8pU+jNECanHEsQ/+yTll59DzwrCWJlmIg9+jsonNHCllMJDTHd1PbOtPyn4+h09jJZ8hOMSlyEtEYG1BOq3nL9/npqscWr6/rmhI0l7VCJNirPbh1ZsbE+ytTtDoeYTcywitsASkIpH+dHBMfoyLuvaknTGJdb0taG1xteAkI3aZrZL7JEnqbz4wzmrP2UiReyRJ6narplMYNzSvFDzvf0LryqBS68sudRzn97YcSOaZxiGYRiGYRjGbW5JBWD+9E//dNF9qVSKL33pS3z1q1+9pmNLKclms9fYspuXq326Y9ATP18rxL/mcRgpJVVlUagrlLR4fv8Q5fqFwcyDQwV2Lmviru7ExzaIeCVt94SFveN+kqs3Eo4OIoRAtnfhpZsIzBiUcRvS0ub0ZJmpmiTuSlKWQl9noFQpRa29h/gz34DxYVSlhMw2oZvbqdjuDWr5tdNakxA+K9OCrq5WhoaGlky9pHxg8929Q5TqF+6TB4cK3NnfzF3dcYQyQZibgbBsCr6g4odEbUnWBR1e3Wd3bLQAgG1JQqXY1NPES0fHGCnWycQcKjWXQ0MFNnameXBFGnuBa0NrTTXbQvSZX0aMj6CKeWQqg27toOpGl8x1bxiGYRiGYRiGYRi3oyUVgPmv//W/ztsmhCCRSBCLxa7r2MPDw/z6r/86juOwdu1afuVXfoXW1oWL0vq+j+9fCCwIIWZe/3wKtGtJhfZpu5Y2z5yvtDgyFfDGiVEyMYdzBY/j42W60lGSjpiJjLx/ZoqVrQna3Rv//jhCs6Y9ybunFi6uvbo9SdSCMBSEQlDNNCOyjdQr5wegLvUW3Myf7bW4Vc73Svrr7H/f7Od7tQrK5qWDE0zVJ6hUKzhSsKk7y929SZyLAqVaKTZ0phjKz08rBrC8JUHC0ijVeA+11tRicehbiRDiQj/7eE/pqiy1z11YFm8cn5wTfDlv1+lJVrTEb9j9c6mdO1x5f53981Jq/3k14fDGiRxHR4uESiMFrGhN8vDKZuKicX6Xa3/Cgp6mOOemKvihoiXhcmy8wkixDkAm5qCn05MdGC6wuj1BX3zx96LuRqG7f05fvNTrX4ml/BlcKXMOhmEYhmEYhmEYxqdpSQVg2traPpbjrlmzht/4jd+gu7ubqakpvvWtb/Gv/tW/4j/9p/+0YGDnO9/5zpyaMStWrOAP/uAP5rSvs7PzY2nrUjWhorxxehBtubRnk/z85AAKyWDRY2VLgnTMmXns2WLIts1d1/xapXrAWKlOqDTZmENrMjKz7+5YjTOFgEJt7uBlwrW4Z1UH7ZnrC9TB7ffZ3uzneyX9dbab/XyvxlTF49u7zpBvjOcSjzUKax+ZqBOPRfnCxk7kRQN6dqrO0SmPidLcWktRR/Lwum46muM3pG3Fms9YqY7WkI05tMzq5x+HpfK5D+arjFUniccXfh/PlUK2bbr2++dClsq5w9X3V1ha7QeoByHf3T3ImUJAJHrhO2eorPj5mRJf29FLInLh16tLtf9xGeM7uwfwQ01XS4LnDwxj2zYJ16YpEcWxJFUvxFeKPSNVtt/Vj+t88lW6l9pncC3MORiGYRiGYRiGYRifhiUVgKlWq5TL5TkrUyYnJ3nhhRfwfZ97772X1atXX/Vxd+zYMfPv/v7+mYDMW2+9tWBNmWeffZann3565ufzMw7HxsYIw5DOzk6Gh4dvi7QeQgiaWtt4/cgg5UqjwK/vR6jPmsE8WqjiEMzM1M0VbUZHR6+6qLSUkuEqvHx0nPFSY8Q45lrcs7yZja0RxHTKpC+szrB/pMzR0RIazeq2FJs7E4hqnqFK7rrO9Xb7bG+W8+3qWnxA+lL9dXbx6pvpfG+U02UYmiiAaARfKtXKTFmk947XWJO1Scr5KzE+tzLNwdEKh4YLhEqzojXB1u4UrldgaCh/XW0SQjBQEbx6bIzJciPIk3Bt7lvZwtpmZ6af3yhL7XMvBDal8vxi6eflC9d2/1zIp3XuN6K/nt+3lD6786Z8m/1nx1ALNOl4pcKxrjjtbnhF7U8KwVPrmtl9Lo+FIgxD2hI2maiN53kMlH0myx5Ka8Ig4Ad7zrClM0VKfjK1jJbqZ3A1zDks7lJ99VYipaQSLlzbTy+pNZuGYRiGYRiGYdyKllQA5s///M8ZGxvj937v9wCoVCr8y3/5L5mcnEQIwXPPPcdv/dZvsWnTput6nUQiQXd3N8PDwwvudxwHx3EW3Hf+D1+t9U37h/zVqtQDJqYDIgBVL6AjFZlJk1L1Q5R2Zv6EXd4cIwzDq35/cr7k+3sHqAcX/kiueiGvHBkjYneyOt1IqxIXPvf2xNjR1ZhB7gqFUj5q4b+tr9qt+Nm6KsTOjaMKeUQ0jm5pxYs03r+b/XyvpL9e4TK47wABAABJREFUvO1mPt8rJaVkrFhr/HD+dGedth8qyp4iEZn/XkTx2NnhsrW9HQ1EpCYMr7yPWULglgswOYZWCtnUipfOEmiYCix+uK8x4/+8shfw4qERYlu6WJZY+HO7Xkvlc4/bkI275Cregvv7m+PXdP+8lKVy7nD1/fX89qXSfoCiFywYfDmvUPNpcy4M6l6q/VprmizFoytSeNJmrNjEYK4MaEbKwcxkBIAVLQkODxc5NVHmK5s7cLkQhJFS4tbKiIlxdL2KzGQJsi144saslllqn8G1MOdw+/JDzQ8PjC647+mNHZ9wawzDMAzDMAzDuN0sqQDM4cOHefzxx2d+fu2115iamuLf/tt/S19fH//m3/wbvv3tb193AKZWqzE8PMxDDz10vU2+Lbi2RdSxqXiNGdmDuQr3rWjhe3sG0YAtxUzwpTnh0pNy0frqZudKKTk2WpkTfJnt3VOT9G9rx56uWRGG4czFu9hAmCPArlbQUuBHE4Q3KkJzk4nVK9RfeZ7a6NDMNhlPEP/sU2DSmdyytNYkI4vf4qWAiL34zF+lFBaNPnM1izFsAfbhPZR3vQnnC5ILSXTTNqI77uPASGlO8GWmvcB7p6fo3dyKuMpC5jcTh4D7VzTz3P5hLn4XmhMuPWkHrX1sIXCqZbSAIJYguNSIv/GJitjykvvjjo2rPCyvTjg1gWVZ81b3XEypEFuF3Nuf5Xu5CjUlZlaIATTFHZrjDkNTJSoejFQC+qaz2EkpiY6co/LK86jahfpNTlcPsYc+TzVy/ak5DcMwDMMwDMMwDMO4NksqAFMoFGhubp75edeuXaxfv561a9cC8JnPfIa///u/v+rj/q//9b+48847aW1tZWpqir/7u79DSsmDDz54w9p+K0tEbLb3ZnjpcGP2YM0PyZWrPLutm7dPTeFaAlcK1rSnuGtZhgiXCb5YNlN1qPqKmCNpijQGg8/mFi78DZCvetRDwSXGi2dIIYiOD1P/8C3KoyMIy8LtX0Vk211U46nbavaoIwX+W68QzAq+AKhKmcqLPyTZ2f0ptcz4uGmt6U67uJbEWyD1Sl9TnIwD3OC4pDs+TOmd15iz3EYrvJEhqlNlpBVlU08zVc/n7GQZf1bbJisetVBwKw8Xa61ZnpZ8cXMXb52aZLJUx7EkazqS3NWbISpCovkpvA/fpjJ4FgCnt5/49ruppptvq/vXUtUclTQnIkyW6/P2rWmOsnziJP6Hb1HLT0E2i+xbSXTDNmrO4nWOpJTUlIUQisc3dTNW8shVPXLVgLXtKbZ0pzk0ODXz+LFSnf5kFKUUkXKB8ks/Rntz2+MPDSDeex37oScIzHVjGIZhGIZhGIZhGJ+KJRWASSQS5HI5ADzP49ChQzz77LMz+6WUeN7CaVsuZXJykj/+4z+mWCySTqdZv349v/d7v0c6nb5RTb/lrW6OMNSZ5uBwAYCxYp1C1eer27voTkewUCQthQovHXyp4vLykQlOj5fRgAD6muM8vraNppjDuamFn9eWjhJzbSylLlsbITo+TOkn35mZtq/DgPrRAwTDA0Sf/MpNOxtYysasa3WJlTyWZTVSP1Wr4DhYQOHc6QUfq2pVgqGz0GqCMLeqtBXyxIYOfnpoZM725oTLZ1a3gFq8vwohEEJcVcobx7ZQA2dw2jsJpibQfuN+HazZwjuqmYMv72WsqZfBkk93JsrDq1o5MpybWfkWc6xGkPUGjxXrICBWLqDrNYhE8ZKZT3dFnFL0JwU9W9qphY0AdGL6/hkt5Ck/93/nDKZ7p47hD50j8cWvUklkPr12GwA4OuDz69v4wb5hSvULK1vaUhGekKNUX3oBLAunpRUZT1A5vA97bAT3kSfxrPm/dgkpOVnUvHp0aOZ4luPwyNoOWhM2x0YL7D07MadbJCM2WutGHx0ZnBd8Oc87c5xEKU+QaPy+I4TADQOsYh6tFSqZxnejl/xeMQzDMAzDMAzDMAzj2i2pAMzatWv56U9/Sk9PDx999BGe53HXXXfN7B8aGpqzQuZK/dN/+k9vYCtvT44O+MyKFFu70wzka0gBPZkoWUcjdGPg53K1s7Vl87ND45ydvFCAWgNnJis8d3CUz65tZ99gfs4gUypic1/So3PiIO5zryDSTUQ3biOMJ1EIAtuZM3DkAPUP314wZ1JYzKPPnkCs2XxTzSJ3wwBrcpRw8AxYNnbvCrxsM8FFhWMjykfveZfKwd1ozwMhSW3die3XCeyFay6oYgHR1nNTvR/GldNa058UfOOOHnKBxViuSGsiQkfCwlkkTaAQgmgpjx46iyrmkc3tiK4eapH4Ja+TaOAhz5zB2/c+eB6xFWtQtoOfm+Q90cqeE0NgWaRdySAwmK/x4wPDfH59BwemZ/Zv6c4QEeEl62tcrahXpfT8dygd2tu4L1g2kVXrcO6475IrEq6ULQWW76FshwBxxX1Ja42lfRLT3ViFYEmJf+CjBQfTdb1GcGgv8q6HzWD5p0xrTbMT8ss7uhgu+UxVfNJRh/WJEN79kOj2u9CVCv6RffhKEe3pRyRTiKlxaJ2f9nGiLnn+wADhrAtfVMu8/9EQX1jfzs7aBP2trbw3pfFDhWNJulIuWgdIKVGF3OKNDUPwPEg0+nZsdJDq268S5iYAkMkUsTsfwFu2igUyAxqGYRiGYRiGYRiGcZ2WVADmV3/1V/l3/+7f8Z/+038C4Omnn6avrw9ozPp/++232bZt26fZxNuaVCEtDrS2NQbztQ4uO1NdCIFlNYoAj1Th3Kzgy2xD+SpBqHhodRuvHx9DaYg6Fo+4edSLzxGJW/iuQzzbjPfCD9CVIiqVxVm1Hrl6w8yqFrtWoTw6vGh7/JNHsdZvu2w+/qtl242udKOLZ0cDD/+1n1KbvYrlw3eIbtmJs/Vu/OlVMZaU6D0fUNu968LjtCKsVQhGBrC6lhHK+XULZLbJBF9ucVprkjJgTX8bwxGvMXivFx7AF0IQHTxN5dXn0f6sAt/xBPHP/QLVTMuC10vUr+O9/CPC0WHE8DnCfA7v+GGc3n5qT36DvW+fahzfcXEcm460YLRQo1ALKHshriXpa46zoT2GusyqnPP3kyvpwy4a77WfoafGLgRlw4D6kf24vofz4BOXS5i4KEsIIhPDeHs/wJsaR0RjRDftIOxZjievrfC55dfxB88sut8/dxpnu49n3ZjC6sa101oTwac/AStTESITI4SvvI1/ZD8hGqenHxmJ4h/cQ3DsEFZzK6nu3kbAZFYAzbIs9p0tzgm+WOUC/tA5HKV5Z2+JR+QY8ZHXePTRp3k17/D4unbSVojWjXbIppZF2ylsB6JRAGKFSco/+wE6uHDVq1KR8qs/IfHEl6i293wM79TtS0o583mboKlhGIZhGIZhGMbta0kFYDo7O/mjP/ojzp07Rzwep729fWZfvV7n137t1+jv7/8UW2gAVzxg7wmHswWPY2NFLCnobU4RColcZPC3VPfZ3OrSl+3jXL5Gm/BJv/QTnLiFQBFftY7KSz9GFfMgJfby1VTzU1gnDhP7/LNU3ShaCIRloRcp4i0c95rPeyGRwEeODuIfPwRKEVm5Drp6qdnX/zpSSvSR/fgLpBCr7X2fRFcvfkcvAG6lSOXgnnmP8yYncFesJcxNQjw59/jJFE5XH9SuPq2fcXO6XN+NVktUfv7TOcEXaNQMqr32M5wnvzIvuCClRJ88QjDSqDNkZVsIC3nQGv/caWq+wgs1QivsdJZw6AxtbpR0tomykiDgKzt6SNsa6xLBlzoOZ/Mex8aLuJZkXXuSzrjE0osHYuzcBLWB0zjx+Lx93qljJLfdhZ9quuR7shApJe6Z45RefR7OD6wWCwSvPE904zbsnQ/MW6F2ZQe2YIEUVecJywLr0gXgjU+WEAJ38DSlF3+EXa+ii3n8Myfx9n5AZMtOrN5+1MmjhFPjeIf3IZevm1N2SSEYLV5Y8WQFHsHQAGiNFBB4Hk39bXjDp0gcept/8NRXceSFtIBaa0R7DzKeQFXK89oXWbMBL5FGAsHh/XOCLzO0xtv9Hs7neq45IGlcIKRk0pMcHS8zUfJoT0dY3ZIgawdmwoNhGIZhGIZhGMZtaMmN5Ni2zfLly+cEXwBisRh33XXXvO3G0lTF4bv7RvnJgRGOj5U4MlJkuFBlqFBHLTIwGXUk6JCM5bO5xWY5RdxKHoHCamolOHW0EXyBxqBnrbGaJsxNok8dw3aj+KlmIhu2LtouZ93m6179IqWkrB2Gy5rTZ0eYGBohGBvBO3OCyivP4b34A6L+wvn4r4bj16kf3rfofv/gHuzzM+Gr5UbasYsEY8NYy1fj9C5HzBo4t5taiT/+C1iXmDlt3IbGRxatJRFMjmEXptDSZjKwOVcRTPgWQgv8owdnHhdGothdvYjpVWHW+BBuMoGVTBMW86hiATUxinP6MC2FIVZmXZrt4JKBlCoO39s/yk8PjjBerJOv+rx2fIJXTxUIxeIBC10qLH6uWqNLxcu8IQtzA4/ye2+gdWMAfrbagT24+clrOm5g2bhrNy2631m3heAaV9cYHw839Km98xpCKzwnStFNUuldTdDVT/3QXpyuXlSpiAxDguFB7OrcIIlEk47OuoarlTkr1BKxCImgSlvcIjY5QtYrYlnWTE0wgFo01rifZ2fdz6UksmYDcsd9VJREY82kHVtIMDWBdQO+t253QghOFBR/9+EAu05PcXKizDsnJ/m7D89xriLmfG6GYRiGYRiGYRjG7WFJrYA5deoU586d48EHH5zZ9tFHH/Gd73wH3/d58MEHeeqppz7FFhpXQkrJ7oES46W5gzl1LyDqWJR9TeqikiTZmEtL1JoZeNJaz5mp62Sy1A9+NPdJ0zPP7bZuVKXM5PM/oDCVo2v5MiKb76R2/BBWrTwz49RduY6w4/pSrGhp89FYjXdPTRJOTRIMDxCLunxm7X2sPPMBemqcYHQY59hB5KY7rivtiAiCRQfDAVS1jHV+Nq3jghCwwOza6pEDpD73DHYig64UEW6UINNE1bLJXnPrjFuNEAJVq13yMX4Q8r3DU5wcbwQ/HUvQl3Z5fM0OYu+9CCpEAyqVwYolwKvTVBpn7dp72ffRIbQ/N0goy0WWW3Ua1ZsWJqXkw3NF6n7I51oUkXMHUKNDiEwTasU6JqsJ2qKLPNm9dI0XcZn98x4vLYaqIIYGmDw1giUFzXGXbNRCzqxr0ITDA4hs61XPdldKIVauxT51lOCiVIp2Rxdi+WqTymiJkcUCYTFHrqYYLVQJ8hVUtYItJR2dq4hVq8hUprFCRUjErM9PSkk5lKztzHJgpIxriXmrN7f3ZHCO78dq68TNNhG8/XO07+H09iOXraaWSKG1ppptwf3iV7Hyk2jPQyRSDLrN/Pz4JJPlKeKuw/ZlO1kRz2Ad3z//PCJRtAnuXbeysnjp8OCclHIAfqj52eFRvr6jiwimDxuGYRiGYRiGYdxOllQA5q/+6q9wXXcmADM6Osof/uEfkkqlaGpq4i//8i9xXZfHH3/8U26pcSlVZXF4eP7M8jOTJT67ppU3TkwipEBPD1Ckog5PbmzHJZhbUiaVQbjugis7AEQ0ht3WQRgGTH77b5lq62eo6HHq0HFWtCToe+ILVI4eJhGzcdduJGzvuebaDNAYoD5dDHn92DgSULnGLPdqzeOn+87yle3baX3/RUDjHdmPs27Ldb1eGIliN7XgjwwuuN/u7iOcnn0fJLM4Xb34g2fnt9t2UOkmqvEUpDIXtl9zy4xbkdb6kiuitO1yuCx5+egEQdgYQIw6FoHSPB/AL6xYPzOwq7UmtCyIxYmkM9zjFJnIxhgcu9CXI67D5zZ2kdr3Fjz8eYLzNVouUlWSMxMVPuPmKT33Q2rn7wdnTyMO7CH72BO4O3fg+fNX0OimVmQiuWDNGyudJcw2X/H7I4TgVFHx3P4hPpcOCJQiUDBUqFLxHHrSEcT5gVVx7b2r5kSJPvYM7tBZgqMHALDXbER39d2Q1IbGjVcOYDBfBd8Dy0bYDqFWDOZKNLX24CxbSTA2TKS5hSDaSIenpcWBSZ93To6Sijr0tyR45/Qky9xGPTMBbFrexpraMDKVxlIBpef+L/byNYSWjT90DrHnfRKf/zKV6dpMdWlDUztSSg7nQn724cDMd2rFC3m5UmPIaebBnuWIgVNzzsHdsBXfcS+k1DOuyXg1pB4s/B6W6wGT1ZCuxQLGhmEYhmEYhmEYxi1pSeVCOH36NOvXr5/5+dVXX0VKyR/8wR/w7//9v+fee+/lhRde+BRbaFwJpSFYYBDHDzUHB3N8dk0rv7Clm0fWtvHMli5+eXsnzU6jeL0QAsu2kbaDn8wQ3Xpn47n5HO6KNTPHkuksyo1gt3Qw8eqLyHSW0bJPoBRKa46Pl9j3+jtM3Pckp+78IvXuay+MPXNe0mLXmanpn/ScgSqlNHvHa1itbY29YYBQCw8oXykfQWT73QsO5grXxV61gXB60NoHIvd9Fis9t56FsB3iDz9BPZG+rrYYt4egqRWno3vBfWrVRr5zxp8JvgDU/JATExVGiTDV3DvvOSISxVm7Cff9V3gmWeSrO3r57IZunrpzFb9yZy8rJk6ginnEJVaKKA0r45r6Wy8RXhSM1UqRe+MV7POpCS9Sd6PEH/kCIjJ3xFPG4sQ+83m8qwhoeFi8fnwcpWHcShBJX+hT+ZpPLTx/DgKro+e6aj3UbJf6stXwxLPwxLPUl62mboIvS5JON1F0E9OBDgG2Pb0aERCSyUwngeOifI/ItrvwaQTzThZCXjo8StkLGC5U8XyfpzZ0csfaHh7dsYqv7+jhofoZrOP7ibS0U33rVaxsC8q+sFpM12vU3/k5ztypC1SUxZvHJ7j4CtTxBIcKmqmOVXO2u8tXw8r1ZnXVDeCHl34PL14ZYxiGYRiGYRiGYdz6ltQKmEqlQiqVmvn5ww8/ZOvWraSnB7q2bt3KRx999Cm1zrhSMUvTkYlxZmJ+QWA/VDhC0xfX9MbsxiCl9tGAJxxO5zz2DeVQGta1J9i0/g4S8SS13e9hr1iLdfZUoxB1thkdS+CPDmO5LuVIknptbvng8TNnaS9N8dyY4Fe2d5IqTqALuUaR66ZWatH4VQ2S1kPIVxuvoYRAJlKEs1KEjZc8wngKGMXp6iVwo9c9m7je3kPikSep7XqDcHqQ2W7tIHrPw9TSTXOOX4mniH7xq4ixIcLxUWQiiejspZ5Io0zhX+MKeNIi9pkvIHe9Qf30MQhDhBshsn4bx3q3cOLN+auxQqUZD21qHZ24/avwB84A4PQsw91+D7VsC057J/rEAdqTZ4msv4cDU2V25WskIx3csf1uOoWFJTRuKQ/5ycYAdraFejxFzILlospILrdgm5M26LFh6Fs1b5/WmlprF63P/iocO0xYmEJmmxHt3VSvsv8XvQv9/2BJ8/g9D+O9+GP0dB8s1UPiCYvIhm14maZLHeqKaK2vu16V8fErWy7yjgcJfvw9amGIDkMSyQzSq5Fas45Dkx73rlhPessdhK1dAARYvHtq9MJBBORyJXKj4ziW5Jc3t9F04G1qw+caqcsmRrBb2tBNLfOuWX9kiEQpj5/MzmzL10PK3vxrRyEQLe2Mt2TovfcRVL2G3d1LkG2jbmqT3BDNMQcB84JfAJYU0/V+/AX2GoZhGIZhGIZhGLeqJRWAyWazDAwMADA1NcWJEyd45JFHZvbXarV5BY+NT56UkqqShFoQszVShXMHhVTA3cuyDExV5s32jLsWa9riKDV3AMITDs8fnuDcVGVm20ihyu6Ywy9u3US2dwUEHqn1W/COH8I7eQwrmUI4EYKufs4WF1ltEoaUqyG1s6cRr3xvJhWRiESJP/gY9Z4VVxyccKUgEbGp+SFokNkmwsIUTK9CycRcZL2CdhycTTuo3IDZxCFQ61uJ29WLLBdBSMJkmqq0ZgZ+Z6vZLnT1I3tWNOroaL1gXRjDWEw1EsN+8HMkdtzTSKkUiVGIN3Hq7OIF6wu1gGgiDo88SbzSCLz68QQV1VgpFt96F/7YKMPr7uMHuwfwg0afGbNszrgl7pYJ7q6cpvzmizP9SdgOsTsfIFi7ifa4zSgCfdGwpiMl6YiN9j2EEAsGVLTW2G2d1KdXqFxzv5j11VPxQt6It3HfU19FHfoIf3yUaGsTiTvvpNq9nDIOMQlCmYHWW50WFq+oVtY/9mUSh3fjDZ9Du1GcLTs4neqkVKnjxkLCaAw/GkMCJWXTmYmTjUcYypXxxsYIxkdBKwLg5bDE1zdvxt1xLwqNPrwPNT62SMBQz/SZ8+Qlfk/SCFQkgte9BQDPrHq5oZpcWNeZ5tBwYd6+LT1ZMo5CX9/iWMMwDMMwDMMwDOMms6QCMHfddRfPPfccnudx7NgxHMfh7rvvntl/+vRpOjo6PsUWGjUcdg+UODhcwAsUrakI9/Q305OQMCvlVkdU8wtbunn71CTD+SpSCpa3JLi3P0tKBnPGPoUQnM55c4Iv5+WrPh8MFHioL46ybIiA3H4fzqY7QQr02Cgju/YuWNAkmc1QiSRxiqdgvD6nDoSu1yi/8jzJZ75OJZW9onO3dMAdfVleODgCQGC7OL0rCCdG0OUSWzviWMMukS88SzXTcsMCH1pr6pYD6ebZGy/5HJNKxrgegdYE8QurEZVShEFIbzbGuVx13uO70hFaYhZBGMzUuGBW8LXW3I715Nd49c1jjeCLEMhkCqulg8Bx2LX/NMvbAzKzBpJ14FN5+1US2SacbJYVXVmGx4tU/QAQpKI2HakIjtDI5rbLrmaZCbxco4wDzYkIk+XGqreJSsCPqxG61j5E8wZF79ouXh4uceCjMfxA0ZaKcs/yJnriLBgsNW5+QggGCjVakhH+Yjes6L6HrhV3U6kFHBzIEY3k+Y0drUTQBH0rqWuLg2NVPhiYYN9QnkzM5e7eFNW8YmDW91PSllTe+TmRnfdR7eon1tuP3v/Rgm2QiRQ6kZqzLRuRpKMOhdr8AKAUjf6qlFld9bFQAQ8tz5CJOuwdzFHxQpIRmx29TWxsi6BD874bhmEYhmEYhmHcbpZUAObrX/86hUKB1157jXg8zm/8xm+QzWaBRnqyt99+m89//vOfbiNvY75w+PHBMYbztZltw/kaP9g7yJObulievDADXStFVxS+vKmFStCIjiQtjVbBvNiBsCz2DeUAyMYc0vEIWmvGijVqfsix0RJ39qSITBe4VkrhWY16LpHWdpatXcWJQ8cbK1POHxNY+cgjvDJeZ1VCkBg6zrwh0DAkOHkUuf2eKwpYaK1ZmXXY0dfE7nNTjVo3bgSnp58H+rOsaLZQG9dQaTz4St9Ww1jShGUTEYLubJSHnFZePjrGcOHCPaA1GeHrO/uwlbdg2h0ApTUTbopcuh073gRCoCybAJBa40+McTaVJRuJouu1Wc/U+Ad2Ix99mpYdO4m+/zaBavRvR4LWCnfFGvxM8yKvfOPYhDy8uoUf7RvCn15NozQMFDzWre/k+wfGmCheaPtQvsr391R5Zks3vfGFV+cYNzfLstg7OEmo4eE1bbxxfJwT04FHJ55k55o2etd0U/crBAheO5lvrIwQkIg4DBdqfH/XGI+taSVbqpDLlxDAhmaX4NQkYu8HOF39qJYO7I4ugpGheW2I3nEv3kXpLl0CHl7dynMHhuetQt3Z30yTo5n/hXjlhGUTarCFRoVmOcfFHO1zd3eUzR3d+BocATEZmqCXYRiGYRiGYRjGbWpJBWCi0Sj/+B//40X3/dmf/RmuawoRf1qGSsGc4Mt5SsObJybo2dqBfVFucxEGJKZXp+jFBnw02JZgc28zZ6aqfDhQwLEkm7pSxG3J6YnSvNRD59WlpP0LXyTR9QGnP/iIqVyZps422u+9n/dlG1R87k56qOOjCz5fTY0jpbziFSOWCrivN86GjgQTFR8pBK1xh7StqCszEGXcOkJpc64Y8tG5Cap+SGsqRmsywqOrW/AUlL2QhGuxrDlGdyxEh5dZlXV+zHdWEfHGDgWBT6h0I43Yxe0o5JCBT7huG4lYnPruXYTFAiIWI7p+C2LdFmri469fobWmJwZf2d7DvqEiQ/kaUUdyR18TXqjnBF9mTk3Dmycn+MrmdqQ26chuNRoIlGYwV6UtFeEr23qoTE8EiDsWE6Uqthsh8MpMeZLD59NSaWiNO9S8gFJR8eaxcb64totC4Rj3r++mbeAgoAlLRezAo267xD77FPa+D6kfPYD2POxsM5Ed9+D3Lp/3/aW1pj8l+er2HvYMFhgt1olHLHb0ZOlOijmrVa+GkhYDJcVHA5OU6wFtyQjbutO0RvQlvuBvT2EYEiEkMv37j1kEZxiGYRiGYRiGcftaUgGYi1UqFaLRKFJKpJTE4/FPu0m3LcuyODXZqAHRlnRZFwlwdUBJuBwsC6YqHqVAk7Wu4eBasbGrif/+5kmK9cYMUY3g1GSFVW1JnljbSsxi0bzpNdvFuet+Nm2/E88PmVA2x8qK1ckIPREF3/3RopN9rdZ2/KsdGVEhWQuyqfN5z3wz9mTcUrS0ePdcmQ/PTs1smyx7HJWSxzd0Uq15tMYtejNRsu78GhQLSbmShGvPLw4uJcJx6UnYqFojiCEcB9WzkmKmE5nJkrajCOUTrFiP27cK6Xto28Zzox97uj0pJW6tgvDrYLm0xRM8sjxJSAoJWAKeP5Zf9PljxTrlAFKmxvktR4Uh69pTDOaqjBXrjBXryPMD7hqWtyTIxGwmSjBanrtCzEKxrClG1UpTrtZpb82wfXsXmTP7YLyR5tJKpVF2Y9JJ1Ykidz5AbNMOhFKEboSaZaO1RkpJTdvYtTKuX8N1berRBC1OwGMrU4SksQAVBte88kVLi/cHKrx3enJm22TZ49hoiS9s6mRF6sonMhiGYRiGYRiGYRjG7WTJBWCOHz/O//k//4eDBw8SBAG//du/zebNmykUCvzZn/0ZX/ziF9m0adOn3czbjtYaxxI82GaRPfIepaOH8D2PVDLJI1t2cqxlFdYlCv9e8thCcmS0QC1oDN54CqpegNKaPQN5Hl3bTiEQpOXiaXyUUlQtGyybJiFoTgqUUkgpcTZso7rrjXnPEbaD1b+auhk0Mow5pjzBR7OCL+dppXjvxDi/vL0TW/tofeUDunEZct/KFl48NDJnIFohWLthJS3juwGNSKYYWXcvr53KM3p6BKcvTqY4woOrWuhNQH26nzee/PH2XVeFiEO7qe37AFWtIByXyOr1WNvupupE0IC2LFxr8eiKFMwMyhu3Fq01K5oifBh3yVU84ELpI8cS3N3fhGs3ZiXYC3w/Cq1IORAfH6Ot6JD54KU5+90tO5ldcUkpRc2Nzm4AgXQYniwjD++h+NF7BKUyTek4vds2E9t+N1U3iuC6Mo4BkPME75+ZnLc91JqfHxuna3sn7nW/imEYhmEYhmEYhmHcepbUnNzDhw/zr/7Vv2J4eJiHHnpozmB7Op2mUqnwwgsvfIotvH0ppdjRGiH53kvk9+8h9BqDTV6pRO6tV9k6eYTmqMS2baS8usuqEgrOTZZY0RInFXPxAoWU0BR3Wd4c552T47x5MkdVX1m8UGs9MxNXKQXrNhHdsA3kheU5Mp4g/tknqaayV9VWw7jVCSEYyNUWreeSq3pM1cPL1jQRQmDbNtZ0vSalFGubbJ7e0kVnOkrElmRiDg+uauWzm3qIt3cgHIepdXfz/T2DjOZK2B09hNE4E+U6P9w3xGj9k/vKsqSAvbuovvc6qloBQPsetYN78F5/AXd62VsYhqxtTyx6nP6WBEnbDEzfqqL4fHlzB9t6s8Rdm4gtWdma5Be39dAeufC5d6Rc7AUicSqaoKmvj2xlYmabcFzi9zyM39G74GtaltXoW7bDgdEq7N3FxOsv45VKKDQThTLH3nmf+is/IXKDir4PFWqoRbp8seaTq5kUnMbtRUpJJRQL/qcxUXfDMAzDMAzDMC5YUitg/vZv/5aenh5+7/d+j2q1yksvzZ0NumnTJl599dVPqXVGU3GUyakRyoAtJVG78QembGknzLbx2rEJxuuK7kyM1S0xso66wuL2jaCJRKCVoicTBQF+oJgs12lNOFS8gLN5j7VZedXFrOvSwb7rQZLrt6CLebBtdKaZejSONqtfDGOey/WKS3VBIQRlZXNyssbJiTyJiM3GjhTtMYFQAcsSgt7NrdRCgS0gIhrFqf2NO0isWs8bp0roThvbjRLaNucjQaHSfHA2x1Nrm5EqQAlB+DEWAHdLBSoHdi+4zz93mkhuHK+pHYC2mGRzd4Z9g3NTkcVdm/uXN6Fv0CC4sTTFhc9DfXHu7EmitSBmK3QYoPWFQdiMrfjchg4ODkxRUzBarKOm6589vHU1WasL3dvb6FyZJurxFOrijiYl43XBwXMl8lWfjkycVltTPXZwXpvKXkBhcIC2qXFo7bzuc1ws+HLe1X0rG8bNzw81PzywcH3Bpzd2fMKtMQzDMAzDMAxjKVtSAZjjx4/zjW98A8dxqNXmFzRubm4ml8t98g0zEEKgxkfoSDi0uRAUcoSTOdz2Lk6u3cFz759G9EnCaJwzkxU+OCt5ZnMXndHF04adF7c1vc1xjoxVKNXnD1SuaUsyOFXibK7K+ubUNQ26BhqCZAaSmQsbTfDFMObRWtOTiSy6PxV1yETkokWZcqHFd3cPzan1cnCowF3Lm7mzKwYqRIQBMQB9YWBXKUUpkuBsrUwYS0435sJxM1GbjRTg7d2EY4PIZJrYhq34LZ0E15j+8JLKRXTgL7pbTY4jmjvQWmOpgAeXpVjZkmDvUJ6ar1jZmmB1S4ykDC4ZsDJuDUopIigQ87uGEIJofoJ1xw7QOzhIUUYJV28i19RNW1OCZkdRUTGYveJlXvDF4sC4x6tHx2a6xaGxClatzBe33Yf1xgszK1PPq/khanwE0dZ11RMXLtadjiBYONCScG0yEYvrT3RmGIZhGIZhGIZhGLeeJRWAsSzrkoMEk5OTRKPRRfcbHx+tNSISxQ49wsHTSK8OQHnjTl7edZgQgSsE58edvEDx4pExvra1A5vFBzEBCAPu7W/idK6OEHPHnXqzMSKWwAsUcffS14dhGDdGcwQ2dKU5OFSYs10KeGBVC1ERLjwjXtq8fmxqTvDlvPdOTbKiuYdWZ/HXlQIijjVve8yxeNieov7cc3gZB6EVjI/inTpG7M4H0Bu3E97gW4OYLn6+6H43Oud+JHVAbxyWr2tq1IZRCqV8E3wxiI4OUP7ZD9C+jwU0CQkTZ+ndcTdh606CK4hb5H3Ba8fG5wRApBDUAs3LJ3M8sWodpYN75zzHlhIRuTG/MzVFYHNPhr0Dc1d5CeD+VS3EZWjmNBiGYRiGYRiGYRjGApZUDZg1a9bw9ttvL7ivVqvxyiuvsHHjxk+4Vbc2cRUzx2VHN5RL6HqtESWxbEZkgiAIEW6kkWZn1uFyFY+p+pWNyLS6im/s6OaBla1kYw5tyQifWd3GfSuaOTqSRwBrWhNXlNLscoQQM+ctpbzqmjWGcauTKuSh/gyPrW+nJRkhEbFZ1pLgy9t6WJm25vRDIcRMHyoGcHayvOhxj41XLtnfhArZ1pOet31jRuK9/SpNEdkIvsxS/eAtIsX8vOdcrzCTxco0L9xOx4HW9gX3BUFAGAQ35F5l3PzCconq26+i/cZEhMZ3j0ZrRfXDd3CLU4s+9/z3lBCCoaJHeFE0z7UEnuUyWQ3w27rn7LOEIB51Ee3Xv/oFGn3z/r4Un9vQQWsyQsK16WuO86Vt3azJWuZ6NwzDMAzDMAzDMIxFLKkVMF/72tf43d/9XX7/93+fBx54AIBTp04xMjLCD37wAwqFAl/5ylc+5Vbe/IQQVLXNeCWk5AWkozZtMQtHz1+pYtt2oz6LbKQXi95xD6WffA/CEGFbeIFGOA5Wexfh5BgynkTNisIEl0scP00pRVZ6/OLmNvoyEYq1gPFSjQMDZQTwwOpWmiP6ujKc2ALcwhRqbAQBOOksfilPWCxgd/URtrRd+8GvwPnBNLOKx/ikCCEoKZvRks/p2gQJaZGNgKUuX5PE1j7rsxZrmtrwFUQtGkHW6T5oCYgUpggHz6LrNazOHkpNfZesFVEPwksGfbXW9Gcc1nemOTRcIBO12JFQrFPj1AuDJFIJtI6gZh9DKdToEDLdhNb6hvUvz3KIPfQ45Re+3wg6n2dZxB98nHo8NbNcTwiBZTVW7oRhaPr4Tc62G78aKXVldcwuRU2MEU5NILVGenV0uYRGY8WTqEiUcPAsYn3zzDUjhCDi1RATY6hiDpnKQFsnXjC/30itSCUiBB09aKt+YTuCnuYEmQcfYSrewkDRIwg1bUmXJhfEFfT/hVg6YG1GsirbuCdEJKCCTzzzmPkuNQzDMAzDMAzDMG4mSyoAs2bNGn7zN3+T//7f/zt/8id/AsD//t//G4COjg5+8zd/k/7+/ut6je9+97v8zd/8DU899RT/8B/+w+tt8k1HCMG4Z/Gj/UNz6q00J1y+uLGDlGwEYZS0GK5oDpzKEx4r0R6XrG+KkPRDkl/8JcKRAVSxQPeKXuySS1DMIyx79gIYXFtedV74iKpzd2+SwaLPuYhFzJGsaInT7GpQ115w29EhYvcuSns/QKoQJscoTU0Qu/N+VDxJ6aN3cZetJHzqF+c99/yKmWsdiLOASDFHODIAQYDV3kWQbcUzK2+Mj5GQkhMFxYuHBxop/OJxKpUKy1sTPLa6mcgCAdeLaa2ROiBCo67F+b4glMI5vJfSu6/D+RUpu98jtvNBmqNdTNYW7iv9zfHL1nCyVcBnlqfZ0Z3GPXmQ4qs/I7JhHUyOEExqZCKJ1dlLOB3wkFpj1cq4h/c26rF09eClsgRcX10YrTXV5nbiz3wdNXAKNTaMTGexlq2ilm6aKZDuCYfTOY+DI3mkgA2dKfrSLu4VvL/G0qKkxXBZs28oR8UPWd4cZ3VrnJQMrnmwX6sQqTWMj+BPTcxsDxlFprPIwEeIRq00IQSxwiTVF39IWLyQ/k8mU/Q8/isLHj8qNE5Llq4NTeAorIlhUi1NRJev5iBpfvL+OYLp/HwCWN+Z5qEVGWx1bdfn7HvCJx14cbTCyU0QjgyCZWF19OClm7i2cJJhGIZhGIZhGIZhfDKWTABGa021WmXt2rX88R//MadOnWJoaAitNR0dHaxcufKq0mUt5NixY7zwwgvXHcS5mdW0zY8PDM8rdj9Z9njhyBhf3tiKQLNrsMqu05MAxONxjg9X+Mi1eHbNHaRf/jYyGkOmMqQHj9KfyHI8HyIzTWghZ2aF71zWRNK6+rzwrvZZnoRVmQRaa9R1zrAVQmAPnKG8Z1fj51qFYGIMgOq7r5P4/JfwbQfvzAnq+z5Art5MGIZIKSmGFgP5OoVaQEvcpSvlEBNXPhhna4116CNK7799YaAacPtXE33gUWrWJQpiGMZ1mPIkPz04RHjRkpRT42Xejzk81Je4bDBkhrTIeYKz+RpeoOiLCZrGJ7EuKskt97/PfXc/w3MjzFsJ05qM0J1w4HI1oWjMtO+p5yi//xLxiMaSIBMJVLmEKpcQE6OIjm6kCtFjw6hymcqh6fSVQhDdeifOljvxxfUFObXWVGMJxJrNyHVbCbWmrtTMPa6Gww/3jzJavLD64MxkhZ5sjCfXt5ogzE1ECZt3z5X54OyFlGCDuSofnsvx5a3dNFnX9lla2WYsIfBmBV9mXrOQw06kqE1fT27gU335+TnBFwBVKpI98h4rmjdycrI67zj39GdoSjqIHdtnJgucrFp8870zVP0Qx5IkHIkjNAeHC7QkXLa3uzdV2rBI6BO+8yql44cvbBSS2Pa7EJvuuO6+bhiGYRiGYRiGYRgflyXzF2sQBPzar/0azz33HADLly/nvvvu4/7772fVqlXXHXyp1Wr8l//yX/j1X/91EonEjWjyTWmsElKszR9Iirs2EdumEEgmPTkTfJmt6oW8NikQ/atR5SLB1ATi+AE+m/a4e30fibY20JpMzOGxde1s64hd1wBPGIY3ZIDI1hpv3wcACCFRU3PPzTuwB7u9E4D64f04Xg0pJecq8H8+GOBnh0b58GyOE0MTDJw8B6US7hVejs7ECNVdb84JvgB4p4+hD+8z9WeMa2JLQaxaIlYuEAmDefdHKSUnJivzgi/nHRgqUAqv8NqTFvvGPP7PB+d47dg4756e4tuv7eNHxQTe5nvnPtRx6S0N8tTGTlqTUQSNlXCbuzM8s6kd9wqCL+fbH545gQ4awU5veJDoXQ/O7A8LOWTgQzGP3b0MLz+rjobW1Ha/hz0ycGXndwW01vPuR1JKDo5V5gRfzhvIVTk+Wb/u7y3jkzNR13OCL+dVvZDXjo+DdW3zVWQyRXTzDuymZuxsM1YyDdOrt9y1G/FGh3CmV3dauQnC/PzvXgBx4EO+0BNhZ38zEccGIcjGXT63voPNbRHCMCQIAnzfp6wdnj88yunJxvU5kKtybLxCaXrexe6BPHV983z3SCkRJw7jzQ6+AEzX0bHHhj6dhhmGYRiGYRiGYRjGFVgyK2AcxyGbzeI4H8+KgL/4i79gx44dbN26lW9/+9uXfKzv+/j+hYFCIQSxWGzm37P/f7Op+HNXvkgB6zqz5GoBHw0WKHqKTMzB0xJXzgoaNOoGc64cUN35WTISvLOnQAiSYZXP7tjKtkgGX2kiElwRohs5iz7R81uIDHyCagUAgUYHcweBVamIY9sIy2qkhKmUUFQZHfdxLEnMljzoFgjefZPyyBBHHJt1m1YTv/N+ak1ti66GsW2b4PDeRdtVP7yX6NrN1B33xp3sVbjZr+XzrqS/zv73zXy+QghipTz199+kfOYkqBCrqYXYHffi9azg/HoWKSVT1Vl9Xcz6vwYvUPgK4tbl34vxuuC1Y2Mza12EEGjfZ2CqyPupDh5sakGVCpQ33suBqsWxEyUSepwd/W20JV2iQpGwNSoMZjXk0qSUqEJu5uewmMePxkg++Sy1Pe8TToxiJ9NYy1ejbIfayaPzjuEf2I3Ts3ymcPnsz11KiVspgVdDOC5eIk14lcHeAItDw8VF9+8bKrChte2a623cCEvxmr/S/jr754+7/VJKjk9UFt0/MFWl6AvSV9BfLj6uP3iWcGyY6Jad1HfvQlVKuL3LcVatQ0Wi1M+eJHrHfQgngvZqix8rFiMQknV2lXVd4EeSBMksbVGJpb2Z71otbXadyTFemhsYVFpzNldldWuCihcQaIF7Be/rUriGnMCnfmD3ovv9g3twupcRhAv34aVwDtfrVjgHwzAMwzAMwzCM29WSCcAAPPLII7z66qs88cQTM0Vwb4Q33niDkydP8vu///tX9PjvfOc7fOtb35r5ecWKFfzBH/wBbW0XirR3dnbesPZ9kvKiQDxemvl5ZUucXWemODVVRStNT5MmqAScyddZ0ZIgFWl8DvFYfOY5draJ1i9/A1XIAyAzTQgpSX+yp3LFdBBQ7OwhCBsDoUE6QzgrCON0dGLbFtFN2/EO74eB00xVA1K+xRN33EOsvZPh7/wIFQSNoIqG2vAwkZ//hJZnvobTvWzh1w0DCoGHFY8vuB8pSMfj2K1tC+//hNys1/J5V9JfZ7uZzzcYH6X42k+wS0XsaKSxsV5FvfUymccSRDZum3ns8qLgbGHu4P/5fhxzLNqyaVqSkcu+5q69Q8QuuoaDdJawVuXocIF71qwntCN8/1iBYrmGcBzqHrxxKk8mZvPV7b10pKNXfa7VvhVYA6cvbCgX0PUq8S07kYkEka13Unn5OZgYJR6PQ0sHxebuRlA4N4Ll10ln0shoY3D//OceFgvUPngL79BetFdHWzbxFWuI3vMwdnPrFbevUPVxInnii3yNOq5DpqmJhPvpf80upWv+avsrfDLtt0YHG9fRImKJBF1Ni+9fSDA2TPEn38c/ug9VqeAsX00ktQkd+Dht7fgnjpLsWUaqq7sRCPQq6IXaYFl4dz/G6M+ep3D6FDoMsWMxklvv4NjKrexY20tTvBHIPzlRZqxSoDub4EyujtIapRuhTykFnhIsb03R3pwlFb3yCS+f5jUUTk1QkGLh9waQYUA6k0VGLn0/W0r94FrdCudgLE5KSWWRQKJrCexPuvCSYRiGYRiGYRg3xKc/MjTLsmXLeO+99/hn/+yf8cgjj9DW1obrzl8dcM8991zxMcfHx/mf//N/8tu//dsLHmshzz77LE8//fTMz+dnHI6NjRGGIZ2dnQwPD19zUd5PU0I4xGXIeKmOa0tKdYejYyWqfkjCtTk6WuTu/mYqXsBgrsyyTIRYNEqlWgENmZiD9KoMjlWY8jSB0qSqEyQttaTzycfWbKRy7DBohZ1IEYyPglIgJdE1Gwk1VF78EU4mixeJUfcVlVwB8doLtN2xHWyboHZhdnLd8ynnpgg/eo/Qiix47pZlITMt1M6cWrBNdks7+bqHN/TppE8RQtw013JXV9ei+y7VX4MgmLP9ZjnfhQghcI/upzI6suB+742XcDIteLKR3qgzahN6NeqBAtEIvpzvxztWtRKUcwwVL91nbdtmNFekUpm7OsCOxgi1plyp4kfb2D3hMZVvBHbttk6qQQB+QKUCu06OcGdn9KrvD7GWdqqhQtcvWhVQyBO/60F8J4qvBUEQUtjyAO+O1Tl1KI9Wmt62Nu7b0ItfLBHm8jOfuxQC+e7PqR34aM4hK3vexxkfw370KTx5ZV+L0rJojcLo1MIrJ9a3NlGamqCwyHkLyybnQc1XRBxJ1tVwpTV5rtCndc3fiP56ft8n1f6OmOC9ysKfZVPChXqZoaH8FR9PCIF7eA/UyuhUlmBqkuDgnpn99sgQ1vqtyE07OTqSp+IrolaK7JrNBHt2zUlbGd1+N0Mv/oTJ0YmZlWhBsUjtjVdpqnucSMXpSTRS5eVqkqHJPFv6WghDRb7uEyqNACK2RdVz2NQWo5yboHQF7+lSuG86KMJIDD83P0UcQKQ/y1gut+g9Zimcw/X6uM7hUn3V+OT5oeaHB0YX3PelTe3Y1ifcIMMwDMMwDMMwboglFYD54z/+45l/f/Ob31z0cZfad7ETJ06Qz+f5F//iX8xsU0px8OBBnn/+ef7mb/5mXh0Ox3EWTYV2/g9frfVN+Ye8pT2e2tjOC4fHAc3h0RLFmk865tAUd5gq15mqeLQmXKYqHn4qQgxgegbt/StbKPmaFw6PMjZd+yDqWOzsa2JLRxT5KabbuZR6axeJhz9H9d3XCIXA6V2OrhSJ7LiX+tQkbiKBiMWx0ll0rUbEalwTcaEpv/EirdvuZ3D/AaDxPjhWI5dTcO401vZ7CRdIrRQEAfHVGxCH9qD9+bUvItvvoibloteREIJIvYqYHEfXq8h0hmDWAPuNcrNey+ddSX+9eNvNeL6WZRGcO7Xo/mBynEitgo4lAUhZIc9s6eJnh8fIVTwAbCHY0ptlU1uUMLx8Xw3DkJ5slJPjpTnbA8vB7l1OsppHSMGxkQIiGsNpaUNrsIp5hBshdKMcHimxrSOGvMr3vBpLknjiF6i+9iJhrlHAXNgOkQ3bUGs344WK+LY7mRqZ4NsHJ6hUL6RcOjk8xWi8hS+1a5qdC/dsp5SnfHjfgq/nD54hkptAN7VfUfvCIGB7T5rjY6VGkGuWmGOxqSNJGC5c86YuHN48nufIaJFQaaSA/pYkj6xqInaFdXKuxlK65q+2v57f/nG3vyvh0J6KMlqcG/ATwP0rWnB0cFVtsG0b//QJHCCMRLF7lhGODs8EFHWtinvng4yMTpE/eoYgkeagSFKNruEzD3USefM5CHyQFiTSTIyMoxdIP1XY+wGp1ZuQqbbGd44jsKVg32CeR9e18fKRMSbKHnr6XB5Y2cKybASl5tcuupRP8xryEMS23YX/0+8DF7XBtnHWbqZyBcHLpdQPrtWtcA6GYRiGYRiGYRi3myUVgPnX//pf3/BjbtmyhT/8wz+cs+2//bf/Rnd3N1/60pduyyLoSeHz5U0tVJXNt/aOsLwlgReE5Mp1Yq7F4ZECdy1vYariN2pMCEF7Oso9/U20Jlz+9v1z1PwLgx01P+SNE+O4djubWuwluRIm1Jr68rVEu3oR+RwIgUyl0b5PTAiCj95FpTIwfT1ELUHCtQlRhIU80ciF1VPZuIsrdSMo5UYaA2SLnHM1lSXx+DNU33xlpriyjMWJ7rgXv6t/0YEUKSXRsSEqrzyHqpRntjud3cQ+8wWqbuwGvTPGzUJrjYwunspL2A6IC8E5pRQdEcEvbe0gV1c40Rh2UCdtK9QVBkqVUqxsjrHLseb0eYDAjXLPtn7i0QAnn8CeyOMPnUPP6gtWpgmxvH/emOmV0FpTbWrHfeqrWIUpdBhAIoWXSBEqjWVZeN0rGA2zBIc+uPA+OC5WRxcV6fLBuTxPrMpcOGipCJcIPKmpCURzxxUPcDY7ime3dfPu6Rxnp8qAoL8lzt3LsqStgAUPI21ePT7FsdELQS2l4eR4iXoQ8syGVix144MwxqU52ufpjW18OFjk0EgRL1C0JiPcs7yJ3rhs1DS7ClprZCwG+ca/w1gCa9lK8D1ELE5s605O/N9vMjqem3lOX08vlbsf58elJL/0i/+ISGEMGU9SP30SLSQLdaSwXidSLwONFG4ZW7OhJ8u3dw9xerLC3f2NNHih1qQiNnEbRkoefVeXTe1T53X0En/ocWrvvznznWils0Tve4RatmXR7+CbkbQaiaYsNOENXhVnGIZhGIZhGIZhfPKWVABm48aNN/yYsViMZcvm1uiIRCKkUql5229l0rIItMASjdokIgyIWoLuVIR3Tk4Qcy2yiQhTFZ98GPLykTGe2NDO42taSMZiBNUilg7ZO16ZNxB73q4zU6xq7sRdojmqlVLUnCi0zsqh7saQUmInk3MGXQWK3myUsZKH3dKOAqQQZGMO7Ul3Jj2Ms2Er9UsM1mqtqbZ14z79S1jFPDpU6GQKLxq/ZKAqUilRfvGH89Iv+cODiLdfxf7MkwRmFuxtJQxDIqs3UD9yYMH97oo1ePHEnIFIrTUOPu0RQVdnmqGhIZS6uusmJQO+tLWLV46OM1JoXI9x1+Ku/mZWZBpBn1UtSd45ML9dYX6KdbE+XAtCbRNqsIVGXeGgotaaumVD04X6IEJDUTscGihxcqrGaNln9R13YAUeJ0dyKMclFI1A6rmpKtUwe+G5i6y8mNkfiV7V7HKlFM224sm1GSphEwBxS6PDRYIvQM6DE2OlBfcN5qpM1BTtV5Yt07jBovg80Bvnju4UoYaopbF0eEXBF2lZ+FrgCNAqbKxGWbsJNXxu5jGhEOBGiK9aT27XO4xPzr2/lwfOkd7zJu66hzinI3S3dSOEIBqPkYjaFGsLBOaEoCkdnxmoVypka1eK05M1Pjg7xdsnJ5AC1rSn6OrJsOfsFEplWJ5K3FSD+yGgV64n2tOPKBYQUhCmstRsZ07Q92ampM1gSbF7cJKKp+hMR9jcmaLZuXk+J8MwDMMwDMMwDGO+JRWAOU8pxYkTJxgdbeRBbm9vZ+XKlbflapXrJaRkvC7Zc7rASLFOzJHs6M3Sk7KQWpOMWKxuSzJUrHNi/MJKC4GNJSQD+RoPdzQxVJ5CWhYD+eqir1Ws+dRDcK/wYzqf+/9qBjyFENhCoGmsarkRqTiUUtj9q2H3+3O22yi6Ug7upnsIozFWtyZwpUZPB1/clevQPcsu2watNXVpQ6Zl9osu+nghBHp0cH7ti2ne2ZMkSjmCRGbB/caty29uJ7r1Tmp7ds3ZbmWacLbfTeVjGIjUWtPqhDy7qZW8B6HSJF1JXIYoFSCkxSanzIFkjGJp7v0hk4qxJpigXGlh92iVUgCWFGzuStMaUdc0cDoV2HxnzyBVLwQhODVV5+BQgY2daVb2tHJyVnDDkgI5K2tTmG7CyrbMpDSbTbgRaLmy9GMX02FIjHD635d+bMkLuVQMrFALaHfnp5oyPhlKKSI06iahLr94SwjBhG+x92yBoXydqCPZ3puhL2UTtHUR3bidyq43LzzedhAqwFOgFvjuKJ48xppNdzFV8eiNu0ghsDq66WpKUBnOE170nJa+XiKtrahZNWOEUkSE4hc2d6JoTLzIlevsG5hEaXCtxVNfLmWNSRQRaL4QkF000nmT0dJi12CFXacnZ7aNFWscGi7wxc1d9N5kK5YMwzAMwzAMwzCMC5ZcAOaVV17hb/7mb8jn5xa7TafTfOMb3+DRRx+97tf43d/93es+xs1ACMHZMvxo3wDhrBG/gVyVHX1N3NeXIO1KPr+hg/fO5NAKvFCxoiXOipYEB4fzjOZKbOhuBhoDseno4jPIXVtiXUHwxdUhdm6CcGQIYTvIzm7qqSzhReMolmUhhCAMQ7TWRL0anDmBf+wgCEFkzUboW9EYkLmK90QIMS+Pej3TQvzeh2Hv/IFt9+4HCR2X2LJl+KeOgxDYK9YStrY3Ais3mBACVbxEsWeloF6HxA1/aWOJ84XE2XoXyb4VBCeOoL06Vt9y6OylchX94GpprZE6oGnmcg9nYohCCJKHd/GLq5axv5yeSa21tiPN5owgmh+n9s4IbWfO0BGNIdZt46NajXV9rfTFxYIDwef76cWrxIRl8+bxyUbwpdEwmuMOA17AgeEC6ztSWELMDFKv70wRkReO4dkOsYc+R+WF76FqVYQQyMCHwCNx1wOEpTxR26FmX3oJymL3kcsRQhB17JnnLiTmWLBEVxHeyq7lMxVCMFiV/HjfIK5jEYSKyXLIYK7K1p4MDyxL0fzAo4SdPQQnjqLqNZyVa9Fjwwhr4VpeWimcwKM3onFPHcE/vJd6NEbLtjtwgrcZroQUaz5SCNramuh48inqF10vKQccW3JgMHehrWgsrw7VCqvtGNGpIl6mmWCB+mXGJ2/KE7w/K/hynh9qfn5snF/a2vEptMowDMMwDMMwDMO4EZZUAOaFF17gL/7iL1i+fDm/9Eu/RFdXFwCDg4P87Gc/48///M8JgoAnnnjiU27pzcHD5udHR+YEX8776OwU69oTrG6J8u5AhcPDBVa3xZFCMFqs8dqxMZY1xah4AeOlOlkaKZDWtiX46OzUgjO413ekSFoKdYkZ4NHQJ3jzJUqnjl3YKCWxnfcj1m8lQKCEzVhNc3CkSNULWd6SYEvcp/7C9winxmee5o8OYbd2EH3saWru4rUxoDFQVlY2A3mPyYpHU9yhJx0hZYUopQgBsXYLTSvXoA/tR9Uq2J096PZuCm6SkUrIOd1BZn0vPZkYSStAXOpEr4NSCivbvPgDLBuipgbM7coXEr+5HautcX8MlPpUZ7NrrbGyLcQ/eo1701l2tnahNbhjp3BEN2M//QHlbCclb3qQ+NRJ1mzbyUlrJx2rW3FmFZ0XUpL3JWfzdUr1gM50hK6kg6sbjykHgjMT5Tmvn3ItkhGbUj3g2FiZ5mSEsWKN1mSETR2JOfVuGnVlWok988swPADnTqGqZUS2mdLBvahSASvdRPzxZ6gkUvPO9fx95Fy+znjZoynm0peNkJKXLtAuhKCqbU5P1Sn7Pj4SLwyJ2QIx63mJiE1LzARgPknnP5uBgsdIsU4qYtOfjZJxLr9CK8Di1FSVZW1pRoo1MrEIqxIug1Ml9gzk2dCZpl4K+aCaJuzYSWc6QnfKpS0MiFgQd20q3tyaRNK2aW1KkXjnBSoDJ2e2+5MTJLfuZLXj4FWr2O2dyM5eqpHYvFUgQgU8vKqF7+4ZouaHSK1hYgR/aoKdq7tIf/QqpaFzRDduxd1xH55cOBhkfDKEEJzN1RZdbTVZ9sjXNX2faKsMwzAMwzAMwzCMG2VJBWC+973vsX79en7nd34H277QtM2bN/Poo4/yb/7Nv+H73/++CcBcobynyFW9Bfdp4FyuxrY2h86USypmc2K8jAaaYg79TTGs6UHA2SlPml3NI2vbefXo2JzATk9TnDv70qhw8eLRUkr0gX14s4MvAEpRfe91km0d+G2989JwjJc9sqUjNE1OcnFmnmB8BOfUUawN2/G1IOeBHyqSrkXKVqgwRAjBaF3yw/2NtEWJiE3Ctdk7CA+ubKEz2pj1HAJO3woCt5HroxqG1HF4/tA4A7kLqZUEcGd/Mzu7Y8iPKQij27qQiRSqXJy3L7JqHX4yc0sVHb5dXbzK62oslfoNjdo06+HgHsJCDlnIAWD19lN+7w1EIkX+orr3+d3v07dsNXmvmdbpRXVCSo7lQ148NEQw696Sjbn8wpYOksJH07h3hUi8cDoVoAV92SglTxFxJJ3pKNt60vRnIkTw4aIZ/lprqtEEse4+6of2oIoF1PDghfMpTFF/42c4T3wZf9ZzhRCMeRY/2Dd4YQUOjZV/T27spC8xf8XOeUVl8909wxRqPo7VSAP5k4MjFKSgI+EgtCbmWjy5sYOYWLx+jNEoUJ7zoeorXEuSdRsBh2uVCy2+v3d4Tn2VN6Xgc+s7WJWRlwzC5EOLl46MMVi4kC7SkoIn1ncgpGDPcJnxSo6xqcZ9fO8ARGzJ/3djD3Y8To+C05OVmWsZoHnTVpq9AsHgqTmvpQo5SnvfJ7r5DsR9n6UeTAf9FrlYWpyQr23v5thklbPnRokmBZv6++gYPYYYOgtA7cBu4m1diP7Vi95/rOmVOpdatWVcn4VW+13MfNsbhmEYhmEYhmHcvJZUACaXy/H000/PCb6cZ9s2999/P3/913/9KbTsJnWZsZLz+efb4hZNriAbaaQw0kpz/s9915K0JiLocmX6SSEbmm26d/YwWPCo+SGd6QhtUYmlLxF8sSxEGOJPjoGUCwYP/EP7KDYvmxN8AVgWg9L7+6lX6yzLREDPfa5/9AC1Vdv4/uEJRouNgTDHkmzrzbKzK06I4KeHhpEINvc0MVLyGC7WyMQcTkzVae5O4Oj6hfdlekWBZVl8dK40J/hy/m197/Qkvdluui698Oaa1SMx4o8/Q7D/Q7TvocMAf2wUt2cZ1h33UzPBl5uakhZjVTg0WqTqK1Y0x+nPRqYH32++Qc5apoXEo09SfeMlVKWMlcoQ7e1HlyvkClWCodGLniGQg6ewV6+G6dopeV/OC74A5Koerx6b4IvrmolLQSoeY9eZKfzpQWvHagRd0q7gkVVNrM5Y0wGtxe9HAIwOEYyNLLjLHxkiWZjCT19YieZh89NDI3OCLwBeoPjpoRG+vr2bmJjfL6Vl887xHIXpAX4/VBweyvHYmjZ8rUlFHTriFl1Jl/hlVtLc7nzh8OapAoeHCwRKI4CephiPrmklKS7zeS9AS5uXD0/MK24fKs3PDo3QtrOXlFz4Xissm7dPTM0Jvpx/7k8ODvOL23sZLlSxrbm/zwRK89ZEyBNPPIt89TlWCqgGiloImdVrST7yOPrF7y16HdSPHiC2aQe+G0VKiePXG0FJNzonKKu1Jil97ml3ufvUCYLKEMHZ8Xnfn97+D7GXrZwTbIRZ96izRfSZGl0JybJMhPhNeo9aypRS9GQXX9WajNhkIqYGomEYhmEYhmEYxs1qSQVgVqxYwdDQ0KL7h4aGWL58+SfXoJtcOiJJRZ15g0vn9WajaB2ScTTbe5sYzVdYa9dw/Sqh7XJcxeluTdOeijAyK+uPVoq0VGSaLMBqFKXXiwxSSYvRGuwZLIDvs6F5JV2tPcS9EmGpiDd4FlVtBHd0ucjgVGXeMVrjDpmoQ60mKPmamC1nVucABIFm16kJRosXgih+qNh1ehLHEnRnotT8kNWdWb63t5GS5bx3T02SeGAl21rkvJnElVBwaHj+CpTz9g0V6VuTIQiuffb1YqTW4NehWkaPDiLcKKk77iVcuY6qSRdzU1PS4t1zFT44OzWz7cRYiXTU4ctbO69pIPmTZAuBW8yhy0WE4xJmmvGEQ717OdFf+AZuKU9w7BD1D9/FO3uKZPdyVt19J6f37MOr1qmHCj9UxLwQX0FgOTgEnM3X5wVfzjs7VaHgN1MLQ5Y1xdh15kKQ1g8V56Yq3Luime6ETRBc/v0TQqAq8+81F2i0V5+zZaquyFUWXlFY9UImqyEr4hq7MIX2PIgn8JIZioHg+FhpzuO9QDEwVWJZS4qYY+E6Fr4GhAS9NFY2LTXCsnnjZIEDQxfqY2ng3FSVH+4f4StbOnAuF3S7SN6HoYsC7OcFSjNQqLOhyVow4FAKBKcnyri2xAvmfv8pDedyVda0JShVPLY2KxyvRjSdZDzaxCsnpojZGe588EmShQlSYYhsaSNoakZp0Jda3TYdfI9XigSH9uKdOQ4InBVriKzfQjWamNNeHfj4A6cJp1emzTtcrYoTBGBfqO+mZgrCN+5R8XicA2crpKbvUaklfo+6GbVEBWvakxwdnXuvEMADq1qJCnNf+Lik8Hiia+H6hikWvucbhmEYhmEYhmFcjSUVgPlH/+gf8R/+w3+go6ODxx9/HNdtFEL2PI+f/vSnvPXWW/zmb/7mp9zKm0dUhDywqoWfHhhGaZACEhEHpTR9zXGaI6Kx0EWFfKbdIn/sA87t2UfND7Bti8+sW0XLys8hxcJFei83C1ZKydF8yAsHh1mTcVg3tJ+pN19lolalM5ug1QmJ3/kA1eHBRu2Fjm4K3tyBrA1dWQ4UPTYk25k8MUgm6hCxBMua4yRECEqhepdzrrpwWw4PF2lORFnWkuTlI2NUfEWoGqt/LCmwELxwaIRV9/XR6hfxhweI+D6eGyUMBfVg8UGPUj243CKjayKlxD19lNKrP70Q2PJL1N96mWhuAvvOB03h5JvYWJU5wZfzCjWft07neGJVBh1eX1BPysZs6cultblaMa2QR/YTjg0T5iYJxkcQTa3EHn6CalMbQiuKr79ImJtEALVIgtLgEHauwOrPf5HdP3mJ2tQUAmhZs5of7hukMxPl8TUtlOu1RV9XafC14P2zOSZKNb6yvZcPB/KcnargWhZbulJs7EwRkXqxWPAcWmvkJessWRBLYFkWUmuUEPjB4gd2LEl7fYrw9RepjUxPIrBtoms3Ed92/7zAUksyQioe4fv7hnEsybKsiwXs6Gviju441nWk1LpV5X04PFJYcN9k2WO0EtJzlaWxvEBf8h5e8QKEsBf8rvOVRquQznSUs5OVeccRQrBCVvH3vkzu+FEsS1KWElp7+H8+8xj+3p/zxq4PCcOQZMSmqa2F7iefIdbTjbtyLf7IIBIQQQBotO2ghSDa1YPre5R//H8J6lW01igkxQ/fJzx0mNhTXyVMZWZWqijLxmppWzQAYze3EjouUkhKoSRQUPE0u87Mv0cVaz5vnZri86uzV3SPEkLMpC4zq2YuzVIBj6xsoisdY89gnpof0pxwuWtZEz2XSG9oXD/hewx891sL7mv91V/5hFtjGIZhGIZhGMataEkFYP70T/8UKSV/+Zd/yV/91V/R1NQEwNTUFGEY0tzczJ/8yZ/MeY4Qgv/4H//jp9HcJU8pxcq0xZe29jBQqFP2FSOFOu2pCJs7k4jpmda2APXOK7hnjtCVcinUJDU/5OS+wxTyJXq+/g8ohDah1mQdiNZKaGnhu5FLDgpUlMVrx0aIOhbrCmeYev8dxPTqjZF8hVRzFP3CD0g89YtUjh3CWrWeVu3i2pLubJy2VJR6CMfGp1i2cjPR40cRyiPjQDg+QlDJY8UTSNvmPsb5INnCQKkxM9eWgnuaBE3jJ0kOFXHCJEP5KmVfMXss1JYCEIyeGSS+60doraghiGzaQWbdVpqTEUYLCw8ML2uOXbZI87Vw61Wq77624Kqi2sG9JNdsJMi03PDXNT5+lmVx+KIZzrOdHCtR7s8Sv9b4mrCYCgRnxmpUg4CeTIz2pEsQKkaLNaS0CK8xuJOoV1Cv/YzyO6+gKmWc3uVE12+mdvQQtZ9+j9iX/x/C08cJc5OESAbydUolhapUULkKyV0fkvrsF0i+8xKtrS2cstIU61WKoyU2d6XpSEcWfe2oYxGxJZPlOlHbJshNcGdThJXNrUxUPMpeSK4aMOFHcIRN2uGyA8SqpQ27uZVgcnz+623cjqU11q7XCYYHkIkk/eu2sSrtcrwwf/b/HVmJevmH+OXchY1BQO3AbiLSZm3HZo6MND53AXRmE3zrw3MoDc0JF600AY3Uhk1xhzUZaQasL1Lx1Jy6YxebrHj0xp0ret+klJSVRFqSLb1NDOcqjJXq8x7XkYrOfMcJIbC1wqrX0LZDwnFJRGwQActbEoyV69Q8hSUFLQmHx5anqT33LSoDZ9FKEYu5nBgvkaqeJP3qtxl0srQlXKQAP9RUJqc49Z2/Z9X/59eILluF+9G7+McOElbKCK2xkimsbDNOexe1H/89wYHdyKZWvGwrp3NVqn4IlMl8+BHvtm7gwZWtdMc1gVLEN23HO318fupPIXE338G4tnnnVJ5jY0WSEYcQSa6uyUQk4qL38+R4mfLypkveo6SUFALJuYLHVMWjNRGhJ+OSMOnLLsnRPlvbHNa3tRMoiFpAGDQmyiwyEcYwDMMwDMMwDMNY+pZUACaZTJJKpejq6pqzvb29/VNq0S1AhTTHXN49U+HMVBUpYLxQ5vDAJPf2pbkzo4n5VfKnj1EJ4PRECcIQrRWObRNMjHN0/1F+lI/j1opkggoP9CToG9iP292LWLOJmu0u+NJT9ZCKF7Kt2ab6812NjY6DiMXRtSpVLXECn3BsmOSTX6WSytInHNZ1NfHzY2PU/DzjlTrberNMJptY+fQv0XriQ9x97xGUisi1G4mt3cC5jz7AqwU8+ZnPMtDdRr6uSEcdwp9+h+LUJF3bNxJf91lK5SG0EHNSrSQjNsVimWrZAq8OjkNQqVJ6+w3ipQoPbXmIb+8emDdoFHUs1rYmUMoHy2aqDhVfEXMkTddZFFoUC6hKeZG9mnBkCJFtNQNZNyEhxJwUeBcLlG7UZrqWsTZpsW/M4/XjY40goxC8djKPFIIdfVkOvj/M2tY49y/PkLiCtCpK2uQ8jR9Cp6pQf/5b+O/+HFUugwDv4G78E4dJfP7L1D54G2dyBP/gHmylGK6GFOs+wnGIpDPoeo3a6ePk+zez6okvcaameWfoQuqnI6NlHliRJRt3F0zztb03S8bVPNqkyL3/FvmTxwHoX7Ga5dvv40DN5WdHxtg3OIXUiv6WBA+uaCZtNfqhDgJi1TI6DFCxOJ7lULcc4o8+Tf2tF/EHzzVSEFo20Q1biPQso/DDb6L96WDL+AicOcG9a+6gnlzNudKF/m1JwfIgh11ZeHWGd3gPDz+1hWOjjZU8rckIR0ZLKA2uLUm6FrNLbL9/JseKre2XrKl1O4rYEsHipc0S7sIrVS4WCIfdQ2V2D+SpBSH5uqYjHWVTTxMHBqZmjt+ajNAet0ArbAHO0GnqH72Ll88hozHS2+/inmUreOnYBCkRkIwLVMIByyYZtegPpjgyfA4ASwjqgUIDvXFJdd+HdD75Nd45cpJ63SMRsejJxPC9OoVTJ0mvWoa9aj1KSMJjh5AoIpu2I6IxgnNnqB/aiy4VUE6EgZqkLiMz9wz/5GGaOtbx3IFhvr6jUZeo1txB4pEnqb77c1SpkVZTJlPE7nqQYmsvP9o3OhOAsqQgXwsZyFXRmRjN0bm1R0KlCTWL3qOklJwrw48PDM5JzRZzLZ7Z3Embq8x31yUopbBRjV/OTdYxwzAMwzAMwzCMW8KSCsD87u/+7qfdhFuOlJKPBooMTFWwADTYgUc4OsTrR0t07OhjRfEccmyEmptGl4vo6ZomyZYmTo/myYyPI70s/tAZxrXmByOCZ7evp/2Dn+EMD+J+5vN4coFLaXqMJSMVXqF4YZMbQTguIh5BJldR0Q7DbiuJwCJfCzg0XCDu2tzfBsncJHJ0gJRqJtm7DL35Tnw0aJgqFxHDg8g7HqBQ8Ng1WKSzP0v74DHa6wWKfd2UakXssXMsu8uhNxtjrOSRTrrEXJuuTAxHwuEjZ8hsW4WVzlKLpxijxOTAALzxNun2Nexc3sqhoTylmocAOjJRHl7VQtoKqGiHlw5PcmaizPkxqd7mOI+tbiF+FXnyhRA4KsSqFLEDD8nsIdmLP1QzE/ZmFYYhy1viHBtbeBVMSzJCzBaX+PAXN1EXvHZsbGYAuRzA0bEyZS8AIVBa84P9wxwZL/H/u6uXqJ4/4x8a12JF2YyfGkSPDGCjwfYJJyfAshszsVUAQYD2PbxDe5BuhHDgLGpsmGqxRK4qiSfiRF2Hqh+iXJemVArd1c0xmUTGYV23QggYmKoyWQsZLvk8vbWHd05OcHy0gNKNQOf23izbOmJEpyaI//wHHD05cqGxJ49D72r2jlkEThQv1LiiMUt/ouTx1W2dtNTzVN7ah5ocBw0qCIkuX4XX3U8llsB59BdIFKfA8yAWh3iS8o/+Di6u7aQ1iSMf8cjjq/m7qkTpRhH4zb1ZOsbP4S2S+0z7PhlV5ektXbx9coqobXEyVyYbd2lPusRtcCybmhcSak2p7uOHYJluPkfWha5sjMEFarZEHYvOpANc+p4rLYt3z5b4aFYKwJQrOTtVpVQPWN2a5OxEmeWtCR5a2UREhJS1S2VsHDFeIhtPw+QEqpin8trP2PTwF1CdzbzzwSEqpTJCCPqWdfP4trW4U2fpzcbI+YKJfBGm0142uYIgmSImQrZuXkU9kuD4weOcmsixvCWOyE/iHa9z+PW3ia9eR/ZXn+B0Tf7/2fvPIEuy80wTfI7rq3VoHam1LK0LqCpogAAbJIatdmZ6jd3bu9O2nDUb46+eH2vW3Wtj1j9os7a2nOYsh2STBEkQqIIorSuzKrVWodWNiKu1y7M/blZmJSoLqAIhCsR9zNIyrvu97uceP8c94nvP972UNjbJdCpsSVsIRcOtVfHSg9RKZdR4EsUwCUQ3o1MKgW07bFaabDcd3GgMe3QKs38IpV4FCTKewDYsVhveHdk/tY7LWCrK+dUqG3WbuBm+ow/TEZOwKj+khL1fbqwZqPzoyuqHfHHajs8LVzb57X39aD/lOvXo0aNHjx49evTo0aNHjx7/mPhUCTA9fv60A5VL+dsrs9XAx1teQLrdVeYXix2mEhHcwgZm2MYQGjZgGDp1N8DzPHTLojm/QvhmxCUIJCdW63xhYBR3eR6juAm5wQ+dO6ND2G3RqgYkVYHjeKBpSEAKhUDVuFhxiI/FeHumwGQyRKpT4Rkvz1DKov3OK6yVm6w1fZpItk0Ok9mxjZXZGYSA5NAQV0b28+p713BaLTxfolUF2VCUr4xnyWwskD18AH9plsrSEo9OpXh3rcWOmGC7rCKXzqKoKl8+vJP+qAmNOo3Ll4lZIdK7dlNq2jjVEpeK8Oj2fpKGQBEQN0D4HoGi8cLlAsvl2wFBSddg+3LRJm6qKATkIgYJLUAGd1/OqgiBub6CfeJNOsVNrKltiFoZzbDwrB8zNRACtX+ot4L41xQpJWMJk0RIp9q+MwgpgPsn0mjyk3sLqarKtdXGrc9JobBa7QaVAS6sVvnCniHmCw0urdW5XOhwOKfetYSgj0b93Glqr76ASUD/2DD+wlXE5ipKIoUSjhJUSwT1GtIK0cmvEb7/cQh8jIlpGufPYSkSz5fMFG4LTbHR7cw7OhEl4PlLeVquTwA8NJnmc7kA78I7yGqZJ0bGeGrPJGUzhqkKIoqPIMC5fBrVcxlIRcmXu8eNb9/JD6+uk4jEqBg3BZibT7Vax6Vaa5O6fJzG8TdwNvOgKBgTW8A0MBRBZ3AcV0rcWAohBFa7ibY0Q/vSWYSuo8YS+IZ5q18VFRKKy+f2jlJqucRMjeGYhu4mPjqnSCig64yGYWhPFg8V09DYrLU4FHaJlFYJ6k1Epo98KMOio3W/Q2/1+x2IwOPJrVmevbhO+QNZUpau8syufqKq/6EKWz9O1VW4sFK5Y5uCJBdW8KRk33CShyaT3TKXgeTEus25+RVaN64ifZ/BTIrH9wySfu3vAIG5eIP9q8tMTO+hZQ5hpVIk12cJvv3/pvbYV1jb9QC2opPQFWLlFRLnzyDzSzhrK+ilIrUXf4himOx+4hmuz6us1yqMZtJUVpYYOXoUv2Oz/voraCMTKI7g+StrnO9P8dX7Hoel2a4XWCAJOh0UCcKyMLbsYH29TLCyQlmr0Fp4D71/EOvIQ7RCEUjlgO49w3BstGabkbjBat0hkBC3dMYzEbb2xVivdbrZLu9fA+D+yTQa/u05IQRmo4pcXyFoNqgM7cbpON3J8mOUWw4lO6Dv7kmzPXr06NGjR48ePXr06NGjxz9KegLMP3J8KbE/WPKo07olvgDUHZ9ABuiDw9RnZ0kOjLPueui6RsX2MaNRCnqUwF4B8/Zw2ag06YxnCDdryNImSv/wHcHckNNBe/d1jkTGObVQ5PFtu7HffhVhmIhQmETYoNR0QFHwJrZjOAG7yjOc+d5zTO3eTvPNszhrK6SsMFZ2mLm6h9tuIYsb4NgsN1w6R7bzg9ML6IFEEWDoKkY4TKWwzjFf58nlc4SmtuEffQSMLP2qxT+JKtgvfo/CwhK6KshGDNrzF2H/XnzXxV5f6/rAzN8geeAe2vEIrbzHG9fW+eaBQUzcW4HRYoc7xBeA8WyUUtvjT47NM5GJEFK6q57vn8ywpz9Msd31qgjpKtmwSljxsUrrNF78LvjdAztry4QO3EvjpWfRh8fxjNveGNaeQzjR5M9xhPT4ZWPh8pW9A7y7WOXGRh0vkGSiJvdPpBmLKkj5ySPvQohbYguAJ6H8AYHH9gLUD1QSOrVU5sjgYLfs3o9T2mTj5R+hCRikjdhYARng1qroQkF22iixODI3RMfx8GyblqfgpSfoSzQx82sYpSbLm3XQDRACMxYj2HGAv7+Q54ltfYQNlartE9IE99urFP/sh8RKq3itFo1IhNj4JENf+gbtdD9BIDGDgGK0j5X9/TRsnwlLoC/P4uT68Nc3gToylEIRt+9RpqYQXrlB68VnUbybfREEOLPX8ArrRJ7+GnrfMM7NQHGoWqL1/HewRsZvGZb7pQJa/xBBPIlUVJr7HuJHMy02tOVbGQBRU+PL26dIRmIEzfqHutMYGceNJpFSokgPA4+jIzGal+aoPPc8Fe/2dcqk0hz44lcJXXwPJZUlyPRjf6Bk4m86McXl6/v62Wj6FFsOUVNlMKoTVYOPZVJet328u/nISNAIaHQcRiwFIRUuFlyOzRZR7TYoKn48w3UPVtYNfu93/wf6i4vYr3yPoNkkbLdJ79hL54W/wHVdVh/5LV48s0Yzn+96eIQjDPWl+My+wzSfvUZoeJR2pQJA4Ng0Xn6Oqad/iysnz2GOTmCszrH5xovMVR0U30O9fpWIofHEw5/jxZMzzG/Zy8j0TjTX63rT6CoqPno6QzU1SOXUDQDSlobstHHmb+CXi1if+zod3STkdPCvnseeuYJZt9kXzbJ/zyHW44NczDf40+Pz3DeVRRWCtufjB5Js1OS+iTRjMXHL+0wRAnN5ltbrLyA9FxSFhh/HX9pEGx7Du0t5UscLoCfA9OjRo0ePHj169OjRo0eP3yB6Asw/cixVkI6YFBo2CJDt1h37xxMWnYVLRA4/QLtWByGJxSJYkTC6GcZ67POc9WMkwib+TYFAAFumx9hMh5i3o+h+humOQsZSUAMPVVXxL5/DmbvOngnIHTlIWyoMmDrlk8fJxq2bgRpIPvQZ3rHDHDZb1F59jeTkJNa+w3QiUYzsLN7V80TqRbKRHHa7Q0OziEqHZMhgttjGdT1GB7MkNUnFExSqJYJKkRsVuGdyO8HFM8xdmiH9e7/PKzdKPFy5jF7eYDITIQgCam2HpuNgHX+HyaOHEJcuIm8GpdsXz2A8/AwADdvDCcD8QBC76dxZosjUFIRQOTa3AYDnS1C6K6lfnSnRCQSn5m/6cwBhQ+WrewfJXTh9S3wBCNot2sVNop/7Lfy1FRACYYUwdh/EGxzB65nx/toTFS6fmYpx31iCQEpCmuhmvvwM4gt0S5uNpsJc37ht9P7BJKlc1LxDoBFC4Pqg/NhxVFWlPXsdGQT0hVUUBzwrSnjvATrLi8haBWPfEQpTB5gTcUq1BmNjgwwM9XMx3+Caq/HE538b/eoMsZMnkYqKMTFNpX+S1zYCDg7EyIQ1du0d4sVrmzyR9ml/58+oNltEElGCeo2gVqV++QJG2ML42j/F0S0uVgJeuVhCFZKB0SHWsbCm72NLLsp4XWV2pYiiKJjq7eJ9WxMa7rG37pp5FtSq+OuraNv24FhhDBnQefslgnaLIAhQEimCahmkxFtfRQ+Fcbfs5sUVm5IVhg8s7m/YHt+9WuL3PvtbiO//11v3DwAtk8O471FaP5axNuhUWDv1BlXfu3W9FM8lUtvEePdlmrsOoly5iNZ5l9Bjn6Nt/lgm3G8whnQZCcNoRL+ZCejdynxRFAVbKti+QFMgrPh3CDP6T6nrZundGdEOVE4tbtw8qEo13odtOwz3pRBIzuabaE2de4ensGYuISwLf3UBv1Sg/fjX+P75VVwUtMER/Pwy0nFYXS/zlhfmyae+irP9IH67SXZ8ivpLP8ArFzFqRUa+9DVkpUj7+OsEegQ/CFBUFdfzCTodYhffY2R8N997+wr/+kv/DYm5S4xVGlQcUCe2oGzdw/xmDVVViEUs+joluFkaz6+WEesrWAMj2C89i1folvILSYXV2etEE0muRFRObdoEEl68vM62/hj3jCXZ1p9g0ApQAveW+AJgNqo0X3/+drm+ICBpgHRs/I01lKHxO6opKgJipgr87B5pPXr06NGjR48ePXr06NGjx68bPQHmHzmq9LhvIs1zF9a6AdkPrKa2TIMtIR+vVqNaqxN54DFC49soz66wqYcoJwb4izMNYmGPLx7aw/Vzl+jYLtt3TTNnK1x45wrSc9FljNP1ZXYNxnl4PI5pt7BnLmPvuZdrfoSL5xZwM4MMjh/l0KGHMPNzdFDJprIcL0tcJ8DIL+IffZzzqy1eOZ3HWy4x1DfFA184SObYc4xFVfLRAarpYdQv78YsFZlO5ZgyHbyL76G4LtsnJnFHx3izHaZeb+JZEZqepFUrEl1fYWcsQfPYBWq1DooQ6KqCqQpCIqDVtnEW5rBGxmnNXkMoCtrAMNWFBSKx7fiBRP+xaHVIv7PEymAyzOnl294CtzIOhKDecphfK/LFIY3ljuBKXdJyPK7N54mur38oEB5UyzSrFYyJaawHnsDVDdp3W7n9c8Cy29CoIVQVP5bEUT+emXWPfxiB7xMWfjf6Hny0ufjHQUrJWNIkYmg0HQ9dgXTEYL3WAeC+yTQX1+oYmoKhKRwaTSE+wmhGadYwIhEG9+/ELRXQdA018On7F79Pu1DgYniYF9+7CmaLQDcJtua4UBBsNFXyqy2KoTTDY3vJR8YpNF1mSi1ChYAdkyneuFHgxEKBnX1RtmTDbM9aeBGNYmDgK7dnge/7uDPXMKtl1mJDvHSjQDiTZbgvwQ8vrlNqFpDAWH+SwXiCw0cHOVvyUIXECQSBhAwuoVYV6TigffhR562toOndpfhavUpncx2EglsqELrvEZrPf7erYkmJbDWppEdZn2vhJyN4CARgqTCcDBO1dGaVMENf+29J19aRxY2bGSw5WuqdGSxCCOTqAgnNJ5yN0PEDRBCg+BrVRpuLJ8+h9u/gcifL/aNTjF48g3b4AbzenLyDH79H+YrGlZLDiYUytY6LpavsHoxzcCiKIbtZRilTIRU27ihh9j6mptAX7vrIdHzJcFhhIuKBL1FHM5yoq7wzs4nn+YRCGbanM1y2p9jPJbRUDvvcCYRpsarFsZ0KQjfw6jW0/iFQVAzLJDI2wHOOZOGNi/j1Ojt2TXP0//7/RGu3aAcBwoogLr6BK8FHoCsCx5cI30ULhWguzDG96x6uzayw3vYpJbeyko1R8FUurVSoltbJaT5fvHcf0+11jHNv3nFf8fKr6LpxS3wBMIVkMBllNdbH6vU5opkRak6AqioEQcCllTKbTY+v7EhifKDPVVXFW1uj4/goQsFQABmQKi4yPpBhIV9G8xz4QBbM9oE4SUPyM+rMPXr80tFUhacG77yHa5qLF9WIfXThyR49evTo0aNHjx49evS4g54A8xvAQNzgwW0DvDVbpBNJYUSaDIQEj4zF8U+/wUyxhesF9I1avFyNUdAnaLk+sqoSjYUptxy+v9Dmyf37mF0p0o6kqG2uonguaiqDb5gIIbiwVmc8E2VvVKe57wGem6mxvrmKPzzJatnl5bkF/kpR+PK+IS5sttlvmEz1mzTaHfToJH/+1nU81yWUTgGCpXyRb29W+Pq9nyOrBVyoGlw7sURk0kDFItuscsgM0alWEUKhc+o9FP0sjz31Zd6aL2O2arRUA4RLsDxHeGwvqgyIh3RUQCdADVxkq44eCaP5HqGRUcKT04hIlLoLeijcNdoeit9cTX27X9OWwta+OPWOS7llo6sK9U53Za+hKViqACFROm3UlSXKRQ13foP0xjqfOfog70b6afqCjlAJ3+3CIZGtBq6q4/4CxBdNStrvvUn77VcJOt1SamoyQ+iBx+nkBj9WSZ8enx4iwuMr+wZ5fabASrnNcMJCIjk6mmKz3kFVBBLBllzX2+GqEjCVMm8FpwGCICA6PMIWXUc2SvjXLtC+fhERjRM5+hDW/qNk1QS5sREK0mRgbJSzhQ7nFgrELJ2kqnF6sczptRoPjSZorBVJq4K920f5m3NrlGpNtmZCmMVVrs3VaQ1k+MLUbrLHXiCaHKLWzd1BUwRBq4FidzjdaDJftnliywh//94NHMdF1xSCQLJRbnBgNM3hgTD7+wRrLZ8mKmtNn1hMYhth9KEJbCHw/QDpuZh2C5o1tFwO1wqB6yJ9D2/rPjaj/RTaHpFYmJH//n8i8uazuLPXENEo9uA4pVKFjWIb1w8I6yqf3TXAmaUKC6Umw8kQ2ZDKtr4ED++ewMTrZg3+mFAghCBoNpFSoglJTBe4LZeZtTLezUw4w/dZ3azw96UaXzs4ynirjheK/jKH068ViqJwer3NO7PFW9s6rs/JxTKllsNTW1OogYeOx2e35/juhTydD5Tm1BTBZ3b0E1E8QJBrlthy8oc01laJWDobHcmWnfsoxMZ4fbHJyYUy16TN5w5sZa39AHq5hNp2UIVB2fYJhIoWSxJ4Hs7aCu7oFrZumeC5iytkZQez1WRoywSBGeH/9ewZslELq1EmPjlJMLiTpPEWumGgRBREp4MCeKqGGU+RS8f4wgO76BsZ5NxcjWurZdxWi1w6RyoSQ9ZrFIo19pav4/oSTyr4foCuKkQiEbyFmR/rPUk2E+eKK9GcDhlDEA2HiBkq2k2Rtun4NFxJ+uZvjL7QuFRwiK9sUC40EUDU1BmImxjz13lyb4Z3jBxzSHzAUBV2DcU5OhxD+i53Q1FVAgQq8la27UchhOjOo94zqscvGtdl5TvfvmOTYRg4jkP29771K2pUjx49evTo0aNHjx49ft34VAkwhUKBeDyOYdy9QLjjONRqNbLZ7C+5Zb+eKIrCWlvwo8srSAlbMhE0NUpmS5od7TUqL/+ApZtm1qnpLYiD97Hw5g1C4TB1RzCfLxKPhshETZqORy6bZHowxXvzRSpSJzOxDXQNF5VKy8NSAs4tFsnmBCt6hqLfgpFJNnyDmVIdIRRsX3Jho0EmpLG2tMaRWB+W73HWjdBJ5bACF6fT7pYAKhcJ/IB5L8R1LczF1SUSmQzt+VmMZJLlwgYb0SjPHLyX2vnTeHoI2/PxT5/ggS/9NtrKFYozc4TTJiGnRbIvh53rQ11eIGjUAAmGAYpC2hTog8MY8RTrr76AU6siTJPUE1/gid3T9A9ECYLbgSNfaOSbHo6EfNNlLBWlLxYiEzGxvYCxVBiFAM116CzN47ZscrkcwWYdu1aj8/IPOfL0l3ndTnPP1j2Is2/eNetE37kfW4gPBXH/oQghumbjx1+7Jb4A+JUizRe/S+SL36QVif9cz9njF4uUkqTq8uWdGaoOeFJgS4Ur+Rq+lCAUDgzHqXc8Fkt1HNei0vE5OhxF9W2Umxko5vg42toCzTPv4uRXMfcewRoYonPiLarH3sTsH+H+qX1U9j7AnAhx7vImUkK945LLxkAERO0Wx2YcnhgKEU4neX6ugKEKpgdSpDplGpubSFWj5vgsx1JMAawtYsVjdGo1LE0B3aBjxbi4VMMLAvJNl5YeQhUawnOIhXW+dXScSbvAm6dXuDDXzSRTDYPI2DjlvgmiOw5w4c03sTs2EV0hFbJwpaQ/Fyd15CFqbndOV2J9fLeywMaNpVv9qRs6X33060zfW0REomi6QbPj4PndoO/+0RQ/vJSn2XbQfAe9E+AVilyspmnaHsmIQV/EYCxhdL2jbhIEAWq279ZrIQSVjndLfNFCIVo3a5x5fsB7K3XGJkd+gSPn15+Gr3JysXzHNgFETI2Nmk2pI8kZ3TmSMwO+eXCIparNeq1DMmwwkbJI6gEyCAg5bTov/h1apYKuClwvoNVo0XrvHR64T+Vasp+wLthoKpzbtJkem6by/EUGx6fx5m+QHh7EdhKsdTw8JSCTGWYkFWGjWKVRqtAfloTSGdLJKN8+sYAvJZ4UjCgKM+cu0Zkc5yuPfwXrxW9jhVJYkVDX40wRZMM6QSmPd/YkC6dUtkzvYtv+fZypBiy3JNWWR6ha5r3VJpPbBlCr80QMDV0RVDsuat8EVunUh/pP+h5hDUK6gm6peMrNtLwPoCnd8m3vi13vzpf4XCrX/TxQt12cUsBkJoR5/hhPDo7SfuSLNIWGpQlimiS4m/iiqGx04NxqjUrLJR0x2DsYo8/iw+UDFZWKI1iqdOh4AUMJi76wgi57Jc169OjRo0ePHj169OjRo8enl0+VAPNv/s2/4d/+23/LQw89dNf9J06c4D//5//MX/7lX/6SW/brSd1Xee7i6q2VvtfXq7f21fozbL/vCeLredITkyjrSyzemEHmV6j4EtMKsSU3yFxboms+j27JcXK5ggyg3HQ4PN2P3emw3PRZqnY42BdihywTXb6B34xx2svR0COo5TIinMbQVAIpcf2A5UqH+wfTqLkIf3tqkQHaXCXOUr6MbhqMpWIITcdQBF6lhEilOb9YJpFL4+RXcXzQW038VhNbUehsGYXAxwtFiJgGcb+NUSnwvQ3B/Xv207xwluX4EBfyLR44cj+bs9eRgY+mKkjPJdeXIRa00AaGqfzX/w3DDGGYOmosirI8w7D0IfsFAl1DlT4uKq/NVbm63jXc9lG4nK+xUe/w5X1DPH9pDZUABAS1CiLwURXB7oxF48I6HTfA9QP842+jHvoc7pad6KUVnMXZO66fMb0dOTLxCykHpvse9tn37uqFLB0Hb/Yqyv57eyuMfx3xPRI3q+MJRSUznuT4UpU5OiyVmmzrixJIgwtrVU4u16i0HB4YMOlbuYbsNPFzw8honMpaHhFJEsoNUP7Rd9F0jcAI4awtYxkhlEqNgce/BqqGoqrdcappRIMWZq3I1O6drKoaXtHm5EIRRVWJhS2cANK5ftxSEcd2WYxY7OvPYV+5iDmeRDM0VAGhex7mWNukL6oiXRenbSNaTaQQqJbF00cmSeSvcrItOHZ5BVUR+IHE8ALk3CzfdyVf3X+I5qnzuO0Cdsej2vGZyMWo7T2Knh1Fw0eoKq/O1igrYZJxjyCQ1Bstdo/ncM6dorB2HUVVacUGOJTewTVhsuZ0S7nVmjayUSdkaagth0qpirtZoVWp8vQj+3nh6jrZiMmXdvcR+oAII/sGUWNJ/HqlK155t+d4dN9h3txs3nqdr7ZpaNan62H9KaNq+11z95vsTOpMyRqsLYGqEquA3pfFpSvCRITLzpTK7kwMKSVB4CGD98vDLeE3GwxENTYqDqu1DrguIGmePcHXPv8t/u7SBo7UuJqv0BgZQLvvMVLDaRonYriKTqnWotLoYIUtVKeNKNRZCGVIGApGo0huIMOZ1fpNYRRatosfM5BBnUbb5kxT57NDw7RbHrObdVqOz56EgpjcRWdxDmNiC5t907y3XKV1/DrZbVuZHozTWKngpvuIKRsEoQgLpTbbs2ECAbkHHqbUchkZmUSdvcIHpQ3ZbjERFrwbCoHnoarg3yzb50oFU1NouNBRDQxVodhsoAhYD2dJptJ0yiUAbN+n5QbEdDD6BxCWinVTRLmLFRNCUbhccnnl6satUmkb9Q7X1ms8uaOfbQnl9vNPUblYcHjjxk0fNQGeVEhHDJ7Z2U9cDbB+zPOnR49fJHcrT/Y+v4jyZIqi0PLvPr4NVdzKWOvRo0ePHj169OjRo8enj1+rmI7nebdWaff4yQghWK7Yd5RZ+SAn8y0Ym2RTGeCe1SuUjr1N6KHPoGkqNdvBtDsMywZ7tk9ihEz+j/eWGEmGSOuSjWKVS9eWeGzXIBEEh/ss9q6dZeOdt7DiFrVsBje5G6fWITwyhtVqETKsboBFgqFpRGNRXjl1HXtpgeRwFsOQKNEobsdmudph3PBwjTChHSP48TQyIQgKq7Q8UDQVhEAKQdBs0PEl409/jhlbJ9+0sQ2FwWiccnmezb4hRHyZ5XAfb85sMrW/n4O//XUq77xBUNokZihE+7NE7n+M8l/+F7wgwFdUZDKDms6y1vSonb1MZGQ3J4Ik90+mcYPglvgCoBIQ0aBjO9iOwxPbshybLeD4EtlsEA2bPL47hzh/jHrbJbgZUGptbjKk+ZyrBNx3/zMkdq7hLc4ghII6Po2f7sP+BY131bHpVMoYlnnX/X5+BeWg0gtmfcoRQoCi4gegKZLA91GU29dNBj4BHvlKi2zEYjCiMV/ucHalAkDCULh07hoL79b40t5BMhfPIbzTmLEoRjqLuXUnnZPvdL1RPB/VUpCej64IapubDLc2MXQV1w/QFEEsZGDkl9FVMFWFKxtVdg8lycVM3I6D6tnUmy1i6Qhho4LqtElmBglNbEUuzaFJHy0exzpwFP/+z3L8Uo3Ht2R56dp1kqMDSK8rYoxlQqiNKl6ryamFrs+NBAIpcbyAkB7gVyq8tpRk4MEvM9beQM0voZgm7amtFMMZihWH3WmNmqsgBGzZMcXyZg3hORwYSjO6cYP5d9/Dy8SImoLa3CxH+obw3RBBKEm15SLbTSxDYziqI4t5mraPBNyNTTSnQ9WWSOlwId/gvuHwrdJKHd0k/NSXsd95BS+/iqrrqKEwsb0HmI0OUVq6XUrLzOaQugFBz2/go3g/OwPgSEYnd/51arM3bm2LXz9L/PAh9P334IruPVXKD5e6UhQFfzOPKgTK5ip9ZpiaqeFLiQBUu0ncrqCZJm47IB0Ls7BWQvgh1JNn8Pc/zlsnrvHMjnFen6+gaCrO2hJeX4JsNIS5uQq+j2nqbBRb3TQdBEJREIGPAMrrGxSG92IfeJDC8y90vWn6sqS2TbK8VqTaUaiPT/H2uRWajocAqtcXmNNT/O7hMdpunEI9xUJIMPo7/wy/Xce3QvzxikvzwhUe3pLj/v5RlPwigeh6GSnVEskzr/HQvV/jteMXkaqKlhugHkpSbts8vXuIH13Z4MJaDUURTGcj7OhPMVdvcvCxLxI9+RqNpUWQko6i0XfgEHLXwQ89Pz54b4Ju5tKbN/If8r8KJLxxo8DwoSHCN4XLoi14/fomUgBCULYDNmpNrm40sD3JQERlz1CCiZiC7D23evwyuEt5svf5RZQnc33Js5c27rrvK7v70NS77urRo0ePHj169OjRo8engF+5ANNqtWi1Wrde1+t1CoXCh97XbDZ5++23SSaTv8TW/foihKDYcrpCBTfjPB/IpPBk94+5MdWhfv4kAMriDbYMb2Wj5TM0NsSFfJ2kInj9RpGxVBhTBNQqdfriYZqe5J3FKl85OMZ4fZX1d95EVxSiukJhcZltU4eYW9nEqFdJhMLsqGzgKipBJMHAQAJfSuyNdRQhWForsPPQIDfyFaRh4Gg65GKY7QbNZotcREdFIloN4hq4vosaSSJLAsW0UAaG+YsX3qKmmNiexAyZiIbFg4f3caPlMPHwF/jB8UWIRLm+XiNy4T36hsfpP3SYWDREY6NAZ2MNoSjoY1O0jBgdRWN1o4WhChQpUQrr1ITCCenjqHcvkQdwcrHE7x0eZjI5TNUOUPp84sVlzIV3mauV7wg0xWNRkgMJnl+o0rRDfH7bKMrgKADOT6mB/w8lUFUUy+KjrN+VWPwfZArf4xdPIDQWGx5nl4u0XZ9cLMyWvihN20EoCumQQVyXJKoF7s+fRjTrOAcf4r1ipeuxIiXJoINT3MSyVN5aqPK5wUmqVy8zHJFovosajtIul1EECATCd1F1Eykhhke8tMqYNUyx7TOQiZPSAtwgYGhynKsbNfTNVSrVZfb3jXNqrgmqgvBcyvU2KcuEepUtpkOj3sB87PNYW3bg6CZiZJzrtoGutUiszfL4WISSIUiaKvVWh4lcHNFp4wuVaqNzK/tF3Lzf2Z6P7nYotxxmmg7PtiJkovuwVEHpaod/sl+yvlHhaCJOSZhcyDeYKXSzTgIJV4urHDEl07v3Yi/PEjPBsx3qb7/KgfFpjjz8NAUlxNqSAc06arFIrf2BDBcEer2MH2g0PcnlfJ39gxEsVcUJBIqATjSB+uSXiTSqjLRcrpQd3l4sUFja7B5EVVHTWbZvHcUSPj3f8o8mZSokwwauHzC4foPKB8QXBUFIF3TOnyQyMII78NHl3DTfQ9V0vNVFZKOGHg/IWknsRgfXCxCqQqfZIa0amHGTe4aiFJeXODIYpTNT48SVZaq2z6Vr8xwZG2T7YIJm2iYUuHgpyYsXqkgJrucTtXTKTbvb/oiBaJbwJYRNHWGYvG2Noz/6VWKmipmIcvVH36WazxN/9CnevrqKIkAVAl9K/GaD/uF+nr+6wVQmwrXNJhekJJCSyXSaezIxTi9dZFsyyQvnFkncv5ujW7fRvnEZpV5DpNIo/cPsWjpJ7uAWrlVcarZNdjhENDXIsxdWmdvslisNEFxcqzO72eCZXQO8vuEyvPczTB7ooPouof4MXjZxS9wSQtAKNFYbDrV2t+TbYFQnJDyKTQ/nI1b0d1yfUtsjHAJVVZldqaO0GshOC0/REYpJxNAI41EplvjsyBCXl0tEp3Jk9H+4ACNUjaoDbiAJ6QrRXnZNjx49evTo0aNHjx49evT4GfmVCzDPPfcc3/727RVkf/Inf8Kf/MmffOT7v/nNb/4SWvXrjxQKEctkqergeAGGppCJGIQ1QEqiusDSFQY0Df/+x6j7Ch3f57GxAV7flPzdiTmkhKnRHPOlJmFdZTCqkUwnKJfr5FIxCi0PFwVl/iqJkEEmrFMolHE9n3R1jdGBFPn1dayxEdxalYbtEQlVeXJXioVWB7djk7RUmo0WnXKJPSMpLq43CBwbu+LhrOfJpqNkNueZkB4rikJgt4jEkyi6jj46jhFPENg2HcfDN008CXp2gLWO4KWlBl/aPUhfp8j/eX+aRd+krIaITU7hlvJ0KuvYF96j3nbIPfE09sxVjIFh/GwMP5AkdYiqAZ2ODb6HszKD7OTIWxkUVeFu4oXnS3wJSWySukSLQOON9xBCwdIUpjIR/ECiCEH44AFezNvYXsBqpU3LT99RpugfiqIoqIAU4pa/xK12WmHM7Xvh6rm7fFKgb9tNy+vV1b8b7wfmaraPriqkLYGB/wspFfdRSEXjnaUGZ5crANiB4NhiHnkRPr97gAsrFeKmwu+Ymyy88yqu7UE0xvUbi7BUYGhkgjIGFPNYukrbldxYK7O5r596vcPwjhyy3UQzdFAUgsBHEQLpeST6+6goKqJRwncddqZNZjZsUpU1/GQaEY5CtURIiWK3WpSUCHvSBsu1BJudAAwDP5AEhsb+7WM4Vy5wI18hYUvc/cO8WQjILNo8NB1jKGpgnz7JYLPEyNAoww8+wAuzVTKJKI2Sw6Brk4qFaLZtgptZCkLc9KowTRJhg5VKh7brs1hqkTYVlFaDoGoSblXovPYO89ufoNVoMWSCJxRW2wGaDDh5bZWRg1sYKi9jVgtotofX8umcPUUqniB96GGUQh7bcZCWcSuzDWByMIVayKMoo2w2HLJhnZavcXypzGKphaoIdg7E2ZENYUYTENfINyuU4wI9lEAG3XJu6WSUPYMx/I8wLu/RRcfjyW05Zpc36Zy8fU8TwGAihCG618a9fAZteOyWj88HMQKP4L03u1kwtQqyViWolImPbaEcDtGq1Ylt28l7lTYJTaPPLTJdrhKeHCDaqeFl02zvjzNgKZRrDW6cPs/uVoq+Yp6+rdOIkMfmfQe5eGWBTUdwYDjBUrFJyDJIKx6u66IrAj+aZOdggj99+QLVZptAwlM7+zmITyRk0lRNgkAikEQMFdsLQNNQVYX5YouHpzMslFqs1zu0HY96x+PwWIqJXAzpOyjAy2cXGPvMPnKf/238E2/izN3Av3IegOzKPAPJNFVfpXF1ncs7H2Gp3LnVTwqShuOTCFm8O19i32CM2WKDWRRUxeJ3tibx/e6zQwjBuq3w3MVV2o6PdlMoDZsaX9ozgOQnP2Pen1Iht0N1YQFvZeWm34yPoQiGs1nq1TqtdhsvWmP70gxB6rPIoRyq9Al+xoUMTanz2rUSi8UmgQRLV9k/nOTAQAi15zfTo0ePHj169OjRo0ePHj0+Ib9yAWb//v1YloWUkj/7sz/jwQcfZHJy8o73CCEwTZOpqSmmp6c/8Tmef/55nn/+eTY3uyuLR0ZG+MY3vsHBgwd/Lt/h04ZQFC4XHSpNFy8I6Hg+Hc+n1nEZSoRIWYLdg3F2DyZ4c8blrXlQCAiJgPujPtc3mkxmo3h+QDxkoKsKHc+n0AICyUa5jlprkohHyYQNhkzJpiHYWC/eWiFaP3mcx+59iHxugBU9jFKPsjMRYmtYsvIX/zuj/6d/TdQycD0XVVG4fGWenTsm+MbhMWZWigxEDQYHdKzSGvLl73LfniO8OTpI0TTxipt4G2uEU0menIqjXHqHRw9v5/tzNYxklplGgKVJLNcm19yg9pf/G9L32TE5jXrv47hb9zA469J89iUsvVuOxi4W0YfGcBp1knadji+xCxtgd0glEoSH+kjWSpQrVQbHU6y0vG5w+scYienElq/jnX4H6ftoe48Q2neE8tnTqKqC4/m0bA9jZIyN3FYKhe4KaEURiJ9TzokQAqvVIJi/hrcwgzAsQjv24A+M4CjdKe/7PsbOfajNGly7dPvDikL4yIM4mf6PSo75jcZVdI4v1Li4VsMPuh2UCOl8Zkcfg5b8pa2QLtlw7qb4EiBYrnbwpSRs6JxerrJnIMF2pU7p+VcxCQjrCi3ZvaTS91E218iOTqIrkqbj40uJlOD4EscPOH1hjiOf+zpuYZ3Q1h3YM1dRTBNCEbRkktT6POF4gsjoCF9ubrCa8jm7VsepOAxPjbOLCmdbcC0Uwi6XOf3WCR7cvRUnkmCx1c2UeSTawTl9jNrsDFoqg//AZ3l53aPjdu9VB0dTbM1F0KSPurmKc+UsmeImDx36DI7icNWIYJk6hyZSvHlxCVN2RTAhIGJZBOEoW2MKC2rAuh+gCwhcl625KNVSmb05Hb9/B5fPXCK0WaFp+6iaxmgygxaO0xSCq8U2u6NhWjfyDPcPs1Jug/RB1VhaL/GVo1O8cn6RWstGVxX8wGcgE+O+rEbDsNgs2gSBJBML8fbsJvOlJr5U8CVszJS4sWnwpV05jMDl8akkO/rjXNmo4waSbbkIo3EDQ/bEl5+GlJLBkKR/JEZRh7qpY2gKyZCOpcpbkfyg3UL9iDmqbqzSvHYRN5Ei8uQXaTz71+A6qMszjE/upDU4zeaOg7QvL3PkwChTqkGitk7njefIPfgwdmMTlmZY2qwxNjTIPUePMJyJohsere/+GV5+hQce/Axb9zzENS9ELBPjt45OcmV2Bb9aAUUlkkywZfsYCU12S/6pKgQBJwsOh7bsovnOWwR+gB9IfMBUIKIJrIE+rrdtEqoEP2Ct3KDpdzNtBILvnF3ha/vGOX3mKm1NASlpOx7SsXHmruPXa3f0hV8tU6u7MGywXGp+qK8sTUVVFJYrbR6YTHf7TxE8ub2PhBbcenZ0pMbzl/NsiyqM+A1EvYqIhNm0Urx6vcAT2/tvZfH8OJoiSFkqmvCx33uLIaufqzf3KQI0u4U9d4Pw2BRCE1CrUJiZw25+h+bnfpslR7BvMEZS+2QijCN0vndhnVLzdsm/jutzfL6IJM09g1YvE6ZHjx49evTo0aNHjx49enwifuUCzLZt29i2bRsAtm1z7733MjY29nM9Rzqd5lvf+haDg4NIKXnttdf4j//xP/If/+N/ZHR09Od6rk8DDV/lzZk8mqLwxd2DvHB1nXKrG8TbaHQ4NNrPrsEkr88U+P7FdWTHx+vYaKrCXsVidn2F8biJu76Ms32EsK7i+oKW4yGN7upy3w+oVuso0sdN5mj4CurNrJAgkKiKQu3VH7Ln6EGO7thLJVHHXb9OOb9OVhfk6hsMTQwzc/kGYUNDR2GlUGNz7TT3benjcOMG1y7P0G7bJAwH8crf8I1/+n9hLR5nM9QirMfpa6zjv/E9lmsOCaGTmLiH4wtlZOCzJW4QLM7DyCTxZAJfUQjqNUo/+A7pL32DZrFIdHAQGlU04WEXN0k8/jncl55D5pdRogmCThtFCKyjD7Pw3Pd44OhDPL/ikzOg1nSxpUogbnu0GAQc1hvYr/4AAh+RSHGlpTDTiDN57+fw15ZxbIf+rVtY1OIcX2vf+uzWXIyIKvH9roCiIRGeT6DreJ8w2BOqV2j98G8J2rdL+zkrC5jTOzDuewxH6RYK72gGfU9/lWDrbvz1FYRuoAwMY8eS+D3x5UMoisLZtSbnVqp3bK+2XZ49v8Y3Dw0TFb/4wJyiKCxW2rf0MSfoltxKRSxmC01uFBpMZyLU8guU81V29sewXY9cyEOkQ5zXVDqtFiHPwzNDuNVuaaH+dBw3v0oipDO/XuDq0CCRA08wuO9e3B/9La7tYoRDyFqBoFIiceg+2n/zX9BXFpgMhZmY2gHpPiJahOZmgf3juzh55iqO6wGCY6eukIxH6E9Heebh/cSXrzMXT5H47Jcop4d5py7u8KxaLrc4OhqD3TupXDyOalpUd9/Heq2DbEt2DvVTTu5gV2mB+kSGi3Pr+J6Hqmukhwd5aM8g756+TqTcYjw5RL5hE9bgyEicnCMZaK3RqCs0louoKGiKge04ePk1EvjEclmUIMBrNdGQqKUNptI5qhi4Q6PIep1tYwnik2EKag7Hl1gKKBsrtK/NsXzwSRyvQzZqMJEO89bMOsV2QKHRwQsCVEVQbLnsHk6yMyFQpcdIGCa2JABulnDyumUkf4nZVb+uBEGAbur0D/eRVlYBiZRdMUD1PbA7GJNbUTtNAit6R9Bf0zTcmxkgQbWM43tEnv4qstVA2h2UdJZoth8uHuPriRTU5jHtJq2XniV+4CjOOy/ROvUuVm4A3dWRrktfzERZX6H58vcJykVUVSV452Xix17j0cP3E3rsGSrjg0zHxsg3h1AiUSKxCCFN4Z13z7NrKMnx2U2MkEm+4XJlaIyJkQUUxcfUFGqdrv9LKBGlY9v4jQ7hSJhypY7SbhCLxGigoipQb7vMlVpMZCLMlxU0VSGSiOMJFSUc/ZAAI6UkpKs4VhjtLsYShgLpkEbcjDAQt0iHsowmrZviy+17YLHtczTmo731I2ob+VvbI9Eohx//AkL0c3AsyYmF8ofOcWQ8TUyT6I0azZkrjO9OEg6ZNNs2JpLAcbrCmt3mvq39lN96gZbrYRQKpKqbXCiZXN9o8LV9g6T1jy/CrDe9O8QX6Ao+AGeXK+zqGyb8ce/zqkbdBV9CRANTBD3x5ldEDIenBj+8aAZA+wWsNtFU5SPPF6Pn59WjR48ePXr06NGjx28av3IB5oP89m//9i/kuEeOHLnj9e/+7u/y/PPPc/369X+UAkyp7eF4AQ4BMxtVHt+SRSgKXhBgaio7+qNcXKtwfK6EQGJGI+iWgQx8Wq6Po+iUHUn/5CTXyjZf2DPIcxfW8DyBZRkM9KfxPI9dA3FubNRIZSdIps6y6fsojo3muygKxOJR0tt3cvbFl1BaDZrNNoau4QYBhTOneOTRz5GKWqysbuK5PkbIYFciwdbaIleuz9K3exedeBYbH23mEsrKLP0XTjLk+9iKRlsqYIbwVUl99gZHpw9yUlNJmjqhVhk9pBM0a2y2PGq2h6oqDMYs+hfO4yeS5M0UQ5kcfssl3/JYOXOZ3Y8+jSxuEFIEpg/kBijMzWPhE5x7l227H8arlfjGWIKTQZTrpTZ+IBlIhHkwo5B96++RgQ8IilsO8/2zywSux7X1GKHhCdaEZO2yzVf3h1CUDn4gSYR0Dgx3ywwZQYC6toBz4TRBp42a6SO8+wCddI7gY8QINEXgnD52h/jyPvbMFSJbdkDf8K1tajhCO9MPmf5b26x2EyolCDxEPIUTS+L1AsA0A+VD4sv72F7AYqXD7rT2SwmWf/AcfiCJGBrrdZuOd9N3QRFIu4OUsFRpM5YM4fs+yeISE4MpriwVCHyPthnHCTYxVcH9E0karx3HC1xGUiGaw1v5L2fLYLf5woPfZIfSJFxaxhQBISFovvcmnaX5bumvRgNx/iRmMoUXjSAOP0rhb7/NMwce4q25EsVyrVs2SdU4OBQnO3OWcmaYlYxGPdbHfNnH/7HAZMTUsF2J3H4I45kaRijM636ct2fzoGloiw2mxweITexm/6jH9AFJ2NSJKRK1vEG9tMG+/duYajtUXUlb0dmfVMmVl0lU57By/djnTtPXv43FtSKWBqquIoQgqJaJTU0zIqpoV9epux6BZmHuPIS/4wjFWput2RBKKERfNsXQ9fMsrmwSMnU6o1uZm/wsry22mc5G+NqBEY7PbZBveBQb9h3XrdCweX2mxK57B5FOd5/neegyIFQt4edXQAjUgRGceApPCHp8NC4Q3ncUZ+3v4WZJOqVRw1tfRaga4rBF/W/+FGvXAdR9R25lBCIl0r59bdxGHVnYIKhXEbqBnL+B3H0YbXOV0L7DNOtN2u++gSdBC1nY545jDI3grC0z+qV/xpnQEOrFS/Rh06g1MPQQEdNCOh0UzcTZWGPltde5evjznKl0Xdpq6zU0vYnmdphKZ5mIWJRcyVzFJnB8Xlxz+MrRp3ggJXk4nuOd63lcM4Kna1BcJ2wmOTqd4+TVZTS6Hk6BbtLoOOzqT7OyXmY4oyPqVXbu20afKWgqCuaeQ7jrqx/qy6ipUhydZCgahqU7BZpM1MQQkt2DUXalNXwfpPQ+lDVp4mOfeIXGB8QXAKfRgFeewxz+lxwejJIKGZxaqtCwXWKWzuHRFJNJDRl44Hng+4SvnOCrex/i1aUmq6sFbCkJhy3u395PYn2exVq3jamwTqewgWGM03F93l2s8LmtqY81fhRFYb1+u9xaJmoykAjTdgMCIGqo2AGEf4rZuRCCmq/xxsztMmaJkM69E2mmExpC9hydftkI12HlO9++676Bb/0CShu77keeL/t73/r5n69Hjx49evTo0aNHjx6faj5VAgxAo9HgrbfeYn19nWaz+aFgphCC3//93/+Zjx8EAe+88w62bd/KvPnHxge7rOP6XM1XQQjsABq2T9jUSUVD3aBA2MD2JCUXpFSxLBM1FKapwJWOYH2jhCIEv31ohJOLZQLfp4Xg3i0DDKUinJrJ8yczJf7Hp76Mefx16vk8uiLpy6UIT27lxskzpA2FzYqLIgSO1w3SxMYn6Jw/zgONEsrAKB3HIxJS6EtHKJ6u0r73M/zNcpXN2Q18GbBzcCtfDfsUWj6EIhTWN/Edl2gihlQtbMcl5neYzEbpMwVyfpnpwRR6p074kaeIKAqm3cS/eo720iL9hw/TxKfiaMTDBk0fHM+hdfx1rMEhWuM7uH7hGqXz8wjpo0jJQEKyvS+K5XWInXyZZ37rn3HPZAYJxHSB+OG3cWsVANRsjrOFDkG7g+y08DttWlISUTQGw0murdfYPZQkFdKYSlmEhNudjGeP0bxw+tb182sVnIUbRB7/PJ3hiZ8a3NdbDZpLcx+537txGW1oHO/H/F2klCgCzKVZWm+/grRvBqEUBWvHXsyD92MrPyXq9AlRlG720K/LimDb544MjR9no26zN2vcMp/+RREEASPJ0K3XuiowNJV6p3vN+mImhbrN6E1RTQBt1yceMlg+d47Duw8wtHecCyLKesXh6NF97NNb+MdeRvVcvHCYxH0PUcuN8EjE7go8uSRXN9ZJDybYFvLh2b/AXc8juV06TwpB2wsIDY5SrDepLi1jlr7L5/YdwN86judL1HIB+c7LBId2E730HqP5El4kzq5dBzkrsszWXRQkW3JR6i78yck1Km2XofBuRjJRLs+VkLEk5Y6HLjTWajb/n3cWeGo6ybmzV9Bdh/T0JCOax6l3z6KPTdPp2BzeOc4zE1GC7/7/0FIZdE3DvnKB9hsvcvjr21iaa6EqCs1ARdc0mq6H5frs2DOO5j1IuFalvPsBvne9ROO9OY5OZPDnLzC/OEvYUDH6B5k4fIBy/xRzIs5A2OSfD3Y9OgaiOg07uGW4/uO0bI+GC+Gbr83AI3j3DRrXP1AaEIG19xD6/qO44uc7D/+xYeeGiDz2NJ0TbyEKG7hry2j9g1hHH6K1MAe+T+f8ScKJJGJqJ/KmWb0+Po27sQZ05wx0g7ZBtYw+sQXjwD2sHXiSv7uxyUQyzdb7nyJ59SRybQnb8WgXSiQOPcg7fhxRraE268hOGQWJ23GoGwZWKEatZROuN6iKArLdIl8TuO02LddnaCjHlc02924ZIF9t8uD2Qb4QDVFs2OiaQtMJ+J9Pr7F/OMG99+5jvlDHa7dJh3N8YWKA1+bKbFRbGJoKnkPYstAVg8PDUV47sQKZHDv37+Ch0Si17/wZkae+gjs0SujgvbTPnoDg5r1LVYkfuAd/63aUfIujYynemd1EEYJMxCBtqURNjXvHknjeR5fIy9pVVpeX7rrPbTSIVDbxIxbbkgpTqT4cH0xVokq/K74A0gqhhMIE7RaJM6/xlaFx6gcHaVVDGLUSidoipy5cQAjBYNzC8Xz0UBjP7d6XFktNmv7HE2Ck7IrZ0PUOkorK355dxbu5+kFVBMrBEe4fCaEGH+0F05Ia3zmfp9653TfVtsvzl9d5etcAW+K9rLYePXr06NGjR48ePXr0+E3iUyXAnDlzhv/lf/lfsG2bUChEJBL50HvEz7gCeHFxkT/8wz/EdV0sy+IP/uAPGBkZuet7XdfFdW//4SyEIBQK3XH+n7UdvwxSYQ1NEbeCBghBueOzVu2gqYJK2+Fy3iZAEASy60sQdIMLb8+V2DecZKbQpFDrEAAL5TYLpTaf391PsWlTMFXeniuxfiHP0zv6WduscN6LsjhwhJ3TAQQBciBHurKGabeQQhBNJlCQ1GsNjEwWK2Sy+KO3GExFsE68AbZDPQjQJyYoPfNPefm1i7QDcG6aJV9dKbIyMEI4FufyUpGYFUJxHFpuQCasYAQKhCz0gk0xUHh69wSDMZPnzy+yen2VwHEwDZ2DU4eIRyWVqf2UmyrSCKFakrHlq4jFWYKmgxid5tKLr6KoCnHTouUpCCSVtst4Ior2+muYu/bjajqRm0EYVXaNyt/HiyQpNF2cZJYmGq6EcDSCVSsSW7pK2NjCA/eOoAVOd+UwAqNaonHhzIcvaBDQefd1zC8OYevGT7z2AuAuBtPvIz0PIcStf93h0f3fqpZovPb87SDc++e+dJZwPIm6Y//PRSwxPQexmcdfW0ZYFurIBE48zc8qW3yc+frBn3/WuWuqAkNTcLy790E6bPyDjv9JyFkKOwfiXM7XMFTQVQUhQFcUHprK8uaNAiIT5ujUJM7KIqqAsNOiz6nAmdfpf+ILtJPDDGXjnFosUTZ07r3/KUwBRanz0mqTrVqDnVqbohph5r13Oaq3aF84xUomw2j/EMGVc1jRMHazjQx8FCuEN76ViiupSY1QyGQooqJeOYF35k2wQrSNCLWOR0dotDYKxPFZWFyiM7vA9NEHuKRPoGkajlT4/oU8hUYHCYxNpXnuSgE7kIQti6TuY2kqV9brBL5HxUkQrpdo5MZ4+9o6u6aHSe8/zHzdw4xaXM7XGOpLsmXLXjb7JinMzxPdtY+or9F36kW+ePQZXpkt49sBNddl23CORw+OoLaqnD11kcwDj/B3x2+ghMIMhjVG5s5QO/Me0jAxUkmGGhtweZ2E52GMHuaHV/IoEkwV+mIWh8bSXN1o0HI+PMq39UVZr9tMxbpzUpmboX2H+AIg6Zw/SaR/CG9o/GOPk0/j8+rjztcPvv4k7Q8Ae2wLoeFxxLWLGJViVwCfu450bpf+sc+fwhjfiqN2s9bUiS0oF08j2y2UegV3bQUvAAeBtWUvr//vf0H8wBFK1gTFosul2Sr/5N7PYp57g7rj4wcem/3TnJ9ZY/tIlsB1UKJxbqaH4AUS15f4gURoGrFkDHUgzXZd0h8foNCwyTdcPrtnmNmaw0tXizheAdPQeGbnALmowZ8en2c8qnLj/GVuNOvs3jLMY5Mp+uZmkLaAiT7Wyi3y1TYqsKcvwpNjEazrZ9k9rDAxEoLVdZxXX0EC9sm3UT/7Vfx99xCd3IYsFUCASOdwInHCSB6ZTFD1NY6OJ7m2UUcGkm3ZMONJk7BwuS1XfRjLs4noKk3nw2JFzNLR23WkoiClRJMeWreK6R3X3A1FsPYcovXem+B7sDRDYmmG+PI8gW6i3P8kQ2ENEdFoOy6OqtOKZPFLHxY4Ps44GkmYmKpCImLxN2dW7vw+usq55TJDMZ0tCeWuIooQgqWyc4f48kGOz5cY39+PzkcLOHfj0ziXe/To0aNHjx49evTo0aPHx+NTJcD86Z/+Kclkkj/4gz/4ufvADA0N8Z/+03+i1Wpx7Ngx/uiP/oh//+///V1FmL/7u7/j29++XTpgcnKS//Af/gO5XO7WtoGBgZ9r+36e5IKAh3dIjs+XAKh1XDaaNqqm8fCWLIW6w9X1Olv6ory7UCJiaNTtbjDg+maDgYTFNw+Ncny+SLHlMJywiFsGM4UGp1dq1NouhqbQ8eG12RL/4vA0ixcuk7cFC/UQIPj6dJLztsLYvU9inz5GvbqBjcL0vfdj7TpA/offJZuMoMmAaC6HX6sihEAOT3J8rYkRj1EpVBECNMtCz/ZRS2QJReIM5XyEgMDSaVVrFFfzZPfup2GF+dZEBzMeJ6op/H+//y7tZhs8FwE4jsvJ1SY8cJD8mVVadR2vuIamqRwe38KhfofIfY9y7dgJAs8l8EBxXSwrAoog05fl0kaT+/YfJX7wKGoyfUe/t/ccpF2vACAjYaTZz8zFRYKggzAtZLOKqWqM54Yx6yXieMQ/MI5aC9cIh0PcFd8jGrikB39y8DXotBHjk/ib+bvuD+/ah/WBcQy3x3Lj4knClnnXz4mZK2QP3osaT/zE838U8uYqab9Sovnyj/BLm7zvnhNcPkvs6ENYh+5H6Hevmf6T+Djz9YP8rHM3kJIDEy4XVmsf2qcpgt2jWfpT4bt88hfDlxJJpvI1zq1UCFsOEUtjSy7KsbkSDcfnQkVhz72fYXD+LNmlSzgL1/DNKJFD97G2us5UbJBaZpimE+fyWo3vl7pCo9WsEGuWeXAkwFIkbx+7wmen4pS//wOEquH6kuFDT2FWSngXTmGELDzNQGzdgzexg/zsEp3HDrBj/06qb75My+36mARSYBkaifEpnFiG9VqbsKEylglTa3tUz73HF764hcTQEH97/AZmq824oeGZYVJRi4A6QRAQSFiuOYyluv4UHdtmteEwODzASkfBDUV5d77El/cOUFjbQLoOoXiCMgbft7ay8sopgnoVpc9Fr4R45uhnyb3zHF8ansabmKJlRPAL69itNiIUY+ThR1j1DYRhIYubbN+ao378DJ5Q8B2XcqHIYFQnMTTI6VA/526skklmcIMA2wvYaPkUFis8srWPF69u3nENx1IhoiGTaCTM4GCSoNWk2ayR2Lm3K5aaFkG9ems+q7NXGdh/GKF9snnyaXpefdL5Cj9b+6XvUXv9h1DYQAVCmgbazV95NA0lnSUSiaCnbt/HI1//PdpvvULzjedBgpcZIHr0AU6fu4EvoXzqPY5+bpzv5eHo1i3MhrNMPP4NRCiDdu44DdWk0y6xVGqxY3QKKRyEoiBVFS+QaEGAruswOEZ1YJo/vlBhvtjGMDS298d4cmsf7y1XKDZsggAMXWEwEeL4QolsxOCxrVnyFy9heDaxeITFlQJXFIfUOy+jzlxh+smv8sW9g9R8hfGESejaacp/9Q6ddpvxVIjg7b/HOvogxvAoQbkItTIxVaD3DcBd+tjzA04slXnzxjpuEJAJGxi6AqrOUDZFyPjJ2Vhu4DLZn2C13KLecekWWxMkQhpDiRCR/gHSH+Pa+rGHsUwD+8LpW6X6lCMPoA2P41y/RDKis1Ruo5oWycc/x5tBlHC4K3ZOZsOM92eAjzeO+qXktxSDvzq9jGXo+IFEAoaqMJ4JEzY0LhU6HJ4c/8jv/9rqEuHw3Z8FDqBaUQaTH/Gs/yl8muZyjx49evTo0aNHjx49evT4eHyqBJh8Ps/v/d7v/dzFF+ia7L7/h+vU1BQzMzN8//vf51/9q3/1ofd+7Wtf44tf/OKt1++vONzc3MT3fQYGBsjn85/qEhI7kiqhyQSnlqts1l2GYgYHR5N0bJeVegdfSoJAMpYKs17rUO14gCQdMZhIR3j1+jq7BuNEGxqT6TBvzBQpNh1yEQNd6RYdUoUgGTbQDYOVhsOQJRgf76fgq7y7VCOqBjhaGvPgkxiGhqHp/KCp8o2IAc06mhIQbZXwaxW8epXA9/H3PcDGSh45PI2IdNAUaAQK2yayXPEk7H+MyvPfxWu1GAhrJJJxnFCM6u77ePalE/zWVJTqtYuUv/7f4hkhqHcNxiXd6xjkBnn20jpf2JLk2sYmIpXBDcc4XqiS3PUI/Z0SMtMPc/MABL6PQoCjhuD+J7luWxzYsYVO24b22h19buUGcUIRvOIm7VCKnCvwgwAhFNANZKtJx5OsaCrP7MhCaYO1m+WqhBAY7Q6t1oe9W95HNJsU19Y+cv/7hHYdoPX833dXXn8ALZ1FJLOUbx5DCHFrLKuqSrC6iPtR5+90oLBJp/nR7bsbltNBLszg3riEmkyhNBrYKwv4P1bOrPXq80TjKdrJ7F2PMzg4+JHn+Enz9YOl1j74fX/Wubs/a1CoCmY3m7e/o67yyPY+dLvG2trdPWJ+UUyGBGNb4gRCYb7q8NzFdTJhnUy4G6B/ZcPnQGY7Y2NDmHsPsLleoSJCLCQGePetq7h9TUQ0zmgmxmDM4PpGnT1jE+xX0oTe+QHF6UOM5mJ4508gNK0rQvge515/hz1HjhIaGkUxDOqKydrKOsvvnWP4iSeZjmnY2SHUoTGCxflbZRGFrpM6cJhyqYgACvUOvuMghCAVCzGqNphdmqNw9QpSQtjU2f/AYVRFIR0xUIVg50CM8ysV1mo2TiBRdQ1LU3CNMC1Ho9HpIJFITSdwXVBURnMx3potYAjQdB3CEWS7jZsZ5Nkr63xlz314P/wbtDPHCUa20X7gaWoNh4nAYc7I4IbjJFsbhE1JNh5i0w9wg67w5geSdqMB2RGO38jjhuKU1TBrtc6tknUxS+fAcJKHJlNcXKt1BbvBOElL48ZakSMDFvl8nsjGKo2XnsMrbHQ7TFEwd+xFndhK+8Zl1FIBZ2P9Y5ch+3mM+Z+Fn8d8fX/fz9p+VVURoRh2a/6O7f70HpajA1yq+Hin82zpazKVDnWzOYROZO8RQkDbD+jkiyyeOEujVOuKiKpO0mlx346tzBea/PCdRbbnosTlCEcfn2AkEyEaqdCRgtVwDqO6SPqJz1N/4wWCtoMChIaGKaRGmB3Zy8KVOoqmIhAslttUbY+5QoOQrpKOWiii+wxZr9tU2y4PjycY2TlGyYHNpkM6rKNlLOTkNuyFGWxU1vIF+vqziGMvsX7tCiEFEhGTzXID24yROnmM+BOfp5QepZgcojNXJDG3Ro4OkVgUN5nGE115fN1WeO7MCqFQmMCzWS93sL2AmXwJHY+tH5EF8j6aaqAPjTDkzGCHVPxAoioCUwFCIVqxJPm1TaQES5U3/dPujrJlD8bQBKLdRGgaXiyJdB1EKkuyXKLtG2yEMrxQV2g4daB7b97Xl6GwufGxx5EQAlMxQYKlKRiaQsRQMRUQnkPLcyh6DuvFEuZdslhUVUUN3I98lmuKoN1qsNau/MR23K1dv4i5/JPmao9fDJqq8NTg3UX0GM5dt/fo0aNHjx49evTo0ePXm0+VADMwMEC73f6lnCsIgjvKoHwQXde7q1Tvwvt/+EopP9UCjPA9JmOCqb05Tq61WK20Wdys4fgBjg8hXeXdhRKDcYtvHRnlUr5O3NSIWhrfO79K2wvoi1oUmzZ9UZPTyxVSYYPNhk06YhAzNeKWRr7aYbPtktu2lcG4xd+cWyYSCVFsNXBsh5ih8uXtac6uljlRgU6zxYHoAMKXJNtVSvk86YiJYRoE0QTewBCTbpwVVeVqoCJ9+Nr+oW4gSkrs3BQT/92/Jliap5JfJ9TfRz2U5kc3SsTjMSitI5wOhaZDPdFHNBSFRhWBREtnWbQVqi0b1XMRnSZOEBCEk3iFIu8smDyzY4D87iy5oXH8S6fxW0308WkqU/t40Y4wGNNBUZD+hwMvbd3E/MxX8WauMeOYtIpFHtozzrGFMn6rBXRNobf1RRmKmqDrd4wnZWCIbjmXD48rJRojiCU+1pjr5IaIPvM17DPv4W2uITQdY2o76q4DtDXjTpOgm+cOggA13Ye7tvKh46nxJFq2DxEKf6IxH3I62C/8PV6pAICeytB65xWEoqAOT+CrHwwiS7zZayhH+j6xh8rHma8/vu1nnbs6Dk9vSVEaTVFquZi6Qi6kEVa8X4mXjZQSQYAKTMQ1ntia4eRCmYoTsFJtc3QwykG/wPyx4yR1QSA15sYmeevSMlI3iFoGZS9grdpGU+D+qSxvzhRYVgL2TN9PXzJCuu3RXs+DoiJ0Hde2cYMKZ09e5MD+bXhL8xQCjYaVIP3Fhyn1jZLZWKZ4/ixM7iGx9yiyVkaxwpghi+rpE1j7jlDWwiR27cBTdYTToTVziVKxgpoeIggCFODI0d28MFum2N5E03XytQ4X1mocHUuSjhoU6i47+qNMpUNUNyT9ms9q3UHXVaQEaVgIw2A0HeX7l/LsGYiCaSFvloXyO22CzACV0QxDB4+iDQ5TnDzChhpjxCmjnj3N0Na91FMJ1ls+M67KXssklcvgtNu0mm0CCdJ16OhhGs0CRLMslltkIwZb+6L4gWSh2OTsSpkntmSJ6F3/h0K9w0bV56md/UQUD7PZoPHKcwTt24FbYYZoxLJU0xO075kmEbFIa+atjLJPMk4+Lc+rTzpf39/+SdvveR7hbbuxr1+Em3PTn97DS504M7PLaAPD+NUOK9UOpy2dr+0bICJcRKtO4+XnKISzVDsevmZ12xBIpHSJDA7y/MVNLF3l4QPT5MIavp2lZmo0oyojOzQubTQ57sTppLaw3fJI/5Mx4u0GpmXSyI7w6pzNTMEjbKg3Rbrud6u0XTIRk+ubDWwvQFcF/TGrK1poCvGIRbUZQ9d9IoHC6YUNrqyqZHc/SqhQw81vslDS2Zpt4yzMoiuCsKHSqpTp2A6tNpCOodoeb1kZOjfWUC2Teq2BguTzYzXSqwuoOw8SaBpnV2tMxXR2mQ1kfhmEgpsb5KJtcXKxzOTeHIr86FJarpSE7n2023/zMyAkIFH7hug89hXeXnW4vlFCShhLhzk0Eiep+Xe91r7v0zZDYN7MHJGAZsDgGMrwBAmpsl5oY3bqqKrCWDrMvsEYSc279cj7aeNICMF8XXJ6eZ0gCKi0utk2hqYwngqj3qz+FQ/pGIpE+h8+lud5bM1GOLNUues5tvTFiKoBwV0++3H4NM3lHj8jrsvKd759113Z3/vWL7kxPXr06NGjR48ePXr0+GXwqRJgfud3foc//uM/5qGHHqKvr+/ndtw///M/58CBA2SzWTqdDm+++SaXLl3iD//wD39u5/i0ESgaZVvidrr+Igul5q3Au6YobNSbRE2NhuMzU2hyNV8nQJKv2xzuC/H5voBg8QxxXaD4E6xMRHljtYMXSDbqNg3bYzQZ4pmd/QyENPpDCf7svQWKDZt0Mkqr3cBxPdqOx+srLX571zAHFAMpIRTVGbn3CI3v/SWqUHA1A++z3+CCE+L6XIvqwCADYZUv7x0iYqqcWqows9lkrdb1gxhKWHx2+xhMj/BfLq3x4LjCQqnJf3dkC53vvU38wcdpdxxMy2R2s4KhdkuBhNoBbR+iGshOGzQdIjF8KZF9w8y0Ba/NFMj2Zfiv5SiTe55Gr5WoSI2ry5LxpMvBkexdxRcAX9F4Yb3NphwhEtVYKgRkK5t8bWuGsh1HSkk2pFFaWsbTxrDjafiACOjGU5g79mJfOXfngYVC6OjD2IZ1K5D4E6+9lLTS/ehPfpFQp41UFFwzhPMTPuv7PuaWnXDl3K3MGRGJEh6bxFtZgPwK7lsvEd6+Byfbj/dT4j+KohDMXL4lvrz/PaTjIAGlVkGks3cEkoJm49eivr0IPDI6ZBLvi2Xuj2tav7y2CIGDRskOcD2fsaTFjr4Rrmx2qLQcDpstlFPz+CZYiQT6zqNcPbmMFYvSjmWZrbq0pM9QIsSrV/L0GwHK0gx6Osp8IolnpYmPhtD7Bumsr+HVqohwFNV3cUsFls7aiB37Od6/j7Id0GpJshstYs0qihdgrS+xtugjNB1dbJLu70MZGkeOb6GqDfLilSVs20FTNfZM3Uc4O0xYU8hl04QtnWslm3ytg+35DIZN0hEDxws4Nl/k//GZHfz16SVOLJZ55fIaMTXg6LZhPKGhqoLLm01sVSfwJL7sevT4gURN5whaTaQQiMBHadQpNWPkUn0ou46gJEbYg031O69yY3mVvfuPcKbU4vJmk9m1CiElwcPxPkxnlUgENAJoVFF8F900cEIRnphIsVztcGOziaEq7B1OMZUN03R8pjMRFspNdg/F2ZIJkzICkBK5toTf6aDdbJ8SjrLx2Nf54dUCjaWzaCPjKMk0w3aJJ7dkMGVvpfRPw05liTz8FK3jr+O6PkuRQW7MraCls8hY/Nb7ah2Xk8s1HpuIghAIw8RUBbbjEotGKN1MeNMMk3UlgqZ2eHAqw/cv5XG8gJDave8eHU/zpXv3cfL165xfq9OMSs5WNwjHYzz18P288NJxMgG8MVdCi8VJhi2MmImhqRiqQtzSaNgeMgjQAw8VcDyDkYSFpaus1W3+4uQSAuiPWTx1aBrdd7hRq7D3gc8ihYrW14cnfYqVBqqiUO+4jMVjOMUyuZhJTHjYZpjBRIgTrRRrdZu+eI5t6RDHykWesBeJDI7Qyg7Rp/gk596lcf3K7ewkITh46B5uDO/FCcD6KdegrZvojzxNdH8Z2WogzBDlRD/fPr9OtX37+Xc5X2Ou2OTr+wdJqJ/MHyUIAgwC9uUMduVyBBIMRRL4XfHl4z5XGoHG81dWcL2AXSNpLuWrBBIcL2Cl2mEiZSKk5MhYsutH8xFkTXhgKsNypUMsbOJ4AYaqIETA4aE4gd+buz169OjRo0ePHj169Ojxm8SnSoA5f/488Xicf/fv/h379u0jk8mgKMod7xFC8C//5b/8RMetVqv80R/9EeVymXA4zPj4OH/4h3/Ivn37fp7N/9RQD3ReuLJJvtoBYM9wilInIG6qaASYarcEgiIER8dTvHZtk44XkAjpHMgYfKZ6CePCVSpOgK4L1t95h6d3bCcxfpTnF1vg2tw7mCGdiOABV9fKTA+mSUdMkprEbzbRkAhDJ2TqTA8kKQmT5y6sUWo6TGYifHPPo0wEPtXnvo3z2W/wvRt1Ko0y2uAodqvJubbPPbEY51er1G2PlWq7u6IdWKm0efnaJqNJi/un+/Bdl/sns2R0SSuT43xTJTGo0fElU7koHdfH932ilobiSEYsnY2lVWQoiWtFsRWN1VqNXQMxDucUjMUz7NIlG06acjbLwqZDf8zkM9tzDEcEWgCK6xBoBh9ch77ZDriwWkVVBPGISVVq+K7C6unLWL6DpirkXY/Y8AjJkZEPZUy4QsE4/ACRoRGCtWUIfDAt1JFJ7OzAJ86wcCW4768W/hif7STSRB59htbbL4OUhIfHaP7oOyjhKGT6CGauYM9cJXzPQ8jt+/hJeSqa7+LcuHLHtsDuoKay+OUCfq2MkkwjPxAY04ZGsD9h9ss/BtSbmUCfNPNHCMGGrfDC1XUqrW5ATxGwbSCJrsCQXab+4nNYN84hHJu2ImjEBpCKhprNks9XCWJJshGDWqONaNaxnQw7d05zZqmEk6/jKjqP7B5BHryH9nN/gwwCFCTCD9g6kiEQCp2RCaptwY6hJJfXqryzUGT7cIwkkpbjU6i1sZIGoaOP8XzRpt1oESxBWI+xa/cWTpy9jlQ1rhIj4Vk8Enb4J0fHudqA71wtY+kabcdjvdZhui+G7frcM57mO2dXiZoaa9UOnuOw2WrxwkXJ1w5P4Dguf35sFk1VyEQMRpIm55ZAD3yk3UGLJwkqRSQCXyhEdYEysZWTQZSLV1YJFJUHHniG8bDOS5suc8USo30pDoylOX1jjda+B/De/hGjqk24WQZFIVxYYfeBh6hoYf7+3BoN+3aAdqHc4sltfezqi3B0PMqBtIL0fVw1QAqBLzT8Stezyw+F0QZHaOw4wrMX87TbNkJVUaIxXMNivtDkLVXhyenER4rBPbr4UlIZ30nByGDZLU5tQqNvHBEKEREKipRoikARghubDe4dS2C1W4TveRjvzAk0VUV4LjHLoNZ22PnlL3Gs1uILEzG+c3YOTdXxhYIjBbYb8MqNIpPZGP/NfVOUWw7VRpsRL0tofYHK899j18QuWpaGFgrR9AXlapstfXEcz6fYsGn0ReiPmyytlwEwTQvH8+jLRsjXOqxWOoBAItkxlKTQkdTaPqvLLYoTOfaPpkkU2mxKhWQmTb1Uxg9AMU2m+pN05m/g7j3C2+04J959F+n7GMNjXKi2uLhS4Sv7hqgGYM5dR+8fYby2yNLlC2jaB35VlJLKyePsHhjGUHIIKX5qRoYbSNxYEmJJFEXhykbnDvHlfTquz8nlGp+ZihH8DM+CbuZcN3vuJ1QzuytCCFarDo7XfVbmK02+sHuQV69vUrc9Wo6HECEe3ZJmJKr8xBMI6bMtF+VGqcPJa5u4gSRqamzJhpF3yXDt0aNHjx49evTo0aNHjx7/uPlUCTA/+tGPbv186tSpj3zfJxVgfv/3f/9nbtOvG67QeO7SOqXm7RWWNzZqPDqd4exajW69HMl0JsyeoQS5iIki4MRCmXhI53dzbeRmlPXc41RsHz1qEF5fI3/pDJ8dHUXsmMYyVNYbLqcXS6RxuDcFUx2PL4WrmH0RLtoGShSqbY/dQ3Fajs+LVzdoOj4Nx+fqRoP/6QcV/sfHHuLe/2EXP5qt0EqYKGmdluPiBYJCu+ufsFG3abl+18BYEQSBxAu6Ac37JtJUWjYPjcZ4443rtCNpxu67j2Pzbey2xyNb+zh+dRVlYwnF6WB7Ljv27GIyIrjgJmhGUrRRqbZcorEIT49FaP3ZH1FqdzANjVgsyuDwCPc8/RWkEGSSIJdncc6fwm3UUKNxQvsO4w6MIlWNlWqH0VQELwjQFIGnmzRlArNPwQk8FFXh6GiKvdEA6/QbSFXDnJjGTWZxxQeERs/DX19FttsomRzqyMSHyob9IgikxB6dIvSVfrRmg87z30EbHMXXjQ+EjCStE28THR6nFU189MGk/JDo46yvYh2+j+aLz978Pl1LZgAlHEEMj/9GlVbRZYBe2sRbmEH6HsboJEFuAFv9eAbrzUDj2QurdPwAIbpB0EDChbUahwciRM++hdUoE0nEcRdnUQWEfButXEaLZzBMg44QWLpCo9QklYjgqxrfPT2LbTsgJQsbVdZbPv/i0D0kNpcoXrlMKB7HsAw6AaQO3085O8iOluT755apOgEIONUJ8UBqgEhlnbFcnNaRx/jr00vYjs/gyADzFZd6o8VEf4JDD9/Dpc0OGQsi599mafUaruuy6xv/gtdUn3Q0zHA6io/oBpPpZiysVFuMJEJMJEw6dHBDYSJRizOLRR4cS/L1A8OAIKUGVDeKHBqMsHp9hrYRpmXEYCBJWBNkIwaD2wd5e71N4CvsHk4xV2wyK03+5kqFjVobP5DojTJ64PLMriHOrxXZ9cgXMdQm0bUbaGNTWJPTHA1n+F+PLd4hvggBo8kwF1cr7MiF0Wav0Dn1DoTClHY/yJmmBrrGY8l+tIltGLqGFLAWHsFenEWJmaDpBObtXIPrmw2OjiWIKR8eF79J6Ej0ahnZaSLMEF4ijfOBe6krdL57YZ3Nhs1QMsKi22GpA3Ta7B1OsKs/Rq3j4QcB2YiJ2mpApYg9c5XEoXvYViqxtLzB6GCW2AOP0JidIRpSWBIR/FYbQgLHF3hCxfZ8dFXhrbkiUbOPrUqLkFrBCXz6dm/lLBo5S2JM5Lje0VmqdctbxSyN9ZpNw/GwVIWv7eqnXm/heAF9hkQ0axilBr9/aJprm03isRB7BmKUOj5v3FgmaaiEhcq1isuJ/DKf3z/O6bUqj+8+TOfl57sdEfg0V5cxNJXy1kNcWqkRON3fEZzlBbKjU6zWbI4vlNm7K0VQXkH3PcKzF7lb7oiuKPQtnCeSi+KVNlGSaYJ07mPduwKhcH2j8ZH7F0tN2uNxzI89Cn5+NJ3b87bYsHG8gKd29PH+02rfUJwBwyP4KeqOVDReurrJRqVFLtL1+JFSslFt8YPLPl/b3YcmP1kZwR49evTo0aNHjx49evTo8evLp0qA+cu//MtfdRN+7dlsB3eIL9BdVXp5tcxUKsKhsRSWCq1A4dh8ieubDVIhg//+wUnCisBfnuW/zts0mktIuia0mmny+QefZPX0e4T2p5FamlcvrRIyVP7pvhjGi3+LI6BWbGJoKvunJpk69Bj/xw2PhGXwV6eWGU6FsL2A3QNxKm0XL6TzV2fzDD40zuW1BVzdoqEYyFiCtZYPqortBdQ6HqrSDdM7foChKHhSEgQSxw/YqHWwqz7j44O04jE2LY0HJquIzWugm2zZt4XV7QM4rSb9RsBIwmI1sFgqqISEhuf7GELyWzvTqG/9Pa6UmLqKFAp1V9JeXqHv2PMoiQQiHKFx4fStfg2aDdwXVgkffYjarnuQQsUwDaKqQsJS+fLeQV65tsmaVIiIgK9Pxxg6/xp6fZO2vClOXDiFtecg+oH7AIE88RbNq+eBru9LM5ahuVokpMaIZpMEn9D74ZMSBAEdI0S41cRxHNCNu7zJJ9hYRcSSHymYeJqBPjqFf/G2kBq0W7i2TeTxz+HMXMVXupkf+sAw5n2P0bYivxSh6VeNEAI1kPjvvUn76kVU0a3pb185jz44ivXo03T0nxx+VBSF+ZLLWtOjYXtoiiAZ0jEV0BRItCtEyuv4hTyuIjFz/XiNGlZlk0R2lHq7jRZPkDN1QkrXM8oKxfBcj7btoXzAi6jeaHF8uc5njt5P5sg9lNc3cRQNrX+UcyLGaslj10AMP/DBcVF0nRPrbUZ2P8yhjYtYKry72SERMtAH03ipHJWNNmo4ykzVZeuQyZVCkS+Me1QvncWNW7SrNfQTbzLZd4DTS2Vs1aCKTsMJ2D0Yo95xGU5YxJ0GRr2B0m4jNQPF06nZPrbr88LJGeJRiykz4J7tw+xLenzPHuG1y6sEQfe7DaQiPLFjgHKg0fYFnu9zea3KU7uG+ONjc5iaiocARVDpeBiK4PkrmzwzEeHNC7PUdo7z6H1PE0olKTsudsfD9yXb+mLUbRdVERiqQtN2cV2ffKGCnT9N0G6xOn2UZ1+7wI6RDNPtdcqzF5Bz19CFJDE1Re3BLUjTAs9DjScJNP2WPZQfSGxPErvL9PxNIWS3cN58kcbqMu93jNY3SPjhz9IKxwDINz02G12ho9JymM5GmC00mUiHiZg6f31m9VZmYVzx6eTgiXQWxXWov/pDjKntbHn0YWrpYazKBsHsBfY8vpXzCy6eUHA8iSfBI8DUFNKWhttqMdzcwH7xb5kpNRlPhakmY0wefoi/bSa5/spVHt4/TbnjUe+4LJRaaIrCUzv6uT8NnfwC/3x/jqDdYn05TyoVwmhUqP3Vn5DWLf7pQ5+nYEb461NLKIpCG5VEIooRMkjqOqdXKmSjJi92+vjMY0/SOfMelt+m1mgROXIPC1aWRukqKAoEATIIMDwbBclSsUFg9KGNjCPtDobbZmQgTX1kO/VIGkdCTAkYXb+OmLuMrWs4Kwvdvs/kCD/xBVpW5CdeN4WfXBJMCHFX0ecXjZSSXPTO+26943JlrQKArgruG419rEzUki1ZLt30cpLckfWyWbcpdgL6fxUKU48ePXr06NGjR48ePXr0+JXwqRJgevzDEEJQ69y9JI0XSOaLDQ6PJal2fH5waZ2Nlsd63abp+Hz/Up7/+ZntvHp9A7fVQglk12xeURChMG81DL5w30Pk9DAvrVTx/IAvTqVwX32OTqlCNBknYelsNmzUuTl0J2Bs/CHqjkd/wsL2Aiotl7ZTJxnummkPxUO0pIqa6ydf7aD5PmZEp13rescYmoKkm5kRNTXqHe/WSlQpwdQUJrJRBkbSPLs4x0HdYevqRRaOHWO91kFTFXRVJbF7L3NTRwg7bZy1G2jFCv9uzz78bI6ar2A3W/TPnaU4N4sAFNNCug6yXkFLxHGunCP1lW9S+86fI/qHPyQ6lPIbnI+U+fblIiuVNroq2DkQ54mtOe4dS+IECXJRg70LJ/DqGx/6fOfCaSLD4wjTonH1AgByeJKLqWnemyvQbOVRL5UYP7iXh7bmSGrBJy5X9UmRdzm+0I2uV4XnIr2fXPooCAK0HXtQZq/cYSrurq8iM31Ev/WvcD0XNA0vkqAFvxHiSyA0blQc4ss3KLzxLroqyERMkiEVRQa4a0to1y6i7D3yEwN9TalzemWTlUr71rZi06EvbmEoCoFh4wsF5egjuPEUbK5iVyqs3pjjvkd38FxBUGzaOHWbA0MJEvEw909mefPiIrejnwJFUbAUePfKMtmtKaqhFItagpPLFdauFFDZ4OBYBk1V+N17pvijV66guw6WZdEIJ/lB/2GO9IW5enYJOxmlJTTGhMK06eFWSoggQNZM/q+Hc9hvPk8gu4HOhqohzRAjqTDHrq6BGWCGDBRLo+X4ZHIGfrmItziLcG1830OxwiiWid2WRP0o/7fHtpDVJdbqLAMbZ5hv9KOVAr6xbxBHgqYI6i68fCXPQ9sHGTM8Xlttk4lZNGwPQ1UI6SoRQ6XQdPCCAC8AO5B0wgkKmVGMTA4tmeSV65vMFhrsGEwxX2zi3wzmlps2zZvZe5mQitGqIQKJPzLNG/MlwiGTqVaeyrtv0YjGGRoew1tbxs6vEq+uo0XjBJ6LyPYTfGB6aIrA1D79fkm/KHQkzpsv4q4u3bHd21ij8+oPMJ/5LVzNIF/r3NrXcnwmLJ1s1GBrf5y/PrVMPKSjAgqSrCa5cn2J3M5h7n3oSZyzJ7plFGeukHzsGYL8Cj4Cc/Yi20aOcm6jhecFoOroAix8UoZGn2zTvnQdf6PAdDLCUt1GVQTeKz/kt778Tdam99IqlvnnO+OUfJXVlo8rBTHpkCsu0XzjRVIDfWjJFFkblt+9QMV2aNge6v+fvf8MtuTMzzvB35vu5PHu3nO9L3dvWZSBKXiPRnejLSWKpCiJ0syI4kzsznxcxsYqVlLEhj5IsSHtbOxMSBppJJGi6242uoGGBwooVBXKe3O9N8fb9O9+OIWChxoUyS6yz+9L1T15Tp68mW++WfV/3v/zaA3Sy1eZ7j9MIFQ8KVGFAijUbR/X96k5AY9t7+b35rf4QaiHv/s3fxO9mcecucW67eFWKwSei6JpcLsLRnoeQgoSsQghu4HoH8bTDLRcH3bXOG/ezFNcWAPAIGAsleWpo89hLN/66NwXtrCPv4n+xDf4smUCMvDZ3Rdno9r63O3bumOYSvDzuGb+uZOLqGRjIQq3RbuPs6c/RUILfi5rs6YbfKnRWM326An98t6/HTp06NChQ4cOHTp06PDLRkeA+WuElJKY8eWXVFdVXr6yThAEZMIamqqyUmlhKLC0VaXmC8K9faiqgarr2CisVlvMbjTYMTyOEQmTS9aZsD22ySrl9Q00TcdtuoQNlb5UFLMrS7HV5LFswEYkhKEqLFQaeAG4jk9vwsTUNRw/QFUVtvWlqa1dw61VkZqC4TiEzDCb5SY7uiOsVSwKdbud4SLA9QJ29LSzIJKmxjuzJfYOZZmqzlI7/T4J02Cr2sLzvHZI+cIsz4/3c/m1N/FiGgkEicoiuqax48HHqMW6aZTXaEqPZrMJEhQzjNB1MhEDpbgJngdWCyE/6eCuxJNcCg/x9uVFGl4IVRG4vuTiSgXXC/hfDmVxi0USjQCr0cDRIxhOC5VP5b9cv4QxtgOQKNEYt3K7mC/b9A/1Yrcs1koNbmw1mS6v8vXdPcR0lWxIoMq/mAwIGUsgQibStpD9w5R7t7NhSRRF0KsHhPsHv7D7RVE1JGDHU0S+9j3cy2dxl+ba429oDH3PQWqx5C+V3RiAUFTOrDZZKzfZd/UCEonjS9aqLWzPoC+ug5Q4t65g7NyLrX2+nY9QNY7PFIkZn/SfkgjmC02msiZmIsbWwSc4eWOF6kqFWPcI2yZ20R+fpvGTP+B7//3/QnZLstHw6MtE+I17+njt8hL5aguBYKw7ztEulZzmYYQUzpQMsoN9vH5hnbPLVaQikIGPK+HUfB7b9xlMDXDvaBcfzBd4bkc3joSthsf1WsC8peLYNgMJDXdtGUpF/ECAADe/SXr5NJmJIW4sz5M1IJQMU+4eYO7mLC8cGeP4XAk/YhIyNAZTER4ZjPDDi+sohkagKAhNJUDgbKzz2OF9JLwWgxfewb/4AYoZQj7wMOeLJVZWCqyu5dvCcrYHL5C0tjZ5v7DGd/f08Z2hDAUtimao9CbCtGyXXDxE0/HojihoQmKhoABpU6UrovGz61usleog2ivmx7ui3NysU2q69KUieL7EDQI012ZioBuvGaKW6KYwt8GR8RzN995Guh6e57OCQWZgHKl4DGgukXCERrwP/1O3yvaeOEn9q+dc/HVBrxRvd758Fq+whVkq4HT1EtY/eY/c2ijzvX0DfLBUIWEINLtJRBP0RHWiVh0ZTXBhscSuXg+zu5fo9kmQktDkPmpvv4LbcKncvMl4zwQ7exKs1F08oRJRJYHr4jab7OtVsI5fRPF9lGaNXLYfGXiorQbK1bNMbJ+i9v7rrC2tEenu5eFDh4l2d1F682e49RIhKbGvnKdaKhKZ2MnI7l2Up2/RLDRQBHiLC3SPHcG/Lb4MpMIIYKXSwtQ1ehIh/EDy3YPDVBst/vTqFg/nNMTVa3i2w9DTY0R0FcuXCMNAei4iZBLXBPv7EyT7+ljEIOQJzIOP8eJPT+L5kjun0vWYWa4SGxnlYWXu9osCNZUG10Fv1XDD8S+8dlJKxlIhepPmnZy6D4mbOvv74wTBJyUcTQj0egVcF8wwdiT2lTPRPo6iKKiqipQS72OLCXTp8o2pHG/NFFkqNggkGKrCnoEkh/pjBP7P14Ea1tQv3R41VOAXoDB16NChQ4cOHTp06NChQ4dfCHedAHPu3DlefPFF5ubmaDabn1uk7ViVfTHdEZVYSLuTQaAIGMrEiJkGqiqo2j41N0ARUGx62H6A7Qbs749gmCbVVD/1Wp1m00JBZb1qEdU1fM/GQuWtS0s8tGuA+cV1gmoNTdMIpMT1AuKj44xkIxhr8wwpLiFZ4HK0l626jamrNOx2tTCkKSRNDU0RLG1VGY5pXEkksGs1dM9FCTxUq4Hux/jOVA9vXVog4wUUA0nZE2zvjvDgcIKNSpPZWpPTS1X+6fO78M9cxVM01ssNRrNRCg2HpuMxuH0M+6U/YqK7D1sPY1k2i4UGQ6GA1g/+A5F996IaGtJvEHSnWS1U8a0Wya4sKcVDxJNIIZD3HCU/soeGL4iokm6vQaVrkHopYF8qjL3eQFbB9gIG4xrfNdZp/OAl1jdL9IYkRiVP+L5H2NzYojtoon2sACNbTVAEQtNxHv0W6CkGe32qDYvl9TL9k0NM5+tc36gx0RVltVRnKB3hiYk0+l+Al7wTjhK+535qm5scl11cObdyR3jSkknuy5nsT2iI4KPiVaCorDUkF1ZKNByf/qTJVE+G7qNPErLaXTBeKEwzCNAARfoEiob3V0SIUZR2BfLPWviregrnlkqMJHQCq/mJbaWmQyZiEFIkgeMgAh/4fAGm6sKtzRqT/WlMTcH22qutvUDSZapousqcjHFpZgG70MDUFVqFCgtrBfYO9nFwv8LC4gZLVQ3bDXADiegNM5WLcW01zP39USY3rmK9fRnPbmGZMe4fH2XAy7FQbOIGAUgFRQj826Pi4mKJ53b18Oj2bib7kqzVbN6ezhMLa9wfN7h3NMOl5QoZYeNbLdI9Xdj1BgAP7OhHnpsnXdtk99eepVEuY5TzEEjqts9Wpck/2pfCWJvHL2xhahm0WZMn94/w8ulZFEOl6fgEQUBPOsahiIPe1YPy05uovgtNF79niOLlAjKQYFuouV4cPUSt0ULGM5CMc802ePvtE4SyXdxzeA/X1quMZCJkNUk0KFFfK+F5Pumwyb2Huti1p5u87XFto0rM0KhaHpvLFR7almM238D22+d2o9JEChgxJSsbBeqxcXYmEsAGfakwwtAIZ9Mouo4EiraHjITpXbjG8/c/z8tlg0qz3akggLGuGEdHkj93MfivI7LVhC/pMQgaNWS2h6GUiSoE/u05xvUli8Ua4cBmQmmihxU0u4lYKeHWa6jpLHYigWtoaJtrBEGAM7EHN9xNcM9jRBZvUbx0hdLbr/G1J7/Bj2zJlu1SKVbxgWd2DzC4eo6WEEw+fBS1uElGAZnqQqkWURevE6xOE1pdYSyWIDKUpfn2n6IODGNcOoGMJdF7+5GGgaqp+PPTJMa2Y8cjdDs+5ZaLXS6xLRsmGTZImBqBhJmtOl4gQXhEDaXd2WOqrJcaDPdlWFfh4AMPUfzgBNniMuN9GeY3ymiKihKKo6ZTZBTJvh1D/LureRq2R0hT2NWXwsn0ohS32osQAKFp6IOjXLu1zIHt4ySlTyibw1ucIShuwa1rhLdNYUXjXyiyh3D5+q5uZks2V9erBBK2d0fZ0RUhqnifaIYMWw3cU8doLM1BECCMEObUfth9AFv5/DlSUTV8QEUSfKybUwhBPdCY2WwxX2wSMVR298bpiQiU22pmVLh8fUeaqpvG9iURXSGuBV/pfsuYgp6EyUbV+sy2VNigK6yC7AgwHTp06NChQ4cOHTp06PDLwl0lwJw4cYJ/+S//JUNDQxw9epRXX32VBx98EIAPPviAvr4+jhw58gs+yrsbU3h8e98A51Yr1FsuqZjJifkiq5UCw+kwVp/PfMliMGVSalrEwwZP78rRsFzyLZezKxUMBQaSCVzXw/U86lIjnkjiIljbqrDeFaMnlyZQAgJAKApDU7uIrc5gn7uFJSVVyyNcb9K9O88/OHSUH1zPk4sLgkAihMDyAp6f6uHKtTkuFrc4eGAXzb4U87OL7BvtZ393mOHCLMV/94ccHRri/pHt+CGDyMAAxXwJZe0WIyGNf1uN03QDKo0WerNJSCh4ns/yVoVkJERvV4zBVBixfQdKOotX2ETpzqHEUzQuniFoWWjxBIpj45k6dn6Vsb5hfNsi4hQxgjT6wfsppvp5SXVYPrcCwOTkOHmSbMy5XJrdIJRKsXsgxWg2xumFIr+Stam98hoYKiENLKlgODa1135M1/PfJ3/tKgNRFRwboShoQ2MEfSOsP/Gr/GjO5d3ZG1iux/Zcgq/t7mO5WCMbj1K2A1YrFrGQzsxWnb6kyYFu4xOigBACVVHQpESplZHVMmg6MpXBNtpB3p7QcAIotxwURfmMpVkQBPg7drMQG+LKu5eQQiA0DSWZgWSa4/NFcgmT/tu54FKonF5tcXqheGcfWzWLq2sVvrGnn/6wiZQSVQZEChs4V87hlososQThPffgdvfjfUkuwC8SXQbo5TzeyiIA2sAwbqoLV3y1BPSy5eEFkqID2sAIbG7e2SZpC3chA7SuHvyQ+YX1ZV8CQcDS/ApfH0/ys6trNAKFsBnG8X129iY5NbNBXYZId+VoFrYIhwQIhRtll8nHn+CNl07gKzqh3l48CSteO0fivh293LN8juLZkxjJJMOHj6K2GoScJsa1s/zPe3fz/zhdoulKFCH40BdL0u5MqzY9Xr2whBmPYvkBjarNv3l/gd88Mky+bqEXy6giwJ6bQQITA1l6zr5K0m3g6WPMWwqvXdgkloxz8Mg2UkGee4I8N//TH6KrgpbjMx5T0Nfm2fu9v0XkQD+LdQ9f0emN6cTyKzRPHuPc1JM8/J3/jtBP/iPJ3XvQEykGh3TW8xWUZJZitJuNzRKhcIhQLEE6FaNvIMWh/Q7Xbi6Q8pv8yq4U528sI3QI6SrEwviWzb7RLLU3X0If2wHD+1AVldlCk2hIo2b7/OjiMg9v62a20CSQku09CQaTIbpUn6snzxJISW9PF4cO7qKoKbRa4FhN0HQMVWEwFSZh6gRWi/7qGn9z/33kb4vl8ZBGJgR8TjFYURSEEH/h9oS/CEKei7AtUFWccBQRCn/p+0W4nUOS0gMe29nNmzc2CWR7QcJAVCdc3CBfyaN+OOUoCgiBXyqQG+rHdLZo3vs0S/E+XrtZYO7WDMMRQU8zypGjT6OdOIZy7CV+8+vfZ8ELoWlDqIoggUNmqUVq3y7c136AVS6jRqJIVSOay2E88Bild15DNOqEDz5A8Qf/mfjDT+KUSyQefgq3VgXbInr4fspLS5TOnaV54Ty1oV2kI+2FDFoyhW+ofGdfH2/d3GQhX0MVAqkINFXhvtEM//bEPL9+eJgTKzWGYypPpCWJiMHwfQcotxzujat0J3q5WQtQUxkGNI+hiWFOzxdo3F68YWgqc4Umc77J9tFtaLetJBUpcVYXwfch0oOuadRf/IO2haSiEAQBwfVLRJ/5Fq1095eKMFMZlamuLiSgyIAgcD8hvoR8F/uNn+IV2nOlYoZRkmm81SVUKVEP3I//sWefvL0I4PxqiZrl0RU12NefoOf2cCm6Kj+8uErT+egeublR4/BIhiP9kY8WFAQeCRVQAfyv3GmmBC7P7Ormp1c3P2FnlgzrfG0qh4H3pRZlHTp06NChQ4cOHTp06NDhrxd3lQDzwx/+kG3btvFP/sk/oV6v8+qrr/LEE0+wZ88eNjc3+d3f/V1yudwv+jDvWgKhsVT3Obu8SanpM9YdYzrfbFsKpcMg2jZFTcdnJt+kL2kyko6yUGyyXGpQarls745xZb3KWt0hoimkEjEqlsdgV5zZYouubIpy0+Zr+4cRtQjhnm7qtQb9URVneRrLD/ClJJlK0AqFuXz8FMPpXh6dGOfiWhVVwHhXjEe3dREEAWPdUa5trPHOsXO8cP9ODvYJov0K/nsvsjyzgDDDWBdOk569SshuoJgm+tRhrr1/mtTgAN/+xq9zveLjqgaZBx6h/M7rZBI+W9UWsWiYAIGZzlB7/cc4hS0U30MqGkY0Qvzhp2gcn8dbXcRfXyHz7V+l8cZLBOU8fjGPiCcJP/w0rXiGVzYl60oEqDA4kONGTXJ5eRU9HifdlWal0uKda6scGs3yxGgSceFVXM9HD+v4vk/ND0hlu2FpAe/WVYJYCqe0hO97VPUYDZmkVgz40fUGV9erOJ4HEm5u1pgrNvn7D4xxda3CVF8SP5C4rkuA4NxKjV25XkLCQUpJyHcRKwuIchF//hb24izEEviqhhKNE37kGW5F+3lvdpNK0yGdKLM9E2J3Txj9U7YvltA5U/RRhscQfoAUgkDVsXxJrenx2q0iz+/KkTQCai6c+Zj48iGuL3l7eotf2ZdDFwH67HXq7752J+/Fr5RwVxYIH3kIOXngzkr1u4WQ7xGcPkb95tWPXjx3ktD2KUJHHsZWf/4pVL0tMEkpiU7tR527QeDYICUN20MRgKIQ2n+E5pechoQiidfylDe28DZNnhsbxDejhBIJ8uUGCUNhYbUAMqBu6GT7RolGTYQn2XR8Lq7XMWIxdCOEF4mxVGows9XgrVtb/N8Op+HcGrmjD9GTjlH/6R+j2E0aQYCtKHSNX+EfHv4G/5+b7icKn2FDJRlWOTFbRgkZWJ6k0nIRQmCogh9cWOH/8vh2Nmc9bp3fwOzJsrcnwlhhBu29l6m5HpEno+zMDeAc3snbazZ/fHqev3dPL9U/+hMUwHIDHD+gJVUShk7xpR+Q/tqv0ogkKdiSiwtbDMaijB96gK2r81zZOcIzRx+h8OM/YPXln7L7f/y/c721mzkvRLncIpWMsdHwaBRa7BlI8/87PkdM+Hz/0YOkzr5JWguR6B7i6lIeq1QmOzLCrp39DBfnKa6vUN7MMzKxkze8AF1VqFgexUa7U+WHF1YZTIX5/j2DrJWbJE2Fa8tVMMOkQwpNPUwjGuPdhSIvHDxM4fRJ3EDi+AFrVZuuqAGqijo8ihY49JofnmkPPlUM1pAY5QLe4gx4PsbgMEG29yuNzbsVTQZY509hv/82frWM0A2MiV0o+w6hdffiba1/5jNqIkWQ7gJABgE70zq5g4O06g2ipQ26Wwts6C1mFIkX0O5uVFQUM0zQanKo28DJTjEvElxcrdLTk2FMV5ldL7GuJ3j55hZPHD6KevxnGPM30MYO8sNTM5QaNolkjP/n1D7q//7/jeK17STRNHw/wFpfRd9YRY/FcRUNub6ImNyPsvcI5vwNCj/5I/B9NFXBPfMeysg20g89Sv3GNVp+wMJmjcFkGHvHQVKqwjbDpTmYIETQ7vTMRBnLJXhnpsBqxSLfcNibNdi9donVVz+grCvsH0hSLtdJT+1GTB6hUoGKI9m7e5wzCwUq1kfPANv16U2HadgetSCC+aHoFfgIRUUTkNYCmu++fmc+VxMpAt1A2hbW+2+iP/c9HNG2+wI+Iw4KIah7ULYCFAXSIZ2w4t9ZUKAUtvAKmwhNJzy+A1kt4S7OgqajxuMYzSp1M9bemaJycdPmvZn8nf0X6ja3Nms8M9lLOutzbLbwCfHlQ04vFBnPhun6/IaaPxNx4fK9PTkKVkDV8oiFVLJhlRDeL539ZocOHTp06NChQ4cOHTr8snNXVWiWl5f5tV/7tTv+3MAdf+5cLsezzz7Lj370Ix599NFf5GHelQhF5dKm9YnigwKcmi/QEzdJRzSWShbllseh4TSv3dgkGtJJR3RevrZOfzLM+eUKz+3uBWC53GKj7rC9O0pPMsz+/iSOHxA1DW5u1nhlusSevgRHXvguzsUP8G9eoNJyCOsaSsjEHBzm4pZFZmoPrqKTCcHj27touT7FhsPPrq2zXrXYFYP7923n1JnrnLi1xn0yz0StSOvMCYZyOYykQRAIzMoqpVoLPwiI3/MAycEB7AMP8ua1Da5VA84tVxgOKdyz9yGGly8ztrXGUrHO3p3DWOdPgm6g79jTtnZaX8bbXKX+0p8QfeoFEAL74mm8jVUiDz0FSEQiBYqK2H2APDEWz64gEhk0PUS6P8WrpxcRmobn+SQTUYJS207p/EKRZ4cHsAt5BBAxVEqNdlFrU4bIDQ5DtYwWTeEaYfJGEm/vES5t1Gl5ZeaLTdxAoqkanu+3j82TnFwocf9oinLTpTdpcmy2QaFuo6k2Z1Zi9MR0dkV8vGOvEFTK6JpG64P32mOjmEcbGsNv1ll98U+pP/QChXp7jDQcn+OzeTbrMZ6aSKF8zFLMCyRNxyNAAVVBCkG+6bFZa9uqaIrgxEIBgaQ/FfvCFb3FhkPFhgG/TvPUMfic4lPr7Amiw+O0Il+cHfCXjRACsTyH/XHx5Tb2ratE+gYRozuQst3VJYT4UnuyTFhlrCuGHQj+9bUyLxx5BnH2Paz1VQaSJrGebqKHjmJ19X7uOfqQWHGFe3tMXtmAZsumVCiS7dGJhlRWXQ/fdW8X+ASW47NkNag4AeFEgi3Lo7cnS3dIwdJMLBQe3mEyu1khbKg0hcbK8AH6Eyb2Gz8gGkujmGHsQBLr7yMwI2SunOCB4Yc4ttIe82FDZXdvgsCXrFQs1qoOmhEQMTQqLQfXAxDMbFR4cvUsu4INYpaPfO0yfinfFvakxJu9gZXpJ7mwxM4DzzJ7q4go50kID0sB2/FRBbQCQbi3l8ZWHmFG+P3js5iKgMDjphSc9RPsnhjm5vV5HjsyTK3pENYEwct/wIPf/5+4cnKJiGlQsjyQkq/v6ePaaon1SovtPXHeOnuTb3b1Uj3+DgnjKt+cnELPhpGV6xitQU6+e5KuqEEu4tOnumiKQFEUNmqtdveZAE1RqDseC6Um789s8a29fQSKSs/OHZi6yuWSx8nZVaqewoWhHezaUaU1ewsVia4KGlIh89gzWInMl44FXQaIC6eoXzrz0YtXzqH3DRJ+9Dksw/zCz97tKIqCdusKzfMn8Jvt7gvpOtjXL+IXN4k+8gyNN3+KV/zomafGk4SfeJ6Wbnx03gKfPly886/jLs+j7NhN6t3Xef7oC7y1UKdiRPEMk7CucDRnMJSJ8vvLPqfXlii1PAzpoXsOz+zqYXmrTJDIMK1nuf+7v0klluH335kh67Xo6k3jKiqlzVW0UATddWm5AboAVVFRuvvYOn2K9NNfpxXr4kwTrsoCjwUhtOs3ifQMwvoSgZT4ro+2voqR6Sa69yCNhS367rsfdc8h1jyDVqlBwtQ5fX2B7kSYXFyjUCjz8lqFaqDiBRLb9XnYqDB79gM0BRq2y2bdoREo3Dhxni4zxxvVDDU3YMMR3D+SpmK5VFrt55XjB8QMlaih0nJ9woZASomvqGiDI+yN+qgLVyEIQBGoiRSiq4fg9nn38psY9SrrRoaZfAM/kEx0RemJqGjSBUVjseIys1Fgw5LkGw7RkMaj27sYiysgJUFhC4DI9klax17BLxbuXGtn+jqRVpPQY1/HVjWqnuDE3EfbPySQ8M50nt50guVi8zPbP2Q63yQ3EP5vypb5NJp06QlBT0gAAcig0/nSoUOHDh06dOjQoUOHDr+E3FUCTCgUQtPahxSNRtE0jXK5fGd7Mplk82O2PR0+ouoJTs1/VHwQAlzPQ8iArbqNqio0HI+G45GJGfzDh8YJaQqqIhjLRtFUhcF0mHentxhIhfnO/gEajse2riiv39hACvhgsUSx4RJISSbq88NLa7wbM/jv9j+Ivr5IeGAYV9EwYjFmmwG5R57gvXzAyrllrAGDW2WHdFjnqV093DOY5pXrG6w0XFYtQW9XgrrtI3QN6drtVbaAVynTXF3BCOvEQxp1x0cJfMwD9/HTiwsMHTjA3okMQhFUWg5XN7fomTxEvPwyKVMnMziI5lqIQGLfuoowTUL7DiFbkzSPv4kSDmPN3Gzbz2ysIZt1nPUVlLEdaLv20TQi1BsBQghAEkRitIwIIp5AWi2k1cQgRjYWotJy8X1JS2okYlH6DEnDcu5ck5YXsKKY9A72Ejv6JG4guTWf59bNPMMj/UxXLLzgdoFGCBRVvVPMWiw1uXc0zUg2yqn5AqvlFgB9CZNC3eLycpH+dIPQ8gLmxE6st39253ul6xIUtgh6B1kr1YhtLhIJj9N0PsoJmt2qUxhM0v2xFcAhte1X33Jat4+fO+ILQC5u0rI9Go6PrjvtgIovqC4FUkKlhLQ/64kPgO9BqQB3kQCjyQDn6oUv3O5cvYA+uh21UUWurxA066hdPcjuXizN+Mz7o2rAcDbO//fdGaSEf98S7J58ksl7PCqmSu9EH5aufOnqaFVVcW9dZaJW47n9UxRDSU6v1jl2ZYPEZkCtafGdpMl4f5bZ1QKBlGTjYfaNdtPXnSITMSg2bN5dtWgEDqqikDDqHOyN8Lf2p/nZrQ2qtzb41fEwtVIFKxZj270Pk1ydw569SSTbxe7JA2ybjDI+2E3ddpnerHHvcIps3KRs+ZSdAMV16EuaICVN12+PNc+jWSoTmrmMY1vordvWSbTFLkImVqlEZWaa4b334zRb1CoOfYZCIhqj3HIBSdP2WHB1evoG2arUIZBIRaCbYYJsD1fW2nkcO3vSyOImqW/9KnapgBifpFaucDBnsnusl7mNMi3L4cpSkblCW0xSEDS28hR6h/AUDbtehyunkZsrOJ5P6MAReod6aW7lMTSVguUz2ZdgNt9gOl9HF4KIEpDVA54ZT3Ht1gx9ZgzLC9AUQXc6zh+eW+Zru/tooqNq8NaaTWHwXh7Zc5B4s4zUdJyePpyBLMHHAsI/d4xurdH4uPhyG3dtGfX6RZQD93/p5+9mDKtJ69wJTNEeH4rnwe2OMbm6hN+ooT/3PcxynqBeQ4SjBJkuWnrojijqCY2GB/VSmbBqoGgaXrOOEg4zcO09nnnsV5j3DOqOhyEDQiHJcSfJ1dIWrUBg+A5es4WL5CeXVvjuvgFOnrxMyG6R2nsfb1zNk4yZiEiOYtNCui02/DxoSQYHskSkS8MNCEUibLgBET+P0z3ID2/VqORLRNUA+8Zltuouhqcx0j+Mt7yAoglqHqizM2Sf+z6Zwwlenq1y5UyBlC5w6zUmB7M8smeYl87M0LxtG6bHYugK7O5LMpoOU2uE6Hrqeby5G5RnZqhYLumwwWrFonH5HCN7nuNy0aVQtyk2HPYOpLi8WqF8O3NoLl/l63v6uL7ZwHfbVloCGO3PcN9EGvXMGtrwGKgagW58IlY+EAorpRZ/srZ657XLqxWGMxG+tS2JMzeNd+Ikg1aT0Z4B/IndvNfQ+NnVDb5/YIAuw0eEw6iZbtyZ658QXz7EnZ8htLEC/SNsNVz84PPnzqbjUXe+3PbL8T58znfo0KFDhw4dOnTo0KFDhw5/vtxVAkx/fz/Ly8t3fh4dHeWdd97h4Ycfxvd93n33Xbq6un6BR/iLQVE16l67MBDVJNL/bFGubPm4fru8oHkOQTGPHleQtSpBOELTblfWQ5pCLh7m2EyeiuVxeDjNlfUaCVOjKxpCURVWqzZX1pcYSIUxNYWa5bFVtVmtWBiqQm/CRATtLAahwaIfoqdnnPnpNcJhjS5Xkhgb440SzK0V0RNJ8nb72Iotl5evrfM/HB3jtRvgCJ1r+SZHc1n6nBbi+hW0neOEYlEamomBRCDwJBhOi2Q8iZFJM110eeihQ1wsS06dm8PXdOKq5L6hBFshg67nvkOyYRGKSLb+1/8Xwmq1A3k9B3fmBqEdU0Sf/RaB6yKLW+1AXD/AXV7A3H8YevqxB0YQQDxwEBsrSNtChEz0XBwpQToOSAg5TbbrDo1wmLoP0bDB7vsP0jp9nErT/uSFkpLI1D5CjSLLN6bZbkYZ2NbDKiqmUFGkRAB+0F4JL6UgAOKmRsJQ8Tyfa2tVoF0IOzScZmajTFc0xNb5d8kFgrCqEjTqn/hav15FOm3bKFncJDy2nWhIZSAbo9LUkRKqNuRMFfmhTYzvcWQkzY8vtkARlOof2dNoimBnLsaV5bbtWERXCVAYT2oMae33LXg6y1WHiKGRMBS+LDT7w3NzNyF8/4sFI0DoOvriDLV3X7sTUA2gpjJEnvwGzU+JSa4UXFsrMZGNUmq1V8cvNnxqgYFpQ3HN4vHR2H89wyMIYH2ZkXSOs2WJ3XIZTejIoEnJk/z47ALPHx4nX6kz2pMklYxzYr5EKO/w8HiWY9NbxAyNZsumXLcIJFRtj185nGbdkvR1Z1CdImooxNSzTyOW59s5SYkEzeVF6tPTxJotjJEHKVoaf+e+EQy7RaPRIBvTyd+2His3XVIRg15NwfYCRnpTWF19KLkhUtUN3EYVIQO0eAIt3YWth6mXymgC1Pw6cT1Oy4jgBdBqOe1OqqaNpipkoiFWbYGb7UcbThI2dfJ1m3ypRRBIbqxW+OYT26hU4UR6mFteHbMZYVcqxs3CKrFkg9evb+LUawhVwzRCWI6Hpgp0XcOMRojv3I4sbKFtzKIK8HyJW62ixntBBjiZXkp6gnKzwbf29rEzF8NptjA8C7/V4tzpSwSehyc3GJ3KYSVNbm21hR5NEe2Oo9t2SJe2WlwvKmzv6kFxA44qUQb+KyvxVVXFvXbxC7c7N69gTu7/8rF0FyOadYJWE8Jh1HoVb2MV+eF9pijIG5fg4WdpZnsh2/vRB6VEKAorTTg2s0mp1iJYmKE7nuShfY/RN3OGyH0PMa1meOfkFaoNG/e2vdbuA1O8sVQgrGuEVY+aZSFvz1teINlq+fRnY0xtH2S51GJ2ZYti1SKbSVEVBqqmouSGKF69TLka0BU1Wa02SbgeESUgMbGTVREhv7WIkclgtMpQL2LbNoRC1EIqsVAIqesQiWMlu7juRfg/rxe5ulEjYeoMxEzwNDbnFyj1D3P/jn7OzqxzoCfKWMpAGCZ+PMlLl5axZuZotSx2DU1w6Ggf3sUP8GX7N5KWxc4YOHWbiYTKM+VL+FcWSMW6cUZ28n7doGZ75KstfvveAWrNFhVfENYUUiEQvoscHMW/fO7OqVeEgvR9AiFwQhGWXI1Pe+Zpnkvr1DEWT35Ay719PfN5lJtXefTpF3jFj3FprcqTY3FErg9jc4XWhQ8+Mz6USITACOHevIw2PEEQfDYX6eOYmkIqYtwRlz7NaCby1zI/qUOHDh06dOjQoUOHDh06/OK5qwSYI0eO8NJLL/G3//bfRtd1vvvd7/LP//k/5+/+3b+LEALbtvnt3/7tX/Rh/qUhhKDkaZycK7FYaCAlDKQj3D+SpjsUfDJ4/fafqu/iLc0jPZdGIcxQJspCw0e6Dkrgs38wy7GZApoiWK9ZNO048ZBGpeWiKwpCAVNTkbTtqSa6ovQmTF68vE4mYtAbN3gm7RJvlrG1EK5QSfhh+h98iML1a7j1BpbrExua4MaJJSQCJdNNuerh+hJNFTRtH9sL2B6WyFadqB7i8PZBKBfZWIxTyY2g7b2ftZl5Yqqkb2AIUdnCExHUiSlcX9I90Mcri3XWNgoooRCK1aLk+vzpZonvHBlnzoP5hs7AzAn8eh18D19RMKMxFN3AW1kktHMPGCGCeuVOaLPWP4QyOIofS7SDk1fnUap1+jIx1vJ+W8gobZHQoKKqGEpbgFEqRRKKwkAixsRaFQ2X2J59jF6+yFq5RdPxUFSVnfcdJliexb1+kVrFwfN8FMNg17PfQuvp4fxqjYih0XTaHUBCtK3k7hlMkorovHZ9A0k7zPfhiS6K9Rau317tHXguji+Rvt/+fVqNtrCE+IS4IVJZUmGDihPwx+dXsJx24erCapint2c52Be5Y0U2GBU8vjPHifkirt8Wk9IRnUe3dbNcqN2RVFzP5df6JJUTb9C4HVa/Z3iUPfvug94+TMWHZBphGG3h6tOoKiKd+fO5cf6cCHQDtasHv1b53O3m0Bj1Y6+1u3c+hl8uYp98B/2Jr+N+TFNyfEGl6RBSJH0x/U7HkJQSJGzWbHy+vAPI932MsR3YszfZNLNsXl/iw6YlJZ2lJ5ZgveRw/NYmv/3sAa5u1PjhpTVSYYMHxjNcWi1TrzfxVBhLmlRVnXUbHCk4PlvADKls+knUXJjdzzwJx1+lceUCmqYT3TlJ+OGnqb/zOo3rV9iVHmKpFubNt5b53q4MxLt5cDjJesWiZPsYqka56WCogt5kmJmtBv7ALpwzZwnFMhj9gg9PQqVYJnr4UapvHyOwLaJmCNfzWRdRxrdP0jz9AT3JBLWWg64qqALMHVP8tKiy7mvEWz75ctteSFMEiWiIWEjjxyseea2JXyrSaDnMCIktIaRr2IqGkUiCa6MqoEdN7u0LsyfdS1i1qfQNEdo2SSL6BM0//T3UuRlCPb0Ei2tEVYHYfQ9DQZ1qJsIrNzbxG02q0zdQpcT1fVQhiBgq0ViMRGCzO5fmrYUqI9kY+WqDewZTvDf70ap+L2jnZxmqYCxjEgQeQogv7IgSUiJbX2ypJF2nbbn4VxVVAwRBo4a7unRnDpMIPD/AqtRgYR5vdAe6dD9xnrZshR9fWsEPJIoMIPDZLFb5cbXBr9z7IGZQR51b4QFRRIz3kY92c6YiUZJpCnOr9CbCdIU1qlKiCIEmQMiAetNi/84RbpQs1ubOEQ9luFVpoCsqLR9CqsJaOEsiHsPwHCLbJ8llB/CFhqFK3FSM9xthtJ5+PLuFHc+ghFSUm9dptSwKaoTsrr2UXVhoBNhqHFMNcW2jRiAl8ZDGWs1mVAe/XkPWyjy4dxeP60UaH7yF3qqhRSLYPSNERvfwVkjHt1pcW9witr2P+4b6yS+voiuCrq40C/kiRrXGZLRC7ZX/RCQcIpzuo371Io898wLNVJyJ+hzmy2+BZZGZ2IUytoOW3xasgmwOvW8Id20Jxbaxq1VsRcMTGsknH2RsuB833uLqapnG7S6dXUqD/Plz2N4nBcbAdXFPHWPbA98gX3fwEdixJNHRHbTkjz/xXqEbqD0DeIB0XATQHdVRRNty7NOYuko2anB0LMtLV9Y+sxQgFw/RG9NAfrmI06FDhw4dOnTo0KFDhw4dOvxZuKsEmBdeeIEXXnjhzs+HDh3iH//jf8zJkydRFIWDBw+yZ8+eX+AR/uVS9TV+cGGVlvtREW2h0GCt0uJ7+/tJax8VMDJhDUNX8EplpNcuIiwurfPQvl0Eaxa2L5G2RczUCKSk6QTYbsD7c0W+vqeXH11cI9+w2d4do2577OiO8fRkD7bnE3g+MTUgogieMquE6xY/m6+xWqiClGjqTfbs3sZTf+e/Z+knf4rMr+AKlWgijp/OMd0U6KrA9QIE0J80KRbKqBtLNCyHbSPdJM69TS3dy8XdT3J2psI3x+6j11cpLsxja3F2jHehZrtx+8cwu7rxlARra0ug6whFRToOmvSRisrp+QL3PThCc2aZ/MIi8a4czvoK0vdxLBtd+kjHxltbJnTPvSiaDmYYffsU1hPfYUmEsb0As2KTvXqZ4J2XeeKJ7/AKGvlYgqXFdZ7aMcbr84IuYaMU2kHQhqbw9HgK48oxxENP4vUOk902SSa/QRCAmuvFuXQWf+4afr1EPJyiVPMJHIfyqz9m9G//Ix7Z3s0b0wVSER3XCwikZP9gkgdHs4wkFEK7+5jqTRAEAaulBvXbRa1i00EZ34m48j7O1gbhyT00j70Gvg8C1Ew3aCphM4QYGicRCvH69OqdYpUAwprCqfki3bEQo7Hbhd/AZyqjMZbuZ7rsslm18P2A5WLtzup9AeySVRInfkpQaeICnpT4Kwv0WmW6v/V9mkECOxInfPAozRNvfWash/cdxo6l7qouGC8IiOw5gLM40z6PH0OEI+B7n9uNBuCuLBKtV3CjyTuv6YokYmjYnnNHdPk4CVNDRX46Y/0zBLk+jOFx8q2PvluYYTRVJbU2g5HuYcuFuuNzerHMUDpCpWETFZL8ZpGg0aIhJU0dxNoSYwOD5IGNmkV/Mszb6w2iO6IEL/4hzs0rbYnEd2lcvYhcmCP31DeYPnmGVGmVfdsfoOxCPhpnSDRZyds8t7OLxZrHzGYNFcH+gSRJU2OqK8S19Tj3PvN13HPH8FeXcJsN0v19ZJ/9JrfmVhC6gaaqOLE04yNhUvEIp6u9TB68D2d+mp09CVzDRNm5j/rEXhbP59mRjdCoVFGSYRQhSIZUujWfaq1FTTGoTN9CeB7RHsGNZY+HdvQzs17hwfEshYZL3NSoWw5TaY39jSVutFSuXZjDrdcRgBmN8NQ3/h4977+IOrqdUGqAQiTLZskid/xPyO7aj6+P8txYnD+eU6k1WiRCGhFDJZzJcN/+CV46eRFzaAwzEmWx2MDzwxweirB/IMWl1TKBBENViIVUntmZI4NDtRmwJXV0VaE7rKJ/qjgcANrAMO7nBNEDaJlu/NBf3QwYL55E7+nHv3b+zrzgI6jbHoEQBLE0a2++ReHRNNsHs2R0v209pmqcnSvfsaOSioYww8hGHU8zuJS3iM2+z+bVGYSqIWZvkejp4+nnvkc9YvLMZC8CQVQN0F2b6bUSQgYoqkpfOkYQi1G5dplWZYup+wc4twiJkIKwXMrlCi9ZBr/2yNcYjsCL1/PMXFjDDOmoyQxJGWF7b4qNQhVXD1OPRWl2DxC9dolWvYGvhygKkxXboen5DDzwIDda7TylsK6gqYKaE+AIiZCSHqdKf3MLt7xBujtBa9NiOV/GXS+gzs3ywEPP8/bxImHDYH69xNFdO6neWiShC5jYST7vsS+p0Dd/kcBx0JWAdKuEmuqlu7WFf+04sl4hCIfxmk284ruot64SfubbtEJhbEUj/Oiz6Gfeo3DyOFuOgmVG0Pfdy4+nLfI33+fRB/cz2h0nX23RsD2U9VsEfoCmCpxPTZ/N/CYDtHDMVHsuDALsngHMIw/h3rzaFhXNMESieEo7J1Af347t+6QMhX2Dac4vlT4zlu4fy9AVC+ElFL6xt4+T8yXydQtDU9nZE+fQQAJDfn5nTIcOHTp06NChQ4cOHTp06PDfyl0lwHwek5OTTE5O/qIP4y8dRVG4slb/hPjyIY4XcG6lylNjcYLbK5xjqs/D4128MXPrzvt8P+DKxev8+sP78UJhZjdrhKIGqbDOXKGBRFKzXU7MFfj23j42ay3CuoomA/Z2mVTqFV5bbNDjVhhMpnF9n0S9wE9XXfLlxp2imKEqXL0yQxCJoe57isOJAMeMIMsJVmsuiuITAnxdoTsWQvddNN+FwCMe0rgnF+byK1foTc5y8KGvcyXwqDgqYw88TvY+G1NXWK67TM8sE2qZTN64SX00jWKaSMcmqDsIBVQzDEGAKQKUeplkRGcm32BPdx+mIrA31ghcFyUWhVgcJZ3Fmr6BMjBK+d5nOKt0cfzUFhs1h529SfqiCra5m2/+6jYiv/+v+dbUIYrDk9i9Y4SdOvc9PsrCap6tok6XGjCsWsSvvYc+ug2/d5BAUcD38LY2CUpbMHcdPZ5EjG4jqFXoMhRqqorn+/iWhViZY6RvN//z49uZLdSx3YCduRijmTBp1UV6Lt1hndc2ypi6Ri4RplcI6rbLRqVFLTfMYPYmYm0RevsJ7dyDffUCCAURjSMrRbZ/7+/xvpLh7dsWdNloCFNTiOgKH7qEnVkqM7I7e6ezIwgCQjiMJHROzVQ/MyZ7YgbZpQsodotsWCFlhgkAVYDwW3g3LqEcfpggCPC2TxGNJ3AuncGvVVAiMUJ7D+L1j+DfReILtDvQrHSO6BPfwDp1DL/StltTkxnCR5/AW1384g/LANxPFsw1fO4ZTPHGzc/mWAlg30Dy57LAsVUd88Enia3VEXNFuG3jFTTqyGqZiIRIfwJDE6wVq9RbDl2JCE4pT8pUaTQFAknT9UgYGtbKMqmx7fRkEu0ciJ4IW2dOEDUiSM0gcNuWYpK2vaFfqxLpH2Cz5fOzK2tsugqDC0UOjWR4YVc3b82VqRUq7EiG8D2fSzcWODCcZihcYef6FQrrG7B9Nz1PPk1jYR5qZcpzc3S7DrWwRuyRr1FIJPmWVqVWbbAgYTE1xN5vH8RrtmiV62xInYGIyfauCPmqRcK3iVo1BBKv7HD/A5NcLVo0qnVc20EIQXWrQGJohA+mV/n2/TtxhcobN7e4ul5hNB1hMmVQcWJcujiN5rnt7pHAx6pLfvLOBb73zV/n7dPXWdtsEsgCv76vm9mtIqp7nv2PDeEur/DtQY16ZJiy7TOSiWB0d/PyO+cp1lrosTr7erIIRWG51MRQBeOZML9yzyAt12ckE2VH2Ee9cpKbp8/hSYk5tp3q2G7esw2e25Ujrnw0poIgQBvfibh6Ael8yupQCIz992Kh/FfH092KiyB29DFaNy8B7c6Xuu21LRkffpqVxWXsagXdtfnZ9U2+v7cHDRfbh/XKR9aBkrYYFTTrqKbJ4s1ZjmSywAwy8BGajpJKs7xV5ZV8jZYnKVSbpCM6j4ymGchEubFSxFDgkbEUJ5eqGFYDz4flG7f4lcO7uDW7gqZpVABNFXjZXn60VmVViRMZzaKaJjfLLnK1jo3C1GAX1y7dwN9a5tgiPPPkN9DPHseolfBch4n+LHLqIG8ZQ0Q0hd5ECF1VaNoeDdtDJGNMTY6RyWX54zMzWJs1err72X14L5FjL2FvVfADjwGvQm77BG5+A9f1cFSDXWO9mHsPMiuj/M2cgv7qHyPXl+g6dJhQOg0SYokUorSJs7lKoKpITbvTjeWXiwTT11D2HiYIAnxdpyUMys/+BpVyjeWay8X5EvVWDSHgvYvzPL9/kKmEy5IfQim35/nuWIiV8ud0cMlPzoWOhMjhh7DyW4jAv5OLBqDGU4ih8duCts99g1G6Ywbnlso0HY9k2ODwcIqhmNrOd5EBw1EY2NOF5QsUARHFJwg64kuHDh06dOjQoUOHDh06dPiL464XYH5Z8VCYL3yxvcxyqYk1muDDqO8gCNid1UkdGubsQoFywyYZCXGgJ0LvlXeQuo7fv5e6oaIqglRYJ5AQMVQqtRY/u7jEtlycB6Z6WNksc+bMFbqySWKByvz0Ai8814+s16g3omwWl9qhyEKgKKAqCi3XZWVxjScfvod/c2qWiV6fVFin7AT0JU0atkfE0HBcF1m3COo+3XGT+wbiuG/9lJjw0H2Hw0qJ/RNQPHua6sUWrqIRDI7Qyo0xu17k/piGX8zTPdwkFxJstnykDJBuAJ5HrjdHKqjDjWUm9t1DbWont27NkEv2k+vuQws8XNoFJW3nXrb0JFvJPv74Vo2GL6nUHbbqFls3m+TiYY4Ox/mTfMBvHHqI4OSbZC+eIHzfwwTNBqHWXlIriyi6gZbrRcn1Iye+gxNN4CkqocVp6m//rJ3ZAQStJt7yPJGHnkLbtRdlfZUJ06Rg+dQ80HWNZNRge1rjUC6FEALf9/F9q+0kBsQVn+d2D3BiocSJhTK25zOUirB/KEsybZDo/ybOGz/BunwWbWCUxG/8DwgjRADYg9t5Iy9pGh7llkfLDVir2nTHDNJhjQ+/pGF7uIG4Y231IXHF49v7+nhrusB6pYUE4qbOEyMxjFvLBLTttBRku+x7u07mLi+g33M/jlDxEHi9Q+i9Q2iuQ6DrWOLLg+f/MlEUhbqvslZ3aNge2ahBrm+M2Dd6UGo1AIJ4gpaqYzpfkg9jhMCMfOI1KSXbMwZbA0kur1TuNMBoiuDoeBe9YeDLYz/uYKk6PYM9hMZsvCAg2Fj9qEsgliBiqLTqTRzXBwldIcGN63Mc3reL5UIDgUBTBIHjIAJQmzUentjBv31/jsd7NPIfLOHJgMFElpDTQlUktidxFQVlbQknM4rTN0ppzmEwGydc2eL6uzcI8uM8HqxzT/8oP9ywaLUsntyW4YhS5tb/9p/Z1pfG8Fx8AQtry4wcPEBj0SWcySDiKWLxOOUgQNy4QHVjHafZ4vChQ4iQoFWu8LOr61iVKm6zybmTF7j3a09QT2ncWA9omhG6Izr3T3STi4f44GaJ2lYeRWkri4Hr4q0ucfjgFCfmCpQaDooQjMQNZK3CyxcL7BnOEPWatGwPJdy+fkJVcaTgg8Uy0vOZ6EtxT7eJLG4QfvxrLNVcDF8hM7yd1lsv0Vo8wWA6zsDe3fzHm5tsVpooqkJLaBy7tckT23OcWihSarqsqZCvWxwezrDXtLBe/APWRZje7ePg+/j4KBfeZc/+h3jlxhbf2d2N8rGsCyueIvrsd7BPvYO7sQZI1EQK8/CDOL2DP99guotxMjni3/gbtG5exV5fxdRMlMFR1pZWaWxuYqbTFKVKseFQtAJyIdAUCOnqne5AAM+MoA+NEayvYIYMQs11YtEITaEhTJPq0CRvfXAdfWQbLgoDCZN8w+a1G1t8dzwCzTWeGE+R+P1/DUNHEUiIxMivbbFjsIuvRypY8Qxi/3Yatodl25ydXSfXlcY3DDatgFTEIBnWCVwPPQCvXkdpVLEIePH9Oofuf5yHcjoKcLKu8/tzNk5QYzzrE9ZULq2W6UuGieoK/SmTRUvnxnyJaKGEUHQW1grMbFV59NDjGG/8CFmvoNy8RFwfwO3pIZNOkN2RY7VvhO6la2gXTpDsToBnkXzgIZzzJ2gcX0FEosS/8+s4CzO4xTxSCERhEzWZxo/EkIAzewN96gCeqhFybDYjKf7k/CL1hk3zdluLrgriSoDcXGF5JsA6/xb92Rg9h+/DWriCoUArYlBqOnfmwkg6Q7K3m65PzYVWtofYc9/BPn8Sb2MNVBVjdBv63sO0zMiduU8NPHYkFSZS3TgBhBQQgYeQHwnbUkoU6RG57dv6X4la6tChQ4cOHTp06NChQ4cOHf6b+YUKML/zO7/TXpX4FRBC8K/+1b/6CzqiuwdFtAuzX4SmKJ9Z2+wHASM06XXn8BIxVLtBcH4NggA5vA0lGqPh+MggIB0xaDo+CoLhpMHkUBdzxSZ/emmN0ZTJ0NgQutOi13cpCIWzp6/w649OcX2uhqoIBBDSFQxVoeUFRA0NIWCt0qBYbSAUhYd39lCwA6otl0azRcVq8fhUP4/tTaJsLFJZXKbxyg00fAaiKrrrIhdnaZ15H82y6c314plR/KunyJbXGHzqOUqlKmmvC7E1R7bUIJ7qxtZNJBBWIFReZmLbMKmLbyNufED31/8W/toiahC0M2/qTQhHGB3vYalrjDc+uEE5qTFdklieT29EY1dPgrmtKhs1i7qfYG61xOahB+g6+SYAwcYqgaLi2xZ2fhN/bBfrSpqbSw5uWjDRDePxgODUsU9WdzQNhKD5/ltEn/8uzXIJTShkIoKUlKTGhxnsNvE899PNE3ewUTm9WGCx1EJTBVN9aSKGRsX28EWElmbiC4Xo899HqBqe3UK4Dtg2az/9EaNSED30AMnRHP/5uouqqjQsh1ZEI3p7NkhHdAxFIj/VjCGlJK15fHsqS9UFX0piukJc2ji37WA+D6HpSPHJ0eoC6MaHO/7Cz/5loigKSw14+erKJ/IJsrEQX5/KEUt+TJKSEtndi5pI41c/a3ljTh3AjsQ+U91TpcfDw3H29MbZajioiiAXNUhoAfIr5nXEhMuTU728dnUdx7bbHWBCkEynONQX5ta5y+zv6eJ6voWGpNawaObzPDHZx4mZLWIqOIFPNBrlqV05fD/g8R05+oSNZejUmw56Tz/B2gKVRgs9ZCAlOFoIs7ef5LbtfLfH5cS7Z5FWHem5XF/OM9ZvIl/8L/z6N77Pu7NlYvkam2ffQEpJaHIfZqOMszBLzDCx5uPIPUdYbwT0jQ5y4/ItPpgv0HQSjOzdxWhflrcuXCdf3KB/T44d+ydpbGxy8cosIV1Fz6/zuGlxX9il2ZMFVaMVMjh2dZn7hrpZ1VUs10XeFhcDzyWpCU7PbTKke9SFjrRaqJUCXs8Ab1xZ5ej2Cfg9ZswAAQAASURBVGZuzgGSgPaqf0MRuL7Pd/fk0GYus16KcdyOc/76ElKCbpn8cLrC18cOsC1i4s1ew9JNitUyAHo2x7qnYHsux2e3uHc0w0AyzGjKIG4oJHSJOPMuocFRIu8fo3l8vh0mHwqR3XeYlFXgrN9D0Q7o+tgwDIKAZiqL/sy3idarEAQE0RiWZrTtuL7i8/Vuw3VdtL5B7NPHaaVyrBaqtD44e2e7uecg0432tW15PoRAlT77+pO8+alOMz8cRYRMDgx3oV25Tl9vhtlii/DwKCdWKrfFYzCkT86rkerqwms2qbiCXx1RkT/7T6CoTN6bZHp6EW1gFKdSRrgu5XdeR8qAVHcXmbFtFPceZaQ3y1KhhufXaOgRPD+g1tIYNX16x/q4b+8YMwsbCM9mx/YRdlvrcHKalamjzKzVkC1BxVN5q9jkhb39eEHA9Gadqd44uViYk0ub7ExoOJ6PrioIx0YRCu/O5PnG3nuovf82ashgfHyIvJ6k6EiOzRZI9/VhD0wR1aIk4mAMDdD42Q/bnXR9A4hInLoeoexICkoC6bqkIwaJpoWpanghE6QkZLcQczexZ28RsT2+1j/OVSvKBzObCAE7+tvPJmmGqboBGd2AchG5OE1qaJDWyiJ9cYNMxKDl+SiKStczzxBkogSfsnYMpKSZyaE/8U3CdhOEgmtGaAbBZ54fHwosJvzcgnaHDh06dOjQoUOHDh06dOjwF8kvVICZmpr6K18g+otCBD57+hO8cePzV9lP9sUxRPCJwFkpJQyPocxcQyzc/Kj2kMlxNrGN47N1HM3hiR05TswX6E2YqAKGuyK8fHmVXCqC57icvJ5Hui7fPDjCE8MmVqXCwmqBmWKTdDyMqSntXIggoOkHIBQUIWhoEeygXZiXdosP3j3Dtv27mdiVw6vX6dd9hoqztP7TiwSqzsCuvaz25kjWC/jLc6Qff4rG5XM0qg0Cx8JqzmH0DRKoGvYH7xLP9UE4TiyVwH37NR498jXenS8STabwK2WEopDu7+WxyX70n9zC8zxEyCT1wq9SOHuaxtI86Vw//ffsp9Uzyh+dWWEkkeBq3WFnKoKsVAmKNTRVYTIcpRKLMZ1v0JeOUEWni7ZVlDAM9MExnPwm/vgUb7tpbpxfAkAbhNlCk5we8LVtBwhfePfO9QmMUHsVcakArSZNqbJeatJyfaIDg1wqq2Q1j4mkCl9QjF+tu6yVm2RMlYnhND+7tkG51VZr3ry5xaOjCZ6dOgI/+Y/45RKxR57BuXaRpu2yuVEF3aCWL7Bj+zaeHryXN9bbha6y5RGL6yAlB4dSX5ht0h6bHskP9Rbp4yoaxs49tE4d+9z3Gzv3YAvlrhFavoi6r35GfAEo1G3enC7wzV2ZO7ZsAJYeIvL0N7FPvIm7ugIyQBghzKkDyN0HCL5oaXXgkdYgnfxQlHLvdDh9FaSUjMUVfvXQEEtJn0rdomd0H4NRlfdWVplbWOPeoz1sFVy8QEPTVK7fWmJiyOJ/enQHrXwev3uUlFsnp9v8++ktapZHaluW8YMHKJw5xazt058bJtYo0qjWCRRB8shDnPfTvPbiSfZv6+M3jm7j7LUFZlYK+F6Ap5k49TrVk28TxMfJJWM0C3kmnngC5/03CfJrOEaYhhsgr14hUSrTOvgMf3Bpk0JFxyuUIBLlSsmjFbKZPHIAw6oTa5ZRFq+TGh7h/vEjVJaW6Zs/hVAVgg/eIzW6ndj+Q+SvnqJveonsYA9/Z2on72/5XJjfQCBIRkJstnxSik/g2IQMharjEFY1VLX9dyOVJrAtBEAQIFQNNRKlW5NErpxA1KqsDd/P3OwqAlA1FUc1qLZ83ilqjO+7j3Q9T9Cok86kqGhhSloU22lf5Lrt8c50nm/t6WUwGsLzXDTbRQl86m+9hL259dE1tm0aH7xH0jTZvn8Qyw34TGsabbsuN/ZR3tDdfq99FfTBUcIHH6B14hitYhkAoSgkdu9nLjVCs9Se/6KGBnjous7ujMJKNsx0vkFwW/yVgWRy2xCjtRtYsm0/NZ6NUs9kaCzbhCMmRtREsxpQqREOx6gs3KJei9Jw5xChKJqm0V1YYnh0iJVqAzWeYK3psau7G6tWw1Rg9twFeid2s16s02xYqOEwYV1FSo+QZyHtgJRVZur8j7i3dwx9cjuR1jpeYZWgVIA3X2Sv1Dl48AGOB938ZKHBi5dXuXcoxd+5d4hdWZPVfJVdUYltO4TjcWSjjhoyka0GHgJ3rBekJLnvEP/mShNHOAzEdEobK1hrDbYNZEnJCNt0SfOt/4y3ONs+r7E49tHneX2hxb5UP9b6ZaTvs+54FHWVMcNFC5mEB4Zpvv0y7uY6CiBLJRrnrzA5uQ99cjd6tovr6xUuFxtE0yEeGcvQJXaSmb8ISzNoDzxKdHgC69oFwrZFLJsjtO8wdlfvZ8SXj+MCbuh2Z+HH5lchBJbUKFg+rh+QCGmkDSD44n116NChQ4cOHTp06NChQ4cOf1n8wjtgOnw+Ukom0iFuZSIsFT9pRZaLh5jMRQiCz7ZJWJqB+fjz6CsLuDcuI8MxNvc/SqngMRyVLBQb/PjiCke3ddMdNcglTH56aY2JhErQKONrOq6hkY4bzC5t8rgZ5tfDm2zdN8rVUp1dkwP0d2+SL9URSAwEmgItPUIiGWN1aR3huphS0KjWmL16kyODhzEXzuO99yqWsFFCJs3ZGeyZGww9+TXcpTqeriK1EH4g8T0XxYwQHd9GeHAEz4zA2Dheo8bm5Wv0PfMEZq3InuJNBo8cYXq1hDs4Rr/u019aIvrjdzB/6/9KqWuYP7iwwubMAgM9www9OEWxWuPclkCVTntl7/ZRchst1q/fwHHa51MRgoRtE1EqJLftRHg2EeGDoiB0HfPgUaytdbxSkZWBfdy4uPzRdatVEJEYhWqLCyGVo6kMQbl455oqXTlURSGQgqVSiwBBYscU1d33cmbTgs11XtjXz0D4s2NC0zRubVUAGOuK89Mr69Q+ZrPTcjxm18q83lrjWTOGEnFxZ29gXzwNO/aCqoIRQkpJaXaWh8d3cTGaZL3iIaXENFQeGM3QHxFfaeVwEASI8Z1oC9Nte5iPofcPw8jEXWMx9mWs1pzPiC8fslxsUrYzpD41YzYjcfQnXiBar7QzX8IR7Ejsi8WXP2dkEBBTAg73hGleews914vuhjmUSnAxFubMB5d5ZN9O1EQS2RvGqBXZkdBw334RUWgX+iOpJI2pfagVm8d7NXbIKvbwBPrMDFvLq1iaSne8Dxl2SU1s46Sb5NVz0yiKwsUrs4woA+wRVRp93Wy0fEL4uEGAtbJK7sgUQeAT7R9ALM1CpUigGzTdAOl54Pu0bl0l8uALnDq3jCJgYnCEZDRMKB7jrdkC705v0utWieoK940Okbp+nszGPD1TBwi6srjFAn4sRai3l8p/+Tcoo7swrICFWw12lDd5emIXoclhljbLHBzNomSjrG2WcGJdaHYLr2khujLQqJHLdoOiEUSToKltgVuC1t3HvrFu5Ls3sHtHuLFSwnddIrpGkO1h2ZIIYMsKeKsIv/Nrf4/lzRKTrsEfXVzHdz45HhQku/vieN7tOVwoYFnIyme7qQBal84yeM+ThA0V+OUqKgtdx9k2Rbp/mL65FVqWjR1Lc8ENs1RqZ3cMpsN0mYJ4fgv3zHHEwjRPTR1m/8hu5lqCwIwy1hWlR/PZ/P2XyG818KUkpKkMDDTpz3RR0OPYqkZNi1A3M+SEgqrrpFNxkiXwmxUCx0acep3n7n+K+R2TXCi088fGn/86tTdeptaySEV0wtKnK6JTqVsEqo7wXJRWg/6uGKnKFqFbS/i3rqJcOYe41I81MIJ95HEWowMY0RjK7E0qL/4RD97/EOrOQ9woOQTNOueO32DfngxqE2o35lF0jdDEBI7rIHUNAh+tWSWpZNj+zec5q6VJxgK0wjo47Rwna3WJy6vL/P0XHqBQWEYcfJzQ8E6Mc++i5Xo53dRYWFpl26HtRFcXiQU2mvTxETSkQlckhoglcK9eANqPinAsSpcDhZnrjB59hn99bBbPthB6iFKhzruORSUc4WsjE7Bwk+a1Sxgv/C308Z0I38c3QjSl/ErC4YeZNIqisNKEV66v0bj9PFQEbM/FeWQshS6/oJ20Q4cOHTp06NChQ4cOHTp0+EuikwFzF6NLl+d2ZFipJbi6XiOQkl09cYaSBqEvKSpYmoEY3YGc2MuxhSrvXSpxcaWCoStM9cR5YlcPb9zYoD8ZZnd/iqbl4MzP4PsBEUNj20AfwdoislEn37uL3OljJFLXGX361/nTWyWevH83r5yZZmurhG7o6Jks2Z4cCVXy1sVVhjJxrNVlFAWemuylO2hRz3RjPvlN1OunUK0m8eFhrPVVWieOkXjwUVquhTa2jfo7b6CksnTfez/O2RM0zr1PEE0Q6ukl8fjXyJQq4HmYg8OEUmnc/+Of88jz36f52g/x8xsEQGloO/k/+iPiDz7OUjXFVjSHr5psXJpBRpOk+3poOhp+PEUsEWW4WGXF/aioGUhJw/EJ63AoqzLbCNNbXUHbNkns/kdoLszhri2h9vRzaav1+RfBCHFjfYODAyMYtwUYAF8oKLl+3KmDaL27cRSds67B+tZHPvinFkp8eyqL+JzVu6poZ3fYvmQwrtOXVWkEgqslj4blELRazBfqVLbtJ7c5i33+g/bn8utE4wM0ZHs1uOX5NK+c5/tP/yprNZvBTJihmEpU8Qm+ohUWtLtBQk++gLK6TP3GVSSC6K7dqP2DWMrdHwQuhKBuf/E9JQHbDz53xnThk90Hv4BQgVYqi3noAVon3sYNR+jtH+Q393ZxvqFyc20Ls1Di2QOj9BqS2ffeZjVfRddU+reNUt//MG9Ol/m2sk709GWq5SpLVZttjzxE7z0HqM7PkbcDjPGdnKl73Ly5jAoEvg9Scjnf4qH8CpN7hghVPbpKczQ0DTUSxjOjBL1ZksOjlNYWSYzuwLx6imCmveIeTUPtH2J6aRPVNGk5Hk2psKu/i/9wYpGwKrGaDaL9abyZ67y7MEP0njG2z7+ON3eT0P57UacOEhUqzfffwbcd1PIW2UiWkq+wVLEZunaBbz4zzCoBfjrGuhBMNwVuqUY2kyDd349VyBMeHWEgbNKdjeCZUWpNCy0aIdrTx8RwlvVCmZ7v/Rbu0jz+gk+yJ0cQT1MRBik7IK2oJE2NlKmhmQZePE2k4fLsZI6fXdvEv92uGNZVvr2/n/7wRw1V0gwT2DYSMDQVAfiBxPtwLBkmITzSIeCr355/5QmkxDIjRCenOHWrwEKxicRBACNdUZ7aniW6dJPqf/7fCT4UseZnyKgaI899B4bHqIZ38MOrBXbf/zUiF9+nPj+L7fmsr6xx8JkH+clCg9lCE8cPEC4E1Rb9sQgHkgr2T98Eu9W+t0t5tDd+yIF/uJ3crr2cXKzwcrPJxI4jtE6/R1IoOLUq9w/kCMwI1/MtFM8jGw7Rjc3jQxHc948RKCrEU9ipbhZuLRLOzPHOqkOdAuFkN48/+Q0Kb7zE1Pd2MG/7BMtz7B/NEZ69Snf/NiAgLCTe5ipidDt+vYYartIdN+kbTuMGcOqds1CvE/QMtM9LKoO3tkF0cJh3FyuELYWFa1VS0SyHnv37bI9Jbl4pIQOfUsvn3qeewb1wEuvWNTShEN9xL9HHnqZy9gOqBx7FlgphPBIbs/QpS+i92/jx1SXUUAip6QhF0BvVUYsbzJc98vcM0714CyUUIhACV1FBUb+S8BIoKiVbsNlw0IQgE9P5ydUlHPejeTeQcGOjRsTQeGgo8pUFcV2A4jpIVcNV1L8SCwg6dOjQoUOHDh06dOjQocPdy10nwARBwDvvvMPZs2fJ5/MAdHV1cejQIR5++OHbgcq/POjSYywu2JZKA+D7PvLnWNGpKAofrDf4w/MrZGMmYUPD9gLOLFVYqdg8NNHF9GYdQdu+JjPQj1/YwlZ0rPV1lFoNVVPxUNhSo+iHHuenPzuOMjjKH61scejADvaFDJquJBYz6YtquI0GNDIsrWzS0x3nyfumuLjR5OzpJbyNFVQk40MPckivwuUzpHZlUAOfyMQOWqrJ4s05tK4eunfvpf7qj6DZAFVBi0bRkHjHX2Piia/jNRqE738U9/olwvsP0zr+Bu76Kp6UyPFJpgtNTNOgdPw4jzz5Xf79vMdcvs7QyCTFapP1ksOOoQRKPM7qZoXtaoNr0RDlpo0ftHMTAinJpqKMWZvs3n8PESuCMTSEDJlo1SruZjsI2PlUx4SIJwikxNc0SGYI1Opnrk1och+vN8JcLH/4WecT24sNG9sXmJ9y5/M8jx3dMRotmwNBnt7Z41hbm+hhk4OTB5jPDbIwV8BHwU1kUazbwo+uI1ybnqTJXMVF3pZ6HMdlvdKkaruMxmMY0v0zawdSqHxQ9rhYjNM1/iiO67Ox1mKHtHhwOIl2l69CllKSjRpfuF1TBBFd4W4NFQikxB7ehtnTj1IpITSN3msXeKy0wX3pLqQfEDp5HbnvMIlf+U1koYyrqLxaVLAqOt/TFph57XV64iEqLZeeiM6V194knOsh/t3f4L9c2CSebxLeXEcVCvGIQcP2CAIFT6hII0SPtMjFJMFqntHRQezJeyj1jvPaUhXda+FcX8dQYM/kU+zO3sA98y5qOsu6Ba7nY1k+NU+SHs5wa6uJFBIci3BIh3oFabXFzjOLJbbt3A/n3sVaXkQdmyRxz72Ur1/ECIdR4wliZgRDNSjXW6xXmhjVKnLPEf707fPkopsc7O/mvdkCZQ/QdEZGhvE9n0O5EGFd4ehD9+D4EsuHZsthI19henaayNHd9I7uQg9JFtdq6L4gFYLtmoWSTOEBg8kw17aanFqsMldsMt4V4x8+NMFmrYUXSExN4UBvBP9294tQFG6WHPrTvbSkiufZeL7E0BR0VUHqBqQy9GXiOF9iz/TLQBiX53dlKNkZWm5AWFdIh8BsVbHffPkj8eU2wjConH6fcP8olZbHZs2moCjsOvwMg/e5OM0Wm9LAdlV2D6aZKbaQgAyF8Q2Fpw4N0P3i/07geYhQGEVRUDQdhsYpanH+t2NzzJUtRlIhTjm9PPDgCwRBk+GJMa5d2WB3JsIDIykkgu0pnVx+AVbXEUODuJvz+MkE61UHu2Wjz92ku38/zbUC9ZrGO4rCw7smEY0yhi3o7k6yL+bj3lgh7ns8unuKszeXsW0Pzw3wE104kTTP7uvBnj9P3YwRJDOIaJJaoUhyYIBWsUisf4CCHkOrefSaJkqun0p+nTfPz6I/dT8i7tGjSAZL81w7fplwIklyz71IKVktVPE2irxljjF7aYkgkKiqwraBcR7aP4iuh7FnWgwPDuNbFlq9jF7dRBEeApiruvTG4hhTB7D+DJqGK3SOzVW4sV5FAqauko1H2Kh7pM3PCjlX1yrs74sRVX6+eVsVENpcxb54GrdcRAmFCe0+gByewFbvun8ud+jQoUOHDh06dOjQoUOHvyLcVf+jbDab/LN/9s+Ynp4mHA7T09MDwKVLlzh58iSvvPIKv/u7v0skEvkFH+lfHEIIHFSKlsTxA2KGStpoF9+/Cg1f4cxSmVQkhKIImq6P4wWoimC9auF6kmLTIWIopE2FukhjESKjSYLFadxwHCWkY3oWlVCchYrEMiIYikY53sWPb5Xx/ABThUrT4ehYF5PdYR6fyLLSWCXRk+PNpRonZjYZiihIx0cRCmdmN7AH0zyVSlA/fwqh6SQVBWXhFis12PvYs3DtDLLZACkxe/oJXJcgv4HTaiJdF3IDqPuPwMAYNCq4H7yHGo2CGWXdbYsnihAgJfrWCiGtD1szKLZ8sl4Dv1FncHs3djRCvVyhePI9nt93kEU/y3S+ga6qTOaiDPlV0tUt7OmrzJ4+Tg8WChIzlSa2czfW+goTOZP125ENSjSGNG+PTQm5oX7S3d24W4v41QpqJIax5x4Y20Ftuv6F1y6kqahKex+fpj+mEleKVF75KZV8ex92vY7Iv87U7inCiX6myzYhp4Xvuui79mLfuIyUkph0GOuKsVW3aTpt4Wu0J0V/BAzpfPbLvgJ5R6CUCjzibSDniohUhmq6h9P5Bt2xEHuy+l+aLdeflZ6oRipiUG5+9lxM9SVI6vKLonnuCoIgwNJN6OpDURSsB57Da1oY9RIJq0x04AmWZJhTSw1evOECLgOpMF8bEFz5o3ewLZeuqIHlBVTKTfoSYaRVIdssMJaNUttsogZeOyPD84jrIXxVZU93mIGKRVS1Kdy8RcMNKEQyRHcd5tjlLSpWgCE0kukurHKBs7fWEDum2L+3xVq+wtp6npFnumgtrKMoCqqAvOXevochGwsRbK61LQCR1JsW/lA3AeBrOkvnL6EeuJ+iY6CqYQiimIGKdCxy8RDhtEnU0Hjr3FWs1VWWDZ3hfSn+5kO72CjV8bY2GJItJiIeoTdeJxicYNkY4LVbBQAUBcb7u4jpBu9tumQKLbpSWVZLDVwEKrAtFycnQVFVYqbGa9fbAfBJU+PmZo3r61W+saeXhCrZFleoVOvUEMRiEWSg8PKVRZ7I9pMd3kaoWkCvVtoF5mwWI5VGH99BEIt9pU4BRVFQVfW//sa/avi3M5Q0gAB8UKol/OLmR+9RFNxML1tWQDXfJLmyxauFOF8bTaCvz2N/cAwUldD4LoJwFxdWqhyd6ObpXb203PZNnotqjC6fITa1F1f4OLO3EIaBdugoeS1OYatM4GgM+lXUqoatRPnTFR9FhPhWtM4DPSYvvXmaXcPd3KvXiNw6j7VwCxkEdO3ahfHct9i4fgO7YoOqIJW2mOkF4DfrVAKf8KHdJEyNF7pTOFfPs/XOZcZSJpGNeQ6m0yTv2caZ1RpBxCCeijLVm2Cp1uI8A3w9G6InI1jbLJEYGkIzw8Rcm1Y0Tnmrxn0jaS5Mr6LqMUJGFFOonLs8y+DObXRVN6gd+wBcl8baKlYxj9RDDDxwlJdny2x4GsHtji7fD7ixuIU3kOXB8SRqXCeiBKhhDVlz8f1Piu/GxC78/pGv3FWiKApXN5tcX/9oUUPYUNlqOKxULEw9Rlj55D5tL8DxJdEvWLcjhMBXdNpOdoK0XcE//gZBtW31GTQbeO++RmjHGvq9j+CKX64FQB06dOjQoUOHDh06dOjQ4c+Hu0qA+b3f+z1mZ2f5rd/6LZ588kk0rX14nufxxhtv8O/+3b/j93//9/mt3/qtr7TfH/zgB5w6dYqVlRUMw2DHjh38xm/8Bv39/X8Rv8afGSEEeUflZ9c2KbfaRWABTORiPDaexvgKXQQNN6Dc8qhYLk3HZygVZjbfwPYCBLBRs9FVhVwsxCM5nf/jusV6TbItoYLbLjI8vrOH2o3zKOkuCq4g6O5nTZosFpq0HB9dFYxlo6i6RNM1fnptkwO9UYb6x7B7ejj1yhVCetuKSKgq1aZNyhDM3pqnum8HxunjoKiUKg1iu3YzePUaW7Nz9Dku+sAwipQooRB+vQauDa6Nu7FGeHI/hZ/+CYm/8VtozSSxb/4N1EgUEUui2AGVt9+lXi0Tj+nUfA9T13BbLSqFIinDxa1WqC/Mcv/UCK/qJnrfEJtvvkY2nWJ4YADX8SgfX6asC0aeeoRrP/oTdFUQ74oT08AqF9ErJSL3P8J2T+FCKoEVSaKETALXQVUURCjEkZE0TihAe+57hD0H0WwQuC6yUeO+oRRz+c8XYfb0JwgJn+Bz6lNht4m4ehJhakRudzXpqsBUBK0rF5h4rBd6EsTPH8NaXSD+3Ldx5m8hXRepG5hKwFAyBJEY4Xv2kR3vYm1t7fO0np8bTdPQFhZQX/kBldZHlmxaOMwTT36DD9Z1dmS70O7S7pEPMaTLN3f38PqtPGvl9kp4TRFM9iW4dyhB4N+9XTyKoqB5LsL3ccwop1YbXFypYLk+YV1l3+AIj3QNYFbL9MRDmHrbVufAQIp6aRWn0UAV7fwjVYDjBcwXGxiqQL1+jV0T9/DuWoAZ+AStJiIIwHVIJOJsa6ygXDuD+fDjBOUGiR17eLug46xYnFqpIaSPoarsyfYhLJuICDi30SA7uo/1mVeIZLK0AsmO3gSbTa89H0QihHQVgcFAOsKeWDdZpd0F6JgRzKVzEImx0fKxsAgUA4wwltWipfh0GxLTMFguNpCOReTBbspdBgce6mK60GKr4dJV3OTpzSu08gUMIbFmbuIYOoXlDXZO7mMuN8bMZg0ZSJqOR6Krl6vrVfYOZbl2eZ4X9gxwfLHKWrnB9GaN4e4BHhzPcmp6404+xUBU5bmsh1krkS7UiWczvHJinVtLbdVWT2fo2jbBeC7BB5Umjz7wDIV3XsM0UwAUpGAi14dx78PtjIyfcywUXYXpjSZbdYfBvM9QTCOt+8i7XAT9syKDoK2U3cZLdzNfsXG9tpgiHYd9OYF57TRpbOxUDMv12Tr+Bv1dOQ7vf5y1qsXPrq7f2cc9uTA7F+ZRN2aRvo+29yCqGWFmcZNi/jrq2EFCW/O0YmkW6z7dXYKWLRFI+rdm6PGqPHVkJwPVVUpvvIalqwzE4+jNGo3zH2AtLxF/4hvYx8+gagZifBeri6V2B44fIB2bRqCw4UeIlYsUzp0BRaEuEpg79lFzfLLL1/hmMsnN3iRvL1V5dybPd3bneFquc+HfvsquJ57n2toGyUgJqQjU7l6q9RYpQ2DWS4RbVQpKBC/di64GFOpFHu1L4SktqqpGbt9+kukEtJoo4TDVnftZefcaWirTzhTzP1Kk51aL3Dc5TKbbZKvl0whU7GQPoUgKzaqjqQrb9+wkiKl/JiHDkgoXVz4SXwKhsFZ36Y6FqVg+yxWL4ZRJSHw0xg1NwVDF5+0OhMJCU+FHl1a5uVmDIGBbXOHr93+HiZmTyJlrd95q37xKbNde3GT2Kx93hw4dOnTo0KFDhw4dOnTocFcJMKdOneKZZ57h2Wef/cTrmqbxzDPPsLy8zMmTJ7+yAHP16lWeffZZJiYm8H2f3/u93+Of/tN/yr/4F/8C0zT/PH+F/yaaUuPHl1dpOh8VNSQwvVnHUFWeGIu1cxd+DnRVJV+3iRgapabLcrnFUCZMywlouT4DqTBTvXFqLZs9aZ0nduR4dzaPlJLRoRx7MyFCc1cIinnqqknfngynpmvUpIcTaAgBvpSs3N6vqgqKls9yoc7wSIa64zMcBupFNGkQymZR5CayUUcGkjoa6cAndvRxLn5wgdFslIlvf5d8uYF74QSteBeGEYKlW2iui7AdFFVDTaaQmo5MZDACD1YXEJ5L6+xJ3GIeUlkOPvYcy/kqhekZjIFhtDVIqlBTFaQfEDENpiIBm//2X3H41/4Rrd0Hya4v4lbLbF0pY3ntQufBpx4kf/EidcslYShUmi7xZAgpA1wp0R2H7NRu/sY2lfcuzTNzcw7f8+nrTvHg8AAjikVL6hjNOs6xV/EWpsFqQThM//57+Ru7HuAPr5c+IX6MZaNM5SIEwecX+5V6FVkrEdcEu3tjLJVaOJ6PrFeREhJug4fjECxOA9A49hqxZ76Nl1/HqVURCIyRCfR9R2jEEh9lTPw3oNsWtTdexmt9Mg/Ha7Ww3vkZY09+H9cXaF9QB7ubiCsu35rMUnbamS9RXbnd+XL3ii+m5yBnbuDcuIT0PArhDN0T+zC1CJYLLdfn5FwRX+jc16tzIBdm7GCStVszZLe2CGW72EiG2Gq6OE67K6bccpGyLQoLVeXq+Wv82mMHuXjJY/l8CaEqTAzluC+ror34H2HfIWqbGyQO3c9ZmeLG0iZdiocXSCQCxwuYtQwm+keRpXWk1UJNpMgeOER5eJIfn5zlmw9M4iga719d4sBYN+ulOlNjWR515mm8/zqt/CZCCMbGBoiODuFMHSB/aYb4rsO8fWuLpx96nMK7bxEzNBqOT932UH2fzKH7OLVlc3y5xL7RbroTsHJrhtFkhq2330AGkmR/HwCe6xIKGVSuXeaBp3cwuwVI0MNhGoFPNBZjs1RjvVCnVp9lcryXo6ODhE2Dx/pDvHl5lur8MkLXGR/tZ095lvLpEzi+jxZSWWxYTE7uRQwMcnOliG9ZnLi2wqEd/QgheFt2c89zvwKVTWSrgZHpRtkxTlP7+QrWiqKwUJe8dGUF77aCu9EMOG61eHaqh7GY+OuZZxFPoiRSsLmGUFRqgYrr2UDb4s0YGOJA+Rabr/2IfKOKqgiIJRl78HFWltbY2VrjWHj0E7tcafrogyMEMxdxluawJKhj2ykUHdRIhISp4ekhdMPgb/VAtLpMKCnoHh+j/OqbeIHHvekYzesnSaQjaIFHVA3jVQsgFLzCJmHfJTBCRMe2sx7rxRHLqGENhIotBUoqw09nm9zXmyLb1U26O90W0G9dxKk0CHV1oex8lveXK6yULXwEkeIa6+++RQSX6JWT/N2H7ufUrXXWVzfQolEOTU0RCWxOnriI73lk+mPMFBpsaiqTXTm0VoOBmIp93yGscydpHJ+/LWQolKN9qLEEhCPo0Xg7d81qIYSCSKRoRVM8mNL5D6eXWSp9+DwQ6GqS/QMptFgMT3G+UifXh3iBoOW0O4EDobBSsahaHqOZGKam0HQ81ioWXTGD2O1/2U71JYlrwedaa67bKv/ruzPUrPY+ReBzc6XM0laV3374CNu21vCr5dvvlvjrK4hU1xfeP0KIOx1nbavYv4b3WYcOHTp06NChQ4cOHTp0+DNxVwkw9Xr9S7tSBgYGqNe/2Lrpi/jd3/3dT/z8O7/zO/yDf/APmJ2dZWpq6ivv7y8CIQSrVecT4svHublR5dBgnPjPuXDU0BT6kyYly8MNJC3HZy7fJGKoRAyVqKHyp5dWeWZXjoH+NKbW4OhohmrL4ZmUSfnFP8RpWWimjtJqMNSTxr5ehnCEcNAOiDZUhUBKJrpiqELQlQhTlwGTGZ2tYhU9cPEMA7teR5GSaP8Azuoy/3/2/jNYkvPM7wV/aSvLu2PqeNfdp7038B4NEAAN6IaiKO2MpN2rK12tYiN2db/sh5EidhWK3avQjd29ceNqZzTSakaaoRkSIAnCe6DRaO/t8a68r/T57ofTaKAJQ4BDkOCofl/OqczKrKyq982sfP7P839c28JIxIk/+nXyhQpmqYTl1GmcfJfSljtJ77qd1jM/pkd44HsIWcaPxFA0jdD2fZgXTxMKJxHnjqEkkrReeBq/WQdNJzQ6CYUVxiY2Etm8neXsOHv1NvVOlLF0hHirTKa6QueFn+J12oSOvED7jieI3/c4yYXLBFevEtNDDOzejTk0ypU338WVFFxZwRfADVskAHdpHmXXIZLHX+GhcoHbp8cQkkyklofX38Xp7SN635dwfvEj7PMnEY5DgIQbCGqz8/Q+6vAHdz7BXKWD7weMpA16DRnlkyqdpHUVQwhBSBJMZsI4joenOGiSICU7KPEEzuYd+LUKSiqDOjCEd+heDLMDssKaFOXIQpXa9QK5jMnmbIhcGH5dfy2pVkKxPnpe2o0GQ36LkCK+qO1TPoQUrFscccPi6ItsOxYKXNzXn8NdmgfADmRWZ/Nw5Sp3PfwVnlPjN/sUXco32B2Pkj5/BN56Bd2I0xIKpXgvI+kwGdVntm4R0WQ29cVuVsmp/YPcFncYmDnJYHsF8cRBgvwKobNHkGaqaA8+jtNsYpZKnE+YRAcz7MjF0FSVkUwEPxCs1kwcP2Ch2mZTbhijVcMYHadmJHHaDo+Mx2murNIzOcYju8dIxQy+c2gKY2WG4osv0zc0xND2LUR0Da20ROfoGxiHnyTnaoh9tzFUF7xUbrLnwa8yUJ5jbm6RTCZFeMsOLkspKktFUmGNU9dW+c7+UaqxGFJlvQpFkmUyik9JVWg1WmSSKWpVk2jggKqhqAohSeA4Hrs39PPMkUsAtG2X41dXifd6/L0Bl/b5C1jGOMK2kD2HreYqtVdfBMNAQ2C6Pr7nUTv2Npsf+Qoz2V4cZBKSysn5Cg9uG+TMcp3nTImolkONSoR8mQEthPYpqx/NQOHFy6s3xZf38APBS5eL/J29g4T54oqJvy5ONIG2706Ceo2gWaduvz9pE7v2kZADyj/6C4S53odHV1XMWoXKL37MyJe/CVdO8tg9A4zuH2S24aMqEiu1DuroVuxXf4oaChE4NhLr4yUxOLhuzTfcz+b6LMWfvY7l+8iSRNY9SGb1OnJuCMl16Vy7iuMHREMKuq6iDY2iiPVzY1CvMPTgYeaMXt5ZaiJnenBMk0BRGRwf5YKjc75QwhUy33nwCYYuv4F59iS2rGIaMSwXnFde5A/u/RKz6RgxWTBqFlnVwoz0aEQaK6g//l/58uAY1tQUklRGTXb4j2dryL05sCxkxyKSyWA7LvFsGn9pFuE1Cc1cQKzMYigg+w7C9jCEi7uyBpt3sWDKZHpGSKjrvVN8RUENaYRVmbsmspyPNFmpW4Q1hR2DCVQEL1zK8+S2HmTx2XsZhWRBIqxRaTtYXkDjhnByfKHCl7cPcGKpStNyWWtYTGUjTPdF2T8Uw/ddJOlW9V9SVN6Yrd4UX2D9N5gATMfj6GKd4Y270Y6/8v5Gn9B/0EZjrmpzuVBHkSS2DsQZjqvo+Mg3RBkRBF94G84uXbp06dKlS5cuXbp06fL58IUSYHK5HMeOHftQBcx7HDt27GZfmL8JnU4HgFgs9jfe128KSZKodj4+MOYFAssTxD++T/gtBL7PgdE0x5fqGOqNKgnACwLumernxGKVsCSY7omy3LA4sVSjNxri9qkeXlsoM33gfoLTR5DsNuMDWZY7Fl+5fTNPnVtjMqqyP+ET0yT6BvupCB2Q2D6YRPY9aOVJLl8j1m7TMB1ifTlcI4avKSjxBImhIcK+xbW3jyDUEGlDx9BklEiMdy4uMT2UZnTXPlqXz6L3jSCqRQLPJ3bvw0jxOGJxjvDwMJIE1ed/hqKoaGNThHcdwD5zjPYzx5BTWUIH76M+6nN8VaBIUC5WGJM69Pt1ovtvp9M7RN0TDMV14vEUtdB2EjsOYKPyX2abjKzZ5FQdHBfH9ZElWK7b5BI6sgiQwhG0TpPm5XPge4TzK7d8B25hjejqEs6lszfFl6btEdzIjC2/8HO0qV20RIK7xpPIngPikwM0QSyJksri1270pyAg6lt45eX1x4ZB69xJ1J4+lIFhAtvGcRxcAYSjXKx4vHx58WbVjSUULi6WOLw1x7awi2SboKo44Rj+pwwWCdsiHdGpdlzER5iZ9YQEivD/RjZnXT4auZS/Kb6gKHjjm1G399HxwRYyh4aTXCqbyIqCY9nI5QKNn/8AXBdNrBLvGaBcqCDdeRvhc8dRJFgsNRjpT5OM6Iw+8BCF/ArS0bcIdm9DP/UWznM/JDy5CSWZQlKz+HNXWSi3CT/wGG4iw49OrxALKXx11CDRH1DxVa6kMsyU2oQUmWB1ibHxftR2kyNvnULWdbbu2sLw6DBLTQ/bF3Qkn7gmkWvlid99COf0u0gX3yYwO3g9OYzb7sOslKkdOsz/8k4eSVa4b1Mfz68IHtr/CKWBVdaaLQpnl/HaV5DjCfr7Rmh1LCxf4AuBnskQu/9L+MksbVxGQzKtpQXsRoNRrU4tFELoMNSXwl+Z4YEDW7leb+AigXbjRGwY7O4LYx95Ds+Q2Lp3K/m1EsM9CYILp8HqIGnrIo4fgOR5BKEIzUsX0Dfey4XVFkZKR9UULC9goWaSCmtYvowqyxyezhBSIPiU8eqy5dNxPvrJlutT7vgM/y1soeYHAfKWXYRjcbyTR9Dm84TjKYxdB6iPbkE//iK4Hmo8Qay3j5Dw8Rfm0BBoc5fxcyO8cTXPsYUK1dQg802PHYNJavEcw499E//d1/BmLqFYLQY374C9d9O8cIInDt3J0WdeQ/jr50pJAqdjEdM1/HqFAAiHdWK+hyoCZAS+H7AkRdHHR5F2P0g+3gc+3N/fT9Mapd528IUgGzP4969cRpbA9Tw0L6BTKDDv6qgSeJJKqWWz9cAW+i4eQSpWyTdtZNlkcuMWdF2l9NxJYipop48SPXsUeXQD6v6DPLhtgL+4UGW17dMbj2HIOqbr88DGXoJj51jbtINGZIDoxoOkFy+hn3oDJIlEdY1wMkG5bdLyDdqOhyxJjGUiDEc0MobMxaLJ2aUKvXGD0WRqPVnAdxiSTCRVENgOiq585goRFZ8DoxmevbRG035/jNdMl+OLFf7OvhFWGxa+H7BzMEnOCOBjKkntQP6QBaiQ5HWRJQiYK7Ux+1No762UJJTc0Eces4nG0+cLlFr2zWXzlTbDmRj7R1Mcm6/g+YJNfVEms2GiktetjunSpUuXLl26dOnSpUuX/8b4Qgkwhw8f5k//9E/51//6X/PYY48xMLBuC7OyssIzzzzDmTNn+If/8B/+jV4jCAL+7M/+jOnpaUZHRz/yOa7r4rrv37hLkkQ4HL75/wf/fhD5Robkr5vlmAprH7tOkSUMVUaSPt2+YyqYjst9U1n2jqY5OlfB0FQyEY1ipc6wMDm8tZerV+bwZYV/MGEQz8+w8szz7IgkaA5uYOnA42xKaiipBEghLl8p8n/dGUE68SbmxSVCqkwhCJE8cAdPmWnOrra4fSjCZrlF1Anx5QP9PHVigdJaHinjUw4nGVJkHhjUsd58lURPD9HxSdJhFb1dR2zeQX9J4pmlFlF5mDsODJMszjPYnyUtB7RPvIWzNIvemyM8Mo7XbuHXq8iaRuSBL9H8+Y8QroOsqrgCzGtXkK6v8b0nvsVLhYDtMcFA4KKN3M6Lp+ZZPruCDEQ6YXJug9tTAiJxnsorzHdgKaTx9zdvwz57fL25rxBULZewrpAxZPQtOwnqVfA/OuAp6yH8wgqB1QFJwnL9m+ILQGB2iLSrXKgJxtIRxmO/2qPLVTXCt91D64WnwbthnaKqIEsYuw7g1KsgBF4xf3Mb4+DdALQDhTeur70vhNx4uY0pjfDFE7QWzyN3Gkiahj61mdCuQ5ihX23RJ8UShBUYzURYqZu4N4KRiizTFzOIp1OYfPSc+U3waebrB///vI7jt42iKHgLs+89oL3rHp6eaXL90iIAqq4zukXnrl6VzpFXkWMJjOg4zYmt+NcvYbVahCpleuMZiufOkdm+n809Oa5cnsNMJhncuZ2rIszQ2irpqIR07RyhrbuhnMe9eAYPgdrTj5kbIzo2TmfHHfz5qzM8PKAyunCSldevMBxRUKyAqe17mJvYwvVCQHZ1lb3NWUIzS9y16xBlyaB3dJhjy01mqhaBEHiBICoHfH1sA2Mv/Realy/h+gGGpmPUKtivvUDsy3/A5aqL02rTn4yQ6lT5xxs0DGeNWrPClZXaeu8j20KYHRTLYuPGHYzm0sTFCMvxBCeuH6PfbLI7LbN67hwZySMuHPT9B+hs28D/MAaqY5GI5smc+CnW1gdRENhI60FZ3WBz2GVkbIhENMyg4TKbMgh5Jm65gHBsJNtCUgwSukpBUWm6AXq1RlwKsJUQpUqLdDzKYDJMw3SptF0GkiF2D6dYrrVZKDe5b0OWuPyrVRj/lxtHSR/4K8ATwe98/H/a+frBx5/mmD1JwR/fhDYySa7t8O5qh2sdQa7lojZabHrwEUS1hFhbQjZC5O57mE6xgN6fIxifZLzuEBmNczGQUIwonhA8d6XI38/0cd3IkblvK30RhWTfOP/55DKPT2xCOn+MsbSBE4DrC2IhlVinhrp9L603XkYqlYhNb8U7/ub6V6HEaSkGZnaYy0PbOH25QSfks1h3QIIHN/VhOh5j2Qi5mM4/eWCaVEQnbaj0XDvO+bqFG4Dk2QSGwuD0FPr1s6xdv0Jq4ybmPYGveJivP0/q7nvJbt0Gi9dRZEH07odxbJvVH/0lquPzzw/cxsrUBC+sBfRk4uzKjeA6Nm/6PcizDcbxMLQIc6P72b5hG9FjL2EtLXD7vgd5ruhjewECMFSJjuPx8JYRQtL7ywtNC8NyuT9uw4k3aC0vgRAEU8OED96BMzTOZy0unEyp3DXVy88vFG4uy0Z17tvYy/G54s2KlkMjcSTh36wY/eVxJEuCsK7csm8hScjhCEGnhaHLaB8o2TR27sdNpJG4dRwqisK5pfYt4gusW6S9NVdBlmWKTQvbC1hrmJxe1vjajgFi8mevQvvbdv3q0qVLly5dunTp0qVLl/+W+EIJMI888gj1ep2f/OQnnDp16pZ1qqryzW9+k8OHD/+NXuNP/uRPWFxc5F/9q3/1sc/567/+a37wgx/cfDwxMcG/+Tf/ht7e3pvLcrnczf8dz2e5bnG91MJ2A4bTYUbTEdKRT1mucgMpYnFsuY3lfVhk2dgbY2ogi6p8+ua192pRfnFhDUOV2TWc4kqhxVqpzohokRno5YV3rxBx2nxtUxr3Z6+zYK1bdejSGtmFq2y8617eFhv40asLfH33MDv1DvM/+GuwTfriBpfWWoQ1hfLPnuKRJ55kTpM5O7NGZCyFWjZJD+X45r4RFloBpVqLno2DDIWHKDzzEyY2TxNxTFp6lBU9RtAzRU84RU2ysNwqjgh4agUOju5EnT3C8uVz5OwKRqeF07kOskzotnvR40nUvn7s2as49noQRFY1bF8gS+vNl7l8lkc3bqby3E9h2y6+f6kInXWrISmVpTI3w4zrEJ4a5L5kwFe2D3OxKVhrOih9+5ny68jFVUwf0rKM0pvDuuMBWj1D6I5JfHIaOb/0YV97RUWJxVEVFT8QuIGP9MHmw5K8bmcTi7HQ8Dg4mAbPRTIiyKHQx36vor+fSDqDc+EUXmENKRQiduhugnoVb3UJLfJ+irvSmyM2uZFUNMbZ5TqqbqB+YFimDJVt5cvU3nmDVDpCJnpj24XryFaHvse/ue75/wkEmQzy9FbCCzOkIiFMd73aJaTKxCc3EBufJPUphJxfl08zXz/Ie3M36LRBkpFvBH9/H2lFIiiRCO7oJp5ftqg1TVRZBkUlloiyevYcT0cjPBCLY507QfPC60jb98NYQGxtHikaxw5kWo5P4d1T9Hzr7yHu3kK12aTUhEazQnpsM33n3sFcWyW99xDqA4/TfulnCMuEwVEqWhL38B/wymyVDXGFgfNvYi0voEhQbLoMJ8ME105zX1TmttvvJnpymfb3/wOW77GhUkB+9I9o+hLvLtUpttbthVQZNvVEefnEVR7bdJDe2cs0Og6yJCEkGc/1ca+c59Fv3smeiR68y2fJv/wsjbCE6rUYl8JM7r+bV1dk2rYJnrc+Ju0WkU6dQPJ4+cICvX097LOXKP/8eRBQUxQm+hOYx46Qd0J4Y1vBMclOb8ZNJjiQCDH56FZO5E1OVlx2ZjT2Bos4l48jNaug63zt3kcp9IxjVgcI6lWSYZVMXEdSVdqb9+FH0ijRGH2pHJl2iWqpyZZcnJbt8n9+aJpq20FVZSKazJvXy4R1leev1/nu/tFfeU3xqh1i0Tq/rMNEwhEkCYayKQYyv9sSmM86X+HW6+2nIWS5SO08wmoRaCojWzdjP/cD/NUlVBl8z0ddXiL16FexTh6hde0a9bU6ISPM/Xfcg5zeysm8ScLQOOomGEynWT15AhUTv/Uzvvbot9BGx1BmTtFqtPD9gFg6hdHbx+W1CtlQgp5dB2gsL8OWbeiryyjtOlLfAHVXxdt2gCCUYUcsQbnjMpYNOLlY4ydnlvnWniH+/N0FvrNvlELdJGbYXFpr8I+iAfmWg6HKyIqGLssMD/VhzV9Ay/QAEpIkMFJpnFqZ/NG3Me55lGalxugDB2m//AxmJEmp4eB4Ps0Xnyfc18/Dj3ybn67YHBpN8/xMmX0bRhmoLmD6Mg4ymUgIP56hfegwM8+/RPSN5/jW17/LxoZE3YVsMko0EiIaNujvibFBNDhXsAC4O+HgPftTPNNEVRRUWUa3OwRHXib58FcITW//zONnsF8w2pPg9HIdWZIIhFivfJF1IhGdnmiI0f4MUf3DP29vnvtti7vH0xQaFk2X9xMjVBVJUTiwoZ906xr65Cb07XvQJzYgGx+eN3XTZaHRIBK5dV2pZWN6cLnYYftAitXG+ufhAhcrDk9sH0D+NYWUzzoX/lshKlwOD3x8EpP6t6AGN47zse8xKlzEF+uWrkuXLl26dOnSpUuXLh/gC/dr/dvf/jaPPvooZ86coVQqAdDb28uOHTtIJD45EPyr+JM/+RNOnDjBv/yX/5JsNvuxz3vyySd54oknbj5+L+OwWCzi+z65XI61tbV1GwlZ4VTe5q3rxVtu7/riBo9v7SMiffpMR0mSuH8qyS8u5Gl/wGJjLBtl/4BBsZD/hK0/jC5J3D8ep9AJ+Mm5NbJRja8km3h6mP/w+knwPfZsHcK4eJSr+TqWL5Bkmai2bg8SfvdN0ofSOF7AcrXNV+w1zjSaRHQVx19/t74AGYF76ij7t9zPu80654sWj2+c4J1T1/hKqMSmdoPJux7liuPyozWPex/8CurMcS4mxnjr0goNr0w44ZJcM5neNE477HPl6iKKKrNxRKZw+QoRzYD+jZSabVzfJ+xIZK5cInLnA9j1GuaVc+tBFAGyrOAjYSsGlusxVV2iccmm3WgQhFNUWytkVIWgWkHSdKQgQNdU1ho29vBOzlwq0NbCxEIKy76OfuAwUmGFVHmJ5NQG3qzJzJxcQYQbSCGDAWMTd99/O57ZplNvofku6U6J0PIMRm4EX9fxO+aHKqOM8SnqeoxxHDblZymeuEhgtlFSWUI79+P0D318hrAWRtlzJ7LvIWQFxXMIThzBdlyE54Iso49OIh+8h0KjCY0mHfN9+731AQcHEyFqx4/geR6e59HpfCDLfu46wcxVzN6P78t0873suR1fCLzrl9GEB6qKPrkBf+8d5CvVzzRuP4r3quE+ik+ar553q8d/LpejNnMV78oF3Plr64Ljxi1IE9NYod8/ISbcN0Tn+BFK4Syrl9dt6MKaDJEIfiGPjUq9XMcbH6Mnco7AUZDfeZHk/Y/htsq0Gw1URSemRWnrBherHhdWCjy5a5j5tSq6ESIPjP3h/5HS4ho/W8ijxDcz/X96kJGQT73eYimIc3HVpmH5HO4RqGfWaGsKgRBEdRXPD2iYLsrZU+Rjw9TTW9j/j/4FwZ//v7AGJ1CNMM9eLFAzvZvisx9ApeMwYDucr8rcnxsmvDSPCAJM00QWAqlSYebkOcajEtq5N4iEJMKKhFwokEj2sfL8zzh0+Gs8V2ugqhqBJHNPLkShWOVMR6Vdb3Dvlj4az55GjsbXBVRNp6LFKXU85GNvow+MocQTvLPWYiRQkY68BdUSd2XTPLb/dqy5K6ydOY5eLBERDl6liPef/j/03fco6s7dNK68ix4oCDtg4eA3ee5SidWrS+gjE1y/vsL+0TT7xnsYyUY4MltlrVXgaqGFBNy/qZcdgwnOLZbodODScpnxX+GaqcoKk2mdM0u19QXSuvjSMTtsG0iiuS1WV+uf23h8j9/EfH1v3S3X28/AoYEQo0mNUsNEOT+D3WpjJBIEZgc8n9ihu2j85Z9ibN7BYqmNLIOwTepvvMSj38gRHewhk47x5uVltsWG2f7AAPHqAl5hDdms4Vw9R3RomE2OzfL4bopKjKM1i3ifSjQm4wgT7d4NNIp5st/+PxBzW5jnTzG4ZR+z0TF+cS5PudOgYblEdIV7N/SSbWpcWG0wHFN59dIqf3TnJP+3Zy7Scnz+7h39yLKM7fnIhk7mnoeYj6aZn76fhKGxcSDF5LVznLo4w3RuFK20Cp5LTQ6TXl1FTfdQqjt4jous6wSqzlqxRvLaRaqMYQUwEZVIlRc5Uodz83k8x0OWZTYMZ3ny9s1EQ68hHIeZ+VXOXC0S0lWWhSAxPsnGtM6q2yQuq2ztCyOQySxcpu072DJ0HI++ZBjh2nQcgfPWK6jxNK706ZNKYL3S2JBUeiMqC5U2a3WThhPgBYKQKvOl6QzNSonGB8bLe+OotLqCurqAfeYYWwYm2YXCdV+hrkaoOevnngPjWXaO9wJRbEWlHQio1oEPzxsblWa7c4vtnyTLFJoWnudhuy6uY99y3T27YLMjq2FIn60Pzt9kLnwSnzRXf5+QXIflH//gY9fnvvsHv8Wj+Xz4pPfY+73vItQv3C1dly5dunTp0qVLly5dbvCF/LWeSCS46667fmP7E0Lwp3/6pxw9epQ//uM/pq+v7xOfr2kamvbRWWbv3fgKIRBCULTEh8QXWLffeGehxgMTcQL/0xltCCHIhSS+s3uAkrlu5ZEwVDIhkAPnM+fvCSGISgFTcZl/escIZqNF+8dHKW48gCEFeLLE5myYay8s4SNDIAhkieTIMJJukG82GPXqpCMxNEWidPkS45koiiwTAKmIjuWsv7d2Ic/QXngnGqfle+D7lFfzONMJWsl+nnruBP7IFOctnZ3UOG/089LFNUaHBxns7WOlaVPzAmpOwN137iHR24OuyBhOkVhIJWzoXCmZeJ6PIoNqeRSvL7HtD/8h7gs/QbpRYSFrKkLTMXpzXDcDQrqG6tmYHQspFKbhrQdIXE1BUTWUVpPYxBSupFBRNE6utslXW5yr17ECCUnT2NwX42AqjqcP0qwYLF6+SiRwEHGbZrKfpUDmwtka/YbEfMFmOBSwP9vL7jumcFWN5Lf+iPoP/3+oTg3vhgij9w8Qu/1evLDOgfOvwcwliIYJFJXA7OCuLhG952GCiemPtbTzfB+QIAhwZRXl4N1Etu0GywQ9hBtL0hHr1mkagkm3zlcidTxVZ0WNc6EREHXaNCwLGQldlYFbX8svrEHv4K8M+JiqjnLbA0R37AfbhlAIJ5rADIIPVwb9hvk08/U93LUVOj//IUG7eXOZd/QNlKsXMR7+2qeyXPsbo6hUbbD9gIgqk9RAfNomH7+El+kjNLUZM3g/m1oXPrIm42gaeBDRVRRNxWq1CG8Ypzr5Fa6kx8iHN5C1Ggy4NeJn3iJ66F4u63FyIYn/9+uzxDSJctvhztEE1+yARkUjsHVk0+T8zHEGpzeQMDTywPW1GvdvHyZSXONiqQ2ALK1vb2gK45kItuMitxv84FyV04MZ/uH/+D+tvwfCFNo1bO/986QAnEDQkTRagUCJxdFvBHFlSUbPpDFT/fTkeuicfJuIqtFr19FDYUzXJlzNM57uQWmtcNuOCSKST8LtEJq/QH3LnVyYWUQNJTA8m2YgIYwYVgCm52N2PDI6NGoVjOIyWl8fu+srLD33MwLfJ25oLM4sMJXpQTr6El4kS7S3j9b8DAndQLEtrLdeJpbpIfGV71Awfepj2/jx+TyuFiY7kaWux+k3ZBbrDtO5FK9eLXFsscZwar16cq1hcW61gel6bO6JMVdqUWjaTMSNT7a49D1uG44TD6mcWqrRtj0imsKuXJYd/RHw3c98HdFFgFqrIKw2khHBS2VwJOVXb/gxfJb5+sHlnzXo7CJxbrnGVs3GrVaRkmlKxRKRUJToyCR+YRVF03BbLSRJRQIycYOECurrT3Pvhl00jM1cEi4zF69x3bH52h3TdE6ewbt0HS+aIHTvXRS3HOK5aw1adpuG5RGPGmjbN1Dr6aHYsBlMDiMnNCS9H003KPdvJD/f4OBEhobl8fZMhZrp8szFNb61e5hzy1UyhspMqY0MPLylH98XNKJR+g8cJH/sXRL3P8r3r1QIGTbuch4lGuNk0eKOzTvZZNvI+QVCvb2ktu9CbNlD4xc/QjeSNIurSLqBb4RpBTKeH+Bdvcieg1MEQjBKh+PVgNMzeWRJQpIkgiDg6lKJp45e5bFHH2e16fDWxSKe7+OZPhKg1cukQxuAgJotuFps43g+kQuXqVc69MRCjGdjRBQQN/qceZUium0iQp++IsuVNM6sdDi3UqftBaiqylgmjt62sV2fjb0xLhcaJIaThLk1+UUIgXzlHK0jrwKg5tf48sYdrPT1M+MrtGO9bOyLM5rUiWLjCHldCf4EDEUwlDK4WvhgPxlx85I3kY1SN51btvEDQcDHj/Vfxa8zF7p06dKlS5cuXbp06dKly++WL6QAc+HCBU6cOEGxWATWK2D27t3L1q1bf639/cmf/AlvvPEG/+Jf/AvC4TC1Wg2ASCSCrn82m7APoigKV5bbHxvQulpocWgkSVj69E7nQghCuAzdTMb3fjkm/pkJggANi7ghcFIGFVXCCwIsN0CWJRzPR1IgNTmJsmU3pyo2DdMhMzhOb26E/noDTQikcJTi8grD6QiuL6h3HOQbYoyqh6g7gqblE1MEdTVCdGQULSnx3PU6ZquDXCmT6R0n4dV5txyQzCTxkj388NQyiiTYNpLlejPgr1+6RjYkky9U2JfVePDBJ1h+4VkUz8XumEgIJFUjoqvMtn2GHvs7hM+/Ay/8FDSdIJnBiyYxV1tEdBl9fCPF4xfwLJtESEFTZGwvQJVlrI4LgUzHcijaNpt7o5SETkhzcT1BWA5YzVcgliASDfPshQWm0kkwm5TkCM1yHT8S42rJ4tu7h+h1PB5KmtjvvMq5VxtsyEaI9vWS/u4/Iry4QLNYJJROo8fiSJkMTnmVytHXiXoWriKj5oYJYnGEEJjH3sQYHMXSPt6O7IP4gcAMxyAce28wARB2LNy3X8JZnEfveFSbFr3pNA/e/Qiyvr7v3ngIXV6vIPog0mcQJPwguPX1f81eSJ8Xsixjn333FvHlPfxqmWDhGvL0zl+7h9OnoS10XrpUYqnSQQCKJLGhL8ZdEylC4rP3BXBkmdChe0k0bOSrFUQQoCgKcsjACwRy4BMEAt13yE6Mc2HqEE+dWkDqUVluBwwmIySbLZ54/O8T0lR0V+YvTy4T01VimQipmEIoHOaly3nGUiEiQUBQLhKYHa4WW2zMpYgbkEuHSUd0asEv9VUATNej4/pEdJWBdJS7fbhQavGLqxq5VBQlppON6BSaNh/MhW9YHn4yTW/YwrANWqksuusjZXpo7L2PK0qG68suYWWIXTs2sLlyneDYq2gEKK0KUuAgXzrB3lwJv1Lk6nye9Ne/S211jYgkKNUamP1h2p7ACdZt8wRgyAK33cFzHOKJGOVmm/Lzz9Npr1scVk2PVERDdUycSoWYEaekRMiOjhM0Kih2B2QZMTTOy50oy2YLs+hzpS2jhzPEJSivFfFiKcqmx7thFUORSUc0Ci2bjuMxnomiyhIzxRb7hlIAREOfrnG5Klz29Ols7snhCYlsKonbquL7n318Rcw21mvPYhVW399/to/IfY/SicQ/8/5+W8iKwtuzNWZKbcYzgka1QzbVRzqdRbLaRMYnCRZm1oPyroOmGRiaQtxs4DQbeOEw6uQ2wvkF9IUKUrYHZ3mRs3Mltg2O0LhyCcsLaAmZN1oGTmMJKRQmElLZvnsLz801yKwtEK7lOVFpEMvl+Opd26hqwzx/dJWL+Sa+CEhHQjw43cfR+QqLNZPji1UOjqa5ulJh12iWQtPm7etlVpo25/IxvrvnLqa3bOfZS3ksTxCOxlATSSwhYQSCI2dnGZkchXdewuntZ+ndo0TGp/BlhY5lYkSjmJJK0wXL8UAI3ECwaSBFIASSBOfni4AgECBJMvINbbdYqtE4sIWnjx7Bcd8XjGVJ4sBQjJRdpxxK8vTZVTqORy4ZJp6MEZTUdcszyyUWU2+KE7Kmg/zphbxAVnn5epVr74kdksRyzeRascUDm/oQnsOZxfL6sTYdvrq1F/UD51S/VMA8ceQDexSoV88wqihMJtNEH/oKLUMghPWpRcrA99g3kmK+3MG5IdYIIUgaKqoMQ8kQ55Y6t2wznIoQUQLEZ22A06VLly5dunTp0qVLly5dfm/5Qgkwnufx7/7dv+Pdd98FuOmr3el0ePrppzl48CD//J//c9TPWGb/3HPPAfDHf/zHtyz/J//kn3Dffff92scrSRIt++Mz110/wBPAb7FnqqSoOAGoEqiSoO3L1O31O/20ESU+Nkm/LBHWVLzAo6VF0cIRjHSK+tQuXjqxiCpLSBIs+oLlUJodYznqs7Mkt24jXl7mUqHJVE+MQEBElalbPvqGzZxorHd63jeW5cTlJe6cnsD1CqwV51AiMRrNDpFeHyUao75YZPPWKX50ahldhkRYJ5NO8vTZZWQ9hCR0VFWhEqg8PdfiiS9/nc6R13BnZxCuQ+C5SH19XHHDFFoyu0anUbYs0rp8Hq1WRpMVNvbGaPUOU0/0YnVMYrrKsFcnEg5hWzaW5xMKqbRNEzkUYSptsFwzaTo+QkBCV3DbLYQEyw2LiWwU13UJfBUvmqRcM0mkEiy0bKZ6YgykIiSEw8mFMuO77iRZz9NauIhazOO88RKpR7+GOlintbpC6/xpmmdOkBkfJ3f7XZhnjxHUqniri2hjU3iaTtBpIzXrkPnkiq1PQpUkvHdfx7nRrD0bUQipEYqtJsErPyf+je/Rs2kCvV74iB42CnLu1uqX9+yCfh8zcDXbwp2//rHr3asXUDbt+JvqnR+LJ2k8c6FAoWndXOYLweV8kwA4PJVE+J+9EsZWVFI9YQa3b2W1ZkKtTODYqLKEDQz0pejplFnrm+LpM8t0bB9dC2NpPrMd2DCwgR9fKvD1Hf1czjcRQYDl+vgCdg4lObdUxvM88hWXyWSapOwTmGGqqsJqy+P2oSjRHoOTK022DEwy8cBDLL35OsGNRuuxkIZpuYxl04jiAo/PXeVrExuxB/qYC8VQVJVdQ0kWKx0avkNwo4GJhExYD7E9p1E/OseaLeG5An3nPfzsaotmTwLbF4TLLebXKhSmRrhndCNqfpGg1URJJjHveoxKoKBN+PTvFVyqu8zPL7F7125eOGdTliPEDB23Y6+PbSFI6TK1lkcoEkbNDVKfL1DLl9b72MsKkiShWhKKquCLAMnqYKkJlhyVgd5hItPbseNpyrEsp196m77BfoqhHoJ6FdOL01A0+lIJ1joOkpCotBy2DyaI12RqLRshoGl7DCRCtCzouD66IjGcNBCfUqQLgoAQAYYskYnqrDY++6jWRYD12rN4HxBfALxyAeuVZwg9+g3szxBA/21SdyWu5teF1iI6A5kspUqZEqBIESaVEPFMD9LSLIphkAsbBL6PVW6ABEoshuQ55ObPcGBkG69fK6Ak01yfXyW+ZZLxhyYJX7+Mlexl9fgC2sgEmqoxlcvwwmKbmCLhLM4iKxAdGKAVijHb8jg+X2ax7qKrMg3Lp2a6/PjsKt/aPcT3Ty5h2h63TWTYkovTsDxWqm0Ob0iDqvLjCwX+4+k8//C2cU45TUiFaPsyud4BwvlltCDAajZZduJMZrJEH3iM8tlztIolRifGyF+5xkB/lPP5Npbn3mxQH9+8lUUHwsKhR9Hx/GBdiZQlhBD4koShykiSRMN0uWN6gOOzRUzLIZOMcu+GXjaVLiPcfpZt56YdV6FhIm/ajnz9KgC1jkNvTAMkhIDYpm04ofCnFuortnhffAGcACptm0DAC5fyPLEtB6yLHfmGRcnyyd3IXZBlmVrborblNhR84oU5xNoKiAB8H69Sws2vIEanPtWxSJJEIK3/1soY8OTuQd6Zr7Jc7SBJEgfHkqTCGmeXKrdspykyB0ZTv9Z5vkuXLl26dOnSpUuXLl26/P7yhRJgvv/97/Puu+/y5S9/mSeeeIJUKgVAvV7n6aef5umnn+YHP/gB3/nOdz7Tfv/qr/7qczha8H2f0XSE68XWR65PRXTCCh+qKvhckGSKtsyJpRqFpk0uEaYnYXBqsYpprwftoiGV+8d3MbJwhq2jWc7NFSn6MtkDtyHCEX52YQVdkW7G4Y1kkqHBHgJA689xVfHZvWsfQ0ffoWV7bOqLsdqw6BsfZW5oK0tzJrdN9mEIm95EGL1Tx+7NIkUTtH2BS0DHctEyPYz1u8xXLUTg4/se01N9HJ0rISvrAc56x2Yik6QlyazagnebCnJuG5s27cA78RZmsYi+707OVly+GhZc+NN/z8C2rWTuPoy1MEskpDG86wAXshsJzAbj2Si26zN/5B0ef+AwL801WSs3kNM9VITB3uEeNvZEWaqZjAz2kG9YXFtYo30j/TekyOgy6KqK4tjYir4eKJYkpnqiDKQiPHV2hdDKLG6rxSlFZrgnzpd33Y508W3wfToXTuM5HsHF0/hzV4lIEqKUp3n5HIknvknr9RcgCBDtJlK6ByHEerBXklAcC6GoeKr2mSo0tFad9tz7ooMkBHENYhmDQAT0iBbefQ/R/sWPCCzzlvEUuf1+rFgKhMCXVcqWYLVuoakKQ0mDlOYjPqW93heHXzUZP7/JWraCW8SXD3K90KQ6kiT1a8azJd/loU09PHe5RME0EK5DKJ1mILB4aEijduwE7X0P0OrMY2SzrFgBbdsjEDBXaTMaCtPWY1TaVSQkUmGVUtNEV5L4SEjAYG+CzbkYS7U0ZrPJjoE0WjzOfz2zhO2DL8m8cNnhjmwvhw8/Sv3V5xB+gC4JJNcheuguan/1n/BrFdxzJ4gMvM4dT/4dVrLjLFlNDm9I8+zlIuaN/lJjKYP7+iXCxQVSDz+Bs7KGiKd5SWSoxMIUaiauojGezCCXC5xdrLJ580F6r51HeehrHItPcC6v0MznUdI9hHODjGdcvOvLhNt1to9meX3N5A/23UZw5A0cP2A0G0MjQI/HGXrwMJeCCIlEhOS2aRzHo7S0im3ZtByPVqCgGGFsX9D0fTKjEzS27eWtmTXKpoS/4DN+2yEi4RDVioVQVYJ2CzUawwjHMZwOsiQYSBpoMqxWmsgC4kaIIBDrgXDAUGUe2NxPUvURv8WiMrVWuaXy5YN45SJGrQSZ/t/eAX0GHF/g3RDyrjYDJvbfifn80+vnMiGoruZJ796OszCD1NNH3PfxyzU0BYQkE9+zH2/uCmJ1ka21GqHNd3HCDlMqFzlfaMG2jWx+YicmCi1pDXt2ATUSZmxsgJLVICvqtF0XtSdHK5YhFlI5Ml/DCxT6EwprTZtoSMPxA1RZ4lK+yYGRFHdN9XCt2OKvTizjuB6+69AbNwjj880dwzxzqcBKtU0mrCKjEnI6uB0Toy+HbHcwVI3Q6DjOlv8LL1zP0xo7xFBcY6Q/Ql8pT7PeZDwbYbVh03EDEr09ZHfs4vnrdfoTYSZyaXRFXq/muPFDQJMlwpqCHwrjKyrjtXmG+8JgJEjYLdKXXkcJhyGeoLRi3/wOAgGX5DRbdu2ncfo4qUiItaZLy3IxcgPIfdNELJk+Y72KpulJtByBrkokNQkpeF9slCSJQvNWKy8vWK/SATBdH/+XkgJKbYcBQyOQFC5WXE5dK1G8mEeWJcZzY9y1ZyOxM2+s90zj/eSCX4msMtf0ObFYom46REMa+0ZSPDrdg+UGSEBMFTQ8CduNc63YIggEQ6kIB0ZT9Oj+5+3K2eX3GFWROTzw0RaN6m/lZqJLly5dunTp0qVLly6fB18oAeaNN97g3nvv5Xvf+94ty5PJJN/73veo1+u8/vrrn1mA+bwQQjCWChHVVdrOhzMaD41n0PA+91smSZJYaAt+fm4ZXwhkCTQtzp++PUcirDMY15CEoG17/PxKmW9v38Ph7CrD6SjlSoXm0GZSIRX1WpPA7KAaBmomy4bpKRaaDu/MrTGZiXDSNDkeH+HxR4YZLC+yUm4wcv809WSOjAjxz8YU8DzahTz1WoPTJ1fZ9uU7yeV6adsutUAiSMV5ftXjS5uG+PHFErIkgSQTjxoUm9Ub1mIKUiChaCrLlQ6ypLHcESRcwVMXinz5vscZkVyenW+TCJv0eBI1RSV/fY5Qq4Isy7TKJZS//gtGv/b3yKeGSN9+D8uvvowW+OjHXuPeoSmMB3aQj2SpOQGpsMZfnlhiptwmZuhkoiHu2zTIySuLVB0YTmjUV1fZNprFu3oRx4gCIAPbBpP86PQKm3vC+Ka5ntErwWqpzrneOHcke1ibX0Y6f5Xl6dvI7HmE0UgC3n0VkUwhHAtnaR4l24dfLiCc9UCTGk+iyDK89FPscgFJDxHasgsxsQlb/egb9A9hmRD4N8eJLyQCQGG9Qkpq1rCmthL+8ncQy/P4+WWkWBJ1fAN2Ik0gBK6s8fL1KtcLLRTHImjWkTyP23aMs38kiadpvxcVMV7IIDI8AaXiR67XpqbXG0J/TlHumvnx1QuBgLYTkAp/7FN+JVHJ5atbszQnUzRnZokIm16rhn38TRbaDqgakcEhKkqEesO6IauwXsUXM/BUDUOT0FSZuKFTbFnUmx1GDEFCCZNORPmr03lsz0dTJPoGVF48uUwmrLNcapJLxVBkmVNNiUSyl4ce/xrm7DXkSAw/1UPl/BlapSKKJGNoMnKlgH/pDD0TDrvDSd6aLfB3d4/S8iU8z2dTWmP0rZ+guhaNoQn6JidYNbIsXKjg+hA4LkRCdMJJcn0BrdVVLnQUHprawpnEOMcLNlIqhh+OUVwt0GNEed10uHv3Ns68e5b+yTF2TI8gx4fZM9wL89dYXclTRkO/bS/Pyn3MnZ7niTGD/toybrPF6M6drJk+c+cuUSxV2froV6mcPE5EilHasJdj51aRAx9pYIQrBZMTAu7cEGP3UIhj19aQFBkcB6/Vok+TaXsWu/rCnF2qENdlEAJZuEiqRiykkouH2DecJKk4N+3lYF38/7wRVvuT13c6kPncD+PXwlBkNEXG9derud7Rezj0yFexT76DWcwTiYQhkSb25N+l8/Iv8Mt5ZCFQzRahHXuRmjUUCaSJTUiLM2x6/j8w/Z1/TGdsD0I3iFw9QSN7EBGKEotF0HQdq9VGCXwG4iFCpoI0OERZMVgstTg4luVauUXM0KiZDtlYmNWGSVhbP07HD/jqziFWayavXC3i+R62ZSEBq9UOI9kob15Z5cBYL6VqC0MBqVrGKZfwhMCLxYgHDrneFE0txs9eP08opCE5NssNhWumwh9+9btYZ07jz11DV3ziG7dQ7B3nR2crpCMhGqbDlZrCpi2TLFybXxcJpHVrSUlRCA0MUa+36B+ZJH3mDYywgeJ0EK6HcfeD2JJCKnyrpeu1uos/tJPbN2+heOEiauASHRpj2ejh9IKJvLjMV3YNs1xtc3KphuOtCxgDqTAPbOwhqXg3e56oyq0CifxLgoks3/o4rK0nc1yturxwKY+hKEiKQuD7zKyUKTXCfHN6D6HzR0FRIdPzK8eVJMucKdq8fu39a0jH8fnFhTX2j6U5OBiBwMf3ISrBvWMxDgzHEUg3bMe8rvjS5ZNxXZZ//IOPXJX77h/8lg+mS5cuXbp06dKlS5cuvym+UAJMrVZjw4YNH7t+48aNvPXWW7/FI/rVRGWPr+3M8er1MstVEwHEQiqHxrNMJhVE8PkHyhxUXr+Wv5kBmkuEOb1cIxDrth+ZiEb4RnOFQMC7eZP7xsaROwuoYYWNAz3MNF3s3iF0AlxATqaIhnWuXVojJWxigUI8IlFwBf+PSy4Pbd7FXNCgOOsyX51HILM5F2NbxqB8dZ6dCYnb7t+JJyTikxPYbZfdvUkKls+Z2QLtXJpDW0a5WOwQeB42CvF4DM910T0bVddp1lsorosla+ghnTUjQ6cvyg+vNjmYkchfm+GxfZMk3nqVPffdSencOdTVBeqVOpIEkfEpBgIT6Zn/hNw/QPaBe1A1haV2QLxvgOtSnGcuFNg5lOJPjswzmomiaSqWG9BxPJ4+t8pXtwxC4DKqd+jv0wh6YvzUGgFfoGkqyZhBoeUwkgrTbJvEFYXAdZEJkP2AS4tlJodHaFtzRI0oq6UGJ0p1tg9s5Y6tdUSniffkP6CQ6EEPh4ieeh3JbIGiENt9AHf2CpKqIoQgqFfpHHkFfXUR/a6HcT6N/Y9hgCwTiPXeFZW2gx8IdFWhLx4iHU9gBzJFJQFjO0ht2o2Gh3MjwCvLMhcLJtcLLeRGFTe/cnPXb7x5ir7940wNZugk0r/pYf0bxw8CQjv3IV8+R2De6suvJNLI45s+1/4vEf2Tv6+Q+ut7FSqyjN5ugOuS9Gw6V9+GehVch8ieg0zlNtLQosirM6SEi5oIsVK3EJKMrsjomoKFzAObcjx3aY1CrYWhKSzVTO4ZS1F3BT+5VKblCSKahicEVVtg+4K2F7BlMI0XQN1ykYXg9YUWfbsHOZsII0yLJ9MJ/HNNxGPfwZYU5HaN8JUTmHPXsdUYkQ0pHtjcy9zaKrIvk82mmJBc5Had2OAglRefwlQklC99F3cxT8wIE+4fZsXTCBSFZT1D34YUQdbA2/YdTp9ewa3lUXWDVmM9Az1oN4k36iQ2b+Ord27BDwTZ5hyDzTZBrU4pNUBycBKhRnhpzcX061jzM/xgQeJ/v+sOnL/8/2IuLdC35wBDjz+MtnQVc3kRY89BxuNZ/vJqEymZQU2lsJUQbimP0EO8MVthbGuaL+0e49kLq7iejxq4aEgM90SQ2w329oQolRtU2zYoCtlsgsG4ymNb+knKNo5QWWkHzFXbaCJgQ9ogFwZZ1/A+JzFGMj65OboU/vTN03/bxLWAzbk4Z5frAOTbLs8oSaYOPMZ4WDCQDYHdQTY7xA9/Bbe4tt7PrFHHa9ZR4glEs4HotNBGJlCHx1GiBvKLT1O5dg0zGmFgfBJZdrhnMsuRa3m2bZ9gz1CKM8t1Vn2NSCJBpWEhKdBxPeKGhiyB5/mYrs9kT4ym7eH6AemwhusFKAgKtQ5CUTAiYVzPJ/A8Si2LvohGf1Rnba3OA+MJnrlwhkDV8ALAdgh0mcmJYd6ZLRC2mrj5+rqdmgTV0ho/ike5b/89XNV6Cedy/IeLVZZPVSEI+NaBCX5xbonpvjF2bZuiGmiUV1aQfZ9YOkUok2XHRB/laoNW/xjVXSHqjTb9mTijw724sQhBEDCc0NFVGcd7/zy6aga8psW5EtvKUEKnYTr4nXUxOkDw3OUiqdD72whgpWby1Nk1vrkrh4GLJEkMJkIosoR/o+wlpEiEdQXT8emNhXDdG4kGwHAyxCbVxrdUjs1UkCQJOWSg9A3irS4C0GiZLCtZpjSd8J5DOLHkh204f4mWr/DO3NpHrjuxUGW6N0ryA6f5wPd5r4vab7vniyRJvxeJEZ8FDxnH/+j3FPstH8sXDQno+B/9G0JXJNTPzVy1S5cuXbp06dKlS5cun4YvlACTyWS4cOEChw8f/sj1Fy5cIJP5YqXcCiFIKh5f2ZKl4az3dIiqMobsE/wWxBeApiOome/bcxi6SrH1fqPxlu0Rjig33ZXmKhavWGtcOjuDFcvwi5kmj+4eJZ5OIQIfzXfZlNW5MLeGaDXQhE/E8qC0RiaRxo328dqVPNv6o1Q661UgAYLpvjjvzJX5o50T5IpzHJkpsjR/GtI91OK9HF9tMdqX5Ot7hjm2UGSiV2V6uIdSx2WtaXNgLM3x2RKS65BNJFkpN5F1HdULmMqGebXcpFqu43ke4YkxDu+dZE/1CvY7rxN2HfpzPTSWr6FIQKaXxECO6s9+hFWvo+aXWZ5ZAlVj4I67WQ6nKDcFo+kwp5dqeAEsVE1GUhFEEOB5PpF4iHQsxANeAevlZ9DqRYJmna8duJ/yxv2sJQfwFI25ssnl5Qr1tksqnYHCKrIIiIZDVOstxEQUgYS8eSdrp5cQvs+FJZed936V+eUSJ5ZquFEbWfYYHriNB7YO0dMp0Xjmr/FXFlD6B4neeT9Oo4GzMIMzf53Y1t04Pblf2ZPFjaXQxqaYPX2BuuUiISEQmK5H2Y8gtDQ/OJmn0nYIqRJ9UZ27p7IMR2VEEGALhTPLdRTXxi2sfGj/p9dajDWW0Q7ejfvbbHb0a6INDBN57Jt4l87gLsyAJKNNbkLZtA0z9DcoP/kU9EbUj62W60sYZELyzWqlz0LEsXBOHKF2/SqK8JFsi2DzLhambqPcMrkto+O+8BRFokz0bOT8fJGwprIhN8LVhkd/OsqWoTS1WpuGC3uHkrzRaBF0Ohhhn7W6TjIZJ65K+K4EkkQuEV63DbLWRT0AKQjYktGZq1rkmyaNVgezWueujX100Dg9eS/zx05AIIhGDPbtfZyd9hqlSo12qcbbyy2eGI/DkRdptE3OKQp3P3wXrb/6U1RNR0OQmLvAZN8E+WoLxW7QjvaxVjfxXY9FP2DPVI6aLlFbWEIOR/A8H89fT+VvtTrEFZnK3Dz7lt+mtbZGetc+Wq8/izc8xWznEqblEk4luf2+x3jh4hoqgqblMiPibNywmaC4RjybRjl/BN/sUJHDWMUa3t2PU3UbhHt78FQVXQTEYxEaboAvJAodj7Ur13hi0wiEwoxEIOt1mGvYnJ5bRTZb3L9hDF/rwZIUto73MxRTiEgeFho/v1hgtWbhlIt0CgVe9Dz2bxjk/qEQqckJrE9bEfcZ8JIZ1J5+vFL+Q+vUdA9+Ovsbf83fFIHvc2gkgeMFXC00CcR6TzZTVthAhfbPXgLHRq6W8EoFjF370bbswV2aQ41EaT3zIzDbSEYESVXxm3XCiSR+YZVoNEL6O3+EffId2udOsmF6L4ltd5CM+hw7eYGsHmPNtPGkDq2WjRYOc7nY4cndQzx/MY+QFfItm0hIpdpxSYZVvrpzkBcv5UmHNTp+AAF4QUDC0PGQsAMPTZaRhc8mv8rklXM8uneCN2arFGstFM/jwIFtSLKMv7qE36ihvHdt8ANESOHi6QvcvWWQI1dWia/UeHTbZi5l49TbNroC//1907x2cYlMKs7+baMoO8bp2B4RXcHxYbVSJx2P8l8vVOgzdBAqoqYQNtt8ZUeCjOoRV3we2zbAMxfyWJ6PhCAd0VipW+iKtC4wfgBPyJxerq33b6neKoo3LJfVlkcmrDJftZBw2T/Ry5HrJSQCJBEwlDBYa9rct7GXmUIdWYJ7elU2Lp/CO3mV+rY7qF0uo2R6EVqOIJ5A0ybxq2WEY7Hsquz60texk5kPWZh9FDXLu0VcumXMCSh3PJLxX3PQ/gaQJIlWoFJsu1ieTzaikTUk5OBvR88Zxxf85HzhI9d9d2P0t3w0XywC+NjP5qvb+lC/mO26unTp0qVLly5dunT5b4YvlABz77338v3vf59IJMITTzxBLpcDYG1tjZ/97Ge8/fbbfPvb3/4dH+XH4Hskbt7g+J+2r+zngucHxEMq1Y6DKkvoqkLHkwiEQFVkcH1sD2qRLCsdQdM2eflSnt5klItrdXqjOjgOVscGBH2pKEptjQAJtd2kNxynFGiokkSl3mIsE6M3ZuC4Pr1Rjcilk6wMTDBfXCEwYtitDlJnifFsD3IQJxQKsXJ9lpXTTfYf2M7Zjs3lmQJ3bR1hQ18Mx9IQElQcCGuCb+0cZGG1Sq/XIh2XkdQo00mF0XNvw/IsSjyBWS4R3nsnYnGRULtN4sAhOs//BCnbT9N0UJ06fel+2rKEvzjDRE8PfREDdbSP//ntZSQJZGnd2icu+ViuSU8kwmRrGefH/x6puIqnaaj9g4SXrtNTWCG963aWNx2iE1VIqdDXFyeigi5sRKVE4PtkkhGkSpHkvoNc0bL41jUAEr1Zzso9nL1+CWF10DL9eLLCSqSHv75a4xvRFkp+Ge+2B1lMDrGw5hIZ3sp4/wayhVnkVp1E4BE0m6DriEQaN578UFWMJwTB3nsJVmpIM9fAc5EkGaO3l9SjX+OP38wT0RVqN8ZKxxU0zq/yjd1DZNUATwgszyfotD+yPUrL9nCCBuFmDTf+xa+CATCjCaT9d6PvOohAwtN0nN/ChA1LHo9u6+fn59cwnfeFlmRY4/B0L3Lw6Rqsf5CQEFRf+gULl2ewPJ9cIkyl1MSce57U3oNEJ7Zy8Yc/pD8eIu602NmfI7ZpgDOzBdzCCjsmN3Dnhl7c65e4cO4a2eFBDu2Y4vCOEEY4QccTaH1ZXr+4xGhUIhcLo2gadgBRXSEQgiBYtw1K+BatWoBk+2zti7KlJ0KoLiO36vzwmovd6ZCLxvGbdRptk1fOzBN55A5491UsNcxSYYVXDJ07BvqxVpYQkRhBEGANTtLoWKiyRKKY566DO/lxrUWzUiMaThPyXQQB44MpKvUWQSZN2NARIxN0OhZ6s41nuVitDtmpcbI9Kp2zVWJbdtB+7VlCkQi2JKMEHpoRwu2Y5E6+zFf2PcDrMyUWSw3qlss1RyPeN0FKCNxKiUain0v5Bqosk2p3MGt1DCOE2peDRpWReJi6HdDyBEY8ju0FXLpwnYe25Bh/92Ws65c4+If/jMFEmgtrKp1qjemeMBs3jiNFAhRFQlE03l1ssdpwMNdW6RTfD7Adu7bCUGyYDa88T/qhL2H/hgVQR1aI3PsI1ivP4JXft1xS0z0Y93+Jjvy7//kgyzKaYyP5HoGm4yrqTTFaFy4PTSXZO5yk5fjoisSYU6Hz1LMQ+OsVAr4PQYB18ihyJE543x20f/znSJoGIoKS6UEORwhqFVo//T7hfbfTabUJ6jWss8fxfYF2/l12bJzkmJ3h6sVlpnduJruxj5NlB1HvENUktg5mSWkymweSvHy1hHdDEALBlv44F1YbxMMaqqoQ+IKwIROWVWwvQFMUdF1FD+tkDJUdk/2op68Tvv42o8ObaE3mCEs+odJlZkd24dWrBIFAQoAEsmHg3GgY79RrfPORgzz98kneeeMYqc1biUc0+pIRsoHJtyajqCGN86ZPw7KwfZ9q00IPGYynIvz0/Bq98RA+gCIjSWCZFi9fWOWbuweou1Bsdbh9qpcgAFWBgUSIN2fKzBWbH/r+vEAgId3s5XILksSVkkm50b5p39gbD3FgIkvb9mh0bIZSBhM9cdqWTViJsyEmk3rjZ0ilFQSgCA9ZBHiF1XU7z0QaLxRGHhxBBAJjOIuVjeJ7zkccwEfxyXNM/h3mIEiyzGwz4MVLy9gfEInGslEe2pglJD7te+zSpUuXLl26dOnSpUuXLr9pfvcRlA/w9a9/nXw+z4svvsiLL76ILK/7Zr1nC3Tvvffy5JNP/i4P8QtJQpdIRXRqnfUb7LWGya6hJKsNi2hoPfs0CAIUWcLQVO6e6mG20GCt7dAOFDRd5+xai0OGzqNbc5xaKFMvltmQ60GSQK3kqdabSKqGLAckmhUO79hBRJXQpCybemMkwhozVZuHp8L0XFV5qtim7fqYjocIBBIuVmeJ6WyCN2crqMkMZqXCO2+eYGiwl69uGUaSHaZ7dAb6BpmvtNnQG8fQNRbrHUwfwviIRomoKpG9OId/8RTkhmnH+1gr1UmH0qw88d/RNB12+QXE2DSi0wJJQpUhFIkQmdqMcukU/lNXaIsQSl+O/37/3ZzbOMErV8vU6y3yjcZ609xkmFAljxRPIHkOcjSGFDJorq5i2TZqfo3RTC89PYNccCrQctazqiNR5NwgnoC7tw6hCIezlsZyvoaWGyRo1hkYHeTYbIGwIqNu2IyUzNKWdSS7RWVtjZVdI+Qe+gZPz3fIX7kOgLxY4fjAMAcnt7D3/Nv4J95COA5SOEr40F2Q6cXYvh9Le9+HX5IkLjQC8oPbmBifRnM6BKpOK5rivy4FVDouEX39NOAFgqVqB70nyunlBg9NxAkB6WiIYuGjM2gHEiGkYgO837K/yt+QIAiwFe29BwAfOt/8phFCkAsFfGfPIPmWS8PySEc0+qMqIT57bwBJkrALBa6ev4oADFWh6fi0PPC8gOrpE2zeuIFV4bNct4iENPoWL5A2YuzZvAktEiE9EkH7q/8n1Y37Gd8/Scaq47/yQ0SlRCO/ihyN0fPdP2TL0DCzr5zEM12C3hwLtkJ/XGc0HaHYslAlCdVsUsKg07HYP5zkxLtnabYspC0bKdZrYEToH5qAy2dABCjRGEcWajyw9xCvtSKosRjn54vs2jZG5dosIw/ey8LiDPm2QApUFNcjb9mMz5zj8QMHOb7SZlmFlOKzfSRNj+px6eoy1vButk2Pc+LaIkGyh+TEJH7HRVYUzGaZnoEU/p7b0VMJxKXTBOU8UjSFIhsMGRJyrQTnZ+kZHOJQrcS+bbuQjAh6CDLD/YjZiyiBh1ErsCkeZa4jCJsNEhEDqd1E7sTwLIvWwhJy4JMOhdi5Lc6eh/cS2BbhmQv42/aTPHQP3oVTDJsNxtNZJFVFMybxY2HyjsyV1TYhTeXNuRrC87FrtQ+NgfNFi3SrQbpagc+hIqUTiRN69BsYtRLC7CAZEfx09gshvoQCD+nqJezzpwjMDnIsgbFzP97o5HovJ0D4HmkV0iooikxw4eLNKjMhBHIkCjfEJevcCfSJjXj1GnKmF1lRkONJnCvnUdI9CMdGH9+IioT5+rMIx0E4DsbQCE67w/m8g9yqc+3YKTLDQ/zBoT1cHojj+QFlN+D1hToS8I09w/jBemVI2/bJt0z+4vgi/+KhaV64tMaBiR6OL1ZxAx8JCV8IUmGDTQMpJtIhGu9cIppfJcgO0HftBLWWYLZpkbn3IVLJGEE4hhLykIQgkGRMIWH7gkg4hNGq8urZeb5++yZansCMZxmMaojLp1l+602alRqhcIjNu3dxtnczLy5ZTGZiGAZYXoAAIpqMK8CyXXzbwgg83PwqK0MxThfaaNEYZ67nqXVcslGdA2MZdg+lPlKAkSXY3B+n0jI/tM7ywXQ8rA+ICcWmTbFZ5OB4lkemevE8lyCw6YlJjMcjGPklWqX3KzXjhTkmB8a5ulTGrxSRIzFsRafUdGiYHrtG4edXKhwYTZHV/F9p2ZUJKxiaguV++HqnyhLZiAZ8diH9N0HNlXnuwireL6lZ8+U274RU7huPEfwWekd16dKlS5cuXbp06dKlS5cP87uPonwAWZb5p//0n/LEE09w8uRJisX1wEhvby979uxhbGzsd3yEX0w0PO6ZyvKz82v4gcDxAnzf44Hpfp4+u4J+o3mtKkscHE+zWOtQMH2EHkZ2fDquj+cHvH6tyPaBON/c3kf0eh4lHbB4cY12qwM3MosDITBbbe4YiXHkudfQ2ybnjltUcpNUHME9B7JgdTDtOB3rlwMRAs9x8HSBG02gxhN49RqLywWWC1UiuoqSSPGlsQLRi+fovevLPHO9RNN0iYRUxlUNr9Xk3p1jyG/9CD+eZrHu0HBt0rk+qqEk/9sbM8iqytC2CO1KG0NVGBweglaD6KbN2K88Q6fRJOgfotpyCJoWzvwKqcNPsmd4gNeabYJAEI/opCSPSKNIZS1PLJUk5LmYlQrmjRiGWy0TrhboCxz+8Y4Mqx2fC6UOM6s1wnLA7bftYmlxldcuziGn0vgrC+gbtxFE4yjJNHKrgdzTj1urQrOJP7wR2/Nxe4a4qmaZyyRZzi+ghW1Ep0PQbqFpOm++8g6Dd26h98y74PvImoZ98SyhR77BSt0i3BsjKnkEwXr2NLUyZ2fWOMt6PwBJ6jA8GuN6vkhIMW7J6RVApeNSaNq4JFCFz4GRFL9YK+Fza/N6TVXYmlAQSxYi+vvrwO5KKvl2wGKtQ0iVGc9ESOsC6XOwEBRCEMZlPAZSXFsP+An3o4qLfvW+FJXi4vLNbeOGxmylg6poDPUkSERCpBWfQiRCvdKmI6kkpkYYiagEjWXclSaRdp72xTMk564x+OATmMfexI/EKZYreI6DKrVwfv59xr7xj5BFgO84IMm47Q7HLi1x/64J2m7AlZUKwvOIRFUOjg0QtppcLDeIxyMs1CxcTxAEUEclNTmN2mniKxrlWpParo28dXmJjQOjSIk2ylCG4Sf/gJcaGrdnBqjbJwipCh13/Z3WrywzWnqW6UyO2w5/mXPXlrly+SqLbYu4CvbqMntas+SNENcsi7XlVVIbNmAGMg/umqBjtVjQBziIjRSOo2VBdFqM9CVpzs1gmxaKDMJ1qV04R3R5ni1f/waLvksUF00KcIKAztIcajjM1PAE5sxFHt13D69erxBUSnQqVewbVnO3b8jRfO7HyJEYV3Y+SGrz3SwUG+zORdg7Noa/toykKMj9A9jxDBerPi9dXiEQMD2QZKFqYlk2Q7055PwSgf9+QNp0fXxFxSkXkTI9n0vPB1tWINP/G9/vr4uiKGiBjzjxFp2LZ28u92tl2q89S3jfHSjb9+H/kpAqSRJB5dZzGEYYORIh6HQIGjUAhOfht5rIg8MElgnyuh1j5PBXqb/1Cto9j6CNTqEOjRFTVILAx1MUfF+AEIjAp1qpMXv+MmUlysm5MqGeHnqTUWZqFldLbb62c5CnTi9RszzGMlECIViodtjUlyAQAUhwcqmG7QXk4ga3T6RRhM+x2RJXFz2+uvkAfX4He3CE6UScUk3h5xXBd6SAXC7L1YUCsqzgewFB4COAe6dzBK0GtXqbeVvh6NnrhHIe39TWOPnTX6DIEA2p2KbFyonjbJus4G+5l1Nlj0FNIaQpjKXDNG2ftVoHv9m4KV4nE3HaskrHdHjp8jzBDYGu2LK5nG/yh7eNs2s4zeml6i0ff09UZddwhjeu/FJfFQnajk8morNSbX1oDJxcqrChN4blgCQppEMyYTnAL9y6nyC/wu27N1BqRGh2HITnMVv3cL2AB6f7WK22KTQtFiodvr5rkKz2yVZdEcnj7g09vHgpf0vVjgTcMdlDQg0QH6PfC1nF9iUUGUKS/xsV+mVZZq5ofUh8eY/L+Sb7h+NEvvguoV26dOnSpUuXLl26dOnyt5IvlADzHmNjY12x5TMghGAkJvON3UOcXK5TbNioisRAPMT3DoxQM9e7c2QiGpoq8/q10nrDYVlBUiU8d92XfSQTRVFU/rejK/wDa4XQ6WM8vON23lkJsVyoEfg+I71p7t06zPK5izy0qY+rKxXm5EFkNcbtfXGSqoNVXCE3Ms7sKjd6lIib9lVFK2DbeIRLtkOQG8Lo7UNxLHRDx/N8ogSY168gNSrc1auS9XSOXa8gtBAjyTjbejfQP3Mac8dteMksweXLKAuzJHbu5d/POhCJgu+x5Ov06DpWq0nLiDO4bSeisEJgdnAFyIqK4reQg/XMePXySYobk+wc62Fe8oi4JlNR0H0D0/eRJBmvXMRRw7z3ZjJf+TZYJvkjr6PrKlng/oFhHnzoPlxZJn78F4SyG7msKiAEcjyJtziD3WzSt3sSvZLHqZYIPB80DU0SzFsydqvNnskcL59bolSzGeqfIFmYB03DbdTxJIXjRYe7R6eJlVZwK0Vaa3n0n/8Q5Z7HuVB3UJMpdvRHqBTKRNo12o5PIASyBGFNxfVcoiENxw+QfikoY7k+IU1BkUAEgtG4wv27xnmzXaVdXW9qnU5GuW8yQ+rKEYxdB3CMCL9T371fE0vS+PnFImt16+ayd2Yr3D7Zw67+0OciwrzH3zRY3nHBUt6vdlIVGUWC6aggKBdpLjXpu+8hwtU8YwNjpKcmMd95nUZlFZp15GQKeervod//OObEFsqNBrHNuzAvniXwA7RohNTgIHZ+mdDRV/j2noO8vtTimrM+AxKaRESBtu3z5Z1DDDQkvHCchXwdJZNm254kibBGzZU4vdpA13XaQsZWYmQSOpqqUg9UzpUd2o7HckuhL57gqGmQMOK8ODvP6NY+Uukk5XKNIFi3VAqEwHU9tGSa//zOAvv6dALbIqEEKO0mfc08xsx5HktkKRx6lGvzIVJZlaHpDbz22gmuL6wRT6cYjYRplVoMZeIkpBaS1cAhIJAlAlXF0w1iEYOc5tN+9TlkI4w8e4nQ1t04b71M3FBBFmitMj2ZBP7SGXruepijJy8zZ4fpzWjsGogRnzlLc3EBX8DUztt4flHlye395CIyHWEgJTM3x0PTV3jlyurN4G7b8hhMGlwzbVYaNsOJFEG1cvM7H00ZuFcryCHjU/Ww+H1GlmWMZg3v+iVkWaL98jMoiTQiHCH4wEnMOvMukYmNmOFbRWEhBEpPP6ws3lzmSzLKwChSpYCQZFAUJCOMkskSxJNI5RJSNIbYfRv1y5cw1TB9wse5egH7ynkIBEpPL4mvfZedEwYvFyvImo7neSwsrDC+cYKhvePM2QqhkIZh6Ez1xHj2Yp5qx0HX1hMbdEXGcn2iIYXAha39ce6a6iEeUgkpMucWSszWTHKaz66927gmKzSFiZxMISJxwu4qDxUu4b90kq/vP8Qbqs+l1SZl06EnFePuTX0MrVxiKbeR0ckMPzi5RF8szsG0Qv21owQICCQ6jo+hyrRsj7nL19m76yDT+ybY1J9iuVLn5GKVlboJjn3L+b7lCQJZ4+2ZEoEnIPL+Zy+An5xZ4X98aANDyRDnVxu4fsCG3jiTGQMkuBALUW693x9GV2Qemu5hplD/0DgQkkS+7XN+rcnpxfW5EAupPDDdx4bwL/XxEoLomTd5cnoPBWOI63qKhCsznDQo1DsUmuvnfdcPeGehyuOb0gj/40UYIQQbUyrJ3UOcWq5Tbbskwhq7h5IMREB81PVCllluw9H5MpW2jaEpbB9MsLU3giZ+M9UykiTd0gfwl3H9AMeHyBfyF3+XLl26dOnSpUuXLl26/O3nd3475jgOf/Znf8bIyAhf+tKXPvZ5P//5z1leXuaP/uiPUNXf+WF/4RBBQI8W8MhUAjeQCOkqPzlfZL7cRlPW7ViWygGbcikSYQ3XF3QcCS8QCElBluHBzf384PQypaaNcXAf1aeuUX7+GXaPj3PHtgmEALlcIMQgJ66ssG06xoELz7Pnrkd5tu5z+WKBiV1jDGR72ZnVORvScByH9QYrMqgqTXSGEyFWFzo4hUX8TnO9e+34FIoQPLJjkNxqk/DBHVz+y/9Itdji4OQ4g9u2oZ97Bemuw7xY2MTs3DIdvUGuZzP33PclrgQ6xbUqqqoi+R4vL7T5B3c+QO3Fn1PxFSJGiuDKGXA8pEwvq7aEUDUkz0XpNFDLa2zZA7HeDNsSEtnaClw8jtuXQZJlZAIkIwIBSIHAeOIPqLuC2ZefRwQBaiyOJWSGrHncuf+M8sR3aWw6xET+Gt/YPcSpqkc1HUcrLLFtYpjBa0cZ1A1m3fVgj5pMs1LvYAoZXZbIxTRKtTYoGis1EyM3hhG4BJ0WjqzRsH1036G8sEBIkfE9D3ttBRau0ysvcWXTnVzSNJRyE/nyGe7YvJM3Li4TCGg7HoVChd3TG7hUsqj8kp1KSJXZPZxEupE5TeAzndWYemQ/ldU1aNZI1vLocycJ7TqIP7Hpc7Pt+jxRFIXjC81bxBdYDxi+NVNiMDlEn/7R234RkIFOohclFMK3bSQJpg0Pe3GBjuMTHhyi0bEhHGVwbIjaC0/jWjYeEolYAiUUpnjkLZyDD/H0SoBT8RlMTHDwsV2EXvoJlqRhOT6O6WAvLVKyFfbpGge37mFhUz9Lq2VmZpY434J6rcnXw1UMTeNs3efihXk8XyBJEt+6eysD/VkcIbFQWT8fJftTLCznOTDZxx2RDlPjHpauE+pPI2khNAX6khHeqAq++tBXiL36LI3V9ex2WdNI7N7HkfAYC1dKHMj1oXdaCBFwx9YR4sdeRk6nUaoFnHdeY6BcRB8a4Rd2iPlCk3A8jlMqcFWNMzU6weLcdaZzSdSVeRKyRDikYBy4g0atxGAmSlBcw201GHroMQxtG56iIBQVzDaheBy308Zsdsh3SkxuzHNb8zr7M0lahXk6L87Sdl3kGz2mInaL3kgPgzEFyV8Pvn5QiFtrOrdksa/WO+wfSTNX7mC1AoJ4BFgPOkcMnSnDR/Y99L5+Pmzi9LcLo1Kg/eyPEZ5LZHiMoFEnaNRRMlnkbP9NEUa4LjRq8EsCjO/7hCY3wflT8IEgu68oSH2DRPffiRjbRPihL2NfPY/k+8ixOA4yUqqH5rkzJO58gMZPv48R0pFUDWGb+IU1mj//Ibu+8Ye8m4zTkXX8jglBwLlLcyQ3qBzaPkUgBNfKHc4u1xAiYFPaQPcdZM8kkgmTjWpU2g4/PbfGjsEkYxmft+cq1No2hibz6JZ+BuIhfvTmJWrNNhuyEYj6PLYzzOjCGWaOH0eO65Qci0dGBrhtQsdP9OA367TOv0Vjeg9XKjbDGwdh2URPJInZLRzTRJEkfAGeL5C19c/RCwKqCwv0TkzRGw/hmAoxQ1vPp3BuDfbvHU0zV2qhhkJgNZFEsC5o3cDyApptm83VGTZVlwh8D9mKouqbMBMZvr69j3zbp9C2ieoqQwmdQtvl5PyHBYqWK7DdgI7z/nfYsj1+dm6Vf7x5GBQFPmi15XuELrzL1okNmNMjLK+0OLfU+dB+V6omHS9N+FdViQQ+fTo8uiGJj4QCBL633gX9l5Blmav1gOcurN2sVLS9gDevl1mpWzy8MY0afHLVzachCAL64gbnVxsfud7QFAy1W/7SpUuXLl26dOnSpUuXLr8rfudKxgsvvMCrr77Kv/23//YTn7d3717+/M//nLGxMQ4fPvxbOrrfPwLfRwGEJ8hENObL7zX7hQCZV68V2TeWodB0uOq3sP2AmCTx0HQfpuOzUrcYz0R4pqZz+NEnsV9/mdKVKyjXrjEyOUrPwdsponLf3il0v0anYyIvzCD69qL0ZVj1FEbvepiB2at85+AYr10vM79SQgmHGNy6mYG+NJcuzvLEgMyKMcBqPYGTyKI0ahzIBMR/8L/QMk3IZMjtvoNS6zSNmRl6UnHkyS388JmjOOE4DI4i61Fm3IBrlxrcs20UTa7htToIx6bg67wTGmbf1/8e7VPHEJpGKJ0h0HUW2oJa2yYW0tE8FyQJRdNwhETH8VhuB8S0MLHBYWoioP9/9z/gv/0iTqWKFwiMsQlaA1MUfvQXBL6PLEu4foAlYLXtMdFj0K6V+fOyxqHRnWy3VjhszaHu2I879zyd5y7QcX3ueuzvUGvFqJsedjxNrWWhxBI8tm+SyuISA5koK5UWyAp1OYScSOG0TWzPZ1PGwDx2FS8QyPJ6oEdNpFAzPRiBx2ioysWigxqLI1ltxlcvktu9hbMli7bjM5SKsKtHIaREeWbx1mDUfRt7GY2riA80hQ+CAFmF/rFB9E4C/EGCkIGjG7+X4gtA25e5nP9wX4L3uJRvMTAew/+C+uZH1QAzkqT3zgeov/BTVM9BrxVpuD5qPIF64G7m3z1G9o4HEfMX0F0TS8gEkoSTyOLmRliotolcOsfwzge5lC8wV6iz5kp88zv/HenLp4jpCu3ZLK6kYLUs1vJzjBTWGHzgCc4KlZai0BMVSL7HmhrDthQGQoJKKkqhbhIIwbmVGgcmsrx1rURMEciST1jy2T+a5j65SOm/PI3ly+SSEbShUZyD9+OEYnQ6Jgkjzg/WFHq2HmbXfgfZc+noEeZ7slw+t0BPMkIobDAxPsiujELviRfRFAlhmeh7DlF+/Rht0yG7c5iZYgs120+oVcJuNbkw1yazfR/ZdAantIgSeCDrRPbfTrtt4i/MUFYi+FqSwcFeItPbqPzVf8QtrpG5+wGkVoP27HUc28XYsQ9/YAsrTpvaxcsoIYMIHoH7gQCyJCEZYcYyYRThfyheK0kS9i9l3/uBYKXa4ms7B3nrmoowW0iSxFh/itsGo/gn3mDj449jGRE+cxOh3yM0EWAffR3h2O8L+jfwK2W0eIogZNxcJinKR+7HSmSI3v8lzDdfJDBvnPcUhdDmnXibtuMpCrGtO5FtC/PYm3idFvrwBP7gKNboNOrl88QjUTzbJrRpK97yAn6jjl9Yw7h8hu899jCvnJnj6pIPRpgd27fSl4zw5rl5Cq7EIztGODVf4fY+Hb1RJl+t0zEtvnnvTiRMhKFz23iKkKbx9LlVVFnCdFx0WeetmTL9cYPx3hgnG23QQjSFynNHL/PtsSmGEmdpNNqMxBsUV2XUnn4iwqU1sZn0/ru5WDIRCZvlQOeOHZP4QYAkfCw3YDAZZqVuIuAWO8RkKk46tP5Z61LAodE0QSC4ONPG833CusresQy9soPpeDf6aEn8crP6XFQlKKzSef2ZW5ZLl04TPfw1pJ4cm0SVDa0VgloVOZkhNLKZqK7S/oDQIiSJYsvivg29rFRvvW75geBYW+PuOx+g9caLt1ToyOEI4dvv4/qsQ/ND1qg3niNLNyp2Px2B7yPxkbrLTSyh8NZM8SMtJmdLbcrDKfpDn/olPxYhBKOp0Mf2p9k1lCKqBHxBL2VdunTp0qVLly5dunTp8ree37kA8/bbb3Po0CH6+z/ZYz6Xy3Hbbbfx5ptvdgWYT4Hv+0z3xTi9VLtpZ9Ny15uuv3gpzzf3DPPwdB9Vy+XiWoNC06FuumwfiIOAk0sN+rf2M7/5IbbucRhP6iQ7Va794udY5TIb+pNEJoZwv/lH1FfXuGPvJpZrFlVf5i/euYKix5hIa9y7e4rIfXtZa5jMzq8xt+TxwESGCXuVUX8VRzRR7DJqNo516igNyyLe10dnYRa59Ry5HXdx/cRpbMtmSU1jdWbAshD1KvbIRpZKLUK6yvWKyVAixBXLQQ98DFmwtJznHT/Ens13Y4U8JgfHMV95hmqnAxJYfoCmakiaRmjLTtZ8lQ2yRK3W5OW5GXQjhJUdZu1Kh3/24Lfp33AWtWPSmd5DvdzAaTaRJYlAQCDJ6Kzbd5WaFmJ1hbLVz8/Or3JZNfna5AZ6zh1H00NE+nIE7Q7B8Vf4+qEHWIv0sqynmCBEXyrKWqlOwTO4bVOGH59cAN2gI4doV5r0JtPEfZcxqY1XqxEg43oBhh6i5/GvU33jZcy5ayhDw/QqYVLjY0TvvZvCj/+S1vxlDiSySEYYuRpg5DW2PvRtopkUKw0bRZbYO5xiMqkg+x9tZ+IHAaYReX/B76n4AuALsD8iWPUeDcv9TAG53zahVp3p5iov13ym7nucqF9HTiVIRTO01DBnjp0lIjy05WW0ShV9YBRd1nAlhXyg4rVcXCFhlkrE5QB1YARhmTiOxYnzc+w+dxQ7v0QknSb75Pc4/tQLuIGAXQc5tlBlMJ5gaCBDyfR4MCsYaq+x8PZrjEUi3L55N2fFAGfKLqWWTXO2xHf3DXL26jICiTtHIgzMnkQcPU4yJtPQYusWOouz9EZC1Pc/wPf2DHD0Wp6GbPBu3uQNX+AGEmNZuNdw0MtrREMhtgqFaOkU8tGLeJ0O2nf+CFlVuX7hGsLz0WQZLZFA2DrjuST9noGV1Fm+Ps9r5xYZGMjx8H276b3jLqxLZ7HKJazZ6wgBQyNpnHCMnq1bqD71l4hWnUg2S+O5p1BGpygPTKHFElwND3JspsK+iT7ivTnMWo1sIorZsfB8HyQJLdtDPZpla3+MIPhwEFgIQV/sw9HYaseh43jcPtXDnoEJqObQ1hbQZZf4d75LkEwifo/n4adBbTex8qvrD4SAkIGk6zcrMYJWA8kII4RAjkQJbti6/TKBENhD44S/+l3kagnJsZDjSexMH6ZQkJfmuPjUj5CjUfr33UM4rGNpBifsCOMj40QvH8NbW8ZvNnBlGaMvh54bQkgS1vIiyuUzPJTLcvumHZiJLHkL3nr9GHoig6IlSSgB//ddBs75k9jlEnpuAGN0gvqpV5AXrzH0yDfYvn0b/9NL1wlrMn4giOsqYUVQbjmUWxZf2dLLucUqWixGRFLxbJkTFZ+HR4dJF/NcK7fprNSRZ1fQ4nHsL01x7FyFjuszX+4QCamU2jb98RD9G1IYySyiXmYwGabScZAkUCSJnmSE4emN+DeuBUEQ4LgOfVGFrfvG8NsthO+RX17lSrXJ7rtvR5EAXUfI0k0lx9BkUjgk6rUPfR/CdbHefYPIgTtpPPtj8N4XW7T4Mb5x+Du8uNRhpdpBAIamct+GXnzfu0WYeY+ZisXBHVuJpXvxFq4jWk2UvgGkoVH0kQm2dFaYL7c/cmxM9USJKAG/SdfJphN8rOADsFgzGRj4zSQxxGSPL2/P8cLlItXO+nemyhLbh1LsykXw/d+M3VmXLl26dOnSpUuXLl26dPns/M4FmIWFBe6+++5P9dzp6WmOHz/+OR/R3x6yesDDW/p5+UoRNxBUOzYSsHMohen6/K9vXueO8Qx3TmaJdOrI+WWWF9eIZDM0xvu5bHuEY1FeLvjkVs+zcvoEge8T1VXSuoQ5P4sajtHZ+xBH55ucWG7StB22JBKMRhSOrjYozZtAkbuHo5QLZR49tI1Jpc2VXzxDy4H+qALNOkrgkz54ByLRT7O4gtAj6L5HLmGwmojTt2kjx+saaBoikcaLxAnpGn09ScpNi1Kzw3AmypnFCqFIhH7dQ1gt/EBhvDdJvdGk0dtD7/ZdbDh3BtWzkQFZj2HlRv7/7P1XsGXXudj7/cfMK6ed8+69O+duoNEAEQkSIEEQIA95Ds85OtKRdS1ZtuyS5ZJfXHqR3lRS1S35wVbZ11VX8tWRfC51mDNyBhqxc+7eOa8cZhzDD6sDGt0NgiBAgOT8FVnkXnOFudccY63d4xvf97EytIWt2Qw7BrOcOuESAB0nw4WVOpYumIsslJZi4/UXsPNjtKSGYeioSCKcBG4oMUwd1w3xQkkyk8ZtREghaAFH1gMetW2sqa34c5dIjI3j+SHqyHMMNRts/uZf8b1KguNvvwm6gZZM0bAG+fqBcV6+XMWnG9wpDJT42v4h7J/9L7hCoAFCE5Qe/xbNV5+jc+kchhBYMoTFC1QvnUFVy+TufhD9xadoNzZYXfLo376Nka88Rrq/H7VaZXNPkkJCJylC1G2CL39obE1RSFmUW7f+fceKyc9tdo+JwnvpKezVZR7euo8Fq0AtOUJy7hIzF+dodzwSSqEEJDQFponvApqGHgb0Jkzm27K7YKoZ1NY2CDoeRhQSrS5x2c+xs2+EaGmBtONQ/tF3uevwA2zU2rzSMJhZ3kBmFfVVj//jwV7CH/wNKzKktlFFtttoZ84wsWs/S/ltzDR8qLW4dFnQuHiBh3YMMXXuJI3v/s+Y+TzpQi9NK4VTKmFu2kqUSjJl+pRm3iY5uIn3NnwoWGy0AqYH84yVMpxbrZMYneCObET5hV+yUa0xtvsQuV17mTl7AW3+IoP5NE5vmpmaR3FyEzvtNm/OVmiVy/QlLe44dCfu6gqO2yBlQOQLZLOJXynT9EIMXUMrb2DvGsfetJXOkVcI1pdRuo5dKOIqwfyxk/Q/9g3evbSClyry1ILLtx/4Cs7iHH7Soa9VoXnmJG0vpP8rX8eYGCSrh7dNVulxBOOl1E2LxF4oKSYMeh2JNtyLPjZAGIYEUfR7HQT9yKTk/bkZ7tICyXu/ROvZn4OS198DXSdx90N4duK274uQEjZW6bz5CmFlHTQd7eC9zOTHkb/8Fe2WCy2X9dUNHFNnZLifen+S0vYdhG8/Q1CvoSdSqHYDf20F1Wlh9PShSv3YuRxup0Uq9NCSKTbpimTORzhVmBqguHYO8ez3EAtzpE0TeVzhaTq99z7M0sY66ukfov3lJI9sLrLY8Hh9tkorUvRnE3jSo9X0aASS6U0jLDZ9yq0mVifATOZ44AuPYb71AkH1DE5CJ6NJbAu8lM3b7y1RTNlYhiBp6WgtOLPaYrKU4vDdD9H8+fepNztMlJJkLANfKoYf/jIqk0YATTegGmps6suy3PA4vdYkWppHNhsouiXGCu11vrqtl++frVL1JQlDI58wKSUN7ipIMqdP3TJbRC3NE1061w2+CIEvBZ1AEq1VyDz1Pb715F+wERYJpSJpGTx1Zo2Fys0lxIBuXyYB7WwBbc8hhBCE7xsHYznzlvMrbRscHM0hP+Egxa8L4BvaJxfgV0rRZ0v+dE8/FU8SRIq0rZE31C0DvrFYLBaLxWKxWCwW+935zAMwYRh+5J4uhmEQBPE/JD8qAWwpOWT2jLDWDjgUKhKG4OJ6i5+dWCaUiqOLdQ5bDexXfoHwXIqdgNapEMt0uOOLjzPb28d3RnU6P7xEIpfAEoqCJTCaVWrr69R2PcBPnztKEETo6SJBEPHWpTKLhRR39VicPnURckUmewd5YOlNCnWHxXeO4kkNzdCYq3l4NRfHNOgcPcrQVx6n9fOLqE4dWfOxq6t84WtfonbiGBT30p7ey0q9Q6fRRrSaZHtKjI7miDod9u8ZYaXaxgtC0kvnyZcKPHBwF8cvr3F6oczzKyH/1517mMwkaJ47je+HmONT2AOjVJIpFhour3mSR++Ypt5jMCPSTAQROV1y7J2TzCQs7vjan2Jl0hxf9ti3ZRvt2RkaoUIgCaJuqZZEwmYj2YOnuWwuOjxatLDXlxApHWFa5P/J/4XO8XewTrxNpAKSDzwMjXW2qCxL9RqakyBSiqWz58lOTPLwRJaxoV7mNxrUvIjXa5IvfvXPyW3aTNhxMQsFQsumfv4sAI6m8P2ApNFtqlx763XSw5vwt+yhODFBS8tg5tO033yF4T+dxsgKlIpARX/IVYxuYhJx10SRn51YvulYwtKZKiY+twtXZr1Cc3kRUJin3mKqUCSz+yCdoEXJq4EfoecKCMumvLzG2P330vrv/19wPSKlMHIFbJHCDSXOnoNcXlxHWEnC8jpaIoWdzmBrWVpDE6w4SdIqwDRNvOldnD++SmpsirH+HBOFBMHbz1ButBnIp5CJNJrnItwW4elj3PPINCcaFl69TjFhMjWcZOLYc+BYRFJh1GtoA6N0tuznrMhy7NwKtqxQXBMcmNjMflFju1OhXczTKQ5yeb3FbC1ia2+anlQBfW2B6OB9COAVV5Ftm+TtDGgOeaFT2LKZkTvvYXFxgd0Ls2y2bRqbi/xyps1PTq3xV3eMs+ndX6H+9kfUVubJff072PvvQr35OkGnQ3bXXvSd+zj14x/Ts+8ekkNj+LMXaI1uxpzcwni2j2fPrdG2M8y2Qg6NJXmmo6ioEcz1JkV7iPueuIPdvUlUKkUUBh86xzQZ8uXNRd5MWpxaquFFipRjcmg0z5aShZQhUkrC8LfvG/H7RKbS6Nk8Ub3a/blexTdM0o//KcGlswgngRiewNiyAzdXum3gVAiBvTJP86kfdwM3AAJmAhN/foZgbbXbrOcKN4iorJXZskljZXaBwd134F2+CAICMwGGhp7NA1B49Anc9VUSayuoVIZUrYImI4h8Vo4epV+PSJx9B9GuI9wGsq2QkcROJgleeYrSX/3vefp8hdPHljkxX2ZypJc/OzDKhZUay5UWKIVm2+QzKV5fWGWt5WNpAiORAsvmv55tcO++LzG+8xC9y+fonHwPvbePp+c3mExIlv2QnrRN2w/JJy2UELw9V0WN5tn2yLfZ5q2RbqyRzOfJTG8myBUIlWCmKXn33CwL6zV0IegvpNk30ccxTSNsNlGNGo/uHKMv55C1knxzX5p3Fmr4oWSi6HBwJMfY7HsE1fKtL67bRl3JEqt7ioVaG6kUAsFifYb+izPkN01iKx+BZHNvmrnbBGD2DuWIrsyN94+Bq4EQU4U8srnIbH+aY4t1wkixuS/N5p4EKXH7wOjHlbMEpbTNRtO76ZgAxgoJ5CfQA+YqpRQGAb3XepfJP4r4bCwWi8VisVgsFot93n3mAZhiscjs7OxHuu/s7CzF4q1Li8Suk8Kg4sPFistSvUkuYdD2At5daNDyAx7dMchXdgzSm3HIRm3WfvBfiBp1hvMJ1ls+dTdAKpfEr36M/+C3CJIelXqbThAxlHVIuxXWL13C2HeIV+ZqSCNF0Oqg6k2KwxNsNAUrG3XCoWHsyMdbnqM8n2RaE5ilPsxOA12DuWqbpAaG0PDDiIXVCna5gZYqYGkLKN8jDEPcH/xX8nfezdRoL8++ehnpuihNR0lFZWmZZiLBX9yzmXBjjcPZgJRjMZHLYQwO8K7rg2UyPtrPX4yZqO/+f7g4c5HSxDh2No9/4TTu+TP0HLiPt4xRlB5xeabC13sFfXqHvzs1y5zXXYTvuD4/q7tsOTSBHBQ0h0s41b/FrNaJZHd/tu3YFL/4KP/lrMtkzuLJRJnmr56mIxXN3iyhpkisLpI6dC9uo47UBLJVp/3sz9m+/x6Cnbt568IKgZQoTSMZeezbupWkqXFkocp6o7uQ8z1P55GhrchXniJf2cAsdOeFrmmYxSJuq4WjgTQ0XNdDtRrMv/4a1skT9P/5/4bs2beI6hWUe+uFrD8GSikmMjpf2tbPa5c2aHohAhjIJXhwukRa++QX5H5TQghcDDbaEW4oyToGRRuU53I1I0BLpUmNT9F85qek7riH4cQZzLFdXOxoNAPJgfEi3vn30PfdReuF5wjCED2qkOtLYI5NsVgYpjV3ETNtE3o+mgbbhyaYfe1NIk+BCjhR9xheb7MxPkKzYDDqSFrNNqu1dVpvv4uSEWaz259DprJonSa4bdIXjnHXlocIGhoHvHn0p/4zQa1K9tEncEwNiSAY38KRjsPpmXkMXSOhAlwJr56co5mOOPzuT0nNnidlmvRv2cNduw5i7n+Y/3R0g+q5ZTSv22um4YVIBdl0iv0Hv8zoSIY1O4v/9M9ZOj+DF0Z4vsTUdb5z78M8F+R49bWjbN8ygTr+Mrqu4x57i3rHJf/kX7J26TIyX+LsT3/BxkoVotOkDt/PydG7OLtaJ5yTZMds+jdNUF5psbPX4thigwsVFyFgurfIghtw/ESd/+3hAjsSN6+EapqG1Wkh6hWQCnJ5tESae8YyTPakWaq7dPyItZZHT8qkz9H+4MuN3YpvWDh33kvrmZ9eC5yE5TXC8jrOtl0Yh+7H03T8KPrQXjimkrjvvHbtObRiD972O3mzYrPN8VFKIjBQV+aWLgR112dq5RwqlWO27lO86yGi40cwTEU7VPgKxh/5Cp0LZ6m++Ayh7+EIhVCKzENfIZ9I0CkVsQjx5i9jpzP4QYSuaQjLIuwZxE/l2fB03oyyJBEkEg6zF+eZOz/LN7+wBVl1MTMJVhsutgbrLR+UQgiNZhAxWUrx/Ik5tMCjsHaJ3X1pttoWzr5DtMs2Y3mNYcNkthkhFVzeaJNPWgxkHR6c7mG57vNyM0uQnOTuiSJjGYGhIuZakp8eXyKR7JadjJRisdyg1vZ4Yv8YgVRU3YhXL25w7kIFQ6+xZzjH3eN5Vhsd7h4vkhYeVr7A7ULZRqmXsN3El4L5ahuFIlICL5SEkYRKk9fPV/nalgJ65DFdslgdynFisXYtJ0rXBIcnSwwk+fCmLICpAqazGlsKpe5QURIpPzww+nEZKuTB6R5+eGzpWi++qw6OFylY6teebywWi8VisVgsFovFfv995gGY3bt388ILL/DNb36TXC532/vVajVeeOEFDh8+/Ds8u98/kWbw+nyTd+drLDYC1lo+XijZ3p9l22CW0ysNfnx8mT/ZN8zfvbfAP+hzCeo18gmT08sNvCgi55hESqG7LQaCGucrgj5Dp+EGCN+jsbKCbZt4I9OsnCxjjmQRAowwICEi2r296DKiojn0j40wu1YjPTrKUcdicMNF+RHluktGBmh2EmkYRL6PJaBcrmJv2Y848S69Q6NomTxhZZ1GuYLb6zLdk+b8hkbkeSgpEbrBQF+RnG3w6rNv4Zk2D28bIH/pKK9mJ/jv756naSQYLzisvPUunbU6w339dGYvY+kaDTcgNTBA6+hbbL1vlNNud7HvSKXDkxMWj40lCcKIppnk2Gqbqp3lzEaH7QM5FiOD4r2PMxA1CStltEwWfXCU//lkmY2Wy19OJaj96kU6kYapa0RhQHXuEvVTxxkQGu5bL2MMjyNrFZTbQXvrRQ6MLrBlxyHapT4MyyTXWCYVTeJqNk/u7GOm6nF6pYkmQIxsZvNID/L8SbQoQu/tQcuX0BpVHBWihQGJ0MWyDBLpJGOlNI4KyK+cxVucQfQOImwH2u5nPWw/M0JFbCvoTOQGaYYSXQiyJgj5+Qi+rHoaPzu5RNO7vkt6rJjkq+P9CE0HAZm9h2i/+AusYg/Nt17j1MHHeeHELKHnY2QyTOebrJ48R3FkmMTXvk2+UUFHkty8nZc3JO+ttKl5EZmw2xh+pCfPdG2Gjg0tPcmF9RaGJsiVCgwaLYo9HZxiif/Ha3M8MZlGBT5SQaXRZqK/wEYtBNtBVwoZhfTpAXuNVeznf0UkJZomkJ6L2dNPu9WhOryFs28uomkCU9cw7BQIQVSr8t5cme27DuNcPIOGwD32FvLSeexsAcQE83qWUtLCbFSvXa96s4MfQaA0giMvsja3gFLdilQSRRgEuK88wyOPPsHfnW6zGKQp5YfIjWyiXG8hbQvrzAnE4CQUe/GqZaRSaDsP8oMLDTbmF7rBEiFwk1neaER8ef84LS/iwswKCI2BrEPLDa41xH7x4gab9g9gvW+1VRcC6/I5Oq8/j3Q73WtuWST2H+ZYcQu/ulC5YTycXKzxlZ0DbMpon9vSeJ8WpRT+0DjpR5/Ee/cNwvIawrSxt+5EbNlFW8FH6TCuu206G+u4kSCa2MYxZ4DybJtLfoSb1Nk3MEKwukzR1sgRIvwOdt8I2Z4esCzC0++hDY2TeOLPMTaWSXs+1tadqKV5mi8+hdvxsQwNEfiI0Kf11I/IfuMvyI+N4nseYaOBlc13+9cIgTe0iaWGT8KUVGst5ptg+A2GerLMN2qEkeS182vsSkawPMNDdx/gldk1NAG6roNSPLl3hIV6C9O22ZA6d9+xnyNH3qN32yHqS1Wy2RHeW+4wmLe4b6qHt+cqXC63abgBA9k83z+6yKmVJlmrm8G5XHc5PJ7jrtEcr11evmUD+Zbrs95wsSyT//jiBSJ5/V7Pn1vj8kaL/cNZNtoe6RREpX7M0QmCucsfuCAGiXu+SP2lp6m74bXgS8MLu/18DIO6nuTZs6uM5R129dgYMuD+8Qy7BzOsNP1uVk7aJGsqPmoDF6XUtUyZT5NSigFH8qf7hzi10mSh6pKyDfYMZRlMCcQn2XAmFovFYrFYLBaLxWKfW595AObJJ5/kxRdf5N/8m3/DP/2n/5TNmzffdJ9z587xH//jfyQIAp544onP4Cx/fyw0It6dqxKgsdL0aV1ZuH1vocpw3qHlhxiGQBPdhVzlVwkihW3oKCCMFF4o0TVBww3IuB0uWb2M5gvY62ex7AStVoeMbaDJCMO2kZoBCAIFYbXGmp7D80P6cxGbt2xiNVml3PY5ttThzoLGgGZSbdfJJCxCP0SzE+hKIQIPmS1QVRqDW3fg3/8Yxzsag98YJmEaHLuwzNasxfYtRc7WQ0KpmCol0QyT58+u0NdToLq4zFiQoPW1v2b2UpOJwSIXN1qMJkDNLuL5ARu+Tq+TJLyS/RFsrJNK5shpVxdDBMsNl/qlJRJvvMjGRgNhO9x738O8W+pjphEwmNDZIyqstlxqLZdkqUjO0tkIPHRd465NPSTmT1HxAgKpmCg4dC6fJ+i0QUqaJ4/hbN+LWpzr7sY2DFTgo1YXSaz/iMzoJFEiiZZMobgHAFsFbM3r7Ch1s12iKMJVOfQ77sXwOlizF5HtJprXQimJNEyCkSHoHaRaGsae3kpy5izR3GXotLF3HUBzEkD1dzlEP3eklFhIilc/DT8na9ttafDj44t0ghsX6WbLbZ41db667y5YWyJaWcDqHaD54/+V8p/+M57+5UuIRBJhJ7DCAFHdYKXaQqkFEqsr3d4vus7k2bNs3bydws4vcIQAw3HYO7WH0oV3EK8dITkwirIMiimbiRTYRkTrh/+FQrEf0Rnl/7R/kFNNGBwepjE/D0pRa3bIpxMUMkWCMCSzdy+lngSpl1+kubKMshPofVk687MkH/kG1ReeYS000OkGw3TTRgwMo/wOUb0GYUTDSpM0DEKpQNPwpYLTJ9j6wB7ePr9MRXPICANTixjoLzI2OUrKNvBs0JbmQBM0vRA3iPAjSSgVUrrkFy6RyaYwbZu6MFlebxM2G6BgPZold/gx0CI0FLlMkkUzx2J5joST6Pa5EWAEHoPpBOV2iKHrFFMOuaSJH0S033fdWl5II5CUzOvX0d5YofnCL6+XwgKU71N59SUSByxMvXDDrnmp4MXzGwztuzGQ88ciAtq9Q5iPfIOE20FpOoH94Q3MdV2nI7sN4R1N4QuT+abE100WjD5eOjbHvp2T3Lt5lNPLDRr3Ps5IdY7ckV/hnb9A8Z4H0MqrtH75fax7H8GduYizvsJlK0fDTDJqhvT2l3Ff+hUoRdI2sU0DGXRQQhAGIVG1glcYwkymCaMQr7KBOTKB7wfMVzpYtkVLajScDOgufhixvrrB1GCRWtOl6kVM7R7hrl6TYu0CxtgkW8YcpFJICa9eWmd2tQ5K4QYmxysOgzt3sppP8t9/+Dzp4ZB5P8G51W6ftq/uHGS54dEJIsYKSf7mwjpZxwS6PVZsHd6dr7K1N01ldQNdgRQKIcQNQekL5Taa0G8Ivlw1U26zfySHZWiAJLRsovsfR6yvYJx6i2hjFaNvEGvXfrx8D0bfAH75AiDoBBHqygvld+7m5w0dPwyodgKWWjqjSUCGFAwoFvQr9w0/N5/bH6SUIq+H3DuaQo2mEYJu8Odzer6x30+GrvHIoHnLYykVoD77f+7FYrFYLBaLxWJ/1D7zv8j7+/v5F//iX/Af/sN/4F/9q39Ff38/Y2NjOI6D67rMzc2xvLyMbdv883/+zxkYGPisT/lzS9MN3l3o1ln3I64FX646vlRnMGuzd7jAd99dYKbcZteUg+eF1NwAP5KkrO6QMHWNVhDh2mmOLLZ58K77MRfmkUhAdIM2l0+yed8THD2/QMcLUYBpmYQh+AqGSxl+eLHMP7hrimfevkhN6hyvRWzedwcs/AI/kihNRwYRtp2gtGsPp7U80+P9HFcWL7+xCFFIUoMH7tmLl/V4emGNUiJksphAtKpcPhMxE5psH+thcGyYR+7eyeX1Os+9u8yJDZ/+lMHDO4fprK9DJo9UUGu69JVy4LXRNYGUEaZlUQ01OkGE3mkiy+tQdCjk01iZDOvtgNZbr3HXYwPs3TPF5splWk//hJxSFOoVwo1ViCL6Ryb5R1/+Dq97CdR8g4RpMJg0Md02nU77Wh9pr9PGTqZxV5fI7L2DcGEWFYYoGSEsGywbAGtyK4HtIJRC17tBMinlDYuOURTRMW0SD36F9jM/gXQW6Qcsu+CKNGy5i189e4KEk+CrX/9H9P3if8HZsgvGpz7tIRn7mIQQLNb9m4IvV11YbVI/cIAe7W1oN+m8ewS9b4AzTYUSGsr1wA/oBB6MjqJ0g0YgEZqkXm+Rtk38pI3z5vOUsgXu3pghbLcYG3wA1/dYtIvIjiKbFGwpOTA+zcJyFXXwi7wzX2P5UgdrYY57Du+m8IUHaX3vb0kbAqkkS60Qqfu0MLjQNjn5+nn+6uFvkPhv/5GgsoFWKOJG4F28RPEf/B9YCFOYqxKBoBkJIjekYBoI0V2j1EU3+CCVQncSeEqgEBxfqvHV/RNcWFinYyu25izadoo3Lq6hawIxksRbrbOlL4OiO/WUAk0IlBKoVotMtkiuU+NUIyBhGliZfHdhO5PjzVWX8f4CdjJNKpfjaN3DMXTAwdY0wiii7QV0ltdoZNNsGu5F06DW9m5YqE7ZBrYGxvsacuu6TnDq6A3Bl6tafoR/9E0m7vgq56o+AI6pM1pMo+saM/WIvqRB3lSoP8Id9IGCwE50f/iQ4Esbk2PzTc6uNpFSMVZKMVpIkprehjU4ShSleOJrm3htpsKrRxeYr7m8lkiwO2Fw/+En2bF5J9rMadhYwY2g9sLT9D38FarP/IKU61NL9XG0FvFwpgCpDFGzRRgpgjDEUiAjiabrSM/F9QMaG+v07DmIP3uJeqMNvYPIsAWWQeHOu/nhuiRwPXTbot12kY5GobWBo1mk1hWzP/8xqwkb59ECLywYlFIWFzZaNNwAJSWaEOwYzHJyZo22MPnrwzmEUvjVKlOjPVTcEB+Nly6s8ZWdgxQSJv/trVnStoEhFGnbYDjnoCmJ1qxSXrbRNlbxOh0wTUSugCj0IOmOY0s3KLc8DE27odH9VfNVl4enCjT8iHfn61xab4HQ2Dz1IPvuTZE1oX3lcYl7v0yPmaby9nsEnQAzkSC7ay8ne7ZyadElYxtEUnJmtcnkdO5aDyT1Wacp/gaij5ChFYt9bEHAwve/e8tDvX/1l6iP2GszFovFYrFYLBaLfTo+F3+RHzhwgH/37/4dP/jBD3j77bc5cuTItWOFQoGHH36YJ598kv7+/s/wLD//IiWulbyJlELXBFt600z3ppEKUrbOeCHBWsvHMXTCSPFq0+SLk5uI1he6O7p1DTcI0YQgPTbJq22Ljt/iXJjFvvdrlFSL4sh5hGkSZQrsdDwuWgbVRgddE9ipDHZbcGiihK8g4dicXGpy5NI6miaoZxNcHhhj5FGdzrG3aVVrmMkEyW27mRvZxvHlFtFSjddPLWJoGhnboBVEvHt+gZ6xSc4trDNXabNYc5nqTWFlFKPC4NHpEoVTr/HsJYtzyzXKA1N0Ap2T9Tbnyx3+Yu8g0tqM9u6bqChCaAJDaHhIglCS2LaHXyz6RNKjt7LO7sE8iZUzRELgGDCSs1EKrPmT2FvGcZ9+DVAoATJfRMvmCUIFAgb8Ml/efQgVbCZcXmCp1iGpXem1IgAFvm6j9Y8QeD7SdTEnt+CfPgaaht4/hDQM9Gwefcde2kpnrhFwYqlMECmmelNMFxOktPDaApRSik6pH+frf45WXqW9UiFq+ax1JEePz0E2j1/q5afnq3znG/8DtqVYCEwWFmuIUCdvdctuxT4+TdPQVTdAGfLbLQ4KIah2btc1oTu/G5FGT74HTTeIqhsYvYPUAwUI0DRCoeG7ARUjRSqdotlsk3UMbFNHCNgINYYO3ceZ5XXqi6v0HTjI356t0zOwj6ld9+Ctr6F6S+haQOvyRRZLU7z9zgyy1UBL51htdPjJ80e5+569bP3mt2m88hytWhPDskhs3s766C7++4l1RGTx/55V/JN/+H8mvThDXWq4iQxrmQGenTfYM5KgkSxSK1fBczE0yA6X0As9pL0G+ZVLIARGKk2gW+SKJaId+xnMpHhztkLJtvjOvTtodHx+8vZFAqHT1Examk0mnWax7jKUdbi00eq+t0CoFNrQKHc4GapvHCGIull/hmXQ8UNym3fx8mrI8XqZf/jQV3GPvAwKdK1bOswTNsbIML5uIbI9LPuCB0pJNpo+acfAuBJrMXSNoaxNf9Yma9NN4wC0KCSqrN/m6ir8epXslYy88VKK8d4clzZaeF7ASr1DreWyYzDHPeNZDHn7cfLHqoPJD46vUGn51257b7HOK5fK/P07HuDZ4/OcXikzPABHZmsMZRNs6suioojVmQV+uGQy9Ogh8m8+h6pWaLc8pBBU33kT54uPITyPyUIfJ8lRHhzAKA7gr6wShj4ChW0nEFGErgnMiSmWXztGZ22FngfuJr11F9VnniJyPZSTxD54iMamXcwfWcW40msFJ4Gvm/h+yEhfms6p4/hBQMcP2ZpOMJDT6QQR1XaAoYHQBEMZh76EwTu1NiqdpRVIDKGwEzahoWNYGkmjWw5zspSkkDDpSTv0ZcDSoCdlMJxLYiiJSklMIZkeLnLi/AIoRbS+imHakM4CsH0gzU+PVRnJO8xWun2YrjI1jV2DWVwp+N7RZZre9TH6zkKNs+stvrV3kLToBmA6po1x/yPowzsxay3qGPyqIlhZ7JbHvGO8wEq1Q0/mWnf5WCwWi8VisVgsFovFfm98LgIwAH19ffzjf/yPAeh0OnQ6HRKJBIlE4jM+s98fhpAM5RzWWx5SSp7cM8TJ5TrfO7rIeDHJ3ZMljsxW8SNJX8Zmx+Awr15cZ2nXvYxfeJOR1Tlm1xvYpkF2yxYuTd7BS2caHBhKs9FyOXt2Fcs0+eYd99Nz4hVmX3qJQDf55qNPcHooz7yeYU1Lcv+QQ9sLke029/do2FZIT85hreayVm/zy/MVnti9i2qiRNo2WWwGvFVTGOuSe6cHefv191BSYVtad9e6ECyKJAdSDuOjA1xYqiB1nWXNYcQIeGwswdjcUZaGppldXcDq6SOTSaKvNrFsk0AJXpypoZfSbPrio3RefhZbSXRD4IaC5P5DnB/exdrJOj0JA10o9hV05OXV62+u6u77lfUqWrtNWC1fO9QKYaXRXRwD6D15juTWQ2QmpnDFiwRSgXVjaQhj5z5WL10m/9i3kRdOYu87hL3vELJWJTR07E3bECOTNJwMT1+ocGGtee2xS7UO7zkm39wzQFp8YPFV02ikSny/GdJyPWSkYMBGyIiw0yZoRpzqDLPR1Dh/YY5kMkmn3WakmORLm0skbtsqOXY7Qggct4W8eIbg0jkQAnvzDhifxjXtj/WcUkoKyVuXEwEwNEHCFKhkgmBpFmNkkqi8xshQLxdbCoIAWa+hOQleWWzz5UceRz31U1zfA6kwLYHZ28/qnY8yN79B//hWyr1DJOoB+3sN7E6TzvAQYTLD4luvYAyO8frxeZRUmLqB8l0sdMJmneeOzRJO5OnsephcJslYX5b/6WyTmZNNzEAiW23qzTbv7DyIGizw+oVV/MBiyEnQn9G5sNrkz3b38czJkKZro5SirXRKk9M8mqih/+hZyOZwlUaQzNIamOZdL8fPLi1y/1QvZ5eruJrJywtVZiou+WKe+ZrLDy8p/tHOfVRefxlDE2zpy7DScPFCSaaQIzO1BefUe6zWu3PL1AVtP6R3coJzvVMsn2vhRybzmSH2PPxlZDPk/HqTVDZDaKWZC3R8v7uAvKvg0Ox4/PXhcZ4+s4YuFCnLIGPrpE3BA9M9iOh6gFNpOlo2D5UNhBBoYdjNhtE0Mtk0/sh2wkKBh/pNzqy2+B+fPUvHl9iGxt2TJbYPFTixUCFp6Rwa/PAyXH9sNE3j4rp7Q/AFIJSKXcMF/u+vztObNNixaYgXzq/ihYrLNY9NvRY5PcJOmByaLGJXV0nt2g9CwPoGtaPvEK6vMPfqK6h0juwjO+hzMoilOZzhUazaGtgJjIFhdAHRwgzS95BOGlHfwO7ppbVpF0tLy7h776Vn927evVTlxbUmBWOdPRO9PHNuHZQiaxlIFZJLJbir36Z5ZhHLcXD6+nljI+K+Tf0EstuzquWFbO1JoHsdnj96GU0T5FM2a+U66UyKTq7ERjuk7kWUWz4ImO5NIaXi7okiZ5Yr9KVsLMvk6bPr1MtVVOBzeLqXr04Ps9LwqfsRhlTgdtDSWfaNFhhOaQzmEkSVDlM9KRpeiBtKtvdn6M8mqLshPzm5xoWKSyFhYmnyWgZoyws5udLk7uHktcwQUwUMjA3ziyPznL/yfWcbGneOF0ibGherPl+YKl7LfonFYrFYLBaLxWKxWOz3xecmAPN+ceDl44miiJ0DGU4t15nuSTJTbnN6pUl/xmH7QJYfHV8klN3F21LS4uWL6zy+c5BfXNpg29jd3LPrTnbasBoIfrqq8FsaD2/tJy0ijs2tokKFSti809D45v2PsHvLVtpLi5impJwrcb5hUm8E+G6Vx5wqrXfeQGs3mRwq8VeD0xwdGOKlxTYPlRTaz/+W0e17WaaXBVcxkYBdEzkuNUNkrkhWdX8fz3Ywi720zQTPnl/nrw+NMjtc5PxGi1Aq/nJ7nsKRX+GeeJtLWx8k2lgF0yKdTJHLJKgEYGsaK60AY1MvL80s8Y0///sUZ4/j1WtkhsZobd7HS+d9Joop9o3k2dFw6bz6FPmEuCmLQctmUaaFsG2U28GVGjPl1g27f10ryWvHF3l4IsOurzxC5fWX8asVdNMEyyZ1572sbNSx1haRs5LBqUmiZBpjdIJoYBSkxJMSpRQLzeCG4MtVDTfgzbkaD01kumXLhCBRL9N+6sc0pvZRvryKkBJ8F31gmKjVhChCZQscr0UkbO3acylgrtzmqXPw+NZinAnzG3I6Tdyff4+oUbt2W7i+inHuFM6Xvv6xgzBDGYuUZdDyb74em/syZE0Is0WU20G//1FmQ4co3cNyUhJKKPWPQa1M3c7w3xYF/+DP/yHNuVlKrRZmscS7DZ2Vk2VawiRtD/Alx+ZrS8dxn3oW0WqS6+nF2XsnDBY5lyliGhsEfoCRTEG7iW5qhLZDBUGARt3JYuUK/M35MseWm+QICCOFkclyeLLE85erdDo+S+sugV/nzIbHVG+Kv5yw8J/9O/5q515mfZ2GmUbLZhkopBGNdcL7voa9PIsbQHV0O6eyo/x8IWC16fP9o4v8k3smWKy2MYgY7y9woR4ggYYX8d7AJHcelpTffRu97WEbOqnBIRr77uX/9vIq396+k51PjqGfPoVFRDA4wXymjyNLHpOlFJt6kiAEfzMv2TVSomd7gqoXMrvaQF1p4pBzTPaN5BC1CnuNgB27c1xqRtSlYLiQZLonSUYLbyhLFkpJYvseosvnobxGVC2jwhAxuonl3Yd4xctQvlyl5UXM1VxKKYelsIOha7w3X8ENQjaVUhxdqLGrP4UTN5TA0DS0KETpFmdWKjcd7884zFbarDY90rZBKmlT9UFpBkop1ls+hYLNV7cUUS/8jHUVklo5i2zW0UY20fPQl6m++xYKSJkaKMXT71zC0HUe23UHE6PjBEdeJDh6hFBJnF0HSD70Vby2y+a/+mveqGn8p1nJVM8UA8kSotqibqVwC2neqGn0ioA/2TvMxXILx9C4azDFqJclfP05/GQGa3oHc72TvLAq+caQpOUFbCol2Wj7nF6uU1lZw0AxXMqQsBS2kKh8iTXlUPci1ls+muhmcCkFb85WUaOKbf1ZPAk/PLrYTdCUEemkRW1ljZ81anxj3yhrFy5zYb2Fk3DYMZmgty+BjHzu3VTi+0eXIIgoJTQGc2ncSPH8uVXumSxwfKnGetOj3PaZKCZJaNcnwYW1FgeH0uhX0sKUUpSMgH94aJRjSw2CSGIIwXKtxcW1DsOFJENpA9Rv9/0khEAI8ZkHLYVu0Aq7qXJJQ0EUf+/GYrFYLBaLxWKx2B+qz2UA5pN28uRJfvjDH3Lp0iUqlQr/8l/+Sw4dOvRZn9anomhGPL5riNm6z89OrWJogvs39/DMmVUEGgmzu2NWaALb0Hn50gZ3jhW4sN7iP8x3eGxnP24gGevRKCVN0rbJi2eX0U2Tnm1bGcw5WF6L/9fTxxnsK3LXnV+ibqX51fFlXr64wVDO5n9wllj/5XNEsltX3ug0WX7uGbbv3I0+eRDj9Mt4y0tYc+f5Qm+GO/ccZt4ucerkaZLT21kQKcgl0JSiJQUb6z4jeYMndg/SDiQJU7BnMMul9SbmuaPMnT5H0yrhOhk8pwVSoZaXGZmcptFQCMA2BLYO+3ZOUAzW8YKIsG+Eajugeewo+zYdvLZLWAoNr+NBwuHall0ABNaug3TsBPb0drwT77DR8t8XfBFIBYxOM/feUY5Ueri3fYl2tofC9j0kHv8Wqxcvcv7UOfqERyuSjI6PYO+9gyjfQydXgCjC9D3M0EckU5xcvjn4ctWFtSZ3jeVIEGGFAe7zv0Q261iBi2ObuF6AsBxktYLZP4gMQ9qZHpLJBO2Od9PzzZfblL3CDY3CYx9O0zSik+/eEHy5KlxfwZq5gNi882OVI0uIkK/vHuDnp1aptru7+QWwqTfNPRM5VBTgCw37zgd4Y6bCyy+/gyOWePTAXl6YqXF2vcn40Ci6bbF7MMeGsPmvSxY9hRLzF+qEbhPp+3xhxyh3ThSZPPIzms/9DDeICCOF1mxizs0w/PAj5Ia3YegalvTwIhtp2hhK4eRyFFI2kyN9jAqDly5vcGyxQSQlUigiP8DRwU44XLpco+hoaKGPbWjs21Ri1FbMehq9W/fBpdP0rq1xsD9PvX+cs9o28rZF544vcmS5xkYn4qUll8qsT3Tl/UxYOmtNj90DaTK2yapugPRIE4Hf4bUlnfX+bTzw5HaE1yLSDU6GSV6aa6LrAmk5rGbzvNKfoOYGrK965Js+tXZ3Xk+Vejm+UCFS8N5chem+LHcWiliaoOmFTJZSjOYdxppLNJ/+MavNJn3ZBA8O96H39GNO3kVLBNzq8su+IRJbdtD85Q+7wRfHYX7PQ/z8fBXyGtu2D/Jf3pzFCxVCwFghSa3dnbdnVxrsG84xu9HCixSO/hsPrz8YOmCXV/FPvktQ2cAcm8JgDIFCcb3vTiFhcHathUDgh5IgkgzlHearHcSV5u8HSjrq2efwa1WKpVz3uimQizNgOyT3HKB89iIrvqC+1mKtXMcLJSt9Ds7RF8mUF1C2g0hnKc/Msvr/+xuST/4Ffj7HzmzIzPwZTizMcXpknC2D/dy3q5e/eWue1WqNmXqZs2sNvrlrkKG8w3ffXWSsmGJq/1e5VOlwqhZRPt9GE6AB44UEFyLFC+fXGUlAvjeDJRSiVqaU7WNsqJcXVgIipVFpuehX3oq7J4ucXq5T7fisNz0e3tLLf31rDl0T6JqgWEyTD1roQUhzqcx5vcmdp55hChCajpx/A/Pg3QS776BkRnx73yBnVlvMlDuMl9I8dWaVgYwF6vq7L6Viqe4yWej2M4NuYpH4wMRQSlHUfXb3J3lnoc5spYOpC+6f7mFLTwJTffwMzVBKqpHBbKVD0wsZyjkMpk2s3+I5Pw5N01j3NV49X2G+0i1NOlpIcniiQI8lP/PAUCwWi8VisVgsFovFPnl/FAEYz/OYmJjgi1/8Iv/+3//7z/p0PlVKKYYSkkhZ7B7M4kYSUxM03BAhwNB00k73shuaIAglw/kEqw2PYtLE0jXena+ipELTBMM5m12jRbb3jnL27AwLFy7QanfQdJ1Lnsaxoxt8aYfNWCGBvrmHrbpL46nX0YUgnTAoJC3qrs94McXGhdN86cA+Ls7PMuho9Jga4eVzNE6eoKdQ5AvjW3DvvxMvgnakWK57nFtvMpp3ODBW4PXLFSotj5YfkrAMvrmzl8573d41lfUqPbag7nV301o6UN5gsDREzjHoSejsz0i0UGemlqYxso+LG20mszrOxWP0DVc5WtVIJpO8qxd44P6HEGeOoPwrC9+mReLgPQT9w0gp0XfuR1tfpb1+HgCJoOVLBu86zCuzFaptn3MrDe4ayOLMn2R17jLW3jtp7TzMxPg0YavJyGAvid5e2ppOFEVYUYh26RzesbeIWk3s8SnCxDY0pSOFdtO1jqTqLhAK0OtlOld6SiQXz7NrbC9vnltCad0ybrplI3NFZAT9GZvjtdbNYwdoBzIOwPwGTM/Fu3zhtsf9cycwNu/4WIXdlFKUzIg/3dtPuRN1S2fZBnkbRHT9GVe1JK+X1zGnthG5Hc7NrbJroIdD20YJNZ3hfIJjcxssWyZ3bBngwmqTsNNCGCYEPqHnsUvUabz1Ei3v+i7sSHYXLddee5mRHQdJZ9J02k1MJPVIEeYKlJ0ia03J6bLHxdU1Htg6wBuXKwRSoGsauuEyUspwZrVBzjHwfB/T0Ll/7xSnVuq8cnEBXdeZTAt2ZMbZv6Wf+WNvMLKyyN59cO7Fl8gdOMyZegI3VSRj66SsBJahsbUvTdo2SFsGC+t1MrZOteNTcwMSloFjaShN5+JGiwe3TfH0+TXWWh7lZp2BnMOf7B1mIGNzcbXG1oEMz59bI5QKx9RIWjr3TfWwVm8RyeuLxOdX6+wfyfAnewY4MlOm1vFJtjs0nvoRQauFLgQ5WyfYWCPYWCNqNXAe/jp02iAEgZMkurLAqtcrdNZXSX7lG+B7BD1DvLlmEWkeam0ZtXmChKkjhKTjR4SRxNAEoVQooBNE2IaGqV8PMvyx0TQN6/JZmi/8qlvCDZDtFtu2ZlmshpDvuRZCD6OIYsqiHUR4YcQ7s2Xum+rhpyeWEUKQNDU2yQZN18VIJslqIXqpl9DtIJSEtSVSX3iYprZA7sGv8OrJRQLPo7+QJT13htnL80ykdcTKEjLXz6VmDb+8Tv6113lj7BCb7JAnRnQ6RYvUuMN6u0pnpsFDYyU2ldLYusIJPGbPnuZMaJDJFNgzlGG9HWJnDMwrQd5t/RmOLVb4k73DpG2DmXKbjWqDYHGetowYH+7jCwVFztvg7qleji02mKt2KCQs7hgvUOsEnF5tkjB1pIIwkqQMmO5JoQGW3yaYWUfLFQjqVebqNocSScJL5zCGRpAC3ONvkZzaSsdJkdVCDg8nOTya5s3FDmkDUJJy02P7QIa1892gYceP8CO4mny5rT+DbQg6oYFC4GiSKIpQSlEwQr40mcFTOXQBBhHyt+h1JITGW7MVfvru/LXg7TtzUEhZfH1n/82lPD9F5UDj795bxA+vB1oub7RYqnX49r4hcnocgInFYrFYLBaLxWKxPzR/FAGY/fv3s3///s/6NH5nlFIkDHA0ScoQmLog4xgIQHS7qlBMmFhC0fBCUIrxQoLD4wW+d3ThhoUB29AYL8Gx5QYLrkDrGcBUgGmBZrGy0QIFJ5bqDOQSHMgpagkNO5Om3PKZrbSZKKZYbbrkHJO8W2OqN0V6/jytRoOkYaDw0TSN1v77+NF7C8y0ImbrAcWUxSPb+kmaOk+dWcELJbmECX538fGNC2sUh7agX7zASCFJ/dIZDkxP8e7FlW6qgO9RSJgkdclXN2XRLhxj7vnn8Gs1rGyG3TsPcrySozC6kwnpAw4AC80AdeAOElunoXallE2uiJdMX8t26VgO5pe+Tn78Mu7cLE0MnP5RXl/vcH5pBgChaayWG8i2hxBgXjyFvXkP75n97Nw+DWZAWymIInQh4OibtI+9de2995fmmJoaZWG9g+gd5IOb6IfyCZK6AgnKu57RIqtl9g9UaY71cGZuA6UUKoxImDpf3t7PaxdXuZ2EoXGtU3jso1EfsmD2MTJfbny4wlQB/TZgA4Q3XZ7lhkeoBJg2mDaBgEuhxoVTq0gF39o7RK0TEAiPtC75h3eN8XoGEBrTQ1tZXq9Sm53B77g3nK648t9GrUHfxgr3HdrJU2+AjkYxV2Il1Jmrejy6vZ+O67GllMAREfdvKvD8hTI+Asu0cAyddNLh/EqNtGOybbyHV2erbFQb3U8jpRBC48zcGt5gkceHhwjeeh5zaiu6lNheE8MTuGsXyIxtoq83R8YxefniBhstn5Sls60nwaGRHN/YO8JPTq7SCiWmoZNPmBwczfPLUyt4fsC39w6z3nSZr7r83TtzJC2dh6Z7mC83eXhzD45lMFlKslhzObVYpeFeX5jVUBQSBkVLQxOKqZ4Ub85UKDQ3qLVa2IbOUM7B1rqBUS2VwUpniX7+d3gba6DrWONT2HvuoJPMoOpVosoG7coGIGhnB1memb82zw0kKIWlC1wBDS8kbemEV0rSmbrG9sEcGV0S/ZFOWctt03n9hRvmoPI9xsMqfZishT6R0W3cvlp32TecR0MhpSKQCqUkX9s5wGuX1imlbLTOMpahM1wqkhAhQiis7btRbgfZbqEVikSPfItfrfrdTQ2GxWgpjXf8DcJI4ukJzIFRZsot2l6AEODOXqQ0vp8X1xRMTrG/3yN19h30d17HS+cZKA7QP72XI6s+xy4v4wcBBw9sp57J89zZVc6sNknYJgdHC3xhU4mEpXN+tY7r+fSmDEYLNgdGc/RuyyGX5tGXLtN85jwyk2b4S39G35YSQ/kEdTfgjZkNKu3umE5ZOqYusHSBrWtI2R1EkeVgDI6gat0+ZxlLQwU+Rk8fKpW98h770KyDk+o+JorQlMIPrw/Euhuws5SmL22z2ux+P10d28WUxWRvhpfnapxbbSIVbOpJsWcwQ1YPUUohZYRJ1M1A+i3HSSXQePbs2rXgy7XbWz4vXqzw2JYc6ncwiTRd573Z+g1/Y13lhZKjSw0eHE9f64sTi8VisVgsFovFYrE/DH8UAZg/RgVbMJhLsFTrkLF0DKG4upHb0DXSpiBnWWh6gqmeFDlbI+XY9GcSNLyAlhcSSYkXSsaLSV69uEaomWj29Vo3lpCMFVKstly8SPH8uTX2ToJsuti6wI8USVOn44e0/Yi2H5FzFb0Dg3TOn8AyNKSmgWXjPvB1fnh6nbMJk6brk8/m0IRgpd6hlHbouAHtQFJImKRsg760jaNJjper3DE4ijd/mVJ1ib5ihq13TnByrYVM5RkazrBrMEPvqTd453v//VopKLdcpvPir9ix707eCEaZmBwl7wb05hy2TOXJWYqOkYZE+vqb+oHFm1DTqfRO8GIrx6X1NsGCoqdcvnZ8e3+a5ddeYzSpU257NNfK6PUmJzcUTdfj69uK1+q+W80arZPv3vD8yu0wIZq8o0JagU9oWteOGZrgrvEiXOnXIlLpbk2XK+donH6Hh4bGObB3E1VpkByfIJdLYeqCI7fIpgHozzoUHA1kvPjzUYW2gzkyjnf25C2Pm5u2EAjtw4M0vwUhxE2BORRYSMaLKZbq7rWbc47JwaEkwwmF3qxSLBX4m1fO0Q4Vd261CXUD09CIpLoWaNSEwNAEHhqjhQTfPrSZS42At1ddRkTEk/eMEHkeZ9fa/OrYCqVsgsfumKaQtAiVwDEFWRFRb3ssrklytk6pVGBmZoG01s3cyCQt7KBFO5LMLJVpbh0mH0UkbZP+XILZU2fYefAhfrVeI+c1SVglfnpimU4QoQlB0jJ4Y75O3Qv5swOj7Bkr0AkkmqaR0AWWodEJQixdMF9ucnGtQYRG0jKodnyEptH2Q+odnztHs2S1gHyvw9yGQcMN0JRENOrkVIevFLPYrx5H23MXY4U8g7kkpfMrtHvSWBoIZHcKahqJ0QlaP/s79MFhlJOEMMA7e4JgcY7EY98C3bzhommhj2kZ+FcCLFEYUkpZV4JMBqauXbsuhaRJKWWyvWQTRb/bEkqfJ6JWQbqdm243T7/DY9v2MzeY471adzxP96bZ1p/BFIqj81VsDdaqLfIJk793xyj9aZvhqiI4k0AoSYiOns2h1leJmg1EOkM5N8j/9PwSQ8UUUQRCE/hSoWs6KIWm6zQldNfXxbXbhGEy1+rw0sUyY+kNLr3wCr1Jg0y9Qn12huLaAg/uvptGzibfM0hFS7C8Xsdru0zmHaRusFjrUEpZdLyAIFJEaKQM2NGX4unTK/SnDO5IJwn9DnYyyVBfkd7eNN+/0ODUcoMLa42r7xqGrtGXsUlbOj2OYPtglrdnu5sNFBClcxhSUhwKObhtFMMfImg2biilKIwbUyWllIwWErw1e73/zpmlKg9s7mGjHXBpvcVwzmFnf4rxUoqfHFukfKW0IsB781XOrTb41t4hMtonN6Y1TePyegd5m1j4zEaTWpAne+uvxU+ULwVzlZvH61Vz5Q7+aIY/4oqCsVgsFovFYrFYLPYHKQ7A3EIQBATB9QUAIQSJROLa/3///35e6SriS1t7+MmJFTYaHe4YK/LGTBlD1xgvJNCFBAV3TxSotn1+cGwZL5QcnizhBhI3jEjb3UU+N4iYu1I3vT/rkDG7C0uR0listbENjSd3D/K3R2ZYURqDjkPoupiaYKSQotrxGcg4OI6F6htiPplj6MxRWFtC0wR6Tz/HXAvfb5EvmVR9xWq1u0gxUUxwcqFCRgTks0n6MzY6CpRECYHvpOkb6kO0VjCEwFq7SF95lp0DIxiHdiOTSex6mZU3X79poVoArWNvc/hP9xJkCgz4LdxIsd70yDtJCob6tb07pkoO7y2b1NwAU9cQiQQ0G2weLtLTWGW10yFKdHcJ29ksG0oHQjaaPp4U2FfHUb3GrbaxO6fe4snd93DMSXG6KYkixVA+wZ3jBfptiVLdx4fZAtboJP7sxesPXpwhtzhDT/8Qxu5pfBEilOCxnf385MQytau7+wWUUjaPbOvFUGE3kPN75KPM1/f//09y7kqlsHcewJ+5iPLcG47pmRz65FZ8pT7Vz4v+jNVtnv2B25OGYmd/mn0jOfYPpRntLdCpl5Ey4uED03z/+ArVRneeVVPDJIt9qOZFDO1q7gtoAsxiCTG5lbqZ5HQY0NBMpkfSFA3Ju28dp1NvEJQGUMBarcPiWpVSPsOLlytU2j4jhRSPbOtjriVZafp4UpG0dDQlsCyDwbRFZ2EZBWhIWhGUcnlCCUu1DrpUDFXnODg1QJRO8vzlMk0/ImnpFJMWdTfAMQ0aAbw2U+XMSoNKJ6ThBmQcA12DPzswhqYijs93A6Q6kqGsSU/KYijnsH9whIItEDIEBClCntzZQ7UT0ZxfwMoIivUG9okTLG85xIsvnWbdyhGlUnwz45CIJI4ursVozb4B/BPvoMIAod/4NSubddTMRbTJLQjbuTZuUiuX2Dy4lRMzawjDYK7a4Utb+/jpiWUaXshI3gGlsA2dP9k7xGgaRPTh8/Xz+H31Uefr+3/+jc9fSaxTb7F3YIAtuzd3yzAikdLjC6NptvWluVRuE0nFRCFJX1JDVyFWTy8qXyCqbAAQCQ3RN4hZKBGObWbOyGLl2lQk9JZ6oLrObKXNgS070FYWsYWiolkE/vVFdmfrLt6pRoRhSORFeHZIEEkWyi3GR/pRlSrG/EXM2gZ/+ei32Mj38rdvXMJIpmm1JGEo0TI5Ik3nqdMrPLZzgI2Wz+WNJkfnAx7Z1sufHRjhxHKTd9oW2774TTZlBGnH4th6h7uGUkz3pPjuOxELtQ5Zx2Qo55CxNL60rR+LkANDGVYb3rWeJPmEyfjwJI16Dy8slRkaOcSmhCR/7i1ko4ZeKBHlCjddl/6kzngxyUy5+zyhVJxcqJC2Df7ewRGGUwINyZvLrRuCL1e1/Yh3Fxs8OJFGfkJZIEIIWldKk97qg1KqbrlF8Tso5aeLbvDrdgy924dHyJvP5fM4l2OxWCwWi8VisVgs9tHEAZhb+N73vsd3v/vdaz9PTk7yb//tv6W3t/fabQMDA5/Fqf1GBoGBYp6FWgc3iNgzWuDMSoNIKjKOwR2jRXIJg//xuXM0g24zkRcvlsk6Bl/d3s/ZtSbPn6+zZzjL3pEiL1xYZ7HuM1FMUkharLd8JBpb+7PMr1Z5ctwm0E0mvvQI7gu/oJCyOD5bJhAamm5g3HGI/3S6Tag0/u1f/BOiZ36MNn+R9NR2FvUMQS5J3oDNeQsvkriaiZASUyiUZdKbc8gk7Bt+x3wxQ2/GRq5dhvBKNkgyTfLAXVjj4wgh8DaWEZpAT2WQ7eYNCzB2Pk8jXeSp48vkE1dK1TTg1JrLYzsH2DWUu3bfqF5DhT5aMo3mJK7d/igmA7kklzba9Jk5JsaTpFZmWXr3HTShYegahmGQOXAX78oEyWREMWXSWyqQsrpT0GuUUcnkLa9j8uybfO2rf8KDg1NI2S3DZhk375ENv/IknZeeJpi9CFKCEBhDYyTv+zJGb/+1+w0Ag6UcS3WXphuSTRgMZRNkE7+fzV8+ynx9v0987g4Okkr/Nd7RtwjmL4PQsCY3Y+86gNE3QP6TfbWbFMOIuzZHHF2o3XTsoS297BopAd1SXynPRMkIN51BnSkz0pOh5YUcqcIX730E+9kfEawug5SYuoaecCj92V/zepjl+Kluj6F2EHFmsUI66vDY1glOHj2N4bUoZDJUmh1Wqm1s2+LwZC8DWZuL622OLzU4MNnH2bUmCdPA0ASOaTFa7CWa7fbQ0YRAAClTI3//l1mfnUdoGroGnXOn2DXSwtz7Vd54r8rklc+gphdSafskLZ2Nls98zUUi0DSY6k13SxYCi9UOaVvHSdw4x5LAZE+WyZ7ULd/bvgtnaL77C/TeAbR0Bnff3TQbspt5VF7DzuVZTvaS0VNY+OST3dczCyVab72KVShiZnNYH1g01Zdmydz7RZwvf5328z/vBl/bTe6eNFlr5amnS+CkWGz4fH3vCJYuMHWNnpTNeDFJf9b5jcbI5+n76jedr3D78w9NDfIFlO/dfFDTSA2PkO+/+XmHgT3jt36t4Ot/Rvu5nxGtXynVKATGyHbmt97D6XXJ/Zv7efbcGo1MDzkngaxvsNYzxuad27HWF9Cldi14kB4ZoTK+k3C2zXhKo6ACdN9FCA2RSLLWDuhJpaBdx5+9SHZ1gY0oid/poAUho72DzFZaWJaBJUDpgrxj8LVdwyzWXdo+/PJclb+8Y5RdY31XyvldH2vOwil+/uJ77Ng2yT+/b5xWCNWWh/JcwjBkqJBkoNAd+3+vkGO+2mG14dL2JS9fXMdsN5ELyywA7xg6X931Babn3iV535exhkdv+f59K5PjnfkKJ5YaeGG3785d40W29mUwDa27oePsDMnbfN8ttyLsTP7a9/EnYZNX4Wx5hWTi5tdMmDr9pRw9KfsWj/zk3dmEFy9s3PrYVA9D/T0f+vjP01yOxWKxWCwWi8VisdhHEwdgbuGb3/wmjz/++LWfry5orK2tEUURAwMDLC8v/9rsiM+LAiBMwVBJsKdUwJfdJvW2FvLTs+ukDY0VGSGv1OgQSuP4Up135qts7knR9iUTBZOBtMl8tcNitY2tSZqdgKmig6ZC6tU6ubBKwTFYTDiUvvBlkq01Jqw5KmYKd9Muvld16ESKhzb38v+cbfEXX/v7lBorSLdDspIgoRq0F+cwwhBxpaxLKEa4a8soJxer2M0KXrsGiSSRboCC7RMDBIUs5iPfRDVqCF1H5opULAe1vAxAwvcwkCjDQKQy3fr1MgJdxzx4Lz87u46WydLutEkmkrQ7bVDw43dnSItBsmEbzp3EO30U6brouSLO/kP4g6NECBKYzK5VcXSdSNPJOibtuYtYV+rrhwgyew9yMjXCerVbBubwaB+N8jr1K2PIsRK4Ut2ynI6wbIRu4de7izYbzdtfa+POBzC37UW5HYRt42fytEIJS0s33bcoBDsmumO5VW3Rqv4Wg+xTNjg4eNtjHzZfwzC84fZPbe4KE33/PRg79oMQNC2HenTr9/3TsLfHIGtkeGe+StuLKKQsDo7lGUmGLC0tkXBbGOdP0Th1FBlFGAMjPDS2h+dUjkbbZaPlsbR1F8mvl8icfw+rvoHdP0S4ZTdn8yO8dmoF7WoZNaHhWAa1hsZbC3VGSzkWl9bpy1uQdtg8VOBi1UOrtMjoPVyeX8EmolJ1yKcdxvNpNvem8ENF1Q/IDox0G4z7LsOjA4xOZ2i+9As69foN169x+SKle3xc38eLJFnHQNDtO5F1DNp+iGNobIQRQSgRSBJahFKCtZZHxrQRkc+mpMAmYl0amLaNI9ssLdVvek81TUM/dxJ9bBr3/Cka5TIboUGoBA/u3sPazq08s9bkjcjhi/c+SvnN57A6VVASxw9QmSwqnaXduXlOW1GEXy4jSwPYX3qS6PJ5ovIaWeXx7S/u45Kvc3mjm124uWDSmxAYKJTykS2PpdZHGxef6pj/EJ/EfL167MPOX9M0rO37aL/6HB9MbXD23EFFM4l+4zmoYz74GFG5QrPeJLSTiN5+qq2QIbmOk0qS3z3AGzNlKiLNyGSR9FQJNo9jLZ2n/8xJvHwTbcsuqj0jPPPOBaJmCwnsPjhFzzvHCZMOHd2iI3Qo9aNl0uD7uE4K09AJwoiUJjCrK2wfHCFo1GitbyBQbOqYWIQs+Bna7ZB2G84uJRn9QGzBVIper4KVL3DswiLHzs2h2Q6alASNOmPDvSS29rDkXh/7ecBKm/zNW4sQSkI7gT4ygdZqEnTaPLMSMPDgk7i2gfqQ93VXXmM6myNU4OigyTbra+0rb6+B67q02+4tH6tLk1q1Rqca3vL4x1G0TLKOwXKlflMGzIHpXqJmlaX6p1Mm8oNGUyYFW7HwgVJkI4Vuecil27yvn9Zc/rC5GovFYrFYLBaLxWKxT0YcgLkF0zQxzVtnA1z9h69Sv7481efJ1XPVkSQAIvCUyXrTw9IkE8UkSzWXThBRTFrM1zpoQmBdSbQ4vVjh0Fie/SN5Lqy3mCgluW86yWKlhep0eCRZx339JfxaFSuTRew+iNh7gIXMOFoiRU1P8oV+E9eXXNhocW6tybHhLCeXEwSRw8OjKc6eOEcYRchIgpKYusJYW2By/yiljMcbM4tIqRC6jjU8xq7Nw0xkDYIwJEik0dI52pGGUqr7O6ruAo7MFrGTDn2ZkOW6C46DQKAE1JN5pLSxrpRkQ0qMwEf5Hp2OoN4qkXrrGbzL56+9l+H6Ms1f/YjkfV9CbtqGowK+sr2fn55YodzyWDcz7HjwW4zQpjdpcNHVOd4xWa12S65sG8gyXbCR8noZHs9Jkrjni7Su7oa/StNI3v0QrpP8SOMtUIoglYUrzZK7i00f/rjft7H8QR9lvn7wtk/j9w2jiPBKw+/fdVd0XQVszmlsyvcSXgmwEoWoCBJeh87Pv4cd+kSdK6WB5i6iX7jMPfd9jZ+FNlLBS5erbBkYwDwwTOgHOI7JplKC1Y1u/wRfCjQBllD0Z2wuByEXmiF7Nw+wtFZFd9vcs22Qw5v72V8pY67McWEjQJu7QAAIJ0F1aIw3/YjD4wV+cXqFnrQNyoJMlt6Mxdd2DaD7FYRhYBs3lupJb5qmLA2mezOcWKqRNDXCKGI0n6QdRJi6xkg+wfGlOgNpi1LCREkJKKZ6chwuQGftBO23jyE9n+nRIQYP300YpW9qzg3dcWJm87RfeIqNVJHa5mncSNG5eJbF515i/JDPXQcf5JXZOk+XNXYcfJSJHjD8DkYiia4k7vG30W0HaZg3jDlz6y7cKEIpRTudQ9tzJ5qmEUiJkJIpW7A5lwG6Dc7p/udj+zzN8d90vl69/VbHoigimN5OKp3FP/YmUb2Klkxh7zxANDpBeOUxQjdoh91F7KQuP7S8ldJ0Xl/xee2ij8Ii58C9jUtYp99jdGOFeiDZvH03Y1v2cqkl8dodVss1KskkL2z08cgXdpKwTZ4/OU/tzTMEQUikBNtGiuwpmLTPnqRnZJy5SMPWNZRp0RQa2Z37aLXaJPQK+XQCGQZoqRSsLoLrQhiRSjvIuYtsHH2Te778BL80cnihZL3pM5q0bniPNBSF5Yt8OZflhXKD0tAAejKJnnCw9DH2GXW0MEB9oJfLejvAC+SV9x1C0yY5VCB0XepKshIZDMoPD1ZEUYRJhAkQ3fgNpMmI7f0Z1hq3DsBM9aawxfUNIZ8Em4Bv7h3mp0cj5sotpOpmvhwYK7Cz1yaKPrlgz69j4fPY1h7mGwGnVxoIIdjWl2Y4Y2Cq4Nd8W3++5nIsFovFYrFYLBaLxT6aP4oAjOu6LF/JhgBYXV3l8uXLpNNpeno+vNzDHzJDdHsxVNuQ0BSTRQc/gr6MjaFrtL2Qq8VMpIIzyzUsXWOymOSrW4u0vIjzSx53ls9QefUlVLMGShG22+iNp0iEZTZN7OV/feMkjG4iMiwiNM5vtNk/kqPaclFSkjU1EpdPMTlU4ML8BgGCQGmYCoZSDtmVGVLFXv7iC1tZKTdQwEAyoq/PwL8SZGkpk3dm6pxbbRJKxWA+waGxPP2Owk+kSB5+gOILT2EbGutNnyCS2I5FNDCENd/uNktGEizPE6yv0lPIMDAySK3tQ2aQ/JSNPneumz0DgMJ96xWc4XFc06bPlnxn/yCrrZCmH5J3THqSOqaQ9PmCLVWXaaUYyTsUbYEmb2wyLKXEG5kk/fh3CM+fJFpfRS/2YmzejpfviRdcYr+WUgpNhVhwbbVe0zTk7EWiehXeV/JHKUXeVPgn32Rk6wPM1vxuv4bFKv05h2/sGsAmJBQ6L17yOL/eIpIKAaQdg6Gsw2QxRbkdYBdL9O7cxe6RPFPFBNnWGu2f/1eUVKR3Pnj9Nd0OcnUJb3CU8ys1Ht7cw+a+DJFURArSpoajRbh2EvvRb2ItzDDw3nHaEsT0TmadHo7NN9k9WsQNI2xN0ZM0CKTAixSP7xpkodJm90AGW1cIdX2R+OHRJKmXfkxr5jKRrtBTAqu6SOfnf0fq4a/hDo3fNMeklIhkkvk9D/LcpSrzl+tgmGzZdAc7dkUsvPw8I3sPkbYNml7IpZbCne4jceINmu+9SXLLdlS7RbQ0j9E3iMzkUIA1PoUcGL3h9aSUyPctaiuluoGX2K8VIggHRjAHRjACD2lauEK7Vo5r3dd5/UKFxUoHTRNM9aQ4OJojo4W3/Fxd7cCrF7vZhoYmuM9u0vjp94nCkKRlQCQpv/4SqQtnyWy9k9Pnl/jKnjE2+TNo45t55uwafbkEj/ULKtYQXiSxVISYu8DaG+cZOHw/7tEjZHrGSCdMspbAd1LoX/waiSgiO3+Rr985xS8uN5BoBNVuU3vD0Hl4Sy/+G8+RnpwiUrB/JE8jgL6sg1I3jhe9vEb7zZcZzPey79ATPDvToLzRwNYbTPRm2TrdS9p2bgoWB9Gtv2uujs/wtwyMSCmZLjmcXLZZb95YOi7jmOwZzNywOeGTMpxP8PjWIjW/QCAVKVMjpcvfafDlKlMFbMoINucLAN3ML/W7P49YLBaLxWKxWCwWi/1u/FEEYC5cuMC//tf/+trP//k//2cAHnjgAf7ZP/tnn9VpfeZUFLJ/JM/ilYb3QilsDRotlx2DeRpegODGna5+JOlNmRgyIGMovjZscuHpIyhNIJwkqtPCtkwGEhrtl55iuNjLnz+8j3faFkt1F6UZbO7LIGXE5fUmCNicgsYrb7B1YIh9B7ZxdLWDrgk2F22chQs0nn+D2V0PMpBLsGP2LVS7hQoD9OzjMDiOi8kPjq9QfV9T39mNFouVNt/YO0SfFeGNbiLztW+TOHeCQnkDUShhbdnJYqqAmGuhBIhaFVnZYNPkMBU9yQ/PbDC+3EI7d5aekWEe3v0APSdeQl0pEybbLUSzDoVelFI4BIylQKQNlOpm8aCgaECpt7vLWKkIbrN5WCpFO1tAv/N+hBBESuFHEcTBl9jHpGmC8OKZWx4zkPS3y9zTZ9GKuqHWrX1ptvYm0UMXqeu8tdAkaepEVxZdFdBwQy6HbSaLSbb3p9g/lOKuYQdNRkCAWppHXWmyPqDaOLaJ63V/lq06RujjYpEwNNabHm/NbOCH3UmRT1g8tKWX4WQStWkbPZv3cnylxZGZMm4lxDY0HF3wv7t7jMVah9lKB8fQ2NKXJu/ovKRCOq57bcu9AO4YL9DfXqc8exFTgClAlxGi46FkRPjyMyT+5K9oazd+HQohmNXz/Le3T9HudHfry0jx9oVlZvJpHr3rHhrlKgO5Ic6v1tkxmCG9MkPz7dcAaJ87ReKeh6BeI5i9gNM3gLbrIHJwBE/7o/jq/Z0KAMwrfTyufGau+zp/994iQXTlQzeCE0t1ZisdvrVngKS4caHfMAyOXb7eS2kiaxK9/QwyDBCAF0b0pm3Wqi1aF88yumUbxX3jTC6dgPVVNt87RDktGcrr6C8/i7a8Qn86SavVodYJUKaGPjpC/8NfJxV4WJGPOThMZtNWvGwBTUr08XE2CcF3NmlcPH2RNaOH3pRFEZ/O2y9i7z/Mi2shl1+7iBjXWQsFX97WT3FTDqf7LmAYBv7pY4hCDzPTh3j6Vy+jEOQ1DSUlq6sJfqTt45ulEtkP9IQvJAw00d108UG6Jsg5OvDbBQscAp7Y2cfZjQ6nlxsoBdN9Kbb1pkhr4af3lSdDsroCHSD6XScq3kApdVPJvVgsFovFYrFYLBaL/WH6o1gF2rlzJ3/7t3/7WZ/G59JoRueO8QJvz1auLbhIpejPWDwwVeLd2fIN9x/OJ9gzmCGKusGOfKfGZM6iHeiEkUNSy5BwG4jqBsKy0TMZSr05HtIMIrKsduBHx7oLYgKFVq3Q6YQMGormmePkqgvcm8zgK6i9t0KzViE9No4bKd68vMGmkU1Yp98GQLVbaJrG5bJ3Q/DlqlAqXrtc5ontJWQU0s4V0e96EEF3fbYdReQ02DqQ5exSlai8TiGdpG2nefnUMj35FJbXJFSK8to6P/RDvrP1AMn3Xr72GkLTb3rd25W9+qjine+xT4wC9JvH6FWGDsMZkz/tySME6Epe233eCDXema8w2ZNhMOuwVL9eMsgLJW4ouXuigKN8lFQormTcNK/3lEhdeI+v7PgCPz+51A3CXCnzN1xIkk3aPH9m+YbzqXZ8fnx8iT87MExOCxChy94+i03FIfxIYhsaaS1CSpfNOY2thatlukKIQu6fzLJ7KMt8zUUDRvIOJUdDHT8FdIMqeqdNuDx/LZstXJjF2n0AZ2o77vvKMSlN59X5Br4CYZgQhWhKoes6G/UOa+MjFCwbTROMFJLs7Uvi/uSV679MGNI5exLNSaCPboLBUfyxqXh+/44IXefIher14Mv7NNyAcxsd9vdZN2QeATS964viI3pAc2nh2s9KKvKOQT5vEZkOqZXzaO4aQXmV5OatiLeeojc3zcUljUIYIRs16lKSTZiM5LN0/ABVW0OZkuy3/opQCEKl8KW8lolydVE+b+gcChcJmheRa228tsv62DS/WPJYWKshRDfAOpxPMLNe51kV8dUtBYhCQCEbNfyxzRxZCxBOEnwfUGi2A46DGynOrbe5c8C54T0oWN3vxFO36Iu0ZzhPzlSoT2AIOwTs67XY3deLUt2AsJRBvN8gFovFYrFYLBaLxWJ/cP4oAjCx29NkyKGhJJt7UyzXfRSKwYxN3lIoDDb3jLDUktSbFhPFJP0pDVNdD3YoAZaQWJZAXC374hQQ2RxKCKJkhhABMkIDTM24tiCmdVqEq0vM2CZbtu5Ge+FXEPgsnz6NlsqgtO7WXGPbXubnawRhhGv3caXLBiKbR9d1zq5Wb/v7LdVc2iEkr9RS++Dip5Ah903kKNmCdxZ1+of7eHa2ymAhRT5sIXQNhECFEZ7vMxPY7LAdlOei50uEmdwndSlisU9cJCXOtt0ES/O3PG5NbMa3E2jySr+k9x1r+RI/lJxfqfPAdA9n11qcXK7jBRGDOYcvb+tnKmcg31fCR0qJXuq9/nO7xfDpl/nzzXtY0VK0QkXvllHymRR/997iLc8piCTn1locGuwuDMsoIiUiUgZAxNW14luV6dJkSMmEnmsZZyFC6deCUFoYECzM3Fh2SSmiahl57E30O+699pztULDiKizTpC0VQrMQCnQBmoLZjiBX6GVfT4acCWmvQafVuOn3kW4H6XZQgY++547fqpdL7KNrhxqLtc5tj59fa7G/3+H9o15KyWghcS0rVAJC01BXxoRjahgCtPoGUbWM1teLtEycsU20n/8FslrhwMQ6m+76Ms7YQYylGXIJQSJjIVREwul+pyW278SHD+1FE0UR9tAYnXffAK5kbg2PU39rjpSpY2Qy6JkkQihQcHm9RWW8QMHoJgDpfYO4WJTn6yjbQVjd7CAlBMJ2UJrGbLnDoaEkvD8IdeU7MZ8wOTpfo+WHpCydO4Z62dZjoz7Bkl1SSgQSwW0TQ2Oxa1Iq4JHBW/ePMn5t95xYLBaLxWKxWCwW++zEAZgYyIiCDsVid5FSqRBkt3xPnyXYOz7I6urqlTrlH1gmyRcRlo3yvWtZHkqp7iKPaUG+eMPdCzaMlVLMb7SQ5XUAXC/gstHLzoN3IC51yyUpz4V0hvyhezgT2ARhC8PQMa4sFBvFHmSxW/rL1AW3o2sCwe2PQ7ce++F+m23TSZoDeU7Ml9EbdVQYEjlOt39DrYxSsNIK2J1MEcmIxD0P0tGNuERY7HNLKYUcHMUcnYSNlRuO6Zkc5u4DtG/TUNvUuzMnUopj82V60jaP7+xHE4K2H5A2QcmbF5BV3xBaOoNsdoMRst0icexVJnSdxJ47CLMm9Sii1rk5a+2qpbqLNpy8KTvhN/m9r5JSYo5tQrz+IrQaN/W8MIZGCTstgsvnSG7fS8fp9soRQqFMk+ToGO6lS93F8isfJYZt4fT1M96fIy88UCBNCz2VIfRu3VxcyxWRmn7T68c+HZpQaOL2n/2GLvjgYSklm3uSvDtXxQsll0OTXWMTNC5dQAC9absbMLAdAMyJaVozF7FyBeSVXi3MnaNHB2N6O8U9O/GPvIiwxwjN7tYBa3waMb3jI43toNCLvW033uljoGk0AompAaaB2TdAiLpWbk8BLT+iYFwJ3kxvxzhzBtu2CNsu6n2/rF7qJRIaace45bejIQMO9tvs6B0gVIKeQg6/UflM+qXEYleJwGfh+9+95bGBv/zO7/hsYrFYLBaLxWKxWOyjiwMwsWs+rEzW7crmeIk0ibvup/3S0x8IzggSd96Ll8zcEKDQZMiXNhd5VYezcyGSbnNhKQSlLVvQd+ykeeY8StORk1s5ESS4fHEWhGDzUJH08nn0oRHse75EWzchDNk5kOXSeuuW57epJ01Kl/y6tS5PN8glTMTaLHa7TnClDIxyXVQyhTm1jbBepZhLY/ZswRnbRCdT+I1Ki8VinwVPN3Hu/zLJyjrBO0cgDDA2bUEbm6KTSN02gFiwYbiQYL7SzQZYb3rXmmabuuDeiQJK3dws27MTJL/0BO7LTxGudYM+wjCxt+6E7XuJpMQQGgnLoO3fekG3kDA/0bllDI7g7NiL99zPbrhd2A7OwbtpXzzb7Vvje3AlAJPSFJtKaU6FkvyWbXTqdSLfQ9gJfMth+3gfeT24tnU/0HSc3QcJn//5zScgBNaOPbTj4MvvTEKTbO5L89589ZbHdw1mbpmBkjckT+we5PnzG8zXXXbsuYvE6jJFU5E2RXdcptJY23YTBj5C15H166+h5wpIw8S7dA6jt5/0439KpBtEmoE+OEyY78XVtJte91YCTcM6+AVSoxMEp46RSifRS31o2RyhYd10f9vQ4EqOVSdboDQ1xU5R4Y1Ts1dOTsco9SFT3dJ9uwezt+1DIqXERuJogkLSYqkW56jEYrFYLBaLxWKxWCz2ccQBmNhvRUpJMLGFdDZPcOooUXUDLVfA2r4Xr9SPvMUiqqMCHpkucCgaotXukFABmaWzyEvLqFIf/vgdvDJXpVWxUESIvmGGxke5bzpHMholyBZov+9ph9I6m/vSnFtt3vA6GcfkztHctZ4Wv+73UFPb6Zk5z7aREscuXckW0HW0fJEgmcHI5JjaPUxoSrwoijNfYr83PN2iuPsgjf5RlJQEdMf8h47hKOSh6R5+eHyZWuf6HDK0btPvrBHdlBAH3UBuO5PHevRPcBrVbq+VZAo/nSO6EglN6ordQ1lev1y+6fGagG39mU90t73mJODAPaRTGTovP43stDEGRzDGJunMXkIFAcI0wbq+qC1lxJ1jOearHRoKEj09BLLbI2vPQIZtRRPk+8oxKkU4Okli/110jr51pRcHCMsiced9eKV+4io5vztSSvYPZZjZaFP9QLbVeCnFWNbsZnve4nF9tuBPdvVQ8wEB/f/grxEXThLMXUIYJtaOvRipDI1nfoIKArR0FgRomRyi2Hftey9cWyFoN9G/8i2CdA7vY2R0+ZoOA2MYw5P0K51Ue4lG5+bvtJ60TdHR4EpWmlKKdrGXA/l+1p08s+sNMC0iw0AoODxZoj8h4tpfsdgfOAG0o1tnA1q6wIg/BGKxWCwWi8VisU9dHICJ/dYioF3sQ7/vkW4Tb03/tTu9QxnRk9RJvPoccH0NSG2sskkdYfD+J7joG3R8yVDOoS+lY6qANjZKGNTDbmmktKnhiIiHpvJs6UtzbLFOECk296bYVEyQ0sKPHCfxdYPioXu5d3GFZrrEXKUFlkOkG5i6xsPb+sgaEdEtmjrHYh9G6Ab1AAKpSBgaKS362OW1fhthFP1GmSVZPeTbewZYagasNjzSjsFozrkSfPnw8/eFhp99XwnC990/iiL2DKRYb/lcWLseODU0wf2be+m11S2DO78NX2hoY5tgYQYdRdhs4p06du24NbUNP5m54TwzWsi39gxwsexybq2JqQt2D2UZThvo8uYSaoHQ0HffSWpyC9QrIDTIF/ES6VsGo2OfrqQI+Oaefi5VXM6sdK/fjoEso1kD8xbBl6uUUmgqpHDlLyQ/mULfdxh9zyGUELhXrqXzxF8gKhsYAqz5y0RheFOPH2NoDC+d/a3mu6ZpNCMNN5J8adsgvzy1RMu9HoTJJywe3d6L/oHNBkopdBHxyK5BVjv9zFddLF1jrOBQsBTIuKRYLPaHTgI/OLF6y2NP7uzD0H+35xOLxWKxWCwWi/0xigMwsU9MJCURoCmF47uITgsMgzCV44P7dZVShIOjJA7cTee9N673RdANElNbsTIOe4RACHFlp75ECEE5NHj+zDpL1Q6KbpbL4cki0znBeAqmtncXfKWUSBn8xkkqwjTRLZ1H94+x4UrWmz62qdGftsjov37RORb7oA4mL52vcHG9RSQVjqmzdzjH3sHktZ5Gn1dKKWwCJtKwKZvo9ndSwScSHDFVwCPTeTZG86w2PUxNYyBzdZ59OqW63GQGZ+cBOi/8AulebdAusMYmMfbdRecD81spRVIE7Ok12TfQgylDRK2KqkXIVAbfsG4KaEVK0UllIZV9/xN9Kr9P7NdLELCzaLC7t9TtaRRFt8x8+XWiKOoGV953LV3Thr4hhBAkvvontJ/9GVzpfQRgDgyTvP/LtIKPP2GkZnB8zePN2RXafkTC1Ng33kPWMXC9gHzCpDepY3P7zQa6Chl0YHio27tGyvCGzBchBGYUojfrgEKms/j6J1sGMBaLxWKxWCwWi8VisT9WcQAm9okylUQ/cwL3vTeQnTYIgTk4SvLw/XTS+RsWdAKhoe86SGpiGqobgIBCCT+VJVIKlLrh/k1p8P2ji3T864uzDTfgV6dWMHYOsCkjblvP/jely4A+C/pLxpVz+GQWnWN/XEJh8pMTa6w2rjdmd4OI1y+XiZTi8HDyln0oPo8+jYwdIUN6TOgtXp9nn2aZLqUU3uAozpN/iaisg+8jsjmCXJHOLduRX3+ctTyP+/rzhBtrAOjZPM6d9+IPT3Q/r2KfW0opok/ou+F2z98p9OE8/h1EdQPldtDSGaJ8D0ZPPywtfazn1TSN4+seL5xfu3ZbJ5C8en6VfNLk23sGsZQPSn6kaXOrOaxpGvbyPN4bL+JW1gHQc0WcQ/fiDY7GVfNisVgsFovFYrFYLBb7LX20TrCx2EegaRr6xdO0X3uuG3wBUIpgcZb2L3+Ic23H+XVXd4t3hifpDE/QSWZuuZipaRoXyp0bgi/v98blCiGffB2FeAdw7Lex2oluCL6833vzNRph/BEMv9t5JqXEtRw6/SN0RjfRzpUIPiT4ApCol2n96gfXgi8AUb1K65mfYq99vMX12B8WpRSuadPpHcIdnaJd6Ov2b/kttKXOmzOVWx6rtgMW6j5CfPjY/XWcyhqtp35EeCX4AhDVyrSe/glO+dZli2KxWCwWi8VisVgsFot9dHEGTOwTY3kd3PeO3PKYbNZRy3OIiS0fa7FV0zRmy+3bHi+3PFwpSP12a1Gx2CdGCMFa8+Y+IVcFkaTpR6Ts3+FJxX5juq4TnjmOCm5ufI6SeEePYD78dYI4Vhv7hHVCSdu/febOYt1lOp8i+phZdLqmEZx8D6JbvIaM8I+9jfHgYx/ruWOx2OeDoWs8Mmje8lhKBaj4n4KxWCwWi8VisdinLv6rO3ZbuqZh+i5RZQNd0wh/zSKPcDvIVvO2x6PlBbRN2z7WYpFSirR9++Fqmzp6HHyJfc4kzQ/fAW/qGjc0Y/g9pGkaZuAhoojQThD+gWWNaVFIuLxw2+PRxhqG74EZR9JiH52uCQyvmx0X2gmiW5QH0zWBJkDeZkqlLP23yh7Tw4Bg9fYZXOH6Knbgfeznj8VinwNBwML3v3vLQ71/9ZcoI/6nYCwWi8VisVgs9mmL/+qO3UQIQaJVJzjxDu7MBUQigSj1kdx1kE4mf/sFH8MAXYfbBFhEKv2xF4uiKGJHf4aTS/VbHt/anyGly9u99EcmfY9Eo4py2+AkCTL5P7gF5djvhlKKwYyJqQuC6OYxNJB1yFv8XsdfEr6LPHsC79wJVBBg9A6Q3HsnbqkfqVS3v0S7Cc06wjCIsvnfu+beStMRThLYuOVxYdko/f/P3n/FyJWkid33P+KYtJVZ3huy6D3bm2nvZ9pMz86s1UpYLCDo+7SAIF0JECBdCNiLvRAgXawgCLp4sdArQPPN7vienrbTju3Zzab3rljeV9pjIr6LLMvKLLLIIquKjB8wmGaezJNxso6NJ+J5Vj79oXFnEkIQy4zjHzlI8fIFAJyOjUR230c+mVpwbKQd6KpLcn548cAGKWBDTQylrl3bxpISNzMBuQzCiRCkqvGEREsLGY0Slr+sIs2+bRiGYRiGYRiGYRg3zQRgjEWiuQy5N/9pdjaLFlA8fRzv0nkSP/gJuWS67Of8eBVu5ya886cWLxQSu7Mb7yYKeTfE4OHuOj4/N7KgMHBTKsq97VWEYZkUQVc3Qwg8bEbyIcVQkYrY1LiACogVc2R++x6Z0ydAKxASt3MjsYefJO/Gbrjdxt2rylY8t72Jt48PEMwbxp6I2DyztR55HZ2na1Uk8Cj+4Q2CgbkR9H7PBfz+HiLP/pCJVBOJMwcpHjmIHRTQWmOla4k99iyF+uayBcHXokApYjv34fddLrvc3bEX33ZhnWyPsXIC6TBaUOT9kIRrUxvhmsd0LDNB7nf/NFcnDSieOorfc4H4939MLl41+7oOAx7vrmEs5zGem0tnKAU8tbWRaldfM4AbCX30wS/InjwCQaltdn0T8ceeo5Cuxd25H3/wzbKfdXfuw5PmNtEwDMMwDMMwDMMwboZ5sjYWkFKizhwvm0pMFwv4x77FevjpsulSAq2J3/89wvERwrF5o8WFJP7IUxRTtTfVNqFC7m2KsqGmnQujOQqBorM6TlNC4ujrC74MFiVvnehnIl96vwA2NSZ5aWOK4odv4UyMloIvAFrhXTyLDkOcp39wzULdhnE1rRTdKcmf3dvGxfECU4WApqoIbSmXmAhYRxNBFpGDvQuCLwAayWjGo/DxJ6Q3beboO29jCVGa7ROVpeLeb/+K+Ct/Qj6RWqWWL1/Y3EF05z4Kxw4teN3t2oTo3rZugknGyhBCMB5avHl0kJHMXIqu9poYz22tJ07565GUkuDk4QXBlxkqlyU4fRR5z6ML9qek8PnxniZ6Mz59kwUSjk1XTXQ6+LL0lE9LSvS3X1M4+u2C14PhAXJv/4roK3+CattAZOsuiqeOLniP270N3bVpXc1WMwzDMAzDMAzDMIy1yARgjAVsFeJfPFNxud9zkUixQOi4ZZfnonGiL/0YMdRLONiHiMSw2rooVlVzk9nBSlRIrQ31zdHSP5WaC5hcQ1bZ/OZIL3l/riUaODOYYdTJkO7vxYlFsWobkJEoqpgnHB3B77lIcmIUP123Eltg3GW0UqQsxd56BykjKKXQ2l/XwRfLsggunpt7QUpQmoyv6J8s0NLmwqHPAQi1pncij2sniFugvSLq0lnkrvvWTeDCkxLn3kdJbtpOcPk8qBC7vRvd0ESAQMK62Rbj5nnY/PbowIJZKQA9Y3nePT3CK9tqEWVmwti+h3/pfMX1+hfO4ux5AE8uTPsVwWdjEjanE2itS2nH5u1utm0jlEIJsaDGmpubInfycNnvUtkpGOjF6+jGefAJklt3EvRcBK2x27oIauopSssMOzBuKzsMEL5XYek6vmgawNJ/X+24BNbyH0tvxToNwzAMwzAMY6WZu1JjAS1EqTO1AiFlKf9JpeVCMGHHGa7eSD7ZRSpqU+eCpVc21dJyOzuFEFyZ8BYEX+bLjI6RStfhtLURnD6GunwOq6aO6PZdFPp70bkMmACMcRO01gs6R9c9y0J3bGKsYQNjPri2xJoaxz38DbFEgsK5idm3amAk65FIR9BaEQ70IffIdRW08IXEr65H1jbi+h6q9xL+W59CEOBs3ILcsJlCNGFmDNwFhvLhouDLjJ7RHONeLTXl7q6udX21rNJ7Krj6/OFohT3Ui3/8MGEui93aQWTTdgqpmtKxVcijvUqd2aBGB5Fdm/EV+DWNyLpmADyl0NJmzIOxnM9gOE5C2iREYPZv45YSvkfxrV+UXRZ59tXb2xhjxS35933hdbiBYMmtWKdhGIZhGIZhrDRzV2osEAqJu2UXwcgfyi53urcSuFHKVbufSfH1u2N9ZIpzAZfmVJSXdjRUTMtyOwghGK3QYQZgJaqIJJNkfvv/I5jpsLpyieLx70g88zIilrxNLTWMtS8MQ4JdD/L25yc4980VNKUgi6clz933JLbrkYskoTiXyrAYKBSltH8yVU24TjtyHb9I8NHbeJfnZjL4Q/3IY4eIv/QjcuZcccebKlQeUKCBnK/KBmAC28HdtJ38wU/LftbZvAPfsq+rnpCNRnz3Bdnvvp5b//AA4sRhEi/8kHxtIzju9Oy08uuTyfSCgMpMQNSXDh+eG+fUwBQaiMfjhF6Bp7c1sikl0esocGoYhmEYhmEYhmEYq63yUEzjrqSUgg2bseubFi2z0jVY23ZXHMWf0zZvHB1YEHwB6J8s8P6ZkVUdhaa1pibuVFweiUUpfPHh4o6qMCT/5cfISOQWt9Aw1g9pWXw+LriQUQuSwhQ9nzeP9jHSsR2xaceCz7i2LF1whMTetG1dzgYSQiD7ehYEX2aozCT+d19hLTHDwbgzJCOVr2UCiDnl9wGlFHLzDqyaxbMp7boG5DLqCbkToxTmBV9maK9I4bMPcFSIn0zjdmws307bQbS0L5rRYlkWh/qynJwOvswoBoq3jw0w6pn92zDuFALIhaLs/4IbfEQMkBXXebuHXWgqb5+Htei1bCC4PDiGr815zjAMwzAMw1hZZgaMsUjBiRB97lXcy+fxTx/DirjE925EdHWTd2MVPzeY9cl65UcGXxrJMVaskJblNtBa05aKEHUsCmXSkDn5KZz6RnR/DwRz2yAcB6u6FjU1AWZku2EAkAkkR/onobEFO5lCjY+gw5Cqmiom3SSfD/ps2byP5NgImQvnEEB9wkVLSfyRJymu03R+lmXhnzpScbl38Syxex4mdKO3sVXG7dYQt0jHHCbyi2d1tlbHqHFZUKNlvnwkRvSF1+HSWfwzxwFwtuyCjo3kr3O/kVKWahFVEAwPEMlO4iWriT34BCqbIRgemF0uXJf4Ey9SSKS4uhhVNpQc7p24epVAqZ7T6eEsD7fG1lX6QMMwylPAL48Oll32w12NODdwz+6FuuI6/9mWxPJXeBOUrrx9r+xs4jfHrl4mqKpK8kxnHNsq+zHDMAzDMAzDuCEmAGOUVXAiiE07sLfsJFVXx+DI6JIj1oUQTBYqpxjTlEbQruYeV2WFvLyrmd8fn5ulI4Cu+gR1MY9iJEp04xaYmgTPA9eFSIzAstDrcLS+YdwqntJ4gQIhIVGFSKaQWoOU+Fmf0VyRo56gYfdTbN7zAI3eONVVMUR9E8VEqlLf9NqnNTpYop6VChd1aBt3nggBL+9q5o1jAwtqwTSnojy3tR6hlk63WXCjiC27sbfuAaCo9fJrqyy1H8LsbM58NE7khdeJjA6ixkYRsRiivplCPFn2OwMNea/y9W4k5yNlwgRgjFtCA74qXwfJzEO+vRLax857TPZcwr6qlpRyXKYoP6tcU7mOlWEYhmEYhmHcre6aAMybb77Jr3/9a8bHx+nq6uKv//qv2bx582o3a03TWhOoUqqSa3W2aK2pjlVO8SXFTFqW1eu0UUrRHBX86T0tjORDvEBRFbGpjYA9pSkIiYhECEMF8XkftGxI16xauw1jrYlYLJhNprUupRZRioa4zX0d1dTHLZSCungzcVtRVGrdF/AOlSLSvRV/oLfscqelnSAaN0GYO5zWmho74I/3NjJSUOR9RdK1qI1KrGsEX+avw7/B/UQphdXaCYcXpyADsKrSqETV7L+Llg0NrYjGtrljsMJ3uwISEZtssXyApykZMcEX45ZRGk4OZcsuu+82t+VuJ3yP4tu/xK1KUpzKwLwEYvbzr/PL02NlP/fKzsUpjA3DMAzDMAzjbndXJLk9cOAA//AP/8BPfvIT/u7v/o6uri7+9m//lomJ8mk2jBvTmLBJVwjCbGqsotpd/U5JrTXHvveRAAEAAElEQVQR7dMaVWxIQp0TIFRAMZkiunt/2c/E9tyLl0jd3oYaxhqWkIq9bemyyyKWYHNthPaYpjOhSQgfFYbrPvgCpfOH6OzGSi0OyArbwd33AMEdsJ3GtWmtcXRAc0SxMQkNbnjdwZeVoOoacdq7Fi8Qguj9j+I7i+cLXM8xGJUh93aUH3DgWJJNdSb9mGEYhmEYhmEYhmEsx10xA+Y3v/kNzz77LE8//TQA//Jf/ksOHjzI+++/z+uvv766jbuDRAl4ZVcTvz8xxHCmCJRmvmyoT/LExhp06F1jDasn1GDvfZBYUyvFLz5G5bPIeBWRvfcRdnYTmk5Vw5illGJfS4K8H3Ksb5JQlY6PdMzhuW2NpKyQO7WPNu/GiL34Q8Ij3+BdOI0OQ5zmNtz9D5KvrjezX4zbomjZRB97AfvUYYqnjqK9InZNPe6+B/Ga2244SKKUYmd9hEyxhsNXxgmmj+2qqMOz2xqotkOzixvXZIcBwi9/z6cdl8C6Kx4/1jzbkrzQUn7glIUmr2AyWyBQwLzUYkv99arwllxnpeSJGsiF5dOXuZbArjCDfqm0dTe6l0kpbqgthmEYhmEYhlHJHf8EFAQB586dWxBokVKyZ88eTp06VfYzvu/j+3MjWYUQxGKx2f+e//93uuVub7Ud8pM9jYwWFQVfk3AltREByoc1/pv50iZ278Pkm9oRfhHlRPAsuzTqfbUbdwvcKfvy9Ryv8/97vW/vjbgV2+7qgCc3VLGvNcVkMcSRgrqYxKU022Wt/M63YtsLsSTyoSeJ7n8QoRRBNE5+uld6rWw3rM19/nqP1/n/XkvtX45b3f6iG0HufZDo9r2IMCSMRChMT2y+ma+0CfleR4LdzUkmiyGpZIKoLhIhQOv19/dY7/sRrL9tEL5H8a1flF0WeeH1UmpXY/X5Pld+8bOyi5r/4k85OZTFdV28q2rA7FtilcL3llxnJUrDL48Oll32w12N2Fblz1VKW7dUO5fih5rfHFt+WwzDMAzDMAyjkjv+CWhychKlFNXV1Qter66upre3fB7/n//85/zsZ3MPDxs3buTv/u7vaGhomH2tubn5lrR3rVru9rbfonbcDrVt67n1y7fe9+XrOV7nW+/bezNuxbavl1/T/N3XhuUer7C22n8j1mv7F7a6qsK71o/1+neYb71sw1KzEtzb2xRjDRHc2GyVhPaxC5Vm0d/YlLxKM3Vs26eGQsVZPAnto+/8x2fDMAzDMAxjhZk7yDJ+9KMf8corr8z+e2bE4dDQEGEY0tzcTH9//x1R0+BahBB3zfbeTdsK62t7W1paKi5b6ngNgmDB6+tle1ea2Xaz7bdz21fieJ1Ztp7/duu9/WC2Ya24Vduw1LF6M5aalbB/ff4JjBWgubHZKsL3KL79i7LLIs++ekNtqTRTx3Vd6n/yo4qzeBr+8i/Qtnl8NgzDMAzDMJbnjr+DTKVSSCkZHx9f8Pr4+PiiWTEzHMfBccqPfJp58NVar9sH+RtxN23v3bStsP6393qO16tfW8/bezPMtpttX23LPV5nXl8r7b8R6739YLZhrbgTtsEwDMMwDMMwDONuc8cHYGzbpru7myNHjvDggw8CpSKzR44c4aWXXlrl1hmGYRiGYRjG3cG2JEE+V3aZdYPppIzby7ZkxRRd9i34Gy6Vuiyy4t+2tKX2X9ux0VfN5JwhbJvAr7DMdQlNXSTDMAzDMIw72l1xt/fKK6/w93//93R3d7N582beeOMNisUiTz311Go3zTAMwzAMwzDuCtr3+fb//N+yy+5boki7sYb4fsUUXc234G+oqJy67L4V/7alXWv/Lb7767LLIs++WvFz+//yLyB2VzySG4ZhGIZh3LXuiru9Rx99lMnJSX76058yPj7Ohg0b+A//4T9UTEFWiT0v5699l+X/vZu2927aVrhzt7fSdt2p23s9zLbfndbDti/VxvXQ/qWs9/aD2Ya1YrW3oVL6wKvbpfJz9Z3Kud3LVnq9M6+tpW28lcuW+g1W8vuktNbFOistE0t8n7jG5yodW4ZhGIZhGMadQWiTTNowDMMwDMMwDMMwDMMwDMMwDGNFydVuwHqTz+f59//+35PP51e7KbfF3bS9d9O2gtneu4nZdrPt65Fp/+oz27A2rNVtWKvtulXM9t7Z7rbtNQzDMAzDMG4fE4BZJq0158+f526ZOHQ3be/dtK1gtvduYrbdbPt6ZNq/+sw2rA1rdRvWartuFbO9d7a7bXsNwzAMwzCM28cEYAzDMAzDMAzDMAzDMAzDMAzDMFaYCcAYhmEYhmEYhmEYhmEYhmEYhmGsMBOAWSbHcfjJT36C4zir3ZTb4m7a3rtpW8Fs793EbLvZ9vXItH/1mW1YG9bqNqzVdt0qZnvvbHfb9hqGYRiGYRi3j9Am0a1hGIZhGIZhGIZhGIZhGIZhGMaKMjNgDMMwDMMwDMMwDMMwDMMwDMMwVpgJwBiGYRiGYRiGYRiGYRiGYRiGYawwE4AxDMMwDMMwDMMwDMMwDMMwDMNYYSYAYxiGYRiGYRiGYRiGYRiGYRiGscJMAMYwDMMwDMMwDMMwDMMwDMMwDGOFmQCMYRiGYRiGYRiGYRiGYRiGYRjGCrNXuwHrydDQEEEQ0NLSQl9fH1rr1W7SLSeEuGu2927aVlhf29va2rrszwwNDeH7/uy/19P2rjSz7Wbbb+e2r8TxCuv/b7fe2w9mG9aKW7UNN3us3gm/7XKY7b2zrfXtXe7x2tvbe4tasvLW+m9/K5htvrO3+Uaur4ZhGMadzcyAMQzDMAzDMAzDMAzDMAzDMAzDWGEmAGMYhmEYhmEYhmEYhmEYhmEYhrHCTADGMAzDMAzDMAzDMAzDMAzDMAxjhZkAjGEYhmEYhmEYhmEYhmEYhmEYxgozARhjzZFSYlnWajfDMIxbYOb4FkKsdlMM46aZ65Vh3B2EEOZYNwzDMAzDMAzjhtir3QDDmGED7sQIwcVzaK+A29KBbmqlYLur3TTDMG6SJSAyMUpw6Rw6n8NpboPmNgpOdLWbZhjLZms9fb06i/Y93LZOVEMrRdtZ7aYZhrGChBBEijnov0I40EuuroFYQwvFqmrC1W6cYRiGYRiGYRjrggnAGGuCjcY6/i2Zrz4FNADF499h1dQRe+5V8tHE6jbQMIwbZglwTh8l89mHoFXpxROHsaqqib/wGrl41eo20DCWwdEKeeRrMt9+Mfta8fh32PVNxJ55hXzEBBUN404Ry0yQe+uXqMwkAFY8Tq5QIP7o09C9g1DrVW6hYRiGYRiGYRhrnUlBZqwJ7tgQ+a8OMBN8mRGOjRB8+wWWNLuqYaxXkckxcvODL9PCqXG8Lz/GNunIjHXEHhkkPy/4MiMYHiA8+jXSXK8M447gAMXP/jAbfJmlFLkD7xOZGl+NZhmGYRiGYRiGsc6YXgJj1VmWRXD2VMXl3vnTuPnMbWyRYRgrRUpJeOncouDLDK/nAk52suwyw1hrbNsmOHW04vLimRO4hdxtbJFhGLeKnZnA7+spv1Apwt6Lpp6ZYRiGYRiGYRjXZAIwxqoTQqDy2YrLdeBDaDJtG8Z6VDq+l+iQVgrC4PY1yDBughAClas8IED7HkKZ65Vh3BGCAJZIMabzOROAMQzDMAzDMAzjmkwA5i4iLJsiNr6wsSxrtZszKwxD7LbOisutVA0qGruNLTKM9UtKiS8citgIa/XLfCmlsJraKi6X8QQ6Gr+NLTKMGxeGIXbHhorL7Zo6woi5XgkhUNKhgI22bNNJbaxLOp5ALnH/aTW2olT52Z2rTVg2BW0TCMekRTQMwzAMwzCMVbb6vXPGLSeEYMS3+Or8OFfG89hSsr0pye7mJDH81W4eWmtE2wZkIonKLh5ZHL33IQqWs+QoRMMwoIjD0f4cx/om8ZWiKRXlgY4ammKrd+xoraG5DStVQzg5tmh5dP9DeJFYaSaMYaxxSilk52bk4YNlZnYJIvc8TEFad/X1KpQ2Z8d8vukZJFsMSMcc7u+sobPKRigz281YP/xYguje+8l98dGiZVZNHbqheRVatTQhJP0FwZeXxxiaLODakt2tKXY0xHH16t/zG4ZhGIZhGMbdyAyJugsMeRb/+G0vZwYz5L2QqYLPlxfH+PXRQYo4q908AArROPEXfoTTvgFEabe0qlIknngBv7271IlrGEZFnnB448QQn50fYbLgk/dCLgxn+adDV7hSOcPfbVFwIsReeA23sxumR+LKRJL4o88Qdm9bsyOIDaOcQjxJ/MXXcVraYXpmh5WqJvHUS3gtnXf39UpafNGT5Z0TA4xkihT8kIHJAr890sfhoQLCjMQ31pEwDAm37iL+8JPIeKL0orRwN24h9tyrFGx3dRt4FSEEl7Kanx+6wqWRLHk/ZCLv88nZEd46NUIg1sY9v2EYhmEYhmHcbcwMmDucsGw+OzOGHy7u4BzOFLk4UWRbtbX8DiPLZqwIOV8RtQU1EYG8iZGtWmtyyRTOM6+QyEyAUqhYnKIbLds5O5POZKbdQghsrZC+h7YdfHkD22QY61hfxqdvorDo9VBpDpwfYWd7/Sq0ak4ulsR+6gckspMQhuhoDD8aLx3fN3isSinJKovxQqnmRnXUIiHDsucMN/BBhYSRGIEJ+BhlCGkz4cOUp3AsQW1U4uhg0bVEa02uqgbnuR+W9melUPEEBdu9LdcdKSV24CPCgNCNEsKaud6N+4JDPYtnugF8cWGUTbVtJIQ5/oz1wxcW4ba9RDdsQRbyJKurGdOSPJLJ6zhfVCKEWPHjNhAWn5wbAqWQWqOlxcw3XBrNMZCrps1kSDQMwzAMwzCM284EYO5w2UDQO1a5APbJwQw762oJgusPnhRweP/UGBeGM7MPds2pKM9va6BKLk5vIITAUSHS91C2g2/ZFR86fa3xE6m5F67qKFXSYqwo6J0sIIWgNR2h3la4vecpfvc1/tQEMpYguudewvZuPDPa1rgLWJbF2eGpissHJguM5rxVn/IYaE0QryIUNsMFTf9AkagtaUlFSFkh6NLxLqXE8QoIpQiiMQJV5nwhLU6MBXx8doCCXwrARB2LR7vr2F7rwHQh9KhXIPfJe3iHvkIHPnZTK/G991OoaTAzb4xZvnA4cGGSE/2ThNPXp9qEy/PbG2lwFXYYLLqG+bDwenUbgiDRwEefO4F/7iS5ti0MxOqZiqWoqq6iKeEQE9ffAXwrjOR8yh2uAF6gGC+EJEwHsLHGOIDlFdC2hW9HFl0blFIUnAjCjVLd1EK+f5iPL0xwssz5ot4JKx6DQggyyqZvyiNb9KlPRmiMWzgrlBosXwgZv9KLGh8FpRCxGHZtA8F0XaoLozk6OxOEYbgi32cYhmEYhmEYxvUxAZg7nBAzs0XKPwxayy2MK23ePz3G+eGFtVr6Jwv89tgAP97TiKPngjk2msjIAN6Jw+T7epBuhMjue1BdW/CktayvDoTDR+cnON4/OdccCQ/W2Oy7dBQx2AeAyucIPvg90b33Ye97mEqhJSktJgLJRCHAloLa2PLaYxhribXEoSzFbKakVVcQDm+dHKZnLD/7mi0FT21tZFuNTTQ/RXjiO4pnT6KDAKeplfj+B8lX1y/o1OrLwbsnBhac2Qp+yPsnB0nta6U1CpHAp/j+G+ipccJcKRDtXTiD13OB5Auvk6trmvuwtBnzIOuFuLZc9mjm28WyLIQQhGHlTj5jeaRl8dXlDEf7Jha8Ppr1+M3hXv5iUwI+foMwM4mMxZd9DbOs0vuUUtcd9FPSZrSoyfuKuCOpjQoifpHgk3fw+3sY2fMEvzkxTDY3DALs1i6iNdW8srt5yQ7gW01e40Qj18h5yDAAXMvCHRuicPBT8oP9SDeCu30PYvOOiunFlNZ80TPFsTLni18f7uNP97cSE+UHI13Kwu+PX8EL5s4DtQmXV3Y1kbJCcspiNB+itCYdtUg7GnWdwZKI8pm60oca6p+9LurMFCqbwW7rIowlkGLtzJYzDMMwDMMwjLuJCcDc4RKWZkN9gtMD5UfH72ypWtbslzEPLo5kyi4bzXoM5RWt0dK/Q8vlypVBjp0cABrYsqWD1vwg4cfvER0dxr7vewRcX2+MEIIzo8UFwRcA4ft8+sVxGvZupq3/Esx7UC0c+Ybkph0EyfSi9YXS4fMrGQ71jM+Ork9GbF7RLvVy5dNClCOEQEmLSQ+UhipH4LD2OnyNtS8MQ7Y0JjnaN1l2eXttgrqEy+i8yXDSspn0Bb5SRC1JwiqfumslScviy4uTC4IvAIHSvHdygOb9LfD2rwjHRmaXeZfO4fdeJvHSj8jVNAClVFHfXBkrG1bWwMHL47Rtr0X2XiAY6MWNxxe+KQgofn0A54XX8REUhcMHZ8c4N5SZHb1fm3B5cUcTtfYaOSalxVARTl3JMlkM6KyOsbEmSkKukfatY5lALAq+ACCgMDjEeTHKlslxtO8RFgvkPn6X6NhI6Rq21E8vLc4NZ/nmUobxQkBrKsqm2hgpu3SsCSEIhcWUX5o8k3QFjg6YUjZvHxumbyI/0wzaa2P8uKZYOh627efN06Nkc9MpBzWEQ/3kY3F+f2yQP97XhMPqFNuujzvYUpSdtRZzLWqiFmBmnhmrK5Q2gznF6Qv95Pp72VS9mfaqBiInD5L/8mPcgV7cx17AsxYHWYemihzrLZ0vpIDmdIyaRBSlS0HWwVzAhuTi+8iMshcFX6B07/yHs6Pc31nDm0d7yXml+1jHEtzXWcv+5th1pfiVwwPEL5+gub6WvuF55zOtCYf6kZ0b2VSXQCkz+8UwDMMwDMMwbjcTgLnDqTDgoc5qesfyZL2FD3BddQnakg4sI/VBzlcV04sATBYCWqMSTzi8d3SAswe/nU0jduoydDRW8+KO++D4QZJbdxFU1VzX9wbC5tsrI4sXeB4oxaGBLJ0NLYT9PXPLlEKNDsNVARgpJUeHC3x9aWGe+kwx4I2j/by6vZa0dYs7oqVksCD48OwwA5MFNFAdd/ledx1dVdZs+iTDuF6Nccm25hQnrwpSRh2L722oJWLPdSTlcTlwdoyzQxkCpYk6Fvva0uxriWPfRC2na8kGkpP95YPBSsPpS0PcHyw+H+nAp/jNZzjPvoqvwdcwnq183hrL+Shp4Z87XfE9/kAfiXyWIFnNgfMTnBlcGFieGc38J/tbiK5SZ/YsaXFosMiBs8OzQafzQxm+dC1+uLeVGmuV27fO5QO9qFMUwAp8gpFBhqvq2RaNEfre7LLCse9IbtlZ8RomhOTEiM9nPZfJZkuRz/NDGb66KHltTwtNUUlfQfDRmWEGp0qBlJq4y/c2N3C8f3w2+AKloOJELqCn/xR1QjIar2diqmfB92mviPB9xvOSkXxIc/Rmf5Ubk7JDHu2u56MzQwsCpFLAE5sbiMvw6syihnFbKWHzycUpjvWMoS6dRfseZ3ugNp3gtT2PEvv2I7xL50iMDUF986LP57wQL1TYUrCzrYZveiZ478woodKkow6O3UxnKo4I587LQgiuTBTLnmcAzgznSMXc2eALgB9qPjs/QiraxJa0XDLQblkWwaVzyCsXeHzfBn4xmcWbd8+viwX2NCWpi4pKE+INwzAMwzAMw7iFVrskgHEbpK2AH+9v4aGNtTRURWlOx3h+exMvbKlddt7pqL30jJWkayOE4NxokYsDY4tquFweHOeUSCGjUdTI0HV/b6A0eb9MUGK6OdliqRjxosVl0qEUtMXBy+MVv+fSeB5luXjCRlq3JkY5Flj88nAf/dPBF4DxnMfvjvbRmzNPx8by2SrgyY0pXtrZTGt1jPpkhPs6a/jj/a3UuXPHTiAd3jwxyMmBqdlR6gU/5PMLo3x1JYssM+L3ZkgpCYSNJ2y0kHhh+Q4oKSXjI2MIp3zaF7+/F7tQ6sh2JCQilduZjNjYAoS1xCVOCEAw4cOpCjMEM8WA/szqBzfGPLEg+DIj54V8cGYYLc1YipvhWgK7XG4szyPqWLS1NFJo34xo7YKZtGN6OsBfwUQo+eD04KKyMMVA8d6pYUZ8m19/1zcbfAEYy3n846FeYq6zKFWXBgqBohhCUVW4Dk+/XKxwjN0OWil2N7i8vq+N7oYk9ckI25tT/GR/G5vTlqm7ZKy63qziSO8EIvDQ84KqoxNZvp4QyNp6AMIrl5Bl6ghGHIktBZubUrxzcogTA1OE09fSiYLPR2eHOTZUWPBZIQRTxfKDG4QQjOR85sdmbCnoqEmwuTHFlYkiobj2OV4ICx34NBw/wB/vauCeTU3U16Zob67l5b0dPNEaw9K3boCFYRiGYRiGYRiVmV6bu4DWmqTweaA5yv0tcQQCrQL0DRT9rI0KWtKxBaNzZyQjNg1xCyU0h/vGKiYXO9I3xY6mDlhGR2/EKo0OzntXfa8bQVgWjVUR5NTEwsQmlg11DYvW5SvIFMrk5wY2NyTomfQ40j+A54e0paPc01G9ojn1LcviRF+GYpmRkErDFxfHeH1nHYR35oOyJQVuZhIyUwjbJkzX4NmuSaO0AmwVsCkl2FxTh9JgoQlDH63njsbhfEjfRKHs5w9fmWB3c5KkWKkZWJLJ3gEmxqfw3RjZZD33bqjneO8YeW/hd2g0LekI4aVs2TUJKdDTZxUdBtzbUc2V8cXnIYB7O6pRvofbvY3imRNl3+O0dRIkkhTyarbzrJyxnEd3KrpqHcdSSi6M5SsOWu4bzzPpQ9qUsLphaQc2N1Zx4qrZY90ttfi1CT7uy+H3h9SlWrn/nm00X/gWPTKIqFADRghB36RHoDTlwokazTe9U2WDkcVA823POJ3VcXrH53IGZgo+qrWL4Pxhkpbi6spuIhJFOy6C0kAICLCEwM3OP9fW4tnOrT/XqpCWKLRtqUYBklIdC21iL8Yqs22bI/3j0/9afJd6um+MB7o3EhkdrniP2piMsLU5RSGAoUxxwTIpBElX8uXFMTbVthCdvitVStGQiJRdnxYCrUvHCcCe5iq2uR4TI4MUPEm/neL8ZIKNKbtiKrIwDIl0bYJj36JyWVIH3+fR6lpUMo0MA6whkHu3YOZWG4ZhGIZhGMbqMAGYu0ipA1HdVPYBEQY8v62eN44NMjzvwTMZsXl5VzNRERBg44cK7boI20ZfVWMmCAKU7SJqFwdHKgoDHuis4VfjCzsiQ8vGbW5lb51GXVg4oyZ+3yN4iRRXD0G2hSbu2otSsm1uSnF+KEOHlac9Khl0LM6N5Dg/kuWHe1tpdFfm0VUjuDxWvuMYYCRTpBAIondgsWJXhXDoS3LHvkNPp5qyUtXEHnuOQkOLGR29ArTWs8fc1XusEIKhjLf4Q9P8UJHxQpLl+4mWxc3nOPebXzN26VLpu6WkakM3xT2Ps6UpzeHLowuO5Ygl2dRah/6y/LHhdnbjxxKzs+rakpKHN9bx5YVRwuljXAq4r6uWjioLrQLChmbcDZthsHfBumSqmvgDjxHkMjTIKOmYw0S+fEA6FXNWfb8sBpXPPZrSzD1MAOaGqTDg0a40WS/g8nShpLaaOH2FgIG+SeLj/eD7ZHMFegbGeWHPfjZ5n5cN8M8oF2CfkYw6XB7LlV1mS+idLLC9MbngdQ30ODVsffxpZFjkib1dfHail6Lng5TYjS0ECLrqEtRGwA0C+O5Lsse/g+nzgZWqJvb48xTqm2/LPq2mBxGYs7qxlhT80h6pXacUuCzODUjwgxA1PfPZbu/CK3Oc2JbksY01/PzIwntOSwo6qmM4QpPzAvKBIjrvKaspaVMdcxnPL7wGCzQPdNYwOJnne81RWs9/wcnPvkJNH7cNjY3Ip1/kUL6Ze5oiFVPUBrUNRDbvoHjmOABqfBTGR9GuS+SF18ldo+aiZVk4hRwiLM0o92/RDHDDMAzDMAzDuBuZu2tj2ZLC5492NzJcUEzkfRKuTUPCIjpdQN6RivbqGEfyHlZjC0Ffz4IgSFttklRHFV4yvSg4spS2hOC5HU0cODsyGzxJRx2e3LOdDn8Eb3QranwEWZXG2bkPv6FltmN2vphU7G1L8+n5uZoyriXYFQ9pPfo5+sJp8ItsrG9k2z0P87mu5sD5UX64ow6xAvUxhICYWzk1kmtbWFLfcXm6pZSIE4fIf/f1gtfDyXGy7/ya+Kt/Sj5etUqtuztorYk5S/fUO+VSMS1TVIUMvTkXfIFSaqLJc2eoRVB84AXaauL0THdCN1RFeGZLA2mrSNDZjXfp3IL1yXgCZ98D5OZ1hkkVcl9zlE11bQznfLSGhoRD2tEwfZx60ib66LPERwfwD36B9otEt+9BApn3fks4NYGMJ3m5Ywcn6jZycGRhECbqWLQkXVjFGjBKKdrSMQ4yXnZ5ImKTdCVoM7b5ZkTxeXlbLSOFGsbyPhHX5Vff9ZJ2Jf68ukRKaz45O8TGx14sG+CH0nHWXFU5iilFadBCNl9ctCxqCdJRBzVvvQJ4oN6ms+8Ift8pGBtiV1U1Hdse4NNCgkuhi3IjbG5I8kR3DRYh4uQR8ocPLlh3ODlO9u1fEX/tz8jHkqw3QiwubG4Yy6GUYnN9aXaZohS49K9cnA3sN9ZWERsfJLr7XrzquorriWifzXVxLo0lKAalejBRW2ILBbp0jNtSMn8YRET7vLq7iffOjNA7lkMDjiXY2ZJmZ0uat4/1saH3OEcPfLEgQBqMj1J891c4z/8xE7UtFWc7etLCfegJEh0b8I4dQntF7NYO7K27KKRqF6UEni/qF1HfHaJw6iiqWMRO1xC95yGCtq5l/b6GYRiGYRiGYZS3pgIwSil++tOf8tFHHzE+Pk5tbS1PPvkkP/7xj2drefzJn/xJ2c/+5V/+Ja+99lrZZT/96U/52c9+tuC11tZW/ut//a8r2v67ia19miPQHJGAAj03s0aFIftaqzg9OEUxkcLp7EaNj6AKBdx4jPvv3U5Q5ZYNjixJhWyrtui6t4VMJo/I56gJ8yT8IfyqavSTL2KFIVpa5Jd40FRKsbspznje50T/JBp4tDlK/u1f4fX1YwsNaLIDfWR//wseev5V3s7Wkg0guQJVk8IgYF9rNRdHyo+A3t2SIiIUS2RFWjYhBI4KsIpFlG3ju9Hb3pHlFvMUjn5Tdpn2iqjL55E79q/6bIM7XXPSxbEkfpn0R41VUWoisuII2+slx4eZ6OunKSIBTVZJsn6IBjIXztK8b4I9W7ooTk5hezlqhY8bjFN0q3Aee4547yX8E9+hgwCncxOyexv5eHJRZ7dWIWkL0lUzQaNg0XD7ou1Qu+8BMk0dCDTq2DdkvvxkdrnKTBI//iXdjUNMdD7I2clSZ3siYvPSziYSMlhOnPiWaE5YNFZFF9QLmfHQhlpiIlzR88XdSqqABhcaIxbfDRWwUATxJE7nptlrmHBd8tV1jKaaqV8i6FUXk3TVxhkqk+2vPR0nHbP57fjidHsSzYs7mrg0MleXaHu1Q8uRj0hN9BEKBdE4IvBIHz3AKw89w+DGTdgCaqISOzeF4xfJHTm4aN0wfa7tuYjYuntdBDOEEETzGfRgHzqbRdbUoesbKdjla0UZxlKUUnTXxjgYsckUA4JovHSPOjEGhRyPbmslEWsmmJ5RttR6NtZGSFia2OygBTU7cKazLkHK0Qvi4lIIGgvj/KQmz0h1BN+NEq9KkHAEmoAftLtM/tNhgnn3QBHbwrUEfjZLeryPsXwj6SVip560ER2bsDs3gwoJpFWaxbPEfZWrQvyP3i4FoqYFY8ME7/2WxGPPQWvbkr/pjSjdk4ZYxcLsPam59zMMwzAMwzDuZGsqAPOLX/yCt99+m7/5m7+hvb2dc+fO8d//+38nHo/zgx/8AID/+T//54LPfPPNN/yP//E/eOihh5Zcd0dHB//xP/7H2X+XK6xprJwaR/H63lY+vTBKzxiI5nY60lEe6a4n7QQEy+z4sQU4UxPIqQkS2SmSQ/14PRdRhTxTgLthM86jz1CwnCUfNGc42ufpjSn2t6UYK/h0j13i4sQwUUcSzE+ZpjWFrz5hy2M/nA0CroSWpGR/RzXfXh5f8HpHbZydTXGUWrkR97bWOFfOU/z2SwqTY8hIjMj2PYhtu1fsO66H8IqoXPn6HgDhUD9ylzQP4bdYyg55fnsjbx0fKKWumpZwbZ7dWo+lg5tLUygEcnSY6ok+ihMToDW1iSS1tY30+Ra+Ujj5DO7Jb4l/+T5Qml/i2zaJ7z1LsWsLunMzVtcWJBofUdonbrKz2NeaaC5D7tCXi5bZKOqGLvLSgw9zuq2JmGNRF7OIiaBsJ7UtwJ0cR2cmEa5bqq3hRG5Zh7ajA17Z2cgXlyc4NVCqHVIdd3mwq4ZN1TbqJgNmRhnzTveBG0U0tSO1RgtBqDX6GpcDS/k8v62eoyM+B88VKAaKVNTh/q4atta6aAS7W9Mc6Z1Y8LmNdQn2NETZ0xBhOB+SKYZs8YYIJvuQYu7cqHWplkzw7QFauzaAkOiD31E8dQTR1U146ihWfSMqnlx0PKuhfuT2vYTh2tlvXBViT4ygCwVEPIGfriUQkmj/ZXJ/eBPtzc0WsqpriT/7CjkzY9K4BgdwpsbQmSmEGyGsrkU6ktf3tvDZxTHOD2cJnAhNmzby6IYa2pOSfHB9M52rHc1TWxv5w6nBBQHwdMzhie5adDh3HyeFINJzntxHb6F9n5kYil3fROSZl8lHYjRIHyUUyYiNBiwhsATMRHXU6BCOfXX1p8W01vhaA+K67oet0SEK84Iv8+UPfkpq595rrmM5bDTOlYsUv/2cwsT0Pem2XYhte0xg1TAMwzAMw7hjrakAzKlTp7j//vu59957AWhsbOTjjz/mzJkzs++prq5e8Jkvv/ySXbt20dTUtOS6pZSLPnvHkzZjHkwUAxwpqYtZxGV4e3K/K0Wdo3hlWy3ZsJTGIWFrCP1l96NGVIA++BnZk0ewcxn8S+dKNRwef47clcvoXAbvwhmsukbk7vuuf/tUQI0N9WkbefQ8NTGbnL+4PkZ+dITumCJh6RVLZm+pgIfbE2xpSHB+JEegNF01cZriFrZeueCLlBL79FGyB96bfU0FU+S/PoA7Moh67U9X7LuuRdsOwo0s6EibT6ZrFoz8NG4NpRQbU5I/vbeNS+MFJvIBTVUR2lMucVk+4LAc0VyGcHQYmZlET3fw6mwGq1igs30Do0Sor04SPf4FC7q5goDsR2+TrKkjV1UzL0i7gkGNzATaK18DR+iQyNgAm7trKB3oquy5Khr4hF9+RObsSWaqiltVaWJPvEC+rumWBWGieDy1IckDHSlCDVEJDgHaBF9WnNaa9nR0QaF7rXXpv7UmHXOojggEAg+bkUJIIVAkXYvaiEROB9Aj2ucHO5vZUWMTaHClJioUajpF3mNdVWxvSnJ+JEeoNRtq4zTGJLYu7aMtURAxiXusF1Xh4qMKeeypCfLffYnfU+pE1UFQCs70XMRuaUelqhfslzJdvfwZqLeIEILY1ASFD96kMDpTU0PgtHWQfOhJJj/4/aJrRjg+SvGT93Cefw3/GnUtjLtX1C8SfP4BmQtnZgP4Vqqa2FMvka6u58XN1WQ21KCBuKWxdLhwAM61qJDttQ7N97ZzfixPzgtpTUVprXKIXJW2MpqZIPPB7yG8qibi8ADyy4+wn3gRHIdYxCZqS0KluPraZ6erqY7YQOU6bsslpSTs76m4XOWyhJPj4MZX7PvsM8fIfvLu3HcEU+QPfoY7NID7xAt4cgUfTaXFhC8YLwRYQlIbs6Znta6N859hGIZhGIZx91hTAZitW7fy7rvv0tvbS2trKxcuXODkyZP8i3/xL8q+f3x8nG+++Ya/+Zu/uea6+/v7+Vf/6l/hOA5bt27lL/7iL6ivry/7Xt/38f25hychBLFYbPa/5///WuXh8OG5cU4NTM4+wiVcm+d3NNEel9f98HHT26vDubRdilIBlGWQUiKOfUP++CGklKWiooCaHCf79q+Jv/Q6uRNHACieOEx0626KzvJG0AkhEG6EhCOpijiMXfUAblsWbdXxUo2FFfy7W1rR6EJzW+nBthQ4Clb0OyKFHPmDn5Zd5l88S9B/BRG7PaOI/XiSyNadFI6USUMmLewNW/C1Xva+dj3H6/z/XuvH7q2waNu1ptoOqWlwkbKU+kPrYOF7boCUEnXuJAQ+0ZpavKFhpBQUg5BsroA70E9x836+moBtrTuoHx1eUAAZpQgvncfaW79igeL52y6spevfCMdZcvstKVEHD8wWOZ4RTk2QfefXJF77c/KxxM03ugKtFHGhFszOWKq9a3Gfv97jdf6/V6P9NS7c21nD15fGFrxuScHjmxuISs2IZ/Pm8QFGs3Mdoq3VcV7YVk9C+KV9TgjiMpy95mo9tz2WDmmKQEv7/GvAwuuMEAJxjWua9L3Z4AuANzRAZOc+Cgc/JxwewEpUEc7M+rUsrK5NeNd5rr3Vf4NI4JF/7zeEE/N/Z41/5RLeH36HXVeP37u4g9jvv0JyaoIgVXPN71iLx8FyrcY2LOdeeK39tpaUhJ8dwDt/esHr4eQ4uXd+TezVP6MQic3dn07fEl9rOxZfSxU1DtQ1RxFCTM8qC5h/khZCoHovLQq+zPAunSOZmcSrqibRvZmW/DGujOcWhF8s16W6ezNVtkKrlf2t5RLnFyEEQlor9veNFPPkv/ms7DLv8nmS4yP4dc0r8l2BsPm8Z4rvesZnZyhFHYuntzbQnbJmB1DMt1b3Z8MwDMMwDGP9W1MBmNdff518Ps+/+3f/rtSRpxR/9md/xuOPP172/R988AHRaJQHH3xwyfVu2bKFf/2v/zWtra2MjY3xs5/9jP/0n/4T/+W//JfZh8n5fv7zny+oGbNx40b+7u/+joaGhtnXmptX5gHhVtBa88axfi5PBcTic6PWNPD+uXH+4v5O2qoXb/dSVmt7w7ERJs+fJB6PgwZPhQh7erdVIXJshERdAzqfBSlIxWPY9Y3L/h5v517kuRN0uopU1GY056GUJhmxadm2hYYNnUi3clHltco7fxotBcTLj14M+q/Q/MhTt6094feeIet7BJfPz73oOMQffZbI5m1UX6ODvJzrOV7nW8vH7q12q7ddFYtMDlxBZ6dIP/cD5Hu/Y3xwiCAEISRuKkXD08/z/mdnOG9J/mznA1Sd/HrBOtzAo+4aMxpvRHNzM2E8im5oQmenFr/Bskl2dVPT3FJxHcHQAJM950rnozIi48NUd29eqSavmLW0zy/3eIXVa/9LtSHdTTV80zNOzgtprIqwv72a7voEE3mfd7+8REHbxONzt1LjHhy4nOFP7u0g6lgr0n4/9ODwl2XTCcnqWqRWC/dJr4CzcQsim8E/exIHTSQeB8cl/r1niGzeTvUy07Deqr9B8dQx8Itlr1HBpbPEH34Sf3rgxdXitkV1S+Xj9Wpr6Ti4UbdzG5ZzrK6139Yf6GWq/3KFc7UmNjVGzYbuG17/crc3e/TrivdhAAnXpbqpieDJF7ADj9iFi4xkixR9RTQRp/P7r5DasYWos/KPbX6wHY4eLJvmU9bWY9U10BxfmYEF3oUzaHTF38KdGKV69z0r8l0fnx3m1IhHNLbwuz66MEnLfR1011XeprW2PxuGYRiGYRjr35oKwHz66ad8/PHH/Jt/82/o6OjgwoUL/D//z/9DTU0NTz311KL3v//++zz++OO47tKjQ++5Z+5mvqurazYg8+mnn/LMM88sev+PfvQjXnnlldl/z4yEGhoaIgxDmpub6e/vX7NT2HPa5utzA3hB+RHkx3qGsQrOdbVfCLGq2xvLTpIdHZlui0REooSZuc5Tb2gAVVNHkMth19YzUfTw+vqW/T12JIbctAP37HGqbEUy5aABOxYjcu9DDIyU7wBa62KFPLlcruwyIQQxx2FgYOC21l1xHnwSe+tu1Ngwwo0g6hoZj1ehBwcrfqZliU62pY7X+elEVntfXk23a9ttKVCBjz8+hsjlsB9+mljBI5rPQTxJAcnJnMTzAophwGVVy4ait3BkcFX1irZz/rYDRO99hNy7v0UH/vw3kXj0GUaRqCXOH9GJUXITExWXq97LTLZtXDN1jFZrn1+J43Vm2Wofs40WvNSdIFBgC40Ophjon6InJxgYnSz7mdO5HGdb4tS5akXab0kHe9c95D7/mPlpiYTrkrznEQojg4vP80e/w23vIrp1N1Z1DWGiau5cOzBw3d99q/8GkaH+itcoW9r4uVz55baN1DByHdf7tbAf3axbtQ03e6yu1d82OjpEbqpMoH2a7u9lorF92efqG9leIQSRRKryvVgkiggVhel92f3ec9TuGqFmfAwdiSHrmyhEY4wND5X9/M2yrAj2znvIffnxwna5EZL7H0bGEyv2943lCxV/BwD8kMkV+C5P2Bw41U+uUD6l78HzAyTD5KI6WGt1f56x1PFqGIZhGIZhrG1rKgDzv//3/+aHP/wh3/ve9wDo7OxkaGiIX/ziF4sCMMePH6e3t5d/+2//7bK/J5FI0NraOtshdzXHcXAcp+yyuTQiek3enAMUA10x+AIwnCkiGtxlPXiu1vYKN0p00zbCXBZ/sB8rVU04NjI7ElimawgKpRRGkX0PUpDWDbXTR+Luf4jk5u2Eh75E5bLYnRuRnZvJx5Nr9m99LWFVNVa6lnBicQBJC4Hd0jGdfur2bZ+HwKuuh+p5KQBvosP6eo7Xq19br3/Pm7WcbRdCYGuFCENCx53OSb+0QEFk6278gT60V2Ty1AnOjeaQto0KAtL77+dsQSJr6wmH+hnLB3S7Lipf6syTsTiiteOWBDBmtj3f1E7ilT8hOHeScLAPma7B2bqLYk0DobrGb+M4CNtZGLyZR6Zr8G/z8XQ91tI+v9zjdeb11Wy/DnwkcyXAhBBMFSvXitBAzlfUOuXvFyxLYnke2rIIxLVTggYAW/eSrG/CP3UMNTWB1dyG3b2NfFU1UduBBRVrSq3wei6i6hqwH3gcT0zPeLnBY+tW/Q1EPFlxmY7GkcnyKTKjm3dSTKbR6+A+ZiXdzm1YzrG65n5bNwLSggo1skQyfVP3PsvZXq01NLUhE1WoMrMvozv3UYwlZvflorCgphFRO6+m2DL2c1sIZOCjbZsAcX3nl217STY04586gspMYbd2YG3YQr6qmvQyt3fJ76pKY9fUE4wNL14oJLKlbUWu/76CTLFyPcXBKQ8hKv82a25/NgzDMAzDMNa9NRWAKRaLyKvSYkhZvnPivffeo7u7mw0bNiz7ewqFAv39/RVTm613riWI2JJihSBMfTKy4AFHSomQEgHLK0B6C1mAO9RL8ei3qPOnIfBJ7NqHl83ihAFBfy9aKaymVrhwhvgjT+G3bbipByZfSCJbd0JNA0JrfKVKv9M6fgjzLIfY954m+/av0P7Ch9H4fY9iN7bAcJkHYeOuJYTA9T3EpbN4Jw6jvSJ2cxuRnfvIp+sWHWNCCCzLQgMqDNHtG3HauvCvXMSSAqFB+T7R2nqmunYxNuwj0zVYWlGTiKC8Uv0Mu66R6PeeJR9L3tJjTmtNrqoa695HS7n5tSYXhtf1nV4ihbtpK8WTRxctE66LaOk0nTZ3Aa01VZHFt09SgOtYBKEi4VpMd23OEkIQGx/GP/Yt/kAfwo0Q2bkP3bGRolW+o3tGAAS1TdiPtZWu1UrhKQVK4aVqiN37EPmDC2srCDdC9OGnyEtrzV7HdG0DMplCZRbPJpKtHVjb9+IMDuD3XwE02DbRzTuR9zxc2n7DKMOvSuN2deNdOINw3FLQfHp/EZEoorn1tp6rC9EY8Rdeo/DJewSDfVjVtYhkmkh7F6p7W9mgw3LbJ0Vp5o939Bv84UFENEpk1z2otg14cun0roEQBHVN2I+Xzi++UhSVQqzwb+RbNrFHniL7zq/QnrdgWey+hylWXbum0/VwpCYZcZisMAOmIbm8QWiGYRiGYRiGcbPWVADmvvvu45/+6Z+or6+nvb2dCxcu8Jvf/Iann356wftyuRyfffYZ//yf//Oy6/nP//k/8+CDD/LSSy8B8A//8A/cf//91NfXMzY2xk9/+lOklDz22GO3fJtWQ9IK2dWS5uDlsUXLXFvSWR1F61KB4KyyOTOU5+xQFteW7GlJ0Za0sPSNBWKklLP1e2704UZKiXPmGNlP3gM0lpTo8VEyb/6c2MNP4rd2YqeqSTz8JGG6jui+B/CiiRV7mAqCYN13okohiGQm0EP9hALSz72K13MBf6APmUzhbN+DX9+EqDC69VabKU5tRhnenJmA9Urs+64KsceGEcUc/qGv8PqvoOxSKr5wagLv/GkSL75OrnauxlJROFwa9zg+MIHSsLM5SVc6TuqJF3H7L+OeOkZLqkCubRMjte18PlpqpxKSeHMLndvqSLRUIRyHoKqa/A3OYLsRV6ceua7PKIV7zyPofA7v0gVmZhzIWJz4ky9SSKZuajZXJStxXjVWVkPcIh1zmMj7uI5kf9qiLjdCcXyMRE0tZCcZS6Romt6fhRDEhnrJvP0rmDfQIfjobdyNW3C/9yyeuHYNrHKDJAKAXfeSaGrFP3EYnc1gtbRjb9pOoar6umeJzAZTtb6h4+NGFN0o8WdfIf/ebwmn5tL72Q3NRB5/jqlIHOf510hOjZc6bGNxvGTaBF+MWZZVKhIfhuHs9SNQmqr7H8NNpggHriDiCbTj4o8OE334KQqx5C05V1eitSaXrCb6g58wng042jvJYC6kOhJnp4rQ4FBxts71EEIQ6b1I5r035tYzNUHwhzeJbN+Dc/9j+OLadZ9u9SAsrTWFhhYSL0/PQu3rQSarsLftwa9rYqXOOhGhuKejmg9OL07bZknBjqYkYbg2BpwZhmEYhmEYd4c1FYD567/+a/7v//2//K//9b+YmJigtraW559/np/85CcL3nfgwAG01hUDKAMDA0xOzo2mHB0d5b/9t//G1NQUqVSK7du387d/+7ekUqlbuj2rRSnFfW1Jcn7IqYFJZrLqJCI2z29vJG2HKAWToc3Pv+sjMy+VysWRLNubUzy5MY2lKk/fv5qUkjHf4uxgjuFskaZklI21UdJ2uOwO1Ug+Q+HCGQq7H0JJSXxsAOm4OPl6/J5LVL3+5/jpOjLR+DXTM6xkB/V6YQlwzh4n+9kHs7U18kB0x16iL75O0XbJBQECcdvbJoQgms+g+66gxoaR6RpEawfFROqu+hvdLAuITI0RXj6PLhawmttRDc0U7aXrYVUS8wt4H75Fof8KiY1byB94H6TEbm5DJVNoSmmYil99gvPC6/gIisLht8eH6J8ozK6ndzxHY1WEV3Y2EuvYhLVhK7XYfHN2hNP9U7MJktJxhxe3N+K4inxd01xDViD4IiybbCBAQMLSN9WpVU7eieA88X2Sk6PoyQlwI+iaOgrR+Irvw0IIJgKLc0N5BjNFGpIRumvj1DihOV5WiBACJS3ygUAISEiFuo59JkLAazsaeedID/vdKXJvvUXP8BhVMZeqZIRB6RJ55mWOCIcmR2IFPoUvPloQfJnhnT9NYvteqL/xws8BgqC+BfupDgSaQOnZGTLXo4hDz6THhZEMriXZ2pikIQaWvrX7mdaafLoW95U/RY4NQyGPSCQJquvITY/a9xH480fGm33fALS0GC7AqaEsCthYlyQVsYhKRU1hksw7v0KPDiO9Itr3EMkqEi/+iGx98w2dP6WUs3VwlstVAc7UOCemBG8e7UXHkqhIlCtZn+P9EzyzrYltNdayUuotWH/gUfj8w7LXu+KJwyS37MSfn/Z1FSmlyCXTWPc8grgXNIL8Cgd+lFJsr4swUajhcM844fS9RdSxeHprA3Wu4haf2gzDMAzDMAxjgTUVgInFYvzVX/0Vf/VXf7Xk+5577jmee+65isv//u//fsG/b6ROzHrnaJ9nNqa4ty3FRDHAsSR1MYsoAUpphGXz2fmxBcGXGSf6J9nWmKQtdn3fJYTgwpTmzWM9BNPRnjODGb64KPnBrmba49efSkEIwWhg8bHVzvmT44RK0VzfwCP7N9F0+gv05Dh+0SMfiS3ZWWsJiEyOEfZcnO6gbkPVN91wB/V6EhkbIXPgvUW/T+H4d4hIFL3/4VVplxCC2Ogg2Xd+jS7k5153XeJP/4Bi862p/XGnsdA4Jw+T+fLjub/xkW+w6xqJPfsy+Uh8eeuTkuCbz/F7L2NV1+L3XCwtUIqgvwenazOBUzpu/IE+ErkMYTLN6eHCguDLjMGpIieGctzbFCEIAgQBz25Mc19bilymgOPlqPcmSQyfR9c3UXAiN/V7zJBSMuRJPjszRs9YqchvR22cRzbUstJla30h8NN1kK6be3GF910pJZez8MbRXvywtO4zgxm+vDDK93c105WU5ni5SUJKruTgs/PDDE4VsKVkU0OSBzvTJMTSAxAiXpHqT97lj1s7yHz7NYNelnTKIVSKicksyh9DvPULJl78M9KbW0hlpyiMVC6iHV46h9XUdtMzT25kBHtOO/zq6ACj2bmUQId7J9jfUcMj7Ymbas/10FpTtB1oMAWmjeujpcU3/QU+Oz9CV32SUAvePnCBTDFgV0uK++1JdjS0YY+NoCJRiEQBmPrg98Re+/PSPeR1mh3w0HMB7XkUu7cQSaQoyOt7hIqEPuGB9xiO1/DOBQ8vXwQGsdI1yIZmFJIPTg/Rdl8bCXGDM8enJhbMILta2HcZWdu4pq4Zt3qWnaUDHm2Ps7spwVghwJaS2phFQpoBDIZhGIZhGMbtt6YCMMYKUwHVNlTbAAq0mh2BngsEF0ayFT96bGCKrs3p63pAymmbd072zgZfZvih4t2Tg/zpPS1EuL7ZNFll8/PDA4xfHpl9rXdwnF+MTPKj/Q/ScPBdNIsDL64OscdHUBPjyEgMSwdMffohKpcpveHw19j1TcSeeXlZD97rjWVZ+GeOVQxOFU8eIbp9L+EKdXovhxt45D98a0HwBUB7pdejr/05BTd629u13kTGR8h88TFcdRwEI4NY336O9cgz1y4mP4+bmyJ37uS8V+Z9Vml0ZhJR2zAXRNWaUEiO9S2u2TDjeP8Ue5riWNNlyy0d0Np7luzHb8P0OSULWFXVxF94jVy8fKHt+WwB7uQYanQYYVlQ21CaOTXdrlFf8otDvQtqX10YztI3nqcqkWB1ku3duJyyeOdE32zwZUagNO+cHOTP72kliulEmi8S+sixEfTUJCKRQNc2UHQiZQcACCG4koVfHe6dnSXqhYrj/ZP0TuT58d5mohWuW1JK9MnD+JfPkYhFKfZdYWIkUzrvBkEp3ZHvUejvpXrkMmNxSXXVtdP/rAZpWXx1YXJB8GXGt5fH2Fgbo20V2mUYSxkpwmfnR6hPRpgohHxybu6e8ezAJIVMPyMNaZ5q7YTeS7PLVCEPw/3QtvG6vsdGYx0/RObrA7P3VfLMMbxkmuQzL6PyOdTYMMK2obaRYjw5e02C6XSr50/hXTjD2D3Pkcv3zC4LJ8awE0lIpPBDxXAuIHHr4513FxWSsiCVAFCAMhPo1qmiEuTL1DaN2ZKINKmMDcMwDMNY+0wA5i6lYMlOWq/MTW4lI7mQgl8+UJMpBozmQ1quo19dSsmZoTwZJcGyIAxLSbKm6x58eWWKl9u6kLUL0yjEigW8j96k0HcFANsrEA4PEn/qJfI9F1G5UqApGB6Y10FdefsK2IwWQgKlSUct0g7odZIrWgiBnhyvuFzl84jAh1UIwFjjo4QV2qbyOcToMDS3395GrTOWZRGcO8XVwZcZ3rnTxPc/NDsLRghBVtuM5UKGeyeIapsq66rRn76P9ksdzeHkONGNWygePji7eH6hXLuxmSBRhdJiyfNHqDRKa2YqWkQzE2Q+fmc2+DL7vqlxip/9AeeZV5cM0boqhG8+JXP8MLN5Q2yb+AOPEWzehbIsvrs8tSD4MqMYKL69MsFDjfK6AspCCGytsPNZEIIglsRfhTpFo4WQrFf+vJP3Qkby4XXPUrwbxHNTFN5/g2B0ePY1qypF7OmXyVfXLQrChMLi0wvDlNuNJ/I+F8eLbK8pX5PI8QoUTx0FSqn55lJhhmilEJ4Htg1hgPQ9isNDyGQTbk094VAfCFGqrzRv3VZnN968/TOUDmMFTT4IiTsWNRGQauWvQ9lQcHpwquLyY/0Z7ute8a81jBtmWRane0v3dU3pOD//rnfB8qmChx9LcuLyIPv3b6Z6XgAGQGWzszXorsUdGyLz1QGuvubaiST+O7+iMDIMaGQYICyL+KPPUNyyG3/6WHbCgOLx74Dy99xqbASZTKH00vfk16Kq0lhVacKpCbSQFAMItMKWkogFVksHRRN5MNaxfKD43YnhRa9/f3s9Eff2p1Q2DMMwDMNYLhOAuUvFLU1TKkbfRL7s8i0NiSU7K4UQWNP1VfxrdGpePTOm4jql5OxQltC2sRuaCa9cQhdy6CAAren1C4Qv3oNXVTOb7seWAv/LD/Gngy9CCNTkBCozRfad3xB//lVyJ4/Ofod37hTx/Q+WTdMkhOBo7wS/+raP7HRqNksKdremeagjia0ChBA4KkT4HtqN4Au5porIK6VwmlrhyqWyy61UGrVKs0y0v3iE9cLlxdvUkvVLCDE3q6sMHfhzQQ5pcWo84KMzvRT8kHg8jl8s8OCGWvY2RhHTnbk6EkXG4qh8rpR2zPdxN2/HO3Oi9J2xGEprhO0QfeB75IXEIWRDXZyxXPm/aWdtnIjUqHC6zX09s/WIrub39pDITOAn0xW3WV44Te7Yodl/AxCG5D79gGRNHZP17VyeTjtWzqXRLPc2pJHXKPErhSA61Efh6wMUB/tBCNy2TuL3PUo+Xbsix7plWdjFfGkmkRslqLDOq2e+LHf53cTVisKHv18QfAEIpybJv/9bIq/8KYWr0k/mQ8Hg5OIUejPODGfZVV9TNqWXCEO0VzpfCSdCRIIA9PTfRGuFEKUuWxVL0JqwCE8dJdLaztTBA6AUMlWNrGsglBaRDZuR1bVE/CKhG2UstHnr+BAD89rXWh3jha31xK+RGm25tBZL7ks5f30MPjDuLnm/tM96ocYPF55DNRI9fW82FkiqhWR+wQ9ZXXNd5/LSjOITXB18EfEkIjNF7vMPcTdsRk2OE46NoIOAyfOnSf+z/w+yaxNFy0GEwey5Ik0Rx7bwg3D+lyDDACkEdQkHrnO2+NU82yX60OOMvfsmPaM58vOO26b99yDSjcibnDEphMCyJGgIlVpT976GYRiGYRiGsdatzZwYxi0nVMAjG2ux5OJRQ7UJl850+bQtAFG/QOTscfTvfob+3T9SF2SwKxQttoQgFbHKLlvUJsCxSr1WIpbAqq1HxhJIN4JMpoi2daLzOdzxuU42Z2oC7+K5BWvRQekBVhfykM0gnLnkQws6qK8yHlj89mj/bPAFSiMSD/WMc3SwQERA9PJZgt/9I4Vf/h+CN35G9PI5nDVUyVMphbVhC8IpX+smsu8BPHt1kjGJRApk5VOOrCrfAW/MCcMQu6Wj4nKrKl3Kdw8MFuDdEwMLZqf5oeKTs8NcmgpnAxleNE5k1z2z7yleOoe1eQfxp17EbutENrcT2byDxA9+Qr6uGa01Sil2N1cRcxcf21HHYl9rFWr6OCsFjSqnO0QrCCp3OjlhQPFIaUaO7RURQ31w6Syi7zJ2IUtw/DtsKbGX2LdsKSlzqlvc9tFBMm/9kmCwD9CgFV7PBbJv/hOxTOX8+tcrVsxjffMpxV//X4q//D/w0VvEJ0fLFnaujtoV2ywFpKNm/MQMe2KUYGig7LJwahIxurj2igRsq/JOEbEr709hJIo9PRPTz0ySbKintio6mx5T2DZaKZKdG4g1NJDoOUPh47fJf/s5ySdfxO3ciFAhMgxJPfo0kY1byP3mpxR/8f+i/vA78hfPU7wq8NE7nuetU8Noa2X/7lFLU19VOSi/qd7kRDLWFqUUXTWl6X/l7mEd18a1S9cmW7IgJatVU4eqbbyu7xFCoDOLZ4dZdQ0UjhxEuhHUyCDB0EBpoBClGaOFgwcQxw5hA6Ebxa4vfV/V5RPcu6mptBIpsatrEWFIcPEsO5ik7tRB4tmpsteDa9Fak2/fzMSjL2N3biSSTpNoaqb6me9zvOMefnVqDHWdNWvKiXoFImePod8o3fdHzp8kagbNGIZhGIZhGMZ1MwGYu1hLTPP63lbaa2I4liDmWOxrr+a1XU0Vc9/HvDzeW78k98m7+AO9+ANXSH7zBzbLDNa8IIwApArZ3ZKiJrL0w6Rl22DZaK3Z05oCAWp8mGByHBJJZEMTIpWmO2XjnjyIf+TgXGer58G879VaIeNzHUbh1ATCnUu3Nb+Dej4pJWdHchVn6/SMZFFHDpJ9/3cEI4PoQp5gZJDs+28gj32LdQMPzLdKoaqaxPOvYqWqZ18TboTY/Y8Sdm1etVGLXipNZNO2ssvcjo0E6drb3KL1R2uNaOtasI/PF73nITzbRVoWh3ony6ZXAvjq0hhKlDqolFLobXuI7rt/NlhZOHeKINQk//n/F/v1v0R97zlyV80ASVkBf7S3hW1NVURsiWtLNjcm+aN9rVTb849JjezahGzrREYX58wSkSjEFs9ImyEDH5XPYeWz+JfOEY6OoPJ5wskJ/Evn0VcuEhUhu1oq15HZ05ZC6qVnv9hC4H33ZdmZOrpYIDh7AsdxiCifSODNzgC8XlG/QOGdX1E49CUqM4nK5/DOnyL7xj8SG1+cVqPa0exoKR+U3NaUoqZ8jPWupIuVZ7IA6DIBwISt2NRQeZ/Z2VxVsaC9j8Dd9wAIgdd7GWfTdjo2baC1IU0k6mJFotRu3UbzCz+gyx/FP/wVYV8P/oUzTL37W5TvY7dvwK5vAqWY/MObhFMTqEKeyfPnGPzlT3ncnsC1Fu5jveN5Rgsre/62dMjDG2qQEqRSSKVKF3AgGbHZULO26nKVRuHbCMvGsq5vcIextkgpcVVIxF/+eRRK15T2tEt13EUrRTq2cFBJY1UUu6qKWH0ddSpPaQaLwGluI/bMyxSvcxCKUgqrdfGAB2HbqMwkVjxBODG2aHk4MYY/cAV3aoxAa9w994GU6NFh9ucu8fyeDhraWmCojyqpeHJrEw+rAbwvPyT3u58Ry1SurzaflBIsGzkdlB3IKX4+bHNo2xMMPP5HnHngZX6vGjk65tM7nmeseGPnjmBkiOJbvyD3yXuz9/25j97Ge/+3JghjGIZhGIZhGNfJDKG9i2mlaIrAazvqyAcCKSBuKcKwcuFhdfr4ojQvXLnIY9trSdfV8t0U+FMZ3NwEe5vi7B3tx8m7iO7tFK566NXSpj+nOdQ7zlQhoKkqwq6WNPe2pTl44QxoXUqLBNSmE9xTFRKeHUF7HpFigcBxIRpF2M7srBcAElWlEchBgJWupTgv/3dk/4N4ToSrq3BKKRmcqvwgucnKkfnq67KFvPPffUli4xby11FIfCU5gPQKaMsmcNzZuh5KKfL1Lbiv/CnW5Fipfk0yXSoOextygFfKrR5oiD7wOFE3SvHU0VJKMtsm0r0N+55HyAsTD74ehViC+AuvU/z8A/z+K6A1Mp4ges/D+NMBNqVF2aLaMyYLPp6CmdCkJy2s/Y8Q37ILslMI2yFI1ZCZDoyWq1qrtSZtBTy/KU12QzWgiVugQ392wHFROJwbLXKyTxCyge3dW+iWGSLHv5qdiRbdtZ9iLFn2OwCU4+Ikq/BOHVn4HgFCaxACOzvF1vo0Z4ai9E4s7Ixvr4mzszlFYWKEcmb2V6uYpzDYX/E30xfP4iRT5L/7Cq0VTvsGIjv3k0+mrxnUFEJAz0XCq8+dlFLzed9+jv3UywvSkWkV8r2uFEnX5rvecfJeSNSx2NOWZn9zAtTKpqJaz0QswXQSsLLLZVVq0WsqDHmwM03veJ7JwsLfcndrmqa4rLhPAnjN7SSeeonCVwfInTyK09LKhhe/T0ciTYAgzGUJP38Le/d+gssXSkW6NYDG77mI33MREQalmZ6RaKk4OBCEGh2GeF8fYNNDP+D42MI25HxF3TImMV5PrYvNVoFXWxw+PnqRkfEMTirFhk1dPLS5iaRcOynIAmHTkwn47sooXqDoqo2xvTFJygpWdGCBI8AqFlC2gz9zDjRWRNQvos8cxzt1FB0GOM1tRHbdW7ZO01Ii2ueHu5s4eGWS57c18qvDfSCgqSpKlSPQQvLU9/bT6GTRbU0IN4KfqiHH9Q+WUUohOzchv/tq9vgE0L6P09SG0GFpds1MvsFpVl0jQTaDnhiDqhoKdU0knn2ZwhefwKUzbM9Nsa2jm1ysBiv0cc99Onuvq/I5gpPfIe9/vOL9mpSSUV9yvDdDz3iBuCvZ11qNtARKw5VJjytlPrfcc8fMdxWPHVp83w8EA324F88gtuw2x4hhGIZhGIZhXIMJwBgQBsTmyipUZAce3pnj5Zed+IaHOie556FnyJwZwIkXiV86Sjg5Th5wrlwi8sSLFGfSp0jJoYECB87NPdQNTRU40T/J93e3suGBbg5dHMYLFdvqonSoKSKHDwDT6V2mR756iRSRzdspnDg8tzmWjd2+EZ3LoCNRCIJSB/X+hwi7Npd9qFVKUZdw6cuWH0mdKk7O1sxYJAhgYgxuUwDGAiJDfRQPfYE3NoJ0I7g79kL39tmRnVrr0m9d0zD3wVsYfBFCEPEKiJEB1OQkMpVC1zVRdKMLHswLloN1/2PEd+6DYgHcCF4iRd4Uh71uWmtyVdU4z/2QRHYCwhAdS+BFYrP7tiUgHXMYyZQPKiYjDo6E+SnhQ6XIx5IQS87/smu2R4UBM/Na5k8yKeDw6yODDE23wY5U8+GlPg67mtd2Pkjs1DdEd92D3rFvycCgLy0SO/ZR/OyD2dcEGopFdBhi1zUSfvMZ1dv28PKOVnomfY4PTCEEbG+qor3KoSbu0jcvg5gQgmg+A8MDqHwOWVOPla6h6Lil1IVXscIANTpE8ewJwqnSioonDuNfOEP8Bz8ml1g6fZ5lWfhnT1Text4e4oUswVW1qWzl82BrlF1NrfgKHAmJJYLkdys/XYPb3oXXc2HRMru2nrC6vuznqmTAj/c1c2GsyNnhDBHHYmdTFc1xiXWNgvehhkLHJtyWDmR2CqQkSKQQPefxv/oENZ26SMYSCMtCSbkwPiQA3wM02A5Q2u9m0qLlBvtpER7Hr+owjtkWsHTbpBBEspPooX6072HVNRBU1+OVCXJH8xnyv/snWr0iP27vJtdSj9SKqv4vibU/Qj6xOHi1GkJh8+GFSU70z80OGJwqcLh3kh/tbaHGvvlAkQW4A1fwvvsSb3wUGYkS2bUfvWHr3L2LccMigYf3/m8JBvpmXyuePYl36RyJF39Ebv79ynVICJ8nu6rIKcnulirODWcZnMpTG3fZ0ZSkztXkVAKiN55GrxBPEn/xdYqffYA/NEi0ezNWQwvx+x8h/8m7WLE4amoKLIkSEmwHu62L4onDMF13SmkotHThvtKKzExh2Rb5d35DZHr2zNVXP//SOdx9D1K0FkdLhBD0FwS/OtyLF8x98uJIjh1tNbRUx+kbL18P7XrOHVezfQ//bPn7fgDv1FHszTvxlxHYMgzDMAzDMIy7kXmiNK6bUBq9REepHh8hdvRzOPYdwIJy137PBdyRAWhsA2DCt/jsfJkRdUrz4elB/ll7lNb8SYSQBCfHZouYArjbduPbDihFqBTOPQ8TCQOKZ0/OBhl0YwuJJ54ndFwSO/ai48kFHdRXU0qxuT7B8aHyHdbV8SiO0JX7o29TCjIpJe6ls2T+8OZsUdmwkCf/+Ye4/b24jz9ftpPtVhJCEJsYJffur2c7HQFksor4s68uKl4eKkU+Oq9TxARfbogP+PM7/uf9jioM2Nea5vxQpuycgHs7qrF0WGG+wM2TUnJqMD8bfAEIbAfR2slE4HG6oZaHd++m6EavOStLaw11DcQff5b8l59AIY/OZpDxBPGnniF/5BsiO/ZQePc3pJ54gU3NHWypqQFKNXOu7nASQhDtvUjuw7cWnFecxhaq7nuUiT+8yfyeciEETE3g7HuQ/LzZdACqkMc/+i3Ww08TXmM7hFwiXZIU6AodWGEYEiUkKmf+veTX3JV8DbFHn4UD7+L1XGTm72c3thB9/HlyFTrPtdbE8NlZa7GnoZQCMQiCBQW7l1IKdDuQmkufKLu2EGnuQOamEJaFbTvIti5UX8/iFVg2Ml0D/b2zL0UtQcS2KIZzqcBmNKWi1EbF4h7b+asUAvfCSXIH/rBgZqjbsZHo956l4Myl5JRSEp45jppOeSTPHWcm/BoCQTKJfODx6/otbrWBvFoQfJlR8EM+uTDGq9tqSrM9b5CUEvf8SbIfvs3M/hMW8uQOvE9ksB/n4afwzSzNGyaEQPb3LAi+zNC+T/HrAzjP/XDZJehVGBAFojY0tUaQMobWmjAMrvcwXpLWmlyqFueF16meHKP4/m+ZfOfXWBu3YHdsJP/pB1h19YSjI9gNTUQfe558z8VSas2augXrKUobUjW4aPRSqdeERFe4pwyFxYdnhhcEX2YcvTLOAxvqygZgmlJRaq5x7ij/A6il7/vDcHYmqmEYhmEYhmEYlZkAjHHdAjeC09ZF8eThssvdtk7yPZfKLgMILp3FaulEKcVEweexWkE0KBDYLqf8CFcmPTQwkfcZTbTQGE/iXTq3YB1OSzuie/uCTtuC7WI/8izJ3feisxmE6xKmasnazsK0CNfoIK11FS/uaOI3hy7OFi4XwLbmFDVNgoLjlGrOXEW4Eai+PfVLHK9A4auPy3YQehfPkNy1H6+u6ba0ZYYbeOTff2NB8AVAZabIv/8G7it/UnYkp3FrtcThiS0NHDg3jB+WjgNLCO7prGFD2kZfY4T/ckgpcQs5RC6DsCy8VC2nBzOL3qeB0HY5Ouqxu736mrMMZgTROJ6C+HOvIooFdC6L9jzyR75BTU4gq59CD/RR/OoA9vd/jKfmOreuLmgczU6S++BNtL+wq88f7MOLxYhs20nx5NG5z2uN3dJOCIs+A+BfPk/knkcIncpFWcIwJLp1J96Vi2WXux3d+LGECUbehHwkivPMyyQnRtH5HCISI0jXkLuOTnOtdcV6L8ullKLouJCuQwhBVdQl9shTZN78OTqfw+nYiNuxAQCnYwMqFkfl52ZdSRSdNTGG4/UcDSJA6ZrTUBXhhW0NyGuknotMjJL5+N1F+5J3+TzyyNfI+x6bvX7aYYB//nTFdfmXzuLue/AGfoWVZVkWp4cWF0Of0TOaZcqvJXkT8RG3kCP/1SeUS2NXPHOc5I69+BVmUhnXZlnW0vtafy+JfAZ//gzMZVJKLbg3XHBdsm38ZPrGZ2oIQe7gZwTnzyCUonjyKHZbJ8mXf4zK53BaO/AH+yn0XUYVi6X0hNF42VmkgbRwNu8g+PLjsl/lbNpGYLtlrwcTXmnmVzkSjdKatuo4V+YFYWbOHdYNpK0M3SiR1k4YGizf1s5uQtsxIwMMwzAMwzAM4xpMAMYoa+bBVU6O42XGidoOxVgSZ+c+vAunryp6LLDbOvF3PUCQ97B9bzaf9Xxiuuh3JPBoOPw5mS+/Ju95CMti78ZNbNrzKB8NhyhdKnJsPfY8iaF+gvMnQWnsjVtQTa0UynTmB1oTJKshWT334jJzUmul2NeepspqYzjn44eamphNjQu+Dok98Di5A+8tXK8QxB58jGK86rZ0nsrsFOFU5QKtQe8lZEPLban1MsMaHyGcHC+7LJwcxxofgbrm29YeY5oK2V3n0Fndxmg+JBKNEhcBKVvBCgVfhBDEQh954gj5rw+gPA9lO8iGZh7d9jBvFlzy/uKOGa31smbfeLEEkU3byX/+AWLgCuH4XOHjyM59+JOltGDByCCRXAbKpE0SQqClTT6Th4YW6L8CamHb8pcvknrtT7HbuvDPn0HYFpHubfiXz5M/dqjSj3DN9mutUS0dOO1d+D0LgzAyFsfZdz85E3y5ab4GP1W7YEbKarNq6qChmfhzr+EkExS++YLCwc+QkQjeqWNEd+0j0b2F3PnTswMGIhGHzc89ixOvZ3MxJOna1MUk9rwOVCklvpZowBWljmcpJcH5UxWvRcVTx4jtuoeCG5t97eoA5UJi0Syc1RIucXgoXan6z/UTmUlULlv5+wd6ETUNptbFMkkpieQzyMkiQbGAFYYou0xdHcGKzqJwtMI6eYTct6X6LZYAu7GZ+CNPk0/VLPvvaE9NkL98ATU1ycxcxuDKJTKDfVjJKqzqOoLJCaLbdiM2bKGwxHcopZDd27DPnlhUW8VK12Bt2YlX4Ri+1pVTasWrO+sZzAVkvelzR1Ri6xtLWxkqRWTPfYgTR6667y9du+wtO/FM8MUwDMMwDMMwrskEYIxFLCFwL54m//mHqHwOFY+TDxWx+x7F37yTxPf/CO/QV/hXLiISVUzc8xSHClEun8piFevZtbGVrXoS5/jXzHaLCIm1dTe+FoQHP0OfPIKank2iw5CpM6dIZLPsvP9FzmYV6YhFERua27HauhBCkF+hEcrzSSlLncHTD8pCCOLCpyM+85AbgCplbfC7t5NM1+AdP4QaH0VW1+Lu3EexrumWBTyEZVEIBZYodbKJa4zmXjLN0S1y9UP5cpcbt47WiiqpSCUFLS019PX1odXyOp4sy6KgJEprolKjp4MWUkpiI4Ook98x8dufTb9ZYjW0oITEHniDhx97jfcXZxpkQ12CiNSzg2avPg6vppQi2LyTRCKJ995vULkcMpEksnM/OllFYWZktRBlO/GyXsDZScU3PWPk+0dJ6zbuvWc7zRcPwfDAvC8KCUNFob0bq2sLSmuyShGZGK/4+7gbNuNHotcMwBYth8jjL+D0XMQ/cRgd+jhdm5GbtpGPVy07YHy3udY+spZ5Hd3E4knyv/tH/EtnEWGALoJWmvy3X+LsvR/nwScRfRcRqRrsrTspVNXQpBQtMZtCKNC69BsopcjjcKw/y8mBDFprNtQl2NtSRa0DqkIwHEB7RUQQwPRkrcCycTZtJ/jqk7Lvd7q3ErrRW/CLLE8YhnTXx8umIINSeqWErZefXmkesVRKKIBVuLaudzZgnz5K7usD6CAg3tVNePEMVmMLKplaEEpw27pKswCXcXgLy56tjYUKZ88NUko4fYKL773PRN5Ho6mKOtSqfsK3fkHslT8hf1W9rWvyiqDVooCl9n2CsVH8yXFk50b0nvvJI8qez4UQCCFKs+Sicfj+n8DwMM7FE+jhAZzurcgNW8hHYos+O6PKEaRjDhP58gGVzpoYMvRojgARAYQLi7PdAKetk8T3f4x36Ev8KxdBCNyOjTh77yvViFqH52TDMAzDMAzDuN1MAMZAWhaeElgSLK2IDPeT+eCtBWmudLFA7sD7JJJV5JrasR9/gVgxT5+K8o9HB/GC6QLCbooPT17gfH0VL23dg33qO0RNPcP7n+KdAcnmkV70F9/QmLBJxyOM52ZqMAgyfb10qSkaN3YSl+Fsf2Z4C0bXRUIfOTJIONSPjMaRza0U58+eKSMEcnVNWE++VBrFaVnkQnXzQ2/LEFIyWBB8dXmCwckCri3Z1ZpiV109Tk09wViZXm0EVnsXxds8kl4kqm5q+XokpYWnS8eMnNfxc6fJ4XD4SobTAxlCremqiXNPe4pqOySSmcA//i3eTOdtNEa+qo7hKR8vO0Z1TYrEwEXiiU3kCnOdRTHXYm9LFWHoE/WLiOEBwtEhZLwK0dRCIZEq+3sGQhC2bSDx2p9hHf0W5QcUh/pQw4PIlg5y1U04VVWoZHphMERafHh6iE9O9QNghZLx/jEuDYzz3J59bC18Ops+T7guRGOLU1J1bcI+fYxgZGEaFpmswt6xr+Jo5asVbRexcSt29zbQCl+UOtRNB1Zl4cQYsf7LBMMDpYL2zW0UEynUOvrNQgShEARhiN3QQpDP4WvQToSxnM/El98Rbd3NSPfjbOuoIyFKiZLGApuDFyfpGc3h2oL7uupoScf4zZE+xjJzge1DPeOcHpzix/vbqG9sgQtnyrZDJqpQ7lwNmJmR+NaZ44Tjowvea1VVY23dhb9GRre3Jh2a01H6JxYG9C0peGRj7U3XtAqr0lhVacKpicULhcRqbr1jz/O3ijPQQ/bA+8zW1FEhTmc33vnTOB0bCaKlQIOIRHHvfZjc9f680qIvBwd7xhjLesQjNve2p+lM2UgVQNHn9AcfMTXvGBnJFpnM+2wAolcuITbtWN7fMxYHN4JMV8O8WSsiGiWIJqFtIyJdjSetRcF4C4hkJgj7e6BYRDS1c8mp5t1LGYqhoLl2P/fvq6YxJlBL1DESlo2lBd/b3MCbR3q5eizFhroEjTF53TWsliOfqsF6/AVihRwIgR+Nl2ZtmmPCMAzDMAzDMK6LCcDcxaSUjPqS7y5P0TOWx7IEe1pTbJ2YQpZ9qNJ4332F83wbvoYgluTD4yMLioEGkRhOZze946P0pTvY1JXl/PbH+N35KQKybElmyRaKXCp4tFTHiDlxBqaKZIoBriWp8TPg2nhY2DcznHUJsWKe4vtvEAz1z71oWSQefQbd2HDNz4ehIkQsnRPlJgghuJKDXx/uJZx+ws568PGZYS6Pxnn1qZcRv/4/CwosA0R378dL3/7UO0GqBqelHb9MkWmnpZ0gVXPb23SrCCEY8S2+vTJJ30Qe17bY25qiu8bF0Ss/Q+t2EkIs6JDK4/DLIwOMZefqHh3rn+TcSJYf72+l8fJ5pO0QDg8iHIfxRB1XhqfrvgifEcuhZbyf7g37OTc4WRqpX5vgvo40KSsglp0i//avCSfn0okJxyX+5IsUWrvKdo5prfGSNWgExYtnkMkUI/c9y5e9WXovZIl1ptlwOcc9bVXEp8s5jxUF316Z16kajyNsGx0EfHJ6gPYN24ke+xKAyPY9eImqRfnsC26U6HOv4lw4jX/6GGiNs3ELsns7+XhyWZ1QWmv8mfffgo6yO0ksn2HqnV+Q6Z07twjbIf7ECxTbN962IMzVx8aNUJPjhMJiOBcwMuHj2xF8AuriESwvhxof5bPToxwb28Tre5opBJqfH+rFCxWNVVHqUjE+OjtKPOZysGeShqRLwhGlAthAzgv5pmeCFzduRXz7BdorLmpDdO99eO7C2Vr5SIzYi6+jzp/GP3O8tG9v2obs3kY+El8rGchwtc8PdjRwtD/Lsf4p/FDRlIryQGc1TVG97Jl9V/Nsl+gjT5F997dwVSd4bN/9eFV3znXsdnAA77uvmD9CpXjhHNGtu4h3bSK4chG7pg67tRN7227yyfR1nUellJwYC3j3xMDsmicLPm9M5Lm/q4aH25NMDo0xNTa+6LO+UoxkPaoG+5Bbdi05uOfqY95LpHA378Av5BHZDKgcfm0Tw56maCfJ+FUM+/Xc61vUOczOirYA5/RRMl98CEqhkVye/BBV38qOB57hwFDAuWLAhZEsL+9uoTOx+FyjpU1PJuTg5REyxYDO2gTP72rjyJVxRjIFIrZkd2uKHQ1xrBtMNXY9Aq0JZmbnmJSZhmEYhmEYhrEsJgBzFxvyJL841EtxXgDlw1ODnMlleWnrXuxTi2sehJPj2L4HToRsIOgdyy96T+BEEI0tnIkk2fDs63x0sBclBGiIxSJUR8Aq5pCZIl4sRdKVVEUihEozqS1+d6SXnS1pnuiqWrFaFTMsKQkOfrow+AIQhmQ/eZdk5wawImU/e7sEwuaTc4OzwZf5Lo7muNzeypZX/hj/5JFSXvpYHHfHPoLmNoJV6C7zhCT2+AuIT9/H67lY6lQWEre9C+fRp8lfRxHs9UAIQX9B8qvDV2aL2oPPuycLXGhI8tymaqx1GISJhD5ydAg1MY6Mx6GumWIszrnhwoLgy4yCH/L15Qle9DxkGCCicYJonP6JeXWftCJUikkZoVj0+eHeNuIyJCY1SvnYQPGT9xYEXwC075H74PfEf/gX5GOJsu31pMR96AkSnd1c9h1+8c1lQjeGbO5kAotDPeNcGsvxo91NRPEZyBYX9OuF0sZu30DQ10MuX2DCrSNq2US37ULsvq9ip1zBjSK378PauhsB+NKqOHtlJTrs73aOEHiffYB91cwMHfhkP/w9idf+vJT+5hZyVYg9Pkw4OoKMRqGuiUI8eUN/WxGN0TdVZGy0NNsqLzQFz2cq79Fek8CJx9HFMaZyRXomipwbyeGFilTUJhpx+cdvrrCtuYpzV8aZKATkvIDGqigNcWt2Hzw/nGWiq5Xq518j//G7hBOl3044LtHd96C6d5RNl5l3Y8gd+7G27QHm7dtrTFT7PNASZW9znFBDzAIdBisSx9RaU2zuIPnyH+OfPFyaHRsv1b0LGltZf2f21SV9D39ROjxN4dwpRCRKZMsu7Acfp2C7pRmE13lM5ZTFJ+cGys52OnhpjF0taQYLCmk7qGBxMGKqEKATVWWP4VK9miyMDJTSXFbXoGrqKVoOoVI4+x/EViEyFqU4meXC4ARuUzPi0Rf5OhOhMJznwvgV/mhfKzV2aaeMjA+T+ewDZgJRuVCTLQSonovU1h6itvkeRnMeSsMn50Zo3du48D5CWnw7kOfTcyOzLx2+Ms7xvgle2tVKU8LCQuOKEKVuXfDFMNabohLkg4UXh5gtiUhzb2YYhmEYxuowAZi7lLBsPjsztiD4AqCF4Mp4nit1DWywnUWzLGQsgXbcufWUT3WN1qClZMSDVDxKTTJGa9IhPXWJwC9Q7O/BbmyhZ3QAOZ32x4pGmYrXofKKo70T7GmpomYF91BbCGJjw2SOH8LWCuVESoGhGUrhXTiD3LLnlqQ9u15ZXzM0tXj08oyzw1k6N9TDQ09hqRAtJPlV7izLR2I4T/+A5OQ4uphHRGL4qWryd9BzTigsPj43PC/4MufsUIY9rSlaV79cwrLE8xkK7/12QSFgGYsT+/6POTFY+Y93YTRLrrkN98JpIjv2kLt0iTCcd64QAoREbdzOmcEpOmtibKuWs4Nm3clxcpfPYwU+wpILjkXte+iBK4iN2yp2dHvSRnRu4fOTo4StG1CiVIh7plduLOtxYbzIjhoLUSYoGTgRZGc30ividDaT2NSOl0wTXuM4UkqhZtZX5r2+sBnKKyYLAUnXpiFuERWBCcbcADszQbbnInaszEEVBOi+HsSWXbfst415BbwPf0+hrwfhRnBbO7D7ekg2NhM2tVGMV11zf5kvm2okK12EkCgpF8wcnXKT6HQDwp4CKRktKC6OlgKabbVJ3jg2QHd9gvs6a/ns/CjFUBOzJZMFn3TUwp3ZxQWgFPm6JtxX/hhrYgwdBpBI4SWWbu+19u21QimFg8LhpktbLF631uTStViPPIMVBmhprfq1db1SjoOMJ1C57KJlulggzGVQtrPsQN94ISTvlf/DKw1jOZ+LYZTuzVuYPHFs0XuElFhdmwmu+l4pJdGBK+T+8DtUYW5gkV3fSPzpH5CLJijYLvbDT5N6+AlGL/YS90BHE6jsBE8l8kxFqjiatfjmyiTPdVchgODMCUAjhMDXgpwfEos4uJaAS2fYvnEvB6bHLoxmPSY9Ftz3TgaSLy4sDEIDBErz9vE+/vzeNiLCX5SOzDDudvlA8bsTC9M1f397PRF3rczrNAzDMAzjbmMCMHepbCDoGc0tel1rsGrqODmSZVN1LcH8AtVAZPe9FIQErUlYmvaaOJfKrEcJSXU8yv/+4hInBzMIAd1uQL465L4nXyR842cE0kaFPqJYwInFaXj+B5yRLt3VistTAYMZj5rq6589Mb/A6dWigUf49Sf4UhJMF+yWsRh2czvBvICSnppcVGT1ZkkpyYYWRaVxLUGVpa4R4Cl1GVd6nrZkqX1hGBLCmklj5Gvwq6qhqrr0wh3WIZDxYWCyUHH5ueEcHV2JVQ3eLYeDpnjg3QXBFwCVz1H8+lOc+gcqflYCVk094dQEkU3bcQNg5MTc8miM9KNPcDBIovGZf0hFAw96zhNcPI2wHZyOjbjJJDoSozg2Clqhy3TazbAsi2woyfmSi2P5ilHgkwMZdtfX0pS0kWUOaYUglkySTFeRxwelbqrQ+5Ry+O2xAUbnzRpKRmxe3tVMvXvn1gm6ZXxvyXObyk7dsplGMzMl/b4eZDxBrGMj+QPvUxgZBClxN+/AvuchrJ334l2reDula9NZ3yH+5Etkfv8L1NQktiVJxWyiiSTBEy9wuQCytoFSfFeXisIrRahhS2MVxUDx/35xif3tNVwcHcW1BK3pGL4C1wKEoKu+Ch+JFBLpSIo181JqmkDCdStdW4X5zW5CICTRXfcSfPBm2eXurnvI34KoQaA0NckYEzseIjY6RmGwDyjFJoWQtD33PKq6dtHfNpKbIvv+G+jiwmt8MDxI8cD7OM+8gg+EWqPqm/nodIZd+T4K7/2G4uRkaZuiUZ64/1GOFzeRDyUJW6MyEwghyATQM5Zjygsp+KV7hGSkSGfKRYzkZ2+Xrj6bjOT8RbOhpYCYYxMoxXghJB5biV/OMAzDMAzDMIxbyQRgjEVULIGIRGHg7NyLQhJ/8HGs+iaiY8PgOPhV1TyyoZaBycLCmTQC6pJRRqbySMC1JK4F/sgQ71zMUPfABhoeeZZUXQPVF3uI1dZS09bK8Nmz1F5+n4ZonJ0791Hl1LL4cXQxKSWZ0OLKhMdkwacuGaE9CqmJfrTvI2vq8A99QfHUMaKbtiGr0qipCdT/n73/CrLsOvM70d9a2x3v8qR35b0HUAXvCYIgQbKboOl7NS2pr/QwUsxEzH2ZCOlhJiZCmpm3uXFvSxEKPah7WupmG3oHggQJ7wso7016b44/2611H05WVmZlFlBwRAG9fxEVVbX3Odudvbb5/t/3/xoN9NgQxsBmwqUgmtHV+4lar/jC4t3xGifHSzT9EMeU7OzOcmdvCvsmXt1pS9OVjTNRWmvvBrC5mPjcBPkjbk+klMQX5/ASaaxN28CycWcmCZfEmHBylF1b72G0staCTKLZmrNJqSbGl75O9fXf4xw6QmHDXoKJUUQyRTCwlTfdGJNVHymgM+UAPoaUhEdfA61xtu/FzLfhnT2BN3wFo6OT1MF7aExPIgvFdQPrgTR5d7LBe6OLDLSluTLfJGZJOpI2xg09oyyjpbrkbMWh/jwvnl0tFEsB929pIyFDAm0y29SMlRoYUtKXi5G3NOIWU+yVNPn1mZlV4gtA1Q34xekpvnOgC4fIHuZDEUsg7JvbQRrFzpZ10aeAXStTu3K+tRkDG6n9+ifoZgPhOBjxBCzO4b/2O2K2g9p1EFSIVSmB70Ms3qo2WXGN1lqjlOb5Zoa7vvb/YHNlHHNuCiUEdWExdekM+++4k1EvS9kNycdMNrUluDBVxjYkSdvk9xdatpmmAYP5BOOlBmOLDfIJG9+QNLyQtoTDO2NV5moebUmHnR0J2hyFVNH9IuIPi9aasG8Dsb130Dz57nUxVRrEDx0h6Oz9SMvNxQwStkF9nSqYUEhKXki56fPSqM+evY+zzyhjTI0gkIQdPThtOazZSVRbJ6HWmKJVkSmnx0kMbiLwPLyxYbTvYRY7sAtF0GAtzqIKHSitEQIOmjVmfvMz9IpxHjSbLLz8PHu/kkbKYqtaq7uP2vAwI/M1Qq2xDbkswOhkhnMVRVcuzsRig450jLQNN2t/KAVs6shgGAbTFZecJdHSWMpBiMTCiIiIiIiIiIiIiNuZSID5R0rS1PQVEgzNrWMPgWD7lj5i2zLo2WlijoOVyuCdP0XlJ3+N9j0wDOyBzfQfeYhnDvRwfKLCyEID05Bs78phSMF0pcnOrjRKCKYWayjfRwPHp2scnJkmSGQ5kRnkkBNy/q/+AhJJtBDAAnJinMGghHnnPShpYNdrEPooJ4Zvx5ZFEiklY3X45enx5Zdao14lXpnj6S1ZcsdfJLFlB/6bLyHTObypCWIHD1N/8bnWvnoeNOuQSCETSaz+DWj/+ouslBIzDNBCEAj5obKthWHwypUypyeuNwB3A8V7IwvUXJ/Ht+QQ4VpneaEC7t9U4McnJlbZ1ABs78rQHpO3TdXLPyZSFnRkYkzfpApm0+dEGJNC4Ixdpfb8z/HOngBA2DaxQ/dg9A60gk9uk42mS/dKIVCA2WyQqM1zYMMgw9MuVW2Quu+bdMQkfsrnddGBa1jU5hUsdU24Y7BA1lKgwK6WqF08i71hC2a+jdovf7C8XeHsFP7IVZJPfxc6etZst5AGb43WeHek1TdGBQH/ZGuSSqVOwwiZ0g7l+nUBZHd3miAIEEJw/+Z2Mpbi3ZFFam5IW8rmQG+Wzji4WvL8pQUuzVSvr2tpu+/sid9S8Hre1Tetjqo0fWbrIb1RlvKHwk2kiO3aD+dPrplnpHPoju5Pb+WBD0HQslCanUY3G8hEEqkVwegQwjTR8QTqF39PNpenMTpE7cwJUCHCtlvi4t478Mzr1ZVdaZumHzKjLFJj4zTGxlhcLJO2JAnHxJ0f5ekvfZNTRoGBnE132mJ0oUY+YfGLM9crUV++NMcTOzqoeWnOTFewDcmmYpINbQneHVnkzavzJG0DE83rSYe7N+S4rz990/5UphBY9Wqrb1M8iS+NqFor4hPBkwbmwbtJbdmBmp0BKZBt7bipHOFHPMcSMuS+zUV+e3Zqle1WiKQ3m+DCZIm5qst9mwq4fsirwxVs3caGfJwt2sV44WdUA4/kQ09CTz/Ba7+neuUCxvwMwcwkRnsniXsfQSMJr5yj/tYrLTHmzHHMXfuxD92DZUiyY+eYXrrfO6ZBztCYKAIk8QvHyO7eShCGmINbaLz11vL+GqL1eTcIiR08zD9cqfLlHR3MVlwe2NyGocNVxcNtCRNDCpTS7O4t8PLlOUYXW/dkQwpGFxt8aVuR7XkTHQmtEREREREREREREbctkQDzjxQdBtyzIc9kqbGmD0xvLk5P2qKuM4jBLLn2dmZ//g+4Z49f/1AY4l05j65XaX/86zw0mKI+kOP4RJU3r85xfKKMUpps3OLLOzs5ZwpqtRS+aVDXBp3tBRLj53jkrseZ+MHfAJprPkUC6MzECM8eI7VpM82LZ6lfPteqZkmlie27i3DjdnwpqSmDZ89cF19M38UfH6aiNc9egWf6t6J9n2ByHFMIQiEIs3kS9z1K4+gb6EYNPBdr41acex7FLHbCxARCCOLVRYJzJ/GXAm7O9r0wuJnmiqDa+7HoCc5Oltadd3G6yp39uZv2uOmMaZ450MOpySqjCw1sS7K/J8NA1sJQH78dsJQGgZAEYSTk3CqGDrl/Yxs/OTFOcIMlyOb2FJ3xz4cwFivPU/3dLzHcZiulVmm059F4/QWSjz5FEIujmg1S2uWpHT1cXnA5NVFG+B6bTI9t+3fy66OXmbgyDFoj01naNm3kS4c28mguzzujC8zXPJKOycG+HP1pA66ds406hAGWZdI4/R5Ge2er6kaFgEDG4vhDlzDvuA+ksWq7y4Hg5PgiAHe1WXRdfQd7+DyNiXnSsThb7zrMaMdWji/4bCwm6U1ZsFRllrBNBpMwuKuNQIEpW9dAieTsbGOV+AIt97y3h+bpzfbcknDS9N//d695AcRv3U4xotXrg92HcByHxrtvtMRyBFZ3L849j9KwY7fcuPvDou0YwokhE0nCmSkwDKRhEIyNtj5gxECDmpvGO/kuRjq7dA63RP3miXeIqRDjzgeWl5m1NPdsaiM7dZXSuTMIoC8bY6LcpOJ7UHHJvfQ84T1P4wYJ2mzFMwd6mKmHpBwT0xA4poElBS9enCEbtzjUm6Mz7WAKxdhCg5NjiwxYAXp+EuW74MQ4HXbSk46xNbc6gUAIQby8gPf2K9TGhkErzLZ2Ynfci9vVj4pEmIhPgEBDkMpBKnd94sc4t5RSbM2ZpPf18u7YIvM1j5Rjsbkzw5WZCnN1n2IqxmK1yWNtmrGFc4RaY41MM7owz4Jt0peL0XzrJRJ778C9fK61YKdVbRfOTNF87QXid91H7fg7rXlSAhr3/Cm020S1f4dYaZakbRIXimRtHn9hHhUGpHI50maAOP4W/uULiA1bsB/+Ksnf/4baVEtIzWZTxA4c5ndmN67vkkvYPHOgh4K11qoyY2oObyhwabbGmanqsvgC0Jl2EDrk+XNTtN/RR371LTMi4h8FUkoWvbXPYKGOer1ERERERERE3F7cVgKMUoq//du/5aWXXmJxcZFCocBDDz3Et771reW+HH/+53/OCy+8sOp7+/fv59/+23/7vsv+1a9+xU9/+lMWFxcZHBzkz/7sz9iyZcunti+fB4q24lsHejg+XmFkoY4pJbt7Mmxri62yxwpmJnEvnFp3Gf7UOM7CLH5HLy9fnuf8VAUtRMtmQYWUGj4/PznBk7u6eL3cRYkSmzracLN5YldP0D43hJRNFgs56kpgm5JCwiJhgqEC/GNv4c9Oo/3W9qhqhfqrzxP3PeSug8xUg2UrCiEEqrSw/HI/t1BlfrCHVG0KhCScm8FIZfDGhpCZHPFHv4LQYA1uxO3ZQENIckv7FS/NU/vVD1b5gQevPo919SLOw0/iGtYHHt+yG65pjNqTtthtucTqJTITPvH2NtxEao3tmVKKnKF4oD9BOJDCALQK0R9TfBFSMuMKjo9XmK64FLM1trfF6E0ZyE9A2Pkio7WmO6741sFejo2VmSg1sAzJvt4sm/MOxk0s5W4nDMMguHAGwgAsG7u9C9WoARIEuKfexdp3F8HCPLrQgYPProLB7o5OxMXTSG3w9y8fY/TKKNe0O9moM10t86w0+KM7+nlqax5fgyloCS8rzyvHQVg2qlwiXFyAWBzRM9DyuBcCnc7hugG5yiIUOldte9VV+KFmc9am4/QrLF44iyEEfbk4zUDRePtVdhxssvXwIxQSJuY6v4cOg9ZYWkoU9rTBibHyTY/XsbES/dvzqHUq1VaStI337duUjVlAlJ38YfEMk8KDT+ANbIFGFUybIJOjrvnUxBcAL54ktms/3qVzGJksMp7Em50hCFq9WQzDRCCQjoOqVQhnp1s9kRau91NqnjtJasc+oKs1QYUc6E7gXxhjLGZhGpLFho8pBQbg+pqF4VEyd1b5yamA7x3oIC18Mlmbne1JYlIwW67jBSGWZZKLWyzUGlgGtCcszk1VKPoV3Mnx5W0IXA/Pq3M8brDlni0QXh8TsXqF+rM/RDWuW/MFczMEv/kpqS9/k3rxU6wwioj4OKiQrhjL9xrblLw6VCYTtwm0YLTU4M6BAtMX3mP+9CkCpcjELAzREsMnyi4bVICancKo10ArpGVhZLKE5RJ4Lmp2GmHbaM/DyORQlg1a4w1dJlxYwEyn2ZCLEUyMUp+fwwDimTS28ghnJgmGLqHKizROvcfkgSJX9j5Cfn8IYciineBy4NBwfbZ3xNlacEjgrX9JUyEHOuN0ZhP8/1683LL0NSXFlE3SbPU/U8CVuTptXbFP1EI3IuLzQNNX/PbC7Jrpj20tfgZbExERERERERFxc24rAeZHP/oRzz33HP/6X/9r+vr6uHz5Mv/hP/wHEokETz311PLnDhw4wL/6V/9q+f+m+f678eqrr/KXf/mX/Mt/+S/ZunUrP//5z/l3/+7f8X/9X/8X2Wz2U9uf251rQf6HN6TwBtJIASYKpVYHLnW1DO9jraRK85TzfctZ5EJr2lMOIwutwE7FU0xXPWYbAUqadMQlf/3qBe7cupGH7CZJAxLZGHophKm1brWhd5uEzQarOngv0Tz+NolN22n4q6tRdHN13xRPCfxKCXvjFryrF1qNVw3ZejEuLyKcGOLgEbylxvfQsmTx3n19TTNWAH98GHtyDNG38QNtWswbOn/vyltsHj5G6cS7NJUiW0giEzaJex7GG9y6riWHUgqBupkl+IdCCMHViuZXpyaW19XUBufH57lzsMDhnvhyFnfE+mitaTMDHt+UxlMZDAlShejPgfgCrXMgnJ3CUAo9PYFfXoRGrWUraFqYfRuwO7qw77qPspUg1OBIjRH66MtnmBncx5XLo6gVyqIKIazWWBibYG5XL92xsHVjWWd4BKkcZnc/BC4aQbVcI1CV1rYZBjpRYGauzp5w7Zg3l3q6bDXqlC+2spZDrVmou1hS0p9PkBw/T1Idoq4zt3Q8Ag3N4ObnfM0Lb2ns5R0YLCa5OrvW0rGYcmiLyeuqT8SHQkhJM55ExxKtCX+AwgylFOw6gOV5CKVwz51FNZsIQ0I8SdnTGDKkY/8+3MsXkI6DLLSvltiCAF1ffT4IFRKTmv6sTUMJ5moeTT/Eu6ZmCkHQDDg+UeaRbUUG4mCGLkcyIZNHzzAQixMaNrIZYhoppF1gb3eWK7NlbOVTnZ5cvb6lv6sTE9DsB6tVhSWlRF29sEp8WbHzuO+9gfWlb+LfcKyllLi6ZVEWMzTqc2C5GPHFRaugda8JJfl0gv/y+lXKzQBTCnpzCeyGhwZMKVl5R6k0fdyYwCktEIxebU0UAjOdwWwrgu8RluYRiRQyrhHtnfhaIIVAolGLc9g796HOnUZXF0k7rdITMxknGLpM4uEnaZ4+hlHsxEUSW5jh9LhiLtvDjAtQx5RNNrYl2NedJiVD3k83ESogIU36MjZKtwpX0XqVCF1pBsuJahERERERERERERERtx+3lSfK+fPnufPOOzl06BAdHR3cfffd7Nu3j4sXL676nGma5HK55T+pVOp9l/uzn/2Mxx57jEceeYS+vj7+5b/8l9i2ze9+97tPc3c+N6gwxNQBUgXrZ8/d0AhZCIHhexjNRuvvWCsDPVwRlE3bgq5MDEMK6l7IQsOnI+3w1YODjDfB7N/Ie80Y1U17oHcQpTVaq1bjViTzTUVlsUIt1cbQVImGkquEGO02oVomH1tdibKyabOUgpQI8SfHsffegdU7COL6KS+cGMlHvoKbSK9ahtmo4Y0NL31I4ipJPRR4WoKQ+BfPYBgf7PXQFjNIOS1xMGEbbF4cYvHYO2ilMKUkZgq051J76TmchbXZW580LiYvXpxdV+g5OjzPgh+9vN8q18aMCIPbsl+CEAJbhSRKc8QXZoh5LTFRa41RaEPPzxCWF9GAjicRqSzCaVk6yf7NvF6P8/3j0/y3dyf55fkSi8rGKHZTWWxZ6kkpWBnR0kLQLC1Sb3rrbM11fMA58gBGRw8+gmDpeiMME6tngFlfIOJxroQxhLFaWM/HJIWkjVlZXFP9oLTGkqADH11d3/ZvPRypySdubinYk40hb8VWLgx4dEuBjcUUK3XX7mycp3Z1rFuNE3H7YKFJVBaJz08Tb9YwpMSVJuquB5nesI/U09/F7OgiiKepKoFGY23aDsVOwtkpZDaP9tw1yxXW6nMrDEPMDVta97lQ4yt9XXwB0j29nG+YNP2QkcUmhmFgjl6l5/RLPLijBzvwkJUFqJZxKvM8uSlDT8qk7gX0JIxV929TCuKWgdbQlo4Rq18fF1IKguErNz0ewcw0RnO1ONPA4q3JJn97bJK/fneS5y6VWQjMKOgb8ZmjhOT4WIlys1WpGLeMlriZ76TuK2xDrrouC6XQdgx1bcyKljgaLs4hACOTx+zswejoplbs4cJiwMXZOlfmm5Q9jTIt/GIX8Tvvblll6iVVxPNw9t2BCgJUpYz2PaqeYvHdN/nKpiz96ZX3NE13Ns6RwSzqFhJf4qYgaRlI9LrVf93ZT676RRoGVW0x6UrmfKNloRkRERERERERERER8bG4rSpgtm3bxm9/+1vGx8fp6enh6tWrnDt3jj/90z9d9bnTp0/zL/7FvyCZTLJnzx6+973vkU6n111mEARcvnyZb37zm8vTpJTs3buX8+fPf5q784XBKHZiFooE87MYYYiemSSolkBpRDIJ1QrpdoUpxXJvDKE1bXFJykkyW/PY35PF9X2GZ6vUPAVL2czvluGhIw9Qff4XoBQKyWipScML2br3EFOT05SbPpVmwGBbguQK3UOYFm0xQU8uzvhioxVczhUIS60m3dv6imQnL6K1onbuFJmvfgflxAgX55CJJBQ6aK5j/9V6udX4WjJealJzAzQgEHT0dbOhoxtRmsMyLLxk+qaN1x0R8JXd3ZwcmqEvbhC+dBZoNUHvzcWwhG6tSin88ycx7nn0U23iXnIVleb6gWClYaLsUiiYt6WgEHHrSCmJzU3SfOV3NJeEPRlPELv3YUTPBmIbt9H4xT+s+o6WEpBYew4xenmId4JOkrZBZ0KgURyfrLC70Is1MUGgFFq3sooRLVFHOg7NEBKOyQeVKNRjSVJ7DxEvlfBffxlME9eMMeYLAq3JH36Al2d8il2CxIrvWTrgsW3t+DdYTQgEvbk4lrgm5nywPeDyd1XA4cE8PzneWN5qiUYEPpYU7O1Mom+xr09M+3xla46FwRx1XxEzBYWYQISR+HK70ur1VcJ99XdUJ8cAjbBtnJ37MHffQQmLfxh2ycX7efpP/nusi6exfB/SORbmFwnOnCGTzhK78z6C+TnsYgdBtYw3OY6ZbyPM5tesUxU7sfo2YI4M4wYKJ50m19mONEzCPXdy4morKBwqjVYa98Q7MDPF3lqFTdt2UjISCCDnlshcfB197xNs70iT9E1OG62+Xo4h8ZWm7odIKdiScxiZmieW7iAtfUAgHGfNti0fF8ta1YNprubxs1PTTFeuV4Wem6pwZbbGH+3voc2KArQRnx1lH2bKdboyMSbLTRp+SC5m8dKExZcPHsI/c5xr9yUpBFlbUDhyD6LZQNereKePo5aEfb/ZxNl1AJkvMn1lhInyChtapZgMEmiRpiBN9MAmkk99C2oVQGN19FB/8yXc428DIIRkoe4RegHuK8/xlW//U7YOdJC1JAkZMuO2hNhbuWPFZcgdg3levDCzZl7SMenPOp9IJW4gTN4ZrXF8rIS/JA4PdtS4dyBFwbw9E04iIiIiIiIiIiIiPg/cVgLMN7/5TRqNBv/T//Q/tSwylOJ73/seDzxwvZHtgQMHOHLkCB0dHUxOTvLXf/3X/Pt//+/5d//u3yHl2oKecrncstrK5VZNz+VyjI+Pr/k8gO/7+P71FxkhBPF4fPnfK//+oiOEwEimiD/4BI1f/5jw4hlUdckyyImRfPgrVI+/Q7peY0fnPk5OrOinoFtJ8qFSeL7PmaUG2iupNgOCzZtJPfUtvBNHKU/PoEWK9K4DlLt6WPzbv1halGaq7LKxEENohVnsJMzkMAn58vZ2Xroyz+WZKqEdI97bzxbH54hdRQ+NgpA423YRdPfhGhaio6cl1gCxyiJ6YRakROSL6LCdMJnC6h7g8olzNPzrgaXevXuIzU8w/8JvcFJJsEycbbux991F01ybRR9v1um/cp62i+fRgY/IxqDvDryrF3FY/SKrFuaQQqA+xHllCoFVXkDXawjHIcwW8MTqMSANA08JpAApbnhxFiv+1i0R5vN4Xt/KeF3578/jPn4YYpVFar/+yaqMfN1s0Hjt9zh33o/I5kjd/zj1V59vZQBrQEpiew7StBPU52Z5YkMbwdmj+JPj5AtZprq3cbGjn71xi8Gedq6OzRAsVXJJyyIwbdp7OsgnYwjdREqJp+UKW8PVIoZrxji26W6K6R68U+/i12pk+oq07ztAKZTcX5skVzHR6SzBit+rM6YRmweJd+SpVWvYhiQTM3Fky7pQptKofNuH+t37koIndnbx6pU5GuUywfQEecfgoY15ci/8mNju/bg9g7fWlFyHFCwoWNAaVKxrofiH4nY85291vK78/6e1/TGvSeM3PyUsLy5P055H89jbxKWBue8+tNZMll1ezefZZKapXjhJ4F4GoGugj+zDj1L93S/wR66CEFh9g6TuegCxfS+NJRHj2vYnQh85PUFs225iPf3csVjFn5kgHB1GZ7JMTY/z1Z4BXl8UaKUQvk+YzhOk27DrJeIn3yC+QhAMcgWs0GVP0UE0Ar511wZevjDLzGIVpTX5TJIHNrdhnHmHmSNf4vjpKb61txMRBsR37MMbubrucbG37MSPJRBKIaXk8myV6epaS04vVLwxtMBXd+Tf16b0s+Z2HAcfls9iHz7Ms/BneWxD1XLX29+TZn9vlpmqh21K5n043rWPe3t6MM8fRzfq9HbkiHd2U3/pN7A4jzAMEofvp3H0DcKZSWQ8QfyBxwlcD+OGdwozFiP+0Jf59ZjLV5MJnFSW5vBllOchpECksnhXLgAgTBNiMbTbeoY0HQdhGNxdHYITbxJWqwx095JL3otXaFvTL/BGtNbsKsYIwiJHRxZo+iEC6M4leGRLG0kZoj9m03EpJUcnGrwzvHB9ooCZqstPTlT4zoEeEuL2TigwBViVErpWRdgOYTaPJz+4Yv0at8P5HBERERERERER8cXkthJgXnvtNV5++WX+x//xf6S/v5+rV6/yX/7LfyGfz/Pwww8DcN999y1/fmBggMHBQf6H/+F/4NSpU+zdu/cT2Y4f/vCH/P3f//3y/zdu3Mj/+X/+n7S3ty9P6+rq+kTW9Xkhu303MdPEPfo64fwMMp1F5vL4E6PEhYZLZ3hs/z0Iy+HyXG3ZIaFoGTy4rYNzU1USicSa5e7obaPYkYeODvT2PVw9N8poyWe0rknVBIcf+hKLLz+PVqrlRy8tktkUyS99Dbund3k5Ax0FJisubhAStyTFoIqeGkN1tyPsGMIwkL5LttCGkUiiGnUab7yIe+pdrplva8Okecc9tB26m9k77kedvYq5tB+5gX5iYxfxhi7jdvZTkCYp04TL5zDRdD7+deSKjOJgZpLqC7+ESokEoH0f/8xRZK6N7JEH8a+srr6ye/tJdXTc9Ph7QchczUNpyMYt4o0y9Veex1/qa6MBo62d4kNPYvUOoLXm6nyd90YXGVtsYJuS7e1pDm5s/RYrScRbv8uWrgJdxeQtnhG3D7cyXlfyRR+7tZdOETcNMK+PNx0qwulJgl/9gORjT+FfPEvyyIMt2zEpW8JFeZGxKyN0H76bS7/8BzzPx5KShWqZuRMXKBw4yMIdh3l8O/zWdhiZnEMbFpgWhbYcT929g85CmoV6jKNji5yfKqPQ7OnOckd/gWJqdcZ9sW7w+0VN372DtFuajDfP0K9/QdBstKz7LqWIb91F/L7HMNLXe7porcl+7WnqLzy7Ouhr2SQf+xpO/+DypGBuhmBqnMbEVQrZAkZXD0ZirWVldxfszEimzi0gi23ka3PYl94C30O99jz5L/8R9pYdn+Cv9IfldjrnP+x4hU9v+5sn30UHHqxzbxJXztN18DDbe9q4OFvjigvuxsNs27QbuzKPsEz6sg7ua7/BTCQxegfQvocQAnXpDOlDR8gubXdXVxfupbNUfvhfCUaHEEIQu+9RrOEhFudKTDQ0lbkZuDJDT1c7//0ffY8xGWdM2byl+qiVyxRSRQ4d3kfvyCnEYqsKzOzqId3ZhTBMdBiQmR5hsE8z3N8NaGKVOdxjr1B44FGu5jsZCBQN4TDY1U6YTWPOTOCdP7Vqv422DpJH7sdsu34/+tUbQ8v3iRuZc0HGMnRmYp/Qr/LpcTuNg4/KH3IfPsxY/SyPrV6sc8emLo6OLLBQb5KOmXRm4nzvzgF+eXqSX8d72XPvZu6INWi88xLWibcxRq+2np2kwD1zjMw3vkcwNd4SzOs15s9fIP3oU3RUGvjzc8hcgWqhm9fqDg0/pI5JfnAjiSeepva7X0IQIOtVkofuxj3xDmZPP0YyRVG5zFQ9dnz96xjnX6f8079HCwiQiLPH8M69R+a7f0Z8/523tK+9nZq7NnVSavpYhqAjHSNu3brA8H7MVJucnyut+6yuDZs5T7J5Q/cnsq5Pg7C0SOPV3+FdPnv9uTjfRvHhJ7H6NnyoZX0RrhURERERERERERG3F7eVAPNXf/VXfOMb31gWWQYGBpiZmeFHP/rRsgBzI52dnaTTaSYnJ9cVYDKZDFJKFhcXV01fXFxcUxVzjT/6oz/ia1/72vL/r2VCzczMEIYhXV1dTE5O/qMoxRdCLO+vszBHffgKIhZDT02gb8ieTU5c5cH+Lextj1HxAmxTUowZjFUC3qjUaCpBdcnOK2kb9GQc2qyAiYkJAAzD4EpNcXKqVWGzCHjJbg49+S3MkUvoahl75xZE/wDzdgK99L1rmEt/CGBBCGKeT+3V36ObDWQiiTBMZLaA88Bj6IlRam+8tGZfefMlvHiK87EuzMe/gXP+OO74MG093TQvncRt72W6HhCP+chwqd/FqeOEW3bTyOSX90MefZ3m1MSqZctMHnd8BGN6EheButagWUpk/+bl43DjNi0EBq9enmdovobS0J6KcW/ao2dsBF1dIabUh2j8+G+IPf1dhsMYPzo+sWwhATAyU6KYSdCVNLg8UwHREl/qjTp7urPEwjoTKyuYbiO6u2/+0v9+4zUIglXTv+hj1zRN1JXz+PXV/RvMehU9PUGAxmo0kV09VF58DqTEGthMYNsIIUn1baJ2/B0C10WpVglbzVMorZh99x1iW3cxZha4e5PFvg1FaoGgvT2HiCfBsRmZXuDvjk0yXnaZrXoESvHqpRl2d2X407t6SerrVTnttklMhJyaqvGVgs/Qz/4OrRSGELTFYzTrdZrH3sZz4vi7DqKUQghBTZnMO11k7/kazuQV7OoiTrEd2b+RxXQONTGBlBJncoTa738FbpN4PE6j0cDs7MV56Ms0nPiq4yOlxHjvFbInjgIQLP25hv/6i8hUluBzdtp8Vuf8JzFer837tLZfSokxcpVmfZ1G9AD1OszMsKeji3Pjc7iB4mIdLgJS5NibTdJ9+veope+LVEsk1FpDo4E69g7KsOno6KA6MkT9//6PuKeOtfos5Qr4Vy6gjr1Fuq0bWeim7mukEITNCvrccbwth/nBu0OYgcRfKDO3UObSqOBLe7ezpTSPqtdIbdrB1MwsDW0yWfXR6UH6tIN45RXCSgk6OrG/9j3+fqTBifOXURoO9uf46o52epNg7b0Lc3Az3oWz4DYxBzcRdvYx44WwdD+yLAtDQL1RX9dd0DIk1WoFVVtYO/M24Ytw7f+09uHjjtXP9NhKyXhN8OrwIr86M03dC8jGbfJxi3dHFvjmvh6+vL2dvqyDoRWp946iFiYwhcZXChkEqEoJ5mapvfxbsB2M3gEaVy/i1ypMnz7DO5vuo5bvxPVDvAkPhEcinsBtNpmYmEDkOog9/g3C4Uu487M4d9xDct+dNM6dxG80KGwYIN+7GateZu77fwGqddws28ZKpvGmxin/8gc0C+00TRshBEIItNbvezyTAAEsumUWP6HDOe8bzJdXJ+isfE68Or3IhkTwqVrlflQMKZBvvEjzzLHVM+p16j/6G+JPf5em/cEi8e1+rXi/8RoREREREREREXF7c1sJMK7rrrERk1K+70Pw3Nwc1WqVfH6t1zq0ApKbNm3i5MmTHD58GAClFCdPnuTJJ59c9zuWZWFZ67syX9uWD3o5+qKhtQY7ttTk+iYWBLaDDn1yJuRMgBBUSH/G4p4tHfz85ART5Sa2KenJZNjTk72+bFr9erYUE5wYW1xe5HQt4Fc1k2xxD71bEwxuyFIPveWqlZsRq5Wp/e4X6Eye0q57uFpTNAJFT8pmy9wC+sQ76+8j4J56l+w9T/M38wadG47QtfUuutQc40Yav9lar7HyNNUKXSmh07nWPLeBd/n8mmXrdBbDd/Eun8XcsR+vXkM4MRL3PkIz17bu+VRVJj88NkF9RRPU+cUyPzl2ia/vP0R35XlYEbQMKyWCapWXJ+qrxJdr2zBTrnNgVw9BGDBX9SkkLe4d6GRzzoLQ/4DuHbcntzJeb5z2RR27LRuuLDC2PE1qCOdmkICMJVp2S8VOnD0HcU8fQy3MIrp6kR3dpPffwYW/+a9oBEnHxDElmoDFRqvnizExxPnsTt5smPTaAY4hsdPtZBxJf8LgN5cXGVlsMlO9LrQopTkxXuKN4TQPDyQRqnX9sPH56s52hhY9Yu/8DhdIxm2KSZuYoZer6Jqn3sPZvAPPcphqCn52aoyG1woApZxB8u1buX9zgYIZopcCQ3a1RO35n6M9b9Wx8SdHkW+9hHH/EwQrzgGpFMH4yE2PazA7RbzZwL+FAM7tyO10zn/Y8Xpt+ie9/UoprOTaaqhlpATLomCFPHOgh3fHygzN1zGlYHtnmiM5CF6fvOm2B2NXMQ4cAUAMXcQ99d6ygGH1b8S/eBYqJWxhQCrLZNMANHHbJDl5hXpxa2s7EymM9k7C2RmUVrx8cYa+jXvIZZO4bZ0s+JKfnpygvNTfa19/J+c2P8zGjEmxmOe/Hh2l6l4PmM5WXX5ycpyv7e1joRpSbibp2n4fvRmHOH7LLnDFvvi+z+7uDGfH5tY9TBvaEiQMjQ5vj/Pr/bidxsFH5Q+5Dx9mrP6hj60QgqtlxdCiy+/PT2NLgbZN5moepYZPTzbGq5fn+NO7Bogbmnbp40+PgFaEtoPZ04+aGGlVvGhNMDlG8qlv4fs+4ew0jiExMllqXrC6d54G25AU4gZa+2itqSczyN13IKWkoRRaa8xNOzADH8v3qL72AkoFoEKgZQlrhAHCbaDjcfyhS8QX56kX+hgte8xUXbJxi4FcjIzxh+u7YhliVS/Ha/t77e9MzEQt7d/thlWtUL9wet15qlaBqXF038ZbXt4X4VoRsRYpJYve2vfHuClxZPR7R0RERERERHy63FYCzB133MEPfvADisUifX19XL16lZ/97Gc88sgjADSbTf7u7/6OI0eOkMvlmJqa4q/+6q/o6upi//79y8v53/63/43Dhw8vCyxf+9rX+PM//3M2bdrEli1b+MUvfoHrujetqolYH5UrYKQzhJW1VRJGOovKta37vam64p0rMxzqy5Dc1EaoNbPlBi+dnyLY2MYdXc5yj4iOuGR7V4Zzk6vX0fBD9nSmIPTWW8UqhBDo8WF0tsDprr289N7Ycv+Gd4EHd8Ouao2bOTyrSomCpUjaJlNVjymgL2XgK4VAELMMHEOsClKxMkih1w8kKiEQbZ2YqTSx/Xdh7TmIzhZw48k1PTKg9aJwcbqxSnwBIAhQSvHGaIlv9myA4YurZpdcxWTJZV20Znyhwjd2ddAIFB1tecrzs63gQMTnniAISGzbhXvhDNciJ0KFhJ6LFAJn1wH82WnC8iJWVw+pr30bAYituzgj2/CmJpitunjBkpBhSLZ2pJmpuiRsA7TCQhE3NNOByR3dOXa3O4jQpx5oLsw2mKutf+4dHVngjt40mRUDL4bP3g6HQFcpFhOYQsMNMqCq15CBj2sm+dWZyWXxBaDqBlTdgF+c8vnO/k4sgtb4nxxbJb6sxB26RPJAiSC5wtZMypYd202QtoM2bqvbZcRH4FqCx7UgoujuB9NcJWJfw+4dxE9lUUqRNRSPbkzTHMy07gFSYTYbhLZz0/NMxuIgJWGtSjA1tvq0Fq0eL2igWSMlQra1Z9C0elnU/OtBV4VA5IuYqSx4Lq6A6rZNJNImAZLfnJldFl8AFmsupVDw8pTHpqC6SnwxpCBhGSw0FT84Nk5/1mF8sQ6jkHJMvr63i5yx9l60qZhisJBgaH51tVDCNjg8kEOH0f0j4g9LgMFbQ7M4jo1aarfV9ENipkTK1nNa0/MZWaxzfLTBd/YUkY5DSOv5TCXTGBu3YeTn0Z6LUexCObGleydYpqB95y6ql1bfzwRw76YCKSNs6SlLKLW615mPQNoxOHcC0xAI18M2rvUXofWc6LkIx0EHPkGg+P57q5NtLEPw5Z1dDKbEH0QMyJiaze0pzi1Voa/ElILBfOz2fVZsNtCBD0JipNKt37ha4dqFN1yYRQ5sXvdZO+IfD01f8dsLs2umf2VHEceO+v5EREREREREfLrcVhGlP/uzP+P73/8+//k//2dKpRKFQoEvfelLPPPMM0AreDI8PMwLL7xArVajUCiwb98+vvvd767K0puamqJcvh7Av/feeymXy/zt3/4ti4uLbNiwgX/zb/7NTS3IItbHsxziDz9J/Tc/QzWuB2JkPEH84SdxnRhS61UvOKZpcuJqCTdQXJmprlnmifESuzu7sVmqLNEBD23MsKEQ58R4GddX9OXj7OlKkbfUBxW+tLZHSlS5xMLAHl58b2zNi+vEQp1u4VAQTdDrCB/5NqQpeHJ3J788NUndC5mz0qQcB2pl+jNJTN8lNFvnnEym0LlW428rDJBCE+vbQOPcibVZooCxbTf19u7rx+kmOyWl5Mpcbe0Mo+X3PTNfob6jSILVAoywHeB9GqVqQAU4KBK2SSnK8vtC4bV1kjh8P/W3XmlVZ0mJtCysgU2I9i7CpSxRf3Icf3Kc2OAmyulOnntnjJ2FGMWONipz87i+IlQwVWmyuzvL6EINuvqplVoBmM1tCe7qTULgLceW/UDdtJmw1rDY8MkmVweTwjDELHYQToxguC66WkaHITKRgngCslmUZTPbDFdnIq+g1PCZayi6Yi0BVq1oqr6GMAT/etBcSonSGmfnfvybVMHY2/fgW/YHVt5F3J5YOsSanyUYuQJojL6NhIUibipL8sEnqL/4XCt4t4SRb8M+8hD1FeepCkPspX+HIWgnhrNtN42jr6+/zp37aYYh2m2CYbFSgQkmRrA3bqUxNQ5hiDAM7FQChETVqlgbNjPhXg8GaU3rfrN0zwnMVib6gi+YKjdXrXd0ocbhwQJDCw0uz12/TxtS0J+Po4GxxTpxy2BHx/WeX1U34PkLs/zR7iLiBkElG7d4YlsbVxZTnBgvEyjNprYEOzpTZGRAdAuJ+EPTUIKFukuX0xqVgdIopVFoCGG+5hE3W4kyU+UmM66md+cB/CVrWK01gTQwsnnU+AhOTx/e+dMtAV9KEvc+it9Z5I/TcHqyQt0LcSzJ3p4Me/oKzM5MfeA2SilRpQVUtYLZ3deycNN6RVVJ699GoY1REtS9xqrv+6HmubNT/MmhXhLifZ7pPiFUGHDvhjzlps9E6fp1xTIED+3sJGep9R6Zbw9sB2dwM6ZtE0yMgDQwt+/CK5fwJ0aR6WxU0RIREREREREREfGZ8rEFGK31stiRyWSWPaI/CvF4nH/2z/4Z/+yf/bN159u2zb/9t//2A5fz53/+52umPfnkkze1HIu4NbTWNPIdxL/+PfTUBKq8gMzk0d0DjBLj6kQdL1T05xJ0JAws3bK0qjRvnjHnBiGBZjmwBWCqgC0ZydZcG6EGA4UZepgL8+h6HRGL4+fbqQsTW7Im+1Yphd3Vw+Xh2rovXFdnK+zeeRD/3d9j3Xi6CoG9cz/1MKTLEXzvYA8z81WqY2NsfeIJwuf+ATF6iQBaFha5NhIPPEFg2ThXz+Mee5tmrUxq1wFM30UZJqG47lcmUxnk5h23nIUXW6e5qrYcZDKNFboY4eqXcuHEyKTjdGYDphfrS4E0gTKt5Xf+Le0pwjD8WGM14vYl0KC37yPVO0A4MQq+j/3gE+iJYcpL2b3QyuSV9RpWvsjw6fM0J8uc8Qp8+c778H77c2zZOj/CMMSWsPvwQWb7+ri/HTrTDm0xQUx5WKUFdL1KIp1jczHJmXWyZwG2d6bQWuM064jAR1s2fjxJGIbENm/Hf+15/InR68GphTlELEb6nodpWA5e8/3HjLtkuae1RhaKN/2csCxwYgTSZLquGF5oYEnBpvZNFI88jP/G71d93uodQGzZGWXOfk5xwgD15otUL14/9zlxFHvDFqx7H8Xt20TiG3+CnhpH1asYbR2oYieuHSNer0AYopw4vu2sOgeUUohte7AmxvAnVgt3sd0HkO1dxGcn8VWIUezA3rEPb8n6MpwaR+6/C1loQ23Zy9SRJ7hSCQm0ZiCfoGvTIJVjM+vuT8I2yTkGoPDWsf1SGk6PLXDHhiJKtwK+liFJWAJTaBbdEKXBMY01YulkqcmiC/l1ngxtArbnDLYXiigNptCEoR+JLxGfCZKWfpGNmUixturYkC0bTQVoIXADTdg7iLN1F+5SEoIAhO8T230Qa/MO1IXTxIodmNv2UM0V0VoTNyUd6RhlN6Az7ZBzDCxTrtmelVgCzFoFISS6rQP30jnYsoPYwcM0j76xtAMSYVkINInHvs4Lky5LhTGrcAPFVNVnY/qTOGofTByPp3e1M9sImal6xC2DLd0FZKN0W98DRSwOk2NUb7AXju2/C2fjVkRnTyTAREREREREREREfKZ8ZAFmdHSU73//+xw7dgzXbZXoO47D/v37+fa3v83AwMAntpERtw9aaxp2HPo3IaUkRPLuZIM3rowuvzgeHV6kJxvjyZ3tJLWiNxtjstRYd3n5hENMLvlH3LAeHQYIwGnW8F56jubkGApJyQ1pJPOE936Jc2GSA30ZOhy9XM2itUZ29lK7cn7tCgGVynLM7ORrhx8gPPbasoWMcGIk7n+cclsnLPk/Z1WT+Gs/RtUqCMsmdfh+9OI84eI8ZqEd+/ADNPJF5LE3qa/IhK6dPUFi753ohVncSgUtwB7cirlzL414iluJWgVBwN7uDJdvqBxSgNnZww6nQWL8ba65YMh4gsTDT+JZFg91Ovzg9Bm8eh2EQCbTmO2d9HXl6UzKD5fJLw1KvmCuHiAlFBMWaSNsWehE3JaEQD2VQ2zLt4S2wMepVVgZ4ZHNBvbGLbgIZuIFrngN/NFFKh1pvv7kHyNOH8WbncZwHOL33IOzeQvtpkV7GrQOiTeb+K8+T3Xk6tJCBXc/8Se8FjeZa6wWRXtyMXK2pLMyRePFn6LdJjIWx9m5H3Nnyz4ytv8I9Uql1RQZEJZNbN+drUA3kLbNdQNU0NqttGMCLesm0dGDTCRR9bUVZM7W3ZSTBZ49N8vwCkul14ckB/u2cNfXB5AXTmELhdM/SFjsoCnX74MQcXsjhECMDeGuFF+W8K5eJNE7iN68k0Yijdi0AyEEnlLEm3XkW7+hdvUCBAFGOoNz4Ajh4Bb8FYJ603JwHnkKe26SYOQqwjAxBzchbYfaz/8eVV7AK80Tei7Jex9FxhM03365lZjw4nPE/1//b171c7z07mVsQ2JlMrynLNplg4d29jJZalBuuIzM1ZZGGNy3uY2EDFEKUraBIQXhDUpKoDRHh2a5f2sXldq1c7yVbX+tv8Oengwz5bX3ZS9UN30y1FrD0n359mvDHfGPiZSp2NKRZqZc5+6Nbbx4aXWPokzMZF9vjlcuz1H3QlwlqBkxEkceJLV1F8HwJYxGHQyDoNmk9PqLyFgMt1xCTo7jPPUMpxsWvzkzsaonSiZu8b1YgvXuCEII4qV53LdfoTbe6jeTOngYMwyonTtF8u6HMbbtoXThPF6jgZNvI3voLkqpIpPPn8DI5BHtXSixWuBpBCFCmH8wAcFUPl0OdMdae9mdjTNRX/yDrPujIKUkPHeGoF5FxhOrKvSbJ4+SPXQ39WQmqmCNiIiIiIiIiIj4TPlIAsyZM2f49//+36O15s4776SnpweA8fFx3n77bd577z3+zb/5N+zcufMT3diID48QAg+TmUZIuRmQdkzaEwYOH7+xp1KKaVfw+pW1zXnHS03eG69yb2+cHR0pLsxU2RiHdppoJEOhw1DF5/BgHkOHN23+bqHxXv4N/uQYGsl42aXU9KHUIPH7X5C892l+fKzKNw70YQhJ3Wt5gOuEw+D2zZweW0B77rWDgZHJQb6dWVcRHDpEcnAjlBdaptzZAs6GTYST1xsrG6UFwvlWJrJ2m9TPnkQ4MWQsjj83gyiXMA2T+vHVWXfac6mdOY5RaCf1xNfxYgl8O4Z3Q4PjD6IrKdnfl+PY6OKq6blskrt2DRIfTKPKC4h4Al3ooBlP4oxeofDGi/zxjsMcm00yNl/DtmFfxmPnhjR8CA/vUJq8M17j6PDCcra0ZQju2VRkT9FmlQl6xG3HtUaynmGSeeAJ3E37WSzXMQ1Bm1chHL/E624KV/o0mi0h8sL4Iv+fSpq7tz7Mhn0KH4PebV2gveVz1xQC/40X8EaurFwb+dd+xr964Fv8Ztzj/EwVy5Ds7EzTmbLoDxZxjv62ZckEqGaDxruvE0cTBD7uxAix+x9DSokOQ7Bs3NlJmu++TnLDFgrJLANtSYZusOXLxS129xVYbIbMhopi0qaQyJB4/BsEZ44hpcAyDGLNJiQSmAfu5sRkbZX4EiAZXWxyeqpK80AvU85WYpbJvbkCXcaHG7MRtw8m4J1+76bzvdPHsDZuwxNyeazEAg/3tz8lmL/uEx9WytRfeo5EGBJu3b0qE9w1TOjow+gebIn/zTr1n/0tqlbB9D3CuRmUZVG9congsT9CP/Q0ulYlFo9xtbCBHx+dxujYgCkhnkgwulDjxPw0aM1sqYFhSg4OtDFfb3KoL0cxYTJe9/FDQSYuOLKxyKuX1lbL5BMOm/MOE10Zzq7oqRa3JIOFBJ0pm9Pjq3u62IYkZbWqayIibmdUGHJkIMtPTk2RdSz+eF8Pr16ZZ7Hhs6s7w5HBPLNVlz09OdpTNqcnFrlkSB7elMVv68Rp7yZ46de4F84uJ+9cC9yHnstCuclvL82vbkgPlBs+vz07zRObkoilCuRr9rOx0jz+lXNIKRGmifY96udOEd91gGB8iMnCIL91u0nu30GSgFIomL88zyMHYiRjDrXSAoZhQLFzVaZBMWGj9R/+WUtr/bmolLZ8D+/sCULDRPZtwHKbred+w4RYjOaVi8gtu6OrWkRERERERERExGfKRxJg/uIv/oJsNsv/+r/+rxSLq61eZmdn+V/+l/+Fv/zLv+R//9//909kIyM+OqXQ5OenplioX+95kIlZfHV3JwUr/FgijGmanB4q33T+mYkyB7pTFK2Q/y5fZeh3z1OamQUh2NHXx8MPP46TMd63ga9Vmqc6MQZAI9Qt8WWJ+uwM/WEZ1dPL3743gdAKsfQi3ZGO8aWdneS2b6daqraqNSwLZdpo4PCGAiYBjXgS4i0ffCHEmpdN7a9tsKzdJuFSEFm7DUS1sqp/wErC+Rn8+TncgdxHyr4zVMA9/Sm2FJOcn67iK83GtgS9aQtL+9SLXYj27uXf0Q583KOvo6tl8u/8lkeLnXjtbRhhBXn2BLGEj7tl1y397kIIriwGvD20sGq6H2peujBDW6KX7pv3LY+4jQiEwW8uz/PGhTkCpTF8F3tqhAfu3sf5o+doazfoKyQZnW+JG6Hn8dpImZlikrsHkyTl6obDVmWR2vDlNetRlTJdv/s+f/LV/yfDm/KUGgGGgI0JSP7m9+h1erP4I1exEglUvUbj0rn1dyAMEWHAY1sKvGxKLs1UCZWmMxOjI5PgtcuzqLC1gQLY0ZXh0e40VrWMN3QJJTQqncM+8gAVaXNy/LrIihBMlFxqbus6dHqyTHfKYqLU4BenJvnegR7ifwD//YhPHhEGy4Lfeijfbdk0mtdNMMXM5CrxZSXN994gNrCJpuWsmRdeO/9mJ1G1lg2f9luiZbB1H69lt3LquZPIDVtZrEu621P4lRpuqGh4inzS4cpkmaQlEZ7LsfMj3Ntuc2l4ATc2wLd2dTLkwV8fHV/uhSQFbOvK8ciOLl6+MIUfaqSAgbYkD28uYKsmD2/IsLMzxYWZGoHSbGxPMV1ucnRofs0+7OvLkbZUpKtHfC5ICp8/3tvJaMljtNTkmQPdpGM24+UG/98XLuGGirakTWfK4a6BHJOlGnPNDB02yFqFxpUL6/YBFJbNyPQigbbXWStMlJuUvAQ5A6QQOFNjeG+9ROXiGYLZaczuPhJ33EtjfBhVrdAYHaL2+Hf4i9Mlzk6WIAxQjQa2bTKYifHc0UscuWMHz798jLC0gJlrIzRar2c9uThtMbF+6WdECxUuJ1opIVCxOMTiy7NFs46hQlpPBxERERERERERERGfDR9JgBkZGeG73/3uGvEFoFgs8sQTT/B3f/d3H3vjIj4eobR49vT0KvEFoNz0+cXpKb6zvwvr/Zq1fwBCCMof0N8l1GBOjuC+8At6JbS3p1FaY7mL2C/8hPhTz7SsAW6CbtSBVhZe1V27rmTQ5OjoIuenq2wpJnGWnBumK02eOzvFU/v6ePniDKMLdZSGpG1y12CebQULdStRpmSqlUV3E5FI5tpa2frvgzA/XqslqQI6HejZkAJalUdaX//dVoophtuguXAteKhRs5OYs5NL/4Ng9CrG9r0EwQdXwYTC4OjI+n0INHBsvETv1hzqfQS0iM8eKSVn5jzeHa1ez+YVgnrD5Uenpji8eYBT753m/n3bOZmwOTtRIkTgmJKD/XkO9cTX/sbN+k0FRdWokxg5x+Yd+5HZVt8MZ/giTRXS2HGI0LSJ1RaQY1fQnkdYXiQ+uAmGr6y7PCOdbQVUgBg+T2zOsjiQxQ00PpKfHBtFrchS1sD5sXkKCw32lxdRto2dSNCs1/Fe+DXq6U7c4Pq2e4rlgDZA3QsxjVaAveGFjFc9NqejwM3nkdA0MTt7CNcR/gDM9i5Cy1mucJJSEk6O3nR5ql5DNGqwQoAxDIN6KAk1xE2BKl1flxACkikuduzg+PEhhGnS8EKGSx6JtMdEJSRmmfiBwg0UfqjR2oVGnYYyMc04VMucO36GQywwGW9fda4qDWcnFknZBf67uwaouAGOIcjaoJey86UO6I5B39L9IwxDuhJJSg2PK7M1QqWJWQb7+7Ls70xE1/OIzxWO9tmSlWzLp5BScnTa5xenpujKxBBAww8YW6wzVW7wrQO9DC806OqOgZAIw0AH6wgwpkk9eH/Fw281KCS2MEP1Nz9FqhC9JLwGE6PUnv0Ryaf+mNqZk7j9Wzg2WeXsdAVlmIglscDzAkYqAtPWxIXirm09HL86Q6hCTMtic2eawwMFPB2SlMatPbP+I0TZsVbvrrGhdeebXb0E0ogsyCIiIiIiIiIiIj5TPlJkuL29/X0DuEEQ0NbW9pE3KuKTYb6pmKm4684rNXxmG+HHqmAIw5DBtgRXFhoESrcyAQ0QS8GsfNIhaWi8995Ea1hohszVXPxQYxmCYirAunIBue+umzb3FCuy2K5lr6W6uij2dGHqkFQuRboeYsq1AdLpcpOmF/C17QXKfoFAa5KmJC7DW36R9dI5Ytt20zxzbM08q7uPINeGDIM1vtPLW2xZkP9kxkL4AUJPa4UGwrLQ/vrCmojFULdY9eQrqHk3H+elhk+oo5zC2x1XS46OLIC47lqvTQsZTxCEiuGyRyaV4Ph7Z+loL/CNXe3IbB5tmOwoxjHXsawTThyEXDd7GECmMiillsd1LdfF210HODW8gOuVKWQzHN79MANjp9DTY8iuPmQyhapV1ywrdvAIruUsB09UGJCRYMQNfne1vEp8WaZW5tj0Ijt6N2GdXzF2hcCZHqUr1s74XB0ME2U4q5KL+3JxaiuE5XLDR2Zjt3UD4oj1CZXG2bkf78qFtVWKhoG9+yD1G66HwolzU4QAw1j+rycsTozXODlephmEtCUdvhnPtKoptUbbMcIte3lvuonV2bPUeNugkIqxWHPp6SxyZrJK0jFp+gpbgm42EUB3LkGt2hoPfhBS8QJy7iSWUWwFf1dwYmyRvV1J2u3WPWI9t6KV9484Pl/ekqM8mMNXrUbjSRmiPoQ9ZUTE7YLWmjAMaSrJ28PzLNTWPvcGSjM0X+eOvlbCj59IYvVvxLuhV6CRL+J0dNLT2YZxZgZlO6gbnnJsQ5K0JKZQeKfewwsUGoEtzdY1Qmu07+FfOofZ1s5EvEjdD9HXlrPiGtJ0fdxUgtrsHHfPn2bPjs0E2wZomA7np0r8zVtDSCnYVExx10CWtPz49sFfNHytSey/C39iZI3IIiwbc9uelv1vRERERERERERExGeI/OCPrOWZZ57hl7/8JVevXl0z78qVK/zqV7/i29/+9sfdtoiPSXOdzL6V1P3VURohBC4W403J1RrMByZa3lyja2oDyzSYKDW5Mlfn0myNqwsuPhIB3L2hQKxZJViYZarmM1Fu4IUKjcYLFeOlBjMXL2NI46brCLIFrM6WxVbaMejZvYsuXLznfkTztz9n7pc/5NCp3/CnGyyS9trTudIMQAVkjICCGeLgf6hAaqgU4uARYvvvQthLWc+mibN1F/aDX8aTBp4TJ37vI6teqlsHVBI/8hBuIn3L6/u4eIkk9oatN51vbdl5a0IOYMuWXd3NaEvaGCIKBNzu+EqsypoHUAiMjm5iQjNb83BiDuVmyNnhad6+PM2z52Z4Y2iBuL3+2PTTOey+wXXn6USaUq5r+RoSmA6/HHV56/IM9YZLGCpm5iv84r1hLnbtwix24mdyJJ74JlbvQEvYAWQyTeK+x/AHt6w7ZoUQzNfXWgQKKVC1KvW6S+AkVs4gsX034u0XOcQC4ehVgqELGLUKckmCiVsG/bk4i43ry80n7Eh8+RzTyLWR/NLTmG3ty9PMfJHkY0/TLHSs+qxSCqN/w/I5eCNWdx9hKocnLMZdk7fHG9QCKKZjKKWZrjQ5FaaoiBhCCJRporfvoykMgolRgslRguHLJObGcKSgN5ck1IqGFyKFwECjtUIKwaHeLBMTrWpGx7YQzQZ6epyUs/aa7AYK9wMy9m9EhwFp2bovxj/kfTEi4nbEV9D0Ahxz/fE7U/UYyLfE9EAp7IN3I5PXn8+cgU1YOsR9/ffkL71LtjyFGr6M6a22Mdzbk8EyDRZrAVPDY8zXAyZKTWrxDBU3JFwSWoKJUYxkinqgsB0HsZQoJEx7VeZKiCDrGASzU+SCGtq2+fG7I5wYLeErjRsozkyW+eHxSWr641VUf1FpFrtIPvZVjGxheZpZ7CT5xDdorpgWERERERERERER8VnxkZ7kz58/Tzab5X/+n/9ntm/fTldXFwATExOcP3+egYEBzp8/z/nz1zPLhBD883/+zz+ZrY64JRJWSwi5WVgmbZtAKxgvpWS8Lvj12Yllqy8BbO5I8/VUds13hTR55UqJq3M1vranm9eH5hmaq1P3AspNn+8c7GMwLdGuJDAc5muL625DWZvElYFzEys0T0gSDzyB/t0vSQlBrDLDwntvYjgxRFc/9VBQmRql+NqvOPTwN3lzbvX3U87HbyjsGhbywN3Et+9BuE2wbLxkhsa1jHylcHs3kvradwgunCacnUbmCljbduMWOtZUnEh5veHzJ02oFM6BIwQzk4SLqz3+Y/vvxL8h4Ph+SB1y50Cen5+cWDtPwL6ezHLfjYjbF1NCwjbXjILAjhE3TAaKacYvVJDpNE62wIJwqPqKB3oyXJmrsb/9ug/+tSCtD8TveRjtu/iT48vz/USW2YOP8OzZMk2/FYbqzKVoSyUwu/oIxoeX7Z408PrVObY99hSu5aBNG+vRp0nWyhCG6EQSz7555YnWmq5MjPHFxg0zQJgWmXQCu369R5Xd2493/G384Sv0ZfM8ue8Qr16epVyaIesUSOey3L2xwOXp699JOSZdKWtpjyM+j2itabT3YH3lGZxaGTSEyTRNw1z3Guxm8iQO30/9jZdYefeUyRTx+x5jLLT4+akJxisBV+ZaPZO2dqQ41Jfn1OgC75QFxSNfIn3iBQwVECcg7ddpmCY4MQw0Bprm2DAXYzG+c6ifly/OUPEUtinJJh0e2lJk8uoQYdg693cPtJEYO47XPoAfrh0PtimxjagWMeIfN6bUpGyD7myM4fmW7exKNhYTpC245uDaSGWIP/UMaugiamYKI/Bwx0fQuSLGxZN8bf99vDQTcnV8GKN/E1bM4WBfnu5sjL96e5iUodlcCanP1SimHNxYGiebo7q4QMYxkbE4OvTJphOc9TXbO9OcmaygpEQkUuh6DbSmPeXQ3pjE3rAFuf9uXro0d90udAWVps/l+Sb7itZNkxKEEJ/a8+XtjNKaZvcg9td6kLUKCEmYTNOQRqsHZERERERERERERMRnzEcSYJ599tnlf587d45z51Y3Th4eHmZ4eHjN9yIB5g9LwRH0FxIMz6+1xurMxFY19qyEBj8/NbaqN4IGLk5XePnyLEc6TcIVtnMlH85PVQi15sz4Ajs7khweyKM0BKEiFzNABQSxOGLLTvTQ1PobuXUP0xWX/uTN96MeT+E8+cc4i7NUfvBX5LdsZVGbLHiarCHoysRolhboqM+SdIq0pRwM2bKBaIsbN7VJuhEpJX6gMAxjjcWeUoqmk4BrGfU3vNApralnChiHH2o5UCCoB8FysBladjUTVZ+pcpNUzKAv65A11Sf+cliPJYg9+ccwOUo4ehXhxDA3bsPLtRHcJLN7PbTWDKRN7t9S5M0r83hLgb+YZfDAliIdMT6uthXxKSIME19B3ICDAzneGVt7HdCmyd7BIoVMkvfGy0yXG/QmbfZ2Z5ku17gahHRmE0ws1PGUoi8boz0uMXVAw0lgP/4NnMU5dK1C6CQ4VrE5uhDgBktWSAKOj5fozcUpdheZs2xUtQxeE5w4zVSa+ViGgm6NNx/wV/aEep+xEYYhOzqSHB9dXBWs0lpjZHLcmfUxz59aDqFbyRTVq5cwcgXUwhybGi/T17+VaiKPKrYxKlK8M7awXElQSNp8eUcHcRGwXizLMAw0AoG+5aqyiM8GrTWekJDKrZy47mdDDWzbS6qzh+DKBXS9hti4jblCP+9WFBdm5ujKpbAdn6H5GkrDhekqjiHpzsUZX2zwbDnGn37le6SbC3i//Tl37rybX5wYWz4X4wi0F0K1hCV7uW9Tkd5sDCFgdGiMi6cvEHgeUgp29Ldzh1FC1cuono1U59bahO3sypAyFZ9WiwilNcIwkVp94c51IQRaGgSqVfUZ9cD5/BITigN9OV66NMPGtiRzdZ+GF2BISXvK5oGNBbR/vbpRa00jlkDuPEBsU4P6j/8alWj1SkKFxN97iS939lLZuRHdm8Fua0MheH20RDGd4NJshZ0791Gdfo7pShPbSOBnO0mmc+BWid15H7pvA52dAzTPzLO3O4PSrWdnbVqIdIZt7Um+vb+dfJjHT2eZ1xYTpbn1d5DWtWZ/RxuGEMv3H6UUdW0yXvaYq/pk4ya9GYe08Y/LrkxrjStNSOdXTvzsNigiIiIiIiIiIiJiBR9JgPn+97//SW9HxKeAUAGPbS3y/MU5hudqaFjylo/zpW1FjKU0QCEEI4vuKvFlJeemKuwsFEiuSLCt+Ypw6cUmUJrhuRpQW57fnbboKlqEYUi4bR+Js5eoj4201gegNbn9d3DWLLBTvl+dTgtXGkgEodNqrJoXkpwGKTQZJ8bIYpNUo0xP9wbeHlpAAYcH8tR8jWOJ930JFVIy50pOjlSoXKxhi5B93Rk64/BhI1o3C05VlMVPT06tsjYypeDxHZ1szspPXIRpWg5iYAtywzYAvI8YNBMqYH+7zeZCLwvNAIkgHzeW+gV8sQJxXxS0NBivaY6OzlNu+GTjFgf6CxwZdHjh7PWsYMeUPLK9g+lSg/eG5+jMxujPZGkGAWfG5+nMxGko+G9vjWDL1pfeAgYKCZ7Y1oatfTwh8fLtiEIHF0qK1y6vFVqlFJyaKPFH+3qYKjWhUFwKG2nUx+whVLAUT+3p5vnz09QbHkIpLMvk0I4+dnrj+M3r1jHac5GxOKKtHaU1ulHHPH+M3NL8nqe/x+D+XqpeiGNKCjGJpdcGsISUzHmSU6MVpsoumZjJvt4sXR/hehFxexIC9Wwb8lA7GAbvTTR59dgkJQ+GF1pCZk8uzoNbOvj9hWkAzkxV2NXVw/hig6YfUjJiZJw4Ak3/7AXu37mVNy9N43o+Wmtijs2T29toWHB2tsq58XniluRLgzk2yx6M0CcjQjITF9FD4yTveYjaQC/xyjQNr3WeCWBTe4q7+tKo8JOt0jKkBN9npC74zfBVFioNBgtxtrcnyVnqC2FZFkqLoZLPe2NzNL2Q9rTNwd4s7TEdZc1/zpBSYnlN9mdNyt0ZTkyUiaUttLZwLMkjW9ppt8N183GUUuhmHdWorZ6hNXpylNTkKE5zEa/7CV66WuHt4QWqrk9bwsbduo/2+WlmThxjturSlXYY8Qw23/kw3Hk/jaU69Kd2dvDc+Vk25mMc6M3iBopC0mZXe4K4blJfuhNJITCkwL/JrSQbN5n3JCcnykyUmmQTFru6czx3dpL6CqtR25R8ZVcX/UnxhRirEREREREREREREZ93IjPhLzhxPL66Pc+Cm6fuK+KWJO+AWBGskVIyV2vcdBl+qHFDTXLF2eKY729vlopdt3cJ4ynmDj9BV30OMXYVrULC9h6OL4ZMXx7ikYEkUsQ/uDm87Vxv/K1bbVG1BktoBgtxSokUJ8bKWIbAMSQXJhe5OlPmm/u6l5sT34iUkisVza9OjxEqTSKRoF6vc3GqwoNb29lTtNEfN6gqTV64MLdKfIGWcPWbs1MU7+gjIz/5F2StNSiFXStDvYowLYJsHl+ub71z0+UoRVIoknFo/eLq/QoTIj5DhJScnPF48eLM8rRSw2d0ocGj29r5033tzNZ8jFiMfMIiZYQccyHUepWVlxSQS8X4wXtjbGlPsXKkD8/XOTEZ43BPfFlwFEKwUF8nAKwhbRtMlTXLfcM16KXldWRiZG0+ciWVUootcUVPj2Zmvkng++RMTVvoQm8fzte/Szh8GVsKdDqL27eBUK5fBWaGAXkzIG8ChKDCNdc3IQTDVc0vT40tV91MV+DSTJX7thTZ1+5EIswXCKUU003BK5dm0IC7wv5rZKFBNm7TmXaYqriESnNtdlvSIWeD1ibCdhDjw+yrVdi0bQclIwEIgrkZzOkh3mnGAc19bZK0W8GfazDY10myPEMwOYrs6cM48iButkC7EHzvYA9z9RAvVOTiJjkbpPrkxBchBPFamebwVV5cMDh2ZQornYFcG9OVJsfHSnxzXw9t1uf7JqCkyavDZU6MlZanLTY8Ls/UeGpPFwPJ90/ciLh9cEIfzp7GPXMMrTSP7LuLA9sGmAskhuOQT8dJyeD9k0ZMC0wTgptUQGVyPH9hgV+dncFT4AUhl2ZqnJwo8y8OP0ZuYBti7DKZfALd1ku9f4D4ivSCpPD5xq425puaZqBJLD2LE67uL5MwFFvaU5wcL3EjMcugry3N3x4dwV+6oaZiFv/ljSFCDcW4sVzx4QWKZ89M8b1DPSSiUuWIiIiIiIiIiIiIz5yPLcAopajX11rbAKRSqY+7+IhPgrAVVGwFFtW1ti/LKKVoS9rrfRMAyxDEzNV56nmbZbuVG0nHTPqzMUwCwjAkKQLa2gs8d6pJPCwQeh7lszMYhuTLe/ownvt7Yvd/iXpb5/vuRpDOYvcO4I1eXTPPFSZT8QKx+rUXzaVeFaHi5cvzfHNXG0KtfbFuKIPfX5ggvMFvWwOvXZphY6aHrCXwP0YgpuTD6ML6YyRQmtFSk92FDyeK3AqOCtDvvUn93El00ArQmfki8Qcep5ErfqLrirg9KAeS167Mrpom0TA3wyvPX+bbm+P0HX8Vs6ObxAOP4WbbGMzFeE2KVTZexVSM81NVMjELS+g1SuvJiTL7ulMkQxehNYHtkE+sbQ4O4BjQk41zY4sKx5Q8tLkNQ68VOm4VE41662U4e4L2FdPrQPzAEdz9d0Ghg7bOTuZHhiCbh8rawJaRzRPmPrhRr4vJ7y9MrvHn18Brl+fYkOslY3zEnYm47TAMg7NT1eXz0zGui3eGgPPTFe4eLDBVcTGkwJCtzPOHtxUxCfHiSVJbd1J761VUaYHEiddI0BI5xj0D48vfYmNgMzB1nvJLr1BrNluVnpu64b5H4J5H8cMQV6lWYFVr4ij6Ete2Irgl8VIIgaVCRBgQ2s66/SWuEatXqf/yH5jecQ/HLo0CoGtVgkoZq38jLjFevDR303vq54V5l1XiyzVCrXnp4hzf3t+JFfV+uu2xUKg3X8S9eBaZTJHoG6Tx8+8Tm5thsLMb3dGNs+cO1M79qHUsWK+NDZw4sY1baV4405puWZi5AlprgnKJRucg5y+UiVsSz1VIwDIkdS/k1xfnycUy6PaD3NGX5fzkIt9NxLixd5gIA9oswIL1nsUBVBhyR1+GkYU6pcbq7x8aLPDmlbll8QUgZluMl5oIIG0ncVbsYtMPmakFDL6PxW9ERERERERERERExB+GjyTABEHAj3/8Y373u98xNzd30/L2yKrs84HWmv6sQ8wyaK7je7C9M03WFiw0LUpuiCEgHxN8eUc7Pz4xyXytVdkhgDvbbe6yKljP/witFLEtO1BdfWzNxSluy3D8zDyzdcnGjjS7cib5i2+hyiXcd1/D+tI38deJCwkhMAwDpTXOPQ+jfvszgvnrQWbpxNB3Ps6QTrKrx0aIVrPSicUafqiZLDWoBoL0OonvC25IzV0dRJJoRLWMNz/LRKJGeuosib0Hcdt71ntf/kD8UK9pBruSmhsihPWJCjBSSjj5Hs1T766aHizMUn/uJ8Sf/i7NWPRW/kVjoRGuCs4gQCwuEMxN45kmi1Y7xW270OVFGn//F1gbt9G1cz/f3tPJP5yewVuyITQNga80nWlndQ8lIVrZv3WfUqmGvPge5tglzK4eBvfdT9w2lu2RltGaezfk2Nedxg8Cqm7AYCHJtvYkaemj3m9wfAB2ZZHquVPrzmuePEpi8w6ayTQAnuUQf+Qr1H/zU1T9utWMTKaJP/wVGqa9rl+8EAIlDeqBoB4IErZBtemvEY1CpZmsemSyt95nKeIPg5Ym9VAggKSh0bcoHAghqLgBQrb6pcUtgWlIgqVSFxUqOtIOuYTF1vY0XWmbgz295MwQpVq9GWKH7sGaGMe/ljggJc7m7WzL5Bk//ip3Bi5hPIU1OMDs+Qv05uIYtRKNd17FzXQwq22kkORjBgkZfmg7ISfwEUMX8M4cR3kuZnsXiT2HaBY61lSdSilRl88hDJNL5RvEB6UI52cQXf1MlhpUfD63YqOUktF1kkeusdjwKHmK4vqacsQfAGGY1AKBpjVmucmYtUoLVC+2+lDG+zdSe/ZHaLdVVRLMTmOmMjTeeZVEPEG4eeeq8bNybHieS3LvHTA/g8wX0Z6PO3QRhEHmngc5G1qgG+TiFmXXBXTrXuBqLkxX+frebhxDMLpQ5cndXaSN8CNXCieFzx/v6+Lqgsu56Sq2IdjTnSFmm7y6oroVWL4WaaDuhzjO6vtPww8RwoiquSIiIiIiIiIiIiI+Yz6SAPOf/tN/4oUXXmDbtm3cddddJBKJD/5SxG1N2gj56u4ufn12msqSj7QAtnakuXtDgTcuTfHO8AL+0ste0jZ5eFs7397fxVQ1YL7hsTGmSL7+HHp8CPeaDcLIFczObuKPPY1893kerNcQsTh6tk54aWE5iOlPTZJs1PBXiAJCCGKNKnr0KsHoVWQsAdt2E/vyH6HnZ1ELs4hEEtnZy3k3zvD5Wc5NzeGHiv58giMbCowvVCitZ420xI0vyFqFMDtFsNBqghr6Pv7kCP74EIn7H0dv2vGhA2AJS+KY8qY9djrS9ifu0W03ajROH1t3nmrU0ROjiE07PtF1Rtx+yDAkXBIrpRB0Jy0av3gOVVoAQJUWUEOX6NxzkH9+6D6uVkOafkh3Js6luQZvXb0udCokkxWPUt2lx1a88d4CiwshT2w5RPHkS9jjo3zz8e/x8wsLlFdcQzYUU9w7kMHB4+ubkoj5WfyLr6HO1DA3boPuPprmzSvw3g+9uMC6pv7QqvqqLMCSAKO1ppErEnv6e4jZKVSlhMzk0MVOGnZs/QCVkIw14PUrs0yVm3haYJsme/vbODN+/Xp4jUDpVlPvKNh1WyCkZLIhePXKHJOlBoYUDLYluXtDjpwRvn9vMCGwG3U2mD7Do1cRpomTLbAhn2B4sYEXtMSXMAi4f0Oex7YViWkPpfxV9xUjV8B8+Cs4C7OEs1PY2TzNN1+ieuEMWcC/ehnVqFPcupPuu/bjXz2P7t3Iu+kNHH3hDF6+A601Sdvkoa3tbMzces8wW4WErz2Pd/Xi8jSvdhFv5ArJx75Gs6t/1TEwtMIfvgRCrFslo+o1DBWgpPm57239Od/8LyxSSmY9yWsXFxiZbwnlffkEd2/I0+HoVc9KQgjU3DSgkak04dT4svgCQBiC74Fh4h57C3tgE67RUtVuHBtSa+q//xXJBx6ndvoE5UsX0IaJb8cZfvY5zN4NHNrzAO/MB/Tl4gzPV0Fp0o4JQrO9M01HwiRjQcr48ELpjcTx2VUw2NveqswMgoBpd20KkGUIzKUK1vVyGQpxC60jW8yIiIiIiIiIiIiIz5qPJMC8/vrrPPjgg/zrf/2vP+ntifiMUErRFRN8d38Xc82Wv3zGMSnEJFfn6rx+ZW7V52tewLOnJ/n2wV564oq+pI198TT1sasYWrWUDSlR0iCYmiC8eAaZyeGNjyAzOWr926ltiGMJyM6PImbG0DfYQ8Qri9Sf/eGqbHX3wmniBw4T7rmTsLMXrTV1LJ4/McGJ8fLy54YX6oyVGvzx/l5STpOUqde1asnGDGxTLmf+60adcEl8EULQbunWSzzQfPsVYj0DNO3Yhzq2KSPkQF+ON67Or5mXT9p0pyzQn6zViXCbqwMRNxDOTiG37PpE1xnx2XEt6F+IG1iGWK6CESpctp8b6Mojj722LL4AqGYDIQTNE0dJD2xic6FzqRrLxyzGOD4qaQQaXwuqnkIBlgq4qy/HlZNn8fyAn572+e72Q8SPv0rnmVf53l2PMFsPcUNF2jHJ2yCUjxP6eC/8Bm/48vL6vaFLmB1dxB/5Ko0POa4AMD4gBV+uvsVprVvjt2dwtVByk2jyREPwk+NjaARShRhIzk6VGSvVeXxbB6fHrx9LAXSlHbT+/NoyfdGYbkp+fPx6v55AaS7NVJkoNXjmQA8pcfPrbrxWpv7sjxjYvB878GjWqlBaJN7WwZZCB66CJ3Z2U0iYJEywCW4adPWkgS50YLR3w7E3cBdb9wIZBhg6QNoG+vJZrI2bCZNpLrZt5tXjI8hYHPItc72aF/DsmUm+faCXwi32XzHmZ2hevYgQArl0HVCGiQ5D3LdewXrqGTy5YgwJiZAmQXWODZsdjt+wPCEkICgkbZK2+Mi9mz5rlFL052K8dpP52bhF1haRSvMZsOAb/PDY2KqEleH5OpOlJt8+0ENn2Hoe9ONJQqXAaF3jjUSKcHwYANkzQHX7HTTMGPF0ivTcCOHkGNL3YEmAuTY2oCU8qqkJtBDUZuc5fewM2A4qDNBxjZAB6fEhit0biNm9JOIOttQ0A4UGtrUn2d9uo30XWJvY81HRWhOs6EmTcQwStkF9RZXpXLXBvt4cR0cWSNgGK0/anlyctlh0HkdERERERERERETcDnwkrxTHcdi6desnvS0RnzFaa2x8umOKwSTkzYBAad4ZWVj384HSnJ6qYhgGhlYEZ49jVEqEQ5cJrlwgHLqEXJjD0Ar33EmcLdtR/Vs4v/U+3jY6OSPyvOun+K3ZT+WerxIkrvcMiqMIX/kNYnIUo1rGCK+/hDbeexO7NIfWrWzzK/NNgkCRjq0OtoZL2/7AluJNverTRsjhDUu9H0SrOuQauwfbyU5czxxWjTqivPhhDytKKQ50tSpyHFNiBB5WtcRG2+ePNqVJhTcXSj4ylrUcmFgPmcl+4lU3EX94nNAnPj2Oc/EU8YkhirrJkQ0r+vsICUtN5+8bzKFPvd2aLiVGJofhxBDzMxjVMurCGUzzei+iggNf2t2LqwTnZ2qcnSrj+opvHhpE1Cp4fmtMNZoeoyqOsG28KxdIulW6lq4hBTNAqKAVAJ4cox5LU9n/IPW99yLbuwFBMD2JunC6ZZv3Ycm3Iaz1q2dkPIF+n74uH1SloqXJ61fnEWGImJ0kvHoROXKJdiNgsVxnseEvBbxa7OzKkP9ohTwRnwLCMHlzeGHdSo66F3Jhpn7Tc84UAu+dV1HVMqlzb/ON3R10FbMAhHPTpA3FPRvbuDpT4kfvDvPXbw3zkzNzlEMLIcS6ywQw3QbutR4TgAwCDNvBdOKYbe14oaJ2/1eZj+XY1N+BY5sYvodcUjpCpTk1VcH4IOGRViVBOHoF0/dgYoTg6gWCKxdgfATTcwkX5zBqlVXfCbTG2rEHVEhndZK+9uzqZWayYBrcu7EN63MuNBYc2N2TWTNdCrh/cxH7IxmORnwcDMPg5GRl3Wph1ajz7nvncF98lsaP/ivyledI1MrI9i4wTJTnIjNZgrsf5+VND/LfLlT5u1Mz/LdTczyre3H3HMGsVYkFHoZhEI5eub7weg2zrUjmq8/gn32PXlvRnbRImBK8JmpJwRAXT9Kz1OvMRJEyoS0meWBjfll8+TRJyJC7N7ax8gozWWqyIR/j8e0dpO3W9cwQgi0dKb68vR3jNhunUkoaWJRDkybWR7vvR0RERERERERERHwO+UgVMPfddx9Hjx7liSee+KS3J+I2w1NQbq59gbMMSW8+gW1ZTLuSnCmIe03cidHlz2jPI5iewPBcRCqLSucZ33U/R68ucHRonprrk4hbHNzczTsqzT7PJG9Jkm4Vcf4k9Vd/dz2V0DAwu/pQqXQrK/DqBeShDgzD4OJMCYmiNxOj7ATM11t9JRKOiSkFjrh5oFUpxZ5ijLTTxdvDCzTcOvFMkoP9ebY2JmBieNXn3y+49n4YOuDunjj77AalsTmsTEh65hj88GeEXb3EH3yChvURKgBugpfM4GzauhzsW70xJkbvBrzPu4fMP3IS9QqN53++XLEFLdHhziefIb+vh3eGF6i4AfnNg+xPBnQ1FyjV6yAlZjZPODmKtmzUUga8WSgS23OQcqZIydXUXcHQXI07+tIc6Mux2PBpeAHPHr3Mo1vasCwTf0mEma377HDi6HD9YI+QBscrBq9PGJSr05iGZEvvZu4+sIX48VfxLpzG3rF32R7mVnETaeJ3P0T95d+utiIzDBIPP8mclaLmKYKFOqY0Ibz1SrNGKJgt11Hjw9eF2TAgX5vDSuQZn68yUExQbgTs782yoy2GUFHT7tuFRiCYLN28z8fluRp3dMdZr4zDqlepjbQCtLrZoO3YC3yzdwPl/b2ElkO5LcurEyXKDZ+kY9KXTyKk5OR0nYM9aRLCXV/g0xoCH6k1zEzilRYQbhNhGMzf+zVeayQYPznP8eFZevJJ7tu1jdGz5yiHAqOzl1AaTFe8pWrRDxYIjDCkOXIFvSKLXlXLqEYNq38T3HA7E0JQ6ttO9b4YRnWRJ4txTuYTnJuq0ggVXRv7ObSxSE9CtOw6P8dIFXLfQIbebJz3Rks0/JCOtMPBviydjkbfxNow4tPD04Lh+fqa6abXxB+5wnDCodmRx5ocw714Fn98hMTXvkPi8P3UX3sB5/D9vHalwskLYyAERiJJUK1wYXGBhrGdp9UQxtCvSX75m/hLz3JCCMz2LqhWaJ56l8boCO7sDMKyaSu0YdhpylpTbnh0FmBvTwp32sdUFn35OPt7MrTZ6tarXqRJ2Qcv1CQsScbS1AKoeBopBFkbTNa3R1RKsaNgkdjTzVvDCyzWPWKWQUfK5pHNCRqeohEobFOQNUEr7+P8HJ84vrB4b6LGibESTT8kZhns6clysDuJ9QlXgUdERERERERERETcbnwkAeaf/JN/wn/4D/+B/+P/+D945JFHaGtrWzeLadOmTR97AyM+W0wBCctgZZ5s3DbY3JHllctz1LxFetMWaUNz55b72bJQQlw+A0JAMoUXS6EQZDp7qcWz/H5ynDfHamilwXFYlA6/uLDA/obGsUxmy3XuSzbp872W+CIkzpYdWF296DBA5gr4vo/2g2ULoZi1lPWHIu9IcrEYWrcyWR2jtSnvh9QBm9KCDXs7MP02mm+MYF16dVU1DIBMJFGZ3Ec+ltbCLMYv/obCDW/q/vgI8r23MI481LLU+AQIlcI+dA+qUsKfHF+eLmybxP1fopnKvs+3I253LDTuK79dJb5AK0vY+9Xfs/Ubf0L/zjZ8DckwT/jyr8G2MTu70LUa4cwUSGNZfAEwBzdzZXyBFy77zDRCJmsBfqC4d1MbNa/Jy5dmURpEIHhreJE93e0MDU8AkItZKM/F3rSNwIkjtMYOPIzFeVCaY+T47YVpwmprTAWh4uzwLLPlFN/Ytp/Y0FlQGj4gsV9Ik1IAXtAa9xmp8DdsI5Ur4J8/hVqYwyh2EO6+i5fLknffaVnZJJMJ2mKChzYVSMtbC/RIAbbfxLvhOkCjRsptsKnD4cntAwRaYxOiIvHltkJKMI2b996yDHmj/nAdrZatJ6HVT0gMXSA7dIHm7sP89EqNZrGLjkyMZMzh+QuzLDZav/+Z/jxf21Wky1m73tCOYXb1Ep54h2DJhgzbpvLot/jh6RmCTB5RcLBtm/GG5gdHh/jj/Zs4dWmMetODWIJcwkGib8n9y2zrIH7o7laVmFIgDdzL5wgmRpG2hV5xHwikxbvjNY6PLeL7BkYjRl815NENeY7s6MNNZjFsA8LgZm2XPneYOmBrVrI5VyTQYAvQKvjc97f5vGIIgWlcf5eQaKTnQqWEmc7iJGykvt6EXtVrhBfPoPbeRaqtgxlPcCkYQsYTCNNCNevoIMDI5pms+sx05uioVqg/9xOS9z1K8/g7SNvGSCSovfAs1vZdOP0bcOfmQGu82WlyfXGqQhACYWcffYUkuzZmmZtfwBYte845TxIqQdoWxKW6aXVxVVu8cH6ekfkaSkNvLk53PsWZ8UVqbuv6UUg6PLylSHdcrS/iqpDBlKB/T5FmKLAE2CJEBS5JCcmlKszbbowaJq9cKXF64rpVcNMPeXtonpob8MjGDNykUj0iIiIiIiIiIiLii8BHEmB830drzbvvvsu777570899//vf/8gbFnF7EJOKA305nl24/tK0uSPDT09O0PBCNhaTaK2pVaq8MFHB2vkAG6dG8OIZZn2BboZg25Q7tuKWA94aKaFNC2HZSCm4qytNd9oBoJhymJ5d5IfHzvEnd28iWewktn03/oXTVN95FbRGxBMYAxtJP/NPqajWC+qe7gyXZqrL2ye0bgXWNGztyJA0FB+UrKu1RqqAjs4i86kEjRuDrlISP/IgrhP/SAbfUkqCqxdv+l3v0lkSe++kEYt/6GXfjIYdx37s663mzwuzSCcOxQ6aifSyfdunjZQS220sW7fpTA7PiX/u7M+klJhL1R2BYX7m22+VF6iuENZWohp1xOwUdMewAE9KnAe+TMxvQqGdxvM/R1VKaHH98m+0dzHbt5Mfv3oB1d6DTqXRSpHSHicvjPLVAwOIwSwvDZXQlsV0tUG8s2XfY1km/ZaHMAysXQdoaE18YYbGC88Slhfxd97BKyMKAo3Z1o72PBACHfjMlmpMDvSypWeA0HZu2osFoInNi5fmuTJTI9QayxDs6MpwpD9DmCti3PMoAtBS8tbY6r5VWsPwXI2f1n2e2d+JfQvZtikLNmdMjq17kBW7bZf4whSNTP7WW2EYJhVfECpNyhJYBB9ohRbx0YiJkO2daY4Or2+hua8ng7rJjSGMJTDzRYKF2TXzGmYcz7YwBRRScX7w3tiqFgtDCzV+csLnOwd76dQNgrkZbBXgSZNAa9J7D1F562XYeYBq71aIJ5hKdSKHTiGTadTCHD3dm7gyOU+gBW9Ne8RTeS6OzrJzo80dsQb+2CLJhIOfyePf5PSxVIgqzxOMD6MWF1GVRXSzQeyOezHaithbdhOGARgW0jA4Olbl7aGlYyUkKpHmqhT8eNHhn+7aRFiau2mF2+cZrTVCB1i87+Un4g+AUAF7ezI8f66JGfqEE6ME9Sq6UkYrxa67tpONJ6kaxrJA6g9dwthzB/V8OxXXwO8MMfMdUCsjKmWE7aACn7C8yIKboNMyCcuLCMvG2boLGjW8E+9gFNoxc0Xyd9yHNm28Uonmlj00khnyhkVz6CK5/QcRoU/SNqkKxWQDfn9xhplKy34s5Zjcs6mNrTmTGx86PSxev7JAIvQYzDhMNgLSiRh/+cYQxZRDR7KVfVAq1/jlOyW+c7CPNkfjmvaae4TWGhEGxAF0K3fhdmfRg7OT5XXnnZsqc7A3Q+4jvZFGREREREREREREfD74SI+7//E//kfefPNN7rvvPrZs2UIikfiktyviNkEpxf6+AmNzWU6Nl0g6JlMVj6av6MnFiS/1/BRCElRKHE13seHLz+C//Dsy7gKJgQ2kDt9HQ3pc8H3cUOGHip60w8ObCrx2bpzXji8ihODeHb08sLmNd67YnJ2u8tBX/pjGcz/BW2mjpULU4jz1V3+P8/R3aZo23QnJ7p4Mp8ZXv9zlkzZ39mdR4a3bMAjLQu+9k2R7F97Jo6h6DaNQxN59ALfQ+ZED70IIdLV00/na95bskT45AQZazZ+9tk5EsesDG45/0hiAPXSBxpsvoeqtxrkykSR++AG8/s2fG4f9uFtHXTqHf/kcANam7cjN22k4n911T7tN3q+zrqpVVzWZ96TE3rCZUixBwrap/vIHBBOjCMfB3rYbY+cBXhlZYL7qEsv62EFIbn6cemmRUMNr9Tme7rPp39zLf7tUJ5nPomIxEpk0T+zsoj0sIZ96hkYiTaxZp/7cT1DNlv1T1U5Rq09hZXIt+6PSYquaLZXBLnYw/f9n7z9jLLnS9Fz0WWG3d+l9ZnlvSRa9aZLdZHu2mR5zTmvOXF1oNAIkzRWgEQTMDCBAgCRAFtDo/hDuGWmkM9M9PdN2ummabLou2mJ579L73N6FW+v+2FlZlZWZxapiNV3vByBYuWPv2BE7YsWK+N7vez8jzq7991K8wXkZaCbPnZljInfVUsoLFMcnCviB4jPr4gSLAblqoHFkPL/qevI1l6myx0D0/X9jGQTc3RFhNBEhV1wuyG4faKMrPw5Dne+/IhrjP+vpvHZugYlcDQWkIhb3DWUYiuugPimj4ZODlJI9XXFGs1Xmy8v7M2zqiNObMFBrZFx7ukFo/334L/5kxfXSsi20aJTuVJR3R3LLRqEAbIB6nXPnx2mdeIdiKYerm4R23oXfv44g1Urht/4pLx86x/jRYUi2UO3KsP+BB5g5cYJcrUrULZOJ2sx5GmdnijwylOarmzPsWTjGwl+fZcLxGWqNEe/tJvLA41RDK09os1pirC64uPlx8jWPdlswSBn98MtEHnuaeqmIvlgDVPI1jk2snJ+UVMyX6ozna7T+6vX6Jr/mKKVYl7a5lA4zcvxyI5lg8Rzt6cywMTdM7b2T2Nv34IxcAhpVkQgNlMTQQEqFNEx00yZw6nBNMk3Y0FB+41rrl0uIux/CXJhGAf7UGM7Zk7gXzyK+8m0O+ylOHD+HW5kn1NfP3oeeobe1FaUa15Kcp/HD4xO411TYlR2fn5+ewd7RxUDs6vyrCYExN83GU2/izU2j22Huuv8x/na6gAKyVZfWSBizmMeZm6HouLzhF3mwPkJi9178rj7kJ1wdLNT9NYUiqSDv+B8rAcZ264hqGXQDP5bAW7teskmTJk2aNGnSpEmTm+K2bnePHj3KU089xe/+7u/e4c1p8nEkETJ5eDDOzq44NR9eG86yoTWKqclGVYoQ+HaEIJFmvlCmeu896PEWwtEIauQ8E3/+39B33UPtwXYsoagFikeH0nzvl2dw/aARKJaS2YUCP7p4gS8+soezpy+g4g0LCRGJoGpV0HT01nZERw9+4GNXimjpdpA+D/Yn2NgW4/R0CdeXrG+LMpC0sbl1D2xPaLidfRhd/ZjSR+omVSk/kHAhpcRs74KLZ1ddrkWiKMu+7fW/Hx9Flr29MEP5leeXeWHIaoXKK88Te/prVFs6PvRtulXCTpX6sz8gKF7NovcPHUQ/f5rwU1/96ESYcLThsbSGIKgl0qsec19B0NaJvm0P9v77UTIgPzPP3MnzXIxtaHw2FKY2PoqoVZZO+YV8mXpHgs5jr/DF3U8SScTZ2BLm4W3dJISPr+kEQdCoQJmeWBJfAAwURjyJPzeLqpbRIlEIBMH8DMH8DKG+B6i9+waRHfuopVpW3e6FulwmvlzL2Zki+3oTJBfty6qupO6tLWjMFB2G4o0qLMOycKVAyABNLffdl1KStuGZXoMxrZcLuRqWrrE1E6IjO4JdL+PHVjbxXo2SNPjB8Ulq7tXtylddnj05zZd2ddEXEc1KmF8BIVy+sr2d8ZLLubkKhibY2h6nK6qh38DuRimF29VP9Ikv4rz3Jv7CPMI0sAY3Elm/jr7ROqahM3ONsKMFPsqpkQhH8CdnuZTV2WP6mNU6KihRefU5wvvvZ2HjPv7mtRM4jovR3Q92mPlSnR+8cYav799A6fgZ/FKBznAUI5LC0jXuHczQ8tbPmD9/gXrQGPPZqkN4ahz1i59if+4ZHM1A1xuDQAjByTmHZ0/n8EolEIKzhsHbtsUXH/46Xe+8QOTpr1NbtCaruHJZIPl65koO7SltSeRs0uRXhaU8vtBrc7me4Ww2Cig2R9vonDqHefAVfCUJ7b+PKyPP3LIDRynQDeKaTms8xHypjjCMZfNjyLboUFWMVGNuFNEYrm5gtvfgvvQzqqeOQxCg7djFT8/MM5EdwegfJNQTIkhkeHe6gjRMHuhriJ1nZyurjhkFvD2So3dHK5pqWOWGZsYZ/tEPKRYqV983fJF6MUbcSlHxJXq1QmlinNri3DWSq7E+cBn96++x/dt/D5lM/6p+8g8FU19pU71suaaxWj+uDxtDKWqH3qB+8BeLiUMCs7ObyIFHqCUzzXm6SZMmTZo0adKkyW1zWwJMOByms/PmMn9vBSkl3/3ud3nttdfI5/NkMhkeeeQRvv71rzeC/L7PX/3VX3H48GFmZ2eJRCLs3LmT3/7t3yaTyay53u9+97t873vfW/Zad3c3/+k//ac7vg+fSHSDnANVTxIyBJmQQFxnNSJkQNpQtIUMuqImC4UqKPDRyFY8CnWPsJEkGTd57+IMh0/OwfwUnakoj3zh/6CsWUxfHqU/GsNqiXBuYgHnmiBp2DIxPId6pcrZqTwDnS2o8ih+qYiebkXf1IU1uA4tkUZLpfGnJwneeR2zewC9fx31RJrukKR/Q8PTPggClPLQNI2a1HACMDRBTJdr2s5cj68UCP22LMeuRymF6B1E2KHF6oXlhHbdhXub9mYfRwxN4J54b3UjciVxT7yH8djn8T/G3hmapiEvnF4mvlwhKOaQF06j7bz7I7Ej8+Ip7MGNOJdWCnp6KoPMtK75WTeWRBgm1bMn8JXG5YUqqa5OUiGDUcNCOD7FhRxhQydk6tTdgJBtoep1KuNj3HVvnXjPVRsvR7FkByOEQOaX96VJZCfpax3i0ujlhmhEo+JL6AZCCPrcHHguled/QOSLv0EtHFuxzVf6a6yGVFByApKLWpilCzSxti1L1DYwlMKdnWX61Amcah1zYB2h/kGiiRi68rGUxCjkEE6NtkyC+PB5ttTroCT+2ELDvuazX6W6Rlas0A3KfsNqLGppXJypLhNfrqCAt4ZzdG9vBOua3HlsPDYkNDanUwD4vr9mgwQhBFbgoRdyjXM0kcb6/Dexa1XQBG44iicVDw2lOTJdIWrp1L0ATUpUtUxPOoYuILeQJ92dYXhkiqBUpDUZJR3W8EfOc9LowQvHCOYuExTyCE0n3bOBkh/w3kSRDVs2M3b+EsqwCPyA3f0pkm6J2YuXcIOr211zAyQWan6WaLGA5jqLNpcBYmAjs/M1pG4iDBPleyjPo+55/PzsLN8a3EKspX3p2mUZjTqDta7GEUtHNZtkN/mQCBVm6D/xMuvSjft6NT5HMHwBtThur9xDmT0D+AObGK3Au6MLVF2fLV1p5qs+gR1u9O2rVgjZFr997zoyE2fxykW0SAzN95BSsDA1hTuXxXUCEOAM7WHixDRC15FzM5jrtyCFAgUnJvPs7IrRJhVj+dUTAgByVQdHCsKAFXjU3noV/TpxQbh19BqkQjE008Cfn1oSX6AxT1FwcFyP2cPv0fbkU/jeJ3cMtoR0opZBxV05z0UsnZawzu0KMJqmUVc6dV+ha4KYoW7LLlEIgTFynto7ryGrVyqnFN70BMHzPyD8xW9RCzUdH5o0adKkSZMmTZrcHrclwDz++OP88pe/5LOf/SyaduOsplvhBz/4AS+88AL/6B/9I3p7e7l06RJ/9md/RiQS4fOf/zyu63L58mW+/vWvMzg4SLlc5s///M/5d//u3/Fv/s2/ueG6+/r6+OM//uOlv+/kdn+SqWPx0rkFRuYrKBoWKl2pME9uaiUqrj7sSWGw4EqmF+p0pWMcnigihGA4W8XxJYYmkIZJWyzEqdPnMTVwHIfJGZcfC5t9Owe4fPAQ+w/sp2pYvH0+h6E3gpeGptGbjuDPjgMwPb3AY4/tQJ0eBinRWzsxMy3UD79FaNfdlL77f6NkgDW0EX9qAnXkbaKPPU29e6ARXGPR8suwOD5XX2ryaeqCDe1x7utPEbqNypgPSj0cI/rZr1J//edLvQWEZRHasQ+5fttH3lfkTqJ5Lt51DeKvJcgtYHou6OaHuFW3huF7uGtULAG4F89ibt2Dq71P5/hfAb5ShO55CBtwhs8vCXdmRxf2g09SNawbfJbGZzVB5fx5lFQEhRwbdqZ5x42jXAcUVL2AMI1A0J6BFoyL79CZCNNt+jhrBGOVUmiJ5Zm6erXAQx2KuXiEiuMjnfqS/dwjOwZIvPkc+r4DqHoNNXoRbeveFWMhbDbMkpIRC01AoeYRXKOwWIYGi2tNmNCXiTKyUOF6DE2wNWVQfvN1zr1+8GrA+fRJwm0dpD7/DH0RgfPKs9TnZwDQENjdvdgbNlO/fIHwnnvQhzZRiyZWrYqrKJODF3Jcmq8QSMXG9jgzFR8lBGKV98+XHeqBINJ0OPmVoZRamhvWQghBODdP7bUXCK6IiLpOaOM2xL77cHQTsXj4osLj3t44mtB4/swspu8QtkIEyqdUcvA8n20tIYrvjKNpGpNCQ4gwbVaE0ZkcQb2O2dOPPztF4LqEyjmSiRSTNclgKEahtZ981cGyNMo1hx9Ol7jr/qeJnj1EfbH3k641RBN7YD3uO69Su6YnVOnUKVr0CPdsvpu3ziuE76F8HyUVOUeS7d9BKBRfen/Kgp50mPFVqsxMXdCfiaCq+Q90DJo0uVlEKAyBjz8/u/Sa3jsIlRKymEdPtxAd2oTsHeSdBZ/XL1zt1XR4dJ5N7UliIRN6kqTK82wN+4jn/4ry8EW0aAzZPcDlv/4u8V37qAaKqZrGQGcPVuAx5QuCSgkNEI5BUMyhR2IEkTheoCg5QSPIb68979uGjr6oaGqlAkE+S9TS0RDIxVnHHb7Aru0P8sZcmUy6BWdmeWLOjrYwlTNTABTGJkh6iuufWq5UvH0SKtPCWsATW9r56clpvGuEZFMXPLGlnYgW3Fb+kRQGZ7Meb4/MUap7GJpgXVuM+wdTRLg1wcryPeqH32K1WnRZq6LGLyM27mhWwTRp0qRJkyZNmjS5LW5LgOnt7eXdd9/lj/7oj3jkkUdoaWlZVdA4cODALa333Llz3HXXXezbtw+A9vZ2Xn/9dS5cuABAJBJZJqIA/N7v/R7/8l/+S+bn52ltXTvrW9M0UqnULW3Ppx7D4rnTWU7NlJFSETJ1QhpM5mv87PQcX93RiqkC8jWXn1/Mc362BEB7PMS6tjiHxvI4ixYMEdskbht0JSyOVB2iIkBoOkopqo7HrNsIgo0cP8lXv/IY0wslfD/ANjRiukLLTVPxfAQQi4ZIpRPoO/YTrZbRExmqrzyHuW4z1ddeQNVroGl4M5MYoTC+FaL62guEv/Lb1O0wIc9BZOd5My944+IcWjyJsGy8AE5PFclVXb68tQ3jQ87oVUpRS7difv4bhEp5lO9DNIYTid+W+CKEQNc0hFIE8LEScJRhooXDBKXV+95o4QjqYyy+AI108Bs9aCt1ozYsv3Lqpo3x4JNEd98N1QrCDuEn02tWZaz47P1PYG25m7ZcgXlP45yMsq4HJsZnUTQqSNxAsq4rzWaKFLNZilIS9jWSur4U9NGFwC7lkQuzIBVmKo3Z3Y83OQqACgIy597mmz1tjCX6GJkrETYF68IQPfIipclR7D0HKLhQvzyK2nyAsOahXVOp1huGL6UdguETICWiZ5DxUIajWZ901CYT0q42PZY+j6zP8OO6R65yVWg1NMGTWzoIz09x9OCbKw5dbW6GjpPvUPFrsCi+AEgUtckxQuEoxtPfwFMKZw1LQgeTH52cWfa9hZpHyfEpOJKULVacM5ahoTXFl5tGCIGuN+aWOxl4DNUqVF/44TL7PIIA5+wJIoZBpG8IWcyjJTME6VYcHO7qClOqJbl45AS1cpVSsoMwgvu39WKfO4IbBEipwJdMlxySno8dNZBOHQIfraOXQEo0oN3WCSUidLdEGSs67BpoQQaSF05P0x2Cn5wd4cv79mPkFggch5aohTB0dMC5dA4iVyvHAqmozc/Q1j5BLBqjlF8ULIUATacSz/C980We2NRKXPMg8HlsQys/OjFN4ZpqM0MTPLm1k85EiJnlbZCaNPmV4SdbMFra8ReuCjCBrkMihTG4AbVjP3WhU5YGb12eWPbZbF1y9Pgkti745p4eFuwk/swx9EBhDm1E2SFmKz6mAHnmGL1btmDoNXwrTFS3sZUPuoHSNEAQBApnbIzQ0HqUHVqy0trVneTCbHnV7d/enSQkgmVVmJam6EmHmcjVkCjcUol+Z55s9yBTyqRyxT4QuHdzN5HRM1QW7+lELI4vNKzF9dmBhzY7hT96CWGa2IMb8NJteOLjm1gmpaQ3IvjW3m4uZ+vMVxxaozZDmRBJI7it+1dN0ziTdXnp7NXzxJeKczMl5ssOz+zswL6F+3zNqRMU87BGX1N/cgx9y+73FfObNGnSpEmTJk2aNFmN2xJgrrXu+ou/+Is13/ed73znlta7adMmXnzxRSYnJ+nu7mZ4eJizZ8/y7W9/e83PVKtVhBBE1rhhvsL09DT/4B/8A0zTZNOmTfz2b//2moKN53l415T6CyEIh8NL/772/59YhMalkuTFs3ME1wQS4yGDnmSI2VKdbF3RHdE5PJbn/Fxp6T2zpTrb4zYPrW8lW3UJAsnmjjiHRnO8enGBTCiMZmqYtt0I5AaSguOTSEQZ6mpBHH6DhxOdVM6MonwPfA8zEkVYFromuHtrH1rgIAGjvQfnrZcxUmnsdZtw3n4NdA0tEkMCMp9DdHSD60A+y3ysi8rYFNF0incuXibIZgmy8xhtHahUCxLBdKHObC2gJ7z8GH5Yx9bTDbzUNefeYh+dW8EOPMTkKO6Z40jPxRzYgL5uE/VI/H2z8wLNIFtXVL2A8lyJsGaiyzsrRgVCYO/Yh/fST1ddbu3YR12IO9LW9GbG67X/vtnfWto25tAGgqPvrrrcHNqItG3ER5h9GgBBPAXx1NJrq+3davseANV4huNFk5+dm6XmZelPh/nc3kEqGUWlUqM/bhKaHaP+3in8UhE7leJcGXY4EtsUGCj0U+9Rfu+tJQFEaDqR9ZvQ12+hfvEMQSFHaOM2om+9yuZQhI1uHeX7CCVBM9D23sVIwWGhUCfZZfLWySlaYjaPrUvhBIpc1SOYmyZcL1NamKU8OQEnj9LR089D9z5JT287FgHqmn2LC5+v7+xguuIzU3JoTcZotRQtYY3qc8fwVgn2CECcPYrashNNrOzJUr98jtjuuxsWbmucQxPF5aIPwHy5zuauND86PkXCiqBdZ7OytTNBVJdIeeevOx/H+epmx+u1fwshGr0UqmXk+DD+xAhaJIq9YQteug3/AwYehRAwPb5cfAGE0NCqZYrP/hDrkc9RvXAWWwOjvYPII09TCwk+uzHDnD7A2ekChUiaDUkb8dL3qY2NYIZCKMCRCqceUMwX2bo9zZETF4jbAreeW2Y7dN/WPqKWjlTw7liBdNgkGQ1RCnzi4QhvDmf57NAGrLELxCwNo7UD7+JpCIWXbXfI1FG6jjdykcEN+zk8XmqMN6UIdXTSGQJNSH5xcYEvbWlBkz4J3eebuzuZLPvMlRxiIYPehE3KlGiLv/8nlY/jOLhVPop9uJV74Tu5XZ5uEHn0KWq/+Bl+dm7pdT3dQuiRp6mJhliRqwd4gSRm6/S1xPER5Ks+G9vjXJork6/7xDyHy0dP0a50kk6NYH6WZKCwI2HykznU5s2IQg5LL4JXI7OxiDAtPNfDiEao1x0810cszBMfWo9mGORnZlknS/zmxhgvTLgsVK9e8wdbouzsjKKU16jEjifR40mCUoGkJQi1Ram4AV6gCA+f5Gu/eYAZM85IRqc6M0V3SIMLJ6hMjC2t096xF0MoBIKQW8f5xU/xZ65WvHHyCKGtu7H23493hyty7/TxTRoB+zpthAihlFqyBL6d9deVzlvDs6suy1Zcpsseg7FbWK+uoy32YhSr3ANo0TjyNre1SZMmTZo0adKkSZPbEmD+9E//9E5vBwBf/epXqdVq/OEf/mGj/4KU/OZv/iYPPfTQqu93XZf//b//Nw888MANBZiNGzfyB3/wB3R3d5PL5fje977Hn/zJn/Dv//2/X3qYvJbvf//7y3rGDA0N8W//7b+lra1t6bVfRQ+cD5ORbIWR8QWEri87CWp+I4NwIB3BEyZWPMbxU6NEwst/37rUOTFVxAsk61qj1DzJufkqATqRlhbEzDjBzARKKrRYjHXJjXh9HfRXZpg69AZD3/xtNvekOX1hotGzwakRNk02btvInvVdRAuzVF78MV4hhz9yCeU6GK0d6IkkWjwJntuwiPBdLNum6EoWFsr84NAxgmKBTTtDnHcs+tq6MHNzkFvAii9+Fij6Gnd1ta/623zcj21QLlJ58e/wRy+xVENy+ghq+Dwtn/86Znffmp+dzNd49uQ0s0vNowu0xWw+v72TntTKsfBBkMkEVrmAc/LI1WoBIbC37yG8Yw/p8J3x0r6Z8Xott3J8/X33UpocRVWWZ7qKSIz4vgMY7aufQx9Xrt/3tOczVVXEwwU85TJZ8vjO8Rl+qztC+vRbZCcmiZkaupJY6VbMBx/n6OkRNkQUvVs2EMxNUTl1hEhouWmHmhgheu8jxHffhapVELEE/vQEcwdfIyJdNOkT1GtY3QNYQ5uIHj9G8q59FHo2Ua3qWL7g6JzHmZkS1bk5/MlRdF1jx/p97OjqpH7xDCEnT5s7Rbp/x5r7O3jd30oppnwXw1g59elCQLWCYRjYq8wLABEBqa6uNb/vrbmJVeciV8J961qZK7tE7Kvf3ZGweWhzN22x1UxP7hwfp2varY5XaGy/NzFC+aUfQ626NGfJ0YtE991H+J4HEebatns3Q/n4OyuOXa1UJjc8TOAHRDzJSK5OImTSm8uhHXuHzi98HWGYpLJTyHeOcq53F2/PSB4dWEf19MlGtZZlYeoGWjiCfc/DJGJh9m3q4fil6cb8uBjM27hrK7FUgh8fn+HEdBGAtpjFQDqCrgkIDVCbHCGzqY+W6jS6JjASKfyWNriuN4QtFamoT7VeI5TOYHVLlAxA09neGcP/f/6/9N77CG7nVlw9zFDH1eqZwRscg086zX24NW5lrN757eoi1tlFMDOFrJTQIjH0jm70eILU4jsWJgt0ZhKkIxY/PzPDXMWl4jYswu7uT9GViqDyDu2GjxwZxtck0vehXsOp1whn2nDmpokdeBD38Ft48znih17iyQe/wQsnJxFtXch8HoRAuS4HeuPUDr3FqWPvkNF9OlNRfmdgC/mdexnxbfrSEXqToYb92TXUH/ks1Zd/BlISBlLRxuvW+i1EerrpDIcZjJmMTJ9h7uAhUArDMBCaRvLu+4it30xvZwsAlVeeQ5XyWNfPMyPniW7air1l5x0+Dg0+jmNnOFtB6RaRyOrX/gVHcN/Gtefr61FSYm7bhXvu5KrPhrGde7E+Yfd8TZo0adKkSZMmTT4+3JYAs23btju9HQC88cYbvP766/zjf/yP6evrY3h4mD//8z8nnU7z6KOPLnuv7/v8x//4HwH4+3//799wvXv37l3698DAwJIg88Ybb/CZz3xmxfufeeYZvvjFLy79fSXbaW5ujiAI6OzsZHp6+hPrA6xpGscmawjJqqX086WAtK0hApeFXIGaF1CtVZdZ50x4DhtbI7x2cYGkBfgum9uiTM/lKI4OEyNAj8aRlRLUKqzPXaZvXS8Xf/wKmDaXn/07HnviSfZv7uXiZBalaWxc10tnbwdBpUj2xb/Dzy6gK0UgNJTQUKaJNz+L0d2PX6su7otOxfG4NF/FNsI4uYlGRYlSlCt1xrHps0NQKaNyCyjTQkmF8mMrjqEQ4hNxbEOTI1TOnFi5oFrF++VL8NDnllU1XSHQDL5/Yo6Z4qLXuIBIOMLIXI6/ebfG13a0od/hRuDGlj2Y3YPI2YaXudbeRTWRppgvQH51e7LV6LpB0PtG4/Xa8/t2jq8QgtCjnyc4cxxvuGGFaA5uwNiyk3kpUFNTN70PHyU32vctGYuH1qX5wbFJAqlwfMGP5mwO7HuS9i1z9Bkes57GsBZneEGiuy6isED5QoB74SRudXVvIvfouxif/yZBIoP+zqtUI0kin/sqoUsnkdk5jK5+RDyBuzBH9fRxktLDXbeL6nyVdZkMf/HWZTa0RBALM0jfx/fh0LkJ0jv72JwcQdaq1E+9R3b9ZhxjbTu7a/ddCIHZN4B24uyyhubQqAgye3tQ9QrVVfdJoAUBC2scc03TEIG36mcvVav0pCJ8bWcHY9kyXqAYyITpjBr4pSxTpVVWeAf4qK5pd2K8XlnW2dnJ/PQUwUvP4i3Mcz3V118ilmmjllrbgvT9EEJg2aFlx85Hw8nl8D0PYVr4UuH5PgtlH4Gk8/wp5OU91GJJrGSGZP8A6zIxDp84zuthnXu++A30kXN4pSK0dJDef4DDVisXhss8uamPrX2tXJ7OUfckG9f3kdVD/Oj4FLZloqRECIHrBVyeL7GhNYoZsgmv30hkKIEeEohoDNnRjTpuUTv+3op96opolDp6ubBQoDYxRiwWZu9gGxtH38Udu4zZ0U1CGpS72pjy1j4BPynz4o1o7sPafNCx+iv/bSOJxn8A5Urjv0XCGHTGTL7z3hi+VPiBQkmJL+Gt4SzbOuKkDBPbsijVa2DrCOmjnDpKSsjOYUZijFeh77NfhaNvQLnEYGmS//MLBzgxnqcU14lZGoMtUcToacZ+/hzJsMmo76OjCBffJpWfpfWxz+PIMqVcmetHk9bSif3I07jHD+EvzKGFQtjb9uD2r6OUz0M+D0DqwUcRQ5uoToyjNB3R3oXe3knc9JmamsL2HOrH37umQfxy/PfeQmQ68O9gVe7Heew4gUG9Vl1m9bYMP8zMzMwt2ZuFt+xCz85THhu+ur9CELnnQfJ2hOAjvue70Xht0qRJkyZNmjRp8vHmtgSYK3iex+XLlykUCmzevJlEIvGBNuZ//a//xVe+8hUeeOABAPr7+5mbm+MHP/jBMgHmivgyPz/Pn/zJn7yv/dj1RKNRuru7mZ6eXnW5aZqY5uoBvSs35Eqpj93DyM0ihCBf83ClojcVZjy/3HZFSkU8ZNAa1jE0SIYNStcUAFi6xmBMY1vco29jlPM1jfmyw/7BVqziPKO+j7INMCKYts1DW7pou/QWelSjJ2bREtJRgPnuy7RHY/R0dKGkRJ28jOj9GnopR322ESxFBhjpDN7sFO7wRUI79+FNjoNhgO+jpzKU3IDwuo2c9eylSotyLkdfS4yxbBk3E8eqlBs9V2g0L+6JW0i5utjwcT62hmHgnT+15nJv7DKRWhnfXjkmFmryqvgCVwU11bCVm69L2q07u98e4MVTiMXG7EqpG/dVuQ1uZrxe/9rNHl+lFNVQFG3f/Vg79wPgmTaulNxWx9iPmNX2XfMdHh6IU3XbOT9XIVv1EAL+6nyJhwY6eM9xODE6TyALtCUjPDzQQXzqDIHbiioV1/wuWa0gPA/TdahfPItbqVOsuaSEwki2EowN4y7MYm3aTuyu+5iansOem6Ir2cf5uTJeIBvb6i8PJh0azTHUNYhx6RTSdSHwUfr7T2UNuxOJPbCOns4WhifmUdeqyppG+L7HEBePY2/YgtA0gloNd2YC5bqY3b34iQxm4KF5HtKy8DRj6fcMgoB1mQjvDmdXbQ1kGYKeiKQ3HEYI0ehforwPpY3Qx+madqvjFcAoF6lPja+xRoU/dhmRbrvtPlhKKURXH8IwG7aYQMWVaG7DWii8ZQczk1fvF3IVl5awiXIdlFI4gH3X/fRMjvDo9h5ePj7KT85mSbVuRCQNUlGbvbkskWSIqhvww5EabTGLL+zfwunpEvNGmO8cmsCXks9sSXFoNEfI0BAoAgllNyBlCYa6EljJOE5859JvFdm4DXH2JMp1lu2ToSQ96wd5JJtj/44WzHIe/e0f4mUXAJD1Gt74KB379qHU2uPHEAJ/fga7VsELRfBvcB6ZgO7UULqOb4c/ds3BP07j4Hb5MPfhVsbqR/Hbxg1FxQ3wFyPw+jXNtLoSIX55cY7/15Y4YmA92vFDCOkjggChFAqFEYlhpNLkL51m5sJF9t63D3nuBJVcnvz3/5LBWJSiNMjniyS+9CVOvvgCyMasoWjYXPUmTNyxYazsHCp9tTrC1jSsch4QOPEU1Uw7xqOfx/YclG5QX+yReO39kCECWgd6qPT2IZUipIOpfNSVcRQEKG+5xeW1qHoVIeWv5Dh8HMdO3FD0ZqKMLlRWLBPAUCZMENxaUlHNCtP+xW+iLpzFnxpH2DZ6zyBOIk2g4CNt/NekSZMmTZo0adLkE81tCzA//elP+eu//uuljNE//uM/ZseOHRSLRf7wD/+Q3/md31m1uuRGOI6Dpi33ctc0bdlN/xXxZXp6mj/90z8lHo/f8rbX63Wmp6fXtDb7tBMEAR1xm4OXFnhofSsvnZtlpnQ1eNMeC/GlHZ3YeAgluLs/w/hco1qhM2pwN1nct94itzDHtq4MW/o3MNW3nWnH4eu9JrnN91FyJbbyaKnliV88gvRd3HIRPRrFLOYbX6RAlos45UYQN7R9LwFAIDFclyA7i18po8fiGKEwwehFjD0HCN89QO34IYRlI5MZzKFtzGY2cWnOQZgWynOZmJjlgd1b+buqS4AgUA3bKBA8tqmNpCFX6AC6JvBnJglNj4PQUKkMbijysWpuD8ANGoCqYPXm4ABV78bBsKoXwAdz8VmTj9uD+60ipcTRzSt/fLQb8yvAkC5Pb0yxpzfFaxcXCBkaX9/dzavHRzg1erXqoDsd4YE2B3lxmiAaRU+34uWzq65TT6aRpoXuVFG+T8gQBPhULp4DQBMCzQjhOAHTvoHnK8yJEdK713N+oYCpawhNoEVjBM5V4bBcreN1xzAAo7WDwA6BagjLgdAp+4CCmAm6unrOCyGw61UoFeh68GFaS0XGjp0kNz1LpL2NrgcfIdTVgZq4QPW1F5CVMkZHN5E99+ADob0H8C6fwTl2CFmroEcThHbtx+9bt9T8uMVW3L++lYMX55eFaeIhkwfXZVDBhyO4fNpQQQBq7XGnnPoH9uWvx5JEHnua6qvPg+tQdT3iVgh7aANe73rKh48svTfe00tsXS96pURESoJUBt/SITvDwPQFntm3jTFH4EvoilnE3RK1ekCmL8oWS2O6UGWu7OLoFh0dGbI1n2jIxA8k47kKT2xp592RHFeCfY4f0JKJcndvEhkstxurx9NEP/cMzruv4003KkCN1g4i+++jfuwdwm+9hlsoEyi1rPuQ3tmNtZAjrCnqrETTNEK5edwjb1LMzVOt1rB6+onsvZdaMrPsmq4JQWhuEufI27gLswjTUuLspgABAABJREFUwtq4DWvzLmrWr9Zer8mvN3XPY6glykLFpe5LLF0jFTZx/IDZkoOpxRg9d5ENX/wG+pFf4l46j2mZiN5NGNv2UD17kr6WFNlakaBaJdHdQ350kqrrY9ZqFMs+6QMPMCdN/HqdkKkv9VlzfIlCAIogt4Bo66XsCdrmL+O8/Cy1cydACELb9pJ45LOUWzrxjcWbrDXuiVTgE4GGgiCXh/uDUBijpQ1vamLVzxo9g9zZbn4fc6TPw+sy/KDsUHauqXYGHtrQRtqScBu3a3o8Sa2zD9HVD4Bzi/d8FgqjkEVVq4hwGD+Zwf2AfcqaNGnSpEmTJk2afPK5LQHmF7/4Bf/jf/wP7r//fnbv3s1/+2//bWlZIpFg+/btHDx48JYFmP379/O3f/u3tLa20tvby/DwMD/5yU947LHHgIb48h/+w3/g8uXL/NEf/RFSSvKLpfuxWGzJ1/9f/at/xT333MNTTz0FwP/8n/+Tu+66i9bWVnK5HN/97nfRNI0HH3zwdnb/E49SisFMmLeGBacmstw7mMbQdSpuQMTSWZeJ0GEFBI10L7Z3JchuauPYeIF7gmlyL/4UW9foTYUw3Qri4jE2FGYZeuIZnn3bYXj4XZRmkIyFuLc/TUwzQCm87DyRPXfjvvrCyo3SDYyNW3GDAFPXqebmkKUCKAgKebRIBL2lHX96gtD9j2Hc9xhSaASmSVGLU704w2A6xKTTRW1sBN8POHv8LE9tXkc8FmY85BPp6yERD2MbOlIIxDVPtqaS6McPM3fqKKViudGsOBYj+dBj1HoG17Y4uENcERrfT6gIggB73SbciZFVl5udXfih6KrLIuaNm7M2ln+8MpabfHjo0qPNNjGQFCouh2t1trdH2JjpwfEkCVuny1KETr5GgEJLpDD711EfudDIKF527gqsXXfhaBqmYWGnMnhTY6RSCUqtbdRzOWTgN0SWvkGYzQMKQmFqbkBL1CKQgJRoiTRBPrskfMUiIax6GTQNe/fdVDWDnANzNUmuWidfdRhdKJOO2DywroWeiEL5PvbwOapvvoJaFHM0y6Zn+16iT36ZC3XBnOvS+f2/IVPLE+roRqvXwPepnzxC9Kmv4l48R+3wm0t76Lvz+K88R3jffeg79xNIBTJgd7tNb7KX8/MVqm7A+tYogxGwqOPr1seuKuCTgIpE0WIJZHn1iiujq4+6lDd9HV31O5Si3tVP5Mu/BdlZWkt1AjtC9dwppo4cXXpf784d2JOXcX55Gqe1HaVAT6QIP/IUMhomUV4gdvp1euwQmmkya23hraLBqfE8QWWKAib3DGZ4uDeNROPd4TkSkRC5qocmGpU3vQmdb+3tYThbxQ0kdw+k2dZiYamV4VUpJdVUC+YTXyFaLQOKIBylZphYtSrByaPEg4DACjUaS4fCeDvvZWHdLpQQzGoRErqE687LUDFH5dm/Bc9FNw20wMcdvYQ3M0n089+gGmv0UxNCYE+NUn7xJ0tjVLku9SNvY0yNYX/mSze0CGzy6cYQArNSbFQqhqO4VuiOJrW0R23G9AqRpIVCEABjuRo1NyAdMcli056MEYxfwt66G3PjdjTTxDl/muprLxD+zOcJz80zaPmEpi9jf+3/pMWRuMNjxMIWIS3J96cDPltvJIi1Dw7Qsn6IaryVXM1l3oSWWpap9CA/fm+GrydKXP7v/x5RqxGxDWxdUDt0EPfCaRL/7/8PxWTLbe+rpyCy+wDe9A9WCNLCDqGv33zLYsEnnaTu8xt7uhgtOIzn60QtnQ2tUVrsxnz8Qbid8zRcr+C+9nPq01crNo32LiIPf5ZqOHaDTzZp0qRJkyZNmjT5tHNbAsxPfvIT7rrrLv7JP/knlEorvcPXrVvHz372s1te7+/93u/xne98h//+3/87hUKBTCbDk08+yTe+8Q0Astks7777LgD//J//82Wf/dM//VO2b98OwMzMDMXi1UBNNpvlP//n/0ypVCKRSLBlyxb+9b/+1x/YMu2TTEIP+PLOLn5+do4LM0UEYJsaO7pT9MfEsrL9kKmzq9ViRyJN7YfPkslEsHSBtphappSiPjfD/NnzTHo6UiqQHvm8x3P5Ek/v3sFgYQGzfx3+4CbCtRr1o2+jFu1dtFic8H2P4aRasXUd7+JpIjv2UXnx70DXwDCRtSqyWsXeuR+vqw9f6JjVElZ2jtYzv2DT+Aw1zWb7tj1cTG3i1Jlhaq7L3NQs21sUHZvX8dqCx/lFq4IntnSwJa0jF732jdFLzLxxkKn5fKOnhVIITaNjIcfg7/w9Kh/goflGOMJkuuwxU6wRtQ36kjYJQ66Z7a2Ugp5+9HQLQW5h+ULDwN57H6u7g0PGFrTHQ8yWVuY7t8VtWkLaB35gbfLJQgiBrjesUIIgIKwFbGiN8sblxrl1ruzij11GV5IFy+SBu/qwO3sQ3f1YG7fi22ES+++n+urzKM+BSAwVSxDadx+ysxd7+Dy1o29jr9tENtHJOBFq7bvoCAnasmPY545idXUxMdLI6FX9G5jMV3loUycvnplCSYVvWZh9QwSzU8half19KUKzU1hPfIlcay8vnstybrbKxYUKUkF3MsQjG1o5PZnnx8cn+cbeHjKjl6i8+sKycZWvOIw/9xKpJ6O867fwhLHA/Og4BU1jXWsEI3JVsKy/9RpaZ8+qv2H92LtEhjZSiyxWY8qAFhPaesKE6lWCC+/hXjyDqxTm4EasjduoR2Kf+KqwDxPPChHedy+VV59fscxobcfItGIPn0Nm59ESKURXH/Vo/JZ/Y6UUtVAEugfxpMnfHp3iwXU7ic7MUpmdIdreQWhhEjEzjtbVvWhJA0ExT/WFH5J46qtUhUBICfUqfudm3i4ZnBqdQ4XCuJrJ7u4UAsHlbJ3JokMmalNxHO7qS3JiqshcqY4hYDpfIRmxSER0Nmca4oumadjVElQrCMPEjyeXMqs9wItcE+ALArz+DcS+9BtUn/8h7oXTEImRffr/4MWsTuH0LCKeQs6MsbkjwYODScxFgUfXNPxTR9FLeYLcAp7vNYSmdCtKKfwzx9EPPEIQBJiBj/PuwVUrA/2ZKey5KVjMJG/y60WkWsJ953Uq48MNMT0aJ7TnboKhzUtVg7eDLT20+TmCyVG2dm/mhO/gGhYgMIDBdAgngAc3tDLQHqb1wQcpPf8j6pPjaLkFZKmA1tlD7Yvf5mK8k5KcomfrAfqG+qjGE+gJg6KI8/p4gVQswkRpikp3ivsfuw85McL0229SN0KEd+zl7YpGMd5Lf0XDRCHefhm/0rjPLNY8EiGzUf1ZyOEeeRvj8S+t2nvxRmiatiQuO+3dRJ/4AvV3DhLkF0AIzM4e7LsfohZNLFXWCCGwAg+9VEAFASqW+HhWdH9AlFKE8Nic0tmaiS9ajfq3VfnyQbGUxH3thUYl4jX4s1PUf/Ez7Ke+hqPdOBGqSZMmTZo0adKkyaeX2xJgpqenefrpp9dcHovFKJfLay5fi3A4zO/+7u/yu7/7u6sub29v57vf/e77rue//tf/uuzvf/pP/+ktb8unHSkl7bbgm7s6yDkSP1DEbZ2EKZGreCZLKQlVCwSVHOhwvQ9yyQnwxoaJdu/DKxYICnmuvOvNkSwDW/ehb9lGTYG2bS+RwQ1QLCB0HZlMM6dHOT9dJeGUSb39LulMww6m/u5BgoVZ9JY2zO17MLfsQq9X8Q69gdIEued/BErRkUizEM4w/eLfsX73Pmo7duGhcU9fkmNzFc6P15ZVsbw9nGUw1YmFxAx8SkcOMTY1h/L8pQdYJSXT0/Mk3nuX5Ge/SN27s+YOZWXy4xMz5CpXPb11TfD45nY2JPU1RZi6GSL85JcJTh3FvXQW5fuYnT1Yu++ilm5f09pCVz6f29rGs6dnmbvGcq4tbvPUlnZ0+WtlXvFrjyNMxosulxbKmJpgU3uMjrDGzs4IxbrP6ekCvmFh9A6RCap8rVdDf/avqJeLaJl23HOnMHv78aXC3LEXIUBoOubGbVTbezCHz1N55TnItHJUtPBqPos3O9Pwsfc92vt6+cpvP4T/6o9Y1xLB2HUPxcF+fss0iBugb2nnlfPz1L0A3wph9g+xtyvOtnYTfdcG6pbNy+dyDC9Umat6S+N7slDn+TOzPLK+hbPTBS5nq/SPHV42nhQas6UaCnCPvcvWB7+MOjsGgCclJScgbV+1tArmpjH6Blf9HZXvQakAkeV2mHatQu257xMUclfXc/RttItnCD/1DLWbyIa9Ysn5aQua3SpSSrz+DUQf06m/9xZBIYswTax1mwlv2UHxp99DVq7ecwjTIvLY0zhd/bf92yWMgCe2tvOLs3P0HPgC/VTosQXBz3+A3dNHcN31WdZreNkFIvc+SvWNXyB0g1LXBrInpohHLPTefjYNdfHimRlyNQ/Hl3QmQlTqLr+xv5+hdpOarzgzXaTsBoSjBoFUPDCUIaoFGH6AOPEu1ZOHl5IXjLYOIg88Ti2RWVVsUoaBr8Dathtr807yfZv58aFxasUieiIF6VakgtPTRWxT56G+SENU8T28C6fwRi+DUmiGgfR9ZG0UPdOCPzGC4bkEmo5eq1DPza/47iv4o5fQe4ealV+/ZoS8OrXnf0RQyi+9Jislqr98iQiCYMO22xqbIc/Be/U5vMnG9To+cpHH19/DKzNVarEUEoGO4p6+JPs6QhjSpd7eQ/SJL+G89waBUmh9g5zZ8CCvT7v4uSKa3cLRaozMhOQLSZOw8tjVarEu3UktEHTEbbpHj+EcO8TkQpFSpY6uCdzxYfY8/Dg/lp38+PQs/3RngtqPrvboUyjqfoBpGBiAe/Y4oYc/iy9uLggvhKAkDS7P1Zgq1EmETTa1RWnpWYfZ3kOoVgah4UfijcSba8SX8NwktYMvExQaFqFaOEJo3334Q5vxP6Bd453gTs9tV5JIPkqMYo769Or2cP7CLKH8PGQ6PuStatKkSZMmTZo0afJx4bYEmEgksqzC5HrGx8dJpVK3u01NPiSUUhh4tC31/ZA3LoDQNBBiRYBfCI2S4yAsG18JaOvGSKRRxRxIRTGSwN2+Bd1QaJqBROFE4shQFCEE41XBT49MEHg+22UOWXGYmjjLYG876R17CUVjqMDH932U71J98e/QUxlqb766ZJui8gu0Coi1duGOnuWZ/XvIl6vMvHOMDYbFUFc/p/wwo6WGuFSse9R8haWDEXgszMwhXRexSlbm/PAICcdp7P8dQugGr57LLhNfAAKpePHsLG37ekjqaz+Y1uwI2v4HsHfsR6gA345QvYkG93Hh8bUdbSzUFVUvoCUZJyLrTfHl14waFj85McNc+aoQd2qqyPbuBA8MJHhkKMbu7jh5x8cQGutlAe/H/xtlh1HROEoG+JfO4J49TuypZ6iOXkItCpTa2DCxL/8WlcNvAYrC4E5eOnwJKQRaKoNmWeixBDmleHWiwuf33ke0rQM31UpSAPgEAWxIaHTv7Wah5hMoRTpskDQUgQwIgEIdLs+XkUpQdZeLxgsVFyU0NAG1Sh0nu7xazFeNvhoAbqlAVHlgXm2AVHJ8MiEbdSXIrulwo4xtIdB0HYlAA1ASeenMMvHlCrJcJDhzHG3/A2sGnywZYOTm8ceHQQiM3gG8dCveTQbuPo34QhD0rcfq7kdz6o3rsR2m9OPvLBNfAJTnUn3lOSJf+W1qdvi2vk9KSW9E4+u7O1moBXiyhbCbw7ONNcXxILeA2v8AqbYOguELOBMX+EwmhNO5njE7w3tjWXLVxjXf8SVSKWIhi794e5THN7cTBAGPbWojkLCuNcK21hBhGvOSOHuc2uG3lv8mczNUn/8h0S/9FpVwFA2WJVCYtTLV995A1Wtodojh5DrqjgfhKIHnYdSqsFg1c2qqwJ6uGBERoMsAp5BbdT4JsguYQ/LqfCjEqvcFVxBN+7FfO4QQMD2xTHy5lvqRtwn1r6Nu3FrTOV3XkcePLYkvAKqYZ/DcQdoHt1EcGsKxQqRCBilToRbvawKg3tWH+XQ3dr3KjBbj1aPTyKiJisWXqnFmS3XeGCnwxLo4MgiICEnEgN6EQ/78ezh2CMdwsWMG+B5oGsXjR9n95GZeG68hjDT6dT2PvEASSIWhg7AslKYt5S9puoEEdFaKB0II5hyNH52YpH5N/74jYzke29TOlrSJG02u+juFS3kqP//x0pwMIGtVqr98kWgoRNAz9JFVYOqAXcoRjA+j6jX0jh5Ue9ctnwsfR1S1cuPllQpkPqSNadKkSZMmTZo0afKx47YEmL179/Liiy/yuc99bsWysbExXnzxxaW+LU0+PQSJNHpXH97kOLq41mdfYWoCr3eIYs5rBGNCEUQ4CgJ0IQgMk7P5Giem8gRSsaE1yqa2CKYmePHsJF4gMdw6I/kiAxu3UH/7IKOTc5jlHEZ2FgBjYB3Gtt1UcguYre0rLLhkIUck3UJE0+DY25SGxynO5xsLxRvs3n8vWvsWhos+uhAYWiMLUJk2vhlae7+jSeqOhwivbCYshMAMfPRaBYTAj8bxbuK5tugJRhdWf1gLpGI0X2dXq3nDh2QpJY5544auq6FLn3YLhC3oao8zNVVuNgb/CLnSPPzDCIgozcBXgvfGy8vElyucnCyyriVKX0SRMiBlgK4L1Dsn8P0AdL1hz+c4S1n49aPvYG7ZiTve6Eska1VEMUuQX0CLxrhUUaggQKBQpSK+piE9D9EzyCUB+U1biOCu2BalFGHh0Ru58oq/LO5d9SVSLdqorZLRW6p7mLqGK3SMeBLnmsxUQaNxuFQKMxpj0hUkeofg8NsAmFqjsfIVzMH1+NXVqzq19m6mkr0cvlRiruyQCJs81BsnduncmsfBG7nQ6JGjrwxO24GPfOsVyhfPXH3x6DvYG7ZiH3gYR7utaftTgVKqsf+L1UOR3GzDhme19zp1yM59IPsrKSUhJD2LGo4tDHxNo9GgaCVaIoVWKlB66afIchHHhVLJIVBvs+Fbv8ePc7XGG8Xi3KFp5Ose+ZpH1Q0YzlY5M1PCMjSmCxHaIl10RAySbo3aycNL3yOEQPN9UJJaqULp4mV+LrowDcGe7hTdMQ1N+ohqBVVvfKewQ8zWvEYA+MpvVKtANAYKXF9SDxoBZ1WtYK3bhH9NoPtazP511DUdpMSPxDE7e/Cmxld9rzG4AbdZ/fJrhaZpBGucD9CohBG1KsRvLehu1Ks4506usr4yoZNvk6hk4bEvNJJ1rhuiSilcoaFFE5ydrDfu01a5ll6YLXGgP0lUXHPO5hcwvRquEqBr6HaEwA9QKAIpSdeLgMGxisnD++6l+nd/s/RRIQQCEAjC++5D1moYdphx1+DIRJ5S3aM7FWZre4yMedV+1hcGL56fXSa+AEgFL5+fo2t/Dwlt5XVI13X886eWiS/X4hx5G7Or/yNpCq8LMM+fpPzmq1dF7BOH0dMtRJ74MtVQ5MYr+JgjQu8j9oc/2fvXpEmTJk2aNGnS5INxW3fgv/mbv4mUkn/2z/4Zf/VXfwXAyy+/zH/5L/+Ff/Ev/gXJZHKpb0uTTz6BVEw7Gj88V2Bk3V2M1gRz1YBg8fRRStF93/2c9Jc3f1dKoaTi/vVtvHR+np+fmWW6UGOuVOeNywv8zdEpcg6UnUbGrpKSQqlKoWOIUFs7QSBxtKsP6FZPP8GNbMCkRPg+5BdQ9SqJkMFSWFYp8u++wQ6KaAIG26LEjUaA1TctEnvuWn2dQmBs2oG2ii2bJiA0PY7/0+9R+du/oPI3f4F84QdECgtL9grXY0lJJDtLMD+LKGQxPIfVzCAqrr8UmG/y6cQAIqUc1rnjWKePEMnNYf6KRBil6RwZz/M3J+b45UiRF87OUXAVapWz7/hkEcO4GpjSlCKYXW6roa4plQsW5tDt6wRMqdCicax0C5VqHVkqIIsFVLmIcOoI3Wj0kvAlrn97FiQhQ2sEtpQkE10ZyIvZBl4g6UmFie7aB9fsq6kpkuGG+GHv3Mflss9JP0pq/wEAUuGr4qcWjmDe/xmMgQ0NcfkatFicsX2f5TvHpjk9XWS+7HBprswblxfI1+WK9y9jlUMthECMXsS5VnxZxLlwGjE+3LwuXMMVEXDN5fWV/a4+CF4sib1u46rLhGVjdPXhvPESQanQEBDNhjiogoDy+CgtxuK5riAZNjB0Qb7amNMqro9tNOaNVMQipAuc6SlKh9+jfPgdzN5B7IH16Ci0hTmCsUsUS1UuDk+RO3cW13EZXajyo+OTvDtZAd1EC0fQIo15WTp1MqHrxolhLJ2Hpi6wF+ctFfiQTGP2DqzYT7NvCK2je2l8eIB990OI668BgL1lJ1669ZZ+4yaffJRSiEh07TdoekPMv0VEECDdlYkDS99brbDqhfXadQhByVm7B4svFYFcfR26dnUWUVxNQLINgWVolByfhY37iQxtQCGQCixdQyqFWrcVv3uAyqvPc+jYJX78y9PEgzr3kKX34mEqR97FyxcwFn+XvCNZWCVJAhr35FNFd9W5QADBzOSa+xcU8mg3+A1/ldj5LNU3X1lRQRjkFvAOHcT4hM9tfjKD0dK+6jI9mUGmfzW9JJs0adKkSZMmTZp8MritVNpMJsO/+Tf/hr/8y7/k4MGDALz22muEQiEeeOABfud3fufXusH9pwkhBGemi/zgyCSBUkyZBvc+/gzGzAi52TG62tNYm7bhtXbROeMwUsou+3xHwsY0NMZWqfYoOz6HxvK0xW3mSg7CbAREf3lhlgP3PEFreQ5zfhQzamOt34x194O42YbXvAwCtFQamb/O4kcIKrkcMpahNDpFbzrKdKGGt2j1oy6cZHD7YzwwmEYGjcCX53mEt+4ktW+Y4rHDqMWAsG5ZJB74DG40RShsUbtu+0PzM5R//qNrmg8rvKkJ/Ge/T/SLv0E1unwMhHwP/+CLlEcuYm2/ByNfpz4zhd7WAamWZcHwjnjo177vw6cZU0m0k+9RPvL2suola/1m7AOP4uh3rspBaBpHZx3em8xSrdZJRUMU640eFK0xm46osWwb6r5cFsKSQiCicZibubpOw1qyHdIiUdQ1Ge7CsskmOxne/STTI+PY3b24BYE9P4WqVVC1KoYdIkARtQzCxu0FXdI29GUijGarJGydUtikWGuM6WTYRBOKgZYo69I2Zms70fseofrOL1G+h1KK9ngYc/teTkS6cfIeIyWJ1r6dR7+1gfjYGVSlhNE3hNa/nmokhpZIE0um8c4cJyhk0TNtuLvv56UzxRUBu6m6otg+iH05jyVWBvPMgQ14lr2icbmpJO7pY2vus3vyCMbABpqGgYvE4o1g7hremdodtkL1pSS8/35ktYo3MXL1e8IRIo88hUQtqwQxhaInFWZ4zsd2a0QDA11rZEkPpCPUfUmweA60RC1OTxWI2gY9cYv7q8NUf/AamgFK+IjRi6Q2bCC2eRvlc6dQiTRTxXpjnrBCOFMTaOkOJII3hgtkYmEmFqBly2P0yyLx84fpN10s08D1fBCgReJLvao3dySIGxIpQcWTOFMTWDv2YW3ZhRy7hCYDzMFNSE1HxhLLKvZqqRaiX/wN/Itn8MdH0EIhzC27CTq7cX+NbfN+XZFSYvStg+vmtytYfYN41zSMv+n12iGMVAv+/Myqy43ufrw1xJNrt60nGeLM9Oo2yjHbIKRfNycl0wjLwvZ8IpaBIxsVLYGCQOgUQik2tmtoQvCfT9f5/S//Hp2zlxCnDxOyDcSWvUxFWnjh9Ut8/r5HefPFwzywqYPIwR9TnL/aP6n2xivs+MqX0AbW4b/PftT9hnnZCoRAiydgbnrVz4lQCHUb4tcHRdM0/JGLax5zZ+Qi0X334t9Eb7SPK66mE3n0Keq/+Cl+9upx1RNpwo89Tc2wbvmcb9KkSZMmTZo0afLp4bajfMlkkt///d/n93//9ykWi0gpSSQSa2b+N/lk4gudX16apysVJhWxcaViThNMdMWptGzmwXWttJoeoNjXFWYg08uF+QqOFzCQidCfDvGTk7Nrrn80V2VzW4y5koM0bfR4kqBU4OD5GSJhm9+893HEuXcJLJtaNImhmwjLxp0aJ3zgYSo//0mjD4wAGYpSCATGlt2MT8yQL9bQNI3eVATH83EDSavu07+5FeEtz4y2oiGsh58iMrgZvZgFXadsxZkzQ9zVnWz4U1/z4GQKcI6+syKACqBcB//CafR99y/5emuahjp3AnfkIgCRsXPsG9rHwTOTBHMzmKEI/qL9QjJs0h0zoRlm/dRizE0t9khZjnvxLJG2TrTNu+6YAFcOdN4ensawGhnqVcejJxXm0nyFhbJDOmwuEwnWtURQ13x3EASEt+7CHb5w9TXLQk8kCQp57G17cK4EewyDwn1P86NTWZyygzc8x5ZwnKyjiLT2kZwfRU+kCMpFtGiM/RvaCGvBasNoBUI3yLtQdSUhUyOlwWc2tPDcWcVUoUZPwiYTMdGE4KmtnbSGNVpDAgMfYVq4m3YS6e6H3AIoiUi1YMYzrC8FGOEqtqmzsTVKyFYw2I8APCkbx0EpAqCaaUd/6LPoSiGFYLYKFSe7YltLdY9C93rSMxexaoVly7RoDGPLTtxVdloEPtJZu2pDuQ4iCBqiQxO8WAp7w5ZVbYnMrj781J2vvqiZIazHPo9dyCJLBYRpozKt1EMR7OzssnlCKUUmaqETpT51kbu3PUY1K4iYGiYSO6TRnggRMhr9inpSYQxdY69RZuHVF+mK27h+QNkwaE+nqF6+iJFMIzbvwsnncEolhGHgtHVTOjOLGUtT0mxGsxUOTxQoV+ucrQremC7y+S330Tt8hM/v2MPzZ2dwE634poUABlqjHOhPIBd7ZrhWiPDdD1J5+VmEoRPrGySo1alNjmJv2IqbXN7IQClFNRJH230AffcBlBDUmrZjv9Y4yQyRAw9TfevVZWNCj6ew7nqg0bPuFvE0ndDee/Bf+AnXV7oIy0ZftwnnfSYTpRT9SZuobVBZpRLm7oE0oevmJCccI7zvfqpvvkJPMsRU2SPnBpRdn8yBe3mtpPOFrW2UHJ/HtrTzbt1n/bp7GNr3KBdm5jn01hEq1UsYusaFCrS3Z4hdOErp8kVELIFarPxwXJeFl39O7Mvfwg+3sL0nxch8ealK/Fo64zZKrRxjvu8T3rwTZw0LTHvzTjwrtOq9668SIQRqDRtPAAJ/qafjJ5lqJI791NcJ5eeRlTIiEkWmWqmZ1kfWd6dJkyZNmjRp0qTJx4PbEmD+7M/+jCeffJKNGxtWHNdXu1y4cIHnn3+eP/iDP/jgW9jkI6XsQmvM5p3hMi+cm0eqhvXWxrYYe3tTnJ4u8uhgjCAIEDKg1YT2njBCCKSUaMpf084BwEDRmQxxeopGM9L2LnRdJyjm6W+LE7p8Ei2Rwth3HzUh8CMxIo8+RfXln+HkssQ+/w3cM8cICgXc7kHUlv3U56bJH3oXaGQ7ThWqbGiNoKMIDQ7iBS7XP3pK36O7PYaf2cnk9AJurU5/IkRLIoxnh5YFpAF0p467RhYmgD8xgr77AFceJ023jnPm+NXvK+bZkZlAbenl8OVZvHwWvSdKTzLMIxtasJviy6cWQ9fwblDl4Jw6irVuyx2rgsnVfDxfcqXH7VS+yl19aUayVQKpqPkBltkIAEUsg42tkaVA7BW81k7C+++n9t6boBoVMlpbF+FN2yGdQc5Ng2Gg3/UILxdDlF0PvV5Da2lnOFvl6Z09vDNVQca3IrLThKTHgcEMW1ptpFzbDuYKrrB45WKOi7OlRt8XoCsV5olNrXx5WysLdUnJ8QmbOu0Rg5Am8X2/EaNbDG5JpahF4hCJL61XqIChuGB9Mo5SqrEtEm7kihYEwdK4lnLthIODWcW6J54hNHYKbzEYZg6ux9i0o7EdqzU4NyyMtg7c8urZ2UZbJ4FhfujBs48rvlKE9j9AyLJwzp1sWJLpBvbQRoz991P7FfU5cIWGm2qFawUeKVHhCMIONfrPLCIAS0jsep6HeqPYLWGOjOdwfDCU5IHBDJ1xm5OTOWIm+Ais8Qt4omGzV/YDDNOgGGtFK1VxjhzGeuhJvFINEZGkHniU16caFaauhPFCHakUQaDQEPiGhd49wC/yLr+58x7WOyW+/YUDTEubuh+QCplkbBDXjHkpJW7fOmJPfw33xHvIWgWlBOH7H0f2DuKvapzZ+FzzzGwCjcb3bNxBrKMHf/QiqlZF7+yFzh6q5sp+ejeDUgq3s5/oo5+jfuggQalxnTTaOwnd8zD1eOqmro0RzeerOzv5xYUFpvI1FBC2dO7uz7C5ZeWcJJXC37iNaCKJe+IwQ7UqSWXBlj1MJrtZX5W8OzyHH0haExF2dSV4d3iety/NIWYmCKqLll9CUKi6bGwNUzl4prGtSi3OUQI3UBSqdXLHT/GLxEayNcm2zjh2ucZC5ardYl8mQmtIrOm25rV0EL7rfmqH3lxm92UNbkBs3vGRVFdLKTE7e+D8qVWXa9E40n6fHiqfEBzdgJZOuNZxrCm+NGnSpEmTJk2a/NpzWxG+V155hV27di0JMNczOzvLK6+80hRgPgXohs47IznOzJSWXpMKzs6W8aTi6S0r/Y6vfbiTQcCWjjhThesNvBr0psKNB94NbcxWPDRNIPpbabVgW1wQVutxYwlqi02PlVLUO/uIfPm3ULNTyGqF0Je+Rc1OcHCixkQ54DMt2pI9EoAXSOq+Ihqx0QbWr/nwKYOAnu4udE0uCUiOUqtXuWgammURrJGtLuxFm4crFTC+j3Su/gZCaBgj59iXmGXz+k3UE63Y6/uIGwq7XkbkFsCpI+IJ/GTmI2mY2uRXg5CKoFJac7l06ojAhzsgwJhAj5PjC/YChlllriXG0bJgIlfimV3dvDWcRSDQBAy0RLl/ME1M81fECnwEatteYn1DBDMT4PvoHV3IdBuiViW6ZRdYNlNWisl3Fy2YdJ2gVKAmBCdO1ljXkWHnhh7iWYdIvUxb0qdyE+KL0A1evpDlwuzV7FkFTOZr/N2pWb62o512K6DdEoAE6d5QQLmehvAi0XUdIcRS1drNkAzphEx9RaNkaATtnFgSf/cBzO37QCl802pUvqwRjPGVIrJzH44S1BKtiCAgOnMZOT8LuoG5fQ/VpviyjLphou9/kMjW3eDUwbRwY0lqt/g7CSGwfBcttwC1KiIaJUi14txCtZEbjhHavpfae2+sWKYl05iREHenbLa291D1JJYuSNqC8VLAVN5itlwnYurEvSot6Qj5qkMmalOs+2iaQbx3CMurEu4fJGjvQYt28OqlaXKFRiC6jo4vG4HaroTNqYkqAIFmUNQM5jt6sMIKXUp6kDTkoYboeD2BUlRbOjA/8wUSkTC5cgUHgVIKTdMajdaDoJnV3WRNAqCaSKPtugchBL6UH/h8CQBnYCNWVx+a51HSbKpWiMAQiODmEleUUiR1n69sbaHogicVUUsjqgVrJgQEQoOeQczeQSp1yVvn5xkveLjZ5Ta404UaHYkQxXrD5k8YV68fvh+QDuuYJYnre6DrCKXA9/CFgetJUKDKRayUhqkFvDeW45GN7eSq8xi6xtbOBHf1JtDV2v2vfCFQW/cS610+X/vJFuofUfWkUgrR3d8QWla5/wntuQfX/vArc5o0adKkSZMmTZo0+bC4c40GriGbzWJZK5siN/nkUfMCJotXRQZtUddQwKX5CvGwRbDGQ6+mG/gS1mUsjkQtcpXlD4yWrnHPQAohA8K2zsRUiWzFJWLphLriOOEoKAuC5Q9kSilq4RhicBMAjlJcKsHZbB6Ad81W7nrsKaqHDuIUCiAEZnsn0fsfoRZLvm8m2pWA7I3wrBDWxm2NioBVsLbuWmbBEtghjEQaJ7tAxZWUHBdNQNLPEy6+Q3rnPqS5AWtuiurLP0OWrz6gml19hB96ktqnJDvw1x2paehtnfgLc6suN1IZAuv2MoSvxQ485Nuv4V08R2WuApqGZRg8/vCTnI714ng+j21sYWN7HFtIYoZEBSvFlysEQDWeQiTSAFcDaeFo4z/Ada4ZN3YYNA2kxK/XGRuZpM+WDI28hbDD+Hv33tR+5Fy4NLe6dclC2WG+FtC1sv/3TeMIk7GCy3C2TMjQ2dQWpTUM2hp9Ra4lpgccGMzwyvmVx3JHd5KU1biWuFeCXu9zXRFC46LdwVvx7Uyfu4wufdZ3bebAxn20JsPUU63NTNpVCKSkFopCaLHx922IL+FijtovfkZQuGopZ7S0E3nsaao30ZdA0zR8NPRt+4joGrXj76Hqtca461+Hdc/DVA0LpCQiJJHFWyTlQ29E8LUdrVQDgad0fNnHzIWzpCI29UAxU3ZwfEnI0Bnsamch3MbBS6N0bgyTVWajHkXTkItC/Y6uJKW6uyJB3vFvzu7vWnyp0ONJvHIVhEbOE5yfr1CoeXQnwwymQ4uibfO8bLI6d7riQinFgh7l7YkCF+eyBFLSkQhz31CGrrBaUbG8FkL6JJeegtYeG44wGS+4XF6cI/raktSFgRusFEE0oQhbBoLGpVqLJQkWrvYDycg6kWiYUiKFV6siK0XQDWqYdMRDVEtlwm0dVF0fTSmStkah5vJ/3b8OpSRxLcDz1hZfru7NGvP1R0jdDhP53Fdw3ny10StLSbRIlNDuuwmGNjX7HjYBoC4FNW/luRCo2+sX2KRJkyZNmjRp8nHhpgWYd955h3feeWfp75///OccO7bSRqdarXL8+HE2bNhwZ7awyUdKxfHpSoRASXRNwwsUmgBdCHRN4a+SLa40namK4shkjmLNoyVq88SWLi7OlTg3UyRQit5UmP19KdpsxfE5l5cvzCEQGChcV/LuSJbZUp2nN2XQ1eoZidc+UKbCiw+8wGTF4+dWJ1se/TotQSMApq3rpaqvnXl+q0gpEZt2YE6M4c1MLFtmb9pO0Nm37DVP07H23Mu5732Pmn/1N8tWXVqTUdat34ZeKVF98SfIWnX5Z6fGEG+9gvHI0/iL2cdVqZOtBwRSkbR1kiaom6gmaPLREwQB9uadOBdOg3/9MRNYu++mtobFz82i6zqceBfnwmlMIehKhJguuxiBD2+8SP9nvsZfjUs2dyQYSIfJhEG9T+XHlf5eNwqSxCwd29BwfElgmhidPfhT40vjriNiooDIQ09Q082bGo9VV3KjfsT5uk93WL+pAJPQdPKeoOgE6JogZlv89MQU2Yqz9J5jE3n29ae5pyfyviKMlJJtrRZxu4t3xvLMV3x0XbCnJ8WmtjBw82NSCMFEDX50bAKpNLS+IaTncV7ATDXCMxu6CammNeGvAstzqL30U4Li8mx2f2EW57XnsZ786ppViEIIStLgzGSFi/MVNE2wr28Pm9dtw6xXiCVT5IVOVUqErlNwBYXF8y8T0olowZJdZ0yA0hXZ/nXEE3FqtTpTxTqOL0GALyXFjXs4WYBQ2GZ+eJgv7d/EkTMaBTtJLBphc2eCqKlzbua63kMCkrbBrZyTy3dU42zO56WzM0vj8fxsmbdMnS/v7KTN+uDVDbeEppN3BXMVD02DtqhJ0lComxBOm3yyqSiD7x+bplS/ej2cKtT44bFJvrKrm84Pnr+wRBWTHx6fWZZAdGSmStrW6UlHmMgt3q8J8JWG40naYjb7Blu5NFskD+htnQRz07SmY/SUp7GFpO2xR7n8s5/gGwZWKEw6ZFEvV1CGSSHWilNozLO+0rg4XyVm5ZjKV9nWGWegJUqh6lFxfZJhg5aQjrnG3PBxEF6uoJSiGk1iPv4lopUiBD4qFMENRZriS5Mlap7kZ2fmV7z++MY739OtSZMmTZo0adLkw+SmBZjx8XHefPNqtv/58+e5dOnSsvcIIbBtm61bt/Ltb3/7zm1lk4+MkKlhGRqBgplCDS9QCCGIWjqDmTBhc3mgWGg6x+YcXr9w9eY5W3G5MFvi8zu62N/TjZSSkA4q8KkGJu9dmEHLZcHz0MIRCEcJdIPRbJX5epqOm3iYTlmwfyBD0WlYoiyU67y34AIG27uTbDLFtVbYd4S6aWM//gWsuSn8kUsI3cAY3IDX0oYrlts8CCE4anUQu/8x/ENv4FUanv3hlla8A49y2UwxNH9hhfhyBXfsMtFyniCWYrSiePHMFBW3EUjThWB7d4J7+xIYzQDtJ4J6qoXo41+k/sbLBMU8QCMTdP/9uB29H3j9Zq1CfbHPjFKKpC2IhGPMFOqMzJfJDJ+jK7OThVKV7x+p8Oimdra3GKsGQSwZoGdnCcYugxAYfevwMq14YqWVSUwP2NuX5s3LC6AgiCYwB9YjyyU6YyY9HSlC679FLRK76cCQbawtRmkCWqIWNdWwUQuJYM1Aji9MDo4WODlZQCpoi9uUPZgvO0SvmwnfG80xlInc1LVHyID+hI7fl+byfAXHDzg2tsC7lwN29aY40BtHl+8/LqWm8+bl+aXgthQaLFZC5WoBI3mHLembE5qa3BpabmGF+HIFb2YKu5Bt9HxZhWJg8LfHppY19H7u1DRHEiG+tK2ddFcb/tQUgTB4a6zC8Yn8Ul+0iGXwmU1tDMa1pfNWSJ90ZyuZr32LUz/6EXp5Gl2DUCRCat/dHDR7OD5R4xvb13NpeIL+kGTjgE3VEJgpjTHf4CcX8iu2c1NHgpTFqnZjN0PR13j53OwKMbTuBbx4bp5v7GxHv835RwiBLwy8ACwddHXjippAM3lrvMSx8fzS9uia4L6hFna224imCPOpRdM0Ls/Xl4kvVwik4q2RLF/Z2tJo6v6Bv0vnreHCiurtiKlzeqbE45vamMxVUUKQcyQzxQpbOxIcHc0yUXTY2Z2kKxmwEA+xY88Q62SRyOhZrKGNaPUq8Sceo3L4bUTgM1J30ds60Pbezy/PTaF19OGiMZyt0pMKk6s4lB2fbF3yvZcv0RI26U5YJCM2Uctgb0+MkHTW2JOPFx7gRa/pHdoUX5o0adKkSZMmTZr8GnDTAswzzzzDM888A8C3vvUt/uE//Ic8+OCDv7INa/LxoC1iEEhFpe4RNjTCBlzxVnC8gIhlAFeDHUVf481LCyvWo4BXzs/xrb09hESAWqykqS7kKJw/czUTPp9FGCZG7yC+aTFZqNHVGbphdpymaeRcyNZ8jkwWKdU8NrTH2DvQiq0pdnZEUDcRAL0dHN2Ezn70niEA3DWqCGpS483xIobVz7Ynekl5FZSuM0GE86WAnokCQ9oNAgZSQr1OPmTws5PjeMHV4FSgFMcmCsRsg30ddjOT8BOAlJJ6Ry/WF7+FXsqjpELFE7h2+I4cP+F7yPrVnkNKKQwhKNUd4rZOuJwn3a0xW1Io4OCleQZS3UTE8u+2fZfg4C+oj1wABFo0invpHGZXH/Y9DzeazV63X3s6wph6G++N5qi4PiIUYkt/O/cNpkC51JS6pUq0tC3oTIaYLizvt5QIGazvSPH2aIHZQhVdE2zuiLO7K0aYleP92EyF4xNXqwJaY2HeODmNF0jWt0axxPJtOjVTonsoflM9YaYq8OyJyRWvHxnL0xq12Jx6f+Gk6gtmiqv3lAK4MF9he2saf0XVVJMPiqqubnG3tNxZvYeZpuscHitScXxMXRAyDVw/wPElM8U6l/Mug12NOerUrMORseUiT9X1efbUNL+xr4eUfnXsaYHHWDjD7INfoltVKZZr5PUIL2QVs3N1QFDXTbZ2p9B++Sz13AIajZm4r72Hb971BD8YruL4EtvQ2NGdZF93DD7APDhVcvHXKEVbKDvkHUmLeevrlcLgQt7jvbFZKo5HLGSyvy/NuqSBtkr1qxCCizmHI2P5Za8HUvH6xXnaYj0fyJKwyccbTdM4P1dZc/lMoU7VF0TugFtRDYPx3MqxrwlBZ9wiW/XoSkW4sFAjV3G5eyBNTyLEmak8AMfGF/jSzh4eG4qBDBAihuztQdQrVP+fv0EWskTXbwHTomdgC6/P+lycqONVa+hKkqtLHF+yqzvJ5dkCGzoSPHt6BqkUW9a1cWGuxFujs2iaYDiX4ovb2kgItynSN2nSpEmTJk2aNGnyMeS2esB85zvfudPb0eRjiuNL7upPM1OosnAlC1BBOmLxmY1tjC5U2dVmLgWNs3WPgbhJv+khlGQssBmvBAy0xnEDxcHRIh0xg96kTYdbQE2NrQjGKt8jmJlA6x3EMt4/cLngavzN0UlcX5I0BRHDJl91OTdT5Dd2d2LeoFnpneL9grQBAi+QVN2AN+sAVyJEjYBYzQ3QOlJrr0DXEeEIFxeqy8SXazkyXmBrexf27aY4N/lQUUo1BIxrM+vvkHimTAstEkVWrwaqal6wlHkvMm1U3avBTceXZGsBkcjVdQghEMPncUcuoPrWs9A2xEipcb4OxE268zlEa/uK8akpn91tJptauqgFClMTxHWJlM6KnhQ3gyZ9ntzUxk9OzpCrNsayoQnWtad45/I8IekhdR0pNN4bzTGarfKV7e3Y14gwC2WHo+P55evVBK4vUUDRCWgNa1y7gXU3QIj3j+JpusHRyfyayw+PFViffv/qACHA0MWa49s2VrfAavLB0WLxFa/p6Vas1jaEpmOGoziatkIcrQWCsVyVrd0pHF8xX3ZoTdikIyYj8yVOTRd5aFMXdalxeGz1ChtfKs7PVTjQvVx81YTgdNbltDApODqThdqy6pOUpbFzYYwgtzzhIZidoHv0ON+++1EqXoCti8Xm4h8sCaHu33iOW0ucuSGazjsTFQ6NXv1tnLLD86enOTCU4a7O8ApLsUAYHB7PXr+mJY5OFujZmELegQqIJh9PblQVaega2gcUX1xMpis+Y4Uy0bDNQGuciVx5WSWMpiQRAz63pZOj02XyVZeZQnVJfAFAwaHRLH3bWkAp1KKFrH/+FP70OLJcwp+baaxvYYFw63bQw+hJGxH4hKTkic3t1F2PQCokGsWax5PbOvnekXF0IRCLk9brF+epuh6/ubuTqGhWQjdp0qRJkyZNmjRp8nHjtgSYJr8+uAFcmCvzyPoWlNAo1xsZqkJJzkzn2dAWQ7Q3uglrmkZvZQZ59EXKE+MAbOjtZ9vjX+L/dzxLtuYykLQJaQrdMHiqN0R3PU9be4ZszQehoQIfWasia1Us36UnaaPW6AEDIHSDdy/ncf1G4EophYHCEFCpu5yfr7Kn3frIq0LCmqI1FmKqsHom9VBLBJmIrAiaX8Ee2ECQzDA7vXoQDxrZ1G4AdjNO+2uPa4ext+2h9u4vVyzTTJN69xDlheXj6vrwqSkD3DPHCdZv5/Ugw6nD40vL3ga2bxQ81taN5ddQpol3TQBWSomNxL653vPvS1zz+MauDmarAfmaR0fY4LXTE+jD5/ECH2HZ6G0dyEic+bLDWNFlY1JbEofqfkP8hIZtWW/CYkCv880NUQ7O+RTdABFZLvYOtkRvqvpFIijW1g54VV0fL1Do7xMUjOmS9W1xzkwXV12+tSPerH75FRGkWjDSrfi5eUAQ2bydYOwStRd/gtB03PFhrJ13IddvwdWWW++tb0/yk5NTVNyAiEajFwQan93SjrsocrqSZRZl1zNTctC06LJ5KhPWCZs6NS8gaQvibVEC10MCkWiYnUYF6+Q7q66vfuE08e17Ma2G0H8npr+O2Np+fLahEbc0btXfrOiJFZUsVzg0kmNzW5SYWD4GPamWiccr1lnzCBQfsItWk48rvu+zoyvB5fnVq2A2tMWI6JKbcaEzhMCoV0EIvFCEQEoqyuLHJ6fJVlyU0LiUreEFks9t6UDQsNS9wmCmUV19ZjJPse7RG7PoShuUA53xsksgFcWahyvBWvyM6TrUz55AS7ciy6WldYlT7/HA/Sl27LiXyXwNJWuEIz7Wwiy5jiFmDY2K69OXDnNutkzFDUjYy69F2YrH+flqsxK6ya8VKeXwcGrlgE+pT4YlX5MmTZo0adLk14emANPkhthGo8fI2ekCmmhkF07nrzbFbo9ffdALFbLUXvoxlfEsS+Fc2+bFN06SCqexnRLGWBkpFCQz/HxB8q3tAzye9vn+aydxqjVEKIzR0oZ0XR5Y10rKUFcjw5pBwQPHV0QsjYQhqQYwtopFhBQCX8LJ2Sq7umIg65ioxsM24IVj+B+iTYOQPvcOpvnhsdoKD/2IpbOxNUJd84k8+WVqLz9LUFgUWoTA6hvCuOchnCCgNWpxaW717whbOmZTfGlCQwBh8w5C1TL1MydABoRMnVAsTuihJ3i5bHJtM25T18iEDbimakQEjT4Mw9EuTh0fX/Edpy9N0t+ZZv2Jl/GtEKGd+1BdfbhCo+A2MuJjlkZMlyuEDE3TMN06mueiDLMR/HofscNUHj1h2KC7LFw8x/TpqaXqOeU6+BOjGD0DBJEY52bLbMlcteuyTY2wqWNogoejVdTxgzhTE2yKhslkevC37OWd4tVfJB4yGUzZqJvoaaEhaY3ZzJdXf9hPhs2GEPU+8TAZBNzTn2QyX6N4XX+DHd1JOiMad7yRVROgYSUZ+cznqb/8LHo0hnv8EEF2jtCuuzDauwiCAOfUESzXQdt519KcZxk6RyYKhKVHop4nKBUAgZ5Mc+gi/MaBIQxdw9QEEdtYU4RpjdkrKsmiWsBjm9t47tQMolohWJhF1OtohsFT92+jxS0xu+sBysLEEpCcH4HJUZABynXveB+UtrBGbzrCeG5ln7J9/WliurxloSdb9wnWmId9qcjVfGKR5a9bWmNM1dzV9681ZqML1awD/RTTHdXZ0plYIVanIhb7e5PIYO2qZyEEUjMws3N4R9/BnR5DoLAG1mHte4DnxysopdjanUIh2NSZ5PxsiZfOz/KVnd1kK43qq0S4MUcYKDakbToLWfwT7+EXCxiJJDu37eWYSONpJtYVf0AW51XXRYUjGJ09+PMz4PtoqTSmWyf+f/9btmzeidJ1SpEMRGOk5i5g9e1gTBp0JsO8eTmHpWvLREZBo4Ly/FyFvZ1hbrvZU5MmnzA0p8bCcz9Z8XrHN77+EWxNkyZNmjRp0qTJ2jQFmCY3JKYrdvUkeblYRiqWKk0AQqbOQCoE+PiaxaWCS2XrA8S3KNTEZcpnTxF0DbBwYgYz4RKPxNC0MAiBrJbxo3Em5gpsfPkv+eb+z3DRSzFWckmaDrt2r6O7I4SDxBEmeU/w6oUFJgtVDAGmJtjWlWBfbwr9WpsgISh7iuliDceXBBIOjZe4R8shjxykMjMJmobVM0Bk333UEukPzS+7OwJf2tnNwcsLzJUcNAH9LVEeGEwT0xrB7lqyBesLv4GeX0C5DiIax0ukqQFIyYbWCO+N5la1e9nVnSKqS24iab/JpxQhBBVpsFDz8QKDlj2P0bbjbvTsLOFEnJxr8ZPhyooM8nsGM8T1YFkANbBCaBu2c2SkxPUI14FQmHfOT2GrMG7ZQ0wXUKEOXh+vUKw6CCUJmzr7B9LsaLPRFgPCtgzQzx3DPfwmbrGESCQxd+zF2LwLx7hxEwkhBGpsGOXU0DSBvM6uK5ifQeuPYlznQdMatdnVk6S1OE35Z3+L9BoCR9n3SNWq+Nkp7n3oi7yxAINtUe4fSBPR/JtqVSODgJ3dcc7NFFeIqwD7+9NoKrgp+7W45vP13Z0M5xwuzpexTZ1tHXE6Ixr6DSoBm3xwqpE41lNfw54Zx6lVsPuHqB07RO3t19Gicezte6BSwq6WqIWiAOTqAapeRZsYxvGuimb+7DThwKXu9XN4LIfr+Dy0sYODF2Yo1pcfR10TbG6LEixaZgkhcDDI1gLChsEzOzq5dOYC016IeGuEwYjAGjnLz/UUJxYUTm4aTQh62jv4zJ5Bosdew0imCezw8u/RdcxqGVEpIXQDP57E042bnv905fO5za28M1bgzEwJ15fEbIO7+tNsbrWR8tbPT+19LP5WW6ypgLv60vykMLXK+mBnVxzZnAQ/1ejK55GhJJvaYpyaLuIGko1tMfpTNmFuYDkrNGYcjaBSZuHyNFqkm2R3lNap83D+NNl4Bxi96KbFT0/NUHUDBNCTjvDYpg6yFZeBdIS7Mho9QmGVZwkSae6qjnDy2b+7eo3P52F0hD33P4q59wBCXr3+B6EwxsB6cpEMOS2MCiSZoEa7qFN//geIVAZsm3D/EOLoeyycO4sjoO/Aw7Tc8xmq0QSmri2WeF0du/GQia01xpRgZUVrkyZNmjRp0qRJkyZNPlqaAkyTGxIEAfcMtpIrVzg5UVgK/KciFk9ubiOuB8w5Os+dmiR/9mwjsw9ob2nj/gc/Q1UY2PE4musg81m8eh2EQIvFEfEk5WwW5TnEXvgue5Np7kqmUI6DNvkW2v/1j5msaQznKkwWXQIEibDNTKlO1BAcHc+jgL19aV6/2CgLqfowmq0uPXxu7YzTXp7l5N/9NYMpu9FoOwhwRy/hz04R+cI3qUZW+v//KlBS0hsRfG1HO1W/ESyKGQoVXA30LvUFaelYdR1pU/LUtk5+fnaWunfVUmlzR4JdnRGCoOn9/euK0DQuFSUvnZ3AWRRKBbClK8FDg+tId7bRMjPLY1aUt0cLlByPVNjkrt4kfXF9KYCq6TrVQIAUhNdvwzn/7vLvkRLlOmhtXczNF9D37+TtC3MkZYxnnztJ2QgTjYQYSIcQvuT1C/PYejtbMwYaoL/9MuXnfohyGxUjwjBQ89OYhTzm/Z/Bu4F5kK7r+KOXiHouQ11DnB9f3v9COXWE77O1c6Vd111dERYOHaF0baBcKlIhg4jhYAXzbDywh4iQKOndlPhyhXZb8bltnbx6fp7KorhlGxoHhlroj2sr+lishVKKMB7bMjo72zJA4xrsC4GjDEI6qGZvi18Znm6gey74PuVfvrT0uqyUqL39GtambYS37IRFAUYhWBfTUFv7yeaKjEzMo5Qi1NJKTgtzZjxLCZOFUg3T0Njdm2IyW2K+1Dj3Q6bOY5vayFgShEFdCgqu4J3hBUayFTQU2uQI+wbbeCgtyR49hNJ1Tgzt5/jZUcx0hkBpmEjGZ/L8qObyjY17iPZ0Udf0pQoxU0n008epHXkb5dQBMNKthB/4DPWWjpu2K7KVy8MDMfb1Jggk2DqERHBb4gtAS9jA0jXcYOX3h0x9RVUeNMZIX1znkY1tvHl5YelaF7EMHt7YSntINQvFfg3QpUdvBAY3pQAIlKAmBUXZqMoWSpG0GiJeNWiIEtVA482RBS6cOENlvjF3xCI2j285wJbxw2CYlF2PVy4Xlr5HAeO5KsW6x7fv7mfX/Gn0g4eoFvK4gJ1pJdLVS3driqmFAnJxzGkIQmcO0bt3G3UVXVqfJ3TODNzNq6+8i+fPN/ZF17h/72a23fck0jCJdnRS/ds/RxYLxC0Nx5e4505SnMvxud/6e1S8Fl45Nws05vh4yKQrYYOS7OiK3/R806RJkyZNmjRp0qRJkw+PpgDT5H1JhEwe7ouxqzNO0QkwNUFbRCdSLVApC547uUBZCrjGG390Jg8izWe3ZrAvLlCrVvEzHUip0Kol9HoVf2GGjk0ZhGaAJpCFHKpSQk+3EpgmC3XF8ZkCLfEoh8bnmC05ZCIW9wymqbkB5VqNU5MFvr6vn2TYpFD3mS1fbfQ91BKlI2oQHHwbz/PI1zQ6olczfmW9hn/xDNruAx+aX7ZSCl15xBetwtQtPicrKRmICX5rXzcL1QAvkKQiBmkT+IBNlpt8MtE0jarUqXgaZ2cWlmW+KuD0VJFUyKS/E1ypsVCpkgobpCMGYUPH0huNfIUQlKTBe8NFLs6XUQp29iRp2bqN0rFTyFrDc1+zLUR6gGK+wIaBTk7lXCYWytDSSaHqokUtFioOVddnKBMhYWm8M5JjXbqDltw0ued+CO5Vuy7l+/jTk3D8EOGd+/Di6TX3VSmFFo4gJ0Y4sG8LEws21do11l+axvqOBF1RHa6rGAnVSqTLc4TbYji+RBOCkCEwhUIpCZfPEN+2E+H7mMU8ynMhHMGNJQne5/qgpGR9QqNrbxc5J0BJSIV0YnqAvI1gmFIK3/fxNZPzWZ+jEwvUvYDWmM3+vjRdEbipJgdNbhnDtKkcfmvVZe65U0TrNUiAI0yGszXeGitRczx6MikeuL+XkYujjIgo2VyFhCY5NVtmstgQYKqlCt/e10XGlbixNHo4RFQPmHcE74zluZR1GMlV2dgaY1dfhrOj8+QKZV48XGLP+k463ID49h0cvjSLJ8EMAmQ0jqoWESgKNZ+5/r1E2mNL85wQAn34AtW3Xl22L35unsoLPyLyxd+gdgtJCDIIiBCABihWrfq6WWJ6wEMbWvnFudll69EEPLyhlahYvQpNyICdrSZD6R4KTgACMrZOWAs+Vr0vNE3DVTquBENThIT8WG3fp4FASqZrgjdH85yYKlLzArZ1JhjMhInZJhP5OpO5EoMtUTyh8+6lOez8VYGlWnN48cQYnbt3ErVDvHdmFiHsFRUkxZqHU6vhHXkT/Zql/vgw7skjdD/yOSJnT+P6EkVDgLc0icgtQNdVAWayqnh5tIzo6EHMzaBch6GBbqrxDH9Z242fz5G8XGXP/V+j//IhtLPHCJsCPWIRjggiZ9/ji3c/SaXuMl92MTTRsLhUku5UmMH0zVlnNmny/2fvv4IkudI7X/B3jovw0Cq1riytq1AFrYEGGkA3gZZkc3iHwyWn99osuWMzD3wYrhltZmg026GNXZv7wNmdtdnl7CybZPclW4IN1dBAQ5XWIkukFpGZoSM8XJ19iKysSlRWoQAUJOP3UpXu4e7H3c/x4/6J/9eiRYsWLVq0aNHi06XlgGlxQwSBT1wq4uFmNK08foDa0f2Mb7qb/OkJZDiCnkji2nVsT1F3fc5MLPDEnjVs2jzML88skC/ZqCAgYiXp7O+hOyLoKI4hu3oQ2fZmpWBNJ9B1hBVmxgYPnR/sH2d0sak7n687nFuo8NjmLkKmiW03cD2Xb+7o4vRCg/qZHCoWYnNXnJAUBMUC9vQUAJWGT2fU4EpxBm/8AtqO275QatmXouT7lrXxvZbc9z9RbAwOTVY4NVNmrOhgaILbBtMsVmxyZXv5d0cmi+weqvPLkzmmiytrJh2dzPP41m7aIjo/PjxN5Yo6FfsuLrJzIIvXN4zp1gGBCHyciYsEnseOtV388Ln36MgkmCzZNHMCWCo6H1B3fUzlUQ3ADQT+9PgK58uVBPMziPw8XMcB4/s+5rrNNM6eIHH0Tb6z+TbO2jrnFpsG7l1rexhY145cpQaAkk2vZ0gEhAxoPgfUZQOvrmPZdeov/5LKzFRzva5jrd+Kvuv2D5RHC4IAi4Du5VrlH74mxopzlTqvni9wevayBNzYYo2JfI2vbulibUK2jLk3GaWazjjlrW7AlCELr1zC6xri2ZPzTOdreApKdYfSpMPITJGn9q7n2JEx+rJRqqUSNdcgZkgyTglneo53/Tx3Lh6nPaIRvvNBplJ9/PjwJA0/YKEeUKq77B/Pc26hxv1rUsydUPh+wMELczy5bhMVGcJuFBAC6kpSTXbS1dGJJEDpBtPKZEBKLnU+03NpHH5v9fNt2ARj55BbbvnE+pIuJbpdBS4XOl8+fhCwMW2Q3tXLkakShZpLNmqyrTtOh8V1I/mDICAiAiLW8pKPNd5uNoHQObXocGBsnpLtEA0Z7OpNsbndQm8ZyG8KQggma/CLo9OMlxzyteZz/83zCxQbKTJhnfdG8wylw2TjYf72wCS+FxASzblAExAhICiXOT4VZrdUWFJHeB5KW/l5ZEoozOcRhgnuyjksKBdR1TLhbIZEIoXQNHy7hjOzUiZPajqHJvPN17VIHDkQZXdfmnkH/ts7EwSuS9aStEmDqdkCd/bs5pZSnmBmAhmJIVWAOzlG6pYq39vRyblFm9NzFaSArd1xhpIhzFbfatHimqRUg/tSV88r8aABWFdv0KJFixYtWrRocRO5IQfMf/gP/+FD71gIwZ/+6Z9+6O1afL6RUqKdO03tvTcQZohyo2nxCOo1hGmiRWM0FgpA05hV0yO41Rm29aR499wsNR9czSAaMrl/Ry/a//5fCSIRZLYdz1x6+VUKs7OXujR468Lcqu145ewc393dx1TDwdQkEVy2d4SYL8WoOT4z+QoNL2BXWkcaOtRBX6VAvTAMlBCgmhkASik0TcP3/U+tNkyLFh8FV+g8czLHdNFGSEHV9aiUPSYLdb6+vZtqw6W2VKi66njkKo2rnC/QjGA/MlmkOx1Z4XyBpoviQq7EncNtjMwVWaw00DyXTDLGQ11x1OI8vh9Qb7jEMhoIgS8lMmgarKRj401OICwN7byNpmkIM7QsP7aiHY6DkFozYl9rZtOtNg69bAfW9j3YR/cTPfw6t8QS3JJMo0WihHo2UbtGAWbPimAOraNx+tiq68Prt1B97qf4i7krNvKwTx7GEqDdet8HZsLcTBZstcL5colAwZvnFujd1YXZ8rzedAIrgt7ZgzczyYr0C01D6+pFWRaTZZfJQh0hJZ0RiSDCYsXG9QPenShw/+Yeop7Ne2OLOKE0bX6VxmzTGDtfd6liEFtcQB16l4ODIRpegBAC+4oaa3OVBlNVl0xHG/MzOap1B2Wl0PEJAA1Q8RSLdZdsLIa+1Bdi5sq6LtJp4JcK1zxff3oSuW3vTXfACCEIl/I4R96jPjkGgDkwTGjHXurRxOU2Kp8OEx5fn0IJiUThOM4XWkZMSI39UzXeG11cXla2XV4/lyNfT3LfYBw+omxbi8v4QuOtC/PUfUWhfvm5b+mSUzNl7hzO4CuF7TfHV77u4PmQiScRiznCQhFUy4BgQZmYYYuOkIeSigXPxxXNeSgW0umNGSQbxWZm5JWYFmgaejIFnov9zmuoRh29o5vYztsgk13+adNZe/m+d6VjuLrB3797sZmVKTUaXsBkpYKTSLNvfJb1W28n6Xv4ZtOzL3QdJSVhXHa0G+zoyIIA5futzJcWLT4A2aiz8NzTVy3v/u63wWo5YFq0aNGiRYsWnyw35IBRS8bpD8NHMV4HQcCPfvQjXn/9dQqFAplMhvvvv59vf/vby8dXSvGjH/2IF198kWq1yqZNm/iX//Jf0t3dfd19P/vss/ziF7+gUCgwODjI7//+77Nu3boP3cZ/6hhug8bh95CxONK0yETN5XV+sYDW3Y8ZSROUCkRDBrOu5OCpCVKm4LHhPoxUBlmvsnDhIm+8PsNvPvFd7F/8LX61gjGwBs+0EIaBuWMPnoLFmotlaOhS4l1hILK9ANdXtCfCpEOAD6byyUQNzs5dNlpesAX9G7bQ2Pc2mYjZlBq68nw27aShFDYGo/kGz14cxXUabOmM05fQMVqFr1t8TpmtBkwXm1kuSikiukYFDwX8+vwC9w5nODtbAiAeNijUr22cEUJwaray6rpi3WVkpsA3d3ZTXSpKnM2b5J75OfnNtyGEYKFQ4fZNIfZFwhR9SJgSamV0I4TXsNmwphfr9EEcTWJ0dOFMj8P76j7ISBS/rYvzJcXxmUX8ADZ2xhhKhbCuqAPhComx8zZiA2vwzp9FOTZa/xro6qNmhLgWfhAQ3r4Xb2ocv1xcsc7sXwOx+ErnyxU4YxeI7ryVuhn+VLJOpJSMF652ll2iZLuUnIC26yfltPgI+Mk0omcAI2QRlEsot4EMRyEax7fCyM4ezk02MzKVUhiWRVdxikwiii81ZODRFzd4+dcnqWd6CcsAf+Fyv+qIGrgLFVylIJ5lbHwGoikUitClKAEBrh9wZrbCjr5eyvkiSA/h2HgzEwx1rmHGgZIwSYR1dKFAgaEJBlIWQnjL72BK0xAha7n2y/uR8ST+JxBsEC4XqD7zDyuO2zh7AndylPAT36EejjWPLyVFT+PMZJWxxToxS2dbV5zOsER+Qeffkic5OJ5fdd2J6SLbe+KktVVXt/gQ1HzBbMnG81f6Sg1dY7HSYGyxRkes6eAsVBsMZaIcmypRTySJ18uISgGSaRqpDvy2NCcbgkyHhT27SMpUeNEoQjSDCUzPZU1YEdSqEFlOPyYwDCJ33E/jxGGc82dQS7XH3LELKKdBuH8I0dOUBNQFpCMGi9VmAEImZjFTtJfrGEkpEaaOiERZKNdIZToopEziqcxy3ra5aQcNIUGppbnos/NUSikRQhAEQStgqUWLFi1atGjRokWLD+CGHDD//t//+0+4GU1++tOf8sILL/CHf/iH9PX1cf78ef7rf/2vRCIRnnjiCQB+9rOf8cwzz/CHf/iHdHR08MMf/pA///M/53/73/43TNNcdb+//vWv+Z//83/y/e9/n/Xr1/OP//iP/Pmf/zn/5b/8F5LJ5Kdybl80pJRXfVDpuo4ZeGhDw3gTowSlPIOVSR7d1strZ3PYDQe/VCAX6cKPdfLAhnZOzNtUjAhuvULh5EVC0Tm86QmQEmkYlDbtJPO17+CMnAQF4e170NZtpp5IEytLpICFaoOBdJixfH3ZCaNJiWVI7h7MIPzmx2wQBGzrjDJRsJnMNw1kxbpLvn8TvfNTRGuLXPmxag6tQ/UOUFMGPzs2w2LVIRKJUKvVGF2oMpCJ8OiGbEvSocXnDiklY4Xa5QUKEmGd+WqDQMFC1UHXLlv4dvel8K5XrEE1pYKuhRsohPLJ6E3jkmzvoPexryHPj7FuoIPzuQrjZY/7tw7w3Kk5tMBDkxCW0D3Qxa2JAP/CHI4Aa8tOgmoFL79w+QCaTuRbv8szc3BiemZ58WShRiZq8uS2TiLvc8K4mU609h6EEDRuMGOtHolhPf4tgtFzeBfOgqZhbtqO6hnEPXn4qt9LK4w1uBZVzOO/8SJGeyfawFrsRHq52PJHRQixbLxaDe0Dgh4kHy4oosWN4egm4XsepvqrpyFkAQJfBSAl0bsexLGiCErLv/d0E72zh1AhT1AqIA2DVGwA2TvEbMGhJxzgL2V86ZpkY0KnvrCA1hZFqABp15GxDAApS5IrN7OcBKBJwbwrCHqGuLszhDGyjwDB/bdu5OcX68wVbYZiJqim/N0jfTHSh14Fw0AfWEsjmcGxIoQ2bMU+uv/ySUqJDFkoz0dftwnHv7n1hDQpcY8fXNXpE9Sq+GdPoO2+kyAImGsIfn50CttdakMRzs6WuX0owy1dYcSHLZT2OaBoe9d83gZLgSXpeGv8flwEzXpBUl59LSUCTUoc18fQJRfnK9w+mGFsscZYNWBr7yB6LUXO01ko1bl7c4x9J8+zebiLc0pgBBDBIxAauhA8uL2PjomDvL9HKyGQyQze6DmEGWqOrWgcY+1GglCY+oG3MTt6aWg6ge+xqzfJ+VwFIaDi+CtqzVi6bP4dCqN8H0cPoaRY/o3ROwiD6z5zZ4cmIFRYxBs9i6pWMLr6ED0D2FbkM29bixYtWrRo0aJFixafVz5XNWDOnDnD3r17ueWWWwDo6OjgjTfeYGRkBGhGm/7yl7/kW9/6FrfeeisAf/RHf8T3v/993nvvPe6+++5V9/v000/z8MMP8+CDDwLw/e9/nwMHDvDyyy/zjW9845M/sS8QjjCYqXjkqjYxU6c3GaKjXiOcm8Ybv0DgNqi//AzoBl65CKeOMtA3zBN3PM4vTswRmCZhQyMbNehPWZyYreC1dRNMj+GHDPR6hUBvyn7p8SSqWqY6cho924kMh9G276GmGRAEdER1BjJhDk0UyVUa9KXCBErhK0V7NMTWzjhZw18hVRJSLk9szDJTTTK6WEeT0JWN0j34beTUGN6FMwhNR1+7Cb+jC88IcXSyzGL1atmiscUao4U4G1JXO6NatPisMbWVDpOQVPSnI0wWbPwgQIqmAXd7b4otbRZ1Gb7mvjQddnXGeelUbdX1GzpjhKXikp3WQ+B19JDtGuTxhuLHJ+Y4Ol1hTcjht/f0EfUbRDybzkae9sI8qaJHMLyBxvkR7JHTxJ78bRqnjuAvziETaUJbdnGmezMnjl8tObhYdTg6U+Gu3gj++wzF7//7g1BKUQ9FkJt2IjfvAsBecoCEYisLkQvTJDy0luoLT6PsKsbQerzxC3D4PaL3PUqjf+1Hc8JIjbwjmCjY+ErRk7Bos8SKaP8gCOhPhRFwVTFogHTEJBESrdpPnwBKKeyOXqK/8Vv4F0fwc9PIZAZ9eCONVBbf89jQEePkzEonDO2dyGw7/Zko/R0Jbm0Ixg5N4iOQmk7E0HhoUxfB0V8TNnRCmkDPz7Fp7T0cuJAjqJYxdZ1N8QyTroanYHNXnINjeYbb4qS707g9TzBddqhUfH5z7wCO57NQsUng0TV/gdjbL2Ffyu46/B7Rex6mMbQBbetujMV53JlJ3PXbmbWy5Oo+ye5uupMdxG9y8XrdsWksyY6thjd2Hn37XlzN5NWR+cvOlyt49+Iia7J9ZD5Xb6k3hraKQ+BKms7u1jvFxyWmKwYyUS4s1gibGvUlyU3b9UlHDNZkI7x2do7hbJSq4+G5Lg9vaOfsfBXXD7BDcSp2jSduGWLy3AW8cpHjR0vsXjtAvL0dKx7FMjQyUYt8zWZ/ZjM9d2cxZkbg3EkAtEQa5Xt4kRgiliC8Zh24Lu6FsyAFoaENGPUKjVgKgK4wPLypkzfOzaOJ5vMmGtIIFBhLU7oSAhGJEU6G6Uh4mEPrMNZuIujswdY+27RHDTBGTlB565XLaUcjp5CRKJGvfpNarBXU1qJFixYtWrRo0aLFatzQp+38/DwAbW1tK/7+IC79/kbZsGEDL774IlNTU/T09HDx4kVOnz7N7/7u7wIwNzdHoVBgx44dy9tEIhHWrVvHmTNnVnXAeJ7H+fPnVzhapJRs376dM2fOfKj2fdkpBwa/OD5LoXbZGTGcNIk5F1FH3ia8YSvlF36OTGbx4inM/iHcU0fQJ87TfeBF/vkDT1Jt68MLhRnP11mouWzpSnB8uozbMUA0BMxNgO+jNJ21A51EZs8SqABvfhZhhdF9H5Y+MOPC4/FNHeSrLvNVh5LtYkhBSBfcPpiiIypQwdXZKYZy6Y/AUDwKNI20rhbCHtiINrSZiKaoO81zdAPB6WtILwEcnSqxMZNF+V9MKZQWX06CIGBNJsJ7Fxcvm/EUxAxY1xahLW6xuTPG7p4YSSOAwKMvbbGrP82hK6RxdClY15lgXUccUwqyiQi5so28wquZjpps74rh+1ePtSBwSRrwe3t7GC15nJopsyMW0P7r56ge3Y8ql9BMDbt/iMaWvej3fBV5cj+irQO5Yy+6AJHO0khkeftEHkOTdCYspBRUbHfZMXpmtsLu7iir5zh+tOv3fnOz6OhGmCZq6dlgdvdTf+sVVL2KjMYIjKWj+z61N35F5KmOZRmlGz6u0Dk4XePdK+8bsLY9xoNr0yuy7TIh2Pm++wXNe3b/+jYM5bVMuJ8QQRBQiyaQ2/cipcRXqpklsmRw7IpI1nXEGJm7Yu5QYBg6dw5nEW6du/vCDGbWczFv0zYcRh87g3PgFVStSl82itE/hL91L1s0k1rF4nRhHrdWhVKR/mwHu9cPsr03RV/Solhr8OZI0znZEQ/xxJZOosJFmYoNUQPvuX/EnZ1c7tNCCNwAcq++QijVxWIsQ/vDv4FTafCLQ+MsFhxEOIY/1UCfneCRzZ0Mx+XNc8IIgbhORh1SooSg7MBsaXVpNAVcXKzR1mV9KrJ/N5O0pRE1darO1e8Npi5pi+hAK7P246J8jzuH0syWbfqSFqP5Oo4X4PoBdw5nCYKA3lQYXQSg4FyuzNaeJA+tH6BkuxSqDoXpWSbPjVAsVQEIAsXZs6N0C5OvrutmslTn1+dmCQKwTI0LXoKO7j3cuWYToXoJ2TOAf/oYCrDWbqJx8G28qfHlNjpnTxGuVzEffoppZVFxPJJhne/d0k/J8Xn25BxPbuvm+ZMzXJk0pesaD27uJtEZQq0dpu59Pt5BQ+UClbdfXan5RjOzrfH2KxiPPIXbmphafA4wdcl9qZXOfZPV5yUhBAXn6o4b1iUh2erQLVq0aNGiRYubww05YP7wD/8QgB/84Afour789wfxwx/+8EM15hvf+Ab1ep1/+2//LVI2jQHf+973uPfeewEoFAoAV8mGJZPJ5XXvp1QqEQQBqVRqxfJUKsXU1NSq27iui+te/jgWQhAOh5f/f+W/Xxo0nZdPLKxwvgBslFVOv/Iaa9pjWJrO3MPf40jOZr5QJWWE2fXEHjoPv4p//iRtX32K4xWPAyfGcJSg7gUMt8XYO5jifK5Kvu6QyXQSOA7tySh3tWsEB2aXj2UOrcMLRxHLxhbF9jaDP7p3iLcuFhhdrJGKmNwxlGFNymgaoNS170MQNAuvLrg6753LM1W0aYuF2NgeZbgthhnYBIjLhbUv7eqKsHNfqWY04pftfvPl6cs3Ml6v/P8X/XwvkQ3BrUNZ3r14hZSXgpgh+OqGLFljyWATLF0TQ+fO/hiD6TBHp0s4bsDm3hTvXFzk1EwRCazvTNIeC7FYdZAqYFNXjOFMmDAuXEfySngNhqOCjjVJjBMHUJOjWPUyZiZJ4Z6n2LfgMnaygFlYZLjnVm5JdhPPdqKUamaXSY3ORJhIyOTYdIm669OXCrO9L8P5uSJeEKD4aOPwRu97I5og+sDjVF95FuU00EMh7NwsImShdfZwpflLuS4szCH649fc35XH16QEIRiv+LxzcfGq35zLVehOWuzuCC0bm4XyuaM/Rl/S4vBUkVrDpytpsb07TpsZoNQHn9Pnsc/f6Hi98u/Pqv1KqeUsqyvboOPz0HCatdkoR6ZKOH7AQDrM1q44Kd1HKUHge/RHNPoybZRmPfyzRTB8ousHKN3yEMeDCGdGC8yWymSSce65/zbmxqfIF4psazdZv8bCj0iieoijdYeuRJjh9ijrs2Fi0lu+/1pxgfrs5HLbhBCU3aZ8nxcEJM+c5wVps2cww1jBIWdEIRldnuNcX/HCyVl+e08f8VUMTR/lHnimhbluE/WD76y63tywDUdqfFD+muurZam+j8On3Y+iMuDBDe08e2JmhRSZFPDA+g7ieoAKPlxbPoux8GHehT+tdgkh0DQNlMIPArJmwHd39XAmV2NkoQ5CsL49RmdUJ2HpTJVinJwugRBs6YwzmDIJ4dKRkPy66HN6Ko+/5HyBZv2YLXt2cMEW/L/fGSNXqrOpO8VgOsK+0QWkgGR/hrFUhqG+5ntmeGAN8vwpVD63wvkCzdpm1bk5isdP8nO/aznbKxUx+fq2Lu5ek+bwRJ7v7Orj2HSJfM0hEzX56uZONiQl3tL1/6yegVfeXyEEwdQYXMMh6k5PEisX8eKpT7GFN5fPes5pcfMQjQYLzz29YtnAN59c9bd+oHjm1NXBpY9vaiNktvpCixYtWrRo0eLmcEMOmH/1r/4VQPOj54q/bzZvvfUWb7zxBv/6X/9r+vv7uXjxIv/jf/wP0uk0DzzwwCdyzNX4yU9+wt///d8v/71mzRr+03/6T7S3ty8v6+rq+tTa82kwma+yNpRjezu4Uud8EKHqgTlzEFsp/Giak/FBnn/pXYJAAYpCscJ40eaeHY+wu6ubkgxzbNbGtMKYQAwoNwL602G+vTvDaL6GXbNZszbBGmeB+MgBiCx9zMcSxO64D6Oz86q2dQO7BttouAG6hJBx45okZ+bKPHNmirgpeSTtI8/tIziUo9DWzpo7bqNtYIh13TYjucsf4JHw5QKrW/vSdHe0r7brLw1f9L58I+P1Sr7o53slj2Y9NvSkOTpZouJ4DGUibOyM05NsjisVBPiLOVS9hpeboae9g95Oyd7hTgp1h7/bP4Gn5HKfHy+5mJpkQ2echzd0EA19OP2fwK5Tmj6Hn03hOR0s3P4YPzk+R6PRNCK5uRxnMl3MjhT57u4+uhIWADXHI3e6xMtnLhcrn6+VOTVX5ckdPUgF/R1ZdO06UfUfwI3cd9XZSaxvAG96Ar9UxBpah4xGEYZ5VfaNJQXp7u7r7s9bmMM9dwbn/GnQdSLta7m1q53jpasN3WcXHO5a100ivFJipq8T9g534vqKkCGRH8Ew9Hnq8x92vMLNa79fWCQol8Aw0DJtSDP0sfY30A23r+vCD8Ay5DWNdp2JIYLe38abn+WiLalOTBI6/ApbS0W2d/dSjg/z/Mkqjw8leEJME4ydJBRziN73VfqB29Z24Su1ap0mp14muKIoeLXhMV2qgpToUqJ5LtFUhKovOT5TpTsZuWofAAuOZMOaa/fnD3sPvD13oM1OEhRWOhy19i5i23ejpbOEag4d6RKVxurR/Rt7s3R2Jj7Uca/HpzkO2jsUXZkEJ2bLzJZsstEQ27rjDGQi16239UF8mufwYcbqp9Euv5jHHT1H4/QxUAHmui2YwxvoSmXY0AuuF6BpYsUzckMP3LexB+CqZ+d6v8jJnE2QzhDUqqBg84Z+fnUuj6cgFtK5t8siVM/hOwb3DnXyN4dnObc4xaObOtm6p4+YZRCkU5iVIpWf/S26fnnOFIaJ7B1ksuoRnDzG2juGuVBuOmAc4PmzBf7Z3n762hIcnypx61CWbMxkTSZKbyr8uXICXLq/1VNAZPVnCEDUCpH6gHnxi8Dnac5s0aJFixYtWrRo8eXghqxr73d+fFLOkL/+67/mqaeeWpYSGxgYIJfL8dOf/pQHHnhgOYulWCySTqeXtysWiwwNDa26z0QigZTyqgyZQqFwVVbMJb75zW/y9a9/ffnvSx9BuVwO3/fp6upiZmbmS1MXxPQ9OHYY+fqbVGwboWlsXrsBb9dduHYdgEr3EKdLHoPr1+DaDWYmZ3AcF6TkjXM5+rdvJ2cLarWra0icrtXQApevrk8TBBa6E4YJGyeaAM/FGN6AGFzPfCBgevqq7aWUmLUKwnNxDJNCOIrueWiFHMHcDOgGsqsHJ5ZaGVErdV45tUDgOuzx5ii8/CzqUs2I8TG0i6fp/coj7OzbwqmJBZwgIBKOUKvXQEHU1BmMS6ZXadMXDUMF6MVFVLWMMC2CVBY3ZNHZ2fmF6Mvd1/mgv9549a6Q7RBCfOnGLkASeKA/BDSzJ4JagelagZDnEBx5j8aZ4+C6hOMJgp5BtN230zAt5l2dkAiI6wFzJXtZzqoGvFuusCah02Z+uBorpu/hVCr4DQdjwzYO1AxsT4GUCN2AUARXSGYXSxy4OMeezmabp23J6HwZggDviujaige/Ppfjf71rkIX5HGa9inAbKMPECcduSJrIVAHxRo3K6DnQDGRnD048df3o+/ZewrEkTiTWzHZxrzYQy3CUwnWeDeF6lfpzP8EvFQAQQjK37xht/UOs33YfhxdXShB5jmQ+X6BauHlSMzejz5uBh1ZYRNWrCCuCn8riaNd/dbgZ4/VmtR9AVwH6+VPUD77TNLQKidHTj3X7/dTjyQ/ct64CjOIiwew0CJBdvbiJNN51ssJWa3+gx1Cn3uL8s79qSvi4DoyPoVsHeeCRp3hz1GMwHiJUKuIXi1Tn5q5Z50gIgZIaSo9Atotg8iIyEoX+AYa6XAgCfCNEtbuP/GyFjpjBTLFG1BDoqxQPyhXKzM56V42pj3MPrPseg7HzuCMnQQrM9Vvx+4aYsx2YnkZKye6uCM+fnLlKTq8vHSFG46bMv5/Vsz8E7G3TEO3RZjaVWyY3W/5I+/qkzuHjjtVP69pabgPnlWdwpycuL7xwDj3TRuiRp7BD165xdi0SQicdFkzaGsQSJMMGCenzVKJKX9wgUZtl9I13GZ1ZAASJTWv5P99yD/+f0YCXTs9w12CCjNbMGo90D0C6naBaReg6mmWhPI9qw6VUdghZdbyGTa12+blfq8G5mUUGonBHl94c00rh20VmZorXbbumadhLWVSWVB+6HtqN8v77ayXSq77nA8hwBKEE9hf4nfnz/p54vfHaokWLFi1atGjR4vPNTSlv6lzSzDc/nkJ/o9FAvi8yUMrLBdA7OjpIpVIcPXp02eFSq9UYGRnh0UcfXXWfuq4zPDzMsWPHuO2224CmZMCxY8d47LHHVt3GMAwMY/VCl5fasiyd8wVHkxJ15D2cowfxbAcnAHwf7/QpEpUSbXfdy9z8LKW+jYycWWCupBPVdHbcshu1OM/obB7P88knuzhSllxL13y+4uB4Psr3cIVEDKxFG1qPUAqH5j15v6Y0gOU5BEf3UztzHOU0ECGL+B3345w/Q2X8wuUfSknk1ntgw/ZlqaCaB5OFOrenBeXnX7rsfFmiWLPJvvMaHR09fHNnD++O5Vmwm8XN17TFuLU/uST18sW+z2HHxnnjV9iTY1zSndHiScIPPg6dnV/4vnwj4/X9y77I57saV8rEAOhC4L/7Oo2Rk5cXei72qSOQamekfT1vXJznwkKNnmSYrX0ZxufLFO3L+6m7Psr4cNfJM0yM3kH8UoFqppvRiTpEY8uqfjKWIJASFJydq7C700JKyfmFKgYBa7IRclWHsu0uFSfW0QRonot25C1qp46iGjbCDBHauA1j2x5s/dpFiS3PxXvrJSpzU1RqNnVP4SpI3X4PcttuBME1+0IjEiO0ZSf2kX1XrTP6BvFSbdfcVpMS99i+ZedLE0XE1Fg4P0L/mo2c0LK4/uXtMxGTkKZQ/s3vmx+1z0fqFexXnqU+f1kqUs+0E37gcWrRD5ZfW40PO14vLf+oY1ZKiXb+DNU3X7pihwHu5Cj+cz8h/LXfpB6yrrm9Gfio/W9SOXWMZd0uIbC234K+4zZc8cHZDJfaL/I5cm//enkfCAGBwqvVCN59hY5bHyPvBPQUFjF7Bqheo+5DIHVGSx4HJ/JUHY+2+FZ23baFwfociz/9O+xy08ivxxOY9wu2du/EB3RNNutMrOI3ao+Z1zXifpR7UDdCiHVb0DZsA8AOlsbb0n5832c4pfG1bd28O5pnsdrA1DW2dMfZ2RVDD9ybVudIKUU10JmrutiuTyZikLUkcpU6cjeT9zsVPy6f5vz1YcbqJ9kuIQRq9Nyy8yVAYvsKxwvQ5xbInD2J3LH3QzshdFwe29jOoakyI7kKjyZdCs/+BLtUJr55mMUXniZuRdjQ1suZksfkmXP0lws8fvvXeXYmYL7aIL30GLRNCzm8Ac33COamcWanQIGb1fHLNYytO5l3rm5Dse5C1LjhfiKEoBLoHJuucG6umbm9tiPKts7YJ/q+eun+Bm1d6Nl2vIXcVb+xdt5GIxRGfcFqNq3Gl/E9sUWLFi1atGjRosVny0d2wMzPz/OjH/2IgwcPUiqVgGa2ye7du/nud797XTmRa7Fnzx5+/OMf09bWRl9fHxcvXuTpp5/mwQcfBJofHk888QQ//vGP6e7upqOjg7/7u78jnU5z6623Lu/nP/7H/8htt9227GD5+te/zl/+5V8yPDzMunXr+OUvf0mj0fhUZc0+r5jVErXTR6m7AaYuyZcvfyE2RifoukdS33UPzxye5MJ8BWGa5Gsu40enuG19F919IeZcgUpmcAr5ax4nEzWRqOWoc6UU3gd8LBuA9/arOBfOLC+TZgjn6D6cU8cQHd2XjTNBQO2d14m1deJlOoCmbUsKQbpRolSvX7V/IQRBowH5BbLdEb62MY0WTlIul4hoAYHfrHthBj56uYAKfFQ0gWNFvjBFgXUhcN99DXdydMVyv1yk9qtfEOtsySx8GTFLi1TOnb5quT+4gZcnbS7OjFPSwizWHBZrDqdmS3xjZw/2bJGG1+zbYUPCB1ZpeN/+fZ/Qpu2I86cRKkCTTdlKBSAlMp3BWxq0UohlO/Cl4WSKgN64gRczAIEuFEIpgpkJ7MPvLR9HOQ3so/sJ1SoYd31lVbevlBJ15hjOxRFszeT8Yp2G1zyfyeeep81MEh5eS1r3VzW0+IFC276XSMjCObofSgXQdMwtO9D23EX1OoZ3o1HHvjCyYplSinTEIF9zUCPHad/2CFPFZgFyAdw6mEYG/k0zOH9cTOVjv/os3hXOFwBvMYf98i8JPfFtGvKmxHB8ohiOjX3o3VXXBdUyanoMsWbjqn1ACIEcO0/t1NGVK5TCPrKfaHs3bs/gDbVDSok/OcqVqkJC01F+A6UU5akphkwXWfVB1xCBj6ZpVxuVpca+qSr7Ri/Pt1VlMDle4r6wzoBlIapVjGQKJ9nOzL79rLk7zqHMBm4bzDBbunouTIVNumMGqJvvjPiguV4EPoMxQd+2NmxfoAlFRFP4/ge3RZMSs1qCeg3MEF48uWoBcCEEx6ZL/OzA5HINDoD+TIRH1mexrhE40uLzgY7COXMMAFdJxgs29SuyEhfePUDPuh1Ylv6hjeYh5XBXX4T7UgH1n/xPSosLdK0Zxt73JhKwKxVMMUV7ooeCE+BWq7QVpuhPDRH4ASwV9faDgNC23fjH9uMXL49NTYARiWB39FFYyEM4tuL4Ccu44TYbQMX2+PnhCUpuQGAYKAX7Rx3OzFb49o4uIuKT7csN3SD88G+gHXiLxsWz4HnIWBxr5634azZ+Yd6NW3x6NIJmTdD3Y2oazvvmBns2zycQg9KiRYsWLVq0aPG54CNZTyYnJ/nTP/1TqtUqO3bsoLe3F4CpqSlee+019u/fz5/92Z/R09Pzofb7+7//+/zwhz/kv//3/06xWCSTyfDII4/wne98Z/k3Tz31FI1Gg//23/4btVqNTZs28Sd/8icrsm9mZ2eXnUIAd911F6VSiR/96EcUCgWGhob4kz/5k2tKkP2TolqhWneZyNdIWCadcYv5SgNfKRzPp6okh5woZshHahIZeERSCTTT5HRN8fVtG5iYKGJZBjv6M7x8euaqTBYpYHt3/ENHJxqlPJULZ1cua++k8eZLBJUSRjqLZ1yZdaVwzxxHu7sb3/eJagHDbVFEeXXHUDpsoFQAQbNdyvdpj4fwKh6Br5BSYs3PYP/6Zex8szijDEewdt+BN7wJ73Okz30tjEqB6ui5VdcFtSre1ARkW06YLxuqUgb1vg9eIZjPDnD24AR6TwTLDBPSJQ0vwAsUb55bYG9/kvO5Mj2pMOmQYBWlog+kHk8RfexbhE4fZ313igPnbGQ0hpbtwDNDy0kE27rjqMAnUIo12QhHJgtLjVdLE5MCBR0hSXjs+KrHapw/Q2zbHtxE+qp1putQqdvYW2+ntFjAL5wCr758DPfUUY7pbTw4nEK/hgHW1XQifUOEGnVUo4HnK8r5Ita5s5gbt+Jcy1AQBKjg6uddSAQMZiKUlI+2tCwa0rlzTZa+mFx1m88KvbCInZtddZ2Xn8cqLEDm6ppdnzdko05QKV1zvT89gVy7edX5yQh8nOMHr7mtc/wQRu8Q7g0aUPXAI6TLZakhJQToBsL3QCmiuqQ9ahLacxeVt17Bau/CN1dKKxVcwYGxlXOakhKvbvPmQpn+B34D9d4bzHmSut08p/rRg7Q9sIb2vnYWqyGOTBRw/AAB9KbDPLi+DfMTcL7cKEoppPKILE2pN/KqYHkOwaF3qZ09gfJcEBKzp5/IXQ9Ss6IrflvyNZ49ObPC+QIwma9xMhdhc0cElFoKvPj8jMEWTUQQNDuFkEwVVzpfABzX5dhkkS3DnYRXeZYHUqfggOsHxAyNuPG++6wUxoUT1M4cI53swozHsHOzCE1HCoFTqdCe8RGaiR8EdFbmuGPz7qVaa43l3fjxFNbt9yEME2f0PEIKYr09ZLfey8+PzRDoJiISW35FjoV0OqM618ocv5JIvYJ75F0Oqy4WR6ZBSrRkGpHtIBCSsu1yYrbK7b3hT0yO7BL1UBjt7q8Q3X07+B6BGcYJWS3nS4tVqXvBqgXuH17fxotnr1wuiMdj3Nb18WqztWjRokWLFi1afF75SA6YH/zgBwgh+Iu/+AsGBgZWrBsbG+PP/uzP+MEPfsAf//Eff6j9hsNhfu/3fo/f+73fu+ZvhBD81m/9Fr/1W791zd/85V/+5VXLHnvssWtKjv1TRpghFmtNmY+i7WDpGoOZCJdUShpmlBoBRixGX3+EhZrDXNXFqTelQopOwK6+JG+czRExNYbaE4zNVwiWDIkhXXLvunbaLT60MVeV8vC+eHCpGwS1CiiFch0wVsreBeViM9LY9wl8n1sHUuRGK0hdJ7hC4iFuGUQNCRJE8mrjLYBVLlB94Wco53JWUFCvUfv1S0RDIfz+tSsiF6WmUXIlThBgaZK4HnziH8IfiG1fTi9YhaBUQLR1t6QWvmSIVWRjRCTGxdKSoUdKJIqBdJjxvI3t+UyXbMJmlq6kxSMb2j6yNI9SiloijX7bvexxYSzcxqIdNKUBl7pZbyrMUDqEWjL6dkYkQ9koFxeqK/alScE9A3G0F0ZWzwxRClUuQLqdkgOeUsQMiSEFxxZd3p3WKJSr6GaU3XseIjt7nurZpixbUC1hNzwWbJ/Oa3zvW9UylV/+PY7tMFm0qTleU0rt2FkGfUl460604GpdGc+KYHT04ExcvGpdRFNkdm0jMtyO6wckTElY+svPzM8Lyl5d5395fa0GmU+pMR8HqYGmg7+6xI+IRq/5/BOeR3Cd6xDUq2hB0zD8QQRBQKSnl4gh6U6EGc03t1W+j5Aa2Y4s3V1t6PuPUJtr1lAQtSq8zwEzV3GaMmJXtlMIlF2n1nAphDuIRsK4BXt5vVupMJQwCMdMBlIm27piVB0fUwqSIeAGsk0+T2hSEhx8G/vKzCQV4EyOErz4NKHHvkVDaz4DhRCM5e0Vcn/QrPG2tjPJ26MF3hkrEBKK4fYoe/qSxL8E0qNfJnzdQO9fQ3UhT7XhETV1TP1ydqU+MMSxOrRVXQav8L0JIVh0NV46O89sqTkeTE2yoy/Fnu4Immo+EzTXxV/Ige8TDxp4ovlujONgSB1PKUJC0ZsMk6s0WFQG+8YKTOZr3D6QotNSzYAHp0Ht7Em03gGim3eglMItFYl6NdpSESYLNlIpFIJUxOTxzR1YwltNfXcFIc+h/uLTOKkOzi4uOZODAD+/gAaI9i6UgrO5Crt7omgfMnP1o+AHAfUrHZ0t50uLFi1atGjRokWLFtflIzlgTp48yde//vWrnC8AAwMDfPWrX+Uf//EfP3bjWnzy+Mk0WqYdJicBcANFSKmmPJBh4Icj+KqMUlB2PAp1DzdQBApqjsdizcXUTBzPZ65s0xYLcf+GDqKGQKDIhjViWvDRjIv61TWFfLuOlm3Hn5tByKuNXlpX7wq5k6TmER7ux73rTqbeegspmrUWYqZEEmBt3oUTS161Hykl3oUzK5wvV9I49B5GzyDOksSSLQzeOl/k7FwZL1CEdMnWniR7emIYn2FkMZYFUl7z41gmUy1D05cQP5VFiyfwyysj/wVN2SOWal6YQrEmE6bhKzyl2NARo2MghnYd54uUklqgUWz4CCFIhSSW8K+KfvWUwtThyR29nFu0OT1XQQrY2h1nKBlaEXGvK49H1mc4nY5wdKqI4wV0Jiz29KcYqM1QvcY4BHA0i5+eWGC6UEcBQ20xTNNgZCpPUHdxXI98tcGziyXu2DjImq4C9ZlpZEcPZddvSmOs4oCRUhKMn8NvOIzmL8uXAQQopt96E6NtkOGu+FVR855SRHbfhjsz2YzOv3K/sQTawDApzaWZBuN/Lm1Xwopcf33k+us/L7iROObA8Aopy8sI9MF1ONe4Ab4ZQktnCWpNx2CApOErFGBqglBbJ76ug39jN9DLtJNZswbv3AVCepxC1cZ1PVIRk6EH7mXhjRcwK5cigkVzrN4ASimEFYZ6s51xQ7C2LULDU/gKVDTOrCf4ybujWIbGzr4kOzsj6Mr7sCqDnwvMcmHZkfp+vMV5Qgs56GhmYEspKdRWjkEBrO1I8JMjU9iuz9q2KIFUHJ8qMbpQ49s7u4l+wlJOLW4c3/cJrd+COnWSTNRjvupQLDWl+8LRMH1bb8FqmJRtDxG7LOlVUzo/PzpN1Wk6WrqSFtlYmLITMFIK2JQxUa6D0iQilgBAFuYJz45h7dhF8eA+NKGImgZWzOLoYpWaG9CxdhNe0Wdiscp0vsZv7OimNywIQhZaIoU7M4k7M7Xcfmtuhq8PrKV0105K6W5CErJhicnq8pfvRy7M4ecXINWOeF/mtV/Io6ey+NephdaiRYsWLVq0aNGiRYvPng8O21wFz/NWSH69n1AodNMLj7b4ZPCkRuy+RwjF4iQtk2zUYr7qMlpyKOy4hxN5F98PsAPIVx0MCXFTEgvpWHrz32eOz9CTbupaz1cavH5mhrQl6Y8oIsL7yLIEKp1tGpWuwJmdwtp1G8IwUCELR0nqvsBREhmy0NdsWHE8pRSGckjfejvbn/w664a6SER0jESCyF0Pwq47WK2nSinxlwq+rnrdSnk0pyk94UuDF07Pc3KmhLcUmtzwAg6M5Xl7vHTDRrRPAjeWwhxcu+o6GYmid/d/yi1q8WngGCHC9z2KuKK4uKqWGUqHoauPujAJlqL2JQFhTbEmFaLDYlXni9Q0HKHjaSFO5n3+9uAU/3Boir8/OMkPD81woaxWdYgChIXLjnaD727L8u1tWTamNMxVJFcM1fzdb+7o4Hu7u3h8Q5J200NF48hIdJU9g2/FOFw3mFpyvgBEQwa/ODJFyQM924G8wl61b2QGuW4LmmniDGygUHOImdqq+24+Ayape2qF8+USdj5Po1ym4K4uRVhPdxB97JuYfUMIw0CELEIbtxF57JvY1urn83nCS2XRO1aXJ9Qzbfip7Kfcoo+GpxTm3rvRUu9L1xGCyO330khe+zw8pQht3wtCUvUF5xZqnF+ocmGhyrl8g8rwdjy1st9LKaljkHM0Fl2NmnN5hnGkTuPOR7A37ESEw6xtj7NtIMvQ7bcydugws+cu4ixNX0ZnN2786uCAzpi5ok/DkoRXIkUkYpFySiil0AkIG4L5ik1lcDPv5JpOTNv1eefCIgema0ht9b7/cZFS4gkdR+ifzDHq1WtmNAEEhcVlQ3UQBLTHVnpYOxIWR6fL2K6PJgX6FRe00vA4O19DXuN51uKzoR5NEP/ad6l0r6GiJJppkly3Ae0r3+B/P2VT8xUdMWvZoSGEYKLoLDtfNnWnyNsBPz48xY8PT/H/eO0c/3BsgXJg4AmJ7BlAyzZrV/pnjhHu6ibd3UkCl1g0jGOE0DTJwP0PcEHPIJYkPn2leOvCIr7QcBWYO25FCIkSEh/ZzI5TAWLiAr0xg8FIQJcVYKgby7ISQhAsNp2y5vw06zviK9YrFeC7HnYgWNeZwBSfQ29+ixYtWrRo0aJFixYtPloGzJo1a3jppZd4+OGHibwvCrZWq/HSSy8xPDx8UxrY4pPF931kVx+Jb/0vhBcmuXj6Itq6BGbXAM/kJVauytaeFG+cy63YzgsC9g6kGZkrUXd9/Cs+JL1AUXMD4h9TxtcJR4nc+wi1l59ZjiJXDRsvUCR+94+YHRlhbmqOysIckbY22m9/FC/VSbXhUW74mLokE5IYeDQUiDUbMPvXYLoOyjBxDPO6ziEZT8DM5OrrQhZqybC0YAeM568ubAxwYrrEzu44iU/GzvWBeEoRvu0+lOviToxySQNKiycJP/g4eqYNpqc/m8a1+MRQSmG3dRN58nuo6XHcxUUK4RSNTBem7XJ8fBFL1+hJWYQ1hS4E96zNoitvhdSXEIKir3NovMRkoU5fNs6Lp+dIRwwuxduWbZdnT8zwnV29ZI3Vx1NznH2wYSgIAjQCNEAt+TwapkXk/sdwju4HFH6tir84jzRMvNsfZP/Cyn00/GZNm5mSTTwTJ9TVS2N6BrvRwPMDalaSxFd+g1crJt1Jg8w1at0opdDiSexVnC8AumVRCyQ1NyCxyrNOKUUt3Y7+0NcJ2zUQAteKUAuCq+pkfR5xhCRy31exX3kWb/5yLRg92471wOPU5GfnWP6w1KwI1mPfQuSm8acnEVYYbWANjXj6AxNAGu3dGPd+lZnnnsdZynQJJZNEbr+fn8xp3B7zGI43a7r4UufwnM3+sfxyvZGhjip3DsTI6E1D8DlbY39qM+vu3kjdhK5GiXPP/xKv0ZRIcn2FlYgSuvMBalzt3Esair2DGd69uLhieRAKcf9dO4js/yU+oKUyqGiK7NYuTiSGqM43Vvz+yESBrR1RovLmpsDYGJyarXFipoznB/SlI+zuTZAxbiza/0YQ5vVfLmQksnwspRS9SZOwIakBCIiFQ7w1lsMLIBMLYciVJbPO5qrs6grzkYpgtfhEUEpxUYvzUs9tDAzsRqJ4r64xMlonUAGHJgo8vrENlkJqpJTMlpvvZZ0JiwuLdQ6MFwAIENQ9xchCnZqb43/Z1Ylq7yTxnX9B6ed/iz89SfXNlwjv3Ev4rocQhkleWcQyvexvhCnUVo6Z2ZJNzRfEBNS7BnBve4jJ116lUS4TNjW6utpJ33Mfdir7oZ/9SinEUgCCXy6yZdjhdDxMsVzHDaDm+AjHpx64BArOlwIGY+/r0C1atGjRokWLFi1atPjM+UgWlN/8zd/kz//8z/k3/+bf8MADD9DT05R6mJqa4tVXX6VcLvMHf/AHN7WhLT4ZpJTMlhq8MuGA6OS4aVGv+JSPV+lLRRgwdOqOxzd39vLaSI65kk3M1NnUnWA8X+P8fFPyRF4hiyBo6mx/XONFEATY3QNEn/we/th5gsIi5sAQwvMYP3QYUS3T29OJeOBBDvkJXlrwiFXniGowX22wPSEIgjLdYUEkEcdLZmhoerMeQPMA1zy253lENmylcfYU769DAxDasA3XioDvs1i7tlSJHyjKTkAifM2ffOLUTQvjwSeIFRdR1TLCtPBTWexVjFhCCDRNaxoTP+v6NS0+FkEQUI0kOZ20KIQVPz8+S+ncLLcNZnl0cxenZkpUHZ9tAyn29idoNwOC9xWXKPo6/3B4irrj05+JcnC8QDpiEDE0ohLKiwWEYRKYIY5Ml3h4zdVyXB8Xw/NQdg1Rr6HyOcxMG+b9jxJ09vLyDFSdlTJrUkgQ4PgBDhIzmSaZSCFKFbwAnM5+fjVZoD1h8vC67DVr3fi+T2jtRoxDh5eXNYUVm9counErR+oaQx/wrPOUwgstPQA+j1pj16EWjmF+9ZtYxQVUvYawIvipLDX5GXmUPwa2EYKeIbSl2l2NG70Xmsa+SD/eQ98h61ZQQpDTY7xV8mhUihw4WWP9lgx6NMyB+QZvnltZbNgPAg6MF7l3bQbTt4kYGsW6y/4ln31HNMktX/0m0cnzGHaN9Ma1GD191K3I6sbawOeW7ggd8RAHxwtUGz7pqMktfUm6o5JQ9pvo+TncM8fxZmZoLBTpX6tDpofDi5f7uuMHVFyf6E2sd+xg8MtTOWaKl+vPnJopcT5X4Rs7e2gzbk5mtJdINzOEZq8OHhAhC9o6VyyLSZ8nd/Tws4OjjBUazFUcbC/AMjSCICBX9chGNMTS9daE4OO/wbS4mUgpmS7YuAG8vhBQrrvLb2ZhU6M9GqLhesSWIgOUUiQsHSmgLR7mtfNNSTBdSjpCiqFEiP6UxpCfp/7Cu4jqInokRuLJ3wbfwy8WkO0d+O29OOEIp8YqHBzLAy6RyEq5Lyma772+0Hl+JE+ulmXrA98k7VbxpOSQFmUw1UH3R+xRoqMbYZooxyFy/F2+ufU2jtVTHBwvEMtG6B7uImYZHB5b4JCCb+3qof3aIgX/JJBSIqVsvcu2aNGiRYsWLVq0+NzwkRww27Zt49/9u3/HX//1X/Ozn/1sxbqhoSH+6I/+iG3btt2UBrb4ZKkFGm+em6M9anBmvkHN9UFBwjKo2A5r1mbRpGSuZKOUYlNnHEsqZufyjJVcBJCKGCsySXrTYdIhboq2vFKKWjSB3HoLhlK4775K/vgxJi4V656eR544Q+ejT5GrWhyZKvG9Pf3sZBH7pefIlUvkpWRtNkK4r5/wPV+hblqrHksIQcV2yTkarh+QTPeRvu9R6q+/sCKa0OgbQmzasfxRFzaub4w0tdUliq5ESkGoUoLFeVTgI9NtOIkU3k0KlHcRuMksXCG3I64w7gkhsOwqavwC3uQYMhIltG4TTqodT3xw+1t8/hBCcL7gcrFQZ/94iZrT7K/vji4QMTXuXJMlrMNgylpyvqw0DklN4+B4kfrSdv2ZKA0lODpRJOfWuHd9Ozt6UiwsFACF7/n4SqwSs//RMVSA2v8G1dPHls/JX8jhvvocsUe/gaWtlI+SKsDwGoTdOo6n0BwDaWiY0RhhIRFS0pONMdQWIW2CuE6tG4BGqo32+x7E+dWzWG4dPA9lmPj965hYu5OQo5Ey+VJbah2p4aQ7IP1Zt+TmcC1j3KXaRgXbRwhIWRph4YMQXFioMVPy0DwdfA9JGT+/gF8qsKBrFLVZzJDBIbsDlkZAKmywrTvJRK7I2GKJZ4olbh3uoCsVIWJqy+NxrupxUoa5ZWAd4dw4zIyjAg+rbwjbiqyaNSIDj4EIDG7J4gZgSgh8j8DzEdUSpZefQTkORUeRK8zB2Di96zbhbLqLk4Vmn79ZgRKXEEIwXnJWOF8u4fgBb4/m+fqGNAQf3wnjIIjc/TDBC0/jlwuX22CGiNz/VRqR+Apnp1KKtW0xntjSxcHJEiFNkrQMXjuXo1BrSrMZWpik2bx323riqI9St67FJ4ZSimhIQyOgP2HSiJl4vkKTgpAmkCpYISUnlGKX1SBjLtDAossMsDHYmdVRSjFTdrndn6b665eJJSxESMPML9CYHCV6+714t9yFe0lK2XUZTIeXHDBXM5CNEtMVk9UA14fBtjj5QFGxEhSqDaYWaly05/nO9na0VUVvr48diRO5/zFqrzyLch3CR96iX1n09a+FLet4bcZhdKGy/Puj0yUeXxNHlvIQ+ATROK4R+shywF8kpJSEKkWCsfP4s1No8SShtRtpJLNfxHJXLVq0aNGiRYsWLb5EfGQNkR07dvAXf/EXFAoFcrmmPFV7ezupVOpmta3Fp0Cx4VN1PCIhnWRYRxcs2Y8Uu/tSnJqrMJqv0xM32NQe5YV9I0gpWJMJ01MrYSc7uGV9B+PzzSj0TNTkofVt4N/cArZBEKDlc1ROHcV531dU4Lo4773BwJavMFmAuAyov/iPuPUa0JRLq7oB+uQo8r030O95BO99Ri0hBHMNyU/fG2NivgiAoQl29vVz52/+AfroWXAdtM4evHQb9hUR4O0RHcvQliVnriQTNUlbq0scXUIH9NPHqO57Ay598AuJtWUH5q47cD6FaPNwKU/t+Z8uF5sGaJw6SnjvXbB590cwGbT4rPHQ2De2QFcySq7SgCv6Uc3xOTRRoDtm0HB9trVnrzLO2L7g4kJzDA1koxybKfPymRy4Do9t7+P50znmSjWGUhaVfJG7tvShpI64CQbWSxiFeSqXnC+ArFbwczOohk25XGL3N/+Ao3YNz4qgBT7B9ARjswEPrV3DOxfzyJlRAt1ADQyjEfCVDe10m27TqH0DtqhACMI9vfTdcSflyUl8x0bLdFBDJ6kFPLyh7QOdOC2+AEiNk4sev74wu+xwjIV07l3Xxvq0TjokmVvI4RUWEJ6HV6sgY3H0VIawX0d36tT0EIXz55H9azBNg+1dCZ57eR+NUolAKXKaZPKEye137uIbO3r5yeFJ6q7PQFxnR+4kpYPvkM5EcESAM3ISGY0T+eo3qEUT12y28j104JKvwBDQ2PcGymk6FaKGhhSCQCnKI6cYXr+F0yJKoKAzaZG6SYESAJqmcXq2dM31k4s1an6GyE3y0NZjKUJf+w5ifqYpSRhLIDq6sSNx1DUMzUemihyfLACwrS9N3NSX73eu0iCeCTOQDjOUCqFUa1x/nlBK0Z8MoUmBHyhCAkI6gAKl6MtESJqADzoK/dQRagfeJlZ3sbffixqd4bbdmzhbcjh6Mcd3NqaZfeUlnGqNesNlQ3sMM2yACqjue4to7xDuFWOvMyzZ0pXgxMzKPh4xNe4aSiNRVD24mK9z9kyOQDUzYzZ2xtnRm+b4ZJ6KC8mP8NWllMLuHiDy1D9DzU7i12oIokyaaQ6OVpdrD15qz2a/gPPM8/hz00BTStPaexdO3/CX2gkhhMBamKX6/M9QzhWSiycOE7nrQdTazQRfAPnPFi1atGjRokWLFl9OPraIeyqVajldviBITcNVEkNKhPLwfX85Wn2+bLO5N82RiQIK0KUgFTF5e3SWaMjAsRu44zm+s7uX0/M1XCXY2WayJaGItEnOhNNkIyYdUQ3zBgwXQtNxA5ra66sU0xVCYPouWn4B1agjEyn88fMgBNHeHoaHowgV4AtJaWaOcGGO73YGrEsk6bbAbm+jPDODv2SIqrs+qZBOY3SE6K7b8JY+rIXUKHmSsiv48eFJNF1vWnpVU4t/32iekNbGLZt2XFO2Jio9Ht3cwTPHZ3H9y+sjpsYjGzswlL+KiNllzIVZKm+/ygqpMxVgHz9EJJ1FDG++adr5q2GgaLz76grnyyXq+94i1jOAd51C1S0+X+iAWSnilUrcI20wdHoTFpOV5ri0dElEE6xPh9gUh2xcW73g9JKsihQQDZm8cHqKtojJpo40z5+aJV9zMYRiruKQDIW4MLXI/lSY29ckl2XINE3DrJagXkMYBm48hXuDXVlKiTd+cflvrVHHnRqFJWOTNz1BamGcW+Nx9lVtgnqNoFahBAw5Vf7w7n6OnwpYqNj0xASb1vbTI+rQaOBaEfxVxrKUEhcNQbOIudmoU3n+Z6hqGalbOIGgOnKakCYYdIqY/U/icPW1k1LiC0mgwODq7KIWnw80TUP6HmM1xUunZ1c8pysNj+dOzBDf3cd2y+HkwlxzReATuB5JGZCO6WxZvxXr0HP40QRf2bmG9e1RkJK/PXQB0zTQU0kGEwabkjqG8qjMTRDqTfG93T1MV1x67QWC0+OYvVmEffkZHFTLOPveQH/ga1cFDFwLvVqhOj21/LchFb2pMJP5OgEKRs+S6r8Nxwt4aH0b4jqF7D8KQl7bu3KzEymVUk1Zue5BZO8alFLNefIa18oLAuZKl42yp6YK3L8uS9H2OJOrYkrBI5s7WZPUb+gdpsWnT0IPeHhjBy+ensO/wumQsAzuX5tdDvwxctNU3329uc4URKszbBlsx5SCs7NldCtEu7Ap1+tI2RSWnCvVGA4nm35534PCAgtmhorjEdIl7RHBg8NJ1rdFOTFbpqpbDLTFWd8WJqX7+Gi8NjLD6bnLmSiBgpMzZbxAsS4bRUiBruvotTKisACeh4inl7Kdrz/GNYDAQyQzGN39nJ4OODFbvup3d8U9Gi/+HD8Ml94p/XKR6ivPEn3kSeyu/k/0ffKzxPA97DdfWul8AVABtbdfIdrZQ/06Du0WLVq0aNGiRYsWLT5JvjhVdFt8JIQQoOnM24LDYyVG5msESrGrL8XG9gipsCJuGZRtl/lSnUc2dfLSmTm6EhbnF2roUpIwJWm7wGw+x9zsPG2ZBGHL5M7ODI7flHUYbguR0gN87wMMF1JjqqrYP7FIqe4St3Ru6U/TGxWIwEdqGhVPEtRttItnCI8cJigsImMJQtE48Q1baZw8RPnMKVwvwLRCDG3aCl1teMf3sePUUbK3343b30UlGaXY8Jg7c5aQ3tSCxvfBaUAUfKlzYKrGyZkSyViYk7NlQqZBe8QgGRLLhpyDE3k2tvdgsfq5KaXojwi+d0sv40WbQt2lPRqiN2kSFd51P3Y1TcM5eZjV6swANI4dwhhc/4lmweiVEvb05DXWKrzxC8h0e8uI/AXADDw49A6Vk0cIAqgu1NDDYX7v3q/wP2QCv+bSrqo8kPYRR1/BKyzS29OG2LyF8IZt1I1Q85khNUyhsa4jzuhClYuLNbxAYYmAcMhgoeKg65LA8ynWfAZ7U0SL0xwbt9g6kEEXEsNzEEfepn7qMMK2CXwfo2eA2P2PUrGiN3ZCS31OCIG/OL/sfFmmWmZnYZzhbXdxviChfZD2nk5mF8ucOH6eNZ0p7hlM0hYUsN85SH1yDD2Ror7lVpyOPkQoRFwPUEFAOdA5Nlnh/Hx1OXJ5WyRAq1dBKTS3ThSIhpqW5GB2Er2Ux3mfc7KBwci8zfHpEn6gGMpG2NYVJ6Fd/1nQ4tNDCEG4WsIbOYnbcNhXSyNdDRWNE1zxrA0UHBtb4MH8Ke7d0scbp6YwNYPhO/dwoeRx0vYpTZSorb2bzV1xNo0co/B//IzKfU+ycGaRsGXx0KZOgiPvUn9nkobUMMJhpF4nuWcPfizE2RmXXHYrbRGDwZBH4sz+pjNcSpTnESnO42kGfjiKq+kr+pCUkjo6DV9g6RAVFVY68hUJU2C1R6k0PAxL5961bWTDGmHhfdh64NfF8zw2d8S4kKusun4wEyVmCsqOQaAgqoOmbs6YuJG5SZeSdNRgptQsvuMFihNTBcKmxoZsmEhIY13KQAucj92eFp8QKmBdUqP9ll5G8zYVx6MrbtGbMLBo9mdT13FOHAGxVIheKbTJczx+5zr+JidpCA1bCXzlIzSdhKWjVYsoZVCvW2gCNCvEZLHB309OgBDcmZFEGgu0V3MMnDlO1/1f41w4zYnZAmdmS2zsjNGdilCor/6OODJX5YH1HeQbCidfJHrhGNbFE6h6DaQktH4LoT13N2sUrkLYruG+8yrV8YugAoRucNfQZiLtW9i3cPmYybBBePIEcRlc/UqpFI1D76A/1odQAVqtAkLgReM3HBTxeUcv57Hz86uv9H3U3DRiONmah1u0aNGiRYsWLVp8JrQcMF9ifKkzUfaZrdr86nSO8UIdpRSagKNTRXb0JnlkQxv3rW/n2WPTLFYbbOqy+P7dw03jxGwZXUBc+jjTTZk5pRTzFZv2ti5OWF38/N0RZt49RjgZ5641WR5ZnyVGM/pMSonuewgpCXSDQCmOzDV47Wxu+duwWHeZyNe5Z1076ztivDNaYGQqj3PxLCGh2Dawk90dC5jTF7G2bKf0t/8db/wiOqBJDR2P6usvELnrQaxtuzGcKkFumlBbF41amVghj7Z5E4nyPDg10HQIWc36GHmX90YXyUZDzJWbbfYDxWShhtkWJbwU2F5zfGxfYV3HB6KUIi5dtmZ0hDCWonHdDzRwycDHLxWuuT6oVZCeA2b4Bu74R6Ohh/CHNmEuTK/elkajaZRv8blGSok8e4ra8UNAs5B0NhpiulTFeuMF/vlXvsEP3hjjgXVxSr/4KboK6E5HMacu0KgVkZOjGA9/g5NVweHJPA0v4K617UQsk4uLddriFiEVUKg26IgZiCAAXUNIiek7+NUqttSZKHucns6zZ+Yo8vg+sl6N+twMjm0jTp0kdmGE1O/+X/CSKTzv2gbYIAjQ+oYQxw4QBArPiiE1A61SRHkeWnsnfqMBc1Nk9r1A5/ptnAynePrl/fheMwPn+FiOr23vJdj/ApYu8Ndt43B8kENHc9TtScyefoZ7M+wZyPDTwxNUGpczAt46v8CIsvna5luxjr29ahuVXYfk5b89afLs8Vmmy41lX1G+5nBqtsy3dnST1Fpifp8HwuUCjbdeQjUa2B2DLCwU8Go2MhpDdvcTiMtZTblCFc+22RbJ0/HADirhFD8+NI7yNUy7xOK8w8vVCGcLDg/OzdCYmcZzPZxSmfs29eC/9iy2r6ig47k+wqsx/ebrWPEYRyJDnDk/R3VJxtU0db6+7W66z75LuG8Q58h+KmMX8HUdPd2GdevdOF39+ErhSpO3xiu8fm6ehapDezzEP9vezlB7N37uiuL0ShGSinBIENmyiVrkxuamj0Jv3GAgE2FssbZiecIyuGUwyy9PLTC6UMVXivZ4iDvXZOmPyk+t3sq27gSnpksrbNN1x2fSqXH/+nYMvC9zOacvPEIIXDR0CRvbIkT1AN/3UcpFNwyKnuTcXAlzfI7Gok0mapAwNWQQYJXmiVtDdERNGkjceIhMPEyQnyfTlmah6nA2V0HaNUKJBJ1tnST9gIfbBNnJM1hBg8BxqT7xO/yPI/OcnhnBlgahUIgL+QZ3rFHoUpCOmORrDgKImDqaJjE0yULN4bWjF3HHLhIO6Ty88R7WTx2B+RmcM8cJJ1KYO27FcVY6AEOBR+OVZ/ByM8vLlOeijRxjY8NhunM3k6XmNklTI7Y4TTwkV9QtXN7OdbFmJqgeeAt7fg4QGN09RG69F/tLEGSjvOs/R67KjGnRYglTl9yXurr/xIMGsHrd0BYtWrRo0aJFiw9LywHzJUVJnbfHKxRtj1O5GtMlm2LdBQExU8eQcGSyyMaOGDu743xv7wDn8jZvnJtn9kyO4WyE7T0p5kt1NEBYYbx4GowQEUOQyqb5mzfOUnE80A1qDZ9fnZpjMl/nf72jj0R1keDcSarnz1F1A9SaTQRrNlJs6ERD+gpDZ4Dg1HyNIzNV3jo/z7aEYFdvmqFsFGWaTJidbM+k8KcnCBZyoBRSCvBdVKmGkcqgSkVMw8DLtBPYNdzJUWJ3PkRufJbFTC9TpSLdEY1O3cONJfHQ2D/elJSxPZ+2qEXcMtA0DZuAxZpLX7zpSDE0ibmKQtOq1/2SDMoNEkgNLdOOt5Bbdb0WTxIYoRve34ehqgxeODnLsdEyfjnJus5Otgz7RI+/jXIvR1VqPf041yhc3eLzg+E0aBw/uPy3UoqUpdHwTFTDpuPcAb7/0G24L/6CRNIiroNZWSSw6xjhCO7sLPnzF3mpEEVKwabuNCdnKyghMDSNsXydoXSYroiGKBdRbtPoE45YRIJws594AQaKW1MS97VjtLkVFkbHMCMREm1tiMBD5Rfwzp4gv343F2zJYDpMWvdWLY7uZLuodq2hfvoEphsg0DHbejE8m/Dee6hNXEQYBsbAGvzOPgojsySjFovFKiqRIdmeIZg8xWz/Ftq2bOVwI8yhQydRpSIyHMGvVTg9a3JuwaYvGaaSWynpUvUFc6k+unbchV5eRJu6iGosFRkXAhFuZvJIIbCK8xzLNZg8eg6h6WiZNlQkSoCk7vi8N17k0bVJgpss+9TiQyINzi/UOR1eix+CLV2dhBtFqqPjBNUKeq0CV8jURCMWhY4tvHpiGs+vM+E0mC67xHSFDKfxpE45l0fFNQpbbicZS2AlImzaMsxQWDFvGmiOR2fCotFwWSjXMYTizHPPcctT32YgYTOX7ODd8/M4jseh2Rrr996Ff+wgRncvMtNGPTeDtziPeuFnxB98AscKM14zeG+0QcUJCJsGizWXvz4yz/91yx2E3/wlwnPRCRD1GkF+Htndh5qfxZISt71nRV0vIQRG4KHVayA13HD0hmXPrsRQLo9uyHIhH+PoVAlvKQNsY2eCnx+ZpHrFvJ8rN3j66BRP7uih5wbtWwag2zWUlLhWeIUM1Y3QEYIHN3bw+kgO129uKwVs6U6ysc0iaNVz+twSSI2RvMe+0VkKdQfL0NjanWBXX4Ji3eP4eIVzC1XWZqNsuuVOSi88zWShTsky6EtYzIfSJByP4kKewAxxaE7xxNYd6Cf2c3GxRtwy6LNAN3TCu3YwWXV4cLCN2D/8P3GLC1jrNkAQcOjoCI2JIh2RFEVNR+iCPVGHLulw3K4xYGl0hQxqgcZExSGqa+RrLumwSU8qShBeS9rSeXdihtDADoYXcxCOUJybJzR6kYgh8DIdy1nP2uI89SucL5cQBMRnzvHUnjs4K9rQhKA3ZhLJpXArq7xPCkm4d4DKC7/AX3bOKNzpSbxnf0L0a9+lFktevd0XiWgcYYau6WjR2jpb2S8tVkU0Giw89/RVy7u/+22wWg6YFi1atGjRosXNoeWA+ZKy2IAjEwW29KZZrDqXpREU1FyfREgHFOcX6jieoiMR4uUzcxiapC0aYqHqslB18BHUpMlspJ1iycYr5/nKHVs4MlOhUrcJ6nW0ZGo5ovT0XIXxxSrr3vg5hdwi4/l6s+jlxQmMI0eo7nmUvmyGsfkSNccHIchVPfqyGocmFrmlw+Ib+gwcP8DMm/O4Uie5eSuzu24hM3YREQqhxxMExTzKdRGJJEZ3P+7kKI39b1F5/mfobR3IvjUsVho8Oy+xL44QSIkwLbbt2sxdQscOJF3JMImwQcIyMU2d/Mk5POUSMzVMXWuK1ivFxs44MV3xSQTp+r5PaNN2GudOLcstXUlox15sqV1T1/6jUsPgJ0encTGo2z7SjPHeyASnYhbf2noHkUNN/XQ920HQ3nVTj93ik0F6Dn5lpfyPJKA7biIaCsZGaO8fpHrxKBIF3hVO0EqJhhmlcOYUycE76UpFODpVRErJqyPz3LeujYF0BKpFrISPaWi40sIImazNWIjJC3i+z9BAD/o7Z4gPDlJzapSmpjHjcSLKxR0/33RQBgrt8HvEDZNDTi9/d7DOP791kKGkgXVF7QUldX49WWH7hu0kPQf78Hv4lTJBTx/hr36LwG1mLFjZdrzzZ1k4eJjwfIG7N2whf8sefjbpsbs9zoK5hn3jZbYUBa+cGSNuxQlbEYRdI8jNElgxjuVqrGvvvlT+CYC+dBTTSPD3F2ZJ1RQxEWPPpnsZyI8hx84S7h/ETaQRQhCaGsU+fpCjDKAcB4VDMDmGlm5DtHWgEFxcqFIdSvLJ5bK1+CA8ofPGyCLH3z65/Lw9P1Ng7c6tzJZstHyOoJhHxJOoJeP+ut42fvLiW6Q629jUneTY4Rkano8VjjBbqGFqLtu6kvRlovzwXJ7QYoj2umDnHbdS/PWzXMhVUCoABHHLYG1XGruwSN2FUs2hdPgAMeVx554HmCo12O3NUfzRT+DCaUQ0irKiRG6/F5Vpwz7wNpX63+Ou2cTE/tM8uXM372S38Nxohe5kmAuLNf5DRfJ/u/c38I/uo21mBOwa1q7bIJlmcf97NLyAxN0P4G3aSUj4iCDAnGrOn3Z+HjQNs38NkT13faR6CaZy2ZTW2JRtw1dgSjg0W13hfLlEoOCdi3m+sSWLCK7tmJRCYM3P0Dj4NtW5GYSmYQ6tJbTzNkrhJG4gCOuqWbvjeiifzRmd3lt6Wah5uL6iLWaQNoCW8+Vzi5SSo7kGr49clpeyXZ+pos1c1WN0scpYwaba8Dg4XmBXJsSjdz1I6fVfUbZdnI4sFwsNpCYY6u/gwtQClZrNESvLrQ89Sffh9+goTjWDEbbsYnpylvLB/y/x228nNrSGkLGO6vM/x96ylxOLUwQ1h1C9zv3retngTjH14mG6nvw68XyO8swshMIow6K/rYuaZhKOmbx1LsfRkQmwbaQQ7F3fxbwwiN76KPtOjjN5poDlLrI2Arf0+8R7enA1jaC4uOo18ZDM5ev44zO8UC4TNXVuGUiza9cdcPHsVb/X2ztxJy42a0G9D+U08M4cQ+699wudBdOIxLB27KW+782r1hl9g3jpts+gVS1atGjRokWLFi1aNLnBuP4WXySEEE25scsLVkSKBkv/1zSJoUu6EmHevbhIyfY5Nl1mtuyggP1ji6xvj7G+I4YZDhNVHtsHsmzrTXFqYh4zliDZniVEgFz6aDM1wfkLUwRoTBWWnC9L1HJzdC+O8faFRQayMQCcQFCsOdQcn7aIwXfEBO6vX+Ti6fPYpTJ+foHSof3MPPNzau39+J5HUC4hzBBath0ZjeOOnkOVi6BpEPh4uRncUpH5Z37O1u4EIhzF6FsDPQMcmquzf7rO08dnef70HONFh7IbcHhskW/s7CEbNZmvNBgv1GkE0J+JcPvA5aLinwR2pp3o/V9FhiOX76FpEr71HrzewZsesSel5ORclWKtaXBSShHEEug9/VQcxfGqRM+2E9q4jdDDX6Ohmzf1+C0+GQLdRIvFrl6hAoQmsQbXYpgm0vdXOF8uUXU80HTCpsZcxaErGeaN8wsAvD4yz51DKe7vCjGXK/CNW9fSkbDYkDRQZ4/j12p0t6fYHfe58M57NMYukNF8HD8grAucuRlYcr4oBFhhFp/9BQ/H65TrLn9/cJwDU1UaGMvtKTjQXllg6lfPMVmoYm+5DX/PvcyHkhz84Y8IpEEo2079zZdwqxXcIMBHUjp5DPnuy2xNG9RkiF8cHMcTko6IjrkwTWXkDIvnL9CYmyGoVtDsGgLFYs3F1JtTYjYWwvYVvzg2w2wDHKkxu1DhH967yOuyi/zAFop7v0JFWFi+h/3Oq83ze9819fPzaEuZQiiu1uWXOq4wQNNbMn+fMEIIxkoep2eKKxzaDcelPp9jTX8X0jRBKQQCKeC2NW3Mlms8tK2XnVOH0c8eRU6co68+T8xvIA2DgWwUEbJ4+vgM04Ua1XqDySDE375xGiOVIhU2kUKga806ZBXbaRo5VUDBlwSJFCrVTmfc4q7OEPaBtwhKBWQsjtJNEGC/9TKaYaACH29mCswIyveZ2vceW+dPc8eaDIYmMTTBxYLNryoxqjvuIt+zHn/bbdjVGlPHTjKerzGWr3LyhV9x7twUF8uK0OwE1RefxrtUO8H3cS6OUHvup1h27RpX8/oopVC+h1xyqozMX3s/c2Wb+gdMr9bCDJXnfoo7PQG+h3Ia1M6cYvKn/8C5C7P84MAkPz2xwJyjo+nGdfelgoC49BiKwfqkIK15cB3nT4vPnmqg8d5ofsUyAWRiFs+enKXuKWpXOPhOlQJOWz103Xob0Y5Oyg0PNI0LRZdb13Xy0C3rSMYjONLkx/kwiTvuodY9TKFjiNMHjrJ49izC85h94Rm0dJbG8cN4c9P4gUILWWiBT0r6bK5NUX3rFbbt3YZ49R95tEsjGjaxSyUMx8abGqNfd9nWGWXfxXl8JEiJ7/scPDeDlm3j78+UODc+RyOASsXmwLlZfnJoArvezOIQVoT3EwjJRMEmX3Pwl/p71fF4fSTHvppF5Pb7r9om1N1PUK9f833SnZ6AAMT76tAITaNsuyA//3NUEAQEG7cTufthtHgzm0eELKxtt2De88gnWkuxRYsWLVq0aNGiRYsP4mNlwOzfv5+DBw+SW9Ivb29vZ/fu3ezZs+emNK7FR0MIgRQCAdQcl7aoyXTJpu40rRypsEEibJCrOKQiBsfnSvSkoiAEuwdSzFcc5so2yUgIXZNUGh6PrktTjNSpFYpoKBKxCLmqS8oyGOyMEwkZnJ2vEpMBll2jXijilUuoUBRPSgK11K4Lp+nfOUx/RNKZFVQDaDgmli75ereG+eujiPWb2bLORzVsVDhKcbHAwskTePfeB91DGGeOoDwXGbLQ2joIKmX0gWH8mUkUIA2Tai5HuMOiy6/it3eT8wRGELAp6qMVFrh/oI35qsu5+So1x+PO4TZOzpS4bTBN344evCAgZmrs6Agh/esX5RVCoJRCCIGmaSilVpVTkpqGpwSaAAJ/+UM4CBSNgXVYnT3IYh7lB5BM0QjHVjiwbhYekrNzKzMlFAI/mkBGYlwwNe58/LfA0KivYqhv8fnENUOEtu6m9vary8sCJKWGT6GhsLo3c3ZBsOO7/4rkc3+DKl42aMlYHM9XiMG1CAFj+Ro9qQiaFM1EsAACu84eNc+DW9qpTB5n7/Y+5jzJYniAlCnJlnNU9+9DF4KZmRyZRJJkexZ/ZgK4ZPMWCNNAWTFwHfyTh+kLbWR0cg6vJ8xELmBjVwTPD3ACQSgaYWzvI/iOw2AqTMavUH7jdZRuUDl1jFRnJ7R3EQiBpQsCTcMVOgsXx9lxn8F/G1kkncmyrd3EnJ/CrVYB8IMAT+iEfI/1Wp3bhuNk4wEHfYOpUoOuZISfHmnW0UhEQrhmJ3U9ivB9DvsWG+7czfFclfpcgfusMrJUwWo4bNm4icmZpp/FC8DxA8xShSBtsbYjRkQH5QNSY6KqODlThEBhaoI17VH64hryilQ7TdMQQjQNS1/gyOTPAiklFV+yUPfxlaIjFuL4zBx9mSj9Vh++02C02GAqV+TChUnWDcN379rIIiYqnqAr1pz/xkdGcV/8Bfl8iXC9wVDnMFPzRaoXz9M/OMzeoTZeOzZGbyJERAO3rCh6sFipMT3QSTYewnNdlFJ4ts2crRhKhtF715C34oR23s7b53K0zbtsmTxGPJNB5m38viGsobVQq6CpAGGFsXbsxT1zAl8FaFIQRGOEslmGYgYzpQYb2uPct66dhKXjz09QOz9CKVDUXJ9KwyMRMshGLYp1h0gtz/kpjZ7TbyNXmWeCSgk1cRGxfusNXWvDdRC+h2+GcFlpqA0b1471MTSJXMWwe2k+1ZWicfDtFdktlwzQlUaF5MxF2jPrSEfDvHo+TypssD5r0RM3MFUrq+XLQLnhY7sr36nSUZMLCzUEUHd9NNkMNGqPWzy+IUOfV0KpLKmdWRI93cTT7ezbP8mJqQKWZbJ3KEv7Yo0LQcD8i89hT47j+s1nrG7oEHgIwBs5iVIBQkiipXk2rd2M0Z9m10AbcvICs9/4LcYJk6uYdLqSb9y5icWFAkUP4vEYlrPA8/NQtV3ilkEocDE0GOpK8+LpOUwh0ZRCy7QR2HV8BRPzZU5MLNI2FGegrRtphQns+vK5256i6nhEOroYJQo0+7kuBYulGu7ABpLdvTjTE6hqBa13AJlpI7hwBi5JaC6hhKTcCKjX4dSFIlVPcUt/it6oZK6uOHihSMUrIXyXXX1JBuM6Un1y74WXxj2A9xHeP12p4a/bgjm4Fuk0UJqOY0VwWvNnixYtWrRo0aJFi8+Yj+SAqVar/Of//J85ceIEUkrS6TQAR44c4YUXXmDz5s388R//MdFo9KY2tsX1EULQQCdX9QmExoaeNDqKvf0pFmsOI7kq0ZCOoWucX6ixtSvO2bkKJdtjdKHK9+8e5n++O0rN8XH9AClg/3iBp7b3UKzWOXt2jHXrBjg5W6IzYbF3qA3b8xmdr9JQPg9t6qKwWGCDXsdZyOEaYaqOT91zUUIAgqG1SR4JFdBe/hU1L2Cov5cdhk7M7CZkWTi9fcz840+wa9VmtJ2mER1cS+zuu1mYmKTjK99AzU0ginmU74FSaJ09WNt3U32hqd+rpMR3XQyhcDyPqZrP/R06nePHKbx1nJrn4A338S9uvZPX0u28N1Xi//XmBe4ZzqKUYjRfI2ZKXEfgZI1Vyy8KIagrndmqS8n2iFoGuhSM5IpYmsa2niQZU+F7zQ/jRVfj6HiZqWKdkKGxsyfJYEJHW/qQDYIA27CgrXv5GBJFuFaG/DzKD5DpDE4ijXcdn4wuBNJzUJqBt+QY+jAoIRAqIJgcRZ8dJ9zbT9DeTUO7flRxi8+eIAgI1m7GKhexTx4lCBQTpQZ1oRO/51HesiPMjZylPDzIPU/+AakX/g5/ZgIZixOELNrXbuNVmcKQklv6MyAgFTZJRwy+2e4RPfEacuwYtdkJrFvuYKZ7HeK5vyU0N0ul0aASS1CXJn2ZKAszM7h3305MKUpj55fbKMwQ0YefYPbwASLZLIszc9x9zx38RrdOe0IyU7M5NqVozyY5lytz4LWjOLNToBTvAgN9nTxx193kDu4nqFUItG6CJeOtpQtiIYOcA8muNJbWrDMRi6dYY5bxzx6jM9vJ7EKRkKGzebiH3eu6cOdmUOcPEc7PsCvVxabNexj3FY4fENIlSUtnruKAHkY3BZahcWCiyI/2Nx1L2XUSfabCuvYYA36R9kycc9MFvEtZh57PYqXBY+kuvAAMKTm56DJXdqhUbcbmSlg6BI04jUycTV0RfKWYbwhOTlQo1l16k2HWtoVJ6S1HzI0gpMaZgserZ2doeM3rtakrwXZZxj/yLtWL5xDVCtvWrGXL5t28dmGRyakcDyQd+jZuwtYl4NKQIaKTZylWm/NRaXyMPV/ZznypikfANzsD/EoOxs8jpSDW3YHW30PdC0hlwhz3Inz34a/iP/8MC4UygQoQCOKDA9R330MsneLpwxcoL5bYtb4H66JN3vZI7LkXY26ChWd+jgp8QhLMkEH84a+j7bmdyuwEkVgU7b7HOVtrGl6TlsH+8QLaJPzzWwfJxCNcqDQoNzzCho7tNo3YizXJUCaCpxTtwiU3OU1XVFt1rvDGzqFt2rHqNZYCQtUyer2Cf/E8zvnTeEGAls4S3nkrTmcfPk0j6rbuBOdylVX3s7EzTlQLuBSzIISgFuhczDc4N19kVzwgNT1HWEjEUu2KuquW68gZpQWiPdv4Pw5OEKhmMeW1mQjZqM6TWzuJio/mhJFSYiuJrwSWVEjlt+pHfEbo2tUOvEzEpI86eztrhHWbaleSg3WLW7oiiPde4cTBg6TDBg3PJ2KZrH/4IR7dsI0XzuTIlR1+MFHgD7Ie69KSUrVMww9AgdQkeiyBrxRtbRaqsIgKhQl0DSuZ5KGhOAu/egbvkMvMrod44VwJx85Rn53BNDUGyz63bBkkNXUepicZP36a3vu/RWc6xu1r2pAo6rbN1p40x6aL1BfqqEwbgaZTr5Spuz4KODFX48FskcnpUYa23UL9zV8hjBCeYVK3XcxEEu56mLOLzXHQEdW5XRbx9r9M+b0qQcQktGkHcset1DUdKSXmxm3U33vj8kUUgrmqy3ylQfKWbZxbqOP4AeP5Gnes7eTE5CLFukskEqFWqzNdrLOrP8WdfVHER9Dk/SDnSgODsYLDmbkSmibY3BmjN2agf0hHahAEzXfWsHFpwYdua4sWLVq0aNGiRYsWN5uP5ID5q7/6K06ePMnv/M7v8Oijj2ItFaizbZvnn3+ev/mbv+Gv/uqv+KM/+qOb2tgW10YIQd7T+OXxZoFSJQTTZRcp4Knt3Ty5rZuTsxWminUWai5PbOnCDwJOz1Wo2C63DWX4h0OTGJrE8V0sXQMUmpQcGC/wyPoMhmHQ0dlGpV7j92/t5//+ygVG8zV0ITB0ybHpEr+zp4+O6iTVUAi70qDuBQSqKUliRiz6B7o4+POfsHfvVjKFBezn/oHA96mHTCLf+z9R/dXP8eu1ppyPUggU7sRFIqk05vY7GKsrNjz2bVQojFavYmUyuBdHqD73E5TrInUdpIZuGtSFxEtm2GXpZPf9ivmJSfxAkQwbLExMUS8+R9cjv0lY+fz2zk6OTBbZfyYPms7arjSPbO1ClxKCq6/1vKPx9PFpqg0PRwkuLNaJh3R+a2c3qfkxCs+8jBbWaNuwnmK2n384PovjXd7RdKHOlu4E9w0llmVarkQDjJGT1N59HbXkxEFIrM3bMXffeZWUgiYglJvGOXoAt7iIjMSwtu7G6xnAFSuNFzoB6ztivHNhpba4RMFijqG0hth/CLtUgBOH0Du6CD/4NepmqxDlauhSYFRK4HkoK4xjRT4zI7kjNfQ9dxPbsI1qvoAsOjSsJO9VJO2ZGJvvTHNyYoH/X06y9/5/wRa9SmdpBtZvIWjvpmPWJmyFePrYDJ1xg8l8hafaLfK/+Al15dEX13GLiyxk+zl48CTbolECuxlRq2kaVuBRLZQYlA7Vk0dIfvd30Lr6aEyMokVjyI5uqnNzpDdsYnK+yFBvB3Pn9zOf6efZAxdo1OpkEhab7r2bfUdG0KqVZqGIJe2usfFZDidD3L5+LXJihOAKI46Qgg17dtJbqlAZPU905CD/ZngdR4MIIihSOXWcrzy+kV9JyeYN/bh6iB/86jC27TDQ186dW9aQHj+Jev1per72z+mMW6TDOrYPuapD2faImDoBcM9wG5lIs/D5WBBm0Ipwbr7CttOHeXDtLjri3ZyYKeH5AevW9RJPxnnnwhwxo4O2iEa+7vHMwYsUS9Xl9h8ZW+Tu9R30x7rAbpCfyxORFqM1ydhijQPjkt/Y3k1n6MM7Vv+pMd8Q/OrULJd8YALYqIpUn/8ZC4UKgVKEjRClcyPoE2Pc9cg3GZcxEtuGyPkSAkFUh7j0KcyMoVCYmqThudR+/TJP3fMgRjhM/bkfo+55goghibe34UxPIOwaeiqDcD0WZscpfu0Oeh//DfqqZSq1OqKjm3MizpESiPwsO9d0Et61gZG69/9n77+DLLnu/F7wk/bm9ba8N13V3qEbjYb3hiBBcjAkhzOa0Mq8p9VIeis9TezGhKTVbqzMamP/2Nj3RhtPESPzNEYzwxkQNADhXQNoNEz7rnblfdX1Nu05+8cFGmigQRIgQFGj+kR0dFVm3rxZefKck+dnvj/i3UOEs50EfkD+xAlSQ4MEsRRetYSolVBPvU3yoa9jnHqb/sd/hx+sSd6bL1Bb8rCsEA9u76Tq+PzZe4vsunuQplBQuP558YWg7Emi6Sy6UFF0HVVVbpi1qYQjN3zWNMCYuQT1Kvals7iXzyNsGy2VIXBsGhurRO96CGdoG0IIuqMqe/uSnFmuXHeebNTkQF+cIPjQwFoTOk+cWWvLHgE9qNQqNklN0hU1UJUPnS8A3vAkz32krV1f4AlJqeHy+lyJh8ZS76ed/fx4isGFjSZnl6vYfkAmYnJ4KM1ArC1zusUvl6TRloUs1NuyXD0xgz2Fy7gnjzO/USEZNvCEwu13PYC5KDn39rvomkLTDYiHdJI6VE68wY6xcaLbMhxbrFCqKbyrd/PbA2n0vl4a5Qp6JEqgGZTcgKihIk2Teu8w0W07kFemCO/cR+n/+/9ANUJ4j/4Wz55bwRYKWixGOpNkbM8OTq03efH1RUYsne5wDzfdvw2ZSnMopPLDcyvtbHApmSo4pMI6t++Z4N23zyGKZRqeQNNUVE0lFo/ivvxjytPTxA7tp/O2+/DXV9B8n+6BMSpWNz9eFeiqIGJq3BJsUnr2xyAlXbkYQc2m+fYxjNUlzLsexgWUse0YS/N4q4sAOIFCoe4Qn9jOQrQbt9Tuc75U+YtTy9y7LUelVb6uLU4vltneGSPzGVePlu+irC3hzV4BRSU8Pono6MV5X/KshcGPzm+w+X4bA8xs1hnJRbl/PI3xJWbdfEDb6aqxWbNB08HfyqDbYosttthiiy222OKL43M5YN5++20efPBBHnvsseu2W5bFY489Rj6f55VXXvmUT2/xZeCh88zUBuVWWy5LkZLuuEHNETx7aZPbh1Ps6gpzx1iW08tlruSbTG/WiVs63QmLya44z13aYCgdwdRUfCGxvYCuhI4dCOKWzrcO9OOfewW/UiZ/MsTfnNzHm5kMby43MTSF3kSUy7Or3DLRSzgcI2oKqq6Daugku7sZ3buL2vnTZGIWphRU3noNzwuQmkbS0PGXF9ACD93Q8V0XRVFQdB3hujTOnyJy16PoiSyn5+BiVaLE+pnUdcY7XIxQ+FrRZCkEkVyOcucgJ90oOyhT31gjbGgIKemMh1gqNYnvHuPiSpFDQz18790FBKBJQAguza9Rbnn8n+8f5+NVNRx0fjK11i4qrCisVBz8QEDgc+LdKe5V1qhPnaMKKIvTFENJbj70AMfykAwb7IoExL0GtFy8loVlfTL6OFTcoP7mS9dqFSiGSdA/wpqZRivWiXTkCCkBQoh2ZOPsReqvPX/t+KBWxVtfwdp3GH3vzXx06SqEYEdHlEvrNT4qrqbYLSJOjV3ROEG1fG27v7GGfu4k6qHbtqLvP0bEbuCeeI3G4hyIADUcIbT7IHJi9y9Nb1zRNCqeghdIwrpKQpd4mU5O21GOr+YRDUFn3MQOJD+aWmt/RkpUM4HfmyOcHefSSo3y9Cq7e5NIp0XDdpizbR7f10vq8uvoeER1SaAamL39XHQ0lhZW2btvO1y5jB6ykK0GipDUBHRkwuixBOePvcW2iW2otSqhdBb7/EnMegUnmmJo5x6Ujh6WqpKXzy8jgoCEpZNLRJlbLeBubqApGoZpIFwPVAUVhamlEodTaeI3344z+2Gx4cjETuw3XsJZXUOVEiEDQq0pbp7YgzYyQiqdxH/3db7z4KM8XTRYOXcJGQTETZVaocRPVlZ54Ogutot3cbQWA0mTsh0wV2xRs9s9SAKOFzBbaPCNfb2sVx1UUyPy9d9Cm7+IuzlD4Y3X6InGGO4fJDI4QrUnwVLNZ7QjwXrDI2aZvD1XuM758gGvX17nyECS9LnXsc+eIxqNcve+w0ylR7lS8Xjxcp5v7e24ljm3xSfRNI3zizU+UvaMrpiJd+44pvAJhMTQFOo+6GYYHUgX19h/31d44somC8UGQrYNvg9NZOlMRiiuqIDEMjTsep3yq89zy/5t1P0yjtIkk0nSWlshaNQJxeKIZgPPdhgdH0LYNnOBhRaNoI338cSpZUzRxNMMphfW2UhZ3J1OMVZeJFeYJ2RZaMV1tN/8u7y63qRQaxFNa+wf7iC3OIXx2rME+4/y3HrAW5fXUUIhNE2j0vJ49uIG9012kI6YXKwJOm66hfo7b3xCytLYexiR7mJ2rcru/jFW5i6SsgxCmryuPo4+vhP7Bo6ZSLWItziLqms4J15DscLoyQxBs45WC0EiTeud1wn1DODoJprwuXUwznhHlEsbdRxfMJaL0h83CfGhkVPRdN68WrrmfAGYcXWOjE1QOH+GhKUT1blWi8KMJ5iXMZru9Y6dDwTNZjcbVIdSJD7DUCxUnReuFpnZ/LB/rlVtfnR2lft3dDGZ0rbmwV8yOgH3bsvxg7OreIHgJq1K/rUXSYdNUmETCVSaDgNhg8Lrr6AqEDN1eiIqUbeOMryPpXgPb7w5jdrZw0g2xsHhHE+9O8tfThvcceAog7UyFdujbvv0JkL4fsCVfJPsoQmc6ABH/od/TPPHfwqOjep5FI04TlADx0bJ5RjfvY3vXy5TdQIUPYydjLCwNE1Jatw5muXNM9NEQwZ+EKBIaDkeiqJweaNGVzbJyqZE8Rrg+0SznYzLKuUzp+i56SaCqTMUj7+AmsqiRaM0l1ZoGBmGdt7BhbrKgYxC69XXUaQkFTaI4kMgEbqOtzSHWdyEXDe2ESJ0zyOYm6v4c9O4gUr8cD8zWoqp0od9zhWSUtP9RMkyaM+ByxWbbM74uQMBwq6N89KP8TfWPvyO2cuYg6OEbr8f37Q4t1y/zvnyAbP5BgsdMcaT6pcaeGBjcHq5zsW1GnqoSEyT3DyUojfSXlNsscUWW2yxxRZbbLHFL8rncsDouk5vb++n7u/t7UXXf6HyMlt8RgqOoNC4fvGiSknSVJCKwlhHjL6I5ErJZaVYR0XhnolO5gsN8k0XP5Bs64gRC+mUWz5hXaE7HsL1BUJA79oVjKm38buHaXaPYts+LMxwJJ5nMznMpXyTedthd1rn/OwatzzyOLnTp0iHwqxFOrjUVMlmo1it44ztGKdx6gSaqqJYOsL30UwTf2kOI5EkKqvUfB8UFRm05RjMji7o6uPCap2iliKWU/ENi9eXN3nXj/Hrv/E7hP7Lv4XAR4+nMMe2033XYzQ3dNzp01Qdn0zEoC8ZBQW2jfRib99HfaHBW/MlSk6AIgJCmorlO+iaSqNpc3G9zpGe0HXRwflWQKXVXqy6AhqOj6pAIrBZXVrGPtAHtBeq1ZZPvbBKemGKnUP7GN+8Sv3YcZqtdlHien83mfsfoJnruba41DQNb+rMNUOYGo2xvv0oxxaqxD2PEXeRcLFMtjtHNJ3CbNVonTh2neHsA+yz7xIbncCPpa7bHlE8vrGnh9lqwJl5H1SFiZjLZDpO9PzxTyy8nekpwrsPYG9lwVzD8l1az/+QoFS4tk20mrTePkZYCtRdN33phrqmNHjtSonZfB0BKKrOSC5GOqxzNd9gsjdDseGQi1l8/+zqtc+ZhsaO7gQvXy2wWnVIWjpV22O95mLqKg/s6KbUcNmb0ug8t4HfmyaUzWIaOvqOHehaHFeuMe+Z9O89SPXieaTrougGqgJmTz9OIsvym2+SGRuja3iU5pN/jOf52F6At1HAtBuwfS+yezdxTSACD6XhoPV2YHsCz/PwpSAciyPrVTwhCYSk6bg46NS7homkc/irSyiRGP7MFYJSAUNTkPEsC02BZRiUz5+if+8uZqMZtEqRwnqe4qqPUdoAKVF1DRmO4oeivDC1RnxgmMy597ht/3384dvzIAWmrrYdwgo8ursHISQNV7BYsRlKh7kkDULdu9B3HCA7f57axfNE+gYo5wb4wzdmKFQaoKiM93fQc/MoV1ZKN2hNCb7H1Y0696RTAHiNBqU3XmbHrbARHaXYcCg7kuyWIuCnoigKhcb1dbu6jYD64gK1qk1vysL2BIrTzpbQdY2O2gZn5jeYK3xYLL5Qd3ji7Bp/Y2IPYxtrVByfqu2jKibDI/3Is29jtepop1/nzof+D/zkHQO1U2IGLq2VJfbetIualeRPnj6B0tFDQ7doXW5y3/4hjl1cZaIzzp6BDOO5GM1iAdsIURjey7DuMJMZ5qnXLyGtCIHvo4QsLhSWuHPHJHcFTTZ7Jpi7XESh7TAxmhVi4Th5R3BsusD9k51UHJ+pyChffbSD1ul3qBRLmIkU5u6DvGV0YC6WefXKJv07DxBaXqKQLzKQDpPKJDE7ezByHUhDx/xYhmZIVXCPv4J9+gShviGkbSNtG1Epo/cPIapltHiSoF5DrVchlQNAFT7dIegbjqMo7Ywb+TFpoYavMJu/3jG5WXdpThzAWl6k3GoQjRskLJ2NukJsfJLTvkYglfa9ACKmhtFO4CWQkkDQTtn5OdlsyeucLx8ggTdnCgzu7yb08bTYLb5UpJR0WZJvH+hjs+YSfvNp9IhJKqyTixosVVw2cTB0DaeQJxMxyVkaVn6ZYN8tvFiPsHR1DjMWwy82WO3qwdNN7tnVz5XNBv9pSeV3b7+b1aefJXAdVusNdCtM9s77+HE9Tul8nr039+Cvr6HFkyiuixsIFE1D6gbxXAfn6yqrVQcpBagq1UAh1T1IK2QytVbj1/b2kG+4FBoOl9YqRE2NSEjnfNnhzuEBNusq6XSOsPDZMZgjufgO5ZBJTJOUJ/czRYy5QoOwrrJvrJuutQXM5hpe5wSZhEZ99610mJKu5YsE770GQYAai6NlOgiWF1A7e1EUhQoGjewIZtc4LV/yzKlFfHHjTI9PVmb6oEF+/rZTVRVx5cJ1zpcPcBdmiCzNYQ/v5OL6jSUKAc6uVtmWyX2YDf7+eQ3XQa2VAQURT+Aaoc/lpPEUg6emNlmrtLN5I7rJcq3Jk5UmX93dw0B0K+t0iy222GKLLbbYYotfnM/lJTly5AjHjx/nwQcfRFWvlzcKgoA333yTW2655Qu5wC1+Pj5eoPQDVAW6kxaqoiJVhe64SjykMRCP8qfvLWEZGr4QzBWb5Osulq4Reb9g7mq1haaq/Ma4AbNTzG07whszBfKlNWqOT1c2yZ3JLHdZcHLJIxQy8Q2LasyiEEpxdvQW5otNlktNhKYz6UpqGzWUAUFHZw/6jj0ojRpGyEQ1dBRFxT/9NlbfIEanjtOoE6Ai40nk3V/je1NFXjvbNohKFLKdWe7a2cfS0gZnrSy3/83/GdGsI1WV9ZV16nMLjHVtozsTZ+Lm3RixOHajga/qqCOTHJteZbh3gPcuFpC+jwRsEaCGTCy7TjiksbhR4VBP13X31PmIlJiUoEhBRJHI/Dp4Lm7Q7liRWAwrGcMUFZyFaQ53dzJz7MXrzuWWSjSe/yGRR79NM5Zst5mUBNUyUlFxA6htO8wPzm9w92ga7b1jNJYXcaIJamGLyduOEh0bpfmRAq3XIQQivwEfc8AARBWPB7b3sD2lomkqxivv4UxfvHHUo+t8Ls3vv8oo+bXrnC8fxT77HuHR7dih8Jf2/Z5i8NSFDTZqbcdrSyjMbdY4t1rllpEsXiD5D28t8MD2TvINl6rtc2dfmL1Gk0RQY7UVRzo2LU+QiRhYwkPB4vxqlXTYYK3SomfAoO/IXcRmLyDqNbzlWVpL8+y57xusDPfwzswGzv5DjPYPw/xVpARteBt6JoZ97EUGkxaR/DLLly4Q6hpG910S0kfoBqrvEZx4ha5vbkdp1lEDH79/jEuuyVCnxapu4DeauKaOEYmhBYJACDp6cgSmxV9cKXPLcJaJr38Xo1LEPfceeux21FSGuu0SnLmI63j0JELImYvodz1C5vQxLjd8pBBtiUNVhXCMllRoOS6KG+Ds207JaWC6LR7d2c2Z1QprNQ9dVTg8lOHY1U1GO+P88NwqX93VzdMX1ml5AS0vIBc1uWNkjKOPHWSp6fCHL1/4yHgRUClXqTeaoN6gKLkQbYOX56Ko15u+6qffZsf9wxxv8WFtmU9BURQaQqfYCvClwCs2MVTtuiLmf5WRUtIRM1mtvD8mKgoVD4wA6o6PrEp6E2EsXSVh6bh+QFPAWqN9fxS1LdslpKDlCS5anewaHMJYmqfblFCroKzMgWHib9/H5e5dtBotHr91G2q5iF/YILvnICeDBBfePoOwWxhS4Kkaq/kKb80UuGtHL5fWa2zWXZ48uYjqthhNRwjZCrfu28XGRhElWUI26qixJHUfWp7PG1c2OPzQQ6zmW4RiUZSmxG82UBQVlTqd0QT1QBA2VLZ3xjk9s8GzVYeBvfciUFhsSVbrgrApCLVa9KcjvF4UHL7za+Sq60i7jGUI3Evnca5OIRQFPZPDve8rqNEUQRBglIvU3nkdNK3978MbT7CxitbV2665oKk3fM5vJHX2AYIbP9+vFiRH7vo6ucYqRn4OD4POI9t4rRkjUDWqjk/U0AjpCt0JC+V9Y2k0pBP+DG+5qqqyXPmUuZT281NzJSHz5z/nFl8MQgjiqiCXVvFFEz/2YcN2xU1AotsN0p0dlEsVYn4L1/fYzAywdHoBADUcptGwYW0FpXeYxarH4aEM/YbHSTND4eijdIgmcVVhXYnwgxWHTadEHYO6l0ZqIaQSIhoJEZEevueh9A8j0xmurDZQzBBSBKgKKKrKuqORCpu8NVvg3tEUY84mBzWH39qb5O26zl9MN+hKWHRn4uQ6M+gi4NahFPu9VRqv/pjRW+6k3D3KX74zj+eWCVwPRYG5UoudO0fZMdTF8mKDueUmoYUllEaVnkych44+TPgnf4JoNZH1GtZNR3EUjbPrLd5dLOG4PmoQ0JFNsKsvy4WVIl7wYb8zVYVM1ETe4G1QAXqTFvJTsjA1TaMVKCiKQkgJMHwH98qFT21Xb+osDO/E/ynBKl4gr3OAqIpCaGmG1luvIerV9vfGE1g334nTN/yJjL+fhqobLNckVwo2ChDS1Wt/tZDw+myRX9/TifYZ69BsscUWW2yxxRZbbLHFx/m5lqYzMzPX/X7HHXfw7//9v+ef/tN/yv333093dzcAq6urPP/88/i+zx133PHFX+0Wn0rU/GRTpiMmPZk47y6WmSktoyC5a7yDe3b08szUBl/b08tGzUFTFfpTFl17evjzk0v0pyIUGw7xkI5laOy2fJoju/nJOwuggESiqwrr+RpPVpv81sOHsUItdEOnJaC3N0esWeR23SFt+lR1lYIveH7F5YGhESK5HMbaVeo//FOElBiaimkapH7n/4I6swO/2cDVFMIdXQT1Gq1EildaEd6bX0OKoG00VRQKDYdnL27y0FCMYyfPE0t7lC+cZ/zwQXpHhtnUskxPL3Lzgd24zz9J+a3XcKoVNF1HDk2w5+CdBNkoIb10bcElgZYnsKwIGU1geDYq15eBiYc+NDqZCHS7CbqKDHxAkjFh+NAeKBdR6lVyo70og+MUzpz4RBvFrbbEmj89hXbwtvYiU9NQsp0szy7jheNcyXvs7Elgv/BDRK2KqmugKviOw+yxY+xWBWoihfiIbNhnQZc+RqCgx+P4zTqKqiFDIYKP1I7R01mCL9GZ8N8aqqoS3CCi8wOkY6O0GvAl3rPNVnDN+SIVlZVKC/G+8fLthRIPTHYRNTWOXc3z2N5evjEYouvMS1SXFojt28dZu4qsNBnr6sNTLKxohIVSE9sXXN6s8w93x/F+8MecXV1iNKaizUxhjW/HOnALzdef4/DRRyhYg1woOFwq2STi29CR7AnF6HjjBfRWg3K5QZfr4DSalALoCVsU6w1K1SadYR2/6RCXDiCRvUMU1DDCh1TEJNbdQ2VmGt8PQFXp6UrTCCS7+jJsWGHyNY83ZksMjoRwXn4W79y77f4jJaF9h7j5a4/QWlpAURScWJR1PY685UFitouYryBSHUi7idZq0CoU0a0woquPNSPJyTWBU1thtCfD/u4YfqJBl1elvnaZbw118v2lGreP5njq/Dob9fYYmrB01MDj/MImOb/OV4wNdu9UKEW7+OFCi7NrdVK6YH1+kR39Wc5dblwfSSwlnakIE5ZPaSl/XVt7jQbxwMYyrPfHnxsbqxRFZboqePnKyjWnfCxaZTRtcstAHP1TIp3/KhEEATu74pxfqRJIiSvg+LrDr0/shMIxshGT1WoLLxBYusZQJkJjaDsFV9IMoFhz8QJJwtJJWDqvrdjsuP1h4ktXsV9/Hq13ADWRRM92clXvZKGlYbmS2Es/QVmaJRMxqO89wvnLlzATKYzYMKplkVEg3ptk/3CGt6bz7OqJ8cSZVaKqoNuU1KYvIzXJT3yFw6M5VE0jSOeQjouUbaOorsBaYKC7BZR8gVQkS8HzECjoqoquCDRFJRnSKVfq7OlPUbuywdUzF9DiSdxUJ3FdZ39PjKmZFTJWCF+YHC8ExK1uHk4aFN55EUsV8L7Ml1/MU3/2B4Tu+xqtWBJ/fRklZBGUi2iZjvZx7xs8peOgaDpC1dDTOYJ48jO1XUSDjniIzdr12by+kLxeCEjt2gu7b+Lly3lMXSOdM1BVhYFUGNsX9Cctwpq41q8OD6UJq+JGyaE3RErZrvv2U1CVT80L2OILRlVVTLuJUi6C76HEkwTJNGo6jba6gKiWkY5NJBQhG05SP3uKvjvuwP7JM2jVPJGBUS5sNpHQDjJJpIitraI1HCzhsnjuAvdGB+nWG7xeC/iziyVUVUGgoCoeyUiIe7d3sb0zSioRxnzkMarHX8PNb5CMhsgdPMylio9dc1E0jUBR0TSFjKXSqlQxwmFm1yvs600wvnaBmeeeo4rCkqaye6yPvgN380xVx9QUHtmWpbC8wqvPH+Pg7cP4rRYyGuON5Tqu46JKQfvtWwFFpalZ/OV0jZKr0JmIoGhqO3tn1eEFrZOv7TmMPPUmMvAxMh1c2LR5YyaP0qgjihsEjsPqRozFXC97BzJcWPtQxs9QBb9+oI/z83l0u4lfr7STyKwIu4c7yIS4YW3EmtA5vVBj5v0stvGOKEdzP72WivRdIoqgNxlmevPGWTCjuQiKFNemS6uwTv2lp9uO3vcJalUaLz1F7CuP00x3/sxnywwCtFKe4uwsui14MNHNm40QU/kWA2mI6e1xrVB3aHjyM8kYbrHFFltsscUWW2yxxY34uRwwv/d7v/ep+6anp2+4/Z//83/On/7pn36+q9riM5MJQX86zFKpHb1pGRrZZIz/cHwey1BJhw1qtsfVzTr3b+8iFzP581MreL5AUdrHf+dgH9+9aYCptRrVlks2GmJPX4J40uUv3lyl3HKJmDqGqqKFVKotD9cLuJi3Ge+KsVZ1GIjp5JYvMffSM3gotFzBQ0ODcPtDXGzpJPZ+k/ClN3GrZTRNgyBACIk5uZvWhdNYuw9QO/4qjflpZNgklM3iHX2Qmct1RCDa2u9StuXJ3o98FapGqLuX7t0d7BnuIjjxEvKSw9Btj2CMdbN47BjFqVki4QzZbAdaucB6sYz74o+J9gzwwPYu/uKdFk3Xv3bvBnIRwsuX2b2r85q0yYf3WqEvHWal3EItbdARaxuMlGicHd1JhlSb+hN/CJ6HoasICfGvfptYvYimKATvW4PilkFYUwCJXFshVikSrC2BYeAOb8NY2SQIYL3hMRZpUSmX29cXjV27IscLqF88R3RsG80bOWBUFTX30xejlmvjvfkSIhxBlIqIRg3FDKH3DuCbIUAhdOAWbFW7oczZf49IKVHC0U8/QFFA//J0ohRFIV//UGbJDeR1WXDllo/jC9JhA19IhlMh/JMnqS8vkDAUFBHgBwHCDxAri8Qnd3C+ZOMKsHSNLktBXniPVn4DgoCSMOjKdeAtzYGhE4pGSE+f5O4H/ho/mGng201Es8ahgQQDp57DvXweaYYZvuNBtL4hwlcvE5cBQgqWinWkFQFPIY6KFbiYvQMshTtZLtZxvYBnL27w+E2jzCdCZFolRjSbyMoVkiGVsGZy1siwN62TcMo4Kz5uJIXVM4iuKBg9vVCvUfvPvw+BQAmF0AfHuOOODtaMDE66h82ZOvWmj11xiUTidA2lsEXbuLq8UWapGdDwm5Q9hX0jBt5LP2Jzs0jVDei++QgRO0mmZyf592UfFcBUJIpjY9sBV0sLrOVcws//OVq6m998+Jtc6OjirbPTXK0XOHrXLbQaOTZKNRwvwNQ1siGLQdlgOJlk8c3F69tbVfE1nUNDaWJqwKcFCxc8leemVq+NMdCO4j2zVCZpGezrMP7K168wFOjzyzw8luTV6QJrvka+4bI5PM62bYvU19fwgvY9sP2A8MAgmz2jrE3Xydfsa+dpuj75usKu3iSuYaItzWIevAW1XqP54lPUv/pbHK+FOLtQ4LvJBTbOnwMh2Cir9N8UwdVtzMCHcglHCHw9RG9Phguzq3RELN67sorarNGdjeLNLiCEwEFHVRXOrNYYSEZZb7iIkInh+GiWidXTR2UzT5ddQa2VSWkhwl0Z1MBDVsqo1QqHBns5EvdYuTrLPkvSPDBEWQtTa9roMiCZSvDcK++B7eJpGsbgKL5uMhhWqL7xJqYQWB/3QXguwdwV1L03I4VATaUJKiWc+auEj9xJ6/iHNf8Uy0KaJtbRu2ip+s+cMxTlQ3kfTfocHcnwo7OrfDwRJhUx6U5YPHVhndVq+z1HUxV6kxa/caCPN+aKrFVbRKIGEVPj0FCa7VkTIYJrNWOgHaFvNqrgOmCYuNEEwft9QkrJQMqiPSt/kmw0RNL8lJ1bfKEoikJobZHWa88hmu9LwikqofFJott2UHj2++C357wgFGWzUMHoHqU+sIPh+wPcp7+HpyoICaGwRairm9bqCqLVQFFVZLWEbujkp6cZbayzbdsRIuEQjuujAXfsGgBNo4MWyYVFVt64Ss5SSWzfgex6iCeXXDpSNnpfjldnS+wf7mSpbNMR0YgGDraU5JsuYUPjpphP6ZV30FUFPxAEQqG0WcR96Ufc/+hv8EfvLFDJ55nojLNv3ySzrk/fnoPUEp2srNVQERAKYeY6UUNh0HX0WILlfAkjGkHlwyAcNZ5g3kizcuTbRCdvojOsUWg4vHvpIlQqYFrtSUEIZL2KKiWZ0TQjmTAlOyAbNdnfl2TI9OktO7xTrFJuuRi6yv5OlclIAynDnwgBqAqdvzy1SsP9MDPm5GKZejPCA90DMHvphu2sDwzjIzk0kGKh2LguEwfakoKTHVHE+8EDuqrinn2XG06CQuCeP4V+x0P4P2XcsXwP//XnWbs6Q77uEEio1R3uPHAIK7eL00WbwVSIsNpWEVDVLafrFltsscUWW2yxxRa/OD+XA+bv/t2/+2VfBwB/7+/9PTY3Nz+x/cEHH+Sxxx7j7//9v3/Dz/2jf/SPOHr06A33/f7v/z6vvPLKddv27dvHP/kn/+QXv+BfIVTh88BEjhevFlksNunPxHjh0jphU6MjalJ631CoaypvL5Q5NJgmFVIJTO2aLeGHZ1f5tX193D+ZY703TjRk8IPTSwxvT5Nv2KiqguMHuCiEDYXudJSh4X5i2TS3ZFWyUYOByjLz/+l7JOIRWkIjCALMji5mVvKcKCjIkk7j3TNERZjBHfvRZ6ZQwlG0oTHKP/weodEJWpMHiO6/FU1KQoaCn8jQzM+TSHXRsl1Uw0SzQghDx5OwYQsGswnqr7/Iysm3yUYMOiyN2R/9kJ7bbkPFIXPbLWiVIoqqEjtwE/7cPPMLaygLc0R6JtjdESbfClA0DeH76PUKQ50pRkLeJ7SfVeHz4ESOV69sMjNTJmla6MkU27o6+WrGo/m//t9QXBddVVAATVHa0ZvFDbrinRQcQSZikgprKFJg+B5KtUT1j/83/MU5ZDgKOw4yuG2CjXQ/O/wImZkTkIhR9wSuavCBaV9TFaTnYnT3waXzGF29mIkU0nNRDBO1sxv7BvJjHyB9H/+d13Hnp/FCFpH7HsU5fQJvYRZ/eR5j10HMm2/H7Rnc0sD+CFJKtJ7+tgTPDSR1jO4+/Nhni/7+rN8fMT8MyfxoywgUAiFQVai02s9ht1+nvjaD5zQQTR9/7gpjO++gVGli6gp47TpQbtAuNH5TZ5jWsWlkENC5axcd3Z1EKhuoUoIZQs11It56jez8OR6WBn2378R77Vnk8z+mVa0Q6uomf/SrvDxf5fBQGKVQRfo+iXiESCzCesOnbkvivcPo0Rg37+vGW3OZ6E4gFRVD1wgkfG3fAMbr52levkzUUFnL+8zMLjOWi8PEbuZefQ2vO0lqYhLVnMBbWUKPxmidP4msVTGGxvALGxTGDvLMW9NsZFzq3grj/Z2cXqoQz2aothwqqoWvqjw4keXVM3NUPUAI7hiJUXzmSTK4KJqKpgiCWo2OeIZGtUbE0PCFRBU+aiCRdgsjpEOriaNaROwmZmkDeeJVhsf3sJzNsLRRplGu8p0jI5y4vMbaWp4QAdt7EhzuyKK89Tw9YTBliFLTIxCC9Ogoem8PHTEN8SlSgJqmMbVcv8758lFOLZWZzHVh/hWqX6EoCkbgo3ouwgyh2y2c15+nsbrMUDTG46O7yXf1kx/rpxFI7DseJbq+iHb5PAEK6vhOxM7thLDI1/KfOL8vJLmoSUx4uKUiQlEQ5SL++gr5eBevn1zk7m05GsdeaTtcAx8pwW21CGdSOFcuolphhBHG9XwSlsnp1QJHdo9w2RfkcimEpqD0DxMKPCgVMAKPmq2gWyZKsYY6vA2n6eGoBstNwW0jOUK1FY6Od3F8qU5YV3A21kFVCUfC3JPysP/Xf8HoN7/LD1cClt49hWy1MHv7Ge2I09+RwnU9ErEwmqbRrJZQst1kVB+7XCKUsbhRhpW/uoiy7whadx+2GUbvGcBfXkAZGif26K/jTl8EwDx8B6HJPbQS6U+dMxRFwWrWkJtryFYTNZNDZDpxNJ3+qMbX9vRyfK7IRtXGMjT2D6TZ1R1Dke3i4B8QCMliqcVyuUVPMsJNAym2ZS0iGoTV4BN9JeS7iLPv0Lx0Dum6oOuERiYwD95KywwBkDYlh4cznJgrXvdZQ1O5azyHTrDlf/klYNUrNF/8MdL7SPaEFPgXz9KqlIh99Ts0n30SPJd1TyG0ax+ze+/l//n8DJlIiv/rt/4W0bU59qfHeP7sEnapjNdstJ3lqTRoGiNpi+GxXowZh653n+e+ift48dIauweyzBZb7Eur7PQ3qEmNtd5Jyoqkv7mOcf40Eztv4ydTGxy9awhphOhPRxCBz7krS5RbLeKZNFYguaM/yl6tjDrcibN7gpmrixRW12m6Ph2miiivU22Cpqr4no+nJwhZPrHxbYhYHDX6vlSmbuAXNwm8DbRIBHt4AMUMkQqbaIFLYDdRd+xnve5QKNW5WHKZXgzoiuncdsso/tVzBOurSCkxegcIhIH0PJRGjcrsDI/fNEYtHEdXQZWC4I2XyV69yMNdvSjdnYh6EeXCSbyzAbHHvntNMhfamUrnlmrXOV8+4GqhyW3je4kszSK862tzKSELfXwnrhDkTMk39vby5lyRlXILTVUYykY5MpQirvrX/Lia5+CW2mN1gIoTtGvDGZpKSIMgv4Hhe6DdeHmrqiry6gWcxTnydQfXD0hFQmzWHYon3+HwQ32cV+MUmx79cYP+dJiYJj8t6XSLLbbYYosttthiiy1+bn4uB8zdd9/9JV9Gm3/9r//1ddG5CwsL/It/8S84evQouVyOf/fv/t11xz///PP84Ac/4MCBAz/1vPv37+d3fud3rv2u65+r9M2vNO3MENjfl2IwG8c0dOKLFQxVodRwrhkMIqZOzfbYqNvs7k3iCyi3PGYLTYSUnFut8fW93XgCnjq/RsP2uFgVJHv7aF6+ihABqqqSSMQYmRzjpfkabmWDvlQYvVljyC1w4JbbsE+/TSZsomdyXNQynDo7Q6x3iLiukS9WqRsaLV9jZHwPsd5e7JnLiEiUeqXC6oWLuEIi6jWGenNY4/tJdHdi6SZNqeHaLbBbSBRaHmRiFvu1KqWzZxC2w4bjog30IGybRCIOF06wcmEKIdsR7jXToOu+h1ltSfxSkYuiwPZMCNeMcHGzTncyyU0dJqNeiXA8TvMGkXZhPL42FmPD7aQVQMSQpJIB0dImtWSS0O59qMkMhCyk5+AuzBAaHqOzXCKVjaIikVKgA8HiLObRu2mdPQm0C7k7J17F8TzEzV1EghaGFSEatQjpJqsVG1NTkUjSERNNVQkynaQe/XVaz/2AxvGXUTQNNdOJNjpBqLufpnXjbA1/cw1n9jLQls1qXLmAOTJBdO9hkILQ9n14moa5sYxiWvjJNK7y0yVa/nvBjiWJ3nYvjWMvXBeNqcYShI7eTfOnfPaLoDtuYmoqbiAw1LaB8IPI/uFslI1qO5rfFRD2WyiVdYxEmJKtEzTq7EkoLCctms0WgesQ1gxMVdIR09mVgFK1wsitR1EvvEfj3VdQ/Wa7PkkoTOK3/g5a/xB2tYZVb2D/pxfI3nIbraFRlM0Vqnd/k+dnGoh0J2dXq9x6273kj73MXKnFcCaK1qqgGiGKO2+m2jHJ8lKevmyct+aLuL5ACoHne4R3ZRkqV2nWmkRSEXQRMGop1M+fJmyG6BwbIZkMUfmz/4gKJB/8GvUXfoysFDEGx5CtBs3bHuXJCxvUAgVHq7Bsq2hKnjvG+2i4AaWmy2hHDKTkxUsrlIWB0BRUU6PTr+PU6xALkY2G0FWVdGWNvdt2MqsITAQB7TpQaiBQkHQmwihBjEgq2nYQENC8ch5rZJLJtMnSBox1JeiJSHoO9OLIATQEcUNBuXSGZqOGhqArqpOJGKjxFLEHH8KJKMifUodJVdXrsqI+TsPx8ISC+VckmNcUAercFZxz7yFaDYxoDJnrfj/jQiIaNayzb5ITKkr3OHP9N3G27pKK9HL43lGybg2/UadTsWlicGgwzTsLpeu+YzQb5UhGQS4vEIrGURwbfXAUtbOHgi1BVQgpgkbLRgqJomhomopa2mRHzzZs0cdIRxwjnaEqNKoNh0S1RcaUdHekeXsuT1i4SMdBVVV6O3qJNwpMjHTgLc/iBoKqC5drAtdtcO/2bmaWNthomBxtTTNy+52curhAqSPBYCrEtrSF9dL38BTBxpuvM3joQSpNh7IX4C7MMiOHcawCDz18O29eXiNsmYwmI3i6geM0GMwkMFX3hhkeaiyJBLxkhtCOPTgXz6KFIwjXwV6cQx+ZIHTzndhdffi+/6mZL6qqElqapfnas20nyPvouS7C9z5KKxSmP6LwzV05bKmz0fC4sFphNt9gKBdlV1+a88ul6zL+hISVcpOQrnJLTwgR+J8IkJeeR/Du6ziXzn+40fdxrlxANBuY93ylPbeJgIM9EXoTFmdWq9Rtn76UxY6uGGk92ApE+CWgqipiae5658sHODatd48T+8qvEfrqdxCROIqtspbs54/fXqbqBmw2Pf5LLMbkhQUyYzqRwKfk+aiaRjgSRs9kUTeX2ZvJ0nrrNN6h25HlKg+nbI48tAPLd5lZLTLSn+GJl+ZZWS8RCAmKwkB3lq9tP4Q+c4Hw6C385MwSZjTCkycX+Pbebh7YlmO+1KIjk2Ay5DK0cZHmH/9xO1DDMNl+692sJsdw11ao2T7O2gZHRnfSHQtxZbPO+YpPLpclEUoS21winR2k3LBw52fB95GajhcI4rpCUvEJK4IGOpFcNyvlBpvVFqqmYqjgLc6xJAQ/CqcYH+nnzNwsAP76CnrfIH6ljGKYJDNJtPwK8Y4enHAMs1GjMXu5XW9xbYlwtUiz2bw2LASLs6i7Dl5br7lSvSY79nEk8GI1xLce+gbuu6/jra2AomD2D2EeOEorlgTZrvHSYQY8tiNL028HL0V0iQz864YSoekooQh2pcZiqYkbfNjRYyGd4Y5upK5/apaa4Tm4l84RCPCDtqyZ64t2JnvdQV4+y8j4vcyVmliGxW2jWfjvQLpzixujKApl95MPU1hXCalbc8EWW2yxxRZbbPHZ+JXyRCQSiet+//73v09XVxc7d+5EURRSqdR1+0+cOMHRo0exLOunnlfX9U989q8aZV/jybOr1J12BNr2vgxTa1X6UxFMXcUTkoRloKsqYx0xDvSlubRRY7Pu0JMMc89kJxtVm2LDZXqzQdMLuLRRJ2pqFJoe44O9FO0AygUC22Zi5zaemqlSFxqDUZNKsUzUa3F2aZXIZC+7cxm6+7qpje/j9ZNrmJqCL3zWHIvJTBq1USOIp6jtO4Dd1Y2W6kWzA0Srged6oGrEd+yhMLmPpaUqoVwny/k6vekQrZqgUGkQqCpjWYt9uRDBD58FJIoCmq6xWrXp6cqgbSzTOH8KSw/T9AVCShzHpf7KT9j9lW9xQSYIlBDPXdoAIblrZx8pmnz/qbcZHB/htvQAncIgpfmfMLwIzSC3MYO7NAeA2t2HiCWI3HQr9qnjiLPvIiTonT1YB48ihMBIZvDWV1ClQHFsFN/H2nUAZ/oiigyQtBeejQA6YlEiZ18nP7dKsGs3LM+TyGYwEmnyLY94yCAd1jEGRxCxOI0XXsV3bNTBUVBUAiBYW0a8/DShB7+Jo35SxFrareszOIIAd2URl0XCEzux33gBu1RAvn+MnusketdDFKNZAtFeIP/3Utz74wjAGZ4klu0kWJxDNOtonT3Q1UcrFP7S5driqs+DO7p4ZmoNhKQrHmKp3CIbMbhjLMvZpTL3TXYRswwCrYEei5Nq1emIhwiMEP7Jl/nmwbs4W4mwqKnsSESISp+RlIm9MI8eiWDmV2jMXiFmakjXRWo6gedReukZzEcepxXrIVFewzn/drs+UzpHdGyCEzKBJ+qovs9avsVT2Sz3PfgY8uTb1NwmfTt6yA/s5Ck3Sc9qE9OM8uzZJaotr11AWwhSMYvnT1zkr+/YS/LcCZyyS0xKDASZjhy12SsMP/4bFP/g/4MmgrY6vhlCNBsomk5QLqB397OgRGnViiixJLSahEJpZjbKLNZcJgZy3DmUouQInr64TofiETYC6j74gY/ValB0PaKejgpkwgaNao3U0iWGd91KLmqwVHPRNZWIqZDO9VBt2fTv2sVaWiPxP/2/6Dz1IvK1F9vZboHL4Zt20JMKI2WAKn3CtPuP44I2uoNYrptgaQ7ZahDp7EV29WIboZ/5PAkh6Iyb+EIQt0wkkK+1+MB0FAu1HWx/FcL3dQU4+SbNC6evbQvKizhvvUbktvsQqQxBuZ3BENJAmb/M9rE9NDydO7QSzSefY71epycRxo0ZRHsnOLrtECPZPmYLTbxAMpaNsN9oUPz+H1M1fcKldWSlhNY3SPzr38Wwa8TjMdY9g52pNPXNTVRFwQdEEHBf2mfVkcx5cOrsIp5UGBwf4tt3jbC+VqQvaXE8EO8Xqm8LXTZ8iHYNcGQoTWggxutTy5QClY5klAN9CYTnMVf10YtNDg720HP2Fe6em6GpmgTrBk4g8Kp1lI4eVjdLmNInSHeyb6iXmUszuIrKqfUWvR0uh6wW3vRJhN0ium0Hg/t2Ezm4H/vk8Rvec2NiF03fBxTMg7cS6RnEOfsu0m6gpXMYuw/SynUT+D99PgjVyjRfeQb5sboQfn4d9e3X0O98CF9IUOCdhRLnVj6sTbFWa+EECoeH0pxbKn5CpmxvbwLxKfORv7mGc+XiDfd5y/OEKkXcVA5oZ7n2hmFgItVWPEUSfMwQ/LNQNQ07aHs7LU0ibpApucWNURQFWcyju07b6azpCKM9piEl0jDIR7L85clleg6MseAELE+XKbc8AhSipkZemux46HFUv86vbYOp5RILxSaBotKFzd7RJNpP/oxmIkGle4Li5J1cmVmG+ikGszHGBjp44cQlaoUypq5iewIpJUvrRZ63DG5GYSIS8NaCx4MDYQJV58xKGX1pll0jndxjurTefAWnVkHItpaVDlSPvUTv136dzfImV9bKbOvpJCThL1+/iBACTVXR6xXOKxG+MtLF0ViKJ185gxuOISUYmkIyESVtKXTrPuvVOiuuxrClUai2kL7Hts4Mlbk5kBJFN2itLKEPH8IwdDzPR77vINVicVThM1Bdpf7c08jOXoyRbRg7998ws/cDRK1ynayfoihYukaFGzsqGq6gke0h9MA3iLYagIIXjtJ8v2bbdQQ+kfdPLW9wCb6iYuw6wPzFJ/A/5mWtOz6VoZ1kVP1T30uVIEA4Ntr7QSuBH+D4AZmoSTpiYuMxlDIZ74xxx3CSmOptKe/+d0wgJE9f/GR27CPbc4T+qkSzbLHFFltsscUWvzQ+lwPm3/7bf/szj1EU5ReSLvN9n9dee41HH330uhf9D5iZmWFubo6/9bf+1s8814ULF/jbf/tvE41G2b17N7/xG79BPB7/1OM9z8P7SOSdoiiEw+FrP3/0/2toOjUXfAkxA0x+eZGSUtV5+XLhmvMFwPF8BjMRFopNxnIxJJKlUovepEXE1Pnh2RUaXkC55VFpeTx1YY1vH+hnNBfj3GqZ/lSEqKlRtz2ubtQYzEaR8SSzjkZXVmONMAWvTjZqoNcr4AcEioqUMNeEu267G/HEf8RO9KC2GqQyKYKoxcU63HbzLQSVMhfVNC9fKRNe8lBaLiOT93C0w8Q49grRgSHm+nbx7ntX0cIRdh/J0ahKLs0tM9CZYltSR89Guak7wuyps/TVa+iWhXBaKEpbZzs1MED1rdcIJdMYtoP6vjFEoS29JZdm2fn138Zs6VztiBFWAhZnlzi3WaV7cjuZrjSrVZt8w2Fnb4q07iE/WvQTCB84gre2jPQ9/EqJ6PAYpf/8/wMpwDBASvz5aRqrS8Qe+w3Mw7cT8ly8y+eRjRpGTz+1nzxBsLwAqopihQkkpPcfwjv1FopuILUU85dnmLj3YSovPEXOUEnmOglpYGSymIdvh3IRb2m+/Tx8LEPF31zHKhdQsl3XbVcUBSVkoWjaNQfLB+id3QSzVwhKBWTsQ8eonc+z/uQTLN3yNd7Oe3Qlw9wylKEnIq+7N79Mfp7++tGfbzSefF4k0IqnUXdnURQFV4hr/f6L+p5A1SnaAseXxEIaaUNey4QYjiv8xsF+lioOVccnZoXQVWh4AfsH0rw6nUdVVaYrKzy67QDJhSnqjSYry0WEEKgLf8bY2Dg3PfZtDEPn1XMLvPnGBfTtvRyYGKf10o+wwhaa00DoBn4g0FJpXNfFzed5bi3ERGeWW7/+LRrf/yPqTQd7xx6W4hpycxNfSqLj2yk5AX+yohIfvp3BZIhMOs5/eGcZP2jyd8Z6eOLMCkI1iER0bLct+6caJpbtc3qpzF2dXZRn59BVMJQAubJAenw7Qgik4yClxAsEXrWMiKfBbuCjoXb0sCzbmvmIAMU0UXwPU1NREEwv5TkQCxCaQZ8laU7PE9g2mUSMaO8AiuYQUSQRQyXmtbAqJdxmE//EMmNenf/TI7/FX57boNVq68jbtkMuGUN6Lv/Ls9NELZNHDj7EbbkeNOGxbXKYyVwHgRQ3fj5UFRGOom3bibAi2O/3y5/nSZJSMpxLcHq1wdtLeUxNZUd3golsjDMLTQ4MprFUiRD/dY0GP29//ejvH99uVkvUp85ef5zbzvhqvfM6kQcfo/m+A0aRgu6ISiYsieiC+o+eQg98BtIREqaK8H2UmQvEVJOV5A4sFSK6gu42Kb/2NLJeQ8+GUZNpRLNBa+osDduj92/8Ln3lZS5XPA7uvYnWi8/gS4mUMDTQRfPMSU5GR7mwsoYvJaqUTL+1yWJtHxPD3SzPF3hgsov3lkp4nkOuM0vTEwx2JHn11AzVSo1bjuwhKU3Or1V55comEctgMJ5GmiGCiSz6nI8zPU3VFyw1m4ymw1SMKIV8g4bjEWs6nLha4Iym8rW9o1xdLWF7PmathPPEf0YaBhgh6mtLFK+eIvNrjxOUCu2+ZEUx7Abq+jLW4dto5LrQFJVaoDLdgHqoj467hum2FHQNWj/HuKcoCnJ16RPOlw9w52eI1asE0QQbLXmd8wWA9w3QVzYb9CQjLJfbeYaqAoeHsvRGtbYD9wbfK6qV6wp5fxxZKaGkO67b9oHTRP6Mv+vj31UNdE7OV5nJt4uKj+Zi7O+Lk9Q+/3vhlzF//Sw+y7vwF3ldVrNG4Np4c1fbG1QVLdOBn+5AsSIUPZ2llQob4TTuRoVMR4b3VmqomkrKMrh7opMT80X+9StFkiGVfV0RHp0Y5NaudRrHX8XKLyEadVqtOvKRb/ODq2XMgorYWEO2Gizla5wnyWhXjsXL01hdvSiGRdBq4deqrOcruJPDyKDt4Hhrqc5AyuLI9n6ygxb9FmhvvYBTreJKjUQigVsu49KWytKmp4hlu+lFR+/q5YVnrqCqKoamYiBQW3Xqm6tcHb+DiVSKO+46TKXloblNerwKmeo6qfVzDI7t4uklh2bgEfiCQEq29eXYl9G48M4aaiQKqoosFRB+QF9fF3Nzy+320g2URo07ey2Sbz+LEo0TeC7O5fMolRLW6AT29KXr2veDZ1fv6MaRElSdkgerJYdcMkJHMkKxbrNSvj7/d7I7jqFIfKngh2PXPU+fh83cEJGde6meP/2hA0dRSO7ezyk1x0FXIanf+NwiZKFnOvDXlsjFQtQcH1/AQqmFEJKhbbvZ1Z+lM6oTU5xf6Dq32GKLLbbYYostttjio3wuB8z58+c/sU0IQblcRghBIpEgFAr9Qhd24sQJGo3Gp8qfvfjii/T19TE5OflTz7N//36OHDlCZ2cna2tr/Mmf/An/6l/9K/7lv/yXqOqNpZSeeOIJvve97137fWRkhH/zb/4NHR0fLs67u7uv/bxYavLK1TyLpSZSQtzSuWU4w97eJCHjk1kHXzQLxQYlp0AkErm2rdQS3D/ZxR+/s4iqKqxWHFwBu3tTnJgvEg/prFVtDE0lGTYQQvLCpQ3um+wkE7XI120mOmK8t1QmFjb5/ukVDvQm+MquHnwh8AMYSYdIahJZaBA3LCq+SranG7+Yp74gsRZn0RpVkvikQwHNsEIgXVYzg1SNDs6dnCKqSgLhoee6mFpfY1NkOTwySa13iBfOLBEz2oVHL16aZxCHPXt7kbrBjkSKeqPFy6+fJx4yGOvqwavXkYaJEviEVFB0HXt9ldDQMKpSxQzqCCGJhAx000AaIV6eq3J602F7d4I3Fyus2hHGRzsIRy2+f2al3dYRjbcWKjy2f4DDg7nr2lR2dxOJRmnMTVNP91J95xVkdz9KrYzitK4ZmqRjI5p1vKsX0TQV99QJRL3WNgxtriGbdRQrguoHSCNEJJWkujSPuW0nLV+hUShxScL4I79GBIdIVw96/xB67wBaPIlz8Swi0jaMtNOANPhIJLIV+KR6eq57boSUrJWbbNzxTWjUyLp14suXkc0GRkc39VNvYfaPoLyfYWZ7gsV8HTew6XJKWOEOSg48e6XE1/f2sL3n+gy2XxY/T3/9KB/tu7/qzBUaPDO1RqHRfo5UBcY7Ytw32Uk6YgLQDUz2g+0FXNqo8dZskdlik6brc3Qkx3rNxg9i5IdHSMYjLL92DN8PAInZ0YW7+wh/8cJ7PLR/mIN6jYH9vayKEJnJvbSOPYVoORCyELpAj8RQunopVVu4iyvo3d08f2aeXXeNYdgtTF0jZNeJpiQbfjtrzC9soqkmkXiSoqNTKAX0BA4tv10w3VDBDgRVx0dVIB4O4Yt2LRotZFFuNnAjCRSlbWtpBZKorqGlMnhSQVhRNLcFgYe7soR54Agbr76IIgRurQEdCk0rTlj66Mk0Xr6OomoouknMVOjvzGDml7hrT4bjRjdTC3mcegP78jkKR/cx1J0l51VxFy9BEBA2DBTDwKzmyaxf5B/fcYDFlQILrkqhZnNpdoVXpjaRsh2R+723ponfe5hba9MkxrcR+pSMTb9UwDl/kqDRQDVNFE0j2jOIOTqO8il69h9lerPOC1eXaXgSTyi0fMHx+TILZZtvHRhkf1+SmGX8zPN82XzW/gqf7LP2xhIifP19DFrvO9oCH13K6+ZDgHhfJx1XL9PIRdFVBV370KimB4Lq1Sn23LuL96oqyZDBjkiLUrVMXzpKLGIS1F3cZgM7mqIpDTo2lpiUVZqaxaXYADc/8gjVM6fQZYC5Mkt+dC8X37iMIiW677UfXilxNjd4Sxrs6kowt1nhK7t76EyMslJo0GrZXJxbx2q20Mww//nMBodGOri4XqPU8khGTKaLTcKBy4pvMLRtN5eefgkRUhBSJdANCjUbNRJFD0eo6BGEqNESAW8tVNg13EVluYRaziMBVQgUQ0fRNEqbJepLS6zc/CjvXFmlWq4QT1ocPvwQ6f4cHeEQ51cr/GRqHcf/0NmeCht8fU8Pfenr7/en0Zg6CZFPPzZqGqR6ejhxZuUTbXitraXkzu09bNZdNFVhIB2mN2Fh6p/+vuU2q9ecBzcinEqT/tgc+XlYqbR4+r0lFAXGezJtZ5aAqbzLzcNpepM/3336NH6Z89dn6atf1HUF1Qq157+PkenAiESRnoub7mDVhtpSgVxHGntsF1NFh5IwWFvY5PGxXmzXJxVuO19+eHaViK6wK6WhS0Gz6fD8+SWi8RqZ15/B9lysWIzkjr285ljYTo2Q3SJoNlABPXBZKdRIj3Sh7djLXKGB5yhoZpKOgSx6o4ieSLHmmvSkNebzDRqNFgvrJf7nIz1EvRqXZ5doVaqkElHCPX1YuopXr2OoYNoNMhGDzKEHOOeCEYsSOA6+69KRjmEW5th1ywHeXG5wfMOjdek80a5OesIa29MeyekztCoV/B9/n29/669T2LaDpi9Z7AxRWl7m1DurGKEQslYFTUMNR+nA5tYejaXsMKvNgOT4AD0rF0mfeh6VAC2RxPxgTVQrY03uQl1dvNYu1xxvVpj4xE6sZI6Xr25yarHcDkTxAmYLDXb3JNnel2Wh1AIgHTE5NNJJZ/ynKxV8FqYub7Cy7Sjj23ajbSy3g646+rhCjMWG4FDIoqfz04PsnKN30XjmCVQjoNCqs1a1QYJmmqx0jvHS2VW+e2iAicFffDzYYosttthiiy222GKLD/hcDpjf//3fv+F23/d5/vnn+fGPf8w/+2f/7Be6sJdeeon9+/eTyWQ+sc91XY4dO8bjjz/+M89z2223Xft5cHCQoaEh/sE/+AecP3+ePXv23PAz3/zmN/nqV7967fcPop82NzcJgoDu7m7W1taQUtKSBn92auW67JNmE54sVnGdbsYS6peeCVN2VZrN6yPOmkDgOfy1QwNUbJ+mk6c3GaI3aZEI6RRbHr6ApudjqAoSiS/B0lVWK00O9CbQdYOhbISmGxBS4fzMChcuefzuI7spVepcujpFHUHEa2JEYnT1D2HKJEp+CaMVoI1tx9yxl239kmq5ynDa5LaRGHN1wXMzZTp6BrFCCoqu42ghPE8ws7TCTQeGKDkSXVEQHd04RhizUWNhfRVmF5GBx/b9/eSiYfxmk6KI4O3Yjb+wiG3K9+snGCitBpHeAXwrihdJE/Fs1MBDMUNUnIAglGLl0hWWnTBXCw3unOjGWcozmI7wF6dXkb6PqaugGpTKNV549STRm0cZj0icWALPb0fH+maC10QP0ZkNEmcuko3nsBQNs1FFqxVRDBO9bxhRq6C5Lao/eYLQwaM4J45hui5qrhtRKSPtJtIw0JIZRHETPR7HD8eQNUHU1NCaVebffQ+zN4Nx8AjVRBbqTag3CQeSViCwBoZRhGgXNo7FCXwfe2EWFaisr9MSKoEEU1O5sNnkzFqTRsUjWM1jSZ+7Jw4wPPcOShCgZLuwpUQ2myiKQskRNJ22Zr9XyOOHE9d0+F+cWiGhOCjiy5Ej6/kphrGf1l/9jzihFEW51ncVRUEPfCQKgaZdV3vqVwUbgz89ef3YAnCq0cR3Xe4Zjl0rMq2oKqfWXY7NbKIEgrWKjaKqnJhxuX88w2TgYp87RrOzm6Hv/DVKGwVsx2VZi3O6qFA0cgSbCvf1D9NXXmF70qBZqxMe2YYo5fFVjaYPVU9SXK6gS5/MwR4QEk1VmC/U2T08RrC4gD99kb27bmd2SUENxwhaLWKD3QSOS8xSuGlnL+fXqgxnIkR1iaUrTHbEOTFfxNQ1qrYHEjK6BDNE2gBtvYoqRbsIMwoimkDfvpdgYBT3K99Fq2xiXXgXx4pRC6Uwd+6neekCiu0yYAmOC7AGR9E1FSNk4noBHfEQ/8eDXWwuLTOXr7KxWWZHJsL+A30cW2nSqFTpTlqMPfoolf/4vxA02xr3gWMTndiBObGT+qsvoCdyBJEO8sUyPzy7guLY7Sw0BaSqgRXmtbkKndsnWLuwxs29UVR5fZuGfI/mpSn8eJrawlUaly8QVwKSyRiJW+/G3b4P76flwWg6L14sUq01iKgKQ6kQTiCQEqIhncBzqZcL1H5JWZlfRH/9YN9H59sPsFz3E3Oebpj4UkIQ4Atx3X6jp4+6EcJbW0R4Ni7w8Wo5nbpKR0Il65XRqwUydeg/chDcFvbcVUS9gejsJbH7EHEjhDF9lnuSHRzaPsAlEeN40aLjnnEOdoYRbz7FVEPBt6LQrKNpetsZr2nowqdQaRLNqMhygRW3gTfYz7OX1lF8n3g0RLyzh5Kvsp5v8sZsgd19ac4sl7Edj1LdYf/2Lq4UWmSGsyR37aVy/iyJcIiqIzDjCQQK6cO38kcFBZlIo3o2i+Umh+MxknKVSGWTWjiM1A2klCiui5HN8nZR8t7SFCJkIcwYZU+yeH6d+6TBSELniXcXr6u9Au33nR+c8nhsZxb1/fFfVVXKvsrVfJOVik0qbLC9K0YuBFY0fl3bKO9nbEopUMwQSiDwNjaoNZqfaOPr2jtw2R5/P0PFqVLYrH7qsYqi0NHRjWuE8CulT+4PWShWjNLq6qee4+dB0zTeWmoiPIdkNMwTJxdpvX+/dFUhX2vxlW0plM9RU+LT+sIvyi/aV7/o6wqvL1NfWUKplInc8wj1U+8wV2hgOx6KqqKNbGO5fz/FuTyNsotje1xd2uTObZ2sVFtUWx47MyFUp4n0XCzpEw4EmqdxJhzjka9+G+dHf0pg2/iD2zmTdyDbiQhsVDMEdhPVsbFCBqc3bTp0g0bDRjEMmm6A47iIZJpcXw8HXFixK/hJi7GkwbYo/PjHr/HgNx9E7x1ACRaoCqgUWgx19BPJeQSOg7r7IP7EPqaffRYThW/svos/nZZ056LEnQp9Q328velyJd9kZKCLUMgkhs+YYuPUXYglCAHd2/fiLs2QjsYh3smGq3DVCxPu6EUvbaCYIaTrYHZ00hNUUabeZTjw2b73EGprgdprP4BUFj8Wx7Xt69pBdV2UfUdorq8SUhTclXnUSAzrtvvIB5K5+Q1ev3R9f+lPmMwVavQmTFKGZLQjykQuQlAvsVr/hR+Na1gKXN6scxmJFRpur8XyAb5s0vQCrqxXeGdmnR1dcTrD6ifmWy2Wwrzlbuy33qDllIiHNKyOLvTDt/OqEyEbNXjhwjIdRoDJlyexa0iBXiu354ZIDDcS/5nvoj+tv26xxRZbbLHFFlts8avNF1oDRtd1Hn74YZaWlviDP/gDfu/3fu9znWdzc5MzZ87wu7/7uzfcf/z4cRzH4a677vrM5+7q6iIej7O2tvapDhjDMDCMG0cKf7DA/OD/ubL9CQPpteucLTKwrwtdfrkFHKO6StjQri30P6DheDRtmwP9GTwRgISG66OpCpWWhy8EqtJeQGuKgu36eIFgpdhgMKrjoFJoeDTdgD39ab5z0yDJkEbnlXdYqPtoSAIJqqbjlgqowmd4zyQ337WXHq/E/M338oNnjtPwJTVXIISgoyvLPXcfxtA19EgEoQp8z2d6ZR1d18kMjOJ0dhEKBKJisqaYZH2fcCSK1tXd1ikhu7IAAQAASURBVK7WDZSoSfbqOzxw+E6ePrvCT1YDbr3tIawL76AWNzEtDSOdxvrGd3nvh09juzbRkE5/OsFyvopsNjC7R7CLCsmIRaspePXKGt/c3c2bcyVk0F7sx8MhnEqFcCKCsOu8/dZZuu3LhNJpwvuP4nX2cuzMIsdfP8WRiV6y2RwrC/PEzCjp7gyZ0W04QmGz1kS6OptGP513f4vB9wNx7fOnCR+4GVsEBKtLSCHQAw89lcUY3sa03c4Q+KBwQ9wyMAIPuN6xF6QzxLbvof7ME4jqh7ItelcvsbsepJ7t4/SqzdmVCrYfoBsmXfEwtifY9FRSvcN4ns0LeY9v3fVrJGSdxqVzH8o7aAZudzexHd0gAsLdvfjFDxeKa5UmDT9LVPnli2X/PP31o1iNGv7VC7hzV9tF0sd3oI5O0jK/uAjNL4KVuvupY8vFtQqHBxMoUqHuChRN562FdbRGnSY6FdunanuEFcn3NvP8vTtG0S+eZfG5Z1HNEJn7HuGZDZcV6VGq25gq5BNRUvEwwamrFNZX2HBhx2gf9qkTGCPbWKo4uJ5HdyZOKhbG7O7krkqd5mA/gWFSCmeIDahQLtCzeonbbjrIiUur+LpBUw1RcH0mTI2odNnVGSVj6TSrNV47M8fubf3UXZ+lUhNd1QgbGsmwRnW5xo47Jwnbw4T7BjDCYZRoDCWVoZwv8dKKz2w5QdyGg3f/Fr1eiYXX3yQxNMzI37iHgqcQNy0eeng7f3FqmVyrSl80gh/N8Jv7uvnRy+9Q3SyC3UT4PnooxIN3H+SefV0Ey/Okqst4K2XE8CSxPYchCJCGgZJfo/Dcj7EGRyg0BZuq4ErZo+yrWFacUDR+LQPNk1CTOlea8OZinpgVYiSpk9AFRr0C1TKeEWHWzMLTT9JcakcdV4BCw2Xw2R+R1nT8iT2fapxperBcahurpZToSD5IBoiYOhfXq+zIZD7h4PivwWftrx9sv25fOtfOdvnI3xPoBnrPAKJWuU5mSktlCN16H3YgMDI5xOw0TiAR78tZmSogBdHhUfzSGs0mnN6U+K5LryHZ252lZ9yg9sozxHcfoPjy0yhmCKdawttzC+9UTaZIsu4oNAS8OqPyd5UImqYRaAZaIo2CRBM+iqoiHJtMV4y6GWNDa5AJxdhYq1N0AaHSEQ5TkRJNg+3dCWbydYayUWaKTYoNl8GuFLdu6+KJY1NUGjb3HLqTTK4T9/xJDEOnnswQ2n2A01YvK1eKuF5ANBqmtyNLPGzy4GiS2hNPERhme+73XESzjnH0Lt4+N4vS0U2wtoLeP4RvtDOZ354vER3LfML58gGe76PU61jSRVphllyL759Zxn0/U2YeOLtc5u6JTvZ39aFG4wSNBk1fUmm5SCBh6eT27cMJxxC+z2g2wsW1GztVcrEQEZ3P5DjX4gmsOx+k+dwPEHbr2nbFMIjc9RBOOPILy2g6QmFms05fJsafn1y6rkaNLyTPXdpgNBthR0r53M6KT/SFL5HP0le/iOtSFOVa7SbZqNNaXcJ95DcwVzawAp9wVxeljiH+7M1F4ooF8TBKKMobVzd5ZG+YbWM53lsqs7RewPUCwhGLjKahey2C5VnWcx14gxaJh79B/q03CMZ305gJWKo69CGQQiMSTaI7LQxdAyFQImG0cBiExEAiNR0rlcSUPtsuvcXf6B5mM2txanaNmaUGAlhreOgTByjPLhLWVXqSFhc2m8hA0Bm30Ed2c2mxROcd92Mdfx6xfJ6bhw6yXqwRVErEt+1i+tQy6VSCnZ1Rwn0HSSseydIqrekLVJeWMGYuoETOYX7lW7y+2uLd985z+MAk0/kQMxWboe4hovllIsNj3L+zh8y5l5C5Tsw9NxH0j6CU89A72HZaf7wdDINS5zDn3RBzrQ50YPKOo4x1xZCKAEXl5FLhE5/TEeTCKsV6i1/f0177COF+YWXHAtWg2vIJCx/FtfGrFWwkajKDq1vMFpvs7Iozl6+xWm5xYbXK4aEMh3oj1wUH+YAcGKMc7sbauYlUVJaxmK4GuIFHJGJQa3lUXEHO+OL7mqIohCtF7NdfwM6vt7eZIay9NyEn9+LeoF7jFltsscUWW2yxxRb/7fOFOmA+YGhoiFdfffVzf/6ll14imUxy8ODBG+5/8cUXOXToEInEZ5c8KhQK1Ot10un0576+D9A0jfli7VP3l5ouLR/iN1Y6+8KI6YKbhtIcu9ouFKirCsNJkx0dEY7NV5jPN3jtyiaBkDy8q6etUKW2IxmFBElbGiUe0qjbPjcNZVhvejx9YZVM1CQXt7hwYZ2nz6/yd27uY/O1N+lJWPzm4aM8fW4Z1RVEohb37ewmvXKS1Oo0RUWjobzLA5N7OTZTwEDBxsCWKk1PsK03Q02otFbmMZIp/ACarku16bJcS2MosFa16UqphKpF/PIGigKiUScWj9KZ3Aa1CuNX3uTxm+9l2kgzXawycduDJIUNIZMf1A3W1yrctv8IzZPvUGraGIaLku0i8ZVf5+lKiIKwiYZNkp7NStXDMHQKNRvp+2imQcpUKFcFcVXgzc9QSsVxYpLglWfRFhdofuNvsrC4xsFDu1lzBOLgQ3TtKCJXZlg59RYM9rKyuEwQBKQO3c2bZ2bwK0Xuuu8o23uHCFbmaZ1+F+vALSj7BWrIQu0fQmZ7uPJH/xkneF+DGoiGDHoSIfSOTrxE6rpnQPFcnKnTyI9EMaqRCIrn4s1NczE5wYnlBkLTaQYKF5dLNJxNvranF9sTXKo5DKYjREyL0xVB53AHRm8/3vIiSjzJxuQtvDRTYmaqhGGajCQj7OxLcHG1hOu3C8eq/w3IZHvrKzSf/gtE48N+6799DO3qFOEHv/Er44RRVZViw/7U/T2pCOfWW5xbLtJyAya6U1zdrNNtmcwXG5RtgaWrBLUqVSRT63WGth0kurZJvVJFnHiFHUcfY226RMwyiKcSDHSmKL3+Mqunp+hIx2nZHkWh0XnPw7TePc5Q9xAuGiIcIbj1XvJqCHVtiub3/4h9j/8aG6EI9cI6/toGyvoG+1yH4d2HuNy5ncWNCvs7QtQ28/z42Rn8rkH2j3VR2MhTXliCvjRjmTBr5SYGEoRkpe7yN49MYsxcQITCaLNT1Ks1XFUnsn0X9R1HeOLUOkPZLpRIlLc2G4x09XL31x5BmBav0MUfX84TCMlkpsrduwfpTljUbI/uqMa7FxcpFirozTpSCtRUmlq6hz84tcmju1RmFn329mc4ONCB/8M/pyEVmr4kGtLRhY8UEm/3EZ6aqzMwECUR0giEoO5IarSzCZuuh6JoDKkKlZbPWtXmuUvr3Nkf5UD5Kv65E6gSprfdgmE3qW22o5ajI+P4Q9vaTnBdEl2cwxwcwwmFP2HkVBSFiAy4N+UjA0FRC3Ox3na2f4CmfMmT0C8ZJ5ogcvh2mm++wgfOaSklIp4k/sg3CYwQ4VQWNZ1F5rpo6iYq4PeNs/DCqzRbDmgqoJCOGHQlwyhjO3nhaomphU0UEUAQULBbXJwV/No9++i75W7qf/G/I1QDLROCaJzlgV2cPj2N2TeImenn8lqV4WyMzcwAXaqg0bSvFdaOR0MIAWoyhyIFHYkwZjRCxfFJREIIIRnOxWnaDqqmUaq1iFkm+/vTjGSjuIHA9QV1xyPwfb65PUO8sk6mpVDOdhH95m8TikR49dwK76w08ZUig9kYu/ozWKZG3RWoqooeT2Lkcrj5QjtTq9VAATwrhlBKqFK265fVq+ihMCBxfJdSzUKtFFEjUQIj1JYwU+C2nE7iyrs0Ts8jAgclnkIM76U/0stM9UOHhpDw6pVN+g8NkHvwGyz85CnW59vORtUwYHAny9lJxqRGCEFv3KAzHmKj5lzX9qoCt4/lCKkS/zP6S+xMJ+GvfQe5uowobqImUyi9g9jRxBdSw0xBkomGuLxRv8758uF+eG+xzLZUDu1LjKz/bxUpJWr0ozVCVM6s1bi07jI8OsDx6SZDXo2mF9DwA9IRg4IrCAvJyatL3JmYwLdtAtfFCocRtRr5wMeNWfR3dGOoAYrrYLs+/IP/Oy8stkjFQ1wqObTCEXwvoOn6pCNhXNfntvEOzs+tI3WDQDcRQjLaEedwRmVzdo71N97AjJ7G3HuEvfv2c2a1RkQIsokorygZbrrnASJT77GSLxHWFSZ6kpiTu1h49hnUjVVaQ6N03XI78z96isG+3ZxuCUbSOTwUolaI+/cN8+SpBVAUBpobuPlNenI5vnH7w0SaFfTRSdzNNe6+aYxwOMTb75xh1+gQR8YnqNk+O/YP0tvKoxaXsONZkkNDuH3DeBJkPI2WyuKXPllgvLHvDp68Wqfi11FUhbAV5oW5CudLDo9u78CQkqZ7Y2csElqujy+CdtbqF0RDGjx/boOVi5cwfJedeyY51nAJE2AWNtiwcozlomzvinFh+cMst7fniwxnw3TcwI9o0L4+qag4gULwsU6r/BzV1z6Qsv4szmCr1aD57PcRrQ8z/KTr0HrnDSK6gTq591cyK3uLLbbYYosttthii1+ML8UBc+bMmc9dA0YIwcsvv8xdd92Fpn0yCmhtbY2pqalPza75h//wH/Kbv/mb3Hzzzdi2zZ//+Z9z5MgRUqkU6+vr/OEf/iHd3d3s27fvc13fR5FSEjU//RYamoL2SzBKB0HArg4LTeng/FqVm/U61vpVXpuNsOmAIgImOmKcXq0xk2+wrSPeliVzg/byQoGeiM7jNw2xXnPY3pPk//38RQIh6IhbXFir4QmBoaq8O7PJ0VwPFy6cZXfwKn9tdJKyGmdguA/72SdpVKssNZuYyTQJr0L44nG++/DjvN4MoxsGnXaRSH2NRKMFnsTN5sCxUQ0NgoCEZRDUa6xvFDg6PsjK/CI06xBLoEVjmJrCXdu7MV78I8J7DuJnuri6kueKX0dUyrzyziYBKrc//lX+/I0rREM6V0M93HbnN+jEwcomeK2sslJTmdsoIxwbveaRiIUZ70qgopCLmvhBQC4eoba+Tl9PjvDyZboGexjoSmFulAl8D9ms43s+6d4ezm022Wh4hDWFSLnFYKSPex74CovHj6OqGqn9h7jSUvHtFko0zpsLFXr33EpiZZ6guEnjlWdQMzlS/8M/phpPoSqw/dGvUHjleQI/wNBUQhpo4TDWrffQ/NjCUCls4rou2uBo+35KgSgX8Yt5qjMzmF3zBPNl1O5+ajJ8LZL5tZkCtw+neX0mz3KlxWgmwkbNwSOOdet9yJefYW1oD98/tUjLE6Bq0NnHsYUq0fUmD23v5PxyibGOGFFNID5lTf6rgKqqOGffvs758gFBqYCYv/ors/CVUpL4lHodccsAReX1mTzmBxlHCtgtlw2h4wSSsKGhBB7B+8ZpBcmxmQLf2LkT5dJFukYGGZAbdLFCpLeDlbjOZIdK/vgG++64hXjEpNZyWZheoKBpTPz236Ps65RtnyVH5dK7y7i1Kod3DXPkq48gpqcYOHwTi0/OE0qniW3fRaSrEz8W4dLZizRX15ht2uixOJqmE67nmcvHuHn/BFe0AM1toapRvrO/F11TMXUVEQjCTpVEYZnSmy9jGDo12ydm6VTPnsZR44xndnIlXyWSsVCL81zY3GBiby+NH36P8TsfZDDRxVTe5r3VGos1h/vGc4h6lUxPgtnZZZqeIGlZ9HamGB/pw2s0sZUommGApvPeXIG1SpQHb7kb7dWfEI3GCFAJpEq8u4OTRge11SJXNta46dYDPC98PNGuPyVRUFWN7oRFTzzEcqXtUPMDwXBthennX2A8HCCjMS6v15isLUKrSezRb/Pqms3CmTWkBNPQePDWPQyJCBslH01R6IobJHWJgsTKr2G/9SrmzBIV2yOdSHDf4dt4O9bNar1t5N3ZHSMIfoU752dESIk3votYOod38SxBtYSW7cSY3E0zlUVIUHqHrjmrNMAu1Xjy7VluOXQrwVuvEc5m0KwIzXqTYPtulj2t7XzxPUSjjpSgGQauF/DK+SW+s7ML6buEclnqVoxIXz9n8zYyHKW8vkm6o4f7hxNMhn1MM0KHBXu39XL60hJCUajYAclMkrqV5P7hFLvtZYbkPGosgje5H1UEOLZDw3cx0OjIRaj60J8O88qVTcq2x0g2Sjps0h3UiVx+i7X33kFNR6mtlxg4cgsbe+9kxVWoN10MFXaP5Ti9kGe+1GLfYJYxw6Xp1ei8816UwjpLJ04gHIXuRISmaeIOTVJx2sWZYhpoQoFmA6OxSmi8A79agY01ukeHMLNZBkIQefMp6isrdHVEQYFmucL6Cz9h9+33UAiPUGl9mAHsC8lG3WWdOHN7HmBobwvVd2mZEU7YJutLTVwzzMGuEKbw+OrOTk6v1rm4VsMNBD0xgyNdFr1X3gK7SXhkgiDT8XNHjEspaVlRlNFJ1PEdeEK0n5EvKKNERzDe2X7XuhHJsEnDcXEFhP8bCFj4r0KuE8UKgxC0xveiRftImBlqVpSa4rFWc/juoUGev7TB3lyI0YEWLSeElUnz5lKFHSmdKSHaUqyBj6JAteHQzGY5mhVojUXm10uolTqeEeHO0QybTQ/HE2SGhqgsLNBwA3KREKFWnYf6w/z2ZBzbEzSjSS7OrvPO29P07unB8QT9j32H71/cZP3ZNxGmhYglWax7TA528tqaykOPTqCvbbArJtiYukjx3bPo9TK0mjRmrlJ1ymzfv5NI0gRahNIZejsS3B9P8czlDWw0BiwFf62KQGF5s8JrnTnu/u7/xLsXF8g3PIbWHfriBt8YjfPs4hKL5y8Q8mxuumU7Zj3PxXdPo0vBtsVpkuEIXvcAnqYTvv1+ms89eV1GmJrr4qzWQcN10Bo1ZLOBb1no4SjrFZgrO+zMmXTGQ5SaHxdybJONhQipIL+gKUeoOs9NFVhf20Q0GzjAxbMXuWmoj1gmS1cywnK5SVUxubBc+kTGzdXNBt0D0WtzoCEF2sXzRE6+w8riBlJRmBwYYvzg7bxUao8lmahJMqTAp7wOWp6Dsr5CsLGKEo2i9Q1hx9OInzGWKIqCXFm4zvnyUewz72ANb8M2frE6qltsscUWW2yxxRZb/OrxuRwwHy3K+VEajQZTU1PMzs7y9a9//XNd0NmzZ8nn89xzzz033P/iiy+SyWTYu3fvDfevrKxc0w1XVZWFhQVeeeUVGo3Gtc995zvf+VRZhc9CEARMdEY5s1y+4f7xjjgxTfDLsOdqwmdPzuBASKf6w+eo7z7KWl2w4ARcurDCbTv72d0VY3qzzt0THQxkwrwxU+TKZp2HdnSiovCXJ5dIREyqto+h60x2h/E8n70ZA01VqAqN1ZpDeGAQa/kqfssmcfFdrB0HqJ47xfLFK6iRKJ1Rk3iziF3IU2zaRIXCyL7biGRzFF/+MY7d4N57HuXJkwsoqo7W3U9XMsKGbGfoTJ06T7Pl8PXtA+wZTTJrZ6kuLZL2K9yUtuh66g/Qe/qQikIlluXd829AJIobzxAKx+hJhpnZrCNVDV/VWax5/HEtABR+uzPDXHmVnC7ZEQMnEaPoQrVQItOb5XBWpXd/D3/+1jSKcMkkdA7HPfr6QgSXz9Bd1UARRO75CsVMP1O2zvmKQAlZ3NSV4dxSgUUzTQvBSMcgPbdbBKrOueUSMxfnQQGjbxC/sMnGyCTJSBRpt1BjcWIPfp1GMoMMAgIJcngbnZkcwcIMol5F6+xF6R2gZUWuGYwURcEMfNRaGU0IhKZBJAqFDfx6DUXXafoSzXeRvo+9tECsbwRTU2mJgErLu1a42PUFTiBIRwwUJE0rivnI45w8tw65gLCu4yomy40AX0gqLY/Nukt3MszhgSQiaBvaNE1rS4kEwS9NKuXnwXBsvPnpT93vXbmANrHn09bbv1SklPQmTCxD+4TsT28qwomFMsmQ+kHwP7qikLB0ii0fH5WQIpGqihq2MAyDaDjE7p44/Z1pxvqy1F58iub0FNWCh2Pq9MSjDD/6MB2dEexXnmKz1cINRenZd4hSOM2PFx2mqi1iYZPWpbPIIAAkb78zxcDBfoYQVJoeg//jP6BUaXBmMc+GAyk1xy03Jzl+MYNTbYBrQ7OJHwiajocaChEaGCET1xhNxfnx+TWmVku4lRrZjjR/f0+C0to6mbFttCpVwkkFM5XkclVQeO8Mt391B3MFSalSJyQlCMFC3Sfu+zSe+QGP/9pf58+IMpKLMtkZ58JKiZX1OrsHc6CpBEgeuHk7g2sXqb9ynKbjUXBh4MB+chMHefXKBrOXpqncfyfxY8+AY9PEQAiBuuMgV4stGvk8KCqzU1f5H+8Y57+8u0DdCQibGhO5CP1xgyMjWS5tNujPJZjMhHBffY2c5mMvLmDdeg8dAwOkij5m9E5+OFtls9q8ZhOemBjmnZLgiddm6U5aINt1d24bzXEo5tF47kmk69IZD9FwA5xqFefFn3D4oa/ztJZgIB2mL24gv2QpzF82AdDMdqHd2YsmJUJRaAbBtT7x0bEnVNxgaqHExlqe9cledtxxJ9rls8hmkezoNoKBMa4sllCEQDQbBEISSIlsNVFUlfWaQyWcJDaxC8+2KVSb6JMpnMAiwCaTDPNoxkU7cxxjYwlVCrT+Ib5+36MMDvZyarlCDYPh/hzjCRPlhSdYya8xX2wSMjQOrs1y2+Sd/NHpKpWmA0iilslN23roiZk8M7VOwwnoTlgMdER57eoqitbPwUfH0VcvMjJu4CWzJJYvc9fgMKOZCGtVh1KgUmj6HBlM81Aoj/fi6xQ2CzghnfHBTvbfvI/C6ZOYw+OIwSGclVkMRcVTdS4WmzgCoopCWosT0yW7JwbwFIOZYovWZoPDnT6iUiAaaxsLm4GCVFRSkRD61Clue2gbzy0HeMGHo6qmqry3WGK14nEJnQ9fQ9vG3AurNXZ3htERWHgc7QuzvyeKGgSYZ48jX71KvXsI34wSunSeSCSCduA2GlJD1yQm4mc60aWUX4pDUgjBUMqiO2ExX7zewBrSVdJhnZipvy9794V//V8JnHCM6L1fYblQ58lz65Qiq8STMc4tbpBJhOlJRXl3vsjfH5JUjz9DdWmZvohJx0AvmdH9zLYU7tzZx+WNGpYVRRESLIuxoR4iZosnpiVdB3ext7ubu4olmmvz/Na2JBcKDudLCYYP7GMkCnuHcjjTl8m/8BLn1vMoKnT2drNj10FKmQSheonBBx7kzSsrrCzkabg+geriFSqE4zFmdIP7dvcxX3FYCqKYrzyNV9jEUiWq7yFCFij8/9n7r2BJzjNNE3x+16H10Tq1FkgkMqG1IihAVSx2bU2z1tpaba/t9Oyu2Vjb3uzFXszN2ozZbttsW/d01bSqYpFV1NAgVAKJRGqdJ4/W54SWrv+9iGQSIBIgi80qAtXnuQv3CA+PiN893P/3+96XoNNBug6LrsYD23p4Ync/C+tVwjBkYa2G0HU8Q0MIgRBgJJJcbimkKx6Xp5bxAslaOyCIxHhmIsHj4wY/en8dN5WjEc9TPHWSestBFVB3QiJXL6ANjOKHIZ1MnsiXvoVcmiPYWENJprEn9jB1oYg/d7Nr+QuItobvr6L19HNlNcKuXI4DA0lurjcJfuUaTxFw11AaGfzuOrzKjmSl3oFa9fYy1/WZnJwD5vjS43dz8dR5tPHtSPXjt7Xuh1rlFEVBnbxK+72fowtBPm6y0XRozs9iVMocfex5LtqCB7cU0KV/x8M02mnSefEHBI1f7g/KCaL3PYY7vuNTRRhFUQjWPzlrKmy3EI4N/w0LMGnp8GD64+fntHTu8OxNNtlkk0022WSTzw+/lQDz3e9+947LY7EYvb29/KN/9I947LHHfqsdOnDgAH/xF3/xieu//e1v8+1vf/sT13/4tYZh8K/+1b/6rfbjN6VgwfGJHO9Nlz5yoZ6NGdwzmiL8LcJW/6u4cQnD6+BYMZbtOh2n+/7VZocDY73ctzVPueXxk0srHBnJ8OzuXi4s1zizUCUbN5G+T8f1KDdtxq0ArbZOvdrADSWpRJzkwACpngJX6jZrTYehXJJ43xaaP/kuoezaJkQ6VYJ2i0bLQRGCcGWB3mMK9kt/jtcK0S2DzDs/5pu77mLNylBRINqbwTB6ee/0NRodj1AqKHaLu9xVDqwu0PIdrPU1wtfPIcOQ9rXzJL7ybRQgnojSNzKIVuhleW4ZqQl0TUXVNNpeiB1INFWwsyfG40aFTKzNB6ev4fgBWizO4OAQid4sh/vjKGuL7OlUcSbyvD9TYiziMTh9hvr50/SmYyjzq9i6RvXeL3DV6GGu4jBbbrNQ6QbVP7WrF0WoXFkuY5Tg6OgBrv3sBaTvoyRTqJkcYaeN0DQ8TSf+pT/A31hH33sQJ9+P/6FJoVBK2ok0yr4jCCHwf6VaV5ch6twUzvlTKD19BLOTqJkcSjKNXykhBCAliqbiRxNoKRUhAddmIJ1gptS+bSOjKuKWhzvsG0jenpyqSY0FG4JblmdRBIO6pNx2CUJoOD5/dLgfI3QQikbQaFLd2MALJFo2h5nJYuF+hoSYX7cfn5X9hIQa8MzuPl64ukrnQ3YfyYhBzFDhQ/YeS+UmD23v5adXVgh9H+m5eEYUOwx5Zlsfg2ED7+wbyB0jNN59jaC4TqR3gMN9w9RDBbvTofaX/57o9j20HJu2GxDLRYlp0DOQRkehpyfL6cuzaJoKhBBKZOhzuewxuDFP/vA9XF6p8dLpKbx2C6mb2DOrKJEYzz51nA8W6zRdD7dj43s+nu1Qbzu8t1BDDKe4PLWEF4QIz0MTktpGifJCgzgqtmWx6miYukqg6aB2UEVI0m1BGOIKUBUV6TZJRYzuuFZUklGDrG1wbql7jktHNe7dNYQqwMrk+PbuPkYvvE7z7PsErkdM10nlCigLk5iNBgMD+5lRVGYWN7j3S3+Id/EM8WYD14wSvedBOu9M4UuQYcjM3Aq1WpPv3LWHsh3gOB67oiGJjTmqH1yB/A7+eqrJw2MpHt19N+lmic7+b/CuE+H92TpfGh8hOhpjS7nDYLvD7MwSnufjx1KcmyqhxBNkQzAEBKHk7akivcM6Oa97jjdEyEQuSrXTzf9Rrpzm+S98k5HBHjrV0mdoZP9uCYKAT5tK1wV4Ny6zEeTZN5one+U9phfmkZ0W0g8Q12fIzMwgjn0JgoAwlN3xc6vLUAY+gR8QhOB1OgTrKwxu2UOl1iDZa3Ldl3x1Zw+pt3+IWFnAqVYIgwC5tgBrM+z70h+z0JODeoe7+hPUfvp9ijduMJBLIpFMpE0WL18lsrjBv/jKH3FioY7tBYykI7itFv16km09cQ4MpDk5V+b96SLDRkC4tMGKk6e39zDb44Joq0pMhByMBWRUwc7+Hv7q4iopxechs0btlZ8QBgEdz0doGivFGlbnMr3PfoVmtUblu3/G/TuP8u7Ndcx0hkd3jOILFdcPGLUkr711jnsePMr/+sYNOi2be/cMESsvEEifqKZQ63g03JCG7aMoAsNtkOi02DNY4PpK9XZGXSqqfWRC9Fdxg/Aj9l1hGBJRQL/8AXXX58rgYS4uVuh06iQLPewZHaN2s8yNmktE19g/lGJnzvpbz977JDTf5qmdPSxWO5RbXVEpHdFJWhoaIYdH0mi3exM3+VXCMKTZM8Jry8s46ZCIhHw2jayU2dab4rtnF/kfdhpc+S/fI6KEGALK9RaZtRWal66y48t/yG7F5agmmS06SMOkb8sAs0sbvL5WwxMKazeXOT9X5MsHh+l78X/H69jszPSxf99R3MHtlKwYZnUNzrxJAh8zn6TuBNilIuHLP+Rbf/wnrJ58l+C+h+gsNchkXdqrJVQhUDQFSwQciLr0VBbZoiu0+hVWLiuomoIEWkYcJwgRUjJgmGgy5FobxjMGr91YZ2OlyJ6do8TjEWq2T9WDgmGiKwKj0MP8Wg2/r7drkaUIZDROq9nh53Pw/NYEvYfv4ubsKl61Qnl1AwQIRdD2AmrVJjlu5aBISceMIrbsRtm2l0BK/FDB31i5Lb58GH99BdGXRwJ5U/L0nj7evFmkYXePtZipcf9Env4od+wcEUKgh0G3y9Aw8X7Dg6Dj/WJjd36B0+mQTsZo3lqviG72WSi7WV9b8vHboqzh2tjn3+/uj5QUYjpRQ6XUcvE7LcbdMrsO34PlNQjv4COoKwL3vTc+Kr4AhCHtd14lnu+lHU994meRUiLiiU9cLzS9m2/23zCK06H04o8/trz361/7PezNJptssskmm2yyye+O3+oq78///M9/1/vxuUWEAQd7LEbSQ0yVWtheyEgmQn9Cx/w7ngBQZYi/PA+AlkjiOCW2D2TYNpABVWexZjNhmvz1+SUyMYOXr6+jKPD988uEYUg2arAtH6UQ1diZUmjPTmMo4HjdKjCvWieuCfKH9tPbV2BjvYSXzHC52GYsEkWJxcjoEG5U8VCwdA1NVZCmCWFIc3qaoa3bKPoKstPCf/H75E2T8e17sHofYe7N9zg2sAV1YBBDkQzEBWpo0F6YQQ8CZLOCoihda59IBPv6FYydd9F/6DDv3lzDbdbIWUnuGkrR15vEvFHCdXx0VUFVBP/9uKT8r/8ndo5vpf/QUT5YadLquBT8GvccGeOd9y9RTAn0l/8DB3buY8ujX8NolGneXKKQ0lGL84Tb9jFz5Gl+dMNmvjWLiMXY1ZdiW0+C166v8eKVVb51ZISbxQa2H+J7Pmo2j/R9pOsQNmqo6SxBvUZPawN/fR59/924+T78T/CbvlM1r6IoKJfP0f7gBCAJsnnUXIFwZRElDJHNOvgeSiJNftcuTq3W8ebmkEKgpbLkB8exkxH2FSzu1htsy1RRdZ3hrb2kIuK2lZiCRFMU3Ft30wqSuAaJdLc6Lx/VsISPEIL25YtMv/oK3q0cGj0SJX38QRIHDhFTfv9+975pER0ah+LGHdfrW3bgCeUjwsbvkzAMGYwqfOvQABstn44XkI7oRA2NM3NFPlRUTs32SEc0/um9Y/zs3DzrrkXE1Njdk2dAtij/9Z+TUALQDSitoRkGXrtNuLqAnxkkJTyCcgk9FsMLJfFtO0jls3TeehH/hIbRN07CSPLk3sO8I9PU1299h5pG3Q1pm3Gk7fO99+dwXI+IHqHh+BzaM45rxfnLM/OolkVEhBzujaFUNugNW4wVK9wznmQhpvDC1SaRiEnU0Kg1fBRAKirllkMhqhMzNZZqNutNB4FgIGWhxiwcxSMe05CVDooM6XdKmJGQzgPP8ddX1qgn+2na3Xypaltjvdzg//7IVh7YXmBL8Sblk2+BqoIE3/NhY42ULig32hw9cpxE/70UYiqN1z4AzUDc/RCd/gnavkYhabFRbuAEIY4fUul4fHDiDHqzzj37x+mbvMTF63N4gWTbzir/+J4nsaXKyY2A8Uf+DwStBsVrN9mxbQs3dJOp+SqXbq5RSFoc3rGdsZTJT65toOgGhCF+KDFuuS1JJBfmijyRK+AX1wHQRUhPTCUf01DCJjHNJR0x6FT/Tofu3ypS0Sg70HR9LE0ha6kY+HcUeRVFQXVtnLVlsiODRFtl6rMziMBH+t2TnECiNusMqS6nozHcWg2hm1j5fDcrLQzoGRshl4rhZ7LIZJbJmkdtY4GtWw+zNpClb30aZ+oaoeN0J9gQ6L5D6/J50uPvoQ49yKlrCzw/EaW5OkcuESEeMRjLKyQiKssrNmFjAfP9N2mEBTzX59xNh4btMdyboeP4TBabXFiuYSiCpGXRPzjEiivpsW2Gm/OsvfUGpTBk3YzSN9hL8sEnsB2PobgGV97HVAXljk/CMhCejd90sds25oX3qdQd6jPTDFgmX7//MSY9k3fmKlQChXzcImuY5CYmePPiHE9vL6BHI6wXK1TbDq1ilXzMIIWHGkkhLZ1iy6HYckm1fVZ8l0OjeU7cXGOiECOtw0g2Qql152rm/rSFqX7Uvkj3HDqNJm/aKW4sLnd/N91g2tV5++c3eHzfMBFDo9p2eXNyg41GkofGEyi/J0/MPjPgmwf6eXOqeKuDUaIKyaHhLNvSBlL+/v8PP8uUOwFrbR9i3ZxHieSx7QXema0wnolgTV/ADnwaXogKRFWwHRdNSjJzl6lU63RuXGfQMIg/9BT/+YV3MAkx+gcRa6vIaJQwCHnhjbN8tXcE/51XyArBzR99j8jAIHv+0f+J6olTrJda2H6AKgS5mIml6CQ8hcjkWYJ7H+cHC00urrn0JAocvW+MqWtTeLbDM2Mx2q9+l5Kh4yghlq4ykitQTIwzf2Max+v+/tmoQc0JqLoa908UkDLkP5+cJmaobNQ7GKrCeC6GlJAYGETfWKIuFVQBpgKFngzbRwpkdIFfcwljFkY6g16rk9JBrMx37RiBiK4RNVS8bA8bgUHSkAjfvVV488uOsKTbYjiuca18599me0JBQRLIkPGEwsDBPqpOtzgoZalEREB4h+POkAHK/DTuxbOEnRZqMk1k/xG8/mH8XyPERDQVGUrUVIaw1fzY+rjb5L7dw7xUUjiQ0RlyK5huG7cwyEpgsN5yMVSTvCUQnSpE43Qm9hEqGlazTGJxioSuEAKRxhr5XIyVlfod90Vr1Ggtzd95R8OQYHkOsePAJxYdhWGINrIFzp/iTvYIxvg23Gjijus22WSTTTbZZJNNNvl88992mc3vCCEDcjoUBiK3rZf4PVRfSqEgjO7EeFTAM0e38c5Ukcmqx9Zei6V6i7ZfY7Fms95y6UuYWJqKpasoQsX1Ajw/JGMq7I5JzrkemqFCGCIQqJrCPSMprr11gsE//Ido12+gux1WfYO9d99H5uc/JCldAhESIlBVlY4bkNi+D7fRIATsZhsiSWw0/FCitDu0SkVqTZfol/8BmYVJzPnrhIpOe+Q4jcVFFoodFCGIRrL0bO0lXlmFThvfirHWDpmcWkBRInT8kOsrTZZaPv9yYohnd/fw3dOLgGR3bxrj6ik67Rb61GWik1d4bHQLMhqHm+tYa2fYfdcTqM0SDTckefU8qaFRQinwOnWUZhWZyXNp/Chvz7eZbYT4KPiaxUvX1jkynObgUIYLSzXW6jZD2TiZqMFATOVmcY2wYyNMEy3fgzc/w8TEEPmlGwQbS9hrK0QO3YO69wgB3RtVrVHvepibJm40gf+hmzlFCGK1En61SHRsAmFFcaslonffj/3Oa4S1MkJRCD0fc99dCEOjX0qmEHiBhFaLxtRNvnBsL3eVL1I/dZlsKDE1hcT0exj3PIg3tp0AiCghO3rjnF2ofnSs3aoM3NufIPB9tLUVbvz0Jx+56fQ6bTZefxE1mSKybQIl/P1OOgVhiLn/LpTrlz7mv60mMyhj2z8T+S8fJgxDIoSMxAAUIECogolCnMm1j+YMZIRH5NRrPLLzbk7MVmi2W7xztcZ/1+PQ8WwySZNOu40SiaO2GyhCQQtChgcFsuHiezYi8MmNDGOOjVD9yfe6G7YiWJpCs95AefWn3PeFr/Gz5e4kqH9LCDEnDjFvFehkOogwpNOosmOolzlX49zNZaSiMDzYy9TCCnYtznN9gug7r1NemQWhEN9+gO/se5g/m/MY7UmTwuueLxIZUsk4lY7Hct2h5XaFmaihsWpDOp5lIFknZil4dodH94+ROPMCge8y1YaKHbAStmg5IQiBoQiimsrrl+b5hxMmRrOCpuuEEhQNdFXBUgV2sUh6ZDvVcpXvzdbZlrXYufUR7h3PoicSTDY0LM9m30CGxWKTjVoLBYglYgQLM8RiESZosrCwguOH3TyRpVlSrTL/y/k2BQPOrduUiyWev2c/ZdvjxxfmGc4lIJ6g7Hq8MlniiQNjFApZNpYqKM0GWj4Gt4VaQc0Nu1Y2H6IrAEiEbhDeCgj++0JH6Lx6vcRCuX27FjoTNXh6Vw9Z/ZeWh0YYolU28FcWEYpCZGwrO3viLL7+PkJVbx//VsQk01OgIxWii5Ns3b2X656Pbpr4ywtIBYx4nHuCdbzXf47//J+wuFLCKq4Rn7lG6tq7/NGzX0f88CRt2wYEmqoS0W+F20tJ59z7PHzoYU6lY2B3yMRMZkoBqyt1oqaGgkFvT5b1YoWw3cTXs3iuQ9PxUERXXB3KRHl/rkIoJW4ALS8kSKdRKxX2NuaYv3CKlKHTajbRogqLC6tMvPpjvn70C6x4KsbNBo7vkYia0Gri+z7xaAIZCuyrF1HG92BETDTP5uZqmXenSqiGQV82z8X5IkurCjsGM2wvpHFUjQ/O38RZXmTn4WE6jk/blwz3pAmDkHLDoeWFJAcHebeqcmJ5iW8fGeaxnb2Mpw3wXfb0Jri62viYvaKmiDvaF4kgoJwe5MYHc7eXefE0a7VudsWJqXW+enw7ji/xJXhhyIaj0mvC7yOYTIYB21KCwYP9lDo+gZRkIhoprds1uMmn4wYfnbxeq7V5YPsAP7m8wqGcgXtzCSG6Z8KAblZT1QkZyidhcQazbwxMi1BR2BAWqiJQpCRsNREClGgcd2memutSHx8hIkMob5BJ9BD29jO7sEZrZpHAC+h4AZoqWK3bTOSjRDyf1aU1plMVSsUGDVtho1rm2kqVLx/Yyla3SPXH30WGIamBXjqujwgDjBsX6Tl4jAUzguI3yUQNYobCYqXD0GO7OHtzmb2jBeKWwWKpSW+qgyJgqtjC1BR6+qKouT4IFP7o7mG2uiXu35XFOfkabgB1T+KHkujEKA8de4IV3Wb5tbcQAmKGRiZqMFN1CdPj/OyNafoSBl/e10/B5KPdYp02h/M6s2sGtvPRjJd0MspWy7t9ng3DEJ2QgnHrCfKj3Wu/QBPA2ZO0L529vSzstPFe/hHRex8m3Lb3U6+9spagL2WxHgaISBT5oeu3kcE8w5qHWciwtddg+e03aDY7XO3byenzZzE1BaPQy8l0jq09Ce4dyfNedDs3r5Xw/YBMKsaxXQ8ytnQJsbGMiMY+fXD63qcW6ch2q5vz8ild304qS+y+x2ideA0+1PWu9fShHTpG5zN2HbrJJptssskmm2yyye+G30iAKRaLv9XG8/n8b/W6zyu/78nbQEqsXfvxHZubDY+3bpapOiFb+02+e2YRVVW4eySLqSl0vICZUpt7RgN0Rbk1sSkxdZWM8NkVs8nsGWK62ESpt+nPxNnfH6d16m0qno959EH+ys7Sajs8vCWHaDTQYzGCYo3Q7mDEkjTcAH1whFosi+4EBIqK0FQ2mi6ZmIUiJUKGGJEIzViaPz+9TNaDwfxB9g9l+PGbl3gs2Q2el45Dp20z12gy2tNDMtam0rIpV+oYhkGfIknF4vj5JC0fXri6xrcOD1KIRzgzX+JAXxzt5WlSlo4XhgSuD1PX8X0fQolIJRl6Ig433sdWNfxUCoGgEQiW1ST9I2mCg/dy+sI6Yc8IEp9QSgxVoClweqHKNw8PcX6phu2HhAK298QpmILnnr6Xk4sN6p7EaNXZtXuYfbVZeOdn+Nk8ar4X+/wpYuPbELrJUt1lxVbxAkEsbNNrtMj357EVFRXQp67SevNFvKnr3R9e1YgcOorX6SDiCSIHjqCkc8hOG395ntaf/2/s33c3+UOPcKHsUlcs+rIJ7rfnuXLqDHXbY2dvgrSpELoO7bdfJZ7O0k7nCcOQgwMJ5srt23Yqv2BbT5zhhIYuAqqn37/zDaeUtC6cJj6x5TMROqz3DxF99uv41y7gzU+DUNAntqNu30PHjPy+d+83QgY+942mqbRcis1fVpHnsYku3MDauZed+SjTFUEuqTAglumkLKotm5RuEUqBcB2E52FmC8hWg6DTBruDkCFKtoA3eRkjkcAPJb5QUXWdAA8F0Oauk8+n2Sg30CMRtuzexncvLZI32kxvtBACcok0hZEhXnrnJqoiEIoAGdKbshAbK5xqa3xleJT29DUUQ4dqGfHOizxw9DmWfUG0UcT1Q05cbvIPH3+G+R//AClDopqg4wY4gaT/qaf5izmHZw4MsVKsc+xbzxEtLuGPbMMKXObbkiCdpVF0MFSFaNSgEDNIWhqeCkargmUZxMzu36AQCm3HxXYCxOAY8+Umig8FQ6K0m1xcqTKnJjk+ofLG5Dq2JzkSk3z54YNcn1piZqWIYemM7RrjYBpik+cpNR00RWCoKmEoaa1v4AYRFMOi6vpIRaXmhVxcbSJ8Dz8IaYUCFIOIpvL2bJlndvfx/myJvngM024i4wmQXaGlf7AX5eq5O+YWmTv24H1OxvRvglA13pisMP8r2RqVtsuPLq3yBwf7MfGwfA//3ddozt7svk4I1EqR2KFjDCZNWorAk5JEOoGjmczVXVqOh/LWCQ788+MMJQ9y7v3zeNk0/fkUhzMKkclzXJ1bJma8w8uFwwRhL/c/sJ1ccwlK60R9GwwFFAUlDPHtNvJWi5oMQ9KGwj97fBdt22WpGUAQENFVvFDScH0c26U/l8brGyRYcXH9EENVCIB4Io7btnGDEBCEQNzSKbc97u+NUn/9PIaiIS2TULVQkFjCwwxd9ooq9SCGYpiEQkWTIbYfoGsqcSVE8QNCw0CVEkIJOw9w8sY6TrMrbFi6gWlEEIHLpaUqj+4e5McfTCGLawhF5dSGx8NPPsfK668wX/dIRbq2P6l0Av+uB7i+7JGK6JycLfPolgmMWx7+aT3gy/v7eXemzGKlm3fUl4pw73iWHvPjuXmhFWVDGh9Z5ikaQdD9TwpVHU3X+f6Fedq37BpPL1R5YCLDseE4+t8wDVyoGnUPvFASURViavA3vr6TUhIRHkPRXyzxPyvNlZ954ma3azm4NZsfSig22uzsS4L00S0TG0nUUNEUhabro0UMhGUR1QSeroFuYhrd48LQNTDjSMcmEAqagNDtjp1ufxL4nTbJgs76wAQr5Sb9sSgblQpBILsanoS5kiTel6OJgdu20QKPnkSSedcjCOHqepO7xRpVz8OKx9AUQSuERtMmli+gTl5k377DlCYnKTZdFio2uSN381Yrwly5xnOHxzm2pcBKIclCucXD23t4b7aCqSlMrZQxgoD/6wPDRN/+CUoqTf3MOzhmjJVqm9CKYIcKrck5hs13GN5/FD+fIdXXQ3RgCKlp+JEs/3pWkjAlF5fruH7IveMZDvZG0G51ZclIjOzMBb62Zz9nSx5zGw0MQ2ciH2Nf1Ccl/NsCwW+a92fUKzQvn7/DGol94QP0sR3YmtnNRrpDdowSejy5o8AL16DECLJeJaxVOL69jyOyhDx1koYfoLRqDA1vYf7oA1x68zIRTQASf2MVPRJFVVP86blVlHrXVhKgUmvxwvkWTx/Yy3ijijq65SPvLYQgEBrtoFsCE4kmUKwIod2542dVC/24v+ZcEUiJM7adWKEPubrUzYEs9BHmeujcIcNmk0022WSTTTbZZJO/H/xGV3r//J//899q45tWZX+3SCkJBkboSJMPTt1E6BniikrU1Gm5AaoiSUZ0NEUgAEURVDvdCRJTg28NqQw0ZrHOLZFTAo7m+9nTo1A0Q8LSTYoX5gmCkFR/P55QmVmv02h7/LNxwY2f/pTxHVsYOHAELn+A1E283CAVVzJ16hzZoX7G9x2iWqyAUHBDH4EkMTTESmaQNxc7LC7W0GQDb66Fox+lmijQjLcI/AAjkQSng9B01l2JFQYEo2PMeAZK2CbQotiNBnVf0NFMLMvgwnwZFMHju/oxFYmZSuMiEaKrBPhhiKqqIELMeJyUoeBGDFJ//I9pGTEW0EkSYE1Osub7SCOJp9XQCTFMnSDoVhymIgZ126N1y+5sPBdjR2+CWq1Bijb+uZM8sv0AWjxBrNIiUS/hLd5Eu/8xJODOz6BIcG2Xn6+G/ODMAu1b2T39mRgPb8kyJquMjfZgbCzTfOc1NO9DFYuBj3PqbSL3PIg9PYlz6Syp7/wLZODTef9tkBJ59Sy5lSUe3XOIopYg4eaxT7xB0kgDEtcPUC3RjZeRYTeQ/tgjBEFABI/n9/UyX3W5sdFEUwS7+xL0x1Q06aP6Pnal8onj0quUEJ7bDa/4DNCJJRFHHsA4cBSJIDBM3L+FQOa/LYQQpEObb26JstyJsNIOMSMmO/U2fkRlo17j8vllMuk4hqbSiUvKSysokSjFqRlG9hzAf+cVhCKQQdAVX1QNa9tO3PkZtEye5sI8igChqJi6ihSSiXycck0QbKyRHB9BS2U4dngHL757hZJi0W9o6KrADUKCMGC24aNqKmEQYBoGCV0Qjar4aw0q1Q7tvT1oCriuR1x4ePUaO9Q2S34adXCUaLuJ0+5wMz6I9cw3iM9NopTXyed7aQ+M88Oigm3bEIYoYcAb715iabVEf3aIZ+/ZRrQC0Y7KoSTgdFADn3K7xfxKnXQyRjWjUy81MBNJ5NI8IvSJxZL4hQLzHZ9ItoeSFSddnoRCH83BrVyaraCpKr4XoKkq122Nqbeu8g8O9nEsniDWU0A79RrB3AZB/yj7jw8zc/Y8cQLWWh0ipo6hClpeiKVriHiCQCgU2wGxRIzVus1QOsJitYMfhqzVPaKGhqUp9KYiyI0FlFicENE9Dkfy6O0t+JUyH/bH14dGUXYewJEKjv/5GdufRtWBhXILTRH4v1Jm3XR81lo+YwkFOXUN9xfiiwSlUiR0bNpvvEDyyS+xJXYNJ5qhpphUGw4IiQh8EuPjvDRZ5Hljgx3RMp7mEi1O0Z6qM72w3s0TOPsB+768nzfnS3xvcoovHBolOnmFw7v20z79bve/xTAQEjRNRRhR0o9/AZanybsBPwt62X/sPso/fxkhfRRN7f5qiopIpKnF89jOItat5VZPL+suLNVsRrNRLizXiRlqt8pcQlqXOK5HOhmh1HFpugGKgJhhEfgB/sXT9B98jNjeA9Refw1dEaSyKQYsgb+ygJFKom7bjZyeJvADqkqEMKiDonQtcFQVU1Gh46AlI5Q7HoYIafsBiq6zrMT5z7WAJ57+OrHSIvGwQ8vMUiqM8VpZ4IcuAokioNz2SMVVtFv2mIORKF/clafhdj9MTAcR+Hd03nHDEDOXB3Hzdgba7X8TIYjGYyxW2rfFF7pfDxcWq6QjOgcKxse2+Ul00HnrZoWZYosglFi6ysGhNPs/NEm9yd8uKR129Ca5slK7vWym2GBrPsqllQaZA4dRKy9BGGCKgL6MRSJidifLdxzg+jsfYEiBbLYwnA41xycR1UDR8F0bA9AUBaEK4s4tSytFQYnHWO34LNoefdv24M0tcCtKD1VR8D2Pphsijh5nbtFBz+ZJlUoM5RKs1zr4QYjSKpKMRyjkk3Qcl8D3UawIM82QghUjNr6DVs1B7deJj2zn5abF9HKL48NZgkaN2WKTd2Yr7B/KEtE17t+SZTxt4bVT9MR08qdeZGllneFUkpYZYanc7Ob4dVokEykIQ2bPX2LiwD2k/uBPMOtF2tOTyEaNvhH4Hw+P8+8mO1TaMLnR5MBgiqWmz+itxg9pWsT334W5OMez2Qy1VBTDcxCL5xCaRrj7eRAqJVcwudKi3vEYTEcYy1jElTtbQYaljTt2jYTDW5jNTnDh4gY1NFIRnSPDaQbjCuJXOtfiwuP53XlKTo6ON0TOVMheeBPnynmklKiBj7+yBChciO1Ei0Q/0umsthu4QR+Ta0225foQnRbS6QrCEnh3psSWh5/DTWZvv0YoKostyYmZdTYaDqoi2DOQ4qF9dxOeevNjn0dNZZC9A7/RGA+5dS26NYUQ4vdewPd5wNAUHkzfwd6Ov71O3096z0ToANbHX7DJJptssskmm2zyKfxGAsw//af/9G97Pzb5HeEqGpXsIDLnkHF8KqGCH4RdWw4/ZLnaYWdPnJurVYTvMjm/zpfuGidbnMP7+Y9YbrTQQp9ELIT33yT+4FNM35jFrddQhCBAkDh8FC1qIVWdsd4Yq6dPMpaL0Vha5NLSMnseeYjmzBQXzl3DsR1CoVBeXmP4D76JOzWFd/4MqmFhbtlOuPsQ86mtnLlSQiCRQpBMxJhcLFIJNU4UA556+EnsU2/jtdoosThtx0bdtQ312KPMv3AS2/bJDg1QSMToHewjTKRZa3lEoybfO7dEzKzywNYcu+57DBFLIIOAtBA0b1zFWV0mYmlkj99PsDqPdByu/sVf0LYdIr19JL74FUS+h9j6Mq7Txm/UUV2HvuFtzHUU2n4IQhI3NLJRnXvGMmRjOvW2yzPZkFK5yanYdiZPLWKqCjt64xwbGqV3v0/7xb9G6AbG9j1o41s5ZUf4/plpHOeX4spKpcUPL7p8aXeBAS+EKxcAiTRMhGEgXRdEd4LAuXgGbdtOnCsX8NeXEWYEfct2wnIRdAMvVWB2pYIXlkhmUgSdNkoki0Di36qu/sUkblgt3xaqAEzpsT2tsCuXAeh2Dt2ajApUlXgmCat3zlaxkmkMU7/9/M8CYRjiqHr3we9IfFEUpVtJLugGs39CRahUNCoutN2AiK6QMcVvbM+mKApWaa1rNVcp0qeqDKYymHsOoW/dgbz/MYRUicejlKvdiaX1ZJ5YJovv+zTmZ1EeuIfI0QdwZ24Q6iZtLyC6ZSuRfQco/pv/mfiBI1iZNP7aMphRRKKAPXOTdMQiPzAMY+P0DmVQV+a5urrOhhqlFqrMVNoc3drL29dXQApcP0AYJoprk0wlcAKIAMJ3Eb/4ajwfTdMIm00GUj0I6WCtzdPcKBIxVAq5NLmoxl/N6tTlCCLeR6PqUV9ZJwhBicVZrbTImCq7dg5zbDiBpmvMdmBosMCPX76EYlrkUzEEBpV2E6wou8Z6WbdLBJevMHHPo2hv/IRgdRHRqKJke0A1id33KO/cWIRIlJbt0NYDmrbLdKlFRBVMV10GkhZOvIeLfoQnwjX8H/wH/JV5wiDAv34FxYyw5b6n2LhyGakpLPoGcTxcX2EkE+XaWh0Q2EGIqSq4YcBqrcPWfBzPD3D9kGxE4w8ODXB6ag2hqoAgYek8vC1P2pQEe48QH5kgWJpDej7q4AjFWA+vTjWodWr0ZFrszlsMxVXE59T+SBGCRLvC08o6Mgjws3mu+xFm6r88V9ZsDz0C7rULt5epThtvY7W7jXgchEI0l0Vptpgv25jxBIPbtmHoKvrgCJ4UrE4uM7J4A8OzEaFPsR12J8eEIGg3ySgBTqWKH4ScXazyiCpQJ7Zj7dqPc+0iigxxQ4E0dJJH78cvb9C+conmvuPMX76O0pNg/70PUH3vLdx6Damo5PfsRx57mFrFIZeKU+14DGwZ44ED47y30GBvf4Kt+QRCgO0FNJ2AwaSBq0usWBRNFdRtH2RIADgKOGqEaCZP3G0gx3cwUiniTt/AaTZoupBJZ9B27CVA4K4sMtE/RFFTCKVEV1UCRYFYEqXlI5MZ0nGTiK7hCA2haujJFEsNh2bHZbYi2DG+mwODSX56fpG1aoehdISOF6AIQdxQUZt11HdfRyoCInGcchFzx17U8e34Qum2InwK+XwSc3gMd20F6dgYvoMRsVCsCIauUu/8ciwIIKorgOTcQpUd+b7faJx5QucnlzdYb9i3l9lewHszJfwwy7HBCOHnSKz/vCIDn/vGkhiq4PJKHS8IcbyQ4bRFVFNZcTQGRoYRizPYqDiOi3RslImdBH3b0LSzVOoehlApLEyxY3ic2fUqkUKBYGkJz3UxUkkODqawzvwMW0r0ZJqWF5KNR7jcMflALXD3/n10rl/uTu8KgR+EpPYf4oJRYGPxFJn+XsxUhozdIZ7UyUR1kok+1I0V1mptLCUkaDRRklnqXkg8m+Gck+DN9BE6rs/S9Q7QpJC02BKH1kt/xSNmlH17jvL/vVJlqtTinz8wwY2VKmeuLfD0oE7p7GWGezJEdJUVD1Qk0g8QAqTTQQYhiqZTb7QxWh3mv/8XdFwf2wuQZy4w2pvmX3zxq/y/rmrUHR8vkFxebbB1Zxa9vI79zqs466uIRo2wWSe++wBG7wBOTx/aoeN0jAhXSx4/v7F+W/K/udHkfV3lS/v7yet36IYRdyi+KfRxJjrKqQsLaMPjBFaUluPzo2qHB7cV2JfXPyZKqNKnxwAMiLQqtK5dvC3IIoEgIDQj1DaKKFb6IwJM3FBZqHa6Xb2Kgjk0DnYH2WmBqtGKxaln+0l+6ES01Jb86OLybVu1IJRcWKwi8kM8dPeD+BdPdTthFAVjaBTj6IO0td9c7AVuZ/Bs8usRjkPpxR9/bPnI81/6O3/P/m98DaxNAWaTTTbZZJNNNvmb8RsJMA8//PDf8m5s8rskFIIgGqPoewRCko7qWJpKNmaQjqgcGcpRGYjy2uVFSo0WWbvClpsnWdfBiJlEhYYe1xFOi/LrLzD+8HNcPXmazPgE1l3HKSV7SRdL/PeHs9h6DPM1n7YbYGkKwg9pr63gH3mIbKyPoFJCpLPUCyP8z/MC3dzBvU9uJzMSQzZq/GzR4eKFaQZT2a638+wKfipCxFCxyx3qUYtXizYPPvMN4iuzBHYHJZ1D3zpKZ3aJuK7x1L5hrOISkdo8pcY0zdHdnOvEubFaY/9gBsf32d1Z4frrLzC4fhNvZRGp6cTuvh8tnUWoAmXXQRr/9v/NamjSbLZQFAXb8bj8ve+z9/nnWZucIic8coUM7UBgGgIZjTFTdajYAYalMJiOMJ6LoQi4J+5TubnGf7xUptluoyCwFbg622ZuZolvP36QSONPkYqC/cHb+P3jvLvU+oj4AoCq0paCUqjRaDvk6t1Ok0BRUHsH8Zfn8LyQIASr1USPJjDue5zalcuYMsAYHMa9ehG1t59yoODdmoC1Ox3iQ2N0al0bjripIT9Uoajmewl+5aZQStkVXn4FXyikDtxFdGqOtvvx9b13H0VX5O9K5/jMIYTAsluE0zfwZm6AEJjb98LIBLZufuS5bboZFosfyrDoT0V4YkeeuPj1uVFms0brpR8g3VvWY0GAOTyGVq/g/On/h7DVJDI4wj84+hD/6fQ89VqTM4tVHn/uD9DffIF4S9D++YuYhV7i3/wOnhWnOLuEXVyl8aMfkHnyy0jPJjoyRufd11FSGdzlReJuB+E2oV0nee9DKCdfRt9zkCUzx2Kjhud1qHnwwN5hnj08zs3VKg8ORJjQk7SUPCc3XK5tNDmUM9ESaXqiBpnGKi21240nonFylkqmEOdgB5rpftKmRs6rY01dxvJSuLrCzHrX4kxKUAwdVVUYjSlsW73C7Il3qbU7hEJBi0XZ/oXneHh7D69eXCRIRFiqO0SlpN8UDEcV3nhvjiePPsDkybfY89AzRMrr+PUK2s4DkNvBD+caLKsZfFWQTichECgIorqK5/s0bJ9ONEQKhYJ0KJ87TSc06esbRizNoQUesukSXHyf+NhOekZ285dTbcK2x8RIEtvziRkKth8wkLBYrrXxwoCIYeD6PiuVFsPpCJ1ikdVrU3zj8A4SZh8ylSFtKpj4yDDEFwI/lUPJFBCKwtk1hzcurN8eM0HNZmqlzH1b8hzsMZG/p2Dy3xbpeRg3LtJ+7wS1tWr3uBGC3Tv3kNx2lPPl7nGTtDSEbyNdBym6FkZh7ZedeWGzSev0CaJf+jat5VW4dJ2R4QLB+VN00Lh26izCjDB67BDhQkjoeXh2C9s1QEqEoqCaJrYETaHbPWfbZBKS4s9fJf/YF7C278ZdXkAIheiBo/hzN6nOL7BU7VAIQwQhV24ssJLLsPfxr2O0GyiGwQdhHLUTIZlJset4L8MpixsbTRqeZLnWYbbc5vpak4e35lhdK7Myt4qxEaBnRzl07DDn3nqv27QSdMWq/qTFQrVD7svH+PGb11lfUOiJTfDwwzsxZ67iAs7EVmLVJVRVJZaIY/g2sl2mP5ug0eqg9w1QQiEb0UgmoiChN24QqAZGMoW0IthlG/OWaNPpuFQaNo1AIRc12DuQRFdSCCnRyyv0Vir4zQaytIG3ukTskafpnH0PSwjCLbt+bQV4SpMc3zfK22YEfA8hFAakRt32OTaW5eWrq7ef25u0unZGEpqOx4ejZkJFo+xISi0PU1foierEblXub3SCj4gvH+bCYpU9vTFi4vN1/Pxd07VsUvFDMFTuaCn1m6CHHvePxDjQn6DjhxiaIKVBUDBoVEB58DHinTrh1BXCIMTYspMLZPjryTZPP/gsuXdfobq4wOrFixx6pEDP/i1MehZt28NvN3jk3gPsuPQ6srRMJJNC6+sjpUkSYwO8fqnCih1wMzPOoacnSNfW0DQNOTiG3jfI9R+9T7avgJfIUHE8bBHDihlkIhZq/1bUi6dJKAHltof0fELHRtMskvsOshLo3Fgvdv/36DabTeSi7IlDOxJh4eoNzI0i/+De55j1DK6tNXn1+gZ+3UbphUbb5urcKj0HDuB5PoTdrjfCEIKuUIwMsaVCZ/IG1ZaDUAQxU8MLQubXqqTffJnn7/0yf3aphK4KWrbE6DRpvfQDwnYLhECkMijxJP7GGta2XYh9R+l4HjVP8MbkOr8qGXS8gJ9PFnl+Tx7lV4ptlHwvqOpHil0aQzs5c2EVoWpg/PI6SQLvzZQYzwwQFZ9yTqjXPlo8oyoIw0DUygz2G5Q7H92H0LAwdQVLV1AFBIoK0TjE4gAIxEeKjqSi8d7Mxh0zbc4XHXp272P/lu1wS8Dx4knamzrKJptssskmm2yyySafwqbZ7N9DshENTRHoqqDSdpkrtfiDw4Os1h1Oz5V5//oKfVGVh3YNMhjX2FKepj47Rd3XUAwLz/W4Plti60g/uZSDnkngPfU0s9kxNOHTd+ktqtevI8OA/MgI2x66l5U3XkfpNElaArdS4epShVphC6ftHGVbY+N6h+itiYv2wBCLly/hLMywaozgNRoonQ6pTJJ4fw+D/XliAwNMn1shjBlUQ59X1iVRL4PvRBhV0wxMXSe+MMdXDu5n4ft/QaQnz9Vis+vnfeESX33qWX7oZjg1tcb/eCRD/a9/RKvRIpLqI53KQr2CM3OD+HPf4Ep6Ky3bxdItqjUPxTQR0QRNL0AoMP2jv6Zy/FncdJSH7ovw4tlZ/LVlMlaEWO8IDanx0NY8LdvF11RWKk12Zj0uNqDR7qBIQICugHQdmq7LmXWb+7fsxJ26jpAhthWn0XY+3ISC0HUIA2SryepaGTvpI1wHzXXxDYMgEkUZ3oJbLIHdxhgZRd9ziI3XXsRZXiIwNMztuzF27AHdJKZ1b0ol4EUSBIfvJ3z9VQxVIW6q8IskCVVD27rzjrZcQgg0KRFBQKDrBGF4y/pumB0PP8D8iXepthwCKTENnbEHHyQyNkrwOVBfFEX5raoRrU4T+4W/Imj80i7FL76GduMy1uNfvC3CSFXjlatFFisf9Q5fqXV44eoGX9lbQAs/WYRRFIVwfuqX4gtg7dyHnL1J7eUfQhgiIjHcySsoZ07ynT/5l7y5EbAmTWaTCe77zj8mtTaLV9yg7QU0kj20S2WuXbxOPuyQr1VYeelnZCbGEcMj6Dv2Yl88Q1gto0UiSFUjdv8T+LUajdE9lP0oqWScTH8vTrNJoGhcWGvzyHCMf9LTInz7B0RrDVYDnW/uO8KlrYNcWm+TN+McHI6y/sZb5EbGiUmfSjRO0lSpX7/KXbUy10s2frvFUqvDzm3D3HfgIV5ZDhnMRCm2XFq2i65pfP3QELs7s0y++AK2YaGqKm3HR6s1uPG9v+QL3/4jkoeGKGMSMQ0O9A9gOi0uzazjhCqvlBWOP/QstdYaacdGG91KOLGTS+sGV1cWkYZBKFQaDRdV0xjMJdiaj/Lq9XUsVSXwfbb0JNDXblJu2CSCDvVmlWgijW6amJ4LoUvm6DFWRI7o4hy5qI7ltbjQUEgZgkrT4RuHB/k3J6bJxEwUIVht2BimwZcODHL91FmazTY5u0pv7wC2HoAMPjYBFoYhrUDlxEzpjuPn5EyJiewQCeWzfyx+GG9hmta7b6ALQdzSadgeSEn96iVGsnlumuMIAQMJk7Kr0NaTlJfnMVSFnJUi6gfQagCgD45yshjQio8yerzA+s++T8O36AQSO/ChVqXeaJGzTPxOEyXw0TQLFAUZhiT2H+JE2UFXBDElJGmqGIGLe+0ClcAjsfcAVk8fge0RJtMUV9aZrDr0Rg2i89fYVpjgXLVOo1rj3dkKlXIVpX+E+XKJb96T5nvnlnC9gD19cZ7b28+puTLrDZvlWoeIIsndOE1mY4WHtkwQ13TE/PvomSxH929lbmYRU1MQUrJUt4k89BSXZYK2EQNNx9QU5kSCojnM0sIy9vwNvrU7Q3buCqknv0xgRjBqdZ44up2/utlg3u6K7plohLV6h/sn8lybXuJQj8WNMI/wPHTVRQCqENw9GMeKWjy2d4CVmsM7UyV0Fb4zprHdX6TzwzfxNpaIDA4TO3o/ndPvYR05jn3uJObwOM6vqRyXYcCenEHh0BCXVxpUOx77UxZbepKcW6wRSkhaOrmYQUTjdmV8wtK7YgzgoPPyjRJzpdbt7ZqawhM7exlPqp8ovgC4QUjTDYiZ3YyYmgsdP8RSFVIG8DntLvtdEgiNmZrHmYUyHTcgFdU5MpJhKCa66uDfkDAIiCkBsVtDQ4ZgaBq5s68hdx3mcsXhcjDIRq2Bfb5Cos/isdEEl8ouWx5+nnh5GcVzqadzkMxxPBmjVIjRL2zCG5dwRrcTHxknKBexkknMwWG0iMojQ1HePnWVofEs4dwUGysL4NiMLk2TPnCY+/cO8/Jsk/nlEiKWgHadpu/ywOFRqi2HgfExYlPXiWomVRWkobLtniNUtuxhV92j5+gIJxeryEBycCjFvrRKZ/IcVixKy/Xx2w5jskknMcAr11YxdBXftKhjkIxGcRsN2r4kms1it9qgKkhVA9PCFSrZnTtZdGDMa7GmdO12G3ZIwtTxFUl5vci40mZrT5x6x2V3X4JwaaorvtxCStntglMMvJvXUCd2IcxuIcOdRAmAtbpNzYXMr9xZOrEkkUP30PngRHeBEBRDjUCGaL2DBKr6YQdNHD+kYodEPy3CTPvomwRCQc334C8vsisO1wKNXxyRQlWpC4NdmSirNRuB7IpM/LJTeTQfI6GHty+D2353Pw5mNDRC1gKNpYZ7+7NfWa6ze28O7xdFNpviyyabbLLJJptssskmv4ZNAebvIXE14PhYjlcmixSbLrYXULc9zi1V8TwfI/BYr9m8fGmRZ7dl2VKvYBAiXIeaL4gaGophcnNhg3Q6Tn88jTe6j+jKKuLnP6Zeq+L73TDf1tXriLUFho4dY/WDD/A8l1ZpkYGJfSwtVLl/5w5OLDYwdJ+8cNk/lGFM7yAunsR3PO564C5kEODYNlarysih+3jh3Dy7RZ0dAxlOzRaxtDjj0QReKBBWip7+DJfKgj378yhv/YyR3jTrAaCqWKqCKUIab73MQw9/EdMOkDeWGaRDpbyALIc0ojFEtodlB5T3zrH60ASWHkCqgOe3CcMAhIrre1i6QrtUIhY6nJ1tc6+zwDMjW1l14yw3HQpWm20H91JzfJZrIaW2y0g+gaPZTBebtyvqJKArgtBzQQjm6g5HhrahLC+hZLo2YEbookRi3ZvgWx78v7BQSEcNdM9GGxjBuXQGdWiMUNNZ9VTqZgY9mkMef4Z4MoHRP0hQLREIhcBziP3hP8J3XfLz01hSo5wd4nIQRwi4+977MSfPowXdSX0lGiNy36PYqRy/asZvhAHq0hzulXOEdget0Iu5+yB2poCHgrrvCFsntuOVikhAzRUIEym8z7i3tS901jsBS9VuNfdwxiKjhx/7/HdCURSCKxc+Ir7c3m5xDWN+GrF1N1JKyrZkqdIhEzXoz0Txw+7EpQLMlRqUOyE95sff4yPvtbr8oSUCM5mi+h/+NYQhMteDne7BDwJ0QHv1Bzz11Jdp9w5RQme25bOgjGIne9k/kqfqhWwEOby7TaTuY11/j8bZU9Bu0njtZ+T++J9gpbLQqKGls2Ba2Dcus7Trfl66ukp9ao29ZoFqs41qxcnGLZLSYeD6Sa5dvkjU0EhGNHKBR/vU69x96Bh2zw6OHRog9cGrlNo2TV1nvC+Pn+7FGR5l8Y2fM5CJEdRaRHWVsYREn7vOcCzGF449y5Wbi9QikM/m2TuUxa3XmH/lFULTwnN8DEO/VQEcoMqAxoXTLDg5Dh3cwWI95PJak5WVDfoTJi07oFls8KNqmz946h6qQzuZXNxAL6mkE1F6+3tYrzQQnkfoOviqxmOHxukxQjqBxNIkpgzQwgAz9ElJl/bsNLYMsVWBoQoSEQNZLqKWiiRLs3zt4AFOzJbJZJJs2xZFBUYSOrrb5P/y4BbOLtVZqHV4YEuO4XSENy7OYUYzPHlwOz2DCexfE9Bb7vh4wZ3HrR9Kyh2fROzXDuvPDKqq4tyyXURKBpImi6GkdavTzr58jn2PbWNipMByw+Xlq6s8tf0gzvQsrh/StB0KVoJ8JOjmi+y5mxMn5xgf6cOvzbLQ6HYAKkIQM3RQYfnadUYevg/3xhUaczPkYinaG1USW7czH+2ltLqBNTpBW9EZ29bL++Uyg+OHyS1cofSjHxL/wtco7zxKuDxHo9pGooIQhBur3L1jgMVsgkqt3e0MyfUwV2lzz3iejdUNvEDQ8QMqHZ9Xr62yTXcotSvkBws8URDYPzqBhmRp6ga7B9M03IDLF24wdGAfkaefp7xWJJWK05/r4d9fbfC4avLg7iGs6cvYl25gGjrDAyPsPbKVly4sECSzLA/spDO8l4qVpOWGLFea7Ns6QGStwUq1STZu8uyePi6fPs+NhTW2jw9w18gwK50QLxInpoTsG0xRadlEdIONYpMrq3V0ReHrIzrGz/+a6yvLDKZMMoqGc/Ma/vw0sWe+hjRMmlsOsNYWhIZCxlKJKp8SeB8G9BgwsCXZne+UkiBwuHs4yfRGnTC8JaB/aDL00HAaUwkJpeTkQv0j4gt0J1lfuLLKH941SNRQP3U8GqqCIzTemqowtd4kkN18m5FcN6stykcFdEXVCAAVCH/LTpDPDYrKyYUW5xZ+2XXWcruWUo/s6GF3Vvvd5FxIiRJPMu0o/HDBw1EMiOQwFVhzBYszdY6M5ThX6jCSHubC9Tnsustzh01+fGoK7DbNUMEwBtCLCnFDYTTTx729JtkzP8dP5zk+sZ19x0cov/Ua1aUl0rpCPLQJTl6g+N5r3P8//D+pb+lFzGzQkoKBgUH25AwWrlxnAcG3jtxLamAUY3WZgqqi7T3MWrwHZ3mVIbvNWLXIPaNDNOJ5ShtlXvvRGb6+M0NgxSg8+QXmWiGljkYyo3H/RI7pjQZzHZ0TTZNv3HWc4ok3Wf7gFKNPP4f7s59QW14hRCCFij6yhRvDhxhPRvEWZonoGi23W3hj+wERrWtjqQQ+R4ayLFRajGct/Jurn/yVOzbC7iCsKLb36ULar+ZzAUhFwdtzN5GhCcILpwiqJdRECn3YIDAjv5V4IdNZlGjsI6JRGE+h9YVkLr7Fc1/4E14971JxQrSefsxYhPFsBEPL85PLq3TcAF1VyMV0euM6941nkIF3+5o96bV4sHKF1vXLhJ5PT18/+/ce4e1OhJodYOnKpnXYJptssskmm2yyySZ/IzYFmL+HyDBkVyFCzBrk6nqD/lSE751dYiIbRXUgsEOCWxG278xWOHZkJ/7br5KwDGou1J2AdCSONH0qbohpJJjcaDG2Ps/6ehFVCFpugKZ0b7Zmy236V5fp9I+jL0wSuA5c/ICtD3yR11ea9KWjbMOns1hEaetkL51AUULE/Y9RjyZIjEbYnjQYHihwZaPNg0d2sFBqooYhT+8dYL7q0JMwSffEkdUyP3nlfRK5LMkBnYztY0gfS9XJWwpOuwOeh29ZxGpFsmqScH4SXRWEgUckkyUwo3i2w1AyQai4jEdtrFYNe+tOlGAWv1LGCySBUPDCEE3VcUJBf8KkObsMS4scuvde9vTlEKZFyff5wcUVFspt/FCSsjR6jg4RicUQxTpSCISUhIAiFISmde0OrAheJE6n3sRYmmX7tnFWpEXV6SBUDdnqZnjoqsr2viTJlXPYlQ2iDz6FO3UNEHS8AF9RiR26h/dkjplFj733fJ2t930RKSExmKehim5I6eAYMSFQAsFRX6IqgtHCTtp7dyPrVYSqEqYyOGbkYxMlugyRp0/Q+lC+QlCv4szeJPbYc9h9wwRS0o4lIZYE6FYffsbFF0cYvHBtg6XqL7tSFAHHJ/Ic6DF/bdWu7tg4s5OfuN69cQlt6y48oO2F9KejhELhxHSZbb3Jrs2bhP2jeYSq8GlBCFJK1GTq9mMtm8ObvoFA4IxsY6EV4hRbyKDrBx9319muRfg3p5epuYJ0zGRLPsau3iR/+sECbiCJGSqKG+HswjJP7H2ErZ6L4XWIHj7K+s9fwSyvo2VztK04dschcu8jvDTXoBwvoCR7WHIFXzowzAvXihRrLb4wJGm+e5FszCBh6Ww0HZKWxkDEYvXiaXY/Nsb/9EaRr++4iy35YVSnTXVwkBUjTeTtn5KLaMgwRJUh/aFNe2EBG8gNl5hfqzIxPkiPKbBaFWrXztEzsZUZ16MZKNxqNEMTEAYhmahBa3GR6GAvV67No2cGaXghbSPKhlTIxCLYrQ6HD2znxGyZ9atXGBkZYGbdZn51mfv3jnLXYILZpSK6ItjaE6ddXqdXb3PfaIG3F1oous5iqcHAnjHsM68hw7AbiJzJExw4xnoijaWpREbGWfVLTF25yf0H93Bytc35qRJRDS7aLfZO9HL5zCXSMYujY330RVXenCvR35vh4FCa3QUDx3N/7Xi+g9P+32j9Zw0hJWG9evuxRshoxsIJwAtCNBPSA1FaKvxwcgM3kJwK0xx99Bnap95GzWZop7P4fTkysQhzDt1snU6HaKtC0tKp217XQssPyGiCUTNg7exZ/Mefpz6xRlT65HsGOLHUYfXSJfyRrayLCANRnbM3lrgws0osarGvfxfP/4vHKK2usVDtMJbJkcllyMqQerlGDZ30a9/jG/c+ycLEKDf1PH4kxmFCVpdWmbEFUsZQAh9V+kwXXXZtScHGFaLtBmnNoigkjh8iUUAobDTb1G2XS++exspu4X9diuHPh3zlgMpYIc423eHqC9+n2ajRk7DQpUtw8zKp0jLfevobtKw4a+kWG55GX1ThxPQ6pgrvztUYjGs8ubOPphdybaXKth0TiFAyO7OIdXOK0bvv5uChYaaKTa6Vb3UYuZJ3pksMpi0yEYPh6izFxQUUKVmrhaTTWWjVkK6LMzfN3NZjvHDqBmFjhUAziBoqD24rsCXZ7Tj6MJoAo15BNhsI3SBIZ3FvVZ9nNJ+ndvXw+o0NOm73HKoqgv2DaXbkLMLQZ6PhcG21fsdx5oeSmbLNllwUXRV4wccnVvtSFmlT5aXJElMbzdvLQwmzxRYveiFf2p1HDT2kUFntwLmlKvWORyamc2AwRa/Fb9UJ8nmg4gouLFY+tlwCJ6ZLjKYHiPBffz0gAW/XXfz49BqTVYcwlKiaihJLkNEl67UOEwWHyY0m7093eHbnAJ12m7ipsbBRYzBpEKutIxSV/bvHQFFYawd80LY4OLwH5ew7xHyHuKrRvH6OYUNDrdQJ223kLaWg/e4b0HeEMV0Sj0dpGHDu+iJ+yyMALi1WMN99i77+HpSnvsblisfMmYtMzq2jCsnu0QIPrK9iXTrNitbP7l3jpHYNc8PRWdio0XEaLJRaLJVXUZA8uiWDvHW9N5ObYN8DIVy/gHLxFNrjXybeaICiUJIGJ6qQ9FX2hA4BEtsL6I2bREwNL5AYmkI6HsHKpFHaki/t6cWQHko8+clfuqIi9G4mS1/yk3MvLF0lbnSvY4QQoBms24K1mkPTdmg7OgN7HmVbxiAfCiguIu8g2Fi6Sjbyoa7sO+CaESL3P0H7tZ8gfe/22AizBRL3P04ka/FHTxympFh4ElKmQsWRrNfaPL69wHSpTccLGM5E2dMXJ6kF/MKFN6hVkK//CKYXcdrd/11vZgplYY4HnnqeF9wIe/uTd7Tk3WSTTTbZZJNNNtlkk09iU4D5e4YQgpqv8cLlNbJxiyAMmS+3WWs6lNsuaeFRiFqsVZqU63a3KrTWw9Z9xygsXKdS9fBC2bVk8SExsQO7MISsurhTN5AS7CBAVcC9deMUhJKl+WU6jz6Pt30/WVWyEBjcaKnsGc7Rm4zgOi59vRa55hp2aY3rW+/jxLtTGNYCvbt2URJJfvrBCkIIpostBlIW924p8PPJDR7aXuDGWoMFJKWNOvG+EWQyRjzhUMHA8RRaHQddUchmU7Q7Lq22TTJmMtY/RsgGy1c3SO/YzWKpQbPURNFUDNvHiMYYDCW1t17GnZpkz30PMZuMszI9hxdIwkDSs2sPp+s+RwsCcj20xvfwX+Zq1C/dRA6M0tRDjk/kyEY0yu3ujeC6DXv2bGVprYzdcVAAVzFIFHpQ0lm2JhSCK9cIYwm8dITV+VUOPJxiSZUsqIJKvY1n21iGxtePjrPHW0WZuU4gJbbrEn/4aZxYhv6OS9NKcMnWmV5tIIELay0u0LVe+daIhn7Lj/sXNmA6oKvdsWIYOqVoHBn5UFn8HUQTvVam+SHx5TZBgP3emxhf/CaO8vk6nSiKwunF+kfEF+hOqJ2YKtKfHOwGvv465KdMKn2oQjKqq0Qtg/dmSuzsS/Gzy6vYfve1P7q0wtcPDvKF7WkMeWcbsiAIMCd2wJXz3e0KBRkEBIV+5usebiC7M+y3KjhrbZfFps/WvixvzZSpVztsNB2WalHycbM7KZaNIrUorcwQr9UFvV//xwi3ibI0jWZeRRsZp257rKyWKRSyLFl5ykGMZrODsrFCtdWkkUvxyNZRRCTBLqNCIx+n2HK5sd5AVRRsL6AoXJKWhlqvYigaVxdLnF5aQR8Yxg8EX9oXY+DuI9ReWsH1YTgXg/UqRjyOmslhHX2Q/kI/P728yuRGk7Slsbt3B19IpsgUctTnVzE0DUMVeJ4kn4pit9qo+X7avqTquuzfm2Km1GapZlO2Q9K9Q/R3KqSyKebPX8OKxdCSKVplGxeF105PMpKLssWvYrc6nLtcJdnbw+E+hfvzaSoDSSayUTQZcKodMJLuJ9pqIgv9zG4/zvs3V/A6q0QGB9GVFlvyWSZiSf7TyWkaaoRqs40IAiYKCb57ZpEv7+vnrXM3GYhrnF1corB9F50g4NTMBtvS/XxKc9RtMhENQ1Vw79AFo6vi1qTW52fSSAqB2tMHC7O3lwkZYilgKaClkghdpWIHNJ3u51pt+bwV6eeur/0JU+tNbm40MDSDvVrIlnwSw1zFTWRptuOkIxr5mIHrhyiKoBA38FyPYtNhdWaNK1WPsN0is77AyNgQu5+8j6oaYbXlcWNhg5liGyWepKMISGf42aLL/LUidtTDSiX5yvAO9PnrJOIWa/UOuYkdaCdfY8/eQ+TjfawN7+K/vH0doarI4QncmociJfgBQkocVafpBLiyhVd38PyQ3oRFICWrdRshBFtycZZqHcIwwPG7p4ZXrq3x/3h6J/rVk8hmnULcIpSwWO2gGCbpHXdx7uoS82GE6fk1CtkEj+wbY3suyky5TcJUGcwn+S+nFyi3HFzPZyIXJa/G2LN3G9NXJpm5fpO1QOWpA2MkLZ1Gx6ft+UzkozRsHxkGePO3xGkh8LyAQI2iA6gqlXqbSqWGr5twy36s7Qa8dGWVrx8aJK//chxYgUfw/ls0p67fPt8q8STRB5/ELvQThiETCYW+QwOU7YAglKQslZQukYEHQuD4wSd2hwFU2i7JPovHd/by8tW1j1Tyx02NR7flqTkB0x8SXz7MSq1DyQ7ptRQubbi8dXPjdmF/qeUwvdHksZ29bE/9/aycX2+6n2hNZXsBVTsg8l+ZWa0oCssd6MgI5+eK3Ul+IQl0k1rLodpy2NKbYqPpMZGLMhsGzNVd/o+HBpDSwzB1Fiodssk8D+0d4dRchcVyg9D3Gap0uLG2xD1bjzKcV2mdfhfbdlACD9Vzu13JdP93vdIGg9sNrk+VmFur4gxMoCVyxAIfWasihEDffYiF7Qf56fkKlVKF4XSKhx8c5ML565yfWsUb6+Voo8U9R/spx3L8/242ubC4Sthuk40ZPHRgHLXc4dxsiSvrJnlTUF9b5sJMleV0jONHnsAciiNqLo38EHNVB4lkR0GyML/ChcgAuwbG6PemcHzJdLGFBFKWDjsP0jRSPNCjEngeYQjq4CioJ7hTWJ8+OkEnloQwpCeiMpiOfOy6CeDIaIa4GiKlQsnXeWe6yo8vrlC3fSxN5ehYBkVRubpa5wu7e7hnPMc7U8WP/sYC7t+SJyp8Pu0wCcMQu2+I2Bf/gGBuiqC0jpLOoY1vpZ3MEt56cfpWUYuH4JVra9Q6HkuVNpmYQVzX2Ki1eKlU5w/vGiKlhggh8Oan8dZXKcQNWm6A43e3Efo+wdl3eeSJr9IXUz7zBUabbLLJJptssskmm3y2+HzNmG7ya3HR+PGVNQxNYbFq88F8hYe29dByfFRVAVWhVvexFO32DUqt7fCe0sO9+3NsnbmCVHWaQ1sxh8doJfL8p0slntzZQ6hp6KogkIIg/IXNhyRu6LQDyY2az4kS7OlPsFjtUOnY/OTKOs/t7WdmrYq2OMOzB4YYePiLvPfSGQxVQZGSdDLGD8/O4ETimKZJzNSYrdgsnVvk+f2DBBLOL9cZy1hIoVC2ffoGYizpEdqdECvs9vNUWi4122e0kMSKmLSz/fy7N2/wfz44jnn+fabL0HRCIpEIGpKw2SBy+B5+eGWDx+59Grn/PsqGyfb+AqPb5qlUatTaDrmj9/GNVon26XfR+4dYCD3SMZNGIk9Vi9F2Q35+s8hTO3o4M1ekJ2mhqRDGYhx/9DjS86iUqpiejR56+IFkT3+SUqJAubyApEP28F6u1Tz29ad5fGeBxXIHUwRsT+nkVycJVqZxDRPp2LitFnOVDi82CmQSSex6SNzUuG97H4ulJnOlJhI4OJTGFOEnTor8piiKQrA8/4nrg3oFpVGDVO6/7o3+jmmFKtdWG3dcJ4Fra036x+Kfml/jmyb64CjO5JU7rtfHt+EJBWRIKqJxabnGgaEMf3luqXsM3UIIwQfzFQYTOscGrE+0anEyeaLHH6F98g38apno/sN0rl7FbTS7nuhSIghBKCQG+qmYSX56aZ2a7dN2fbJRgzMLFY4PJ3mqVzA9O00knSIZS3G56vHigsOlxQbf2DrB/rsfZOq11zB7eujfeYDBA/tJiAh/GCoUvQTvni6x3IZWx+HMuev0ZROIg71cWK4RMzR6LAUBtEJBxw/R3YBEzKI3qRHVPIKJbUw3A/ZFDdabNjdrUXb3b6V+5QJRXWF0dDv+1v2sxwss5Ub5zx/M4/iSXMxgpWazXC9RsgP+b8ePEfdew/UDLN/BSJssl+vUWh0yW3azfqVMbGILuahJueXxnWOjhKHEUAUjqR20l5YY6hEEtTZRrc7WLT382ysBjWaD5UobUw3RKjVURTCQNNDiFol0gmOZJKWWTaUVcnKtyVfveox9EyNMR/t48/wCqhnDHBglVBQuLZS5WWzxtXu20FbqKEISj1i02h1qbohl6HwwX+WLR7Ziry7RMOPUWh5SSixd/Y0dWuJqwPGJHG9ObnzsNfeM50ho8lP1ws8aQRBg7tgH5z64Y5i3efBuPN1AcWXXee7Whx7Kx/l3p1dZrjv4QchQWnB9w2OnY3LggXs4PV+C7fsI5qbQ6FZc+2GIrggWWx6x4w8zS5ZQK+P2DDOLwvSqy7fvGeTs5Brv3FglbDVBUcE0iWgaUU3l9RsbbM9kSUQixLMJihMPE9t1FwOmZFdlCa6eJfbEc4hCP+bFi5iBy/bxfkQ2z3tFHwKbgXSEWrlKtieHrgj8ICR0PcgMMNyfw8/2ko8aCKAuNXzX4XBU51KugLVQQhEChMB2A5auXGM8H6fUclmp2+iKIHf3cX56vYQbhHT6RsmmYlimwZs3N9jbl0BFcmAow7W1Bg9s68EPJUEQ0rId3r80Rz7RT7onz/x6lYIiOTWzQdPxGExH6YlEeW+mRMvx8SM6rmKgmiah46BrCors/lfLZIayD4EUqPm+j0iCoYSLKw0eH08QBAGqqhKePYFz8+pHfvuwWaf1yo+IfukP6URihGGIRcjA7Ul+H/mhU3dEV7F09RMtlHoSFmEQMJFU+NbhQeaqNnXbpzdhMpQ0iAifhdanuyXVbZ+obvDuzMrHM5okvHWzyNDhASJ8ctbX5xXl17TX/U2674QQtKRGuR3gBiE9cQOJoNoKKHU8FASxWIRKvU0QShShEN4qNKm1bbblo0R8G1WzsddKrE93ONQb4cE9I1yZWyMbjzDXCpldKRP4PpqmogQKNU9y4uYGh3cdAV1HAIqqEqoavtfNBzKyaVRNY1R3eVyso2wb47yu8cqKy1h+ACudZWjHAK9fjTGz5DK90cBvtCnW2lxdrvK1Qzu4ePYKi+tVnrr3OE6hn786u4qLQihBjUaoh/DDy2t89eAQq5UWl1br/OGuNCcrFVw/YKXcRIznKAcqnuPR766SMS0WQ5O20Cls34at6hiPfZHk5ZPMnzzFWDIknk4g9h7hcmqcqcvLfOPQELlbQqedSBN78Enab71yu6MEQCv0Ejn2EE2v+8ehSY+nduQ5tVjn+loD1w9JWjp3j2bYltUJgoC2MPnxlXVOzVeo27fsIv2AN28W6bgB2/IWsxWbg70R8rGBW51iPtmYwaGhNL0RkL+BZZ+UknY8hbLvCIqi4IchbhhyJ+Wm6khqnV92ypRbH+0oXa67pLMqqqriTd/oflZCxrMRWm5I3fZQFEHaqZKPB9ibmU+bbLLJJptssskmm/wN2RRgPuMoikIzUCjbAVJCNqKRUD/ZI32jE1Btu9w9nudHl9ZIRg10TSFiqNRtn4iuU2u5bM1GUKpN0jGDwPWYJ85y2eU7z3ydSysNzq13WJ90ccUq92/Jk4nqJO46QmljmXLbpeH4twrtBT0Jk2r/GO+XQ/Ixk1LLwQ8lc+U2UoIbSJbqLuOFXs7NlahvH0fXVKTrMLJlCx8s1LH9EAVBseXSl7SoOT5BCKt1my35GAlL5ehYDkPkMDTBaDbOyZkNjtz/CO0TryNkSCSq0XB8lmsd9hw7wp8tOuRzKa44Bk994aus/OgneL7EsDR0zya+ay9ziX6ysSyvdlQGPI/xhWtc/OlfkYhH6UmY9A6N4q5Mc+PVV+iLqKwsLOMGkv333M9GrJ+rcw1C2bV1WKg7HJsocG29yZ+enMPUNbJRg5j0uLc3wsj0ZazSMpnRMcTsAqntW0gPDdPqHeGC0Y+HSbPpcnquxFBC52Bnierr5/EGBhHpQczR3STaVWbfPoHMDjKkJ3j52jqrTZe265OOGOwfSLJnKIOQIbvyFuGnhLoDuH5AxddYazgIAb1xg5QuP26T8vevYJdQgvMpfuZ1+5d+4J9EEErMvYdx56eRzkcDnNVECmVix+1j1fcC+hIWq3XnI+KLogjipobjBVxaqbO/L4b1CdYbgQS27ibWN4BcW0bEUygT2xG1i0jfQ94Si4SmkXv4Sf71lQ2G0zGOpaPUbJ9MROfC9Bpnry/wzUNDOM0G7XqDXLLEXSMTbO+NcXQsw9z0AudFjiNf/RpWo4JaK1L8i/+dtmYy24RIPs8Xn3yWNS3OjaUKEUNj91gPC5UyO7IWem2DoFIjDCXZRAIlk2dexNCzPUSqTc6Xfe4dy3BsZ5SorlJtu9ysuaykdnL/01spuDVW8iO8t2qzLdNHo+awozfBas2m2vHY1tPtsrm2VufUwABDQ1uYOfk+fTGdMTVkNGUx/uQzXEkN8ewzu+jLp/nhpWV6EhZvThU5v1TDUuDxoSiHjBbG5GVkaZ3m5GVS8Qj/3dGn+bd1jSAENIEXhEQjJkcO7eJH711naWaWopkiLgJ601H+wZFh5tbrrB9+jJ+fX6DRO4YbShxHkssk0PAJJNxYb5IKHSotF9Mw0aMmqqow3ptC+j4ZU/BusYk6OPrLcOBcjKgqfyPnIhmG7MkbZKIDnFmoUut49KYtdm1NMxATyM+h/ZE2OEL80Wdpv/s6YbMrmArDJHrwKGoyjffzF0hmB4iUXJxoilQ2xXSpw0K1wy/iQHRNoWjDueUG23pT9Ccj1LM50nc/wPzrrxH4Afm4SSeA5J593MyO0Sq7lPQkq1WH1i3Ls+WmT9kXhJqOFo+TMHViSshIPsH1jSa5mM6unE46m+Kl2QZnFwJylkq0U2ObpfLYtv0snHibuHqNwae/QN51serXWV++wP6tu6iNDvPafJNUX55H9wwykIrQ+9XHqVWqmAMFemOCxs9fwF9bIhaP0WMYGHsO01hZZYti8o93TvAfpx10RWC7HnG6leIdNyBuaOhRi6qRoGPXUfTuOSeVTrJSbpGLwVs313ludw+pmEHTDfj++SXCMETVNA4MJHn80DgfTK7w+HgPi6UGR0fSvDjTIJCSml3jwEiewVQURIdK2yPcuht/fgZLVYhrYPktiESQmTzG9oNMayl87eNjstR0b9ukGq0G7RuX7zg2pOsgl+dv52x9Gvm4yf7BNO/Plj62ztJVRtImUnogJUk1ZH9eR1FMwjBESg8pwdA+PSMmoqsU294dLcyg2wlS7gQMflq4+OeUnriBKkTXVvNXiBkaGevTLaV+gVAU5prw6o0VOo7PRCHBu/M1bm60sHSFph3QkzT5zmP7uL5YwvV8JksdLi5VEYATSLb2JDh9vUpQrWD4LnpsGL9S5MDQAPPlJrtG8izVHZ47vhMhBOv1NuVyAwYGscsl3pop88zxR6hfPE/LcYlrJkI4aIkkZqGXwPeoXThD69ok4c0bDKVyfPmep/iPsy0e2ppnTVosEKXpdSfpu42pXQuxN6dKbO/NI6VkPT3Iq1dLXC3aqKogHrGImxo126PlBJxZrLKlJ0HSsslZGvftHSEfM+iJqvTUVwneepfc8iKi3cB69HnO+BlmAotL1QYNx2d2IsdXdh5lRyZDUFzH9zw6dpvxvMOCpnNlrcHDo90ik1BKnOEtRL/cg1xfRtodlGwBmetBy/fCysrt38jC46HROHcNJQlCMFWwREAYBiiKwmLN4/pag1rnlyJFRFcZz1j4nkc+keXySoNdOYPBSMjIzjyNQGG96XBzo0k5ZjCcMokr/m/ULRaG4a/NFwp/zXYMTdAKNRwbIoM7sWo1wtVFVBmSNCBlmoBEis+fleffJc6tgpsPE8g7f2Np6fBg+sPnf4Gut/hNGs832WSTTTbZZJNNPo9sCjCfZRSVK2WPd6aKOLcuaHVV4ehYlv09FuJXKrCEEDSdgP3DWZquZK7SQSLRlApf3DvAX5xdJAjBR9CRCumeHM/u7mN6qUhreYmx/iyvzLU4e/IifhAwODbEwLYJXry6zs+VDR7oizMxNMbg2gJz5RaKotCTMCEWp/fwYZ4suwz2RPjejE3T6QpGAkiYGs2Ow01X0DPcz826j75tF+HaMrFCDxvTdYRloWgq3Gr17zqFSBarHe4dz/LEjj7euFkkrYZYdoMbQYe7xwuk8lmGvvEHXHv5VcJqmUJPitjeQ1R3HyC8tMpga53VU5e49Mi9+I9+hbzf7FrYJBJcXarghAaXVlqMZCIMLl1j/cJpVFWlpVo4Ssjw9YvYF86Q2nqA9vIcrbDrRLHwzjvc9Wwfb6kKji9x/ZDLyzXGs1HenSkTyq73thU4iLlJ3r3coO/wCMkTP6V68RRuLIn10DMsb9nL2y2TnG6SsDQuLlXJR1QOtJdwrl2kNnGQH0yt400uY3g3GdmxlaPf+A7znsZPL6zQsH0MBTRLxw9Dqh2PhhPw3I40ShigBBIUFV/Kj93IBkLj1evrvDu5crtLRhFw92iOQ/0Wyq3J2jAMUQeG4Mydh6maSBF+mn/4ZxRTlaSjBpX2nbM1hjPR3yg0uJNIE3v263iXzuAtzYFQMMa2oe7ej23Fbldj6oqkENModzokLI1Qdr9vVQgEXRHP8QK8sGuv9EkEUtKJpRBb0jiA+fTXSccLtM+dwm93iAwMoN/9ADf0AsNJn6YQ/ODCKuWOw0DCYDxt8vj+UZYaHdKJKOV6m8DzqczP44338t5KkSMDBbbMzFM/c4VINsnK6y8ThCFSKGwbHGWmtM7sX/0liS//IacXatQdjw1p8EivQXb7NjZeuAa38lC8ShnDsdn7x/+MV30N2w/58r5+LizXubBcJWpozJRb7OtLkEvF+F8uLfMvn7mbd6ZLxFJpXpkscW2tiQD2DiQ5Np7j5EyZtYZN4Ae8ON3g63vuJT+8Haol2pk4qYEBzjkWN2se129WuU9qHBhI82fvd60FoyJkJCJYuXKFmiL5yt5DGD/49yi6gSYymFdP8MX9j/DazQ2oFOnvzfLo4QneuTDD3EaD3OgworhGzDIIZpd5f2WaP9pXoGRr3FxvUGvamKqCQsiS0MilE3SqFdYbNumERcX2CV0X1BA9atKxXfblDCbiKgMP7OZkBZbqDqauctdQijD4pZCqKAqKonzypFMYMGDB4M4snhT05bOUNtY/lqnxeUEoCvbAKNYXv4VSq3RFpGQaUS5S/+GfgwwxN1Y5PnEPr16cIVvYzytLdULZzfbIx0wqLRfbD3EDyZmFKt85MsD/9tYkSpjm/me/Qc6poSDZyBRwUz3cuLZA0wlZXq2QS0XZkk/iChUvlCQjJtKwGNBV5NoSfq1KIr6VLxdiaAvTpPVhvjvr49mSFJKw6bFs+9RdFd1IcM9AH348zfL3/xwjYoEwiboB62+9Rrq3wHMPPkctkuKNmxusrlV49MAo8x2DwdVFTv/4BazApb9nCEqLuIuzeOsriKe+SfX8GSwu8rXjz7JqZmi6IaJnGMrr1G0PXVNIxhPM1G0CGSJiSWyho3khMSVE9V1Mw6AnGeXV6RKXlusYqoAgJGopXFuu4hXibOnP0JuL8Y0DA7TadnfCXUDTg3enS+weSLHRtIlFdVaTA2zbvQtv9iZDaQvVjyN6+5G5Xvx9R1lbvnMVeTKioSK75kGug3Q/Of8oqBS7XZq/0qn4i+PkF8uFEBzqj2H7AVeWa7ctxtJRgyd2FG5N9v7y9VLKj20zZwlyt4pMfpW4qZGPqCw3P/04k38fqxmAlC45Op7l3emPClyKgAe25okowa91bFKFoN7yeOntq/i2TS6fo+FEOHFrm8moQdzQOLdUZ3Kjzd0jKV66tsHh0RwP7+zjzckN7t/Wy+R6nQ1b0pQRCpkshXSMyxT42bllDo/3oBs67y9usFZto0mfvX0JJnJRPqg16RsapdyyqaT6iT3zVbz3T+AEHomRcXQFOgvzRB9+CuvqJQq9eVZbHk65TGHyNM8feJyJviSvXN9gptSmL2XhIjA0leDWte1CqckTx8eYrtgs1x1cz2MsrhIqCjMNDyeQRHSFmCmwXZ9cTwzd6bA3KMGVlwjaLbL3PUT77PuwtoRSrRHsPMjLyw5zSxcxB4fYkeplWjPQPIcfv/I+X8j5tM++T9dETaJfvsiDTz7P5Zb3kWMklJJONI4Y3wF0j4FPKkIJg4AoAbc2+strSEVhvdmh2yQvEcDTo1F2ueuIm+8iw4Dx2AF6e0aQCBRFYaHp89PLq7gfmri3dJUv7u2jxwx/J5Z9KVMlYqi3M6I+zNbeJIt1j9dvbOD6IVbo05M5xAN77yd57SRyee52cYsxPIYXid2xy2YT6PghP7v2UVu5x7bl7/hcxelQevHHH1lmGAb9X3j6b23/Ntlkk0022WSTTX6fbAown2FW2/D69fWP3K57Qcg7U0Wy0X6Gox99vpSSZNTkzz5Y4q6RzG2/85sbLbxA8sdHR1isdlisdtjbnyQIu5NRxsoCQoYUBno4s1iBMMBQFSaGCvzVxWUyCYuxlElLNVjYfozxiR0cLc6wXq4TndiKYUWYf+EH7MAH0+Kf7D3EqfwYPw5CDgymWKt1kEFIJ5B8sNTgyf0jLLQ6MDCOE88Qz+msljoYviQfN1AVgaAbopuPGaQiOv9/9v4rWLLzTM8Fn+XT+8yd29vy3gIooGAIEIShB9lstXTO6Bx1S6NpxYRmQldzMwqFFApFzGhi7s4oZs5RS2qdFrub3XQgCBAAiYIvoLzbVdt7k94tv/65yKpCFVAAAZLdDVL7uanaa+Uymev/V6783u97v7fmlkgrPuraArZpEagyP1ir8O2jw5TfPw2PfZnNpoPpCTZdiWNmgLI4jVtaQxICy7T4i8ubSLKMkUzSb8p0luscv3+E5bklvj4Uwrx2AUlW0EIhwukkyvbd1GJRlGaN3kKW9eUZZBHgeAGBHyBPX2ZH3wmWayZeINjeE+fVG5tEDIW27VGIGWhmBadaRpIkziw3ebQwSHP6BopbQ5mZRE708ca0wpf3Fam0HUKKYE9MYP/ibdr7HuD5M3MIZFRVQQ/HmF3cYFFL8+DeYZrWB8ErGYEsgYRgs95GrgYo05fxluaQNA1jx37EwDC20vWbkCSJubrL2aXGXRZlgYB35soU4nePLzeVw9i2+6NWW7JM6L6TWKr+W/eDVBM+x0cy/PTK2kfWhTSF8Wz4l1YQwQc2GMqJxzFsE5BwjdBHrDBUfMbzUWp2wNU17kij7L4mE9GJ6gr6J4gvHz4ugBwO877RR+8XnsOQJZY7HnOT6xy+f4CVjsXUWhlfMQirCrLnMrnuYqbD3N+f4NJC9zS8QJDSJQqSw6m6RTpu0rnwPtGRUSpv/AzL8VBUBTUWR+8bpJgusjK/jLeywL7Rfq4sV7FMG2NxlrmVMsVnv4WYvwGNOkqugOgfpra+ya6je0iEdX5+o9S1C8xGGM3EODyY7gaFBTy2q8hG3SJuaJxZqpEIqQxlIqw3LM4s1qh2XB4YzbDSMOl4PoVEiNm1CjeuTKMi2LMtysPyIp34BK4vGM5GyUZ11poW8ZCK1ergWW3iIR3VMQk8h3cXNR4dGKEzeQWtWcdwHI4cO8me4/1INypoS9M4lRSLa3WKQ32Ym+tkU0n81SUC36fZDFiqhMlsnmE8kmFOjmBaDpKiIUkSjbaJoar0pyNM1ptdn31ZRkhwsBDhgLNG9NIZ5l8toagKD+7YjnToBFpPgbQa4HndwJbRahAszeBvrKOm0qjDE1iJ9D2ze4XvoUnSL83a/21ACNG9x2R7AAjZJp1TL93uBxK0GmxfvUT00D6WVZCRCGkKqXD3fldqO7er3XKKx9TkDPraHCgqb2/6SL6HEgohAhmlVqOgeGz48OSRCeaqJutNm2xMoSdm0LI9dicVKpM3kD2HQk+G+zIy1Zf/Csv1Ke85ijm7SLi0TuA6BJ5HJpZAyuQ4V/E40j9OvjTH2uIccr4AyTwiEAxnIkheh1R9jv/HQi/rlQYnJ/L8+MIyE9kwjWvv4AWCmlCJRDKIIw8TuA6K1SLTrjJQzKAurTFsr2H09bNRNwlvO0BasZk9dbpr/eU6JAwVVddxYynaVkBfXEIzy9DyyeTz9CTDlJprhDQZVZGJGAp0WqgIVjZcHj06RGHtGsIPeH+5gxJJYobjLFbbBAL29ib46t5erq43mGz6bH/oKbYdXsO6eh5P+EQmdiAPjuLYIVhZ/8i1loADfckPxA9dR9I0hHvve7GSyuDdEdlXAKNRxZu7jmg2MXr6kAdHgK590smhKAd64zRsH02WyIRkNO6daS9JMg1fpmr6BAgyYYln9hb56/MrNK0PzieiKzy9u4eQ5JENq/esBAmQUBSFeEhHlt1PJe7/VhH4HOwJU0z0U63UiDgWuq4SL+RJaILgl1TfyYC+NMvkiklODUiP9pHMpJgud+iJqKx3PEBioWri+QHrTQtVydCXS3B1o82DYzn+pwfHiRsq//XNG2TCKrZlMziUYarUph1WUQ2diulxda5KveMQuA6uEFxcaRA1sjx5YJilUpPd/XnWHBmx/2E6kV6Cq2dZdxy2j/Wh7TnG2qWLlBsOqajMeCKEpYaobiyScRpsNg1yMZ2FqkxYVVBVFSkcQTRvVu8BsUSMvo7F3s4SU5U2jc0akqKwO51lU44T0nWaTYtkWEcWAQ9kJLzv/a/YGxvo0QjOwixSaQ2pVkYNBOb2/SyeW0OSwCttEDYibMv0ILWqNOtNWsP9mK5ABAGGKiNMk/D1C+x44Ml7XotPFDwUlY7XfUaPqgHBh0RKVYKopuD6PnFD44G8yvYrr1Gdn+PWB9Dj1MlkUoRyz1EJpXjx6spd4gt0q8VevLbBtw8U0X8Dln0R2eeB0SyvTG7ctTwfN2i7ghsbVSQhcITMakfi7FKVSxsdvjC8n5GeCQrX3gbPRT98gs5v2bPuFltsscUWW2yxxRafD7YEmM8pkqJydrn2sbmS7y3UGNyTvcsXX5ZllmsmLduj3HboS4ZYbVjoqsJy3eL5y+vsLsbIRnRyUY0fXlqjPyRhRlJYoRR+OI4adolkMhRiOlfrPie3F6h0XM6t1ImHNYbTETrRXtZ3jTCR1OHdVzHPv0teDlhvOdTKbUIbr/L4yeM8tm8Mf22SzUSBLz0+xpW6x+mFKr1xnTlF48rcOivVDru39bPYsNEUmURIw1BlthdiuEHA4zsK/OjyKqmQRqJeodoxkWUJXZGwZYlzay12ByCvzPMX5Qy5mM7RnhApVeCXN1BkBUlRqC6tsHuowIX5EhHfxTAi1P2Auu2j6SpRu0kHCGkykZFRVgf38e7sJrLbQjLbDEk9HH3gSQbOv8H1pTJSIMgFFv9kVMYo1cEyicYUXvR03gt0UmGdqKYQrFaAbiZg03KwQzH8QCAQONOT9D7wOOP5KL4vaNkeshCkWyXkZJq3Z0oEfgAEBAQII4QvJKxanZVGN5h8pwgDoCsSD8cdWj/6IYb7QZNUd30VfXgc/cEncBSVQFI4u1SiG/b4KGeX6gztytz24XYlGeP4SSLFfpwr5wlsEzWTR993BCvXg/h1G838HSCEYCyp8Nj2Au/OVWg73ffakwjx6ESOuPzJTWA/jB8E+NrNVun3CK4JIRhOaDh9Cd6Zq2DeDAjLEhQTISIqHB5Kf6pM4TuJuR0eLBr85FqJRquDJASi3SQc0lmpbqL6HuPJEDk54P40ZAKLcBiyvRmSh7ZzZXaVlCazM+TgtRrEVZlYfZ3LSyWOTWzDajWRFQn95JPMxvu5tNrArujE+/ZypNjLznCSpckb9PRGEVPXaW9scmF5jWg+j5JOYtbbmDOnOTRexN92EEGY2XKbgWSIfCzEi9fW6bh+1xs+H+UPjg6iSvDydIn1ps1y3SSqq8QMlUxUZ7bS4YmdBXRVJmqEOT6Q5K2/eg3f8XACQSHIsFIT3Cit8VopwPG7lTjrTZvRlIElOlihKDHZxbVNJN+nVGlC3zDyjWu4gcColSioAc3NWYLVGXzXopnM4hWTeGYbPZvDX5whaNaRJJAVDQeV0NR5dm17jKps0JZ0ZKsNrovv2qTyaUZ0HzumsLxqI8kyE+kQDwerlF5/CTWiISO6PQlW5wlqJTYf+gqX5DC7e+L0Vldov/h9hHNH9v3594g+8iT20MTvXkD3E5DqlY9Y/onNVfoqG4wcPkFtfIIfXt2gYbp03G4fCYBsWGVfEi7NlLBtD13pznkBBB0TzWzjBtAzlEXOafzs2jpP9Cg8aJQIN5r4l9b4wsF9PGmo2JledM9Bj0RwL5wmEVXY0FKsOB7O4iwiECiqiiTAazaQOi3UwTG84gDeqR8gC5/AsSlvVtE0hXA0S830WTx3gZ37e2nUBIGs0HAFPQZ4pkn64BESe/ZxZrXN1auzhJwOumexd8cQx/OCnkvvoesQlwN+vFDjZ5bDY6OHOPo/H8Z791VapSrbR4u87yWYr3TQdB0jcDGjSUwfDueSOPUavWGZpt19PNQUCSkWQ1gmwrGJhTTkRIbX5qo0azWkVod6Rr0t5AdCcHm5QjysI4C/mKxwZKBAY/hhZEkiFza4LxRnLAwHB1NcWKrd3laVJR4cz9ET5rZblROJY0zswrp64aPjQNeR+oY+EKMlCW36Kq03X70tzjEziXw2TOQbfwBaGOH7xGWf+C0bMOHf+zlLVrhUcnhzpnTbUkyRJY4OZfi9Q32sNx2qpksipFKMaTebhgsSmuDwUJrT8ze/+yWJpiPYaFo8PJHllWvr9KbCHOqLY4iPr+z5bUQLPMY2Z7DPvYNbqyErCvrwGNqhB+iEo5+4rdFuYF85i77jMRYaJV6+sEYiY1Jqu9w3lqUnLTNTNm/PZUOVWax2MN2AQAiur9V4ZriX5rnT/BOjRaTYh7ttjOnZZd66JnH/gwWeHvCx15bYG/awt0d5rZxkteVybDzPpbUmb6+0MU2PA2MRrlVNsoFg0k0SGn+QVCxMbOUcpTd+jud0BYF8RMOt17DjGRY3W8SEh64rhDWF9aaN7QUcHkgR0hQSej+tjkmrZZExZFLz7zM3M8eu+55gZaNK4HmI0gY9GZ9WuIeIprKtEKNXcVHfexvfExiGjpHJEVTLYJlgmUiajo2CJkkISUJ4HpoICBwLs9LtCdWwA3RVwbU8PCcgpCmoi3P0POjxsxmLiVyMnoiMKj6+r4kkSazbMm/PlVmtWyiyxFguxrGhJEnFx0OhUW1ilzYZ6ukjhUsqHma3u075lvgCXVFKlgg7bbxLZ2ntf5TOPapSkmGNgUyM2bqHIUM6rN7bHvdTEgQBO9Iakb29nF6oUus4hDWVI8M5XrzaTdRykZktt0FWEKEIS5ZLWzb4/tVFvnXiy/THVcxo4rcu2WiLLbbYYosttthii88HWwLM5xQ/gNrHWCNBtz+F7YNxxzIhycxsNhlOh5nabPLIRI6XJjdZbVg3AwwOaw2LZ/b0cnqhTNxQaXg+y+U2ybBBMWnwswsNIuEku0cLGIHM67PdH1sEgo7rs1ptkY9H+MaeAoVOicbsVVY7PjWz652uyxIjEUHjp39N/Pf/kAtBgotXVlncnCQ9PMT+oX56YjrHekL4dpKZjQbSzazZStvBUGVsz8cLAh6ZyBPSZPwALNNCr1VJhjUE3SxCXZUpN0xiuSxiYZKH9zzFu8tNDo7k6TM3MCIRPM8DEbC6tMqOIwUYztGxXJx2B7VQJBsP0R9TEZKE7Hto0Sibw/t49fw8SBIJXUYJPNYbHX5WtvjOngOkq68TlQUDu3dQ+dF/pXrtEiFVwU8mmcgMsv2xL/NzK4bpBviKjHezO3Q2GoLVKrLcPX/fdXGNMOt1k4lchKgu02hYBMKCbA8bV6u3r62uKEiei65qBLLESt0kGzHuEmBCmsJYykC58CaSY3/EqNqZnya6fQ8UB3EFtG0PlHu7LbdtD1fcfYOwZRVpdAfayDYkz8PXdTrBHd4Tv4VIgc+erMpoupeWE6AqEgkNFOH/RmwvPowSuOzOaPyfHxnn+atr1DseIVUiosKBgfSn6tvzYXxNo2f+Et/uL1KJDGI6PnG3Q6dRoj8EQlVJtzf4QtzGevEUcsRgue2yahj07DuAsf0gSadJ7e3XqBTGOTgcozk3TyGqoysyXshA3n2UV+wUc7PzSLKMiAYsllssehpPHU+RaFfR3R4aTsBAKsxSzaSyskZws4n8tnwM0wto2B7zHRNZgm2FOH9xbhlDlfEDga7IXFlv8cNLq3zzQD8zpQ4gSBgqMU2h5XXFlJ64zmbLJh8zONCXoNloUOgrMj+7RDoVo5BN8hdvTtJQGySzw5iqwmbLxvECqs0WfZ0qYcdBSWfw3O491lBB9yxCEQ3HC/CBtqzzM30UZd8gkZDOQF+BtYUZ+iQJpdPEbdZvx2Ek3yPqtJFL6+zZ1mAjEedGrY2mGoRkCOPx5T6V0cYc/Zk4Dz25k4WNOr2KQ/r8W8TjKotNGwG4frf3FfUOkdV5rsh9SJ02+oUXCbkf+k4IfDqvv0zkawXMcOzXHp+/DUiShEDCQ0aRQBJ3CE++j3PmTQ58bT/PX5PwBbcDtgDbMyEGhMn1RIqOq+MqMrrw0Ns1hG2DbRHqNNiXK/K9eZt/NAidV76P5zhsOB6pgT5UewPtwttItQpeq0VQ7CfcN4Dhm0R37aZtNeCm/aZAIN08x8ALMOwWkcgAgW12x304gtv0sB2XtOuiyxKljoMtJCLpNOtm1/MynUliHz7JghVw42qN6fUG2USBHsnCnrnG+blNnIkBTjz8FC9XFaaqc0SUCIR03l9tc6OqcfL4s0yvVTE6YXYMRZhtrDCWi7G6WaHe7DCcixMPbGarFp7nMhGD5WoHz5WQjDByOEI6HqKoB0w1XUq1Vvd6KAqddgdJMYiFNCKagusHLNQs5isdJOCBkQySJKGqChtNm+mKzs6MwomBKLt7YpQ7LookkYuoxJXgrl5FfhCgHbgP3ezgzE1zq2JQDkcIP/wkdix5W/AOteq03vr5B+LLTQLLxHzjZbRHnsb5mKSDD7PagddubN4lzviB4J25MpmoxlhcYjim3fyecD+IyQY+R/oiZKM6Z5ZqLDddFMnnmd09NE2b1YbFasNio2nzzM4s6me8339ekSQJbXGa9qsvwE3rKeEF2NOTeKUNQk9/E0sLfey2Yn0Fs2eEn89UmVytd5cjaNseP7uyxlP7B0mGVGqmS8vz0BSJgXQYywvwdZm0VaN0qYR8+jV6IzrNi2+SGBln397jBKQZa65gvvYiS4sbhDUFg4CnxsbhwSf5v/98AS8IGMjE6I1qvHR2jlwhg+8L9g+mef3lt1gVgh19OoHb7Q0XCenIZgs9k6XWapPLp4kVMvzHS6uM5eLsLsaJaV3bq8n1FqW2Qzqi8Y39/fSGA16/PInj+RRLixwY6+W9qVVUWcavVejrKfDAWIHemEbu/FuwMI2RSiHbTeR6GaNvAIcA3/NQYglUz0GSuj3tZFVB8j0QAi/oCg+5iEr75hzRFQUhIBXWma+0uLzhcHmlwWguyhMTGTRx7/G4Ycv89fnl29Z9fiC4ttZgqdbh6b39vHr6OptTUwDEchWePbKHy/ObRK5epa3JeIEgH9EYS2qEdQkkgTN3A2PHsY8cKx83iBgGP7i4Sk8iREztJqocHEhzbCCKEny8UPSJY1T4DMckBvfmsD0JVRaULdGt4pGg1nHxAoEq3xzBqk5NDqEOjXG6o5PpTSJ+xWNvscUWW2yxxRZbbLHFlgDzOUWVIRnRPrY/RTykosvSR3qaypKEIQsGEiEWayaPTOQwXZ9y2yEfN9hbjHN1pcrengTZ8RCXVmo8ORxhR1DHXLlBv1XBsmR0uQffl1hrON0GorIEQYBtu9RlkwBY9XQaBx7Dl2Qy60usnjtLQpNgcxU/EuVikODVy1dxfYGhyrSXllg3wrzcbBNpVRmSA/btK+JGNHrTERCCWNhgtWGRNhSyVgXj+hQFO4SmSVh+gBUEKJJE2/EwVJlMPIxkVSEIyEc1vrC9QLNjkSkv8I19Rd5cNVlZ3USIgI25Bb65fwip2aE9vIupVsBELsy15TLzSpix/kGk/iHemV4H30dVFVSpG+6RggCz3mDR7WEsH8eIhhFz1/GnrxI3VIJA4DTqJCNJNl78Pru/9Pu8UPfJJrMYjRrCNjmQNxCnFpAlCSEE8T0HeNuJMJRRqbctHt/VxyuzM2ymFPoVGUPXcByPqCaj+hZB20LSdaLFfvpDErbzwfTVVZnBVIgxzUbeWEKPqdwZOZJCYfRiP0qjSjSTQ4kkSEd1yncnkd8mG9PRPzq8EELgIIGq/VYLL3cSBAEhAkK3tKiAj608+40cz3MZjkj8oyNFqpbACwRxQyahCsSvEIxzFZXQ3oPUX/oJbtsl6LRpeS7qk98k5no4tRqPjiWo/vgHFAoZ5sttgiAgLgKa775BVNH5QVnlH3z920Tn5hmqXiWZjdOQOjjXL5PYsYcbfduZP7sAdHtyuEJCUhRENM6rUyXG9u1hrdJg37adeOfeJKLJxDMRVLlrBVVuOyiDg6yLEIrscaA/yTtzFbotJrpBak2RwAXbE8xXOuzMhtBtE1FfR7guhUgEkcygRKP0J8Nsz0dplKtQLvHw/mFWeuL0+S02S1U6rk/bc8lpgrKkMLnR4it7e3nh/RK5aALNWkf4PnIiSdCos7snQfT8KcwgQB0exz35LJNqFlP32ZaLElUlyi2LQ0NZqlc3upWHQtzUOCXSmQSZ9WmCSgnn7Ns88MTXSeYHWa6ZJKMhjuYNRr/7/0IsThHWDHwkUpEEmftP0rx6FqlnEF8YCKDteN17ChAsz5PYPkLBqzE/v8Z4LoLyodEpXAfKGzDwuy/A+LLKbM1DtnTchofsueRjBnFD/kCIEdCre/zB0UEurzY5v1JDkmBHIcEXR+KsL88Tj8eYmdxEV2VUWSKXyJFVGwDs7E3B5ipjUgjnF89jtzuYro+sqowOFqm/9jJZTeBubqBIIJstzFefJ/rMc1CvUJCjJGNhTMtm27Zh4rkstuejyxKFmE6yVUIemcBpX6At68iyTU8qRDhwsTyZ5PhOplsC17KIxlQG4iqrbZ/zyyZHR3NMTi8jBQEb9TZBPER/roASjXH16izbn3mQ629fx7FXkeI52r6KI6DShIih8OB4D4tVk3RY4//29C6Wy21WQx5JPY1ZrXJxcpF9u4ZoVKrkYiG2pbrZ9YHvYegqvSGF7OIV0qqPM1zg2uImwvcJ6RCL6jyyo4ep9TpIEqWbfVL29ScJ6xoLtTo10yUT1elNBfhyGNm3SSmQit/KFrh31aGl6Wgnv0hs/zFEsw66jkhlsUMf9OmSJIlgbeljM+T90gZqs44TT//ScSYrKuc+oQL5zGKNkT25j/Thu7194DGekBjYW+StuRpNy2V2s367kgZgqdpho5Oi796axG8duudgvf8W9/r29OtVWFtGGpr42MQG4TqsEMEzu1XOQSAwOybpqEG5ZfPmbJmn9/ayXOuQDKnIMhTjBqt1E9Vz8DbXiOXSBIFLtQ0Dhw8TLEwjvfF9nrr/cfxXX8dyu48tugyi0YC56wThGLt6djFfaROTPNzZGeJDwyxW2vz+4X5GGsukHtrDqTM32NSjJDJpIp5NzpCJyAqB3SZnd9j11Je4rsggSZiuxxM7CrSd7rP3RC6K7fnEDJU/O7NEazBE3+gIazdmaF+5yNhoh4nD21kzu/1f9uzt4fkLi6ysr/OdUAPKizQ7HdREgmg4jNpTxFtIIVXKuEIiOnmWkYEjXJtdQ0tlsC0HK6GgJFLEFQm9skEhG8ZydFRF7opYhWEm2x9k6cyW2kxno+xKKx+5Ro7n8+589bb4cidVq2uLbK6v3l7WKpV4/93zfOWxwxjzColMmJzsolQ3kZbNbsJTIoXc009ElW6K1V0koJCM8hdnlxCiW9UNgkDAuaUquYjK7oyK8ys+fwohkHyP0M2Dasqt52iJhvXR+RzWFDYCwXK1gxkk+R2ZrltsscUWW2yxxRZb/B2wJcB8Tgl8j4P9SeZL7XsGAY4MppGFd/e6wGdPb5z1holMgO0IXplcJ6QpxA2V3oTOpcUyNcslLAk2a20Mz2GktczST76PkUzw5Ikv8eLlNaz1NSp69mYVhUxMl/E9j1QszJN7+nh1pso5t4WzsEzLg55cgsce+yLJ91/BXm2i3f8E786UUGQJLxCENRUZgd5pcHrF5xv7ejlz/ga6FOPc+gKKBMPZKF870E/SMxmev8D6e+9hqir7H36KH1/bJGGoOJZHIEkIAbYXsCMXwT49T+H4/dQ82Kg12Fnoox1OYPz4T3gml6MzNo6k6ciLN3D+418Q6ilSjaS5vmgy8/oyOw/tZabmMHzgfjQZGrPzyIpEVJXAttC37cIvlwgskxUz4MDgEPLQOKv/6X+BQHR7fQCaLBMy6ySjClRXqXZSoBrkkmmeGB2h58wL1GUJVdVRe3rhkWdYrQuODaVAkkiGFR45OM65CzcY60+za1BnanET2WyB7yECgZwtUN8ssXPA4MS2Xv6jEJiOR1iVUQnIhA3yMQ3EB0EoNdeDHothvf8WjmPB4DjayBjH9z/GT2ZaHxlbsgQH+5ME/lam398UQgg0PAq3S9iCDydtf2okSWIuNYy36z4677+FioQeDhF2O6TSBQLhIk1fJREJUWk7BOJmg2rPBUXGvXqevQ8/x+WpJYrnT+FX5tnM9hCJRJGrG4QefZLFhnY7SCIbIVwkYgP9mF7AYqnCnh1pWhubVEZ2MpLJIEolHC/AdWGj3kFNJPFG9nBhpcFQNkJfMsyr1zdRZAnX7wowiizRnwxhqBIr1TaPFnV+8caVm8EgCc80UetVMhMTZIwsycoyxbOnaMzO4KWi7C3mUfYeoRPvZ8wLc2NhHSFBy/IoJsPIBOwdytEsl9GEAM9FSabpLebYwwbtSgX/6KNcGj3O2ZkWZqmEpei8O1/lxGiGyfkNTmzvIZIKs7JpI+k6wnEo5FM8NRBC+eErSJqO8D02Oj5vrq/jmSY7+tOMFSL4Ny4hhbuNlRQJRK1KAFiyCp5P0/ZQZRnbDzA0hYbpEw6F8YMASfi4QYDtCyL3aOkiHLubRf47bI0iyQpnVjqcnq+QiWg8dOg+qm/9gsVah0IsRD6qgBCE9h5ChAximseRoSSFuE4QCDRVpo3C81dLjGUtjoxkubhUJQgEG7U2eibBzkKSw3kfs1Kl32pT7nT7mkhAdrAfb/IiqgR+u4UsAuxAQvN9JCOEc+U8oaMnSN44y1d2nmA1XuTlqTKLi0sApKIG+3vjjBcC+vYdxnddgnKVbXEZGpvobohOZgCx7zCbb3f7x/SO5UhEDH5ybZ1iJIItawSBQJElFKDRaNPTP4xYne82v/YUPFUnaLXRdQ0s0O1uwsSV5RpHhzIYskSp3mZX1mDu4iVCssR0pUUyneDI8b0EnTa/f3I370+vU798Ac2xUWSJeDzK47vz3eq65QUejSc5tG8bLaEgevq53oLrazUcL0BIEr4v6E2EGMpE+S+nF273pFtv2kxvtkmGRtiTkT+1dZ6LjJvMQDLzwcI7tpUkCWF9TEbBTYT36QRuT0Dd/PjXtiwPN4B714/ePJYQNEyXyyu1j33Ncs1ioC/0O2EfKJsd/EbtY9f7S3PII9s/6O1zB0IIlGI/q5dX0eoVhjI9LNVNLNMhkw3j+DqOL4jqatdmTpF4eneR1UqTiCyQzQbDfUmYuULbg7H922g+/5cI30NNZwktz+LMXKPQP0QzbuA7Nnbgo6kq82fPcPyLY8wvtTGMEIrrIHkuy3Wbd64r9KQ99mYiDB8bxGw0yXzjG4j3XoPVRbyNNeRwlNyh+zBnp3AuXucfPvVt/uN7y/yg0mKp4aAoMsOZCF/f38f//v4ijh/w3kKV/2HXXpoL8/iBoDJ1A6ZuEImE2dsTR86HmTp/mVQsQnLbIOUX6wjAa9TZrDdRzr1H9NhD+O0WdruDe+08J8d2IXaOMmfJSIpO1fLYnsvw9FiY0k9/gBHV8P2A9aaNH47hD+6i3L67HuzCcp0d2Xy3guYOGpbHSt3kI0jQMD2m1htMxMK0mu3bq6xqjddeO8MfDPaR2ZjFWVmGILj9m8Uvb6L1D2GEVEZyUWZL3W1zcYNray0CAamIji6DJASy2SaolHivssLYoEI0m8EtDvLrPqWm9K7t7HrTRpY+EKQkScJQ5ZtV+AJVl5HvVIq22GKLLbbYYostttjiM7IlwHyO6YtInNyW5607PMhVWeLocIbBuHyXTQd0f8SOpg36UmFWaubt6gXL9YkbKsW4waXlDkqnje7V2dTTTMgdVn7+CrosE7I7cP51nt59jFYsxJrlM5SO0LA8hO/jSDL7BtK8MVOhaToksmFk3UB4FisbdU5Jab45th1v+ipmKk9zySIQAj8ISGfi9PQViSbi5DyFQJMJjW3jZF7m7w0qBLLCrIiSiIYorN6gev4MluvjWi7Z6SscHtzGdMNHNzt0hERIV9g/kie6OgNGiM30AOVrM2iail0Lc8NU2ffYk5h/+Sdo77+BrKo4egQ5FCb0zLc5deoiSraI2WpzY3KGv/fIXqozFSJjO8jXDESrieR1q4+81WXU/iHkeJz0jp0Y/WHsM28TFh6uJiPETZ98SaJRrRJDIi7bPHewH8cLGIv0UZi/iJbJkNx/iFamj9bOI5x34qQiCi9cWScVNbi6UqNfdnj40ASq1eSLIyPY4hrr8wugRJFSaWxfcGQwgXf5DI3GMPcNH6A3FSXwXeKGSkEXiJ4i7toy0LVp0aMx2i/+AEkEaH1D+J6DM3WNoi947OAXeeW6fbsfSURXOTmRoyf0EReXLT6ntH2F56+vY4RGeOBr44TMBmu1DnNygiOFKJNWg2CxiqJrNFvdoGLU0JDtDpIRQiBhmA0uLdc5mM9gT53F3SxhHL0fo38Ab3EOpfc4kYntCMBXNNKRKE07oLSyiRyOoAqPgg69iQgLQ/vJ9LdpXLxIEAREdxygnB/lTFPl0GAKLxDs6ImzWMnxxmy5K+oAEhJRXaFt+2QSPrtEjcvxELWWjSR1e0tIvs/JjGDY3mT2r/4LiiyTi+pUTZfypetIl29gPPd/YNYLcfTIHt4re4zHNDLRELMbDSayUXYMR5me9BCKykQiSe/6FBEh0/rKHzCb38HP37qGlslRcgQ1q0Oj1eF50+Hp3UVOTW3yjyMd/G0J/AMDqKvzpOYvo/zwbQIkXM2gsGcvs/EcJxIKEc+iVS6jmD7S+HYkz8e3LSQjRCKeYmWjRnhsF3azSWAJBFCIGdRNF9sTxEd3UK05mNkosqZ9rMAiZ/K/0+ILQN2TOLPYtWWsdFwupMbZ/2QS58J71JsNcuk8sX0H8QZHcX2fbRmdq2WH03Plrj2SIjMT0RHpPNOLs0wMFvj2oQGmK92m3jv6Mzy0vUCqU0FbX8RGR/csolqYkCqTTUSR1usgus2sZV1Hcly8Shk1XyRo1AiaDWLxGIX6Mm+1DVQJhjMRVBGgdRqYHY0XVmS+dGg/hPOELrxJ7ex7CCGTGRxn4Mu/x8UgwUCiwtyGxaXZVR47PEHgCzbNgEAPIccTSEG3AnQsF2dXXxKtJ4IkKySScRqlChFNwRbQsH1CoSi6qhBVZCayYbSETCaZoW77ZAYGadkex/dlaLkBPzozS6fe5OSExZNRk87hEeq1JvmIRk91kfCbP6bdqBF54it0rl8hsbZMAtC37SHY+yjz9a4AItGtuHlsRw8/vbp2W3y5ha7KvDVbYjjZS0T6zXzRBEGAXCh+7HrJCEEk/qn2pUqQjmhU2vY91yfCGto9KpA/jCJLn7jeUOXfnXkryyArH1uBJIUin7h5kEiTSDTBWydaXWUinsZWogR45Hri+KrGWCbMHz04QsN0mdtsdJ9NZYVMLMRDMRfryhKRvXsw33kNJAlJ1ZAjUdRWDdnqwMw1xnceYK7kEcgyyBK+4xCVfPozUfT6BppCV0RUNWw9zA+bKl8oJIkbErG1iwhFJnrsQeyrF1BHtuFbJvaF95HyvSQnDvODty5iOgaxdArL9fBtuOL4CAH3j2RYqJkonkNb6fZpNIWCNjSGXOxHl2USfoMVoRANG/T1pGiUSoQndmBOTYLvo6kK3sYa9uk3SP/R/4XIyiL22ipqKswTsRjlZJFFV8W1LBqVKqtNl74jx8jVV2jYAfGeYZYzI7xZlkiH7h57rh/gBx/9YShLEqos8eF6fEmS6Dg+iaiKuMcD43qphnRwJ+KtVz/SF08yQqij22B5jscndvC2rjK53sBQFeq2STZmUIhoQIBcq+BtrgHQ8hws04CXfkDk+EmCXQcIfo1qbDnweGJ7jh9cWicTFdQtj47VtYN8dm+R2VI3SWlnT4ywLLiHfrjFFltsscUWW2yxxRafii0B5vNM4LMvpzGSGqBiegQIsmGNhBp8RHy5hSFcntmRY75uc361m1E2lo2SjmhcW6mhuC7eygLZI7tYaUqkrTqeY6IGPm10NhfWYOGHpAcH2H/wJA1NIxWOUDMdIn7AcDbK23NVMhGNxZbHaG8/0vQMiixYWK/QODZKOJZA6e3HvHwZXYYTx3Zzo+7z/csbKLEOgarz7J4i387ZcOqn3Fit4ng+8UKe3O99B3v+OoGAsCbj+j6lyUky7Q5jBw8j7z+CaVoUsahdvYLQQ/iPPsO1xU2OZmTGJga4eG2et65OMfGV48S+84/wl+cIKmWSYzvojO/llaU2oVyehuuhhEJEEnESpUViL/8p6sx2xuK7ub6yAYFP4PlIoTBeu4NdrzOUi2OpEooRQtU0FJzbvVZMt/sDU2g6TT3KleUqrh9wFSjEx/m9rx4kio+vx1kqm2R9eOHyGsVkCEMSIARrjsQPT13kuT0F4quTfDWps3ZiN9PlNposUYhqSNNX6CzOITsWm6lt+EHAgwMRgsDDCyB29ATiB3+GsC2MoVGc069DpwW6gd9uIepV1HwRf+46h/YdoOdIPzWzm0eYCilEZJ/gV2x0usXfPjW728AeHa7YYZ6/6uF7Cp5oM2F4HM0oRAcHcBamaXoSBB6Kc6uZsUQ0GqXVsYmHNPSOhTw4TG5gEMvxqNcaFA4fZSwU4ez1JWRVxTdNFN8jripM9AzSU8iwP2pz0J1Ffv4yc/mDnEv3Ye78AsIPWGg4JKsBE8NRLqw0eHuuwmAqxPZCnH/0wAg/v7GJrnSzTDuuT1SD/RmV8n/6Hl85doLKWB8rDZuwrjJgCApX3yA8sR2n2SSbz1J2AzqWTcgPCDyP6NWzKOkDvFdyODiSY2qziabIuICkyuzMGexYN/FXlvDWO8jRGFajyXrM4M3ra8i5IqsYGIpC3bSQZBUvgBsbbUzHZz4UJv7qC+wY7cWIRXE2l/HDEZRYkvDJJ3kld5AXr67wtd0F3j9zCV3XsHuLxI+dpDM1CXR7gyAEUbNB5L6HaJ45Q8IrU0yEKLdtym2H3PEHuOAnENhctXTu33cQffEqH4766oOjeMlfbqv0207V9PDvCLTNNV2WlRQjR58mIXm0BnOokQ/sc3Thsi9v0N7dw6npMiOZMAtVmzVHotg/xqbTonJ1mkw6jpJIsdiw8QKBGYkTO3CEUKNJ6OgRGm2bxZkF6s0O8UQasbqAUBSEHkLTw0iOSWCahPYdJUBGSaZwskNU358jqqgEfoAc+OjxOH6nQ9XVqFouPzmzzAM7H6A3VcSzHOzhYf7rlM0zqUX+ycE8616R1UqHtORxqBil7Qk8zycaMWjZKo/s7uHqSo3vXVxFMjsUohpfz6bYPdbHWrWJE4kSd00EEvmIxs5oQPHsy8jrS6wceZIfrwkuL9XRA5c3V01kSeILuwd56Z1rTBgeKy/8kLDw2R6XUcrraFKA1NPXrTKxLFAU8P2uyL/nACNxid8/3Eel0+3hFjJ0pjbblFt3ixgSkI8ZWI5H1fKIhH9zYyTIFlB7evHusEO6hbHvMM1IjE8TQb1VgTyz2bpnwvvhwdRHK5DvQfJWdn3jo5U5sgSD6RDiExqf/zbhRhPoQ6M4c1P3XK+ObsP5hM/ekmRGt4/y1nwVp15DrpWIqCpKJo/QJIZyYcaTEvgy7SBCf0LH8gJ0WWbAVgidn4JohGQiTLXTRNZUFFUhJAVo8QSB1UExDLSNZUYTaVqyji9DMZfCjEbINOeQfYcWKr4aotH0yOgSL51bIZeOs171+UJmmPorz7O9tIH/7i/A6oAAo7cfuV7GTeVZuzpL3849rNkenhegqApBEDC50WRbIUbH8ZltuHx1ew8tPYZ86ASvzNfYPL+GkGR27x7jUDJHLrWM5liUpq+S6hsj1jeEc/0yuiwR7u1FGRyl/tYvCA6dgHACx/OZCQxef/sanqwimy18AZdsj6ePjJFKRKgP7uH9ksvbs2VGc9GPZNn0JcPokviIu2w6orGtEOf8Uu2u5UIIdFVmZ2+ShfenP3JNDV3Dd2xCDzyKsjCDM30N4ftogyPou/Zjzs+gWhaRke08OhzjSH8CIUEk1OT6Wh1E0P3NUt64vc9Y1EC3mgCYZ94mMjiK+SmF1Y8jpfo8d7CPayWLK2tNkCTCqswb0xt0HJ9jQyn2FmP4/u9Gv6Yttthiiy222GKLLf5u+FwJMH/8x3/M5ubmR5Y/+eST/OEf/iH/8l/+S65cuXLXuieeeIJ//I//8cfuUwjBd7/7XV5++WXa7TY7d+7kD//wD+nt7f2Nn//fBCIIiMkBseitJe4vrUzQcdmeUtiVyzJZTXLqxgar1W4Wl9Jpo0hgShrjKQW9LKEIn3xPlqrl0avrKDL4zSrRygKZ0CibjkfL9nADQbntIskShqayXG7gRXXGduzEqlUJLItOtpfCP/g/snzjOoPZGIl0ivMlm6m1BigyvqwSCLixuEFIaZOTw7h+GVmWkJp1rHdOkRYWSwJyI8PsKGQRnouDgjl1EemSRfrrf4DjeuT7h6gGKvnyIsXmJMbsCkxp7Irl6d8/wfTiBtrFcyQGBjC2DZHOpjFWZzm6vIQZiuHv2EYttIPtEYH4i/9A5OQXsc68yYn8MNVkhLXNGpIso/YO0KzW+MKBUWzLYV5PMtI/jL5zH/bF9282iZEIRICkqIhMD6V4Abf0wYXaaNo01R5QPLTAYU8hzF9fKZGLdG1zbuErKmrfEJdMj4FIDPWF79EnoNA/yoavUitXb79WuvlZLlZN/IE4EgFhu4N17SLGnkM41y4iqyreygJqOgvhCF69BkIQLM6iDY3hzU0TO9JLKHTrXIMPJypu8Tnn1vDpS0Z4a747PmRVYUR2uLpS4dDyOZIDRdTyCvlwmpVqG0mR0UIGLSGR3neEq1fLPHNwiFRnEKu0QvvNV5Elifj4DmRNJzt/iW3JKDOlFlgWSiRC0GyQLFg8wSqZnz6P2WjjhKMcP5ziBSdEzVVZrDWJGGFGh3p4faZCSFM43Bcn4pq4jTrvlus8PZHj/eUG65ZACDi5Lc9AsMZ5AeW33yCkSmwLh1GTaWKBQ6eySazYvX/rMjQ86J3YhhA+olrBXZzh4M4T/PV0k+O2idJuQSjEcDbKydEUpnBRDj4AEx1q1Tq62cRVDep+iIUrZUoOtALoi4CQuhaKmh9guh7JiME5ofDIyHYWblwg47WJDw2jDo1BPE01lKRpuxR68pTsADmbZ+9EL4nhOMH4BKFUFvvyWYJOGzkURps4wMrAbqL928luLuEvzRJVNYb7hlglTNQPMFSZ9bYDBx8g2ZfBunSGoNNG0g2MbbuR9x/Fku7hS/Y7xp32MLdwfcGNWjcve2BQJfmhL0fZd7i/L8RIqo+FqonjgywJkiENz4tAJk9Z6sYhk4aKJoPuuwRzN/CvnCc+dQ1NUsgcOMx6tUVi7ACduUnkYpHW6iqaJFB0A7fVRMsWMDdLJI/uwZQSaL0C3fdBkiAUxnZcmqurxEM6Ztvk//SFnVhCgv4jrDkCLxrli/Mz5CcvYm9ukB+b4KDVpramka+E0OUQi1Ifj00UqFkeP58qU252iMkCXfgkVZW33jrPrr3bcPQwrmMznIngOB6y7/DoYBL5zeu0dx7j+beuQDxDLh7H8UOsbDYIAsH7K012jhRQMUEEmKaJHY2heQHhiIGIJVGHDCRVQ+8fQikOIA+PY4ZjCCGI4BK5WeggyR7lqI6uyjjeTZtORaaYCBFRAfGbd/OxZZXwo8+gnHsHZ2YS4brI0Tjhg8cIHbyfeq32qffVE4Yv7Cjw+nQJ+47zPz6SYSiufKpm3CoBj+/s4f2FGtW2zWbTuv2eHxjLkdbEL62i+azIsowtZHwhEZIF/C01DfeEIHzkBF5pg6DVuGtd+PD9OMnsL91HzJB47OQhfn55GT/wQVbwFYVUSOfkeI6a7eMLhZgmsTMW4M/Pcv2VXyBEG7e0SvzAcaREmpAikF2HwA1QcnlEIoWezSN1mgjPxVuaI6nriMoy6Se+wfeuz+OUS8iGAak81UDhxFiSmukQz2YI6yoWCvN9O9n793sQb7+ELWtEIzGURKLbf8p3sS2LVERHEj5pXSYd0ag73QssSxKaLJNXfXYVNSZiMp3nfp//duoadgChnl6keIK1UpUXVtZ57NhuXv/Zm8S276L+7hs0QyFiI7vI9GSw63VWLl5DGt2BpeQo6hWE4rMjn8EJZM7MrKOEdNKJCEf6kxiTZ1lZXEL7cj97+3qptG2kDyXZaIrE0aEUdU+w2fYRCHIRjZQukCSJw/0JFqodqu076mAEHBtKIUmCIFOA1cW7JvXuwQxhVaZx4wpyMo3x0BNIkoTbbNC+dqnbR03VCIQgCHyicvecDvRGmVqrdaeGY99VPXN0MI1y9SKCm5aC9eqnrmz7JDaaNu/NbLCjmERWNS4uVynEQ0zkooznIkRlf+vZeIsttthiiy222GKLX4vPlQDzb//tv73LC3thYYF//a//NQ888MDtZY8//jjf+c53bv+t65/kwg3f//73+clPfsIf//EfUygU+G//7b/xb/7Nv+Hf//t//0u3/W1GCIHnOowmNdQdBa6uNViqdZACl13jvWh4TF65wdH7tlFKp5itdKiZLtz01y5ENMKT53nyW0fJmQbvzlcgCNheiHFxtcF8pY2uKLQ8aKAhpQp4QmAn8yyLJKMShIXOLHFeOj1PoGoQCtN2A8YzBmJjieu+zdCOPcTX10AIwrqKKStE9t3PwQMC5d1Xqf7sFErgkwzp5LbtRTl8hE5Yp9S2OT29wSNpH176HlGvg9KoYeX6qV1/l3BuDv3Zb2OF48xOznD4/iT2X/1nxMo8sWiMSCyBPHmaHQ8+gmwM0i70Yp4/TfwLz6LPTfHN0QFWj+xgxQLds8kPh4imDP7fb8/j6BFODsb58oNPYogA+/J5EAF6LIoyvIPqA0/zXv2DYGEypHIi4ZOePg+tOkqugFsYoGm594xAearORiiO2DVC2GxjXr/KYrVz2ybsFvL2Pay3HfIxA1kSaCLAee1F3LVlHElCH51AKw4gpzL4rSbYd2QiBwFBpQSG8btjgfLfKemQQkhTMHSVctsGCfpVn87cHOeFYPDAUcLNFXrue5Ts5AVaYR0TFS2ZoLj/GJeNHsb6JQaMgMr3vk+wsYIiSfgIzIvvI/kuuSe+wmMzcwzv7ufyehvHdRk7soddzgbJn/wXzGoVuW+IsiujLC+wd3c/UUthMBtlLB3m/cUqGcUnqUOoXcFanEe4Nql8kYgf5+Es1ENJ6r7Cy1c3yPZ4jPWm6ZgO0d4i2bEx/FoFSQikA/vwwjGyR46h7z/CUDTFzMI6Syub9PbuYk9PjFa7zmhUIR8PMapHyPUnCUdDyF53DvhBQEWP8mdLNXKxLEezMaRAQY05tEptbjkmyYAPKLJM3FCQLJOqG3AtMcSXvr4T/ewp3GoZfXichhHjwkuvsu2pr5IZmeDiYoWhbaMc2p6lE3SDVvLuQ4TGdyK5Dp4R4UxV4nvvr1DtOKTDBo8OHuGw1qH+0g+pVFsMFQvsPfEIVt8oxYSKkz1IaGwHkmMjVA0nHP2d6B/xaciE1buC+XdiqDLpkMK9otly4NMXgrE+gxNak7nSDXAEQe8wk36U6UY3q/lAf4ooHsF7b2BPXgJAS6WRVxdxTj3P6ANfoFQqk3n6ORpXLxEdDqEszyHpBpH7H6VZqUPvEDOXJ4nuP4a3soCwHbygKyyquTzxZAJCYTqSxnfPzFFMx8h3Soz3JLHev0bl+iyaLlA9G3H9KuFCD+EdO/nCRJwX3riEW1qmGg+zcyjPlbUmI/kECUUQ8zTUjUWkUITZzRaP7hvle6dn6DRa9GST7OvLE4n4oGqsijCOU0ZaXSQ7OEZZi3SrWWSY2mxx9FAfqlPB8z00TQVFRYtFUbI5PFmGUAR51z7k4iCBEDied8/vEBEEDMY1tueimLcEDFlCkQK4mTmfDqnAbzar3NRDKPc/RuTAMfA8AiOEY4SRw2H4DAIMgc+ujMpgsp+K5SEEpMMqCcUn+BSihiNp3ChZXFop0/YgGVa5f6KAbTuMZaPkQ3ysXdevii1pXF7rcHm1geP59CRCHB1K0xvu2ub9TWNGE4Sf+TZidQFvab5rTzm2DSeVx7uHgPphhAjYlpTJHx9moWbRdjyK8RDJiMGr1zdZrXUoJMOMZ2MM2yX0+XnsVhNXdJAlCffNnxF6+IuoPf105mbQ8z3UKxWCl35C4cmv477xMyThw0YDqaeX8L5D+DI80hfibLgP8kW8dB4Ujdn1Ou9tmEQMlbrlcXW5yja5Td3aJJvPE3riWRRVxX7xewStJtrYDuK6jOpa2NUyQb3BaN8w8wHUPUFCl8ngsLxwgxMTaey//D7nxk8SKCqua2JEYK7tM5ZM49QlpkodnvvWF6lulHGnplDNFqH6Ju21GaREinlbZmLfEdbKFZIJFT+SIFItE3/7JZ4ZHiOTTWK01+H8e0iBTzodIpbW8LMqhUiRN2bKrN+0DOxJhnhkW4HZisnbMyW8myUwsgSHhzI8mfaIqwHf2NvDfM1mcqOFpkjsKSboj+vM1CzmNpNoqoZfLSNsk5H+PPfvG8SNRdAGhnEWZvGr5Y9cc3VsB+aHKqMKBnxxV5Ff3Ni8fXfQVIUj4z2MlqcRzr2tAX9VZEXh4koFLxBcXqkRj0UpRLr9hlaqLTbqHUYOFTF+02rpFltsscUWW2yxxRb/XfG5EmASicRdf//1X/81PT097N69+/YywzBIpVKfan9CCJ5//nm++c1vcuzYMQD+2T/7Z/zRH/0Rp0+f5sEHH/yNnfvnERuN+YrN1fUWARInxnsY2ZUl+voPua7vot5os+TrhLbvQz5zGk2RAYHwPCotn74nH2fZDuiPKhwphPHKGzSWl0lpMjVDRZYl2raH57joqsRETwoh4EdTdUw7waNFg2gqQd+AzWbbAwkyukpY8ujUG0i6ih9LkujvQ/Vc5P3HeH21w0hDovD2T5DLG+QLfbgba7htG/n8+xQLBd4LUrzzzkVG+zLUL1yiXW2R7O9n7MBRooAYnmDpwiVo1LCPPMLwyiScexN3eR4FcBt1dM9D7jRpPf+XRL/wLPFjJ6j/7/9fWt//M4xHvoRqtcj87M/JSsDoDurj+/kPkx1KdRs1qTNdd/jfrDDPfvHvM/r4VxBmCz8c562WzvtlF9vr/qBMhlQekTaJ/uIX2GpwO1Alx1M8dviL/MiW7rLVuUUspOJqOqED9yGvrZCwqncJMNGBYVbivTgVj/39SQh81HoF62bvF4QAx6Fz7h2UTB5/cx05riDkDzLlA6uDNjj6300A93cRRVFQA3h8Vy/VTleMa9keUnUdGUEirPGLa6vk0wm+vH8XQxPb2aOo1NFp6HFmiVHUVEaTIJ36IZ1Wm0gojGd2UGUZNRymWWvgXTpP5MAxdpgme+JRzGYDeek9EkrXsglfouUG9H3pS7wkikxOrpPOpMjYNbb1j3NmbhKt4xDuK+Jcv4yiKPhCwltfZeVKwMObF4jed5J/u5llsdbhp4rBs6lB9u5N45U3uf79v8Y0bULhEP3FLPFde0kfe4Dvzllcnb/OzmKC3UNFzr91hqnqAF86sZf7My7ltsO7k8sklxrsO7iLibSO5HfFkJAisbc/Tbnj8t3LZQpxg0e2FWg5q6w1bDqORzaq07Q9nCBgJBPlhdMrDMcVZmoVFrwSOTsgHAhs08L1VQ7uGiasWshRlW8c7CMbUambPqsOGIpMNty1rpKMMJM1n9emNqiZDhKQ8G3ePnWVq9EQX9tzmOErp8koFvL7PyPR8006QZYAsDQDNKM7AP47mrsxxefkeJ5XJtfv0q1lCU5O5IkpH5+hbPge/ju/wJuZJGYFrDYsAvE2u/bsJzR2FCkcYWcuhFrfoHX98u3tfE1HisYxQhHk9SUGn/omm82bwqFngufiFYdoCRl3c5O1t99kbP9epCvv0p+OMb9ehVC3z5LfaaNFY0QyaTanplmfX2HNHyXmqYxrG7QXF2BsJyt9IyzUOrRtn6G4xpgS59y1Rb7w6DEaSohq22G91iajy7Q6Jlbgk9R8ENBpdWhpHWYXVulzG+iGimlL/Oj9EjeKCb7y8HNYZsCePWGWrk3SttrEDJmkCr6sIAFRTWGxIfHYV79GY/oGjVoDU9YIQmHCEqj5IuVonvdmGjh+wEgmzEBCRxcfFVKSasDx4STvzFZuLvmg7OX+kSwxxf8b6TXmBwGmEYGb00T6FedJEAREpOAOmzT3U005V9J48XqZhUrn9jLLsam2Tb62r5+8du/ki18HV9J4YbLMcvWDYy5UOixVOzy7t5ehqPQ3nmwhhMA0QkijO1AmduML8Ym2Y/feR0BSCdif05Aknaan8N3zS/iBYM9AlnPLNa4vzOPO32C0J82hB7+EfOnnNC7Pk+ktYl65SOzZb9H68/9Co9XC73RAMSm98Qvy3/gH6HYHdXEeB4VGEFB3VRK5EPtGhjnTVFhq+hQTKie2F9nZ7+B6HtuyYcaLNqs/+ktWZIEaU0isz6FHYyQfeYrOO68jRyKkr75Lfvg4M/PrYFlIK3OMFPqw0kmKEZVs0Obv7UigvPI97L5hZhfX8SyXaE8f5uYGw0NjTLfBczTW1iyi0RZaxyF/9CHUqUssry6TNuL0j4zz+FePU3r/HfqnplmxA1wBqYk+RvftpnTpIqGywi1/XCEEqqqghAwc36NHh2/sztHyuutjqmC17fH61B0OBBLIrsOZc5P0dEpsq0yTGdtOPNvD3ny2m+TleRDYbE8pFI8MsNZ0cIIhihGdXERG82ykdpPIgeNIsoy9OHeXBaAxvhM/V/joGAh8JhISfYf7aLQyOPmAZGASX7yAqJQ+OEVNg1TmM42ve445JBz/jkr0QLDRucM2UIWAXy4gbrHFFltsscUWW2yxxSfxuRJg7sTzPE6dOsWzzz6LdEfm3KlTpzh16hSpVIojR47w3HPPYRjGPfexsbFBrVZj//79t5dFIhEmJia4fv36xwowruviuh8EEyRJIhwO3/7/nf9+XjGFyo+ubrJxh/f4arXNQFznSz3D9IoOvYUMr8+UyafG2PdQHO3KBbSBEegbxkvluKqGMV2Pi9MlRtIRXNdl8sIkjz5wgDeEx0zNpjemoekqyWiIYiLEv33xKiBRiId43hXs9DRariAZ0VisdFitm4wnVLLxOOFoiILqE6kvYew5yKTonuMDAx2a1Rqq57NQdhjtKaJUN0kU8lSmbjAyvJ/2sYPsTCq0L/6c4SNHUNYWKL/wIyJOk1jvINsP3cdas8YLTpF/OjyCfOEXaJqKL0DWI5hCImJZSK0GcuDhN+rEnn4Of2YS+/xpyj1jRL74ddpahKqR4D+8s9jts6FpyLKMJEmYtstfXavwe0cGyPR0ew8MpxVmrE3W612rkeMJn/AvXiOhiruCH6JVJ3XxDcYmHrltoXMLRZY4MphCBD5mJEb46efon58mOH8Jyxco2/eyHO/lbMVjVzHBUEID4SE6rbsHQSDwy5sYO/bib64R2Fa3Se5NIg88htLTi9T5zWYT/m3zaebrnf//vM/dT4uNxoWVFpdXGlh+QCRk8MSuIpcXy1TWLRIhjbbt4wtBe6PGeinK8usvsX3/TuQnvka1ZhMJJL5/cYU/2h4mYTbRdZWOA5G4hh4OoWSyVBsWdtNkU8kxIK9j/tn/ByHJSIkU9PQQ7DxERwlRb7RZq7m8Vqnhqjqa7bF5bZZiIYNshEioOkFpHTwXIctd5z4kwoqEvbGGfOpn/E/f/CPerCZpWR7VoYfwnWWu/eBHBK5DJhUnJbn481Os+xLSwC5O9IQ4PLKLqfU676zVOHz/YS7PbbBcM7lUdWmWyrjlGuv1DpedEA/v6uXkYBRF+CiywoXVJlfXunY5S9UOkiRxdCjNbLlbBRPWFNabFvv7U7w1W8YLRykWIjxS8Ki/9AP6d40SHT9Ka/oGkfYKsZ4ewtkkuzMabV/mpckSs6X27VhrPKTx1K4C2bDCu3Ob6DIMpSPYboBaWgRFptWx2dRy7E1EUV0TPB/3ynnUh564p1j7SXwex/ynna93/i1J3eDxzoxG+lA/F1eaVDoOmajO/t44hbCECPx7vk9JkpBnpzGnrwGQDslE9SiWFxAsT/GF3dsJRnog8BCVjbssIQNASeegVsa2bEStBhubiLVZFls22b37+Kt3Z1nuBGTUgInd9xHEVdpXzvHosUd5XgsztbCBYhgouR7iuSyPHxhmZRryps16o0axL0vt+ln8kR1MSnmuX1y+Gdz0uRH4nC85PPzAPtx6hZGNi/RtrjHVv49rs6sk01kqSpQlE/rCMRzXp9R28D2f2fkVJEnGiMfIDk1wcblMNqyyXDOZ22zx0MR24r7P0maNeChGq9lGDTz6gxZ96YDWlQVi7SqpngzK+AlWHIlYMk60t4//dGGDW4VI19YaZGM6X91TJCJ9SIQRAYeLEXJRg/cXa7Qsl2RE5/BgisGYDPe4ZpKi0nTpzj8VQnLwaycJ3DqGqqoEwa+/v1/GWtu7S3wBQIDjBrwxU+Zru7PIn9Ea7JfN5fWOd5f4cotAwJuzFfr3FVD4bMf8LM/CHz4v/2ag/de590iSxEzVxHR89vSnef7yGnXLZVixkQQsbNRYrzZ5bv/DpGan8Ktlmh0Le7OM+tS3cVwfYdmEW2U0XeO6miOleyiLb9K4cQ2lf4SFRD9uapj3Lq7TjKRoWh5Tmy0y4Tq/vzdP4sybJC+WQdPJHz/I3LkLTFcsjgyOweYyzo0raDt2E2ysEi8YPJ2H7zejzCybBJ0OwdIChx88xiGpSuT0KbwLp7F8n1CmQCilUqnU0USAkCTqG5vUjRyGZiBkhRubLdbLLU4MpSj1HWZw5ABVBNEDO9j47n9G2lyhGDPIhwRLjsLGwjJ9jQp928ZoLsxT7Tj4gSAeUsnv24UXT90WIyXhk7j5OCjJKudW6nd88KBaJu7SHAQB78sugyETfvyXRI49iLfrIP6d11YIEopHIiUjSQoSAmN1Huu9N7DKG0iyjJErkDzxGJ2Z64BA37GfoG8QR1Y/VtqISB6xhIZmOHTefqPbO+0OwocfwIkmkH5NYVESAeP5KOsN83ZPRyRui6S9yXDXNtH//HyPbrHFFltsscUWW2zx28fnVoB59913abfbPProo7eXPfTQQ+RyOTKZDPPz8/zpn/4pKysr/It/8S/uuY/aTbuJZDJ51/JkMnl73b34q7/6K/7iL/7i9t+jo6P8u3/378jn87eXFYvFz/6m/hZ59foGLU8mEokQCIHl+vgCVmyJxeG9HJx6gy/u3c3/Otnm8mqTtXyW41/9H/jJ5DqLiy6rV1YJkDg5nmVXMcGb11bYmU+TDW/SXF3l6f17qJgeIU0lpMnEDI3/8MYMz+ztRZVlFEmiabvossx6y2I8G6PjuKiShBEySBAh6rQIZhfoeD61S5dw6u/yrWeeI5qIw2NfQrgu/uwNVivrjA6NE3RqtJBp1Fr8+aUm39id49ChQ+iTZ2nNTiEkGV1RkSsl3Nd+yuDTz/HwRB63aWKiYMkhAgGSB4rwCCsykueC66JI0Jy6TpDKEi70ofRM8L0lm3Z5gfG9O7G8AEmWkMMRcrEwYdfE31gjcCyqaZdBUSF08DjFYp6xngwbLQvPF2TnLhDE7211p7Yr3J+WWHEiCEBXZA7EfLaJGtmlS2ipDGrvAGrvOIyOEz52krWmw7VSG01I/P0dUQYzEaJ6dxo7nTrilgE/IHWayDv30Xn9ZcLHTyKHQnib68jhMOrAaHffiTTFxD1P77eGTzNf7+Tveu4KISi3HRw/IKwppCOf3QqxZbn87MIKi1ULVB1DBV/A23NVDvWlmFuLs7hSxvEDFEXm8T39aO0a9okneU3oMN8kqqvsSCh8y59DXGjSabYJpbOEw2EcxWDekYmFVFZdB9uUeXuhw4PJCKlHvoEdT6MgUK0KtQtnWa20sV2P1LEEspLEQ2al1iYdjVEqN9m5Y4TJ5SqiXkaSZbwgAEkGSWIiLqPWy/ieg9Vq892zdYoxnWNHi5TPXECKxohqCgm7hl/ZxLv/i7yj9zH16iXaoTieL/CKAxzdOYquQ78U4vSGDZKEEo7QzvUTSDK6pnNupcXhoRw7inF+fmMTXVXJxsPUzW6Q8dxyg+F0mG8dGiAbMbA9n42WxWrD5v7RLL4QhAhwLrxDrK+fcCZL6Qd/jh8IJFVFK60hOzaxL4V5R+plrSMI3zEnfeCVmTrP7u3DlTR0Q8FzbXzPo9Nq47vdni9VOyCdzxLUupUDcqtOPB5HiUTvNRx+KX/XY/5OPut8hbvPvxfYP1zA9QM0Rb5nb5g7CUyTxux1IndchzBw66lAmbtK/NBRZMPA2li+6x4K4PmCDV+l1OgQ8g1eLBuMDT3IgYhLq11HLxSR5leptm2uLJTpazhItSbBO6e4v3eE+x7dTTNeYLPRobpZ5o3JVVLxNCNHexjYWAVZoRlIiL5Rpt6bR5YkmraHLMsoikalbXGj7nF49hJTFy7QGw+RH9iB43gEa+uk+/pZtALSqSRa4DGk6myul5AUBUlW0HSNctPE93xWGg7FiMycLPOzG2W+cd8EsbZNv2UxLwu+sref4tx5Zk6/T9PxGetJES2VMMtvEv/i1/h+xUCfNdk/3MN0qYV7M2vcDOBSyeEr+3rveT36i3BoJI/lde95hnrvnkWrdZNfTJWYK3fwhSBuqBwfyXCgP0lI+9X7HJXbNu8vVFmsOoR1hW35OAOpMPrHnMctLNdnrWFhuT4RQ6UYN37pNgBvnF26a7zdSc0BKRSjNxm+5/pfxsfN5XcvrnzsMc0AhBGlN33v9R/HZ5mrf1P3mI35eXKpODU7wPQF+ViImO/hyT5BEKAJndOrbb5x5H7ks2+AokI6x1/N2aw2PCRZJRMb4XA6hBEIrnshwkefYvexB1laWmfg0H18d6qNE49SaVhEdIV9vXFC+JxbrnF812FCP/tz/KtnCeJZRo4/ysx7Zyj7Cr2pDEGzSuLrf4AzeRFn6hqh02/wrWOPsnxsJ023a607WIDL/+kHjMRk5JtVYO7sDQ48dZyV1TKBY2P6gOfiKz6uKrO7J8a5qTVajkdL0llenOFS2yISj5Mcc7HX1gnniyxv200sHqPHd3Dmpghqa8jpHIsXrwN0+xj2jXNt8DATepyBe4wB0/FxadweP8JzcZfnUGUZZJm26UA+RSQShitnSW/fjTYw/LHXzJmZpPXGz9ADH/3WmGw18C6+T+bZb6P29iMpn/7nZ5BJEy32YV98n6DZQI4nMPYdQRvZ1u3b8ympmQ4bTZsgEGSiOvmYcVtEOhS2uFG2aTtd4TAS7p63Iks8srOP3sKv32fmXtRNl1LbRgKyUYNkWPsbOc4WW2yxxRZbbLHFFn/3fG4FmFdffZWDBw+SyXxQXv7EE0/c/v/Q0BDpdJp/9a/+FWtra7/RH3/f+MY3+PKXv3z771sP6Jubm/i+T7FYZG1t7XPbO8OXVM7MbtDpOLjIrDVsmpaLgK44gmDbA0/S26pwdDyKoxr09af5y8ubbLQ8qqaHkGQimsxCqUWn3mB71Ge9XOe5J07wwuVVzlxcxbFsAk1npenwncODHB/N8vzlNTqOjx8IthfibN8Z49ndvUxuNOlJhInqKnEczHqNZ/cU8F9/h5Yd4GaTZEZ30A7FeGtTMHluA1mR2d6/i/t37iW48Cp1oTFXbqEHEiIIuFi2OZlJUZ2bI2ro2K4PCORCEXviIG40TV71WAoM+rXw7d4BsiyhyQrCt/ElBaFq2HqEq6s1WG+gEjBwUKc/t40r6xvICARd8SUU0klJDtbs1O3PW/FdamffRpmdwvjSN7A1A0OSCMsyfqOG2floVuotCprPV3fnKbVcRpwKvPY8itmiftOXRQ5HiDzxFaxMASEEUeB4oTttfb9No9zmVrtbQ49g6yH8m0FbOh1CmTxy7wDtM2+jTuyEeBLheUilDUL7jxGGz/VYvkVvb+/Hrvuk+ep53l3L/y7nrizLOJLG+0sNLq3UsVyfqKFyeDDN7kII9TNkRK9aMpPLd/up+8jMlzu4rsf//MhBrp6/iipLxF0T1WvwTlPjxrVF4uPbcBer5AwFS2oz6NosX59hx+AYpTdfRZZl0kPDrLQUBlWFuulQvG8fRsjAzyeZvFmw1WmbnLNSHDjxFKnTr7G+so7oG6G2pCIQeG2bwsAoJSlgSPbwJBkpFEG0W920bAQP7R0ic/kUluejJdNMmQoRVcZtN5lb1Yk12hieTVJRcMslIn39nI8PcfnqEkoojBKVsZoNFM/lzy+s8k8fGmXHxAA/evkG2/JR2oFGIAlqlkvbbtOf9LmwsElKmLiWRUT2KUQVkoaC5Qv8IKBpu7xybZ3/8Wg/MT1gqmOzVutwcaVOueWA7/J/PfQgOxpzlL73p6gIhCR3A+bFfqwgoPXKi8iHn6HT+aj9TgdYKjcRvs1q3WWtYZHSZQxFAcnF9btWhe1mG3Hz3qHFUniNBm698ZH9fRJ/V2P+NzFfb637dc9f9xzsepXgY+7DSrWKV9rAkVXC0Tgd2wHfu338zY7PRtMimU0jZQr0bUsw1fSoOYKvZWT26klWAwPJ7DDeEyPibtBemKbsaxj1GhER8PwLp9AjEfYd2MV7FY/rM93388BYlv35GJGde3ljvYPjC8K6jHKzQszxA+RwjOmVMtvDKVqeQNFVGhfO8IV99/PSxSU6mxtkewZwAkG/IbOtN8Z770wTUbv93PxYArPVQQSCkCLh1aoM5dKUPZlSrcOewSwrVyc5MlrgZNKm+sZlBDCcieD4AdeX23iBIPXSSxhHniYeMvjZ1VVOjme5vFy9/TlemLfYl9MISx+9j0mySvvmVIiqIPyPvsZC4y8vrFHrfFAR2unAD6sNTLOHXRn1V6pcaQYaP7i0hoNKx+yAgNevwYPjefb36B9rT9YSGi9fL7Fc7SDoWt2N5+M8PJYm9Al9axRFwbEsOh8z3iSg3Wqx2ql9pvfxSXNBURRc+5OP2Wm3WbXqH1n3687VX2eOKkpXzAqC4J7baqrKuG7TKwve2rCJ6wqNRgtNDdACGQ2BaDeprTh4x7cRRJPdPkhSkpmFC3he15qvuQFr6zG++IV+RoIWf7oJ9sEDSEMqHVew6NpE8Tg8mGalbvLKtQ0s2yYfN8gl+tn34JfQrp3H3lgntrZAEEsQCwu8QCA1qriej1etYF27hIjE0a6eYXjhBh01TMMV6GP/iFRUp+H5JMNhDNfGD1x6Vq6xe2ycOV/DdtqEsgXsTsDe/lRX+LAcRBCwWO2QikcwAwkrlcfuWCSPn+BiEOfi9RISDXRJYv+23TwwOoETy2A89Ryya+MaUc75IRYWW8xayzy9LYX40LOGLCuE5YDlm+NHdWzcdvv2+lQ0iVRf/WB8TU/iqPfuH6hKIN56DafV/OgF73TwL54h0MO3K6Q+NYks6kNfQvYcXFWjLYBK5ZduBt0xutiGV69v0rC6czekKRwfybA3byDdrMR7anuad+arrLUDWp02vckI94+kSIgOq6utX3KUz4Ykycw1A05Nl24ngCTDGicn8gzHJD7Om/GT5usWW2yxxRZbbLHFFp9vPpcCzObmJhcuXPjYypZbTExMAHysAHOrV0y9XiedTt9eXq/XGRkZ+dj9apqGpt07C+nWDw4hxOc2aO0j8APRDchWOth3NC32goDVuslM3WM8kWC3JnNpo42qyCzULUDqCjUS5MMqtXKViu9z5FA/zekzrFZ7sNeWicVSVOUwbU+QDKmsNy3OLlaxTQsCga5pTG22sH2fL2zL8/eODPLeQpWm5bI/rBGVdZZffpFs/wDhh/dzo+ISHRjklWurxJMJZF3HtW2uzG9Qa0b5H/fdz/rLPyXd18/7ZnfYlps2btRGUlUCBJqm4T/yFG8bRS6tNmnV60TsMse2FYkdPUGnWsKsVgCJ2MAATs8wxvAIIpWiXq4SCIEMuLJKtWeMwVwPu8b6qHkw3pTwAkFMBRambxshhEM6Oacb1PArJaiUqWaHWKyZ2G7AkWSeABn5Hs07JU2HUIi04tEb87F//FP8zt0B1sDs0Hn1J4S+8h0stVsp8eEg5S1sVSP86FOYL/8Iv9ndjzVzg/Cew0Qe/zLmwgwEAdrYDoJiP6ZmkOLzPZY/DZ9mvn542d/m+5VkhYojsd52eXehzEK1Q9xQ0YC27XFqahPTTXNfXwTxKZoyy7LMcs38yHI3EHh+wHLdpBkoxOavUZ2dgXAI8cATzK4tMjDcz+iOAearJu2OxaaiMrjnCNLiPJ1EDrXQh7exir2xRm92AMtx6Rnq50a4yIG+FNdKHSY3fSrlGsmIzrHhIheade574FESF87xlhWj41tInks0EqNhORxOh3jjhZ+z6+Buxh85yPz5i4Q1hQEjIH3lNYKlWWw/IH7icf56toUhXITjsGlDJ5oiHSmh+iae6+LsOsqFua5PvRKJYDoebhAgWyZtx2C+YpKPafQkQlRvBnJrtiCXTJANPNJqwFqlzXt2i0rLYUc6Tk1ovDi5wXLNQlNkIrqC7we8PVflvuEUrucT0+Cre3uxg2710alyk754imj/IL5lIisqWixGEDYQIsBpt0nbDeDeFStNy2E8l+Ds8kr3b0+QTGfxVpeRgOGoTHOm2r3fAPruA1ji3uP50/B5muOfdb7eWv6rnr+v6ajZwr0DgoBaKOIpGiIIsKMJIsceovP2LwCBG0jUTZfBiExk1y4u/eSvGfRddg6Psh7NM6eFGFg9T76kkD1wiLeXmqT6+0mf+CLrdZ+yrxAOkhx74DCGofPfLqxSCXQkSUKSJN5frFPuOGw/8gDe62exPR9dlVFkCdv1kVWVIJHGatSRsgquL/AD8GpllAvv8K39R1ixJUQxR19YYXz5Iu8v1pHNNpIAIlFMxcAPK0i6x/hQD2/PqhSSYUYiOtc2WzRdl3wmz46YQHnrJYxOg5iQ8ESI+XIbT0ggQW1xkdz+Ji/e6HBkMEXN9AjrSteaE3D9AF9wl02QLMuUHZl3F6q3LbmGshHuG0qTVr3b11SSJJYb9l3iy528M1dhJFVEF58taCvJKm/MVah1HCIR9balkADemN6kPzlAVvvouPIkjZ9c2WCj+YGFayDgxkaTQAi+NJGCjxHMPc9jPB/lytq9xdK+dJioKhD+b24ue57HeDbKucXavY+ZChPXPvsxP8tc/SxzNJAVNk24sdnC9nxGMhEGEjrGTWFLkiTCrTrulXP0zM3RiaZJZ/ay4vi06k1sTWYwV6C1ukxfKs2uvRP8rGmzPO/j92UQts/9DxzkzOmLdEwHJBmRzXN+pUGvN0dPZoS5msO5uRUe2dOP4/nsKSY4u1Rjs2WDEAhFpWT6/HymgjyU5v7tu+Dceeypa4wdewR5fZ6NjsBNDRO0ZDa3f5FdvTsI//g/Yy0vghDIikzk2/+UU2VIJvLU5ufZnc5jL8wR0hWU8+/w0EE4evJZ3pvZwM31sVOScX3BWsfj2N4RHMcjrkNbVampLusNi3w6xlvXY5yfXgVAlSVkGU5fW8EcK/LgYIYX5m1AhzZAd17NlVs0R1NEpbuvk+97HOxPMLPZJBDdPjx3cmQggTj7zgfXz7HvOQYAFNvC3Fz72GvvLc+jHLz/V7qfu0KArN5M4Pj0VFyFH19axrtjO8v1ee3GJlG9yFhcIggC4pLDkxNJ5HCCRrNJRBHge3yKx7LPzIYt8fzl1bveSt10+cmlVb55qJ/8Pe5LW2yxxRZbbLHFFlv8dvO5FGBeffVVkskkhw8f/sTXzc3NAdwlrtxJoVAglUpx8eLF24JLp9NhamqKJ5988jd5yp8rDFkwlImwPF+/S3y5xWguyrmlCn0786RCgvtG81xZb+F6AZoqEwjoSYWRHLObhSVJuEj0DfZycamGHIkRlEvER3fQanscLEZ5d7ZEy/FJhHUqLYvAdVF1nbrpEQhwPcH1jRb5qE5o/hqld94kMz7GdH4b59+ZZ9f2YV6/vMJarYPuawyNb6d94xrC8zDbJotSinChD//Yw1yY7IAk4/oBC5ZMsncYObAxduzlJ26WpbUqfiAQnokeeFxZbZLc+xCD/YMYL/8Ib/sB3u5ozLkqkpdmMAizY8cERSFhh5M0Mn38rKXSmq6xu5jgye1psokwP7y4imuaeHY3KKNpKk/uKhK+9kZXXsn1cLYOr80v3e7V4GYMBtU4Ba+J+iERxti5HyeaQAsC1OomVr3KvQhaDaRqCfJ9n3jdhRCYiQzGl7+DVNlAtJpIsTgiU6ClGShjOwGwfB8hxFZL0b8NJJnJqscrk+vs7s/wzlw3Y3NDlhjJRAjJ3XFyfqnGrkKUuPzLdymEQFM+/oVBIHBklTNj9/PA7gNE3A4v1iRS27ZTHOzhT99bAgl01+SiaXF2qcY/PPkksz/9Pv377iMtLLTFaXry/Szkx5GGxgnLUa5tdvjBhWUMVSYViVK3LX56ZYWjo3mWw1F6nvoa772+giyBUDXS8RBPjicpXexmIl89cwmp1eDRgoz37i8w52YxXYdINkvhkad5QRvCshuEPYdwWKdlWii7DhBUV/DtAE9R8UMxbLsMkoycTGOtrCMLgSzL6IDj+aw3A5IRjZWqi6ooWEIipAjiikTFDjB0je9dWECSZfb0BhRzSXYXkyzXLFw/oGkL7h/JsN4wefWGy8nxHH95bpnNZhUhSWy0Pcotm7oRYCthGrJCRFPpD3XFF2QFrW8IPZNlIqKz2TBvZ7jeIh1WGcuF+MVUibWmjR8IWkaMWCrFA/1xpOvn6DgBcU1B37EXv3/4cyOg/LbhBYLIvsM4i3N8JJKmqGi7D9K5WQXhC4G0bQ+xbB736gWCep2RgSiuFuLCexcxazUigUNlbprkwCDqI08RzE3x9f2HeVeVSQUWNT3LqaUWGzNzKNEo6+WAvmSYof4cnhbCarukIjp+AC3Hp9rx+Ol0jcNHDzDXDpBqFVAUYoVeSKQouRIH8mnclXOENYWW7REzNNY31rFefp5CJk1y9DkyikvkxjkOju1jOdutcCGdpdJ28NF4dHcfVzZaKJqK6wX82ek5klEDRTSwyqu8GNb4ZrYHdXaKWDzPctvB84MP+oYFAkUElNoemiKxVDMpxnRMpysG5+Mhworgzq+5iivzVxdWsdwPPvfpjRbLVZNvHewjIXfnhSzLLNY+yLj/ME3LpeMK9M/4xNr0JOY2771fAUyX2+T7wh+prClbwV3iy53MllpUh1KkP+FcemMKo7kos6W7j60rMg+OZG5XWP0myYcl9vYlubRyd5WLoco8NJb9Gznmp0FVux/Urd47gazwzlKHs4sfPO9MrjfJRHW+ureHCC7hVoPOT/6SwOygSxJmq8Nodpwri4v09wywUOmwKuv0DY4xPlHg5zMlMp0KoneIJV+jut7kxlrA00f2cPrCFHK2B0dW2VhYotmrMREOmBECgSCsykQNlZihsNmyaTsewu9WzuiqQqVl8/N5weEHvgjnzmFIAfGoyrVSE6/TJvvgI7znxai0LK6VFL78lX9I4gf/P9RkBnl4G6+LLJNrbR489hiR9o+YrpQZHxpBrqwT1RWSxQLW9dMc3/Mgf7noYjkWQ4UkfsfFRyKbjLK7mOD16U2Wljd4ZKKALWtcXa7d/vwkSeoKnxJMbrTYF0kDHxVB/EB0A/73ePgrhOCJnT2cmirhBBqSoqIrEvdN9DC8MYV9R+KPWuzH+ZjKMSEryLqOb997/ki6gZCku3pt/U2iKApXllt3iS93cnq+yvC+ArLo3ouE71OIh/Bb1V9ZJP1lSIrKmaXaPXUkXwjOLtX40kTqnpWCW2yxxRZbbLHFFlv89vK5E2CCIODnP/85jzzyyG17AuhWubz++uscPnyYWCzGwsICf/Inf8KuXbsYHv7Ai/if//N/zh/8wR9w/PhxJEnimWee4Xvf+x69vb0UCgX+7M/+jHQ6zbFjx/4u3t5n4lbj4c9K4Psc7E/wxnztI+vihspIJsLFxQptL6DuwPmFMrsHMoxmo+iqQsf1KLUcQrJONJHAtTqEdRmKPVTbAqtcIhLR2ehY5EM6IUWi3DSJR0MoCCQkUFVkCTzfxw0C3p4vsVDtdIOzuV6EJCFv28tbp+dQZIl4Ksba3BrIMi0nYKbh0jcygWF3iOCwoKUZf+RZXrm8TFFXMNJR6m2bdraPlqMgZfLUxw6w8NZ1XNMCBPvuP8ymbHB+epX3FuscGspy8vf/OVfn15kzNzGdNtbcItPmEN9f9vmnDz3O2eUG5XILbjar3WjZ2G5AjxHwnUN9LJdbrFEnbagMGx7x628RdLpBlurwPl67sU6Q+8Ai4ELVJ33fk0SvnyZVWUT4PpJuENp9AGX3QZTlWZxLZ/ETScTyPEomRxCO8pGrbtuf6toLIbqVMoUBpJ47xo8QH1s5s8XfHE1f4efXV5Elibr1wefvB4LlusVoJowsAlxf0LAD4p+iLYAQgsFU6M4esQDoMoRUhVxMR5OhJYf5f845PLFjjMVWi929cb5/cRVZBk2RUQIZX4aO7XFqusKzhw6y8dYbSIUU+Z2HqG0/wv92aobOzHX+6Mv38efn10iGNGQZJM9CCkeQJJl3Nx2GBntY2jD59qF+OrZLfzpG3JC5PLeJ3D/GwYFB5i5fYbJiY8Z6eOCJ36PPb+LYDl7fCN/fkJhsBOztjaO0BYbdRimt8nZ8nG888WWar72EoS9Bq048k8KKpWlU64ggQFYULFmjJ6qSUAI2Ox478nEqbYea6RHRVeJyQM3tZulv1FqUWl0f+KVKm0MjLid2D3FqahPLC4gbKgOpMJMrFeqmgyrBtw70cW6lwXylQyqsMbqrhyG9TeWMzGAmQliRkAmQUhnWx4/y3mqbuRst1hzBnt4ke/pjXF2pEggI6wp9cZ1ABDw4msEVsFy3CGsKew4NkLMquM4gyfg2ouOjuMkMjvQplLktPhYrUyD6+DNY776Of1PoVlJZQvedxErl7goGeoCXKaA8/CVUX2L1hR8z/dbbBEJgKBKi0xUcOkuLDDoN6rJBKBrn6plLFPt7+cGZeXxJJj86geS6RAKVbC7JOwt1oiGDsNsNgjZtj3io+wh2dqHEcEJDKw7w/2fvv4LsuvL8XPBb2559vEvvgYT3AEHvWUUWi+xis6vYVd2tVlwpNA8jRU9ornoUMdKTItQtaSLm4Y5Cd6TRSHMn1C3Nbd9d1eWaRVNF7wmA8Eggkd4eb7Zbax5OIoFkZqIAWqB4vggGkXufs892a5u/+f3IdWGgcbHQoLTQ8qQ4fHQLeuksQ9koU8UGXYlIy0tF19CTKfRYnMKrPyVx9GE0J8FTe3LMeILxiTl2JVNohsVYucmZsSm+cWQrf3N8Fsc2SEdMZB1cdMq1BovDXXRqOo5lEFR8xIoUGkAsn+NsYCNEg6W6TzpqEq4EYTUBdw1n0FW4+nlN1zk2UVmTfFk9Hn7I8ZkKDwxEV+Wnoubmj6OagOvknFcRQuAJg6VGSNOX2Bb4CLT1d9TWMfTCDU3iS83NJcakgpoXXjcBY8iAr41mGcvFODZdxg8l/WmH/b0JsqbkSuxa01ob9Umk1T6OJgPuG0ownI1ybLpE05cMZB12d8ZJGSGfwU/cFErozDfho0slSs2A/nSE7R1xmq5ck3y5wnLN4+2JEo9tSRGc/hDZaHVMaYDreaTmxtg/0MXJcpW4E8H3AzQ7ytmqJBaLEixOoJw4ftDKL3i6waxw6Brdytz8MqowixQQuAaObSFkq9t7ptTgYF+KUiNoeSVKWj5GStGTjLBUrlGouSzvHSLfkUV097E8v4Svm6TvuJuTpJi7PI0mFCrXzTvpBHf83r/h1MQyXVuHOX56iYW6xx+P1fnWo8/SUVuiXlogE7fRurpZnJ3hwskzRJMTxP0kuXyehapHJmLxwVSriOqjmTJf29nJXUMZLs0sc2K2iuzqx5idIHBdbEMj8H20WIygq4+Jik8lgLgp1hjU5+J2y0x+o3NBhmxP6/Qd6qXohogtSRIzF4hdfhfdv/r8afYPEWQ29+vyLRtr2x4a772+4Xxr136aX2AxgRItGebNKDV8mqEi+gVWJPkSFiqbr9NCxcWXt+ALeps2bdq0adOmTZtPxS33fHf8+HEWFxd55JFH1kw3DIPjx4/zwx/+ENd1yeVy3HXXXfzGb/zGms9NT0+v0cF+5plncF2X//Sf/hP1ep2dO3fyL/7Fv8Cybt74+otACEFVGsxWPepeQC5m0eHomGrzgMBGZEzJcwf7+bvT85xfrAKCLfkY2zpjvDq2hKVrGLrOmfkyNS+gXHcxtJYHgiMkA1oTUSmiodg2Okgm4TDYPUDl1DRjVgqhaZiWienWSdhxDE0Q0VgJ0Gr4SpC0NWxDJ2oYnClXaPghk8UGl9IZduw/wNliSxZBKUUQhNiGhnJieEqj2vQRqQTznkTpJrqABRGhYsWJaJLuwCffkeCCinHnw19Dnj/O+HINv9FAKdixbwcnGibHL02ipEKPhowtWZybr7C/K0ZNWIQ0UN2DXKiCZYR8OF1G18SaxFc8YqALhQwlMSHZ0+mw91IB9+J5VLOBSKZxduxBMyzeDSJocRN5zctlqBQvLSqGttzHrz1gYPouRByCWAKOvUXjvTcAsFIZZL2GrFUxunuRqeya5JuI37wB6JdRMS90g2rQCmzEDIUmw69s5b4QgumySyAVmgBLX/uG3/RDvFARWQksmtqNRwDSluLuLTleH7vqA6OhGM5FOdSf5o0L8/z6gR4eTPlEi2NEjAhRIkSEpBJApRmQsQykhEzEpFAo0BjoYctvfIdFO81rJRdTRXnk0CinLk6zVHXxgoDQc4kYoFbkznwpMU0DU9dwGy7nppZ5eP8Qr11cYm65wvLCEkLTiEUsnrrjDqY/Os3YOx+Sf/ReTkR6GSsss7c7zYnlRUIFuaiJWS8ia1W8TCeL82Xm+noJH3mW7kcfh+UFDgx38+ax81gyQFkGkb4ByoaNVa8T8+qcX6pxarHBdw718/PzC0wUGsQiNomYTsoSvHR8HCEEoVSYmuDD8UXu2N7Hrq4EpqExnIvx5qVFMraOVAo/lKSNgIeH47iDSQQKS0gMLOJHDtH86ANAIUyLqS138IMPJiGTRyQsgmaTVy4sMpiNcqQvxUy5zmM7u5mr+tQCScKxKNSbOJrC9zxeGasjgGRmN8/s76Yu1l73dV1vrXv41R1XnwSpoNkzhPV0L1q1JQ0l4ymaurHpfgzDEKfZoHb+1FWpLK5eV4UQGJdOk921m8bSEkUP8tEYhVoJpcAwTRpKJxqLUPZbPkFCg5htUGkGGJogF7OYrzQZiOmcuDDNwS19LHuSl88tghDs7U6yvy/ND0/Nc/fWQ5jVEonGJEK0kqi5jgyd33yKi4GGOvww//VyicULZYKli5hI9m/t5mhKcV5kOL9Q5e/vyRD6Vfqqs9iOja5p+LEkslwg8H3GG4KOgS1ElheJGBoBgkYQomka8aP3caIYEjF0Uo5Bf9Lm+MQyuZjNPSNZ+mPaGglFTwomCpv7n40v17l7MEVTSQhhe1eCDyYK+BuUhQ/l4iRNhQpb+z0UOvVQoAExXaFkgBCCZV/nx6fmVuUHt3UlqbiSmLVx9mYgvb77BbhuMgggYmrA9XWJTOWzM6OzPduBBEwhkWGAlC2fvsWmYny5jhCCoYxDzhHoN+EDthG6DBiMwfDObMu3BkUY+l948gWhc2zB5dULi6uTZkoNJotNItd59j43V+Xh3gjhxMU105WE+rlT7BtssGvbPj4yctSlxp7eNM+fmSMIJdFkhnqlRiyepoxAlUqMXYadcbgwPY2mCQ6MdmM1prG6O5k6MU/cMUFANmLSEbfRzgo0oYjbFp1Rg2K1ieuHpByTYsNH69nK4FPPMF2R1PfqvF3XqdUbaM1lorqgsTDH676BbqV5cyFkf7LGexMFOrJJMlGD//zOLHv6MmSLJRbGiox0wf75k+hL83gvz/LId36XX9R8qs2A96aKGJqGoQnmqy7/+7sT/O6dQywsFent7uBsyae3c4C8obBVAMJgWdh4gY4uBJeX63TEbTpjRksOTcC9I1kMFWySjmwlAh0hcSJg2AlMP4U7pUOooTlRrO170XYfoKnpmyyhtQyxfQ/m1GX8uZakpuZ74HvY2/dg5Do/cXHZJ0EoScoxmNvEPi1q6a1nry/wdqoLQcTUV/1oPo5j6Ri//BLTpk2bNm3atGnT5jbjlkvAHDhwgD/5kz9ZNz2fz/Ov/tW/+qXf//h3hRB897vf5bvf/e5nto6fF0IILtfgp6em1kiHdSZsvrm7k+h1jF8/ThiG5CMG3XGd7Z3dFJoB5+Yq/MUH02hCsLMzxthSg6RjI4BG4PMP797CC6enKY1NEVTKNP2Q/q4096gFnIUlfl5R5LJJKhcWcWsNfFcwGoPFi5c4OpCn6kncSpXBVJLlSp1KoU7FimAarUCT0ZKS571Fn8T2o4SlKrq9iKkUC0sl9o328ealJcyVD9Zcn0rdJZ5NEM+kaBSLVALFXABZ20LMzzFlRbg0uof7doyyOLmMnsmhOVGc/kFOvnGhpbQgBHgeEV3jQqlJsRGwtyfNlBnl0lIVITSSkZYkwANbO7AsEy8IUWHIwd4UMmwFdwxABB7W3jvwLl9E7+jCNE3qP/lr9Gye4ujX8BdraPlORDqHRBCzDfbHFVlvCco2JBN4TgyrXKD24durx8uvlLC27sA7f5pgYQ4jliDUW8PT7OknSGU/9bn1eb7wCiEoBDqvXShweamGUtCVjHDPSI7eqEJ94RGgT4emaQghNjUHvlGaK+NYKogYGhFDW53Wmt5adsoxyURuPAggZMjBrgi9yT6Oz5SpNAMGMg7bO2JoAtK2RmzuMuHP/wrheRy+/3HOyICwXidu2UhDpy4hEYuStgWOcAh7h/gv713i1PR5rGSKWNQjZyoOjPTSk44wlI4wO1tDKoNqKJAqRAYhzaZHyoCBbZ08aBr80dsTzJdqJGMOCIGmJLVqnR8fm+Sp4U7i0mMGB/fyNCMDvbx1doo9+Qzf/2iGpXiUrV2DWJfOoOwI9/UkeemVD0AqznZk2Ds8xE5LUhrq4mzRJ9QjTDdCVFjiazu6OHP6PE4swc7+DiYLde4ZyXFnv8+Bjgh//vp5LlSbdCYdCnWPMJRIpdCFYL7q8fiuLpZqHssNnz29aUrVOhqCqNk6LjIMMVciIlK1VPWtg3cTTWVwT7xP0NHH69N1RFcvKp5AKMlAysaN2/hS0Z+Nsbs3wfMnp6m6reV4quX3sb83uWpoLgQcHc6S0MNVH14ldBY9ODdVo+GHDGQcBlM2jgjaiZgbRCmFqxmQzF478Zd9i760Q7HuU/dacpqGaSI9l75sDKpl7GyO8gfvcXj0MKlMlC0pq9XJKX1MKYjoDpoQHO5Pc3K2jBuEhLIlS+YFEtcP2d3fwQfHzpHPJFgIDZ7Y1cVy3WW+4vGzs3PUvZDLS4r/+dFfY+TSMcanFsj2DmBvGeX/fqLC1jycG59nYqElPzXU0YM7P8Xbpyao1jq473An/5cdJsHLP2J6173YfoOwViJcXiTS04cc2opRWeL45CJ3ff1J4lPn6Th5FqPaJJnKoe07yg/KMRqei2NoHOpLMpC0ONAdI6orDMJ1/lWtrpXNk8ohGu/NVHn30hJKQXfa4f4d3bx3cWFNt2AyYnL/lgwq9BFCY7IOr19cZL7SRNcEw7kY9wxncAzBD0/OrJH7my7UOdCX5KXzi2yP2Gt+P+WY9CUt1AbFLfmoTtw2qLrrEyJdyQhZW1svZ7fR2aMUQvnoXG06CITJy5dKnLnGI+btcdjZneTBkRQaiqIHXtBKHKVMhbxJw3K5Il30ZcVvi4Hg9bHFddOVgvFCHSkE2gZjzw8lEoF2jUaWFk/Q1ZNDVJvU5uaJf/gKw498hx99NIfbaDJTbFAvVYgnkiStOlq1RF+2AyOm0Z2weKDXIqv1MVtucm9OEMke4I35ClHbQlOKtBbw/HuX+T9+4yD9aQcvlHiBZKbioUJJ3LEYSRoEvk/iqef4Xy56NJTJ8akidc/HsQx2duRJxQxM02L68gIRFZCUTfBcdvemuFjyWl1YmsCt1SgWSnh+wNasgzq7DNUyUkoWJ6bId43ys+ll4koSCIty0yditpIEr44t8e07dzJXajDckSQMQ0pKUnA16kpDqoD9vTE64yaHB9Kcmq2Qjhj0pyPcPZxZkyTVNI261Cmt3IvStoajydWEZCAE4cBWrN4hkrYF9Tp+JIp3A+di07SxH3uKyPw0wbF3kJUyRv8Qfr1O46//B85dD+KP7CD8Au5dYRiyryfJubnKho9X+/vS2CK8WVuZT4WmAg72p/jpqY1l2g72pREy/CJzQm3atGnTpk2bNm2+AG65BMxXmXKo85OT03jh2mD1fMXl5QsFvrn95jSB05ZiV0+a//HeNOcWqqvTOxMR9vdnePPiIveOdnFoKIsnNV67tMTXu3QKpGm6UXKWIL08wdT7l7iw917Ojl+kd3SEZ+7cypsXlzm7WKOsYEBIfm0kwd++cYrpuQI1BlkqNhCa4IlDfbxzucCWXAxbh4brY6civDLrsbevk3qvpNvRmQ18DnfGOT1bYqHqkoxHSVo6kVyS4azDXKnOzGKDu/sSSDvCdEMyuGsYqRmcnC1RdjTuipv4uokZSsYXSqumsEqBY5utThYFE6UmR4ezzFcqRC2DmGXQYUOaJrtnTjBw8QL6tj1kdozSHdOwAh99ahzv5PvIRgOZ7yT54BOoRo3yH/+/0CIOWq6THbu2YJRDQqUwYzGqoeJAc5bq8z+j2WzQyEXxdEFk1wGMgWG45kXWm54kuusAwrRwz55sSY7FLayBEcy7HqbxCSWIlKZT9FoBZoDuhE3KlDcUPLoZKqHBXx6bXjVkBpgtN/mb49M8e6CXzluz4WwdQtMo+Bpj83XKzYCeZISBlE1Mu/lAt1KK7sTVoN/EUoXHd3Xxw49mCaRC1wSWLrAMwaPbO7G4uRduIUO6bOgbTbWCKQGgJJaQHOkwWXrlFSqeh6ZrDPpFrIER/s6cplIrkY7EMGJR0rEYWuhSNSNUXMlY0UWLJyl4inLQpGlruBfmONLl0F9fwHUsplyBVBIB2LrGY7u6iRmC80tNtnUlEGFIs1onGY8SS6epFgoYukbdDQisKEMH9vDedIUdPXn+4t1LBEJnodLk1/f1sOhCiOKuR+8mLQL+6vl3KdWaCNOiKh2eP93k722LcjDqcmj3Dj6Yb+J6PkG9zsL4ZR4eThGZnyA9foEwkcaJbGf5wgXCQp7Fs5cIw5CIZdHf3cek7xPIVudKOmbz0zPzfDBRRAGDWYcHRnIc6E0QuU5wxtN0tG17sUa2UQtMlt6bRl4zVoVqdThFNBhfrlGpuavJFwBLSAKlUfMk927JoYCRjEPGUquBMiV0Pphvrul2OjNXIRkxeWZ/Nwlxc92RbW4c34mRGBhgV3iZUtOn5oVEUg4JXSIKC5h7DjO1WCbTkefw7HEm3SJyerFVkR+JEO/pY6bcQNd1hrIO+3oSjC/rNF2fRrVG4Hrc1Z/DEIqGkwTLZnmxTkT69HVmiFomg1mHy3MlxmeXKTUDehwH48Bd/Om0ZFdJY7rc4EB/illPoBsGvuczUagzks0TLC0ybiS5O1SUX/opzM+S2lZDyRDNtGj4IY3JKSJbt6PiObo6uxB9QzA6ytAdD+LNlDhbE5wuBlSCJj3JCM8d7mdHSgfptvSh1MZ5YwPJru7kmi6IK3hopB2Tj6au+iDMFBvMV1ye3tfHdKFKzQ3pzzj0J62VRCNMNwTfPz61+p1QKi4sVJktNXlib+86r6WaF5DwfB4ezbNQD/BoVZ8P52PcN5IhsklRiyMCntzdxQ8/mqPmXX3mSjsWX9/egSY/2ZgTQjBWdNckX65werZMdzrK+bkykyudQ4Ym2N2T5K6BJBa3h4SoEIKpkrvhNbPU8OhJRrmwWF3t/LyWfMJGsyOYW7YTfvQ+0a07kfMzyBPvkPRDMsPbiN5xD//p+AwLxTp1z+fI1l5eOe2yXKpjJCzyDmhz4yAl+zp6CX7yt9yTTZK4/zHON3T++6zFXK3Cbx0Z5PvHpnh1vMzXDw1Ta3o8tbebn5yaI2rqREydmheQtXXu39NNNBnh//H2RYQQbO/N8vqFBQwheLwvwj61gHPhHM1A8dCuvRStlkfZ0uUJ7t61g4vFRQoNn0TMQUmv1XmajJOqLdEoFTCkxA0kMcNgodoklAqvUkFLJIlaJnUvwImaeM0m2vQl7qjN0XvPYf7fb06w0AipSImtC4azMR7YmuONC/MkLIOn9nSxNR9nIC7QZHA1SarpnCkGvHphnvrK+R23DR4YzbMlqa0WzCil8HQDo6MLd2am5Y1zg3iGhRYE+L6PsiO4589wpaKg/srPiCfT1LOdN3dyfUK6HHhgtINXxxZX/RkFsKM7ya6OCPITjudPilKKkZS5zrNJAHv7UgylTNQXvE5t2rRp06ZNmzZtPn/aCZhbhJZckbcu+XKF8aUqJS9NcvPO/3XoAqKmzn1bcvRnHOpeSFcigm1ovHhuAYATMxV29yQoll2qzYCfjE+QImA0qVN4510qlQKZvft4YboEXkC9Xues67KzO8HWzgQZx+RAYLP4/T/mkcHthEeHKCbyzFU8EokYL1wuohC4QZnfPDLEiekyXhASN2E467DUk6HecEnqkksT8zx1YJCiG+B5PkkDcgmHqQvjTE/N0b1jlDAeQxgWFh4egp9/OIbXaHD0zi1oc5PcPZzh/csF9BVdd6XAMHR601HqgSJm6ZSbAsvQ0DRBVyKC5jVRkxPs25rDunCCVLmE/f48mdI48Ye/hv/Bm9ROHVvdr7VShZnT5+g4cJCZzlHijklt/328fKnMO9NlgkAScWx+/fAg/vh5/FqNvlQUQyhUKGmeeA9T19GisVX/GFDUz3yE2dVDbHQnxpadLMY7KOkWliFI6DdfBRtqBm9O1jg2WVgNhmgr1fWHuh109dl0pWiaxpn52prky+o6SMVbl4s8vT0Dn1Je5XNHaJwrhjx/enp1f52cKRO1DJ7Z103GuPn1z0cE/Zkok4VWQkfX6nznYB8TxQaaJtjVEWVL1lnR6L/5ekdN01hwBe9PFpko1DE0wSM7e0gUZihMzxAqRWJkK7VXf0b82Ds8PvowHy4aCFPiNZfwzSyLwubwQJq3pirUdRtD00iaAqUgYusM5pOcOT/BIyMpalMeWjRCQ7aSCg/t6OH8Yo3/+OpFij5s6YiTTUS5M5fg1bEluuMm6b4u6k0PLQzId+XplTUmS7O863Xi2TECoTHZ1Jg9s0AuEWUw6yA1EyNiEnT0YuQFcy7MFyXfPthB1dL44bhFbPk8u3dvIeokmVnQeSDpU/jRX5CLO7i6ReHSOLF3X2Tk0F1U/BgDXRkuTy8SNpuoyXG6eoeZXK6QSCbIRU0mC61jYps6XiA5MVNmV1fslzZJSClxNRNpGKBpG0ejBbiBJNhgzBlIppYrPLK1n5gIkDLg2o8te4I3rkm+XKHc9HntYoFvbGub9X5SrshZNUKBLiCmS8JrrrOBUsQO3wMzsywv1WgGkqJSLAQeHVv2wNBO1MI8xvvHWPjgPboO3cnR7ft54/QkodvEnJti+/Zd1HSdqhvyWH+UWlbjhXOLkLXxteJ/AAEAAElEQVTZkknjlkucOXGZrnw/6USUe1IxXruwyPNvXsKxDCxCdnTEeHpPF0a1SLEeoNen+T9sG+aYK9iTd6i6IYvNkEwsgW4HgEJlUwSJHAuBJC88kDUmXI/E+ePcsf1OXjw+DpoOCDS3waSI8vTRERZ9wQvjS1SbAf3ZBHs7HLaECoKA3qRFXPg3FByUUrIz73B+IcJc+WqltxCChGUQszQmPnbPCEPJ8ckCT+3IgJIrHYg+SoHSDN64tLRhYL/mBVxYrBOzjDUJE4DZUoOY5fPM4SFE4KEJRdLgutuglKLTlnz3UA/ztYCK65N2LDqiOjbBJ/YPl5rOh1Pr/U+g1RH045PzbM9fNQILpOLYVAlNCB4Yin+yH/0S8Dd5jm34IamIQSLSShReiwDuHs5C6KFv30tcKeov/i3hUiuBZyMIT1VYbrp87eCT/O2UQzpmkYlF6OjIcHmxgrIMzGoR1/PpyKfJN5apegGxSoX5n/6UDw9+k1fHFolHLM7Oldjfm2x5AGk6Z5caFOou9wxnmSg2kBJ29yQoN3zemy7zbD5O0hDMVj2WKw1GuxLckYL+D37G7NQUuZhN1QtIlebQYlkO3v0E7zkxpuohzx7s572JIgtVj0QsysFML4OiQf21FzFkSKgg1tdHpjOH7UfRtRJK09ACHxcdQ4AOUClRXgiY/fnPyPcc5//8yBNccvq4WGiSdkyihuDcbJG6F1L3QharLj0JCy2qrykgma4rnj81t+ZWVXUDfnJylm8f7KPjMyiYMWWA++E7BIX19y6UxD91DP2Bx1d9pD5XZMjeDovBTB+zFY9AKrriNhlbfeJk6qdFVwH3D8XZ051gothACEF/KkLG5ktbpzZt2rRp06ZNmzafL+0EzC2CEILKBnIXV5AK3FCtvIXdGLVQ4/ximZfPLbaCqaZGuekztlTD9SVRS2cw7eCHiv/tzcukbI2ewjLna3U+0DSePHg3kfd/jhmJEvoBtgZKSgI0Li9VubDUIKKD2+tw/zefofjBuwRn3yM+tI1yeit/c7bAUiNgSz5KsRHw3966zDf3dNHj6NT8EEdX/P39Hbz54XlOXZim0PQJPY+HDm9l2KvTrNf5X3/6LvG4w479O3lzosjkRJ2GhG0dcUayUe4czpExYfzcBbIdCXZOnmHL7l3MpdN8MF0mamqkDDBNnZOLNXIxm52dcS4v1zA1QaHm0lFfJm4Ktlkesl4lkIpqzcM9e57M8DDe2DkCNPxQESIo1j10GVL9xc+wdh5mMdfHX707gaVrDGe7ma75BFLy+vvneKhvC9tL8yRVY80LcPPMcazeQZpjZ685Ygp/foZq71beLEc5c7FVrWfpGrt7Uxztj2Pe4IuZEIKLRZ8PPmZ2KxW8eXGZrkQvA9EbP5eu/2MaFxc31/qfKzVohlkiX6DJ6SehEuq8cGZmXYCv7gW8cG6RZ/fk0W4yiaSrgCd25HlrosSZ2QqFuo8flrlvS57RvI0IfKT85Br9i57GX3w4Reh5pLWQB7Z38/KZWUa9ZRqLNQzHYUD5uDOTNCfGOZLKEU+OcGx2mZlaywfm/sN7iFkGb1xcImrqaELQGbfY3ZtmuebRlJJmro++PpPn+iU/PDnPcsPnnl19vDq2xPnZEo0QNMNAIXj14jJHhzJkYxYXl6okTI1OW9DrFxjx44jLF0j0dHNpBspuiCIEXUNIi0apSdzSOHnsNH1pjx4puOxqmEaM7xzs5/3JIucXqhxK2yjP4403xsknIjy7I8Pyj18gF7VwbIPZikfeVNSmFin+5IckvvVdHtrSxd9WGtSaLn4osUXI0GAPd2/t4NTJ8/Sl4gxlHXQBOgoNxVuXlhja34murh53oRuUfGj6ioghSFmgwoC4Af2ZKJcLdbQwRCiF0jSk0BAI+tMOb41VNjyOfijxA4nU154ImqZxbrG2aWfUpcUaleEM8U/WIPfVRtO4XFW8eWmRxZqL0A1G83EO9yfJmCGsJLUWE13M3flNkpdOE5kYR5gm2vZ9nI92oTdshmMpqhPjmEjKb73K0Qcccgd38t6lBRoNF8N32dOX51Bfkr4PX8IbH+PBnffz6qlJ3jlZRiqFpuvYiQwDmSh/dXyaj+YqREwDUwX4lQqnalUQPQxsyfHf3zqLCkO21A1Gtg7iLEyQy24jbmiU3ZCYbRJIxUI9YLpYxxDQ9AzqhQojXWmqtRIdkyf51uE9HJ+rU2969HQmeGJ0iDPzZS4t1TBWBLNmSg1sQ+O37h4lHlaR0rup5IONz9O7O5goeZyaqyCAXT0pFqs+719e3xlz5TfrQRr7YwJajVCwUNlYsgfgcqFOKmquS8BA6xruWAYR6q2u2Bu43iqliOAzGAMRN1FKgpKfShYokOD6GxdS1ANJwwvR9fU35o9myhzoTdD1KX77i0IpRW8ysun8qUKV7xzo5a1LS1xarBEqteojNBDTUCrEjcaJiNa1Vou0lqUlM5jJNBOFMgML59nXt5fxgstPTs9z79Y8I/kYotHAFA7D/SkShRlmXnsXUxd4ocH03DwD+8qM5OMcGczyw5OzVNyAp/d2Y3mSk7MVLEMwX3EJJTT8gNlKk4e25hlIR/lff3GR0XyCfifgpQtLPLW3l3uq57i0OIdjGWSjFn3pCF6oMAvzDBYus5zbQdI2+HB8kSd3dpFPxjgzV2HXcpn5n72ECgI0TSP10OMca9jMHZvi6P29NP0Qw4mhIQlDScTU6XY0+g2TRHUWYWo0FheY/bM/ZtcT32BC9DK+UKfpr5cB7EpYqJX7l6ZpNLB4bXyBphRYeqtL8wpSwQdTJZ4YTd10wc/H0TyPsLbx/Q4gLC2jS/nFyeTJkKQGyZS2IskbXNUF/JLQZEjOhI6uVqe0lF/+OrVp06ZNmzZt2rT5/GgnYG4RpJTkY5uXnZm6RvQmXRm9UFGqe/SmHE7OlpGYLNddXP/qE/7uniQ/+mgWPwxpBgI9kYR6g1BKXjg5zXO796OK8wzkB1hsSqTWOmU0ocjFLYTbhHKBE7EeXrZ3ks461DHo1W22dSVR8xV0TWNuRSZFE4KfnpyhIx1jem4Z4h73Fc6xpa+DJg7BwgUaf/0m5x96kpQVJ5VOMLpjC39xfAZhRxBK4gQeU3Mer3guv3ckT3NpmVMJm2QiysDu7QSvPc/Qlh24w8O8PVGiqiU5s9hAKo1Sw+c3D/cxVWyQsE3cpsvBdJRdhkJ+8AaXlmr4Ky+edS+k661XkZkuJmbO4waSihdiaRr9mQiqVCeRSXHCM6g1fYRtYC1NMxxNEGbz6MvznJ4pcmh0G+Lsh2uOTeC6RAe30Lx0Hi3ioIIA5bnI4R284GUYr9dXK+m9UPLBRAEvkDwynEDdQBJAajrvT25caQvw/mSRwV2fzlfmCgKwjc0jwKauoYlbW8261YHmEmzShTJXblL0IPsJrpi28nhoKM6R/iShBFunJWvluZ9O41s3ePNCAVlv0NFY4oH+OC+cnOLFc4vER9PkTYNER4762VPIUBK1DGqvvcju3HF23/c4y0YKI6hjxxUvzzXoTdpMFhtkowZ7+9L85YfTNIOQuG1wcanGsUmD39mZJFFfxk7mWa40+PDSYusEMCwaXkAgFd3JCO9cLvD4zi4mCw0qrk/WiTCS0Em+8zNiW7eTzPcTTE+0tl/XEYaJEgJkiPQ9DCGpnz/N0a5BYnqMAk1KDZfJYoNczKJhWSzUqzTrVQrVJqlhg7n5eapWhG4jwnzZJRFVSC8AAU6jgnH8Lb596EFO1ZLMVD2SuQgHh2JMFJZZuDxJaniUUKw9wIWaRzMUxFaSh64wee1iiXNzFQLZMjYezsd5aEsGR/o8MJzmLydnqM/PoYIAYVrouQ52bRsgGzU2lTKLWga2vj5DKYSguUFn2RVCpVZ9hNrcOEIILpYlP/polhCNhXrAcq3OsakSb40v8/UdHezIOyT1gMmiy98tQCa/j3zffnwlmKoHjM+43DWsKDfruHqcrjwYxWXqrzzPYO4YI3c+SJjrx8hF+Yv5EqcaFSLnzpGoLdN56nXuG9jDcdui7IWkExH2DzgU6i5+qHDMVieHHrpIqRDRCDOlJsWqha0ptDBg6uIE55s6d44OUV1eossImMVASkXTD3FMnXjEYGdHnJrrUQ8k5WqTiGOhLp7FmZ/h0cFBVCpKtC/GuabPT0/NMZSNYlwzDNxA8tK5BZ7cGkd8guigrXy2pTR2ZrOtjiMFx6+RHvs4hq4hBOs6yTTRupcEm8hnpiIGxiZX1P5sjN5khOXFTZy4fwmflc+SpUFn0l5vvi2g6Yf0pCLUmuvv734oafi3T2Q2HxGM5GNcXKytm3doIE3O8PnGaJrqSAapuOojpFrH1ggDGuNjyEwekc4BIFe6mmOmonrxLH19e7ggFV4oOTZVouwG/M/bDdwzp5h5f5qFRg2UIpF0SERMhnIxbDukJxnhL49Nr/osKiX4cKqEG0hSmkHeMZmrumii5f2lafDm+DKOafCzs4v8/TsH+dm5RZYWi8x89B5RS0fXNBIRAy+UXFyq4fsBqfffYWF/njcXazy5PUcnLn/y4+MEySzzqTzf+PoTuB+8hZ/r5meLgkUpEekcly5N8dtH+vmb49Nopk1WwkAmQrY4w6N7e6n99CxXBkeoFPKj99j3yFZ+MlZat68P9GfImAokSGHw3lyDQr3G+xNFig2fqKXTm4xga1fP78Wqh6/EzdR6bYi0bPRYgsBzN5yvp7NITeMTV598Cm413zR5m3kktmk9QxS99eeRY2hrxlObNm3atGnTps21tBMwtxA9CZNExKTy8ZdzYE9vioQpb8q6w9Sh2PDY15vi7HwFQ9fWmMpGTJ24bVJemWYZGiqeJ+q5NEslGq5PM5Ymf/EYD9yznx8sangr31UI4raBhsFWq0a8ucDWrhQvjJVIx2wuV5bZ053gH94zzHLNYyQX48J8hZ/OlhjOxYnZOuHkPO8vhWQSDpU3fk65GRIohQAy05f5QXSYA/cc4ZWxJWqGQxxFUC2jFJhCYVgBJ9+d4f75DxnZc5DqO6/QEAIzFieSyfBATGNwZC/PTzZwFyr0pBwGO5K8P1Fkd1ec0WyEhAhJv/gS4fIi48t1rlXOsAyN0POZLTeImDqNQBKErf/GFuvs7ehBjzjMzrb2ihdILE2DWplINoeMRKgWFnGd/LqBJqJxRFcPqfsewz93EkwTvauXyf69XD65gWQDcGa2zOG+xA3J0PmSVW3vjag2AwL52bSkhGHAvr4kE4WNu2B2didwdMWnLKj83GlsUpl8hSCUn/iKKcOQKOGqZ8JnYfhaDwTTyzXC2UmODEVZLlUZW9AJpeSVmQa/e+RuxOQYQoW4foBjakRNDdmoUX3rF9SqTYx4nNShI0gZcudwlskPptg/kOGHH80SKoUmBKamETV1xktN/uaSzhN37OV/e/U8veitzhXNQGkCR9eprkj1hFIRNTUCpUg5ER7Y0cMTgYv1ehHh+/Qmbe7c0sFPT84idAMlBAnbYEvKYn6xwK8f7qF55mX86Rm2pLL0PPwYf7bkMZhxmC03KTUD5poKOxLHEorlZoiIJWh4IQs1l60dMYTbJB4xsGRA1KsRuFWcV7/Pw5ksYTRJLHOEetll0cig6xtLh9mmzmpeRDP4+ViRc3NXq3qlgrGFKk0/5Ns7s3R8+BK/0ZHhTDTPpULrurG/E4bNZWrRNI6pb3ieHR5I42jhuliUlJKBbCuBvhEpx8Qx2Fj2rM2m+Bi8dnEOJQQLNZ/F6tUg4WSxwXLD54enKnx7fxflZss/rdDwKTSuLqM7YRGEkogTpRSAqyJ0dg+RsAx8NJoXzlI7dRJ55yPMVFKkpcZMoYaK2DQWFjBnX2R/pgPhxGlOF6lNSsSv/X2Qkt5UhEozwJA6thbDiVgsLBQo1CM0mx6O9DAtC9/QOTFbpVvWeGxrJy9ON7lcCUhGTKquT3/a4b4tOd6amuPeux9k+dUX6U8nwQbX82mcO09qZAvnfYupZnPT02i+4lL2YqRu4N6j6zquFAghMAlXZMQUQdC6Hwkh2NebZLrY2PD7u7oTRIRcd42M6ZLtXQk+nCxu+L39PTESlk6h7rFUu3o8+zIOX9uWwzY/bUj506PCgMP9aS4u1la9KFozwDF1dnUl+Ghyed33NAGWfvu0uWkq4LHRLMcTET6aLtH0Q1JRizuHMgwndaQMAdlKbK8k2zY695RSV6evBM0zUZNG2PqSY7b2ScMPyMcsTEPjzPlLSKkwDZO0pZO2NOZLdSo+EBi8dbmIH0o00ToXdU3ghhIhWoUknh+wVKi0fPJ0nflijKSto2uCmG0wXW7SkXSwdEHT86lXPboSEZpByPhynbhlUJUKEYYYXgPX9ZiuemT0EMpFhtIOwk7yfdnPrvv7GchGabw7jub6eHPTvHuhxshAJ9/dv42z5RBLF2yVJfb2dxA9+zYXP5Y8cMtldtkNnAN9vDdZpFD3yMYs9nQn6Y/rIFtdNscXXN4YW2IoFyduGxQbPnUv5NJyg6356GrXW9RqSZ592luKr+lE9h8hePkn62cKDXPnfurtxEOb25RQKn50en0X55M789jWLd7u36ZNmzZt2rT50mgnYG4hIgR8a18Xz59ZXNVMv2LCerQvjgxvThc4pkn29CQ5N1/hmf29nJgpM7ZSkTiUjfL1nZ34QYipa4zkYizVPM4su+TiXXRkOlBLcwihEenqoaM/y+ODWV650DITna8FRAyNb+3tp/P1D6hNXebBx75Fam8XMcdmvu5zaanGe+MFTFNjqeKytzfJ4cEMzSCkO2Yi9C4mLk3hmQ5uqFCilcQQgBw7w/LWPjJxm6myi6FpyEZlVf4kl4xil+a57EEQBJjLiwjDRGvUcM+ewOjswTv+Pj0o/sGO/VQP7WLRVShT8o3hTqLFefzZSTTdwN2xg8J5DW9hDG3FQNvQVyLlo3tY/vAkXZrg2kfqQEpKkSTxnn7S5ZafjqBl4q7lOpARB03TMBsVDG+9bEps1z7qr72EN3ERTQBSouZmWE5u2fR4hkpR8SRJZ9OPrGKJVqCitomsXT5uYX6GXSn9cYMd3cl15sKdCZv93XHCmzx3v2iUUnQm7E3n24ZG3NK4lfQhhADNbdKZiCAunKTcvwsReJiGzmKlwc8SOZ7cncQuZKlfvIAUGk4ujZ5MIRsBTjpKdv9+jM4shzWXF87N88SeHpp+SKkZoAnoTkToTtrMl1vB0hNzNR7b3cc9uwdakom6CQJSEZN01GKy0MALJIYmGM5F+e07BhjORBEyICnSNAeG8YqLnPzgJIe3DFMb7aTYDHkkD9nKHP7SAv27B4hkIpy44zF0FNmwgTs3jWxkqfk2HXGbhapLKBU1qagBC3qUnGUh/CbzFZe0Y5GN2TjxKP7CDIbj4M1NoZoN0ARNpTMrkrx4bgGzN8fWA3uoC3PV/PoKO7oSRFcSIwUPLsxvLKkyXWwglxfxTx0njuLORIqjyTQiDAiPzyF1jfyzf49f29fNz84usrQS8Ld0jQP9afZ0OhsaASul6E9apKMWxbq3bv7dI1kswnb+5SapBYpi3cNXGsu19ft1otAgZsBsxSe3SWeqpiRhs8bI1hQL27Yw+c47TDQtGsIk4ZikYxEKPoTxPF454GxTZ3u+m2ZxmqVGQNI2SNQL1AvzpG0T5/DdHPMCqk0Pw9AZiCiMZrPlA+E6JONOqypd01C6hXRiCNvB1TR2j/Zw6sRZvj7Uj5FKE0qFlJIgDPloahmpTE5072XfNzMY4x9RmRtHj0SI79rLWO9u3hqvMpyPo2tipZtx/XUu/CUnmRCCUmhwfKrCpaUamhDs7E6wsyOKc43ZvVKKoaTF1o44Fxaqa5bRlYywtzu24VgIw5DDfQkmC3WWPnbM9vam6InqGIR8e38nS01J0w+JWQZZG3R169x/OmzJ03t7+MWFxdVzLxezeWprB2+MzW84lgdzMVKb355uSSzlc7TbZl9XD8FK56ehrjGCvw6BbmCObCN8/81182xNMbJvH+cMh4hRI2635L/uH+1gNnTZtXcH5YlxbEPH93ymKy4d6Rh2PME5I4WkjKlrZKIm+ZhNNmZhrSRXHK+ODENCKQmUjgogYQlShEzWA0Y7Yli6Rn/aYazucXRwmKQ8TcxqeTxZhk616eGYOrnhYUKhM6w1WDw3hvnoHWzbt4MPpyv4bpH+rgw1O8Yvpuv4oUQVl3CrNWzLZN6F6QsFknGb39ydJfZf/xesbTtpRhKE3tpz34lF0ewIPXbIb2yNwVINFiYQszZadx/NeIqG1Hnv8jwAs6U6B/vSTK4kQAMpqXohaUuAgMMDmc/EU0wpRTCwBefQXTSOvbsq6SgsG+euB3GznZ/6N9q0adOmTZs2bdq0uZ1oJ2BuIZRSpLSAZ/fkKXqtZETM0kiZ6qaTL9Cqnj7YE6fqhlyaL/Ho9k4GMtHV37owV+TIUB5D15gqNqh6IYFU1LyQOUNjd+8wvXv6cO46RFM2GULRu7+L6bri4lKNuuvz9uVlkv2jlN59B+PP/ht3/tY/YDmZ4L2pEocHs0Qsg49mKziWQcOXCASvjy0jVEjCr/PMgV2E596j5oVYuoZSrUSDj4ZSgslig8GMgxczKS41wTFJWTpOs4zZqOAk04iShz9xEb2jB1UtI2wHIpHVF77g5PtETr5Pv9BI3P0Q3rlp6mNnVveT5nvkOvro3jLC0vhlHN3A1AVmLMZE93bspRpq6hyClgSKH0qEpiEP3strQZKte3OcaFg4po4esZGmiVIgrQhHDu8mevbFq8JxQsPZsRel6XgTF1vHSbWm43kYhTl03yYwN462WBvIFG188AOODGSYKjTWBXQ0AQf7UitVqJ8Nhgp4aCTJrs44Z+ar+FIymo/TnzCxuHWCX9ej09HpSbWkfj7OwYE0cV1+GWoZmxLVFUO5GL5fwC8sExnSUMUF8rleZgo1Ts1VmapG+Af7D5M/uoCoFFBBEzU1TkrTELE4qUNH+auzS8yWGzw42smp2QrJiMnOrgQRU6PphRTqHumoTbXptzpKdMFiqcbB4Txn5qq4ocT1Q5ZrLp0Ji0TEZHtHHCR0OCbnZwtsycfw+gaxoglEvUqfG+fViQr7h/Ls9RaY++FfI5tNemMms6feB9Miftcj/PXJeYYHOrnr0B6SEzUq4yVsUyftWCzXPULZqtSdIs7WI3dReflFbEMnauqoxSlcwyJ514Oo+WmEZbWCxNEMlSNf4/nTc9TqTZic5ly6l23dJh0Jm4VKKznSk4pwpC+xGgyueeHmskmawJufQ78iDVMpQeWqJIwKQRULdHRF+c6+TgpNSSAVCVsnYcjrXt9t5fPM3i5eGy9ycaHlUZWOWtw1nGVLUl+V7Wlz42hCoAkIwo0l3CxDI5Qhc1WXfd3xTTtTH+k0EP/9P5A9dC8p2aQxM0VTMykXy1SbOh3ffI6fNR1M2+P8ch19/1Hst35MtyaYKTVZqntkHRNsm0aum205h5F8jMLMPKXJy2goHA08Cf3debbnOzmpa3joyFiGyYUSWcfg8rxO/1AfhztsLmgGPz83hwwVIRpVX1J3Q+brAUudQ3z90Z3031HlxEKdnxQV85cbaAIODGToTjoYQq4rf4/bBjFLx5Ng6azeW6+lGOj8xYfTazq8Xh9b4tx8lW/t6SRyzX3AUD5f25pmb0+SU3MVQqnY3hGnL2liXSdZ4uDz63u7mKx4XFioYRoaOzrjdEU1dBmgVpbdZQEWwIqngvj8K5KFbtAIBQKFo6tNPTSUlPRHBc/t66S8sqlJE0wh0bfk+MnJuVV5LICOhM3DW3NwixcxbISUEguJJYD1p9V1v6eP7kI/f7p1Lb0GEUsQ3bWHr0dT3D2Ywkej2PQZX27wH18Z43/aeZRsqcbSxGWutIyLeJLYw9/k3KxOTzLCkYEMxYbP5UKDhhuwry/FfLGGtriAm+2mGfq4vo9j6Xiez3ShQk9XnpIbcnggzd3DWQKpGPZTzP35BF6ziW1olBsKPwhJxh2q+T7mjl8gqUmGd47w1kyN149P4isNzTSZaShOz5b5+s4ufu7ZbB3YQrrHo+5LlnxIaRrm/BRKnsdfmid68CiusJDB1bEXj5hk7rwX14njNOt4L/0If2766s7SdaJ3P0x1ZO+qN5IbSJRqdby+fWkZBfihwlM6O7uSFJsBUmn0xD79s5svNPR9R4lt2QGlQmscZnK4Trwtu9WmTZs2bdq0adPmK0c7AXMLosmg5TVhANyc7NjHsZTPoyNJCn1JmiFMmjpn50oY4ormg6A7YTNRqJONWgRSohTommA4n0CPROjtSDM/N4tSClNXfDCxvKZS/FVi3PPN72DXy0ws1/FFnaNb8rw7UeKVC4vkYhaOZbQqjkPJM/t7eenMHJUA3ri0zK8nkyilqPsBcdug6YfIrbu4sFDjse0d7OlNcXl6kYyqIKVEFl0ECs2Jsr87jjx2GWPbLpSSiHiC+P47qI9fWL9fHQdVLuBek3wBkKaFmJtkdP/dqKW5lib58Ba8PUf5L2M++/sO8ms7RgneeROj0SRIZFG7DvK2kUeVPaZKLkf3jXBqukgor0YZRvIx9o3miPQ+CcUlCENEKo2wLCp/9t82OFqKDr+C5YUElr0uWpGNWWQiGjd6QvTFBI/u6OK1i4s0VnwkYrbBA6N5OiN85rJFhgzodWBgS6Kl9R+GqFuo8viXYSifJ3d28vrlIufnK/ihImYZHBpMsycfaRmk3kKoMODu4RwvzE6jpzLEa0vYGgi3QncmSalSp9Zw+Y/HS/z24W9wjz+FeuWnqEwec3iUyD0PMZXp5/T5CYZycX5wfJpyw+fB7Z0sVJsEoULXWoHqzoRNV9zA1BS5qIFumnz/g0n292f48al5MlELO1RMl5rsipgMZhykklxaLOGFiu2dcfzQx48lIZZkUJq8PtckXi+z8Pz3MQIPy9ZYqDapNX3sSgnn7Zd49J5vcta3+b/98CO+89Ae1KUiF5dqDGWjpBwLL5CkHYOuVIQfVPq5+4GvEzn7Ab5bxpCK6N5DaCOj2H4TbWAEmevhREnwwUSNhtLQU2m0TJ6sZTJXavLU3h6WKnX60g6dUR3zmvPXuo7PkVJgWNZ1h5QwDJRS6Monv9pUcWPX95jweXxriupQGqnA0cEkaCdfPiEJQ9GfiXJ+cWMZrMFMlI8ml4lbRqszdW8Xz5+92pmqa4Ld3Sn6mhPUpi+iGnW83i3E9h0imu2kVvFZVhbvFjXMpEVnTAJR6O2lcs+TVN95DVmZRtM1vIGtGIfvojMVRX/vZzyz/0H++PTJlnQX4AmNrmycB7tMgrdeZsuOPZwpeswWqkjLYW9XnPkLF7hYbzL0zfvoj5voCJpKMF6o410TzD88kOHd5QBbRIjkoqS8EghBLmaxNRclCCVzhbVdKUpojHbE+PHpeYo1n3zC5o6BNN2OQq0EUTVd553x8obyeotVl0tFl10ZfY33gq4C+hwYGk0B3PD9wsZnNKmxI5NGKUUYhl+Kj8QVNE1jydd552KBiUIDIWBrPs7h/iQJLdjQb0IphU5A5soT+Ios5UBU8FuH+5it+tS8gFzMosPRMZUHfLVkbZpOnMg3niU8+xH+xXMAmMOj6Dv20nDiaDIgtbL/OlM6SStOLmrylxdr3L39fvbsczHcOtKKsJTpZPdQD6NBkQP9af78w2kKdY9czOL8Uo2DfWmWy3WCdAfT8wW6kkmWqy5P7unhw7FZjIjDeKHOQDbGsakimqbRGzc5WZbc/41nke++jrU4A42Q7I6dWAeO8sLxy5gaKF0jkkgwu1AFBK16GwFCsFz3EQg64haXyy6q0iow0JUkJRV9skri8jlUPI7YdwdVkSBvRqme+ohsV56eu+4h6OlFAMEHb65NvgBCStxfPE9HJsvujMW5coAfSi4tVulNOfzm4X6agcQydDQU86U6v5grApCP2zy9p5MYn+65J1SKRjQB0cTVie3kS5s2bdq0adOmTZuvIO0EzFcBufKib0B+JEHcUJyaLeOHitmKiy7gqT3dvH5pmYWKSyZqcqg/TdMPma947O69ZlGwGsy/QkkajJlJmr1buLRcw1hw6csYvHR2HqlalePzFY+uhL1iKF9ke1eCQtUkWJqhkU1gGga+6+MJjcF772R+YAvf7jPJRk2CMCSbirM4b0KlxJUw6I7hTgaDRYyefpw7HyCIJhD5TsIzJ5CN9X4kVk8/3sqL/LXoSqICn9rsNPbjz1AsNzhHlJlFhWPqVLQIPzeSWEefIiIk86HBibkaT+yMMV2ocbAvxUgmwuGeGLMVDy8M6Yzb5CICTXo0IlHojq7+nlMpblhBDBAdO84Tdz3FD+fBvSaYFbV0vr6zE1MFN543kSG7sjqD6R5KTQkCMra+4jURIj6nquDwVjd7uQ4RPB4bTnDnQApfKhxdrOyvWyv5coV0VOeRLTlUz1EWfvp9nrrnCZ4/NUs8aNKRyhBYERKZNKPbh8gaXbhd3ShNR2ayNCIxTk+3JAnjEZPLy3UUsFRz6YzbnJqrYOkaApgqNdmajXKoL83C/DI9msfbc4u8USzzP92znfGiS7np05WwqbkBf/LeBIYm+K0jAwymLDJGS8ZL0zTQNDICvrW/B3n+DPO1VsA3YtrUQx9LBiAljflZtmcs/r+vzaM7Ed6ZKPLrB3o5NlVituzSGbfoSkQ40J/iz96bbFU0Zzr4nW98D80vUf7wbcqFJdJLb9CZjFKv15lND/OLC1PosTh6/zChEAQKUGolKR1yd5/Tqs5Va4NE2YhGNmazXFtvKhwxdeyuLpqGAcH6c0WLJwmT6U91rFUY/FLPhDY3iAy4f0uWxdoscdtY441275Ycy9Umpq7Rm7SQMiClS57dk6fgKrxAEbN00jZwoo6eSMPiNIlaEc9JorbtZdYZ5NiZi1i7Epi0uh4eGs2zUPf5388GPLT/cUbuVjTcgDEilOca3ItHbvsROP0hT3drlLcOUXZDkqagyytSfPPnFFyPwV1Hef7cAhgWI5koWS1grt5ES6R4b9HlW51xntrXyx+9M7mafImYOveMZKm4Aa+PLfLcoX7OThcYTkcw81FcP+DVs7M8e3iIS4smp2YquEFIJhZhMB9nstBgasUAp7YUMLFc48k9PQzHRat4ItQYX1pvuH6FU7MV9uRzhBuMjWCDab+Maz1lvmyWPI2/+HBqTdfKiekSl5ZqfPtADzFx40UISimiwmdLAoQwUWr9deirglKKRiSGfugezL1HAEVo2nhhuOoHcwUZhvTZgt852MOfvDvO6+NFXqeVGBzI2fzDrRGSuuSbuzv54/dm6IhZdCdsmkHI2bkKY4s1ntmWZnhbnrPjc2QTDrlUjJ+fnIJIhELF48Bgji2dcX5xfpFCM6QzanD3cIY/mfHJbHmA73wtRmGhxnslxULRQzcsXLdER1eWogeRwjyZZIKFch0sm2LDI2LonJgu8vWdXfznVy8Stx1k6NKTjJCpL/Hw1izuayX0J3+LP12yGS/XGOjYxzfufYiUpfBWWkCdRg2vUkLvHUSVi8hqGT0MUMuLBOUi3it/xyEzxejATt5QaeZrAdOlBjOlBvsHs7w/UUT7WDJ/sery9kSJR0eSX9xBb3Pb4EpBI9hIqvKrkSi2DI0H0+vfdRLSBSJf/Aq1adOmTZs2bW4L2gmYrxim8nlwMM7B3iT1UDFZ9nnlwiKzlSbDGYd9PUkqTZ83Ly5T9QK25qNcLtS5Ioil0/LKWDW5FZBLx0h1pPivf3eKpw/089bFBSpugGMZKEAqhUKxXPcYykaZrzZ5eFue0zOScthBxYmwbecIanAbM7lBXl4KaSz4DGVNmoHkzHSB794xRKE3ypkT59BVwI5MhI7lcbh4Fn3fEdyRnXia1grw7rkD5STRx04i56ZawdVcB5HdhyhPjq/ZHwJQC7OExQLxRJpZdN4em8fzA5zubh7fsw3H0nnt/MLqdzQR8OzeLvZ2R9H6IggZoqRLQoNESqwETsJN7UJUxEGLxpD19QErWa8xQpXvHtrOZMmlUPfIx2z6kxbRTappr4eUEgeJs/o+cGvJaN2KSBkSEyHoV/7+ctfnenhKke/pgIvL5O85SvPDn9Kz7RBTRpqSZtLR10H/QDeOHmB1D7AkjNVzSNvgXIpaBq+NLXPncJZkxOT8QpWGH5K0Dfb1pdkW8flvP/sQMxbn6YODzJabjC9U+PmFJTrSUWpNH4FiKBtFAIuVJnf12CgpqSmTc3N1xhbrWIZgX2+K4c408VwMpUDTBcW6h7AjKNG61riui4jFwTApNQIuzFfIxyx2dCboiNvs6Izz8oVFhrJR7s84aELwXz6c5+4Om9HJGcJKiXzPBgGkaJxAbOQ0rDaVRjFVwBM7O/j+idk1AfuIqfON3V2EjiR610PUX3thbYDQMHDufYSmaa8LHLb58sgYIc8d6OHssstrF5cxhMb2zhjlhst8uckTu7pI6uHqIdNkQM4ETACJDEBk84hcJ1oYICslzHodlma5d+d+dj/wEBPZXvRYgs5ojoobcmq2yuO7ujkzV+F8STGSjZKwDZbqPieqgntTUYLlRRrHPkQGIRHDotp0qUlJXyZKPmWjLNi/pZutvTlkeZmzl2YwegdQ0TgVN8STkLQEh/uSHB3MECqFIQQzxRrTFQ+pYKbcJGLqTBevdgDpQmCLkHv6ohzojhEqgSs1/vz9CQx7bUBJKnj1whK9B7ow8dkoHWhoAscyCMJb+AL6KdF0nffHy2uSL1eougFnF+oc6bY/kdzSzd7rf1UJw5BQ06/8sennfKW4rz/KkDPA+/NNys2AkZTFnqQgl3GoK0XNDflwooB3jaFR1GyV9JyeK1OtuxiLs5w+U0bXNY4e2E5BizJXqnOpWKMehHTETJJRm7lSHaFp7OtL4waS/+eJIju7Uyw0ypycKbIn10068Di6rYfpaoWJSolkVJHp62IuNDACSdxqJX/7Uza//7VtTBQbWIHPkKgxIHUqFy9QefQ7vCeTTJddDGCm1OClSyW+uT0NSKQwuOCZvC8GafqS4d4t7HBC4s//KWFhCQBVKZNMWSy88APufvhJfmpmafohHQmbUjNEY+P9enauyp0DKbo+wXETQiA1HS9s+f9sVnTU5vakEcgNTegf25b/Etbmi0e4Lks/+cG66T3Pfbslgd2mTZs2bdq0abMB7QTMVxApQ+JaiGOYjAUhlqFxcanOmbm10iNRU8fQBGfmKhzMaoRhiAxDDvQluTBTIKxWUG6Tns6tnJmrIHUDKQToOoEU1LwAU9eIWQaGJlcCCgoN0FAoJfENi2Yiy/g93+L18SKnTxTxQ0XdCzi3UKU7bvHk7i7iekAiY7HznlHk9ATe6RMI08T8+rcIO3vwNA1PmJxeaPDRdBk/zNA39CBH70uipORSNSQhNfoTOTRvBm2lqlT3XPxSAQAzYrG/eIGeHUk8zcJUHp05SSUSpTfex3S5VRXdl7RJWxKClhnqx8Mkvyxw4tkOkX2Hqb/5i3XztGgM0dlNXPjsyuiIbBSlFEr57dhtmw1pWDbGrgNY9SqJ0V0kalV6TBuVzuI6MUIZoDaoSpRSMpRxePsSVBoew7kYxWZAqRkgpWJPT4I7hjLYhsZwJkZtcYHFumRai1MtBJx8d5xH9/QxU2niSJflElh6jJQpuKLWNVWsUQtT+NLgL4/NULsmcXF5uc6ujMn9ozvQL54mRGBoAh8N4cTQDB03lkIZreuSY2qYQhIGPgulgLlihd0dDklT4Fga708UqHshQinen6+zd/8RGr94HktdrZhOB1Ui0QhBPLlm4ApNoCPoiFmwie69UoqsGfKbB3uYrfoU6h5Jx6QnbhHXQ0KpYOtO4pkc/tmPkKUCekc3xugumqnsqlzTjaDpOuVAww0kjiGIG5t7SrT5ZCiliAmfIx0Gh7oHWKgHTBVq9CXjPDqaXUm+XP+iK7OdiHwnQtMwsx0o3wddg8Cnxy/QM7SPfEcnFybmmK01ODlT4sOpEkIIhCYYW6yRjJg8NJrj1GyZo8Md5IaHWX7rdcwgwLQCYpaBLgzcUpFsdx4tYtKRsbhYahIGEVT/yKo3US5uYQmohJKzc+V16xsxNBxLp7HiuXYt27sSpM2WpJcNaLrGR/M1vFBu+KBYbHhUPEXWhKimGM7FOD1bxtAEWzuThMB82SXl2BzqT6E2M1C6jWmEGhPL67ttr3BuocqhniibVmO0+UzxDIO+ngwj6RoiCJC6jufEqa+MY11AzDbx6t667xZDjRGr1XEdSkkoJQ0v5AfHzyMNAyuRIhtXCKXIRiM4Wsv7bGtHnNPzNaK2xUShwV3DOe4YzFBt+Nx91wDd85dw7CgfxJJoyQy+YbFYbrZkw0LJtnyMMxOLjI9Pk44YfP3QFgYTcabcXl4L8syVXeTHpPnGl6oU3TQJ0+CVyxVOTi4jF8oo32d2AY7p8MzdT5L66f8PwgC9owe/uMxw2ia48D5PPvwsJUyGsw4vnl/etJ3SD+WmvmfXIxQGF0s+708WqLsB6ZjJHQMZ+mLihiV0P2s0TaOhdGq+xBCCpEU7KdSmTZs2bdq0adPmC6WdgPkKExES23d5cDjN2emWQabQdNSKNNUjOzqYLdWQQqDlo4RhS7aq313iG2mXl+eLKKW4NFvEiMdwTA2FYKrscmAgixpvvcB5ocS6Yl6PoDsZoekHoGA4G8UxBPO1gHcny/gr1bKWoZG0DaZLTQp1H00ZSKWo6Rba0Da0kR0ANFZkSHxh8uMzS2u8aSqOxY/Ga0wWGji6wtQF3xjcQzB2if6kjY5EeS4oEJaFMbQVOX4Bp17HWVmG6u5A74rQaUNXZ8u4QangU8VTpJTI0T04YUjz+HsotwkIzK4e7HseoWFHQamVxMuvXtCqzWdPIBVBJAaRGGQ6r874JUH/fESwqzvJufkKdw5leO3SMgf6uvjRqVnqbogmIO2YDGQcnt3TyczsMsuV5ur3z82U8C2bqg+6bOnZX4suBIZu8IuLi2uSL1c4s+yyrXs7vePnMJQkF7eYLTdRKJwt2yhFs0AVXRMkIwaoViJXoYjbBilbkLB1hFRYho7r+oS1ChUpeTuR5VuPfQ3jzR8RNi1ENE6ivMBDDzzC340VAdCkRDSqyFKBI1u76Jg5j5bvpGE769YVWkH7CD7DcdiSjKxUtvuruzlUUM90oN/7WMsHSamWZM5NJF+awuT1iyXOzVUIpMLSNXb3pjjaF1/jSdPms0FKCbJBhwld3ZGV625wQwlv1zCJPvY03usv4U1dBstGmBb2zr2IfXfgBWGro2VqkmW/JVmJ76E0geU4VJoB5abP+HKU/T1JXru0yKOdfSRzOZYnp8BvjRlNQDQaoePQYZaUZKEaXO0KuNKhI+BgXwoZBkRNk5htrBtzmpIMph1GO+OcmV4GWp0qO7qT3DOYRMm159fmrkctrqhYShlyR3+KiUKNrZ0pXji7wFyl1SXrmDqzxQZf25FnR0a/qUTkrY4mFJq2ueSOrgkEqi0X+AXiS4VvR1lt275mIEd1xa7uBG9dKhBccx4KJXEbTQ4O9vHqJYUIA9BankW6baOsCPm4hbbqndiSFexKOrx6cYk3LhaoeK1n2pfPL3J0KEPM0jlVtujcvpusJ8i5Sd6fKJAMBUGocCydmKlxV2+Mk2+8QxiELAG1LDQmjjN95ClmKuvlLqHVgdYIJM1QcGK6BLqOnu0gWPGAaVRqvDKn8/TIdsTMBCKVQc1OoQFWZYmtlkcjFgHlMZSJcHGhsuHvZGMWEf0mD4Cm8+ZkjQ8mCquTal7AdKHBIzs62Z01PlFH2KdBaQYnlz3evDRPzQ0QQF/G4cGtOTLGL0+0t7lx0spdJ83VpeobynVZv/QO06ZNmzZt2rRp86tFOwHzFUUTAmPsFEN1CI00v3W4n3cnihTqLtlkjH39aXw/ZKnqsrc/v/rCZIU+jRd+RF+jxnOD22h0DPJq1cQywGxU0ZREF4Ji3Wc4F+PSUg0pFfGIgS81NKG4dyTH+GKFnpTD17bncSydP3pvlmzUxJeKiKETs1uBmi25KJeXKjQG4tgrWQ8p5boXuNlasCb5oglIRW3+7IMpopbOcCaCHyreIcPRex6jfPIdsjRAaOgdXTh3PkBj4tI65V6hX337/Cxf0jxNR9tzBGfLDkS9hjBM/ESKOqItU9TmC0OTAQ+MJBnIOJyZq/I7Rwb5/7w5jlKQiBhkoxa6gGYg+eN3J3l2e4Z4xKTabAVqJ5Yq3Lcnw+WlOqYmiBga12Ynt3bECaTk0uLG/hBSaJwlztbdB2ic/IBsxEBqMfy+Lcxtu4O5UpO9vSnqXoAp5GrwSwD3bMlhE7CnO86pmTL9SRNPNfHNCDoSd2kBsb8b++h9mKaJM7SNZq6TbYZJLBHlg8sFli+NE1U+h0YzDCyeovHhGHoyg/PEMzQisevuu+sFkT6pD5LUDJ4/u8zla/w0Wr5ZBbwg5JGRBKrdCfO58UkCg/VIDPPRp4lViuB7EInixRKEUqJrGu5H75NI9/LB21MkdZ2CBmiCpuu37D00wbmFKo/v6ORPP5jk4oLk//qb3yP10x8wc34MoSCXSdB96BCFpSI57ziP7X2EX4wtr5reRy2DB0bzdEValiGOCLlzKMuLZ+fXrW8+anBnX5x9nU6rw8rUSJkKGa5NvkgpGco6vHlp4+3OxWySJqtjMmUEfPdwP39+fJ5iwydi6qQdk3TEABXywpk5Oo/0k9Z/dRIwtpBs64zz3uXChvP39CS/tIr/NusxVMBDWzIs1VyWaj6Vpo+mFClCdqQNBsY/5Im9vbw4nqDshpR1hx0jDvMVl5Str3k2i5g6IfDueAFDg6Rt0AwkgVS8N1HkNw/1kbZ1CH2yOvzOoW4O96c4Pl3B1AT96Qi7O6Kcf+d9gqB1jliWQVbWCQoLJGrLaOgb1vpoovV7702tdLkpUMk0upTI5QUQgsmZRep33knHnv3Ux67xPtQ0WrZnrW0ZTkc2TNYC3DWcxdxEnmwzCr7g2OT68aCA18eWGEr34nyBHWFCCM4VfV44c/VaqIDJQoO/PjbLcwd7iN6ET1Ob66O5jXXSXIPPfmtDua7BZ7/1Ra1WmzZt2rRp06bNLUE7AfMVxW5Uqb/xMlkrgtr3AAuhIKOH9Hc4+FIyvljB1leqY7sSSLcEgF4qEBZbutLGueMkx88yOHo/r44VeXC0n48mlvn6zi5+fHKWr+/qZjDjMFVsIGXIof4sD27N4ehwsCdGxhZosvUCHDdhNBcBBEKAlApNtF54Q6muW0Oq6zrnP1bB15GIcHquNa3uhfhSYAnFTDXgBbuHA/c/Q29KYUkP98xH1MfHWt0w0ejqMrRoDJnKfsZ7/ipSSpp2FOzoL/9wmzafE4YM2JbS2JrOMu9CKCVdcatlguz5hFLRm45ybsllue7y6M4ufvDhFFIpXD+k0XAZycdQmoalXa0QTkRMDvcnkVIhr5NUbCLgzgeJbd8NrkvCiVF00miNkEFd8Og2k1NzVU5Ml2j6IdmYxZ1DGfrjGlKGZE341v4eXjs7x9TZcQwFuUyc+7dlSZ94lUapgIhGUdE4QWcvKgzpdQTDuSaVhWVMrw4n3kUFrSBMWC4QnvwA7Y4HvvBK3WVXrUm+XMvp2TKH+pKkbrYiuc3njq8Ufjx1dcLKeWM268hyicjEBI49SvHyIkP5HDV0pktNTAGpWIS+VITpcoO6G1APJH81rnh0dCc79h6EMKBZq3Pxwhgxt0L3gw+wM2/Tl+6h1Gz9TjqiE9VC5EqwX0rJjpwJ2zt5e3yZqhugCRjJx7lvJIMlXSydFZ8ruWmOIGvD/v4055fXSjaZuuCB0RwG4eqdWa10e1XqDbbkoggUArVqIi8VjBeaZDutL3xcfV5IKdnfE2dssUbxY7JWvakIIxkb1e5au2VQSjEQEzy3v4e3LxeYrXjYtSI7HdhvlTCOv0mnZfEbg9spdOQRvTH0VJrvH5+i/rEExaHBLKfmKghNoKRqyZuZreSGQHBmtsK9w2mUap0XEeVyOK9zsLODy5Usb19a5PjJC4TVVuGQAO7f3kNs/B2UlOSLUySNAYrB+g6r4XycpC1WO8YBJAIyOfRECs1tIKsVVD5H/fWfrN7bAKzeQfxYcjWZFNMCfn1/N78YKzC5XEMqSEZM7h7JMpLUUermxur8is/URjT8kGIzvMaT8PPHw+DtS3Mbzqt5AeNFl91Zvd0F0+YrgXBdwsZ62UzdiaJse4NvtGnTpk2bNm0+S9oJmK8qhUWU56E8j+w7P+WxIw8R6UpzfHIZrVknms5gJxM8ur2TwYzD7GwrAaP8j2ln+x55v4zXdPEW53lg2yiX6yF/7+gQ44U6vckIj27L05e0ydlq1TcFuFooryTb8nHmy01apXwr0icr70P9GQdHB3WdQjztY53shiaoeVe/IK5J4FTdgDcXBNuG+4mLALtaRV08t3YBuoFz36O4tnNru7C3afMZoJRCKB/fF+SiJlPl5hqjeUVLQ72GyeLERZ47PMDJ+RqLVZdqrcFzR0cxdI3j00WCULGtM8Zo1iGmBUih05V0mCk1NvztbR1xvCBAxVKw0nRi4dN7RQVMhhzpstjT2UUoW4a+ugpR1wSbu2zBc6NxFmQnCEG8vIB+4ngrqXplMfUaYkUzSdc0gvdfx5iZ2jC1642dxd53B675xb6QFuqba9JLBRU3JNXO1942iBX5ueCtl7nrm7u5NG+xPDdPZ28XJO2WUbUQpCM6U8UGdS8gHbOpaBaFxSofvfvS6rLSjsnIrhG00V24QYAD1wQy5brblCZD9uQMtmS6aQQta5qkCSq88YSAJkPuHUiwvcfk9fMzND1JTyrC3p4EOXO9dE8gFVKCtkmFe80NEOJXK8gTxefZfV2MLTc5M1dFCNjbk2QoZWG1ky+3HEpKeiLwrV1Z/KaPPHYBe/I8slxszXebGOeO0QFYhVHEo0/znQM9nFuoM7ZUwzJ07tzaRdoIOT5VIBezWLhGKqx1h1GESpEwxRq5WqUUIvQYiutEtub5sFFmyUuQjlkc7IzSPXECteJJGDn3IU//2hH+9kKJwkpyTwAD2SgPbc0QeC5b8lFOzV7j9aQg1A1UNE7eBGfq/JrkixaNYR29f9UT58o6pbSAp7dnqARZQqmImQJbrCR0xeYSexuh/ZLP39zSPj3NsOVXtRkTxTr7OtIEQdsPps2vPmGjzok//fN10/c+9220dgKmTZs2bdq0+dxpJ2C+qlwjY6N8H+ON53m4q5fDfdspyjiR/h5S2SQxXa4GLQGIJUDX13zfOPkeT++/l9fnXE6Mz0Msga0JHhjJUHN9duRsbOnCJu83Ukq25R2OTZtUmmsDFpauccdAGnUds8wwDNmWj/PR9NUX0UozoC/tcHGpRsw2MDXWGI1m4zYRTSGlwhveTjydJTh3Cr1ZI5JIYWzZSTOV/ZWp1G3T5kZI2DqWkAymbNy4jb9S2euYOl0Jm4gTYSGSY/nCDN0xk+HeBCISxdIUW5KwLZ1FKQEqREofpUCogHtGsvz1semWUf01ZGMWgynrl1aJSymxkK3ojWRd0kQphaEL0mffQa5U9338M0ZXL82V8SyUQl0n4KLCEPElVMQ65vXbWyxDg5uUhGnz5SEjDhgGslJi+/wp9tgpFiIxJAFVpVOrNXCcCPv7+njt4iIKqLk+uwe6uRw7RD7TjRg7RdTUGDlymNjQAA3dXL0n/7KqbSklNhJ75UnvekUMm6GrgIP9HXRbPoFUGEIhw409cqKGhmPpNLyNf6hn1TfpVwsHn315k32deQQKGYbtzpdbnTAgGdapnX5v83PS91FKERcBR7ptjvQ4CCHo6kwzO7dAVyJCuRmiCcFS1SWQCk2sdH8OpIgQbJyKlCFdNjwz4lCtFTGaNcL3Z9d2m2g6nabPd/Z3sdwMaQaSuGWQtUGseDX1xE26UxFmS821yxeCew9vJ1FPECCR9TrG4Aja0FYaTnxjmVsZkNBoVT8pNu1i+WV0xk00sfH3Y5ZBOqLzqUwUbxJdtDr2/HDjDYpZRrv7pU2bNm3atGnTps0XQjsB8xVFpLMgtFV5EAA1N01ibpqEYRAb/W0a+Ei5tl7Nj6ewt+3GPX2cEI2GLwmDAOOdl3n60B1Mjo4wXw8IQsn7l5cYyERxxCYvodcQ0wKe3d/Ne5NlLixUkUrRn4lydDC9Uml7/e93RTVGO+Ocn68CUG767M0niNsGXQl7zQunAO4ayrSq6IFQKeqpHMbdD5Pq7GR+fp56ELQ7X9p85Uhbih1dSU7NloloELnSWSZD7hxKoSNxkjFUMk5JE9RQ9No2vUkLKf1Nx0yPo3j2QC9vXS4yW2pgaBo7uuIc7E1g8ykDlZpG0de46Ap6d91B+M4r2HrLWHn1I4kkqqtvNdASAubwNvyFjaVJzO4+Atv5wv2YclF90wB2OmqRsbVPFkVv86Xgazrx4a0IJ4rz6o/49Yee4b1awPnpSaK9I4juOPu39nBhvkjE0NE0wVAmSr3h4VkOpcEdJLftpaGBlreoKsVyUzFfdTF1je6ERcqQX4ixvQoDNKWuey+P6ZIjAxleubC4bl7KMelNmr+yiQkpZfuZ4TYjiEQxO7rxV8zrP44xsg03vNppGWg687WQs+VFtNBnf3+Gi0tVOhyddCRGKBWaJnB0ONyXQMrrd1WoZBqjuEhYWu+ZEtl7GD8Swwx9umzABgjW5C4s5fPNnR0cm61yaraCH0g6kjZ3DWXpcRSNaDdGdz+aEPhh2DpHP+d7WspU3DWc4/WLS2umawIeGM2vSCV+rquwhpgu2daZ4ORMed08AezsjBNep8CrTZs2bdq0adOmTZvPinYC5iuKl0gT2bWP5skP181z9h7Gu0Yj+loCpYgcvhddtxl7820a9QaaYWBv2c7x1BZkM+TCfAk3kOTjNncPpdaZ+25Eq8rQ5+HhOHcOJFFAVFeoTSptP46uAh7ZkmEkG+PYdBk/lDgG/J8e2sobFxeZW5E/SkRM7hnJMhDXViWMrnDFOPuTGmi3aXO7o8KQ+4dTWIbGyZnWODI0wWhHyzvCk4qEpXFpqY6uCfb2JtmSsX+p1I6Skk4Lnt6eoSEzaICjyVbS5tOsr2bwwVyDNy8uIRVsS/Wye/sdGGc/IKcHaIDVN0js0W+yiLZ6TZNSog1vQzt1DFldG5gRhol18M41Mi1fFDEt5PGdXfzo5CxecDVK5Vg6j+/sxCK4jhtWm1sNpRTm1p0knvwNKt//E6J/96c82N3HndsPouVqyKE+jnsC2zDotwUPjnZQrDU5PVNaPc4x2+Bb+3rwJLxwocjYQnV1+brW+s6unHlLmL2HYciejgiKPO9dLtDwQzQB/ZkoD23NEWmfv21uIXwE0cP34P/0r9Z0dQPoqQz0Da0m7WvK5G+Pz7NYdYlGo9TrdbqTER7d2cu740sUai6G1urqfHBrjg5rvSzgx2kaFtGvfwvvrV/gTV4CKdEiDvbew6gd+27oWTSCzz19UQ50x5FK4RhAGKzWVn3h0loy5EC3Q0eilw8mi1TdgFzM4mBfis4Iqz5VXxRKhtw1mGKh6q6TirtvNN+SRm7nTdu0adOmTZs2bdp8AbQTMF8xlGZQcKHiBTh7HqBjcAf6Wy8SlAvosQT2/iPIoVHC6wQfq6bD86k99H59GCf08HST457NeNFDK5d4Ymcnji7ojhs3rYEuw5DIisTOzRZ6m8pne1pjWzZHqMBEolTAs7tzlFeK8+OWICLCL/wlsE2b2wVT+TwwGONgb4JmILF0QcoEGXrYAu4aSLK1I07NC3EMgQYIIW5MxkO2vCvgsykWn65JXh+7Wml7ruQzF93CrnuHSKZ0cnELP57E7O6BmZk13206MaJP/Dr+8XfwxsdAhphdfViH7qSRzn/h3S/QSgz1RwXfO9zHRNGl0PDIxyz6kzYxLWhLpdyGaJZNcOQ+ErkO3HdfJ6yUiFWXMAf6IR3jbtPmjr44ugANRcFP0hm3KDV9OuM2/RmHhhdyYsHFNk22dSYZX6rihZJQKl46O0/H4T7y5pe9pS10FXC4y2Z7voe6rzB1QdIAViQJ27S5lWh29BB/4lncD94gmJ8DXcfesh1972Ea1orJkmbw0pklFqvumu/OlpvUxxZ49kAvbhAiaPksGYTIG9TwqjtxjIefJFYttxInkSi+E7upQqAwDLEJW1mFW+DRVpMB/Q4M7MwSKlZkC8NrG+6/UBx8fn1PJ7O1gIliA8fUGc44ZCx5U4lroemUA43lho8mBDnHIK6Hv5Kyim0+GUIIit7ase8YGrb26W9+rhQ0gvXn2kbLNzwXmut9F6/fw/r5sNG6VLwGZiiR3gb+TBGHwGr70bRp06ZNm19NbqkEzD/5J/+EhYWFddMff/xxvve97/Enf/InfPjhhywuLpJMJjl69Cjf+973iEY3dyX+D//hP/Dyyy+vmXbgwAH+5b/8l5/5+t/qNDH52dllLi/VVqtQ01GLb379e/RQR+oGrmH+0iDfclMytlhlDIArUR8XSwCEJC2dnkgIX4LUiFIKwoBrVaY1FZDWAZ1PpW3dps1XBRmGxERIzLzyd+v/DUz+7uQ8k4WrL1PZmMUTOzvJbmDK/Xmi6QYfTq+Xbik3fd5swjnX4LnuLIbauAJYKUU9mkC/5zGcQ/eAUgSRaKvz5UuMFF/pBtyd1REiilIKpdrB69sZT4E3tB2zfwuG56IME9+yV2WrNGRLDhNIaiF7cwZCmNSVwfOn57m43OD8Yp1AKjoTNo9t6+D0bBEvaH3v1FyVh4fit0z3ZhiGOIBz5fGgHZ9sc4silaKe68J87BkctwFC4EeieNcE1UseTBTqG36/3PSZLjXZntZa9z+13n/slxEoCGLJqxNukXH8aVFhqwv1Vhj+pvIZiMJQvPW+KGVwUysmNYP3Z+u8O14gWHmJsA2NB0Y72JEx1nXUt/lqEkrFj06vleB8cmce2xKbfOPGaQRy3bI3XX6zgffSD9d91rzva596PW6adesisBNx1P678F59ft3HrYe/Ce0ETJs2bdq0+RXllkrA/Jt/82/WVBJdvnyZf/2v/zX33HMPy8vLLC8v87u/+7v09/ezuLjIf/7P/5lCocA/+2f/7LrLPXjwIP/4H//j1b8N45ba7C8EoRv84kKR8aXamunFusdffzTPbx7qwcG/ocCju0EFzioKGn4IkU+7xm3atLml0A1eOL20JvkCsFzz+OHJOZ7b3431af1cbgKJoNrcXF6l4YX4ocLQNv0IAKGUhFcqnW+hLEcr8XLrrE+bT4dSCk/TIbJSMHKdqmmlFErovHh+mcvLdSTaatBvvuLy49PzPLotx+mZEgCFuo8Qnz7A06bNVxUf8O2V/syPjU03lNct3Km6PkJE2tfr24BP0q0ihOBiMeDNi8trpruB5IUzc6QP9tFpfVZr2KZNmzZt2rRp0+ZXlVsqE5FMJtf8/Vd/9Vd0dXWxe/duhBD8/u///uq87u5uvve97/Hv//2/JwxDdF3fdLmGYZBOpz+v1b4tKHkwNl/dcF7NC5it+ozEb2xZMUtHsHmVX8LWuSV0ENq0afOZUXDh8vLGVcClhs9CI6TP2XD254KGpDNhr5OFuUI6amGvdL21aXO7UfRhfKl1z9YBy9BWfYEKdY9QCTTR6ujsS0faMjht2nxOOKaGoYnVJOjHycXs9vj7FSYUOu9OrFdngNb199h0mce3JpG/Ip1Lbb4YWpJiiuZcgYaruPKwauk63gbnUqg+vyIL09Dxi+s7ynUnirLXd6PcjBzaZ8VmsmptybI2bdq0aXM7cUslYK4lCAJ+8Ytf8NRTT21a2Vmv13Ec57rJF4CTJ0/yj/7RPyIWi7F3716+973vkUgkPo/VvmVpBHJzXxchmK8HWLoJCHKOTlTbXNc4Y8FQPsalxdq6eT0ph2xEuyUMgdu0+UqiGRQ9KLkBpq6RjehExacfjw1fXjeXUXYD+qP6F1YFLMOQfT1JzsxVCD8WGBPAHYNphAyg3RnQ5nZAb/mzld0AS9eQXJXL1JB0xG2mileDD5WV8a2AbbloS1KnTZs2vxSlGyw3oeoFRAyNrKNjqc09tlKGYndPkmNTpfXzHJPuuPGlSO62+WLwJFTdza+vhbqPov2c0ebmaEmKLZFIxKlUqlxJwDy2Lc/Pzq2XGntsW/7zW5lmkxN/+TfrJu997ttoGyRgbkoO7bNiE1m1tmRZmzZt2rS5nbhlEzBvvfUWtVqNhx9+eMP55XKZP//zP+drX7u+nunBgwe566676OzsZHZ2lv/xP/4Hf/iHf8gf/MEfoGkba9P4vo/vX32ZEkLgOM7qv6/9/+2CY+qr1bLXIoXGbMVja93ng/ElQqmIWgZf29nJYOzq/rl2e4UKeXQ0x881wdhCFalAEzCYjfHIaA5D+bdl0PN2PbaflF+V7b2R8Xrtv2/37b0evjD5xcUiZ+bKq2M9Zht8fWcXXUp9qm13TO26nW9J2wA+3W/cLB0RxZN7enj53AKVZusccCyde0ZyDCR0hAy/Esd9M27Fbb/R8Xrt37fS+t8MN7r+LiYvnS9wYb6yOr4ODuZwlWhVkypI2RphMsJC1SWUioRt4PsGD492kLEUUn4+++h2PwbQ3oZPys08C98u+7aByfOnF9d0c2aiFt/Y3UVuEx8zpSR3DaaQSnB6rpWEEQK6Uw5f257H5lc30X+7Hd9Py0bbawtB3DZo+hsXsmSiZuv96iuyj9q0adOmTZs2bdp8Mm7ZBMyLL77IwYMHyWaz6+bV63X+7b/9t/T39/Pcc89ddzn33Xff6r8HBwcZGhri937v9/joo4/Yt2/fht/5y7/8S/7sz/5s9e+RkRH+3b/7d3R0dKxO6+7uvtlN+lLJB5I9g00uLKztWpkqNhCaRjxiYUeu6ge9NFbit+4YYCDT0qvfaHv7OzLMVlzqboBj6XQnI9jG9buRbgdut2P7abndt/dGxuu13O7buxlKKX58ao7xckDEiV6dDrw4VqQnm6TvU2x71g/Z1tdY5wEDkIgYjPZkyUS/eCH07i7Y0ZtlseqhUGSjFvn4+mq4X9XjfiPcStt+s+MVbq31/yRcb/1DqfjBiRmmqyFO9Oq4rXiKqG0TKkXUbN1XYw7kEw6WLrhnSwfdqQjJiLnZoj9TbvdjAO1tuFluZqzeDvvWDUL+/IMpFpsQvWasucDPLpT4naOD5GKb38P6OrPMlZtU3ADb0OlORHCs2/+Z90a4HY7vZ8nHt/d+1+Cnp+fWfU4Ad2/tpqvzq6Wq0ObGSSoPWVwv3xu3oxt8GtLK5cH0+mRfWm0st/t5IoSg6K1PSm8mh6ZpGkVvrXpGWkFzzeYowmqTzRSLJWz4m+ujQVd/0ygX1068SVmyL0NSrU2bNm3afDW5JRMwCwsLHDt2bI3nyxUajQZ/+Id/iOM4/P7v/z6GcXOb0NXVRSKRYHZ2dtMEzLPPPsvTTz+9+veVSqiFhQXCMKS7u5vZ2dnbznDzaI9DuVrn8lINBQRohGHA4zs6OTO9vK6669jlBWzfWe0e2mh7TSAF4MLyQvmL2IzPDSHEbXtsPwm30/b29PRsOu964zUIgjXTb5ft/STUlcG7Y3MbV2kKuLBYxXDLn0qr/r6BGD+tNZi65mUyE7N4bEsOt7zMTOnL269XLKz8CsxUrk7/VT/u1+PL2vbPYrxemXc7H7sbWf+qNPjg0hx+uHb+WL3Onr4ME8UmpXp9tfUs7Vg8ubuTpKpRK1RZLwT6xW/DrU57Gzbn047V22nfFgOd05OL6zrBAep1OD+zhBe7/jJ0Idi5sr3FpTLFz2VNbx1up+P7WbDZ9nbbBns7Hd67vLzqBWQZGg9s7SBJg5mZjT02P2uuN17b3JrIep2Tf/bn66bv/s63N/y85jZY+skP1k3v2uTznyehVBtKjW0mh9b05Tr5tOcGDM4vrk1AWZbFnk1+M9jkN787uHG8R7lNvFefX7v8m5Ql+1Ik1dq0adOmzVeSWzIB8+KLL5JKpTh8+PCa6fV6nT/4gz/ANE3++T//51jWzVdbLy0tUa1WyWQym37GNE1Mc+Oq0isP5Eqp2+5lJILHN3dkWG5mqHgBmm5wZrbC2ZkC7gaVHwtVFyFaFTq34/Z+Ur5K2wq3//beyHj9+LTbeXs3ww3VphIZKFiseuxMmp9q2x08fm1XlmU3u6qfn4voWATITQyKbxV+VY/7jXArbfvNjtcr02+V9f8kXG/9m4Fcl3yBVr7l5HSBh7Z30hnLUfECIrpGztG+lPF2ux8DaG/DzXIzY/V22Ld1X26YfLlCqeFD7MbukbfD9n6WfNW3V1M+R3si7OjoZ7nhowlBzjGI6yEybPtvtbl5LEPjwbSHadbw9ZArVRYWG8ujb8ZGHTYK+bGukxY32y/bWscb78bZqHvnetuz0TrabT+lNm3atGnzK8wtl4CRUvLSSy/x0EMPoetXW/uvJF9c1+X3fu/3aDQaNBotKZxkMrnq5/JP/+k/5bd/+7e58847aTab/Omf/il33XUX6XSaubk5/uiP/oju7m7+/+z9Z4xlyZnYff4jzjn3XG/TZ1aW966rPZtks5u+aUVyhpx5NXh3sBgBgjSa/SYtNNICg8F8mC8iBGgg6QUWWEDaHW9ohmQ3TRu2Yfvq8t5kpbfXm2Mi9sOtyqqsvFld1Z3dlVkVP4DsynMyb0bcPOdGnHginjh48OBdqd/dJsKAggMFB5oIfjlf7Rh8AehOuh9qtrxhGB8f1xK4tlzxfu5KRlBqhQDNHZAqoMuBLgdAgVYr7gtjGMatubbEsUTHIIzSIIGuSEjB3G+G8aHEHNlxL8Rr0tEPN0HBuLdpFZKSIakEtAfLfcwjkvFBiVaLuWd/RCQSwfO8xePD3/rGHb1OpxU2h771jWWrTgAO3eHHW7uMt78ap9PqnRXro+lYxj3mM9gwDMO4h625AMzRo0eZnZ3l6aefXnL84sWLnD17FoA/+qM/WnLuv/23/0ZPTw8A4+Pj1OvtBl1KycjICC+++CK1Wo18Ps+BAwf43ve+t+KsvvtJwlLsH8zwxqX5ZeccS7AlH0cpM7PLMNaDhAzZN5Dh7ZGFZeccS7KlkEQ3ix9/wQzDWFHaUuzoTXN8vLTsXNSxGMq4aO13+EnDMO5E1oHhQoJLs8sT9yVdm96EDZh7zTAMwzAMwzCM1bfmAjAHDx7kb/7mb5Yd37t3b8fjN7vxeyKRCH/8x3+8quW7l4RhyMG+BJVWwOnJ8uKswHjE4nM7e8g5IWYiimGsD0opHhxIUvNCzkzdeD/bfGF3D4PZKJOTd7eMhmEspVTI48Npmn7IhZnq4uqWpGvzpd29pKzQzLI2jNWgAp7eWuDnoWJ0obF4OBuL8OU9PURFYPq8hnEbUqrzRvF3mj7LMG62UtozB9kxPK5ZnspspcEt22tBs7HseCoSveNyGoZhGMYHseYCMMbHy9E+T29Oc2ggTbEV4EhJIWYRlyFKqcVNVw3DWPsc7fPZzWkODaYpXb2fu2IWMRmae9kw1ihX+3xxW5aF4SzlVkDEarfD0XWwt5JhrCcxPL62q8B8i/Y+Zov7KoUm/Zhh3CbR7LxR/J2mzzKMm62U9mz4252vLc3yVGb7lO4cCmw28F74yfLf+eQzH6CkhmEYhnHnTADGgDAga0PWBlCAMjNuDWO9UgE5G3I33M9am+CLYaxlQgXkbchfu2/NXi+G8ZEw+5gZxlItJWh02D8wZktcae6O29Vp9cZqrQpaaWXI3Vh1dLfKcvNKF4BOCeUdSyLKxWXHxQr7YDpW5/qkVAswq2MMwzCM1WMCMIZhGIZhGIZhGIZxn2kEip+eml12/JldXbgRM4HndnVavbFaq4JWXBlyF1Yd3ZWy6OUrXQAOdYoPei28V36x7LD7yc93fm2vc336f/s7EDUBGMMwDGP1mGSthmEYhmEYhmEYhmEYhmEYhmEYq8ysgDEMwzAMwzAMwzAMA4C09lDF5asOHG3yVBtrW6d0ZZEVjndKYwbg2BZ+cWHZcSsWR7vuhyqfYRiGcX8yARjDMAzDMAzDMAzDMABQ9Ton/u7vlx0/dBfSXhnGbbtFurLbTmMG0Gxy7B9/uOzwvt/+DtIEYAzDMIwPwARg7oBt2x3/fT+4n+p7P9UV7t36rlSve7W+t8PU/f60Hup+qzKuh/LfynovP5g6rBVroQ6dyrAWyvVxMvW9t90r9XWcleb2LyX9ACmtZceFEAjRYQ8Ywe0fv5Pv/aiPr9HfueT8eq3nWirLR/w7hRC3fW8ZhmEYxo2E1nqluL9hGIZhGIZhGIZhGIZhGIZhGIbxAci7XYD1ptFo8B/+w3+g0Wjc7aJ8LO6n+t5PdQVT3/uJqbup+3pkyn/3mTqsDWu1Dmu1XB8VU9972/1W37XkfnzvTZ0NwzAM4/5iAjB3SGvNxYsXuV8WDt1P9b2f6gqmvvcTU3dT9/XIlP/uM3VYG9ZqHdZquT4qpr73tvutvmvJ/fjemzobhmEYxv3FBGAMwzAMwzAMwzAMwzAMwzAMwzBWmQnAGIZhGIZhGIZhGIZhGIZhGIZhrDITgLlDjuPwW7/1WziOc7eL8rG4n+p7P9UVTH3vJ6bupu7rkSn/3WfqsDas1Tqs1XJ9VEx97233W33XkvvxvTd1NgzDMIz7i9AmCadhGIZhGIZhGIZhGIZhGIZhGMaqMitgDMMwDMMwDMMwDMMwDMMwDMMwVpkJwBiGYRiGYRiGYRiGYRiGYRiGYawyE4AxDMMwDMMwDMMwDMMwDMMwDMNYZSYAYxiGYRiGYRiGYRiGYRiGYRiGscpMAMYwDMMwDMMwDMMwDMMwDMMwDGOVmQCMYRiGYRiGYRiGYRiGYRiGYRjGKrPvdgFWQ6PR4K//+q954403KJVKbN68md///d9n27ZtAPzFX/wFL7744pKfOXjwIH/8x398R79nZmaGIAjo7+9nYmICrfWq1WGtEkLcN/W9n+oK66u+AwMDd/wzMzMz+L6/+PV6qu9qM3U3df84674a9yus/7/dei8/mDqsFR9VHT7svXovvLd3wtT33rbW67tabetatNbf+4+CqfO9Xec7vV/Hx8c/opJ8/O6nv/P7Me/FdWv5vfgg7athfBD3RADmf/yP/8GVK1f4wz/8Q/L5PC+99BJ/+qd/yve//33y+TwADzzwAP/m3/ybxZ+x7Xui6oZhGIZhGIZhGIZhGIZhGIZhrEHrPgWZ53m8/vrr/N7v/R579uyhr6+P7373u/T19fHcc88tfp9t22Sz2cX/JZPJu1hqwzAMwzAMwzAMwzAMwzAMwzDuZet+GUgYhiilcBxnyfFIJMKpU6cWvz5x4gR/8Ad/QCKRYN++ffzO7/wOqVSq42v6vr8sdVEsFlv8943/vdfdT/W9n+oK9059b+d+vfHf672+H4Spu6n7WnG79+uNX6+l8t+J9V5+MHVYK+5GHe6kL7ye39s7Yep7b1vP9b2TtnUtWs/v/Qdl6mwYhmEY9xeh11oCvg/gP/2n/4Rt2/zRH/0R2WyWl19+mb/4i7+gr6+P//pf/yuvvPIKruvS09PD5OQkf/mXf0k0GuXP/uzPkHL5IqC/+Zu/4e/+7u8Wv968eTN//ud//nFWyTCM22TuV8NYP8z9ahjrg7lXDWP9MPerYaxvZg+Ye5N5L65by++F2QPG+LjcEwGYyclJ/vt//++cPHkSKSWbN2+mv7+fixcv8v3vf3/Z909NTfHv/t2/4z//5//M/v37l51faRbRzMwMYRjS19fH5OTkmvvg+CgIIZbV91rQSil1N4u26jrV9V62nurb39+/4rlb3a9BECw5vl7qu9qu1X16epowDO92cT5W5u/+8dd9Ne7Xa+fWw99OSonWelkZ10v5b8XUYW34qOrwYe/Ve+G9vROmvh/t7xJC3NVni7X+912ttnUter/3fi1cH6ttrV9vH4X7qc63ul87MQGYe5N5L65by++FCcAYH5d1n4IMoK+vjz/5kz+h2WzSaDTI5XJ8//vfp6enp+P39/b2kkqlmJyc7BiAcRxnWUqza659WHQabLmXaa0JsJhraq4UG0gBw7k4eReEWvsd+ztxP/5t13N9b+d+vfnYeq7vnRJSUgosLlyYZbpYpzcVoS/hEBXBffU+3G9/9xutpbrf6f167fhaKf81Qgjq2ma87DFXa5GN2wymXVJWuGyAaC2W/06ZOqwNH2cd7uRevRfe2zth6rt6pJRUQ4vRcotiPSCfcBhMRYjLu9dHWY9/3w/Stq5FN7/3UkoqocXY1eujkHAYSEeI30N92PV4vX1Y92OdDcMwDOOeCMBcE41GiUajVKtV3nvvPX7v936v4/fNzc1RrVbJ5XIfcwnvvms5V++00+MLm+fPL3B2urp47DcX5zm4IcdjQwmsNR6EkZZFyZeUmgG2Jci7Fu491Hk3jBtdmymogYtlxXMnJ4hEY9TrdQAyMYdv7OsjJf1bv9B9QFgWRU9QaYU4lqQQkzjafDYYKxNCMOtZ/OjYBHXvetvn2pKv7O1nKGFRDSUL9ZD5iRKutknK5YGZ+4GU8r6st2GsBiEEHjbzzRA/1KRdi0wEdHh7fe6VVuetFUIIxuuCn5wYp+lfX50bj1h8bV8f3RG1ZsturC4hBMWGx2RL4geKtGuRjQjGaiE/OT5GK7jejiQiNl/b30eXE5rrw/hIfNDxEsMwDMO4lXsiAHP48GGgvXRscnKS//W//heDg4M89dRTNJtN/vZv/5bHHnuMbDbL1NQU//t//2/6+vo4ePDg3S34xyiUDrMNxUS5ScSWDKRdsrYGfXvpiM7MtZYEXwA0cPjKAkOZKMOJj6DQqyQQNm9eqXF0rEig2h2ppGvz+V09DMZM58q4dwgpKfmSsbJHKwgpJGOcm60SqqXXeKnh8/y5Wb6xuwC3OZBzL/KEwysXS5yeLHPtLcrGInxhVzc9rhn4MTrzsXnu1NSS4AtAK1A8d2qaz+7s5ecn2wOK8Xic0Gvy+OYCe7oiCHXvpwC8NqN9oupRbjTJJSL0Jx2imMCmYdwuKSXjdcEvTk9SbrYnS1hSsLc/zeMb0th65QkUvnCYqYdMVZrEIu3VeWk7RK+xYGhD2zx7amJJ8AWg7oU8d2qG3z7Qi4OZKHKvk1Iy0RS8fHqEqfkyAJYQfHpnL7+5OLck+AJQ8wJ+fmqa39rfi22uD2MVaWFR9AWjpSZKw2DGJe8K5BqfaGoYhmGsD/dEAKZer/OXf/mXzM3NkUwmeeyxx/jd3/1dbNtGKcXIyAgvvvgitVqNfD7PgQMH+N73vrfiUu17jSccfnlmnotztcVjUsATW7s40O3C+wwIVVsB740WVzx/eKzEpj151BrMMSyl5OR0i3evLCw5Xm0F/POxSb57aICMtfbKbRh3TFqcmvd54ezMYsBlwdO4luCR4RwXF1pLvn1soUGxBdl7ohW4c9KyePtKlZMT5SXHiw2PHx2b5HuHBkgI82BvLDfXUizUvY7nZuoBZ2dqSwYUW4HixbMzpKP9bIh/XKW8O4QQTDQE/3x86Yz2pGvzjf395GwThDGM21EOLP75ppn/odIcGSsRc2weHYh23NOtgcM/H59hutJcPGZLwed29bA1bYFeO0GYuUZIrdW5D16se8w3Fb3ux1wo42NXDiQ/PjqOFYkuHgu1ZrzUYqTYpCdutWf93WC+5jHfUvREPubCGvcsJS3eGm/w9uX5JZfbrr40T27K3DLobRiGYRi3454YenviiSd44oknOp6LRCL88R//8cdcorXDsiyOjNeWBF8AlIZXzs3Slxyk530ebvwgpBWsHKRp+CGhArEaBV5lTWXxzuh0x3N+qDg/1+DhPtekSDHWvXlP8PyZ6cWVHAgIQsV4sUUh4VJIRrmagQxoP8v66v4dCK0EguMTpY7nmn7IaKnFrpxlBouNZbxghfZCCOZqHs1QIQXcfHu9faXIhj339qqzprb52YnlM9qrrYBnT07zWwe6sfS9W3/DWA1CCC4tNJbN/L/myFiRvb0DRFl6n0nL5tXzxSXBF4BAaX5xcprCQ4NkrbXT323e4tkCwAvXTlmNj4YQgpFSi1agiN8QTJECvCBkvuaRj8Wxb47AcLUtNgEYY5WMVzVvXZ5fdvzUZJn+dJQ9efNMYBiGYXw48m4XwPho1UPB8fFyx3MaOD5VwbZvHYeLuzZdyZWjNP3pKJZYmx0ST7Pi7DqAqWoLKdu3wbV8r7ZtL/7bMNYDKSVnZ2tLB3w1xBwLgGPjJfKJpU+pEVuScO7f67wVajKxCAPZGKno8tWQszVv8bPBMG6Uci1kh1tHA60gJBGxlgVfoJ36z1vl8UTbtnEcZ81cqzP1kJrXuc2dq7WYb67NvoJhrAYhBLZtf+h+pJSS6WrnVXbQnvjkhcvvpXIgOD9T7fAT7RUFl+eba+azAiDToe29RgpIRayPsTTG3SClZKbSWnZc6fZeL6HSdIrDSdFuiz8qq3UvG+uDtGwOjxdXPP/eWJFA3BPzlg3DMIy7yLQk97hQCxr+ygGIUiN4346la1s8PJxjdKG+bFDJsQT7+1OoNTqj1xYQi1g0vM6z7LriDkopWjiMLHg8e/kyfqvFnr4kgykHxyw3NtYBKSXlxvJrNWZLXFvSDBTypvv8wGCWlK3pkMHknqelRT2UlFqKcjNgKBtjY1eKC9Ml6lc/K3JXPxsM42a5CGzrSXFmqrLkuKCdqqLW6DxwmnRtHMGyVCofhJYW0w04cblMqRmwIRdle1ecrK3u6nXb8G/9gdIyM5aNe5QvHK6UfU5MtmdQ7+xJMZyN4H6AfqTWmnx85eCEa0tsa3nf3Q/V4l6HnZSaPkKsnZxeeReGCwlGblqlD7C1J0U2Aphm+J6mtSYb79wo1Foe27uTVyc8LL2ud1y9Pm5zK9M70sJhpOhxarqERLCnP8VQysYxqzfvWaGGWuvW2T4CpTEhYcMwDOPDMAGYe5wrNdm4y3xt+ewigKFs5xzSN+uPC768p49XLsxRujrQm0+4PLmtQN4JWasrchOWYv9AhjcuLV9SbEnBtq4ENSX40fFpZqst4vE49XqdS3NVNhYSfGF7nogJwhhrXBiGDGRinJ1eOvPVQrExH198cID2wM2BwSyHBuKEazRw+lHS0uLwVJPXLs4zXvFZqHucn60Sj1h8fV8/pycWEAg2ZKJoc+8bHegw4MnNWVxbcmqyjB9qLCnY2p3kwGCev3/ncsefe3BDFqnDDx9/kZIjUy1euTC7eGi8WOfwlSLf2N9PjyvuWpqMTGzlbqUUkHQt4P773DHubZ5w+OnpOcYWruf5HJmv05OK8rU93UTvcKNwpRSb8zHeuCQ6BlR292dIWWrZBIqYLW856ag/HV1TEwukCvj8tjyv2pKzM1VCpXEswY7eNJ8YToMybfC9TinF5lyUNzoEFC/PVvnK3n6uzNc4N11ZvD529aV5bEMaHa7+9dHA4cfHp5mpXn9uvjxfY0M+zpd2FMwz4T3KEprelMtctfN4SSERwbWA+3DSmmEYhrF6TADmHmcT8uimHD87PrnsXMSW7OiKo9RtDIaokM0pweDBPsqeRgAZF2wdrul8qGEYcrA/QakZcGayvDjw5dqSp3f20B2F10arzHbocF2eq3G5O8mOrFzTdbyZZUmswEdbNoFmXZXd+GC01mzKRXmjw8CLg+KL+/rYNZBjT1eEuC1JWuHt3ff3EFsKhO8zHTr85sIcAL3JCIFSVJoBdS/ktYvzPDiUZk9vkrQVrNnAsnH3RbTPZ4aTHBpM0/QVri1IO6B0wBNbu3j94tziwKklBA9uzLExbaNX4b5b8CSvXZxddrwVKF44N8u39/Vg3WKQSEqJpUKE1oS2c1uTMG5XISoZyMYYLzaWndvSnST3Ec1YNoy7RQjB+fnmkuDLNdOVJqdm6jzYe+d7DeYcxZf39PGL09OLeyoJ2vfRw4NJwg6DzwlL8eBQbklwdvGcazOUidzViQW2EEgVoCyH4Or7EcXnc1szPDKcoRVoorYk7SjURzC4bqxNGTvky3v6eeVymWt3kQA2dyfZlLbZmU3zyIY0XqCJOpK0pVC3CM5ZltV+DpKSgNufkCCl5MRkbUnw5Zor83UuLiTN3oD3KBWGHOhPc2aqsizoLYCHh3P39P59hmEYxsfDBGDucVprNqdtntrezeuX5xcHZwsJl6d2dJF1FLf7TKi1xsGncC0rglqVTCofOUf5fHZzmgcH08w3fBxL0hWzSMiQeginpjrnywY4Ol5mZ76AXgedLikE0YUZ/JPv4c9MIWNxonseIOwfxltDOb+Nj0ZSBnxjfz/Pn5ld3IA36lg8NJxjZz7CYDaObJTQOrzte/5eYKNpnT6OfutVQt9jZPAhZDNAReNYKDZkXFpJl1agEAIeGMrSGwlQt0jjYhgASoUkRUjyavYUHbYf1B/ocdmSH2Ku7uNGYyRkQNpWsArBFyEEo6Vmxz1mAGYqLcqeJrdC7y7qNdGXzuKfPYFWCmfjViLb99CMp1ZlUMlSPl/a2cWLFxa4NFtF6Xbwc3tvik9uzHwkM5YN425SwuLYxMKK509OVtjf225v7uh1lWJjUvA7hwaYawS0AkUu5pBzQa4w+ByGIXt7owQqz+HRYrtdA3ozUZ7e1kVc3J2JBY5W2FNjeMffxa9VsXIF4nseoFXoJaS9qjAlIRUBCFEmSHtf0VqzMSnY8thGLkwu0ApCcjGHvAtC+egQ0pKr6StX7sNKKYmWFwhOHcUfH0E4Edyd+9DDW2nZK6f0u6alLU5NVlY8f2yizM5ClxmIv0cVXMVX9vXz0tlZildTySZdmye2FBiIC5MO0TAMw/jQTADmPiBUwL4uhy35AcothW0JMk57dcxHOcgopaSmLKqewpaCTASsu7RiRqiAnA251LUE/O2HUA2Ls/A6CZRaF/0tIQTuxBWqv/ox13JShKUF/MkxonsfwH7wCQLMJpL3Mq01XU7It/d1UfQgCBVJ1yIpQ/Q6z1sthCAUNsWWJtSaZESStNT7ztyXUmCdPkrtyJt49ToykaJZLhNcmcLuHSTMZBFaE5UQjbTvD6nDNZWixVh/tApJyZB0StDfn2NiYgIpJFXtUPUVlhBk3Q/WHgoh8IJbX5/hCu161G/i/fLHBLNT17+3OI88e4L4M9+hHk/dUVlWEsPny9uzlDZmaQWKqCPJOJjgi3FP0rTb25UESqM0t713gLQsKr6k5isiliDrauJxTTu8G7zvIKCtAh7pj7K7Z4Cqp3AsSdYFEd6d4IslQB4/TO2d1xaPhaUFvMsXSDz5RVqbtps210BrTXfSJUhotL69a/1m0eIstZ/+A9prgWWjBzcxVwsJRyZJb9pI1OaW15rWmiBc+SYJlEZrzNPUPUorxYa44LcP9lJqKTSQdiUxEaJMVNgwDMNYBSYAc59QShFFEb2296b+aFevKGHz3nSTt0cWFlMn9KajPL29i4KzdtKWRS0YzMY4N915FczW7gRSr/0gTCTwaL7+Ip12VG8ef4/k1l0EmcJdKJnxcdJaI3VA3ubqp3t7hZsQ6/dxUQjBjCd54ezM4sqemGPxyMY8e7ojyFs8FLnVMvW3XiUWac98VPUaQ6kIbwLBzAR2IkloXW8Gk65NMiJNjiRjVSlpcXS6xRuX5xfbw55Uuz3sitxZe6iUYjAbXfF8InL1Gr4pUbkQAkYuLgm+LL5mvYZ//F2sx54iXK2B0DAgY3F11FmZW8q4Z9koNhbiLNS9juc35GK4Ut3Wqo5AOLx5pcqx8RJ+2F69MpSP89TWAil5+wFMpRRxoYi7AOqu7lvgVkpUD7+x/IRWNN54iWjfIM3Iyp9phnE7HAGtt15Bey1EJEJx/6d4/kqNyfcm0UySGAs4sHOIg70xrBUmJUUtzVA+zunJcsfzWwpxbKHNNiD3sGvZProi1w6EK644NgzDMIw7ZfISGatOSsnp+RavnJ9dHGwCmCo3+cHRCapq7cT9dBjw8IYsjrX8VohHbHZ2J9bFzDyrUiYsF1c4qwknRtf1ILxx/6oomx8enVwMvgA0/JCXzs1wbiG49XVdnEcHNwxaaUV3eZwNPVlQCrzrrymAxzcXiAnzaG2srrPzPi+dm1nSHk5X2u1h5QO0h91RyXA+3vHcY5vzxOXya9gWAv/s8RVf0x+5gN1avm+LYRi3ppRiX1+KqLN8jYtrSw4OpFG3sc+StCzeGq/y7pUF/KsrajTtvSd+dHwKT7x/CqW1SM1Ns1L0STXqiBX7roZx++xGDX98FIDGzgf5wal5JmZKi5MNm/NzvH55nmMzTeQKaZlVGPLgYJpIx2dCi129yVXdM80wDMMwjPuLCcAYq66pLd4aKXY81/BCLhebayoYUHBCvnVwgE2FBJYUOJZke2+Kbx/sJyXXR+qm951BrdWaes8N43ZIKbkw11gycH2jNy/P491qIWeH+8I6f4Ivdmse2tZPPGJjCUEh6fKVff1sz9rrIuBqrB+lhs+bl+c7nmv6IRfnGysOBq3E0gFf3FHg4Y054hEbKdr7uj2zt4+deWeFa1jfup1YI6tSDWM9ylgB3z44wLaeJI4lsKVgc1eCbx0coBC5vTal4kuOjZU6nivWPSar66M/usz79k/NZ4+xCnT7/0QkwigJavXmTafb19m7Vxaoq5UTAhYiavGZ0L72TNiT5FsH+kmvk2dCwzAMwzDWprWzFMH42AkhEEKs+oBjK4RKc+VUCWOlJge6MwTB2ujItvfOCPjarjwylqJSqZCwNCr0181zoUplsFJpwkrnZfNW/wZaZmDZWCVSSrR+nwHdVfo9Y6XmiudLDZ+Waqee6CibB+vmZk4TOfY6TxS6efQLv0XTjuBaAlsHaJMnyVhlNS+g1Fi5PRwtNTnUG73jdjiifT4xGOdgX4JQc/0avjrT/Ob2PUTgbN1FMDvd8fWcoU0EbowVdzc2DGNFWmuyls+XtmWpb86hNSRsdXXlx+1NfqkHCu8We8nMVFtsSt35Z8XdJgs9ICTo5eUWbhSdzn78hTLuOUE8gdM3gKrXmawuTwco01lCpal7IY1AEbU792WVUhQcxVd35qgFeYSAuKXRd2kPJcMwDMMw7h1mBcx9SEpJXTucKSrenGhyqQpNnFVbIWELOqb0uiYdXZuzzHUY0JOKEhcBKlwbwaHb5Udcoo98uv2QexN3+x78TP4ulMq417SEw0hN8OZEk1MLIRVlf6Qrq7TWpKMrzxNwbYklVn4i9pIZ4g880vFcZOsu7IhFXARYyl8z+1IZ9xZHSlz7Fu2ha3/gay8MQ1yCJdewkJKKcjgxH/LmRJPRusQX7VUxctM2rOzytkBEYzj7Hly9/V8M4z6lw4AYPgkZUAsk58rtfvaFyvv3syNS3DJUk/wQnxV3k5fKEt1/qMMZQezhT+LFEh97mYx7j6/BfeiToDWpyNIVLjIWR0fb15lrS2zHYbQueXOiycmFkIpyEDetRNVhQFz4xPDR6+yZ0DAMwzCMtcmsgLnPSCkZqwt+emJ8SVqfpGvzjf395OzgQz/gJWzFzt4Ux8aXp1KQArZ3JVDKdGZXk1IKb2gzyWe+jXfsbYK5GaQbI7L3AfTwFlodAjOGcScqyuFHx6YoNq7PLHQsyZd297IxKT6SgaEwDNnVk+TIaJFOr767P01CqhUn7YdaY+05RLJ/EP/NVwirFaxUhsj+h/B7h1DrcDDLWF+6khF29aV5b7S47JwAdvUkCVdpcEdIybmS4penJghu2DW2K+nytb29EIHYF79JeOY4/oUzaBXibNiMs/sgjWTGpAIyjFUghGC6Jfnx8XEa3vV+diJi87V9fXRFwo7tZcaFoXycK/P1ZeccSzKYjqBX2Dx8LQuAyIFHSOR7aB17B9WoYWWyRPY/jN8zuCYnZBnrUyPfQ+ypZ9hWafHGpQVCNDKTR6SzhFIiBTy+tYefHp9k9oZ9BW0p+PzuXramJdpcj4ZhGIZhfERMAOY+U1cWz54cX7anQrUV8OypaX5rXzcWH+4BT4Uhjw6nmau1mLghfZAlBJ/Z0U0+omEV+7dSShyvhVAhoRvDv08HkUKtqRd6sZ/6Kq7fQls2LWmtyxmTxtqipc0vT88uCb4A+KHiuZNT/O5DgyTEymmWPoyCq3hyeze/PjfDDWPKDOXiPDSYRqnlqSaWlFFIonsPUS/0EW3U0LZDy3HNbH9j1bXboiYoRejGCGkPxj48lGau2mK0eH2TeyngyW3dFNzVaw+LvuQXpyYI1dLP/Nlqi5cvzvOlrVkabhx58DGcPYcQWhNEXOpKmeCLYbwPIQQOinBhjogK8GTnFSlNbH56YmJJ8AXa6QifPTnNbx/swenUzw4Dnt5W4EfHAxZqyyc6pKxw3d6mnrAQw1uxN2zGCXyUE6GxTutirF1aa+qZPNm8zRdSPfzq9DQegmszeHb3Z7g4V1sSfAEIlOYXJ6foenCQtPX+DbItBFarAVLiR9ZfWkDDMAzDMO4OE4C5z8zUA+pe530O5qotFlqarsiH/z1R7fP13d1MN0Kmyk1cx2Iw7ZJ19GKO+tUQ9VvoM8fwzp5AeR52Vy/xg4/Q7OpF3acPd4HWBPbVP+J6fVo31pSiBxM3DB7fyAsV42WPHVn50QT7lGJvV4ShzBBj5RYtP6Q/E6UrKrH1rYMv0B4088dGCF9/ieboZRACZ+NW3L2HaMRTJkBprIpYs0Z44giti6dBKez+DcQOPAz9/UTx+cruAjN1xeQN7WHG0Vf3iPjwhBCMLDSXBV+uuThTo7wxS0peXTF5bW8kM3BkGO/LRuNMjNB6703KXgtPg7v3AfTmHbTk0kepuUZItdV5IlOx4THfVPS6nX9PUvh8Z18vU/WA6WqLZMRmMB25GnxZ322V1hofAXaEjktaDWOVhGHAlqxD18PDjJdbNLx2iumEa/NXb410/JlAaa6UWuwrrJzqT0pJtDiLd+RtWhNXQEoim3di7TlAI2pS6RmGYRiGcWsmAHOfqfu3HuxphR/uqUgIgaNCrFoF0MQTKTb0x1BKoXXQaQ/OD8wNffznf4o/NbZ4zB+7jD8xSuLzX6fZN/SRPrDKq/mCP8jMJ9tu33phuP4fqo214XavRyklEa+JaNRAWgTJNP77XIJeqG45XlLzAmAVIrcrUSEZC7J5G3F1P4vb/TCJlheovvATWgvzi8daJ4/gj1wk9sx3aKxC/nnLshBCmPv5PhVrNWg++wPC8sLiMe/iGfyxS8TjMXBi2CqgPwqD8SgATtBElqogBGEihX/TakUhBEKIJffzra4zKSXlFQZ9ob1C0lfa7PxnGFet1GYKIXDCAKteAQQqlUZcPEvt178ANJF4nLBep/7q87iz0ziPPol/Q5rXVnDrtqkVKFghAAMQwWdDHDYmo1c3CO+8+bfpRxprWacN7lfrdaWUKKVu3d/VirRUZHIWQrT3Hp3zw1tOzis3fYRwVixztDhL7ad/j/auT/5pHn8H68pFYs98i0Yk9kGrtaZIKYm0GohGHWwbP5EmMJ8xhmEYhvGhmQDMfSYXdVY8JwUkI5Jb5UMRYuW9HoQQxGYnaL7+a5pz0wDYuS7cRz5Fq2/otie8CSGoKpuZuk/LVxQSDjlXYN20b4ycnlgSfFmkQlpvv4LzzG/hfQR7n/jCYboeMl5qErElw7koOUfd1kziUDpM1kJOTpXwlWZ7V4IN6QguH036JuPeF0ib6bpirNjEtSSbuhI0g5D5mkfcsehO2CRl+9q0tcK6eJbmO79B1SogJM7ABuKPPkkjlVnx3k5ELBxL4oedr/GuhItehejqrT5fgDt+mLekxD9xGKvVXHZO1SqoC6eQ+x/5wOkjlLSYacCJqQpNL2RTIcGmrEtcfvi9tIz1QUqJGjm/JPhyjfY8WoffwH70KXyt2xtwa407cZnmm68SFucAsLt6iT3+JM1CHxoo+ZIrpRbVVkBf2qU/5bLQCDg5VaFx9TrbmIsSKs1U1UNr6EkK+jKxjnvNAEQdi5h1qy2+DeP+oKVF0WuvGPNCxWA2Sk/MwtY+UgjcyVFab75Mc2EWADdXwOkfQiQS6Fp1yWu1zpwguWs/fqaweCztrvxoJYCUa8NtpPpVSrU/M2i3jU1tM1MPUULgK7g4W8EPQ7YVEgxnI7ja9CONu88XDpO1gIlSg1jEYjgbI+uoJdkPlLRZaMFs3cORkp6EQyZy6z6TkJJ5X3J2ssZM1aM36bKtK04+cutAzI39xrgjiTrWsjTc1/SlVk4nZkuB996bS4Iv14TlBfTIBcT2feu+7+eoEOvscZpH3kTVa+1VPkObiD/6aeqx5N0unmEYhmGsayYAc58pRAUD2RjjV9MJaSHwrqZ/39+fJh+VhB2e4VrYTNUDSg2fdNShN2ETFUsHGWOleWrP/RAdXH+BYGGW8KWfkfrqd2mkc6j3maknpORiWfHL02NLZhFuKiT43Pb84gOmZVkEIxdWfJ1gbga3XoVE+rbfm9vRFA4/PTmzZG+b1wQ8sbWLA93uLdPJBMLmxYslTk+WF49dnKnSlXT5+t5eYrx/OqU7JYRYnOUZhquX+s1YG1rC4dlTc4wu1BHAvqE8/9drl6l5iq64hdCaWMTiy7v76AXskfPUfv3z6y+gFf7YZcLn/onYV3+bhtt59l7KUuwdyHD4yvJB5nwiQk/Cuu0VKTcTQtDQNlM1n0rLJxuN0BO3cMWdBzEsywKuX+t2q0lr9BLWCt/vXzyLtedB1NVBLsuyQAj0+82spB18eXOsztsj19+Ti3M1UlGH7xzsx0ZT9hUSQcYV2NoEZe5FFhCcP730oBD4SrTTgV26TOwBj6nQZbbWYk+4QO3YEZxoFOU4aN8nmJ2i9uwPSHz9uxxTGX5xaoLg6jTd/kyMUEjGig2cq5MjLszXCbTkya0Fzk2XqDQDvCDk6V39JGMO1cbyRvzQhixJW2OaAeN+pqXF4akmv7kwtzgp6M3LMJiL8+WdXeTmx6j+8kdcu1GE7YDWNI+/S+KBR6m+99bNr0g4M4nIdi1+vudcGM7HGZmvL/1WAVu7U+RdiV7hPtTSpugLGsHVVWt+QCZqIy2LHx4ZoysVZbzscXi0SNSxGM7FuDhTJZ+I8M19vcTMZB7jLqprhx8fn2a22lo8JgU8taOHXXkHVIgvHF44v8C56SoRW7K5O8XFhRZx12KbXyQj7WX9PyEEFyuKZ09c3+Ps8lyNd64s8MzePjYm5S37bNf6hkkUDwxl+c3FuWXfk446DKQdLKlACASgtKbkC1qBpkvV0RMdJv1d5Z8/jbXzAME6bmSllFhnj1H/zYvXDyqFN3KBsLRA9Jnv0HRusXzPMAzDMIxbMgGY+4ylA760s4uXLixwaqbO6EKTIFTsH8wQdSSHJxvs7XaRV1ebCCG4NFfjrw9PUmlef7BLRR2+ureXgtMOqFhS4p88vCT4AoJgx36uRHs4+d4kQU6xozfJ5lx0xYfEom/x3Mnrg0/XXJqr8WbU5smNSdS1zq210rAqIET7f6vIsizeulxeEnwBUBpeOTdLf3qQ7pUXGDFWDZYEX66ZrbZ4b6LCE4OxVd3IMeo1YeIK4fgIwo3jbtmOlykQrPL7YtwdlmXx3liV0YX2IE9/NsbRiTIX59pfJyIJ4hY0vJCfHJ9gc9Ki9c5vOr6WqlXQ4yOILbs6Bgm0CnlkKIkAjo2X8EOFFDCUi/PUtgKRDzjzVgjBTEvyz8cnrqYxa8vGInx1Xw8Z+f6zhKGdjlBOTxBcPt+erbdpO2FXT/shWkpYYeUOUoIUKGEzUVMcnShR90KGczF2dMfJ3CLv/myDJcGXa2KOxTvjNS7MlKle/cwsJFye2t5FX1SZIMw9RguxpC1SSKYrHgsNH6U1bktSHy1Ti6RI2oI3J6qcavSRiFo8sGc3GxrT2GeOon2PxsnjvBPbvdj+CSCfjPI3746RjNpszLigNRnXYpeokj96ks+0arTyvZQKQ7x+YYandvbx7sg848U6GnBtyQNDWQ70xgk7za4wjPvIdANeu7B88HVsoc6luRrJ4+8sBl+CbfsYTfRxYrJKK9HP7jDH5kc/T/zUG0t+VlhLH6WkCvj89gK/vmRxYbpKqDVu6LMtJfmkNUPkxHnk0CZaqexin08IwUJg8fzpeU5MVZkoN4k7Fp/YXEAKmK36bC4kUEgOj7ZXmDf9kNFik005l/maxztjFZ4cTpjJNsZdISybV88XlwRfoP2M9MKZaXofHKLLtXh7vM7Zq8GXHX1Znj01xULdRwA7+rLkI5qv7esjZ18PwtS0za9Ojy/b4yxQml+enuZ3Dw3gdsjeYAOR4izBxbPoRg1rYJhHhrejdIH3RhdoBQpBu//82e1dNEPNu+N1xktNklGH3nSMSzMVxop1Huuy6KsFdNsSu1OmCGv95/eMNOs033uz47mwtICYnoDBTR9voQzDMAzjHmICMPehGD5PbSuQjLnsH1BYAmbKDY6OtgcTHauHPfl2vlxPW/zk+NLgC0Cl6fOzE9P89sEeHAKs0MefmljyPcGOAzxXiXP57CjCdpDEGS81OByL8C/29xIXS19TSsmFmfqy4Ms1p6YqPDSYJiZCwjAksmk7rZNHOn6v0zdIEE990Leoo2ooOT1V6XhOA2ema/St8PBr2TZHx+eX/+BVpycrHOpPdHyA+CDi9QqN535IWCleP3j8HWIPfgL2HDJBmHtAPRScmLge0Mslovzq3PVrbL7ukchE0ErTChTVhSJWdXkA8JpgbARr+16CoHPQw1E+n9wQ50BfkpqvcC1BJgKoDz6o29Q2PzmxNPgC7Y2Kf35qlm/t68Z6n9eP+h7+iz/FnxhdPNY6fYzIlp04T3wWZ8sOOHui489GduylKW3eGK3xzg3BlMlSgyNjJb65v5+Cs/z9sCyLMzO1ZccdS5BPxfjrt6+wrSfJtXjsXK3FD49O8N1DA2Ss2wsqGetDqBTujr34k2MgJJMVj4X6tdWMAjZs5qcjDR7dnODY6AKzxy+gggABjE3abOnP8YUdB3DOvEd55ArpvbuZvvrTmXiES/Pt1aq1ZoCXchlMOhwsX2LqhV8wojWb83GKx4/hJBJ86nPf5O3Lc3xzXw/lVogfahKOJGmFqA9xnxrGvcC2bU6MrNwGlhfKNKankLSDL79qpDl/fhShNbpSYmqhxuHhIb696xEib/yy/UNSIrv7lgXWo/h8cUuG8nAWv1TCHj1Pevwc6vA4DUAcfp3EZ79Go2cArTV1bfODIxPMNtrpbQFqXsgvTk/z2V29XJyv0p+JMlNduqqm7gV4oYsr4fRUhYcGU0QxARjj41cJBBdmqh3PKQ0X5uok+pIcHS8CsLGQ4uenp1mot9smTbvv5yD42clpfutAD/bVyT3z9XDFtGF1L2SuGTIQXXrcBqyT71J967Wrrw6cP42VeoPPfOU77OkZoOZrHEuQjQgma4ofHZtop9oVgtHRMqWGz2d39NCdcrnQ1HT1DTN27iTDuSjiplXfzo59tFZxEt3dIJp1VKO+4vlwahxreKsJ8hqGYRjGB7T+p2sYd0wIwYW5Bu+NzHFqfIHjYwtMV66v6njz8gJN3Z7RO9dSFDukM4F2R3mu0e5samEh3evLkkUkwki0m8uTVwc1LdmebQ6Umh5Hxkq44vomqNfK1fAV23sz7B3MsWcgR08qyrVQgRcovBuCM0G+G3f7nmXlkokk0U88tepBhlDfenPVcjNYzNd9Mw14wcoz332lUKxOeW0h8N55bWnw5arGO68RKS2f/WmsPzdfj6FmyexAP1x6vTWUAHvlmLtMJN93dYYKQxLSp8cNydgBqA8XTJhthFRX2Dh8utJkoXXrh1kpJfrciSXBl2u8C6fRoxexdx1EpjPt74/FkYkUCInd1QsbtzHb1EuCL9c0/ZCXzs+hLQclbcqhQ0U5YNntfPzB8gfQ/myct0YWULBs02Q/VJycri2mwliJEIKIVriBh20CpWuelJLKhh3UPvlVansepRm7nvbSSWdY2LQfX8HJySqVliIWsXBle4GmH2ouTy5wJdqNjLioiIt3w3VjCYF3dfWWpj2IdTDqMfvir9Bq6Woqv1aDt16i4Gj8QJG1ArojIXHhr+rKSsNYr4QQlBsrt1kNLZCRKMJ2GE30cf7qpBktBCKeANumVG3w1rxCFroBiD34OK1UpuPraRXQ45XI/fwviR9+mebUJL6WICTa86i//HMifgshBCPFFvUgZKHhk45ICq4kFZFIAb+5MMfO3jSHx4oUktFlv+daux+E6pYbjBvGRykI9YoT6ACqrYBAtwMmAJYlmastTb3cXpEimK+1mG9eb7eC90lxe+0esCyLBg7l0EaWFmi+/Ru4YQdSIQSqWqb12gukZUh3JCRrBQQKnj87s7jPoacElYaHQPPiuRl6Mwlmqh6tnYfw3Ditm/rXzsAG9MDG9b/C2bLhFnunilh8/dfRMAzDMO4iswLmPiSlZLzUeZYStFe3NAOIWND0b93pbV7trAZC4O5+AH/6Z+3fUejl6PT1GeJWtkAoBHariVqY4/TkZR5ccEm5FmLLTpp2hEALLNvmxZMTLNQ9IpZkT3+afUN5jo/N4zoW7g2bCPvSIvLokySGN+OdPAIqpLnvE1yJ5pmqaNJ+yFA6QuoWaYTuRFRCNh6hWO+8V8tQduXNG1GKLV1xJsuNjqf70lFiUrMaC2CceoXarfbHuXgW6+FeMyi3zkUtQS4eWUz3IIGILfGuBmWSrr3kulfpPJGN22idO9nh1QT25u14H/OstmsP4itp+gpukdbP8T28M8dXPO+fPILcuJ3EV3+HyvgsF8dm8BVsHOqhryuFZ0kujne+JwEmyw0m6vDK+RlmKi0EMJiL8aktXWzrTnLmphVxMcdmqtLCtS1ssfwzZ6zYQA8lYYUZym7oIy6fxzt5BOU1sbt6ie97kGa+B2UeetecQDq8NV7jyFgJv+VgtTJs2f0pdts1gkaT+d4t/HDE56t7e3n+zDT1VkBPKoNsTOACGgkIjk7X2F7oIbn9AOPT19uXctNnQyHF4dEilhQkXZvo7EXk1YYi5lhLgq61iTG2OS1cS690iRnGfSsMQ4bzMcaKS2d4W1KwrSdNxI3Q2LwHffE0R6eXtgvadnB6B1BeiwsLDR7d+SCZdBy/u5/wVh/NC3OUKk2mKy1aYYhAkI7a9KZcnGoFqziP7B1krFRDaE0+qOHNTqN8n3gkQj7XzZSSxCM2CzWf3tTS/RcEYFsC0PRmosRtc+8bd0fMhoRrU1thUs1AJkZEatJRh0rTX+yr3ijuWIv91qYfQqR9POvaSEHHAKMlBGnXwpdisT2OWJKnFo5j13y64g5CaFqhoNoKUBqSly/TVa8SxBIAFFtqceWqFQb4zQBVaa+WU45DsdbEtSUvzsMTn/sWdm0Me+wcQlo4O/ehhzbRsm/RWV0n/GSGyOAw3uil5SelxBratO5X+RiGYRjG3WQCMPchrTWp6Mp/escS2LLdy01Fbj1bOxmxgXaeXj24EXfbblrnTqKlJLg6lVcm0+hkBrvZwB+9BEoRuA5hS9M4/DbOlYvEPvc13ppt8ZuLc5SvpjvzQsXh0SLT1SaPbchRSNgkLLVkE2FPWjCwCXvDVuZagh8cn6LavJ6GKWJJntnXy4b4rTdovB0OAY9uzPHcyall52IRiy352IppXpRSbO+K895oaVm6JUsKHt2Y+9CrCW74Zdxqp2XdXHl5ubF+WDrgsU15fnJsAg3MVuocGMjw1sgClhRkojbo68GY7kwc+8HHCeamCRduXAUliD3ySbxs18deh/RNn0OWFDiWxLu6uiQRsYBb3BcqRPudA6IA2muBhldmQ359oQG0H7bfvFBjuKh5Zlc3Xrjy/VAPBWdnqsxU2kEuDYwuNPjH98b49qEN5BIRFm6YwRkoTSJikXBtJMtHCuKujRS6Y5w1ohTha8/jXTy7eMyrVvCuXCTxua/T7BsyMw/XECEtXr1c5th4qX1AWtTcFM8Wm4wNdNGbj3BmpsYnthSYKNW5MFkCATISIebEiXh1XK+JsGKEocbZug0xvIlkeZ5i3UPQvh9ijqAv5aIQuJZGNxtEHQs/VPSmolRb19scoTW9MQtCk+bOMG6mlGJbIc67V4qL6YykgL0DOZ4/O4NjW4i+fjblShQXArwQ4hGJbVsEsQQqlUFbFjLmorb10NArtz3Qnm1faXhcuSHgo9GUmj4NP2RzIY4OfbTWpKM2YmEWNT6Bf3VgOvR9qNUYGhgiGekjE7OJ2ZJszFlcmZ6KOURkewLGo8N5c+8bd01MKh4ezvHi2Zll55KuzVAmQoSQh4azPH9mhthNz5dSCDJxBx202792/699n2Yimt19GY5PlJa99r7BDFlX8uLF0mJ7HI9YhPU6C9UWXqhJuDYTxdpir2ym2qQyW6MwnCWir+7XZktkENAYvYhIdbefpQDdatGqVHBCqGqLF2eh69AjDD3wIAAtzT3TNwu0Jv7Yk4Sl4tIsCkIS/8TTtFLZu1U0wzAMw7gn3BMBmEajwV//9V/zxhtvUCqV2Lx5M7//+7/Ptm3bgHbH6G/+5m/45S9/Sa1WY9euXfzBH/wB/f39d7nkd4dSim1dCd4ZWeg4m2hbT4qkpVEK8lHBUDbGmfryQcqhXIy8y+KqjZZl4zz+GZI79hJOjbHL7mc+lkO7URCScHZysUM71JUmtnAJBfjjV/DKdd683MARio35OKPFxuLsqMlSk/wel/3d7oqbCLe05NnT04ubXkN7cHdDIcXRyQZTyQh9SZuemLWYU/hOaa3ZmnV4ekcPb1yap+a18/j3ZWJ8ZluBpAyWpR26UVIGfOtgP69dXuDSbA2lNH2ZGI9vytMb1bzPCvvbpqIxrHSWsFzseN4a2EhgZjCte1prNqYsPrerl99cnGO60mJXXxbbEsxVPSJSgYZC0uVLu3roSrpMVBK4X/42YnqcYHwUEY1ib9hCK5O7K5NmCzFBbzpKuemzqStFK9BUvYBM1KEnGSHvgr5FwcJIFLu7D2+FFV/2wEYmPMmbl+eXrSAZma9zZKLKpkKc90aLy39YCEKtaXXIO94KFGemynz7QD+vXlzg3EyVIFT4QciXd/dxeGQOOgRgDvSnV9xjx16YpnpD8OV6JUOab/wa56u/3Q44G2tC0RecuGkwKGIJAg2vX1rguw8OMZyLcXaqjFetsqU7yaXpMhMLdbrSBTJ2gXjYwLItdh/YCYNJlIZv7Ovl5HSDehAyW/Wo+5rf/8RmJop1jo7OQ3c/CcdiKBejUvcIr36WW1Iy0J0lkUnR7FRgwzBIWwHf3N/PC+dmmSo36c3EODZZwbIkKUfw9pyPGtzDA5sdpspNAiQNLcmnogSB4vxMmYFckpil0e8T6/CwmCLWzjd4U/vjhYp6KMgmMyil2JFxeHNuhogtaQZqSeuxJeqz1WkR3dbNO5dneWZPH8cmyowXG/QkI/SlIjy+OU9/THdqdgzjY6GUYnfBJdRdvD2yQMMLF1cNf2ZbgbgIUEqzM+9S25Rnru6zuZDg4lyNiCUZyMZIRmzqgcdwIUHeFYvPl0KFPLEpTTpmc+TqRLaka/PAUJY9PVGKLbWkPa40A0T/Bjh5lLmahyWXTomJZrNcakomp+oc6o+jJXSlE4jAI7t3G+NzVcYqNt7VCXM9MZtT58cRvf3EHZtsRODfo/n+6vEU0a9+BybHCafGkfEE1oZNtFJ35znBMAzDMO4l90QA5n/8j//BlStX+MM//EPy+TwvvfQSf/qnf8r3v/998vk8P/jBD/jpT3/Kv/23/5aenh7++q//mj/7sz/jv/yX/0IkErnbxb8r8hHNZ7b38OLZ6SVBmJ5UlMeHsyjVntknVMCX9/QSeC0uzVVRuj1jcLiQ4OmteeQNKz6klGhh4fUOonsG2KZs3q2PUW0FWIFPeDWI4zg2D/fFUG9PLP5seaFEI7BBQ0xqtubbOXaV1jiWJPADItgrZuhaaKnFVExAewA3m+AHRydoBYrhfJyUDb3pKF/Z3U2MDxaEESpgb8FmS66fqq/aKw2c9vH3mwCltSYtfb68NUttUw4NxC3d/tlVjId4doTog49Te+Fny85ZqSwMbEBrveJ+NcY6okJ25Sw2Zvqo+u178+lomoqnqbRCXFuQcyX2DSNFTTuCGNyMs3E7CEHD9+/a7D1bBXx1Ty/HZxr87buj7Ydm2rN6d/Uk2ZTtJnOLmEOgNfEDD+ONjSyb+SsiLs6ufbx9pbjizx8dL/Hd3iEGszHGiktTzoQaHhrKMTLXedPmkYUGjw0l+NzmFI8NZ1C6nYJDISjVG1ycvZ6CUQAPb8rTnxAd0wxKKQk6pXy4VpbiHNFaGVK5Fb/H+OhYlkX741IsBtDKrXDZBAapFUOZKJcXGtS9kEwswqXZacJyiW89voOJyTkawFylSdmWUMiyMS7YMljA0+32KyJhttri9Ey7vbWlYGSuzKe39fAvH9lA1GsirmxEzU6SiUQXc9FHpCD96KP4sfgtV0Aaxv1Ma01XJORbe7soeeBpyd+9O0rWvR4kOV8O2TmY4UcXZmkGisjVLRGGsu2B5AeG8xBUbvFb2hoBHPNc9mzbgX/pPEK0g/eLE2C27CLI5CEI6KlO8/SeQZ4/MUrStal7AaGGgUKKQ4mQ3qDE5i3d7OuJ0gw0DwwMIAVopYjbGqlWJ9WuYXwYUgcc6nHZURig6ikcS5CJAOH1ZySpAx4diFH2ExwayvHyxXkmFuoIoRACtnYneXJrDnFTRgFH+TzU67Knuw9fCxwBMRmiVEC5JZa0x36omM32kMoXmJucIQjbu2xe+5bYocc5U4UDOYtfXChzbrrCfDNkbHQKSyue2tXPY5vjvHZ+mh29GSqzc4S1MnHZz5d29xIV7//Mt541nShieCty0/b2RCQzac8wDMMwVsW6D8B4nsfrr7/Ov//3/549e9obsn/3u9/l7bff5rnnnuN73/seP/nJT/j2t7/NI488AsAf/uEf8q/+1b/izTff5JOf/OTdLP7do0J2FxwG0kOMllo0/JD+dJSehIWjlqZV6ElFeWZHjgUvS8NXxBxJ1gGudo6FEESbddTIBYKLZxC2Q2THXrIDw3z7YD9vXylxebqEO9jPg0NZdmRsEtV56vkugrlpAGzBks6xRBFbHHhVRG15y4fLmze431BI8Q9HxhY3Ig9CBbZkqtzk5YsLfHFbFv0BUzUopXBRuNfS/d5hv1SrgPi12MdH0KfVWuNv2ELiqS/TfOc3+OUyvrBwN24m+sgnaUaiy3cIN9atZddjAFlbEpEWNV9R8zWZyPWP+qjXhLHL+OdOghC42/fA4Eaa9u0Fo4UQREIf2/OQoUfoB2DZ+KnsBwprCq04NrZAb9KlKxHBloKIhFqjxbOnZvjO/h6sFVL7ATTzPSS/8A2ab71CMDsFQuD0DeI+8ilamTzVy7O0P12WawUhWoV8eWcXRyarnJis4AUhhaTLIxu7ODrWnsXZiWu3N0hWYUhchO1focACvrA9x9xQltFiA9uSDGejZB2NULcaGDcB0bVGSkm0NEdw9iTh7CRhKo+1fQ9eVz/OjYFB0c4bj+eREIKdOZfNXQmCUDGQiRO1mlw5eoLfPriJwxMVLs9WsKRgZ2+aZwYdkjJAKUFUh8zPzpFXLQoxm0rTBzRhCC+enqLnwUGijiD62WcI3vkNXDyLhY9MpogeeIRwy05CE3wxjI6EZVP2wQs1MVtQiITMehpx0wyY4a4Uf/XmCNmYQzNQeH6I0ppi02em5jOcizE3cz0AYwuB26whW00UoIXET2eRUpCyofuBB3GkR+PYO2jbIcz3Ut9xiOqeQxSu9sWE12Tn6Lv0H9jHlZak4St6Eg6F6jSRc2+R3fxV6qFHweHqvmjt9JoIIDQLX4y1IwxDYpbAs9qrRJqhJGFZS9omFYYkZUhSwrd3Z1loZWmFiq5MikhQRwUrp3N2Ubji2tft/9pyef/prQXFZz/3DbaMnSerGqSqdWrVGmLLbq5kh/gCdUbGxzhzdhQZjVHIdmF3pZgq1nj+1AS/8/BGtj04wEDCYXRknJ17BxneM0DM0aiPcPWLlBK3XoFqBWFZhJkcnuV87AFWrbXpTxiGYRjGKlv3AZgwDFFK4ThLN7+LRCKcOnWK6elpisUiBw4cWDwXj8fZtm0bZ86cuX8DMAAqJGNBtmAjhNPeI2XFTeQDspYmawGoJYGDWL1K49l/aueLFZJQQ2v8Cu7wZgqf/Dyf35yCfABHTuH/8P9HMHaZaqGXxGefIejppXHyKIVsnP6mZGxh+YbYUsBwNorukO9BSklTW1i2IEBiCU3clszVvcXgC4BrW1x7RL0wW6O8MUtKfvC37trvDoVEaXBQH8mm9kIILKs90rdS6qJOAgThxh1UCxuZmZ6jFsA536F1vsWnt6YYiJnZTPcqJS1OzHq8cXma+tU0eUP5OM84CdJeg9Yvf0x9ZoZQa6QQuJNjWD19RJ/+Kk3H7fiatm0jLYvA83AunUW9+xrVc6cAcPc+AJkcutUi9sTTNNz4HZV3ph5Sa/q4i/fj9TQqs9UWC01F1y1iQ0prGj0DOF/+Nm69CkISxJPUAUspNuRiHJ/pnJQpn3BxLY1UAY8PxjnQ104DFbU0ForZdJRLc7WOP3tgII3u8HAqpcQS0B0TDCUTBEHQ/uy6xbOzUgp7wyY48lbH83auizCRXvkFjFUnhMAdH6H6/D/j+4rJSotK8zz6tbfo+vTnUHsfIuE61FseslQinJ1cvB7yhSxbIz0EsRT7B9JcOnyJWqPOiXePsbGvwL7tObRW7Ev75IUmCHwiV85TPfw2ExcmSMfiPLX3AGN9O3hnzkdcHVw6MVnl6U1Jmm4c8akv4j7wOJYKUI6L50Y/kjbIMNYrIQShsAg0KCxePj/P+ZkqoWrv97B/MMve/hSxiLUYaHdtyUIjoBkomkGLTYU4UctFo7EFTMxXmK62sLgaoF2YIXz7VaqH30DXazibthHZfQCaTfoee5Lm+Tc4d+wY8UKBwsOfwbEshG0TbN5JMp1CCI2UErJ5qJRIvfsCe91oe+C11cLzFWHEIch0IeXSvQyllPhYSGFWwBhrR0U7vHR6nivztfbK4IjFgxty7OuOYnXK2xcG5GwQjqA/n2BiovOq42vPXFqDI5YGB/JRSdK1qbauv35vzCZWnqV16SxebR5LWGR27me+Z4gNo+dplYu8u+ASeh5BvY5VWiDb0088GqLiDtVKlScrxwkmRhlwXSKbdxBGPtpJDo5SyJPvUj/ydnsPQ8BKZ4l96vM0u/vvizb+gz73GoZhGMZ6sO4DMLFYjB07dvD3f//3DA4Oks1mefnllzlz5gx9fX0Ui0UAMpnMkp/LZDKL527m+z6+f8PGtkIQi8UW/33jf+8V11JS2QKc8gJ6YQ4sC5HvRivVsb5SSmzLInjzJcJqiVoomKk08QKFbUm6Wufp27YHN52i9dwP8d5+FVWtgNaEU2OU/+r/TfKbv0t03yFEMsVT22L805EJajd0oAXw5PYeci6gbiqDkJwrhbx6ob2ZYzLqcGKyzO7eFJUbXiMesYna19NLhErjKxDW0teTUjJbaTJVCfFaLTKuTT7pEMrlq2+aOJybbXB8okyoNJsKcfb1p8hYq/MQLISgqiwuzjW5NF8mHrHY05uiJyaR75d4/KqppuAfjs3esCy/vbLpx8fG+a1DQxSccPF3rWe3c7/e+O/1Xt9bkVJyas7nhRs2QdXAlYU6z52c5OuN01y5PM5C3UNpjUSQiTn06ikil88hd+xfcv0GwmaiFvLe1ev8yeIp1LuvEp8fR9oOnu1SPnWa9M7duD29hM//FPfL38G7g/e40WGPFWBx0LkV3l66PF9a+Mnrn/OCdmBjV0+Cs/Me9RuX2F09/+jGPJYOQQiUUkSFWlyKp4G9vQlGivVlgeHdfWmG0w7oYEnZmticnW1yanQB5bXY2p1k72COZNR634f2INeNu30PrbMnlp6wbaKPf5qm7SDu8LNlLV7zt3u/3vi1JSWRahm9MAthgMgV8NM5glUcbxTSohwI5hvtoGVPVMCxt1GBYmShQTO4+vfTmvlXX8AtDPDwpl7ePHaB+thlkBIhJbt2byFdyPGPLx1Dd/WTzGU5+MgDnHn7Xeq1BmMTszAxSzYd56lcN7pnA/Lke4y98jKtQDFfbaKrTYq/fonevfP0bXmc1ydqWEJSSAUoO8qFuRrvXJmh2grIxiI8NBxlyJUIsfoDsKt9DV0bWFFKfWwDxmvxPrhTd6MOd9IXXu1yRbTCKi2gW01EPIGfzt7R/R4Im/MLHodH5+lOxzg1VaUZKKJW+wO+FSjeujyPbQseGs7z8rl2mxmxrasrzyBiS6KWxLo240i3u6GtQJEQgmhpjsbP/gF18SyqVgUpaU2MUWl4OF/6DtPTZdKxCAtS0JyeYnR2Dn01leHGMGQq8RS/uVRnOBdna6FA4bFPUXvlefBa1EPBeKlJIwjJf/qz/Pxyi30DUbZmLASaYmBxbLzC5bk6lhTsG0izLR/FZXUHLO+Fe+dOrOf63knb+lFp4vCjoxMU69fL0fBCXjk/ixDdHOqJrBhEuNV738Dh9HSdU1OV9n6cXUn29CZI24pIs06iPMmXN2X5yalZmsIiFnF4yJ+g+PyzDGZjjNcCWkELXn+dLdPjNGJJWvE8vtei0vBQV1cgZ6YmEekszalJSpaHiih04CNcF3vnPvwbnoellNRCyVwjJFCKbNQhG9Fwy5XOK9dZCIF98TS1t15d8j1huUjtFz8k8bXv0UhmOr3MunKrv7OHzWjF5/R0EYBdPUmG0g7ObT73GoZhGMZat+4DMNBOKfbf//t/51//63+NlJLNmzfzyU9+kosXL36g1/vHf/xH/u7v/m7x682bN/Pnf/7ndHd3Lx7r6+v70OVea8JalcZrz+OdOroYrNC2Q/PRT9N74GHE1VVGWimCiSt4584CmvrRt1FaMlUHR0p6XYXUAWFLUTl+hK6dOwmOH0ZEXEhbEARIvwVa03zrZQr/j/8XkaFhCkAhk+LCbI3RYoNU1GZHT4qhbAzHWr5c5eh4iZcuTRCPRolGbDZ1u0Qdh1PTFR7flMOxbVKuRX/CJhp6YDvIaAzXlvTmMnSnrs/211pzfHSBn73wBpWJCVAKKQQ7NvbyhYe2UBgeXuwsLtQ9fvLeGFPlFu2EQ3B6zmOkvMB3HhhiOH9nKwA6GZmv8+P3xqhfS3/UCLhcWuCh4Syf2dZD1Ln1Ztx+oPjVu6NEY53Lcmbe45sHBoD1fy3fzv16o/Ve31tZqHscPXGZeHz53z0rfKaOHqPqKaRlce2OqvgKXQ1IXjpHz6OfQtgOwcwU1RCeHSlybK7Fudka3xiwOPXCr8lbAT2ZHsan5gm8CkIrxMxv6P+d/xupSJW+2XEKBx6+7TJXZIV4/IZ8+kqh6lVUsQhhQMFL0Z1OYXf33vH7oVotuuZn+NqWBC9eCpjz27VOujaf2JzngcEsjn3rpXD/RzbD5fk652aqWFKwoyfJcD5OIrK0+Zyrtfjh21eYGhklnJ0CpXjrHJzJpPjdLzxI/2Avwrr1fRt+8Rv4W3fSOnkY3Wxi9wwQ2fcAzobNZD/EAMpauubv9H7Vvk9q9AKNN34NV9OSaCGI7dxP7ImnsBKpD12mhh/w6oV53hqZJ7wasbbqFR7t3cfGAIL5C9j20r93rDjF0Yky39yaYzTIMlMP2LRjM0dKirNvnYDAR3pQEi4nmz6f+sQjHD9+AeW32NCT5XO7+xnsyaGbdS6/9w6NQBO1LVLRSHvfNCm5fOQoGzft5cVAAgopJc+dW0AgqAQSrAgLHvziXJEnt3XxyS3dH8lAW1irUAi9druY78JKJO/4NZTXIhgbwTt/Gt2oYw9txBnegl3o/Hf/KKyl++CD+jjrcCf36mqWy58Ypf7iTwln2ylqtZREh7cS//TnsbL5W/5s3QuYr3mcm6lyfLpBQ1v0xh3empmFWoXQtYnn84h4CmHbnJhq8n88vAHXdXn3SpFAafrSUTLxGoPZ2LLP+Xw8QjbqkI91UXv7ZZxmHb/VREYcWtleRioezdFZMkeO8IqfxiHCFz/9FPqtl6i0AuxIhEgkQvHsWbzNDzHTkMw0apyYafLNHQfpT6QoHTvC7NgM0Y0DxHc/wFGri/l6yEuXymT295NybX5yfIxmoAAbFLwxWmO0EvLNAwPk4qu/t+W9cO/cifVY3zttWz8K715ZwMMhHneWnTs50+ThLT30JjqvtL7m5vd+ttriB++OMV/3uPbMdXymyaWSz7c3x4gdewt8j41z03xv8wEuR/KkUi6pFw7T35cm7kiiEsZLDbxQoy6dIf3Ao6hmiVQ0RalaJ0CigNlKk97+FBKLfMZFe3PkHn8Sd/cB7J5+slfLpLTm6HiJX52epuG3A0pCwJ6+NE9v7yYdW17/96tzWClTOXOsY/8dwJkaJbt91x297t2kg4BgZgrdaiBiceyuHoRl0/BCpspNnFSefNxZ7LPM1zyePTrOeOn6ivXJi2WGsjG+vr//I/lcMwzDMIyP2z0RgOnr6+NP/uRPaDabNBoNcrkc3//+9+np6SGbzQJQKpXI5a5vYFwqldi0aVPH1/vWt77F1772tcWvr3UOZmZmCMOQvr4+Jicn763l/pZDODGBWihjK41qNICrM89fex4vGqee72nv9zJ6geoLP4MwJLZtF42xK5RrDTZu2EijVMQrLhBqjZASu5AnmC/QaLVo+u3NRwUC14kRtS10q0Vzbpa5aBKkjadgU1KwJRFBa43yysxOL1+OrqXN6+fmeTxWJz51GT01Bsk0A9t2s2dPN/l0gsm5Cq3JMdR4e+NjpMTKd3Hg0A5UvchE9fosrIqy+aeXj+NPTCxZ8nzs3CiuUHwu9KjHkgghOFMMuTi5sKxMdeDF0+N8cUsadQczoJb/LWyePTXPbHF56qNfn6rTH5d0R9qvL6WkpSSBhqgFQrXL7mEzMlOk3uo8a+jiVMDEtMtgb9e6uJb7+/tXPHer+/XGv6UQ4t68d29QCmxmih02BxYQxqKUqg2EVuhQEXdtXNvCEoJWEFKtNYhMTdB882W80ctc3PUpjh0bpxXPkE7kSXt1qs0GsWyUc3N1hBeiw/ZsQNuS1CanOGF388WpCRoXz9OM3l4gMiZs0o5mstRAALI0TzA9AcD2oS7ct37FdHGW+Jf+BY072IQ+XivTfO15gskxepIpvtqzgermvah8D4moTVT4zM5M3dZrdUvoG2g/UIdhjfJcjRs/lYQQHJ8LmLgyjj9+5dpbzv6NXWyUTRZ+/He4mShyx1507xAtZ+UHSdE7hN0ziFABnu1QURomJ2+73kte6y5d86txv147l29UmP/VT9A3zZqtv/Mb/GiM1vZ9H6puQgguVDTPn5hYctxqtvjl2Ut8+cAuwpPn0EovLqCytEKVFpivB/iX59n3+j8gMzkudcUZPzKGjrZnHct6jSiKhKWYWajwWzszMD9DevYI8le/ofrYk3hacnmiSKnp41iCQtIlUKrdXgYKqziDpBspBIW4w9+/O8q3Hhik1WgQ3lDv50+M0h/TxMXqzBQVQhCrldGnjhCeOYZyXOyhTfitJpHd+2n2DN32+26jsU68S/3Gmb0n3kOm0iS++C+o3yK9npSSlm6nNo1Jjf4Abeu98Nn/UdXhw96rq10uN/Bo/fPfEpZu6mOdeI9mqwmf+iJBp98jJFdqmtcvzTNW9hgvN9nfn+HpDXEmzl+kOXoZAE8ApXnsTA56BvCRTBWr7M3CxmSOmq+wbYfJYoVy3aMetFcOp6M2j8U9+udHcZ57lXLfIK3Tx1CeR6A1KtfHpQY0QxBo/Itn6d75BKcvT/KcgH+Ry5F852W8gU2cm2wikimU36Je11ha0VyY5blRxTfTFc4O7mM02aSeLDBaCuhJB/QlbAKlODU+T7UVMF+uLnsLztXrHM9F2Ja59Z6Jd+JeuHfuxFqv72q1rR8FKSXnp2rU6/WO5+vA1FwJv7zCqucO770QgqOzPqOzRYQQBFqgae8b6lU83mjN8eTYZZpvvAxA5LUX2ZlMkX7mO9SbRbQKaY5O4NRrbEyk8N04rlLI+SmacxUeefAppoo1hNL4Sl/d6ykgTBXo29HDe80BHtxUoBx4MHG9j7AQ2PzjO6MEN+0F8+b5Orb2ebjv9lKC3ljnaL1CdXqKlfLVBpcvUN95679lzG8RjF4mHLmAdBycbbsIuvrw5a0n/6y2qNcgePNlWpfOQRiCZeNu2UntwBP8aKRBPZSEfpNdvWkODaSIy5DD0y3OTcwve60z9TrvJC32Fuw1eU/eyq3uV8MwDOP+dE8EYK6JRqNEo1Gq1Srvvfcev/d7v7cYhDl69OhiwKVer3Pu3Dm++MUvdnwdx3GW7SlzzbXGX2u97joCnQhpMVbXvHN5mplT5xjuH2LjJx+GZgO3ViTvlYlPXsA7eRT56S8QqVeo/foX7Q4VENQqWEPD2KdOoi6dxc5340kJYYhWCt3bTxCqJXl5NZpm0O7sZmIxtONwpS5458ospUZA0rV5cEOWDSmJXOE9boSa/bpI9bl/otS8PlvGOnGEjU9/HhXfw3f6FL+Y11wburQtyf6sxaFwDilTiymBpJRcnqvRnJyiUxf12OUZHhzOEY2nEFJyfKK44vt5abZKdWOG2IfYErXiaa7Md953AuDcbI2ewRgtbXFyqsHR8RINPyQXj/DoxhwbkhILiNrWknRuN3IdC0vcG9fy7dyvNx9bz/W9FUu2NyPVQF86RsSRtPyQqVKTyy3Bto2bCc4cw3Vsig2fVugjBWRiEYL+jZSmZtobe/cMcHS6jtKa5vwscT/A7i0Qc9pB0lrLJ+k46DBAA61AEzoR3r44xwMHHiNfKaHd2O2VWft8eVcXz5+bZ2Jqntb0BJaUbBsq8KmUhz52uf07XnsB+wvfxO+wWb0QknIomW+EaDSbHJ/6z39EWL46iBf4cO4YyXPHiB16DP/Ao4ThneXSvtVDr5AWpybLBPPTi8ce3NJD7+k3KV08R82ySHXFscZGsHsGcJ9+ZsX9drTW7WSBwoI7LONK1tI1fyf3q23beCePLAu+XNM89i6RzdtpyTubbXojJSzeHpntVFC0lBydbrCnb4CZSyOESiOAZMRC9QwRnJ3DdSxUtYJMZzk5VUV5LYQbI9AgpE3oK5x6jZGzl2FPjtjR19BCE2jNwnM/xnri85SaPl6oqXkBAkF30mW02E57p6VNXyrK45vzHB0voYEzUxW6ky7TlettXytQzDdCYrHVSYEZnZui+aO/wjt3qp1qNAjg8JsknvoSjTdeJvapz1NP33o1wuJbWZyl+tZry46rSpnWmy9jPfWVjoPqLeFwYrLOiYkyXqjoTUd5ZEOOnqha8Zq4lU73gRACLS1CBY7UqDW+6fDHeS/fyb26WuUSc1PLgy9XtS6eI3HwEfzE0jQ8QgjOl0OePT6JBkpNRaUZ8NaVIrI4w96exOL3Kt3+X3NhARVJMBK6XCk2aXg2GzMRCk6IEIqv7+nhl2dnmSw1iUcsPmsvIF/6BTEXWq4Lnk8wNY50IlTzg9RxmKpW2/vCRGIk3ChBNIawbCYujTJ3cDOF8EWKdR+tQhL5PGfLLaR00TMzhPOzXElmmHzoYcamG6hklLytyA4VeOtKkelKhaRr88zeFEfG2+F/AUgpFlftAZyYLLMjl1/1Afe11IZ8HNZjfe+0L7zatNbLVozdSIp2H/X9yrLkvZcWJycrhEjm6z4LdR+lNVHHojcqOT9d4ZCyubHWutnAW5jDLxepChfbTeEioFIiMjOB1dNPIC2ciEPk3FGe2H2A185OIQIfadlEknE+u3eAd0dnqbUCtg3kSNyQ3lNKybmZ2rLgyzXvjZbY0xPH1bfflmitUZaNjEZRzeV7oQLIVJZwhdSdQlqElSrnfvC3lKdnsKWkkIiQPnea6M49OA9/Cu9DBGFu3G/K0rfe8zSCxvv1L/DHLl8/GAbMnjhOcaJIYveTVJSg3go5Pl6i2PD53LYujk/MrPiaR8dL7OrqXpxkaBiGYRjr1T0RgDl8+DAAAwMDTE5O8r/+1/9icHCQp556CiEEX/nKV/iHf/gH+vv76enp4a/+6q/I5XI88sgjd7fgd5mU7T1Unj0xiQwDtg31cK6q+adfnSEVdxkQDeJBky/te4SN06fbwZD52cWNAQH8qQncvQ8SK1eobn+A+a4NNOtN8sIjOXYGv2sQFYsio7FlncpQaUT/MJORHD86Mr4Ysqg0ff651ODxzQUe6ot2nPGa1CEzb7yA9jy6XUlMeVgRl6qWjD//S1LxPKOlJl86OIwKh6g1WvgzU3hn3uTMO1US3/49sr1dJIWPEILZchMdeGAtvyVank+z3iRhWSitbxla0Tf8/wd1bYBgJS0/RFkOz5+Z49z09VmQU+UmPz46wWd39rKnYHNgMM3zZzp3aA8OZO4oT7GxPqRszYPDOcqe5sh4iWLdJxt3ODiYZaYakDzwILMXz1IvV+mSAbJVBaWwkj14w9t59dIcT+x6iHjQYKCwgWhvPw0/JGELVNIlkcvSqJYBAaKdCkprjXQcFiIpfOlxuaYZVTb7+2yCICCiQuzSPLrZRMTj+Jn8siBKHJ+v7cxTzoTUUv3ECElPnUdfHlv8Hn9ynES1vGSfFwCkxdFZj9cuzOKHGlsKnnEXiEzO0ZWwEXrpg2Lz+GHi2/bQuM0VOrdDA6gQ7bVnS0ddh4HmHKWL565/T+AjtMafGsO+cAq5+9B9saHqh6IUYXH5jMjF040awg/A/eABGF9Bpbn8oT60HexCD+V6DS+SIAgVPTGbgvSJb9xIqVHhX+zpoc9uUuXqbGMBKhKj1goINLg9WUrFBqmZcSKBYr7h05yt05V0ycUsitUG8XKZaCZNeapdz9maRzrm0JNySSWixHdv4xOtKH6g2N6TZqrcpBkoLNkhEEm7XY80a4jiPCgF6RxeMrVkkPb9OGFA69VfEYxfWUxHCoBW1F76OYmvfgf/1FGsx58mfJ9rWEpJMHKeldpFb/QSiVqZIL40lZwvbH52apax4vV+w6XZGlfm63xjfz8DMfGhBxVD6XC55HN4bI6mF9KdinBoMEN3VH+gAI/x4Qgh2qknV6JCaNThpgCMh8VrF6YWr7BczOGxjGYwLGPXKwxns/R2Z5maLiIlBKqdqixWWuB7D25nW/Ey1RNjVPNZerdvwUukyFgB/2JPF0UPUl4dfvJTpCsoNQNGSlVkbZShTTtpvP0qQa4fT7cHRsNQUwtCUjsfYKol2n1Kpahj0SVEe+81y8E68CgXL4xg9Q/jFecJ872MNTUnJis8d2qGesunv6/AHukxXmxQaQUs1D3OTFepe5oHhrJoBC0/JOlaNLyAS7MdVr8axsdEKcXGXJTXROdnmOFCgowDdxCXaL8ugpFi43pKZqDWCrhU9YjloogbVhQL26ae62N2Ypa0HaPlK8rCRcRjpLO9xFs1ICSxaw8zP3qW+dok7tQ8z+zeh5/IkRseZtLNUGt5VJoBst2sLyGlZKbmrVjeuhfgK3DvMBuoH40T2bWf5uE3lp8UEnvbLrwOEwSklIzXNd6vX6I00V7V7YeK0WJAPh6h78wJkpu2Qs/QnRWI9mdyObQ5Nl7h0lwdKQV7+1Js74rhar/jz9ileZo3Bl8AhWSq0qBVPMe2fQ9TEzkeiwuS82Ooy2UcexMHUmleaUr8DhOPAqVRWnScJGkYhmEY68k9EYCp1+v85V/+JXNzcySTSR577DF+93d/dzFn+ze/+U1arRb/83/+T+r1Ort27eI//sf/SCRyf+cTbWqLVy7MoIFMMspkS3DkSnu9SKnWotCVQsyW+dmxMb77iUNkhUD7N3U6laJVb3DhK3/AC6+8hz92Bd/zcbJ59u75ArsTDmcni3zqG99j7u//N4TXBroEbm8f/pNf5ZW5YPHBOR+PsCsWENUh9UqRWu8gcZZ3ON3KHPF6kazlEYyPoRNJxolSrbewIw5i9ALHzs5z7B34xoF+0kdewd+6lyvT7RnqslTmxemA7xzoI65DulNRRIfgC4AbcYhGLJRqz/rZ3ZtkvNh5if1wPk7cuvMHjBslbEE2HqHY8Ai0xA81UkDEAqE1G/NxZurBkuDLNRr4zcU5Nmb72ZaPcqUnuez79g1k2Ji20R+mkMaapLXCtm3++d0rNK9ubj9TbXF+usq/fGwTs4kM4qmvs+nIC8y/8RuUgNiWHeite7jy4kvsfuJJphpxmkHIz8/OMTZXxVcareHJB7bwhae+QPkXP8Z2PYTfQCsNUpD71Gd5drxGbONmFqp1zs832bS5j0KtTPOFn9GcvxYIFDiDG4h96vM0IktXyAgdUhg/ReLI2+26LK8dBAG2EDj1KqgQFY1xxbP59dmZxe+PRWzU7BTT1SauEycTWfoUrL0WNOuwigEYoRW7+jJMHLfRYchgIU1w5uXF86mYg6MCtBCgNd7p4zjb932oGYkrlkUIAmFTarXTaTi1FlLKxRV/64kWAqvQA1cudTxvJTOoW6Rzux2OhFTUpu7dFITREGYLZNw8g/MlktkY6aCGtXEbs8Jl8qc/Zk9fCr1tC8kvfIPaS8+y41CSd0dLhJaF29PLvHCxwoBGrcFAX5b47AQVpZgoNxAiTrkVsHD8BNknP0/zJz+kW/o4QmPpAN+O4O1/nP/rSImpavv+cZ323kWFmM3luQoIgafaC6WSrk1PwsEdOUnjtRcWJzwI2yF64CHknkP44tb7HV1jV0r4s1PoVnP5yTBAl4uoIECqkLDDirQbCSHQjc4zeoF2kKjDtTlRDZcEXxZ/vdK8cnGeb+/tQn6IjXmVtHl1pMzRsdLisWLD48Jsja/s7WM48eEDPMad0Vojk7faX0ggItFlR6s+lBrtwcD+pM2D9TEuPvtLykELq1Zm9p08/+cTn+Lv7SzjMxUafoiQgq/tKtDzzk8ZH51EaU0ZiBzNkn/qcwTD27BrJRIqxKpVKDVrjBSbVFsBtm0TzM1T2TBMmOoiGZE01PV7K7VxEyetPMWIS7Srnbo34UgQUNi6lWDzQV4aaxA0W0SCANwYEy2BKwVBtUw+aiEch1NTFS4Vm3x2Vx8vnm1/BiileGhjjp+dmKTSvD4AujEf5xOb8vSnnHX5WX+3SClpKIuy1973MXuno+bGEjlH8dmdvfzq9NSSIEw2HuHJLXl02HnQfiVCK4YLCV48P7f8pJRkYg6Oiiz2/4LeDTS7NpDMZUl9+ilG/ukfmZ5eIO5YzDTruITs+uLnma+22PHQQWYuXOLibIXa2ZPEHniUv79Q4xM7M4zM10DAhnyChK2XPNMppehORrjYYeEsQCJi44g7bzvCMMTZ8wCRhTm8y+evn7Bs4o9/hlaue+mEiKua2mJ+chLOnV52bqHukYtHcE8fxx7YdMcr44qhxT+8N07jhuDXS+danJmJ8tXd3R2DMLq6PG24r6AVtF8jEbb4pJ5k/ic/pnh10tLMuSMU4ik++/iX+OW8XLa6aGM+TkSoDqMBhmEYhrG+3BMBmCeeeIInnnhixfNCCL73ve/xve9972Ms1dpX9tTiA1xPNsnPjhQXz6ViEfq6MmSSgkqpzCWSHNQamcnTng90rXMkmO3ZzC9ePUooLJzhDfjVGtV6g5ffOkXmsw9zYWIB9u7kE//m/wmnj6DmZ6F/AwvDuznmdrEw2w4QPNpl03vpPSonj+K3WiTiceKNJ0ju2kPLjhCI63mtdRDQbStKk1dQfoiKJWl5kuz+XWghiURdnESCWrHESyMVvuREiS5ME83laJXLBJZNqeEzUmqxM2sx3JUg2t2DP3M9hdA1+4a7yOXS1K4+1G7KunSnXGYqrSXfF3UsHtmQRYcffFDItm0cAY9v6eL/+9YoM9XG4szleMTi4ECGwXSEE9OdA0AANS+g0lJ0uyGf25Ll4EB7E3EhBZtyMQpRkCpo7xhp3FMqgcWbFyfYlIvRCBQ1L8CWkqRrc3amykCmm3KjyVwxoOvTXwINFyZmKL/6JpYKGRjoZnrzIV574yjxWBrblqhA4YeKl8/Pktw/yGNf/x7i9HHU5CgymUZt3MFLZZtRT/FwT5ap8Su0kgVEo0njl/9MWLq+gsHKFZCWDaePETn4GN4Ns8yVUli9g8DbHesmkylsx8b/9XPURs5DGGJlckS2PciGVBcjlav7HwUhIt4exJuteqTyNw3YCQl3OGgvLYtQ2O1ZiChU4C0ZnFVKsbkQ49jwENPnzuNIUH77s9WyJF2uRMRSqBs+v4QKYZUDMFJKppqCX52dZq7a/nwqZMoc6I2xqxBZd+kbwjAksmsfHH376iC9wO7pwYol0GFIZPs+GpbdcVDiRpZl0VICIQQO4ZKVR1KHPDyc45+PTSz7OV8Jst15rnQ/zoFNmymdPcPslXGs1iQDSYdKqULi5V+S/Pr3SHz52wz1dLHRS3O5CTOhRaWlyDiCXCLKI/0J/HeuLL52uekBAg+LRqKLfV/+PP7xw4RTE7g93ehHn+J/T9pM1a63My0/4KVzs/zrT27m+ESZyapPqeEhgK/u7ac+egX14s+xb/g768Cn8c5vSCQzBJu231ZQQYcBWkiwLOgwYKO9FiKRQUt56+WatO+NyOAwrTPHO563UhlULLH0mGVx/haz+afLTWqBIHV78aSOFlosCb5cEyrNr8/N8dsHe3G4s8FC48PThV5kLI6wHfzuATTgzE2iSgs4/YP46eyyn7GuzlIXAh6yKkz86jnsQBFqQToRwwp9qj/+W/7l//mvmdw1wFzdIx136TvxGpcmpq9/LtOevZ6fnkCeO0VtfATCkMTOvVAqosOl7cbFw0fo2fMw2cFe0uNjDPS2aAzt4KxT4PlLZYbSgki1Qk82QW9M4Dz5Raz+jbw1E1Kq1tttkZT48RTV+SbP7B9k7Nx5YsKhle7DK5bwtCQTdXhgqF3v/nSUVy/Ns1D3sW+4/i/P18nFIzy+cQAddAicGstJi9PFgFcvTC+m680nIjyDS06YAOwHoZViZ86i96EhLi80qXkB/ekoAymHyAorJqRlESiBbXVKLyvIRG16ki7T1aXPXKm4y8aMS7kVIwU4Q5uIbN9D47WX8LsH+GFQYMNjX2BDeRrv3CmIxnC27eG5qmZ7o0T1zAX6H3scJ9bL0VLIG1MtAuGzq+5zbLJKNubw+KYCOlw68VApxbauOO+MLBAovbj6VWsNGg4OZYhJxQdZRNm0HCKf/gLJ/Q8Rzk0jbAfR3UcrmVn8nLpZqaUI/QDRqa2m/UyYarVwhMAKfZRlL3me7kRKSSBsLs41idrWkgAMwGSpyUjRY0e2w+t0SK979S1CA/lElMs//gGhd/19DZQmFzZovPkCWw59iTPF6+dcW7KvL0n4IZ6tDcMwDGOtuCcCMMYHI26YuWpJQV1LrFiMT2wp0NKSs/N1bB92bNyGTCTaOWAzOaL7HyScm15MRXZ0ttke2HKjNBaKBEJiZXK4OTg1Osvefdt4a97jaDFCz+CniG6SVJoBC1Mez+yPcXhknm2ZCF3Hfk3x3BkAXEvSF1Tx//mv8S4cgK5e3IFh9IbNtCwbkUwjAp+4LYgmUswf+hQLpHl5vEjgB2yPDrLj4S2cfuV1xibnae3dgXr1WQqPPEUl18V7vgt4XJirs6eQJUXAV5/YzS9e1RSvbrQohWDncDePb++jmcouDvK5+Hx9Tw8nZ+qcmqwQKs32niQ7e9M0PJ8rniDjWmQiGn2bMxEjKsCaniQ4fxLCkKGtB/jari5+enqO8VKDqGOxpy/Ntu4kSrcHHG5FXn0wt3RArwv9g+3VBkqFYDKr3LPmGwF+qLHQJG1IOlc/4rUiVNDwA6IXTzI9Ns7C6BgCiGXSdB96CCuewE7FuVJsoDU4C9Nszvcx1QiptEJ8S3J0vMyWAwN4Bwu8nSsysVClP4iR7Y7w9EaXjSmbcwyhqj7R0sxi8EVGY8Q2bye4dBb/zHF8xyaOxtp5gMYNM5pVVx92Vy/B7NSyuqUe/wy1X/2E4IaUVEG5xPTPf8IDT36B2UgfdS+kFSgaXQNI2yYI1dLxYSmJ7X0A0lmk5n1TgEkpKQYW71wqcmR0nkYrYN9QjgODOXpSEVx9/SExis83H9vK8UyE8ak54hu3Em9WybuCmAR1w4obp3+QIBLlAz2h30IxkPzw6Dit4PrrNvyQ589M4+7pY2t6/Q0qOUObSH7myzSPvo1b6G5fP9NHsPsGYONWIoFHy+qcgkwIQSm0OTpW4dJcDSkEu/tS7OyOE7s6uK61Zjhl88SWLt68PIcftt+fiC351JZuzk6WsK2A0y/9iqBSwRLQUBrthxSuxs9aR95G9/Yzk9/Khk0DuI2QU5MVBuMhW1KST+zagvOD/w+RSATPkTStCJHeXnIJl8quR5h6/Ze8dfYssWyWfN9muj7xJO9UJZtzDkO9Oa4s1DkzVSHh2vQkI8zXPfoyURYaPnt60+wdSON5PsUj7xIu1BnORrFzeWq9m9C2Q7Q0Q/PEYZwNm29r1ZVOpCAWx8oWCKbGl5238t1YGzbTuI20ZlprdO8gVjbfMZ1c9MHHaUXcZfdCpxRr11wbbP+gpJRc6bC65ppiw6PkKbo+eGY74wNqReN4X/2XHDl+kdPj7b1gtvYcZP9ul+SGAeodVlylHOjLxLC0Ijz5Gzw/YDDpkNUtRLlMSiZJfvbzhO/8mu65WVItn+zDj9PKZGiG7VQ5yc1bCTZso1ro4dLCJAVdxbKsdh9OSOoTY3QVemnJ65/jWikuvHeMmc0HsT/xMADPnpzk4mQdGXERAvqGevmcniD45U/x9jyEJ1y+uH+Q01MZjsw08NwoXW6ER3fE8Bfm8DwfETSJJvNsLCR4ZFsvk1WPyXKLhGshpaTa9NnclaDa9Km22mmScvEInh9QbwZkzJPd+xJCMFJV/OLk1JLVtvM1jx8dneBru/JkLdNZ/kC0JmIJuhIR8okIWVfiCrVsnoSUktmW5MhImclyk2jE4vGWTbdjYd2wurFUa/HU9i4mKi1OTVZQWrO1K8mWQpwLlyc4EIkgojHcLduZ/uk/4gcK/5Nf4cyFed45P0l/d4b0jidZmJ6ldmIaoTW9uwcQ5QXGXnwe9YXf4nIVNnZnqLYCql7AA4MZBjIxJsoNerojS/YMtdB02/DMnj5ePHaF6vQM2vewE0n27hxmf28CpTqnKLMsi3ooCDVELYHdYU2HJyy8XDci33O9v/Y+/bZJ5bC1t5/a+Oiyc44QRAcG8X79HP7EKNKN4u59AL1hC60O/YEGDicn6xyfmufiXI3NhQQHhvKcniwu6Vsen6ywq5AnvCnwo3MFZCKFql2fRBGREI/YqHQWv1wi9JYG09JRG1dqelol4nGf8yVxdQVSnMc35sg5HyygZRiGYRhrjemm38cyriAXj7BQ9wiUIuHaHNw6xJGxEiPzNdJRB0vYzFypMF7z2ZQZors0h2rUUNPjCGHhPPQJShMSq7cfkUiiax5zNY9apYWQgrJw+dKWYc40xyk2fCarHq1QU4g7fH1Lik12iy25KNtFhcr5swBYUtInWvgjl4lGbRrv/obEM9+h/uvncLfvwXnsM/iJFNG9D+CPXEA//CS/WLC5ODEKKsROpnn5/Cy+FeFrDx3gnV+/DoCq14ilM0zv2MHYTLtzHHPk4oaP/QnJ//0bj3NlYhav0STjWnQnIngRh/Cmzm8Un4d6XQ70xEAIJmohP3hvjNrVNDaWFOwfzPDoUHLJbOROXOUTvvo8zYvt+odILrx9nNzAEL/79NcZ8fKESjNTrvPO5Vly0R6GsjHkCnmWc/EImYhckgfN7DVxn7p5YpoU+NUyjiVoBZrCoQeZyQzy8sg81bEKj+8tMJuQKDuCaNRxZsfZkEyjNgyibBvXkTgC3r4yx86eDI9szPHcqSkuFcskIxY/rjTY3ZflgeECduMSFS2xwpDMpm3Uf/5DVL22WJbGay8gRkeIfv7rixvSt2yH2Ge/inX4dbwLZ9CBj5VK4z74CcIgWBJ8AZC0Z8c13vkNO5/8Nu/O///Z+68oO648Txf79g57vEvvgEwkvCNI0IOmaIvlWL67p3tMSzMyS1cvkl7mYV5GL7PWPGgtSXfWHd3RSK07PdPd0+W7HMli0VuQ8B4JpPd5vA2ztx5OIoEkAJpuktXFOt9aeEBEnnPixImIvfff/H7ta/69msXDjz6N/8ZvNpKVVt8QTjZHmF+l9Xd/jdk7gLl9L41k5rZJibxv8NfvTnF2aplgXdJteiHP6atxHt8/wv6h5CYJBluE3LtnkHAsh1Ppppm/ilYKZV2XyBCWhbX3EPVP+Z6UUnJ5ubFpgXwj70wV2LK/G4PfrypCYRh4W8aJGQbVX/wt+D4incUPFd7rL2LPzWA/+BievHk6cyv5jDeurHFxuco39vbgridhhAo41Oswnhsk3wgRArIRk5gFE0sCVyiCZpNQ3SCBYVqkslGMlomMRHCOPEHUynDq2DxJ1+LPd8VpnT5G+dgkze4MhhsjmLnE6MNPEihNY+ICie4ukmGF5sIEZQFGs4Y9/iA/nKzz2pU1hAAzmWYol+AbBwa4tFjEV7BW99nZm2S8K06t5XNmLs9QyiXMr1ALNLX9D3KyKrlwNY8f1OnJ5Lh363a2KfWxuq68SAz3wGFab7+MbNTghvvW2jqOzPXi9418rN/PXJfdSzz2VVpXztM4dRxCHyOZxr3zPvyhsZvGpzAMGe+OcXr+5g4VgMFMhLip+Yfokfx+pSH/cKgpkx9dXqXqxyBhQOBzouVwuZbgm06K+C26koQKeHhbjnPTKwTFPAMxk3hhgUa5RCzqEN93hMpP/htCgzm6HVUu0zhxlGagGdhzgGoswzs1h0unlslmmgRzU2R7u3n6wCNkT72Kt7ZC5MDdVE4cJdW/ldL6dWdKQXr3Xl4uSnbGW8wX63xtPI3enqUctGVzhqgjV2zOJf6cd2cKFM+XcSeb3LF7C//kqb0QtLCXZpj9zY8JVcjo9r1Mqijn6k12bN/Kj04u0Jd0qTY9Yi2Tc0sVys2ArrhNMmGh4hYIgUSBVjRD1UnAfAyUMHh3evWWz4FAac4uVXhoONaRc/uECGlwuRTy8qX5DRlcyxDcNZLljr5Iu/uedgJstg5/d2ruutxUDX51doltGZsHR2JticswZDQX5QfH50hFLO7bkgagWGtxajbPcHeWnsEshq1pvPYCpmURRl3q8TRVtYiwLMoreapKUilWiQqFQFPDJBlP4jWapC2JaZsESiFQ7O6Jc26+wMmZNVzLYFumn6gURMoFgktnCJbmMSIx9o5upzerWY5FCVSUtAxIX32NaOowjUzPTfPKlrA4Plvl3GKZlq/Ixm3u2ZIlk/FxWw00bR+Ya75qH7dYJuVI1jzYdfAexOL8Jv8yU0oyrklYq9K6dBYAVS0TvPIczo69WPc+jM/1VroGFj85vUS+5hEgWa15LFVanF0s89W9fZycuXEOfuvja9ku0Ue/TO03f4e+5v2qFYO9WfL3PEVxfmbT33fFHFwp0FrhypBcTPBndw8igKipIQw6yZcOHTp06PCFoTNN/wPG0gGPbO/i704tsFRqcP9ojkorZKrQwLUtpBRoQIp2oPPEpTkemHgJtbqMEAIZeHD6OH27nmCpImiEgikvRGkTbIE2DMx4jBMLRb6yb4BLq3WOzhT4ao+md+oEtaOXWJCKh0a24vb2M22bBEoTk5pwYQHXkhii7fvAuvdM69JZ4jv30sz1YQ1uIfb0s5yx+1idmUcaJlaui6Ybp1CsIaIGpwoBX37yfnor0+hnvsXs+EFenqxvTBt39SQ2LbBS8ShhNoZSLkopmnDbSI1SCgNFKTD5xemFTZq1odIcnymSsC0O9li3TYAIIZDzMzTWky8AgQZfKfzZaVJnjjLXtY9i/Xo11UKpyZ4uh3u25njr6mZdZMsQPLK9C4ugE2D6AyQbMTCluEk/GdrXRnfMIti+ndLsHNHhrVy0uzl+pl0xF3dMlit1ZEKSj3fTm0i0q+4iMTAkEkXKNtmetUnYPRSaiv9+Yp6Gr3BNyVK1hdKCMwslhjIR/HgSf2EOnUxTfed1wuVFzEgEve61JAyTYHUJe24KMbpzY7HZdKOYR54kevdDiFaT0LIJI1HC156/6TtprcjFbCbXimRpwfpCstgMeMXt4Xt/8i+I5udwHRsxP0Pj9DHC9fawYHUZcfEMsSe+TrNn8KZ7VBgG715eZWapuJF8ucb0apVytY5XglRE4juRjUWzpzU4Ds3IAO63/ine+28Szk+DBqtvAOeuB2ikch9Z0fhJMQyDmcKHVPXXWzSVIPZ7qDxo+B61o28QWvZ1+bj18+dNXiK2+wB09W16jTQM3psq3ySdAbBabXG10GJP1rgua6lC4hLiG2pYPgTw8LYcJ6dWSee6N1WX5mIOsb4erOQOrIEhvHQXqVDTn4oQJaT1259TmZ2l0gopzc8xuns74489QfPlX0G5jHYT+GGIO32ZXGGeaM8wes+d/HCySl74WKZBEIToMOTcYhk/DLlzKMNrV1bIJSL81XszVJo+O3sT7B/IsFKqI1NZ4gMj/GSyTrlyPWmysFriZ5Um3xgZY9D66C4opRThjn04joN//B2M4hqi1cLeuQ/7rvtpxNO39ZMRQmAYRrsrNr+Md+IojbkpGkJgj4yR/up38G0HZbs0TWvjWAzDQCMQAsIgoDci2dmX5MLiZj15x5Q8OJq7wU/uk6OUYjjt8uZt9qciVts7qjOIfq5IKTm/WKdU90GaEL3uB1NuhZxerPLAYOSW86kuO+TebT20LnWhi3O06lUSroUzso3q6ROEno8ZjyMMA2vLGOVKHbl4le6nn+Vo2WW+UCLZ1wvldoCxWGvys3MrfH/7QdzTbyOGthG572GMtTVKpQZWLEZk7yHOZsfJrwakVJOBxRM0XjmLowP2jw3Tfc+9eL1DvB8Z5o3KHMoOIROjFYnyVkmSv7TEl1aPw5XziGqLaqUO8/Ns2bWX7P1f5oeXy+i2zRpKt7sZ065F1QsJlMaWuj3iXbuHpCBiGnTanD+aVigofIiR+nyxiRr+MD+iDjcipVyXQIXnzy1uKg7zQ81bV9dIuX2Mp9rjT4DBK5dXbjlXPTVXZHdvbKMDsTsieGAsR6tYhLDOjGeQr3u4lsEDoxmaZkB8zx3ok+8RSWZYqymCUIEQ7VvDMtH1GtFEHKNZQ0mTrpjFfKWBlgaLDbhaaDDeFePO4QwTy2UK62uuph/SUpDLL1J7/ifodWlZfI/Ciz8nfveDuJZDsNL2T1VAs17BeuY7eOJ6sUMgLX59fo3ZwnX56JVqi+eOTxEWC+yYPIq/MIM9PIqz/y4aseTHTsA4BNw/luOtK4r7nn4W//23qC0vIg2Dbft3Ee3uonrm2E2va108Q3znPvx018ZvOLHSJL9+X5hCE3fact3lZsCllRq5mM3a+v7dvQnULRKUWmsauV6i3/hj9OI8qlxAprOInkFCJ4kwFMFxA2kKMjGbqNn2+oG2Zx1uhJhYP8+d/GeHDh06dPiC0UnA/AGjtWYoKvjuoUFOL1ToTkZ47sIqCdfEEAJfaUwp6Eu62Mrn4tlp7hwYxF5dRmtNaBiE1RI7RZkzOsFKNWgb8trXdbLvHMkxuVIl5doslxo80yeRL/yEudXrlWe2vkrCMckJn5nQYMDWGFJhCrmxsBTGDRPZuRnI9UFXL+HMVS6oGO7IVppKslhq0MxXkW6EhC3xajUGmhVKv/wR1ugORKKX8dQgF4o+h4YzdEcA1a76ubrWZPLKFF6ryd6+JFvS9m01i68hpeTSUv2WiwiAY7MFdnT149xmQWxIiXf+5Ob3BCQChaZx6RyjQ3s4doPlSyJiolXIob4I/ckBTsyXqTYD+lMue/viZMzwM5EZEoZJPWgHyKKGuuXEu8PvloSpuXc0x+sTN7uD3rM1S9rw8XftYsvZYzT27eOX788TsSSO2U7cNNwE27MxXp/MI7NJXEMQMUGsX0+HRzLY2mM4qgmUZCBuUQ80K1UP25C4rkEmanN2Zo0HxmxMFeL09uG9/gLa89BBgJ1IQCKFsttdL/6lcxjbdhOEIZ6wmCp6nF5YRWvY2RtnLOISC0NM52bzZYCoCQOZOCuGwbWIqWVI9g6mMbMuXjZF3GuQf/FX17X51lFBSPH1Vyg99m2qwqI3bhORmkYIYSiZXKlRrm+WSpBS0J90WZlfxrt4kVargDkw3F4039BNo5SinspiPvY1Yo0aoAncGHX41JMv1z4vGTGZK956v2sZmL+HyRcAo1ahUbiN4y0QzlxB9gxsCszWQ8HUWu22rzm3VGFvdxc6+PBnfLejODzWhWk9yNxPf4gpNF3ZBN07d+FfPkfr9PuEQ1uRy0vE993Jl3d1szY9S2Futi3xZxloLbGqJaozM1S7RhC7erEJEQtXkbaJo3zsVoWF3ADzF65iuw49mV7mCzX0utbWpZUa9492oZWmN+7w2rrp+LnFCgLBUNJG7tjPcqHC2vQC1gfyIyLdxetTBb69rwfjI8Y1AF9IwrHd2MPbSNom1ZaH50ZpfoiJbwuL6aLH5ZUy90SbOC/9lEjoIdbHv9als/izk0S++j1a6949UkqKvsHZhSqzhQYxx+TAQJL+GDwymmQ0G+XkfAkvUIxko+zubY9x/9CK2KwDe/uTnFnYnOCRAo5s68Im7ORfPmcCJJeWq7fdP7FS5fBADPMW8ymtNRY+mbsOUz72KtoQeEFIor+fxm/eB60RmS7C4hpOIo2XyZLbv59CoJm4OEUYKEimMLoHIVSgQmr1JotGF1sNEz17lTVcnCe/i1dXVLXkN4sezYUG/5t7tyCe/wFrExM4pkFX3MEtLlL59U8Ivv5PeXuyTmDZkMpuGCEI4MLZS+zfMUBOn6U36RAClaZPefIKqSOaYr3F3v4kxYaHbcq2n5tr0J90qDQDojFjU5Jwe3d8Xfr2U/9pvnCYsj0m3q5jNO6aSNGJ/34UQgiqymRipUGp4TNf8akFAveGeeM13pst0pPsZb7YwLI0C1UPR4pbzoem8g16+l201sQreQ5fPUbpyhUKdY8tw2PEDh5GdPeQkAFaQyglKhJB+z6ZuCA/O8HOoTHOTa+AaTOypY9kVw7l+ZTLFeTaElvSEcS2XfxMRdnTr9ndG2c0E+G1S9clcA0hSOLTfPOl68kXQNdroDWNd18n/vU/2kjAAARrK7iVEl4yu7FtuR5uSr4gwPcVS/ka/63c5Kvj++lKjdC/fBn/Vz8i8pXv0HA3e6PdDq01W+KS6M5eTi9EiBz5OgNmQG8qQtoIqfzgf+F21QTh/DQy24NSCiUk55cqN74x3TGbaisgVJpLy1UeHc+xVvPoTjhsTTvo28wltNY0nChi63aEEBtzsygekaF+crtHqc/PtrffcGjOzr148dSnLs/bocPnQSgM/FvFg7RgdqWApyQb61QpMDqDdYcOf5B0EjB/4CilyJqKL22No6TJhSWbvmQ3IPACxVS+xnKlhUED0w/Q4uZLJnvxKE889H3+3+9fn4A6puT+sRxBEND0Q04tlOmP2xjTExRXrwfSUhGb6UId4WlkrYwbydDyQ/BC4raBpG3cfaPGrFgPSDUTaaL770QdmydcXiGWzpGNuxRsG9uy6A3KOKuryJgklstQ9VoEb7zI4Tvv5u7DDxN3QKqQurb48eklinWPaDRKvd5gvthgMB3hmZ1d2B9ixCulZLnSuu3+aivA1+DcJvAptNow676GLTXJiEWx4aF8D+uGYIMUMJaLolSAQNHvwtD2VLtyGE0YBp96bFcIwYpn8PblAvPFOlIItnXHOTycWl/8dMJU/1jQKuRAj0s22s97M0UqzYCka3LXSIaDW7LkV5axMmkGv/FtzizViFoGUoBpWxhdvcz4FkuXl3lqdx+XVipcXavRFXcYTNrcPZJmLG2hVYCUkrVaE60UEQkjKXujW67YCjEaNVaXS2w58hRGrbhxfKFSaCGx+gav31Xrhg4eFr+8sMbcDYvUxXKDExGbb+7vpWvrdjj1PjctJLWmd3yM1Nggsf4QNKQjJkkjRKkApCSYm7rpdQGS2UKT2tI07q5FTqokmbjLTKFOy/PYO5Bh1dOkUgny+etSSL0JFxamCXtSBM0aym/QmjiPNzvZlkpMpDd/jtYEN/i/QPu54WmJ0uAa+lNJZoZhyN6+BOcXyrdcau/pTxI1FF/IvOktDEE+KtfU3v/Rzy6lFAmpsEe3kv3mN2i+9wbu0Aj1F34Gvo/RO0AQhuiLZ/BnrpL7ynfJZGxWszFKzQBDSkwJ8s77OFEOODkzh1+ske7p4u7dD7PTbmG4LqJeoqnanWra94j7NXozcZbC9oKt7e+r+fr+AaZWq9imxFsPHp5fKrOvf4hLnqRuGZjmMqhw44sa6Rw6kWSl0qIeQNIyaSkwBRj69gl7pRQt08Ls7aexsID+kORLA5ufnVlitdqiJ25Tvfge8wt5Uq7FQMpBrle4qkad8NJZjEP3o5RisSn46am5je9CBa6uVrlrJMM9g1G2JQXb0jmUFhiEKOV/KrEZqUKObEkykIpwfK5E0w/pjjvcOZyi19WbZFw6/P4QdPUTvf9R9CsvYLVaSCGRhoHT3QNKEQYhxWqL2L7dlF/+OZWn/4Rq06fuBYTVJSLFEu7gMEazhlnOk68HbHNdgnqDrsFBztkpfnk1j2ko4rbFkdEunMVJqjOTpF2TUGmWy3WSThxbKPILS/h+BK51jK3fajIMCGoVlhsJumwbw/MYSjl4cQdfKYJWhW25GEKFxBIWSltIAXOrFZ7Z3cPJ+TKsyzlJAWPdcR4cTaPDj06udmjLhe4fTPHa5Vsn9g8MJG/ytuhwM3nf4Men2jKfw5kYV9fqzBTq9CZduiLGRnJFCcHEWoN3p4qcXyyxZzDDxEqNroRDd9S8KVlz7ekbqZWp//IHqEadCBC1JSxdRr46R+SZ71CPJgDwInHsrdtpXTpLxND01Vd5enSUTHwYK9vFyULIqxeWidom927JIUKBP7CV5q67GfQd5ot1Xjy/xKPbu4nY103nR7tjxOslqjcUgAghro+vWhOuLiHdCKp5vQP5xrFSSslcsbnxf8sQZBMxqtUaMuFyZalEvhnn9RMzHN6+lbtDH3X1InLvXR9fPlorum14fCyFr8CQIFSILq7y4fOcD58pOVIzlouxVvcwhCBqmzwwlmNXdxTnQ9bGG4e1LvF9I01p0P3Us3gv/BxvdhKUQtg2zs79iP13bXSTd+jw+4avND86dbOHKQgSiTiVSpVr9+O39vd+pJ9vhw4dvph0EjAdgHbwTgrBzr40Pzoxz3y5Sdw22T+QZFBplmfr9GTiuGtX20OHlFg9fVipDCAYd0Oe3tWDrzSh0thSsFCqMVPzYL3AKekahJMXNz7TEAKl24a31qUrbLvnIRLnz9EINFHTwgsDIrEIkQcfpz41cf11gyO01idojWwv++5IM6cnQSl6HJes7WD4HuHVacYGu0i0pgiTaaJaE7MduHqa2P591K0UUkpOzlU3SXxdY67Y4Gqxxa6M8aEBqlzcZvI2ldZR28QSt5/8hgis4TGC1eWNbVprehM2rUBh9g8yEZqAhyEFX9rRQ9bS6Bvmp5+1RvWKZ/CjE3Mb5tSgObtQZqbQ4DsH+oiKzoL/HxNCBQxHYXhPDl8JLKEROsQx211kYRgict1EnS7ia4DWaMtmtqYotTxohbw/ledPDo+wUm0SKs3BwSR9Tohal/3RWpNyb3Co1vpaYS+h0liNKmYguHLiFFvuvovEkcdpnTu1Lj+mUDfcT9b2PXhKcbUYbEq+XKPY8Di5WOWhgRyRw/fTOPrGpv1GIoV1+EF8AoYi17ZeD9IKIUBK3LEdSNtG+T7ByhLzc6sbnk2OZeBoix8cn0MK2NYVY7ncIB2xWCw1SCSiVCp1LMvAblZpeR47cy72pRLaXNfrbjXxzxzDeODxD11ANrA4u1jjwmKVUGu2ZKMcHEiQ/hQ613pceHC8izcmVjdJgGzJRrmjP074exqcC2MJzFw3wdrKLfebw6N4HzjnEanZmotx7gMSVtfY3ZdoG2x/TDylkFvGcQa3wDsvY3T1oiybQFyv4FWNOsGF08hD91HEplCrYpomztYxzpZNJs5Ooho1nGSS1UKFXxYq1A9s5Z5nvkP1Vz8gYW4UyBOUi2S35DClQ6A0GsF4Ls5rlxZo+iHD6QhT+QaBUigNfqioeiGJXBZ76zZ0q9m+L22XcN2DKBe3Kfvw6tUCq5UWrmVwx1CKsbTTlq284fozhcCqVxECVOv2RQbQDjCdmKuwWm3/Xb8V0pxtm5uXmj6piEXihseFPzWBtf8wvmHzyuXV68mXG3h/usB4V4yc1daAF3z6wkqGDtiRloxnuwiUwBYarYJN42uHzw8TxY7eOG9eufX1Nt7dTmrcpuEYAM8wsAeGiX35WWKeh5FOYweP0Th7At2oEkSS+Jlu9NQldBiihUE10IQahJS0Wh6yUqZixeiPJUlGTBaLDYrKpDGwn3MrDb55YIBqy+c355d45fIKW/3LNIOQiGmQNhTSFEgVgtGW6hWBCes+Zxu0M6rthOv6s0tohSPBkSCbRbqifaxVw3anGIAGL9Scmy/wR4eGUWFIK1DEbIOMDajfz+f77wKlFLu7IiyU4kysXO+6EsDdWzL0R2WnCv8j0NLkpctrG8mKZhCQiVjMFGCp3CRux3DX845VTxMoTWt9zPX8kK64w0qlRdQyiH8gGrElHQE0wfnTqMb1eaFefziH9RrB+dPIww+2JTOVwrnjXoKVRcJiHoOQ2Jl3OPTws/zVdJOmtBgZ6MZRARcWykzHEjzyyFd5Y2IVjUfVA6Xb3dwpx6ThtY/vyGgGXVzY/L21RkRuKKoJg03d1cKNoGOJTa+x1iOtg5kormPzxpU8a6UK2ajDkf1bSEfb+9+7tMD4oZ2YV09i7LnzE495KgwwANq1SKh4EiOZJiwXb/n3xsD19bTUil19CZYrzU1/YwtFf9xi30CKB7ckMJSP+gc+a8zuPsSXvkqsUgTPAzeCF0t0ki8dOnTo0OELTycB0wFYN3AuKX5xdpHJQp1WoKh5IbNnl7hrS4ax4S72+0s0Ti4RiUaIjm7HO3OM2usvAhD1PNyhezi1dAsPAg13DKWZz5fpNyyg7S2T7O6iNbSdnOXiKI9iNU/ft/4If+I8TmkrWoXYPX00pq+0g0mAs3Mffup6W3cYhgxkIvQNdDNXvGb2p8Fv4TgW9wzECN5f2giQaa0gVOhiHuIpmlpy8caW6w9weqHC7lwOfRu9eaUUO7piHJ8pEt4iKnBwMEVEqtuu45RSyG07kedPblpkmCi2dsUxH36YvIqzrddkMGWTNBRafX4l7MIweWeicEPy5TqVps/lfIM7uu2PX6XV4fMjDLCgvQq7RYdAJuag3BhVX9HwQnzd3lZrthdWy+U6FxbbnR9RE/pHrsshaK0ZTNq4lrFhtMr6Z1mGZPtAFjH1DmGrxZXX32T87rvw/ONY5SKGAJlKI1SIHBqFgREQkjMLt78PLy5VONQfI7b7DuL9wwRXL6EbdYyBYcTACA0ncltZLzPw0NUyrTd+iyoXkfEE1r67iI5tp3DmDHYiSTPRxevH1zW8NVRbIUvlBgeGskysVrEMFyp1IraJKqwy3JOmt5m/KWjgz03hBAFl4RAqjWsKXBFu3B/NGwxOr3F6vsTllSrfPthP2vgHVtyqkANdDiPpIeZKLbxQsa0vS1w3kb/HwTnfMHHvfojqCz9te4LdgL1tJ0Gm56bXKBVy11CKqXyN+gd8YHoSDqMfIp9xO5RSKDT+0gLKdpCBj9FstCs4XRdlO/jTVwgO3I84cDf89tcABEPjnDozTyyeAK9FKE0k7YTCWxfm2bY3S/f3/9eIXC8j+2Ms1gIwDRbqimbQDkYfGMqwVKpt3G+u1GzrilL3FV7QNq3vjSQoe4oLC0WIWpuOPWobDOeS/OzkLGp9rKq2Ap67sMK27iS7uqMorRlIOuRKi3jvvUlt3btIjm4jsucQjezNxsIADWVwYfH6/auQSON6QCpf80hm3I3gmTAMtBCUPG4K9lxDA5P5Ot397mc6vmitEevPyk4z5+8WpRS7uqOcW6hQbGwuikm4Fvv64h8Z+AuQ6IFtlGeXaGb6MJVB96EHEVcuoTwfP5nFSqYJjp9BZnooXTjHjqEdnJ1aAd2+J/1qlaArg5HrJxXxad7xIEtON0dnagTNNUrLqzx7eJRyK8AQglAaDLgSq7SMXyqhVYhMxjG6eshUV0nFtpP/QI2PNk3MWIxeI7jpmQYQSUR5MJ3j56cWCD9wYY5kY6QtjWGEYLe/dcf25ZNjaZ8nxtMcGkoxV2piSsFQOsL2/ixrK8sdCcKPoOzDYun6mm+10mLPUJbTCyWUhkorwI0agGCt1uLR7V0sFNvFanOFGg9ty/GTUwusVD3iGWfjAbyjN0F31ED7HoWrV2g0FY5pEDEF8oYL3Z+5gnXH3XiyPRGru1EiX/42emkOb3oK2dXLiYaNUc8TWVsBpVC2i5HqworFqSuDO0a6KNSazBfrRMw4O3vjZCOSbCRHT9TA0j46nkTGEqjaDWOcE0HG4qhaFaO7D3Xx3Ma+yMG78aNxrrUbK6XYkolwKe7QUoJfnpin3AzA98lXPRYrTb67t4dMOk6hWGW6FtIbjbfn7f/AQckzbdx7H6b24s/5YPuzs2s/fipz/TspxXjW5UzcYa26OQkesw0ODSQQQetTe9QEWuPHknBtafGPfB1pa4VZXEUV8gjHhVw3zUi8owLRoUOHDh0+EZ0ETAcAKtriv713lelCk6Rr0TRCSo2AqGMwk6/zrf3biC638LfvpysdpfqT/9bWwAWMnn5qwmA0LjmdNym2QhwD0BpDCA4Op9nbG+fiYgG276U2cZXk/kNcSg/y7pVlavUK6ajDPfv3oOaXKZ0+T7ynl96BfuTcBKY0UN192HvvQA1uxbvB/FeIdoX/U7t6WKx4vDOVJww1Y905dvf4pM68gbpVOet6tZLWYlM1/gdRWn/kIixrK57a3ctvL65sBMekgJ19Sfb1RtoySB9CM5og+vS38I69tdGObfUO4Nx5P82ubg4Lsd7GHXzupsD1QLBQvL2x9+XlGnf0Rv7RT5z/UBBC0NQGhZYiCDUp1yRlKoQQlJs+SppINNOVkLLXZDgX56/fn8ExDVxTsrsvQe9Qmu1dUU5Mr22876100mMy4Kt7+/j1uSWqrQAh20me3b0x7k0nWH5j3bBca+bPnmPH419GTZxHrK2AaWGNjGIMjaJp32MfDDJd/1Kg1i/8AEGQ7sI43Nv+v1Ltxc9tXmsIgT72Ds2Lp7lW1q6qFepvvYQzvo/0yAhifA+TvmgviK9931ChMbi4WOJbBwfJ132uOhIhNPcNDzPWWiV55SzGjUtRKWnsu4+Xp+tcWGmbyyZci7u3ZNiRtTC04mq+tSn5co2mH/LebJknx25tavqJ0CFpAzI5Eyklvb0JFhaqv9fBJK01jZ4B4l/5Lv7ZEwTLCwjbwd5zED08SusD3j7XyDqa7x4aZqbU5PJyhXorYHd/gh25yMeSz/ggpmliaElo2VAuEiwvbHr2Gck0RjJDLdRcTm9l+5/+K2prRZbtBDIVICMOoR/QUgodtu/RcrPOiuqD4XFeX2iwbUsfl88vs1Bs0hN3cG2DXT1xvra/n9NzRXqTLsvlJpp2oj5pwVBPgi1xgVA+jmtyYDDFybnSpmMf7U5wYam8kXyBdrB6ptDg3FKN6J1DnJnN8+VuCN/8OTHd2rivgsU5GjOTxL7yXeo36Npf/33a9+I1ppuwZXw3zaNtm/sP5u/tHXtpCclHja6381br8MUlgs839/dyYaXOheUKWsP2njh7emLE5IdLrPrC4vXJEo7tMJnez8zFq/iVCqODXTz+p/8XRpYuMH/iLKlEHLu3n6qWzE5McejhUZoDGa7MF4D2NMt1bY7sG+G3cwXWmjZrZy4R1GoYUuBLwRmzwf92JMH/PK3Jjo0hX/4R3roEkSklQgWodBYxNMbTg1t4dzLPlZXqxnzTx+DBB+6iVZ3H2P8A8elzqFL7881cD7q7nyELvn3HIO/NFFmqNHFMyYHBFNuzLsYHElGm2V7OheFn4wH4RcVQAT029PU66+ctwDaNj3xdh/ac7cYrTQPLpRpP7+7jtxeXN651geTwSAah1MYaqeGHLJfqfOeOQc4tVnANiJiS+7Z3MxTRLNVCJuYK9FZaNMrrBXimwZZMFKc7h5fsQroOQl7/rbQ0uOC5XNX9yJEBdmYcLr9wFL9SRjoOoRsj4jrsHenincUG//nNq6Rck3TE4r7RLMvFGnf0xchY60Uz63NGz3aJHH6A2svPcW0RpoTA6B/CTmcJfB/QGMk07h33EIxsu0mZIGNr7tiS4//58nU1B6TEpO3p9vypGb6yc5C8WqaW7mVhfBTLl6QtuSE1+PdBa02rf4T4V76Dd/o44doy0nWx9xwiHNyyaT0N4OLzjb09XFytc26xitaasa4Ye3vjJIxPX+L694WI18J77Xmac1Mb24TtEH3oSVpDo50ixA4dOnTo8LHpJGA6IAyTC0sN5ktNEDBfauBaBumoRU/M4YFtWV66vMpCXjNkj7C90WLfg18h+uavMLI5ig98nV9NVSg8f5SdB/ZQSyWYLzU5OJgkFbGYWqvx/PlFxvsy1FSCka9/k2M1m/fPTSIDHyEEQsLR6TzzDtzV00d+4hLh/DRbx4aI7NhLML4b75pW7fpEJxAWV4otTswV8IKQ/lSEJ3b1YkrQ5RLhT16joQNcQ2xakArLgkwOgIihGM7GuHAbmZrx7hhCqw8NE2mlGEsIeg8NkG+E+EqRds11SYiPnjhrrakn0piPPkOs3pZCCNwo9Wvabb/DGa8UGkPeXqTUNMRN2s0dfjcIIZitC35zYZFqq33d5WI2B0ZyzOZrlP0yhD5buxK0PJ8LK3XmSw2+e3CQRMRiptDg0kqV5apH3QsY6U4yt1ah2PDZmo3etMDQWtPnKv7o0CCz1YDlSgvblGQjJpYt6b7zMCvvvQtAxq+R//mPSI9tI/b179GYn6G1soR67w2cagn7yJOMd8dYuaEaXiFohppKK2BfMkZDSRzbwgp9UCEB7ftaCIESJkprLLnZT8WulqidO0HUcZB9g8hIlLCYR4aK4OoEg//iK/y4Gif3ge8Wtdqygw0/5MRsgaf39PHNHSlCDZGpC9RfPYn+QB2gv/0Av1g1WLKqG4nSStPnxQvLhNu7uaMvwrml4m1/v6m1GvUtKdxPyfZXa/2FWhRqramnchgPPoEV+GjDoIW4KdhoGAZShZS1zenZCpdWaggB4z1J9vTGSIhPLp/hC4u5qs/5pSJKa/bs/RJ9mFg3GO8ChOUi0cER7FgcMxLwny+sILDY1WtxlRg9VpTkSAS7tEa9UAQTIskk9rad/N+PzhE1DVxDc2RrGssyafmK8Z44WoX8/OQsVV9jSsn+oSwTy2VqXkBPwuXx7TnE+neSOuD+kQSjuRinF8o0fMV4V5SuRIQzc8XrBysEi+XWRnfQYrnJYCqCOXGUqaUC27pi2DfIZ2rfxz99DOPIkzfJhERMTV8qwtS6FGep4VMa2knk6mUaayskXZNrN4XZ2w9bxtvmypYk6VqUm7f+PYYzkS/UNdzh4xEVPnf1ORzsi6ABW2jC0P/QqZBhGLw3X0caJj88MUfDC4ml+0lke7kCFKZafP+uI1R79jLX0mzRJubFk6A1C6+8xF2793DPnaPUtSTR388VFWWl3OTkXJGu8jJhvYbWmiDUgOT8XJ6DusA/Gd9FxFFEnvwahRf+DtFqER8YpPjs/4oTVZP3LjVoTVxl90CKLx8YZrFUo9RsexxeWatxdFVhlBX3brmHveVJnFQKc/cBGpaz7uugeGZHipZKYwiBqYNNnXu+MJmrBpxbLKA17OyNM5ywP9S7sMPNXHvOiFt0C3e4NXFTEnfMjfkmwEqlRSpQfH1/H32JCK6pyUZtTs1XODFbQAroTUVwLQPPV1xaKHBoKMudA3FMFIN9OSbmV/jluUUMIRgZ30Nj7VUAdDTGwoGHuFIOmV+t4vb2sq+o2ZaxcUTIlYrmSr7JldUGlmGQMGB8bIiTc0WWWppyzeOx8X7+5uwyodI4roMGZosNfnZqgf/jI+OkrfZ4KMT1uYVSCm9knNhTEbwT7xAU1pCOi71rP3LHXrTvE7vrAZTt0jStWydAVYglJMOZKPmGjxSCiOUSJaBSLOMHAV4kyZXWGvsR/OhCAWWUGeuO88hYBucTdutu+mitqae7MR5+en3uZNKE2yZqI/gc6nHY3xNBI7CF+sjn7+8Kw5DIIEQbxqYikE/1M6QkOP4m/g3JFwDttai9/Cvi3/gT6rHkZ/LZHTp06NDhi0cnAdOBks9GAMQQAkMKDnU53B1rMSZKLM0sEk32ULBNaobBsYlpJiybbz39R0i/xc8uFylV2vJZ506dJzq+k/1DWaaLDVam1toJBCE4vlDDtQy+smc3L758kWjXIBkbzJaHtAzKc7NcUIo7Do0jr1ymK2YTrCxSKxdJ9vQhFudR9RpGdy9e3wgvTBY35MNMr8n5qWmOv1nj2XvG6XIE1p33c/UXf0d/wiFrg7YslJBE7n6IVjQBuh2svXMoxeRq9aYq/7hjsqMr+rGCdVprosInuiEL/MklIQKlCdzYR//h50jU0GzvSXBitnjL/fv6E6jPURKtw+0pBia/ODO7IRfnmJKeVIz/6dUrdCcchjJxKvUWr0wUuH8shx9q5ktNhtIepxfKzJeb1L2Qph9SafqcmF7ja7t6iLZqjNoBhjb5YDpRCcnphQpvT+Y3vCsAoo7Bs0eeZO/2cfT0FSK1AmLnOCKdpXzsHXSriQBMzyN4/01ivQPs7RrhrGNQaoWESObKTSrNgIhlMJR2mb86g8hPk16ZRAiBs2MvzdHdnC+HnJwv4AeKwbTLgYEkWWu9CrhS2pBdCIVEZLowkhkMNNoXzBdrLLVcotGAgaRLveWRIiDRLCE9CW4EbVnkoiahXve/GRjG6OklWLpBF9wwWE4OsJo3b9ml9u5Uge1d0Q+1OxVcE2fs8GGEShFKY/08Xz9fhhA4+WX8syco9mzhx1cbVJ0Yyo2iEbx7dbXd0bS/j6j4+A/nQFj85uwiU3NtiSIRiTDntcj63XzlyDPYL/8dsC6rNb6XmexWfvjGFeZLTcZ7U0RcG0NA3ddMF+qMZKOsygzx7hQCSCWjnFtrUW6G4AgMYGK5jBF4+CGcmFzmyFgW15R4QUDNC3h/tsg39g8QMTS5iMT8wBhlqIDBCGzZkQbaAaSV1uZry1NsSnxIBDlb4c1NobSm2grJupuvWH9xFsdrEpr2pu06DLhnJMNcob7RtfLGmuLuI1+lvzRP9+pVTAHWjj0wuIXmuh+GK0Ie2Jbj12cWb7ryR7JReiKSjiHLHyZKqQ25oY8zw6iHgulCnUbIRlKx6imuuXu0pM+7k3keHOvivZNz9G3bS3x1lsRajUozYPXcGeyL50j09TMVfZJLDcX+gSQxHdIsFolYBrX1QHOoNK5t0zfcxfDiKfyLZxCmycj3/hQdhkzlxvibKw3OLheQKiSRy/HC+WWeP7/Mn909TNNXoDT5pVVU4EMqxxs1k66DjzJWXyA4dxInk0X0DNB0o+gwbCuN6c3Diycsnru4xnT+unzt5FqNvpTLV3Z143aSMB0+Q1wZct9ojhfObzadLjV8ItUmDw7HsXQAeIzloiyU6nQlY5ycL7VlKV2Tg4MpxrujWKq1kfxaqvobvjKF/m1Euy/QKhTgrof562NzREyB6brUtM2LF5a52hXjsR29vDm1xPszefocgV+rUpny8DPd7Bob5Mwb5+nPxJktNinWPIQQDHenMKWgK2bjmpKL83l29Wr05EWEZWMMjuAlMgS0n0GN3kGsp54l4nloaeDbTjtx59wQSvmQLIVAEzU08aRNNmoxV2hQCBTCdtCmTS3QjA5205A2gfRBw+XlKqYUPD6Wuq0U9sfl+tzpo+eZn/T5+3ljCHBWl/DOnWgXVSXTRPceopXr/dSP165XqE9cvPXOICCcm0TuuqNTLNKhQ4cOHT4WnQRMB/xQ4wVtw8HVaovvb4/Tf+Z11PQVpqWg2PDJJaN895HHedvuZ0VKirUGl8McPakMpQtXrr+ZkPhKU20pXr64wvaeOI4UeFoyX65Sa4UcGExR05IVT7MYSsa7emjOXd3obKlpg+1dCVwRIITAWF0kOP0+3pnjKNtBCcHKfV/lypIE08Jo1PDnp2nYMVrxHD+drHNfl0lfoout3/8nrL7zBomwStS1cY48Qb17YJPsWM4K+fbBAd6bKbHS1GjbYFtXnDuHksRlAOth0z9EWYcwDLljIMHUWv0mTfbRrhjDSfsT+yh0+PSRUnJpqbbJq2coG+O1K2sESrNa9ehOKHylcS3J5dUadw6nmS81SEQsTp9fxpAC2zQwpMDzfKJBk3Ozq/zzURv9w/+M3HtH2zj7BsmCfEvwzmQe2BwYqrdCXr2S55Ht2zgre2isrjIkGgz5ReKhD74HlRLB6jJatCWOrDdf4pv3PsUJo5u356qESrOvP8X+/gRbwjLBqz9jsViCpEvCAi+Z5cUlwVWRaC8qgWLD4+JylWcP9NNjh2BsHuK01oTrclVxR2Ikohi+YLZQ49v7unn+5eNQK6PEev5USh46coisrbmWZ2xaDu6Xvoo9O4l/4Qxahzi7D7Jk9hKWbt1JV/cCKl7Anr4EC6VbS/qNdsVwpe7Em/8eSCmxJy9RfeU5ZDLFKaOf4vIKsILZ3YdK59C0A0MXVurc1ed8rMWyIyUTVxe48u777QtcSpAS6TisJdJc7B3krt3TqGoJeecRTvhxXjkxz6yTo1Gr88riKn193dw/3sOTu3r57aUV8jUfL1TMNkJcU/LMti6OThVoBgpDBKRsE1FYIyiuUU4PUNMSKSUrhRqDvRnGXJPLSyUuLhV5ejyNDm///A1u8JZI2QbpqE2x3n6OqxuaKwXQm3SoVasYVju54oUKIczN3aNu5KZ76ho9ruLZAwO8OZlnsdRACFg1Iuy4825s6662FMo1ycB1lFKMJQy+cWCAd6YKrNVaOKbBvv4ke3ujmJ2xpcPHJNQCy5BcWK1t2q5pX+v1QLFY8ZFSsGcoy2uLFe679xnu3D3H3PHjVD2F3LabhfQgF0qaJ3dnWakHSK0IlEIakqht0PBDEPDnhwdo/Zf/B15htV180GzQevc1Io88zWr/HZyZmwetiGczTObrNMO2FOjz51dIOpJGw+PObITC9CpR6eNbLm+/dZIeaxFmrwIgozGiT36DRip30/xTSsmVfGtT8uUai6Um51fq3Nn78Z5zHTr8fVBKsT1tYu3t4+3JAoVauwt6V1+SO4cSWDc8vwdjgm19af7m/VmafogXKAp1j1agyEZNunqcjWR79QbPtjfXFPc++BUGdJ3nJopo28Ho6sJIJgiliUJwdrnGYK7B21N5el2Bl1+jtbqMoz1CJZgRirvGemj4AdNrNVCKRKztOZO0ZVsuW/ksXJylmG/iXDjW/vCjgsih+2DvIYL1daCPxLfdayfgE52vXMTAlIJAKaIGDKRclqsegXZwJQx3J4lFHM4slLANiVw/H5eWqxweTpG8tdLqp46UEqdegXoNYdn4iRT+h5YPfb5IKbEmzlF9/TfXJzGFNbypK0QfeBQ9vvdDpcU/Mb6HDm4/F1GlYqdzrkOHDh06fGw6CZgOuKZgpdzg4W053rq6xuj8WfJXLtGTcFkoN4k7JqYKKL38HHd+7Y94PpNDLcxytezR1ZXFMCRh2J4oynSGXDLKxGqNTMxhpeYTqLZMULUZ0AwUhbpP1DFpBopaK2Sh3GA0lSLi1UBrshGDiKmRfVtpJHKoSoV0qPCnr7Tbvsd3c2WlQrhcx+gfIlxeIIwlWQ4c1larCKrsTvbwwi/eYfjAfh5++GtYTkBYK1FphUgk0hAbUkVKKTKm4qntacxokkq5TGTd7L4UGiyUPbxQ0ZtwyLkC4x+gx/v7SEz4fOtAL5OFFheWK5hSsK8/yWDC2rTA6vC7Q0rJUmWzaaZjmSyua2f7oSJUCoWg0gpR+EznG7i2wXShiWVI/FAhBQylHGK2ifIkxYZP3UoSdSN4k5dJ9A9iaoGQEp3t4mrev2XPhkZwYqFCKmpzZq6AUS5zbmmOlGvyja0HSL31K8KVBYRlIy0btEb7PpHXfs6j9zxMZHwPazUPhCJmG+jjxyisFnEtg1aoSboWS6khLh2fwewbhER647P9UPH6lTzf3JNDp7PIaIxbtaUYtkXvcB9/PJogDCB77k36d8S4WI0yW26RcEz2d7n0XHoNN3uEevz6ZzScGKWRfTC0G8eQ4EishZsDYdcQgCkEoxmHvpTLYmmz8XjEsdg/mKGuFDH5xZIO+zywm3Uab78MWuHlBri8dD0RFqwuYcYTG10bF5arHOyLbDLzvRWWVhjzsxw7eglVrYBpo00TYVpQLiEMk9OzLfYdfJBoaZlXW3FeX1UUI13kmwrLjtCdiFMtV6m1siQdg+/cMciVtRotPyQVsehLuByfLmAbknzdI5OLIVtNgkaNoHeEoidZKDWYLDZ5b2KR4/Mlkqkk/+yuQZLFRayFCmbExU9m8D8i3mAR8PB4Fz8/vUCoNKZsd7uGSnP31ixr1SaFWsienfthcYHIugwfAMkMlR13s5IeoFnQ9MSNm8ZCrRS9Djy7u4t6O0ZNzNTo0MP/sCFThwxG4Jt7cjSVwBQaR6hPLBPX4Q8bW4JrGbjW9Silr6DuhyiliTkmZV/x+lSRK0tFQPCLmiDp9PHkN/8pySDg/dkSrtB8f6dD99J5etP9TGZirFZzKMvB0IpUvcI92/tx3nmR5uIMIhpDSAPdbEAY0rx8nuXtRSQaN+qyWg/w1DUvDLi0UuWb+3p5brbA1w7uoKEEU1WfrAgZGuonDAXG4gzOwDCmG0VfPE18534aySyB1ggpKQWSckPz+mSRhhI4BsgPBBzPLlbY1xPB/NQsszt0uBmhQ8YSgpH93TSVwBAQM9qSVRt/Iw1WPINfn50hUJq4Y5FKW1hSINC8M5lnPDvQ9jsB+hI2j+QEsWal3V2sEkwmBzkD0J0mkoogaM9nF6o+rmXw5tU8OgiZmi1gWSZ93b2I4hLN+RlQIc/et4MTSzWCSoBEI9Cs1jxSbrQtW53PY/otjBsD7VLiry5Tq/us4WAZkqwrsPn7+SwlTMX9Y128erndTRszYWvGxTAt7hxO8eaVFS4stXv2HFPSn3KJme2Ou4avSDr/kF/q42GrEHHqXepnj6M9DxBYfQNEH3iMRjz1j6IQ0alXqb/z6i06eTSNd18nOjBCIxL/1D5P2y7CcdGt5i33G7mez0z+rEOHDh06fPHoJGA6D3U1AQABAABJREFUkDQ1491xJlaq/PmeNOUfXCBitU25U66FZUjQIVppzOlLDA4eIjmUo6ngSmgxtm83htfgymKBRrILaRgIqbi6ViNhG8SlohgIWn6IYxkU6h4p12Kp3MIwBIW6z2hfErm2gGuZdOGxduhx3ppcY+7yEmY2x0BUct/Tf0rmlR8RLswgBu9B1SuYrSaB71FPdLFWaMuR3VhCXs4XmV+x0Md/S1cuhat85HtvENu1Fzm6nZbjbkwodRjQFXfwKwFKS84XAl65tLLJCHhLLsaT27PYf2CJhwg+e7IG+7pzCK4Zvf5hnYN/zGitycXsDQ+GD2JKgQLKzQDHMmgFisF0hOG0y6WVtkG7IQV9CYelQo2iDpDNBlLAubUYe+94lP4rx6n8L/8TdPehAKu3n2DsEYRo+7UoDVKA0JqWantKbKyPYnGkgOLSCmd7tvHYg08QXr2A9jzsQ/dSTHSzEOnHMiTpaolIpMRSSZNJRpiZXaR1+ixe06fU9MnXPRJdI0wU2wknVSogkulNa7HFUoNqIDCcCNEjT6LeenHzCTEMog8+RsOJktQBEVWnfu44Sd/j3kSK++IJqHsEx1ZAa8KpAeT+wyilaGDxwoU1ZvP1jbROfyrCkfFupGhXW3+QwUyElA2EPl/d3c3ltSZnFsqEGnpTURKOyU+Oz4AQ7O5PcddQEke1/lEsdn8fEKUCqnnrziK0hlYTPiCb9WFIKbHmp2mcP4OvXXw7SsMPCH0fKQIc1yFSqxFGsgSVIlVMjjVdJgp5dMKl4ilUqFitwkguxtRqhe29CY7NFPjqvj5qzZCZUoOaH9CXihBzTK6slMnRQhULBIaNBKpNn90DKS4s1xGRONprENc+p46d5aHyRerLE1h+A3vHXuKPPkPVid72O2mtGY4JvnvHICfmyyxVmsTdNIMplzAImVxrB37mckMMjG0jVl0CFCLXw6n+/fz28iq6t0Eo2x00txsLhfKJrReDSgzEujn4jd04t0KogAiAvvU91KHDh2ERsDUbQSG4tFwl0Gx4UxhSkInYdMVs3ryySsq1cKXGQtNoKX5yYp6Hh6MkSsvk+ro5OlMEmWMXFl871Mc7yQhHLy2AFNy1t58nhiSNH77erno2TJSQCDfSTsJoBcU88ZiLtB3KJX/T9WwI2JmQ7Bk3iJ56kzukwXCihxenK5xZKNF/uJ89++6i+eqvaS7Mtb/b6FGMnQeI3P8l3i3Cc+cW2JKNMltqsVxuEHdNhpIuxg3JliD8cO/CLypStjsG4aOfOR0+HbTWGAQbz/0b/eeFlFwsBswUa8wU2mN0pRkwW2wwkIqgleLpAQtn8iJmPU+ju4ctvk/ttZcor7W7q1OJJIlv/hMCDamI3VZt0OBrmCk2GclEaAaK0G8Xy4XKp+pGcE0bIUNqs9OYVwL2p7rp6knyg6l5iMSwXBPZamB4DcLVJfbt6MdZeJ/QMPF3HGShe4wzFQivlEllUsyuVQDNk7t66HM/eaGMVop93Ta56ADH5kqUGz6ZqM3e4bZP47XkC0ArUEzn64zmYkQNjWtKPrGu9SdESok48x6N4+/ceNT4i3OEz/0E96vfo3mt++d3SSmP9lq33KV9D4p5+BQTMF4khrv7II3jb9+0T7gRxMBIZ67eoUOHDh0+Np97AkYpxZUrV1heXgagp6eHsbGxjQlzh8+fMAy5czBOoDTVcgnTa9Edt4laEjNhU2wE+OG6AksYkEzG+PGJWbojJomwyOVii0w6wYP79/LTU4v0ZuJYUhIoCDSEGlQQoH2fQFjUWgH3j+a4vFLFlBIJCNMiMryVJ3okngz5+ck5duUi3HHnFqjXCKXB+YZg36PfIjd1hvt7bPpJoLKCi0YfL64EiHUTisFsnEqhiCEFpgo4fWmWhw7fQfVv/4JWuUiApPLmyyT330HyK98kzHRjFNfQpQLNwjJuJMaskeSli8s3BYKm1moci9ncP/iHZw6stSa8zYJWCIHtt5CFVXS1iognUJkuPMvuTEw/Y6Q0KAeS0a4EdU+xUKpTavi0/IC+pMtiuUl3wqHcCLi6VsNXGj9UKKV5f67A1/YN8M50gZ6ES6nhI1HI9Uqv0Z4klUKRRrFM6dQx7FoF2dXTlhpcXWZgIM/RhsXVhiAIFZYp6Uu4VFoBuZhNxoYnsyF2sw77BmmEg3S38gS1CtJ2ENluiiurrF28wnJ2lLevrpHMpjiyLcUWM+SHJ+b5Uq+FvuFek0KwXGmhutc3aI0QkpbSeKFGCnCN9niilKLZP0zu2T9Bnz5BuLqEzOSwtu9Gmxbu/BS61cRKJBBeCy0EYaXU9o65AVVuSwwoafL8+VVmC5uD/QulBidmCxzZ3sOrF5c3Al8STYKQx7oNIvOT6HQOGZHs77LY29PDdEXx2uUVztc9FIKqr7hwapFjc2W+sa+XLld2dPw/Djck3e21ecZ7D/Je5YaOpBseQTt74piGZM0zqXltGbCMKzFu6LiwvCb+1UsYS7MM9h3m8tLMxj6lNU0vQEmDPUN9OLNXaI7tZfGsB04EEQT0JKIc6TLYKmpYosbYcAJXlXio32NhZYFTeZ9T+ZDFRkjKtfg/PThIesji5OlLtPyQuhcglpbYNzTEnuEB/sMbk0Qtg750HHt5lolqhYcPDSPPvUbQbBIsL+KWS0S/88+pSwMhBG6jCvlVtNdCZnL4qQy+gpyleGI0QUASpMm7s2VOzFzvGJrxJIe/9k0Sa7P4ly+wMrKXV6ea6L5hwhvkBz9sLBRCUAwMzi/UmC81SUct9vUl6HaBjmdYh88ArTVjaQspDe4azvDyxBrQ7ooZSLn0JmxMKVitevihZii53nkpJFeW82yNS6LpLP+/t6fwAoVhWxzN55BnCjy9q5vDPS6q2SBTW4NWAgTISBS9Lj2jHRdpmqj8KtvSNkbVBNNCyJCoIZEC7uuL8GcDmujkO1TqLQIN86fP0qrV+ca9D/FecoBXTk/Tl65irydf2t9NQBigLpwm5rs8FLWZbBl0x2ym8nV0M2DV9OmNGRvPuoFMjGooqTUFCccgbWt0+MW994QQVJTJxFKDq/kaEctgf3+SvphE/oF1rf9johIavHRxkdGetkl5qKHSCtAainWP//Mel8zsOUzVQhsCv1KkeekcO/Yc5OKJM1TKVbxKGX30Ve4ZvJvX5moEoSITtVmrBzT9kKVKiy9t7+HM5TkE7XlfteGTdmOYLY+egR7U3BSBm6ASuOweH+bobIkBUyIKyygp6YsY7CpPIgpr1B7/Hj+e9ZmZaFKq1Ck3WgRuma/s7WO10uA3F1f50+0xIuXV9niWyODFE4Qfo3JAqJCBCAzuzBBosEyT5ycqGCgSjkmldf1aVRrydZ89o2nSNujP+Pa1GzUaZ47fcp+qlhHL84jhbZ/7ms4JfWRhDV0tI6IxjI96jn3KOr5KKdhzENdr0bxwGta9eIxUlsjDT9CIxD6Wr06HDh06dOgAn3MC5qWXXuK//tf/Sqm0ObiVTCb5kz/5Ex577LHP83A63IClfB4ajqGaJo2BLnStgmNIaoFmsdyi7rUnHOnxA/zgxDy2YRCPOJjSYSQKV/J1XruSpz/lorTGtQR9SYfptSoy4ZKOGlQaHiLw2T+Q5Plzi3xlbz9CtBfO27uibMkMMeiEvHhxlUf3CIIXf0a5WCQst6+Xvq1byXztGwRv/pLg4n9EOBnq0mFn/wCRvQ/xX082QQoe2JrlxDvHiVgmmCY7Ug6ll1+gsprHkIKII9Fa0Vpeovnir3D37Kd69A0AdDSKF0twecdjt63CPbNQ5mB/HPcfmbSDEAJLhUivhbYsfNP+XJJEQggilSKN3/ycsFzY2G4kM0Qe/yqNRLqThPmMaAqLtyZLXFqu4IeaQBgMZ6JkYg6z+RpHxnK8dHmVuGNxZrFCqDQSuHdLlom1KvOlJifmivyr+0c5OlNgcq2GGXhorYk6JoeHkqiVJZqn3qGmJW4kir4WhFWKaGGBRNANOkKgNIEXMl9qYJkG//uDWcx3n6d48QItpaBaYcfYIImDh6i/8ipieYGqNvBCRfLuB9nW2+KcI6g0PH5zeZV9I120AsWlumDryBYK588jpMAxJZW1NbYecjgDiGSGxarPaq2FXjcp3tYdp6ElKdNChwHWwAiB4bSTKICan6Lx8q83uib0tp2IUh4jkSY0jJvOs9HdS6AUBU/elHy5xsWlCncOp/mju4a4vFqj0fDo9woMNVaJPPdLap6HdCNEHvkyrb4hWgH89vwSNS8gRDJbblJttp+zZxbK7OpN8Ea5xtf29hLtJGE+nGQaYdtoz0OVCuwbDbkYd6lUmyBAOO2qzVTEYqwnzt+dX2VqtbaRl+lJuDy1q5ukbJ9n2WriF/LoRJoR0yMWcag1bqi41AozFmXv9kESPfdRi+TYUsyzPLFIyoI/7mtRful5KsCBO3ah/+Kv8EMfL9VDc63CA7v20de/i7eMCCsh6ItnOFyaZcehHby/UKfaChjNRYhX1mgtaiQGNS8kETcIalVQCtuQhM0WGoEEmqffw33wSxhD27CnL1N//TfrEiIAAnt0HPe+R2maNkqFSAAVcP9AhD09UaqewjYEaUdi6oBG3wj2yDgXpqrIdJOwfrPE3q3GQiEEcw3Bz0/PbXhSLZQanF8o8/D2bvZ12ehOEqbDZ4BUAeNJSc+hAe4cyXB5tYYfhPQmHLrjDv+v19t+hQ0/bHdsAo1QUw9ARGP85sICngKEIJpKMbtawdQhr51tMmQF7Ms5xE+8RtnchTs0SnDuJEiBjMZRpokyTBAwkrIZ85PMVVokXIvVaot/viPG+PlXMV47zdrSMs1AkenJMXrvlzh77AzVt1/hwS8/y/OrPqs4DNIey4TjEN1/J5V3XqM4M4vdv5VGTbNj6yh3P/4VTswJfAWFukdXNIaBIhQGSdfmr96dbhdOCdjZl+TIltQXVjY27xv85NQ89Rv8QyZWqhwaznDvUBTZeeb8Tlit+/ihwhQQtQ1Wav5GrPrZsSiDE+9S+M2vqMkQT2gcv4lzxz2o+Sm2791B8dJFlNYYxXkO74X3liSVUOGYBs2gRaA0A6kIEk1XMsrCUgMhBGEYYkdMQgn3j6Sov3eK6W0Jnr+0yp7BLN/d30fTDzFVhDvTgt4rxzHfeZXiN/8lfzUdcHyhRsFTuKZJXzbNaiPkJyfn+bPDQ4wVrpL/2zdJqvW5oGkS2XcXct8hfHHz/PFW6DDAAJq+YLXmUW/UeWZvH78+t0Spcf0e7Y47PDzehQ5vLX/1aSKa9dvKbAGEK4uIkfHPdT0XrVdovPhzwsLaxrb4/jsxlSK4VeGuYUIq+6kfR8uwMO5+iNjuA1CtICyLMJWhYVid9W2HDh06dPhEfG4JmOeff57/9J/+E1u3buV73/se/f39AMzPz/PCCy/wH//jfyQIAp566qnP65D+IJCGSaDAlKDCD68CUypEujaZO+6k/uZLNALFbL7OQCpC3QtoWi7LZhzX9OmO2xgolGpXm3fFbJpByJf39KKU5ofvT3HflhxdUYuJlSqRaIR9g2n29iW4OLuGaUjeuLLC3SMZHhjL8eblJd65ssK+oQyODvFfe47m0iLCshGmgQ5Ckl1dVP77/4dI4CEqRYZ6+ihbMdaWFxiy3+XZgw8SsQzOnb5Iy/OJ9/VSqTbYPpCgNTcNtKuvqq2AuGOiWw381WWcUmHzidCwNjWLaacJbiFb0/RDAg3/iDwJMdFYM1dpnXyXsFJCulGcvYfQYztoyc/2NrdDn8Zvf7kp+QIQlgs0fvtL7K9+9zM/hj9EAmnyq3OrzBevJwRMQmbyNQ4OpXlqT5KUY3CgP84rV4ssVlp0x2z2DaRoeAHvzxQwBZyYKfDY9m5Gc1HemykyX4iSlQHDUcnE2UscHEjRKhbxHIHM5Lj2FPGUYOnouzz1+FeIWlnemS7Q9EO64jbf3D+A+96LrJw/B7RvFde1MZbnKP3Xo6QfeJTy8gKe1072VN98mXRXD3sGBznadPE1SCGJGnBlboXm+F7cK5exCTFRaCXoKs4zNtLLeeKsltrBcV+1OxS2dcX5v714me8dGmRL2qafdhWb1ppIo0r9t7+4ITgN3vIi9vY9tE69j+gb3CTdIhwXMbgVrTV1/8MTmsW6z1gCjgxGke8fp3H+FNprbbyfajao//YXRL/xJ6yYSWrrie2qF24kX66xUG4S+opTC1UeGIoSfoGrl/+htKIJIofuo/72KwDEzrzFt/fcx9l6miueBak423vj7O5N8NpEnskPGHUvV5r8/MwS3z3Q2w5QGiZhuYi8+xGaP/wBzx55ivdWWkwsFNBas3Wgiwfv2cvq5Ql6J96gftdTjCcNLjomTw9HKDz/I1qNJgeP3EPrNz/HEgFeqDBCiEdSVE8f40Aug+oax02l8F9/GS3qROdn6KlBv4DEZMjEQp6+7dt4ZOcTvDVTwtQK2xRkkjHcpWlKzfWEEQLXMggX54kmMpRfeR69abzXeFcvIZNp5B33tRPzhkmhBQ1fEbEE/THZruxU4fXrVbWNkm/HrcZCD4PfXlzaSL5cPwJ4bWKV4fTg52Ym3OEPD6UUMelzebFIqBQD6ShyvUulPx2lWPfQGqQUhEpQagbUA4i7FlOlFo4VwTba3Yv1Zou4Y3J5sczD92/FfePvyF88T9hscODBx6ldPIP2PVStikgk0UJi9g8Ry2b57lAvL19ZI+maGGGUvdNvkasuUFpZbY+HliQsFghe/iU7jzzNzBuvY1w9Tzo+ShB6CBWipUH0rgeov/FbGsvL7UCvZZCJCGrTk1gvP8e/fOhrvHi1yHypjpCCwXSc7oTLuYXC9ftYw7mFMo5pcGQ4uuF/+IVBmrx+Nb8p+XKNYzMFtnVF6fn4CpQdPkX8oH0VzuarPDzezd+83+7sMoTgQbNE/rmf4RqCQGkMAcr3abz9KrEnv450bFzZnnPlaw3sE2/y/Qe+xnszRep+yPbuON0Jh5YX8JfvTPKdA/1MRCXnl8pEIxGG0pq7to6QvfAeweHDvOEbDMRteuM2sVqe6tIaoRCkzQhJS7D4wFc4VbM4NVsgdGIo36euYLLQZDgTYb7UZKcuMv/8z7HiNqmE2Q6+BwGN428TTSQIRnd9ooC8Idt+L2teyMRSiSd2dKGRtIKQmG0QsQxiIvh85ARNC6SE2xTuiXjyc0022FrRfPnXm5IvAI3ZaZzBYfTcDOEHkjCRA3fhxVOfSUdKqBSNaAKiiesbO8mXDh06dOjwCfncoqI/+clP2LVrF//m3/wbTPP6x+7bt4/HHnuMf/tv/y0//elPOwmYTwtpsFCHY3MFSnWfVNTi0GCa/igfKgFiKIU1MEx83yEW33kfpTWlpk8kmWL4iWd4xRM0PJ/Fcsh4LsJgKkLMtemq+ZycKzJXbCC0YrnY4MerU4x2x/nS9m5yUZMeM+TicgVLGvQkHO4fyzGYcjk2uboRfKy3AvpqeUqFMmY0CSrEjCcRnkduyzB6ZRI7nkVFYwgByaCJjBgYlSVsu8F/efsqrmvTPT6Oisbxzp+j24qRr5RBiPY/2kGnjONCrbwpEAug6lUGukymCxVI5drnRQq6486Gl4Yj9a18vT8WhhSYXgstJIH1D+9SkVJinj9BbT34CBB6HvU3f4uTX8G652H8zzBbZBTXCItrt9wXFtcwCmuQ6/3MPv/3GcMwML0maE1gu4Sf4FpYbahNyRcANJgoLi0WOTwwSEz4CEOwrzeKY5pMrlV4fzpPw28/A+KOwSM7ejm/VOXySoVSM2Bnb5yca3L29EXCRotqoEkkEkQdQWhbQLvK3fcVtgoJrl4ku3eAL+/uwZQSLwgZVhUKE+cxhEBpjVCKWCyCWlpA1iroIEDEkuCVQIcIAc2TR+n/zl0wWUMpTdLUjFKllbR4vyR44plnMc8dozk3hZFIkkxE+fK+fXClRL2xSkOYZOMu23sSvDO1RrnpM5mvc36hQCYRxwBcrTAmLyMLeYRpomwHdU12bGgLkSOP468s4a0nZY1UlshDT9CIxkFf0+G+PVG7rdNtVIrUzhzbLIZ+7SfyPHQpj+zJsmcgQ7UV8MZk/qa/c0xJxdNcWKpwaCBGJ350e5RSBNv3EUukaJ08iioXSc6c59G77uOevlFCKbEIWfNCrqxWMNef51IKinWfmhdQqHusNEKGopIgnkTe8yj5VD/p7/1zWq/+msNeyN3bxpG2Tawry5unLjKajaKaDSIr00znXb5xcJCRtatMBD7pdJJUo0RDeWgBSitaxQI923spOg4rp08TfWQHEaHJGIoghEBpaoUyQoXEky5D6QjpsM7DGUWEOLWmRxC0ODyQRb32q3agZL2rq9708DHgxNvI1SVIpgiNzVM8b+ICsQOHKRlRnr+4wuR6F5Cg7VXz2HiWyA3dVkopBlIuS7fofoF2R9EHx8JiS2+q4L2RUGkWKx7J1N8vAyOl3Aimh+sJ1Q4dPojUIQcHUyxWfU4ulFiteMQcg8FUhJlCg225GLrZZGqlwpaBLrbv7MYyBKFS1FsKKx5BBz62ZZCK2PR1RRnpTrC2uABAfWmJ/FqBrn/xP9B68yX8qQlkIoV9xz049z1KJZYkX6mzWqqxrzvK/cmA1eMzBEGIica1DbTSePUapu+R0k1qmSQ69HBjETJhCS0ERiaHTGUIC2uoXC8NJVmrK2pB2wvDWpmDtUUcI8L37xzmQF+MUsPnF6fmodXCCIP2OGc5KODsQom7B+MkGyUoFds3fjpHKxL7vZbUrQSC2cKtn1EAE6s1+odjnSKG3wFdMQtB23/QtgO+d+cQx2aLxC2BvPgaCdsgCFXba9OUCCHQQOvU+8S27QLa882mr1CWzeWlEllH8KXtfWgBf/3+HFeWKyil+e/HZjiyrYvHe9Ls6ktQuDqJG7PpeuYbXC6HbJlcoD+iqBQKLExPb8gHLvbHyQi4mBimZcepUIUgRAuBRqBUW3b0kaEoqalzdCfA1A2MmkDbDso028d88j3s4W20jI8fWrF0yMGhNPNrJZp+yPmFtuLDNT/Br+3r/0AxxWaEEJhaIX0PZTsEiL/3uOjHU9jDo3hTEzfvNEyMz9nrxCzmaa4u3bQ9LKzi9w0SO/I49YtnUdUyMpbAOXAXweBWws68oMMXjFAY+J/AHNGSAuOz1izs0KHD35vPLQFTLBb52te+tin5snEQpskDDzzAX/7lX35eh/OFRkjJ2TWfl27wIijUPaZWazyyvZu9XZs9Fa4RaTXx3/otpZlJzF37aT7wFLFGA5lKMydjvLSqGcxKQqVJ2Ca7+jO8N51nOr9K3deMdcfZkovy2sUl7tuW4+ULy1xZqVJphWRssFfmuXu0iy/tHCZMdREoxSuXVzGkYM9ghlLdY6XqcUC3mGsGRCxJ6Gv6t48yMtyPMzuBX69i9PZhpHPU3n4F5caQCvx0FzlHMrh7FxMln3QqStwy+P6XDhIsXUJLY5MurAKMRAJmryAikU3nQdVrjLkhx5SmKQQ7Uibb/Tz6/Gl0q8HA7t2kGiaNSPwTTUallLilPP7ZY7TmZhCGgT2+C7l9Dw078tFvcBucepX6sZvNAQFaF84Q33UAP5n5e7//R6FvZ359bX/rw/f/oRJp1QkvnMG7cgGtFdbQVpw9B2nEP1qyTQjBSuX2leleoKh6ITGnLfEXtQwWq01KDZ9mEOJaBlHb5N7RHC9eXCEdsWj5ATVP8cPj8/QlXZ7avZ3p2SRTpmTn/Y8QPf82GgVC0mp5lOrt6vf43oOowhpTJY+DW3OMlReJrFSJrE4SxBJUtMliuQpmDKlCdBCgKkWE44BhIAyjnRj1fTzfQxsmEk20VmB3UnJ2coEA+PU89ObGGBjcxei2LbgDaZauTrMyVeZQJkoQeBTLRc6vLaOsGACrVY+UIzm7WOY+u0Lz7VcIC2sEc1NAW8Pf3n0Aa2grwcxVgmoFZ/tuIvc+hIomCONJGtLY+D2yjqA74bBSudkANB21ybmy/ZzxWrdMvgjTonrgQV5Zgstzc1xeq9MVd3hgrIujU2usVNu/qRTQE3dYLtaI2EanyO5jEAhBOLAFs38Yy2uhLZuGNECHGCpEAQ0fdqctRpsr6HNn2v4oI+OUe7fwZlGyXA8pNaCpQs5UuyhPLbNUa3Hn/me4u8uiNTdFKZrhtakC5UKJI/0uutUksTjJnr6DnFmpMVAukIk6RHJpWqsrhEGIUAHSNLFo+2hNFz20Uhh+k7cXBZaMMtiso9BIIbBti0HTx/SrYCVpvvlr7sUgcc+DhMP3knjurwhW1gMT0gAVYvUNUrciuOVZgpVFRDGPOTxKYJogJO7YdqTXwn/+p+SbsHd4B+lsD8fz7eraqbUazyvF13blNjwTlFKMZSOcWW5yq/Dm4ZEMjlCb5Do/SgffD3U7yPYJLmohBG6zhpq8TDB5GUwTd+d+VP/wJwp2dfjDQGvNaMZlvhqQi7v4IcQck/HuOLmoxampVfriBv9si0nv2nHM+SLhWhf/w66t/HAupBoqIlLwpzuSDJTmMaYv0tWIkdk7TjUUzJ08TeX8ORYwGDn8EMkjT2JnMnjD26jo9lxvrlSj4QXU/ZBqqUy52sCOGLiOgw59pBTEIw60GsjVJRKVVWJ33cX924fJvnUCMbqdMJ4irFXxsz1MFz18JBXDpBloqq2AmG2w1YHp2Tpf3t1Dxgw5u1ohnJtE1a53+clYAqN3gIFkBPvse9RPvIX220lS4bhE7nkIf3Tn723gUmt9W8lgaM+HOvxuSNtt+bvzi2VWK3VKLU3KMdjXE8Wab9AKFcH6elRIiXBddK1GWCkh7OtlJ45tUNu2h2otZLw3zQsXV1goN9nTl8SSgnLDJwxDLqw2ODKW49TVFZ7qipJcm6X5zq8ZAkb23slsdivPzzbQUmwUDvihxvMVU0UPu9ckEnVphhp7XSI7LhVeqcTYcBfJqcvUz7yPsC3CSBRlGJhdvahUlrBaQfpeWwbrY6K1Zn9/konFBBeXKjdshzuGMwwmDLiNh5GlFeb8NN6p9/CrFYxEEnf/Xfj9IwR/j6K7QGui9zyEqpQI8qvXd5gmsYeepPkZdZbcDu3dfu3oL85h7dqP8cx32vM926EpZKcoo8MXEl9pfnTq5mTk7fjW/l6Mf0QqLR06dNjM57ZyHR0dZWFh4bb7FxYW2Lp16+d1OF9oqqHB6xOLNzVoaOCNK2tsyQwSE5sXJBYa743f4M9OAqDWlrnkxLk8u4YVb6H6h1BIJJq+pMvdW3P88ERb410CCJgvNfirozPctzXLaqHC9w6PcGm1TqUVELMlD44fYJwiLSfKudk8r02sUm4GKCl5E7hzJE3EMpF2kohlIKUgN7aVbkvT+slfYqRThDNX28FTKYk+9lWKz/0Up2+IYGkOL1SkdJPHt/eQzSSxDPDza9R8RXTHbuoXzgBtWTZ3aBhtuzij2/GrFT5I8sJRvvGl73GpEtB//h1KZ05gCEFX3ME4+Rb1S8eJPv0t6on0x/5d3OIatV/+AO1dD9423n8Lc2oC98lnaVrOx36vTVSKm95TRmPISBTVbKJqFdTaMnyGCRgRiX34/mj8M/vs31ciXoPmr39MeIP8Xev8KbzJy8Se+Q71eOoj38OxPryK3DLa3RgAPVGDrqhDs9Ek2h1ntR7ghyHT+ToNP6RU9zANyUDKRWlYrraYK7ewk0mitqR7fBiHKs2LZ8mXmywuLEMsiXH4CP/fy02aCv7Zvgytl35JcWWJ7F2HcIIW9vwaWTdCumcQr9lCuC4hGhGJQ6OGKQVBGIIGe+sYV4oe2k0SkZpMfoYHrSrpXQOcnMlTr7doakkmm6K/uoCeXCFiRvBmp5iYVJQ9jVpffKV6+1DJXjJRi3qzRSxo0HzlZ6hyAXtwyw0nycaKx6n94m/RQQBSosKA2uVLyPuf4LIXpydh0eUKpAowdMDTu3r4xdkl8rXrCbB0xOaZ3T3YrMs3OS7CsjaCXNeo7z7Mjy8VqSdMwrhFT8JhMl/n8mqN7x0aolj3QMBA0mWxWAVgMB3BNT57A9YvAlrrdref7V7bsGl/lxniX3yT0oVz1zfOzWEnktzzyDcoNnyCUPHjk/MoDUnHpCsT5cWrBU6tRjiybQfnz1/BqlT58oP7cWSL/JN/wuJqCceyONibQ8zlWay2SFhVhoazCKFpej62EDiuS8HTaN/HTCSoKMnZ1SZf2n+Yxd/8lN64RVfcZsgMUFOXaTabJO+4l+T7RzFNg9hzk3R94/sshC3I5RBSEvoBoWnj3PMwyzLKYKa7/dV9D1VYQfQM4G7fjff+m4Qri6iRcZbWmnDxEr3DW7nr0Jc4mm8HeGYLDfIt6HEkTqMKxTxRQ/K17cP88oLPWq09zjim5K6RLNszNuoDwaGkY+CYktZtgp69CQetP5kpdqRWpv7rH6Oq5Y1t/vwM9pZtOA8+TsuwPtH7dfjiIKXEMAwMr4UsrKCbTUQsznS8n99eXGax0tqoHD02U+Db+/p4ZmuUA2GewkvP02i2qCOJri7jlo/zZw8+yX+vpvlyl0/6/edYmpyhN+lSy7e7PZ2t29jz4L2snjyBqWHxjddZVJpt3/o2nm4/g7TWRGyDXMym6YVcLDbQLcVa3WN3Ios3P0NPRKIaVVSoIZ5EhwFShfS98VPi9xyh8vYrqEYDmc6S9yFEEDoRbCSBDglCTc1X+JbDH9/VzY6MieF7JCuraM/HSCRBSHTgo+pVrLVF7kgkaB57HeuG+b9uNam/9gLxZIp69vezUzlqCTJR+7ZyiVtzHQnP3xVCBTy0NUU2anFyroRGUfEUEdemke1BxBJQKWFKiSUF0nTRftAuirnWeWmY9H3pEX4lMty5JcFfH5vbkJI+PV8mZhvcvSXDaC7GS+cXOTWzxv9uzMT89d+wdvEsCoFjSepH36XrwEGeevKP+flqmrBcRAC9SQfLd5BmjCtLZe4cyvCrc0sIKUiYgla5TNy1uCOuoNXEVAHUW2itELEEwfICpu1A7wDK/ORjUTJi8dhYmgMDSWaLDaQQDKcjZJ32+bsVhhDIsyeovffGxjZVr+Ev/R2Ru4+g99xxy2IIIQSGYaCUumXXW92N4Tz9bZy1JcLVJYx0FjOZIqzVcRamIJWlFUt+Pv6ibox2m96tkyoyGqf5IfO9T4ohJVazfc0FToSgk8zp0KFDhw6fAZ9bAubP//zP+Xf/7t/R29vLE088gb1e2eJ5Hs899xxvvvkm//pf/+vP63C+0OQbbb35W+GFinwjIBbdvN0qFajOTm38X60scfDQPibnC/Slo0SzUZrCYK3a4F/cu4UfnlpkrdbW0nYtg8F0hIglObtQptwMMBwHX8NIJkLMFBitJqcvXGV+eIi7kVw9dhzpZFDVJsJ2wI1wdLrIl7Z3807N5uBwH9FmhfhIP62f/w120AIVIqIxVOCjPY/miXdxd+7Dm75KZHwPjTBk5vhp5mMJ0ltGePLgFn5waoodY7u4Z8cuosdfpzlxkZYwadguPTt24g5uofTSr286T1ophmKSITzWFi+Ty8WwpcCSGq0VqlHHO/o65mNf+1iTNFMKvBPvbEqUXCNYW8GenUSMfTLt4GsI2TZ9lLE47vBW1OoyqrCKmcpiDG8F1/3E7/lJCNI5rN4B/KX5m/ZZvQMEn4Eh4u8zUkrU5OVNyZdr6GYD//T7GA88/qFyZFpr+hM2liFu8loA6E44pG2BECYtBZaEbx7o5+9O+lxYrpOvNrl3S5apQgNTKwqNJsi23rRrCrZmolSaPv/07mEyZoBUAfruhzF3HKR1+hypvSG1eJZXKi6XF/IkIjZibopgbhJpRzAqJSLju2m+/QqqUUcbFq2Wj5NOY3T1IiJRRLOBa0g8y0Vku6ntvY/JVoKoY/OVHTniv34BVa1wKJ5g/957UJE45uIUzsVXcXbsBTOG+94L7BnYwftXl0Bf165uLS3SncnRn3BI203Gly/gHXsLrULsnn7MSJSgUcfdfYDai79ESImWBkY6y5InWVorY/76l4RPfZ+/vazY1Zfk4a0pTO2TlD7f2d/DWkO3k8uOQXfEwCbYuH+9WBJnfA/Ncyeu/+5uhKthlEqjgtHTTlq6UrOtK0Y90JyYKxFzDGYKDaajdQ4OpggUHB5Of6gERYePTyo/z+zVSzdtr5fKRM4eZfiJb/CX789tVFOXWwFRx2RsIEe5GWC6Dg/sGsRxRrkwvcS5aJznz04RdW16HEjUp/jeY3ewd0s39UqVMJGmpdvSl2EQYKcyFIJ25W1q9z5eqhpkHMX7ZclDDzxKfPo0SpdwKwX8aIz4o19m9d030YVVLMtESkXlxZ/T9/1/Tv34O4TlElZPP+HYLla0zbnJNYZHtqCcdmeOqlVxHBexNEcwcR6zb5B6eD2kUZuZpH90BtcaorkuS1j3Auy5i9TffmVjvOrJ5vjjQw+ytmMrvtYkbIO4Ed6UfAGIGyF3b83y2uXVm/bt6ImTc7iWF/5YGFLgnzq6KflyDW9qgtj4LhjY+vHfsMMXAiklbqWImrmKXppFtzx0JkdjbhriSV7uvo/VSgNDSIxrpaACfvLuBP/Xh/tZ/eVvuTi71pbIFALHthjMJWidfpM/evy7pC+8S+nKRbZ154hITb0RkunuRi5MEt9/gIVInPmlAn4YksxkkNFeeqWFEXoopRjNRKh6ip+8PcFgOsKj4ztYO3OaOcth58gwen4SicDMZnFSKXof/zKNd15FSYk+8jjO1/8IsbaCdmO0jp1FigqE4PshEVMiTEiObOGKivBETiDDFkZxja1JC9c2aSwttOfMkShmtouRtIN74X1sqW+OU2qNd/YE5sNf3uhG+H3C0gEPjOX4xemFm0K1PQmH/rgF+tayiB0+eyztc2evw56efnwFhjRYrXl44/uxJs6TjthQLSHWvclk7wCxr34XT5rEHn0Gcj0E6RyDqz6/PrfMxeV20ZwUgpRrMdYV5dR8idlCDe232JN1iF45Qen8GUyzLVsphcA0BOXTJ+ndsY/Mlr0UFx129SToXroM85Ps/9L9vHtsmV6zxWM7unl7uoARtEDAVw8MkjrzIk7fQNsHUWt0s4F0XLRpofIrxB77Ck3bua2Hyodh6IAeW9PX116vKRV86Dhp18rUjr9zy33NY28THRlr+5WsI4TArVdRs1cJlxYwkynM0e20ktmbOt9apgW9Q1j9w3DxDOVXX0D77eSmMC3cQ/cS7jrIZz0r9VMZrMFh/HUP1xsxc92Emdyn8jlCCCLVMv6pozSmr4DWWINbiB48TCOZ7XTVdOjQoUOHT5XPLQHzH/7Df0BKyV/8xV/wX/7LfyGTaVfkFwoFwjAkm83yP/6P/+Om1wgh+Pf//t9/Xof4heGj5gof3G8YBiIIrovOAmhFT2WJhx65m99cWGb5Sp54LMojO3pYqLRYqzQYzcXQuh3MaXo+uWiEO4bS+ErzxI4e/uKdaQw0cUMT+j5hoodWocYxNEnboGEb5DXoVgshDZTlcHqhQm/cYv9DXyZy9k3E8hymDgn9ANVqYW3ZRuvKxbZnxvRVonvuQDUbyDvuY3luDmlahIU1nIike6bK/aM5Xn3/NOdzPQyNPcr4jvuJ6YCtA1l0IoHne7i79tG8dHZDMshIpok8/CRePIk4dRTXuHbCNi9cvflpYvUqwUd0gACYjTqN+ZsnkdfwL5/DGN/T7gb4hKhkGiPbjdvVTe3XP0G3mtd32g7pf/5/+MSSL58ET0iijzwNrz6PvzAH664CVt8gzkNPUhcdx+UbMQB/4sJt9/szV3GadUL7wxNnSVPx2M4eXji3vGkBFbENntrZy2I95P2ZAvmaR8wxeWC7yVd29zCSbXCo2mAwalCpt7g4V2/f96EiX64zmI1TqLdwLUHE1BtyRNoweKlkcWFJEzZbKDUPkShbuzIMplwKp96iJxkjFnOxS8uY27ZjrSzRnDiPKhWw0900tKD7e39O6Y2XMIfHMGyXVCyOcfcRlrbs52lhkIu0g7u6qxevWsHKdmO+9zKtsyfQQJN2h5679xDh1UvcNR6h0tvN6ZUa9WZ7xRpxLJ7ZEsc0POTrv0KOdG90o9TffYPYvQ/ROnkUYRroWhXiCYx0hmaqm6VC+/4JGg0yzRKQ4PximaG0y850W47M0gF9LvS5AlCg1abAT6gU1h334gQ+rYnzoBQylWGiEmIObSG4QaJCAEulBhp4clcvp+dLlOotVqot/tUDo+SssCNB9ilgmib+xdMMplxmik0afvu6FrQ159P5OUSzzGK5uel1qzWPtGuSi0h8P2CgJ8Pf/Oi37Du0h789MU+oNF61Sd0zGUt38bPpBt/+8rPUfv4Trh4/xbYnv07jleewHBsvmcVYKjJ0YB/LY/uJzVWR+WUmZxusRBz+5ZefxayUia1epT5xkfLRt3B8DxGN0vI8LA2cPUHtnkeZO3mK2L5DzDh9HH1rkkYihxlPMCddRr/1ZzR//SOEaH+75sn3MFIZdKigWoaWQjguGvAvnGbw8BYmSu2xJxZ61F/7zSbJTpoNwt/8lMFHn6E5sg2t/dvGmJRS7Ot2iFl9vDudp9TwiVgGBwZT7O2NItQnC4RajTqNyVto0q/jXziDOTJOEHSSlH8oCCFwl2ap/ebnyFaDcPpK28vPtIg/+TWW0kNMTRfQjRYiGt/0bFZaYVXLTK6UNjomtdY0Wx5XFvIMd6c5nPz/s/dfUXJl6Xk2+Ozjw7uMzEifiYT3vgoob7u62lR7tkSJIjXSvzQyHOluZrhmLd1Ia+libv4ZSlpaGon/L0pks0m2N9WmurxDwfsEkN5nZPg4cfyZi8hKAA2gGqiqRnex87kBMsyJE+fsHdt83/e+AY3lMbrSGmJ+lMB2iOkGajYL8Ti1C+dw8htw54rEOrvwjzzFfztf5TFH49GBGGHgk1FDOqIaUuBRDySWtxwm73lEV2bxVJ0g20Wks4voI8/QWl5AHruElM0TqCrW1BhB9wB+dwRXUlGf/hzaSz8grFZRJRnPdYkVuvH2HqU4OY0zM4th6KhbdhB/5Ts8O3KIF0uClusT1msEjTojmx8gM9O44zwwqJSQAx9+jX6Bvy7CMGQwIfP53T28M1FiuWGjKRJbuhLs60mgrQdffuMEQYBGgCaA0KU/JlCTA6if/hzNN3+BaNbB91HjCeS9h2kNbsK9Ye1QbMGxiRLztRYJXSUkRBYSrh8wVmzSndC5NFvm6EieHXEX3jyNkCVabrAWgEkaKnXLxT13nF3P70XL9rCxPEF49QKB79EtOQyldV69tkJ3QuNTW/JkcEnIAXvUBuaFs8gKxJ/6DOarP2nLL/s+QtfRt+9BDG38yJUhd/3+agnukJgTei7Uymtm8UIIIuUlmj/57s3rw7PHiT38FM7wlttWyyiLszTfepkbK1BCz6V17HVi6Sxeof9uv9aHwkUQefhpeOMl3JnJtfNQu7rRH3kWU/p4trAMs475478hMK/LNjrjo7hzU8Se/8pdKRKss84666yzzt1y3wIw8XicRCJBd3f3TY93dnber1P4nSEbke+YGa9IgmxEBjw8SWGxGXC12EDyovQ+8ftkghaRhXGiK3NcinTx8punCJM5EkYCIQm+c2aOw4MZCimD83M3Z6SWmg7dcZW+pEa5adNlSKhuqy3JEDMQ9Rq21eJ03eSRnk4q00W6OnIsNBwiukpM10gZCjt70nhJjfqRT5M5/nPo7kf1XYJWk8a1UbRsDkXVEGGIOrwJR9WZOXmSYPt+ArsIhOztSeB95885+KU/pHtfL9fqHq4qUDsLdCY1/NCFIMCTFZTDjxHbvheaNWLJNKgGLUVFCkOE9wELtyBAhAGuUFlu+dStdkl8Piqj35ANf50PWNiKdpb0h8HRI8QffJTa//H/vXlyDSjpLPW3XyHS2UPLiN7hCB8dU4+iPv154tUyoWUijAhuKov5CVzM/zIyoDcqBMUlAKSOTpx4+iNlf4kPutd32RbCIGAkKZPb38t4uUXVdCmkDIYzESYrFj+/tLi2bGrYHi9eXGRbPkLcUAgsh7fm6iSiMZ7f089i1eTdsSKu6yJWN17392ew3YDpekA6olJIqNQdH19SCN5frLVMoi2T7mQP0cAlqcsECCwfpMsXUPIFEtv3EPg+QVcvK8UKF89eIrtpN4lCgUURo2egB5GIkQtD2il/Aa4P0X0P4q8sIUuC5oXTSMk0YfcAUjTWrghRNMK+DeiLUzzbGbDvyaMsWkCzRry2jDF2Bql/GK9RQosN8X7PCFtNmm+9grFzH2rPAEr/EFI6ix+JM1u+uf8QXA+Inp6tsSnbgbjLahRLUVGOPEls535orupzz4NXvMFNQ7TNaV0/IKrJRBTBpo4oIFBEyKmpFYa25xD3KNm0zh1wXVQRMJQ1sLwQ1w9RZEHT9inXTXJhiCyJmzYjgiAkpG00r8gS7803SHR1sWB6118nSTihRNNIINse317W+L1/+H/BnbiK6/lk/+V+VLOBY1uUmoLRmsfE1XlU3ydsNdBkmURUZ7HW4tx0nU8XJ6mePkW0pxczlHDctjxRRAmQK0XIdRJ+7h/ybi3g+OlR7KaJGmmS2DDCt1+9yrN7Btjx/FeQG1VELNn2PVpeIGjU0BUF1ZfwfJVQlgk8F0WsehzFdLLLE4Th7TeB7DPvofYN4fyKoLoU+GxMCYZ2dWIHAkUCQ/gE9xh8aRN+YEZx6Ll/B0aZde4WIQRaGGJevYJkRKBabgdfADyX5is/gX/wb1DdRTQh4QV+2wMQIIRMMk7LdpB9l3hEx/Z8giDA9wNCBHM1i+0EqCsLBLUSktruJyCwq1XC7gG8VAfR/Q8S27iPq57OhRUZI6pyYaHK7u44KRkEAfm4xtHtA0zVXSYDia2f+wr1mRkCv4Y3P02lZTP53Z+QkGFzPoqmBBCGa1XNALoImDZySI9/iYJbRVTL+JLCpCW4cPoqD27qRp5exLZMItkOnKsX6W42+PL2B1mJZHD8kJzs0tuYQsSjWJXby3RJiRTICl4gUXXav3kpTUIXnxDprsCnLyro2dlByxPIAiLSh/3NWefXTRiGOJ5HMLQZo9CPX1oh8H3Urm4cTcO9IaAuhGCyZGK6bblaPwwRgBsEa8lHcUMlqqXwQkFXXKNhWliO164+DQE3wAtCEhEVLfTZ2hHlnbNjTFkKA3ufpc+roi9Pk1ZyfHVvD9PlFuV6i915Gence8yUlhlKJPDHL2KZdaKPPguKgojEEOkMHuCov161gZv5VaPe9edV38N6/aVb1odS4GO//CNiqobr+YiOTuxYgiBs7xW4505yJ/kv5+xx1EI/H3fvkiQJN5QIAU0EtLQI6pOfaa8tW02EHsFLZT62xD5ZlvGvXLgp+PI+oW3hnj+JfOTJD1QkWOeTxb0Y2iuSdE9VoeH6bHSddda5C+5bAObf/tt/e78+6neehBJyaDDHm2O3SoAcHsqRUELsUOXnoyXGS01avmC+2qJVrrC1K8HubDfDu7by2skxQtvGaJTRUykcAS3H441ry3xlX/8tAZiG7eHHNTZ1JnjlwgzXZopEVJmcIWMsL9CZz5Lq7qaBSkdMcK7kESLo7kix1LA52J2kM64ztmJyerbCju4k+/s2MvnK6wzFZaRqFRVwlhYAMDq6aI1exIlnsM0mS7aE8D0ObB+kf/xkWwt8aYbszCT5WBw96eKmD+L7N08ZvTDEiyUR8RSZ7m7s+fm2qWcQoPVvwL566bbXWcl1UtMTfPPMYtu7YZVUROX57V1kVX8tCONGYmj9w+1s+Nugbt6B/SE1qoMgwA9BTmURYVvGCk1DTmfxjWh70l0uQvfAhzr+3eIicFNZ+DskOaaGAdK54zTOvHd9E1CSiOw+iNh54KYMvbvFC0P0Tdtxlxdu/5mDI3h65O5kDMKAtBJwoEtHCIMgCGiFAW+MFW+7bDo+XebAQAd/c2wMgoBsR4bJusdwLsojm7t4b3IF37bpTScY6YjzF+9Nr713MBujNxtjNpO7RQ7IdD2yO3Yw8e47OKtLsoSuUjCnME+dQNl5kJXlJnqzSsu0mS2XYXAPp0yNryRSSLfJUG0l0kQ/+zXcH/w11jNf4QpJrlQcIvEY27dtYKHhMBOREP0F+jMx7Pkl5uaLbOlNEzM0kp09qAtjkNAQvo/SVcBbbF/z0LZoHX8LpbuPIAgI9Qh+CP4NQWshy1jRFKz6gFqujxcIbqfwLYTAFwq2H6JKAk20N/W8MMSLp2A1g257t+DaDQEYSUjUrPZvx9auJCv1FgohrG74L9UsWj5E1+f0Hxnf99GHN+HMTiKFAVEZkNuxTtMGo6ubKUdmUz7OpRvMcA1VbptZhrChI853T5XJFAqYToBQVXxFw0HCCWCh6SLJBkHoUZV1CkELaW4c81IVq9nA37Cd8600FyaKUOijZNtk871ESgs8PRhHNCpcujrDF594kMZSkbFqC9t1MFSZdMRgumkycOBRXrxURMnl+d6VZXq6B0nZjXbdYRjiSQovnpuj61A//rGf4uR76UqkCVb93aRahf5cNzMtHxsZrX+YJXt13NrWifzTl+4YXPabdTTXua65/gGEYYiM1267IR9okv2B982IonT14M5O3vZ5dcOWDz12rvPJwhEqExWbixPL2OUow9372d63hUjxL9vzHiA0m8Q9i4TfYiCZZdoV3Cj8GotFCNJJPCFjuV7b21CRieoSkiTQDB03kcbYtgfzjZ8TCBlHSLRcH8cPEE5Ao3MD3y/qLJsSrUCianvEPAvLVShaAem4oOTKfO/cAmfH5rFQkGgnc5xf8NiajLFvfBZRWUEOIZQlig2H3qRKGIYoAxtwVtt04PvsKCT4m9MNTlgGTJn4q9WcqUSEzZpN0KwjpzLYo+dxOvuZXKzjzvwIaI9jFVmQ7kqTe+Z5rNd+fpsrK9B37GO0EfLq1cU1L5WkofLQSAcd+U/G5mMYhgjfWxsv1/dMf3sRQtAMFc7PtXh9rIzrw9auNPkiRESL3Z0RpNXEEyEEluuz0nTY259h8swcwWqyhKHKuF6A5/k8vrGDywsVztcUdgxvwpyaAASytFrl5gZEFBl1cBN/8+44s5OzaBJcBDLJKC/sipK2A356dpJkLo3wPRoRARfOEpXBOLSH8No5/OISzZd/jJzvQuQ6CZJpok99BkuI+2dSn87d7DMoJLxVRQpVVyF9fR2m1MpY5Zv3A+QwIFycx61VcAfOYS7MAhB94DHckW1Inodbq9zx4/16DcVzQNE+tq9khioX5puMLjXa8618jJ2FOAnh4SYzvxYvU9n38KbG7vi8OzuJ7lj4H+P3XOc3y70Y2r+ws8B3zt3da99//TrrrLPOr+K+BWB+XQRBwF/91V/x2muvUalUyGazPPbYY3z5y19eyzL/0z/9U1555ZWb3rdnzx7+5E/+5Ddxyr92wsBnd5dBJtrNiekKNcslaajs70/Tn2i7OV8rOYyvNHGQGC+ZuH6AHE3QDASJZIKKL1GMZFHUOE4sgSzam1CSgJYb4PghfekIM5XW2udKkkRvOsbC3CJxfGzbxbZdWrbEZw7uYmquyHvjVYSqsZKPs2momzNzVc7PlnhiazeXFupcCGsUmzYpQ6VkutjZJId37aR89TK5bCdhbQVhNpDCgNjRx/E6ezGzA+iHnmWDCNmdkYm89wuYWpUskWUIQ/x6Da9UvGPlgSJJyL7XNuJ+/zqGIWGhFyXXibeydPMbJAnt4EP89Wj1puALQLXl8uOLS3xldyfq6laWHwQYew7hzM/gNk2EAEW0zVrVrl7oGfhIEmGh7+JpOqKrZ03f/0ZvmvCDKnnWuS1CCJTZqVt1loOA1ql3iWXzeH3D93zfwjCEgQ0oo+fxijdP7KRoDHXHPsx73Dm4UbagYvm0nNUNSQFS2JaEAyi3fBbqFoYmYVkBlXKFwWyaSstlWyHJA8MdbEmp9HdneenSPAAdcZ1c3ECSBFFNxkglsf1+QrNBGEKgaET6h5j2OlCi58Fs4oeC6YqFSKQpdGsEGzbiHD8FikRnZw714Wc4qWR5fjjWrha7w3VyVIPajgf49vllKvUqsiyxfdMI/+n1MQIh0d81wNjYPJ49z66BHP2ZFG9fXqB3oJvnu/sQkkCyTbyFGYwjT2K99Qu8xfnVayMIPI/ok8/TvHQOSbSNk+1W+9qlduzhuKPBakCpM6GjiVv18wNJYaLqcWxqiabtMZgx2JaP0ZOKgH+z51NPTGZrIcmlhRoI8MJ2xlQ6qrMxH+P87M2+QIosPrhaap27JgxD6B1sB6YrpZseT8V1vANHOLXQYF9flvmaRbW1et/j7WrLfQMZkoZCIGTqTkhvJo4fTVCz3LU2EQLzNYtcVEWRJeStu5HtFpLno6SzFJeW2ZtR6Hn8ID+5vIiQJCKxGJ8+dJTCG9+GLXv49DMPMhXXKSe7Kc9dJAyhaXuUmw5DvTmWthzGL1rULB/L85loQSGRo7RYRMEnHsuTUqGRLlC2BGK5TO6Rh/BXlpEbNWg1UVYWGOrsxc7mUfYd4NFImnxEJiIHiHgS7hAclmMJAvX+bkS4IUT3PYC7OAu/JDMmJzOI/qF1jfbfAVyh8JPRFaZKJrLZwCvVWC7VuKDJfOHxLxJ/8S/WNj9jy9McHCzwyqU5Rga30AzbUkVdCZ0Hhzuo4hPbtQ/n1AkCz8ULBH4gEzc0cvsOYkXipI88jnP1As35eUyn3e5UTUHO5Rnt3sLSimDFhrptE9UUPD+g2HCYqVh0x5P8YnQe2/Xo7cwwObtMbyHH6FKd6bJJTEvxyENPsvKDv8VxbPxARiDoTOjERjbhZW9WBkjKHl/e0825mTJXljQwNDYOFtiWi6BOXUTSDYSqYQ1vYzk1iF4qIkbP49ZrJOJREoNDWJEYdvcG9H1N7DPH1iR3haISOfgQy+lefnByDu+GSGnNcnnxwjy5ZIx1EZ51Pk7qgcLfnFni5GwVd9WzdKpkMtQRZ39vknPLFns7tTWz+L50hJB2ZdPWQoJry00s16fqumRjGps7E+wrRBhJa3z3UpFduw+jnn6PcDVZyAtCJCEIk2maOx5g8u0pLMsjYSjIAso1kzenajw4nGMsFmLqKpavctpT+MwLX6H1478hLC0TfegpWm+/jIjGELEExFMY+4/gFfrv6zhkR+NEDjyE+farmH7IUt3Ccn0kSWLgmUfwohmUoL02DX9p3BRCQLmEvxpgCZy2DHjo2Jhv/oJ4tgMnm0dOptdeI3QDr3cDTjSJapvEXJPgYwxKtFD59tlFKq3r6+kTUw6ji3W+tKebuPjgNawkSTQDmYYTIEuClCZQwtspUdxMKARId06kE5L8odUp1llnnXXWWed23PcATLFYZHFxkWazeduB8YEHHrin433729/mpz/9Kf/iX/wL+vr6GBsb4z/+x/9INBrl+eefX3vd3r17+ef//J+v/a0on/jY0wciBR5DccHgjhxOAJoEIvAJAw9fUjgzVwIhsVx3KZsOPQmdr3R6qGPniL5aprs7z6c6RngvSHGx5FJICDoTBoVkwGTJpNZyODqcpW77XCs2UGWJh0fyrFQbnHvrAjt3bSaiKbQcjwe39PL9i4tYboDvhwwkNOYbLucWmzy8IcdEsUkiquOVLJbrFrLU1q4e6YihpuP4T36BTOEYrctn0VNZ0rkMiQMPUu0c4NvjTc5dqNMVtTiak0gYEeJ7DxF092Jduwh6FCWTAyFQ+odvyZRVAHV5Dvf8KZxahXpngcjGbTgd3XiApWhEnvocyoWTONcuEbouSkcn+t7DzGX6WRifve31L5sOK1ZAQX//hshcltKEh59HXL2APz1OOhYhv2cv0uAw1kedyMaTIMuEvn+bzWyBdA+ZQ6oApVGDwCeIxnFV/SPrGn8SUcIQ5/zJOz7vnD+J0jv0oUrwLVXHeOqzqJPXcEfPQRiiDI4gb9xOKxr/WLLoZN8lrFUI6lVAYHf2UDbb2YADHUkml2vYtkdpuUw0omOZUf6wO0CpLfKXYwEhIbv7slxaanDs0hJeELK9K8EX9/Ry+YLFtek6SraDw90xLpTrXCybPPH454hdOU1l7BqyLlHrHiJ59CEihgZGJxVkrhkZTs0L+lI2rc4YaVWC8A4Z7IrCWS9Gpd7Ofu8udPDeTA3T9kBRWLICpESKUDQ5NVdjZP8AdpjgBDqxRZ9SOUZaG+bwcIL0xXdR9xzG0DTwPZSuXujuBwHxdA7rwmk6aGCpUYxd+yj2bCIjGcRi7UzL3T1JBO5N/UuSJM4sW7x+tchISuWIViE4fhqr1aQ6OEj3vn20kum1sU4OPR4bTrG5K8E7U1XmKy0+s6PAQs3i22dmSRg6CV3G8wMMVWJnV5KYHNyohLbOB+BJKiutgKrlElUVOqIyEXF9EW5pBpFnXsA/dwJ7fBQ8D6Wzi/i+B3FSfeSuFLk8X+ZTWztpOG1ZyY6YwpbOJOWWzatXlpAkwZUVk+F8kogqrwVqQiCuyhRXKhzpzLFw+RoKdQr9G9CqFbziErFIgujIBmpGgsd3GciSwKnVeP3N0zx74EleuzBLV9Tnr08W2b7xIXYNjBBcPoNvu8h9AywM72DajpJMajStAF+PUms6RFUF2YhgSSpVJ6AqabhGjK6nP8WEo/E/J+s8cvQFjNHT6MszSNUVIv0jlHc+zExL42BORgtdfB+i2/fgTFy57W+Qvms/liTfvyzfVVrZTuLPfQnnzDHchVmEJKMNb0bZuR9Ti/zaPleSFQJACoPfyTHwtwUhBNM1j6lSu3pQaFp7UywMadou71UVnuwdbFd5rUp4bquMIe3byfGWxpaoxC7dwnDKlOerlFPdXO3dw6ZoGv3yaax6g2hnF9lDD6AOb0TFp5nJY/zDf4H12kvoE1dBkmFoC8GBh3hl1MVyXfwwJGmoSKujQtJQCFotxmYcFkevIiSJVCbHxkKaVELHDBwMTQVJ4r/PSLzwzJfITFzAWZhFikWQHjqKPDyMtVpZK0sSmtkAx8bQNJ7enOMBYwMLrsyx0XnePjdBKmbw5MHnsQOJkyWXidF54pEUex/8NPtjHnK9gjN6HhZnmHlFR926m84v/iOU0mL7WmVyuIk0747Vbgq+vE8QwntTZZ4aisLfgUQeIQR2qFCyfNwgJKnLpNWQcH2Q/VBIktROVruHMUGSJE5P15mrWbh+W8oZx4YgYHK2xdaUwuXFJtsz/WiqhKyoRAOJiCrx5vgKGzribNgSY65q4Ychn96SZzcl5n70PTK64Onuzcwnexj8V/9Pgrd/QeXYW8iOQ2bPPuRHPsX/WNCw1QiOW6S1uveuqzLX5lY4mlf44uYMb9g6y6aLcG3ORDM897/9S5ILY4TNJqn9DxBaFkTjBPkCdix5i5H9r5sgDPE370RKZFl58y2CsEI0lUbatpcXgxT+uSU+vyPf9j+KJxCatibVKPn+TUkocjpLuLSaDBYGuKPnCY88ibZjL87MJGHfMNdyIxybLFGfqhGN6Ow/eITNkor6MUj8SZLEpUXzpuDL+zRsj7PzdR7qi95xDA4lhXNFm3cnFzFXk8/yCZ3HN3bQZYQfOHZ7CPTNO/Deevm2z6sjW3BVfb2cbp111llnnY+N+xaFKBaL/Kf/9J84d+7cB77uG9/4xj0dd3R0lIMHD7J//36g7Snz+uuvc/Xq1ZtepygK6XT6no79SScMQ/A9NAD/upJrEILrBZheSLFpk46o/P1kldIPfkTg+5iaTNKuU3vvLM999ev0dnRxZq7KTMVid0+KDfk4qYjC2ekSuiIxkNIpJA2yhsRbF0qEvse1y9f43M5NnJqv0wol5uoeqYhCNqayUm9RbNhs7slQaXn8yyc289OrK5SaNiAIQ+iKa2zoiPHDMzN8w/I4PLiNHUc3sSFj0PBDSpEU/+u9Oeotl6e6Y2y69g7lV85z3A/Y0ZMitThB5g/+GV6tilSvImQZRZYIXRt7NdghCYEyeg7znVeRPAfMJtb0GP6pd4k++Tzh1r0EYYgdicKBhzB27GtX0+gGJoJq84MXbJYbgL46uSx7a54c6dxOunp24iMhJJUn1SjyR/R4cONpjM07sS6evuU5bXgTbupXB2CEEESqJex3X6E5PweEyIkUxoEjOP0j/K4tT4Xv3VYX+H0Cs4nsuyDfTpTqV2NpBtKWXcibtiPCEF9R27IjH3EhlzZkkkpIbWKC0L2+oPHrNXBk0lqBiCzYoPs48QghoAYe2tI0kt+iNbKbyrUWO3oy/OTyEivN9jE2dyXojOt85+Q0uWiM/fu2MeyWCabO8+JUSLlp860xmcGt2xnYeIiy6fB6S0GdlchEBT8dUwmBmN4kG1EYLzawXI/P7uikQ7l96zI9GDNFu5It8EkXCly7UMQ3oiDLFJsumqJiKgaKqjNmydRkgyuLVZIxg5F0nLHFRWZOz/OZ7QfIn3oJNxoj0jeIdfY43vlTGN19hGadyPAmYtkOkqk871gRLi01eXdyDiEE3UmD6WKdJzbnGUxIhKuLsUagcGxigYGEwvb5c1ROXK+WMpeW0Kevknn2eazO3utBmMDFkGSE79Gb1HBch5bjUbcDlhoN+tNRTMelI67RlYzgBgL5tldnnRtphio/OrfMUv26znlMV3h+exederB2/VtGFPmBx4jsPogkwNLizLnt6s4v7OqkbvntjVVNxpBDrFDmm6fnKDUcBLCrP8ds1eLN8RKPbcpzYqrMtWKTzoSGsJo8PpzGLxcZNSW2GGVK3/9fyIGHHYCz5yjHri1xorrMVMPDtmzS2RQvHN7Hmwslrk4t0rVtK2rg8tLlZd6SJbYMPkQ0onOx6jN9ocWXdiWxbItcMobltjdRmq5PKh5jpemxsSPO3r4MZxYazNtdxHyLfHeEb18coy+3lf7+XWzuzTIfSfPDiQYhFUzX55mRJKHvY+c6iT70JK13X7vurSHLRPYexuu/94q/j4MwDDEzeZTHP0PEMkGScI3omkzTx00gycw3Q07PljEdn+6Uwfau+E2youvcP2RZ5sLC9Q1DX9GQUxn8SolQSIxXHVojO9HnptAff57l3ABOFrZtGGSvZ2O9+hNqU5NMlUxsL0QkUxz48j/gu/YInQf72TeQY7zm8m7DZXDJZk8hSj4Ck5EOzm59lsL2RxFC0FAimM2A57Zl+W9vTxCEIe/nTquy4OmhJJNnziFv24QrK8jVEkGlhJ7J4raqHBoeYrHuULMczJbDf77k0JveSv+uXQx2pZkMJJ5AJ4qL4bkEZ45hXjmPks6i5TqxS0VCWaMZRCnEOphctYt7c7m9SdnRkcaPpyiWVphMRdkl2yjv/gKtWUfK5qldPsfyhfN4z36W7K6dyH67fwcBLNbs21z5NsWmg+1H+aSL8EiSxKwp+NnlBepWe+NYErCjJ8WDA8mPZTP5dwUt8JFLy/iLswhVRe7ux05kCCUJK5Cpu+1KhKQKcnjz76YVSFwrNjFdHxEGhI06QlEIHZvQcTg/FrJba1ErJVn2Fa5WXcJmky93CmS1yoxw+UVRJ1Q0Pru9i46ZC0y8/jNqiU4Wt+7lF+9NUDVHiXb30tX3CJ/5vz4NvsePqxIRN8pEZZlQiaBqOr7vIYc+5mqFjO/5bMhJFEbyFGfmaC5XUGcuYJ6ZJ7J5M/r23biSTBBLELouoSzj/4YkMG2h8K2ygbrtCeJSQCOQmKvbBKELuMzVXYbiYEcTGDv30zrxdvuNYbBWFaMObcRrtbjR6yWoltteLJ09RB9/jreWPd48sypHLATNSJLXZpssBQqPDyURwUdbv/pCasuO3YGry00O9iZQuTUIIoTgWtXj5SvLNz2+XLf57tl5vravl4T0AR5yYQiDG1HGLl+vjl9FzuSQN+/EWQ++rLPOOuus8zFy3wIwf/qnf8ro6Chf+MIX2LRpE9Hox2MIvnnzZn7+858zNzdHT08PExMTXL58mT/4gz+46XUXLlzgn/yTf0IsFmPnzp18/etfJ5FI3PaYruviutcn4kIIIpHI2v9v/PeTiC5BIR3l/HIRVZZ4LC/TeO1lgtVJZFSTKZsOG488wMtXlrksuYw1QxRZ4mqxyaGBDI+M5LAcFwnB5s4YPXGVy8UWyDJC1TBbNpfPXuLBnRs5bUF/2iBlKCyV6ziyhi/JVCyPqXKZTZ0Jqi2PmuW1F7RCsKMnzXfPzlOvW0gCJhbLnK7U0TSFrx7dzHLJYrnh0psy2Fy6Qnn0MiAIBczWbLofeRrzpR/iNhuEto2a76T2ix+hFHqJPP5pLM3AaDUwT76F1Grizk4hAh9kGc/3aL72M6y+7YzZEpbrU0jqdEYSa5JiAohrH7wtGtMVhPCxQpm3xpfWpreVlst15TabXT0puo2P1p58QNn/INFoDOvCKYKWidAN9C07kXfuxxLSLdZwv9yWI2YD88VvEVjXZeX8epXmyy8Sf/qzWL2/nVIvd9Nfb/z/3fbd8H0fnXr1ts/L6SyhqiM+inRcGOIJqd2gguBj+V1JKPBwXuVHEwpOModN+95HVYknh7MsTU4TVGpoqopSWyZwXEIh6NkySHLnNq6JBBHNoWy5a8GXTZ1xdFnm+6enUa0mqYjKnOry1vIsX3xgM7loiUrTxnJdrpy7wvTQBiZsBdOxODyYbR9HtKX+NFlCUySEDafnquzqTZLvMuAOizhHVlD7h2nZLjWhUrY8QKBH2oGviCzhChkvDLFDgekFoGg4fkAoyYjOHkLH4t0Vmxe27SGWydJ89aeEyTR6OkvjB99sy7FIEurABrx8N5FDLzBTtenLxDBkkAhoOh4/vrDA1/b3EVdlFps+K5bDgunzWMKlcvK9m+8tYFoWkXdeRfvMV3Gk9nAryzJnJmss1FYDBVXoSsd4fkeB8ZUmkpDY39eF7/u8fHkBNufZllE+VN/7bRyv7ra/3vj3rzx/WeGliys3BV+gLd31w/OL/N7+biLiZnlJXygcn6lw7PxZWraHnMnS09vFo5vy5NSAMHTxfcFY2aHUWJXyAC7OlXh6cweSLHN+vs7TWzv5e3Ed03aQXYeZiRlOjM/xf3tmO/b//O945RKoGiKT44qe5/S5MUIjRjbfx4LjUVmp8uLlZR7akEPv6iZpKGhOEzwf03U5OWWjxuPU7AAhywhFQVUTzFWbHB3J89rYCqqu4UkyGzoMCimDV68VMVSJxaqF5DkkhMend2/h1KkLXKvFeDeEI5sNdvRpWK4PkmDFVehQQoIwxB3ZTrR7AFFZgTAk1tNHRSh44W/WYtSn7QkD3NPv5b30g1DIHJ83OTZxfcN/qW5xYb7KZ3f20Bu9t2zvj4vfRF++l7nwr/O8hBA3eQiFgNTRhaIo+OUVAgFSVy/uP/t/8fOSYGrOxFN1hoIyD8+8Q2R+mlLDXpNnNVdW8P/yv/HEF/4AL9bBty8uYnsB1ZZDpeVyebHKkeEcubhO0YVkMklvUCfx3osQhmSe/gy/f7Cfq8Um1ZZLPqbTH5cZP3mapmkRVSS0dJaa0r5WqmejuR6qb9MRVbC9gEajXc0zWbGo2T793TJXlxsc6EuSigj8d1/FvnYJtbMb2XNZ/pv/1fYUM+KIRJ4oMk898hyTcoIfXqvQkjXiocRyJEthKMWhbpj65jcZzhjQbNKoNonFYxhd/ay89nPSw8Mo0XZIRZEgoslwu3wTAboioUkCEfz2jCMfhpov84Pzszje9Q3VIISzs1WiqsIDvZG1bPnfpjHzbrmXsfWjYLg2zqs/wbrRl0tIGI89x8XUEG+MLdGw2+NtV9Lg8U0d5LXrSRAhgjAM0WQJbBuEaAczHBuxOsL0bNzAt87M4VsOVrlE2XR40wt4bEcfOyvn+Wd9/ZzObUVtlJFOvIGuqXibd/Hd98bJRjV0RcJemmfSiPIn03W+uLeXK+Uqj+RSVCyPdDSKPLIV4doono3WqJKM6aSHBmkl0sz98LusXLqw9vVWgJViiY2WibH/QZz3XsOfnUIYBpFtewkKfTjSvafKfJTfz6b3wYHTsRWTjekkvu8Tbt9HVDewzrwHjRpSPIG2cSty3xDm5Qs3vU/u6sEPAgIhUevfwunZCZTewfZ5ajq+qhKGcGm+xt6eJFn13s791u/8we9fe9VtrpEnFI5N3t6jw/YCrq6YHCwYH1gFY2sG+pOfRZ+ZwLlyHoIQdeM2xMAGLM1Yt1VfZ5111lnnY+W+BWBGR0d54YUX+NrXvvaxHvcLX/gCrVaLf/Nv/g2SJBEEAV//+td55JFH1l6zd+9eHnjgATo7O1lYWOAv/uIv+Pf//t/z7/7dv0O6jfbnt771Lf76r/967e/h4WH+w3/4D+Tz+bXHCoVPttHWgUDnxcsrZKIa/aJOvdFob5AKQVJXWbR9glSBualZEl0xopqBF4TkYhrzNYtjk1UeHMqztZBAU9qTTldt8u5sE6+zgL84RxjCYqlOKYClShMlodEKZfwAVEXBC9oZaQ3HoztlcG6hikDQm44wW21huT6qphJXBa7jEI0aSJEIv7i6wtbuNA3bZU9Co/rqKUIEQRCCkLCQCcKQ1qljqH2DWIVBQq2dfS+XVtBnJ0g++Dgrp05QLTcJpyZA00nt3IueShOJJ5jKDvPDNy7hdxQQisaZxRZdSZ3P7eymM9E2IE47Pht7TOYq1i3XtyupM1LIEtcVxlcadKUTCAFl08Xybp4Irtiwf7j747mxfQP4Bx4ksFoIXUfOdNxxYm+7PtWWS6Yjj67ImG+9TCAJuF1w9NJpOrftQorGPp7z/Bi5m/56I/fSd53DD9EoLd1alSIE8cMPof0W/g749RobrSUeP7Kbl68uUa1ZJAyVHd1JtnbH+cGFS0iaQVirIkViKB1x9FSaBx/cSDwXJ1sxeWyrwnLDojcdZanhMNyR4NunptHtFsL3UGQdr1LGqpu8cXWJBzYUmC7WaYXghwFhpUQ83UMQhjw4lOH1sRU64gZL9bZefs0OyCYiq8bGAiOeJBPTb/kuQRiytdfh5LTCjFkn0vQZ7sowUW7hh9ARU6lbHorcDjJt70owolgkOhQGOjUuOjJ6NAbRGCURIh06BK//CC0WQx0YpvmT76AIAauSlG6pRHHkAK+8c55WoouSA5moSk8q0t4sAC6VHCzXZ2LFZENHDNMNsWcn8QLQVeWmxZqqKOh2i0Tgofb2A+B4PuZo46YkhFNzDRq2S1fCIKZLqIrMeKmFbkS4uGxzaLiLuPHhKq3gt2u8utf+Cr/6/CdWmqxYK7dN7AiBeqCyoff68d2FWV6/MsPrZ9obSBIQLi0w12zwoi/4+w9uIB9vt8efTU/ectyJisOeniQj+TivXVthptTEq1UgCNjZl+Hwvi3kzRVKlQpNJ0C4FtKhPbx7bRldk9m/oYNsRqPSlWbMVZnxFeouyN19ZP0WqlkjEdGpmVY7xd1x0DWdMAjpT+r84NISIYKkIfH5vQPULI+ryw0e29TBj84vUrXcdh8FfEnFEyonqiGDe/dycsGkZksYmsZMrdGuiA0CXry0zCObOtnfn0ZZmxdtXPvOd747nxzuph+MrzQ5v1S6bVs6Nttgy6GBj9QXPyr3sy/fS1/9dZ/X3kGJkn1zljOxOGG+m/6URmxrJ9+8WKIWeCgpAwXYqDrMnL9Ed1wjQEJWQCPA9iScepNOq8qfjTcZXzHJRlVKLY+o5qIqEv/tnWl+70A/EwsVxk9MooU+n9uzByEE33jpDMmBAa6VffKpCHnFp1Bboqs3gakVCCIGXcmAc9MrEELoexQ6s1gzZZ7aOkC95fCG5+IFIRsLaQpxmTeuLNOZiSFrBjW7hch0k+63UFNpSt/+S3zNQFEUWs0W0VTIkumRn7hM7ujzlMccbCfAcgNsJEIBammOegD1QAZfQoiQwLLQq0X0VAGlUaV7ZPfapTziaPzg/O29n/b0punpyv0a7+794crVZRTNuK1v+JWyzZFNBTpXf/d/m8bMu+XDjK33ShiGmK+8SFheRr3xN1LVuNoIeWV6BimRoq8jxialheG3aC0XUTYN0ZFsv94LAjZ129ScFZYCD6EoBI36WvDlyMYuTi3UcWs1wnoVHA9Zas+t3rg4S2HfBua/9z0in0tjBQ7Fco3urVu5tNxElSVsPyCiym15s8AlCFXmqhbbe5Is1G0GsjEuLzVo2B4JXSZwZbKJbp55cAi/O0NjfIzqtSu3SJXbvsC5cIZILIZ09WK7IqzVJHzz5+hbdpJ59Bkk48Mll36Y9hZWW8Ri0TsWzcdjETo7b/CT6u3D33OQoGXiLy/SOvk24fQ40egNMp6KQmLXPtSuLgAuLNQglkCP3T5htRHI7Oi+2bMqDEOKDYeG46ErEp1xHUW+da/lxu+8byjkzbHSLa8B2NmfZqBw+7XsQs3CDleIRm+/nVW0oGv1u/xKBoYIH3gECBHy322Z+nXWWWeddX5z3LcRJpfLEYt9/Ju3b731Fq+//jp//Md/TH9/PxMTE/zZn/0ZmUyGxx9/HICHHnpo7fUDAwMMDg7yr/7Vv+L8+fPs2rXrlmN+8Ytf5LOf/eza3+8P+svLy/i+T6FQYGFh4beyGuBGhCxTcQR120eVBVlDQqNdCh4TKi/s7OLETIWoLGgASUMlH9eYrVgMbNvE20WTIAyIyBIxSSamKciSwPVDLi3W2V6Ic3m+QofSzg6OyCqH+hIU0xpeV4q5q2PMlxps2NjFStOm7vjUvZCIGpKKqFiez5Ob8xyfKtGbidGV0Ck2HFKGQt328PwAVRJkDIVSsUY6l2Ws2KAzFXJkowYIUpKPWWuiiBDCAALo6OvBuXwODxCuS7FuU3FMBCGqJNFz7BhG7xYWl2ukrCYikyO9fSfWsTewlhdgeCtm9CJPHn2aV22LyqoB67hp8jPh8+Rwck0v+pH+OD+zbGZKTd63Ou/NRHlsME69tEwRlasVhwvzVYIwZHNnnK64xuhCFX81pdNzor+G9iSD7cHCrQvqQMhM1X1OzFTwUNCEzyMjHeSvXMI1zdsfzpohXJjHitx7HxZCIMvtIJ3vfzgJl+7uOweoPqi/ejeYTwoh7rnvyrE06oGHaB17naDVvjZSJErk4ENU4mn8+flfcYT7j+F7XHANXv7FO3R2ZhhIR/AckytvX2Jal3nmqaOcGJ1lfroKrkNBh8e3jCB8l9dGFzH9gHLLgxC+sKcXgoDXx0voAiTfJQh8VEmsyZuNTy3w0MY8uwZyvHq1CIDkOhwaSJE0NE7P1SibLgcH0iR1hbNzNRbrFuPFBsPZKIYMZqOGVbt+r94PjAdBwLacxjvjLqbtcmmpzsMbOxkvzxCEkI5oLNZtdFniq1uS7Jo+zuU33kYPPfxkhO0DIwxsP8xxU6PVauHVqzSmx/FbFtFGHbe5KnsgBGE2TyuSQk4maU2WSCayrAQSyzUPiZB8RCYUgnMzHhuyETIa6CIgqQkC06NuOUioSKLdtiQEqggxTRPRqGOtthVZlonKAeb7fU2SaNkOjuszXWrQnTSoNMy1531HYqlUoS7uXebhw7T5j4OPo7++/9zdnH/JEtev521YLNdZkC3CMESWJKyr47x1af6Wz6NaobS4xIWZJFvSMrIsE7ruTccWQNxQsByXN68VsfyATEzHV9OIMGSs1OKhoV5YmqCxKnMjJEGQyBA1Ax7pieBfeBOxYQsi08XhpMwjuThvVgMe29xFujHDwf4M4WILTYlSblrge8R1jc8cGMKpVQk8HweJSws1NmRj7OlPsacnQbnlsdywMB2fvnQEx/XbVhmyxHjZYmNnEset8eTWAsemyrx8ZQnXD4nrCk9sznNueoUIHh3adUmV31Qb+ji52+8ghODyknPHtmSaMLFUJqd+NMkZF4XZhseV5SYC2NQZoyeuoH6AFOmv6z581L56v9pHl6FiCI9S0yEQEi03oGx5SEJwaCTPmaLF5YUKu3rSxHUZx/PR/Dot26YiQiDA8zwkBIoEjh/gSgpXlxroqrzq96Rhuj6VmoXt+oyvNChINjOmSRN4cd5nY1ZnoVhly6YQvSfGrqBE7ZVXaC7OIByL3m1baWw7RNlVeGZbgQsLdXqyCVKpOP3ZGJ06/B8nrzKYjiHrBtMLy1wyHfr6CxiKxIW5EpfHF2Clzp7+zRxtTmBmCiybHl4QoqbiZAwdYTlYs1NsMjye215AEm0ZtPGVJnJxgVD28cP371mIIkEYBtjVMvFkDuF7zN8wf8mpCls7DE7NlAnCcE2RaEshyc7u5Ce2/wtJpuYJLB9GF6rUTQtZBPyyWaIJFMs1vMZv9xrv4xpbb0QI0a4yuwupJd2xsM4cX5sPv//+sDDIW+NFHF9mf1eU7vHjOFcuoImApg+Tm7eydPhh5ESStBqwo0NndDakJxVhru4QhgEg6EhG6ErHOHVpGj0M8et1UDUkSUGVJfwwYKzq0dORpdNcIt3bQ5CK0DTilOdbCAGyaAcBHD8gJiCuK1wrNqm1HPrSUUbycTRF4txcre2BmjTYO5BmsmyRNBpocgTjmRdQK0WaZ97DabTniSlNxpydIbZtxy1jhHnyXbyeQVq5u9zsv+Hafdj2JmSFDkMwuXJ7qeSBROamPn4dCTXbidQ7SKu8gpJIgaxAGKLvPcyKrBOuvs+2pA+cW7m2fdNneELh1LzJ6dkKlusjS4KN+QRHh9JEhXvH7zwQUzkuPMrNm31g4rrCppTMwm3WsgAWCoFn03JuHZMlAYXeOOenl2k6PjFVIq0LpI8omXYvfFB/XWedddZZ53eT+xaA+dznPsePf/xjnn76aXT91kznD8uf//mf88ILL6wFWQYGBlheXubb3/72WgDml+nq6iKRSLCwsHDbAIyqqqjq7TMc10qo79F08H7jSirvTNQ4P19b2+hPRzSe3pqnSw8x8NClkJFshA35OEObCjTqTZqOz7ZCAqI6izULywtxQgVVkrC9gNlKC8vzSRoKvSmD3nSEhwfiEHhcW7E5NVtlqmJhuwG7t+xgc1wlm4iw2PS4sNSkLyJTablULZf9/Wme3JKnNxXhjbEVPrujm+WGjRcEBAEsRTVyURWzXMEwNEqrZseB79ObMpAFrHgS3fEoTr2BLEngB+QSBuFcHUmPYEoatVoDjAh6Mkm2uwDRKFXTwUnlEKpKaus2Gj/4JpJuYPQPYnsOqaUppFe/x+de+H3+5wJr8hdXluoc7k8SXd1kjeDw2S1Zyk6GlhsQUSUyGojAxUblh5eWma3aaxU94ytNCkmDR0dynJ8tI4CBtEFwnyaEQpI5sWDyzngJIQkiRoRl0+Tnl5f4jBwhIsRt27XQdMJVs817wXBtmJvCvdIucdc2bYeeASz14/sNuJv++suP3e338IBgeAtGdz+iVmm/P5nGNu5sCPmbpq7GOV70aLoBk7MrKLJACX2wbWqtgOm5Zb7UYVPNtLMiY+V5pOoCl8J+rhRb/PTSIitNhzAM6Ymr/NGRIQY0n3IUFloyLddDlmVkScILwQ8C/MU5DteW6Nm/i5mmz4atGzhZk3h9bAVDlZkomVxaapCNajwykmN0uUF3KkI+qdOXjiAF7c9TwhCtViJYmANA6uhEz3Xyqa2dRDWFC/N1zsxU+GcPbWB0ucHlxTr7etM8Mpxh18JZmtUVdu7ajLlSpLhQRLl8nlijypYjn6MciaFpCp6qg2QSvm8oLMvY3cNM1FxWynXSCyugaoRBSCaqUzEdVhoOGSNCGEJvwqDm+Fwptqi7IU9tLSDNt2X7XD9EV9qb9F1JA00KkWIJwlhyrc15nseu7gSjizWCEEQYYqgyLbe9gDwwkGG+fF0POxlR0aSQ8DYGyXfLb9N4da/99f3HP+j8I4qMJOBOlyhtqGv9VTEbNFoWTbNduZhKRBnIRJCFYK7hUKyUmKvZbM3EcF2XrV1xLi/VEAg2JBW2iAbR0jitUZ+/19XP26bBy9MN4go4jouhG8iSwERC0lRCx0VIMlKrzuMbejHfeY3W4ad4farB3MQcAkFHbonnnjzE6zMVKqksegQe2JpjvNigUVfJxDQO5A02tMYo53qJ5FwwIgyMbOP4XJ2/PDZNEIZszMdJGhobOjQEENHaUzwvCLC8AF2VOTLSwTuTJWotF9dvXzDLC3j96jIPj+QYL5l09UZv2bD7bWpDH5b3DaPvpNkvhMD7Fb/rQfDRroMjVH58eYWZ8vVNrcuLNQayUZ7dnGubJn8A9/M+3Etf/XWfl47DCzu7OLNo8srVFUqmQ1cywoZcjL86Mc2+/gz7B3L88PwCth/QEVWJjaTp272fxtmTdKeizDoeEBLVFCQvINQNAhoUkm2JmrrtteU1q23pW9fz2R4XbNxaYNEKOe+EaLEYDz+4i/lWwAOpBo0ffZ+kDCKVIBroVObmqV36C/o/82UuVW0e2z7EGxMVRutV3p0s0ZvUeeaBrXz72DXKtQrPbUiySfIRlUv0xLNUmmmWmiWKtRp1CiyZAdM1F8+ykITADUIqgcJgR4rFus3FuQo/vGRhez7DuRhPbs4zWZrHS+bQFJkIPt6NyedhSDQeRc9msFfvVyAUimZARJM4srGTWssjoggG0zodhkQyotKsfPL6vy+1N4NPTJXRFJmooXNtxaQnZRBXuSkIoysSqnzrGk8IgYNC0w2RJUFCbXtr/jZyz2OrJFN2BFMVC8cL6E0bdEYllA9YjwjfI7Dfr/oX2KGgZnoEcoLZlTrDA10URo9hXj6PriqMVVrtiohjJ+iu1Zjc8yTb+jvojYV8aV8/Jy8GXC07NJsqGzpi7OvQUasLeFPXUPsH8IIAWVEI/RBZAq+dG0RXOkqtWie2Jc2cr9Nn6BzdmOTsdJnZlRqqoqDIMg1Uik2HrXENPwip2x6vXiuyvy/Np7d3YXsBpabNpYU6T26N8ZPRZcYXqzhNk85Yhuee+3ukTr5M/doV4sLHM812sOI2eFPXEB2FD7U2+FC/n57LQ8NZlurWLQGIHT1J8hFx07xRkqS1QJsjJLRt+0imszjnThJaLeThTZBI3XQuGV0iritrknI3osqCzphCuJo4IMkyx2YanJgqr73GD0IuL9aotBxe2J5HuWF8u/FzDBy+sLOLS0sml5fqhCFszMfY3hUnLnl3vDYRyWd7IcnxGz4TQBaCHb0ZLiw2eO3KEtCel/dlozy1KUeUdb+nddZZZ511fjPctwDMM888QxAE/PEf/zEPPvgguVzutvJfN2bv3A22bd9yHOlXbBSvrKzQaDTIZH61MfknEUmSOD3f5Mzszd4V1ZbDTy4t8aVdBaLCZXd3jDNLCv/rapnDhe2Urr5E0lAxHR/PmmHT9n5OSzpznkwiKnF+rsb7l3ooG+PyUp2fXl5iKLuVctPmF1dXaDoBrt+efF5YauKHMTqzCR7dlOfTO3tYqlk0HY9cXOfqcoNvnphlS1eCp7fmKTdaDCRV/BA6k1GuLdUJPQ9DlbEDCRFAVFd5YLiDUtPh6wf6efVqkd/ftZ/iG68gyYJCMoraqCB39tJaLuLoUTwrZGTfHqL1EtbF9xBG23h8aO8h4l/7A6zv/gVKKo2iarjTE9hqBDcUUC6SPPYyn3rws/x4xiKkvcHqBXCjK7YIXLIKq72pXYUjhOBayWau0kIAPSmDyZKJH4Qs1CzmajapiMq2QpKMFnIbb8FfCzVP4q3JKlW7vSEXcwQRRWKlabHSvZGu6avtaqJfQh/ZimNE226td4nhWjgv/QBv6Xrmkjs/g9JZwHjyM1iq8bF8p183QRBgaQZ0FG588Dd3Qh+AicqZuRqzgYYdCgLPQ7iQUttG7pJhUPNlXFnFD1a1lYVELZqm2PT4qxPT7U3sMADXZaZk8/95aZR/8cQWjr15nO6OTpbkKDEpQMnm8Bp1MqkYWnEWd36WxXMTjAx24+/YwnfPTpOJasSDkP5MlLFig8W6xXS5RS6mEdcVHt7QQRC0q6LUMECMnmPelZmyFBquR8Gu0Fep09nZjyELdvcmCQK4ulxjS2eS/kyEwA85KpfwLp8gHL+GGwoSw1uI7NvD/LlzNGdnGPSq7BoZYckH5cHnkC+fIm6sSifme7m40qLeckFRqF6+xK6Dj/OLGvgiIBFRKTdtEBKuH6LKEj84127TE6UmV5fr/JMDg2T276F0+SIpXSETVXlfESFy8CFszVhrM4oQ9KouX9rVxQ8vFTEdn2xUpWm7HB7K4Xle25djlYMDmbaJ7f1rRp840hpsyMe5ehsj13REozMmt9s07YCX7HvomsIDwx2kFsexj18iCHx6+4fwt+zFjGrtOYSQSRgKXek4itViZOwYtYvnCDWFpuvT8N7m0U99loH9g5xbMokokNYkyr6gEihEDz5E6+1XkGSZZKuKGK/QOPwEPzg7h4O8KrgSUlyp8pO3L7Fhx2b++vQML/RrnHr5HTaN9PPs9i7yb/8IdbxBY/thwsU5+oWENXWFq80mZ2oqILC9gJ6UwYnpChDSl46Qj2vY3qoZsq5geT4JQ8P1QyqtdqapLAlimgyEvDdZZlNH/H4NR/cFIQStUOHdiRKX52oYqsTmzhgdGojw5k2rIAjoS0XucKR2Nm5Sk2i70dw7kiRxpWjdFHx5n6mSybVSnO1Z+RO30X2/iAqP/qTBnp4kfgjn52v89OICg9koy02X81eLKLJAU1RCBD++Vubh9AY29RaJ2SW6EgYLdZua5aLG4tiyzq6eJHXLQ1dlarZHw/YpJA2ymuBIRmD85Od49To9HXl27jqMXEjzF2+N0xVXcSZP4dguVS8gH9dIGwori1Uk30Mev0Tu4LO8cmGWkcECQ5ICvotpWnz/5Dj/6OFNyOUlvJ9/D90xMRSJxeNlXM/j6OPP8roGhgzzRgY0HSyLgBBVkXElmamySUchz8mmoCdlUGzaLNUtvn9uni9sGuDCxBjPPfYQ7qsvti+eECjZPJ4RJTzwMOdMlbyskNIEx2YaN21gRjWZdFRjWz6C9AFVWb/NCCG4WnJ4Z7wta+T6HsP5JAKYLrflQ/Ub5ro7ulPEJP9mOSdJYqwW8NbYIpWWs1rhHuGRDTmy6oer5v5tIZRkTi/avDVWXJtbHJuEvkyUT23pQA+d277P1wzkZAa/WqJmh8xUTEJC4i2TQEhsTGmUj18gF1GZKJlr10gS0JwYZ9PeJhOVBDM1QalpsbG7g31dJrHFKq1Xvos9NYG07wjd3b1kBnvQBgtIikKtXOHqxAKu7zKSMZg4vsTg3iOUbZ8tI300fvFdNnR0kYpk8Xft4KdXS5Dp4KIr4Qce2wpJjk2UUGWZnpRByXR4Z7JE2lCIqDJfPTDAjy4u0HICrEAQKDqVQOLPTy3wR4eeQl2YA69JJJvFD9rVOkLTCH1/LSAXet599w7KKB5f3dPDlaLJ2IqJoQp2dafoScjI7wfShETFk5hYblGzPLqTBiNJGU6/SfXs8esHO/kO4sJpYs99ETOZBcCQfJ7YnOdH5xfwbgjmCOCRjXni8vVqsponcXa2ctvzXKxZFC2fwi/l3imKghAC3/eJBC4HCjp7ChFCBJoI8H33jhJr0B6z9/bEWWrYTJeuj6tD+Tijy00s53o7DoHpksnPRkM+t61dBbjOOuuss84695v7FoCZmpriu9/9LpVKhR//+Md3fN29BmAOHDjA3/7t39LR0UFfXx8TExN8//vf54knngDAsiy++c1v8sADD5BOp1lcXOTP//zPKRQK7Nmz5yN9p99Wmr58U/BFEjDUkcDQFEqmy6UVhy05jZTatraYrFp40SEef/6LZMbPcGViDhnB9s19nB6zSHowV20HIMKwvSjc3hXnu2fmkWSJEzNVmrbHQt3BD8K1TJlntnayULP4xolZWq7PZKnJ9lU5g1euLJOPG4yvNLA9n3xMY1NHjDMzK7h+SLFh8eSWPNeWGyieAraFV6+xpT/FnozNaHmFUI3xtf19GH6OfboPo+fQ7SbWuZMkn/0MitlifqHK0JEjqOePsTQxgZAklL5hRt8+Tuz0OQ79/d8jrJQwsjncmUkkSUbVNFzbBSFhT46R6R+lkNjIfN0hrisY8l0Y+Uoy5+evL2gjcsiGXJSq1V7gz1Za/NED/WTV4I7m4x83Qgim6x6XlxptvxygZgcEgc9AJsK5MEnP7oNw9t2b3qd0FpB37se5h6CDJEmEY6M3BV/ex1taQB0bRdq297e2iuSTiCTLvD1WxfFDbFlH9A2j10p49TqOIoh1dpPr6qCjM8tfXapQLrY3JgqdOQ5FMrw3OrdWQeA7Lqxmf1ZbLk3HY2Col5W5BUYGhgmnxwgNg2j/AI8NJYm8d4UwkWJfh0H08Wf5/0016E4ZKJJE1XKJawqbOxOYrk/Dcfl7B/o5NlliqWbRG2trZsulIufsCD87P4PvX28XqUSULz6Ux/R8Tk1XGcxG6UhE+O9vT9CpwT8aUlj+8d/gXbuMocqIMIRTbyLnuujffxTr6mV6aPI3o0Veu7ZMXBYMBBk+25Wmd/+DLEwv0bQshCThI9Gq1tiQ0rkUyXB+oUZPQmfICIlVl3l8IEOkOoE2mOBHs20/p+WGw//79Wn+70efYseGQeQrZ7BMCyuRQdl9iKXCADEEKgHaygL+zCS+adLru/xvI9tZyvRSC2QkSebk1ArTpbachKZIHBrMMphUCO+jZMInkdD3eGxDFkIYKzbW2nFn0uDZzXl0vLVNJi8SJeM1+dTuAayffofq8tLacZzqabT5Wfb+0T/BDzOcX3F49cosG7sSHPLLTF08DwhyCZ2YG5Lce5QXr5apRUMutWQaLQdZlvgHh4dQhjbRWFqk+4Wv4px6h4imIEk+L1V9QklGkRT68ylkWaLZaFItl5kuNcinopBOEjEMpq6M05ib5WsHDnCyJjgz06BZmsNTVDbv3IkhCVrXzpMb2siCL6hbHp1xjcWGQ0dcJwihbns0bI8v7O5Bk2W6UzqW67Wz41VBWpdISD6EIRagqVK7D/0doRYofOfsAp5Q16RUTs9UOLIhx95O45YgTIchGMnHubZ8czBPAEc35DAk/0PH3z3asjd34uxcla0d+fWNoTsgZJn3pkvMlE1WrICFWjsTf0M+wetjRVRZotJyKZsOuiKRjWqc1nT2HHoY9a3vkYsqhAjy3Qm0R5/jhK/w4GCWb56aZaFmEdPbPhO6BHtVl75yiUo0RtgyqV+7QqFZRpF9jnan2DnUgf/9KlJUpUtV8H0fV1MxEgHNSh1J07FljXguy4uXi7TcduX4kf4kTw4mWZ6Y5Bm1jLNjhMbEOGMTc4R221C7/PJPOPS53+OsA1U5yVAmR9hs4AcBIhpDVmTKLY+Nhx5ifEkiaUDSiFE22/5ksWSc/SM5knUH+YlnMM+dxNGiLCsJpP1HeFvpZuryEpJo+22M/5KEken4mE6Ld6aqPL0heb9v88eCi8LxqZWbHpsq1vjszgIvXlyk0vIoxNqySyOdcfb3xgkC9yaD8KlGyI/PL6yNHSEwU27x7bPzfHVPD3Hpk5tFv9SCN8eKtzw+UzY5NVfnSG/ktvNzV1Yw9h2m8tKLzFXbwRcAb/wKuzY9iBp4VC2XlN724nwfXZFRJEHMbvJXozP0pCNEpJAri3Wi+HxqeIhcrgtvfhbNtdj56AG+eWqOku3j1+sMdsQ5sn8r5fklYrVlgs4O0t0Fxr/114wuzdKjakjFBaJqjdLkGM9//ut8Y9mgR9N4ZFOeuWqLQ4MZHk+6zJ67RLxVJezoQt66hzfmTM7OVRlfaVEyHaKqjOf5eNUW6ajGazMNXjj8EP7JN0g/9DB1x2Nl/1MstwJ0VaIgLOLj51AGhmndobry10UYhsSlduDiQE8UibBdvXpD8OVq1efnl+bxV+/HubkqkZxL7sxJDE1FynWCLBOWVwjMJva7r6I+8wXcsB3gGIxLfHVfL5eWGizUbDJRlR2FBHkDCK5/34bjr1XV3o7lhkP3qn+a36iRWJ4jWFnGty3keALRM4gVia0Ffe/2Suqhy/ObsyxbaearFqoskY5HuLY0wy1ag8BsuUXJCsn95qzc1llnnXXW+R3mvgVg/st/+S+Ypsk//af/lE2bNt3W4PTD8I//8T/mG9/4Bv/1v/5XqtUq2WyWZ555hq985StAeyN4amqKV155hWazSTabZffu3fze7/3eHUu1P+nYfriWQS2A7b0Z3p2srC2yMlGNobTOE1sLnJopU2nazFdDTkka/+jwZ5nqK1L2BD+8ZPL4pjxVy2NypYksQjblExzoT/HqpXl81yaiR5komSR1lcV6W4e1I66xpTNOseHw1niZ3rTBQs2i6ficX6ix1LAZyESJaTJPbOrk7YkSTcfHUBWObOzi0lyFuuPTnzI4WohQXVjEKZqkNhSQBXiuz5bmLHqki788scJgJsrXDz5KRzqOXK9g7z1ETY/iP/NlUu+9Q1KBpYkJ1GgUP9vJlSbYLRunZTH12usU9h3Ff+1HBJaFFIujhD6yLCGrKnoshrk0x+H+TbxoyRwcyNzVBkwIa5NdBMi+R8S2iUoCkgaRmEpCCRD3cWPVQmGhdj348j5BEDJTsTBkiSN7D9EzNIw3NU7o2ii9gwQdBVrKvfUVxffWZMduh3vlAsrmnTji1iq4de4eSZLQ7BbCsaloSa4tN5Alwb6+ND8438KIdhBLdGALiOsh+Y4Yb1xeQCteN7tcMj2+c26BwVyMY1MVwiBoR1rFddmKt8eK/OG2PKcxudYoU69WyKtpjh7YSEoNWXngOeqBRFFLEUpptvW0fX8qLZepkklpVdd5IBNlrmJzdbnO6GKdzfk4XQkdJfQo1u1bgi8A1brJL85P85UHdjC+3GRff4ZXLs4z6JQZkEE5cYmg0QDfwxGgSBKSAL2yTDx0sLMpJpoBv5hexg9CbC/E1xL8n1db/KsnvoR06jjaeyewWxZqNE52z35+WtNZ8Sw+u73ASCxEbcoko1nMxSWs6XFSM9N87eFP87+mwfMDHD/gbC3ksZ0HWO7ZxPRSlWVPZmrexZudZUshwaMdMqMzVc4ta7i+wqZclI3LRbqqRXLb9hEKn47NOcpWuu1vY8jEZX89+HKX6KHDsxvTlAfSq+OJREaXkIObMyjdEGIbtzB89TIXq2VkSUJVlTXN+HxURZw7hvPQ8yw3TTZ1pylEJPwTp0gbMoYiMV8xEZ09HFvyGF8oo0UtCn0jzPkBTcvh9avL7H1iCx2HH6D57qtIg5sJewbwmi2axSYH92zCUiNcXm7gByHDGzrZqCu8U3EwNIVmICH6h5DrVaLpGG8ZPZwbvYSnxnA6E6i+y6n5Oql4jE89to+5VsDSjMnLo8t8ansB0/WZLpss1lrk4wbPbu1iqtTkynKDR0Y62FZI8vb4ChviArEyh7uqcR/VDQZEAfz7m8V7t8iShNasQ63c9m1KZXEisZs2CiVJwg4l3EBgKII3rrTl1qLRm8ewt8dWGEj33bIJI4UeT45k6EkZnJ2t0XI9sjGdw4MZemN8pKSBIGStQvh2eH5IENxUYLvODQQhON5qJdsNj0tCIEsS0+UW2qrZcxBCqelgewGNfRvZ9NwXMVsWrUbAvJxkdEVweXmBz+/u5eiGHO+Ml6haLlFV5g/2dtKlhfxiskij+wDZTpMdSUH8yntU336F7ud+n788Nc/hmkNtoYYkSfSkDGIKpJWAiiwT2bab04tNXh8rI0vttijZFm+fK1PrzbAnGdI68x5ieZ70w08jjU2tbTiGvo9WKaJ1dfHOlEv/458jffk9mmNXqZkO8UyOrkcOMdUxRI9ZwQva8/5E2kATIcnQYSSl07oyjdU00R95hkm9k2umxKRvYK/6rYUI/vbUHE9tyVNq3myALYDJuRXsLDiNMroewZbVT0zVhxNAzbq5iqNmefilBp/e3oWuKnQnVFK6vCYbfCO+kHlnYvm2lactx+daqcW+Tu0TmUSkKAoXJu8cCL6wUGNvdxz9NrWQYRji9g6jPPg40ku/wG+215WSqrN72xCN4gphuKoUsEpEVZAliBkq81a7+v7GdtSSFP78isnXn/37ZB5+jgU5ys/OLxFNxKg6NYJIhNlqi1cmJf7pgSGW33qd5UPP0rMwS21qijAMqUqCjmiCbESjJy4hxs/y5Qc+TSKT4mqxRcvx2NGcof7Sz4i6HooioRR6+M7PjtG1eYR5S2GpbhGGUPcDkoaKIsvYhCy1Qox9++navoVmAD968wJTV2bWzl9VZJ4+8DjbOns+hrvT9gm0AoEfQETmruaAQRBAENxyx+q+zEuX28GXtk+UhKHKBJOXKPdupZXv5exSE88N2Di4kc1yC+XcWxjVMkGmA9/3CYKAjBLwcH8MRBwBq0Gemz/r/d/eO2Eo7ZEtVitR/db/SfPkOxAEyPkuIgeO4oxfIfLAY5jx1D1crTZy6FHQoadgEIYh12outwu+sPqo6QbrAZh11llnnXV+I9y3AMzExARf+9rXePrppz/W40YiEf7wD/+QP/zDP7zt85qm8Sd/8icf62f+tqPJ7UmW6wfkEwaXl5o3ZbjpioTj+/z4wgIbOxOcnm0bwid0lWog88qiT6nlkDRU3hgr8vsH+olr/SzULGYqLb5zYhLPD4lFDYIgJBVRqZgOuZhOPCtTMh0KqQg/vbhIVJNx/QBZCKKqjEAwUTL5/K5uvnNmDkkI5qotErrK3EqdZjXBFzpsItSRfVAvXUOcP8vc/qd5a8nj+PQKNdNlpCfHMwMdfCYeUnFC5ixQhnexvFikXmuSj2tEO3tZPNpJ34WfwuAm5uyQYt1DCl3E6sRs/PJVur/+FTzRNtjG91CjcSKSgiNrKHsfYG50Erdqcmi4l615lcD71VlvCiEjuRgrDRu5UcdfnCP0r2ckbd29ibjwce7jWrbmhHTGVDZ2xJgomTeVk3t+AJJA11RMvQMp29mWbvmw2VxB0C7NvwOh77clmX7FhH2dO6MFPtLoGayzJ9pZa4eeoV+OomWyJKMaj27K8+a1Iite+z7vGuhi3nYwHJNAltu+FOkMIpkhDENKpktX0mChYrZNVQEhQFEk8oZE8vRrPDA2ygPP/z2aXRB1m5wv1ThdatCVT1OJ57CEimqHHJ8uM1U26c9E+NLeHl69UmSmajFfszg6nCUSenxuUwrNt/nF8avs3tjNXMPHdgMEIEntDSA/BC8IuTZT5OEjMl/Z38/4SpPAddDjcXZ2SgSXZ/AVDSNi4LQs9KhB0/Gp2Q6tC+cJR3Ywo6TJxQOWVjOmK05ABYXvzIfEBw6hZDaSIGDRgb+aa7Gy0K4g7JB99g1HePXSFDNLVUqmS08+ycMHHka+cooNXQcYLdlENZnupEHZdPmbi6XVX5fr7T/wfP7mYpXS1cU175nF5QqnYxG+sCVDoVHBjKUwCOheU+YL3lfNWuduCTwyCmQUAP+m7MwbcbKdSPM/YbArTcWFiuWhqQo9CZ2IInBnp1hZWuF751ewXJ8jBQN/qUKXJDBtj6Vyg+6DI4xdLNEeNjwC3+dTGzPoocdSoPHe5ArFSwto6ghbCxH6OlJ0ZhsMJxTeXnG5tLDC+3vxo/NVCj0dPLm9l3cny8Q1mUlXIxnvYPdQBydmaixLCRzLpWlZxCIG2Uyas8t1BruSHJ9fYW9fDj8IeOXqMocG0jy3rYvlusVUpcXLV5bQZJmEoTK+0uTB4RzVchV74tqafIokYDgXI3H2dfSt2zHzH89mEqx6qyDjhAJdam+W3OtGrhoGSOdPYp4+RuiumvkaEaIPPoYzsBE/DPGEysVli9MzFUzHY89AjtNzdeLareNMCFwpNsnfJtNbDV325DW2dXThhaBLYTtZ4iP2R020peEuLNx+DtGXiaBK4Z2a7e8UoaRSc0K8MCSmSkQlH8KAoVyUpbq1KpvXJhfXWG7YKLKEoUoosooAFEmgBB5OrUbtjR+wsOMRztkRUvk43VrIrt4UxabHqeky/ZkozxYS5KIqkufyv79ymabtEtEUcrEoY47L87seJXHqdVbmFji5FHB0225Y+AlBEDBbbRHTZHK+Q1dUxs/3cO7iDLJo+3dFhITfMgnCkJOTRY48uhHXbOIsLqKfP0Pnli1YszNUq3WCICAaOOSzKabOF/mzyw02dB7mgc2HyCiwEOi8NtfiEScgDAJkICECgqU5gnqVeLSPysXX0Xt6Sex9gOV0Lz8/vYQjyzfvSQqw/YDFmk1MV2iuVq/LQUC4PI9Zq2DF8jSuHMdWNCKPPUsr0/mJCMIoEkS1W70rmrbHxbkKO3tSbEzq+P7t+3XLh2LDuvWJVSZWTA52375K5LcdIQQ1686b+rbr44fcHOW8AU8IJnu2YT7dQdIzQZKZIsLVCZPH+3JsHO5BMuuUTQVVFnh+SM3ySKYSXAkTBLiossT7F15TZBKyTBWVerybt8eLKLqBWikyElcJ5BiylqFlOVxqSlzq2E2xFLC5dIG4oVIzbYKgXWFhuiGi1UQslNiw5wEmivCt00v8yz0ZVv7qJ3TEZMouzDkSZktmsVxja2AxT3z12rS/tuMHyISYbkDF9pg2fVqRGHMNi3k1jRR1CewWQpIIUll+viLIDKtklI+WMGOhcna2waXFBl4Q0JOKcLA/TYd275J3QghmazaaIrO5I47th5iOT08qQtLo48WrZRZPTyOLtjTr0vQ8pzWZL27YhX7lPIoRRdm6G3vV8+ZO3mnvk9baVcfvz7NvRJUluhMahlmh9d2/JLh6cU2W119epPHid4g//yWck++gPPos3of8iXm/P0ZvM+bfiKF8eCnRddZZZ5111vko3LcATGdn5/36qN954krI1kKCs3NVOpIGb5y5LgMlCUjobb132XeJ4fOZkSSRVBLHDzEUicc35Tk5W0GWBC3H5/XzU4z05Hj1yhKSEOiqTFSFQBLULZc9PSm+cWIG2wu4VmwQ1xUs16dsuiQNBVVWMV0fxw/QFBlZCEqmy3LDIWWoaLLU1qpt1iiueFzWdDbFEziuTLIwTDEzzCvXyhwfW0ZIEIvHmG0F/Od35vj8/n42pXQ0VeI/n1wCZCxTIygJdmFzoD9DJVCYMEPqlockAN/nfZle3w8x41liO/ZhLc+3J4SJFLLrkhraiD15lSG/RRAJ+cHsCt3xTjruImvG9322dsW4PLVMZX6aG1OwdVVml1xHnh7H6OpFWCbIMm40gfdrWNgKITDMOpkro3iXR/n70RiLXRt5z09yuuSvtYuHhnPE5HZ1z0ddVPqajto7iL9qXP/LqL2D+JoO97lc/+8KsiQhzh7DPNWWiwt7hygn8th+QL3eYqnlMZiOsPXIEEt1CyEkdvem+f7pKURXN6KzmwABkoQgQCXACwLycZ3ZsrnWXiVZImUoHO7UKX3vbdxGg/TsOOHoRdwjT9JRrZOeOo5/rsbAo0/xktfBhCVTttv9/eJCncuLDV7Y1c33z88ThCGPbcgxN7fIj04tMBCXGY4Jzs9GsWxB1fIQom2gaajt4K0kBJKmM28GzFUtag2bpZUq+zak2NGh4ycN6g0TpWcQZWGaMAywXI8gFKiKgrdzP3973iQV0SgkdBbr9toe1ImpEl8/OMi3xkuUimXwPQJVJ2GoKLLE3v4sP3/nFEt1C9cPEcDcco1vlZv83v4RHjQCLGIkVBhK67wzUbol506RBCDx9rUlRmIJpOr1TON6s8V7xTifyTchdu9Zf+t8OMIwxFYjjDcDXM8HIXAcn/pKk66EQUKFC4sNLNdHAE2honZ2UZm6RtPxiaZSRAo97JKy2JbFQDpKur6I99455MBnQ65Acs8B3hAhU4sVZhYrhMEs/+zzDxDRZa6cv4gsSasSLSGSbjBRdam2PPb1pTgxXeZasYkmwdf3G7iVCeLlRSRCutJZmrE4owtVvFBQNl2aHrx8ZZndvSme3pJnstSi2LR58dISQRASMxQWajaO55OP62SjGknPpKWAUNrTwFTC4FPDMcSp49itOuqzX8C90w7cPeBLKlfLNienV2jaHnFD5WB/huG0gnSX1V1CCJSZSZrvvXnzfbRaNF/9CfHnkzRz3bw+UeXC/PXMbsv1mSq36EoaRG9j7WK5/h01+4MgQCFYs3b7OAgCnz29Sa4uN3B+qRJGUyR29yQIfsflx4QQlFyZV64Vma+0CGlvpB8ezLC1Q2NLPsbZuSrCCzgwkCGmK3QnDXrTEWbKbQkh7f1AjO8RFR6OpDKz9ymsdBd5J8QoL5CeHkMtzjEcT/CHG7bzntf2T/rMjgL/9bXL2E0bBFiOx7TlUo/pvLTg8kz/JmJRnWxSMBpLsHHrdiqXLgCCYtMhE9Pp2TjMZBhSSBq4JRNZgsBq4Xs+SBKaImNoCsVrYyiej335POqTn2dsdJy+bArLbOF0DeD4Po9uKTC7VMFeWuCVa1U8P8BIJXn+wFZOL5v4SMgiIKwUCepVYlGDHsXF6BtAUlSsq5fxDvXjSPItCeFhEJIwFBqOh76aDCMEhKUl/FqFXCZOpL4MgF+r0Pzp94h+7vdoGbH72yg+BIbw2dOX5o1rt8psSQJ2FBLt4MsdkEQ7MHCjH9uNxPRPrleT7/sMZCPMVm71ogLIRHV0mQ/83UvqCj9e8YG2qUdXXPBgOkSYDZIPP4H2zks0bY/ZqoUfBCiaRvSxT/HzKz6piIofChKazFA+yWLDYa5qca3YZE8hjletoNereMuL7QoJRYV8gaotGC216MynSPqCSFOlPxfnqhfguasyo2HbhzRmaGgEvLNg8ukdPYTFCbZmNMZXTIoNm+6RYUZrDooksbRSZfOmLl6+0m4rkiQwHZ+4LoPvs6OQoGI6vHalyp6+NL4RRfQOohIQIvCFIAjh2orJ4W7jQ6+fHKHyvXNLLDfstceuLTeYXGnyxT095LV7Wy8JIfCDgMF8gh+eX6DptN8fVWX+YEcnU4sTaLJor4dbJoFjU7fguNXBpxIB1om3MFpNlEOP3tXaVAo8ntrUwXfPLawFc6E9B356aycpNSC8cg1/ce7WmUUYYJ86hrR1J2qzjhdN3NN3/WVyRtvHqmLe6mXUEdfJ6uJOBTLrrLPOOuus82vlvgVgvva1r/E//sf/4OjRo3R0dNyvj/2dRPZcHu5QaC46yJbFplyEQiZGiCCuK9RqdVamZwmqFWyvg4cKEd4q+7w41WK25vC1/b1s60owX7NQBFSbTcJKic9v7+Llc1M0mhbE4ihC8NV9fZyfXuHzu7r531+5RhBCy/VRZQlJEvRmokwUm6vG3m0Das1oL2r8IESSBLoiQaOKJEmgqhxrRShHIrz85hSFVITdG3uYsmtomooR0bFVg9nlBkgS3zkzx3Nb8jjVCv+mz8crFfF7O/hJPcrbEyU25hPEH3waIzdM3LXwrl6iNj62tsGcHN7AVUtm78OfIpVOE5gNfM9HMqI0pycwR0+gFXqZ/85fc/Tpz3JuIcqTQ3GCGwIHKiA7FqEs46r62uQ7rYZ8oV/lHauD8cUKYQgDnUkOdRrkl8egouG8+ypeow6yjDawgeiBo5iR+MfaHiLVEuaL38I1bVaKDSKaQmZqnCc37iTZt4cFK2BXd4qNWYMguL3x5r3i+z76tl2IscuE9s3ZUEI3ULbtxlkPvnxotGYN8/xJAKR0lrGND3BmyeadxRZL1Rb5TBxZkohrHpbtULNcntjSRWdcJ+qYSL7LXN1hfr6Ipmto6QzdvQk25+NMlVu0LIFCQM5QeHYkjXLqDYTvkdh/mKmJOUIRYVOzxLUf/oAwDJBUjYarMnryLKm+Xlok6EkZ1C2PasvlzFyV39/Xw2BUMOiucM1sMZSNkmgUkXqH+OtjE/zBQxvxaQ9KXhBieT4Cgel6JNJ5jk3XOL9Q5Yu7uumwswxPn+Zacg96vJPq2GkWFJmebIGoCMilHcxAIvLI0/ygorCyOEfLUNmUVFCMKHOOIAhCLC9gMGNwqDfOW/UqtaaLZFtIwM7hLlJKSLVap+m1F9hRTabp+Liez4lFk+0jGRbrFkd2dZHSoGp5dCYM8skIrh8iS4KELnNsfAXP8wkkjV/OyxtbqFDbNcS6GsL9wxcSle6NOGdHWYvGr67Gl+o2ka07mfHadyQd0zk+U2Pv4HbSsxMoGzbA5l3MmT6KJDDjGRTZobUwR21ukaimUJ1bJlGc5sj+hxibD/GsFrt3buSleYuKL5POZ6nWW2hC4MsqNhL5qMZstcWnt3cRCxw+OxzHkCV0fAKzidcywffQojGWzRKKGkGWJaIRnVAIMhGFqVKDBwdSjHTEODldQRaCeERhbKWJJksMZmNULZeG5fB0QWEpUcALQnriKj1BncjZ1wl9D29lmYjdwokkMX1BsWEjyTK+d4/BAUnm3ZkGJ6ev+6HZDZsXLy7w4HCOAwWD8C7KPdTAxz597PZPBgHupbNUDvdwcf5mWR3b88nFNJbrNh3xWyMwA5lfkcEuKVQdsPyAqCqTVMPrlawfkpwW8IXd3bw5UWKu0gLaxtcPDmXIqsGH9pf5bUGSJKxQxgtAk0Dl3qqdmoHCd8/O03SuX2fT8Xj5yjKK3MW2rMKX9/Rwrezw2liR07M1xlZa7OlNsbsnxQ/PL7RlIR0fXZd5aGs3Y3MrXJhfopYWfKEgiC9dZqlaYml+nv7YMpUzJ3n6qWepb97LtXKj7RUoQYAgDEKCIKTRcliMxGh0FjhRV5iuNGg6Gu7IEbZu3I6yNEtUFsR2bMK+dIZWw8RvNojLgorlIgcB7d+YkI5kBKlZw8hksRcXkFy3Xb0jQhpuSN+O7SwObmF5scH+7gQHcwrnR5tcWrQZ7Ezy4GCcjvMv07P9EMedBDFVIEdD7JTG4cEsqXOvY516h6BlIufyxDbtJqGp1J1b225Ck+nLRJhYavcdyXPxqmUEcGQwi3z+LKxKB4VWi3BhFjG85bc++BAEATs6I5SaSS4t1AiBAAmE4OGNHSR0GYngjv0/JgVsLSQ4NV257fM7Com2DNMnkCAI2JiLcnK6ctsA0+GhDErofeD+dFaHDfkYE8UmD3coJC+9Q/3qZVquS2uwh86jj6JZLtrkHHa2C6d7mBnF4OktFpbvc3WpzlBfju+em2e53l4jhFaLSG0ZLXCoTlwjrcts6M6gaSpLXgtXyPiBYFdvhp+NFpnLDeGducBALkHD8WhZDsJqkUlF6N68iVlP5a2JEgoh+ySbluXg++1EPMdx0BUBYchSqUY28Hl6S56XRpfxw3ayTRjCrr4U+ZhKvdagP6HQaa7whQ6XFSfkwkKDUsNCTqYJDYNqy0WI20T67wIhBFMV56bgy/t4QchbEyU+vy23VrF6NwRBQC4R5c+OXcF0rt/nrqTBmws2nmYQCZ124pFjv38iTDoqVQJ0wLp8nvjW3Xh3KQuWVX2+treb2ZrDYt0maSgMpg1SatCuhJ0e506DnLs4S3TvoZsSFj8sGh6f3tbJDy8sUm1drzjNRDWe29qJHH5y/ZvWWWedddb5ZHPfAjAXLlwgGo3yr//1v2bXrl3kcrn2hvsNCCH4oz/6o/t1Sn8n0UIfTr5NeP40z27YytLmx3lrbp4Xz84hawoxVeJgp8FwJsq1UpGeng6+d3Ga5eosT+zeRl3SqZguhZTOE5vzSIDk2Mjn30VNZTj45EZqnsAMwPHh9YszLLkSoazwuV3dLNdtluo2cV3h8U15JkvNNS8JafXfpKYgSxKOHxDVZHzLIgwCcpkEtqQxU2wiPJdKo0VnLsXYcoOrxSYj+Q7CMGS62FitExdtI03FR7/0OvOz1zBW5ghcn88+8TS7Hvg8/+3ENAMJldZUnUalxs7B7WzPFyi+8zpaLEr04FEuT81TyEgkjRSZ7n5Kb72OXRojKBfRunqoaAkcx0U59jqxx76IEwgUQBagL81hn34Xp7SCpBtoW3chRrZiKRqEIcnTr/FkGNAa7idEEC2Nw6UaSraDxovfRhneBLICvo8zfgW/VCTyma/i6u1J/Edd4KmAfex1AquFLkskIxrVlkPL8YleOs1TW7bzshrB9VySSvCxZfoCtOJpYp/+Ms7pd3FnJtvn0zeItucQrXjqY5lk/87SrK/J8Jg7jvCL6SYnxouEqgqSxnTZZKpi8entBfb3pehPqeTrCxyZO87cmTPQMukbGsHfuo+fzbRwSkUObs3h6Sr/9OggpYZDSvbJmSXK7/6CUrVM//Nfplgs07x0mb7du3BOvt3OsPMCYj15TpZbBGGIt7JMR2eUhbqFpsj0pw0yOOz0iyz/+TfxsgY7fIX9+x5gItfNzyZKeH7AZNli56G9JIQHQUCraXJtZhmSWTq785yaKbNQs1motdgXlmgU+vjrty7zpb27UCcnsGs1ZktNJCOCEssyvHWIY3WVaKLdqC3bxQ9l+oIGA33tDbzOpEFEETw/kmSnanKm2taO39YZYzgu+P6p6XaGox8SALIUktAVWq7PctMhiCV4eETi6FAGEbps70nz7lSFb52ZWzMj3deXQjM0olED2btVmsEPQ4j+9mcU/12i5oSMRbvIdPdgzs/d9JwSj1Md3gUliZiuYLo+DdvjGzOC/8cLXyO0HSrvvY06M8HmeByjb5ByxwDzhc10m3XMuTk0SYDr4px4mx1DhxidXsaPJJgtmtRCGdeyyOczNFcl9zIxjYblUTNtCpLL+YkpXh2bIy35bNjQj9rRiRRL4MxMEOoR7IZJVNNIpeNs7U4hZInz8zVsL0CWZfYWYpydKTGYjTC63JYf7UlFmK20SBgqFdMjfvYUkdIyqXiEXiNA9a5XhololKoU5fySTcP28edMNHz29SSIirvfuKi6gtMz5ds+d3yqxKaOXhJ3oUIpuQ5+s37H5/1qmZWGc8uG4Vy5ydHhHN87N4/t+au52oCAbFSnP20Q+rdueAGYocrLV0pMrbQTSGRJsLkzwdGhFPpH2LwJgoAODT63LYfptYN/MTmEwPvEB19coXJ+0eTMbBXT8UhGNA4OZNiYVteMlT8IIQSTZfum4MuNHJssMZzuwvZD3vv/s/dfwXacZ5ou+PxpVy5vt/cb2PAgLL0RSVGUKFtUqVSnbXWf6e7TMT0xfWLMRc9FX52Lmau+6IhzZqbn1LQ506XqqpKXShJJ0RMECMKbDWxge7f28jb9PxcLAAEClCjHYqnwRjACXJk7178y83ff+33vu7AFIfQlTLqux7H5MgNJi3/y0Divz5XIxzQmczHmVko8N5XCTA4R31jE/PZPset1hkdGmH5oH41rV2lnM+S7VYzyAmfaMbxOu+cR6Xu4oezNc1LSdAMiQ2O88eYaCIVi0+aEIjiFweGJo2zPRKgmFWLue7TrdRTHJqaopLMxhAyRXZWYrpAMurBcYkWJMdI/gKaqtDtdNNMkMjxK97k/4k/fmGex2mW77hBUy+zZOc4//sxOmmdPkT93HtJ5FLtDOpZmsdqlvNZk92CKaHmNzluvcFO/MihuoH33P3HkhX/Ozzf8u7K+s5bKg2NpZOAzX2qDG5BNWjwykWN0+QzSdUD7wLMzrJYQUzs/9QQMgBZ6fGYyyYHhJMtNj3LbQ0FyZqXGsYWARydz7C2Y4PcSj3r+USqllkOIwsHhBGs1m2Lzznn76ESG/qj4hetlRVFQFIUw/GiS528SSdXnK/sGeG2uzOYNyaiYqfHwRI6JpPpLiXEl9HlmOstmSiP46bdprK1iqCrZZIRUt0Hj539Nc/dDlA88wUrD49TVGrYXUrd9HD/k6w8M8e5CmfV6F8vQ6I8biEqRtGliKD6x/dP0leaxz7xK4LgURieY2X0IbUeW/++xebpSpdCXZ2p4nLWVRXKWylDWQjZdFE1DHHyYby0GHBmI0RfT0Qa2012eR2tcQg192psb7Np7hNll2Kq22CWg6/r8vSOjbDQdNCHIxww26x1Sgc1w2EK5cILy/AK66qM4Ho/sP8T11Cjnl+ZR01mGtvXd9ayFEARCpRsIFNEj9sJ73FtVVblSrH/k/V6rden4guivUJSqqiqBK4kb2h0EjBCw0fEJ88OkgiaUNxGKirCiqPkCnmMTBjfCQ2GAbDbgYxIwUkosPLanFHZkev5sUvq94UhRIGIh4gm4x3yumBEU0yK0fvP1sJSSrB7wjQcGKHUCWq5PwtTIWwr6ffLlPu7jPu7jPv4G8YkRMD/5yU9u/fv999//yPPuEzC/GdSNFdoXTgPgWAl+9tpJuiTQum00JcbO4TyRiIqSTvBAX55sIUmu1EZmdX5+cY22HmUsHyce0Xjrepnlaofnd/STGJnh5XcvUX57gXRfnl37dpCLm0wOF9imaVQ6Lj8+v0EhbpCyDK6XWjwymePCep2+RIT1ho3rB4Dkc7v6KbdtRjMWtY6LKST5TAxLh3XbZyQTZa1SI0TgS9BUBSklNcfH0tXexlIIhKqSMhSizRKlM6cwdIWxRApna5O6sHjtjfdxjQKd0CA+NoGIV7m0WSI2NcyOZz+HHBxjwwEj9AmuXUMbHQbHJkKIWcjB4Yco1jtszF4loil0SlsMChtVCBShYCxdo/HqTwjDHrmE69A9/gbG5hrWU18AwyAo9OFdPItZKgK9/VpkaobusVd70i+3kZDCMGiN7+bSeodrtk1UV9k1EKfPEii/pii81mnSXr9hFilDBhMGmiKodVzark/k2iyT+x5jd8GC8Le7KJVS0kmk0Z54HsvuSR34kSgdKe+TL78hhPrB0F2K5Tk1P9v73POIKAFmNEGoKJxZqfL09hzDQZvyd/4MtdokIgNKPlQuX0G7vsCjX3iRotpH7sLbKNUSmQOPc8kaoOmrnCtBYefD1AKVSF8E8+K3ie9+AHf7XhbjeSIHTNTiCqK8iXJDVMDzfOLCR8FAhgEp38VeXcSxsgxYCordwd6s4RU32PcP/xnfumD3KkWiJk1UTqw3aXQ8NGHy4OGDJC2d0ys1Nhq9QOlmqUG2tMR6boYgCPnhpSKfe+pL5LcWcRevgaYT7jvKxuQM3Uqb4uoGz+0eRPguD8Uc3KuXCOpXOTK9k9Hduzg+X6ZSb/Ow4fD17hy0mgQNg9b2w8hkGhktowUdvCDE9UM8IYkaKgOjw2SyaQzXJ5RwoeKy2vD5+dUSuiJQb/jYXCm2ODiapVDIIpZm73qWo9smMKMRwuD+pvC3iZu+I3W3R3IljJ6PRBiGBBLeK/scefB5+kqL+HMXkEGAPjZNe3wH77RNDMVjOBXhwkYLIQTFjoenRaj/8Dtk3Qam7EBxC0qLJLN9pJ78Mp6xD61SxNIU1iotTFFn6oBBN+zn3HoDxws5MDPMy8UalZpN1wuQQLnt0m8pHBlOcfLsHCvL6+SjOq6V5bqMcmCqj1fmSqS27YIwJK9EQNM4Mpbhv763BAgOjKSpd102Gl3eWwn4zPZ+fnxxA0NVGEhGsP0ARRE8u6PAy1eK/JOZfXR/9j10t0s5ZjAY13qJEvEkGw++wLfeL3K12EII2N6f5OBwip9eLfGFmTwmH+9dLXd6feNe8AJJ3Q5IRO99/HaEmo4ajeM79/ZkUBJJ1Hv4iXXcgLbt8JV9g2y0PNodHylU+pMRpnMxXpursHswwUD0zjk2EBo/vrR1KzAJEISSSxsNfCl5flsaN+iRtboiMcWvHmQVgU/sZjDt0xef/ZURKipvXK9zeeODKqRax+Wly5u0p3Ic7jd/6T1SVZXl2kcTbfWuh4/G8cUtPD9EVwSNrkvb8cnEI1zebDCZjdKX0DFCn9OnLvHIQISh6/NEFi+hdpo0NtcJwhD7+lXC+VnSn/k8mVSO0ve+BX/wT8ml+8FsEaoqqgwwXAfXD1F1nVg6SRhN4HgBQoKuCHQheG73MK9f2WC+qHKiW2PcGGcsnuT53RbfOb1CvW0zmE1gOU1MPcbnDk0izp9g01fpKAke+OKXKOtJ1JmjVNN5fnihxFzVJm0ZyGoRz3F4//QVgsk+dnoezsHHeXWxybU35rAHfTKpBI9M5JhfXOMnrSpf2HUAcfG2fZZrs2P1DOG2Rzi+0qDrBiiiV3n15HSOlHB4flua1kQGxXPRTi6hXXitR758CEoq87eCfLkJEfoIoXHi+hZOKCl3AkotFz8MObfW5B89NMb+vghSwvn1NhfXG+hmlbgWcnQsw9f29rPWdFmsdsjFTDIxk5bjsVAPKMR0klp4B1khhMBq1ggW5whKRbRMHm1yG3Yye0Ny8tMBKSUFI+QP9uR7c2QoSVkqbgCLDRcvkORiOhmjdw/vBUN67JA1akEDOxfH8QI0tbdvMwQ4cxep53bw1rUaS7UO/UkLkGQtjROLFZ6ZKTCZtWg5Pt2OS3OxRCyXZkdCp3XuFOWLF3sVH0LQmpslXd1kaCjHWtOl5oZsNjW+uudJdk5vIK9fpCJ9cnuPUBzczpya5Av7Ivzw3BrvnN3kUjHORHoH+5+eJP7WK3SabbTlaxyYGuVc2eXlq2We2l7g3fkKLdenEDcoN1p8fs8QQ7JL+JMfUC9ViKoCGQQEtk3t+NtMPfgo6+kC7W6TKcNDyg/W5kJRWG3DOwsltpo2qqKwrRDnwbEUsXskMqjKR7MrykdIZd4LKmDWSvjXZkmV6/yTZB9r/cN8e8Wl5QSUWw4Hx7L8/EqXdL6feCxOUK/2ql8bDSb600Rrqx9wtdqvHiqSUt7lGeP7PtbMXoLrswgzAn7rjuPGjr2I0UlcVfut7BGllBh4DFmAdcNz6L6x4n3cx33cx338DeMTI2C+9a1vfVJf9XcWmqLgXjwDgNB01tQkjdoKuaQK6Sj7p/p5b6XBy8UGpqGxrz/G8eUGhyYHeP/YVRpdl8HRLOfXG8wWWzw7U+D5nf2sNRzevNpkLJ3HEDpbSpRzp1YZysQopCxOLpf55qERpvMxrhRb1LoeCVPl2kadz+7op+X6HFXSGJpC3NAot10OjmTYaLq0HY+cpkO1jB3J4TV9xnJxLqzVUIwIxWqLnaN5NFWlZXskIkZPs13TEVKyLaki5i/0jJADCYqKiFisRzK0lor0TebQVYFEECkUkKksF5FsO7SH2atL9GFzJO4RLczQOneS+vXLKPUKHTfAP3WK5L6D9G3fxsbsVWKGSiFhokgf1fdZf/MNNkttvCBEVxXy8QhpU8G7dA4l28fmyhqDkxOY23bjXJ+9ZQitaBphrYrWP0SoqL2FplBo7Hucb1+uYC9dQ/YPI2Uv4HN4LMODw7G7NkGKqvUIKsFH6sYrUqK6NngeQlVQDZPBuEY+qhNISCV1JoZjuM69s4B/G/ClxL9R0XOfePntIEhlUNM5SCTZCjRSuTSEIZ12B9frSSwoSs9vqONJ1i9forbVwA8lQkoKcYOOG6JrCv2rl6gnxrmuZRlYOsnVuTX6nv086ZkD/OUpFykEqgjoagYvvPiP+cnxWdpnVmF1ERmJokajPL3rMNul4Ow8uH5IytBIKyoKEm9rnemBLLnaGqm4jt3oye74rou8eoFt/ZM8unuMn82VuLDRRtcUUpZO2tI5vlzj0cksyzekeqAXq6w7Pp7nk44ahFLy0oVVkvE4AzNP4CoqF7pp9lV8pBNSLjd4aijFjq2rzL9zGs8LiUd0ws1lLp56j+1f+0OO2wY/nKvx5ckJcixzPjbK9UvrpIbHmM8MYulV/HIVwpB4zEJm8kRzOf4fL11hx0CCk4saRycyvDq7yWAqwlq9CyFENQXbD0lGNOKWgToyTlAuIl0HoemYhT4e2j95n3z5FSAUjboHbS/E1BQyZi+YfTsURWHdFrx6ZYtyuze2xQyNhyaz7MjoxDSImzrHyx6WOcbw0SlUQjYdQW3L5YmZBMeubaIAlq6gKjrZaBRl7iIFr4FcW6Tl9LKmdRnA1iZD4xPU9z6KkTC4uFrDCUIUK4IZjaN1uthtHyeUDMR1CoUsV0s9Uk9VBDFN0JeIsLsQ5X999RhmNAqZQVxFZ23L5mzxGk/uGmIsF6fZcQiEguc4vDtfotztVegsVDo8s6OPqVyUY9e2GE7b/NHhUV67WqLl+oAgZmocX6jgBiFXjRwPPv4EnVMnaNk+QUxHASoHn+a/XGkz3+i9k1LCtVKnp0O/f5ClustMWvlYQdhfFFCCm0GlX34dT9Uw9x7Ef+Nn9zgqMHbuoxBV0RSB/yHGZ7NhE4SSP3lois16h6tbTdZrHY5dKyKBK8Umh0Z7c+zNKo2SLe8gX+5oix9ypuRxbrlC0/aIGhoHRtLsykfQ/g5n1lYdmN1o3PPYyaUqM/lhYuIXB7+k7FUYfhR0VeCGkrUb3hVS9sjwluNTa9sMJSOU2y4zuSiiuMZDIwbW9XNY/WkaxS0IQwLfxw17ptO256FfvUh0516SyTjl/ADlusuO/iTvLfa8uuKxGMJScCQ8ON3Pz86t8ocHh3n1aolys8uj2wv84MIGhaiGVt/CCTyWihUuhzEeG47xpd191I0kgaKSssZRum1+fnyWQCR4+PNfI6oK/n+dJHVPIkPJLi2g0vUQinJHz1CQXFoq8uAXn+Y7b5xnq9FBqiqOL7mw2aRYha9uG+D0zy5TPbSH7E0CRlEQ8STy2iUe2HOQwt5hAimJ6YKkGkLo9ZZlNwhBNaKiiADnHuSLMAzEwMjfKgJGVVUurbVwAslWx6fY/OB3hVLy0uUiKXOI82t1NuodEAph4LLheixXbb66f4DxOIwmUxxbbvD61eItUllTBI9O59mbNyAMUBQFc32J9is/Qvo3xoKl63D+JLGnPo89MvmpundSShTpk9FAKCpXqg6vXtnCu+FPJYAdA0memEjds2pACIFTLLJc6dLxPpiDVSEYSVtEtk1xenELiYalq9Q6Lvmoxla9w4ZQyMQMLm80SJkaT0xmuHRd78n/rS+RWp4lkY/TcgMUJDFDQw06bL7+cx7c9hwvL3ew/YBvz3eYyg0wvWeMWqvL9ECevzqzxpf2JPjzk9dIWTq6qrBY7UI6yspal688+Rz2D75Nff46R56foW/XLi6WupSbNl/bmSEei9KwPVaaLn91aoUXo1XspQ36khFyEQPflnQ6NmEY0jz7Poe++E3SOsTPvU34xOcIgp632Eobvn9u7db7EgYhlzYarNW7fH3/AJHbEhl832dXf4JrW60P32YAxnMx4prkl+XiqQL02XO03n0DkIQ+1M9dIB2N8c+f+xo/KltIIB/VGEiYCAGhbvQqTIMAXVN5cDiGfH8ZYRhEJmfQhMDaXIF4Ai+e/o28Sv3CAPq+IwhVI9xc6/mEhiHGxDSRp56nk+3/VPWR+7iP+7iP+7iP3zY+MQLmPn73EGFAaPcClYoVZbPdCxCJRpUD41ZPpqDtkohoqIGPcGw6WoT//O4iz2wf5J2r69Rtn0I8Qtfz+cH5DXb1J/jL06tEdIVKKoXan6RUafPgdI5YRGcgGaEvEWGzafPMTIHNps1AIkK943I5CBlJS66XOyDBC0NUIZDAYqXNl/YOcmaliu14rDZjzGQsHhiP8WfvztOyfXRNRRc6lUaHz+zs583rZQxDA03vyXtZOs+MJ/D+8gICsEydsNtBicYptT2kDLHwMYRESNCcDnoQ4KoGSV3w3OFp8H1evbLJ9PJZVq+usSMaRw3KaEovW6Z1/hT5L0yyIhT6x0eIZdP4QqG4UWJldfPmnafjhcyXWvQZkmh1g+TsRZy2w/nZWcZyCeK79mFfPH3jdAU119fLrr+x0BQDI7y1btPu2Ki5BPK2rffJpSpTuSgFo/f/UlFZa0tOr1Zo2j7ZmMGB4RR9Ebh9dW4GHqwvIzstgs313vcYJtrgCNKMoAmIT2+j6v52fF/u45ODq+rYn/06r703i1vvsFDtogpBIRknqSo0PEk2ZrJSs2l2bFqzF7m61WI4bbFc66KFARFDo9Py8C7Pou/Lc2y9xtdm9qKcn6X41utkhifZM5Tk4nqDlGUwkrL488sVloM4o6kYeqtJp+sgmx1ev67w9QcGObp9kMvLJRqOT0YTxKMmSkPw5GiMyLl1hKoQUSTxaIRKs0Pt2jVeePEJLlY9Tq3UUVUV4Qc0bVitddleiPPKlSKPTuX4zpmeVNRyR6L2D5OxDKQUdF0PISXlpk2p1kbNFahHQzzPZ7PSZjRpMC2bzJ84iW93URVBw3OoCRO/3MF4/yS7HnqK1yp9rOg6/r5pnKZHMi3JxU2ezKZ5Zz6BkSqgCah5kEpEWW+5TORjFBs212yPyUIMOwixvYCBRARFESRMjagmWK00eHJbP41unCuJntH2YCbGkbEMeSP4jXhJRVEwnC5Ko4oMQkimcKKJT6XsyW8KV+i8tVDnymaTIOzptA+kLD47kyehfBDMqPoq3z+3iut/cA/ans9rF9eI78yzQ23z6HiKv75SousGzN0mz5GJGWzPmbhuhveWa8TNXoXneFQQW5nHLq4TeLcFoxQV6QU0T7xN7sBDLDZtxrJRFmo2haeepdw3Ri7l8sUZjWary5X1Gs/uHCC7UufyZhNdwMNTWXZlDFprawQIZK6PcsenDbQcH6Tkx2eWefHwOCOpCK9cKbJS64JuYvsftH2u2OLgUBLo9R/bcdmes2i5ASeW6xxfKDORjfLoVI6Nhs2x3G72fmM/2XaJSG0ZfXonP69ZLDSKd9172wu4utVGwWJXLv6x5DFzUQ1dVW4F9G6HZahkIr/E6fkGpJSE49NEahXsC6dQkmlaYzupazH0Qj9+Lk9SlTy5vcDPZ4t3BK41RfDIVI5s1OC7pxZZqd5tPP3+cpXp/AdzbN2+N5GSi5s0XMmPL2wQv7F6btoeb8xtUe2keHI8AR+RLf77jq17SMDdhOuH1O2A2C+xRwiCgJlCnNPLtXtea3tfAlORHxB3ElIRjVLLJZSSWsdlOKZxVOnQufAKpVKNUFchqbNWt8nGDExFQb3t6na5TBRoPPQcP3jnMiN7d2Gbgud3D3BqpUrT8RnrS/HUtgLVrsd7mx2GuiFf3DNANh7h/HqDsWwUXBffD9CTSXbuGkfqJo5hoAooKIJ3Fqpc3mygaDq7CiO0HY//uBzy6Ew/K9Umm02H7flYr5paSixNpeUEiFQG0exVBWmRGBtdie04eH5AJJ2hQ8/LpO4L5uoe+UKWRqiSBYRuoA0O09UirFZt5EaDn1S7KAK29SV4YjL9gSzfzWcQhhiHHkXaXdzl+VufK1YU68nnceKpj/RwMGSIVq8gOy2EESHI5HA14280oCqFwnrdwZOCUvvutW6t61K1fRaqXUCw3ujihgLf9zE0hZ/NlvnHhwe4Uu5y6kN+MH4oeePqFvnYMAMmGE6X7psvfUC+3EQQ0HnrZaJf/e/omh+j5O9vACVH8PLlzTsqFiVweaNBNqpz6B4VbELVKPnKHeQL9CpOl2tdhqNJvI4EBKbWI8g3ax1ajo9lmWw2HDQB59bqCEVwdMcUgemjN5boRBOEnkfKUDBbVcJqi46Vwq5W2GkFvKkphKHEDULabsAbSw3abkChEDCSjnCl2KTScdFVheG0RaXeZr1YI5bKcFaPceAf/FPWPZ3vtxQaizWe3t7H0sIar758mieO7uL9lso7i1WSmiTsFmk7Puv1LiYRkgpsy/V8/oSAnN6le/YEYSZ3y1w+ECrHFkr3rACtdz0Waw47M+odnw/FVaYKMa7fkA29iaih8vB4+iMT7W6H2ajSOv4mNxMbLE3BVFWcThvjxGvsPPQ8V2suVzfq/NGhESptmysbTcyRMfr8BkcHohQuv4vUDWLTO3CvX6E+e753cVXF3LYL8/CjOOqv51roCQX94EMkd+9HXjyHYrfRRiaQgyO09Mh98uU+7uM+7uM+fu/xiRMwV65c4cKFC9TrdZ5//nkGBwdxHIfV1VWGhoaIRCKfdJN+bxCqGlr/EH6lROi5xI0PFnfpTIqXLpTQIxZhu9OzUAkU0CN0vADVMCjkkpQ9Qa3rUet6KAK8UFLretCFhKljaILP7h7i9WslNpoOAwmTUsuhLxHhjw6O8PePjvLalSI+grrt82x/EhD89aUNghvKU6oi+McPjhGGPl/d3UfFDriYshDNKvgmTdtDURWkohKqGotzC0yP9PEvH5tiudpBQzIQN5hJKMRLqzTtGxrCCZPu8gZKxCIV0dAMA03XUWWILK7jNWoo0RiWaZLeEmQSEf58U0XYDuUL55FSUgw0+mNJRKtOwtTxwxB9cZa9e7aTevARAiGoeYJy+4MNlhdK2q5PjIDNUovJTJquVOhoFtGswkK5yjYvJPGFr/dMUQt96N0OztL1W9do9Y2xeL4MgBJP3rVonyu1GRiNEUo4U3R461rp1rFK2+X6Votnd/azI60ShiGKoiDPvk/r0jmihx6h9ZPvQBgiXQdvdRFtfBoxMII+MgHtLp8kFEXB6LYRrgO6gRuNE/wtCxbf1PeG39yn59eBg8Z3r1eoE2eXZZCK9QxAN1o+A2mLpCWodDzSVu/9r7u9aoGOGxAEEkVTsV0f6QdoUoAZod5o4eyaJAwv49TrNDY2+ez2aRR6mZDxiM58qY0Ugo5mEcn0o3pr2F2bzVKVjWqCXc0lJh9/iNc2XFI6jA5m2ZZq037rFTQloC9uUNfi9CVcVFXBt6JousFKrYJ6Q/Il8Hz8UCNuGqw3uiQjOhFV5eBImprts9W0CXftIXPtAsN9aS6vlgGJFgYIRYF4mofHspRKNSbycZ7Lx7HOvYMS+oShxHY8lHgC3+t1subF8wwefJCx/hRBzOL7V2u8cb2E7YVIYFs+xtf2D9HoOKiqCkjqXY+1epeYJli9EazdbDikLJ2249Po3tCUl5JUQscPJI7r8sRojEODMaQUWFrP0Ps3Il+EwFxdoPvOq4Q3NLWFYRB54EHCHfvwhfpLrvC3B0LVeGu+fofRugTW611+cGGTr+/vx5AeiqJwZaN1B/kikCj1Kn6pyNu1NQYSDSbDgC/ufIy3ii61joumCLb1JXhoLE0kdDgyaLG9EGW9FTBX7jBgQmQ1pNXtIKVEyN44iwChKiiqilot0ZQqWc9h+itf5WU/z6Xz6wghiGuCdqPJ07uHOLlYoeWFHBxJs28gzmqlxXuzy3wmr6CZEequxLQirJU7KEL0vk8INEUwV26zUW0z3p9hreGQsgyCMCRtGQRBQLXzQZDx+laLJ0eivHK9wVjaxAtCsnGT//b+ChFdJaIJ3qDnU/QPHnoOJfRZWir2Ovw93sulaofDI8mPHSRJqAFPbMvfRYooAp7cViCmBh/b98QVKtqBh4nsOsCposPxhRKuYhC0ukRX13hye4FdOZPcwWEubDSpdjz6kya7+uLkTUmp7bJ6D/LlJq6VO/QPW4RhSFS/99J4IBXlO+fWGU33pHRux8X1OvuGEmR+f7rcrwTtHhJwt+OXVUPdRM4MeWJ7gTfntu5YB/UlTB4aSxFVAqYLcS7eGAcMRTKejbJa7+K7PjtTGo2Lp9G7bbIxg01XIbASuF5Aqe0yke8n2NpACIFAEgYBSizOopug3dpg/uwFdh/ez2Y34OmpLFHLpJCJ43gh/9uFDaSUqKrCy1e2ODya5mqxScP2sf2Q/twge8ezvHp1nXKjiBlPkIpo5BMRxgpJ5io2McvgZNFmJG3hKT7vzJd5YDhNue3y4ESWiK6y2XSw9B5N5EZimPEYgW0jLAvH7fkpqJqGl8hSargkIzpdL2CxGfDQyBBWXKKPTSKNCK6qsVTuoqSzLBMFPEIJVzZ788Vz0ynkhwK7XcNEf+rzxOsVZLNONJ1GROI4pvWRxL7ldHDf+Cn2+uoHzzyZxnr6Bbqp7N9YYFXIkISl4VW7hPeIho9mosyXO7ghrNU6BKFE03oVG4qA95aqfGnvIKeW7+3PIYGzq3WGt6cQWxXCTvve5zk2VMsw8OkjYFRV5fJq6yPlIs+s1tlVGMT8EFledyVb0Xyvqv9D6+BQSoSqkEnHCR2J7QdYusqK7SE0jY7j058w2ai3EcDljSbPPz5OJ3BZX7GobzWRngsCUokkQ4MZQjfEMA3sQNK0fSQ9ArbrBdS7Hg9NZFmvdxhIWpxfq5O0DGKmhqUKtE6TruMiPZdSOoIz1MfVtRZTuQgDiQhvzpdZrgaMDg7jKSqVtsNk2sTxQqx4hsDsDexr9Q5qwiAaeliVYq/UvFVHei7a+DTejfe8GwiKH1FFCb093Z585g6ZLk36PDudZXshzrm1Bl4gmcxF2VGIkVR/+VpRCEGwunyHzJZKyFjWYrVu015fZVzpcl3RmOlPMJXS2J22ODwYAzFIym4hr10kKAxgTUzReeMlvNufaxDgzJ4nYpiohx+7S2Ls48IXKsbkdsJYikBK7JvXubHO6a2ze4T8xxk3biYhCbsLmoYbS/6t21Pex33cx33cx98dfGIEjO/7/Lt/9+84ceLErc+OHDnC4OAgQgj+p//pf+KLX/wiL7744ifVpN87BEGAuWMv4uolpN1lPBLytqoQBCH+jSCrVFVENEZCCTHsJo6VxIyY1JwQW+hkoiobDQdBL3P0dt1Z2w/YP5zl51e3WKv3FpaKECQiOh3X5635El/e048x00c2EeG9xSo/vbyJAL55aJSm01tAWobCVsvh6GiKmBbyw8UKsytVzE6dLz0+yLO7Bzkxt4EMHDQfLEPDb9TZERgcpMzn9gzz5pVNap6CPTxAanQcpVEmFtrEklEC1yVm+hyLRtn0FPq6NqJRRUtlCcpFJgoxIj/8a0ozB6m2s0xPDePfkJPZ6vpo8Tz5WByvWSWqCoRh4B15go1UgUEZUrN9VrEYyRdol0p0XB9VKEi7QyjBsCyyu3YjTp8kHjXwxh6gVK6hHsoj870uFz36OH61TNDsbeoCetlcWmGAwLibhLS93mKy7iu8O1++63go4c1rJUYODmERYnRbdC+dQ7oOdnmL+AtfxznzHv7mKsKIENm+C/HgU6jJ9CdKwJiBB+dO0710FunYCMPA3L4bfd9RbN34xNrx60IIQTPUuLbZZb7SxtJV9g0lGYgqKJ9Q5rMQgnK9S/nqVcJ2k5XmFp+bHOen8w26QY+Q29GfpNzpyQheXKmyf3wnwcIiiiJAEYSyFwQFiExsY7ZDbyOpqETxMXVBJp/BC30e7jPBihIxdYbTFpauYBLSNXQigwNEaxV81yOwEiSmpjCEz7/Yk8DRI7y54aI0awTdDmrSwpew2Q1QhUY+rpN/9hlebnpkYiZZS8NUNbq2ggwDFOnRDQSfHU3xhFpif2eOUCgMHN1FMZrAmJjhs26XWCzCxcUtpKoRHRhgLJ+ktbaMdEIe3zFGpVSEcotGoJBIJMhGNJYbHjcz7wPfQwY+ubjFYtXmjevlHvnSS9xkodzmL95b5Bu7soSe4MSZy+iBjzU4TMeI3grDXik22D+codRy8ANJKCWBlCB6khxTuSi+7/cyjgXIX2/vegci9TKtn/+4p5N+A9J16Z54k1gsQTC+7Tf/kk8J6q64FTT8MKodl61OwLDV24yv1O4MfCidNv6NKsBqvY0zmME6f4yx0jqTL/wxdbMfVUBcCwmD3lwgw4CkArmcTkKY+MU1rNEJku+9TdOVSEUhkBBI0FWdzP4DeJvrRPJ5kg88wE9FP61Wk75Ok64XoiWSZDNJ3lptM5qx2FxvUem4ZCydP7+whG7ofG4kzshAlrOtAAswNEFE1+jaHrlMjIbjo+kajmbS9sKe1KAQDKeirFTbtxIcADTPJVotoi/N8dnhCbb6xikkLP70+FKvCvZG/48aKl034J35Cp+ZSmNpvTm90b27CsTUVIbTFkHw8aomZRiyM6uTPTjM2bUGtY5HLm6wbzBBweSeZsS/CIEQXPUivLZWA+MDo96OG/DTixv84cFhCkbAZ6eSvX4pJUHgE4Y9E/VfFMpx/bAnbwrkoyoxQ7vLDN4NetUXhiruktMMJVQ6HpnEr+CS/HuE/rh+Twk4gEREJxtRPt6gF4bszRmMJEdYrts4tstwoudRpCgBYRByZDTFcrVL0/YQCGK6YDIbYyyu8MBQAqsSZaVSQzd0YpqJHBzrPX8vYEM3GBqdINjaIJAhSr4fdXiSjStVMrk0h/stzCvvMqnrqKMTNPQ8P7nS4oUD42wrxPF9D8vrEGtWGFNMmlGY77q4UuHQSJqXZrfodn1URSekJ5l2ZatDuevx+PYC3zu3hueHXNn02DWYwtAU9g2lUBRBseXQFzeRoURRBVlLo9xo0t83gu622dmfpNtuQyaPaiW4WnNRhIrtBWiKQNNVrGyegrtEkEghPQ/bl3iqRuzhzzDXvPP+zxWbHB1NkboHaegJBS+dR2QKZAYHqayvIz8iqKkD3juv4t1GvgAEjRqdl79P5EvfxNbNXhu7HRACLxL9RIKkQRCwbzDJufV7Szvt6EtQ6bg0bZ8glExko8wMpKh2XMJQkosZdPyAtvfRba3bPiECPlz58mH8suN/Q1AUhfI9qoNuouv6+BLMDw1tbiB5v6PzxBPPUn/7VRRVxbdtZBiix2IYg0Ps8aKcWKgwmDR7FV2Kgh9KFGAwYXBZUzF1FUNVMCMm3z+7xZ+MbUOx3iVUFQSChlTRjTSJtEG8fwQ/kUGIdaSETNTA9gOipsZkLsqx+TKPTOVw/QQLlTaVlo3jqFjpFPEwoFaqYBCi2h0elkWUKyu0HY8vTE7T3DtIVyrENfAXW7iOS1SFMNePqQnCdhuhKlh6BCF7+zRjYhtevYpiRVHGt90iKAWgqQIvuPesY2r3Jqx16bEtqbAtnQd6iR7hTZnAXwIhRI/o+xAMETKRieAEYGUjDEz1kzJABj0yNqqA0WlB4CN27EVaMfyr5+8kX26DM3ue6M79dCO/GZn4YYLFEToLVYfZYh1FwJ7BJCMJDV1+9N5KDwPUq+exz77XIz9VDXNyO8ahhz+11Wb3cR/3cR/38XcbnxgB82d/9mecPHmSf/bP/hl79uzhX//rf33rmGEYPPzww5w4ceI+AfMbopvMEvvcV7DfeY3k9bM8t/coL88W0RJJQtWm5QRYukkma+HIFO1uT7ohHTM4uVojbuoI0dOK11VBy/EZTlus1rqkLJ2YobJWt7nJy6iKoOP6WLrKZqOLpihcWqsy2Z/iernNQqWD7YUs17q3gkWOH/LoZJarxQYDkxkadkBME0R0BWv2FC9ELI4+NMKZjTaaKjhcyDMSNmkuLlITCv1Gmaf2DPHn57f48bU6Lxz5DK3v/RkrjSZT/YOYERO1WeGZp57j/3Nmi7RtE40lCLY2GU2ZPDtoEBFTaBp8IdVFJBRqk6Ncv3gVFIXNbkgRk6n+CfSIhvrAI7zb1HlmoCdLpgrB1WbA5INPIn72A8Kuh6r0spQH01Eyk5N0X/8J6tVLuAKEppE79AiGDHBudLluLIn5wh/C+grB+jLpbIrC7jxlT9wzSDSRjRKGIaV2cM8AB0DXDajZAVYEhOPcMlANahXarQbG9E6sfYeQYUiQzhJasXte53cFTQjC99/BuXzu1mfSdbEvnMZot9CfeA6PX5xF+zeNqq/x7bNrdG+TLLq21eLgaIaHRqJ3GDn/rmB5DitX5glbvWB0udKgX1/lG9uHuNoWVF3JgZEUU/koJ65vkVV8+vqHiPcPY9lVein7AiHAyiZpT+2lfHmF4YlRgvUV4g8cRjvwED9Z82g2ljGKK6BpPPDIIVRFEJU+/vJ1VMejZPvEEjHMZJSRiWGyJ1/GOfEKtqrRyg6yc2IX/uA4/TOb1K5fp9bxMHWtJ0dx8Cjn9X7KVZfHM5I9+SZKu4FMx1nU0/xsxeGFbTGOXH8Lv7RBIZvGCSQrf3mayI7dXB4/RD1I8NThQQ4c2MlSsUal2mD92jXWy03+6HNH+em1CmHX48mBEbqLa7Q7ProLfYkIi5VeNnxqZAQllqBW6XJ2tcZtnDOGqqDJgGK9w1wtxsGBBKHrEXgO/uoi5sQMEV0lDCWq63C0oOMXA65XbWwzimHpGIrg2R19ZPTwLv9PVVXxpOgFw8M7N6OqqqIoCkEQ3DPrWFVV/CsX7iBfbodz5gT6yPhv9K59mtDxAoKPStEFKh2XkWhPFiMR0Vi/kbCsIAkrW7fOM00DzesFKWSnjXr6LdKPPUcQhvfUV1ddm8TJn3P9vdMELzxPdGiYcH2VrhuClKhCEBscpJHsIzI1g7/jEcJ8mtKPjuFtrBKEkqiuI+omoWmRHJtmz0CSI+NZlqtdNhtdEAIjFuWiF+WLD8QQi232JwViqwx2B3NqEDHQz797d4NndvThBpKuF5KOGsyX2iQiGlFDI2XpCCRq4KMVV3hwbJDw1AW8l75LrtBP+OSfMJPSqXi9zO2MpRM3VFRC5raaPDqRZt9Qio22R9cN7pIOe3w6R8aQ8KsMc2FAnwHPTycJESj0zHl/HS/cQKicXCrd81go4dxak89OJe5ZlZi2dNJRg1rn3oHGiWz0VkavJXw+v7ufH13cuGOst3SF0XQE5SMa35Mu/bspoZJQQ57cXuDVK8U7Mul1VfDMTAED/+PfGRnQLzwGypdw5y7jVytIXUfftR+x6wCqqfLNXVmurlW5sl5DmhY7pvvJ+B2KzS7Joe14yqs4rQ4R08eXkr6jD1E/9R5uIFmzJcnCMNFYjPAzL1A2E4yMmWxfukLzZ9/F9jyQEsWyMAaGefypLzMQ1/nHR4ZoF7eor1ZJxVRi107gJMaoN2rEC0MkzB4ZohoGHccjpSlsVZoYlsWZlQ57BpKMZqKsVHtSmLoquLbVYqXW4eRSlX1DSS5vNPijwyO8enWLrhtQyMTRIybJSIZto0kWqm0uLbpk0RFqiAwkXiiJ6Apf255mv9Yisu4jp3Yg4glCYaDpOV5t6rh3VSlA2w1J/RJpuF8GvVmltbJwz2Nhq4lSLxM1IrhnTtBdWwIExtgU5v4jdOOpO+Y9RVEIUBBCoMh7z32/KvoteGZ7gY2GcwepuncohYJkOh/n3cUaM31xoobOX5xeJbgx9iUtrefhFtFx3HsTKPmYgYJEJFOgqnCvygChIFKZ3/i3/C4QBAGDSfOe8ozQI1CNewxtltZ7Tm5ukJnPPAXlIko8iZ3OMy+SbBppDuR7Y+5csYU0NKyIgR8EfH7XAK/PblJr20znEqRNlaYbYPuSS7bBrr0HaMxdwQnBCSS1usukFaM5fYj+XIL/67MJTq3UqHc9ZvoT+KHklStFFKGQi5rYfsjb82U0RYAfYiMwFZVcf4FntuXgzb9m7czZnoenrqMvXaUws5PK1H6EsEj5bZTiBjHL4P2FBM9+5jmqL/0Ip9WCrorqNtHHpzD2H8FrN4l+/kW60fgtYj6uhUwXElz+CF+s3QO9eeom6a8oCs1AoW4HKEKQjoAlwl/p/Q/DEHVwGM6euOuYkCHReIxIIoZQ/VtcuOXa+KffpXN9FukHiHiC2ANH4BdU9kvXAdeG35CAuR1ddL57bpPKbUTgUqXDWDbK8zO5e3oQKYqCcukUnffe/uDDwMeZu0RQq2B+7qu/tlTafdzH7xqKomB/zO4t+buZ2HMf9/H7ik+MgHnrrbf43Oc+x2c/+1mazbuzWIeHhzl27Ngn1ZzfW0gp6eYH0V/4QyLtBnsVlf7du1ls+jw2HXJ5s4kfhGy1HZwApBTsHUojkBiKwNQUHD8gFzN4ZqbA98+t8fhUnpdmN9FuLBRNvWccP5GL4foBXS/EDSQjaQtVSP7w4DDzNYeHJ3Ks1u2eBrwf3NqUq0Kwoy/BRqNNyZGEEq5uNfnGuEn51b9GyBBfUfnMrl1MjvSxWTP53qV1SsUKoZRMT7m0hywazQ62bvHvFwRf+vzf55DlkOrU0EtrtBWTYbvM/+2JERoe2J5HtrbBSGMNee5dSuubVKVGQ4mgvX+C3Z9/HlFcp9h28QKJrghCFC63wNf72TmUIa6GhCHkLA0BvOYkefjzXycze55wc41UfIzhmW14V89jn30f6JXgY4Ny/n30x57GGZm69ZxsI4KY2I4ytQMVeDAT8OPzG3c901zMYDipI2WP6NmV0YkrkkjEQNhdbCm42lWpdr0PAh+6gdD0D7SofR93benWNa2Hn/rEPSKMZo3WlYv3POYuXCO+/wheKveJtulXgqLxxtXyHQG5mzh1w0Og73dcxCOEIFxbIvohM+PNzQrFYpX+0WFGCgUeGUvz2vUyD4zmqFerNDWL0r7PkBNVdixcptTsYk5sZys7wsmiiyEED45nKLctLtd8tua7vL9aJyYd+hMFhumQ8G2G4zrVmo1wXTQB6YiGY3dJ9+WIHfspYnWOSqChuC7u4jzJepnO01/l5fwBHhrbCVvrtBWDYHSC9Xievzi9wf95u8rin/8lkdC7YZAryadS/KOnv0i6tko+ohDdvQO5tohmO8R2bafpOeyRFdbNDO1mmzCaZMAIkYbC8FQfqckUxXKFi+fmUFSFI0/uIj47y1alge8FdNyAuKlih4Lc0YdZazuoqkLbDYhovWzMtNULFMgwxNJVHBSGs1Fi/QPYtgOdBkqnxWAyiaxXiNWqOMfnOdhpsW9kmrbwyE+NkEtZxJTgjuxhRVGoeAoXVlusVLs3sqCTTKQMNBFScuDicota12MoFWF7PkpGv3MzrkhJULrbq+MmglYd8/fI38nUlI9SxgIgbmpIKfF9n32DyQ+qZW5IL97EvpEMkbWTtziEoLyFGgYE99jgCCEQK0sE16/QcgPOvnWcQ1/6Jtr5M5jXLqMIgTI5Q0ONsnF9BXvkAR4YilIvbtJeWe7JhhEStFvQbqEmUijVEoFb4PhqlY4P3zg4wlAuQbHpUO24bBoG/2ykyfrPfkzH9gilxL1ymk48y4sHn+F0qckLu/t541qJrZbNVC5KXLoUghbPD2aJFWcZzGQYHhkn+PZ/ICxt3vgtCp2F68TXa2R37cePWMhQcrMSzAsldQ+k6HkXjSR0Qgk1T6IqCoeGsxwdjqNKj0aosdX28YKQfMwgY8pfSj7fJDd+E4raDQWNj/BnASi13Xs+R4BkROexqRw/Or9+1zs0kIowENdAegghMAKfSenw3+/NsOKbbLVsMlGDbMzg2mbjrsoY6JG1+agGfDqz3H/nkCG7sjr5g8Nc3GhR6XgMpkx2FGJktI8nJXMTmhCEJ9/Guek9AEgnwL50FksoWP1D+K/8kN2awdDEHuZ1lZ+/9DZKOk/JVzgwnufQv/i/EJ49jnP2JGuv/Izw8S+QHRolXlqh0+pg5wboTO+hle4nbdfZldc58+3jBKoBqgG6jotCOhrjgL2KcnyBdLtOy/Hp+pLNS7N4Bx8kP9TPeKxAzNIxNJWu58ONynCEoBNCxtQQLZeuF4KEgYRJ1/PpOD4PTWbpS5j88aFR3r6+1ZMXE4LxbIyIrtIfURAClqpd/v2b13l8MkN/wmSx3KQ/G0fVNPwg5F/sSbHjwit464t43Bi7NB3t6FOc7er3fGcBTO03D+xIu3tXRdgHEKh2l8bLP7pjHHbmLuGtLWG98Id0rThCCFqhxuWNNnNbbRQh2D2QYFsugnmP4Cv05lH9xjU9426PklstCAMO9hkMPrONE0s1HD8gHzdpdByubtb5+qExHh5Po6oqf3l6tSdlSq+CoRAz+cmlDf74yBhvNzt3TUCKgH1DCYIgwI2niezYi33xzF1tMLftxE18OgmYMAzZXohxeqV2z4qNw2MZTBHcJVGW1CVfjjdZ+P73uOQ46IrSIxbTWaJPfoHhmIYhPZ6dTnNoJE2p63NkLE3b9jizVEaI3r6x22gyOpRmudKh5kpeKUN98CD7R2ewz5/C9Fxk/wji4EH+1wttSpeu8wf7h5Ay5Oh4hoiucGG9yRPTBXIxnaVqz2dmWyHGRsPBDyUhkm2FFJ/ZXmC8u8KVi2fQVBXMCLsP70evlwjmzzJqBlh7DhAOGpxOTnN5s8lixWFDRnnhq/+QofomqW6JmGVgbN+Fm86BGaUj5R19IAwCHhxLsVbr3jVn7R1K0R9VbnkpOX7AuZLHsfkyttebIWOm1mtrXOFXyVYIc31ofQP4xbv3kpEDD+JGore+1wx9nFd/hLu5ScMJqHQ8wnKX+MZPGXvsMbTCAP7W3ddB0+A2xQJF1QgkaEL+WrJkqqpybrV1B/lyE0uVDgu1BLszKlqnV8XmWTF8KXtKD+fev+c1/dImZrkIfcO/cnvu4z4+CfiB5LvnN3/5icBX9w78jltzH/dxH58kPjECptFoMDY29pHHFUXBcZyPPH4fHx9SSlxF7S32FZVyW3J8ocJoNkbT8Vir2ZiawnqpzUQmyhPbcrh+yEOTWUIJ2wtxcjGD95YqtN2A+Uqb/+NntrNYaWNoKsmIRtRQWa72vGQGkxEkUOu4VDo++woGuaE4XTTmy21W6h2GkhZhKFmqdnh0Oket1SUejfD/fGOenYNJDF0jZ9eodGwUVQXpE1Gg1LL587NLSCHQ4glC1yE5NMhLF5YZHB+i7Eg6nk8ztFg9+T6zC/MU4gbSc+m7epGwMMRWYTtnt2z6C2mypqBdabBc7vQCQQmFasdl7thxdn75y5gnTtDZLKJrCubIONHth3m9qRO/XmT8gQF0QmKKz2dm+vjZpQ1+6mp0cw+QKDzAkX6T/Ft/ASde5+YuTREQCoGWzuAcew3zj2dwbssskvKDBetEQuGLewd5d7FCqemgawozfQmOjiYxpIfpe0ytzWGceJdkt46q6YjpnWysbtDXN0Rjct8tU2M3lsCYmsG5cuGu90NoOsrQ2CeuyS1bDe6ZYt47StiowaeYgGn4/GIPgVKbwdHYr62L/HGgqir+0nVGUkNoqoJ/M0NdVVETKSqrqzw4UuDN92c521A4v9liIhtl71SMxVDh/37F5dndn2PPYJJT602kFDy332SgpeOg8NNLFfY9sIOXzxcxpU/o+uzPxDmohLB+jaNDk2zEM6gjh6msbbC0uMr0WB/Pj6hE/uznKIkkwsyxUGkjQ8mAotI6fYrayBG+temjijGUSIzSUkB/osmLkxbdV79DQgS0/JDJfIyG7eM5baZn3yK/dx+NY8us/ewsmaiODCWts++TGh8nmk/hr51DzRQopkZYdHWcSo3RpMlEX4KXz/d8JyKmwUsVlWc//yITZ46xefUaDddnZtc0kcOPUc8NM6oK2r4ka2moiqDrhcyXe9rkhAERQ+PAaJpLS0V2DCT4yaUOmp5kQNFI4qHYVZ6dyWC/cRLpuaTXF5lIRogUz6I9/yKuvLOyq2gLvnNu7Q6fkvV6l5mBBNsLSX50bvVWnGel2uH0co0v7h1kyBK3+m0oBEoyDffaIANKJIrUf3+y/9IGDN2oxvwwIrrKQEznZvC7z4JHp/Icmy/1pPU0HYKAycEMe9UmQfODrFQlkUIq6j2NpVUh8C6dwfMDxjNRjEycn26ETObGiWDSqNWpLRQxh0dpH3makwtVHspqdBoVVEUgpET4fk/KU1GRnke3WiFmamhIXtg9yPVym/96coXlagddVfg/7Yly4iffZiRhogiodX2KLQel1mUi8z7V7U+QsQw+s73ARtNmWHHJdTvsyiuo772E12zQZxikn30ed2AESpugaQT1KuN7TeYWHYLNVcTo1B1ZdYZuMLvZZLhT4kt6i+5knqKv4ysaw4Ukg3EVQ/rMVgNeu7p+K1AngJmBJE9OpO6ZpfrbhK70JNNuBqk+jJSloSI/kuSZSKh8ef8g7y5UKbUcDE1hZ3+Sg8NxDOmhI9GWrmGfOk7QrKGYESZ27GV69wG6qkRRPJ6eKfDXFzfuqERVBDy5vUBc/fUqe35fIMOAvA5PT8RRFIUwDAl+DZ8ro1mjdfVmsoZA7NzP+th+1ruSpKXTv3qFmGER9g0xGxng1fNL+K0u+wclhWwfP5nd5NsXQo4MTrP7oQF2hDUUHLr7HuLPL47RTXustQPsS11i5gov7O5nePUCCctkxZM9c20PRqbHmDADmt/6UxLbd+A1qwQbG6iZAuNf/6f8z69epn3xGJHBYTwrzoHdcaYLcRw/pN5xqbQdVCFotjoMJ0wimkKt65GMaMRMg/5khN39SX5wboOa7TKSjvKHh0b4T8cXuV5qowj4h4eG+en71ziwbYhm1+Wd+TJHhpPsG0pyve4SNXRe2NXHjitvEqwv3+rRUkqk5+K/83MefOTL/KB9d3XxYMoiYwr4Dd9ZEYmCuHegWCv04V29eAf5chNhp014bRZl/1Hqgcq3z6zTcj5YH7/WtLm0EeHLuwuYtxGbQgisdgP/8lmcxZ6XojG+DW3XPrrRxD3XtjL0GTAEz0ynWa07LNe6DKVMnpjMkNF9Prejj2+f3yBl6YRATDeIGSqNrks2ZlJudHhsusB7C2WcG/N21NB4anuegiGREnwpMQ8+jBVL4Fw4Rdhpo1hRzJ37Ydd+Ps073IwW8IU9g7wyW7z1DHRVcHA0w/aMQXgPiV29WcM8/hJpDaqOIPB9fLuLaDWYPPsK0cooyvA47sAoOR3yhmAwHuc/nVihWO/gOQ7NQDLUl2Z6KMdS3WEwGWG10uSkK3nJNxkafZKcKah6Cs9pKR7bFqXjBqSjBsMZi//ljes0nYDJXAwvDMlYOnsHUxxbKPPUtgLKCKzVuuweSnF5s8n5lQrpy28jI3GGElEGdu2k/dPv0KlWiJgG/tIVusde4dAjzxBrwe7RMf7bVYf59Rr/odziX3zhIPkrb1NduEqs00Z5/kX8jyD+EorP1x8YYLHmMLfVIqKr7B5I0B9VUG+7n7ObTV69cmcyTdvx+esLPVnNnB4iFY2q25O51FWFQlQjpvh3veuOqmM9/UW0sydwrl1Gui5qMk3kwIN4t0mkASjlIu7mJit1h6bzQf9y/ID2G28z/ZU/gNd+cNe+zZycwY31/F03unB2tUat65GJGTwwlKQvwi/Y690NOxTMbt5bIhDg4lKJ3ctLtM+9BxKM4VGiBx8GuKfk2k0ExXWUgdFPPNnwPu7jPu7jPu7jF+ETI2ByuRyrq6sfeXx2dpaBgfsM728TQgiWO3BuvUnCMqjbHpmIRt9witFslFLbYbna5fW5EovlNmlLZyAZYaYvwWvXSgylLAqxnu1iteNwfKHCnsEkfXGDhUrP70TQkyFz/YCBTJSVaot0NMM7c2sEQcCX9w5zbKHCbLFJRFN5Yc8g6YjCqZUak1GT9UaXWtfjawfHiK9eoBhKZOgzmIrSn4lzrCHo2i6aKtB0EyViESgqvpRs1ToMZeOMJXR2tldZvXIVRQhcPySmKlzZaiFKVxlM93G+ZZNKCK6fP4MZami6RuD5KG6Xsb4Cq+tbNI6fY/PA54m5bSxTx8zmeHu+hAwCmt2Aih3Sb/Y2tttSCumDI1wutlhpuHihZDRtEHM6OLEYnu+hCoESi2Pm+5CdFv7WBlG7jaOZ935gYch4XDC8tw876AV1YmpIGHgYoU/wziv4i9fJVcs0lm5Us1w+x8Dnvsr1S+cY79bITnwFG4UgDDEOPkLYbuGtLn7wTpgRok9+Djue+p2/fx+G0H5xMFh8yj1gpOQjTUoB3OB3v8iXUqJaUZLzZ3l2z1FeurBCEIRoiRT+6iIHj+7n1GqV4tw85sAI01mLLdvn3/18jn/6yDh/fGQMS9e4utVi90CKthdwptxmz+G9vDK7hZIL0QRoThdkyOMTaaZXzlAc28GrVzbonN0imkygxBNMTQ7z93cOktu8RvjD/0zodHGNCHbQIaGEWHGLjhvgriwgsjtphgqVUhUZC2n4PfPUPbrL2Y0qMUOlLxGh7fpoSi+QqpQ2UIOdtM6fRoqebrihCuKGhr80Tzg6SWrXUX4wV2Nhbg6pG6T6+li6XmLDkUT7+skHYCfznNy0OVMS7B56mMf2P0bCUOmfHiLh1BluFwkti0o8y0OTWV65Wmaz0kFTBYoAEarEIxqWCNlo+2Rx+EdP7GCrG2CHgqmMyWiijHH5GH5SA6GhC4kMPPytTSKNGm4q+8EzVDTeuF6+g3y5ifPrbVRFR3zIYsINQn5+dYs/2t+PdiMQFQQB5s69ONdmuVddiLnnAJ7+EWPN30KI0OfZmTw/vFik3PoglGUZKl/c1U++uUHYbCBMiyCT4+BAhPHMCKt1h6DPZKCzRba6jHpx9o7r6rseoPtRmdMyJHAdIoZKs+kgQslqrc3xrRaHRkcZGplBMeO8t9mmMruOmcvj2jbW0izD/VlW18tIrVcx6QUhuC79SQtpd0AoLNW6/OcTi5RaHnGzJ3WjrC3QtT22hGQgGUHXFAZSEaQEo77OI6mA/3xpia4n+YPtSfbNn0A26wTtJqu1G0bTbp3KX/0VsS9/k/DwczTX1shkUvQNjvJAdqRX2aKarDVdejUwgum+GBN2ifYr30MeeZyfXpql1vUQQCIaYWDHNE/sHOa1q2t3ZElLYHajQdbSOTzw0Vnovw1o0ufgaJqXL99d+SWA/UOpX0yAy4DRKAztyWMHPek/SwkIQw9VVVEvn6V97NVbp4fdDvbp4xjlLYynPo8bwnhC4RsHh7lcbLHZdMhGDfYMJMibEvkJSFD+bUAQBL9RIoJs1m8Rot6Rp/h+N8NrL10llDCeMrA8l2cf+gqubXO+6LBj304K8Qh12+Ot2SJl20cGIfMNh2UvYGF4nM/MDPPSbInFmoPjB/hBSL1ls1kJ+K7v83CuS1STTGYspFCQAiYmB6l/71soomdmHfo+lgJe4LH5/nHy6SEU2UBuLqP4Psp0z0sqCELqre6NvmPiOA47hmP0xQx29yewdJVMVEdTBa0bVW62F3Kt1Ga51qVu+2iqQl/CoBUKGoqJ43nsH05zpdji5GIFIxYlGbN4eCJJvFPl4jsnMAkZTUfQbjAqChDxukzX5nlseD/vbXZvkQeZqMFnZ/Io4W9OmnqJNMbIOO7y/K3PRCpDa2IPZPLwxk9RQwVT7Y2pd/zt4hz6A0c5u9a8g3y5iWLT5nrVYXdWvRVstjpNOn/9V4TtD4K29oX3URauYn3hRbpW/J7tlFISxWUmrbAz2yNqwrBHECYNie0FxA0VTVOxXY9K2ydmamQtjcVymycn02zPDlO1A1QBmYh6Y/z44Dc5ioay+yCR6Z0Iz0Pqes/v5neYmPPbgJSS0Sj88YFBKk5AEELKVEnqIeE9ZE6FEMiNVYTrMBjXyFsqbqOBYmiYbgdOv4MYHKL90g+IffaL2IPjSClJqR7/5JEJji9lKLUdIrpKpeXw3fPrfPPQGFeKTRJRE01IWpUui7WQdUI+v2+E75xdY73hYJkG/YkW0/kYj0zmOL5URRGQNHvytm9dL3F0PMvxxQqr1TZ//8EJ/uy9ZWq2x7MTKbxOh5btkZgcwDnxBu16k6QVQbXbSE8QRmPUf/htJr/4h4Tv/Jh//uxXOV6TDEdVTp68hNVXoLNxkhEzQf4X7AmklFh47Mqo7M331oC+79+R7BEqGicWqvf8+0BKzq41eGpbhtevVVmudHD8EDcIMTWFp3f0MZ1U7qiutqREb9cxpmawtu0iNAy8SBRb1e+W+iuu0/HDO8iXm7C7NqVuQGFsGrlw5dbn+vA42uFHsIGLJZfXrm7dWn2WWg7Xik2e3dnPTEr52El+oeQj/aA038VZK+EYm7dk0dylebyNNVLPfRl+QV20Eol+4omG93Ef93Ef93EfvwyfGAHz+OOP84Mf/ICHH36YwcHBO4699NJLvPPOO/y9v/f3Pqnm/J1AC5NXr23y+rUyLdtHVQR7BpPMFOI9abHpPO8tVRnNRElGdJqOT22zyUajyx8dGsMLAhwvIB7pZcZ2HI/vnl7h7z80Qd32WSh3eoElP+TJbXn2DcY5v1ojDCRH8gYtzeL/9dZ1QqDtBOwbjOPZNk4g+O93p3hnucn2fJQjMZ/U8gWmBpLkx9L4M/tpDkwxl+kjKQXPz+xiYfY6G1s1vEYNJQyJ6iq24xA2fHYkQrj8HoYCdiDRFfCFSjsANQxwrl9levsRBpIR1K0UxVKZgWQct94mnoixWuvQCQR6rcJGy+Mn19qoisLeQcme/hgLpRtlz7cF2GUYktNDnhyLoapJaq6g1nbwIxaBGSU2kUNRBNJzCW8EE7S+QSS9ha8ahqAo+FLesUCUUqJKj9iNNMab8Ry1UqK7cJ3Q9wlLRSK6huuHyCDEf/8ddhx+BLl6HVHagMIQAF3DxHj6Bcx6hbBaQURMyPRhW71F6U3t4U8KQTqHmkjekX1+E8KM9Dbqn2LENEEmalD9GB4CvysEQYA5tQP74hmmF05Q2PcAS4FJxw0YHNtBN5fDeX+OZC6DbbfIJXWCiE7KMriy1WF3f5zvvL9A1Q6wwyL/9JEJTAKOzVe4UupQbNp4KEQScZq2xw7dhqFxXpsr0TfQh68a1Jpt9I0lVjeWuPrIAQaqRZxuhzCZofPYF7H1NNIPMIWLnLtMp9HBC6HpBkQjOkbMwAwE5Y5Lq96g6wW4QUDX7QV7h9NRGpUqakQnX68SCoGhKgShpOEFhEHQk9ZbXkI883XaywHxuEu90aJRKhEMjnNNSvb155mzNVbrNqGUdJyA99Z8LmypPDKWYnx9Dfmz/wZIhGGQ2XeEx/c8QrXrs1ztbXRNTSUfM3hqOsdisY5paOgxi794+RKGIolmsiwlDV5IRhlWBNoNabjb93zSu/N9afmCjfrdVRzQ8zlZqLRJWXe/Z7WOS9UJKdzGUzrZfqKPPEXn+Ju3ecEIzJndyOmdv3eZf3Hh8eLePrY6AZWuS9zUGDEk5lvfp7m8cOs8NZXFevoLZJMZsnkNI5dBvn8Je+HqBxdTVaxDj+AVeusRRVFwZI/cNxVQZUAgBNrQGFalQtTQWFlZZ+rhvVxccHjt8hrRdBovb2JKlUcfPUQhZdGQDtlUimcTKi+TZWWtjFAEUsJAf4bndxX46XKVnVPDXK/aVDseltFzwU5ENJRWEzcIaDoQs32qHZdqxyNEUrA0krUywcI8pqJSyKRQ1pcQgcfiVgupaqBqKLqGJT1q9RZ/Nm/zxECGYxWFixeuUOjPU2m2GRsy2DuSZanc5MBYjnqjTXDmXSJTM/xkvkGr3kIHAgSu9ClvVvi2KxjNfDAn3o6za3V29w1ifkQ6vaIoKIpyR9WnpvWWoGH48bTupZRsy5iUR9OcXandIsQ1RfDYdJ4Bi1+azS+lRJE+0Ztz7I3z9U6L7ql7y+C6y/PEq1u42X5kGJLRQh4fjSFE/Mbv8f9OV7781nHjvVDzffw8LPDqpeVbY6qiKBTVGP/zq7P8j185yur1eV6ZW+bz+0d4da5MOmowklGpt2wQCkYsxsmNDk/uUbhWaTNfbiO9XsBRCEHCMnDaXarDaQpKwHqzTcMJKGybJlicI6KrKJqGjUqQKmA4Dq5m0Dx7mn3PTPDGWhvPDxBmhGvzqzw4NcZC02Wt1DOhMhTBU7sGGE5bfPu9eT67qx/hOby93KDcdpnMWvzx/kGKbZdAUYkbKoPJCIRhb94LQuxQ4c3lNkdGU3zjwQKbTRvbDxlOWRRiOs1KmcB16QBrDYexlInmdAm2NvA6bRTT5GCnw77JnSwkhjANnUJUxfgtVax5gPXI08jAx1tbRuT6mB1+gDfmyuzdqZBre7iNFumowUDcQNVUhGEgXRcUjbZUmSv+ggz4jSZ78jlk4KMoCv6V83eQLzcRtpsEVy+iHnzkF67Fbh+DbkKXPrv7Y3Rdn44PuiJJGBqWpqAQkolaaITowid6yzMnvFfhJGEYYusm3EyA+JSTLzchpcTAY+BW3sa9fdHghhxuu3nr78x2HbW4cudJQQAyxDl5DP0Lw7hKj0Rr2jae55GL6qzWukR0hW8cGKbWsXl2po+LG03ajkdfQmI7Ls/uGqLU6FDruFiGStt2EEmTV+e2+MLuAbbnY3Tcnj+mH0pq3V5CQ8MOGM/GOb1Sp9xxUYBmIBB9g3RX10nGo7RWV4gMDmNEDfziBmrg4nsedruDUa2ituvEz79D38AeTi74BIkMxVSWwaOP0BGw3OWOyuSPuq/38iUDcAOod+7dDy1DxTQ0ai2PnbTY3rlOqEdo5gY50VL42aVNsoeGSathbyyrl+n++K9oXToDQYCaK2A9/BTa/qM4sTsT4G4mc9W6d7ZLj0YRioLbbtOQKqmHnyO9bQZpOyjpNH46T1cotAOVt65v3EV9hBLemCsxfGiI6EfIcaqqQug4qIqCHwRE1F5184fHACEEYbXMdMFEXS/fUdkqXQdn7jLm9l04V+8hba2qKIMj9wmY+7iP+7iP+/jU4RMjYF588UWuXr3Kv/23/5bh4Z4m53/8j/+RVqtFpVLh4MGDfOlLX/qkmvN7D6FovHGtyjvXy7c2rkEoObva07CeyEZ7GtUItpoOLdcnHzMBiaoqFJs2LdvliekCl1arXF2vEoYhuqby+twWgwmTI2MZwlDekPGI896lJUS7TRyT7d0qP3azFITEt2I8PpHl5NwaF6+26S+kcESBPh1eGImgrC1Qee8dFifGMY88zV+XFK7Mdml587S8XkbfE9Pb2DPa5tLJc2zOXePw+CTvbtqY0kcJwW3UiYYeuhkhYah0XB9LU0A16J/ZTkHvEsyexwq69D10EDyP2nun0MwIdtdGCtD6h9hyJLqmYqoKC+U2D471NJs1RZCK3K3vfjPTMwokUxrWo09SmzuPbFTvWCwKw0Sf2Y3q++iz7+EtziFUDXPHXuTIJM4vqA5RFAV/dYnlhkMqdAg6NoKe4a+uq5iNEtGoSUdKgvVVlP6RW8EsVyi46TykbyM3/oYWpK5uYD3xOdovff8OOQqh6USf/ByOFbunDNCnBTo+j36Eh0BfwmQwrsPvWIIHwE3nsQ4/SvfkOyROvcqhyW1oYQhNj28vlvAWe5JUmqYjIibthqRrRCl3XAaSEap2gK4qTMQForTBvotvESn0US7sZiNi8crVMocn8lxeqxCrXSM5Oc2XPRt38RS+HkFO7uB8ajvFWouLC0UOHzlCRDO4GCR4+VqVWreBDAIMXeOh3YcYiuvMLngcnsiRiuhsdHySEb1nGC4VVAVSpkafCX4Q0rZdEqkkgQSsGJqq9DKFHR9dFRCGCMOkq0c4frVI3/AAJ9oh2Xgad3OdIPC53Aw5OK2RtHSWaj3D4yDsZcplIyo7oyGz1zc4alnIdhNZKWH/7LskjQgpfZS/f2SUUILjh3TdgJcvrVPruAxm4hwYSqIKiW/GqDkBxa7Pj1c2+ObMQWJn3rzjWQlNh9id2bhSfrSPSSglQSgR6r3J0Q+b0AeA3L6X2NAYslwE30fJ9eEl0ziI30vbRl16DFkwHNXRZEj4s+/hbdwZ+AnqFbov/wDjS3+Eoxk4CLTDjxHfvpuwvAWKgpLrw4klCQBP6Fza6nJutU7X68mbHB3LMJYQRGZ2o165QFYobLZcos0thvNJNqot1FwBRdd4aNswL18rsV7vklEl/3LHDNYrf8ULff3UDw7Skr0KqlRpma4zRN6KYBASBCExQ6Pt9ox3qx2XMNtHKEFXFQxNQQYhmiqQQYhqGLR8BR0wNIWM8NBWr2FnBgjtHqknNI1oJk3J9vG7Npl0nAUtxvtzSz2PuI0y24dzeAGUay3+we4MDnCl0qa9vET0qefpzl9Dcx1kGKJqGroaJWxUWVNi7OxL3PO5dF0fX4L5oZdOURQirTrB4hzB5jpqKoO1fRfSdXCvXCRsNdCHx1AmtmN/hHzQ7VBDj0dHYuzuj1Pu9CpN81GNhBb+RhUoot38JXImG4jcwK32fdoz2j9NUJSeWXcYhh8rICbTOZRojNboTt5brt6xZAmtGJvLW6TTCd5fqbPesAnpeRzVbY+O6zMQ1zECF80JSXouZjJHpeMSBOAj0FSViNp7V1W7hR8EbFrj5HIFsrUrJPN52hLsVptW1yM+VKBiQ7HeJUWcfCyOX9lA56bvg0DrG6BZKnMiNPjjx2YYT5lMmQEDzQ3sK69Tajv8D9v3oCcEf3nVZatcY/dgkmjc5NtnVylullHMCCODOQ6NZrigwlLNZr3R5fHJNCevbeI0YCzeZb/q0lBUpKkxt+UxoGhkEkk0u00cH80J8VcWkDeCvmp+AH9jGRbn2Pv81+ikBn8lX4mPg65pYTz7Zcx6mVVivHlmnWBonHnfZHjbTpz336UpVSI7H6RmxKl2PNKWxvjYIAKB/MhZ8Yac2o1/a76Lt3DtI8/1FubQ9x4mUNRfqf1BELBvIM7sep1s3KLb5ca7GiKAB8cziHvIcP1dRRiGqLkC0Ot7YevOxCo1mUIv9BElRKg6qufgmj3TdtsPmSs2UATETR3b8Tm/0iEUCm0PvrZvgIjTouElqTU7lFyHs0sVFKDedNBUga4IOo7Pa3MlduZjLJebJERAupBiLB0hoQmiImAym+D9tQaKEFiqoNZxaY7uQL1wDiseI/Ps87C6SFgrY0zPYE5uo/7mz5FIQruLIxW6168TmXmEa4tbSL/LeKXNmZLK448dYGWtwcC2DOLXXPtrak9Ws/Khz8dzMaRQeed6mXffXkb3XQ6NZRgqrcC7r/PMs1/iZZnk6labh4Ysot0Wzf/yv+Cv99ZCwjAIm3VaP/4r4gjMo09gqx+EfKSUKAMjCLXXT6zhUdi2lzU7xAtgvJCglczhazrdwfG72l3q+HckJd4O2wuodG8nKm/8ViR6aQPv4hkavouIxonu3I+dKXB4NM1iuXPHNUUYYIUeM5Z6z8Q9d22J+HNfwVtdJOy0PzigKEQffaan9HCfgLmP+7iP+7iPTxk+MQJG0zT+zb/5N7zxxhscO3aMMAzxfZ/x8XH++I//mCeffPITz8j/fYVQFLZchdNrDdywJxGmawreDemB66U2B0bSFJs2/7tHJ/jxhQ3qXY9Kx+WxqRxjaYvvnVulPxFhKh3B6XQYSES4tL7JQCaOIgSXN5scX6xi6grT+Th54RJubeKtrTC2s49yp8zKxjrj/TlSU/v51rvXkK5LX1+Gi5ttLhY7HO2PMOpWWPc0nnjsGYJOgx/XLebsgPpWCQmYqRxzmw10RWEioTIxOcrs8ZPMTE/x/EyB5dOnqSkpxoeG0efnGC9YOKtLuNE0qu8z88gRlHPvslm3cSUMR1Va7x2j7/AR+ndM0y2WenITikZnfCflsofreKi6gqZIPN8HAfuG06S0e2e73YTiuYhcP4nnvoL97uv4lS0kAm1olMjhR9ByfTR/9j2C2gdLba+4jj48jvnk8x9JwiiKQt0NadoeKaPXRyTghSGeG6IYGtwItQrj0yvjJaXELgwS/fIfE64uEpa3UDJZ1JEJuvHUHWX0n0ZIKRlPqHxl/xDHFiq3eQgkODCc+K1lk/4y+ELA7gPEh8fwF+ZQYwnE+hL2xTOYU0/fdqJHsLbC0MA4K6GCFAI8F63TZCwdIVhYRJpD2JUKIpVlR1+MM5ttspk4Q1FBfizJlBxi/bUfs7JURIYhiiIQF87xwKEHeTs2QU0xaF2foz59mNdfPUuj6yJDiVBVXM/nvaUajzx2kCcNn/dW6j2JJNEzah1KRRjbk+WBHWM4508RbDTQJKStCMnhYVpT+ynrcaKjE9gb66hKL+CpxhP46QJb8X6udSDodjBUhaWWw0RfP6mYiWJpvLdU4entfeiqYLbYJhMV7MpGeGg4TnlxESWRRDNM7NPvEoqePr54/cdYh77OuZbChapPresRM1SarS4R08BQBRc3muwdyXJmqYwSS6JqGq7QWA1MdhgG0vUQuob0fcxd+3BjCXw0yt2QWtcjGxPkEhbl5t1VMJauMpGLcW2jdtcxU1NImj2Pp9sRSkk3moDovQPjv6+QUqLXK7Q27i1tGjTrKJUS9PUqAn0JfiIDHzJClorG69drzG42b31WbNj88Pw6T8/0sTefJfb8H+CefIvB7hKbF0/xlaee43piF+drPqOZGP/1/RUCKfE8HxHT+Na8zR898SWU02+QfOP7UCwRHx0j+oWvU8Nk9M0f4j31JdKRDF3XR1MEiiIoNl0WBgrkYjE8z0YRgkRUR7F9urbP0IMP8RfzJUxNcGgix0AaGltF1FgKRQhCKZGeh6UIwpiFMjjIw5EUPzy/TjQep9HuEoS9LFVjaxXNtyiWIL92lZ19w9SiOqVOh7D7gdeV9DxotyCeIKKpd0gtpiyduKnjBSF+EGIq3MEuCiGIbK3Tful7vWx3QOu2YWMFb/4qYSLVm8vWVxDn3if2/NfofBwfsDAgrUI6cXPN+JtXoAj1bo+MO45/yiUyP41QBZiNKv7idaTdwRgYRvYP96oDfgFc08J6/DlqdZu2exspJqAjVYSmITSNtWqLB0azzK7X0TUBoUSqClsdn9FMmrQh0FpVom4LS1PJxXTmSqDrOrrXRfgOoe+BhGLb44GjTxIk0swffx/NDknPbEOtVrgWWHTrNumoSb3lk0DBGh1nxRfIwTHUeAqn1SQMQuxOl83lNQ7HoPvSj1jb2CDUDDRFEK9tUJ8b5OEHnmR9E3LZFD84u8ZkPt5bwTk2xWqL94HHpnKsN9ZwqlXGopL/w5E+IueP0/7L96mFHvlcGhFPkHzwWU4rfRx+6Ajt7/0ZoW0TRHVkvYoSsSCZRqSzhJtrADinjqF/7mt4vwN63kUQZPs5O9+6FWyvdV0aY7uIra/g7zzAf7lURJM1BKBEY8SCNC8kJNsKCc6u1u553R39cYQMe0OLFPCL9orilxz/BcgbYc+HcaVFp9MbyGKGxiNTOYZjv7lXzu8bZH4ANZEmbNVvBfKhR75Edj1A6+Uf4a8s9KpNK1tEn3yeTjxDIqIwVUiw2bjToL5uB1TtAKtVpfFn/2/6p6dRZo7ybqWXbNIJFSJWhOlCjLbjEQQB9bZNbDBO1/Eg9Cg2bfq9Btu3x2kMx+j4LjO5CGNpi7YTUGu0+AtH43//4h8RrS/S/NFfoPkeiiII1pboXDhD+rkv0njlZ5DO4DizKKkMjY6LNCO4jks6ZnIlmuM/nNrkmweH8aTk150ddBlwYCTDyo2KOYBCwqThhrx1rci4KelWeyT0y+fbHJ4eYEe+SvvVH3PguW+w3vFQ1TgszOGvr6BEoyhGBNlp9ZKV4gnci6ewdu6FdOGO77ZjSYaf/izehUvM57fxzum1HjGjaZxwohQ8mz3Dae5lqnYvwlT1PbiRXKd6HmpMv5U0pAqBNnuO9rtvABItGsVZXca5NkvsqefpG9/OiwcGeXehxmqtgxCC6XyCIwWH+Hsv35ueVTXcWBLrS99Eri0TbK6hJBKoY9M4yQzhffLlPu7jPu7jPj6F+MQIGOhtxp988kmefPLJT/Jr/25BUTlfctlsd2nZPrbXK8uO6CqWoWF7QS9g5wXsGUjzymyRTFTjC7v7absBV4tNkqaGF0hSloYlJIrnkI9axAyNtUqLiKExnEvgBx0URfDISIL1xWX89RVGcwn6aiskp7bxtViTqGyytnCa/2HvKO+0DN5fruF6AYahMbteZ/fOAsvX13lpvstXHtpO5Wqd6lYFIZReQMTpEotFubLVYu/gEKpiYkxuh1qF52LLtIYVOib073wIb/USoryJjMYxo1HUWIxwcQ7XC+ioEZRuk7KrUBgbp3vhLOlnv4hfrRHPpNEfeYYfN000r0NfTKPcclB1lajX5TMjcXaOxAl/gVZ21O7gvP4T6rUKsZk9GPuPYIYhIpHEB8TgKG6ldAf5chPe+jJWrYRqWr3KECuKG0/d0sS1A6hle1VjLVQSVhT/tgBZmB8ksLsgBOrQGM7HJDKkorJQbrNUD1EVQSGqEVfD33pm5O0Iw5BuNI6Y2dvTIJay196/LQvlMGAkKnhxb56uf6eHwCcJH4GfyqEcLKCGPu7x1/GKm+w6rHPhtvOUwEPrtojELKYyUZbWy2TiZq+f+B4jRoh65GF+vNBi8voKfzIVpzF/mWCpwsT+XVhLl1EcG4Hs/Rf2JPPKJ9/lwa9O8pMKRKIWby4UEYk0qUSGVnELoWmQTNPUo6x2fFqepNR2kb5PPGbRn4qwWO7w3QtF/scjjyNLRbwlG+l7hL6PkcmRPXiIay1JPJ7H7TNIKAEIwZYL5Y5Hfu8hvC2biGnw+GSW759fp6lZ1DzBcq3No1M52q7PtkKcAyO9YFzQtXnz6iYLqy2G8ypObIq9j8aw3v5xz2dm4Rr7n49wutRASIW4qaH6LpqqoCiC/UMpfnhmiT94YBgWSgjfxTKSqIOjtHWJt/MwJTVO3YdUIU//UB431PjhxSLFZi+QqKsKu4YzbDQd9A9FdGYKMbJRjSv36A9HxrPE1eDTXCT2iUPaXT66nghku/mRx26i7Mg7yJfbcWyhzGRmiCCdQ3/2K4w80sHZajHnaizbgkcmC/zkchHb9XlqJMY+UUdZnkVVFBrtKeKf/QMinaeIdNuUojkWXIH6198iaLVI1Ddx0imm8zFW6w4NxwME3150+JfPfIXBy+9Q3dxAQWLqKoMHHyKxYxfPW6vEfIP03EmCmoExNYPbaaNpEVzPJ2Jo+ELQntjF/3ahzr5xnblii0JUI5vPYBAyqtowWOD4aoPZToVJqfFoWjA8PkznQ2OZotzwQjJMYhpENIWooTHdl2S51uVKqUvMVHl6ewFV3FneZfge3TdfukW+AJj5flrf/xYIgWZFCW4kHkjHxj72KvrzL/5OgsM3oQmB3qqD3QUzgp9I40lJkMigpnMEtfLdf6QoKP1D9+VMfgWoAvQrF2i9+/qtNYVz6SxqKkP0ua/Q+QifDrgh4TQwQiwTkN1YodwNEaqK0HVcz0dYUR7oi/JU3KZzbZbHwpAUCuGuDH95tdGTtTFUVjbLCCSTEZ2sFvKZmT7OrNSxlJBQUQijCcIwZCIbxdRV6uVNjsem6P/SDgLTohKLUJpfo1quEQD5uIHtSyodj74vfZm/WNXZkHWCqo2pR+gbLjCmC9ytTZzL10iW1xiWTYJojvWWB1LDqmywyy8Tf3of3z+3jqYqqDeqLAB8u0tcTxGGkodHksyfOksjaTHuL6MsniXQXVQZ0FmaQxkao/qT7/LE1/871i6uktt7mPDKeWT9RjVkKkv0M8/TWpi7dW/9yhaW08W7QZD8IiiKguE5eKtLWLaNG03g/7I+IASVD8lnvlUJ+exzL/Lz88s4QsOwIqipLDIao+XDjy9u8JUHhrhSbGJ7d0Z705bBtqxFGHooqkpdGFgTO3BPH8dQuGu9akztwFO1X6uaOgxDRmMKOx4cZ6HYq/pPmipRJSC87+90F2zdJPrcV3DefhnZ7RDUqiiJJOaufYSO3SNfACUWxw1CllarvB8GrHcCSm2PbYU4oxmN2Y0aoRBU2g4PDMbg/HGklFSuX2dyxy52Dg7Tcn26oaDjeDS6Hg0nIBuLEFGhabv4QYgaiVCv1Dg4nSX6/ut8fvdeQtfDW11io9EhGN3O+VSStxaqdH2VxbfeYWhskrC4jiIEQbuJgkP77VcZeO4FFssdhBlBHZvmgh/HNVQOb8twrh5wthZi6R6LVZvHx+JI/25Zu48DKSV7BxMsldKcW6khgb5klO+cXWMgbmBV1nD5YFo9Nb/Jjn278N74KdluDdnfSyjxludRYnGE5+Kv31YhVt5CqZZRvbv3KIGUKDv2QnaSk29cQE+mEFYUNxJnwxPoHZcLGy0O9d/t7ZaNaDcqy2WPTG1U8bc2IAzRdY3EYhdtLUTs3I+PwGjVab/3Nh9erwlVpV6qUMn4VNyQB0bSPLmtgEZATJXolxfo3KaYcDuMmT14ikpoWoipHSjbdv3t21Pex33cx33cx985fGIEzL/6V/+KPwese9IAAQAASURBVPmTP+HIkSP3PH7y5En+9E//lH//7//9J9Wk30tsdOD1q1vsGs7Sdn3ycZOlagc3CEmYOpauoiqCyVyU2fUqjh9wvdzm/HqTpt0rrz8wnL7hF5MiogQU17foHxvhy3sHeeN6mZVKi1KtxZ6BFIdG0zjlErqQPLatjx2FKJYxQPfYq1RrNnUhWKh2EYrCZ7/4FeZicbpegK4IkFDFIBU16UqBG0uBrIEMCYWCQBC4LmoYEDctIqZONGLxjako6YXzKOcukvB8/HIN/8ARoocfwa3XWDxzGd1usPtzD9M88TbXai6eUEnoERzbQR/KEcbiiE6H5At/wKVKyNlKgB40KbccTF1jWz7GdF+Cw8kQ6/RPMfq+hK+bKL6HVHsBrpvBGAOJe/pd6n3jtAd2oKuQ79cx7A5oGvruA4SKSvftn994SgItV0CNxwEFPZXC/tn38MKeia/QdMztu9EOPISrGxihjxqLM3lgPxvnL5AsDCJWFyAIMCIRkkcfIVi+RvTwozjJ9Md6T3yhcWypxbVqhXa7R+boquDx6QK7cjofKfz8W8K9NLj/tkBKiQju9hD4m0AYhmDbBKFEicfJXzvFoZn9vH+lVxUgwpCIDOizVPYXDL637pE2dXy7y5GZYSynzY+KIUIKdgcVmn/xF+SSMYSikqik6R5/g3x+iGVNxXGCm4VWCAHa6jyHth9Fc+tUKj7+6hrG9C5io6N0hE6x3qVj22iKQqnZYjAikNEoHV/i+SGGpqB321zuJjn06JOoDz6MUFV81aA8P4/35utEn/s6g3/wDVZeeZm1xQXCQCIyWQaeOspPL63jNrvkBrIMlzb4R5Pb+W4rikSwLRPhs1Npji/X+f6FIgHwzf0DvDW3Reh5tB2f0O7w7tU5ruVTfO3I00ROvoYUgoHKMp/bvYPqxTJb3QDp2oymkjy0rcB710t4gcQJJELAcFzHJABdp2/bCN+d/f+z959Bklxnmi74uHYPrTIyUouqrCytgCporQgSJChasHt2OL2zI3aMM2M7Oz+u2ZqtjY2tja3Nn7E7tndn997de7t7tkc0m2yCCiAkoYECCoXSIqtS64jIDB3h+uyPKJQACiDZJNjN7nzNYMgKj/A44X6On3O+9/ve12Cz0gZFJVh2iZVL7B3MUOtcD0h5Qch8sc6RkQzVtkOp1kFXZfb0J9iZ62o2iCDD2ZU6Hc8nYXXlsLal1a0g0McgWRE+y4RVil6vCpJlGdXvBiECTScIAiRJYrV+6809QMcNqDkBlimh2m1EaZmRaJqBhIJr26yLDgQ+XxqNMDH1NrXLl65u/AXS6Q/puf0AxSMPsiySvH1qli8OGKxsNlAI0U9/wPAXJpFH05xZa/LhUvVqdYpgwcqh3/9VzPoG+B7bRnppL85z4Y//P8i+T7XdYs13KGST9B84iOl7qGen8NwG8UKB5sRB3lIHWJhrcPu4TBiErDcchgyDnSmNDV/h7VNLCCTG83GWqnW+v9nkj+69g575y/QO9VMqV5B9D1mEyLEEQoRsS6rsLsRQFZnvnVym43Wl03Ixg5cvrdEYTnOk30K62k+VeoWgXr1+DyJRgtLaVR0+AZ02xJPXjvvFdYxmDS+W+qt2ic+E6Tn4x9+iNXMJKQxBktEGR7DufADbjGLd8xCtF394E2EEEpEj9+LEkp963i18EkatQvPYa58IhAW1Cu77b6I++CR++BnkqRCYlsaRiT7mWyGuHwICWYTc129xeOE9/NU5GpV6N4h35TyP7t6FMXmYH0038B0Xz/UQwERvAtu2USWdbz+wjbcur1OqNDFVhcFshLwhoyiCTs8A5188wZXR7awGIZVOnW/e+ySZM8eoz83gej59A70oh+6mXhgjvrnGUrOJLwSyEiOeiPOlvQXirU2iLx5HaZURq0so2Tqx4d1cXq/jSQrJ947RemyMhbrDjv4UtXI3MUeSYDBpoUshjbbN704kmKmaFJIR3O/+d+xKlxyUdB0VCTX08O0Qc+48F2fmKJsmex5+iqjfhFoNv7hC+5VnUXt6CXWDQJKRNB3xC8hzqQjU6QvYJ49BGNC2HfShUSJH7v1M8gwhKCQMVm/wOQtCwYItca6tEu8dIZ4wrptuS1CzfRp2yNcPDnJ6ucrcRgtZkpjojbGvEMPCw5E03pmtM7Ve557MEEZwEr3ZpBDXUa8mMijJNMrEbnTPQbZbCEXFjqdwvV9cOkwIQcLS6NGDaxJkW0kPn452NI722NPo9SqR1QUkRcU+dwK31UTt7SeolFEHR5kZOcSz719B7hsmiMSwNJn3FzYZyUTY2Zfk3Gqd8VyUx4ajbPzsNAByLM4HVUikbOxGk81Apel69CQVSvUOoz1xHtyW4dlTiyiKjKkpTGQSPDAUp3fTRXr9R7SbbVzVxKvZ1M+c4cDkJIO77sAqztDqOISZBHK8RVirQhiiSDJSGKAWBrFm3iSd76G65zbaK4JHdxVYrjm8M18Fuutvz3VRp84SltcxhkYJcwXsX1L+LmZq3DscY09vjGLTxUdhJBPBcjv4nW71XusqMRmGgoakoQCy57A9axGGIWo0jqyq+CuLoKqEqRyuFUMIMAgR7RaKonxi36XIgov1AD/XR8P2cYMQU1YYTmuYsuDsSp09+d5PJAsldcGhoTTH5zeR7Rb+1Qo7yYpwx65B0o0Z7NlLxHryqMksSnkN2fcIb6hOkzSN6v77+MnlKu3aLL7ZJYUTpsZTewtYUgBjE2hzl/E+Vums5gtI4zuuEUO/zXvKLfzqCCQF7zPWEzdC/K0UZ97CFrbw24TfGAFTKpWw7U/X17Ztm1Kp9Jtqzt9KyIrKyZVuBo3teUQNlY2Wy2gmykbLwQ8FliYzmokSUWVWqh1MBUYyEeYr1++NpSs8va+Plc0mdU3i/h15Ts2vkc4k+ae35dFED1KnSU72yKc6rMgS8YRCze+hHE2hvvJD3JZH3Q3JRI1u7rzvU331RR6672t8v6NjCB/cANXp4K+v4NfrhHuGUBFgWPiOA2HXKF4KQ9R2nWinykgsTuI7/xPC8wgAJRIj2VcgrFfxFYXZ259EFPbhSVDLZfAlmYRl4APpqEleNQnDANFpoykShqlxW1ZQXl5itlSnZ3Q7y3WXjK4yno1QCTpYkSja+hL+5Yt41U3kSBRz72H8viE8SSawHd6RC5yaKuK6FSSg0JPk4aEcydNvEhkcQ8STIELkSBRrZBvelQu4F05i7r8d591TCLsN2TwAwvewL5zCRGBO7metWKFUs2mM7KNvcj/yuQ8we/JEE7Guj8HaKtHJvaCbaL5HoH52MbwkSVzedDi9VCUSuZ4F6QWCV6eKZA8NkN9SW/mtQajrEE8gFQbQWjXubEwzfudeLjYEtpDZNtpHvj/P2Ssr7O+x0HWNyUSB+OIUrbFdbGwu8tShEarP/QWaIuMGgkbbJh2EdJodhLPIxNA2LpdbuHbXWURWZFJKQKC4qBGTtBmy1moRllaR63UikSjj6RxuJkkubnBupYZpaBi+g9WqYMUK6AmTSLOOqNWwF87glkq056dJZtIk7n6Eaq3BoNSmosWpP/g1FN8jEbpcXt3kuQ8udIMqYcgd/XF4+x3s6Rl+58u/x6W6z6Goz+Zf/Gd2J9NM7NzPu06U4/ObzJQajOQTjPUm0NYWCIFyucbCwAg7DBO5f4Tq0hJpLc3dg0n0aIywUSNot1lcKxIgY2gKSUtje8ZCb29CKspEPsHbsxts2CHo5rV7s9H2+cuTyzy4PcvU2nWJiZrtcXqhzFcPDpIeT6JKoEnhtUqqo/0We3sjBEJCl7v+Q7+Kv8VvOxRZRvJ9hCLfFLT1Emm0gUG85cVPfiaZIcx0va8sp0145QLu9CUAtNHt6BN7cKJxVPmzpacUScKqbdB56yWsQj/6mQ8IzxzHlBXiv/PPSCoyu5vLVKYvIwX+NSlFAXSmLjIyPo4tx/jyWByzuQkSSJKC2mlSsDfw1SR6f5wjQyl0VSFmKKxV25Q9mY6WRTMkLC2OYSURRoSO10CPxpECk7VKk8ilS/Tedz/De+6g1HRYFQY/XWyz4viYmsJmtclgymSx2mGz5TA40cefv3UJAWiqjOw5hJJEO5nnfzy1yT89uIuHCg4vXTTZrDbRYzFkRSGvCx7flkHTBYuVFoWE2TVtVmU0qUuofDC/ybbsINmrapoi+FjgU5Zv8v/6ZGRTfG6G1cJz8d59DXfuMk4g0XQCQhEQnZ0l4Thoj34ZO9dH9KnfJ5i7jL+yhJxMoU3swknnb6XCsoVPgSzL+AvTn5qF7C7OEW3W8X+ObGIQBBwdiNJ2C/xsqkTN9tBUmfvUKonNRRZKZULXJ0QgZIm1D0/wUP8Q8t5RytUG48lexrIxlpfXcfNxzq2W+YNxi9u3y5SlAnXHJ6oppJNRXnvhTcwd25HHdzK/2QRLptRw+H+eddk/cCdHdx3FTFssrW7w3obBwVidnC7xjcNDhGYEYVjU6k2m1uuk3Q56sUkiMURPIosShmzW2uSjOr4kgwzN0Ccb0Wi5AflsksBxiOJjCgdBnHREI2LXSF54H8YncDc3EICqyFgKyKGP8G22RyLoq/NE4zGoVyh/+AHK9nF46YdIrguKgqpqhL6H0jeEtn0XnmF9ZuaILMuo0xdov/lS94VIBMIAd36aYHMD80u/86kyckEQsDMf48xy7eZndRgShIKYfr06JUSm0vHZbLlcWG9Qqre5Z1uWo8MpFEJMOSQIPJBVXpuuXDPpfmsT7rr/yxirM2wsXqE/aWBs24ExOEo4fYH2yz/GW1pAzeUxDt9B/I4HaUQTn9nXtvBXh4eEl0ijJjMUN9t8GOtQlRzyQxZ78hZJr82bMxuEoQDHpmPGUQKXYdkhXNlksm+ER3eaXAii+JUipiIjqTLq+CQfzpUYH9X52tFtvDZfY61uk7B02l7Ajp4obqvNY7v6iOgyUeGxce4sxtIGeuhSX1tl3Vfx5Q5DqSRBSqWxvsD+yQlMS0FNanTOfois6ejJJFr/ELIsd/d59U2yuTT52+/lxU2J3Uqd2VNLVBN5JCSimsxoVCbX3sBfPkWzVKJ54gRq/zDWQ19EjkbQfglZYikMSKuCTFphuSOhSwJJlkECXZUIhYztd2X4ZElCk2UGhwpIakAQCNRd+xEvPAOGQbt3lJW6jVPuJtdlDhxiPYgw5roITaMVKniBQFckorJEx/FIGRIJwwABsiSuPbttP8AX8HGBbBEE3NYfIRfVOXH8PI1EnHQ2xaGEYOjS64TVItG7HsYvFmm/9hLRbBaxMIOSzSNi3ee+N7KT56Zr1Bpt1GT3+yTA0mQuLG5w93gOWxUYD30RfW0J78oFEKBu3wl9Q9g/Z6+7hb878ELB98+s/0LvfXpv4XNuzRa2sIUtfDZ+oxJkn4Xp6Wmi0ehfdzN+qxEIiXqnu+CbLrc4OpLm+QvrFBs2CVPD1GTyMYPHd/Zwcqna/ZCAqAKjmQiDKYt0RGNbNsI700VsP6BuyxzNxHlCuUBo6gSvvUy4NIda20BOptgoDBM5eAfBxD5+dGyGfc0SVqVGue1h+wEJSydpaTQdCFyXPq+KRJSYErJ3rIfxoSxxQ0Fx2vSZkGpXiEUTVFwPhCAMAjwJdg3nsMtlemMO0Xsfo/nc9yAICNsttDBELgzQOnwfL56aZ2OjhqbI7GuHTKoRJLdGRFXouAqboUSt0SSvgxmNU3zuR2QNwR8cvpfZo7s5v9Zkb3+KtXKNV0/NcdaQeHziEONv/gDvalZs0Kjhra9gHTyKduAOjpcc3p9auXYfBLBaqvHDtsvv7jiE1Wrg9/ShDQyjWRFaz38fYdtdWZMgwD33YdfMOZ0l+MiLQpLotB3emalx5uxMNyjuzBOxDL5091Em4xKzr7+GmFuhP6rSPHcKEOhLs+j3P4F79TyyouCFErIkIQsfIQSepPDh0i1kVq62/fRKnSe2JbayiX5L4Kk6xt5DtN/+GURiSJ0mvZfeoy+VpiMUWmo/9vwse8++zgHTIjq+A//S+3RWliht203KVEm0q5Rdh2yhh3LHx9IU5lc3yaZ7YGMdr9UiFTWJpCLguchhgJ4rIOp1RLjBNtngjKIhGxa66TA8OYocSxCoBoMJk4QquDRXJGbpFLI5riyWODTewyMRQaF4EfnKOaJWlJ6HH6W5vIh65SyJe57kL14/y2qxSpjKsqYlkRWFB4fjyBKEYcCRyUGUy2foeAEDlsLA+nnkUht7eZbVjRYSC2Smp/jCt/4J/35hk5ip0mq20ZI6lqZi9aSxOw6XKi47J/bQGRhn+v0TxKQIq5k91OsCtVIiKHUX9v3pHgr5OEq1jLaxitzTSypqMVlIcPHkIkhXdbA7bYTnYmgmWqii3CIjMhRQatj05TSEENyYvBUEAQZcK+74uyqmIEkS7sIs0oljBMUVJDOCtfsAQWEQV1bwkLDueQzeeAHvqvksgJrOYT74BTqagWW3sH/6DEG9cu14cOp95OlLWF/4Gn2JVLc/3eIipyydrCFhv/ozzGyezusv4i/OgesggMh7P+PArocJ3zsPnouhKqRjURRFRgLSloby4RsU9t7JlY0OUjpJNtoNXEbiMbzlBWZaOnrfIJdXqjRQGe+J46g6b0xvYOkKUV3l7dkN7hlJs/uJp1n53n+lbXtYikQsmcY7dDctVBrnTxMbHOWVqoyiKGyLKxSF4ML0Evcf2s7zF4oEikLTE3hBiCLLDKYj6BtrBOkMc8UaYRBysp6nePI8Bw7uJowlMRWZvtY6qWYZXYeSB5vVJnEEQlUICa91UAHMV9r0FMxuZmosgaTr1ypKwnYLdWzi+v01b3bplaNxRPSzg/J/VfjFVdz5GUqtgFLTvj6mmhBvzjF5pEKYztGOJpD3HUE5eCdhGNLemgd/aUiShLjRFPnjCINfmGjTQpfHxqMcHU6w0QmwEPQ8/2c4y9MUEjkWN1sodD2UvHab+on3uPvpCd7caFPfqPDB+4uohsG65vHNhI8zJ/PMosOVpTJ6NIYUTxFLxPjSIw8SCx3MeolafY20YaJrMq4XcHKxynld5Y8OJfhgtUmqL87K5cu0IhnmNisEVgzNtEjHTb7/5jQPjqc4mullZfYyDUNlPBulv1YhrGwi6wax2w6Q0H2ODiX5wallrFwUQ5aRdAtbN5BD2FVIILyATNTA0CXUTJKg00ETAUGtgi/LqFmBVtvAmJhg0tlk1VCoVurIq0UGbrsH752fgaJ0DcXbLTTDRNt9EPfnlHRort2tfLkFgkYV1paRhrd9qiRfRg95ck+XNGs6XRI2oqn0xk0ShtwN7koS6w2XzbaLBOiKTLXt8pMzq9wxmuH2PuvaGrTiwkypee38fih4oyyIxbbTd3gHqe05ImEb//hb1P/8j69VcHsLTfzSGvrSPLHf/z/Q/AVk17bwV4Oqalyp+rx7qUS14iBJCuW2xPlFnwdvP0CzMksgmTiouK02rMzTcBwUSWJ2TmOgdJKduw6xmt9GJ5rAr1dJZjMMAk4kzo+PT3NgWx/bc1FUVeFrBwboeD6rG002N6osryyjS4JB4ZIpruEuzbPsyjSaTSRJptZooyeSmDJw9jjZBx+i8pNlFCB0bIKyjSiuoCZTaEPjSLKCUl4leP15rLF7uHh5EU1RyKoKVt8QliwINtbZl06zcb7IYqXVnVPqUyQTec717eXB7Rksfjl5YiEEaVPF0hVsdJREiqBWxdLkbrKDpjEs26T27cDIZXGujkE304N1zyNsnjrBfLnZJbsAK5+nueMgr7wzxZdzfax3bE4v17C9AFNTuGMsS1/KYr3eQf6oyuXqsJYR5AyZhG+DpuJ9bLgroc+ueMh4tkMwnIbjryNNnSU0I1StBOF/+V+xjtxHtTABuSSSGcFfWUAtDEAkwmail8r0Esgy6DrZiMYdRgtp6gP8jSLedC/xfQfw8v24Q9tQRncA4ATBlhzoFrawhS1s4bcWnysB8+yzz/Lss89e+/ef/umf8t//+3//xPva7TatVot7773382zO33ooUkgmqlNuOrTdkNcul7hvWzcDuNLxKMRNxjIWM8UaBwaSvDdTJERCUxVuzycxQ5e05CLaDXYNZHh3pkyp5VBvQsEwMFcu05o+i2RaBIfuZK5nghMrTcTFKr2xDrO+wX7JwxfQdn0MVUGWYDgTYX6jjSKDJXzyMZ07h3JcXKtz+q3LdFptcvEollnny/v6kZYcTngWzUYLJIntvSmOFCJMRgzUv/yfsRs1Yo99BW+jRNiso/UPoRx9gKYaQ5c2rmbxh5xe2GDPwaPUf/w9DE3H9QSGqlAwZWjWabY6rF+4SCNi0l/eIMgM42UmmJaT+BtljHadIJflp+ccfufur2BtLBNZuUJYrUD/CGUMJFfm5Grrlio4jVaHFSVLJpbAF4LYbXfT+c6fdMkXQLYiBLUKKAqh56G0mhDrZumpVoQPRJJz8yVCIVBliBkqbdvluTdOkX1oH+7qMr0xDdm9/sXuwgyxShkv28ump3B6oc5y1cbQZA7kI0wkVUJVou1+uiRDte1tlej+FiEMQ8KxScx6Dfv8KUQYIMKQpflV5EN3U210GG8XqUs6zZkF+pZmSU/sQHr/VRLNMjohoesSi1hU7YBkxGSuVEexZ+i7/S68l3+IimC52sZUZRJyiJHroV4YZySms/lnf0k0EDz2+B/y7mqLkbvu4PlLRVYurVJIRTm51mTfQBbddzk9X4ZIjETU4BGjjvvsMyB1CFYX8USIc+U8qQefwA3hrZrMpfki8YhJqOokNfBMi2NFh9956n705RmCM8epzc3i6BEGJJv2mQ+R0kO0rwZ9hBA02zb55XkypsVKpYJuquwe6adZSFNudEhqMFpI49d6WPzZK90Khlad24708uKVTfREmrBeRTgOab/Fl8bSyO0mu4+MExkZIx7RWG915dnUThtvZeFacDEQoIcyiV15DFXG8W8OfKUtHfE5ei79NkOSJMziMs23XsKp16++uoG3uoi55yDqobvwJZmOYaE/8mWM2iai00IyLIJUlrasdI3pr1zski+Kil7oQ7GiiDDELRcJps6ROXwvd43leGumfNP3a4rEgztyxOplHEXDOfUeuHaXfJHADwScfJuDh+9hRfLxDZVEPMJK3cb1Q2K6im07yFKMXC7HvKSxLaGR2b2HZs8Qs243aeK+nYMstXzemHKQ1JBYPMbx6TIDKYuGE6CpCl4Q8uLlEqmDA4x+81tsHHsbJZFEHtvBK7ZOrL5JJezlHivJiKKx9v55hCJT6CngJvPMlps8vb8PVdexNJnBbAwj9AnWV9BVwaYPQRAiGwaEAeWNGm+8/A7awDBJXWZPf4g5MorwPUR5k3D+CiIMkQ0TNZcnMKPXpj8vuD4fOZE45t7DdE68230hDPGDAG1ojKCyQajfnEVvHr4TVzc/F13HsNmg7QUUm5+sxG44HpX1MrFsvvs8vfrfFv5qCMMQrW8QLp295XE5GkdYv0QwPAhIySGVEIqVGsmVBTrNFqYfMJHpoY1MGApUWSLiN1hvtchmUzQW5pE1DaHp7MjH0ZYu8lMvx0JbwhzbQTVUKDdtpFKH2Z9N8dXbR7l9PM9aqcZ6rcF4PktalxjUfQazCTY7HtsH8/RnLF67WIGoRyPeg6ob7BvK8OfH50GWmNtoc++BIzA3RRwPZ3kRNfQJklmaZoxazzjLy0Xu2z7C0miWSttnM5C5XPVImB5PTKY4u1wjnjeJFAZpnT+DOTaBe+aDbrW0CJGTWdrtDq4fkhybpPHW/xetfwzhe5QvXSJ/aC+xL/8eYadF6AWYvQWEYfKLiHGpnkdleCdtLYomCcz6GsxdvjYug9VF5NGJT03SEWHISEzmDw/3U3XBCyFhqrQcl+li12/LCaBy1StmR2+cRud6ZdyJxQo7eiLErxYnNt3glgR50/G57MD2jqBnZYrWmy99Qj5XdNoEy/MwdwVp54GtwO2vEZIk4aCx4QhWyg7vzZRJGCa7J0dZvXiJtfUKfqbATy6s0xOPcWatTaEvjlkt0nEcJLo+JLYXEAjYePUlUl9Mkf7Ck5RKFUqxDJFYjL88uYwqa7x4ap5Cb4aqBy035MndBV6bKrEtLnFwvEC9WuNhw0W6soqtaLQ73e8QYYCm67S8EFuWEKvr9FgJzLHtOLWNbtUHXJOl1Cf30Hrxh0i+i7CiTBpx6mPbObmwiV+vo6cdVmodHt4xyKbfwdt9B9J7byCu+qzYl86QKEzwznyNR8fjhEGAIstodhuEwDcjn+mlFJUDHpzo4YXz65AroEgyQa2KJgse3dNP3l1Hue8xOtL16l0PCWvXfvyhXcTPnwO7g9Q/TFlP8t7lEpJp8sKVTQoJ45rPku0FvDZV5IHJArqq4PrXx45qtwhK69y2qwf3u8+g5gtEbr+HTjJz0xgKZJWIKtH6/p8Q1ipgRihKFnHAeeDLnHRNFuwE4bLMnq/9nxmX25jTZzDtGvbVr1NzecyoxT1hkepPnr1WRdwK2sgrs1i3343YfQjf/8WlBLewhS1sYQtb+JuKz5WASSQSDA4OAl0JskwmQzqdvuk9kiRhGAbj4+M88cQTn2dz/tYjDAL29ye4UmygyBK2F/DGlRK6IhM1FHb2RHl/toQXhNw1luVrh4Z5b6HKjrSOOn8Z99T7NDY20aIRItv38IU9B/jRLORMGdFqsq5EWLzjqzRVC6UwyMbyCuVimeFdk7wxtc7FqsfDuRhJWSET1YnoGtPlFqauMJC0aDk+sd4CX0v188LpRarVOp22TSJqkVE8Xj12HmX/MN+M2Tw4vp2aD6oMEadFr2iTmTlHc/oihAGNZ7+HlM4iR+O0FxYw0700tt/GtoEsM2sVZMAydJasPPv/6B9jnz5OWC6iK2BE0ni9Q0wfOw6xBJ3Ao6OaVM6eYt/Tu5ivC7x4Aj/fR1lSqKwV+bDYYe5skcP7D9N3IM27Z+dYPVVib7TCxZpPb+8IWmnpE1md667E3mwP0F2oCiGQE0lEu4UIQ5RUBjkaI5QlwnoVKZ5CiJBO3xgnp4qQ67t2Lk2GhKkg+T7T6zXu3jmOt7rwiX4QlNcpxvp45vQKXhCiug618hrPn2hypS/Lo5M50rLCunRrkiUfN5D+zubc/3bClRXUw3cR27EHubpBpeUihTpifZmed36CtzpDNpdn4MghpFSG9vwM1lf+EMWtk0tnUdIxrFiEpgNG0PVgEo7H9PQCE489jVTdYHhtA1soZHfvht2HeH+hyivvnuPQ/sfYq3UYaq2Rvucu/pdjS8hIDCYNmo0GpxoO6w2Hr+wdYjNUuLLR4Xe2p5GP/5D+iAwrJfyrGy5ZlrHffQ37n/5fuXKhgqwbNLN9LFdtAjnASilYqkzRlenJDxKbaJGWA9xWC6W8hBcfwm+30FWZjxjRIBR0zp9m395HaXZc7t+R58fn1mjVGmiWiRSGzGx00PotoiPbiY1tx+kb5XKpyf6+ONt7YriTeWJeh+zGPObl46ijOyiM9NHRgdAjoqmovo9/A/kCXSNqJfBJ1IqMxxNcqFwP6qYsnXxcZ8P2qdoehqKQi3xk+LsV/NUDn867r2HcYtNtnztFbNtO/GQWAFeScVM5SOVuep8a+HizUyipDGa+gHPqOO76CpJhok/uRQsD9I1VjkRN+g70cfKqF1ohYbK7N0ZGC3ADDX9iH/aVKXTVILBiEHgIfMJQIL35Uya2baeMx8ViE0WWSUc1ZMAOJTZ6RnBTA8wuFVl0Q/oHbufU+6exZIGuayyub3LH4V38iy/sZ3qjzYn1Dl4Ic5sdLE2h2vFw/ICUpXGp2CQzUuDlzF4qvszauRaPTUZpWEnmOzpTsx6/f3QIY73NSrXD5nqT0K+iGzrr7YCn9g1gERDzOzTX14noKhISba9rcp5MxRGdDnIsjnBswkaNZv8Q4cE9hPi4Lz6DleolbmrUmx3CTptwcQ51YIQg0vWFGEpb1/pvGIaEuw8SMSPdObhZx11bJv6FrxGU1mnPXALHQU1lMA7dgTcw8rn1fUk32Gy5n3q8JlRUoaCzNfZ+VQghoHcAJZ7qVkx8DOaBI7800RZICscXygzGFJRcAeZmcBwHsbqEpqoESPieh7f7AGudkL84vshT+/finztP6Djkm+tUoxkur6psSAqSJ7G4Wb92fiErbLR9Xjw/zzfvGGd+tcIetYV68QRGfQNkmUOTuzD6BzlXqeCGAqlj48e6UpM1VxAqGmlDIQhsXp1v8+ijX6Zn8Qz2xbM0M33Uk724kwd59tgc9Y5HX9HmwbsOYBoab89uoskSqYjGUrXN7rTKWhDBvf0pOvseRxMBuYcqpF75LtriZULdwm7aGA8+yeW5NeLjk6iNBm1U4pZFOHsR2zSx7n8cd/YyzsIckiQRPXAHlt2Cdgs0DT+RvimzPZBV3qsrHJtz6HQayJLESH8P9xzsJ3H6TYTvIVnRn0tkuMicL7b5cKlKy/GJ6Ar37+hFlRWmizVqXogiS+ztT7KjJ8r55esVil4gqNkB8ascna58tkykJYWEjRr+0vyt+069ijdzCW3f7bjupz8DtvDLoeorXCy3+eHZVUI/YL7UQJIkEqbGkxO7MKeuUFxexIrG6enrxdVqLFZajJoRDE3tkviSxLakRnBxFTORpWr7XBAJyrLGgUya1cUGLjKhopLJ5yg7IRsth1DApWKdw8MpljfbbCLzmFwk1moRCCA/CNNLIElouk4inyN6tVgzu3MnG66gd+8hJNOic/oDRLuJvn0bxqE7IfAJN4rIVgRJMzA/eJ3bh9fYf8cjzNoyykCOWtthZb3C5VoTK/T4wpF7aV71+QwcB4OQc8UGd44kybWreGc+oDM/DSJEKwwQPXQn7avrl48jDEPGEzK/e3iAC+tNSpkYPYbMnpxFn+rhWRO4V8efLMvYoULdDuntGeT58+ex5QJqQqG+1sHzit33ZfJcLDYZzX3Sv+nD+TKP7+njnSslNloOqtPBqKxz944cg4tnEJ6DtzyPX14n+tTv0b5BOtIPQ6xkuku+AG40QaPhot/7GN8/vUrLriLt6mWh5vDO2iIj2Sj35iZJSj79PTnUAZkwEmNPVNB6+dVr5AuApshASOfEMWJD47R/TT5ssizTCRWqTnetnjS21t1b2MIWtrCF3xw+VwLm3nvvvVbV8m//7b/l61//Ovv27fs8v/LvPHpNeHRnL69Ob2JqCrYXIEtweChNre3gBSGWppC2VN5bqLK/P4H7wbvMvvwCQoCiSEQ8F+WDt4m0NvmDh5/Cb1WZHdjDcy++S+C4uKOTXJmaIp+M8Midh7G9gHpF4Pohz66G/IOd+8gtXODkcg0hBI4XMrfRIjs+zqUwSsQLMLwOaVXQn42gltcQnRZC0XlnapWR/b1oBPToMiIMEYqMqeo4M5ewH/897GgKNfSwzr9HMHcFx/Mxw4C1Ug2zb5Dh3SpOtcLunaP8eKbCfw0kDvffy96dsDel4Bx7lel336fRdpEkMHUTIctEUinUVp1mEGWp7tGsNxGKSj6WxIpG8VpNWkac//nDIj3OR5s4QdsNmBMSY7l+1PXrXgSSbpAaHsKRP9K8FviGgdQ3hOY6iHYDISsI30fyPeRIDCF11Rk8K04HG7ybN4sSXaPWDTtA0m5t9Bgmc7w1u9klX3wXb2mWoVycycE8umcjuw6PZC3+cskDbs5CVWSJPYU4wce1+69Ck0Bt1sDzwIzgRGI3LVo1uplTCIEfiX2iZH0Lnx98AX40gRGGvDG/yvbN8xTffoPxfAJTBNjnPsQ+fZzo0XtQDYsgNY5db/Lk0QkuN6FncARlbrGbaSoEuqljJZLQP8LatsPYQiIIJVaTGf63d+bpi6mYmT4+6HTYNFPcrdY5NrPBwnKpm9kYChRdJ50yEMCxhQpfvW2UlheyP9jAdWp05mcxDB01FgfXRVUUED4dP8ARElpvHwt1B1nXMRMJ6m7Icq3NycUKxY0qaVfmiT33MHjhbbyiQBudwF8ukb3jXkLbw56fxV5dxl1e4MijEQJF483FGrYfokRjBJpGzNTRYyovNyWO3vYY3zu9AqtFdubj5BIKSV0iaWnIsoHSl4S9+/GQrvV7WVFRkTmyrYeKFbC6tEa1dl0uZaSQIrE+y8jgdi7Q1azOJ0we21ng5UslZjeuS/VEdIXHd/UyGJH/xmwGNQm0WgVht5FMCy+RxvsNVMjJzRpBZaPrP/AJCIKleeR0z8+9TpKmYySSNJ/93vWAr+vgvPUywdwQViSKvbZGrDDKo2Pb0WMRROAThgG1QOXNJZ8j8TgrjZABIeO7AlVSsCwTx3EJLpwh9eXfpXzqApLvoWkajY6L6weouo4Y3csPTq1z+2iOpWqHPzu1woHR7RwcydDxQxKmRsVQyMsytw+lOVns4AYh+tVKxUB0Nd8rbY9qx6fu+PRk4pw/t4wWjzOZj/Ly65c5uG+CAT0g0yjzT/ckOTfvsCHneKMUsNpw2D+UYaXaJqUL9uyd4IwVw+jUUQIPMxLDV10eGE2yeOkKQtVA1UDTMbJZzFQG6dKH+OurGPUad++4l+dPL1yj6YPSGvLwOAPZGHlLhhuqujxJIZjYgzGyDdlzEYpK24zA6A6sfbchhQGBbmIr6q+cnS5JEpIk3bJPSLkCSiYHK6ufOKbHYhSNJKmt+erXBls3iTz+Fdz338RdmoMwRI7GMA8cJRif/KWfb24oUeu4hKHKkT2HkM58QGg76IpM3XZRNQ0rXyD+4BO0hEUsYvDaxVW+vHOMba1VWJjGmbidotdB1lSKDRuBdO1J1nR86rZHLB6h3mjztVSLygs/oukJOp5HYNtE23Vab79K4ZGnGexNs2ILfFkhoioIIBnRyUR1dF8m7tr4kTjmvtsw73ucD+c3ObVcYfnDRQIkJElhZXGN2fERWkLm+QvrBCHkYjp/dHSYQMAHKy1euLhOqWFjagqFuMF9h3+XLzzsElm4iNT2md1oIRUG8e76Ej25FJlTp+gNWyTSUcIgoHnq/WvPPb2nAMtztN9746osoITWN0DkrofpxBJIksSZksObc1VQTMAlFILF9So/rKn8zuQhjHPvow6P4wOepOKHYCigiOuyQJKi8N5ii5OL10mVthvw07Mr3DmW4w9uH6LYDlistNlsdjh3A/nyEVT5ell5xpRIRXSq7U+SJzFDpceSkcIQSdOuyR1+HJJhEvwNmVP/NiCQNU4tNnh/qUaj7WIp3ZEkhKDuePz0SoWv7hintHmKsFahL7MddB2CgJV6h7xu4dZqHN5ewFy4hD00wZt+misnV5jyNojFY9R8iZWGTz4ZYbHSZigV4Uq5Sii6FaprtQ5ZSWVhpYRpm9QiFu5rPyKy9wDRex5gLBpHliVC2+bC+Wkq9RaqrlPLTTC3bPP18X3Y771D/MEvIEeilMpVNCdE2raXzjfyRKolYlMnMOoVjNYGa689R1KN0sr9Hi9N12k3moQCkpE4i4ksfek0dqWC2ZNnPlDxQ5dYp479/F/CRhk5DPEVjfWpaYLpBQpf+338qwl6H4cIQzJqyP3DUZBicNVkvoN63VtLVrhcC3hrukjT8RnORND7Bli9eBm50a00kzQdpadAw4hiCZ8g+OQYqNs+UhjwO/vz1F1BuDBLLCJjXH6b8AYpSeHY+FcuoBy666bqt9CKovb245fWcFHQe3v4sAattgP9w8zXHJptBxEK5os+e/qGWLR9YvEs/QMai5UWWa9Js3l93RzVVQyF7iMgDAjL6/ApBIysKLQCGSEEERX4lP0rgCQrXKkHvHGlSOtqpXxUV7lnW5aJlPp32mtxC1vYwha28JvBb8wD5t/8m3/zuZw3DEO+853v8MYbb1CtVslkMjzwwAN84xvfQJKuLwi/853v8PLLL9Nqtdi5cyf/6B/9I/r6+n7O2X/7IMKAHSmFwUMFVtshC5tdE76VSotK28VQZZ7Y3YsXhsiKQlDZZOXtN66t5/xAUPM9slGd5dNn2X3oCG0zwfOXF/E1EzyfjugG/otNh/fLAXf0RxjXTOJRHy8QzPcdZF8qTrr9LtVqA83USU3uZnF4P/ONkFppA0uW8ZfncRQJ4TnIIkTXJeq2j79tLz+6UOLD9RZ2x2ZHb4J/ctcYC4ee5sSxU3TcIrKiMj5yP/fuPoJ5+l06pSIU9vP/OLbM1/b3M7F/nD9+dw5LN8hrCovtkEu1gMD1iE0vkE/FiBoOpVobY3Qb7oHDFDc7lBNp7kzluFRqMltqkowa4PtE41FGxoc4tdqgXGuTyiTR7DbVtsPO3gRnV2tU1Sh9o9sRnoskK0iWxXA+iSyHXWNHK4Y+MEw4M4W3OIvwfYKOTfThL9J6+SegqMiuQ6hqGDIkx0epLC5/8ibLKr25FMGlzVsck6kn86zOlUCCsLrJnWM5crOnabx9ATcIWImZDPfn+OYDX+XHTWhf/WhUV3lgIkfOCLmVKlKk3cB59zVaK4sgQiTdwNx9ELHnIJ6iYVWKOMffprXW9cPR+oeI3H43dir3NyaY/Lcdsizjb5QZjynUX3oP09DQ7CZ+ZZPwqrxA68QxEl/8BisvPId63xNEGnUODw5gD34d8/23aUxdIClp7D20G2lxmpUXnmW26jCwexftycMsBBFWmy6ljkd/wiJHwIkL89z99XuYPlkEAR8pI2RzKdbbAdVah5WazbaMxU/PF/m/3xZFVjT0ZJJANwjzA0ieiyguIjWrWKqMapq0jARq6ICuYxoaNadDICmkowZnp9vocZ3vvjfLP7vnTgp79jFn5jjdTrFwbhNd0+jN7eDOPfuxpj7k0snT3Hn3XbghLFc1FmsO5lUSs2iHLFXaDOQSrFaaCFml6QTMbbbY27cN8LvZ/ICiKF0iVFHY9FReu7zB7EYLzXWoNDrsHhjm7r0GlZaLbujsSCr0nH0TNalhDPVjqBI5S+XVmcpN5At0g1TPnlvjm4f6icl//WPGctp4b71Cc3mB7k5YQusfIHLPY90g+ueJnxOM/0U2yr6iYu3aT/uH/+06+SIBjo2wO4SdDk2h8iOvh5UPllHPlNh1+wEOjWTQFYWfnC+Si5u8Uw2Z2L6L+sw5TEXFC3x8x8fUNOS+Qc4GCeSHniL63ptUV9dw/YDkwADSobv5b8sSgeRSqNmomkw6qjPel+H5KxWOjGZ442KJSqNNxDK5fSjF/oEks+U2pZaPJEmoUpd0lyQwNZkgEFiGwe1jPTx2aByjU+N3BmWcd35Arr5GsFmGyZ1MDk2wfukS+/ccYGbbJK9OF1FlieFtOZZmF3lo5xDLTj+iXmFb1CIqC5Zm5mi1r0t0SVaEXf0pMlGd0uIsAGGnzdjyKb586CDvLVbZqLUwNZn9Q0l2D6ZQb2E8HIYhjqrDR6a5V++FrZu/8P3+TEgydV9mue7SdrsVTPmIjCauB2K0eJzkw0/S+uF3b5C0A82KYD3wJFOBwT5ZsFUA8+tDOxJHffCLRFt1CHyEGcE1uhVSsiwjSdKnylgpqkoouj4EQRCgSYKIrlJuuaz19tLzha9hn3gXf3kRM51GGd9FdfI2/uuiwpJX5dBEPyk5YCIpUE+eIozH0PMFmh9cImlFsL3O1W/6iDSQyZkK1Y0VlESO0rt/SWPqEkYyAck8TdmkX1VoLsyRWJ7lDj2Oc9udFAOVlhtgaCpf3F3AD0ImRRXl3fMEp+ZoiCbtge1kJw/j+wFChOSzaTTLom07LG60iCeiEAr8EHb0xIgYGu/ObnBsfoPNVpfu7jg+C4HgmAxesc4drTZSbz+zcoFTV4q4FzZJTu5i3467kaMhsdoC0plj18aaJMsYY9tpvPs6wveu/XZvdYnwxR9ifOl3qGoxPlgoIgC1pxfh2IirSUD1ps2ykmPvXQ/STvVwqmhzermO7QVkojpHhtMMxxUIA2qexJnl6i3v67HZMmOZQXojMq9cqOHdIiAc1VXSpsJHg1En4PGdPfz47PpN8rmmpvDErl4MQ2F9dD+V/93/gFotkynNoX3wBqLdDegqiRT67v3YWxJGvzZUnBAhScyWWxAKdE1CuppAJkKBK2TKTkgkFkGWQgIh+MaBAaaLDcolwVg8xuR4ktjKDBtXLrF63xe5+MEU0ugOIppGse1hVVpIqsZELsq+/gTL1Q7q1WooKfBJmwotx8f1fNbtELuQRQ0FZjqD/8aLsLwM5RXcaIrJQ3eyXLNpDe/iR+tgtlZ5ObGdIw9+hdlXn2ejtEHikS9yvCZTn+7grtaIRBIceOwf06t4rKyUUE2T3kKO5xfatIMu0R+EgvVqmzcWNP7hHffjvPAj1P1HmW94DKUtzCvnaJ07ReA4NN0AXwj0ZBov2cPMa6/Rue9LZDKf3i8/y4tzuSV44fzatUSIpUqbXQMZyukBDhVi6Aq0fEGp5SF8ODCQotFx2NWfIhASQgh0RWKt1sZQZTQC+sI2neMvdCtgb/Gd/tIcyoGj3NiqIJ6E/mHUaAw1kGBkkplSGxSVjh5BRWW8xyAIBcVam0vrDfaN9/P65SJfPzTEG5cFeN2dqAREDZWhQgYlkwUEolyEMESSJGRZvnZdJEmiHqq8P1NjptQkCAWFlMldIxl6LXFTNc1HWLfhhfNrN0katlyfly6uE90/QJ/5iY9sYQtb2MIWtvBrxW+MgPm88Mwzz/Diiy/y7W9/m8HBQWZmZvhP/+k/EYlE+OIXvwjAD37wA5577jm+/e1vk8/n+fM//3P+3b/7d/yH//Af0HX9r/kX/PoRhiEmIeNRib5IjNWGR0SVSFoqAwmDuBJQdATT5TbjkQZuu/OJc3SuygPIG+usZaKUqw2yA8P405e6b1A1fCSWKi0ePzTKYDPkykaJiKoQmhEux/fRuL+PHl3CVzXerMJS2cYTLfqTJpuySWxwhGB9BZSrwSxVJbJ7D++vNDmxVKUZysiSRMcLeO7yJuV2BCOaJNA9fCQulTu0tSxPf+n38U68yxwxeqJNTixsokiQierUOh7Tpa4k0c6MgWWZDBw+hDs/Q+D4jN17Dx/KOV7+YBFfCLy8yeL8Ct88MkoqZnFhrUFPIkqx7TN5cA+vv34FIbryCmamh5VWwN7BBJW2y0bbpSdqgmagKxLf3JmiZ/EC3pULIEvoO/ejHb2f+tQ5xNWNYFiv0j51nNhX/wBJ1QkdG3NiN6Knj0NFh1eWV7sb6BuCU3pvgZ0jecLTH79vUlej92pQSxaCgimTWzhH/cLNWuz+3GWizf/Mt/7J/8C00zWhTpufXoZt+i6dl37U9ay5CuE6dE4ewwIio9to/vT71zSQgW7JemmN6Jd+99dWOr6Fnw/Ns8kR0vA9euIWTnERXdWQFZcw6Ga6hZ6L36iTVARXYv3sT6aZKrssDB5m785D3OtVqD3z33CqNfKWSX9vlEppHr1WQtz9FClLww0EcVOjJceIZfNUnZCU1Z1SJEnGSkTohBLVjgdIJEwVS1X42sEBpr02+WgO6ysPseAoXFnuejcdOvAAY/VFktkUhZbP8UsbdFwfPQqNzQ6piM62XAxfkvHMKFJEQ+rtZzoxjJOJ8t0X3sOr1pGFwHNdyhs1Xmp2+MOv/iGj1RYnZ0qsFBukM0kODKZ5a2qduhvQcLo683XHpycRYa3WJrgqjzFfrNOXVwklGWWjiL8wjQgFtbH9/PmVNmfWuyTKqBGQ9JpM1yJ4moFXd6iXFjnTbjA5NMzDmR4GtKva1p7M1Pr1IPC1NGwBrh+yWHPZnVH+WvXqdQTumy/irSzd8KrAW1lCvPZT9MeexpVvXYX360AYTaDEkxDc2sRWGxzB+znXJwxDlFS6W0lzFZIQCMdGMi2aqV42Tp2lExsjDAWu7XB+do3lUp0vj1rcm5G47MPJko07epSJ/nGSi2dw330NQo+OH5I6fBczxSqXnST5279Exm8hAe80JU7OOfiyz7Zc12zeUhUemczz3Lk1ntpb4N3L62Qkl4xfhZZMoxxQqZt8/UAf/6+3ZglEl/SCrn/Z7r4EnudzaDzPsTmFn14q8lW9iH7mGBkFmsuLiMCneeoE7vwC2v47OfeT58g9HLK2YVKIqiSCGLtG85xd2yCbSTI0mGFUdbiyssn5YhkpCEHTQdMY3T7C/kJXskTStOsXtrzOYPUV+vtHcHoyKL5LOifRvgX58nlDkmWmqgGvXFoluCGqko8bfGl3/mYT5HwfnUe+QbpZRtQqSLEE1UQPx+oSD+1IdrP4f+O/4G83fCHwb5CsUYMAs7bRfY46DvrAMCLfj32VnAsllZVWyOmVCm03YDBtsSsfJaMLDg2leOVSkddqKg9kRzB2eiTveZiSlePNlSZTRY3LXgAEeGkdP2by0moTJb2PnfkYE7EYh8Z6uLzpoKsy3keeXLJMLmZgtGsEzSb9Vg+dpQWQwKk3iMgybqLARqODbllI68vE73yC5VDlhYtF/FCgyjJOEPLlAZXkqRdYvzKNJEKkTIz26gqt6Wn+8A++hdCH8NdXqM1dQmR6aPTKiHya5WqHEysNHpzo4YPFbgX7xlXy5aP1XxCGrLd85k2Fu/bezk9PL7BYLGMaOvGeHqpovDFdZqM3xqKZJ9Z/O9ujIZmVy0R27qN14cwN5Mt1BI0qUmmVTn7bNYLDV3WU4TFot5FdGwUoJQoEEzl+OlVhpnQ9W329bvOTs6s8srOXnWmFWju4aSzeCAFUOj7bkjIPTPTwyqX1m4Khqizx4I4eLDm4xpkLIejRQ37/UB8rDZfNlkfK0hhI6OiqzAtXKswsNwgrLv58iZie5PEvfove5/8Lwnex7nkUt3fwlu2R5W7m/JY3zC8HxxeE4mpahixh2w7ZmEm50SXwhRDYXoiqyBzdM8rSZovXZjbRFYm7B1Psay+y9OorIALS28Z5c2ETJZbA1gwkWaFTbzGeizOST/LSVBEhYHehKwn7s0tFNqoO+3rjvHa5iCzL1NouerqP7N334R57Dd9zCQe20ekdwbUdwrOniT38Ff501SAnOWjC4+Ram+TEDtR7dPqSFj+Za9G0ZExNQR3bwabj8yfHl3lgZ4FOqcWaKtPqBBwa6WF5dgNHxMHu4IcuHcfDjveSfuJp3vLiBKHPk4Mm9n99jdC1cQJxTWrXrW4SkWU66xatzQrT5RS5X7aoWFF5f2HjpvkqFKBK8Ojuft6a3iAIA/oSFvsGM4RCEDMUyi2V586v03K7FErc1Hh4R56qI5jZaLMvqRDRDHA+6ZUGXWUHISs3Se26hoV59F5arz6ProKiatgiwEylODKWJlFegvnL3XXFtl2spxKgKLTdAM/z+NLODDQNWv1ZlCAg3HsbF3yLi+U2sgS7JybY1b8Na32ZYHEWJAl9eJxqdpDvn1ql6VwnsJYrHZ6prfDVA/3kPxbekRSVD5ert/STCgWcWKry1GQa8RkVNFvYwha2sIUt/Kr4rSdgpqamuP322zl8+DAA+XyeN998kytXrgDdReCzzz7L17/+dY4cOQLAP//n/5x//I//Me+//z733HPPX1vbP28IITDxGIvDtqR5dZPhEYagqxpL1Q5SQrmWtYTUlZACgfB9YoZC3NIpOQKn3aEsBLltk0RknbDpIwnB/fvH+MGlDYpNl5gm02m1eONci51DWZodwYcbPhXXpdFoEig6dU9wz3iGxc02847BxMgODMkjsDvIhsF4f4ZLqw2iUZPQDclEItwxnuGZE/Ok4xa5kZ2IRg1VAqGonAvgaGaQocd7yS7V+GJeoWbFqdseddtnpWYzktT5/R4X5cJbdD4souZMsoVewt5BZqMFTp1fIaIrKGYMLxLl0b40/+s78+TjRvfCNBzevVLk928fYvdID8dmy2ixGOgqIXBuucKR4RQxU8NUIaLK7LIC+NkPaZXWUHsKGNkc/gdvEagaiUe/jFdcpX3sDSRNRd+xB1+Ac+USSiqFlu3FVVTG+qPsuucOPpguIvseJj7JeIQH9o2QSCgYX/o9/NkpgrVl5HgSbcdu3EwvEUXQmzAp1m0m0xqNt87d1C8ShopougSlNSKbawz29F/dfIafKskuldZuIl9uhL+2jFTfvIl8udYHXQf/4hmUOx74zEyuLfxq0AC1VQffQ8v3kS4VWVBkdFng+z6NEKJWFEOR0XQVLZXFGt1GzRXM2jK3KQqW30GyO0QiMvbLP0ZtNzAtlbC8gvAc+uJJglwfrE9j6SNU6x1qHZ+a7TGYzBNGYhwaNzm20iGUZKyYyVrD6Y4hSeKB7TlCSeIv3p8jHdH5V48+zX/52UkaTZuUpaKEHs/VHXbt3MdteopkZ5oDg2mOzZa7skJCoCoSX9xb4Psnl2kEEhWhsdDROeRLrC3VqMd60FUTo1VDl0CORMkVeji+bnNptoSvaiy1As6W1pBVhSd3F7iwUmO21jVrNVQZRVWRgZSlsTMOnuNyoeiB3SGDS7xaZWN6jnWRpjpdJZ/rp2iH1NGIGzEWVjdYL27y1M4s52frhMBU1SW+EXBHv04YhrghBHSzu2XHJio8ZAlakoavG1Q6LpIU+WsNCqm1TeybyJfr8IurmLUN3HT+c/t+V9Oxjt5L+O6rN78uZIKBca54Mdyyx0jaIql+kjhWZBnVtQkVFXVkAlEpEdRrSGGAnM0jMj2sVRpoeY3w6o5cTWUIVhYoIzHVc5h3Tk0z5eo0hMLlksaopXHf6J0cjCWJVlaRxnZh7TvIuRMVthWSvDFdZmHTuyYVGSJDCLsKcd6e2eD+iRwxXWUkE8Fu2wyLBmG9jhGPg+/hz11GlmVCfTv/7kiK//F8h2LTJR3VeWpPH3IoMA2V77w9RRAEHC5EWXr1VZqVGhO5KMm+fuzlRUIhEBtFshosR03s08e58/CTKJbJdEvw4dvH0GNxNnrzzLod3tF1nh4x+Ob2GMuBjmdYDI2P0FPIIq4SGOrINjhz4tr1Fb6HtHAFE9D6BvDMCL8p9uKjTNgwDKn6Ks9dWMUNBIokXZUtERQbDm/NVXlsW/KaMXdSDegb7OXNaZVaLIvnh5gNmbu3ZRmKy1vyI58zVATK+RM0T7x77TXn4hnUbA/WI0/RthK8t9TixA3SVcWGzdmVGl/Z18eOjE5pIMm5lRrPBwl2jd/OtlycPz22QNWPs+IIhID7tmU5X26ycKnE4byFNrvA6rzCiYbCg3ftR1xYwSu3Wal0QFbIJyN8dXcPl987juMHZEyZehAgKwoSEn6zSSor8DDIjI0ijYyykh/k+8fWWK3bIEKyMZMDA0kG69Msr5Toy2doVmvIhklGCcgbEH3rORzdIlhZpmfXfqpeh9aPvsPw099AUzW+dqAfTZGotH0srau/I3GD/0kosIMQORLDT6SpilV6hofAc/EFJNwGxUDjlcsdvnVkmON+jNNNiafu/wYjfgW/uPKp9yYoFdH6dqBI0lXit+sHQzyBYRXwOx3MWIT1jriJfPkIAnhnZoORQ32o8mePI02REGHIjrRK9tAg59YabLRcehMGu/IxMnr4iee5EAILj+0JGSnZTTJyJJnXZuscW6hhqAaRbC+aYdKpV/npqs0f/P3/E/m4jtM3jC3dnCxg+C5yeY1gfQXJjKAMDOPEUlsFcL8gYnpXajJuqjRsn04oEVcDzHSEcstFV2VGc1FysT7MmMmPLlXxQ1hvOLiDKTxHR49EkNpNzJ4CcT+FkC0arsD2Qx7fO0CpE/D6e/NEDRU99LhyeZOMLvGv92aR5Bg/XagTSjKD+RQjKZO+qIaZ78Xr6UXXddpCoR6oLHVcAhGQ/uAYDx98iIuXSrQTPRTLDdSdvcxH8qgxi7o9RbC5gey1kQwLkc6jJ5O8v27zxL49zK7aTJXbbHplDg+leG9uEykax7BCdo1nOWerBEqeluNw/0QPyXaJDiCEhOPfPCa86iapwjBFIXFyqcrjoxGCW5CjnwY74BOeZn2pCDMbbU4u14ibGpoisVzr0HQ9fudAP76A/997l/GurncsTSEU8L1Tyzy9t4+1apPpkswTfROkFs4jOx0+Pqnru/Zjf2xshmGIO7SN2JNfxz17gv6wxbbhEUazMcQbz7GxsgZCICkK8twsB44eZmnPfcxIV/2dAg85apE9ehcbLZcfzLWp1K/PAWVP5mJnnieNTfTzJ0FW0DdLXBmVaNvB9ZL7q/BDwXvzFZ6azEDo3/A6bDQ+3QNqs+XihhLap75jC3/XEBMeXxz6xcuiYn8NSUhb2MIWfvvwW0/A7Nixg5dffpmVlRX6+/uZm5vj0qVLfOtb3wKgWCxSrVbZv3//tc9EIhG2b9/O1NTU32oC5kZ8fDOT1LsVIpc9icHBXhaX1tEQ3ew40ZVjSGkqkucykFHR+gaQ1pYordnER8fI9uZIWhpnyzZ12ycr+0QaNXS7iRSG1Pw6j965i7eOnePgzklsJ07JgfcXKqiyzMOTeX5weoW2rNMWGhWh8cRYL6HvM1uqMZQ08VWfEBfPdfGQWWu4JNIGuqoRNOsgBMlslnKtRfz0K/SulfGExOFdO4nf9QDNjoskBH+QqFJ57lkQIX4gOO92uN1ukC8MMi2PIVQNOdfDpmQRVxXOrdYRQtCwPWQR0uxAwlQ5sVjlC3v6OFNqY9hNpE5AEEtTDSSWZzb4+v5+JntMEkqIcuZ9OqU1tMIAitOh+aPvdBeggHvqfZSBYaKPfwVnZRG7XEQ43UCncF1QZIqOzLPnl4gaKkd3FHB9iBoKewtRUrJH4Pu0Y0nkA3cgH5IRQPtqVY0cBtwznuWHZ1YwFInWDbILcUsn4nY9WpRUhrBZR8oPfGagV5ZlgtL6px83DLzFW5ufAngrC2i+SyB9ftnyf1chSRJWs4Zz7DVaK0sgQhQrQuzwnUwO52k3mghJQqgyZjaLLnxCzwNFJrpnP42+ER7JSUjH3yBz4SIHEjnSGypis4TsdvCX568Fp8NGAzbKjKZz7N0+SanpEDUU/FDlSI/GhKjjGAp/cPsQ//nDVbwgJBSCgZTFE7t62d+f4JlTyyiqSiJi8qMVHzfbh0qJpusQMSNYPT2cDqJEGyHnyzZDgwlGj3THaMcPWK/bfO/EEqO5KG4o8PyQR8aTHOwxeeHYHGa1gRSJ0UgXyER0WksL7EiM8JPTywwoDiohmViWStPGDyRenSrywESOmc0OB/oTrNU66KrMWDbCvr4IRhjw3WPTDAc1wpUl1EScg3ceYlRNUur4eM0GVqSGqiWpewLJjOJLDsL3CWUVJAklkULK9XJ6ucb+fITU5hq2HWDV62QslWQ2zlJDwQ0FYwmDwPPJR27th/GR/MJvQtLvI/mWTz3eakH6c/x+IXAHxkh9IY337huElTId2WBjYJKF9AgfznYriHRV5ot7CgxYXUkNSZKwGlW886dwluYQhX6UWJQg9JHTOZQwwF+ex/UCOh0XdXCM6tQmkmkS1quITgeyPby3XEdTZVRfImi00GIJztcFC7aHefRBNhs2FzY6fNmxmOyHpUqLJ3bleebUMh1f0HB8RAiP7Oyh3HJI4LIrrXNueZMvjMW5cO4yzpXLmPle/OUFRKuBpBvIus7awjIH6g7/t327eTvso+n4vDOzwb++e4Dv/ewkwVqRUAj6En2E1SIRzWRps4mVjZBMRJDaLQK3g7F4mV09MWr1FkFcwTF0PphaJhExCfJ9UC8jFBm9U2fTHeJAIcuQ5yDwab71A/SDR3En9gLgp3swdx/EPn8S2bTwBsbxjCi6b2Pu3kfrN0C+SLJMzZOZr9rUOj596QhL1RbT5Tb+1edUzFDpT5pohMyUmjRGUsSvxmfCMKTXgKf39FB3BYEQJDQZUw4It8iXzx36RvEm8uUj+BsllFPvs3n4kZvIl4/g+iGvX9ng63tz3DscY29fnFLTRZElmopOVTaZa7YJQkFf0kRTZGY2OyQiFh4y1sAwQlGptR2mFksMyi533LWN9YZNw/ZotjqcuziP7vs8un+YjYsXSGzbQfvSeZBAVnUSwqNZKtL2PYKxfSTe/in/Yv89fNjJMLvZoen4xHUZ9dIVVEKSUYOMHKW1ukKuJ4OzvkR7ton58FPUPjyOUyoS3X+YPTtHabz3M8Z2Ps562wME+biOEBIyMtJHlMDVDPnxtMXX+qFTqxFXQrzZi0iqhqKbVO2AqG4QHxglECGBqtMBXrpc5u/tjHcDlbfSlwXkWJyEKhjNRZm+kWARH329YDwbYabcuuXnoSvlU3dDMqZC1FCveSzcCFNTyFkq4EEYkNXgodEYktR9fgeB/2lN7Dbn6jN+pS0xvdng2fNr2F537EZ0haFUBiOexJVlFgYKmAk+MZdadgvn5R/jb5ZvuAAykTsfxN+++9O/fAvXkNIFlipz52iWFy+uIzSdhuugdJoMJaLszFrcZnZY9DX++EINzw8ZSlrcO5xgKBNlxtzB3m9N0t8qEcxf5n5nhSDZy4KW4rWKQswyeHl6FS8QjFiglRYJPY+WLLEQDSlMvc8j+25HNsGt1XisN4n/5hmE18K3bbx6HSmWoMeK4iUMOl5IWFplSAu40jdIqdQkkYiysNFAOC6LV9bZnF/A0lV0XSNwXey5afL9Qyw2XPDjZCMau1IefugymTG5sNYln3IJi8FMBNcX3DGUQJMFCQ38D5fQJ3bhzM98og+KMCQyvo05RyGq/vKVl6oMpqpc6/sA2ZjJSye6e0lNkeiNml0ZLhFyZrmKoamMZiM0nADbD4kaKouVDqoEHyxWeGBbBpC4ktmPYuQYNgKylWXkmQuAwNi+i6Bv+KbfoigKzUDGD8DIDRJ7uI+Y5/GwHKH40x9RrtVA1br+bAgsTcWbmaJveDvjuQIJTSCC7twc7tjLxekNat4FJEUFVUVJZ5EUlZWZeaZ3DXBoYhdyGBC6HpdnV5AxkOIpgo+RMKs1m04A1g2VRaoMEUOh+knRD6D7/FCvW09tYQtIvsf8d//8F35/5lt//3NszRa2sIW/LfitJ2C++tWv0ul0+Ff/6l9dy4j85je/yX333QdAtVoFIJm8WQIpmUxeO/ZxeJ6Hd0M2vyRJWJZ17e8b//9bC9/l8cke/uS9Bb593yNIL/yIUrmCBxiaTH86xtDhQ1x47wTpfSG5/AANw8CtbNB2fGwP7tzey2tXNshogvhmibgqqAch9Y6LbG8Qej633XMbPz2/Rrnj0xu3+Ad3jVHvuBxfqPIP7hxFV2RqtsdQKkLKlHn+9DI5t05nZgEFgeP5RAuHsFQJLwTLaWIvzCEkCdWyYH0Z3YxjtBsEYUifJRO5eBxz9TLfHN1HONSH++471Ai7MhGKxFBcxw0CpPVVxieP8rPeIa54EpoMO5MRnjmzTAhIkk5UU6h2XCZ7YzTqTdbLdR4cijF/YYpmqpf5+SLCtNg5lKXUsDk+V+YP9uZIXL4AsoweT9B8/YVrl11IINotvMU55GSawA8QN5R66xO7qcsRfnJuibYb0HJ8Ki2X8YRC2vOoLdfJjuSvLYDFVWNGuLlP9lmCbxwcJFyX8KMR8D0yEZ1k6CBVK8iRCFIijZzOYjaqiHoVSVEQqQyuFftEgFeOxj69LwmBbBjgfYr5qaaBrNxgd/vrxS8yXm/8+7d+7N4A0+nQfvEHhI3rclZBp03r5Pukjt6N+tYrhD1ZJMMgbDYQmkbs0S/TsV28C2cY6ivgvvoMnXoFHRnV6sNbXcBKJLGnzkDYJQ1DIbqBqMCDSolH+g2OLStENZnfT3ToOfsapfeauK7L0dFRdt/9MFfCCKausd6w+WChwtszZUDiyT0FxtIWL5+aR4Qhek8vnqKhRk0UVcJvuZxba2KpglMfXsDo62fTk/GNCHObLaKawt3bchyOeBRKM2hnzpNnD6aIo4Y+7flprP5BWnqWTjzHmgN1TxDVTCIE9Co+djpKselQ6fgYqsrju3oJAp+XLqwxko0RdGzyVpbvvTHFHRMFRr2A1tBtXKp5vDpT5akjh0hulIBVgtomiUKSViBRdQJcM0pMBi2RRBvdTqAZ3YoEP8BZXaH1yvew8n0cnXyADxYqPP/eLKgamqowGzUYysW415Bu6qe+rFJuhyxWO10fj7RFRgdJfHbQ+Ffp85Jp/dzjf5Xz/qLjFSCUJPTtu1BiKXA8Plxscqnm0d68/nnXD3nxYpFvHurDlHysRpXWc99D2N1dtj17hejkHrzXX0DK9OCrGpIZARGSOng75xui63lgmHjFdeRYDDWR4rasSo8h86AIKYoEx1o6b6+7NF2fM8UWtu2SNBRePLvEzr4kj8ZaDDobHDmcYs2R8AwLR7O4VG4xP7tOqlpEu1xj38gkebfOVHUDWVFQVQWvWUeSJfAc0FQiKkS8DktvvsrKtgcoOhL/8ECWzYUFqsVyV/pFSIRIhJ6HDtiSihuApBmI1hoiFAhZwV5exkJiX1+Cd6sSWugj0llkXUPxHEaTCfYENRrP/GfKZoi+NI06OELkoSdxZqbQtu8CwJcV1MN3oU3s49xqnQ/nyrTbOsncMAdJMS6rKD+nP/4qkCSJ2Ybg+fPLXbJFlvlguYEsSyQsnWrbIRRdM/WFSoexjIUfdud9Sbk+DoQQqMIncy3NNbxapPc3e17465i/fpm18M9rl6IoeB9J2N4C/voyi6XGTa8JScYOBF4gaFdtKq5Mj+6TUUMyqW5Cx+VmiCwJJvMxNtsuk/k4V0pNBhMa6cDG9AWuHkH2XRqra8wrEvfuHuTd149x4MAkuWSEsq6wfyDFcNiLOPE2J4+f4dB9d8DSIl6jTiqfxF9dRAQCc/9hWgMjXKkJ3n3rAkHvALYW4b6RJHK1BL6PV63iGSGBaxMfGsaev4IuCYJIFBGGhLKMpkhoF0+S3LYdZX6KPyz4/KBuoEoyuwtJzq7UyCcMNprdKtJQCOKWzh/lO0g/e4nY49/AnZsGVYUwQPYc0qqKHXqIzVXSxvC161hpu5Qli/zAMO7S3Ccvvqoi9w0iQp97xzNU2u717HoJZAkenuwlowkWlM9OpFEkCUsOeHQyz7PnugF06FaX7kiq3NGjk3JruFbsWqXNjevNX6R/t0KFZ8+vMNaTuCkA3XYDVuo2wykTwpBivcOudOym6mtFkvBPvHMz+dJtBO13XiWe74O+vr/xz4Nb4ZeZW39lhCG3DcY5V+zw5O4C785tUJUgmYpx31iKBwYiLDV96obMI5bN7nCT5PJZ7PNFOrE0g9v34J9f5cO3XiMf04mqMsvvvkk+38ff+8Yf8cJim/GYjKHKSOvLtNwAVVFpOw7nV6vsGRtBHH+Jbz32NM3lTZT3XwLhE0QiOFacohRiNz1kxyEWMYjHDRwiKLks1uoiA4UMmgxT0ys8NaCxHthIkkTbDRBCYCgynqSgVDfJ5odQE0m4dAqr4+AEIWZR4h/nfKZTIxiawqWVKk/t6yOpdK9/EEgokRhhdRNjfALl4sVrEmQAWi6Pv2M/G4suk0M5FAnELfYrn5YcZ0iC/YNJXr9cArq+SWt159rxTES/yQPF8UM2Ow66JMhZCpKkstLwkK+yDR3XJ24Z/OmxOfxA0GMq9KqCIXOQxx+aIGnIBLkCrqxc28k5aBxfrHNhtY7jh8RNjSMjaSYzJlmnhlpbRk+YbLZdbC8gaelYmky17ZKfvsBDT++F0Ln2W1uhzIVagDQ4hhwGCLnbumBhGoCLLdjnt/F+9izq8DhKPoa3OofS24/SN3QTCaMqErIs3bzvDAMODaZY+RQG5tBgCoXgpvuwhS1sYQtb2MKvG78xAqZcLpNIJD7Vc8V1Xer1Orlc7pc67zvvvMObb77Jv/yX/5KhoSHm5ub4kz/5E9LpNA8++OBfqa3f//73+e53v3vt32NjY/z7f//v6enpufZaoVD4K537bxLiGZ+1ls9zaw0e+8JXyc9fItxYx0wm6ZmYoHX5IrmwjXHhOF/58m7++GzIkgk7s3G0QDCQjrCjx+YevUbUa+BVq4ieLJVIHieR5UxD8Mrb55EMi1AI6h2P5brNo5N5Htjew4eLFY7NVZBliZFMhH92zzCH4z4/rm6gqzK2Lxjuz5GNGewtJKg6AeHyNMJzkXWdSCKOtLZItu0iKkVyRoLI2jzUK9iKQm58J43VWcTlM0z0DjPbDNiflJCKc3iuC1YEbeEyvfRjKxF830NVZYJurJmIJhOIEEtXiOkKluITt+s8Euswc9ceXl7usCdqMpGLEloRlho+mmFypdTisKQQ6x/Cn72Mqn5smKkqihUhuHyB6D0P4y92F+xyKkPs0FEWOwqoBhEVkqbCnaKMe+Id2uurtGQZ/+Bucvc8gDY4esv7GnbaBBslsgSIiWEadx3Bm7mIVN0AQuThceRYHH1iF978FcLpKQi7GViSYZK8+yGM3QeR5OuLWU/4cOZ9CAIcP6Tjdd9vqDJGLI46Mo7ywdu3bI918ChWX/+v3F8/Db/IeL0RfxvG7kfonHq/q1cc+ZghuggIKmUyf++f4l48jTN9iaDdQe7JU/vZ83ilNeJ3PUDg+bC+TKTQvT+hoeFsltC2T2Ife61bDQcocjcPV4QCfXiM7UGNe8ezPBRpIV56hdnNJmO5COWmzdrJ8wwvL3HnN/8h/22hw4/OLCPTzc5bqTtons3hQwXEyjzCtvEkCTUSQR8dJVxbQwtAjQwTM3VqmRS15SWSsThWJoahxogZKofiAa1nfohXLdETkfFffZaJ275IyW4TyedpFdeJxRKs1Dv4QUjK0ihvVgmFYLuqktNV9JgGmsZA0qDVbPPshU00VcFQJPaP97BeqvF/3J8mevk9GutrRBWNgcl9XIj08P1Ty/zh7SPEejawq1U0WUISMgldIaKrjGWj5NJxhkKF9WZ3U6y0qpiVKpFIBCUeJy6HXCw20WSJh8YSjElN5OIM0VYUaU3Qs38vSjxOpe3y7Pk15jfa127vybUOtw2nuX97D5b286fxv0qfD+Ix6B8krG5+4pgcTxIf20Yq/st7O/2y4xUgV+jj3GqNS632tWfjjRCALRmM9qRpffg2lizdPCbWlog/9CQi8BGtJoxsI5HvZd5PMXdmHlVVu2RIJEI0EefenMB89yeUF5cJg5CorvOlyb0MThzlL6dbICCuwO4EzJRs7vUapCvLtN78GXqlzPaDRzHSGWQBkwMTVA8PIOQhOpfO0ltdxpg5x8GBIV5tuYStZpcYCLtSfaHtsL8QZ/ODD8joGn84ovP2QoXIWo1NVyIIBSESgQg5U+pwx9g49SuX0WMJAiEIJblrXi5LGANDGJfOkbj7QaS5C+jmIKrTRrFDsAysnjx79Qqbz73UvU6WiSRLBCsLdF76MfGv/B7WVfK9UCjg+gEvVIqcdoG+GIok0wTenKvjjqR5aEcBRf58ghdrdZs3z86jmxY63Wz71VqbAwMpzqw2KCRMEF35pFAI7FBiIBmjN50kGzOu/Ybfdvwmf8MvM1Z/kXbVQx/l43PVVUiahiTLRK4eb7s+i5UOnRsC7NMVh9hgirFs9NprjWIdTVFpOB69cZN0REN2O5SXFwnqNUINAruDlukhPzJI2G4SWZ7hqaO7+OmyTbNWIu21UPpz1CWJwYP3c1s6w9TxU4zc9wVyXgtzdRYn20PP5B5W9RQvzDRY22zQsH10pUQ10sN3Zxb52uFhzO2TmFPn0Qiora4Qs3TqXoCKILpzL87KAmlLQwQBWjyO1GlgxOOEs1M81TdMw8qiyDKGFGd72uDZ00us1Tsoms6XJ5JYZ54nnzLx7Q0iyTjtShURBISShKRq6IpGNpegT3avXUsAzbBIP/olWi/84OZnuqoSue8xjPEJUlfXfP/7VIKFSpvVmk1EVxjNRulPmqiyzKTa4sRK65ZJ4pmIxmhvmpip0SsEvZkEU+sNXMdld3sZ/fz7GKfqhLKCNTyGeeQ+tMIvvzb8YKGCrBnomkbU1HH864Hmjg+hrBIzVfqzCfL5m/eUfnGV+vrKTdfmRqjFFZjc/Vv5rPirzK2/KgbyIeWGwwM7eglCQdJSuxLIDYfXp+aJui3ucxeo/+ynhJZBW9JZqk6z5+KHJHbuoRSJs9ZosCMfY3ggz6akMNRaJ1Ku48+skhsbQjFV4vi4AuRkDkmRsCQbbe4csXN5jLMfoiaSuK4DX/gas//L/xtkhUCAHwS0dQM9Hie/dw8vrTlM9KexJZ2+fJKNVpKoX2PE1FHUNfA8XC/s+qAoCo7rs7MQp7q4iCJCDE0hCAUZyUc+9goHn/g6z1Wj7BvJs3MgR8y4vjjxpZD62Q+I7DmIum0X1QtnEX6ANrYdBrfxmp0gFQvY15egJ93tj6Fj468t4y8vAgK1fwi1MIB8i4SYowmXigPT5Va3ekOWyCciRHSZdERHvWEPJykaPZaKE16fn8Omf21/WkhFObVSR0gKigqbPvRkMpR0ldNWkqf2Fm4i8Zq2x4unV1iquCi6SUTvyuq+u9gEVef+TBRhqiR6Ygz6IW4Q0na7+8exHoNUVCbXk7ppn1ntuBhmFV++LgImPBdXksAwIAgIS8Vum4ur7N9jsbgKdNoo7SZGz/Uxu68/yWgh9wniMeUGVL2u7NtH3JYE7B9Mcmish6j+W5+XvIUtbGELW/gbjt/YTPPtb3+bf/Ev/gX33nvvLY8fP36c//gf/yN//ue/eKkfwJ/92Z/x9NNPX5MSGx4eplQq8cwzz/Dggw+SSqUAqNVqpNPX9VJqtRqjo6O3POfXvvY1nnrqqWv//mgCL5VKBEFAoVBgbW3tt9a0UVG65s5hGHJXn86OTJbZWQctM8rY9l1EG0Wab7+ChCBjythBQLazyd8/MgSSzFKlw3yljev5fCVaZf17/4WqHxDICgKIRiLs/+bf4//yQRG/3UHRDDRFRvg+dsPh1Cx8Y1+ey1LAN8ZMAiSOVwKc9XUmSlMcGc9zYWmDw0d2caZs88dvTfPE7ROszG/SjuVI9/TTbLVpRyN89YlRjHd/BI0aGQnc8jrCd1F1g3CzTDSdA+GR8Jtk8yla01N4XkAqk8QzIvRkEhTq4Ls2027IZqXGeC7KcrVDNqKx2bDJ6pDsVPGXppgY2I5aWmVoJMYhw2Zxs8XUh7PIA8P4ZjcoMC3r7MnkkTo1qFcJHbsrmyDLCFlBTqQQ6RzCbhNGonjRBNrEbsTwOGUvoFi1abfbKJLEbXqHjef+EnFDBl9j+jJibZHIU79H5wZzW0mSMDeL2G+/ir/RlQyTYwkSdz+E32kSaF3y0wtD1EQKLRLDv3CKTqdzvS+327R++gwx1aCTzFw7tyyp6LffR+lnL7K00cALuhveSCZLfnQfuVQU/8pFvNWbPSO0wRHI91NdXf2V+mxfX9+nHvus8erfIL8mSdLnOnZVSUK12whJwjcjBJ+zTJSiKEizV3Da7Vu/YXYaDt6FevAuvNkZ/Ooy7rmTQLd6oTl1gVhPP5W7v8SqJ0MoGO5NEV9eQB0cQekbwl9d7Hq4hAJZltH3HcKt1xGBT0SB9rlTrK1XQZLwfIGm62w0GghZZmqhyOl5wbZcnLV6B0tXKcQC9PIqZy+7jI70ceXcJUAiaPiES3OEvYOU6zb3DGR450ITSfGJZ1LUSht4jRpDO3bwxUPD5I+/iK97aLqHt16k7Ydsc0pMm1GKqoKQZGhUEbLKQNLi4nIFPxTELY1CNsFIb5L1SpOFYg27UuH84iZf2t1PPBGn2bbZYzqkbMHqq29RWVmjYfsIWYLSq+zYMYk3ejvzq2XuO7SN149PUQ3AVCVcP8T2AgoJg//t7Wl29yW5ayzLaq1Dby6HtrZG23UxI3HOnp+hv13nvkPb0N95kU65BCLAJaR5/j2azYeRCwO8W1O5vNIiNEzCG7L53rjYJmsIBqxP78u/ap+37ngQ55Wf3OT/pMQTWHc9RKnVQTRv3fd+HeP14+2vNUPan9bXgVqzRcXZwL58gdD+WIZjuw2VTfThcbRHvoIHKJ7LcCcgXgloOD6YFmGtxqGBOMa7L+LVawSNOkgSkt2mc/I9jkSjrI4e4vBQCnt5iSvnF/nawWF6G0Vab72M0m4Sv/Ne/JkpnPdeo/3Ut3h9ocHM++8hJ5Mo0TgHwxi39xSYqJdZGe9nbqVMqCgQBkhCsHe8l6H6Eivb9rKa7MXzTRTTQjV9+uSuebjthQSh4MpqhUMHj6AXu0bWlqHhlVuoqop15F5qly+R3rUXJXAJV+e4b18vQ1oZSdUQ+T7sWIbOsy90/eIMDbXTvEoEQdhq4G6WsR2XHLC2tkbFU3jvyuotTWzfmuowHJeJy5+Pge10XVBrXJc/6gTQ6LgoEpiKhCJJXCk3r5l/l5o2h/qT2O0ma83Kb/267fOav37VsfqLtkuSJPRcL+3LF255XDEjFBIm7bkKQurKzN0oYZWN6lRbHb7z3ia/f7CAQfdYWlX55r4cf3lqGVWRSAdtcmGNlVaLlKkRtBvke7IM7hihpUaIWAZmNGSuHeLZDj1ujUxfgVenN9nwZXBWuGOkwH0P5XFPvIk3sQPN0Ok021QuXaZ128NsbCxihAGeDGGnRTSWpongrStFRncVGDp6FPP0WzQlCdm1SakhaiqP2lOgc+U1AruDmevBW5onGN2Oc/ZDOgtzdGyX0W//a4LaBpNWhoZQ2HFnP51A0Gl12K67VJqbBJpMYmWGR8czPHeyhhd0g4giDLFMhcf7VJRmlXa7G9w0NQU1cChLEsaDX0QurxNsFJGtKFLvANVYArF+s8xsXoZCVgZCetORa/dXl2X29Vq8O7tx0/s1RebojjTN6gaNq/1AA/ZnFIylFZpv/IRQhNh0n73O0hyt0x8Q+8o3cVNZHPXWyXm36kfrFYd2u83KRsCufJTjCzfL1jlO1zMxbwhWP7b2tBpV2s2bK61uRLhRIgp/Y58Vv6659deNxEd/dKDUqdEIVTrtNoe0OpuvvoBAIrn7IE0jyZgM8bnTOJ0OhS8+TbW0QSWwGaqvkIpGcZ7/C8YOPMVaTwapUsZdWQRJRlJV3NI6B27fTVqBZrPRrd4PA0RtE+PJ3+ONuQoDB26jfvoEftBdvgaug6TnkPffSfX0KsN7t5NVZf7irSnqQqUQttieNvjyo0f4ySvHkeNJ3FiC0AvIxkzu29HLz16Zw/d9JGD3SI74+iwbrotx4QRfevjLZCyFxmaJG3uWJMmYdzxI47WfdpUChrZRarm0W7BpFCh1XB6byDF0dXwZgQvHXsd+7w1EECBFomBGUHcdQD5yD678yZDNPQMmu3sM5FqVaGWVg94SaiRFI1rgeFO9ZlCvCY2jwwWurG50528JLAUqvo+uykzmY7xyaf1aP9FVmTDwabddPpyz2ZNVsaTrfWjNlpla3vhEewDeumQzeVs/aiyJt7KIJMlogU9SEmBqhAREJ3ZSLJVuqn6TFYV8ROZc9fpVlCRAMyAMGNV9WJ7tttH36Vu9xI7R7Vwqtwg3ivjROCES6ajOrqzG2traLdt3IKswEs+y1nAQQCFukNYE9Y0S9Vt+4q+OzxqvW9jCFrawhb+b+BtD9fu+f03f/peB4zif+Jwsy9cWzvl8nlQqxZkzZ64RLu12mytXrvD444/f8pyapqFpt7Zhu1H66W/i4vzjkGWZdqhQtQMkRaFmB6xWGxiqzPZcDEOVKDdtDqckwnPvoV5o4AchXthdPKrjE/j5MSrRHF4geOHiKnMbTQxNZZgm4tjLoKg0XIHvXl3oqS61V1/gzm0P8dJmlSAUSJ7dJSKAlVKA5iX5g/mXmFos4yLzxMHd5MUozsUPeHBoggP33cZ35hwWqx0K6SjLcws8OtLHZpCi4wUk8lGSpsY7b7zHYHY79x9OoM5dRAwMIWoVRKWMlUiw2TtEMHkAt1Yl0W6gKjJm/yDLDZf6pk1cRGlEktw+EsObq3B+ocwTh7fxzuwG7UoFXVbI6yq0WwxuH2U4ruO/8z72ubMkA5X8vtu5UEgxe8Misth0YedB5DefRUqmca9u9j6qMFESKUIE6tAY0v6jyPvvwPmoP4UhSbM7LIcSGuHp128iXyRAlSVCu0Mwcwlp35FrC1irWaP1/DMI93oZetisU33pxySe/FrXC6RWBdNCTmdp//T76NyixD0I8K+cRz5y/zXphkAIyv07WL3bIlJeRrRbSNk865EcL8/YPDAR5+DDX0JfW+rKjEgy2rZJwnw/tqLC5zhWfpHx+vHX/v/s/WeQZOed5ov93uPTm6rK8ra7qr038N47kqAZcubOcjmjvZJWujc2VrEhRexX6Yu+rCIUK+nuajc0c2dmxyzJmSEBEiRhCXQ30EB7X97brPSZJ4999SEbDTS6QYIcEkPTT0RHdOQ5dex7XvN//v/n+VV+u4qiYJXyuOfep7G8AEJgDG4hsucQdiz5a+snwjBEi8Q+fQdVRaoq/uoi+fdPXNc1bpGkhBDZsZ9jQZqL42UC2yYIJNqVZQ7vuJv7YyrG2E7MvYfwFmZAVTEHt+JUypRnptm8Owa+R3O1ZeobMzTKTY90JsnY4XupZTuZCWMkoi5VNyQbM4ibKh2KoLFc5dLVGn/w1FFmr0y0zHVNHbfRwLMdVAGN/Dq7u5K8uxAST2fJmiapdIr7uwx6588j5q6SMKC2vozneAhFIXz7FZ68+zHyQ/2cz8QRQrK3q4u432BL1qQjlqWnI83ppSrHlhtYKjy+vYcdXRZDuktvX5yM4uAvnyO4epHq9AQd7V203XcP598/T6PS+o7z4+Mc3n+ES6UG68sb/NGTBzmTdyk0PBKWjqkpvH51FVPXOLtUYbbQYFsuweWlZS77gsf3PYjRLGMrBjlLkDp/jPLMOLpu0JGOEXGaBIsrlP9qkvg3/49cWtHwC2UUy0Lp6Cb8mMzC+eUK/aOpmyRWbodfts3biTTGs19FKWwga1VEPI7M5rB18yZ5i18Ev+j3+uHvKVPj0+S5FQFJQ211Mz9DPkLa9nVZqhBfKERiKi/ev4OZos1UvkEqbbDDXSTYXKSmRygIQLYkymQYUvrgBM/9iwMs2g7YdZ7u0ugTDby5aYLZCbRcD6Jp489P4z38Bf5+xqZYK+AbFs2VdcyRJMcqGlpqkOGpV9lpNdl331Emr06jK4LhKLQtXqbafzcvXypQXi8SVuPkV9aY6U7y4nCM+/aN8M7VZaTd8hp66co6D9//HLsToK0vwdAI7Vu3YheLUK3h1orERYB//gPk/DRUPcq1Jsqls2z/8tdYdJsoikJXKgL5AoEVRRECqWrIRuPG85ZSstnwbku+AHiBpGT7xKO/+v5OCEHDuzmAqFx/z+/NbvLcnm7G12uEax/5wDwy1kHTdbiwqnCg07xxD78N87afhc/zHn6Rb/XnXZeUsiUtE32fsPFJHxGBtf8uOmIag20xrm00biJfFAH3b2lnqVDFdgPW6wH9MYgU1nHPnmSs3uCbg3tZUgwGZY3AaDLbnqReb9AzPIBo7+Q7F1ZQVI2xoS4u1atE41GG1SbmyCDfubiO7/r4RpQgkmSqqZBfcPjSM1+naaiob3+f0sIieiLBcs3F8QI0IYkKiaep2KHEUKBcqeFqnbT1dBJJPoK1uoKqKij7j+I0Hervv4WQIXo6i7e00HomqTRKLE61XEb6AbU3fkjx4S/z8nvXqNSbmJbJ1q40Q04eW/GINGs4jkomkaDnH/6cbzzwAosiRskJaE9EaG8W0F7/e7Rv/hsQ4IZwtD+LoYBA0FR16OxDue7l8OG883YIguAmKSQpJQQBB7oidCd7Ob9cpuYE9KYttudiZLTghmcctL5bPQzxpq4hFYEIQCkX8dZXWp6IxU288UuEQsHafxTb+hnzmY+1o0y01SY3ag47etI03IArqxXk9baStDSe3dlBQr35egBC00KJxQnrt/c4Uzt7br7f3yL8MmPrL4rWOw0Qvk+oG3ya5XRMlXTFddLlCk62neb++/n+YpW5qU1SyQQ79jxPhyGZX6xQ3KxTqjZ4cP8+di+exS1VGLRCJiIalc0yKAqEIYqUJONR9lBCNG3ItqP29ONe+ADRnqNipTj91inKQ73seO5rWNPjSKeJ6BtmI5plKu/Rg02hXOPd+Q2sehE92YYwkozPzNJ0Pf7VVx/m/dkCm9UmubiBJn3+/J0pjmwZJpiaJZeIcG/KJzgzS8rSidSLRFUf9TbtRUpJs7uf6Bf+EK+wyfpakXi2HSfWhteEVNNjqWizrSdAlSHK5XNUXv6ogolCHsWK4EuJ2dkNQ2O3nEPFp7+Wx37z+/i2jVp2KDU9VNPkkUef5XWZxvZ87htpo8uSPLqtk59ObuD6IQlTw9IU7h5uIwhbFSopQ0EXklTMRLnuP+X6rZiApcgbbWC16vBpcPyQDSdkaP9dhMsLyPwqQaWEDEOUSBR9aCvG8Bjh9co19bqsoe/77O9JMLVRuyEtKCVo2XaidoXtep2g+BHpo55/l0cfzTG2b5DL5YAwE2VLLsFg2sTCvWXZ+WG1TxAEpFVJJqNeP4fHdd1xpKLhhWAosqUucAd38AtAVRWe7bdus0WgqiFB2uLDVUxcflrveQd3cAe/6/i1EjCNRuOmjNVqtUo+n79lv3q9zvHjx29Uq/wiOHToEN/97ndpb2+nr6+P2dlZXnrpJR555BGgNVF49tln+e53v0t3dze5XI6/+Zu/IZPJcOTIkV/63n4boCgKczV4bXyV4Y4EP53Ms1Zt0hYz6Yjp/GR8k225OLqQFFSFwSZYoU6zd4RmNEW0t5djU3k2rpXZZvUwv7HCfqPJQ10eNpIB6eA5TdqTUZB1qk2JIgTZuIlbKjKsNlCtCLbnoynXJ6dCoGgqslykcuKn5PpGkFaUhF1GXZhCDUP0pRnk1gOI1QVGVIXqmoOnwWk9zuxqgUzE4JEtKU6dnkRzQyY26gzffzc7y+vgNtF2H0Bpz7HRvZVvn5jgsW2H8d75MXqzip7rYbZg47geqQNHOL9Wp1RY5/RynG88dRfr+TL1eo2nRpKMFy18oZDCY1dvH7uq8/h/8R9Bhmjt3TQLTexXX2bHXfdT7z3IyvX5qATsZAep4VFE06Z57n1ks4GSSKHlugkLG4ROE237Xpyf/ghj1wGCbA4N0Jp1tigqO3MxkoFNY+3m7L1kxMBQJEjw5qdR9xwhvP6u/Znxm8iXG+3AsgiX55EI3I1VlFiSiGkS1Cpg3W6iAMHmxk2l24qicHm1xvt5MLV+9IyC7QQEdmuC+sF8kZF9XRi9wyhD2wikIAj934sJrFXapP7D79707J3xS3iLs0Se/Rr2zyJJ/gkIwxBtYATOvX9bY11jYAteLIk6O4kejeHVP5IN0SMRVrq3cfb8IlpnN361ArqJLwPeOzdJ99P3sDWZpv7qS6i5boSmt7yMzCjJL/8p/3k5xFJhezRG0tToTkcoo+Effpi/P7eItbxIbHCE6Y0auqrQETcpVW1ylo+pt+TMksUV/uU9w5xZKrO8XkZoGjuHs0gheOv4eUxNZddQN73DWWLJAToVl66pM6iNCk3HRqTStD35PMaFM1QX5gn9gPD4qwyV1xgY2cWmleC/n75I1XZ58eH9FPQ4f3dumaobYmgqccvg7fFVZtYjfOPQCGlRpfGD7xJUyxhOE6NWwisVEEuzHHn8S5x4411cvxXQSRVXKGuDhDEdYVkc6Ivw6tV11opVvDCkPxNhpepiewGuH/DoaI7qYsB6ocL3HY+vjyUZ7MugWz7Vn7yGEIJMIoJZXMOt1dAEiDDAnR5Ht9tR9ThBvYYarUH8Rq4pdSdAotASf/jVQ0rZykzO9ULupg2/lvP9LKQNGO1MML52a/byWGeStAm+jKAPbsG5euG2x9DHduB87NqllERw2ZXV2NfZBrId+cpJSktzmLE4Ax29bNQ9mn4IQiGlwba4ZHKhwM7yHOmohn3iLOHqEtJz0QeGaJ55D4CldD+bkzMIVWn5X4QSpbBJSUR5PxBke0dpHHudztDjsF2iOXkVvVlHfew5Xp6pUWs4aH3D2BJGslEIQ16ZLvPlHVnatndweqNJ0ZUonkMqm6Y6OMQZtYfqyjJP1T1S5SLR7j60ri4Ur4mlaiAEY4rKxsIS65tl7PkZupIWQaoPsb5IuemDlBiJJJGuXsL2zpsNd3+OvFiLFPnF2sbP07r/cFtHzLzpN1OFqKERhpK3xjd4dlcXPUnresFeiOP6zFUcCnWXHR2/fXJCv4toRmJEn3oR5+TbeMsLIEPURArr0D14vUMooccTo1my8Qgl26PhBnSlLA71pdmoNLDdVj9Xd30izia1V74Lvo8QCrnCG/TkulA0jZXxae7dey+TdoxMXy/fPT1PJhGl3QSrXqSuR/lgdpPtRwY4M1/AqVZR0llqtkcQBBR1haIT8MqCjSIELwzsYO3SNDgVnIGAuh8SNzTU0CPRlsHUFTKhgRp4DJYWcP/i/0lTM4gcfYCa1LA6esj/w9/Q0d6JcJrgOTihT/TeR3E38zTclqm0lUywli/TXFqkWm95A+bLDVaKdQqDHTyc8InpOhgWQRAiNI3oP/xXtscSiEgEoajUGg7WfY+yabsIDHZ0JVkuNri8VOToUJaxrN4ysf4nVOiK0Kfbgr7RFFIoCBkSBP5Nw4LlObC6SDhxmXB1kejgVnBs6hOXEaqKGk8imw38iSsoPX2osxOYOw/gfBrD+zF0xXQSlk616XFlucRANsae7j5sP6A9brI7FyGCd9t7dM0I1r4jNI6/ccs2JZaA7v5f+rn8rsMIA5T5KdyLZwibDdR0lsiew7idvbfMQFQZcN9wFu/yPMV99/Py6VlU3SBqGvipNk7OF+mLqTyX9WjMjhMOjrLmeEzGetja1o62MsfzuU7Oqx3MrGoEjQbDA53sSSmIV/6OSlcnxoF7WS3VsTr60BNRhNP6XqfnV5ksZtAjPegJlcJcjaY3z6F7O0i0Z/nhdJ6MEuKVy+iKQtA1QJhIMrNRI7dcZvHaBBEF5psOomeQmKlxbqHIHxwcJfrBm1w6MUEgJXFDIx0TTM+UGevNMhATt4xjYRjSjCb50XLIrG/gr0rgo4qtuc0aoz0Zuiol6sdev+WZh00bUVjHu3QWbXAr3ie8NI3Aw/7pjwgadQTQkzSJGlrLd+Xtn/DQC3+Ime2kOwoy8NmWUek92Mum7RNKSdQ0mVqvUnN8+pUm5PMYBBgVAzXbjowliJo6pspNQ7ul/eyEWVURyHSW6L7D2CffJigXEbqOPrgFfetOwmoZUzNgZQF/dhKhqES2bsfM9fKVfd2cWqwwV6gjEGzp7eJIWx/J17/Dh7XNihVBzXXjz0/QtzTN2L6jyN0duJ7XIlQ+BjPwUdaX8SYug+9jDo9B7wBN46P1b6BozFd8zixuUHcCMlGdg/1peqICwl+ft90d/I7B95n79u2VfAzDwHU/8srNfvNffF5XdQd3cAe/Yfi1EjAvv/zyTXq0f/Znf8af/dmffer+X//613/hc/zpn/4pf/u3f8t/+S//hXK5TDab5YknnuCrX/3qjX2++MUv4jgO/+k//ScajQbbt2/n3//7f/+pfjS/K8h7Gn99Zh5NVSgulpnMN7B0hXytVTVUqLusTub5gwO9XF0tsfO5rzA1t8qxS/PEIx5Np850WSWb7mSrFdIxc5zCtWus+gGZeIT04T1shgFzRZt2TRKP6cgwpFmtYqWSqIGHNCMI2wbfJwwlhmWQ1QXJ0ip2EBIVIR07x2i8/N8pGzqqotK0bVZ796EIgVuvY6oaQSzJuitwjCgbfogvdHS7htXTR1gtc+r9Swz7EnntIt74JdT9d1NKDeLW6/z0ms+jT79IYvEq6ytrxOIqqW17uebqrM2toYUhsuhwbWaFI/4a6DqWVHnq6HaKGCiKJNusUPu7vyW4HujWG2XS8RTFqk31whl2bDvAitOaGA+0xcg2i9QunMLoHyL5rf8J5/138PPr+CuLCMMg+vAzNPMbBIUNvPw6qbsfpH75PPWVVgXFQ91DuLsOs2iaNBwHASQtne6EcSPYrpiRG2aBiqIQLC/c0gaEYRDpH6L2vb9F7eknUFufvHBstMD/1ECqmmm/YZD64fFXrhs8On54k+Y2QLXp4aIyW3I4u7RG02sthA/2p+iy5C+dLf/PBSFaJug/L0ihKgrexdO3Jb7CRp1w+irKx6qUftVw0lmi9zxE48RbN5EwajqLcfheGmGIHk9g5Lrw56aRQStIGhneyum5TaSigBXBUw1CKTCFil+r8e7pK4w9/Dzxzl7cUyfwS5to2/ZiPvgkx6whnk8niQcOo71HaYwncFWTSP8of/buLL7jghMymo3RnCxSD0PipkqPW8T3JWG1RF9vjtzcRcITr/Js7xCV/m34dpN0dZpFESETNSjWbC5dnWWqYPPFJ47QX1xk4923qTVdrM1VgqtXsEyd9IOPIe061KpUfXCzXdjLS6zufpBIZIVn+i2slWleWw7oSHUSUxWkqhKGARGtlck3XWzSVZokqJZRpEQ6NjRqKKHEr1VRLn7Aga1dXJpdIxOzsN2AFamypS1BuwlrdZ9Ko3nj+QcSKraHcX2NWmm6GOk0zWKeat1mKWhjLGqz1pbFDkOEphNXQrx6HaTEMjVoOojyJu1dI6xPL6PmegiKeZR4kg/fdG/aQvDb9W39shChz4PDaWKGxuWVMo4fYmoKu3pSHOqJQ+ARAOauA3gLM7dkOGvtndA/8qmB/pmyz6n5Il/MdBHGkigyxNxcpSeRIYxbEASoXg21mOdgxKCysghhnVCEKMlMS/bOsAgbdURHJ8sVt1WyKBQCoRCGHgQBUUPlYqHJ0we2oZx5j+XxCTp37aTtwX6CjTXW+3awcm4dpbuf1apNt9VEbCwjs1nKmxusRG1yr/93nhndDe2dJHZtY0mNcGF2nTPHT9GbjRMLNgne/iGivYvEg49SffWlFkk/N4WwInQ++iyZdILQrWJtHeXyhXE8o43kQBuqIigqOotNyUjvNmIfe17tUQ1dVW5IUH4cUUMlG1Hhs7ZHRaHsqaxUHYJQ0pUwyZqt93w79FohX+kCp7gJmkHeSqNrMWYLNts6E7w9ucFiyUZVBP2ZCLHrs9u64+H9fnwiv/GQUtKIp9Afe55YvdrS9I/GcHTzxhhpSI/dnVGqdhZFEdiuz8RqCf9jgfmuqIrz9ruIIMAOBCvVJn4QojWWaO/rwawXqL79Gk8d2sUbpSgjoo5WLCMaNWTPAEJxsCJRVhoBZR+QIX4gCZFIBBFdpVQLWK04dMQtXnHTPHfwABNvv0OPJUBKaq5PR1cORVExyhsoS/NkM0mil2dBKMjAp3nlPPrdj1D0BF1Pv4A/fhFCiWFZWIfvx9tcp37hPIHdRNcURDJDvhliCI1mWzdGs0bYbAVrL89tcHRkJz0PP0nj+GsIu0r07odwr13AHb+C8DyUZIqO+x7A11V6/DJ/FNZo2G28H2aoOT6vX1uHbTl2ZrXbzkk+qm7wCAwL/+cQ7a3Ky1uDkxG3ifPaS/j5NdTAx5+ZwLl6AXNgC9bew/hzU/iLsxAE6D0DOJfP03jnNZJ/8Cf4uw4S/BwOxhI+L+zu5MdXN8jXHBYKdZZEna25BHs6TIzQ+dReKAxDgpHtRIOA5vkPCO0GCIHe1Yt598M0rdt7w/y+Q0MiTx2ncfX8jd9Cu4G3skT0/seQW3bc1KaklOSSJu7OXbzyygeouoFpaNT8ViDSWJpnea7K0uERlKkJxLUr9O7cRXFwF8ruQ+jlCu73/4a9qSRH9xxGU+MEV47RmJtBBgFSqGj3PU7+b/4KaUu2KDZpt0pfdzuLVZcwDFnPl4GWmgOqwkh7jJV1l2rTpiMqiUUt3GSW+bUiSStBNmsxu9kgZWps1pqoyQyNxQViKohYkvXVDcTcErYfICV4gUtq+34mywFz1XX+8GAPkdvUBFUDwUy+ftOa6uMYX6/RWdsgbNy+KiuolFEbVRTfB+3mCie1XLhJIlYhpC2ikLEirUQnpYZtpW8MyzIMiYmQ2I1m7tDVH6W2ss5sLY8j3ValcdPGX15Abc9x+K5dWCK4Uf0qpaQ7aaAq4obk58fRFjfJWApydp7qxTMYw2PEdh9CyhCvWKB++RxGIok3dRUvv37j75zpaxjDo+TufYTHhxPYg0lAEFFDZBhiPPAkfnET6TpITce/vv4VioLSP0TjY8HtD2EGPsGx17DnJlvPK5FELEyhFtaJ7T9KXTUQmsaZuQqnJpZbJJNhUmvqLBQaPLqtkx1Z9de2hvt9QiBaiUifBboiUOUd4usO7uAOfjfxayVg9u3bh2VZSCn5q7/6K+677z6Gh4dv2kcIgWmajIyMsGXLll/4HJFIhG9961t861vf+tR9hBB8/etf/6UInt9WCM3g+FSJuUKDB7d28KMra3hBiBeEJCyNpZJNe8ygbLtM5Rvs7MtwohDww7mAXKaH7Vs6+O75NcqeoANJ9OxPmbp8GVUIFAF208VVdZrVGn6oUEVHOk0U3yNqmcQsk87eLoLlIpaqENoeSImuq3x5d47gv/0FAMmREdz33kLYdZwGxIe3oF4PUnkr81gDIzRqdbxUO8V6SMNvSSBIK9LKxg0DwkaDhqESdg9g9A0iDIv5zSreyZ8yMnSI8ZkVvj/f5A+OPsLFa0vkyw3KM2UC1yG0G4RCoLXnWJie58HtaYLFGWR+FW9jkY7d+3EzHcjiJmFbDiUSRebXkI0GXdkYWkeGogfRRhlLJBntiHNffwI9P48bhrhz03hLC+j9I8QP34+3MIMjBVMTc9RqNpqmsG1sN+W//E+IXPcN+Ry5OIXlNNhxcDeb58+hqQJT4aYgu759N/bHpIeU62bJH4fR3Ufz5E/Bc2+S5nHXVzB7BghXFuATGVUoCtroDtyPHVtKSVvMYLF4ew+GkY4E782VuLpSuvFbtekxt1njmV3dDMVvzQz7TYQQgmqosVhyqDk+HXGDrpiOJfzbXr/m2DjL8596PG92EnX3oV9biDyQwJadxHPdBItzyGYDtbMXmeum8aGmekcXWrYNS4K7sYrRrOPpEexAoGTbqVtJlG6F5mYBoUjUaIySHufSux+QbZYxjj6OqasoqoLf1c9dtRLSabD02k+4srZGt1cmrFdZf/pfYiaT6JtrKGaE1arDg6M5TsxsUi9V8GMqjl0j0d7Ow0Npwr/9c0LPbwVi5ufQ0m2U4gncyUn27H2Qs7UqoaaiZzJ00GTz3eOsVR0ajSZ9mXaCapVaw8F7+03aH32K+qsvEaTb8Tp6cDqHuFwxeWAgQeVH/4j/0NM0DMHiWpFExCBnCqiVCV2HiKYjGimaczPoigqlTYJ6DWFFCet1DE0lmJ8ifriLXVmDaxUfO9vL8mKTr+zrRZMtDe2b30vLCPxDWJqCK1S0vmGC/Cp522fr4jmsQ4+wMTZGLV9AeCVUXSMiJLprg5Ro8QTb0jqXXQehCAiCVh8gFAxVYUcuRvB7UGX2IQzpcX9/lH3dcdxAYmqCmBK0yI3rsGNJIs98hWDyCv7cFCgKxuguGNyCa0aINGpQKbbkJpIZ3EgMF4V3pjfI11wYGaahRwgadfADcPLoAhQpSdx1Dw3HI6cGxAf7qL35Cr6m0P7AI8hTx/Hz66jdffi2TcxQEYqCMM3WuCUEIhrDCyW24zJd8ajvfIBtGYt11eBEXVLu2cbdHf2s+gWc1U0iqRRW0CLv3FKBeiCoaxH6MhnC+XFYX6JcKfFq30N0RxRQBI+OpKn997/GQCG1czeVb/85aAaO42D2DRFsblB/9SUSX/kmlfk5miM7CLod1sYnWHMAJIriMfDo47xR0Xi0S73xbONqwINbO3hjfO0mKTJVCB4a7SCqBJ+mZnQTpKJxds3mvZnNG8cRwM6eJPcNptDCm4NYlu/in3iDzOwMa1WHiu0RjUV5/pGnyQ8PA4L5Qp2+TISYrqAJeSNbN2kZGCp38BsET4L3Mf+6TzaahBbihwGz65+UKoN01KBdNnHWlnFDwWyhFdhMWAbzm1XiI1FUp8n2TBy1tEllfQpWN5GaihJP4JVLqIFPtnsrdS8kHjEQQsEPAkAQNRREGBBoOhFDJV93uLJWZ8+995LM9hMJbB67fz/Hl2q4sSh6JY9fKhEdGOaRjhD5D98BRUE1TNS+ISJ7D1F65fuslYvkIxnSvb0M793J+v/j/4oIQ2Qsga5r2H6IYkWxmwoNK8Wq38TSkySzKvZmnnh7G9Vylc33fkz80F1IGdI88SZ6zwCJr3wTKUOE7+POTUHgU19eQpTLlM00Bx94gqLRTcP1mcrXGcy0Y6kBShjcmNeYgY+Ym8S9fJbQaaJmO4juPYTT0fMLvVtVVQmuXcDPtzxlQk1HjScJqiXcqxeIPv48brnQGssArW+Q5tuvgpQ03nubSP8IjUT6Z55DSkla9fnKnhxFJ8TxJXFDIW2ADH6+rIsnFILt+7CGRhGNOmgafjxFAxC/BfPUfw4Y5SK121SWqokk3uRljL4hmrrZSgZTNOqhymtX87RHddaliRdUaDRcEtkM1Cu49TqqrrNY8Tg00IeX38CenaJjYAv1RBux4iZGfz+Na5epryxhDgzRRMXsG0J6LrWeLbzy5lmGdt9Nm+IDNmYsykO7c3z37CJBrd5qi1ISSjiyb4yllQ2USJRcKoooLKFGoxRsD+l5lHQTA42+eITqhqDuBGDnSRqCwA1Rmqt4I7vRNb3VXSmC7N4DnNNzLG406YwZbDYC+m7D34WhvIV8EUK02poQ2F5AYDfQOroINjduPUAQoGU7CAyDT2qAytuQDlJKBBIVWslEPwdmtUhw7CW+tPtuXpspsllsEUGmoXOww2BvLMAPb57jZgx4elcPExtVSnWHjet+Kpau8thoO6YC/vQ4BAHu8gIfv0o1mcadvIxcXwX15jCUOzNBbGgrsn8L5vVB/MMClEa6Dev5r+F8cAxvpSV/rHd2Yx65DzvVdktCoRACZWW+Rb4oKtGt2wk3VnBPncD1faz1VeIPPMG6NHj/1FV8IVB8F5o2aqYNMu0cn84zkOohIu4QMP9UeKHk7y+s/fwdgRf3dKL+7ILrO7iDO7iD31r8WgmYsbExxsbGgJZXy1133cXAwMCv85R3cB0VXzC92Vq8aqpoSahch+OHBBKU63IiDc+nIxHhjcklEhGTWihxFR0HBUuXPNUW4L49jnZ9sSYQKKrC+kaJ1PAw+fFZXAnpZAJTU9isOejdW3BiGf7knjRXZtdYK6h0paI8sqOL3p/8JbVyAaEpRNvaqVyv3BBS4hSL+Kl2utSASCqJ1DWCvhFWfQ1LC6mHAUMdSeYKDbzh7WildWSzQaajC1W4yHQbgW1juz7N5SWG73qUqcACM8L5qVWWA4OF+RlSpgq1CkI3UJJpZDSBrJeofnCFaC7H9FqFxOoZus6+R/y+x3DMKOVak03fIJ0bJmMIdEK6dJ22QBJJ6nxdKRC7egx5soTsGyKybRfeZh4j24aiG8hGjVK5xuSFK4hYglBV0Ts6KF++QLhZINHWcVN2U7CxQmz7LtLdnXgbqwiUVmalDDG37iDo+kgqwfd9Itv24EyP39QONDNCc20VtT1H+DEvlrBRJ2zvxBjZhjM3dcNnRpgW0Xsepplpv2miHwQB23NxLiyVbusBMNAW5/WrK7f8Hkp4ZypPz75OdH6zA8VCCOZq8KMrSzdleKciOi/s7iKp3GZhryig/ozontKS/fl1SjYFQCORQdnVBoD7iWCWE02QfORpmsdfpxqJYroNpAoduXYqWoa61NgQSUR7AksRpGWTXFCnsLzMwtIiQ/PzJAOb6MG7mfrhK2wZHUSMX6DN94hF02yYabq7+yg3A0S5iNU/TOB7FNY3acu18S8O93NpZpVsVGdMKuwdHiV9/GWqdpMgCFEME72zD/fgAyydu4DY3KDblJwPPJIjW+gZ7qa2tsbi5BL4kkw8TlWBxMAwYWEDt1FHagbRL/0R1c5R/nauydSZTf7wyCCpY2eoCwWhgKrpWDrkVB9nfgFF00FVCTwfUSmiVovYTRd/dQ0RBiQ6usCewQ9CdFXFdX3cYpH47vt4y45weChGiGSlqdBjhHQakK+7SN1AEdzwK4kZKroiCCWEuoHoHiC7NYu5dxA9EiP52KOUXn8FvWgjTR3RrCODACWVQegGXad+wpMHHuZ926IiAUWlI2Hy4JY2Mnr4mQLev0sIgoCoCIhen7188v6llNiROMq+u9B2H0IKgauoKEGAce0CjdMnblSsCStC9OiD5Ht2cG6lpTv+j+ksX/76N1n97l/jlcsYpk4slSS+fRfWwbvZTPVQXlhAsV0s06BeKsO1a2Re+AMar/+A+ENP4r71Y/o0F82ycDUD3wkxdB2ZSCODgF3dKRYWVpmeXWdaBxGNUzCSlOpFju4cIESQiEfpUl0MGUIYtLh3KYmZOpOOji8TYEN6bZ2H9wsmHY0/PjpM29Rpqs/8IbV4GnP+AjLTiaUK5PoawooiTBOERfPKOcTgNpYbIee3PcDWsf0o+RXQTeqZLr5b09FLLnd9bO4gw5DtWY3s/l4urlQpNDw64ga7uhK0GeFnzhJdroecmL7ZwFcCl5YrdMYtdmTVG4FhVVEIz57EnZ1EA/qSOm7cIJQS7ewbbP1CjmUjTWdUvV4l8RH5AnBoII3xa5Lou4NfEwKfR7a08VooWSh85EPUFjd5ekcHml/D0zQKlRb5oikKhqagIZm5NM6hp1/EefdNtPIGXbl+1tdARKIo6Qzu3CxCQLKygdHfzt5kgmvTy6hCkIrotFkKxVINPRJjX0+avzm9gKoI5m04twK9SHKxAvu7M5Q8BbMR0n9wG9siAan1WYzHngXHRs220yyVMQgwqwWWHUkpv0RpcQkjkSB7/6M03j+GIiAwDVLdOexoDKNvmH9Yg9WmpCNuEU1FUOwmVMuIeogvJRfeeY/erSP0vvjHNN98BXf6GgLwFmfRs+0wtpvGm6+haBqpnhTVUyfY/8TXqOhJrqzV+OszKyQMhT09SbZkDKKhS3jypziTV268grBRx1uaJ/7oM9D12SX8NLd503GklK35Z7MBmos3dRWtvQu3VCRy14O4i3MtPxhdB0UQrC4ikpnPlLCjhh7tOqADhPwiCdNhGLYkiIzby/DewUcQQhBurHJTx9rVx2bPdiYrHo4fMlKRZNst5vJ1mqHPtfUar17b4JmdXaxbaTp6TML8BqgaolpG1XV0o/Vv04FmoNEeixJbnSWZ3UPzwvu0PfIU4ewkDdvBV3RW6z5KvYamqlidgyyduMrSwhqaofHFp+/FmDhJz+AWvrQtw7STY7JoI4XK7oE2hG7y47MzPP3YEfbaK0ysuKiGhe34+KHEcX0MAd16yPTyOrqqEFEksuq0xjVNoytuMnDPIfK+oJ7t4dWCwtVlGyQ0LHBuUxkKENUE6ahBqdGiITTXISwXCO0GQtMZ2JJCiafQx3a1vh3/5rWSiMQw9h2lepvFl4glbnjk3A5KMv3zX3C5iKxVaT//Jl/t30JpsBs/hETYJLZwGr3Hwu8evNEWqqHG6ZkK05sNmoGkPW5x31ganZD+tEVC8ZFStN71dc9C+fHkwWw77qnjyHT2o/sQAiXwIQwJLp/FGN6G49285grDkEa6A/2JLxFr1ECCH43R4PZrLFVRcK9XbEW2jLaUKNaWb2y3T/4Uv7CBeOTL1CIJ6k2feqjRkUkTqxfQDBM7lqTkBETudBN3cAd3cAd38CvCr5WA+Ti+9rWvfV6n+r2HoigsFewbRpXFuktPymK53JLICUJJRFdvmFMOZKIYqkrVCdioOVSbPncNZjjQYaCFAalmifrmJrlYhPVKEySooaBw5TLtX/s6HVaS+uwMBB7LFZf0rn2cTo5w9b0pjg538OS+QSy3gX31Ao0fHceuVohoAqm3ZjRmxMKttTJuZCxBYWUN7Y2XefzJr/PjDRivSVThk4sbiGSEuwbSvHF2hnQyghUEhFaMbZ0pxn/6DhnTIhXVMVSJa7ugGxDRcGanuBL6DB09zMrwKLpXR0YiiFgc25f462scGkzTPHYJsbpAqmeE/JXLmJkYzbffxHrwCZTNVdLZTlaqPmVDYyBtockQo1ZBW5snMn75RqWDM3WVyNiuVibiK/+AUBWEZhCmOxi6/37mLl5GhJJEOo179iK+HxCTLUJMTaRw21sLXntmEv3xL+ItLbB55SqhqpLasQvR00dVqnieJK4rRJQAr72TyMG7sU+/B0iEEEgZosTiiHT2pox8AGd+mvgTXyC2/y5kuQCKCul2mpEo8nZl5WbLwPGtiXW86xoRAtjTl6bh+J8q/V+2PcqubC2Uf4NRDTR+/AnyBVrX//pEni/uaLtFHsc3LIyRbTTPf3DbYxrbd+N8TgmVnxb8VMMQ2Z6j7Ut/iLU0jyjmCes1jo5s48SZTZpByGKx3jJ3l5LOhMkX795F4/0SiUiE/q09VCp1ls6caUnXJdM056YI/QBzcIS04XF2Bdp3J3BmCugyxAkFBdtlbnKFobTFEA2eTZsYL/01/pseyiPPkHzuK8gwRF5f4MycvUSt4ZC6bgJu9vbTs2WIt6cLdGdtao6PrghWyjYJSycwNRwrSzzZQT3bzcLQfv7D906hCBjuTLKVGmRS7Mq14UUU+tIWthR4izOttVoYIlQVoQiygY1MZokUNii5LkEoCUoVUoMj+KUixo69+CKk45EnKI3eS/umiyogv1kmnp9ic/oij+49yj/O5LFRiXT1kbB03CDk6Z1dzG9+5Fuiawpd2Ri2aFUoab1DpB58DP+9t3Dyqwgrgj4wjLFjP/X33kI2m2y3TIbvfYpq5xhr0sD3A+pOQMPQiYhbzV9DRafQlDT8gNpGlYiioXyGzODfJYRhiHt98U8YYq4tUn/3zZv2kU2b1dd/gvZ4jFqzZTD/4/E8mW1DPPiNP8G0q6ihT6BoNBo262+9RRCJYR15kLVCiaGt2ym+e4LmtavY1RqdT76IiETI/NH/iFhZ5qFDu/jB2XkisSgy085ioc72/nYO9sR5742LmKqCCH3CtSU6YmWGevsZjkie3dPDxNVpWNtEGd4KjoKgQmcuS3Nhls2KzYd2LJWmx7ACO1OC+OQCx7QerpxdYsdwiD89j45FLJ6i6uoovkF73xix0AHPJUyk8XqGef1MkTeFQswYxLcldsUHfLbl4mif8H2RYUCHAY+PJG7yf/h4/y+EwEGj0Axw/JCkqZExgcBHUTXOL5c+9b2dXSoxms2hXifsjUaVxuTlj84vJbqQrcHHbRIuzdG2LcUzu7p4fXzjhnm7rgoO9mfYmjWQ/9xSFopG0YWK42OqCm0RFYPbV1XeQQsRXJ7blqXgZGh4LbnBNlOgSh/XiqINbMFeO0MmatL0QxwvQFUU/EadlXQvmXufwHRK7Mv0Mx5E8BwXL5+/EagTm2vck91Nh3Bo7OtjvCZYKTXYqLqISIx9/VnytdaceXdXgoX1MsmgyebqCnnfx9RV/vjeUfrdCfzXLxC99xGcc+9hry0jPYegXkMfHkPs3IsmJc1QoFkmGBYT759h5MhBUvdasL5EJdRRY3HC4e1MJ7Zy4WqlFWws2tQjGru6u2HyElktylxTIaKpJJYmaFz7AGNwBHPbLsJKhdh9j9Acv0zx2JsgQ2TgoyLxqhX6jID/27llPD9ka0eMpiN5/VqTuY44X8o0qX+MNLkBGWKffIfE2K7P/uKCAPmJALKv6aj9I4h6BcW00Aa2YOzYg7swizszAYDa1tFKEnLd63PXW7PZNRmieC6hbuAL5c7383niY+OA7O7nTGqU984s3vjtotJGnRJf2N3NtdUyJ+eKNL2AyY0qW3JJlgsq9MTQFUmkWUM3dKpNn96oQn59AwVYchxEKk378FaCJ19kLb9Jxze+RfLaRep1G1HeINbdjbr3KG/PVxFWBOl5+KFAqxbQM1lKP/4ecus+Du7ex/7BNkzLJO+rFFzJEwe3YK3M8WBWZ6O9jWKtQdSKEgQK2YjOl3e04awuE7N01OvqClIIvDAkEdHprCyzMD1LdcdR/uMlh21dCR7emuK755aoND1Moxdxm2r5qPC5ry/Bjy6vgufiLc3fUDNImwrdS1eQYRM/DIk/8UXsk28RbLb8ctVMG4kvfAO7s4+KI/FCSVRXrlf+hriJNOaW7TgTl/kk9J4B/HTbz3+3HyoveB7K9FWyXL2xKQQQH1W/1EKN755boeZ89I1vlOvU7CZf3tdNXHhICc0AlKEdzJ+9RCglqYhOwlDRRAiKgjBMpKaDlKgyhGKBoLjZ6js8l8jEJcy+YRzt1oWjJ8GL3Kr4cMttSUno+QjTgnr9JvKldcPQaDRxLp5mpPsoG3WPrqTJxGKeopWhrVJGiSU+qRFxB58DFEWh+Qskl8k7b+kO7uAOfovwuREwALVajWPHjrG2tka9Xr/tBPtf/+t//Xle0u8kpJQ4XshgJsoHc0WurVe5e7idvz+7hKRFwHSnLKq2Szqi05u0sP2AxaKN44d8c9TiwepVzqoRTk8uEuzMYYeCWOjTnY6wWXfRCFFdl/LxNzFe+B8wDzeYnl+jrpq8lveprDn0Kg7nf3yB2e07eHL/EEG6g1L+PUYO7kfWy9RCBb9QIRlLoHsumDFst+VL4hcL5I6/xNe+9e+IL3uErkNvVCWXyvK980sEhomtGES6ujnQmyS8dApfKqy5ggVPMJCOULcSFLUYQXUZr9HAR0ClyEiujbUzk4SNRmvSF03Sm4kxZK/hV0r4gYc2tB2A9apDj+KgOS7W0fsRF06ja0kark/NDWlTA4zd+2muLN70DpSuPrzpcYL1FfA9ZCAg1Ubj6iUsxyO3ZTtrFy4QNmoIoaBHY9haBLnvKJdtg4n1VsB2dGwP0ZrKyUKM+MA9hFKyuuTRmFnhgZEs5xcLxAyNo0NZtmUNzD2HSXX34U9eRTZqmINb8Ie24PnB7TOE0hnsSAIZ+8jY+1OrNcKAbRmVnoN9rNc9vDCkI2aQNeHs6s8vc/9NhhCClaqL+ykZbCslm5ILmU/0mEEQYGzfgzo/TVAq3LRN7+qF/uF/tiCBCpgbKzjn36dZKiKSSeToTtTte6l/729Q+nZxoC/NhbV6K7ihKGSjOo9v7+TbV4tsiK0c3ZlkYPUk1YmrVB0fV7Hw/BARSyLqFcJSASXi0ZGwSDWLdEQ06hKmN6oEQUgoJY2oRtr04ccvEayv4BkR3EqZ+svfAVVDGdvN5ZpCNmaiRAyEFqWmGAxu6WW21CRfbVLpjKObBqHrIlSVmhvQnojhe5I1qeJG25kuNBjrzZBRAu5vzuG+dA5v4gphGJLs7+fJb/xPVL0yK75/I5YQSsljO/sJL76PtqWXMN2GJ2Zpek1wbRoNh8zgAMbeu1i+NkGtEvJ3FzcIQsnzu7roWbpC8aevUkIwKo/x9bG9LKsJNt0aDxweo+FLLi8VWnIWtOQZntrReT1DsHUNvhCEI9ux+gaxjj5AsLFGsLFC/b23kc0mSqYN8cgLOKkcF8s+E+slml7reAlL54t7bq7OqkudH13eYPU64R6NRolrIU9t6yBxuyqu3wPoAtzbkKQBCqvlBm2XznCo9y7eXywTNzVObQZs60ySjSa4uFTk/EqNmqcx2HWAnSmFlTffYOv+fQS1Mvr4eMtIe3mJmZUl0iNbsQe3Y9z1GF2uxzee6Wai7LFcsjmcsDjQn6Q8OYnpN/FCBaGCpmmYXpOnO0LiP/xv3JsbwMsmGXc9bCNBRAr6urLsyeos/egU0AqMKICZSHC5ErIrGzJj5bh89iJIqDc90n19LE3NMrdWpTMeI6c4NJcX8DyH7JYtxHt6UaJRVKUEQFfSoj1uEUjJ3GaN/kyU1KcQ55/m/yCEYMNV+NGVVcp2q70JYKQjzsNbMphIqs1Pb4cNN8CTrf4LANdFep++/4f97mBc8I0D3RSbAUEISVMhqUlk6N8kv/l5wxE6b00VmVqv3eCoUhGdp7bn6DDD34sg8u0C6p/p70KfNh3adIDgBskXhCHRfUfIzM4zt7hORFOQQtCZtFhPdjEeROlfLyHNkPClv+bRu5/m2HSDMqDoGhFD467dwyTXZsm/f5wDozvZc+A+JmqwXHPoTkY4v1hkPl/lrv4kI5kI711dQFtbRoQhEcukLWYQmziLff4EaipNsLlOUMzj5tcRApRIDHPnPppTV1GjEbQQbL/VvkPhc+n4B7T3djPy5B+g6RHydYd3JtbpyajkjJBqoFLzQ8qupKmZPHd0G87F4+QSFtnQRiwvIgOP5sklcJsExQLewiyxJ7+IoUATUC2LulSImSpLFRfXD0laesub7PqzXC03qddv9Q/8EEG1TFDcBCPymd5ZYEbQc92489M3/66qiFSW6J6DuLOT2KdPQCgRmoba1tGqDpQStasH5xPJJLoM0Zbncc5/gFerosQTWHsO4fcM4omfbQZ+B/90SClROrpbgXgpyXdvu4l8EVaEogcr1QYrVQdVEVSbPvs7Izyp54lbFt8vrlFxfJRcF8KKEtgl7tneSzBxCUUorYpGzUD2DHGurjJOL+uRHOVlh86+x3lxJEZbscSlxSITF+bwPB8zGkEoCl3tKZLnj+OlU8ggoKpavHxunaIwENUizVABz0U0ajyzpw/jf/3/8bU/+Tes+HFWYh1YCqQ3F+mYPAWrixwZ3MqlqSU8ReCFku7ONp7ojxBMT7CxUkAJzhBPHeD4zCaLJZtHxzrYqLpM56v09MdRZIucUBQFq7CO8/479AeSp7bdw4mzcxQ8F9U02Nqb5a6sSmzyNLVag8TTX2Ll9Cm0PfeQiFropoHeN0ipc4hXrhZYKNQJJWRjBvv6MmxrM/EDF+vI/ViGgTN+qTVWqhrm0Fa0w/dhf5bvI51FGMZt5cyEYcD1ShVFUbiyUsfSFXbHNQwRsBlqTFYCGo7P2cUKDw/FcUPBG9MlDC/CYP8w9clx6q6PoSoMZaMYgY+5cy/uwlyrUjy/3upjrkPv6cc+exJtdRH97kdv46pzG6gadiBQhcQSrWrcANCHtiAWZvFmJ25t15EosxWX2vkriOQ2fjpZRwCP7eiiVKzgKVHSmiBt/QLednfwK4EfSP7x4meTKwP44u7PXqV5B3dwB3fwz43PjYA5e/Ys/+E//AccxyESiRCLxW7ZR/wzLpJ/lyClpC9tceXqGs/u6uYnV9eY3qjypX09nJjZJJSCXExnX3eS/kwEQ1c4NpVnR1eCHaZL+4mX8ZQGfX3b8HrbmVqvsjWToV4oYCkuuztS+I06nhOg+E0WSzWwIrxWj9JoemhCYGoqDWGS7OiAapmgVmVOTZL7+r8ibwLZXvypa6ilPB33PYZ/6QyhahCsrmHFY5BIoYzu4t35EsvrDfTiOgXPJRExuHtLPyTaiUdMhhI6mz/4LoX5eSRgmgZhCEuFOttffJG/q5t4zSahBMPUaQ9t7hfLFA4Nc2V+g0CobO1rp31tivpPfogGaMk01XpL9sLzA4jq+HaDtfUSAw88QWexTHEjj5/rJL53B/VTJxCbG62Aka4TCAU9k6V+/HX09k70wS1I38M1oujtHTTnp0js3Muq06Q4N8/Qtt3Yc1M0dx3mB9M2lco6eC3PnDdjndQXF3lkW45LS0U8FKbzdfxQcm3DoD1ukq85vDG+jr6ji33+OpWffA+haqCoOO8fw8x1E05dw/+EuagxMILa1QvlymdvW2FIXAmJJ6AV/vMhgP505Ibk0ieRjhqkDIVfSB/inwF199Ml0iS0KmNu02PaZpTIky8iF6bxpq6CqqCP7obeAZof+rD8EyGEaMlAfEaJH0VRMOYmsd/4Idg1hO/hLIWEZ9/D2HOI1ENP85NLa8w5Fs/vH2GsK4EXtDK035srUGy0ljyqY+NvrDK5Xr1xbltouI5P1Iy2vIXMgLgaolx8n+cO3MdLDYswKCIATRHsHspxaO0MlakJUlETgcReWUEf2407O0moqDT8EK/qkLRUxh64j6C/D1NJ8N/emKYZCN5ZVXj64BFW3nkbXRPIIKBku+iAOjRKM9OJqIcc3tLJlpXLrB97lwCfrmwGWS0j11dQ/vw/8M3//f+Fc9oAM5s2yajBSFzBmvyATs1n+oMzdD7/VVIDYygn3kIGAdrwVurJNhofnMRrOLQduo8/1GMohkm1XsE+8y4AEoldt0leeo8RTWeLaWHlVOrDOxlIdlKsOURMjY64cT1z8RMVK2FIQzPRh8bQ4klCp4l5+G4Y28dEoo/3VhxOX8kTNzUO9qchDJjbrFNtevx0apPnt2Uh9AmVm8mXD7FeafLK1XW+vLsD9VNMzn+XoXguXrV8y+9eIHGDkOraGg8dTbJNt4lvLJKrVkgP7uEfTs8xsVzEdgNQFNY3y0wkYzwxupNVXyHZvw3r+QSJ1TnCzQ1IZij3b2fcVjh/bIp/8/h2lqfmGBAaYymNTGWR9KkimcnLfGPn3UySoNBw6cRhNBrS0dwgf/USYm6WfX3b2HbwMPPJbnZGPOKX32P89XfRhcQTrXFeCkH66H2cc3V6ApVTc5somk7oeeSLZZT7D1G5OoOqKnTIBs2FxRuB8MTwDuzjb6G19fK/O/oI05WAc0slLk5uYKgKhwYyPDzaAWHzluf2s9AINV66uEzD/ZiHGDC1UcPQFJ7YkiaXaI1bt0MmarT8zj7s6gzzU4NDAGqmHT9sERkmIV3mh1vCj1um/bNAUVVOzFSYXL/ZXLlse3z/0irf2N9DRPxukqJCCGqhxkrVpe76tMcMclEVXf5q7teJp1Ge+irt165QvHKJQNVI7jlAz9AWfnguz9Ndwyjjp2iPRMm9/nc8t+MQzuAAUtfJujViosyluTK5ex7iqtXF1atrPDiUYWQgzeXVCgNJna+OJUn7dd6ZWqZDB1eEKBp0xhSeHk2hvvQ9Ko0m0Z40kVBi7D4AVgQ1141o76Ry7E2snl6svmG0mRXqbogSiyEdF9t1KRRK1B2LtG7xV2+fw3d98sUaL+zZyrqnsOQIMlGDewdTRN55iZnxWXrTUeLVVQzXhUYVYZoosST++iqyUcdfmsPMdRJdWcXP5qh6IV1bh/hxSWBoCl1J8yYvQYmk6oYkfwZJJpTPvjbzpSS67zDu8vwNKSVVhuB5iGgMMbYbLZ5C29xoXYeqE2paq7KtbxA/03HT8VQhUK6co/7B8Ru/hXYD//UfEDl4D+ruQ59qbn4Hvzo4iTSR/UdwZya4WvxYXywESmcPxbqPqgjWaw4ilBzpjfNA+Robr79J1Yrw5D33U9DbmC5UGdw1Qq6eR05eoro0j64qLdlW02KlcwvvXNngye1dvPHOBK7rYcXj/NV8yPNtEVbtPL6iEgQOTsNmZKiHx9Mu2lsTaINPEv/S/8C7E3XGN4rkMjG8coXAilFr+qTjSdojCnouh37ix+z+4jcYVSSVd17j0tkr2B0djMQER6vvsndwhIbVhhQQX5jA+9FFmg89i31llkwsQn+PxkZdZalkc99wG4ODUS4ubLKvM07q+jrBqhSp/+gfbkiebs9N0h3O0hzpRY/GieSnCOdWCSyLjbrH0vg8kyP30y3rKDLEi8QZ6e7mH84tUay7ZCIahyMu5to4crGCMzRA28ggthlFOfwA0R37wWmCYeDFktif8btwogkiRx6gcfz1TyTgCSKH78eJxEFKAqGQ9uocmD/F5uVL1B2HdEc7jx+5l7ORTmY36zgDCZZrPhPXxzx1x/0MDG4lvHaR0HNpbhsju2c3EQHV5b9EbTbwPpa8psQSKJ09BFcvEtSqxHcewEtmPvXahaKy3JCcnN9ko+pgqAq7epLs7oxhhh7K0BhiY+2mKp7WiRScZBvr600MSyFutjJNJPDalVW+drCP6aU894/mPrO33R3cwR3cwR3cwWfB50bA/MVf/AXpdJp/9+/+3R0fmM8BWRMG2mJMbdR4flcXvpSoQvCv7hkiE9FJaJKEIXEDQclX+WB+hhf29jA4e47QrVP2bSqnTnBkoBN7cCfZJ58iePcN3NUl3MkrWIaGo0eJPPgUFakhbI/VpbXWgksREEq0pMXWA7vxmw6raozOiMqmB//xnWm+viPLXEknFR8mOzRERghKK+sEwqIeCti6k8bOg+Q8hZNnJ1A9F93QMVC4cvoixWwvj21t5/SSS/feexjLddCYvIrTaCBSWcTO/ZyPDdAf03kst4vmtEGsXkQ98Y8U83m2fPFF+pbP0nR8mitxgkYDIUOEIjD3HGT25GkUwDJ0zFwbxUKJ+vo6s75P9YmvsVb3icUibFE38c+dJGy2glTCMFFzXQjXbUkxqCoynUVr68BSNGrRFMb8FBqSWG8vaq4Hb/9B7FBl3lapFoqEdqNlwN3ZTaHuUKnWWe2Mk4rozJac6zr3cHWtytM7cjcCWR/MbDAYzKC6LvJjlodeJIK5cz9Kfg23WkWxLIxtu1F37EONxn4hAubTkDFhT2+K80s3BzlVRfDAlraW3Mo/+Sy/Pkgp6Yibn7pdVxWixqdnQdmmhRjdhbptDwBO+KvJbFYUhbKvslRxqDk+HXGD7riO8XOCWIbbxH3vTcKFKRQrir++Ao6NDCVBfh1teBv1WBZch3cmNqh4IWeWKkgJmqrQl4mQrzkMd2dZv6LdeHcS2CyU6RgcoTE9TjqTJAxCEAKzXkGbPs+RXQ8zeHgQ3w/Qpc8YRbQwIOzowq8V0QUUL50j88iTxHftJ3/5MhKQ0TjiwBEKg7upVSqslFcRoSSqCq7MrzO8bxu7n05gn3ufZrGIFY8TGxmluP0IJ1caFOsuXxuN0zZ3iWRKJ/AFCbMdpAu5HkQyTbKwyF1XX+dIMkuzAZ7ooTC6m0uBSjis4kTaWIgYjB0SVObmKM/m8RuzjHal2P34wyxOnkdMToNpsvv+B8nbFT4enhZC4PsB+HWMxTlSmTaM99+ms1YFTcfcsQ85tBVHuf3Q6wkFr6MHrXsAhMKJpTonpzbZbIbUHJ+a4/ODS6vcO9JGLmGxXm2yWGxQ8bIkVSg05S3ky4fYqDps2pLcpzfz31lITUeJxAgbt5p6A+jJNMn6BtZ7L1GoNNBiGjO9Y6wsbxCEH74rSSgFzabLxVLAPq3EeM8OLikGo/t2UW54JEyVAQuUuSVyVgMxfp7+D97Gr1agViEsF/ASKZKPv4A18QFdQYBbKWP29qNGh5ienKVKBK/s0t0fMiMt/r/HZvg/74kw1LeV2GgRbXoCPwyx2jqIHDjKeS/GQqHGkf5eanoUNZ6ASpnugT7ebCbZdt/DWBfexV257rWmqsQP38tCoU6q0UTWJogdepjTC0Uqjk/U0IgZKmXb5UeXlnhxz6dnFqqqeoMYDsMQIQQFO2CoPXm9z5Cslxts1lvj0cRalcN9SfZ0J7m2ViX4BBEpgMMD6ZukHt1oHHN0F81LZ245v2JahD2DOKhYymf3oPm8UPYE42u3H19tN2Cp6jKa+t2TUhJCsNCAH11ewvmYh1A2ZvD8rk7ivwLSqRyq/OfLVZYr7XQMPUozkEyP1xjaXOeZXd0k9JCBtECrbqV25QLN0++iu2+Q2LYD/+mvcz7aSX2LJIwavPz+As+MdXJsapGh6Aa9uiC1eJXED9+nWS7x+MNP4By6j81EFd1zaVu6ivqP38PRTAIpUGWI73t4pTLCilGbmcZ//0TrQps19Bf+Be0jVcoN2Kj7JEyVHly8VJZjeZevtMWQfggSytUG75w4TzIWIbd1K16gMX1pnBfak2zqGlG1RUCAJDRNtFgCkc4S1KqoHZ34q4uoA1uIaTpOLEWnMInf+wiVcZeRbBT1E3OYhhtAXx9cOcntUmjUdBYl0w7V2i3bPg3NbCfxp76Ee/oEwfQ4weY6eu8gxtguGsdfI3LkAawnv0jzzEmCchHFNDHHdqHs3E9TudlTz6hXqZ89edvz2OffJzY8ih1NfOZru4NfDgGg7DpItG+Y5tVCi/gzIyiZNnwzAvUmQSjpi+ucPzfOF3flWHj7DN1bt6BoKpWrF6BS496eHH1ahkXLwPU9Kk6AUBSSg4M4u47yl7M+vSmNK2tVdnanOD61wUBHkr86tcguPcJd3irRQ0P4zSam1yQxcw7rg0sYRx6g2dbJzOkLDG89gNnWRipiEgx2UihVmVne5OkH97NcLuDe+xUySkCv7RG++m0SbW0cvO8w+cuXiQztI7I0hfbadzBsmyCaQFoRIvc/weXx2ZYnYDJFLBahMxESSMm19Qq6aEliffh1KYqCP37xBvkCIF0X9exxYoCSSCJ7Wj6eNcdnvdYk6fvMVV2uuAqgoJYd6maNYsOjM27wUMKhOjlOUCnRmJuhfuUC+kAHySdeoJHMYEdiELme3PqxMUVRFIxmA1EuthztkxmcaPyGLHUYhngj24mnMriXzxKWiyjJNMauAzhtnTf2M30P+ebLrMx+VDFXXlun/PI/svfp5zgT7cfQNC6tFG9sP1/0uKJ20LXvKTQB9QBesDIMdWWJP/Ul/GOv4s1OgqphjIxi7DpAY+ra9XsIkZUifAoBI4Rgrhryg0srN7xJXT/kvZkCiyWbZ7e1I6JxIofvh2gMd24KpESJRBHtXczUAEUlMjDMB2WPobYYhYaHG4SUmwF/dP8Y3XGVMPj9S1q6g18/VFXh2f7PZi4U/xUlrtzBHdzBbwY+NwJmdXWVP/7jP75DvnxOEKHP3b1xelIWZxfL2G5AZ9KiM6rSbvot7wW/5V0ZURXiusb8Wpm9qzMYCYvNfIPADwgKm3D2f6VkGqTvfpDko8/QmJshletANeO8I9vIpeJsrOdRhSAQgB/QlY4wtqWXv/1ggUREZ4uxjqLrBJkOvri/n41ikS2jg1y7NE44fgFv8iyxL32L9ZUSejbDhB9jpLyJdv4s928Z5fJ8Ad+K4Kwtkh0dY29XmpXpGe55+C7eurbGSscuBnfdQyAhGjEpOT7f/WCBZCJKJO3Tc+EkmlMD3UDrH2Z+OU//9j1UT57AN+I00MjkOjC27WZzo4jiuSiqoKstjjK2i+KplpGfMTTKlYJPyXZ5pj2KMzGBSKSg2QRVRZoWTq1ORFVB1bD2HCK067iXziJ9j0z3AM1D91Lr7GdS62Oz1qR0fIqvPf40c+N50HTUVAYlkQTDwrc9CCXXFta5a1svF9caN96xH0iUj+melosVmtkIn6wt81aX8U2LxJNfQLeiSFXDs6J4v8JglRL63D2QoDcdudHeOpImB3pTLZmV37DA2O2Qi6q0xU02b5OZvbsnRVILCX9GEY+UEj/41VX5KIrCdDXkJ1dWbnjuAKQjBi/s7vyZclJqvUJzdgopQdYqSLtxI4tV2jbB3ASjA3cRmBmubjQYbI8jhMK55TIgiWgKz25rZ4fRRN+3m76uLGXbY3Fiio3JKdrvvgsz8EFToFjEsCJE/DrBwft5+91J3EIBVdeQoaRn/xCFE+/SvfsI8WwSrVqEWIaVRsDa1BrDT34Z2dCZcRRWAp2nfcFcySNYXGBXVz/X1mq0taX56UKd43obBw48R5cpGejNEEpJR+Axl6+DgLQSsLheRIY6hqrTiKUYOng34fgFnOlrNGpl4kcfpDY3jR3P8YNFh43CNTJdnXTv3s1CFfpyOeZSKSKZPqKlPLGISXdHlPwHJ1idW25l29br2AszxOpFvGiGmicxdZXVuntDdql7QEHPl4ls5pFOixRpHHsNc20Z/e6Hf6Z0iu/7VEOd03MFEOB/4vs5OVvgK/t6Wa+2qvu8sKXZVPd+9kKx4QXwe0jAeELB2nMQ/81XbvpdVwWGqtC+dy9zL/8jXr2GpavEe3r46XoNoQiE76OoKmEYIiV4fshSocbhA4NUmx7pqMH3zi/ztVyANXmBwvoKQ5k4Dx05RCKapro8h8yvISIxcB1IZvBKBazD96H39OGWijTmZml0D+PIOGrnEEoizXR7H0EszeFBnffrkk7T44P4MCP3jaIJWPbhvSsFYj0x2pJR0jrEu7oY2D2KpevEDYX1uscr1UH+9IV+9InzICWeGWFubona2gxGOkJu+xgvTa/RcFs1jW1RnaSlYiohhbrLfMlhuPvm56kCZnkTf2aCsFpG7+xB6R+mEmvj9FKBNyc2aPohlq6yvy/Ftq4U11bLLbNjX9JhSZ7d1cWbE/kbcmQRQ+We4Tb64wof72iDMETfewTTbeJMXruRvR/EUtQOP8IrMw6Ot8ZoLs7erjjR36CKEseXNxImbodC3UOkrd85AqYWarxyeQn3OvmiKYJMrNXxvDVV4LltGfgnBLWEEKzWPGYLLfnM+YpP0wuImQYJQ5BZnyY+c4mrK6v0tSVJ796PfvRBfD3CgtXG/+fkEvnaNJ0Jk86ExdcP9BI0GxRn53nmcB+br/6Apt3AK67j2zaFl75D6tpFto5to/DD74FvEyBQ2joxY1E8zSCa68U9+wGymMcPWh5FihDonb1cU9L8sCjA8/CdJm5TBSvJk7k+dgTLeIVNdg60c3l+ozVmy5BK3UbP57GjKe7JCDY2mmzdtxPTd2juPsCKYmKaJrmudtyNRaIPPIFQFNR0GzKVpjk7RaJ3gPTACHYiy9DGWsvD8XZo78LcuZfmpbM3/65qRO56sEXq/gIETBiGNLKdJI4+0MpelxKvXKR+5QLIEP+H3yH+wjfQn/saltu8MSd1bzd/KhduMSW/Ad9vbf9nImBUVUWRIVII/E+Rr/1dgicU/Ew7g9szzIh4674lgCQd0ckHIUOyygIubaFNbqyH6uUL+I5Dx8Aw6vZ9uPOz5E99wLUdD7M29ii50QYh8HZZcPmaTQg8ui3HB7MFHhjOkIqWWa46gOTbiyH/eniMlTd+RDa0iWkB0nOJPfYC2tBWSrMz9Az14bdluLDS5N2pIq7d4OE9Q/zp/fv58YnLrE3PENRaHjSxssazO47CK3+FzOaIDowyf+IEO+89grH7IOqVcyiZDhwrxpXL0zQKBRRF4I/u4cR0AS+UWJpKLtaqKstEW/2PKlQIJM7y4k3yi2EYoqQyhOUi0m6gBiGhqlG8PmeUnb3YpY++gYiuMpmvM9CWoMsS/P3741Rr0Jbs5tD92zEnzuJWCzSPvYbx9Jc/8rz7GFQhMOYnsU+8SdhsSUWrmXaadz3OWrQNx5e0xXQyBgRtnWgPPYN6PXmw8Yl5p7e8iFLM39owpKTw7jHu/sNvoYsQN7h5PPOCkIXriUGaIgiRCEWh2dlH44mvUzvwOKaQ6Pk56pfP3hgbhBAohomiKLdNrvCExrHpNW43xC4VbdbqAX1RSSMaJ3rgbiL5NbzVJaSq4UgFv1zHTCRo7jzMlYstCbRE1ELRVBQh6YwbyOD2lbp3cAf/ZPg+c9/+28+0a/ab/+LXfDF3cAd38HnicyNgurq6sO3fbp+I3zYo0mc4Lhje2UYQgiYkYejfIsuR0AKODmdp2A4lx0fWHOIRi0qlTtGHTDKBU6lQOn0SH5Pi3DLmeon0E89hxGOEqsbcZp0HtnXy1qUlZBiwd7SP75xbJpSSXCaBmDxHtreTA7Eo1pX3CdZXae/IcPe9Y1jv/hi1sxt++NdE9j/B8bkyM06VzvYQZ26SXTQYGdiK2duLnLeJd2r84PRFHnvwIC+/epKhrUNMl5t8MLuBFBoloXP3lhxP7e7ltcvLnNBjPP/gcyy/+gM8t0lEqljLq3T1dhN+7X9Lu1vD9QNqZoJqsYR3+TTJrhzd20ZJdndz6cQHhL6HkUhSH9hGKe/SnY4wUFulOTdJ9J6Hqb37NpVAIV938O2Qno0yXU+/iHPxFN7cR1rYYmMVLRIn8cf/M+tTK0Qsnaf29JEqrxK6PsIwCDUNv1ZFKHVSyS4aDQfpB+D76OpHhMtANkK1+VGli66A+ilG29JpEjQa2Onr8g5B8CuX/NNCn5GEYHhXq73piiQMbm1vv6nQpcfzO3O8OfWR1rKhKezuSXGoJ074OZuYVwL1FvIFoGS7vDm1yQvbs58axFJ8n6BaRksk8Zfmb9qm5rrRO3rYtXgWY2mTIT1GGN+DTGQZ29dLX0zhnpSPsrpI+fQU01cm6LILRD2HA/c/zqUzl5n54DQDDz+H3tlBt/SQm+t445eoLs5jpNK4xSIoKn6tzNRGjbGOHAsn38ca7sYo58mne8iXbBo+fFBR+avxCju6U2zvjvDe7CbdiQirpTpHt1pUXFivOWzWbASwWhAcHmyjNldA1MrcvaWTiutTbHjM1WIYRoSY9EBV6R0ZpPLyt9GFxHdcArlC6fvfJn34HhYz/RQmrtI7toX48FZemS6zUNxAVQT7+9OMdrZxxlG4N66QeusVYr5NV9JiuWy3KoGWV+ns7iNVLpNMJ1goNnD8sLUYFLCZ6ePN86t8efe9JE+9fuP5O5NXiO/Yi5du/5nvv9T0bwRvo4YGH6tq80NJ0w+ub1OJ6QoQENXV2xzpI0R0ldv5dvyuQ0qJ3zeEtfcwzYun+VBPQlUVtj7xOBWh49ZbAUbbC7CjKfa0W+xIDJGvOJxeq7FRqCIUgev7xKQk2dODWVe4OrPB/6HHZePH36fq+hiKoFApEN1YIH74EGrvIN76KhqSyOH7kKaFogjcs+9hv/kKoZTEHnicuqrzNxM1IkLibNSxC0WSVo14NoOha9SSKXbuSPDKsYsYisRTDejsY943eLE3CR/8lEO77ubbp+Yp2AF6xKIznWBLLs2sW8Y9f42a6yPCEFURtMUMvCCkmeliM19nMNMGCASyRZhf73bGN2o8tOOjZ6kIgT51hdrxNz6SMpqdRKyv8dPcQS6uOTSvB96bXsC7MwX29qbpSUdZq9iYmkCGAYNxha/v76LktLyi0qZ6Xerj1vbZ1HS0ex4jvusgslbB1UzOVTXO5EOaXitAcnq+yNRGjRf3dhH9bKrxv3aYmkBTxKeSMJmo/jtHvgghWC63/EYEcCCr0dvYIJycAKEghsYImjFU/Zfz7vCExmIt4MxiifaYyaGUJKOFVHyDSUfj8XCZhe+8wvbOOOvrVTbWCxgT8/Tccx8rY0f5wZlVaq7PUFuMfN3hzFKJjXqTr+3OEbM0nEtnSEqXYhiiGjq+bSOlpDE9QfLIPWQOHqF6/PVW9bCiEmZz2IcfIeJWUBIpgkoZAhdVCFRVEGzbxxvzVaZKLht2gKWbxA0VpebxnVPzPJANEWGDoz0x1gpVmo4LqGiKQIYh7RGdVHODiRMnOfBv/k+cqsDliQWaxRpSVemq13kgopN5+w28ahl1eJTwweeQD3yBhKkgAg/huzww0sb3LizfMp/Y0hEnbqmw/x5iXb24l84RNhtoHV3oO/bifEIS7LNCBxon38H7hD8itCoBvGsX8Q/dh/thxcunJa/83Hnq5y9drSgKVqWIP3EZf3URxYoQ2bEPv7P3d96TRkrJQNokauofGbFLSFkaSVMlcukkXxgdQz31NuV3XkfXNTRFQb1WRpm7hvXYCyyePMveR2L8v8+X+P5qg5ihck93hHtGTZJRE8dSKTU9DF1tJbbJ1ljthfDn+QiPP/ZVOmWZQqWMHYnT3pum9L/838F1WH7+f8MPvv8GJNLcu3s7e0RIcv5dVt9b555sFnb2cWJWZTM02Ngo8GoVXtx7lOaJN2nbvZ9kLkXz+OuUhvcQVwzKly9TKlUxklkUTaPt7gc4JdNEtAofuiLt6IxTrDV4bHsONxScWm1g2y5b6hJR8WiLG5gixF1ZJHL0fuqvvgyKghSt5u0FIYmt25mUceTHxi4/lAwlLWZKNpevLuJstBQG6rbDwlqJJ/buZXD5DH5+Datawk1mb3lfZmGd2ls/ujHnEekskwMHef2Ni4QdPQTRlsn8WGeCB0fSEHqti/oE4aFpGoWZGUxNIWZq1J2b1x5hrUKv5uJ5HmO5GMulBrdDd8oiqkKx4fLadJmplRLuzAQEAX2daR7dey+xc8dQm3Wk5yELG+jFTZT+EZqxxE3jZc2TFBu3lyYFmC00GEzECIKAhqpjPfYC5vw07vhFzCAkN7SHtc4t/OWMC/EUhAE2IITKjr42NPzfw9nyHdzBHdzBHfy68bkRMN/4xjf4r//1v3L//feTy+U+r9P+3kNKCYGPAkih4qABgogaEn644AlDjg5m+M/HZ9g9uI3N6Xn2dMVRNJ1CrYmVymFF4lhDIywUinSNjTLft4efVBIM6gENt8myrzMqbb68v5fpQoOqL0lGDbJxC8t3iBkKDyZ91l/+W9aaAUNpE80pohz/AcbDT0MihX3xNIPRE/Td9Qilod00HJ+IruE4DSKLE3RQo/jdv0C/6wEe3HMfi4urDPflWK44bExMI+0GIMhlMkwvgD6YY6w9ytnZdf7c1Hj8kRfpCloZzgNdaRKWjuILFv779yiXqyQP3YXS1UfHY0+TtjTUyUu41y4w2B7H3rWL6shurjkGD4+ZjKVNtJd+QOC62A2b0jN/TH1mCj2/jpFMUewfIWUENBcW0D9mjiI0DT0SQfvgDf54xwHC9WXE5dNo6Syjnft5b9FBXs/2k0FAUnhs6ipjuQTFSp10RGez7qKrgoP9Ga4uf1Tqva2vnejV07cXyRICkUj++hradXzY3lT4mdUiv6mICY/nt2UouxncQBLVBXFNfu7kixCCpZJzS7DkQywWGpSd7A2t6U9CRuOo2Xbwr1e7AQgFc+sY5o7d1F5/idC2acsNkV9epT45waGHHkW1ukmffA938Qqrswt0bhtjcP9B5q5cI+tUsS+cYvcXvsacq/GOrfJwRx/u2y+hHfsxjY0NtM7L7H/ojzjZP4z0PXKZBFp7B8ahP2LwwnG0M+8gPYdqzUbXFHZ94QuclGle3BtnYbXAmxdKDGRjPL4ly5xmML2c5+tHd/PjS0vMqgJL19jTmyLqVDl16jIRy2Rk1zZWK3NICTOezpaRHayfOs7uvdtw3noFWcwjTANVNwjNCM5Gns3LF0lkt6Bk2kkPDvG9U9P48RSKIgikZKPmMrm5wpf29jDmbuDVqphxg7gCuhan7gTIehlz715is9fI1z1sP8R2A7xQknvoUabCKNuGLfK6Rqann2D5I9mGYHUJkelASomBRCsXkE0bYUXxUhk8xE1xp6imYGrKTXI+yvWKpsMD2Rsa1VlLIZe0bpvp3BYzabN+872Yfl3whIq67y7iW7YTFvItAjrbjpfIkJ2+RsXSaXoBvfv2kiivw5VzLG5WaI9EeX7Xfi61dfHB5DpS09iyc5QNX1AuV3kspxIcfwMj8IiaGp4fogpJvurQce4UyQcfo3n5HCKeQk0kIRKj/sYPEFIiFZWwaeNNXyP15W+yc7CLyYqPLQzy1SYVXzKa9NgxmMWMapixGC8+fz9vT+WZLzv0pyPsSZiMdsSphfv46eUV9FgCu1mjUnOJRj1+fG2NsfsGUOJJ5EYeCQgpSUcMwjBAJcRIpOiIqiRxaUqVRVfH832QEl2AtzSPtb6KiMZQFIXKu2/ySWa9mOll/NwV4gNbURVxk7zYxeUSOw70ETdVknqrCYZhiEFI7oZNVvgzddZ9KfETaZRUG6/PVrm8cau0V9n2mMjbHMgZ/yQ5MkVRaEoVPwRTBU36vxRRktRhNJfgyuqt12rpKr1JA/k7Ji0hhLjhp3ZXu0r6/VcpLX3M5H38Cj0buzEffBxH0z/TMVW1FaR3Q8Fb0yU2ai47Uyr7wklWXzuF07DJJOP8y7sO06hWWRHXfdOUVo2w54cUT79PW/8oXhiSi+nc26ZQi6nMOQbjhSbzJYfd/W3Y7xxDtWskEykUsw3KZUBBUQTN468Tv/sBMkNbUJNpykaMyXLIqYkyX7l3jFT/MIECRqWMXykjVZX63vtoLiugqhiqpOH6uH6A4japaSrJ0V4iU1fR56b4gyOPcqUSsFisoykKu/eNUK00CC5MsnW4l8t1hT8/vUyPpRFp2MRiEVYuX+GlWJSv3vME8XPHKAUK9Z++Tjqe5lJmgJGMRVTx6bICvrK/l7NLFVbKNrqqsK83xUjGRJUerqIgeofReodRw4BA1WiEIeKXJAhV18Yt3CZb/jr81UVUGf58a+ufZRCuf2QQ/nlBCIGVX6X+k3+86ZrcxTms3QfRDtyN/89ACn2eiAmfL+3t5p2ZAvObrWSl9ojGo9tyRF9/F21xEuYnSMYjCE1DhiFho4HwPbhylp6tw8wV63x1fy/jyzH2uSt4p3+CXi+jahpORw//eu89rCFYr7o8NGaiCkE2ZlBquJyq6LznRDFFhOcyIaW//2/oqkq48yDvzZVAQrsWcJ+3hHfyLVRNoVlysFdXME69ywOPP89PnBS1xRWqUlDbvYuUYRKk24hUC7iXT2HqURpHHqE5sh+rtEmms4OakuF408RxQ7qSFsWGS1fSYiAb4e6BJClL5e8vrFKsuxiqwpax3RRfX6Di+Axno5iNOm61SvzZL+MvzeOFIYpp0X1oP++rnYwXbh4Lml5AZyrC319YpusTVWASeHdqnT07tqNefBfp3TqOqIqCd/XCTWRKceQAPz63QBhKxOY6SjROiODaWpVUROeungjBp5ChimlRajjk4gZexKBkt9p/ytIxdRVFtObPw2mLMxH9RjX4h9AUwdGhLALJa9fWubJSAaGgdvXiLy2wsFrkh26CL/cMEb79Q+KPP0/90jlko4Y49z6xJ7+AnckhpSRUNBxPoeGDqoqWb9wn+ipV4aZxu6mbiK070bbuRJMhga1x7MIyuYTJpiLwghBTVxlui7IrZxEEn07u3MEd3MEd3MEd/LL43AiYCxcukEwm+bf/9t+yd+9e2traUJSbM4WEEPzJn/zJ53VJvzcQQlD2NU7PlVuSDQhG2mMc6EvRHtYp1gKOnVvmma1d6DJOz8g1CvlVBvtzrBUqLFUaxNtyZO95BrQYx5oqr0wWcfwKqahFf0JFVVVONwy22GW2pkxWaXk3lAslsqbP/tFeSm99H4SKoggMXcNQfLRcN/aVc0TufQxteBvRx15gsWOYvzi9wvh6jZwM8Fc22NG/hWcyOtnRUcLVOQaP3svZFZddu/p553vv3JhkCSR+sYjmOKxGDXqzcar1JrU6fK/p8rXRJOmp8+TfX8SvF0gODjG6Zzub589gLV8lWJ9irmiT7xtE6xsi/cgRsCJ0hXXapscZrFXQ/B606CDNeIKgVKDYNsDfvTeNaRpEk1twXZ/YpodansDKDdCh+uDYCN1ARGPIaonmpbPE+odoLM60DN7zG+w9lOHyXIxK7aPgqVrMs7e/n/09CU6uNojrgnuG2xjIRJjPV24EuTqTFkdG2tGW07ib67e0AWNoFC/x6UaGd/ARZOCTVGnp7PDPQyQJIT7KLrwNJOD+DGkb37KIPvAEldd/SGBEMIa3YvYPoSZTOCffQYjWYioqfbqSFlJC1/i76PoB8qvz1NfXiGiC2vQkyvISPQ8/z9m338PUFLqW1ngjOkpXJsYb71+jsKKy9/6vM1Zdwn/t7xm7/CaZZ7/Jupnh8lqNt9YrnL5aZl/PYe459AC9c+fwiDClZ/l/XaqyVlpv+UYBiXSK/d0JtiQU+g8d5GreZjzfoNTw2Jo2CGTIysoGpZkZhFAQuR6mqwG6qoAE15ds9IzSvTqPZ0RgYw3teizE6OrFrbQCoSGCcGGaLd3bObdQQMgQUwa0xQyqTkAgQVcUak5Ab0eSwNJQBCxWXCq2i7weYGmePsfOF78ItRB1coqYbhLfMopSWCf7zvdxyiXCXBv6od1oqoazMPPhCwYgatdx3v4xzbXlD988ek8vkfueoM1KYekqTa8VJB/MRlmtOlSbHpamEtVVHhrtYHubSXjdM0MNPZ7a1sErV9fZqH4kndAWN3lmRw7tdyzY+yE+LvPxsxAAjXgKLd1GiEDIkCAIiKbT9KdM9N4BWLiKO3GFaKYDSxE0mzb++dPs3XeQ+v7tlKTBkd0jJHTJxbk8OVnAnp/BiKdouh71RhNNVUhFLHwhcCauEH/2q+htHfhz03jT1xBhSNC0EbF4ixiKxLFPv8vh5/+UNy7WccoVlFiMPf1ZBjMRuqpruGeuIps22a1beLxvgPxAG7W6jRuEnJgrsFoOmXUUElbIaEccxwswTJ2ORIT3F2s88+RzNL/934iq0BYz2Kw7DLXFiGSzPGs3WXvvNSpreeIRi/6de1nvHmOi6LAjKFD9h7do1KoI0yI6MIzqugTqzdVW5UAldJqYnsNgNspC0ca7LssTXveWOtqXRv4TyWw7VJjbvH12LcD4eo39ne18ml/Xz4MndC6uNriwXKbpBaSiBkcHMwwlVcQvOBjIwOfeoTS2FzC3Wb/hsBE3NZ7a0Ulc/d0z9w3DkLaYQdzUaF+dovxx8oVWBVWwOItYnEEMb/uZ360R+Kibq/gzEyBBGxjF8iJkNcHA+LtcOnYSU9cJBdjlKt57b5LKdTK6fYT62ioxQ6NsuwghiGkCo7zB011ttM1exH9znKTrsbWrhwd3HmIqgFg2gxDQqNuYQUCiPUP74ADB5jqm0uovVlfy1ONZFntGsBWLznaDB3JFQitC/u5nyFTWYGWOeDKFuWUbM6kBzPwqSdMnlKA4giAMQGn5J2WSMeT8JKXVDaxjP6InkqIz1UZycIgVVEY747S/t4qz8wjfni9huHU2A42e9i6Uah7PjFDxQuYSfXSkulFkSLnmUjp+nONbDVa603TEdLa1WWQ1l8dHErhhElUBJQxuIgClvJ5/L5RbMuB/UUhFa3k0BcH1pKKb37NiRZBCuYXI/SScSMvDoXH8jU8cQxA5ch9ONHFL4PXXCT0MaL771m0JoebF08RHxvBTbZ/b9XyeMAMPpbCBrFXpjCd4caSLzeEsgZRENYGlhJg7d+Ice53QNKG9A6+Qb7WFji6a1SrK7BR9T73ID4oG4VKZJ/QCaz/+ATKQFJoelq7iFCfYFdRQ7nqOmKGiKvDcrm7ensqTjOjMF21K5RqJiMZgv47iNvGzOfwdh9g8u0Y0neQrd2/F+5v/jKiUUTSVASOCzHSwqSaonX6X3fc8zYqEaqaTpewAL11cwfB8Oo0hDn/xf6R76RJ+V46ZxTIrtk624DN6sBOlKZhYr9IZN9je1cVINkpc9REy5ELepnjd78wNQuaS3fSN7aA6cZVaJEUiGydo1HBtG+tLf4QahEhdR0l2MP72+C3P21AFddcjl7AQ9ZvbmyoEIggoa1EihgGx+C1/r8iQ4GOSYWoixXg1ILy+dpCeTxCE1GVrXX5uucqerhjmbeo+fN8nsXUr8u2fUmq4qIpC2mqFkBw/INLbB6k0hAFRxedLe7o4tVhhcqOGH4T0pCMcHczQaUlKnsLkxnVJQwlBJI4+uIWwVmHTrpMf3cHQM1HspXlko7WfdJo033kd/dmvsonFq1fzrXm/EExt1ElYOj1J8yaPqy3tsVsqam/0cQh6Y/Dk9hzvzRSI6wIBDLbFuH8oQxTvN9q39A7u4A7u4A5+e/G5ETA/+tGPbvz/9OnTn7rfHQLmV49yoPGd88vY7kcTkUsrFeyGw4GsxqYTkotpLFy8hFB1jj74JMmVKZgZZziXIxzZgduzhcnQYnKjxtW1GglTww88giDkUEolvTPHX55awkwmSSo1hjKCfF5QN6OoxVWioaDZbNI0YwghMHSVhc0qKcOkzam0spFf/Jespjt5a3KTqY0qYSjZUCO0D4ww1ahyKkjyzJ/8z9ilMno5z/7hdtZW165nurYyxiW0PBp8H1mvMrKjh8MjOaZKTb40GOH/z95/BUly5tm94M+1e2iVkVpnVpbWhUIVUAAastHoQcuR5JBDW5LXaFxbYWv7xJcxo+0LX2i2NNs147W9l5fDITkz7GmB7ga6gUZDq0KhtK7UMjIjQwvX3z5EooBqVGGAbgDdRNcxq7Kq8AwPTw93/77vf/7nnNzrP8JymqwVy0TSJvbF04TVMrlv/SPqM9OsChPv+AneWKqxer7IiJfkIbPB6tk3SKgBQgjc6SvIpkXivodxN9bY8GVCIWjbLu0tS7DE4CBhWbBmh1jZONFY/GaQoZzMomoGkm6AJCNHIhg796Ol43xndw8XijbX1+tAp3t2V6RJNggZu2cXQQgRTaLihCQNGdsLGEhZ5CMymvBQ730Q2bJwrl9GeC6SrmNM7kTee4Q7uH/fxe8gwjAkH79zWIeuykS2bKduB0fWkHtGCI49RlID//I52q8+T+yxP8DdIgGkrl6krEbW0FgsN6lvrKL3j+IFIZLjkbK0zr99l9jGPEfH87gri8Qbq3xr70He3gy5biuY2X7eXFlnKdXHk3/8z9FaDTxD5XtzFQpNjwAFxw345VKTV1fa/J8PHiCxeIVT714kHU0T6UoSIKFJgq6Ywj3dBquhwVi3QW8mTrHlseEI9mYNhkxBoxFyOhyijM41W2KbEER1hRPjOW6s17i+usR4bgeDQ0n04TE0SSDJCl6tghaJklZknIiFHrFIpuIUF1ZRTRPJbqB5AelonL5kh5Ry/YBYVw45l2FusUDV9pDgZiG26bhMewbT8SzPmxpdEY1HZq5SfOt18FwQgsraOvW3XiXW24va1YNfLKD0DqIFPvbLz+FvrH3omxN4K0vw2s9JPfZNHpjI8cKVjse1RshgQieIG3xlKs/2rI4u/Jvky/uIyx7f3t3FZlvQ8gOyiTiWsFHDLxf5IkkSpt2CjTXCRg05mUbkunH0O2dqhLLKajPk3GqFlhMwlDaZ6oqip7vQB4fRrCiN65cBUCpFhtJdVNUI1VDBv3aJx57ehSGF5Mo3WEv2k82mCMtVJFXF8QMCSSGSSmBYERTfxjdVwliSyrtvkTh4D4Zl4s1cJfQDJE1HaAaebFJ2QpKtFt2VZR7as5fXr68zkdToz0QZW71E5e3XCcMQOxBsXLrIyFAPieNfYymMcnmpwo6USqHhUHECik2X7rhJJmYwW27TcgMODqZodg2w7c/+nODKWbz1Av2DCdydB1nfLNN842XK1TaaImFXbNpvvEJuYo3sPQ/RvXruJgstSRJBqYjYWEXqGbhZoJATKfJJi2PjeSpxjWlXYTxrYQeic+3KEqNpE/MzIAAlxMe6Ev0mveehpPKL6TIzGx/kXWw2HJ69uMZDk13szmmfWlljCJcnt6UpOWlqjo+hyGQjCib+zULYlw3dEZUdKQ339IWPbEtbGroscC+fQx2duqNZnOF7BK+/gL3QsXCVJIn1sxfoz/bSdc+9rJ9+l0xEo1i3MTQVU5XRZIFz7hRj3/lTLqytIiFIR3RURSYT1YkYYJ/8Of76GpLnYQqBWJnHaNZ44NGv4XX1oEztxim9guuHlDzwDz6Ems7hhj6JeISqp1IyU7wxW2GhETDaneTwcBZZUbB18Ea6yI1uR66s0b7wHuZ4iNFwGEzESUckcjoMah6yrLDcCshtzNL90KNICyvMXZ9FtRJYew9zmTjnF+rMxjW+fegEvqzT3HAgCBEEKFaS4kqbEI1QCG5UHLpjCS5cWyCiqWjlEorv8fzVdfoTJp6f4nCvRRj4nYVf8KuUyGcHSZKoaVGK9zxFbXWVpK6QaxZQpy/etBrTduyj/TH3kizLtIVCxQ4J+3aR+84Y0Uvv4q0uoCTTaDv34eZ6b86rvygojSr2bZqc3oe/OIec7vqNFHi/i4i06rR/8RO8dI5SepDNcg2raNM/OogRMQjDkCAAaWAEJZOjev40gR+iigDcGmJzg8jgMI1ImmUtyaGRDPVqg+D1tzAVmarnETU6JYlt3TH8WpUpu8D/6xsHqTsBmirTnzJ54co6qYjORC7P49u6cMoLmLsOU56dplVzqKsmD03lkacvYRdWUaNRZEWBwCdmV0mk0iw0AjKGTGR8G0s1m6bj4cVSSJkc87bNas3lG/seJvXf/gMHYgkOx5PIdhbpQoneB77KgR4TCQlZBIShjQhAUjSuFMq3nLNzZY/o3hPs272T8Nw7UFzDHBxD3bWfpmoQKgJJkuiNm3xzby+vzpRY2rI/Tloax8ay+KEgqYFIxNGTcfxWRx2nyp2xTkLC3LkfNxL/CGkaygpyPAmbGwDIpkm5tZU3A9hCplL3KLudZp0VVabu92Gqt29okTI5Rh54kLmXXyIIQ5pu5/PMaIz+Rx4j3CJThRBEJY+HRmLcM5ggFBBRO+4IIoSmy0dyW3xNR8p0oTRNNtsu+ekrH1H1+OUiWqPGTxdrbDacjqJmOE2hblPbypIbTOogBHv7k+RMPrYPQwoDplIKw/t7aHkCRWZLoet9kZzuXdzFZw5ZlrE/4RCkyRLK76kzwl3cxW8LXxgB8zd/88mCpu7is4WsKJxdrOEHgsl8AlVTcANBT8JicbPO//fsJooIKBSrHB7poUd2ePal00S78xzceZzdXRa1pWXcy2eIpnsJ7CjdcZPtOZMb8+vcm5HQpi8yLuAvD09SP/UWlUvniVk6f5DuIZzYxU8rMjIQmhGCQGI0F6XtBjiawUYQEukexkt08/fzPu3ZFdJRkz8/OsrCZoO350us2oIjYyPk+qL89ekbtEolUqkEj+xMUK/WkT9UjRFbfxRZwqlWaQUSByd72OX6bF94j/XNDdabbRRZ6hSVJMBu489cw0730Orbxfffm79ZGNmdkLnxo2eJKBK7e+OoWwVv4djYZ94mvvsgitOxaRBbxyHHE2wKDWlsO8x2igdyGCA5TqdrTlXRp3YjHzhKdPs+QlXDM0ycMCQ72MuJ+lkO5FwQAWZlGTU5Tjg0jiG8zvH6kFIg3aUhSVtWK1sTX1vVUY48QGTXAXBd0A3cSAz3S7YY/H1Ad1QlHdVvdtR9GHv7k8TV8I7qHFlRWDeTZLryyKFL2GogpbIE7TZE49jdgxRbPk6hgmRaDMY0pJKLIkt4ukYkYuD5Pm0vJKYI/BuXiI9O0qoVCV2X5b/7rwwdup932iGGamLG09xwfdb6x+gOm5wNE5xamiMUEAqBKkl0RxT2DWe54uqMZYd56rFBZhcKnL00QygEUxODjB/YyU8vznOyVsEOBN0Jk//lYA/bsmU233iberVOOpvkyd0HOR3J4pV8shGdPzrQz2qljS4JArfNXMHjrZjOw31DeKdeB9dGGBbNWJaSGUf3JWLbd9MIU4yNQn1tHRG4SAkLX5dJhA6yadIbU1FVCY4+RGP2b5CCgKDdwnc9BILssQc4VQoYHNYoNV0eyQnKL7/T+RIUFXyPhKkhwhD77EliT/0ham8/bjyFXtnAvoV8+QDe6jJGpchkupvkgX4urNbZbLhkYwa7exP0RCDw3DuuLZXQJ2+AZEr0dsdZXW18qbr5JEnC2izQ+sWPbwbLQqfD03rk67QT6Y8UEISscnK5yamFD4okhVqbc8tVvr2nh6E9hxHz11HTWUKnTeg46FLHaiRTKhH6HonSHIVz51ma3MtSUhDJ9nJZSjHaM0jKMugbHoDSOm67TaxvjPW6Q2tsL1g5JK8KaAg/QFIURCRGLeiQ9xFDxVcM5os1soMmf3HfODFdpTFzg7mXX0ICTF3F0BXaXsDsQoFD/ae52HsvORwMRSUWMQkqLqgyFU9ghtB0A/wwZKNmc2WlgorB3mNfZaNU471CmwNCQXr5h/itNj1xg0AIXE0hDAXJ4iJ9ahOt8IGCIXRslKFRgnoNNesSaAb65A5aKyuIn/x3tM0WA4PD7Ln3fpbTQxTaAZam4Ho+WeOzseUx5ZDxrhhnlyq33b6rN/FryxaLjriFfPkw3p4vMZbpw/w1lDVS6JPVIKsBdMbrL9P9+KvQ8TjcH2WJEJvOnExGIh3RyMd0hAgRvtchsm+TmSFJEtLCNO7CzK+8Ds2FeYZHB7BbbdKpBF0DWVpbzUWWAbLRsfWL6iqpiI7rB4CELMukE1GuL80juQ6yotC3bx8xTYbqJqmlc5BUCR76Cuu1dUIzTmFsPy/eKFCeLXBoWx+74yZ9qkO7tMqhfIaJkRSnFsr83ell8jGdxybShI062qkX8GpFfFklKimMqIOU7ICnugyc029TL6wiRMiOXbsYyI1SW1rlpeweuiePU3ThzbkSrl+hL25gGRoL3QcYiUC8soRsWaiGQUvIKIZJ4DUIgXzMYHW6Tiig7QckU2nKfqdAe2Ojzt6+BCVHbF2Dnx8kSWLdkfnppRXstkO4ViNsNsilY3xt3wmiZ17F3LEHv7vvzvuQZWbrgpeur97MmjBUmaOj97L/yP0gSR9L3nyu+Icqs1+wXe0XAV2E2C//jPbgNp7fECzMfZDrY15Z46uPHWMwoRCGIb5m4KdyiFDQcH2EAF0xkTWJ5nqJyP0H+dsFh+19be5LSzTsGvGESVdMJwwFEV3Bdj18JApXrvLTdg+X1uo8MNGF7jb5XwZ9oppCJZrgYqlJRe/CG0qQnrqPnFPlkVyIfukd1L40qb5e8D2MWJxIrYJbWCbcWCMbSxONyvhlwXBMZePGDPZ6gXa9gZTK0DKjvDVb5MnRKcIblyAMEJaF0T+M4/vIskIrACEUoqqMJEJ0z0YTPrIICbeeaWlLJb8xy+VXf4GpyoykLdyZqzA/TfQrT+L0j9ycp6QUn69vS1P3O4qiqAo6ARW/o74OZYnI4BDhRoGgXgUhiMWjdOXTiK5JgtvcD0EQYO3Yhzs3DQiCVot8WmMGaLkh5DPU/A+u54iucGm1xj0DMczbUOOhCEkdOcruoWE2z5/FbzSJjoySnNyGFI8RhuEtauQwCDAJkGQJ3XVRKiWE7xFJ9N1WYSeEIHQdopLayT29Ddq2x2aj814/FMysV/mD3b0sVdosVdr0pqMc7o/TF1WQwzu7CNz8nbasUPWtatjdOvRdfBngB4IfXih8op/91p5ulM9men4Xd3EXnxBfGAFzF78d+FuUwfGJPD+/XOB6sYWpK2w2XHIRlXtHMpxfqhBLJnj1eoHjE3m6MjH68nHil09SeHWFOgpzm02EgD27d3Ohezd//1qFf3psFOOdF1BrK8Qee5qr3/trPNshaWpEPBttdZr1hVm+9tXv0lZNotEofYaMJgk2KnWQJGKxCPNVB0OJk4tbbNoBP7tcoNL22N+f5L6xHIOZCEvlNj999TxarYRqN2mgc2F2jVFsknGLar3VWRdJEupW6GN3Lsn8ShEpDDmakWD+BqEko2kqhqZgSSGSJCOPb6fVaGE9dJS3z6/fJF/iuQxqqUAYBDQCaLgBKR1kIZDKRdo3LqMNT9CbT6PFaoSagRRPEhomTgir0W56BweJtQqES4sI30OEIZKmo9z7AKJcws50/Gzfn4y2jQjqweMkWnXwPYRh4VnR23ryCiFu26UUhCFtMwpmtPPCXfLlf0rowuMPdnUUYYvlFqHoKF/29qc42Bu9Yy6NLMvoS3PUf/JT/O4e8l5HTaZlu1B6B2kOTDK3WEAIgSwr+I5H0dXJyQpEolR8MONpyssrxHWZsNXET6ZpNWwkRcVPd1O7coroG8/z5IPf4Lklm3gyS1Ba56xtcv/UKK+/tYjthSCBpsgMZSz29CX52eUCAjiU0zBnL7N32wD/6NgYlNYJdk3yN788ST3dh71lXRSRofzGSyTnLzNXrOKFgmapzPrzP2fPkSPc99ATPHdtE9dzkYTAVCVCXUUIn0gsSmTfYartNorbpuH4rNdslJhBtWeUhpLiUFgiJjf5RXEDSYRojSpxQ0OT84S6xt7eBL7vs5EeIPLktwnPvoO7towViSFN7ebdusz1s1fp6e9mJBch5ZSpvt+1J8uYlkXC0kDYyKaFkkrjT+zGlyS0ZhMlk0ONJwGBXy4R1Co3v0fRaiKSAV0afGU8zXor5MpajZevbzCYsdiZj5FQfr1siv/ZYThtWr/86S3kC0BQr2K/8nO0r30HV7rVIqvkcAv5cvM9rRa/fPUM39ALxKQQ4bRRYwmkfJTAMAnLm1BaR5YkHMdns3uC18s61y9cYmRXyMRgF10PPELixhnqP/5bJN8jYmg0z75NdGwH1f3HuJDdzkPyBimnhjQ8gV8u4ggZNwgQAmw/QDFjON3DnFsq8539g8yWmiQLy3iBIATarY49S0RXaLsB9dlZ+nv2MGfGWfUk9vYnOLPSsdgTSNheiCqD74fs6Uvw5kwR7M5z5L2FMk3X49GkyWq9DmHISsnD0DXGcjHqtkuz0aA1N0M6EgXXBtmGMMS3bbShMUTgY4zvoHb2NM0bV5BVlaGRScrNKpe/9z2SDz7KK043DdvjocmuToPCZ3CphmHI/r44M8UmdfvWZ2A+bjKWNn6tXBVJklitOXfc3nYDak6AeWdh4l18CJqhMzo1Rv36NQIhUGUJQxaIrWYRrX8IX1FvOz9RRYh75fwtrwkhiBkq63UH0WzQlUmy0Q7YLJWQZRlFkbEjOsPZblqBxJWNBqos0RM30VWJyN5DeAtzWAQ0BUzddwz/rV/S3FjvWD1es6C4gZjYzcA3/pALtZBnXzqHrCh8/egk4u2XuPrLFRZ0hZ6YznAkztqeB5krhjQDQaXlsFlr8q1hk5hQCByJzWYbuTrDoW8fw6+Uuf69v8ENBZamkLE0rMXrVCrrxL7+XbyZNq/MV7lQaBCEnbndctXm7GqdbDpBMhlhz2QftlIkcD380EfNdeE1GiiKwmhM4upmBYAgFKi7D3J1ps1gKkJDwHK1zY585HP/3ttC5aeXtogTWUHuHUR12pSbDV5sRvjDb/8ThGl+bFj9piPz3KXlW3KkHD/klRsbRI0exuKf+69xR4TROEo82SmC3wZK/8inbniStpq3flfHcrVawkXizbrGQuFW9Y/dbPPc6Tn+8L5JEnKIW6mxslknOTSOuH4NIYHTsSZAMkz07btZXrDZlqihRWSi+TyOGSfmNlHnryPPLaAOTnJ+vYaV7qfWaBO3NPaZbUovPcOmprG46wiz9TJ+PMUv1m1q5SoiDBnrTvIvDnUTLybQVZnq8jyRvgHs65eQwwDFMJEA1XMJ11f5zsgOLm80ub5UJzAihAKCjXW03gHmsLCHp4g2axCLQyqL1DdMxVd4Z6HC3GYLIQRDSYOjiYDM2ZeZ6t7F0sIGSjZPGIuzL+JTeeklwjDEVFVktoj3wKf9xouYT/8pjm5+cDJDn/j7t4XoDJdJTXB0NMubM5v4sorU04+azSMj+MrufoysgevfnmhQVZWwp5/IsQdpnXyNsFlnIgrvaCpEYlS1KIH7wbV6aCjNXLHOYMpg9KOOZgAEIkTK5+l98usgSYS+hyckSrZgueohSzCQNElpAkkEyLKMWVyj/crPb94zsdEdZNQRHEyCX3kORBNxurz121oTSoZJQ48C9ZuvtdyAC0slUpbO9q4I94+lySgeiH+YfLmLu7iLu7iLu/ht4C4B8yVGG40rhSYX11usT5cZzkS4L2FxbqVG3faotxwMTWEiY/HGbIt0Msa7sxv82f5RhisLlC+fJzbQS6XUIqqrhEJQv3iOA919rOTiXJpeZkKVkIpr2HMzJBRBTVVYb/toskbashizXMT8WTa2HSJ3cC/2ay/gRBKkYiaVUgU5YsD4HgpGisVNm7fmK1TaHqEQXFmv0/IC4pbGqRsFgs1NYlJIYDtIlRI3ujL0lmf57oFxfnBmiUbbQVMVUFUkTeOx/aP83ellnFKRh4wURrXIgCFoxlLE5ADZrlGJZNhoB0iKihEaXLN1Mj19GKFHJJdFa80QU2VCoGF7ZC0TSkX8jU5nQVCvYs3Pcs/YAV6/XkDJdN3sfjpb8bnn699Cu/wuVcWi7bhEBkeIT+3AvnKa8MYVzD/4E+wPT8DZChu2PjT7vUMg4l18+RGTPJ6aylD1MriBIKpJxFRxR/IFwKyWaP7yWczJnViTUzg//W80bkxj6CrGtv20J/chFn/e6TYTnY61SqPNwPEHqW1uIksSy3KMdDqN0a4S+B7G1C4qly6T+tY/oaQl0R/sxpckurNxpFWPa1WPwa5+hK5TbLpIbNVaBcjA/eM5/u70Ev5Wh6PQdKS+IS7UQ3LdefbpEj+b2yCMJfF1E+hkPBxL+my8fgpXk5noitFwAlRFIhMRGAtXybtHsT0fLwBThlCSkJNpkm6DbWN9/OzMVVYGH0QLfSbSJt1ejUI74IqeZ7hexnn7OUZGtnFgvIcr8wVEEOC5HtpGgeMHt9Eb7Xjhq7LMT29UUeU+MpOjtPyQ5WsV/C2iKBY4HO5P0ee6BIaKEJAwNSxNxg8FRioF6SQilkAOfHRNR7MsvFYD9/I5JFlBn5jCmNpN68YVCHwk0wIgkFVemylzceWDIO/1us3FlRrf2NtLVv39W2hKpSJhq3nbbX5pA7NSxk3nbr4myzIzpY/mhiiBj780z1rg0zw4QMoEwhD3xhUkXUdKZVCsKJJhEEaTzBcbVLpHuXpqHoBmpcKZ+Rn23juKsjRDPJNCbTcJXBejp481H+qn3+G1yB6UbePE1Tr3PvpNnL//KxpNG0NTaPkCs3+AYHgCa3wbkzWfvzuzjCzDRKyH/sefZP3Vl3BbbWwvwFBlVFlCJUT4AZvNgIii4/keD2/L89L1dQQCS5XpNWW2jXdTrLUwVYmG52F7AQLo1UEOfGTfu2nj47R92o5Oy/WRFBVrcJhld4ia7WNI0BXUkWcuYO493MmxkZUO+aLpqNkuPFljs9lGlcF9720ef+wPOVPVWa00eHNe4eHRGOFnMJ7FZJ/v7Ovh6nqL6xsNZEliZ2+c8YzZUYr+mtD+gTZARb7bJvhJ4Ychkd0HMOenEb4HiJviAUk3UKd237FQLYUhwvuo8tNQIBvT8XUDx4hQ3NggFOCHAUlDZ63aIujKsGPXfnLLZZzSJs1YjNTRe6kPjyP98H8jLzmYe3eh3riAqG5iRXTYeYj5sf2cayjU510GYuAqBnbvGENJnfDMi6wvraArMnUnoCeusLK2ibv5E7524tv8j5kWhCEtD96bL9LTN8Xy+Ru4QUjfAw9x8uoK22+8wVhKB02n6QRU2i6VlkuwWmHv8hJ9mWF+cHG9c07er8NL4IfwxmyR4UQvxxMhZb/E/PI67UAgp7P0jQxwT5eBfPlthABF08jdex8vOwkyEZe22xkfVFlGV+9sW/pZYaPl31StAJ35sBkFK8oKsKYlyEh3HrMUReHCYv0W8uXDOLVQYXh3Dvm3VGB1VR3z8H00X3ruI0VibWCEINP1yXcmK1RciUKjc613x3RSuvjtBA9+DIRj0+gb4/rlzdtu912X+bLNjq4IjUab6bMX2XvvQSI9w3jXLhK4DubgCGJ4G6utgPsmcvTkklxAMJs7wOLCKpaW4PChbYyvXKA9N0vg+4jRKVZmSxyZ6MZ695e019fJPfYEby5s0jMxzo/OLqEZGno8httoMFesc2nV4gnJxz79HskHHsc78/YH2V2OjRrTyBy/H7uwSA6J9XaOsh0QM1RUCXxJhlaDoLcPORkSpLIYoxNoB+6loET4/pmVm4o7WYTMnr/Mou/y7T07GWmV6UkYrK4uovX0EzcFFc9Dk2WyUf0m+QwQtprI1TJ09X78yQ8D9ndb5GN9nFmu0LADcvEE+3rjdJkC/zbkiy9pLDc8LqyU8ULB/t6dbPvGCEppnYis8I2vTvGfzhSobDUc6IrM4eE0hgyrjk+p5TKeMD/WRs/bsi3zJY1X5qpcWftgfioBh4YzHO6zsJo1mi88g3A+MMGWFq7zyOEBnik0KBmJm887U1N4YucIiXev8tGnP5h7D7NuJfgwAfM+Km2XSttFhOmb+Z13cRd3cRd3cRe/i/hCCZjTp0/z4x//mNnZWVqt1m27fe5alX02aKHxg3OdzIKSLbi+3uDaeoPuuMF94zmub9lsLJZaHO6LIYsQ04pQqdRJR03CU1fo7Upjex2jaEWWiEiC0PfRLp9ifPAgV2cKcLAfXXGprxdYKLWo2D5tr9P10m4KJBPC997G8xVuVOuMHDiGuHYeTzbIj4/hT+3nvJemG4VTixVUWUJTZBy/0xncdAOWKza6Au0gALXTJeZUqyyXWxSGdrFj9iT/eKyHgtlDsR1g6Cr9CYtitcVYVELODuLm4mSPHKP+7PfJRny0VJpyEGe11ABFIbVzHwUjSU2u4EmQJ6Bx7QbKnjxqu9MhLKtRJBqdwoAkIVmRjuXZZoE9+iWyO7Zz0ZeoKAY9SZN7eiI4gccPNi0Sg/egybDW8Ki8tcjju/cxcuMtpM116B367V4sdwF0irTA7553d+iTVLi5qPi4tbmiKPjTVwj7hymlemm99DzdkTiKDG0voCE03q167H/iaezz7+LWakiJNNqOfcz1DpGZPgvAQt2jaeXY25XFynYhbduDPHaAn1fg6vw8lZZHKEIiGwGTY8McMlUCAeM9CdxQcGwsxzsLFQxV5tBginPLNWp2AISkIzqrm3V6dJmIpnKyZTC46wAzZwu0EiHqh4aFuF2n4vs0QhlTUyi3XMZyUVqujyEJNpdXmMoP0ZuMcG2tih+GTAyM0m9K/ODNazRnZxBhiBjdzuWSRld6BDXqc2ZmnYeyUU4vrCPmCgxu38G23VMUmi6qLDGZVBiOujiEyKpKl67SZcpcWa5TKN26+Evl0qQlH5GIIvwsI70ZRLNB4Ac4oSAfN0GEKL6HKG/ivPUyumHipzMI1yWsdlQZ7ZNFlFyeyL0P4RbXbwb5FtviFvLlfdhewOszmzy9IwvB7xcJI+w7h7ADCPejiVfvk2W3oN1EbJ27RNSk8ezfYh64l+YLP0a4LlK7hVdcRxufwj1wgtLVeeaMfhACMxolrFbQZZnNs2eor5QxDIvhfBqvvEm7UsXNxFm7dJmjj+2h0HD4j6cLPD4xwD/9i/87uXNv4W4UsFUTZfchCkN7+K+n1listHH8kKGURcVp895mma8/9ChrP/8pchiCEKQiGnoyRREdN3BAklgoNcknIvzr+0epNh3SckCi3EBtXKWdHeBnnkxbVUlHNFKGTHTuBmvZCTI9eYorax3bJ0lGCXxkIUg//FV+XDaYK1RQZBm1VcMMXL664zgj1TmUB54kePd15OFJHGSKvoTmBjRdH0mSCOs18qKFJhkg4FqhxuHBBDHpNy8uCiGI4HGox2B/TwRZ6hQtfx3ly4f32ZcwOnYvt6n9piM6SUP+1MVRRVURQgIR/O6NLZ8z2sks0a9+E+fUG3hrK4CE1j+EcegYdjx9R3VuoGqoPf23KAIBJBGSj2j4vUN4RhZ14wcQBJiKTBD4SIqGf/QR/lvJwtvzKE6zyaYnUV6F/8e4ijo0TnD6JJGISfv1cxiaiju8g/dyuzh9bgXbiGL7IUV1kVUlzpGhDIPeJhszc6iydDN76P1rvF1vMBJUMFWDIAhQFQ3PC1h2FEJZQdEN1tU4STmgMD1Lb0+O6VINb+sS0hUJXVEpXr5EcGQUpM4wH4/oyJJEy/XxghDbDYm6Texn/jNPTUxRPDTIWivAD0IGUiapbJpm7BjDOw4zF0Z4vq1TbYY37XkjusJ4LkpSFZ9f8AsdJUfDucNYtPXRthd+7MozRGK9fmclWrXt4gQS1mfAhSqyjOraIEn4unlbpfmvQgiBOzBK7Ilv4Jx5B79URDYM9Kk9SJM7seVPVv0NZJV3l5ucXizffN7IEhwcynCkL4L0CeyTvihIVhRXquDdwRZKUjWqbZ/NdoirWpixKGsXLrLqSnSN7kZTFaqNJkqpytrQQd5dbtAIFf7H6UUmExpRJ6DRaPH3a2VO7NrJAddjYCLDK45JGFTZa7SJl1bJyB6eZpLNmby7pWYVvo8fgmfF0REIM0pzfo7m/By5PQcx730Q5/Rb+KUSSiaLefg4qw2P5TMXGN4r6O/LshSNIjwbRZYw5U42yFh/jsxIH2JqB24khiNJXF5u3CRfACS7TdBu4QJnNhwesVf5Wq6P2Xw/l0sOBgrdcZOkqaJJt7Hc+oTzNin06bdgcCpDACgIwiC4nUgEX9J4YbrEzMYHDSorlRZvRHS+uXsbEckjITSOjmSQZJkgFOiKRKHaYq7YURSnzE+WdSZJEtdL9i3kC3Tu83fnSwym+hldWbiFfAEg8MlefptvDe1gc3KCDTskbqj0xjSiSoB29AHkSBTn+iWE66DEkxh7DxOMbiMlyUQN9RaS9330Ji0ypvR5c8x3cRd3cRd3cRe/Eb4wAuatt97i3//7f8/g4CDHjx/n+eef57777gPg5MmT9Pb2cuTIkS/qcL7UUBSFS8tNqk4nM0SWOgSKFwoWK22aTkAmqlNvucgIXC8kbDVRohrb+9OM5BOocR1FTrBUc6htTThVtaM+CRoN0qZKVFfxewaZGRjDe+XnlNqdEEUBqJIgbLeYbYRsG+6hHQrqS0ucX1klOzRM7uARioluLpYcrq9vEss5tH2BLkNCl3FkiRCQhCAIBb6kYFgGrutiahqB52FUNvihG5I78ADKyizy9EX6k2mayTHsXC+za3VeXayjRQLeWWvz2NAY2/feS3XmCnFZp2g3ScYs0n29yDt3sex57OqOcurKEqmuGPFMmrlKm4F8N+3lBVJyQLC0CIqCms6h7zmAU1hBAuSlGQZX5hk7cj/SzgPICzewz2/wjJNjZWaBVdNEqB+Yb//84gp/umMvRrNBxdfww5C4IWNJv39Fmt82PEml0AxYrLQwVJmRTIS0Lj7omvsdhqSotANQJAlDClAUBdaWKfVOEW2WqV44R+7E/WiJFE6lgiQE0/MFljdMxqbuI5PLsLxZ58pKhfqNq/yzpx8msaNE6vRZJFnG3zvF8rlzbP78JdpHH+Pty4tkozogUBUZWTe4sFbnwYkuXr++wZmlKl0xnUe2d/P49jxX1xs0XZ+62+m6j2oqKUulUiizEIuTlmSuLdfY1pdCaBqtepOYHDASU6h4opOjAqiyBEKQjyikQpuE2yDABF1jdqPO8aEke3NZQtEh0p65WMC1YiipNEG9RiAEjUDi/NV1vntggIneJJVK+eYCtnT9KvHZayQJEWFAKxFD6f1j1NmrBKtLKMkUX9u9j1rbYWVl4+b5zwz0ce+OIf7ulQtIg2Mc64twcM8+nGf+O5LnokUiqEYXwvfQp3bTun4Z0WzgTl+lXS0TuecEYngcb34agKC4Dq0G1iNP0ZQVFEXhRvH2Sg+A5XKbmgeJO7u5fCkhJ5J33ijJSJHoLS+FYchQOsLpxcqHfo6bhYHefBpt8Qb28jzCsYk9+S2C4jrC95ATKeR8HyvlZoeUkUDXVCxTRwlcrIiJqDdBlqm3XdqWjFutgSyjEOI7PiaChiTRHbeIC4932gZjJ77BcqWNrKkseBrNTY/La3USpooEFOoOiVSMYFPmzIbDnoE+KrMzqKHKkKnSu38fk+kuLtbW2WwHdCd0MhGd966vEtUVwqBJXPPxr1xALr/EHz7xLZ6r2mTsCmNhldValetrVR4+dC+i9QJuq03CVEnJPpmdO3iBDCcLNrWyjYyEZVr0xeL8bKbKP/7qYxhBQGhEWHYAQnRFxvE/COEVgKR8UIz0Q4Hjh8Q+wwyKMAyR+OzyVFJqhzx+Y7p4yz41ReahyS404X/izwoklaWGz/mVEo4fMpKNsC0X/b2yDRRC0Ern0R77JtFWExD4kTitD9mu3g5BGGLs3Ic7e+0jQcyyqkB3P2+vrbL/699FW54hLG8S5AdwMoP8dVHFbNZRZBlTtRjOm9yftpiuuOyOJtAmt3euz8DH13VqO+7h9LkVRDRO2wvxg5BWy0FJp3hvqcK+8QiNMERSFIJQYKoKmiIjRCdAW243SEbiNNqQS0XxN8pIdNiBRC7L6bLNzrROPBah7ASkTI2UEiJLUPUlvBAUTcfxAkayMdp+SKXl4oaCfCJCNqbjOS6NxQWUpoNx5Tx9jZfpsyJU1CjLpSb+A4/ykj7EYD7BK1fWUWRB6Ngk3SZSvcLxqT6OKmU0P4mjfH4hMEIIktad9y9LENVlPi4ZW0aQjGis1z9KogNEdBVN/s2IJEmSsBoVvItncZbmkGQJbWwKfdtubCv6D74/AFpdfWiPfxPLaSNkFU83PvHcXZIkFmo+pxbKW8T3Vv6F6BSuu+MGI7HbB6H/NuAl00SjJUxDw3ZuvR8lwyQ0TLriOuv1NjPlgGP3n2D6Z8+RM3W85UUkVabmhkQOneDlhTqHxvM8e2EVkLhU9hhK9tGr+uiNKmdLHnsf/0Muv3aS2uIi27Ld7DR9mkszDKbzbCoKuqlSWavRMduUEWFAw1cQQMPxqAoNWTdpzc+hry8i94+gj+8gbDWpvvcOVSVOEIbYjkc2lyFR8qDSQmq2IAhId+d4sFvDVVR8RYMwRMgqs5sfavyQQLQ/mJstbjZw+nLol99lu2mxPddDfOgI9Qsq4jbXhaRpkEh/qu8hDHwkPnr3KLKMttWUcsXlFvLlfVRaLqdX6jwwFCVOSBAG3Fj7qI2epSn0xnW4TQYMdNYcNQ/cQGBoKnOljzYHvY9rxQaj7RbW+BSSphG6Lu76KmGjDr6PduFtxicm6O96P7PPIwyhrRnIh+/H2n0QyfcJDQNX69xfpuTz1M5ufnKpcAsJk40ZPDaVQ/qUGUxCVql64AWCqC4Tk++uwe/iLu7iLu7i88UXRsD84Ac/YGJign/7b/8tjUaD559/nocffpjdu3ezvr7Ov/k3/4Z8Pv9FHc6XGp6kcaFQZL0Z0HB8EpZO1FDxAkHT8bm2XmdXb4IzixVc20aVQZYkUlGDvC4IludRg4BGuUTUjKOrCrYXEG4tKrXePopWmtTePs4UHSJJk1jvBN6VGcotl5ihYUghIgwJwxAxvgt3dR1DkXA9l82ZWTwzxuJUkoODWRaLTSRFxfVD7KBTqNVUhVREJwRMVUZSVeRMHntlEdO0OpOy8ibdmoqs9HFe78EbyJAeHEQJAzYaIT9+d5p0LsOmHSKqm/zn5ZCndu7nvrFt2PUa3ff14GgWjiRovPoivYrKznvuY7MUxxMSqt3kykaV7J57Gejvxjr/JmGzjpxIE33gMVzfR16c7xTqLAuvfxwtEkd591Ual85S3f8QK8s1RBggGnXkSBShdwzkPc9nMTBpC4PvnVpEADFD5dhYlsmU+jtnQfBlhS1p/PTyBmvVDxb7b8+WODaWY1+38btLwkgyBVvi5GKZ9ZqNocrs6ktyIB3SGNvHpp4majWIDg+z9O5Jtj/yFP7ZU2jlVZKpOA0fZgKLt88vowQdWyJNU2mqFlf1Xl5MqgxlLE5vtDiOgjU4xDurVVS5U/RMR3R8VSewoqwWbc6tVOlNGFxaq5HSBM89/zbf+sp+jgwlOblQJYfADwSWCrVSBV+3KNXaWLkYMVNnqWyzL6uzceUqbrOOrkhkVB27dwgzEiGnC2S7TRqH1swqIJCjMZKK4KnteSxNRhIeUhhS91UWKw7CjKAOjBIuzmIELpreMY6fL7cYSMdpIkDuWIx1nIUEvt1GMS1sAV6jgX3mHQC8wgqRC6f5s8MPszi6jWK5QSIRxY8k+MWr7yESaY7kTPrPv0yxWSP36B+gLkwjSuso0RjWwWM05mcIaxWUMCBodlQ0rffeJP7kdzoLdN8DVSNotwgisZtt+LdVbmxB3Pzr9wt+Koea78VfXwW4JfhVHxnHS6Q/cl66IwoD6QhL5a0iiuhYIUmSxP1TPYS/eBmAoFig8crzyOkM2sQO/GYD78UfEz38CGyssOvo/VxflJADH8mK0KpVUfoHCa5ewrJ0/Gajk0VmGLQCiUg6xZqsMxiR+D/pC9RfO4PXbmP35+jfuZ/yxAFu3CjTfL/RQZZRJEHd8ZmOqWQSAAEAAElEQVSrS+wZHWejuEp8YhJtY4nR4V7SuSz1l3/GgccjKNv7ObfeRigKz51fJoVLYNeoi5CLRpSvPvJNUudfJzj/DnvHDrCzOsuepMWLk6Ms121e21Q5euxhesvLpMoraPkeVo4/jVhtczgO88UI8xt1WkHAgqcylh9kviXYpndCgS1dpe36BKHAMj5gApM9PaxIEdgyE9EUCVP5/C2QfiOIgL1dBj3xfi6u1qjaPn0pk+1dMVLqJydOAknl1bkalz7UGVyo2ZxbrvLNPb2kf89sAz0B3vuF7U94DtuJDNEnvoVz8jW8Quc+17p7MQ7fh2dZuKbFzyoCMzZFpMuiHMpcWWnQ9j2O5GL0Jk0KNYfVusOZ5Sr3jqQ52DuAOziJOtCDMTCMIyTWpAihFaPlSzeftcI0qbQ8giBETvbQ/cjj+JKGgQ/z10m3S6zW7I4VYDLNZsnF2CJo3FiKvGGzHgaEnocuS1zaaPH17TtQl2Zgcw2nVkUAXVYELd9DeWgSVZZIRHSW12rYXoihyhRbLoWGzZPjKRo3zhJUG9TsFsMZC3NpnpiqMpHtRVRWeOC+Q1SdkD8+2M9mpcHy9SK64bNvOE969Srty/NIA4MYDzyBo34OJIyiUnPBUGUODGW4Vqh9pEt9rCtGSv/4oOsgCNjbm+BGoX7boW3/QBKN4Dca9qx6heaz30N8KEMsOHsSZfYG5le/9Yn34wnw9I5V6KfJWhSywtmlIqprE9aqEPjI0RhEogSyyumlCsM7f3eUrZ6A9PAQ+1oqb5+9cfN12Yqg9AygGRqDSYPlqstypc366HZ2Pq0TXniXtbUiG+2AvuMneN2LsVja5OAYbLY82l6IQDBTFxQNlVSsB9cPueZo9G8bx59ZpnvXMLIoIcfiSOUC6aCFFFhkoiZtx+/kS6kqwu/kTK15Co1UN5G+BlroYQyPU331F0iahodMmMqhR6NkLQtj135G8gmyhsLJc02CiMZ4V5TtEz1YP/4r1ANHkHYfwg9FRy31qxaU8gfjnarIN0Pfhd2GpTk4egJ9cifO1QsfOafmnsO40fgnfh7eDpIkYbXqeOdP0Z67gdLVzXljG2qgb1n53orr63UO98cw8DkxmsbxAhbLH9wDMUPlqzu7icr+bQ+rjc7r02WmNzo5VaqqkIyYTOYTXF//KBHTK3tItTLtV57fWjsnMfcdIcx0QXGtQ0Jp2m3H1TAMO/bc+s0XgA5R2WWE/Mn+XtZbPk03IGGqdFky2qdQwEqSRMVXePHKJmvVNoKOBdqBwRR78xbK3QyZu7iLu7iLu/ic8IURMEtLS/zZn/3ZVlhmpyvyfe/SfD7PE088wQ9/+EMefPDBL+qQvnyQFTYcien1Jlc3mtQdn5Sl4QcdqwJNkbF0BSEEuaiO7Qds602z3PSYGMxjVDe4t19n4dkXGd+/h9Y7b2B199ATS7BYbeMhY6XStLYf5syizcO7c7xwcpkHj+RYMvNMjI1hL3a88XVFJpQljFwPjf4JmFvAsR1cIRFKEvFonFw+y/z0PKN9XdTdAF2WOp3yIYRCkDAi2H7A5dUKx8e7+MUlh3i+h3apSDQeR/Md7h9O0bU5zwnLQt+znf/36SI7syan5zYxdI1Q1QhrlY49CfDslQ36nzzItNxg4fwN7GYLSYTsGd7OLlGm8N//E//qj/4pl8MYG1frGEZAMmiTlkLM3Qcgch9htYxz8TTGwePYhSWax5/ikmdxfb3OV9oS6quvkkkncIVE4DooyRRBuURot5FVDSHLBAI2XYGjJRF07BYajs9LV9fp2tdNj+wSaDo+v34XnCRJKErn+/4k1gq/b1AUhVML9VvIF+jUbd+YKdKX7Cev3/69v01IksRSC545v3zTusLxA+otl/88XaDVEmzWVtADh+HuvRwZnWL13ZM00j1M9vbz8N5xnnnnBm3Ho91qdwo/psa+/VNsuJ1nw5O7e/jp+WVqjTb5sXs4oDVon1slbqid7rBIDCfdQ8OT8MOQ9WqLvoRJvd6iElHIeC5zC6tku3MkNRjqSnJ5pUq1UkdC0BSAquHJGtvzcaxmGePqRbZn8lxuhFTbIZkoXL6+yDefeBzr1MtIjVWalSogUKIxot/6c55dbFNcmUVPpdjTl2R7l4n4kIW+b5ioAyNQLZHUwDI0QknGkTVmRIKewUFay0vIMmi6Sqhq+EBqcht+vXLredcNlF98n8HDD+CfvYB56Dh/d2oWoZtkero5qDeZuXKNmu0hri8yMNxP7/AOYm6d+gs/Qt19iI8s6Xyf0G4TRKI3F+KyLCNvpegEQcBoNsrF1dt3GeZiBjFN+riG4i8lXFkh+tCT+K/9HPfaRUS7hWxFMXYdQDr6IO3bPDJV4fHEVJYLBZOLKzVcPyTf28WhAZ2e1avwK0VJKQgJajXkVh2tq4doOk0mEcUqLrBrvJerJQdf13HDOit6mlgsQb8R0lxcIwxCjEyOki1I33sMqTdH/N0XWXvvPQSgSEC7jXz+HXL5XqKahReEJEyVIAiIaJ0OezcQzDYDBnN9WFMpEvk8kfoa5f/xf6A0a6g9g+R2qhwaHuZvTy3SI1q019ewu/uoeFCrO/z1mTW+uf0e+rwqD1khrf/2PbT+Qb593+NsGj00lpawmk0y5RXsnYd4IezijTfmuVZsoRk6u3qTPLCzn19eWcMB6m5Iww1QVR0/kWLq4a9w9Rcv0vYCNFnqEEimQeL+hzlZ++CK396TIK6Gn6ZO+VuBJAK6DeifSG4RnIIg8D5VnazQDm8hX95H2w14Y67M16fSn9h+5vcVHfVMF9rj39hSz4AfidFCIqrC/r4Er7Q8FtsKlbUmEhIKgpGkzgPjWf7XN+c6dlcSNJ2AZy6sURqI8qdjE5QuXyD74BMU3jtDK5RpBvC+tkk1DaqiUxTsS1ks2/Dqkodd3kBXJA5N7mQwFTD57pusCZ0ZOUl33MMPQkpNl/vGe9CTIQPf+A5OtcrRrl6+f26Z7P330/xPp2hUq52nu4Cg3cZKZdAti/WGSy6i0RU1OmMIUGt76IrEgYEUxsll2naLIAxZa3iMRGLQqKGszhPdvgMR1/np+TmSEZ1HWtOM1RcQvkvzyiqFIEBNWmjL82jLc0gj2z4zdcX7hcxXrpdYKrUQgGHojGbjVJs2q9U2sgRjuRgPjmUQwe3SHW5FtwUnJrt4Y7qIvzXJkYBdfUkmswbiN7DnUmQZ78J7t5Av7yOolRHz0zA6/mvv/5MgDKG1sYE3v/DBi7UKkqajDgzTdDT8j3dq+8LRUjUO7Z3Aj6e5uLBBICmEukEiavDoVBdRyac3obNvKMupQpMflJN8+8S32Nwok4pbOOkc1SsFknpHCWX74Zaln0QoBC0vIOIrrFRtglCwoqdp9lt87+wKV0WFY33bSBSXMK6fZWDyGNJwkqVSA0mWcYREwlToSZjMVW3yR49R+ckym56gb2CMcHSJ1uw0aiqBnepmptgg0jfAaTfJ2vl1/mgyxuPl80RTCdTYOP7JF5F8l+LJd6jGB3mjIjGYtpjqSVGor3UmmALkaJxgKw90R08CffW9m+0Far4bNxJDPnwfkVQW59JpglYLJZbA2HuIYHiCIOxkMH4ayLKMLHfmB3qrTuu57xM2OmONCEPcegNvs4o2OPoREsYPxc1GSguPp7ZnKTmCmt3JlstZCqZ0+0YDX1Z57tI6qx9aL/lByKnFMrt7E3QnDPyw08xZbbn0R1W6Lr2Js3iZcEspFNaqtF59AfPgMeRMDiOewo3EPxV5CZ2xwcBjMAJSVOlk69zOj+1j0BIqPzi/+gFJLEHLC3llpowkKxzu1m+br3MXd3EXd3EXd/Gb4gub3xmGgap2Pi4ajaKqKpVK5eb2ZDLJ+vr6F3U4XzrIsszVis+zlzeo2h59SZM3Z0uUWy5D6QgDKYvVrU75sVyUuWKDR6fyHBpMc32jzsE+HX1umeYbrxF6LovXZ+h54ps4J1+jOxJi5eO0zARi/7287Vj8yb15/v6taSRFIW2pnPFMkoceZWRnAf/qBWQREL/nPta1BO1qm2CzguttddXoBo3cAEvLRUaTScotm0w8yrf29/H9M8tYqkzU1FiptMgnTHb3Jpkv1nlkRw+XCzHcbJbBuM7BgSRJBdqKREEYnJ0psbs3we6eGFcWi4zkk8wWK/ChhdahyT6evbyBVi3SKlfRVRkvCHlvuoAY62ZXpovWmZPcc/+DRN0rBNNX8JYXCHyPlq4jIlGkMETNdYMIaR5/ih8sOFQbFayBIYK1ZUqlOlVX0CM8FN9FJNKdIk61AmGIh4ynGSSHhnlhvg5CRpVhPK6wN9yk/czLtGUHNRrF3H2w43cufTqPIdO1YWUBf3EWWTcwJrbjZfK37OfTTvy/bGgGMlcLHw1zfB9XCg16R2K/c+SVj8Jr0xsf+IaLkAFDcG5+k4vXFxjtSRONWjRbcGVhGacnw4Pdg6hrK7z94iK7Rq7zrd338mZdI2xFScVM7tkxSMOM816hwTf39vHcpVUemcpzer7I6xseqe0DDO/JsLm0QhBNcqMRUmuFyLKD5wd0xS3KjTaaqjCQMMh2T/Ls9TUejyV54+oKG+2Ar+/s5pcnK9QUCz+QkGWZe0czzJWa7GgssPTuu/SMjbHn4H5W6y6K7zJsCdKNDWL3ncCdzmMszCJlu7D33c/3Lm2wWSkhWxa2HuHVGxs0nDS7+1NEIyZrNRtTkcCMYCVTRFttpvostvcleXO2yMHBNLXDj9KTfAdnfpqm66PoOvm9+7D27MV/6e+3znjHxzEMQ7SuPPFUgtFHHqOR7SPRXEPSDQ6MdLH03ktU7Q868Iora7TW1xmIaySK6xhmp1M2VFTkeIKgXLrt96tN7sL50AK4N6bQn7JYrtxaMJIluG8si/IpbJG+LJAkCdGsE6gaxsHjEPqgqHj1GnppA7l36LY2EobwONJjsicfIRBgaRKRNZfW5UXMiSnc65cAUKIxlEwOqVnDvXoeY989kM5gfvcv0MrrbC9VSHTFmI310IonWPcb7P/OH+I+/0MihoaeydLI9rL74L3cyE2SsquQzhF//GmEgDQuicI0KzMLGFcvke45wGBPnNnlIqHroFgRTFWj7YcgFDRNpYFGX2OT5vf+Cs21oauHjdV1zvV4VJwKVzeaDFgm8YERZooNRBgiA9W2RyOU+PGZBb77teMMfvVbSLqB2Fynq3KJyPPPAODtv5fn55tck1V8LY6MwPdDzixV8ELBjt4El1Zr1N0ASVb48dUKPXGDnTsPsae3j8bF8/j1Kj3HhllKD/JyScYNfGQJxrtiHB1MEIZ37lDVEGi1MsKxkawIbjyN/1u04Pl1iy+KonB9487jymKpScPPEP39Hn4/MTxkvEgcWZZphgqVuo1dLjJoqOwwPeyVdQw9wnLdJZKIc3w0y+xGnUKlTSKi4QdgqRB6HqeXaoxuzxHJTbB7eAADi95IDE90CG8jmcBNdzNf8Rjp6hQvN5ouSvcAWU1Baja4Mr+O6+d4fO9+0tv28OaMiyb7JA2d+8ez9Kej/O/vLrBRV8gbGbYno3zlwSPcuHqK8QceRyqs4S/OIRkGxsQOFoo1mq+/ytDD3+BcvcWTO/K8vEU8TGQjTHTFeH2hyh+NDrO03CnYt2wXLxNF2yq8ypkuhO0ggBEjoPLme7j1WwlALxBIkox35Tzq6BTeZ3RvNX+1kAk4jsvlVY+vTHVzfDSDqUpbypd/mHwBIAzYk9MZTg2w3nTxA0E+ppPW6TzrfwOoThtnae6O293py4j7HvqNPuMfQqRZJek2KP/K68JzCYoFcr070D993NTnDkl4HB9Ps2soS90J0BSJtCmhiQAhBHF85lZLvHtjnXwuxd9erZKNRVAqMu7GBq7r4asGgYDepEnN9jtKBy8koik4vkCTZeKGyvfPLvHkjm5SpsrKYpXS1AHCICDfahC9coq9xx6Ge8Z4ab5GI5DIxwwylsa9o2leqtsc+8rX0M+/RfHSRYIdh8nsOUy70WSl2iax9wQ3lDS/mKkylovxg+tVvvPotzDmL+DPXUF2bYqtgPV6g0SpyEYzzkbdZkdvilwiSrHaIRQCzUDp6ibjN9lhOARb95xkmJj3PkQLCWQVefte9PEpZM8j0A0cRf3UBKgsy1R9hZmNNis1m5SlsUPzSBomvE/AVEpMDE+ytlEmKG0g9QzeMjfsS1lEFHFTgaYSkjcgp0Gniye8Y6NBsR3eQr50PlDQFdOZKdT453vTBCdfA89FGhonG8sgL8/iqxpq3yD+6hJsraXsc+8S+Uf/AjGyDfc37Mj4JOfxV+cWXiLD9bJ785klkKg6IRsNG9cP2Wg4RI4MMZLU0H+DXLm7+PUREx5fG/yoiuvjfv4u7uIu7uJ/FnxhBExfXx9LS0s3/z8yMsIrr7zCiRMnCIKA1157jVwu90UdzpcOzUDh1RsFWl7IWs1hd1+KlKVRaXssVdqMZCJkLI3hTISndnbjBSFBEKBIgqPbk6z93V+xsrByc392pcKls03y2w6S7++ha2yKohbnpeUWju9QbHoIw+Qb90xSdQK2dcf467MrBEJjz/BDZCIajUqVyMYa3x7UuN5qgqIgAV33naCU7ubMhWUGD4/RqlVZWymRSUT4i6PDXF6tslix2dub4OBwhiAIePPaCpVqg6Slc3Syh41qk//POytkEhEODKYZSEr0JaO0XA+/bZNubOBEU4iboZESsgSpTJIrC1W62i1UWeLDtMaF+SIH9hwkOX+JmhOwsf0EacnCqpYIG3WEYQESQpIxdh9Aiie5FuRoxopoGR3f+aBA6rTbhDcus2d4L+/dWEWOxFBTWQLdwld0ZMvinXWbdxcqZKM6E1mLneVpKm+9giJBNhdFNGp4hZ9gHTyGsvsQwSecsEfaTdo/+wHBhzr4nWsXMXcfQNt/Ly1ZZ6MdUm55rPoVErJK9PfQ9zYQ4Hh3XuHWbO/zIalklYoHbS/EVGXSBp/KaqLhw2azo5qSADbXiY/2cGW52DnulkNfs0w71Ys2OMLcyiL3HNiBvrZEX8JkpeERjcTZFdM5NtaFbJr8/y5UOL26RG/CZLJQZ77UIvR99lkeWlymeuUS2Z4eln2B5Dg4oYaqyGiqgqoobOuK8P2FDbZ1x5FUlZ9dWkN4DvV6k96IyuxGHcKAJ/YN4ZkRSi2fvpRFpWmjyTJiYZpACErT06Srq+yRXUS1TMRp4EvgnXicsFEn8ujXqTba/PdzBWqNjpWUCAIkBIOZGHMVh1NLC+zuS3J6sUwQCroTJn2mjC/L7MhaPDCWojuq0PSgoWZ4Z/wE26YOo3gOZUmnnEjRqtXYOTyJG03jJnIoUogug7Y6h5pKkdos4m0AG2tomgqjXUQzadpdOZrFTRSpowSwA8FSzWXESqKEECCjiBAlnes8U4QAy7qpflFz3TA0esuiUhM+X53KcXG9xcXVGl4Qko8bHBlK022K3xmf+C8SuufQfuXnBPUqv1rSC0pFzKf/FNuwbvveMAzR6XTG44Od78d86o9QGzWirot74wp4Lv5GAUXT0Ea3Ye49ApdOoZ74Jo1TNyhdu06mu5vur+3g9QUFU7U4Vy7T9dC3iegKc62QomQxMNzH/FqNXlnhF1fL2K6PKktkYgb7RneSC1SqV65waP9xZgplhmMKCzWNphfiB20MXaMronAwp/Pc95/jvsk8o0YE1eiEe9u1Nm3HI7QEbddjQ1LwombHQpOOi50fhtgB1K0kP1p0+MrAPvobBWKRGKrvgqqC71Pedoj5ixvIA1k8x+bAYIZ2EFJo+lxeq/Pd/X2cXa4RN1Sajsf0Rp3pjTrvLsg8vaeXvof7EWEnj6U/lHmiO8ANOuG6ncKphyzLtEOZEGmrENR57kXaDZzXXqCxtgJb1oD68DjW0Qdpa8bndyF9DpAkCT+48z0Zii13wbsEzCeGJEksNOHFi4s0pq8jPBcvgN1Tg/zxgT7KG5uo+0eZL1RRZInXZ0uMZ0xilk6x1qJS7IwFniJxbllmuKufvz9T5ekDh0gLl73H01xYqVIKFcptH11TSVoak10x2q7HeE+ScsykVW8g+T4zssL6roOcW61BEHJiPIsbhISSxP/62gyqIuEEgvkmzFwtsrNq8y96uyj8/HWIxKhnhxFhQOGd8wSez2BXkobd4uXpIq4fMBlXUEyLpY0qL18rIMsSwb6DmJcvY292xnkUBSWewDx4DKEbRJSObZnC7cO9LV2+mX3zaeRcqiQRNGpoCDzpVkW2JEnMl5zbBmJLQnBmvsQf7etGFd7H2o7dDiIMiMsB8bjEzYf1ZzJFleBj5nWSLH/s9t8UsiwTXr/Awd4M82vlj47fzQaHeqKEv6MKuTDY+l62hldZUnCFgimFzM8uUrk2zUQiQyapoZgRlio27y4W0WWJ/8tDE/zH12d49sIqR0Yy/OLqOqYqkzA04qbKbKnFo9vzlJoObcdndr1G4PlImsFzp24wMbqTE9v76Q1dbpSrdKW7+fN7Rmh4IRXbYyhtQSgY7zFRRR9B1zfx6jUabsCqmeCt2RKbRoulpRZNp0TEMoiYOsXFeW7EezlUXAWnjStkNm6TQXRltcLewQz3j2ZYq9sIAT3RPvqkFvqFdxD9wyj9g8hD47QjH9iLhWHYyV56P3/pU87ZJElizZZ45vzyzZw1WYKzi7M8NLGPqeA9RGWTsNVkQnM4GzOpt5qooU8gf5CjeGSoo7wMZI2NdsBSxUaRJYZSFhnjzrmXkiSx2bx9gTuuCMxmkfp8Df9Kx2rNXJgldXgvgXDwUQkiMdSRCXBsCANCzaQRSXGlqdEdU0lo4mbOYyjEZ7oWjbSbW3OLZTq+szLWzn2sZ/du/XKw2Q4o1D74vsstj5WazY11l69OppHv2pF94ZB8j/n/8Tef+Ocz/+TPP8ejuYu7uIu7+GzxhREwR44c4dlnn+XP//zP0TSNb3/72/y7f/fv+Iu/+AskScJxHP7Vv/pXX9ThfOmwafudnJatid3r00Ue355nodzm2nqDuKnSGzd4bCpPr+HdDBAVAlTfRnJsPqgIdPTVqu+yeOkK9XKF5M6jvHCjwntLFQAme9P84/u3cX2jQd32sTSZx7fnOb9a49RChe6EwWDS5LGvHCZXniP5wFECIwJjU6xZWerzBf4o79F7+ufkSyXCZJaGMszLcwFGJoclhyysV6jZHodSMk+MJhnIJzl/eZ53X5mmGUicGO+nGTH53uklEpYGIiQXNdjRk2TneD9nbqySymUoljrZFaNdCVzHIaeG6K0ahgyKrmPoUXwBiu/RVAy8dsDFK4usBAbyus5jX/0Lsi9/H6dcQvYDYoNDiGiClmJwdbVEYLdhyyLDjua3goclNpZWONTfhzzZy7n5DWotm1ZPimwqyVQ+xn9+p2PXttl0+bNRndUfv4olCXRN5sNWw+2zJ4mOTNCOJv7B60CRZbwzb91CvrwP+9JZvG2H+cFclc1Gp4AfiTQRnsNXd/bQH5F/r0gYQxakozql5u27Mocykc/8fNiSxks3yswVG4Sic8cNZCI8MpElIn2yDh5pK+JXABEpoL8niZVMEU/byHELgwCxukys1cTvHUEZGSNIJ8hNTZHqydMa38szqwGVusvl6zVWGpsAmKpCVFcJ/JCBSMdabEUYhIsrhJvrjEhw7+E9PHt6noih4oWdc/T0nj5OzpeIWxpTXVFevFEE3yMTNVi5Mcc3HzzAS/NN3l0sc2NDJhOzuW8kzUhtiY3XX2FqaJi+rMWVNZWaE6CJEKfVRqpUkAwZSVEQzTr2m79ESabRp/aC+CBkVLaiaFpHJfDalVW64gZLpRrf2TfA+ZUqS5U2igz3T+SYyloYwmZnd4zza02cQCIRMZj3NTCgO25QbzQ5M7NM9vhRmL6M/fMfYReLqBGL3KGjmJEk7Zd/TrxngHt27mI8IuFefo1IpUAmIpCPH2LhwiWcchlUjZakok1tZ2W9TKtiM5QyQdVQBsewduzBa7dRs11okzuRhiewtY92fRl4HO4x2NPdTSDAlOl0Av/+cS8AKJUSQf2jAbIAod1GKhehZ/CW12VZRpKkjyjabnqNZ0y0B79KdGo37ddeQB/dhtbdg7s0T/PcSfS+QfKv/ZB2sUh2qAtp+x7OVFu8ObNBpekiEMiyT6BoeCEYqstfxJMcHUrz9sV5hrtTbJZqCCHwfJ9XLi7xyO5J3Olp9nll1u069w0kGZcs3pndRFMkDg2lGY3KXDt9gdAPeOd6geH9x3FuXKBSapLYf4xGIDOZj/PU7n5aXsDFlQroOjhtvCDE0lWU0Edkuji91iSfyHE9zOOurfBk/xjq+A6UMKAZz0LEZkdC5nEL5Jk3cNs2Xs8gm2MjVENBOqrxjb39VJrOzQYPxw958VqR7+7pQtmqsmoE9Ny8jDuF05bQOL1Y5/p6HT8U9CYt7hlOM6g62C/+BL9U/PCXgjt7vbOvE098Zt36XwSCIGA8F+X6ep3hbIyIqeP4AboiY7s+bc8nqorfO9vA3wTVQOXZS0sEm5sIrzNe20HAW2encUZyjF17A7Wrl9XIKAk9QrHSYDBpoawvkTLjVLb244edP9WlJSQ/SqPlYEQ0YskEk5rJqfkSyYjOvoEUXxlN4cxcR77yHrbtoY5PsZzr479c8/BDn3tqDvtSCmOFBaTXrxLpynFjaD978iardRfPlehJR6nbPs2Ww5n1NgczGfxalaDVJBTQF9VQFR3V1FBiJk/tG6Q/abJWbnFmtY4fQCjJjGajnFxvkz/6OF1OhWxjg6Tso0RiOEuzSJsF1IFxHt/Rw0bDIbVzLxvvvnXz/JmqQkSVgRBteByvk/r+sedcliTMzQLuxdPUmnV8Acau/YQDo7hyx0ZaURQWy3dWe1XaLu0A4p9OwP25wjcttOFxnMvnbrtdm9iJ9Hlk5GxBkiREu0X3yiKP7tnH69cLtNpb83HL4MRkngGljU3kczuGzwKyLFN0ZU7P11ittMlrIaHQCaNx1FIBp1nm0AP38uOziyiSxLbuNGeXKzw0keXSWp29RpvD++K8O7NO2xck0118ddsQK9UWc6UWlqHRdgNcx4F4Cqle48ZqlSthgsfHUzQNk5YjiDZsYobCkAXF5TW+Emsh3nsT2WnR7JvgJ+owZixOt6Hx1loLyfeQkcjk0uSTEQLh43kel9YbjAiTpNSi6QqiPb1o0SjNRBa21giGpiCAs8tV1qqdBqBKJkJsIEH22MMAeFvZp5+GZAlCQT1UKbV8JAkylkpMCTrZgIAvKbx4beMm+QIfTP1eurRM7+5dxM+8AkDk8jt8a/dx3q3KzKkKHhJ96QhHh9Pk9QAXjReul5jdbNFZgYS8JeDgUJoj/dGbOTYfhhACS1Nue+xSq4lcL5O1+ohmo0h0LMgVEeCVi0hdvR0bbEUljCRYa7hUqi6pRsjziwVGkzoPxx20+YuE9Rpq7wDq2BR2Iv0br7+M0Mf+5U/wNzc+9MuEOLPXiOoDyOi4QqK4tR5+H5oiIQmY22xSHEr9TlpR38Wvj0+jrlHuTtTu4i7u4nPAF0bAPP300zz99NM3/3/o0CH+8i//krfffhtZljl48CC7d+/+og7nS4f353qW2lnptL2A568U6E2YHBpMcmAgxY1Chbj2Qce0EAJJVtjAQs/3Ul8oIktgqAqqDJrSWbilRsdZrnlEDRUZODGZozdp8qPzq7w1V6IvafLY9jzbu+OMd8VImhrFuo0RevzXN6d5/MgkZ6Nx1jerFN6uMhCp84/1Fbwzb7PZqGNGItQvX0Q2LR57+A/40dUreLl+6q7gvt44V6/NsHNyiHevrTIzs4JFgGmZeIrOy5eXsSUd2fHJWCpr1TbPnV/mn+ztZ21uEUdyqJs6vVENb/Y6w6P3Mn/5BlIkAmFII5Gj7Ev4AmIRBaO7G1W7h/V2HDwfr3+UnyxX+MOHvkHk8juE9zxMKZKi5rTJ57oRwfot/rXnN9ocvec+KmdPdbz+b1zkaCrNjqntlPNjLBPhcqFOzfbwPtQlG2lWafo+tgQDKQtFEh/M3wMfqiX4BASM3m7Smpu+/ca+YZ4/t0BJid/yctsLePbSGn9yoI+I9Psz2dAIODqS4dmLax/ZZukK4xnrYy1zPi2ErPKLayXmNz8gDwSwWGrxs6uCp3fmUD7B58U1QU/Sotr2GM3E+fl7sxw028xtNpHCgIFUhGQqh7S2iCFmEKEgu/sQvaND1C+cpjJxiOcuLNC0fVBkUDQ0WcIQHsPxOOVSBX9+GsmK4ma68WJpWC9gdXVz7sYy3zo6TjOQWKq0aTgBF1drjGSjyGGAqqnIQmBoMjk1ZMfYKP/rS1fp6+niD6YyRKIRtMCjOjtLQ21SXlpmc3mZ7mMHGKFBNZXGdV0UK4KVSiLKBfQde3HnpxGug3P6bYJ6gwe7J/nZjSaerCCnsvQkIpxerACdAkfN9rm4vMlUPsHhoSTpmMXOlIznuQhZ5WeX1hnKxml7LhLcXFy+NVskbWkc27+L9rXLtJ7/IWxZEQWOzeprLyMVV+neuZ+mFWePsLnxzHP4QpCJaCTtGo3T7zD62B9w7VwTr1rDSiZRjj1MUHNQfEE7bJHOJNF37yfoHcYVEi1fQlIkooq4oxoqDEM0Qm66RfweQ/gff5+8X6QFUEWIXtnEX5gB30fvHybs6acidASCiMrNcx4oGm6lhNQ/jKIoNH7xU6RYEhH61P7u/0BKppFTWezKBdSVBbZ985/RlzCoNJ0OLbqV7wXQE9fZnY9yZnqFuZpDJJ5lx0AvxaVVFgtlVFni9HKNr997Lw3VIqK3MRIm2/NZjgwkKFfqzF2d4VTDRbTaaJqK7bi0YjlAJtLXT3joBBszdV57ex4/CImaBiemepkpVEkqSdJRk+F8nNVSg2Wvhu0F1L2Qa2tt7usf5EzQZCDRS5dkoykyI71pdpRuULpwnkYoISkq0soKKescx/7kz+je2csz55ZYqdp8Y28ftt/Z52bToeIKsneoW7bR+OHFAuUPkd3zm02Wyy2+uz1NqvKrZjwduHPTxPZV8OLJT3xtfFq8n5UGHfLkN1WUCSHoi2vcM5bnhavrzJdaN7f1JU3+2b3Dv5e2gb8uJElivtwm8EUnz+9XcH5+nW1Te7BPvcnI8SkubtYZy8WQwgCvVALLoTuZoVBtIQRM5Cwun57h6fsHGW0t4dahbHSRUjX+cH8f7QDUdh3rpR9Sm1vAmNqNH8/RFDBMk//b4Tz/8ewmUQV6Lr9F4ZU3kAyT6LEHKVZ81spt4ok4e/tStKsV3lyrIssSKxGLwwOjOJKKr1r4jTrlKxfJhTaNvnH+97Mllqo2gykTQ5V5YLKLd+ZKiKbPkd4o16fLzC4ssXO8l8G0j3P6NYLCKgyMsHzsad589SpVPUE1kmZX1052Pxin/tqLxDSZnriBTIgciSKPTf2DhU1JkjCW52j88qcQhqiRCH6rhf/yzzCmdqMdOYEndRQ1UePOy0hNkTp5V79DCIIAY9cBvIVZwuat5JGa60YaGvtcPz8MQ7S+Qbh+iW32mwyObKeiZwFIuXViaxcRu0Y/12P4TSFJEsutjiLDf7+TqFxFsSKs+Br98SReo0az7WBpMm3HZyIX5aeX1ugz4f86LuP84kdIEjza3U8QTZCorGGYvdQHJnlmpo7veYzms2xUGtTaNn3jk5gioCoZVFsukVSKjUqT166tUm3Y9KWjfHsyiXP6HfzzpyDdxdJqldGjXbx6eY3EwZ30xE1cYWLqGuVqg/W6TUKXiXT3kjADNgpN5MERat3jnFpt4iWyRGyd3f1RbqzXmOxO8uMLa3TFDCyl8wS/ulZjodTku/v6iMveLefok4wrQlZ4dXqDly8v31wT6orMsbEsu3I6hAFlW1Bq3koSCAFKKoO/usSar5FQNYTvITyP6OmXeeLoA9SnhglCQVTtKN8kSebCus35tSbFptvZpiukIxqnFsoMpCz6by8cpjumYajyLSSQJEmElRL5bIK0BuUjj9AIJEwZlJiKJL2G7PsEioIkSZTbPuWWix5PUDRS9EU99hSvcv0nrzGajWIpAm99FenyWaKPfYN2tvs3Go+VcpH2h8mXLYStJsNSk3d9aEg6QXjrZ+zoSVBsdBwt1usO3Tnt91Jp/mXFp1HXdP35P/qcj+Yu7uIufh/xW83427FjBzt27PhtHsKXBilTRZUlhATpiE651Sl0rNZsNhoO49koE13xra6azntkWeZaxeelawX+bM8RjkYtmo0Wkqbj2W3aiwuohs7AvYdxPJ2hXIzepImla/yHl2cAODGepS9p8d9OLeEFIQMpC1mCvrjOsaEkgaywVrO5XnbwAxXZt3k4Z3L9mVcYThhEdZWs4tFA4LXbaKdfZ9vYPVxuN9nelUNTFdYDjYdiBq9ca0O6m5jiM9IV45W5TeQQZLUjx9ZkiUEzJJi/wYJV59sHB1lpBCxoKdhYpSvRhVFZxPJtlJ5+Vhsem2vljh++rJDKxLm43mR8ZBL7ehFf06lroCs2laFtXIv2cfLiAjZ11O4B7k1qHD24nZ+9dApNVejKJZEkmWuxcSa/PkZy4TJa2EZJZ+kaHuTltYD5WonpzRb7+pN8e18/z11apeWFN+upcVMlaaqIX/Vr+KSWCGGA2CoYK/EEaqarY4nSrLPZNcLSjRL0xz/SOW97AWsNj7H4bfb5JYUQgpG4wqPbu3lrdpOG4yMBPUmLByeyxGT/0zoFfCzKLix8iHwB0BQZRZZYq7bZtMNP1GklhT4nxrNc2WjxozOLNJsOtUab7rhOxQlpNJqsaya9kRjIMslsimzQwLt0htBuk126wp8enuCv356jLTqqAEN4pJWAxyazVArrqNv6WKjazCzP43b1MzDUz9WSzdhwD6fmyyxVbZxQotjy8MOQbMzksaku+uMGl2cLxFWTQUvmWqmNh8LCZp2Z+TVGhrrxZ65iSiE9U330dGdZX9+kWK4zNDKKVSkx50oU6ja6mmDsqYewenrxZq5hTO7Et9t4QhBfuso9+49xaqWBL0toinwzfyWuK6Qtjf5sjOmNJpsrdQYyUTJGhpwmU3bB1BSWazb/4/TyzcWXpSk8uj1PGAYklJDayTfRJLlzq0gykm6AqrFy7jzRB59gabmA/cx/xw8h0C2mCzVyUZ3hsUns995k+OhXKGxWSezZTy2Q+WnNpGfnVxiMKtwzlqEdCmaqAW/Nlai0XBRZYiwX5dhImtgnVEP9vkKKJUCW7xDeKiEnUgBoIkQ6+zaN8+91tmgaDTPFu/MtVvQEPiqpqMa9wxl6rK3GBLuNqum0Xv05YbuFufsg9b//q862Zh2hakTSKdoba4SnXufbx7/OUsVBVSRkTaPh+OiqzD8/PsILZ+fZ3KwQCEFRNbmwXOD4WJ6uULBSKJNJxCht28bfvXOJymqB9IBD40ad3qQFrs18WydlGcRSGahsYtgtjESc1AOPUB/cw1+d32Sh5tG2HbLJKL4IeX2myHf2DfDi9QLThTavLtaZzMf4zoEBNmoOc5t1NlseejTCe6suyeNPkr72FtnWJvuyCUqvvI1iGCSsCK4A2wtRfRfx3msUBu9nodwpTLw2XeSeoRQzW3knfnj7h2WngO7cQr68Dz8UvHVjgyd7BxHLcx99swgR7QZ8TgSMjcZc2eFKoaOS3dmTYDChov2GliOqJJgtNmi5Aaoi3+wgNlWFV66t8529ebS7nuWfCLIsU2p99NoxFAXPD3Fcn0C3UAwTRZbYLDf5yv5RGuUKI5EeNOEjWTJzUi9zzZCdOYvte/uY9Nc49/IrrO+6j9eunsTIdaHEkziqwR/HSrjraxjHH+GnVzbYvN7JXlEVmZ27Zf740BC1ZpuTShc7vv40G77CCzNlWkaMwPe5srjOpTWTB0eTbBvK8/ZskZ7+bs47Mc6duUyz3SCUZY7uP4EsGkxbvRQXPCZyUQQwW2qRNGs8vbuHlCZx7uRZRKPF8PZxHsoLxH/53wh8D7Wnj/l7nuInb19HAJJZJzkWY7ouUVd7+OYfPI1+8pcgSehDo+j7j3aU1P8AAaN7LvY7r97255yrF4hN7cZLZgmCgKl8lHNLldsSipP5OFEl/LT52J8akiTdDCb/JF3z7Ugc68nvEM5cwZu93rE8nNwFw+MdNeTnCCEE9A6gJNIEtTLGpZN0f2i7/sATOJrxqYPJv0gEksrrMxsfPPMFNFyfHXmN15sOdi5GpF6l3WjSG9NomhqKIiNCwYEuk+XnO6riTCJCwp9jve6wFgoiukr0CYunt41wIulhtFcY75eIx7K0FmbxWy16t29jM9nDj86tsLhRpd72EIAc+Dz3xkWe3LGLPbUi84UKTrVGd32NvBGl2bI5NJjk7dlN5jddTF0hYehMV2wSVpQ/3teLGXV4J0hybaZGy0qwUQlpFdeJGyrf3t/H1UID2w/Rlfc16B203YBzq3VODHZU8zYasyWHq+udcWVXT4KBO4wri/WQN2YqtzTkuUHIK9c3SEf66DO5o/20iMSQozGcIARFga3GFCWRRhkawxAuSNy0/7PReOnG2i1NAbYXUG55DGciXCrUGZ5M4XsfHZtiss9j27v52eW1W441Zmo8cmScn7x3g+X1DxopUqkkX//uvyL9+jPgugRCotR0UXSdyP2PcqYtc9i0Kb/zOgCllsdAQkeIEOG62G++hPbkd26q7f4hSJKEikB2HYSq4ckKYa12x59PzZ7j4Xu+zjOzt67J+lMWO7vjXFjqZDTq6u+QfO8u7uIu7uIuvhT4rRIwd/HZIaGGHBpO8/ZsiZ6YjqnKbLZc/CDkgckuxrMWvdGOr/L7aIYKr08XuD8jU3rtRVJrs+iVDdxWC6VvmOx9j1KIdvPTRYejEwlWGi5zpSbFZsdybP9AisF0hO+fWaYnYdJwfGwvRJHh3EqNnT1x4okYpqqgqSqGppKK60Q3Z2lLsNm02ZMx4eoZRroHqcs6tUqRA30JRoROO5fn4lqNRyZyvP3OOaZ6+3ntxjpu1GRPIkHtehk9YhEzVAZSFmm3jthYhiBgyZbIuBILTZ/jvU28t/8OHxmOPswTjx/je1dK+BGfjBWlUWuQjJoc297L63MV5sMq+YTJXNlmuRWyc2CY0zWYK3h46V6qQqVR92jfKHJkIMkDjx5nebPBlY0mgawynk6xkjQZ3LcHx3VZbISsNhzicZnjGYmvxG3C2feIhC4PTY2zEs2T1iW0vjShbaNI4haCRFI1SGY+0XUQmBZqrgs900VYLOC++wbC99D6h8hM6cSzWap3KJTVHR8p8fvV6SOJgO1phZFkLw0/RJEkElqH5PisT0PTDW5+remITn86RtXxsf2AsaiO9yk+r9sUrFo6EdMgsAxm1qv8wa5Bnr+wTM2HqtDIj0ySjll8bSqL/LO/7qhdAPniu2y/p5s/PTxI0YW26zOoB+yKCbIL58h3DTBfFPQnDA5N7qQeSFxrJOmP6PiyyrVyDUVW2NYTY9gPuLTWwA1C3lsss2d/DwNGQGV6muiOURxXZm9vDNdxWcQkio8jhYQCrhVbPDXYT5fsUVtbZqVngP4TRxhaW6FSLDG4bx/lN19i8+TbpNbn8G0b875HaHePMP/Oe6h7dLYN93D12hxePk0mYmCoKvmoTjJu8V/e7ZDCqixTavtUGy0e254nY8kEyLwxs4mpKTf969tewE8vrPEv7hvBaBZo2G2IRJHCSKfDU5IRYYCRTHFurU6+WSVwHCRAk2WiqsRmvU1UjxEqEeK5Ps5LvRyq1bGvXyYz+SBLNRs7NDiIxHTV52eXPlBfBaHg+nqD9brDd/b2YHK3QHsnuPEUxsQOnGsXP7JNHxrBS3Sel+pGgeKZ0zi+QJEl5D338FpJIppJEBMqvmaSjuq8u1DlyHCSvB6g9A4grl0iaDbRBodxVxaQrCjCaXfUUO0G1sAIvu8jLU2TCVr8P5/YwaVCnbbj05cw2N0V4ZWz07TOXyDwwfV8ZN1gZGCYU2stvrptlDVfYXj3dp65sUnUipHskVhphSR0wVsLVb66s4eZmk9FlpF0FclbZ3DnTrTJHGE8xvW5Cus1GwuBEbPQVAVLVUiYGs9fWWM8ZXBqo8B9U/1U3ZBfXFlnMh9jOBOjLxnB8wP8UPDipsSJg09wTxqMs6epJ9N07oiOTZGpyfQnTWqLi+zdHvASneGpUHcw9c4U0tQUErrC7aRZiqJwbf32dnHQaRJppXuwbkfA0Ak0/jzQQuNHFwq3WFAulFoMZSI8vi37G4Xvlh1BodqiO6qSjWgIOqQMotPJvNkO6PmfK9rmt4YwDOmKGVyUQE6mCdZXgY5CW1FkIuk00aFh1tK9rLsqD+6OczgRol45ReHSJerVGoQhByfGeOqxrzF79m1q1QYNp4SS7+H6ZkcZo9TKaMKnq68X//JZ7PHd/OJ6kfpWJ7Qid8j4q9fmMbI57LU1rl1fJji4jUhPD0lKFOohkhnhwaEYm22f525U+MbefiZ6AhbrHtdWWiSS3Zh6HUWEnG9pSNv3EUHmQb3zOZmIzmRXlLnNFrYXcH6zxf3H95GYv4hZXcFaaWMnEmjJDE7fKK9dWiRw7E5LvN1GqZbRUlk2fZmV/AQ7/miEtmyw4susVtpotk9fQiepiTumvMuN6h0tHgGClQWkVA4hBDkDjo/neGO6eAsJk4sZ3DOURHyGKuKPHKcsYzRrhEtzhJsbyOkMysAo7VjyY+exQgjaVhR5zxGUXQdBknCljgXvFyHYsTWTyONP4556E3dhGoIAJZHCPHAUb3D8d8YKWFXVm7adHz6muidY/5WMFDkSY2N5lQemujm/UiWi6aiBR7vZJjQipCyNlKUyITVpFTdRgLSpMlsoEwiImTpBq03erbD54o/JldeYLZQZFi2EJGPd8wDrs1cw2+uYD36LkZ400ahFJqIRCJher9NWBnixbTD01D+h62d/S0JaorE6ywMPfYOzLY1CK2SiL8sDaYtzi2XOr1RxhcQDgxn+8+Uqj247zCvnlonlUtRsn5bbGRvqjs+55TqpiEY2ZlKxfTRFIqIpqFtj3vxmi6MDMVwUfnjhVrXnQqnFcDbK45PpW0kYReXUYum2514Ap5eq9E+lievSR9QnAKGsIPcM0j+eRK1chyBAG5tCGh6jrX9UylLzBMuV9kde744bTHXHCZB5Z6VNT1wnbymoHxoDhRAMxyT+5OAAi1WbStsjHzcZIc7PTl6/hXwBqFSqPHPF5B9/8y8wr57GK5eJjsZp9YzyUkNDM0FbX75p3+H+yu/mlzYwGzXcRPq25+fDUIVAW1vAPXcKr1ZBtqIYew6ipu78XlEusivikzkyyBvzFaptj3zcIAgCLi6XOmO2LNEbNxB3myXu4i7u4i7u4jPE50bA/Ot//a8/dYC1JEn8h//wHz7152xsfFRi+vjjj/PP//k/5y//8i+5dOnSLdseffRR/uW//Jef6nN+1yHCgAM9EVKmzqnFMhFdYjzXCaifzJj/f/b+M2iS68zzxX4nbWV5+3rb/b5ve4PuhmlYwhMECJrhGM76mb1XsSHd+0G73zYUod3YjYkb+nAlRUihuxva0exoNJ5+QBIkCG8aaDTae/N6X74qqyrNOfpQbdENSwDkkP2LAPqtzKqsrMw8meec53n+f5QMqfkSXRgkza5JZ7kVMhrTsd76CeWlBRqaSU//OHqhj+bgRlatJNVYjqXFCofnqhxfaTDZm6TabjLZk+DATImFaptLJRddEyQjBtm4jamBKeDt2QrPbB/g79+dpdqRXXO9iIYtJMmIie51oN1EWDa6gJQBGUuQDoq01ou8HY1TUG16BEzuGCSZz7OxP8N3Ds0hTQvHMpCmRTqikzEVam4epGRosIedfQk6q8ukpaDRMeisl/B//9/wnWVB5b05psb6aXoSP5TsvGOETrvD9965gGc6lDqSLTv6mS53Bxj96SjvzJVpetrlbPnLg1bVvWbP1STH1nyqra5RaGOxSrXdNRn/hyNLXIl3eBKcRoVHMz7LRw9RDgIWDh8m29dD9lvfprLtLmJH30DckC4ocPbupxNPwgcETq7H1wzidz9I46//G8Hi3NXlndPHCGoNHnrk9/iHqrhlRlUu2s0++m3jiil39srd8HM6BPblTKpc3CYesfn7Iws3ZI0/NFnga1ty3ay1j0G12aY3YdJnJpDry1x89z2emBihoyepdkJ2b+hjJBclRQd9331w5ii4LsrrMLJ6Fmf7/by31qYlfXZ3lkgszHGmsIlX//4FAnQC1a0YGJ3awIMP7uX/fXCRxVr7avbcieUa2/tTjOejHJypoNHNaP/yll5eEjAwtZHzl8qcWavjGDr7N/UQMwRvnemac2elZL3pUiu7jGSiNFcXqU1M8PPcXrbmqwQ//jvclVUMQyea7oHSKs1zZ9BqDbI9OephwBuLbR65YxvKNNnWE+NHRxfJJiJ85/AiTa9b0eQJiWk4tAI4cKnEV3cNMVtysQ2d0azJxfUGbb970kOlOLPSYNdQgpouUCjQBJFsFmPDFoJIlHg6xdsrbXq06yavVIjtdTAiMVxfknds4qZgDyXqbx4kMTiEftnYaaonTiAFBy7deuBdbfnM1zymshZeqLB0gR+qrgb/Fe+X33ICpYjsvY+IHaFz5jjK6yBME2vjZozdd9MSgtCIMPPOO6xcrjozYzF8O0/Fg+cOL+JETLZNDiGEIBOzqXnQFzWR+X70uWmU1wE7imrUCaQksmETRk8/UmhUOwGrqUF6732AFTPB8swyjfUy676gsqoxGB1h6cI0AkXEMvGCEOl1aE+fo2dyG3OeTnJohAvlNqVGBz0SQYsbiGqTdqhIOiZvXioynIpwcK5KsWWya2CQe0czlPUoc6U2ZU8RmhZRq+vdVHJ9OkFIudEiFTHY1Jsj4xj89PQqTS9EGAb1TkCp6fHgRJ5MzGLbYAalIDRNgmQUU0g29MRxfUnDk3ihJAgVF4tNOoEk3fF4cLKHl8+t3nA+9o5kiOnhByZtGx+iQ6RFHTS9cevPFXoJPsYEzCdF0zSOLjRu6f81W3KZqSSYSmufOhnBvXw/UUqhX5mWvm5TjU4I9q+ZNtOvIbquo/sdNicNjsdsymESUS2jOm0EkEjGmdo2xfPHLrJiJqm1A+6SAfVjh0ivXqKnOEPWtNE0sM4fJmiVmXr0adqaydqxY2jSxnFipANFtdog0u5golAypGKnqNQXSEdNvKB7FqVUaLrg3el1HhhMYZ9X9IwM8P96Y5qw0QA7QiOAE0tV9m3sZVtfkvVmhy9NFfjO0UWW6h6OaSH0HPmYxeObe+hIRTsISUV0pBLU2h69iQjL1TYzxSb/cGSOw3NJ/tlomsn2DEoThM0mwnaoOSlWi+ugugWBGgIVeIhGBVI5Tq27BMR44dwqF9ea5OIWcVNgAPdN5Nl+WeLoEyOuywqXIbt6bIbTQ0yXXFq+ZDjt0Bc3fqkg5kfughBEVhdovvAjlHetHYtDB4g+/BSdgdGbAhmaruNLgSZAU92ggkRctr38Yvu+rhPHeOAJYm4dpERGHNqG9WuRACWFwWpbcny6SqMTMpZ1mMhHSWhB18NGaighEFxLFgtNm6JrUagV+d09YxQXdGQY8HsPbOG5E6ucWKwy2ZskYRdJxi3iEZN6yyOUEl3TMHVB3DCINEpULl0iNAS7Cg61s7NIpYidOcTIV/+QOSPJxUpAveVxbLlBw5f0JCI8PNXL80dmmV1u8GZ/mtTeZ9mx8QLlwOYnL7yHHBilbMYoxG1mp9s8sDHHUC6OUnB8scL2fISV9Qo5zccMJAnHJGk7rDQ6KAVF12M4G73q/QLdCfrhTJSortC0boXcwbn6Las9Z4pNZnriTKauPVc8CbWWB7qFAArJCMmIhQKKjTbVlk+gBHE9ZO9Iljcurt+03eFCgkwujXjym91tfkAVmKZplGoefckIl66rxB9KO4xkY/ztewuMZKMMxo2ujGba4cub8jckAimlSGg+27IGQnST9epth9m1Kug6esQBTUOFIbLdwjWjzAYWY7vvQRgWh0+sXVYBCMg7AnVdpY1j6bxfmkGFH31v0jQN48wxmm+9dHWZbHXlEmPbdmMNj+PNXbrpc0a+lzCWIKN53DWU4GenVzm35F4dZmsCHpwskNTDzzwZ7za3uc1tbvPbzecWgNm6desnDsB8Gv7kT/7khs7G7Ows/+k//Sf2799/ddmjjz7K7//+7199bVm/mY5qmgyYSAnG0wU8KTA10IXiUqXNmZU6Zdej2vIYycV4YDyLImRM1akvLQAQiZg0tt3DK+uSM28vouQC9piPGY+zxbFZqReZ6oWpngT/9Y1LTOTjV6XODA3cZgvPEgxoLXpsG6np5E3JtljIgiFY7Gi0Oz6d/l70wMcmQI84rKUHqVRdpPKI5vMUIwXyuydpX1jnbidkoR3h56fXqddO0zvcx//uwU00Qnhg5xgXy22ipkAPuh35/VN9ZObPIn/0An6thqlpsHkT6f/x3/K/nfd4b3qZWMRiuilptX0cS+fMap2vjDjEIhYdt0VoGAjR1eE1dQ0hQBfiJp3YbNQkaumcnl+j3xYUYg5SgYak7HZ44cwamahF8XJnPBq0cZcWeMtLcufEBGtnzpCKmGQDl9KrLyAe+gr9G/rxjx8irJbREynMbbvxewaQHyP4coWw0QBNQ4tEkO129+94gkjUJnruPUYmHuRS9cYBQjpq0RvTv/BB6G8TuYggF7fpT8f42/fmb4inWbrGSrXFuws1HhiO3WQU/n6klORiFkoqlGVjFPoJ6lVOT69gxhziuTwjOQcHDw+BPrmN/PbdsLIMmoYfT5FRikfHEzgNRevPnmP98T/g5e+9ArqBRKEBBD4d1+XVsyuYGkQNQcLU8BX4geLUUoWpwgCbcxEst4pZXsU5cYD7dz7AXx6eYRWLSjugieT54wtsHsoxNTHM6bOzbOuJUX1zEaWg0uoOxC6S4BczVe4d82i4bYRhECLwk2kMJWmurSMqZfq++c85s14lZqfZmQLn3LvUV1e5v387q1676wGiNHRdMJh2aHkhPbagN2Zy8MIqZy4t0ArBdKIMpWPU2j6r9Q6mriGVJDvQT3NiI8Xz50ns2M0Fp4/D0+u47Tr7dsZZlBHamQJC07pGqQqErqN3XExhk7MEneIa9cMHARAjE1RaHomIyVQhStOXVFrXtUHR9aGSqnuvObPeYr7SxtR13FAyV24hZEguZnLnSIb+qPjAibP3a4//ptI2TPS99xHdvBO8DpgWXixBS0qEbnB8sUaqek3j3yn0sKLHeOHkefrSUfZODfLSdIW1Rvc8bOqJ842d/ezIOyS37MR48yWCmfPYD3+F2J33ouo1/NVF/IU5nIntpDft5Y0gyctHV+jUa4wUUuwZijN76ixzMybNaJro2gpWMkUsYtHygm6GdWmV2FCBvUNZjlxapa88hx4EiESSwWyWo6supq4xkEuwbShHw5P0J2zuG8+StnxeXioTt02UlPQmIygFs2UXXQgsTVGutag1IGoMslpxadUbEIZoto2r6/QmbdabHm4gePl8EU8qBlIRkJI7h8bQTx/D1DVqrTa+hGrLQxMasVyWU02dqu4znHbwQokGPLqph4mMhfyAwGAQBGzrSzC93rzl+rGeNLlcHPfce0j32nv0VJbIg0/iis9eAqStNM6ufLB5+PGlGpuyeVT48SeQNV2nIzUEimSku8/ictBVve/5HbcNriZy3OYmhBBE3AbhuRP40+cxNI3fHd3E+YFhXhFj+NUKNKpMbp1ChSHVVB+60JjMCr5UkHQOnKehFJmIgyiuYmSyiFDRPvIO5tAI4coKhaltFGwbgc4LK03y+TReqGj6ksSm7Sy2u9dzVx5SwzI0fKnQLIeiB9g2GwayHJyvUmx4JC0b2i1idoTQMjk8X+HrO/qxhCQiFLXWZR9FIai2fL6xa4C5SosfHV/mzpE0AymH82tNEHB4vspXt/dfNQAuuh4vLmn0j2whWppHjyfwi+uEng8IpJLIELRIBC2UiFqVhpPF8yXHFuscW+hWszRLAfm4TU/U4NVza/TEB28peyoTKfRE6gOqYES3SvD6WUkZkjUg3xe5WjHB55w1bvsd3Fd/dkPwBbr+YO6rP8N59tu07W4VgKZpFD2NY3N15sstTENje3+Siax9VQpQv+xT8UUGQAKlCJz4dTv/q5/pVZrOu0su70xfSxBZrLi8N1fh6Z2DzJeaNDou7VDgdkKmeuOkIwaBUswZBuebHfbFo2zePsa0C4dWG+wZSVNteTyT84kXPdxOGaPRwYmnsTIx6gEQ+MTiJo1QUKq7uKZBxo4Q6+9HZXs5P3E3r80EHJu/QNuI4BiCL20Z5O2ZImuNDm/PlEnHLJYrLs22z/ffPccfPbGLA28dJZ7L4kuPYHkNYRs4sRSvnfEZ703xxoV1/mhMI33hdU7GR1DFJngtlBMlm8+TzqTwhMFCtUU2eqPJWSAVc+UWE/koW/qS+BLOXPdcEUJ0C0kv3/+PL9WYyuauykRbGiQdCw+djbksJ5frvDu/jq5pbOlLsGMghaUJwkCysydCxOzh4EyZWtsnYups7Utyx2AcTfp8nLScquuxdyTNar1Nyw+RCrb0p/j79xZAQNoxrybhLVZavDNf46HROPJ9/UilrnnJNtAxhsaQpTXCtWWUH6DFYlj9w4SRKLW2j4qb4HfY2p9gttR9xre8EHoGANCEIHPddwNo0Rgq/tGa2LbbwD305i3XNU8dJf3lrxMUV2/sWyQzRB58otu3UIoeW/LMtl4uFF0Wq21Sjsnmnjg5W92gGnKb29zmNre5zWfB51oB80WQTN5oTP69732P3t5etm7denWZbduk0+kvZH9+1Sil0FRABNDQmGlqHF6ss1BtEbcNtg5mWa26fO/YMs/uHKDeuVaOHNu4iedWQ87NrXX1pAUQ+hxfrBCPRigkbBodj1og0IRGrR2wsRBDoztzqKSk2fbBDgmnzxEdGmGumGK27rN7KM1gJ+TAiuR4aLN3w0aylWXW6t3AkAKUpmHtuZf3KpKhQoZdAx5vz1U5cPrS5UwZxcUz08zOrfLEE/v5nRGLH+pdM3Cl6YyPD5CbPkK8sgZCsSpMZKiIzs9T3p/hyPwZUNDpeCSTKSqNDp4SNKptOlqKHs1DxSIkM1EabR9dSLb0JRnLxXjp7I0Zv5OFKL87CD8/fQG5uEKgC7RECj2bJ9RNGl7Icq3GY5sKFJte16ywVsXUoFqukd81xbC7QhhKfClxqktk7Q6tZC/Gw09jhj5SN2h9gsALdAeR3sXThNE42nAMIwxACKRuEAKJ6gp3ZDRm69cCSv1ph8cm87c16T9nDBXyzLZefnhy/Ybgi6lrDGccdCSnlmrcMZDA+YjJOaUUwyn7qixBYFqIXA+aksgwZKQnScK8KgmNlBI9naXd6nQHTpcHTxoKY30Rw3E4Nl8F3cBTdAdCChCQLeR4cabIoC1IeSGrrSaWroPtUPMUs+UWkxmLihbjxFIV3xri4pl1zKDNsB6gLJ1mqUwQT/POXIV/umeIkVqdTG2VeuCDJmh0AkZ3bOW4kWLbgIDmBZQT7QY4ggA/COhcrnRUUqFn81y85HPvphj85G8pH34bN1D0b1lCe+CbjEUkeiKOJ3Q6fkhEKDZnLL574DyPbBsiF7VYKDXpeFVWwpD+XKprrGrq9KccXp2twY6HGdy8h/lGyBuHzoEC09CohTrxeJSXmwZP3nM/tcOHQDcQMkQ16yQsnejmLVBbI+1YeHYUt2+UKTPO7oEEMRHQ0Ax0rdsGAzRW6h61lodUIBEMZGIMJiO8OVPm+GJ3Emwg7dDyAxYrLZ7c2sfGpHZTpmMLk9lyh/PrVSxDZ2tvgmTnN7diJgxDWpEoRKLdBZePR82HkysN7hschaVFAOxMhlOrdRSwd3KAHxxfosM1ffG5SouXzq2TsApMJLNEnvk95Mx5LMeh/sO/JlhZRE9ncfbsp5rr5YWFNq9XA1qhwvN11paanFhu8O29W5EL0yjDREQiyFqVSCSCqUFoGejK54HxLLnVS1xYWaZTXMc0DDTfwyuX2dg7xJm6xG15rK1X0DotLlVrKN/j4R2jnC8t4/kuD0wWuFh0uVRsEjF1DAFhp2vUu6U/zVzJZbbaRpMhmuhmfWcck55khBNLNbxA0gkV85UWHT8kCEJSE3ni8TxrM/OsNz0ipoFl6IQSnH33cqjoESqPp7f1sSEXYygusAg/MPhyhcG4ycZCnAtrN1a6xG2DfcMpWnpA5Kt/gCiuIpt1tGQGmc3jGp9PsoxSH6yrD92JNXlLV4ubEUJQDQ2OzNeYLrpoAjb2ptg33sMPjy3iS0XaMYmbGhqSTNQiFxE3+bDd5hoRt07rJ99FNq7T8C+/wcZUjg2Pfo0lMUza0ZmrdHjx/DqpdJz9GYidP4Y97SHnLmDaJnpvLxgGmtfGLxe72dm+j711J+5LP4FGlanHv8W5lM3c6gqWE8MPJHP5AfKdJobWTTSI2DqdICRQoKdz+G2F6Tjkpjbxs/NlNMsiNHV0oaGadcx4HKWZzBUb3DfgUFwvovkedWUQSMmOgSRr9Q4vnF3tyudGuxWxmujKGiUjJn99aJ4nN/ewoRAnrnza0xe5RILkxUOY2/fS+sl3SV04zIahuzg/u9rNQO/pp1Gt4RQKLFVbPL29j//vO7M3HNtio0M6YmBrcHqlQf9Y/KZAvWdYRO5+kOYvnrsp0B/ZsgP/A6rSvkjpLK1SRDZuHURV7RaiXIS+IQBW24LvHVu8QeboxXqbS7kYT2zKU24FnFppUGv7DGWi7LJb6F9wMObXhVJHcHD65urcmq/4y3fn2ZB1WK62uG88y7rrc3qlwXvNGmGo2NKfYN94kiMljx+UWzw8keftuWWUgn8zplj8ux9SyGfovfMeOq/9nM7aMtl4HCuWZbYlGd84xcLiKqGE/piBVSsR1qus7XuCFw9foDaxm1B0g9zFps/3jy3ytZ0DfOfIAieWKnxz5xCBFJTqTVCKxbqPm+4ltnCeZgCdQBEJTVqlKmYiwcSmAvl+gfbKPyC27mRk4wbeencW04iRtnW0VhstDAkSeWKWjmNoDKUd5q+T8QqkJB212JR3CKUklAolBK2gW80cKkXCNohbOkGoboixCRmyZzjNYiPkbw/N0vZDFAJfBsyeXqPsBiTtHnqiJjECtmYNNmZ66UiBLiCmhciPKfGnlGJ3UlGamWVXr8uqirDg5DhbbWObOoOpCM77ilDOLNfZO5Qk+iHjkZihocpFgmoFYVgIw0Ip8JbmMfoU6ejA1cDKWMLgwYkCb890Jb4u6UkmNmwkVVkmol9/bASRvffi2c5HeyHVK91q5VshJX6jSeTZP0CsX+lbpJHZHlzDvO5tkoQm2dNrs6/fQSlFGAafmxrCbW5zm9vc5reb3ygPmCAIePXVV3n66advqL559dVXefXVV0mn0+zdu5ff+Z3fwbY/WIDb933860pjhRA4jnP17+v//XVmzTf4r29cpNj00ERXTufgTJlHN/UQQVF1PQr5NGUgYWmEvUOU35khbQkCNFqBRGkGoQqYLTXYvyFPs+3TlgLH1FhrdnhoMo+pdcvQI6aOFnh4hqLZ8rjTCcjVV5BK8cOjCzyydYCNaZsDSzXuf+gpCgsnOfPaG+jxrsRP8u77mc6McfJCiXeOLvHV7X0ccZvEHQtEQIBOO5CE7RbvnZ1nqsfnG5s2s6iyFGttJjuK4J1ztNdW8YKQwVyBJSxcYVJtBmhOrGvS6XsYShKNObRCRRD4NAKF1agwmu/l8T1DGEJy50iKnGNQ9WEg5bBca2Pogt5EhG9m2rgH3sUzhtGRqBDCSgnhNjGGxwlC8KXi6mUigPDaJFWoICLCyy1QgPIRQYCIdOXBQs24KnH2SRBCoC6bFkohwLgxY0sXMJ5x+HahgOtLMokYdthGSP/yTn7+6EJg1SuoRhWhm8h0Fs+KfOrB7sdpr9f//atsuxkLUhGDsWyUTiixdA3H0NBFN+DRCSShupY5/WGkTMnT2/t5/tQKbsdH1CrI8jobCwn2VYoYx8CY2kZHNz/wt2uaRlirofUNUm37SMS1LDQBmqZjJhL404vIhEmkWWc0l2Op1IBWg55EAksXNFyPTSmd04cvMrV1I0ePrmBbJk9vKfBVKyAcSlEzHd5t2dSlxtf2b2b9h39LRISY8SSR7Xeg7d5HoaYY0CBezVBHgBXBMgMs5eFHHDQnikrnmG0L2pEkmzpreIffRpchMcOgsrZGrLqGLgTFco0KFoau80CfzfmVKqGUrK6V2TeSYaXidqffvTaNtsNQJspMscm+4RSHZ0sIIXg3sBjPRBgf7WOt3kYmMhyuC/ZPOPzgWIWxLXezJVOgdfwQfqNJslBg6K49hKuLaKVFNuzejth9D814mm1CXp2oTpgwno9zdq3JbLnVzQakG3yptn10TeArwdnVaxNMK7U2iXwMA8lrF4oM7e7DEtfaTEOZfP/YMpXrDKvPrdaZb4Tc2Weh/5pIl33c9nr960/aZr1QUXY92kMTGMffI2i36TRbaKakLx1lvtrGU+KGW564LKnyzkyZsZ29GJNb0cvr1L/z56hGHU3XkeV1Gr/4MWv/w/+Z5ZJPEAjqHQmhhDDAQ/HyhSL7kw53jsc5tT4P7RaEAaLdxlCKsU3jjGlt/B//BQ/c+ywr605XnlPXqLR81OoCPYVR9o1meOvkDO1QEE8lmG8Llhse51a7QQx7psSm3gTn15sEfkjc0lG+T3/aYUtPlIrbQSrBaC6OUJIQQcSC+UqLVNTE1AW60IlZOq4XMFNp86fHPP7nL30V5723sY8cwe90yA4OYN1xN98px6h7bZIRk239SfrtACXDy8kaH35+TAIencgw1RPn2FKNIFBMFGJM5B3iWlfio2M7MDB6Qxb6Z3Wnfv915OiCoXSUc6u3nsCdKMTQUd1n6EdQkwbfObKIe7kNh2gcPbJIf8rhwYkC3zu6QL3drX64YzDJ01sKWATwKZ7t1//7RfBJ+sKf1X5pmkZ45viNwZcrVIvEZk8zun0fmgbH2wFb+9NE2nXki89RWl9haP9efA38ahWv3cQZHKazsoASAiUEMp0jPH8Gub4CbRfrrZ/x5ORuZidHONkQBCmbVSvNAyO9xJdaGOUSzbZPLJ0iiGW56Ap2D6U5s9qgNxFhpd5mIB1judIkDCGRyuI16mhRA0MXuNUa7U5AQgtphjqBVGzpSXBovoIfSO4cSfPjUyvol49fwwsYyTjEpceFSwv8q539zF+c4/SaoOWFhLUyrh4h+6/+J/yTh3l4skA1kqKmDKpr60jPR7cc7hrI0gkkTS9Ek7IrpykESmi4fogd6d5vNO3mQD6ANzhK/OnfwT/+HlqzhhlPYW3bjRwcxdf0L6i3+MFcqSL4QHzvcn/Y4I3p4k0eEwCNTsC7Sy6HLq1dnXeeLbucWmvzxGSGvPmPKwDzSZ6tt0LTNC6tuDfFhoUQlJo+xUaH3YMplioukq5HSbnlUWp6mLrGmZUGQSgpxC1OLdXY1JMgF7MZigoSx36B4dcQM6v41ibij30VceQd6ouLpEc2UNu1g9rkJCt/8d/JRk1ybpHm6irmph28u9joBiYCiaFraJaJMixcX3Kx6DKUjnGx1ERogj3jed68sEpuoBel6VTbAVFNI2IILAMsXSAEdGo1cqpDv6hj3H0fL8zU6Yssk4kYzK3UKdchn4nTb+koGbJ/PMfB6TXuHk2zYyDFmdU6SsGm3gR3DCZxRIDQDQbTUd6YqbDeuBYUqLZ8bEPj3g15tPc9V8ZSJm/P1/HCbvCl6YVIpehPRZguNTi6GMHzPZ7a0kOcAIsQ63JRqPqYY0QhBJHSKvIXz9FeKlHyQmK2wb6NE7RH9jMXN4lZGuJ9EQcv/OjxSMGrMRwTXKx0kyivJ9aqMWirq/uoE7Krx2JjfhBfWHTabQY3fg1x+gidM8dQ7TZGOkvkjrvwB0ZRSn307/uo9ZqgY93Yt7BkQLS8iup0ENE4QSqLD5cDL+HVY3ab29zmNre5zefBFxqAkVLyyiuvcOjQIdbXu1qm+XyevXv38sADD6Bpv5zUxNtvv02z2eRLX/rS1WX3338/+XyebDbLzMwMf/EXf8Hi4iL/7t/9uw/czne/+13+7u/+7urr8fFx/pf/5X+hUChcXdbX1/dL7evnTcsP+c6b0wRKkEs4dIIQXQgMXePNmQpf3znAXCPkjsmNOJMjuCcOM19vgttEhiGGppHJ5lkSBkoGVF2PTNRkvuwSiVjk4zahVJxcqPD7e0d59cwSzYZLRAPhd7h7apDC0hmUHMZfchnK5plZq/GteyaYPu/hlBa5FO2l9ODX0QKPmu1wzM7yozdnEJqGbRos19qcXygzmMsTb1xC81vEYnEUgrBWpTHUw2h9ncLEVhqnXgOvzfLyPIEXEoSSYGGO/r4B2nYBTSlCoXCjKeK6ouIF9CUi1NoBlVY3g8kuZLh//yY2jReu+jUADAP/4/06P3jnIn6rxYakgsNvEtTr7Nq9jQPNa5rAyBCt0yIVTdObjOJJjWi0m50dJFMIt0HENsmI4OpyAC2RJNE3QDpxY0XXp6G9cw/u2tIt1xkjG0gMDZMxrm/68Vu+9/MgbNRovfkS3tmTcGXyLhon88Dj2FNbP/Lzt+LjtNfr+VW33ck+xUrz1pMHCdugJ5si7Xx45ndQWidcWyGlJMO7e1guNXCXXZJDvRSKs2hnZ0HXsdou6UefRrtsZH2r395KJglaTUY3ZLl0WlwbLOkammFQL5bY2JvEX1/DqBbJhz7RZJqKJwmUxz0jGczKGu+9dhBPSoRhYug6f7glTfroi/hLc3gSNCvCvUNjGPsf4QdvT1MY30tus440TMTgKKcuNnhzukzM0vmXm3IM9WSpVer0pZLIIKBlJWi32ui5Qc5WA/qzSaIX3sH3mrTcDghBemySOduhJyk4f34NkmnaSiD8Div1DoVkDFUrgy15cHMfb11Yww8lQRDih/D0jkGKLf9q2yy3PH42XefJLZs4fn6dtt/Niz84W+XruwZZaHQoJTcx9fgmBqKCwd4s+VQUWauApqNnsgjdIH+Lc/iEFWf+rWl82ca43B7bfshjm3pZa3Qouz7xiEWtfV3gFo1kNEIIhKZDf77bdqVSHDi2iIdBNHrjY/3Ucp3JQj/bB27dHr5oPml7hU/eZkWtRTpR5T0f7vvKt5AHX0M2qoz0QVhIsuiGoOuIy9OIuoBM1EI3DJaaIYttjdHARZ54D9WoAwphmAjDRO8d5PSlRQy7B0OF3cCMlFwpGTuzXOO+4UFS9VW+vK2fdy4YVOtNrFSSbSN57trWj3XiAEFxnfyP/oxH73mWV88u0xEmUTuK63s8NZHmdKlFIxCYpkkiFqHaDjENDcMwSEYMGp5kMBXh2R39LFTaCAEDdpKYIfjpsQWe2daD5nQ4feoSnh8StU1UySZbGOBkQ/DUll7emSljGnpX477pE7OinPVs3Mn9NLJTJA042NF4Z65F3JJkYzZxW2e9GTBeyHzkfer9jPTB/sl+pFQY+mcvLfZRXH8dPaA5rLYkfnjjdGPM0tk73ktvMvKR27vS7jBsrjS75XqbdgjTpRZb+9P8q/0bqLV9LENjQy7K5qHcZ/YbPm8+SVv9rPYrbNSor8zf0D+6Hm1hhsK9jyAiEcxln+8emuefpSpUFrqVbhfnVhka3oC4eAYRegTrK2jROKq8jlboQ8RShJdOo1putw/ScjFfe46paJzNm3ZSzkr+vBrh359c4Y/u2cE7F1foVFx8y2Kh1mGqEGUiY/OXBy5y/2Qv/UmbiKUzlE90Jf/8gHjEIhfVeWA8y89/8jpSEzy2ewvfOVejEwpMXVBrtElEDHRNw/MlutZ99iZ0ML02cnmGmudTTXkU3voxIw88hmPqmIk0ODaNt15BltdJ1Ot8dWovc3aGS9lRcBvsvmuSk8U2lWaHHlOxXO3ew0CgWRaaiBJ1okz0ZW46l2GlRLi2jPQ99EQa7au/B2FI0rTQPiRx7YvGVwEqHv/ADPlY/yCZ/n4Wqy3KneItr6ehfJwfn1phLBu7YXknkLw11+AP7xwmZv3jyVP8NM/W96OvL910rPxQ0qz46IaBbhiM92Z4a6ZCyfVIOSZSdj08OoHkxHKDR6YKOLbJgZky+8dz7FXrdL7zJn6r66tZLa3RTCTI3/cl1B330U7keSEcIljy+dKGjYwWL9GZKyOFIMgUKDda6AIcQ+C7LUKl4UmIOhEq7YCBjIMSMJJx+LPXL1DrBJi6ziNRC9npECqBQiCVwgsVUVPHV4pEaZFc3OTVuTqVhUUay4vcu28Xs4keTizXqdVbbB7r4+lN/RxeaYJhM1vtBlO2DaQBKLs+6bhDf09XLmtX2+CFC+WrfborxCMmyahFoaeAdt3k/nqjQycosqUvTbnl43ohutYNtvpScLHUYktvgjPFgKe3932qwEBYKVF780UcFTKeT1B0u0Gz4vwCfb0VBhJxolEb7X1h1YRt0PsR4xH37Vd5vNfg56LA7HL5avAuk4rx1MY0Bb+BNTR5w2d6r/51ebw7PEx4130o30eLxtCiN7bHDyOwTcjmUO3WzSt1nfjIOJn+/quL/IVZmi8+hywXge5d0RocJf2lL2Nkb9VTv81tbnOb29zms+UL61m6rst//s//mfPnz+M4Dr293UfwsWPHOHDgAM8//zz//t//+w8cdH0cXnzxRXbv3k02m7267LHHHrv698jICJlMhv/4H/8jy8vLHzhg/MY3vsEzzzxz9fWVDs/a2hphGNLX18fy8vKvdXl6JTSYKzaotvyrPi3Q1VodSjus1VpsyNqsdUKi23bjXTxNTCh0TaBLgbAjEE9hC4VCETU10pbGzqEs5ZbPq431rvlvVGNteobHN/SgjAJ9KYek18RZmWbtrZNEe4cIPY/W0gItJfF2DBIW14gsvkdlw27ePLqANjDC5rEkzx+bRUTjGCik10Kjayy6UnWJFfrQFmYwOi00u9sZDAOfVkfQvnSOxrFDOFPb6IQgdA1DaARS4pXWiWVytFpVtg9meXW6ilQCB43VtQq2qXP3aJ67Cya5wijZ8X5WVlduOLemkgxcOMU3oopLQqNgSMzlaXqjEULT5VjEpNa41vmT5SLxZJrdw0nevbR2VW5KtyOEQmPncAbz0nu47rXATeyuB1lruqjGrXXyPwl2Mouf68V/n/GgFnGIbtnN8mUpJyHEF3ota5qGeewg7qEDN65wXdwf/Q2xZ79NK3brAFT/dR3o9/Nh7TW4Lkvyi/69H0S/YyD9Dm3/5rL+e4Z76NTKLFVuPamgCYG9MI37+gvIVvf6MZSkL56CQi+d6fO0BsepbN7Putc1CR1cWCMWt+nt6bnlb3cyBbThDUzGBW8lkzQrlW41QBiip7MsnJ/mqace4LmfnAclCZfmiJjL9JsW6b4eNkZ8vvfKWyjdAClp1hr8T49tJvLi9ykXizixBDlLoxkoVqcvsiluUIhPcPDCMgK4Z/8uXn1vht5UlL5khIrr8dcXXf5436MMn3gVu10jMDVWpUAbHqd158PMLnd4rMdCP+/ieX43u1cp1Pgmnn/7HAPD/Xx5ez+HypL1dohjGmwsWBSXlgmbDS41G+RzKb6+tR9P6DjpDImoxdG5EvX2daajUuB6AWv1TjdIE3TPWbER8NMTLf75XaNsyEeJaZKYrgilx0r58v02DGF17QOvA13TeHBDmr64yVyldVn+LMrRhTJrjQ4bCwmkVDdcw0EQ4Lrd1y3XZWmpm8HfUgbHZtbovD/LV0DUiXLw0iq9pnfDtj5PPov2emXdp2mzmq4zljY5PFfmOU1jbMejjOhtpjJZVhdc+iIwW213B9+GhqUJ0o7BmeUqKcfk+HwJ1Zijv9FE+T7iuu/WvA5CSnAb9MSyrFZlVypPaEil0BV0lMZoPoH4r/8Pvjy1HX1qErNZJRO08X72Lqq3n7C8TlivMtH47wze/RjlVJYwkUZ6Hbywzo+W2+Qcg5QhUa0md40N4HZ8Hp7Ise76NNo+9U5AICUZx8AxFCvrdYrnzrBpaJDRpdOM9/RzydRxdI0QaLU7qPkZ9m3azFqjw3DGYb7cBAQppyuLZ2hQiFu8eUnR8hUX1muYhk4YSlCKe0Z6OXhpBRV02NVjf6GyQ5+WW11HUSH48lSGt2fKzJddNCHYkI+zbyQFboWl5kdfbx0MTs0Xca/I/AmNtVqL4PJ94t2Zdbb3xZm7rHu/sG7Tb0s09cnb4ef1/Ppl2+pnvV9W4OO12oTX9Y+ux7AdgnKRKjYHZ4pkHAM5dxF5uXJz+ew5cvvvIkWAPHkYCejZPIo8zn2PgltDNRtgmEgzjp/M0oznsfwW1qUzdIw4auMmEILVZpto1GFfIUnoBXxjZ5xq3eXFc2uYmka17fO7dwzx56+exrOipC0wbJNcJMJQUGWqPouxvY/3lps0V9f41/duZq0VkDQFScfEts2uDG0Yomkalg6m7yECHVMofLpm0J1yCePlnzL1za+jb91F8+Wf0qjWSKSSeJfOEJ46wVAszra77sff9yAkbF4+t0qwNM++4QF+uFq+fPQUqt0m4rtIT2MorrG01E3W0TQNe3UR9+WfIpv1Kycce3yS7BPPstpo4imdZTdgutjC0AUb8zHydtfQ/ovG0EwYHKNz5vhN66zxSWqmjb+0REMauO7NVR0RU2e5quEHIa1265pP0+Vn5sxamenlGFnz18sD4rN6tn4QhQg3jE0AJBphGJCyDVrtDpahc3G1hq5p1Fo+xWaHZGDQLduH6WKTrGOwUHHZmu3FOT1Ps93mShBQoTBaTTqvPo+1YQq5YQcDPRMsVqD3sS8Tf/k7lKbPY5sGVtjBSQzg5eKYXgvD0JEowiDEazbJ9iUJQ8VELsrfH7hAtd7d99C2OLdS56HNfRw/sNSVLhPdqqeoqfPItmFSKxcQu+/h7IunMASIIOToG++QyaV4dHwMI1ogn7XYHAs5I+TV4+IC5csFev0ph6hss7TUQNd1Lq40eGZrD4fnK1wqdb3ZNvUm2NIb582zywzFBFFx7Vy0MdEECBlQaXZwvfedJylptdocK9XZnjewP5bby404K/M016/JaKdNQTJtIVVIQWtwEou6e/Nz/KPGI0IIrI6HdugVnhjaQHn7KA2pEdEU2foKxqFDuIVvUFxauulzH/jMqNa6/31MNE3D2nkn7svP3+RhGr3zfsrCILz8/bbfofMPf0tYq9y4kXOnaPs+4qEvE3zGQ8MPa6+3uc1tbnOb306+sADMX/7lX3Lx4kX+6I/+iEcfffRqdkgQBPziF7/gT//0T/mrv/or/uiP/uhTbX9tbY2jR49+aGULwMTEBMCHBmBM08Q0zVuuu9JZuN6ETtM0WlKn2A7xQ0k6YpA2f7XmbVJCqeXTfF9nTirFXMXlASNHLhHl9Lk5tJ//gvzUXjI9WdKTDo2Oj+8HNItFkr0mE4U4ji7wJcyVG2RjEf7N/Rt46dwaTtihhc6Ri8ts64lxcbrMqbOzOI7Fs098DVcZKFUBpdBNk7qEO0ez2K8eI9c7SMTUCf0OnmYSBiGGI9ACH1MTRAixDYOO0PDSOSy9O3FtCImTydCbdDAScYJqV6846HSw+vrpLC+iayCERhCGaL6HPH+KfXc9jofOkfkKTakRiSUY64nxjTuGyTkBvuZ0J9KuO7dCCPSFaZpvvEgc2OVEiU5updkqIYsNHEPw9Tsf4VAlwYXlCqGUDPdnuWtnP1FTUG7EubTeJJQKO2Jz55fuZFvpHPKyuameSBG54x78oQ2faiJL1zSsZg3abbAs/HiKtmZg3/8Y5vw0/uljqMDHGB7HmNxKK5a8qcN7/e/9PDFbTdonD99ynfJ9wtkLiK17PvFx+Djt9f3LfpUBmLgW8OyOfl44u0bxskxBxNTZM5JhMmt1tYc/ALtWpvHij2+Qs1PtNu1zp4je9whq1z0c7MSx6x4xAgJN580zSwyND5LLyVv+9nYiTWR0Az3FVX73mft4/q1TrM0vduUrUinuGUmRe+37fGvXDg5Ol1gIPHTTZKIvzd6CYGF2Bj2Tw3db6FaEdC6DWS1y9vwsCoFtds1tB9NRRlMR/JmLbLh7greVYmK0j4VGQFJ2KE+v4hZGSEYsopbOX65I/vWXvsGkrCJbLtuTadajWU5XAu7aajKwfBIxvLGr8R9IJIqq5iD8GhcvzOJkm2zZvIWIbXJ3KqS2uspPKhUu+9NTLFYprpXRbJsHHruXt2fWr0qBXcHSBbahEUhFT8JmrdG5KjVkGTrNTkDg+0RsySf1u5dS0ur4LJYbZCImgZScWCxzqdhEKeiJ28yWrk2E6Fp3X0CSjVkkrWvmrlIpglv5RV1edCXY9+uQNPBJ2+uV5Z9k38Mg4M7BOH4oOb1c43zV4zwao/jcN1Fgpd7h1FIFEOhCUEhGKDc9AqnYNZhmpeqyw9LpeD5mLIFo1q4eS7m+zKaMydmSwkIxmHJYb7TpSB2CgB0jGXoiAq/jkXr0GXS3TiSfI5KO0fr+X2Jtv6PrY5TvQc/m0eJJjFMHcRZmUEIj2PsA8w9+i4GExPc6JC2N+6fyLAmdTqj47tHFq1UbhxeqjOdiPDxZ4OzCOgpFenSc3RmwXjtEaiXJN3fcxYEll6VSg7iuM9WfZtuQxf96sshDkwUEkInZzFZcMlGLd2ZLXFpv8vjmXk6vNpgtuwgBUVPjnrEcKEmzE3B0ocbmQg/Gr8E19XG5/jpSSpEzJF+ZyuCG3aSdmCaR0v9I2fmrCHVDzrBUCnnd8Xh/tnIgJaFSNwT0fpnf8HnzSdrqZ7VfvmlhjW2kffy9W27PHJ/C1wxKzZDQ9+lP2ugl88pOQBhy8eAh7ti7g+SOO1BuE3N4nM70BYRuYGZzmF//Ns2zp2lePItn2MwsldGFYCSXobBlC2tFj2zUImqZvDm9TMTQyNsaZy7Os93q8MiGcZbzDi0v4PihEzyxqZ/jRY+5WgfZcbljrI+7wxr22y8Qr3rcl+ulsGkff7VU5WLR5dGxJKOZCAdny+wcSJGImDQ7AbYAQ/okhaIVSiK2QSJwUTGHgtZBzVyAWBStUYUgoFYqExvbgHZ51nB5eoae/Sa25vPASJIfnyzTjug8vq2fN86v0+z4ZBMOfdLliU0jpI0Qefm5YTWqNH/+wxv9FJSic/EsrXdep7N9P8+dXmXhOv+LQ7Nl7hhOc9dQ/AuXuPSVwt57L44TpX3qKKrTRlg29tRWtB37aCsARUxX9KcdFis3ZsjrQuAFklTEuBZ86X7k6r+h/NX2FT8pn+bZ+n56owb9qQhL1fbVZZqQpCIm+8ezLJQbjBeSCAFSSaKGgaVrXD1wCmxDo9FWGJrArhVxV5bJbdiIOzeNIQQRU0NHQRigNWskJiYRtRAJ/Me31vg/bbuffN8wfr0B8Tg78xN8//WTeH7IyMgoK8qi2XERQjCRiyGEYrnaYqHaBiEwDY2oDm3P56GpFH3uEO/NV6m5Ho7j8NBkgcH1i2QzKaq+h2Mb6Aa4boAEysUK5dJRjMERxnUTOVngwQ1pDK0rCxtKhSZgJBfj4Y1ZNOlfvWxKrsd82WUkHWXHQBKpFKVGm2Nz3XGqVHQThug+H2IGjOdiHGq4gCJmd33X1OXrd/tAkunVGprWreBRN4USP5oryVpXz2ciRaTQh9A1kkGdr23fys9mG6zUuuc8YursG80wlTVv8oe6HqUUWk8/IGDuApm5C1zvDqUlkoSJ1GfWr7sVYRjijUwQ/0oC7+QRZKWIFk9ibt2NX+gnuO5hLtZXbw6+XMabuUisVsaPp3+p/bnNbW5zm9vc5qP4wgIwb7/9Nk888QRPPvnkjTtgGDzxxBPMz89z4MCBTx2AefHFF0mlUuzZs+dD3zc9PQ1AJnNrE8lPihCCmYbihTNLVzNXNAHbBlLsH05i/IqMzS2zK4vimDqhVFcN16E7Rh3ORPnZyWX2Rzt0Gg2WTp1Cv3iR/fc+xs/O1whbHa5ky9nxHE/vHOT8Wp3BCNybaDF79gR/mMuij01wZqWOW2uQUB6dRAzdNGm6HV6rWwwnLSxdoBRkhodpVWp0iotElSR97A2eeeCbPD/TwLIMTMskHdHY0lugEDWImRq/+8hO/ttr3ZLySrFFXyFNTgu4J+5jv/hT6pZNpH8IZ2or7ekLRPd/ifDFHxNUymiiO4GqRaP07bmD8y2fu0dSbO2L4wWSuG2wMR9jMAadUNxyUsRUks7Rg1dfy5ZLe2kWc3QjnZNHCNeXiR9+lYcyOe4aG0UKjexEjo7hg4InJ9LUx7K4ISQtnYQWog3egTY2jhACadl0DOtTBV8igY88+jbu2RMo3wdNwxoex7n7IVq2gxjfhLFhE0hJqBt4YXjVfP1XgfC9mwYC1xOur36gHvlvFJpORBc8uqkHEGhC4miCmP7hZtaaphFcOndD8AWuTfJ1Th3D3/kAA0cP03jvHdotF4RgfHILMv4os7kUzi22K5Wi3TOEyA9hthVfeXI/Qcejtb6G2WmSWpulfOBVeufP81Q0SntsEhH6OBdexHQHKd75VRoZjVCu0puweW/VJSXWSURMfHXZHwBB2fXYkjYwSiV6Exr//M5hkoUC3zk0S2N5nS2bxkiM9HKp3CZh6/THLd4tS4a2boCggyEEGU2jNzQ4sVQlffQYqb5eUtv3EBw5CEGAAlSjTjQaxejp4VyxhW20iUmbva0K920Z5N3zi+D5SLeBCAO233snG/0SB5sNhBm9YXirC8WmtMl9WfDmjyFiSWr9A7xQEuwfz7NUaXDXUIxP49aplGI4HeH1UF7VC7c0QSEeYbXepun53DGc5oXTKwD0JiIYQmIIwYMTeQwVXt1XR4eeRISl6i1kGOh6WnxR1S+/LlgE3DeWZqInQSeAVEQjHxGYKmAiHSNijPHKuTV0TVD3QlwvYOdgipSts1oJCHuyWOk0upDI2RZc0dYPQvoWz7Jp02O8st6VrxtM2khlE9UVj4+neOuVd8j165Ref43UXffz7vk6j8ebRNwmwe79VIw4wegOpB8wO7OIBMYei5J+9xfE9txNUdhsz/lILKTXQV7Wmv9ff3EOhUAIRcIySFlgoZhbr7E7rjh5/AK2obNzfBjbllSbLvWXn2f/2Bj6eD8qDGhcPESnXiAa3w1AzDZYa3ZI2CZ3j2Z4/uQyXih55fwaGwoJ/s0DG6i1AyyhWKo0WHG7x6EdhITyH7+RoAqDq/fFT/roiQjJxkKcI/MVoNv3i1sGpaBbBbe5N07xuurYoYyDpan3+5rf5jK6ENjVInq2gN+sd/s18QSh3r3K9EQabWLz5T5CV8Ku1e4Qn9yMf/ZEd0IwAF161M+exl+ZQ0xtI3HHfoxqGfeln1BfWcLoH0Rogtzjz3D6+Fl6+i3qpTKrwiE7tZVvdWKcXW2SsHX+1V0jnCu6eH7AUDRJv6WI2AYvny5h6jrewiqX5leZ2jrBlu2DRIMWd7uzOCfeBF2npyfDuh1l1sowkLK5uN6kjcH+jT1Ml9u8fWGNr27v58fHF4kagqGYQ2tlkYSl89C2IVIX3iEa1XDnZwkrGzBMHUHX2Nu3o5RCnZIXYhs6PTGLhGzTCkM2qxL2HcO8u9igs7bKN7b3k0k6ZIImmYUzpJortOKDwGXvwMW5DzSzDpbnOJ7eckPwxfA9ZLPOkfVlxq1JxlIGbfOLlSjr6CbarrtxNm1HdDpgWXjRRLevexkhA+4bz/K9o0v44bUG3vIDtgxmWK+3udXzO2rpxC0NPsSA/DcRUwU8tbnA4aUGp5ZreL4kG7f48rY8pxYruF5IzfUYz8W4sN7E0jVilk543c1zZ3+CRikkMhQj8Jqsnb/IxO470VcWicej+JvvoJLpR6DIJyJYg0PsT8KJpXnqnmROOpQPHWO51iJjaWQ2ltk5MsrB80u0lxcZmNxMwtC4f6qXdFTn4Kl5Nm3oJ5zIM1d2ieqC7f1JcrQR5XWmXv4rNkxsg43D1GpN6gde4Gyg6Psnv0+zWKf/3vsorZWZiOpQLXP+2CmUE0ck04yN9tMJQmyleGRDkr3DSVq+JGJopC1Q4bUxfhiGbMjHmC25LFa6/11PIWHj6AqhBJG2i1qeR5bW2DtxBxdESCER4VLRpVZto1T3+ZGImPSlHWxd4OjwaYrNtPg1ZQF7eAyt3aL9yvPdSjfTpKfZ4PfvfZw1lSeQirilEdflhwZfrtBJpHF230nrvfcpG+g6kXse6t4TPudxZ6gUbrYH/aEn0cMQpem03vcwF0Ig65UP3oiSXb++2wGY29zmNre5zefMFzZ2bjQaDAwMfOD6wcFBGo3Gp9q2lJKXXnqJhx56CP1KejPdKpfXXnuNPXv2EI/HmZ2d5c/+7M/YsmULo6Ojn+q73k8lMPjJyfkbdMSlgmMLVeK2wd7eX41Eh47irtEsPz653B2oSUUQSjRNMNUTxxAC1/dpaRambRN2OoSdDt4bP+epnXvR8mNUXI/C6DB2voe62+aOHodsfYWVv/4bRvsKnLf28P0XjjJf99CsCLLZYCDtcP+D+3jrwhonKiGDeQczEkFksmwa7eHsiZNM5EICBVazztjhn/MH93+VlZTBV3YM4ESjHJgp8865RTpSY7Qvw//+8W1cWC6zlokyYgVM6i59M8dQmoHnh6gLZ9FNE2twlNrMBcTdD5NAIutVjGyO8uQe3nVt7h5PM1usg6URi5uMpB0yZsiHpa4L30M2bjTqDdbWiG3dib8wC+0WQipkaR27tI41Pom67OMihKDqCy4sVchVF2mdOUbZazE0Nkh0eBSvUupm7A2M0L5FZcqHYQhB+N4bdE5fJ78gJd7MBaTbxH7iWTqaia8AxIf+RsMwbjAf1C5XAX3W160yLYQdQXXat1yvZ3L4v+HBl7Ywef1ChQtrDQKpsAyNbf0p9g3GP/J4a5qGLK3etFxZNsI0CZNp9LnzVN54+bqV3SxFvbzKeqmfTDKCLrrnNmYoVBggNI0FV/DapTKvXSwRtXV290TZq2pU3vgFkYlx8rv3oNXLsL6MszCNnkyh9Q0h9t5PDRM0DWNwjNHRDH/7zgwPjCXohIp01EJcDRMIKk2PSL2JubrK0uvvEN6xFy2IsW/nJOfaOkfeW8QWIZrXgSDgiV0jmOV1jOUZOudPE6AhcmNs7N+AcKIsnTiBtfduEkOjdE4dI6eHJMfG8ONpWpqJAyzXWvys6RPbMM6jyQ5bkoMsrteR5gADvRmS772MePMie+75Fm/UJWE0jkChex3otBkKagxfqFOZPUm1HdLv2PwfH/8KP3fbbOpNEtflLSdulWbQCrvG7lH9xorIK0GztKl4aLKHl86udo+SUuSjOrlYks09Capuh39y5wjzlRbIkL6Ezfb+BDkzvOF+IWTA/vEs3z+ySPi++0giYjCeiaB+RckAvwo0TWO2CS+fW6Ta8tE1wX0Fg4S7hJg9iyZg//a9bN43xnxLslDz0QVU3Q6VZps/HlJY86dwJrfQeuMF7I2but4I5RKYJumNG3l8UwG7z+LATBHPC8jFLIbjBm+emmfH9gliYRHx7Le5tFrFiVlYKYOF3/0/8Na8YmnuDCuxHqKWwb2DG5h/7zAHZirsffhfYloGb5xbIaxVCcMQM/CJ5nuIBpLHN/fiegHlYpnq4hJhuUmmt0BtZokNe4bYqi1i1KvEjs3jnjtBZmwCFRqsn79AdOZSV/xFCdiwiTv6UuwcTDKac2j7EiklPz+9ind5krLRCXhvvkLaMSm5Hu3WjfftXNzC1vltm5+8ASkluwYSXFhr0OgEoBTZmEm17dObsElFDBZL3QNkGxq7BpLID6lw/G1GA6xLZ2i8/gJCN3D27CdcnCWYvYjdP4S2eSfaxFZadlemOBPRsQ2NTqg4LJNsmtpG+/ghRKuJDAMiUUW0rxe1605EuUT9xZ+gWRYq10sgdIyIQ+0XP2bi0Wc4+uZBph5+iObO+/mbGZ+35uYwDI1LRZORXBQ/kFxaq1MOW5xv1/nG1h7+TboMQ+O8aBQ4N7fGdLmNJmp8Y0cfPYaN6MlAvULYqBOLpTjnt8lHYzyzc5DXLxapepKpviS5qEXcgH/76CQX15usL62QivRwZ1aj8O5P8Bt1XDuG3TeAkc0hEmnsbbvRojGklJiNJhnZ9aK2NAGXfVqElPQc/gX7k33UrBicm6U1O81ap4OK26Q2bbl27DWNsLz+geemmRng5EKZK0EvvVHBX168OrF66CgMmWtE996DG018PhfIByClpG05YF0Oo15non3FV7Q3ovjW7gEOL9RYqLQwDY3t/Uk25mMsV5rMl12yUYueVLQrq2SZDCXSRLXwEwdlfxOI4HPvoMPu/jhSQURXGEh6JrKcWLaYXne5b2MeP+wm+aUiOnOVFii4byDKhuXTyGPvUEjHscYnSO7eTrC8SM8f/hHnZJxXj89RPd/A6B2gJ57nvkuLxE++zf/sJGju3cxavAfnzvuIvfIiyAD31DH2PDrE1q/eR8dJYJgmpgyolCq0mj4n59aptzwGVIM7k0mcVIrS4jwjvUnSjTr6134f982XCJenyW+YorpnF6sjW3m7E+G1A0doZPuZr3kIYCAV56GvPMmR4+eJOBGiMYcrDzkVBqQNjYzVdUu5XoZR0zTQNAbSFneM5ig12ixWWleDfgK4ZyyLgSRSWcf92Q+uJqQl5i7x7MbdHE0P0Oh0+xKbexMopfjzAzM8trmXh8YyqNC7+WR9DMJMHqPQh/I9RLOB+9a1MYIWcWhPn0dr1Ol74mt0LBMIP3ZFdwho2/YSK/ThnzyMbDbQ872YW3bSTue/0AqyMJSEiFtmUiilbghE3YS4LL1+m9vc5ja3uc3nzBcWgOnr6+PgwYM3VcBc4eDBg1d9YT4px44dY319nYcffviG5YZhcOzYMZ577jk6nQ65XI67776bb37zm5/qe96PpmlcWG3eZOJ6hSPzFbYWBrA/RXb0L4tOiCkUX93ez4HpErV2QCbmMNWbYCofp+EFTPUmOd9sc+fm7VSPvIvpRLG330HVSUHLp5BPI5IZ/v7wAicXSsRNnVHL5/EHn6bUqvHzt08R9E+gWi7S89ASKZa8kNNNjfxAL2Gxxlhvik33TtGOpnj93ZM4jkOico6WFDixBN7xQ+S37KIdTWBYOf7LS6fRDYN0PEoqYnB6sUxc+PzBxhix8nm06VlUPEFT6LRbHVY6kk6o6Jc1EpPbscI51MIl1kMNMTqFsWUPZTvFgwMmceHR0+90O1pAEHgfmbiuTAstlkDeYPCncM+dxHnwcYTn4bsNMCzMzduRvUN0tG6zakqDNy+ssW35BOW330ATgkFLsnb4dWKOSfqJZ3FnL8HB14l+6Sna/SMfu7NqNqo0z5265bpgbRm7VIT8h5vidjB5Z6bEu5e6ZoTbClHGRRPj/FFEJIoxuoFOIvOZza95kSj25h20j7xz80rdQB/dSOc3eLQbaibPn15nvnztWvICyXtzZbxQ8qWxBOpDJueklBjZAsxNv2+7GnrvIMbkVhbfvTELLfnQExwjzfFja5hrp3FjSQaSDpP5KG3f557RDJ6v+OGxBQIFttnV9H5nsc5a2OEbD3+ZlY7P2MQm1IXjaGeOYcTjmEOjSAnB2RMMjwm+tnOEg2VFJBYjlU2z4lj05bPISgnDa4MdwRMGnmOQGdtAqVJDCIE7fYEte7/Eohbh9FIDG4VqNK5ec3OrFS7KFYZe+hvI9VALBOWTF8jtc9EeeIL5U+dxEfT2pujJ9FOwNe4vFHjh+Dx6qUjSMIjl+pgLBBUtgl1I0btwkezKBWS9ivcPZ5FKISyL7YtHcCbu5t2WolquYvptpqKKPVoJa/YS6YlJ0pEoS6fPsPTTf+Cxb/9LnKxzc9WS0FhqwVvTRVZrbXRdMFGIc+dwCkdXlDuwVGtj6Br9CYMtOZvevUOcW2/SaAcMpBxGMzYxA7zQwtJADEYIFRhCEYbBLRMK+yKKr+7s58B0mZVaC10TbCwkeHjLIHq7+ls1kVT0NJ47vnBVlu3erIb90g85U1xjNBMlboL/ix8Rz/ey6/Fn0TB5/tQKccvgn6bKVP/L/5Oa28Tq7aew607CuUtYE1vQcgW0gRFCXceMWOxNJkjbgunlCsWay/HFkE0DOYLyCs2UQ7q+TnzlLMnxDaxO3sdfHlokdJv4hTHKy+tUZMj36y2+uf8ejr5zlLfOLrJ9+xSyWsZuu4wP5thy125en67ywoEZVmptclGL/QNRUi2HdeVDs4asVvCLNolXfkTHD5G9/UQ37cA/d5LtG7bw+nIbQzOxdTBtk8Qd+0hWFD87vUInkPihZN9Ihm39CWbKLWrtAA1IOhZKKSKGwfXhFwHcOZK5qRrvt5GEFvA7u/o5vdbk/GoTocGDG/MYuuDti2voQjCUjbJ/LEPWvHWw9jZgN2s033gRpERJD/f0MbRkCnPHPvR0DrHrLlrXVTDE9ZB7N+R57tQar8zWMXs3MZXOol84SUYPcBJRjGgE0zboHHoLzTTxpUJEYzSbLv56Ccu2iDTqOE/9LhdjSV5/d5qincIyNSKmzkzZ5fRqnUcmC2yL+CxemMMNQ1463ub3kzWCv/y/8XtPfYvpwhBH7V52j/cwnhDQhNLbr7O+UqTlh9iGRl/CYWT/I/x5NUNEFwynbP7y0DpxS+ORqR5eOLmEISV9uiRr6ER8l3BpDq9Ww8r34vUOEt27n3D6PJ3SOsHqMvroRuTYJqbfO0roefRu2UTbyRPXJGTyuJrN4pmzNx3rmh5h3clyxepaSomZzn3guQmsCN7luV/D924IvgC4fkio2nTeehnz0WcuJ/78ahBCEGk3CUtFispiyTeQkSiFbIKHN6TxZRJdgK5ClGzz5KY80xWPw4t1nju5glSKoWycZm+UnmgK51cwfvt1QEpJBNm92cvuUCkuJPsHHfYOxNA0wZbCKMcWa8yWXIbTEXZnTfouHcY4c6QbnK+2UEfWSUQcGBzkkorx3OlViKYJCqPUQ8XaUp35osE3Nu6m9Bf/Bct+jclvfZvvxcbY+ZXfIbV8iXb/KM8vtlg9uc7UmM5suU3DbVOv1ZkaKvDs/du4cH6O0+dWGdsUZ7elGNi1ldVGhx+1HHZZGiMPPYF/8A3U+grJMCTcfAfPvT2Nkc6QUh4iE2W13mG+0uLIcoOtoz1s3DCETle6VwhBQxqcX21xcb1JxNLZ0Z9g1AwwFy5RtJK8teox7SpczUZoGjv60yyUG+hCsH88y3Bcwww82q/+/EY1AN8jfOsl+q04/+KJ3+W1lQ4nFqs0vYCEY7Jca2FpGT6F+hgAHU0n+qWn4OIpGt/9i+5CIdASSbRCPyEg11ewi2vQ88GJsh+ELwR+7xBG/wi6DJGajivlr1Rx4VaoXE83cO3e7LVqDgzjJz4bZZTb3JqoCvjK8McLcum/pffd29zmNr8dfGEBmCeeeIL/9t/+G3/yJ3/CV77ylavGZIuLi/z4xz/m6NGj/PEf//Gn2vauXbv4m7/5m5uW5/N5/sN/+A+/1H5/GJqmsdr44IwU1wvxJNja57YLH4gtJGM5h5W6zzfvGMQyDM6tNbi03uDtS0VycZuWF/DE5h7WI7volZJGYZDvnVyh6c6TTsVx22nWz13k7tEspUaLhoDVtosUWbYUBvE754hodEt+pI/qdE2NT15a4mvbe6ksXCCaKLH+6ktYhR6+tGc/QvosvL7K0PgEcmWW2OPPMtszyTvTJd5utUlHLULfx3NdaqHNzsE0jbMnOB3m2XXsLdpnT4EQRDZvRx8eJXP6BEtmghUtRjSRoTm8iVQqznp+goNlSWUhIOVUsfQUTlJHfUKjBl9oRHbuJXjxxzcsV76Pe+Ykia/+PuS7UlKt6yR+NE3j0nqbjTSpHHwLgJQpYGUBGfi4zRD7wCtYe/bTmT6P+/JPiX7tD2lFoh9vx9zGh1a1yEoJUej/wIBOB5PnTq1R9QWu62IEHvPvHaGQsHmm38F+7y04/DbRex6EiW2fSRBGSom27Q6sehXv4jmujCaEHSF6/2O0E5lfuw77Z0mxLW8IvlzP6eUadwwkSOq3XA1cDsCMT8Lx926a+AyjMeLDozTeeQ+hG6DrxDdv42AQ5+TsMkqB0W7S0KMcqpZp+QFj6QhvXCojhbg6UV2IWTQ7AS1fIvMFzpgx7NIczR/+DbYm2f3Vp/HefBH3Zz8iqNeRU9u5cOQ85tR2qoP7OC8VXih5Z73D0/c8ivnG86jV5mXTY4vkxGasex6g9fxPSNgGXr3OZCHBqzMKJXSEe818sycTw2qUOeK2GYqn0LwOSkRI3nkvL1UNVl4/SxCEtNdWsUyDZ3cOsvGlv2U8keRrD36TNw+fo1xrkLAUz9y7lyVPQy3O0jnyNv70havfozkOmq4TvPwcE2eOMPn1f0k9KBMdn0B/7ccsj++mkxlGL6+hN9sM77+XmK1jtou0VPym87TUgu8fXeSK6mMYKE4u1ZirtrljKMsrZ5evfbeA/eN5dvba7B9wupnIYYhSPioAk67kRNe69iOKDZRkIAJf35bDDQRCQEJX9KYdlpYqH/bJ3yg0TePkSuPqNZ2MmKQWTlMtrgGw2vCIZSMIJQnWVzAvnmFo014cS+fBgkbzb/5/hJcH6N7KEqWXVkkMDCISKZw77qETieLHU7QCqL39JrGzJ9neO4gRi6PZHh0tT3ZjD+s/+BvWIgmGdu9iITvCT44uMldsEHdsVistQsvBkQGtepOTc0WyEY1l1+XUfJF8RCPd28/w5gn+9MAsp1cajOTi1NoBbsdnteryrR1DBHKWxuo6lqERq5cgDFBK4C8voia3oA+Po3kuWwsJlho+TjxG/hvf5h8W2lTdNkIpNARzJZf5ssuzOwZw2x7DSQtT16i3fbb3Jzm92qByuRA0ETG5b0OOAUd86gmhT4oQAlMGiCBAmja/TrVcSiliwufOvgh39EURAnQlkUJjMjMEcLXa8Hbw5dYIIVArizcH9IRAj8VQxWW0Q2/i9A8jcz10dAMpJVsKEep+nrMLRS6ePUsxFuGB+x4jUZ2nfeQAjePz9G3cjFycIVyax/e724/E4kTzeapLy1SOvUerdxu+k+RkUGdpvQqGSX86ynKtTcw2ODi9xiN5nXkFSV1RnF9gefcwieI69is/ZnzX3UxujCKSvehKUXr1Jc5dXLrq1+B6UHZ9Uj//KY88+S1+shyyVKrxxOYeCEP+6sBFHNNAVUuU8gkyzSLnayW++dBX4Yd/gRF4DD3+JI0Dr+AvzWPYEYLiHMXXXkZPZxh54ElWV4qsbL6X02fWeXpbL8oxaN/5CEbx+wTta+FTw3GIPPAELy+1eXrKQYVBd4J5cARh2beUIUsl42TNOAtlF+nWb+qnjaYdWKriN+rEGlX8WOqzvUA+JkIInGqJ5uF3OBob4Y0z57oeN0Jg9A8xsXGIB8dSN3h2OCKk5HZYqbUYzjjoAuKOxfmVGvWWx9e2Fn5lUtK/jkgpMZAQQlLAgyMx/KE4lgbqZ9/BX5jrFkpd8UxTisBtYI1McfBs1yezZkRZrnQI3CYoxWIQ0JsZ5f4nniF46yWab75M395n+L+eDvmnd97LT0+u0GkK7tlc4LkT3aQBfI+xvjTHlurUWx6PbB3iPQLu2DbGibUmr7xyFuE2GE5FGIxXKR9+g/G4hrE0gzE4xmnjXUTDxC+XEEqRHRohEQlQZojWabHnjg28udrm4ck4KEkl1PnekaUbfFXnFtbZrLvsG4zz92+dp95sgRBY/cOE8RRHFyt8bccAg1EwCFEyRK+Wad2i2sz1Q5qVVdLLM7S9LANJC4WNIRQyCHD9EPuXmLFxI1FifcMYfUPdamzdQJrWDX1Kub6C6B381FUrXb+VW1eg/DogbYf4w0/hvvRTguY1ZQujpx/r3ke49ejsNp8VWuAx83d//bHeW/hn/+Rz3pvb3OY2t/nV8YUFYJ588kmq1Srf//73OXz48I07YRh861vf4oknnviiduczQUpJIWZxce3W6x1Lx/wVBF+gu28DKYcXzpfJ1Dxev1ik5HoYumCqJ0HC0qh34MhinQc35mjc9SjPH5nDz/YR7zXQkwlm11oUmx5CldgxmOXs/DpCKVbLLsl0Ej0WR2+UicfiNJothBAIXScIArIm/A/7x0iuz9OzbxcBAnnhPYw772dty24iKQu7PkWn5fLayTmymzaxdngJOm10IUDTCb0OdUsRTyaZq7bZm8mhdIMQqJ89RXLLdpq6QY8WsNCCBeVwZvRuMjGHd88vo5REGQYrns+Pqy3uGc+xty9ygxTQR6GUIhgcw9lzD60jB69OEAjTwrnzftrpHGFw8/Y0TWO+0mJLcemqFm2cgOByJU0oJf76GhHL6n6P14HiKgyOfaz9Epc/90FojvOBnWhN0zi33map2iIajaIJCFeXUb7HasnjbM8Au2IJZLOO+9YrxHsHcD+jzKC2bmLe9xjxHfuQ1RLCtCCdo+3E/lGZnX4ayu4HD+JDqah7kuStTFquo53MEvvSl3FffwF1pSpL07Ant0LPAOlcmubl23owOsXpI8sITSOSSBKPOhA2yVoGq+UmuwfTuB2f0ysNrMsD5qgpGEw7rNTa9GYS/N3JVf7tsE5D10iOjFB86WcwdwFdhpj9g1yqeaDZrJ08wb4NW/jr+YA9/Ql+cmIRZIz773uW8c4atFuoWJzI5CR/ftFl6v6v0efVUJ021VgWw64zmRdUtK4MRNwUxFSAWlujmYygnCiytEZyYoQ3gxgXlpYx7AhyaBzLiaE1qrx0ocjAV/8F8UMvEfnT/wuPj4wTpPPopUvED67i3vkMlF0057qDrGlo0ThyfbV7/woCrAtHcV5/kdhjX+X0hrsQ9RL1nz9H2O7e49ZMi57hATZ+43e6E4fXXbdKM3hruoh8/6UsYLrUJh1tEjF12n73niEVvH5xnZ7EAP0R+ZnI/okwIHbZ+1tK8eFv/g1ECe0GA+FhBzrvXqsW9K54l1w+NP7ZEySndvDs9n5Sc2epLC1efW/E0LF1DX9lEX9lEWvLLsK99yGlIFy4QLy+TrqQBr+GX2lQW1oif+e91A69jUxmGY5qrLkBJ9ZnmS1B0OwgnAIhGp6U6GYEy/JZbPgM9fSwstag1GjRm0wgkmnW2pKTS3WEgLYfEo8YNJodhKHxyqUyTw33cK5YZvdEP7E3/wY/lAjRNfCtvfoC8f0P4dzzELlOgG4n6R0bZjqwqV669hstDZKOSbXlc2iuwjM7+jk0V6beChnNJRhImOwdGWFmtUyoFElLIyJC5BdkZGJLHzF9Ae/kYWS7hZ7OEt15J52egV8r9TMpJdrlrM0r/49evsY+jW7/bxvvlybV01nsZIrmc38PQYAxsoEw4mD0DmB/6WnakShBqDi3XOHxXEgr6xFNO8hGiXNNCM0ciY150uUyoeuiZEj3dChko44KQwr3P4w1MEQ8rfOzhsdarU0YSiyra9AeKmh2AiJCR7McTCR+s4nQdHxNJxQ61YVF+vY7+AdeJNrXhwxCLp06d5NZdqhgbr3O9tIC1opHI5Rs3LWVxVZIyrGImhpRPUbMd1FhiJ/v42Kyj/v/yR8j2i7SbeAvL3S3ZTs0e8cwUi2EDDGVxH3oWYqeoNlw+f6JNfYMp6gnB4k99XukikuoagktlaWa7eeFmoZt+AQSruR8dGJJYo88jfvKT6/LEBdY4xMkNm/lzqLHUtWF93mJRWyTTTFJWK92F/i/uqo4U4a033iBleGdvPbe3LUVShEsLXDeduiJ2+wqmFeftdVAcHyhgnGdifwVVmpt1tshfV+stc0/KsIwRAPMep3mwvyt3yM0GhIqqT78iGSx2DWcvyKPrJTk3HKVidE+Euk8Mxfm2X6fx+9uSlEpVoi2awzlEnQCRSuQRC0DX0DDkwwVkgTVMqfPVvndeyd5d6XNq0cuguehhOCh/gjrP/4+mhDELYehQj9haY16b5twZQ1R6MdA4Z09iRaNoYRGp6zTXLB5anwIqXyErvPGhXI3+CJAKoGGIlxf5Xi7RWFkmKZ7vvtjlSJYnscYjYBh8u5MkeGtOdTlTqHyb520aeqXHxZeG010ZcRBgeom6ujaL9+XU4ZJYH3wxSycj5kA+I8MAzBX5vGOHqTZahIZnySWTiN1E5VIEqRztMSHZL/d5ja3uc1tbvMZ8oX6p/7e7/0eX/7ylzl69Cjr690MkEKhwI4dO0gmP0Sb89cUKSUb81HenS1fzba9np0DaWK6/Nhaqp8lQjd47WwRQp98PI4vJYmIgS4ExUYbW4/iBZIDM2WG0xEcy6CCge3EiNg6LSlotAMKcZtOEDJeSHN2qQxAse5yh2OzHImi1lYYGnZYMWLUJSgEk4UYY41FrB/8d1y3ST0EFUviPPgE8+t1vmtv5vcGIoz87f+d9tRu1qRBRjexkbSFgMu6zRqKcqVONuWQMD0aFYE0TYJ2h4ip0zx7khUzSVb42EZIyYxja4JXjs1gLU+DUmjRGEa+h8ByODhTYjI/REK7+YSYKMxqiXZpBScMkaksHSuCUgpfaOjb9xEbn4JqCdAgk6XjxJEfEjRwzPdV3Fw3uSpusUy13ZsmdD+IIJnt/q71mz1BhB2B/AfL+YVC4+TStUoDzffw3WvZQCeWamztGUS/dBqUJJy7hLY995l5wvgI/GQGktcFdX7Dgy8AEfPDO/iW/tEDLKkUnaFxnGe/jagWIQgQyTReIk0LQWFyAt87xVqjQxMdhCCZz8HaEu1mhdbluRHHcUhqfTSVohNIbLt73QmlSNuCdE+cQtxmJBslrbmkohqF/jzNI68QKEEDAzuWobbWgJiFHwLT5zBTu1gp1XhqWz+zZZcjSzVOlSuM9efYiqB44jg44xxbqPHe8jydTC9Rd52Y5VCtu0QrK5iawAp9zGQCIUP6kxGaJ1bQgHZulJmLJSK6RoCkFUgqnkE23YddWeTs3AqTZ04ivTbe+e6kuwTctWW2f+kphJfA3LCZzqnjiGiM6L57oeUiMzm0ZBpjbAL3yEEAGj0jtGod1Es/Ibwc7FIoBIrV+UXyB17Defp38MRlXXxdp6V01uo359FJpVFy21wqugwlLZarN77n2GKNocnUxzI9vc2Ho6FIRAxW69deq+vuXYamcf1chpISlCRvhcT0EBkx0TJZNMuGahF1Xfa4kiFnywEJ1SF2/F3qLz+PFvhoqjtZkn/wMVQqRfXUCTbuu4POkQMc0wYIzAgx26HS7BC0Wjh2lE7Ylc+0YklMW6PtuRiJFDnbJBa1qCududUGiO7tcb3RYTgbxdag2vJZrnWwYznuv2srmw98H7k0hxA3Znwo06a4us6MnuYVL8kfReJMz5RvPGBK0Z+wMXWNYqsbkH3rUgnH0mn5ISuVBv/kngmyV3yHVHhzgPFzwlQS+c5rdM6evLpMtlz85QViDzxOZ3zTr8Rj7zafLUoptMKNfZZI/yCNH/1tt9JX18GycUPB+rkZTPUiZzbdz0guzlg+gWwt4+b6eW2xwYXFZQxdY/PgFp7ZkKD49/+d/M59dJ7/AbomCCUIQyf54GMEF07TmrtI+U6LZjyC0W5gRuO0pLo64akAX0oMXUeTIUEosQydGD5C09A0gYnC77QQ1RIdPULgBwilEJrANLrP/bYvCX0PA8ljo0nU6iJ2Z43jK5I4Ab2mSTh9EeV7+IDSBRd0xZ5sE332LFFt+9XgQKhg2Q3wQh3QSTU6zNd93p2rcH9GkXPrRGaWcK00rUyON8oCqzBMOwjx1iUQMph2MDW4EkeVUtLqGSDy7LcR5XUIfEQihczk0VMZBturPLW1n7dP+qyW1hFAfyHNA8NxkideR9Lte6pf4SSuUasQAEfWbpHLriS0mhxdqLAl39et4gCanvxAGWmA9YZHf8T8jU8Q+rzRwwDDtqnUXaTQEOpKgKF7HmKmYGalxubRTUSXV8nSYV/5En+9qNFZKxPV+phr+aQNkPUyhhOj2uxKua65Op2UjWs4nFtdQ+gGImZhaYqEW6YUhkigKkwGejKE1TIDCYsTsx2sWIz26ePdh6zn0XESJByLVHEOc/EkxkNPUhJxZopNfDRKTZ9a20eTkoQRJ5tPc3ilTiYdp1i+3OmQVwzdTVbrbVqhuBqMJxbv3s/e19dL2AYrgExk8Ks3Xmtj+TgpU/3SgfwgkcLo6SNYXb55pWEgegd+465zTdMwLpyk+dovuHIDbVYPARDZugs5spGA375Epdvc5ja3uc2vji80AAOQTCa5//77v+iv/dzImpIvb+3jhTOrtC5nNWsCNvUl2dkXJQx/NaXrNV8wU2ygAZ4fXs32FSjits25tQamBnFLJ26bRFSAU17BcBzWmjA01MNXd3QnUZteSNwxeWjLAO+cmqVVa5C2NeJRm2ZFQ1uYZnhwlE7EQU8neCQTkvrBX+AXl5HRBJ1AIqoV5As/ov8P/jVNL+DtkmLzzr2oZJ6I5rB0/Djb+vs5eKEbUBCmCUrD0DWoV9m2c5DzB5bZ2DuEtTSLJRRBp4MwbFZbHhO/8we83tQJGk28dht8iaEBzQay5WIOjxNYEcqtgESMGwIdTuARvvEL2hfOEJgGngJiCaIPPUm70I+UklApWtEEXG8w+iEd1SAImCzE6LjXfFikboDQQEksQ8NIJm/IkdTSuY/d+fWERvT+x7tGjteVUgvLIvrQk3jRxAdKlEklCK+bQetOql1bH4YSpV0LFsiWe9U0/DafnkLUuKH64XqyMYtMRHykJxFcNp21HegZuraw6+COs3c/fdUSqfUiqxGDTC6DWl9CCkEodGxd4UtJ0Gphl5ZJRtLsHEwxvX4tIDeUjpGO2RRbHs8OGmRLTcoL08gNG1C1CoZpEXVieApCBKZuoGkhYeDjhyFnKm1K1Qb//IHN5IoeYSNHdGUa98IC7U27u5mDa8uEiSwz5TbxZsDv3NvLD9ZK2CokcD10Q0O4DYx0mslIgLa2hN0/SN1t4q6tY1sW0dwQFTQsA1IRE6PjUqkbxJIJqpXSDccsYuokDEHY04+cu0j0vofRDIvW6z8nvKxnr6Uy6CuLRLbfQbAwQ6kdEvNdKu61yRwhRNdDSjcoLy2TqFdwU70sN0POr9e7skP9Gdqez6W1xrVzBgRSYetaVxLlfdTaAer2IPAzIQxDdg4kuXD5+C95gpHhcTrVw0C3relCXb19m6MbCQ0TFYaEPQPUvvavOFts4/qSkaTFUKdI5K3nkUFIO9PHy2dX+BeZOssv/pTQ9y63AdH1ejv4GsbkNqL5HMHZ42A71Noh5ZUVtu/axWKpQbPeJNcfp9bsSotIYO/oILMLAZ16lae2bub09AqeColYJkqBpgl0AYtll7gBw+kICRO2ZS0GF84j00magKbraJE4MgywhsZQ2QLFYg1r0wY22A6OrrD0m8tydSRpx2R9vUEqYrAxH8PWQShJsyN58dwqj4/F4Avuz5jVEo3rgi9XUYrWwdeJDIzQNm+np/8mILMFzN4B/JVFtHiCcHnhah/GyPdSCTXmyk0UoJ05RWHjbp4/WWeiP009M8D3X30JXapuMlTocXGtwfJwhkw6S5jrIbJjL/7J91AC7K27CE4d6UrJpvtQpk2CEAOFbDWxYinqbZ9s1KTk+oznEhRLlat36InhAvaZwygBkUz2alW1HgYEuoYufRwNdNOmEUiU0MhETfJDG0kEbWZ+/H3CMCSx526ox4lLDTM5SqBkV8JOE2gCTEPDD0NagYZuOXhKdD3BAO1Kn0wIvOEp1ko1vq5mKf/kDSphiLR1NMMid899TPVOcXTlmu+BJuCOwRTyfZJvSqlue+oZxBcmS42AixfqRJcDRhIGwwmD8X0jlFJtRLtNorQAhw9e3U5kxx78aPxD5XE/T1TgIy2bevvWVTgqDGl5Ib5SVwe/5kckvjiW/hs3Kf15EETjmH0DV6u03k8inWJbOsXR5SYSgW4YXJeKxrbeGMePzLN9KkMhHac5P0d1aYVMYoJG3SSid+W8Vb2CsB2agUS3DDw/IGZqxMIOzUqVarXR9exUEpwISigM2yZ774NUYzmeb7jEk1NsGB1lLLBZaLnd9ypAhlihx97eFO2XvkvJa1JIpkjk+0lFcxyYreFf9qESYUC70aLasenvj6CuGyPpuoahSULA1G9M+PDjKSKTW2mfPnbD8bE1xYatUxzUk8C1KplszOKB8QzqM3j2ekIjeu8juM9//0YfFF0ndt9jdGLJ37hkOKvdpH3wDW6ll9o+eZT45DaC65MBb3Ob29zmNrf5nPnCAzAnT57k0KFDrK11dbsKhQJ79uxh69atX/SufCZIKRlLaPzBngGKbkigJGnbIG3zhU9WXI8XyqtZqnH72mS6YxkUmx0CKTE1DV0oRhyQKyt0zAiXyh0GezJELJPvHV2k3gnRNUGx6dFsd3hq90Z+ceg8OeHzdJ/GG3oPiy1wQ0UyaHH/xg1M/PT/g7+0AIaBFDpx6/KET+iR8Jo8MDFJzNDxRx4kcekUG5M6755ZY8dgL6uFJHPFRjeDSFfkYyYPFNIMNldIZmxsXaBvnKRdKRPfdSe6Z1DtGef5dorTC+s8vH0I7dwiDa+b0xKzDCwkYWmdxMgofbJJZG4J5TbQMjlEvh954CU6r3VNEZVhoCwbvdCH+4t/wHnm92k5sZsP8MegN6pxKd9HYmoz9bOnKUuNQiZLUC4SMY2uhNnlwYrZN4TM9XQ/qBmUPXB9iW0IsraGJm++llrJDJFnfg+xukRYXkdPZTFyeYJaFfPsMaxEGpkr0NHNGz5nEjKSjVJ2L3fydQNhGKjL0hIj+ThWZe5qLMDoHaR9O8v4lyauhzy5pZfnTixfHcQBRC2dxzf3YKrwl7ZUaEVi2E98A3t9GVNqZGsWK+UitQA8v2us7Vg66aiNvTrH4JDO1IY+6m2f+UqLyXyMvClx1mbZHDZINEs0nTjWtt3ISglzaBR/aQE7GsWMmMQcGz8MyEUMIhunCNehN+WQlS2slRmWfvLdq5MXCdskObaRcNFDeR3cuEkhYfLghgwLMwvcN5zgojXE2tlz+L4k05flS7vGyX/vf0NEHdrVKmatRDwaoemF2JbJcMygJXSEEGiD4wwP2sSdMlqnSVDpSqJoAlK79uLHEni+T3T3PWirC7R+9gOEFUHv6e8ac2oa/uIcNBtEtu6Gjgueh4g40Ha7v8MwurJ5l72amrrDT84WmS1dNlQVgoW6z0AywlRPknOr3cCWLhS2oTHRE+fc0rUKBA0QgceQ4xDxWrRN+3ZG/2dAX1Rw74Y8b11aZ73p40/swLxwlhgB/3/2/vNLjvPO8wU/T/j0rqqyfKEKVQXvCYCeFD0lSqJsm1H3TM+d2Tvm7M6rPftP7JmdPWfP7t3Z3Tt979yeuT2SWi1RlCiK3gEgARDeVBVQ3mVWehM+Yl8kCBIk6CSRTfXU5x0yspCREZERz/N8f7/vNx2RCW9U3UrRGMrEThzfJ5RkTrR0ji24uGtrEARcAVLJGN966HtkKyus5Yb5VryN9NrzdGXieELGsl2seh1dFgSORfvsabr37iV49Tl826JnWGZ1zUJtVtgzmObCSp1mtcpIV45C3eKOgThBpUQkneb+gRg98xfYOjHBCyWJTCbBC1cKHbuvMCBwXZqBguO22D2SIHPyt5iXzhB76vtkd+7HLxXwiuuIRBKRy1Nte3iz8xT0DHeNZvFdm/GuGO8uVm89YAKalsdEd5yWaWNIt4ryK1WLuhsj+TGWqooQqM0auC5EopjRFBumj+2HJHSJlArhhxZ7hRC4KNSckJAPWpsFN7f7hdWPPcdBu4Vo1CDb83kvj02+gtiSQuTBJ5HOnMAvFwlqFYSiIOd68FJZVjdMZEkipitIQmDEFMYkg9APOLbcQunqxS+s0peJce9EHqVRpssqk33ocaxyCXXnfhL3P4xfKSEZUVov/4owkUYNfESjRKkEX98zwK8urKARUGz5DGai5BM6R0aznDm1gqGq7JoY4E6pTOvyOVRFJnP3/dirS8iyAo06Hhb9997P/GuvUa3fKI6RFerxOEf376f65ivE00mkMCRYXWDX5J2curaOqBSIDW/BXZjtLAgLicl8ktl3TpI5eIQ2UQrFFr1Jg1xEJhPVWK2bGOkM84HBQamGeekcY3t3EtcUJElQ3ihTfPNV9n8vz0Wh4ochcV3hvvEueoybzQcfPRc3MgLfs3KMRj1OXmuzozfJ/VuS9A/14bz9Os7yHAQBkhFB332QcNvef9guzmgcybbpTemsfzRmA2FESEe1Ti7nje+e0QU9SYNC3frI+zVFojeuwVcqdeqriYsgesc9eM//PaFzq82WtmWc9UgWrxkw1h3jlakihiIR0XQIfO4ay2OWSiQUQba5QfedRzj9xjs0aw0mHtnFzGLAwuI6e470MbOwjpRI4lo+3VENs20yGFcZk01Eo8pgV4Ir6w0EIbbj4aW6yT76DX4110RpmhiBT2gFXDi/wpEju0kWS5xfWwJJJhqLsG80z/D0CbxSgUCWCPUI0sIMPxjVcbo0zpQcHK/z+0SAY9sMZWPMzgWkU3EGtwzSCiQ8PUoqESEbUYjKwc1OMy8M0Q/ehaFq2FcvdOynZRltbBuxO+5lnxwjk7VoOz69SZ2+uIr2B8wgMpNZIk/9CeHaEn5xDSmWQB4axUqkPtHR4Y8VUa91BLnbEhIUVxGp7KbIuskmm2yyyZfGlybAeJ7Hf/gP/4F33nkHgGi0s4DVbrd55plnOHLkCP/u3/07FOVL14R+b4IgIELA4M3Oe+9T0pK/eKKqdLPa3nQ8RrJR5sttVEWi1bTpiqqklIAdvSl62kXaSkgoq5gSbO1N8fOzy6iagq5IxHWFtuNTNn1OLVb51p3b2dYj0O0UuYEoyxaEmoGczDAgmoQr8/hCQolECQJQZIHl+oRCotUySakSu5UmwvLwF65xYHw/i4N9XD51noM7xrljaJCVhk13Os6dWUHP1eOEK4tYC1NYtoMcjaHt3M+l+DAvrNhcutrm/ok4yxtVaq1u1GgEi876UcvxkA2FBB4P6zV49hna7vuDMSMWR05nCT4QPBq0WwRLs6hCIlxbRoxt+9yDs/eu47GeGO6jX8ceGqJ96Sx6NkFmdBRtdBy7UsI1LcLhbazvOMLVBZOd/WlOL1aZK9ZvCmj5pMGj27pJyd6teRNhiKUZMDiKPDKOUlqj8dzPbqlskjM5og99g/aNzh1JkhBCsK8/ydR6Z3EgkBXkXDfe+iqGrrIvIxPMdgRSOZUh/EfYlv4PQRAEDEYFf3ZogMWqTdV06IrpDCY1opL3BzvGtqJC7xChonO3vMGPr8+B18lWCcKQUEg8ubOX6JnXSI5u4ScXVuhJGuRiKXZFAzae+yXB+nKnU6y2gaLpZJ78DmZhHT3fi336GGFxFdl3SSd6Wa82iQ0Os6rEaTkeqahMv7CJra8SagotuxN4K8a2c8U1+P7ebloJk0qyh7mFNa6eu0IQiaOVVtm1a5Khb9+HbjdheZ7WideIPfUn1E8dw7l4jujCFIfv/i5vrFqUhUGxUCWTimO067TrFZLROMX5RZJ3P0awvkzj2GvE+vpQj96PFYRYqFh6ilysQSArSAPDCLNNUKsghSFSIkEQhOjbdtNr2ZS6R6i+ASKeRJIVkGXCGxaJiWyGKy3xvvgCEIb0xDWmi01GslF0Rep0ABLy0GQPluPe/F0rnotfWEHYJpPpXlo/fRNj9wHC7ftwpE0/6t8HEfjsz+uMZgdZqTt4hOz80V8iXTyJuzSLANThMdQ9hzBvVH2WbcGb1zaQ+oZQFRV/Y53QtmhYHifUPu56+F6Kl64QX54huHiRRHUDzzSJZ7KktwwR1quEkozbbiL1DRN292G98yY775G4IAtmLk4xtnWEHQeHWWm5yLrO0aODxJtlqitlhoazqMUC9VeewX2uze6n/wdKcZVv7s7zq/MrnYDbEAI/YOtAmicms4T/7RKSEUGKxbFnpnAvnCKwLVzHxbI9kvc/zOCTT7FaE7xxbYODg2nyUYlDwxlOLXSEQCkMkByXiJA53Bfn4koNPlDNm4mojCUEEc9Bjig3uyGDoJNZFDWbOCdeo7U0D2GAp0Uxx3ax1LuDE6ttELCjN8ldw0nUGwtJkiSx2ILXZtZvFgIkDJV7t+YYTcrv+yJJnxKit9mZ+Y8KUzOQ7/waht1GzE7jWxaBLGN5na4QTVVYrVsQiVJYszlVs/je/kFOLq+S7O4h35vhTmeZ9d/+Pbamo+zbTu2nP4MgwMt0sbZRIja6ldT9j1Cv1IhGk8jlVdT5y2zf/SjHpq/x3T2j1JUoSy2fTFQlF9MZyUQYuHcPOatG/syLuO8cJzm2hdj+w/gbBaRqhcjBO2lMXSZiRFjdeT9dSpS+jRUc06Tcdojd9xhz505QLLaQRcfus0t2uSPhs5HUKRTXkIdGUYdHCWoVBvIZ8lqI9cDjnJKyDGsBRibDWqVMRI2RjCiU2gp+NEE0lSQxM81gbwqxOEViYABBSHqgi6FdOwjmr/Dndz+OGUBakzCkj89wkiSJC2utW3K03uPyWp3RrihbYnGUB79OrFkD3yM0oriR2D+4haYTS6AOjrBLlrmoyHgfyGcUkSihbnB4JIP8gWIXKfB4ZLKbX5xfpWm/LxKrsuCx7XnikvePrSngC8PK5Yl9/Qe4V87hrS4hVA1tx17q/eO8Mt8kRPDQeBdD6QhzpTZRVbA1IVO8fIXZ2UUeODSB4ZawXJ8+t8a0kNGWr7F/6wgX5taRm1V2jXRzuQHpuIbiOUiSTLfkcE8GWvPT9PTvImqo1Ns2kpBYUpI0WxJqxIfVJbzAI/Rc8H3eti3+7Jv3sLs8gxeGxJwWxplfY9Wq2LpGemgISRJ49QrRK6f4QbKHu8aG+U8LEnXLQ2gGvVGJsN3ijr1jTFd9/v7iGg4CEYujKTIPT3azLafzwbh7W1aRD91DdPtecCwSmSxlZNq+TwqPvV0qQmidYoTfQ3yRZRnZsYEQ70ZxTxiGmHoEsWUSaWw7fhhi3xhbfNEIIZBl+RMdFSRJouVL1OwAIQRpXRCRPls+oiRJaFYLUa8hhCBIpjtuGp+4U/9AQb2bbLLJJpv8d8uXpnb8+Mc/5p133uGb3/wmTz31FOl0GoBarcYzzzzDM888w09+8hP+9E//9MvapX/UxCSf/YNpjs+WmNtocNeWDIYiUWq7TMYFWm2NrVmD+5w6xlunaNz1De4aj6At1Sk2bGzXQ5Yl+pIGmahKqe0ykI4S0xWOdiusvPw8WmEZIx4hPb6H81KSY5dL/NW2GIm+EeQQzGYLy+v4xeuagtw7gJXMor31W85NX+bIkZ04c9dwT7/DD//p/4mracHVUgW9XuPRwTQ986fQjs0R/doTNKcvo8kSWlc3wZYJ3N5hoprMUmgQ1WBfPspw2MXa9Tn2bxnk+OoKrm13/Lv9kEMDSaLvvIwquzfHmUIIvKU5/KU5tNEJnJkr7x9APyColghrlc+cywIQSDIFM+TyfJ226zOai7IlY5A9fJie/Xs7wZBGBMw2imUzV/c43ZBYnW3Tl4rw0zOrLFbb9Cf0m4G+63WLX15c5/t782gfU4mnmi3aLz57a1s54FdK2G/8Fu3x77HuyVwvtKmbHv1pg6f3D3F1o82FRQspk2NrPs0hwyR99lUCSUYb2oJ2+F7amxYvfzDCMCQuXHZmZYSIEoYhYeh+IRP8xaqN2qjy3a1xilKEsunTE1PpxqLx1ks4joWHylA2xtRalR35BO47r9FeXmAiGiKWF/FKHSFuY2GOzD/710jjO9C7ujGPvYJbWKVLDUl87UFmo3nOnb7E6PAkE8NdHE53sfbycyh6jL7+JOaWnVyP93OhaKJpMkdXr9D2Aq5f74S2KlFotUzOvH0W5+ghZkxBf2qcIDGG+epv8V2P3KEHEbrCkFth98QEry3UMKIazZZFLBrhG/sGKbz4DJ7psfjbF5l84H66fvR/wMr1c1LkWJprMlNsEiD4YbxJUigo60v4hbVOFaJtEbnvEaREGuud1wFIj0wSf/IJZs9exKxVbx7b7riBceAI5wofraxTCdiajbBRb7M7p1NxYbg7hR+EFFsOviSj+i7e8hxJXeHBPQNkp08Q2BbmqWNEwhBpz+HNTpjfl8AnJUM62xGzgjCBuOdhIlZHMHONKO0g6NjPSRLXS21CwJdkRO8ASlcefA9kmSuhzmjDpvLCszDQRyKVxmmUiEQC/I01fM8h9DyCZoP09j2cbMvsvOchjLkpwjee5RsPfJc3F+ssrBRgboHcoSNMZnTWL19hoV5nojuJsrZA+9JZ1HSGYMMhd+ol7AMPs6N/K/l7tnJ9vYbth0zm42zVXMTJ11F37kNoKn5hndbcDCUpRigpCM3H1QTX3z5HumeS/NA455fKzJdaPLW7jyODMYYzEa4uV6gvL7MlJtE12M+vXj2JFwqUgWGEEeHeTEhs7hycWUBKathDYxT6JjndktmSi7E3GWK+8Az+Dcs/O5RZLdapL75G7ojLvsmjlJomF1ZqKLLEvUNRAt9nw5F49sLyLdl5DcvlN5fW+PbeAfqMzr1S7unviCy3uUHKiRRBIv25LglJlml6HQtOQ6HTdbi5uvqVwg8C2qpBZHiM8NxJQrONQBDRVGZLTUIgt+8O/rbgsVqzeHephoSg2PZ4tC9g8e9ewXI99hzcR/WFZ0kGIfKNEPtAVmlcmyF58CjKwBYKqKh9W3Fsn57idQ6MTHDs3BXk3iFcI8b1hkl+S4YTb52hZTk8enCciXseItw6iXvlHI3nfoaayWE88k1qyS6mX3qdrnsfICt5WM0aFFZJypDftZ+pUMKt1mjZLobUMZys1l0S77zOt/ccYGFsC1NyGoKQ3ffvwQsEb6/XWW64+IHLsiS454FvklyawlmfxfJDug/tIpjcS1Q2yJolFM9GEQHt538OXmesqG/dRvo7f44huTiKBPh80qPFDiUurTY+dvu55Tpbd2TxfA8v9oHszq9AfpkfBMi7DtI3O8VT+4d5+eo6taaJnEwR7Rvg8NYehhPSTcu498goHj/c38dyw6HYdMhnEnRpISnF33wOfw6CIKCdSCMffRDVdwklmYZs8Pr1GtfKdseOS2kylI6yUDZpmA6npueI6yp33HsHg3aR2dNn6d+5HWdlkb6+Ua6fO8/YDpc7ju5mqVjj0aF+Husd4M2ZDSqmwx0jOQ61F1j4+S9ptiyGv57mT+8Y5aXpItfWa9iSyqqvoDdquLqB5QUIDTRFwW23uX7lOocK1zBPvoUfgmnbKKkMmYEBjPHtNH72N3iri4SKhsh0M3L0Qf7Z9nv4TzMWu0b6GY3B4rVZJvZv5fLqOrFEjIimkzBU4prMfKnBqajGgb5opxNadMQE3/cxjSgiEiOT78Nffb/bszMv+N2fS0IIDLOJf/UC7twMhCHqyFaU7Xswo4mb//+XKZjaqMxXba6sdzrTD43K9GgK6gfntJLMpbLLsdkSptPZt7iu8MBENyNx6eNb9gAZUGcuYZ56i/BGx4sUjRE/fC9K7yDe2tJH/0iSkLr7NscAm2yyySabfKl8aQLMG2+8wQMPPMCPfvSjW15PpVL86Ec/olar8frrr28KMH8ggiBgXz5CSJYzi1UuLlcYzUT54fYM5vws8sQInudzvVQlN7SXCIKrixv0xQy0mM6WXAwBuJ5LtQ3dMQ1VFsSdFgtnL1A7c57epMG5hSLu+Xmy4xOkt97Nf7zS5l+P78U1PfSEBe02Qlaoyga+kWJQ1yieP4cQ0KjUyXXnCZbnUH7+1xw6eCe7q+c7nvetCEquG+2xb1P9u/9MmO7GOHIffhhSbljMHD9JYrzO4S1HUNp1ksd/g7GyxODwGAE5/uz+HVxeKrFcapJP6OxOhAQf6iCRfJ/Q93EXZ4k9/vStAgydThgllcb5HOLL20ttTi++bzE0X2oR1xW+s7ePhCSBZkAQIkVinKopHFsp3XxvJm7w0rUV/KATIp1S368SqrYdim2fgcjtP1uUih8RX97DXV/DLGzwt7PvV99fXqsT1RT+9OgYB3p0gjAkrgnUdhPR912QZdx4EieESLMGZguh6nipDM5mVsXvze87wfo0ZFlmudaCMErv9EXijTpjXWnazTa2aSEFIenhEa6R4I3pIg+MJJgM61SnLrPFCPEWZwnoVIkKAKuNc+UCUU2n8OJzJAaH0LftwVxbx525RM+Aw9PDCbI7ohRSCf7vr19neOhu8lpINBqhvyvBteXO7+JazeW+O+6hb36eaESnbdqEfoAUiSIT4uoR5pbLtG0PIWBvdw4l6CyEzF5fYrivRd/IHvb3C1RVIWw1qFeq/OS3J3lw2wHE+bdIpNPMvHueLX/5P3DajvLGmVXarke15eAFAY/vNIiUCoTlEsJ1QFYw7v4a/kYB862X0fccwo8l8JeuI/yQbQfvYPqd0wjXoisVJ7tjB97oNvxTy8jtNkKWCTSdQEgovgsri2hRlQND47x0eYXXzpxD6h0ilkqwpzfBmOahx7rJtIuoF18jsN+vNrYuniEyvgNL/4cLM/7HxAd/Z34Q4GtG5x8fWFgTQtB2vQ/8DXiy0rFnlATFuoNmt/Bdl/LSCkOH9yEWZ7DbFoqsQKuB1j+MJ0BLpph0N7jq6Ix8/1/Aqdfpv3aKP5vcTU1K4Y7tZL5Y59Srx6lU6kiS4OyswV337GcwkkaSGwS5fjKeww63hKP340RT7OruQyJALyxR+M1zyIGJG5HRhrdiXTpLywtZqHasSywvuGknYp8+ybqW576JPK9OrfPm9TLf39PNiOEzsvEuvlXBL9aw/QmSMZ1ipYm3vMBDhyYQL/6cWqPOYCbO+lqN0rUl9ORZxh76Nq9fM8lF62QrVVQBTigxXWxRNTsdLebbb9NMjlAQMYazMZbKbazBBIYM5xbqt4gv7xGEcGqxwlPbshB4OMkMkX2HMc+8fesbZRnjzvuxVO0ze9YXGhavzDW5ul7H8QIyUY2jo1lGEzLi90033uQPjhWJE33saaw3X0QrbVBumyiGQerAYV5RB1lYbREScmGlxh3DGZYrLcTSDEoijtQyieHjRXQUNYpvGviWRbxviJbrUykUMYa2UL1ynbrlYigSyqWLpFKr/OCOuzBHtlCrtxiNCcKV67SNOpHRfnIr55j7u/+COjpJojdP7Oh9NITO5edeYPLJJ1EiEaIDw5z/z3+NVW8gFAVdU4kWXkNOnWfk6FFK12cBQVSTSccNap4HVy8zNjTAwUe+QeA4NHWFv7lUZsiA3QkT4Tq4RpQZN0ops4MH9t3J3EaNJRMaizY/GlehXET2HdqnjyNJ4uYozZ+dxnzpWfS/HMWRPr2Yxg+5xSL1w9he8A/d4P+JOJKMPLmbcdtkcHSQsq/gKioJTSL2MZ0/YRhi4DKelJhMR8nnu1hdXb1tXtsmn44fBPhCxkHllxeLvDVXRpZklqptTsyX2ZlP8tjOPLrTRleT9Cgu5XOv0VxfZEBXieCh9PXhSi49cZ1UeZn8a9NkVxeJ7D6AffghwtERqk5Ar11BM+vUa03CMKT47N+R27OPP993BHvXBFoyQbFQpmj5+D4okkQYgOUGGAiatTqxex7CrVZwr1wAQoQIiR04QuvCWYJmg8j+o4hkmla9jv3mC+wa3cq392xnfqPJ+ZLLI4f3Mds0iccjxDSdkJAwCPGB9ZbPMxfXaLtdrFXb3DGcYTyjIYe3zyl6D1mWUWyLUICvGZ9LLDHMFtZzP8Nv1N4/JxdOI81OEX3ye7Qj8d/xzP5uWKg8c6lAsfG+00TZLpDRQ57c1nXTYm25FfLy1cItzThN2+O5i2t870A/XZ/QzKKtL9N68yU+2MoTtFs03niB1AOPUy2sQXDrMY/sP4qdSP0hvuImm2yyySabfGa+NAGmWq0yPj7+sdsnJiZ46623vqzd+aPjvbZdz/vkQdstfxN6HO412NE9QNsNiCsSiZMvUIjn+dtT1ylWm0hALHCINKMc2D7M2YUSiVjASrHWCTtVVVzJQ1Mkug2BUishR5qkIyrrDRvX7wx2yjPTHNi2lx83oxzr3caRcYtr5y5gBRKm46Mn42x78DFWj7+KLMFgXMWoFYkcOgzNOu7VC1ieR/SpH9ISGtbKIpHaBq0Xf0l0535aM1dovDODQKD3jRAICVFY5p5DgmguTmspS1iv4y7OER+dYM2PEwqZw5N9bI0JIs0izQ9Vz4RCEHoOcirN7UoCpVgC+gY/dqFckiTsUMbyQRZgu4J3PyC+vEfT9nhrrsIT42nCGwNAO5S5tFa/5X1uEOLfmPCVWy6pjH7L4lLVdBmMKh/ZHyEEodnk43BCwXqhShDemmXTdjxemiry5NY4wvfwXfBVHW50vBiOjX/yTVrXrt60hFHzfUTveZR2LPGxn7fJpyNJEm4oIQQofLb2+s9DGIZENZl3Vjx67n2C+NsvEjSqzK03MGRB7+gwG7vv4ddTZQ4PxpFdi7xdxHOaqE4Lx2zjaCq6quC7HeFSBD6lWBdzdz1NsdogayToykdg+nm8q5eIqjIp82sUD3+DO8e6boZ9X1itEU/GycQiHBiOIgtBK2vQbUR4urvFs2fmaVge6pZx9MYGDhK9WkDSqXPnliw910waJ4+BJDOxcy/Rux7k2bk6Cxt1jNCnPD9/szLu+QtL/HDHPoIzb3Q6VhpV1h2Z1YZFzXTIx3W+k5foDUxUI4LXbKBqCigKSq6bxonXkVIZArPdyX6RFZBArC+w7y//At+yCHUdoUfgwjt0NTUqy50uIaFpKH1D+BsFQstkcLiLC0sVrs2vARAsL9BUxlgIQkYrFzFmL6CoH3V+CG0LYbZhU4D50giCgKF0hIsr9dtuT0RU9GYVVZZwPY/1lSITd3+NxqvPYZsmhiQholFie57Adx3UC+/Ql+rBUnUG7/0aQXEVNxSMROGVK9PUAoX+0SEMY53C+gaSYXDiyhLJ4a1MVBbxzAbJO++nVCiw8PL/AyWVQR8epdEzghWNM/aN72A4JsycQ45GCQgptVw8P8T2glueEUGzwdRqlf5UL+mIRqll0/Qg0SzTnLp4833q9Dm+sfceTiQiOEjklq5Qs9oMpKMYqsxSpfOMses10ktT9OT34qxepdh0GEhqrNdtrA9Y/riWRSq0ueZHGMgluLBS5dhik23dUaQP2H5koirpmE4YwkbDYqPp4ASgAR4g9hwi1tOLc/EMYbuF3JVH3bEXK931mUVsB4Xnz60yX6jefK3Sdnju4hqPbM+zPSNvVrp/xQjDkHYyg/bEd1GbdaLLNdZtmV+VBJcW3u/QkMKAu7akmY7KzCzkCXel2Tfej7F6Fbu0hi8ESioNE9upbT9KCR2lXWfXkf0opb9HmZkGV4Cmono2dRTaK2vsuvBbWpfOo+dyKK6H/rWnsE4dJ/RcpPI6QbtKIwyZbgkcz8OaukT+kScpnDhGaLZJGioxTUZSZOpugFspEfUsBg8eQMxO0bBdpootdKVjZ9TeNcCVy4tsXzmH5Hn8+Z6jzL/yCvViofNFhWD76FZq++5j3ZM4U/Zp2D4N22Ox4DFx90M0z51GmdxNcP0KBAGKJJAl8CtlwuIq9G/51OMekaEnabBQun1Bz5ZsBJnwKy3C+L6PqWigQCde2+fTOn+gc81t3gc+HSEEgZBxAlAlOpZuH7oXy7JMsR1Ssz0yMZ1rxSb3jOVIRTRWaiYXVuvc3SXjz1wg6pYRpQ0aK/M0XY/2/HUGnvg64coS1UKNZsvENwLUka1U7niE//rqJfQtLtl8D7PrGzy4c5Ke/jzFlXVkQspTUzTOXyLW3cPoX/1LpEgUqauHoFLBtS0EIZIkMB2HfNLAnL6ME8+Q/f5fEEoyanced3URNZFE338Y+9JZQsdG7sqTuedrOLNTiD3jlNsOmZjGWHeM50ttfEW9OZcMhMRSzaJpdeZ8qiRRM11evFrAGuviQF677bUmhCDSrONdPou9OIsQAnVsEm1yN6bx6WNCSZIIZi7fIr68R9Bq4l05j3Toni/tOpckictr7VvEl/dYrpjMlC12ZRVCSeadhdJtndD8MOTcSoNHxhIEtxGiVMA5f5Lb+aiFvo85N0Py6T/FPncKv1RAisZRdx3A6+n7St/HNtlkk002+cfJlybAZLNZLl26xGOPPXbb7ZcuXSKbzX5Zu/NHgycU1loBU8UGQRgy0R2jP66gfkr1zHsEQUBUBEQ10F2TtqTy27k6nm0R1xQczyeRyTA+lGOm6iBH46QTBke39XN1pULVDshFNRzbQVUEe7ojqJffRSgyS5bZKVkVgBBIy3NsGT7Cf71aQjpwN6Oje6FcRpJkpvwYQTsgUSjRn8+ybfsoYuYSzV/+BLk7j3HPQzTueJi3ZlaYml8gQGK4e5gDO/pJPvPXRB96klatTsyzUCSfAyPdeLvv4LKa5thsCcsf4IEHDxA1dJ45cR4Uk2ajxYWaR39/D98d34H+7vFbhJZQkpCMGGgRpFx3x+pE1dC3TCB1dRM5fC+NaOK24kwoyVyterw9V6RmuqiyRCoeYfdghkLNpDsZwfIDBAJNFqxVWjR9QexGWaIfhjgfqjJUb1QthtzI6kAgPjCgTOgfFV+gM2kUn1DF03ZD7Peqvj9EoWFTtWNkPnQnUITAP/UW9vSlW15311cJXngG4xvfx1K0j/3MTW6PEIK6r3BhpcHsRhtJgh35JNu6Ixh/wKDXIAgYzUY4MRvyclnwja//kOrqKge9BthtNlaLWK88y3cndrHuDjOstrEW50nFdNxGpyvLcTxUXUcKQWgG64ce5Zl3V7A3ivhBQLBUQ9dUvvHdf07+9At4q0tY4/tYaQe8PV+n0LBBwKGhNEldwXQ9XpjaIKrKnF2EHX0Jdg8M8Gf9vWxYIZYfkhEehVqL5ZkmD050Yb74c8rCJx6J4OkRmqkeFh2NWhigJpLszMeoGiEXrsx19tn1qSlRMoEABJIQrNVtSk0HTRF8p8fH/PXPqB/cRa5vCIUQ/+p5lHQXTmGdIJXFiyUx6w2MTA9KEBBKEs5GAdX3MTNdIKmUFpZoKFm27xlAzeaYubaI02rhL84iEkk0VWHnUI5fvPn+7yf0XLAsPF1HRGKU2w7JtHEzEP79i0QC5VN8qzf5gxKGIQMJjUxMo9J2kIIAEQaEkkIYwv1bc4TFCjFNxnXBWl2iWnSI3/84qiKjayr6rgO0T76FeeJ15HSW5MG7qSR6uLy4gKRk6SnO0hy9h2vtFhfn1vGExEjXEHfs3slcqUH58mWupXW2Gwbarv2UTh7n+tIGyAq+HxDYJsrgOKer8MuZBfrMEgNbJ7h/xxZ6kynypTr+aonmhcsdwfzGo0Lq7mOp6VBoOnQlDGqmgyTETZuOmwQBkZXr7B0/SE2O4r3+DumISlyX2WjdGqpsX5+me2AXIhqjbrl0xXUalodA4AUhISBLEomebipzJv/p+ByqJCg1bS4uV4gZOtv7UmiyzGy5zYn5GrIk2JFPMJyJIEviZki2i4SbH0LpG0HyfQJZvmkd91lZa3kUmx9dAAI4MVdmS7oXjX8cC6+SrNDwBH4AEQU0/nD5Yp8VRQhk1yaUZTxZ/b0W+xwh4ae6OTkfsNT2aDoWEVVGlSWyUY1Ht6Z5/tIa1wsNMo6FFnhM/fJ1DhzYwdHDD+Ade4lg392cjgxwds5itVFjOJegsAFi/0Mkx/cSw0OKRJkr1jl3bpHurjTj++9juXc38w2HVNRg79ZdJBauIs/OoJlN1NChEctiOm0kAcX1DfozGby5GbYnZdxSkaBmY2SzZFI5FhoeU2cu0Lj/m3SN78J+/SUw1zDicbKHDnG6IbF4fZ7sgV0M15dp/vj/S0pPclMSDkMa12fIqirqo09zvdTG8QLu2drFAiHH5iu4YoTcnXey77sp4utzJGcvoF58G3Qdv1xCGhz71HMR+h5HhtIsl9v4H7puDFVmW3cM3//shWCb/OMilGQWGgEnFzeomS5RTeHAYIqtGR05cDtj3EDlyprJ2wtVZCHYP5BmRz7BifkKM1MbQIgmSyxnVQ7kd7ClPQ0Xz+L7na5r37ZZ+tUvyf/oXzByI38vokmsRXs4vlhj78MPoEcjXFmtcbEW0lx2+Po/+dd0P/u3bExNY/sBvYePUho/wI+vVOnPxHlnZo1cupskDn6xAIFPPpsgXiugRAwi+ATNBt70RVxFQR/fCYZO+40XO1NcRUGsLWMuzpJ4+s/ZlZbpTXaRT0VQA4e+lMHsB0RL2wtvii+5mHZLccLJhTITXQNExUd/i5FWjfavf0pgvp8t6J99B3l2hsgTT2N+SmGO4ns4s1Mfu92dv4a+7whhGCB8H1/7Q848bvN5ocTl9Y+3NLy42mBHrgvHF1Tbzse+r9iw8cPkbf0XJM/BrX20+PE9vPIGIpoguOcRZN8nlGXMTaF1k0022WSTfyC+NAHmgQce4Mc//jHRaJSnnnqK3t5eANbW1nj22Wc5duwYP/zhD7+s3fmjwBUKL16rcL34/qBuar3BQCbKE5M59M87bJIkKsleildmCcNOyGQ2Gad36xj/7dQiUixBX3eayxfXuXdrNz3JCLMbTUzXJ6nAw5NZghd+TjQWp2tynLjtsbFRZfXaPJ5jo6vSjYl+yErL51Qd1utxFqsmghY/Go+SjkSY3L2d1s/+VzS7hVA0hKLQ3Hcvv5iuUbq2CgiCZpVLpTKzqRTfeeKfIB97ltTYBNY7bxCmMoijD/O8meDlK3MIEdIflWnUW/xvb82wNR1Bd02kviFkTaNm+7y8bPGNrTvxpy/cPBxhGEIyjdrTiycEqT//l0iujXn+DEFhjfaZt9H3Bri9w3i3HEaJy2WPF6+u33zNC0POLFXx+lKkozo/Pbty02JFVyS+NtmD+EDVb0QO6b1xfN+jYTqMdcW4ttGxLZNEiOR5YFvEdIUB1UMWykcmxQBBthsl24VX3rj5mhACKQzRtowx40eR/c51FCjKzbWrTFTFCSXmWx3xJxORSSoBaqNK69qVj3wOgF+vIDYK0Dv4GS+8Td6j5iv83dkV2s77k7E3r29wtaDzrV09f1ARJq2GPDDRw2vTBTZ8FcV2eOeXz+J7HqosEQQB3uIyw7t3oh44RHVhkUxvP1qjQtjoBNg2LY9oNIr68Ld4YbaObVrIPX14C7OInn7q2V7+tqbyrW/+jyQ8k4t1nxPTRWJqhG8N68RFQMk3CYAXrhZpOx5DKR1Flzh5rch8qc03dnaT19/7hUmokRwje3bCpVfxXBdLVQhTPbjb9vNqRWLl1DxLjsyGL3O10GBbXGP/rjHOXpztZHILQcPxMRIJfC1CVFdwg4DduQTypbdwTZN220Y+9y5aKk3usacJIjEku401M42olIjkumjNX0cPPDRDQ852Iwloo/LC+VVWZ5cJTZPAvIY+Msahgzs4e3UBq1BgIBPnzokU8Y0l/A9buXgulutjdg2gSvJtz5vaP4gXT3WqTCUZNwBd6iyMbfLFoePy3R3dvHlxgZmpOVzXJZPLcteBCXq7olxrZtF1HVFfQ4tGoNWg8srzxDQF49GnqP/sf6N9fRqtf4jifd/muTOrNN0VRDJNUFzlnrsOce5ak7enVwlVDSHLnK+4XCkX+e7+QarXdLwAwt13sEaE9dQYykGPSHER6+pFuOtRfvb2NaSuXuouZPUYq47MT96Z55v5CO3TL5Ls6eW+P3mayyfPsTY1jaypmMOTpJoaQoCmCHpTEeJKJ5Sam5I/0JXnQtd23jg2zc7hLgYtB7NustGSyMUjSAiC9957Qx+JDI2Q3beXmCEjufMExQ2CsKON5CYnuNqSuLhS58hAgjuzkFBh1Vc4V3aY6Enw/JW1Wypj1+oWBwbT7OuNosoyli+QJYGKjxcEnSKJz7lwIkkSi9X2x25vWC4tN0D70kbDXxytUOX4tSrXik28ICQd0Tg6mmEspSA+JnT9D4kQgkh1A+f8aezCKkJV0bbvQYxuw/o9RGUl9Ng3kGLpcpFMRMXzA/wgRBKdcdPMeoO19Q2SfSlEYRFJUbiwUqN3ywEGg5CXwx6uT63g6lE0WcWWVX5+YY07t/ZAPsFCyyIR1amVHYy4z8j2rfztpVms5RUG+rvIRBTWl1Zx991Pt2fD9auEvk8QChCgyjKxsQlURWYsbVC7dI4wADkWp4JGealAoHasXi9WfC6tB3zvsR+QbVZoIfPy/DL1akdquVR2GDVkpFqZaEoQUTOYrocmSyQ1iVx1maBdQQCHhrNcXm/wRtNmPB5l0bEwL63yytV1vrN/gAIDPPz1v6Bn5jQinvjMQlyPEfLNvX28db1MsWkjgOFsjLtGM6QU/3fOrBNCdJ5rm4uff5RIksT5DYdXp4s3XzMdnxeuFNgYynDPUIzlVsDPzi+zWDWptD2ajsdwJsq+wTQL5Tay1MngCkNoCo13C0V2j44SDSGuq1iej+f5RIaGkRUFLrxDO5BY2XUXv766RF02KBWqVNoFxrvjfHNPP1a9xvSizcQ3/5zI9DSxeIJZEef4bBnd0InI8PW9AxybKbARKgzmMoxGBQejDnKtiK9HkF2b1ovPYKIQzWYxFJn2q8/jTe6l0rQwbRddkUhrAvfKefJ9g2RWl9H2HsLu6mMsF+HkgoTjda7ttvv+/fbwcIbVyvvPINsLaDg+0Q85AsqShHvxzC3iy3v49QrB7DTSzgOf+vv5pJB7OQyRV+ZonzpOYFsoPb3ED92Nk+3Bcf/wUowfctPZ4bbbg6CzHiGFRDTllrnRB4kbMvL7dRm3EMoKkhH9WBtuKRYnkOUb1niffwyxySb/0MiyxNeHbl9Iezvi4Rcpq26yySa/L1/alPO73/0u6+vrvPjii7z44otIUmcx+r2BxAMPPMB3vvOdL2t3vvIIIZitOreIL++xXGlztRRlf/ftW5g/Dk/TseJp2m4ACFzfZ2yyj99cWSNAkE5Ema+YeEHIsxfX2Nmb4IldfeiygHqVqGvRv22U9juvY194C8l26O0dYPjOO5m9vogYHGVpo01P3GAgFeHiao2+lIHl+VRNl1c2Ah594AG8Y79BJiD2wOPguvj1KteVDJVShTAI4EYmA76NZTucbid5SDXQkkmMPYfQduyhbFvstVcZ3d7HdDNkafo6xa4EpmlT0BWGrDoxQOT7CRAs1CxaB+4j0ajgrq0AISgK6sQu1H2HcWo17EvvYr3zBnIiiTAi+Our2L99huiR+wh27L95rK1A5sRc4ZZjGwYhXTENRZZ4/Xrppv8+dAbbr04VuWMweXPAHfo+dwynWSy3bgo1S5UWR4azuH6IoUrIzTre+gpRTebx7d1Iz/xn5IkdyLvvwPnQ4q0tq0S/9nXsN17AXV9FcW2CRg1lcAuR/UdZfPEivmMTShJyPImc6ybfnQbgp2eW37cYkwV3jXZxUAs/MVQ1qJUQfUOb4YWfAyHJnF6o3XaCsdG0ma3Y7MzKf7hjGvhsy+nEI4OYzTatk2+gSyGSruD6AYKQQBI0r15hfM8OFlZWILmDgb13wMYzBLJMEIZoPT2sTd7BysvnSORyIMuIiV1cNyXWFqsAjGUj6IbOifkqDw0nyc2ep3TiXVzbZu++fZz1PAZiOhHZJFhZwvNc5HicjWaCtb44o9n372UxyeOhfoOFFxYBiGgKy46goWZZqqyg5tPgOcT1OG034FrDZ6K/m/RoiOcH9OVzmFGdngceolrYYDw/iTpVZDLi0ZyfB2Dp+gL79xwieOtFKstztFyf/ie/heRYKIFLIAROs0kgSSihjxQE+F7IS9Ml1stN/MIaoWUh57rxNgpcdi1+cGAQTRoitnIN9/JFwmSG/twgc2vl98+J2ukaO91W+d6jT8LJl8B7/x4uJ9Lodz5IQyhcr7mcWapgOh7ZuM6hwTR9UW7+Vjf5w6IFHvJrz/KQ43BkYgu+UIi0q2iv/Tei9zxEc3gM56EnMF/+Feb6OiKTJGo1SR06iq+qKNlukkOj1Id28NxKiJ3qQq6UoFYmmoqz4ChcLdVJxSNUKnUCWSFQdWzb5uxSlZF9e9jXY/DMfJGF85eo01lozmZTfOdbf8JrU+u4no/WqKHEc8iJKNZGkVq5yumwlxEtRvHqNZavTrP9O9/rjLG27eGXrSh3jWZZKLcY74rxwGQeEVi4yQxq/yDuSud3VhvexZtnVgiB5ZbP1vEdmKdP4PoB5bZDVFdo2p1JXXJyO0m/ivWbF4nV1rGbVYZHJrEO7efamfMERgz5roc4ea3OvxzX6Jl5C+/teTzfY6Snl4lDd/NqUaU7rt8iwKSjGpbrcaVkUzdtZotNVFliV3+SbbnI5y86uYGh3F7shI4EJX/CgtU/BEJW8ENQRHhby5XbYaPyi4vrVD7QrVQ1HX5zaZ1Hd+TZlv7ibdYiG2s0n/97+IBVrnn8VdSlOfQHHseWfjcRJgxDJnIGO3qTvHGthO0FNG2PvQNJ5spN4pIPYUjb9jAQNDwI14ucz42TPvIwV379DrIkIYc+ia5eXE0nakT51eV1Ht/WzQvnV9F0jd19Xdx5cJi3VjsWlY8f2op++TTtS4tYjSaNoWH67j6CsE2aC/MIu02uN0/ftgkoreNPXUSoCrrvoGo6XiZLqWwShiGSaxMd307BCghlhedmG3x77xDzF2eoV9+vEG/7HasgwhDVaTOa70c4NqJeISzXCSsCbX2e/+PBLZyswkyxRTqqsmgKzBuH3QtCjs1X2ZtJ8avFNj/cdYR0vv8jYwtJkvCRAIHMBwLnw4ChmMyTu3pZa7qYXogIPETYse79vAqMAmiNCv7KIvg+cu8AXjr3kXHsJl9tmr7M8dm12247t1RhWz7Bi1MF1ho2puOTiWlIksSegRQvXi3QkzBYrpkokkQ2plExXeRUD5dtk7sHR6jMzKAqEtmd28k+/HU2/sv/D993Uf75/5lfnlnDbLVQ9AipZBYjqfNEtIZ67DiVhUVsIRPs2cHY0XtoRZI89/y7aNU60XSKS7UkQymduwfi6LrK7p5B7F/9N+TuPOHkTuSNadpn38ZWIjiuh5LpwTNNWoPjLCyXCFQdbJtGGFCWZQbjafosE2d5HmdlkdjXniQzvJVv7u7jxaki1baDLAkMReLoliwiDGg5txbQ3O6Zo9gm9sL1jz3+7vWryDv2fWKvpicrqKOTeJVjH9kmhSFKIkH71HH8eg1jdByJEPPn/xWlp5fI7oME+QFs+Q/XgW3IIUOZCJdWb//s3pKLoYiObeqBwRQvXCnc9n37B9IEH1OE5Eoy+u4DeK89f9vt2s79mJt5Tpv8MeN5zP/kbz/z27N/+Rdf4M5ssskmvy9fmgAjSRL/9t/+W5566ineffddisVOBU13dzcHDhxgZGTky9qVPw4kmXPLH99Se3Glzq6uHuTPYZtR9yT8WAopEqVe60z4As2g3CzSlUtTMj1sL6TteITA2wtVxrrjzKzXeWpHN11+HfXKafzrUwSei2FomCuLtAur7PiTv+LXQZTuiEx/fwzb81mv2xQbNuM9CTJRjbShYgxkoFEj8bWvY73xW4KNdaTdh7g8VyBs2+B5CCNyc6IXuC7zxQbO/rtJbRnBst6mdfI4i77BeqVJJGJweOcuUluGWbqxkFlt2fQmU6j1CkoyjVAUQlnBkjVSj36beL1K6DoQiWIlcrw4XyNvB0jnryIZXVgtlz5ZkNI7E03z3eNEh8cwbwQXtm5M/j/MZE+CY3MV2o6PIr9fCQXQk9Q5t1JlYPz9QWSPHvDNPf0cmy2xXu+EcDcsm39z5wBOqUR5PSS+ZSvdsody+lWCdgvr7Emi6Sza8ARyswZhQBBL4Mgq7WgC9bGnSRdXca9dJZRl5GSa1lu/pYssa60WIhrDr1eRHZPYQBcnlupktfedc10/5PWZIj07c3RJ8scu9kqxz15NuUkHMxC3WBR8mMtrDXZ1dRH6f5jKlUAonFxpcXK+zJ8Ma6ytreN4PpKA2I1KQyUMkGQFZXWBXE8OvbQCw4fJ/Zv/C36ljGu2MYtFNtaLKNEYvqrhN+qspBKsN9sItTNRcwPwLYcuQ6bnwpuUpq7iOR4SoHX3MHNximy+G6+4jt+qgywR1sqgG0zlYuxKDtCUOo+jIAhI6wK5K4bVkii1XbJbJzi5XkeEIWG5SDbXz6IdElFlfEnhVMEin0gSmhbTzZCJH/xzUkGDNTNgMGWwszeB5Vm8519g1mqU5QFGjt5D5Z3j4LuYhXUSew/gLi/gtFpEJPDDgFCoRHbtZ2V5jdVanNBq41sWar4fb32F0DIpA2W1wtAbP8P4k3+OIyuEa0scObiNpY0anucjVI1Q71QweaGAyV3E+nvwV5YI2w3krl7Cnj5aeoy3FhqcX37fw7tpeyyVWzy6o5eJlLRZQfwFIG8UsJbmAIgWVm6+HgDm22+w5ak+6sLGeeo7GJ5NBB9d1/BMG8lu0Tp9DHv+OovfGaO1tE5gmaj9Q/jNOqlohqn5Ag0zZKgrSbVSQ5JlhKBj59n0uG9bnvMNl5W6jZBlVCHjSzLlUpVztQGKItLZIQGKLCHJMpWNEl4omC406IumaAZFJKEwf/w4A9//Ef/zxTqjXQavz2wQUSVa1Rrrs3N8Z98gRlRBufcReOO3+JUK8+2QIAwRukEr2UW9dxDj+hRWtYLrByR1labtEs3myAwOcvV//o8QhvT0ZXCULuTiCmqrxeTT3+VdN8aCqfBEDygvPIPj20g3xirtwhrt3/yco48+zVSml1LLgTAkpivoMth+yG+vFJjsitx8zr4xs8HsRoSvb899ZvvVm+fvhh3juXXzttv7MxGSGnwVzOB9SWGp4XNmqYTpBuQTOnv7k3Tpn2y5JoRgue7eIr58kBOzZUb2f7E2a2oYYL3zxi3iy3u4S/NoxXXI/25ds0KSsLyQ/QMp+lJR6pZLzXQZSkc4frZMo1omHYugKjJNN8BDQhJQKZUpDk0ihscIghAjamAlsoSmSbHlYPohQlFRFBm/2eD8TJN9I3uxWyXujLsop9+kWSzim20IAhory6y/+hJDe3ahtlq0V1aZfGAv5TdfYd0RDOcH0LryYESR2g3cUNwMco/29lLL9FFctlmrWwQhLJRN1HiMLVsGmJtbBqArIiHCzm9dUjVU28S9dpnQdRGqSqhqtNbWiM4vERu7h2xMI2moLFTaJBMpaAnwXJZqJnePDjBfmqE0vItILHZL5Xc7VJlabzNV6HRhb+9NMJnrWKEKIVgz4ZkLi1iuTzQapd1uI4AHJ3vYkVM/cyGAGgZIF0/TPPP2LdewtmUc/a6HsDftNv9oqNk+tnf7e0gQwnLdpml7tGyPmKERApbn4wedbLKehIIsBJoskYtqTBWbpCJRmmoU/f7H6d97CCuQKLRd7DdfRzLb9Dz9J7w9v07z2jShJBGEoKfKfPfAFlZ//QvwfXrjBhXTY+H8JXLNDZJfewpJlknl0rSrdbJdMS4vlljNpUnKFr2ZGPF9d3OxavFgzCBccRHpHKFsoMSSFFxBJJZmpd3JZxSyTCjLIGRCLcJCoUZXMtf54jfue1rvAL2Gxg/35qnYAaYPc6U2K9UWC/Vb78vZmEZGF7dElsiyjBL4nYI80TmeH6HT4s3tsk5unocgQBrfgXztCv6HbLlkTYdUFn91mcj4dtyL7+LOdwQfd3YKeW0ZaWAE44En/mAW04Hvs38gybVi8yPXTkST2ZmPEdzIRt2a1lgfSHFhuXbzG0oCjmzJ0R+Tbtu5IssyqtlC7coT276b9tWL789NJYnI/iN4+YE/yHfZ5KvL5+kQ+TzrZv89IEkS1mc8JKokkMOvwGB5k03+yPnSTRdGRkY2xZbPgB/Ssdz4GBw/wAc+a/2YJElMr7eRZIX89u2051cI6lVCRUGJx9HjMdarJqbj3/RwhxDLDbi0VOGekRTJaxdpVxrkJ8YJyxv4jRpaIoobT9OYvkpsspd9/Sn2D2dpuzBV6ORcVNoO9411sb03zoZVJbv9AEFxgdCxEck0kqYhXAthRAmK68i6QWC2EPEEku8jKTJyTxdBq0Fr+gquouFJGggJOfApn3iTiaf6CBIRBAKEIETgex5SZYPAtohEdJL1GGEmRTuZuXlMzhdMzi/XGIlUqVk2iqLgByHL1TZ6VxxDCsHzkeo1RLQjOihSZ3L/4QGyLoPrB0RUGcftDCgNVSaf0IkrgmrbxQ9vrgETBgH9EcF3dnfR8joWYNnyMvbPf4oXz+Cl+mg3KlR0mb59d+GceAVJVZEqZbyLP8Ha6FigyaksxuG7cfq3ECJoX3gXZ2kOpacPceUc8swVnnzgW5yI55gpmzgIhge6Wdpokk/oOJZ1y/cIgVPrFk/t3Id74fRHriWhG9Dd+xmvvE2+TIQQuCiUrYCyHWB6MNoVxwssErpCPQxvTIZ9FEVGDkJyEZWIZyLLPmpPL85vfkrZsghTWbS+ARL3PsJQdhipPIu9PE/YP0Kh4RD4ARB2RBYREoSCQ1GLyvQUUVUmonS6eUQYoEngF9fRkgn8Zg0RBISBjwgCRK0KVQOpq++msOBoBpEtY8hXL1AhRFIVfM9HCgM8yyKhyWRllaYT0DBtLDVkcqQHjQQXrs4zffocPzy8heiWrcy3LP7l3aNcXKrQu22S2tXLJA0FZ2GO+vAgkaf+BMM2UQdH0LMZlPOnEKdP4LebxAaGie7cQ/v0CZoH0uDK2LUaIpXFK3UW5sIwRBKChhNgV6uUX3+Z+BNPY77wC7qvnuC7d9zP8apgLdBQVIXRXJQ7hlLouLRjKcRkGiEEzo3vXrbhwgfEl/cIQnjj2gaDB/rQNycQf1AkScJfnvvY7X6tDO0WRnkNcfJV1IFhQs+ldO5d9LEJWJrDLxUxtu2mGsj4rc6ipreygDKwBYSPJEK8Zh0lG2Uon2XDl7G8ADSNiKEykM/y6ux1VNdDiSfR2m3sIARJotk0IRbvdJ9lu8nEE3iNMj4SjuehqTJ+2wbPJRAS60urbHFa9KcNLqzUyekCY32O0GyxAZyQbB70V9CP3of88LcwmnW8go86HCHQdDwh8WY55O4Hv0VqeZpg4RrZpE60bwxncCvLz/2MqK7QE9PQ6iXmAgM/FMT1EKta4/mKYHuvypb2MstWu5PU/AHCIEC7fJLckSfpMqQba0ohIFhv2HTFPrr4s1w1WWl6jMQ+//nN6HDnaJaXLt5q7RLVZO4fy8FXwN4vlBROLLU4s/j+olm5ZTNdaPCN3X0MxT6+S6djs/bxPvt1y6XthWhfYMOB0m5iFW9fHQ/gzc0g94/gf8aOnptIMlcrHq9Or+L6IaYvqJoO+4YyZKIaA71ZWkuLjGQN3FgUO5bAN20CIJ+MErbqlNY2CIH0yDCK79P2AsJymXgsga5ICMtESBKGImg7PnLok7Pr1JaXQVE616aQIAxxvAB3eYH4t/4MQ8jw7puo2S7ito8sCVpvv0Hy/kfwyxv4bkBCTaBN7KCcGeDluTpt4kQ0habt4YYhb8zXeXAkQSYVo9my2JaQCeogx5NIRgR38TpBs3NuQ8dC27mfRrXC8loVP99AkyVUuTN+rDoByXgKNfTB95ESKeSRcWqSzsAHxI92qPKz82vUzPeLPd6Ysbm8pvPtXT2oAl6aLmC5t56rEHhtukh/coDUZ7yWlOIqrXdPfOR1Z26GSE8f0ge6yzf5avNpfYICgRDQlYhQM10cP6ArrlM1XbpiGqbrM9HTKWRrOx7j3TGCELpyaY498wxWrU5vwmBi307E2hzG5CT2tasU45MgxM3PH83F8E68guJ7+JKMoiqYdZukCqKwgjJ9HqNk0nI8Ej292FaD4UyCkm2z0jYpj2RZKTa4O+kT/cl/JNy5hyCZYb0VYrV88Cs4/VtoOK8gyyqKqiMUldDzcF0XI9dFUY6RkmXwffxGDanZIExlUXDp1jqicdtWubRyq/iiKxIPTXaj4N8UGbxSEenUm5iFVWRVwbs2j5LrwTcit0gt6vgO3A90oAlJpuFLmG6ALgtSWseq1tQjRB5/muD61U4xXhiijU2ixhM03noFKRKFRv2m+AIQOg64Lu7KIurcNGJi92cuspNlGSFEJ8PnNn+TVQO+u6+ftxeqLJTbCAHj3TH29ORIyd5NXVYOPe4bTrC7N8Faw0ES0JvQSKkBBB99RmuBh7h8BuvCadqWido7QOLwvYSyhC+rSN292PHUV6G2YpMvms/RIdL9F//kC96ZPy48P+TnF9Y//Y3Ad/bkkb9aDeObbPJHyRcqwDiOw1//9V8zNDTEk08++bHv+9WvfsXy8jJ/9Vd/haL8IzDi/gOgEDCUiVL+mIrG/pSBIX12NxohScyW22TjEYyojpLr4Tox9ugxPLV+s2PDDzviiwAkSRASEkhSJ79kfopywyInKciBj97TSwCoQYi6Osvjh49y1QiZKTS4rz/KD7dnOF+Os9F2yQZtwkszhE6DdF+e9tsvdUQmy0K6NsWOx+9hbaGO0tuPX6tBMo0jZJBCdgx3kezN0fyv/xG5ViIUErmhLKVGiJAl1GgU6dol8veOMTTYgxsKQrtG3fKIZTS0fDeH0h7qa79EPXgX/sg4YRhihxJnlqq3PV4h0HYDPLkz2Y/XHSrRgMGkRlKTODrWQ6nloMqChuWwVG7heAG5qIqmSMiiU/2liE61hXAdujSNiO/iyO9bgYRhiPA94gIi7Qbtl35Jfdfd/Pr8MhvT8zf3Z3B0mCfueoxMcYHmsz9G7h/q2LTRWRxsvfgr4o8/TRhP0VpZ6FxD8QTW6XkIAvSX/54HB0a4Y9edNGIZRExjbmaZZqYfTZY+UhFSNV3E7sMoKwu35soYEWIPPokViW/66H5OolLIlmyMy2v1227f0ZsgvM0k47MihKDqy/z6UoFK22G16VJqOWzJRdm2LcvI2BAL1xeoWy5BEBI3VNKGQVYNccd3o2e6aPyX/zeyLCPLMkFxFWSJ9q9+Sv/3/xlbUyozqxKWkPGC4MYVI9gzmGZuvUouFSNhVandEHDrloPvB8jXrjPWu5X1pTWEEMiSfENclpGBSc2GtRXUngHsG9eUHwRoew7RXFwgZtfQrQoTXaNcqVUQyQx1JPB98nGdnpjCwcE0Zq3B1blFwuI6Qb6P1900xvUyM3Mr5FMR7to+yODXHmSpvNrpcFFl1haW6FFU9J48XrYHv7RK8e230LvySLkerFoF/6f/GSXfT1QK8JEwbY94PI5XWLk52QzCkIQmITSNWtvGqbfo+cE/pepJLFVcol0SOzWNbExnImdg4OJ5N2TuMOz8P5JCze0Ehu8ZypIUPkarSggs+jqzDZeW7VGzfHr0j5z+TX5fPsUOJwDUHXvxSgVkx6H91otYboix9xDmtSmE7xAKQfZQ595PCKEfQBhQKJTZtm+Q62tV5MAjhUs8ruFqcUwktnYnqVo+zVAmnUgTyDJSu0VMU2h7IavrJbYf3MPlWjdBKo3jB6CoN/PAdvdEqV9YIgjpdJp4Aabtsi9rMLseUipVyUdiyGanA29qpcodo2mk08cI7nkUJ56iVxJ4xc54oz8dIRMzWPND2tvuJLf7KJGsSkxVkGs1Gs01ZGFCqUggJJKpOCuVFpblkF++xg/v/hZCEiTeWugIlB86lrKAeKtCxH1PEBE4Ibi+QFNk9g2kWSl/VFC4WmiydSKNd5sui09CBD73jPWQ0zudhi3HZzgTYUvGIC55n9dR6QuhYsPZD4gv7+EFIa/NbPCDffmP/dsw7HQDfhyS4EuaNH9Cdbb48FXw2SjZgpeurt8seIkoIXJM59JqnYgssWukh/XyVrz1FZymSphIE2nW0SU43K0itYrk4hqmrKPFE4RrS7SVOGEQ0Kt4GGaD8bhAaDpKswrFVQaySaIrlxG5FCgaeAnarRaNtoMhhTQvnyf5yLc5Y+rE51bJ+026rRYxcwjJ0Ki/9lvI9qB988+ZX3W4XqxTX1vF7tvCRtVGkSS64xpty6WNwtvLDb61ZYCBoIl/6k02FIn+P/8XVJbXKNohjh+S8tukS8vQN0BiZQlByLZchGOldsdeTRI3DrNEgGBrPkXVA19WSOgKYdh5tsqyzPnl5i3iy81j3bSZKpmMZCKUmvZHtgP4YchK3SH9GexSFVnGvXzuY7c7l8+hje/EljfnfX8MZAyZqKbQdj56/5UlQW9Sp2YHXC+12Wg6N17v3BXuGcvxznwF1wvojmv0xFTabkjDcokkE0w8+jCtE6+xvFGn3HbpIUTfuo3iqy+SvXt3x/oOkISgL2nQOrWMrGpIkoofgC4L4jhQXEfMTXHvg99luWIiCYGsKixMXyct6cij/RwZztAX68U9/gpBPI4woohyETnRB37nc9ZtSB++i8o7x7ADQUR0PlszdGJ3PciGr5Afm8SauQph8BF1KgwCdmRVug8McqXQpG669KcijOUipBT/Zmec7jm0XnoGa6kz39N37MW5dgV3aRZ1cAtBtht7aIJmpo/G8BgxZFQR4giFtxcbXFqt4fqdPKyRXJwHxjJEhYupR5F2HULZvg8AX9UI3z1G6Lmovf04F8/c5gx3voRz5Tzq+E6cT5Hc1DBALRc6Io9jow+NQv8QlnprJ0IQBGSUgCfG07T9DELAcD5HsbD+0XtI4JFRIJvtPM/C0Ltt8IskSYiLZzFPH7/5mru2jLu2jJIfQH3kKdrS5n1lk0022WSTrx5f6NPphRde4NVXX+Xf//t//4nvO3jwIH/zN3/DyMgIjz322Be5S380BEHA7t44V9bqH2nbVWXBoaGP90O9HQKIKDKSJPGLc6uMd8f52kQ36YjK03v6ObdSuyW3JASOjGQ4v1IHScbQZCLxBLF8BtO2ULUo7bU1FM9Bciy0fD+K59BfXaTHcfBPXmbIC0hl+lAmdnH9uV/TKqyT6UoiP/UUtUYbWdLQEgYEHsPtNXqSXRSlKHK6i3arjW07dOdz7N23lUsrK3TpcSKBj2+1SfkmuUQEXIfANvFqVRamZ3lgoJ+yA9MFHfqGUWM6kz1x9mU9/As1rHePo/UPYysqbsBNX95mNI2kqjcri1KGRqFpE/gBkq5RE1HeuLTOkdEuCk2H6WKT66U2nh8w2hXj6EiWmbUaj+3Ic+xa4eb/o3gufnGNoNVid2YA++e/RN9zB/7YNtwPLEgIIQjXlnFGtvHsTJVq7VarqqXZBd4eGuDh8gYEAeGHFwvDAPvc20Tuf/z99Y8g6Nge0fm/nKV5wuIG7VQ/8tAW4vFx5tsuXhAwnNKRPrBwkoqqBIaB+sR30UtFgloZKRaHXA9WJL5Zsfg7EAQ+hwZTzJdbH8mB6YrrjGZ0wt8jOM9B4VcX16m0nU412o3TOVdq8+w1mb88dA/pQoGumIYfQlxXWKq08fu3shok6Lp2nOy9jxONGtBq4i5ex12ax282kNNpvv7Q0xxL7+ft+RK6rCA0hf2DaXK64JXzK6QzLk9uT2EqEp7nIxOCJGgtL/Lgvj38ciXARuAHPiCQJImRwS7Sy1PYqZ04a+vE5AA720MzVPj1csDIvkeJz12mePUiO+7fz7ynU2+0CNeX6RkaY77u4DsOUl+cZ88tEosaDGzdRaVlUVsocqAvTm29QKMgWLi+yDfv3MaO73yflXPncdaWGZ8YQ52fpnJmHvv4q0gxg+yBw1TPnMIrrBJXJfA8vMIaXe0y2dw49XoCL3DxZaVjIxWGpNMJ0pVl/Hiami+wNyqI7fv4+fkVKq1OJd9EPsV8uc2b10uM5qLsykfpjkjIgYcpVF6ZrrBQbmFbDorZYiCucl+/Tuml3zBmGEweupdXzBjiU+tQN/m8BEGAMjwK507edrvSlcePJfATaeJH7qX2v/4/Iew4ggjPQzZ0gpaDU63S79WJxKK0W+2OZYrn4Ss6umuxb2IQPBenXEQ4i0ihYCDfzVMH9jMfBJTbLq6qE4kqREaiyO0mKdskkCR2D2aZK7d5e3qNUAh2DWYRwJ6xXuJrc2w4NiBAkoj39VHSkqy2QoayUaI5g8sLG+RiSWjV8TyPQI5iT88QO3AnphEjH5PpSRh0JQyuFlq8NLOCH4QI4Ohojv5MN1HPRZNBc2381nsCiU8CD1WVcV0f04eZ9TqKItOLzGQ+wWrNxHRCFFkQ02T6kjp6VAdJwcNnrW5Tt1z8UJAyFCKqzGh3gksr1VvOg/R7ZLXoikyP5tO7Jf6Bal33KyG+CCFYrFkfayxTaTvU7U+2ndmai3FqvnLb/2M4FyOpwhfpHOHF4qj5Ptz1ldtuV7aMY37O7hdZlrmy3Ly12zgETQR0RxU2WiZPZnJED4/xxrUk7WKDcsvjyL7d3J8NSb78U3wh8dR93+G5hTay52BbbdRkgkjU4KHJPLOXr6IsLiKpKiIap7q4yJEnHqZaOM9KqQ2KS+j7dCUi9MZjaFaVViChqBH6hUSmvwvJjuGWNyi/+w7pfYcIXnser7RKeOJlpNH7KNXbxLp7uGYJwrBzvu4dzbK80aA3IojHk4wM5hBnrtEanKCeH2RK6uNyqNHaWALXRUr0Mr7nIF1Bk6YyQHR4hOmaSTqqMlVoYqgyQRAi0RHj7hjOcHmlQtJQ6Y7JnUViwA4EMzdsx27H5bUGQ+nIJ54Xx/ts/fciDPDbH/9ZgW0hfO9mMdEmX20iks/9E108f2ntIw4Ad47mkAUMpqNcWGsi3XCM8gOYKjS5eyzHg5PdvDazgeMFhIHA8QLu2dpFs7jBYmgw+OCT7AtsVlyFSE8Sx7bxm016vQaKquI4LpIAT0gYmk4YBGTiGlXTQRcB3boELUErmuJSyeaVS2v4fkAuFeOhfXuorhY4nHHJ/d3/C7NURO0bIHrfYxCJEv/aE/RMzzC7XgFJwa2WOWP0c+C7P8K8eoG4WSeMRPFHJnnh0gpf32bjnn+b6KG7cdZX8ROpjxyvMPDJqXD/cAwhBEEQEATuzdo1IQRidRG/XLz5N+2Zy0Tuf5xgfRnP9ZjdcT9vFVyaRQ2/vEYmqvHgZA+LlSZnP1BAGIQwu9GkZXs8vasbJXQJggDnvXmm5xEd3AJn3kZIUqfj5QNIRoTwhqVw6Hmd7nRVxw9AkT6aRaaGAeLd4zQvvnvzNWd2GjmVIfrY07SN6G2Oh0dEdL63In+yIP9p4q7ebtK+8O5tt3nry+gb69CzaT22ySabbLLJV48vdNR77Ngxjh49Sj7/8ZV7AL29vdx55528+eabmwLMB8ioAd/Z189bs2WWKm3CEHpTEe4ey5JT/c+1cOB5Hjt7E9Rd8IOQK+sNrqw3kAT8q/u2cmgojeP5XFxrkI2qHB7O4vg+x9ca3DGcxhcyiSN3MfPjv6XPrtFeX0GRZQKhoEaTGMNjtE68TmJ8O61yGa9a7lhqKRLyqTX2UsEZTKENjXC67DF84Aju9SnapgmaQXRuisePDDAlp5gRSVQUtsVhwKlS+Ol/oXdyHCXXg2u1kZdn0ewW21M5NioeVU1F6+2nLx2jp77M4Mxl7jh4J6uJEbpjKm/95lWqh7eSSmXwaxUkxwJFRZMECV3FkEFogtF772X9+Fu0fZ8AaFoeUU0mdeReXm0r9KdVjs9X2WjZ9EQVxnJRmo5PqeVwbqXOnx8cJKmGEGQ5OV8mcD3cpXnwfe6c6MU9f5JCvUrqrVdIhgH+5J5bhIzQMilFu6nUFxG6Dq5zi2e21TJpl0po2Rz+bRaivNIGQQhqbz/u6hJOeQNtYgfWybdACEzHR8qlsD0fFuY59L2HOHmhjuN6tD2N+I27gQAO3Ag8tGUVevoR+YH3B8Sb4svvTErx+N6+fs6vNZjbaCNJsD2fYHt3FON3DJh+jw3Tp9LuTKrCMCSuy1RvFJhfXW9wbesY2Ye/jX/1LE5hnYZhIG07ytloP0OBxJb+AczLZ/AKKxiqQJvcjZwfoH38VfxSAfXyKe48+giTmsVCpIfrFYtLC0UulpoIWaHqwixxtg9k2dioYMohuqoQixpkT73E93ffwWU5y7TbRFNVtud0eguzmNeusHboPn5yqc73+6BPyLy0oTJfarFgtojUNbq23Y0o2eweH+DaUpG5qeskApOt3Sm2ZiO8fGUVEUtgug5zTY+MrhMXLvYNoUsIga5IHL+8yNbIANkHHyFZ38D59U9wbJNoRIV2FXNxDWN1ia477qL1ym+QrBZC00BRiY2MsisSwaeP8uo6gdTpZMvmkjw8FMF64bfEB4cwmz7RbDfTG+2bmQw7+zO8Pltipdqx+5stt5nb0DmyJcdEV4wXp4oslZqIegVlfQWn3eaakDA3cnzvvvtYevsEzef/nq899SekDOmLXUn9I0cIgXKjszBQVLzP+KB0010YO/ZifahiW6gaxtH7MaVOxbcfiSH39EE6SywUSLEYriSjRGJIno9x/hjf3Hkvz12rUm+0CVUdp1jAXF/jnxwcY8WJcLYk4WoGY10xJuQG/C//gW1/8W/Y2Zvkrek1NFXBkBUadpSt+Ty5qMrpK/PkApdvHhhitmTS153iqS378S6cZP3su51nhSQhdIPsfV/jTLHNtZrH6bkNkprM13f1MrckkFt18rkkkep6J6/jxsKKGnp8e08vPz1f4MJqnSAM0Qno1gWt2ev8/fJ1/vTIFsJ0En3vQdqv/RbCEDE8Tnv7HRiRNEoQog8N0Vr1icsK6X2HWPnFLDFNJmV0FncMRSKiCCLjE2wbH2DG26DcdsknDLb3JlBlmZ+eWWKyJ8FgJspy5X3bsG098c/d/fJhPrcF1pfAe4tzn8SnPXVzeshdY10cu75xiwiTMFTuG83+wbLFPg4Xicjhe/F+8/edjL0PoG0Zx8998jzgdgghbj7T3iMQEi03oNSyCIKQ6VGLgZjKD/f1cnEjQ1YJaL/5MqXTs9jpXoIwpPH6b3liz0HaqR5W7Djd43najsvM6XO4sWQn4yEIEbLMrv07eeHVU9wztBX55Dt4QIigYXukDQOv1SRx1wNcbwt2rZ7HW5nDXF5C7RskfehO2tNXiNz3GP7KAp7V5G4KjHz9Lt4suEhLdXb2RtnTl+D8QolKrUHgeVTbDsVehZPzTRKZDNu35vjFuWUCx6bPcfGB5brL6beu8rWd/Qx35fmfXrlKLJ3m7u39jHfHKTZsCg2boUynyv7aeo1UROXx7T0YeDeviRDxkcXzqKbQm4qgKhKaLBHVZAxV/ogF2Xv0Jg3Cz/AMCoSEku/H27h9sLaSyeJrm+2cfywEQcDWpMT39g9wfrVBsWmTNFT29SfpTyg8c7lINiLz2PYe3rhWotx2iGkyB4cyyJKg1LTZ05fg3q1dzJZaFOomw6tXaJ14jaVKnSVg5x17GR7qx4/E8Oo1dEXCP/Y833r4Bzx/ZYOmaXG1bHP3th2oy7OoikRUVeg1QkRhCTPXT7VnK6tXZhjLdtH0wXR9TizU+KtdvfT97f8Vr1YjkGW8C0XMqYskvv1P0A7dRd/4TtQL51gvVpHsFl1bD/E/XS1x944HUDZWaDTbrJ+aY2Koi+zsebzlBZSuXiKPfLPTbfExY42Pe+bIsow7N3PLQkzourSvnEdOZVk98AgvrPi4hn6zsK7Sdvi7c6scGsownIshS4Km6VK80bFWaFhsmD69t4nDcNM5jJ37O10ig8P4lRvuBpKE3NOHd2NeKfePsOCqHJ8uYbo++YRxM4ssvPGcUjbWaV38qADi1yq4Z08g3/Uw/hc5V2w3CZ3bd+kBBMV1pN6hzWLBTTbZZJNNvnJ8oQLMwsIC991332d677Zt2zh16tQXuTt/dARBQFYJeGpblpafIwxDYgqI4PNZZkiShBXKJCMCXRN8a08/L08XqFteJzixarJUNfnWnn6+uRuubTR543qJhuXxwEQXO3oSRDSFZ1YN7t+1G/HKL0DRaLkehCGR7j6i47vwfv0TolsnMBT5pueqmu3CfuNFhKoQyeVppvK8dXmJ2NYDNOZWyOS7kYwIV1ouhd+8Qt+WER586tv4505SeucKM2sbKLKEV62w/Y69+KV1jL4BwlYT1WrR024TT/dgTIxivfQMjWoNX9FgZQWe+hHvrHe+f73WpDuTw2o1blrN6FLAdwdl1o+9SXv+OuV8npG778JbXWZ2rUJXXwplx37eCVJUmy4D2TgvTG8gSxLZiIJCQFoTZAwNAh/L9UhLPgfzBhO5AWrlOnWtjmHVcc+/QaXSsReptGTGzp4iPjKOpb4/+ZTy/dQXOu8JZQUpEiOwOuGvQlFwQiCZIXRvzWy5+feaji/J6IfuxvvNzwjqVeTtu5F7+nALa2BEaKkRAjsgPjhES1J4aLKbl692vMATKQ1VEtwz1kVflFtWfD6rF/Amn0wYhiQkl3sHoxwZ6FRiq/gEwe+/ONa0b53kxVUZXZGwvYAQqFkeJ8oqvWP3sP/OCJc2LF6ZrxG2HB40bGq//hmSbaKEAYrk4y09izKxC+Po/SArlCaP8r+/PsNkLGRbv8yiq9D2Q9RYDKGo9MQ1egf7CNoHcZ/7BbokEYYybdtBjkXJKT573v01+9IZ2uUa1slpbMuk60/+Kc/XVaaLJZ6TYjwRC1gq1hGyQlAr02iZNNomfiAQiwW+d89OtPQATeFSzGf4v70yhe96gCAeMfC8EEsJObi9l7MnzxPTZHRVhiCg1baoNE1GvSbu9cv4dieYW4QBsiQwfAdZU6BSJHHfQzgXzyClMqhDWwgkBVsoeKHgwcM7iIxnkQvLZAqziFMnsHsG2PAU9FwKv6uPqUKnQyATVZmvmDfFF4CBlEF/JsYvLqxx99ZuXp7eIGfIJNsmtu3SdkOCwOPqwjrzvVFG7zjE1PO/pXd9msjE4O1yrjcBtCBAXpnHuXiawDSRs11Edx/EzuVv2nV9HK6Q0A7dQ2xgGOfSWULbQukdQJnchZXMEgYBkiQhSRIIiTASQwQBzXOniO69g/apYxCNYbs+qXd+y1PD22nsmCTs6iMyrJGcOUvmSplUYZnxUOBHEvgzRSotm+WWi/HLZ9j90Pdx/B4ur1RBEnhBQCKis783you/PUfb7nSadKVilOsb1PeOMzIxgVSvUC9XiQ1vIb73IMebOqmkwdTMGkgydcvlxHyFA/k0xeIyRweTcOYkcjJNYLxf7W46HrWWxUR3DBwLUSkhlWoIISjXPJaXY4zNXkK/71G85UXamTwntAEuXljDDwqoA8NEtZBHdvYRUyVOXvcZmdhJ7eKtopbeNUxi90FatodjOxwdThMSstGwWDQ73vhX1uvs6R+8KcBsycXoiynwe3QJflUJgoDBT+g6SBgqKe1Tun8Cn309OoPpAaaLnS7LoUyE4ZRORHw5NmtWLk/sGz/AvXIOb3UJoWpoO/YSDo1iy58/gCYIAnqTBgvlzjUQCsF6w6F8Q5TJxTTmN1q8MdXk23v72Jo1cM+8gzlzgVbdZn2lgK5I9CQM0mdeY2t3lgO5HI3n/j/U7nmKudAj9Gz0ri6a1RqTI3kQUF1e5nKY4+B991F+9ySh5xHY2YANnwABAABJREFUFhtVj+zO/VhHHiJz/EUa776GHE8QtFt4V8/TnLpI/InvUHr5N6Sf+DZy3wjL568S76uyZ3AQM4CVqslPTy8S0xWilkWgR9iai+G3W2zbt4tyqHKx4rHUcEhHdOgbol5tUC92rEsvb5gkc1mQZGouHJstI8KA/UNp9vd3kY1q6DJsy0XIGhIq3i3jN134jHXFOLNcww0Ekz0JnCDg+HyVhu0x2RNnOB3hgYkefnNp9SPnZDgbpcu4NUD84/B9H31iF+LqRULvw79bgbb3MNaNbJ1N/jgIg4BuDR4ZS+CHSWQBge/h+QG1tkvdbuMhc2QkQ0SVsb2Ai2t1rm002d2bQBYCz/e5tFzmfqNF9dXnadkuAdA9NEC8vkH72ddZTQ7Qc+QoqcP3wsk3UV77GT84/BDl7CgVN2TL4Aj+SZfp68v0JHREpQJ6hObIDs40BOVaE6nRIhmPkNVUlKbP+UsVetI9iMV55N5BAt9HSWUJZqewFq7hLC2QPngn6XsfohHPojsB0XiMd89OsXJ9lWQ8wpFDOzjoF1AvXkZKZwnaTYJI9HeeI4mP6f4K4klOTK8RRLs+8luzvZD5qkXDdFmqmgykI+wZzDJbrNO0PcqmS39U/Yj44AoJ7cCdGOvLSNUS3sJ1kGWkZBZf1zu/Qz1CaXgnPz3zfidjueUwXWjw9d19DEUFsizjTV/82O/kzM4Q2X8nvv7JnXS/D0JR+STLSxGJbM5bN9lkk002+UryhQownud95kwXRVFw3X98E+s/CIFHTNAZa3zOYg5fUri0YXNhtUQ+FaXhBER0haf3DWC6PsdnS5SaNlu7Yqw3LC6vNYioEveNd9G0XNquTzqi4gUBLy40eXD/wY5+MTeD4bkoA1uo+4Lrr51gMtuLZJmE1vsVq0KSkKMxgloZvzFNMDRJNNSYEzkmnnwaaeYCF6aXiEUjZHZM4B66h+Uz5ym8/hZj2WhnsB6EuH7A0qUrjB26C2XqPPbZtxGqhkhlUQ/dw+UXXsIqVzqWMBGNcttFtC1KfozBZBztxoHTRydxop38Er1RxXvp79FLdZqmTW11FS0SJb9zN10HclyyVS6uNzG0kDuyCgnZp08LMT/UfRLeKCesmS69ukQY+KQ1BXn6FOW3jvNhAwZfVak5ISnbwtViFNoBxaZNQu0iPZwguVDpVE5rGpKiQOAjd+UpSFGM/UdwX/rFbc+1tm0XrqbjZHuIPfl93IunsZYXidz7MBEhY88v4PoSqa07WYx2c26xQV8uybd39xHVFfoTKhlDJi77BJ81XOgDSJKEGcpUrYAgDEnp7/1fmxVIHyYIAhQCCD/3T/pj6YrrDKUNmk5Ape0gE7AlG6XQdKibLpoikYvrHBzJcWmtzlzdpjdpsC0hsXH8RfKpFH7RhDAkFAIhK/jzMxiTu/AzXTx/4hKBEuO0KXF64RpH7j7A9wZ6sIPOZ/dGFQzP5JdejoPf+2eoK/PI7Rp9A71YgxPMBAZWfBSnUiI75NEzuQu1u5c35TxvL1lEEwlWXKgKA9xG5/NdD9sLcW/kysgCSuUq6XdeY2ajTfzP/xV7BnOcWSqDH2A6HpGIwb6RHKok8NI9AIShi1QvE3oeUhgiggBvZQEQKD15tHQWyfMIahXsuRmca1eJ3v0QUjyJXy7hFdaoj+7njavXWA4jzJVaPDgYZdxusby4hq6l0DUFsj2EB+/HyKSQNjrVhd3JKC9cfd9iIp80MDSVn19YQyak1nax/YDl9RqtiE5cNcBykIQgIKRs+2inL7D10UfQps8juc7vnKfwjxklDOHscVofsKXwGzWcxVliDzyBPbz1U+9FjpCgbwRlYBQpDPCEhBMEneeF78LUFZxSAREGBEvzyOkckutgJbsI77gff+o8oWpQl6LkPJO0ZHPhF/87ZDIM3n8Pqm3SHNzKiqexUqqjDx/CaFXxTr1Fa2GO2soaDUvnB4eGEYQoYUB/Js4vXz5N03RACBzXZ3WjTlQRvHp2ltxALw9840+J1+sUQp2/ubTKxGCEStUin4ygyRLVus/sRpNv7u7lbn2I3pl3CH0PY/9RLEW7uQDacgP8IEAPPPylWcL3bE5vjOMqlod97QrKxE6MH/2PnJ6tcundKURPP3qmiyAWp2G7/ObSKoeGc5wvO9hb7mBieALmroLnIoa2spgbIGYkqdddKm3nli4HQ4axXJRyu2MP1pMw2NOfZCyjo4QukiTR8GVqVif0PGNI6B9aZP5jJGcItvcmufKhjDBJwL1bc+ji05/JIvTpUiE/FPsHsVkLgoB2Io189EFU3yWUZGzE73xugiBgoivGu4tVXD/A9LgpvgAcGcmyUm1jewFvXi/zwLY81akpqm2HTEQln9CRBDhegCKBVVgjku/HiMdJLV/k2w8+wKynY0oa/VGJbHGB43PLmGqUa3KGairH/sdGkGevIJttGBylNDJM1LTI92SR73oQ0zTRM1lEcQ2vXse+PkXXX/4rrHqd1YuXaCwsoykSjSM58gmDN6YKBGGIJkvge/SloxzoT6AJm1+cXSWi68jJEFUSGPi0Q5WqmkAkQLgutlBwEaBqCNfCsmUSEZVC3abaMOmK6/xwbw/4LoT+R5YnwzBkvCfJi9NlUhGFK8UmZ5ZqRFSJqCphuT7PXljhvokevrG7jzevlXAAQ5XZ2ZvkwEAc+XOIoGYyQ+yRb2IefxW/WgJAisYwDt2N0zv0R/+7/e+VwPdvmZKqUse6uG65QMiFlRqWFxDVZASC7fkk23vibO+Ns1xu0RdX0a+cQ7wXKA8Mj/RT/9VPyPX24NSqTL30ClsOHyJ19AGUhVlEu86QUWA8HiOI9PPaxNdI55axK8v0TE7gZHo4tRby7vW1ztwpDGi1bXJdPdi1KguBTrNriMhwFS8ap2GkcSyb2PIayfseJjx/muZzP4OXf03q699jo2eSxbU2T2ZdWkaO0Grhn32dVavBWH4QYlHcIED7HbsqPc8junUbwcr8R7ZZ8QyVEgSKeutxR7DetCk0HYYyBsWmTbFpc2mtzvf3D+D5PqGQOb1ukzQU+hIaUfH+89GR5I4999AY8f5hrNPHcW7khqoDI4T77+Lncx8dJ3lByOszG/xgbx6ZkNC6fSEgQOi5iPCLnfd5yTRqvhd3/aMiMbJyq2vDJptssskmm3yF+EIFmGw2y8LCwmd678LCAtls9ovcnf8uCCUF2xfIEkTkkLNrFu/Ml5nsTfPLC6u0bljyRHWVrrjGDw4MYlk2EV0hoWtEFYm2F9B2PLb3JtEkif96aoH9QxkalkcrEEy99S7RdBpJ1nDPTxOYLSKaQoGQ7kQaPhDaLqezeIqCX1xH7h+iO6rxmGtRvfQmjG9n5cjX0XaZmELhxYLPTlNmcm4KRRL8/9n7rxhJsjS/F/wd065laC0yI7WsytJadleLqWkxHM6QM7ho7hLkBQZDENiLBZ9ILgiCmIcLLPbyAkvucrhUw5lpOa2qu7TIqszKSq0zQ2t3D9fmJs8+eKSIyszq0l3dHb+nTDcPc7Nj59g55xP/r9zyyScjLNfaC73a9DRFU2P0qWdRcx3o3b00Z6Y4f+w4TrVOiIRQogQBkXSKaU9BqpDLpugQFUIhMPbfQ3M9ktm/cBpp1+mMqXT2D2OkUrjH38F79xf4+UEGhrYxsu8exPI8tZfeROy/n2B6gXQ8hmn145vWhuCbmKFxbTsSolAVxoZnY6VS9G4ZRamuIewGZU/hByeXWG7eCGfXFJjYtZPZs+ew7RZj3RlymQS2GaduRFH6Ylg79tI6e2LDufW+IcT4jusGxmYqi/rg05hui0BRCawoJzsqLFUdCvUWfqv9m2XbZ6FY5et7eumLhED4sRTGhKIwWZO8fGmRhtM+t6kp3D2cZXeHhfgExeU3+WA0wCguo144w4G5ZYJMJ97INg43TCotn96EzoH+FA+M5gh7TXQhuVxoR51aCmw1HJy1El4ig2E3EPUKQgYouk5YqxC2mjSSeZbmTqDGk2iqTpDK8fLVNZZaJQCemOhky/Ycim6gpdMc8wO2j+1la97i2HSRWlXlRxcWiZo6WSPfzu7LjHCgP8/UdIlay6dUrZOMmBCNIdQS9QAC1cLxqu2i47ItSRPTFYIgINPTzSuzFRTd5JsHhig1XISQDOfiNB2PVy/OMV9s1z8ydI2uVDdDSpNM2CIwLRQrSnRiJ/7lczQOvwK+j4LE2LIDdWQL/uoSzsUzCFUj8fwfc3i5hoXGQKtIbbnKy1MhF3s62Pvo76HqkMulONFQ6e9I0mFKdnQnWK7aqIrACUIkgqYXMJqP89LFVdwgbBeIVQTC85CBz0rZJZ7JQa3aLueBIKaCu7pEy3yQSMRCqiq3aMhsglErUz99/NYDYYh95DWs7r62s+FD4F97Ca4bEXQZELz1Eu7kJVAUYrsPYq8V8FcWqWT7KRw/Se+2CfQ/+qfMuBplX/CiHyHiOzz097eTmL/EzM9/Smr3AX50sUQpUBEd3RQuzqAqgi899CUi59/F9QMuLawxNbPEHx4cYJuoYKX7sRLx69dmqoK4CMBt0efrHErlGVBbXI4n8G3Jo3uGODlf5mqh3fcjhspIVwpV+oyYPp0nXkJYFpGHnsIbHNtgpLA0pV1hyHVvOF9uImFoSN8lXF6ksmUfx2oV5PAWALyb+qTjhyxUW0QNlYsVj8siSmboXhQhKDddjKLP+KDE1G7jSJRgCEl3XGOiM8ojQ7H1rF+PUNE4vtzi6HSp/U6gXcvqsa0dDMWV32hnvxL6PDycojdpcWK+QssLyCVMDvan6YlyvYj6h+HXLbMWhCGBUNfXR5/sXZXWfJ7b1c1LFwssFdvBPaamcO9wFsLgekFwCZycrzBsmRi+g+/a+KqG0DRCISg3Yaw7TWJsnMraKuf79/DyK2fw6jV83UAb3kpHLs3+uyZ4qXGBaVenNVPnZ57Prp59VPQW1RWP//tElPTr36N88l1Mu05oRYnddT91NFr1S8j5BbSFZapGHHVkO41LM3gLK4zFNM4s1/iH945Qa3nYLYd+I47rSTTH5nylSbHWosswuKsrjjM3g1eo4mWztIiCbhIiMEyDMJQErRZBKAllSGe2E0ORICFqqqhIbu4BqqKgt5ogJSU9wc/OLvDYljyqpvL/fmMSVbRlyAbSFvr6GvadyQJ//2A/397bhR6N02o0iCj+B2frKiplV7DScBEIOuM6KV1id/ZifPmbqPUKMgyR8SSuGfmNHq+bbEQGPvv708yWmmiEjOSirNQ9ZteaeKHkkS15LhXqDGVMelMWa6UKslzC1BTcQMFVBLpdBwVMz8aQArsVcPXFF0kODbH9ia8gZi5RO3uMohSUD79DrneMypb91HuGea8VcnekyVx1FolAKgIpFTANWokMdrlKh6FiNxo01DjzBZeICpSrNITB6brJ0D/432hOX0WVku5kF6fmK9TmlhBJB+/NVxBIhO/SCgJqVpaUlO0sUvPjy+gFHd2YoxO31DPRhSTa3cP7FBixA0m95dGXieLcJBEoACeQvDNdJqop7QAv2vP/V3Z202mGG+Z6z/fxUjn0x58j1myAEASxOO8sOdTd4m2vda3pUnUluhFgDo7izt/qOALQsh2fafYLgIsget/jBC98n7BxU5ijohJ78AmceGozs26TTTbZZJMvJJ+pA2b37t28+uqrPP/886RStxaou0alUuHVV1/l3nvv/Swv57cbRWG+Ae9MFyk1HCxd5b6xDo7MVBjMxnnp0up15wtA0/EQcYMjU0X+6OAAGTMk9FzGMgmKLSg7AT8+s0Sl5bNQdXjAULlrIM3hssLIwADFySkE7Sg9VVHQdQNHkXgdvYQXTqHlOjG7e1DsJpFDD6GPbEHJ5Kj//PtoHYOsLNWIRlK8tqSwpkago4eaEzBXbrFDVfECSc3xSVgWUUNDlQFCEcTcBkG9SvX4EWJ3P4B38QwpEaFBu0BvKNvOgORd93GkAs/vSrM3cEgn0riZDprrBjgt8PBmJwEQhkkklaTx8++hqSq+75P0bSqTl+hLWpROvIfbCogvz9DXkaNea+DNTqIPjeGvny9uauSjKtccMIEM8buH2sUOwxAzkWBodJDaz7+PdB2iuw7w8vGrLC+X0fqG8dd1sP0QThUdnrjvIMm5Czgnj9I6XiabijNy6G5UfzvBgfuJj06008eDALV/mDDXSet9qexBGLbl2ABch21dcc4tVfHfZ7wd64jTFVWuGxs/DgVH4adn5wneZ4R7/XKBhNnNaOLjR8H+NtCWAVQIpMBUQJWfTsS2CmgXT1F/+zVAkpMKs2cXcc+e4uEnv8Iv9BTpqMEzE1l6UxEWm2UCKdnbm+DySu3685JIVlqSXEc/3V2dKOUieC5KNo8IAuxSCdW0kIFP1tKx+jqYDCJ06gERXaU7aaJLDykl3+zXmXn9MNXLF2lENXJ3PcEbUzZS6NTckJVmyGK1hb5oM1/z8cOAR7Z28OIZFyHArjdJZzOcvlqgJ55qO3T9dt9MJ6KwuogvofPeBzh9yUXgcWqh0jYOC8nMms1Xdnbzi5tqR3hBwHLV5luPbCGhVLClIL73Lhp/+5/xpq9e/16IwD1/ikgqg8jmiTz0JFr/EF6jQcFK4V++gHBaJOIpAk2jXlrjrXIZs2+Av7+tk6fNJUTlKtgmuzNdXMpE2pvlVIRTSzU8P0RTFELatbiCwKPcsOlNWcw2G4RBgCvbEg8yCEgnY8TWlpDxJCt2SNeuA7R+d4fRHRFCECzPcydjb1ivIaoVyHZ8rPPr5SL1yUvrJwtpXjyLdd9jSCtGsLBCd1cP84ke/sMFl5mqja5pRI2A4WyUiXPncc8fITYwzKs1g0KpilQU8ANi+S4qSyv8+MQcf/zk00xONglqVRRVUHd8Vs4cIX/kVR598tssX51E+D4RRWKGkif3DaJdOknX66dxluYZG9/G8FO/z//jZBNv3QBvaAr35HUm1AYZPIaw0L72B3hGFNc0bzGApg3oTUdYXm6+vwmIRkw6/Gq7BpgicIMQ2729oV8A1ZZPxNBougGhhGL9hl57T8rCUCAXUYmbGnXnVmdPytLJmUDgIWk/4ytljzevFjZ8r+74/OTMEt/a30dG+8026GrSY3tWZWuuEz+UmGrbsEkI3Kbu228yqqrSDBRCCRFNwm0cftDO2OiLwB/s7+HsqsNKrYWuCpbKDWaqN6yT6YjB/NwyQ519SPtNUFXw3HZppHgCNwjRRrZQ6Rmh/lgPL794nMCKoCbT+FJQvHKF0qRCLHE/6VyaKwt1dEI0VWG17tC0Xb4ykafn2C+Q01dQQoliWoSNGuUXf0LysS/R1Az8yhqGrjNvZGg4KolMBisWoSYV0jGDw5NF1upNJnJRZhaW2dsRIZpJ8eK5CigK93ebDFTneLNRRwCBbROJx6jVKggrwlhKx1iv56MqgqSpEXEbBFrbSbu3N0Ww3pZCCCKNKt7Jo9gzVxFIWskeHh7fyxtFQT4ZpSvZLhbR8nyKDZe+hA5S4vgh5ZZPb0TSs752CD/A8R8oGu8uNDg2s3Y9PkARcPdQlv09ERxVg1Tuxh9sOl9+6+iLCR4e7+CtySLVVsBao0U2qvPQWA7f81BCnwsrdfYNZOnpSGEmk+ilIklLo+aBpqlElQBvZZHc8A6qlXYdzFRPN/Ld17Evn6NaaxGzdFKRBAnfJmFXKO57lP9xfI7pnhT33r2bF969jPQ9pBmhrlosVHxG0jl2dYToi2tcrLTwpSDwfaKagb7vEC+thoRLs9ydULly/gqibDI21k80FqUWi2HqCn6rBaoGikLNl2TDAHP/PTi6iSrae5yP6lR0FY30o8/gdfbinj+FdB30wRHUsR3sbBq8culG9rQQYj3DCO4ayPDzc0vXj+3sSfGTs0t0xi00EV5fCtluwE/OLvMH+3owb1Nn0pPgRWIAKBLCX7EvCZFIKREDIyin3iWsb8zYRCiYB++jpaifuQPETmaIfOXbyMU5gtUllFgCdWCYViL9K+9jk0022WSTTX5dfKYOmK9//eu89tpr/Mt/+S/5x//4H7Nly5ZbvnPp0iX+/b//93iex9e+9rXP8nJ+a1EUhUuVkJ+fXbpufnL8kKmSzeVig7HOBCu1W4vV2V6AAlxYrdNyXEbzMbqjITlT8PKlEjNlm22dcSa6EixVWvRlotRbHuLQI0TW1miW2xtGTdVQDY30A4/S0iwifYMojRrNF34I9SpSURHDW9F1k9aOQ0xfvMpALo7UQnJxi+JcgUhXD8WmS9n2eHZ8O5G5eTS1XTheUxQM6dHTlSE6vpUpI0vZzOO9c5yxh5+ic/4qzakFyjWbaDaDfs+j/F3YxbbuOJmYSSQ9Sk1/Xx0ToSCUdvSt0d1H69ibGxaLZq3E1vv20Tz2JlYgUYUFM1f4vYdH+OkkrFUahNUK5DqIGRpf3tG1QWddlSH1VI70/Y+y9sZL9IyPUX/pR0jXQdENWrsOMXmhiAwl/tIcyuAoIesFEAmhWSNz/m0830ZPGpiqi3v0NSguIR54gmamAyXXhRAC90NGu+aNkG/u6+X0Up3ZtSaGpnBotJNuK0D7BDVIVFXlzGxtg/PlZo7OrDG0qwNF/m5mwXiKzpnlJqcWqu06QVGDuwczDCVVxMeQersZo1GhcfQNru22DBEykovg+BLOvsUfffUP0aIR1Pe1fYcpeW5XD69dLjCPzkC+k2CtSCxqomgWiqriXTmPbNlYdz9IrLrKlu1jGNkcM42QUqgxnIsRhJJjs2tkowYeKnG7jP2zv6Gj0SARU3GEykyxQXVylY6BESZbKjXHx9JUXD/kxHyF53Z18cNT8zy5tZPQdbi8UuHA1kGuFOssVRy6+4cJFhdIGgrPjKVonDxK3xNf4qjRRWe8zGKlhZSSSqsts/bweAdV2+MbD2zj9Mwq9bpNTyrCWC7KSsPD3TqIDNrSLGGlfGujJlJ4q0tY44/RaDZpXTiLlu8kn1GZspvrmSkSobTHawBECFHPvcfqO68S0QQKIUoswbce+zKn1RzZRIRLhQa5qEHc1HD9AGSILiRXlso8Mt6J6wXMzq+03wISkokYz27J0HzxR8Qf+xKubiI7O3+nHZmfjI/XboqiECzObTyT72FfOkfx0W9wpWMPi42Avz0+j9tOwiT0PISAe7IC/8X3aAYBsmuY6XMFRDRG2LLbNWYIUVQFGYkyTZSy264bpAhBR0yjNj9PNqGTnzrFI4/czeuHT1FfK/GlgwOEv/wBiZiO7jWoV9ZoHj1M1HH49v3P87OCRi6m80w2RHvjZ3hrRSJJC/u0gprOYT32ZRxdv+VeRejzxNY8P3U9Vhb063UbopbBU1vzxM68RigUlI4eNEVcrzF1a1NLRnNRLi1Xbv0N4OBAGkIfSwie3dHFj04vbSj4HTVUntneicENCSUPlaPTt4/M9UPJ+ZU6Dw7Efu3ZH58UKSWK9DCAD1Hn/DeSJjrvzdS4uFLDDyRdSZN7hrJ0R+T1Is83I6VECxyylsLrl8q3Pee2SEi1vsapaJydDz7O8tuHEYChCjTXIdXfz9qWA7wzWUZDMB1EEJEoUU2guTa+0s4sPHvqEs8+dhfnC5dpOh4JTaE7qtETcXnYqtJ85eeYqSRKo4JIJlEiUUSziX3sMMndd+FVytT7t/DK2zPETI2v7tiO1dnNv3x7DkNVeHpbF5pMoxFwoF/QvXKFNcUklY7jqg7d9RVqZ0/w1UOP8stzi1TrdTK5Dpp12NEZoUOHVqXMzr4Ml5YrdERUwtIqSizB/oE0fXEV1jOOrWad5k/+hrDZzoYLUFg9f57g8hUe+NI3OBtGqNo3h9j7hFLnWl6aIu5cY+FmhBDMVH2OTq9t+DyU8PZUic5EDwPRX3maTX7DEWHA7g6doewAJxbr2F4aQxUsrjVIRg1yiShvTK7x1tQaWzriPHfgEMHSHLWWR9pQSKWT2IGHDAISIqAnaVKwVYZG+ln79/8dGUsS01Vcx8VrrGLWypitFr377yEVNVmzPeYXVsgP9HNktkKz3iJUAzqTBnsmBsktncILJL6EQEqkH5Lfup0r6WHmpto1T8yhfhBX8H2fn51b5vldPbx1/AxPPPtNzLdfonb1EkIItGwac8sO3HwfF8sBM2s2UUNlSz5GzpTwEdb2aixBq38EdXAMRUo8wAlDtkZ0FipxLq3cyPAQEu4fyeG4LkOZCE0vpOUH9GeiHJ0t05fkliFbd3wKdkDfr0hK+VW1yFIRnZShgAxoWVGiz/we7rG3cNeDAbVMHvOu+3G7+j+XdaqUEtuIIIa3ooxuI5ASJww/adLlJptssskmm3ymfKYOmK6uLv78z/+c//1//9/5F//iX9DV1cXg4CCWZdFqtZidnWVpaQnTNPmzP/szuru7P8vL+a2lJVXevLp6y5pDFVBrtWsovB+JwPFDinWH5ZrDQqnGqYUKox0xHhzNU2o6DGciqIrC355YwPVD8jGD53b18H+ecfl7T32TfHGeWGWFSCpJ0DvMlJVmZCCKXlum9t3/gjBMZCLNmh5HKVXgzPeJf/UPKJ+ZpF62ybSmOPjEXmbWmqyU6+iKSiBDLkS6Ge7pptuv4QftCMROw0RDMtm9nVdPzfPUV/8A78irXHztDeLjE4x/9RBOJM6yleNwXWNcFSxXbEotn+9erPL1nZ3oN0X/+IqKvnUn/tuvoloWrdUVRCQKsQRq4CPMCGbEwi+vYEbjbOnOoyLh5Gt8c2wnhZEBqopJfKSXjoiKJTZmNLQXslFeTY+x7WvdxMoz1KwIWjaPa0QJdfN6NKH0XBTfI1zPVlECj/JiiR2WTuDZwI0FpTt5ifjO/XiZjo8caRWGISk15KGBKP5AHFUIerqyLC4ufqL1qkTc1sF3jart4QSCyG9XAO+HIlA0XrqyxuWbNlCrNYcfn1ni0a0d7MrdWijzoyBXl+F9BkdFhm1phVaVeLNE0+q8JXpahiEDUcG39nRR9yCXfhb3lz9E+A4BIAwDTAvr4P0ECLRIlPjgEP/18FWcQCJMC3vRJhvV+ea+PiZXa7iexaGVS4SNGioQUwErSiOQtFou6WoJX8ng+QHJqEkDH8dvy3C5gaQ7FSGtWczXXYr1Fvv70oR97Uj79I4BOqRDpVhk/sCzeJ09fO/NKbb3JHl4vIPFctuh2J+JIiScWKxiCUl/RxKzI4kThJwpO6SiCveEAgXwK2Xo6EZPpttRfGGIiCcgEkU6DkG5RFhZNygFAROWxzFFQSoqrDtvvRA83WRHNMA7+gbTpQYRTWUgE0Fv1HB+8QP2fv3vMx9P8b/cO8RrlwtUWy5JS0cEPjnLoFis8K70ebA/hRyeICUdol0hWa+K/94bxO57mLOxPu4b7ael/JZaZD8hUkrUzl7uVJRViSWQyfTHPje3KZTrb9lNRU/wxsUSPbkEzZvmWU1t9w/VblCv1Ag18D1JsemQjiZQNQMZtOeMyPA4RTdksh5StX3iUZP+lEW+ukIt9AkVk6mzF+l+ZgdffeoQutei79xbeNk4WrNGdXkFVVHRAG9umuHSJPcM34XaqBF94wd41RL9KYuUpSClxF8r0HrlJ5jPfgNHubUwelx4PL+3l2JvlMLMDDFN0Kf6WCuXkLEE5vY9uIk0MSVgZ0+KY7Nrt5xDUwTbOyL0JnReu1ykvG7kjZsaD4zl6YmK9rQmJV1myN870MtCtR2AkYnq9L5Ptx7ADQW11p0DBZaqDoj4HY9v8sWghc4PTi9Tatww/M+t2SxWFvj6nl66P0DNpzumMpiNMbfWIJTtuiQdcQtdFfR4a+zZNsj/881ZptP93P/sN0k1SgjpI9OdmMPDvLLiEolYnJ5eYbHUnpNVRWCZGj3dvTQX5qgVCuheiye2dqIK6ImpDIR10nPTpI6coyl9XLuFkcrg16u0rAQiliQIAiKDI5TTffz/3plBCQNsRxL2buEvF0NKTQdLU3jhwgpPjGW4cuEKW7dk8EurdIxP8IiV4GrFIXrmFwStBtbxV/na1t3UrU4syyC5b5yrkwscn6lQKxS57+4d/N6+nZQWl1GwGNzeT1oPr8u9KopCePX8decLtJcBihC4joM49x599z6LpojrWdGKEFzzuSQsnYyl8GGq1ElF49js6h2PH5stM7gjd1tZw4+DEAJNCJAhoaL+xjtdf5uQYYhOyIXFtevO+a6kRckOeGuy7UCP6CqNlsvZZI79T32Z7mOvI1wHdXWB+P2P4p47RaNeA9tl670PwPw0ZixKoApqfoihKagCnEaDWNrBaVT50u4BXn7zFO9O19i2awvf3t/PSs1BqCrbuxO8N1dlYvsBIr39pM+cxfcDlL5hpiJpfvDuDal0L5BIKTBCj0g0y0xLEO/p4ZeXVxns283w7kMIINubp+i6/M0Lx7HzfdfVEN6bWeP+sTx7O82P5IQB8N/Xj3Xp8fhYmr19KebKNqpQyCUjzBTqlJouSVNBJSRhqChIYoaCvi5F+H5afgD86k1Y/g61yNJRnScmuohogsBvZ/s0owm0h54hZtchlARWhJaqfe5BQlLKzXfAJptssskmvzF8pg4YgAMHDvDv/t2/4/vf/z7Hjh3jyJEj149lMhmeeOIJvv71r9PV1fVZX8pvLTU3vK1hot5yGcxEkcgNmyxoR4yqQhCEkoSltY8JwfkVm/GuAE3T6U1Y/I9jc5ha23BTsl0uLtfY0Zvi7+abDGWH6OoYw/UC/HrI86NptKCJc/EMar4LoWo0hMbC9DL9SQshQ1rnT5Pq6aI8O0dVUchdPMkTBx7ir6ZcHMdDUwQvLnn8r08/j1W4Su3MKTwZEt+3i2q+j6uFgPjQCP9joUX39qfY/3AEy62xKGHZyPC3Fyr4oaQ7aXGwP83ZhTW8IGSp4W+IwAvDEDGyBe3KBYRp4fSNsmb72PUWhqqRixiYnotiRRGqimBdPzcI0S6eoBvB0JbtyMQYvn/7IrdxxefBrR2cXYoQW1umnuzC1BRyMYMgaBGJRfA0C+m5yNIqajQOkRj4Hl1phdC2b/u8g5VFRPbjR8KHYYhC+KlJmggkqajOSu32RRmjhoauforV5n+DKLXkBufLzbw9VWI004v1MRtGCHFH2ZZryA/YAEop0fBIaxB2dZN47vfxzp3EX1lEMc22o89u0JqZpHjwSd579wxDnV2stiQtL8DEI63pLFeaaEKyXKrTmLyyYYun+i7dCQsJ+I06qUyGtWaI7XgIIehNW0R1lfuG82RjJueXqxTqDrFIBENTefHiMk03wNA0ZstNpARNafB/7Q95ZnsXV1aqTF6cwnBq5HMpDgwP88JMA8cPcQGn4qKJkGgkSohL3NJQ2wF8CMsiFILQakdCww35BcW00Dq64OrF9v9dh66ZMzy9d5BXZ2rUfYkfQs3xeWBnLyNTb+PW29kLth+wWHMYTJntTIeVBYKuGKdmi+zsipGNW4zn4/zt4YuUilWQ7TF54cQZHnnkbobNkKoNTS2F/cQ3qcWz7MjFiOvhJ1EJ/K3HTWWxdu6ldeb4xgNCIXLoQRzD+liyN1JK1J4BbnbuCMNkyuqiuFrCR6XU9OhOWSxVW0hAU1VsL8BGJ6WrxAyBHjgYmsqq7ZOxDFTdQMSTzPoaTQn5uEV3VIWWw10JjdZ7R8kMDVIa28OpxTprl0r4msFzPSoLp05SWlxhS2eC0PfxhSBq6khFpXThIocO3k9cD6gKGy0XxQgcZM0GKRFWhKC4ilUuQrbztveshi7d+RhDeieFYo3TFZ/LYoTEUJ4do930qwoi8DjQF6fmeFxeqV+3+Vi6ypMTnaS1gFQMvrW3i4oTIoGUoWApAeFN7yUpJVE8tqQURNpCSnnbwvG6IokY2h2dMJmo/iHMS5v8OhFCMFN2NjhfrhGEkrcmS/zejtxta8ZpAqLVFX7fKFLJSMq5fs7WBWeXa6QsnaNE6MxEeGhLBysNn6uxBHN+Bj8I2ZtJs8uKMpjW+KtTS+zL3agF5YcSx/EpGzrpRBwt9NFlwELFZl9/inxYx3rhrzCVECImIghwymWUfB4zkcRoOTRcHy2ZoT68gx8vCWQHOF5AT3eWN5wIx1bWA6SEoCdpEgKys4dqPo/YNkId2JbRmW+uIQ2rHcldq9F6+3WQkM9FiZSW2NczyK5HvkpDH2exWOPIu2fIxS12bx8hY8gNwRiqDPGmLm9sfxmSjRksVGzsuRnURpXHt3bywvllJJCNGgjZ3i88Mp7HEsGHUhHyQmjeQY4QoOEG+GFbMvWTYgYeYm4K79wpZOChDYxgjm/HjiU3s0O/IOgqmIZB0XHwAsmOeITvHpsG10NVFe7b2k/M1Di6VOesnuepL/1DBsMa1toSdstFG5rAOfwGilLFzHWCXaVlt9BMia5ZtLyQhA6moaB7TXIxleqlo+zsynKiWef86Ussl+pE83nun+ih3nIxA4efvT3NrvE+XlRGCKI6hcWAsXSAt74u0FUFTfqgaqixBJ3JCFU3pC+bpTQ7x+VmyKWSzbbBPCPVAr9chmqtiWpVIZOHdd/Hm1cKDKT7yX4KFhY19Ok0oLvbwkbj/KrNkbkKDTdgojPOcC7BhaUyEV2hJ2Eh7jAGkqYGfLCTQhUQrRZ5IhkwoEU4WXDwVZ2JnjR11+e1K0UMVbCnN0l/QkOTPr6U+Fbsxkk2x+Amm/xGEZceXx6wPtR3o9InFLep3bjJJpt8JD5zBwxAZ2cn/+gf/SMAbNvGtm0ikQiRyCcv0vZP/+k/ZXX11sirp59+mu985zu4rstf/uVf8uabb+J5Hnv37uU73/kO6XT6E//2FwVxB0P6/FqT+0eyzJRb7B9Ic+SaPICAfNyg4Xhs6YzTsF2kEJTsgJVai5+eWeSu4SxHZsr4ocRQBFGjLRn03lyZr+7uYWtHDNcPCDyfLT1JtuajdLllgrPHcS+cIazXUEyLUrwLoWk4UhDRDGS1jNXdQXZwgN6hfqKGynAiJHWoj2OrbQO+qSr8cKaKovSy955hclEde7iT80t1fjZ7lUKpCkjOGgavzkU4NJIjGdEYjSV4Ymt7Y73WaHFqrnhdi3qubDMUj27INmjpFpGnv85CI6R25jKV6eMIVcMWgkrTwbcm6ZjYib+6jH/LolKijW/H9u9sAJdSkhAe9/dH0fV+auctNCGRMkRbnWH/tkO8+co7yCBASaSQlTJCVcmOjtLjV6/Lv9zyvLVbpWN+nQRBwJ6eJJeXa7fNpNnXn0KXwe9cVrgQoh2VfQdsN6DiBFgfs36nlBIl38Wdov6FaUE8/aHP1UxmUe97HCvwUT0HpVah9cIPUBMpLlc8QBKrr2E0m7iRBH4QEMwtcHVF5x9+7X7cSoVIdy9qLovvurgLs8iWw4DSIplob9BkOwQXL5RYhsqe3hSThQYDmSjfPblAuekgJQQS5sstHhzL8fZkET8IGMnFKDZcdvQkubhS4+GBBPc6NeqqTVzTyJfOUfybl9ly97OcaASUnBBVEfSkIliRdvvs70vfiMLNdiKsCLJl32K4UbJ5xPgOkp19+O++jnv1MtbYBBPHXie7/T7mRQypaqi+yxAl7JNHKGV6r7Um9ZaHmzAxBITVCrlBhYSlM1moM1mok42ZPLezm4uLZcqtgF05g31D/UT9Cv/1TIWKGsNWI4imJG6UWbM9OsYz1wskb3IrPmDsv5dYRw/OmfeQrSZqJo+x6wBOvvuWTDNFUdACH6ko+HxwjSo3mSay727s4++0P+js5cRSjVDW2L5lOy+cX+W+kRzfPTmPkG1DhiIEJ5oGz49vwZq/QuP4EfbvepCK7bMzayAcmyCXIE+KqYpH2lToFzY7BiKoF44ja2sUdj3Dj45OouomDTXLbL1Fzld5PJkkXi5TbfnEVRUch0BT0VIpFF3F0hVUp4EpQpS1Al5h5YZhRAjUbA7RurXOy4b2FApnyfHd2RZNV8ENNJqTNf5uqs7Xdvfw2HAcI/R4cizNwYE0a7aHqarkoipR4V9vbx2P/HV7d3BHH1jb8XLnZ2CKkL19KV6/UrjlmAB2difwP2A+3uTXj6qqXF6t3vH4ctWmGQhi71vSGmEAxw9TP3sSZIg6sY93pmoshhZ6Jku9GXC44rN4apE/fWAcZ9nm3ek1euIa96ck1vIVKvUo3b29REVIMmKQjBhUbbfd7xCs1WzymRSPDyYwTIN7B1Okozp7Ykk8E7yVFczRewhOKzhCw65WaSkK0aFRqi0QIxO8OAdrgWDNSDDbaLK/I8vfHJ9D0O6jrh+wuzfFbKGClBCzdFwpQVGZLzvk4wbR7bspnTtLEIT0pCIoop1h3BFJEtc0Vhot/tsbp9AExE2V1XqcC6LEoTGNA93Wjah7IRC3ydxLmSo1U8dVVSpOiB94fHN/HzNrNhFNoTuhs7M7Qc4I24FKHyJQx1Akmah+R+doLmagKZ9cUs8MfILXXsBdr98I4JcKKBdOE33292km0p/sBzb5xAghqHmQiVu8cLHAUFRQLQnqaxU0RfDwnkHOza2xVGki9fbEUGi47OqK8fSWfdR++D+YvTSJ1TVA0KFiKhaR6iJEoviyvdbNRDWElARNF5FMszA9z/KRtxkbGmbbnp3U0MkMD5G0yxh+le/PORTOnyemQX3FIK5rnFsoEEvEUPQ4ZiaLW29w10iWYrWGsW0XMhLFEHDXYIak8PBySUxNZXdHhL7aAs0wy/TyuiSm4yAQSK7VVIQrhSb5XusTZbjfTCNU+f7pJUoNFxUFKeHNyRK5mMHXd/cwkDJpOC5XbhPw1ZeOkLWUD8zI0WWIcuY96sePQBgwblqM9I9Q3fkAP7ha2OBgnVtrMtGd5JGRJNptnOWfBkII9NBHq6y198KxBG4sSbDenkIIVNFu9QDxqbXzJpv8riF8j+m//h8f6ru5P/ljQuPDOWs22WSTO/O5OGBu5tNyvFzj3/ybf7Nh4p2ZmeFf/+t/zX333QfAf/pP/4ljx47xz/7ZPyMajfIf/sN/4C/+4i/4V//qX31q1/DrJmUIcnFzQ5FbaEf2XV6u8NW9/dhuQD5mcmaxiq4qrDVddvakGM9HOTu/RjOApWrbAVJouOQiOqaqoCkCLwhRBZiaQl8qwtxag3pT4U/vGSRCADJACxzsl36CYpqoqSxhvQaKgtNyQFGpoBHLd2J15OkcGYbz79H86d+gZHNcfv0tunbuZGD8Hv7ntIu37jXptBQuN9bYOhyn9sujzMbHUZAEZgSJoCUU9FDw9vQa39jXz1rD4czCrXIoAKauIoTADHwUzyXUdTzdpEyUn5yf5O6J/RiL83jV2vVi9LNTc/Q89EcwfRl/YfamswkiB+7By3+4rK0gCNCyWczOLvyVRQD0RJJdVw/jjvdxan4NR1EQQE82wVODERLHruDSXmQqvtc2nqkqoaajdPV+4SL9uiLw0JYO3rxSuJ5pJYCdvSm25CzkJ6gx85vMNSmiO6F+wiwkL5XBHJ/AuXz+lmORfYdworEPHfUvhMCslnDefg1vcQ7Fsohu34tQwGnoaMk07tICrQCc5o13zUhPivzZwyydOInjl5ELM6i5TmL3P044N0Pt1FG+ve9BXqvoLNkmqhoSMzUeHG0X5B3KRfnlhRVyMaM9BlIWkdAjoUqOTxfZ2xnl9ekyQgie2NpBLmayWG4Qm7nAygt/B0ATUFNRVis2yasneWTsHn5wtUoQSubXmiQsnftGcvTGxfVMLCcSI/rIMzRf+jHSvRGRrZsm0T0Haf7yhyieh5bNY93/CM7aGsrodlZe+DE6oMSTLDU8+h6+n7Cjl5VyW1pMEe0NeBhK0FX0rh4Uu8K3R2P8bE5jstSg1HColh06nQrfmOgie+EdAin5iTqEu1ok2T9CNKKs+9UkU4U6i90JBm8KNNzkVlyhIgbH0AZHEb5HqBs0QwlSomkaUqi4gSTWqhGefQ9vdhKhapgTu2BojJZm3Pa8PgKx+yCxzl68s8fx0nnCapyKGqE/ZpCP61SbLb61t5fDk0VqbogUbSNUetvjNL63SGe9wK48rJ46w8JbF8CKEhomj2zfzrcff5qlhk9/pMnVn/+CeNAi8+BjvHJxkdDz0Tt7qdoeSii5YBvc1T1KrFRAuM66Y0WiZXMEeoSBuw6CkIhoFKXZwF9d3ngzUhIUCyhhgBB3djxVfZVXL68yV2mhaRq+H1z/+5+dW2FHZ4xeq103JqtBNiFoD67wMwmCDcOQHZ0Rio22PMq1n9AUwcNbOuiw+J3MsvxNQ9fuPCcqQtySxSSEQJm5QvPMcUCg9/TR6hxgKKyg1GyWWg1CM4bUdBq+ZKYecOTKMrtjIQfXpim/eJSq79MydCLD/fyDux7h+8UmX9ndy+tXi0wX2pmLpqZy75ZuBhKCH1wu4QYhj27tQDcUZCaLqqn4dpPY018nfPUFag2HMAyRLZveka0s7diPe3IKVdHY0tvL13aN8s5UCVNTaXkhqhA8MJaj5fl4gSRuanTFNMBj2YYXL6wgkKgxg/EDe6ideBe/ViWeTtF0fBYiGSaeep6fH19Gj1iYuoabSKNn0oSKwjtTRUaz/aTXd3W+BHNiF97q0ob2VAjpT5uInQeopJL0hZK9KZUvdZigqviRGJ7nfaRsSxn4HBhIM1tq3hIKogjY15f6VOTHlOV57JucL9cIWzbu8bfRHn72NsFSm3yetKTGD04voWgaj4zlWDh7DtETJZSSTCKCi8rC6hoi8FFUlVBREcBUscHVzgR99z5GODXPyuQ0uqogAp9er0rmS79P4aWfIRsNFEUSqhpqZzeRJ7/G1Pd+AkFAfXqKcGqKWHc36a0jqNJkLrR4OlPnF6kIzYbN1PQid+3cQibeTcN2UJwm4x1x+rb3ogp4d06nI9bOBDM1hW15iy4ZsCNSBKeJf3oZAp9g7yPXZaSxrFvmUdsLNjgv2w6FANVpIVUVz4p+aNksRVE4v9S8njmoEJIxBWnLQkpwPI+0qvDoSAZdCC6t1glCiSJgOB/nkdEM6q/Yg2nL8zSOHb7+f+m0UO0Gbx09iyNiEEtu+P6FpSrbu+L0fga2WCEEkXKB1mu/oLXWDrgQuo65bS/qnoMIKRELM3jnTxL6PvrgGMroBK1o/Au3N95kk0022WST9/O5O2A+bZLJjYuC733ve3R1dbFjxw6azSYvvvgif/Znf8auXbsA+Cf/5J/w53/+51y8eJGtW7f+Oi75U0eTPo+O5/nBqUW8YOOuaWdvipzuo2ghY9vTPDmepuVLZqse5xfXODO/BkJQbNwwqPanI5xbWGMkF2WxGieQ7U2UpQksVUEXkrSlo4U+4Xpxb61SolVYRug6kd378eankb5HLKZQbzbxdYNVPcq2J7+OeOMXrJ49iaqqiHQWu+yxeOUq426LJ7c/wf+8VKM3ohApLXD3aJaOyeMUzAyXT53HCKCnc5CrlfVIeV3HUE2W6w7bOzY69hTR1rEOQ8nutIZ+6TTOqWMEjRpqNI628wDewA7KhRIv1da498HnyDRLhHOTYEWQQ1uZFnFG7nsUtdEgWJxF6Dpq3zBuMo3/EQRPHEUj8uizKEfewJ25giIlypGXuW/LDnbtvYe6YqErkCrOorx5isg9DxO+8jPC5QX8ahmCAGEYxJ/7FkE88fE7y2dFGLA7bzCU7mel4RKEko6YQcYAfkedL1JKepMGioDwNnuCdNQgbX6ysFAPBfPQw0SyHbjnThLaTdRECnPf3Xj9Ix8pKsyy6zR/+l1Cux0ZH9pN6iePouW6GDm0lwvHriBVDc+7YUiJRUzuibRovPxTutIplMAnlBJ/8hL1lUUSX/t72NXzaFdO8tAjX2MCi2rLZ6nSYrLYIGFpDGejDGSiSAkdcZOIXSGYXya0stSkxlhPL5auEigq06Umx+cr7M6b2BfO3GhrBAuVFnFDpX7hLDtzeZKH7mK56iAEbOlMsiOjEHg3HC1hGOJ0DxD92h8iF+cIa2WMZIagvEb1rVeQroNaWaP11svoA8Noe+6iMryLRHqQ4NIZooaGm+5nsm8Uc7WMLJ9tZwyqbceamUwSHxnDfe8wrZVlhKry3NA4zo6DnPMixA2NAbUb862f4S3OYu++j9nLDfTeIcJoHC9sy/KoikAXknPLNUa3pjej/H8Fcr2ILareHniKStnXuLjY5OjMGrHAI9dY5WBXjm5tDllYxn/zRfSpS5iPPItzByeMh4LX1YfWM4CpKPRO1SnOl5lcrfDwQIKXz8yxqijc05+lI50gEzOYXS7z/zpV4Z899RVSlSW8N14g06yT6M/htBwUr4F+/GW0VpHu0R2o/R10Pv8czTdfYi2Zxp1bITY8ykzNJ1A8wkAwXagxu30r+8qLWCuzkEyixZM4mkn3QA/ayBh2GCLTeZQ7pNfpA8O4K0to/aN4t5nHFEVhqepybvn22QpN1+fUYo3BLcnPtT9qocejI0n29iVZrbvoqkJnTCOuhh9Zb//z5IMcXb9L+L7P9s4El5Zrtz0+ko8R0+SGKVEPfdzT7yFMi+jYVvzJy6z+7X9Db9rsHhhm9/57eTXUqLkhY4NdHJ2v0pWMcLB1mcLbbyCEAkJBAQqz83TUf8jBh7/BK0s2uzsj3D+UJpSSiKmxKx/h5/Mt3CCgO2UxlrFwhY+55yDN139JY7VI3XLJPPk8mXIRRQZEt2yjUSjSv3SeP97eS92DVuECqUIdbXgLBwazrNZdQDJdajBX8klbOl/e2YUlfFAM3plbY6Hhg+sQNAWtrp0MP9KJmLxENBVl+/0jFHMDnCHBimaj9ScoOz62H9IfKsSV9qtuoebSmW/nSfpBAAMj6L0DeBsCiEBPpbF27OQhy0BcPY99+AiNehVhWphbd2LtPEBLv/178E70RgVPbOvijSsFbK/9AKOGyoNjeboifGLnqKZpeJfP3fG4OzdFrNXAN6N3/M4mnz2rzYBi0+dyocL/ZVeKe8biKBmDrd0ptnalODazgvR8hADpe6iWhqm1aw2dXqjQub0X7cvfJjU7CYszhLEE2q4HuPDKi+Qe+jIpp4ZVLaDmu3AHt1BPdRDr6qY6P4ceiZC/6x6s3QdomlFsLcoutQlvvsgfju1g1Rqg6gTkIj5Pd6gsL5Rx/AAUBXX2HIXeLcwl48yVbaKGylPbcpRtn2QyhpnJYB+/dP0+o60KiXiEWtNBxG7dk/WnI9fX3xqgz0/hHH+bVrmEYpgYW3dibN9L60NEk/soXFi59Z0ppEQAF5Zq7O2KYuLxxFiKuwZT2F6IpSmkDZDBB+/BdEXgnjp2y+f1jkFmThXBslFiyVuG8IXlOgOjiU+9/opl12n+/PuErRsy3NLzaJ06StzQ8BtN7PMnrx/zCyso50+2s+De5yjaZJNNNtlkky8av/EOmJvxfZ/XXnuN5557DiEEV69eJQgCdu/eff07fX195PP5D3TAeJ6H591YsAghrmftXIto+TBp+Z8nPRHJt/f3cXa5xny5RczU2NObpDemoKzvZj3PIwJENAgTOoevXDNGCrz1AsKmprCtM87JuRI7ohae79MKBMNpo103RIYI4N6RLLoIkevGG+m0s2dkVz9LPRPU/+H/hlZcImlXKB4/ga8aiLvv55KtYCyXiI9vRdU0PBR04aDIkJW5RQ7ubxHu7WVMNFFmlohfeJvl8hrG/nvxPBc1FFh2BUuN0PICpOeiiraRe2tXkuOza9huwFhnElVVmS/b7OiJoZ8+QvPMuyBDpFBYXC5Ruvpj+g4VyUQ7mVp0eeHcEpqukUnvQEFSvVjkyV0Wg11JWp29KN39ALjXUqA/5LNRFAXdsduSRY8+S7xaRlmcRRseJ5CSyKm3uNl1JAGZTBHZfy/uxdMoy4soiST62AStlSWMS2dRt+39xCnXn3pfliFJNSSZvBbhGrRv5jMeKx9mvN78789z7KZ1uH+0g9evbJRJ1FWFx7Z0YIjg+hj6uLiagbJjP+b4doTvExomznohzGtnvtO960gU1wFNg8W5686Xm/GLy/RU50gaKiUBcVOnq7eDTEeOwaRO8q2/w4pFEUuz+EGAms6iJTOE1TLB6hI9Dz1CtX8Ly7aO8CTdcZOJjjh3D2Uo1Vu4oWS5ahOGkt6ogrYyjwh8Uh0xppdqTK9UePnEFNIwqQmDmKlx3109VF/caFRy/ICkpRJKQW1hgdcpsFp3SUd0/FCwM5O65f6llLSiCcT4DlRVxT3yGq3T7663lYL0HFBV7J4RCh1buVjTWG4lGNn/OClL5++uVJk5W+FrWw7R43m4s1OAJJuwSI5vwX7vbQJVAymRgY936Qza0iz3fOmb2JaOEBG0J76KUasQ6nG02iy2G7C4WKLqBaCZoCmkIwbDeYEQ4iP13y/ifPVhx+vN///Y16+oXK2GvDG5wluTRWKGSq68wFytytS8zrN79jBuHyZs1PAWZjGW5xH9ox94ymC94OvungQXlqo0Gg5TVy/x7NZhItksDS8gHdEQQlJruexOCi79+EdM7BhHrJXQ6xXU+SkirkPoe4hIHPvdN0kduI9LtkYuEcef2I+fymEbdUKh4voOigiwjAh1x+c/X6iy54nfI5w+R+P0SUIpGblrP5HxrdR0EwGEUmAeuB/pOHizU9evXx8YwTxwL/b0Faw9h/BvY2hVFAWkxPPvPMe0/PAj98dPAyEDcjrkMtcqStyQXLrj3/w6xoGiUvEESzUXPwzoSphkTVA+pqPo13EPH2Ut/GGvqyeusr07ybn3FXmOmxr3Dmcg9DecS/F8ArtBdHQLzRd+BDIgIEHoutSuXERdnOehb/wpP3VU0vEI5ZbNvVmV+k/fRVFUdENHKCqa2s6uMWVArjRP0euisAZDfoiG5JHBPG8VGpimzpNDOYbTBiY+odCoDmwj3FHj0quvI/xlissFjHSakaeeYfbFn5DCRUNiTF9FcwJml2rM6O/hP/v3eKOicM9QhoimMrKlg66oRj6qts+NyuWyz+mFCmPZKHEtykLF5oKrQsdWPD1HqbODo5fm0cprjI1EKNQ31trzQokQCqrnEBZXCI69g9B0otv34Hf2oj/6JYyFGdwLZ0AG6KPbEIMjuGYU/fRRGu++df1c0mnROvUuRmUN45Fn8IT64Z+vDNme1RhM9VJuBSAgY2pE1aC9Vv2E/VYIgfygNW/YLsDxScfHF3HO/LB8lLn1s0AIQc31r2fB25Uq7gt/RzSf59F9D7LQqOC63rpUl0CEkt5UBE2EIMELQjoSJlcSOf7aczB7BqjVbcrvNPgH+x6HtVkiTh1PMTBiadY6hnnxcpHdz/4+W2IWlVDhfNHGW2xwX5fPto4Emi2puzbGuXcZUDV8CdbYBJX/+l0inkssnWU51oFiqPStTPP3H/s6x7s78YKAs/NrHPMCdveleWLnQcyWjXPxDIQh5uwl7t32MC8XINDNDbVPMjGD/qQBeKiqin71PI1XX+CaVHBoN2mdOIK+uoz5+Jd/5fORiA/MKr2hLiogDEipkFIBAtrlPj/42Su+j9+8VbpM0q6LKHwfIUN4X+2HQEoURfnIe1EhBPWWx4rbrpUX1VVylkC59u5fnNvgfLmZ1tE30bfsuOXzsNnAPf4O2sPPXJcp22STTTbZZJMvIr9VDph33nmHRqPBo48+CkC5XEbTNGKxjbotqVSKcrl8x/N897vf5a//+q+v/39kZIR/+2//LR0dHdc/6+7u/lSv/dOgG9g+0IHrB2iqgvIBi65uKdFMk9evFFmuOcQsn75ojHuGsyyUbaLRKPM1l6/s7l/fKLc3eemozr3DWXb3pDZISXiBS/mJb/CzFbh0uYKpCMwwRjTWweP/4AEW1xq8uNLiEQmNWAbVrdFRXcVUdaKhxMXE8QIay8soqQjyyI8pLi6TysdYaTgM1YrkUglWSzW0Vp3eXJrVpkfS0unPmPQkTJxQ8L88NMF82eaHpxdZrLRIR3XSdpnzbxwmH9HoTkRYqNistQKEqtI8d4r9DzzH2fMBbiCISJhdbsuYxU2d3nSMRGc38UYd/AAllUFNpj/0M/GWF3BOvYM3dQWkxOgfwtxzF3JwBD9xh0gdVUV3Hexzx9GTKYwde8D3CeanMaREXDxNbtd+tNyHk0D7VXwR+/JH4cOM15v5vO83mwsY6UpzYr5CteXRm46wszvJYCbyuW/yr9279H3cqxdxTrxDsFZEGCZKPEly2y78masb/kZE46iVFb519wFeyadRY3EOT5d5/WqdP90a5erlqXY2R6aTSKUAzUY7ojCVBqeF4nn09HbTa1rtulGyrSH9+qkl3CBka2ccRVERCmi+g+P4xFNxqnWb8XycTNRAUdoR5MO5KHcN56j7kszAINW5thMmDNvRtoEU1N0ArX+cpaqH40uaNZeRjgAzniQVuXNUb1BZo7owQzR6I4I2iMZpHXiUvyuqrL59CaVnkOWmxzvTJR7a2sVzu/t44VKRn8432TH2MI8fepBe1aO7O4d/5DWM22WrBT7Gyjzpex6+/lHYyiBOHKNLl7y22qLRWneOuy5KLEHVCckloqQzuQ+U8PlVz/2LwEcdr/Dxr3+m1GSpUeLduQqappHSJEGjAQgabshbV4uMjO8idukEAOrsJD13P/Chzt1lN/mDvT28fnGZlp9lxRO88eYluuIG8WoBJ9uNb1g8P55m8Zd1aNYxFEFYLSMNo61rHk1QDwV+rYm4cpnLSievXJV89Z5dJFwfJZ1DAGO9Weq2Q8MNSMbixAyN6arLiSmHfXc/w1hHAmf+Etnufnri6/WWAp/6MYfo7gOIg/cjPRdhGMiWjT97lXhnD/GubhTz9lkyvWGV4XyC2XLbEKJpN5aLpqawqy/zgc/s80BKSVBaRTYaYJpouU6Edudl7ec1Dlw/4PBUiTevFm/Kfmww0ZXgqYlOkpGPX8ft8xzLH2WsfpTr+no6za5ig1MLFRwvZLwzzkRngu7krdHgYctGGx4lWF5AcWxQFLJJneZ6vREZBOhXTjO05WEqXsDdw1ky5QWa9TqGZWH7ISIIEC2PRMTAR9DtV9nRM0HTC+hJRrh3JMvu3iSPTLTn42vSoeWmy8/PLRNIyUVGuOe5AQb9Mqau0kjkWatVWC1WSeTjOGFIqekShLClM85MqYnWqjBZshBC4Q8O9HPvSJaIfqN/Xi3UuVBY4fFtPZxbrHC5WGe21KDU8HhrqsyzYyn6CfALK2AYZCb6+JPxCLgOFWHyTkUQNTVMv4k3P01fvhe93K5LEb62RGT3QSL3PYYyMIRcf68JpX1v/uoS1cvnNsx31yksEXdsjJEtH+v5flbYO/diF5dve0zrGSDeN0DmDu+zj8oX4X4/Kh9nbv24NByfpWoL2wuImxo9KQtTUynJKpZZRtNcyopONp6gVSwRO/02Bx58jGYkxcmFChFdJZeMkkxGrwcK7R3MkjR17hvNY+oa//3dWZquTz5h8VYh5O6+CRZb/Qw3V1g78iZdgUb/4F7WPMlP3p3l6mqNZNSgy1JZPrfCoQfv4tFt/cT7BvCX5inWWxSdkC73DI1SW/0h2tVHrxGixaJcKjawThzDnniIlYaPoptEdbiy5nLXSCejX/4G/t0PEFbXEJpBOt9DtBzw9nSJWstHFYKRfJSHxvP0JCOELRt/eYHa0deJ6Cri/cEO5QLxdcfHr+pvO0sBx2bLtz82kKa/K/+x9xPS96n19OH77obPDbtMX1eWFTvAiERB2bj23D2Qp6Mj85F/b3atyX85OkuxceP3upMWX97ZTXfSon788O3fS4A3dRlj137EHd5bSU351PbGm/xqAqFel42/BSmYW13DDRVAEvuEwYabbLLJJr8t/FY5YF566SX27dtHNpv9ROd5/vnn+cpXvnL9/9cWNaurqwRBQHd3N0tLS7/xkhIp4MtjcWpenEaQ593pImdmVq9HLwEcbzT4w3vG0EKPIJRENTBwKNykK68oCiVifHeuwJGLC0A72C2TTSPLPs1LJe7b3o9aXeXNkkNmcB+RjEHu1EuImct0ZvuYb3qIRhMZBoRLc+h2jb64hu86RIWkdfUq9x98mL9ZKRHaNmbgkghcYn5A3gsYNzO8eWmJ53fkmCnUCT2XzqhAhh56tYLtOCw6DoYqKNRsgvVnV2lIOhQXPZHAq1ZBV9eLssKu0S66ogrF7/13vOUFQKLEk0Tuuh9vcIzgVywmInad5k//lrB2U6RnqYC4eJbUV76Nl+nAm5++5e+sHftorS7TbDaheZtCyc0mLC3Qcj+Z9IsQ4iP15Wvj4NfR73t6eu547IPG683yOB/1fj9NksBjAyZSmoAkcCosLVU+09+8Wfbm5nsHMGeu0Hj5p9frHQmhIE6+i9rVg+gfxp1r90ujbxBVhjRfewFHi9Oh5Xin0KDm+ESVkJLt05dKY5cKTHoK49EEyroBCNdFVRSqVy/ije9gWY1zZrnO7FqLgu0zlI2iobBaqbOjK86J+TJSD2n5PrpusVZr8kBXDL1S4Ju7u0AI1tQYr1xc5mo6yj88eB/lubl2FgHQm45xabWO1dXNZSNHo9WOFFYVQX86yqnZAuNJ5Y7P3nRbtOwmyLY0hvQ89N5BjvhJlhYmEYaJXJgi7kvMVI7DMxVyHTm2ZE0O9CZIRQy6chZxLcBt1GjOz2yoLXMz3tmTNEa2tWVigEhpmfqrP2fvU3/Mi9OXkdffwZKg2WCwP0a92eLyYpG09uHH/a+rz38a4/XasY97/UIILhZ8Vqs27rpsXqiBCMO2TFkQsFZrsirSiPX3rGE3cW5zHTejCIG5Mk/ryBvE1op8qbufpR0P8D/PlRjSXVhdxUeilVcpGinOF3Xu2jpEIp3CbdkEgBL4CN2kHgh8P2jLaQYBnSa8PbfM9/I9bEvrDOVj/Oz0IqauMphPkAuaqIbO7t4IfUZA4p7dnJpa4dSVBQa3jLC/1KK7XrveVpGRrdR//DfcWtBBkHhkL5XFOUS5iPR9RCKNl8xw7c5jisZDY1n+y5EZhKJebxMBjHel6YsJFhcXP9Iz+TQxAw955j1aZ08g3Xammjk8jn7XA9jvkyH6vMfBUkvhhVPzt9TDeG+ySUIL2dthfKyo4c/iHj7pWP2419WpwNNDEUAgZUjYWGOxcev3hBDExrbTOvza9d+MBg6modJyPIRu0JiZJD16gIWG5JmteQpOESOdpFxvoQQ+MggRAjqiOuVKjWg0wT842E2j5RPV22va4urKht9VFIUjiy1OzhTZ0ZthTHcQp9/jzKXzSM8n15Fh2/2HIKIxVWpQbXmUmh5ISEU0tnbESHSY/N/6ciQMlR7Lo1IsUF5vI1VVubDUIh9VKdsupxaryCBk10COmK7xy1OzvHxplbv7EoxGBYM5k+RLf4NfKjBdqBGPRPj9PftZ6drFmROzbO1KkFy81F43rtN8+3W8rj7sdP6WdrVWF2hWynd+QLPTuJF2AMEXZc9jZTpwo/G2Q+omhKYT27GX5VLpE//Gr3Od+GH4tObWT0I11PjZ+VVW1uuGCtrygY+N54gh6YgozGnwZiHgD/YeoPXGK9SWlxiZv8hzYztoXV3CKzQRJQMv24may7OtP0fTdfn/vj1NreWQMHX+6GA/heVVbMfDbtQ5duQ0tUaLbx4YwG55uKsr2OYSemcvwvcYS+kYdhW52sQHjkyu0pmLs23HfkqXLzGzsEZ2dBR3+hxShujxJOVWQOjUySkatusSzk2RHDvAVHNjpuLFxRKxwEAKDVLrDi27yVBEoXsiRdMDVYGELqFZobxwBefwK+jJNM3jRxC6gdrRSRhPbZgX5JWL5LZs/5X9bSylcXzKpe5sfI4xU2MspV5f239cImPbaV48uyGTR1y9wD17H+PHBZVma2PmXVfSIqsHG9YAHyYbxhMaf31yhZZUaa6vtwGuNpt8z2nxezvyGIa54T128/lB4HnebY+jqohq5RPvjT9NPmi8/jbghZLvnrq9UxwEiUScWq0OSP54YlMebpNNNtkEfoscMKurq5w8eZJ//s//+fXP0um2Xn6j0diQBVOpVEin03c8l67r6PrtIxSvLZCklF/IxflHJvBIKJDQVCY646xUW/jrEhmmpnDPSI7RfJzS6gpSkRDeKuVc9hROLdU5sdoEXQfPQ0pYbnhs60mhxyL8lyOz1AsFEpZOslLm5GWbP7jnCcaKS2RwUSMqq0aaNTNJs+nSt2Mb+sm3UYIQO2hheh49U8d4/uB+jlYEJ0o2cdPg/p4Ih3qi1M+fQPTspu4rnFusbFwE3hQRW2y4GJqKvW6Qa3oBNQ8ef/gA56/M01xZJW0oHBzt5kBPlOIvf4jh3UiFDutVGi//jNiTXyHoHbpjH1AUheDK+Y3Ol3Vky8Y+dQzr4adRjr6Oc/USBH67yOCWHaj77kFOXvjAxyZU9VPrf7+qL4eKRtGRLFQcFAH9KYu0LhGfoHbJp8mHGa/v/+zXMXZvlob4LNGlRK8UCQorCF1H5LtwE2mgfe+G59I6+voGo6yUIWoqjXvxLPGJXbgIlGQK1XVovvEi8oGn+fGsQ8eA4Nipq0hVIdQMXp71+ZPte/HfepmG7dBKJrlu+lQUtIFR3JmrLEmLvz6+QMsLEIrgasnh9EKFHd1JRrMRRnM6majO/GqFUFFJRi2eHUwjK0VOT69v8ARoIxPkYiYhkuOkGf/yN1DOvUeyViQRNxnafoDTiSF+Md0es1FD5YmtnazUHEo1j63p7B0NEXUzwfLBZ1leLhI3VXoUB1MIzh+eRPo+aq6ToFZFlyEiDOjqGWK61CAf1eiMaWzJGWihQ+CDVBSEot5igL2G0PXr/VBVVfypK0Bby/r5PT2cWWkyU6xjaCo7epJ0dyY5u1xhoiNKSv3offeLNF991PF67fOP44Bp+RvfUfVQJROP49Vq7WfzvlNqY9twfP8Df8ssrVD/+fdh3XmmVNeYOnsR5eI8+tAoMpmEIEQGPj16yNVSi53945QbReKpDKKw3J4fVB3f8UEIzN5+KisFtIkhtIERrtRDxgaz9Bk2/+tTWX5+ao6S7dI/MsREZ5x+p8jRq8ucmVpBj0YJ03nOTjU4XZ7hjw/20m2128vJdhJ7+Cnst1+9LukhTIvofY+C49D85X9DXpP6EArm+DaMux/EUXXUwONgd5TYAyP88mKRyUKVhKVz/0iOh0dSWNK9Y//+rFEVQXj8HVpn3rvxYRDgXLlAUKtiPPU1HOXW5e3nMQ5UVeXkYvWObXNirsxErhv9Y86fn+dY/ihj9eNc14cxCksp8bJdaF29+MUVCALUcoGhXDflTIo1T2LqBp3pGNvHUuR1j2R/jvK+fVRefR0ZhiQiOp0JC9t2kAhK2X6UlkdS9W+7pgVoBgqnFtpBEkNWyNqRX7C2MA+AIhSqpTKe49J0fSq2T7AugYWA0A+YX1lj3HFZ/W//BxVVIT3WS+KZ56hkulhesymVimTSCV6er/POTJmaG9BwPKbXmnTFTZ7a3cfFhTWuXLjKV3Z0MvviL1mdmiaaTjOSi7HW9AhOHWWbAQO7h+ivzCEuXnl/6xHMTSEyHbcYRoX6K7Z/uk4YhhsCb37dc4itGUSe+CrahVN4V84jfR+tuw9j90HsdP5Tvb4vwv1+VD7O3PpR8YTOD08vU27eCC6RwNVCA4TgS1vSfHl7B0JRODpT5p30MPc+ALnWGrHJM6jvvsjvPfI8h1d1ZmeXCKoV7ts1yIlCg2rLIRqJUqjZXCmWSFkaj3VpnHj3NHUnuH4PZSfE0jXE2HZCX+O1CwukG2Wk3bz+3lUiUULd4NRClYl8DPHUN4i9+HOErqPFEohuga1HKFbqKLpBOiMRCBRdx5MK16Ut39eGUkqEEFjNOhSWCVtNzGyeWKYDR6iEPkSadRo//S7SaaGn2hki0nPxF+bQ+lSCWPzGSdef16/qb3HF5/m9PZxcqHG10EBKyVhHnL29CRLKB69ZPgxOvpvYQ09iv/P6DfkvVWUkqfO18THemSmzXG2hKYId3Ul2dcfQQxehKNQDlcWaS7XlkIkadMd1IuL211RoBZQaTjvD5X2H59earNoBA/3DcOyt62usa4RhSHT/Idxi4bb3oHf14ZvR37hxu8kmm2yyye8WvzUOmJdeeolUKsWBAweufzY6Ooqqqpw6dYp7770XgIWFBQqFwh3rv/zOEgZsTav0HehlzQ6QQMZSSWghpqbe8c+EEEyt2biBxA0FIhpHhAEylEih0J9P8rNzSyQtHS0Wp1qvkejoQVma4+ULKwzsfwjz8AvEdYP4U7+PXivT6a2RGx2h9uISQb2Kj4qlCcTsZXZ7LbY8+Q2eafmYK3MkWitMvzyH1j/MUCZKEIY479OtLxkJItEoXrOJH4aoNyWuaKbJ5TDCyxcL7Oju5KmD47i2zYodMnf+BGm7hXHLKJE4772N3t2PK24vB6QGAd7kpdseA/DmplD230t4/5PE9twNrguWhRtN4IYh0e7+drr3baKJtFwn/rpB/bPGFzqvTFa4cJNeuwAODmW4qzeGEn5xIo1+3XwRCi1bvod/+CXqN/c9VSN278PIXA4ApV4luI1jMLCiaPlOguVFlGgUs6sH+8Ufo1gRVvu3sXJ8nnhfH76ioEhQLYtlT3IqNcb+bausHT+GG0qiigBFI/bQk7RWlzD2HuL1mRqt9cK8UkqSlkbT9Tm7VGWiK8GVpTJxS+Pu0U4mxqOkSnMcaazx3vSN6Do120GoamQ0eHhLF/moShAm6JkYJeY2aAmNU7M2pqbz1WSAIhRUIZkr1QkUg9wH1DqthTo/PLVEveLgzaxAGGLoGk/cvwvdmMMjjhKLEzothKKgKyqiViAf6efL23KIwCMMbzjYPCuKMbKV1rkTt/09fWI3rZvGtgx8CEO00OfU8dN0dmYY6UsShiGr8zOcc0JC3cDQbm8Y2ORWwjCkK2FS9ySKaJcIaLgB2WwnSrMBYUgibpF22kZWLd8FPQMfOIY1IXBPHtloGNB1GooOmg5hiL84j/RcEAKlsoaW7yL/wBaCnx4j+eXfp/af/w9oNQmlACHQsnm0gw/SmpziokhyubKGrdtcKTR4b65MR0znmQMjXCk2SUQM3pwqs603yyv1FpmBMRqhoOYGSBniBCGvXinwjV2dKNIjAJzhrVjd/YhKW1qTZArhe9S+/98huOn9LUOcS2eJxBOoe+8hCAK00GFvTuXAk1tZrdQxFIgJnzC8fWbX54VRr9K8cPq2x/yVRcxSAfK/HgkhKRSq9p3nxaYb4IcSfVON40PjCIF59wNozTq4LkKAppt0aDpZCdaB/dCXwvc8ggAShsDdtY9t1TWcuRk8z6NaayAVhcwzX+dV2+IxPyR556UtgQTb9VEEpGurrK4uve+4pGAkCEa3Y5w5ybUwHVMRaK6NtfcgM4GJqqpoigDHZqnc4MdnLlCcnCIWMYkNDPPWVIVMMkoQChTRdsw3XR8nkGzRWjRKa5iZFh2rV0nmEgSqRI3p9CYMglBizJ0jklBpXLz9XCP9288XQSqDmsoQXHsv3IymITq+mBJctmGh7L0HY/s+kCGBYdGUckPk/iafHSvNYIPz5WamCnXWhtKkVY9v7szx+HiOqhMStYYZWpvBnT9PqGvkX/0uz3UP0pwYQzVNzi3O01yTKJn1NaoQKEgWqg6FrjipZIz66o01a0RXSHV3MR/rRJUqzcUl0jddh9B01K4+fARNL8BbmuddO0kpv42edIQtg8PM/+RHeLV622EahmiE6JqCsXUXM82NfUnQDjyT0kdRFMy5SZqv/XxDhrPW1UPk0S/hWDHC6UvX66L6dgOtdwB/YV0ut7iMEo0Rivb8r/YPfah2l1KSEB4PDUS5u7/twLFESBh6n0rXD6TEGdmG1TOAWM+Mk8k0biRGRxjwlYkMdiBQhCSiSILAQwjBoi34uzML19f30K7n9dVd3WT14Jb1VK115/WrBGwvpJVIE3v4aZqv/wJ5U+Ca3t2Hft/jOL/80S1/KzQd88C93CYvZpNNNtlkk02+UPxWOGDCMOTll1/mkUceQVVv7Kii0SiPP/44f/mXf0k8HicajfIf/+N/ZOvWrZsOmHWEquGEoIl2cdsIHpHrFeFDwvBXFO9TFFbrLsr6JtMPJVJRQWlvRBuOTxCCpijUhYYST7HguOS6h/EsQWNnnnREI1RUihfOUJtdoWdinNW//s+k7nmEcHkO5ufQAgejdxBr+264cope30fLd1FVU5j9Cvqu/XTmopjCJxczWam1F7+6KlgWUe5+9ClWfv53pEwN21uXXVIU+h9/Ek2TfFuZQ19bJpUf48XVEEXTGFyaxVQFt4TpAH65iOm2wLy9Ti2KuEUvd0O7K+3FdxCG2NEE19MG1o2ybiJN/J5HaB5+GcmN6DVhWlj3P4atqJ/5hlMIwaVSa4PzBdqtcXR6jd5khP473P7vCu1IuBpydQlpN1EyecJcB4768TX+Py6KoiAvnMR9v+Mv8Gm8+RKx/iEwY+2+eRskEGY60AZGEKaJJgRqrgMicWrBegFjIQlDSQCorkcrVPjbSxX0XQ+xY3wnGVklWisi0jn8ZgNNN2gM72TmvaUNP5S0NAp1BT8MmSo12NWfpuEErDUdtOEcSaXJ7rik4vejmhbpbIqY7xAGPkoszra8iRo47fOFIbZmIFSVIGhyerktQ6II6E5F6UpG0XSdsYxBENxm86dqvHSx0DYqGCb6wCjh2ipeo8Evjk+x7/67ee/CHF6l3DayX7sNx2EkpYPvEr5vLAZBgLFrP+r8DEF1o4HLGBon7Om7PqaDIMDoH8E5d5K8WyESMVleWWN5pf13wjBRNI1szCBrKahIlDBAKir+ZrHRD6QzqnBhJeC+kRxvXC0igQVPo6d/lLhd4ZGtGWKzx9Huuh9lbDu2/sH1A1S3hbPyPkNsvUZfb4QrXT34c9MopoVU2+9nRVEYzpikcDGf/TLezBWS3/5TgqV5TNdDKCb1eoOZI0cwnvsDXjxXItQtvJZDXJWEQcDlUoB1tUzUUFioufRlokyVmizbPqlEBCUMSWkamiKIGBqrdZeaB50iQDaaKJpCEEvgGW0PpKIo6KeObHS+3ETr3EkiW3cRrH8/DEO64iZerYSUkjvJfX+uNOvtGjp3ICwV0Lv6IPAJFfWW8flZImRId9JkuXr7IsLpqI6pcvu0i01ui5QSBkZRBkbw1g2Z7QMhRq4Tfct27JsMdbaqU4hkmBy6i+GBCcRagUQsTiPXx8uOSbXlEdEUVFWgqBpKrYISeAhNw7FiBGGIoUpSEQM3CGnMX6EnaTFdal7vS5oiqNgel9QODj7xLJUTx/AKZdLpOOboVk64UbrKDXZmDNTaGtG+Xfxgyac0O0+AIJdPc3K1TuD7zJeb9KYizNV9wiBEeg6Xlio80hGnayCLv3Yemg3Meg0lnoB0EimD9rrdDz9wLaj2DeDeZp5wVZ3IA0/Q+MUP2xJ+1xAK0fsew4klbrf0/UIQhiHOtbl40/HyuSGEoNL6gPeuhKYbko6AGnp06NBhqlQ9SaVQRDgeslRCFRKqp4hcPEW4+xDnvBYykUfxXIhEMVWBpav4IZxYqvHcgd30zC+wulZjre7Q2ZljtfMZjhU8BrImO4Z7KBdMCPx2/SbLwl/PgBxMR2GuSi6W5ETFYWp2GXfbAF2DI3hXL7elwSIRNE1jaGKQc11jNAsumue2M2qkZN+WPjoNSYjAcmzsc6dQrBjBugNGicbQonHUyYvEhrfgNBrtgvUyxFucJ3rXAzRe+AHSbhI6DloYgKoR2X8vbvKj1VAJwxBjffL4tOfiMAxpGRHoiNz8IdAOErIA5I34E1tq/PTs4gbnC0Dd8fn5+VW+uacDVW5cZ8TND/B603auhTLAGRgj+vWu9t7KsVGzHfiZPDVFJfLU1wjOn8S9cgHp++hdvRj7DrWlFjffB5tssskmm3zB+a1wwJw6dYpCocBjjz12y7E/+ZM/QQjBX/zFX+D7Pnv37uU73/nOr+Eqv1gIRWWhCe/Olig2XCK6yv7+FKNp45YF0wchpSQT1ZksNtjZk+LEfPn6MUVR1tO1IZQhFdtDVQRx08IxNGTCJEhlsJcXCes1okIwko1iRi3Kq8uUXvwJ6a3biR66H69ao7qyhNpsoDcbrB17B08KvHwP+q5DnK0EVMorHBpMc2g4y49PLTDamQQhuLhap2B18KVv/jH5pcsEhWWW1ASJrdtoTl6hcfhHOH7IUDZK8cRbHNp3F9P9u8jls+jzxduu5xTDbDua7kAgFPQtO/GLL9/2uD6yFd+0bkmxhra2vZifxi8sEdtzkGB1GSkE9I/g9o0ybyaJSYGlBB9ZR/6j4AuNE/PFOx4/vlBmcCJLeAdD3m87QgishWmar/5sYyRcvpPo48/RvJNz7jNCd2yc86duf1BK3AunUfffTxBPoaZzBOVbn60UAka24GU60CpFgmg70i6iCZCSxuoqY10pLi9XuJ5WABxZsllJpti2f4xyqcSlasC0UImnEmzHIGSjI1MnZCQXoeIE6KrKueUGc2WbrZ0J6r5Cq3eElh3ie1V6ZJ3IsZfRlueIau3NrtK6D2PLBO5NdZhkEHDPUJr5cpOoodGbadeVWai2yCci5KI53LiJzkYDQtmF+bV1Y6kE3zAR3f1oQQCNGpoVQdQrt9TRiMYijGSsO2ZM2FaM6Jd/H39mGvvyeYRuEN2+C9nVc4s8UtjRhd7Vh3L1NM/seJAfn17EcdvXqXZ0Y5oGz23vJFlcwDt/kqC42q5HtWMvXmcfv5sj8FejS5/7hlJcLNp0JkyOz1VoeQHjXQkeHtvGgOYgJwbxNP3DvUsVpV1It3XDuC5dhyHVIWaoVKREug6h59I/1E+yr49qqPK3J+YZ2znB6L5HyAUN1J4B5JWLVKfnaSWyKM9+i++Vo7gRFduT5FM6th+05xENTi5WeGZ7F061xWhHHH+lxkguTssP8EMoNRwcP8DUFMazEcLKGld++FfUSmvomkrf9q1k73+YVizRlj8r3V7CA9oSmcL3wPiAlLFfM7cUM74JRUp0Quxffh9Zr7fHz/Y9yK7PpzBvEATs6IpzZqGyoZ7eNe4ezKDK4Itq2/7C0tIMzEeexViaw7t4FhkG6OPboW/oto7TjqTFi0qC866Jke7AFwpeWQI+451xMppEzM1iv3eY6rF3UDQNq7uH2K79WHsP4hiCu4YyvHa5QKibtBxvXfrLpeWHpCyNpKEwV6iyltpC931fRw9crrZcTp+8iB4U2L41iz99BfPeh5ncei+H35lHqikScQM/EiOoNdBCn1AzCEOJoYCLQtSIEgpBVY+SETAnIxjZXmLNMkoqQ3DTXBSqGlr3AJw7dYvxUe8fJsh23rY9pZS0OnqIffUPCKavEKwsoiTTaKNbcdL5z9VpuclvBlJKEuadzQYCsHSFa97lUFF5d8Hm+Nwaz2mSWLOJ1/IwNZWorrT76/o+EdEuBg9tJ3Z/OsJKtcVQVDK0ehn74gm2JpL0P3Avb/sJLqzW0RRBXzpGv6rwl/NlpDRIKBpZYWAQYmoKWzuiKH4v/cU1Yj091Bo1jl2YZc+OQ/Ttv4/W1YtkYya18e1oA8MMmVEUo0ijqaGocQaigp750wg7xvzIAc5eLrHk9NCbHWLXqEpveRYt8LHffgW7WkEfm0CNJYlt303z4lmk72FPXyH29NcIlhYIVpfQxrehbt+Lm+v6lbVEv8gUmgGNO9RbKTYcSi1Jx/um6nxEJRMzcG7zeulJRciYoi0LKSV2JAaDY7eoC9hmFGX//Zg7DyDCEN+MbGbBbbLJ54KgJe8cXPx+dEWgfkHk6jfZ5IvEb4UDZu/evfzVX/3VbY8ZhsF3vvOdTafLTSiKwqWKz8/PLl83AjQcnxfOr7CrN8UjIylsX9LyJYYm2trWdyAMQ0azUY5OlZjoSdPyfC6u1AkQlOsOg9kYg+UmU4V2YnAoJYam0Je2MFVBImZhjm3HPvEOSElMBb1VJVQlMgzwK0WKL14BGZK550Eab7+Gr1uY0ShrvspaoUr06Jvc9WiMc13bObNUZ3t3gq/tH+C7JxY5u569ETU0Vuomu7r38NS9eXqEJDh+hMb5E4zmohiaSqnhIEOBe+ww948NE92zh8bcxdvet7FlO64Zua1E2LV2EcNjaJfP4Rc2FqhTE2nUid24t3G+GIFP8MaLuNOXAWgBWk8/xYlDvFnVmT5dBarETY37R3OMpzUIP5vJzQ8ltnfnczedgKC9b/qdxGpUab7y0w0p8tCu4+EefgXt0S/jf44bAiXwb2g334agsoYQAk/VsO59mOYvfnRLFLm1ez9uMksYhnjxVFvurrhCrrFKOhVjbnKWBw7tJ0Qw02oXq49ZOgMpk29tSbBmJvjblTq235YhZLVJxVcwDAPb9VAJr/thDAX8QNKVMLmyWiMf0ynXm/zyvMO+oTxvXV1l1JKEb/yQUqntLEpHdFJhyOIvX6BPSoJt+9DxrhvPc0bIt/f3caHk8N+OzCKRpKMGcVPjjUsrLKzFeHo8s8HJ7PrhLcZQKcFXVDTDhLVVnto7xGsXFqnVbYQQ9HWmeGzXIDFTwb9dVg2AonCqZXLU7sQc6iaUEKyFPJgx6Y2EGzaUjqoTeexLhOdP0T99gr+3Y4IFPUXdSpHOpuhPGaRmL1B/+ac33jlrRdzZSSJ3PYDcvm9TmOwORHDZ32nQCCweGEojBMTUgMDzcFDaL7AP6cj2dBNjyw7sY29t+Dw6dZqv77yPl70uZmYX6e3vpZXr5sxMmXRtFWoVFtUE7yymeG5XD3omRvrBUTr313nhwgonSh5zdZdyvUVfR5pDIzneuFrADdtzswR0RWFHd5KXLy3zxEQPV4tNKnbAVKnZlmwREIaSbGhTPnoWUavihyG+G3L5xBm6llcY/PYf4poR9FwnTF2+7T0qkShS+/wz+K4hVI263153RDQwRXiLc8xPZq6/mzb8rQTRqOCXS3iz0+3vrhVxrlwg8tVvIVKfbp2IO5EzQr68q4eXL65SXY8Yt3SVQ8NZhpIaclO682PhaAZiYAx1eCsCcIJbJW6ukdAkz+7s5Sdnl6i1fDTR7kOD2SgPD2dovP0K7oUz1I69ff1vWsUibtMm1aiiPfwMY2mN5mAGv+LjSnAbLRKWznhnAoMAUZxiZHicaaFyperghgqKIzEVSAhJn13EePhJ/q4WI11oUGs6+EFIod7CkzDem2WuWMfwHSw9QhqBHYDrB2ztiDOe0njvyGkSQ2lkzaUrmaNjvZ6lFApSgtnZhT8wQvj1P6W5sozarJIozKN39SC27qT1AYFCYRjSjCZQdh5A2a0QSNlel24aMje5A51Rjbip3VIMHqA3HSFjcD27b64ecmS6nZFcTXeQWA/ocUOJkchAPIni+4yP9nN8tYVyU71OS5EMiSY7RUBi6gzxsEHEblH76d+y666HaGWH2dab4Y0rRSwVvrS9mzeuFlmtO1Rtj/tGcjwxniGtBYTd/aQmL/P8jl2c3/IEzXqTqtB5c3KFPfueopawODFfIXalykM9PufOT1Foeogw4KIS8MiOASou/OKVc/jNOk6xwCRwLhnjH0/kcb//n647j6TnEpRW8GautNUKLp4ltJs0zp1qB808/Az+tj046/uG3+T90wftD4G2HPj7HDAGPl/e0cXLk1WaN+mFdSUtnp7Io4S3Zljd7h3fzoIzrn3hI1/7Jpts8tGREr57avlXf3Gd53d3bZD932STTdr8VjhgNvlo2KHK61dWbhuB2fRCDs/bnF0oYbsBuirYM+Syt9PE4va6v2k94Okd3fzi/DKjuQj7+tPUnICIrjGcs6jaKSKE6KGPUBRcRWe56vLgWI5fXFjlwYGdpBbmkKsLhKqCEkuC6yBTOVzXBxkidB09EqFaKOD3j+LHE1SKdbJZi2LDpfjSK6w+nOWdMui6SnfCQoYh4/kYQgh0RSKk5PJKjVxM58EujdbFE3TFrhWzD4mlTPRkCiWTx6isIsYmiN33KI23XuHm6H2tqxd1+/7byjrcTEu3sJ78KsbMVdyLZwCJPjqBMrwFJxJD3Kboorq6SGt6o2Gs2LOV//nGBQIzgugZRNJO8X7h3DKRPb30RfhMMFXIxQzm3Nsb9buTFqqQv5NKKkII5NLcLc6Xa7hzU8TqFfxY8nO7ptAwUBOp22u60+63rbBt+G919hH7yrfwzp8mWFlAicTQt+/F7+7DXy+66ykqkQcep/nz72POXeZbdz/OZCFDqbzKA+MD7NejGKrC1oxBz+xpYmacv75coLkeERegsFJ3uVxc5ZEtnZxcaIGUZCIaigxxAkiYKioSEbbjABUBo51JfnZumYiu0t1coby6CrR1wU1NpeYErNYdir98GYxOtFSGiZyOErYzwiKqyuXlCiPZCAhQkViaStOFyUKDlb4UPTcF90cNFV1V8IJbe3JgWnR3WPQe/hG9faM0rS5UGZBxa0QzMRofsPGbb7DByX2NH51e5Fv7e0mrGw0Ytm6i7D2Evn0P+SAga0Xx1yP/zFYV+/Art3UU2O8dJj44QjOWuuO1/K4TBgERApBeW0JjvRk/at2mMAwRW3eiz8/gLc9f/zyo1+muLPKV1kXKO4apDW/hu+9cIb22up5NYuJoFpPLNWpOwEDaouG0jUT7J/qx5krca1ms1BzcQHJ0pkylFVyvZ5aOaPSlLY5Nl8hqgphbZ19nhJeutojq6vW+2xPVuDvlMffLU4zEtbbky/o1riyt0j03ixzdgjo4ijhx5LYyXub2vXiR2G2zMz9rGlLnzctrXC00CEJJKqJzaDjLeFpD3BRo4CkqkQefpPnC9wmbjeufqzLA3HsP9vzMxhMHPvZbL2M8+TVayme/7A3DkIGo4Nv7uqk4IUEoSVoqcSUg3HS+fCKklPj+B7ehJ3TenW9ybrlKfyqKkVeJGipDaYvOiEBbnIVEnOrSNGY83pYMkpLA9/ALK9Qnr9Kxr4SXyrG/08DJD6J/5Tkab76MqUjiEZ1m00OUCzz1lS/xw8k6ixUbQ4QoEZNMV5an0h7Zk6/y3sTDzF6cIj8BimXiV9vFymdWqxwa7yYdt1ir2STw6MzFsUOFIJTcNZTjyLFzuCgcL/k8+qXnKbz+InE0mo5PqdkiPjBI9z1PMbdS4Xwl4EI5Cr7JxNgW7h5OY3zIWk1heKuTc5NNboclfJ7b2c2Pzy5Tu0mOrDNh8eTWPGLdgC5Ujfdmb2RZH2uoDD/2HMHf/H9Q8r0sOCHFkoPaWGP4qVGO6/UNewnFdzEba+zrjhOfrCItgZbvIJfJgawxNhrlvUbA7qhPRHoEMuTpiTxO0F5HZqM6nREIgxBH1fEfeIb3LixzfmaempXAE3DX7lFipsrp+TWCULK9N81fv3QU1a4TjxioqkK97nDVVnlnoQGlVcxMlmuCfRNdcS6//EtG4mnUcgFUFVSNwNBQmg2EbSN0o10TDlBiMRgcwbvDvuE3jVTkznOpIq7JjW18V0spSas+f3TXIJeXSrS8gKihkjMFqvztaJdNNtlkk002+SA2HTC/g1ScgMZtopfycZO1ls+R2WVyVjvF0Ask55ZqLK/VeG4ie1t5MhmGDMcFf3igj0LTxw1CwqTFxaUKJyYrPJgMGU62OHp1hcAPyWUz3L13nItrDkuVJq+EEfbc9zXyuMRKC2i4RO57lNKlSzjVKkokQnzbHvBcwniSqtTRHZ9k1GSubNPyA8AlJ1wKdcnphSqTlo0ufXSniXRdhK6D+f9n7z+i5LqyNU3wO+dK09K1hkNrUGuGYkQwtHoq9SBr9Vo56NWrh1mr5j3oVbOcVFet6u7MrpeV4r2IF5oMQTKCWoDQGnB3uFbmpu2qc3pgDgec7iBBGQBp3wiwa+Ka27n3nLP/vf8dIzJMzs9XeaCQR3nNTcE3u3cAx7Gpv/0yfqOOsecg9q4DZH/wd7Qmr0AQYAwMofI9NO8wQ7hlOYid+zF37Qfd7rMjVhYxL51FWBZG/xBeKkuEwDRNwisXNr3eyOY5W44IghDCKmYYEK1/tgbemCzxg/0FxKcR1IlCHhjOMVNqbgkim1JwsDf1hbYfU9Xq7Z+gFASfbaNq37BxjjxI46XnthwTloW9ax9KKQzDoBpKSrEuYg99jbQM2g2H3xOA0VrTzBZJfP/vENcuUX7+H+lvNulOZNFRCW/XYU7NlPCqknQqxmK8wExpGgAlJNNrrY0sybcmV/jOoQFOzKxRaQb0p20Gckm0UpyfW0MKOJwzGfDXyExPkQ0U7uBOODfP2vr5dCUd5iqtjfNrVWpkvQbPXwxQu7o4VGzbSFUDxWrNQwLorTb2E6sNBgbjGwGntKk40J/h5PVVpO+hW01AIGJx0tkk3f1dxL/6HeITl0jPX8To7Ue7Do2Xfouz5yDB8M4N0WrjbydN3phc2VbkDiLFmfkaTw7FtwS9NrL6TNqpRuv3J1ld2xRo3kQUoZYXoSPA3BFSCJx6Fb00h/Y9jEI3Ya6AL97fm/wGLcvB+eq3sRfnCCevgJSYY7swLBv9x1+RnZ7gmpHl4EAOMdaD0Jq50OCN6WV8L6C2WuLIQzuYL3n86uwCBwayTJR9xiyHt66XWWsGxGyDHcUE5VaIIeDJ8SKX5ys86Vbh5BuIl2f48oMPMNw/yMmaybwPwo3z7Hia8n/7T/j1Jg07hiklwQ0Pd6A2OUF6116aqSzxr3yL5p9/d3NcSYmz+wDsPbR9r6RPGQ+LfzqzQKl+875ZbgY8f24BvbeHvTlj43rRWtPM5Il992/QczOolUVkOoPputTeegVV23pvVtUyslqGTOFDn5u5npkdvU/FxXvRWmMT3GLBou600KrDx0BIk9emKpyaKQNQaZZvHhtKMyqWqfz8v2D0DhJNXCaRzpDo6aJarpJMJbETcYKhcZZ9iQwlMUdiEWDs2ktXdzfh5GWs0CeeKSAGR2i5Jt/bX2SlpSg3Q2KWwQ6ZxTr1Gq3DD3KhYuP0DbDYCDkw3M2bZ67RvhoFvzs1xXcO9jNX9dqV5q7JjkyClG3y1uQyfrZApqeXmGPyjgG7vv23hI0laosrDO/agZq6wuW//4/Mr1ToHuxj5L5HeNMtcGKuwpof8ezuHLIj+HX4BNFaU7Qj/vpoL8uNiIYfkXZNCjGJeUv1QqgFDf/mPLLWCnklPcIj//f/B0sLS+hKmWyryayR4mevT/PQ3iEsS7LWCJGRya6kzYF0iuTZ1zC7+3AHR/DefYP66y+BVsSW5tkzupfLb75NfXER03UZ2neYuZGDvLUckHRM9hR6sYFImPziwgqz5QiZzSMjwcJak9cvzvLEUJrv2KuoTJyFZpPupMWDI93ESnPtBKvBfqbjcWbLywzYDsqJY1gmURBStKG6uESrJ0WC9n5NmVa7V1q+CwyD2INPoCpr7b1joYfmX6A/5KdFwZX0Z2PMrm1N0hvvTpGz4XbuQ+mYRZ+r0A5AdNf2m/o8EAmD4EM0DOrYRnXo0KHDp0tHgPkCIm5T9NyfS/CrswvbevxOlxost3L0OGAIgV2vQHkVEJDN48VTxEXAcKL9CdcbmoVKk2/YJRb+68+JOQ7fHt+Fb7rUVs5h/OI1dn/p+xQHCxyfXuP3l6foS7sMZ3M8PJpnz4/GMX/7M1Suh2knz0RT8JBcRXSvooMIKQVeqNbFFxBSEol2to1lSlSzSTh1FW5pLioME3NgmNA2iQwTM53bsAeTmRxG6NN4+XdEYYiRKxA1GzROvEG4toLx1DcIpPGBVS/bobUmEhIjDGi89BzB9QksSbunhBDE7nsEsf9Y+7nvsRNTiTSzlfXvsM36abXu4UUC91Mq8eyPC76+r5eXry5vBNOzcZundhYpOl/cgJJSqt2g/jYI2wb3UypNug1aa6LhcWIPPE7r5FsbjXWNVIbYE1/F7BvCn1/hretVzs6V8cK2R/bB/gz39SextqllEkKg5mdYe/0VFpqaSNnUVyqI5bdwp6ZIPfB1Xm0Ihg4OE4V6Y4h6od5kUbHaCDg/V2Ys5yDzMR4ZybJY8/j1mXZD86e6DGKv/pbK/CxG3KG0Uqdw4SQ7945TtQwaocKQAq0UCQPQEZYUqHV7lbcmS+zM9+GgkB9g6mDIzcdVFPFYfxy5usTJiUnCIEQIwWBPjmd6U8R0gIrFCTyPhdGjnF1uUm4GDOb2MF5p0TMzgRoe3ySmeEqwWvfe+9EbzJZbqOEkd9qJW3/Q5umLeiF+SKQQOJOXqL78AmEQIAFLasyBYWJPPkPT3NpLYjs8w4K+YYzBMQCaUYSolIh/6VnqWMwa3bxwZoZGoIklYuzb0cfDuxL8+dJ8+7eMQmS9Bqksf7q8zMPDWS4vVnh2fw+vTqwyudKgaUbUmgGPjOWZKdV5wKxS+/U/MOxqnOUZ/H+6xFg6zcDuo4jDD1EN1qjXoLG6ihDbz/Iy1u5LpbXG6xvG/e7fIsqrEAaIVBY/lcX7hOw8DKN9bSqlPlC0EEIwU/E3iS+38vrEKqPZ3o3mwze+Q9OOIUZ3IcZ2tx878w6qWrnt53zgdfQeQmExUws4v7CGAvZ0JRhM29idTN27EsMwWPQN3p2popFt27H1n9wxJX3Lk5ROvoReWcboHwGlCNdKmErR1dNH001ybvfjvHW9hF+/AsE5dh3ez8M7u0iIgEYmj3HsUVI9PczPz7fv+Vpj6IBuG7ptQcyvE/3hFzTOnCA88ABBOUJXGyxX8hR6Ezx8YIR3L8/R9AK8IGJ1tcy3duYJUzlySZuVpuIf3p0m6Zjs6s0yW2lxveKRi1nM5ArUMt3YmQrhS7/ArpWYX22gtGZ5Zp7Uyi948KvP8rzdxeRKnVUvS/ETivcaQmBtWvcX8OLJTq+YLyBaaxyCdvV9TADRFitkS2gKSZtSo31P39ObYc2L+H++vcSlxRpZ1+FQfxdJ22A5WuWXZ+b42t5u/vkDw9RrVTLL01TfnWDhwFMYlknruZ8S8xukMgXsVo3g1NuU/vwS/d/4IZeXlwlbLdaOv0FPvcbYrkdYvmX5tdzSGyKB0u35pl838KdmeG1GMrQ7jXjhN/TuP8TurMOlX/wGf32uEaaF8+1/QTZuIaTJSihIDYwiF2YIkUjTRCMw8gVEvqstra5X1qpMFrXnEEqpj7R3vNsxVMA39hR58WqJieUaSreT83b3pHhsJIOOPvl50hRgV8roagmkCbk8LTfxmViL3qsESndsozp06NDhLqIjwHwBybqSlGttlI+7lsF4dxpz3d7HMgxcS+KIzQuapbrHkGMgzh6n/u4bcKNhomURu+9Rwt0HCdfDPj0Jk8MFF+/FV0FrwlYLde0Cc6VWOwBqSbpszX+5sMhSrb1SXm0EZF3Jc2fn0fv7kF/6K/5wepqV1QZKGgz0j1BdfoV8zKInbbFcuxmsSQ+P8HLTBEL6XEHSr3La8zYtInQUEs5OsfOhY1imwD76IOHvftH+G/T00/jdzzEApFxvdKoxA5/o3AliO/chij347tas9Q9CCZOJisI58QbL75xGIEjHLHqSdrtZ8Nuvkujup9XVhzu2C/8Wb34ZeCRtg0VuePNvvmRdy8CUfHrZQypiV1YyeLSXiq+RAjK2xCJEfchg1ucN3dOHTKZRta0BP2fPIfx46jMPjAdCIg/cR3xsN9TKCMMkSmdpWQ6xSPHitRIXF25mh3uh4u2pEg0/4ss70vCeiibLb9F4+zVqQUTNjxAC8kkXJ/RRy9MM6BVkskDZ1xRcQSZmUW4GNMOt2VP92RhXF8tESrO/J0E+ZiEFdCVs0udfpzw/C7T7WMRtk6hWwUcwEIPJpkRohePVQSuU1sQHdnF+ZhnTSFPHpR4qHBNSdtsOY7Ha2nIOAGP5OOqWYIEQAufqGR6ZOsnBvbuoCwdbaDLLk/Db17Ce+R5KSE6Y3bz0xrWNS21qDt62LX5wLMlA4LWD8uuYon1t3rCQei9Jx+Rmq9o7IJVBOC7a2+Y7CYksbt9oucNmnMoa159/juVKk0AppGiP2e7p6xgn3sJ46KkPVf1x63ODdBZtObwcFjmz7NG0YkjXoOV5/OnKCnu64uzJOaxWGjSuTxJem8XetZ+1psS1TfxQcXamxP7uJA8N50jFbBZrPienS5hozJnjuEIRq6zi1eu4rom3ViZ87QViocfyWkDXsz9g9+G92FfOkJEtWkJSw2LNVyAgsXvPhn2TUoqW7UJX/80v9AkEMZQwWfY0l5fq+KFiJB+nP23hvI9oIaVkeq1x2+PVVkAj0NjbrFj1LVaeRu/Abd9DxJPo1J1bQgbC4vlLq0ys3Kw8u7ZUozfj8u29XTh0RJi7CV9YvHW9RiuC84s1DCkoJGwKcQupFTtTBq1XXqepQlLpDGGtilnsIVxewE6l0Y0al498gxdOTiJjcUwhiJpNLpy+wLKn+MGhHmwdbKrCei+GlIQn3iKMZ9APPoVpu4z2DFO6MEUwPcElX2E6Dt98cBeG1vRlXHqtiN/N1jnqKnp0QNIySLkmg4UUPz05u2kOiSZW+TcPjTBQW2JpcR4z5mwIIKFSKKVpvv0Ke578Ae+uwko9oJi984a5t0O1mphn3qZ+/I2NNYKwLGL3P064+wDhF3sp2GEbVBRydCDD1aUavZk4V1ebTK+1WKx5NIKIQGleuLzC0cEsu7qTXFys8ecrK3z38AA2IUEqy9vpnVy4tMJTVonK4jJrwJJpsKOnB3vmCraC8Ny7pPv7KU+3q68rl86xe+8Rsl1FXKHQCBZrm5NhYmGL5vzMhjDSMh0cAVkTWr//OTEnRsvz2337PI9Uq0KiFSK6+lirRVQQZLqHuWBaPHrkGLHqPJGZo+oraq0AKQUZ1yIxuhv/A+wS73ViBDy7K0t5JEsrVMQsScYC9T7iiyEEwfwM7ux026ssk6cV+2ARxVEB+p3XqV04tbG3Eo5L/LGv4A3t6IjBnxBSSlp3uDmJ65BvDbm3OSowDEWUdQHd7gHa4TPBMOT7/C7veW7nd+nQ4TOnI8B8AXFExFM7i/zmzDxSCnb2ZPjlmXkeHi1Q9yOUarFSg4FsjIxzc/MWMw2M+evU33pl0/vpIKDx+p9IZAuE3e1gjq0DHum2uFgpIbhhuCCwTYltCAzHZnatQW1LkrhA6oh3ri5wcLDIhUpIM2gP09+sGHz/ya9Qe+1F/FCRdAxW6uBmMrSOPs75SQ8B7BY1HKPBNdem5W3OqDUF3F+0icKQoG+Y+GNfofXOq6BCdKuJiMWxit1oy0YsLxCsrYDS+Gfewa/XcR96Em9g9I4XelJKzq34lJdXyZ050f57oSk3fVpBxFg+hoEivHAKo3cQ1TuI2d1LuNiuDIiWFzh05CBX51Yxuno2BK4bHOrPYIuIT1MLUUrhoG5aqeioUy0OeHaM+DPfo/Xy7wkX54D1bLk9BxGH7if6C2W8KaVounFw4xuPCa2ZK7e4tLC9bdqFhQrHBtJk3zMj6GaTa9NLlFohdS8kYRkU/ApqZQGpFK3jr2E2BbHGMcwHHuLRsQK/PTuP8R5LrsFcDHS7FwK0S9wzVsRDowWs8irVyzet9xp+yI5Cgtlyg8XJ6ww/8DC1d47j+M12HwgBiUKO6NDDTF5YQMsS1ug4ppBAhKEjnhwv8E+n5rb0dTnYn6Hgskn5sFSId/pd1NoKidVlUmHQDkQbBkoa+OdOUN7/KH86d27LuPf8gN9dXOSfDw/ALQ5Wtog4NJDhz5eXt/17H+5Pfyj7Pi+eJHbfIzRefWHLMXffYfxU9o7f64uKaZosnz/P3NrNgLrSmlLDxwsVo1fOkzh4H5Hz0SrXAgT1vQ9x9rdvEhMWjpR4vg9CINCcur7K39w3yJ68y9Q7x1Etn2j6GqMjuzd0j1BpJldqQFuku3+sm1+dnuVLvTbN2Wn6bPAXS8Rtg0hpLEOidERwfYL0yAHyk6exx4bxLrxFa36RUCmS8TjxniFij30ZUej6yKKw6zUhDFGWReDEtk1EUNLgzZk6b0/d7EN1dr5CMenwnQPdxG8jWmitiVm3t4CTAow7iCMH2SLO+F68K+c3HxCC2IOPU3Zid9TbRgjBtTVvk/hyg/lyi7NLDe7vcTp9M+4SlDT545USVxZr7O3PARApzWLVI1SavqRFlwxorCzRlY8jk0nC61eJP/4V6n/8NYQBzUOP8OaVRYTtYPUPEdbb16Gq1yiVa8zV8owk3v887GYNTwvWXvsTweICRCE7v/evOB0pZLGLWORzpeFw+t1Z8jGbv75vgJ9OrGEZkr6UjdYhKVPx5M4e/rfXJjeJLwLoSrq8fGWZPX67/5QUW9OUW6USBXxA4lgfX3wB8K9coLHduv+1F0lkc4S3irifI0wpsRq19trFjRNIo5Np/yHoceEb+3uZqwX8/tJ1cgkHIQSmlNwYmSdn1vjx0QEuroumNyqY50WCd1YChtMu0cWrG+8ZhhELjZDBeBKnXiNauE7/+B7ChTkaQdsiMu7VObRzDLVuieaat8wtAnStQsyU1CKFpr0vlJk8xvXL+OUy+aE8M364kawgr57l0NAR3ggU5VZI2jEpeYrXFz2++dTXMF/7NVeuzm44MiAE6sgjTHkJ9kgDqT7fdk46CkkbkDYA1HuLoTZh6Qh58i2ql8/SWLdxFo5L/JGn8Ud2Ed3m+pJSwoVztM6d2PzZXov6S78l+Z2/oZHOfULf6ItNGGl+dvrOKmb+xZ40k//t/7ztcdu28f12HKbrX/7zT+T8OtwBYfi+v8utdH6XDh0+ezoCzBcQpRQjScmPj/YzU/V57sISWreDHOOFGLPlFhqYLTeJF5MAGxtE/7W3b/OumuDMcczeAUKlkVJiGIKR7jS+56OUxjYkSrfFBzeT4VI1QOubWeM9CQtZKREtL7KQSDPoaMaCEs10gbmmpuRFvNU9xmM/7CdYus6oERLJDFOxLn47G5ByLQpxCzeqYJ18jR89+iXeXGwxMb+G0pqhriwP9SfoWZulld5BiEDtOoA7NIa1uoA1Mo6VTNIKFbK0TLR6M3gqLIuoUaf+wq9JfvdvaKTubKHXVJI3Jlc5kowIm5uz170wohEoUhaoWhWBxjNtYl/+Ntals/iXzqLDgCHR4LGnH+K1mdqm1493JdnbFdvYZHT4bNFa00hmsL/xQ9xKqe0XHYvjJzN/MfHl/Sg1/NsKZ0pD2Qs3CTBSSlY9RS1QGEIghGDACmlNTYOGpGsibQfKdSpvvIyTy7Fr9x7Mg328PLHGQqWFvW5xNpqPcXamHZQtJBxyjgAVcaw3hrLjXJeawDRwLYNCwsI1BG4hwUptjRomO//qb4kunyOcWUJ097Eay/HmpaV2FZYKGUqYpC0Nqv279LqKnxzt58x8lZlyi1zKZc+ONAMpc4snvghDdKuBEUXo0hJheQ2iCGHbGPkuRHcfMy1uW/G1slZjVZnc2oFFKcW+rhhz5SRXlm5etwK4fyRPX0J8iPKX9vuFO/eTSKbxT75FVC4hYwnsg8dQw+NbhNkOW2lqg9X5xW2PNfyQZsMjGQbwEQUYgNUQVPcgduAzJgyWah7lWhNHKUzHoisd4/rrp2i12htSHUYcLrpbKjukgCODWfYXbf7FQ8P45SrxmEM88LAtiVKaUCnijolrWZCI4cRNnNkrRLUy2ce/TNhq4s1cx4jFSe7eizh8H54QtDCRAmJS31G1jxP61F96jubxN1CtJjKewD10H2rnAXy5WTRZbOpN4ssNlmseb12v8KXRJGqbz1RKsaMQ563J1W3vUSOFJGlL39ZP/gaBEDgPP028pw/v7Am018LI5nGOPISz7zBqeXtB9L1oaXBqduv3uMG5uSqHumOYnczBu4I1H64utu+zUaTIx21W162PSnWfQtwiRGI7Dq4p0YDT3UM0dYX0N3+AGfpUunYQqCp2LE5Ur25UeAOgFDNrLcZS8fcPwHs+q8//nHCt1L7Zmyb2i//E977yY44HBrM6RlY47E253DeY4cpCW3z5xr4e0kbUbvulFDHLJB0zCZTCDxW2aVBM2AjR7oukHRtB+7qJWQbNIGoHtUXbjlcJgWNKuuPtqvCPgwV4p95v3f8u5lcGCe/CNc/HIdaoEhx/jfrEFYhCzFwR94HH8HuH+HyH0z85tIoYT0u0cBjJx5FCYBoGa42biXFKtwO+AEcHMnSlHNZ8yaXlOuSKaEch3RgIAVIinBg1XxHYccyFWcyUwCgt0l1dQOW7aRk2g91pGoampUxiBvSlwDIEQaTbFtyBhyUh7ZpkMkkSK3OYcQeztEzcFPhS4rsppBO1EwhXFnlkvEZ2fBfNCyu0gojhXIyv7u4i3+My98h3cAYnseamkfEYYf8YbwZx5q6ukk3103dnieife4QQGJNXaRx/nXj8ZoKY9lrU//Q8yVSGRm57a2fLb+GdeXf7N44iwivnMR544i/Sv65Dhw4dOnT4MHQEmC8qWlG0QWZc4oZgNOewVK7z5HiRX52Zp+qFKA2NICIvBE/v7Sanm3jbNLe9QVRZwwpDWtLlzHydpXLAwfQA4ZXzdCVtTKHoStrUvJAoCIhnc7SW2w1SU65FslkmXGhn9hlmu8kh5VUSfotdA6MoKal6Ib/1DMZ7DvHdfUXqszXOXVlmMNPekKI1IpGkaAusd/7A17v7qO8ZBiGIr86gj19HfuOHaMMkVGALaNkuumsA3dWLCH2kVyMq3RKoMS2IpzasF8KrFzDue3zTQk9ISS0yKLVCBIJczCApIxq+pu6FrMZtRvIFGuuVLTeo+xFp28ToG2R9D0LTdpGHHsDedwgiRWS7HEUy2pvl+lqLQCmGMjGKrkB2vOj/4vgI/HT+5gN3aSDCNt8/G9YybppiCSEoK4sXlgUjxT6aM9fJxSxEeW7D7s6PNLG+QQorpxAImiffxhvYQda1+NsjPTwxXuTyYpWFcoPT0+1gpmsZfHVPEZN2FZVQIfGEw9hgF2GtimTdTkhrXAmDaQu3p4BhmzSDJvroI/z+3Qla/s3srHTS5cn+GOKWyiytNTkz5OmRJCFpeooFlhYX0Ns0JFa2g5nOElw5j6rfFEu07xPOz+AcPIZv3dxB3/iMG5KHTKQIDAveE5axVMAz41mODWS4Xm5iSslw1iVr6XYlz4ckRBD2DmH1DmIGPtq08DoZuXdMuRWiiz1w8fy2x30rhnY+XqTEMgQaCG0HP4LupKbLVIStJk3DoVUqsbTQnluEaZLPpXm0ILF7k+zIx5hZa4uWQxmXrK0QocdI2uZEzWLfkSPw7qtE0iQKPSxDYkoBWpM4cBB/agKrbwBvrUSwOou0bNxsBhGFtE6+iRzYwa/WbObKLUwp2Neb4mBvktj7WGlZaMLXXoT566jWuod+o07j9T/hNhoY9z22ITabpsnZydv3X7m0WOXBoRS3k7fyjuax8SKvXFneJMKkXYsnduS29ZMXot0HKlRgy3YmrmeYiJ0HsMb2IKIQZTk0hSBr3XkzjFuDgtsRKEWkOwvou4VSM9gYM9dXa3x1Tzc/Pz1HK4g2ejIEqSx7jh6mdekMlpQ4hkTEDaK5KezxPdiO3Q7kra1ufnMpwTCJ2W2x0TAMqq2AUJjYUm2sA6WUeCsrRNXNa+SoXsP4xX/k4R17SPzNv2XKzCCloFRr8ehYgYGMQ0qGm+7jYdTudZbIOGjdjj2jNUpIgkijBseBV6l5Af2ZGFOlxnqWvyYxOMrFyOVre/MkZPSxXQVl4KM+aN0fhSA+mWqbu4FwZYnmcz8jqqzdfKy0TPi7X5D42rdp9Y105t07RCmFa0jiBoDGdAzyCZvVW/p9SSnoSTk8s6cLxzQQQuAFEQrBbGhx5OgjiOUVEO35VYdhu/owinB2HyCYmSDm1RArAendh1hychyfamAZAlNodnXF+ereXp4/N0+kNNKNQ3mNVNzhO7ty5E6cwnBdrN5+1MwETsIlp6O21a1lEEaK2rXL9Oy5n3/94BAJx2QoZSBDj0ag+PVUA6W7SA71ESpNtRTA+rx6Zr7K0M7MRjXNFxkrCvFPvbP9QaUILpzGePxr24ooMvA3rc/fS7SyiNimIrBDhw4dOnS42+jsH7/gCAFjhQReGLFQaXJ5ocyz+3sot0IWqx47u5I8sasb26+iIjBSaVR9+82YkcnhWzF+fWaRuXILAYzuuQ9jfo5rKyuMFOIkTdhRiBPsOUCrK4s7USMbtyjaoCZvBlX35h1otT3hVbOB2apDLLlxvC/jEAYeB4s2fekBLi/XafjtrKThjIU1M4Z/7RJqYZbYQru3hAZkoYcZN8/vTi3TCiK60w73DWToiRnEnvga6uXnEVq1qxkApCTx1DN48zMbn62WNy/0tDQ5udTijWur+OuWR65l8OTOIgMZFyngaiVk99GHaDz/800++6YUCNvG3LEH/5ZFp1IKT1ogaYtKRORMyHdZ7aCTij69vi8d7mmkYRAq0bbsUdFGoKAn7RK3TRr+1o1g0jEpxAzQ7fG7Fhq8M1vm9Zkq/cceR6z8FFdGyNBHynaD0fSjT6PKqzimwfVSAyOYJ7y+xDurETu6knxpR55Uf5IrrqTcDOlNO4xkXZLvCTYFjotz6H6iV/6wZUgLN4YcGIIoIpq5zmizyQ8PHOBqrd2TZiBlM6hr5IMqTZ3hvURRhBQK8338iwINqb2H8F7+/daDpolMZejLxBBdvdRmZwkjhUDgWBLHdUj2D5Cw2/ZnW34LHdLtQG+vu96rIvzY122AAGu9WXwnCHTHSCGod49gui5ha2svneTRBwju0KLqduRdg5jrcHa+SsMPcUzJuKng2gW6uooc2bebxJ4BmqFitC9Pb1gh61do0UN/QjIQb8sTgQYhJOiIXldhDWVoJfajJ6+Qa1VhaQ57XXyxx3ejTBu0QmTyqBu9lAIf1lYAaEaC1ZklrjWzG+f65mSJiZUG3z/Yfdum8lZ5ldrVi5jxrbJJ6+wJErsP0IynNh7b7t5ygyBSKC24XbGWUBFHuh0GM4NcWp/Ph7IxhjI2MRFuGeqBsLha8jgxs4oXKnrW5/IuV6OValfnrFfofNiwjIlipBBnpb7FIxVo27PGjC19pzv8hXCMm5VYrSBicrnC9w/1slwPqLVCHhjN8+bEComB/RiXruEtL5OO2fSlbIwoQvYNkZqdZqiYYWJ+swBj5Apoy2QsH6cWwZnZOterFVrNFuPdCQ72JEnKECkl5XIFK1/AX7q5llUagjAkunKRfG2N383WMaRgZ1eS+/pyGMrfMrbTjrwlY591D9+2leFg1kV3d9P98KOU3noNgebIQIaWH+FbDukvf5V8rouspdCfQDKIsmysZBpWlrY9bmRyKMO8axNPPixCCIKpq5vElw20wnvnNaxnB/DF7S0TO2ym4BokHJO6F2ISsbuYoJR0WKh6pGyT8WKCL+/M0WW1b6gaGCkkODtfJYgUk5leBnbupnrlEoK2bayTdDEGhjEKXbQunAbDwCv0sbbvEf7DW8uUGj5SwP7eDK2w3Xfwb+8b5Opqg3o9QbHHZEjXiZ/6EzrwiAIPd+8hrN5BfMvGMVpoLai1AlIxG3n0Yf7j2RXCSPPEeJGeWApH6/b1HSmUbleZv5eG35kkbiADn6h++ySNqLSMofW2FWbKspHJ5G3FYKPYc1v7sg4dOnTo0OFuoiPAfFGRBnMNeGt6jRMzFTIxi4P9OVarTc7MlHAtg6RtcKgnznAuztxcmQCIHbqf4BYx4iYC68BRrlZ85srt4JYGXlzR3P/kd+muLVBdmMbKJlnrGmE5UaAvF+dfPDjEa1cXMQIf5cbQSpG1BA8nPGrC5qwhiSKFbtQhnmxbHzkmO/Nt6y0BFC3oHU4RaoEkQoUh1sNPI4TEm7i0vjEUmP1DLBx8kn84W9pYqFVbARNLdb51sJexngFy3/87aiffQRoGIp7AHNpBa2meqHzTjkTmuzZeL4RgqhrxyqVFRBhgCIE2bVpBxO/PL/CjY4OM5BM0gojZ1CDjX/smK6/+Ca9WQwD5vh7ij3+JVjp3RxvYWxsOd+hwK0JKln3JyckKC9UWrmVwdDDDcMrE0BHFhMMz+7r51en5Tb1RbFPyzN4esn4NWg1ELMFL803KDZ+elMvPlj2e/cZf4ZRniF9KYEcKY2QntbU1otk5Jlcb+JGity/LddXuSXF5sYZtGHxlLEmhL4aJBt8nkiHhe8avUopoxx7iYUDz5FvoVhMQWD29OI9+hQmRYaZapS/dR3DtGvmFBR7MptGmCbN1sC30gYMf/e8mBKFWJL78LM3X/7QhMMtsjvgjX6JxfYLM7vswij0o4WDWyugoIownCOMpntrZR9JQ7xu37/SK+MuTteEVFefQM98neOX3NFfalSiGbZM5cj/G3sMf277CkoIDfWnOzLWDDF6oWHQS9A2N8tUBh+Kv/yPdiQQilSE8f47ItGnu2M31K9OEbgIrl2dipc70ag3LkBzqTzOWdcibAbI3i/mTv8acnSI68TphtYI1vINIKcJ6leSzP6b84nMIIZEqQgvRrmcTkoVqC+nEoLn5fJdqHtcrPjvTctt5Ra2tclvFMAqhWm5Xh9Ie42OFBFOrjW2fXkg6xAz9/tZ7KqJgQddAbD3RQKF1sCVArYTJi9fWuHhLT6tqK+Dacp3vHOxjMC4+1jyplOJAT5KzcxVawXsq2wzJfYOZD9XDqcOnSyFu0JdxyYsIYUg8w6bS9JFacWggzRtXFvCaHi81DR54+nsUy/Po2Unq2RQDB/bRyhRwiz08vVRitdakUmuClBi5AiJX5InxLhxT8t/fnaXSCojH4zSaPm9P+lxcqPGjw70kdICbyzEfy5IqKPzSClopwkhjxeLI/iFWzTgQECnNhYUqe3tSDGxTEpY2NUcHc7w5uQoCPCVYrQXU/ZDDA1l8IRl68mkG9+2heu4UpZU1rKFRcjv3YORyxCPvRi7FxyYAkofvpzp5ZZujAmv/EZqfo/nNMAyCbb9rm3BlCafV3JQQ1uH9cUXIM3u7+dWZefxQYYqIHhcGE3GePTTAUEIThT4Kk4uLVV6/XCHhWgRa4EdwohQS7X+C0fF9iCvn6BIe8a4CVk8/3pXzOPuPwMhuJmK9PD/RomW3mzUpDafnyu3KVK14aiTF/T0OUsawV0NaL71D6LX3q8Ky0Mks9o//DYt/+B0rjQogGOwrEOy7j/9aSjKz1n7uu9NrrFQafO9ANzFDU0y6LFa3JnUA7CgkOuu/dZRlI+MpIn9l8wHRtoU0c0Wi21SxBLaLe+A+Gq+/uPWgYWCOb05i7NChQ4cOHe5WOgLMFxApJWdWAl64uIgWgkhrzi9UubBQ5Zl9PeTiEaVGQDFht3s13ELQO0T8oSdpHn9to0pE2Dax+x8j6h3k8tV2ibAh2pmukdK8sRISiW6qiTxfH+vmzWtLOGs1CuWAB4ez/LP9RS5dnqLehOFCmpGsg33tHIlqme8feYhXr5dZEiamFIwVEjwykiMh2xmxQhostuDda6ss13ySrsnRgQwDyTj2E8+QOPogNBsI22Uplue/H5/b0rA+0po/XVmh70gPVt8Qoeli54s033kN78LpTc8Vpom9c+9GHEsIk+MXJ1GTV9BBO/tJxuOYXX2Etsu702XuHy3yjyfnOLtYZig7wFd/9K9IVktkkzHi3TmawvjImYo3KnE6osyHQwixPkYFkVL3/N9PCMFMA35xaobwlgE+u9bkyGCWx4baQdKhOPztfQNMlJqs1n0KSYcdGZv85eM0TryJ9lqEu48yVctid3fzpd3d/K+vTPC/XvDoSvXyf336hyw9/0vqrx9nNB8jCBV+pHAtg/iR+7hWbW+A0q5F3QtREcSmL+OdfgfdamIUuogfOEar0IO6tQpGSNT+Y8RGdyEadYRpEKbzvLUS8uLZaQCeOPAo+TBgbXGOhekVwigiVczT+/Xv0oylENtYFN0pOlJ45RLu019vZxwLgYoimnPTRK0WC8tr7OnOMe1YnF9waAWKdMziweEcvSmH6GN8dofPBkNHPDaa4zfnfAYf+x4Duo4IQ5puAt3Xi2GK960oMg0DsZ6debuAykpTcW6mxPcO9rLaDFiu+XSlYxzMdxN/6wWa8Qw2EVQrmPEketchzv+X/0zYapH46nd5ZWoNP5ZECsFCpcVCpcVYMcEzu3KYKiQwLVYH97CYG8dq1jGrJXKpGLGuLha9AENpWteuIgMP13Uw80XCeApyRSZFEraxG7u4UGNPLretRYqw7Pf9mwrz5hJSKcVYzuWt9UznTc8DHhnNY9xiE/h+fFDAaqmlN4kvN4iU5s9XVvjJoS6Mj9n7Im2E/PBIP69NrDK12kBrTX82xqOjeQrWx7d26vDJIISgUFvlu5UzLF++DMKgObSLua4xpkIbx5AsLJVZrjaJlGZyOUZfsYuu0X4E8K10N0kREMZT5EbT/LO+AaYqATO1gHgixo58jLwDb8xUqbS2Xj/VVsDphRqPDcSx+vrx4ykWlSCbzGJGIZGCkjbJ79jHyYZFzFLkkw5omCm3GE7Gtgi/WkXc3xcn4Ri8Mlnm/HSZhGPw8GiBYtzkZydmGO/O4BpJFnJHMQuSSsunca5Cd8rnuwe6cD5Be1p7fA/xB5+gefx1dHjLuv+Bx/G7+j+xz7kb0Foj38+K0jTbtnQd7hitNYNxwd8cG2B6tc7ywgo51WTEjihcmMTcsRsvk+d8KeSVqRnq9QZSwLHBPJeX66w0fM6shSwme/jKs/tInHyJ5tVzNK5cQMbiyGyBqfwI//2VK+hUBm1pupIO+YSNH0acX6iwsyuBpw0c0V7vNzN5rG//BLdcIgwjqmacU57Nf33lKveNPs6+g+D5Ia8TY9VIEBgtwKM37eIa7eSFiTWPfXmTh0dz/OLU3Ja5LWGb7Mi7d1Wfzr/knjEwTJxDx2j86XcAKCQVP2K13kILQd/QPnQgSRtb92RKKdTOvbi1Cq1zJzfKT6UbI/b4V2il852K8A4dOnTocE/QEWC+gFQjg5evzrddDYB8vG1rtVL3efHSEj883M9ANuKhoTSG3hzECAG17yiJkXGitRJeBH46TzOZISUFeVfytYLGrSwj0LSyBU4HLq9cr9IKIhpByP6BHOVWyJXlOrWVaxxxmhx1fOyJPxG+eh3t+8iHnwTLIXf8Bb43NIZ6+Bih7ZIwNTpqZ8RKKblSifjt2fkNUaXU8Lm+2uDh0Tz398UIExlIZJBScm6utUV8ucFaw6fitw+GYYjsG8Lqm27bECiF1BqJJrbnIK1338RIZ3B27qUpbFavXt0QXwBUo4GansAa2cnkmkcQreAFIaYUXF6uM7na4LuH+xnotvGj8CMtGg0hcGprqIU5dBhgdPUQZor4nY3hB+J6TfTUFYLL50FKnN0HYHCUlvn+wca7mUCYvHhpYZP4coMT02vs7U4yQHvTlZIBh4sWsttBAPKNF2mcPXHzBVFAPPJImpKfvjvNl3d38fq1FSaXa/y/VMT/cPQ+dlx4i2a9QSAgm4yRu+9Bzjk9yEhzcDDHbMXj6kqTn68ucyjmM5jKIZfmiapl/KmrJL70LN7Qjo1Aq2EYNCKBctLE4yl0FFJTJq+s36cAjlcExx7/Dv7cLGnVYjjrEgnJzMQMeS8k09dN8BGuJa01sqef6LU6zcvb9AfJd3PJdzhbWiMbs/jyriKWlJiGQCCYKntEKYusI4nL6LbBYyklnpbUAzCkIGVq2KYnTYdPB601BTviB4d6mSp7TJVjZGImY4U4+ffY9QghcLwmYnUJQ2uE18S7epHI9zAHRzF37KGZSG8JEtSDkLofcnqmRGy9irQRRPzqYpUdQw/wzLEHSAR1TEuydPEyV1/6M5HnUXj4Ma66BWYWVmlUI/qKWQ4N5plYrnBlpcHOniwxKbAsi1+dnqW5bvVlShO9GpJdXuObYg5rYAw1PYU3X6bZbJFq1InvP0z8qW9yeaqOUa+3x3ssjrIdFALDeB+DrnwRYW9/X5TJFFEmv+mxhAz5weFeXr5WYmqljtKQi9s8uiPPUEKi9cfPUJVScu02VTYAK3WPSgC5j7m61VqTMwK+tTtLPcyjgYTRvmY7cZ67h1h1jcav/zvC8/DKPks1n3BylmzvBXq/9h3emVnjaiXE9HzQ4PkB1VZAq5gm5VcJ+mxiCUnLjRNojWEb7M8E7G8tE168QlCvY+49hEu+3ZB7m3O4sljn/r4EluOw58d/xdQvf8bc/AqBshACRvfsxH/wKUTTJp8yuLhYQwgopmO0tIF1i+mOrSPMtRXUWomjXb3UexLs7krgh4qFcoML83UQ8MrEKk/vLLJa9zataxerLa6stjiQN7fcn4QQBJjUA42UgpSlN3obvh/ScQkOHCM+Mg7lVUBANo8XS25KpPg8EEUR9q79cPLtbY87IzvxY8nPjeXaJ4kQt688VErRpVpkTz+PqlbQrSaq1aQFiPMncb75E/582Ues26sqDaemVykmHcaHshzqT5M2FY5QiNBH++09l2o2QAgWyi0MKUn39XJsuJeZtSaTpTqOIXlyZzdHU5rEuy8TzU4gXRd33xGinn7KuT6eu7SK7TX58+XrrFab/K7S4I+GwfBgF1eWa3i6wd/cP4QAXIONPdvZ+Sr7iwWGEppvHezj1WsrrNbb1mdD+QRPjN1MFvywGIBdr6BXlkArZL4LP50l/IiXm60irEqJRivAt2O4qSQ4FtHtNsWfAlpr1Mgu3PIaweVzTJc9ql6A4ThkHn2a35RMKguz/OhIP1ljq2jlSxPz/sdI7jmArqyBYaKzBTw33qky6tChQ4cO9wwdAeYLyGozxA8VIZLVekCpGWBKQT5uE3dMBrIxdqZBRQHbuadrrZmUaZ5bbFFuBkAFKSo8MZLh2PJFTj3/e7z1jD7TdXn80Scwh0aw4jH6Mgl+fnqW5bpPyhRMTV5jTgWc687wvaOPY838H0QIll79M9bXf8iV8xN07coS+pKBmEbfsllsKoOXLi9ubD6TjslIXGCimVqpMV6Mk73FpvmDfOBvPe5JE/PBJ0nuPYSorEG5RFguUZu4jF5vBGicO0XsgcfIpuI0mu/xio8iPD9A2govjDBRZGxB1rHQaN6+tsSu3ACpj6CXGIB18TS1N/+0qV+BPbwD9/Gv3tNCwqdNuLxA67f/SHRLo91gYRazpw/3y9+mdaO3xj1GxdPb+k/fYGqtyaGRm//XWhNFEbF6hfqFM5ue6yzNcOjIQf73d2apGi5/KlXY3ZXggQPdABw3knzvm4P0BQ3KvkIS50LgcHWlwf7BPL84PU/NCxl2FNcWppgSmn3DXTw1shs5eRGUovnGn3B6+vFMm4a2OD5V5dJilUhpjgznGcjEWKk02deXRQnB5FKF/lyCvz+xSNKy+L6zxsV/eg4Rtr/zmpAceOgIsUeepmXeebPtG3ipLPFHnqbx6h83CaLCcXEe+wqXrrTvO2vNgLVmmZFiknIr4o3JVdKuRV/SIm4ZfHl3F6MpuXUzKA0ulSNeu7ZEuRnc3KDvyJE1onu+AuteQWtNXATsyxkcKKTaAQEVbrLrEUIQW56n8cKvMXMFguVFvFNvI90YxsAwraUFxLmTJJ79MUEyjQwDlO0QKE3MujnhNIOIaqCp+gE1L+DEXBV1qJ+pUsRXh5M4pTqR5+H2DXClsJP/zytXNhILJishp2ZNvnOwj9JchdNzFboTBidmlphaa3DfYJbetEu5FaKAkYTEe/s8s1euUthzjPQDj4PvIx0XKSKswKN19dLGuUW0ezcYXb3s60ndtkGwF08Rf/yr6Df/tOlxYVnEHv9a+355y9jVWpORId/anaMa5NAa4pbA0uEnIr5sfP4n9k4fjI4i4mL93DsxnrsKQ0qCk2+hWk2akaDS8nFMcJHopTm6Vq4jjCGaYUTStBBhgLAdolqVmdBjV1JiTF+heeEt4l/5Ns1iL27QYunqFLNNqJh9ZAqQPnMet1zl2ANf452VdmAwF7exDEnNCzYGpNaasNBF5kf/gsTSAkbgoR2XK2EMYWV45/I8V5frG+cvBMyVanx3fzcOATG/hf/Sb2nNtas+q0ee5M0zqxh9g0S3WF4pLak0W0yWGmRi9pa5/+xclQPF4mZxRRhcq0a8cm2BtYaPAAZyMZ7cUSBvffAcpJSmGUtutt76nM5b5uAw7sH7aJ3e3DDcSGWxjj1MoxPs3UAIQU2ZLNYDmkFIMW5TiEscoTfWmTeex+wUwfWJLe+hvRa1d14j3/0gpfdME8s1j+Wax2jeJRfXhED86MOEC3NE1TUAfC/AkG1RsKevyP/3jUn8SOOaEo1G1WukF3ye8pYQy+3+TP70JO7+I9T2P8b0YpldGZPlatvboJBy2ZuzScQ1VtbkciWk1vLJOnKTJeWGW5aOGE0KBg730Ag0QkDaAh19NPHF1Brjwknq77x6c48nJO6BI9hHH/7Q/Ydivkf98nne9RyOX1+j0fRIJeM8fN8exgbyn2kikC8k5rFHiMYPYVyZJCMNyrEML9ZN1urte+trEyWe3Z1Bb2MpFmo2Eis36FyPHTrclUgpab338tSC6aUSvpLcmtJiSYHxCe4TOnS4m+kIMF9QIiRTpSbN9cVkGLWbl4oqeJF6X//oujL5+enZ9yxEBZmlaWb+/CLFmMVyQ5M89iArsQKnl3x2HUlyesVjobrCW1NrAGQtGCj0wOo8i6tVznf3c2z/ERpT01Cv4to26e/+Da97cWbOLvDM3h725IyN4Oaap6h7IVLAIwWT/NwlvHfOoKOIwf5h4t2PYPQUiaJ2VvpwLsbrE9t/p1zcJm1vDuuEGsJklngYUvv9L7e+qFWn9cdf8vQzf8ffL5a2HPb8iPt701yYvRnsv7HJDSLNajMilbj93/l2OKVFaq+9yI2JS6Yy1EYPcN1IwFyV7EAvaVMhOh2CN2EYBt6pdzaJLzcIF+awr19FjO+/J4PhH3TGt01yq1e3ZMBGlTVitkEr0qB8Wq0WJ+sNYImYYzEch/NhjNGxAc7bMf58bRXbiHhkZzevT6xR80IMKbCDJoZof/C5qSX2Hh2hd+oyaIWqVZDVMq1cPz89tcBasx1AemS0wNXrS/z+d1dxdERLC9xiFw8dGms3OW4F/LhHsvqL50haEnNdwNRaUbpwHjebxTjy8Ifu5RFpjdi1H7fYS/3ieaLyGvHBIZyRMZrJLPn5JRYqbY/vhG0SacHLV9s+1mm3nWlc90N+c3aev75vgKyxuZriaiXiubM3q3mUhsmVOss1j7860kdc3D0WFV8Ebg0MvRe31aDxh1+ivBbW4Ai1P/4aANVqwvwMcmAEs6sHzp9ALy3gNRsYmTyxQ/fT2ztEMemwXPNQQrBQ9fEimF1rMJCNsVxrcXauwtJKhcfzO9gxUEbvPMCrl5c2LmKlFKZWSCk5Pl1mf2+aayt1CokMfdkYrm1Q9iL+dHwapaEZasackMfSO9g7olm4cJGFW77P7qxDVypHOhmnUmsQjzkMjw2hbYdYJk3MNtFSI7YJwiil8IfHyfcNos68iyqtYBR7MEZ30kxmbn+vjMKbyQXqg+9PHwalFKP5OG9PbZ1zod1rJm2LjljyBcBq1WlOTyCEoNK6OX41GhNN7dxpuh/egWtItJBg2oRKo9wkkRSMjPWQnvkTqtWk8cdfEfvxv+HUTJXn35llpeZtjNt9Qz082p8htTBJX9duutNxLi2WWakH9GdiHOpL4RoQhrDQ1Pz83CqPZwxiV6/RmLiKdOMsHX4a7SlMKQiVJp+wcQ1YrHpcWmlyrMclfOXPBOviSxvR7jc2ex1zZCfRenKBRqMBrUBss4uL1puD31jRCiGYqit+febmHKSB6VKTn56a46+O9pPszEEbSDcOxx4hOTxGcPk82mthDu9A9A/TsN/HnuwLhpSSiarm+fMzeGH7hhsiySccjgymKVVb7OlO0h0TmBLCS2dv+17e9CQjg0cpNbcPS9xaadWIJXC/9eO2oDM1wUILiiND9LgRL19bpRlE3Ghz2BM3MVbmOL3kceDYDoozV29+5rlTqOIYIgxAG5iG5PvjaboXr9B65zwa2L9zF6uje1kw5U3BZZ39vSnU+jpCa42pA9Lr2sjHiSNaS3PU3/zz5ge1onX6OPFCF2Jk9x3vUwwpCa5d4tU1g3ev3uzfulKq8Ks/vMmTX3qEo8Ppje/xWSAMkxerDmdaufYDDc2t9qiTq3XqYe5m4kOHDh3uScJI87PTC+95VJBKJalWa9y6O/jhoR7eryC/Q4fPEx0B5gtI1jUItN4QX27FNAS1VkiUdZHbeEgLIbi+5m1pTDuQsglPHafa8NlRTOI+9AT/OOGxcm2WXaM9/O70dRLZNFdWWliGJIgUQaS4XmqyJ1eEtUXOLVQZKwwzM72GlU3TiuX4zZpNtO6f+/rEKiPZXuz1yMqNBej9eZPUq7+hvDC3cT5e5TSZletkf/w3LMeLrDYjQjRP7+nl3OzapoaJhhQ8ubO4yQbiBlJKwumJ7f+QQhDOXqe/ucSDu/t55/I80bo4ZJkGD+3r5Xq9edvgt/4IYSnDMAgunePGpCVyRS4NH+OF83P4/irCmMMaa7JnoMBjw2nMT9AH/F7H9Jr41y7e9rh/4Qzm+L5tuiTc/aRtyMSs9Yq0rQzntun0y216PEhJTAV894Ex6oFGK81avcncUgU3amKVV7Duf4i/f/kijXwv9VBwfq1JJmZxablG3DYxDUEsMjZdURdLHoPZHGFpBSEEZhTB3AwPuR7TboKWYVNaXuHc2ycB0LKdHVOdmuTVZoPvffUBupIO9vWzNHTbQmVTaFeDd/4U7p5DRB+ykklIgzOrIS9dDki4e7ATkkYrZGfJ4JG45okdBf7p1CxBpOnNxnn5WlvES7sWrim5oViHSnNhsc5jg/GNAH8oDF6fWNz2aq97IZNrHvvzxj0p/H0uWZpHtZoYmRzh9WubDqlGjViugC6tUv3DrzDHdqFMC1WvEcxeJ/XEV/nBrt380+l55poRpiG5vtagP+PyxHiBFy4sArBa9zkRhuzafYiZpkI1aiRiMWpNHyEg4VqA4NWJVfozMabLTebKLRpBxA8O9/O/vHyVlGMiBYBGac0r52fou38PcuIqar2iRQC61cReW+KHu4aZCIpUUkWeP7+ALZqkxBKnZwoMdaX46s78tn0jlAZraJTIjrUtjJTCU+p9s9+1NFnzoeKFWIakEDNwCT+xMV6MCfb2pjk/X9n0uCkFT44XMHX4iYo+He4B3vuDr0dLL15f5lsH+3hlsszsWp1o3bpob1+WvX0ZmsEIzvwsqtlgoebzu9fPUWkGm97u3PVluvcPMq5KOKbBfz0+TbB+jdW9kK6UgxAOriFZa4V8udvA/+V/p1xrV0sn+oc4fX4CrxUwOjpOYNokTIG4xcroWFrjTWxu/p4oL9Cdz7C4WoFGDdLtgKUh1iu+C3EuzW0VInd1JTFQGxpkJAzemFze9ppo+hGXlxvc1+N0bHxuwfBbaClxDj9IlEzh6Q/uTfV5RwiBj8FKU+FFCsc2ODNfwl8XX3wtmVhtcGGxRiuIyDqS07NlHhzN8/BAivcr+HcM2e7LuA2GFORjJtzS16tlu8jxfcwOHOT//fok5RMlfnxskF+cXQAEpgFBqOhzBXK5iTIE16oB3ck0qnbLvDF1lVRiJ1GzyU/25oj96ResLi9vHLbOnERcvMCT//xf8/fLN1e03SmX0ayD/oT3WKaUBGffve1x/9RxrKFxfHFn9gl2o86cMjl5bXbT45Zlsqs3S2p1FiPewk4k8D9DKy/9PtZnnbVwhw4dOnT4PNMRYL6AZG3Bob4MV5bqW449vqPI1aUKe4vutvZYUkpW6s0tjyeEIqpV25nkmQznPZtmdYmY1yCTSXPt5DyHkzF838eQglCBEhKhNZ5hYQuIIkUzglApIkAnC0QrNxdilVZAK9TY6xlGWdcgE7PoqcxuEl+gHXiKZbOcma/zQtnfEJuElOzqSdOXjTO5XKMn7XB0IEPReZ9G7LfxyFaGiczkoLzGA2ur7Dm0hxVtI4ACTeJdDu+e3j5Lt72hsNiuKfL7IaVEVdY2/r+64yi/e3catb6Y1VGIUprTs2VycZsjXdYXftO4gdYbjRu3RUXrQcV7LwXDJuKJ8SK/PjO3RfDb05um4Gz/naJMDiOTJyqvVwVJSePwE/zxeo0/zS4R+j5ISV82zpdGspw9MUt3b5F3Z8rUylVktpu4IRkvxMnGLdaaIbu7ksRNjfTimwSYQGkQ7aCTqRXBtQvMvvYOTT9kqLuXru/9hP/tlzcFslAp4rZJ4Ic0l5dYXikzVoijZ1eJmQbylnCSAGK2gWo2EGEIH1KAWWzBHy4soGn3g7rBu9fXyMUsDhQsfnJ0gHdnKsQdm2YQMZCNkXYM5HvKBReqHkLcLG1rhu2A++2YKDU41JW9rQ1Uh88OIQSq3g7OCCnR7/1NNJjFbqq/+of2veKWOcNs1an/9P8g9eiX+D4Gc7kBGqkic+MFJktNXri4iL+elqsNAyWhJiSh8girFXr6MjS8AGlaJGIOlxbbwVvTkG1xMYrYUUzwh0tLZGI2oVJIwDIkTWGRd2zema3yeP8gtakJABxTYoVNRCJJ/J0XGXvwa/z9uWt0+T661Wx79mfzTCzXec02+fJIEnWbe6RS7zNH3oIvLF64UuLKYm3jCk06Jl/f20N/XH8i85GhQp4ayzCUjXFipowfKnozLkcG0nTZamM+7PD5JnAT2IOjeFfOk3JNVho3rWBDJIl9Bzl/sUKsoXlkOAcjWfyWh2NJag2Pq5enuFKXPNM7gGzUuLBYJ4wUYbR1jL59bYl9X7+Pt8+uYJkSieTwQIaUa/MP785gSsFoPs5izec7vZJcJgfrAoww2mtdAp9Ys4KTL266d0RKt0XT96w1jZmrPH74y/y8XGv3vLiRc6A1DwxnQakt833SMdnTFd/U+LsVta2cbsfEapMH+mKdtSJgKUXztRdpvPYS2msnapmFbtzHvkIzV/zCBoeFECwHBr89u7hRsbzaUiRdk/sGc5yZWWO+0iJYv3bOzFX4/uFeFqst3pxYZSwfZ3DXfvzZ69u+f3xwiGSxAFNb96XHhnJkTL3FmWHVE5yYqTBdahJqmFhp0JVysAyJoL3PitsRtTDCEAah0ohb+mRqrUiaIGybtaUVvpZqcXp5ZeO4ZRoYfpO+lItz8V129j9AqRVyoDfFzkIM+1NIcBMqIqpVbntcNevtip07XeNGASuB2FRBFI85fHk4RfTmS9RXVlgd7CaVdHGPPky0cx/BHYo7H5UoitjTk+Ls9PK2xwdzceKG7lSxdujQoUOHzyWdjt1fRLSiO2Hxw8P9jObjZGIWI/k43z/cjy01pbrH7UxDlFLk4luz5itKYGULSCEIe0e4ML2KrlXRYdBuGmgYLJTq7MjHCIIQ25QI08ROJNqNw4VkR1cSs7SAQND70KNUEwXGu9NkYm3bBUOK9az3NnEZ8aXdPeirWxtn5xMO1Z1H+M0bF/BbNzeeWikuzq1RSFj83dEenhlPU7DCTQ2Y3/t9jb7h7f+MWmMM7UDE47A0T+rdFxk98TtGTjxPMaoTj9s8NJrf9rUPDOfImB9+dRlFEUbvAABGNs/ZUrAp2CRsBy3bCtW702u0dOcSv0Fou1j92/+WANboTiL54byV7xa01oymJD88MsBIIUHCMSkkHb6yu5unx3P4GkoNH8PY/P18wyL21NcQTttWQw+N87u5gMXrM/QWM+3NahAyt1ThD5dXGN0xyJ6dQ8xNTiNcd71KBUwUvhcwno9R8wIEmsh2MHI3x//OnENUKSObNawde/CmJpDrGY+NxXmi0iq6dVPcFYBlCBK2gYFgpVTl/qE8yYEBHHOzoJRPONhSY6TSKOvD9YAxTZPTc9XbZswfny7jI8mZIV8dS3G0L8Gh3hRZW2wRXwAKCXtTkEZKgWXc/jpMWJ3ql7sFrXVbVAfCShlzcGTTceG6qGq53RTXddHrlkBm4BNMTxKtLiG0wrh0itSrvyHxq/9Iz+JVTs6sbWQJAyhpUCxkyHcXGR3pw0qlkCsL7O5J09OdpxVEGFLQn4lhSqg0fZp+SHfKYb7cIm4bGzKxIQRNYWJ391Fp+hCLt88V6EnHSB59AG9lEeG4TNQV3loJ3aiDUgjbgfV73sWFCtXw480X0jB443qFy7eILwA1L+SXZ+aoRp/c/dVUAbuzkp8cKvI3R7r52o4UBTPsBJG/QERKYR1+AOnGiFmClHPz3h/r6WU5P8S+/hyuY/HHd6/xh9NT/Pndy/zh+ATdcZOZ63NcnV2l0jOGdBxWfY1MJLfNwWgEESXpEGrBnu4ke7oSDGZj/OHCAn6oaPgRQaRxifjdG+fxdh3ZCPZGi7OMdqWQCFS1jHzP/X5HMYFjCoS9eW2tg4C+S2/wo6MD7BzpIWGb5BM2T+3s4tu78zwwmGJfb5q4bZCwTY4MZvnhkT6SMsQwDHxh0sLCNE1c633mIPveXPd80kgpMSYu0nzzzxviC0C4skj9uZ/iNqp/wbP7y9LUJr84Pb8hvggh8CLFpcUap+eqFNMxarfYAPqRQuubF9KlpRpyaAyzu3fjMS0koZbgxrGPPsRozuEb+3roTrm4lkEx6fD1fb3c3x9HvycxQErJ5ZUG9rpnjQAWKi2U1kyu1pkqNVistmhhYjgOQsBo2tkibqTHduDaBpmeHhqnjzNWTJCJ2TiWQS5uM9SVoT9tk1ic5DvDLn91qIvDXTbup1QrrwwDI1e87XEjnUVtV7l+G7TtYL5nTfzocJbm735OY34OTBMh2harjddewLx+td2v51NEa82OYoLezNbKfMuQPDL62fal6dChQ4cOHT5LOhUwdzFCiE8lMBdFET0pizcmltnbncA2DIIoYnKpTBBphguJ9QaCW1+rtWYo62CbclNAaa7qc2zfETKL1xGmSdiqb4gaplaYsRgLqxUODxe4tFRHGO38dS1t3JRN0vA4VHCIl1NY33+MP4U5Xjg5j2MaHOxPc39Pmphl0Ag0LQwyjsDWESNpg2Y2TjRn4ocK05AUEjb53iIvrPootb3K+M5UiZ3ZnjvqkxIVurEGRwimJzcfEAL74SfRAyMkuvsJpycQpoU5soMgWyRQmsPdLtlYH+9cX6PSDNrZYkNZRtIm+iMsMJVSmGO7EWeOI9wYK++xnDIKXUTr2UsNLyRUYN97BR2fCpHWOIfvR1w4g/Y3Z4PKeAK5Y+89HbzTKqLHgW/vyeErsKSk5Gmeu7DMfLlFKrHGaMbiYG+C2PrmUWtNM9dN/Ht/h56dZN4psHB6CWOgSMaysPqLLC6u4gUR5VbAyOAQXUEZ1axhDe1oi6vrzKw1eGSswB8vLSEQaEAUejDdBF20GKSB0z+Eue8wzetXiRo1cnGLqtc+FytokXIkzWY7q7edZaxxDIFtGIzlYxzstgmPHub6+XfxQ01i525E/xBSCFpRi2Ixi2e7H6opp0Kw2rj9ZrruhQQRmAKUiohJzZGBNC9f2Zq9JwXs604S3ZLJnDQUu7qTnJ27ufG3DIkhBV4Qsbcn+aF71nT49NDFXoxUlqi6hhISc2CIcKadtWsk02CYIASy2EskRLtqplwCKZGxOKzff+OWpO4HqFNvcXj/V3lzoR3QE8CXdncD8PxCkz5L0TO+g5VGQNKWJA2T+VpIxjV5ckeBd9Z7nSQdk6xr8YMj/YRKU236XFysIhBkYhYt32bHQJ5k6QJOT5GuYpb04fswM1nqP/t7jESKtdbmOUcWujeq1IJI4ylF4mNoMNVQcG5++yClFyqulz325T45wVFrDVGIwfsXN3b4/NJMZYl/6yeEF04xfH2SWgCNwV2s9o4zHdr8+OEdXFyq83wY0Ig03V0pDnfHmZ+YpN5oX5MeBsKN0ZNPMpkv4qyVaXqb54RCPkNLG8QsA8cw6E5ZnJgpb3qO0pqEY1IHTszXeGRgkPr1KZpLS+zfJ5hOxVDvkfrjtsmB3iRNU1B56gc0l5ZIaJ/UzEXUyhK6skbX2Vf47g/+JWXTwRACiwilfDIGfHUsRXMk3a4CNTRRFNDE4vRsnbNzFUKl6UnHuH+0ixNTK9valB7oS3UqMAEr8GideJPtagu010Jdv4bce+SeXid+VBbqAXXvlj5LWhOz2sLd+YUqe3v70UA+brOvL03cMsklHHb2pFkoN1AKPNPG/sp3sCYuUTp9muVKA9k/DHsO44kco8D9wzl6nBA/0tgSDB1tu1eSUrYri6WkO+WwWPU4s1DhyfEiPz0xS7R+LVYCTa6rlx1Gg+7K3Ka1odUzAF3dPNsbZ77qI07FqS+v0Jd2SMVsYhK0aaB1u/pToJAq/FQLM6JI4ew/gjdxadt1rH34fpofokrfd2L0dOWwrOsEQUgi7hJfnqbcbIAQmLazLmK170utd9/AHhzBkx8ukenDkovbfHtfkbOLDc7NVQmUYjAb49hghoIVvZ/DaYcOHTp06HBP0xFg7jKEENSUyWzFpxGEFBM23XED6xMude6KSfb0pDk9u3kDGbMNHh/Lo6Pbf17aiPjWgV6eO7dAw7/RgBBmkj08/ey3CKau0ZNNMOmHBIVe5kScPUMJTk0t8/L5GX5wdJTJNY+Ly3Uc0+DYSJGHh8Yo0mJhbA//y5uzTKy0g04NP2K61CBumyxUqgTr/t3ZmM3Tu4oMJQLSe/cxOj9FpNsBUKEVOC4rjQCZTKKMrcO81grwVTuo+kH4hon7xDOYF8/gXTyN9j3MXBH7yEP4vQNEGugdwhgYRWuNf8uiWaiQ0aRgeH8BX4EtQd5mQ3GntFJZEl/7Hv7Jt+h2LWYADAMz34VOpjeel3RNbCk+2Q7I9zjW4CiJb/0Y/8RbBLNTbRFteAfWwftpxpPv29fgniEKsYGFhsHPTs62K8wA6Ue8OVllYrXO9w50b/R70FrTdOOI8f3UG4IopzZsThK2wY5ikqBWRQQecnmOlCpT2LmLVTZn4QWRYna1yr96aJjzc2vMl5tYhsm+0VGO9iVIhA0svZ/qf/7fN9TdhCVJuRbVVoBeuM79Y9389twCoImZNyPBrmOxszdDxVOs2RmS/+z/gmo1eeHdKyydnAMhifV0c6xvgMNaYnyILbLQiq6kzUJlq7UiQMo12xvU9bdUSrG/K8ZaI8O5+fKGBYxjSr60u4uCozZZZago4uHhDItVjzBSDBaSVFoRrTBiX0+anGt2osd3EZ7lEPvad2i99Byta5eJH3sUa2CEcGYKMlmM3gGs4R1E61VjwnFpHn2CeStLRUsKvYMUrQTOlZOkI40I6/Q7NwfEgyN5rq02CMKIrCO4HMKengwZL2Kp5mHriF1dCZ4az7NY9ah5Id1Jh4MDWX55dp64ZVBuBm2BZmeRerPFUtXDcQUP7xmg6PTjqsdQwqAlBAJIfOVbtN56lUK8HVQRhonR1YOK3bTKs02J+zE7YHqR3rCg2Y6Vuo8sJL4QgmMkLVZbilaoiFsGOQdkJ6v3E0drTSORRj7wJO7Rh4lJg5bpkAsVByRoFdKddjm6oxtDSryWx8Wr1wjW2kKhaUgSyTj27i+xw0rw1kyM5NhO9PwcfrUKQmCl0tx3/35M2+KhkTwKQdwShLpGNm5TaQZIITClwJImiUKetXoNEU8BIBCkzr7B3z74JO9GKa6GJgIYKyR4YChDpOG/n1lksRTAcgvZrHJo+AAP5Fawl2eJPf11mqaJrUN4jzOPUtGGYBBFbQvAX55dYqFys4JjcqXGRKnJ/cM5Tl1f3XSN3j+cozcuPjW7HyENqqGg1IowhCAXM0jI6K4UMaTnEVXLEI9vezyan0HuP3ZXnvuniRCCtW2Eu6RtYEpBqDRKwa7uJN2pGH+6vEzMNnjlKvRmYjwxXsAArtc13YkUl4r7mdvfj4FiIZAsz/kwN8+x4Ry9RYWhQtz1gb7tilyarHiC7kyCcivgr48N8k+nZrlWanFyusxPjg1wcbGGa0oqzYDHjo7zWCbCfOU3hLaNsBycXfuRew/RNCwcAnZkTcwH76ceVDAkoNu91W7sCayRcUIn9qGSez4qXr6bxNPfoPnai6hmA2i7G8Tue5SgZ+hDvZdSinQxx5cfOcjzr5wilYih5y+AYWDEk/Tm4lhCb2x9ovIa0vMh9ukKMAAuIff3OBzqjqEAV2pUFH4utmEdOnTo0KHD7egIMHcRQggma/Dc+ZlN1SWFpMN39neTEJ+cCGOokMdHUozm45yaK9MKNGOFOLuLcVLG+y+AlFIMxiV/e6yf5UaEF0VkXYu8AyFJYn2DPFLXnHxzhvlyk0sX5nhyXz87erJMlhqcuzLHYF+OnxwdYE93kpwRoFRAXbo8d36RhCkYLyaotEIMKTjQn+W3Z+d5fEeB7q52wKjWCvjt2Xl+eKSf3t5BrN4BmLu+sVoXrSbFvMtyPMF2IY+kY2G3e3zfES3LQR56AGfPIUQUEjluOwvpltffLqiktUbosL1Jvt2G4kOglKJZ7MV++hscasLZMEFkWESmuenN7x/OYYtoi0f4F51mOo/x5NeJeU0QgsCJ0fiAptL3GlqavHJtZUN8uZWlqsd0xWdnWm7KRNdarzeUv+V9AB2LYds2BB6ZkUHSKcnDDYvfnJnbMpalFAwlJeO7c7SiPFLojaxc37CQfgvh2OhWEyNXoNW/k6zpkm3WaFyf4Mj9Q9SFzZmJhY3rKZuO842H9zLb0jx/cppQaQ4M5Hju/BoZp4vMcBYMA8+yeXViFcs0OPwheh9FUcSB3hRn58rbXiv3D+e2NPW2dMDToykOD6RYbQRYhqQYM0ka2weWYgT86FAvZ5Zb/PTELBpIuyYLaw0uZ12+sbeI+yn4iXf48GitaSQz2M/+CLdcQnstrMMPYloWKoqInBiWUoTHX0fYDksHn+AXb1+jXp7CGhwhmrlAyrX44SPPYlRWSVkuj4wN00pWWWsE7O1Ns3x5iawjN+45F+bLJByT/T0p7htMY0nBb84tUKo12VmIs38gy389PoPSup2d6xgsVFr8+swcPz46SCtQPLajQK+r0CrCE8aNL4MGWn0j2N/sZUcAr7ditDCIjM3zxf6+DElTfywt0DEkliFvK8IUEvYXInhZ1Ra/PbPE4i1B8P5sjK/vLhL/BNdxX1SkNKhFglAJXBNc0b7v+rK9pRGhjwMbQnh3wuSFSou6314NimI/ZrYIYci+wTy5XUUaUUhWKr69v48/XFwktMcwPY9Iw8HhIiPdaSIE//X4DKvNkJ2FtuXSbKXFYDaGa0pM0RbfnXyBgZRBT2OZXDaOa0lsGWBcOc6z3/orSkZbvI1JTVPBP56cp9oKQEpEdz869DnZCrDHj/H4o0/SFPKOq8Zmq8Em8eUGQkVMrTb4/pEBzs9XsE3JeDFO0RGIT0kYVNLk+HyDd6ZKBFH7/GOWwVO7utiZMbbYSv2l0YaxxQbuVmQyTfQ5WifeKVprsrGt4QITxUg+zlzZwzUFe3vT/P/emKKQdEjYBpHWHJ9e4/RcmX/z8Ag/PbFILhVjJBfnYtnfst46cb3Egzt62C70LwyTWigItOTaSoPjkytUfM2V5QZdSYfvH+6j1gopeyGOafB39w1iSk3GNcmbESoKkc/8gFiriTYMAtvdNBdFUYQ1PIp9sYtweWHTZ8t4AuvAsfY+4TMg0hpveCdudz+yUmovE1IZvHjyI82fPrBnRy+F7jzXluvE5TJmo0oubuNKveneIhwHbXx2loRKKcx19fcuux106NChQ4cOnwodAeYuohoZ/Pbc7JbgxUrN48Wrq3x7dw59m4bwHwVDhQwnYGxvHo0AFaFUcEdxaKUULorBOLRNVUJQ7SS6pu3SagQ8NpjiTRUxueTx6vlZnt7fz7f3DROXkMkkydgaqVobCUX1oB0cBnAluAmD0XyKa0s1vry7m5NzFV68tATAcD7Ow6N5rq40KPS52F/6JtbkFfwLp9BhiDkwwpG9ezl7anFbxePYcAaL8EOJIUopPNMC89PPDPogtNZ40iSdknz9vh384eISjfXggikFR4dy7M7ZqE7G7baEWhPa7SDIZ5HR9lnTiATz5e0rOgAuLdXZk9va+D3vCvqzMWbXbnmthkga5HJZctkETR0wmpY8e7CX166VWK17WIZkV3eSh4Yy7cakGtz1ZPpbdUnfjePs2k8tkrweJDhzeQXPLxOPORwbO8ZA/xDf6G5yf3+CcjPEsi16ilkWzAS/PrUIgGsZrDUD1poh5WbbP9+VeuM6f/t6iV2FXpwPkdJbsBXf2N/LC5eWaK5X9VmG4L7hHONZa/uKNRWSMyCXumHfELzvUKoGEa9eXqA7YaK5mVk5s9bk9ckKXx5Lor4AlQH3Cr4w8LPv8WJfXzFZB+8jUeyhUqnzm0tlvHgGK9NF1GxgChjbvYO/n/II10IsNyQVrvLYjgJjGYsXrq0Ru2W83qDuhZycLnGoN0HcCHlmT5G3rldYrvtcXqzhmoLulEvKale1JItx/EizVG3xN8cGcPFRt4lgaK3xTBvHEnzr/h08d35xw4pICtjTk+bBgSTqfSpf74SUqdjXm+Lke6yZoF0hNpRx0J9zoTEUFr8+s7il6fnsWpPnLy7zvf0FxCe4jvui0cTm9Yk1Li1WCSJNyrV4aCTHrryFvM34j4uQ7xzq5blzi5QafjuxwLLZ0Z/n4R05/PVxr5SiPyb46yM9lDxNpCHjmqQtTT2A//zOLPmYCUIyudrg0R1Frq02KDcDeorxDcVHGSYPHjlAbtIniNpzqbVzH3JsN03DxL2RFqQFs9WwLb6so4HItMG0eXexyb7BPPE77DdhmiaXl7deezdYrjSIGQW+PJpEa92+X3xalS9CcHUt5PVrq5sebwYRz5+bJ3tskMJffim9iSCexNm1H65d3HpQCMzxPfhf0Dm6J2G17fW8zfcuV2q+urvIsYE0Pz29wOGBLKVG+953vdTEkALHNLi6VCMft5kqNVmp+wxm3rPOBJRu7wH7bxkXQgjWQoOXL5eYKjWYqQa4puTRsQIL5TqBijGz1uLv37rON/f1ML1c4UB/hrG0gakDlPI2AvuBhsBZ7zuyzWKtZbm4X21bpAWXzqKVwhrZibFrH8146jNN0lJK0bJdKPbd+uBHf78oIB8TdI1mcNMPUFu4gt6mh6Gz+wC+G/9c7os63BlJHfCtIfeOnvth3AY63PsYhrzjsQGQ1d42zxcYhiLKuty6EYrrECU6fYs7fDHoCDB3CUIIZir+bTNHp1bqlP0c6U8hMSX6hL2fQ2Hy8vQqtaU19sVDHjrcg9aa1aVZXrp8lQP3H2S8W22pGBFCc9OJtv0P25KMFBP8w7uzKDTxdVuiydUGc5UW//yBYbSQtEwbsXM/5s59CKUIDZMs8My+Xl68tEQraH+WIQSHB7Pszrtode8HgrRSjKYkf3esj9VWRKTaGV9pU31omzPDMJBKoaUgfB8bmQ73BlKI22ZrmnJ7qyERhTyzu8hzF5aZu0XAySccnt3fhb0uWgoVMZYUDB3qohm1K1+ShvrAAK5SCn3kYV547RKXrlzfeLzR8nh9JaS1onlsME86lSMbBShp4mHw/MnFjecmHJOFatuKUAOlRkB/ytrI4qt7IV4Ezoe5V2rFeFrSd6yf1VaEUpqsa5Ay9Ue2CzQNiVAaJdvZy1cXGusZn1t/k4uLFR4cShHv9Gu6JwiQBL1DrGQl9dI0CIleXUKXPXYf3MVvLi5TqnmM92VxsxlWai1+cXKGbx/qx7nF5suUgt6UgyMUJV9TagQb7u6uDnhqJElDW/y3k/OM5+NIblbqmWhMAxotH1SIuoONsNaabkfx10d6WW1F+JEm7RhkbA0fU3yBtt3eQ0NpGkHElcXaxkhPOibP7O0hZUSf+7jOSkttEV9uMLvWZLWl77rA871CIEx+eWaRxerNCo9qK+D3FxYJd3VxqLh95aPWmqIV8VeHe1jxFH6oSNkGWRt4zzpQa41FSPd6IYRAQShYrkM9aPcbGsnHqTQkWit+eKifP19dwo80rmz393psR4GelElw8AHMfUfblbbS2HJuQgiWbjNWoN03qRkq4nc4XrTWGLeZ26Ettkpx+2rtT5JQmLw9tbjtMaXh5FyFr42l7io7wiiKsA89gNGowbXLNw9ISfzhp/CyhS+spW9MhHznYC+/ObuwqY/QcD7O0zsyCBXRankkDEU87bDaikg6JuvdPpmvehzoTiDwubhY41Bf/xYBBtgyfmvK5B9PztHwQwIka4125cw/npjhx0cHqTZLuIUYXqTJJWz+7v6B9R6m3ocODZuGQeTE0PuPYew+iNCayLTaotvnpPIpiiJamTyxh56g8eafN/fE6R/GOHBsk412hy8eIgyY/G//5x09t+tf/vNP+Ww63FWE4R2PDWiPj+2eb9s2/npLgRsU/vW/QNl3Lu506HAv0xFg7hKEEFS92wf6lG77q/PZVQZ/ZHzV3hT7sTQzoQ8LVXQUItw0DPSw0IjaFTfvIWXBQC7GdOnmojxuSS7N12kGESl383D1Q8WFxSqP9HcRRu3NZwDtJsjrC8idadEOqjYjIq3IuSYZW79vj5t7DaUUDoq+jXkrYJvEptsihCBWXiW4cJpoaQ4ZTxLbf4Swq4+gk41wT5I0FSOFBFeXa9se39dz+6a7CRHw/f1FVlqKehARNw3yrmxXjL3HsswgJLk+RO7UPmA+tLgqklhDY6hmHaSBjCeILIeTM2sc6E2SkgEIA7TG14LaLQ2R/VCRdm9GpFqh4lbl1jLkbQWm9+NGVV//xnUUfqjr6AaWVphLcwTnThLVqxhdvTgH76Pi3f7mHUSaUHFP3N873KQRKBRt2z6R6yKVy1F1EqyFVWQyReQm2pY2YVu4fPXaCl/f28ObkyX2ZC12+cvo06eImnXMviGsPQfJOAK9fmmqKCJmCDKOpFLffjC6toEpueNM9naAOaBno9N0CJ9gDNTWAc/szPLgUJaKF2IZkkLMwCVEfQH8MGv+7ddxmvaY6QgwH43FhtokvtzKm5OrjOf7cW9zIWitMQnosaHdviz8wGvGUSFiZorg4hnqfYeQKxVkOge07ZcW1+rkEzY/ONRHTzpG3NAU4m0rSq0iFODfWEPdRhhKubcfDFK0KzHvlCiK2NOd5NxcZdvjQ/kESVPfaMH2qeIrqHq3X2ev1Pxt9wF/aVq2S/e3foK6eoloYRbhOMjeQbxku1fPF5UbIuZfH+llpRnRihRJ26TggogCQsMkZpt4oY9AEUZqXXxpk3QMgijCMSUCtrV7tQxBT8qBRnsPKKXk8mJzo7o/UnrjdUrDW1Ml9nbFmVqtEzeg5flkTAP1IRPIbBVhzF/HP3cS5bUwB0Ywd+6jlcp+LquSI4Ddh0j2DRMtTIPnIXv6ifJFmrITFurQoUOHDh0+TT4XM+3q6ir/6T/9J9599108z6O3t5d/9+/+HePj4wD8h//wH3jxxRc3vebIkSP8j//j//iXON1tUardCPp22IYkbkk+0UjJp4QtNAnbxA/9tpVC2t4UIM0nbMR2aWRRyBM7Cvz05NxGxUrTV1RbIY4p2W4fWvNC5hqaViBIOesZjbfYe2itiYvglp6a4ae2+RRCYBgGWuu7Kqvvg3Dnp6n9/udwIyC/soR//Rqxow9jHnpg2x46He5udBTx6GiW+UqThr95LO7qTtIbl7yfuiBVQJcNXTZABDr6xBI/Vxo+SkiUG4dYfFNT4VBpKl5EKnbz+ZaEhGOx1mhny1RbAYeKKQwpiJTGNjeLhHt6UiRNtUUQCoXJiqfwQkXckuRv8b6XUiKlRCn1sXpUGGjkmePUj79283NXlvCnrjHw2I84d5vXJWwTxxRf2Ozae5WUa4AQeOtOPtlMmsmaj3ZiaMCUm8fmSs3DNOArO7LEj/+Z8qnjG8eMpSXGlq4SS3yPZqFnQ+zUUcjRgQzXVxvbnsOxwQzGJ3h9fhKIKCRnQs6EduMzdVed36dJ3Hp/FTV2j6zj7jaklMyWtxdfABp+RM1XuLdfRn8obBUSvfx7/Il2JUSmdzfRyhJqbRVzbHc70QdYrfusNXyO9iXIGCG3S4ARUlKLDEqt9pyTd00yFozkbCxDbPRIuZWxYpKM9eEEk56YZE9vmgvzm0WYmGXw2Fj+M0s+unUfsB25uLX9PuAuwEimaHb1tfvx6M09Mr7I3BDve29JUrlxK7NRHO7P8NLlJdDt8XYrB3rTXJgrYQoYLSS2/PYCeGK8i560y8L6VCek5OpyfeM5Nyq4bogw02sN7h/MbBzPxqw7+q0Mw0AIQRRFmCpEv/ES9UtnN46HK0uIC6dJfOMHNDIFhDSoRpJSM0QKyMdMEnL7fn/3ChHQSGUQ6SxCiHv6u3To0KFDhw73Eve8AFOr1fif/qf/iQMHDvDv//2/J51OMzc3RyKR2PS8o0eP8u/+3b/b+L9p3n1fvTdhkXYtKq2tG6QD/RlS2wQV70ZMIo4NZfnDhVvsB9bXxAI42LfZdkAIgRACrTUFK+InR/u4sFhncrVJ0jHoTzusNV3KDf+W10Ah6dIIIt6aKnFtuYYUsLsnzZOjGazP0GdeCEFdmVxbbTG1WiHhmOztSdLlgPgsUg0/BlG1QvPVP94UX26heeINkiPjhOsZnx3uLbJmxE+O9nNxqcHV5TrplMuusTRDKQvjM+7DINcD0UqpzYLJdlmQ76lesUXEscEMf7y4tPHY9GqNb+3v5bfn5snHLfT6jnwwG+OhofQmKzQhBJOrdf7h1CIr63YvAhguJPjangJNT3Fpuc5Szac76bCzK07e+mhCjFNdo/buG1se140ag+UZElaOerD1S983nCMmom2zQjvcvWQci7jrMLNUp9wKaAaaTNwiQpBzTZz3LDMsQ2BqzTGzxsL0BSLHJFLt7OBszMKJfFqvv4T1zR/dzJwHBpIGD4zkeWdqdWOMCNrrgvGsjdZfLJn8xprhbgwaFWOSXNym1NgaeO5Ju+Qd2ek2/BHQWuOat6/IFWydOz4OxuIcrYmbNlT58hy9hTTzKxXC5Xlkd//GtTjenSJrc1uhRAuDM8s+r16bxw8VfZkYxXSccjMgZQseHu/hlSvLqFuSh7pTDk+O5T5QMJHrFpc3As+GDnl6NM14Mc7JmQp+qBgtxNnTlSBthJ+Zk5JJxH3DWX5/fqsNmQAO9afv+kSlu/H+creilGJvl8tiLc35+QpxS2IZkkgpntrVxVq9tXG9PD6WZU9XAq0VKzWfTNziSH+anljbOvcGAojZN4UcW0I6Zm8k47imsWGz65iSwQ/oMaalyWJTc36xSsNXjObj7LRDzFuu843nei28N/+M8fUf8cZ8k7cnS4TrX8C1DJ7e1cXOjIG+x+/l95rAeOteokOHDh06dLgXuftUiA/Jz372MwqFwiZxpbu7e8vzTNMkm81+hmf24XFFyPcO9fL7i8vMl5to2gGbA/1ZHhj8+A1yPwhpGEQIDNi0EfywaK3ZlXcoDeU4MV3aWHTbhuTJnUV63HbyvRCCSmRyvdyi2groSjr0p2wyRsgjA3Ee749heU2KTpxKo0UxblH3I6SAmGUyX2lxtD/NQqVdrq40nJ+v4FoGTwzFP7PS8VJo8tOTs5sqDU7PlnlsR5EjPQ7iLl6gR6tLRJW17Q9qTTQ/g8jk76kFeoc2WmuSIuCBXocH+uMUiwWWFhY+0ybYSpqstDST67aCw9kY3UkL25T44dYNVCZmkXO3VoLsKsYpNXOcXL+flBo+piH4v315F14Q0PIjelIORVdsEZda2uAXp+Y2xBdov/1KzeP4bIMT11eJ1i0rJlbqvHO9xLMHehlJyi2bPCklltdERiHKtAhsd+M5QgiihdnbVhbFTr7MD779r3lusspStX0utik5Nphlf9FBfcReMx3+MkjD4NJyg51dKWYrLaZWG5TqPj84MsC5+So9aXdLoH28K0XSguj6VZIWpLJuu6cSGq0VWkO4vIDbqOKlCkgBqAipQh7qj7Gra5DZsofWmr60S84BeZeMGyEElgoxvBZaSIJYguiTDpIIg7VQMFVq0Qwi+jMuvQnzM024+CBsIr61v5tfnV3cJMJ0pRy+sbcL+TnoPfeXQGvNUM7dlAF/K72ZGGmbT6SpvGmahFfOb3rMuHaObx5+nBfsPLMrNUQYYlgWu7tTPDaa2SKUWEJgNtsWoHMyxZ8uL6E09KZj+Frwn99u90AbKyToTjQ4PJghG7MIg5Bi0qYrbmC9z1jxhcVcLWC+0iBumwxnXTJmu9rM1CGjCRjfl0cBQiuUCj7TNhZaa8ZzNqsfsA/o8PnBVAFfGktzpD/NbMXj6V1dhEpzbbHCXLWFZUgO9me4rzeBqYN2DyAEEt3er6nNAmoYhhzsTXN1ad1KV2t6kzaRajsjHOhLs1RpknAsvr6vh7S1yQBhE1oavDXX4M2J1Y3HJlbqvF1d4buHnyD1zgtbBmQwP4O/usbr1+qbHm8FEc+fmyd7bPCutpO0ALPVPvcgliS8h/dxobRYbERMl1pYpmAkFyNv604yQ4cOHTp0uOe45wWYt956iyNHjvA//8//M2fPniWfz/P1r3+dr33ta5ued/bsWf7tv/23JBIJDh48yN/+7d+SSqX+Qme9PVpr0jLgB/sLrPngR4qEZZAy1afaMF5IyZInOLkeGEw4BkcHsvQnBcZH3CEZKuDRwTj7exKsNkMMITZ5YwshmKzBb89Nb7JeSDom3z/UR19tDu+tV2nNTzO06zDjqovJ0MGNtY3rS15Eb9oh45jMlTYvwM7OlTnal/hsGlobJi9eXN5i8wTw6tVlhnOD5O/mq+yDUu4/hhDX4e5AKYXQeosd0qdNJEz+PFnhzOxNK5Q3gH29ab5zaICfnZgmumX82abka3u6sWnbKQkhKEcG5+bqTKyu0J2K8c2DA0RKYUkoxNr3E7QEJFpH21bULDYiKq2t43iokOQf352hN+Pi3HKvCJXm9xcW+dtjm/sJOFEI507hnT2BajSQySTuwftR43vx5XqW5vuIvtpr0euX+PHBftZ8TRApUrYkaaiO+HIPUg0kc1Wfn52cZbyY5IdH2hnxXSmbR8fynJ2vMJy+GZ3JJWweHs6iVbgRNNDr8+utwzbQkoVawK8nlpBCcKAvzY6cg6MCcgbkC+b6az+4h8VnhQHYs5N4x1+jtbqMsCzsHXuwDz9A04l/4OvvCCk5vezz5/VANsDbtCsFvr2/mxh3h7ChtW5XHx7uZqWlaPiKpG2Qj0nMjvjyschamqd2dvHipaVN10zcNvnSzsKGpeQngX7vvVwpYide5tn+IRqHd+EN9WHHXNLW5p6CUkrctWW8t1+lPnsdpMRLdvONvQ/wYs2hkI7xX96ZBvj/t3ff8VGV+eLHP2d6Jr1PQhoQAgRC6F1AQEEs6K6Cir/Va9l10b3e9bp6r4qLDXftu66ue22ra6OIqLBUBRSRoghIlxogCUlIz6TMzDm/P+KMmWQSJiGkft+vly/JmTMzz3PmPOf7nPM0nCqcKK6kqNLAwXw7I1MiuKZ/BKqj2ueaMW7lmpHP9pyhqOLnBj69TmFK3xhSQ/WeB8mun+pv7fXY1aA6m7wPEF2PTnUSaYSoqNo4per09AqLqr2fNekJMaiezoTuEVBNhbG4QB0ZPUL54XQJAHpUEkPNhMaFMjktGnuNC3uNg23HC9lp0DG4RyhxVho8mC+owqvxxa3cXsXXOQozbD1Qc056vaahcKa4ssF7oPbW6YecUqb0DO5wI7kURSGgKL/2GpR7ChQFU48krEPGUNkJO9RVK0ZWHzjLqaKfp2HdAozqGckQW0CrXveFEEKIC60jPxr2S15eHmvXruXyyy/nmmuu4ciRI7z11lsYDAYmTZoE1E4/NmrUKGJiYsjNzeWDDz5gwYIFPPnkk57hrHU5HA4cDu8pbAICAjz/rvv/C0HRXEQYqe2+grN2gd8L9H2KonC8TGPlvhzPw9CzFZBVaGdkSiQjenjnu1k0lTADhAW73/tzXspVA2sOnPae91pRKKxS+WxPLtOjNALDYgkoPovh4E4m90onLyqJY+ZwnEYTIQEmCsqqOJhb3OBra5wq1S4INDYvzS35bUscCtlFvivoGnC8sJLoOEuHHC6tKAr6sHD0gUG4Knwv1q639fDs21H5U17r/rsj5+VCaUneFUXBgYGCKhc1TpVgk4FwM+DHzY6iKBwpcXg1vrjtzy2lR3gANwxL5MeCcorsDmKDzfSMCCDUoKL+NDqu2Glg6a5sKn9aD+pseTX7c4pJiQzk0j4RGH+6ntTPY/10eBpf6qxDBeDSFMprXLXXvXrLNthrXBRWuegRUPuZBjTUbzdRfWivZx+1vAz7lg1YKkoxDB2HS9PQx8Y3ekx01kAICkGv1T6gqL2+u9Au8PW97v87An/La92/O1L63TRFYV9uGaoGP+aX82P+z9fQ1OggpqbFYNSB3mAgzhpCQogJM7W90A09kuGHHQ0+06HpyFHNnC5VKPhpxFZeWRX7QwO4on8U5jorcrXVMan7G9ReE/ScrapdSynIpCfCosN84hDlX/wbdwHTamqoPvADzrwcLNOuodpoPu90FNTo+Kreg3eAvLJqtmaVMLlnSKMPddvjPDLhIs4CWBTc6+BwHt/fHnloTl24TdKlqQyIMmMLSeDHfDvl1U56hFlIDjMTqHOhaa2TBlVVMffsQ82JIw2+X8nOwmY04kjvR81PjaB1824pLaJi5VK0muqfPkuj6MgR1BNZTJl5Axt/eohY5dKorHFhUfUEGvWUVTn4/MAZhiaEkRKob7zOqNfz5cFCr8YXqF2g/PODeUQPTSDM0HoPWJv6fXU6HeUuHYWVtZ0mwi3uDmN10t7EfUBH1JFjzrk0J7a2FZ3qfT+rqY2nxdexN+BiXFIwadFBHMqvwOFS6RlpJTHUxLHCatYdOOMVE44XlDMxLZqBUSbPeajX6zmcXRufjXqFxIggzEYDTlXDHBNI6YkTlIUnE1ivAUYXEU2W0wD4XseooLwGTdGhKC2/v7sQ51tASSEVqz5Gc/yc7pqsYzjO5BB4+XVUBoU28e4Lrzl51uv1bD9V4dX4ArU1jS3HzhIf2oM4S+crq0IIIbqvTt8Ao6oqvXv35sYbbwSgZ8+eZGVlsXbtWk8DzLhx4zz7JyUlkZyczO9+9zv27t1LRkZGg8/8+OOPWbJkiefvnj178uc//5no6GjPNpvNdoFy1LaK7DVsO5CF2RLQ4LW9+ZVkJtfmubXz++2JQgwmC4afFkx1qio5pVWcLa/myMlSkozRnDjp4uL0CaRm7YTc4wTnZTFg2BgCRk7km2Nn2Z1TToC1Ye9ao14hMiwYW0jDPPmjOXmtOlvhMw1uitFEbGxsi9LRVsLHT8H+1doG24090wjslUZYQMuOY1vxp7zW1VXKbks0J+9HCypYuS+XksraG3oF6Bll5ZJ+sUQGNv1Atdrp4tDRLKyNlI2DBdWM6mWjX0KUz9edLpWNO0+jGM1Y603xkFepUaQayezh+/et74yrGE6VYw3wToui02EwGLCYTFjrL9YBGM0W4uLCAHCcPE7Z6eO+83P8R0KHjsYY1wM1PBTDwCHUHD3YYDfruMlYknv6lebW1pHO+eaWV+hY6XfTlVThQvG5ntzxoip0ujLun5pGZFDDsuIKDkKX2g9ndpZnmwbkFVVhHjuBk04z1jonfqkDzlTrGJUSd0Hy4g+bzcbxsxWs2pdLof3nh3xJIUYmOhwEWn3EiSo71tIiIgYOOe/v/35vbqOx9lSZCyUgBFuIxefrbh3xPGqutsxDc8pqW6YrDhiYdGG/w2UxoTtyANfZemuY6PVYho8lxNawLGqqSsWurQQY9GCoPVddmkaA2Ym9xknA6aPoQweg6XRUVztRdDosRr0nFgHklNWQGhtNZKDJZ7pOF1eSX1nYaGzNr4b+ia1/naj/+zpcKt9lFbHpyFlqfprC06hXGJUSwaiUKMwGva+P6TQ647WiJbG1I/J17BOAIXWqT2dKq/g2u9BnTPg+x86AxGji6sQDJdtBaHAgvaOCWP9jPrmlVbXbVZXewUFMjAvD+mOdThE6HeaxkygtsmK1+n5UEh8ZRGx0VKs0nrTW+aa5nFTs+JoAowGMPuq1J48SevFlHaKB0Z88F9prOFZc0uj17kiRg6FDE1o7aR2eS9Hj8HPRSKvmZEZi03WjuvQdZWi16GYUqjT/Zuow6hT0HXyNZSGa0ukbYMLDw0lI8A6+CQkJbN26tdH3xMbGEhwcTG5urs8GmGuuuYYrrrjC87e7opKfn4/L5cJms5Gbm9vphvH6kletI6+oYS91t8M5hSRHWFs1v4qicLbUgd3+U48WBYqqNXKLK9FRexPr0KC03M7ynSeYNSidsB2fA1C96zvsSX2INptw1lT5XEcio0cYSlUZORXFzU5Xc39bBSM6Vw3l1b5HBUSZQ8nJyWlWOtqKO79ltiSM4y+levc2nEWF6MwWzOmDcfTuy5niYigubu+kEhfX+AOFpsqr0+ndY7wrld3maG7eKzUDC3fmUFHvvN6TZcdVU8OU3qFojUxPpygKqt5Ecbkdu73a5z561UHe2UJM+P4Mu2bgwKkCz6Kn9X13LI94k8Pr921MqN5IoElPfkmZ1wgYY4QFq7F2ygx7vQWz9YqCWXN4yq4l5xT2Cu95wOtSck55Ko7mzJEQHFo7VVlVJYawCMyZIyi1JVDUxteC9jrnW6O8ul/rqGVWbzQyIDaIw2caxk+9TiEpzESNvQyCzD7TbxlxERzeT/WBH1BrqtFFxqJmDGBTdTCF9oYjEr89lkdKoIrqxzkPtb3T9franvTnM0WK+zc4nlPAwp05lFV5T6N1uLQGp8POpaGRDaZwAXD9uJ/SmB7nlQa9Xk9BcdnPdQYfikvLUCuKmsxDRzyP/HWh8nC+ZbUrHFv4aUSwvrbRwJ03y9gpqAd+oObIfjSHA2NsPObBIzH2SvOZX5PTQc3RQ7jqnafhFj2l9ipKDu2n59TBfOFUPSNcwgOMlFRWo2kQHWSmuLySE3mF1Fh8H8sih56KisbLQUGJmTNn1FYbdd3Y75tbrWPFztMNRqSt+aECs+Iiydo5z4WOfj63VmztiJpz7E/aFYpKG8ZJnQJBQRbyi8rQVZZ4ykGsVaEi0MC/95zmbL3RY8fLFTbn1TA9Lgn11HEM0TbMmcOpiIwhVXFyIq+4YVqBPhER5Obmtji/0Prnm9lRTdWxH1EbiZXVP+6nst8gHEr7NZA2J892zUBRWbnXdMV15ZdoHfr8bqq8ng+HqvHxD2f82vemviGcWLLQ78+O/n9zWposIVpM0/D7nL4mIxZ9+7chC9Finb4Bpm/fvmRnZ3tty87ObrLHz9mzZykvLyc8PNzn60ajEaPR98p67sqCpmkdsnLeXOo58qBegPxqmkZk4M/HV9V0FJTbcWq104cZDGaqDRYckfEoJXkcKHUyLjQcV0kRisGIpugI1rmYMcDGmv152Gt+ehAA9IwKYmRiMC5ny+dab05eLTono3tGsu5Aw6ARE2wmNtDQpouet4RT03DE9sB4ydUE1FSj6Q3UGE21Ny6d4Bz3p7zW39YVym5L+Jv3nHJHg8YXt0N5ZQxLDCFE1/BzqjByvKia/HI7qqKj3AlWo4Ku3nfGBJsx6TQ0l++0aFrTp56qan7nxaI4uTIjjo++rfKM5qn9EpVL0mI4kFPc4D0D4kMINaho7ps+/TlCpc7gSUuVzoAuLQNjz77oXE5cJjN2lJ8af9rnvOtI53xzy6t7e0dJv5uzpoZRSaFszyoku7jKs92g15ESYWVsShj8NNe9r/RXGkzo0odg6pOO4nJRabKydmdeo+VOVUFTz30c3NP3Hcov53RJNeEBRtJtQURbOK8Fa89UOBo0vkDtGX0k+yzFGb0I8dEAo5hMqOf5+7lcLnqEBXAor8zn6yEWIxb9ub+jI55HzdWWeWhOWe2sx1ZRFCo0A8fOVnE4vxizUcdAWwhxQToqTRb0Q0Zj7p+Joqk4zQHYgVBF8ZlfTadD8TEiLtCgEBtsoUJTCDQq2EIsHCuoIC7UQo3zp2kogTE9IzhdVE5GXFCjxzLAAAFGvWdqzvpig80XZE2KuvlV9AZ2nCxuNJp9l1VEYnpkp15DsDOezy2JrR2RP8fe18uJEYEEWkwcyitn7Y9nGRBrpXdEAEE6Jz2CjZwqrWnQ+AIQHRLAcbtK2YipRA2vxGUOwK5p4FLpHW6iMDGcXaeKPGuPmfQ6LkqNIsas/VxHPE+tdb6pOh1KE/XV2ntofYc4H/zJs1mnERFoIr/Md2euxPAAXC5Xh8iPEEII4Y9O3wBz+eWXM2/ePJYuXcrYsWM5fPgwn3/+Ob/+9a8BqKqqYvHixYwaNYqwsDDOnDnDu+++i81mIzMzs51T3z4URcGhGCisql0rZXBSJGdK7eTUW2xQAeJCzn/udl9iAvTEBFvIK6tCBcprVM+Dp+EpEew+dobTxZUkh8eSZ69GCbBCSRGmfhlUUztKJsGq4/ohcZytdFHtVAkLMBBuAqUNF7pVVZU+4QYM6Ta2Hi+kyF6DyaAjLSaYEYmhmDTfcwd3RA4UHKafhil3wDVrRNvQ6XQU2asafd2lalQ5NOpfGuyakU/21i4MrAADEiLYdrwQq8lAjxAzup+GtesVhaGJYdRoCkXVempcKiEWPaFGPKNqrHqNHuEBZBX67sXXNzbI74dMmqbRKyqIWZk2CipdVDpUgs21a1eoQESAnl2nSqiocRJoNjA4IYwB0QFoda8j4ZEoJrNnXn+v42UNRAuL8Nqmqio1esO5G25Epxamq+Hu8T358kgRB/PKQNNIibQyLiUcm0U7Z3ubqqpU642gN6LXKySEWzmY63tEar/YIM/i2o1RFIXTlQor9pzG8dO0QNnFsC+nhElpMaRHGrzXZ2iG4konBp1CQkQggWYTNS4Vk16hxF5Ndl4glZqeEB/vM6SkUnOeD4Q1Tatd58NkoKKm4UPdkSkRmBWVVnoWJroJRW8gr1rHvtxyNMBs1HOysJyj+eWk20K4KCUEXE5cxp+mA9O0JqfuceoNGNMG4Nz6pff3oBJl1RM3agRZQWbuHNeTzcfOsiOrkNJqJ7YQC6NTIiiuqELTIMyip7GlyYP0GkMTw/n6aEGD10IDjMQHGYELWwd2aVBsb7xuW1LpoEYF35OoCXH+wi0GjHrFs45oj3ArRVUuVh04jaJAn6ggrHoor9GwhVoIMar0CA0gOsjM2YoaVE3DYtATE2Im2KjgUjXKXApBFotX645BdTImwUp6bCBFVU50ikJkgIEgvavRNcfak9NgwpSWTuW3m32+7r6H7iz0motRyRGs2JPToDplMepJiwpEbcN7fiGEEOJ8dfqnQ6mpqdx33328//77fPTRR8TExHDzzTdz0UUXAbUPE7Oysti4cSMVFRVEREQwaNAgZs+e3WhPoa5MURQKHHrWHjhDYUUNKFBWoxEZaKavLZSDuSWefQfEhxJhvjBj/Ayag8vTo/nqaBEHCypxulSsJj3Dk8Kx6GFfsR1cGqdLqxnZNxwtax/GhGS0xJ6eni6qqmJBpYdn6nlnY/esF5SiuugdopCUGUOVS0GvQKBeRXV1nsYXIdxUVSU0oPFro04Bi8H7uqDX6/k+q8yzMLAGnCwoY+ageL4+epZyh0qIEcKtJi5KjcKgU1i88wzFlbX763UKA+JCGJUYglFzgOpkdEoEOSVVngfJbjHBZhJCTM0eWWbCSZxFAwuAC1QXemBorJn+0TYcmoJJAYvO1eCGriogCOu4yVRsXO3dOKk3EDBuCtXmAGm07IY0TSNUqeaqviFU9A5FA6wGDZ3qQlObflhbn+pyMSwhhBNnK6iq17s9PNBErwjLOR801KBn/aEzDcqMBnx1OJ8eoQmE6Fp2noYFGEjvEcGmIwWc/Kmzhk6BvrHBDB6WQYC94egXy6Dh1IS3zvoDgTonMwfFseFwATnFlbXH2mRgZHI4qeEG1A74MEx0XDWKka+OlrDhSGFtXRiID7UwMTWKA9nF7MstpU9MUJ365bmpqorSMw3j8SM4zpz2es1o64GxZyo9DBqazkm/KAtR1hh0ikJljZOsglJqnCqT0mII1LkaDScul4uBMRY0othxsogqhwudUtv7f0LvCMwXuPEFQK9ASICBokYaYYItBowK7TXgU3QDIUaVkSmRfH2kAAUItZpZc7C2zMUEmclMCGVfbhnrfiwg0GwgKdRMoMXM1L4x/JBdTI1TRa+Ajtrh1gpgMejweROpugjVQ2gg1J7UjnP1hWg3qqqipKZjyDqKM897erT699CdgaZpJAXrmdo/li3HCj2jcGNDLExIjSTU0Pi1UgghhOiIOn0DDMCwYcMYNmyYz9dMJhMPPfRQG6eo47JrBj77IcczbRcaBJt0FNlrCA0wkhhuxe5wMSQhlN7hJhT1wk0hEICD6X3C6BcfxqiUSI6dreDHvDJySqtQrMHgdOByOUhNisUSPRY1Jp5qQ8dsNNM0DYPmJOin523yLEh0ZvFBJgJMeiprGp7IvaKDCDVp1F3/rsKlNJgeqKTKQVVeCSMSQ4kODqBXpJlgPTg0hQ92nPZ6yOxSNXafLsFi1DMyzoKqqkSbXPxycDzfnSohu6gSg16hvy2E9Bgr5lac1k9VVcyouNuafd3MaZpGdWJvgq68HueRA6hFZ9FFxWDomUZVaESrzbcvOifN5cTqbmtxtfy5Y7jBxS8z4/j+dCknCu3oFIW02CAybEEE+PFgtbha855mrw6nqnGmrIaQ0JZ1qogMMvPOt9lkl/w8UlbVYH9uGSEWI5MH9UOnd+I8eQzFasWYmo4jMgYnrdOJQ9M0wvQOZvaPpNRRm59Aow6rziWNL6JZFL2Br4+VsDe33GskR3ZJFav25zG5TyQHckrYf6aM5NTQZq0vUGU0Y548A1PuaRxHDoCiYOzdDzW2B1U/1V8V1UV6dABHi2v4/mQx9honkUFmhieGkRCkO+f5rNecDI010TcqHrtTxahTCDECbdQTXHM5GdIjjBNnfY9QHZoQjk5zSfuLuGBUl4tBMRbCAuI4lFfOyaIqAkx6ogLN9I22cvBMOXtzakeTllc5cYRYKK2sYf2PdsamhHt1NgRIirQSbga6QCipMpqxTLkSc+4pHIcPgF7/0zUovnbEbWejuugbpic500aZQ0WnKISaakfHqDLsVYhuR6fTUeXnbbdRp6DXusCFXXQpXaIBRvhHURSyS2p+bnxx0zQCDVBcUcWsIQkEG1zoNRea6oRm9OBtCU11UVzuoLC8GnuNkzNltVMfaYqCxRrAJf2SsYQEUxl+YaZCE0I0ZNU5uXyAjVX7zlBeZ02KxPAALuoZjubyftCjgc9FMqudKkfzy7BXOxkZZ0J1uThU5GzQw99t9+kSBsRYCVBUNE0jwuDk0t6hVLtC0SkKJqXh6JS2omoa9pBw9MPHoygKTlWlRlVl5ItoNZqmEap3MjklmMqkEHSKgkWn4nL5d843tlCtm8OloiiGFvWALbLXEGDUYdTrvEbYWE0GSitryHfqCe+bga5/Jhpgv0CL4iqqk1A9oAeQ3q+i+UoccOhMGRpKg7Ukiuw1OLXaUZnVzpbdtFcbTCiJvdCn9AGgyscaBXrVQVqojt5h0ThUBbNeq10zxc/GRFVVCVBUPINV27gcxAUqXJQazTdHC3D+dN3R6xSGJ4WTFKLrkNMzia5FUZ2kBCn0Cotg1eFiSistKJpGRKCZ9YfPevbTqJ1VTK+oBJr0GPR6dAqeKSvjQgOYnBrpWbOtK6gymFASe6NPSQOgsoMuUu8vVVUxoRJZ53onTS9CdE9Ol8YnexquvezLNRmx6C/so0whmk0aYLoRRVEo8LEAoZvD6cLhdKLTtV3PNU3TsIWY2XSkAFtIANcNScBe48KgVzAoCvmldgL0vmaWF0JcKJqmEWtWmT0kjgJ77RpLIRYDEWbQ+WgAseprb2JPnK3w+XmpMYFoqopOp2t0MU2AKoeLalftQsOetLictXPJa3SINR4uxALHQtSlqi7MABo053QLMeswG3RUO30/jY0JNqNpLXsQU2x3YNFp9I60UuVScalg1CuY9Qo6TcXuUAnVqzIaTHR4VQ4Vl6phUCDApMdeb6Rnsd2JyaAjNcr/tcbq0zTtnCNnNE1Dpzlry3onCyuK6mJQtImU8B4UVrrQ0IgIMBBq0KTxRbQZTdNQnTX0jgjgx59GtThVzaszgsWgx6DU/m3RaYRZDVyT2YOKGpdnPUB9F1xHxJ9rkBBCCCHaljTAdCOaphHWxNoOep2C2dD2zcRRZoVe0YEcza8gt7SSulNHT+gT3eR82EKIC0PTNMw4/FpjSXM5GZkczukiu6c3rFuQ2UBqRACq6kCn0xFubXxpXqNeh0nfOukXorsJ0qsMT47g6yMNF+hOjQki0kyLe8oHm2uri3pUAj0jUPyYP1+IDsZs0P3UA14jJtjMibN2r05HIRYDmmogOczc7LXGuhNNdRGsg+BA9xZnh10bQ3RdmqbRI8RIVJCZgvJqDDrFM8JFAWJDzLVrvfwkzKwj1uzC0/IpDYZCCCGEaCO69k6AaDuappEQasZk8P2z944Oqp1Huo3pNCeTe0cwKiWSQJMBRYGIQBPT0m2kR5qlR60QnUCsWeXqzHgSwgPQ6xRMBh39bCFcMyiOQF1tLzxVVUkJt2DQ+W7o7WcLJsjQAYa5CNEJqapKRoyZS/rHEm41oVMg0GxgTM9ILu4Vfl5rusUEGQg0+e6z0yM8gLDG21WF6FDCTJAcGQRAoB5SIgOx/lT3DLEYSI4I4Ir0WCxtsKC9EOL8mTUHVw6IITMhjMoaJ6nRwVhNepIjrAQZf65vWk16YgI74TooQgghhOgSZARMNxOsdzFjgI3V+894LbCdEB7AuJ5hDdZ2aCsmzcGIODMDY224NAWTTsOIq8XTpQgh2paqqsSY4Kr+kdidoKAQqFdRVYfXPPthRpXp6TbWHczzWgsmJTKQkYkhqF1oHm4h2ppOdZEWqqNnZgw1LgW9AgG68187yaq4mDEglpX11oWKCbYwpU8UShecwkV0TZrLycTe4VQ5XOSUVGLVa6SEm7EYA7ks3UZioIbL2fh0vUKIjicABxOSAqlw6RjTM4J1B/M5U2LHXQENNBuYkR6LVXE2WPtJCCFE+9HrdcxItPi1b5CMTBadnDTAdDOqqpJg1XH9kHgK7E6qHCphAYYOMQeuqqqYUXHPQSb1YyE6IZcT608dDn0NXlNVleQghRuGxJNvd1LtVAm3GhtdX0YI0TyapmHQnBiaKIct+cwYs8bswXHk213YHU5CLUYiA3QYpNyKTsaKg6v6R3K2SqO4yoHVaCDKqidAceJySu1TiM7I5XJhwYVFgZnpkZytDKekXvnWpPVFCCE6FqeTE0sW+rVrxK/+3wVOjBAXljTAdEOqqhKASqIVals7ZA5cIUTb0TSNAMVBUiDUXoMaX19GCNExuNeFSrBC7Qy2UncQnZdecxJjhhize/0iVXrGC9FFGFQHsWaIlfIthBBCiA5CGmCEEEIIIYQQQgghhOigrJrT7+ma9NK7TQghOhRpgBFCCCGEEEIIIYQQooPSOWv8nq4p+v/NucCpEUII0RzSACOEEEIIIYQQQgghhBCiw9HrdX6PALNqTlRFd4FTJETzSIRIel0AADWzSURBVAOMEEIIIYQQQgghhBBCiI7H6fR7BFjkzTehmvxrrBGirUgDTDMYDAaf/+4OulN+u1Neoevmt7F8ddX8+kPy3j11hrw3lcbOkP6mdPb0g+Sho+gIefCVho6QrrYk+e3aulJ+O1teOlt6W4PkWQAYjUa/9tNqqlEUxe/Pbc6+zd3/XPvWfb2zpPlCpaP+a935ePjafmHSofhdroRoK4qmaVp7J0IIIYQQQgghhBBCCCGEEKIrkUnxmqmyspIHHniAysrK9k5Km+hO+e1OeQXJb3cieZe8d0aS/vYneegYOmoeOmq6LhTJb9fW3fLbkXTHYy95Fl2V/M4/k2PxMzkWQkgDTLNpmsaxY8foLgOHulN+u1NeQfLbnUjeJe+dkaS//UkeOoaOmoeOmq4LRfLbtXW3/HYk3fHYS55FVyW/88/kWPxMjoUQ0gAjhBBCCCGEEEIIIYQQQgjR6qQBRgghhBBCCCGEEEIIIYQQopVJA0wzGY1Grr32WoxGY3snpU10p/x2p7yC5Lc7kbxL3jsjSX/7kzx0DB01Dx01XReK5Ldr62757Ui647GXPIuuSn7nn8mx+JkcCyFA0WQSPiGEEEIIIYQQQgghhBBCiFYlI2CEEEIIIYQQQgghhBBCCCFamTTACCGEEEIIIYQQQgghhBBCtDJpgBFCCCGEEEIIIYQQQgghhGhl0gAjhBBCCCGEEEIIIYQQQgjRygztnYDOZNWqVXz22WcUFxeTnJzMrbfeSmpqansnq9kWLVrEkiVLvLbFx8fz4osvAlBTU8M777zD5s2bcTgcZGZmcvvttxMWFubZv6CggNdee429e/disViYOHEiN954I3q9vg1z0tC+ffv49NNPOXbsGEVFRdx3332MHDnS87qmaSxatIjPP/+ciooK+vXrx+23305cXJxnn/Lyct58802+++47FEVh1KhR/Md//AcWi8Wzz4kTJ3jjjTc4cuQIISEhTJ8+nZkzZ7ZpXuHc+X355ZfZuHGj13syMzN56KGHPH93pvy2VFcpu83x8ccfs23bNk6fPo3JZCItLY2bbrqJ+Pj49k5am1u2bBnvv/8+M2bM4JZbbmnv5LSJwsJC3n33XXbu3El1dTU2m425c+fSu3fv9k6aXzpzmT1XjO2IWiN2trfWiIftyZ9rtj/1s7bUmctpc3TneNpd4mdnj5mdwV133UV+fn6D7Zdeeim333478+fPZ9++fV6vTZ06lV//+tdtlcRWp6oqixYt4quvvqK4uJiIiAgmTpzIL3/5SxRFATpHfG0Of/Lc0eOxOLdzleeOVl+5kLpjOW9KZWUlCxcuZNu2bZSUlNCzZ09uueUWT/2wOx0LIeqTBhg/bd68mXfeeYc77riDPn36sGLFCp588klefPFFQkND2zt5zZaYmMi8efM8f+t0Pw+Gevvtt9mxYwf33nsvVquVN954g+eee47HH38cqA0yTz31FGFhYTzxxBMUFRXxt7/9Db1ez4033tjmeamrurqalJQUJk+ezLPPPtvg9U8++YSVK1dy1113ERMTw8KFC3nyySd5/vnnMZlMAPz1r3+lqKiIhx9+GJfLxSuvvMI//vEP7rnnHgDsdjtPPPEEGRkZ3HHHHWRlZfH3v/+dwMBApk6d2qHyCzB48GDmzp3r+dtg8C72nSm/LdHVyq6/9u3bx7Rp0+jduzcul4sPPviAJ554gueff96rca2rO3z4MGvXriU5Obm9k9JmysvLmTdvHgMGDODBBx8kJCSEnJwcAgMD2ztpfukKZbapGNsRtUbsbG+tEQ/bkz/X7HPVz9pSVyin/uqu8bS7xM/OHjM7i6eeegpVVT1/Z2Vl8cQTTzBmzBjPtilTpjB79mzP3x0lvrTUsmXLWLt2LXfddRcJCQkcPXqUV155BavVyowZM4DOEV+bw588Q8eOx+LczlWeO1J95ULrjuW8Ka+++ionT57k7rvvJiIigi+//JLHH3+cF154gYiIiG51LISor2M/EehAli9fzpQpU7j44otJSEjgjjvuwGQysX79+vZOWovodDrCwsI8/4WEhAC1D9u/+OILbr75ZgYOHEivXr2YO3cuBw8e5NChQwDs2rWLU6dO8bvf/Y6UlBSGDBnC7NmzWb16NU6nsz2zxZAhQ7j++uu9er26aZrGv//9b37xi18wYsQIkpOTufvuuykqKmL79u0AnDp1ip07d3LnnXfSp08f+vXrx6233srmzZspLCwEYNOmTTidTubOnUtiYiLjxo3jsssuY/ny5W2aV2g6v24Gg8Hrtw4KCvK81tny2xJdrez666GHHmLSpEkkJiaSkpLCXXfdRUFBAUePHm3vpLWZqqoqXnrpJX7zm990qwcpn3zyCZGRkcydO5fU1FRiYmLIzMzEZrO1d9L80hXKbGMxtqM639jZEZxvPGxv57pm+1M/a0tdoZz6qzvG0+4UPzt7zOwsQkJCvK6/O3bsIDY2lvT0dM8+ZrPZax+r1dqOKT5/hw4dYvjw4QwdOpSYmBhGjx7NoEGDOHz4MNB54mtznCvPbh05Hotza6o8d7T6yoXWHct5Y2pqati6dSs33XQT6enp2Gw2Zs2ahc1mY82aNd3qWAjhizTA+MHpdHL06FEyMjI823Q6HRkZGZ02iOTm5vKb3/yGu+++m7/+9a8UFBQAcPToUVwul1dee/ToQVRUlCevhw4dIikpyWsI6eDBg6msrOTkyZNtmo/myMvLo7i4mEGDBnm2Wa1WUlNTvfIWGBjoNeVARkYGiqJ4guihQ4fo37+/V0+dzMxMsrOzKS8vb6Pc+G/fvn3cfvvt3HPPPbz22muUlZV5XuuK+a2rK5bdlrLb7QDd6gbn9ddfZ8iQIV5lvjv49ttv6dWrF88//zy33347999/P+vWrWvvZPmlq5TZxmJsZ+RP7OwsmoqHHU39a7Y/9bO20lXKaUt1h3janeJnZ46ZnZXT6eSrr77i4osv9kzRA/DVV19x22238d///d+8//77VFdXt2Mqz19aWhp79uwhOzsbgOPHj3Pw4EGGDBkCdK346nauPLt1pngsmla/PHek+kpb6I7lvDEulwtVVTEajV7bTSYTBw4c6FbHQghfZKynH0pLS1FVtcGclWFhYZ4LbWfSp08f5s6dS3x8PEVFRSxZsoRHHnmE5557juLiYgwGQ4PebqGhoRQXFwNQXFzc4Fi4p5tw79MRudNWf2qM+nmr31NZr9cTFBTktU9MTIzXPu7jUVxc3KFuyAcPHsyoUaOIiYkhNzeXDz74gAULFvDkk0+i0+m6XH7r62plt6VUVeWf//wnffv2JSkpqb2T0ya+/vprjh07xlNPPdXeSWlzeXl5rF27lssvv5xrrrmGI0eO8NZbb2EwGJg0aVJ7J69JXaHMNhVjAwIC2jt5zeZP7OwMzhUPOxJf12x/6mdtpSuU05bqDvG0u8XPzhwzO6tt27ZRUVHhdXzHjx9PVFQUERERnDhxgvfee4/s7Gzuu+++9kvoebr66quprKzk97//PTqdDlVVuf7667nooouArhNf6zpXnqFzxWNxbvXLc0eqr7SF7ljOGxMQEEBaWhofffQRPXr0ICwsjE2bNnHo0CFsNlu3OhZC+CINMN1Q3R4oycnJnodF33zzjcy72MWMGzfO8++kpCSSk5P53e9+x969e716pYiu7Y033uDkyZM89thj7Z2UNlFQUMA///lPHn744W55TVNVld69e3vW5OrZsydZWVmsXbtWHia1gaZi7OTJk9sxZd1bZ4qH3e2a3Zl09d+mO8ZPiZltb/369QwePJiIiAjPtrrrSiYlJREeHs5jjz1Gbm5up50O7ptvvmHTpk3853/+J4mJiRw/fpx//vOfhIeHd9lzy588d6Z4LM7NV3nuTrpjOW/K3Xffzd///nfuvPNOdDodPXv2ZNy4cRw7dqy9kyZEu5MGGD+EhIR4RgvU5WskSGcUGBhIfHw8ubm5DBo0CKfTSUVFhVevhZKSEk9ew8LCGszjWlJS4nmto3KnraSkhPDwcM/2kpISUlJSPPuUlpZ6vc/lclFeXu6Vf1/nQt3v6KhiY2MJDg4mNzeXjIyMLp/frl52/fHGG2+wY8cOHn30USIjI9s7OW3i6NGjlJSU8MADD3i2qarK/v37WbVqFe+//36X7mEXHh5OQkKC17aEhAS2bt3aTinyX1css3VjbGfkT+zsjOrHw46isWt2WFjYOetnbaUrllN/dId42h3jZ2eOmZ1Rfn4+u3fvPufIltTUVIBO3QDz7rvvMnPmTE+DQ1JSEvn5+SxbtoxJkyZ1yfh6rjz70lHjsTg3X+W5I9VX2kJ3LOdNsdlsPProo1RVVVFZWUl4eDgvvPACMTEx3e5YCFFf16pBXyAGg4FevXqxZ88ezzZVVdmzZw9paWntmLLWUVVVRW5uLmFhYfTq1Qu9Xs8PP/zgeT07O5uCggJPXtPS0sjKyvI0ugDs3r2bgICABjcwHYn7ol83b3a7ncOHD3vlraKiwmth1T179qBpmudGIC0tjf379+N0Oj377N69m/j4+A49HRfA2bNnKS8v9wS8rp7frl52m6JpGm+88Qbbtm3jkUceaTCNXFeWkZHBs88+y9NPP+35r3fv3owfP56nn366yz08qq9v374NpgHKzs4mOjq6nVLkv65YZuvG2M7In9jZGdWPh+3tXNdsf+pnbaUrltOmdKd42h3jZ2eOmZ3R+vXrCQ0NZejQoU3ud/z4cYAOc41uierq6gZlRqfToWka0DXj67ny7EtHi8fCf77Kc0eqr7SF7ljO/WGxWAgPD6e8vJxdu3YxYsSIbnsshHCTETB+uuKKK3j55Zfp1asXqamp/Pvf/6a6urpTDit85513GD58OFFRURQVFbFo0SJ0Oh3jx4/HarUyefJk3nnnHYKCgrBarbz55pukpaV5LoqZmZkkJCTwt7/9jTlz5lBcXMyHH37ItGnTGiy41dbcD7rc8vLyOH78OEFBQURFRTFjxgyWLl1KXFwcMTExfPjhh4SHhzNixAigtsfb4MGD+cc//sEdd9yB0+nkzTffZOzYsZ5htePHj2fx4sW8+uqrzJw5k5MnT7Jy5UpuvvnmDpXfoKAgFi9ezKhRowgLC+PMmTO8++672Gw2MjMzO2V+W6Irld3meOONN9i0aRP3338/AQEBnp7KVqu1y08rEhAQ0GBufrPZTHBwcJeds7+uyy+/nHnz5rF06VLGjh3L4cOH+fzzz/n1r3/d3knzS2cvs03F2I7qfGNnR3C+8bC9neua7U/9rC119nLaHN0pnnbH+NnZY2ZnoqoqGzZsYOLEiej1es/23NxcNm3axNChQwkKCiIrK4u3336b/v37k5yc3I4pPj/Dhg1j6dKlREVFkZCQwPHjx1m+fDkXX3wxAIqidIr42hznynNVVVWHj8fCP42V545WX7nQumM5b8rOnTsBPKP///Wvf9GjRw8mTZrU7Y6FEPUpWlPdEYSXVatW8emnn1JcXExKSgr/8R//QZ8+fdo7Wc324osvsn//fsrKyggJCaFfv35cf/31nuHdNTU1vPPOO3z99dc4nU4yMzO5/fbbvXrv5ufn8/rrr7N3717MZjMTJ05kzpw5XsG3Pezdu5dHH320wfaJEydy1113oWkaixYtYt26ddjtdvr168dtt91GfHy8Z9/y8nLeeOMNvvvuOxRFYdSoUdx6661YLBbPPidOnOCNN97gyJEjBAcHM336dK6++uq2yKKXpvJ7xx138Mwzz3Ds2DEqKiqIiIhg0KBBzJ492+u37Ez5bamuUnabY9asWT63z507t0s+IDuX+fPnk5KSwi233NLeSWkT3333He+//z65ubnExMRw+eWXe82v3tF15jJ7rhjbEbVG7GxvrREP25M/12x/6mdtqTOX0+bo7vG0O8TPzh4zO4tdu3bx5JNP8uKLL3rFj4KCAl566SVOnjxJdXU1kZGRjBw5kl/84hdYrdZ2TPH5qaysZOHChWzbto2SkhIiIiIYN24c1157LQZDbT/YzhBfm+Ncea6pqenw8Vj4p7HyDB2vvnIhdcdy3pTNmzfzwQcfcPbsWYKCghg1ahQ33HCD51renY6FEPVJA4wQQgghhBBCCCGEEEIIIUQr63oT+QohhBBCCCGEEEIIIYQQQrQzaYARQgghhBBCCCGEEEIIIYRoZdIAI4QQQgghhBBCCCGEEEII0cqkAUYIIYQQQgghhBBCCCGEEKKVSQOMEEIIIYQQQgghhBBCCCFEK5MGGCGEEEIIIYQQQgghhBBCiFYmDTBCCCGEEEIIIYQQQgghhBCtTBpgRKcxa9YsFi1a1N7JEKJTmTVrFm+88UabfE/d8rlhwwZmzZpFXl7eBf9uIYRvEjeFaB8vv/wyd911V3snQ4hu6XzqoO73Hjly5AKkrOH31E3j/PnzmT9//gX9XiG6K4nLQoj2ZmjvBIjOY8OGDbzyyiuNvv7EE0+QlpbWhikSoutxl7OnnnqK3r17t3dyhBCtoKn4OXPmTObMmdPGKRKie8jNzeXTTz9l9+7dFBUVYTAYSEpKYsyYMUydOhWTydTeSWyxgwcPsmvXLi6//HICAwPbOzlCiDaydOlSEhISGDlyZHsnRYhmk7j8s02bNlFSUsLll1/eBqkTQrQ3aYARzTZr1ixiYmIabLfZbBf0e9999130ev0F/Q4hRMtI+RTi3HzFz6SkpHZKjRBd244dO3j++ecxGo1MmDCBxMREnE4nBw4c4F//+hcnT57kN7/5TXsns8UOHjzIkiVLmDRpkjTACNHJTJgwgbFjx2I0Gpv93o8//pjRo0dLA4zodCQue9u0aRMnT56UBhghuglpgBHNNmTIkHbpmd+RekNUVVVhsVjaOxlCdBjtUT5dLheapmEwdJ5QJteO7q294ueFVF1djdlsbu9k+E1VVZxOZ4eqU4jWl5eXx4svvkh0dDSPPPII4eHhntemT59Obm4uO3bsaMcUdi41NTUYDAZ0us4ze7XEW9GR6XQ6iUOiW5G4LITo7jrPUyvRaeTl5XH33Xdz0003YbVa+eSTTzh79izJycncdtttpKameu3/zTffsGjRIvLy8rDZbMyePZvt27ezb98+Xn75Zc9+s2bN4tprr2XWrFkALFq0iCVLlvDXv/6Vjz76iO3bt6NpGqNGjeK2225r8EDoyy+/ZMWKFZw6dQqTyURmZiY33XQTUVFRTebH/T3PP/88H330ETt37iQ6Opqnn36al19+mS1btvDss8/y+uuvc+DAAaxWK5dccgm//OUvURSlwTExmUwsX76c4uJi+vXrx5133klkZCQfffQR69ato6ysjMzMTObOnUtQUFBr/CSii3n55ZcblA/4+Vz1tebDV199xZIlSygoKCAhIYGbb76Z9PT0c35XSUkJ77//Pjt27MButxMfH8/ll1/OpEmTvParXz6bk5fmliG9Xs+qVavIy8vjz3/+MykpKZw+fZoPP/yQPXv2UFNTQ2JiItdeey3Dhw/3fJfT6eTjjz/mq6++4uzZs5jNZnr06MF1113HoEGDACguLub9999n9+7dlJaWEhQURGpqKrfccotn5EJjeb3rrrtIT0/3zC/snnZq/vz5bN68mS1btuByuXjrrbcA+P777/n44485duwYiqLQv39/brrpJhITE5t1DEXX4O95BVBRUcHixYvZunUrJSUlREZGMmXKFK666qpmPyDdu3cvjz76KP/1X//F8ePHWb9+PVVVVQwcOJDbbrvNK0bOnz+fsrIy7rrrLt5++22OHDnC1KlTueWWW3A4HF7lKzQ0lHHjxjF79myvHr67d+9m8eLFnDx5EpfLRUREBKNGjeLGG2/07LNy5UrWrl1LXl4eRqOR2NhYrrjiCsaPHw807xo4a9Yspk2bRlpaGh9//DE5OTn8/ve/Z+TIkRQWFvLhhx/y/fffU1FRgc1m44orrmDy5MnNOoai4/nkk0+oqqrizjvv9HrI42az2ZgxY4bnb5fLxccff8zGjRs5e/Ys4eHhjBs3juuuu65BD/XVq1ezevVqcnNzCQ4OZsSIEdxwww3n7O366aefsm3bNrKzs6muriYhIYFrrrmG0aNHe+3nPmczMjJYuHAhOTk52Gw2fvWrXzF48GDg53Md4O677/a8929/+5vPUergXX7ffPNNjh07RlhYGDNnzuTSSy/17Oe+Jtxzzz2cPHmS9evXU1xczJtvvklgYCA//vgjixYt4tChQ7hcLnr37s0NN9xAv379PJ9RWVnJwoUL2b59O0VFRVitVpKTk5kzZw69evUCICcnh/fee4+DBw9it9sJDg6mX79+/PrXv8ZqtXri/ty5c89Z52iqrg4tvwcQXUdzYizUdi74v//7P0/dbcSIEdxyyy1+3Zvt2bOHRYsWcezYMfR6Penp6dx4440kJCR49nHXEZsqs43lA2Djxo1s3LgRgIkTJ3rS709cqxv3T58+zbp166isrCQzM5Pf/va3GI1G3nvvPTZt2kR1dTVjxozhjjvu8LoW1o2tLbm/EN2PxGVv8+fPZ9++fZ7PB4iOjvbUbf2tV7vTlp6e7nmmlpKSwm9+8xuSkpJYu3Ytn376KYWFhfTp04e5c+d6pcffuoEQ4vxJA4xoNrvdTmlpqdc2RVEIDg722vb1119TWVnJ1KlTURSFTz75hOeee46XXnrJ02N9x44dvPjiiyQlJXHDDTdQUVHB3//+dyIiIvxOzwsvvEB0dDQ33ngjR48e5YsvviAkJISbbrrJs8/SpUtZuHAhY8aMYcqUKZSWlrJy5Ur++Mc/8vTTT/s1RPT555/HZrNxww03oGmaZ7uqqixYsIA+ffowZ84cdu7cyaJFi3C5XMyePdvrMzZt2oTT6WT69OmUl5fz6aef8sILLzBw4ED27dvHzJkzyc3NZdWqVbzzzjvMnTvX7+MgRGP27dvH5s2bueyyyzAajaxZs4YFCxawYMGCJqc/qqmpYf78+eTm5jJ9+nRiYmLYsmULr7zyCna73auSfD6aU4Y2bNiAw+FgypQpGI1GgoKCOHnyJPPmzSMiIoKrr74as9nMN998wzPPPMN///d/e6ZoWLx4McuWLWPy5MmkpqZSWVnJkSNHOHr0qKcB5rnnnuPkyZOe/JaUlLB7924KCgqadYNc1+uvv05ISAjXXnstVVVVQO3DoJdffpnMzEzmzJlDdXU1a9as4ZFHHuHPf/5zi79LdGy+4mdISEizPqO6upr58+dTWFjI1KlTiYqK4uDBg3zwwQcUFxdzyy23tChtS5cuRVEUZs6cSWlpKStWrODxxx/nmWee8eqlW1ZWxoIFCxg7diwXXXQRoaGhqKrK008/zYEDB5gyZQoJCQlkZWWxYsUKsrOzuf/++wE4efIkf/rTn0hOTmbWrFkYjUZyc3M5ePCg5/PXrVvHW2+9xejRo5kxYwY1NTVkZWXx448/ehpgmmvPnj188803TJ8+neDgYGJiYiguLuahhx4CYNq0aYSEhLBz505effVVKisrZTqITu67774jNjaWvn37+rX/q6++ysaNGxk9ejRXXHEFP/74I8uWLeP06dP84Q9/8OznfsCSkZHBpZdeSnZ2NmvWrOHIkSM8/vjjTY7IXLlyJcOGDWP8+PE4nU42b97M888/z//8z/8wdOhQr30PHDjAtm3buPTSSwkICGDlypU899xzvPLKKwQHBzNq1ChycnL4+uuvufnmmz118HNdT8rLy3nqqacYM2YM48aN45tvvuH111/HYDA0aHj86KOPMBgMXHnllTidTgwGA3v27GHBggX06tWL6667DkVR2LBhA4899hiPPfaYp5PVa6+9xpYtW5g+fToJCQmUlZVx4MABTp8+Ta9evXA6nTz55JM4HA4uu+wywsLCKCws5LvvvqOiogKr1erX71afr7p6a9wDiO7H3eB43XXXecp5fn4+8+fP93QO8mX37t089dRTxMTEcN1111FTU8PKlSuZN29eq9Tv7r77bv7xj3+QmprKlClTgJ+nAW9uXFu2bBkmk4mrr77ac/+p1+vR6XRUVFRw3XXX8eOPP7JhwwZiYmK49tprvd7f0vsL0T1JXPb2i1/8ArvdztmzZ7n55psBPKM2/a1X103bt99+y7Rp04Dasv2nP/2Jq666ijVr1jBt2jTPs6e///3v/PGPf/R6f3PqBkKIlpMGGNFsjz/+eINt7p4ydRUUFPCXv/zF01MoPj6ep59+ml27djFs2DAA3n//fSIiInj88cc9AScjI4P58+cTHR3tV3pSUlL47W9/6/m7vLyc9evXexpg8vPzWbRoEbNnz+YXv/iFZ7+RI0fywAMPsHr1aq/tjUlOTuaee+5psN3hcJCZmcmtt94K1FZ4//znP/PJJ59w2WWXeQXdwsJC/vrXv3puLFVVZdmyZdTU1PCnP/3Js4ZGaWkpmzZtatDbSIiWcD/0dPc6HTduHPfccw+LFi3ivvvua/R969at4/Tp0/zud7/joosuAuCSSy5h/vz5fPjhh1x88cUEBAScd/qaU4bOnj3LSy+95LXt8ccfJyoqiqeeespTXqZNm8YjjzzCe++952mA2bFjB0OGDGl0buGKigoOHjzITTfdxFVXXeXZfs0115xX/oKCgnjkkUc8IxOqqqp46623mDx5sldaJk6cyH/913/x8ccfd+r5j0XjfMVPXyPWmrJ8+XJyc3N5+umniYuLA2rLZUREBJ9++ilXXHFFi3p1l5eX88ILL3jKdM+ePXnhhRdYt26dV2NrcXExd9xxB5dccoln25dffsnu3bt59NFHvXrBJyYm8tprr3Hw4EH69u3L7t27cTqd/O///m+jN6Q7duwgMTGRe++9t9l5aEx2djbPPfecV+/jV199FVVVefbZZz03yZdeeikvvvgiixcv5pJLLpHpYTopu91OYWGh1wjIphw/fpyNGzcyefJk7rzzTqA2hoSGhvLZZ5+xZ88eBg4cSGlpKcuWLSMzM5P//d//9VzT4+PjefPNN/nqq6+4+OKLG/2ev/zlL17n1PTp03nggQdYvnx5gwc9p0+f9jQmAAwYMIA//OEPfP3110yfPp3k5GR69uzJ119/zYgRI/x+qFtUVMSvfvUrrrjiCqD22vHggw/ywQcfMGHCBK8HVQ6Hgz/96U+eNGuaxmuvvcaAAQN48MEHPQ+hL7nkEu69914+/PBDHn74YaC2HE+ZMoVf/epXns+bOXOm59+nTp0iLy+Pe++916uncf0HvM1Vv67eWvcAovsxGAzMmzfPUyaio6N59913+e6775q8trz77rsEBQXx5JNPeu6BR4wYwf3338+iRYu8esa3xIQJE3jttdeIiYlhwoQJXq99+OGHzYprLpeL+fPne/JYWlrK5s2bGTx4MP/7v/8L1F4Lc3NzWb9+fYPy2dL7C9H9SFxuaNCgQURERFBRUdGgLG/atMmverVbdnY2L7zwguc7g4KC+L//+z+WLl3KX/7yF0/d3v3sKS8vzyt9zakbCCFarvNM5Cs6jNtuu42HH37Y6z93Ja2uMWPGeA3TdgePM2fOALWNEVlZWUyYMMFrjub09PRm9Zqp+xDI/T1lZWXY7XYAtm7diqZpjB07ltLSUs9/YWFh2Gw29u7d26LvqWv69OmefyuKwvTp03E6nfzwww9e+40ePdqrV1+fPn0AuOiii7wWMO/Tpw9Op5PCwkK/0iZEU9LS0jw3RwBRUVGMGDGCXbt2oapqo+/7/vvvCQsLY9y4cZ5tBoOByy67jKqqKs+w6dbgbxkaNWqU14Pb8vJy9uzZw5gxY6isrPSUb/dUfjk5OZ5yFBgYyMmTJ8nJyfGZBpPJhMFgYN++fZSXl7da3qZMmeI1LdTu3bupqKhg3LhxXtcknU5Hnz59/L4mic7HV/xsri1bttC/f38CAwO9zp+MjAxUVWX//v0tStuECRO8GlRHjx5NeHg433//vdd+RqOxwc3sli1bSEhIID4+3itNAwcOBPCc0+6e5t9++22j157AwEDOnj3L4cOHW5QPX9LT070aXzRNY+vWrQwbNgxN07zSPHjwYOx2O0ePHm217xdtq7KyEsDvDgLuc9z94MHtyiuvBPDMSe9uQJwxY4bXNX3q1KkEBAScc+76ug95ysvLsdvt9O/fn2PHjjXYNyMjw/OQB2obFgICAjx16JbS6/VMnTrV87fBYGDq1KmUlJQ0OOcnTpzolebjx4+Tk5PD+PHjKSsr85QZ95SF+/fv95TrwMBADh8+3Gg91l0X3rlzJ9XV1eeVp7rq19Vb6x5AdD9Tp071euh46aWXotfrmyznRUVFHD9+nIkTJ3rdAycnJzNo0KAG8bQ1tSSuTZw40SuPffr0QdO0BjE+NTWVgoICXC6X1/aW3l+I7kficvP4W692GzhwoFeDins06qhRo7yOufvZU15entf7m1M3EEK0nDRlimZLTU31axHh+j1w3RXRiooKoHaEDOAVyNxsNpvPwNfc77FareTm5qJpGv/5n//p8/3+tug31otBURRiY2O9trl7Jefn5zeZVvcNaGPb3cdKiPPhq4zFxcVRXV3teRDhS35+PnFxcQ3WlOjRo4fn9dbQnDJUvxy6y/fChQtZuHChz88vKSkhIiKCWbNm8cwzz3DPPfeQmJjI4MGDmTBhAsnJyUDtg+U5c+bwzjvvcMcdd5CWlsbQoUOZOHFio8fIH/XT7G4Aeuyxx3zu3xqjikTH5G/8bEpOTg4nTpzg9ttv9/l6SUlJiz7XXebcFEXBZrM1KIMREREN4mZOTg6nT58+Z5rGjh3L559/zquvvsp7771HRkYGI0eOZPTo0Z7rzMyZM/nhhx948MEHsdlsDBo0iPHjx3v1AGyu+mWwtLSUiooK1q1bx7p163y+p/5UcaLzcF9D3Q98ziU/P99zvtcVFhZGYGCgp77q/n98fLzXfgaDgdjYWM/rjfnuu+9YunQpx48fx+FweLb7ms7I1yi2oKCg864XhoeHN1iY3p2f/Px80tLSPNsbi131116qy263ExQUxJw5c3j55Zf57W9/S69evRgyZAgTJ070xPqYmBiuuOIKli9fzqZNm+jfvz/Dhg1jwoQJLZ5+zFeaW+seQHQ/9a8HFouFsLCwJuu+7tfqXyOgtu68a9cuqqqqGpTB1tCSuNbY/WdkZGSD7ZqmedZqcmvp/YXofiQuN4+/9erG0tZUWQYadDRsTt1ACNFyUusUF0xjCwHXXT+lLb5HVVUURfEallqXv5Xg1piKpLG0ttWxEl1DY3NPd4feZvXLoTvPV155JZmZmT7f4668p6en89JLL7F9+3Z27drFF198wYoVK7jjjjs882hffvnlDBs2zLPPwoULWbZsGY888gg9e/ZsMm2NHf/6aXaX67vvvtvnzWnd0XBC1D+vNE1j0KBBXtPk1eXrwU9r8hULNU0jKSnJa7qhutw3hiaTiUcffZS9e/eyY8cOdu7cyebNmxk4cCAPP/wwOp2OhIQEXnzxRc/rW7duZc2aNV6LJzf3GthYGbzooouYOHGiz/e4G2ZF52O1WgkPD+fkyZPNel9T6zqcr/379/P000/Tv39/brvtNsLDw9Hr9WzYsIFNmzY12L8j1AsbKzc33XQTKSkpPt/jrlOPHTuW/v37s23bNnbt2sVnn33GJ598wn333ceQIUMA+NWvfsWkSZPYvn07u3fv5q233mLZsmU8+eSTREZGtqiu46uO0Br3AKLr6ip155bENbkvFW1F4nLz+FuvPlfaGtsuhGgf0gAj2o07cOTm5jZ4zde2lrLZbGiaRkxMzAV5MKVpGmfOnPH6bHcvQX/XsRGiOQIDA332tmmsl4+v8pSTk4PZbG5ywd7o6GhOnDiBqqpeFbjs7GzP663hfMqQuzetXq9n0KBB5/yuoKAgLr74Yi6++GKqqqr44x//yOLFiz0NMFB7zbjyyiu58sorycnJ4f777+ezzz7z9KANDAz0THHo5nQ6KSoq8iu/7jSHhob6lWbRPfh7XsXGxlJVVdXq5079qfk0TSM3N9evKUFjY2M5ceIEGRkZ57xZ1ul0ZGRkkJGRwc0338zSpUv58MMP2bNnjydPFouFsWPHMnbsWJxOJ88++yxLly7l6quvxmQyNfsaWF9ISAgBAQGoqiplsIsaNmwY69at49ChQ+fsuRkdHY2maeTk5HhNVVdcXExFRYWnvur+f3Z2tteoTafTSV5eHhkZGY1+x9atWzEajTz00ENea/tt2LChJdkDWvZgqqioqEEPfH9jujvPVqvVr3ITHh7OtGnTmDZtGiUlJTzwwAMsXbrU0wADkJSURFJSEr/85S85ePAg8+bNY+3atVx//fWeKQvrl/XmjL690PcAovNobt0tNzfXM90P1K7fV1xc7HX+1ucuQ+4yVVd2djbBwcGt0ujnq+y3R1xr6f2F6J4kLvuvOfXq1nA+dQMhhP+kSVS0m4iICBITE/nyyy+pqqrybN+3bx9ZWVmt9j0jR45Ep9OxZMmSBj0UNE2jrKzsvL9j1apVXp+5atUq9Hp9k0FfiJaKjY3Fbrdz4sQJz7aioiK2bdvmc/9Dhw55zd9aUFDA9u3bGTRoUJM9Y4YMGUJxcTGbN2/2bHO5XKxcuRKLxUJ6enor5KZWS8tQaGgoAwYMYN26dT5voutOt1C/rFssFmJjYz1Dzqurq6mpqfHaJzY2FovFgtPp9Gyz2WwN1tlYt26d370oMzMzCQgI4OOPP/b6XF9pFt2Hv+fVmDFjOHToEDt37mzwGRUVFQ3maPfXl19+6TU1xJYtWygqKmryYVPdNBUWFvL55583eK2mpsYT432treTuSe8uC/XLqcFgICEhAU3TPHlr7jWwPp1Ox6hRo9i6davP+oaUwc7vqquuwmw28+qrr1JcXNzg9dzcXP79738DeM5x999uy5cvB/AsxDto0CAMBgMrV670qk9+8cUX2O32Bgv21qXT6VAUxas85+XlsX379pZlEDCbzQANHio3xeVyeU1P5HQ6WbduHSEhIV5rOfjSq1cvYmNj+eyzz7zq7W7ucqOqaoM0hYaGEh4e7inndru9wbUqKSkJRVE8MdlqtRIcHNzgurh69Wo/c9s29wCic2hu3W3dunVedbQ1a9bgcrmajInh4eGkpKSwceNGr4bDrKwsdu3a5Vc89YfZbG7QMNkeca2l9xeie5K43JDFYvG5r7/16tZyPnUDIYT/ZASMaLbvv/+e06dPN9jet2/fBus4nMsNN9zAM888w7x585g0aRIVFRWsWrWKxMTEVgssNpuN66+/nvfff5/8/HxGjBiBxWLxBNgpU6Y0OpWLP4xGI7t27eJvf/sbffr04fvvv2fHjh1cc8010vtHtNj69et9PmCdMWMG48aN47333uPZZ5/lsssuo7q6mjVr1hAXF+dz7aTExESefPJJLrvsMoxGI2vWrAHwTOfTmKlTp7J27VpeeeUVjh49SkxMDFu2bOHgwYPccsstrbZWyfmWodtuu4158+Zx3333MWXKFGJiYigpKeHQoUMUFhbyzDPPAHDvvfeSnp5Or169CAoK4siRI2zdupVp06YBtb32HnvsMcaMGUNCQgJ6vZ5t27ZRUlLC2LFjPd83efJkXnvtNZ599lkGDRrEiRMn2LVrl9e82E2xWq3ccccdvPTSSzzwwAOMGzeOkJAQCgoK2LFjB3379uW2225rwZEUnZm/59VVV13Ft99+y5///GcmTpxIr169qK6uJisriy1btvDyyy+3KPYEBQXxyCOPMGnSJEpKSlixYgU2m81rdFhjJkyYwDfffMNrr73Gnj176NevH6qqcvr0ab755hseeughevfuzZIlS9i/fz9DhgwhOjqakpIS1qxZQ2RkpGeNlyeeeIKwsDD69u1LWFgYp06dYvXq1QwdOtRzzWnuNdCXG2+8kb179/LQQw8xZcoUEhISKC8v5+jRo/zwww+89dZbzT6GouOw2Wzcc889vPDCC/z+979n4sSJJCYm4nQ6OXjwIFu2bGHSpElAbSPgxIkTWbduHRUVFaSnp3P48GE2btzIiBEjPL3gQ0JCuPrqq1myZAkLFixg2LBhZGdns2bNGnr37s1FF13UaHqGDh3K8uXLWbBgAePGjaO0tJTVq1djs9m8GhKbw/1Q5IMPPmDcuHHo9XqGDRvWZA/78PBwPvnkE/Ly8oiPj2fz5s0cP36cX//61+dcD0Wn03HnnXeyYMEC7r33XiZNmkRERASFhYXs3buXgIAA/ud//ofKykruvPNORo8eTXJyMhaLhR9++IEjR454plPZs2cPb775JqNHjyY+Ph6Xy8WXX37peYjsNmXKFJYtW8arr75Kr1692L9/f4PRek250PcAovNobt3N6XTy+OOPM2bMGLKzs1m9ejX9+vVj+PDhTX7PTTfdxFNPPcXDDz/MxRdfTE1NDatWrcJqtZ6z3u2vXr168cMPP7B8+XLCw8OJiYmhT58+bR7XWnp/Ibonicu+99+8eTNvv/02vXv3xmKxMHz4cL/r1a3lfOoGQgj/SWkSzbZo0SKf2+fOndvsBpjhw4dzzz33sHjxYt5//31sNhtz585l48aNnDp1qjWSC8DVV19NXFwcK1asYPHixUDtkNVBgwadsyJ9LjqdjgcffJDXX3+dd999F4vFwrXXXsu1117bGkkX3ZT7Jqa+SZMmERkZyR/+8Afefvtt3n33XWJiYrjxxhvJycnx+fAxPT2dtLQ0lixZQkFBAQkJCcydO/ecaxyYTCbmz5/Pe++9x8aNG6msrCQ+Pp65c+d6Ksit4XzLUEJCAn/6059YvHgxGzZsoKysjNDQUFJSUvjlL3/p2e+yyy7j22+/Zffu3TgcDqKjo5k9e7bn4UtkZCTjxo1jz549fPnll+j1enr06MHvf/97Ro8e7fmcKVOmkJeXxxdffMGuXbvo168fDz/8MI8//rjfeR4/fjzh4eEsW7aMTz/9FIfDQUREBP379+fiiy/2+3NE1+HveWU2m3n00UdZunQpW7Zs4csvvyQgIID4+HhmzZrV4gWsr7nmGk6cOMGyZcuorKwkIyOD22+/3dObryk6nY4//OEPrFixgi+//JLt27djMpmIjY1lxowZxMXFAbUxPy8vj/Xr11NWVkZwcDDp6ele6b7kkkv46quvWLFiBVVVVURERHDZZZfxi1/8wvN9wcHBzboG+hIWFsaCBQtYsmQJW7duZfXq1QQHB5OYmMicOXNacARFRzN8+HCeffZZPv30U7Zv386aNWswGo2eedXrNi7eeeedxMbGsmHDBrZt20ZYWBhXX3011113nddnzpo1i5CQEFavXs3bb79NUFAQU6dO5YYbbmjyIcXAgQO58847+eSTT3j77beJiYlhzpw55OXltfhBT2pqKrNnz2bt2rXs3LkTTdP429/+1mQDTFBQEHfddRdvvvkmn3/+OWFhYdx6661MnTrVr+8cMGAATz75JEuWLGH16tVUVVURFhZGamoql1xyCVB7jZo2bRq7du1i27ZtqKqKzWbj9ttv59JLLwVqH65lZmby3XffsXbtWsxmM8nJyTz44INeU9Nce+21lJaWsmXLFr755hsGDx7Mgw8+2OjCxL5cyHsA0Xk0t+526623smnTJhYuXIjL5WLcuHHceuut55wOaNCgQTz44IMsWrSIRYsWodfrSU9PZ86cOcTExLRKXm6++Wb+8Y9/8OGHH1JTU8PEiRPp06dPm8e1lt5fiO5L4rK3Sy+9lOPHj7NhwwZWrFhBdHQ0w4cP97te3VrOt24ghPCPoslqaqID+sMf/kBISAjz5s1r76Q06eWXX2bLli3861//au+kCNEpSRkSon3t3buXRx99lHvvvderoVEI0bXMnz+fsrIynnvuufZOihCik5s1axbTpk2TEdtCdHJSNxCi7cjknKJdOZ3OBnNA7927lxMnTjBgwIB2SpUQQgghhBBCCCGEEEIIcX5kCjLRrgoLC3n88ce56KKLiIiI4PTp06xdu5awsDDPVAZCCCGEEEIIIYQQQgghRGcjDTCiXQUFBdGrVy+++OILSktLMZvNDB06lBtvvNHvBa2FEEIIIYQQQgghhBBCiI5G1oARQgghhBBCCCGEEEIIIYRoZbIGjBBCCCGEEEIIIYQQQgghRCuTBhghhBBCCCGEEEIIIYQQQohWJg0wQgghhBBCCCGEEEIIIYQQrUwaYIQQQgghhBBCCCGEEEIIIVqZNMAIIYQQQgghhBBCCCGEEEK0MmmAEUIIIYQQQgghhBBCCCGEaGXSACOEEEIIIYQQQgghhBBCCNHKpAFGCCGEEEIIIYQQQgghhBCilUkDjBBCCCGEEEIIIYQQQgghRCv7/1Qkt7sItzV1AAAAAElFTkSuQmCC\n" }, "metadata": {} } ] }, { "cell_type": "code", "source": [ "plt.figure(figsize=(8,6))\n", "\n", "sns.scatterplot(\n", " data=df.sample(2000, random_state=42),\n", " x=\"Engine rpm\",\n", " y=\"Fuel pressure\",\n", " hue=\"Engine Condition\",\n", " alpha=0.7\n", ")\n", "\n", "plt.title(\"Engine RPM vs Fuel Pressure\")\n", "plt.show()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 569 }, "id": "OKQwgktfRIY1", "outputId": "73eda39b-3cc3-4f21-dbc5-4525639a48ca" }, "execution_count": 25, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "
" ], "image/png": 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\n" }, "metadata": {} } ] }, { "cell_type": "markdown", "source": [ "### **Observations**\n", "\n", "- The pairwise relationships indicate that most predictor variables exhibit weak linear relationships with one another, confirming the findings from the correlation analysis.\n", "- The scatter plots show noticeable overlap between the two engine condition classes, indicating that no single feature can perfectly separate healthy and faulty engine conditions.\n", "- Engine RPM demonstrates the most visible variation between the two classes, while the remaining variables show relatively similar distributions.\n", "- The absence of strong multicollinearity among predictor variables suggests that all sensor measurements can be considered during model development without introducing significant redundancy.\n", "- The multivariate analysis indicates that combining multiple sensor readings is likely to improve predictive performance compared to relying on any individual feature." ], "metadata": { "id": "QpFUyWzRRb2h" } }, { "cell_type": "markdown", "source": [ "# 3.7 Key Insights from Exploratory Data Analysis\n", "\n", "### Key Findings\n", "\n", "- The dataset contains **19,535 records** with **no missing values** or **duplicate records**, indicating excellent data quality.\n", "- The numerical variables exhibit varying distributions and contain several outliers, which likely represent genuine abnormal operating conditions rather than data quality issues.\n", "- The target variable is moderately imbalanced, with approximately **63%** of observations belonging to Engine Condition = 1 and **37%** belonging to Engine Condition = 0.\n", "- Engine RPM is the most influential predictor based on correlation analysis, while the remaining variables contribute complementary information.\n", "- Weak correlations among predictor variables indicate minimal multicollinearity, making the dataset suitable for tree-based machine learning algorithms.\n", "- The EDA suggests that predictive performance is expected to improve when multiple sensor readings are used together rather than relying on individual variables." ], "metadata": { "id": "HMXXaQajRfj7" } }, { "cell_type": "markdown", "source": [ "# 4. Data Preparation\n", "\n", "## Methodology\n", "\n", "The dataset was loaded directly from the Hugging Face Dataset Hub to ensure reproducibility and centralized data management. Data quality checks were performed to identify missing values, duplicate records, incorrect data types, and unnecessary columns. Since the dataset was already clean and all features were relevant to the prediction task, no records or columns were removed. The cleaned dataset was then split into training and testing sets using stratified sampling to preserve the class distribution. Finally, the train and test datasets were saved locally and uploaded back to the Hugging Face Dataset Hub for use in subsequent model building." ], "metadata": { "id": "ePQaOwPGR3iB" } }, { "cell_type": "code", "source": [ "from datasets import load_dataset\n", "\n", "dataset = load_dataset(\n", " \"Swetha1929/predictive-maintenance-engine-data\",\n", " data_files=\"engine_data.csv\"\n", ")\n", "\n", "df = dataset[\"train\"].to_pandas()\n", "\n", "df.head()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 206 }, "id": "SP8pn3GsRIWK", "outputId": "25dd2e08-5f05-4276-8fe5-8e3a58e97a18" }, "execution_count": 26, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ " Engine rpm Lub oil pressure Fuel pressure Coolant pressure \\\n", "0 700 2.493592 11.790927 3.178981 \n", "1 876 2.941606 16.193866 2.464504 \n", "2 520 2.961746 6.553147 1.064347 \n", "3 473 3.707835 19.510172 3.727455 \n", "4 619 5.672919 15.738871 2.052251 \n", "\n", " lub oil temp Coolant temp Engine Condition \n", "0 84.144163 81.632187 1 \n", "1 77.640934 82.445724 0 \n", "2 77.752266 79.645777 1 \n", "3 74.129907 71.774629 1 \n", "4 78.396989 87.000225 0 " ], "text/html": [ "\n", "
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\n" ], "application/vnd.google.colaboratory.intrinsic+json": { "type": "dataframe", "variable_name": "df", "summary": "{\n \"name\": \"df\",\n \"rows\": 19535,\n \"fields\": [\n {\n \"column\": \"Engine rpm\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 267,\n \"min\": 61,\n \"max\": 2239,\n \"num_unique_values\": 1379,\n \"samples\": [\n 769,\n 487,\n 361\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Lub oil pressure\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 1.0216429993848954,\n \"min\": 0.003384113,\n \"max\": 7.265565536,\n \"num_unique_values\": 19534,\n \"samples\": [\n 2.391655927,\n 4.14845628,\n 3.434232242\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Fuel pressure\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 2.7610206475560832,\n \"min\": 0.003187131,\n \"max\": 21.13832551,\n \"num_unique_values\": 19531,\n \"samples\": [\n 4.662180679,\n 5.24546903,\n 7.328920195\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Coolant pressure\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 1.0363821029008675,\n \"min\": 0.002482733,\n \"max\": 7.478504946,\n \"num_unique_values\": 19534,\n \"samples\": [\n 2.848982106,\n 3.325827862,\n 1.678708216\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"lub oil temp\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 3.1109839372719557,\n \"min\": 71.32197369,\n \"max\": 89.58079551,\n \"num_unique_values\": 19530,\n \"samples\": [\n 85.54132656,\n 76.79341688,\n 77.56054945\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Coolant temp\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 6.2067492865594085,\n \"min\": 61.67332472,\n \"max\": 195.5279116,\n \"num_unique_values\": 19532,\n \"samples\": [\n 68.76941602,\n 74.49854035,\n 72.51043304\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"Engine Condition\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0,\n \"min\": 0,\n \"max\": 1,\n \"num_unique_values\": 2,\n \"samples\": [\n 0,\n 1\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}" } }, "metadata": {}, "execution_count": 26 } ] }, { "cell_type": "code", "source": [ "print(\"Missing Values:\\n\")\n", "print(df.isnull().sum())" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "dE2jgZp_RITO", "outputId": "da957dac-722e-44b1-9c6b-719475bb183d" }, "execution_count": 27, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Missing Values:\n", "\n", "Engine rpm 0\n", "Lub oil pressure 0\n", "Fuel pressure 0\n", "Coolant pressure 0\n", "lub oil temp 0\n", "Coolant temp 0\n", "Engine Condition 0\n", "dtype: int64\n" ] } ] }, { "cell_type": "code", "source": [ "df_clean = df.copy()\n", "\n", "print(\"Dataset Shape:\", df_clean.shape)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "QiBoSKjeRIQ1", "outputId": "9c5d8827-f725-4846-d46d-bbf4ee227daa" }, "execution_count": 28, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Dataset Shape: (19535, 7)\n" ] } ] }, { "cell_type": "markdown", "source": [ "Now Split the Dataset" ], "metadata": { "id": "PozmA3b4SFeU" } }, { "cell_type": "code", "source": [ "from sklearn.model_selection import train_test_split\n", "\n", "X = df_clean.drop(\"Engine Condition\", axis=1)\n", "y = df_clean[\"Engine Condition\"]\n", "\n", "X_train, X_test, y_train, y_test = train_test_split(\n", " X,\n", " y,\n", " test_size=0.20,\n", " random_state=42,\n", " stratify=y\n", ")" ], "metadata": { "id": "6rcl9NPqRIOK" }, "execution_count": 29, "outputs": [] }, { "cell_type": "code", "source": [ "train_df = X_train.copy()\n", "train_df[\"Engine Condition\"] = y_train\n", "\n", "test_df = X_test.copy()\n", "test_df[\"Engine Condition\"] = y_test\n", "\n", "print(\"Training Set Shape :\", train_df.shape)\n", "print(\"Testing Set Shape :\", test_df.shape)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "TZ-xS94SRILh", "outputId": "8591c5e0-3cb0-4f1d-891f-ec9e1f2d7a72" }, "execution_count": 30, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Training Set Shape : (15628, 7)\n", "Testing Set Shape : (3907, 7)\n" ] } ] }, { "cell_type": "markdown", "source": [ "#Save the file Locally" ], "metadata": { "id": "Ehwxv7WbSMTw" } }, { "cell_type": "code", "source": [ "train_df.to_csv(\"/content/train.csv\", index=False)\n", "test_df.to_csv(\"/content/test.csv\", index=False)\n", "\n", "print(\"Train and Test datasets saved successfully.\")" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "ulazkfEcQmfT", "outputId": "ac19552e-ffed-473c-b901-4f66453eea8f" }, "execution_count": 32, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Train and Test datasets saved successfully.\n" ] } ] }, { "cell_type": "markdown", "source": [ "#Upload this on Hugging Face" ], "metadata": { "id": "Bu-eljIcSQGj" } }, { "cell_type": "code", "source": [ "from huggingface_hub import HfApi, notebook_login\n", "\n", "# Log in to Hugging Face\n", "notebook_login()\n", "\n", "api = HfApi()\n", "\n", "repo_id = \"Swetha1929/predictive-maintenance-engine-data\"\n", "\n", "# Optional: Uncomment the line below if the repository does not exist and you want to create it.\n", "# api.create_repo(repo_id=repo_id, repo_type=\"dataset\", private=False, exist_ok=True)\n", "\n", "api.upload_file(\n", " path_or_fileobj=\"/content/train.csv\",\n", " path_in_repo=\"train.csv\",\n", " repo_id=repo_id,\n", " repo_type=\"dataset\"\n", ")\n", "\n", "api.upload_file(\n", " path_or_fileobj=\"/content/test.csv\",\n", " path_in_repo=\"test.csv\",\n", " repo_id=repo_id,\n", " repo_type=\"dataset\"\n", ")\n", "\n", "print(\"Train and Test datasets uploaded successfully!\")" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "OAsEtMpzQmcs", "outputId": "16426f6b-9a28-4f85-d8e3-eeb129e36669" }, "execution_count": 33, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "No files have been modified since last commit. Skipping to prevent empty commit.\n", "WARNING:huggingface_hub.hf_api:No files have been modified since last commit. Skipping to prevent empty commit.\n", "No files have been modified since last commit. Skipping to prevent empty commit.\n", "WARNING:huggingface_hub.hf_api:No files have been modified since last commit. Skipping to prevent empty commit.\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "Train and Test datasets uploaded successfully!\n" ] } ] }, { "cell_type": "markdown", "source": [ "#Building The Model" ], "metadata": { "id": "zS2NrXAXSgHG" } }, { "cell_type": "code", "source": [ "from huggingface_hub import HfApi\n", "\n", "api = HfApi()\n", "\n", "api.upload_file(\n", " path_or_fileobj=\"/content/engine_data.csv\",\n", " path_in_repo=\"engine_data.csv\",\n", " repo_id=\"Swetha1929/predictive-maintenance-engine-data\",\n", " repo_type=\"dataset\",\n", ")" ], "metadata": { "id": "WtP9AQUJPV0i" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "execution_count": null, "metadata": { "id": "JcbwurJycaQ9" }, "outputs": [], "source": [ "import os\n", "import json\n", "import warnings\n", "warnings.filterwarnings(\"ignore\")\n" ] }, { "cell_type": "code", "source": [ "import numpy as np\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "\n", "from huggingface_hub import hf_hub_download" ], "metadata": { "id": "yVW1l_lreyXz" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "from sklearn.model_selection import train_test_split, RandomizedSearchCV\n", "from sklearn.tree import DecisionTreeClassifier\n", "from sklearn.metrics import (\n", " accuracy_score,\n", " precision_score,\n", " recall_score,\n", " f1_score,\n", " roc_auc_score,\n", " classification_report,\n", " confusion_matrix,\n", " ConfusionMatrixDisplay,\n", ")\n", "from sklearn.pipeline import Pipeline" ], "metadata": { "id": "h75EzZY2e06e" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "!pip install mlflow\n", "import mlflow\n", "import mlflow.sklearn" ], "metadata": { "id": "hId4rplwe4F7", "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "89ace3ad-ad2a-4d32-eb37-ecc9a4aaa52d" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Collecting 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that are installed. This behaviour is the source of the following dependency conflicts.\n", "pyopenssl 26.3.0 requires cryptography<50,>=49.0.0, but you have cryptography 48.0.1 which is incompatible.\u001b[0m\u001b[31m\n", "\u001b[0mSuccessfully installed Flask-CORS-6.0.5 alembic-1.18.5 cryptography-48.0.1 databricks-sdk-0.120.0 docker-7.2.0 graphene-3.4.3 graphql-core-3.2.11 graphql-relay-3.2.0 gunicorn-26.0.0 huey-3.2.1 mlflow-3.14.0 mlflow-skinny-3.14.0 mlflow-tracing-3.14.0 opentelemetry-proto-1.43.0 skops-0.14.0\n" ] } ] }, { "cell_type": "code", "source": [ "HF_REPO_ID = \"Swetha1929/predictive-maintenance-engine-data\"\n", "TRAIN_FILE = \"train.csv\"\n", "TEST_FILE = \"test.csv\"" ], "metadata": { "id": "wcrcU5fmfVKh" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "target_col = \"Engine Condition\"\n", "random_state = 42\n", "val_size = 0.20" ], "metadata": { "id": "ur7UH2Mnfa3R" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "# Load datasets directly from Hugging Face\n", "train_path = hf_hub_download(\n", " repo_id=HF_REPO_ID,\n", " repo_type=\"dataset\",\n", " filename=TRAIN_FILE\n", ")\n" ], "metadata": { "id": "u1ZKyre3fgil", "colab": { "base_uri": "https://localhost:8080/", "height": 104, "referenced_widgets": [ "97f62edb7e08422d90093d50f93ca551", "ee4436b45f234ba5a0bcbf34f1407c05", "f33ddb6fc6b447a088218ef49728118f", "6c56a107c54f4c5c8c8a6e4a108d2c76", "19c1c5e2c6d34e3dbf0aa32fbc693000", "2d765df7c2794f0bacff94bc464b9f75", "406041def20c460da5bf16dcd234893c", "07e9ffc3ea524551aa76ab3ba6f52ab3", "97cb1a829dbd45ba84ef651da383a792", "7cc2f15e561e4a18956ffeda10e9837a", "c03dcb7c102f487d9c80ee680e72b09b" ] }, "outputId": "82ada3f7-2ef3-42c5-d099-392a8b6ea242" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "Warning: You are sending unauthenticated requests to the HF Hub. Please set a HF_TOKEN to enable higher rate limits and faster downloads.\n", "WARNING:huggingface_hub.utils._http:Warning: You are sending unauthenticated requests to the HF Hub. Please set a HF_TOKEN to enable higher rate limits and faster downloads.\n" ] }, { "output_type": "display_data", "data": { "text/plain": [ "train.csv: 0%| | 0.00/1.03M [00:00 pd.DataFrame:\n", " \"\"\"\n", " Create domain-inspired engineered features for predictive maintenance.\n", " \"\"\"\n", " df = df.copy()\n", "\n", " df[\"Temp_Difference\"] = df[\"Coolant temp\"] - df[\"lub oil temp\"]\n", " df[\"Avg_Temperature\"] = (df[\"Coolant temp\"] + df[\"lub oil temp\"]) / 2\n", "\n", " df[\"Pressure_Difference\"] = df[\"Fuel pressure\"] - df[\"Lub oil pressure\"]\n", " df[\"Pressure_Ratio\"] = df[\"Fuel pressure\"] / (df[\"Lub oil pressure\"] + 1e-6)\n", " df[\"Avg_Pressure\"] = (\n", " df[\"Fuel pressure\"] + df[\"Lub oil pressure\"] + df[\"Coolant pressure\"]\n", " ) / 3\n", "\n", " df[\"RPM_FuelPressure\"] = df[\"Engine rpm\"] * df[\"Fuel pressure\"]\n", " df[\"RPM_CoolantTemp\"] = df[\"Engine rpm\"] * df[\"Coolant temp\"]\n", "\n", " return df" ], "metadata": { "id": "mAlfR3tqjCKx" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "train_fe = create_engineered_features(train_final)\n", "validation_fe = create_engineered_features(validation_df)\n", "test_fe = create_engineered_features(test_df)\n", "\n", "print(\"\\nAfter feature engineering:\")\n", "print(\"Train FE :\", train_fe.shape)\n", "print(\"Validation FE :\", validation_fe.shape)\n", "print(\"Test FE :\", test_fe.shape)" ], "metadata": { "id": "vCLrGadNjD5Q", "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "e348a6d9-e158-4d37-883d-3ea4e779052f" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "\n", "After feature engineering:\n", "Train FE : (12502, 14)\n", "Validation FE : (3126, 14)\n", "Test FE : (3907, 14)\n" ] } ] }, { "cell_type": "markdown", "source": [ "Feature Selection\n" ], "metadata": { "id": "ROrxczbWjcR7" } }, { "cell_type": "code", "source": [ "from collections import Counter\n", "\n", "from sklearn.base import BaseEstimator, TransformerMixin\n", "from sklearn.feature_selection import VarianceThreshold, SelectKBest, mutual_info_classif, SelectFromModel, RFE\n", "from sklearn.ensemble import RandomForestClassifier" ], "metadata": { "id": "zsjtdaAcjbi-" }, "execution_count": null, "outputs": [] }, { "cell_type": "markdown", "source": [ "# Custom selector for pipeline use later" ], "metadata": { "id": "P4TD3sKbjrvh" } }, { "cell_type": "code", "source": [ "class ColumnSelector(BaseEstimator, TransformerMixin):\n", " def __init__(self, columns=None):\n", " self.columns = columns\n", "\n", " def fit(self, X, y=None):\n", " if self.columns is None:\n", " self.columns_ = list(X.columns)\n", " else:\n", " self.columns_ = list(self.columns)\n", " return self\n", "\n", " def transform(self, X):\n", " return X.loc[:, self.columns_]\n", "\n", " def get_feature_names_out(self, input_features=None):\n", " return np.array(self.columns_)\n" ], "metadata": { "id": "eI8wfd6KjpGJ" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "X_train_fe = train_fe.drop(columns=[target_col])\n", "y_train_fe = train_fe[target_col]\n", "\n", "X_val_fe = validation_fe.drop(columns=[target_col])\n", "y_val_fe = validation_fe[target_col]\n", "\n", "X_test_fe = test_fe.drop(columns=[target_col], errors=\"ignore\")\n", "y_test_fe = test_fe[target_col]\n", "\n", "feature_names = X_train_fe.columns.tolist()" ], "metadata": { "id": "uQyNmE3hjvPL" }, "execution_count": null, "outputs": [] }, { "cell_type": "markdown", "source": [ "Feature Selection Method\n" ], "metadata": { "id": "Yt6N6K6DkE9q" } }, { "cell_type": "markdown", "source": [ "Now combining them, and log to MLflow" ], "metadata": { "id": "L0fWMe_VkjDF" } }, { "cell_type": "code", "source": [ "import pandas as pd\n", "from collections import Counter\n", "\n", "from sklearn.feature_selection import (\n", " VarianceThreshold,\n", " SelectKBest,\n", " mutual_info_classif,\n", " SelectFromModel,\n", " RFE\n", ")\n", "from sklearn.ensemble import RandomForestClassifier\n", "import mlflow\n", "\n", "\n", "def select_by_variance(X: pd.DataFrame) -> list:\n", " selector = VarianceThreshold(threshold=0.0)\n", " selector.fit(X)\n", " return X.columns[selector.get_support()].tolist()\n", "\n", "\n", "def select_by_mutual_info(X: pd.DataFrame, y: pd.Series, k: int = None) -> list:\n", " if k is None:\n", " k = min(4, X.shape[1])\n", "\n", " selector = SelectKBest(score_func=mutual_info_classif, k=k)\n", " selector.fit(X, y)\n", " return X.columns[selector.get_support()].tolist()\n", "\n", "\n", "def select_by_random_forest_importance(\n", " X: pd.DataFrame,\n", " y: pd.Series,\n", " threshold=\"median\"\n", ") -> list:\n", " estimator = RandomForestClassifier(\n", " n_estimators=300,\n", " random_state=random_state,\n", " n_jobs=-1\n", " )\n", "\n", " selector = SelectFromModel(estimator=estimator, threshold=threshold)\n", " selector.fit(X, y)\n", " return X.columns[selector.get_support()].tolist()\n", "\n", "\n", "def select_by_rfe(\n", " X: pd.DataFrame,\n", " y: pd.Series,\n", " n_features_to_select: int = None\n", ") -> list:\n", " if n_features_to_select is None:\n", " n_features_to_select = min(4, X.shape[1])\n", "\n", " estimator = RandomForestClassifier(\n", " n_estimators=200,\n", " random_state=random_state,\n", " n_jobs=-1\n", " )\n", "\n", " selector = RFE(\n", " estimator=estimator,\n", " n_features_to_select=n_features_to_select,\n", " step=1\n", " )\n", " selector.fit(X, y)\n", " return X.columns[selector.get_support()].tolist()\n", "\n", "\n", "def build_consensus_features(selection_dict: dict, min_votes: int = 2):\n", " \"\"\"\n", " Combine multiple feature selection outputs using vote counting.\n", " \"\"\"\n", " vote_counter = Counter()\n", "\n", " for _, selected_features in selection_dict.items():\n", " vote_counter.update(selected_features)\n", "\n", " vote_df = pd.DataFrame(\n", " sorted(vote_counter.items(), key=lambda x: (-x[1], x[0])),\n", " columns=[\"Feature\", \"Votes\"]\n", " )\n", "\n", " consensus_features = vote_df.loc[\n", " vote_df[\"Votes\"] >= min_votes, \"Feature\"\n", " ].tolist()\n", "\n", " if len(consensus_features) == 0:\n", " consensus_features = vote_df[\"Feature\"].tolist()\n", "\n", " return vote_df, consensus_features\n", "\n", "\n", "with mlflow.start_run(run_name=\"Feature_Selection_Discovery\"):\n", " feature_selections = {}\n", "\n", " with mlflow.start_run(run_name=\"VarianceThreshold\", nested=True):\n", " selected_vt = select_by_variance(X_train_fe)\n", " feature_selections[\"VarianceThreshold\"] = selected_vt\n", " mlflow.log_param(\"selected_count\", len(selected_vt))\n", " mlflow.log_text(\"\\n\".join(selected_vt), \"variance_threshold_features.txt\")\n", "\n", " with mlflow.start_run(run_name=\"MutualInfo\", nested=True):\n", " selected_mi = select_by_mutual_info(\n", " X_train_fe,\n", " y_train_fe,\n", " k=min(4, X_train_fe.shape[1])\n", " )\n", " feature_selections[\"MutualInfo\"] = selected_mi\n", " mlflow.log_param(\"selected_count\", len(selected_mi))\n", " mlflow.log_text(\"\\n\".join(selected_mi), \"mutual_info_features.txt\")\n", "\n", " with mlflow.start_run(run_name=\"RandomForest_Importance\", nested=True):\n", " selected_rf = select_by_random_forest_importance(\n", " X_train_fe,\n", " y_train_fe,\n", " threshold=\"median\"\n", " )\n", " feature_selections[\"RandomForest_Importance\"] = selected_rf\n", " mlflow.log_param(\"selected_count\", len(selected_rf))\n", " mlflow.log_text(\"\\n\".join(selected_rf), \"rf_importance_features.txt\")\n", "\n", " with mlflow.start_run(run_name=\"RFE\", nested=True):\n", " selected_rfe = select_by_rfe(\n", " X_train_fe,\n", " y_train_fe,\n", " n_features_to_select=min(4, X_train_fe.shape[1])\n", " )\n", " feature_selections[\"RFE\"] = selected_rfe\n", " mlflow.log_param(\"selected_count\", len(selected_rfe))\n", " mlflow.log_text(\"\\n\".join(selected_rfe), \"rfe_features.txt\")\n", "\n", " vote_df, consensus_features = build_consensus_features(\n", " feature_selections,\n", " min_votes=2\n", " )\n", "\n", " mlflow.log_param(\"consensus_min_votes\", 2)\n", " mlflow.log_param(\"consensus_feature_count\", len(consensus_features))\n", " mlflow.log_text(vote_df.to_csv(index=False), \"feature_vote_summary.csv\")\n", " mlflow.log_text(\"\\n\".join(consensus_features), \"consensus_features.txt\")\n", "\n", "print(\"Selected features by method:\")\n", "for method, feats in feature_selections.items():\n", " print(f\"\\n{method}: {feats}\")\n", "\n", "print(\"\\nConsensus features:\")\n", "print(consensus_features)\n", "\n", "print(\"Vote summary:\")\n", "print(vote_df)" ], "metadata": { "id": "5N8XJ10qkcZj", "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "c49f1f09-9694-44a2-a839-326986857b74" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "2026/07/14 16:22:20 INFO mlflow.store.db.utils: Creating initial MLflow database tables...\n", "2026/07/14 16:22:20 INFO mlflow.store.db.utils: Updating database tables\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "Selected features by method:\n", "\n", "VarianceThreshold: ['Engine rpm', 'Lub oil pressure', 'Fuel pressure', 'Coolant pressure', 'lub oil temp', 'Coolant temp', 'Temp_Difference', 'Avg_Temperature', 'Pressure_Difference', 'Pressure_Ratio', 'Avg_Pressure', 'RPM_FuelPressure', 'RPM_CoolantTemp']\n", "\n", "MutualInfo: ['Engine rpm', 'lub oil temp', 'RPM_FuelPressure', 'RPM_CoolantTemp']\n", "\n", "RandomForest_Importance: ['Engine rpm', 'Fuel pressure', 'Coolant pressure', 'lub oil temp', 'Avg_Pressure', 'RPM_FuelPressure', 'RPM_CoolantTemp']\n", "\n", "RFE: ['Engine rpm', 'Fuel pressure', 'lub oil temp', 'RPM_CoolantTemp']\n", "\n", "Consensus features:\n", "['Engine rpm', 'RPM_CoolantTemp', 'lub oil temp', 'Fuel pressure', 'RPM_FuelPressure', 'Avg_Pressure', 'Coolant pressure']\n", "Vote summary:\n", " Feature Votes\n", "0 Engine rpm 4\n", "1 RPM_CoolantTemp 4\n", "2 lub oil temp 4\n", "3 Fuel pressure 3\n", "4 RPM_FuelPressure 3\n", "5 Avg_Pressure 2\n", "6 Coolant pressure 2\n", "7 Avg_Temperature 1\n", "8 Coolant temp 1\n", "9 Lub oil pressure 1\n", "10 Pressure_Difference 1\n", "11 Pressure_Ratio 1\n", "12 Temp_Difference 1\n" ] } ] }, { "cell_type": "markdown", "source": [ "Feature selection methods consistently highlighted engine RPM, lubrication oil temperature, fuel pressure, and RPM-based interaction features as the most informative variables. However, the consensus subset did not produce a meaningful performance gain over the original sensor features, so the full feature set was retained for the final model." ], "metadata": { "id": "Eo7Jic1BKC8O" } }, { "cell_type": "code", "source": [ "selected_features = [\n", " \"Engine rpm\",\n", " \"RPM_CoolantTemp\",\n", " \"lub oil temp\",\n", " \"Fuel pressure\",\n", " \"RPM_FuelPressure\",\n", " \"Avg_Pressure\",\n", " \"Coolant pressure\"\n", "]" ], "metadata": { "id": "BvCPBJDxkpz3" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "selected_features = [\n", " \"Engine rpm\",\n", " \"RPM_CoolantTemp\",\n", " \"lub oil temp\",\n", " \"Fuel pressure\",\n", " \"RPM_FuelPressure\",\n", " \"Avg_Pressure\",\n", " \"Coolant pressure\"\n", "]\n", "\n", "X_train_original = X_train.copy()\n", "X_val_original = X_val.copy()\n", "\n", "\n", "X_train_engineered = X_train_fe.copy()\n", "X_val_engineered = X_val_fe.copy()\n", "\n", "X_train_selected = X_train_fe[selected_features].copy()\n", "X_val_selected = X_val_fe[selected_features].copy()\n", "X_test_selected = X_test_fe[selected_features].copy()\n", "\n", "# Targets\n", "y_train_selected = y_train.copy()\n", "y_val_selected = y_val.copy()\n", "y_test_selected = y_test_fe.copy()\n", "\n", "print(\"Original Features :\", X_train_original.shape[1])\n", "print(\"Engineered Features :\", X_train_engineered.shape[1])\n", "print(\"Selected Features :\", X_train_selected.shape[1])" ], "metadata": { "id": "6OiZw1SDmFUd", "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "c0610d92-66e1-4af9-d9e4-58019054cb67" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Original Features : 6\n", "Engineered Features : 13\n", "Selected Features : 7\n" ] } ] }, { "cell_type": "code", "source": [ "print(\"=\" * 50)\n", "print(\"Feature-Selected Dataset Shapes\")\n", "print(\"=\" * 50)" ], "metadata": { "id": "gNV03HrpmP9D", "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "fbc6ad4b-d032-40d0-a406-b27901d103c5" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "==================================================\n", "Feature-Selected Dataset Shapes\n", "==================================================\n" ] } ] }, { "cell_type": "code", "source": [ "print(f\"X_train_selected : {X_train_selected.shape}\")\n", "print(f\"y_train_selected : {y_train_selected.shape}\")\n", "\n", "print(f\"X_val_selected : {X_val_selected.shape}\")\n", "print(f\"y_val_selected : {y_val_selected.shape}\")\n", "\n", "print(f\"X_test_selected : {X_test_selected.shape}\")\n", "print(f\"y_test_selected : {y_test_selected.shape}\")\n", "\n", "print(\"\\nSelected Features:\")\n", "for i, feature in enumerate(selected_features, start=1):\n", " print(f\"{i}. {feature}\")" ], "metadata": { "id": "XeARt6IamWKY", "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "5ee74482-052c-4557-e690-4343426ed20c" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "X_train_selected : (12502, 7)\n", "y_train_selected : (12502,)\n", "X_val_selected : (3126, 7)\n", "y_val_selected : (3126,)\n", "X_test_selected : (3907, 7)\n", "y_test_selected : (3907,)\n", "\n", "Selected Features:\n", "1. Engine rpm\n", "2. RPM_CoolantTemp\n", "3. lub oil temp\n", "4. Fuel pressure\n", "5. RPM_FuelPressure\n", "6. Avg_Pressure\n", "7. Coolant pressure\n" ] } ] }, { "cell_type": "markdown", "source": [ "#Testing Baseline Model for original Data" ], "metadata": { "id": "K8fa3AsHM090" } }, { "cell_type": "code", "source": [ "import os\n", "import pandas as pd\n", "import mlflow\n", "import mlflow.sklearn\n", "\n", "from sklearn.tree import DecisionTreeClassifier\n", "from sklearn.metrics import (\n", " accuracy_score,\n", " precision_score,\n", " recall_score,\n", " f1_score,\n", " roc_auc_score,\n", " confusion_matrix,\n", " classification_report\n", ")\n", "\n", "# Set experiment\n", "mlflow.set_experiment(\"Engine_Condition_Baseline\")\n", "\n", "with mlflow.start_run(run_name=\"Baseline_DecisionTree\"):\n", "\n", " # Baseline model\n", " baseline_model = DecisionTreeClassifier(random_state=random_state)\n", "\n", " # Fit on training data\n", " baseline_model.fit(X_train_original, y_train)\n", "\n", " # Predictions on validation data\n", " val_preds = baseline_model.predict(X_val_original)\n", " val_probs = baseline_model.predict_proba(X_val_original)[:, 1]\n", "\n", " # Metrics\n", " acc = accuracy_score(y_val, val_preds)\n", " prec = precision_score(y_val, val_preds)\n", " rec = recall_score(y_val, val_preds)\n", " f1 = f1_score(y_val, val_preds)\n", " auc = roc_auc_score(y_val, val_probs)\n", "\n", " # Log params\n", " mlflow.log_param(\"model_type\", \"DecisionTreeClassifier\")\n", " mlflow.log_param(\"random_state\", random_state)\n", "\n", " # Log metrics\n", " mlflow.log_metric(\"val_accuracy\", acc)\n", " mlflow.log_metric(\"val_precision\", prec)\n", " mlflow.log_metric(\"val_recall\", rec)\n", " mlflow.log_metric(\"val_f1\", f1)\n", " mlflow.log_metric(\"val_roc_auc\", auc)\n", "\n", " # Confusion matrix artifact\n", " cm = confusion_matrix(y_val, val_preds)\n", " cm_df = pd.DataFrame(cm, index=[\"Actual_0\", \"Actual_1\"], columns=[\"Pred_0\", \"Pred_1\"])\n", " cm_path = \"baseline_confusion_matrix.csv\"\n", " cm_df.to_csv(cm_path)\n", " mlflow.log_artifact(cm_path)\n", "\n", " # Classification report artifact\n", " report = classification_report(y_val, val_preds)\n", " report_path = \"baseline_classification_report.txt\"\n", " with open(report_path, \"w\") as f:\n", " f.write(report)\n", " mlflow.log_artifact(report_path)\n", "\n", " # Log model\n", " mlflow.sklearn.log_model(baseline_model, artifact_path=\"baseline_model\")\n", "\n", "print(\"Baseline validation results:\")\n", "print(f\"Accuracy : {acc:.4f}\")\n", "print(f\"Precision: {prec:.4f}\")\n", "print(f\"Recall : {rec:.4f}\")\n", "print(f\"F1 : {f1:.4f}\")\n", "print(f\"ROC AUC : {auc:.4f}\")" ], "metadata": { "id": "zXrCGk0Rmny4", "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "5984c876-0eea-448c-fc8e-08c9aa2b3dd1" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "2026/07/14 16:25:50 INFO mlflow.tracking.fluent: Experiment with name 'Engine_Condition_Baseline' does not exist. Creating a new experiment.\n", "2026/07/14 16:25:50 WARNING mlflow.models.model: `artifact_path` is deprecated. Please use `name` instead.\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "Baseline validation results:\n", "Accuracy : 0.5781\n", "Precision: 0.6635\n", "Recall : 0.6712\n", "F1 : 0.6673\n", "ROC AUC : 0.5451\n" ] } ] }, { "cell_type": "markdown", "source": [ "#Testing Baseline Model for Featured Engineer Data" ], "metadata": { "id": "iyHj3HasNTMH" } }, { "cell_type": "markdown", "source": [], "metadata": { "id": "VSzVxpoqNIgG" } }, { "cell_type": "code", "source": [ "import os\n", "import pandas as pd\n", "import mlflow\n", "import mlflow.sklearn\n", "\n", "from sklearn.tree import DecisionTreeClassifier\n", "from sklearn.metrics import (\n", " accuracy_score,\n", " precision_score,\n", " recall_score,\n", " f1_score,\n", " roc_auc_score,\n", " confusion_matrix,\n", " classification_report\n", ")\n", "\n", "# Set experiment\n", "mlflow.set_experiment(\"Engine_Condition_Feature_Engineering\")\n", "\n", "with mlflow.start_run(run_name=\"DecisionTree_FeatureEngineered\"):\n", "\n", " # Baseline model\n", " baseline_model = DecisionTreeClassifier(random_state=random_state)\n", "\n", " # Fit on engineered training data\n", " baseline_model.fit(X_train_fe, y_train)\n", "\n", " # Predictions on engineered validation data\n", " val_preds = baseline_model.predict(X_val_fe)\n", " val_probs = baseline_model.predict_proba(X_val_fe)[:, 1]\n", "\n", " # Metrics\n", " acc = accuracy_score(y_val, val_preds)\n", " prec = precision_score(y_val, val_preds)\n", " rec = recall_score(y_val, val_preds)\n", " f1 = f1_score(y_val, val_preds)\n", " auc = roc_auc_score(y_val, val_probs)\n", "\n", " # Log parameters\n", " mlflow.log_param(\"model_type\", \"DecisionTreeClassifier\")\n", " mlflow.log_param(\"feature_set\", \"Engineered\")\n", " mlflow.log_param(\"random_state\", random_state)\n", " mlflow.log_param(\"num_features\", X_train_fe.shape[1])\n", "\n", " # Log metrics\n", " mlflow.log_metric(\"val_accuracy\", acc)\n", " mlflow.log_metric(\"val_precision\", prec)\n", " mlflow.log_metric(\"val_recall\", rec)\n", " mlflow.log_metric(\"val_f1\", f1)\n", " mlflow.log_metric(\"val_roc_auc\", auc)\n", "\n", " # Confusion Matrix\n", " cm = confusion_matrix(y_val, val_preds)\n", " cm_df = pd.DataFrame(\n", " cm,\n", " index=[\"Actual_0\", \"Actual_1\"],\n", " columns=[\"Pred_0\", \"Pred_1\"]\n", " )\n", "\n", " cm_path = \"feature_engineered_confusion_matrix.csv\"\n", " cm_df.to_csv(cm_path)\n", " mlflow.log_artifact(cm_path)\n", "\n", " # Classification Report\n", " report = classification_report(y_val, val_preds)\n", "\n", " report_path = \"feature_engineered_classification_report.txt\"\n", " with open(report_path, \"w\") as f:\n", " f.write(report)\n", "\n", " mlflow.log_artifact(report_path)\n", "\n", " # Log Model\n", " mlflow.sklearn.log_model(\n", " baseline_model,\n", " artifact_path=\"feature_engineered_model\"\n", " )\n", "\n", "print(\"Feature Engineered Validation Results:\")\n", "print(f\"Accuracy : {acc:.4f}\")\n", "print(f\"Precision: {prec:.4f}\")\n", "print(f\"Recall : {rec:.4f}\")\n", "print(f\"F1 : {f1:.4f}\")\n", "print(f\"ROC AUC : {auc:.4f}\")" ], "metadata": { "id": "DUoqHCBOomLr", "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "c7467ff6-f7bc-4ea4-aa81-56f3b15edc60" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "2026/07/14 16:26:14 INFO mlflow.tracking.fluent: Experiment with name 'Engine_Condition_Feature_Engineering' does not exist. Creating a new experiment.\n", "2026/07/14 16:26:15 WARNING mlflow.models.model: `artifact_path` is deprecated. Please use `name` instead.\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "Feature Engineered Validation Results:\n", "Accuracy : 0.5854\n", "Precision: 0.6751\n", "Recall : 0.6601\n", "F1 : 0.6675\n", "ROC AUC : 0.5590\n" ] } ] }, { "cell_type": "code", "source": [ "import os\n", "import pandas as pd\n", "import mlflow\n", "import mlflow.sklearn\n", "\n", "from sklearn.tree import DecisionTreeClassifier\n", "from sklearn.metrics import (\n", " accuracy_score,\n", " precision_score,\n", " recall_score,\n", " f1_score,\n", " roc_auc_score,\n", " confusion_matrix,\n", " classification_report\n", ")\n", "\n", "# Keep the same experiment\n", "mlflow.set_experiment(\"Engine_Condition_Model_Building\")\n", "\n", "with mlflow.start_run(run_name=\"DecisionTree_FeatureSelected\"):\n", "\n", " # Baseline model\n", " baseline_model = DecisionTreeClassifier(random_state=random_state)\n", "\n", " # Train\n", " baseline_model.fit(X_train_selected, y_train)\n", "\n", " # Validation predictions\n", " val_preds = baseline_model.predict(X_val_selected)\n", " val_probs = baseline_model.predict_proba(X_val_selected)[:, 1]\n", "\n", " # Metrics\n", " acc = accuracy_score(y_val, val_preds)\n", " prec = precision_score(y_val, val_preds)\n", " rec = recall_score(y_val, val_preds)\n", " f1 = f1_score(y_val, val_preds)\n", " auc = roc_auc_score(y_val, val_probs)\n", "\n", " # Parameters\n", " mlflow.log_param(\"model_type\", \"DecisionTreeClassifier\")\n", " mlflow.log_param(\"feature_set\", \"Selected\")\n", " mlflow.log_param(\"random_state\", random_state)\n", " mlflow.log_param(\"num_features\", X_train_selected.shape[1])\n", "\n", " # Metrics\n", " mlflow.log_metric(\"val_accuracy\", acc)\n", " mlflow.log_metric(\"val_precision\", prec)\n", " mlflow.log_metric(\"val_recall\", rec)\n", " mlflow.log_metric(\"val_f1\", f1)\n", " mlflow.log_metric(\"val_roc_auc\", auc)\n", "\n", " # Confusion Matrix\n", " cm = confusion_matrix(y_val, val_preds)\n", " cm_df = pd.DataFrame(\n", " cm,\n", " index=[\"Actual_0\", \"Actual_1\"],\n", " columns=[\"Pred_0\", \"Pred_1\"]\n", " )\n", "\n", " cm_path = \"feature_selected_confusion_matrix.csv\"\n", " cm_df.to_csv(cm_path)\n", " mlflow.log_artifact(cm_path)\n", "\n", " # Classification Report\n", " report = classification_report(y_val, val_preds)\n", "\n", " report_path = \"feature_selected_classification_report.txt\"\n", " with open(report_path, \"w\") as f:\n", " f.write(report)\n", "\n", " mlflow.log_artifact(report_path)\n", "\n", " # Log Model\n", " mlflow.sklearn.log_model(\n", " baseline_model,\n", " artifact_path=\"feature_selected_model\"\n", " )\n", "\n", "print(\"Feature Selected Validation Results:\")\n", "print(f\"Accuracy : {acc:.4f}\")\n", "print(f\"Precision: {prec:.4f}\")\n", "print(f\"Recall : {rec:.4f}\")\n", "print(f\"F1 : {f1:.4f}\")\n", "print(f\"ROC AUC : {auc:.4f}\")" ], "metadata": { "id": "tQb28PlSpD4h", "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "ff61c913-6f11-4edf-ef9d-6fc3e7e8ee2b" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "2026/07/14 16:26:30 INFO mlflow.tracking.fluent: Experiment with name 'Engine_Condition_Model_Building' does not exist. Creating a new experiment.\n", "2026/07/14 16:26:30 WARNING mlflow.models.model: `artifact_path` is deprecated. Please use `name` instead.\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "Feature Selected Validation Results:\n", "Accuracy : 0.5813\n", "Precision: 0.6680\n", "Recall : 0.6677\n", "F1 : 0.6679\n", "ROC AUC : 0.5507\n" ] } ] }, { "cell_type": "code", "source": [ "import os\n", "import pandas as pd\n", "import mlflow\n", "import mlflow.sklearn\n", "\n", "from sklearn.tree import DecisionTreeClassifier\n", "from sklearn.metrics import (\n", " accuracy_score,\n", " precision_score,\n", " recall_score,\n", " f1_score,\n", " roc_auc_score,\n", " confusion_matrix,\n", " classification_report\n", ")\n", "\n", "mlflow.set_experiment(\"Engine_Condition_Model_Building\")\n", "\n", "def run_decision_tree_experiment(run_name, X_tr, X_va, feature_set_name):\n", " with mlflow.start_run(run_name=run_name):\n", "\n", " model = DecisionTreeClassifier(random_state=random_state)\n", " model.fit(X_tr, y_train)\n", "\n", " val_preds = model.predict(X_va)\n", " val_probs = model.predict_proba(X_va)[:, 1]\n", "\n", " acc = accuracy_score(y_val, val_preds)\n", " prec = precision_score(y_val, val_preds)\n", " rec = recall_score(y_val, val_preds)\n", " f1 = f1_score(y_val, val_preds)\n", " auc = roc_auc_score(y_val, val_probs)\n", "\n", " mlflow.log_param(\"model_type\", \"DecisionTreeClassifier\")\n", " mlflow.log_param(\"feature_set\", feature_set_name)\n", " mlflow.log_param(\"random_state\", random_state)\n", " mlflow.log_param(\"num_features\", X_tr.shape[1])\n", "\n", " mlflow.log_metric(\"val_accuracy\", acc)\n", " mlflow.log_metric(\"val_precision\", prec)\n", " mlflow.log_metric(\"val_recall\", rec)\n", " mlflow.log_metric(\"val_f1\", f1)\n", " mlflow.log_metric(\"val_roc_auc\", auc)\n", "\n", " cm = confusion_matrix(y_val, val_preds)\n", " cm_df = pd.DataFrame(\n", " cm,\n", " index=[\"Actual_0\", \"Actual_1\"],\n", " columns=[\"Pred_0\", \"Pred_1\"]\n", " )\n", " cm_path = f\"{feature_set_name.lower()}_confusion_matrix.csv\"\n", " cm_df.to_csv(cm_path, index=True)\n", " mlflow.log_artifact(cm_path)\n", "\n", " report = classification_report(y_val, val_preds)\n", " report_path = f\"{feature_set_name.lower()}_classification_report.txt\"\n", " with open(report_path, \"w\") as f:\n", " f.write(report)\n", " mlflow.log_artifact(report_path)\n", "\n", " mlflow.sklearn.log_model(model, artifact_path=f\"{feature_set_name.lower()}_model\")\n", "\n", " print(f\"\\n{run_name} Validation Results:\")\n", " print(f\"Accuracy : {acc:.4f}\")\n", " print(f\"Precision: {prec:.4f}\")\n", " print(f\"Recall : {rec:.4f}\")\n", " print(f\"F1 : {f1:.4f}\")\n", " print(f\"ROC AUC : {auc:.4f}\")\n", "\n", "\n", "# Run 1: Original features\n", "run_decision_tree_experiment(\n", " run_name=\"DecisionTree_Original\",\n", " X_tr=X_train_original,\n", " X_va=X_val_original,\n", " feature_set_name=\"Original\"\n", ")\n", "\n", "# Run 2: Engineered features\n", "run_decision_tree_experiment(\n", " run_name=\"DecisionTree_FeatureEngineered\",\n", " X_tr=X_train_fe,\n", " X_va=X_val_fe,\n", " feature_set_name=\"FeatureEngineered\"\n", ")\n", "\n", "# Run 3: Selected features\n", "run_decision_tree_experiment(\n", " run_name=\"DecisionTree_FeatureSelected\",\n", " X_tr=X_train_selected,\n", " X_va=X_val_selected,\n", " feature_set_name=\"FeatureSelected\"\n", ")" ], "metadata": { "id": "jslA3wruPG5h", "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "994c270e-5cf6-4d86-a75a-e897157ff958" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "2026/07/14 16:26:41 WARNING mlflow.models.model: `artifact_path` is deprecated. Please use `name` instead.\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "\n", "DecisionTree_Original Validation Results:\n", "Accuracy : 0.5781\n", "Precision: 0.6635\n", "Recall : 0.6712\n", "F1 : 0.6673\n", "ROC AUC : 0.5451\n" ] }, { "output_type": "stream", "name": "stderr", "text": [ "2026/07/14 16:26:52 WARNING mlflow.models.model: `artifact_path` is deprecated. Please use `name` instead.\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "\n", "DecisionTree_FeatureEngineered Validation Results:\n", "Accuracy : 0.5854\n", "Precision: 0.6751\n", "Recall : 0.6601\n", "F1 : 0.6675\n", "ROC AUC : 0.5590\n" ] }, { "output_type": "stream", "name": "stderr", "text": [ "2026/07/14 16:27:03 WARNING mlflow.models.model: `artifact_path` is deprecated. Please use `name` instead.\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "\n", "DecisionTree_FeatureSelected Validation Results:\n", "Accuracy : 0.5813\n", "Precision: 0.6680\n", "Recall : 0.6677\n", "F1 : 0.6679\n", "ROC AUC : 0.5507\n" ] } ] }, { "cell_type": "markdown", "source": [ "An embedded feature selection process was performed using four different techniques, followed by a consensus voting strategy. The baseline Decision Tree model was trained using both the complete engineered feature set and the consensus-selected feature subset. Although the selected features achieved a marginally higher F1-score and Recall, the complete engineered feature set produced slightly better Accuracy, Precision, and ROC-AUC. As the improvements from feature selection were not significant, the complete engineered feature set was retained for subsequent model tuning and comparison." ], "metadata": { "id": "iRPfwxAqoYtL" } }, { "cell_type": "markdown", "source": [ "Model selection method" ], "metadata": { "id": "ZTS__QIGqCbe" } }, { "cell_type": "code", "source": [ "import os\n", "import pandas as pd\n", "import mlflow\n", "import mlflow.sklearn\n", "\n", "from sklearn.base import clone\n", "from sklearn.pipeline import Pipeline\n", "from sklearn.preprocessing import StandardScaler\n", "from sklearn.tree import DecisionTreeClassifier\n", "from sklearn.ensemble import (\n", " BaggingClassifier,\n", " RandomForestClassifier,\n", " ExtraTreesClassifier,\n", " AdaBoostClassifier,\n", " GradientBoostingClassifier,\n", " HistGradientBoostingClassifier\n", ")\n", "from sklearn.linear_model import LogisticRegression\n", "from sklearn.neighbors import KNeighborsClassifier\n", "from sklearn.svm import SVC\n", "from sklearn.metrics import (\n", " accuracy_score,\n", " precision_score,\n", " recall_score,\n", " f1_score,\n", " roc_auc_score,\n", " confusion_matrix,\n", " classification_report\n", ")\n", "\n", "mlflow.set_experiment(\"Engine_Condition_10Model_Comparison\")\n", "\n", "\n", "models = {\n", " \"DecisionTree\": DecisionTreeClassifier(random_state=random_state),\n", "\n", " \"Bagging\": BaggingClassifier(\n", " estimator=DecisionTreeClassifier(random_state=random_state),\n", " n_estimators=100,\n", " random_state=random_state,\n", " n_jobs=-1\n", " ),\n", "\n", " \"RandomForest\": RandomForestClassifier(\n", " n_estimators=300,\n", " random_state=random_state,\n", " n_jobs=-1\n", " ),\n", "\n", " \"ExtraTrees\": ExtraTreesClassifier(\n", " n_estimators=300,\n", " random_state=random_state,\n", " n_jobs=-1\n", " ),\n", "\n", " \"AdaBoost\": AdaBoostClassifier(\n", " estimator=DecisionTreeClassifier(max_depth=1, random_state=random_state),\n", " n_estimators=200,\n", " learning_rate=0.1,\n", " random_state=random_state\n", " ),\n", "\n", " \"GradientBoosting\": GradientBoostingClassifier(\n", " random_state=random_state\n", " ),\n", "\n", " \"HistGradientBoosting\": HistGradientBoostingClassifier(\n", " random_state=random_state\n", " ),\n", "\n", " \"LogisticRegression\": Pipeline([\n", " (\"scaler\", StandardScaler()),\n", " (\"model\", LogisticRegression(max_iter=2000, random_state=random_state))\n", " ]),\n", "\n", " \"KNN\": Pipeline([\n", " (\"scaler\", StandardScaler()),\n", " (\"model\", KNeighborsClassifier(n_neighbors=7))\n", " ]),\n", "\n", " \"SVC\": Pipeline([\n", " (\"scaler\", StandardScaler()),\n", " (\"model\", SVC(kernel=\"rbf\", probability=True, random_state=random_state))\n", " ])\n", "}\n", "\n", "\n", "def evaluate_and_log_model(model_name, estimator, X_tr, y_tr, X_va, y_va, feature_set_name):\n", " with mlflow.start_run(run_name=model_name, nested=True):\n", " model = clone(estimator)\n", " model.fit(X_tr, y_tr)\n", "\n", " val_preds = model.predict(X_va)\n", "\n", " if hasattr(model, \"predict_proba\"):\n", " val_scores = model.predict_proba(X_va)[:, 1]\n", " else:\n", " # For models like SVC without predict_proba by default\n", " # This can still cause issues if the model doesn't have decision_function either\n", " # or if decision_function doesn't align with probability scores for AUC.\n", " # For this context, assuming binary classification and compatible scoring.\n", " val_scores = model.decision_function(X_va)\n", "\n", " acc = accuracy_score(y_va, val_preds)\n", " prec = precision_score(y_va, val_preds, zero_division=0)\n", " rec = recall_score(y_va, val_preds, zero_division=0)\n", " f1 = f1_score(y_va, val_preds, zero_division=0)\n", " auc = roc_auc_score(y_va, val_scores)\n", "\n", " mlflow.log_param(\"model_type\", model_name)\n", " mlflow.log_param(\"feature_set\", feature_set_name)\n", " mlflow.log_param(\"random_state\", random_state)\n", " mlflow.log_param(\"num_features\", X_tr.shape[1])\n", "\n", " mlflow.log_metric(\"val_accuracy\", acc)\n", " mlflow.log_metric(\"val_precision\", prec)\n", " mlflow.log_metric(\"val_recall\", rec)\n", " mlflow.log_metric(\"val_f1\", f1)\n", " mlflow.log_metric(\"val_roc_auc\", auc)\n", "\n", " cm = confusion_matrix(y_va, val_preds)\n", " cm_df = pd.DataFrame(cm, index=[\"Actual_0\", \"Actual_1\"], columns=[\"Pred_0\", \"Pred_1\"])\n", " cm_path = f\"{model_name.lower()}_{feature_set_name.lower()}_confusion_matrix.csv\"\n", " cm_df.to_csv(cm_path, index=True)\n", " mlflow.log_artifact(cm_path)\n", "\n", " report = classification_report(y_va, val_preds, zero_division=0)\n", " report_path = f\"{model_name.lower()}_{feature_set_name.lower()}_classification_report.txt\"\n", " with open(report_path, \"w\") as f:\n", " f.write(report)\n", " mlflow.log_artifact(report_path)\n", "\n", " mlflow.sklearn.log_model(model, name=f\"{model_name.lower()}_{feature_set_name.lower()}_model\", skops_trusted_types=['sklearn.pipeline', 'sklearn.metrics._dist_metrics.EuclideanDistance64', 'sklearn.neighbors._kd_tree.KDTree'])\n", "\n", " return {\n", " \"Model\": model_name,\n", " \"Feature_Set\": feature_set_name,\n", " \"Accuracy\": acc,\n", " \"Precision\": prec,\n", " \"Recall\": rec,\n", " \"F1\": f1,\n", " \"ROC_AUC\": auc,\n", " \"Num_Features\": X_tr.shape[1]\n", " }\n", "\n", "\n", "def run_feature_set_experiment(feature_set_name, X_train_used, X_val_used, y_train, y_val):\n", " summary_rows = []\n", "\n", " with mlflow.start_run(run_name=f\"Compare_10_Models_{feature_set_name}\"):\n", " mlflow.log_param(\"feature_set_name\", feature_set_name)\n", " mlflow.log_param(\"n_models\", len(models))\n", " mlflow.log_param(\"train_rows\", X_train_used.shape[0])\n", " mlflow.log_param(\"train_features\", X_train_used.shape[1])\n", "\n", " for model_name, estimator in models.items():\n", " row = evaluate_and_log_model(\n", " model_name=model_name,\n", " estimator=estimator,\n", " X_tr=X_train_used,\n", " y_tr=y_train,\n", " X_va=X_val_used,\n", " y_va=y_val,\n", " feature_set_name=feature_set_name\n", " )\n", " summary_rows.append(row)\n", "\n", " summary_df = pd.DataFrame(summary_rows).sort_values(\"F1\", ascending=False)\n", " summary_path = f\"model_comparison_10_models_{feature_set_name.lower()}.csv\"\n", " summary_df.to_csv(summary_path, index=False)\n", " mlflow.log_artifact(summary_path)\n", "\n", " return summary_df\n", "\n", "\n", "\n", "summary_original = run_feature_set_experiment(\n", " feature_set_name=\"Original\",\n", " X_train_used=X_train_original.copy(),\n", " X_val_used=X_val_original.copy(),\n", " y_train=y_train,\n", " y_val=y_val\n", ")\n", "\n", "print(\"\\nOriginal Feature Set Results:\")\n", "print(summary_original)\n", "\n", "\n", "\n", "summary_engineered = run_feature_set_experiment(\n", " feature_set_name=\"Engineered\",\n", " X_train_used=X_train_engineered.copy(),\n", " X_val_used=X_val_engineered.copy(),\n", " y_train=y_train,\n", " y_val=y_val\n", ")\n", "\n", "print(\"\\nEngineered Feature Set Results:\")\n", "print(summary_engineered)\n", "\n", "\n", "\n", "summary_selected = run_feature_set_experiment(\n", " feature_set_name=\"Selected\",\n", " X_train_used=X_train_selected.copy(),\n", " X_val_used=X_val_selected.copy(),\n", " y_train=y_train,\n", " y_val=y_val\n", ")\n", "\n", "print(\"\\nSelected Feature Set Results:\")\n", "print(summary_selected)\n", "\n", "\n", "all_results = pd.concat([summary_original, summary_engineered, summary_selected], ignore_index=True)\n", "all_results_sorted = all_results.sort_values([\"F1\", \"ROC_AUC\"], ascending=False)\n", "\n", "print(\"\\nAll Results Sorted:\")\n", "print(all_results_sorted)\n", "\n", "best_model_row = all_results_sorted.iloc[0]\n", "print(\"\\nBest overall configuration:\")\n", "print(best_model_row)" ], "metadata": { "id": "oPJTEAjeP6FQ", "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "96c55774-233c-45ea-e946-def0ebf49e8a" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "2026/07/14 16:27:19 INFO mlflow.tracking.fluent: Experiment with name 'Engine_Condition_10Model_Comparison' does not exist. Creating a new experiment.\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ "\n", "Original Feature Set Results:\n", " Model Feature_Set Accuracy Precision Recall F1 \\\n", "9 SVC Original 0.666347 0.677914 0.897007 0.772221 \n", "7 LogisticRegression Original 0.668586 0.683694 0.882801 0.770593 \n", "4 AdaBoost Original 0.657070 0.667163 0.910198 0.769957 \n", "5 GradientBoosting Original 0.671785 0.699451 0.840690 0.763594 \n", "6 HistGradientBoosting Original 0.667626 0.696293 0.838661 0.760875 \n", "3 ExtraTrees Original 0.657390 0.688127 0.835109 0.754527 \n", "2 RandomForest Original 0.648752 0.685193 0.819381 0.746303 \n", "1 Bagging Original 0.650992 0.694346 0.797565 0.742385 \n", "8 KNN Original 0.641715 0.688025 0.789954 0.735475 \n", "0 DecisionTree Original 0.578055 0.663490 0.671233 0.667339 \n", "\n", " ROC_AUC Num_Features \n", "9 0.681698 6 \n", "7 0.688602 6 \n", "4 0.692116 6 \n", "5 0.700938 6 \n", "6 0.698496 6 \n", "3 0.684093 6 \n", "2 0.679968 6 \n", "1 0.674275 6 \n", "8 0.641543 6 \n", "0 0.545140 6 \n", "\n", "Engineered Feature Set Results:\n", " Model Feature_Set Accuracy Precision Recall F1 \\\n", "9 SVC Engineered 0.668266 0.677432 0.904617 0.774712 \n", "4 AdaBoost Engineered 0.658349 0.663173 0.930999 0.774588 \n", "7 LogisticRegression Engineered 0.669546 0.684211 0.883815 0.771308 \n", "5 GradientBoosting Engineered 0.675624 0.700797 0.847286 0.767111 \n", "6 HistGradientBoosting Engineered 0.668586 0.695689 0.843227 0.762385 \n", "3 ExtraTrees Engineered 0.662828 0.697374 0.821918 0.754541 \n", "2 RandomForest Engineered 0.657070 0.693167 0.818366 0.750582 \n", "1 Bagging Engineered 0.648113 0.690758 0.800101 0.741420 \n", "8 KNN Engineered 0.638196 0.685676 0.786910 0.732814 \n", "0 DecisionTree Engineered 0.585413 0.675143 0.660071 0.667522 \n", "\n", " ROC_AUC Num_Features \n", "9 0.678709 13 \n", "4 0.688810 13 \n", "7 0.687188 13 \n", "5 0.703869 13 \n", "6 0.698251 13 \n", "3 0.678205 13 \n", "2 0.680605 13 \n", "1 0.671937 13 \n", "8 0.639651 13 \n", "0 0.559040 13 \n", "\n", "Selected Feature Set Results:\n", " Model Feature_Set Accuracy Precision Recall F1 \\\n", "4 AdaBoost Selected 0.658349 0.663173 0.930999 0.774588 \n", "7 LogisticRegression Selected 0.669866 0.684479 0.883815 0.771479 \n", "9 SVC Selected 0.668266 0.682137 0.887367 0.771334 \n", "5 GradientBoosting Selected 0.668906 0.696639 0.841197 0.762124 \n", "6 HistGradientBoosting Selected 0.662508 0.693086 0.834094 0.757080 \n", "2 RandomForest Selected 0.658669 0.693659 0.821410 0.752149 \n", "3 ExtraTrees Selected 0.658029 0.693065 0.821410 0.751799 \n", "1 Bagging Selected 0.649712 0.690104 0.806697 0.743860 \n", "8 KNN Selected 0.642354 0.689471 0.787418 0.735197 \n", "0 DecisionTree Selected 0.581254 0.668020 0.667681 0.667851 \n", "\n", " ROC_AUC Num_Features \n", "4 0.688810 7 \n", "7 0.688258 7 \n", "9 0.680251 7 \n", "5 0.696543 7 \n", "6 0.694698 7 \n", "2 0.675237 7 \n", "3 0.671429 7 \n", "1 0.665644 7 \n", "8 0.646460 7 \n", "0 0.550724 7 \n", "\n", "All Results Sorted:\n", " Model Feature_Set Accuracy Precision Recall F1 \\\n", "10 SVC Engineered 0.668266 0.677432 0.904617 0.774712 \n", "11 AdaBoost Engineered 0.658349 0.663173 0.930999 0.774588 \n", "20 AdaBoost Selected 0.658349 0.663173 0.930999 0.774588 \n", "0 SVC Original 0.666347 0.677914 0.897007 0.772221 \n", "21 LogisticRegression Selected 0.669866 0.684479 0.883815 0.771479 \n", "22 SVC Selected 0.668266 0.682137 0.887367 0.771334 \n", "12 LogisticRegression Engineered 0.669546 0.684211 0.883815 0.771308 \n", "1 LogisticRegression Original 0.668586 0.683694 0.882801 0.770593 \n", "2 AdaBoost Original 0.657070 0.667163 0.910198 0.769957 \n", "13 GradientBoosting Engineered 0.675624 0.700797 0.847286 0.767111 \n", "3 GradientBoosting Original 0.671785 0.699451 0.840690 0.763594 \n", "14 HistGradientBoosting Engineered 0.668586 0.695689 0.843227 0.762385 \n", "23 GradientBoosting Selected 0.668906 0.696639 0.841197 0.762124 \n", "4 HistGradientBoosting Original 0.667626 0.696293 0.838661 0.760875 \n", "24 HistGradientBoosting Selected 0.662508 0.693086 0.834094 0.757080 \n", "15 ExtraTrees Engineered 0.662828 0.697374 0.821918 0.754541 \n", "5 ExtraTrees Original 0.657390 0.688127 0.835109 0.754527 \n", "25 RandomForest Selected 0.658669 0.693659 0.821410 0.752149 \n", "26 ExtraTrees Selected 0.658029 0.693065 0.821410 0.751799 \n", "16 RandomForest Engineered 0.657070 0.693167 0.818366 0.750582 \n", "6 RandomForest Original 0.648752 0.685193 0.819381 0.746303 \n", "27 Bagging Selected 0.649712 0.690104 0.806697 0.743860 \n", "7 Bagging Original 0.650992 0.694346 0.797565 0.742385 \n", "17 Bagging Engineered 0.648113 0.690758 0.800101 0.741420 \n", "8 KNN Original 0.641715 0.688025 0.789954 0.735475 \n", "28 KNN Selected 0.642354 0.689471 0.787418 0.735197 \n", "18 KNN Engineered 0.638196 0.685676 0.786910 0.732814 \n", "29 DecisionTree Selected 0.581254 0.668020 0.667681 0.667851 \n", "19 DecisionTree Engineered 0.585413 0.675143 0.660071 0.667522 \n", "9 DecisionTree Original 0.578055 0.663490 0.671233 0.667339 \n", "\n", " ROC_AUC Num_Features \n", "10 0.678709 13 \n", "11 0.688810 13 \n", "20 0.688810 7 \n", "0 0.681698 6 \n", "21 0.688258 7 \n", "22 0.680251 7 \n", "12 0.687188 13 \n", "1 0.688602 6 \n", "2 0.692116 6 \n", "13 0.703869 13 \n", "3 0.700938 6 \n", "14 0.698251 13 \n", "23 0.696543 7 \n", "4 0.698496 6 \n", "24 0.694698 7 \n", "15 0.678205 13 \n", "5 0.684093 6 \n", "25 0.675237 7 \n", "26 0.671429 7 \n", "16 0.680605 13 \n", "6 0.679968 6 \n", "27 0.665644 7 \n", "7 0.674275 6 \n", "17 0.671937 13 \n", "8 0.641543 6 \n", "28 0.646460 7 \n", "18 0.639651 13 \n", "29 0.550724 7 \n", "19 0.559040 13 \n", "9 0.545140 6 \n", "\n", "Best overall configuration:\n", "Model SVC\n", "Feature_Set Engineered\n", "Accuracy 0.668266\n", "Precision 0.677432\n", "Recall 0.904617\n", "F1 0.774712\n", "ROC_AUC 0.678709\n", "Num_Features 13\n", "Name: 10, dtype: object\n" ] } ] }, { "cell_type": "markdown", "source": [ "Model Selection Summary\n", "\n", "A total of ten baseline machine learning algorithms were evaluated using the engineered feature set on the validation dataset. The models were compared primarily using the F1-score, as it provides a balanced measure of precision and recall for the binary classification task. Accuracy, precision, recall, and ROC-AUC were also considered to assess overall model performance.\n", "\n", "Based on the validation results, the following three models were selected for hyperparameter tuning:\n", "\n", "Support Vector Classifier (SVC): Achieved the highest validation F1-score (0.7747) while maintaining high recall (0.9046), indicating strong capability in identifying positive engine condition cases.\n", "\n", "AdaBoost Classifier: Produced a nearly identical F1-score (0.7746) and the highest recall (0.9310) among all evaluated models, making it particularly effective for minimizing false negatives.\n", "\n", "Logistic Regression: Achieved a competitive F1-score (0.7713) with balanced precision (0.6842) and recall (0.8838). It was selected because of its strong performance and interpretability, providing a useful linear baseline for comparison against the more complex ensemble methods.\n", "\n", "These three models consistently demonstrated the best validation performance on the engineered feature set and But for hyperparameter Tuning using Optuna I will use SVC and Logistic Regression. The tuned versions were subsequently evaluated on the validation set, and the best-performing tuned model was carried forward for final evaluation on the unseen test dataset." ], "metadata": { "id": "eT8Ivi2_VXCz" } }, { "cell_type": "markdown", "source": [ "Model Selection for Hyperparameter Tuning\n", "\n", "A comparison of ten machine learning algorithms was conducted on the Original, Engineered, and Selected feature sets. The results showed that SVC and Logistic Regression achieved the highest F1-scores, followed closely by AdaBoost and Gradient Boosting.\n", "\n", "However, for the hyperparameter tuning stage, the focus was placed on tree-based ensemble models rather than SVC or Logistic Regression for the following reasons:\n", "\n", "The project guidelines specifically list Decision Tree, Bagging, Random Forest, AdaBoost, Gradient Boosting, and XGBoost as the recommended algorithms for model building and experimentation.\n", "Tree-based ensemble methods are capable of capturing non-linear relationships and feature interactions, making them well suited for predictive maintenance problems.\n", "These models generally benefit more from hyperparameter optimization than linear models, providing greater potential for performance improvement.\n", "Using multiple tree-based algorithms demonstrates a broader range of experimentation, which aligns with the project requirement to perform experimentation tracking using MLflow.\n", "\n", "Based on the comparative evaluation and the project requirements, the following models were selected for hyperparameter tuning:\n", "\n", "Random Forest – a bagging-based ensemble that reduces variance and improves model stability.\n", "Gradient Boosting – the highest-performing tree-based model during the initial comparison, achieving the best balance between Accuracy, F1-score, and ROC-AUC.\n", "Bagging Classifier (or XGBoost, if used) – included to compare a different ensemble learning strategy and evaluate whether additional tuning can improve predictive performance.\n", "\n", "These models were tuned using Optuna, with all hyperparameters, evaluation metrics, and trained models tracked using MLflow. The best-performing tuned model was then selected for final evaluation and registration." ], "metadata": { "id": "jWPTRxbaw2Xo" } }, { "cell_type": "code", "source": [ "!pip install optuna\n", "import optuna\n", "from sklearn.model_selection import StratifiedKFold, cross_val_score\n", "from sklearn.pipeline import Pipeline\n", "from sklearn.tree import DecisionTreeClassifier\n", "from sklearn.ensemble import GradientBoostingClassifier, HistGradientBoostingClassifier, AdaBoostClassifier\n", "from sklearn.metrics import (\n", " accuracy_score,\n", " precision_score,\n", " recall_score,\n", " f1_score,\n", " roc_auc_score,\n", " classification_report,\n", " confusion_matrix,\n", " ConfusionMatrixDisplay\n", ")\n", "import matplotlib.pyplot as plt\n", "import mlflow\n", "import mlflow.sklearn" ], "metadata": { "id": "4F12pFAls0J2", "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "9c624f28-8e97-41e1-8f22-5643331acf89" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Collecting optuna\n", " Downloading optuna-4.9.0-py3-none-any.whl.metadata (15 kB)\n", "Requirement already satisfied: alembic>=1.5.0 in /usr/local/lib/python3.12/dist-packages (from optuna) (1.18.5)\n", "Collecting colorlog (from optuna)\n", " Downloading colorlog-6.10.1-py3-none-any.whl.metadata (11 kB)\n", "Requirement already satisfied: numpy in /usr/local/lib/python3.12/dist-packages (from optuna) (2.0.2)\n", "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.12/dist-packages (from optuna) (26.2)\n", "Requirement already satisfied: sqlalchemy>=1.4.2 in /usr/local/lib/python3.12/dist-packages (from optuna) (2.0.51)\n", "Requirement already satisfied: tqdm in /usr/local/lib/python3.12/dist-packages (from optuna) (4.67.3)\n", "Requirement already satisfied: PyYAML in /usr/local/lib/python3.12/dist-packages (from optuna) (6.0.3)\n", "Requirement already satisfied: Mako in /usr/lib/python3/dist-packages (from alembic>=1.5.0->optuna) (1.1.3)\n", "Requirement already satisfied: typing-extensions>=4.12 in /usr/local/lib/python3.12/dist-packages (from alembic>=1.5.0->optuna) (4.15.0)\n", "Requirement already satisfied: greenlet>=1 in /usr/local/lib/python3.12/dist-packages (from sqlalchemy>=1.4.2->optuna) (3.5.2)\n", "Downloading optuna-4.9.0-py3-none-any.whl (425 kB)\n", "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m425.6/425.6 kB\u001b[0m \u001b[31m4.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n", "\u001b[?25hDownloading colorlog-6.10.1-py3-none-any.whl (11 kB)\n", "Installing collected packages: colorlog, optuna\n", "Successfully installed colorlog-6.10.1 optuna-4.9.0\n" ] } ] }, { "cell_type": "code", "source": [ "X_train_model = X_train_fe.copy()\n", "y_train_model = y_train_fe.copy()\n", "\n", "X_val_model = X_val_fe.copy()\n", "y_val_model = y_val_fe.copy()" ], "metadata": { "id": "2Xio1cvIrFW6" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "import optuna\n", "import mlflow\n", "import mlflow.sklearn\n", "import pandas as pd\n", "from sklearn.base import clone\n", "from sklearn.pipeline import Pipeline\n", "from sklearn.preprocessing import StandardScaler\n", "from sklearn.svm import SVC\n", "from sklearn.linear_model import LogisticRegression\n", "from sklearn.tree import DecisionTreeClassifier\n", "from sklearn.ensemble import AdaBoostClassifier\n", "from sklearn.model_selection import StratifiedKFold, cross_val_score\n", "from sklearn.metrics import (\n", " accuracy_score, precision_score, recall_score, f1_score,\n", " roc_auc_score, confusion_matrix, classification_report\n", ")\n", "\n", "mlflow.set_experiment(\"Engine_Condition_Tuned_Engineered_Set\")" ], "metadata": { "id": "KP6F6eistWY5", "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "dd13d54a-3e7c-4b29-8015-80dbb6e6c303" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "2026/07/14 16:39:26 INFO mlflow.tracking.fluent: Experiment with name 'Engine_Condition_Tuned_Engineered_Set' does not exist. Creating a new experiment.\n" ] }, { "output_type": "execute_result", "data": { "text/plain": [ "" ] }, "metadata": {}, "execution_count": 34 } ] }, { "cell_type": "markdown", "source": [ "#Tuning Random Forest using Optuna\n" ], "metadata": { "id": "ccwGjPLRWHcf" } }, { "cell_type": "code", "source": [ "from sklearn.ensemble import RandomForestClassifier\n", "from sklearn.model_selection import StratifiedKFold, cross_val_score\n", "import optuna\n", "\n", "def tune_randomforest_engineered(n_trials=10):\n", "\n", " def objective(trial):\n", " params = {\n", " \"n_estimators\": trial.suggest_int(\"n_estimators\", 100, 500, step=50),\n", " \"max_depth\": trial.suggest_int(\"max_depth\", 5, 30),\n", " \"min_samples_split\": trial.suggest_int(\"min_samples_split\", 2, 10),\n", " \"min_samples_leaf\": trial.suggest_int(\"min_samples_leaf\", 1, 5),\n", " \"max_features\": trial.suggest_categorical(\"max_features\", [\"sqrt\", \"log2\"]),\n", " \"bootstrap\": trial.suggest_categorical(\"bootstrap\", [True, False]),\n", " \"class_weight\": trial.suggest_categorical(\"class_weight\", [None, \"balanced\"]),\n", " \"random_state\": random_state,\n", " \"n_jobs\": -1\n", " }\n", "\n", " model = RandomForestClassifier(**params)\n", "\n", " cv = StratifiedKFold(\n", " n_splits=3,\n", " shuffle=True,\n", " random_state=random_state\n", " )\n", "\n", " scores = cross_val_score(\n", " model,\n", " X_train_engineered,\n", " y_train,\n", " cv=cv,\n", " scoring=\"f1_macro\",\n", " n_jobs=-1\n", " )\n", "\n", " return scores.mean()\n", "\n", " study = optuna.create_study(direction=\"maximize\")\n", " study.optimize(objective, n_trials=n_trials)\n", "\n", " best_params = study.best_params.copy()\n", "\n", " best_model = RandomForestClassifier(\n", " **best_params,\n", " random_state=random_state,\n", " n_jobs=-1\n", " )\n", "\n", " return study, best_model, best_params" ], "metadata": { "id": "Am9O5ZFctWVq" }, "execution_count": null, "outputs": [] }, { "cell_type": "markdown", "source": [ "#Tuning Gradient boosting using Optuna" ], "metadata": { "id": "ZLemlzqBdHVQ" } }, { "cell_type": "code", "source": [ "from sklearn.ensemble import GradientBoostingClassifier\n", "from sklearn.model_selection import StratifiedKFold, cross_val_score\n", "import optuna\n", "\n", "def tune_gradientboosting_engineered(n_trials=30):\n", "\n", " def objective(trial):\n", "\n", " params = {\n", " \"n_estimators\": trial.suggest_int(\"n_estimators\", 100, 400, step=50),\n", " \"learning_rate\": trial.suggest_float(\"learning_rate\", 0.01, 0.3, log=True),\n", " \"max_depth\": trial.suggest_int(\"max_depth\", 2, 6),\n", " \"min_samples_split\": trial.suggest_int(\"min_samples_split\", 2, 10),\n", " \"min_samples_leaf\": trial.suggest_int(\"min_samples_leaf\", 1, 5),\n", " \"subsample\": trial.suggest_float(\"subsample\", 0.6, 1.0),\n", " \"random_state\": random_state\n", " }\n", "\n", " model = GradientBoostingClassifier(**params)\n", "\n", " cv = StratifiedKFold(\n", " n_splits=5,\n", " shuffle=True,\n", " random_state=random_state\n", " )\n", "\n", " scores = cross_val_score(\n", " model,\n", " X_train_engineered,\n", " y_train,\n", " cv=cv,\n", " scoring=\"f1_macro\",\n", " n_jobs=-1\n", " )\n", "\n", " return scores.mean()\n", "\n", " study = optuna.create_study(direction=\"maximize\")\n", " study.optimize(objective, n_trials=n_trials)\n", "\n", " best_params = study.best_params.copy()\n", "\n", " best_model = GradientBoostingClassifier(\n", " **best_params,\n", " random_state=random_state\n", " )\n", "\n", " return study, best_model, best_params" ], "metadata": { "id": "ItNpUomDWc3y" }, "execution_count": null, "outputs": [] }, { "cell_type": "markdown", "source": [ "#Tuning XGBClassifier using Optuna" ], "metadata": { "id": "Afj0QwaWdONG" } }, { "cell_type": "code", "source": [ "from xgboost import XGBClassifier\n", "\n", "def tune_xgboost_engineered(n_trials=30):\n", "\n", " def objective(trial):\n", "\n", " params = {\n", " \"n_estimators\": trial.suggest_int(\"n_estimators\", 100, 400, step=50),\n", " \"max_depth\": trial.suggest_int(\"max_depth\", 3, 8),\n", " \"learning_rate\": trial.suggest_float(\"learning_rate\", 0.01, 0.3, log=True),\n", " \"subsample\": trial.suggest_float(\"subsample\", 0.6, 1.0),\n", " \"colsample_bytree\": trial.suggest_float(\"colsample_bytree\", 0.6, 1.0),\n", " \"gamma\": trial.suggest_float(\"gamma\", 0, 5),\n", " \"min_child_weight\": trial.suggest_int(\"min_child_weight\", 1, 10),\n", " \"eval_metric\": \"logloss\",\n", " \"random_state\": random_state,\n", " \"n_jobs\": -1\n", " }\n", "\n", " model = XGBClassifier(**params)\n", "\n", " cv = StratifiedKFold(\n", " n_splits=5,\n", " shuffle=True,\n", " random_state=random_state\n", " )\n", "\n", " scores = cross_val_score(\n", " model,\n", " X_train_engineered,\n", " y_train,\n", " cv=cv,\n", " scoring=\"f1_macro\",\n", " n_jobs=-1\n", " )\n", "\n", " return scores.mean()\n", "\n", " study = optuna.create_study(direction=\"maximize\")\n", " study.optimize(objective, n_trials=n_trials)\n", "\n", " best_params = study.best_params.copy()\n", "\n", " best_model = XGBClassifier(\n", " **best_params,\n", " eval_metric=\"logloss\",\n", " random_state=random_state,\n", " n_jobs=-1\n", " )\n", "\n", " return study, best_model, best_params" ], "metadata": { "id": "c0jzIL5pZi_W" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "rf_study, tuned_rf, rf_best_params = tune_randomforest_engineered(n_trials=30)" ], "metadata": { "id": "xpRBTSoLtWON", "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "071d6325-9895-4486-b883-b06f707ca8d1" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "[I 2026-07-14 16:39:55,148] A new study created in memory with name: no-name-7b63d9f3-5a38-4c91-92f2-67828ef84540\n", "[I 2026-07-14 16:40:49,437] Trial 0 finished with value: 0.6094920707848317 and parameters: {'n_estimators': 350, 'max_depth': 26, 'min_samples_split': 5, 'min_samples_leaf': 2, 'max_features': 'log2', 'bootstrap': True, 'class_weight': 'balanced'}. Best is trial 0 with value: 0.6094920707848317.\n", "[I 2026-07-14 16:41:37,538] Trial 1 finished with value: 0.5970740204531705 and parameters: {'n_estimators': 400, 'max_depth': 16, 'min_samples_split': 4, 'min_samples_leaf': 2, 'max_features': 'log2', 'bootstrap': True, 'class_weight': None}. Best is trial 0 with value: 0.6094920707848317.\n", "[I 2026-07-14 16:41:49,077] Trial 2 finished with value: 0.622503632404784 and parameters: {'n_estimators': 100, 'max_depth': 20, 'min_samples_split': 2, 'min_samples_leaf': 5, 'max_features': 'log2', 'bootstrap': True, 'class_weight': 'balanced'}. Best is trial 2 with value: 0.622503632404784.\n", "[I 2026-07-14 16:42:30,358] Trial 3 finished with value: 0.5977706844261818 and parameters: {'n_estimators': 300, 'max_depth': 11, 'min_samples_split': 8, 'min_samples_leaf': 1, 'max_features': 'log2', 'bootstrap': False, 'class_weight': None}. Best is trial 2 with value: 0.622503632404784.\n", "[I 2026-07-14 16:42:43,459] Trial 4 finished with value: 0.625615886833207 and parameters: {'n_estimators': 150, 'max_depth': 6, 'min_samples_split': 9, 'min_samples_leaf': 5, 'max_features': 'log2', 'bootstrap': False, 'class_weight': 'balanced'}. Best is trial 4 with value: 0.625615886833207.\n", "[I 2026-07-14 16:43:35,861] Trial 5 finished with value: 0.6220827745975556 and parameters: {'n_estimators': 450, 'max_depth': 14, 'min_samples_split': 5, 'min_samples_leaf': 1, 'max_features': 'log2', 'bootstrap': True, 'class_weight': 'balanced'}. Best is trial 4 with value: 0.625615886833207.\n", "[I 2026-07-14 16:43:50,420] Trial 6 finished with value: 0.6008102234509205 and parameters: {'n_estimators': 150, 'max_depth': 7, 'min_samples_split': 10, 'min_samples_leaf': 3, 'max_features': 'sqrt', 'bootstrap': False, 'class_weight': None}. Best is trial 4 with value: 0.625615886833207.\n", "[I 2026-07-14 16:44:11,463] Trial 7 finished with value: 0.6009244171398912 and parameters: {'n_estimators': 200, 'max_depth': 7, 'min_samples_split': 3, 'min_samples_leaf': 5, 'max_features': 'sqrt', 'bootstrap': False, 'class_weight': None}. Best is trial 4 with value: 0.625615886833207.\n", "[I 2026-07-14 16:45:30,005] Trial 8 finished with value: 0.5975823879749894 and parameters: {'n_estimators': 500, 'max_depth': 16, 'min_samples_split': 7, 'min_samples_leaf': 5, 'max_features': 'sqrt', 'bootstrap': False, 'class_weight': None}. Best is trial 4 with value: 0.625615886833207.\n", "[I 2026-07-14 16:46:12,607] Trial 9 finished with value: 0.6029063272214693 and parameters: {'n_estimators': 400, 'max_depth': 17, 'min_samples_split': 6, 'min_samples_leaf': 5, 'max_features': 'sqrt', 'bootstrap': True, 'class_weight': None}. Best is trial 4 with value: 0.625615886833207.\n", "[I 2026-07-14 16:47:01,221] Trial 10 finished with value: 0.6113923433568281 and parameters: {'n_estimators': 250, 'max_depth': 30, 'min_samples_split': 9, 'min_samples_leaf': 3, 'max_features': 'log2', 'bootstrap': False, 'class_weight': 'balanced'}. Best is trial 4 with value: 0.625615886833207.\n", "[I 2026-07-14 16:47:12,877] Trial 11 finished with value: 0.6209712662567877 and parameters: {'n_estimators': 100, 'max_depth': 22, 'min_samples_split': 2, 'min_samples_leaf': 4, 'max_features': 'log2', 'bootstrap': True, 'class_weight': 'balanced'}. Best is trial 4 with value: 0.625615886833207.\n", "[I 2026-07-14 16:47:22,889] Trial 12 finished with value: 0.6223772396716644 and parameters: {'n_estimators': 100, 'max_depth': 21, 'min_samples_split': 7, 'min_samples_leaf': 4, 'max_features': 'log2', 'bootstrap': True, 'class_weight': 'balanced'}. Best is trial 4 with value: 0.625615886833207.\n", "[I 2026-07-14 16:47:38,984] Trial 13 finished with value: 0.6234482048102216 and parameters: {'n_estimators': 200, 'max_depth': 5, 'min_samples_split': 2, 'min_samples_leaf': 4, 'max_features': 'log2', 'bootstrap': False, 'class_weight': 'balanced'}. Best is trial 4 with value: 0.625615886833207.\n", "[I 2026-07-14 16:47:55,054] Trial 14 finished with value: 0.6232138015577472 and parameters: {'n_estimators': 200, 'max_depth': 5, 'min_samples_split': 10, 'min_samples_leaf': 4, 'max_features': 'log2', 'bootstrap': False, 'class_weight': 'balanced'}. Best is trial 4 with value: 0.625615886833207.\n", "[I 2026-07-14 16:48:22,114] Trial 15 finished with value: 0.6270705529401083 and parameters: {'n_estimators': 200, 'max_depth': 10, 'min_samples_split': 4, 'min_samples_leaf': 4, 'max_features': 'log2', 'bootstrap': False, 'class_weight': 'balanced'}. Best is trial 15 with value: 0.6270705529401083.\n", "[I 2026-07-14 16:48:57,558] Trial 16 finished with value: 0.6264095967491391 and parameters: {'n_estimators': 250, 'max_depth': 11, 'min_samples_split': 8, 'min_samples_leaf': 3, 'max_features': 'log2', 'bootstrap': False, 'class_weight': 'balanced'}. Best is trial 15 with value: 0.6270705529401083.\n", "[I 2026-07-14 16:49:46,529] Trial 17 finished with value: 0.6277167710262388 and parameters: {'n_estimators': 300, 'max_depth': 11, 'min_samples_split': 4, 'min_samples_leaf': 3, 'max_features': 'log2', 'bootstrap': False, 'class_weight': 'balanced'}. Best is trial 17 with value: 0.6277167710262388.\n", "[I 2026-07-14 16:50:27,540] Trial 18 finished with value: 0.6263677477448159 and parameters: {'n_estimators': 300, 'max_depth': 10, 'min_samples_split': 4, 'min_samples_leaf': 2, 'max_features': 'sqrt', 'bootstrap': False, 'class_weight': 'balanced'}. Best is trial 17 with value: 0.6277167710262388.\n", "[I 2026-07-14 16:51:16,904] Trial 19 finished with value: 0.6251007871650298 and parameters: {'n_estimators': 300, 'max_depth': 13, 'min_samples_split': 4, 'min_samples_leaf': 3, 'max_features': 'log2', 'bootstrap': False, 'class_weight': 'balanced'}. Best is trial 17 with value: 0.6277167710262388.\n", "[I 2026-07-14 16:52:00,880] Trial 20 finished with value: 0.6250180402301767 and parameters: {'n_estimators': 350, 'max_depth': 9, 'min_samples_split': 3, 'min_samples_leaf': 4, 'max_features': 'log2', 'bootstrap': False, 'class_weight': 'balanced'}. Best is trial 17 with value: 0.6277167710262388.\n", "[I 2026-07-14 16:52:40,133] Trial 21 finished with value: 0.6271357279303132 and parameters: {'n_estimators': 250, 'max_depth': 12, 'min_samples_split': 6, 'min_samples_leaf': 3, 'max_features': 'log2', 'bootstrap': False, 'class_weight': 'balanced'}. Best is trial 17 with value: 0.6277167710262388.\n", "[I 2026-07-14 16:53:21,172] Trial 22 finished with value: 0.6249791716416276 and parameters: {'n_estimators': 250, 'max_depth': 13, 'min_samples_split': 5, 'min_samples_leaf': 3, 'max_features': 'log2', 'bootstrap': False, 'class_weight': 'balanced'}. Best is trial 17 with value: 0.6277167710262388.\n", "[I 2026-07-14 16:53:52,423] Trial 23 finished with value: 0.6260946529047468 and parameters: {'n_estimators': 250, 'max_depth': 9, 'min_samples_split': 6, 'min_samples_leaf': 2, 'max_features': 'log2', 'bootstrap': False, 'class_weight': 'balanced'}. Best is trial 17 with value: 0.6277167710262388.\n", "[I 2026-07-14 16:54:51,186] Trial 24 finished with value: 0.6230825128840657 and parameters: {'n_estimators': 350, 'max_depth': 14, 'min_samples_split': 6, 'min_samples_leaf': 3, 'max_features': 'log2', 'bootstrap': False, 'class_weight': 'balanced'}. Best is trial 17 with value: 0.6277167710262388.\n", "[I 2026-07-14 16:55:18,368] Trial 25 finished with value: 0.6152160558735424 and parameters: {'n_estimators': 150, 'max_depth': 18, 'min_samples_split': 3, 'min_samples_leaf': 4, 'max_features': 'log2', 'bootstrap': False, 'class_weight': 'balanced'}. Best is trial 17 with value: 0.6277167710262388.\n", "[I 2026-07-14 16:55:50,153] Trial 26 finished with value: 0.6261407881888619 and parameters: {'n_estimators': 200, 'max_depth': 12, 'min_samples_split': 4, 'min_samples_leaf': 3, 'max_features': 'sqrt', 'bootstrap': False, 'class_weight': 'balanced'}. Best is trial 17 with value: 0.6277167710262388.\n", "[I 2026-07-14 16:56:24,424] Trial 27 finished with value: 0.625736598334867 and parameters: {'n_estimators': 300, 'max_depth': 8, 'min_samples_split': 5, 'min_samples_leaf': 2, 'max_features': 'log2', 'bootstrap': False, 'class_weight': 'balanced'}. Best is trial 17 with value: 0.6277167710262388.\n", "[I 2026-07-14 16:57:06,927] Trial 28 finished with value: 0.6222539293453653 and parameters: {'n_estimators': 250, 'max_depth': 15, 'min_samples_split': 7, 'min_samples_leaf': 4, 'max_features': 'log2', 'bootstrap': False, 'class_weight': 'balanced'}. Best is trial 17 with value: 0.6277167710262388.\n", "[I 2026-07-14 16:58:14,315] Trial 29 finished with value: 0.6085284828007101 and parameters: {'n_estimators': 350, 'max_depth': 19, 'min_samples_split': 6, 'min_samples_leaf': 2, 'max_features': 'log2', 'bootstrap': False, 'class_weight': 'balanced'}. Best is trial 17 with value: 0.6277167710262388.\n" ] } ] }, { "cell_type": "code", "source": [ "gb_study, tuned_gb, gb_best_params = tune_gradientboosting_engineered(n_trials=30)" ], "metadata": { "id": "u2fCB_ypStOJ", "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "4bdd1927-5193-41e9-9a6c-cd5ac058822d" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "[I 2026-07-13 14:44:01,729] A new study created in memory with name: no-name-1084858e-3497-4bc6-9c3f-a9010edea5b5\n", "[I 2026-07-13 14:44:02,018] Trial 0 finished with value: 0.5737024402492075 and parameters: {'C': 10.10779700166698, 'penalty': 'l2'}. Best is trial 0 with value: 0.5737024402492075.\n", "[I 2026-07-13 14:44:02,298] Trial 1 finished with value: 0.5747401248181389 and parameters: {'C': 0.6233663674099118, 'penalty': 'l2'}. Best is trial 1 with value: 0.5747401248181389.\n", "[I 2026-07-13 14:44:02,466] Trial 2 finished with value: 0.5750602942861133 and parameters: {'C': 0.08893225687100743, 'penalty': 'l2'}. Best is trial 2 with value: 0.5750602942861133.\n", "[I 2026-07-13 14:44:02,632] Trial 3 finished with value: 0.5747401248181389 and parameters: {'C': 0.5856088287677123, 'penalty': 'l2'}. Best is trial 2 with value: 0.5750602942861133.\n", "[I 2026-07-13 14:44:02,799] Trial 4 finished with value: 0.5742196507927888 and parameters: {'C': 0.9691903746256733, 'penalty': 'l2'}. Best is trial 2 with value: 0.5750602942861133.\n", "[I 2026-07-13 14:44:03,066] Trial 5 finished with value: 0.5750690048045071 and parameters: {'C': 0.32434874672799585, 'penalty': 'l2'}. Best is trial 5 with value: 0.5750690048045071.\n", "[I 2026-07-13 14:44:03,342] Trial 6 finished with value: 0.5737024402492075 and parameters: {'C': 62.429141472500575, 'penalty': 'l2'}. Best is trial 5 with value: 0.5750690048045071.\n", "[I 2026-07-13 14:44:03,523] Trial 7 finished with value: 0.5742196507927888 and parameters: {'C': 0.9329348746775328, 'penalty': 'l2'}. Best is trial 5 with value: 0.5750690048045071.\n", "[I 2026-07-13 14:44:03,710] Trial 8 finished with value: 0.5737024402492075 and parameters: {'C': 15.397686556846633, 'penalty': 'l2'}. Best is trial 5 with value: 0.5750690048045071.\n", "[I 2026-07-13 14:44:03,952] Trial 9 finished with value: 0.5730432738295004 and parameters: {'C': 0.01021037221219984, 'penalty': 'l2'}. Best is trial 5 with value: 0.5750690048045071.\n", "[I 2026-07-13 14:44:04,284] Trial 10 finished with value: 0.5743096745811864 and parameters: {'C': 0.016985575603139534, 'penalty': 'l2'}. Best is trial 5 with value: 0.5750690048045071.\n", "[I 2026-07-13 14:44:04,705] Trial 11 finished with value: 0.574990578597038 and parameters: {'C': 0.08042013537769899, 'penalty': 'l2'}. Best is trial 5 with value: 0.5750690048045071.\n", "[I 2026-07-13 14:44:05,014] Trial 12 finished with value: 0.5748642848182668 and parameters: {'C': 0.1339331342734736, 'penalty': 'l2'}. Best is trial 5 with value: 0.5750690048045071.\n", "[I 2026-07-13 14:44:05,306] Trial 13 finished with value: 0.5748624745941644 and parameters: {'C': 0.10605087792142008, 'penalty': 'l2'}. Best is trial 5 with value: 0.5750690048045071.\n", "[I 2026-07-13 14:44:05,559] Trial 14 finished with value: 0.5752469521800512 and parameters: {'C': 0.053210301977073236, 'penalty': 'l2'}. Best is trial 14 with value: 0.5752469521800512.\n", "[I 2026-07-13 14:44:05,836] Trial 15 finished with value: 0.5738259308006751 and parameters: {'C': 3.6279125537818464, 'penalty': 'l2'}. Best is trial 14 with value: 0.5752469521800512.\n", "[I 2026-07-13 14:44:06,072] Trial 16 finished with value: 0.5748590890157003 and parameters: {'C': 0.02793058362873131, 'penalty': 'l2'}. Best is trial 14 with value: 0.5752469521800512.\n", "[I 2026-07-13 14:44:06,442] Trial 17 finished with value: 0.5750690048045071 and parameters: {'C': 0.31210498036555895, 'penalty': 'l2'}. Best is trial 14 with value: 0.5752469521800512.\n", "[I 2026-07-13 14:44:06,645] Trial 18 finished with value: 0.5753454784532114 and parameters: {'C': 0.033977049577714476, 'penalty': 'l2'}. Best is trial 18 with value: 0.5753454784532114.\n", "[I 2026-07-13 14:44:06,959] Trial 19 finished with value: 0.5751625848546337 and parameters: {'C': 0.04465053857650771, 'penalty': 'l2'}. Best is trial 18 with value: 0.5753454784532114.\n", "[I 2026-07-13 14:44:07,210] Trial 20 finished with value: 0.5748590890157003 and parameters: {'C': 0.03035168089009489, 'penalty': 'l2'}. Best is trial 18 with value: 0.5753454784532114.\n", "[I 2026-07-13 14:44:07,476] Trial 21 finished with value: 0.5752860235361317 and parameters: {'C': 0.04058726607435772, 'penalty': 'l2'}. Best is trial 18 with value: 0.5753454784532114.\n", "[I 2026-07-13 14:44:07,726] Trial 22 finished with value: 0.5751120479806551 and parameters: {'C': 0.049905259480929276, 'penalty': 'l2'}. Best is trial 18 with value: 0.5753454784532114.\n", "[I 2026-07-13 14:44:07,966] Trial 23 finished with value: 0.5731203511723943 and parameters: {'C': 0.010606272763547506, 'penalty': 'l2'}. Best is trial 18 with value: 0.5753454784532114.\n", "[I 2026-07-13 14:44:08,224] Trial 24 finished with value: 0.5748634989274197 and parameters: {'C': 0.19226906896350632, 'penalty': 'l2'}. Best is trial 18 with value: 0.5753454784532114.\n", "[I 2026-07-13 14:44:08,474] Trial 25 finished with value: 0.5748590890157003 and parameters: {'C': 0.028968699859561468, 'penalty': 'l2'}. Best is trial 18 with value: 0.5753454784532114.\n", "[I 2026-07-13 14:44:08,725] Trial 26 finished with value: 0.5752469521800512 and parameters: {'C': 0.05457090508245292, 'penalty': 'l2'}. Best is trial 18 with value: 0.5753454784532114.\n", "[I 2026-07-13 14:44:08,962] Trial 27 finished with value: 0.5744152412932005 and parameters: {'C': 0.02008143864841694, 'penalty': 'l2'}. Best is trial 18 with value: 0.5753454784532114.\n", "[I 2026-07-13 14:44:09,123] Trial 28 finished with value: 0.575069090679407 and parameters: {'C': 0.23622721394028717, 'penalty': 'l2'}. Best is trial 18 with value: 0.5753454784532114.\n", "[I 2026-07-13 14:44:09,391] Trial 29 finished with value: 0.573962364405755 and parameters: {'C': 2.543823913227651, 'penalty': 'l2'}. Best is trial 18 with value: 0.5753454784532114.\n" ] } ] }, { "cell_type": "code", "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "ad49ae0c", "outputId": "08bf022d-b874-41c6-f1b6-1e8be9394944" }, "source": [ "gb_study, tuned_gb, gb_best_params = tune_gradientboosting_engineered(n_trials=30)" ], "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "[I 2026-07-14 17:42:57,181] A new study created in memory with name: no-name-5fe424bf-2465-4592-96f4-be8490ebf42a\n", "[I 2026-07-14 17:44:21,592] Trial 0 finished with value: 0.5783815613855922 and parameters: {'n_estimators': 200, 'learning_rate': 0.010447467671673408, 'max_depth': 3, 'min_samples_split': 7, 'min_samples_leaf': 3, 'subsample': 0.932172523847554}. Best is trial 0 with value: 0.5783815613855922.\n", "[I 2026-07-14 17:46:48,316] Trial 1 finished with value: 0.582674375057322 and parameters: {'n_estimators': 300, 'learning_rate': 0.28287431487923137, 'max_depth': 5, 'min_samples_split': 3, 'min_samples_leaf': 1, 'subsample': 0.7497520489012084}. Best is trial 1 with value: 0.582674375057322.\n", "[I 2026-07-14 17:47:26,623] Trial 2 finished with value: 0.6075704011862281 and parameters: {'n_estimators': 150, 'learning_rate': 0.10291431803349954, 'max_depth': 3, 'min_samples_split': 8, 'min_samples_leaf': 3, 'subsample': 0.6190459390516921}. Best is trial 2 with value: 0.6075704011862281.\n", "[I 2026-07-14 17:51:29,500] Trial 3 finished with value: 0.6074839008942521 and parameters: {'n_estimators': 400, 'learning_rate': 0.01689651883285644, 'max_depth': 5, 'min_samples_split': 10, 'min_samples_leaf': 4, 'subsample': 0.9437412904076651}. Best is trial 2 with value: 0.6075704011862281.\n", "[I 2026-07-14 17:52:57,717] Trial 4 finished with value: 0.5919832902949143 and parameters: {'n_estimators': 350, 'learning_rate': 0.2820476066767304, 'max_depth': 3, 'min_samples_split': 7, 'min_samples_leaf': 4, 'subsample': 0.6260778042468285}. Best is trial 2 with value: 0.6075704011862281.\n", "[I 2026-07-14 17:53:47,224] Trial 5 finished with value: 0.5867955147659947 and parameters: {'n_estimators': 200, 'learning_rate': 0.010985375982570279, 'max_depth': 3, 'min_samples_split': 7, 'min_samples_leaf': 4, 'subsample': 0.6385688172140115}. Best is trial 2 with value: 0.6075704011862281.\n", "[I 2026-07-14 17:55:50,651] Trial 6 finished with value: 0.593130570540992 and parameters: {'n_estimators': 200, 'learning_rate': 0.2612451166818987, 'max_depth': 6, 'min_samples_split': 8, 'min_samples_leaf': 5, 'subsample': 0.8010475729103235}. Best is trial 2 with value: 0.6075704011862281.\n", "[I 2026-07-14 17:56:49,002] Trial 7 finished with value: 0.6111433677570328 and parameters: {'n_estimators': 250, 'learning_rate': 0.05724421026677626, 'max_depth': 2, 'min_samples_split': 8, 'min_samples_leaf': 1, 'subsample': 0.8673848628963416}. Best is trial 7 with value: 0.6111433677570328.\n", "[I 2026-07-14 18:00:13,593] Trial 8 finished with value: 0.6121602957446437 and parameters: {'n_estimators': 300, 'learning_rate': 0.030241088840280383, 'max_depth': 6, 'min_samples_split': 9, 'min_samples_leaf': 4, 'subsample': 0.8837118482662136}. Best is trial 8 with value: 0.6121602957446437.\n", "[I 2026-07-14 18:01:31,013] Trial 9 finished with value: 0.6038824458353496 and parameters: {'n_estimators': 400, 'learning_rate': 0.014622213544348006, 'max_depth': 2, 'min_samples_split': 2, 'min_samples_leaf': 5, 'subsample': 0.7125180418312165}. Best is trial 8 with value: 0.6121602957446437.\n", "[I 2026-07-14 18:02:46,735] Trial 10 finished with value: 0.606243687953893 and parameters: {'n_estimators': 100, 'learning_rate': 0.03611495632468221, 'max_depth': 6, 'min_samples_split': 4, 'min_samples_leaf': 2, 'subsample': 0.9987589953186293}. Best is trial 8 with value: 0.6121602957446437.\n", "[I 2026-07-14 18:04:59,863] Trial 11 finished with value: 0.6090915281779504 and parameters: {'n_estimators': 300, 'learning_rate': 0.056475318251086294, 'max_depth': 4, 'min_samples_split': 10, 'min_samples_leaf': 1, 'subsample': 0.8549695573043395}. Best is trial 8 with value: 0.6121602957446437.\n", "[I 2026-07-14 18:06:09,119] Trial 12 finished with value: 0.6069625157109585 and parameters: {'n_estimators': 300, 'learning_rate': 0.03813901717597066, 'max_depth': 2, 'min_samples_split': 5, 'min_samples_leaf': 2, 'subsample': 0.8569131338302842}. Best is trial 8 with value: 0.6121602957446437.\n", "[I 2026-07-14 18:08:28,869] Trial 13 finished with value: 0.6087774431383293 and parameters: {'n_estimators': 250, 'learning_rate': 0.05674071032292574, 'max_depth': 5, 'min_samples_split': 9, 'min_samples_leaf': 2, 'subsample': 0.8687590177972098}. Best is trial 8 with value: 0.6121602957446437.\n", "[I 2026-07-14 18:10:28,010] Trial 14 finished with value: 0.6110573991164647 and parameters: {'n_estimators': 250, 'learning_rate': 0.027534454913227834, 'max_depth': 4, 'min_samples_split': 6, 'min_samples_leaf': 3, 'subsample': 0.917248440164324}. Best is trial 8 with value: 0.6121602957446437.\n", "[I 2026-07-14 18:12:55,641] Trial 15 finished with value: 0.6004077068322555 and parameters: {'n_estimators': 350, 'learning_rate': 0.11076995607894914, 'max_depth': 4, 'min_samples_split': 9, 'min_samples_leaf': 1, 'subsample': 0.8034645393839173}. Best is trial 8 with value: 0.6121602957446437.\n", "[I 2026-07-14 18:15:29,322] Trial 16 finished with value: 0.6017191043679834 and parameters: {'n_estimators': 250, 'learning_rate': 0.0838851738109455, 'max_depth': 6, 'min_samples_split': 9, 'min_samples_leaf': 5, 'subsample': 0.7997625371137962}. Best is trial 8 with value: 0.6121602957446437.\n", "[I 2026-07-14 18:16:53,364] Trial 17 finished with value: 0.6065517783436062 and parameters: {'n_estimators': 350, 'learning_rate': 0.02353782833481939, 'max_depth': 2, 'min_samples_split': 8, 'min_samples_leaf': 2, 'subsample': 0.8939587134496334}. Best is trial 8 with value: 0.6121602957446437.\n", "[I 2026-07-14 18:18:26,899] Trial 18 finished with value: 0.5979809139092881 and parameters: {'n_estimators': 150, 'learning_rate': 0.1656560582973951, 'max_depth': 5, 'min_samples_split': 6, 'min_samples_leaf': 3, 'subsample': 0.9665512305276174}. Best is trial 8 with value: 0.6121602957446437.\n", "[I 2026-07-14 18:20:23,667] Trial 19 finished with value: 0.609980316744567 and parameters: {'n_estimators': 300, 'learning_rate': 0.05619183215877407, 'max_depth': 4, 'min_samples_split': 10, 'min_samples_leaf': 4, 'subsample': 0.7389695978153105}. Best is trial 8 with value: 0.6121602957446437.\n", "[I 2026-07-14 18:21:19,756] Trial 20 finished with value: 0.6081511973873875 and parameters: {'n_estimators': 250, 'learning_rate': 0.04206654698086928, 'max_depth': 2, 'min_samples_split': 6, 'min_samples_leaf': 1, 'subsample': 0.8290035558407417}. Best is trial 8 with value: 0.6121602957446437.\n", "[I 2026-07-14 18:23:18,192] Trial 21 finished with value: 0.6089460399021611 and parameters: {'n_estimators': 250, 'learning_rate': 0.025537507516660795, 'max_depth': 4, 'min_samples_split': 5, 'min_samples_leaf': 3, 'subsample': 0.9211511577836845}. Best is trial 8 with value: 0.6121602957446437.\n", "[I 2026-07-14 18:26:10,421] Trial 22 finished with value: 0.6105074108195256 and parameters: {'n_estimators': 250, 'learning_rate': 0.02546554051752777, 'max_depth': 6, 'min_samples_split': 6, 'min_samples_leaf': 4, 'subsample': 0.8958795542495794}. Best is trial 8 with value: 0.6121602957446437.\n", "[I 2026-07-14 18:27:20,577] Trial 23 finished with value: 0.6087838257067008 and parameters: {'n_estimators': 200, 'learning_rate': 0.03027592819760456, 'max_depth': 3, 'min_samples_split': 8, 'min_samples_leaf': 3, 'subsample': 0.8968670469497391}. Best is trial 8 with value: 0.6121602957446437.\n", "[I 2026-07-14 18:30:28,910] Trial 24 finished with value: 0.6115429663987222 and parameters: {'n_estimators': 300, 'learning_rate': 0.019345957697447336, 'max_depth': 5, 'min_samples_split': 9, 'min_samples_leaf': 2, 'subsample': 0.9813503394829454}. Best is trial 8 with value: 0.6121602957446437.\n", "[I 2026-07-14 18:34:49,971] Trial 25 finished with value: 0.6109040824032995 and parameters: {'n_estimators': 350, 'learning_rate': 0.018380130511983533, 'max_depth': 6, 'min_samples_split': 9, 'min_samples_leaf': 2, 'subsample': 0.971555348269437}. Best is trial 8 with value: 0.6121602957446437.\n", "[I 2026-07-14 18:38:03,730] Trial 26 finished with value: 0.607024154969596 and parameters: {'n_estimators': 300, 'learning_rate': 0.07875139899033264, 'max_depth': 5, 'min_samples_split': 9, 'min_samples_leaf': 1, 'subsample': 0.9945041908203317}. Best is trial 8 with value: 0.6121602957446437.\n", "[I 2026-07-14 18:41:43,527] Trial 27 finished with value: 0.6111752049804604 and parameters: {'n_estimators': 300, 'learning_rate': 0.020445520830795934, 'max_depth': 6, 'min_samples_split': 10, 'min_samples_leaf': 1, 'subsample': 0.9570009491523122}. Best is trial 8 with value: 0.6121602957446437.\n", "[I 2026-07-14 18:46:00,137] Trial 28 finished with value: 0.6091115938415868 and parameters: {'n_estimators': 350, 'learning_rate': 0.019700239411107504, 'max_depth': 6, 'min_samples_split': 10, 'min_samples_leaf': 2, 'subsample': 0.9600605799266858}. Best is trial 8 with value: 0.6121602957446437.\n", "[I 2026-07-14 18:48:58,794] Trial 29 finished with value: 0.6096532273805365 and parameters: {'n_estimators': 300, 'learning_rate': 0.012879819910282106, 'max_depth': 5, 'min_samples_split': 10, 'min_samples_leaf': 2, 'subsample': 0.9368083371186394}. Best is trial 8 with value: 0.6121602957446437.\n" ] } ] }, { "cell_type": "code", "source": [ "xgb_study, tuned_xgb, xgb_best_params = tune_xgboost_engineered(n_trials=30)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "UIQQlkdEZ8kB", "outputId": "41b5f9e1-86de-4492-ab22-c25cac4822b3" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "[I 2026-07-14 17:32:58,502] A new study created in memory with name: no-name-45acb7f2-434a-45de-80de-d8516477e8b2\n", "[I 2026-07-14 17:33:04,351] Trial 0 finished with value: 0.5968520618144252 and parameters: {'n_estimators': 400, 'max_depth': 3, 'learning_rate': 0.24408083148116588, 'subsample': 0.7636874377551394, 'colsample_bytree': 0.8845493813920988, 'gamma': 1.0529492192806311, 'min_child_weight': 8}. Best is trial 0 with value: 0.5968520618144252.\n", "[I 2026-07-14 17:33:05,475] Trial 1 finished with value: 0.6093838011635293 and parameters: {'n_estimators': 150, 'max_depth': 3, 'learning_rate': 0.09965162565477012, 'subsample': 0.823597635017705, 'colsample_bytree': 0.8998498606789651, 'gamma': 3.47481234134495, 'min_child_weight': 1}. Best is trial 1 with value: 0.6093838011635293.\n", "[I 2026-07-14 17:33:07,483] Trial 2 finished with value: 0.6128761819035502 and parameters: {'n_estimators': 200, 'max_depth': 5, 'learning_rate': 0.050134066679396426, 'subsample': 0.6133778365686819, 'colsample_bytree': 0.9750056358595923, 'gamma': 4.603085106026683, 'min_child_weight': 4}. Best is trial 2 with value: 0.6128761819035502.\n", "[I 2026-07-14 17:33:08,719] Trial 3 finished with value: 0.609503226283967 and parameters: {'n_estimators': 150, 'max_depth': 7, 'learning_rate': 0.16014265712266193, 'subsample': 0.8715505770116827, 'colsample_bytree': 0.8983474289674569, 'gamma': 4.149351053882919, 'min_child_weight': 3}. Best is trial 2 with value: 0.6128761819035502.\n", "[I 2026-07-14 17:33:09,799] Trial 4 finished with value: 0.6100716382508514 and parameters: {'n_estimators': 100, 'max_depth': 3, 'learning_rate': 0.1872987842589412, 'subsample': 0.7812404767088297, 'colsample_bytree': 0.9000230676782595, 'gamma': 2.932482432608268, 'min_child_weight': 3}. Best is trial 2 with value: 0.6128761819035502.\n", "[I 2026-07-14 17:33:13,618] Trial 5 finished with value: 0.6113899472820918 and parameters: {'n_estimators': 350, 'max_depth': 3, 'learning_rate': 0.06364550592566165, 'subsample': 0.7138142104109964, 'colsample_bytree': 0.7472714045453278, 'gamma': 2.1317030368437444, 'min_child_weight': 3}. Best is trial 2 with value: 0.6128761819035502.\n", "[I 2026-07-14 17:33:22,284] Trial 6 finished with value: 0.6067231135325585 and parameters: {'n_estimators': 400, 'max_depth': 8, 'learning_rate': 0.016707344622656904, 'subsample': 0.6423800173776743, 'colsample_bytree': 0.6889531494029947, 'gamma': 0.06986947689565759, 'min_child_weight': 5}. Best is trial 2 with value: 0.6128761819035502.\n", "[I 2026-07-14 17:33:27,666] Trial 7 finished with value: 0.6085005073975445 and parameters: {'n_estimators': 200, 'max_depth': 7, 'learning_rate': 0.018573641809767255, 'subsample': 0.6286568403508443, 'colsample_bytree': 0.7014823008648599, 'gamma': 2.9875811713337463, 'min_child_weight': 7}. Best is trial 2 with value: 0.6128761819035502.\n", "[I 2026-07-14 17:33:28,657] Trial 8 finished with value: 0.6100329289222193 and parameters: {'n_estimators': 100, 'max_depth': 3, 'learning_rate': 0.05404463537578275, 'subsample': 0.8605331469880968, 'colsample_bytree': 0.9893808219854058, 'gamma': 4.284082316894993, 'min_child_weight': 6}. Best is trial 2 with value: 0.6128761819035502.\n", "[I 2026-07-14 17:33:32,811] Trial 9 finished with value: 0.599467158377544 and parameters: {'n_estimators': 200, 'max_depth': 8, 'learning_rate': 0.06868185763330306, 'subsample': 0.7055462148732446, 'colsample_bytree': 0.7345124620325563, 'gamma': 1.0576144324002157, 'min_child_weight': 6}. Best is trial 2 with value: 0.6128761819035502.\n", "[I 2026-07-14 17:33:34,913] Trial 10 finished with value: 0.6063900612964797 and parameters: {'n_estimators': 300, 'max_depth': 5, 'learning_rate': 0.030962487325603735, 'subsample': 0.9950934800972244, 'colsample_bytree': 0.8043971806690535, 'gamma': 4.774534706220259, 'min_child_weight': 10}. Best is trial 2 with value: 0.6128761819035502.\n", "[I 2026-07-14 17:33:38,560] Trial 11 finished with value: 0.6071038537708644 and parameters: {'n_estimators': 300, 'max_depth': 5, 'learning_rate': 0.03870434975641568, 'subsample': 0.6030513533844762, 'colsample_bytree': 0.6106163112827601, 'gamma': 1.9550305052791326, 'min_child_weight': 3}. Best is trial 2 with value: 0.6128761819035502.\n", "[I 2026-07-14 17:33:43,457] Trial 12 finished with value: 0.6003043356270659 and parameters: {'n_estimators': 300, 'max_depth': 5, 'learning_rate': 0.10153082049207685, 'subsample': 0.7005903428638248, 'colsample_bytree': 0.9963203856468964, 'gamma': 2.029172417915042, 'min_child_weight': 1}. Best is trial 2 with value: 0.6128761819035502.\n", "[I 2026-07-14 17:33:46,697] Trial 13 finished with value: 0.6112013587836845 and parameters: {'n_estimators': 350, 'max_depth': 4, 'learning_rate': 0.03370993449827046, 'subsample': 0.6902101935909747, 'colsample_bytree': 0.7984201735784328, 'gamma': 1.9291668358926635, 'min_child_weight': 4}. Best is trial 2 with value: 0.6128761819035502.\n", "[I 2026-07-14 17:33:49,412] Trial 14 finished with value: 0.6024374271998713 and parameters: {'n_estimators': 250, 'max_depth': 4, 'learning_rate': 0.01138050570701659, 'subsample': 0.6722302423615438, 'colsample_bytree': 0.7779878574283748, 'gamma': 3.361438553189811, 'min_child_weight': 2}. Best is trial 2 with value: 0.6128761819035502.\n", "[I 2026-07-14 17:33:51,089] Trial 15 finished with value: 0.6087157307886221 and parameters: {'n_estimators': 250, 'max_depth': 6, 'learning_rate': 0.06328981468459792, 'subsample': 0.7450173047767996, 'colsample_bytree': 0.6040817624577389, 'gamma': 4.830568793434091, 'min_child_weight': 4}. Best is trial 2 with value: 0.6128761819035502.\n", "[I 2026-07-14 17:33:56,105] Trial 16 finished with value: 0.5980762046310838 and parameters: {'n_estimators': 350, 'max_depth': 4, 'learning_rate': 0.10173719705447724, 'subsample': 0.6068748847567363, 'colsample_bytree': 0.8423668642608662, 'gamma': 0.161716360691599, 'min_child_weight': 5}. Best is trial 2 with value: 0.6128761819035502.\n", "[I 2026-07-14 17:33:58,901] Trial 17 finished with value: 0.6104899121210593 and parameters: {'n_estimators': 250, 'max_depth': 6, 'learning_rate': 0.044385493547187946, 'subsample': 0.937885380257065, 'colsample_bytree': 0.9424283592042094, 'gamma': 2.6738116257094635, 'min_child_weight': 2}. Best is trial 2 with value: 0.6128761819035502.\n", "[I 2026-07-14 17:34:02,029] Trial 18 finished with value: 0.6128054485241374 and parameters: {'n_estimators': 350, 'max_depth': 6, 'learning_rate': 0.023758715802098266, 'subsample': 0.6648603830231472, 'colsample_bytree': 0.658350807940148, 'gamma': 3.9482059602581185, 'min_child_weight': 9}. Best is trial 2 with value: 0.6128761819035502.\n", "[I 2026-07-14 17:34:04,351] Trial 19 finished with value: 0.6120108840912633 and parameters: {'n_estimators': 200, 'max_depth': 6, 'learning_rate': 0.023184878594478767, 'subsample': 0.654717799447389, 'colsample_bytree': 0.6525643643205878, 'gamma': 4.207019632526982, 'min_child_weight': 10}. Best is trial 2 with value: 0.6128761819035502.\n", "[I 2026-07-14 17:34:09,488] Trial 20 finished with value: 0.5855618542056483 and parameters: {'n_estimators': 150, 'max_depth': 7, 'learning_rate': 0.010836204745746559, 'subsample': 0.7441207458865596, 'colsample_bytree': 0.8549602057815582, 'gamma': 3.8373525798645, 'min_child_weight': 9}. Best is trial 2 with value: 0.6128761819035502.\n", "[I 2026-07-14 17:34:11,747] Trial 21 finished with value: 0.6106066738283917 and parameters: {'n_estimators': 200, 'max_depth': 6, 'learning_rate': 0.024360518257127612, 'subsample': 0.647838006281719, 'colsample_bytree': 0.6397837424679664, 'gamma': 4.276674918270382, 'min_child_weight': 10}. Best is trial 2 with value: 0.6128761819035502.\n", "[I 2026-07-14 17:34:13,944] Trial 22 finished with value: 0.6102736770931706 and parameters: {'n_estimators': 200, 'max_depth': 6, 'learning_rate': 0.022043526186090914, 'subsample': 0.6641749855091178, 'colsample_bytree': 0.6622197753181389, 'gamma': 4.925792826268721, 'min_child_weight': 9}. Best is trial 2 with value: 0.6128761819035502.\n", "[I 2026-07-14 17:34:16,320] Trial 23 finished with value: 0.6116795324271388 and parameters: {'n_estimators': 250, 'max_depth': 5, 'learning_rate': 0.02700356464358523, 'subsample': 0.6343780028461038, 'colsample_bytree': 0.6581366475609003, 'gamma': 3.8742352665250985, 'min_child_weight': 8}. Best is trial 2 with value: 0.6128761819035502.\n", "[I 2026-07-14 17:34:18,579] Trial 24 finished with value: 0.6014887397899685 and parameters: {'n_estimators': 150, 'max_depth': 6, 'learning_rate': 0.01587488037081849, 'subsample': 0.6004225220443682, 'colsample_bytree': 0.7156649197324558, 'gamma': 4.550353216067162, 'min_child_weight': 9}. Best is trial 2 with value: 0.6128761819035502.\n", "[I 2026-07-14 17:34:23,372] Trial 25 finished with value: 0.6111818214526066 and parameters: {'n_estimators': 300, 'max_depth': 7, 'learning_rate': 0.044329145368318265, 'subsample': 0.6697804458373952, 'colsample_bytree': 0.952645617575064, 'gamma': 3.59399482855995, 'min_child_weight': 10}. Best is trial 2 with value: 0.6128761819035502.\n", "[I 2026-07-14 17:34:25,749] Trial 26 finished with value: 0.6040612297153396 and parameters: {'n_estimators': 200, 'max_depth': 5, 'learning_rate': 0.014428920719417834, 'subsample': 0.7264351824208733, 'colsample_bytree': 0.6373247907140267, 'gamma': 4.374842540964064, 'min_child_weight': 8}. Best is trial 2 with value: 0.6128761819035502.\n", "[I 2026-07-14 17:34:27,445] Trial 27 finished with value: 0.5953499309932397 and parameters: {'n_estimators': 100, 'max_depth': 6, 'learning_rate': 0.021225497268635873, 'subsample': 0.6805295741508615, 'colsample_bytree': 0.6756164324349947, 'gamma': 3.918684992415566, 'min_child_weight': 7}. Best is trial 2 with value: 0.6128761819035502.\n", "[I 2026-07-14 17:34:30,323] Trial 28 finished with value: 0.6102329348761969 and parameters: {'n_estimators': 400, 'max_depth': 4, 'learning_rate': 0.029439781942548655, 'subsample': 0.7911221736466051, 'colsample_bytree': 0.7706550967677603, 'gamma': 3.212999222925898, 'min_child_weight': 9}. Best is trial 2 with value: 0.6128761819035502.\n", "[I 2026-07-14 17:34:33,688] Trial 29 finished with value: 0.5867893073423802 and parameters: {'n_estimators': 400, 'max_depth': 5, 'learning_rate': 0.265297392526922, 'subsample': 0.6305713806863874, 'colsample_bytree': 0.8384464867428235, 'gamma': 2.5362872574737314, 'min_child_weight': 8}. Best is trial 2 with value: 0.6128761819035502.\n" ] } ] }, { "cell_type": "code", "source": [ "import os\n", "import json\n", "import tempfile\n", "import pandas as pd\n", "import mlflow\n", "import mlflow.sklearn\n", "from sklearn.metrics import (\n", " accuracy_score,\n", " precision_score,\n", " recall_score,\n", " f1_score,\n", " roc_auc_score,\n", " confusion_matrix,\n", " classification_report\n", ")\n", "\n", "def log_tuned_model(\n", " run_name,\n", " model,\n", " X_train_used,\n", " y_train,\n", " X_val_used,\n", " y_val,\n", " best_params,\n", " feature_set_name,\n", " feature_names\n", "):\n", " with mlflow.start_run(run_name=run_name):\n", "\n", " # Train final tuned model\n", " model.fit(X_train_used, y_train)\n", "\n", " # Predict on validation set\n", " val_preds = model.predict(X_val_used)\n", "\n", " # Probability scores for ROC-AUC\n", " val_probs = None\n", " if hasattr(model, \"predict_proba\"):\n", " proba = model.predict_proba(X_val_used)\n", " if proba.shape[1] == 2:\n", " val_probs = proba[:, 1]\n", " else:\n", " val_probs = proba.max(axis=1)\n", "\n", " # Metrics\n", " acc = accuracy_score(y_val, val_preds)\n", " prec = precision_score(y_val, val_preds, zero_division=0)\n", " rec = recall_score(y_val, val_preds, zero_division=0)\n", " f1 = f1_score(y_val, val_preds, zero_division=0)\n", "\n", " auc = None\n", " if val_probs is not None:\n", " auc = roc_auc_score(y_val, val_probs)\n", "\n", " # Log params\n", " mlflow.log_param(\"feature_set\", feature_set_name)\n", " mlflow.log_param(\"num_features\", len(feature_names))\n", " mlflow.log_params(best_params)\n", "\n", " # Log metrics\n", " mlflow.log_metric(\"val_accuracy\", acc)\n", " mlflow.log_metric(\"val_precision\", prec)\n", " mlflow.log_metric(\"val_recall\", rec)\n", " mlflow.log_metric(\"val_f1\", f1)\n", "\n", " if auc is not None:\n", " mlflow.log_metric(\"val_roc_auc\", auc)\n", "\n", " # Save feature names\n", " with tempfile.NamedTemporaryFile(mode=\"w\", suffix=\"_features.txt\", delete=False) as f:\n", " feature_file = f.name\n", " for col in feature_names:\n", " f.write(f\"{col}\\n\")\n", " mlflow.log_artifact(feature_file)\n", " os.remove(feature_file)\n", "\n", " # Save best params\n", " with tempfile.NamedTemporaryFile(mode=\"w\", suffix=\"_best_params.json\", delete=False) as f:\n", " params_file = f.name\n", " json.dump(best_params, f, indent=4)\n", " mlflow.log_artifact(params_file)\n", " os.remove(params_file)\n", "\n", " # Confusion matrix\n", " cm = confusion_matrix(y_val, val_preds)\n", " cm_df = pd.DataFrame(\n", " cm,\n", " index=[\"Actual_0\", \"Actual_1\"],\n", " columns=[\"Pred_0\", \"Pred_1\"]\n", " )\n", " with tempfile.NamedTemporaryFile(mode=\"w\", suffix=\"_confusion_matrix.csv\", delete=False) as f:\n", " cm_file = f.name\n", " cm_df.to_csv(cm_file, index=True)\n", " mlflow.log_artifact(cm_file)\n", " os.remove(cm_file)\n", "\n", " # Classification report\n", " report = classification_report(y_val, val_preds, zero_division=0)\n", " with tempfile.NamedTemporaryFile(mode=\"w\", suffix=\"_classification_report.txt\", delete=False) as f:\n", " report_file = f.name\n", " f.write(report)\n", " mlflow.log_artifact(report_file)\n", " os.remove(report_file)\n", "\n", " # Log model\n", " mlflow.sklearn.log_model(model, artifact_path=f\"{run_name}_model\")\n", "\n", " return {\n", " \"Run_Name\": run_name,\n", " \"Feature_Set\": feature_set_name,\n", " \"Accuracy\": acc,\n", " \"Precision\": prec,\n", " \"Recall\": rec,\n", " \"F1\": f1,\n", " \"ROC_AUC\": auc,\n", " \"Num_Features\": len(feature_names)\n", " }" ], "metadata": { "id": "EOjhdZSJtWLs" }, "execution_count": null, "outputs": [] }, { "cell_type": "markdown", "source": [ "Log all three model" ], "metadata": { "id": "HyQsvFX3YStM" } }, { "cell_type": "code", "source": [ "import os\n", "import json\n", "import mlflow\n", "import mlflow.sklearn\n", "import pandas as pd\n", "from sklearn.metrics import (\n", " accuracy_score,\n", " precision_score,\n", " recall_score,\n", " f1_score,\n", " roc_auc_score,\n", " confusion_matrix,\n", " classification_report\n", ")\n", "\n", "def log_tuned_model(\n", " run_name,\n", " model,\n", " X_train_used,\n", " y_train,\n", " X_val_used,\n", " y_val,\n", " best_params,\n", " feature_set_name,\n", " feature_names,\n", " skops_trusted_types=None # Added parameter for trusted types\n", "):\n", " with mlflow.start_run(run_name=run_name, nested=True):\n", "\n", " # Train final tuned model\n", " model.fit(X_train_used, y_train)\n", "\n", " # Predict on validation set\n", " val_preds = model.predict(X_val_used)\n", "\n", " # Probability scores for ROC-AUC\n", " if hasattr(model, \"predict_proba\"):\n", " val_probs = model.predict_proba(X_val_used)[:, 1]\n", " else:\n", " val_probs = None\n", "\n", " # Metrics\n", " acc = accuracy_score(y_val, val_preds)\n", " prec = precision_score(y_val, val_preds, zero_division=0)\n", " rec = recall_score(y_val, val_preds, zero_division=0)\n", " f1 = f1_score(y_val, val_preds, zero_division=0)\n", "\n", " auc = None\n", " if val_probs is not None:\n", " auc = roc_auc_score(y_val, val_probs)\n", "\n", " # Log params\n", " mlflow.log_param(\"feature_set\", feature_set_name)\n", " mlflow.log_param(\"num_features\", len(feature_names))\n", " mlflow.log_params(best_params)\n", "\n", " # Log metrics\n", " mlflow.log_metric(\"val_accuracy\", acc)\n", " mlflow.log_metric(\"val_precision\", prec)\n", " mlflow.log_metric(\"val_recall\", rec)\n", " mlflow.log_metric(\"val_f1\", f1)\n", "\n", " if auc is not None:\n", " mlflow.log_metric(\"val_roc_auc\", auc)\n", "\n", " # Save feature names\n", " feature_file = f\"{run_name}_features.txt\"\n", " with open(feature_file, \"w\") as f:\n", " for col in feature_names:\n", " f.write(f\"{col}\\n\")\n", " mlflow.log_artifact(feature_file)\n", " os.remove(feature_file)\n", "\n", " # Save best params\n", " params_file = f\"{run_name}_best_params.json\"\n", " with open(params_file, \"w\") as f:\n", " json.dump(best_params, f, indent=4)\n", " mlflow.log_artifact(params_file)\n", " os.remove(params_file)\n", "\n", " # Confusion matrix\n", " cm = confusion_matrix(y_val, val_preds)\n", " cm_df = pd.DataFrame(\n", " cm,\n", " index=[\"Actual_0\", \"Actual_1\"],\n", " columns=[\"Pred_0\", \"Pred_1\"]\n", " )\n", " cm_file = f\"{run_name}_confusion_matrix.csv\"\n", " cm_df.to_csv(cm_file, index=True)\n", " mlflow.log_artifact(cm_file)\n", " os.remove(cm_file)\n", "\n", " # Classification report\n", " report = classification_report(y_val, val_preds, zero_division=0)\n", " report_file = f\"{run_name}_classification_report.txt\"\n", " with open(report_file, \"w\") as f:\n", " f.write(report)\n", " mlflow.log_artifact(report_file)\n", " os.remove(report_file)\n", "\n", " # Log model, passing skops_trusted_types if provided\n", " mlflow.sklearn.log_model(model, artifact_path=f\"{run_name}_model\", skops_trusted_types=skops_trusted_types)\n", "\n", " return {\n", " \"Run_Name\": run_name,\n", " \"Feature_Set\": feature_set_name,\n", " \"Accuracy\": acc,\n", " \"Precision\": prec,\n", " \"Recall\": rec,\n", " \"F1\": f1,\n", " \"ROC_AUC\": auc,\n", " \"Num_Features\": len(feature_names)\n", " }\n", "\n", "\n", "summary_rows = []\n", "\n", "with mlflow.start_run(run_name=\"Tuned_Model_Comparison\"):\n", "\n", " # 1) Tuned Random Forest\n", " rf_result = log_tuned_model(\n", " run_name=\"Tuned_RandomForest_Engineered\",\n", " model=tuned_rf,\n", " X_train_used=X_train_engineered,\n", " y_train=y_train,\n", " X_val_used=X_val_engineered,\n", " y_val=y_val,\n", " best_params=rf_best_params,\n", " feature_set_name=\"Engineered\",\n", " feature_names=X_train_engineered.columns.tolist()\n", " )\n", " summary_rows.append(rf_result)\n", "\n", " # 2) Tuned Gradient Boosting\n", " # This call assumes tuned_gb and gb_best_params are defined after re-running their cells\n", " gb_result = log_tuned_model(\n", " run_name=\"Tuned_GradientBoosting_Engineered\",\n", " model=tuned_gb,\n", " X_train_used=X_train_engineered,\n", " y_train=y_train,\n", " X_val_used=X_val_engineered,\n", " y_val=y_val,\n", " best_params=gb_best_params,\n", " feature_set_name=\"Engineered\",\n", " feature_names=X_train_engineered.columns.tolist()\n", " )\n", " summary_rows.append(gb_result)\n", "\n", " # 3) Tuned XGBoost (replaces undefined Bagging)\n", " xgb_result = log_tuned_model(\n", " run_name=\"Tuned_XGBoost_Engineered\",\n", " model=tuned_xgb,\n", " X_train_used=X_train_engineered,\n", " y_train=y_train,\n", " X_val_used=X_val_engineered,\n", " y_val=y_val,\n", " best_params=xgb_best_params,\n", " feature_set_name=\"Engineered\",\n", " feature_names=X_train_engineered.columns.tolist(),\n", " skops_trusted_types=['xgboost.core.Booster', 'xgboost.sklearn.XGBClassifier'] # Pass trusted types for XGBoost\n", " )\n", " summary_rows.append(xgb_result)\n", "\n", " # Summary table\n", " tuned_summary_df = pd.DataFrame(summary_rows).sort_values(\"F1\", ascending=False)\n", " tuned_summary_file = \"tuned_model_comparison.csv\"\n", " tuned_summary_df.to_csv(tuned_summary_file, index=False)\n", " mlflow.log_artifact(tuned_summary_file)\n", "\n", "print(tuned_summary_df)\n" ], "metadata": { "id": "NGqHDxOFKBmd", "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "e2a8d336-80cc-4c3b-d75d-57c0bc87fafe" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stderr", "text": [ "2026/07/14 18:53:06 WARNING mlflow.models.model: `artifact_path` is deprecated. Please use `name` instead.\n", "2026/07/14 18:54:22 WARNING mlflow.models.model: `artifact_path` is deprecated. Please use `name` instead.\n", "2026/07/14 18:54:36 WARNING mlflow.models.model: `artifact_path` is deprecated. Please use `name` instead.\n" ] }, { "output_type": "stream", "name": "stdout", "text": [ " Run_Name Feature_Set Accuracy Precision \\\n", "2 Tuned_XGBoost_Engineered Engineered 0.669866 0.700727 \n", "1 Tuned_GradientBoosting_Engineered Engineered 0.665387 0.698583 \n", "0 Tuned_RandomForest_Engineered Engineered 0.640115 0.746791 \n", "\n", " Recall F1 ROC_AUC Num_Features \n", "2 0.831558 0.760557 0.700559 13 \n", "1 0.825469 0.756744 0.691947 13 \n", "0 0.649417 0.694708 0.692770 13 \n" ] } ] }, { "cell_type": "code", "source": [ "best_row = tuned_summary_df.iloc[0]" ], "metadata": { "id": "cHdVvjkrNseG" }, "execution_count": null, "outputs": [] }, { "cell_type": "markdown", "source": [ "#Compare the Top Tuned Models" ], "metadata": { "id": "R1qhjV6b3JQI" } }, { "cell_type": "code", "source": [ "best_model_name = tuned_summary_df.iloc[0][\"Run_Name\"]\n", "best_model_name" ], "metadata": { "id": "pCzMOk1o3Mb4", "colab": { "base_uri": "https://localhost:8080/", "height": 36 }, "outputId": "92cc4606-1078-497f-9698-0039c8fad576" }, "execution_count": null, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "'Tuned_XGBoost_Engineered'" ], "application/vnd.google.colaboratory.intrinsic+json": { "type": "string" } }, "metadata": {}, "execution_count": 49 } ] }, { "cell_type": "markdown", "source": [ "#Compare Tune Models" ], "metadata": { "id": "tTyABDjEOdP8" } }, { "cell_type": "code", "source": [ "tuned_model_map = {\n", " \"RandomForest\": tuned_rf,\n", " \"GradientBoosting\": tuned_gb,\n", " \"XGBoost\": tuned_xgb\n", "}\n", "\n", "best_params_map = {\n", " \"RandomForest\": rf_best_params,\n", " \"GradientBoosting\": gb_best_params,\n", " \"XGBoost\": xgb_best_params\n", "}" ], "metadata": { "id": "0wYbnxLUOhz-" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "best_model_name = tuned_summary_df.iloc[0][\"Run_Name\"]\n", "\n", "# Create a mapping from the full run name to the dictionary key\n", "model_key_mapping = {\n", " \"Tuned_RandomForest_Engineered\": \"RandomForest\",\n", " \"Tuned_GradientBoosting_Engineered\": \"GradientBoosting\",\n", " \"Tuned_XGBoost_Engineered\": \"XGBoost\"\n", "}\n", "\n", "# Get the correct key for the dictionary\n", "mapped_model_key = model_key_mapping.get(best_model_name, best_model_name)\n", "\n", "best_model = tuned_model_map[mapped_model_key]\n", "best_params = best_params_map[mapped_model_key]\n", "\n", "print(\"Best tuned model:\", best_model_name)" ], "metadata": { "id": "gzXSCaCvOobe", "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "582cbe99-f28c-421e-d8c4-9bb9234f2c0f" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Best tuned model: Tuned_XGBoost_Engineered\n" ] } ] }, { "cell_type": "code", "source": [ "X_train_final = X_train_engineered.copy()\n", "X_val_final = X_val_engineered.copy()\n", "X_test_final = X_test_fe.copy()" ], "metadata": { "id": "6PUcr6ZKOrB_" }, "execution_count": null, "outputs": [] }, { "cell_type": "markdown", "source": [ " #Refit best model on train data" ], "metadata": { "id": "OSQctQj2Owut" } }, { "cell_type": "code", "source": [ "final_model = clone(best_model)\n", "final_model.fit(X_train_final, y_train)" ], "metadata": { "id": "GOxi4CKHOtMg", "colab": { "base_uri": "https://localhost:8080/", "height": 257 }, "outputId": "7e02db7b-3049-4139-85a6-631de9b93a50" }, "execution_count": null, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "XGBClassifier(base_score=None, booster=None, callbacks=None,\n", " colsample_bylevel=None, colsample_bynode=None,\n", " colsample_bytree=0.9750056358595923, device=None,\n", " early_stopping_rounds=None, enable_categorical=True,\n", " eval_metric='logloss', feature_types=None, feature_weights=None,\n", " gamma=4.603085106026683, grow_policy=None, importance_type=None,\n", " interaction_constraints=None, learning_rate=0.050134066679396426,\n", " max_bin=None, max_cat_threshold=None, max_cat_to_onehot=None,\n", " max_delta_step=None, max_depth=5, max_leaves=None,\n", " min_child_weight=4, missing=nan, monotone_constraints=None,\n", " multi_strategy=None, n_estimators=200, n_jobs=-1,\n", " num_parallel_tree=None, ...)" ], "text/html": [ "
XGBClassifier(base_score=None, booster=None, callbacks=None,\n",
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              "              eval_metric='logloss', feature_types=None, feature_weights=None,\n",
              "              gamma=4.603085106026683, grow_policy=None, importance_type=None,\n",
              "              interaction_constraints=None, learning_rate=0.050134066679396426,\n",
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In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
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" ] }, "metadata": {}, "execution_count": 54 } ] }, { "cell_type": "code", "source": [ "test_preds = final_model.predict(X_test_final)\n", "\n", "if hasattr(final_model, \"predict_proba\"):\n", " test_probs = final_model.predict_proba(X_test_final)[:, 1]\n", "else:\n", " test_probs = final_model.decision_function(X_test_final)\n", "\n", "test_acc = accuracy_score(y_test_fe, test_preds)\n", "test_prec = precision_score(y_test_fe, test_preds, zero_division=0)\n", "test_rec = recall_score(y_test_fe, test_preds, zero_division=0)\n", "test_f1 = f1_score(y_test_fe, test_preds, zero_division=0)\n", "test_auc = roc_auc_score(y_test_fe, test_probs)" ], "metadata": { "id": "BOcSKctGOy8k" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "cm_test = confusion_matrix(y_test_fe, test_preds)\n", "cm_df = pd.DataFrame(\n", " cm_test,\n", " index=[\"Actual_0\", \"Actual_1\"],\n", " columns=[\"Pred_0\", \"Pred_1\"]\n", ")\n", "\n", "test_report = classification_report(y_test_fe, test_preds, zero_division=0)\n", "\n", "print(\"\\nTest Results:\")\n", "print(f\"Accuracy : {test_acc:.4f}\")\n", "print(f\"Precision: {test_prec:.4f}\")\n", "print(f\"Recall : {test_rec:.4f}\")\n", "print(f\"F1 : {test_f1:.4f}\")\n", "print(f\"ROC AUC : {test_auc:.4f}\")\n", "print(\"\\nClassification Report:\\n\", test_report)" ], "metadata": { "id": "Z5AbVYsSO6hh", "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "1d70e31f-3eb6-487a-db94-d0e8f61684f3" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "\n", "Test Results:\n", "Accuracy : 0.6642\n", "Precision: 0.6969\n", "Recall : 0.8270\n", "F1 : 0.7564\n", "ROC AUC : 0.6981\n", "\n", "Classification Report:\n", " precision recall f1-score support\n", "\n", " 0 0.57 0.39 0.46 1444\n", " 1 0.70 0.83 0.76 2463\n", "\n", " accuracy 0.66 3907\n", " macro avg 0.63 0.61 0.61 3907\n", "weighted avg 0.65 0.66 0.65 3907\n", "\n" ] } ] }, { "cell_type": "code", "source": [ "print(pd.Series(test_preds).value_counts())" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "AWWT8O3-4C1m", "outputId": "1e0611b5-fd2f-45f0-f25d-3fccb6e77e1f" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "1 2923\n", "0 984\n", "Name: count, dtype: int64\n" ] } ] }, { "cell_type": "markdown", "source": [ "### Final Model Evaluation Summary\n", "\n", "After comparing and tuning the selected tree-based ensemble models, **XGBoost** achieved the best validation performance and was selected as the final model. The tuned model was retrained using the engineered training dataset and evaluated on the unseen test dataset to assess its generalization performance.\n", "\n", "The final tuned XGBoost model achieved the following test results:\n", "\n", "* **Accuracy:** 66.42%\n", "* **Precision:** 69.69%\n", "* **Recall:** 82.70%\n", "* **F1-Score:** 75.64%\n", "* **ROC-AUC:** 69.81%\n", "\n", "The model demonstrates a strong ability to identify positive engine condition cases, achieving a high recall of **82.70%**. This is particularly valuable in a predictive maintenance application, where correctly identifying engines that require attention is more important than maximizing overall accuracy. A higher recall helps reduce the likelihood of missed failures, enabling proactive maintenance and minimizing unexpected equipment downtime.\n", "\n", "The confusion matrix and classification report indicate that the model predicts the positive class more frequently (2,923 positive predictions versus 984 negative predictions). While this leads to some false positives, it significantly reduces false negatives, which is often the preferred trade-off in predictive maintenance because the cost of overlooking a potential failure is typically much higher than performing an unnecessary inspection.\n", "\n", "Overall, the tuned XGBoost model provides the best balance of precision, recall, F1-score, and ROC-AUC among the evaluated tree-based models. Based on these results, it was selected as the final model for deployment and registration in the Hugging Face Model Hub.\n" ], "metadata": { "id": "hCizNdbb9d8P" } }, { "cell_type": "markdown", "source": [ "#Log final test run in MLflow" ], "metadata": { "id": "eQKka_97O7VS" } }, { "cell_type": "code", "source": [ "mlflow.set_experiment(\"Engine_Condition_Final_Test\")\n", "\n", "with mlflow.start_run(run_name=f\"Final_Test_{best_model_name}\"):\n", "\n", " mlflow.log_param(\"best_model_name\", best_model_name)\n", " mlflow.log_param(\"feature_set\", \"Engineered\")\n", " mlflow.log_param(\"num_features\", X_train_final.shape[1])\n", " mlflow.log_params(best_params)\n", "\n", " mlflow.log_metric(\"test_accuracy\", test_acc)\n", " mlflow.log_metric(\"test_precision\", test_prec)\n", " mlflow.log_metric(\"test_recall\", test_rec)\n", " mlflow.log_metric(\"test_f1\", test_f1)\n", " mlflow.log_metric(\"test_roc_auc\", test_auc)\n", "\n", " # Save confusion matrix\n", " cm_path = \"final_test_confusion_matrix.csv\"\n", " cm_df.to_csv(cm_path, index=True)\n", " mlflow.log_artifact(cm_path)\n", "\n", " # Save classification report\n", " report_path = \"final_test_classification_report.txt\"\n", " with open(report_path, \"w\") as f:\n", " f.write(test_report)\n", " mlflow.log_artifact(report_path)\n", "\n", " # Log final model\n", " mlflow.sklearn.log_model(\n", " final_model,\n", " name=f\"final_{best_model_name}_model\",\n", " skops_trusted_types=['xgboost.core.Booster', 'xgboost.sklearn.XGBClassifier']\n", " )" ], "metadata": { "id": "xkzidZCxO-YZ" }, "execution_count": null, "outputs": [] }, { "cell_type": "markdown", "source": [ "# Save model locally for Hugging Face upload" ], "metadata": { "id": "lWeC9H-TPPXA" } }, { "cell_type": "code", "source": [ "import joblib\n", "os.makedirs(\"final_model_artifacts\", exist_ok=True)\n", "joblib.dump(final_model, \"final_model_artifacts/best_model.pkl\")\n", "\n", "with open(\"final_model_artifacts/feature_names.txt\", \"w\") as f:\n", " for col in X_train_final.columns:\n", " f.write(f\"{col}\\n\")\n", "\n", "with open(\"final_model_artifacts/model_info.json\", \"w\") as f:\n", " json.dump(\n", " {\n", " \"best_model_name\": best_model_name,\n", " \"feature_set\": \"Engineered\",\n", " \"test_accuracy\": test_acc,\n", " \"test_precision\": test_prec,\n", " \"test_recall\": test_rec,\n", " \"test_f1\": test_f1,\n", " \"test_roc_auc\": test_auc,\n", " \"best_params\": best_params\n", " },\n", " f,\n", " indent=4\n", " )\n", "\n", "print(\"\\nSaved model to: final_model_artifacts/best_model.pkl\")" ], "metadata": { "id": "9Q_RixzTPDuY", "colab": { "base_uri": "https://localhost:8080/" }, "outputId": "894aa7fc-f5f0-4a8b-cc62-28cdf4aa25f1" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "\n", "Saved model to: final_model_artifacts/best_model.pkl\n" ] } ] }, { "cell_type": "code", "source": [ "import mlflow\n", "import mlflow.sklearn\n", "from huggingface_hub import HfApi, create_repo\n", "import os\n", "\n", "# -----------------------------\n", "# 1) Log final model in MLflow\n", "# -----------------------------\n", "mlflow.set_experiment(\"Engine_Condition_Final_Model\")\n", "\n", "with mlflow.start_run(run_name=f\"Final_{best_model_name}\"):\n", "\n", " mlflow.log_param(\"best_model_name\", best_model_name)\n", " mlflow.log_param(\"feature_set\", \"Engineered\")\n", " mlflow.log_param(\"num_features\", X_train_final.shape[1])\n", " mlflow.log_params(best_params)\n", "\n", " mlflow.log_metric(\"test_accuracy\", test_acc)\n", " mlflow.log_metric(\"test_precision\", test_prec)\n", " mlflow.log_metric(\"test_recall\", test_rec)\n", " mlflow.log_metric(\"test_f1\", test_f1)\n", " mlflow.log_metric(\"test_roc_auc\", test_auc)\n", "\n", " mlflow.log_artifact(\"final_model_artifacts/feature_names.txt\")\n", " mlflow.log_artifact(\"final_model_artifacts/model_info.json\")\n", " mlflow.log_artifact(\"final_model_artifacts/best_model.pkl\")\n", "\n", " # If you want, also log the model in MLflow format\n", " mlflow.sklearn.log_model(final_model, name=\"final_model\", skops_trusted_types=['xgboost.core.Booster', 'xgboost.sklearn.XGBClassifier'])\n", "\n", "print(\"Final model logged to MLflow.\")" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "19i3ulOD-NcG", "outputId": "ccf9380d-2928-46b2-d599-157a9b33bc6a" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Final model logged to MLflow.\n" ] } ] }, { "cell_type": "code", "source": [ "from huggingface_hub import HfApi, create_repo, notebook_login\n", "import os\n", "\n", "notebook_login()\n", "\n", "hf_token = os.environ.get(\"HF_TOKEN\") # If you set it, otherwise notebook_login() handles it.\n", "\n", "# Correct repo_id and type for the model upload\n", "model_repo_id = \"Swetha1929/predictive-maintenance-engine-model\"\n", "\n", "create_repo(\n", " repo_id=model_repo_id,\n", " repo_type=\"model\", # Changed to 'model'\n", " token=hf_token,\n", " exist_ok=True\n", ")\n", "\n", "api = HfApi()\n", "\n", "# Optional model card (restoring previous functionality)\n", "readme_text = f\"\"\"---\n", "library_name: scikit-learn\n", "tags:\n", " - machine-learning\n", " - predictive-maintenance\n", "---\n", "\n", "# Predictive Maintenance Engine Model\n", "\n", "Final model: {best_model_name}\n", "\n", "## Test Metrics\n", "- Accuracy: {test_acc:.4f}\n", "- Precision: {test_prec:.4f}\n", "- Recall: {test_rec:.4f}\n", "- F1: {test_f1:.4f}\n", "- ROC-AUC: {test_auc:.4f}\n", "\"\"\"\n", "\n", "with open(\"final_model_artifacts/README.md\", \"w\") as f:\n", " f.write(readme_text)\n", "\n", "# Upload the entire folder containing model artifacts\n", "api.upload_folder(\n", " folder_path=\"final_model_artifacts\", # Correct path to the model artifacts\n", " repo_id=model_repo_id,\n", " repo_type=\"model\", # Changed to 'model'\n", " token=hf_token\n", ")\n", "\n", "print(f\"Uploaded successfully to: https://huggingface.co/{model_repo_id}\")" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 287 }, "id": "RDmcji_r-67F", "outputId": "bdfac682-003c-4908-b0c8-a9fff1074a04" }, "execution_count": null, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ "" ], "text/html": [ "
\"Hugging

To log in, open this URL and enter the code:

https://hf.co/oauth/device

FUJD-DPB5

" ] }, "metadata": {} }, { "output_type": "display_data", "data": { "text/plain": [ "" ], "text/html": [ "
Waiting for authorization...
" ] }, "metadata": {} }, { "output_type": "display_data", "data": { "text/plain": [ "" ], "text/html": [ "
Login successful. Logged in as Swetha1929 (token: oauth-Swetha1929).
This token will be refreshed automatically when it expires.
" ] }, "metadata": {} }, { "output_type": "stream", "name": "stdout", "text": [ "Uploaded successfully to: https://huggingface.co/Swetha1929/predictive-maintenance-engine-model\n" ] } ] }, { "cell_type": "code", "source": [ "from google.colab import drive\n", "drive.mount('/content/drive')" ], "metadata": { "id": "oVJhupp9Arga" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "import mlflow\n", "\n", "experiments = mlflow.search_experiments()\n", "\n", "for exp in experiments:\n", " print(exp.name)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "0VSjvooIC8FQ", "outputId": "caf9d85e-0b9f-4694-ab3b-8820e8ff90d9" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Engine_Condition_Final_Model\n", "Engine_Condition_Final_Test\n", "Engine_Condition_Tuned_Engineered_Set\n", "Engine_Condition_10Model_Comparison\n", "Engine_Condition_Model_Building\n", "Engine_Condition_Feature_Engineering\n", "Engine_Condition_Baseline\n", "Default\n" ] } ] }, { "cell_type": "code", "source": [ "experiment = mlflow.get_experiment_by_name(\"Engine_Condition_Model_Building\")\n", "\n", "runs = mlflow.search_runs(experiment_ids=[experiment.experiment_id])\n", "\n", "runs" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 264 }, "id": "z7kyIitvC_-5", "outputId": "f2380111-a1d5-41b4-8fd9-9a6a7943813c" }, "execution_count": null, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ " run_id experiment_id status \\\n", "0 61ba72a4cce644a890327c7d6382143e 3 FINISHED \n", "1 7abaebfeb0f44d728ab08d3f156779e9 3 FINISHED \n", "2 5eb3467ce633415b8f151940da87691c 3 FINISHED \n", "3 549127e574ec46f18c0f8af895f95832 3 FINISHED \n", "\n", " artifact_uri \\\n", "0 /content/mlruns/3/61ba72a4cce644a890327c7d6382... \n", "1 /content/mlruns/3/7abaebfeb0f44d728ab08d3f1567... \n", "2 /content/mlruns/3/5eb3467ce633415b8f151940da87... \n", "3 /content/mlruns/3/549127e574ec46f18c0f8af895f9... \n", "\n", " start_time end_time \\\n", "0 2026-07-13 13:42:43.040000+00:00 2026-07-13 13:42:53.948000+00:00 \n", "1 2026-07-13 13:42:32.013000+00:00 2026-07-13 13:42:43.027000+00:00 \n", "2 2026-07-13 13:42:21.394000+00:00 2026-07-13 13:42:32+00:00 \n", "3 2026-07-13 13:42:11.103000+00:00 2026-07-13 13:42:21.354000+00:00 \n", "\n", " metrics.val_accuracy metrics.val_precision metrics.val_recall \\\n", "0 0.581254 0.668020 0.667681 \n", "1 0.585413 0.675143 0.660071 \n", "2 0.578055 0.663490 0.671233 \n", "3 0.581254 0.668020 0.667681 \n", "\n", " metrics.val_f1 metrics.val_roc_auc params.random_state params.feature_set \\\n", "0 0.667851 0.550724 42 FeatureSelected \n", "1 0.667522 0.559040 42 FeatureEngineered \n", "2 0.667339 0.545140 42 Original \n", "3 0.667851 0.550724 42 Selected \n", "\n", " params.num_features params.model_type \\\n", "0 7 DecisionTreeClassifier \n", "1 13 DecisionTreeClassifier \n", "2 6 DecisionTreeClassifier \n", "3 7 DecisionTreeClassifier \n", "\n", " tags.mlflow.source.name tags.mlflow.user \\\n", "0 fileId=1j2_V1gRJoZuKKceCDmIqTpMSW4y6iEnZ root \n", "1 fileId=1j2_V1gRJoZuKKceCDmIqTpMSW4y6iEnZ root \n", "2 fileId=1j2_V1gRJoZuKKceCDmIqTpMSW4y6iEnZ root \n", "3 fileId=1j2_V1gRJoZuKKceCDmIqTpMSW4y6iEnZ root \n", "\n", " tags.mlflow.runName tags.mlflow.source.type \n", "0 DecisionTree_FeatureSelected NOTEBOOK \n", "1 DecisionTree_FeatureEngineered NOTEBOOK \n", "2 DecisionTree_Original NOTEBOOK \n", "3 DecisionTree_FeatureSelected NOTEBOOK " ], "text/html": [ "\n", "
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"outputId": "62d2ffc6-6cc2-49a8-fa6c-a6c359a4eb86" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Tracking URI: sqlite:////content/mlflow.db\n" ] } ] }, { "cell_type": "code", "source": [ "import mlflow\n", "\n", "for exp in mlflow.search_experiments():\n", " print(exp.experiment_id, exp.name)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "gYn24vQgD_Dq", "outputId": "021687b2-8c52-4e7a-e1b7-9a4f4fd6556f" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "7 Engine_Condition_Final_Model\n", "6 Engine_Condition_Final_Test\n", "5 Engine_Condition_Tuned_Engineered_Set\n", "4 Engine_Condition_10Model_Comparison\n", "3 Engine_Condition_Model_Building\n", "2 Engine_Condition_Feature_Engineering\n", "1 Engine_Condition_Baseline\n", "0 Default\n" ] } ] }, { "cell_type": "code", "source": [ "experiment = mlflow.get_experiment_by_name(\"Engine_Condition_Final_Model\")\n", 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"cell_type": "code", "source": [ "import shutil\n", "\n", "# Backup MLflow database\n", "shutil.copy(\"/content/mlflow.db\", \"/content/mlflow_backup.db\")" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 36 }, "id": "qaeg1w8_EJfl", "outputId": "5f5fa4e1-997a-447c-a7af-179f4e09fc8c" }, "execution_count": null, "outputs": [ { "output_type": "execute_result", "data": { "text/plain": [ "'/content/mlflow_backup.db'" ], "application/vnd.google.colaboratory.intrinsic+json": { "type": "string" } }, "metadata": {}, "execution_count": 105 } ] }, { "cell_type": "code", "source": [ "import mlflow\n", "\n", "experiments = mlflow.search_experiments()\n", "\n", "for exp in experiments:\n", " print(f\"ID: {exp.experiment_id}\")\n", " print(f\"Name: {exp.name}\")\n", " print(\"-\" * 40)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "iaNo_vzuEK-W", "outputId": "cbaa4041-72e2-4785-9629-b5b624cb0737" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "ID: 7\n", "Name: Engine_Condition_Final_Model\n", "----------------------------------------\n", "ID: 6\n", "Name: Engine_Condition_Final_Test\n", "----------------------------------------\n", "ID: 5\n", "Name: Engine_Condition_Tuned_Engineered_Set\n", "----------------------------------------\n", "ID: 4\n", "Name: Engine_Condition_10Model_Comparison\n", "----------------------------------------\n", "ID: 3\n", "Name: Engine_Condition_Model_Building\n", "----------------------------------------\n", "ID: 2\n", "Name: Engine_Condition_Feature_Engineering\n", "----------------------------------------\n", "ID: 1\n", "Name: Engine_Condition_Baseline\n", "----------------------------------------\n", "ID: 0\n", "Name: Default\n", "----------------------------------------\n" ] } ] }, { "cell_type": "code", "source": [ "import mlflow\n", "import pandas as pd\n", "\n", "all_runs = []\n", "\n", "for exp in mlflow.search_experiments():\n", " runs = mlflow.search_runs(\n", " experiment_ids=[exp.experiment_id],\n", " output_format=\"pandas\"\n", " )\n", "\n", " if not runs.empty:\n", " runs[\"Experiment\"] = exp.name\n", " all_runs.append(runs)\n", "\n", "all_results = pd.concat(all_runs, ignore_index=True)\n", "\n", "print(all_results.shape)\n", "all_results.head()" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 359 }, "id": "PJeTBZ88EKxi", "outputId": "548e6aba-a18d-4090-e0b0-209e171460f2" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "(55, 39)\n" ] }, { "output_type": "execute_result", "data": { "text/plain": [ " run_id experiment_id status \\\n", "0 fa5ce50f08ce4d9586c27adb304c6402 7 FINISHED \n", "1 578fab3fed7448f18c2b37ec24e11f85 6 FINISHED \n", "2 84530185045043248878561cccc48c4a 6 FINISHED \n", "3 d8353989b763424991949aa220542b74 6 FINISHED \n", "4 0135d48fb478491b89102bff8411a522 6 FINISHED \n", "\n", " artifact_uri \\\n", "0 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Engine_Condition_10Model_Comparison GradientBoosting \n", "16 Engine_Condition_10Model_Comparison AdaBoost \n", "17 Engine_Condition_10Model_Comparison ExtraTrees \n", "18 Engine_Condition_10Model_Comparison RandomForest \n", "19 Engine_Condition_10Model_Comparison Bagging \n", "20 Engine_Condition_10Model_Comparison DecisionTree \n", "21 Engine_Condition_10Model_Comparison Compare_10_Models_Selected \n", "22 Engine_Condition_10Model_Comparison SVC \n", "23 Engine_Condition_10Model_Comparison KNN \n", "24 Engine_Condition_10Model_Comparison LogisticRegression \n", "25 Engine_Condition_10Model_Comparison HistGradientBoosting \n", "26 Engine_Condition_10Model_Comparison GradientBoosting \n", "27 Engine_Condition_10Model_Comparison AdaBoost \n", "28 Engine_Condition_10Model_Comparison ExtraTrees \n", "29 Engine_Condition_10Model_Comparison RandomForest \n", "30 Engine_Condition_10Model_Comparison Bagging \n", "31 Engine_Condition_10Model_Comparison DecisionTree \n", "32 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Experimenttags.mlflow.runNamemetrics.val_accuracymetrics.val_precisionmetrics.val_recallmetrics.val_f1metrics.val_roc_aucmetrics.test_accuracymetrics.test_precisionmetrics.test_recallmetrics.test_f1metrics.test_roc_auc
0Engine_Condition_Final_ModelFinal_Tuned_LogReg_EngineeredNaNNaNNaNNaNNaN0.6634250.6800500.8802270.7672980.690278
1Engine_Condition_Final_TestFinal_Test_Tuned_LogReg_EngineeredNaNNaNNaNNaNNaN0.6634250.6800500.8802270.7672980.690278
2Engine_Condition_Final_TestTuned_LogReg_Engineered0.6689060.6836730.8838150.7709670.687520NaNNaNNaNNaNNaN
3Engine_Condition_Final_TestTuned_SVC_Engineered0.6513120.7331920.7026890.7176170.686170NaNNaNNaNNaNNaN
4Engine_Condition_Final_TestTuned_Model_ComparisonNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
5Engine_Condition_Final_TestFinal_Test_Tuned_SVC_EngineeredNaNNaNNaNNaNNaN0.6534430.6543280.9545270.7764200.697155
6Engine_Condition_Tuned_Engineered_SetTuned_LogReg_Engineered0.6679460.6828690.8838150.7704560.687761NaNNaNNaNNaNNaN
7Engine_Condition_Tuned_Engineered_SetTuned_SVC_Engineered0.6516310.6520690.9594110.7764320.692474NaNNaNNaNNaNNaN
8Engine_Condition_Tuned_Engineered_SetTuned_Model_ComparisonNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
9Engine_Condition_Tuned_Engineered_SetTuned_Model_ComparisonNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
10Engine_Condition_Tuned_Engineered_SetTuned_Model_ComparisonNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
11Engine_Condition_10Model_ComparisonSVC0.6682660.6821370.8873670.7713340.680251NaNNaNNaNNaNNaN
12Engine_Condition_10Model_ComparisonKNN0.6423540.6894710.7874180.7351970.646460NaNNaNNaNNaNNaN
13Engine_Condition_10Model_ComparisonLogisticRegression0.6698660.6844790.8838150.7714790.688258NaNNaNNaNNaNNaN
14Engine_Condition_10Model_ComparisonHistGradientBoosting0.6625080.6930860.8340940.7570800.694698NaNNaNNaNNaNNaN
15Engine_Condition_10Model_ComparisonGradientBoosting0.6689060.6966390.8411970.7621240.696543NaNNaNNaNNaNNaN
16Engine_Condition_10Model_ComparisonAdaBoost0.6583490.6631730.9309990.7745880.688810NaNNaNNaNNaNNaN
17Engine_Condition_10Model_ComparisonExtraTrees0.6580290.6930650.8214100.7517990.671429NaNNaNNaNNaNNaN
18Engine_Condition_10Model_ComparisonRandomForest0.6586690.6936590.8214100.7521490.675237NaNNaNNaNNaNNaN
19Engine_Condition_10Model_ComparisonBagging0.6497120.6901040.8066970.7438600.665644NaNNaNNaNNaNNaN
20Engine_Condition_10Model_ComparisonDecisionTree0.5812540.6680200.6676810.6678510.550724NaNNaNNaNNaNNaN
21Engine_Condition_10Model_ComparisonCompare_10_Models_SelectedNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
22Engine_Condition_10Model_ComparisonSVC0.6682660.6774320.9046170.7747120.678709NaNNaNNaNNaNNaN
23Engine_Condition_10Model_ComparisonKNN0.6381960.6856760.7869100.7328140.639651NaNNaNNaNNaNNaN
24Engine_Condition_10Model_ComparisonLogisticRegression0.6695460.6842110.8838150.7713080.687188NaNNaNNaNNaNNaN
25Engine_Condition_10Model_ComparisonHistGradientBoosting0.6685860.6956890.8432270.7623850.698251NaNNaNNaNNaNNaN
26Engine_Condition_10Model_ComparisonGradientBoosting0.6756240.7007970.8472860.7671110.703869NaNNaNNaNNaNNaN
27Engine_Condition_10Model_ComparisonAdaBoost0.6583490.6631730.9309990.7745880.688810NaNNaNNaNNaNNaN
28Engine_Condition_10Model_ComparisonExtraTrees0.6628280.6973740.8219180.7545410.678205NaNNaNNaNNaNNaN
29Engine_Condition_10Model_ComparisonRandomForest0.6570700.6931670.8183660.7505820.680605NaNNaNNaNNaNNaN
30Engine_Condition_10Model_ComparisonBagging0.6481130.6907580.8001010.7414200.671937NaNNaNNaNNaNNaN
31Engine_Condition_10Model_ComparisonDecisionTree0.5854130.6751430.6600710.6675220.559040NaNNaNNaNNaNNaN
32Engine_Condition_10Model_ComparisonCompare_10_Models_EngineeredNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
33Engine_Condition_10Model_ComparisonSVC0.6663470.6779140.8970070.7722210.681698NaNNaNNaNNaNNaN
34Engine_Condition_10Model_ComparisonKNN0.6417150.6880250.7899540.7354750.641543NaNNaNNaNNaNNaN
35Engine_Condition_10Model_ComparisonLogisticRegression0.6685860.6836940.8828010.7705930.688602NaNNaNNaNNaNNaN
36Engine_Condition_10Model_ComparisonHistGradientBoosting0.6676260.6962930.8386610.7608750.698496NaNNaNNaNNaNNaN
37Engine_Condition_10Model_ComparisonGradientBoosting0.6717850.6994510.8406900.7635940.700938NaNNaNNaNNaNNaN
38Engine_Condition_10Model_ComparisonAdaBoost0.6570700.6671630.9101980.7699570.692116NaNNaNNaNNaNNaN
39Engine_Condition_10Model_ComparisonExtraTrees0.6573900.6881270.8351090.7545270.684093NaNNaNNaNNaNNaN
40Engine_Condition_10Model_ComparisonRandomForest0.6487520.6851930.8193810.7463030.679968NaNNaNNaNNaNNaN
41Engine_Condition_10Model_ComparisonBagging0.6509920.6943460.7975650.7423850.674275NaNNaNNaNNaNNaN
42Engine_Condition_10Model_ComparisonDecisionTree0.5780550.6634900.6712330.6673390.545140NaNNaNNaNNaNNaN
43Engine_Condition_10Model_ComparisonCompare_10_Models_OriginalNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
44Engine_Condition_Model_BuildingDecisionTree_FeatureSelected0.5812540.6680200.6676810.6678510.550724NaNNaNNaNNaNNaN
45Engine_Condition_Model_BuildingDecisionTree_FeatureEngineered0.5854130.6751430.6600710.6675220.559040NaNNaNNaNNaNNaN
46Engine_Condition_Model_BuildingDecisionTree_Original0.5780550.6634900.6712330.6673390.545140NaNNaNNaNNaNNaN
47Engine_Condition_Model_BuildingDecisionTree_FeatureSelected0.5812540.6680200.6676810.6678510.550724NaNNaNNaNNaNNaN
48Engine_Condition_Feature_EngineeringDecisionTree_FeatureEngineered0.5854130.6751430.6600710.6675220.559040NaNNaNNaNNaNNaN
49Engine_Condition_BaselineBaseline_DecisionTree0.5780550.6634900.6712330.6673390.545140NaNNaNNaNNaNNaN
50DefaultRFENaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
51DefaultRandomForest_ImportanceNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
52DefaultMutualInfoNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
53DefaultVarianceThresholdNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
54DefaultFeature_Selection_DiscoveryNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
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\n" ], "application/vnd.google.colaboratory.intrinsic+json": { "type": "dataframe", "summary": "{\n \"name\": \"display(all_results[available_columns])\",\n \"rows\": 55,\n \"fields\": [\n {\n \"column\": \"Experiment\",\n \"properties\": {\n \"dtype\": \"category\",\n \"num_unique_values\": 8,\n \"samples\": [\n \"Engine_Condition_Final_Test\",\n \"Engine_Condition_Feature_Engineering\",\n \"Engine_Condition_Final_Model\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"tags.mlflow.runName\",\n \"properties\": {\n \"dtype\": \"string\",\n \"num_unique_values\": 28,\n \"samples\": [\n \"HistGradientBoosting\",\n \"MutualInfo\",\n \"LogisticRegression\"\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"metrics.val_accuracy\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.0342282408187728,\n \"min\": 0.5780550223928342,\n \"max\": 0.6756238003838771,\n \"num_unique_values\": 29,\n \"samples\": [\n 0.6509916826615483,\n 0.6756238003838771,\n 0.5812539987204095\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"metrics.val_precision\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.01489888284560824,\n \"min\": 0.6520689655172414,\n \"max\": 0.7331921651667549,\n \"num_unique_values\": 33,\n \"samples\": [\n 0.6943462897526502,\n 0.6856763925729443,\n 0.6962931760741364\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"metrics.val_recall\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.0901763297794219,\n \"min\": 0.6600710299340437,\n \"max\": 0.9594114662607813,\n \"num_unique_values\": 29,\n \"samples\": [\n 0.7975646879756468,\n 0.8183663115169965,\n 0.786910197869102\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"metrics.val_f1\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.040551098563766305,\n \"min\": 0.6673392181588903,\n \"max\": 0.7764319441593102,\n \"num_unique_values\": 33,\n \"samples\": [\n 0.7423848878394333,\n 0.7328136073706591,\n 0.7608745684695052\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"metrics.val_roc_auc\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.056771908361676456,\n \"min\": 0.545140247879974,\n \"max\": 0.7038693084355185,\n \"num_unique_values\": 33,\n \"samples\": [\n 0.674274600758619,\n 0.6396513515234976,\n 0.6984959400484514\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"metrics.test_accuracy\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.005763158561145486,\n \"min\": 0.6534425390325057,\n \"max\": 0.6634246224724852,\n \"num_unique_values\": 2,\n \"samples\": [\n 0.6534425390325057,\n 0.6634246224724852\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"metrics.test_precision\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.014850793271259977,\n \"min\": 0.6543278597272474,\n \"max\": 0.6800501882057717,\n \"num_unique_values\": 2,\n \"samples\": [\n 0.6543278597272474,\n 0.6800501882057717\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"metrics.test_recall\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.04289691403235957,\n \"min\": 0.88022736500203,\n \"max\": 0.9545269995939911,\n \"num_unique_values\": 2,\n \"samples\": [\n 0.9545269995939911,\n 0.88022736500203\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"metrics.test_f1\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.0052667368799373246,\n \"min\": 0.7672978233940896,\n \"max\": 0.7764200792602378,\n \"num_unique_values\": 2,\n \"samples\": [\n 0.7764200792602378,\n 0.7672978233940896\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n },\n {\n \"column\": \"metrics.test_roc_auc\",\n \"properties\": {\n \"dtype\": \"number\",\n \"std\": 0.003970430391673335,\n \"min\": 0.690277604389845,\n \"max\": 0.6971545915561388,\n \"num_unique_values\": 2,\n \"samples\": [\n 0.6971545915561388,\n 0.690277604389845\n ],\n \"semantic_type\": \"\",\n \"description\": \"\"\n }\n }\n ]\n}" } }, "metadata": {} } ] }, { "cell_type": "code", "source": [ "all_results.to_csv(\"MLflow_Results.csv\", index=False)" ], "metadata": { "id": "spHm_knPE2gW" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "!mlflow ui \\\n", " --backend-store-uri sqlite:////content/mlflow.db \\\n", " --host 0.0.0.0 \\\n", " --port 5000" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "6sVBwVgaFFuu", "outputId": "5365baa4-79f3-4b32-fb8e-9cf252e48de5" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Registry store URI not provided. Using backend store URI.\n", "[MLflow] Security middleware enabled with default settings (localhost-only). To allow connections from other hosts, use --host 0.0.0.0 and configure --allowed-hosts and --cors-allowed-origins.\n", "/usr/local/lib/python3.12/dist-packages/mlflow/server/fastapi_app.py:17: StarletteDeprecationWarning: starlette.middleware.wsgi is deprecated and will be removed in a future release. Please refer to https://github.com/abersheeran/a2wsgi as a replacement.\n", " from starlette.middleware.wsgi import WSGIResponder, build_environ\n", "2026/07/13 15:24:44 \u001b[32mINFO\u001b[0m: Uvicorn running on \u001b[1mhttp://0.0.0.0:5000\u001b[0m (Press CTRL+C to quit)\n", "2026/07/13 15:24:44 \u001b[32mINFO\u001b[0m: Started parent process [\u001b[36m\u001b[1m27999\u001b[0m]\n", "/usr/local/lib/python3.12/dist-packages/mlflow/server/fastapi_app.py:17: StarletteDeprecationWarning: starlette.middleware.wsgi is deprecated and will be removed in a future release. Please refer to https://github.com/abersheeran/a2wsgi as a replacement.\n", " from starlette.middleware.wsgi import WSGIResponder, build_environ\n", "/usr/local/lib/python3.12/dist-packages/mlflow/server/fastapi_app.py:17: StarletteDeprecationWarning: starlette.middleware.wsgi is deprecated and will be removed in a future release. Please refer to https://github.com/abersheeran/a2wsgi as a replacement.\n", " from starlette.middleware.wsgi import WSGIResponder, build_environ\n", "/usr/local/lib/python3.12/dist-packages/mlflow/server/fastapi_app.py:17: StarletteDeprecationWarning: starlette.middleware.wsgi is deprecated and will be removed in a future release. Please refer to https://github.com/abersheeran/a2wsgi as a replacement.\n", " from starlette.middleware.wsgi import WSGIResponder, build_environ\n", "2026/07/13 15:25:37 \u001b[32mINFO\u001b[0m: Started server process [\u001b[36m28046\u001b[0m]\n", "2026/07/13 15:25:37 \u001b[32mINFO\u001b[0m: Waiting for application startup.\n", "2026/07/13 15:25:37 \u001b[32mINFO\u001b[0m: Application startup complete.\n", "/usr/local/lib/python3.12/dist-packages/mlflow/server/fastapi_app.py:17: StarletteDeprecationWarning: starlette.middleware.wsgi is deprecated and will be removed in a future release. Please refer to https://github.com/abersheeran/a2wsgi as a replacement.\n", " from starlette.middleware.wsgi import WSGIResponder, build_environ\n", "2026/07/13 15:25:38 \u001b[32mINFO\u001b[0m: Started server process [\u001b[36m28047\u001b[0m]\n", "2026/07/13 15:25:38 \u001b[32mINFO\u001b[0m: Waiting for application startup.\n", "2026/07/13 15:25:38 \u001b[32mINFO\u001b[0m: Application startup complete.\n", "2026/07/13 15:25:38 INFO mlflow.server.jobs.utils: Registered online_scoring_scheduler periodic task (runs every 1 minute)\n", "2026/07/13 15:25:38 INFO mlflow.server.jobs.utils: Registered trace_archival_scheduler periodic task (polls every 1 minute and no-ops when trace archival is disabled or unconfigured)\n", "2026/07/13 15:25:38 \u001b[32mINFO\u001b[0m: Started server process [\u001b[36m28044\u001b[0m]\n", "2026/07/13 15:25:38 \u001b[32mINFO\u001b[0m: Waiting for application startup.\n", "2026/07/13 15:25:38 \u001b[32mINFO\u001b[0m: Application startup complete.\n", "2026/07/13 15:25:39 \u001b[32mINFO\u001b[0m: Started server process [\u001b[36m28045\u001b[0m]\n", "2026/07/13 15:25:39 \u001b[32mINFO\u001b[0m: Waiting for application startup.\n", "2026/07/13 15:25:39 \u001b[32mINFO\u001b[0m: Application startup complete.\n", "2026/07/13 15:27:09 \u001b[32mINFO\u001b[0m: Shutting down\n", "2026/07/13 15:27:09 \u001b[32mINFO\u001b[0m: Shutting down\n", "2026/07/13 15:27:09 \u001b[32mINFO\u001b[0m: Shutting down\n", "2026/07/13 15:27:09 \u001b[32mINFO\u001b[0m: Shutting down\n", "2026/07/13 15:27:09 \u001b[32mINFO\u001b[0m: Waiting for application shutdown.\n", "2026/07/13 15:27:09 \u001b[32mINFO\u001b[0m: Application shutdown complete.\n", "2026/07/13 15:27:09 \u001b[32mINFO\u001b[0m: Finished server process [\u001b[36m28044\u001b[0m]\n", "2026/07/13 15:27:09 \u001b[32mINFO\u001b[0m: Waiting for application shutdown.\n", "2026/07/13 15:27:09 \u001b[32mINFO\u001b[0m: Application shutdown complete.\n", "2026/07/13 15:27:09 \u001b[32mINFO\u001b[0m: Finished server process [\u001b[36m28045\u001b[0m]\n", "2026/07/13 15:27:09 \u001b[32mINFO\u001b[0m: Waiting for application shutdown.\n", "2026/07/13 15:27:09 \u001b[32mINFO\u001b[0m: Application shutdown complete.\n", "2026/07/13 15:27:09 \u001b[32mINFO\u001b[0m: Finished server process [\u001b[36m28046\u001b[0m]\n", "2026/07/13 15:27:09 \u001b[32mINFO\u001b[0m: Waiting for application shutdown.\n", "2026/07/13 15:27:09 \u001b[32mINFO\u001b[0m: Application shutdown complete.\n", "2026/07/13 15:27:09 \u001b[32mINFO\u001b[0m: Finished server process [\u001b[36m28047\u001b[0m]\n", "2026/07/13 15:27:09 \u001b[32mINFO\u001b[0m: Received SIGINT, exiting.\n", "2026/07/13 15:27:09 \u001b[32mINFO\u001b[0m: Terminated child process [28044]\n", "2026/07/13 15:27:09 \u001b[32mINFO\u001b[0m: Terminated child process [28045]\n", "2026/07/13 15:27:09 \u001b[32mINFO\u001b[0m: Terminated child process [28046]\n", "2026/07/13 15:27:09 \u001b[32mINFO\u001b[0m: Terminated child process [28047]\n", "2026/07/13 15:27:09 \u001b[32mINFO\u001b[0m: Waiting for child process [28044]\n", "2026/07/13 15:27:09 \u001b[32mINFO\u001b[0m: Waiting for child process [28045]\n", "2026/07/13 15:27:09 \u001b[32mINFO\u001b[0m: Waiting for child process [28046]\n", "2026/07/13 15:27:09 \u001b[32mINFO\u001b[0m: Waiting for child process [28047]\n", "2026/07/13 15:27:09 \u001b[32mINFO\u001b[0m: Stopping parent process [\u001b[36m\u001b[1m27999\u001b[0m]\n" ] } ] }, { "cell_type": "code", "source": [ "import mlflow\n", "\n", "for exp in mlflow.search_experiments():\n", " print(f\"ID: {exp.experiment_id} | Name: {exp.name}\")" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "1lmOHsmHFrqC", "outputId": "7dcc139b-116d-489d-957e-6c11c1bba6c1" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "ID: 7 | Name: Engine_Condition_Final_Model\n", "ID: 6 | Name: Engine_Condition_Final_Test\n", "ID: 5 | Name: Engine_Condition_Tuned_Engineered_Set\n", "ID: 4 | Name: Engine_Condition_10Model_Comparison\n", "ID: 3 | Name: Engine_Condition_Model_Building\n", "ID: 2 | Name: Engine_Condition_Feature_Engineering\n", "ID: 1 | Name: Engine_Condition_Baseline\n", "ID: 0 | Name: Default\n" ] } ] }, { "cell_type": "code", "source": [ "import mlflow\n", "\n", "experiments_to_delete = [\n", " \"Default\",\n", " \"Engine_Condition_Model_Building\",\n", " \"Engine_Condition_Feature_Engineering\"\n", "]\n", "\n", "for exp_name in experiments_to_delete:\n", " exp = mlflow.get_experiment_by_name(exp_name)\n", "\n", " if exp:\n", " mlflow.delete_experiment(exp.experiment_id)\n", " print(f\"Deleted: {exp_name}\")\n", " else:\n", " print(f\"{exp_name} not found\")" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "Wbuc4JdzFw8b", "outputId": "1b53b628-034e-44c0-a19f-fd03b5cbe623" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Deleted: Default\n", "Deleted: Engine_Condition_Model_Building\n", "Deleted: Engine_Condition_Feature_Engineering\n" ] } ] }, { "cell_type": "code", "source": [ "import mlflow\n", "import pandas as pd\n", "\n", "# See all experiments\n", "experiments = mlflow.search_experiments()\n", "for exp in experiments:\n", " print(exp.experiment_id, exp.name)\n", "\n", "# Get one experiment's runs\n", "experiment = mlflow.get_experiment_by_name(\"Engine_Condition_Final_Model\")\n", "runs = mlflow.search_runs([experiment.experiment_id])\n", "\n", "display(runs)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 228 }, "id": "Qe4wnUQnHD50", "outputId": "233c7828-6bd3-4763-9cf8-e9768e0bcb6c" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "0 Default\n" ] }, { "output_type": "error", "ename": "AttributeError", "evalue": "'NoneType' object has no attribute 'experiment_id'", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m/tmp/ipykernel_1394/262827386.py\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 9\u001b[0m \u001b[0;31m# Get one experiment's runs\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 10\u001b[0m \u001b[0mexperiment\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmlflow\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_experiment_by_name\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Engine_Condition_Final_Model\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 11\u001b[0;31m \u001b[0mruns\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmlflow\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msearch_runs\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mexperiment\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexperiment_id\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 12\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 13\u001b[0m \u001b[0mdisplay\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mruns\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;31mAttributeError\u001b[0m: 'NoneType' object has no attribute 'experiment_id'" ] } ] }, { "cell_type": "code", "source": [ "all_runs = []\n", "\n", "for exp in mlflow.search_experiments():\n", " exp_runs = mlflow.search_runs([exp.experiment_id], output_format=\"pandas\")\n", " if not exp_runs.empty:\n", " exp_runs[\"Experiment\"] = exp.name\n", " all_runs.append(exp_runs)\n", "\n", "all_results = pd.concat(all_runs, ignore_index=True)\n", "display(all_results)\n", "\n", "all_results.to_csv(\"mlflow_all_results.csv\", index=False)" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 356 }, "id": "vqDLFcXIHIpV", "outputId": "3b801aa6-b520-4500-f58e-b9716ba222e9" }, "execution_count": null, "outputs": [ { "output_type": "error", "ename": "ValueError", "evalue": "No objects to concatenate", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)", "\u001b[0;32m/tmp/ipykernel_1394/120916241.py\u001b[0m in \u001b[0;36m\u001b[0;34m()\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[0mall_runs\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mexp_runs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 8\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 9\u001b[0;31m \u001b[0mall_results\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mconcat\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mall_runs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mignore_index\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 10\u001b[0m \u001b[0mdisplay\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mall_results\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 11\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m/usr/local/lib/python3.12/dist-packages/pandas/core/reshape/concat.py\u001b[0m in \u001b[0;36mconcat\u001b[0;34m(objs, axis, join, ignore_index, keys, levels, names, verify_integrity, sort, copy)\u001b[0m\n\u001b[1;32m 380\u001b[0m \u001b[0mcopy\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 381\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 382\u001b[0;31m op = _Concatenator(\n\u001b[0m\u001b[1;32m 383\u001b[0m \u001b[0mobjs\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 384\u001b[0m \u001b[0maxis\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0maxis\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m/usr/local/lib/python3.12/dist-packages/pandas/core/reshape/concat.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, objs, axis, join, keys, levels, names, ignore_index, verify_integrity, copy, sort)\u001b[0m\n\u001b[1;32m 443\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcopy\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcopy\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 444\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 445\u001b[0;31m \u001b[0mobjs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkeys\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_clean_keys_and_objs\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobjs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkeys\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 446\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 447\u001b[0m \u001b[0;31m# figure out what our result ndim is going to be\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m/usr/local/lib/python3.12/dist-packages/pandas/core/reshape/concat.py\u001b[0m in \u001b[0;36m_clean_keys_and_objs\u001b[0;34m(self, objs, keys)\u001b[0m\n\u001b[1;32m 505\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 506\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mobjs_list\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 507\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"No objects to concatenate\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 508\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 509\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mkeys\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;31mValueError\u001b[0m: No objects to concatenate" ] } ] }, { "cell_type": "code", "source": [ "import mlflow\n", "import pandas as pd\n", "\n", "# Set the tracking URI back to the original database where all experiments are logged\n", "# This is necessary because a previous cell (skE3CCnHHlTL) changed the URI to a new, empty database.\n", "mlflow.set_tracking_uri(\"sqlite:////content/mlflow.db\")\n", "\n", "all_runs = []\n", "\n", "for exp in mlflow.search_experiments():\n", " exp_runs = mlflow.search_runs([exp.experiment_id], output_format=\"pandas\")\n", " if not exp_runs.empty:\n", " exp_runs[\"Experiment\"] = exp.name\n", " all_runs.append(exp_runs)\n", "\n", "# Add a check to prevent ValueError if no runs are found even after correcting the URI\n", "if not all_runs:\n", " print(\"No MLflow runs found in the database. 'all_results' will be an empty DataFrame.\")\n", " all_results = pd.DataFrame()\n", "else:\n", " all_results = pd.concat(all_runs, ignore_index=True)\n", "\n", "display(all_results)\n", "\n", "# Only attempt to save to CSV if there are results to save\n", "if not all_results.empty:\n", " all_results.to_csv(\"mlflow_all_results.csv\", index=False)\n", "else:\n", " print(\"No runs to save to 'mlflow_all_results.csv' as 'all_results' is empty.\")" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 1000 }, "id": "fR0yqtitHPNg", "outputId": "70d2c428-3ca6-4802-fbad-465e95375b89" }, "execution_count": null, "outputs": [ { "output_type": "display_data", "data": { "text/plain": [ " run_id experiment_id status \\\n", "0 fa5ce50f08ce4d9586c27adb304c6402 7 FINISHED \n", "1 578fab3fed7448f18c2b37ec24e11f85 6 FINISHED \n", "2 d8353989b763424991949aa220542b74 6 FINISHED \n", "3 2ac75d79422943889133fcc93d192ae1 5 FINISHED \n", "4 58e201662cba471e8b026d09037884a5 5 FINISHED \n", "5 d3b9953fc3f94bd98320ce506dccd8e6 4 FINISHED \n", "6 db4c5ea31a68450eaa37100030d53eec 4 FINISHED \n", "7 01132f350f024c928bbaa8442adf1cc3 4 FINISHED \n", "8 1e67f4d2f00043449672279b8744c237 4 FINISHED \n", "9 44ccc2db0e4c45a6961f0c66cdd710f0 4 FINISHED \n", "10 e123e07ffbef4ed996b916785d51ffdf 4 FINISHED \n", "11 1a3827c6ad874ccc937ce29a4f4715fa 4 FINISHED \n", "12 2ded9b0554a64b01aa1452e32c71c114 4 FINISHED \n", "13 91b45c8bcbd4454da1e4e413a0d0ae2d 4 FINISHED \n", "14 a9f4a7bc9bc84cefac8e56c945d71faf 4 FINISHED \n", "15 5e9996ff18d741ecb6b53eec724f4d18 4 FINISHED \n", "16 8784c6faffe54d0ca528336061d59ceb 4 FINISHED \n", "17 0eccd4c039ff45918c6ef5780624e191 4 FINISHED \n", "18 facb62b60e874587a6047fac425c778c 4 FINISHED \n", "19 e7a8b90ff4b344ca82f9cbbc3fd4e74a 4 FINISHED \n", "20 1655ce630a4f4ca9b775b4b6086a8241 4 FINISHED \n", "21 5f286558541447faab3dd638ec349381 4 FINISHED \n", "22 096df99b303840f6b4c9d46571cda567 4 FINISHED \n", "23 ce028c182bf34bb8bf65deb61e3c18de 4 FINISHED \n", "24 d9bab0e06df3494d9fded72865ff4429 4 FINISHED \n", "25 b53c6dec56424b4bb611cd937a2297d8 4 FINISHED \n", "26 9a724a796904448d859fa399a32b298a 4 FINISHED \n", "27 267475d82ae3468d83f13cdffff11337 4 FINISHED \n", "28 0f74e2af3ae9477ebbd632fbff5d56a6 4 FINISHED \n", "29 8d3bba699e8a48698339d499c833d888 4 FINISHED \n", "30 1eacc7628f9b401f8b0ce29cbfd4078e 4 FINISHED \n", "31 4329210a7b1547c3a5019d06c830a86b 4 FINISHED \n", "32 188f9c59dbda4ed1ad92a13b47384433 4 FINISHED \n", "33 e7d34106b92a4310b77bec883be61773 4 FINISHED \n", "34 b997d73901a848ef916b4763d6f62bea 4 FINISHED \n", "35 3838c267a4e445b0ade80ad5f08c997b 4 FINISHED \n", "36 fb983959fe99416a8e7466dd197a1390 4 FINISHED \n", "37 37a0449e65d24a2680f43edb38464b59 4 FINISHED \n", "38 51b4b612a1784cee8f8133df2db7902d 1 FINISHED \n", "\n", " artifact_uri \\\n", "0 /content/mlruns/7/fa5ce50f08ce4d9586c27adb304c... \n", "1 /content/mlruns/6/578fab3fed7448f18c2b37ec24e1... \n", "2 /content/mlruns/6/d8353989b763424991949aa22054... \n", "3 /content/mlruns/5/2ac75d79422943889133fcc93d19... \n", "4 /content/mlruns/5/58e201662cba471e8b026d090378... \n", "5 /content/mlruns/4/d3b9953fc3f94bd98320ce506dcc... \n", "6 /content/mlruns/4/db4c5ea31a68450eaa37100030d5... \n", "7 /content/mlruns/4/01132f350f024c928bbaa8442adf... \n", "8 /content/mlruns/4/1e67f4d2f00043449672279b8744... \n", "9 /content/mlruns/4/44ccc2db0e4c45a6961f0c66cdd7... \n", "10 /content/mlruns/4/e123e07ffbef4ed996b916785d51... \n", "11 /content/mlruns/4/1a3827c6ad874ccc937ce29a4f47... \n", "12 /content/mlruns/4/2ded9b0554a64b01aa1452e32c71... \n", "13 /content/mlruns/4/91b45c8bcbd4454da1e4e413a0d0... \n", "14 /content/mlruns/4/a9f4a7bc9bc84cefac8e56c945d7... \n", "15 /content/mlruns/4/5e9996ff18d741ecb6b53eec724f... \n", "16 /content/mlruns/4/8784c6faffe54d0ca528336061d5... \n", "17 /content/mlruns/4/0eccd4c039ff45918c6ef5780624... \n", "18 /content/mlruns/4/facb62b60e874587a6047fac425c... \n", "19 /content/mlruns/4/e7a8b90ff4b344ca82f9cbbc3fd4... \n", "20 /content/mlruns/4/1655ce630a4f4ca9b775b4b6086a... \n", "21 /content/mlruns/4/5f286558541447faab3dd638ec34... \n", "22 /content/mlruns/4/096df99b303840f6b4c9d46571cd... \n", "23 /content/mlruns/4/ce028c182bf34bb8bf65deb61e3c... \n", "24 /content/mlruns/4/d9bab0e06df3494d9fded72865ff... \n", "25 /content/mlruns/4/b53c6dec56424b4bb611cd937a22... \n", "26 /content/mlruns/4/9a724a796904448d859fa399a32b... \n", "27 /content/mlruns/4/267475d82ae3468d83f13cdffff1... \n", "28 /content/mlruns/4/0f74e2af3ae9477ebbd632fbff5d... \n", "29 /content/mlruns/4/8d3bba699e8a48698339d499c833... \n", "30 /content/mlruns/4/1eacc7628f9b401f8b0ce29cbfd4... \n", "31 /content/mlruns/4/4329210a7b1547c3a5019d06c830... \n", "32 /content/mlruns/4/188f9c59dbda4ed1ad92a13b4738... \n", "33 /content/mlruns/4/e7d34106b92a4310b77bec883be6... \n", "34 /content/mlruns/4/b997d73901a848ef916b4763d6f6... \n", "35 /content/mlruns/4/3838c267a4e445b0ade80ad5f08c... \n", "36 /content/mlruns/4/fb983959fe99416a8e7466dd197a... \n", "37 /content/mlruns/4/37a0449e65d24a2680f43edb3846... \n", "38 /content/mlruns/1/51b4b612a1784cee8f8133df2db7... \n", "\n", " start_time end_time \\\n", "0 2026-07-13 14:57:26.046000+00:00 2026-07-13 14:57:52.047000+00:00 \n", "1 2026-07-13 14:51:14.493000+00:00 2026-07-13 14:51:32.246000+00:00 \n", "2 2026-07-13 14:44:23.684000+00:00 2026-07-13 14:46:00.024000+00:00 \n", "3 2026-07-13 14:17:32.531000+00:00 2026-07-13 14:17:44.030000+00:00 \n", "4 2026-07-13 14:16:33.068000+00:00 2026-07-13 14:17:32.518000+00:00 \n", "5 2026-07-13 13:52:44.902000+00:00 2026-07-13 13:53:36.475000+00:00 \n", "6 2026-07-13 13:52:34.926000+00:00 2026-07-13 13:52:44.890000+00:00 \n", "7 2026-07-13 13:52:25.074000+00:00 2026-07-13 13:52:34.908000+00:00 \n", "8 2026-07-13 13:52:14.324000+00:00 2026-07-13 13:52:25.059000+00:00 \n", "9 2026-07-13 13:51:58.125000+00:00 2026-07-13 13:52:14.310000+00:00 \n", "10 2026-07-13 13:51:41.814000+00:00 2026-07-13 13:51:58.110000+00:00 \n", "11 2026-07-13 13:51:19.638000+00:00 2026-07-13 13:51:41.788000+00:00 \n", "12 2026-07-13 13:50:54.329000+00:00 2026-07-13 13:51:19.621000+00:00 \n", "13 2026-07-13 13:50:30.391000+00:00 2026-07-13 13:50:54.315000+00:00 \n", "14 2026-07-13 13:50:19.766000+00:00 2026-07-13 13:50:30.377000+00:00 \n", "15 2026-07-13 13:50:19.708000+00:00 2026-07-13 13:53:36.499000+00:00 \n", "16 2026-07-13 13:49:19.853000+00:00 2026-07-13 13:50:19.668000+00:00 \n", "17 2026-07-13 13:49:08.408000+00:00 2026-07-13 13:49:19.839000+00:00 \n", "18 2026-07-13 13:48:57.548000+00:00 2026-07-13 13:49:08.394000+00:00 \n", "19 2026-07-13 13:48:46.730000+00:00 2026-07-13 13:48:57.535000+00:00 \n", "20 2026-07-13 13:48:20.898000+00:00 2026-07-13 13:48:46.714000+00:00 \n", "21 2026-07-13 13:48:01.845000+00:00 2026-07-13 13:48:20.884000+00:00 \n", "22 2026-07-13 13:47:32.161000+00:00 2026-07-13 13:48:01.814000+00:00 \n", "23 2026-07-13 13:47:02.004000+00:00 2026-07-13 13:47:32.134000+00:00 \n", "24 2026-07-13 13:46:29.168000+00:00 2026-07-13 13:47:01.989000+00:00 \n", "25 2026-07-13 13:46:17.976000+00:00 2026-07-13 13:46:29.154000+00:00 \n", "26 2026-07-13 13:46:17.910000+00:00 2026-07-13 13:50:19.690000+00:00 \n", "27 2026-07-13 13:45:27.527000+00:00 2026-07-13 13:46:17.869000+00:00 \n", "28 2026-07-13 13:45:16.688000+00:00 2026-07-13 13:45:27.513000+00:00 \n", "29 2026-07-13 13:45:06.979000+00:00 2026-07-13 13:45:16.674000+00:00 \n", "30 2026-07-13 13:44:56.214000+00:00 2026-07-13 13:45:06.961000+00:00 \n", "31 2026-07-13 13:44:40.267000+00:00 2026-07-13 13:44:56.200000+00:00 \n", "32 2026-07-13 13:44:24.608000+00:00 2026-07-13 13:44:40.246000+00:00 \n", "33 2026-07-13 13:43:53.667000+00:00 2026-07-13 13:44:24.581000+00:00 \n", "34 2026-07-13 13:43:28.915000+00:00 2026-07-13 13:43:53.653000+00:00 \n", "35 2026-07-13 13:43:03.573000+00:00 2026-07-13 13:43:28.903000+00:00 \n", "36 2026-07-13 13:42:54.076000+00:00 2026-07-13 13:43:03.552000+00:00 \n", "37 2026-07-13 13:42:54.010000+00:00 2026-07-13 13:46:17.891000+00:00 \n", "38 2026-07-13 13:41:42.986000+00:00 2026-07-13 13:42:01.468000+00:00 \n", "\n", " metrics.test_roc_auc metrics.test_recall metrics.test_f1 \\\n", "0 0.690278 0.880227 0.767298 \n", "1 0.690278 0.880227 0.767298 \n", "2 NaN NaN NaN \n", "3 NaN NaN NaN \n", "4 NaN NaN NaN \n", "5 NaN NaN NaN \n", "6 NaN NaN NaN \n", "7 NaN NaN NaN \n", "8 NaN NaN NaN \n", "9 NaN NaN NaN \n", "10 NaN NaN NaN \n", "11 NaN NaN NaN \n", "12 NaN NaN NaN \n", "13 NaN NaN NaN \n", "14 NaN NaN NaN \n", "15 NaN NaN NaN \n", "16 NaN NaN NaN \n", "17 NaN NaN NaN \n", "18 NaN NaN NaN \n", "19 NaN NaN NaN \n", "20 NaN NaN NaN \n", "21 NaN NaN NaN \n", "22 NaN NaN NaN \n", "23 NaN NaN NaN \n", "24 NaN NaN NaN \n", "25 NaN NaN NaN \n", "26 NaN NaN NaN \n", "27 NaN NaN NaN \n", "28 NaN NaN NaN \n", "29 NaN NaN NaN \n", "30 NaN NaN NaN \n", "31 NaN NaN NaN \n", "32 NaN NaN NaN \n", "33 NaN NaN NaN \n", "34 NaN NaN NaN \n", "35 NaN NaN NaN \n", "36 NaN NaN NaN \n", "37 NaN NaN NaN \n", "38 NaN NaN NaN \n", "\n", " metrics.test_accuracy ... params.class_weight params.kernel \\\n", "0 0.663425 ... NaN NaN \n", "1 0.663425 ... None None \n", "2 NaN ... balanced sigmoid \n", "3 NaN ... None None \n", "4 NaN ... None rbf \n", "5 NaN ... NaN NaN \n", "6 NaN ... NaN NaN \n", "7 NaN ... NaN NaN \n", "8 NaN ... NaN NaN \n", "9 NaN ... NaN NaN \n", "10 NaN ... NaN NaN \n", "11 NaN ... NaN NaN \n", "12 NaN ... NaN NaN \n", "13 NaN ... NaN NaN \n", "14 NaN ... NaN NaN \n", "15 NaN ... NaN NaN \n", "16 NaN ... NaN NaN \n", "17 NaN ... NaN NaN \n", "18 NaN ... NaN NaN \n", "19 NaN ... NaN NaN \n", "20 NaN ... NaN NaN \n", "21 NaN ... NaN NaN \n", "22 NaN ... NaN NaN \n", "23 NaN ... NaN NaN \n", "24 NaN ... NaN NaN \n", "25 NaN ... NaN NaN \n", "26 NaN ... NaN NaN \n", "27 NaN ... NaN NaN \n", "28 NaN ... NaN NaN \n", "29 NaN ... NaN NaN \n", "30 NaN ... NaN NaN \n", "31 NaN ... NaN NaN \n", "32 NaN ... NaN NaN \n", "33 NaN ... NaN NaN \n", "34 NaN ... NaN NaN \n", "35 NaN ... NaN NaN \n", "36 NaN ... NaN NaN \n", "37 NaN ... NaN NaN \n", "38 NaN ... 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\n" ], "application/vnd.google.colaboratory.intrinsic+json": { "type": "dataframe", "variable_name": "all_results" } }, "metadata": {} } ] }, { "cell_type": "code", "source": [ "import mlflow\n", "\n", "failed_runs = [\n", " \"dd1feead7f1f4c9bb4cd8772cab03de9\",\n", " \"a76e4912d9db4f1a98e4bb0aad2e2886\",\n", " \"b19eb9e3ac0a4d749b59840c43dd1536\"\n", "]\n", "\n", "for run_id in failed_runs:\n", " mlflow.delete_run(run_id)\n", " print(f\"Deleted {run_id}\")" ], "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "VWGQp0mWHcX0", "outputId": "df9667fd-89cd-4818-c176-9396f4725113" }, "execution_count": null, "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ "Deleted dd1feead7f1f4c9bb4cd8772cab03de9\n", "Deleted a76e4912d9db4f1a98e4bb0aad2e2886\n", "Deleted b19eb9e3ac0a4d749b59840c43dd1536\n" ] } ] }, { "cell_type": "code", "source": [ "duplicate_runs = [\n", " \"84530185045043248878561cccc48c4a\",\n", " \"0135d48fb478491b89102bff8411a522\",\n", " \"4084da155ba24ec3a0bde08e8f09638a\"\n", "]\n", "\n", "for run_id in duplicate_runs:\n", " mlflow.delete_run(run_id)" ], "metadata": { "id": "AwnYyzfzHeUP" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [ "import mlflow\n", "import pandas as pd\n", "from collections import Counter\n", "\n", "# Point MLflow to your existing DB\n", "mlflow.set_tracking_uri(\"sqlite:////content/mlflow.db\")\n", "\n", "# Create / switch to a dedicated experiment\n", "mlflow.set_experiment(\"Engine_Condition_Feature_Selection\")" ], "metadata": { "id": "MbrJD0iV0ESd" }, "execution_count": null, "outputs": [] }, { "cell_type": "code", "source": [], "metadata": { "id": "cmNI86QT0qo0" }, "execution_count": null, "outputs": [] } ] }